pax_global_header00006660000000000000000000000064151401333320014505gustar00rootroot0000000000000052 comment=f5ec92bd24677905521b689c765e9fa49adbe056 Sigima-1.1.1/000077500000000000000000000000001514013333200127165ustar00rootroot00000000000000Sigima-1.1.1/.coveragerc000066400000000000000000000012321514013333200150350ustar00rootroot00000000000000[run] #--- Ignore this warning because the process isolation feature of DataLab #--- causes coverage to report 0% coverage when no computation is performed #--- in the isolated process during the session. disable_warnings = no-data-collected parallel = True concurrency = multiprocessing,thread omit = */sigima/tests/* */sigima/client/stub.py */guidata/* */plotpy/* */qwt/* #--- Workaround for certain builds of python-opencv package: ./config-3.9.py ./config-3.py ./config.py #--- [report] exclude_also = def __repr__ if __name__ == .__main__.: if TYPE_CHECKING: if DEBUG[\s]*: if self.__debug[\s]*: Sigima-1.1.1/.env.template000066400000000000000000000000141514013333200153140ustar00rootroot00000000000000PYTHONPATH=.Sigima-1.1.1/.github/000077500000000000000000000000001514013333200142565ustar00rootroot00000000000000Sigima-1.1.1/.github/ISSUE_TEMPLATE/000077500000000000000000000000001514013333200164415ustar00rootroot00000000000000Sigima-1.1.1/.github/ISSUE_TEMPLATE/bug_report.md000066400000000000000000000012611514013333200211330ustar00rootroot00000000000000--- name: Bug report about: Create a report to help us improve title: '' labels: bug assignees: '' --- **Describe the bug** A clear and concise description of what the bug is. **To Reproduce** Steps to reproduce the behavior: 1. Go to '...' 2. Click on '....' 3. Scroll down to '....' 4. See error **Expected behavior** A clear and concise description of what you expected to happen. **Screenshots** If applicable, add screenshots to help explain your problem. **Installation information** Describe how you installed Sigima (e.g., via pip, conda, or from source) and provide the version of Sigima you are using. **Additional context** Add any other context about the problem here. Sigima-1.1.1/.github/ISSUE_TEMPLATE/doc_request.md000066400000000000000000000011411514013333200212750ustar00rootroot00000000000000--- name: Documentation request about: Ask for documentation about a specific topic title: '' labels: documentation assignees: '' --- **Is your documentation request related to a problem? Please describe.** A clear and concise description of what the problem is. Ex. I'm always frustrated when [...] **Describe the topic you would like to be covered** A clear and concise description of what you want to be documented. **Describe the nature of the documentation you would like to see** Tutorial, reference, etc. **Additional context** Add any other context or screenshots about the feature request here. Sigima-1.1.1/.github/ISSUE_TEMPLATE/feature_request.md000066400000000000000000000011341514013333200221650ustar00rootroot00000000000000--- name: Feature request about: Suggest an idea for this project title: '' labels: enhancement assignees: '' --- **Is your feature request related to a problem? Please describe.** A clear and concise description of what the problem is. Ex. I'm always frustrated when [...] **Describe the solution you'd like** A clear and concise description of what you want to happen. **Describe alternatives you've considered** A clear and concise description of any alternative solutions or features you've considered. **Additional context** Add any other context or screenshots about the feature request here. Sigima-1.1.1/.github/ISSUE_TEMPLATE/tutorial_request.md000066400000000000000000000014571514013333200224050ustar00rootroot00000000000000--- name: Tutorial request about: Ask for a tutorial on a specific topic title: '' labels: documentation assignees: '' --- **Describe the context and technical field of the tutorial you would like to see** A clear and concise description of your technical field, and of the specific application. **Describe the topic you would like to be covered** A clear and concise description of what you want to be documented. **Describe the features you would like to see in the tutorial** A clear and concise description of the features you would like to see in the tutorial. **Additional context** Add any other context or screenshots about the feature request here. _Please attach an example data set, if possible. And please confirm that you are willing to share this data set under the terms of DataLab's license._ Sigima-1.1.1/.github/copilot-instructions.md000066400000000000000000000422071514013333200210200ustar00rootroot00000000000000# Sigima AI Coding Agent Instructions This document provides essential guidance for AI coding agents working on the Sigima codebase—the computation engine powering DataLab's signal and image processing. ## Project Overview **Sigima** is a **headless Python library** providing scientific computation functions for 1D signals and 2D images. It is **GUI-independent** (no Qt/PlotPyStack) and designed for testability, modularity, and remote execution. ### Core Architecture: Three-Layer Model Sigima separates concerns into three distinct layers: 1. **`sigima.objects`**: Data model (`SignalObj`, `ImageObj` wrapping NumPy arrays) 2. **`sigima.proc`**: High-level computation functions operating on objects 3. **`sigima.tools`**: Low-level NumPy algorithms (used by `proc` and external projects) ```python # Example: Processing a signal object (high-level) from sigima import SignalObj import sigima.proc.signal as sips obj = SignalObj.create(x, y) result = sips.normalize(obj, sigima.params.NormalizeParam.create(method="minmax")) # Example: Using low-level tools directly (NumPy arrays) from sigima.tools.signal import filtering filtered_y = filtering.apply_moving_average(y, n=5) ``` **Key Design Principle**: `sigima.tools` fills gaps in NumPy/SciPy/scikit-image, not a general-purpose replacement. DataLab uses many `tools` functions independently of the object model. ### Technology Stack - **Python**: 3.9+ (`from __future__ import annotations`) - **Core**: NumPy (≥1.22), SciPy (≥1.10.1), scikit-image (≥0.19.2), pandas (≥1.4) - **GUI Parameters**: guidata (≥3.13) for `DataSet` parameter classes - **Optional**: opencv-python-headless (≥4.8.1.78) - **Testing**: pytest with `--gui` flag for visual validation - **Linting**: Ruff (preferred), Pylint - **Docs**: Sphinx with French translations (sphinx-intl) ### Workspace Structure ``` Sigima/ ├── sigima/ │ ├── objects/ # Data model (SignalObj, ImageObj, ROI) │ │ ├── signal/ # SignalObj implementation │ │ ├── image/ # ImageObj implementation │ │ └── scalar/ # GeometryResult, TableResult │ ├── proc/ # High-level computation functions │ │ ├── base.py # Common processing (ROI, arithmetic) │ │ ├── signal/ # Signal processing (filtering, FFT, fitting, etc.) │ │ ├── image/ # Image processing (edges, morphology, detection) │ │ └── decorator.py # @computation_function decorator │ ├── tools/ # Low-level NumPy algorithms │ │ ├── signal/ # Signal algorithms (peak detection, stability, etc.) │ │ └── image/ # Image algorithms (detection, geometry, etc.) │ ├── io/ # I/O for signals/images (CSV, formats) │ ├── params.py # Centralized parameter import (re-exports from proc/) │ ├── client/ # SimpleRemoteProxy for DataLab control │ └── tests/ # pytest test suite ├── scripts/ │ └── run_with_env.py # Environment loader (.env support) ├── .env # PYTHONPATH=.;../guidata;../plotpy └── pyproject.toml ``` **Related Projects** (sibling directories): - `../DataLab/` - GUI application using Sigima - `../PlotPy/` - Plotting library (used in tests with `--gui`) - `../guidata/` - Parameter/configuration framework ## Development Workflows ### Running Commands **ALWAYS use `scripts/run_with_env.py`** to load `.env` before running Python commands: ```powershell # ✅ CORRECT python scripts/run_with_env.py python -m pytest # ❌ WRONG - Misses local guidata/plotpy python -m pytest ``` ### Testing ```powershell # Run all tests (fast, no GUI) python scripts/run_with_env.py python -m pytest --ff # Run GUI-assisted validation tests (visual checks) python scripts/run_with_env.py python -m pytest --gui # Run specific test module python scripts/run_with_env.py python -m pytest sigima/tests/signal/processing_unit_test.py # Coverage python scripts/run_with_env.py python -m coverage run -m pytest sigima python -m coverage html ``` **Test Organization**: - `tests/common/`: ROI, validation, worker, title formatting - `tests/signal/`: Signal processing tests - `tests/image/`: Image processing tests - `tests/io/`: I/O format tests **Pytest Configuration** (`conftest.py`): - `env.execenv.unattended = True` (no GUI by default) - `set_validation_mode(ValidationMode.STRICT)` for tests - Custom flag: `--gui` enables visual validation ### Linting and Formatting ```powershell # Ruff (preferred) python scripts/run_with_env.py python -m ruff format python scripts/run_with_env.py python -m ruff check --fix # Pylint python scripts/run_with_env.py python -m pylint sigima \ --disable=duplicate-code,fixme,too-many-arguments, \ too-many-branches,too-many-instance-attributes ``` ### Translations ```powershell # Scan and update .po files python scripts/run_with_env.py python -m guidata.utils.translations scan \ --name sigima --directory . --copyright-holder "DataLab Platform Developers" \ --languages fr # Compile .mo files python scripts/run_with_env.py python -m guidata.utils.translations compile \ --name sigima --directory . ``` ## Core Patterns ### 1. Computation Functions with `@computation_function` Decorator **All `sigima.proc` functions** use this decorator to enable dual calling conventions: ```python from sigima.proc.decorator import computation_function import sigima.params @computation_function() def my_processing(src: SignalObj, p: MyParam) -> SignalObj: """Process signal with my algorithm. Args: src: Input signal p: Processing parameters Returns: Processed signal """ dst = src.copy() # ... processing logic using p.param1, p.param2 ... return dst ``` **Dual calling style enabled by decorator**: ```python # Style 1: DataSet parameter object (DataLab GUI style) param = sigima.params.MyParam.create(param1=10, param2="value") result = my_processing(src, param) # Style 2: Expanded keyword arguments (script-friendly) result = my_processing(src, param1=10, param2="value") ``` **Key Rules**: - Parameter class MUST be a `guidata.dataset.DataSet` subclass - Always re-export parameter classes in `sigima.params` module - Export computation functions in `__all__` of their module AND in `sigima/proc/{signal|image}/__init__.py` ### 2. Object Model: `SignalObj` and `ImageObj` **Core attributes**: ```python # SignalObj signal.x # X coordinates (1D NumPy array, float64) signal.y # Y data (1D NumPy array, float64) signal.dx, signal.dy # Optional uncertainties signal.xydata # Property returning (x, y) tuple signal.set_xydata(x, y, dx=None, dy=None) # ImageObj image.data # 2D NumPy array (various dtypes) image.x0, image.y0, image.dx, image.dy # Pixel coordinates image.metadata # Dict for labels, units, etc. # Common to both obj.roi # List of ROI objects (SegmentROI, RectangularROI, etc.) obj.get_data(roi_index=None) # Extract data with optional ROI mask obj.copy() # Deep copy with metadata ``` **Data type enforcement**: - `SignalObj`: Automatically converts integer X/Y arrays to `float64` for computational precision - `ImageObj`: Preserves original dtype (uint8, uint16, float32, etc.) for image operations ### 3. Parameter Classes: `guidata.dataset.DataSet` **All computation parameters** inherit from `guidata.dataset.DataSet`: ```python import guidata.dataset as gds class MyParam(gds.DataSet): """My processing parameters.""" param1 = gds.IntItem("Parameter 1", default=10, min=1, max=100) param2 = gds.ChoiceItem("Method", ["method1", "method2"], default="method1") @staticmethod def create(param1: int = 10, param2: str = "method1") -> MyParam: """Factory method for easy instantiation.""" return MyParam(param1=param1, param2=param2) ``` **Conventions**: - Always provide `create()` static method for script-friendly instantiation - Export in `sigima.params` for centralized import - Use descriptive docstrings (shown in DataLab GUI) ### 4. Title Formatting System **Computation results need titles**. Sigima provides a configurable system: ```python from sigima.proc.title_formatting import TitleFormatter, FormatResultTitle class MyParam(gds.DataSet): # ... parameter definitions ... def generate_title(self) -> str: """Generate human-readable title for this computation.""" return f"my_processing(p1={self.param1}, p2={self.param2})" # In computation function @computation_function() def my_processing(src: SignalObj, p: MyParam) -> SignalObj: dst = src.copy() # ... processing ... FormatResultTitle.apply(dst, src, p) # Automatically formats title return dst ``` **Title formatting modes**: - **Parameter mode**: Default, uses `param.generate_title()` → `"normalize[minmax]"` - **Function mode**: Used by DataLab, shows function name → `"Normalize"` ### 5. ROI (Region of Interest) System **Types of ROI**: - **Signal**: `SegmentROI` (X interval) - **Image**: `RectangularROI`, `CircularROI`, `PolygonalROI` **Using ROIs in processing**: ```python # Get data masked by ROI data = obj.get_data(roi_index=0) # First ROI data = obj.get_data() # All data (no ROI) # ROI iteration for roi_index, roi in enumerate(obj.roi): masked_data = obj.get_data(roi_index) # ... process masked_data ... ``` **ROI creation in detection functions**: ```python from sigima.objects import create_image_roi_around_points # Automatically create ROIs around detected features coords = detect_peaks(image.data) # Returns N×2 array rois = create_image_roi_around_points(coords, image, relative_size=1.5) result.roi = rois # Attach to result ``` ## Common Tasks ### Adding a New Signal Processing Function **Complete workflow**: 1. **Implement in `sigima/proc/signal/processing.py` (or appropriate module)**: ```python from sigima.proc.decorator import computation_function import sigima.params @computation_function() def my_feature(src: SignalObj, p: MyFeatureParam) -> SignalObj: """Apply my feature to signal. Args: src: Input signal p: Feature parameters Returns: Processed signal """ dst = src.copy() # Processing logic using src.x, src.y dst.y = apply_my_algorithm(src.y, p.threshold) FormatResultTitle.apply(dst, src, p) return dst ``` 2. **Define parameter class in same file**: ```python class MyFeatureParam(gds.DataSet): """Parameters for my feature.""" threshold = gds.FloatItem("Threshold", default=0.5, min=0, max=1) @staticmethod def create(threshold: float = 0.5) -> MyFeatureParam: return MyFeatureParam(threshold=threshold) def generate_title(self) -> str: return f"my_feature(thresh={self.threshold})" ``` 3. **Export in `sigima/proc/signal/__init__.py`**: ```python from sigima.proc.signal.processing import my_feature, MyFeatureParam __all__ = [ # ... existing exports ... "my_feature", "MyFeatureParam", ] ``` 4. **Re-export parameter in `sigima/params.py`**: ```python from sigima.proc.signal import MyFeatureParam __all__ = [ # ... existing params ... "MyFeatureParam", ] ``` 5. **Add tests in `sigima/tests/signal/`**: ```python import sigima.proc.signal as sips import sigima.params from sigima.tests.data import get_test_signal @pytest.mark.validation def test_my_feature(): """Test my_feature processing.""" src = get_test_signal("paracetamol.txt") p = sigima.params.MyFeatureParam.create(threshold=0.5) result = sips.my_feature(src, p) assert result is not None assert len(result.y) == len(src.y) # Add assertions checking result correctness ``` 6. **Document in Sphinx** (if public API): ```python # Docstring already makes it appear in API docs # Add usage example in doc/examples/ if complex ``` ### Adding Low-Level NumPy Functions to `tools` **When to use `tools` vs `proc`**: - Use `tools` for **pure NumPy/SciPy algorithms** that don't need object context - Use `proc` for functions that need **metadata, ROI, or object operations** **Example**: ```python # sigima/tools/signal/myalgorithm.py import numpy as np from sigima.tools.checks import check_1d_array def my_numpy_function(y: np.ndarray, threshold: float) -> np.ndarray: """Low-level algorithm operating on NumPy arrays. Args: y: 1D NumPy array threshold: Processing threshold Returns: Processed array """ check_1d_array(y) # Input validation # ... pure NumPy processing ... return result ``` **Export in `sigima/tools/signal/__init__.py`** and document intended usage. ### Handling Integer Signal Data **Issue**: Integer arrays cause precision loss in computations. **Solution**: Sigima automatically converts to `float64`: ```python # This is handled automatically now signal = SignalObj.create(x=np.array([1, 2, 3]), y=np.array([10, 20, 30])) # int arrays # Internally converted to float64 # Validation: If you need strict float checks from sigima.tools.checks import check_1d_array check_1d_array(y) # Allows float dtypes, raises for invalid types ``` ### Working with ROI Boundaries **Issue**: ROI extending beyond image causes `ValueError`. **Solution**: Use `get_data()` which automatically clips: ```python # Safe: Handles ROI clipping automatically data = image.get_data(roi_index=0) # Manual clipping (if needed in tools) y0 = max(0, roi.y0) y1 = min(image.data.shape[0], roi.y1) x0 = max(0, roi.x0) x1 = min(image.data.shape[1], roi.x1) ``` ## Coding Conventions ### Type Annotations ```python from __future__ import annotations import numpy as np from sigima.objects import SignalObj def process(src: SignalObj, threshold: float) -> SignalObj: """Use forward references via __future__ import.""" pass ``` ### Docstrings **Google-style** with Args/Returns: ```python def my_function(x: np.ndarray, param: int) -> np.ndarray: """One-line summary. Longer description if needed. Args: x: Input array description param: Parameter description Returns: Output array description Raises: ValueError: When input is invalid """ ``` For continued lines in enumerations (args, returns), indent subsequent lines by 1 space: ```python def compute_feature(obj: SignalObj, param: MyParam) -> SignalObj: """Compute feature on signal. Args: obj: Input signal object param: Processing parameters, with a very long description that continues on the next line. Returns: Processed signal object """ ``` ### Imports **Order**: Standard → Third-party → Sigima ```python from __future__ import annotations import numpy as np import scipy.signal as sps from guidata.dataset import DataSet from sigima.objects import SignalObj from sigima.proc.decorator import computation_function from sigima.tools.checks import check_1d_array ``` ### Module Exports **Always define `__all__`**: ```python __all__ = [ "my_function", "MyParam", "AnotherFunction", ] ``` ## Integration with DataLab Sigima functions are **consumed by DataLab processors**: 1. **Sigima** implements computation: `sigima.proc.signal.my_feature()` 2. **DataLab** registers in processor: `self.register_1_to_1(sips.my_feature, ...)` 3. **DataLab** adds to menu: `self.processing_menu.addAction(act)` **Testing flow**: 1. Test in **Sigima unit tests** (headless, fast) 2. Test in **DataLab integration tests** (GUI, full workflow) ## Key Files Reference | File | Purpose | |------|---------| | `sigima/__init__.py` | Top-level exports (`SignalObj`, `ImageObj`, convenience functions) | | `sigima/params.py` | Centralized parameter class exports (re-exports from `proc`) | | `sigima/objects/signal/object.py` | `SignalObj` implementation | | `sigima/objects/image/object.py` | `ImageObj` implementation | | `sigima/proc/decorator.py` | `@computation_function` decorator system | | `sigima/proc/signal/processing.py` | Signal processing functions (normalize, calibrate, etc.) | | `sigima/proc/image/detection.py` | Image detection (blobs, peaks, contours) | | `sigima/tools/checks.py` | Input validation (`check_1d_array`, `check_2d_array`) | | `scripts/run_with_env.py` | Environment loader (always use for commands) | | `.env` | Local PYTHONPATH for development | ## VS Code Tasks `.vscode/tasks.json` provides shortcuts: - **🧽🔦 Ruff**: Format + lint - **🚀 Pytest**: Run tests (`--ff` flag) - **📚 Compile translations**: Build .mo files - **🔎 Scan translations**: Update .po files ## Release Classification **Bug Fix** (1.0.x): - Fixes incorrect behavior (e.g., ROI boundary clipping) - Restores expected functionality (e.g., integer array conversion) - Adds missing capability that should have existed (e.g., `replace_x_by_other_y`) **Feature** (1.x.0): - Entirely new computation type (e.g., new parametric images) - New analysis methods ## Getting Help - **Documentation**: https://sigima.readthedocs.io/ - **Issues**: https://github.com/DataLab-Platform/Sigima/issues - **DataLab Integration**: https://datalab-platform.com/ --- **Remember**: Always use `scripts/run_with_env.py`, test headlessly with pytest, and export all parameters through `sigima.params`. Sigima-1.1.1/.github/workflows/000077500000000000000000000000001514013333200163135ustar00rootroot00000000000000Sigima-1.1.1/.github/workflows/build_deploy.yml000066400000000000000000000014351514013333200215140ustar00rootroot00000000000000name: Build and upload to PyPI on: release: types: [published] permissions: contents: read jobs: deploy: runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - name: Set up Python uses: actions/setup-python@v5 with: python-version: '3.x' - name: Install dependencies run: | python -m pip install --upgrade pip pip install build guidata babel - name: Compile translations run: | python -m guidata.utils.translations compile --name sigima --directory . - name: Build package run: python -m build - name: Publish package uses: pypa/gh-action-pypi-publish@27b31702a0e7fc50959f5ad993c78deac1bdfc29 with: user: __token__ password: ${{ secrets.PYPI_API_TOKEN }} Sigima-1.1.1/.github/workflows/test.yml000066400000000000000000000126371514013333200200260ustar00rootroot00000000000000# This workflow will install Python dependencies, run tests and lint with a variety of Python versions # For more information see: https://docs.github.com/en/actions/automating-builds-and-tests/building-and-testing-python # Inspired from https://pytest-qt.readthedocs.io/en/latest/troubleshooting.html#github-actions name: Install and Test on Ubuntu (latest) on: push: branches: [ "main", "develop", "release" ] pull_request: branches: [ "main", "develop", "release" ] workflow_dispatch: inputs: job_to_run: description: 'Which job to run' required: true type: choice options: - 'all' - 'build' - 'build_latest' default: 'all' schedule: # Only the "build_latest" job runs on schedule (see execution conditions below) - cron: "0 5 * * 1" jobs: build: if: ${{ (github.event_name == 'push' || github.event_name == 'pull_request') || (github.event_name == 'workflow_dispatch' && (github.event.inputs.job_to_run == 'all' || github.event.inputs.job_to_run == 'build')) }} env: DISPLAY: ':99.0' runs-on: ubuntu-latest strategy: fail-fast: false matrix: python-version: ["3.9", "3.13"] steps: - uses: actions/checkout@v4 - name: Set up Python ${{ matrix.python-version }} uses: actions/setup-python@v5 with: python-version: ${{ matrix.python-version }} - name: Install dependencies run: | sudo apt install libxkbcommon-x11-0 libxcb-icccm4 libxcb-image0 libxcb-keysyms1 libxcb-randr0 libxcb-render-util0 libxcb-xinerama0 libxcb-xfixes0 x11-utils /sbin/start-stop-daemon --start --quiet --pidfile /tmp/custom_xvfb_99.pid --make-pidfile --background --exec /usr/bin/Xvfb -- :99 -screen 0 1920x1200x24 -ac +extension GLX python -m pip install --upgrade pip python -m pip install ruff pytest if [ "${{ github.ref_name }}" = "develop" ]; then pip uninstall -y guidata cd .. git clone --depth 1 --branch develop https://github.com/PlotPyStack/guidata.git cd Sigima pip install -e ../guidata # Install tomli for TOML parsing (safe if already present) pip install tomli # Extract dependencies and save to file, then install python -c "import tomli; f=open('pyproject.toml','rb'); data=tomli.load(f); deps=[d for d in data['project']['dependencies'] if not any(p in d for p in ['guidata'])]; open('deps.txt','w').write('\n'.join(deps))" pip install -r deps.txt # Install Sigima without dependencies pip install --no-deps . elif [ "${{ github.ref_name }}" = "release" ]; then pip uninstall -y guidata cd .. # Try cloning guidata from release, fallback to main or master git clone --depth 1 --branch release https://github.com/PlotPyStack/guidata.git || git clone --depth 1 https://github.com/PlotPyStack/guidata.git || git clone --depth 1 --branch master https://github.com/PlotPyStack/guidata.git cd Sigima pip install -e ../guidata # Install tomli for TOML parsing (safe if already present) pip install tomli # Extract dependencies and save to file, then install python -c "import tomli; f=open('pyproject.toml','rb'); data=tomli.load(f); deps=[d for d in data['project']['dependencies'] if not any(p in d for p in ['guidata'])]; open('deps.txt','w').write('\n'.join(deps))" pip install -r deps.txt # Install Sigima without dependencies pip install --no-deps . else # Install from PyPI normally for main branch pip install . fi - name: Lint with Ruff run: ruff check --output-format=github sigima - name: Test with pytest run: pytest -v --tb=long build_latest: if: ${{ github.event_name == 'schedule' || (github.event_name == 'workflow_dispatch' && (github.event.inputs.job_to_run == 'all' || github.event.inputs.job_to_run == 'build_latest')) }} env: DISPLAY: ':99.0' runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - name: Set up Python 3.13 uses: actions/setup-python@v5 with: python-version: "3.13" - name: Install dependencies (latest) run: | set -euxo pipefail sudo apt-get update sudo apt-get install -y \ libxkbcommon-x11-0 libxcb-icccm4 libxcb-image0 libxcb-keysyms1 \ libxcb-randr0 libxcb-render-util0 libxcb-xinerama0 libxcb-xfixes0 x11-utils /sbin/start-stop-daemon --start --quiet \ --pidfile /tmp/custom_xvfb_99.pid --make-pidfile --background \ --exec /usr/bin/Xvfb -- :99 -screen 0 1920x1200x24 -ac +extension GLX python -m pip install --upgrade pip python -m pip install ruff pytest # Install Sigima itself, but do NOT install its pinned deps python -m pip install -e . --no-deps # Extract dependency names from pyproject.toml and install latest versions python -m pip install -U --upgrade-strategy eager $(python -c "import tomllib, re; print(' '.join(re.sub(r'[\[\]<>=!~,.\s].*$', '', d).strip() for d in tomllib.loads(open('pyproject.toml', 'rb').read().decode())['project']['dependencies']))") - name: Lint with Ruff (latest) run: ruff check --output-format=github sigima - name: Test with pytest (latest) run: pytest -v --tb=long Sigima-1.1.1/.gitignore000066400000000000000000000123771514013333200147200ustar00rootroot00000000000000# ---------------------------- Specific to this project -------------------------------- # Project specific resources/*.png doc.zip releases/ /tutorialnotes*.md doc/changelog.md scenario_*.h5 # Windows specific Thumbs.db # Microsoft Visual Studio *.pyproj *.sln # Sphinx documentation doctmp/ .doctrees/ doc/install_requires.txt doc/extras_require-dev.txt doc/extras_require-doc.txt doc/locale/pot/_sphinx_design_static/ # Backup files (e.g. created during merge conflicts) *.bak # ------------------ Template `Python.gitignore` from gitignore.io --------------------- # Created by https://www.gitignore.io/api/python ### Python ### # Byte-compiled / optimized / DLL files __pycache__/ *.py[codz] *$py.class # C extensions *.so # Distribution / packaging .Python build/ develop-eggs/ dist/ downloads/ eggs/ .eggs/ lib/ lib64/ parts/ sdist/ var/ wheels/ share/python-wheels/ *.egg-info/ .installed.cfg *.egg MANIFEST # PyInstaller # Usually these files are written by a python script from a template # before PyInstaller builds the exe, so as to inject date/other infos into it. *.manifest # *.spec # Installer logs pip-log.txt pip-delete-this-directory.txt # Unit test / coverage reports htmlcov/ .tox/ .nox/ .coverage .coverage.* .cache nosetests.xml coverage.xml *.cover *.py.cover .hypothesis/ .pytest_cache/ cover/ # Translations *.mo *.pot # Django stuff: *.log local_settings.py db.sqlite3 db.sqlite3-journal # Flask stuff: instance/ .webassets-cache # Scrapy stuff: .scrapy # Sphinx documentation docs/_build/ doc/auto_examples/ doc/sg_execution_times.rst # PyBuilder .pybuilder/ target/ # Jupyter Notebook .ipynb_checkpoints # IPython profile_default/ ipython_config.py # pyenv # For a library or package, you might want to ignore these files since the code is # intended to run in multiple environments; otherwise, check them in: # .python-version # pipenv # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. # However, in case of collaboration, if having platform-specific dependencies or dependencies # having no cross-platform support, pipenv may install dependencies that don't work, or not # install all needed dependencies. #Pipfile.lock # UV # Similar to Pipfile.lock, it is generally recommended to include uv.lock in version control. # This is especially recommended for binary packages to ensure reproducibility, and is more # commonly ignored for libraries. #uv.lock # poetry # Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. # This is especially recommended for binary packages to ensure reproducibility, and is more # commonly ignored for libraries. # https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control #poetry.lock #poetry.toml # pdm # Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. # pdm recommends including project-wide configuration in pdm.toml, but excluding .pdm-python. # https://pdm-project.org/en/latest/usage/project/#working-with-version-control #pdm.lock #pdm.toml .pdm-python .pdm-build/ # pixi # Similar to Pipfile.lock, it is generally recommended to include pixi.lock in version control. #pixi.lock # Pixi creates a virtual environment in the .pixi directory, just like venv module creates one # in the .venv directory. It is recommended not to include this directory in version control. .pixi # PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm __pypackages__/ # Celery stuff celerybeat-schedule celerybeat.pid # SageMath parsed files *.sage.py # Environments .env .envrc .venv env/ venv/ ENV/ env.bak/ venv.bak/ # Spyder project settings .spyderproject .spyproject # Rope project settings .ropeproject # mkdocs documentation /site # mypy .mypy_cache/ .dmypy.json dmypy.json # Pyre type checker .pyre/ # pytype static type analyzer .pytype/ # Cython debug symbols cython_debug/ # PyCharm # JetBrains specific template is maintained in a separate JetBrains.gitignore that can # be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore # and can be added to the global gitignore or merged into this file. For a more nuclear # option (not recommended) you can uncomment the following to ignore the entire idea folder. #.idea/ # Abstra # Abstra is an AI-powered process automation framework. # Ignore directories containing user credentials, local state, and settings. # Learn more at https://abstra.io/docs .abstra/ # Visual Studio Code # Visual Studio Code specific template is maintained in a separate VisualStudioCode.gitignore # that can be found at https://github.com/github/gitignore/blob/main/Global/VisualStudioCode.gitignore # and can be added to the global gitignore or merged into this file. However, if you prefer, # you could uncomment the following to ignore the entire vscode folder # .vscode/ # Ruff stuff: .ruff_cache/ # PyPI configuration file .pypirc # Cursor # Cursor is an AI-powered code editor. `.cursorignore` specifies files/directories to # exclude from AI features like autocomplete and code analysis. Recommended for sensitive data # refer to https://docs.cursor.com/context/ignore-files .cursorignore .cursorindexingignore # Marimo marimo/_static/ marimo/_lsp/ __marimo__/ Sigima-1.1.1/.nblink/000077500000000000000000000000001514013333200142515ustar00rootroot00000000000000Sigima-1.1.1/.nblink/environment.yml000066400000000000000000000001611514013333200173360ustar00rootroot00000000000000name: sigima-environment channels: - emscripten-forge - conda-forge dependencies: - xeus-python - sigima Sigima-1.1.1/.nblink/nblink-lock.json000066400000000000000000000743631514013333200173640ustar00rootroot00000000000000{ "id": "5334523766877598", "specs": [ "xeus-python", "sigima" ], "channels": [ "emscripten-forge", "conda-forge" ], "packages": { "idna-3.11-pyhd8ed1ab_0.conda": { "hash": { "md5": "53abe63df7e10a6ba605dc5f9f961d36", "sha256": "ae89d0299ada2a3162c2614a9d26557a92aa6a77120ce142f8e0109bbf0342b0" }, "name": "idna", "size": 50721, "build": "pyhd8ed1ab_0", "subdir": "noarch", "channel": "conda-forge", "version": "3.11" }, "qtpy-2.4.3-pyhd8ed1ab_1.conda": { "hash": { "md5": "b49c000df5aca26d36b3f078ba85e03a", "sha256": "b17dd9d2ee7a4f60fb13712883cd2664aa1339df4b29eb7ae0f4423b31778b00" }, "name": "qtpy", "size": 63041, "build": "pyhd8ed1ab_1", "subdir": "noarch", "channel": "conda-forge", "version": "2.4.3" }, "six-1.17.0-pyhe01879c_1.conda": { "hash": { "md5": "3339e3b65d58accf4ca4fb8748ab16b3", "sha256": "458227f759d5e3fcec5d9b7acce54e10c9e1f4f4b7ec978f3bfd54ce4ee9853d" }, "name": "six", "size": 18455, "build": "pyhe01879c_1", "subdir": "noarch", "channel": "conda-forge", "version": "1.17.0" }, "xeus-5.2.6-h2072262_0.tar.bz2": { "hash": { "sha256": "92b87c1993283014d660b67020e70b1d8fcaa5e80aa079df1e9999633eca6cf9" }, "name": "xeus", "size": 379059, "build": "h2072262_0", "subdir": "emscripten-wasm32", "channel": "emscripten-forge", "version": "5.2.6" }, "zlib-1.3.1-h4e94343_2.tar.bz2": { "hash": { "sha256": "e1cdb929e27c77e8795b469d81b83076c0bcb6d79b7feaf5e9d92c41c045b626" }, "name": "zlib", "size": 98537, "build": "h4e94343_2", "subdir": "emscripten-wasm32", "channel": "emscripten-forge", "version": "1.3.1" }, "hdf5-1.12.3-h1d76a40_3.tar.bz2": { "hash": { "sha256": "cf395da7d88149df5d3b9ade4f68ace31224050cfbf046ab696489ff2336ec64" }, "name": "hdf5", "size": 1030473, "build": "h1d76a40_3", "subdir": "emscripten-wasm32", "channel": "emscripten-forge", "version": "1.12.3" }, "pooch-1.9.0-pyhd8ed1ab_0.conda": { "hash": { "md5": "dd4b6337bf8886855db6905b336db3c8", "sha256": "081e52c4612830bf1fd4a9c78eebaf335d1385d74ddfd328b1b2f26b983848eb" }, "name": "pooch", "size": 56833, "build": "pyhd8ed1ab_0", "subdir": "noarch", "channel": "conda-forge", "version": "1.9.0" }, "pytz-2025.2-pyhd8ed1ab_0.conda": { "hash": { "md5": "bc8e3267d44011051f2eb14d22fb0960", "sha256": "8d2a8bf110cc1fc3df6904091dead158ba3e614d8402a83e51ed3a8aa93cdeb0" }, "name": "pytz", "size": 189015, "build": "pyhd8ed1ab_0", "subdir": "noarch", "channel": "conda-forge", "version": "2025.2" }, "tomli-2.4.0-pyhcf101f3_0.conda": { "hash": { "md5": "72e780e9aa2d0a3295f59b1874e3768b", "sha256": "62940c563de45790ba0f076b9f2085a842a65662268b02dd136a8e9b1eaf47a8" }, "name": "tomli", "size": 21453, "build": "pyhcf101f3_0", "subdir": "noarch", "channel": "conda-forge", "version": "2.4.0" }, "zipp-3.23.0-pyhcf101f3_1.conda": { "hash": { "md5": "30cd29cb87d819caead4d55184c1d115", "sha256": "b4533f7d9efc976511a73ef7d4a2473406d7f4c750884be8e8620b0ce70f4dae" }, "name": "zipp", "size": 24194, "build": "pyhcf101f3_1", "subdir": "noarch", "channel": "conda-forge", "version": "3.23.0" }, "qhull-2020.2-h7223423_0.tar.bz2": { "hash": { "sha256": "bad02d09d53eb322e762af992c3a89883c325faa7b703660bc7a0b71700f16bc" }, "name": "qhull", "size": 3713606, "build": "h7223423_0", "subdir": "emscripten-wasm32", "channel": "emscripten-forge", "version": "2020.2" }, "sigima-1.1.0-pyhd8ed1ab_0.conda": { "hash": { "md5": "1c995b01544f58d2759d9bd674eb94f8", "sha256": "308f0e087e36aa6b8008dacdf9e7df7c15d8989cdd0ec6164b883718c5ddd466" }, "name": "sigima", "size": 8818603, "build": "pyhd8ed1ab_0", "subdir": "noarch", "channel": "conda-forge", "version": "1.1.0" }, "cycler-0.12.1-pyhcf101f3_2.conda": { "hash": { "md5": "4c2a8fef270f6c69591889b93f9f55c1", "sha256": "bb47aec5338695ff8efbddbc669064a3b10fe34ad881fb8ad5d64fbfa6910ed1" }, "name": "cycler", "size": 14778, "build": "pyhcf101f3_2", "subdir": "noarch", "channel": "conda-forge", "version": "0.12.1" }, "pexpect-4.9.0-pyhd8ed1ab_1.conda": { "hash": { "md5": "d0d408b1f18883a944376da5cf8101ea", "sha256": "202af1de83b585d36445dc1fda94266697341994d1a3328fabde4989e1b3d07a" }, "name": "pexpect", "size": 53561, "build": "pyhd8ed1ab_1", "subdir": "noarch", "channel": "conda-forge", "version": "4.9.0" }, "urllib3-2.2.2-pyhd8ed1ab_0.conda": { "hash": { "md5": "92cdb6fe54b78739ad70637e4f0deb07", "sha256": "8cd972048f297b8e0601158ce352f5ca9510dda9f2706a46560220aa58b9f038" }, "name": "urllib3", "size": 95016, "build": "pyhd8ed1ab_0", "subdir": "noarch", "channel": "conda-forge", "version": "2.2.2" }, "wcwidth-0.5.3-pyhd8ed1ab_0.conda": { "hash": { "md5": "36432484e9ce3b073a51bf138767a593", "sha256": "2395599ec9e37e6f21838bb26e7f2336fa03a4b1460ba10897ec856b21ac7d59" }, "name": "wcwidth", "size": 70539, "build": "pyhd8ed1ab_0", "subdir": "noarch", "channel": "conda-forge", "version": "0.5.3" }, "guidata-3.13.4-pyhcf101f3_1.conda": { "hash": { "md5": "e78ae326ad18163b3f3c2ccc5c079a32", "sha256": "b89d6840df9480a9a799aacf783e3b3124837fcac61134db2bc437a52c739d1c" }, "name": "guidata", "size": 310403, "build": "pyhcf101f3_1", "subdir": "noarch", "channel": "conda-forge", "version": "3.13.4" }, "imageio-2.37.0-pyhfb79c49_0.conda": { "hash": { "md5": "b5577bc2212219566578fd5af9993af6", "sha256": "8ef69fa00c68fad34a3b7b260ea774fda9bd9274fd706d3baffb9519fd0063fe" }, "name": "imageio", "size": 293226, "build": "pyhfb79c49_0", "subdir": "noarch", "channel": "conda-forge", "version": "2.37.0" }, "makefun-1.16.0-pyhd8ed1ab_0.conda": { "hash": { "md5": "220b98de4da252648b825e21ba351d5d", "sha256": "0e03e67393eb596430f27bccaf75f5c317cfd0d245e2740a29c61978a82dc9b1" }, "name": "makefun", "size": 26779, "build": "pyhd8ed1ab_0", "subdir": "noarch", "channel": "conda-forge", "version": "1.16.0" }, "networkx-3.6.1-pyhcf101f3_0.conda": { "hash": { "md5": "a2c1eeadae7a309daed9d62c96012a2b", "sha256": "f6a82172afc50e54741f6f84527ef10424326611503c64e359e25a19a8e4c1c6" }, "name": "networkx", "size": 1587439, "build": "pyhcf101f3_0", "subdir": "noarch", "channel": "conda-forge", "version": "3.6.1" }, "packaging-26.0-pyhcf101f3_0.conda": { "hash": { "md5": "b76541e68fea4d511b1ac46a28dcd2c6", "sha256": "c1fc0f953048f743385d31c468b4a678b3ad20caffdeaa94bed85ba63049fd58" }, "name": "packaging", "size": 72010, "build": "pyhcf101f3_0", "subdir": "noarch", "channel": "conda-forge", "version": "26.0" }, "python_abi-3.13.1-1_cp313.tar.bz2": { "hash": { "sha256": "30a61e8347df1050a1aadbf34ece486d4a5fb173526d4c8af83f825620eb844a" }, "name": "python_abi", "size": 2597, "build": "1_cp313", "subdir": "emscripten-wasm32", "channel": "emscripten-forge", "version": "3.13.1" }, "asttokens-3.0.1-pyhd8ed1ab_0.conda": { "hash": { "md5": "9673a61a297b00016442e022d689faa6", "sha256": "ee4da0f3fe9d59439798ee399ef3e482791e48784873d546e706d0935f9ff010" }, "name": "asttokens", "size": 28797, "build": "pyhd8ed1ab_0", "subdir": "noarch", "channel": "conda-forge", "version": "3.0.1" }, "decorator-5.2.1-pyhd8ed1ab_0.conda": { "hash": { "md5": "9ce473d1d1be1cc3810856a48b3fab32", "sha256": "c17c6b9937c08ad63cb20a26f403a3234088e57d4455600974a0ce865cb14017" }, "name": "decorator", "size": 14129, "build": "pyhd8ed1ab_0", "subdir": "noarch", "channel": "conda-forge", "version": "5.2.1" }, "executing-2.2.1-pyhd8ed1ab_0.conda": { "hash": { "md5": "ff9efb7f7469aed3c4a8106ffa29593c", "sha256": "210c8165a58fdbf16e626aac93cc4c14dbd551a01d1516be5ecad795d2422cad" }, "name": "executing", "size": 30753, "build": "pyhd8ed1ab_0", "subdir": "noarch", "channel": "conda-forge", "version": "2.2.1" }, "lazy-loader-0.4-pyhd8ed1ab_2.conda": { "hash": { "md5": "d10d9393680734a8febc4b362a4c94f2", "sha256": "d7ea986507090fff801604867ef8e79c8fda8ec21314ba27c032ab18df9c3411" }, "name": "lazy-loader", "size": 16298, "build": "pyhd8ed1ab_2", "subdir": "noarch", "channel": "conda-forge", "version": "0.4" }, "lazy_loader-0.4-pyhd8ed1ab_2.conda": { "hash": { "md5": "bb0230917e2473c77d615104dbe8a49d", "sha256": "e26803188a54cd90df9ce1983af70b287c4918c0fd178a9aabd9f1580f657a2b" }, "name": "lazy_loader", "size": 6661, "build": "pyhd8ed1ab_2", "subdir": "noarch", "channel": "conda-forge", "version": "0.4" }, "pure_eval-0.2.3-pyhd8ed1ab_1.conda": { "hash": { "md5": "3bfdfb8dbcdc4af1ae3f9a8eb3948f04", "sha256": "71bd24600d14bb171a6321d523486f6a06f855e75e547fa0cb2a0953b02047f0" }, "name": "pure_eval", "size": 16668, "build": "pyhd8ed1ab_1", "subdir": "noarch", "channel": "conda-forge", "version": "0.2.3" }, "pygments-2.19.2-pyhd8ed1ab_0.conda": { "hash": { "md5": "6b6ece66ebcae2d5f326c77ef2c5a066", "sha256": "5577623b9f6685ece2697c6eb7511b4c9ac5fb607c9babc2646c811b428fd46a" }, "name": "pygments", "size": 889287, "build": "pyhd8ed1ab_0", "subdir": "noarch", "channel": "conda-forge", "version": "2.19.2" }, "pyparsing-3.3.2-pyhcf101f3_0.conda": { "hash": { "md5": "3687cc0b82a8b4c17e1f0eb7e47163d5", "sha256": "417fba4783e528ee732afa82999300859b065dc59927344b4859c64aae7182de" }, "name": "pyparsing", "size": 110893, "build": "pyhcf101f3_0", "subdir": "noarch", "channel": "conda-forge", "version": "3.3.2" }, "requests-2.32.5-pyhcf101f3_1.conda": { "hash": { "md5": "c65df89a0b2e321045a9e01d1337b182", "sha256": "7813c38b79ae549504b2c57b3f33394cea4f2ad083f0994d2045c2e24cb538c5" }, "name": "requests", "size": 63602, "build": "pyhcf101f3_1", "subdir": "noarch", "channel": "conda-forge", "version": "2.32.5" }, "backcall-0.2.0-pyh9f0ad1d_0.tar.bz2": { "hash": { "md5": "6006a6d08a3fa99268a2681c7fb55213", "sha256": "ee62d6434090c1327a48551734e06bd10e65a64ef7f3b6e68719500dab0e42b9" }, "name": "backcall", "size": 13705, "build": "pyh9f0ad1d_0", "subdir": "noarch", "channel": "conda-forge", "version": "0.2.0" }, "certifi-2026.1.4-pyhd8ed1ab_0.conda": { "hash": { "md5": "eacc711330cd46939f66cd401ff9c44b", "sha256": "110338066d194a715947808611b763857c15458f8b3b97197387356844af9450" }, "name": "certifi", "size": 150969, "build": "pyhd8ed1ab_0", "subdir": "noarch", "channel": "conda-forge", "version": "2026.1.4" }, "numpy-2.4.1-py313h6394566_0.tar.bz2": { "hash": { "sha256": "719e8eaf8183d02ab96b0a1cf05efd0b8b606355dfcd6b3ac1397539d700e863" }, "name": "numpy", "size": 6904916, "build": "py313h6394566_0", "subdir": "emscripten-wasm32", "channel": "emscripten-forge", "version": "2.4.1" }, "ptyprocess-0.7.0-pyhd8ed1ab_1.conda": { "hash": { "md5": "7d9daffbb8d8e0af0f769dbbcd173a54", "sha256": "a7713dfe30faf17508ec359e0bc7e0983f5d94682492469bd462cdaae9c64d83" }, "name": "ptyprocess", "size": 19457, "build": "pyhd8ed1ab_1", "subdir": "noarch", "channel": "conda-forge", "version": "0.7.0" }, "stack_data-0.6.3-pyhd8ed1ab_1.conda": { "hash": { "md5": "b1b505328da7a6b246787df4b5a49fbc", "sha256": "570da295d421661af487f1595045760526964f41471021056e993e73089e9c41" }, "name": "stack_data", "size": 26988, "build": "pyhd8ed1ab_1", "subdir": "noarch", "channel": "conda-forge", "version": "0.6.3" }, "traitlets-5.14.3-pyhd8ed1ab_1.conda": { "hash": { "md5": "019a7385be9af33791c989871317e1ed", "sha256": "f39a5620c6e8e9e98357507262a7869de2ae8cc07da8b7f84e517c9fd6c2b959" }, "name": "traitlets", "size": 110051, "build": "pyhd8ed1ab_1", "subdir": "noarch", "channel": "conda-forge", "version": "5.14.3" }, "ipython-9.9.0-py313hd355c7d_0.tar.bz2": { "hash": { "sha256": "e39dd7d6e89f16ce39ab2c9bdc986985287c75ec98817646d571ab6648ef105b" }, "name": "ipython", "size": 1177681, "build": "py313hd355c7d_0", "subdir": "emscripten-wasm32", "channel": "emscripten-forge", "version": "9.9.0" }, "pillow-12.1.0-py313hafe190e_0.tar.bz2": { "hash": { "sha256": "927ed68ff065ea2a08cdec59106b1f8e0731753f4640e1015ed41fdf09ccf1dc" }, "name": "pillow", "size": 1205242, "build": "py313hafe190e_0", "subdir": "emscripten-wasm32", "channel": "emscripten-forge", "version": "12.1.0" }, "platformdirs-4.5.1-pyhcf101f3_0.conda": { "hash": { "md5": "1bd2e65c8c7ef24f4639ae6e850dacc2", "sha256": "04c64fb78c520e5c396b6e07bc9082735a5cc28175dbe23138201d0a9441800b" }, "name": "platformdirs", "size": 23922, "build": "pyhcf101f3_0", "subdir": "noarch", "channel": "conda-forge", "version": "4.5.1" }, "pyjs-rt-3.2.0-py313h7595f35_0.tar.bz2": { "hash": { "sha256": "685501d87313eeb2de9c2adaaa3a2850998e03d1bfc55910f58840267bb9c98f" }, "name": "pyjs-rt", "size": 46084, "build": "py313h7595f35_0", "subdir": "emscripten-wasm32", "channel": "emscripten-forge", "version": "3.2.0" }, "pyodide-http-0.2.2-pyhcf101f3_0.conda": { "hash": { "md5": "fa9bbfc44b2482fb55bbb9e106958b71", "sha256": "7e2a6f50f86910c22ab7883aa358fe1f5b4d2e2278b8f158d421c85d27057542" }, "name": "pyodide-http", "size": 16750, "build": "pyhcf101f3_0", "subdir": "noarch", "channel": "conda-forge", "version": "0.2.2" }, "pysocks-1.7.1-py313h945b378_1.tar.bz2": { "hash": { "sha256": "b6ac73564022744246d67e6537ab40d7d88bf1b4a13a70336e47d2cbcc35869f" }, "name": "pysocks", "size": 39280, "build": "py313h945b378_1", "subdir": "emscripten-wasm32", "channel": "emscripten-forge", "version": "1.7.1" }, "contourpy-1.3.3-py313h3a67976_1.tar.bz2": { "hash": { "sha256": "8b1c15e8fad62cd626ef31ce3bd823e83b4ff7de112ad9ed2bf6089397d2e410" }, "name": "contourpy", "size": 158979, "build": "py313h3a67976_1", "subdir": "emscripten-wasm32", "channel": "emscripten-forge", "version": "1.3.3" }, "h5py-3.13.0-np22py313h6514d6e_1.tar.bz2": { "hash": { "sha256": "52fd107c6dfa6a39ee90f37b5452191d802a7ee1ade6ff996481c6b48e65ed0c" }, "name": "h5py", "size": 980887, "build": "np22py313h6514d6e_1", "subdir": "emscripten-wasm32", "channel": "emscripten-forge", "version": "3.13.0" }, "pickleshare-0.7.5-pyhd8ed1ab_1004.conda": { "hash": { "md5": "11a9d1d09a3615fc07c3faf79bc0b943", "sha256": "e2ac3d66c367dada209fc6da43e645672364b9fd5f9d28b9f016e24b81af475b" }, "name": "pickleshare", "size": 11748, "build": "pyhd8ed1ab_1004", "subdir": "noarch", "channel": "conda-forge", "version": "0.7.5" }, "python-3.13.1-h_c8de616_5_cp313.tar.bz2": { "hash": { "sha256": "7f9a3ec3cc534475d23c072b60d4b0b4272fc4fbe7523e80aa88f7d491b83c86" }, "name": "python", "size": 13730039, "build": "h_c8de616_5_cp313", "subdir": "emscripten-wasm32", "channel": "emscripten-forge", "version": "3.13.1" }, "python-tzdata-2025.3-pyhd8ed1ab_0.conda": { "hash": { "md5": "7ead57407430ba33f681738905278d03", "sha256": "467134ef39f0af2dbb57d78cb3e4821f01003488d331a8dd7119334f4f47bfbd" }, "name": "python-tzdata", "size": 143542, "build": "pyhd8ed1ab_0", "subdir": "noarch", "channel": "conda-forge", "version": "2025.3" }, "fonttools-4.39.4-py313h6e18b15_1.tar.bz2": { "hash": { "sha256": "595fa558ea4107cda60e403e1af908094205cb8b7be6a3b43e282fe63f44c947" }, "name": "fonttools", "size": 2937624, "build": "py313h6e18b15_1", "subdir": "emscripten-wasm32", "channel": "emscripten-forge", "version": "4.39.4" }, "kiwisolver-1.4.9-py313ha0aad71_1.tar.bz2": { "hash": { "sha256": "84fd47a5e193a9bf02782fddfc18a582c74dfc76b3dc06cf9d506ce47cb8f51a" }, "name": "kiwisolver", "size": 42559, "build": "py313ha0aad71_1", "subdir": "emscripten-wasm32", "channel": "emscripten-forge", "version": "1.4.9" }, "openblas-flang-0.3.31-h4e94343_0.tar.bz2": { "hash": { "sha256": "a83164e0002ad79374d3011e071746f1e3963a4830588401aa8832695013cc81" }, "name": "openblas-flang", "size": 5481967, "build": "h4e94343_0", "subdir": "emscripten-wasm32", "channel": "emscripten-forge", "version": "0.3.31" }, "pandas-2.3.3-np22py313h9d9dc1e_0.tar.bz2": { "hash": { "sha256": "dbbee329c9543918eeb0d5bf306dae512df42becad06863fd0b82cf1d9e2a66e" }, "name": "pandas", "size": 12864256, "build": "np22py313h9d9dc1e_0", "subdir": "emscripten-wasm32", "channel": "emscripten-forge", "version": "2.3.3" }, "prompt-toolkit-3.0.52-pyha770c72_0.conda": { "hash": { "md5": "edb16f14d920fb3faf17f5ce582942d6", "sha256": "4817651a276016f3838957bfdf963386438c70761e9faec7749d411635979bae" }, "name": "prompt-toolkit", "size": 273927, "build": "pyha770c72_0", "subdir": "noarch", "channel": "conda-forge", "version": "3.0.52" }, "scipy-1.16.2-np22py313h759dc5e_0.tar.bz2": { "hash": { "sha256": "e4c759a8a09df914d327b23b2588773177a32d5b5f56d22faf3fd69d5641e717" }, "name": "scipy", "size": 20029461, "build": "np22py313h759dc5e_0", "subdir": "emscripten-wasm32", "channel": "emscripten-forge", "version": "1.16.2" }, "emscripten-abi-3.1.73-h267e887_12.tar.bz2": { "hash": { "sha256": "50477ceddc687fdda3ab437fc95237b7f1c489e28470adc2ea453105b497eed2" }, "name": "emscripten-abi", "size": 11548, "build": "h267e887_12", "subdir": "noarch", "channel": "emscripten-forge", "version": "3.1.73" }, "nlohmann_json-abi-3.12.0-h0f90c79_1.conda": { "hash": { "md5": "59659d0213082bc13be8500bab80c002", "sha256": "2a909594ca78843258e4bda36e43d165cda844743329838a29402823c8f20dec" }, "name": "nlohmann_json-abi", "size": 4335, "build": "h0f90c79_1", "subdir": "noarch", "channel": "conda-forge", "version": "3.12.0" }, "matplotlib-inline-0.2.1-pyhd8ed1ab_0.conda": { "hash": { "md5": "00e120ce3e40bad7bfc78861ce3c4a25", "sha256": "9d690334de0cd1d22c51bc28420663f4277cfa60d34fa5cad1ce284a13f1d603" }, "name": "matplotlib-inline", "size": 15175, "build": "pyhd8ed1ab_0", "subdir": "noarch", "channel": "conda-forge", "version": "0.2.1" }, "xeus-python-0.17.6-py313h027658c_3.tar.bz2": { "hash": { "sha256": "92394029d395124dca27d7be2a1742650f1e15bd9dea304e8407f33f22ceb308" }, "name": "xeus-python", "size": 5083856, "build": "py313h027658c_3", "subdir": "emscripten-wasm32", "channel": "emscripten-forge", "version": "0.17.6" }, "xeus-python-shell-0.6.6-pyh332efcf_0.conda": { "hash": { "md5": "fb78d1cc085480f0d2b38fee492ff7ae", "sha256": "dd7eb23e335e9baf5b83eadf97c751d649c6128d5fc14746399c138ff45d7349" }, "name": "xeus-python-shell", "size": 7365, "build": "pyh332efcf_0", "subdir": "noarch", "channel": "conda-forge", "version": "0.6.6" }, "brotli-python-1.2.0-py313h33caa6c_0.tar.bz2": { "hash": { "sha256": "0a6262854d45ff2409817bfcb378d6a624e97b3a64eae02bd66019acefba53fd" }, "name": "brotli-python", "size": 320172, "build": "py313h33caa6c_0", "subdir": "emscripten-wasm32", "channel": "emscripten-forge", "version": "1.2.0" }, "charset-normalizer-3.4.4-pyhd8ed1ab_0.conda": { "hash": { "md5": "a22d1fd9bf98827e280a02875d9a007a", "sha256": "b32f8362e885f1b8417bac2b3da4db7323faa12d5db62b7fd6691c02d60d6f59" }, "name": "charset-normalizer", "size": 50965, "build": "pyhd8ed1ab_0", "subdir": "noarch", "channel": "conda-forge", "version": "3.4.4" }, "importlib-metadata-8.7.0-pyhe01879c_1.conda": { "hash": { "md5": "63ccfdc3a3ce25b027b8767eb722fca8", "sha256": "c18ab120a0613ada4391b15981d86ff777b5690ca461ea7e9e49531e8f374745" }, "name": "importlib-metadata", "size": 34641, "build": "pyhe01879c_1", "subdir": "noarch", "channel": "conda-forge", "version": "8.7.0" }, "typing_extensions-4.15.0-pyhcf101f3_0.conda": { "hash": { "md5": "0caa1af407ecff61170c9437a808404d", "sha256": "032271135bca55aeb156cee361c81350c6f3fb203f57d024d7e5a1fc9ef18731" }, "name": "typing_extensions", "size": 51692, "build": "pyhcf101f3_0", "subdir": "noarch", "channel": "conda-forge", "version": "4.15.0" }, "pywavelets-1.4.1-np22py313h3f9f650_2.tar.bz2": { "hash": { "sha256": "3f235e32709f1bc67e1fb04d846eafe3b039c203738df6ba32c48cad8576d85d" }, "name": "pywavelets", "size": 4519764, "build": "np22py313h3f9f650_2", "subdir": "emscripten-wasm32", "channel": "emscripten-forge", "version": "1.4.1" }, "python-dateutil-2.9.0.post0-pyhe01879c_2.conda": { "hash": { "md5": "5b8d21249ff20967101ffa321cab24e8", "sha256": "d6a17ece93bbd5139e02d2bd7dbfa80bee1a4261dced63f65f679121686bf664" }, "name": "python-dateutil", "size": 233310, "build": "pyhe01879c_2", "subdir": "noarch", "channel": "conda-forge", "version": "2.9.0.post0" }, "xeus-python-shell-raw-0.6.6-pyhd8ed1ab_0.conda": { "hash": { "md5": "c753450d7e2b773bb35cfd1e2253c2c9", "sha256": "dd308739e9531ce75f7ba20127cbe2356d00eec63610e813e8d5a06fa0f3af4c" }, "name": "xeus-python-shell-raw", "size": 12760, "build": "pyhd8ed1ab_0", "subdir": "noarch", "channel": "conda-forge", "version": "0.6.6" }, "scikit-image-0.26.0-np22py313h2c67255_0.tar.bz2": { "hash": { "sha256": "bc2377c3c38f46d2c52bff3b00510da40111ecf7f518bb7128ac4ffe6d777866" }, "name": "scikit-image", "size": 9448608, "build": "np22py313h2c67255_0", "subdir": "emscripten-wasm32", "channel": "emscripten-forge", "version": "0.26.0" }, "xeus-python-shell-lite-0.6.6-pyhd8ed1ab_0.conda": { "hash": { "md5": "e053ba510540bd9f6e52a72626062e33", "sha256": "59588e3f38120c0e4df3fa4347727f3f59fdc5e4e677aa0266eb560aa646b618" }, "name": "xeus-python-shell-lite", "size": 7321, "build": "pyhd8ed1ab_0", "subdir": "noarch", "channel": "conda-forge", "version": "0.6.6" }, "matplotlib-base-3.10.8-np22py313h4202e73_0.tar.bz2": { "hash": { "sha256": "af4d7d2d2535c6f20c0912a64e6783c532d81578933b952ed24697374a50d3a6" }, "name": "matplotlib-base", "size": 11824351, "build": "np22py313h4202e73_0", "subdir": "emscripten-wasm32", "channel": "emscripten-forge", "version": "3.10.8" } }, "platform": "emscripten-wasm32", "channelInfo": { "conda-forge": [ { "url": "https://prefix.dev/conda-forge", "protocol": "https" }, { "url": "https://repo.prefix.dev/conda-forge", "protocol": "https" } ], "emscripten-forge": [ { "url": "https://prefix.dev/emscripten-forge-dev", "protocol": "https" }, { "url": "https://repo.prefix.dev/emscripten-forge-dev", "protocol": "https" } ] }, "lockVersion": "1.0.2", "pipPackages": {} }Sigima-1.1.1/.pre-commit-config.yaml000066400000000000000000000003251514013333200171770ustar00rootroot00000000000000repos: - repo: https://github.com/astral-sh/ruff-pre-commit # Ruff version. rev: v0.12.2 hooks: # Run the linter. - id: ruff-check args: [ --fix ] # Run the formatter. - id: ruff-formatSigima-1.1.1/.pylintrc000066400000000000000000000010601514013333200145600ustar00rootroot00000000000000[FORMAT] # Essential to be able to compare code side-by-side (`black` default setting) # and best compromise to minimize file size max-line-length=88 [TYPECHECK] ignored-modules=qtpy.QtWidgets,qtpy.QtCore,qtpy.QtGui,cv2,plotpy._scaler,skimage.restoration,skimage.feature [MESSAGES CONTROL] disable=wrong-import-order [DESIGN] max-args=10 # default: 5 max-positional-arguments=11 # default: 5 max-attributes=12 # default: 7 max-branches=20 # default: 12 max-locals=20 # default: 15 min-public-methods=0 # default: 2 max-public-methods=25 # default: 20Sigima-1.1.1/.readthedocs.yaml000066400000000000000000000012741514013333200161510ustar00rootroot00000000000000# Read the Docs configuration file for Sphinx projects # See https://docs.readthedocs.io/en/stable/config-file/v2.html for details version: 2 build: os: ubuntu-22.04 tools: python: "3.11" apt_packages: - xvfb - libxkbcommon-x11-0 - libxcb-icccm4 - libxcb-image0 - libxcb-keysyms1 - libxcb-randr0 - libxcb-render-util0 - libxcb-xinerama0 - libxcb-xfixes0 jobs: pre_build: # Start Xvfb before building docs - "Xvfb :99 -screen 0 1024x768x24 > /dev/null 2>&1 &" - "export DISPLAY=:99" sphinx: configuration: doc/conf.py formats: - pdf python: install: - method: pip path: . extra_requirements: - doc Sigima-1.1.1/.vscode/000077500000000000000000000000001514013333200142575ustar00rootroot00000000000000Sigima-1.1.1/.vscode/launch.json000066400000000000000000000031751514013333200164320ustar00rootroot00000000000000{ // Use IntelliSense to learn about possible attributes. // Hover to view descriptions of existing attributes. // For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387 "version": "0.2.0", "configurations": [ { "name": "Run current file", "type": "debugpy", "request": "launch", "program": "${file}", "console": "integratedTerminal", "envFile": "${workspaceFolder}/.env", "justMyCode": false, }, { "name": "Run current file (unattended)", "type": "debugpy", "request": "launch", "program": "${file}", "console": "integratedTerminal", "envFile": "${workspaceFolder}/.env", "pythonArgs": [ "-W error::DeprecationWarning", "-W error::RuntimeWarning", ], "justMyCode": false, "args": [ "--unattended", ], "env": { // "DEBUG": "1", // ☣️ Debug mode will reset .ini settings // "QT_QPA_PLATFORM": "offscreen", "SIGIMA_DATA": "${workspaceFolder}/sigima/data/tests", } }, { "name": "Profile current file", "type": "debugpy", "request": "launch", "module": "cProfile", "console": "integratedTerminal", "envFile": "${workspaceFolder}/.env", "args": [ "-o", "${file}.prof", "${file}" ], }, ] }Sigima-1.1.1/.vscode/settings.json000066400000000000000000000015141514013333200170130ustar00rootroot00000000000000{ "[bat]": { "files.encoding": "cp850" }, "[python]": { "editor.defaultFormatter": "charliermarsh.ruff" }, "[restructuredtext]": { "editor.wordWrap": "on" }, "editor.codeActionsOnSave": { "source.organizeImports.ruff": "explicit" }, "editor.formatOnSave": true, "editor.rulers": [ 88 ], "files.exclude": { "**/__pycache__": true, "**/*.pyc": true, "**/*.pyo": true }, "files.trimFinalNewlines": true, "files.trimTrailingWhitespace": true, "python.analysis.autoFormatStrings": true, "python.testing.pytestArgs": [], "python.testing.pytestEnabled": true, "python.testing.pytestPath": "pytest", "python.testing.unittestEnabled": false, "terminal.integrated.tabs.description": "${workspaceFolder}", }Sigima-1.1.1/.vscode/tasks.json000066400000000000000000000525111514013333200163030ustar00rootroot00000000000000{ // See https://go.microsoft.com/fwlink/?LinkId=733558 // for the documentation about the tasks.json format "version": "2.0.0", "tasks": [ { "label": "🧽 Ruff Formatter", "command": "${command:python.interpreterPath}", "args": [ "scripts/run_with_env.py", "${command:python.interpreterPath}", "-m", "ruff", "format", ], "options": { "cwd": "${workspaceFolder}", "statusbar": { "hide": true, }, }, "group": { "kind": "build", "isDefault": true, }, "presentation": { "clear": true, "echo": true, "focus": false, "panel": "dedicated", "reveal": "always", "showReuseMessage": true, }, "type": "shell", }, { "label": "🔦 Ruff Linter", "command": "${command:python.interpreterPath}", "args": [ "scripts/run_with_env.py", "${command:python.interpreterPath}", "-m", "ruff", "check", "--fix", ], "options": { "cwd": "${workspaceFolder}", "statusbar": { "hide": true, }, }, "group": { "kind": "build", "isDefault": true, }, "presentation": { "clear": true, "echo": true, "focus": false, "panel": "dedicated", "reveal": "always", "showReuseMessage": true, }, "type": "shell", }, { "label": "🧽🔦 Ruff", "dependsOrder": "sequence", "dependsOn": [ "🧽 Ruff Formatter", "🔦 Ruff Linter", ], "group": { "kind": "build", "isDefault": false, }, "presentation": { "clear": true, "echo": true, "focus": false, "panel": "dedicated", "reveal": "always", "showReuseMessage": true, }, "type": "shell", }, { "label": "🔦 Pylint", "command": "${command:python.interpreterPath}", "args": [ "scripts/run_with_env.py", "${command:python.interpreterPath}", "-m", "pylint", "sigima", "--disable=duplicate-code", "--disable=fixme", "--disable=too-many-arguments", "--disable=too-many-branches", "--disable=too-many-instance-attributes", "--disable=too-many-lines", "--disable=too-many-locals", "--disable=too-many-public-methods", "--disable=too-many-statements", ], "options": { "cwd": "${workspaceFolder}", }, "group": { "kind": "build", "isDefault": true, }, "presentation": { "clear": true, "echo": true, "focus": false, "panel": "dedicated", "reveal": "always", "showReuseMessage": true, }, "type": "shell", }, { "label": "🚀 Pytest", "command": "${command:python.interpreterPath}", "args": [ "scripts/run_with_env.py", "${command:python.interpreterPath}", "-m", "pytest", "--ff", // "--gui", // "--show-windows", ], "options": { "cwd": "${workspaceFolder}", "env": { // "DEBUG": "1", // ☣️ Debug mode will reset .ini settings "UNATTENDED": "1", }, }, "group": { "kind": "build", "isDefault": true, }, "presentation": { "echo": true, "reveal": "always", "focus": false, "panel": "dedicated", "showReuseMessage": true, "clear": true, }, "type": "shell", }, { "label": "sphinx-build", "command": "${command:python.interpreterPath}", "args": [ "scripts/run_with_env.py", "${command:python.interpreterPath}", "-m", "sphinx", "build", "doc", "build/gettext", "-b", "gettext", "-W", ], "options": { "cwd": "${workspaceFolder}", "statusbar": { "hide": true, }, }, "group": { "kind": "build", "isDefault": false, }, "presentation": { "clear": true, "echo": true, "focus": false, "panel": "dedicated", "reveal": "always", "showReuseMessage": true, }, "type": "shell", }, { "label": "sphinx-intl update", "command": "${command:python.interpreterPath}", "args": [ "scripts/run_with_env.py", "${command:python.interpreterPath}", "-m", "sphinx_intl", "update", "-d", "doc/locale", "-p", "build/gettext", "-l", "fr", "--no-obsolete", "-w", "0", ], "options": { "cwd": "${workspaceFolder}", "statusbar": { "hide": true, }, }, "group": { "kind": "build", "isDefault": false, }, "presentation": { "clear": true, "echo": true, "focus": false, "panel": "dedicated", "reveal": "always", "showReuseMessage": true, }, "type": "shell", "dependsOrder": "sequence", "dependsOn": [ "sphinx-build", ], }, { "label": "cleanup-doc-translations", "command": "${command:python.interpreterPath}", "args": [ "scripts/run_with_env.py", "${command:python.interpreterPath}", "-m", "guidata.utils.translations", "cleanup-doc", "--directory", ".", ], "options": { "cwd": "${workspaceFolder}", "statusbar": { "hide": true, }, }, "group": { "kind": "build", "isDefault": false, }, "presentation": { "clear": true, "echo": true, "focus": false, "panel": "dedicated", "reveal": "always", "showReuseMessage": true, }, "type": "shell", "dependsOrder": "sequence", "dependsOn": [ "sphinx-intl update", ], }, { "label": "sphinx-intl build", "command": "${command:python.interpreterPath}", "args": [ "scripts/run_with_env.py", "${command:python.interpreterPath}", "-m", "sphinx_intl", "build", "-d", "doc/locale", ], "options": { "cwd": "${workspaceFolder}", "statusbar": { "hide": true, }, }, "group": { "kind": "build", "isDefault": false, }, "presentation": { "clear": true, "echo": true, "focus": false, "panel": "dedicated", "reveal": "always", "showReuseMessage": true, }, "type": "shell", }, { "label": "🔎 Scan translations", "command": "${command:python.interpreterPath}", "args": [ "scripts/run_with_env.py", "${command:python.interpreterPath}", "-m", "guidata.utils.translations", "scan", "--name", "sigima", "--directory", ".", "--copyright-holder", "DataLab Platform Developers", "--languages", "fr", ], "group": { "kind": "build", "isDefault": false, }, "options": { "cwd": "${workspaceFolder}", }, "presentation": { "clear": true, "echo": true, "focus": false, "panel": "dedicated", "reveal": "always", "showReuseMessage": true, }, "type": "shell", "dependsOrder": "sequence", "dependsOn": [ "cleanup-doc-translations", ], }, { "label": "📚 Compile translations", "command": "${command:python.interpreterPath}", "args": [ "scripts/run_with_env.py", "${command:python.interpreterPath}", "-m", "guidata.utils.translations", "compile", "--name", "sigima", "--directory", ".", ], "group": { "kind": "build", "isDefault": false, }, "options": { "cwd": "${workspaceFolder}", }, "presentation": { "clear": true, "echo": true, "focus": false, "panel": "dedicated", "reveal": "always", "showReuseMessage": true, }, "type": "shell", "dependsOrder": "sequence", "dependsOn": [ "sphinx-intl build", ], }, { "label": "Generate requirements", "command": "${command:python.interpreterPath}", "args": [ "scripts/run_with_env.py", "${command:python.interpreterPath}", "-m", "guidata.utils.genreqs", "all", ], "options": { "cwd": "${workspaceFolder}", "statusbar": { "hide": true, }, }, "group": { "kind": "build", "isDefault": false, }, "presentation": { "clear": true, "echo": true, "focus": false, "panel": "dedicated", "reveal": "always", "showReuseMessage": true, }, "type": "shell", }, { "label": "🧪 Coverage tests", "type": "shell", "command": "${command:python.interpreterPath}", "args": [ "scripts/run_with_env.py", "${command:python.interpreterPath}", "-m", "coverage", "run", "-m", "pytest", "sigima", ], "options": { "cwd": "${workspaceFolder}", "env": { "COVERAGE_PROCESS_START": "${workspaceFolder}/.coveragerc", }, "statusbar": { "hide": true, }, }, "group": { "kind": "test", "isDefault": true, }, "presentation": { "panel": "dedicated", }, "problemMatcher": [], }, { "label": "📊 Coverage full", "type": "shell", "windows": { "command": "${command:python.interpreterPath} -m coverage combine && ${command:python.interpreterPath} -m coverage html && start htmlcov\\index.html", }, "linux": { "command": "${command:python.interpreterPath} -m coverage combine && ${command:python.interpreterPath} -m coverage html && xdg-open htmlcov/index.html", }, "osx": { "command": "${command:python.interpreterPath} -m coverage combine && ${command:python.interpreterPath} -m coverage html && open htmlcov/index.html", }, "options": { "cwd": "${workspaceFolder}", "env": { "COVERAGE_PROCESS_START": "${workspaceFolder}/.coveragerc", }, }, "presentation": { "panel": "dedicated", }, "problemMatcher": [], "dependsOrder": "sequence", "dependsOn": [ "🧪 Coverage tests", ], }, { "label": "Update doc resources (statically generated)", "type": "shell", "command": "cmd", "args": [ "/c", "update_doc_resources.bat", ], "options": { "cwd": "scripts", "env": { "PYTHON": "${command:python.interpreterPath}", "UNATTENDED": "1", }, "statusbar": { "hide": true, }, }, "group": { "kind": "build", "isDefault": false, }, "presentation": { "echo": true, "reveal": "always", "focus": false, "panel": "dedicated", "showReuseMessage": true, "clear": true, }, "dependsOrder": "sequence", "dependsOn": [ "Generate requirements", ], }, { "label": "Upgrade PlotPyStack", "command": "${command:python.interpreterPath}", "args": [ "scripts/run_with_env.py", "${command:python.interpreterPath}", "-m", "pip", "install", "--upgrade", "pip", "PythonQwt", "guidata", "PlotPy", ], "options": { "cwd": "${workspaceFolder}", "statusbar": { "hide": true, }, }, "group": { "kind": "build", "isDefault": true, }, "presentation": { "echo": true, "reveal": "always", "focus": false, "panel": "shared", "showReuseMessage": true, "clear": false, }, "type": "shell", }, { "label": "🔁 Reinstall guidata/plotpy dev", "type": "shell", "windows": { "command": ".venv/scripts/pip uninstall -y guidata plotpy; Remove-Item -Recurse -Force .venv/Lib/site-packages/guidata -ErrorAction SilentlyContinue; Remove-Item -Recurse -Force .venv/Lib/site-packages/plotpy -ErrorAction SilentlyContinue; .venv/scripts/pip install -e ../guidata; .venv/scripts/pip install -e ../plotpy", }, "linux": { "command": ".venv/bin/pip uninstall -y guidata plotpy && rm -rf .venv/lib/python*/site-packages/guidata && rm -rf .venv/lib/python*/site-packages/plotpy && .venv/bin/pip install -e ../guidata && .venv/bin/pip install -e ../plotpy", }, "osx": { "command": ".venv/bin/pip uninstall -y guidata plotpy && rm -rf .venv/lib/python*/site-packages/guidata && rm -rf .venv/lib/python*/site-packages/plotpy && .venv/bin/pip install -e ../guidata && .venv/bin/pip install -e ../plotpy", }, "options": { "cwd": "${workspaceFolder}", "statusbar": { "hide": true, }, }, "presentation": { "panel": "dedicated", "reveal": "always", }, "problemMatcher": [], }, { "label": "🧹 Clean Up", "type": "shell", "command": "${command:python.interpreterPath}", "args": [ "scripts/run_with_env.py", "${command:python.interpreterPath}", "-m", "guidata.utils.cleanup" ], "options": { "cwd": "${workspaceFolder}" }, "group": { "kind": "build", "isDefault": true }, "presentation": { "echo": true, "reveal": "always", "focus": false, "panel": "shared", "showReuseMessage": true, "clear": false, }, }, { "label": "📚 Build doc", "command": "${command:python.interpreterPath}", "args": [ "scripts/run_with_env.py", "${command:python.interpreterPath}", "-m", "sphinx", "build", "doc", "${workspaceFolder}/build/doc", "-b", "html", "-D", "language=fr", // "-W", ], "options": { "cwd": "${workspaceFolder}", }, "group": { "kind": "build", "isDefault": true, }, "presentation": { "clear": true, "echo": true, "focus": false, "panel": "dedicated", "reveal": "always", "showReuseMessage": true, }, "type": "shell", "dependsOrder": "sequence", "dependsOn": [ "Generate requirements", ], }, { "label": "🌐 Open HTML doc", "type": "shell", "windows": { "command": "start build/doc/index.html", }, "linux": { "command": "xdg-open build/doc/index.html", }, "osx": { "command": "open build/doc/index.html", }, "options": { "cwd": "${workspaceFolder}", }, "problemMatcher": [], }, { "label": "📦 Build package", "type": "shell", "command": "${command:python.interpreterPath}", "args": [ "scripts/run_with_env.py", "${command:python.interpreterPath}", "-m", "guidata.utils.securebuild", "--prebuild", "python -m guidata.utils.translations compile --name sigima --directory .", ], "options": { "cwd": "${workspaceFolder}", }, "group": { "kind": "build", "isDefault": false, }, "presentation": { "clear": true, "panel": "dedicated", }, "problemMatcher": [], "dependsOrder": "sequence", "dependsOn": [ "🧹 Clean Up", ], }, { "label": "❔ Untracked files", "type": "shell", "command": "git ls-files --others | Where-Object { $_ -notmatch '^\\.' -and $_ -notmatch '^(build|dist|releases)/' -and $_ -notmatch '.(pyc|mo)$'}", "options": { "cwd": "${workspaceFolder}", }, "group": { "kind": "build", "isDefault": true, }, "presentation": { "echo": true, "reveal": "always", "focus": false, "panel": "dedicated", "showReuseMessage": true, "clear": true, }, }, ], }Sigima-1.1.1/LICENSE000066400000000000000000000030001514013333200137140ustar00rootroot00000000000000BSD 3-Clause License Copyright (c) 2023, DataLab Platform Developers. All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. Sigima-1.1.1/MANIFEST.in000066400000000000000000000001161514013333200144520ustar00rootroot00000000000000graft doc graft sigima/locale include CONTRIBUTING.md include requirements.txtSigima-1.1.1/README.md000066400000000000000000000163221514013333200142010ustar00rootroot00000000000000# Sigima - Scientific Image and Signal Processing Library ![Sigima](https://raw.githubusercontent.com/DataLab-Platform/Sigima/main/doc/images/Sigima-Banner.svg) [![license](https://img.shields.io/pypi/l/sigima.svg)](./LICENSE) [![pypi version](https://img.shields.io/pypi/v/sigima.svg)](https://pypi.org/project/sigima/) [![PyPI status](https://img.shields.io/pypi/status/sigima.svg)](https://github.com/DataLab-Platform/Sigima) [![PyPI pyversions](https://img.shields.io/pypi/pyversions/sigima.svg)](https://pypi.org/project/sigima/) [![Sigima demo](https://img.shields.io/badge/notebook-link-e2d610?logo=jupyter&logoColor=white)](https://notebook.link/github/DataLab-Platform/Sigima/tree/main/notebooks/?path=notebooks/sigima_basic_example.ipynb) **Sigima** is an **open-source Python library for scientific image and signal processing**, designed as a modular and testable foundation for building advanced analysis pipelines. 🔬 Developed by the [DataLab Platform Developers](https://github.com/DataLab-Platform), Sigima powers the computation backend of [DataLab](https://datalab-platform.com/). ## 🚀 Try it Online **Experience Sigima instantly in your browser** — no installation required! [![Sigima demo](https://img.shields.io/badge/notebook-link-e2d610?logo=jupyter&logoColor=white)](https://notebook.link/github/DataLab-Platform/Sigima/tree/main/notebooks/?path=notebooks/sigima_basic_example.ipynb) Click the badge above to open a basic example notebook in a live JupyterLite environment powered by [**notebook.link**](https://notebook.link/). This service, developed by [**QuantStack**](https://quantstack.net/), enables sharing and running Jupyter notebooks directly in the browser with zero setup. Simply run the cells to explore: - Creating signal and image objects - Applying processing functions - Visualizing results inline --- ## 🌟 Project & Sponsors | Project/Sponsor | Description | |---------------------|-------------| | DataLab logo | Open-source platform for scientific signal and image processing, powered by Sigima. | | NLnet logo | European non-profit supporting open-source and internet projects. Sigima has received funding from NLnet for its development, through the DataLab project. | --- ## ✨ Highlights - Unified processing model for **1D signals** and **2D images** - Works with **object-oriented wrappers** (`SignalObj`, `ImageObj`) extending NumPy arrays - Includes common processing tasks: filtering, smoothing, binning, thresholding, labeling, etc. - Structured for **testability**, **modularity**, and **headless usage** - 100% **independent of GUI frameworks** (no Qt/PlotPyStack dependencies) --- ## 💡 Use cases Sigima is meant to be: - A **processing backend** for scientific/industrial tools - A library to **build reproducible analysis pipelines** - A component for **headless automation or remote execution** - A testbed for **developing and validating new signal/image operations** --- ## 📖 Design Philosophy The main goal of **Sigima** is to provide a unified, high-level API for handling and processing **1D signals** and **2D images**, through dedicated Python objects: `SignalObj` and `ImageObj`. The library is organized to separate concerns clearly: - `sigima.objects`: defines the object model for signals and images. - `sigima.params`: contains parameter classes for configuring processing functions. - `sigima.proc`: provides high-level processing functions that operate directly on `SignalObj` and `ImageObj` instances. - `sigima.io`: handles input/output operations (CSV files, image formats, etc.) for signals and images. - `sigima.tools`: contains **low-level, NumPy-based functions** that implement the core logic behind many processing routines. This structure supports a **layered programming model**: - Developers can use `computation` to process full signal/image objects in an object-oriented manner. - Or they can directly use `tools` to process raw NumPy arrays — for instance, in custom tools or when integrating Sigima into other projects. > ⚠️ `sigima.tools` is not intended as a general-purpose NumPy extension. Its purpose is to **fill in the gaps** of common scientific libraries (NumPy, SciPy, scikit-image, etc.), offering consistent tools for signal/image processing in the context of Sigima and similar projects. --- ## Usage Outside Sigima Although Sigima is designed primarily for object-based processing, some of its core functions are useful on their own. For instance, the [DataLab](https://datalab-platform.com) project — an open-source platform for signal/image processing — uses many functions from `sigima.tools` independently of the object model. This demonstrates how `sigima.tools` can serve as a **lightweight utility layer** in scientific and industrial Python applications, even when the object model is not used directly. To maintain this flexibility and avoid confusion, the distinction between `tools` (array-based) and `computation` (object-based) is intentional and explicit. --- ## 📦 Installation ```bash pip install sigima ``` Or in a development environment: ```bash git clone https://github.com/DataLab-Platform/Sigima.git cd Sigima pip install -e . ``` --- ## 📚 Documentation 📖 Full documentation (in progress) is available at: 👉 > Want to use Sigima inside DataLab with GUI tools? > Check out the full platform: [DataLab](https://datalab-platform.com/) --- ## ⚙️ Architecture Sigima is organized by data type: ```text sigima/ ├── tools/ # Low-level NumPy-based algorithms supporting some computation functions ├── proc/ # High-level processing functions operating on SignalObj/ImageObj │ ├── base/ # Common processing functions │ ├── signal/ # 1D signal processing │ └── image/ # 2D image processing ``` Each domain provides: - Low-level functions operating on NumPy arrays - High-level functions operating on `SignalObj` or `ImageObj` --- ## 🧪 Testing Sigima comes with unit tests based on `pytest`. To run all tests: ```bash pytest ``` To run GUI-assisted validation tests (optional): ```bash pytest --gui ``` --- ## 🧠 License Sigima is distributed under the terms of the BSD 3-Clause license. See [LICENSE](./LICENSE) for details. --- ## 🤝 Contributing Bug reports, feature requests and pull requests are welcome! See the [CONTRIBUTING](https://datalab-platform.com/en/contributing) guide to get started. --- ![Python](https://raw.githubusercontent.com/DataLab-Platform/DataLab/main/doc/images/logos/Python.png) ![NumPy](https://raw.githubusercontent.com/DataLab-Platform/DataLab/main/doc/images/logos/NumPy.png) ![SciPy](https://raw.githubusercontent.com/DataLab-Platform/DataLab/main/doc/images/logos/SciPy.png) ![scikit-image](https://raw.githubusercontent.com/DataLab-Platform/DataLab/main/doc/images/logos/scikit-image.png) ![OpenCV](https://raw.githubusercontent.com/DataLab-Platform/DataLab/main/doc/images/logos/OpenCV.png) --- © DataLab Platform Developers Sigima-1.1.1/babel.cfg000066400000000000000000000001321514013333200144400ustar00rootroot00000000000000# This file is used to configure Babel for the project. [python: **.py] encoding = utf-8 Sigima-1.1.1/doc/000077500000000000000000000000001514013333200134635ustar00rootroot00000000000000Sigima-1.1.1/doc/_static/000077500000000000000000000000001514013333200151115ustar00rootroot00000000000000Sigima-1.1.1/doc/_static/DataLab-Banner.svg000066400000000000000000001136771514013333200203440ustar00rootroot00000000000000 image/svg+xmlDataLab Sigima-1.1.1/doc/_static/DataLab-Title.svg000066400000000000000000001127251514013333200202110ustar00rootroot00000000000000 image/svg+xmlDataLab Sigima-1.1.1/doc/_static/DataLab.svg000066400000000000000000001111001514013333200171140ustar00rootroot00000000000000 image/svg+xml Sigima-1.1.1/doc/_static/Sigima-Frontpage.png000066400000000000000000001676371514013333200207770ustar00rootroot00000000000000PNG  IHDRfr pHYsaaøtEXtSoftwarewww.inkscape.org< IDATxK\y{ A $%Ymc[R*&URY*|}l2*J줢8)REE$ w >=3}?,zf0L~Eӧ{,"ވκqD|&"uDTif"?E?<Α'j_FĿ:'޿h5MnDq8~jfL>ߨ읕{4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH4AH=g\T11QuUUDU7jEδc݊ٙ88v븇Ξi(&&frY݊vvkl9쿶>/}mut']Mn'3Z|KOϧ_ q4'>r{'H۶~dۇ}i"!I1LPT;'DG=Ox}/9AX>t(}wdO{n>ou~㱀y8c1 3{G̴cn=y/:7ŕŷRozB E8w/>^oǃnt(j'{\GQNba]0"V6{ލK{J|뫗҅㽓gc{wֻNQMnM5jZGۭC˪~AA/_XІ8>(IH,f/uJxhjQϨ-VĹj-o\^}!._t"rQxjw뱵3<OOՏ&Xۚ̌}-+ tn,ob0,SVI(nbkḊḊ.-ĹŹpQuj2?ģ3/G]77ǭX|a(ķR|+canpB?qx6F2n-mO޺ߋw?*ɶ8l88ꦉ[K۱ލVʅ'uqlǷ7z7#f(>(G2=꺉8>XwuXS&˪[G+xU]GYUQkʸqӛ>|q ,ANar|xs#6wN΋ꨨ❏Vƽs_qڔU~[ލqy1q_Q폣;q!(0=꺉0Nnǟy'>~">HP)WMZڎgbӟh&>nof?47(bm+8$feAI|i(kBEYǟv{KSn|pc->z'o`7u|p^L~) <+MD4qwy'߇qVާ$(”&q|xc=>qLq+v{#qDǦ;9kY (”**n/mǯubuLMNwo~Iy"n`TFs|?,?tgNv#[;7o]'hHP)޾wWv"uxXGY>U]Go8;;S6pT0*!'PL< /GXۛ[a"<7"Lnb;?Vֻ={~'pN861.>7ѸAk(MDV疃hZjOƽq AP;;`t,>4Muciu:"`R[$Uuqa8Af2Cʉp6}|k#nAf?޽~ӶDнXZFQgžccdyT՚?5M|v_Y֍;AL4ލw>^.:3^ln.~Ya1ib7x:}kfq8.q[#ia U,w㣛Syibs{noN UF?v㩜4aqlMќO*[ø@PAP)sk:L!=ۃ~g3lu+퍏{(_L+ R5(DU5A̍[(GtGqwy'; zSrB'kpTM!B9 ElpE"MqV[=ZF26ًlp+:v(|p\NY8FQb0,b3e`0%꺉QQ۱=E7wb;:ۃSg1(XŸ<'):w:'ME j 0%z"޽[;SYUY9S 6M`TV粬b?q IDATJPU㲚֥a0%"޽;dF_Yձ=9Ǩ(GoPD}J\U7GLzǦi&K"M3a4_MA/its2{>_Dk;A՚DN?ֶqqc;jʪޠyi&ZV41;4.(:ٻ,bnv&f1?7uhLc\<\b݊v+|xAP)buAUV7{э=gn?:53Lu(:fgL|;w6ntvGQVu___VTڟI4wQs3 ;߼/.DČWNAZg(N,~n{vw;qKjMf Ge羔4}؛tf/2Uw}5h%>k ˨ٙv\87W.]}!+ɴދ?Y~~,vccgdلv+ba~6.WZ|;Wcna mƽΩ\;~e͞YTUD_DwpqQ~4ΫdqYEQTQV;ggZ1w(lp~>^8? 8Պ^r䭻+qgyEi勋qgy;V7s4<܋wNoէ:?ێomXj\r!Sw` 0V7{q qQl sk&uDoPDo0:˺ GŧgeQq U eEwэ͝a EUeUV+fcq~&-ŹxqxX\v_cv72>T7MQR2>Zg^ď~'- ^x>N3NqQ _*[ɝϿNY'wbi7mGU7È<"LAZD]7EEX;…S˪ @l0*cT|k,ędf'wg/{ƽXGY<ƾ59\|Ko?wx17ӊiOߝu;ǟě4E8xȧ KqqKWVuw1 iU7MEq _ZA&7/փ;(pTFQ=D*du7~R2~z9Wo3jSiX_{?޽ލ7^ Kd-<;unwڈ?zr1׮^ӹkkXLfnZS"FU0F4(""I8u=equ]E?ӧ}@ ],~2j_"H$@D~RlvMWlcPTq\هlRqG04|C*0tU īc)~E ?BP(ۼsiM'9KO 2:٨LݮnEq=%_v},?ϱ^ xD]ϒ'tj&ޏ|bl&GvbKD"H$3Ϊ]"yD]*^xE2݉GJPlB{+tC48ɸAP~3XRuڪ:eL/:Ƿ^<Ө@z>5˥\up#Zsq]dqI{P+;տx~Tj=E$D"HUDZ|=geBbӕts+Z~ 7"Etz;c(Bp"pX^+S/;#W|k|\? th6+TAi)y|ԡH$D"H)(J$mJvYZ++_,G/6? GuR ]Uy~.ϑ+xndq}|FxT6TMU=*"Ý%tM=ɟ*UQе3!H$D"98()z+V3U-wJBiUlPlĂ Sq,TE!bh&k\v\\ulJ{H%̶TULE(j{r} D̐ddܠ3ٓBJ":&D"H$A"gcIRܙYj6lTh-^~zB VZE (G!0ؓ 59rul7S9$?|ȇWYW[.ߏqh7ddR E*yx G:$@&N"&ݵD"H$%6Tj-Qoiglbš-ۥj2PJ055zDM>g*NK.1X_~sa1rԮ >5‰G+ _vBQh'<57GEtCQ"H$䀑!IR:C1jj>MbS,[ξ/ʺBIdzVP:6Ac"}VSLltM!3Hu.\[K3\[qw')Btgbuӑ54LCE|A~Qج嫬*,g+,BvC0>޽cv1t@ ( xd/OcybaGJ'LNv>{mUxFh"O关\_%_vt$OS}LmJ$D"|UD҆؎Gh1RܓD"0TFSd,e.(~|z~X(YTj~f=X:ik ]!ƣшFd >!D(^tK1ؓ`/`O$=qQkJ=t;v|KdZbqrKk%a]\P cPtgbï>gXWOq3GOpP'񨾏-HB+o m|>5UNDx^{f~5W"H$D (!b2eN"!QSc;H(3;tCbf-WQ(k],TD4q3̅*uav=!"HElWY5TP==·_HC|E(J&i2ԛB 9qWZ.𱚫xvā2y! MXk PED ǎt󝗏_}}D?q')Wm jeز)tuxt??I:עVK$D"HB I^a~&b:q8ݙhې/Y{^ (-烌:񈎪RqwtUUAg:Jjiۅ[\*0Нt"&nhHgw3\$[Q:~it" !P#i TNήYZ+W]Uģ:](IQD"H$#E YUXZkEE L$3(]Wm,ciL,?zK4t[9t-t":.aH ˕;ܘ\"LExC!yYWJl T-kϮ*{" 31ai\P4M UUtc:":?QQ;rc$c&] |Br-J/ӷxA.p"@Uh(y8QAYS%D"H$%6|VsUe > SWI'#t#ΐx`/B~/ӗgeB"5m-"HtM(ۮv Q3x+3I'N8Cv =IQ:3Q} B0GcGi4UvH$D"H$_-(糸ZXP3#!bQ+.b;+k2~C"u"@HDTչqo'YgQhD'hhJ$D"H$W)(J$m,(wV@c7w%LG[<1ܗZq}mWn\ϧX[Z!q y'vXD ˎdGĢz[8DM81\vll޷Ss+`S6 Qݘq?wMBlڶ16zk7J$~!Ep]"{:b=Ӵ060YVZ (mK,rptT,ùs&lh_(b*шtUV].m̩. gQCpϣ(?oo2XvB'G99E,m,$D"i79! 1LG߯x!@5ƶ8fc[@l' P=m hƄIll[@'Xs7ab׿7+\5^+_ +5Ƶܴ߃ϵq=6 wۻbnc SM8r"H)(J$mAYx 87N%eK|P7~_<޶Mx@9&AQUopc mK/r5u9%W)(J$mXr\wB4U3%3*vĉGk{~M@XT%/5@B55 wJʚ*E aP5]S\M.4t8QS#_H%LP CQǣXPO>^yr==Bg:jD"i?Bg*va%[ҍŃnD"yđD&؎Gd/[8n늑h 3HM"EtƈG[̗,J{@rDP5XD҅*h)xO8 JePkZP5N@>"Gx Cd1էKGx BD"H$D"EM(Um斋8- 14zD/`BRjywC(W{rZ)#*XD|@ B\ϧf5_EUq]S}.`(mjS^~r]/92;Hp.H$D"H$HAQ"iJ㵴2a $ԝC3NՇ͡RCQWÐTV0RnB*E\ףf{MWVUA2a">8ߴB`*]ɘQ/rЭH$D"H$>KODjJ"ZϡН-,mJŨAP-" ]E/͡( ĨO BK!`nNP0d*a qH$D"H$ EM(UCA B{D;1D z~QŠɕm$cݦ(CW1 QQ^j;I-l= p(B(*ug%D"H$HAQ"iJ0Vx1M}r(B-&T- 5J!W᷹=.T5uxpRϡج(afA~HED"H$D"4%6\qXX)HPo>IgE-}bŦfBwcUEhK *ڴ|VsUGU!pyH$D"H$IsȢ,IP8B44RqTDU (n%TUj| z  XsG xp!kUtPAԏT^KXX)Q9h0l?Wj,nP7nD"=mq}jGb+XUk+6)>M 3u1tLXT шhjp|? gӸ(rR:Xm7*Uvbx5݈QU6rLG DThDGt-1XDGSEー}?hm5GR"|ED嫬-?o:iZPLM:ӭ+5(K@`ۭ1:SW0ȷH.\4rlfS;y"GQ50F?^"{Alcqĵ5nN16|lRչ;*8tc'H_xT/Ik3 {¾|VwoqWydb׭lͳ8qXD}{M( F5\;+ܜ\LBqƳ~N6_#U{Ls|pr`;dKmRKV+\[7Nct0c­,KkeJmvvlml\:S#4cvS]i}r<~{~ܖۛʋgHtz;N9x*6S >6b٥ %*5wR~(lu yܘXPS=Hd̸', hf׹>ʍ5&,XZ+Q({x>>YR7'#]9ñ ]HiA\Yp}b5 ̯[.V\s-M@R=c ̬skr M2:ġNN+bݚZOgoK2n(Hڊ[K$_A :[R LV"JW\\+ 7E$6Fmc9qNuNP;>jϮ'3|S+\g|6ձ-21 G~("y> eV,|k+wV^SCQa'8zzƭ,p_'Nؑ.t0؛#NT\,f,Uzgbeޙ2ԛ wzƍ5旋[ o!{ACp=GL8&/.m斋Ḽs2]]`bniZ.S y>ų<}Cǖ TuAn^Ra)[fnȅ ||ucX2Wx,g,g|v{Ooy/pNFڃ:S̯[.r{*˅ ܚ̒-.,̬c ݙOS`'p_Pbz;Ymm&'ZH"HVW OԛAR TyGI0>ghyܲvy?ǣXZ^8FTqc[Ȇ "t"{M Sy~/#.ѿh QXJhw.Ls\AP9ܚEc#׎SC &,9X fd 5nNw8e?)Ulrmlc#|荓wƈnj ,a{ܚ~>/p=;Lxq7NF9sETmB-9J9jlg~J>`W懯c7E<cH$)(J$+v˫BW:۶20t8ڡ}r% i}fp=BnXFtmLjBԶ j%bh07'ט^,4}ra|6/;/rj ?]sv [Ki~$rv`jܜ\cf/?絧+G86܁WFW,ŲErۮ/O7o9㕧FM{_ 9W+ϯg.X^B[,~MWWIEЫ R:4[͇||uJզjm-&~ϱ-ia(ϟbD"J#Eq2՚JEБ?YmPDзYc~@O8YU1SV3*[t>g0ҟ*&]Aů#F_WTEHD<~}V(Yܞ01cqP yI|59ןNTeo+Jڃ^u}&]tlml/ְl?5 |Cpv`Ŕ͑ 9>:=zZ X>J0T[/ؑ.2IAl5 'x VZȳtvKÛL0>gsaHČYDUA >-b{txl{Y M;k{ȳS,[-ڮ* 3MU0 Q\XKj.nMqJr=\&7K!P۰bhIt\0\r|29g~Q'xD/dMSd#BT-˷y =?JmE*ClgM՜j>YOfo-?4RBV'~L?{tSƽc+\ ||mBz(|3T`el\= &F"|Dr؎ZyߪE2Qb ҝb><\VQ,ۭ g{)fv( bj(:GR:<~7'ŠM/y`?qC$R_7o^!q)X,gv|̬.RK;9@w6Hڏ_8ܚZ'o w޼GWYX)eFA/PX\-sQz2Qb"q\Bff<4)E( F `_sYoϳ?מ+NP(HHAQ"9@cqr :Q y5T$bjhfB[||JP"̅iڶsJ9~W963YU6\>?w/sX7(wuf `-_O>ar@Yݝi 3u=tM9CTyY.\8~ϞӇ (UC1w3R>m*AlvYY&PU$>50} WuٽF0u ]Yjsd5"'w"A6Wݲ0Ä߿<ǿˋ,!45k `.5ۭa|<9nMgN3Z"ϰ-Sva*Tܤ;^I2;AG*BЕz~@({~(u+֘_)2\biZRX}kWV~+23/Oyy?\/L\~y"f0g?H_ѡ ݙ0D^@>V.mf .^*pg:Kd첰{itҤ3H6 5׿clfk4U!3ӟd?ő x04bhjxObzUr+x,`stCt2Be O3:ġNztwHEH'L;b$ck*poPsesU֋5 5Vr Ϯsg:Zyzƹs#:?zt¬9r+,e- B&i1v0I,p齠T(Um2і~T-boV US ]EUy!Wlc*#})x'-VsUdBu}羚3'_I `aonp}|.s d8=IpPG3t(BPϭ"UL]%0]8J,cL]*Z 5pl달*؎ϫO 3:FUy*͸{?|lyGNo_<}XSN XZ+go0Z;U1Гd7Ý=:8SAzĠ7v팅P:ܙrel˷ϱZP}||u?z8S|,=ӹlr'7x8\%Wxҙ0ؓd'H#d'I<~O=)B<@z#.3Νu&r.X\+-z 6c t'(HI(P]Vs .ģ:޼L$pR:ͣ5=܎^w(`߰r8cAR(YDMv|C!+ܞ?i}qLSyBAk}aunN**DLxTS}!^zbƂńAB) slo_g^S(YXTXtpcb+Z;A4o_w]\_Ef X[Tr;1GG鈡JXkSWӶYn?  oWyInOgw%& pW;/2ԗ"71t%=c5+-B{ ]P8?|8^Oi %5LW8D SqnOm-&vx~仏qx Mg*B4ax;}|7,kB E~ ౣ-z"=Vs~_[xwbQgόC;:q'Ob*f]ܹ>-W,ʓC= e 䭛|rs8!uM;g拣^||$k667>Iҕrt8enMeW-;Y~N@_g Н,H$-RPHRf5Wi*^:p(B2fjRA\)Wm}84QWIFxH?Q{il'YX)Z$)ms%;' e.ӷo36㨊 7OgGxd/.6+BAUT^<; geWJ>sE~8~IE鈵HXYitNuM##]^2I y<܉DL|bqe|\[GM`)[yTu`*Ҽ' #~<SEu(R:\L4U:.\[`'ǻ1 5 I4*0L'ۮt*T#Cxxv#lӱ[0 ?zu0ܗBUǙ],PLQ\_c/?9T7!H$%XΡCE^]WEtbQrŁmO-wF<Uˡf֡)M;vB89,"I'L"V /cr![>23tN/y{f|zkgq N{VgǯtWųǟ_67&׶<Ɲu ?8͕4Ar6ʿˋ )mU^#CiQJ{6s &ԫ"I?8qUm6O bi7u^h8WFsVJ/ͥ17??S &w;Ob'KO |rcq˰wt $95%H$_%P<ݙ(XD# Ʒ-!|"]W~@b;aQVN# ݛQDXr'!ϛq\|HMd7M0>j3Ͽ?V|L?-D$?{$Yv{M_Y޴~z3$fA$"Wj!)}=H!BR aI0`랙]]Wϼf56U7˜Op2[ԧޖ]F'O/ratvex~v-cCb" 4W^2]oZ('|=i)8:p}|םO^= b/miDdߎ.>_ʏ޺BW?qf Oqo(J*(eDP0d$1=_ď;\btZwPt=))V0!c!q2w,K_wPVJ5/`[+k 82;4:>,T-zhPm7@JF'۟_%7S:aoG7>gN V&)8 ~꾥5gr߼FX[S_3e}pyxm}݁!׳Sz/+Hf/O%Bpm|bYӱ.%ܚαRfl:JLJٻ2We3/gզ^ە9{f?/?$1lVMwE"fb:}x=_]_>CX85&H£1@%TfvǗgXUhûNoGdE=7T$^^yz?_~2獽\Gzvf(͏1tBɹk.V2nrpw/_}0wf=,8d=?OvvvŷmL!CG"53c?*y }Ħ>7ٖN6cgBCE0^G쾑,<{$Md)J<|d_E|ɹŲ5#]tRBƥQs <Nj"7o/m'B vex]Ly87TQeSEE`PLsʦ+elK'-"#Z|u\B|E 媋eE&0Og^evp {^l?ztLVZY(Uǎ {(CEǹvx frMet'y#j4/>BkLUk/b/D @7')%sdOo.25"BRɸɩ-ɸő=&}|BA }  }|y VNڼn~d֦+Yo?P_o|Ba9_!(m߳t\gI:ٚ@K +Nڒv//)]<;@<ք7]C<9B_w#osdo/]=P_C|%?$B@oWTCAR?-ȗ)-#agM4jueĉa;>̞.hB#G;I(mFV UJK L5%vglrejk,)eVtUP"hhZxRcFq}rǣ'/ОnK||ybyTkp"/?4B%7 )E..0Tj8&f#8yE[;|ɽ||y7DO}}>b%F !L;銷ɳw4+j{Aئp_Ln(3-$+ B- >k"*2R\Eƚ(5 17l%!S;(]..rEQPTI)Y@ɳJ (N62-{FRR,;#ET] f],.0ۘx')%Sd$yk0[32N)a)Wӫs5r^xd `[iya·f|ÓЅN'叭&$&{FT]>mrr#] iVlclS'[cjrkeMs--;xLR8P{^Z`UV>5Jӛ(2*(Q|R%32u xu.D[ {Pe'2*N%׆5t]"2a 3L5Mc7f'A&e'ܚΑ+˅rW+'Mئn~ )W\>2ˍɕ_ו9`OrSkTwxj#-4{BA#nos &餵Ү %zv_6T_ȕB\;#]\͎|1 .38W=@w&Vҧ >K7)U5(l4̯(|FiqDoqv[6mGPр.ASV5M-iDtY@^5:<ȟalB0@@J\XnoS}RN'lNpҬ (nCH%-zΐhZX㐷${G"?Ֆq4^WŲiURbKz' ]iWH-]򭥆_aW_jL!;Qdz,c͋I2cgڦ7P*.Z5>)%/6lz@!z[Gh;i``#{{HL|?WYlbj(D|斊8gFo6Id|mOk!xT/L7x<[ݦr]aiRٞ Ixɽ?yo|HK@ߘXo\al:x`¸?!snL,7l&SFHM5,gLC;moGڧ*t2IdDo",Dlmt¢+-8)LN3]ya@z_6_uM0>gfkR߇e騋MЕy56RE(ҠlP5cv1FbE2f+a`Tj. ?7|Jp(KxaKyJ\<1[`vsHӇ1h{go5͓'G1يln[GQ6e6C9#{ IDATQ`LmT" U՚G`JH0C=`a:eƁ|_6 2IӇG 8o̓ ,-㷯nr}<̮4z5AJXUYW6 {K*nݽF0 ޜm;;Q3nmSo:( AOWt 7%5GdXY?tYNJcvJޫ&1ā>L]S쵒aGU( (*Joust Tsfx*5bTTט5\6,!, =)CnVH_#8O6ֵQK,MJJp[9lЗk(C*amvZbwUQݙ=m2u&'b-}}5M0'3ITW?V ~x#)Z MҗMlc; $RmEQ6DQ6r%_rp=?҇eНu47Iv:Y}iQDXy:hz z v?}K&]6 8'Vִ=/[*nb[cdž5vꙜK%&]q{U=[daxeJke1m!龻B{şD49\e0}e|ҡ$ٌMhZ"}q ( (*JD\y&Nğ>2koL` Y(ڇÌL]A^5?;pZ= 2)LL;$7ɤmqLkhzR8Ém@3 $~ >$TH_L8{;HIwLX( (*JD ZGV WKۙN$Pּ ()1 c A[{05N+;Tu^(R^qcr7ΎNX|w'1 M݃|JݛM0ԛTZDJN31[lKqZ'h'7A J$c J)Moo[!ųKgSvڸ@H)ѥ(DXv58IbvXd=C1J͋|(KqP ,SPbВ!;E 5g_Jʞ.=C*x7RBPs{8@6eۥ$ A*=ZQ2:2Mv \nvf(LN)%/cR-02';ݙ:g+%&EH+F ӱ<F2o4k5?ժ zIY&z[!0rMw#tm?>5RJs||iMTRMJI \0 ]͵ ,3FPi۝8v&'$4AՒ I6[ķA08*e*CQQMM]%"Ŋe3!$m5Ϗۜ8Oaz[KVjnM?~Hab<5L#\@I*k,9n,Gtc;%,y;P $M=4BO?Ss|.X`)ߠPz~L>ⶎiuD"9lf9MR k.-}Mv@JеWpa4?G?ԱTVQML+JDJe(f1}hz}t7+Tq1}?Xq"(ESXjFf7BD:Ѹ bgş}!N_s9ͩg/p%0Hnbn,ȉ Ep5!5_cz[[(qڍh 3хZ~7ߋTQe#QWtEH+EP-D$3^Zh]VHee~ ) Eͥi0h iBNZ{z糘pcrīr*\9R PTaQƲƬz[4Hik|pjmS?mv;h&B([:)JLlwYulq3 Kch2~P/ynbG4pf2"[6 =1fK+()<9^:L剮Rͳ\ԖmݬhDp! PŖZ*5A8vi}AA8D#$5Gyv;u-TesSEEi@JU*U7t""mM:C1 WjoCeUQ< igoBd`xNd?tv{n C1IĢiHƭH3 P[4M`[:z[ ] ~E&x_xl7=]3@'f2G} f 4AW&f=|#%T-!DO+bwڂ:܍P%$<^XSkŲC2[RpTV( (*J r( ])ێn|TᵩH\/)k@@sHvPŁavS+ָ52Rm[IL} -[baQix/UFw@b}xS %V Uu$\H:(ʦfBgY3ut#ARm*xT.A3>44XJm  @3@$K69Rq|JcqRM *VvmԶŊK^;@]myH ]0؛l~mr^.lJfJ,렢( (*J~RB+a25]iXޘ+.U=哎t$ kiS5-L乽CYth@JXR⍩`lXBpܰ`6ms0Cn bfJ/t[e(}l31هwgB\!W/(]\%y/pxA7pt2NzmRm$Pz?FUhK?]wߺ.-;2wŕ 26kwv'%\<~6MʝEi&3ʐNZ eJ Wn25_W#KeO,+lEQ6=PTqTV>^v- Tq9OxL-:t- jF6IpdOɶN hS}ff6*SD]stvӝi,s%7ώsbG2r7#I_ܕYU7l}BPo9r?}7 (_.Xsm(V\2fNܿ,jOMPy8N?i4|szKg8`o )!fbm}|p<0(5o:u4MaKo6Ka'P0$+\ȭLOѥYEYjx.,WǖT$r"ͫ(ʖ\cŊӲ4)%劋q3f(vKt]0P_c)_%ILڑH&$do{;B2U0 =mB TqApb_8OXkYFX*}ncBLScCZbjH}U~(o-Rit{EQ>dR{Gطtno.qKJ}7)%gǸ:QEiPT1d'OIBPɘ Vj5щ|¿7 EdK7I_}8g) MP(;.fvzC{L] 3wr`KcK|LQ;RRJ[Vى_*a9i5ŲÅ~(+vOп')ì2~6:o+uD(ʶї<@r~u6x_/\`9WkXUErk*N0cў50k/|8{q_㍳c.E+b7I&iw?Zr9)&nL01Wh(n bAOW#C6:!;<~b#r g.N 8yD27OXo/d|2<.eXo1җf/IwB-39KsKNo(J˩ EEQZNe O lnQי&%x^@5dZ/MXkm]иR_w~zƂi˅*_d!W![x- XBi|zeeWXΎ4Xt6 Kw TqyާܚQy۲LL0Rs\Re R ^|_21[sTx>ț Y,G~ӛ(*(J[ئNO&GwRy *.D:mVɸimk(ñj߿v?$#z@5QP &瓫ܜ5މ} ,t/=S~rʇ?G|tyv[hRRS|щU(J=G:_|4U-S*q.$sK%o̅鎴QE (*ӛl^b5n0! 3۾߄jϜɋn*!A IDAT~x&IOWD5]4@lD o=H_X^?3LrtLJٖѮiZxL^)ɗj~v>Se~ Ï/0Tx4EQ0MHá=M-..˷Tkf%Gi˝$EQQ=Ei 0RQ%J*CQQ l#’g/Kw%ϞOT[w/fF2fD{RveI6uӟ/9|zmܚat _kUj#5 U.X䝏'50,Nt=]ʐ*x*3)pN,}S,q]Kf+5/n?3q uA6GvqxO' T\QM'M5>o^r}rjV<_2 85_tD]*ت(֣mu1ho|?`PYwSU[5QBDУ4."knrk_]atbKx\w$|Y}!wM_^Xq^cCw| xg`oKg/M{|kj-8F6pzX}ato"ӷTf&isP?x`ß)m(%@=I^~joﱔׯ},U7)%bo}\mlxV:a5}ߥ(gEQ2uz⑗<*YR(9Pb7^>/%oo=^?3eئ=X*㮭盔>.<&pM xix+~_9qمm/fR ho^cakO/ratpGם a&$R{_O&zk w&iC;g_?@ iZ[?)ySʵ=\]{5^_śɗN!2I -| ;=7?yM{5m7Rµe(Fetś*klߗ,C|r0**郾eرa&f ,6{,媼{nG/f`Bm61!O|gf CRuwǗg)59E^їR50t]i~}|+^k39Xvj\ȣdž8qTŠZ !y\Ϧ?LC K,h*PDSHEQd^/)F\/Lc ed'݉[-$/)Vjq^&g.0,;Ra;&ss*B;̐MP$[Xz,/YtO.R ũC3x0i4=u W偺b ~ IJ5*UG;EW*`ZV Ug\wy+? {S'wsx bEQFEi]Ȥl1\1"Tk7<7^oD4t1cYCB}2er憕,*/k|١R _QBO( Қs"?zke5LMM#8GcA9OIfJMٚ+05_Wgx0<ӇngH[~;k%Ûpg*5-p4?x7rMe&w!N't4'EQ6/!G1u|bSњg\

voEQQEEQ&\:b]Ga:1ٻL=dL)%TvvۅFc`th/s;\ f.gq=n/eUR%Ғrgr_csq"d&Sd}UI䉈d|ut#I?yxb媱x+e_*| r(JF˯?nNy~ E)W׿WʁDMa4몪^%eHJ?~}+S #za gO r0=bcЊIxr.YZ媷mqpTQ8p-&y8uao4 X,kP(_µkxq߹l:#UoRz? GZUy"j?xggWy5  " G.k(U\ m+UrdDvBDii~<|ܼro'paXxcJxmk"~}샘OKc|v 廁.1_A*n;= +5Rf\P&GS89PId= }W(^`o_XZ+nέW X\-bqB}ۚ83xI\Dl01OKh\4\:.O~z{u_U6P,=g a 4v6\l}~P,">rX{kX,ZkbP2fgF>ى4"Q#}"aHDGF QS,(VP4t /ou XXUUT,U\ܼ"V7Jǥ9u DWJ?h5O(kˬ|mq>_O-aurвן7_B&i2$iȞ0u ?>Ճ]T=r!|[rw7qd1;xTX㓪Q(@r7 | Y|˟H'l~y~y/^kc_~2Oo,u}a0 F:ahy|" ]NPO%B*Tn΃z M/od=;o2ى4Q@)w47Ws;_ 4SX\)⣫ x9|oʕqb4G1; IyMs4NOep :kPjn~Rao hq1Wg05R=> ~]Ȧόgqr"# ;V"?b ~>?~6;680Wo<2IB'E":2,bxrx0 躦I{`:~˛vg/P-;C2fc$hq$&Q BT*.6 Un^Z sK[XZ/!_ + ڡQ'/~ƇuVr`:LX[psnӻvKǹ,I0nF#2 ?[s<wRV ܸk⳯¾ve65XÐP*~Afra&cKx\¶feAw3Ͷt26bi|tu|1ŕ"\~lKX W a\<`: Ԟx[!Gh[:KG$ ]" zۊ|p_]G)Zx%R ~kwVYH,$cqötk0 Cנi57y>\Oz(W\J.6 Ulv[*ھ&V?Lr(^8W/&O41P$#@6YqkJCa|+.n{ihлIrֱ6 Ulc/.1!l+/H$lM♓It1|~sl`~9Yaf< gF1=Q ߣhGk":M-ϝ@RQY+aqt-<~РKZQu=Tkaۣ]K#3O!0L$@cH,l)Py(jHƬK/U? (sl٥ W[!t_ ~phˌ;%1(=l:C,9>p.[+ٯo߻*5@S;AdWœx)|id6 ]8qwl#qKZј:?>S/n'2*U*WFp/ Q,~)|)DîXҳW"'@2fan).ժ*xAfTsʱtF ;R ؆b Ŋo0n$G_Za{D?)|H'lH)%Į CINNd0K:?; 'BhR`r$ Wpz*l*^\u#PM MXECDFO `<[/Lr d +O[[X3S3+ñ]eBDtT(ёslɘp6oT][e F[ V#KŃ?RZ^8o4_ዛW:-╋cx$."t,4/ $c^4 ܜkz{w7AWTqL|{h LCWձ ĺp>~Աt$W2v"@~T/_ťS9L (ёRq+]]on,u*nV,J!N8=x(NO 1ADu/!ŸL(Ngq~;'7p&-laq"KX,RQJTB& `(P'F85 0rW9ke/sp<aB@1 f1<p2vg 7cniP0%p6$NMepdN0A U Dt1P$#q $cv+a*U Z *dj!K<7z843|_a}>:V䙈( d2Iϟ >b_[V|r{D1JȦ? 6 %"" u+m ^ºcPEw--|/Ylg!*N<e01[,p6ģ.D ?9||u ^]VZj  "8=Kόrq$4o%ڶkO%k(k cr8ޞ"B0TJ!jIb0A: *@aRY?)*E]u Mc7LB@Em|m*Ԟ(Jģb}[fRԼ'B 1^I)ݛ(PItF6l{-.?'GP:zxf6Ra"^*Հ}DB4>"4r(~K~w/laehm ab84NMepz*lɘxD1>҇ )8 'a$= "z cHDMx^Mb+Tk j k{\ŲXPJQ,~:`cyJ,~ H#q~&zg5R_ҡiJYV71 q5qk喖@^061HmdRaN84|_6vyHDu(Q[@۷JA+ɘ|'>%qԇPhk۞p \y6 Xs \sC0t ַXZ+b~%X*TUPr\7R 0ztF6P&l]p /\RyCw'*P|Rg@c!;,p**'FZL`&6ڰwDDDDԯ(Q[D"j!0 ۞Iύ\Ps}{THBRq/hTE-w aEk[˩T+Li[8P@aj.sQQ§ח'q)&gaHDmYGLmbu@PXu D c' vIz ŎB`=_roiϞB:ap:{k~g RM9t&("U*f!(.r#+\n[,SCeLZ=^_rsg) _}V+>6Iݛ P-hL;͍e|r}0Q`h ñtDDDDT(Q[6W5l{~/_Pnmڽ1,RD Xz0B4nOwI0PT}!'&ؖ)n?F 5t1T|Uo/n٘JX [;DRpk[CbW۝_o~ _v|o!f]ns<ҫw]ֿ/o;/{Z(b㢝_۽sΎ+_Vu;ؿwn5ܨ&Cn?nK=z]{1Znl#"#@ʱ4"F{x^b|\ BE}rC]- q`: B\߇PUdc` " qyϝx_?~ EA;tU#&^<4"L"""":\LDmI#m l+ \z \"Bm}޻#*Re^mz !.b[6yO^_,x$64]uA/9s=R ]qo@,Fs#K"""":NzLz^6M:RX\-4=?ZvV'B ztҪ? G˙tM♓9']/~v_^A8 _Ϸ|T© ;C64=-Dv#<2U]Kk%J)QF R D#FO.wn5C (@1]:P ϡ,F&Gx1\"J)||u۟}w?zXR[ǿǝ͖o+pٷ6caHDmuL2W(VW E ^B E!1}$![w@ue~bF=lSp9@G͍|WG֎pOG7"*nmkx Źl)E"""":<{6KD=+10}X߬Rz n+Q ö!, 9dS"f&qoqR  *5=5lj}ɑNM,V*J\*5ͻOpsnФ@4b+r~ɘwu^oQO:&bLBv;JAPyȗj(((ÐmB@ %`#˶@g~LCpS4b;/@U%J^]ZkEhC׵ 媇b}WK(ZJx \dHDDDDG"I8TVJ{*YehX*qtM pl=$ihY(`p3u-!MHK&p!~xbm_Z~w {$~2I=JA@\ᗋwnWJ5oտ&qj2~#)v """#@:0$1n(oUIbakH-hmy ]v2.gLsUGWz b _\ATg_-gFadcB@XVe ϿZ?O-փ ns-˗g0;mG&u'DVJA|./lwmejHmh=^t]KBۆ>0T>\'=!3qTi>fe_Q,*,pwa _[ &G81B1I Ց)䏣@AJjf6p:>-bqp~^}v[o+"""":^(QGH6cqWVYT@Xke\Ş @ՇJgƱt|i(Cux ?@J*~"Frn/_PxBdGkv4E=>* %KE\t^_Fq|,bbr8x8Fc]QbHDk1D폽Pzm.Q4uT† [G!gjo@:jZqYß0kώ8=5DlV =R5anX/>'q1ԏ!pz*{ڳcHmQ[0P$5T1ǀIm@SvXd?z(gұ% 3b#a_ß~\T 7ci{68GKav"ll;B)4hRY귑B@փJUƽ-ܸqoa K%.J y@X;⻯#GLDDDD6 # TFj(@.M ۀ˾Yiw$ UL/] )s L<}x}JAO劇"9o rMGZ9bQ xDUb [* e ׋X^/a3_Ez8eh+Sx8fI8 ։(Q![Hd EWۨW{'@ugGL #H-\J @aPf[sͯDjG祰>ataOX ӑ(QGEz>І@ќB@[mnB8qA"tp,bbf<iOn_ǝM,Pϛ`F1Kd Fs1H)DDDDD]?lgX@FS>YOuD'RK|tu_ZŃ65 I!YD!xaWΏ%4M '"""" bIKn_&1r`T6u}NH) @L7qqyVOU\E·jl(ύgcIa1P$8FS~o>\2k(,?r0 R:;4MB) b83=8~)l+5p*| Q$&K.D.A*f!ZﱪINn&"""׿gD3ddXi]M CK"b#1ɑ$bi2ַX(cm V6%՚w$ՌBQl*l:L٤S\CRDDDD3얈zm"1e~,{R4V_W(gұUvzWƺe覡a8p6 bz%,QF[* e5oSu}x?P( E} 5ž&kF}¹kL !$l fbd0Lz=}*kQcbz$@rb@Pa#_Fk[*.*5RuaZ=D  DlQ@"f#I8H-躄 @+z𐈈zE" R 0?@"Md]M R8nkIJtń5DB,bbt0aШT㟝## )$ /hRc w@؞TMDDDDO(QWR`|(qqӻshlUԯ@@"#Td5R H@ ڮ`~ jc""":8%v +H!0#!|GEK˰)%Y A)ՌO ǯ2QO /p󸍨FD]AJd{!2u"&1XT(ᐉc9GMDDDt-&x]HE0k k:a#~N:&t])?) "hej< jDU)Cp2qɨh+! ]44*{"~&`19tO)  $%z(s-b8ݙGMP;Dam` zlJ"j"qY{#+a[Fwa:DDN@~DxQP&ڳDeDU CC*`z48ԑN6 ?~6uؖ@a!8ܙW(` "$cƇ4~"5*Q׉E "¶ar$ٖi%,Ceh=[1"DDB"6FP$jQ׉ 3!{DL- v/}J!1ыy[qF[~v_c0P"Q𷌈K "eGCa:Rq ɸ/0 XĀփtB bK8rqģfϮ!%wGD}O]I tzw%14c\V$"C=U(Dx*Q""ôzy/=L&18Q0P$53X.ؗ8dÆp}DDGMc[lNѱ@@C NW c rI:ޛ!@\]"=𬘈zcLƽ |y{%R`0D&3Fa:'2)lS&mؖRC#8R!†݆.a'|.&!zj"Q9L L''%`Gԭ(QO2\|b,XB2na `a|uhíd`&\SI #q4-Oռ_Q~Ls m<׾.\vnxv<ܽ?bc{lx|w=hnl>n~1Şe*ܱR+D"xB&a#7@ ӣIL$0/QcHD}K)|Tj~sRP?h +Kc-S0(V4bã@7<U|P5”GjGHvo$muj׸{os__8;wz!~'?v{<Ʈ{菹cۃ˞⾈]x<|n#_y[Ue}}e 0 2 1P$""""""""q""""""""""""""""""""""""""""""""""""""""""""ߎ4`(*@H aJI2`඿MSpd"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(d"@f(i]8]܅Ӷ+p^}n{:Y_^N.۞mv> ?m/.BIENDB`Sigima-1.1.1/doc/_static/Sigima-Title.svg000066400000000000000000000457311514013333200201340ustar00rootroot00000000000000 image/svg+xmlSigima Sigima-1.1.1/doc/_static/codra.png000066400000000000000000000053131514013333200167110ustar00rootroot00000000000000PNG  IHDR22?sRGBgAMA a pHYs.!.![ `IDAThCŚ p>3PK"*EKUb0NEԪÃ$"thk;tڱSSi)EB|@[[f:RSy( B@ @$owoo~߹g|=g t]qAt#sH{kF敀dJܽf UU35"ZBWKظs!]1ՇZDDZU=2ɑb%Q꣘٩PRɃ N FmDa+ ;D([[!}t.$N EfZ}r]+T4V! ]35E*׮;p$?$Fbq# C-Wkv#WT+ʗ"SӴ](H?!Ѹ:^fɯ8P  ##/"*֍@gڧN@JD+]2&.-i늯N.l,=(8 ّF݈-y pO{b"(l!IȚ,d,ZW7u"NN뚈 w]A3A-*7>SY:?*6!VZ:0fQxM X3'-qM-lq&QAT:邖wC*eY~ۮ*" !##5k}Q/,WPF4S>5F]m1?>nO(b-rwwFpfput+K0WrτDy$qÎhG$aS=Bӯֶw3B(ϭ'{r~Ef$߀$I|JtrQN w{EF!hY wBڎ{fc,aaＰ_"))܇I^6<;vSmvns^$wdj0Cf HͣeEFZPu hhY1f4^cnjݱyUE4 )+|]awTB }z*@Ew\I>JfL !⣺D%4fz)xFs3olԢu{UM7ztH/NS[BNncL79"a=qEUei'!}88!D̃; @%Iyi7;~m]j}UYӊ؁C&7R074/Bzgg/U}ߣ oPn !(!nZ$'ܾ*"m${/R-ʏC8RIYDحY@دkcst@B9pYcߒ""nMXr3-gL ҦjlTÙ79޵nG> B^6^ub g2v!)JѭYd5-0q˰3Ҡ;~ ]+m{i9hL6u(aTH`nQ xI{Di+ZppbpE201K\&A~+$DG Xԥ{3|ʏהpPUZz~$(A-źBvº(G>|ҧWp2W]0ycuʢnG>}8ߢQnD&~Ǜ?]WPP~@^ŹKk\WmG<kBOtV?)[5>;tot'(H$zMW܄W+Ysij9 h}FDS84diI_rE$zB8h<7w._$D>y /}(~Ƈ*CL1}[\@5>9mcMCu7$=W2SIK!#u`mX'vvv`1CS'oΜSNNu6uzɒx4^*33 .HBऌX2k*­mN'A׽fDN&N&N&N&N&N&N&N&N&N&ŹO%nM&qM(tM'wM&zN%|N&N%M&M'O'N&N%N&M%N&O&M%N'O%nK%)UN&O'M&N&O&N&N%M'M&zU+ I$P+0N'.O$*L)%M'!R$J+Q(M P0R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YͫlKN&N&N&N&N&N&N&N&N&N&ɽЗN%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&I$L$TN%O'M&N&O&N&N%M'N&O(GN''P(3N'.O$*L)%M'!R$J+Q(U"UUK-J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%Y׺]9N&N&N&N&N&N&N&N&N&N&ŷ͗N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&O&՘O$*M&N%O'M&N&O&N&N%M'N&O&~@@@ O%7P(3N'.O$*L)%M'!R$J+Q(U"I$N' M&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YȽP)N&N&N&N&N&N&N&N&N&N&پȗN%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'ҒI$M&5M&N%O'M&N&O&N&N%M'N&O&O(-P( O%7P(3N'.O$*L)%M'!R$J+Q(U"M3 U+P M&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YN&N&N&N&N&N&N&N&N&N&Y4ЭN%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'M'N'uM&N%O'M&N&O&N&N%M'N&O&N'\M&5O%7P(3N'.O$*L)%M'!R$J+Q(U"M3 UUF. P M&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%Y׼N&N&N&N&N&N&N&N&N&N&oO}N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&U+N&M&N%O'M&N&O&N&N%M'N&O&M&~UF. M&M'BM$FO&JN'NO&QN'UipuN&N&N&N&N&N&N&N&N&N&vnMN%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&L&6L"%N&M&N%O'M&N&O&N&N%M'N&O&M'M'!O,M&M'BM$FO&JN'NO&QN'Uɰ]8N&N&N&N&N&N&N&N&N&N&ӳO&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&O'TM%YN&M&N%O'M&N&O&N&N%M'N&O&M'P&CN'.M&M'BM$FO&JN'NO&Q_>[׼N&N&N&N&N&N&N&N&N&N&N&ܘO&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\M%N&M&N%O'M&N&O&N&N%M'N&O&M'M%`Q&M'BM$FO&JN'NO&QƺpPN&N&N&N&N&N&N&N&N&N&a=ЯO&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\N&N&M&N%O'M&N&O'N&N%M'N&O&M'M&zU+ P(@M&M'BM$FO&JN'NsS_ʽN&N&N&N&N&N&N&N&N&N&N&ÚoNO&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\N'N&N&M&N%O'M&N&N'\N&N%M'N&O&M'N&J L&P(@M&M'BM$FO&JN'NܽeBN&N&N&N&N&N&N&N&N&N&N&N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\O&DN&N&M&N%O'M&N&J+M'N%M'N&O&M'N&P#3Q%)P(@M&M'BM$FO&JҲȡN&N&N&N&N&N&N&N&N&N&N&oOΫN%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\N%hN&N&M&N%O'M&N%N&N%M'N&O&M'N&P&IP&6P(@M&M'BM$Fg^R+N&N&N&N&N&N&N&N&N&N&N&ؾY4N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\O'N&N&M&N%O'M&M$pM%`N%M'N&O&M'N&P%`M'BP(@M&M'BcBMa>N&N&N&N&N&N&N&N&N&N&N&dAµĖM'N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\N&N&N&M&N%O'M&N%RN%EN%M'N&O&M'N&N%uF. N%EP(@M&R/A|^N&N&N&N&N&N&N&N&N&N&N&N&ؾrTUL&JM%LN'NP&PN%RO'TM'VM%YO%ZN'\O&^L%aM'cN&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\I$N&ØN&N&M&N%O'M&L&6O$*N%M'N&O&M'N&O%{U"J+N%EP(@M&N%>O&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\N&N&O&N&N&N&N&M'VU+ N&ЗN&̗N&ǖN&ØN&N&M&M&5M'!O&M'N&O%{N'vN&rM%mU+ L&N%RN'NM&IN%EP(@M&N%>O&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\M&֗N&O&N&N&N&N&N%vO$*N&ЗN&̗N&ǖN&ØN&N&M&I$N' O&M'N&O%{N'vN&rM%mL&N''N%RN'NM&IN%EP(@M&N%>O&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\N&N&O&N&N&N&N&N%O(GN&ЗN&̗N&ǖN&ØN&N&N&33O&M'N&O%{N'vN&rM%mO$*P(3N%RN'NM&IN%EP(@M&N%>O&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\N%N&O&N&N&N&N&N&N&eN&ЗN&̗N&ǖN&ØN&N&M&N%oM'N&O%{N'vN&rM%mM)8Q$?N%RN'NM&IN%EP(@uS}`N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&hʽaM$+L&/P(3O%7O(:N%>N%>O&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\N&lN&O&N&N&N&N&N&N'N&ЗN&̗N&ǖN&ØN&N&O&N$\M'N&O%{N'vN&rM%mO(GN%KN%RN'NM&IN%E{YoON&N&N&N&N&N&N&N&N&N&N&N&N&N&Q)˧ƞ:N''M$+L&/P(3O%7O(:N%>N%>O&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\O(GN&O&N&N&N&N&N&G+M&N&ЗN&̗N&ǖN&ØN&N&M%mM&IM'N&O%{N'vN&rM%mL&WP'VN%RN'NM&IŚehEN&N&N&N&N&N&N&N&N&N&N&N&N&N&a>jG$N#$N''M$+L&/P(3O%7O(:N%>N%>O&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\K&"N&O&N&N&N&N&N&O(:N&ȗN&ЗN&̗N&ǖN&ØN&N&N%RM&5M'N&O%{N'vN&rM%mM(gK-O&WN%RN'NƝka>N&N&N&N&N&N&N&N&N&N&N&N&N&N&fXR$P( N#$N''M$+L&/P(3O%7O(:N%>N%>O&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\N&O&N&N&N&N&N&O'aR)N&՗N&ЗN&̗N&ǖN&ØN&N&P(3M"M'N&O%{N'vN&rM%mN'iG+K&"O&WN%Rhb\7N&N&N&N&N&N&N&N&N&N&N&N&N&Q)ϭ׵-J+R$P( N#$N''M$+L&/P(3O%7O(:N%>N%>O&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\M&ɗO&N&N&N&N&N&N'L$@N&՗N&ЗN&̗N&ǖN&ØN&N&U+U+N'N&O%{N'vN&rM%mN'iN#$M)2O&WjF[eBN&N&N&N&N&N&N&N&N&N&N&N&N&]9sMM&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>N%>O&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\M&O&N&N&N&N&N&M'M%gN&՗N&ЗN&̗N&ǖN&ØN&N&N&rN&O%{N'vN&rM%mN'iR&5M'BO&WsSN&N&N&N&N&N&N&N&N&N&N&N&N&pPLN' P M&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M(?Q(M&I$Q#N!J G)N'L&R$O#M+J)P( M'!K&"P$#N#$L)%Q(&N''M&(Q%)O$*M$+Q),O(-N'.L&/P%0N$1N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\M%mO&N&N&N&N&N&N'ڿ@@M%N&՗N&ЗN&̗N&ǖN&ØN&O'M(ZN&O%{N'vN&rM%mN'iP&IO'TwN&N&N&N&N&N&N&N&N&N&N&N&N&n'UUN' P M&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YM&]O%aN&eN'hN&lM'pM%tO&xN%|N&N'M&M'N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\N%>O&N&N&N&N&N&N&O(-M%N&՗N&ЗN&̗N&ǖN&ØN&N'iM'BN&O%{N'vN&rM%mN'iO&^I$}_nǺN&N&N&N&N&N&N&N&N&N&N&N&O(̩UUN' P M&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YM&]O%aN&eN'hN&lM'pM%tO&xN%|N&N'M&M'N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\F. O&N&N&N&N&N&N&N&sN&ٗN&՗N&ЗN&̗N&ǖN&ØN&M'BQ(&N&O%{N'vN&rM%mN'iO&dM$2]9N&N&N&N&N&N&N&N&N&N&N&O(UUN' P M&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YM&]O%aN&eN'hN&lM'pM%tO&xN%|N&N'M&M'N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\N'͗N&N&N&N&N&N&N'͘N&ٗN&՗N&ЗN&̗N&ǖN&ØN&R)U N&O%{N'vN&rM%mN'iO&dɡĚN&N&N&N&N&N&N&N&N&N&N&O'ԷgUUN' P M&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YM&]O%aN&eN'hN&lM'pM%tO&xN%|N&N'M&M'N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\N'N&N&N&N&N&N&N&ޘN&ٗN&՗N&ЗN&̗N&ǖN&×N&N&lO%{N'vN&rM%mN'iO&dQ)N&N&N&N&N&N&N&N&N&N&N&̨tUUN' P M&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YM&]O%aN&eN'hN&lM'pM%tO&xN%|N&N'M&M'N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\P&]N&N&N&N&N&N&N&ޘN&ٗN&՗N&ЗN&̗N&ǖN&ØN%M'OO%{N'vN&rM%mN'i—{N&N&N&N&N&N&N&N&N&N&N&mUUN' P M&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YM&]O%aN&eN'hN&lM'pM%tO&xN%|N&N'M&M'N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\N'N&N&N&N&N&N&N&ޘN&ٗN&՗N&ЗN&̗N&ǖN&ÙP&PO(-O%{N'vN&rM%mN'iR+N&N&N&N&N&N&N&N&N&N&hEUUN' P M&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YM&]O%aN&eN'hN&lM'pM%tO&xN%|N&N'M&M'N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\N%͘N&N&N&N&N&N&ޘN&ٗN&՗N&ЗN&̗N&ǖN&×L&M O&zN'vN&rM%meCrϭN&N&N&N&N&N&N&N&N&N&P)N' P M&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YM&]O%aN&eN'hN&lM'pM%tO&xN%|N&N'M&M'N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&L&WM&N&N&N&N&N&N&ޘN&ٗN&՗N&ЗN&̗N&ǖO&N$bN'vN&rM%mҳkJN&N&N&N&N&N&N&N&N&N&—KN' P M&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YM&]O%aN&eN'hN&lM'pM%tO&xN%|N&N'M&M'N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&L(@K(3N&N&N&N&N&N&ޘN&ٗN&՗N&ЗN&̗N&ǖN&fM$8N'vN&rM%mN&N&N&N&N&N&N&N&N&N&T-U+ P M&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YM&]O%aN&eN'hN&lM'pM%tO&xN%|N&N'M&M'N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&I$O&ŗN&N&N&N&N&ޘN&ٗN&՗N&ЗN&̘O'ƒI$M N(sN&rM%mӳN&N&N&N&N&N&N&N&N&N&~/I$P M&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YM&]O%aN&eN'hN&lM'pM%tO&xN%|N&N'M&M'N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'M%O%aN&N&N&N&N&ޘN&ٗN&՗N&ЗN&̘N'L(MN&r|^sN&N&N&N&N&N&N&N&N&N&U"M&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YM&]O%aN&eN'hN&lM'pM%tO&xN%|N&N'M&M'N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'P( N&N&N&N&N&ޘN&ٗN&՗N&ЗN&ęM"U+ O&jΪhEN&N&N&N&N&N&N&N&N&a>e@@Q(J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YM&]O%aN&eN'hN&lM'pM%tO&xN%|N&N'M&M'N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&O&L(MN#$N&N&N&N&ޘN&ٗN&՗N&ИO&WQ%)öQ*N&N&N&N&N&N&N&N&N&y@@M&R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YM&]O%aN&eN'hN&lM'pM%tO&xN%|N&N'M&M'N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N%͘N%>O(-N&ŗN&N&ޘN&ٗN&ΗM'VN&N&N&N&N&N&N&N&N&N&ӴM Q#R!N+$M&(K),P%0P#3P&6O#:N%>N#AN%EM&IM%LM'OM%SL&WN$[O&^O'aN&eN'iN&lP'pM%tM'wM(zM&~M'O&O'N&N%N&N%O&O%N&M%M&M&N&N&N&N&N&O&—O'ŗO&ɗN&—O&N'\M @@N'.N$[N%KI$N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N& N&N&N&N&N&N&N&N&N&N&FN&N&N&N&N&N&N&N&N&N&ɽǫN&N&N&N&N&N&N&N&N&N&ո>ڿN&Q*Ѱ\a>N&N&N&N&N&N&N&N&N&r(T.N&N&N&j?,hN&N&N&N&N&N&N&N&N&Y4vd@N&N&N&N&N&fCy˦N&N&N&N&N&N&N&N&N&N& qQN&N&N&N&N&N&N&S,ԶN&N&N&N&N&N&N&N&N&N&b`}`N&N&N&N&N&N&N&N&N&N&r8s^:N&N&N&N&N&N&N&N&N&N& qN&N&N&N&N&N&N&N&N&N&N&N&v—N&N&N&N&N&N&N&N&N&N&a=oN&N&N&N&N&N&N&N&N&N&N&N&_:N&N&N&N&N&N&N&N&N&N&N&qQ ,bN&N&N&N&N&N&N&N&N&N&N&N&Q) X}`N&N&N&N&N&N&N&N&N&N&N&e'msSN&N&N&N&N&N&N&N&N&N&N&N&N&ѱIN&N&N&N&N&N&N&N&N&N&N&N&uV~ PX2N&N&N&N&N&N&N&N&N&N&N&N&N&rYeN&N&N&N&N&N&N&N&N&N&N&N&Y4ֺG /bN&N&N&N&N&N&N&N&N&N&N&N&N&N&|^Y4N&N&N&N&N&N&N&N&N&N&N&N&N&kJոŹfO'N&N&N&N&N&N&N&N&N&N&N&N&N&N&rR 'پN&N&N&N&N&N&N&N&N&N&N&N&N&N&N&P)tUɣŸʾ̨hX2N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&jHquN&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&c@cN&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&mL$uVN&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&|^"mN&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&sʤO'N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&S,ѱ hFN&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&sTSʥT.N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&d@ֺ=ɣY4N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&dAֹ~.Ӵz\P)N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&X2t˿#׻}sTU/N&N&N&N&N&N&N&N&]8cɣʾyE˿*Bqc1???????~??? >?>>>>>??pppppp`     ????????(  ʿśirǢeȡbgEP)[6N&pP˫@̦PZ5tTдRǤmc@lJʿrlLȶƟoN&–uU+ N'uÞ"ҵ>N!@ M N''|qO'y[P&N'O$TN'AN%O(:N'.U3M&M&5hN&z]O&N&ΗN&M&dM'pM'OUUN'.I$M&r{\7sU٬uS%M$2N&ΗM&P%0L"%M%K&=M&dG+Q(&F. —}]8gFѲ8Q(N&ΗM&M%mM%tN%U"N&rM'!jG${T-qRϲ5Q(N&ΗM&L&CN'M%M&dmGDgO(iuYHQ(N&ΗM&J+M&ݗN%N'NfO(ę]:M&5L$MO&jM(O%N&ΗM&N&M&PQ/&qPz]U"M&5M%SN&rM'O&N&ΗM& gDdҳ9Ǥmy[ʥfEҶ?ԴGmKڦhE*˧Nb=X3qQV0b?ȟXб1o}_nӱ.8(0 O5Է|sΩmMU/_:fͨ ɣQ)N&R+fDT.N&N&q)ɣO'U/Û]%˿XǟZ5N&|ոsV0S,ϮҲQ*Q*ԸvѰV/Ě fݗN&}K),M'pmIټr9` R)M&P$#L&/q˗N&lٗM%`N&lN&yN&rQ(O'N&M'BN+$P$#@ N' L)%O(:T-OhN&kܗN&N&M&ɗN&ݗM'F. O'M'N'bM)2M'!M3 D3L)%O(:ǟU/N&wȗN&N&M&ɗN&ݘN&O(-N&N'bM'wUO(:Q#F. D3L)%ÙspNN&|^繆o7M$+N%EM&ɗN&ݘN&O$MO&M$2N'` U"N';F. F. D3ʤjvUN&c>׻eO#M&ɗN&ݘN&L)%N&U+ O%nN'I$N'N'R$N';M3 ѱiHN&^:ԴO#M&ɗN&ݘN&O(-N&N'.O&N&yO&~M$+O$*N'4Ϯ[6N&mMչmO#M&ɗN&ݘN&I$N%M%SN%N'[M&jQ&N'UN'N}^ZqЗN&Q*ØĽxBQ(9O#M&ɗN&ݘN&N&M&ɗN&˗P( L(@O'a{˗N&[6Ѳk^L)%O(:O&DM'VM(gO&xM'N&M&ɗN&ݘN&O&xN&M%@@N+$o_;O'ЮI7L)%O(:N'NM'cM'wO'N&N&M&ɗN&ݖN&O#N&ŖN&fU}N&sSI$N+$O(:N'NM'cM'wO'N&N&M&ɗN&ЗO(GƝN&mǽh̫N&pP&׾fb@t56hDN&w5 ԵhFN&}`)аQ*N&gDj޲|^O(N&uV´GѲqQN&N&N&Y4{4!Ӵ{ˤΫ˾S?>0p???PNG  IHDR\rfKIDATxw|]`o=EP@'(" 7*)Ɓ ^2 -M5!&\~x{<ܥBJMDtlll"-66U[ll0H7& F@=.P-~/ p2> = -U^@7hуa/J r Pii.(>?B` #}ClE+jRKyu?ddp #"7"9U$&*Ԫ@ډԩ@ډ4k/- # j\\Jfզܸ;3ض0YAs/oРv"/=:pgX vF}["˹,  7ot!'ȍp^en_E1]ewCե1o>|Փol4AU&s+"Ҡ(kx9L; ;<[ nԅ[/=jd:17F#P\ɗE$`i>77^i!XA]` ~7>-Vˉ{vnwQ!$+F0 pn3->c LyqMxVbKMm=obdTn~;OrqPJNa8ɬ =P1tN}㧿3?I okި:S_׋p*pUPRR2vL.k1Bg!0ܞ_k9 n kc8 Uh *mZ~Z߼Qu~ioQ"=홎`YRx}=,篕yžE` TY@HXX 0t5oT/DaEaYPUyE#}C…-3ebWϩ|"}G$&i۬VP Ri[boF xj%b=^.xOzRl׆rb:""}#…-s:ᾖʻ4 X Pf5&>׆?(n>^&a(6eh غ+\gOpE}_BT Hh٤X5JMqξQ0k+  8zy^a_+OIwwWm>1vW wl k:9N`qr"y6U86-qźw9W ߧيۇu UUxHgÀ{1b @pxsRmPgpJ/6Bo2[N9\4# ^غp+?ĆX鋍 QWW8\1ѩogTLiK<hFP6mBZxaWe8gJbbwc3Pd.uaJ` yj,oTO?+).tMZ<7wEZ`LTߨ?0D#;>O4kTbkY SشߙytnS\k1 9pʦ@Z Qo v9= Rַ=bEю=0ZatT2H_lяTEpŅ};& -P q%gyf멤HL* t+ kUbE[%#z_Nَyb=/ 'LcFrtB6b y\GR.$TE{ `QWPBBoc-f,y%|T꘭Ʀ,24ݤ"1PDTBfHT}?r̘ >H?ع7zllRn{RyT(BRR:RCVGk^jb E(Žf %BѼqɉ 8g|V5UWtS "]H%ơ +Bפ"588!TTRTRTPcT[QTB (!'EHEET*T@R*!qKUE u ! QTP)B*G"_HT@ ! "A12:E BH QBp}("ThmP2CfP9ⴅkޑojUnS[[Rr#&ԥۭ $HtA čsM2Gc'slޙ8~yp;2B LrI9tU**W+ŝܧK͡TRq(uE"sOUHUKE(x+)󞧣Jo'yOw4VI|M0XRh|]|(Dri8g8ѿҦ8!NGbwzKh{B-KL/k|>F2RK(l鶝*)9S)})$ OSk:j]b)GR9t]}v[džW^.-FSǭ#'8s5{_ys80$?xCh|M b؈a:-1O̕h6|‘<3#1|ZilH:+-lwl)f&Dr-9 6y͗aLb=*T(Bl셿ʎvƒ-b4E\le5s7#V)痥g94lY>w,Y 2ʇMUU=|evGJk=z_sr-7n?߳%{0Ͽ[{$B^׶*HY:0hP Ƒ >rb,w[Wz^_z^{)laWKٙunzd @A]($\v䥻Z_}v\^&*pyhrbx{x륋5]lA ~5`r wxja$ɰLP 65:)\<`BM{qsm3q(8emsidfz:bll&5qfX8:_Ȁ7?5\Dj$2ڗs祟p1<cS90-.}6 SK&ǜJ޴7ܹ/k ABnd3?k¤EETxL V{I,:Rшn*kx^_{q'K"ٷkj:ߢkЦ`Z"̯ LE"j;>rbE}35Y T-QWZy Ð&bɳ)k^+3Uc4 !8stYn~i׼EGKwzTEV+?r!D f,%pGKwt}=o ;2~M[ϰ|t}'MӁ_6Sw:Jab[n +H]fH.ۿMu<qY}7 6USi{Vly{LVѲEaN$VGCEv_nyk-gXj!7[}fb'9 S 1AHVԹAo~ФdvE?$tG\:#o']jv EX[< T\L.tI¡_HS&,?PtW͍͒YRǕ_֞]ME}Nm'͟ʧ ` .B @1e'y!Mf-u15anUMRJT[vlW*B Y[motaj _M8ȩ49s7=쭩?{vVXft7_ƪo^rrd6mMIAS+ z@QtM8 qir\}עheŏ{ !wi`n9 ;bb:bb(a]䛩N"=F7Pp.>/g/p o=r{`&}Gk&fֵ\?},mN@ cHL}7>:QH0[@A .Wzx)t_=zs9ε"x\rvP^߬ݒΥO($>-Mx HQR)uG ij!PHe갥ѧXKPiEޮ6:3`%/w.CFZ7+俽UE8k?xi6´ĻR;l6[r,8ΔƵ͙FYZ̓ }_vf<~p20Fͨ+My[ᬕ\7)"iVMeٻ@y$2cIPӭWwMYb`sO_ uEwFreYc }`/-Kh܃~¿wic ~  dB(Bbڰ>R-W۔ѻe)x BF>3q%PUf7DQ6!oh}重1|bq8%}@8M*erp̹P'_pW/oٕ^-DR,.zrϱu)@Hת;z)@ei0 +6{ zvnW.U!@Y~VbJ;'.]g1*(sOa^!j58ZHn07(z߭k Ϛi硻Bf 3%3ۘ?]ٰ;Laki;CZunMh#\+ubr 8 S_BF3ץd´ቹSѩ>fLƵl~ >k}ֽ4eiob:uOc&Zxp%PТq |)nG K֦1i% $OF]-Idmƿ)ӥ^fV"k"o1E~%K**m? FIq|8bS㑑Ueűcw^yADgS*~ VpEӿOH7zP7$@~8yдM=`l;b.2nOU 7{W>ؠVRLgs ~.Og "Y5צ80g&_kjL^*N |/;=S^BYj7ʢUG@5mX}w\>ᒳD<_c6 cGu̯1|^K1 O!r>Y|b-0աӗ epyL8)!CםvbDg)̎:92 PvR1DQ4?nFH>< \d.yPxhΫm''Sq(o_ !֡]Ĥe۲\ 6…@ֱ=m"@b5S^(0`:}H#E3?tU37fb LvRcf6Ev#-a翷 #ڸ*J/"9f.}AqM~4 V F\MRul@$ \?ޭBt``:봍9 @> ir@/6 &Jo&qŘ]8/nw^l23xsI39H X 11l„ku8ٝ| !D17Q{gZcj\V>)W4|`|ot'W= iށT0 3 B?Pgu^@if< hd:[rIz_R ;^$F(c^ycs//rxC:|u(}N5"6`C3YHN_n94;p~ o(u TA(oє[)rfYzkƏr؄8%) 13"Z|03wp[?SG+U5o Ut{yN,25HPcݯ{z E7Ĥ.VHWY+}/~Lk)2@dxrtS)Ԁ́4,p>]QM " +F+=ž3!hJRy߽QvG)2 %[4"K#e# #-3>e." !i@yC'N,F׃Ѯl@ؙ#`1zB "5M)1۴0s;<& nض?F1(܀[L'K#wCUxyE4\\2&M0D5R@@ Rgl挀dmzVM; _\[wZs"ʜ3o;rr1|Zjt) E h &BJg6HS! Bm.D(sk:2-B 諏K.yg$%^p-iѸw<=L͂"MO}'ӣS#8"Lyȩ4`wB 5v#Zƣ9΀= =Q~tY9LbE^j2GqⰧ\2ah[~pO4=|Y] ^68=/vĕxxRJX}ɹv#E:)@j\ 9 z?7ҫEx?ޏ}ۇ)r7OZ[pYRAJHބ\0G@ %o qå eg |GD~={ ]&wWon%m۵ePc J D1; H(NfR*B SB\2=DNˏXܜy蹷d-6 ؋{:5myjŸܸs $!j@# yqwaœTP\Sfz~#WQ+ϿயF??Svx^amGK%x5&ZZ9|/JQ+En4bc"Z @FV/ٓ;Sv.匰Z ~@4MDhpPQ/e(AUGH(nbرbݚ./we})xsP¨K֦1Cg=6*&j@T07L $fŨ!Y55+u ƎU45ۭ F~ƶݙ{ʆ_Ёg<'#7Xʆ}:`B/q4g;Q_/' O'-M;83$RD,3"_")mS!8H|lAWnJx{uiW>8{,GI;=3sV=)r!ق ;AR!o>`쑷 u*y0;t-9cI:b  IQ|d^_%Lwrټ;TT(R(F(v"P$(HH"PDB(!(BHEJߓRߨhD-[~5^VNN\WФY{rږ\8*Q#^P#7zcn= x> ̕㛇t9;"DgTM D R/1(tTҘÆOyVJ#'Zp퀓,?߮`qMj8oG10Q/۵-7ݚBJcިEn'o9D`*`.&.[mCL5i(w#f Vnyz=8TK͔`-/篣HСE]׫N^7>;V\ckDx;+/@+ (spiR|n[ $kwr}`9kH߇pP_+Չ6iQ X5@J!t)՚=[XzOZֹqj l?<B7]]hɥy('45+X%A<7atSEJuuw& >U !.)L ?|QsRwv&$H(̼s֬WZ>7MlUe*l;2լ٬@i.PZ.@Qs`7("SލN^[{4WH&5,;m hߢN]}*H)%Rgz0`r" F7lۓ;h]`<'-3ЩPDD`J:4,7GHrS/Rt'@8n2#6g=Nj<*A,E(xSm5VdٓjS|ˬ hn4hע qT #̹E-vւJ;0cƄ^˟,FNkN&d:YɰuĝzJ=a#MG !Eyw&p%׹ X~F/n~#ܴxER. ?Q*%a{J6Iߕ)yVk6߮z`Z}#>ծt#QpB TKu.MwC6Âc(",Ӏ%:Rs^ejTk4\O((7V6kɔZ!JxfqɐF>u릗|'kyעn?CB|L-T*;#mW(X[UT6BfdI,Ї+i֗e` 7]3u9{3Tn=WFsIF#R*k|+|@k u\T6R o&njx ;#p@8:[d~A'Ԫ!R} *h JlD@X: ~ ԧ}8wuE-y#xt`y#z5%GCdɆw0mp;I)7_q"wc=3#.֒cYl9-G(X%ݻ8ۥ5vMV$.p`\պYeE`Y7LX8 6kcI yg#vԪ_I@lj}C8’!6)k:dkGlkkqV &anvC '[bR 9THXHP+asH_p;2ESm1HrED8T[}`†#^0YR"}]S+PPxݟکcFd:#uOPبOs\$?4?xoWX2-ouvG8B$c "}%&X yD*|WT+҆*BBQBl%fߔzH iN?X6gD>f+; \nuE}yD/SV uM;RA~l=Rv7IbX*[pi*2h[]!y[?Ta~?nq}J  WtMsn{˟ZŹ9d\g! )/@QK^yES81q:̴1cSGdmJO:uVáx{}+$cqEh7-`T7;획sFFmL:Lk6`+Em$7F>N}n p/$pj%#l6ϻ:]S es$ndYb4 cQ䐊.c*q HAs *R$ Z"A"Cn]$$EB!upJ!HRs =FRw ViWa5Mذ@&$R"B u]"Ѕ0z.t)5!uDH)@.B(*])uTD`2E(R76A s\ i29mtjnChR#хT@ץb+NL:uـoc<inkoN@7٦5_6qn!t1Ks&t%F.kjI]s: rRhg*0 ft]wM|J59L)ܢ ?:uX9 &IoO/yHƮƛ OÐsӘHNOmbVN.A)]EM3gTƔ ,O$tRI;?T/ݻOkB{#=8koRirx~"~\|$Zeg]4|l3u#pSs;bd&aƸA+R)W|Xb>`(h{/(lR,oV޴KnCТ-H_D%:OC~cҵÕu#LXѫ8rSy%t~]Jƾ Tr 6&~Jz%"l(!ė{ 0ؙV w7Fþߡtϋu[>JvD?Aݚo|ʔ*ZH;̜߬K־s"}#x,bAi:2";򂫵-u*-G9`<)n*9T 9"gTO1|8X țb5?<ޥG6F*-ec={AǖuEnn= zC 5uh'PcR(nBן[2eP>`z8[tKc ?0d'7O&spy9U]>HߌH` O5yF|<:[#}CBRE3S~>C{8oUl8HU:VTJx%lԼZgsdCY\aoQ^b}!`ܨ޴ilѳI;).FWS-pp wsյ)Cz4Ug ;3P``D > `gZ=8GiP;S2poN$ p)ҝ9{|K ; =I[aF<&gvF3]ٸ{k붆/ަcqn枢l0G/pQZSj%gpǤ؄ LKvZʗׇ˻qUz3hQ-xźG 6t;Ic#21>pp#{K4W߯+8N'Zrގc @p| Ɯ(+gN)}d3-(w= U5dfGfݴA 3_JJRcyu19٬\\sq'zt:nJ{7Þ`[T | #v-]ߓZ|\6Vln-?-ގ;Dٹ1 9hk>G^}6!$Ñ~L?|7MbB nõw*-BpEX-M ֻ8jD钥kӘV~ZCYnk8T^]3w[lAB191FGP1HĈ9PM,YƯKvxʈâܘ5'Wvatz#-1sY,]%kXS3(( mAtnS.ӣS#ڷ7FDO2*-xlÀK8v{68]ޟ|2>$;HGIԯHIlRk愚H/:Â+E>b @ #6y^ SK&/ttEKbT=5G`v*l98C Nˆo5sΒ5Tю-Ubh\a1ĕxů0<#/M+I$@ @+ M"ȡTÖN&N&V/öN''O'ƗN&ՖN&N%M&5O&M'cN$1N&M&<R)N%>N,M3 @ @+ ոhvN&N&Q)շN''O'ƗN&ՖN&N%I$N%N&M'VO&N'HJ+N&Q'OQ(&N%>P0U+@ ƺyZN&N&T.ӶN''O'ƗN&ՖN&N%M&N&O&xO&K#,N'N$bP(3N%>U ߿fCN&N&a=µN''O'ƗN&ՖN&N%N&ėN&P N&O&KN'oN&rN'AN%>ոV/N&N&tUҲN''O'ƗN&ՖN&N%N&N&N'4N&O&M%YO%tK-O(MǞděחO'N&N&wҰwN';N''O'ƗN&ՖN&N%O&qN&O%gN&ΗN%P&CO%tN'.prxݗN&N&T-ΫʧCO(-N';N''O'ƗN&ՖN&N%O(GN&O%N&ΗO&qN'.O%teAVƟߗN&N&eC³M"O(-M&ʾ؝X2N&N&N&N&fCۺuYN';N&ėN&ΗN&ؗN&N&L'a@ N&N'N'N%N&ŘN'@@N$UN'}O&qN' J!O$MN'A~ΫO(N&N&N&N&jʻfHN';N&ėN&ΗN&ؗN&N&L'aN&N'N'N&N&ŘO&M'BN'}O&qR$M$+O$MȺwN&N&N&N&P)ЭÈM$+M&5N%>N';N&ėN&ΗN&ؗN&N&L'aO'N'N&R)N&їN&ŘN'K#,N'}O&qL&/M&N';N&ėN&ΗN&ؗN&N&L'aM&N'N&N&sN&їN&ŘO&^KN'}O&qL&CȝxȣN&N&N&N&vWӾκQ#P( M$+M&5M$?L&6K&=N%EM%LO$TN$[N'bM&jL&rN&yP&O'N&ėN&ΗN&ؗN&N&L'aO'TN'N&N&ǗN&їN&ŗN';N(sO&qU/]ɽP)N&N&N&iەU Q#P( M$+M&5M$?M&IM%SO&^N%hN&rN%|N&M'M&M'O&O'N&ėN&ΗN&ؗN&N&L'aO#N'N&N&ݗN&јN&ęM&N&XO&qͬ~aN&N&N&qQסU Q#P( M$+M&5M$?M&IM%SO&^N%hN&rN%|N&M'M&M'O&O'N&ėN&ΗN&ؗN&N&L'aN'ėN&N&ݗN&їM&N$1O&qŸڗO'N&N&P)` Q#P( M$+M&5M$?M&IM%SO&^N%hN&rN%|N&M'M&M'O&O'N&ėN&ΗN&ؗN&N&M%SM'pN&N&ݗN&ѕL&WM X4qնN&N&N&pI@@Q#P( M$+M&5M$?M&IM%SO&^N%hN&rN%|N&M'M&M'O&O'N&ėN&ΗN&ؗN&N%ڟP U M'N&ݗO&f3̬P~N&N&N&U R$M$+M&5M$?M&IM%SO&^N%hN&rN%|N&M'M&M'O&O'N&ėN&ΗN&ҘM&P%0N!=lN&N&N& 9nN&N&N&~9ǡN&N&N&QɤP)ϭ{ö֗N&N&N&xZq/پߗN&N&N&eٳүU/N&N&N&ֺ9E´ޙQ*N&N&N&nN֜-ɣN&N&N&P)ѱڐ6ѳǠO'N&N&N&\7קdAN&N&N&N&fDͪĵǺؽ}T.N&N&N&N&W1 ̟[6N&N&N&N&N&N&N&N&N&N&N&N&N&\7ȪnMN&N&N&N&N&N&N&N&N&N&N&xZڏ׻ޤeBN&N&N&N&N&N&N&lLۀڋ׻ɣě˦ڿ| "??aa!!?!!100pppxx?(@ @KKEcͪvWT.N&N&N&N&N&N&eB}/}aO'N&N&N&N&N&N&N&N&N&N&N&N&hFʾѿzO'N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&|^34mKN&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&]8J,\7N&N&N&N&N&N&N&Y4f}ǞuqQQ*N&N&N&N&N&N&N&U/2_;N&N&N&N&N&N&z]}SJ`ǺoON&N&N&N&N&N&]8ӦhEN&N&N&N&N&Z4ȼ*W1N&N&N&N&N&jH螼tN&N&N&N&N&fC?Ia=N&N&N&N&N&ǡpD¶N&N&N&N&N&fD"*V0N&N&N&N&R+۞Z5N&N&N&N&Z5!JN&N&N&N&N&ǠX|N&N&N&N&O'9俦hFN&N&N&N&^:ṇkN&N&N&N&ě9ԶN&N&N&N&N& fDN&a=N&N&N&N&N&ʼ@ M'BM%`R$)Ϯ5@@K-G+UЙQ*N&N&N&N&Ю8M&N&N%M'N''^Q%)M&(J)U$]. N'N#$O$*N$1O*7N)>N%EN%Kԟ\7N&N&N&N&ǠÙO&M&N(O&M&M&O&M&M&O'N'.O(:M&N&N%N&N'vN'N$1M&(J)Q#U N' N'K&"Q%)N$1L$9P(@N'HM&PO&WS,N&N&N&N&̩oN&N%N'N&N&N&—N&ʗN&ҘN&ٗN'M&N'AN&yM&N&N%N&M'U+O(-N$1M&(J)Q#N' @@U+N'K&"Q%)N$1L$9P(@N'HM&PO&WN&N&N&N&N&ոvYN&N%N'N&N&N&—N&ʗN&ҘN&ٗN'N&N&I$M&M&N&N%N&M'O&D@ O(:N$1M&(J)Q#N' U+U+N'K&"Q%)N$1L$9P(@N'HM&PvsN&N&N&N&N&T.N&N%N'N&N&N&—N&ʗN&ҘN&ٗN'N&N&M'!P&6N%M&N&N%N&M'O$jL&O(:N$1M&(J)Q#N' UUUI$U+N'K&"Q%)N$1L$9P(@N'HM&PȬrRN&N&N&N&S,N&N&N%N'N&N&N&—N&ʗN&ҘN&ٗN'N&N&N'.O&^N%M&N&M&N&M'N&@@K%)O(:N$1M&(I.Q#N' @@I$U+N'K&"Q%)N$1L$9P(@N'H}nN&N&N&N&N&mӴŘN&N&N%N'N&N&N&—N&ʗN&ҘN&ٗN'N&N&N'.N'N%M&N'N$UN&M'N%R)L&6O(:N$1N#$Q(Q#N' @@I$U+N'K&"Q%)N$1L$9P(@dDOd@N&N&N&N&N&fBN&N&N%N'N&N&N&—N&ʗN&ҘN&ٗN'N&N&N'.N&N%M&N'P%0N&M'N%N$1K'AO(:N$1I$N' Q#N' @@I$U+N'K&"Q%)N$1L$9T,@ǶeN&N&N&N&N&sSϗO%gM%mN&rO&xN'}N'M'N&—N&ʗN&ҘN&ٗN'N&N&N'.U"N&N%M&N'iKN&M'N%M&IU"L&CO(:N$1M&I$Q#N' @@I$U+N'K&"Q%)N$1L$9ͳȢN&N&N&N&N&N&M&PN&—N&ʗN&ҘN&ٗN'N&N&N'.L&/N&N%M&N%KM&M'N%N'\L&L&CO(:N$1N' Q#N' @@I$U+N'K&"Q%)N$1ϯ̧N&N&N&N&N&N&–~M&PN&—N&ʗN&ҘN&ٗN'N&N&N'.M%LN&N%M&P(3N&sM'N%M%mQ(&L&CO(:N$1I$M&N' @@I$U+N'K&"Y/+ԱͪN&N&N&N&N&N&mLM&PN&—N&ʗN&ҘN&ٗN'N&N&N'.N%hN&N%M&L&O&^M'N%N&yU+N$1L&CO(:N$1KN' @@I$U+N'pQ)ęN&N&N&N&N&N&]9M&PN&—N&ʗN&ҘN&ٗN'N&N&N'.O'N&N%N&U+L&JM'N%N&yI$N';L&CO(:K#,I$N' @@I$U+Ɵ-ַhN&N&N&N&N&N&Z40M&PN&—N&ʗN&ҘN&ٗN'N&N&N'.N' M'cN'N'O&WN&N&N%M&N'4M'N%N&yN+$M$FL&CO(:L"%F N' @@I$EqQN&N&N&N&N&N&Y48M&PN&—N&ʗN&ҘN&ٗN'N&N&N'.U+N&N&M&N%N&N&N%M%P( M'N%N&yN'4f3M%LL&CO(:M"@ N' @@r[6N&N&N&N&N&N&a><M&PN&—N&ʗN&ҘN&ٗN'N&N&N'.N&N&M&O&P N&ʗN&N%M&jF. M'N%N&yO&DK-M%LL&CO(:J @@sҲP)N&N&N&N&N&N&mK'M&PN&—N&ʗN&ҘN&ٗN'N&N&N'.N'͗N&M&N&O(-N&ʗN&N%N%RM'N%N&yM(SO#M%LL&CO(:KԺoN&N&N&N&N&N&N&iM&PN&—N&ʗN&ҘN&ٗN'N&N&N'.N&N&M&N&f3O&JN&ʗN&N%L$9M'nN%N&yM'cK%)M%LL&CO(:M 4ߪmLN&N&N&N&N&N&O'˥ M&PN&—N&ʗN&ҘN&ٗN'N&N&N'.N&N&M&N&K&"N$iN&ʗN&N%P( N'[N%N&yN'o@@M&5M%LL&CO(:UmZ4N&N&N&N&N&N&\7˽N)>M&PN&—N&ʗN&ҘN&ٗN'N&N&N'.M'cN&M&N&M'BN&N&ʗN&N%U O(GN%N&yM'pKN'AM%LL&Cb:9ҳP)N&N&N&N&N&N&wYӵ]L$9N)>M&PN&—N&ʗN&ҘN&ٗN'N&N&N'.P(@N&M&N&N'bM&N&ʗN&N%N'4N%N&yM'pJ)M(LM%LdEJϽtN&N&N&N&N&N&O'ȣɵk7N$1L$9N)>M&PN&—N&ʗN&ҘN&ٗN'N&N&N'.L&N&M&N&M&M&ĖN&ʗN&N&P( N%N&yM'pJ%0U+N'UgCT۵dN&N&N&N&N&N&[6׌P,#Q%)N$1L$9N)>M&PN&—N&ʗN&ҘN&ٗN'N&N&N'.N&M&N&N&I$M%ӖN&ʗN&O&k@ O&N&yM'pL&CJ+W1Xֲ{^N&N&N&N&N&N&tVHN'K&"Q%)N$1L$9N)>M&PN&—N&ʗN&ҘN&ٗN'N&N&N'.N&M&N&N&ݘO&JM%ӖN&ʗN&O$GM$pN&yM'pK&XO$*˿}N&N&N&N&N&N&yU+N'K&"Q%)N$1L$9Q(?P%0M&5O(:M$?O&DP&IM'OM(SM%YO&^M'cN%hM%mN&rO'wN'N&—N&ʗN&ҘN&ٗN'N&N&N'.N%M&N&N&M'M%ӖN&ʗN&P$#P'VN&yM'pM%gÜbN&N&N&N&N&N&ҳI$U+N'K&"Q%)N$1L$9P(@N'HM&PO&WN&_N&fO%nN'vN'}O&N&N&N&N%N'N&N&N&—N&ʗN&ҘN&ٗN'N&N&N'.M'VM&N&N&N&ٗM%ӖN&ʗM&@@Q&ǻN&N&N&N&N&N&S,|پy[N&N&N&N&N&N&N&n˜N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&h蹿zN&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&˜շU/N&N&N&N&N&N&N&N&N&N&N&N&N&N&Y4ŸX⼎uQ)N&N&N&N&N&N&N&N&N&N&T-ƝA }Դz\X3N&N&N&N&^:f³i8+?????s???~   ? ?????Sigima-1.1.1/doc/_static/pypi.svg000066400000000000000000001530021514013333200166140ustar00rootroot00000000000000Sigima-1.1.1/doc/api/000077500000000000000000000000001514013333200142345ustar00rootroot00000000000000Sigima-1.1.1/doc/api/client.rst000066400000000000000000000000571514013333200162460ustar00rootroot00000000000000.. automodule:: sigima.client :no-members: Sigima-1.1.1/doc/api/config.rst000066400000000000000000000000571514013333200162350ustar00rootroot00000000000000.. automodule:: sigima.config :no-members: Sigima-1.1.1/doc/api/index.rst000066400000000000000000000040471514013333200161020ustar00rootroot00000000000000.. _api: API === The public Application Programming Interface (API) of Sigima offers a set of functions that can be used to access the DataLab computational backend. This API is designed to be simple and effective, allowing users to perform signal and image processing tasks with ease. .. list-table:: :header-rows: 1 :align: left * - Submodule - Purpose * - :mod:`sigima.tools` - Algorithms for data analysis (operating on NumPy arrays) which purpose is to fill in the gaps of common scientific libraries (NumPy, SciPy, scikit-image, etc.), offering consistent tools for computation functions (see :mod:`sigima.proc`) * - :mod:`sigima.params` - Sets of parameters for configuring computation functions (these parameters are instances of :class:`guidata.dataset.DataSet` objects) * - :mod:`sigima.objects` - Object model for signals and images (:class:`sigima.objects.SignalObj` and :class:`sigima.objects.ImageObj`), scalar results (:class:`sigima.objects.GeometryResult` and :class:`sigima.objects.TableResult`), and related functions * - :mod:`sigima.proc` - Computation functions, which operate on signal and image objects (:class:`sigima.objects.SignalObj` or :class:`sigima.objects.ImageObj`) and return signal or image objects, or scalar results (:class:`sigima.objects.GeometryResult` or :class:`sigima.objects.TableResult`). * - :mod:`sigima.config` - Configuration management for the Sigima library, including options for data paths, translations, and other settings. * - :mod:`sigima.client` - Client interface for connecting to DataLab application through XML-RPC protocol, providing remote control capabilities for signal and image processing workflows. * - :mod:`sigima.viz` - Visualization tools for interactive display of signal and image objects, supporting PlotPy and Matplotlib backends for testing, debugging, and Jupyter notebook analysis. .. toctree:: :maxdepth: 2 :caption: Public features: tools params objects proc config client viz Sigima-1.1.1/doc/api/objects.rst000066400000000000000000000000601514013333200164130ustar00rootroot00000000000000.. automodule:: sigima.objects :no-members: Sigima-1.1.1/doc/api/params.rst000066400000000000000000000000571514013333200162530ustar00rootroot00000000000000.. automodule:: sigima.params :no-members: Sigima-1.1.1/doc/api/proc.rst000066400000000000000000000000551514013333200157310ustar00rootroot00000000000000.. automodule:: sigima.proc :no-members: Sigima-1.1.1/doc/api/tools.rst000066400000000000000000000000351514013333200161240ustar00rootroot00000000000000.. automodule:: sigima.tools Sigima-1.1.1/doc/api/viz.rst000066400000000000000000000075441514013333200156100ustar00rootroot00000000000000.. _api_viz: :mod:`sigima.viz` --- Visualization Tools ========================================= .. module:: sigima.viz This module provides visualization utilities for Sigima objects, useful for: - Interactive testing and debugging - Data analysis in Jupyter notebooks - Quick visual inspection of processing results Backend Selection ----------------- The module automatically selects between **PlotPy** and **Matplotlib** backends based on availability and configuration settings. The backend selection follows this priority: 1. Environment variable ``SIGIMA_VIZ_BACKEND`` (if set) 2. Configuration option :attr:`sigima.config.options.viz_backend` 3. Auto-detection (PlotPy preferred, Matplotlib as fallback) Backend selection logic: - ``"auto"``: Try PlotPy first, fall back to Matplotlib - ``"plotpy"``: Use PlotPy (raise :class:`ImportError` if not available) - ``"matplotlib"``: Use Matplotlib (raise :class:`ImportError` if not available) .. rubric:: Configuring the Backend Using environment variable: .. code-block:: python import os os.environ["SIGIMA_VIZ_BACKEND"] = "matplotlib" # Before importing sigima.viz from sigima import viz # Now uses Matplotlib backend Using configuration option: .. code-block:: python from sigima.config import options options.viz_backend.set("plotpy") from sigima import viz # Now uses PlotPy backend Module Attributes ----------------- .. py:data:: BACKEND_NAME :type: str Name of the currently selected backend: ``"plotpy"`` or ``"matplotlib"``. .. py:data:: BACKEND_SOURCE :type: str How the backend was selected: ``"env"``, ``"config"``, or ``"auto"``. Quick Start ----------- .. code-block:: python from sigima import viz import sigima.proc.signal as sips from sigima.tests.data import get_test_signal # Load a test signal signal = get_test_signal("paracetamol.txt") # Apply some processing filtered = sips.moving_average(signal, n=10) # View the results viz.view_curves([signal, filtered], title="Signal Processing") Viewing Functions ----------------- These functions display Sigima objects (:class:`~sigima.objects.SignalObj` and :class:`~sigima.objects.ImageObj`) in interactive dialogs or plots. .. autofunction:: view_curves .. autofunction:: view_images .. autofunction:: view_images_side_by_side .. autofunction:: view_curves_and_images Low-Level Viewing Functions --------------------------- These functions display plot items (curves, images) rather than Sigima objects. .. autofunction:: view_curve_items .. autofunction:: view_image_items Creation Functions ------------------ These functions create plot items that can be passed to the low-level viewing functions. Curve and Image Items ~~~~~~~~~~~~~~~~~~~~~ .. autofunction:: create_curve .. autofunction:: create_image Annotation Items ~~~~~~~~~~~~~~~~ .. autofunction:: create_contour_shapes .. autofunction:: create_circle .. autofunction:: create_segment .. autofunction:: create_cursor .. autofunction:: create_range .. autofunction:: create_label .. autofunction:: create_marker Backend Differences ------------------- The two backends have different capabilities: .. list-table:: :header-rows: 1 :widths: 40 30 30 * - Feature - PlotPy - Matplotlib * - Interactive zoom/pan - ✅ Full Qt tools - ✅ Basic toolbar * - ROI display - ✅ Native support - ✅ Patches overlay * - Geometry results - ✅ Shape annotations - ✅ Markers/lines * - Linked axes - ✅ Native - ✅ via ``sharex``/``sharey`` * - Qt integration - ✅ Native - ⚠️ Requires Qt backend * - Headless/CI - ⚠️ Needs display - ✅ ``Agg`` backend For automated testing and CI environments, Matplotlib with the ``Agg`` backend is recommended. For interactive data exploration, PlotPy provides a richer experience. Sigima-1.1.1/doc/conf.py000066400000000000000000000200471514013333200147650ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. # pylint: skip-file import os import os.path as osp import sys import guidata.config as gcfg from docutils import nodes from docutils.parsers.rst import Directive from docutils.statemachine import StringList from guidata.utils import qt_scraper class OptionsTableDirective(Directive): """Custom directive to include dynamically generated options table.""" has_content = False def run(self): """Generate and include the options table.""" from sigima.config import options # Get the RST content rst_content = options.generate_rst_doc() # Create a container node container = nodes.container() # Parse the RST content and add it to the container rst_lines = rst_content.splitlines() string_list = StringList(rst_lines) self.state.nested_parse(string_list, self.content_offset, container) return [container] sys.path.insert(0, os.path.abspath("..")) import sigima # Turn off validation of guidata config # (documentation build is not the right place for validation) gcfg.set_validation_mode(gcfg.ValidationMode.DISABLED) def exclude_api_from_gettext(app): """Exclude detailed API docs from gettext extraction. This excludes API docs but keeps api/index.rst for translation. """ if app.builder.name == "gettext": # Get all RST files in the api directory api_dir = osp.join(app.srcdir, "api") if osp.exists(api_dir): for filename in os.listdir(api_dir): if filename.endswith(".rst") and filename != "index.rst": # Remove .rst extension and add wildcard pattern = f"api/{filename[:-4]}*" if pattern not in app.config.exclude_patterns: app.config.exclude_patterns.append(pattern) # Also check subdirectories (may be useful in the future) for dirname in os.listdir(api_dir): subdir_path = osp.join(api_dir, dirname) if osp.isdir(subdir_path): # Exclude entire subdirectories except their index files pattern = f"api/{dirname}/*" if pattern not in app.config.exclude_patterns: app.config.exclude_patterns.append(pattern) # Suppress warnings about excluded API documents during gettext builds app.config.suppress_warnings.extend(["toc.excluded", "ref.doc"]) def patch_datalab_client_example(): """Patch the datalab_client example to use stub server during doc build. This function modifies the example execution context so that when Sphinx-Gallery runs datalab_client.py, it connects to a stub server instead of requiring a real DataLab instance. """ from sigima.client.stub import patch_simpleremoteproxy_for_stub # Start stub server and apply the patch return patch_simpleremoteproxy_for_stub() def setup(app): """Setup function for Sphinx.""" app.add_directive("options-table", OptionsTableDirective) app.connect("builder-inited", exclude_api_from_gettext) # -- Project information ----------------------------------------------------- project = "Sigima" author = "" copyright = "2025, DataLab Platform Developers" release = sigima.__version__ # -- General configuration --------------------------------------------------- extensions = [ "sphinx.ext.intersphinx", "sphinx.ext.napoleon", "sphinx.ext.mathjax", "sphinx.ext.githubpages", "sphinx.ext.viewcode", "myst_nb", # Replaces myst_parser and adds notebook support "sphinx_design", "sphinx_copybutton", "guidata.dataset.autodoc", "sphinx_gallery.gen_gallery", ] # MyST-NB configuration nb_execution_mode = "off" # Don't re-execute notebooks during build nb_execution_timeout = 180 # Timeout for notebook execution (if enabled) templates_path = ["_templates"] exclude_patterns = [ "sg_execution_times.rst", "**/sg_execution_times.rst", # exclude .py and .ipynb files in auto_examples generated by sphinx-gallery # this is to prevent sphinx from complaining about duplicate source files "auto_examples/**/*.ipynb", "auto_examples/**/*.py", ] # Suppress the warning about unpicklable sphinx_gallery_conf # (it contains reset_modules function which cannot be pickled) suppress_warnings = ["config.cache"] # -- Sphinx-Gallery configuration -------------------------------------------- # Using guidata's generic Qt scraper for capturing all Qt widgets # Configure to use the last widget as thumbnail for a complete pipeline view qt_scraper.set_qt_scraper_config( thumbnail_source="last", hide_toolbars=True, capture_inside_layout=True ) sphinx_gallery_conf = qt_scraper.get_sphinx_gallery_conf( filename_pattern="", min_reported_time=60, show_memory=False ) if "READTHEDOCS" in os.environ or "CI" in os.environ: os.environ.setdefault("QT_QPA_PLATFORM", "offscreen") # Patch datalab_client example to use stub server during documentation build _stub_server = None def _reset_example_namespace(gallery_conf, fname): """Reset namespace and setup stub server for datalab_client example.""" global _stub_server # Cleanup previous stub server if it exists if _stub_server is not None: _stub_server.stop() _stub_server = None # Setup new stub server for datalab_client example if "datalab_client" in fname: _stub_server = patch_datalab_client_example() # Add reset handler to sphinx_gallery_conf sphinx_gallery_conf["reset_modules"] = _reset_example_namespace sphinx_gallery_conf["reset_modules_order"] = "before" sphinx_gallery_conf["subsection_order"] = [ "./examples/getting_started", "./examples/use_cases", "./examples/features", ] sphinx_gallery_conf["within_subsection_order"] = "ExampleTitleSortKey" # Note: The handler also cleans up the stub server from previous examples # -- Options for HTML output ------------------------------------------------- html_theme = "pydata_sphinx_theme" html_title = project html_logo = "images/Sigima-Banner.svg" html_favicon = "_static/favicon.ico" html_show_sourcelink = False templates_path = ["_templates"] # if "language=fr" in sys.argv: # ann = "" # noqa: E501 # else: # ann = "" # noqa: E501 html_theme_options = { "show_toc_level": 2, "github_url": "https://github.com/DataLab-Platform/Sigima/", "logo": { "text": f"v{sigima.__version__}", }, "icon_links": [ { "name": "PyPI", "url": "https://pypi.org/project/sigima", "icon": "_static/pypi.svg", "type": "local", "attributes": {"target": "_blank"}, }, { "name": "CODRA", "url": "https://codra.net", "icon": "_static/codra.png", "type": "local", "attributes": {"target": "_blank"}, }, { "name": "DataLab", "url": "https://datalab-platform.com", "icon": "_static/DataLab.svg", "type": "local", "attributes": {"target": "_blank"}, }, ], # "announcement": ann, } html_static_path = ["_static"] # -- Options for LaTeX output ------------------------------------------------ latex_logo = "_static/Sigima-Frontpage.png" # -- Options for sphinx-intl package ----------------------------------------- locale_dirs = ["locale/"] # path is example but recommended. gettext_compact = False gettext_location = False # -- Options for autodoc extension ------------------------------------------- autodoc_default_options = { "members": True, "member-order": "bysource", } # -- Options for intersphinx extension --------------------------------------- intersphinx_mapping = { "python": ("https://docs.python.org/3", None), "numpy": ("https://numpy.org/doc/stable/", None), "scipy": ("https://docs.scipy.org/doc/scipy/", None), "scikit-image": ("https://scikit-image.org/docs/stable/", None), "guidata": ("https://guidata.readthedocs.io/en/latest/", None), } Sigima-1.1.1/doc/contributing/000077500000000000000000000000001514013333200161725ustar00rootroot00000000000000Sigima-1.1.1/doc/contributing/contribute_code.rst000066400000000000000000000026011514013333200220730ustar00rootroot00000000000000.. _contribute_code: Contribute code =============== This page explains how you can contribute code to the project. .. seealso:: The :ref:`guidelines` page presents the coding guidelines that you should follow when contributing to the project. Fork the project ---------------- The first step is to fork the project on GitHub. You can do that by visiting `DataLab GitHub project `_ and clicking on the "Fork" button on the top right corner of the page. Once you have forked the project, you will have a copy of the project in your own GitHub account. Then you can clone the project on your computer and start working on it. Submit a pull request --------------------- Once you have made some changes, you can submit a pull request to the original project. To do that, go to your forked project on GitHub and click on the "Pull request" button on the top right corner of the page. Then you will have to fill a form to describe your pull request. Once you have submitted the pull request, the project maintainers will review your changes and merge them if they are satisfied. During the review process, the project maintainers will check that your code follows the coding guidelines and that it does not break the existing tests. If your code does not follow the coding guidelines, you will have to fix it before your pull request can be merged. Sigima-1.1.1/doc/contributing/dependencies.rst000066400000000000000000000071231514013333200213550ustar00rootroot00000000000000.. _dependencies: About Dependencies ================== Dependencies are an important part of any software project, and they can significantly affect the development process. In this section, we will discuss the dependencies used in our project, how to manage them, and best practices for keeping them up to date. Managing Dependencies --------------------- Dependencies are defined in the `pyproject.toml` file, as officially recommended by the Python packaging authority (see `Writing your pyproject.toml `_). The `pyproject.toml` file contains many sections, but the most relevant for dependencies are: - `[project.dependencies]`: This section lists the direct dependencies of the application. These are the packages that the application needs to run. - `[project.optional-dependencies]`: This section lists optional dependencies that can be installed to enable additional features. These dependencies are not required for the core functionality of the application but can enhance its capabilities. Among the optional dependencies, we have the following groups: - `opencv`: computer vision tasks requiring OpenCV. - `dev`: development and testing (linters, formatters, etc.). - `doc`: building the documentation (Sphinx, etc.). - `test`: running the tests (pytest, etc.). - `qt`: Qt-based graphical user interface (for interactive testing purposes). Deploying Dependencies ---------------------- Production ^^^^^^^^^^ In production, we recommend using the package manager that is most suitable for your environment and that you are most comfortable with. All package managers (e.g., `pip`, `conda`) are directly or indirectly using the information from the `pyproject.toml` file to install the dependencies. See :ref:`installation` for more information on how to install DataLab and its dependencies. Development ^^^^^^^^^^^ In development, you may also use the requirements text file to make it easier to install the dependencies in a virtual environment or container. The `requirements.txt` file lists all the dependencies needed for the project, including both direct and optional dependencies. This is the exact list of dependencies that are defined in the `pyproject.toml` file, but formatted for use with `pip` or other package managers that support requirements files. .. note:: The requirements file is generated from the `pyproject.toml` file using a tool provided by the `guidata` package. .. code-block:: console python -m guidata.utils.genreqs txt # to generate requirements.txt Adding New Dependencies ----------------------- When adding new dependencies to the project, please follow these rules: 1. If it is a direct dependency, that is a package that the application needs to run, add it to the `[project.dependencies]` section in the `pyproject.toml` file, and specify the version range that is compatible with the application, in order to avoid breaking changes. 2. If it is an optional dependency, that is a package that can be installed to enable additional features, add it to the appropriate section in the `[project.optional-dependencies]` section in the `pyproject.toml` file. - For the `dev` dependencies, unless it's absolutely necessary, do not specify a version range, as it may limit the ability to use the latest version of the package. - For the other optional dependencies, specify the version range that is compatible with the application, in order to avoid breaking changes. .. note:: In other words, except for the `dev` dependencies, always specify a version range that is compatible with the application.Sigima-1.1.1/doc/contributing/environment.md000066400000000000000000000104601514013333200210610ustar00rootroot00000000000000Setting up Development Environment ================================== Getting started with DataLab development is easy. Here is what you will need: 1. An integrated development environment (IDE) for Python. We recommend [Spyder](https://www.spyder-ide.org/) or [Visual Studio Code](https://code.visualstudio.com/), but any IDE will do. 2. A Python distribution. We recommend [WinPython](https://winpython.github.io/), on Windows, or [Anaconda](https://www.anaconda.com/), on Linux or Mac. But, again, any Python distribution will do. 3. A clean project structure (see below). 4. Test data (see below). 5. Environment variables (see below). 6. Third-party software (see below). Development Environment ----------------------- If you are using [Spyder](https://www.spyder-ide.org/), thank you for supporting the scientific open-source Python community! If you are using Visual Studio Code, that's also an excellent choice (for other reasons). We recommend installing the following extensions: | Extension | Description | | --------- | ----------- | | [gettext](https://marketplace.visualstudio.com/items?itemName=mrorz.language-gettext) | Gettext syntax highlighting | | [Pylance](https://marketplace.visualstudio.com/items?itemName=ms-python.vscode-pylance) | Python language server | | [Python](https://marketplace.visualstudio.com/items?itemName=ms-python.python) | Python extension | | [reStructuredText Syntax highlighting](https://marketplace.visualstudio.com/items?itemName=trond-snekvik.simple-rst) | reStructuredText syntax highlighting | | [Ruff](https://marketplace.visualstudio.com/items?itemName=charliermarsh.ruff) | Extremely fast Python linter and code formatter | | [Todo Tree](https://marketplace.visualstudio.com/items?itemName=Gruntfuggly.todo-tree) | Todo tree | | [Insert GUID](https://marketplace.visualstudio.com/items?itemName=heaths.vscode-guid) | Insert GUID | | [XML Tools](https://marketplace.visualstudio.com/items?itemName=DotJoshJohnson.xml) | XML Tools | Python Environment ------------------ Sigima requires the following : * Python (e.g. WinPython) * Additional Python packages Installing all required packages : pip install --upgrade -r requirements.txt If you are using [WinPython](https://winpython.github.io/), thank you for supporting the scientific open-source Python community! The following table lists the currently officially used Python distributions: | Python version | Status | WinPython version | | -------------- | ------------ | ----------------- | | 3.9 | OK | 3.9.10.0 | | 3.10 | OK | 3.10.11.1 | | 3.11 | OK | 3.11.5.0 | | 3.12 | OK | 3.12.3.0 | | 3.13 | OK | 3.13.2.0 | ⚠ We strongly recommend using the `.dot` versions of WinPython which are lightweight and can be customized to your needs (using `pip install -r requirements.txt`). ✅ We also recommend using a dedicated WinPython instance for Sigima. Test data --------- Sigima test data are located in different folders, depending on their nature or origin. Required data for unit tests are located in "sigima\data\tests" (public data). A second folder %SIGIMA_DATA% (optional) may be defined for additional tests which are still under development (or for confidential data). Specific environment variables ------------------------------ Visual Studio Code configuration used in `launch.json` and/or `tasks.json` (examples) : @REM Folder containing additional working test data set SIGIMA_DATA=C:\Dev\Projets\SIGIMA_data Visual Studio Code `.env` file: * This file is used to set environment variables for the application. * It is used to set the `PYTHONPATH` environment variable to the root of the project. * This is required to be able to import the project modules from within VS Code. * To create this file, copy the `.env.template` file to `.env` (and eventually add your own paths). Third-party Software -------------------- The following software may be required for maintaining the project: | Software | Description | | -------- | ----------- | | [gettext](https://mlocati.github.io/articles/gettext-iconv-windows.html) | Translations | | [Git](https://git-scm.com/) | Version control system | | [ImageMagick](https://imagemagick.org/) | Image manipulation utilities | Sigima-1.1.1/doc/contributing/gitworkflow.rst000066400000000000000000000207641514013333200213130ustar00rootroot00000000000000.. _gitworkflow: Git Workflow ============ This document describes the Git workflow used in the Sigima project, based on a ``main`` branch, a ``develop`` branch, and feature-specific branches. It also defines how bug fixes are managed. .. note:: This workflow is a simplified version of the `Gitflow Workflow `_. It has been adapted to suit the needs of the Sigima project at the current stage of development. In the near future, we may consider adopting a more complex workflow, e.g. by adding release branches. Branching Model --------------- Main Branches ^^^^^^^^^^^^^ - ``main``: Represents the stable, production-ready version of the project. - ``develop``: Used for ongoing development and integration of new features. Feature Branches ^^^^^^^^^^^^^^^^ - ``feature/feature_name``: Used for the development of new features. - Created from ``develop``. - Merged back into ``develop`` once completed. - Deleted after merging. Release Branch ^^^^^^^^^^^^^^ - ``release``: Represents the current maintenance line for patch releases. - Created from ``main`` after a stable release when the first patch is needed. - Accepts ``fix/xxx`` and ``hotfix/xxx`` branch merges. - Merged back into ``main`` for each patch release tag (e.g., 1.0.1, 1.0.2). - Reset or recreated when starting a new minor/major release cycle. .. note:: The ``release`` branch is not versioned (no ``release/1.0.x``). It always represents "the current maintenance line." When a new minor version is released (e.g., 1.2.0), the old ``release`` branch is deleted and a new one is created from the fresh tag when the first patch for 1.2.1 is needed. Bug Fix Branches ^^^^^^^^^^^^^^^^ - ``fix/xxx``: Used for general bug fixes that are not urgent. - Created from ``develop`` (for next feature release) or ``release`` (for patch release). - Merged back into the originating branch once completed. - Deleted after merging. - ``hotfix/xxx``: Used for urgent production-critical fixes. - Created from ``release`` (if exists) or ``main`` (if no ``release`` branch yet). - Merged back into ``release`` or ``main``. - The fix is then cherry-picked into ``develop``. - Deleted after merging. .. note:: Hotfixes (high-priority fixes) will be integrated in the next maintenance release (X.Y.Z -> Z+1), while fixes (low-priority fixes) will be integrated in the next feature release (X.Y -> Y+1). Documentation Branches ---------------------- When working on documentation that is not related to source code (e.g. training materials, user guides), branches should be named using the ``doc/`` prefix. Examples: - ``doc/training-materials`` - ``doc/user-guide`` This naming convention improves clarity by clearly separating documentation efforts from code-related development (features, fixes, etc.). Workflow for New Features ------------------------- 1. Create a new feature branch from ``develop``: .. code-block:: sh git checkout develop git checkout -b develop/feature_name 2. Develop the feature and commit changes. 3. Merge the feature branch back into ``develop``: .. code-block:: sh git checkout develop git merge --no-ff develop/feature_name 4. Delete the feature branch: .. code-block:: sh git branch -d develop/feature_name .. warning:: Do not leave feature branches unmerged for too long. Regularly rebase them on ``develop`` to minimize conflicts. Workflow for Regular Bug Fixes ------------------------------ For next feature release (target: ``develop``): 1. Create a bug fix branch from ``develop``: .. code-block:: sh git checkout develop git checkout -b fix/bug_description 2. Apply the fix and commit changes. 3. Merge the fix branch back into ``develop``: .. code-block:: sh git checkout develop git merge --no-ff fix/bug_description 4. Delete the fix branch: .. code-block:: sh git branch -d fix/bug_description For current maintenance release (target: ``release``): 1. Create a bug fix branch from ``release``: .. code-block:: sh git checkout release git checkout -b fix/bug_description 2. Apply the fix and commit changes. 3. Merge the fix branch back into ``release``: .. code-block:: sh git checkout release git merge --no-ff fix/bug_description 4. Delete the fix branch: .. code-block:: sh git branch -d fix/bug_description .. warning:: Do not create a ``fix/xxx`` branch from a ``develop/feature_name`` branch. Always branch from ``develop`` or ``release`` to ensure fixes are correctly propagated. .. code-block:: sh # Incorrect: git checkout develop/feature_name git checkout -b fix/wrong_branch .. code-block:: sh # Correct: git checkout develop git checkout -b fix/correct_branch Workflow for Critical Hotfixes ------------------------------ 1. Create a hotfix branch from ``release`` (or ``main`` if no ``release`` branch exists): .. code-block:: sh git checkout release # or: git checkout main git checkout -b hotfix/critical_bug 2. Apply the fix and commit changes. 3. Merge the fix back into ``release`` (or ``main``): .. code-block:: sh git checkout release # or: git checkout main git merge --no-ff hotfix/critical_bug 4. Cherry-pick the fix into ``develop``: .. code-block:: sh git checkout develop git cherry-pick 5. Delete the hotfix branch: .. code-block:: sh git branch -d hotfix/critical_bug .. warning:: Do not merge ``fix/xxx`` or ``hotfix/xxx`` directly into ``main`` without following the workflow. Ensure hotfixes are cherry-picked into ``develop`` to avoid losing fixes in future releases. Workflow for Patch Releases ---------------------------- When ready to release a patch version (e.g., 1.0.1, 1.0.2): 1. Ensure the ``release`` branch contains all desired fixes. 2. Merge ``release`` into ``main``: .. code-block:: sh git checkout main git merge --no-ff release 3. Tag the release on ``main``: .. code-block:: sh git tag -a v1.0.1 -m "Release version 1.0.1" git push origin main --tags 4. Keep the ``release`` branch for additional patches in the same minor version series. Workflow for Minor/Major Releases ---------------------------------- When ready to release a new minor or major version (e.g., 1.1.0, 2.0.0): 1. Merge ``develop`` into ``main``: .. code-block:: sh git checkout main git merge --no-ff develop 2. Tag the release on ``main``: .. code-block:: sh git tag -a v1.1.0 -m "Release version 1.1.0" git push origin main --tags 3. Delete the old ``release`` branch (if exists): .. code-block:: sh git branch -d release git push origin --delete release 4. Create a new ``release`` branch from ``main`` when the first patch for 1.1.1 is needed: .. code-block:: sh git checkout main git checkout -b release git push -u origin release Best Practices -------------- - Regularly **rebase feature branches** on ``develop`` to stay up to date: .. code-block:: sh git checkout develop/feature_name git rebase develop - Avoid long-lived branches to minimize merge conflicts. - Ensure bug fixes in ``release`` or ``main`` are **always cherry-picked** to ``develop``. - Clearly differentiate between ``fix/xxx`` (non-urgent fixes) and ``hotfix/xxx`` (critical production fixes). - When creating the ``release`` branch, update release notes to indicate which version it targets (e.g., add a comment in the merge commit: "Create release branch for v1.0.x maintenance"). - The ``release`` branch always represents the current maintenance line. To know which version it targets, check the most recent tag on ``main`` or the release notes. Takeaway -------- This workflow ensures a structured yet flexible development process while keeping ``main`` stable and ``develop`` always updated with the latest changes. The ``release`` branch provides a dedicated maintenance line for patch releases, allowing ``develop`` to proceed with new features without interference. This solves the problem of coordinating unreleased changes across the PlotPyStack ecosystem (DataLab, Sigima, PlotPy, guidata, PythonQwt) by providing a stable branch for CI testing during maintenance cycles. Sigima-1.1.1/doc/contributing/guidelines.rst000066400000000000000000000047101514013333200210560ustar00rootroot00000000000000.. _guidelines: Coding guidelines ================= Generic coding guidelines ------------------------- We follow the `PEP 8 `_ coding style. In particular, we are especially strict about the following guidelines: - Limit all lines to a maximum of 79 characters. - Respect the naming conventions (classes, functions, variables, etc.). - Use specific exceptions instead of the generic :class:`Exception`. To enforce these guidelines, the following tools are mandatory: - `ruff `_ for code formatting and static code analysis. - `pylint `_ for static code analysis. ruff ^^^^ If you are using `Visual Studio Code `_, the project settings will automatically format your code with `ruff` on save (you may also run the task "Run Ruff" to run `ruff` on the project). To run `ruff`, run the following command:: ruff check pylint ^^^^^^ To run `pylint`, run the following command:: pylint sigima If you are using `Visual Studio Code `_ on Windows, you may run the task "Run Pylint" to run `pylint` on the project. .. note:: A `pylint` rating greater than 9/10 is required to merge a pull request. Specific coding guidelines -------------------------- In addition to the generic coding guidelines, we have the following specific guidelines: - Write docstrings for all classes, methods and functions. The docstrings should follow the `Google style `_. - Add typing annotations for all functions and methods. The annotations should use the future syntax (``from __future__ import annotations``) - Try to keep the code as simple as possible. If you have to write a complex piece of code, try to split it into several functions or classes. - Add as many comments as possible. The code should be self-explanatory, but it is always useful to add some comments to explain the general idea of the code, or to explain some tricky parts. - Do not use ``from module import *`` statements, even in the ``__init__`` module of a package. - Avoid using mixins (multiple inheritance) when possible. It is often possible to use composition instead of inheritance. - Avoid using ``__getattr__`` and ``__setattr__`` methods. They are often used to implement lazy initialization, but this can be done in a more explicit way. Sigima-1.1.1/doc/contributing/index.rst000066400000000000000000000103321514013333200200320ustar00rootroot00000000000000Contributing ============ .. meta:: :description: Contribute to Sigima project, the open-source scientific data analysis platform :keywords: Sigima, contribute, open-source, scientific, data, analysis, platform, signal processing, image processing There are many ways to contribute to Sigima, depending on how much time you have, your experience with open source projects, and your skills. Share your ideas and experiences -------------------------------- .. only:: html and not latex :octicon:`info;1em;sd-text-info` :bdg-success-line:`No coding required` Besides the classic bug reports and feature requests, you can share your ideas and experiences for improving Sigima. In particular, we are very interested in your feedback on the documentation and tutorials. Moreover, if you have a use case that you would like to share with the community, please let us know. .. only:: html and not latex .. grid:: 2 :gutter: 1 2 3 4 .. grid-item-card:: :octicon:`bug;1em;sd-text-info` Bugs :link: https://github.com/DataLab-Platform/Sigima/issues/new?assignees=&labels=bug&projects=&template=bug_report.md&title= Reporting a bug .. grid-item-card:: :octicon:`light-bulb;1em;sd-text-info` Enhancements :link: https://github.com/DataLab-Platform/Sigima/issues/new?assignees=&labels=enhancement&projects=&template=feature_request.md&title= Suggesting an enhancement .. grid-item-card:: :octicon:`book;1em;sd-text-info` Documentation :link: https://github.com/DataLab-Platform/Sigima/issues/new?assignees=&labels=documentation&projects=&template=doc_request.md&title= Suggesting a documentation topic .. grid-item-card:: :octicon:`mortar-board;1em;sd-text-info` Tutorial :link: https://github.com/DataLab-Platform/Sigima/issues/new?assignees=&labels=documentation&projects=&template=tutorial_request.md&title= Suggesting a tutorial topic .. only:: latex and not html Without coding, you can contribute to Sigima project by: - `Reporting a bug `_ - `Suggesting an enhancement `_ - `Suggesting a documentation topic `_ - `Suggesting a tutorial topic `_ Share your scientific/technical knowledge ----------------------------------------- .. only:: html and not latex :octicon:`info;1em;sd-text-info` :bdg-success-line:`No coding required` Your technical or scientific knowledge is also very valuable to us, as you may directly contribute to the documentation or tutorials. Or, better, if you want to write a tutorial, we will be happy to help you. Again without coding, you can contribute to Sigima project by: - Writing documentation - Writing a tutorial Contribute to new features -------------------------- .. only:: html and not latex :octicon:`info;1em;sd-text-info` :bdg-info-line:`Coding (beginner)` :bdg-warning-line:`Coding (advanced)` Even if you are not a developer, you can contribute to the project by: - Testing new features - Writing and submitting new Plugins - Writing and submitting macro-commands Develop new features -------------------- .. only:: html and not latex :octicon:`info;1em;sd-text-info` :bdg-warning-line:`Coding (advanced)` If you are a developer, you can contribute to the core of the project by fixing bugs or implementing new features. .. only:: html and not latex .. grid:: 1 :gutter: 1 2 3 4 .. grid-item-card:: :octicon:`terminal;1em;sd-text-info` Code :link: contribute_code :link-type: doc Contributing to the code .. only:: latex and not html See :ref:`contribute_code` section for more information. .. toctree:: :maxdepth: 2 :hidden: contribute_code guidelines gitworkflow dependencies environment Sigima-1.1.1/doc/examples/000077500000000000000000000000001514013333200153015ustar00rootroot00000000000000Sigima-1.1.1/doc/examples/README.txt000066400000000000000000000012661514013333200170040ustar00rootroot00000000000000Examples ======== This section presents a collection of examples demonstrating the capabilities of Sigima. Each example is a standalone Python script that showcases specific features or use cases of the Sigima library, along with visualizations of the results (using the `sigima.viz` module with the `PlotPyStack `_ backend). Of course, some of these examples may seem trivial, but they serve to illustrate how to use various functionalities of Sigima in a clear and concise manner. .. note:: These examples are automatically generated when building the documentation, thus ensuring that they are always up-to-date with the latest version of Sigima. Sigima-1.1.1/doc/examples/features/000077500000000000000000000000001514013333200171175ustar00rootroot00000000000000Sigima-1.1.1/doc/examples/features/README.txt000066400000000000000000000000421514013333200206110ustar00rootroot00000000000000Various Features ---------------- Sigima-1.1.1/doc/examples/features/convolution.py000066400000000000000000000250571514013333200220610ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Convolution and Deconvolution ============================= This example focuses on image blurring and sharpening using convolution and deconvolution techniques provided by Sigima. Using various kernels, we'll explore how these operations affect images and how to implement them using Sigima's processing functions. The example shows: * Creating test images and kernels * Basic convolution with Gaussian kernel * Identity convolution (preserving original image) * Deconvolution operations * Effects of different kernel parameters * Custom edge detection and sharpening kernels This tutorial uses PlotPy for visualization, providing interactive plots that allow you to explore the convolution results in detail. """ # %% # Importing necessary modules # --------------------------- # We'll start by importing all the required modules for image processing # and visualization. import numpy as np import scipy.signal import sigima.objects import sigima.params import sigima.proc.image from sigima import viz # %% # Creating test images and kernels # -------------------------------- # We start by creating a test image and various convolution kernels. # Set the fixed image size for this tutorial size = 128 # Generate a test square image with a rectangle in the center data = np.zeros((size, size), dtype=np.float64) data[size // 5 : 2 * size // 5, size // 7 : 5 * size // 7] = 1.0 original_image = sigima.objects.create_image("Original Rectangle", data) # Generate a Gaussian kernel gparam = sigima.objects.Gauss2DParam.create(height=31, width=31, sigma=2.0) nparam = sigima.params.NormalizeParam.create(method="area") gaussian_kernel = sigima.objects.create_image_from_param(gparam) gaussian_kernel = sigima.proc.image.normalize(gaussian_kernel, nparam) gaussian_kernel.title = "Gaussian Kernel (σ=2.0)" # Generate an identity kernel (impulse response) identity_size = 15 identity_kernel = sigima.objects.create_image_from_param( sigima.objects.Zero2DParam.create(height=identity_size, width=identity_size) ) identity_kernel.data[identity_size // 2, identity_size // 2] = 1.0 identity_kernel.title = "Identity Kernel" print("✓ Test images and kernels created successfully!") print("This example demonstrates convolution and deconvolution with Sigima.") print(f"Original image shape: {original_image.data.shape}") print(f"Gaussian kernel shape: {gaussian_kernel.data.shape}") print(f"Identity kernel shape: {identity_kernel.data.shape}") # Display the original image and kernels viz.view_images_side_by_side( [original_image, gaussian_kernel, identity_kernel], ["Original Image", "Gaussian Kernel (σ=2.0)", "Identity Kernel"], title="Test Images and Kernels", ) # %% # Basic convolution with Gaussian kernel # -------------------------------------- # Now we'll perform convolution with the Gaussian kernel and compare # the result with scipy's implementation to verify correctness. # Perform convolution with Gaussian kernel convolved_gauss = sigima.proc.image.convolution(original_image, gaussian_kernel) convolved_gauss.title = "Convolved with Gaussian" # Compare with scipy implementation expected_result = scipy.signal.convolve( original_image.data, gaussian_kernel.data, mode="same", method="auto" ) print("\n✓ Convolution completed!") max_diff = np.max(np.abs(convolved_gauss.data - expected_result)) print(f"Max difference from scipy: {max_diff:.2e}") # Visualize the convolution process viz.view_images_side_by_side( [original_image, gaussian_kernel, convolved_gauss], ["Original Image", "Gaussian Kernel (σ=2.0)", "Convolved Result"], title="Gaussian Convolution Example", ) # %% # Identity convolution # -------------------- # Identity convolution should preserve the original image exactly. # This demonstrates that our convolution implementation is working correctly. # Perform convolution with identity kernel convolved_identity = sigima.proc.image.convolution(original_image, identity_kernel) convolved_identity.title = "Convolved with Identity" # This should be nearly identical to the original difference = np.max(np.abs(convolved_identity.data - original_image.data)) print("\n✓ Identity convolution completed!") print(f"Max difference from original: {difference:.2e}") # Visualize the identity convolution viz.view_images_side_by_side( [original_image, identity_kernel, convolved_identity], ["Original Image", "Identity Kernel", "Convolved with Identity"], "Identity Convolution Example", ) # %% # Deconvolution with identity kernel # ---------------------------------- # Deconvolution is the inverse operation of convolution. We'll start # with a simple case using the identity kernel. # Start with the convolved image and deconvolve using identity kernel deconvolved_identity = sigima.proc.image.deconvolution( convolved_identity, identity_kernel ) deconvolved_identity.title = "Deconvolved (Identity)" # Check how well we recovered the original recovery_error = np.max(np.abs(deconvolved_identity.data - original_image.data)) print("\n✓ Identity deconvolution completed!") print(f"Recovery error: {recovery_error:.2e}") # Visualize the deconvolution process viz.view_images_side_by_side( [original_image, convolved_identity, deconvolved_identity], ["Original", "Convolved", "Deconvolved"], title="Identity Deconvolution Example", ) # %% # Advanced deconvolution with Gaussian kernel # ------------------------------------------- # Now we'll try deconvolution with a Gaussian kernel, which is more # challenging and demonstrates the limitations of deconvolution. # Create a Gaussian kernel with smaller sigma for better deconvolution gparam.sigma = 1.5 deconv_gaussian = sigima.proc.image.normalize( sigima.objects.create_image_from_param(gparam), nparam ) deconv_gaussian.title = "Gaussian Kernel (σ=1.5)" # Convolve the original image with this kernel large_convolved = sigima.proc.image.convolution(original_image, deconv_gaussian) large_convolved.title = "Convolved Image" # Attempt deconvolution to recover the original large_deconvolved = sigima.proc.image.deconvolution(large_convolved, deconv_gaussian) large_deconvolved.title = "Deconvolved Result" print("\n✓ Gaussian deconvolution completed!") orig_min, orig_max = np.min(original_image.data), np.max(original_image.data) deconv_min, deconv_max = np.min(large_deconvolved.data), np.max(large_deconvolved.data) print(f"Original image range: [{orig_min:.3f}, {orig_max:.3f}]") print(f"Deconvolved image range: [{deconv_min:.3f}, {deconv_max:.3f}]") # Visualize the full deconvolution process viz.view_images_side_by_side( [original_image, deconv_gaussian, large_convolved, large_deconvolved], ["Original", "Gaussian Kernel", "Convolved", "Deconvolved"], title="Gaussian Deconvolution Example", ) # %% # Exploring different kernel parameters # ------------------------------------- # Different sigma values in Gaussian kernels produce different blurring effects. # Let's compare several sigma values side by side. # Create kernels with different sigma parameters gparam.sigma = 0.8 small_sigma = sigima.proc.image.normalize( sigima.objects.create_image_from_param(gparam), nparam ) gparam.sigma = 2.0 medium_sigma = sigima.proc.image.normalize( sigima.objects.create_image_from_param(gparam), nparam ) gparam.sigma = 4.0 large_sigma = sigima.proc.image.normalize( sigima.objects.create_image_from_param(gparam), nparam ) # Convolve the original image with each kernel conv_small = sigima.proc.image.convolution(original_image, small_sigma) conv_medium = sigima.proc.image.convolution(original_image, medium_sigma) conv_large = sigima.proc.image.convolution(original_image, large_sigma) print("\n✓ Multiple kernel comparison completed!") # Show the effect of different sigma values on kernels viz.view_images_side_by_side( [small_sigma, medium_sigma, large_sigma], ["Kernel σ=0.8", "Kernel σ=2.0", "Kernel σ=4.0"], title="Gaussian Kernels with Different Sigma Values", ) # Show the effect of different sigma values on convolution results viz.view_images_side_by_side( [conv_small, conv_medium, conv_large], ["Convolved σ=0.8", "Convolved σ=2.0", "Convolved σ=4.0"], title="Convolution Results with Different Sigma Values", ) # %% # Custom convolution kernels # -------------------------- # Besides Gaussian kernels, we can create custom kernels for specific # image processing tasks like edge detection and sharpening. # Edge detection kernel (Sobel-like) edge_data = np.array([[-1, -2, -1], [0, 0, 0], [1, 2, 1]], dtype=np.float64) edge_kernel = sigima.objects.create_image("Edge Detection Kernel", edge_data) # Sharpening kernel sharpen_data = np.array([[0, -1, 0], [-1, 5, -1], [0, -1, 0]], dtype=np.float64) sharpen_kernel = sigima.objects.create_image("Sharpening Kernel", sharpen_data) # Apply custom kernels to the original image edge_result = sigima.proc.image.convolution(original_image, edge_kernel) edge_result.title = "Edge Detection" sharpen_result = sigima.proc.image.convolution(original_image, sharpen_kernel) sharpen_result.title = "Sharpened" print("\n✓ Custom kernel convolutions completed!") # Visualize custom kernels viz.view_images_side_by_side( [edge_kernel, sharpen_kernel], ["Edge Detection Kernel", "Sharpening Kernel"], title="Custom Convolution Kernels", ) # Visualize custom kernel results viz.view_images_side_by_side( [original_image, edge_result, sharpen_result], ["Original", "Edge Detection", "Sharpened"], title="Custom Kernel Convolution Results", ) # %% # Summary and conclusions # ----------------------- # This tutorial demonstrated the key concepts of convolution and deconvolution # in image processing using Sigima. print("\n" + "=" * 60) print("CONVOLUTION TUTORIAL SUMMARY") print("=" * 60) print("✓ Created test images and various kernels") print("✓ Demonstrated basic Gaussian convolution") print("✓ Showed identity kernel behavior") print("✓ Performed deconvolution operations") print("✓ Explored different kernel parameters") print("✓ Applied custom edge detection and sharpening kernels") print("\nKey Takeaways:") print("• Larger sigma values create more blurring") print("• Identity kernels preserve the original image") print("• Deconvolution can recover original features (with limitations)") print("• Custom kernels enable specialized image processing effects") # Final comparison showing the complete pipeline dialog10 = viz.view_images_side_by_side( [original_image, gaussian_kernel, convolved_gauss, large_deconvolved], ["Original", "Gaussian Kernel", "Convolved", "Deconvolved"], title="Complete Convolution-Deconvolution Pipeline", ) Sigima-1.1.1/doc/examples/features/coordinate_systems.py000066400000000000000000000256231514013333200234170ustar00rootroot00000000000000""" Uniform and Non-Uniform Coordinate Systems ========================================== This example demonstrates the use of uniform and non-uniform coordinate systems with images in Sigima. It shows how to create, visualize, and work with both types of coordinate systems, highlighting their differences and appropriate use cases. The example shows: * Creating images with uniform coordinate systems * Creating images with non-uniform coordinate systems * Visualizing the coordinate grids * Comparing pixel spacing and coordinate mapping * Working with real-world units and coordinates * Understanding when to use each coordinate system type This tutorial uses PlotPy for visualization, providing interactive plots that allow you to explore the coordinate system effects in detail. """ # %% # Importing necessary modules # --------------------------- # We'll start by importing all the required modules for image processing # and visualization. import numpy as np from sigima.objects import create_image from sigima.viz import view_images_side_by_side # %% # Creating test images with uniform coordinates # --------------------------------------------- # Uniform coordinates have constant spacing between pixels in both directions. # This is the most common case for regular imaging systems. # Create a simple test pattern - a sine wave pattern size = 100 x_uniform = np.linspace(0, 4 * np.pi, size) y_uniform = np.linspace(0, 4 * np.pi, size) X_uniform, Y_uniform = np.meshgrid(x_uniform, y_uniform) # Create a 2D sine wave pattern data_uniform = np.sin(X_uniform) * np.cos(Y_uniform) # Create the image object with uniform coordinates uniform_image = create_image( title="Uniform Coordinates", data=data_uniform, units=("μm", "μm", "intensity"), labels=("X position", "Y position", "Signal"), ) # Set uniform coordinate system with specific spacing and origin dx = 0.1 # 0.1 μm per pixel in X dy = 0.1 # 0.1 μm per pixel in Y x0 = -2.0 # X origin at -2.0 μm y0 = -2.0 # Y origin at -2.0 μm uniform_image.set_uniform_coords(dx, dy, x0=x0, y0=y0) print("✓ Uniform coordinate image created!") print(f"Image shape: {uniform_image.data.shape}") coord_type = "Uniform" if uniform_image.is_uniform_coords else "Non-uniform" print(f"Coordinate system: {coord_type}") print(f"X spacing (dx): {uniform_image.dx} μm") print(f"Y spacing (dy): {uniform_image.dy} μm") print(f"X origin: {uniform_image.x0} μm") print(f"Y origin: {uniform_image.y0} μm") x_end = uniform_image.x0 + uniform_image.dx * (uniform_image.data.shape[1] - 1) y_end = uniform_image.y0 + uniform_image.dy * (uniform_image.data.shape[0] - 1) print(f"X range: {uniform_image.x0:.1f} to {x_end:.1f} μm") print(f"Y range: {uniform_image.y0:.1f} to {y_end:.1f} μm") # %% # Creating test images with non-uniform coordinates # ------------------------------------------------- # Non-uniform coordinates allow for variable spacing between pixels, # useful for adaptive sampling, curved coordinates, or irregular grids. # Create the same sine wave pattern but with non-uniform coordinates data_nonuniform = data_uniform.copy() # Create non-uniform coordinate arrays # X coordinates: denser near the center, sparser at edges x_center = 2 * np.pi x_range = 4 * np.pi x_nonuniform = x_center + (x_range / 2) * np.tanh(np.linspace(-2, 2, size)) # Y coordinates: quadratic spacing (denser at bottom) y_start = 0 y_end = 4 * np.pi y_nonuniform = y_start + (y_end - y_start) * (np.linspace(0, 1, size) ** 2) # Create the image object with non-uniform coordinates nonuniform_image = create_image( title="Non-Uniform Coordinates", data=data_nonuniform, units=("μm", "μm", "intensity"), labels=("X position", "Y position", "Signal"), ) # Set non-uniform coordinate system nonuniform_image.set_coords(xcoords=x_nonuniform, ycoords=y_nonuniform) print("\n✓ Non-uniform coordinate image created!") print(f"Image shape: {nonuniform_image.data.shape}") coord_type = "Uniform" if nonuniform_image.is_uniform_coords else "Non-uniform" print(f"Coordinate system: {coord_type}") print(f"X coordinates range: {x_nonuniform[0]:.3f} to {x_nonuniform[-1]:.3f} μm") print(f"Y coordinates range: {y_nonuniform[0]:.3f} to {y_nonuniform[-1]:.3f} μm") x_spacing_min = np.min(np.diff(x_nonuniform)) x_spacing_max = np.max(np.diff(x_nonuniform)) y_spacing_min = np.min(np.diff(y_nonuniform)) y_spacing_max = np.max(np.diff(y_nonuniform)) print(f"X spacing varies from {x_spacing_min:.4f} to {x_spacing_max:.4f} μm") print(f"Y spacing varies from {y_spacing_min:.4f} to {y_spacing_max:.4f} μm") # %% # Visualizing coordinate system differences # ----------------------------------------- # Let's create coordinate grid visualizations to highlight the differences # between uniform and non-uniform coordinate systems. # Create coordinate grid images for visualization grid_uniform = np.zeros_like(data_uniform) grid_nonuniform = np.zeros_like(data_nonuniform) # Add grid lines every 10 pixels for uniform coordinates grid_uniform[::10, :] = 1.0 # Horizontal lines grid_uniform[:, ::10] = 1.0 # Vertical lines # Add grid lines every 10 pixels for non-uniform coordinates grid_nonuniform[::10, :] = 1.0 # Horizontal lines grid_nonuniform[:, ::10] = 1.0 # Vertical lines # Create grid visualization images uniform_grid = create_image( title="Uniform Grid", data=grid_uniform, units=("μm", "μm", "grid"), labels=("X position", "Y position", "Grid lines"), ) uniform_grid.set_uniform_coords(dx, dy, x0=x0, y0=y0) nonuniform_grid = create_image( title="Non-Uniform Grid", data=grid_nonuniform, units=("μm", "μm", "grid"), labels=("X position", "Y position", "Grid lines"), ) nonuniform_grid.set_coords(xcoords=x_nonuniform, ycoords=y_nonuniform) print("\n✓ Coordinate grid visualizations created!") # Display the coordinate system comparison view_images_side_by_side( [uniform_image, nonuniform_image], ["Uniform Coordinates", "Non-Uniform Coordinates"], title="Coordinate Systems Comparison - Data Images", share_axes=False, ) view_images_side_by_side( [uniform_grid, nonuniform_grid], ["Uniform Grid", "Non-Uniform Grid"], title="Coordinate Systems Comparison - Grid Visualization", share_axes=False, ) # %% # Creating specialized non-uniform coordinate examples # ---------------------------------------------------- # Let's create some more realistic examples of non-uniform coordinates # that might be encountered in real applications: # # 1. Time-resolved spectroscopy with logarithmic wavelength scale # 2. Polar to Cartesian mapping # Example 1: Logarithmic wavelength scale for spectroscopy # Simulating a time-resolved spectroscopy measurement with log-spaced wavelengths size_log = 80 wavelengths = np.logspace(np.log10(400), np.log10(800), size_log) # 400-800 nm time_points = np.linspace(0, 200, size_log) # Time in milliseconds W, T = np.meshgrid(wavelengths, time_points) # Create a spectral response pattern: a peak that shifts over time # Simulates fluorescence decay with spectral shift peak_center = 500 + 0.5 * T # Peak shifts from 500 to 600 nm over time spectral_data = np.exp(-(((W - peak_center) / 40) ** 2)) * np.exp(-T / 100) spectral_image = create_image( title="Time-Resolved Spectroscopy (Log λ)", data=spectral_data, units=("nm", "ms", "counts"), labels=("Wavelength", "Time", "Fluorescence"), ) spectral_image.set_coords(xcoords=wavelengths, ycoords=time_points) print("\n✓ Time-resolved spectroscopy example created!") print(f"Wavelength range: {wavelengths[0]:.1f} to {wavelengths[-1]:.1f} nm") print(f"Time range: {time_points[0]:.1f} to {time_points[-1]:.1f} ms") wl_spacing_min = np.min(np.diff(wavelengths)) wl_spacing_max = np.max(np.diff(wavelengths)) print(f"Log wavelength spacing: {wl_spacing_min:.2f} to {wl_spacing_max:.2f} nm") # Example 2: Polar to Cartesian mapping size_polar = 60 r_coords = np.linspace(1, 10, size_polar) theta_coords = np.linspace(0, 2 * np.pi, size_polar) # Convert to Cartesian coordinates for non-uniform mapping x_polar = np.zeros((size_polar, size_polar)) y_polar = np.zeros((size_polar, size_polar)) for i, r in enumerate(r_coords): for j, theta in enumerate(theta_coords): x_polar[i, j] = r * np.cos(theta) y_polar[i, j] = r * np.sin(theta) # Create a radial pattern polar_data = np.zeros((size_polar, size_polar)) for i, r in enumerate(r_coords): for j, theta in enumerate(theta_coords): polar_data[i, j] = np.sin(3 * theta) * np.exp(-r / 5) # Note: For this example, we'll use the polar coordinates directly # In practice, you might want to interpolate to a regular Cartesian grid polar_image = create_image( title="Polar Coordinate Mapping", data=polar_data, units=("mm", "rad", "signal"), labels=("Radius", "Angle", "Amplitude"), ) polar_image.set_coords(xcoords=r_coords, ycoords=theta_coords) print("\n✓ Polar coordinate example created!") print(f"Radial range: {r_coords[0]:.1f} to {r_coords[-1]:.1f} mm") print(f"Angular range: {theta_coords[0]:.2f} to {theta_coords[-1]:.2f} rad") # Display the specialized examples view_images_side_by_side( [spectral_image, polar_image], ["Time-Resolved Spectroscopy (Log λ)", "Polar Coordinates"], title="Specialized Non-Uniform Coordinate Examples", share_axes=False, ) # %% # Summary and best practices # -------------------------- # Let's summarize when to use each coordinate system type. print("\n" + "=" * 60) print("COORDINATE SYSTEMS SUMMARY") print("=" * 60) print("\n🔲 UNIFORM COORDINATES:") print(" ✓ Regular imaging systems (cameras, microscopes)") print(" ✓ Constant pixel spacing in physical units") print(" ✓ Simple and memory-efficient") print(" ✓ Fast computations and interpolations") print(" ✓ Easy integration with standard image processing") print("\n🔳 NON-UNIFORM COORDINATES:") print(" ✓ Adaptive sampling systems") print(" ✓ Curved or distorted coordinate systems") print(" ✓ Logarithmic or specialized scales") print(" ✓ Irregular measurement grids") print(" ✓ Coordinate transformations (polar to Cartesian)") print("\n📊 PERFORMANCE CONSIDERATIONS:") print(" • Uniform: O(1) coordinate lookup") print(" • Non-uniform: O(n) coordinate lookup") print(" • Memory: Uniform uses 4 parameters, Non-uniform uses 2×N arrays") print("\n💾 FILE FORMAT SUPPORT:") print(" • Both coordinate types supported in Sigima HDF5 format") print(" • Coordinated text format supports non-uniform coordinates") print(" • Standard image formats (TIFF, etc.) assume uniform coordinates") # Final comparison view view_images_side_by_side( [uniform_image, nonuniform_image, spectral_image, polar_image], [ "Uniform\n(Regular Grid)", "Non-Uniform\n(Variable Grid)", "Time-Resolved\n(Log Wavelength)", "Polar\n(Radial Data)", ], title="Complete Coordinate Systems Overview", share_axes=False, ) print("\n✨ Example completed successfully!") print("This demonstrates the flexibility of Sigima's coordinate system support.") Sigima-1.1.1/doc/examples/features/datalab_client.py000066400000000000000000000032261514013333200224220ustar00rootroot00000000000000""" DataLab remote control example ============================== Example of remote control of DataLab current session, from a Python script running outside DataLab (e.g. in Spyder) This example demonstrates how to control DataLab remotely using the SimpleRemoteProxy from Sigima. The script can be run from any Python environment outside of DataLab to interact with an active DataLab session. .. note:: This example is not executed during documentation build as it requires an active DataLab session to connect to. It is included in the gallery for reference and can be run manually when DataLab is running. """ # %% Importing necessary modules # NumPy for numerical array computations: import numpy as np # DataLab remote control client: from sigima.client import SimpleRemoteProxy as RemoteProxy # %% Connecting to DataLab current session proxy = RemoteProxy(autoconnect=False) proxy.connect(timeout=0.0, retries=1) # No timeout for rapid failure if not running # %% Executing commands in DataLab (...) z = np.random.rand(20, 20) proxy.add_image("toto", z) # %% Executing commands in DataLab (...) proxy.toggle_auto_refresh(False) # Turning off auto-refresh x = np.array([1.0, 2.0, 3.0]) y = np.array([4.0, 5.0, -1.0]) proxy.add_signal("toto", x, y) # %% Executing commands in DataLab (...) proxy.calc("derivative") proxy.toggle_auto_refresh(True) # Turning on auto-refresh # %% Executing commands in DataLab (...) proxy.set_current_panel("image") # %% Executing a lot of commands without refreshing DataLab z = np.random.rand(400, 400) proxy.add_image("foobar", z) with proxy.context_no_refresh(): for _idx in range(100): proxy.calc("fft") Sigima-1.1.1/doc/examples/features/datetime_signals.py000066400000000000000000000204371514013333200230130ustar00rootroot00000000000000""" DateTime Signal Processing ========================== This example demonstrates how to work with signals that have datetime X-axis data in Sigima. DateTime support is essential for time-series analysis where you need to preserve human-readable timestamps while performing signal processing. The example shows: * Creating signals from datetime objects and strings * Using different time units (hours, minutes, seconds, milliseconds, etc.) * Visualizing datetime signals with proper time formatting * CSV I/O with datetime preservation * Roundtrip testing across all supported time units This tutorial uses PlotPy for visualization, providing interactive plots with properly formatted datetime axes. """ # %% # Importing necessary modules # --------------------------- # We'll start by importing all the required modules for datetime signal processing # and visualization. import tempfile from datetime import datetime, timedelta from pathlib import Path import numpy as np from sigima.io.signal.formats import CSVSignalFormat from sigima.objects import SignalObj, create_signal from sigima.objects.signal.constants import TIME_UNIT_FACTORS, VALID_TIME_UNITS from sigima.viz import view_curves # %% # Creating datetime signals from datetime objects # ----------------------------------------------- # The most common way to create datetime signals is from Python datetime objects. # This is useful when you have timestamps from sensors, logs, or other time-series data. # Create a temperature monitoring signal with second-resolution timestamps base_time = datetime(2025, 10, 7, 10, 0, 0) timestamps = [base_time + timedelta(seconds=i * 10) for i in range(100)] # Simulate temperature data with daily variation and noise hours_elapsed = np.arange(100) * 10 / 3600 # Convert to hours temperature = ( 20 + 5 * np.sin(2 * np.pi * hours_elapsed / 24) + np.random.randn(100) * 0.5 ) # Create the signal with datetime X-axis temp_signal = create_signal("Temperature Monitor") temp_signal.set_x_from_datetime(timestamps, unit="s", format_str="%H:%M:%S") temp_signal.y = temperature temp_signal.ylabel = "Temperature" temp_signal.yunit = "°C" print("✓ Temperature signal created successfully!") print(f"Is datetime signal: {temp_signal.is_x_datetime()}") print(f"Time unit: {temp_signal.xunit}") print(f"First timestamp: {temp_signal.get_x_as_datetime()[0]}") print(f"Last timestamp: {temp_signal.get_x_as_datetime()[-1]}") # Visualize the temperature signal view_curves( temp_signal, title="Temperature Monitoring Over Time", object_name="datetime_temperature", ) # %% # Creating datetime signals from string timestamps # ------------------------------------------------ # Often, datetime data comes as strings (e.g., from CSV files or logs). # Sigima can automatically parse common datetime string formats. # Pressure monitoring with minute-resolution string timestamps date_strings = [ "2025-10-07 10:00:00", "2025-10-07 10:05:00", "2025-10-07 10:10:00", "2025-10-07 10:15:00", "2025-10-07 10:20:00", "2025-10-07 10:25:00", "2025-10-07 10:30:00", ] # Simulate atmospheric pressure readings pressure = np.array([1013.25, 1013.20, 1013.15, 1013.10, 1013.18, 1013.22, 1013.25]) pressure_signal = create_signal("Atmospheric Pressure") pressure_signal.set_x_from_datetime(date_strings, unit="min", format_str="%H:%M:%S") pressure_signal.y = pressure pressure_signal.ylabel = "Pressure" pressure_signal.yunit = "hPa" print("\n✓ Pressure signal created from strings!") print(f"Number of readings: {len(pressure_signal.y)}") print(f"Pressure range: {pressure.min():.2f} - {pressure.max():.2f} hPa") # Visualize the pressure signal view_curves( pressure_signal, title="Atmospheric Pressure Readings", object_name="datetime_pressure", ) # %% # Using different time units # -------------------------- # Sigima supports various time units to match your data's natural resolution: # nanoseconds (ns), microseconds (us), milliseconds (ms), seconds (s), # minutes (min), and hours (h). print(f"\n✓ Supported time units: {', '.join(VALID_TIME_UNITS)}") print("\nConversion factors to seconds:") for unit, factor in TIME_UNIT_FACTORS.items(): print(f" 1 {unit:>3s} = {factor:>10.1e} seconds") # Create hourly temperature cycle (24 hours) hourly_base = datetime(2025, 10, 7, 0, 0, 0) hourly_times = [hourly_base + timedelta(hours=i) for i in range(24)] daily_temp = 15 + 8 * np.sin(2 * np.pi * (np.arange(24) - 6) / 24) hourly_signal = SignalObj() hourly_signal.set_x_from_datetime(hourly_times, unit="h", format_str="%H:%M") hourly_signal.y = daily_temp hourly_signal.title = "Daily Temperature Cycle" hourly_signal.ylabel = "Temperature" hourly_signal.yunit = "°C" print("\n✓ Hourly signal created!") print(f" Time unit: {hourly_signal.xunit}") print(f" X-axis spacing: {np.diff(hourly_signal.x)[0]:.1f} hours") print(f" Temperature range: {daily_temp.min():.1f}°C to {daily_temp.max():.1f}°C") # Visualize the daily cycle view_curves( hourly_signal, title="24-Hour Temperature Cycle", object_name="datetime_hourly", ) # %% # Comparing multiple datetime signals # ----------------------------------- # You can visualize multiple datetime signals together to compare trends. # Create three signals at different time scales minute_base = datetime(2025, 10, 7, 14, 0, 0) minute_times = [minute_base + timedelta(minutes=i) for i in range(60)] # Heart rate over 1 hour heart_rate = 70 + 10 * np.sin(2 * np.pi * np.arange(60) / 60) + 2 * np.random.randn(60) hr_signal = SignalObj() hr_signal.set_x_from_datetime(minute_times, unit="min") hr_signal.y = heart_rate hr_signal.title = "Heart Rate" hr_signal.ylabel = "Heart Rate" hr_signal.yunit = "bpm" # Steps per minute steps = 80 + 20 * np.sin(2 * np.pi * np.arange(60) / 30) + 5 * np.random.randn(60) steps = np.clip(steps, 0, None) # No negative steps steps_signal = SignalObj() steps_signal.set_x_from_datetime(minute_times, unit="min") steps_signal.y = steps steps_signal.title = "Steps Per Minute" steps_signal.ylabel = "Steps" steps_signal.yunit = "steps/min" print("\n✓ Created multiple signals for comparison!") print(f" Heart rate avg: {heart_rate.mean():.1f} bpm") print(f" Steps avg: {steps.mean():.1f} steps/min") # Visualize multiple signals together view_curves( [hr_signal, steps_signal], title="Exercise Monitoring - Multiple Signals", object_name="datetime_multi", ) # %% # CSV I/O with datetime preservation # ---------------------------------- # Sigima automatically preserves datetime information when writing to CSV, # storing timestamps as human-readable strings instead of opaque float values. # Write temperature signal to CSV (using temporary directory) temp_dir = tempfile.mkdtemp(prefix="sigima_") csv_file = Path(temp_dir) / "temp_data.csv" fmt = CSVSignalFormat() fmt.write(str(csv_file), temp_signal) print(f"\n✓ Saved datetime signal to CSV: {csv_file}") print(" CSV Preview (first 5 lines):") with open(csv_file, "r", encoding="utf-8") as f: for i, line in enumerate(f): if i < 5: print(f" {line.rstrip()}") else: break # Read it back and verify loaded_signals = fmt.read(str(csv_file)) loaded_signal = loaded_signals[0] # Verify datetime preservation dt_original = temp_signal.get_x_as_datetime() dt_loaded = loaded_signal.get_x_as_datetime() data_matches = np.allclose(loaded_signal.y, temp_signal.y) time_matches = np.all(dt_original == dt_loaded) print("\n✓ Loaded signal from CSV successfully!") print(f" Is datetime: {loaded_signal.is_x_datetime()}") print(f" Data preserved: {data_matches}") print(f" Timestamps preserved: {time_matches}") # %% # Summary # ------- # This example demonstrated the complete datetime signal workflow in Sigima: # # 1. **Creating datetime signals** from objects and strings # 2. **Multiple time units** (ns, us, ms, s, min, h) stored in `xunit` attribute # 3. **Visualization** with properly formatted datetime axes # 4. **CSV I/O** with automatic datetime preservation # # The time unit is stored in the signal's `xunit` attribute, making it easy # to access and consistent with other signal metadata. DateTime support makes # Sigima ideal for time-series analysis, sensor data processing, and any # application requiring human-readable temporal information. print("\n" + "=" * 70) print("✓ DateTime Signal Processing Example Completed Successfully!") print("=" * 70) Sigima-1.1.1/doc/examples/features/roi_grid.py000066400000000000000000000222211514013333200212660ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ ROI Grid Generation =================== This example focuses on generating grids of rectangular ROIs for systematic analysis of regular patterns in images using Sigima's ROI grid feature. Using a real laser spot array image, we'll explore how to create, configure, and apply ROI grids for extracting individual spots. The example shows: * Loading a real-world laser spot array image * Extracting a sub-region for clearer visualization * Generating a grid of rectangular ROIs * Configuring grid parameters (size, translation, step spacing) * Understanding direction labels (row/column ordering) * Extracting individual spots using the generated ROIs * Visualizing the ROIs on the image This tutorial uses PlotPy for visualization, providing interactive plots that allow you to explore the ROI grid placement in detail. """ # %% # Importing necessary modules # --------------------------- # We'll start by importing all the required modules for image processing # and visualization. from copy import deepcopy from sigima import viz from sigima.io import read_image from sigima.objects import RectangularROI from sigima.proc.image.extraction import ( Direction, ROIGridParam, extract_roi, generate_image_grid_roi, ) from sigima.tests import helpers # %% # Loading a real laser spot array image # ------------------------------------- # We'll use a laser spot array image with a 6×6 grid of spots. # This is a realistic example where we need to analyze each spot individually. # Load the laser spot array test image filename = helpers.get_test_fnames("laser_spot_array.png", in_folder="image_formats")[0] full_image = read_image(filename) full_image.title = "Laser Spot Array (6×6)" print("✓ Laser spot array image loaded!") print(f"Image dimensions: {full_image.width} × {full_image.height} pixels") print(f"Data type: {full_image.data.dtype}") # %% # Extracting a 2×2 sub-region # --------------------------- # For clearer visualization of the ROI grid feature, we'll extract # a 2×2 sub-region from the center of the full 6×6 spot array. # Define a ROI to extract the central 2×2 spots # The spots are roughly evenly distributed, so we calculate the region cell_width = full_image.width / 6 cell_height = full_image.height / 6 # Extract spots from row 3-4 and column 3-4 (0-indexed: rows 2-3, cols 2-3) x0 = cell_width * 2.0 # Start between column 2 and 3 y0 = cell_height * 2.0 # Start between row 2 and 3 roi_width = cell_width * 2 # 2 columns roi_height = cell_height * 2 # 2 rows # Create ROI and extract the sub-region extraction_roi = RectangularROI([x0, y0, roi_width, roi_height], indices=False) laser_image = extract_roi(full_image, extraction_roi.to_param(full_image, 0)) laser_image.title = "2×2 Spot Sub-region" print("\n✓ Extracted 2×2 sub-region!") print( f"Sub-region dimensions: {laser_image.width:.0f} × {laser_image.height:.0f} pixels" ) # Display both images viz.view_images_side_by_side( [full_image, laser_image], ["Full 6×6 Array", "Extracted 2×2 Sub-region"], title="Extracting a Sub-region for Analysis", share_axes=False, ) # %% # Creating a basic grid of ROIs # ----------------------------- # Now we'll generate a 2×2 grid of ROIs to match the extracted spot array. # Each ROI will be centered on a spot for individual analysis. # Configure ROI grid parameters param = ROIGridParam() param.nx = param.ny = 2 # 2×2 grid to match the spots param.xsize = param.ysize = 75 # Each ROI covers 75% of the cell size param.xtranslation = param.ytranslation = 50 # Centered (50% = center) param.xstep = param.ystep = 100 # 100% = evenly distributed grid param.xdirection = param.ydirection = Direction.INCREASING param.base_name = "Spot" param.name_pattern = "{base}({r},{c})" # Generate the ROI grid (this doesn't modify the source image) roi_grid = generate_image_grid_roi(laser_image, param) # Assign ROIs to a copy of the image for visualization image_with_roi = laser_image.copy() image_with_roi.roi = roi_grid image_with_roi.title = "2×2 ROI Grid" print(f"\n✓ Generated {len(list(roi_grid))} rectangular ROIs!") print("ROI titles:", [r.title for r in list(roi_grid)]) # Display image with ROI overlay viz.view_images_side_by_side( [laser_image, image_with_roi], ["2×2 Spot Array", "With ROI Grid"], title="Basic ROI Grid (2×2, Centered)", ) # %% # Extracting individual spots # --------------------------- # Once the ROI grid is defined, we can extract individual spots # as separate images for further analysis. # Extract a few spots as individual images extracted_spots = [] for i, roi_item in enumerate(roi_grid): if i >= 4: # Extract first 4 spots for demonstration break roi_param = roi_item.to_param(laser_image, 0) spot_image = extract_roi(laser_image, roi_param) spot_image.title = roi_item.title extracted_spots.append(spot_image) print(f"\n✓ Extracted {len(extracted_spots)} individual spot images!") for spot in extracted_spots: print(f" - {spot.title}: {spot.width}×{spot.height} pixels") # Display extracted spots viz.view_images_side_by_side( extracted_spots, [spot.title for spot in extracted_spots], title="Extracted Individual Spots", share_axes=False, rows=2, ) # %% # Adjusting ROI size and position # ------------------------------- # The ROI size and translation parameters control how the ROIs are placed # within each grid cell. Let's explore different configurations. # Configuration 1: Larger ROIs (90% of cell size) param_large = deepcopy(param) param_large.xsize = param_large.ysize = 90 image_large = laser_image.copy() image_large.roi = generate_image_grid_roi(laser_image, param_large) image_large.title = "Large ROIs (90%)" # Configuration 2: Smaller ROIs (40% of cell size) param_small = deepcopy(param) param_small.xsize = param_small.ysize = 40 image_small = laser_image.copy() image_small.roi = generate_image_grid_roi(laser_image, param_small) image_small.title = "Small ROIs (40%)" # Configuration 3: Shifted position (translation offset) param_shifted = deepcopy(param) param_shifted.xtranslation = 60 # Shift right by 10% param_shifted.ytranslation = 40 # Shift up by 10% image_shifted = laser_image.copy() image_shifted.roi = generate_image_grid_roi(laser_image, param_shifted) image_shifted.title = "Shifted ROIs" print("\n✓ Generated ROI grids with different configurations!") print(" - Large ROIs: 90% of cell size") print(" - Small ROIs: 40% of cell size") print(" - Shifted ROIs: offset by 10% in X and Y") # Display the different configurations viz.view_images_side_by_side( [image_with_roi, image_large, image_small, image_shifted], ["Default (75%)", "Large (90%)", "Small (40%)", "Shifted (+10%)"], title="ROI Size and Position Variations", ) # %% # Understanding direction labels # ------------------------------ # The xdirection and ydirection parameters control how rows and columns # are numbered. This affects the ROI titles but not the geometry. # Increasing direction (default): row 1 at top, column 1 at left param_inc = deepcopy(param) param_inc.xdirection = param_inc.ydirection = Direction.INCREASING image_inc = laser_image.copy() image_inc.roi = generate_image_grid_roi(laser_image, param_inc) image_inc.title = "Increasing (R1 top, C1 left)" # Decreasing direction: row 1 at bottom, column 1 at right param_dec = deepcopy(param) param_dec.xdirection = param_dec.ydirection = Direction.DECREASING image_dec = laser_image.copy() image_dec.roi = generate_image_grid_roi(laser_image, param_dec) image_dec.title = "Decreasing (R1 bottom, C1 right)" # Show the first few ROI titles for comparison roi_inc = generate_image_grid_roi(laser_image, param_inc) roi_dec = generate_image_grid_roi(laser_image, param_dec) print("\n✓ Direction affects ROI labeling, not geometry!") print("Increasing direction (first 4 ROIs):", [r.title for r in list(roi_inc)[:4]]) print("Decreasing direction (first 4 ROIs):", [r.title for r in list(roi_dec)[:4]]) # Display direction variations viz.view_images_side_by_side( [image_inc, image_dec], ["Increasing Direction", "Decreasing Direction"], title="ROI Direction Labels", ) # %% # Summary and conclusions # ----------------------- # This tutorial demonstrated the key concepts of ROI grid generation # for systematic analysis of regular patterns in images using Sigima. print("\n" + "=" * 60) print("ROI GRID TUTORIAL SUMMARY") print("=" * 60) print("✓ Loaded real-world laser spot array image") print("✓ Generated grids of rectangular ROIs") print("✓ Configured grid parameters (size, translation, step spacing)") print("✓ Explored direction labels (row/column ordering)") print("✓ Extracted individual spots using generated ROIs") print("✓ Visualized ROIs overlaid on images") print("\nKey Takeaways:") print("• Grid dimensions (nx, ny) define the number of rows and columns") print("• ROI size (xsize, ysize) controls the coverage as percentage of cell size") print("• Translation (xtranslation, ytranslation) offsets position within cells") print("• Direction (xdirection, ydirection) controls row/column numbering order") print( "• ROI grids are ideal for analyzing arrays of spots, sensors, or regular patterns" ) Sigima-1.1.1/doc/examples/features/zero_padding.py000066400000000000000000000122141514013333200221360ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Zero Padding for FFT Enhancement ================================= This example demonstrates how to apply zero-padding to signals, a common technique used to improve FFT frequency resolution. It shows the proper usage of :class:`sigima.params.ZeroPadding1DParam`, including the important ``update_from_obj()`` call. Zero-padding adds zeros to a signal, effectively interpolating the frequency domain representation. This is particularly useful for: - Improving frequency resolution in FFT analysis - Preparing signals for convolution operations - Matching signal lengths for spectral comparisons """ # %% # Importing the required modules # ------------------------------ import numpy as np import sigima.params import sigima.proc.signal as sips from sigima import viz from sigima.objects import create_signal # %% # Create a test signal # -------------------- # We create a simple cosine signal with a specific frequency. # Signal parameters freq = 50.0 # Hz duration = 0.1 # seconds sample_rate = 1000 # Hz n_points = int(duration * sample_rate) # Create time array and signal t = np.linspace(0, duration, n_points, endpoint=False) y = np.cos(2 * np.pi * freq * t) signal = create_signal( title=f"Cosine {freq} Hz", x=t, y=y, units=("s", "V"), labels=("Time", "Amplitude") ) print(f"Original signal: {n_points} points") viz.view_curves(signal, title="Original Signal") # %% # Zero-padding with "next_pow2" strategy # -------------------------------------- # # The "next_pow2" strategy pads the signal to the next power of 2, which is # optimal for FFT computations. # # .. important:: # # When using strategies other than "custom", you **must call** # ``update_from_obj()`` to compute the number of padding points based on # the actual signal size. # Create the parameter with "next_pow2" strategy param = sigima.params.ZeroPadding1DParam.create(strategy="next_pow2") # At this point, param.n is still the default value (1) print(f"Before update_from_obj: n = {param.n}") # IMPORTANT: Update parameters from the signal to compute the actual 'n' param.update_from_obj(signal) # Now param.n has been computed based on the signal size print( f"After update_from_obj: n = {param.n} " f"(signal will be padded to {n_points + param.n} points)" ) # Apply zero-padding padded_signal = sips.zero_padding(signal, param) padded_size = padded_signal.y.size power_of_2 = 2 ** int(np.log2(padded_size)) print(f"Padded signal: {padded_size} points (power of 2: {power_of_2})") # %% # Compare original and padded signals # ----------------------------------- # The padded signal has zeros appended at the end. viz.view_curves([signal, padded_signal], title="Original vs Zero-Padded Signal") # %% # FFT comparison: improved frequency resolution # --------------------------------------------- # Zero-padding improves the apparent frequency resolution of the FFT by # interpolating between frequency bins. # Compute FFT of original signal fft_original = sips.fft(signal) fft_original.title = f"FFT Original ({fft_original.y.size} bins)" # Compute FFT of padded signal fft_padded = sips.fft(padded_signal) fft_padded.title = f"FFT Zero-Padded ({fft_padded.y.size} bins)" print(f"Original FFT: {fft_original.y.size} frequency bins") print(f"Padded FFT: {fft_padded.y.size} frequency bins") viz.view_curves([fft_original, fft_padded], title="FFT: Original vs Zero-Padded") # %% # Using different strategies # -------------------------- # The available strategies are: # # - ``"next_pow2"``: Pad to the next power of 2 (optimal for FFT) # - ``"double"``: Double the signal length # - ``"triple"``: Triple the signal length # - ``"custom"``: Specify the exact number of points to add for strategy in ["next_pow2", "double", "triple"]: param = sigima.params.ZeroPadding1DParam.create(strategy=strategy) param.update_from_obj(signal) print(f"Strategy '{strategy}': adds {param.n} points → total {n_points + param.n}") # %% # Using "custom" strategy # ----------------------- # With the "custom" strategy, you specify the exact number of points. # In this case, ``update_from_obj()`` is not strictly necessary (but harmless). param_custom = sigima.params.ZeroPadding1DParam.create(strategy="custom", n=500) print(f"Custom strategy: adds {param_custom.n} points") padded_custom = sips.zero_padding(signal, param_custom) print(f"Result: {padded_custom.y.size} points") # %% # Choosing padding location # ------------------------- # Zero-padding can be applied at different locations: # # - ``"append"``: Add zeros at the end (default) # - ``"prepend"``: Add zeros at the beginning # - ``"both"``: Split zeros between beginning and end from sigima.enums import PadLocation1D results = [] for location in PadLocation1D: param = sigima.params.ZeroPadding1DParam.create(strategy="double") param.location = location param.update_from_obj(signal) result = sips.zero_padding(signal, param) result.title = f"Padded ({location.value})" results.append(result) print(f"Location '{location.value}': x=[{result.x[0]:.4f}, {result.x[-1]:.4f}]") viz.view_curves(results, title="Padding Location Comparison") Sigima-1.1.1/doc/examples/getting_started/000077500000000000000000000000001514013333200204705ustar00rootroot00000000000000Sigima-1.1.1/doc/examples/getting_started/README.txt000066400000000000000000000000401514013333200221600ustar00rootroot00000000000000Getting Started --------------- Sigima-1.1.1/doc/examples/getting_started/image_creation.py000066400000000000000000000133641514013333200240170ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Creating Images =============== This example focuses on creating 2D image objects in Sigima. There are three primary methods to create images in Sigima: 1. **Synthetic data generation**: Using built-in parameter classes to create standard image types (Gaussian, ramp, random distributions, etc.) 2. **Loading from files**: Importing data from various file formats 3. **From NumPy arrays**: Creating objects directly from existing arrays Each method has its use cases, and Sigima provides a consistent interface for working with data regardless of its origin. For visualization, we use helper functions from the ``sigima.viz`` module. This allows us to focus on Sigima's functionality rather than visualization details. """ # %% # Importing necessary modules # --------------------------- # First of all, we need to import the required modules. import numpy as np import sigima from sigima import viz from sigima.tests import helpers # %% # Method 1: Creating images from synthetic parameters # ---------------------------------------------------- # # Similar to signals, Sigima can generate synthetic images using parameter classes. # # Available image types include: # # - Distributions: Normal (Gaussian noise), Uniform, Poisson # - Analytical functions: 2D Gaussian, 2D ramp (bilinear form) # - Blank images: Zeros # Create a 2D Gaussian image gaussian_param = sigima.create_image_parameters( sigima.ImageTypes.GAUSS, title="Synthetic 2D Gaussian", height=300, width=300, xlabel="X Position", ylabel="Y Position", zlabel="Intensity", xunit="µm", yunit="µm", zunit="counts", x0=0.0, # Center x position y0=0.0, # Center y position sigma=1.5, # Width a=1000.0, # Amplitude ) gaussian_img = sigima.create_image_from_param(gaussian_param) # Create a ramp image (gradient) ramp_param = sigima.create_image_parameters( sigima.ImageTypes.RAMP, title="Synthetic 2D Ramp", height=200, width=200, xlabel="X Position", ylabel="Y Position", zlabel="Value", xunit="mm", yunit="mm", zunit="a.u.", x0=-5.0, y0=-5.0, a=0.5, # X slope b=0.3, # Y slope ) ramp_img = sigima.create_image_from_param(ramp_param) print("\n✓ Synthetic images created") print(f" - {gaussian_img.title}: {gaussian_img.data.shape}") print(f" - {ramp_img.title}: {ramp_img.data.shape}") # Visualize synthetic images viz.view_images_side_by_side([gaussian_img, ramp_img], title="Synthetic Images") # %% # Method 2: Loading images from files # ------------------------------------ # # Sigima supports a wide range of image file formats, both common and scientific. # # Supported formats include: # # - Common formats: BMP, JPEG, PNG, TIFF, JPEG 2000 # - Scientific formats: DICOM, Andor SIF, Spiricon, Dürr NDT # - Data formats: NumPy (.npy), MATLAB (.mat), HDF5 (.h5img) # - Text formats: CSV, TXT, ASC (with coordinate support) # Load an image from a JPEG file filename = helpers.get_test_fnames("fiber.jpg")[0] img_jpeg = sigima.read_image(filename) img_jpeg.title = "Fiber Image (from JPEG)" # Load an image from a NumPy file filename = helpers.get_test_fnames("flower.npy")[0] img_npy = sigima.read_image(filename) img_npy.title = "Test Image (from NumPy)" print("\n✓ Images loaded from files") print(f" - {img_jpeg.title}: {img_jpeg.data.shape}") print(f" - {img_npy.title}: {img_npy.data.shape}") # Visualize images loaded from files viz.view_images_side_by_side([img_jpeg, img_npy], title="Images from Files") # %% # Method 3: Creating images from NumPy arrays # -------------------------------------------- # # Convert existing NumPy arrays into Sigima image objects to add metadata, # coordinate systems, and enable advanced processing. # Create a synthetic pattern: interference fringes size = 256 x = np.linspace(-10, 10, size) y = np.linspace(-10, 10, size) X, Y = np.meshgrid(x, y) # Interference pattern pattern = np.cos(2 * np.pi * X / 3) * np.cos(2 * np.pi * Y / 3) pattern = ((pattern + 1) / 2 * 255).astype(np.uint8) img_interf = sigima.create_image( title="Interference Pattern (from array)", data=pattern, units=("mm", "mm", "intensity"), labels=("X", "Y", "Signal"), ) # Create another image: radial gradient with noise radial = np.exp(-(X**2 + Y**2) / 20) rng = np.random.default_rng(123) radial = radial + rng.normal(0, 0.05, radial.shape) radial = np.clip(radial, 0, 1) img_radial = sigima.create_image( title="Radial Gradient (from array)", data=radial.astype(np.float32), units=("µm", "µm", "a.u."), labels=("X", "Y", "Amplitude"), ) print("\n✓ Images created from NumPy arrays") print(f" - {img_interf.title}: {img_interf.data.shape}") print(f" - {img_radial.title}: {img_radial.data.shape}") # Visualize images created from NumPy arrays viz.view_images_side_by_side([img_interf, img_radial], title="Images from Arrays") # %% # Summary # ------- # # This example demonstrated the three main ways to create images in Sigima: # # 1. **Synthetic generation**: Fast creation of standard mathematical functions and # distributions using parameter classes. Perfect for testing and simulation. # # 2. **File loading**: Read data from various scientific and common file formats, # with automatic format detection and metadata extraction. Essential for working # with experimental data. # # 3. **NumPy array conversion**: Wrap existing array data with Sigima's rich metadata # and processing capabilities. Ideal for custom workflows and integration with # other Python libraries. # # All three methods produce equivalent Sigima objects that can be processed, analyzed, # and visualized using the same set of tools and functions. Choose the method that # best fits your workflow and data source. Sigima-1.1.1/doc/examples/getting_started/signal_creation.py000066400000000000000000000167441514013333200242170ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Creating Signals ================ This example focuses on creating 1D signal objects in Sigima. There are three primary methods to create signals in Sigima: 1. **Synthetic data generation**: Using built-in parameter classes to create standard signal types (Gaussian, sine waves, random distributions, etc.) 2. **Loading from files**: Importing data from various file formats 3. **From NumPy arrays**: Creating objects directly from existing arrays Each method has its use cases, and Sigima provides a consistent interface for working with data regardless of its origin. For visualization, we use helper functions from the ``sigima.viz`` module. This allows us to focus on Sigima's functionality rather than visualization details. """ # %% # Importing necessary modules # --------------------------- # First of all, we need to import the required modules. from pprint import pprint # For pretty-printing metadata import numpy as np import sigima from sigima import viz from sigima.tests import helpers # %% # Method 1: Creating signals from synthetic parameters # ---------------------------------------------------- # # Sigima provides built-in generators for common signal types. This is the most # convenient method when you need standard mathematical functions or random # distributions. # # Available signal types include: # # - Mathematical functions: Gaussian, Lorentzian, Sinc, Sine, Cosine, etc. # - Random distributions: Normal, Uniform, Poisson # - Standard waveforms: Square, Sawtooth, Triangle # - Special functions: Planck (blackbody), Linear chirp, Step, Exponential # Let's consider a spectroscopy context, where we often deal with Gaussian and # Lorentzian peaks representing absorption and emission lines. # # Create a Gaussian signal: this represents an absorption peak in spectroscopy. gaussian_param = sigima.create_signal_parameters( sigima.SignalTypes.GAUSS, # Type of signal to create title="Absorption Peak", size=500, # Number of points xlabel="Wavelength", ylabel="Absorbance", xunit="nm", yunit="a.u.", xmin=400.0, # Minimum x value (wavelength) xmax=700.0, # Maximum x value a=2.5, # Amplitude mu=550.0, # Center wavelength (green light) sigma=25.0, # Peak width ) signal_synthetic = sigima.create_signal_from_param(gaussian_param) # Create a Lorentzian signal representing a different spectral line: this represents an # emission line in atomic emission spectroscopy. lorentzian_param = sigima.create_signal_parameters( sigima.SignalTypes.LORENTZ, title="Emission Line", size=500, xlabel="Wavelength", ylabel="Intensity", xunit="nm", yunit="a.u.", xmin=400.0, xmax=700.0, a=1.8, # Amplitude mu=480.0, # Center wavelength (blue light) sigma=15.0, # Peak width ) signal_lorentzian = sigima.create_signal_from_param(lorentzian_param) print("✓ Synthetic signals created") print(f" - {signal_synthetic.title}: {signal_synthetic.y.shape[0]} points") print(f" - {signal_lorentzian.title}: {signal_lorentzian.y.shape[0]} points") # Visualize synthetic signals viz.view_curves( [signal_synthetic, signal_lorentzian], title="Method 1: Synthetic Signals" ) # %% # Method 2: Loading signals from files # ------------------------------------ # # Sigima can read signals from various file formats, automatically detecting the # format and extracting metadata when available. # # Supported formats include: # # - Text files: CSV, TXT (with automatic delimiter detection) # - Scientific formats: HDF5 (.h5sig), MAT-Files (.mat), NumPy (.npy) # - Specialized: MCA spectrum files (.mca), FT-Lab (.sig) # Load a real spectrum from a text file # This is a paracetamol (acetaminophen) UV-Vis absorption spectrum filename = helpers.get_test_fnames("paracetamol.txt")[0] signal_from_file = sigima.read_signal(filename) # Visualize signal loaded from text file viz.view_curves(signal_from_file, title="Signal from Text File") # Load another signal from a CSV file with multiple curves csv_file = helpers.get_test_fnames("oscilloscope.csv")[0] signals_from_csv = sigima.read_signals(csv_file) # CSV files contain multiple signals; we'll show one signal_from_csv = signals_from_csv[1] # Visualize signal loaded from csv file viz.view_curves(signal_from_csv, title="Signal from CSV File") print("\n✓ Signals loaded from files") print(f" - {signal_from_file.title}: {signal_from_file.y.shape[0]} points") print(f" - {signal_from_csv.title}: {signal_from_csv.y.shape[0]} points") # %% # It is interesting to remark here that when importing data from files, # Sigima automatically extracts and preserves metadata when possible. # This includes: # # - **Axis labels and units**: Column headers from CSV files, variable names from # MAT-Files, etc. # - **Acquisition parameters**: DICOM headers, instrument settings, timestamps # - **Physical coordinates**: Pixel spacing, origin coordinates when stored in the file # # The extracted metadata is seamlessly integrated into the signal or image object, # making it available for processing, analysis, and visualization without manual # configuration. pprint(signal_from_csv.metadata) # %% # Method 3: Creating signals from NumPy arrays # --------------------------------------------- # # When you already have data in NumPy arrays (from calculations, other libraries, # or custom data sources), you can wrap them in Sigima signal objects to benefit # from metadata handling and processing functions. # Create custom data: a damped oscillation (e.g., RLC circuit response) t = np.linspace(0, 5, 1000) damping = np.exp(-0.5 * t) oscillation = np.sin(2 * np.pi * 3 * t) y_damped = damping * oscillation signal_from_array = sigima.create_signal( title="Damped Oscillation (from array)", x=t, y=y_damped, units=("s", "V"), labels=("Time", "Voltage"), ) # Create the envelope signal: upper and lower bounds of the oscillation # This is useful for analyzing the decay rate and quality factor y_envelope_upper = damping y_envelope_lower = -damping # We'll create a signal showing the upper envelope signal_envelope = sigima.create_signal( title="Decay Envelope (from array)", x=t, y=y_envelope_upper, units=("s", "V"), labels=("Time", "Amplitude"), ) print("\n✓ Signals created from NumPy arrays") print(f" - {signal_from_array.title}: {signal_from_array.y.shape[0]} points") print(f" - {signal_envelope.title}: {signal_envelope.y.shape[0]} points") # Visualize signals created from NumPy arrays viz.view_curves( [signal_from_array, signal_envelope], title="Method 3: Signals from NumPy Arrays", object_name="signals_from_arrays", ) # %% # Summary # ------- # # This example demonstrated the three main ways to create signals in Sigima: # # 1. **Synthetic generation**: Fast creation of standard mathematical functions and # distributions using parameter classes. Perfect for testing and simulation. # # 2. **File loading**: Read data from various scientific and common file formats, # with automatic format detection and metadata extraction. Essential for working # with experimental data. # # 3. **NumPy array conversion**: Wrap existing array data with Sigima's rich metadata # and processing capabilities. Ideal for custom workflows and integration with # other Python libraries. # # All three methods produce equivalent Sigima objects that can be processed, analyzed, # and visualized using the same set of tools and functions. Choose the method that # best fits your workflow and data source. Sigima-1.1.1/doc/examples/use_cases/000077500000000000000000000000001514013333200172535ustar00rootroot00000000000000Sigima-1.1.1/doc/examples/use_cases/README.txt000066400000000000000000000000241514013333200207450ustar00rootroot00000000000000Use Cases --------- Sigima-1.1.1/doc/examples/use_cases/blob_detection.py000066400000000000000000000152161514013333200226060ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Blob Detection ============== This example demonstrates blob detection techniques available in Sigima for analyzing circular or blob-like features in images. It shows how to generate apply preprocessing filters and detect blobs using OpenCV-based algorithms with fine-tuned parameters for optimal results. The script demonstrates image processing workflows commonly used in microscopy, particle analysis, and feature detection applications. """ # %% # Importing necessary modules # -------------------------------- # We start by importing all the required modules for image processing # and visualization. To run this example, ensure you have all the required # dependencies installed. import numpy as np import skimage.draw import sigima.objects import sigima.proc.image from sigima import viz # %% # Generate synthetic test image with known blobs # ------------------------------------------------ # We create a synthetic image with a noisy background and several # circular blobs of varying sizes and intensities. This allows us to # validate the blob detection algorithms effectively. # To perform this task, we use a function: the detailes of this is out of the scope # of this tutorial: once you have learned how to use Sigima, you will be able to # use the library on your own data. def generate_test_image() -> None: """Generate test image with randomly placed blobs.""" rng = np.random.default_rng(0) arr = rng.normal(10000, 1000, (2048, 2048)) for _ in range(10): row = rng.integers(0, arr.shape[0]) col = rng.integers(0, arr.shape[1]) rr, cc = skimage.draw.disk((row, col), 40, shape=arr.shape) arr[rr, cc] -= rng.integers(5000, 6000) icenter = arr.shape[0] // 2 rr, cc = skimage.draw.disk((icenter, icenter), 200, shape=arr.shape) arr[rr, cc] -= rng.integers(5000, 8000) data = np.clip(arr, 0, 65535).astype(np.uint16) # Create a new image object image = sigima.objects.create_image("Test image", data, units=("mm", "mm", "lsb")) return image original_image = generate_test_image() print("✓ Test image created successfully!") # %% # Visualize the original image # -------------------------------- # We visualize the original synthetic image to understand its characteristics # before applying any processing or blob detection. This can be done with your preferred # image viewer (i.e. plotpy, matplotlib, ...). # The preference of Sigima developers is on plotpy, a library developed # with performance in mind. # # We wrapped a simple function to do perform visualizations tasks required for this and # other tutorials, # to help reducing the impact of GUI code in documentation and let you concentrate in # the analysis viz.view_images([original_image], title="Original Test Image with Synthetic Blobs") # %% # Image preprocessing - Binning # ----------------------------------------- # Looking to our image, we can see that the blobs we look for are large respect to # the pixel size. A binning process can help to reduce the importance of the noise. binning_factor = 2 binned_image = sigima.proc.image.binning(original_image, binning_factor) print(f"\n✓ Binning applied with factor {binning_factor}") print(f"Original size: {original_image.data.shape}") print(f"Binned size: {binned_image.data.shape}") print("Binning reduces computational load and can improve blob detection") # Compare original and binned images viz.view_images_side_by_side( [original_image, binned_image], titles=["Original Image", "Binned Image (2x2)"], title="Image Binning Comparison", ) # %% # Additional preprocessing - Moving median filter # ------------------------------------------------- # The result of the binning is good, but we can imagine to not be happy with that. # A different approach we can take is to apply a moving median filter, to reduce the # importance of the spikes. We do it with a window of 5, of curse in practice different # window sizes can be tested to find the good compromise between noise reduction and # resolution. Lets see how to do that. filter_size = 5 filtered_image = sigima.proc.image.moving_median(binned_image, n=filter_size) print(f"\n✓ Moving median filter applied (window size: {filter_size})") # Show progression of preprocessing steps viz.view_images_side_by_side( [original_image, binned_image, filtered_image], titles=["Original", "Binned", "Median Filtered"], title="Image Preprocessing Pipeline", ) # %% # Configure blob detection parameters # ----------------------------------------- # We are happy with the filtered image, we can now proceed to the blob detection. # First of all we need to configure the parameters of the detection algorithm: this # is very important to get good results. In this example, you find an overview of the # parameters that can be tuned. # # Create blob detection parameter object: blob_param = sigima.proc.image.BlobOpenCVParam() # %% # Threshold parameters for blob detection: blob_param.min_threshold = 10 blob_param.max_threshold = 200 # %% # Minimum repeatability (how many times a blob center is detected): blob_param.min_repeatability = 2 # %% # Color filtering (not used for grayscale): blob_param.filter_by_color = False # %% # Area filtering to select appropriate blob sizes: blob_param.filter_by_area = True blob_param.min_area = 600.0 # Minimum area in pixels blob_param.max_area = 6000.0 # Maximum area in pixels # %% # Circularity filtering to prefer round objects: blob_param.filter_by_circularity = True blob_param.min_circularity = 0.8 # 0 = not circular, 1 = perfect circle blob_param.max_circularity = 1.0 # %% # Disable inertia and convexity filtering for this example: blob_param.filter_by_inertia = False blob_param.filter_by_convexity = False # %% # We finally print configured parameters: print("\n✓ Blob detection parameters configured:" + "\n") print(blob_param) # %% # Perform blob detection # ----------------------------------------- # We can now perform the blob detection on the preprocessed image using the # configured parameters. # Detect blobs in the preprocessed image blobs = sigima.proc.image.blob_opencv(filtered_image, blob_param) print("\n✓ Blob detection completed!") print(f" Number of blobs detected: {len(blobs.coords) if blobs else 0}") viz.view_images( [filtered_image], title="Filtered Image with Blob Detection", results=blobs, colormap="gray", ) # %% # We print the detected blobs and their properties: if blobs and len(blobs.coords) > 0: blobs_df = blobs.to_dataframe() print("\nDetected blobs data frame:") print(blobs_df) else: print("No blobs detected. Consider adjusting detection parameters.") Sigima-1.1.1/doc/examples/use_cases/fabry_perot.py000066400000000000000000000153441514013333200221500ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Fabry-Perot Interference Pattern ================================ This example demonstrates image processing techniques for analyzing Fabry-Perot interference patterns. It shows how to load experimental images, define regions of interest, detect circular contours, and extract intensity profiles for quantitative analysis of interference fringes. Usage: python fabry_perot_example.py The script demonstrates optical analysis workflows commonly used in interferometry, optical metrology, and precision measurements. """ # %% # Importing necessary modules # -------------------------------- # We start by importing all the required modules for image processing # and visualization. To run this example, ensure you have all the required # dependencies installed. import sigima.enums import sigima.objects import sigima.proc.image from sigima import viz from sigima.tests.data import get_test_image # %% # Load Fabry-Perot test images # -------------------------------- # We load two sample image of Fabry-Perot interference patterns. # These imags is included in the Sigima test data. We will analyze the # interference fringes present in these images. # Load the first Fabry-Perot test image img1 = get_test_image("fabry-perot1.jpg") print("✓ Successfully loaded fabry-perot1.jpg") print(f"Image dimensions: {img1.data.shape}") print(f"Data type: {img1.data.dtype}") print(f"Intensity range: {img1.data.min()} - {img1.data.max()}") # Visualize the original interference pattern viz.view_images(img1, title="Fabry-Perot Interference Pattern #1") # %% # Define circular ROI for fringe analysis # ------------------------------------------- # We define a circular region of interest (ROI) centered on the image # to focus our analysis on the central interference fringes. # Calculate image center center_x, center_y = 601, 559 roi_radius = 460 # Radius to capture the first few interference rings print(f"\n✓ Image center: ({center_x}, {center_y})") print(f"ROI radius: {roi_radius} pixels") print("This ROI focuses analysis on the central interference pattern") # Create circular ROI coordinates: roi_coords = [center_x, center_y, roi_radius] # Apply circular ROI to the image img1.roi = sigima.objects.create_image_roi("circle", roi_coords, indices=True) print("✓ Circular ROI applied to image") # Visualize image with ROI viz.view_images(img1, title="Fabry-Perot with Circular ROI") # %% # Configure contour detection for circular fringes # --------------------------------------------------- # We can now detect circular contours in the defined ROI. This will help us identify # the interference rings. To perform this, the first step is to set up the contour # detection parameter. # Set up contour shape detection parameter for circles contour_param = sigima.proc.image.ContourShapeParam() contour_param.shape = sigima.enums.ContourShape.CIRCLE contour_param.threshold = 0.5 # Threshold for fringe detection print("\n✓ Contour detection configured:") print(f"Shape: {contour_param.shape}") print(f"Threshold: {contour_param.threshold}") print("This will detect circular interference fringes") # %% # We can now perform the contour detection on the image using the # configured parameters. contour_results = sigima.proc.image.contour_shape(img1, contour_param) print("\n✓ Contour detection completed for first image") # %% # We can now print the detected circular contours and their properties print(f"Number of circular contours detected: {len(contour_results.coords)}") contour_df = contour_results.to_dataframe() print("\nDetected contours data frame:") print(contour_df) # %% # Extract horizontal intensity profile # ---------------------------------------- # We can extract an intensity profile along a horizontal line through the center # of the image. This profile will show the intensity variations across the # interference fringes. As before, we need to set up the line profile extraction # parameter. # Configure line profile extraction profile_param = sigima.proc.image.LineProfileParam() profile_param.direction = "horizontal" profile_param.row = center_y # Extract profile through image center print("\n✓ Horizontal profile configured:") print(f"Direction: {profile_param.direction}") print(f"Row: {profile_param.row} (image center)") # Extract intensity profile profile_signal1 = sigima.proc.image.line_profile(img1, profile_param) print(f"✓ Profile extracted: {len(profile_signal1.y)} data points") print(f"Intensity range: {profile_signal1.y.min():.1f} - {profile_signal1.y.max():.1f}") # Visualize the intensity profile viz.view_curves( [profile_signal1], title="Horizontal Intensity Profile - Image 1", xlabel="Position (pixels)", ylabel="Intensity", ) # %% # Load the second Fabry-Perot image # ---------------------------------------- # We want now to load the Analyze second Fabry-Perot image try: # Load second test image img2 = get_test_image("fabry-perot2.jpg") print("\n✓ Successfully loaded fabry-perot2.jpg") print(f"Image dimensions: {img2.data.shape}") # Copy ROI settings from first image img2.metadata = img1.metadata # This includes the ROI information # Visualize second image viz.view_images([img2], title="Fabry-Perot Interference Pattern #2") except Exception as exc: raise RuntimeError("Failed to load second Fabry-Perot test image.") from exc # %% # Contour detection on second image # ---------------------------------------- # To perform the contour detection on the second image, we can # reuse the same contour detection parameters defined earlier. # This technique, applied to multiple images, allow to perform the same analysis on # each of them and make comparisons easier. # Apply the same contour detection to the second image contour_results2 = sigima.proc.image.contour_shape(img2, contour_param) print("✓ Contour detection completed for second image") contour_df2 = contour_results2.to_dataframe() print("\nDetected contours data frame (Image 2):") print(contour_df2) # %% # Extract profile from second image and compare both profiles # ---------------------------------------------------------------- # We can extract the horizontal intensity profile from the second image # using the same profile extraction parameters defined earlier. # Extract horizontal profile from second image profile_signal2 = sigima.proc.image.line_profile(img2, profile_param) print(f"\n✓ Profile extracted from second image: {len(profile_signal2.y)} points") print(f"Intensity range: {profile_signal2.y.min():.1f} - {profile_signal2.y.max():.1f}") # Compare profiles from both images viz.view_curves( [profile_signal1, profile_signal2], title="Intensity Profile Comparison", xlabel="Position (pixels)", ylabel="Intensity", ) Sigima-1.1.1/doc/examples/use_cases/laser_beam.py000066400000000000000000000252271514013333200217270ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Laser Beam Size Measurement Example =================================== This example demonstrates comprehensive laser beam analysis techniques following the laser beam tutorial workflow. It shows how to load multiple laser beam images, analyze background noise with histograms, apply proper clipping, detect beam centroids, extract line and radial profiles, compute FWHM measurements, and track beam size evolution along the propagation axis. The script demonstrates advanced optical beam characterization workflows commonly used in laser physics, beam quality assessment, and optical system design. """ # %% # Importing necessary modules # -------------------------------- # We start by importing all the required modules for image processing # and visualization. To run this example, ensure you have all the required # dependencies installed. import numpy as np import sigima.io import sigima.objects import sigima.params import sigima.proc.image import sigima.proc.signal from sigima import viz from sigima.tests import helpers # %% # Load all laser beam images # ------------------------------------------------ # We load a series of laser beam images taken at different positions along # the propagation axis (z-axis). The images are contained in the folder laser_beam and # named following the pattern TEM00_z_*.jpg, where * is the z position in arbitrary # units. def load_laser_beam_images(): """Load all laser beam test images from the test data directory. Returns: List of image objects loaded from TEM00_z_*.jpg files """ # Get all TEM00 laser beam image files image_files = helpers.get_test_fnames("laser_beam/TEM00_z_*.jpg") # Sort files by z-position (extract number from filename) image_files.sort(key=lambda f: int(f.split("_z_")[1].split(".")[0])) # Load images images = [] for filepath in image_files: img = sigima.io.read_image(filepath) # Extract z position from filename for proper naming z_pos = filepath.split("_z_")[1].split(".")[0] img.title = f"TEM00_z_{z_pos}" images.append(img) return images images = load_laser_beam_images() print(f"✓ Loaded {len(images)} laser beam images") print("Image details:") for i, img in enumerate(images): intensity_range = f"{img.data.min()}-{img.data.max()}" print(f" {i + 1}. {img.title}: {img.data.shape}, range {intensity_range}") # %% # Visualize the first few images print("\n✓ Visualizing sample images...") viz.view_images_side_by_side(images[:3], title="Sample Laser Beam Images") # %% # Background noise analysis with histogram # ------------------------------------------------ # To analyze the background noise characteristics of the laser beam images, # we create a histogram of pixel values from the first image. This helps us # identify the noise floor and determine an appropriate clipping threshold. print("\n--- Background Noise Analysis ---") hist_param = sigima.params.HistogramParam() hist_param.bins = 100 hist_param.range = (0, images[0].data.max()) hist = sigima.proc.image.histogram(images[0], hist_param) hist.title = "Pixel value histogram of image 1" print(f"✓ Generated histogram with {hist_param.bins} bins") print(f"Histogram range: {hist_param.range[0]} - {hist_param.range[1]}") print("The histogram shows background noise distribution") # Visualize histogram viz.view_curves([hist], title="Pixel Value Histogram - Background Analysis") # %% # Based on the histogram analysis, we determine a clipping threshold around 30-35 LSB to # effectively remove background noise from all images. # %% # Background noise removal via clipping # ------------------------------------------------ # We set the threshold to 35 and we apply this clipping to each image in the dataset. background_threshold = 35 print(f"Will use clipping threshold of {background_threshold} LSB") # %% # In order to perform the clipping, we create a ClipParam object # and set the minimum value to the background threshold. We then apply # the clipping to each image in the dataset. print("\n--- Applying Background Clipping ---") clip_param = sigima.params.ClipParam() clip_param.lower = background_threshold # Remove background noise below 35 LSB clipped_images = [] for img in images: clipped_img = sigima.proc.image.clip(img, clip_param) clipped_img.title = f"{img.title}_clipped" clipped_images.append(clipped_img) print(f"✓ Applied clipping of {clip_param.lower} LSB to all {len(images)} images") print("Background noise below threshold has been removed") # %% # We can now visualize some clipped images: viz.view_images_side_by_side( images[:3] + clipped_images[:3], rows=2, title="Original and Clipped Images (First 3)", ) # %% # Compute centroids for beam center detection # ------------------------------------------------ # Next, we compute the centroid of each clipped image to determine the beam center. This # is important for accurate profile extraction and FWHM measurements. print("\n--- Computing Beam Centroids ---") centroids = [] for img in clipped_images: centroid_result = sigima.proc.image.centroid(img) centroids.append(centroid_result.value) # (x, y) print(f" ✓ {img.title}: centroid at {centroid_result.value}") print(f"\n✓ Successfully detected {len(centroids)}/{len(images)} centroids") # %% # Extract line profiles through beam centers # ------------------------------------------------ # We extract horizontal line profiles through the detected centroids of each clipped # image. This provides insight into the beam intensity distribution along a horizontal # cross-section. print("\n--- Extracting Line Profiles ---") line_profiles = [] for i, (img, centroid_coords) in enumerate(zip(clipped_images, centroids)): # Create line profile parameters for horizontal line through centroid line_param = sigima.proc.image.LineProfileParam() line_param.direction = "horizontal" line_param.row = int(centroid_coords[1]) # Use centroid y-coordinate as row # Extract line profile profile = sigima.proc.image.line_profile(img, line_param) profile.title = f"Line_profile_{img.title}" line_profiles.append(profile) print(f" ✓ Extracted line profile for {img.title} at row {line_param.row}") print(f"\n✓ Generated {len(line_profiles)} line profiles") # Visualize some line profiles viz.view_curves(line_profiles[:3], title="Horizontal Line Profiles (First 3 Images)") # %% # Extract radial profiles around beam centers # ------------------------------------------------ # We extract radial profiles centered on the detected centroids of each clipped image. # This provides a circular intensity distribution useful for FWHM measurements. print("\n--- Extracting Radial Profiles ---") radial_profiles = [] for img in clipped_images: # Create radial profile parameters using automatic centroid detection radial_param = sigima.proc.image.RadialProfileParam() radial_param.center = "centroid" # Use automatic centroid detection # Extract radial profile profile = sigima.proc.image.radial_profile(img, radial_param) profile.title = f"Radial_profile_{img.title}" radial_profiles.append(profile) print(f" ✓ Extracted radial profile for {img.title}") print(f"\n✓ Generated {len(radial_profiles)} radial profiles") # %% # We can now visualize some radial profiles viz.view_curves(radial_profiles[:3], title="Radial Profiles (First 3 Images)") # %% # Compute FWHM for radial profiles # ------------------------------------------------ # We compute the Full Width at Half Maximum (FWHM) for each radial profile to # quantify the beam size. The FWHM is a standard metric for beam width. print("\n--- Computing FWHM Measurements ---") fwhm_vals = [] fwhm_param = sigima.params.FWHMParam() fwhm_param.method = "zero-crossing" # Standard FWHM method for profile in radial_profiles: fwhm_result = sigima.proc.signal.fwhm(profile, fwhm_param) fwhm_vals.append(fwhm_result.value) print(f" ✓ {profile.title}: FWHM = {fwhm_result.value:.2f} pixels") # %% # That's done, we can now print some FWHM statistics to check our results: print("\n✓ FWHM Statistics:") print(f" Valid measurements: {len(fwhm_vals)}/{len(fwhm_vals)}") print(f" Beam size range: {min(fwhm_vals):.2f} - {max(fwhm_vals):.2f} pixels") print(f" Average beam size: {np.mean(fwhm_vals):.2f} ± {np.std(fwhm_vals):.2f} pixels") # %% # Everything seems fine, we can now analyze the beam size evolution along the z-axis. # %% # Analyze beam size evolution # ------------------------------------------------ # Having computed the FWHM for each radial profile, we can now analyze how the # beam size evolves along the propagation axis (z-axis). This is useful to extract some # meaningful information from all the numbers we have obtained. We create a signal # representing the beam size evolution and visualize it. print("\n--- Beam Size Evolution Analysis ---") # Create a signal showing beam size evolution along z-axis z_positions = list(range(len(fwhm_vals))) beam_evolution = sigima.objects.create_signal( "Beam size evolution", np.array(z_positions), np.array(fwhm_vals), units=("image_index", "pixels"), ) print(f"✓ Created beam evolution signal with {len(z_positions)} data points") # Visualize beam size evolution viz.view_curves( [beam_evolution], title="Beam Size Evolution vs Z-Position (uncalibrated)" ) # %% # The beam evolution signal currently uses image index as the x-axis, and even if we can # see the trend, it is not very informative. It would be way better to have the x-axis # in mm. # %% # Apply z-axis calibration # ------------------------------------------------ # We apply a linear calibration to the x-axis of the beam evolution signal to convert # image index to physical distance in mm. In Sigima there is the possibility to perform # a linear axis calibration. We use the formula x' = 5*x + 15, where x is # the image index and x' is the calibrated distance in mm. print("\n--- Applying Z-Axis Calibration ---") # Calibrate x-axis using the formula: x' = 5*x + 15 (convert to mm) calib_param = sigima.proc.signal.XYCalibrateParam() calib_param.axis = "x" calib_param.a = 5.0 # Scale factor calib_param.b = 15.0 # Offset beam_evolution_calibrated = sigima.proc.signal.calibration(beam_evolution, calib_param) beam_evolution_calibrated.title = f"{beam_evolution.title} (z calibrated)" print(f"✓ Applied calibration: z' = {calib_param.a}*z + {calib_param.b}") print("Z-axis now represents physical distance in mm") # Visualize calibrated beam evolution viz.view_curves( [beam_evolution_calibrated], title="Beam Size Evolution vs Z-Position (calibrated)", xlabel="Z Position (mm)", ylabel="Beam Size (pixels)", ) Sigima-1.1.1/doc/examples/use_cases/spectrum_analysis.py000066400000000000000000000242721514013333200234010ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Spectrum Analysis ================= This example demonstrates advanced signal processing for spectroscopy analysis using a paracetamol spectrum. It shows how to apply noise reduction, region of interest selection, peak fitting, and detrending techniques available in Sigima. Each step builds upon the previous one to create a comprehensive analysis workflow. Usage: python paracetamol_example.py The script demonstrates spectroscopy data processing workflows commonly used in analytical chemistry and materials science applications. """ # %% Importing necessary modules import numpy as np import sigima.objects import sigima.proc.signal from sigima import viz from sigima.tests.data import create_paracetamol_signal from sigima.tools.signal import fitting, peakdetection # Constants XLABEL_ANGLE = "Angle" YLABEL_INTENSITY = "Intensity" # %% # Load test signal and initial visualization # ----------------------------------------------------------- # We load a sample paracetamol spectrum included in the Sigima test data. # This spectrum contains characteristic absorption peaks that we will # analyze using various signal processing techniques. # Load the paracetamol signal from test data sig = create_paracetamol_signal() x_orig, y_orig = sig.xydata print("✓ Paracetamol spectrum loaded successfully!") print(f"Signal contains {len(x_orig)} data points") print(f"Energy range: {x_orig.min():.1f} to {x_orig.max():.1f} eV") print(f"Intensity range: {y_orig.min():.1f} to {y_orig.max():.1f}") # Visualize the original spectrum viz.view_curves(sig, title="Paracetamol Spectrum - Original") # %% # Apply Wiener filter for noise reduction # -------------------------------------------- # The signal is quite clean. Anyway, to illustrate the filtering capabilities # of Sigima, we apply a Wiener filter to reduce any residual noise while # preserving the spectral features. sig_filt = sigima.proc.signal.wiener(sig) print("\n✓ Wiener filter applied!") print("The Wiener filter provides optimal noise reduction for signals") print("with known statistical properties.") # Compare original and filtered signals viz.view_curves( [sig, sig_filt], title="Paracetamol Spectrum - Original vs Wiener Filtered" ) # %% # Region of Interest (ROI) selection # ----------------------------------------------------------- # We fistly focus our analysis on one of the peaks of interest. To to that, # we define a region of interest (ROI) around the feature we want to analyze. # Define ROI around the peak roi_bounds = [35.5, 41.3] # Energy range in eV sig_filt.roi = sigima.objects.create_signal_roi(roi_bounds) print(f"\n✓ ROI defined from {roi_bounds[0]} to {roi_bounds[1]} eV") print("This focuses analysis on the primary absorption feature") # Visualize the signal with ROI viz.view_curves(sig_filt, title="Paracetamol Spectrum - Filtered with ROI") # %% # Gaussian fit on the peak # ----------------------------- # We can now fit the peak within the selected ROI using a # Gaussian model. This provides quantitative parameters such as peak position, # amplitude, and width. # Perform Gaussian fit on the ROI-selected data fit = sigima.proc.signal.gaussian_fit(sig_filt) print("\n✓ Gaussian fit completed!") print("This characterizes the main absorption peak with parameters:") print("- Peak position (energy)") print("- Peak amplitude (intensity)") print("- Peak width (FWHM)") # Visualize the signal with Gaussian fit viz.view_curves([sig_filt, fit], title="Paracetamol Spectrum - ROI with Gaussian Fit") # %% # Linear detrending # ----------------------------------------------------------- # After fitting the main peak, we may want to remove any baseline drift # present in the entire spectrum. # # The detrending function of Sigima performs a linear fit on the whole signal, # including the peaks. In our signal peaks take a large part of the signal itself, # witch is enough for signals where the peak are symmetrically distributed around the # center, with more or less the same amplitude. This is not the case here, and we cannot # expect this function to work well. It is however an interesting example to illustrate # how Sigima functions can be combined to perform a more advanced analysis. # %% # In order to visualize the limitation cited above, we apply the detrending # function directly on the filtered signal. It's important to remembre that we setted # a ROI on the signal to focus the analysis on the main peak. We need to remove # this ROI constraint to perform the detrending on the full signal. # Remove ROI constraint for full signal detrending sig_filt.roi = None # Apply linear detrending to remove baseline drift detrended_signal = sigima.proc.signal.detrending(sig_filt, method="linear") print("\n✓ Linear detrending applied!") # Compare filtered and detrended signals viz.view_curves( [sig_filt, detrended_signal], title="Paracetamol Spectrum - Filtered vs Detrended" ) # %% # The comparison shows, as expected, that the detrending function does not work well on # this signal. # This, as explained before, is due to the alogirithm used, which performs a linear fit # on the whole signal, including the peaks. This effect is clearly visible on the plot: # the peaks on the left, that are higher than the ones on the right, starts after the # detrending at an intensity value lower than the ones on the right, and all peaks has # a baseline under the zero. # # # %% # Improved detrending with peak exclusion # ----------------------------------------------------------- # An idea to overcome the limitation of the detrending function is suggested from the # behavior of the detrended signal: we already identified the problem, which is that the # linear fit is not performed on the baseline only, but also on the peaks. # # To perform a better detrending, we can first thus detect the peaks and then perform # a linear fit only on the non-peak regions. We reasonably expect this approach to # provide a more accurate baseline estimation and a better detrended signal. # %% # Automatic peak detection # ------------------------------------- # We can use the peak detection function of Sigima to automatically identify # the peaks in the spectrum. This function analyzes the signal and returns # the indices of the detected peaks. # Identify peaks in the detrended signal peak_indices = peakdetection.peak_indices(sig_filt.y) print("\n✓ Peak detection completed!") print(f"Found {len(peak_indices)} potential peaks in the spectrum") # Print detected peak positions x_data = sig_filt.x for i, peak_idx in enumerate(peak_indices): energy = x_data[peak_idx] intensity = sig_filt.y[peak_idx] print(f" Peak {i + 1}: Energy = {energy:.2f} eV, Intensity = {intensity:.1f}") # %% # Multi-Gaussian fitting # ----------------------------------------------------------- # We can now fit multiple Gaussian functions to the detected peaks. This allows us to # characterize each peak individually and obtain parameters such as position, # amplitude, and width for each peak. # Perform multi-Gaussian fit using detected peaks fitted_y, params = fitting.multigaussian_fit( sig_filt.x, sig_filt.y, peak_indices=peak_indices.tolist() ) # Create fitted signal object for visualization fitted_signal = sig_filt.copy() fitted_signal.y = fitted_y fitted_signal.title = "Multi-Gaussian Fit" print("\n✓ Multi-Gaussian fitting completed!") print("Each detected peak is fitted with individual Gaussian functions") # Visualize the final fitting result viz.view_curves( [sig_filt, fitted_signal], title="Paracetamol Spectrum - Detrended with Multi-Gaussian Fit", ) # %% # Defining ROI outside peaks for better detrending # ----------------------------------------------------------- # To improve the detrending, we define ROIs that exclude the detected peaks. # This allows us to fit the baseline only on the non-peak regions. # Extract peak parameters from the multi-Gaussian fit # Each peak has 3 parameters: amplitude, center, sigma num_peaks = len(peak_indices) peak_params = [] peaks_roi_bounds = np.zeros((num_peaks, 2)) for i in range(num_peaks): # Extract parameters for each Gaussian (amplitude, center, sigma) amplitude = params[f"amp_{i + 1}"] center = params[f"x0_{i + 1}"] sigma = params[f"sigma_{i + 1}"] peak_params.append([amplitude, center, sigma]) # Define exclusion zone as center ± 2*sigma exclusion_start = center - 2 * abs(sigma) exclusion_end = center + 2 * abs(sigma) peaks_roi_bounds[i] = [exclusion_start, exclusion_end] print(f"Peak {i + 1}: Center = {center:.2f} eV, Sigma = {sigma:.3f}") print(f" Exclusion zone: [{exclusion_start:.2f}, {exclusion_end:.2f}] eV") # Create ROIs including detected peaks roi = sigima.objects.create_signal_roi(peaks_roi_bounds) # invert ROIs to exclude peaks sig_filt.roi = roi.inverted(sig_filt.x.min(), sig_filt.x.max()) # Visualize the signal with new ROI viz.view_curves( sig_filt, title="Paracetamol Spectrum - Filtered with Peak Exclusion ROIs" ) # %% # We can now perform a linear fit on the signal using the defined ROIs to exclude # the peaks. This will provide a more accurate baseline estimation. fitted_signal = fit = sigima.proc.signal.linear_fit(sig_filt) # %% # Finally, we can subtract the extended linear fit from the original filtered signal # to obtain a better detrended signal. We can see that the baseline is now properly # estimated, leading to a more accurate detrended signal. better_detrended_signal = sigima.proc.signal.difference(sig_filt, fitted_signal) better_detrended_signal.title = "Improved Detrended Signal" print("\n✓ Improved detrending applied!") # Compare filtered and better detrended signals viz.view_curves( [sig_filt, better_detrended_signal], title="Paracetamol Spectrum - Filtered vs Improved Detrended", show_roi=False, ) # %% # To go futher... # ----------------------------------------------------------- # In the last step we really improved the detrending of our signal. Anyway, several # pics on the left of the signal are still not detected and the dentrending can be # futher improved. We suggest you to experiment by tuning the parameters of the peak # detection function and put your hands on the source code of this function to better # understand how it works. # Sigima-1.1.1/doc/images/000077500000000000000000000000001514013333200147305ustar00rootroot00000000000000Sigima-1.1.1/doc/images/Sigima-Banner.png000066400000000000000000000431711514013333200200600ustar00rootroot00000000000000PNG  IHDRly% pHYs$$LtEXtSoftwarewww.inkscape.org< IDATxw|S?ё4I'2d ꗯq_'āE@PDeo(Ymv{&ms۴M_ɹ B/RźT*;cJ1^GE>F%< 9GrJQ&pD(LrQp<2Ysg(aQƃ2&2FρRF9&F8(c )!JBPJ(ca&P e F@%02PFA J pUc0F a`22FaRB+p\qێ|QC$t֫g 0<@Jc[5uuLdUx&Fy\g^l$$;ޚ :eOIs ~9(28?2* 'saQ2(QFL)(1B)#%1J!pO%@e20 #QT<#T(Zb<(1U(~v~<*'1\P `PΏx, 'AR]6ΝS|uInWzs t`~K<2ԅK0&]ucYU%ƔMBH\ywIt| HFЖT$nu#_P3چ2' Sn[=%@Xo4d GJUrԲ @eQK&=6l Ώ (БG-.9Ē>Dt`Gp`p 5xh(:~[ǘ_rQ0ʹ1o l ;m _c Ń_.YDA}C9MnTJIB!iuG*(nP MCDhP:jD9zn{jToM(UXw4WL@. |O"gPW>0w&|•alSoFGΕ~ ]_. Aچ L$ b`}9_0dx|3!\CR"DDI{- C\mCꥰG擀umP9Fho ad V)//gudХjHȇA6^!,UfU??7f»r Lzcj^6B!   !)%9Vy [Oynq^d0oQ 6<B6>QѪ3]ڛw%8ZF `Ya ˹v]M_>h mYn 8o T6N*-1 W˳W9t%vLQq1jw4MrrtgYEmPŻ?gXwXG}۶*´^:qŤV骞->;mzKJ%$:+>kO0fKApy&uCͭ6Pe?8q-{C,aНC=ZƪRd?GRl{̃^X&[Nsfs7~uVco(B]'!Q#ua3NuCB4Tm4ļF>tp=~Zv 8vOptu͆jĞ)k^ǡ|RP\cGmI'DCa`*=o FΊ: 9zO>Z7=MuZC 7~k".BCqi=lv7E=. CU?%bHH4墆5rDeJOT aDe'ώf> >]>:+{ΚvYYc5 26S- 'K 1IaWd#T10F׊ZD`aWؠD1*|*_zpУ~jq8k{3n-nov?qΆOJηJ)7udN F)5!FZ}[ۍ(Diӑ煾b3F Y% 0>BRĄSF )ۘښ7Ah5W=R)JVW؟;y@jՉNhވ_C[Q~?w˭t+v2r6\7L5=omҋL=-~LmM(DIa3bcbXGڌ~;UekGH0D_(Uس3m)/,15EtkrCY>>%5b?|kɵd1jߍ^yxq}:':۶=Xk\<CΥ$Dhoe&>3D|CzpkԊFM-DuIa^BZ9%g4@N[1 P":eE{:qWZűE7jPR:2N[[cF:QHŨ;&DTc* 3M&]aZu@/W%!Q#utdx)v+jψXƍ|0&~IMMF2khnQ;(K35ӯr {޴Z!n ` $e]LhV؝ox;@PA08!@Hǐ c,lI.E"8$#BubL-l45/ORLF~]ƮK9_`Z5 iJHH=r"F3MP@pD,|6ĸq )llJik"Fn?"@n*+lϮ+m˙b#6pGvݒhzl<^D39WC<2:v"B^xt|e`,O27K^ ]QY}eE_2',[A`}vZ&&vx̟>s.?4Ca?^Y^M\:1]?kF9[Srl\}U|Ȝ~]"("32<4jBvNuPksKQ5P)R~Ed ^`da5!/v.w,C ~?ᑕw IY{t7L_U炋0|>t)xmw8ڔu0f WX,5-Qy~k]u[_UYW~6}[NCE-sVlxo_-de7|G~s[$OܦACxX`ewiT2U5!@eP.txK]}/K ]}4z[A: =qwN0{eѼ5yW[M2pݘ8~V?~R^>[{P+zY[P}$RTU]Gb̲a#+ͭ /{pPzMV q'kxb"/.5t;[b}ngsK{ɛ.bj6.)-BGVQP _BGkQ1]̘UU>>X]GWx Qwt~.G*%%csmeLC[ JD6&\L4\1z/QVRr}N!XÅ;Ziwբ%VI&3IO6<7:=;ģk{s٠+W(9V\:Y@z#<]%황guls2mJ0i=(pLnnoFj_F>x!u}k/zi~sF\}V 2~CU_c߹M\Y^';[ud`f!c;r4kEҒ'uaFlpDd F uVg x A72VHJw-k=M| q9_ 7pNn)]-F4@Ʀ'=.Z%!iqWD2FsW9JQჍ_T- -{[t,fG4*8ěbMyǭuJ04m ݳt!MW~jRTJ![mlP pz9<7\{7/(mV#4OΟg.aבʽ<[&Fc>%fJQW(ILnI3PB6M1أݖ9ƸWg];9]Kn[eb4&R|e'd!ZF)H%(mr W3)ͻ*m9UᵴV&јx'SCDT(iCp'H7GMA_$f ,mDEEf.XW_`nSE xM[t˽wu#ЌCle<^ԴE}(&>"F0J @uYYŨ6zmrBwo7f-Y'RKe^]>n7& NYhsX [⍺3:FVYc?Xd?S}a]]PV7>ߑ~V)dy[khu<.Z@ ԧSu) T(ݠ>xfC ~2;ct>9UD6J]8sؕ3_PEm<6O O4ۘ2L{̺o*էI6>py?o s5.Z[鿓v HhXk{K.<oSCOĮf׭fi^yq8fM]kv'5;qn:; q.veK(u7|W [bsK@B"*ꭈ#+V{U0Q_Rՠje^)#w'L_5}/K JLzz鳵/rm,N?{EZmG٘ģ^I44ŨĔ͆u]peqѪQSo k 8)?-tNܦp ~9}Wn-USM?u{#^Q=ĭ0 IDATMѓ_qu/2 sbcT;X0rj$#[5?/[]߇/h c+ߏ2tb 6~ ~0'jLJ!Zh˺*hݿ^zhpGF1C k-jEZU}`׬i(*un1! =o6d[_펫ah]Ϙ F1Z4neL^߿Mc@H ;}zH&͢5f3 lN(DdJQXQ ,33c˜WÂ~;ﳡȳŎޔq 1шrj[%gFnke/#3^XG"%[H -*Ҳ 5k_V-ǘG-PI.+=}^Zyu ˈ mV5?_w(7ѬH9f6$# OZmSb:%Pqtn:~yM@H 1qr!\9UOz^!8)j9ʉڥx^ l^uȮK- t!X z;йCST\3\p1!d?#L?H-E)l&u2szvV,)E5I6Ew٦{t&0tE9v˞Cc5/SKѩ_ݧU۶0h]Z<{7Fh2^d4Bc+G58.eGJѸU*ĺ5n*Bܘ8a9s䊚W΅ѫ׻r&Jju R^\:%v'ύ:ѭ9Z⎧VA_oXz{'Q rɬUftJDUЄ i *¦/.-σ0QQm[\%54=8֪53.h>×M|T̚$ 87,@Gip֨c4 R EiV /H(qqQvw$.VB\"Fofw}bxqg&Ĺf.E!«[gWw}|:au&QpnFƤ2HJoģRxօFqy,ƀDR–S\,c!v!D\hX B/*-Be|}~A;ⱻl n+/n=piT bEA (#s4RΛ@h5wJ.^;@a$Xf@d 6_{x"&<aiousz@N)R([C"0ƔZYE4]C4U_/rήQn[$"BPUa ACVBwE0k GHnBĕ.%Tr/&4t ׷~?yu;|a(f:R )Sp9CI')Pcfqb5Wl*Qhspq6e"fq~l[y:H?jg+p=[\,6 @s+n,NKYZ"`bUݷ֯850oH26R ]r 򬎈=Q{X`8 hCUHEa@Qk) %S I0I fRŬ]W8BO+ܛ71֯G-{e͑+h$[gS:v:F4@}ѼY*UX5cwS5J(eBFl*oZҔP/8X ŹCi[9Oq' ^Ne+ǡ}Sh rTtoP4^*n E^<լ~d L>ө%U+: H&@vM;6(:@4"K91%EF!7vI9jK( ?vE6AE[1 nEW>nX՛3+r!cY?%6ZrC_ :#3+""$A&6vKt~/یv'I@ v̆ oZʇJj+Z&'„뉰kwB+[k{ox5E{&>qhHV̪MǕN>[ XK\-vV7jβq Uߴf%e;"Ů}gYlYU Ůyw{{Omf(w6;k .X,ۍB!Qo`W**EЉ4YRt[ro*ՇPر9l@hTVzd؏Yf[q`NӮc 9}l~aS,z"#kJN-;Zо*+h#V'MQ[hT7]>ݭRǧ鞭E%WTX4޹s&W#O +#Ld Qy`٘_jar ?SףS;'|fB/xvhkfkf{ +h.J.[xlƀ/h**r-G#eX/}hr_O' !J;Gw)ځ={+;kOUqѷլ6/ &jPm|Cq_{ZZɠu9]uo2>)j[jVzr"1 v2% MpbU=ax*1y&@dG"`7,`qkU=gkjͿw[`-t4N-"6!!>VaL-:#,by:՛ox>j6ϻϔBNjh<2xkG>]}9&" zՇ~+_XȢo<|hoN+=E.x9}7e~9v7mlɬ^=ͽs sPD8i=a֪o9{]ՏG˷~Rl h򬎷wY{ˣ߶uRLRɭ4Fk68: fw{Oa yy2n6eFI~ED(l6g6zI6PW(jZ 90o+Ũ}Wo pu=x|{eBvQ FB:4GNY^TFܐQ]ף0R5Ek4/[_Jzjl.lPk$xmЂ$sr_`1ʇNח/X#'-;b/W ~(n?V{wJ=reX rxQ[9mU9P.J~ŨDH!"6,%tkk-Ya(ݸqN][oy|&QoUZWpQqyS1_-+hѪ $)M#urLfIw "u#9 D7@Z/w$Y~JwP gTI*Σj\0!(Ub;d!6p|OV+I Z!/#x>W(d!.2#w=ȝ˩p=uӧcBrW clOZ"c19+AL%`w<8Yظt\Yw:.Op{J6)h";(%Ȇ8Nְ{%]B."Bc#FaK'AuN!,lջ.r{{a[>cRL;"JR%vN Ze\۰HW_yN)hxDU}.RK/;\2 *݋%u;2u#7g:kbC QeTN hrM0贁ݓʼSJ:Ӄ~fg -6 35 MyևQا6Nz',ƪx mT5:OXj i/ea#='g_~Z;7$uPjG1J)*Վl⎭MLVD"I4<:2CQԂ45d2 d(Idp3F6[WfIo?v8cr~ܰ.'"yrΗl [#Pf cU5<JD)l$j-#h2BwZ6v?B}n E 2(|vT&ư_k1j5L9KWTz.nM6;Qҫ׻&'r/tבWW~-N[5$CT~R+-䵿7ːFC D& b|k ɢpu_(x+MTBt4"rM,㥩Yyed^7d^~cϲ]x>-y䐨B, (xs R(#ccJPQdRP*0JA(;?( jPeRǐdpjm1VYNAa !N{3䪕geN/nwO-y5.wm^J.F^!֖D"Jaa68ʵ&L\*Pq-j)eD !?IJ#_aȉӫ|Aeh˜^*-r)Lk-r"1X%l5SbߕS،m@Q6 kq ,_JZ.l]5h=:$|<y|g]sӿ:w Thx`dvcvW+0;tkoTU[hDTP*)$EFډZď*l _#Ed~?b5}B΍}c>y>l՘G^~5Z  jbg\*6::['Cѫ7gU=o鈫}fh+!D>>kڨw&"8j#r:I+#jL‘fbu}iq=O` m.|^D} jT2otJp|(sK.AVu)hְ¶-c?2jmv,!w&6a #I+ަ*DŽ}ڋ\ȌljLF(WKjae]`GvŨ:I埜|Ev16 (y=PKIDATD'|@@DË́n8^I`" &uoߒuǨ.(mxO Nz}|3Sl")k:iasv5T*(䜐DumoƔFFkwЉs=ywT\B Fno-)V5@ ʩFSC8%]i XxPLyv=hP=*^Z`iIԥ\WPf--*,v)^yGS+UaV;/kgvMkrtkB}BL ϳ( ;kx_ҋs3X]Dg9ұ:tQ:bhmRJʼ)3=>8ZV cBT4=B|ahr"Wa+lBƍm8獔 :`=#&rb0c]/lj1$jRkפtcadx8 ^}"N WF5 ?ڛG>l |ђÞ0S]TeDXҹɄP#b66v5kaYN,Z'H?2Ph:#K@1bgEØأNAs! Ѩl:wSHc/!8@ /є\BGWM>Ukmdj}rpu*t9sDB!b]*1L# LsS#|c%r(8"p Q&PxF9(8JQ93q0(AG@#@)a#eQv1Fǔx`!( 10QJ(e 2 J`U@ @AAJ( @ %8*1B00J@`0F)8.ȸmVL>R9*l "%"!!!OFRIaKHHH4$-!!!LD3ARIaKHHH4L'IENDB`Sigima-1.1.1/doc/images/Sigima-Banner.svg000066400000000000000000000457121514013333200200760ustar00rootroot00000000000000 image/svg+xmlSigima Sigima-1.1.1/doc/images/Sigima.svg000066400000000000000000000457101514013333200166710ustar00rootroot00000000000000 image/svg+xmlS Sigima-1.1.1/doc/images/logos/000077500000000000000000000000001514013333200160535ustar00rootroot00000000000000Sigima-1.1.1/doc/images/logos/cea.svg000066400000000000000000000035741514013333200173350ustar00rootroot00000000000000 Sigima-1.1.1/doc/images/logos/codra.svg000066400000000000000000000104431514013333200176660ustar00rootroot00000000000000 Sigima-1.1.1/doc/images/logos/nlnet.svg000066400000000000000000000110661514013333200177200ustar00rootroot00000000000000 Sigima-1.1.1/doc/index.rst000066400000000000000000000100741514013333200153260ustar00rootroot00000000000000Sigima ====== **Sigima** is an advanced Python library for *scientific image and signal processing*. It provides a wide range of functionalities for analyzing and processing data, including signal filtering, image enhancement, and feature extraction. Sigima is based on a simple but effective object-oriented design, making it easy to use and extend. With Sigima, do in 3 lines of code what would normally take dozens of lines: .. code-block:: python import numpy as np import sigima.objects import sigima.proc.image data = np.random.normal(100, 30, (100, 100)) # Prepare test image data img = sigima.objects.create_image("Noisy", data) # Create the image object img.roi = sigima.objects.create_image_roi("circle", [30, 30, 20]) # Define ROI result = sigima.proc.image.gaussian_filter(img, sigma=5.0) # Apply Gaussian filter .. figure:: _static/DataLab-Banner.svg :align: center :width: 300 px :class: dark-light no-scaled-link Developed and maintained by the DataLab Platform Developers, **Sigima** powers the computation backend of `DataLab `_. .. only:: html and not latex .. grid:: 2 2 4 4 :gutter: 1 2 3 4 .. grid-item-card:: :octicon:`rocket;1em;sd-text-info` User Guide :link: user_guide/index :link-type: doc Installation, overview, and features .. grid-item-card:: :octicon:`code;1em;sd-text-info` Examples :link: ../auto_examples/index :link-type: doc Gallery of examples .. grid-item-card:: :octicon:`book;1em;sd-text-info` API :link: api/index :link-type: doc Reference documentation .. grid-item-card:: :octicon:`gear;1em;sd-text-info` Contributing :link: contributing/index :link-type: doc Getting involved in the project Try it Online ------------- **Experience Sigima instantly in your browser** — no installation required! .. image:: https://img.shields.io/badge/Try_it-online-blue?logo=jupyter :target: https://notebook.link/github/DataLab-Platform/Sigima/tree/main/notebooks/?path=notebooks/sigima_basic_example.ipynb :alt: Try it online Click the badge above to open a basic example notebook in a live JupyterLite environment powered by `notebook.link `_. This service, developed by `QuantStack `_, enables sharing and running Jupyter notebooks directly in the browser with zero setup. Simply run the cells to explore: - Creating signal and image objects - Applying processing functions - Visualizing results inline Sigima has been funded by the following stakeholders: .. list-table:: :header-rows: 0 * - |nlnet_logo| - `NLnet Foundation `_, as part of the NGI0 Commons Fund, backed by the European Commission, has funded the `redesign of DataLab's core architecture `_. * - |cea_logo| - `CEA `_, the French Alternative Energies and Atomic Energy Commission, is the major investor in DataLab, and is the main contributor to the project. * - |codra_logo| - `CODRA`_, a software engineering and editor firm, has supported DataLab open-source journey since its inception (see `here `_). .. |cea_logo| image:: images/logos/cea.svg :width: 64px :height: 64px :target: https://www.cea.fr :class: dark-light no-scaled-link .. |codra_logo| image:: images/logos/codra.svg :width: 64px :height: 64px :target: https://codra.net :class: dark-light no-scaled-link .. |nlnet_logo| image:: images/logos/nlnet.svg :width: 64px :height: 64px :target: https://nlnet.nl :class: dark-light no-scaled-link .. only:: latex and not html .. toctree:: :maxdepth: 2 :caption: Contents user_guide/index auto_examples/index api/index contributing/index release_notes/index .. _DataLab: https://www.datalab-platform.com .. _CODRA: https://codra.net/ Sigima-1.1.1/doc/locale/000077500000000000000000000000001514013333200147225ustar00rootroot00000000000000Sigima-1.1.1/doc/locale/fr/000077500000000000000000000000001514013333200153315ustar00rootroot00000000000000Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/000077500000000000000000000000001514013333200171165ustar00rootroot00000000000000Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/api/000077500000000000000000000000001514013333200176675ustar00rootroot00000000000000Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/api/index.po000066400000000000000000000107131514013333200213400ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2025, DataLab Platform Developers # This file is distributed under the same license as the Sigima package. # FIRST AUTHOR , 2025. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: Sigima \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid "Public features:" msgstr "Fonctionnalités publiques :" msgid "API" msgstr "API" msgid "The public Application Programming Interface (API) of Sigima offers a set of functions that can be used to access the DataLab computational backend. This API is designed to be simple and effective, allowing users to perform signal and image processing tasks with ease." msgstr "L'interface de programmation d'application (API) publique de Sigima offre un ensemble de fonctions qui peuvent être utilisées pour accéder au backend de calcul DataLab. Cette API est conçue pour être simple et efficace, permettant aux utilisateurs d'effectuer facilement des tâches de traitement de signaux et d'images." msgid "Submodule" msgstr "Sous-module" msgid "Purpose" msgstr "Objectif" msgid ":mod:`sigima.tools`" msgstr "" msgid "Algorithms for data analysis (operating on NumPy arrays) which purpose is to fill in the gaps of common scientific libraries (NumPy, SciPy, scikit-image, etc.), offering consistent tools for computation functions (see :mod:`sigima.proc`)" msgstr "Algorithmes d'analyse de données (fonctionnant sur des tableaux NumPy) dont le but est de combler les lacunes des bibliothèques scientifiques courantes (NumPy, SciPy, scikit-image, etc.), offrant des outils cohérents pour les fonctions de calcul (voir :mod:`sigima.proc`)" msgid ":mod:`sigima.params`" msgstr "" msgid "Sets of parameters for configuring computation functions (these parameters are instances of :class:`guidata.dataset.DataSet` objects)" msgstr "Ensembles de paramètres pour configurer les fonctions de calcul (ces paramètres sont des instances d'objets :class:`guidata.dataset.DataSet`)" msgid ":mod:`sigima.objects`" msgstr "" msgid "Object model for signals and images (:class:`sigima.objects.SignalObj` and :class:`sigima.objects.ImageObj`), scalar results (:class:`sigima.objects.GeometryResult` and :class:`sigima.objects.TableResult`), and related functions" msgstr "Modèle d'objet pour les signaux et les images (:class:`sigima.objects.SignalObj` et :class:`sigima.objects.ImageObj`), résultats scalaires (:class:`sigima.objects.GeometryResult` et :class:`sigima.objects.TableResult`), et fonctions associées" msgid ":mod:`sigima.proc`" msgstr "" msgid "Computation functions, which operate on signal and image objects (:class:`sigima.objects.SignalObj` or :class:`sigima.objects.ImageObj`) and return signal or image objects, or scalar results (:class:`sigima.objects.GeometryResult` or :class:`sigima.objects.TableResult`)." msgstr "Fonctions de calcul, qui opèrent sur des objets signal et image (:class:`sigima.objects.SignalObj` ou :class:`sigima.objects.ImageObj`) et retournent des objets signal ou image, ou des résultats scalaires (:class:`sigima.objects.GeometryResult` ou :class:`sigima.objects.TableResult`)." msgid ":mod:`sigima.config`" msgstr "" msgid "Configuration management for the Sigima library, including options for data paths, translations, and other settings." msgstr "Gestion de la configuration pour la bibliothèque Sigima, y compris les options pour les chemins de données, les traductions et d'autres paramètres." msgid ":mod:`sigima.client`" msgstr "" msgid "Client interface for connecting to DataLab application through XML-RPC protocol, providing remote control capabilities for signal and image processing workflows." msgstr "Interface client pour se connecter à l'application DataLab via le protocole XML-RPC, offrant des capacités de contrôle à distance pour les flux de travail de traitement de signaux et d'images." msgid ":mod:`sigima.viz`" msgstr "" msgid "Visualization tools for interactive display of signal and image objects, supporting PlotPy and Matplotlib backends for testing, debugging, and Jupyter notebook analysis." msgstr "Outils de visualisation pour l'affichage interactif des objets signal et image, prenant en charge les backends PlotPy et Matplotlib pour les tests, le débogage et l'analyse dans les notebooks Jupyter." Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/auto_examples/000077500000000000000000000000001514013333200217645ustar00rootroot00000000000000Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/auto_examples/features/000077500000000000000000000000001514013333200236025ustar00rootroot00000000000000Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/auto_examples/features/convolution.po000066400000000000000000000141771514013333200265330ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2025, DataLab Platform Developers # This file is distributed under the same license as the Sigima package. # FIRST AUTHOR , 2025. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: Sigima \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid ":ref:`Go to the end ` to download the full example code." msgstr ":ref:`Aller à la fin ` pour télécharger le code complet de l'exemple." msgid "Convolution and Deconvolution" msgstr "Convolution et déconvolution" msgid "This example focuses on image blurring and sharpening using convolution and deconvolution techniques provided by Sigima. Using various kernels, we'll explore how these operations affect images and how to implement them using Sigima's processing functions." msgstr "Cet exemple se concentre sur le floutage et l'accentuation de contours d'images en utilisant les techniques de convolution et de déconvolution fournies par Sigima. En utilisant divers noyaux, nous explorerons comment ces opérations affectent les images et comment les implémenter en utilisant les fonctions de traitement de Sigima." msgid "The example shows:" msgstr "L'exemple montre :" msgid "Creating test images and kernels" msgstr "Création d'images de test et de noyaux" msgid "Basic convolution with Gaussian kernel" msgstr "Convolution de base avec noyau gaussien" msgid "Identity convolution (preserving original image)" msgstr "Convolution d'identité (préservation de l'image d'origine)" msgid "Deconvolution operations" msgstr "Opérations de déconvolution" msgid "Effects of different kernel parameters" msgstr "Effets des différents paramètres de noyau" msgid "Custom edge detection and sharpening kernels" msgstr "Kernels personnalisés de détection de contours et d'accentuation" msgid "This tutorial uses PlotPy for visualization, providing interactive plots that allow you to explore the convolution results in detail." msgstr "Ce tutoriel utilise PlotPy pour la visualisation, fournissant des graphiques interactifs qui vous permettent d'explorer les résultats de convolution en détail." msgid "Importing necessary modules" msgstr "Importation des modules nécessaires" msgid "We'll start by importing all the required modules for image processing and visualization." msgstr "Nous commencerons par importer tous les modules nécessaires au traitement d'image et à la visualisation." msgid "We start by creating a test image and various convolution kernels." msgstr "Nous commençons par créer une image de test et divers noyaux de convolution." msgid "Qt widget 1" msgstr "" msgid "Now we'll perform convolution with the Gaussian kernel and compare the result with scipy's implementation to verify correctness." msgstr "Nous allons maintenant effectuer une convolution avec le noyau gaussien et comparer le résultat avec l'implémentation de scipy pour vérifier la justesse." msgid "Identity convolution" msgstr "Convolution d'identité" msgid "Identity convolution should preserve the original image exactly. This demonstrates that our convolution implementation is working correctly." msgstr "La convolution d'identité devrait préserver exactement l'image d'origine. Cela démontre que notre implémentation de convolution fonctionne correctement." msgid "Deconvolution with identity kernel" msgstr "Déconvolution avec noyau d'identité" msgid "Deconvolution is the inverse operation of convolution. We'll start with a simple case using the identity kernel." msgstr "La déconvolution est l'opération inverse de la convolution. Nous commencerons par un cas simple utilisant le noyau d'identité." msgid "Advanced deconvolution with Gaussian kernel" msgstr "Déconvolution avancée avec noyau gaussien" msgid "Now we'll try deconvolution with a Gaussian kernel, which is more challenging and demonstrates the limitations of deconvolution." msgstr "Nous allons maintenant essayer la déconvolution avec un noyau gaussien, qui est plus difficile et démontre les limites de la déconvolution." msgid "Exploring different kernel parameters" msgstr "Exploration des différents paramètres de noyau" msgid "Different sigma values in Gaussian kernels produce different blurring effects. Let's compare several sigma values side by side." msgstr "Différentes valeurs de sigma dans les noyaux gaussiens produisent différents effets de flou. Comparons plusieurs valeurs de sigma côte à côte." msgid "Qt widget 2" msgstr "" msgid "Custom convolution kernels" msgstr "Kernels de convolution personnalisés" msgid "Besides Gaussian kernels, we can create custom kernels for specific image processing tasks like edge detection and sharpening." msgstr "En plus des noyaux gaussiens, nous pouvons créer des noyaux personnalisés pour des tâches spécifiques de traitement d'image telles que la détection de contours et l'accentuation." msgid "Summary and conclusions" msgstr "Résumé et conclusions" msgid "This tutorial demonstrated the key concepts of convolution and deconvolution in image processing using Sigima." msgstr "Ce tutoriel a démontré les concepts clés de la convolution et de la déconvolution dans le traitement d'image en utilisant Sigima." msgid ":download:`Download Jupyter notebook: convolution.ipynb `" msgstr ":download:`Télécharger le notebook Jupyter : convolution.ipynb `" msgid ":download:`Download Python source code: convolution.py `" msgstr ":download:`Télécharger le code source Python : convolution.py `" msgid ":download:`Download zipped: convolution.zip `" msgstr ":download:`Télécharger le fichier compressé : convolution.zip `" msgid "`Gallery generated by Sphinx-Gallery `_" msgstr "`Galerie générée par Sphinx-Gallery `_" Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/auto_examples/features/coordinate_systems.po000066400000000000000000000135321514013333200300640ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2025, DataLab Platform Developers # This file is distributed under the same license as the Sigima package. # FIRST AUTHOR , 2025. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: Sigima \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid ":ref:`Go to the end ` to download the full example code." msgstr ":ref:`Aller à la fin ` pour télécharger le code complet de l'exemple." msgid "Uniform and Non-Uniform Coordinate Systems" msgstr "Systèmes de coordonnées uniformes et non uniformes" msgid "This example demonstrates the use of uniform and non-uniform coordinate systems with images in Sigima. It shows how to create, visualize, and work with both types of coordinate systems, highlighting their differences and appropriate use cases." msgstr "Cet exemple démontre l'utilisation de systèmes de coordonnées uniformes et non uniformes avec des images dans Sigima. Il montre comment créer, visualiser et travailler avec les deux types de systèmes de coordonnées, en mettant en évidence leurs différences et leurs cas d'utilisation appropriés." msgid "The example shows:" msgstr "L'exemple montre :" msgid "Creating images with uniform coordinate systems" msgstr "Création d'images avec des systèmes de coordonnées uniformes" msgid "Creating images with non-uniform coordinate systems" msgstr "Création d'images avec des systèmes de coordonnées non uniformes" msgid "Visualizing the coordinate grids" msgstr "Visualisation des grilles de coordonnées" msgid "Comparing pixel spacing and coordinate mapping" msgstr "Comparaison de l'espacement des pixels et du mappage des coordonnées" msgid "Working with real-world units and coordinates" msgstr "Travail avec des unités et des coordonnées du monde réel" msgid "Understanding when to use each coordinate system type" msgstr "Quand et comment utiliser chaque type de système de coordonnées" msgid "This tutorial uses PlotPy for visualization, providing interactive plots that allow you to explore the coordinate system effects in detail." msgstr "Ce tutoriel utilise PlotPy pour la visualisation, fournissant des graphiques interactifs qui vous permettent d'explorer en détail les effets du système de coordonnées." msgid "Importing necessary modules" msgstr "Importation des modules nécessaires" msgid "We'll start by importing all the required modules for image processing and visualization." msgstr "Nous commencerons par importer tous les modules nécessaires au traitement d'images et à la visualisation." msgid "Creating test images with uniform coordinates" msgstr "Création d'images de test avec des coordonnées uniformes" msgid "Uniform coordinates have constant spacing between pixels in both directions. This is the most common case for regular imaging systems." msgstr "Les coordonnées uniformes ont un espacement constant entre les pixels dans les deux directions. C'est le cas le plus courant pour les systèmes d'imagerie réguliers." msgid "Creating test images with non-uniform coordinates" msgstr "Création d'images de test avec des coordonnées non uniformes" msgid "Non-uniform coordinates allow for variable spacing between pixels, useful for adaptive sampling, curved coordinates, or irregular grids." msgstr "Les coordonnées non uniformes permettent un espacement variable entre les pixels, utile pour l'échantillonnage adaptatif, les coordonnées courbes ou les grilles irrégulières." msgid "Visualizing coordinate system differences" msgstr "Visualisation des différences entre les systèmes de coordonnées" msgid "Let's create coordinate grid visualizations to highlight the differences between uniform and non-uniform coordinate systems." msgstr "Créons des visualisations de grilles de coordonnées pour mettre en évidence les différences entre les systèmes de coordonnées uniformes et non uniformes." msgid "Qt widget 1" msgstr "" msgid "Qt widget 2" msgstr "" msgid "Creating specialized non-uniform coordinate examples" msgstr "Création d'exemples spécialisés de coordonnées non uniformes" msgid "Let's create some more realistic examples of non-uniform coordinates that might be encountered in real applications:" msgstr "Créons des exemples plus réalistes de coordonnées non uniformes qui pourraient être rencontrées dans des applications réelles :" msgid "Time-resolved spectroscopy with logarithmic wavelength scale" msgstr "Spectroscopie résolue en temps avec une échelle de longueur d'onde logarithmique" msgid "Polar to Cartesian mapping" msgstr "Conversion polaire en cartésien" msgid "Summary and best practices" msgstr "Résumé et meilleures pratiques" msgid "Let's summarize when to use each coordinate system type." msgstr "Résumons quand utiliser chaque type de système de coordonnées." msgid ":download:`Download Jupyter notebook: coordinate_systems.ipynb `" msgstr ":download:`Télécharger le notebook Jupyter : coordinate_systems.ipynb `" msgid ":download:`Download Python source code: coordinate_systems.py `" msgstr ":download:`Télécharger le code source Python : coordinate_systems.py `" msgid ":download:`Download zipped: coordinate_systems.zip `" msgstr ":download:`Télécharger l'archive zip : coordinate_systems.zip `" msgid "`Gallery generated by Sphinx-Gallery `_" msgstr "`Galerie générée par Sphinx-Gallery `_" Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/auto_examples/features/datalab_client.po000066400000000000000000000050061514013333200270710ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2025, DataLab Platform Developers # This file is distributed under the same license as the Sigima package. # FIRST AUTHOR , 2025. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: Sigima \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid ":ref:`Go to the end ` to download the full example code." msgstr ":ref:`Aller à la fin ` pour télécharger le code complet de l'exemple." msgid "DataLab remote control example" msgstr "Exemple de contrôle à distance de DataLab" msgid "Example of remote control of DataLab current session, from a Python script running outside DataLab (e.g. in Spyder)" msgstr "Exemple de contrôle à distance de la session actuelle de DataLab, à partir d'un script Python s'exécutant en dehors de DataLab (par exemple dans Spyder)" msgid "This example demonstrates how to control DataLab remotely using the SimpleRemoteProxy from Sigima. The script can be run from any Python environment outside of DataLab to interact with an active DataLab session." msgstr "Cet exemple démontre comment contrôler DataLab à distance en utilisant le SimpleRemoteProxy de Sigima. Le script peut être exécuté depuis n'importe quel environnement Python en dehors de DataLab pour interagir avec une session DataLab active." msgid "This example is not executed during documentation build as it requires an active DataLab session to connect to. It is included in the gallery for reference and can be run manually when DataLab is running." msgstr "Cet exemple n'est pas exécuté lors de la construction de la documentation car il nécessite une session DataLab active à laquelle se connecter. Il est inclus dans la galerie à titre de référence et peut être exécuté manuellement lorsque DataLab est en cours d'exécution." msgid ":download:`Download Jupyter notebook: datalab_client.ipynb `" msgstr "" msgid ":download:`Download Python source code: datalab_client.py `" msgstr "" msgid ":download:`Download zipped: datalab_client.zip `" msgstr "" msgid "`Gallery generated by Sphinx-Gallery `_" msgstr "" Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/auto_examples/features/datetime_signals.po000066400000000000000000000153601514013333200274630ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2025, DataLab Platform Developers # This file is distributed under the same license as the Sigima package. # FIRST AUTHOR , 2025. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: Sigima \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid ":ref:`Go to the end ` to download the full example code." msgstr ":ref:`Aller à la fin ` pour télécharger le code complet de l'exemple." msgid "DateTime Signal Processing" msgstr "Traitement des signaux DateTime" msgid "This example demonstrates how to work with signals that have datetime X-axis data in Sigima. DateTime support is essential for time-series analysis where you need to preserve human-readable timestamps while performing signal processing." msgstr "Cet exemple démontre comment travailler avec des signaux ayant des données d'axe X de type datetime dans Sigima. Le support de DateTime est essentiel pour l'analyse des séries temporelles où vous devez préserver des horodatages lisibles par l'homme tout en effectuant un traitement de signal." msgid "The example shows:" msgstr "L'exemple montre :" msgid "Creating signals from datetime objects and strings" msgstr "Création de signaux à partir d'objets datetime et de chaînes" msgid "Using different time units (hours, minutes, seconds, milliseconds, etc.)" msgstr "Utilisation de différentes unités de temps (heures, minutes, secondes, millisecondes, etc.)" msgid "Visualizing datetime signals with proper time formatting" msgstr "Visualisation des signaux datetime avec un formatage temporel approprié" msgid "CSV I/O with datetime preservation" msgstr "Entrée/Sortie CSV avec préservation des datetimes" msgid "Roundtrip testing across all supported time units" msgstr "Tests de roundtrip sur toutes les unités de temps prises en charge" msgid "This tutorial uses PlotPy for visualization, providing interactive plots with properly formatted datetime axes." msgstr "Ce tutoriel utilise PlotPy pour la visualisation, fournissant des graphiques interactifs avec des axes datetime correctement formatés." msgid "Importing necessary modules" msgstr "Importation des modules nécessaires" msgid "We'll start by importing all the required modules for datetime signal processing and visualization." msgstr "Nous commencerons par importer tous les modules nécessaires au traitement des signaux datetime et à la visualisation." msgid "Creating datetime signals from datetime objects" msgstr "Création de signaux datetime à partir d'objets datetime" msgid "The most common way to create datetime signals is from Python datetime objects. This is useful when you have timestamps from sensors, logs, or other time-series data." msgstr "La façon la plus courante de créer des signaux datetime est à partir d'objets datetime Python. Cela est utile lorsque vous avez des horodatages provenant de capteurs, de journaux ou d'autres données de séries temporelles." msgid "Qt widget 1" msgstr "" msgid "Creating datetime signals from string timestamps" msgstr "Création de signaux datetime à partir d'horodatages sous forme de chaînes" msgid "Often, datetime data comes as strings (e.g., from CSV files or logs). Sigima can automatically parse common datetime string formats." msgstr "Souvent, les données datetime se présentent sous forme de chaînes (par exemple, à partir de fichiers CSV ou de journaux). Sigima peut automatiquement analyser les formats de chaînes datetime courants." msgid "Using different time units" msgstr "Utilisation de différentes unités de temps" msgid "Sigima supports various time units to match your data's natural resolution: nanoseconds (ns), microseconds (us), milliseconds (ms), seconds (s), minutes (min), and hours (h)." msgstr "Sigima prend en charge diverses unités de temps pour correspondre à la résolution naturelle de vos données : nanosecondes (ns), microsecondes (us), millisecondes (ms), secondes (s), minutes (min) et heures (h)." msgid "Comparing multiple datetime signals" msgstr "Comparaison de plusieurs signaux datetime" msgid "You can visualize multiple datetime signals together to compare trends." msgstr "Vous pouvez visualiser plusieurs signaux datetime ensemble pour comparer les tendances." msgid "Sigima automatically preserves datetime information when writing to CSV, storing timestamps as human-readable strings instead of opaque float values." msgstr "Sigima préserve automatiquement les informations datetime lors de l'écriture dans un fichier CSV, stockant les horodatages sous forme de chaînes lisibles par l'homme plutôt que de valeurs flottantes opaques." msgid "Summary" msgstr "Résumé" msgid "This example demonstrated the complete datetime signal workflow in Sigima:" msgstr "Cet exemple a démontré le flux de travail complet des signaux datetime dans Sigima :" msgid "**Creating datetime signals** from objects and strings" msgstr "**Création de signaux datetime** à partir d'objets et de chaînes" msgid "**Multiple time units** (ns, us, ms, s, min, h) stored in `xunit` attribute" msgstr "**Plusieurs unités de temps** (ns, us, ms, s, min, h) stockées dans l'attribut `xunit`" msgid "**Visualization** with properly formatted datetime axes" msgstr "**Visualisation** avec des axes datetime correctement formatés" msgid "**CSV I/O** with automatic datetime preservation" msgstr "**CSV I/O** avec préservation automatique des datetime" msgid "The time unit is stored in the signal's `xunit` attribute, making it easy to access and consistent with other signal metadata. DateTime support makes Sigima ideal for time-series analysis, sensor data processing, and any application requiring human-readable temporal information." msgstr "L'unité de temps est stockée dans l'attribut `xunit` du signal, ce qui facilite l'accès et assure la cohérence avec les autres métadonnées du signal. La prise en charge des datetime fait de Sigima un outil idéal pour l'analyse des séries temporelles, le traitement des données de capteurs et toute application nécessitant des informations temporelles lisibles par l'homme." msgid ":download:`Download Jupyter notebook: datetime_signals.ipynb `" msgstr "" msgid ":download:`Download Python source code: datetime_signals.py `" msgstr "" msgid ":download:`Download zipped: datetime_signals.zip `" msgstr "" msgid "`Gallery generated by Sphinx-Gallery `_" msgstr "" Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/auto_examples/features/index.po000066400000000000000000000020471514013333200252540ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2025, DataLab Platform Developers # This file is distributed under the same license as the Sigima package. # FIRST AUTHOR , 2025. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: Sigima \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid "Various Features" msgstr "Fonctionnalités diverses" msgid ":ref:`sphx_glr_auto_examples_features_convolution.py`" msgstr "" msgid ":ref:`sphx_glr_auto_examples_features_datalab_client.py`" msgstr "" msgid ":ref:`sphx_glr_auto_examples_features_datetime_signals.py`" msgstr "" msgid ":ref:`sphx_glr_auto_examples_features_roi_grid.py`" msgstr "" msgid ":ref:`sphx_glr_auto_examples_features_coordinate_systems.py`" msgstr "" msgid ":ref:`sphx_glr_auto_examples_features_zero_padding.py`" msgstr "" Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/auto_examples/features/roi_grid.po000066400000000000000000000146231514013333200257460ustar00rootroot00000000000000# Génération de grille de ROI. # Copyright (C) 2025, DataLab Platform Developers # This file is distributed under the same license as the Sigima package. # Pierre Raybaut, 2025. # msgid "" msgstr "" "Project-Id-Version: Sigima \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: 2025-12-16 12:00+0100\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid ":ref:`Go to the end ` to download the full example code." msgstr ":ref:`Aller à la fin ` pour télécharger le code complet de l'exemple." msgid "ROI Grid Generation" msgstr "Génération de grille de ROI" msgid "This example focuses on generating grids of rectangular ROIs for systematic analysis of regular patterns in images using Sigima's ROI grid feature. Using a real laser spot array image, we'll explore how to create, configure, and apply ROI grids for extracting individual spots." msgstr "Cet exemple se concentre sur la génération de grilles de ROI rectangulaires pour l'analyse systématique de motifs réguliers dans les images à l'aide de la fonctionnalité de grille de ROI de Sigima. En utilisant une image réelle de matrice de spots laser, nous explorerons comment créer, configurer et appliquer des grilles de ROI pour extraire des spots individuels." msgid "The example shows:" msgstr "Cet exemple montre :" msgid "Loading a real-world laser spot array image" msgstr "Le chargement d'une image réelle de matrice de spots laser" msgid "Extracting a sub-region for clearer visualization" msgstr "L'extraction d'une sous-région pour une visualisation plus claire" msgid "Generating a grid of rectangular ROIs" msgstr "La génération d'une grille de ROI rectangulaires" msgid "Configuring grid parameters (size, translation, step spacing)" msgstr "La configuration des paramètres de la grille (taille, translation, espacement)" msgid "Understanding direction labels (row/column ordering)" msgstr "La compréhension des labels de direction (ordre des lignes/colonnes)" msgid "Extracting individual spots using the generated ROIs" msgstr "L'extraction de spots individuels à l'aide des ROI générées" msgid "Visualizing the ROIs on the image" msgstr "La visualisation des ROI sur l'image" msgid "This tutorial uses PlotPy for visualization, providing interactive plots that allow you to explore the ROI grid placement in detail." msgstr "Ce tutoriel utilise PlotPy pour la visualisation, fournissant des graphiques interactifs qui permettent d'explorer en détail le placement de la grille de ROI." msgid "Importing necessary modules" msgstr "Importation des modules nécessaires" msgid "We'll start by importing all the required modules for image processing and visualization." msgstr "Nous commencerons par importer tous les modules nécessaires au traitement d'images et à la visualisation." msgid "Loading a real laser spot array image" msgstr "Chargement d'une image réelle de matrice de spots laser" msgid "We'll use a laser spot array image with a 6×6 grid of spots. This is a realistic example where we need to analyze each spot individually." msgstr "Nous utiliserons une image de matrice de spots laser avec une grille 6×6 de spots. C'est un exemple réaliste où nous devons analyser chaque spot individuellement." msgid "Extracting a 2×2 sub-region" msgstr "Extraction d'une sous-région 2×2" msgid "For clearer visualization of the ROI grid feature, we'll extract a 2×2 sub-region from the center of the full 6×6 spot array." msgstr "Pour une visualisation plus claire de la fonctionnalité de grille de ROI, nous extrairons une sous-région 2×2 du centre de la matrice complète 6×6 de spots." msgid "Qt widget 1" msgstr "" msgid "Creating a basic grid of ROIs" msgstr "Création d'une grille de base de ROI" msgid "Now we'll generate a 2×2 grid of ROIs to match the extracted spot array. Each ROI will be centered on a spot for individual analysis." msgstr "Nous allons maintenant générer une grille 2×2 de ROI correspondant à la matrice de spots extraite. Chaque ROI sera centrée sur un spot pour une analyse individuelle." msgid "Extracting individual spots" msgstr "Extraction de spots individuels" msgid "Once the ROI grid is defined, we can extract individual spots as separate images for further analysis." msgstr "Une fois la grille de ROI définie, nous pouvons extraire les spots individuels sous forme d'images séparées pour une analyse plus approfondie." msgid "Adjusting ROI size and position" msgstr "Ajustement de la taille et de la position des ROI" msgid "The ROI size and translation parameters control how the ROIs are placed within each grid cell. Let's explore different configurations." msgstr "Les paramètres de taille et de translation des ROI contrôlent comment les ROI sont placées dans chaque cellule de la grille. Explorons différentes configurations." msgid "Understanding direction labels" msgstr "Compréhension des labels de direction" msgid "The xdirection and ydirection parameters control how rows and columns are numbered. This affects the ROI titles but not the geometry." msgstr "Les paramètres xdirection et ydirection contrôlent comment les lignes et les colonnes sont numérotées. Cela affecte les titres des ROI mais pas la géométrie." msgid "Summary and conclusions" msgstr "Résumé et conclusions" msgid "This tutorial demonstrated the key concepts of ROI grid generation for systematic analysis of regular patterns in images using Sigima." msgstr "Ce tutoriel a présenté les concepts clés de la génération de grille de ROI pour l'analyse systématique de motifs réguliers dans les images à l'aide de Sigima." msgid ":download:`Download Jupyter notebook: roi_grid.ipynb `" msgstr ":download:`Télécharger le notebook Jupyter : roi_grid.ipynb `" msgid ":download:`Download Python source code: roi_grid.py `" msgstr ":download:`Télécharger le code source Python : roi_grid.py `" msgid ":download:`Download zipped: roi_grid.zip `" msgstr ":download:`Télécharger l'archive : roi_grid.zip `" msgid "`Gallery generated by Sphinx-Gallery `_" msgstr "`Galerie générée par Sphinx-Gallery `_" Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/auto_examples/features/zero_padding.po000066400000000000000000000133321514013333200266110ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2025, DataLab Platform Developers # This file is distributed under the same license as the Sigima package. # FIRST AUTHOR , 2025. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: Sigima \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid ":ref:`Go to the end ` to download the full example code." msgstr "" msgid "Zero Padding for FFT Enhancement" msgstr "Remplissage par zéro pour l'amélioration de la FFT" msgid "This example demonstrates how to apply zero-padding to signals, a common technique used to improve FFT frequency resolution. It shows the proper usage of :class:`sigima.params.ZeroPadding1DParam`, including the important ``update_from_obj()`` call." msgstr "Cet exemple montre comment appliquer un remplissage par zéro aux signaux, une technique courante utilisée pour améliorer la résolution en fréquence de la FFT. Il montre l'utilisation correcte de :class:`sigima.params.ZeroPadding1DParam`, y compris l'appel important à ``update_from_obj()``." msgid "Zero-padding adds zeros to a signal, effectively interpolating the frequency domain representation. This is particularly useful for:" msgstr "Le remplissage par zéro ajoute des zéros à un signal, interpolant ainsi la représentation dans le domaine fréquentiel. Cela est particulièrement utile pour :" msgid "Improving frequency resolution in FFT analysis" msgstr "Amélioration de la résolution en fréquence dans l'analyse FFT" msgid "Preparing signals for convolution operations" msgstr "Préparation des signaux pour les opérations de convolution" msgid "Matching signal lengths for spectral comparisons" msgstr "Correspondance des longueurs de signal pour les comparaisons spectrales" msgid "Importing the required modules" msgstr "Importation des modules requis" msgid "Create a test signal" msgstr "Créer un signal de test" msgid "We create a simple cosine signal with a specific frequency." msgstr "Nous créons un simple signal cosinus avec une fréquence spécifique." msgid "Qt widget 1" msgstr "" msgid "Zero-padding with \"next_pow2\" strategy" msgstr "Remplissage par zéro avec la stratégie \"next_pow2\"" msgid "The \"next_pow2\" strategy pads the signal to the next power of 2, which is optimal for FFT computations." msgstr "La stratégie \"next_pow2\" remplit le signal jusqu'à la prochaine puissance de 2, ce qui est optimal pour les calculs FFT." msgid "When using strategies other than \"custom\", you **must call** ``update_from_obj()`` to compute the number of padding points based on the actual signal size." msgstr "Lors de l'utilisation de stratégies autres que \"custom\", vous **devez appeler** ``update_from_obj()`` pour calculer le nombre de points de remplissage en fonction de la taille réelle du signal." msgid "Compare original and padded signals" msgstr "Comparer les signaux originaux et remplis" msgid "The padded signal has zeros appended at the end." msgstr "Le signal rempli a des zéros ajoutés à la fin." msgid "FFT comparison: improved frequency resolution" msgstr "Comparaison FFT : résolution en fréquence améliorée" msgid "Zero-padding improves the apparent frequency resolution of the FFT by interpolating between frequency bins." msgstr "Le remplissage par zéro améliore la résolution en fréquence apparente de la FFT en interpolant entre les bins de fréquence." msgid "Using different strategies" msgstr "Utilisation de différentes stratégies" msgid "The available strategies are:" msgstr "Les stratégies disponibles sont :" msgid "``\"next_pow2\"``: Pad to the next power of 2 (optimal for FFT)" msgstr "``\"next_pow2\"`` : Remplir jusqu'à la prochaine puissance de 2 (optimal pour la FFT)" msgid "``\"double\"``: Double the signal length" msgstr "``\"double\"`` : Doubler la longueur du signal" msgid "``\"triple\"``: Triple the signal length" msgstr "``\"triple\"`` : Tripler la longueur du signal" msgid "``\"custom\"``: Specify the exact number of points to add" msgstr "``\"custom\"`` : Spécifier le nombre exact de points à ajouter" msgid "Using \"custom\" strategy" msgstr "Utilisation de la stratégie \"custom\"" msgid "With the \"custom\" strategy, you specify the exact number of points. In this case, ``update_from_obj()`` is not strictly necessary (but harmless)." msgstr "Avec la stratégie \"custom\", vous spécifiez le nombre exact de points. Dans ce cas, ``update_from_obj()`` n'est pas strictement nécessaire (mais sans danger)." msgid "Choosing padding location" msgstr "Choix de l'emplacement du remplissage" msgid "Zero-padding can be applied at different locations:" msgstr "Le remplissage par zéro peut être appliqué à différents emplacements :" msgid "``\"append\"``: Add zeros at the end (default)" msgstr "``\"append\"`` : Ajouter des zéros à la fin (par défaut)" msgid "``\"prepend\"``: Add zeros at the beginning" msgstr "``\"prepend\"`` : Ajouter des zéros au début" msgid "``\"both\"``: Split zeros between beginning and end" msgstr "``\"both\"`` : Répartir les zéros entre le début et la fin" msgid ":download:`Download Jupyter notebook: zero_padding.ipynb `" msgstr "" msgid ":download:`Download Python source code: zero_padding.py `" msgstr "" msgid ":download:`Download zipped: zero_padding.zip `" msgstr "" msgid "`Gallery generated by Sphinx-Gallery `_" msgstr "`Galerie générée par Sphinx-Gallery `_" Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/auto_examples/getting_started/000077500000000000000000000000001514013333200251535ustar00rootroot00000000000000Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/auto_examples/getting_started/image_creation.po000066400000000000000000000166271514013333200304750ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2025, DataLab Platform Developers # This file is distributed under the same license as the Sigima package. # FIRST AUTHOR , 2025. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: Sigima \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid ":ref:`Go to the end ` to download the full example code." msgstr ":ref:`Aller à la fin ` pour télécharger l'exemple de code complet." msgid "Creating Images" msgstr "Création d'images" msgid "This example focuses on creating 2D image objects in Sigima." msgstr "Cet exemple se concentre sur la création d'objets images 2D dans Sigima." msgid "There are three primary methods to create images in Sigima:" msgstr "Il existe trois méthodes principales pour créer des images dans Sigima :" msgid "**Synthetic data generation**: Using built-in parameter classes to create standard" msgstr "**Génération de données synthétiques** : utilisation de classes de paramètres intégrées pour créer des" msgid "image types (Gaussian, ramp, random distributions, etc.)" msgstr "types d'images standards (gaussienne, rampe, distributions aléatoires, etc.)" msgid "**Loading from files**: Importing data from various file formats" msgstr "**Chargement depuis des fichiers** : importation de données depuis divers formats de fichiers" msgid "**From NumPy arrays**: Creating objects directly from existing arrays" msgstr "**Depuis des tableaux NumPy** : création d'objets directement depuis des tableaux existants" msgid "Each method has its use cases, and Sigima provides a consistent interface for working with data regardless of its origin." msgstr "Chaque méthode a ses cas d'usage, et Sigima fournit une interface cohérente pour travailler avec les données quelle que soit leur origine." msgid "For visualization, we use helper functions from the ``sigima.viz`` module. This allows us to focus on Sigima's functionality rather than visualization details." msgstr "Pour la visualisation, nous utilisons des fonctions auxiliaires du module ``sigima.viz``. Cela nous permet de nous concentrer sur les fonctionnalités de Sigima plutôt que sur les détails de visualisation." msgid "Importing necessary modules" msgstr "Import des modules nécessaires" msgid "First of all, we need to import the required modules." msgstr "Tout d'abord, nous devons importer les modules requis." msgid "Method 1: Creating images from synthetic parameters" msgstr "Méthode 1 : Création d'images à partir de paramètres synthétiques" msgid "Similar to signals, Sigima can generate synthetic images using parameter classes." msgstr "Comme pour les signaux, Sigima peut générer des images synthétiques à l'aide de classes de paramètres." msgid "Available image types include:" msgstr "Les types d'images disponibles incluent :" msgid "Distributions: Normal (Gaussian noise), Uniform, Poisson" msgstr "Distributions : normale (bruit gaussien), uniforme, Poisson" msgid "Analytical functions: 2D Gaussian, 2D ramp (bilinear form)" msgstr "Fonctions analytiques : gaussienne 2D, rampe 2D (forme bilinéaire)" msgid "Blank images: Zeros" msgstr "Images vierges : zéros" msgid "Qt widget 1" msgstr "" msgid "Method 2: Loading images from files" msgstr "Méthode 2 : Chargement d'images depuis des fichiers" msgid "Sigima supports a wide range of image file formats, both common and scientific." msgstr "Sigima prend en charge une large gamme de formats de fichiers image, à la fois courants et scientifiques." msgid "Supported formats include:" msgstr "Les formats pris en charge incluent :" msgid "Common formats: BMP, JPEG, PNG, TIFF, JPEG 2000" msgstr "Formats courants : BMP, JPEG, PNG, TIFF, JPEG 2000" msgid "Scientific formats: DICOM, Andor SIF, Spiricon, Dürr NDT" msgstr "Formats scientifiques : DICOM, Andor SIF, Spiricon, Dürr NDT" msgid "Data formats: NumPy (.npy), MATLAB (.mat), HDF5 (.h5img)" msgstr "Formats de données : NumPy (.npy), MATLAB (.mat), HDF5 (.h5img)" msgid "Text formats: CSV, TXT, ASC (with coordinate support)" msgstr "Formats texte : CSV, TXT, ASC (avec prise en charge des coordonnées)" msgid "Method 3: Creating images from NumPy arrays" msgstr "" msgid "Convert existing NumPy arrays into Sigima image objects to add metadata, coordinate systems, and enable advanced processing." msgstr "Convertir les tableaux NumPy existants en objets image Sigima pour ajouter des métadonnées, des systèmes de coordonnées et activer le traitement avancé." msgid "Summary" msgstr "Résumé" msgid "This example demonstrated the three main ways to create images in Sigima:" msgstr "Cet exemple a démontré les trois principales façons de créer des images dans Sigima :" msgid "**Synthetic generation**: Fast creation of standard mathematical functions and distributions using parameter classes. Perfect for testing and simulation." msgstr "**Génération synthétique** : création rapide de fonctions mathématiques standards et de distributions à l'aide de classes de paramètres. Parfait pour les tests et la simulation." msgid "**File loading**: Read data from various scientific and common file formats, with automatic format detection and metadata extraction. Essential for working with experimental data." msgstr "**Chargement de fichiers** : lecture de données depuis divers formats de fichiers scientifiques et courants, avec détection automatique du format et extraction des métadonnées. Essentiel pour travailler avec des données expérimentales." msgid "**NumPy array conversion**: Wrap existing array data with Sigima's rich metadata and processing capabilities. Ideal for custom workflows and integration with other Python libraries." msgstr "**Conversion de tableaux NumPy** : encapsulation de données de tableaux existants avec les riches métadonnées et capacités de traitement de Sigima. Idéal pour les flux de travail personnalisés et l'intégration avec d'autres bibliothèques Python." msgid "All three methods produce equivalent Sigima objects that can be processed, analyzed, and visualized using the same set of tools and functions. Choose the method that best fits your workflow and data source." msgstr "Les trois méthodes produisent des objets Sigima équivalents qui peuvent être traités, analysés et visualisés en utilisant le même ensemble d'outils et de fonctions. Choisissez la méthode qui correspond le mieux à votre flux de travail et à votre source de données." msgid ":download:`Download Jupyter notebook: image_creation.ipynb `" msgstr ":download:`Télécharger le notebook Jupyter : image_creation.ipynb `" msgid ":download:`Download Python source code: image_creation.py `" msgstr ":download:`Télécharger le code source Python : image_creation.py `" msgid ":download:`Download zipped: image_creation.zip `" msgstr ":download:`Télécharger compressé : image_creation.zip `" msgid "`Gallery generated by Sphinx-Gallery `_" msgstr "`Galerie générée par Sphinx-Gallery `_" Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/auto_examples/getting_started/index.po000066400000000000000000000013741514013333200266270ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2025, DataLab Platform Developers # This file is distributed under the same license as the Sigima package. # FIRST AUTHOR , 2025. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: Sigima \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid "Getting Started" msgstr "Premiers pas" msgid ":ref:`sphx_glr_auto_examples_getting_started_image_creation.py`" msgstr "" msgid ":ref:`sphx_glr_auto_examples_getting_started_signal_creation.py`" msgstr "" Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/auto_examples/getting_started/signal_creation.po000066400000000000000000000230611514013333200306560ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2025, DataLab Platform Developers # This file is distributed under the same license as the Sigima package. # FIRST AUTHOR , 2025. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: Sigima \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid ":ref:`Go to the end ` to download the full example code." msgstr ":ref:`Aller à la fin ` pour télécharger l'exemple de code complet." msgid "Creating Signals" msgstr "Création de signaux" msgid "This example focuses on creating 1D signal objects in Sigima." msgstr "Cet exemple se concentre sur la création d'objets signaux 1D dans Sigima." msgid "There are three primary methods to create signals in Sigima:" msgstr "Il existe trois méthodes principales pour créer des signaux dans Sigima :" msgid "**Synthetic data generation**: Using built-in parameter classes to create standard" msgstr "**Génération de données synthétiques** : utilisation de classes de paramètres intégrées pour créer des" msgid "signal types (Gaussian, sine waves, random distributions, etc.)" msgstr "types de signaux standards (gaussienne, ondes sinusoïdales, distributions aléatoires, etc.)" msgid "**Loading from files**: Importing data from various file formats" msgstr "**Chargement depuis des fichiers** : importation de données depuis divers formats de fichiers" msgid "**From NumPy arrays**: Creating objects directly from existing arrays" msgstr "**Depuis des tableaux NumPy** : création d'objets directement depuis des tableaux existants" msgid "Each method has its use cases, and Sigima provides a consistent interface for working with data regardless of its origin." msgstr "Chaque méthode a ses cas d'usage, et Sigima fournit une interface cohérente pour travailler avec les données quelle que soit leur origine." msgid "For visualization, we use helper functions from the ``sigima.viz`` module. This allows us to focus on Sigima's functionality rather than visualization details." msgstr "Pour la visualisation, nous utilisons des fonctions auxiliaires du module ``sigima.viz``. Cela nous permet de nous concentrer sur les fonctionnalités de Sigima plutôt que sur les détails de visualisation." msgid "Importing necessary modules" msgstr "Import des modules nécessaires" msgid "First of all, we need to import the required modules." msgstr "Tout d'abord, nous devons importer les modules requis." msgid "Method 1: Creating signals from synthetic parameters" msgstr "Méthode 1 : Création de signaux à partir de paramètres synthétiques" msgid "Sigima provides built-in generators for common signal types. This is the most convenient method when you need standard mathematical functions or random distributions." msgstr "Sigima fournit des générateurs intégrés pour les types de signaux courants. C'est la méthode la plus pratique lorsque vous avez besoin de fonctions mathématiques standards ou de distributions aléatoires." msgid "Available signal types include:" msgstr "Les types de signaux disponibles incluent :" msgid "Mathematical functions: Gaussian, Lorentzian, Sinc, Sine, Cosine, etc." msgstr "Fonctions mathématiques : gaussienne, lorentzienne, sinc, sinus, cosinus, etc." msgid "Random distributions: Normal, Uniform, Poisson" msgstr "Distributions aléatoires : normale, uniforme, Poisson" msgid "Standard waveforms: Square, Sawtooth, Triangle" msgstr "Formes d'ondes standards : carrée, en dents de scie, triangulaire" msgid "Special functions: Planck (blackbody), Linear chirp, Step, Exponential" msgstr "Fonctions spéciales : Planck (corps noir), chirp linéaire, échelon, exponentielle" msgid "Qt widget 1" msgstr "" msgid "Method 2: Loading signals from files" msgstr "Méthode 2 : Chargement de signaux depuis des fichiers" msgid "Sigima can read signals from various file formats, automatically detecting the format and extracting metadata when available." msgstr "Sigima peut lire des signaux depuis divers formats de fichiers, en détectant automatiquement le format et en extrayant les métadonnées lorsqu'elles sont disponibles." msgid "Supported formats include:" msgstr "Les formats pris en charge incluent :" msgid "Text files: CSV, TXT (with automatic delimiter detection)" msgstr "Fichiers texte : CSV, TXT (avec détection automatique du délimiteur)" msgid "Scientific formats: HDF5 (.h5sig), MAT-Files (.mat), NumPy (.npy)" msgstr "Formats scientifiques : HDF5 (.h5sig), MAT-Files (.mat), NumPy (.npy)" msgid "Specialized: MCA spectrum files (.mca), FT-Lab (.sig)" msgstr "Spécialisés : fichiers de spectre MCA (.mca), FT-Lab (.sig)" msgid "Qt widget 2" msgstr "" msgid "It is interesting to remark here that when importing data from files, Sigima automatically extracts and preserves metadata when possible. This includes:" msgstr "Il est intéressant de noter ici que lors de l'importation de données depuis des fichiers, Sigima extrait et préserve automatiquement les métadonnées lorsque c'est possible. Cela inclut :" msgid "**Axis labels and units**: Column headers from CSV files, variable names from MAT-Files, etc." msgstr "**Étiquettes et unités des axes** : en-têtes de colonnes des fichiers CSV, noms de variables des MAT-Files, etc." msgid "**Acquisition parameters**: DICOM headers, instrument settings, timestamps" msgstr "**Paramètres d'acquisition** : en-têtes DICOM, paramètres d'instruments, horodatages" msgid "**Physical coordinates**: Pixel spacing, origin coordinates when stored in the file" msgstr "**Coordonnées physiques** : espacement des pixels, coordonnées d'origine lorsqu'elles sont stockées dans le fichier" msgid "The extracted metadata is seamlessly integrated into the signal or image object, making it available for processing, analysis, and visualization without manual configuration." msgstr "Les métadonnées extraites sont intégrées de manière transparente dans l'objet signal ou image, les rendant disponibles pour le traitement, l'analyse et la visualisation sans configuration manuelle." msgid "Method 3: Creating signals from NumPy arrays" msgstr "Méthode 3 : Création de signaux à partir de tableaux NumPy" msgid "When you already have data in NumPy arrays (from calculations, other libraries, or custom data sources), you can wrap them in Sigima signal objects to benefit from metadata handling and processing functions." msgstr "Lorsque vous avez déjà des données dans des tableaux NumPy (provenant de calculs, d'autres bibliothèques ou de sources de données personnalisées), vous pouvez les encapsuler dans des objets signaux Sigima pour bénéficier de la gestion des métadonnées et des fonctions de traitement." msgid "Summary" msgstr "Résumé" msgid "This example demonstrated the three main ways to create signals in Sigima:" msgstr "Cet exemple a démontré les trois principales façons de créer des signaux dans Sigima :" msgid "**Synthetic generation**: Fast creation of standard mathematical functions and distributions using parameter classes. Perfect for testing and simulation." msgstr "**Génération synthétique** : création rapide de fonctions mathématiques standards et de distributions à l'aide de classes de paramètres. Parfait pour les tests et la simulation." msgid "**File loading**: Read data from various scientific and common file formats, with automatic format detection and metadata extraction. Essential for working with experimental data." msgstr "**Chargement de fichiers** : lecture de données depuis divers formats de fichiers scientifiques et courants, avec détection automatique du format et extraction des métadonnées. Essentiel pour travailler avec des données expérimentales." msgid "**NumPy array conversion**: Wrap existing array data with Sigima's rich metadata and processing capabilities. Ideal for custom workflows and integration with other Python libraries." msgstr "**Conversion de tableaux NumPy** : encapsulation de données de tableaux existants avec les riches métadonnées et capacités de traitement de Sigima. Idéal pour les flux de travail personnalisés et l'intégration avec d'autres bibliothèques Python." msgid "All three methods produce equivalent Sigima objects that can be processed, analyzed, and visualized using the same set of tools and functions. Choose the method that best fits your workflow and data source." msgstr "Les trois méthodes produisent des objets Sigima équivalents qui peuvent être traités, analysés et visualisés en utilisant le même ensemble d'outils et de fonctions. Choisissez la méthode qui correspond le mieux à votre flux de travail et à votre source de données." msgid ":download:`Download Jupyter notebook: signal_creation.ipynb `" msgstr ":download:`Télécharger le notebook Jupyter : signal_creation.ipynb `" msgid ":download:`Download Python source code: signal_creation.py `" msgstr ":download:`Télécharger le code source Python : signal_creation.py `" msgid ":download:`Download zipped: signal_creation.zip `" msgstr ":download:`Télécharger compressé : signal_creation.zip `" msgid "`Gallery generated by Sphinx-Gallery `_" msgstr "`Galerie générée par Sphinx-Gallery `_" Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/auto_examples/index.po000066400000000000000000000063121514013333200234350ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2025, DataLab Platform Developers # This file is distributed under the same license as the Sigima package. # FIRST AUTHOR , 2025. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: Sigima \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid "Examples" msgstr "Exemples" msgid "This section presents a collection of examples demonstrating the capabilities of Sigima. Each example is a standalone Python script that showcases specific features or use cases of the Sigima library, along with visualizations of the results (using the `sigima.viz` module with the `PlotPyStack `_ backend)." msgstr "Cette section présente une collection d'exemples démontrant les capacités de Sigima. Chaque exemple est un script Python autonome qui met en avant des fonctionnalités ou des cas d'utilisation spécifiques de la bibliothèque Sigima, accompagnés de visualisations des résultats (en utilisant le module `sigima.viz` avec le backend `PlotPyStack `_)." msgid "Of course, some of these examples may seem trivial, but they serve to illustrate how to use various functionalities of Sigima in a clear and concise manner." msgstr "Bien sûr, certains de ces exemples peuvent sembler triviaux, mais ils servent à illustrer comment utiliser diverses fonctionnalités de Sigima de manière claire et concise." msgid "These examples are automatically generated when building the documentation, thus ensuring that they are always up-to-date with the latest version of Sigima." msgstr "Ces exemples sont générés automatiquement lors de la construction de la documentation, garantissant ainsi qu'ils sont toujours fonctionnels avec la dernière version de Sigima." msgid "Getting Started" msgstr "Premiers pas" msgid ":ref:`sphx_glr_auto_examples_getting_started_image_creation.py`" msgstr "" msgid ":ref:`sphx_glr_auto_examples_getting_started_signal_creation.py`" msgstr "" msgid "Use Cases" msgstr "Cas d'usage" msgid ":ref:`sphx_glr_auto_examples_use_cases_blob_detection.py`" msgstr "" msgid ":ref:`sphx_glr_auto_examples_use_cases_fabry_perot.py`" msgstr "" msgid ":ref:`sphx_glr_auto_examples_use_cases_laser_beam.py`" msgstr "" msgid ":ref:`sphx_glr_auto_examples_use_cases_spectrum_analysis.py`" msgstr "" msgid "Various Features" msgstr "Fonctionnalités diverses" msgid ":ref:`sphx_glr_auto_examples_features_convolution.py`" msgstr "" msgid ":ref:`sphx_glr_auto_examples_features_datalab_client.py`" msgstr "" msgid ":ref:`sphx_glr_auto_examples_features_datetime_signals.py`" msgstr "" msgid ":ref:`sphx_glr_auto_examples_features_roi_grid.py`" msgstr "" msgid ":ref:`sphx_glr_auto_examples_features_coordinate_systems.py`" msgstr "" msgid ":ref:`sphx_glr_auto_examples_features_zero_padding.py`" msgstr "" msgid "`Gallery generated by Sphinx-Gallery `_" msgstr "`Galerie générée par Sphinx-Gallery `_" Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/auto_examples/use_cases/000077500000000000000000000000001514013333200237365ustar00rootroot00000000000000Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/auto_examples/use_cases/blob_detection.po000066400000000000000000000206041514013333200272540ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2025, DataLab Platform Developers # This file is distributed under the same license as the Sigima package. # FIRST AUTHOR , 2025. # msgid "" msgstr "" "Project-Id-Version: Sigima \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid ":ref:`Go to the end ` to download the full example code." msgstr ":ref:`Aller à la fin ` pour télécharger le code complet de l'exemple." msgid "Blob Detection" msgstr "Détection de taches" msgid "This example demonstrates blob detection techniques available in Sigima for analyzing circular or blob-like features in images. It shows how to generate apply preprocessing filters and detect blobs using OpenCV-based algorithms with fine-tuned parameters for optimal results." msgstr "Cet exemple illustre les techniques de détection de taches disponibles dans Sigima pour analyser des structures circulaires ou en amas dans des images. Il montre comment générer des filtres de prétraitement et détecter des taches à l'aide d'algorithmes basés sur OpenCV, avec des paramètres ajustés pour obtenir des résultats optimaux." msgid "The script demonstrates image processing workflows commonly used in microscopy, particle analysis, and feature detection applications." msgstr "Le script présente des chaînes de traitement d'image couramment utilisées en microscopie, en analyse de particules et dans les applications de détection de caractéristiques." msgid "Importing necessary modules" msgstr "On importe les modules nécessaires" msgid "We start by importing all the required modules for image processing and visualization. To run this example, ensure you have all the required dependencies installed." msgstr "On commence par importer tous les modules nécessaires au traitement d'image et à la visualisation. Pour exécuter cet exemple, on vérifie que l'ensemble des dépendances requises est installé." msgid "Generate synthetic test image with known blobs" msgstr "Générer une image de test synthétique avec des taches connues" msgid "We create a synthetic image with a noisy background and several circular blobs of varying sizes and intensities. This allows us to validate the blob detection algorithms effectively. To perform this task, we use a function: the detailes of this is out of the scope of this tutorial: once you have learned how to use Sigima, you will be able to use the library on your own data." msgstr "On crée une image synthétique avec un bruit de fond et plusieurs taches circulaires de tailles et d'intensités variées. Cette configuration permet de valider efficacement les algorithmes de détection de taches. Pour réaliser cette tâche, on utilise une fonction dédiée dont les détails dépassent le cadre de ce tutoriel ; une fois que vous maîtriserez Sigima, vous pourrez appliquer la bibliothèque à vos propres données." msgid "Visualize the original image" msgstr "Visualiser l'image originale" msgid "We visualize the original synthetic image to understand its characteristics before applying any processing or blob detection. This can be done with your preferred image viewer (i.e. plotpy, matplotlib, ...). The preference of Sigima developers is on plotpy, a library developed with performance in mind." msgstr "On visualise l'image synthétique originale pour en apprécier les caractéristiques avant tout traitement ou détection de blobs. On peut utiliser la visionneuse d'images de son choix (par exemple plotpy, matplotlib, ...). Les développeurs de Sigima privilégient plotpy, une bibliothèque conçue pour la performance." msgid "We wrapped a simple function to do perform visualizations tasks required for this and other tutorials, to help reducing the impact of GUI code in documentation and let you concentrate in the analysis" msgstr "On a encapsulé une fonction simple pour réaliser les visualisations nécessaires à ce tutoriel et aux autres, afin de limiter l'impact du code lié à l'interface graphique dans la documentation et de vous laisser vous concentrer sur l'analyse." msgid "Qt widget 1" msgstr "" msgid "Image preprocessing - Binning" msgstr "Prétraitement d'image - binning" msgid "Looking to our image, we can see that the blobs we look for are large respect to the pixel size. A binning process can help to reduce the importance of the noise." msgstr "Observez l'image : les taches recherchées sont grandes par rapport à la taille des pixels. Un binning aide à réduire l'importance du bruit." msgid "Additional preprocessing - Moving median filter" msgstr "Prétraitement supplémentaire - filtre médian glissant" msgid "The result of the binning is good, but we can imagine to not be happy with that. A different approach we can take is to apply a moving median filter, to reduce the importance of the spikes. We do it with a window of 5, of curse in practice different window sizes can be tested to find the good compromise between noise reduction and resolution. Lets see how to do that." msgstr "Le résultat du binning est satisfaisant, mais il est possible de vouloir aller plus loin. On applique alors un filtre médian glissant pour atténuer les pics. On utilise ici une fenêtre de 5 ; en pratique, on teste différentes tailles de fenêtre pour trouver le bon compromis entre réduction du bruit et résolution. Voyons comment procéder." msgid "Configure blob detection parameters" msgstr "Configurer les paramètres de détection de taches" msgid "We are happy with the filtered image, we can now proceed to the blob detection. First of all we need to configure the parameters of the detection algorithm: this is very important to get good results. In this example, you find an overview of the parameters that can be tuned." msgstr "On valide l'image filtrée et on passe à la détection de taches. On commence par configurer les paramètres de l'algorithme de détection, étape essentielle pour obtenir de bons résultats. Cet exemple offre une vue d'ensemble des paramètres ajustables." msgid "Create blob detection parameter object:" msgstr "Créer l'objet de paramètres de détection de taches :" msgid "Threshold parameters for blob detection:" msgstr "Paramètres de seuil pour la détection de taches :" msgid "Minimum repeatability (how many times a blob center is detected):" msgstr "Répétabilité minimale (nombre de fois où le centre d'une tache est détecté) :" msgid "Color filtering (not used for grayscale):" msgstr "Filtrage sur la couleur (non utilisé en niveaux de gris) :" msgid "Area filtering to select appropriate blob sizes:" msgstr "Filtrage sur la surface pour sélectionner les tailles de taches adaptées :" msgid "Circularity filtering to prefer round objects:" msgstr "Filtrage sur la circularité pour privilégier les objets ronds :" msgid "Disable inertia and convexity filtering for this example:" msgstr "Désactiver le filtrage sur l'inertie et la convexité pour cet exemple :" msgid "We finally print configured parameters:" msgstr "On affiche enfin les paramètres configurés :" msgid "Perform blob detection" msgstr "Exécuter la détection de taches" msgid "We can now perform the blob detection on the preprocessed image using the configured parameters." msgstr "On peut maintenant lancer la détection de taches sur l'image prétraitée avec les paramètres configurés." msgid "We print the detected blobs and their properties:" msgstr "On affiche les taches détectées et leurs propriétés :" msgid ":download:`Download Jupyter notebook: blob_detection.ipynb `" msgstr ":download:`Télécharger le notebook Jupyter : blob_detection.ipynb `" msgid ":download:`Download Python source code: blob_detection.py `" msgstr ":download:`Télécharger le code source Python : blob_detection.py `" msgid ":download:`Download zipped: blob_detection.zip `" msgstr ":download:`Télécharger l'archive : blob_detection.zip `" msgid "`Gallery generated by Sphinx-Gallery `_" msgstr "`Galerie générée par Sphinx-Gallery `_" Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/auto_examples/use_cases/convolution.po000066400000000000000000000067301514013333200266630ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2025, DataLab Platform Developers # This file is distributed under the same license as the Sigima package. # FIRST AUTHOR , 2025. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: Sigima \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid ":ref:`Go to the end ` to download the full example code." msgstr "" msgid "Image Blurring and Sharpening with Convolution" msgstr "" msgid "This example demonstrates the image convolution and deconvolution features available in Sigima, showing various kernels and their effects on images. Each section builds upon the previous one to create a comprehensive understanding of convolution operations." msgstr "" msgid "The example shows:" msgstr "" msgid "Creating test images and kernels" msgstr "" msgid "Basic convolution with Gaussian kernel" msgstr "" msgid "Identity convolution (preserving original image)" msgstr "" msgid "Deconvolution operations" msgstr "" msgid "Effects of different kernel parameters" msgstr "" msgid "Custom edge detection and sharpening kernels" msgstr "" msgid "This tutorial uses PlotPy for visualization, providing interactive plots that allow you to explore the convolution results in detail." msgstr "" msgid "Importing necessary modules" msgstr "" msgid "We'll start by importing all the required modules for image processing and visualization." msgstr "" msgid "We start by creating a test image and various convolution kernels." msgstr "" msgid "Qt widget 1" msgstr "" msgid "Now we'll perform convolution with the Gaussian kernel and compare the result with scipy's implementation to verify correctness." msgstr "" msgid "Identity convolution" msgstr "" msgid "Identity convolution should preserve the original image exactly. This demonstrates that our convolution implementation is working correctly." msgstr "" msgid "Deconvolution with identity kernel" msgstr "" msgid "Deconvolution is the inverse operation of convolution. We'll start with a simple case using the identity kernel." msgstr "" msgid "Advanced deconvolution with Gaussian kernel" msgstr "" msgid "Now we'll try deconvolution with a Gaussian kernel, which is more challenging and demonstrates the limitations of deconvolution." msgstr "" msgid "Exploring different kernel parameters" msgstr "" msgid "Different sigma values in Gaussian kernels produce different blurring effects. Let's compare several sigma values side by side." msgstr "" msgid "Qt widget 2" msgstr "" msgid "Custom convolution kernels" msgstr "" msgid "Besides Gaussian kernels, we can create custom kernels for specific image processing tasks like edge detection and sharpening." msgstr "" msgid "Summary and conclusions" msgstr "" msgid "This tutorial demonstrated the key concepts of convolution and deconvolution in image processing using Sigima." msgstr "" msgid ":download:`Download Jupyter notebook: convolution.ipynb `" msgstr "" msgid ":download:`Download Python source code: convolution.py `" msgstr "" msgid ":download:`Download zipped: convolution.zip `" msgstr "" msgid "`Gallery generated by Sphinx-Gallery `_" msgstr "" Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/auto_examples/use_cases/fabry_perot.po000066400000000000000000000152421514013333200266160ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2025, DataLab Platform Developers # This file is distributed under the same license as the Sigima package. # FIRST AUTHOR , 2025. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: Sigima \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid ":ref:`Go to the end ` to download the full example code." msgstr ":ref:`Aller à la fin ` pour télécharger le code complet de l'exemple." msgid "Fabry-Perot Interference Pattern" msgstr "Franges d'interférence de Fabry-Perot" msgid "This example demonstrates image processing techniques for analyzing Fabry-Perot interference patterns. It shows how to load experimental images, define regions of interest, detect circular contours, and extract intensity profiles for quantitative analysis of interference fringes." msgstr "Ce tutoriel présente des techniques de traitement d'image pour analyser les franges d'interférence de Fabry-Perot. On y montre comment charger des images expérimentales, définir des régions d'intérêt, détecter des contours circulaires et extraire des profils d'intensité pour analyser quantitativement les franges." msgid "Usage:" msgstr "Utilisation :" msgid "python fabry_perot_example.py" msgstr "" msgid "The script demonstrates optical analysis workflows commonly used in interferometry, optical metrology, and precision measurements." msgstr "Ce script illustre des flux d'analyse optique couramment utilisés en interférométrie, en métrologie optique et en mesures de précision." msgid "Importing necessary modules" msgstr "Importer les modules nécessaires" msgid "We start by importing all the required modules for image processing and visualization. To run this example, ensure you have all the required dependencies installed." msgstr "On commence par importer tous les modules nécessaires au traitement d'image et à la visualisation. Pour exécuter cet exemple, assurez-vous que toutes les dépendances requises sont installées." msgid "Load Fabry-Perot test images" msgstr "Charger les images d'essai Fabry-Perot" msgid "We load two sample image of Fabry-Perot interference patterns. These imags is included in the Sigima test data. We will analyze the interference fringes present in these images." msgstr "On charge deux images d'exemple de franges d'interférence de Fabry-Perot. Elles sont fournies avec les données de test de Sigima. On analysera les franges d'interférence présentes dans ces images." msgid "Qt widget 1" msgstr "" msgid "Define circular ROI for fringe analysis" msgstr "Définir une ROI circulaire pour l'analyse des franges" msgid "We define a circular region of interest (ROI) centered on the image to focus our analysis on the central interference fringes." msgstr "On définit une région d'intérêt (ROI) circulaire centrée sur l'image pour concentrer l'analyse sur les franges d'interférence centrales." msgid "Configure contour detection for circular fringes" msgstr "Configurer la détection de contours circulaires" msgid "We can now detect circular contours in the defined ROI. This will help us identify the interference rings. To perform this, the first step is to set up the contour detection parameter." msgstr "On peut maintenant détecter des contours circulaires dans la ROI définie. Cela permet d'identifier les anneaux d'interférence. Pour ce faire, la première étape consiste à paramétrer la détection de contours." msgid "We can now perform the contour detection on the image using the configured parameters." msgstr "On peut ensuite exécuter la détection de contours sur l'image à l'aide des paramètres définis." msgid "We can now print the detected circular contours and their properties" msgstr "On peut afficher les contours circulaires détectés ainsi que leurs propriétés" msgid "Extract horizontal intensity profile" msgstr "Extraire le profil d'intensité horizontal" msgid "We can extract an intensity profile along a horizontal line through the center of the image. This profile will show the intensity variations across the interference fringes. As before, we need to set up the line profile extraction parameter." msgstr "On peut extraire un profil d'intensité le long d'une ligne horizontale passant par le centre de l'image. Ce profil met en évidence les variations d'intensité au travers des franges d'interférence. Comme précédemment, il faut paramétrer l'extraction du profil linéaire." msgid "Load the second Fabry-Perot image" msgstr "Charger la deuxième image Fabry-Perot" msgid "We want now to load the Analyze second Fabry-Perot image" msgstr "On souhaite maintenant charger et analyser la deuxième image Fabry-Perot" msgid "Contour detection on second image" msgstr "Détecter les contours sur la deuxième image" msgid "To perform the contour detection on the second image, we can reuse the same contour detection parameters defined earlier. This technique, applied to multiple images, allow to perform the same analysis on each of them and make comparisons easier." msgstr "Pour effectuer la détection des contours sur la deuxième image, on peut réutiliser les mêmes paramètres de détection définis précédemment. Cette technique, appliquée à plusieurs images, permet de répéter la même analyse et de faciliter les comparaisons." msgid "Extract profile from second image and compare both profiles" msgstr "Extraire le profil de la deuxième image et comparer les deux profils" msgid "We can extract the horizontal intensity profile from the second image using the same profile extraction parameters defined earlier." msgstr "On peut extraire le profil d'intensité horizontal de la deuxième image en réutilisant les paramètres d'extraction définis précédemment." msgid ":download:`Download Jupyter notebook: fabry_perot.ipynb `" msgstr ":download:`Télécharger le notebook Jupyter : fabry_perot.ipynb `" msgid ":download:`Download Python source code: fabry_perot.py `" msgstr ":download:`Télécharger le code source Python : fabry_perot.py `" msgid ":download:`Download zipped: fabry_perot.zip `" msgstr ":download:`Télécharger l'archive zip : fabry_perot.zip `" msgid "`Gallery generated by Sphinx-Gallery `_" msgstr "`Galerie générée par Sphinx-Gallery `_" Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/auto_examples/use_cases/index.po000066400000000000000000000015771514013333200254170ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2025, DataLab Platform Developers # This file is distributed under the same license as the Sigima package. # FIRST AUTHOR , 2025. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: Sigima \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid "Use Cases" msgstr "Cas d'usage" msgid ":ref:`sphx_glr_auto_examples_use_cases_blob_detection.py`" msgstr "" msgid ":ref:`sphx_glr_auto_examples_use_cases_fabry_perot.py`" msgstr "" msgid ":ref:`sphx_glr_auto_examples_use_cases_laser_beam.py`" msgstr "" msgid ":ref:`sphx_glr_auto_examples_use_cases_spectrum_analysis.py`" msgstr "" Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/auto_examples/use_cases/laser_beam.po000066400000000000000000000231161514013333200263730ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2025, DataLab Platform Developers # This file is distributed under the same license as the Sigima package. # FIRST AUTHOR , 2025. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: Sigima \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid ":ref:`Go to the end ` to download the full example code." msgstr ":ref:`Aller à la fin ` pour télécharger le code complet de l'exemple." msgid "Laser Beam Size Measurement Example" msgstr "Analyser la taille d'un faisceau laser" msgid "This example demonstrates comprehensive laser beam analysis techniques following the laser beam tutorial workflow. It shows how to load multiple laser beam images, analyze background noise with histograms, apply proper clipping, detect beam centroids, extract line and radial profiles, compute FWHM measurements, and track beam size evolution along the propagation axis." msgstr "Ce tutoriel présente des techniques complètes d'analyse de faisceau laser en suivant le déroulé du guide. On y montre comment charger plusieurs images de faisceau, analyser le bruit de fond avec des histogrammes, appliquer un seuillage adapté, détecter les centroïdes, extraire des profils linéaires et radiaux, calculer des mesures de FWHM et suivre l'évolution de la taille du faisceau le long de l'axe de propagation." msgid "The script demonstrates advanced optical beam characterization workflows commonly used in laser physics, beam quality assessment, and optical system design." msgstr "Ce script illustre des procédés avancés de caractérisation optique couramment utilisés en physique des lasers, pour qualifier un faisceau et concevoir des systèmes optiques." msgid "Importing necessary modules" msgstr "Importer les modules nécessaires" msgid "We start by importing all the required modules for image processing and visualization. To run this example, ensure you have all the required dependencies installed." msgstr "On commence par importer tous les modules nécessaires au traitement d'image et à la visualisation. Pour exécuter cet exemple, assurez-vous que toutes les dépendances requises sont installées." msgid "Load all laser beam images" msgstr "Charger toutes les images du faisceau laser" msgid "We load a series of laser beam images taken at different positions along the propagation axis (z-axis). The images are contained in the folder laser_beam and named following the pattern TEM00_z_*.jpg, where * is the z position in arbitrary units." msgstr "On charge une série d'images de faisceau laser prises à différentes positions le long de l'axe de propagation (axe z). Les images se trouvent dans le dossier laser_beam et respectent le motif TEM00_z_*.jpg, où * est la position z en unités arbitraires." msgid "Visualize the first few images" msgstr "Visualiser les premières images" msgid "Qt widget 1" msgstr "" msgid "Background noise analysis with histogram" msgstr "Analyser le bruit de fond avec un histogramme" msgid "To analyze the background noise characteristics of the laser beam images, we create a histogram of pixel values from the first image. This helps us identify the noise floor and determine an appropriate clipping threshold." msgstr "Pour analyser le bruit de fond des images du faisceau, on crée un histogramme des valeurs de pixels à partir de la première image. Cela nous aide à identifier le niveau de bruit et à fixer un seuil de seuillage adapté." msgid "Based on the histogram analysis, we determine a clipping threshold around 30-35 LSB to effectively remove background noise from all images." msgstr "D'après l'analyse de l'histogramme, on fixe un seuil de seuillage autour de 30-35 LSB pour supprimer efficacement le bruit de fond sur toutes les images." msgid "Background noise removal via clipping" msgstr "Éliminer le bruit de fond par seuillage" msgid "We set the threshold to 35 and we apply this clipping to each image in the dataset." msgstr "On règle le seuil à 35 et on applique ce seuillage à chaque image du jeu de données." msgid "In order to perform the clipping, we create a ClipParam object and set the minimum value to the background threshold. We then apply the clipping to each image in the dataset." msgstr "Pour réaliser ce seuillage, on crée un objet ClipParam et on fixe la valeur minimale au seuil du bruit de fond. On applique ensuite le traitement à chaque image du jeu de données." msgid "We can now visualize some clipped images:" msgstr "On peut maintenant afficher quelques images seuillées :" msgid "Compute centroids for beam center detection" msgstr "Calculer les centroïdes pour détecter le centre du faisceau" msgid "Next, we compute the centroid of each clipped image to determine the beam center. This is important for accurate profile extraction and FWHM measurements." msgstr "Ensuite, on calcule le centroïde de chaque image seuillée afin de déterminer le centre du faisceau. C'est essentiel pour extraire des profils précis et mesurer correctement la FWHM." msgid "Extract line profiles through beam centers" msgstr "Extraire des profils linéaires passant par le centre" msgid "We extract horizontal line profiles through the detected centroids of each clipped image. This provides insight into the beam intensity distribution along a horizontal cross-section." msgstr "On extrait des profils horizontaux passant par les centroïdes détectés de chaque image seuillée. Cela renseigne sur la distribution d'intensité du faisceau le long d'une coupe horizontale." msgid "Extract radial profiles around beam centers" msgstr "Extraire des profils radiaux autour du centre" msgid "We extract radial profiles centered on the detected centroids of each clipped image. This provides a circular intensity distribution useful for FWHM measurements." msgstr "On extrait des profils radiaux centrés sur les centroïdes détectés pour chaque image seuillée. On obtient ainsi une distribution d'intensité circulaire utile pour les mesures de FWHM." msgid "We can now visualize some radial profiles" msgstr "On peut maintenant visualiser quelques profils radiaux" msgid "Compute FWHM for radial profiles" msgstr "Calculer la FWHM des profils radiaux" msgid "We compute the Full Width at Half Maximum (FWHM) for each radial profile to quantify the beam size. The FWHM is a standard metric for beam width." msgstr "On calcule la largeur à mi-hauteur (FWHM) de chaque profil radial pour quantifier la taille du faisceau. La FWHM est un indicateur standard de la largeur du faisceau." msgid "That's done, we can now print some FWHM statistics to check our results:" msgstr "C'est fait, on peut maintenant afficher quelques statistiques de FWHM pour vérifier les résultats :" msgid "Everything seems fine, we can now analyze the beam size evolution along the z-axis." msgstr "Tout semble correct, on peut maintenant analyser l'évolution de la taille du faisceau le long de l'axe z." msgid "Analyze beam size evolution" msgstr "Analyser l'évolution de la taille du faisceau" msgid "Having computed the FWHM for each radial profile, we can now analyze how the beam size evolves along the propagation axis (z-axis). This is useful to extract some meaningful information from all the numbers we have obtained. We create a signal representing the beam size evolution and visualize it." msgstr "Après avoir calculé la FWHM pour chaque profil radial, on peut analyser comment la taille du faisceau évolue le long de l'axe de propagation (axe z). Cela permet d'extraire des informations pertinentes à partir des valeurs obtenues. On crée un signal représentant cette évolution et on le visualise." msgid "The beam evolution signal currently uses image index as the x-axis, and even if we can see the trend, it is not very informative. It would be way better to have the x-axis in mm." msgstr "Le signal d'évolution du faisceau utilise actuellement l'indice d'image sur l'axe x. Même si la tendance est visible, ce n'est pas très parlant ; ce serait bien mieux d'exprimer l'axe x en mm." msgid "Apply z-axis calibration" msgstr "Appliquer l'étalonnage de l'axe z" msgid "We apply a linear calibration to the x-axis of the beam evolution signal to convert image index to physical distance in mm. In Sigima there is the possibility to perform a linear axis calibration. We use the formula x' = 5*x + 15, where x is the image index and x' is the calibrated distance in mm." msgstr "On applique un étalonnage linéaire à l'axe x du signal d'évolution pour convertir l'indice d'image en distance physique en mm. Sigima permet de réaliser un étalonnage linéaire d'axe. On utilise la formule x' = 5*x + 15, où x est l'indice d'image et x' la distance calibrée en mm." msgid ":download:`Download Jupyter notebook: laser_beam.ipynb `" msgstr ":download:`Télécharger le notebook Jupyter : laser_beam.ipynb `" msgid ":download:`Download Python source code: laser_beam.py `" msgstr ":download:`Télécharger le code source Python : laser_beam.py `" msgid ":download:`Download zipped: laser_beam.zip `" msgstr ":download:`Télécharger l'archive zip : laser_beam.zip `" msgid "`Gallery generated by Sphinx-Gallery `_" msgstr "`Galerie générée par Sphinx-Gallery `_" Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/auto_examples/use_cases/spectrum_analysis.po000066400000000000000000000274071514013333200300550ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2025, DataLab Platform Developers # This file is distributed under the same license as the Sigima package. # FIRST AUTHOR , 2025. # msgid "" msgstr "" "Project-Id-Version: Sigima \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid ":ref:`Go to the end ` to download the full example code." msgstr ":ref:`Aller à la fin ` pour télécharger le code complet de l'exemple." msgid "Spectrum Analysis" msgstr "Analyse de spectre" msgid "This example demonstrates advanced signal processing for spectroscopy analysis using a paracetamol spectrum. It shows how to apply noise reduction, region of interest selection, peak fitting, and detrending techniques available in Sigima. Each step builds upon the previous one to create a comprehensive analysis workflow." msgstr "Cet exemple présente un traitement avancé du signal pour l'analyse spectroscopique d'un spectre de paracétamol. On y montre comment appliquer une réduction de bruit, sélectionner une région d'intérêt, ajuster des pics et supprimer une tendance grâce aux fonctionnalités de Sigima. Chaque étape s'appuie sur la précédente pour construire un flux d'analyse complet." msgid "Usage:" msgstr "Utilisation :" msgid "python paracetamol_example.py" msgstr "python paracetamol_example.py" msgid "The script demonstrates spectroscopy data processing workflows commonly used in analytical chemistry and materials science applications." msgstr "Ce script illustre des flux de traitement de données spectroscopiques couramment utilisés en chimie analytique et en science des matériaux." msgid "Load test signal and initial visualization" msgstr "Charger le signal test et visualiser l'aperçu initial" msgid "We load a sample paracetamol spectrum included in the Sigima test data. This spectrum contains characteristic absorption peaks that we will analyze using various signal processing techniques." msgstr "On charge un spectre de paracétamol fourni dans les données de test de Sigima. Ce spectre contient des pics d'absorption caractéristiques que l'on analyse à l'aide de différentes techniques de traitement du signal." msgid "Qt widget 1" msgstr "" msgid "Apply Wiener filter for noise reduction" msgstr "Appliquer un filtre de Wiener pour réduire le bruit" msgid "The signal is quite clean. Anyway, to illustrate the filtering capabilities of Sigima, we apply a Wiener filter to reduce any residual noise while preserving the spectral features." msgstr "Le signal est déjà très propre. Toutefois, pour illustrer les capacités de filtrage de Sigima, on applique un filtre de Wiener afin de réduire tout bruit résiduel tout en préservant les caractéristiques spectrales." msgid "Region of Interest (ROI) selection" msgstr "Sélectionner une région d'intérêt (ROI)" msgid "We fistly focus our analysis on one of the peaks of interest. To to that, we define a region of interest (ROI) around the feature we want to analyze." msgstr "On concentre d'abord l'analyse sur un pic d'intérêt. Pour cela, on définit une région d'intérêt (ROI) autour de la caractéristique que l'on souhaite analyser." msgid "Gaussian fit on the peak" msgstr "Ajuster le pic avec une gaussienne" msgid "We can now fit the peak within the selected ROI using a Gaussian model. This provides quantitative parameters such as peak position, amplitude, and width." msgstr "On peut maintenant ajuster le pic dans la ROI sélectionnée à l'aide d'un modèle gaussien. Cela fournit des paramètres quantitatifs tels que la position, l'amplitude et la largeur du pic." msgid "Linear detrending" msgstr "Supprimer la tendance linéaire" msgid "After fitting the main peak, we may want to remove any baseline drift present in the entire spectrum." msgstr "Après avoir ajusté le pic principal, on peut vouloir supprimer toute dérive de ligne de base présente dans l'ensemble du spectre." msgid "The detrending function of Sigima performs a linear fit on the whole signal, including the peaks. In our signal peaks take a large part of the signal itself, witch is enough for signals where the peak are symmetrically distributed around the center, with more or less the same amplitude. This is not the case here, and we cannot expect this function to work well. It is however an interesting example to illustrate how Sigima functions can be combined to perform a more advanced analysis." msgstr "La fonction de suppression de tendance de Sigima réalise un ajustement linéaire sur tout le signal, y compris les pics. Dans notre spectre, les pics occupent une grande partie du signal, ce qui convient aux signaux où ils sont répartis symétriquement autour du centre avec des amplitudes similaires. Ce n'est pas le cas ici et on ne peut pas s'attendre à ce que cette fonction soit performante. C'est toutefois un exemple intéressant pour montrer comment combiner les fonctions de Sigima afin de mener une analyse plus avancée." msgid "In order to visualize the limitation cited above, we apply the detrending function directly on the filtered signal. It's important to remembre that we setted a ROI on the signal to focus the analysis on the main peak. We need to remove this ROI constraint to perform the detrending on the full signal." msgstr "Pour illustrer la limitation mentionnée ci-dessus, on applique la fonction de suppression de tendance directement sur le signal filtré. Il est important de se souvenir que l'on avait défini une ROI afin de se concentrer sur le pic principal. On doit supprimer cette contrainte de ROI pour appliquer la suppression de tendance sur l'intégralité du signal." msgid "The comparison shows, as expected, that the detrending function does not work well on this signal. This, as explained before, is due to the alogirithm used, which performs a linear fit on the whole signal, including the peaks. This effect is clearly visible on the plot: the peaks on the left, that are higher than the ones on the right, starts after the detrending at an intensity value lower than the ones on the right, and all peaks has a baseline under the zero." msgstr "La comparaison montre, comme prévu, que la fonction de suppression de tendance n'est pas adaptée à ce signal. Comme expliqué plus haut, l'algorithme réalise un ajustement linéaire sur tout le signal, y compris les pics. Cet effet apparaît clairement sur la figure : les pics de gauche, plus élevés que ceux de droite, se retrouvent après la suppression de tendance avec une intensité initiale plus faible que ceux de droite, et tous les pics possèdent une ligne de base négative." msgid "Improved detrending with peak exclusion" msgstr "Améliorer la suppression de tendance en excluant les pics" msgid "An idea to overcome the limitation of the detrending function is suggested from the behavior of the detrended signal: we already identified the problem, which is that the linear fit is not performed on the baseline only, but also on the peaks." msgstr "Une idée pour contourner la limitation de la fonction de suppression de tendance vient du comportement du signal traité : on a identifié que le problème vient du fait que l'ajustement linéaire n'est pas effectué uniquement sur la ligne de base mais aussi sur les pics." msgid "To perform a better detrending, we can first thus detect the peaks and then perform a linear fit only on the non-peak regions. We reasonably expect this approach to provide a more accurate baseline estimation and a better detrended signal." msgstr "Pour obtenir une meilleure suppression de tendance, on peut donc détecter d'abord les pics puis ajuster une droite uniquement sur les zones sans pic. On s'attend raisonnablement à ce que cette approche fournisse une estimation de ligne de base plus précise et un signal mieux corrigé." msgid "Automatic peak detection" msgstr "Détecter automatiquement les pics" msgid "We can use the peak detection function of Sigima to automatically identify the peaks in the spectrum. This function analyzes the signal and returns the indices of the detected peaks." msgstr "On peut utiliser la fonction de détection de pics de Sigima pour identifier automatiquement les pics du spectre. Cette fonction analyse le signal et renvoie les indices des pics détectés." msgid "Multi-Gaussian fitting" msgstr "Ajuster plusieurs gaussiennes" msgid "We can now fit multiple Gaussian functions to the detected peaks. This allows us to characterize each peak individually and obtain parameters such as position, amplitude, and width for each peak." msgstr "On peut maintenant ajuster plusieurs fonctions gaussiennes sur les pics détectés. Cela permet de caractériser chaque pic individuellement et d'obtenir pour chacun la position, l'amplitude et la largeur." msgid "Defining ROI outside peaks for better detrending" msgstr "Définir des ROI hors pics pour améliorer la suppression de tendance" msgid "To improve the detrending, we define ROIs that exclude the detected peaks. This allows us to fit the baseline only on the non-peak regions." msgstr "Pour améliorer la suppression de tendance, on définit des ROI qui excluent les pics détectés. Cela permet d'ajuster la ligne de base uniquement sur les zones sans pic." msgid "We can now perform a linear fit on the signal using the defined ROIs to exclude the peaks. This will provide a more accurate baseline estimation." msgstr "On peut ensuite ajuster une droite sur le signal en utilisant les ROI définies pour exclure les pics. On obtient ainsi une estimation plus précise de la ligne de base." msgid "Finally, we can subtract the extended linear fit from the original filtered signal to obtain a better detrended signal. We can see that the baseline is now properly estimated, leading to a more accurate detrended signal." msgstr "On peut enfin soustraire l'ajustement linéaire étendu du signal filtré original pour obtenir un signal mieux débarrassé de sa tendance. On constate que la ligne de base est désormais correctement estimée, ce qui conduit à une correction plus fiable." msgid "To go futher..." msgstr "Pour aller plus loin..." msgid "In the last step we really improved the detrending of our signal. Anyway, several pics on the left of the signal are still not detected and the dentrending can be futher improved. We suggest you to experiment by tuning the parameters of the peak detection function and put your hands on the source code of this function to better understand how it works." msgstr "À la dernière étape, on a nettement amélioré la suppression de tendance du signal. Toutefois, plusieurs pics situés à gauche ne sont toujours pas détectés et la correction peut encore progresser. Nous vous invitons à expérimenter en ajustant les paramètres de la fonction de détection de pics et à explorer son code source pour mieux comprendre son fonctionnement." msgid ":download:`Download Jupyter notebook: spectrum_analysis.ipynb `" msgstr ":download:`Télécharger le notebook Jupyter : spectrum_analysis.ipynb `" msgid ":download:`Download Python source code: spectrum_analysis.py `" msgstr ":download:`Télécharger le code source Python : spectrum_analysis.py `" msgid ":download:`Download zipped: spectrum_analysis.zip `" msgstr ":download:`Télécharger l'archive zip : spectrum_analysis.zip `" msgid "`Gallery generated by Sphinx-Gallery `_" msgstr "`Galerie générée par Sphinx-Gallery `_" Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/contributing/000077500000000000000000000000001514013333200216255ustar00rootroot00000000000000Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/contributing/contribute_code.po000066400000000000000000000064441514013333200253450ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2023, DataLab Platform Developers # This file is distributed under the same license as the DataLab package. # FIRST AUTHOR , 2023. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: DataLab \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language-Team: LANGUAGE \n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid "Contribute code" msgstr "Contribuer au code" msgid "This page explains how you can contribute code to the project." msgstr "Cette page explique comment vous pouvez contribuer au code du projet." msgid "The :ref:`guidelines` page presents the coding guidelines that you should follow when contributing to the project." msgstr "Les règles de codage sont présentées dans la page :ref:`guidelines`." msgid "Fork the project" msgstr "Forker le projet" msgid "The first step is to fork the project on GitHub. You can do that by visiting `DataLab GitHub project `_ and clicking on the \"Fork\" button on the top right corner of the page." msgstr "La première étape est de forker le projet sur GitHub. Vous pouvez le faire en visitant le projet DataLab et en cliquant sur le bouton \"Fork\" en haut à droite de la `page GitHub du projet `_." msgid "Once you have forked the project, you will have a copy of the project in your own GitHub account. Then you can clone the project on your computer and start working on it." msgstr "Une fois que vous avez forké le projet, vous aurez une copie du projet dans votre propre compte GitHub. Ensuite, vous pouvez cloner le projet sur votre ordinateur et commencer à travailler dessus." msgid "Submit a pull request" msgstr "Soumettre une pull request" msgid "Once you have made some changes, you can submit a pull request to the original project. To do that, go to your forked project on GitHub and click on the \"Pull request\" button on the top right corner of the page." msgstr "Dès que vous avez apporté des modifications, vous pouvez soumettre une pull request au projet original. Pour ce faire, allez sur votre projet forké sur GitHub et cliquez sur le bouton \"Pull request\" en haut à droite de la page." msgid "Then you will have to fill a form to describe your pull request. Once you have submitted the pull request, the project maintainers will review your changes and merge them if they are satisfied." msgstr "Ensuite vous devrez remplir un formulaire pour décrire votre pull request. Une fois que vous avez soumis la pull request, les mainteneurs du projet examineront vos modifications et les fusionneront s'ils sont satisfaits." msgid "During the review process, the project maintainers will check that your code follows the coding guidelines and that it does not break the existing tests. If your code does not follow the coding guidelines, you will have to fix it before your pull request can be merged." msgstr "Lors du processus de revue, les mainteneurs du projet vérifieront que votre code suit les règles de codage et qu'il ne casse pas les tests existants. Si votre code ne suit pas les directives de codage, vous devrez le corriger avant que votre pull request puisse être fusionnée." Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/contributing/dependencies.po000066400000000000000000000201221514013333200246100ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2023, DataLab Platform Developers # This file is distributed under the same license as the DataLab package. # FIRST AUTHOR , 2025. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: DataLab \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid "About Dependencies" msgstr "A propos des dépendances" msgid "Dependencies are an important part of any software project, and they can significantly affect the development process. In this section, we will discuss the dependencies used in our project, how to manage them, and best practices for keeping them up to date." msgstr "Les dépendances sont une partie importante de tout projet logiciel, et elles peuvent affecter considérablement le processus de développement. Dans cette section, nous allons discuter des dépendances utilisées dans notre projet, comment les gérer et les meilleures pratiques pour les maintenir à jour." msgid "Managing Dependencies" msgstr "Gérer les dépendances" msgid "Dependencies are defined in the `pyproject.toml` file, as officially recommended by the Python packaging authority (see `Writing your pyproject.toml `_)." msgstr "Les dépendances sont définies dans le fichier `pyproject.toml`, comme recommandé officiellement par l'autorité de packaging Python (voir `Writing your pyproject.toml `_)." msgid "The `pyproject.toml` file contains many sections, but the most relevant for dependencies are:" msgstr "\"Le fichier `pyproject.toml` contient de nombreuses sections, mais les plus pertinentes pour les dépendances sont :" msgid "`[project.dependencies]`: This section lists the direct dependencies of the application. These are the packages that the application needs to run." msgstr "`[project.dependencies]`: Cette section liste les dépendances directes de l'application. Ce sont les paquets dont l'application a besoin pour fonctionner." msgid "`[project.optional-dependencies]`: This section lists optional dependencies that can be installed to enable additional features. These dependencies are not required for the core functionality of the application but can enhance its capabilities." msgstr "`[project.optional-dependencies]`: Cette section liste les dépendances optionnelles qui peuvent être installées pour activer des fonctionnalités supplémentaires. Ces dépendances ne sont pas nécessaires au fonctionnement de base de l'application, mais peuvent améliorer ses capacités." msgid "Among the optional dependencies, we have the following groups:" msgstr "Parmi les dépendances optionnelles, nous avons les groupes suivants :" msgid "`opencv`: computer vision tasks requiring OpenCV." msgstr "`opencv`: tâches de traitement d'image nécessitant OpenCV." msgid "`dev`: development and testing (linters, formatters, etc.)." msgstr "`dev`: développement et tests (analyseurs de code, formateurs, etc.)." msgid "`doc`: building the documentation (Sphinx, etc.)." msgstr "`doc`: construction de la documentation (Sphinx, etc.)." msgid "`test`: running the tests (pytest, etc.)." msgstr "`test`: exécution des tests (pytest, etc.)." msgid "`qt`: Qt-based graphical user interface (for interactive testing purposes)." msgstr "`qt`: interface graphique basée sur Qt (pour les tests interactifs)." msgid "Deploying Dependencies" msgstr "Déployer les dépendances" msgid "Production" msgstr "En production" msgid "In production, we recommend using the package manager that is most suitable for your environment and that you are most comfortable with. All package managers (e.g., `pip`, `conda`) are directly or indirectly using the information from the `pyproject.toml` file to install the dependencies." msgstr "En production, nous recommandons d'utiliser le gestionnaire de paquets qui convient le mieux à votre environnement et avec lequel vous êtes le plus à l'aise. Tous les gestionnaires de paquets (par exemple, `pip`, `conda`) utilisent directement ou indirectement les informations du fichier `pyproject.toml` pour installer les dépendances." msgid "See :ref:`installation` for more information on how to install DataLab and its dependencies." msgstr "Voir :ref:`installation` pour plus d'informations sur la façon d'installer DataLab et ses dépendances." msgid "Development" msgstr "En développement" msgid "In development, you may also use the requirements text file to make it easier to install the dependencies in a virtual environment or container." msgstr "En développement, vous pouvez également utiliser le fichier de texte des exigences pour faciliter l'installation des dépendances dans un environnement virtuel ou un conteneur." msgid "The `requirements.txt` file lists all the dependencies needed for the project, including both direct and optional dependencies. This is the exact list of dependencies that are defined in the `pyproject.toml` file, but formatted for use with `pip` or other package managers that support requirements files." msgstr "Le fichier `requirements.txt` liste toutes les dépendances nécessaires au projet, y compris les dépendances directes et optionnelles. C'est la liste exacte des dépendances qui sont définies dans le fichier `pyproject.toml`, mais formatée pour être utilisée avec `pip` ou d'autres gestionnaires de paquets qui prennent en charge les fichiers de dépendances." msgid "The requirements file is generated from the `pyproject.toml` file using a tool provided by the `guidata` package." msgstr "Le fichier de dépendances est généré à partir du fichier `pyproject.toml` à l'aide d'un outil fourni par le package `guidata`." msgid "Adding New Dependencies" msgstr "Ajouter de nouvelles dépendances" msgid "When adding new dependencies to the project, please follow these rules:" msgstr "Lors de l'ajout de nouvelles dépendances au projet, veuillez suivre ces règles :" msgid "If it is a direct dependency, that is a package that the application needs to run, add it to the `[project.dependencies]` section in the `pyproject.toml` file, and specify the version range that is compatible with the application, in order to avoid breaking changes." msgstr "Si c'est une dépendance directe, c'est-à-dire un paquet dont l'application a besoin pour fonctionner, ajoutez-le à la section `[project.dependencies]` dans le fichier `pyproject.toml`, et spécifiez la plage de versions compatible avec l'application, afin d'éviter les changements incompatibles." msgid "If it is an optional dependency, that is a package that can be installed to enable additional features, add it to the appropriate section in the `[project.optional-dependencies]` section in the `pyproject.toml` file." msgstr "Si c'est une dépendance optionnelle, c'est-à-dire un paquet qui peut être installé pour activer des fonctionnalités supplémentaires, ajoutez-le à la section appropriée dans la section `[project.optional-dependencies]` du fichier `pyproject.toml`." msgid "For the `dev` dependencies, unless it's absolutely necessary, do not specify a version range, as it may limit the ability to use the latest version of the package." msgstr "Pour les dépendances `dev`, sauf si c'est absolument nécessaire, ne spécifiez pas de plage de versions, car cela peut limiter la capacité à utiliser la dernière version du paquet." msgid "For the other optional dependencies, specify the version range that is compatible with the application, in order to avoid breaking changes." msgstr "Pour les autres dépendances optionnelles, spécifiez la plage de versions compatible avec l'application, afin d'éviter les changements incompatibles." msgid "In other words, except for the `dev` dependencies, always specify a version range that is compatible with the application." msgstr "En d'autres termes, sauf pour les dépendances `dev`, spécifiez toujours une plage de versions compatible avec l'application." Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/contributing/environment.po000066400000000000000000000222741514013333200245400ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2023, DataLab Platform Developers # This file is distributed under the same license as the DataLab package. # FIRST AUTHOR , 2023. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: DataLab \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid "Setting up Development Environment" msgstr "Mise en place de l'environnement de développement" msgid "Getting started with DataLab development is easy." msgstr "Démarrer le développement dans le cadre du projet DataLab est facile." msgid "Here is what you will need:" msgstr "Voici ce dont vous aurez besoin :" msgid "An integrated development environment (IDE) for Python. We recommend [Spyder](https://www.spyder-ide.org/) or [Visual Studio Code](https://code.visualstudio.com/), but any IDE will do." msgstr "Un environnement de développement intégré (IDE) pour Python. Nous recommandons [Spyder](https://www.spyder-ide.org/) ou [Visual Studio Code](https://code.visualstudio.com/), mais tout IDE fera l'affaire." msgid "A Python distribution. We recommend [WinPython](https://winpython.github.io/), on Windows, or [Anaconda](https://www.anaconda.com/), on Linux or Mac. But, again, any Python distribution will do." msgstr "Une distribution Python. Nous recommandons [WinPython](https://winpython.github.io/), sur Windows, ou [Anaconda](https://www.anaconda.com/), sur Linux ou Mac. Mais, encore une fois, n'importe quelle distribution Python fera l'affaire." msgid "A clean project structure (see below)." msgstr "Une structure de projet propre (voir ci-dessous)." msgid "Test data (see below)." msgstr "Des données de test (voir ci-dessous)." msgid "Environment variables (see below)." msgstr "Des variables d'environnement (voir ci-dessous)." msgid "Third-party software (see below)." msgstr "Des logiciels tiers (voir ci-dessous)." msgid "Development Environment" msgstr "Environnement de développement" msgid "If you are using [Spyder](https://www.spyder-ide.org/), thank you for supporting the scientific open-source Python community!" msgstr "Si vous utilisez [Spyder](https://www.spyder-ide.org/), merci de soutenir la communauté scientifique Python open-source !" msgid "If you are using Visual Studio Code, that's also an excellent choice (for other reasons). We recommend installing the following extensions:" msgstr "Si vous utilisez Visual Studio Code, c'est aussi un excellent choix (pour d'autres raisons). Nous recommandons d'installer les extensions suivantes :" msgid "Extension" msgstr "Extension" msgid "Description" msgstr "Description" msgid "[gettext](https://marketplace.visualstudio.com/items?itemName=mrorz.language-gettext)" msgstr "[gettext](https://marketplace.visualstudio.com/items?itemName=mrorz.language-gettext)" msgid "Gettext syntax highlighting" msgstr "Coloration syntaxique Gettext" msgid "[Pylance](https://marketplace.visualstudio.com/items?itemName=ms-python.vscode-pylance)" msgstr "[Pylance](https://marketplace.visualstudio.com/items?itemName=ms-python.vscode-pylance)" msgid "Python language server" msgstr "Serveur de langage Python" msgid "[Python](https://marketplace.visualstudio.com/items?itemName=ms-python.python)" msgstr "[Python](https://marketplace.visualstudio.com/items?itemName=ms-python.python)" msgid "Python extension" msgstr "Extension Python" msgid "[reStructuredText Syntax highlighting](https://marketplace.visualstudio.com/items?itemName=trond-snekvik.simple-rst)" msgstr "[reStructuredText Syntax highlighting](https://marketplace.visualstudio.com/items?itemName=trond-snekvik.simple-rst)" msgid "reStructuredText syntax highlighting" msgstr "Coloration syntaxique reStructuredText" msgid "[Ruff](https://marketplace.visualstudio.com/items?itemName=charliermarsh.ruff)" msgstr "[Ruff](https://marketplace.visualstudio.com/items?itemName=charliermarsh.ruff)" msgid "Extremely fast Python linter and code formatter" msgstr "Linter et formateur de code Python extrêmement rapide" msgid "[Todo Tree](https://marketplace.visualstudio.com/items?itemName=Gruntfuggly.todo-tree)" msgstr "[Todo Tree](https://marketplace.visualstudio.com/items?itemName=Gruntfuggly.todo-tree)" msgid "Todo tree" msgstr "Arbre de tâches" msgid "[Insert GUID](https://marketplace.visualstudio.com/items?itemName=heaths.vscode-guid)" msgstr "[Insert GUID](https://marketplace.visualstudio.com/items?itemName=heaths.vscode-guid)" msgid "Insert GUID" msgstr "Insérer un GUID" msgid "[XML Tools](https://marketplace.visualstudio.com/items?itemName=DotJoshJohnson.xml)" msgstr "[XML Tools](https://marketplace.visualstudio.com/items?itemName=DotJoshJohnson.xml)" msgid "XML Tools" msgstr "Outils XML" msgid "Python Environment" msgstr "Environnement Python" msgid "Sigima requires the following :" msgstr "Sigima nécessite les éléments suivants :" msgid "Python (e.g. WinPython)" msgstr "Python (p.ex. WinPython)" msgid "Additional Python packages" msgstr "Paquets Python supplémentaires" msgid "Installing all required packages :" msgstr "Installation de tous les paquets requis :" msgid "If you are using [WinPython](https://winpython.github.io/), thank you for supporting the scientific open-source Python community!" msgstr "Si vous utilisez [WinPython](https://winpython.github.io/), merci de soutenir la communauté scientifique Python open-source !" msgid "The following table lists the currently officially used Python distributions:" msgstr "Le tableau suivant liste les distributions Python actuellement utilisées officiellement :" msgid "Python version" msgstr "Version de Python" msgid "Status" msgstr "Statut" msgid "WinPython version" msgstr "Version de WinPython" msgid "3.9" msgstr "" msgid "OK" msgstr "" msgid "3.9.10.0" msgstr "" msgid "3.10" msgstr "" msgid "3.10.11.1" msgstr "" msgid "3.11" msgstr "" msgid "3.11.5.0" msgstr "" msgid "3.12" msgstr "" msgid "3.12.3.0" msgstr "" msgid "3.13" msgstr "" msgid "3.13.2.0" msgstr "" msgid "⚠ We strongly recommend using the `.dot` versions of WinPython which are lightweight and can be customized to your needs (using `pip install -r requirements.txt`)." msgstr "⚠ Nous recommandons fortement d'utiliser les versions `.dot` de WinPython qui sont légères et peuvent être personnalisées selon vos besoins (en utilisant `pip install -r requirements.txt`)." msgid "✅ We also recommend using a dedicated WinPython instance for Sigima." msgstr "✅ Nous recommandons également d'utiliser une instance WinPython dédiée pour Sigima." msgid "Test data" msgstr "Données de test" msgid "Sigima test data are located in different folders, depending on their nature or origin." msgstr "Les données de test de Sigima sont situées dans différents dossiers, selon leur nature ou leur origine." msgid "Required data for unit tests are located in \"sigima\\data\\tests\" (public data)." msgstr "Les données requises pour les tests unitaires sont situées dans \"sigima\\data\\tests\" (données publiques)" msgid "A second folder %SIGIMA_DATA% (optional) may be defined for additional tests which are still under development (or for confidential data)." msgstr "Un second dossier %SIGIMA_DATA% (facultatif) peut être défini pour des tests supplémentaires qui sont encore en cours de développement (ou pour des données confidentielles)." msgid "Specific environment variables" msgstr "Variables d'environnement spécifiques" msgid "Visual Studio Code configuration used in `launch.json` and/or `tasks.json` (examples) :" msgstr "La configuration de Visual Studio Code utilisée dans `launch.json` et/ou `tasks.json` (exemples) :" msgid "Visual Studio Code `.env` file:" msgstr "Fichier `.env` de Visual Studio Code :" msgid "This file is used to set environment variables for the application." msgstr "Ce fichier est utilisé pour définir les variables d'environnement de l'application." msgid "It is used to set the `PYTHONPATH` environment variable to the root of the project." msgstr "Il est utilisé pour définir la variable d'environnement `PYTHONPATH` à la racine du projet." msgid "This is required to be able to import the project modules from within VS Code." msgstr "Cela est nécessaire pour pouvoir importer les modules du projet depuis VS Code." msgid "To create this file, copy the `.env.template` file to `.env` (and eventually add your own paths)." msgstr "Pour créer ce fichier, copiez le fichier `.env.template` en `.env` (et ajoutez éventuellement vos propres chemins)." msgid "Third-party Software" msgstr "Logiciels tiers" msgid "The following software may be required for maintaining the project:" msgstr "Les logiciels suivants peuvent être nécessaires pour maintenir le projet :" msgid "Software" msgstr "Logiciel" msgid "[gettext](https://mlocati.github.io/articles/gettext-iconv-windows.html)" msgstr "" msgid "Translations" msgstr "Traductions" msgid "[Git](https://git-scm.com/)" msgstr "" msgid "Version control system" msgstr "Système de contrôle de version" msgid "[ImageMagick](https://imagemagick.org/)" msgstr "" msgid "Image manipulation utilities" msgstr "Utilitaires de manipulation d'images" Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/contributing/gitworkflow.po000066400000000000000000000351111514013333200245440ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2023, DataLab Platform Developers # This file is distributed under the same license as the DataLab package. # FIRST AUTHOR , 2025. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: DataLab \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid "Git Workflow" msgstr "Workflow Git" msgid "This document describes the Git workflow used in the Sigima project, based on a ``main`` branch, a ``develop`` branch, and feature-specific branches. It also defines how bug fixes are managed." msgstr "Ce document décrit le workflow Git utilisé dans le projet Sigima, basé sur une branche ``main``, une branche ``develop`` et des branches spécifiques aux fonctionnalités. Il définit également comment les correctifs de bogues sont gérés." msgid "This workflow is a simplified version of the `Gitflow Workflow `_. It has been adapted to suit the needs of the Sigima project at the current stage of development. In the near future, we may consider adopting a more complex workflow, e.g. by adding release branches." msgstr "Ce workflow est une version simplifiée du `Gitflow Workflow `_. Il a été adapté pour répondre aux besoins du projet Sigima à l'étape actuelle de développement. Dans un avenir proche, nous pourrions envisager d'adopter un workflow plus complexe, par exemple en ajoutant des branches de version." msgid "Branching Model" msgstr "Modèle de branches" msgid "Main Branches" msgstr "Branches principales" msgid "``main``: Represents the stable, production-ready version of the project." msgstr "``main`` : Représente la version stable et prête pour la production du projet." msgid "``develop``: Used for ongoing development and integration of new features." msgstr "``develop`` : Utilisé pour le développement continu et l'intégration de nouvelles fonctionnalités." msgid "Feature Branches" msgstr "Branches de fonctionnalités" msgid "``feature/feature_name``: Used for the development of new features." msgstr "``feature/feature_name`` : Utilisé pour le développement de nouvelles fonctionnalités." msgid "Created from ``develop``." msgstr "Créé à partir de ``develop``." msgid "Merged back into ``develop`` once completed." msgstr "Fusionné de nouveau dans ``develop`` une fois terminé." msgid "Deleted after merging." msgstr "Supprimé après la fusion." msgid "Release Branch" msgstr "Branche release" msgid "``release``: Represents the current maintenance line for patch releases." msgstr "``release`` : Représente la ligne de maintenance actuelle pour les versions de correctifs." msgid "Created from ``main`` after a stable release when the first patch is needed." msgstr "Créé à partir de ``main`` après une version stable lorsque le premier correctif est nécessaire." msgid "Accepts ``fix/xxx`` and ``hotfix/xxx`` branch merges." msgstr "Accepte les fusions de branches ``fix/xxx`` et ``hotfix/xxx``." msgid "Merged back into ``main`` for each patch release tag (e.g., 1.0.1, 1.0.2)." msgstr "Fusionné de nouveau dans ``main`` pour chaque tag de version de correctif (par exemple, 1.0.1, 1.0.2)." msgid "Reset or recreated when starting a new minor/major release cycle." msgstr "Réinitialisé ou recréé lors du démarrage d'un nouveau cycle de version mineure/majeure." msgid "The ``release`` branch is not versioned (no ``release/1.0.x``). It always represents \"the current maintenance line.\" When a new minor version is released (e.g., 1.2.0), the old ``release`` branch is deleted and a new one is created from the fresh tag when the first patch for 1.2.1 is needed." msgstr "La branche ``release`` n'est pas versionnée (pas de ``release/1.0.x``). Elle représente toujours « la ligne de maintenance actuelle ». Lorsqu'une nouvelle version mineure est publiée (par exemple, 1.2.0), l'ancienne branche ``release`` est supprimée et une nouvelle est créée à partir du nouveau tag lorsque le premier correctif pour 1.2.1 est nécessaire." msgid "Bug Fix Branches" msgstr "Branches de correction d'anomalies" msgid "``fix/xxx``: Used for general bug fixes that are not urgent." msgstr "``fix/xxx`` : Utilisé pour les corrections générales d'anomalies qui ne sont pas urgentes." msgid "Created from ``develop`` (for next feature release) or ``release`` (for patch release)." msgstr "Créé à partir de ``develop`` (pour la prochaine version de fonctionnalité) ou ``release`` (pour la version de correctif)." msgid "Merged back into the originating branch once completed." msgstr "Fusionné de nouveau dans la branche d'origine une fois terminé." msgid "``hotfix/xxx``: Used for urgent production-critical fixes." msgstr "``hotfix/xxx`` : Utilisé pour les corrections urgentes critiques pour la production." msgid "Created from ``release`` (if exists) or ``main`` (if no ``release`` branch yet)." msgstr "Créé à partir de ``release`` (si elle existe) ou ``main`` (si aucune branche ``release`` n'existe encore)." msgid "Merged back into ``release`` or ``main``." msgstr "Fusionné de nouveau dans ``release`` ou ``main``." msgid "The fix is then cherry-picked into ``develop``." msgstr "La correction est ensuite sélectionnée dans ``develop``." msgid "Hotfixes (high-priority fixes) will be integrated in the next maintenance release (X.Y.Z -> Z+1), while fixes (low-priority fixes) will be integrated in the next feature release (X.Y -> Y+1)." msgstr "Les correctifs urgents (correctifs de haute priorité) seront intégrés dans la prochaine version de maintenance (X.Y.Z -> Z+1), tandis que les correctifs (correctifs de basse priorité) seront intégrés dans la prochaine version de fonctionnalité (X.Y -> Y+1)." msgid "Documentation Branches" msgstr "Branches de documentation" msgid "When working on documentation that is not related to source code (e.g. training materials, user guides), branches should be named using the ``doc/`` prefix." msgstr "Lors de la rédaction de documentation qui n'est pas liée au code source (par exemple, les supports de formation, les guides utilisateur), les branches doivent être nommées en utilisant le préfixe ``doc/``." msgid "Examples:" msgstr "Exemples :" msgid "``doc/training-materials``" msgstr "``doc/training-materials``" msgid "``doc/user-guide``" msgstr "``doc/user-guide``" msgid "This naming convention improves clarity by clearly separating documentation efforts from code-related development (features, fixes, etc.)." msgstr "Cette convention de nommage améliore la clarté en séparant clairement les efforts de documentation du développement lié au code (fonctionnalités, corrections, etc.)." msgid "Workflow for New Features" msgstr "Workflow pour les nouvelles fonctionnalités" msgid "Create a new feature branch from ``develop``:" msgstr "Créer une nouvelle branche de fonctionnalité à partir de ``develop`` :" msgid "Develop the feature and commit changes." msgstr "Développer la fonctionnalité et valider les modifications." msgid "Merge the feature branch back into ``develop``:" msgstr "Fusionner la branche de fonctionnalité de nouveau dans ``develop`` :" msgid "Delete the feature branch:" msgstr "Supprimer la branche de fonctionnalité :" msgid "Do not leave feature branches unmerged for too long. Regularly rebase them on ``develop`` to minimize conflicts." msgstr "Ne pas laisser les branches de fonctionnalités non fusionnées trop longtemps. Les réorganiser régulièrement sur ``develop`` pour minimiser les conflits." msgid "Workflow for Regular Bug Fixes" msgstr "Workflow pour les corrections d'anomalies régulières" msgid "For next feature release (target: ``develop``):" msgstr "Pour la prochaine version de fonctionnalité (cible : ``develop``) :" msgid "Create a bug fix branch from ``develop``:" msgstr "Créer une branche de correction d'anomalie à partir de ``develop`` :" msgid "Apply the fix and commit changes." msgstr "Appliquer la correction et valider les modifications." msgid "Merge the fix branch back into ``develop``:" msgstr "Fusionner la branche de correction de nouveau dans ``develop`` :" msgid "Delete the fix branch:" msgstr "Supprimer la branche de correction :" msgid "For current maintenance release (target: ``release``):" msgstr "Pour la version de maintenance actuelle (cible : ``release``) :" msgid "Create a bug fix branch from ``release``:" msgstr "Créer une branche de correction d'anomalie à partir de ``release`` :" msgid "Merge the fix branch back into ``release``:" msgstr "Fusionner la branche de correction de nouveau dans ``release`` :" msgid "Do not create a ``fix/xxx`` branch from a ``develop/feature_name`` branch. Always branch from ``develop`` or ``release`` to ensure fixes are correctly propagated." msgstr "Ne pas créer une branche ``fix/xxx`` à partir d'une branche ``develop/feature_name``. Toujours créer une branche à partir de ``develop`` ou ``release`` pour garantir que les corrections sont correctement propagées." msgid "Workflow for Critical Hotfixes" msgstr "Workflow pour les correctifs urgents" msgid "Create a hotfix branch from ``release`` (or ``main`` if no ``release`` branch exists):" msgstr "Créer une branche de correctif urgent à partir de ``release`` (ou ``main`` si aucune branche ``release`` n'existe) :" msgid "Merge the fix back into ``release`` (or ``main``):" msgstr "Fusionner la correction de nouveau dans ``release`` (ou ``main``) :" msgid "Cherry-pick the fix into ``develop``:" msgstr "Faire un cherry-pick du correctif dans ``develop`` :" msgid "Delete the hotfix branch:" msgstr "Supprimer la branche de correctif urgent :" msgid "Do not merge ``fix/xxx`` or ``hotfix/xxx`` directly into ``main`` without following the workflow. Ensure hotfixes are cherry-picked into ``develop`` to avoid losing fixes in future releases." msgstr "Ne pas fusionner ``fix/xxx`` ou ``hotfix/xxx`` directement dans ``main`` sans suivre le workflow. Assurez-vous que les correctifs urgents ont fait l'objet de cherry-pick dans ``develop`` pour éviter de perdre des correctifs dans les futures versions." msgid "Workflow for Patch Releases" msgstr "Workflow pour les versions de correctifs" msgid "When ready to release a patch version (e.g., 1.0.1, 1.0.2):" msgstr "Lorsque vous êtes prêt à publier une version de correctif (par exemple, 1.0.1, 1.0.2) :" msgid "Ensure the ``release`` branch contains all desired fixes." msgstr "S'assurer que la branche ``release`` contient toutes les corrections souhaitées." msgid "Merge ``release`` into ``main``:" msgstr "Fusionner ``release`` dans ``main`` :" msgid "Tag the release on ``main``:" msgstr "Taguer la version sur ``main`` :" msgid "Keep the ``release`` branch for additional patches in the same minor version series." msgstr "Conserver la branche ``release`` pour des correctifs supplémentaires dans la même série de versions mineures." msgid "Workflow for Minor/Major Releases" msgstr "Workflow pour les versions mineures/majeures" msgid "When ready to release a new minor or major version (e.g., 1.1.0, 2.0.0):" msgstr "Lorsque vous êtes prêt à publier une nouvelle version mineure ou majeure (par exemple, 1.1.0, 2.0.0) :" msgid "Merge ``develop`` into ``main``:" msgstr "Fusionner ``develop`` dans ``main`` :" msgid "Delete the old ``release`` branch (if exists):" msgstr "Supprimer l'ancienne branche ``release`` (si elle existe) :" msgid "Create a new ``release`` branch from ``main`` when the first patch for 1.1.1 is needed:" msgstr "Créer une nouvelle branche ``release`` à partir de ``main`` lorsque le premier correctif pour 1.1.1 est nécessaire :" msgid "Best Practices" msgstr "Bonnes pratiques" msgid "Regularly **rebase feature branches** on ``develop`` to stay up to date:" msgstr "Réorganiser régulièrement les branches de fonctionnalités sur ``develop`` pour rester à jour :" msgid "Avoid long-lived branches to minimize merge conflicts." msgstr "Éviter les branches de longue durée pour minimiser les conflits de fusion." msgid "Ensure bug fixes in ``release`` or ``main`` are **always cherry-picked** to ``develop``." msgstr "S'assurer que les corrections d'anomalies dans ``release`` ou ``main`` sont **toujours sélectionnées** dans ``develop``." msgid "Clearly differentiate between ``fix/xxx`` (non-urgent fixes) and ``hotfix/xxx`` (critical production fixes)." msgstr "Différencier clairement entre ``fix/xxx`` (correctifs non urgents) et ``hotfix/xxx`` (correctifs critiques pour la production)." msgid "When creating the ``release`` branch, update release notes to indicate which version it targets (e.g., add a comment in the merge commit: \"Create release branch for v1.0.x maintenance\")." msgstr "Lors de la création de la branche ``release``, mettre à jour les notes de version pour indiquer la version qu'elle cible (par exemple, ajouter un commentaire dans le commit de fusion : \"Créer une branche de version pour la maintenance v1.0.x\")." msgid "The ``release`` branch always represents the current maintenance line. To know which version it targets, check the most recent tag on ``main`` or the release notes." msgstr "La branche ``release`` représente toujours la ligne de maintenance actuelle. Pour savoir quelle version elle cible, vérifiez le tag le plus récent sur ``main`` ou les notes de version." msgid "Takeaway" msgstr "Conclusion" msgid "This workflow ensures a structured yet flexible development process while keeping ``main`` stable and ``develop`` always updated with the latest changes." msgstr "Ce workflow garantit un processus de développement structuré mais flexible tout en maintenant ``main`` stable et ``develop`` toujours à jour avec les dernières modifications." msgid "The ``release`` branch provides a dedicated maintenance line for patch releases, allowing ``develop`` to proceed with new features without interference. This solves the problem of coordinating unreleased changes across the PlotPyStack ecosystem (DataLab, Sigima, PlotPy, guidata, PythonQwt) by providing a stable branch for CI testing during maintenance cycles." msgstr "La branche ``release`` fournit une ligne de maintenance dédiée pour les versions de correctifs, permettant à ``develop`` de poursuivre avec de nouvelles fonctionnalités sans interférence. Cela résout le problème de la coordination des modifications non publiées dans l'écosystème PlotPyStack (DataLab, Sigima, PlotPy, guidata, PythonQwt) en fournissant une branche stable pour les tests CI pendant les cycles de maintenance." Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/contributing/guidelines.po000066400000000000000000000134321514013333200243200ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2023, DataLab Platform Developers # This file is distributed under the same license as the DataLab package. # FIRST AUTHOR , 2023. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: DataLab \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language-Team: LANGUAGE \n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid "Coding guidelines" msgstr "Règles de codage" msgid "Generic coding guidelines" msgstr "Règles de codage génériques" msgid "We follow the `PEP 8 `_ coding style." msgstr "Nous suivons le style de codage `PEP 8 `_." msgid "In particular, we are especially strict about the following guidelines:" msgstr "En particulier, nous sommes particulièrement stricts sur les directives suivantes :" msgid "Limit all lines to a maximum of 79 characters." msgstr "Limiter toutes les lignes à un maximum de 79 caractères." msgid "Respect the naming conventions (classes, functions, variables, etc.)." msgstr "Respecter les conventions de nommage (classes, fonctions, variables, etc.)." msgid "Use specific exceptions instead of the generic :class:`Exception`." msgstr "Utiliser des exceptions spécifiques au lieu de :class:`Exception`." msgid "To enforce these guidelines, the following tools are mandatory:" msgstr "Pour faire respecter ces directives, les outils suivants sont obligatoires :" msgid "`ruff `_ for code formatting and static code analysis." msgstr "`ruff `_ pour le formatage du code et l'analyse statique du code." msgid "`pylint `_ for static code analysis." msgstr "`pylint `_ pour l'analyse statique du code." msgid "ruff" msgstr "ruff" msgid "If you are using `Visual Studio Code `_, the project settings will automatically format your code with `ruff` on save (you may also run the task \"Run Ruff\" to run `ruff` on the project)." msgstr "Si vous utilisez `Visual Studio Code `_, les paramètres du projet formateront automatiquement votre code avec `ruff` à l'enregistrement (vous pouvez également exécuter la tâche \"Run Ruff\" pour exécuter `ruff` sur le projet)." msgid "To run `ruff`, run the following command::" msgstr "Pour exécuter `ruff`, exécutez la commande suivante::" msgid "pylint" msgstr "pylint" msgid "To run `pylint`, run the following command::" msgstr "Pour exécuter `pylint`, exécutez la commande suivante::" msgid "If you are using `Visual Studio Code `_ on Windows, you may run the task \"Run Pylint\" to run `pylint` on the project." msgstr "Si vous utilisez `Visual Studio Code `_ sur Windows, vous pouvez exécuter la tâche \"Run Pylint\" pour exécuter `pylint` sur le projet." msgid "A `pylint` rating greater than 9/10 is required to merge a pull request." msgstr "Une note `pylint` supérieure à 9/10 est requise pour fusionner une demande d'extraction." msgid "Specific coding guidelines" msgstr "Règles de codage spécifiques" msgid "In addition to the generic coding guidelines, we have the following specific guidelines:" msgstr "En plus des directives de codage génériques, nous avons les directives spécifiques suivantes :" msgid "Write docstrings for all classes, methods and functions. The docstrings should follow the `Google style `_." msgstr "Écrire des docstrings pour toutes les classes, méthodes et fonctions. Les docstrings doivent suivre le `style Google `_." msgid "Add typing annotations for all functions and methods. The annotations should use the future syntax (``from __future__ import annotations``)" msgstr "Ajouter des annotations de typage pour toutes les fonctions et méthodes. Les annotations doivent utiliser la syntaxe future (``from __future__ import annotations``)" msgid "Try to keep the code as simple as possible. If you have to write a complex piece of code, try to split it into several functions or classes." msgstr "Essayez de garder le code aussi simple que possible. Si vous devez écrire un morceau de code complexe, essayez de le diviser en plusieurs fonctions ou classes." msgid "Add as many comments as possible. The code should be self-explanatory, but it is always useful to add some comments to explain the general idea of the code, or to explain some tricky parts." msgstr "Ajouter autant de commentaires que possible. Le code doit être auto-explicatif, mais il est toujours utile d'ajouter des commentaires pour expliquer l'idée générale du code, ou pour expliquer certaines parties délicates." msgid "Do not use ``from module import *`` statements, even in the ``__init__`` module of a package." msgstr "N'utilisez pas d'instructions ``from module import *``, même dans le module ``__init__`` d'un package." msgid "Avoid using mixins (multiple inheritance) when possible. It is often possible to use composition instead of inheritance." msgstr "Évitez d'utiliser des mixins (héritage multiple) si possible. Il est souvent possible d'utiliser la composition au lieu de l'héritage." msgid "Avoid using ``__getattr__`` and ``__setattr__`` methods. They are often used to implement lazy initialization, but this can be done in a more explicit way." msgstr "Évitez d'utiliser les méthodes ``__getattr__`` et ``__setattr__``. Ils sont souvent utilisés pour implémenter une initialisation paresseuse, mais cela peut être fait de manière plus explicite." Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/contributing/index.po000066400000000000000000000245351514013333200233050ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2023, DataLab Platform Developers # This file is distributed under the same license as the DataLab package. # FIRST AUTHOR , 2023. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: DataLab \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language-Team: LANGUAGE \n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid "Contribute to Sigima project, the open-source scientific data analysis platform" msgstr "Contribuer au projet Sigima, la plateforme open-source d'analyse de données scientifiques" msgid "Sigima, contribute, open-source, scientific, data, analysis, platform, signal processing, image processing" msgstr "Sigima, contribuer, open-source, scientifique, données, analyse, plateforme, traitement du signal, traitement d'images" msgid "Contributing" msgstr "Contribuer" msgid "There are many ways to contribute to Sigima, depending on how much time you have, your experience with open source projects, and your skills." msgstr "Il existe de nombreuses façons de contribuer au projet Sigima, en fonction du temps dont vous disposez, de votre expérience avec les projets open source et de vos compétences." msgid "Share your ideas and experiences" msgstr "Partagez vos idées et vos expériences" msgid ":octicon:`info;1em;sd-text-info` :bdg-success-line:`No coding required`" msgstr ":octicon:`info;1em;sd-text-info` :bdg-success-line:`Aucun codage requis`" msgid "Besides the classic bug reports and feature requests, you can share your ideas and experiences for improving Sigima. In particular, we are very interested in your feedback on the documentation and tutorials. Moreover, if you have a use case that you would like to share with the community, please let us know." msgstr "Outre les rapports d'anomalies classiques et les demandes de fonctionnalités, vous pouvez partager vos idées et vos expériences pour améliorer Sigima. En particulier, nous sommes très intéressés par vos commentaires sur la documentation et les tutoriels. De plus, si vous avez un cas d'utilisation que vous souhaitez partager avec la communauté, faites-le nous savoir." msgid " Bugs" msgstr "Anomalies" msgid "Reporting a bug" msgstr "Signaler une anomalie" msgid " Enhancements" msgstr "Améliorations" msgid "Suggesting an enhancement" msgstr "Suggérer une amélioration" msgid " Documentation" msgstr "Documentation" msgid "Suggesting a documentation topic" msgstr "Suggérer un sujet de documentation" msgid " Tutorial" msgstr "Tutoriel" msgid "Suggesting a tutorial topic" msgstr "Suggérer un sujet de tutoriel" msgid "Without coding, you can contribute to Sigima project by:" msgstr "Sans coder une seule ligne, vous pouvez contribuer au projet Sigima en :" msgid "`Reporting a bug `_" msgstr "`Signaler une anomalie `_" msgid "`Suggesting an enhancement `_" msgstr "`Suggérer une amélioration `_" msgid "`Suggesting a documentation topic `_" msgstr "`Suggérer un sujet de documentation `_" msgid "`Suggesting a tutorial topic `_" msgstr "`Suggérer un sujet de tutoriel `_" msgid "Share your scientific/technical knowledge" msgstr "Partagez vos connaissances scientifiques/techniques" msgid "Your technical or scientific knowledge is also very valuable to us, as you may directly contribute to the documentation or tutorials. Or, better, if you want to write a tutorial, we will be happy to help you." msgstr "Vos connaissances techniques ou scientifiques sont également très précieuses pour nous, car vous pouvez contribuer directement à la documentation ou aux tutoriels. Ou, mieux encore, si vous souhaitez rédiger un tutoriel, nous serons heureux de vous aider." msgid "Again without coding, you can contribute to Sigima project by:" msgstr "Encore une fois sans coder, vous pouvez contribuer au projet Sigima en :" msgid "Writing documentation" msgstr "Ecrire de la documentation" msgid "Writing a tutorial" msgstr "Ecrire un tutoriel" msgid "Contribute to new features" msgstr "Contribuer aux nouvelles fonctionnalités" msgid ":octicon:`info;1em;sd-text-info` :bdg-info-line:`Coding (beginner)` :bdg-warning-line:`Coding (advanced)`" msgstr ":octicon:`info;1em;sd-text-info` :bdg-info-line:`Codage (débutant)` :bdg-warning-line:`Codage (avancé)`" msgid "Even if you are not a developer, you can contribute to the project by:" msgstr "Même si vous n'êtes pas développeur, vous pouvez contribuer au projet en :" msgid "Testing new features" msgstr "Testant de nouvelles fonctionnalités" msgid "Writing and submitting new Plugins" msgstr "Ecrivant et soumettant de nouveaux plugins" msgid "Writing and submitting macro-commands" msgstr "Ecivant et soumettant des macro-commandes" msgid "Develop new features" msgstr "Développer de nouvelles fonctionnalités" msgid ":octicon:`info;1em;sd-text-info` :bdg-warning-line:`Coding (advanced)`" msgstr ":octicon:`info;1em;sd-text-info` :bdg-warning-line:`Codage (avancé)`" msgid "If you are a developer, you can contribute to the core of the project by fixing bugs or implementing new features." msgstr "Si vous êtes développeur, vous pouvez contribuer au cœur du projet en corrigeant des anomalies ou en implémentant de nouvelles fonctionnalités." msgid " Code" msgstr "Code" msgid "Contributing to the code" msgstr "Contribuer au code" msgid "See :ref:`contribute_code` section for more information." msgstr "Voir la section :ref:`contribute_code` pour plus d'informations." Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/index.po000066400000000000000000000235551514013333200205770ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2025, DataLab Platform Developers # This file is distributed under the same license as the Sigima package. # FIRST AUTHOR , 2025. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: Sigima \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid "Contents" msgstr "Table des matières" msgid "Sigima" msgstr "Sigima" msgid "**Sigima** is an advanced Python library for *scientific image and signal processing*. It provides a wide range of functionalities for analyzing and processing data, including signal filtering, image enhancement, and feature extraction. Sigima is based on a simple but effective object-oriented design, making it easy to use and extend." msgstr "**Sigima** est une bibliothèque Python avancée pour le *traitement scientifique des images et des signaux*. Elle offre une large gamme de fonctionnalités pour l'analyse et le traitement des données, y compris le filtrage des signaux, l'amélioration des images et l'extraction de caractéristiques. Sigima est basée sur une conception orientée objet simple mais efficace, ce qui la rend facile à utiliser et à étendre." msgid "With Sigima, do in 3 lines of code what would normally take dozens of lines:" msgstr "Avec Sigima, faites en 3 lignes de code ce qui prendrait normalement des dizaines de lignes :" msgid "Developed and maintained by the DataLab Platform Developers, **Sigima** powers the computation backend of `DataLab `_." msgstr "Développée et maintenue par les développeurs de la plateforme DataLab, **Sigima** alimente le backend de calcul de `DataLab `_." msgid " User Guide" msgstr "Manuel utilisateur" msgid "Installation, overview, and features" msgstr "Installation et fonctionnalités" msgid " Examples" msgstr "Exemples" msgid "Gallery of examples" msgstr "Galerie d'exemples" msgid " API" msgstr "API" msgid "Reference documentation" msgstr "Documentation de référence" msgid " Contributing" msgstr "Contribuer" msgid "Getting involved in the project" msgstr "S'impliquer dans le projet" msgid "Try it Online" msgstr "Essayer en ligne" msgid "**Experience Sigima instantly in your browser** — no installation required!" msgstr "**Découvrez Sigima instantanément dans votre navigateur** — aucune installation requise !" msgid "Try it online" msgstr "Essayez en ligne" msgid "Click the badge above to open a basic example notebook in a live JupyterLite environment powered by `notebook.link `_. This service, developed by `QuantStack `_, enables sharing and running Jupyter notebooks directly in the browser with zero setup." msgstr "Cliquez sur le badge ci-dessus pour ouvrir un notebook d'exemple basique dans un environnement JupyterLite interactif propulsé par `notebook.link `_. Ce service, développé par `QuantStack `_, permet de partager et d'exécuter des notebooks Jupyter directement dans le navigateur sans aucune configuration." msgid "Simply run the cells to explore:" msgstr "Exécutez simplement les cellules pour explorer :" msgid "Creating signal and image objects" msgstr "Création d'objets signal et image" msgid "Applying processing functions" msgstr "Application de fonctions de traitement" msgid "Visualizing results inline" msgstr "Visualisation des résultats en ligne" msgid "Sigima has been funded by the following stakeholders:" msgstr "Sigima a été financée par les parties prenantes suivantes:" msgid "|nlnet_logo|" msgstr "|nlnet_logo|" msgid "nlnet_logo" msgstr "nlnet_logo" msgid "`NLnet Foundation `_, as part of the NGI0 Commons Fund, backed by the European Commission, has funded the `redesign of DataLab's core architecture `_." msgstr "`NLnet Foundation `_, dans le cadre du NGI0 Commons Fund, soutenu par la Commission européenne, a financé la `refonte de l'architecture de base de DataLab `_." msgid "|cea_logo|" msgstr "|cea_logo|" msgid "cea_logo" msgstr "cea_logo" msgid "`CEA `_, the French Alternative Energies and Atomic Energy Commission, is the major investor in DataLab, and is the main contributor to the project." msgstr "`CEA `_, le Commissariat à l'énergie atomique et aux énergies alternatives, est le principal investisseur de DataLab et le principal contributeur au projet." msgid "|codra_logo|" msgstr "|codra_logo|" msgid "codra_logo" msgstr "codra_logo" msgid "`CODRA`_, a software engineering and editor firm, has supported DataLab open-source journey since its inception (see `here `_)." msgstr "`CODRA`_, une entreprise d'ingénierie logicielle et d'édition, a soutenu le parcours open-source de DataLab depuis ses débuts (voir `ici `_)." Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/release_notes/000077500000000000000000000000001514013333200217465ustar00rootroot00000000000000Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/release_notes/index.po000066400000000000000000000017101514013333200234140ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2025, DataLab Platform Developers # This file is distributed under the same license as the Sigima package. # FIRST AUTHOR , 2025. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: Sigima \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid "Release notes" msgstr "Notes de version" msgid "This section contains the release notes for all versions of :mod:`sigima`, documenting new features, improvements, bug fixes, and breaking changes." msgstr "Cette section contient les notes de version pour toutes les versions de :mod:`sigima`, documentant les nouvelles fonctionnalités, les améliorations, les corrections de bugs et les changements majeurs." Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/release_notes/release_0.01.po000066400000000000000000000017701514013333200243710ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2025, DataLab Platform Developers # This file is distributed under the same license as the Sigima package. # FIRST AUTHOR , 2025. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: Sigima \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid "Version 0.1" msgstr "" msgid "Sigima Version 0.1.0 (2025-07-06)" msgstr "Sigima Version 0.1.0 (06/07/2025)" msgid "This first version of the library is the result of the externalization of the signal and image processing features from the DataLab main repository." msgstr "Cette première version de la bibliothèque est le résultat de l'externalisation des fonctionnalités de traitement des signaux et des images du référentiel principal de DataLab." Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/release_notes/release_0.02.po000066400000000000000000000027371514013333200243760ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2025, DataLab Platform Developers # This file is distributed under the same license as the Sigima package. # FIRST AUTHOR , 2025. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: Sigima \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid "Version 0.2" msgstr "" msgid "Sigima Version 0.2.0 (2025-07-07)" msgstr "Sigima Version 0.2.0 (07/07/2025)" msgid "⚠️ Major API changes:" msgstr "⚠️ Changements majeurs de l'API:" msgid "Rename `sigima.computation` to `sigima.proc`." msgstr "Renommage de `sigima.computation` en `sigima.proc`." msgid "Rename `sigima.algorithms` to `sigima.tools`." msgstr "Renommage de `sigima.algorithms` en `sigima.tools`." msgid "Rename `sigima.obj` to `sigima.objects`." msgstr "Renommage de `sigima.obj` en `sigima.objects`." msgid "Rename `sigima.param` to `sigima.params`." msgstr "Renommage de `sigima.param` en `sigima.params`." msgid "ℹ️ Various changes:" msgstr "ℹ️ Divers changements:" msgid "Add Sigima SVG logo." msgstr "Ajout du logo SVG de Sigima." msgid "🛠️ Bug fixes:" msgstr "🛠️ Correctifs:" msgid "Fix API documentation and docstrings." msgstr "Correction de la documentation de l'API et des docstrings." Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/release_notes/release_1.00.po000066400000000000000000003233011514013333200243660ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2025, DataLab Platform Developers # This file is distributed under the same license as the Sigima package. # FIRST AUTHOR , 2025. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: Sigima \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid "Version 1.0" msgstr "" msgid "Sigima Version 1.0.6" msgstr "" msgid "🛠️ Bug fixes:" msgstr "🛠️ Correctifs :" msgid "**Compatibility with scikit-image 0.26.0+**: Fixed deprecation warnings and API compatibility issues" msgstr "**Compatibilité avec scikit-image 0.26.0+** : Correction des avertissements de dépréciation et des problèmes de compatibilité API" msgid "scikit-image 0.26.0 introduced breaking changes to `CircleModel` and `EllipseModel` APIs: old API used `model.estimate(contour)` + `model.params`, new API uses `model.from_estimate(contour)` + property-based access (`model.center`, `model.radius`, `model.axis_lengths`)" msgstr "scikit-image 0.26.0 a introduit des changements majeurs dans les API de `CircleModel` et `EllipseModel` : l'ancienne API utilisait `model.estimate(contour)` + `model.params`, la nouvelle API utilise `model.from_estimate(contour)` + un accès basé sur les propriétés (`model.center`, `model.radius`, `model.axis_lengths`)" msgid "Added version-aware compatibility layer in `sigima.tools.image.preprocessing` with new helper functions `fit_circle_model()` and `fit_ellipse_model()` that handle both old and new APIs" msgstr "Ajout d'une couche de compatibilité sensible à la version dans `sigima.tools.image.preprocessing` avec de nouvelles fonctions d'aide `fit_circle_model()` et `fit_ellipse_model()` qui gèrent les anciennes et nouvelles API" msgid "Updated `get_contour_shapes()` in `sigima.tools.image.detection` to use compatibility functions" msgstr "Mise à jour de `get_contour_shapes()` dans `sigima.tools.image.detection` pour utiliser les fonctions de compatibilité" msgid "Updated `get_enclosing_circle()` in `sigima.tools.image.geometry` to use compatibility functions" msgstr "Mise à jour de `get_enclosing_circle()` dans `sigima.tools.image.geometry` pour utiliser les fonctions de compatibilité" msgid "Used `packaging.version.Version` for robust version checking instead of fragile string parsing" msgstr "Utilisation de `packaging.version.Version` pour une vérification robuste des versions au lieu d'une analyse de chaîne fragile" msgid "Eliminates deprecation warnings while maintaining backward compatibility with Python 3.9 and scikit-image < 0.26" msgstr "Élimine les avertissements de dépréciation tout en maintenant la compatibilité ascendante avec Python 3.9 et scikit-image < 0.26" msgid "This closes [Issue #10](https://github.com/DataLab-Platform/Sigima/issues/10) - Sigima is not compatible with NumPy 2.4.0 and scikit-image 0.26.0" msgstr "Ceci clôture [Issue #10](https://github.com/DataLab-Platform/Sigima/issues/10) - Sigima n'est pas compatible avec NumPy 2.4.0 et scikit-image 0.26.0" msgid "**Compatibility with NumPy 2.4.0**: Fixed centroid computation failure with NumPy 2.4.0's new einsum optimization" msgstr "**Compatibilité avec NumPy 2.4.0** : Correction de l'échec du calcul du centroïde avec la nouvelle optimisation einsum de NumPy 2.4.0" msgid "NumPy 2.4.0 introduced new einsum optimization used by `scikit-image.measure.centroid()` that fails with certain ndarray types" msgstr "NumPy 2.4.0 a introduit une nouvelle optimisation einsum utilisée par `scikit-image.measure.centroid()` qui échoue avec certains types de ndarray" msgid "Fixed by explicitly converting image data to basic NumPy array before calling `measure.centroid()` in `get_centroid_auto()` function" msgstr "Correction en convertissant explicitement les données d'image en tableau NumPy de base avant d'appeler `measure.centroid()` dans la fonction `get_centroid_auto()`" msgid "Ensures compatibility with NumPy 2.4.0+ and scikit-image 0.26.0+ without changing computational results" msgstr "Assure la compatibilité avec NumPy 2.4.0+ et scikit-image 0.26.0+ sans modifier les résultats de calcul" msgid "📦 Dependencies:" msgstr "📦 Dépendances :" msgid "**Dependency version constraints**: Added maximum version constraints to prevent future compatibility issues" msgstr "**Contraintes de version des dépendances** : Ajout de contraintes de version maximale pour éviter les futurs problèmes de compatibilité" msgid "Updated dependency specifications: `NumPy >= 1.22, < 2.5`, `SciPy >= 1.10.1, < 1.17`, `scikit-image >= 0.19.2, < 0.27`, `pandas >= 1.4, < 3.0`, `PyWavelets >= 1.2, < 2.0`" msgstr "Mise à jour des spécifications des dépendances : `NumPy >= 1.22, < 2.5`, `SciPy >= 1.10.1, < 1.17`, `scikit-image >= 0.19.2, < 0.27`, `pandas >= 1.4, < 3.0`, `PyWavelets >= 1.2, < 2.0`" msgid "New CI job `build_latest` runs scheduled tests against latest dependency versions to detect breaking changes early" msgstr "Le nouveau job CI `build_latest` exécute des tests programmés contre les dernières versions des dépendances pour détecter rapidement les changements majeurs" msgid "Prevents automatic breakage from major dependency updates while allowing controlled upgrades after validation" msgstr "Permets d'éviter les régressions dues aux mises à jour majeures des dépendances tout en permettant des mises à niveau contrôlées après validation" msgid "🚀 CI/CD improvements:" msgstr "🚀 Améliorations CI/CD :" msgid "**CI workflow enhancements**: Added automated testing against latest dependency versions" msgstr "**Améliorations du workflow CI** : Ajout de tests automatisés contre les dernières versions des dépendances" msgid "New `build_latest` job in GitHub Actions runs on schedule (weekly) and manual dispatch" msgstr "Nouveau job `build_latest` dans GitHub Actions s'exécute selon un calendrier (hebdomadaire) et sur demande manuelle" msgid "Extracts dependency names from `pyproject.toml` and installs latest available versions" msgstr "Extrait les noms des dépendances de `pyproject.toml` et installe les dernières versions disponibles" msgid "Provides early warning system for upcoming dependency compatibility issues" msgstr "Fournit un système d'alerte précoce pour les futurs problèmes de compatibilité des dépendances" msgid "Enhanced workflow dispatch with configurable job selection for flexible testing scenarios" msgstr "Amélioration du workflow de déclenchement avec une sélection de jobs configurable pour des scénarios de test flexibles" msgid "Sigima Version 1.0.5 (2025-12-19)" msgstr "" msgid "ℹ️ This is a hotfix release addressing a packaging issue where French translations were missing from the previous release package. This release contains no functional changes compared to version 1.0.4 - it only ensures that the compiled translation files (.mo) are properly included in the distribution package." msgstr "ℹ️ Ceci est une version corrective qui résout un problème d'emballage où les traductions françaises manquaient dans le package de la version précédente. Cette version ne contient aucun changement fonctionnel par rapport à la version 1.0.4 - elle garantit uniquement que les fichiers de traduction compilés (.mo) sont correctement inclus dans le package de distribution." msgid "**Packaging**: Fixed missing French translation files in release package" msgstr "**Packaging** : Correction des fichiers de traduction française manquants dans le package de la version précédente" msgid "Previous release packages were missing compiled .mo translation files, causing the application to display only English text regardless of locale settings" msgstr "Les packages de la version précédente ne contenaient pas les fichiers de traduction compilés .mo, ce qui faisait que l'application affichait uniquement du texte en anglais quel que soit les paramètres régionaux" msgid "Updated build process to ensure all translation files are properly included in distribution packages" msgstr "Mise à jour du processus de construction pour garantir que tous les fichiers de traduction sont correctement inclus dans les packages de distribution" msgid "No functional code changes - this is purely a packaging fix to restore internationalization support" msgstr "Aucun changement de code fonctionnel - il s'agit purement d'une correction d'emballage pour restaurer la prise en charge de l'internationalisation" msgid "Sigima Version 1.0.4 (2025-12-18)" msgstr "" msgid "**Image processing: LUT range incorrectly copied to result**: Fixed processed images showing incorrect contrast because LUT range was copied from original" msgstr "**Traitement d'image : plage LUT copiée incorrectement dans le résultat** : Correction des images traitées affichant un contraste incorrect car la plage LUT a été copiée de l'original" msgid "When processing an image (e.g., subtracting offset), the result image inherited the original's LUT range (`zscalemin`/`zscalemax`), causing incorrect visualization when data values changed significantly" msgstr "Lors du traitement d'une image (par exemple, en soustrayant un offset), l'image résultante héritait de la plage LUT de l'original (`zscalemin`/`zscalemax`), ce qui entraînait une visualisation incorrecte lorsque les valeurs de données changeaient de manière significative" msgid "Example: After subtracting ~50 lsb background from an image with LUT 50-200, the result (data range ~-5 to ~175) was still displayed with the original 50-200 LUT, making parts of the image appear clipped or invisible" msgstr "Exemple : Après avoir soustrait un fond d'environ 50 lsb d'une image avec une LUT de 50-200, le résultat (plage de données d'environ -5 à environ 175) était toujours affiché avec la LUT originale de 50-200, rendant certaines parties de l'image coupées ou invisibles" msgid "Fixed by adding image-specific `dst_1_to_1`, `dst_2_to_1`, and `dst_n_to_1` wrapper functions in `sigima.proc.image.base` that reset the LUT range after copying the source image" msgstr "Corrigé en ajoutant des fonctions wrapper spécifiques à l'image `dst_1_to_1`, `dst_2_to_1` et `dst_n_to_1` dans `sigima.proc.image.base` qui réinitialisent la plage LUT après la copie de l'image source" msgid "The `ImageObj.copy()` method remains unchanged (a copy should faithfully copy all attributes) - the fix is applied at the processing layer where it belongs" msgstr "La méthode `ImageObj.copy()` reste inchangée (une copie doit copier fidèlement tous les attributs) - la correction est appliquée à la couche de traitement où elle appartient" msgid "Added regression test `test_image_offset_correction_lut_range` in `offset_correction_unit_test.py`" msgstr "Ajout d'un test de régression `test_image_offset_correction_lut_range` dans `offset_correction_unit_test.py`" msgid "This closes [Issue #9](https://github.com/DataLab-Platform/Sigima/issues/9) - LUT range incorrectly copied when processing images" msgstr "Ceci clôture [Issue #9](https://github.com/DataLab-Platform/Sigima/issues/9) - Plage LUT copiée incorrectement lors du traitement des images" msgid "**Backwards-defined rectangular ROI causes NaN statistics**: Fixed rectangular ROI coordinate normalization when defined in reverse direction" msgstr "**Une ROI rectangulaire définie à l'envers entraîne des statistiques NaN** : Correction de la normalisation des coordonnées de ROI rectangulaire lorsqu'elle est définie en sens inverse" msgid "When a rectangular ROI was drawn graphically \"backwards\" in DataLab (from bottom-right to top-left instead of top-left to bottom-right), statistics analysis returned NaN values" msgstr "Lorsqu'une ROI rectangulaire était dessinée graphiquement « à l'envers » dans DataLab (du coin inférieur droit vers le coin supérieur gauche au lieu du coin supérieur gauche vers le coin inférieur droit), l'analyse statistique retournait des valeurs NaN" msgid "The `RectangularROI.rect_to_coords()` method was producing negative Δx and Δy values when `x1 < x0` or `y1 < y0`" msgstr "La méthode `RectangularROI.rect_to_coords()` produisait des valeurs Δx et Δy négatives lorsque `x1 < x0` ou `y1 < y0`" msgid "Fixed by normalizing coordinates using min/max to ensure Δx and Δy are always positive" msgstr "Corrigé en normalisant les coordonnées avec min/max pour garantir que Δx et Δy sont toujours positifs" msgid "ROI mask generation now works correctly regardless of the direction in which the rectangle was drawn" msgstr "La génération du masque de ROI fonctionne désormais correctement quelle que soit la direction dans laquelle le rectangle a été dessiné" msgid "Added regression test `test_backwards_drawn_rectangle` in `roi_coords_unit_test.py`" msgstr "Ajout d'un test de régression `test_backwards_drawn_rectangle` dans `roi_coords_unit_test.py`" msgid "**Grid ROI - Missing spacing parameters for non-uniform grids**: Fixed grid ROI extraction to support non-uniform feature spacing" msgstr "**ROI de grille - Paramètres d'espacement manquants pour les grilles non uniformes :** Correction de l'extraction ROI de grille pour prendre en charge un espacement des caractéristiques non uniforme" msgid "Grid ROI extraction previously assumed evenly distributed features (spacing = width/nx), which failed for images where features don't fill the entire grid area" msgstr "L'extraction ROI de grille supposait auparavant des caractéristiques uniformément réparties (espacement = largeur/nx), ce qui échouait pour les images où les caractéristiques ne remplissent pas toute la zone de la grille" msgid "Example: `laser_spot_array_raw.png` has laser spots spaced ~300 pixels apart, but the grid was defined over 3100×3100 pixels, causing incorrect ROI placement" msgstr "Exemple : `laser_spot_array_raw.png` a des points laser espacés d'environ 300 pixels, mais la grille était définie sur 3100×3100 pixels, ce qui a causé un placement incorrect des ROI" msgid "Added `xstep` and `ystep` percentage parameters (1-200%, default 100%) to `ROIGridParam` to specify spacing between ROI centers" msgstr "Ajout des paramètres de pourcentage `xstep` et `ystep` (1-200 %, par défaut 100 %) à `ROIGridParam` pour spécifier l'espacement entre les centres des ROI" msgid "Updated `generate_image_grid_roi()` function to use separate step calculation: `dx_step = dx_cell * p.xstep / 100.0`" msgstr "Mise à jour de la fonction `generate_image_grid_roi()` pour utiliser un calcul d'étape séparé : `dx_step = dx_cell * p.xstep / 100.0`" msgid "Position calculation now uses: `x0 = src.x0 + (ic + 0.5) * dx_step + xtrans - 0.5 * dx` (preserving backward compatibility)" msgstr "Le calcul de la position utilise désormais : `x0 = src.x0 + (ic + 0.5) * dx_step + xtrans - 0.5 * dx` (préservant la compatibilité ascendante)" msgid "Default values (100%) maintain exact original behavior for existing workflows" msgstr "Les valeurs par défaut (100 %) maintiennent le comportement original exact pour les flux de travail existants" msgid "This allows precise ROI placement for gapped grids (e.g., laser spot arrays, sample arrays) by adjusting spacing independently of ROI size" msgstr "Cela permet un placement précis des ROI pour les grilles avec des espaces (par exemple, les tableaux de points laser, les tableaux d'échantillons) en ajustant l'espacement indépendamment de la taille des ROI" msgid "**Signal result title formatting**: Fixed duplicate suffix in result titles for image-to-signal functions" msgstr "**Formatage du titre du résultat du signal** : Correction du suffixe en double dans les titres des résultats pour les fonctions image-vers-signal" msgid "When computing radial profile or other operations using `new_signal_result`, the suffix (e.g., center coordinates) was appearing twice in the title" msgstr "Lors du calcul du profil radial ou d'autres opérations utilisant `new_signal_result`, le suffixe (par exemple, les coordonnées du centre) apparaissait deux fois dans le titre" msgid "Example: `radial_profile(i019)|center=(192.500, 192.500)|center=(192.500, 192.500)` instead of `radial_profile(i019)|center=(192.500, 192.500)`" msgstr "Exemple : `radial_profile(i019)|center=(192.500, 192.500)|center=(192.500, 192.500)` au lieu de `radial_profile(i019)|center=(192.500, 192.500)`" msgid "The `new_signal_result` function in `sigima/proc/base.py` was adding the suffix twice: once via the formatter and once explicitly" msgstr "La fonction `new_signal_result` dans `sigima/proc/base.py` ajoutait le suffixe deux fois : une fois via le formateur et une fois explicitement" msgid "Removed the redundant suffix addition - the formatter's `format_1_to_1_title` method already handles suffix formatting correctly" msgstr "Suppression de l'ajout redondant du suffixe - la méthode `format_1_to_1_title` du formateur gère déjà correctement le formatage du suffixe" msgid "Affects functions like `radial_profile`, `histogram`, and other image-to-signal conversions" msgstr "Affecte des fonctions telles que `radial_profile`, `histogram` et d'autres conversions image-vers-signal" msgid "This closes [Issue #8](https://github.com/DataLab-Platform/Sigima/issues/8) - Duplicate suffix in result title when using `new_signal_result`" msgstr "Ceci clôture [Issue #8](https://github.com/DataLab-Platform/Sigima/issues/8) - Suffixe dupliqué dans le titre du résultat lors de l'utilisation de `new_signal_result`" msgid "**HDF5 serialization with detection ROIs**: Fixed workspace save failure when images contain ROIs generated by blob detection" msgstr "**Sérialisation HDF5 avec ROI de détection** : Correction de l'échec de sauvegarde de l'espace de travail lorsque les images contiennent des ROI générées par la détection de blobs" msgid "Saving DataLab workspace to HDF5 format failed with `NotImplementedError: cannot serialize 'rectangle' of type `" msgstr "La sauvegarde de l'espace de travail DataLab au format HDF5 échouait avec `NotImplementedError: cannot serialize 'rectangle' of type `" msgid "The `store_roi_creation_metadata()` function was storing the `DetectionROIGeometry` enum directly in geometry attributes" msgstr "La fonction `store_roi_creation_metadata()` stockait l'énumération `DetectionROIGeometry` directement dans les attributs de géométrie" msgid "Fixed by storing the enum's string value instead of the enum object itself" msgstr "Corrigé en stockant la valeur chaîne de caractères de l'énumération au lieu de l'objet énumération lui-même" msgid "This allows proper HDF5 serialization while preserving the information needed for `apply_detection_rois()` to recreate ROIs" msgstr "Cela permet une sérialisation HDF5 correcte tout en préservant les informations nécessaires pour que `apply_detection_rois()` recrée les ROI" msgid "This closes [Issue #7](https://github.com/DataLab-Platform/Sigima/issues/7) - HDF5 Serialization Fails for Detection ROI Geometry Enum" msgstr "Ceci clôture [Issue #7](https://github.com/DataLab-Platform/Sigima/issues/7) - La sérialisation HDF5 échoue pour l'énumération de la géométrie ROI de détection" msgid "**CSV numeric data import**: Fixed numeric columns being incorrectly interpreted as datetime values ([Issue #6](https://github.com/DataLab-Platform/Sigima/issues/6))" msgstr "**Importation de données numériques CSV** : Correction des colonnes numériques interprétées incorrectement comme des valeurs datetime ([Issue #6](https://github.com/DataLab-Platform/Sigima/issues/6))" msgid "When importing CSV files with large numeric values (e.g., frequencies in Hz like `4.884e+06`), the data was incorrectly converted to datetime timestamps" msgstr "Lors de l'importation de fichiers CSV avec de grandes valeurs numériques (par exemple, des fréquences en Hz comme `4.884e+06`), les données étaient incorrectement converties en horodatages datetime" msgid "The `pd.to_datetime()` function was interpreting numeric values as nanoseconds since Unix epoch, corrupting the original data" msgstr "La fonction `pd.to_datetime()` interprétait les valeurs numériques comme des nanosecondes depuis l'époque Unix, corrompant les données originales" msgid "Added check to skip columns with numeric dtypes in datetime detection - real datetime columns are loaded as string (`object`) dtype" msgstr "Ajout d'une vérification pour ignorer les colonnes avec des types numériques dans la détection de datetime - les vraies colonnes datetime sont chargées comme type chaîne de caractères (`object`)" msgid "Numeric data (frequencies, voltages, etc.) is now correctly preserved during CSV import" msgstr "Les données numériques (fréquences, tensions, etc.) sont désormais correctement préservées lors de l'importation CSV" msgid "📚 Documentation:" msgstr "📚 Documentation :" msgid "**Parameter usage documentation**: Improved documentation for parameters requiring signal/image context ([Issue #5](https://github.com/DataLab-Platform/Sigima/issues/5))" msgstr "**Documentation de l'utilisation des paramètres** : Amélioration de la documentation pour les paramètres nécessitant un contexte de signal/image ([Issue #5](https://github.com/DataLab-Platform/Sigima/issues/5))" msgid "Added comprehensive documentation explaining the `update_from_obj()` pattern for parameters like `ZeroPadding1DParam`" msgstr "Ajout d'une documentation complète expliquant le modèle `update_from_obj()` pour les paramètres tels que `ZeroPadding1DParam`" msgid "Clarified that `sigima.params` is the recommended import location for all parameter classes" msgstr "Clarification que `sigima.params` est l'emplacement d'importation recommandé pour toutes les classes de paramètres" msgid "Enhanced `ZeroPadding1DParam` class docstring with usage example and \"Important\" admonition" msgstr "Amélioration de la docstring de la classe `ZeroPadding1DParam` avec un exemple d'utilisation et une admonition \"Important\"" msgid "Added new section in `sigima.params` module listing all parameters requiring `update_from_obj()`" msgstr "Ajout d'une nouvelle section dans le module `sigima.params` répertoriant tous les paramètres nécessitant `update_from_obj()`" msgid "Created new example `doc/examples/features/zero_padding.py` demonstrating proper parameter initialization" msgstr "Création d'un nouvel exemple `doc/examples/features/zero_padding.py` démontrant l'initialisation correcte des paramètres" msgid "**New ROI grid example**: Added example demonstrating the grid ROI feature" msgstr "" msgid "Introduced `laser_spot_array.png` test image (6×6 laser spot array) to help debug an issue reported in DataLab" msgstr "" msgid "Created new example `doc/examples/features/roi_grid.py` showcasing the `generate_image_grid_roi()` function" msgstr "Création d'un nouvel exemple `doc/examples/features/roi_grid.py` démontrant la fonction `generate_image_grid_roi()`" msgid "Example covers: loading images, extracting sub-regions, generating ROI grids, configuring size/translation/step parameters, understanding direction labels, and extracting individual spots" msgstr "" msgid "Sigima Version 1.0.3 (2025-12-03)" msgstr "" msgid "**Signal data type validation**: Fixed integer arrays not being automatically converted to float64" msgstr "**Validation du type de données du signal** : Correction des tableaux entiers qui n'étaient pas automatiquement convertis en float64" msgid "Integer input arrays are now automatically converted to float64 instead of raising errors" msgstr "Les tableaux d'entrée entiers sont désormais automatiquement convertis en float64 au lieu de générer des erreurs" msgid "Validation applied consistently across all signal data setters: `set_xydata()`, `x`, `y`, `dx`, `dy`" msgstr "La validation est appliquée de manière cohérente à tous les accesseurs de données de signal : `set_xydata()`, `x`, `y`, `dx`, `dy`" msgid "Improves usability by accepting integer inputs (common in test data and calibration values) while maintaining computational precision" msgstr "Améliore l'utilisabilité en acceptant les entrées entières (courantes dans les données de test et les valeurs d'étalonnage) tout en maintenant la précision de calcul" msgid "Raises clear `ValueError` for truly invalid dtypes with helpful error message listing valid types" msgstr "Lève une exception `ValueError` claire pour les types de données vraiment invalides avec un message d'erreur utile répertoriant les types valides" msgid "**Signal axis calibration**: Added `replace_x_by_other_y()` function to replace signal X coordinates with Y values from another signal" msgstr "**Étalonnage de l'axe des signaux** : Ajout de la fonction `replace_x_by_other_y()` pour remplacer les coordonnées X d'un signal par les valeurs Y d'un autre signal" msgid "Addresses missing functionality for wavelength calibration and similar use cases where calibration data is stored in a separate signal's Y values" msgstr "Répond à un manque de fonctionnalité pour l'étalonnage en longueur d'onde et des cas d'utilisation similaires où les données d'étalonnage sont stockées dans les valeurs Y d'un signal séparé" msgid "This operation was previously impossible, even if the ambiguous X-Y mode feature existed and seemed related to this use case (but this feature performs resampling/interpolation, which is not desired here)" msgstr "Cette opération était auparavant impossible, même si la fonctionnalité ambiguë du mode X-Y existait et semblait liée à ce cas d'utilisation (mais cette fonctionnalité effectue un rééchantillonnage/interpolation, ce qui n'est pas souhaité ici)" msgid "The new function directly uses Y arrays from both signals without interpolation, requiring signals to have the same number of points" msgstr "La nouvelle fonction utilise directement les tableaux Y des deux signaux sans interpolation, nécessitant que les signaux aient le même nombre de points" msgid "Takes two signals: first provides Y data for output, second provides Y data to become X coordinates" msgstr "A partir de deux signaux en entrée : le premier fournit les données Y pour la sortie, le second fournit les données Y qui deviendront les coordonnées X" msgid "Automatically transfers metadata: X label/unit from second signal's Y label/unit, Y label/unit preserved from first signal" msgstr "Transfert automatique des métadonnées : étiquette/unité X à partir de l'étiquette/unité Y du second signal, étiquette/unité Y préservée du premier signal" msgid "Typical use case: spectroscopy wavelength calibration (combine absorption measurements with wavelength scale)" msgstr "Cas d'utilisation typique : étalonnage en longueur d'onde en spectroscopie (combiner les mesures d'absorption avec l'échelle de longueur d'onde)" msgid "This closes [Issue #4](https://github.com/DataLab-Platform/Sigima/issues/4) - Missing functionality: Replace X coordinates with Y values from another signal for calibration" msgstr "Ceci clôture [Issue #4](https://github.com/DataLab-Platform/Sigima/issues/4) - Fonctionnalité manquante : Remplacer les coordonnées X par les valeurs Y d'un autre signal pour l'étalonnage" msgid "Signal title formatting:" msgstr "Formatage des titres de signaux :" msgid "**Polynomial signal titles**: Fixed polynomial signal title generation to display mathematical notation (e.g., `1+2x-3x²+4x³`) instead of verbose parameter listing (e.g., `polynomial(a0=1,a1=2,a2=-3,a3=4,a4=0,a5=0)`)" msgstr "**Titres de signaux polynomiaux** : Correction de la génération des titres de signaux polynomiaux pour afficher une notation mathématique (par exemple, `1+2x-3x²+4x³`) au lieu d'une liste de paramètres verbeuse (par exemple, `polynomial(a0=1,a1=2,a2=-3,a3=4,a4=0,a5=0)`)" msgid "The `PolyParam.generate_title()` method now constructs proper mathematical expressions with correct sign handling, coefficient simplification (e.g., `x` instead of `1x`, `-x` instead of `-1x`), and exponent notation using `^` symbol" msgstr "La méthode `PolyParam.generate_title()` construit désormais des expressions mathématiques appropriées avec une gestion correcte des signes, une simplification des coefficients (par exemple, `x` au lieu de `1x`, `-x` au lieu de `-1x`) et une notation des exposants utilisant le symbole `^`" msgid "Improves readability in DataLab GUI and signal listings by presenting polynomials in standard mathematical form" msgstr "Améliore la lisibilité dans l'interface graphique de DataLab et les listes de signaux en présentant les polynômes sous une forme mathématique standard" msgid "Zero coefficients are automatically omitted from the expression (e.g., `1+x+x³` when a2=0)" msgstr "Les coefficients nuls sont automatiquement omis de l'expression (par exemple, `1+x+x³` lorsque a2=0)" msgid "Handles edge cases including all-zero polynomials (returns `\"0\"`), single terms, and negative coefficients" msgstr "Gère les cas limites, y compris les polynômes tous nuls (renvoie `\"0\"`), les termes uniques et les coefficients négatifs" msgid "This closes [Issue #3](https://github.com/DataLab-Platform/Sigima/issues/3) - Polynomial signal titles should use mathematical notation instead of parameter listing" msgstr "Ceci clôture [Issue #3](https://github.com/DataLab-Platform/Sigima/issues/3) - Les titres des signaux polynomiaux doivent utiliser une notation mathématique au lieu d'une liste de paramètres" msgid "ROI data extraction:" msgstr "Extraction de données ROI :" msgid "Fixed `ValueError: zero-size array to reduction operation minimum which has no identity` error when computing statistics on images with ROI extending beyond canvas boundaries" msgstr "Correction de l'erreur `ValueError: zero-size array to reduction operation minimum which has no identity` lors du calcul des statistiques sur des images avec ROI s'étendant au-delà des limites de la zone de dessin" msgid "The `ImageObj.get_data()` method now properly clips ROI bounding boxes to image boundaries" msgstr "La méthode `ImageObj.get_data()` limite désormais correctement les boîtes englobantes des ROI aux limites de l'image" msgid "When a ROI is completely outside the image bounds, returns a fully masked 1x1 array (containing NaN) to avoid zero-size array errors in statistics computations" msgstr "Lorsqu'une ROI est complètement en dehors des limites de l'image, renvoie un tableau 1x1 entièrement masqué (contenant NaN) pour éviter les erreurs de tableau de taille zéro dans les calculs statistiques" msgid "Partial overlap ROIs are correctly handled by clipping coordinates to valid image ranges" msgstr "Les ROI partiellement superposées sont correctement gérées en limitant les coordonnées aux plages valides de l'image" msgid "This fix ensures robust statistics computation regardless of ROI position relative to image boundaries" msgstr "Ce correctif garantit un calcul statistique robuste quel que soit la position de la ROI par rapport aux limites de l'image" msgid "This closes [Issue #1](https://github.com/DataLab-Platform/Sigima/issues/1) - `ValueError` when computing statistics on ROI extending beyond image boundaries" msgstr "Ceci clôture [Issue #1](https://github.com/DataLab-Platform/Sigima/issues/1) - `ValueError` lors du calcul des statistiques sur ROI s'étendant au-delà des limites de l'image" msgid "Sigima Version 1.0.2 (2025-11-12)" msgstr "" msgid "✨ New features and enhancements:" msgstr "✨ Nouvelles fonctionnalités et améliorations:" msgid "**New parametric image types**: Added five new parametric image generation types for testing and calibration" msgstr "**Nouveaux types d'images paramétriques** : Ajout de cinq nouveaux types de génération d'images paramétriques pour les tests et l'étalonnage" msgid "**Checkerboard pattern**: Alternating squares for camera calibration and spatial frequency analysis. Parameters include square size, offset, and min/max values" msgstr "**Motif en damier** : Carrés alternés pour l'étalonnage de la caméra et l'analyse de la fréquence spatiale. Les paramètres incluent la taille des carrés, le décalage et les valeurs min/max" msgid "**Sinusoidal grating**: Frequency response testing with configurable spatial frequencies (fx, fy), phase, amplitude, and DC offset" msgstr "**Réseau sinusoïdal** : Test de la réponse en fréquence avec des fréquences spatiales configurables (fx, fy), phase, amplitude et offset DC" msgid "**Ring pattern**: Concentric circular rings for radial analysis. Configurable period, width, center position, and amplitude range" msgstr "**Motif en anneau** : Anneaux circulaires concentriques pour l'analyse radiale. Période, largeur, position centrale et plage d'amplitude configurables" msgid "**Siemens star**: Resolution testing pattern with radial spokes. Parameters include number of spokes, inner/outer radius, center position, and value range" msgstr "**Étoile de Siemens** : Motif de test de résolution avec des rayons radiaux. Les paramètres incluent le nombre de rayons, le rayon intérieur/extérieur, la position centrale et la plage de valeurs" msgid "**2D sinc function**: PSF/diffraction modeling with cardinal sine function. Configurable amplitude, center, scale factor (sigma), and DC offset" msgstr "**Fonction sinc 2D** : Modélisation PSF/diffraction avec la fonction sinus cardinal. Amplitude, centre, facteur d'échelle (sigma) et offset DC configurables" msgid "**GeometryResult.value property**: New convenience property for easy script access to computed geometry values" msgstr "**Propriété GeometryResult.value** : Nouvelle propriété de commodité pour un accès facile aux valeurs géométriques calculées dans les scripts" msgid "Supports POINT, MARKER, and SEGMENT shapes" msgstr "Prend en charge les formes POINT, MARKER et SEGMENT" msgid "Returns `(x, y)` tuple for POINT and MARKER shapes (both coordinates accessible)" msgstr "Renvoie un tuple `(x, y)` pour les formes POINT et MARKER (les deux coordonnées accessibles)" msgid "Returns `float` length for SEGMENT shapes (calculated via `segments_lengths()`)" msgstr "Renvoie une longueur `float` pour les formes SEGMENT (calculée via `segments_lengths()`)" msgid "Return type annotation: `float | tuple[float, float]`" msgstr "Annotation de type de retour : `float | tuple[float, float]`" msgid "Provides intuitive API: unpack coordinates with `x, y = result.value` or get length with `length = result.value`" msgstr "Fournit une API intuitive : déballer les coordonnées avec `x, y = result.value` ou obtenir la longueur avec `length = result.value`" msgid "Comprehensive error handling for unsupported shapes and multi-row results" msgstr "Gestion complète des erreurs pour les formes non prises en charge et les résultats à plusieurs lignes" msgid "**Signal analysis functions return GeometryResult**: Changed `x_at_y()` and `y_at_x()` to return geometry results for better visualization" msgstr "**Les fonctions d'analyse de signal renvoient GeometryResult** : Modification de `x_at_y()` et `y_at_x()` pour renvoyer des résultats géométriques pour une meilleure visualisation" msgid "`x_at_y()` now returns `GeometryResult` with `MARKER` kind (previously returned `TableResult`)" msgstr "`x_at_y()` renvoie désormais `GeometryResult` avec le type `MARKER` (au lieu de `TableResult`)" msgid "`y_at_x()` now returns `GeometryResult` with `MARKER` kind (previously returned `TableResult`)" msgstr "`y_at_x()` renvoie désormais `GeometryResult` avec le type `MARKER` (au lieu de `TableResult`)" msgid "Both functions return coordinates as `[x, y]` in N×2 array format for cross marker display" msgstr "Les deux fonctions renvoient les coordonnées sous la forme d'un tableau N×2 pour l'affichage des marqueurs croisés" msgid "Enables proper marker visualization in DataLab GUI (displayed as cross markers on plots)" msgstr "Permet une visualisation correcte des marqueurs dans l'interface graphique de DataLab (affichés comme des marqueurs croisés sur les graphiques)" msgid "Script-friendly API: use `.value` property to easily extract coordinates as `(x, y)` tuple" msgstr "API conviviale pour les scripts : utilisez la propriété `.value` pour extraire facilement les coordonnées sous forme de tuple `(x, y)`" msgid "Example: `x, y = proxy.compute_x_at_y(params).value` provides direct access to both coordinates" msgstr "Exemple : `x, y = proxy.compute_x_at_y(params).value` fournit un accès direct aux deux coordonnées" msgid "Breaking change: Scripts accessing results as tables need to update to use `.value` property or `.coords` array" msgstr "Changement majeur : Les scripts accédant aux résultats sous forme de tableaux doivent être mis à jour pour utiliser la propriété `.value` ou le tableau `.coords`" msgid "Detection functions:" msgstr "Fonctions de détection :" msgid "**Contour detection**: Removed ROI creation support from `ContourShapeParam` as it doesn't make sense for contour detection use cases. The `ContourShapeParam` class no longer inherits from `DetectionROIParam`, and the `contour_shape()` function no longer calls `store_roi_creation_metadata()`. ROI creation remains available for other detection methods (blob detection, 2D peak detection) where it is appropriate." msgstr "**Détection de contours** : Suppression du support de création de ROI dans `ContourShapeParam`, car cela n'a pas de sens pour les cas d'utilisation de détection de contours. La classe `ContourShapeParam` n'hérite plus de `DetectionROIParam`, et la fonction `contour_shape()` n'appelle plus `store_roi_creation_metadata()`. La création de ROI reste disponible pour d'autres méthodes de détection (détection de blobs, détection de pics 2D) où cela est approprié." msgid "**ROI creation error handling**: Enhanced error handling in `create_image_roi_around_points()` function to provide clearer error messages:" msgstr "**Gestion des erreurs de création de ROI** : Amélioration de la gestion des erreurs dans la fonction `create_image_roi_around_points()` pour fournir des messages d'erreur plus clairs :" msgid "Now raises `ValueError` when calculated ROI size is too small (points too close together)" msgstr "Lève désormais une exception `ValueError` lorsque la taille de ROI calculée est trop petite (points trop proches les uns des autres)" msgid "Improved error messages to help users understand the cause of failures" msgstr "Messages d'erreur améliorés pour aider les utilisateurs à comprendre la cause des échecs" msgid "Validates ROI geometry parameter more explicitly" msgstr "Valide le paramètre de géométrie de ROI de manière plus explicite" msgid "Better handling of edge cases in automatic ROI sizing" msgstr "Meilleure gestion des cas limites dans le dimensionnement automatique des ROI" msgid "Public API:" msgstr "API publique :" msgid "Made `BaseObj.roi_has_changed` method private (by renaming to `BaseObj.__roi_has_changed`) to avoid accidental external usage. This would interfere with the internal mask refresh mechanism that relies on controlled access to this method. The method is not part of the public API and should not be called directly by applications." msgstr "La méthode `BaseObj.roi_has_changed` a été rendue privée (en la renommant en `BaseObj.__roi_has_changed`) pour éviter une utilisation externe accidentelle. Cela interférerait avec le mécanisme interne de rafraîchissement des masques qui repose sur un accès contrôlé à cette méthode. La méthode ne fait pas partie de l'API publique et ne doit pas être appelée directement par les applications." msgid "Sigima Version 1.0.1 (2025-11-05)" msgstr "" msgid "**Detection ROI creation**: Generic mechanism for ROI creation across all detection functions" msgstr "**Création de ROI de détection** : Mécanisme générique de création de ROI pour toutes les fonctions de détection" msgid "New `DetectionROIParam` parameter class providing standardized ROI creation fields" msgstr "Nouvelle classe de paramètres `DetectionROIParam` fournissant des champs de création de ROI standardisés" msgid "`create_rois`: Boolean flag to enable/disable ROI creation (default: False)" msgstr "`create_rois`: Indicateur booléen pour activer/désactiver la création de ROI (par défaut : Faux)" msgid "`roi_geometry`: Enum selecting ROI shape (RECTANGLE or CIRCLE, default: RECTANGLE)" msgstr "`roi_geometry`: Enum sélectionnant la forme de la ROI (RECTANGLE ou CIRCLE, par défaut : RECTANGLE)" msgid "New `DetectionROIGeometry` enum in `sigima.enums` with RECTANGLE and CIRCLE options" msgstr "Nouvel énuméré `DetectionROIGeometry` dans `sigima.enums` avec les options RECTANGLE et CIRCLE" msgid "All detection parameter classes now inherit from `DetectionROIParam`:" msgstr "Toutes les classes de paramètres de détection héritent désormais de `DetectionROIParam` :" msgid "`Peak2DDetectionParam`: 2D peak detection" msgstr "`Peak2DDetectionParam`: Détection de pics 2D" msgid "`ContourShapeParam`: Contour shape fitting" msgstr "`ContourShapeParam`: Ajustement de la forme du contour" msgid "`BlobDOGParam`, `BlobDOHParam`, `BlobLOGParam`, `BlobOpenCVParam`: Blob detection methods" msgstr "`BlobDOGParam`, `BlobDOHParam`, `BlobLOGParam`, `BlobOpenCVParam`: Méthodes de détection de blobs" msgid "`HoughCircleParam`: Hough circle detection" msgstr "`HoughCircleParam`: Détection de cercles de Hough" msgid "New `store_roi_creation_metadata()` helper function:" msgstr "Nouvelle fonction d'assistance `store_roi_creation_metadata()` :" msgid "Stores ROI creation intent in `GeometryResult.attrs` dictionary" msgstr "Stocke l'intention de création de ROI dans le dictionnaire `GeometryResult.attrs`" msgid "Called within computation functions to communicate ROI preferences" msgstr "Appelée dans les fonctions de calcul pour communiquer les préférences de ROI" msgid "Does not violate function purity (no object modification)" msgstr "Ne contrevient pas à la pureté de la fonction (pas de modification d'objet)" msgid "New `apply_detection_rois()` helper function:" msgstr "Nouvelle fonction d'assistance `apply_detection_rois()` :" msgid "Creates ROIs on image objects based on `GeometryResult.attrs` metadata" msgstr "Crée des ROIs sur des objets d'image en fonction des métadonnées `GeometryResult.attrs`" msgid "Returns `True` if ROIs were created, `False` otherwise" msgstr "Renvoie `True` si des ROI ont été créées, `False` sinon" msgid "Handles both rectangle and circle geometries" msgstr "Gère les géométries rectangulaires et circulaires" msgid "Automatically calculates optimal ROI size based on feature spacing" msgstr "Calcule automatiquement la taille optimale de la ROI en fonction de l'espacement des caractéristiques" msgid "Can be called by applications outside computation functions" msgstr "Peut être appelé par des applications en dehors des fonctions de calcul" msgid "Metadata-based architecture maintains separation of concerns:" msgstr "L'architecture basée sur les métadonnées maintient la séparation des concepts :" msgid "Computation functions remain pure (no side effects)" msgstr "Les fonctions de calcul restent pures (pas d'effets de bord)" msgid "Applications control when/how ROIs are created" msgstr "Les applications contrôlent quand/comment les ROI sont créées" msgid "Works seamlessly with multiprocessing engines (e.g., DataLab processors)" msgstr "Fonctionne sans problème avec les moteurs de traitement parallèle (par exemple, les processeurs DataLab)" msgid "Comprehensive test coverage with `validate_detection_rois()` helper in test suite" msgstr "Couverture de test complète avec l'assistant `validate_detection_rois()` dans la suite de tests" msgid "**Automatic `func_name` injection for result objects**" msgstr "**Injection automatique de `func_name` pour les objets de résultat**" msgid "The `@computation_function` decorator now automatically injects the function name into `TableResult` and `GeometryResult` objects" msgstr "Le décorateur `@computation_function` injecte désormais automatiquement le nom de la fonction dans les objets `TableResult` et `GeometryResult`" msgid "When a computation function returns a result object with `func_name=None`, the decorator sets it to the function's name using `dataclasses.replace()`" msgstr "Lorsqu'une fonction de calcul renvoie un objet de résultat avec `func_name=None`, le décorateur le définit au nom de la fonction en utilisant `dataclasses.replace()`" msgid "Ensures systematic assignment of `func_name` for proper result tracking and display" msgstr "Garantit l'attribution systématique de `func_name` pour un suivi et un affichage appropriés des résultats" msgid "Implementation uses direct `isinstance()` type checking for `TableResult` and `GeometryResult`" msgstr "L'implémentation utilise la vérification directe de type `isinstance()` pour `TableResult` et `GeometryResult`" msgid "Applies to both main decorator wrapper (with DataSet parameters) and simple passthrough wrapper" msgstr "S'applique à la fois au wrapper principal du décorateur (avec les paramètres DataSet) et au wrapper de passage simple" msgid "Eliminates need for manual `func_name` assignment in computation functions" msgstr "Élimine le besoin d'attribution manuelle de `func_name` dans les fonctions de calcul" msgid "**Image ROI creation utility**: New `create_image_roi_around_points()` function in `sigima.objects.image.roi`" msgstr "**Utilitaire de création de ROI d'image** : Nouvelle fonction `create_image_roi_around_points()` dans `sigima.objects.image.roi`" msgid "Creates rectangular or circular ROIs around a set of point coordinates" msgstr "Crée des ROI rectangulaires ou circulaires autour d'un ensemble de coordonnées de points" msgid "Automatically calculates optimal ROI size based on minimum distance between points" msgstr "Calcule automatiquement la taille optimale de la ROI en fonction de la distance minimale entre les points" msgid "Handles boundary conditions to keep ROIs within valid image coordinates" msgstr "Gère les conditions de bord pour maintenir les ROI dans des coordonnées d'image valides" msgid "Supports both \"rectangle\" and \"circle\" geometry types" msgstr "Prend en charge les types de géométrie \"rectangle\" et \"cercle\"" msgid "Designed for creating ROIs around detected features (peaks, blobs, etc.)" msgstr "Conçu pour créer des ROI autour des caractéristiques détectées (pics, blobs, etc.)" msgid "Centralizes ROI creation logic previously duplicated across applications" msgstr "Centralise la logique de création de ROI précédemment dupliquée dans les applications" msgid "**Annotations API**: New public API for managing annotations on Signal and Image objects" msgstr "**API d'annotations** : Nouvelle API publique pour la gestion des annotations sur les objets Signal et Image" msgid "Added `get_annotations()` method: Returns a list of annotations in versioned JSON format" msgstr "Ajout de la méthode `get_annotations()` : Renvoie une liste d'annotations au format JSON versionné" msgid "Added `set_annotations(annotations)` method: Sets annotations from a list (replaces existing annotations)" msgstr "Ajout de la méthode `set_annotations(annotations)` : Définit les annotations à partir d'une liste (remplace les annotations existantes)" msgid "Added `add_annotation(annotation)` method: Adds a single annotation to the object" msgstr "Ajout de la méthode `add_annotation(annotation)` : Ajoute une seule annotation à l'objet" msgid "Added `clear_annotations()` method: Removes all annotations from the object" msgstr "Ajout de la méthode `clear_annotations()` : Supprime toutes les annotations de l'objet" msgid "Added `has_annotations()` method: Returns True if the object has any annotations" msgstr "Ajout de la méthode `has_annotations()` : Renvoie True si l'objet a des annotations" msgid "Annotations are stored in object metadata with versioning support (currently version \"1.0\")" msgstr "Les annotations sont stockées dans les métadonnées de l'objet avec un support de versionnage (actuellement version \"1.0\")" msgid "Each annotation is a dictionary with keys such as `type`, `item_class`, and `item_json` (for example)" msgstr "Chaque annotation est un dictionnaire avec des clés telles que `type`, `item_class` et `item_json` (par exemple)" msgid "Provides clean separation between generic annotation storage and visualization-specific details" msgstr "Fournit une séparation claire entre le stockage générique des annotations et les détails spécifiques à la visualisation" msgid "Enables applications to manage plot annotations (shapes, labels, etc.) independently of ROIs" msgstr "Permet aux applications de gérer les annotations de tracé (formes, étiquettes, etc.) indépendamment des ROI" msgid "Fully compatible with DataLab's PlotPy adapter pattern for visualization" msgstr "Entièrement compatible avec le modèle d'adaptateur PlotPy de DataLab pour la visualisation" msgid "**2D peak detection**: Fixed architectural violation in `peak_detection()` computation function" msgstr "**Détection de pics 2D** : Correction d'une violation architecturale dans la fonction de calcul `peak_detection()`" msgid "Removed direct ROI creation from computation function (was modifying input objects)" msgstr "Suppression de la création directe de ROI dans la fonction de calcul (modifiait les objets d'entrée)" msgid "Computation functions decorated with `@computation_function()` must be pure (no side effects)" msgstr "Les fonctions de calcul décorées avec `@computation_function()` doivent être pures (pas d'effets de bord)" msgid "Removed line 128: `obj.roi = create_image_roi(...)` which violated this principle" msgstr "Suppression de la ligne 128 : `obj.roi = create_image_roi(...)` qui contrevenait à ce principe" msgid "ROI creation now handled by applications in their presentation layer" msgstr "La création de ROI est désormais gérée par les applications dans leur couche de présentation" msgid "DataLab uses new `create_image_roi_around_points()` utility for this purpose" msgstr "DataLab utilise la nouvelle utilité `create_image_roi_around_points()` à cet effet" msgid "Maintains separation of concerns: Sigima computes results, applications create visual representations" msgstr "Maintient la séparation des concepts : Sigima calcule les résultats, les applications créent des représentations visuelles" msgid "Fixes regression where ROIs were not appearing in DataLab's processor-based workflow" msgstr "Corrige la régression où les ROI n'apparaissaient pas dans le flux de travail basé sur les processeurs de DataLab" msgid "**Parameter classes**: Removed default titles from generic `OrdinateParam` and `AbscissaParam` classes" msgstr "**Classes de paramètres** : Suppression des titres par défaut des classes génériques `OrdinateParam` et `AbscissaParam`" msgid "These parameter classes are reused across multiple computation functions (e.g., `full_width_at_y`, `x_at_y`)" msgstr "Ces classes de paramètres sont réutilisées dans plusieurs fonctions de calcul (par exemple, `full_width_at_y`, `x_at_y`)" msgid "Default titles like \"Ordinate\" created redundancy when displayed with function names in analysis results" msgstr "Des titres par défaut comme \"Ordinate\" créaient une redondance lorsqu'ils étaient affichés avec les noms de fonction dans les résultats d'analyse." msgid "Titles are now empty by default, allowing applications to provide context-specific titles when needed" msgstr "Les titres sont désormais vides par défaut, permettant aux applications de fournir des titres spécifiques au contexte si nécessaire." msgid "Improves clarity when the same parameter class is used by different functions" msgstr "Améliore la clarté lorsque la même classe de paramètres est utilisée par différentes fonctions." msgid "**Result HTML representation**: Improved color contrast for dark mode" msgstr "Représentation HTML des résultats : amélioration du contraste des couleurs pour le mode sombre" msgid "Changed result title color in `to_html()` methods from standard blue (#0000FF) to a lighter shade (#5294e2)" msgstr "Changement de la couleur du titre des résultats dans les méthodes `to_html()` de bleu standard (#0000FF) à une teinte plus claire (#5294e2)" msgid "Affects TableResult and GeometryResult HTML output" msgstr "Affecte la sortie HTML de TableResult et GeometryResult" msgid "Provides better visibility in dark mode while maintaining good appearance in light mode" msgstr "Offre une meilleure visibilité en mode sombre tout en maintenant une bonne apparence en mode clair" msgid "Improves readability when results are displayed in applications with dark themes" msgstr "Améliore la lisibilité lorsque les résultats sont affichés dans des applications avec des thèmes sombres" msgid "Fixed pulse features extraction with ROI signals. When extracting pulse features from signals with ROIs, the start/end range parameters (which apply to the full signal) were being used on ROI-extracted data, causing incorrect results. Now `extract_pulse_features()` detects when the parameter ranges are outside the ROI's x-range and automatically switches to auto-detection mode. Additionally, `extract_pulse_features()` in `sigima.tools.signal.pulse` now properly initializes `None` ranges using `get_start_range()` and `get_end_range()` with the `fraction` parameter. This ensures pulse features extracted from a signal with ROIs match the features extracted from individually extracted ROI signals." msgstr "Correction de l'extraction des caractéristiques des impulsions avec des signaux ROI. Lors de l'extraction des caractéristiques des impulsions à partir de signaux avec des ROI, les paramètres de plage de début/fin (qui s'appliquent au signal complet) étaient utilisés sur les données extraites des ROI, ce qui entraînait des résultats incorrects. Désormais, `extract_pulse_features()` détecte lorsque les plages de paramètres sont en dehors de la plage x de la ROI et passe automatiquement en mode de détection automatique. De plus, `extract_pulse_features()` dans `sigima.tools.signal.pulse` initialise désormais correctement les plages `None` en utilisant `get_start_range()` et `get_end_range()` avec le paramètre `fraction`. Cela garantit que les caractéristiques des impulsions extraites d'un signal avec des ROI correspondent aux caractéristiques extraites des signaux ROI extraits individuellement." msgid "Fixed ROI extraction for signals: ROIs are no longer incorrectly copied to destination signals when extracting ROIs. When using `extract_roi()` or `extract_rois()`, the extracted signals now have no ROI defined, which is the expected behavior since the extracted data already represents the ROI itself. This fixes the issue where extracted signals would inherit the source signal's ROI definitions." msgstr "Correction de l'extraction des ROI pour les signaux : les ROI ne sont plus copiées vers les signaux de destination lors de l'extraction des ROI. Lors de l'utilisation de `extract_roi()` ou `extract_rois()`, les signaux extraits n'ont désormais aucune ROI définie, ce qui est le comportement attendu puisque les données extraites représentent déjà la ROI elle-même. Cela corrige le problème où les signaux extraits hériterait des définitions de ROI du signal source." msgid "Fixed pulse features computation to be ROI-exclusive when ROIs are defined. Previously, `TableKind.PULSE_FEATURES` incorrectly computed results for both the whole object and each ROI. This made no sense for pulse analysis, where defining ROIs indicates the presence of multiple pulses, making whole-object features irrelevant. Now `PULSE_FEATURES` correctly computes only on ROIs when they exist, otherwise on the whole object. `TableKind.STATISTICS` and `TableKind.CUSTOM` maintain the expected behavior (whole object + ROIs)." msgstr "Correction de l'extraction des caractéristiques des impulsions pour qu'elle soit exclusive aux ROI lorsque des ROI sont définies. Auparavant, `TableKind.PULSE_FEATURES` calculait incorrectement les résultats à la fois pour l'objet entier et pour chaque ROI. Cela n'avait pas de sens pour l'analyse des impulsions, où la définition des ROI indique la présence de plusieurs impulsions, rendant les caractéristiques de l'objet entier non pertinentes. Désormais, `PULSE_FEATURES` calcule correctement uniquement sur les ROI lorsqu'elles existent, sinon sur l'objet entier. `TableKind.STATISTICS` et `TableKind.CUSTOM` conservent le comportement attendu (objet entier + ROI)." msgid "Fixed `ValueError` in `choose_savgol_window_auto()` when processing small data arrays (e.g., ROI segments). The function now properly constrains the Savitzky-Golay window length to be strictly less than the array size, as required by scipy's `mode='interp'` option. This fixes the issue when extracting pulse features from small ROI segments in signals." msgstr "Correction de `ValueError` dans `choose_savgol_window_auto()` lors du traitement de petits tableaux de données (par exemple, des segments ROI). La fonction contraint désormais correctement la longueur de la fenêtre Savitzky-Golay à être strictement inférieure à la taille du tableau, comme l'exige l'option `mode='interp'` de scipy. Cela corrige le problème lors de l'extraction des caractéristiques des impulsions à partir de petits segments ROI dans les signaux." msgid "Modified `RadialProfileParam` to allow initialization of the dataset even when the associated image object is not yet set (call to `update_from_obj`). This is useful when creating the parameter object before assigning the image, enabling more flexible workflows." msgstr "Modification de `RadialProfileParam` pour permettre l'initialisation de l'ensemble de données même lorsque l'objet image associé n'est pas encore défini (appel à `update_from_obj`). Cela est utile lors de la création de l'objet paramètre avant d'assigner l'image, permettant des flux de travail plus flexibles." msgid "Removed unused `signals_to_array()` function from `sigima.proc.signal.arithmetic` module. This function was not used anywhere in the codebase and has been replaced by direct NumPy array construction in `__signals_y_to_array()` and `__signals_dy_to_array()` functions, for internal use only." msgstr "Suppression de la fonction inutilisée `signals_to_array()` du module `sigima.proc.signal.arithmetic`. Cette fonction n'était utilisée nulle part dans la base de code et a été remplacée par une construction directe de tableau NumPy dans les fonctions `__signals_y_to_array()` et `__signals_dy_to_array()`, pour un usage interne uniquement." msgid "**ROI coordinate setters**: Fixed bugs in `set_physical_coords()` and `set_indices_coords()` methods" msgstr "**Méthodes de définition des coordonnées ROI** : Correction des bogues dans les méthodes `set_physical_coords()` et `set_indices_coords()`" msgid "Fixed `RectangularROI.set_physical_coords()`: Now correctly stores coordinates in delta format `[x0, y0, dx, dy]` instead of corner format `[x0, y0, x1, y1]` when `indices=True`" msgstr "Correction de `RectangularROI.set_physical_coords()` : Maintenant, les coordonnées sont correctement stockées au format delta `[x0, y0, dx, dy]` au lieu du format coin `[x0, y0, x1, y1]` lorsque `indices=True`" msgid "Fixed `BaseSingleROI.set_indices_coords()`: Now correctly converts the input `coords` parameter instead of `self.coords` when `indices=False`" msgstr "Correction de `BaseSingleROI.set_indices_coords()` : Maintenant, le paramètre d'entrée `coords` est correctement converti au lieu de `self.coords` lorsque `indices=False`" msgid "These methods were implemented for API completeness but were not used in the Sigima/DataLab codebase" msgstr "Ces méthodes ont été implémentées pour compléter l'API mais n'ont pas été utilisées dans la base de code Sigima/DataLab" msgid "Added comprehensive unit tests covering all ROI types (rectangular, circular, polygonal) and edge cases" msgstr "Ajout de tests unitaires complets couvrant tous les types de ROI (rectangulaire, circulaire, polygonal) et les cas limites" msgid "Sigima Version 1.0.0 (2025-10-28)" msgstr "" msgid "**Signals to image conversion**: New feature to combine multiple signals into a 2D image" msgstr "**Conversion de signaux en image** : Nouvelle fonctionnalité pour combiner plusieurs signaux en une image 2D" msgid "New computation function `signals_to_image()` in `sigima.proc.signal.arithmetic`" msgstr "Nouvelle fonction de calcul `signals_to_image()` dans `sigima.proc.signal.arithmetic`" msgid "Takes a list of signals and combines them into an image by stacking Y-arrays" msgstr "Prend une liste de signaux et les combine en une image en empilant des tableaux Y" msgid "Two orientation modes:" msgstr "Deux modes d'orientation :" msgid "**Rows**: Each signal becomes a row in the image (default)" msgstr "**Lignes** : Chaque signal devient une ligne dans l'image (par défaut)" msgid "**Columns**: Each signal becomes a column in the image" msgstr "**Colonnes** : Chaque signal devient une colonne dans l'image" msgid "Optional normalization:" msgstr "Normalisation facultative :" msgid "Supports multiple normalization methods (Z-score, Min-Max, Maximum)" msgstr "Prend en charge plusieurs méthodes de normalisation (Z-score, Min-Max, Maximum)" msgid "Normalizes each signal independently before stacking" msgstr "Normalise chaque signal indépendamment avant l'empilement" msgid "Useful for visualizing signals with different amplitude ranges" msgstr "Utile pour visualiser des signaux avec différentes plages d'amplitude" msgid "Validates that all signals have the same size before combining" msgstr "Valide que tous les signaux ont la même taille avant de les combiner" msgid "New parameter class `SignalsToImageParam` with orientation and normalization settings" msgstr "Nouvelle classe de paramètres `SignalsToImageParam` avec des paramètres d'orientation et de normalisation" msgid "New enum `SignalsToImageOrientation` for specifying row/column orientation" msgstr "Nouvel énuméré `SignalsToImageOrientation` pour spécifier l'orientation des lignes/colonnes" msgid "Comprehensive validation tests for all combinations of parameters" msgstr "Tests de validation complets pour toutes les combinaisons de paramètres" msgid "Ideal for creating spectrograms, heatmaps, or waterfall displays from signal collections" msgstr "Idéal pour créer des spectrogrammes, des cartes thermiques ou des affichages en cascade à partir de collections de signaux" msgid "**Non-uniform coordinate support for images**: Added comprehensive support for non-uniform pixel coordinates" msgstr "**Prise en charge des coordonnées non uniformes pour les images** : Ajout d'une prise en charge complète des coordonnées de pixels non uniformes" msgid "`ImageObj` now supports both uniform and non-uniform coordinate systems:" msgstr "`ImageObj` prend désormais en charge les systèmes de coordonnées uniformes et non uniformes :" msgid "Uniform coordinates: defined by origin (`x0`, `y0`) and pixel spacing (`dx`, `dy`)" msgstr "Coordonnées uniformes : définies par l'origine (`x0`, `y0`) et l'espacement des pixels (`dx`, `dy`)" msgid "Non-uniform coordinates: defined by coordinate arrays (`xcoords`, `ycoords`)" msgstr "Coordonnées non uniformes : définies par des tableaux de coordonnées (`xcoords`, `ycoords`)" msgid "New methods for coordinate manipulation:" msgstr "Nouvelles méthodes pour la manipulation des coordonnées :" msgid "`set_coords()`: Set non-uniform X and Y coordinate arrays" msgstr "`set_coords()`: Définir les tableaux de coordonnées X et Y non uniformes" msgid "`is_uniform_coords`: Property to check if coordinates are uniform" msgstr "`is_uniform_coords`: Propriété pour vérifier si les coordonnées sont uniformes" msgid "New computation function `set_uniform_coords()`: Convert non-uniform to uniform coordinates" msgstr "`set_uniform_coords()`: Nouvelle fonction de calcul pour convertir les coordonnées non uniformes en coordonnées uniformes" msgid "Automatically extracts uniform spacing from non-uniform arrays" msgstr "Extrait automatiquement l'espacement uniforme des tableaux non uniformes" msgid "Handles numerical precision issues from linspace-generated arrays" msgstr "Gère les problèmes de précision numérique des tableaux générés par linspace" msgid "Preserves image data while transforming coordinate system" msgstr "Préserve les données d'image lors de la transformation du système de coordonnées" msgid "Enhanced `calibration()` function with polynomial support:" msgstr "Amélioration de la fonction `calibration()` avec prise en charge des polynômes :" msgid "Now supports polynomial calibration up to cubic order: `dst = a0 + a1*src + a2*src² + a3*src³`" msgstr "Prend désormais en charge l'étalonnage polynomial jusqu'à l'ordre cubique : `dst = a0 + a1*src + a2*src² + a3*src³`" msgid "Parameter class changed from `a, b` (linear) to `a0, a1, a2, a3` (polynomial)" msgstr "La classe de paramètres est passée de `a, b` (linéaire) à `a0, a1, a2, a3` (polynomiale)" msgid "Works on X-axis, Y-axis (creating non-uniform coordinates), and Z-axis (data values)" msgstr "Fonctionne sur l'axe X, l'axe Y (création de coordonnées non uniformes) et l'axe Z (valeurs de données)" msgid "Linear calibration is a special case with `a2=0, a3=0`" msgstr "L'étalonnage linéaire est un cas particulier avec `a2=0, a3=0`" msgid "Automatically handles conversion between uniform and non-uniform coordinate systems" msgstr "Gère automatiquement la conversion entre les systèmes de coordonnées uniformes et non uniformes" msgid "Enhanced I/O support:" msgstr "Support I/O amélioré :" msgid "HDF5 format now serializes/deserializes non-uniform coordinates" msgstr "Le format HDF5 prend désormais en charge la sérialisation/désérialisation des coordonnées non uniformes" msgid "Coordinated text files support non-uniform coordinate arrays" msgstr "Les fichiers texte coordonnés prennent en charge les tableaux de coordonnées non uniformes" msgid "All geometric operations updated to handle both coordinate types:" msgstr "Toutes les opérations géométriques ont été mises à jour pour gérer les deux types de coordonnées :" msgid "Coordinate transformations preserve or create appropriate coordinate system" msgstr "Les transformations de coordonnées préservent ou créent un système de coordonnées approprié" msgid "ROI operations work seamlessly with both uniform and non-uniform coordinates" msgstr "Les opérations ROI fonctionnent sans problème avec des coordonnées uniformes et non uniformes" msgid "**DateTime support for signal data**: Added comprehensive datetime handling for signal X-axis data" msgstr "**Prise en charge des DateTime pour les données de signal** : Ajout d'une gestion complète des DateTime pour les données de l'axe X du signal" msgid "Automatic detection and conversion of datetime columns when reading CSV files" msgstr "Détection et conversion automatiques des colonnes datetime lors de la lecture des fichiers CSV" msgid "Detects datetime values in the first or second column (handling index columns)" msgstr "Détecte les valeurs datetime dans la première ou la deuxième colonne (gestion des colonnes d'index)" msgid "Validates datetime format and ensures reasonable date ranges (post-1900)" msgstr "Valide le format datetime et garantit des plages de dates raisonnables (post-1900)" msgid "Converts datetime strings to float timestamps for efficient computation" msgstr "Convertit les chaînes datetime en timestamps flottants pour un calcul efficace" msgid "Preserves datetime metadata for proper display and export" msgstr "Préserve les métadonnées datetime pour un affichage et une exportation appropriés" msgid "New `SignalObj` methods for datetime manipulation:" msgstr "Nouvelles méthodes `SignalObj` pour la manipulation des datetime :" msgid "`set_x_from_datetime()`: Convert datetime objects/strings to signal X data with configurable time units (s, ms, μs, ns, min, h)" msgstr "`set_x_from_datetime()`: Convertit les objets/chaînes datetime en données X de signal avec des unités de temps configurables (s, ms, μs, ns, min, h)" msgid "`get_x_as_datetime()`: Retrieve X values as datetime objects for display or export" msgstr "`get_x_as_datetime()`: Récupère les valeurs X sous forme d'objets datetime pour l'affichage ou l'exportation" msgid "`is_x_datetime()`: Check if signal contains datetime data" msgstr "`is_x_datetime()`: Vérifie si le signal contient des données datetime" msgid "Enhanced CSV export to preserve datetime format when writing signals with datetime X-axis" msgstr "Export CSV amélioré pour préserver le format datetime lors de l'écriture de signaux avec un axe X datetime" msgid "New constants module (`sigima.objects.signal.constants`) defining datetime metadata keys and time unit conversion factors" msgstr "Nouveau module de constantes (`sigima.objects.signal.constants`) définissant les clés de métadonnées datetime et les facteurs de conversion des unités de temps" msgid "Comprehensive unit tests covering datetime conversion, I/O roundtrip, and edge cases" msgstr "Tests unitaires complets couvrant la conversion datetime, le roundtrip I/O et les cas limites" msgid "Example test data file with real-world temperature/humidity logger data (`datetime.txt`)" msgstr "Fichier de données de test exemple avec des données de logger de température/humidité du monde réel (`datetime.txt`)" msgid "**New client subpackage**: Migrated DataLab client functionality to `sigima.client`" msgstr "**Nouveau sous-paquet client** : Fonctionnalité client DataLab migrée vers `sigima.client`" msgid "Added `sigima.client.remote.SimpleRemoteProxy` for XML-RPC communication with DataLab" msgstr "Ajout de `sigima.client.remote.SimpleRemoteProxy` pour la communication XML-RPC avec DataLab" msgid "Added `sigima.client.base.SimpleBaseProxy` as abstract base class for DataLab proxies" msgstr "Ajout de `sigima.client.base.SimpleBaseProxy` en tant que classe de base abstraite pour les proxys DataLab" msgid "Included comprehensive unit tests and API documentation" msgstr "Ajout de tests unitaires complets et de documentation API" msgid "Maintains headless design principle (GUI components excluded)" msgstr "Maintient le principe de conception sans interface graphique (composants GUI exclus)" msgid "Enables remote control of DataLab application from Python scripts and Jupyter notebooks" msgstr "Permet le contrôle à distance de l'application DataLab depuis des scripts Python et des notebooks Jupyter" msgid "Client functionality is now directly accessible: `from sigima import SimpleRemoteProxy`" msgstr "La fonctionnalité client est désormais directement accessible : `from sigima import SimpleRemoteProxy`" msgid "**New image ROI feature**: Added inverse ROI functionality for image ROIs" msgstr "**Nouvelle fonctionnalité de ROI d'image** : Ajout de la fonctionnalité ROI inverse pour les ROIs d'image" msgid "Added `inside` parameter to `BaseSingleImageROI` base class, inherited by all image ROI types (`PolygonalROI`, `RectangularROI`, `CircularROI`)" msgstr "Ajout du paramètre `inside` à la classe de base `BaseSingleImageROI`, héritée par tous les types de ROI d'image (`PolygonalROI`, `RectangularROI`, `CircularROI`)" msgid "When `inside=True`, ROI represents the region inside the shape (inverted behavior)" msgstr "Lorsque `inside=True`, le ROI représente la région à l'intérieur de la forme (comportement inversé)" msgid "When `inside=False` (default), ROI represents the region outside the shape (original behavior)" msgstr "Lorsque `inside=False` (par défaut), le ROI représente la région à l'extérieur de la forme (comportement original)" msgid "Fully integrated with serialization (`to_dict`/`from_dict`) and parameter conversion (`to_param`/`from_param`)" msgstr "Entièrement intégré à la sérialisation (`to_dict`/`from_dict`) et à la conversion de paramètres (`to_param`/`from_param`)" msgid "Signal ROIs (`SegmentROI`) are unaffected as the concept doesn't apply to 1D intervals" msgstr "Les ROIs de signal (`SegmentROI`) ne sont pas affectées car le concept ne s'applique pas aux intervalles 1D." msgid "Optimal architecture with zero code duplication - all `inside` functionality implemented once in the base class" msgstr "Architecture optimale sans duplication de code - toute la fonctionnalité `inside` est implémentée une seule fois dans la classe de base." msgid "Individual ROI classes no longer need custom constructors, inheriting directly from base class" msgstr "Les classes ROI individuelles n'ont plus besoin de constructeurs personnalisés, héritant directement de la classe de base." msgid "New image operation:" msgstr "Nouvelle opération d'image :" msgid "Convolution." msgstr "Convolution." msgid "New image format support:" msgstr "Nouveau support de format d'image :" msgid "**Coordinated text image files**: Added support for reading coordinated text files (`.txt` extension), similar to the Matris image format." msgstr "**Fichiers image texte avec coordonnées** : Ajout de la prise en charge de la lecture des fichiers texte coordonnés (extension `.txt`), similaires au format d'image Matris." msgid "Supports both real and complex-valued image data with optional error images." msgstr "Prend en charge à la fois les données d'image réelles et à valeurs complexes avec des images d'erreur facultatives." msgid "Automatically handles NaN values in the data." msgstr "Gère automatiquement les valeurs NaN dans les données." msgid "Reads metadata including units (X, Y, Z) and labels from file headers." msgstr "Lit les métadonnées, y compris les unités (X, Y, Z) et les étiquettes, à partir des en-têtes de fichiers." msgid "New image analysis features:" msgstr "Nouvelles fonctionnalités d'analyse de l'image :" msgid "Horizontal and vertical projections" msgstr "Projections horizontale et verticale" msgid "Compute the horizontal projection profile by summing values along the y-axis (`sigima.proc.image.measurement.horizontal_projection`)." msgstr "Calcule le profil de projection horizontale en sommant les valeurs le long de l'axe y (`sigima.proc.image.measurement.horizontal_projection`)." msgid "Compute the vertical projection profile by summing values along the x-axis (`sigima.proc.image.measurement.vertical_projection`)." msgstr "Calcule le profil de projection verticale en sommant les valeurs le long de l'axe x (`sigima.proc.image.measurement.vertical_projection`)." msgid "**New curve fitting algorithms**: Complete curve fitting framework with `sigima.tools.signal.fitting` module:" msgstr "**Nouveaux algorithmes de courbe d'ajustement**: Cadre complet d'ajustement de courbe avec le module `sigima.tools.signal.fitting` :" msgid "**Core fitting functions**: Comprehensive set of curve fitting algorithms for scientific data analysis:" msgstr "**Fonctions d'ajustement de base**: Ensemble complet d'algorithmes d'ajustement de courbe pour l'analyse de données scientifiques :" msgid "`linear_fit`: Linear regression fitting" msgstr "`linear_fit`: Ajustement de régression linéaire" msgid "`polynomial_fit`: Polynomial fitting with configurable degree" msgstr "`polynomial_fit`: Ajustement polynomial avec degré configurable" msgid "`gaussian_fit`: Gaussian profile fitting for peak analysis" msgstr "`gaussian_fit`: Ajustement de profil gaussien pour l'analyse de pics" msgid "`lorentzian_fit`: Lorentzian profile fitting for spectroscopy" msgstr "`lorentzian_fit`: Ajustement de profil lorentzien pour la spectroscopie" msgid "`voigt_fit`: Voigt profile fitting (convolution of Gaussian and Lorentzian profiles)" msgstr "`voigt_fit`: Ajustement de profil Voigt (convolution des profils gaussien et lorentzien)" msgid "`exponential_fit`: Single exponential fitting with overflow protection" msgstr "`exponential_fit`: Ajustement exponentiel simple avec protection contre les débordements" msgid "`piecewiseexponential_fit`: Piecewise exponential (raise-decay) fitting with advanced parameter estimation" msgstr "`piecewiseexponential_fit`: Ajustement exponentiel par morceaux (croissante-décroissante) avec estimation avancée des paramètres" msgid "`planckian_fit`: Planckian (blackbody radiation) fitting with correct physics implementation" msgstr "`planckian_fit`: Ajustement planckien (radiation du corps noir) avec mise en œuvre physique correcte" msgid "`twohalfgaussian_fit`: Asymmetric peak fitting with separate left/right parameters" msgstr "`twohalfgaussian_fit`: Ajustement de pic asymétrique avec des paramètres gauche/droite séparés" msgid "`multilorentzian_fit`: Multi-peak Lorentzian fitting for complex spectra" msgstr "`multilorentzian_fit`: Ajustement Lorentzien multi-pic pour des spectres complexes" msgid "`sinusoidal_fit`: Sinusoidal fitting with FFT-based frequency estimation" msgstr "`sinusoidal_fit`: Ajustement sinusoïdal avec estimation de fréquence basée sur FFT" msgid "`cdf_fit`: Cumulative Distribution Function fitting using error function" msgstr "`cdf_fit`: Ajustement de la fonction de distribution cumulative utilisant la fonction d'erreur" msgid "`sigmoid_fit`: Sigmoid (logistic) function fitting for S-shaped curves" msgstr "`sigmoid_fit`: Ajustement de la fonction sigmoïde (logistique) pour les courbes en S" msgid "**Advanced piecewise exponential (raise-decay) fitting**: Enhanced algorithm with:" msgstr "**Ajustement exponentiel par morceaux (croissante-décroissante) avancé**: Algorithme amélioré avec :" msgid "Standard piecewise exponential model: `y = a_left*exp(b_left*x) + a_right*exp(b_right*x) + y0`" msgstr "Modèle standard exponentiel par morceaux : `y = a_left*exp(b_left*x) + a_right*exp(b_right*x) + y0`" msgid "Multi-start optimization strategy for robust convergence to global minimum" msgstr "Stratégie d'optimisation multi-démarrage pour une convergence robuste vers le minimum global" msgid "Support for both positive and negative exponential rates (growth and decay components)" msgstr "Prise en charge des taux exponentiels positifs et négatifs (composantes de croissance et de décroissance)" msgid "Comprehensive parameter bounds validation to prevent optimization errors" msgstr "Validation complète des limites des paramètres pour éviter les erreurs d'optimisation" msgid "**Enhanced asymmetric peak fitting**: Advanced `twohalfgaussian_fit` with:" msgstr "**Ajustement de pic asymétrique amélioré**: `twohalfgaussian_fit` avancé avec :" msgid "Separate baseline offsets for left and right sides (`y0_left`, `y0_right`)" msgstr "Offsets de base séparés pour les côtés gauche et droit (`y0_left`, `y0_right`)" msgid "Independent amplitude parameters (`amp_left`, `amp_right`) for better asymmetric modeling" msgstr "Paramètres d'amplitude indépendants (`amp_left`, `amp_right`) pour un meilleur modélisation asymétrique" msgid "Robust baseline estimation using percentile-based methods" msgstr "Estimation robuste de la ligne de base utilisant des méthodes basées sur les percentiles" msgid "**Technical features**: All fitting functions include:" msgstr "**Fonctionnalités techniques**: Toutes les fonctions d'ajustement incluent :" msgid "Automatic initial parameter estimation from data characteristics" msgstr "Estimation automatique des paramètres initiaux à partir des caractéristiques des données" msgid "Proper bounds enforcement ensuring optimization stability" msgstr "Application correcte des limites garantissant la stabilité de l'optimisation" msgid "Comprehensive error handling and parameter validation" msgstr "Gestion complète des erreurs et validation des paramètres" msgid "Consistent dataclass-based parameter structures" msgstr "Structures de paramètres basées sur des classes de données cohérentes" msgid "Full test coverage with synthetic and experimental data validation" msgstr "Couverture de test complète avec validation des données synthétiques et expérimentales" msgid "New common signal/image feature:" msgstr "Nouvelles fonctionnalités communes signal/image :" msgid "Added `phase` (argument) feature to extract the phase information from complex signals or images." msgstr "Ajout de la fonctionnalité `phase` (argument) pour extraire les informations de phase des signaux ou des images complexes." msgid "Added operation to create complex-valued signal/image from real and imaginary parts." msgstr "Ajout de l'opération pour créer un signal/image à valeurs complexes à partir des parties réelle et imaginaire." msgid "Added operation to create complex-valued signal/image from magnitude and phase." msgstr "Ajout de l'opération pour créer un signal/image à valeurs complexes à partir de l'amplitude et de la phase." msgid "Standard deviation of the selected signals or images (this complements the \"Average\" feature)." msgstr "Écart-type des signaux ou images de la sélection (ceci complète la fonctionnalité \"Moyenne\")." msgid "Generate new signal or image: Poisson noise." msgstr "Générer un nouveau signal ou une nouvelle image : bruit de Poisson." msgid "Add noise to the selected signals or images." msgstr "Ajouter du bruit aux signaux ou images sélectionnés." msgid "Gaussian, Poisson or uniform noise can be added." msgstr "Du bruit gaussien, de Poisson ou uniforme peut être ajouté." msgid "New utility functions to generate file basenames." msgstr "Nouvelles fonctions utilitaires pour générer des noms de fichiers." msgid "Deconvolution in the frequency domain." msgstr "Déconvolution dans le domaine fréquentiel." msgid "New ROI features:" msgstr "Nouvelles fonctionnalités de ROI:" msgid "Improved single ROI title handling, using default title based on the index of the ROI when no title is provided." msgstr "Amélioration de la gestion du titre de la ROI unique, en utilisant un titre par défaut basé sur l'index de la ROI lorsque aucun titre n'est fourni." msgid "Added `combine_with` method to ROI objects (`SignalROI` and `ImageROI`) to return a new ROI that combines the current ROI with another one (union) and handling duplicate ROIs." msgstr "Ajout de la méthode `combine_with` aux objets ROI (`SignalROI` et `ImageROI`) pour renvoyer un nouvel ROI qui combine le ROI actuel avec un autre (union) et gère les ROIs en double." msgid "Image ROI transformations:" msgstr "Transformations de ROI d'image:" msgid "Before this change, image ROI were removed after applying each single computation function." msgstr "Avant ce changement, les ROI d'image étaient supprimées après l'application de chaque fonction de calcul unique." msgid "Now, the geometry computation functions preserve the ROI information across transformations: the transformed ROIs are automatically updated in the image object." msgstr "Maintenant, les fonctions de calcul géométrique préservent les informations de ROI à travers les transformations: les ROIs transformées sont automatiquement mises à jour dans l'objet image." msgid "Image ROI coordinates:" msgstr "Coordonnées de ROI d'image:" msgid "Before this change, image ROI coordinates were defined using indices by default." msgstr "Avant ce changement, les coordonnées de ROI d'image étaient définies par défaut à l'aide d'indices." msgid "Now, `ROI2DParam` uses physical coordinates by default." msgstr "Maintenant, `ROI2DParam` utilise des coordonnées physiques par défaut." msgid "Note that ROI may still be defined using indices instead (using `create_image_roi` function)." msgstr "Les ROI peuvent toujours être définies à l'aide d'indices (en utilisant la fonction `create_image_roi`)." msgid "Image ROI grid:" msgstr "Grille de ROI d'image:" msgid "New `generate_image_grid_roi` function: create a grid of ROIs from an image, with customizable parameters for grid size, spacing, and naming." msgstr "Nouvelle fonction `generate_image_grid_roi`: crée une grille de ROIs à partir d'une image, avec des paramètres personnalisables pour la taille de la grille, l'espacement et la nomination." msgid "This function allows for easy extraction of multiple ROIs from an image in a structured manner." msgstr "Cette fonction permet d'extraire facilement plusieurs ROIs d'une image de manière structurée." msgid "Parameters are handled via the `ROIGridParam` class, which provides a convenient way to specify grid properties:" msgstr "Les paramètres sont gérés via la classe `ROIGridParam`, qui fournit un moyen pratique de spécifier les propriétés de la grille:" msgid "`nx` / `ny`: Number of grid cells in the X/Y direction." msgstr "`nx` / `ny`: Nombre de cellules de grille dans la direction X/Y." msgid "`xsize` / `ysize`: Size of each grid cell in pixels." msgstr "`xsize` / `ysize`: Taille de chaque cellule de grille en pixels." msgid "`xtranslation` / `ytranslation`: Translation of the grid in pixels." msgstr "`xtranslation` / `ytranslation`: Translation de la grille en pixels." msgid "`xdirection` / `ydirection`: Direction of the grid (increasing/decreasing)." msgstr "`xdirection` / `ydirection`: Direction de la grille (croissante/décroissante)." msgid "New image processing features:" msgstr "Nouvelles fonctionnalités de traitement d'image:" msgid "New \"2D resampling\" feature:" msgstr "Nouvelle fonctionnalité de \"Rééchantillonnage 2D\" :" msgid "This feature allows to resample 2D images to a new coordinate grid using interpolation." msgstr "Cette fonctionnalité permet de rééchantillonner des images 2D vers une nouvelle grille de coordonnées à l'aide d'une interpolation." msgid "It supports two resampling modes: pixel size and output shape." msgstr "Elle prend en charge deux modes de rééchantillonnage : la taille des pixels et la forme de sortie." msgid "Multiple interpolation methods are available: linear, cubic, and nearest neighbor." msgstr "Plusieurs méthodes d'interpolation sont disponibles : linéaire, cubique et plus proche voisin." msgid "The `fill_value` parameter controls how out-of-bounds pixels are handled, with support for numeric values or NaN." msgstr "Le paramètre `fill_value` contrôle la manière dont les pixels hors limites sont gérés, avec prise en charge des valeurs numériques ou de NaN." msgid "Automatic data type conversion ensures proper NaN handling for integer images." msgstr "La conversion automatique du type de données garantit une gestion appropriée des NaN pour les images entières." msgid "It is implemented in the `sigima.proc.image.resampling` function with parameters defined in `Resampling2DParam`." msgstr "Elle est implémentée dans la fonction `sigima.proc.image.resampling` avec des paramètres définis dans `Resampling2DParam`." msgid "New \"Frequency domain Gaussian filter\" feature:" msgstr "Nouvelle fonctionnalité de \"Filtre fréquentiel gaussien\" :" msgid "This feature allows to filter an image in the frequency domain using a Gaussian filter." msgstr "Cette fonctionnalité permet de filtrer une image dans le domaine fréquentiel à l'aide d'un filtre gaussien." msgid "It is implemented in the `sigima.proc.image.frequency_domain_gaussian_filter` function." msgstr "Elle est implémentée dans la fonction `sigima.proc.image.frequency_domain_gaussian_filter`." msgid "New \"Erase\" feature:" msgstr "Nouvelle fonctionnalité \"Gommage\":" msgid "This feature allows to erase an area of the image using the mean value of the image." msgstr "Cette fonctionnalité permet de gommer une zone de l'image en utilisant la valeur moyenne de l'image." msgid "It is implemented in the `sigima.proc.image.erase` function." msgstr "Elle est implémentée dans la fonction `sigima.proc.image.erase`." msgid "The erased area is defined by a region of interest (ROI) parameter set." msgstr "La zone gommée est définie par un paramètre de région d'intérêt (ROI)." msgid "Example usage:" msgstr "Exemple d'utilisation:" msgid "By default, pixel binning changes the pixel size." msgstr "Par défaut, le regroupement de pixels modifie la taille des pixels." msgid "Improved centroid estimation:" msgstr "Amélioration de l'estimation du centroïde:" msgid "New `get_centroid_auto` method implements an adaptive strategy that chooses between the Fourier-based centroid and a more robust fallback (scikit-image), based on agreement with a projected profile-based reference." msgstr "La nouvelle méthode `get_centroid_auto` implémente une stratégie adaptative qui choisit entre le centroïde basé sur Fourier et un repli plus robuste (scikit-image), en fonction de l'accord avec une référence basée sur le profil projeté." msgid "Introduced `get_projected_profile_centroid` function for robust estimation via 1D projections (median or barycentric), offering high accuracy even with truncated or noisy images." msgstr "Introduction de la fonction `get_projected_profile_centroid` pour une estimation robuste via des projections 1D (médiane ou barycentrique), offrant une grande précision même avec des images tronquées ou bruyantes." msgid "These changes improve centroid accuracy and stability in edge cases (e.g. truncated disks or off-center spots), while preserving noise robustness." msgstr "Ces changements améliorent la précision et la stabilité du centroïde dans les cas extrêmes (par exemple, disques tronqués ou taches décentrées), tout en préservant la robustesse au bruit." msgid "See [DataLab issue #251](https://github.com/DataLab-Platform/DataLab/issues/251) for more details." msgstr "Voir l'[issue DataLab #251](https://github.com/DataLab-Platform/DataLab/issues/251) pour plus de détails." msgid "New signal processing features:" msgstr "Nouvelles fonctionnalités de traitement du signal:" msgid "New \"Brick wall filter\" feature:" msgstr "Nouvelle fonctionnalité de \"Filtre fréquentiel idéal\" :" msgid "This feature allows to filter a signal in the frequency domain using an ideal (\"brick wall\") filter." msgstr "Cette fonctionnalité permet de filtrer un signal dans le domaine fréquentiel à l'aide d'un filtre idéal." msgid "It is implemented in `sigima.proc.signal.frequency_filter`, along the other frequency domain filtering features (`Bessel`, `Butterworth`, etc.)." msgstr "Elle est implémentée dans la fonction `sigima.proc.signal.frequency_filter`, parmi les autres fonctionnalités de filtrage dans le domaine fréquentiel (`Bessel`, `Butterworth`, etc.)." msgid "Enhanced zero padding to support prepend and append. Change default strategy to next power of 2." msgstr "Amélioration du remplissage de zéros pour prendre en charge l'ajout au début et à la fin. Changement de la stratégie par défaut vers la prochaine puissance de 2." msgid "**Pulse analysis algorithms**: Comprehensive pulse feature extraction framework in `sigima.tools.signal.pulse` module:" msgstr "**Algorithmes d'analyse des impulsions**: Cadre complet d'extraction des caractéristiques des impulsions dans le module `sigima.tools.signal.pulse` :" msgid "**Core pulse analysis functions**: Complete set of algorithms for step and square pulse characterization:" msgstr "**Fonctions d'analyse des impulsions de base**: Ensemble complet d'algorithmes pour la caractérisation des impulsions en escalier et carrées :" msgid "`extract_pulse_features`: Main function for automated pulse feature extraction" msgstr "`extract_pulse_features`: Fonction principale pour l'extraction automatisée des caractéristiques des impulsions" msgid "`heuristically_recognize_shape`: Intelligent signal type detection (step, square, or other)" msgstr "`heuristically_recognize_shape`: Détection intelligente du type de signal (escalier, carré ou autre)" msgid "`detect_polarity`: Robust polarity detection using baseline analysis" msgstr "`detect_polarity`: Détection robuste de la polarité utilisant l'analyse de la ligne de base" msgid "**Advanced timing parameter extraction**: Precise measurement algorithms for:" msgstr "**Extraction avancée des paramètres temporels**: Algorithmes de mesure précis pour :" #, python-format msgid "Rise and fall time calculations with configurable start/stop ratios (e.g., 10%-90%)" msgstr "Calculs du temps de montée et de descente avec des rapports de début/fin configurables (par exemple, 10%-90%)" msgid "Timing parameters at specific fractions (x10, x50, x90, x100) of signal amplitude" msgstr "Paramètres temporels à des fractions spécifiques (x10, x50, x90, x100) de l'amplitude du signal" msgid "Full width at half maximum (FWHM) computation for square pulses" msgstr "Calcul de la largeur à mi-hauteur (FWHM) pour les impulsions carrées" msgid "Foot duration measurement for pulse characterization" msgstr "Mesure de la durée de l'impulsion pour la caractérisation des impulsions" msgid "**Baseline analysis capabilities**: Statistical methods for:" msgstr "**Capacités d'analyse de la ligne de base**: Méthodes statistiques pour :" msgid "Automatic baseline range detection from signal extremes" msgstr "Détection automatique de la plage de ligne de base à partir des extrêmes du signal" msgid "Robust baseline level estimation using mean values within ranges" msgstr "Estimation robuste du niveau de la ligne de base en utilisant les valeurs moyennes dans les plages" msgid "Start and end baseline characterization for differential analysis" msgstr "Caractérisation de la ligne de base de début et de fin pour l'analyse différentielle" msgid "**Signal validation and error handling**: Comprehensive input validation with:" msgstr "**Validation des signaux et gestion des erreurs**: Validation des entrées complète avec :" msgid "Data array consistency checks and NaN/infinity detection" msgstr "Vérifications de la cohérence des tableaux de données et détection des NaN/infinis" msgid "Signal length validation and range boundary verification" msgstr "Validation de la longueur du signal et vérification des limites de plage" msgid "Graceful error handling with descriptive exception messages" msgstr "Gestion des erreurs élégante avec des messages d'exception descriptifs" msgid "**PulseFeatures dataclass**: Structured result container with all extracted parameters:" msgstr "**Dataclass PulseFeatures**: Conteneur de résultats structuré avec tous les paramètres extraits :" msgid "Amplitude, polarity, and offset measurements" msgstr "Mesures d'amplitude, de polarité et de décalage" msgid "Timing parameters (rise_time, fall_time, fwhm, x10, x50, x90, x100)" msgstr "Paramètres temporels (rise_time, fall_time, fwhm, x10, x50, x90, x100)" msgid "Baseline ranges (xstartmin, xstartmax, xendmin, xendmax)" msgstr "Plages de ligne de base (xstartmin, xstartmax, xendmin, xendmax)" msgid "Signal shape classification and foot duration" msgstr "Classification de la forme du signal et durée de l'impulsion" msgid "Implementation leverages robust statistical methods and provides both high-level convenience functions and low-level building blocks for custom pulse analysis workflows." msgstr "L'implémentation s'appuie sur des méthodes statistiques robustes et fournit à la fois des fonctions de commodité de haut niveau et des blocs de construction de bas niveau pour des flux de travail d'analyse d'impulsions personnalisés." msgid "Comprehensive uncertainty propagation implementation:" msgstr "Mise en œuvre complète de la propagation des incertitudes :" msgid "Added mathematically correct uncertainty propagation to ~15 core signal processing functions." msgstr "Ajout de la propagation des incertitudes mathématiquement correcte à ~15 fonctions de traitement du signal de base." msgid "Enhanced `Wrap1to1Func` class to handle uncertainty propagation for mathematical functions (`sqrt`, `log10`, `exp`, `clip`, `absolute`, `real`, `imag`)." msgstr "Amélioration de la classe `Wrap1to1Func` pour gérer la propagation des incertitudes pour les fonctions mathématiques (`sqrt`, `log10`, `exp`, `clip`, `absolute`, `real`, `imag`)." msgid "Implemented uncertainty propagation for arithmetic operations (`product_constant`, `division_constant`)." msgstr "Mise en œuvre de la propagation des incertitudes pour les opérations arithmétiques (`product_constant`, `division_constant`)." msgid "Added uncertainty propagation for advanced processing functions (`power`, `normalize`, `derivative`, `integral`, `calibration`)." msgstr "Ajout de la propagation des incertitudes pour les fonctions de traitement avancées (`power`, `normalize`, `derivative`, `integral`, `calibration`)." msgid "All implementations use proper error propagation formulas with numerical stability handling (NaN/infinity protection)." msgstr "Toutes les implémentations utilisent des formules de propagation des erreurs appropriées avec une gestion de la stabilité numérique (protection contre les NaN/l'infini)." msgid "Optimized for memory efficiency by leveraging `dst_1_to_1` automatic uncertainty copying and in-place modifications." msgstr "Optimisé pour l'efficacité mémoire en tirant parti de la copie automatique des incertitudes `dst_1_to_1` et des modifications sur place." msgid "Maintains backward compatibility with existing signal processing workflows." msgstr "Maintient la compatibilité avec les flux de travail de traitement du signal existants." msgid "New 2D ramp image generator:" msgstr "Nouveau générateur d'image de rampe 2D:" msgid "This feature allows to generate a 2D ramp image: z = a(x − x₀) + b(y − y₀) + c" msgstr "Cette fonctionnalité permet de générer une image de rampe 2D: z = a(x − x₀) + b(y − y₀) + c" msgid "It is implemented in the `sigima.objects.Ramp2DParam` parameter class." msgstr "Elle est implémentée dans la classe de paramètres `sigima.objects.Ramp2DParam`." msgid "New signal generators: linear chirp, logistic function, Planck function." msgstr "Nouveaux générateurs de signaux: chirp linéaire, fonction logistique, fonction de Planck." msgid "New image \"Extent\" computed parameters:" msgstr "Nouveaux paramètres calculés d'\"Étendue\" de l'image :" msgid "Added computed parameters for image extent: `xmin`, `xmax`, `ymin`, and `ymax`." msgstr "Ajout de paramètres calculés pour l'étendue de l'image : `xmin`, `xmax`, `ymin` et `ymax`." msgid "These parameters are automatically calculated based on the image origin, pixel spacing, and dimensions." msgstr "Ces paramètres sont automatiquement calculés en fonction de l'origine de l'image, de l'espacement des pixels et des dimensions." msgid "They provide the physical coordinate boundaries of the image for enhanced spatial analysis." msgstr "Ils fournissent les limites des coordonnées physiques de l'image pour une analyse spatiale améliorée." msgid "New I/O features:" msgstr "Nouvelles fonctionnalités d'E/S:" msgid "Added HDF5 format for signal and image objects (extensions `.h5sig` and `.h5ima`) that may be opened with any HDF5 viewer." msgstr "Ajout du format HDF5 pour les objets de signal et d'image (extensions `.h5sig` et `.h5ima`) qui peuvent être ouverts avec n'importe quel visualiseur HDF5." msgid "Added support for MCA (Multi-Channel Analyzer) spectrum file format:" msgstr "Ajout de la prise en charge du format de fichier de spectre MCA (Analyseur Multi-Canaux) :" msgid "Reading MCA files (`.mca` extension) commonly used in spectroscopy and radiation detection" msgstr "Lecture des fichiers MCA (extension `.mca`) couramment utilisés en spectroscopie et en détection de radiation" msgid "Automatically extracts spectrum data and calibration information" msgstr "Extraction automatique des données de spectre et des informations de calibration" msgid "Supports energy calibration with interpolation for accurate X-axis values" msgstr "Prise en charge de la calibration d'énergie avec interpolation pour des valeurs précises de l'axe X" msgid "Parses metadata from multiple sections (PMCA SPECTRUM, DPP STATUS, CALIBRATION)" msgstr "Analyse des métadonnées à partir de plusieurs sections (PMCA SPECTRUM, DPP STATUS, CALIBRATION)" msgid "Handles various encoding formats (UTF-8, Latin-1, CP1252) for maximum compatibility" msgstr "Prise en charge de divers formats d'encodage (UTF-8, Latin-1, CP1252) pour une compatibilité maximale" msgid "Added support for FT-Lab signal and image format." msgstr "Ajout de la prise en charge du format de signal et d'image FT-Lab." msgid "Added functions to read and write metadata and ROIs in JSON format:" msgstr "Ajout de fonctions pour lire et écrire des métadonnées et des ROIs au format JSON:" msgid "`sigima.io.read_metadata` and `sigima.io.write_metadata` for metadata." msgstr "`sigima.io.read_metadata` et `sigima.io.write_metadata` pour les métadonnées." msgid "`sigima.io.read_roi` and `sigima.io.write_roi` for ROIs." msgstr "`sigima.io.read_roi` et `sigima.io.write_roi` pour les ROIs." msgid "Added convenience I/O functions `write_signals` and `write_images` with `SaveToDirectoryParam` support:" msgstr "Ajout de fonctions d'E/S de commodité `write_signals` et `write_images` avec prise en charge de `SaveToDirectoryParam`:" msgid "These functions enable batch saving of multiple signal or image objects to a directory with configurable naming patterns." msgstr "Ces fonctions permettent d'enregistrer par lots plusieurs objets de signal ou d'image dans un répertoire avec des modèles de nommage configurables." msgid "`SaveToDirectoryParam` provides control over file basenames (with Python format string support), extensions, directory paths, and overwrite behavior." msgstr "`SaveToDirectoryParam` fournit un contrôle sur les noms de fichiers de base (avec prise en charge des chaînes de format Python), des extensions, des chemins de répertoire et du comportement d'écrasement." msgid "Automatic filename conflict resolution ensures unique filenames when duplicates would occur." msgstr "La résolution automatique des conflits de noms de fichiers garantit des noms de fichiers uniques en cas de doublons." msgid "Enhanced workflow efficiency for processing and saving multiple objects in batch operations." msgstr "Efficacité améliorée du flux de travail pour le traitement et l'enregistrement de plusieurs objets dans des opérations par lots." msgid "✨ Core architecture update: scalar result types" msgstr "✨ Mise à jour de l'architecture de base: types de résultats scalaires" msgid "Introduced two new immutable result types: `TableResult` and `GeometryResult`, replacing the legacy `ResultProperties` and `ResultShape` objects." msgstr "Introduction de deux nouveaux types de résultats immuables: `TableResult` et `GeometryResult`, remplaçant les anciens objets `ResultProperties` et `ResultShape`." msgid "These new result types are computation-oriented and free of application-specific logic (e.g., Qt, metadata), enabling better separation of concerns and future reuse." msgstr "Ces nouveaux types de résultats sont orientés vers le calcul et dépourvus de logique spécifique à l'application (par exemple, Qt, métadonnées), permettant une meilleure séparation des préoccupations et une réutilisation future." msgid "Added a `TableResultBuilder` utility to incrementally define tabular computations (e.g., statistics on signals or images) and generate a `TableResult` object." msgstr "Ajout d'un utilitaire `TableResultBuilder` pour définir progressivement des calculs tabulaires (par exemple, des statistiques sur les signaux ou les images) et générer un objet `TableResult`." msgid "All metadata-related behaviors of former result types have been migrated to the DataLab application layer." msgstr "Tous les comportements liés aux métadonnées des anciens types de résultats ont été migrés vers la couche d'application DataLab." msgid "Removed obsolete or tightly coupled features such as `from_metadata_entry()` and `transform_shapes()` from the Sigima core." msgstr "Suppression de fonctionnalités obsolètes ou étroitement couplées telles que `from_metadata_entry()` et `transform_shapes()` du cœur de Sigima." msgid "This refactoring greatly improves modularity, testability, and the clarity of the scalar computation API." msgstr "Cette refonte améliore considérablement la modularité, la testabilité et la clarté de l'API de calcul scalaire." msgid "Fix how data is managed in signal objects (`SignalObj`):" msgstr "Correction de la gestion des données dans les objets de signal (`SignalObj`):" msgid "Signal data is stored internally as a 2D array with shape `(2, n)`, where the first row is the x data and the second row is the y data: that is the `xydata` attribute." msgstr "Les données du signal sont stockées en interne sous la forme d'un tableau 2D de forme `(2, n)`, où la première ligne est les données x et la deuxième ligne est les données y : c'est l'attribut `xydata`." msgid "Because of this, when storing complex Y data, the data type is propagated to the x data, which is not always desired." msgstr "En raison de cela, lors du stockage de données Y complexes, le type de données est propagé aux données x, ce qui n'est pas toujours souhaité." msgid "As a workaround, the `x` property now returns the real part of the x data." msgstr "En guise de solution de contournement, la propriété `x` renvoie désormais la partie réelle des données x." msgid "Furthermore, the `get_data` method now returns a tuple of numpy arrays instead of a single array, allowing to access both x and y data separately, keeping the original data type." msgstr "De plus, la méthode `get_data` renvoie désormais un tuple de tableaux numpy au lieu d'un seul tableau, permettant d'accéder séparément aux données x et y, tout en conservant le type de données d'origine." msgid "Fix ROI conversion between physical and indices coordinates:" msgstr "Correction de la conversion des coordonnées physiques et des indices de ROI:" msgid "The conversion between physical coordinates and indices has been corrected (half pixel error was removed)." msgstr "La conversion entre les coordonnées physiques et les indices a été corrigée (l'erreur de demi-pixel a été supprimée)." msgid "The `indices_to_physical` and `physical_to_indices` methods now raise a `ValueError` if the input does not contain an even number of elements (x, y pairs)." msgstr "La méthode `indices_to_physical` et `physical_to_indices` lèvent désormais une `ValueError` si l'entrée ne contient pas un nombre pair d'éléments (paires x, y)." msgid "🔒 Security fixes:" msgstr "🔒 Corrections de sécurité:" msgid "**Dependency vulnerability fix**: Fixed CVE-2023-4863 vulnerability in opencv-python-headless" msgstr "**Correction de vulnérabilité de dépendance**: Correction de la vulnérabilité CVE-2023-4863 dans opencv-python-headless" msgid "Updated minimum requirement from 4.5.4.60 to 4.8.1.78" msgstr "Mise à jour de l'exigence minimale de 4.5.4.60 à 4.8.1.78" msgid "Addresses libwebp binaries vulnerability in bundled OpenCV wheels" msgstr "Correction de la vulnérabilité des binaires libwebp dans les paquets Wheel OpenCV" msgid "See [DataLab security advisory](https://github.com/DataLab-Platform/DataLab/security/dependabot/1) for details" msgstr "Voir l'[avis de sécurité DataLab](https://github.com/DataLab-Platform/DataLab/security/dependabot/1) pour plus de détails." Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/release_notes/release_1.01.po000066400000000000000000000161571514013333200243770ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2025, DataLab Platform Developers # This file is distributed under the same license as the Sigima package. # FIRST AUTHOR , 2025. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: Sigima \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid "Version 1.1" msgstr "Version 1.1" msgid "Sigima Version 1.1.1 (2026-02-02)" msgstr "Sigima Version 1.1.1 (2026-02-02)" msgid "🛠️ Bug Fixes since version 1.1.0" msgstr "🛠️ Corrections de bugs depuis la version 1.1.0" msgid "" "**Stub server**: Added missing Web API control methods to " "`DataLabStubServer` for testing DataLab's REST API integration" msgstr "" "**Serveur factice** : Ajout des méthodes de contrôle de l'API Web manquantes à " "`DataLabStubServer` pour tester l'intégration de l'API REST de DataLab" msgid "Added `start_webapi_server()` stub (returns dummy URL and token)" msgstr "" "Ajout du stub `start_webapi_server()` (retourne une URL et un jeton " "factices)" msgid "Added `stop_webapi_server()` stub" msgstr "Ajout du stub `stop_webapi_server()`" msgid "Added `get_webapi_status()` stub (returns server status dictionary)" msgstr "" "Ajout du stub `get_webapi_status()` (retourne un dictionnaire d'état du " "serveur)" msgid "🔧 Other changes" msgstr "🔧 Autres changements" msgid "Updated development status classifier to \"Production/Stable\"" msgstr "" "Mise à jour du classificateur d'état de développement vers " "\"Production/Stable\"" msgid "" "Added \"Try it Online\" section with " "[notebook.link](https://notebook.link/) integration in documentation" msgstr "" "Ajout de la section \"Essayez en ligne\" avec intégration de " "[notebook.link](https://notebook.link/) dans la documentation" msgid "Sigima Version 1.1.0 (2026-01-31)" msgstr "Sigima Version 1.1.0 (2026-01-31)" msgid "✨ New features and enhancements:" msgstr "✨ Nouvelles fonctionnalités et améliorations:" msgid "" "**Stub server**: Added missing methods to `DataLabStubServer` to support " "new DataLab features" msgstr "" "**Serveur factice** : Ajout de méthodes manquantes à `DataLabStubServer` " "pour prendre en charge les nouvelles fonctionnalités de DataLab" msgid "Added `remove_object()` method (removes an object from DataLab)" msgstr "Ajout de la méthode `remove_object()` (supprime un objet de DataLab)" msgid "" "Added `call_method()` method (simulates calling a method on DataLab's " "main interface or panels)" msgstr "" "Ajout de la méthode `call_method()` (simule l'appel d'une méthode sur " "l'interface principale ou les panneaux de DataLab)" msgid "" "**Test infrastructure**: Refactored visualization code in test suite for " "better maintainability" msgstr "" "**Infrastructure de test** : Refactorisation du code de visualisation " "dans la suite de tests pour une meilleure maintenabilité" msgid "Centralized PlotPy visualization utilities in `sigima.viz` module" msgstr "" "Centralisation des utilitaires de visualisation PlotPy dans le module " "`sigima.viz`" msgid "" "Added standardized helper functions: `create_curve()`, `create_image()`, " "`create_circle()`, `create_segment()`, `create_cursor()`, " "`create_marker()`, and `create_contour_shapes()`" msgstr "" "Ajout de fonctions d'aide standardisées : `create_curve()`, " "`create_image()`, `create_circle()`, `create_segment()`, " "`create_cursor()`, `create_marker()` et `create_contour_shapes()`" msgid "" "Updated all interactive test functions to use the new unified API instead" " of direct PlotPy builder calls" msgstr "" "Mise à jour de toutes les fonctions de test interactives pour utiliser la" " nouvelle API unifiée au lieu des appels directs au constructeur PlotPy" msgid "Improved code consistency across signal and image test modules" msgstr "" "Amélioration de la cohérence du code entre les modules de test de signaux" " et d'images" msgid "" "**Visualization backend flexibility**: Added support for Matplotlib as an" " alternative to PlotPy for test visualizations" msgstr "" "**Flexibilité du backend de visualisation** : Ajout de la prise en charge" " de Matplotlib comme alternative à PlotPy pour les visualisations de test" msgid "" "New configuration option `viz_backend` to select visualization library " "(\"auto\", \"plotpy\", or \"matplotlib\")" msgstr "" "Nouvelle option de configuration `viz_backend` pour sélectionner la " "bibliothèque de visualisation (\"auto\", \"plotpy\" ou \"matplotlib\")" msgid "Environment variable `SIGIMA_VIZ_BACKEND` can override configuration" msgstr "" "La variable d'environnement `SIGIMA_VIZ_BACKEND` peut remplacer la " "configuration" msgid "Automatic fallback from PlotPy to Matplotlib when PlotPy is not available" msgstr "" "Basculement automatique de PlotPy à Matplotlib lorsque PlotPy n'est pas " "disponible" msgid "" "Backend information exposed via `sigima.viz.BACKEND_NAME` and " "`BACKEND_SOURCE`" msgstr "" "Informations sur le backend exposées via `sigima.viz.BACKEND_NAME` et " "`BACKEND_SOURCE`" msgid "" "Matplotlib backend provides stubs for unsupported functions (raises " "`NotImplementedError`)" msgstr "" "Le backend Matplotlib fournit des stubs pour les fonctions non prises en " "charge (lève `NotImplementedError`)" msgid "Unit test ensures API compatibility between backends" msgstr "Test unitaire garantissant la compatibilité de l'API entre les backends" msgid "" "**Jupyter notebook HTML representation**: Added rich HTML display for " "Sigima objects in Jupyter notebooks" msgstr "" "**Représentation HTML pour les notebooks Jupyter** : Ajout d'un affichage" " HTML enrichi pour les objets Sigima dans les notebooks Jupyter" msgid "" "`SignalObj` displays shape, dtype, X/Y ranges, axis labels, and title in " "a formatted table" msgstr "" "`SignalObj` affiche la forme, le dtype, les plages X/Y, les labels des " "axes et le titre dans un tableau formaté" msgid "" "`ImageObj` displays shape, dtype, value range, origin, pixel spacing, " "extent, axis labels, and title" msgstr "" "`ImageObj` affiche la forme, le dtype, la plage de valeurs, l'origine, " "l'espacement des pixels, l'étendue, les labels des axes et le titre" msgid "" "ROI objects (`BaseSingleROI`, `BaseROI`) display their geometric " "properties" msgstr "" "Les objets ROI (`BaseSingleROI`, `BaseROI`) affichent leurs propriétés " "géométriques" msgid "`BaseCoordinates` and derived classes display point coordinates" msgstr "" "`BaseCoordinates` et les classes dérivées affichent les coordonnées des " "points" msgid "" "`TableResult` and `GeometryResult` display result data with source object" " information" msgstr "" "`TableResult` et `GeometryResult` affichent les données de résultat avec " "les informations de l'objet source" msgid "" "Centralized CSS styling in `HTML_TABLE_CSS` constant for consistent " "appearance" msgstr "" "Centralisation du style CSS dans la constante `HTML_TABLE_CSS` pour une " "apparence cohérente" #~ msgid "Sigima Version 1.1.0" #~ msgstr "" Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/remote_example.po000066400000000000000000000026041514013333200224660ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2025, DataLab Platform Developers # This file is distributed under the same license as the Sigima package. # FIRST AUTHOR , 2025. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: Sigima \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid "DataLab remote control example" msgstr "Exemple de contrôle à distance de DataLab" msgid "Example of remote control of DataLab current session, from a simple notebook, using the `SimpleRemoteProxy` class provided in the `sigima.client` module." msgstr "Exemple de contrôle à distance de la session actuelle de DataLab, à partir d'un simple notebook, en utilisant la classe `SimpleRemoteProxy` fournie dans le module `sigima.client`." msgid "The only requirement is to install the *Sigima* package (using `pip install sigima`, for example)." msgstr "La seule exigence est d'installer le paquet *Sigima* (en utilisant `pip install sigima`, par exemple)." msgid "Connecting to DataLab current session:" msgstr "Connexion à la session actuelle de DataLab :" msgid "Executing commands in DataLab:" msgstr "Exécution des commandes dans DataLab :" Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/requirements.po000066400000000000000000000144421514013333200222060ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2025, DataLab Platform Developers # This file is distributed under the same license as the Sigima package. # FIRST AUTHOR , 2025. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: Sigima \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid "The `sigima` package requires the following Python modules:" msgstr "Le paquet `sigima` nécessite les modules Python suivants :" msgid "Name" msgstr "Nom" msgid "Version" msgstr "Version" msgid "Summary" msgstr "Résumé" msgid "Python" msgstr "Python" msgid ">=3.9, <4" msgstr "" msgid "Python programming language" msgstr "Langage de programmation Python" msgid "guidata" msgstr "guidata" msgid ">= 3.13" msgstr "" msgid "Automatic GUI generation for easy dataset editing and display" msgstr "Génération automatique d'interface graphique pour une édition et un affichage faciles des ensembles de données" msgid "NumPy" msgstr "" msgid ">= 1.22, < 2.5" msgstr "" msgid "Fundamental package for array computing in Python" msgstr "Paquet fondamental pour le calcul sur tableaux en Python" msgid "SciPy" msgstr "" msgid ">= 1.10.1, < 1.17" msgstr "" msgid "Fundamental algorithms for scientific computing in Python" msgstr "Algorithmes fondamentaux pour le calcul scientifique en Python" msgid "scikit-image" msgstr "" msgid ">= 0.19.2, < 0.27" msgstr "" msgid "Image processing in Python" msgstr "Traitement d'image en Python" msgid "pandas" msgstr "" msgid ">= 1.4, < 3.0" msgstr "" msgid "Powerful data structures for data analysis, time series, and statistics" msgstr "" msgid "PyWavelets" msgstr "" msgid ">= 1.2, < 2.0" msgstr "" msgid "PyWavelets, wavelet transform module" msgstr "PyWavelets, module de transformation en ondelettes" msgid "packaging" msgstr "" msgid ">= 21.3" msgstr "" msgid "Core utilities for Python packages" msgstr "Utilitaires de base pour les paquets Python" msgid "typing-extensions" msgstr "" msgid ">= 4.0" msgstr "" msgid "Backported and Experimental Type Hints for Python 3.9+" msgstr "Extensions de typage rétroportées et expérimentales pour Python 3.9+" msgid "makefun" msgstr "" msgid ">= 1.13.1" msgstr "" msgid "Small library to dynamically create python functions." msgstr "" msgid "Optional modules for GUI support (Qt):" msgstr "" msgid "qtpy" msgstr "" msgid "Provides an abstraction layer on top of the various Qt bindings (PyQt5/6 and PySide2/6)." msgstr "Fournit une couche d'abstraction au-dessus des différentes liaisons Qt (PyQt5/6 et PySide2/6)." msgid "PyQt5" msgstr "" msgid "Python bindings for the Qt cross platform application toolkit" msgstr "Liaisons Python pour l'outil de développement d'applications multiplateforme Qt" msgid "plotpy" msgstr "" msgid "Curve and image plotting tools for Python/Qt applications" msgstr "Outils de traçage de courbes et d'images pour les applications Python/Qt" msgid "Optional modules for development:" msgstr "Modules facultatifs pour le développement :" msgid "build" msgstr "" msgid "A simple, correct Python build frontend" msgstr "Un frontend de construction Python simple et correct" msgid "babel" msgstr "" msgid "Internationalization utilities" msgstr "Utilitaires d'internationalisation" msgid "ruff" msgstr "" msgid "An extremely fast Python linter and code formatter, written in Rust." msgstr "Un linter Python extrêmement rapide et un formateur de code, écrit en Rust." msgid "pylint" msgstr "" msgid "python code static checker" msgstr "Analyseur statique de code Python" msgid "Coverage" msgstr "" msgid "Code coverage measurement for Python" msgstr "Mesure de la couverture du code pour Python" msgid "pre-commit" msgstr "" msgid "A framework for managing and maintaining multi-language pre-commit hooks." msgstr "Un framework pour gérer et maintenir des hooks de pré-commit multi-langages." msgid "Optional modules for building the documentation:" msgstr "Modules facultatifs pour la construction de la documentation :" msgid "sphinx" msgstr "" msgid "Python documentation generator" msgstr "Générateur de documentation Python" msgid "sphinx-gallery" msgstr "" msgid "A Sphinx extension that builds an HTML gallery of examples from any set of Python scripts." msgstr "Une extension Sphinx qui crée une galerie HTML d'exemples à partir de n'importe quel ensemble de scripts Python." msgid "sphinx_intl" msgstr "" msgid "Sphinx utility that make it easy to translate and to apply translation." msgstr "Utilitaire Sphinx qui facilite la traduction et l'application de la traduction." msgid "myst_parser" msgstr "" msgid "An extended [CommonMark](https://spec.commonmark.org/) compliant parser," msgstr "Un analyseur conforme à [CommonMark](https://spec.commonmark.org/) étendu," msgid "myst-nb" msgstr "" msgid "A Jupyter Notebook Sphinx reader built on top of the MyST markdown parser." msgstr "" msgid "sphinx_design" msgstr "" msgid "A sphinx extension for designing beautiful, view size responsive web components." msgstr "Une extension Sphinx pour concevoir de beaux composants web réactifs à la taille de la vue." msgid "sphinx-copybutton" msgstr "" msgid "Add a copy button to each of your code cells." msgstr "Ajoute un bouton de copie à chacune de vos cellules de code." msgid "pydata-sphinx-theme" msgstr "" msgid "Bootstrap-based Sphinx theme from the PyData community" msgstr "Thème Sphinx basé sur Bootstrap de la communauté PyData" msgid "matplotlib" msgstr "" #, fuzzy msgid "Python plotting package" msgstr "Langage de programmation Python" msgid "opencv-python-headless" msgstr "" msgid ">= 4.8.1.78" msgstr "" msgid "Wrapper package for OpenCV python bindings." msgstr "Bibliothèque d'interfaces Python pour OpenCV." msgid "Optional modules for running test suite:" msgstr "Modules facultatifs pour exécuter la suite de tests :" msgid "pytest" msgstr "" msgid "pytest: simple powerful testing with Python" msgstr "pytest : tests simples et puissants avec Python" msgid "pytest-xvfb" msgstr "" msgid "A pytest plugin to run Xvfb (or Xephyr/Xvnc) for tests." msgstr "Un plugin pytest pour exécuter Xvfb (ou Xephyr/Xvnc) pour les tests." Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/simple_example.po000066400000000000000000000025531514013333200224670ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2025, DataLab Platform Developers # This file is distributed under the same license as the Sigima package. # FIRST AUTHOR , 2025. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: Sigima \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid "Prepare data and compute processing feature" msgstr "Préparer les données et calculer la fonctionnalité de traitement" msgid "Demonstration of using Regions of Interest (ROIs) in image processing with **Sigima**" msgstr "Démonstration de l'utilisation des régions d'intérêt (ROI) dans le traitement d'images avec **Sigima**" msgid "Display results" msgstr "Afficher les résultats" msgid "ℹ️ The following code use `viz` Matplotlib backend which has been introduced in Sigima V1.1" msgstr "ℹ️ Le code suivant utilise le backend Matplotlib de `viz` qui a été introduit dans Sigima V1.1" #, fuzzy msgid "Sigima V1.0 uses an internal version of `viz` for image display based on PlotPy (`tests.vistools`)." msgstr "Sigima V1.0 utilise une version interne de `viz` pour l'affichage des images basée sur PlotPy" Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/user_guide/000077500000000000000000000000001514013333200212515ustar00rootroot00000000000000Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/user_guide/features.po000066400000000000000000001024271514013333200234350ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2025, DataLab Platform Developers # This file is distributed under the same license as the Sigima package. # FIRST AUTHOR , 2025. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: Sigima \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid "Features" msgstr "Fonctionnalités" msgid "Sigima provides a comprehensive suite of signal and image processing computational features organized into logical categories. This page provides an organized overview of all available computation functions with direct links to their API documentation." msgstr "Sigima offre une suite complète de fonctionnalités de traitement des signaux et des images, organisées en catégories logiques. Cette page fournit un aperçu organisé de toutes les fonctions de calcul disponibles avec des liens directs vers leur documentation API." msgid "All computation functions are available in the :mod:`sigima.proc` module. The :mod:`sigima.tools` modules provide lower-level utility functions used internally by the proc functions." msgstr "Toutes les fonctions de calcul sont disponibles dans le module :mod:`sigima.proc`. Les modules :mod:`sigima.tools` fournissent des fonctions utilitaires de bas niveau utilisées en interne par les fonctions proc." msgid "Common Operations" msgstr "Opérations courantes" msgid "These operations are available for both signals and images with similar functionality." msgstr "Ces opérations sont disponibles à la fois pour les signaux et les images avec une fonctionnalité similaire." msgid "Arithmetic Operations" msgstr "Opérations arithmétiques" msgid "Signal Functions" msgstr "Fonctions de signal" msgid "Image Functions" msgstr "Fonctions d'image" msgid "Description" msgstr "Description" msgid ":func:`addition `" msgstr "" msgid ":func:`addition `" msgstr "" msgid "Add two signals/images" msgstr "Ajouter deux signaux/images" msgid ":func:`difference `" msgstr "" msgid ":func:`difference `" msgstr "" msgid "Subtract one signal/image from another" msgstr "Soustraire un signal/image d'un autre" msgid ":func:`product `" msgstr "" msgid ":func:`product `" msgstr "" msgid "Multiply two signals/images" msgstr "Multiplier deux signaux/images" msgid ":func:`division `" msgstr "" msgid ":func:`division `" msgstr "" msgid "Divide one signal/image by another" msgstr "Diviser un signal/image par un autre" msgid ":func:`average `" msgstr "" msgid ":func:`average `" msgstr "" msgid "Compute average of multiple signals/images" msgstr "Calculer la moyenne de plusieurs signaux/images" msgid ":func:`standard_deviation `" msgstr "" msgid ":func:`standard_deviation `" msgstr "" msgid "Compute standard deviation of multiple signals/images" msgstr "Calculer l'écart-type de plusieurs signaux/images" msgid ":func:`quadratic_difference `" msgstr "" msgid ":func:`quadratic_difference `" msgstr "" msgid "Compute quadratic difference between signals/images" msgstr "Calculer la différence quadratique entre signaux/images" msgid ":func:`arithmetic `" msgstr "" msgid ":func:`arithmetic `" msgstr "" msgid "Generic arithmetic operations with parameters" msgstr "Opérations arithmétiques génériques avec paramètres" msgid "Constant Operations" msgstr "Opérations avec constantes" msgid ":func:`addition_constant `" msgstr "" msgid ":func:`addition_constant `" msgstr "" msgid "Add a constant value to signal/image" msgstr "Ajouter une constante au signal/image" msgid ":func:`difference_constant `" msgstr "" msgid ":func:`difference_constant `" msgstr "" msgid "Subtract a constant from signal/image" msgstr "Soustraire une constante du signal/image" msgid ":func:`product_constant `" msgstr "" msgid ":func:`product_constant `" msgstr "" msgid "Multiply signal/image by a constant" msgstr "Multiplier le signal/image par une constante" msgid ":func:`division_constant `" msgstr "" msgid ":func:`division_constant `" msgstr "" msgid "Divide signal/image by a constant" msgstr "Diviser le signal/image par une constante" msgid "Mathematical Operations" msgstr "Opérations mathématiques" msgid ":func:`absolute `" msgstr "" msgid ":func:`absolute `" msgstr "" msgid "Compute absolute value" msgstr "Calculer la valeur absolue" msgid ":func:`exp `" msgstr "" msgid ":func:`exp `" msgstr "" msgid "Exponential function" msgstr "Fonction exponentielle" msgid ":func:`log10 `" msgstr "" msgid ":func:`log10 `" msgstr "" msgid "Base-10 logarithm" msgstr "Logarithme en base 10" msgid ":func:`inverse `" msgstr "" msgid ":func:`inverse `" msgstr "" msgid "Compute reciprocal" msgstr "Calculer l'inverse" msgid ":func:`real `" msgstr "" msgid ":func:`real `" msgstr "" msgid "Extract real part of complex data" msgstr "Extraire la partie réelle des données complexes" msgid ":func:`imag `" msgstr "" msgid ":func:`imag `" msgstr "" msgid "Extract imaginary part of complex data" msgstr "Extraire la partie imaginaire des données complexes" msgid ":func:`phase `" msgstr "" msgid ":func:`phase `" msgstr "" msgid "Extract phase of complex data" msgstr "Extraire la phase des données complexes" msgid ":func:`astype `" msgstr "" msgid ":func:`astype `" msgstr "" msgid "Convert data type" msgstr "Convertir le type de données" msgid ":func:`transpose `" msgstr "" msgid ":func:`transpose `" msgstr "" msgid "Transpose coordinates/axes" msgstr "Transposer les coordonnées/axes" msgid "N/A" msgstr "N/A" msgid ":func:`log10_z_plus_n `" msgstr "" msgid "Log10 with offset for zero handling" msgstr "Log10 avec décalage pour la gestion des zéros" msgid "Signal-Specific Mathematical Operations" msgstr "Opérations mathématiques spécifiques aux signaux" msgid "Function" msgstr "Fonction" msgid ":func:`sqrt `" msgstr "" msgid "Square root" msgstr "Racine carrée" msgid ":func:`power `" msgstr "" msgid "Raise to power" msgstr "Élever à une puissance" msgid ":func:`to_cartesian `" msgstr "" msgid "Convert to Cartesian coordinates" msgstr "Convertir en coordonnées cartésiennes" msgid ":func:`to_polar `" msgstr "" msgid "Convert to polar coordinates" msgstr "Convertir en coordonnées polaires" msgid "Complex Number Operations" msgstr "Opérations sur les nombres complexes" msgid ":func:`complex_from_real_imag `" msgstr "" msgid ":func:`complex_from_real_imag `" msgstr "" msgid "Create complex data from real and imaginary parts" msgstr "Créer des données complexes à partir des parties réelle et imaginaire" msgid ":func:`complex_from_magnitude_phase `" msgstr "" msgid ":func:`complex_from_magnitude_phase `" msgstr "" msgid "Create complex data from magnitude and phase" msgstr "Créer des données complexes à partir du module et de la phase" msgid "Fourier Analysis" msgstr "Analyse de Fourier" msgid ":func:`fft `" msgstr "" msgid ":func:`fft `" msgstr "" msgid "Fast Fourier Transform (1D/2D)" msgstr "Transformée de Fourier rapide (1D/2D)" msgid ":func:`ifft `" msgstr "" msgid ":func:`ifft `" msgstr "" msgid "Inverse Fast Fourier Transform (1D/2D)" msgstr "Transformée de Fourier rapide inverse (1D/2D)" msgid ":func:`magnitude_spectrum `" msgstr "" msgid ":func:`magnitude_spectrum `" msgstr "" msgid "Magnitude spectrum" msgstr "Spectre de magnitude" msgid ":func:`phase_spectrum `" msgstr "" msgid ":func:`phase_spectrum `" msgstr "" msgid "Phase spectrum" msgstr "Spectre de phase" msgid ":func:`psd `" msgstr "" msgid ":func:`psd `" msgstr "" msgid "Power spectral density" msgstr "Densité spectrale de puissance" msgid "Convolution Operations" msgstr "Opérations de convolution" msgid ":func:`convolution `" msgstr "" msgid ":func:`convolution `" msgstr "" msgid "Convolution operation" msgstr "Opération de convolution" msgid ":func:`deconvolution `" msgstr "" msgid ":func:`deconvolution `" msgstr "" msgid "Deconvolution operation" msgstr "Opération de déconvolution" msgid "Filtering" msgstr "Filtrage" msgid ":func:`gaussian_filter `" msgstr "" msgid ":func:`gaussian_filter `" msgstr "" msgid "Gaussian smoothing filter" msgstr "Filtre de lissage gaussien" msgid ":func:`moving_average `" msgstr "" msgid ":func:`moving_average `" msgstr "" msgid "Moving average filter" msgstr "Filtre moyenne mobile" msgid ":func:`moving_median `" msgstr "" msgid ":func:`moving_median `" msgstr "" msgid "Moving median filter" msgstr "Filtre médian mobile" msgid ":func:`wiener `" msgstr "" msgid ":func:`wiener `" msgstr "" msgid "Wiener filter" msgstr "Filtre de Wiener" msgid "Noise Addition" msgstr "Ajout de bruit" msgid ":func:`add_gaussian_noise `" msgstr "" msgid ":func:`add_gaussian_noise `" msgstr "" msgid "Add Gaussian noise for testing" msgstr "Ajouter du bruit gaussien pour les tests" msgid ":func:`add_poisson_noise `" msgstr "" msgid ":func:`add_poisson_noise `" msgstr "" msgid "Add Poisson noise for testing" msgstr "Ajouter du bruit de Poisson pour les tests" msgid ":func:`add_uniform_noise `" msgstr "" msgid ":func:`add_uniform_noise `" msgstr "" msgid "Add uniform noise for testing" msgstr "Ajouter du bruit uniforme pour les tests" msgid "Signal Conditioning" msgstr "Conditionnement du signal" msgid ":func:`normalize `" msgstr "" msgid ":func:`normalize `" msgstr "" msgid "Normalize amplitude/intensity values" msgstr "Normaliser les valeurs d'amplitude/intensité" msgid ":func:`clip `" msgstr "" msgid ":func:`clip `" msgstr "" msgid "Clip values to specified range" msgstr "Écrêter les valeurs à une plage spécifiée" msgid ":func:`offset_correction `" msgstr "" msgid ":func:`offset_correction `" msgstr "" msgid "Remove DC offset/background" msgstr "Supprimer le décalage DC/fond continu" msgid "Region of Interest (ROI)" msgstr "Région d'intérêt (ROI)" msgid ":func:`extract_roi `" msgstr "" msgid ":func:`extract_roi `" msgstr "" msgid "Extract single ROI from data" msgstr "Extraire une seule ROI des données" msgid ":func:`extract_rois `" msgstr "" msgid ":func:`extract_rois `" msgstr "" msgid "Extract multiple ROIs from data" msgstr "Extraire plusieurs ROI des données" msgid "Calibration" msgstr "Étalonnage" msgid ":func:`calibration `" msgstr "" msgid ":func:`calibration `" msgstr "" msgid "Apply coordinate system calibration" msgstr "Appliquer l'étalonnage du système de coordonnées" msgid "Signal Processing" msgstr "Traitement du signal" msgid "Array Operations" msgstr "Opérations sur les tableaux" msgid ":func:`signals_to_image `" msgstr "" msgid "Convert signals to image representation" msgstr "Convertir les signaux en représentation image" msgid "Frequency Filtering" msgstr "Filtrage fréquentiel" msgid ":func:`lowpass `" msgstr "" msgid "Low-pass filter" msgstr "Filtre passe-bas" msgid ":func:`highpass `" msgstr "" msgid "High-pass filter" msgstr "Filtre passe-haut" msgid ":func:`bandpass `" msgstr "" msgid "Band-pass filter" msgstr "Filtre passe-bande" msgid ":func:`bandstop `" msgstr "" msgid "Band-stop filter" msgstr "Filtre coupe-bande" msgid ":func:`frequency_filter `" msgstr "" msgid "Generic frequency filtering" msgstr "Filtrage fréquentiel générique" msgid "Signal Conditioning & Processing" msgstr "Conditionnement et traitement du signal" msgid ":func:`detrending `" msgstr "" msgid "Remove linear trend" msgstr "Supprimer la tendance linéaire" msgid ":func:`apply_window `" msgstr "" msgid "Apply windowing function" msgstr "Appliquer une fonction de fenêtrage" msgid ":func:`resampling `" msgstr "" msgid "Resample signal" msgstr "Rééchantillonner le signal" msgid ":func:`interpolate `" msgstr "" msgid "Interpolate signal" msgstr "Interpoler le signal" msgid ":func:`reverse_x `" msgstr "" msgid "Reverse x-axis order" msgstr "Inverser l'ordre de l'axe des x" msgid ":func:`xy_mode `" msgstr "" msgid "Handle XY coordinate modes" msgstr "Gérer les modes de coordonnées XY" msgid ":func:`replace_x_by_other_y `" msgstr "" msgid "Replace X axis using another signal's Y values" msgstr "Remplacer l'axe X en utilisant les valeurs Y d'un autre signal" msgid ":func:`zero_padding `" msgstr "" msgid "Zero-padding for signals" msgstr "Remplissage de zéros pour les signaux" msgid "Signal Analysis" msgstr "Analyse de signal" msgid ":func:`stats `" msgstr "" msgid "Statistical measurements" msgstr "Mesures statistiques" msgid ":func:`histogram `" msgstr "" msgid "Compute signal histogram" msgstr "Calculer l'histogramme du signal" msgid ":func:`contrast `" msgstr "" msgid "Compute signal contrast" msgstr "Calculer le contraste du signal" msgid ":func:`derivative `" msgstr "" msgid "Compute signal derivative" msgstr "Calculer la dérivée du signal" msgid ":func:`integral `" msgstr "" msgid "Compute signal integral" msgstr "Calculer l'intégrale du signal" msgid ":func:`sampling_rate_period `" msgstr "" msgid "Analyze sampling rate and period" msgstr "Analyser le taux et la période d'échantillonnage" msgid "Peak and Feature Detection" msgstr "Détection de pics et de caractéristiques" msgid ":func:`peak_detection `" msgstr "" msgid "Peak detection in signals" msgstr "Détection de pics dans les signaux" msgid ":func:`bandwidth_3db `" msgstr "" msgid "3dB bandwidth measurement" msgstr "Mesure de la bande passante à 3 dB" msgid ":func:`fwhm `" msgstr "" msgid "Full Width at Half Maximum" msgstr "Largeur à mi-hauteur" msgid ":func:`fw1e2 `" msgstr "" msgid "Full Width at 1/e²" msgstr "Largeur à 1/e²" msgid ":func:`full_width_at_y `" msgstr "" msgid "Full width at custom level" msgstr "Largeur à un niveau personnalisé" msgid ":func:`dynamic_parameters `" msgstr "" msgid "Dynamic range parameters" msgstr "Paramètres de dynamique" msgid ":func:`x_at_y `" msgstr "" msgid "Find x-coordinates at given y-value" msgstr "Trouver les coordonnées x pour une valeur y donnée" msgid ":func:`y_at_x `" msgstr "" msgid "Find y-values at given x-coordinate" msgstr "Trouver les valeurs y pour une coordonnée x donnée" msgid ":func:`x_at_minmax `" msgstr "" msgid "Find x-coordinates of extrema" msgstr "Trouver les coordonnées x des extrema" msgid "Curve Fitting" msgstr "Ajustement de courbes" msgid ":func:`linear_fit `" msgstr "" msgid "Linear regression" msgstr "Régression linéaire" msgid ":func:`polynomial_fit `" msgstr "" msgid "Polynomial fitting" msgstr "Ajustement polynomial" msgid ":func:`gaussian_fit `" msgstr "" msgid "Gaussian curve fitting" msgstr "Ajustement gaussien" msgid ":func:`lorentzian_fit `" msgstr "" msgid "Lorentzian curve fitting" msgstr "Ajustement lorentzien" msgid ":func:`voigt_fit `" msgstr "" msgid "Voigt profile fitting" msgstr "Ajustement de profil de Voigt" msgid ":func:`twohalfgaussian_fit `" msgstr "" msgid "Two-half Gaussian fitting" msgstr "Ajustement bi-gaussien" msgid ":func:`exponential_fit `" msgstr "" msgid "Exponential decay fitting" msgstr "Ajustement exponentiel décroissant" msgid ":func:`piecewiseexponential_fit `" msgstr "" msgid "Piecewise exponential fitting" msgstr "Ajustement exponentiel par morceaux" msgid ":func:`sigmoid_fit `" msgstr "" msgid "Sigmoid curve fitting" msgstr "Ajustement sigmoïde" msgid ":func:`sinusoidal_fit `" msgstr "" msgid "Sinusoidal fitting" msgstr "Ajustement sinusoïdal" msgid ":func:`planckian_fit `" msgstr "" msgid "Planckian (blackbody) fitting" msgstr "Ajustement planckien (corps noir)" msgid ":func:`cdf_fit `" msgstr "" msgid "Cumulative distribution function fitting" msgstr "Ajustement de fonction de distribution cumulative" msgid ":func:`evaluate_fit `" msgstr "" msgid "Evaluate fitted function" msgstr "Évaluer la fonction ajustée" msgid ":func:`extract_fit_params `" msgstr "" msgid "Extract fitting parameters" msgstr "Extraire les paramètres d'ajustement" msgid "Stability Analysis" msgstr "Analyse de stabilité" msgid ":func:`allan_variance `" msgstr "" msgid "Allan variance" msgstr "Variance d'Allan" msgid ":func:`allan_deviation `" msgstr "" msgid "Allan deviation" msgstr "Déviation d'Allan" msgid ":func:`modified_allan_variance `" msgstr "" msgid "Modified Allan variance" msgstr "Variance d'Allan modifiée" msgid ":func:`overlapping_allan_variance `" msgstr "" msgid "Overlapping Allan variance" msgstr "Variance d'Allan avec chevauchement" msgid ":func:`hadamard_variance `" msgstr "" msgid "Hadamard variance" msgstr "Variance de Hadamard" msgid ":func:`time_deviation `" msgstr "" msgid "Time deviation" msgstr "Déviation temporelle" msgid ":func:`total_variance `" msgstr "" msgid "Total variance" msgstr "Variance totale" msgid "Pulse Analysis" msgstr "Analyse d'impulsion" msgid ":func:`extract_pulse_features `" msgstr "" msgid "Extract comprehensive pulse characteristics" msgstr "Extraire les caractéristiques complètes de l'impulsion" msgid "Utility Functions" msgstr "Fonctions utilitaires" msgid ":func:`check_same_sample_rate `" msgstr "" msgid "Verify consistent sampling rates" msgstr "Vérifier la cohérence des taux d'échantillonnage" msgid ":func:`get_nyquist_frequency `" msgstr "" msgid "Calculate Nyquist frequency" msgstr "Calculer la fréquence de Nyquist" msgid "Image Processing" msgstr "Traitement d'image" msgid "Geometry and Transformations" msgstr "Géométrie et transformations" msgid ":func:`rotate `" msgstr "" msgid "Rotate image by arbitrary angle" msgstr "Faire pivoter l'image d'un angle quelconque" msgid ":func:`rotate90 `" msgstr "" msgid "Rotate image 90° clockwise" msgstr "Faire pivoter l'image de 90° dans le sens horaire" msgid ":func:`rotate270 `" msgstr "" msgid "Rotate image 270° clockwise" msgstr "Faire pivoter l'image de 270° dans le sens horaire" msgid ":func:`fliph `" msgstr "" msgid "Flip image horizontally" msgstr "Retourner l'image horizontalement" msgid ":func:`flipv `" msgstr "" msgid "Flip image vertically" msgstr "Retourner l'image verticalement" msgid ":func:`translate `" msgstr "" msgid "Translate image by specified offset" msgstr "Translater l'image d'un décalage spécifié" msgid ":func:`resize `" msgstr "" msgid "Resize image to specified dimensions" msgstr "Redimensionner l'image aux dimensions spécifiées" msgid ":func:`resampling `" msgstr "" msgid "Resample image with different methods" msgstr "Rééchantillonner l'image avec différentes méthodes" msgid ":func:`binning `" msgstr "" msgid "Reduce image size by binning pixels" msgstr "Réduire la taille de l'image par regroupement de pixels" msgid ":func:`set_uniform_coords `" msgstr "" msgid "Set uniform coordinate system" msgstr "Définir un système de coordonnées uniforme" msgid ":data:`transformer `" msgstr "" msgid "Apply custom geometric transformations" msgstr "Appliquer des transformations géométriques personnalisées" msgid "Frequency Domain Filtering" msgstr "Filtrage dans le domaine fréquentiel" msgid ":func:`butterworth `" msgstr "" msgid "Butterworth frequency filter" msgstr "Filtre fréquentiel de Butterworth" msgid ":func:`gaussian_freq_filter `" msgstr "" msgid "Gaussian frequency filter" msgstr "Filtre fréquentiel gaussien" msgid "Edge Detection" msgstr "Détection de contours" msgid ":func:`sobel `" msgstr "" msgid "Sobel edge detector" msgstr "Détecteur de contours Sobel" msgid ":func:`sobel_h `" msgstr "" msgid "Sobel horizontal edges" msgstr "Contours horizontaux Sobel" msgid ":func:`sobel_v `" msgstr "" msgid "Sobel vertical edges" msgstr "Contours verticaux Sobel" msgid ":func:`scharr `" msgstr "" msgid "Scharr edge detector" msgstr "Détecteur de contours Scharr" msgid ":func:`scharr_h `" msgstr "" msgid "Scharr horizontal edges" msgstr "Contours horizontaux Scharr" msgid ":func:`scharr_v `" msgstr "" msgid "Scharr vertical edges" msgstr "Contours verticaux Scharr" msgid ":func:`prewitt `" msgstr "" msgid "Prewitt edge detector" msgstr "Détecteur de contours Prewitt" msgid ":func:`prewitt_h `" msgstr "" msgid "Prewitt horizontal edges" msgstr "Contours horizontaux Prewitt" msgid ":func:`prewitt_v `" msgstr "" msgid "Prewitt vertical edges" msgstr "Contours verticaux Prewitt" msgid ":func:`farid `" msgstr "" msgid "Farid edge detector" msgstr "Détecteur de contours Farid" msgid ":func:`farid_h `" msgstr "" msgid "Farid horizontal edges" msgstr "Contours horizontaux Farid" msgid ":func:`farid_v `" msgstr "" msgid "Farid vertical edges" msgstr "Contours verticaux Farid" msgid ":func:`roberts `" msgstr "" msgid "Roberts cross-gradient" msgstr "Gradient croisé de Roberts" msgid ":func:`laplace `" msgstr "" msgid "Laplacian edge detector" msgstr "Détecteur de contours laplacien" msgid ":func:`canny `" msgstr "" msgid "Canny edge detector" msgstr "Détecteur de contours Canny" msgid "Feature Detection" msgstr "Détection de caractéristiques" msgid ":func:`blob_dog `" msgstr "" msgid "Blob detection using Difference of Gaussians" msgstr "Détection de blobs par différence de gaussiennes" msgid ":func:`blob_doh `" msgstr "" msgid "Blob detection using Determinant of Hessian" msgstr "Détection de blobs par déterminant de Hessien" msgid ":func:`blob_log `" msgstr "" msgid "Blob detection using Laplacian of Gaussians" msgstr "Détection de blobs par laplacien de gaussiennes" msgid ":func:`blob_opencv `" msgstr "" msgid "OpenCV-based blob detection" msgstr "Détection de blobs basée sur OpenCV" msgid ":func:`peak_detection `" msgstr "" msgid "2D peak detection" msgstr "Détection de pics 2D" msgid ":func:`contour_shape `" msgstr "" msgid "Contour shape analysis" msgstr "Analyse de forme de contour" msgid ":func:`hough_circle_peaks `" msgstr "" msgid "Circular Hough transform" msgstr "Transformée de Hough circulaire" msgid "Morphological Operations" msgstr "Opérations morphologiques" msgid ":func:`erosion `" msgstr "" msgid "Morphological erosion" msgstr "Érosion morphologique" msgid ":func:`dilation `" msgstr "" msgid "Morphological dilation" msgstr "Dilatation morphologique" msgid ":func:`opening `" msgstr "" msgid "Morphological opening" msgstr "Ouverture morphologique" msgid ":func:`closing `" msgstr "" msgid "Morphological closing" msgstr "Fermeture morphologique" msgid ":func:`white_tophat `" msgstr "" msgid "White top-hat transform" msgstr "Transformée Top-Hat" msgid ":func:`black_tophat `" msgstr "" msgid "Black top-hat transform" msgstr "Transformée Top-Hat dual" msgid "Thresholding" msgstr "Seuillage" msgid ":func:`threshold `" msgstr "" msgid "Manual threshold with custom value" msgstr "Seuillage manuel avec valeur personnalisée" msgid ":func:`threshold_otsu `" msgstr "" msgid "Otsu's thresholding" msgstr "Seuillage d'Otsu" msgid ":func:`threshold_li `" msgstr "" msgid "Li's thresholding" msgstr "Seuillage de Li" msgid ":func:`threshold_yen `" msgstr "" msgid "Yen's thresholding" msgstr "Seuillage de Yen" msgid ":func:`threshold_triangle `" msgstr "" msgid "Triangle thresholding" msgstr "Seuillage triangulaire" msgid ":func:`threshold_isodata `" msgstr "" msgid "Isodata thresholding" msgstr "Seuillage isodata" msgid ":func:`threshold_mean `" msgstr "" msgid "Mean thresholding" msgstr "Seuillage par moyenne" msgid ":func:`threshold_minimum `" msgstr "" msgid "Minimum thresholding" msgstr "Seuillage minimal" msgid "Exposure and Intensity Correction" msgstr "Correction d'exposition et d'intensité" msgid ":func:`histogram `" msgstr "" msgid "Compute image histogram" msgstr "Calculer l'histogramme de l'image" msgid ":func:`equalize_hist `" msgstr "" msgid "Histogram equalization" msgstr "Égalisation d'histogramme" msgid ":func:`equalize_adapthist `" msgstr "" msgid "Adaptive histogram equalization" msgstr "Égalisation d'histogramme adaptative" msgid ":func:`adjust_gamma `" msgstr "" msgid "Gamma correction" msgstr "Correction gamma" msgid ":func:`adjust_log `" msgstr "" msgid "Logarithmic adjustment" msgstr "Ajustement logarithmique" msgid ":func:`adjust_sigmoid `" msgstr "" msgid "Sigmoid adjustment" msgstr "Ajustement sigmoïde" msgid ":func:`rescale_intensity `" msgstr "" msgid "Rescale intensity range" msgstr "Remise à l'échelle de la plage d'intensité" msgid ":func:`flatfield `" msgstr "" msgid "Flat-field correction" msgstr "Correction de champ plat" msgid "Image Restoration" msgstr "Restauration d'image" msgid ":func:`denoise_bilateral `" msgstr "" msgid "Bilateral denoising" msgstr "Débruitage bilatéral" msgid ":func:`denoise_tv `" msgstr "" msgid "Total variation denoising" msgstr "Débruitage par variation totale" msgid ":func:`denoise_wavelet `" msgstr "" msgid "Wavelet denoising" msgstr "Débruitage par ondelettes" msgid ":func:`denoise_tophat `" msgstr "" msgid "Top-Hat denoising" msgstr "Débruitage Top-Hat" msgid ":func:`erase `" msgstr "" msgid "Erase image regions" msgstr "Effacer des régions de l'image" msgid "Preprocessing" msgstr "Prétraitement" msgid ":func:`zero_padding `" msgstr "" msgid "Zero-padding for images" msgstr "Remplissage de zéros pour les images" msgid "Measurements and Analysis" msgstr "" msgid ":func:`centroid `" msgstr "" msgid "Compute image centroid" msgstr "Calculer le centroïde de l'image" msgid ":func:`enclosing_circle `" msgstr "" msgid "Find minimum enclosing circle" msgstr "Trouver le cercle englobant minimal" msgid ":func:`stats `" msgstr "" msgid ":func:`line_profile `" msgstr "" msgid "Extract profile along a line" msgstr "Extraire le profil le long d'une ligne" msgid ":func:`segment_profile `" msgstr "" msgid "Extract profile along a multi-segment line" msgstr "Extraire le profil le long d'une ligne multi-segments" msgid ":func:`radial_profile `" msgstr "" msgid "Extract radial profile from center" msgstr "Extraire le profil radial à partir du centre" msgid ":func:`average_profile `" msgstr "" msgid "Average profile over region" msgstr "Profil moyen sur une région" msgid ":func:`horizontal_projection `" msgstr "" msgid "Project image onto horizontal axis" msgstr "Projeter l'image sur l'axe horizontal" msgid ":func:`vertical_projection `" msgstr "" msgid "Project image onto vertical axis" msgstr "Projeter l'image sur l'axe vertical" msgid ":func:`generate_image_grid_roi `" msgstr "" msgid "Generate grid of ROIs" msgstr "Générer une grille de ROI" msgid "See Also" msgstr "Voir aussi" msgid ":doc:`../api/proc` - Complete API reference for all processing functions" msgstr ":doc:`../api/proc` - Référence API complète pour toutes les fonctions de traitement" msgid ":doc:`../api/objects` - Data objects (SignalObj, ImageObj) used by processing functions" msgstr ":doc:`../api/objects` - Objets de données (SignalObj, ImageObj) utilisés par les fonctions de traitement" msgid ":doc:`../auto_examples/index` - Examples demonstrating various computation features" msgstr ":doc:`../auto_examples/index` - Exemples démontrant diverses fonctionnalités de calcul" Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/user_guide/getting_started.po000066400000000000000000000124461514013333200250070ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2025, DataLab Platform Developers # This file is distributed under the same license as the Sigima package. # FIRST AUTHOR , 2025. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: Sigima \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid "Getting Started" msgstr "Premiers pas" msgid "This page provides a quick introduction to get you started with Sigima through practical examples." msgstr "Cette page fournit une introduction rapide pour vous aider à démarrer avec Sigima à travers des exemples pratiques." msgid "Interactive Notebook" msgstr "Notebook interactif" msgid "The best way to start learning Sigima is through an interactive Jupyter notebook. This example demonstrates image processing with Regions of Interest (ROI) and uses the matplotlib backend for web-friendly visualization." msgstr "La meilleure façon de commencer à apprendre Sigima est à travers un notebook Jupyter interactif. Cet exemple démontre le traitement d'images avec des régions d'intérêt (ROI) et utilise le backend matplotlib pour une visualisation adaptée au web." msgid ":download:`Download simple_example.ipynb <../simple_example.ipynb>`" msgstr "" msgid "What This Example Shows" msgstr "Ce que cet exemple montre" msgid "The notebook demonstrates:" msgstr "Le notebook démontre :" msgid "Creating image objects from NumPy arrays" msgstr "Créer des objets image à partir de tableaux NumPy" msgid "Defining Regions of Interest (ROI) for selective processing" msgstr "Définir des régions d'intérêt (ROI) pour un traitement sélectif" msgid "Applying Gaussian filtering to images" msgstr "Appliquer un filtrage gaussien aux images" msgid "Visualizing results with matplotlib backend (web-friendly, no Qt required)" msgstr "Visualiser les résultats avec le backend matplotlib (adapté au web, pas de Qt requis)" msgid "Using the new visualization backend selection feature introduced in Sigima V1.1" msgstr "Utiliser la nouvelle fonctionnalité de sélection du backend de visualisation introduite dans Sigima V1.1" msgid "Key Concepts" msgstr "Concepts clés" msgid "**Object-Oriented Approach**" msgstr "**Approche orientée objet**" msgid "Sigima wraps NumPy arrays in rich objects (``SignalObj``, ``ImageObj``) that carry metadata, units, and ROI information." msgstr "Sigima enveloppe les tableaux NumPy dans des objets riches (``SignalObj``, ``ImageObj``) qui portent des métadonnées, des unités et des informations ROI." msgid "**Region of Interest (ROI)**" msgstr "**Région d'intérêt (ROI)**" msgid "Process only specific areas of your data by defining ROIs. The example shows a circular ROI applied to an image." msgstr "Traitez uniquement des zones spécifiques de vos données en définissant des ROI. L'exemple montre une ROI circulaire appliquée à une image." msgid "**Backend Flexibility**" msgstr "**Flexibilité du backend**" msgid "Choose between PlotPy (Qt-based, interactive) or Matplotlib (web-friendly) backends for visualization, making Sigima suitable for both desktop applications and web-based workflows." msgstr "Choisissez entre les backends PlotPy (basé sur Qt, interactif) ou Matplotlib (adapté au web) pour la visualisation, rendant Sigima adapté à la fois aux applications de bureau et aux flux de travail basés sur le web." msgid "Remote Control Example" msgstr "Exemple de contrôle à distance" msgid "Sigima also enables remote control of DataLab sessions from external scripts or notebooks. This is useful for automation, batch processing, or integrating DataLab into larger workflows." msgstr "Sigima permet également le contrôle à distance des sessions DataLab à partir de scripts ou de notebooks externes. Cela est utile pour l'automatisation, le traitement par lots ou l'intégration de DataLab dans des flux de travail plus larges." msgid ":download:`Download remote_example.ipynb <../remote_example.ipynb>`" msgstr "" msgid "This notebook demonstrates:" msgstr "Ce notebook démontre :" msgid "Connecting to a running DataLab instance using ``SimpleRemoteProxy``" msgstr "Se connecter à une instance DataLab en cours d'exécution en utilisant ``SimpleRemoteProxy``" msgid "Adding signals and images to DataLab from external Python code" msgstr "Ajouter des signaux et des images à DataLab à partir de code Python externe" msgid "Controlling DataLab programmatically without GUI interaction" msgstr "Contrôler DataLab de manière programmatique sans interaction avec l'interface graphique" msgid "Next Steps" msgstr "Prochaines étapes" msgid "Explore the :ref:`features` page for a complete overview of available operations" msgstr "Explorez la page :ref:`features` pour un aperçu complet des opérations disponibles" msgid "Check out the :ref:`API documentation ` for detailed function references" msgstr "Consultez la :ref:`documentation API ` pour des références détaillées des fonctions" msgid "Browse the :doc:`gallery of examples ` for more use cases" msgstr "Parcourez la :doc:`galerie d'exemples ` pour plus de cas d'utilisation" Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/user_guide/index.po000066400000000000000000000077311514013333200227300ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2025, DataLab Platform Developers # This file is distributed under the same license as the Sigima package. # FIRST AUTHOR , 2025. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: Sigima \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid "Contents:" msgstr "Table des matières :" msgid "User Guide" msgstr "Manuel utilisateur" msgid " Installation" msgstr "Installation" msgid "How to install Sigima" msgstr "Comment installer Sigima" msgid " Getting Started" msgstr "Premiers pas" msgid "Quick start with examples" msgstr "Démarrage rapide avec des exemples" msgid " Overview" msgstr "Vue d'ensemble" msgid "Introduction to Sigima" msgstr "Introduction à Sigima" msgid " Features" msgstr "Fonctionnalités" msgid "Key functionalities" msgstr "Fonctionnalités clés" Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/user_guide/installation.po000066400000000000000000000273021514013333200243160ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2025, DataLab Platform Developers # This file is distributed under the same license as the Sigima package. # FIRST AUTHOR , 2025. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: Sigima \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid "Installation" msgstr "Installation" msgid "This section provides instructions on how to install and set up the Sigima project, including dependencies and environment configuration." msgstr "Cette section fournit des instructions sur la façon d'installer et de configurer le projet Sigima, y compris les dépendances et la configuration de l'environnement." msgid "How to install" msgstr "Modes d'installation" msgid "Sigima is available in several forms:" msgstr "Sigima est disponible sous plusieurs formes :" msgid "As a :ref:`install_conda`." msgstr "En tant que :ref:`install_conda`." msgid "As a Python package, which can be installed using the :ref:`install_pip`." msgstr "Un paquet Python qui peut être installé à l'aide du :ref:`install_pip`." msgid "As a precompiled :ref:`install_wheel`, which can be installed using ``pip``." msgstr "En tant que :ref:`install_wheel` précompilé, qui peut être installé à l'aide de ``pip``." msgid "As a :ref:`install_source`, which can be installed using ``pip`` or manually." msgstr "En tant que :ref:`install_source`, qui peut être installé à l'aide de ``pip`` ou manuellement." msgid "Impatient to try the next version of Sigima? You can also install the latest development version of Sigima from the master branch of the Git repository. See :ref:`install_development` for more information." msgstr "Impatient d'essayer la prochaine version de Sigima ? Vous pouvez également installer la dernière version de développement de Sigima depuis la branche principale du dépôt Git. Voir :ref:`install_development` pour plus d'informations." msgid "Conda package" msgstr "Paquet Conda" msgid ":octicon:`info;1em;sd-text-info` :bdg-info-line:`GNU/Linux` :bdg-info-line:`Windows` :bdg-info-line:`macOS`" msgstr "" msgid "To install ``sigima`` package from the `conda-forge` channel (https://anaconda.org/conda-forge/sigima), run the following command:" msgstr "Pour installer le paquet ``sigima`` depuis le canal ``conda-forge`` (https://anaconda.org/conda-forge/sigima), exécutez la commande suivante :" msgid "Package manager ``pip``" msgstr "Gestionnaire de paquets ``pip``" msgid "Sigima's package ``sigima`` is available on the Python Package Index (PyPI) on the following URL: https://pypi.python.org/pypi/sigima." msgstr "Le paquet ``sigima`` de Sigima est disponible sur l'index des paquets Python (PyPI) à l'adresse suivante : https://pypi.python.org/pypi/sigima." msgid "Installing Sigima from PyPI is as simple as running this command (you may need to use ``pip3`` instead of ``pip`` on some systems):" msgstr "L'installation de Sigima depuis PyPI est aussi simple que d'exécuter cette commande (vous devrez peut-être utiliser ``pip3`` au lieu de ``pip`` sur certains systèmes) :" msgid "If you already have a previous version of Sigima installed, you can upgrade it by running the same command with the ``--upgrade`` option:" msgstr "Si vous avez déjà une version précédente de Sigima installée, vous pouvez la mettre à niveau en exécutant la même commande avec l'option ``--upgrade`` :" msgid "Wheel package" msgstr "Paquet Wheel" msgid "On any operating system, using pip and the Wheel package is the easiest way to install sigima on an existing Python distribution:" msgstr "Sur n'importe quel système d'exploitation, l'utilisation de pip et du paquet Wheel est le moyen le plus simple d'installer sigima sur une distribution Python existante :" msgid "Source package" msgstr "Paquet source" msgid "Installing Sigima directly from the source package may be done using ``pip``:" msgstr "L'installation de Sigima directement à partir du paquet source peut se faire en utilisant ``pip`` :" msgid "Or, if you prefer, you can install it manually by running the following command from the root directory of the source package:" msgstr "Ou, si vous préférez, vous pouvez l'installer manuellement en exécutant la commande suivante depuis le répertoire racine du paquet source :" msgid "Finally, you can also build your own Wheel package and install it using ``pip``, by running the following command from the root directory of the source package (this requires the ``build`` and ``wheel`` packages to be installed):" msgstr "Enfin, vous pouvez également créer votre propre paquet Wheel et l'installer à l'aide de ``pip``, en exécutant la commande suivante depuis le répertoire racine du paquet source (cela nécessite que les paquets ``build`` et ``wheel`` soient installés) :" msgid "Development version" msgstr "Version de développement" msgid "If you want to try the latest development version of Sigima, you can install it directly from the master branch of the Git repository." msgstr "Si vous souhaitez essayer la dernière version de développement de Sigima, vous pouvez l'installer directement depuis la branche principale du dépôt Git." msgid "The first time you install Sigima from the Git repository, enter the following command:" msgstr "La première fois que vous installez Sigima depuis le dépôt Git, entrez la commande suivante :" msgid "Then, if at some point you want to upgrade to the latest version of Sigima, just run the same command with options to force the reinstall of the package without handling dependencies (because it would reinstall all dependencies):" msgstr "Ensuite, si à un moment donné vous souhaitez mettre à niveau vers la dernière version de Sigima, il suffit d'exécuter la même commande avec des options pour forcer la réinstallation du paquet sans gérer les dépendances (car cela réinstallerait toutes les dépendances) :" msgid "If dependencies have changed, you may need to execute the same command as above, but without the ``--no-deps`` option." msgstr "Si les dépendances ont changé, vous devrez peut-être exécuter la même commande que ci-dessus, mais sans l'option ``--no-deps``." msgid "Dependencies" msgstr "Dépendances" msgid "The `sigima` package requires the following Python modules:" msgstr "Le paquet `sigima` nécessite les modules Python suivants :" msgid "Name" msgstr "Nom" msgid "Version" msgstr "Version" msgid "Summary" msgstr "Description" msgid "Python" msgstr "Python" msgid ">=3.9, <4" msgstr "" msgid "Python programming language" msgstr "Langage de programmation Python" msgid "guidata" msgstr "" msgid ">= 3.13" msgstr "" msgid "Automatic GUI generation for easy dataset editing and display" msgstr "Génération automatique d'interfaces graphiques pour l'édition et l'affichage de jeux de données" msgid "NumPy" msgstr "" msgid ">= 1.22, < 2.5" msgstr "" msgid "Fundamental package for array computing in Python" msgstr "Paquet fondamental pour le calcul sur tableaux en Python" msgid "SciPy" msgstr "" msgid ">= 1.10.1, < 1.17" msgstr "" msgid "Fundamental algorithms for scientific computing in Python" msgstr "Algorithmes fondamentaux pour le calcul scientifique en Python" msgid "scikit-image" msgstr "" msgid ">= 0.19.2, < 0.27" msgstr "" msgid "Image processing in Python" msgstr "Traitement d'images en Python" msgid "pandas" msgstr "" msgid ">= 1.4, < 3.0" msgstr "" msgid "Powerful data structures for data analysis, time series, and statistics" msgstr "" msgid "PyWavelets" msgstr "" msgid ">= 1.2, < 2.0" msgstr "" msgid "PyWavelets, wavelet transform module" msgstr "PyWavelets, module de transformation en ondelettes" msgid "packaging" msgstr "" msgid ">= 21.3" msgstr "" msgid "Core utilities for Python packages" msgstr "" msgid "typing-extensions" msgstr "" msgid ">= 4.0" msgstr "" msgid "Backported and Experimental Type Hints for Python 3.9+" msgstr "" msgid "makefun" msgstr "" msgid ">= 1.13.1" msgstr "" msgid "Small library to dynamically create python functions." msgstr "" msgid "Optional modules for GUI support (Qt):" msgstr "Modules optionnels pour le support de l'interface graphique (Qt) :" msgid "qtpy" msgstr "" msgid "Provides an abstraction layer on top of the various Qt bindings (PyQt5/6 and PySide2/6)." msgstr "" msgid "PyQt5" msgstr "" msgid "Python bindings for the Qt cross platform application toolkit" msgstr "Bibliothèque d'interfaces graphiques Qt pour Python" msgid "plotpy" msgstr "" msgid "Curve and image plotting tools for Python/Qt applications" msgstr "Outils de tracé de courbes et d'images pour les applications Python/Qt" msgid "Optional modules for development:" msgstr "Modules optionnels pour le développement :" msgid "build" msgstr "" msgid "A simple, correct Python build frontend" msgstr "" msgid "babel" msgstr "" msgid "Internationalization utilities" msgstr "" msgid "ruff" msgstr "" msgid "An extremely fast Python linter and code formatter, written in Rust." msgstr "Analyseur de code et formateur Python extrêmement rapide, écrit en Rust." msgid "pylint" msgstr "" msgid "python code static checker" msgstr "Analyseur statique de code Python" msgid "Coverage" msgstr "" msgid "Code coverage measurement for Python" msgstr "Mesure de la couverture de code pour Python" msgid "pre-commit" msgstr "" msgid "A framework for managing and maintaining multi-language pre-commit hooks." msgstr "" msgid "Optional modules for building the documentation:" msgstr "Modules optionnels pour la génération de la documentation :" msgid "sphinx" msgstr "" msgid "Python documentation generator" msgstr "Générateur de documentation Python" msgid "sphinx-gallery" msgstr "" msgid "A Sphinx extension that builds an HTML gallery of examples from any set of Python scripts." msgstr "Une extension Sphinx qui crée une galerie HTML d'exemples à partir de n'importe quel ensemble de scripts Python." msgid "sphinx_intl" msgstr "" msgid "Sphinx utility that make it easy to translate and to apply translation." msgstr "Utilitaire pour la traduction de la documentation générée par Sphinx." msgid "myst_parser" msgstr "" msgid "An extended [CommonMark](https://spec.commonmark.org/) compliant parser," msgstr "Un parseur étendu compatible avec [CommonMark](https://spec.commonmark.org/)" msgid "myst-nb" msgstr "" msgid "A Jupyter Notebook Sphinx reader built on top of the MyST markdown parser." msgstr "" msgid "sphinx_design" msgstr "" msgid "A sphinx extension for designing beautiful, view size responsive web components." msgstr "Extension sphinx pour la conception de composants web réactifs." msgid "sphinx-copybutton" msgstr "" msgid "Add a copy button to each of your code cells." msgstr "Extension sphinx ajoutant un bouton de copie à chaque cellule de code." msgid "pydata-sphinx-theme" msgstr "" msgid "Bootstrap-based Sphinx theme from the PyData community" msgstr "Thème Bootstrap pour Sphinx de la communauté PyData" msgid "matplotlib" msgstr "" #, fuzzy msgid "Python plotting package" msgstr "Langage de programmation Python" msgid "opencv-python-headless" msgstr "" msgid ">= 4.8.1.78" msgstr "" msgid "Wrapper package for OpenCV python bindings." msgstr "Bibliothèque d'interfaces Python pour OpenCV." msgid "Optional modules for running test suite:" msgstr "Modules optionnels pour l'exécution de la suite de tests :" msgid "pytest" msgstr "" msgid "pytest: simple powerful testing with Python" msgstr "pytest : tests simples et puissants avec Python" msgid "pytest-xvfb" msgstr "" msgid "A pytest plugin to run Xvfb (or Xephyr/Xvnc) for tests." msgstr "Plugin pytest pour exécuter Xvfb (ou Xephyr/Xvnc) pour les tests." Sigima-1.1.1/doc/locale/fr/LC_MESSAGES/user_guide/overview.po000066400000000000000000000563321514013333200234700ustar00rootroot00000000000000# SOME DESCRIPTIVE TITLE. # Copyright (C) 2025, DataLab Platform Developers # This file is distributed under the same license as the Sigima package. # FIRST AUTHOR , 2025. # #, fuzzy msgid "" msgstr "" "Project-Id-Version: Sigima \n" "Report-Msgid-Bugs-To: \n" "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" "Language: fr\n" "Language-Team: fr \n" "Plural-Forms: nplurals=2; plural=(n > 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid "Overview" msgstr "Vue d'ensemble" msgid "What is Sigima?" msgstr "Qu'est-ce que Sigima ?" msgid "**Sigima** is an open-source Python library for scientific signal and image processing. It provides a unified, object-oriented approach to working with 1D signals and 2D images, combining the power of NumPy arrays with rich metadata and processing capabilities." msgstr "**Sigima** est une bibliothèque Python open-source pour le traitement scientifique de signaux et d'images. Elle fournit une approche unifiée et orientée objet pour travailler avec des signaux 1D et des images 2D, combinant la puissance des tableaux NumPy avec des métadonnées riches et des capacités de traitement." msgid "Sigima was created from the externalization of `DataLab `_'s computing engine and is now an essential building block of the DataLab ecosystem, but is designed to be GUI-independent (and independent of DataLab itself) and can be used in a variety of scientific computing contexts." msgstr "Sigima a été créé à partir de l'externalisation du moteur de calcul de `DataLab `_ et constitue maintenant un élément essentiel de l'écosystème DataLab, mais est conçu pour être indépendant de toute interface graphique (et indépendant de DataLab lui-même) et peut être utilisé dans une variété de contextes de calcul scientifique." msgid "Quick Start Example" msgstr "Exemple de démarrage rapide" msgid "Here's a simple example demonstrating image processing with Regions of Interest (ROIs) using Sigima. This example uses the matplotlib backend for visualization, making it web-friendly and easy to run in Jupyter notebooks." msgstr "Voici un exemple simple démontrant le traitement d'images avec des régions d'intérêt (ROI) en utilisant Sigima. Cet exemple utilise le backend matplotlib pour la visualisation, ce qui le rend adapté au web et facile à exécuter dans des notebooks Jupyter." msgid "See the complete interactive notebook in the :ref:`getting_started` section." msgstr "Voir le notebook interactif complet dans la section :ref:`getting_started`." msgid "Why Sigima?" msgstr "Pourquoi Sigima ?" msgid "Scientific data processing often requires more than just raw numerical arrays. Real-world applications demand:" msgstr "Le traitement de données scientifiques nécessite souvent plus que de simples tableaux numériques. Les applications réelles requièrent :" msgid "**Context-aware data**: physical units, coordinate systems, and measurement uncertainties" msgstr "**Données contextualisées** : unités physiques, systèmes de coordonnées et incertitudes de mesure" msgid "**Reproducible workflows**: clear separation between data and processing logic" msgstr "**Flux de travail reproductibles** : séparation claire entre les données et la logique de traitement" msgid "**Testable components**: modular functions that can be validated independently" msgstr "**Composants testables** : fonctions modulaires qui peuvent être validées indépendamment" msgid "**Flexible integration**: ability to work both with high-level objects and low-level arrays" msgstr "**Intégration flexible** : capacité de travailler à la fois avec des objets de haut niveau et des tableaux de bas niveau" msgid "Sigima addresses these needs by providing a structured framework that bridges the gap between raw numerical operations and scientific data analysis. It is designed to be the processing backend for scientific applications, particularly those requiring headless execution or remote processing capabilities." msgstr "Sigima répond à ces besoins en fournissant un cadre structuré qui comble le fossé entre les opérations numériques brutes et l'analyse de données scientifiques. Il est conçu pour être le moteur de traitement des applications scientifiques, en particulier celles nécessitant une exécution sans interface graphique ou des capacités de traitement à distance." msgid "Signals in Sigima" msgstr "Signaux dans Sigima" msgid "What are Signals?" msgstr "Qu'est-ce qu'un signal ?" msgid "In Sigima, a **signal** is a 1D data object represented by the :py:class:`~sigima.objects.signal.object.SignalObj` class. Unlike a simple NumPy array, a signal carries complete information about your measurement or calculation." msgstr "Dans Sigima, un **signal** est un objet de données 1D représenté par la classe :py:class:`~sigima.objects.signal.object.SignalObj`. Contrairement à un simple tableau NumPy, un signal contient l'ensemble des informations concernant votre mesure ou calcul." msgid "Core Components" msgstr "Composants principaux" msgid "A signal consists of:" msgstr "Un signal se compose de :" msgid "**X and Y Data**" msgstr "**Données X et Y**" msgid "The fundamental coordinate-value pairs that define your signal. The x-axis typically represents the independent variable (time, frequency, position, etc.) while the y-axis contains the measured or calculated values." msgstr "Les paires fondamentales coordonnée-valeur qui définissent votre signal. L'axe des x représente généralement la variable indépendante (temps, fréquence, position, etc.) tandis que l'axe des y contient les valeurs mesurées ou calculées." msgid "**Error Bars (dx, dy)**" msgstr "**Barres d'erreur (dx, dy)**" msgid "Sigima natively supports uncertainty quantification through optional error bars:" msgstr "Sigima prend en charge nativement la quantification de l'incertitude via des barres d'erreur optionnelles :" msgid "``dx``: uncertainties in the x-coordinate (e.g., timing jitter, position uncertainty)" msgstr "``dx`` : incertitudes sur la coordonnée x (par exemple, gigue temporelle, incertitude de position)" msgid "``dy``: uncertainties in the y-values (e.g., measurement noise, statistical errors)" msgstr "``dy`` : incertitudes sur les valeurs y (par exemple, bruit de mesure, erreurs statistiques)" msgid "These error bars propagate through many processing operations, allowing you to track how uncertainties evolve in your analysis pipeline." msgstr "Ces barres d'erreur se propagent à travers de nombreuses opérations de traitement, vous permettant de suivre l'évolution des incertitudes dans votre pipeline d'analyse." msgid "**Metadata**" msgstr "**Métadonnées**" msgid "A flexible dictionary for storing any additional information about your signal: acquisition parameters, processing history, physical constants, or any custom data your application needs." msgstr "Un dictionnaire flexible pour stocker toute information supplémentaire concernant votre signal : paramètres d'acquisition, historique de traitement, constantes physiques ou toute donnée personnalisée dont votre application a besoin." msgid "**Units and Labels**" msgstr "**Unités et étiquettes**" msgid "Clear labeling of physical quantities:" msgstr "Étiquetage clair des grandeurs physiques :" msgid "``xlabel`` / ``ylabel``: descriptive names (e.g., \"Time\", \"Temperature\")" msgstr "``xlabel`` / ``ylabel`` : noms descriptifs (par exemple, \"Temps\", \"Température\")" msgid "``xunit`` / ``yunit``: physical units (e.g., \"s\", \"°C\")" msgstr "``xunit`` / ``yunit`` : unités physiques (par exemple, \"s\", \"°C\")" msgid "**Annotations**" msgstr "**Annotations**" msgid "User-defined notes or comments about specific features or regions of the signal." msgstr "Notes ou commentaires définis par l'utilisateur concernant des caractéristiques ou régions spécifiques du signal." msgid "Why This Matters" msgstr "Pourquoi c'est important" msgid "Consider a temperature measurement over time. With a simple NumPy array, you just have numbers. With a Sigima signal, you have:" msgstr "Considérez une mesure de température au cours du temps. Avec un simple tableau NumPy, vous n'avez que des nombres. Avec un signal Sigima, vous avez :" msgid "This signal object can now be processed, analyzed, saved, and loaded while preserving all its context. When you apply operations like filtering, peak detection, or statistics, the units, labels, and error bars remain attached to your data." msgstr "Cet objet signal peut maintenant être traité, analysé, sauvegardé et chargé tout en préservant son contexte. Lorsque vous appliquez des opérations comme le filtrage, la détection de pics ou les statistiques, les unités, étiquettes et barres d'erreur restent attachées à vos données." msgid "Specialized Features" msgstr "Fonctionnalités spécialisées" msgid "Sigima signals support advanced use cases:" msgstr "Les signaux Sigima prennent en charge des cas d'usage avancés :" msgid "**Datetime Coordinates**" msgstr "**Coordonnées temporelles**" msgid "For time-series data, x-coordinates can represent actual datetime values, with automatic handling of time units and formatting." msgstr "Pour les données de séries temporelles, les coordonnées x peuvent représenter des valeurs de date/heure réelles, avec gestion automatique des unités de temps et du formatage." msgid "**ROI Operations**" msgstr "**Opérations ROI**" msgid "Define regions of interest (ROIs) to process or analyze specific portions of your signal independently." msgstr "Définissez des régions d'intérêt (ROI) pour traiter ou analyser des portions spécifiques de votre signal de manière indépendante." msgid "**Scale Management**" msgstr "**Gestion des échelles**" msgid "Control visualization aspects like logarithmic scales and axis bounds." msgstr "Contrôlez les aspects de visualisation comme les échelles logarithmiques et les limites d'axes." msgid "Images in Sigima" msgstr "Images dans Sigima" msgid "What are Images?" msgstr "Qu'est-ce qu'une image ?" msgid "An **image** in Sigima is a 2D data object represented by the :py:class:`~sigima.objects.image.object.ImageObj` class. Like signals, images extend beyond simple 2D NumPy arrays by providing comprehensive metadata and coordinate system support." msgstr "Une **image** dans Sigima est un objet de données 2D représenté par la classe :py:class:`~sigima.objects.image.object.ImageObj`. Comme les signaux, les images vont au-delà des simples tableaux NumPy 2D en fournissant des métadonnées complètes et un support de système de coordonnées." msgid "An image consists of:" msgstr "Une image se compose de :" msgid "**2D Data Array**" msgstr "**Tableau de données 2D**" msgid "The pixel values forming your image. Sigima supports various data types including unsigned integers (uint8, uint16), signed integers (int16, int32), floating-point (float32, float64), and complex numbers (complex128)." msgstr "Les valeurs de pixels formant votre image. Sigima prend en charge divers types de données incluant les entiers non signés (uint8, uint16), les entiers signés (int16, int32), les nombres à virgule flottante (float32, float64) et les nombres complexes (complex128)." msgid "**Coordinate Systems**" msgstr "**Systèmes de coordonnées**" msgid "Two types of coordinate systems are supported:" msgstr "Deux types de systèmes de coordonnées sont pris en charge :" msgid "**Uniform coordinates**: regular pixel spacing, common for most imaging systems" msgstr "**Coordonnées uniformes** : espacement de pixels régulier, courant pour la plupart des systèmes d'imagerie" msgid "``dx``, ``dy``: pixel spacing in physical units" msgstr "``dx``, ``dy`` : espacement des pixels en unités physiques" msgid "``x0``, ``y0``: origin coordinates" msgstr "``x0``, ``y0`` : coordonnées d'origine" msgid "**Non-uniform coordinates**: variable pixel spacing for adaptive sampling or irregular grids" msgstr "**Coordonnées non uniformes** : espacement de pixels variable pour l'échantillonnage adaptatif ou les grilles irrégulières" msgid "``xcoords``, ``ycoords``: explicit coordinate arrays" msgstr "``xcoords``, ``ycoords`` : tableaux de coordonnées explicites" msgid "Rich metadata support including:" msgstr "Support riche de métadonnées incluant :" msgid "DICOM template integration for medical imaging" msgstr "Intégration de modèles DICOM pour l'imagerie médicale" msgid "Custom key-value pairs for any application-specific data" msgstr "Paires clé-valeur personnalisées pour toute donnée spécifique à l'application" msgid "Automatic extraction from common file formats" msgstr "Extraction automatique depuis les formats de fichiers courants" msgid "Physical quantities for all three dimensions:" msgstr "Grandeurs physiques pour les trois dimensions :" msgid "``xlabel``, ``ylabel``, ``zlabel``: axis descriptions" msgstr "``xlabel``, ``ylabel``, ``zlabel`` : descriptions d'axes" msgid "``xunit``, ``yunit``, ``zunit``: physical units" msgstr "``xunit``, ``yunit``, ``zunit`` : unités physiques" msgid "The z-axis typically represents the pixel values (intensity, height, temperature, etc.)" msgstr "L'axe z représente généralement les valeurs de pixels (intensité, hauteur, température, etc.)" msgid "Structured annotations for documenting features, regions, or processing steps." msgstr "Annotations structurées pour documenter les caractéristiques, régions ou étapes de traitement." msgid "**Data Type Flexibility**" msgstr "**Flexibilité des types de données**" msgid "Unlike signals (which are typically float64), images support multiple data types optimized for different use cases:" msgstr "Contrairement aux signaux (qui sont généralement en float64), les images prennent en charge plusieurs types de données optimisés pour différents cas d'usage :" msgid "``uint8``, ``uint16``: efficient storage for camera data, medical images" msgstr "``uint8``, ``uint16`` : stockage efficace pour les données de caméras, images médicales" msgid "``int16``, ``int32``: signed data, difference images" msgstr "``int16``, ``int32`` : données signées, images de différence" msgid "``float32``, ``float64``: scientific measurements, calculated results" msgstr "``float32``, ``float64`` : mesures scientifiques, résultats calculés" msgid "``complex128``: Fourier transforms, wave simulations" msgstr "``complex128`` : transformées de Fourier, simulations d'ondes" msgid "Consider microscopy data. A raw 2D array gives you pixel values, but an ``ImageObj`` provides the complete picture:" msgstr "Considérez des données de microscopie. Un tableau 2D brut vous donne des valeurs de pixels, mais un ``ImageObj`` fournit l'image complète :" msgid "Processing operations automatically work in physical units. Measurements return results in micrometers, not pixels. The metadata travels with your data through the entire analysis pipeline." msgstr "Les opérations de traitement fonctionnent automatiquement en unités physiques. Les mesures retournent des résultats en micromètres, pas en pixels. Les métadonnées accompagnent vos données tout au long du pipeline d'analyse." msgid "**Native Support for Multiple Image Formats**" msgstr "**Support natif de multiples formats d'image**" msgid "Sigima can directly read and write images from various scientific and common file formats, making it easy to integrate into existing workflows:" msgstr "Sigima peut lire et écrire directement des images depuis divers formats de fichiers scientifiques et courants, facilitant l'intégration dans les flux de travail existants :" msgid "**Common formats**: BMP, JPEG, PNG, TIFF, JPEG 2000" msgstr "**Formats courants** : BMP, JPEG, PNG, TIFF, JPEG 2000" msgid "**Scientific formats**: DICOM (medical imaging), Andor SIF (spectroscopy cameras)" msgstr "**Formats scientifiques** : DICOM (imagerie médicale), Andor SIF (caméras de spectroscopie)" msgid "**Data exchange**: NumPy (.npy), MATLAB (.mat), HDF5 (.h5img)" msgstr "**Échange de données** : NumPy (.npy), MATLAB (.mat), HDF5 (.h5img)" msgid "**Text-based**: CSV, TXT, ASC (with coordinate metadata support)" msgstr "**Basés sur du texte** : CSV, TXT, ASC (avec support des métadonnées de coordonnées)" msgid "**Specialized**: Spiricon (.scor-data), Dürr NDT (.xyz), FT-Lab (.ima)" msgstr "**Spécialisés** : Spiricon (.scor-data), Dürr NDT (.xyz), FT-Lab (.ima)" msgid "Each format preserves relevant metadata when available, such as DICOM medical imaging headers or acquisition parameters from scientific instruments." msgstr "Chaque format préserve les métadonnées pertinentes lorsqu'elles sont disponibles, comme les en-têtes d'imagerie médicale DICOM ou les paramètres d'acquisition d'instruments scientifiques." msgid "Define rectangular, circular, or polygonal regions of interest for localized analysis or processing." msgstr "Définissez des régions d'intérêt rectangulaires, circulaires ou polygonales pour une analyse ou un traitement localisé." msgid "**Masked Arrays**" msgstr "**Tableaux masqués**" msgid "Support for NumPy masked arrays to handle invalid pixels, saturated regions, or excluded areas." msgstr "Support des tableaux masqués NumPy pour gérer les pixels invalides, les régions saturées ou les zones exclues." msgid "**Coordinate Conversion**" msgstr "**Conversion de coordonnées**" msgid "Seamless conversion between pixel indices and physical coordinates, essential for multi-scale or multi-modal imaging." msgstr "Conversion transparente entre les indices de pixels et les coordonnées physiques, essentielle pour l'imagerie multi-échelle ou multi-modale." msgid "Key Differences from Raw Arrays" msgstr "Différences clés par rapport aux tableaux bruts" msgid "Here's why Sigima objects are more powerful than plain NumPy arrays in physical data processing:" msgstr "Voici pourquoi les objets Sigima sont plus puissants que les simples tableaux NumPy pour le traitement de données physiques :" msgid "Feature" msgstr "Fonctionnalité" msgid "NumPy Array" msgstr "Tableau NumPy" msgid "Sigima Object" msgstr "Objet Sigima" msgid "Data storage" msgstr "Stockage de données" msgid "Numbers only" msgstr "Nombres uniquement" msgid "Numbers + context" msgstr "Nombres + contexte" msgid "Units" msgstr "Unités" msgid "Implicit/external" msgstr "Implicites/externes" msgid "Explicit and tracked" msgstr "Explicites et suivies" msgid "Error propagation" msgstr "Propagation d'erreur" msgid "Manual" msgstr "Manuelle" msgid "Automatic (where supported)" msgstr "Automatique (lorsque pris en charge)" msgid "Metadata" msgstr "Métadonnées" msgid "Separate variables" msgstr "Variables séparées" msgid "Integrated dictionary" msgstr "Dictionnaire intégré" msgid "Coordinate systems" msgstr "Systèmes de coordonnées" msgid "Index-based only" msgstr "Uniquement basé sur les indices" msgid "Physical coordinates" msgstr "Coordonnées physiques" msgid "Serialization" msgstr "Sérialisation" msgid "Just data" msgstr "Données seules" msgid "Complete context" msgstr "Contexte complet" msgid "Processing history" msgstr "Historique de traitement" msgid "Lost" msgstr "Perdu" msgid "Can be tracked" msgstr "Peut être suivi" msgid "Common Use Cases" msgstr "Cas d'usage courants" msgid "Sigima excels in scenarios requiring:" msgstr "Sigima excelle dans les scénarios nécessitant :" msgid "**Scientific Instrumentation**" msgstr "**Instrumentation scientifique**" msgid "Process data from sensors, cameras, spectrometers, or any measurement device while preserving calibration, units, and acquisition parameters." msgstr "Traitez les données de capteurs, caméras, spectromètres ou tout dispositif de mesure en préservant l'étalonnage, les unités et les paramètres d'acquisition." msgid "**Automated Analysis Pipelines**" msgstr "**Pipelines d'analyse automatisés**" msgid "Build reproducible workflows that maintain data provenance and context through multiple processing steps." msgstr "Construisez des flux de travail reproductibles qui maintiennent la provenance et le contexte des données à travers plusieurs étapes de traitement." msgid "**Remote Processing**" msgstr "**Traitement à distance**" msgid "Execute signal and image processing on remote servers or in cloud environments without GUI dependencies." msgstr "Exécutez le traitement de signaux et d'images sur des serveurs distants ou dans des environnements cloud sans dépendances d'interface graphique." msgid "**Application Backends**" msgstr "**Moteurs d'application**" msgid "Provide the computation engine for scientific software, keeping processing logic independent from user interface concerns." msgstr "Fournissez le moteur de calcul pour des logiciels scientifiques, en gardant la logique de traitement indépendante des préoccupations d'interface utilisateur." msgid "**Research and Development**" msgstr "**Recherche et développement**" msgid "Develop and validate new processing algorithms in a testable, modular framework." msgstr "Développez et validez de nouveaux algorithmes de traitement dans un cadre testable et modulaire." msgid "GUI Connection" msgstr "Connexion avec l'interface graphique" msgid "As the core computing engine externalized from `DataLab `_, Sigima seamlessly integrates with it as an essential building block of the DataLab stack. You can leverage Sigima's powerful processing features within DataLab's graphical interface, using for example Sigima to handle your signal and image acquisition and sending the results back to DataLab for visualization and further interactive analysis." msgstr "En tant que moteur de calcul principal externalisé de `DataLab `_, Sigima s'intègre parfaitement avec lui comme élément essentiel de la pile DataLab. Vous pouvez exploiter les puissantes fonctionnalités de traitement de Sigima au sein de l'interface graphique de DataLab, en utilisant par exemple Sigima pour gérer votre acquisition de signaux et d'images et en renvoyant les résultats vers DataLab pour la visualisation et l'analyse interactive approfondie." msgid "Getting Started" msgstr "Premiers pas" msgid "To start using Sigima, check out:" msgstr "Pour commencer à utiliser Sigima, consultez :" msgid ":doc:`installation` - Set up Sigima in your environment" msgstr ":doc:`installation` - Installez Sigima dans votre environnement" msgid ":doc:`features` - Explore Sigima's key features and capabilities" msgstr ":doc:`features` - Explorez les principales fonctionnalités et capacités de Sigima" msgid ":doc:`../auto_examples/index` - Practical examples showing signals and images in action" msgstr ":doc:`../auto_examples/index` - Exemples pratiques montrant les signaux et images en action" msgid ":doc:`../api/index` - Complete API reference" msgstr ":doc:`../api/index` - Référence API complète" msgid "Sigima is designed to be **GUI-independent**. If you need interactive visualization and analysis tools, check out `DataLab `_, which uses Sigima as its processing backend and adds a complete graphical interface." msgstr "Sigima est conçu pour être **indépendant de toute interface graphique**. Si vous avez besoin d'outils de visualisation et d'analyse interactifs, consultez `DataLab `_, qui utilise Sigima comme moteur de traitement et ajoute une interface graphique complète." Sigima-1.1.1/doc/release_notes/000077500000000000000000000000001514013333200163135ustar00rootroot00000000000000Sigima-1.1.1/doc/release_notes/index.rst000066400000000000000000000003711514013333200201550ustar00rootroot00000000000000Release notes ============= This section contains the release notes for all versions of :mod:`sigima`, documenting new features, improvements, bug fixes, and breaking changes. .. toctree:: :maxdepth: 1 :glob: :reversed: release_* Sigima-1.1.1/doc/release_notes/release_0.01.md000066400000000000000000000003171514013333200207140ustar00rootroot00000000000000# Version 0.1 # ## Sigima Version 0.1.0 (2025-07-06) ## This first version of the library is the result of the externalization of the signal and image processing features from the DataLab main repository. Sigima-1.1.1/doc/release_notes/release_0.02.md000066400000000000000000000005721514013333200207200ustar00rootroot00000000000000# Version 0.2 # ## Sigima Version 0.2.0 (2025-07-07) ## ⚠️ Major API changes: * Rename `sigima.computation` to `sigima.proc`. * Rename `sigima.algorithms` to `sigima.tools`. * Rename `sigima.obj` to `sigima.objects`. * Rename `sigima.param` to `sigima.params`. ℹ️ Various changes: * Add Sigima SVG logo. 🛠️ Bug fixes: * Fix API documentation and docstrings. Sigima-1.1.1/doc/release_notes/release_1.00.md000066400000000000000000001341201514013333200207140ustar00rootroot00000000000000# Version 1.0 # ## Sigima Version 1.0.6 ## 🛠️ Bug fixes: * **Compatibility with scikit-image 0.26.0+**: Fixed deprecation warnings and API compatibility issues * scikit-image 0.26.0 introduced breaking changes to `CircleModel` and `EllipseModel` APIs: old API used `model.estimate(contour)` + `model.params`, new API uses `model.from_estimate(contour)` + property-based access (`model.center`, `model.radius`, `model.axis_lengths`) * Added version-aware compatibility layer in `sigima.tools.image.preprocessing` with new helper functions `fit_circle_model()` and `fit_ellipse_model()` that handle both old and new APIs * Updated `get_contour_shapes()` in `sigima.tools.image.detection` to use compatibility functions * Updated `get_enclosing_circle()` in `sigima.tools.image.geometry` to use compatibility functions * Used `packaging.version.Version` for robust version checking instead of fragile string parsing * Eliminates deprecation warnings while maintaining backward compatibility with Python 3.9 and scikit-image < 0.26 * This closes [Issue #10](https://github.com/DataLab-Platform/Sigima/issues/10) - Sigima is not compatible with NumPy 2.4.0 and scikit-image 0.26.0 * **Compatibility with NumPy 2.4.0**: Fixed centroid computation failure with NumPy 2.4.0's new einsum optimization * NumPy 2.4.0 introduced new einsum optimization used by `scikit-image.measure.centroid()` that fails with certain ndarray types * Fixed by explicitly converting image data to basic NumPy array before calling `measure.centroid()` in `get_centroid_auto()` function * Ensures compatibility with NumPy 2.4.0+ and scikit-image 0.26.0+ without changing computational results 📦 Dependencies: * **Dependency version constraints**: Added maximum version constraints to prevent future compatibility issues * Updated dependency specifications: `NumPy >= 1.22, < 2.5`, `SciPy >= 1.10.1, < 1.17`, `scikit-image >= 0.19.2, < 0.27`, `pandas >= 1.4, < 3.0`, `PyWavelets >= 1.2, < 2.0` * New CI job `build_latest` runs scheduled tests against latest dependency versions to detect breaking changes early * Prevents automatic breakage from major dependency updates while allowing controlled upgrades after validation 🚀 CI/CD improvements: * **CI workflow enhancements**: Added automated testing against latest dependency versions * New `build_latest` job in GitHub Actions runs on schedule (weekly) and manual dispatch * Extracts dependency names from `pyproject.toml` and installs latest available versions * Provides early warning system for upcoming dependency compatibility issues * Enhanced workflow dispatch with configurable job selection for flexible testing scenarios ## Sigima Version 1.0.5 (2025-12-19) ## > ℹ️ This is a hotfix release addressing a packaging issue where French translations were missing from the previous release package. This release contains no functional changes compared to version 1.0.4 - it only ensures that the compiled translation files (.mo) are properly included in the distribution package. 🛠️ Bug fixes: * **Packaging**: Fixed missing French translation files in release package * Previous release packages were missing compiled .mo translation files, causing the application to display only English text regardless of locale settings * Updated build process to ensure all translation files are properly included in distribution packages * No functional code changes - this is purely a packaging fix to restore internationalization support ## Sigima Version 1.0.4 (2025-12-18) ## 🛠️ Bug fixes: * **Image processing: LUT range incorrectly copied to result**: Fixed processed images showing incorrect contrast because LUT range was copied from original * When processing an image (e.g., subtracting offset), the result image inherited the original's LUT range (`zscalemin`/`zscalemax`), causing incorrect visualization when data values changed significantly * Example: After subtracting ~50 lsb background from an image with LUT 50-200, the result (data range ~-5 to ~175) was still displayed with the original 50-200 LUT, making parts of the image appear clipped or invisible * Fixed by adding image-specific `dst_1_to_1`, `dst_2_to_1`, and `dst_n_to_1` wrapper functions in `sigima.proc.image.base` that reset the LUT range after copying the source image * The `ImageObj.copy()` method remains unchanged (a copy should faithfully copy all attributes) - the fix is applied at the processing layer where it belongs * Added regression test `test_image_offset_correction_lut_range` in `offset_correction_unit_test.py` * This closes [Issue #9](https://github.com/DataLab-Platform/Sigima/issues/9) - LUT range incorrectly copied when processing images * **Backwards-defined rectangular ROI causes NaN statistics**: Fixed rectangular ROI coordinate normalization when defined in reverse direction * When a rectangular ROI was drawn graphically "backwards" in DataLab (from bottom-right to top-left instead of top-left to bottom-right), statistics analysis returned NaN values * The `RectangularROI.rect_to_coords()` method was producing negative Δx and Δy values when `x1 < x0` or `y1 < y0` * Fixed by normalizing coordinates using min/max to ensure Δx and Δy are always positive * ROI mask generation now works correctly regardless of the direction in which the rectangle was drawn * Added regression test `test_backwards_drawn_rectangle` in `roi_coords_unit_test.py` * **Grid ROI - Missing spacing parameters for non-uniform grids**: Fixed grid ROI extraction to support non-uniform feature spacing * Grid ROI extraction previously assumed evenly distributed features (spacing = width/nx), which failed for images where features don't fill the entire grid area * Example: `laser_spot_array_raw.png` has laser spots spaced ~300 pixels apart, but the grid was defined over 3100×3100 pixels, causing incorrect ROI placement * Added `xstep` and `ystep` percentage parameters (1-200%, default 100%) to `ROIGridParam` to specify spacing between ROI centers * Updated `generate_image_grid_roi()` function to use separate step calculation: `dx_step = dx_cell * p.xstep / 100.0` * Position calculation now uses: `x0 = src.x0 + (ic + 0.5) * dx_step + xtrans - 0.5 * dx` (preserving backward compatibility) * Default values (100%) maintain exact original behavior for existing workflows * This allows precise ROI placement for gapped grids (e.g., laser spot arrays, sample arrays) by adjusting spacing independently of ROI size * **Signal result title formatting**: Fixed duplicate suffix in result titles for image-to-signal functions * When computing radial profile or other operations using `new_signal_result`, the suffix (e.g., center coordinates) was appearing twice in the title * Example: `radial_profile(i019)|center=(192.500, 192.500)|center=(192.500, 192.500)` instead of `radial_profile(i019)|center=(192.500, 192.500)` * The `new_signal_result` function in `sigima/proc/base.py` was adding the suffix twice: once via the formatter and once explicitly * Removed the redundant suffix addition - the formatter's `format_1_to_1_title` method already handles suffix formatting correctly * Affects functions like `radial_profile`, `histogram`, and other image-to-signal conversions * This closes [Issue #8](https://github.com/DataLab-Platform/Sigima/issues/8) - Duplicate suffix in result title when using `new_signal_result` * **HDF5 serialization with detection ROIs**: Fixed workspace save failure when images contain ROIs generated by blob detection * Saving DataLab workspace to HDF5 format failed with `NotImplementedError: cannot serialize 'rectangle' of type ` * The `store_roi_creation_metadata()` function was storing the `DetectionROIGeometry` enum directly in geometry attributes * Fixed by storing the enum's string value instead of the enum object itself * This allows proper HDF5 serialization while preserving the information needed for `apply_detection_rois()` to recreate ROIs * This closes [Issue #7](https://github.com/DataLab-Platform/Sigima/issues/7) - HDF5 Serialization Fails for Detection ROI Geometry Enum * **CSV numeric data import**: Fixed numeric columns being incorrectly interpreted as datetime values ([Issue #6](https://github.com/DataLab-Platform/Sigima/issues/6)) * When importing CSV files with large numeric values (e.g., frequencies in Hz like `4.884e+06`), the data was incorrectly converted to datetime timestamps * The `pd.to_datetime()` function was interpreting numeric values as nanoseconds since Unix epoch, corrupting the original data * Added check to skip columns with numeric dtypes in datetime detection - real datetime columns are loaded as string (`object`) dtype * Numeric data (frequencies, voltages, etc.) is now correctly preserved during CSV import 📚 Documentation: * **Parameter usage documentation**: Improved documentation for parameters requiring signal/image context ([Issue #5](https://github.com/DataLab-Platform/Sigima/issues/5)) * Added comprehensive documentation explaining the `update_from_obj()` pattern for parameters like `ZeroPadding1DParam` * Clarified that `sigima.params` is the recommended import location for all parameter classes * Enhanced `ZeroPadding1DParam` class docstring with usage example and "Important" admonition * Added new section in `sigima.params` module listing all parameters requiring `update_from_obj()` * Created new example `doc/examples/features/zero_padding.py` demonstrating proper parameter initialization * **New ROI grid example**: Added example demonstrating the grid ROI feature * Introduced `laser_spot_array.png` test image (6×6 laser spot array) to help debug an issue reported in DataLab * Created new example `doc/examples/features/roi_grid.py` showcasing the `generate_image_grid_roi()` function * Example covers: loading images, extracting sub-regions, generating ROI grids, configuring size/translation/step parameters, understanding direction labels, and extracting individual spots ## Sigima Version 1.0.3 (2025-12-03) ## 🛠️ Bug fixes: * **Signal data type validation**: Fixed integer arrays not being automatically converted to float64 * Integer input arrays are now automatically converted to float64 instead of raising errors * Validation applied consistently across all signal data setters: `set_xydata()`, `x`, `y`, `dx`, `dy` * Improves usability by accepting integer inputs (common in test data and calibration values) while maintaining computational precision * Raises clear `ValueError` for truly invalid dtypes with helpful error message listing valid types * **Signal axis calibration**: Added `replace_x_by_other_y()` function to replace signal X coordinates with Y values from another signal * Addresses missing functionality for wavelength calibration and similar use cases where calibration data is stored in a separate signal's Y values * This operation was previously impossible, even if the ambiguous X-Y mode feature existed and seemed related to this use case (but this feature performs resampling/interpolation, which is not desired here) * The new function directly uses Y arrays from both signals without interpolation, requiring signals to have the same number of points * Takes two signals: first provides Y data for output, second provides Y data to become X coordinates * Automatically transfers metadata: X label/unit from second signal's Y label/unit, Y label/unit preserved from first signal * Typical use case: spectroscopy wavelength calibration (combine absorption measurements with wavelength scale) * This closes [Issue #4](https://github.com/DataLab-Platform/Sigima/issues/4) - Missing functionality: Replace X coordinates with Y values from another signal for calibration * Signal title formatting: * **Polynomial signal titles**: Fixed polynomial signal title generation to display mathematical notation (e.g., `1+2x-3x²+4x³`) instead of verbose parameter listing (e.g., `polynomial(a0=1,a1=2,a2=-3,a3=4,a4=0,a5=0)`) * The `PolyParam.generate_title()` method now constructs proper mathematical expressions with correct sign handling, coefficient simplification (e.g., `x` instead of `1x`, `-x` instead of `-1x`), and exponent notation using `^` symbol * Improves readability in DataLab GUI and signal listings by presenting polynomials in standard mathematical form * Zero coefficients are automatically omitted from the expression (e.g., `1+x+x³` when a2=0) * Handles edge cases including all-zero polynomials (returns `"0"`), single terms, and negative coefficients * This closes [Issue #3](https://github.com/DataLab-Platform/Sigima/issues/3) - Polynomial signal titles should use mathematical notation instead of parameter listing * ROI data extraction: * Fixed `ValueError: zero-size array to reduction operation minimum which has no identity` error when computing statistics on images with ROI extending beyond canvas boundaries * The `ImageObj.get_data()` method now properly clips ROI bounding boxes to image boundaries * When a ROI is completely outside the image bounds, returns a fully masked 1x1 array (containing NaN) to avoid zero-size array errors in statistics computations * Partial overlap ROIs are correctly handled by clipping coordinates to valid image ranges * This fix ensures robust statistics computation regardless of ROI position relative to image boundaries * This closes [Issue #1](https://github.com/DataLab-Platform/Sigima/issues/1) - `ValueError` when computing statistics on ROI extending beyond image boundaries ## Sigima Version 1.0.2 (2025-11-12) ## ✨ New features and enhancements: * **New parametric image types**: Added five new parametric image generation types for testing and calibration * **Checkerboard pattern**: Alternating squares for camera calibration and spatial frequency analysis. Parameters include square size, offset, and min/max values * **Sinusoidal grating**: Frequency response testing with configurable spatial frequencies (fx, fy), phase, amplitude, and DC offset * **Ring pattern**: Concentric circular rings for radial analysis. Configurable period, width, center position, and amplitude range * **Siemens star**: Resolution testing pattern with radial spokes. Parameters include number of spokes, inner/outer radius, center position, and value range * **2D sinc function**: PSF/diffraction modeling with cardinal sine function. Configurable amplitude, center, scale factor (sigma), and DC offset * **GeometryResult.value property**: New convenience property for easy script access to computed geometry values * Supports POINT, MARKER, and SEGMENT shapes * Returns `(x, y)` tuple for POINT and MARKER shapes (both coordinates accessible) * Returns `float` length for SEGMENT shapes (calculated via `segments_lengths()`) * Return type annotation: `float | tuple[float, float]` * Provides intuitive API: unpack coordinates with `x, y = result.value` or get length with `length = result.value` * Comprehensive error handling for unsupported shapes and multi-row results * **Signal analysis functions return GeometryResult**: Changed `x_at_y()` and `y_at_x()` to return geometry results for better visualization * `x_at_y()` now returns `GeometryResult` with `MARKER` kind (previously returned `TableResult`) * `y_at_x()` now returns `GeometryResult` with `MARKER` kind (previously returned `TableResult`) * Both functions return coordinates as `[x, y]` in N×2 array format for cross marker display * Enables proper marker visualization in DataLab GUI (displayed as cross markers on plots) * Script-friendly API: use `.value` property to easily extract coordinates as `(x, y)` tuple * Example: `x, y = proxy.compute_x_at_y(params).value` provides direct access to both coordinates * Breaking change: Scripts accessing results as tables need to update to use `.value` property or `.coords` array 🛠️ Bug fixes: * Detection functions: * **Contour detection**: Removed ROI creation support from `ContourShapeParam` as it doesn't make sense for contour detection use cases. The `ContourShapeParam` class no longer inherits from `DetectionROIParam`, and the `contour_shape()` function no longer calls `store_roi_creation_metadata()`. ROI creation remains available for other detection methods (blob detection, 2D peak detection) where it is appropriate. * **ROI creation error handling**: Enhanced error handling in `create_image_roi_around_points()` function to provide clearer error messages: * Now raises `ValueError` when calculated ROI size is too small (points too close together) * Improved error messages to help users understand the cause of failures * Validates ROI geometry parameter more explicitly * Better handling of edge cases in automatic ROI sizing * Public API: * Made `BaseObj.roi_has_changed` method private (by renaming to `BaseObj.__roi_has_changed`) to avoid accidental external usage. This would interfere with the internal mask refresh mechanism that relies on controlled access to this method. The method is not part of the public API and should not be called directly by applications. ## Sigima Version 1.0.1 (2025-11-05) ## ✨ New features and enhancements: * **Detection ROI creation**: Generic mechanism for ROI creation across all detection functions * New `DetectionROIParam` parameter class providing standardized ROI creation fields * `create_rois`: Boolean flag to enable/disable ROI creation (default: False) * `roi_geometry`: Enum selecting ROI shape (RECTANGLE or CIRCLE, default: RECTANGLE) * New `DetectionROIGeometry` enum in `sigima.enums` with RECTANGLE and CIRCLE options * All detection parameter classes now inherit from `DetectionROIParam`: * `Peak2DDetectionParam`: 2D peak detection * `ContourShapeParam`: Contour shape fitting * `BlobDOGParam`, `BlobDOHParam`, `BlobLOGParam`, `BlobOpenCVParam`: Blob detection methods * `HoughCircleParam`: Hough circle detection * New `store_roi_creation_metadata()` helper function: * Stores ROI creation intent in `GeometryResult.attrs` dictionary * Called within computation functions to communicate ROI preferences * Does not violate function purity (no object modification) * New `apply_detection_rois()` helper function: * Creates ROIs on image objects based on `GeometryResult.attrs` metadata * Returns `True` if ROIs were created, `False` otherwise * Handles both rectangle and circle geometries * Automatically calculates optimal ROI size based on feature spacing * Can be called by applications outside computation functions * Metadata-based architecture maintains separation of concerns: * Computation functions remain pure (no side effects) * Applications control when/how ROIs are created * Works seamlessly with multiprocessing engines (e.g., DataLab processors) * Comprehensive test coverage with `validate_detection_rois()` helper in test suite * **Automatic `func_name` injection for result objects** * The `@computation_function` decorator now automatically injects the function name into `TableResult` and `GeometryResult` objects * When a computation function returns a result object with `func_name=None`, the decorator sets it to the function's name using `dataclasses.replace()` * Ensures systematic assignment of `func_name` for proper result tracking and display * Implementation uses direct `isinstance()` type checking for `TableResult` and `GeometryResult` * Applies to both main decorator wrapper (with DataSet parameters) and simple passthrough wrapper * Eliminates need for manual `func_name` assignment in computation functions * **Image ROI creation utility**: New `create_image_roi_around_points()` function in `sigima.objects.image.roi` * Creates rectangular or circular ROIs around a set of point coordinates * Automatically calculates optimal ROI size based on minimum distance between points * Handles boundary conditions to keep ROIs within valid image coordinates * Supports both "rectangle" and "circle" geometry types * Designed for creating ROIs around detected features (peaks, blobs, etc.) * Centralizes ROI creation logic previously duplicated across applications * **Annotations API**: New public API for managing annotations on Signal and Image objects * Added `get_annotations()` method: Returns a list of annotations in versioned JSON format * Added `set_annotations(annotations)` method: Sets annotations from a list (replaces existing annotations) * Added `add_annotation(annotation)` method: Adds a single annotation to the object * Added `clear_annotations()` method: Removes all annotations from the object * Added `has_annotations()` method: Returns True if the object has any annotations * Annotations are stored in object metadata with versioning support (currently version "1.0") * Each annotation is a dictionary with keys such as `type`, `item_class`, and `item_json` (for example) * Provides clean separation between generic annotation storage and visualization-specific details * Enables applications to manage plot annotations (shapes, labels, etc.) independently of ROIs * Fully compatible with DataLab's PlotPy adapter pattern for visualization 🛠️ Bug fixes: * **2D peak detection**: Fixed architectural violation in `peak_detection()` computation function * Removed direct ROI creation from computation function (was modifying input objects) * Computation functions decorated with `@computation_function()` must be pure (no side effects) * Removed line 128: `obj.roi = create_image_roi(...)` which violated this principle * ROI creation now handled by applications in their presentation layer * DataLab uses new `create_image_roi_around_points()` utility for this purpose * Maintains separation of concerns: Sigima computes results, applications create visual representations * Fixes regression where ROIs were not appearing in DataLab's processor-based workflow * **Parameter classes**: Removed default titles from generic `OrdinateParam` and `AbscissaParam` classes * These parameter classes are reused across multiple computation functions (e.g., `full_width_at_y`, `x_at_y`) * Default titles like "Ordinate" created redundancy when displayed with function names in analysis results * Titles are now empty by default, allowing applications to provide context-specific titles when needed * Improves clarity when the same parameter class is used by different functions * **Result HTML representation**: Improved color contrast for dark mode * Changed result title color in `to_html()` methods from standard blue (#0000FF) to a lighter shade (#5294e2) * Affects TableResult and GeometryResult HTML output * Provides better visibility in dark mode while maintaining good appearance in light mode * Improves readability when results are displayed in applications with dark themes * Fixed pulse features extraction with ROI signals. When extracting pulse features from signals with ROIs, the start/end range parameters (which apply to the full signal) were being used on ROI-extracted data, causing incorrect results. Now `extract_pulse_features()` detects when the parameter ranges are outside the ROI's x-range and automatically switches to auto-detection mode. Additionally, `extract_pulse_features()` in `sigima.tools.signal.pulse` now properly initializes `None` ranges using `get_start_range()` and `get_end_range()` with the `fraction` parameter. This ensures pulse features extracted from a signal with ROIs match the features extracted from individually extracted ROI signals. * Fixed ROI extraction for signals: ROIs are no longer incorrectly copied to destination signals when extracting ROIs. When using `extract_roi()` or `extract_rois()`, the extracted signals now have no ROI defined, which is the expected behavior since the extracted data already represents the ROI itself. This fixes the issue where extracted signals would inherit the source signal's ROI definitions. * Fixed pulse features computation to be ROI-exclusive when ROIs are defined. Previously, `TableKind.PULSE_FEATURES` incorrectly computed results for both the whole object and each ROI. This made no sense for pulse analysis, where defining ROIs indicates the presence of multiple pulses, making whole-object features irrelevant. Now `PULSE_FEATURES` correctly computes only on ROIs when they exist, otherwise on the whole object. `TableKind.STATISTICS` and `TableKind.CUSTOM` maintain the expected behavior (whole object + ROIs). * Fixed `ValueError` in `choose_savgol_window_auto()` when processing small data arrays (e.g., ROI segments). The function now properly constrains the Savitzky-Golay window length to be strictly less than the array size, as required by scipy's `mode='interp'` option. This fixes the issue when extracting pulse features from small ROI segments in signals. * Modified `RadialProfileParam` to allow initialization of the dataset even when the associated image object is not yet set (call to `update_from_obj`). This is useful when creating the parameter object before assigning the image, enabling more flexible workflows. * Removed unused `signals_to_array()` function from `sigima.proc.signal.arithmetic` module. This function was not used anywhere in the codebase and has been replaced by direct NumPy array construction in `__signals_y_to_array()` and `__signals_dy_to_array()` functions, for internal use only. * **ROI coordinate setters**: Fixed bugs in `set_physical_coords()` and `set_indices_coords()` methods * Fixed `RectangularROI.set_physical_coords()`: Now correctly stores coordinates in delta format `[x0, y0, dx, dy]` instead of corner format `[x0, y0, x1, y1]` when `indices=True` * Fixed `BaseSingleROI.set_indices_coords()`: Now correctly converts the input `coords` parameter instead of `self.coords` when `indices=False` * These methods were implemented for API completeness but were not used in the Sigima/DataLab codebase * Added comprehensive unit tests covering all ROI types (rectangular, circular, polygonal) and edge cases ## Sigima Version 1.0.0 (2025-10-28) ## ✨ New features and enhancements: * **Signals to image conversion**: New feature to combine multiple signals into a 2D image * New computation function `signals_to_image()` in `sigima.proc.signal.arithmetic` * Takes a list of signals and combines them into an image by stacking Y-arrays * Two orientation modes: * **Rows**: Each signal becomes a row in the image (default) * **Columns**: Each signal becomes a column in the image * Optional normalization: * Supports multiple normalization methods (Z-score, Min-Max, Maximum) * Normalizes each signal independently before stacking * Useful for visualizing signals with different amplitude ranges * Validates that all signals have the same size before combining * New parameter class `SignalsToImageParam` with orientation and normalization settings * New enum `SignalsToImageOrientation` for specifying row/column orientation * Comprehensive validation tests for all combinations of parameters * Ideal for creating spectrograms, heatmaps, or waterfall displays from signal collections * **Non-uniform coordinate support for images**: Added comprehensive support for non-uniform pixel coordinates * `ImageObj` now supports both uniform and non-uniform coordinate systems: * Uniform coordinates: defined by origin (`x0`, `y0`) and pixel spacing (`dx`, `dy`) * Non-uniform coordinates: defined by coordinate arrays (`xcoords`, `ycoords`) * New methods for coordinate manipulation: * `set_coords()`: Set non-uniform X and Y coordinate arrays * `is_uniform_coords`: Property to check if coordinates are uniform * New computation function `set_uniform_coords()`: Convert non-uniform to uniform coordinates * Automatically extracts uniform spacing from non-uniform arrays * Handles numerical precision issues from linspace-generated arrays * Preserves image data while transforming coordinate system * Enhanced `calibration()` function with polynomial support: * Now supports polynomial calibration up to cubic order: `dst = a0 + a1*src + a2*src² + a3*src³` * Parameter class changed from `a, b` (linear) to `a0, a1, a2, a3` (polynomial) * Works on X-axis, Y-axis (creating non-uniform coordinates), and Z-axis (data values) * Linear calibration is a special case with `a2=0, a3=0` * Automatically handles conversion between uniform and non-uniform coordinate systems * Enhanced I/O support: * HDF5 format now serializes/deserializes non-uniform coordinates * Coordinated text files support non-uniform coordinate arrays * All geometric operations updated to handle both coordinate types: * Coordinate transformations preserve or create appropriate coordinate system * ROI operations work seamlessly with both uniform and non-uniform coordinates * **DateTime support for signal data**: Added comprehensive datetime handling for signal X-axis data * Automatic detection and conversion of datetime columns when reading CSV files * Detects datetime values in the first or second column (handling index columns) * Validates datetime format and ensures reasonable date ranges (post-1900) * Converts datetime strings to float timestamps for efficient computation * Preserves datetime metadata for proper display and export * New `SignalObj` methods for datetime manipulation: * `set_x_from_datetime()`: Convert datetime objects/strings to signal X data with configurable time units (s, ms, μs, ns, min, h) * `get_x_as_datetime()`: Retrieve X values as datetime objects for display or export * `is_x_datetime()`: Check if signal contains datetime data * Enhanced CSV export to preserve datetime format when writing signals with datetime X-axis * New constants module (`sigima.objects.signal.constants`) defining datetime metadata keys and time unit conversion factors * Comprehensive unit tests covering datetime conversion, I/O roundtrip, and edge cases * Example test data file with real-world temperature/humidity logger data (`datetime.txt`) * **New client subpackage**: Migrated DataLab client functionality to `sigima.client` * Added `sigima.client.remote.SimpleRemoteProxy` for XML-RPC communication with DataLab * Added `sigima.client.base.SimpleBaseProxy` as abstract base class for DataLab proxies * Included comprehensive unit tests and API documentation * Maintains headless design principle (GUI components excluded) * Enables remote control of DataLab application from Python scripts and Jupyter notebooks * Client functionality is now directly accessible: `from sigima import SimpleRemoteProxy` * **New image ROI feature**: Added inverse ROI functionality for image ROIs * Added `inside` parameter to `BaseSingleImageROI` base class, inherited by all image ROI types (`PolygonalROI`, `RectangularROI`, `CircularROI`) * When `inside=True`, ROI represents the region inside the shape (inverted behavior) * When `inside=False` (default), ROI represents the region outside the shape (original behavior) * Fully integrated with serialization (`to_dict`/`from_dict`) and parameter conversion (`to_param`/`from_param`) * Signal ROIs (`SegmentROI`) are unaffected as the concept doesn't apply to 1D intervals * Optimal architecture with zero code duplication - all `inside` functionality implemented once in the base class * Individual ROI classes no longer need custom constructors, inheriting directly from base class * New image operation: * Convolution. * New image format support: * **Coordinated text image files**: Added support for reading coordinated text files (`.txt` extension), similar to the Matris image format. * Supports both real and complex-valued image data with optional error images. * Automatically handles NaN values in the data. * Reads metadata including units (X, Y, Z) and labels from file headers. * New image analysis features: * Horizontal and vertical projections * Compute the horizontal projection profile by summing values along the y-axis (`sigima.proc.image.measurement.horizontal_projection`). * Compute the vertical projection profile by summing values along the x-axis (`sigima.proc.image.measurement.vertical_projection`). * **New curve fitting algorithms**: Complete curve fitting framework with `sigima.tools.signal.fitting` module: * **Core fitting functions**: Comprehensive set of curve fitting algorithms for scientific data analysis: * `linear_fit`: Linear regression fitting * `polynomial_fit`: Polynomial fitting with configurable degree * `gaussian_fit`: Gaussian profile fitting for peak analysis * `lorentzian_fit`: Lorentzian profile fitting for spectroscopy * `voigt_fit`: Voigt profile fitting (convolution of Gaussian and Lorentzian profiles) * `exponential_fit`: Single exponential fitting with overflow protection * `piecewiseexponential_fit`: Piecewise exponential (raise-decay) fitting with advanced parameter estimation * `planckian_fit`: Planckian (blackbody radiation) fitting with correct physics implementation * `twohalfgaussian_fit`: Asymmetric peak fitting with separate left/right parameters * `multilorentzian_fit`: Multi-peak Lorentzian fitting for complex spectra * `sinusoidal_fit`: Sinusoidal fitting with FFT-based frequency estimation * `cdf_fit`: Cumulative Distribution Function fitting using error function * `sigmoid_fit`: Sigmoid (logistic) function fitting for S-shaped curves * **Advanced piecewise exponential (raise-decay) fitting**: Enhanced algorithm with: * Standard piecewise exponential model: `y = a_left*exp(b_left*x) + a_right*exp(b_right*x) + y0` * Multi-start optimization strategy for robust convergence to global minimum * Support for both positive and negative exponential rates (growth and decay components) * Comprehensive parameter bounds validation to prevent optimization errors * **Enhanced asymmetric peak fitting**: Advanced `twohalfgaussian_fit` with: * Separate baseline offsets for left and right sides (`y0_left`, `y0_right`) * Independent amplitude parameters (`amp_left`, `amp_right`) for better asymmetric modeling * Robust baseline estimation using percentile-based methods * **Technical features**: All fitting functions include: * Automatic initial parameter estimation from data characteristics * Proper bounds enforcement ensuring optimization stability * Comprehensive error handling and parameter validation * Consistent dataclass-based parameter structures * Full test coverage with synthetic and experimental data validation * New common signal/image feature: * Added `phase` (argument) feature to extract the phase information from complex signals or images. * Added operation to create complex-valued signal/image from real and imaginary parts. * Added operation to create complex-valued signal/image from magnitude and phase. * Standard deviation of the selected signals or images (this complements the "Average" feature). * Generate new signal or image: Poisson noise. * Add noise to the selected signals or images. * Gaussian, Poisson or uniform noise can be added. * New utility functions to generate file basenames. * Deconvolution in the frequency domain. * New ROI features: * Improved single ROI title handling, using default title based on the index of the ROI when no title is provided. * Added `combine_with` method to ROI objects (`SignalROI` and `ImageROI`) to return a new ROI that combines the current ROI with another one (union) and handling duplicate ROIs. * Image ROI transformations: * Before this change, image ROI were removed after applying each single computation function. * Now, the geometry computation functions preserve the ROI information across transformations: the transformed ROIs are automatically updated in the image object. * Image ROI coordinates: * Before this change, image ROI coordinates were defined using indices by default. * Now, `ROI2DParam` uses physical coordinates by default. * Note that ROI may still be defined using indices instead (using `create_image_roi` function). * Image ROI grid: * New `generate_image_grid_roi` function: create a grid of ROIs from an image, with customizable parameters for grid size, spacing, and naming. * This function allows for easy extraction of multiple ROIs from an image in a structured manner. * Parameters are handled via the `ROIGridParam` class, which provides a convenient way to specify grid properties: * `nx` / `ny`: Number of grid cells in the X/Y direction. * `xsize` / `ysize`: Size of each grid cell in pixels. * `xtranslation` / `ytranslation`: Translation of the grid in pixels. * `xdirection` / `ydirection`: Direction of the grid (increasing/decreasing). * New image processing features: * New "2D resampling" feature: * This feature allows to resample 2D images to a new coordinate grid using interpolation. * It supports two resampling modes: pixel size and output shape. * Multiple interpolation methods are available: linear, cubic, and nearest neighbor. * The `fill_value` parameter controls how out-of-bounds pixels are handled, with support for numeric values or NaN. * Automatic data type conversion ensures proper NaN handling for integer images. * It is implemented in the `sigima.proc.image.resampling` function with parameters defined in `Resampling2DParam`. * New "Frequency domain Gaussian filter" feature: * This feature allows to filter an image in the frequency domain using a Gaussian filter. * It is implemented in the `sigima.proc.image.frequency_domain_gaussian_filter` function. * New "Erase" feature: * This feature allows to erase an area of the image using the mean value of the image. * It is implemented in the `sigima.proc.image.erase` function. * The erased area is defined by a region of interest (ROI) parameter set. * Example usage: ```python import numpy as np import sigima.objects as sio import sigima.proc.image as sipi obj = sio.create_image("test_image", data=np.random.rand(1024, 1024)) p = sio.ROI2DParam.create(x0=600, y0=800, width=300, height=200) dst = sipi.erase(obj, p) ``` * By default, pixel binning changes the pixel size. * Improved centroid estimation: * New `get_centroid_auto` method implements an adaptive strategy that chooses between the Fourier-based centroid and a more robust fallback (scikit-image), based on agreement with a projected profile-based reference. * Introduced `get_projected_profile_centroid` function for robust estimation via 1D projections (median or barycentric), offering high accuracy even with truncated or noisy images. * These changes improve centroid accuracy and stability in edge cases (e.g. truncated disks or off-center spots), while preserving noise robustness. * See [DataLab issue #251](https://github.com/DataLab-Platform/DataLab/issues/251) for more details. * New signal processing features: * New "Brick wall filter" feature: * This feature allows to filter a signal in the frequency domain using an ideal ("brick wall") filter. * It is implemented in `sigima.proc.signal.frequency_filter`, along the other frequency domain filtering features (`Bessel`, `Butterworth`, etc.). * Enhanced zero padding to support prepend and append. Change default strategy to next power of 2. * **Pulse analysis algorithms**: Comprehensive pulse feature extraction framework in `sigima.tools.signal.pulse` module: * **Core pulse analysis functions**: Complete set of algorithms for step and square pulse characterization: * `extract_pulse_features`: Main function for automated pulse feature extraction * `heuristically_recognize_shape`: Intelligent signal type detection (step, square, or other) * `detect_polarity`: Robust polarity detection using baseline analysis * **Advanced timing parameter extraction**: Precise measurement algorithms for: * Rise and fall time calculations with configurable start/stop ratios (e.g., 10%-90%) * Timing parameters at specific fractions (x10, x50, x90, x100) of signal amplitude * Full width at half maximum (FWHM) computation for square pulses * Foot duration measurement for pulse characterization * **Baseline analysis capabilities**: Statistical methods for: * Automatic baseline range detection from signal extremes * Robust baseline level estimation using mean values within ranges * Start and end baseline characterization for differential analysis * **Signal validation and error handling**: Comprehensive input validation with: * Data array consistency checks and NaN/infinity detection * Signal length validation and range boundary verification * Graceful error handling with descriptive exception messages * **PulseFeatures dataclass**: Structured result container with all extracted parameters: * Amplitude, polarity, and offset measurements * Timing parameters (rise_time, fall_time, fwhm, x10, x50, x90, x100) * Baseline ranges (xstartmin, xstartmax, xendmin, xendmax) * Signal shape classification and foot duration * Implementation leverages robust statistical methods and provides both high-level convenience functions and low-level building blocks for custom pulse analysis workflows. * Comprehensive uncertainty propagation implementation: * Added mathematically correct uncertainty propagation to ~15 core signal processing functions. * Enhanced `Wrap1to1Func` class to handle uncertainty propagation for mathematical functions (`sqrt`, `log10`, `exp`, `clip`, `absolute`, `real`, `imag`). * Implemented uncertainty propagation for arithmetic operations (`product_constant`, `division_constant`). * Added uncertainty propagation for advanced processing functions (`power`, `normalize`, `derivative`, `integral`, `calibration`). * All implementations use proper error propagation formulas with numerical stability handling (NaN/infinity protection). * Optimized for memory efficiency by leveraging `dst_1_to_1` automatic uncertainty copying and in-place modifications. * Maintains backward compatibility with existing signal processing workflows. * New 2D ramp image generator: * This feature allows to generate a 2D ramp image: z = a(x − x₀) + b(y − y₀) + c * It is implemented in the `sigima.objects.Ramp2DParam` parameter class. * Example usage: ```python import sigima.objects as sio param = sio.Ramp2DParam.create(width=100, height=100, a=1.0, b=2.0) image = sio.create_image_from_param(param) ``` * New signal generators: linear chirp, logistic function, Planck function. * New image "Extent" computed parameters: * Added computed parameters for image extent: `xmin`, `xmax`, `ymin`, and `ymax`. * These parameters are automatically calculated based on the image origin, pixel spacing, and dimensions. * They provide the physical coordinate boundaries of the image for enhanced spatial analysis. * New I/O features: * Added HDF5 format for signal and image objects (extensions `.h5sig` and `.h5ima`) that may be opened with any HDF5 viewer. * Added support for MCA (Multi-Channel Analyzer) spectrum file format: * Reading MCA files (`.mca` extension) commonly used in spectroscopy and radiation detection * Automatically extracts spectrum data and calibration information * Supports energy calibration with interpolation for accurate X-axis values * Parses metadata from multiple sections (PMCA SPECTRUM, DPP STATUS, CALIBRATION) * Handles various encoding formats (UTF-8, Latin-1, CP1252) for maximum compatibility * Added support for FT-Lab signal and image format. * Added functions to read and write metadata and ROIs in JSON format: * `sigima.io.read_metadata` and `sigima.io.write_metadata` for metadata. * `sigima.io.read_roi` and `sigima.io.write_roi` for ROIs. * Added convenience I/O functions `write_signals` and `write_images` with `SaveToDirectoryParam` support: * These functions enable batch saving of multiple signal or image objects to a directory with configurable naming patterns. * `SaveToDirectoryParam` provides control over file basenames (with Python format string support), extensions, directory paths, and overwrite behavior. * Automatic filename conflict resolution ensures unique filenames when duplicates would occur. * Enhanced workflow efficiency for processing and saving multiple objects in batch operations. ✨ Core architecture update: scalar result types * Introduced two new immutable result types: `TableResult` and `GeometryResult`, replacing the legacy `ResultProperties` and `ResultShape` objects. * These new result types are computation-oriented and free of application-specific logic (e.g., Qt, metadata), enabling better separation of concerns and future reuse. * Added a `TableResultBuilder` utility to incrementally define tabular computations (e.g., statistics on signals or images) and generate a `TableResult` object. * All metadata-related behaviors of former result types have been migrated to the DataLab application layer. * Removed obsolete or tightly coupled features such as `from_metadata_entry()` and `transform_shapes()` from the Sigima core. * This refactoring greatly improves modularity, testability, and the clarity of the scalar computation API. 🛠️ Bug fixes: * Fix how data is managed in signal objects (`SignalObj`): * Signal data is stored internally as a 2D array with shape `(2, n)`, where the first row is the x data and the second row is the y data: that is the `xydata` attribute. * Because of this, when storing complex Y data, the data type is propagated to the x data, which is not always desired. * As a workaround, the `x` property now returns the real part of the x data. * Furthermore, the `get_data` method now returns a tuple of numpy arrays instead of a single array, allowing to access both x and y data separately, keeping the original data type. * Fix ROI conversion between physical and indices coordinates: * The conversion between physical coordinates and indices has been corrected (half pixel error was removed). * The `indices_to_physical` and `physical_to_indices` methods now raise a `ValueError` if the input does not contain an even number of elements (x, y pairs). 🔒 Security fixes: * **Dependency vulnerability fix**: Fixed CVE-2023-4863 vulnerability in opencv-python-headless * Updated minimum requirement from 4.5.4.60 to 4.8.1.78 * Addresses libwebp binaries vulnerability in bundled OpenCV wheels * See [DataLab security advisory](https://github.com/DataLab-Platform/DataLab/security/dependabot/1) for details Sigima-1.1.1/doc/release_notes/release_1.01.md000066400000000000000000000052461514013333200207230ustar00rootroot00000000000000# Version 1.1 # ## Sigima Version 1.1.1 (2026-02-02) ## ### 🛠️ Bug Fixes since version 1.1.0 ### * **Stub server**: Added missing Web API control methods to `DataLabStubServer` for testing DataLab's REST API integration * Added `start_webapi_server()` stub (returns dummy URL and token) * Added `stop_webapi_server()` stub * Added `get_webapi_status()` stub (returns server status dictionary) ### 🔧 Other changes ### * Updated development status classifier to "Production/Stable" * Added "Try it Online" section with [notebook.link](https://notebook.link/) integration in documentation ## Sigima Version 1.1.0 (2026-01-31) ## ✨ New features and enhancements: * **Stub server**: Added missing methods to `DataLabStubServer` to support new DataLab features * Added `remove_object()` method (removes an object from DataLab) * Added `call_method()` method (simulates calling a method on DataLab's main interface or panels) * **Test infrastructure**: Refactored visualization code in test suite for better maintainability * Centralized PlotPy visualization utilities in `sigima.viz` module * Added standardized helper functions: `create_curve()`, `create_image()`, `create_circle()`, `create_segment()`, `create_cursor()`, `create_marker()`, and `create_contour_shapes()` * Updated all interactive test functions to use the new unified API instead of direct PlotPy builder calls * Improved code consistency across signal and image test modules * **Visualization backend flexibility**: Added support for Matplotlib as an alternative to PlotPy for test visualizations * New configuration option `viz_backend` to select visualization library ("auto", "plotpy", or "matplotlib") * Environment variable `SIGIMA_VIZ_BACKEND` can override configuration * Automatic fallback from PlotPy to Matplotlib when PlotPy is not available * Backend information exposed via `sigima.viz.BACKEND_NAME` and `BACKEND_SOURCE` * Matplotlib backend provides stubs for unsupported functions (raises `NotImplementedError`) * Unit test ensures API compatibility between backends * **Jupyter notebook HTML representation**: Added rich HTML display for Sigima objects in Jupyter notebooks * `SignalObj` displays shape, dtype, X/Y ranges, axis labels, and title in a formatted table * `ImageObj` displays shape, dtype, value range, origin, pixel spacing, extent, axis labels, and title * ROI objects (`BaseSingleROI`, `BaseROI`) display their geometric properties * `BaseCoordinates` and derived classes display point coordinates * `TableResult` and `GeometryResult` display result data with source object information * Centralized CSS styling in `HTML_TABLE_CSS` constant for consistent appearance Sigima-1.1.1/doc/remote_example.ipynb000066400000000000000000000071631514013333200175430ustar00rootroot00000000000000{ "cells": [ { "cell_type": "markdown", "id": "76b9af91-1233-485b-a616-826a8ccfcbc8", "metadata": {}, "source": [ "DataLab remote control example\n", "==============================\n", "\n", "Example of remote control of DataLab current session, from a simple notebook, using the `SimpleRemoteProxy` class provided in the `sigima.client` module.\n", "\n", "The only requirement is to install the *Sigima* package (using `pip install sigima`, for example)." ] }, { "cell_type": "code", "execution_count": null, "id": "47c889ba-ca07-46dd-bec0-b08d67bd1eb2", "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "from sigima.client import SimpleRemoteProxy\n", "proxy = SimpleRemoteProxy()" ] }, { "cell_type": "markdown", "id": "721d52f6-2df8-4559-89d2-f7088a5e2ee2", "metadata": {}, "source": [ "Connecting to DataLab current session:" ] }, { "cell_type": "code", "execution_count": 20, "id": "1de8616a-619c-4d5b-869f-fb41cf72b7cf", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Connecting to DataLab XML-RPC server...OK (port: 62547)\n" ] } ], "source": [ "proxy.connect()" ] }, { "cell_type": "markdown", "id": "9246a105-d73d-4ba3-81e1-4fadd042a4c6", "metadata": {}, "source": [ "Executing commands in DataLab:" ] }, { "cell_type": "code", "execution_count": 21, "id": "ccdddb07-cc54-42dd-b744-751516ae73d9", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "z = np.random.rand(20, 20)\n", "proxy.add_image(\"toto\", z)" ] }, { "cell_type": "code", "execution_count": 22, "id": "7216fc12-2675-48ff-a62a-64b5516c2e09", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "x = np.array([1.0, 2.0, 3.0])\n", "y = np.array([4.0, 5.0, -1.0])\n", "proxy.add_signal(\"toto\", x, y)" ] }, { "cell_type": "code", "execution_count": null, "id": "4a094ecb-5314-42d8-be60-0ce419275e8f", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "proxy.calc(\"derivative\")" ] }, { "cell_type": "code", "execution_count": 24, "id": "94fc3b6d-8d4a-40d6-ad34-9ecb4888db58", "metadata": {}, "outputs": [], "source": [ "proxy.set_current_panel(\"image\")" ] }, { "cell_type": "code", "execution_count": null, "id": "2b0b4fc7-c282-4c2c-bb57-6df3241524ce", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "proxy.calc(\"fft\")" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.6" } }, "nbformat": 4, "nbformat_minor": 5 } Sigima-1.1.1/doc/requirements.rst000066400000000000000000000074721514013333200167520ustar00rootroot00000000000000The `sigima` package requires the following Python modules: .. list-table:: :header-rows: 1 :align: left * - Name - Version - Summary * - Python - >=3.9, <4 - Python programming language * - guidata - >= 3.13 - Automatic GUI generation for easy dataset editing and display * - NumPy - >= 1.22, < 2.5 - Fundamental package for array computing in Python * - SciPy - >= 1.10.1, < 1.17 - Fundamental algorithms for scientific computing in Python * - scikit-image - >= 0.19.2, < 0.27 - Image processing in Python * - pandas - >= 1.4, < 3.0 - Powerful data structures for data analysis, time series, and statistics * - PyWavelets - >= 1.2, < 2.0 - PyWavelets, wavelet transform module * - packaging - >= 21.3 - Core utilities for Python packages * - typing-extensions - >= 4.0 - Backported and Experimental Type Hints for Python 3.9+ * - makefun - >= 1.13.1 - Small library to dynamically create python functions. Optional modules for GUI support (Qt): .. list-table:: :header-rows: 1 :align: left * - Name - Version - Summary * - qtpy - - Provides an abstraction layer on top of the various Qt bindings (PyQt5/6 and PySide2/6). * - PyQt5 - - Python bindings for the Qt cross platform application toolkit * - plotpy - - Curve and image plotting tools for Python/Qt applications Optional modules for development: .. list-table:: :header-rows: 1 :align: left * - Name - Version - Summary * - build - - A simple, correct Python build frontend * - babel - - Internationalization utilities * - ruff - - An extremely fast Python linter and code formatter, written in Rust. * - pylint - - python code static checker * - Coverage - - Code coverage measurement for Python * - pre-commit - - A framework for managing and maintaining multi-language pre-commit hooks. Optional modules for building the documentation: .. list-table:: :header-rows: 1 :align: left * - Name - Version - Summary * - sphinx - - Python documentation generator * - sphinx-gallery - - A Sphinx extension that builds an HTML gallery of examples from any set of Python scripts. * - sphinx_intl - - Sphinx utility that make it easy to translate and to apply translation. * - myst_parser - - An extended [CommonMark](https://spec.commonmark.org/) compliant parser, * - myst-nb - - A Jupyter Notebook Sphinx reader built on top of the MyST markdown parser. * - sphinx_design - - A sphinx extension for designing beautiful, view size responsive web components. * - sphinx-copybutton - - Add a copy button to each of your code cells. * - pydata-sphinx-theme - - Bootstrap-based Sphinx theme from the PyData community * - qtpy - - Provides an abstraction layer on top of the various Qt bindings (PyQt5/6 and PySide2/6). * - PyQt5 - - Python bindings for the Qt cross platform application toolkit * - plotpy - - Curve and image plotting tools for Python/Qt applications * - matplotlib - - Python plotting package * - opencv-python-headless - >= 4.8.1.78 - Wrapper package for OpenCV python bindings. Optional modules for running test suite: .. list-table:: :header-rows: 1 :align: left * - Name - Version - Summary * - pytest - - pytest: simple powerful testing with Python * - pytest-xvfb - - A pytest plugin to run Xvfb (or Xephyr/Xvnc) for tests.Sigima-1.1.1/doc/simple_example.ipynb000066400000000000000000003422751514013333200175470ustar00rootroot00000000000000{ "cells": [ { "cell_type": "markdown", "id": "dbaa17fc", "metadata": {}, "source": [ "# Prepare data and compute processing feature\n", "\n", "Demonstration of using Regions of Interest (ROIs) in image processing with **Sigima**" ] }, { "cell_type": "code", "execution_count": null, "id": "d64b7637", "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import sigima.objects\n", "import sigima.proc.image\n", "\n", "# Generating a noisy image\n", "data = np.random.normal(100, 30, (100, 100))\n", "\n", "# Applying Gaussian filter on the image with the defined ROI\n", "image = sigima.objects.create_image(\"Noisy\", data)\n", "image.roi = sigima.objects.create_image_roi(\"circle\", [30, 30, 20])\n", "result = sigima.proc.image.gaussian_filter(image, sigma=5.0)\n", "result" ] }, { "cell_type": "markdown", "id": "d0ca49c4", "metadata": {}, "source": [ "# Display results\n", "\n", "ℹ️ The following code use `viz` Matplotlib backend which has been introduced in Sigima V1.1\n", "> Sigima V1.0 uses an internal version of `viz` for image display based on PlotPy (`tests.vistools`)." ] }, { "cell_type": "code", "execution_count": null, "id": "fbcd89cd", "metadata": {}, "outputs": [], "source": [ "from sigima.config import options\n", "\n", "# This is only needed if you have both Matplotlib and PlotPy installed\n", "options.viz_backend.set(\"matplotlib\")" ] }, { "cell_type": "code", "execution_count": null, "id": "c2699c37", "metadata": {}, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from sigima import viz\n", "\n", "# Display results with Matplotlib\n", "viz.view_images([image, result])" ] }, { "cell_type": "code", "execution_count": null, "id": "7c284933", "metadata": {}, "outputs": [], "source": [ "# Show ROI on the original image\n", "image.roi" ] }, { "cell_type": "code", "execution_count": null, "id": "f754e7a8", "metadata": {}, "outputs": [], "source": [ "# Get statistics of the original image within the ROI\n", "sigima.proc.image.stats(image)" ] } ], "metadata": { "kernelspec": { "display_name": ".venv", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.6" } }, "nbformat": 4, "nbformat_minor": 5 } Sigima-1.1.1/doc/user_guide/000077500000000000000000000000001514013333200156165ustar00rootroot00000000000000Sigima-1.1.1/doc/user_guide/features.rst000066400000000000000000000577141514013333200202040ustar00rootroot00000000000000.. _features: Features ======== Sigima provides a comprehensive suite of signal and image processing computational features organized into logical categories. This page provides an organized overview of all available computation functions with direct links to their API documentation. .. note:: All computation functions are available in the :mod:`sigima.proc` module. The :mod:`sigima.tools` modules provide lower-level utility functions used internally by the proc functions. Common Operations ----------------- These operations are available for both signals and images with similar functionality. Arithmetic Operations ~~~~~~~~~~~~~~~~~~~~~ .. list-table:: :header-rows: 1 :widths: 25 25 50 * - Signal Functions - Image Functions - Description * - :func:`addition ` - :func:`addition ` - Add two signals/images * - :func:`difference ` - :func:`difference ` - Subtract one signal/image from another * - :func:`product ` - :func:`product ` - Multiply two signals/images * - :func:`division ` - :func:`division ` - Divide one signal/image by another * - :func:`average ` - :func:`average ` - Compute average of multiple signals/images * - :func:`standard_deviation ` - :func:`standard_deviation ` - Compute standard deviation of multiple signals/images * - :func:`quadratic_difference ` - :func:`quadratic_difference ` - Compute quadratic difference between signals/images * - :func:`arithmetic ` - :func:`arithmetic ` - Generic arithmetic operations with parameters Constant Operations ~~~~~~~~~~~~~~~~~~~ .. list-table:: :header-rows: 1 :widths: 25 25 50 * - Signal Functions - Image Functions - Description * - :func:`addition_constant ` - :func:`addition_constant ` - Add a constant value to signal/image * - :func:`difference_constant ` - :func:`difference_constant ` - Subtract a constant from signal/image * - :func:`product_constant ` - :func:`product_constant ` - Multiply signal/image by a constant * - :func:`division_constant ` - :func:`division_constant ` - Divide signal/image by a constant Mathematical Operations ~~~~~~~~~~~~~~~~~~~~~~~ .. list-table:: :header-rows: 1 :widths: 25 25 50 * - Signal Functions - Image Functions - Description * - :func:`absolute ` - :func:`absolute ` - Compute absolute value * - :func:`exp ` - :func:`exp ` - Exponential function * - :func:`log10 ` - :func:`log10 ` - Base-10 logarithm * - :func:`inverse ` - :func:`inverse ` - Compute reciprocal * - :func:`real ` - :func:`real ` - Extract real part of complex data * - :func:`imag ` - :func:`imag ` - Extract imaginary part of complex data * - :func:`phase ` - :func:`phase ` - Extract phase of complex data * - :func:`astype ` - :func:`astype ` - Convert data type * - :func:`transpose ` - :func:`transpose ` - Transpose coordinates/axes * - N/A - :func:`log10_z_plus_n ` - Log10 with offset for zero handling Signal-Specific Mathematical Operations ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. list-table:: :header-rows: 1 :widths: 50 50 * - Function - Description * - :func:`sqrt ` - Square root * - :func:`power ` - Raise to power * - :func:`to_cartesian ` - Convert to Cartesian coordinates * - :func:`to_polar ` - Convert to polar coordinates Complex Number Operations ~~~~~~~~~~~~~~~~~~~~~~~~~ .. list-table:: :header-rows: 1 :widths: 25 25 50 * - Signal Functions - Image Functions - Description * - :func:`complex_from_real_imag ` - :func:`complex_from_real_imag ` - Create complex data from real and imaginary parts * - :func:`complex_from_magnitude_phase ` - :func:`complex_from_magnitude_phase ` - Create complex data from magnitude and phase Fourier Analysis ~~~~~~~~~~~~~~~~ .. list-table:: :header-rows: 1 :widths: 25 25 50 * - Signal Functions - Image Functions - Description * - :func:`fft ` - :func:`fft ` - Fast Fourier Transform (1D/2D) * - :func:`ifft ` - :func:`ifft ` - Inverse Fast Fourier Transform (1D/2D) * - :func:`magnitude_spectrum ` - :func:`magnitude_spectrum ` - Magnitude spectrum * - :func:`phase_spectrum ` - :func:`phase_spectrum ` - Phase spectrum * - :func:`psd ` - :func:`psd ` - Power spectral density Convolution Operations ~~~~~~~~~~~~~~~~~~~~~~ .. list-table:: :header-rows: 1 :widths: 25 25 50 * - Signal Functions - Image Functions - Description * - :func:`convolution ` - :func:`convolution ` - Convolution operation * - :func:`deconvolution ` - :func:`deconvolution ` - Deconvolution operation Filtering ~~~~~~~~~ .. list-table:: :header-rows: 1 :widths: 25 25 50 * - Signal Functions - Image Functions - Description * - :func:`gaussian_filter ` - :func:`gaussian_filter ` - Gaussian smoothing filter * - :func:`moving_average ` - :func:`moving_average ` - Moving average filter * - :func:`moving_median ` - :func:`moving_median ` - Moving median filter * - :func:`wiener ` - :func:`wiener ` - Wiener filter Noise Addition ~~~~~~~~~~~~~~ .. list-table:: :header-rows: 1 :widths: 25 25 50 * - Signal Functions - Image Functions - Description * - :func:`add_gaussian_noise ` - :func:`add_gaussian_noise ` - Add Gaussian noise for testing * - :func:`add_poisson_noise ` - :func:`add_poisson_noise ` - Add Poisson noise for testing * - :func:`add_uniform_noise ` - :func:`add_uniform_noise ` - Add uniform noise for testing Signal Conditioning ~~~~~~~~~~~~~~~~~~~~ .. list-table:: :header-rows: 1 :widths: 25 25 50 * - Signal Functions - Image Functions - Description * - :func:`normalize ` - :func:`normalize ` - Normalize amplitude/intensity values * - :func:`clip ` - :func:`clip ` - Clip values to specified range * - :func:`offset_correction ` - :func:`offset_correction ` - Remove DC offset/background Region of Interest (ROI) ~~~~~~~~~~~~~~~~~~~~~~~~~ .. list-table:: :header-rows: 1 :widths: 25 25 50 * - Signal Functions - Image Functions - Description * - :func:`extract_roi ` - :func:`extract_roi ` - Extract single ROI from data * - :func:`extract_rois ` - :func:`extract_rois ` - Extract multiple ROIs from data Calibration ~~~~~~~~~~~ .. list-table:: :header-rows: 1 :widths: 25 25 50 * - Signal Functions - Image Functions - Description * - :func:`calibration ` - :func:`calibration ` - Apply coordinate system calibration Signal Processing ----------------- Array Operations ~~~~~~~~~~~~~~~~ .. list-table:: :header-rows: 1 :widths: 30 70 * - Function - Description * - :func:`signals_to_image ` - Convert signals to image representation Frequency Filtering ~~~~~~~~~~~~~~~~~~~ .. list-table:: :header-rows: 1 :widths: 30 70 * - Function - Description * - :func:`lowpass ` - Low-pass filter * - :func:`highpass ` - High-pass filter * - :func:`bandpass ` - Band-pass filter * - :func:`bandstop ` - Band-stop filter * - :func:`frequency_filter ` - Generic frequency filtering Signal Conditioning & Processing ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. list-table:: :header-rows: 1 :widths: 30 70 * - Function - Description * - :func:`detrending ` - Remove linear trend * - :func:`apply_window ` - Apply windowing function * - :func:`resampling ` - Resample signal * - :func:`interpolate ` - Interpolate signal * - :func:`reverse_x ` - Reverse x-axis order * - :func:`xy_mode ` - Handle XY coordinate modes * - :func:`replace_x_by_other_y ` - Replace X axis using another signal's Y values * - :func:`zero_padding ` - Zero-padding for signals Signal Analysis ~~~~~~~~~~~~~~~ .. list-table:: :header-rows: 1 :widths: 30 70 * - Function - Description * - :func:`stats ` - Statistical measurements * - :func:`histogram ` - Compute signal histogram * - :func:`contrast ` - Compute signal contrast * - :func:`derivative ` - Compute signal derivative * - :func:`integral ` - Compute signal integral * - :func:`sampling_rate_period ` - Analyze sampling rate and period Peak and Feature Detection ~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. list-table:: :header-rows: 1 :widths: 30 70 * - Function - Description * - :func:`peak_detection ` - Peak detection in signals * - :func:`bandwidth_3db ` - 3dB bandwidth measurement * - :func:`fwhm ` - Full Width at Half Maximum * - :func:`fw1e2 ` - Full Width at 1/e² * - :func:`full_width_at_y ` - Full width at custom level * - :func:`dynamic_parameters ` - Dynamic range parameters * - :func:`x_at_y ` - Find x-coordinates at given y-value * - :func:`y_at_x ` - Find y-values at given x-coordinate * - :func:`x_at_minmax ` - Find x-coordinates of extrema Curve Fitting ~~~~~~~~~~~~~~ .. list-table:: :header-rows: 1 :widths: 30 70 * - Function - Description * - :func:`linear_fit ` - Linear regression * - :func:`polynomial_fit ` - Polynomial fitting * - :func:`gaussian_fit ` - Gaussian curve fitting * - :func:`lorentzian_fit ` - Lorentzian curve fitting * - :func:`voigt_fit ` - Voigt profile fitting * - :func:`twohalfgaussian_fit ` - Two-half Gaussian fitting * - :func:`exponential_fit ` - Exponential decay fitting * - :func:`piecewiseexponential_fit ` - Piecewise exponential fitting * - :func:`sigmoid_fit ` - Sigmoid curve fitting * - :func:`sinusoidal_fit ` - Sinusoidal fitting * - :func:`planckian_fit ` - Planckian (blackbody) fitting * - :func:`cdf_fit ` - Cumulative distribution function fitting * - :func:`evaluate_fit ` - Evaluate fitted function * - :func:`extract_fit_params ` - Extract fitting parameters Stability Analysis ~~~~~~~~~~~~~~~~~~ .. list-table:: :header-rows: 1 :widths: 30 70 * - Function - Description * - :func:`allan_variance ` - Allan variance * - :func:`allan_deviation ` - Allan deviation * - :func:`modified_allan_variance ` - Modified Allan variance * - :func:`overlapping_allan_variance ` - Overlapping Allan variance * - :func:`hadamard_variance ` - Hadamard variance * - :func:`time_deviation ` - Time deviation * - :func:`total_variance ` - Total variance Pulse Analysis ~~~~~~~~~~~~~~ .. list-table:: :header-rows: 1 :widths: 30 70 * - Function - Description * - :func:`extract_pulse_features ` - Extract comprehensive pulse characteristics Utility Functions ~~~~~~~~~~~~~~~~~ .. list-table:: :header-rows: 1 :widths: 30 70 * - Function - Description * - :func:`check_same_sample_rate ` - Verify consistent sampling rates * - :func:`get_nyquist_frequency ` - Calculate Nyquist frequency Image Processing ---------------- Geometry and Transformations ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. list-table:: :header-rows: 1 :widths: 30 70 * - Function - Description * - :func:`rotate ` - Rotate image by arbitrary angle * - :func:`rotate90 ` - Rotate image 90° clockwise * - :func:`rotate270 ` - Rotate image 270° clockwise * - :func:`fliph ` - Flip image horizontally * - :func:`flipv ` - Flip image vertically * - :func:`translate ` - Translate image by specified offset * - :func:`resize ` - Resize image to specified dimensions * - :func:`resampling ` - Resample image with different methods * - :func:`binning ` - Reduce image size by binning pixels * - :func:`set_uniform_coords ` - Set uniform coordinate system * - :data:`transformer ` - Apply custom geometric transformations Frequency Domain Filtering ~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. list-table:: :header-rows: 1 :widths: 30 70 * - Function - Description * - :func:`butterworth ` - Butterworth frequency filter * - :func:`gaussian_freq_filter ` - Gaussian frequency filter Edge Detection ~~~~~~~~~~~~~~ .. list-table:: :header-rows: 1 :widths: 30 70 * - Function - Description * - :func:`sobel ` - Sobel edge detector * - :func:`sobel_h ` - Sobel horizontal edges * - :func:`sobel_v ` - Sobel vertical edges * - :func:`scharr ` - Scharr edge detector * - :func:`scharr_h ` - Scharr horizontal edges * - :func:`scharr_v ` - Scharr vertical edges * - :func:`prewitt ` - Prewitt edge detector * - :func:`prewitt_h ` - Prewitt horizontal edges * - :func:`prewitt_v ` - Prewitt vertical edges * - :func:`farid ` - Farid edge detector * - :func:`farid_h ` - Farid horizontal edges * - :func:`farid_v ` - Farid vertical edges * - :func:`roberts ` - Roberts cross-gradient * - :func:`laplace ` - Laplacian edge detector * - :func:`canny ` - Canny edge detector Feature Detection ~~~~~~~~~~~~~~~~~ .. list-table:: :header-rows: 1 :widths: 30 70 * - Function - Description * - :func:`blob_dog ` - Blob detection using Difference of Gaussians * - :func:`blob_doh ` - Blob detection using Determinant of Hessian * - :func:`blob_log ` - Blob detection using Laplacian of Gaussians * - :func:`blob_opencv ` - OpenCV-based blob detection * - :func:`peak_detection ` - 2D peak detection * - :func:`contour_shape ` - Contour shape analysis * - :func:`hough_circle_peaks ` - Circular Hough transform Morphological Operations ~~~~~~~~~~~~~~~~~~~~~~~~ .. list-table:: :header-rows: 1 :widths: 30 70 * - Function - Description * - :func:`erosion ` - Morphological erosion * - :func:`dilation ` - Morphological dilation * - :func:`opening ` - Morphological opening * - :func:`closing ` - Morphological closing * - :func:`white_tophat ` - White top-hat transform * - :func:`black_tophat ` - Black top-hat transform Thresholding ~~~~~~~~~~~~ .. list-table:: :header-rows: 1 :widths: 30 70 * - Function - Description * - :func:`threshold ` - Manual threshold with custom value * - :func:`threshold_otsu ` - Otsu's thresholding * - :func:`threshold_li ` - Li's thresholding * - :func:`threshold_yen ` - Yen's thresholding * - :func:`threshold_triangle ` - Triangle thresholding * - :func:`threshold_isodata ` - Isodata thresholding * - :func:`threshold_mean ` - Mean thresholding * - :func:`threshold_minimum ` - Minimum thresholding Exposure and Intensity Correction ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. list-table:: :header-rows: 1 :widths: 30 70 * - Function - Description * - :func:`histogram ` - Compute image histogram * - :func:`equalize_hist ` - Histogram equalization * - :func:`equalize_adapthist ` - Adaptive histogram equalization * - :func:`adjust_gamma ` - Gamma correction * - :func:`adjust_log ` - Logarithmic adjustment * - :func:`adjust_sigmoid ` - Sigmoid adjustment * - :func:`rescale_intensity ` - Rescale intensity range * - :func:`flatfield ` - Flat-field correction Image Restoration ~~~~~~~~~~~~~~~~~ .. list-table:: :header-rows: 1 :widths: 30 70 * - Function - Description * - :func:`denoise_bilateral ` - Bilateral denoising * - :func:`denoise_tv ` - Total variation denoising * - :func:`denoise_wavelet ` - Wavelet denoising * - :func:`denoise_tophat ` - Top-Hat denoising * - :func:`erase ` - Erase image regions Preprocessing ~~~~~~~~~~~~~ .. list-table:: :header-rows: 1 :widths: 30 70 * - Function - Description * - :func:`zero_padding ` - Zero-padding for images Measurements and Analysis ~~~~~~~~~~~~~~~~~~~~~~~~~ .. list-table:: :header-rows: 1 :widths: 30 70 * - Function - Description * - :func:`centroid ` - Compute image centroid * - :func:`enclosing_circle ` - Find minimum enclosing circle * - :func:`stats ` - Statistical measurements * - :func:`line_profile ` - Extract profile along a line * - :func:`segment_profile ` - Extract profile along a multi-segment line * - :func:`radial_profile ` - Extract radial profile from center * - :func:`average_profile ` - Average profile over region * - :func:`horizontal_projection ` - Project image onto horizontal axis * - :func:`vertical_projection ` - Project image onto vertical axis * - :func:`generate_image_grid_roi ` - Generate grid of ROIs See Also -------- - :doc:`../api/proc` - Complete API reference for all processing functions - :doc:`../api/objects` - Data objects (SignalObj, ImageObj) used by processing functions - :doc:`../auto_examples/index` - Examples demonstrating various computation features Sigima-1.1.1/doc/user_guide/getting_started.rst000066400000000000000000000044071514013333200215440ustar00rootroot00000000000000.. _getting_started: Getting Started =============== This page provides a quick introduction to get you started with Sigima through practical examples. Interactive Notebook -------------------- The best way to start learning Sigima is through an interactive Jupyter notebook. This example demonstrates image processing with Regions of Interest (ROI) and uses the matplotlib backend for web-friendly visualization. :download:`Download simple_example.ipynb <../simple_example.ipynb>` .. toctree:: :maxdepth: 1 ../simple_example What This Example Shows ^^^^^^^^^^^^^^^^^^^^^^^^ The notebook demonstrates: * Creating image objects from NumPy arrays * Defining Regions of Interest (ROI) for selective processing * Applying Gaussian filtering to images * Visualizing results with matplotlib backend (web-friendly, no Qt required) * Using the new visualization backend selection feature introduced in Sigima V1.1 Key Concepts ^^^^^^^^^^^^ **Object-Oriented Approach** Sigima wraps NumPy arrays in rich objects (``SignalObj``, ``ImageObj``) that carry metadata, units, and ROI information. **Region of Interest (ROI)** Process only specific areas of your data by defining ROIs. The example shows a circular ROI applied to an image. **Backend Flexibility** Choose between PlotPy (Qt-based, interactive) or Matplotlib (web-friendly) backends for visualization, making Sigima suitable for both desktop applications and web-based workflows. Remote Control Example ---------------------- Sigima also enables remote control of DataLab sessions from external scripts or notebooks. This is useful for automation, batch processing, or integrating DataLab into larger workflows. :download:`Download remote_example.ipynb <../remote_example.ipynb>` .. toctree:: :maxdepth: 1 ../remote_example This notebook demonstrates: * Connecting to a running DataLab instance using ``SimpleRemoteProxy`` * Adding signals and images to DataLab from external Python code * Controlling DataLab programmatically without GUI interaction Next Steps ---------- * Explore the :ref:`features` page for a complete overview of available operations * Check out the :ref:`API documentation ` for detailed function references * Browse the :doc:`gallery of examples ` for more use cases Sigima-1.1.1/doc/user_guide/index.rst000066400000000000000000000016001514013333200174540ustar00rootroot00000000000000User Guide ========== .. only:: html and not latex .. grid:: 2 2 4 4 :gutter: 1 2 3 4 .. grid-item-card:: :octicon:`download;1em;sd-text-info` Installation :link: installation :link-type: doc How to install Sigima .. grid-item-card:: :octicon:`rocket;1em;sd-text-info` Getting Started :link: getting_started :link-type: doc Quick start with examples .. grid-item-card:: :octicon:`book;1em;sd-text-info` Overview :link: overview :link-type: doc Introduction to Sigima .. grid-item-card:: :octicon:`star;1em;sd-text-info` Features :link: features :link-type: doc Key functionalities .. toctree:: :maxdepth: 2 :caption: Contents: installation getting_started overview features Sigima-1.1.1/doc/user_guide/installation.rst000066400000000000000000000102271514013333200210530ustar00rootroot00000000000000.. _installation: Installation ============ This section provides instructions on how to install and set up the Sigima project, including dependencies and environment configuration. How to install -------------- Sigima is available in several forms: - As a :ref:`install_conda`. - As a Python package, which can be installed using the :ref:`install_pip`. - As a precompiled :ref:`install_wheel`, which can be installed using ``pip``. - As a :ref:`install_source`, which can be installed using ``pip`` or manually. .. seealso:: Impatient to try the next version of Sigima? You can also install the latest development version of Sigima from the master branch of the Git repository. See :ref:`install_development` for more information. .. _install_conda: Conda package ^^^^^^^^^^^^^ :octicon:`info;1em;sd-text-info` :bdg-info-line:`GNU/Linux` :bdg-info-line:`Windows` :bdg-info-line:`macOS` To install ``sigima`` package from the `conda-forge` channel (https://anaconda.org/conda-forge/sigima), run the following command: .. code-block:: console $ conda install conda-forge::sigima .. _install_pip: Package manager ``pip`` ^^^^^^^^^^^^^^^^^^^^^^^ :octicon:`info;1em;sd-text-info` :bdg-info-line:`GNU/Linux` :bdg-info-line:`Windows` :bdg-info-line:`macOS` Sigima's package ``sigima`` is available on the Python Package Index (PyPI) on the following URL: https://pypi.python.org/pypi/sigima. Installing Sigima from PyPI is as simple as running this command (you may need to use ``pip3`` instead of ``pip`` on some systems): .. code-block:: console $ pip install sigima .. note:: If you already have a previous version of Sigima installed, you can upgrade it by running the same command with the ``--upgrade`` option: .. code-block:: console $ pip install --upgrade sigima .. _install_wheel: Wheel package ^^^^^^^^^^^^^ :octicon:`info;1em;sd-text-info` :bdg-info-line:`GNU/Linux` :bdg-info-line:`Windows` :bdg-info-line:`macOS` On any operating system, using pip and the Wheel package is the easiest way to install sigima on an existing Python distribution: .. code-block:: console $ pip install --upgrade Sigima-0.3.0-py2.py3-none-any.whl .. _install_source: Source package ^^^^^^^^^^^^^^ :octicon:`info;1em;sd-text-info` :bdg-info-line:`GNU/Linux` :bdg-info-line:`Windows` :bdg-info-line:`macOS` Installing Sigima directly from the source package may be done using ``pip``: .. code-block:: console $ pip install --upgrade sigima-0.3.0.tar.gz Or, if you prefer, you can install it manually by running the following command from the root directory of the source package: .. code-block:: console $ pip install --upgrade . Finally, you can also build your own Wheel package and install it using ``pip``, by running the following command from the root directory of the source package (this requires the ``build`` and ``wheel`` packages to be installed): .. code-block:: console $ pip install build wheel # Install build and wheel packages (if needed) $ python -m build # Build the wheel package $ pip install --upgrade dist/sigima-0.3.0-py2.py3-none-any.whl # Install the wheel package .. _install_development: Development version ^^^^^^^^^^^^^^^^^^^ :octicon:`info;1em;sd-text-info` :bdg-info-line:`GNU/Linux` :bdg-info-line:`Windows` :bdg-info-line:`macOS` If you want to try the latest development version of Sigima, you can install it directly from the master branch of the Git repository. The first time you install Sigima from the Git repository, enter the following command: .. code-block:: console $ pip install git+https://github.com/DataLab-Platform/Sigima.git Then, if at some point you want to upgrade to the latest version of Sigima, just run the same command with options to force the reinstall of the package without handling dependencies (because it would reinstall all dependencies): .. code-block:: console $ pip install --force-reinstall --no-deps git+https://github.com/DataLab-Platform/Sigima.git .. note:: If dependencies have changed, you may need to execute the same command as above, but without the ``--no-deps`` option. Dependencies ------------ .. include:: ../requirements.rst Sigima-1.1.1/doc/user_guide/overview.rst000066400000000000000000000273671514013333200202350ustar00rootroot00000000000000.. _overview: Overview ======== What is Sigima? --------------- **Sigima** is an open-source Python library for scientific signal and image processing. It provides a unified, object-oriented approach to working with 1D signals and 2D images, combining the power of NumPy arrays with rich metadata and processing capabilities. Sigima was created from the externalization of `DataLab `_'s computing engine and is now an essential building block of the DataLab ecosystem, but is designed to be GUI-independent (and independent of DataLab itself) and can be used in a variety of scientific computing contexts. Quick Start Example ------------------- Here's a simple example demonstrating image processing with Regions of Interest (ROIs) using Sigima. This example uses the matplotlib backend for visualization, making it web-friendly and easy to run in Jupyter notebooks. See the complete interactive notebook in the :ref:`getting_started` section. Why Sigima? ----------- Scientific data processing often requires more than just raw numerical arrays. Real-world applications demand: * **Context-aware data**: physical units, coordinate systems, and measurement uncertainties * **Reproducible workflows**: clear separation between data and processing logic * **Testable components**: modular functions that can be validated independently * **Flexible integration**: ability to work both with high-level objects and low-level arrays Sigima addresses these needs by providing a structured framework that bridges the gap between raw numerical operations and scientific data analysis. It is designed to be the processing backend for scientific applications, particularly those requiring headless execution or remote processing capabilities. Signals in Sigima ----------------- What are Signals? ^^^^^^^^^^^^^^^^^ In Sigima, a **signal** is a 1D data object represented by the :py:class:`~sigima.objects.signal.object.SignalObj` class. Unlike a simple NumPy array, a signal carries complete information about your measurement or calculation. Core Components ^^^^^^^^^^^^^^^ A signal consists of: **X and Y Data** The fundamental coordinate-value pairs that define your signal. The x-axis typically represents the independent variable (time, frequency, position, etc.) while the y-axis contains the measured or calculated values. **Error Bars (dx, dy)** Sigima natively supports uncertainty quantification through optional error bars: * ``dx``: uncertainties in the x-coordinate (e.g., timing jitter, position uncertainty) * ``dy``: uncertainties in the y-values (e.g., measurement noise, statistical errors) These error bars propagate through many processing operations, allowing you to track how uncertainties evolve in your analysis pipeline. **Metadata** A flexible dictionary for storing any additional information about your signal: acquisition parameters, processing history, physical constants, or any custom data your application needs. **Units and Labels** Clear labeling of physical quantities: * ``xlabel`` / ``ylabel``: descriptive names (e.g., "Time", "Temperature") * ``xunit`` / ``yunit``: physical units (e.g., "s", "°C") **Annotations** User-defined notes or comments about specific features or regions of the signal. Why This Matters ^^^^^^^^^^^^^^^^ Consider a temperature measurement over time. With a simple NumPy array, you just have numbers. With a Sigima signal, you have: .. code-block:: python import numpy as np from sigima.objects import create_signal # Time points with some uncertainty in timing time = np.linspace(0, 10, 100) time_uncertainty = np.full_like(time, 0.01) # ±10 ms timing jitter # Temperature measurements with measurement error temperature = 20 + 5 * np.sin(time) + np.random.normal(0, 0.1, 100) temp_uncertainty = np.full_like(temperature, 0.1) # ±0.1°C sensor noise # Create a signal with full context signal = create_signal( title="Temperature oscillation", x=time, y=temperature, dx=time_uncertainty, dy=temp_uncertainty, units=("s", "°C"), labels=("Time", "Temperature"), ) # Metadata is automatically preserved through processing signal.metadata["sensor_id"] = "TC-01" signal.metadata["location"] = "Lab A" This signal object can now be processed, analyzed, saved, and loaded while preserving all its context. When you apply operations like filtering, peak detection, or statistics, the units, labels, and error bars remain attached to your data. Specialized Features ^^^^^^^^^^^^^^^^^^^^ Sigima signals support advanced use cases: **Datetime Coordinates** For time-series data, x-coordinates can represent actual datetime values, with automatic handling of time units and formatting. **ROI Operations** Define regions of interest (ROIs) to process or analyze specific portions of your signal independently. **Scale Management** Control visualization aspects like logarithmic scales and axis bounds. Images in Sigima ---------------- What are Images? ^^^^^^^^^^^^^^^^ An **image** in Sigima is a 2D data object represented by the :py:class:`~sigima.objects.image.object.ImageObj` class. Like signals, images extend beyond simple 2D NumPy arrays by providing comprehensive metadata and coordinate system support. Core Components ^^^^^^^^^^^^^^^ An image consists of: **2D Data Array** The pixel values forming your image. Sigima supports various data types including unsigned integers (uint8, uint16), signed integers (int16, int32), floating-point (float32, float64), and complex numbers (complex128). **Coordinate Systems** Two types of coordinate systems are supported: * **Uniform coordinates**: regular pixel spacing, common for most imaging systems - ``dx``, ``dy``: pixel spacing in physical units - ``x0``, ``y0``: origin coordinates * **Non-uniform coordinates**: variable pixel spacing for adaptive sampling or irregular grids - ``xcoords``, ``ycoords``: explicit coordinate arrays **Metadata** Rich metadata support including: * DICOM template integration for medical imaging * Custom key-value pairs for any application-specific data * Automatic extraction from common file formats **Units and Labels** Physical quantities for all three dimensions: * ``xlabel``, ``ylabel``, ``zlabel``: axis descriptions * ``xunit``, ``yunit``, ``zunit``: physical units The z-axis typically represents the pixel values (intensity, height, temperature, etc.) **Annotations** Structured annotations for documenting features, regions, or processing steps. **Data Type Flexibility** Unlike signals (which are typically float64), images support multiple data types optimized for different use cases: * ``uint8``, ``uint16``: efficient storage for camera data, medical images * ``int16``, ``int32``: signed data, difference images * ``float32``, ``float64``: scientific measurements, calculated results * ``complex128``: Fourier transforms, wave simulations Why This Matters ^^^^^^^^^^^^^^^^ Consider microscopy data. A raw 2D array gives you pixel values, but an ``ImageObj`` provides the complete picture: .. code-block:: python import numpy as np from sigima.objects import create_image # Create a 512x512 microscopy image data = np.random.poisson(1000, (512, 512)).astype(np.uint16) image = create_image( title="Cell sample - 40x objective", data=data, units=("μm", "μm", "counts"), labels=("X position", "Y position", "Photon counts"), ) # Set physical coordinate system # 0.16 μm per pixel, field of view starts at origin image.set_uniform_coords(dx=0.16, dy=0.16, x0=0.0, y0=0.0) # Add acquisition metadata image.metadata["objective"] = "40x" image.metadata["exposure_time"] = 100 # ms image.metadata["binning"] = "1x1" image.metadata["camera_gain"] = 2.5 Processing operations automatically work in physical units. Measurements return results in micrometers, not pixels. The metadata travels with your data through the entire analysis pipeline. Specialized Features ^^^^^^^^^^^^^^^^^^^^ **Native Support for Multiple Image Formats** Sigima can directly read and write images from various scientific and common file formats, making it easy to integrate into existing workflows: * **Common formats**: BMP, JPEG, PNG, TIFF, JPEG 2000 * **Scientific formats**: DICOM (medical imaging), Andor SIF (spectroscopy cameras) * **Data exchange**: NumPy (.npy), MATLAB (.mat), HDF5 (.h5img) * **Text-based**: CSV, TXT, ASC (with coordinate metadata support) * **Specialized**: Spiricon (.scor-data), Dürr NDT (.xyz), FT-Lab (.ima) Each format preserves relevant metadata when available, such as DICOM medical imaging headers or acquisition parameters from scientific instruments. **ROI Operations** Define rectangular, circular, or polygonal regions of interest for localized analysis or processing. **Masked Arrays** Support for NumPy masked arrays to handle invalid pixels, saturated regions, or excluded areas. **Coordinate Conversion** Seamless conversion between pixel indices and physical coordinates, essential for multi-scale or multi-modal imaging. Key Differences from Raw Arrays -------------------------------- Here's why Sigima objects are more powerful than plain NumPy arrays in physical data processing: .. list-table:: :header-rows: 1 :widths: 30 35 35 * - Feature - NumPy Array - Sigima Object * - Data storage - Numbers only - Numbers + context * - Units - Implicit/external - Explicit and tracked * - Error propagation - Manual - Automatic (where supported) * - Metadata - Separate variables - Integrated dictionary * - Coordinate systems - Index-based only - Physical coordinates * - Serialization - Just data - Complete context * - Processing history - Lost - Can be tracked Common Use Cases ---------------- Sigima excels in scenarios requiring: **Scientific Instrumentation** Process data from sensors, cameras, spectrometers, or any measurement device while preserving calibration, units, and acquisition parameters. **Automated Analysis Pipelines** Build reproducible workflows that maintain data provenance and context through multiple processing steps. **Remote Processing** Execute signal and image processing on remote servers or in cloud environments without GUI dependencies. **Application Backends** Provide the computation engine for scientific software, keeping processing logic independent from user interface concerns. **Research and Development** Develop and validate new processing algorithms in a testable, modular framework. GUI Connection -------------- As the core computing engine externalized from `DataLab `_, Sigima seamlessly integrates with it as an essential building block of the DataLab stack. You can leverage Sigima's powerful processing features within DataLab's graphical interface, using for example Sigima to handle your signal and image acquisition and sending the results back to DataLab for visualization and further interactive analysis. Getting Started --------------- To start using Sigima, check out: * :doc:`installation` - Set up Sigima in your environment * :doc:`features` - Explore Sigima's key features and capabilities * :doc:`../auto_examples/index` - Practical examples showing signals and images in action * :doc:`../api/index` - Complete API reference .. note:: Sigima is designed to be **GUI-independent**. If you need interactive visualization and analysis tools, check out `DataLab `_, which uses Sigima as its processing backend and adds a complete graphical interface. Sigima-1.1.1/notebooks/000077500000000000000000000000001514013333200147215ustar00rootroot00000000000000Sigima-1.1.1/notebooks/sigima_basic_example.ipynb000066400000000000000000005311131514013333200221150ustar00rootroot00000000000000{ "metadata": { "kernelspec": { "name": "python3", "display_name": "Python 3.13 (XPython)", "language": "python" }, "language_info": { "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "version": "3.13.1" } }, "nbformat_minor": 5, "nbformat": 4, "cells": [ { "id": "489c3f46-68fc-4762-ad4c-09644022c377", "cell_type": "markdown", "source": "# Sigima Simple Example\n\nThis notebook demonstrates some features of **Sigma**, the signal and image processing library that powers [DataLab](https://datalab-platform.com).\n\nWhile Sigima’s core computing features are now stable, its Jupyter-related capabilities are still at an early stage of development.", "metadata": {} }, { "id": "b236b805-13e8-4395-a4cf-a43aa2700451", "cell_type": "code", "source": "import numpy as np\nimport sigima.objects\nimport sigima.proc.image\n\ndata = np.random.normal(100, 30, (100, 100)) # Prepare test image data\n\nimg = sigima.objects.create_image(\"Noisy\", data) # Create the image object\nimg.roi = sigima.objects.create_image_roi(\"circle\", [30, 30, 20]) # Define ROI\nresult = sigima.proc.image.gaussian_filter(img, sigma=5.0) # Apply Gaussian filter\nresult", "metadata": { "trusted": true }, "outputs": [ { "execution_count": 2, "output_type": "execute_result", "data": { "text/html": "ImageObj: Gaussian Filter Result (sigma=5.0):
Shape:100 × 100 (W×H)
Data type:float64
Z range:[-14.67, 207]
Origin (X, Y):(0, 0)
Pixel spacing (Δx, Δy):(1, 1)
Extent (X):[0, 99]
Extent (Y):[0, 99]
Physical size:100 × 100
ROIs:1
", "text/plain": "Gaussian Filter Result (sigma=5.0):\n _tabs:\n _datag:\n data: ~= 99.668 [-14.673 .. 206.973] (FloatArrayItem)\n metadata: {'_roi_': {'single_rois': [{'coords': array([30., 30., 20.]), 'indices': False, 'title': '', 'type': 'CircularROI', 'inverse': False}]}} (DictItem)\n annotations: (StringItem)\n _dxdyg:\n is_uniform_coords: ☑ (BoolItem)\n _origin:\n x0: 0.0 (FloatItem)\n y0: 0.0 (FloatItem)\n _pixel_spacing:\n dx: 1.0 (FloatItem)\n dy: 1.0 (FloatItem)\n _boundaries:\n xmin: - (FloatItem)\n xmax: - (FloatItem)\n ymin: - (FloatItem)\n ymax: - (FloatItem)\n _coordsg:\n xcoords: = [] (FloatArrayItem)\n ycoords: = [] (FloatArrayItem)\n _unitsg:\n title: Gaussian Filter Result (sigma=5.0) (StringItem)\n _tabs_u:\n _unitsx:\n xlabel: (StringItem)\n xunit: (StringItem)\n _unitsy:\n ylabel: (StringItem)\n yunit: (StringItem)\n _unitsz:\n zlabel: (StringItem)\n zunit: (StringItem)\n _scalesg:\n autoscale: ☑ (BoolItem)\n _tabs_b:\n _boundsx:\n xscalelog: ☐ (BoolItem)\n xscalemin: - (FloatItem)\n xscalemax: - (FloatItem)\n _boundsy:\n yscalelog: ☐ (BoolItem)\n yscalemin: - (FloatItem)\n yscalemax: - (FloatItem)\n _boundsz:\n zscalemin: - (FloatItem)\n zscalemax: - (FloatItem)" }, "metadata": {} } ], "execution_count": 2 }, { "id": "59dfeb34-8c97-4308-b2c6-20fb7d9ae2bb", "cell_type": "code", "source": "from sigima import viz\nviz.view_images([img, result])", "metadata": { "trusted": true }, "outputs": [ { "output_type": "display_data", "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAABJQAAAJOCAYAAADh3102AAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjgsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvwVt1zgAAAAlwSFlzAAAPYQAAD2EBqD+naQABAABJREFUeJzsnXd4HcXV/797+1VvVm+2LDfJvTcwYAPG9F4DhBJCCf4BCSGhhTeBAElIob4vNYBDQkKHALYBG2Mb995t9d6vdKXb9/fHxTJnzmJLYDX7fJ7nPvasZndmp+3Z2Tnf0XRd1yEIgiAIgiAIgiAIgiAIXcTU1xkQBEEQBEEQBEEQBEEQBhYyoSQIgiAIgiAIgiAIgiB0C5lQEgRBEARBEARBEARBELqFTCgJgiAIgiAIgiAIgiAI3UImlARBEARBEARBEARBEIRuIRNKgiAIgiAIgiAIgiAIQreQCSVBEARBEARBEARBEAShW8iEkiAIgiAIgiAIgiAIgtAtLH2dAUEQBEEQehaPxwOfz9dr6dlsNjgcjl5LTxAEQRAE4WjR23YTMHBtJ5lQEgRBEIRjGI/Hg8E5UaiuDfZamqmpqSgqKhqQhpEgCIIgCMcvfWE3AQPXdpIJJUEQBEE4hvH5fKiuDaJkfS5ionve093VGkLOxGL4fL4BZxQJgiAIgnB809t2EzCwbSeZUBIEQRCE44CoaA1R0VqPpxNCz6chCIIgCILQk/SW3QQMbNtJRLkFQRAEQRAEQRAEQRCEbiErlARBEAThOCCohxDUeycdQRAEQRCEgUxv2U0H0xqoyAolQRAEQRAEQRAEQRAEoVvIhJIgCIIgCIIgCIIgCILQLcTlTRAEQRCOA0LQEULPr93ujTQEQRAEQRB6kt6ymw6mNVCRFUqCIAiCIAiCIAiCIAhCt5AVSoIgCIJwHBBCCL0h+dg7qQiCIAiCIPQcvWU3HUxroCIrlARBEARBEARBEARBEIRuISuUBEEQBOE4IKjrCOo976PfG2kIgiAIgiD0JL1lNx1Ma6AiK5QEQRAEQegzHnnkEUyePBnR0dFITk7Gueeei927d5M4uq7jwQcfRHp6OpxOJ+bMmYPt27eTOF6vF7fddhuSkpIQGRmJs88+G+Xl5b15K4IgCIIgCMcVMqEkCIIgCMcBB3cr6Y1fd1i2bBluueUWrF69GosXL0YgEMCpp54Kt9vdGeexxx7Dn/70Jzz55JNYu3YtUlNTMW/ePLS2tnbGWbhwId5++2288cYbWLFiBdra2nDmmWciGAwetTIUBEEQBOH4oDftpu7YTv3tQ5xMKAmCIAiC0Gd8/PHHuOaaa1BQUICxY8fipZdeQmlpKdavXw8gbBT9+c9/xq9//Wucf/75KCwsxCuvvIL29nYsWrQIANDS0oIXXngBf/zjHzF37lyMHz8er732GrZu3YolS5b05e0JgiAIgiAcNfrbhziZUBIEQRAE4ajjcrnIz+v1dum8lpYWAEBCQgIAoKioCNXV1Tj11FM749jtdpx44olYuXIlAGD9+vXw+/0kTnp6OgoLCzvjCIIgCIIgDHT624c4mVASBEEQhOOAEHQEe+F3cNl2VlYWYmNjO3+PPPLIEfOo6zruuOMOzJo1C4WFhQCA6upqAEBKSgqJm5KS0vm36upq2Gw2xMfHf2ccQRAEQRCErtJbdtO3bafvQ19/iJNd3gRBEARBOOqUlZUhJiamM2y32494zq233ootW7ZgxYoV7G+appGwruvsmEpX4giCIAiCIPQHXC4XCdvt9sPaT939EFdSUtIZ52h9iJMVSoIgCIJwHNDbwpIxMTHkd6QJpdtuuw3vvfcePv/8c2RmZnYeT01NBQBm4NTW1nYaS6mpqfD5fGhqavrOOIIgCIIgCF2lL0S5u7u6++CHuH/84x/sb731IU4mlARBEARB6DN0Xcett96Kt956C5999hkGDx5M/j548GCkpqZi8eLFncd8Ph+WLVuGGTNmAAAmTpwIq9VK4lRVVWHbtm2dcQRBEARBEPozZWVlaGlp6fzdc8893xm3v3yIkwklQRAEQTgOCOp6r/26wy233ILXXnsNixYtQnR0NKqrq1FdXY2Ojg4A4S9sCxcuxMMPP4y3334b27ZtwzXXXIOIiAhcfvnlAIDY2Fhcd911uPPOO7F06VJs3LgRV155JUaPHo25c+ce9bIUBEEQBOHYpjftpoO2U1dWd/e3D3GioSQIgiAIQp/xzDPPAADmzJlDjr/00ku45pprAAC/+MUv0NHRgZtvvhlNTU2YOnUqPv30U0RHR3fGf+KJJ2CxWHDxxRejo6MDp5xyCl5++WWYzebeuhVBEARBEIQe5ZZbbsGiRYvw7rvvdn6IA8If15xOJ/kQl5+fj/z8fDz88MPf+SEuMTERCQkJuOuuu77XhzhN17v5KVEQBEEQhAGDy+VCbGwsdu1MQXR0zy9Mbm0NYcTIGrS0tBBRbkEQBEEQhP5Ob9tNQPdsp+/SOPr2hzhd1/Gb3/wGzz33XOeHuKeeeqpTuBsAPB4Pfv7zn2PRokWdH+KefvppZGVldSvvMqEkCIIgCMcwMqEkCIIgCILQNfr7hFJ/Q1zeBEEQBOE4IAgdQfT8N6TeSEMQBEEQBKEn6S276WBaAxUR5RYEQRAEQRAEQRAEQRC6hUwoCYIgCIIgCIIgCIIgCN1CXN4EQRAE4TggqId/vZGOIAiCIAjCQKa37KaDaQ1UZIWSIAiCIAiCIAiCIAiC0C1khZIgCIIgHAeEvvn1RjqCIAiCIAgDmd6ymw6mNVCRFUqCIAiCIAiCIAiCIAhCt5AVSoIgCIJwHBCChiC0XklHEARBEARhINNbdtPBtAYqskJJEARBEARBEARBEARB6BayQkkQBEEQjgNCevjXG+kIgiAIgiAMZHrLbjqY1kBFVigJgiAIgiAIgiAIgiAI3UImlARBEARBEARBEARBEIRuIS5vgiAIgnAcEOwlccneErAUBEEQBEHoKXrLbjqY1kBFVigJgiAIgiAIgiAIgiAI3UJWKAmCIAjCcYCsUBIEQRAEQegaskKpa8gKJUEQBEEQBEEQBEEQBKFbyAolQRAEQTgOCOkaQnrPfwHrjTQEQRAEQRB6kt6ymw6mNVCRFUqCIAiCIAiCIAiCIAhCt5AVSoIgCIJwHCAaSoIgCIIgCF1DNJS6hqxQEgRBEARBEARBEARBELqFTCgJwgDj5ZdfhqZpcDgcKCkpYX+fM2cOCgsLu33dOXPmYM6cOUchh4IgCIIwcNiyZQuuu+465OXlwel0wul0Ij8/Hz/5yU+wbt26vs5el/jiiy+gaRq++OKLXk/7wQcfhKZphr8nn3zSMG8Hz/k2Tz/9NF5++eVezfucOXNIfh0OB0aNGoXf/va38Pl8vZoXIw7afMXFxZ3HFi1ahD//+c/duo7f78eIESPw+9//vlvnXXPNNcjNze3WOQOJ3Nxcw3Z70003dfkaf/vb3zBixAjY7XYMHjwYv/nNb+D3+0mc++67DxMmTEAoFDratyAIfY64vAnCAMXr9eLee+/Fq6++elSu9/TTTx+V6wiC0D8JwoRgL3xHCvZ4CoJw9Hjuuedw6623Yvjw4bj99ttRUFAATdOwc+dO/OMf/8DkyZOxb98+5OXl9XVWD8uECROwatUqjBo1qs/y8PHHHyM2NpYcGzx4MJxOZ5fy9vTTTyMpKQnXXHNND+aSM2TIELz++usAgLq6Ojz//PO47777UFpaiv/93//t1bx0hUWLFmHbtm1YuHBhl895+umn0dTUhNtuu61bad133324/fbbu5nDgcXMmTPxhz/8gRxLSUnp0rm/+93vcN999+GXv/wlTj31VKxduxb33nsvKioqSNu566678OSTT+KVV17Btddee1TzL/QcvWU3hdMauMiEkiAMUE4//XQsWrQId911F8aOHfuDr9eXRqggCIIg9DZfffUVbr75ZixYsAD//ve/YbPZOv928skn45ZbbsGbb74Jp9PZh7nsGjExMZg2bVqf5mHixIlISkoy/Ftf5U3XdXg8nsPWodPpJPmbP38+Ro0ahVdeeQV//etf4XA4eiOrPUYgEMDjjz+OH//4x4iMjOzWuf19IvVoEBcX973aZ0NDA37729/ihhtuwMMPPwwgvOLN7/fj3nvvxcKFCztt69jYWFx55ZX4/e9/j2uuuYatzhOEgYy4vAnCAOUXv/gFEhMTcffddx82nsfjwT333IPBgwfDZrMhIyMDt9xyC5qbm0k8I5e3Z555BmPHjkVUVBSio6MxYsQI/OpXvwIAFBcXw2Kx4JFHHmFpLl++HJqm4c033/xB9ygIwtFD/2b7257+6QN461vh+OLhhx+G2WzGc889RyaTvs1FF12E9PT0zvC6detw6aWXIjc3F06nE7m5ubjsssuYC7qRSxdg7ML02WefYc6cOUhMTITT6UR2djYuuOACtLe3d8Y53PMYMHZ562peD+bp888/x09/+lMkJSUhMTER559/PiorK7tUloejK+54ubm52L59O5YtW9bpdvRtVyuXy4W77rqL2DILFy6E2+0m19E0DbfeeiueffZZjBw5Ena7Ha+88kq38muxWDBu3Dj4fD5iK+m6jqeffhrjxo2D0+lEfHw8LrzwQhw4cICcv3HjRpx55plITk6G3W5Heno6FixYgPLycgBh+0nTNEP3Pk3T8OCDD35n3ubMmYMPP/wQJSUlxEXrcLz33nuoqKjAVVddRY7X1dXhxhtvRFZWFux2OwYNGoSZM2diyZIlnXGMXN6am5tx3XXXISEhAVFRUViwYAEOHDjA8n6wD2zZsgUXXXQRYmNjkZCQgDvuuAOBQAC7d+/G6aefjujoaOTm5uKxxx4j6Xg8Htx5550YN25c57nTp0/Hu+++e9j77S0+/vhjeDwetuLo2muvha7reOedd8jxq666Cnv27MHnn3/ei7kUfgi9ZTcNdNtJVigJwgAlOjoa9957L26//XZ89tlnOPnkk1kcXddx7rnnYunSpbjnnnswe/ZsbNmyBQ888ABWrVqFVatWwW63G17/jTfewM0334zbbrsNf/jDH2AymbBv3z7s2LEDQNj4O/vss/Hss8/iF7/4Bcxmc+e5Tz75JNLT03Heeef1zM0LgiAIwg8gGAzi888/x6RJk5CWltbl84qLizF8+HBceumlSEhIQFVVFZ555hlMnjwZO3bs+M4VOoe73oIFCzB79my8+OKLiIuLQ0VFBT7++GP4fD5EREQc8Xl8tPJ6/fXXY8GCBVi0aBHKysrw85//HFdeeSU+++yzLt1LMBhEIBDoDGuaRmyDw/H222/jwgsvRGxsbKcL/kH7pL29HSeeeCLKy8vxq1/9CmPGjMH27dtx//33Y+vWrViyZAmZVHnnnXfw5Zdf4v7770dqaiqSk5O7lIdvU1RUhLi4OAwaNKjz2E9+8hO8/PLL+NnPfoZHH30UjY2NeOihhzBjxgxs3rwZKSkpcLvdmDdvHgYPHoynnnoKKSkpqK6uxueff47W1tZu50Pl6aefxo033oj9+/fj7bff7tI5H374IZKTk9lK9KuuugobNmzA7373OwwbNgzNzc3YsGEDGhoavvNaoVAIZ511FtatW4cHH3yw09Xy9NNP/85zLr74Ylx55ZX4yU9+gsWLF+Oxxx6D3+/HkiVLcPPNN+Ouu+7CokWLcPfdd2Po0KE4//zzAYSlHRobG3HXXXchIyMDPp8PS5Yswfnnn4+XXnoJP/rRjzrTCAaD0HX9iGVhMplgMtH1FMuXL0d0dDQ8Hg/y8/Nx3XXXYeHChUdsu9u2bQMAjB49mhxPS0tDUlJS598PMnHiRERFReHDDz80tNkFYaAiE0qCMIC56aab8Je//AV333031qxZw75Sffrpp/jkk0/w2GOP4ec//zkAYN68ecjKysIll1yCv//977jhhhsMr/3VV18hLi4Of/3rXzuPnXLKKSTOz372M5x00kl4//33ce655wIAKisr8fbbb+O+++6DxSJDjCD0F3pr+9uBvPWtcPxQX1+Pjo4O5OTksL+pL6dms7nz+XrhhRfiwgsvJHHPPPNMpKSkYNGiRfjZz37WrXysX78eHo8Hjz/+OHFfv/zyyzv/35XnsRHdzevpp59O0mhsbMQvfvELVFdXIzU19YjpqXEyMjI6V+UcifHjx8PpdBq67v31r3/Fli1b8PXXX2PSpEkAwvefkZGBCy+8EB9//DHmz5/fGb+trQ1bt25FfHx8l9IG0DkRVl9fj2eeeQbr1q3Ds88+2zmpsHr1avzf//0f/vjHP+KOO+7oPG/27NkYNmwY/vSnP+HRRx/Frl270NDQgBdeeAHnnHNOZ7yLL764y3k5HKNGjUJcXBzsdnuX3bRWrVqFCRMmsONfffUVrr/+emIHfjvPRnz88cdYsWIFnnnmmU7h6nnz5sFms+Gee+4xPOfGG2/sLLO5c+fi008/xZNPPom33nqr88PjnDlz8MEHH+D111/vnFCKjY3FSy+91HmdYDCIU045BU1NTfjzn/9MJpROOeUULFu27IhlcfXVV5OVYQsWLMCkSZOQl5eHpqYmvPnmm7jrrruwadOmI2qUNjQ0wG63G7oRJiQksIk5s9mMsWPH4quvvjpiPoX+QW/ZTQfTGqiIy5sgDGBsNht++9vfYt26dfjXv/7F/n7wq6IqcHnRRRchMjISS5cu/c5rT5kyBc3Nzbjsssvw7rvvor6+nsWZM2cOxo4di6eeeqrz2LPPPgtN03DjjTd+z7sSBEEQhL5j4sSJsFqtnb8//vGPnX9ra2vrXElhsVhgsVgQFRUFt9uNnTt3djutcePGwWaz4cYbb8Qrr7zC3KeArj2PjehuXs8++2wSHjNmDAAY7ihrxJIlS7B27drO30cffdSl847EBx98gMLCQowbNw6BQKDzd9pppxm60p188sndmkzavn17Z12npaXhoYcewj333IOf/OQnJA+apuHKK68keUhNTcXYsWM78zB06FDEx8fj7rvvxrPPPnvEVWS9QWVlpeEqrSlTpuDll1/Gb3/7W6xevZrtTGbEwUkbdYLssssu+85zzjzzTBIeOXIkNE0jk4AWiwVDhw5lbe3NN9/EzJkzERUVBYvFAqvVihdeeIG13+eee460ve/6qe6ETz31FK699lqccMIJOOecc/Daa6/h1ltvxWuvvYaNGzcesTwO525o9Lfk5GRUVFQc8bqCMJCQCSVBGOBceumlmDBhAn79618zY6ChoQEWi4Us2QbCD7nU1NTDLmu+6qqr8OKLL6KkpAQXXHABkpOTMXXqVCxevJjE+9nPfoalS5di9+7d8Pv9+L//+z9ceOGFXfqaKQhC7xHUTb32E4T+TlJSEpxOp+FkyaJFi7B27Vq899577G+XX345nnzySVx//fX45JNPsGbNGqxduxaDBg1CR0dHt/ORl5eHJUuWIDk5Gbfccgvy8vKQl5eHv/zlL51xuvo8/qF5TUxMJOGDLmddva+xY8di0qRJnb+DE1I/lJqaGmzZsoVM8lmtVkRHR0PXdTbB1h0XRiBcB2vXrsWaNWvw5ptvYuzYsXjkkUfwxhtvkDzouo6UlBSWj9WrV3fmITY2FsuWLcO4cePwq1/9CgUFBUhPT8cDDzzQpQmbnqCjo8NQWPyf//wnrr76ajz//POYPn06EhIS8KMf/QjV1dXfea2DdmVCQgI5frhd0dS4NpsNERERLE82mw0ej6cz/NZbb+Hiiy9GRkYGXnvtNaxatQpr167Fj3/8YxIPCE/kjRs37oi/7Ozs78znQa688koA4VVphyMxMREej4donR2ksbGR3TcAOByO7zVOCH1Db9pNA9l2En8UQRjgaJqGRx99FPPmzWPb2yYmJiIQCKCuro5MKum6jurqakyePPmw17722mtx7bXXwu12Y/ny5XjggQdw5plnYs+ePZ1uApdffjnuvvtuPPXUU5g2bRqqq6txyy23HP0bFQRBEISjhNlsxsknn4xPP/0UVVVVZBLioNbMt4WzAaClpQUffPABHnjgAfzyl7/sPH5Q6+XbHHxZ9nq9RKvQaHXR7NmzMXv2bASDQaxbtw5/+9vfsHDhQqSkpODSSy8F0LXn8ffNa3/n4OTfiy+++J1//zbd3UHL4XB0utJNnjwZJ510EgoKCrBw4UKceeaZiIqKQlJSEjRNw5dffmmoPfntY6NHj8Ybb7wBXdexZcsWvPzyy3jooYfgdDrxy1/+krSNb3O4j3w/hKSkJMM6T0pKwp///Gf8+c9/RmlpKd577z388pe/RG1tLT7++GPDax20K9UJk8NNQn1fXnvtNQwePBj//Oc/SZ2q5QZ8f5c3Iw66u6paSyoHtZO2bt2KqVOndh6vrq5GfX09CgsL2TmNjY3d1lkThP7OwJ0KEwShk7lz52LevHl46KGH0NbW1nn8oMbCa6+9RuL/5z//gdvt7pIGAwBERkZi/vz5+PWvfw2fz4ft27d3/s3hcHQu1f/Tn/6EcePGYebMmUfhrgRBOJqEoCEEUy/8Bq4OgHB8cc899yAYDOKmm27q0uoRTdOg6zqbUHj++ecRDAbJsYM7Y23ZsoUcf//997/z+mazGVOnTu10I9+wYQOLc7jn8ffNa3/Bbrcbrt4488wzsX//fiQmJpIVUAd/6i5kP5TExET8/ve/R01NDf72t7915kHXdVRUVBjmQRVmBsJ1MHbsWDzxxBOIi4vrrM+UlBQ4HA7WNrq6e9l3ldN3MWLECOzfv/+wcbKzs3Hrrbdi3rx5hu3uICeeeCKA8Oqmb/Pt1VxHC03TYLPZyGRSdXW1YTl9X5c3I/7+978DwBE1qk4//XQ4HA42QXVw18SD2qLf5sCBA0wcXei/9J7dNLBtJ1mhJAjHCI8++igmTpyI2tpaFBQUAAgLJZ522mm4++674XK5MHPmzM5d3saPH8+2kP02N9xwA5xOJ2bOnIm0tDRUV1fjkUceQWxsLFvZdPPNN+Oxxx7D+vXr8fzzz/fofQqCIAjC0WDmzJl46qmncNttt2HChAm48cYbUVBQAJPJhKqqKvznP/8BAMTExHT+e8IJJ+Dxxx9HUlIScnNzsWzZMrzwwguIi4sj1z7jjDOQkJCA6667Dg899BAsFgtefvlllJWVkXjPPvssPvvsMyxYsADZ2dnweDydK3Hmzp0LoHvP44N0J6/9hYMre/75z39iyJAhcDgcGD16NBYuXIj//Oc/OOGEE/D//t//w5gxYxAKhVBaWopPP/0Ud955J1khcjT40Y9+hD/96U/4wx/+gFtuuQUzZ87EjTfeiGuvvRbr1q3DCSecgMjISFRVVWHFihUYPXo0fvrTn+KDDz7A008/jXPPPRdDhgyBrut466230NzcjHnz5gFApxbTiy++iLy8PIwdOxZr1qzBokWLulxOb731Fp555hlMnDgRJpOpc4WVEXPmzMFDDz2E9vZ2REREAAivYDvppJNw+eWXY8SIEYiOjsbatWvx8ccfd4piG3H66adj5syZuPPOO+FyuTBx4kSsWrWqcxLmSKt6usOZZ56Jt956CzfffDMuvPBClJWV4X/+53+QlpaGvXv3krjDhw/v9vUXLVqEt956CwsWLEBOTg6am5vx5ptv4o033sA111xDRPKXLVuGU045Bffffz/uv/9+AGFXvnvvvRf33XcfEhIScOqpp3ZOWl1//fVs4qihoQF79+7Fbbfd9j1KQxD6LzKhJAjHCOPHj8dll11GDBJN0/DOO+/gwQcfxEsvvYTf/e53SEpKwlVXXYWHH37YcNn2QWbPno2XX34Z//rXv9DU1ISkpCTMmjULf//735kmU0ZGBmbNmoUtW7aQnWkEQRAEoT9z0003Yfr06fjLX/6CJ554ApWVldA0DZmZmZgxYwaWLl1KtvhetGgRbr/9dvziF79AIBDAzJkzsXjxYixYsIBcNyYmBh9//DEWLlyIK6+8EnFxcbj++usxf/58XH/99Z3xxo0bh08//RQPPPAAqqurERUVhcLCQrz33ns49dRTAXTvefxtuprX/sJvfvMbVFVV4YYbbkBraytycnJQXFyMyMhIfPnll/j973+P//3f/0VRURGcTieys7Mxd+7co75CCQhPjPz+97/HggUL8Oc//xn3338/nnvuOUybNg3PPfccnn76aYRCIaSnp2PmzJmYMmUKACA/Px9xcXF47LHHUFlZCZvNhuHDh+Pll1/G1Vdf3Xn9g0Lvjz32GNra2nDyySfjgw8+6NK93H777di+fTt+9atfoaWlBbquk10JVS6//HI88MAD+PDDD3HRRRcBCK8unzp1Kl599VUUFxfD7/cjOzsbd999N37xi18ctlzef/993Hnnnfj9738Pn8+HmTNn4rXXXsO0adOO6mTltddei9raWjz77LN48cUXMWTIEPzyl79EeXk5fvOb3/zg6w8ZMgTNzc341a9+hYaGBlitVhQUFODpp58mguxA2A0uGAwiFAqR47/+9a8RHR2Np556Cn/4wx+QmpqKX/7yl/j1r3/N0nv33XdhtVqP2o5/gtBf0PTDjUCCIAhdoLa2Fjk5Objtttvw2GOP9XV2BEH4Fi6XC7GxsXhvSx4io809np67NYizx+xHS0tL58oOQRAEoe8466yzEAgE8N///rdHrr9o0SJcccUV+OqrrzBjxoweSWOgM3v2bGRnZ+P111/v66wIR6C37SZgYNtOskJJEITvTXl5OQ4cOIDHH38cJpMJt99+e19nSRAEQRAEQfgWjzzyCMaPH4+1a9cecUOWI/GPf/wDFRUVGD16NEwmE1avXo3HH38cJ5xwgkwmfQfLly/H2rVr8corr/R1VgThqCMTSoIgfG+ef/55PPTQQ8jNzcXrr7+OjIyMvs6SIAjfQW9tSxuUhc+CIAj9isLCQrz00ktHZTe26OhovPHGG/jtb38Lt9uNtLQ0XHPNNfjtb397FHJ6bNLQ0IC///3vGDJkSF9nRegGvWU3hdMauLaTuLwJgiAIwjHMwaXbb2/O7zWXt/PG7h2Qy7YFQRAEQTi+6W27CRjYtpOsUBIEQRCE44Dw9rc9vy3tQN76VhAEQRAEAeg9u+lgWgOV3lnDJQiCIAiCIAiCIAiCIBwz9NiE0tNPP43BgwfD4XBg4sSJ+PLLL3sqKUEQBEEQjkAIJgR74ReSb1XfC7GbBEEQBKH/0Ft200C3nXrE5e2f//wnFi5ciKeffhozZ87Ec889h/nz52PHjh3Izs4+7LmhUAiVlZWIjo6Gpg3cpV+CIAiCYISu62htbUV6ejpMpoFrQAhHjx9iNwFiOwmCIAjHNmI79V96RJR76tSpmDBhAp555pnOYyNHjsS5556LRx555LDnlpeXIysr62hnSRAEQRD6FWVlZcjMzOzxdA6KS765eQQiekFcsr01iIvG7hqQwpJ9xQ+xmwCxnQRBEITjg96wnXrbbgIGtu101Fco+Xw+rF+/Hr/85S/J8VNPPRUrV65k8b1eL7xeb2f44PzWTSeeB7vFCgDw5ATYeZFRHnqdoigWZ8LEvST8dTHfqtGpXMdhpWk11/IKHZJNt9wsd8WxOOosnc9lJ2F7LZ9Z9amXifHz63poo45JdLM4roZIEtYcQRKOjqT3DACu5ggSnpp7gMXZUEs7b6DeSfNmD7FzVDQbjxMd3UHC3u3R/Lzh7SScG9NIwrtrU9g5allpEbwdaY02Eg5F8PxpHlpXsRktJNzSRssOABJi2ki4dUc8ixO0K+FomnbUAd5G3Lm0Zc0etovFWV40jIS1dj4QakpRpOXXk3BlSRI7R7ceuX75SfyQpZXeV0C5b5PH4KtDoo/GqbKxKIEYeh1zO72O0a6fZtqsEOBND4imhaWZgyxKqMNKwoXZZSS8vYivMNCVvhC5n9dTcAzNoLdWaWtRvE3Dq1zHz1cr6BH0HjT1HACJGU0k3FhM27BuM6hcNSmjtJ1KOzJoVs5YOiYEiuiYFjeS9n8AsJnphSwar6faNvqc8LTTTpiU4GLnRFroOFxSxMeaEwt2kPAXe0ewOCbnobry+fx48eUPER1t1OB6jt7a/nYgb33bF3TXbgK+23a6dfIh26k1j3cuazQdS817HSzOiBlFJLx5by6LY4qh17FaaX/zVfPnYkZeHQlXNMWyOKzlNNOxPsJgx3NPAg0HY478HLcN6mBxfEewaWzRXqj4G+k5Y4YWsThbqqntZKqlz4uQYgsYYWRf2WJofmybnSxOewGtp+x4Oq4XVwxi56jP4FAkH0ut9fSZEeAmOMxKEVuy6PPM4+JtLyqOxglt4RdWbSef0ozi9/Kyas6j9zSpYB+Ls3ZvHgmb3fz5pSlmecxIWp7NB7itF7KyQ0dEMxhCrdT0hF+5b9WeAQB/Mq07Rzl/1qvvHhZqvhraThalbn0G776qTQsDG1Jz09fQIUOqSLhobxo7R7fTwonjZjBaJik2YzVtNKrdCfB2b+KvYAhG0LRNXt5GIrJaSdiznz7n1fYLgNlOxmkrBwxsJ1OcMibso4nZRnMbx2yiF7Ka+IXrW6kNFnTTRh2TxN9FnVZ6E/V7E1icSePoe/qaHfkszrftVZ/Pj5cXvdertlNv2U3htAau7XTUJ5Tq6+sRDAaRkkKN7pSUFFRXc0vgkUcewW9+8xt23G6xwm4JGxIhG++wdrvygLPyF8wIBx04bTY+qqvXsVtpWkbnOB202OxeHoc1CeU6dqvBbKf6gsZvCXqInme387TVPGs22hFY2Rmco5adUVpm5ZyQwWSRitGEkt2uvBQb1KVmpwOTWgdG9aSWlcmgHWlWel7QIH+moFp+9Bybj6ftUOL4DO4paKX1HVDStlv4AOZX2ohRPallYfIbTCgpReGwd6E8j9KEktWq1gttj+agwcCt3LfJoDzV61j8XZhQUvq7yWiSRGk3JoN6CQZpeXWpfbL6NphQUvu30l51gzYNXZlINdg1IqSMCZrO01bbsN2q9vcjTygZp33kCSV1TDAr9a3mDQBsykSfxcDtx+5X7iFAw0bXdSj91Kguu/KsMRuNP+KaJKD7dhNwJNsp3P68Bs8zm/IypvYtoGvjl1m5jtWqjClWo+eiYjsZjYvqAdV2MrBadeUy6rMU4M9xm2p3GKTFxmiDSR3NdvixH+Dlp5Z5yHrklwgj+0rNj83CyzOojNOOrtStUlZBG3/m2az0OkbPTkuAjm8WxY4LGdrkyhhtdE/Kc1tT0rabDcpKaZ9dsZ0sPn7f6oh9pOckcBQnlFR7xar2ZYNnjI22c7uVt09NuY5FuY7hhJIy4aFeAzDoh0YTSn6aH/Z+ZVSean0bjAl2++FtRtVeBHi7NxnYL+o9mUNG76fKOKKkrdr+APiEkmHaynkGtpOZjQk0bZuBjWNhE0q8bOzKe05AsaWM3kVV28moLtV+aPRMUO1VQGyn/kiPTbmpla3rumEDuOeee9DS0tL5KysrY3EEQRAEQfhhhL4RfeyNn9B9umo3AWI7CYIgCEJP05t200C2nY76CqWkpCSYzWb2Va22tpZ9fQMAu90Ou52v//NHAqZvJipNTTybvkq63C1jfBWLs3rzcHpAdbUA0FFP1xDGZlFXClsDr9yyhDgSDnVhhZrJS6/jj+YnmZQPZnozn6nNGEJdk2p28uXKygcJBO00bZfLYJa4mhqtXwX5skP106E9ma55DYUMVtR00LozN/C6bPEpLnqJvGw0ZRXYjv2K76yTz6irSzBdTZEsjqZ8nDV18HtIU8q8wU2vo/sM3IUcNO26ZL60f0R2JQnvKk0n4VPPXsPO+XDpVBJe5ilgcdSPc8Eo3u4z0mk7L69V3Zn4OckpdL11XUUci2ONp+6UQYPVRnGp9Dr1ynVGjOQvRru3Um0Qfzyv75SUZhKuqaHXjUtU1nEDaN9F6yUihS/bbW9Txqc6Pl5pytewbTW0LvNy+CqD4ka6/Dc4nrtTeBoUFwzFJTN6J+9PbUNoXvRYvnbaVkEbfiCK97mWDuqOEJdL663Zzd0VdOVrnT2BrwLwKq4wthb+wtxho2XsyKP10mCwdFr9oBeVy5d2+xXX6Nh8ek9N2xLZOcOnU3e2IhN/ji3ZN5KEC3IqWJxvt2HNwBVQOH7prt0EfLft5IsCtG9WGNga+LPJWkr7bczUehZn61rq+mNy8vFBr1X6qDI+mPhlUT6Ijrch/cj9wOyhcZg0ALh7iLWJ33fsMOqa1LaFuyY5leEqoHw9D7Zwl7JYpatvCnBpBdWDJJRK3XF0o8W/7cpKjTp+T34vzU+Qm4MIKjZYyc5UGiGSJ25OUWy7Bn7f6sonSxuvy5jhzSTc1Eqvo/m5fZDgpH5bpenc5S1nMO0nJQdoH5l26WZ2zvIPxpPwOs9wFkddQBMwsNPjhip2UDVt05qBO1N0GnWBcpdxdx09kTbiYICXZ0QGta/8pbRsMsfx96DKddRlzGNgX8ek0/y5qmj+7IMMfOm2KvZ0Ordf0Kqs5q82WG2mjC17KmldZgzlA0llXRwJt0zl9iCU8SmguKolbuGnNCuvPf44ft2IUtoP/Qaunm2KK70zj9qePtWmBAB1pZOD206WSjp225t4XbapqyyH0XoJ7uTvIipaPreDrfto2pYRtE34N3Kfx+w51J2t1sTtq5U7qUTH4KHcVv52G9b838NTQugVjvpUmM1mw8SJE7F48WJyfPHixZgxY8bRTk4QBEEQhC4Q1LVe+wldR+wmQRAEQeh/9KbdNJBtp6O+QgkA7rjjDlx11VWYNGkSpk+fjv/93/9FaWkpbrrppp5IThAEQRAEYcAidpMgCIIgCAORHplQuuSSS9DQ0ICHHnoIVVVVKCwsxEcffYScnJyeSE4QBEEQhCMQhAnBXvDRDxqp8QuHRewmQRAEQehf9JbdFE5r4NpOPTKhBAA333wzbr755p66vCAIgiAIwjGD2E2CIAiCIAw0emxC6YcSM7S5czvOpuI49nd/DJ3FK6riaoRZ+XUk7P4kicXxzqbCYrX7qGhY1nguEFZSkkzC1iaDbcQVATh1cjNktM1lA/WdtLn5TGVVPBU+0x08jlURyzbvpyK4wSguNJd/YikJ727kQqBeD830lOQSEl65ZQQ7JyaTiv21+riCXXSCgeCfmvYeKhKolu+QwbXsnCq3IhJnNPGr6LtFZbSyKBWVVADY5FEqM5qL5+2upMKXZjdvI3t3UmHxSEV78C3bBHZOzmTaHhs/5/Xkm0Tr36EqggKoqFBEjZXsGeW3VhGfhMHWp5NTaDsyGRR6hSeOhIeN3EPCK4upICwAQBGNVgXNAWBvLe2XMNFzQqu4aGD87AYSVoW8jcjM522tXdl+3r2Blu/JeTvZOS9uP5mEA0HuO23OoiKcphIqjBicxIXGHYo6tc/HBxt/BhUANRlss+xto8LdquA2DHy9Q4pAvbaPi0/qg2naegoXDbfvoWOWh2qy45RJ29g5qz8pJOF2LxefVDfMam6k41H8yGZ+3VWj6IEMH4ujlkSth49zicMOCeF7vPyee4OQbkLIaA/oo57OwP3KNtCxjGyD5Rvbybefi/9642hrrVafBQCSRtJNG0xv8/bccCodM9w740g4fgodWwHAc4Cm5WzgY0iAdn3oihZ1yMLbllMZkm0uPp7VJ9KysHCdaSaW7dhDx0CDbo3k0+izqLWO25mqMPbkdPqc3LxuKL9wDrWLAl6eYUuShx1TidhBz1PLN304r6caF283KppSxKZcbsc1ldIx2Oyl9R2I5vVUUk7Lz2Yg9l25mdpXsTW0TXxoG8vOSZmpbLjz3zgWp3kGteVMJt7WWpR70pT2aW3l+W3TaXnqNhYFE9LpZiRGtlN5exwJDxtLG/76fbnsHLMiLJ5tYCuXVNP3Hk2j50R+zjfgCMyjm150VPE2o1wGcQWNLE6Hsh29tpp2snkjtrNz3tg0h54T5GLfnhz6jHUeoHFaZnThGezhtlN7lvL+ZDAeaW00rXbVdlLDADRl46bIndx2cg2jaQdT+btc1E6adlsuvYcZM7gtuu0d+u7m9fINjFQjx1NPxxXHaC7kvfULqnIezDYQT1eKr87NB1lHwSEhfM3rBz7hl+lJestuCqc1cG2ngbs/nSAIgiAIgiAIgiAIgtAnyISSIAiCIAiCIAiCIAiC0C36rcubIAiCIAhHDxHlFgRBEARB6Boiyt01+u2EUnNpHOzWsC9oznCuY1RUQ/2sTWZeCUk26tPZdhJ3XG6vproqU8bsI+GvSwazcxz1tGF50rhfqBagDqdmNw1rBnop6VOqSFi9RwBIjaMaPw0VBrpQLdT3Nq2QivMk2Lmv+7YduSRs8vH8RSt+6l/b6e4z1lSq3QMA7jLqV60lcr/lOCc9r6KRa59EtNG021JomZetyWDneDIVf3gHrydzFM2PbyfX2VF90EOKdlBEkYH/9iDlHDtvn5Y2pR0l0Ti6nw9gJXWK3kUhL09LiJ6n74tgcbR0et6sXNruNzZQfScACG6jdek3cLNW9Y/SBzWzONX7aJs9EEG1j9JSm9g5bj/tu/u28fzlF5bzDH2LySOL2bHX180iYdsgrknhb6L6ATUGPt6eZhrHNJRqcWxuz2bnxOfT++xYFc/ihNz0ut7hNH8BLx/TIrfS9ujnMltwNil6bRNaWByXTtMOBKhYhM7lL2BpUuLwYQTR2+hjJzDFy+L4ImlfsNTSe1raRvWSAMAxjo5roVLe7oODFF0FJw0HgoogBgB/LM2LqYn3d81Pb7TFQJdm/NS9nf/vMHPdNUE4Gvj2R0GzhseFROXZDwBVVco4Y2AnJzqo7VR8hoEWWiXtXyMmF5Pw1n18zIusoWF3Fn8umhSJMquqoWNgO0XNovfJ7hFAfALVm/OWxrE4HS20b9vG03ExxcFtp6LN1Paw8uEM8ZXU9ljvVMomnZ9kKVa0LxO5/ZIQQW2nujpuO0W6aBl3pNFw83KuP+rPVWwROx/sg1H0mGMz13jSY2ldBW30ujF7eV22p9IGGTSwnawuel57mmJfG9hOTB+RS1RCU2yniF38FcmdTe978tAiEt5Uy22TqI20//ii+X2r+kcJyVzPs21PHAnXOKn2UVwm1TUCgHZFo6h6EzcIcsbRjqlqKE0ZS+8RAN5eOZ0eSObaguYGmnaDixuNehO1YULDafludPNdLq0jaNlYl/Hr2ly07lpUW7mdP8cTN9FwWzq3B5z1tGw80/h7j0cVyfKrQnDsFNgblTarClABSNpAw82z+YX8kbRtOato2qtcXOtWV2ww6wGumeVR9JrMTmrDBIO8z4Xi6D3Y6nl5mpRqCZZxLa7BJxR3/r/DKrZTf0Vc3gRBEAThOCAEIKhrPf4zsJcFQRAEQRAGFL1lN30f22n58uU466yzkJ6eDk3T8M4775C/a5pm+Hv88cc748yZM4f9/dJLL+12OcmEkiAIgiAIgiAIgiAIwgDA7XZj7NixePLJJw3/XlVVRX4vvvgiNE3DBRdcQOLdcMMNJN5zzz3X7bz0W5c3QRAEQRCOHiGYEOqF70i9kYYgCIIgCEJP0lt208G0usP8+fMxf/787/x7amoqCb/77rs46aSTMGTIEHI8IiKCxe0uYvUJgiAIgiAIgiAIgiD0IS6Xi/y8XgNxvm5SU1ODDz/8ENdddx372+uvv46kpCQUFBTgrrvuQmsr13A7Ev12hZKe4MdBXbOiai48nZtCRRjLt6exON5kenvNLi7SalOE0IY5qQD43nguWNheGUfC5jY+L5c4hAruegM0Lx27ufizy0uF0KxVXDSu1kIFy/LGVbA4e6uoyHH9Llp+ztFU/BsAglFUcM1ewpuGa4Ti3emmwnM/L/yEnfOPyCkkXF7FxWrLS2j+EtMNBIJjFKHx5GYSbormgpAR26hQnyp6DQDmFipgpwrEAYCmHNMVMUq9kIvyWRU14kCAtxG7IhDsrqf5TVzP89I0krYJRz0Xd4ydTPtGdRwXVI3cS+t3ZQsV6lNFhgEgqJQfE0sFEPRS0b2aXbzvmjMU4WtFzK9uDxWaBAxE7A2mwvdtp2KYFkUIf18EF8vMGUn7e8VWPo44B1MxV2znotwWRSw7wk4FKrc28Ot21NPxyBpnoGCtEOmg1w1s5uNI6zDalzUPL6yOVEWotZJfBxalv4SUvhLDRTgnjlc2NSgawuJ4fEp+6g2EOpU+BqVoLC0G96QIo08cf4DF2bCb5qfDp4hEGmywoUVSEUi7gQi/TxHuzx7Px9h1VYeEeL0+PwCDDt7DBHUTgnov7PLWC2kIxviTQtBs4TGgqpKLU6elUdukaaPBxh7p9PmgbjoAAJF1NDwqopKE9yZy2wllypjn4mOeI58KC6u2k3k7t+NavfQZF1HOxV+bLHTczplSw+KUlNOy8GylIteeCdxACMTQsSrCQGi6YYzSH1ppnP834WN2zt+jqehxQ3kci9O4n9ZvVHYbi+ONozZjXBq1r1wx3HaK2Uhtu/YUA/uliR4zsp1UgXW/Mk62jecn6epjx8B2MimbsoRqaP2nfsVfvurH0jbsrDOwB2fSl6jWRC5yHr+D1t3mxqH0Ggaawe3JijixwbuauYPeZ/v2OBbHn0ULVFdsJ892nl+zouWu867BhLqtyiY470bxlQtJo6md2byejyP+YdQuitzIbdHWQlpgNgdtE9true2k19Lr2BOObDvZlA04nGt4u28cRcPmDt5G2tT9f8r4dczK65OmmDOBOC6wP2xqMQlv3cPFyE1epS/U8PL0xyiC+krR2Jt5Wfka6XWGTi1hcXZuoxsJhJQNYdR+CwChaHrjMXt4X/Ypwv3xU+tYnC2lh2x3n89goOlhestuOpgWAGRlZZHjDzzwAB588MEfdO1XXnkF0dHROP/888nxK664AoMHD0Zqaiq2bduGe+65B5s3b8bixYu7df1+O6EkCIIgCIIgCIIgCIJwPFBWVoaYmEMfeu12PnnYXV588UVcccUVcDjo5PoNN9zQ+f/CwkLk5+dj0qRJ2LBhAyZMMNgO8zuQz4iCIAiCIAiCIAiCIAh9SExMDPn90AmlL7/8Ert378b1119/xLgTJkyA1WrF3r17u5WGrFASBEEQhOOAEDSEVP/BHkpHEARBEARhINNbdtPBtHqCF154ARMnTsTYsWOPGHf79u3w+/1IS+Pupoej304oRTk9sNvDfqatVdHs71Vr6Y36s7jjclU7PU8zWI91wqwtJLyoaDIJh1zUTxQATIMVDZg6PnPYuIf6tgdiqS9p7HCqEwAAbYoOQOSIZhanuYZqnezp4L7N1kbqJG1V/LVd71CNJQCwzqF+qaECro/i1KiTrKedls1TJSeyc9qbqX+xxUBvKqgUcSDE4xRMLCLhTfupf/G4PO7zu2e0ouHg4donwQ5a5p4M3o40RfNlVCbVR6n3cg0Yv+Lb7t4fx+KEFM0sDKFl7hrC254eTetJb+D3VFVF215ELR+g3CNoWukJVFehaTXXv0gYSX3mKxrieP6UsrJkc30pr0E9fBurgX7TkbQYACAqlzZ0VwttewnxbnZOyT7af0JJvP7tJkX3YQjvG1GbaDtqG03vYWQy1+tISS4m4eXrC1gck1IWrgba1rQ8A39yVaPIgNTsBhKubeFjbFDRF9JU//163j7L4+LoOTauFQBF08mR3M6i+MqpTkrh6GIS3rluMDvH2kLzu35fLoujqc1GCat9HQDscXS8t4/j7ai9keqz7Kvm/UczH0pMD8mEi9Az2KK8sNvD9kbQQN+jtYhq1HlzQyxOdZuiqWYwpEyYu4uE39hDbSdzCzcvg/mKXkqNgR7ZDpq2L17Rnyng44W3g45FtkLeR82VdEwp7eB2kFPRJLQ3KwPE61y/CfPpGNc2npenSXmGBN30vv+6/2R2TqiBPlNsrXzMCNrpdY1sp9wZZSS8dyfVEswfWc7O2TeRjl+BDl6XFuWYO9vgvhUpo5zcWhJu8vDy9AboOG7ezeOYPTRt13CadtNwrvnlV3RrnPW8rJorqAZRdCWLgqZCWuYJSc0kHPqS6xhZRtM49bVcs1B99vhzuQ6UblAP38ZIx8rspfn1xvJ2pOXRPtXWrGiSxXM7rn431UwKpPD6tyrt3jWMx0lcS++7YTxNe0gGbTMAkJpG35/WrxrO4pgVMy1QS8fCFlUTFsbPf5WoITTt5iZu/6u2kslDy9xWw+uxPD6OhHWbQf4U20lP5W3EUkLbfu4EqrNbvlIVgQJsTTR/O3dmsziq7aTqQqk2OgBo8XS890/h9rW3gdZLZTnXUMW3bCdVy/N4p62tDfv2HdIuLSoqwqZNm5CQkIDs7HA9ulwuvPnmm/jjH//Izt+/fz9ef/11nHHGGUhKSsKOHTtw5513Yvz48Zg5c2a38tJvJ5QEQRAEQTh6iCi3IAiCIAhC1+gLUe6usm7dOpx00kmd4TvuuAMAcPXVV+Pll18GALzxxhvQdR2XXXYZO99ms2Hp0qX4y1/+gra2NmRlZWHBggV44IEHYDYbKPgfBplQEgRBEARBEARBEARBGADMmTMHutEWe9/ixhtvxI033mj4t6ysLCxbtuyo5EUmlARBEAThOCAIE4K9sBdHb6QhCIIgCILQk/SW3XQwrYHKwM25IAiCIAiCIAiCIAiC0Cf02xVKrU2R8NrCwoVTR+5jf9/ZnELC3lYuPuneHUfCehpXDVu8mwvhEsx8KZkqqBqKNBAj7KBzdapIW0szFxpUBddMSfy6tngqEBvr9LA4dTYqsKubqACkdwQXRrOaqWCh32cgqKkIIULR2w1UUWFaAJgzfTsJr67NZXFCXpq/5jp+nU0uWl5RRbQONgX4dZ11Sj1lcIHgmHwqRh1p422k7XMqPliUkEDCoxKr2TmqIHDiqGYWp0ER8rXUKwKlvPphbqJ1EDTaSVJps55E3obNdTSt6kZ6j6FMnvjQKCqOqDGFY6BqJxXz9DsNxDyt9NpBRdTel8DrydJK+0YwiufPVamI8CtRWhq4WGb8UFr/HQbtvq2VihymD2pmcWrG0bRDiujq/tVc5HC/qi0YwcszblQjCTdvp23P4uY+zp7hVKhxWDYXtSxtocLtMBm0kVZ67ZAisGhq44K6FVU0f0ai3EPzqNLp/r3pLE5kdhsJb6ulmzBoVp5fk48WqBY0+F6i3GfUARqnnWcFw+Np+al5AYDIIlpW3ngWhQishwzEU3uDkK4hpPfCLm+9kIZgjL/eCe0b22n0WL5Zxe5GKkatt/CHiLZdEZo1eHZ+tXUECau9zVAKQrGd/FG8H1s6aByzYuL4mrjgsqlduW6Kgd2WSDtdTCS3nVqs9L51E+3XzaP5RgRmxXYKevmYrHkUoWnFBLOV83saM2cPCa+tzGFxVJtMr+J25a5meu3EvfTBuC9ARboBIEIxadr44wv6CCrknGDntpP2X/pcLBsUR8IjB/HNKlRBYPNYLrDeWk/v016rbCBh4AFir6dxAka2k4mWTccgg00alLTa6uNIOJjNE58cU0fzZ5DB1i302emJMGhHilCzpVax7Q1sPauL9o2AQZ8zKeL9VvUdx8Amtw2nz+iQge3kUzY1SkxpZXEaJysbjbTR69R9wTceqtXoMY1nD5YxVDzbsZkKodtaDUTZC2j5Zg6pY3HKm+LoAQPbyapc2xdPxwhbK6/bpkrFPrVyGzd1ON0Yp2YH3/wDQ2i/3FNFx3sHH8Jg9iji/gZ7qehKluP20HNas3l5Dkmi+VXzAgBxu2lb6xjEbYdvC6ybjTLXw/SW3XQwrYGKrFASBEEQBEEQBEEQBEEQuoVMKAmCIAiCIAiCIAiCIAjdot+6vAmCIAiCcPQI9ZK4ZEi+VQmCIAiCMMDpLbvpYFoDlX47oWSL9sJuD/uQrts6lEcYRHVCzFbuV+mPUvzLA7yiTIq2USiSXmfhqMXsnL/smkvCjljuix9ooT7e8flNJNyyg/pLA4Alj/okB4Lcz9av+MzXugwcwVWXXsVfOyuhCSrt/04k4YgLG1ickmKqW2Vror6eRpoJX+yhOguWNoM6UFyFQ7Hcd3h0RgUJbzNTsRNTA9dzYdpBBq6pFiXxihoufhI3k/piJyg6Sy0+rt/liKPt02biulUWOz1mz6btyFOu6FiAawfZPLyNxCfQdtTcwbWDzB5aGL5Mqi+RmkC1hQBgTS3VcBiRwPUPyhWNhKRorn/Q5KZ9Q1dGIc2gn44Zd4CEN5ZxUQfV9fiUYTtIuMHHHe3rvPRYYzkvK2srvXBVaxKLY1N0CnInUp2gIgftXwAwJpXG2dvCr9usjBO2Vtqmx8ylOhsAsK2JavzsquCaP6qmR1RyG4vTlkDrwVxDne+NXL011e8/xCNVuamWgVq+ANDWTse17EQ6ZpW4eVlpdiVtIx2NEjpO2KY2k7DPw8fTnfVUr0EP8fYZMZnm78R4rl3z0f7Czv/7fXw8EISjQqwPmi3c+Hetz2V/9qXQsZ71WQC+aEUDMsD7qMlLjwWj6XVuHcdtp79tobaTKY7r7pibaB+0jqRjU3AL1eUBAN9w+uwMGuin6R10zHO18OsYyKEQkpNc7Jj1ZfoAC1zDBdLq99Fx3KGYV6o+CQCs2Z5P03HxOlCl5Lxx/Abys6gg0l5Ff8bWyK/boUid6EYae4rt1KhqwACwn9xBwnGKzlKTj2s+IYHGUfU9AQAORbdqMD1HL+GaVP5oeg9OD79vexLNb6Cd58+iNAF3Di2H+EFcJ2hdFbVXhiVxbZ66VFp+0TEdLE5bG70vXdHL1AyKKm9KKQlvL85gcXQT7S+zCnbSvBnZTh20/3hLuL0aobRZlyuOxYlsovcQO4Pq7lQ4uU0+IrOKhA80cnsgsIXaGfYWWk+Dzypi52yrp7ZSSSnX/DErem22NP7+51NsJ0cV7eBG70q6Og4bjEW1rbQebC08kruVjp+Dkqkt39DKyzOUbCDYqhC9n2bacwLVagp0cHGmvTWKxpOBbR+cRcf32YOKWZylOw9pHft8RxikhT6j304oCYIgCIJw9AjpJoQM1ZKPfjqCIAiCIAgDmd6ymw6mNVAZuDkXBEEQBEEQBEEQBEEQ+gRZoSQIgiAIxwFBaAga+f72QDqCIAiCIAgDmd6ymw6mNVDptxNKFlOoU9/GZ+M+k9EbqZ9o+3gvi6NibeS366yh124tpOG/7TuZnTMrZx8Jf7VtBIsTRd3W0ZBC/YtNqvM7AJPip54T3cji7C2n/u9mB9fi0JuoL2tA0TYorlD8WgFY5lK//yjNwE9VcbP1JlOHbXM7X/Cm2ZSTUrm+QKCD1ovmO/LCuZBf8VE20GGJGk11TeprYlgcXe28BpovgbX0vIrB9J4sUfyeLPupr3tDPouCIYlUSKHRQ/313VHcr9kcQdPyx/Kycu+Kowfi+XW8qs+0Up61+7nmj8lPy2aTl+tWReyhx1piuFaYnkH7ano29Zm3aDy/5e3U7zs1iWs8VVXROCs/G03C7RlcYEBta85krvnUbqcaWYU55SzOvibap8rXUo0vjctsYaOH6ipYIng7CkXSfpiwg2pFuIPcbx2rqLZB9DSujwSlK7S28Aw6o2k9+ay0bkMOPkZERVE9AVVnAwCa6xQ9hhReL+ZGmlaZFkfCE/OK2Tn1Hq7zoFJhozoVWVF0jHA7uIZSyVZal5bsdhanwUXH90/3jWNxMocfaucer2goCT2DyaTD9I22StDO+2jS13TMa5h6ZP0Mex1/zkRV0n5bP5H+/W/bT2HnTM6juiUbN3B9zKhy5brpdGxyGAx5mpK9jFj+fKgooTorupOPOxbFRvTH0PKrK+X6Izib9uVUjetCqY+0dkXWzsIfOwgpmnC+DIN6UnShVF0rgNs4WlDRgDHQYcEE+swIVRx5bFXtQwCIWEHtoKZhtC71aD4ORu6mdeAaxe8pM5mO200d9LruaD6O65E0LV8cfx+wbaPjuJ7Ay6adPg6gKbaTe08cO8eivJ7s8HBdw7jt9DreWK7xpefQe4gdQtu50fO2rI3mJyGZazw1K9qRmz+k7zRtXLISJrWZp/F3sA7leZqXV8XiFNUrtuYK2k8dEbz+d3dkkrBatwAQUpps/PpmEm4LcJ2tmM9pfl0ncX0kxNL8+Jt4WzPH0sIJ2Wk/NRqXbTG0/EwG8wr+atrO/VwOC7Z6mladiRp7BcPL2Dm1iu2kGaRdZ6PtMT+Gtj13BB+YG9ZTu9g3hI+Nrc30vefL3aNZnISC5s7/e73cThb6B/12QkkQBEEQhKOHaCgJgiAIgiB0DdFQ6hoDN+eCIAiCIAiCIAiCIAhCnyArlARBEAThOCCI3vHRN9i9WhAEQRAEYUDRW3bTwbQGKrJCSRAEQRAEQRAEQRAEQegW/XaFUlqUC05HOHt7ayPZ39vGUnEvIwGzc8euI+F3Nk9icVqHUHE0Sx0Vg7Vy/TqsCOWRsB7FBeHaxyvzjA1UuC0+n4oKAkBdvSL+vJmL8pmG0fsOdvAqVGcJE1PoTTRWxkJlSAIViG7xccE626AOEva6FDG6RC64lh7nImG7mZdVpYXet6eZp71tZw4JO1OpMG7KRCrsDADVbbT8bM1mFqfRT8ti2NBKFqd2J1VhtCrXCfj5vKweTduVzcRF+KqX0Ou6qc4gYrj2M0wzqHBfh8VAcNtG6yVxEG/EahvQleuk59excyr3UYE9SzkXI9R0ep9Tp+xkcdbXZZFwRRUV7o6K56LH7jbaJnQD8XRNOeZT6iAtlfe5js+pIGRLFL8ney2t78ok3n8CZVQsMZhDhQNNDbyfqvXi9nJRQ08EHUeSrqRq/+VuLhKrCmia9/NxRFOGp4ihXLhb9eV2ZtI47ZVcqLVdEW/VDPQTmUC5k0dKG0o3JGhop8KNGyuVzgK+qUFsJBfUDPppXW4uooUVUc7HiKRJdGypPcAF6yNqadgbx9tntetQPYiwpNBTpMa2wmEPjzdVVXwDjvrJtJ8YCbCeOmUTCX+6ZhyL0zRc2Rijml7IbiD2vDY0mKYdzZ9f9dPoMatqk43gzzNvHbUR29YmsTj6SHpdk5v3dRVHOlXL9pRxWzR9EH2uuLzcfgmlKLZRCx3r/YO4XZQQT8dbu4XHqW2mY7se4M+Qkm3UzjCl03ExchpXBK930XHc1sgbiddPyyJ7ZC2L076ZjpV2VfTcx5+LvhhFRNxAaLrjfXpdXy6ty4QS/p3ffRKtA5+Ft88OO21rESm8bNQ2oCu3EDuCb6bTvIvaOBEl/L5V26nwhH0szsZq+txrrKC2iCWBC2P7W+k9qXYSAJiU4vIpz6+YTC5yb/0vLYe6GL5JS6SyOVFlMt8Yx1pCba62ITQzqsg0wOvF4+FpB5UNTey30LKpaOV2nG8oTcuyK4LFUW2n0AhuZ6j2qZ5N45jK+BiBEiUt/joFLYLekx7B+0b0SDo+NrtpWtvLFVV5AFBsp4hI3o50ZQObfXvodaJK+WWdM5tJOKRuGAQgqoreQwc3r9DYcqit+XxiO/VX+u2EkiAIgiAIRw8R5RYEQRAEQegaIsrdNQZuzgVBEARBEARBEARBEIQ+QVYoCYIgCMJxQFA3IdgLX8B6Iw1BEARBEISepLfspoNpDVT67YRSRWss7L5v/GIjuO+4Vk99xQflNbA4n3w6mR4YauB72ab4dCfStOxN3H83MoL6l7rruV+9PYrG0dJp2u0+7us+MbeEhDdYs1gc1fvZ3MEbX0Iu9elvUPzhH57yETvnVzvm0QNtvGk4amhaaYq2SMMOrltQGaR+yo5iA52YTFrmjhpe5t5s6lDc0UT9gssqua9zMJL65p42bTOL8+n20SS8by/3L9YUuZasEdQxvKQohZ1jTqV6U6G9vI1YfDR/I0ZS0aSdify6tgCtF6ZjBcARQ9teQy3X0IFT6VMBWrc1Ln5OMJo6j+sarydfIr2nFcVDWRyTi97DnLE7SHhbM68DUzQtz/YD3Bdfy6R+6prSRqrLuXO2dZDi6+478mDuC/L7HjPuAAlvqcmg1zXx/hRhpW26oZFrEqUNaibhPeuplpiFy03BMVrROnKpokWAJUIZj9y8HZkVXS1PO43jaOJaDP4Y6osfTOZjrnMPHQOisrh+U4tH0cxS/q7qJQFAwEvLeER6NYuzung4zV8MbdOWsVTzDQCqaqhOlSOtg8VJzKe6BSXVvK2Zg4fKy0gDTBCOBlXNMbDbwrZTMIprbNhqaT+JGM71UVa+M46EAyP4dSxtdKz0JtM4Tm6SwRalaEDWcC0RTemTyKLhDh/XSxk1hD47t1syWBwVSwfvg46htP+7Gulz++HZH7JzfrVpPgmbW/kzJKqKhs0zaJl7NsWxcxoD9BkcvY9fN5RLx8FILgGJtsG0/Mz1dBxvKjfQfIqi1508ZweL89WmkSRcsYPbKyYqmYX4QtooGvZSbSEA8GfQNhK53eDZ5KHPlYwxVL+paBDXDjMrek26i7cjU6xiZ1Zxu01XdGwQoO2ovoU/xxGr9B8Tr0uPYj6v3TeYxVH1O6dO3kPC2xrT2DkmJW1tD7eVvdmK5mMjLZvWYm5v2VPofZs8/Jms4g9yOyh/chkJ76xMpREM7MwIG62n9np+T7GptC9Xr6ZlY2vl+fVOpDakp4W3PfY+2srfaXSrUt+N9B4iGgzSjqXl6UnlOmBxO2i7Cc3iGl+tHiU/uqpJZlBPXpq/kdk1LMrWA1Q72B+n2IeTuJaUX9H40jK5NpOlQNHDKo9jcfRv9TE9ILZTf6XfTigJxwfWYACRrlbEtHsQ6+5ATHsHEmu9iPF0INrbAWswCJOuw2QNwhQKAToQMmkIwYSgKfxrc9jhskXA5XTC5XSixeGEK8KJJrMd7XabseqoIAjCcYYODaFe2P5W76UtdgXheETTdUT4vYhpbEdsewdiO76xneo6EOPtQITfG7abdB3YFIRZ1xHSNIRMJoR0DUGTCT6LBS6nE63WCLgcTrgcTrQ4nWh1ONHodCBgPrJouSAIwrFOb9lNB9MaqMiEktArmINBpDe0YEhpKzJaGpDZ0ojE9lY4Az2r2O83m9AUGYnyxDg4K/1oznDCleGEP0KMJUEQBEEQ+i/R7R3Irm/E0OImZLQ1IrWtGTG+dpj1I68I+SG02e2oiYlBWWICIjo8aMqMgGuQw3hLZUEQBOG4RiaUhKOOputIb25EVnMj0nfVIauuCekNLbCE+LL5rhI0aQhqJkADTCG9y9eyBkNIdrUi2dUKFB067k6woSXTiZDFjNKkBBQnJcJn5UugBUEQjhVEQ0kQ+i8RPi+ym+uQ6WpE2o4GZNU3Iq6du9h2lRA0BE0a9G9WaZtDoS5PREV5vYiqq0NeXR2wK3wsYDWhOd2JpowI+IJ2lCQmojY6RlaBC4JwzCIaSl1DJpSEo4LVF0BBZRkKqsoxqroC0V7uT/ttQgCaIqLQYo9AU7wDrggHWiKcaIl0wtMRCZc9vAzbZ7YgpGnw5tCVTLrHDE3XYQkGEdPhQVyTN7zs29OB2PZ2xHg8iPaFl4MnudpgC1J/5MhGHyIbfTgbmwAAfpMJe9JSsD0jE9syM9ESwX2yBUEQBEEQjhaJDW3IK6rEqNpy5DbVwcQU4ygesxWNzii02pxoTHSixemAyxmBlggH/K4IuOxOuK0OBE0m6JqGtsH045u5XYNJ1+H0+RDj6UB8iwcxng7EfGM/RXs6EONvR6y7HQntVKTP4g8hqcSNpBI38lEHAKiPjML2jAxsT8nE/kEpCBnoAwmCIAjHNv12QknbHgHNEhYXcxp5JykLVKqtXARVz6XiaZqbX8gUR0XC7FZ6TsjEBfY6aukxJsAGwKRRoyDKTtOpLuH53WemQoJGH310JSkt0cfi1NUoQmiKAOx9y89g50QoApodqSwKOrJp2axqn4o5e3bgpD3bMePAHjgCXDwdCGvCNQ2JQO2oaHySMQq781OxNy8ZHRHh+k2OoIK2m8sy+TUUYTnbLio03JHFXeesDeHmbQ4GMaSuFqNqyjCmrByF5eUYVVEJp//QOdZQCAUVVSioqMLFa9ZiW2omvhhagM+HFiBDqyaVUVKaTNLJz+NKmHv3U2FpUyQ3EhtH02NN+6gIu1G7ckbRr5UecEFNbyM95qjlBl4gih4bUkDvYU8VvUcASEqg9dRg0DeUZg+znQsLDlVEzf067Zft66kIMgC059DrzJm8ncX5Yj8VXNYUgejsHCrcCQAldtoPjQQLtaG070bbubDgpipad6EOek9WH+/MZZU0bbOD95+WNVSpM5hI82cdykUZ2xvoZKjZw9MOWmj+Bq3kcSxn0/quDtFxxVbI0w4UK2LurQbCp0F6D7UNXAA+Lpa+yHiKaJwhoyvYOXsPUNHNjXV8HInPbSbh9nW0rbkTeF4Sh1AB3YYaHqeyhJa5NoiPR0HfoTIP+b7/ak1BOBzRG22wW8L9LmRgO2kh2v/arFxwN5hP45jdBs+QeDpeWWzKpg0mLmgbrKLPphDXs4VVtZ0cdLx17afjEADsNyuKxkYLZpSh3TeIj7eBStq3zcrj6zefnsnOiatTyjODJ9465FB/N4VCqPBmYe6WHZi7dQfyausMMhvG5XRga1YmtmZnYFt2JrZmZaI0KQH6wUmbo+H1dphrxLndKCyrwOjS8vC/ZeXIbmgkcZLcbThxz26cuGc3XE4Hvhg5AktGj8IXo4bjlA1UNLr+ABXhTh/B771qN7WDfbG8PN3p9Lli3kUNVoM9MGCNpu3IC4PG10CPRVbxKL4Y2hdSx1EB49IyLggemUSflW0mgw+WSj1odv6MSC+kG+GotpNlJbfJ3Mq+KNNn7mZxVu3KJ2FfLM1M4lC60Q8A1FXEkbBuYDt5htM+FuPgH5p3lCq2soeWr5m/4qC+jD63dSe3M7GCjmsBZYjwDed2nF5Lxyyrge3ks9D8pS/lO6N4Lqf33Rik44p3PE9b20/bhMXFx1zVdmqp4/VtT6DvCKb99J4GTeJ2cOUe2mY3V/NNDRxDqT0YobS19iTepiPy6YYrnkoucu86QPOnG4iRa95DZaF1YeMcoW/otxNKQv/E6fVh2u4iTNxfgpy6NwzjtNut+GpsHtYW5GDYKbWoHxEFf2S4qb1ZNqk3swsACJrN2Juahl05qXhrSnjnP3MwiLzaWlwf/TmyNzdi+Jc1iKs5NBAXVpejsLoct674BE0REdicnYWVw/JRHceNWUEQhIFASNcQ0nvePaU30hCEAYOuY3BdPWbs3ofC8gpEeg3ekgHsS0nG5wUjsDk3C1uzMlEyKLFP3cmaIyOxYsQwrBgxrPNYrLsdhWXlGFNajhl79mHa3v2wfiNBENPhwdkbNuHsDZsQMJlQlDQIa3MHY1NWDvwWed0QBGHg0Vt208G0BioywgtdIrOhAbPW7sbEfaXMfQwAaqJj8Pn0fHw2aThWjx4M3zfbFt8yallvZ7VLBM1m7ElLw8aTc7Dx7BxA15G2qwXakzactHc7CmoObUMc396OObt2Y86u3dibkoIvR+ZjS06mLO0WBEEQBMEQW8CPiaXFmFG0G5lNzezvQU3D2qGDsaRwFJaOHoWiFL66pb/REhmBr0YMw1cjhuGZU09GdEcHTtyxG6ds24GTt+9CbEf4w5wlFEJ+bQ3ya2twzqYNWDM4D1/l56M+mq/wFARBEAY2MqEkfCfWQADjSkoxa88e5DY0sL/vSM3AZ8MK8PnwAmxPywDGthlcZYCgaagaGYd3Zs3G07NOQ4qrGXP278BJe7dhRvGeThHw/Joa5NfUoMXpxMrheVg5bOgRLiwIgtA/CMKEIHpBlLsX0hCE/kqyqwUzD+zB5OIDbCdbj9WCJYWjsGTMKHwxagSao7gbyECi1enEBxPH4YOJ42AJBjHpQDHmbt2OuVt3ILc+bDdG+nw4afdOnLR7J3ampmFF/jDsSE8/wpUFQRD6nt6ymw6mNVDptxNKjnEtsNvDq1zadsaxv/sTqH9xakYji1NdRjVKdIeBb6YS9vmVIkkwcDBXfIWtjVyoICpV0UyqoL7jpji+5DkQpA1Ja+D6Ixn51Oe8qpnrH5gUf2KHnabl9XADxj3k0DnxbW7kNrbgkmVrEe+m/ritDgf+PXkSXp8xA/pphwylDFSg7CuuWfLX4Ek0bzu4z2/lcEXzqdTJ4gRT6D2krKVGWkkSrwN15aCWwv2W31gyk4QvuHRl5//bALyPQjxWcjJO+3QHznlvM7LLwr7ksR0dmL9pG+Zt2YGdX2Tiq+zhKEpI6TzXpLQbo7QLk6jv/fYqamAlxnKNmoY6+nXPUcPv2x9F0/YZtGGrixbOnnKqQWBr4Net99O2ZnZyDQrbPuoP7Uk1uE4EbQN7d9J2E0rn2gHRe2nfWFlbwOIMKqBjQGMR9bMvbeDaTOZWmr+QwYjob6EHM0dzzSz3l3SsaR+n1HcTLwdHLNUT8FdyH3RfnDLWpNP+2FHF+7IpgfYVPZIvoR2ZTNte09m8z9W20LbmPKDoVozj7TOkDllRvI0EHcp1LLy+XeW0rdmyqU5B8Qbu458xho6NFeVcp86raCIkTKZtZkQk14rYWJ5NwjFJBrpVrYr2ShNvSCb/obR1v2goCT2Db4ob2je2k7aFjw8eRUskNqeFxWkpos/kUISBtpwyrHxbIwwAOpIMlu4rtpOjnsdxZNCxs6WE5iUYb6CXothOtjo+3saMpH27oYnbIiEn7ZcWp7oZCNcsbBkevidN1zG6tBwjt1Rh5p59LN7G3Gy8esJ0fDhhLLzH6I6yAbMZq/PzsDo/D7897yyMLy7FlStW4cwNm2H/RmNzZHUVRlZXoTw+DjtW52BtSj46rIfsBpPSbvzpXI8uL4WO9fvKUkg4Mp7vjNdeS/tCJJfhgy+Gpt2RxOPYW2gbLi2mepOOWt6m2/1KW4vgbThmF22z7nT+YtkQRW2Eqi30voPZvJ8mbKdtelPVcBYnaizVx/Hup8+z2hou9WBrpvkLWXnapiZqD2ZMqOZxltC0GicrNoPBe5Aplto45nKu1+ahr1wIZtFxxVTO+3IgiaYdNLCdcjNo22u5nF+nSRlbYvbQsvJN4WUVVCS9AtHcRvA76HV0K29HwWLazoND6H03rOL6qHGTmkm4uZjXt6+D3qc2g7aZodH0GgCwo4S+09hSDHasbKVt2l5voHX8rerWAgPXJexYp99OKAm9T6THi1M37sDs7Xs7feIPsj07Da9NnYn3JoxHhz08eA+GwRP5GMQd5cBb50/AW+eNx4SNZZi7aBfmbd4BSygESyiE0bWlGF1bij2Jafg4fxwqYviLrCAIQl8jGkqCcJTRdYyorMJZ6zcjq5FOWnVYrXh38ni8Nns6tmXzD27HNJqGjYNzsHFwDn573lm4ePUaXLFidaeod2ZTMzKbmjG7fCe+zByFVWnD4TfLK4kgCP0L0VDqGjJ6C7D5/Thhww6csnkXnP5DM/ReixkfThmN106Zhg152TA1GuyKcTyhadgwIRv/jpmC1KZmXPblGlz+5ddIdoVn6oc1VGFYQxU2p+Tg/UljUB/NV48JgiAIgjDwyW6sxxmrNiC/mu6cdCA5Ca/NnoF/T5sIV4TBjl7HGU1RkXhu7kn4v5NPxAk7d+OqL1fhpB27YNJ1OIM+nFqyCdMqd+Pz7NFYkTBU9CkFQRAGGDKhdBxjDgYxff8+nLZtG6K9h9xvfGYznj99Fp4/fRYaY/iycAGojo/DE2efir8tOAW/e/p9zNu/BYkdYQ2psTUlKPyoFKuH5OGTwtFwOcWgFASh7wnBhFAv+Oj3RhqC0Fcku1owf8cmjKkqI8fLEuNx3yXnY9nIYdBlUoQRMpnwRcFIfFEwEpn1jfjzM//ChNoDMEFHjL8D5+xfgxnVO/HfkeOwJT0beh/ucCcIggD0nt10MK2BSr+dUAqujEXQEvadHTG/mP191/pcEq71cjejwcOov+6Bcu47qvr9z8jdT8Irg0PYOaZ66tM7ZcouFmd9LdXdsMYpeinN3O/WsoGuAAoZ6D2XVSr3aeK+uKouTIedVnPer6sw/KMaTP/rfsSWH8pXwGTCvyZPxd/mzoPLFweUAt/2xj3jipXkOv/+YhrNbzL3552YTvVmtu3OZ3EiI6iP7+gTilmcr7YMI+Hg/6N+zLmPKw7TAEpPV7VaeP4SCuh1PvjXDBbHQqsOpomH/IBDAO5eeA7uDSzA5cvX4Lb3l2JQaxvMuo6Z+/dhYnEJ/jV0FnafEgWPneZn+4EsEnZW0oHENJH7UNtrad36Iw30kVqpEZY0vo7FqdpHxQHMilZE9hiqsQMARTvTSDho5r7Oql6TkW5Z4Is4ep0Cep856fXsnDI/7buWQdwXu3WL0gZiaF5Gp3Hto20avSdTPV+Fpyu3ud/FhRU8ibTMg35alxYDuzhYRH3dQwZ1mT+C5vnAVqodFIrl5ZufSMvvQD3Pb1lrHAm7q/jE8egRxSS8uZ2OaR1VfAWevYneaHo+r8vySlrmRkt8TcpthfbTSdmCyUXsnI1FNH+JqS4WR9Ugq6ulWgF1GtcOiI6j+k0OK9eFak2m/cdm53F8nkP9P+DjfxeEo0HE5w44zOG2Fnc+H/MqVtMxpNUbx+Ikj6L9trqE21e6j45xE4YUk/CGQC47R9U2GjV7P4uzqVLR1EugfcvcyDVV4r+mY0jTCD6WNlTE0QMaj2NrpfcUtNHwVxNzsPCjxbho1VqY9UPnFw1Kwh/OOh0fjR/d/yeSDGRB+4LypARceN9NyKuuwc/f/xinb9kGABjkbsWP1n2JLVmZePTs+UgE1xst2k2fITHlSoTp3HZSNZN80fy5Y2umhWOfxvXFWnfFkbCuaEkmTOY6fHVb6O59fgtvI6rmmKrnBQARH9H3BvcEmt9B2TztJh+1iwKpvDwj19Pnvx5H/56fybWP9mqK7qaBbplqOx1oNhhHFP1TXc2ege1kO0A1k4zs4LQxdNVgzXqqN+U10BbNSqGaimXV/L2iskXRlyvn+pPDRtPGtq+Naglp5fwjc0Q9zU/ySK4L3FSu7AIZ4oWjKaaFYzctq+zZdBIcAPbsoWOuM8NAJ7KG2qv+atpmdtZyG9IWT1+ejGwnVwo19kwOHifUcegd1ucT/cn+Sr+dUBJ6hoTWNpx/3UZkfU0fPB+OGYs/nTYfxYPCA5aDz0EIh8FvseCVk2fgzRkTcf3iL3HTh8sRGfDCEfTjR7s/R0u5A/+aNwG7Bqce+WKCIAg9QFDXEOwFH/3eSEMQeg1dx7QD+/E/7/wb0Z5DH8BqY6LxlzPm4Z8zpiBg8IFFODL7U1Nw0w1XY1xxKe5+7yNM3xueZBxTVo7Xn/o/rB2Wg//MHod2BxdeFgRB6Gl6y246mNZARSaUjhM0XcfM3ftwzrqNnbttAEDJjASsXJiHe4sv7cPcHTu0O+z461lzsTQ0Az/a+RnOP7AStlAQsW4PbnhnJdaMysa7J46Bx3Gc61EJgiAIQj8nzu3GpWtWY0TNoVUaLqcDz847CS/NmYUOuzzLjwabcrNx2W0/wYk7d+MX7/8XBeXh1XWT95RgWHkN/jlnErYNTj/CVQRBEIS+QCaUjgMSWttw2cqvMbzqkBtTa6odS38zEiWzv1mCWtw3eTtWabZH4a/jzsa/8mfh5xvewvSa3QCAKTtKMbykFv+aNwFb43P7NpOCIAiCIHB0HdP278O5G9fD8a2PcP+cPhkPn3cmWiJFG/Goo2lYNmoElo8YhgvXrMd9b72HmA4PYts9uPGjFZ2rlTzgbo+CIAhC3yETSscwmq5jxr69OHsTXZW09aJ0rPh5PnxRUv09TXVkAu6cdR1ud72Bs5dtgdMX6FyttHpoNd6eMkG+cAqC0Cv01va3A3nrW0GIa3fj4g2rMby2qvNYkzMCC6+9DMsKRvRhzo4PdJMJb06bjOUjhuHF519AQUm4Hg6uVvrXpKnYnpF5hKsIgiD8cHrLbjqY1kCl384otGUA/m8+QhS7uDAaVF2uRC40V7mOCvdZuA42Yoa2kvD2JkXsL0pRZAbQ4qG+8utXcAPDH0UF1kJ2Gra2clE+V54Sp4U3rGAmFSyz2rgorydoR3ybG1csp6uSKuLjcPeVF2HVjBxA0cIsmHaAhPc3cvG8f22YRNP2KCKCEVzkbnBkAwlvGsqNAG81FcpdWcrFfi0dtLzKShSh4QsNxOmo1jf0Kv5F8crRn5PwX8aczOKcM2IjCQcVFf43v5zKzqm9kLab93PH4auaobjuka8wdnVYsG/avgMYVV2Bd88Yi31DkmFNp3XZsI+3e8tQKhCslXFBQLVvlFfx68TnULFJtfT2VXEBe8TQC9si/CyKfTftG7F5zSxO5RBFELydlmdpHc+vI5Xet74rksWJGkN1wbwBOrztX5bDztGUZhSMNBD8U5p1ooMLFobyaQm2ltE2bKXDTDh/w2gDHRTLr7t3H13ib7IdWVG1aBsV3UWal8Xx76R9LpTKx5FtNTRtWwy9jt9jII47ngpJluzmmmHBJJqWuYlfx5pORdf9yuYJO9YMZudYlHnZlkg+4EfF03bk8dG0E6N4HdS10LLy7I9mcfQkOi77DB6tpm9tCqAFeXkLwtHAlWOG1xpufy5XPPu7WRni/IMMROZX0ee/3WnwfB1On3E7Gmlft8cYjDse+rzavYRvemKOUdJSbCebi+elaTh9htgMbKf2bHqfZgPbyR+0Ytq+/Th//Xo4/HRV0m8vOAutEQbP267QT4SwBxo1cbFYcOf/wwVr1uOB/7zbuVrphuXLsGFkJt49ZSw8ditM2bQuO3byzRUCI2l7tBZzTSZVp72xnF/HMYQ+IyKUyq0s57Yz4pQLR/A+F7NN0eCax42GphFxJGxRHle11Ty/5nR635HbDD5gTmojQc1Pn191n3JXQ1sK7WMBA2FstTwTIvhmKvWjlL5bTO10Wwu/bksBre8YZeMMAKjYSW1YTaluzcDUq1uv2L2ZvJ5smxVh9Eyevz2VVADcFE9t5WAH11sz59I6qNs6iMXxJyvviI38OoEsWt8+xXYqW87fwWx2WpftUbxvWBLpdQNeet2YGF63LY3UTjfv5uOnptxTyGhawvqtytJFlLu/0m8nlITvT151La5buoKIRy6aNRUPn3cm2pwOmMENPaHnaUyJwuNPnIoTPtiLK//8NSLcfsS0eXHFv9bgsxOGY/WswYBskysIQg+h6yaE9J7fhUrvhTQE4WhiDgZxyeoNmL7v0Ne2yrhY3HP5hbIqqS/RNPxn6iSsGJ6PR/7xb5y8I7yr8oSd5cisbsYr506DK/l7TvQJgiAcgd6ymw6mNVAZuDkXDJmypQi3/vfzzsmkxsgIXHnbDfjV5ReizWmwREvoXTQNy88ahl8uOg97h4S/QJgAzF2+G+e9sxkWv6xcEARBEITeIqrdg1veWUYmk1bl5eG0e++UyaR+Qk1cLH58049x55WXoMMe/hae3NSGWxd9gaEHao9wtiAIgtCTyITSMYIpGMI5n23CRUs2whIKLwnclZ6CR887HStGDuvj3AkqjSlReO2iKVhywvBOD7WCHVW4+u+rEePiS0cFQRB+KEFovfbrDsuXL8dZZ52F9PR0aJqGd955h/z9mmuugaZp5Ddt2jQSx+v14rbbbkNSUhIiIyNx9tlno7y8/IcWmXCMk1HXhDv/tQRDqsLu+T6zGS/Pmol/zJiGVqesfOlXfLNa6a9XnoSqpLBbudMbwFX//hoz1uwHdPEtFATh6NKbdlN3baf+RL91efvRlGWIcoTnu96qmcD+7kpWVnJ4uS8pFJ9e3WBjiAQH9b09UE9FVbQ6flJEJnVcbjcQZ9JUoQKlkfis/MFniaR+toEg92ONcFKtqHfNJyK2w40n3vk7ppUc0kF67ewpeOLHpyBoNsG8k84bhlSNAgA7qqjP773jPmJx/vfXF5Bwaza9jrmDl9VHxdNJ+KRzN7M4S3bQL4C6mc9zBhTtmLMmbCLhag/XXVq7LY+EL5+2isX5w/L5JGzkk/zv4pkkbPLR+7YM47orfhf1U99Yzf2W98xJxn/njMbsk/biocfeR2SHD2nVLlz+6los/OVFSPFz/21vPTVwTQY9ePSsfSS89gDXm3HviaPXGUzvQWvn5ZAzpIaEa9q4lkw7lSBDW6OBT3+SomWwm/Yfn85vqsNP24Qlj2ub+VbE0XMmKD7fg/nqL1UHKtTC+9zZBRtI+MOvJ7I4FreiJ5ZL+2mk4h8PAJqPtpGGA1zvRB2hLanKZGMFf+HRU+l9B9t5eTo7aH/SbNwvPdRK+3NOLtVHOtDOffxrXbRNBKMNVtyFaFlpPj4eeZtomxiU3kzCzXn8ugEXrTtziF833knLr7IiioQj46kOFwA0VdB6MtJ00IK0jH2pvO9+W2txIC9r7gncbjfGjh2La6+9FhdccIFhnNNPPx0vvfRSZ9hmo/WycOFCvP/++3jjjTeQmJiIO++8E2eeeSbWr18Ps9nAPjhGuWj2ik7b6d+VfKxypyp938PLxheljGcGtlNKBLWdKhStPlsdv64ph47bblX4DIDObCeKx2bQd6Jof/MbZNiq6Na8lT8VZ2zYjFvfWganP/wcqIqLxY03Xo2tOVmHzUO3UYcimff4QTwz7lT8fcQJ+NOrb+C0Ldth0oH5n++A2+3Ery+9AOds3sHO0epoWwsZ2E45p5SS8PY92TzSDqoL4x1Kn7fmNv7cSRxGn531rVwDsjWD5s9Xx+0rLZnaK9Hb6U1oOu9zfh/tL+7h/NmUuJjqFrmn0z7Ykm/QYJX3FZOBFuK8CdTe/2LZOBbH2kav3TqUPtsdQ7l9bVVsJ88+bv/DTK8bVLSkLGXc1vNk0LIxuXl5WhUTTDewncwt9Lzkoc0kXO3mOqHNzbRNaLFGep7KOxeXDkaogZZNTBbV4modbvC+2kLrTjewneKU8b6llN5DVFIzO8evaIk6mvg9aUHaPjsyeNq69q04QbGd+iv9dkJJ6BpD66rw5H9eRHbzoa9rv7t1Pt6dO7aPcyZ0lS+n5eO6J67C4w++hazqJiQ1u/Hiva/i7TGTsSZ3aF9nTxCEY4SQ3ju7iIS6+cI8f/58zJ8//7Bx7HY7UlO5yDsAtLS04IUXXsCrr76KuXPnAgBee+01ZGVlYcmSJTjttNO6lyHhmEbTddzx/sf42cdLO49tGJyNn9xwNepiDV5OhX6H2+HATdf9CAv/uxi3f7wEAHDhmvUYUluHD3MnodXBN2ERBEHoLr1lNx1Ma6AiU30DmLziWvzj1b92TibVR0bjmstulsmkAciBnEG49PEfY/WYXACALRDEJRtWY8G2DbKMWxCEAYnL5SI/r/f7bwjxxRdfIDk5GcOGDcMNN9yA2tpDuinr16+H3+/Hqaee2nksPT0dhYWFWLly5Q+6B+HYwhwI4qqPVpPJpDenTcKlt/9UJpMGGLrJhCcWnIabf3wlOqzhVRYTiktx26qPkdzW3LeZEwRBOI6QCaUByvD91bj6ra8R6Qsb6NtSM3Hx1QuxKZO7NwkDg5aYCNz0wOV4fcHkzmMn79mB8zavgyaTSoIgDDCysrIQGxvb+XvkkUe+13Xmz5+P119/HZ999hn++Mc/Yu3atTj55JM7J6iqq6ths9kQH0/dRlNSUlBdXf2D70M4NrAEgrj2g1UYt7cCABDUNPzPBWfh51deDJ9VFuwPVD4aPxYX/r9bUBEfBwCI87bjpq8XI83FXZgFQRCEo488QQcgo/ZU4rL318Hyzdq4pfmF+PnZV8Jj5XoEwsAiYDHjkRtPx/6sQbj32Y9gAjDrwG5YQkH8e/wUcDEGQRCErhHqpe1vD6ZRVlaGmJhDqz7sdq5b0RUuueSSzv8XFhZi0qRJyMnJwYcffojzzz//O8/TdR2aJmOmANj8Afz4vZUYVhZe2dZhteKmG34ku7gdI2zPysDZP78dLz3zAsaUlSPK78VP1i7G85NORnls0pEvIAiCYEBv2U0H0xqo9NsJpXdqxsFuDy9h9W6K4xEyqXDb3PydLMqqWrpaJ8bOhXyjLXQJfqiDiqk5M6kQGQB4KxXxtHg/i6MKz6oiZ6YO3mgiE6nCmi+VC89GR3px+QfrYP5mMmn5Kfl48tezkGkp64yzZwkVo7YoSVm2ciHftlwqRvfwPy9mcS67/wsS/verc0g46OCraDzKPayr5mKXWqvSDA18VU2KjuD7W8fQA0F+juakJ72+YSqLo6Ln8h3WQkrdxcZRkcCGYi6mbE6g7erU7F0szvuLaX5yJh/akWjZxcMxObcEp/1qO0whYFrxPkSPdeM58wnQTYcq1KjM1+2k9a9FcRFGXxI9z+yjdZCRW8/OKWuk92kk9jy2sJiEt+zLYXESMppJ2DaZigZWlCWyc2xRSt9o5ZOnruFU8C8ntoWEa8xc5DK0X9FZyOQqh+/uHE8PxPN+GUyk5WlqoCKHdYEuuFIYCFg7KmgZe5z0vjWDOeTorfSgezS/J3cWzZ+9lAtq+mPoPflDdGzMSqFCowBQVknrTjPol2b3kYUl41Jp3TXvpAKQ/mQ+5moBZaAzmEdQ82fz0Ei5zgZ2TkkWbffW4fw5EtoQR8JpKfw6TZ5D467VbPDMOAaJiYkhE0pHi7S0NOTk5GDv3r0AgNTUVPh8PjQ1NZFVSrW1tZgxY8ZRT78/81bFhE7bybrGQEcmlwZnjNrNonxdRSNFObirYqyV9oMqxaYJ5vB+Yi6jgrCBBAPRfuWRpo4h6gYIAGAapGxokk6va/MHcN4nWzonk9rsdvz4pz/GmvwhPH2S+OH/fFxzNDRFtKO78rohOgpX3HYjXn7mBUwsKkGE34drNn6Bq2++HjnVdLWS30D0eNcWKsKtx/A4nmTFtvfR52LiUPrsAoCaero5iamNiz3nTqgg4f0701mcyGxqe9pm0nbuLo5j5yCa9g3NxZ/1DaNpeFACvYd6MxcRd+yhHwfas3lf/nQTld/Qk4zKk7YBVcy/NUA3zghfSAlH8+tGltJ6ckfQ+w7ZedtL3EDPaZjA78mVS/MXVcTf5Xxx9Dr+ID0nKa2ZnVNfRu0M9Z0H4GOf2WOwudNIugGMfwt9/urp/J5MXTBH6stp/pT9rJATwe3Bitw4Eg4VcGPPvpo+oyINyqal49BzQ/ceH7bTQGTgToUdhxTsrcTd//MJzMHwILL49BH4071zEbQcPzvYHE/sPDsNHz0+GiFz+CFS8G4VLv1K3N8EQfh+hKD12q8naWhoQFlZGdLSwttKTpw4EVarFYsXL+6MU1VVhW3bth13E0oCxRoI4vr3v8LUfeFdcF1OB6667YYjTyYJA5JWpxM/uvl6rB4art8YjwevPPM8Mhv5C68gCMKR6E27qadtp55EJpQGCCMOVOOKD9Z0TiZ9smAU/nz3XITMUoXHMnvmp+CDJ0YjaAkPMjP27MeFq9aLULcgCMcMbW1t2LRpEzZt2gQAKCoqwqZNm1BaWoq2tjbcddddWLVqFYqLi/HFF1/grLPOQlJSEs477zwAQGxsLK677jrceeedWLp0KTZu3Igrr7wSo0eP7tz1TTj+MAeC+PGHKzGsvA5AeDLpittuxMbBfOWscOzgdjhwzU+vw1fDwrvkxnR48NPPliKtWTSVBEEQegKZjRgA5JXW4ar3vu7UTPps3nD87c6ToJsG7kym0HX2zU3Gfx8tROib3nrCzr04Z+2mPs2TIAgDj6Cu9dqvO6xbtw7jx4/H+PFh99I77rgD48ePx/333w+z2YytW7finHPOwbBhw3D11Vdj2LBhWLVqFaKjD7mxPvHEEzj33HNx8cUXY+bMmYiIiMD7778Ps1lW8B6PmEIhXPPx1xhZUgMg7OZ29S3XY2sOd7sXjj08Nhuuv/FarBkSlr6I9Plw89KlSHa5+jhngiAMJHrTbuqu7dSf6LcaSh1+K0KmbzSU0rh/rGajx6o8sSxOQgR18qxt47649TupWJ8pgq788JUbaBAkUz9Q3UBLxhKp+PS7Vf9dfk9tpVTj5e2TxyC3ph6/euZjWIPh+P8dORY/n3QlgkvDRrIvjq9UsY9XfLjX0LK57/rX2TlLm0eR8LLioSzOK1+cQMIOKocA2wj+oHaa6H0mRblZHF8V1UfRDVpl7snFJGxSfO/3rshl52R+Tuup+Ex+4cylNH8j7ud6Ep9uKyDh5h1Uh8XCqxKBKPoS82V1HoujKa7A5Y1xJPzkhvkk/Nkl6/CHN96ASdcxd+suLJk8Eh4bv6ekQYr/ewtv9yEPbY+6m+a3Yf8gdo4+hJZnbBKvy2011O/fFMX9nZvctE/ZrTSObuMF6m+gjc3C5TkQTKJO5+V7k+nfnfy65myqDWKzcv9yn9K/LU38BdWi+JN35NJ7Mrt4PeUMo7tPlW1NY3ECityZ5qffAKyt/OGTchLVYqhYmcHieAbR/uNJ4fc9dnApCe9ZSTXpOjK5k39EOS0b71CuvRJS5BgCHbxsYpT+HcqiFR5p4+3KtJ2280AEF4B2TmgmYXdlHAkXd3D9rpCf3pMvwPPrV2SCEmxce692bcqh+H4D4ajjmDlz5kA/zKrLTz755IjXcDgc+Nvf/oa//e1vRzNrAw6fzwLtG9POl8n/ro6vRrZTXATVEmxs5XaQd6uiC6NEMZUoBgIAXyodM7R2g8m+SGVccdP+FjLQDdSKaOLvzB2LX//nfYw+UAkAaLdZce3NP+4/K5PUYbu/LzjuqZecHn556rDZ8eOfXIfXnn4O40rKEO314pI1q3HeHbfhxAM7WPyoVGrTNDdx7SBTO30Gm9po+/Tt4v0Jw2ifs6Vwrc49lSn0QAx/Jre2KXaQ0peNdIHMddTWs3TwMlef/83bqU2uRfDrtg+m/dRkYDtpbqrnaK/laxisbfTarXn0niwt/JykUVTjs2kDF10PqOOR8si1tfBycM6nbpFxn/HrulPpee1pvGyGDqM2WNVn1C5uy+XnRBfTsGukgVZnlKLN1G6gxauEPYOprWS18+vGbqRtxBfFx+XgVNo3tDKaUpGb205Q7NVAwGC8V/Sm0hz8vcL71SH9Js3A/hL6B7JCqR8T1eHB80+9grj28MPn88Lh+MU5VyJoki+uxyPvTJyE+64+uzP80CvvYXAlF88WBEEw4uBuJb3xE4S+4oLV63DDZ8sBAH6TCTfeeA3WDhXNpOORNqcDP/rpDdiVlgoAyKutw99efh1ayOBLoCAIgkJv2k0D2XYauDk/xtFCIfz1//6B/KrwriR705Jx642XIyDL949rXj9lKl46dToAwBYM4sf/XYm4Vr4aQhAEQRCON7Ib6/DwP/7dGX7w4nOxYuSwPsyR0Ne4IiJw/Y3XojEyvGzlxF27cc6azX2cK0EQhGMHmVDqpyzYshmnbA1vNd8c4cR1t16NNidfQi4cf/z28jPwZUHYJTG6w4vrP/wKNr/BHqOCIAiCcJwQ2+HGtauXwR4Iu3W8Ons6Xp89vY9zJfQHyhMTcfOPfwS/Kfzac8qW3Ziyp6iPcyUIgvD9Wb58Oc466yykp6dD0zS888475O/XXHMNNE0jv2nTppE4Xq8Xt912G5KSkhAZGYmzzz4b5eXl3c6LTCj1QyYUF2HuzrB/d8Bkws0/uQIlydyXVzg+CZrNuPXWS1GcHPZzz6xvxuVL1srOb4IgHJYQNIT0XvgN4K1vhYGJJRjAtauXIcYb1ltblZ+H31x0Th/nSuhPrM4fit9ccG5n+NLla5FbI7IBgiB8N71mN30P28ntdmPs2LF48sknvzPO6aefjqqqqs7fRx99RP6+cOFCvP3223jjjTewYsUKtLW14cwzz0QwyPW2Dke/Vbcy7YqAyRIWdIsd28L+rorlbS9PZ3FUNIuBgLWi7RpSyi8YZyBgFkGFZlsMRGWDipCryUPn7kIGAsFjCw8gsbwNZ6zd1nns96eejfWxo+D4RuPtxPM2kHOWHuBLudvbqBitTRHUu3vJJewcR60iLDiYqx7rDloW51/4FQknWLiY2rNbZ5PwvqZkFseuLrzSeD0dWJ5Lz2mmf08/g4rgAUDlcKqUG/0lF+ltKKD1cqCVT9zZy6iwYO7sEhIuWpXNztE9tP4tr3LBuqgrGki4qYGKsmtpvA7un/Rh5/83ZGcj5VwXnP4Axu0vx9xVu/HJ+EK07qVpmQ105a864QsSfnXNiSTsz+dpFw6iItLbt3KB05BNOWDidekspQNm2zDa9lThaQBMqFU3EObTfUofi1cEYFsNhrsGmuG0/BoWpTyoCAuymwQCqg6nck5UVis750AVFT43Zxj0uQbaZq2NStkM4e6OeytSSdhmUP+njN1KwktLR/BICoFhNH8pkby/xyr3sKc0lcWZmneAhLcsz2dxGpx0fDdX0nJIGt3MzinNVsTn47nwtaeUVlQomz4ASuqpGCkA6Ep7bG/n9W9XNFb3L85lcXzph/qCj2uKC8JRIXKrDXZLWGTVN4WPD6F6qvRfVJTC4qg2rW42EPv10mNBmyIYG89tHEck7ZPeDieLo/Y3q5teNxDF8zJ8XCnm/nsXsprDorplifG4+fqrui8RIPOgxzyvzZ6BEZVVuPKrVbCGQrj+kxX44/z5aImIQGgntRkjInmDuOC0L0n4n8uojds2iq8Wz0+pJeGSjXyjDIuNtmsjKZXYInqwie4XA5OX5zcQTfuhKcj7hPp+4kuktr7FZSCmXUftqYSR/D2tNkjL0xfiNphPtZ1C9B7MuXwMq65QNvLJ5g9Uaz0VmrbX0+t2DOP2QUUJtf+dUbw8p0+mYu7L9w9ncUwaLfO2Apq/2Gguyh6dQ98r2ww2xhk9spiEiz7NZXFcEdTgcyobpcRM4JsnNebRdwa/wXuvtUjZ9CRXucfaOHaOptjkgTYri+Nop+2+7j3+Lu/JPFQPXrGdCPPnz8f8+fMPG8dutyM1ldviANDS0oIXXngBr776KubOnQsAeO2115CVlYUlS5bgtNNO63JeZIVSP8Lu9uOU13fDEgh3sDfHT8WrU2cf4SzheKV5aARemTMDB4f1MzdsRUEpn1gTBEEAAB3hL2A9/dPlzVzoRcasLEf+1vBLu99mwvU/uRZNUXyHLkEAgN9ccA72Joc/bsZ6PLhu+XKYRKRbEAQDestu6inb6YsvvkBycjKGDRuGG264AbW1hya4169fD7/fj1NPPbXzWHp6OgoLC7Fy5cpupSMTSv2IaR8UIdIVnjWvyY7GbxZcAGhimAvfzfbsDHwwaWxn+LIVa+D08a3aBUEQBOFYI7W5BdOWHNLCWXr+SOzOSOvDHAn9Hb/Fgpdmz0ZDZHjSMaehAfO2b+/jXAmCIIRxuVzk5/V+v/e6+fPn4/XXX8dnn32GP/7xj1i7di1OPvnkzutVV1fDZrMhPj6enJeSkoLq6mqjS34nMqHUTxhbVIYhW8IuUF6nGZ9fNgx+S7/1SBT6EYvHjMS2rPAy0dgOD87etbaPcyQIQn+k13QAdPkQIvQ8plAIV3y1CuZgeFX3phmZKBolepPCkXE7HHhp9mwEv/loe9rWrUhta+rjXAmC0N/oTbvpoO2UlZWF2NjYzt8jjzzyvfJ+ySWXYMGCBSgsLMRZZ52F//73v9izZw8+/PDDw56n6zq0bi5o6bczFr4oQLOGjYRkB/c3ba+jjrfxoxpYnBoljt3JfWa9CdS/1OyhBWhpMvA3VrQBVP9jgOsATB+9m4RX7jqkfRTp8eDir9Z1hp++cw6WnTYMjqZGdt3/bi0k4Yi9XM8j8QDNX+ul1LdZ9/Fqj86hZRzYbmCUKSuCv6obQq9hM5hBLVYEXGK5b27hyXtIeE8D9x1ub6caKiETzUxxCT/niklfk/DHn85icbyz2+h1arjWkVXx2bUoaUdU8E7nj6HHqmcaCGY3Up/ktFRqzMxPp77aAPDnpy4k4dDZ4XO2zUrFO7c9i1i3BxOqirGuIAtbczIBACNyKtl13lgyh4Ttitt/lIE2j6qZFD+kmcVpLIsjYadB2bhzaFmYrLRNmOt5+wyk0DjBaN6OzK20rwaVpDNyufhm9T7azitdMSxOoJX6fVtbeX/3J9D8mNppHHcz1ccCAE2RD8lL5/pNB6qpP3nkyGYSdhWpAgSAI4P2Za+F+60vXzGG5pcPI3AlUnGzgKLnVGPgD1/vVHSrArz+1+4YSuPE8b4xJYPqlG1StOIsGndPiKhSDqTz8Sg6luoHVFdSLYZQO297mqrf5eXPhEAe1Y56ZPhyFueONfMOXYP9VRCODr5YQLOG+12sg+uyuWqoK5htLNfUcFXT8crs5MIVHYPooGFRHhn2Bj5Oaom05Zu5aQd46XljJu0n4U1bD9kdp+zYiZyGsO23P2UQLrnoZnhtfFwSuslxMCH87tTxAABHyI9bP10Ks67j3OJV+NPppyP0zU5w2UP5F/q336N2pNNP27RjGG/UqmaSbRjXVPQU0T4XXcqfEi1DaL3oiu1krTHQc1VMcH80f3aqNs3BnfAOEpPH9ZHa9sSRcF0Lt3FMLTQ/NhdvV54kep+WNiVOAxeBNCu6sGlZfCKwtpLqtepjqOajdR93iQ1mUZuh3crLc/2SkSTscPB7akmmxp1Z0XNqMbCdmp2KHWygh7x902ASNsXzOGNzSkn4wN5cElbfXwAgulR5Z8zk431kIn1Xai2ltrLmNrCLVP0ug3dl93BqX/3P6M9ZnLuWH7KdgsfJMpiysjLExBwqY7udawB/H9LS0pCTk4O9e/cCAFJTU+Hz+dDU1ERWKdXW1mLGjBnduvZxUjX9mwu+Xo8YT9jw+3pWLpadykVqBeFw1CVG49HrD/nAXvLVWkR8zyWSgiAcm4R0U6/9BKEnSWlpwfytWwAAQU3Dz6+8WCaThG7z19PmYVdaWLA2q6kJc8X1TRCEb9GbdtNB2ykmJob8jtaEUkNDA8rKypCWFnYLnzhxIqxWKxYvXtwZp6qqCtu2bevZCaVHHnkEkydPRnR0NJKTk3Huuedi92668kbXdTz44INIT0+H0+nEnDlzsF0G6O9kTEkZJhWFv8a3Rtvx7J0niG6S8L1476QxWDYpPBkZ2+HBhavW93GOBEEQBLGdji6mUAiXr14FyzdCys+ffAI2DMnt20wJAxKf1YKfX3EJAt+syjlt2zakN4nrmyAI/Z+2tjZs2rQJmzZtAgAUFRVh06ZNKC0tRVtbG+666y6sWrUKxcXF+OKLL3DWWWchKSkJ5513HgAgNjYW1113He68804sXboUGzduxJVXXonRo0d37vrWVbo1obRs2TLccsstWL16NRYvXoxAIIBTTz0VbvehpYSPPfYY/vSnP+HJJ5/E2rVrkZqainnz5qG1lS/xPN6J9Hhw8apDejfP3z4LTUmyM4nwPdE0PHjzArR/85V28v4SjC4p7+NMCYLQXxANpb5BbKejy0m7diKnMezqVhMdgz+d2fWtjQVBZWt2Fp6dexIAwBIK4fJVq2TXN0EQAPSNhlJXWbduHcaPH4/x48MuvHfccQfGjx+P+++/H2azGVu3bsU555yDYcOG4eqrr8awYcOwatUqREcfclF94okncO655+Liiy/GzJkzERERgffffx9mM3djPByaruvfW86hrq4OycnJWLZsGU444QTouo709HQsXLgQd999NwDA6/UiJSUFjz76KH7yk58c8ZoulwuxsbG442dnwG4Pvxh7A/ymLDupX61W2MbiqLo7JjN/QAQ91EfWEUM1B3zV3H/X0UArvD3DQM9F0VAJRtK0P4ufjMc+eBULdm4Mh4cW4PqfXEtWJ9kbDfyNkxWfVB+PM3X2ThJeXZxL81akiLcAsI6kOgq5CVy/aU8V9UkO1NLrRJbz+cn8s/aS8OaSTBbn/IJNJPxR0SgWJzOO+nAfqKHaN2aLgcOxgree3zestPknfs19podcQzWetv13OAmbJnL/cncdbTepX/A23HA29bVPTaB10LSY71Qz9nyqq2Q18fvOWNSAh//yHgCgLj4Kz1wxGx1Oqnfhrqb6TYimPtMRe7nrgFXpYkGDFZjeONoeDaRu4M+mWmZ6iJ4zPJXrFuzfnEXC+WPLWJziFupQbrXQxF0uXv/mBlrfeip3Ewy10LIz6nO2JnrMO5Teo7mSixSpVwna+VCsJdP8dGXxolZKtY9Mg90sTkAZU/VaXpnBCFp+mk/p31GK8BaAM/K2kvBHm8ezOOmKlpU/xPtGbQ3VhoqIpX3FV84n3k1epXAMPpcEVV0l5ZSQgbaBqh1nVP9qWdlieDv6tnaB1+vHX578EC0tLcRPvqc4+Fw959MfwxppIJh1lPG7fXj31Bd77f4GGj1pO93y07M7bSe1nwNA1Gbaxtsn8LYaUPuBxWBs8tBrm6LpmGeq4mOKs5Zepy2HRWEaKv4Yes727DR89PsnYA8EEdQ0XPT/buark77vfGZfzYN+Xyu8K+d9n2sfpQlhbQCJxdkCAbz7hz9jRFXY/vjTGaehfBjXBdIraLsOxNKxP247f/DYWumzMuDk/dKTQM/Tgrzw3LnKw0iJkpPBdSJr16WQcMpkbl+VNcWRsEWxnbwtvC/b6+g9eNO57o65mdpXqkYtADga6U24htO0neUGL7XKfQcdPIo/TclPFxqj4wB9NvryDezBAK0nazW3GQKKxpNJke8NxHDDeN5wuhr187WjWZzYofRdw28gKNRapejfxdN7MBfzwjIrt2nU/TuyFXtPiWN2GdSTcptm1UYDEIhU6iWetyNNsZ2efe7dXrEtettuAga27fSDhA5aWsKNOyEhLGxaVFSE6upqnHrqIS0Xu92OE088EStXrvwhSR1zjKso6pxManE48Zt5F4mrm3BUeP9brm+DmtowZ/WeI5whCIIg9BZiO31/fv32B7AHwh9SxNVNOFr4LBb8/IpLO13fbl68FLFtRqrxgiAIgsr3nlDSdR133HEHZs2ahcLC8M5j1dXhme+UFGVGPCWl828qXq8XLpeL/I55dB3/b/mhLfv+dMKZqI8aWDORQj9G0/A/Pz0DHlv469D0jUWIdfFd2wRBOL4IQeu1n2CM2E7fn7yaGpy8fRcAoCI+Dn9aIK5uwtFjW1YmXj4hvIubwx/Aqav5TruCIBxf9KbdNJBtp+89oXTrrbdiy5Yt+Mc//sH+pikrbXRdZ8cO8sgjjyA2Nrbzl5WVZRjvWKKgrBKTyg8AAA4kJOPt0VP6OEfCsUZNUgwWnTkZAGANhnDKyt1HOEMQBEHoacR2+p7oOs7esKkz+MSCU2VXN+Go89Spp8DlCLsFTdlejEGNomEmCIJwJL7XhNJtt92G9957D59//jkyMw9p4qSmhrfeVL+o1dbWsi9vB7nnnnvQ0tLS+Ssr49ooxxJaKISz1m7uDP911nwETd0TvhKErvDC+TPhigwbRhO3lSK5/tj/gi0IwnfTX4UljxfEdvr+jC4rx+C6sEbMntQUvDVlYh/nSDgWaY6MxP+dPAcAYNZ1zF+1rW8zJAhCn9KfRbn7E1yB+DDouo7bbrsNb7/9Nr744gsMHjyY/H3w4MFITU3F4sWLOxXHfT4fli1bhkcffdTwmna7HXY7F3xrr4hC0Br++hSRxQW33UOpiljip1xoTE+jt9eRx8W+bLV0MsejqLuNGM53ydpXP4iEc+ObWZzqDakkbP5G7HfCzlJkNIX1EzYNzsTb544AtLBi29g8ahDuqqEi2AAQaqNlZY7wsTi7G+l5QS+9x8gCnt/WUupyt8PFy9Nip6JsZ8zYSMKfLp3Aztm8Po+EQ04uRvefLfQ8Ux0XP9s7SMmPi9ZtKJ6Xg91J69sazwX2VCHsqROLWZwP9heScMJsavS3enj7NbfSMh91OzdKtjZQ0e3Gz2nYk8bLau3SkST8P5csYnFWfRIW86tDPP53+im4a8mHMOnA6St24I0LwquWAs100PLYaH4Tptex65ZVJLJjKrZGep208dxdo3w77RvIoEL4u/dy4XYoIoa7d/A4IaUafIr8QdwQLp6elka/Pu6sTGVxolPo+DM0lpfNxl1DSNixj7bhpCm17By1PE1ePr9vVoQk/X5FTDvIHz5aqiIIbiDMqwqh29KP7BKZH0/ve1t1OovzcSkV1Ddx3W64PLQva6ujWBzrRNpX1bQ3N3OB9bhcWk+tHbxfhhQRy+RYWv8NNQnsHFXwU/MbCIsqz5FAJK9Lb/WhPHv9/FkkHLv0pu2EEgdgDY8/liG8X7tG0Laa/g7f2MGdSa/bMoI/i5xVykYEfjrmpRfUsHNKB9H+NSiRr/5oX003Vwhk+qGFQjhzy6bOY4+ffTpCph8kASocZQaSAPeReHHObPzoy68wqLUV4/ZWYHldPcpTw+3SrOxX026j7dAyp5ldr740jh4weGe0K3raUVObWJzgJtp/vNn0OVKxk78z6LG0Yio3cxsH6oYgHTSDzny+sUdqJrWdi8p52uY0aoQNjW9gcfZspbZczG5anvZZfIOghhI6RrANOQDWIHUfHfc0A9upI5OOhVqAjzGqzRXM8rA46pUHJ9D73lvB62DxAWrb2wzsDNWmiVlmIBQ9nRpdQxJp2vsauN2m5dPnhMdtcF2lLGITaZvwVHHZlqBDESc3sAcjlFcEdwy/b0vFISPM7Jdxv7/SrZq55ZZb8Nprr2HRokWIjo5GdXU1qqur0dERHjQ0TcPChQvx8MMP4+2338a2bdtwzTXXICIiApdffnmP3MBAwhwI4vSVh3yyH73wdBHiFnqUv0+bDVdU+CE0cm8NMiu4kSIIwvGBfGXrG8R2+mFM3l2CtMbwC+z6wTlYPLqgj3MkHMu02+3422lzO8Pzv9x+mNiCIBzLyAqlrtGtCaVnnnkGLS0tmDNnDtLS0jp///znPzvj/OIXv8DChQtx8803Y9KkSaioqMCnn36K6Gi+/ebxxvStRUj8Rhx5WUE+Vo4a2sc5Eo51PDYbls0c1hme+8VOQD+GPiUKgiD0c8R2+v5YAkGc8fWhF/pHzzlDPsQJPc4b06eiITYSAJBfWof8Yr7KWBAEQQjTbZe3I6FpGh588EE8+OCD3zdPxyRWfwBzvz4kjPzYhaf3YW6E44kNY7Iwfc0BJDW5MbisEXnF9diK+COfKAjCMUVvfQEbyF/ZegKxnb4/M7bvR3xb+EPc9pw0rBk65AhnCMIPx2+x4JOZI3H5R+sAAKev2I69OYOOcJYgCMcavblyaCDbTt2aUOpNQhEhBG1hv33fbv6FzpRL/Vbd6fxW2jOoP2xaPNdQcW+lOib2YdSXNNXOhYz31VCf3xIf15ZJGk39ft27oxHdEdYF+XD0WOzTBsNRQs/ZYskg4ZOG7WHX/boyh4Tby7n+SEMd1Rc5Z8Z6En7/y0nsHCRQ3ZXEBK5bdU72FhJ++dM5JGzhMkYIKhIPsdt5PXUkK77Nw3na3hYqZBK3h57jWMDrqeMjKmbqy+ZGfUUVLatVo3hnDu6jZexqVNqjQf83x9C0ln05msWJyG8mYXUcMbfzC9ta6LGHtp3J4tjHUre2D988Gd6CBDy84jUAwOAVLmyaSs9xxtH+VO+O5GnXK/Vk8I7ki6cHy3dwQVlzNu1jV2WtJuHn209k58QrWhuDo7kv/sbybBI2tdIdgDr8fEegPYoeWkxsB4vjPkDre4uJj0dmRWJErTnPO1ybJzKFLhB1Z3OdkqCi+aN7aB2YnNwpPdRB+1jAQAfAbKNjY6CE13cgiuZnL2hZmWp4eQZi6TnOLmgztRbye5ieQgdHdSvVzHSuq1BeF0cPGPjaqzpVDbW0XtJGcn2s5g46RrTV8jE3EE/v21LFtW3srd+6BwMtAUE4GgSiALM1PA47t3GtMX8ebXxt2REsjlvZMC4uiT+TLetpPwiMogZAmpPbW9WV9HlQ64tlcWImHhrrNV3HhJcP6Vj+/LJLWPyjivpM6ynbXhYJ/zB6qfzunXsxxm2qxKjKSmTVNGNvKAv5NmpfaYnUdmpy8z7nqKMNyRTkN+BJosdcW7jN4BtM+9hVeatI+NX2E9g59iT6DB4Sy5+dO0qoro6thdoZPh+324trkmg6sVyjVNtDx5b9Jj7WWFSzR5l8t77On6UxigyQawgvT12xnUwdNByK4PaWqV2xtwx0jGCn51n3cb1Zv2L/HwB9R3RUcV1LbwJNO5jNtZnUs+q5bC0mZJSSsK7T6yZkN7NzGqrpOGzy8ftWdaq81VQzKXo0l9NwddCy8VfxsvIqzdxezu1KW/Oh8tTEduq3iLpVL3HF6pWd/39xFn9hFoSe5PPs0aiOiAMAzKzYhXg3f0EQBEEQhP5CXnFd585uK4YPxY7MjCOcIQhHD91kwosnzu4MX7Vi5WFiC4IgHL/IhFIvkF7ZjDEV4R3ctmZkYnNW9hHOEISjS9BkxlvDpgMATNAxo2hvH+dIEITeRoQlhYHE1I3Fnf9/9YQZfZcR4bjlg/Hj0BQRXlmzYOMmRPj4yhFBEI5dRJS7a8iEUi8wacMh943Xp80QQUmhT3gvbwr8pvCi2anF+2AO8u2iBUEQBKGviXW1Y8T+8J7SVXGxWFI4qo9zJByPeG1WvDl1MgDAHgxicvn+Ps6RIAhC/0MmlHoYZ7sPBTuqAAAtDic+GDO+j3MkHK80OqPxWfYYAECUz4uxFaVHOEMQhGMJHWE9qp7+iUSM8EOZvLkEpm8a0qKZUxE0c90RQegNXp85vfP/00r3QtO5/o4gCMcmvWU3DXTbqd+Kco/JKYPTEc7eRo27iEVYqTKXL5ZXg8VF58s8g/jt+mLpaqFz07aS8L+/ng6VYKKiCtbGr9toCYvcztlYDmsg/PB588QJaM0BAB9+O/Pf7Jx7/305CS8z57M46mYxI0aXsTi7SlNJuLiNCsKFYriqmUVRxmvayYXGX3VPIeGEkVQY2buE74Axas4+Et6UmMXiaIq6c4zdz+JYFWH2lPOpaO++jfy6wULlOhbeRmxVVADOZKA0bWlTxOgU4WlrG19x5o+h5Zmwhc/dxo53k3DRcCpYePm4Neycf3wxk4Rtm7moqUYvi5ZvNaNXbDNx2osbAQAnVu/AgVPD5ze307T97bxNm7Op6OJFg9ezOG8tp24JITsvT18TFeb71/qTaP4NBBbNSr1s3DuYxdGV+o0a1kzC7T4bOyfYQgUfW9xcENCUQtvRyORqFmdHDe1zHQ56Hd8w3ud0ReTcaHo/L6mehEvWUw0RXzo3bG3RVLgzWMOFEKNLadoto3mfS02iorqxNipYvjuKi4+aW+lNnDFyG4vz1rbJJBxZyvvPKg8d+3Q7XU03JJWWCwBAEeEcmlXDopQ0UwVIdTyNtXJR9qpmKj4Zk9rK4oS+puOTu5DvUDBp4qEv2+2eILCERRGEH8ywoRWdttNOUyb7uyrI743nY55V2ePCE+DPA4siIntWFt2044Nlys4PALyDaNqWVj7ouSwRMAeDmLgp/MHDbzLhjRn8Wr1CV6x7dfjqqTeCgfym0R364X2WJiXhixHDMWfXbiR2tGFk5AHsGRIWmPe4ledrO5/4bB9Mn//n5W9kcT5ZTJ+LAf7YhtZA++qHq2eRsIm/MsBiojbC7h18TNCUIUArUDQ2vXyMMDfRMcHfyseIUJry3M6oZXEOlCeTcMBJx4TWAm63WWppp9PNvNFkpVDx8cYD9P1E3XgAAPRYagdZK3nasQdoedZN4iv9E5KpjRBjp26SZdF8sxqrsuHOvDE7WJyP19MFCfFF/L43t9NdMEMOGic1g4uyI0jTTh/C7auKBvquEVRcszLt3Haqb6IbNzgyeJzI5dQGbzBYczF2+oHO/3d4AsAqHkfoe2SFUg+i6Tpmbjv0EvHaSX1kFAnCN6zPHozdKWkAgKzyJqTU8N3xBEE4NhEdAGEgMLaoHDHf7Ir7ybjRqIuNOcIZgtCzvDbr0MeyaRuL+jAngiD0JqKh1DVkQqkHyS+rxaCW8HKR5QVDUZTKV/AIQq+iaVg0+dAqp4kbSg4TWRAEQRB6l1k7D61sfnU2XyUuCL3N56NGoiI+DgAw7EAN4lra+zZDgiAI/QiZUOpBxu0v7/z/ojmyOknoH7w/ZgJ81vCy7JG7a6CF+uEac0EQjjrylU3o70S3e5BXVQcAqImNxtdDhxzhDEHoeUImE96YPg1A+MVp1N6qvs2QIAi9gqxQ6hr9VkNpZ0MK7Paw366jkvskWxKoH2tsfgOL09AWScLBEJ8/Cyp+ym/soBM/9g5euSEXLTZHipvF+WfeNNzz6scAAI/VgvUYjZhNh/xx74s4h51jUdPawTVKnHX05T/r+iYWZ1cbdQ7evCOHhE0dvBwmT6U7V6ypGs7i6PtpedZHUt0dfQzV2AGAjXto2vHruC+2P0rRKHLw+/Yn0/vevT+dhKOGcNet0No4mj+D6dOo6XUkXFaZwOJkb6H+7+Un0wvpBr0oqpi22cYT+FaznsWKL3sBjfP619P4dctp2u0GGjrmsdR/26b40PsBrJmSi1lf7Udkuw+1GTGwLaH14jDQnNQ1eqNvYiKLkzCK+mc3lMTz69joxd2ptKzs9byimqNpmzDHcI0au43WU6SNxmmq5m4T1nha5qFKLlzgSKBfIndUp7I45jpFiytDuW4Fv65uVw4Y6HeVttDyGzSWtle/wZjWsIe2YXs2H59aVT25Fq4VUF1CddTcabRdOat42vZxzST89oYpPI6iFeAewesyPpqWudVMdQqqV6excyILqe5DkzeCxUGpUg+K7la5I46dEmylZeOuUisOcEymaUcZ1OXKdYd2qfL6fQA28/wJwg9kT10ybLbweBTFJRbhG0TH34hRzSxOs4v2HWuI20EBBz321iba1yM6eB8Itii2XDp/LvrrrZ1fOv89ZTIAjerqdMXeNvpG0lN2unyP+f70t7I7Qn4+Hl2IOz8K2/UJ5R34xzmzcfFHm0gcU5BfRDfRdv82uFBM9Bj6fPUfiGZxVD2c1gx6XWctT7stlj7ztDiu52hWNAojbFRLyFtJbX8ACCbROLYybkPog+izXdVLAgBHNb0Hbw49x17KrxtgthOLgopGqvmTMKmZhK0GtpNnOz0nMISPT3WKvWpu5u+nrgP0Om0Z9B4iy8HwT6F22qerJ7A4zgZav02FvL6dsVSnyGahdetexvVxzRPou1tTB38HcxTTewgpJmS5M45ft0WJVMHf/1yzaBnbNP7ysXnlIXGwsO3E9VuFvkdWKPUQhWUVSGkJPyBWjMiHx8oHRUHoK1bOyOv8//RVBw4TUxCEYwX5yib0d+ZuOyRGu2T0qMPEFITeZV9KCoqTwi/kU/YXIaZd3N4E4VhHVih1DZlQ6iHmbT5kFC0eI0aR0L/4etpgHPzoPH2lTCgJgiAIfYs1EMTsXXsAAHXRUdiUY7AVkyD0FZqGJQUFAABLKIQTd+7u4wwJgiD0D2RCqYeYu+XQhNJnY0b2YU4EgdMcH4Edo8JuQ4OLG5Do5luhC4IgCEJvkV9Wiwhf2JVmaeEo6CYxUYX+xZLCQx+I527b3oc5EQRB6D/0Ww2lQJMDpm90AJDt538vpv7Frmjud+moor6trkzuv6nIucDcTg2YQCT3UY1QtPg6QtS/ON7dhoLycKTNmVloDsZj4sU7SZxVu/Ogog2lvqQnDd/D4ux5tICEQwbCQLqT+swiQJfQxe/gS+oOjKB+tTNm7GBxvtw8goSjUqhuSEZsCztn954MEm6awusSQZqfOaN3sSirSnPpKR5al23VUeyclFm1JDw6kYsoLjswlISnD+OrdTZcpWgdeWm3CQR4HbRGK37Vfh5n1Fn069a6jTQvg9bxc1ryaXsMxXB/+KQo6ottpDfTMC6EpRNHoHB7uExG+YqxvPCQn7JpF9f88STStE213I3TEkMnpkIGYkxaOy2byBx6jquR++snK5o69cVcmyluCL1O5T5lV0U778t2Ky2/jjSuA9bhpW2tII23o5JIqls0dVAxCa/aVsjO0ZRuChP3xW8bSsu4dj/VNglE8XuKqqHhVgcvz4JhpSQcSuJtbddu2u79W6gGVUcu78vttXRcTsltZHHcq2lZxcdx/bO6fXQ8CiYo7XyQwX2vo/fZHmGg+5JD8+yIoHoNLZVcZ8ucQNtEwMYfm15F7yIqv5nFIRpZfbSqubeWVA/kZdsDHVO9FWZreMxqHcLHX/s+Ooa0RHO9jKgKGm7L4W1eHdotblrnfj7sILqc9tu2EH3OFG49NHgtLTzKH+LUIaM/NdH+piWkasANtP7cg+W5fvBgtDidiO3owJydu/D5lKEImg89u6O38r7SkULLz17F45jjaIcKOvhNmNuUehhC7SJ3Pe/LMTFUU6djH3/GxQynNmPLbsW+MrCdrFZqwPgyuD2ge+h9Ds2sYXFKo2haM1LpzsPbN3A9V1NAyY/BvHPTSGq3tSv35OcSVYippPfU4uR6iUMLqP0XSOGJV2yjOpuO9bReWofy8jRV0XE5Oo+/T2nlNNPxSfxDcPuOOBJuGUTvycIlQBH7FS0rXyS/b/dQeh1zJK1vrYy3vdAgard5HdzGte9RNL5Gcs1PMvz0wVDUm65oA9l2ks8/PUBB+SFr7LMRBYeJKQh9x7KphyaQCg5U9mFOBEEQhOMZTdcxqjpsO3msFqwYPqyPcyQInIDZjM9Hhj+uxng8yKuq7+McCYIg9D0yodQDFFYckvBfOlImlIT+yYGsJJSmhb/aDKmoh9PDd9sSBOHYQde1XvsJQnfIbGpArCe8mmLF8Hx02GUjE6F/sqTwkF1fWFRxmJiCIAx0etNuGsi2k0woHWVMoRCG1IW39q6MjcPuVO5uJAj9Ak3Dl5PDbnZmXcfgSvnSJgiCIPQ+Q+sPucN8ViC6k0L/ZfmI4Qh8o++VX1F7hNiCIAjHPjKhdJRJaWmBLRj2Nd2QnQtoA3e2UTj22TzikE5OVk1TH+ZEEISeJgSt136C0B0ymw7pra0fktt3GRGEI9DqdGJvagoAILXJBWvg/7P33mF2XdXd//fcXmbuvdO7NCPNjLrVLbnLHeMSXgMOsUlCHl4CIQkhwI+8hCSYvHlNSQIkOJDgEAzYYJoNGOPeZVm9j6SRRtP7zJ3bezm/P640o7XXwZLs0RRpfZ5Hj73vrHPOPruuc85e3821LAVBuDiYSb9pPvtOc1aU21sTgt1eEApzmPlgPWajIsyLSvnDcI+Lir/WeLmA2bCVCtTZe+gy6/K1Y+yY0QQV+7WcoU3dODSVj7J3hfDpu38FAPjqb+8ix1jrqJgeAGTi9NojSa4aN76Kipq98eRqZrPpNipqvfNEE0nn7+JCueMBeq0bargguCVMrx1zUjG1oN0gZMpChQZVQWYA0DK0A726g4cJ6i4qCGcfpCJyqXp+7fSvaT0l/oivwLE7qLDcMX8lv7ayBJGJHKa42HsqQQXqio/w5ftHS6tIWhWEj97J26vWRturKcK7cPY79LzWRXyACkcKAoA7a6baxiL/OMrdhcY8XMlF+Tw1ND9xA3FHu4X21RUL+XLwExO0XiIx2o6sE7yNuOpo/Tq5tiOG8+X0B1X3MMfLIZ2j18qm+LVNUVrG/U4fsyl3UYH6FxURbjPXEIdeTe+p0mOw0952Kk6tCt3qVi7uGFH0/s0e3jeO71lI0jknP0/5Ijqmjjq89O87+PeIZCn9bcTkYzbmZTQ/8e4yZlO6KEjS0UO0AEvW8L48mqXnsXBtR1jsdBxJhGjbM3ENY2QTtP6bavicMOah81HioI/ZFF8WnPx/W8pgcwJBmAYsdXFYTvlORRbuO4VsVPy1upyLvw4V+Ui6tCTKbCasihD9Sdr37Zv5eRMJel5bZGrcaZjwF2ysVnRU8Xl42jkX4ea349vPNYHtGcIoUkPV9uYGRieajtxceA7V12PZ4BDMuo7W+Aj66wpzVLSW+0UW1d8/5mI2qu/U2DLMbLrG6ByXjVA/zTnOC9SpbGpkGjLwGXQfSWvKPMg2EIHBZjRJ7jtZItSm3+VjNmVuOlHvUES4LWX8npK1NEO+Ej7Z+16l9ZBWNjDJcxcXwSU0v3kfHz8H36wl6SyvSjhb6EYjUQcdK6tf5Zu/JCuV5ykzb0f6ZfS+rSd8zMa+hPqR1j3UN7FezsflSIae58xx+TSa4jvlA7QALQb+NWLUd6qu9zMTv5c6tfY9vECz66fqVxPfac4iK5SmmfrgVIcZW8F3HhOEuURvZSlCrsJEVj3Md9sSBOHi4fRuJTPxTxDOFWcmhfJE4aXV0boasmuWIMxFDjdMre6uHQnOXkYEQbigzKTfNJ99J3mhNM3Uh6ZW/4wvN9iXUhDmEpqGtqbCF5fiaApFkeQsZ0gQBEG4lKgNT62GPHTGg7ogzFUO1U+107ohvupDEAThUkJeKE0jpnwetaGCYxRa6EDaM2cjCgVhkkOL6ib/v3pIVikJgiAIM0ddZGpl96EF8kJJmPscra2dFOaWFUqCIFzqzNk3HomMFXlTQQcgknCwv3vddCXFaIyHl2lKAHdQ0bUBuIZO1kn1cJK/oTpMAJC5QolJDhSKsSYQhDVfiDN9o2Exvnlsy6TNR255kRzzg+OXs/NilF77WGAhM7Er4aPxZq6PsrtnAUlrQeWeirjmT07RjnnstSuZjS2hLMWz0kBr639zLRTcQeNuTaU8dth+iMbM+q7jsePjIVq/rir64qPZw1+EtI81kvSb25cyG1WDRo35BgDfaqrX4rbRMg8O8Vhnc4Kep/n3TjCbgzuaSdq0kMaBF/3GQENrvVKeab48cuAGek+2AI+HNvVO9am24kYArwMAygaiONBUz2LoASDaTfOTK+GB9aksHVL6Jrh4kMtByy+Tpm3PsZhrCTnMtOEny5kJyhdRbbARP62XG5ra2TEHgvThJZ3gfUNdgRru5/Ud8tGxRXco8eY5HsKhh5VreZkJYrXKD4ommW7mdevqp9cyd3GxgHgNPc4a5u1o4oRSdz56T5vuO8iOeWbXWpK2FfHxyeuiGmQTY1xfLJqmv+UUE6NlwWr9r/X1MZtXXl1Dj1H69tCYjx2j0uPnc8K1DR0kHb6Kz1m90anjTGcVF7kwzNS2tPN569v5TiZjgUkrjMOpOO9bTjedg8ejBqH5SvsMxXl7NjupvkjWTceZ4p/yY/xb6BhiO6WXVxs/Y4XSXHqhNE/0fCaZb/mdx6RsVpyorsKywSFUjEeRjpuQtZgNtRrzJ6mPmynjFaX6TiPj3CGwOakflFb89twSOrcCXIM2UGmgs9RK/efwKB0TrlzCNVX3jdF+Gk8YPE4q40iuh+vjDJXQcUNT9By1PM+vOUTvWys10IVqoGldyV7eILvF3TRt6eB+W1QZnmxBg7o8Rn1EvYT6bSs+Rv0FAHjtjVVKZrjvVKyM3akR/oyQSNIx32an5WfW+TOOcwmt//Wlvcxm5zNU29a6ia7KM3oOUjXSjPyrzU2dJB2+gT+n90amjjMbCV1eYGbKbzp9rfmKrFCaRhrO2KXkyOKaWcyJIJw7h+vOWLo9Iku3BUEQhJnjtPZk2myeGUFuQZgGToe9mXUdtWPiOwmCcOkiL5SmkfrA1Fc2eaEkzBd6S8uQOLUrUK28UBKEixYRlhTmGvZMGuWxgiD3oKdEBLmFecOZwtz1o3ynaUEQ5j8iyn1uyAulaaQkNhWy1FVnEP4lCHMRTcNYaWGJsyeahCk380tKBUEQhEuPksTUlupjxQZhE4IwRzlZObWariTMw80EQRAuFeashtJ8xJMoTCh5AH6fgS6BIMxRokVTcexF8RREmlsQLj5EQ0mYa3iSUw/iIQfXzxCEucqoZ0rDpjgmO+QKwsWIaCidG3P2hVI2a4b51NLnXJovgZ5IuUlaz/DFVqo4bbyBiwiXllMB4ICLCqxFruci0jdVU0G113svAwB44wXHKGp3IDRKv7QlF1EB3ivru9l5tx5aTdJalpkg3qQIgod5FeaTiihvkjbQdDd/2WVriJO0PszFidOKCLNLETTvv5kLgBaV0PPGwlyoc8ltVLD6xJMtzMaymYZihY9TweDrr+ei10dcVJzcVM7r0nmQigRm13FB6MxTFSQ9cA0Vz7b6uCNhHqZlfGhbM7MxLaRlY1EEly//873smIVOKiL8/UduZTaxVrXh8P6T9dBr+R1T/ckynodexhufzU1FAnNBXpdDw4qQs4FodDSniLceom0tvpavkGofpUqIjro4s6ly0robTVDx5JeOL2PHmON03DDzIQLOhVGSXlU6yGx2b19C0hkPvW/vSV4OyRJ6bX8pF6x0VtK2lu5Txr1KRaUfQLqYnjdbz8vT1UfbRKKK58/so/1ldeUQSe96WBGRBGBupmNNfoC3kfEiWv+b1vC+m1OEI3dFGkl6ZNjHr+2ibXZXvpHZuFcFSbrYRu9xJMb7yh9teJWkf9h5BbPZNrSI/tDDH4zPbBPpNK83QZgO9JwJ+Vyh/+hp7hfFU7RtmlLcxqNoskYauZ+hjk2pIjr/j9zGHeNr6qm4777nlqJ0Ymosj+MSeaEk4tm/G7XZzOGyGvFOCWcXh1NIR+2AhzsR6tykBbmvHB6gzwyahd94Wtmdonw3/bt/M++nA0NUk0xfyP3VSsV3isWp2PObh6l/AwCWKK0ou8HCdn0RXbW1opxvuNP+ahNJp330vkuP8LkyUUHvM1jOfSdzDZ3bLd3UF0lVcx837aXnVdwOAICni+YvVsdtciU0zy01oyR99N/5iS1U8xqmXt5G4sXUV165sYtfW/Gd2sJUnTw1wIW8827aZnfkeP6wXtk0SNmcKBrj88g9V24l6UfbNzObHX30Ws5Oft9p71SZpzLiO81V5uwLpfmGpusoThUGz7D9EnGKhIuGsGuqzXpiSUAiNgXhokOfoRj9+fyVTZhZTvtNABC2ie8kzB8iDgfSZjNsuRw8cVmhJAgXIzPlN52+1nxFNJSmCVc6BbNeeIsakWXbwjwj7J76enN6pZ0gCIIgXEiK01PzTUQ+xgnzCU1D2FXwncRvEgThUkZWKE0T3uTUsu2wnS+/FIS5TMitrFASBOGiQwegz0AIyRyOUhHmGB5ZoSTMY0IuJ8ojMbhTaViyOWQ12aVQEC4mZspvOn2t+cqcfaFUtMcOu6UQL7rojk729xNBGhcc7+e6QKlSWjVl+/l1tJupjW6laet+7uC8uprq4aTrsnDkpnRWJirsMHlonOfDu64kaXOAaxRZTPTaWRdvWqY4nayKevkis3W/f4ik9/yMap1ElvLYYX2QvgTTi3lAtK4ESSdPKjuy+Ph5nTZaDtYSHl9+eLCGpJffcZLZhNI0/tm+LkjSv35hEzvGPU6XDiYyXM9FjdfO9/B2FFlE79u5l+rYpMoM9HHU+GwLL88iRYMqGqRtLZXn3fNbr99I0i6jNYaKbkb9pgFm0tlRTc9TOxUPXZsNGsbvZ3tpG7EYXLt1RT9JH+mvYTaWERojHa+l17qilseFt7noeaLHfMzmkIfmz6RoAOWivM/lHfTa7h6+3DRWSfO7rWcRs1mxnoqOHBun41OqmLc90wqqzaTGpANAOEmPc9JQfGTqeX9avoaOl8deXcxskq20bJzH7cymbpGfpGNZajO2gTvOWhE9rx7i8fC6oqu1o7+R2dj66HHmhfS8NT4uG19mp+XZEaxgNskB2ncti2j55R28n/6473KSzsUMdOscSj3U8rrUU1Plpeuyk6JwYSh7A3Ccamrl93C9t46AEs/cxT+AJZWuU7Wd6w9G36PMnUpXL9nFx9utujIWLdThOjz1QmmkmY+TTFNnJpnP3v2ljFGbuUB1mSqxACOF/1/kGsHxVC2zsXbTuVM38J1q11KNwu7uKmbjHKRzboTKhGLDAgPfyU19PRzmPm6Xl+Y5W0r9V7OBVmvOqehEdvICnqiig8L+0EJm03QVve/O4XKSTvn4teNr6HhUZOO6OrEELXPvIJ2jMwu477TocpqXgWfrmU1oBT3O18b9oOIlAZrfLC2H4Wt4HeSKaZlbAvy86iPBge4FzMbdTRuXvpjmt6yU68SWOqgmaaefa16Y+ujYHG6lPkzWyev/x50bSdoc4feUc9LOGjfwabUzdP7Ec5q7SMjbNHFm/PSZqz0EYT4QLZ6afN1R/jAsCIIgCNON99TuuDG7DVmLrO4Q5hdn+k5FUf7iVRAE4VJgzq5Qmm8UJ6ZeKEWcBl/ZBGEOk3BZkdcAkw64Y/JCSRAuRvLQoM3Ako/8rC4rEeYTRad8p4hD/CZh/hFzn/ExLpYGfLOXF0EQpp+Z8ptOX2u+IiuUpglzfmohXtYsxSrMMzQNuVPt1pSTRaWCIAjChcdyynfKmGV1kjD/yJ4R+3/mc4AgCMKlhKxQmiZM+an40ZxJXigJ8w/dVHgzfmZbFgTh4kHXtRnZlnY+b30rzCymU2qneZO0GWH+cWa7Fd9JEC4+ZspvOn2t+cqcfaEUqwWy1kLB7u3hQm5mGxXucjdwobF4igqhReIGwriHSkja1ky3/ow2cVFZxOlvmjkPiz6Vn7wFuHMZFcYOZaiu0pH/WMlOm72HiuAmUvzay6uGSfrYAi7ct+NJKsJd2k3LKlHBqz1bRgXhahv8zCb6LBX3u+revSQ9GPeyYw71UrG/m5YcYzYvvrqGpBe3jDGbp56iotvpUvolyMo1+VD9rj6SvqXqCLP59ss3kbQqPA4AN62mx724m9adY5h/WV1+RQ9JH32NCznHrLQ93rnqIEm/9n0qaAcApiaav3gjv/G1S7tJel97I7NR6R4qR0Yzw4YccmkTLAO87aXLFDHCo/zFabtZETF08fJ0NVNB5WiMiiduPbKUHXP50g6S3lFWzGwsbloWWUWE21dBRZsBINJLheXTHj6YmxQR6ZLiGLPpCFIhyVycXjtnIKuWS9N+mDnJhRodLbSsIg3073qU11OulNZLbmWc2ZQ56E5+EyX8PAMR2p//tukVkn7EtJod09FG69+1kI/Ldgsda8ocvDyPJem4sbAkSNI9/bS8AWB8lCoJJ2sMxB1LaBspt9Nrm2r4A4H/ML2W1WAhRVYR89aCfIzVSqZCSTUT38BAEKaDSIMFaWth/Bk7Wcf+rs5xtiY+PmSSdPwKR7hov2mvMmYspX0r2MxFuRFX+oUpP/lCKWcyMcH+GWemLv92Hhq0C5S5uf4AM4MC22+HUHhq3o6OO+FK8gkiUUEzXH6Az00DFmUDEze/yfxS2ldTyvy/bz/fgGP5ZdQXPVzuZjZ68VuLcFur6XMRAOS7qZh/0scrSrPQMcHl5RpT3eNUAFpTNr3IGGyanUvRMs6182c763JaVqEmOh7pEe7zZCuo7xRZy/3rYie9h3g590WjQepXfqH1BZL+rmkDO2ZoH32+0hfzcdlpUQS2Xdx36k3QZ8LKcupD+jvpMy8AJEd8JJ1rYCbIltJr1zsV36mO+/qp/fS8eYO1FqpvbA3y/pM5QyReN/O+I8wN5uwLpfmG6Yw9BfPaHJ+gBcGA0+1Wlm0LwsVJXtegzcADZH6uP6QKcwLTGXONrFAS5iO5M9qtWVYoCcJFx0z5TaevNV+R2KxpQqYR4WJBlxeigiAIwgVG5hphvnPmwrF5/CwoCILwjpAVStPEmV/XzLq8XhLmH6dXJskKO0G4ONH1wr+ZuI4gnI0zXyiJ/owwHzHpZ66yk2/0gnCxMVN+0+lrzVfm7Aullau74HQUsndgmOsANJQESLproJKfRKkYrZ5vh26aoHG1lW4aF5p18djh8X4ag6q7dOS0qYnElNXxxhDVzMn/msYJGxV8KkPz8sHWXczmiV6qW1LjDTObzqU0Nth0bZCky3I8RnWkt5SkB3vLmM2i2/tJeuuP15F05gqul6Ipmggvv7iG2VhT9AXGb3+1mdncf9+PSfr/HbmNpLNjPnZM1wi9h+/6r2Q2tgB1ANxrA8zmhf3LSdo1QMsvvpi3q2SO1nBuUZLZ/Nnq10j6p93rSbr199vZMftfbyXptRu7mM2R56jNwmsGmU3vEK1vb0kc5tOOkRVwDfNRTVPaTZKHYrPRUMvyl1OxbhpzXruEamYNalyLa/fhZpJ21vD4clXMTr10OMaFjGw1tH8nQ1wrZGMVbfe7TjYxm/JK2g9zYXotI8kck5XGgtesHmI2q4oGSPqpJNXv8mznOgAHk430Bxe/uH+U5q91RT+zOabonz00SjW97GZ+XpdyCw0rgsymvY0G6NeuCjEbKONGtYOWb1Ej12Lo6l9A0kZtzzpGy6t9jOYlX8X7smaneTHV8GvbTTRMNJniDxZm/9S1tYy8tBUuDE0b+id9pyODNezvNWW0vw0bzPWaEvUcX8h1K2x+Oh94i+hYmnPxfpLoLVJsTMhrGky6DnM+Dy2nGWvmXAimy3GfqWUpsvzlnaEW3zTVv90xNWeYirNw93LdHS1L/cFEmYEQn5IfQ5m9DiooVLFygqTHQLV7AODo3kaal3rui2p5WjhqU0saaKiZa2n/zga5L7Kqjvovh49yPVxXLdW2zPQqzy8ZXlEmRUO3ZGOQX9tDr/1sfAVJV77MpR06E9TnyRdxm8Qw9V/r1wwzm55OqmP0zSH67GHkOxX103vyruN+0cBeOp7b1vPnP91Cy6vGSc/jbuXjcqCX6jeZuBsEu6IVOzhC85Ks5fdkU5pNpo73DbPiO2XT3HeyjU31Hz0jkhxzFXmdPk2cubObSTRohHnI6S/EOdGyEARBEGaA0/ON6M8I8xHZ4VkQBGEOr1Cab2TNU29vbVlRoRfmF6ZcHtZc4UVo1mLw9UwQhHnPTG1/O5+3vhVmlozZDGsuD1tWdj4U5h+2zFS7zVrkhZIgXGzMlN90+lrzFRn9pomwa2rbSm+ch8kJwlymKDa1DDbq5subBUEQBGG6iTgL4bce8ZuEeYgnNhVCFnHx7esFQRAuBebsCiUTdJhOBRXbrPzLVfdoOUnXVHHtmyE/1WLx7rcym+Aqeu7wDqonEFvMVxutX9pJ0gf2LUI0O6UN4POnoGl0+XbOQd86Vnygh5137HA9Sf93+Gpms7mFXnvX60uZja7ENo+FqW5BKsZjnRcuGiXpWJrb9O6mWlbZZTQeVht0s2Mco/SdZaKRx9DmHLQOHEe51s2Xjr6LpKPj9FqrbqDlAgDtr1Gtm79872+YzX9tv5OkgydKmc1t1+wn6dcqFpO0cw/X/InW0ZcyuQRf9fPfT9xC0iZF82VXPT+vpsR0B/9+AbPBNTTpf76WmeiLaJlbj03lbyLnQdrL35Jni2ibzvsMvijH6X26yrnWUXyU1t1ggN6naYi/0LI3UX0uo7f4mZNK+yujfddm520vFaft/IbWo8xm7wTV2dGsPKR13E/j6s3Kq/p0MQ/nyCn9sK+H650s2Eg1Enxu+tBVdQfttwCQfpnmd9nNfKw5+Suq8XbcV8VsvGUx9hs5pr+a/WZZQ8ee9oO8fZa00ns63NbIbNxUVgu7YlRDa81y3t+LN/pJOhkqZjamEtpmi2xULCD/qlFfpm3NbOZzgnqepIm34Vzx1HH59OysYpUVShc/mqZP+h9mG29nQ8NU/K6kjmt1BEeoFkvFTj5+ja9XxsHX6DHRJfyY5Sv6SPrkrgWIWJyoQhiObBae4Tm+unua2rX2NqL7pEudwQXSQ3o7FI9M+RXh4RKkSvhjVdpDM5wp4e3cHKdOg1bJtW5yim805qd9ztHPr51rpZpJRm3PdoKeN1lOjcx27uvlEvRaV644zmz2jtNnmryd+04xxR+0Kr5Tyscbfj5CfSf/yQpmE7yaPhO6i2k5uP+AajcBQOa31A+qv6uP2Yw8Sv3pbh+/tqPirV+O9/fwY3A5LePYLu4P2pZTP7h7H9cX9o7QujsSpc9BLav5PQWuVjRA/UXMJlVG82dX/OnKZ7nPE1Yks0wmXv9OJ/WdYmH+7JnxTh2XTc98Z5cVSueGrFCaJsLOqZcg3oR8aRPmF57kVJsNO/gLPUEQBEGYbs6cb4qT4jsJ84vTvlMeQNQmK5QEQZg5XnvtNdx5552ora2Fpmn45S9/Ofm3TCaDv/mbv8GqVavgdrtRW1uLP/qjP8LgIN2oacuWLdA0jfz7wAc+cN55kRdK00TYMTWReMQpEuYZZ7bZiLxQEoSLkryuzdg/QTgXIvap+UZ8J2G+4UkV2mzM5kBeRLkF4aJjJv2m8/WdYrEYVq9ejQcffJD9LR6PY+/evfj7v/977N27F48//jiOHz+Ou+66i9l+5CMfwdDQ0OS///qv/zrvcpqzIW/zjYTVhrTJDFs+B4+sUBLmGWeuqgs55YWSIAiCcOE5c4WSJ8VDpAVhrqLl8yg+9UIpJB/iBEGYYW677Tbcdttthn/zer14/vnnyW/f/OY3cfnll6O3txcLFkxJUrhcLlRXcxmL80Fep08XmjYlLilf2YR5hoS8CcLFj67P3D9BOBfICyXxnYR5RGksBvOpwe7MlXaCIFw8zKTfdKF9p1AoBE3T4PP5yO+PPvooysvLsWLFCnzmM59BJBIxPsFbMGdXKO3tXQibrSCibQlyQeNlK/tJ+ugwF5W1OaloWGgRv13bKBXqjtfQ2rSN8GMOTFBB26YVhXjE1HYzEAPc6TRK/8WJtHnq3JVfPEaO2b1tCTuvbwkVq02muYj44TH6BjHr4+J+Jj8VNctUUSE01zEuntaTqCRpexl37NZf007SBwapIFxTMxXFBYCjxxXRODPvLasW0HjO4WebmE0qRIVEHVSTHe2j/JhMCb3vr+29idlgLb1P3UAQ7sXOVpLO9bmowXJeVsmf0fZoWmEgyuyiv2UUwcLyN3nb82+hQo0n/5C/Ey6poPUQO8CFxjU3FdjzalODR7QFKCqbUA9BfIwKQNaXBZlNdD+tmFQZX75p8ihCyEFa5lotFU8EgFictlk9w++7ZsU4SVc66YB4IsCFEFXR2pePrGA2lfW0LMwBXi+lzVQAMjhKy1ytawCwD9L+narlouGvnKCi+9YiauMf4iLSpZupyK5V42NEze10/KxmKqdAxwSty/AIFWrUjFbmDtN68jQHmYm/l/ZlSzXvP3EfLRs9Tet73wne3xkuft/pEer0lzTSFRHDrbyedAvtl96XuU7G+AZ635Ygb59Fi6aEL1MpXteCMB0c66qf9J1sE7wd1q8dJunufj4umpT5IbCE+yKOIToAROtp33EO8Wuf9FOR/oq1ozCVpIC9hXSVh/sQs8rbCN18O4LbF/K8En164agMT43pgQo70otSsLm4mHZ2lM6dZZX8Yc30JBWnnriBXy+n+PuWCfpslFrA5xU9SvuuluUNwraG+gz1LipYfdJPNysCAM1G58Wd+1uZjbtR2UxlnD/L2ZdSQejsMPUzM3yvH7j66D3EG7jY844jLfSHYjqm9fRz4WnHtXQjErOB2rvrHjpGGXki3WO0vPyD1OcxGfRJS4DWk2kpFw1PdNGNRnJ1aWYTLKNlbErRcbj9CBVKB8BF7l28PNXNcmzN1E/3r+B+sW6h5Vf1LC/P4atoBdsDBoXTeoafdon4TuEw7Rd2ux12+zvbgTuZTOL//J//g3vvvRcez1Q/u++++9DU1ITq6mocPnwYn/vc53DgwAG2uulszNkXSvORWPHUg3FpOoJhJ3+QF4S5iCdamBxyJg1xpx3F4E6RIAiCIEwn0eIpJ7koKvOOMH+oCk099IXdIsgtCML00NBAd2v+whe+gPvvv/9tny+TyeADH/gA8vk8vvWtb5G/feQjH5n8/5UrV6KlpQUbNmzA3r17sW7dunO+hrxQmkZCJVNfv5uiI/JCSZgXWLI5VE4UviRNeFzQDZeeCIIw3yksqb7w/VtC3oRzJex1IK9pMOk6ykf5V3lBmKssGZpa7ef38BUvgiDMf2bKbzp9LQDo6+sjq4jeyeqkTCaDe+65B11dXXjppZfIeY1Yt24drFYrTpw4cV4vlERDaRoZrZ1ajrgk3P8WloIwd2gZGIU1V1ji2l9VchZrQRAEQZgechYzxioLD+PlY1E40jyMQxDmIqv6+ib/v69SfCdBEKYHj8dD/r3dF0qnXyadOHECL7zwAsrKePiqSltbGzKZDGpqas7rWnN2hZIpaobZWogFzZZwLYwjvbUkbQnxd2M2P41JNa/lO4jkcvQ4U9ak/J1r6uil1OHp6CkUekAvxrvRBgBY6OvHwEemYj17e6h2gInfEmIJ2mCyAy5m425VdJYCPCa59Ypukh77biNJu/5ogB1jT9Jrl995nNmkX6NaC6lBGvvaeYTG9wKAImOFRH2W2RzspjpLtrtizMbloGWeO0xXf5lT/O1x1WKqqeM/UMlstCZ6Lc/CALPxd1NHQffRe7B18aXOmTuDJO0yeLtd8n36Ravxb6jO1v56RX8KgNZFNXP0Yl6euTxtw+kK3tjMZ2hZXdY79fKzv7IE+byG8W7uHBXV0q/Hw0e59obeQJcmaBnePjFO+5SrntZBq2+MHXLgWCNJVzdyrY1Ehvb3o3todHumisdel5bQa8csBh1TwVTDNZ5GFX0pk5uWg27jSzYyyjiCxNmHYw3qeXmse+412kaitwWZzWCc5jcwwb+u1lXRvjCo1KV5lOuqWBqoHlKwn2s82YK0L2TTXMy0uoXWb4mdnvdk0GBS7KDj5ZLmXmZy1EY16AJJem1nOZ8jVpRRzZnd9gXMprmSjjX9A7XMxnSGCIrpQgmtnAVd12ZohZKscpwtLCENVmthDkiX8vGhp5Pq+zmCvK5co/S30CYeipaspPOMqmun5fh4limn89XgicIc0uWuRBUiMOnA8v5B7F3UyI6dq8xSVz5nzpa/6eqqs1oO6j2cS16M7vs872Flf8GXTlvMGPZ5oOsaEif5139LA/UZYod8zCa/WEkbvFe1jdI+lV9Iz7ukjPtOHQdp6Eyxga5hIk19sv43qe+Zq+V+kbuUzslJCx9rVNL1/KbSijajRXmMyFt5pcSa6LVMcYO1EUr96koDzfNHO7ieo7589G5uNBSl9Zvyc/+lpJrq30yk6U05hrlfnG6kY2yux0Djya/orqZ5/pzLqB5WiYP6ND1+HjnjPEbPU3v1MLPpsNPnp0iclpVWxeeIFZX0PAcdDcymrpb6eqGecmZzZuubDc9ipvym09c6H6LRKDo6OibTXV1d2L9/P0pLS1FbW4v3ve992Lt3L37zm98gl8theLhQJ6WlpbDZbDh58iQeffRRvPvd70Z5eTmOHDmCT3/601i7di2uuuqq88qLrFCaRvxFbsRshY65onPwLNaCMDdY2TXVVvsqfbOXEUEQBOGSo6906iFnZR//4CUIcw1PPI6F/sLD8EC5D3mTPE4JgjCz7N69G2vXrsXatWsBAJ/61Kewdu1a/MM//AP6+/vx61//Gv39/VizZg1qamom/23btg0AYLPZ8OKLL+LWW2/FkiVL8IlPfAK33HILXnjhBZjNBgsC3oI5u0JpXqJp6C8rwZKhEVQGo6icCGO09K1jFQVhtjnzhdKALNsWhIsWHef9Ef5tX0cQzpX+kqkXSqt6RS5AmPucXp0EAL0V4jcJwsXKTPlNp691PmzZsgX6W4hWvtXfgIL496uvvnqeVzVGXqlPM31lZ3xpk1VKwhzHks1hWc8QAGDM50bSzsOYBEEQBOFCMejzIXdqM4iVffJCSZj7rDqjnfbJCyVBEC5x5IXSNNNXLi+UhPlD88AoHJmCrkW/rE4ShIua01oAM/FPEM6VjMWCYW9Bb611aESEuYU5jwhyC8KlwUz6TfPZd5qzIW/WqgSs9lMCjgbCvvoEFRHLcV1kRBXhtpbiILPp20nF54pXU5uiUn5Mf4ci7nzGa7k+75RY7IqTQ8ifEv127qWCse/7w1fYeZ/47haSXv77R5nNMT+99uYtbcxmZ99C+kMzbaC5n3DB2NASmk78/ZXMJrOdLp1zBhRx3SK+tE7V5bRO8LrM1FDBv2yfm9nEo1TULtOgiHSHeVMOv0bFR51cSxkRJ62XXBMXlnMM0Txni+h7WCNxv6wi9u5zJ5jN+AofSY+8sILmZTE/RldeAf/VFS8wm//8+btJ2mLn9WLvLpTXugNTIo7DmQo49hQ6UriVCyymj9M6MBmMe5lKKnytTfCdCfJueu74GK2DQ2m+s0DVVloWw2YuLGiO0cLJKiLcWoy3kaBFEVSc4JU5aqc2rjIu3JxWxPtrF1GR5uFjBkKDLlqANdVcEH60k4pPl9VQEfGW6lF2zK5i2v8tGhfUNL1A67LkpgiziaRo3bmctM9lMryssgO0rEwGOp1qdnLlXCx99CS9b38Nrf/csIGQ92oqSHr46EJmo/votbKKkPDVDSfZMTGlbk0G4qNdE7Q95isM+s8ZAuWpNL9nQZgOcnVp5E5tAqAb+E7WcToOZh18fggqPkOtl48Pwa10TNPX07HJXcFfCgWOKuP2Gd2v31eGumAQZl1/a2HuaRBTnnXeTn4v0HPGXBcVn6ucDnnLaGZkjpagTCs05okVvEAdR5QHFIO6TFbRidEyzleLZ5XNPrRhOke3p+imEwBQ+xwVRh42VzEba4xmKFFD5y9LhK89iFnoPdnGuX8VtdO501zJ/et8ll7b20L9oOgh/rIupzwieOrDzCZ+nG4I4q6nfltrHRcw3+2lotGVBrsn+Z6k9xm6k/vpMUUs2+Km873JaFzupXWpGfhOqj+VMthwRz9G7ztUT30l6wD32+wbgiTdfYhvCKQrm2PllPUoGxd1sWNiWcX/t/KbGhjzkbRB84TWO/WMkMmI7zRXkRVK04y/qGhSmHv98R5YsmffNUoQZov1fZ2T/z9QxF/SCIJwEaHP4D9BOA/6SqZeIm/q6HwLS0GYXaqDwUlB7mFnCXRNHqUE4aJlJv2meew7ySg43Wga2msKKyy8sSTWH++Z5QwJgjGmfB7XdRwBAKTMFvR6KmY5R4IgCMKlSHvV1MrUGw8fmcWcCMJbc2PbVPs86eGrggRBEC415IXSBeBw/dRywRv2tM9iTgThd7N6sAeliUKYwglfDXKm89siUhAEQRCmA39RMYY9hXCNdV29KI1EZzlHgmDMmS+U2j08PEgQBOFSY85qKKX9TsBWiCHW7Tzu0h6hcbf2pTyGNtZHdUJ69/KBP91I4zGTo4pWTxl/55Zz0fyYEtTmSE0tspoJFj2Pm988hn9ZdzdwVZDY/PCFa9l53TfQ2OEdnY3MxlVEY5BfP7CU2WgZWjZFStFkinkAd9UqJc76SCWzybtp+J5pIc1LNs1fSNzQepykD3z7MmaTGqFxtkvez1/C7TrRSNIVlfSmgooWEgCULaM2iQyPSbceoFotKyuGmM3QDTT2OvhoPUkHlrFDkBgoIum4g+fPXELb0fKN3STdvrWJHVO7gdbTfx25htmoGjWVe/kayuErdFyz49Bk+kBzPWJndA+zm8cpZ2w0v9ZBXp72XhqfnVrAz7O0mt5D+zANmtZHuO5SaClts+V1E9ymjYbsqa3c5DMQeh2j+dUMYvzVEaDSzfVERg7S+tYVmTJTHRfwymdpfxnuL2M2ehEt82CCxsMffpb3//RmWuYHDi9iNrl1il5Dh49f20LbTekiOj6N1/LytDmyNC9+Lm5nqqeaA3qY17c1SmsvlaBtTXfzOWGwm2q6lC/kmlSBE1SPwbaA6r5sMxhP8zZaDqY0Hz/NSfqbYzF/GM4dmWoj+mzJAMyU6OM8Fpac72hjNmjWQn/RuNQYbCHanrOXcQ0QUyedrwJvcg242CLFDxqiwiaZSu47qRowlgRtJ2019agOh2DSddzQdhQ/v2IjvwEj1OY218IGpiM/RueQbjbjuFIpXHn8BABg0OfF8aXlgDZVEfliPrjHHbQvuHt53yjqpr9FG7lcRmM91f3p7qerym1D3CeLrKb+lWuBwdx0gD736IqwVraUz7e2Efr4mKnm96022Zoifu34bjr/5xuUuX+hgd+Wor5TtNvDTHIeevVwnPoiPY8v4MdcT897Yi+3yVxBz2tv5/6LrjxZO1uozxip5/VkclLfSRvjWkephYoWU4ifxxal+Usn6D1livlAEj5JdZeci7iPaz5G20i2ifq0B3Y3s2NyVnotW4oPWBbFNU4v4b6y88BUGZuy7M8XnpkUy57HvpOsULoAJOx27FlQeBmwMODHonEunCsIs81Np8IKcpqGI7VcqF0QBEEQZoq2mqmPNTcdkrA3Ye5xTftx2HOFlz0vrlhOXiYJgiBcqsgLpQvES60rJ///huOHZzEngsBpGh1D82jhRefepkbE7AbbJAqCcFGh6zP3TxDOl56yMowXFVY6XXu0HXbZ0UeYY9x0eGpn5RdWrHgLS0EQLgZm0m+az76TvFC6QLzUOjXR3HC87S0sBWHmubHtDKdo5fJZzIkgCIIgALpmwkun5iNXOoMr2jtmOUeCMIUpn8f1R44CAKJ2O7a38DAfQRCESxF5oXSB6Cstx4nyQuzymv4elIRiZzlCEGaOM3fRka9sgnBpoJ/SApiJf4LwdnjhsqkPHBL2Jswl1nb3oCxW8OVfX9KKtGXOytAKgjBNzKTfNJ99pzk7Gmq5KfGtohr+MiY5QkXYwhNuZqOV0uXS7oVxZpMO0+McQ1TArKnJz445EKZKl7qNN4BbJraje0EJWsZHYIKO+w7sxtPvmQqDO8mOADK7qWDsTXft49cep8LipnZeheHLqLBwzkbv6bq797JjnjtOlaU1g2V3RZW0HqIjVIjY6KBXX1REuJfw82a8VGVt37ZWZuOI0TKOnaBihO+6exc7Zr+fimePj3DhvtbNfSR98McrmU1O0cYr/4MBko5u5WLvSUV8dNMKXuO7dtH7PHS8gaRXXNXNjmk7Sm2WLBlgNh0e2qbrPnGCpEvHYrj8p10AgBFvMZaP9sGsiBymY1zsb+PiLpLerXHBwtKdynm8vH32Omk7ry6h4un+QS4Aa18TJOnIwVJmk3fSMreO0ntwt9JzAIDNQ0UiTQZtOK8M8H1H+DbBFRvHSXooQNva0kquo9YZoveQzPD3+1qK/mY2UXHM2rto+wWAwADVw/Is4AKLiWM0f43reDs6cZKex99L681I5DylCGxX1XNh7LEeet+2Ci4KXNsQIulMnrar5UVcPP+lHatJut4VYjYTVnoPmRxtn9XNtB4BYHDMR9Kal4ulWm10DDPt5vNRom6qbaUlkke4QGhZQDul62Ir4z6P1k/9l/Q4V+7Wy2kbNy/mQqkI0jBptzKE1LTyvn9COSbPpxkUp+LImE2w5vK4a/c+fPH9v4fM+T64G/nk6tB+LjbTxXSIhs/f54yLhjv2H5j8f7+7CHft3geLIjScjfC2unxpL0kfRj2zqX6dziEpHxd77nf7SLqkgs7tqX76dwDIXE7HAPOeImaTV6Yrp/IchOX8Gczmo+ct0rhwt+o7BQ5w3855TZCkJyZo/ppqqBA5APROUB8ilzMQuVYE/02Ke1V0L3+2Qy8VMNcW8fHTeYhuWFB2Bfftho7R55NkFxW0RilXltZD9EHD08g3mooq4tn5au6DFSvHOfP0xpd56KY4ALDrNRqlUFccZDYnrfQecsqmMh4D/3pC2eQqX2LQRux0rvFs42LkkQVTdZkS32nOIiuULiB7WqYeuG/75eH5HRwpXDTc9OujMJ1qi3ub+EshQRAuUnRt5v4JwtsgbbXg0ILCRxpPMoVbD4gGpTD7OFMp3L1rNwAgbTbjcB3/kCgIwkXITPpN89h3khdKF5DBch86qwtbgTd2+rHsEP+qLggziTmbw02/KmgA5DQN25aKBoAgCIIwd3h9Wcvk///ha2/OYk4EocDv7d0HT7KwUm9PYyMSdr6CSBAE4VJFXihdYLaunHpgf/cv5UubMLtsfL0Hpf7CMt5DC+sQdLvOcoQgCIIgzBwdNZUY8hXCcjd1dKJ1kIdpCMKMoev44BvbJpNbW7ksgyAIwqXMnNVQctZEYbcX4mIjA8Xs7/YWGtNbZOKxmdEAfVhuqeOxuDuUeN2i1TTu/3BbIztGs9HQNd3CQ9nczkJsa/vKSkTfsKEokcYVL3dieHMF/MXFyNWm2DHmYnqerX2L+LWV1XCpjQYxvoqeR9pLY1JVvSQAWLOAarEcPcwnzGgJLU9XD20+8UU8uLW4m6Yb7utkNh1PLybpmpsNdGEeozHngeuopsPWQV5WqriZq4PH5p6wVJJ0kUGPyG2mMcmxR6m2TPJaHseMNH1Xu/NEEzOpWUpjrwcHaVz4xpIent9SGpudyvEMazlF8yfim/z///Oz9sn/37VxIdwlBf2ahJPGoDtsXCfGaaL3aXfwOPBgKz2Pp5uZIKLTgP3ICE3bDAQmwlFF56OY2+jK6/GcidoEJrh2QEP1BEn39/EYf7V/a+X8vm1mtbxoHXSHSqBiOqzot63gfRlF9No5JR6+L8rPixhtExk3/26QW0j7T/c+vny/eiXVE/IfpmWTy/D+ZKmi49qIn+uWVS2kZT4y7GM2QTut78AQPc9wlPZbANAaqBZTf9zLbHIuZZ4YpV+ZM26DOlD0xbI5g/IM0vNoK/mYsKxyZPL/E0nehmaCmdqWVqK7Z5H6FGAvtPNcL/9gkF1B+77F4LNi1k/bc2sJ1wk5OL6QpPWNVI+uez8fU0x2xXcyMxNY3AU/YtuaRXjvK/sBAB98fRv+4ffv5sYXGlVTzyAcQf3JSH+Sn/ftZ2m6uZARFudUFvOAtT09WDEwCADori7FYKsbJhTmuriL+jwmOx/b3WY6H5id3GZiJe1zvhMG/pVONcgwSI9x6Pw5aCJCbWxegzasjAG6Q/E7DHTWiuqC9Dpd3BfJKy6CXsX9So9ZyXNe8V8D/LxFe+mJo2sNfHDF3curfnHYxw6xRGhB5Ir44JhapNTLDu6LeNYGSTq5j15Ly3C/PVNDn59Co/y517OYPotE+rmN6julB+gcsCvM9UeTjbT8Bs54ZjhNVtGFtQzTdp81KCtzgv6WzxpMNhO0LCbW8jayqHbKd0oms8Cv+WkuJDPlN52+1nxFVihdYHIWM3atKjhetlwO9+zaMcs5Ei5VGnvHseFAQRxytLQIJxfwlyeCIAiCMNvsXroQKWvhjdPdO/bCnTQQBheEGeAPt06tTnrjssVvYSkIgnBpIi+UZoCdqxuRP7W06N7tb8KU518RBOFCc/dv9k/+/47VTXy5myAIFzf6DP4ThHdA0m7FniWFj3FFqRT+106+O60gXGhKo1G8+9TubgGXC/tb+A5tgiBcxMyk3zSPfSd5oTQDBLxuvLy0EGZWGwrihqNHZjlHwqWGM5HG7S8cAgAk7RbsWdEwyzkSBEEQhN/NG5dNhbL/4Wvb5nc8gDAvuWf7TthzhTCcn266HFmLQZymIAjCJc6c1VAqsqXhsBVW8qRjPE40maAxtPY+K7NBJY3F3NnOd7RSQpvhT1PdDd3JVxOVVEZIOtTHtTpiQRrHmlxvAgqba+GLL/0c29/7CbZCJFtMl3R7nHyJ9/ieKpLWDOa2zAKqJZKvp+exneDx0KPltIwTtTyO1TZAyzi+kMYSW8d5cyp+H93Z7sAJ/iLDsZ6WZ8fJamZjVVYZt9RSTYf241yvofgEzY/p6iCz0XqoNovvVr4T39WVJ0n6x9dcTtLOTgMtmQ1UiytxzMdsBnUlNlzRXfr+1mvYMeYotelJGXRhpc1e/0I7rt15AkXxQmM/2FqHiMUJnFF9eozWLVfDAt4cpjpVJgPdslwRbTeJTTy2XVM0aKJuRb9pmDdqcx/VAbj5Gv61eoef6lQFY7Sd59L8vH2DZSRdWhVmNhMBJRg/xsu830rHgHxC0d2x8nf32RaqN5QP8V1jNEVPQFd0odIJfl5nDdWXy+b4fdtOUC0Gw/5uor+pMfSmFF/hZuqh5/WN8wfAbMpH0toyfg9Rpb/YF1Fto6SVl5XPTtuaRePts6mOjhuRNM3vqJ/PNUXd9D6vfvdBZvP6CJ1bkik+H7WPT2ktpFJGPezCo+sa05a7UNcRZociRxJ2e6HvpqIO9ve4MtY7uw00wWpo+vChRmZjVfp/IqWMk07e9601tB/netzMJjsx1bf7zFUYaPCiri+EJUMj+Pobj+Kvr/kgO+acvuqqTdLomLPZGIkCKW3dqOnPppbQbHbFt6UvNVOcQ17ef3wrPvbKSwCAPICxBgdyGdpfVJ8sZ+CU7+xvJGnNxC+eUXQh/dfy+UvP0XkjqIh+ugd4Zbu6qM1VN/P5680x6jvFInTc0NN8jBjvo/6rszbGbBITVL9H1SgCgFErnXNNSUV3x8GPCS2nZWMKcB+cTf9K0ehJg46hPCvlDPQSPcdo/UbreV0WKbpQGWWYU587AcB5ko7L7hGuoWVOUr8ntpqfR1O0OaH4mUkrLytVD9XCNEGB6gV+kg6naBuJjHGN0pKTtGzWvJcvpnhtUHkuT3D/umt4Sp4jnZ5532mm/KbT15qvyAqlGaK3uRQTFYXBtbo/gi07js9yjoRLBUcyjS07C+0tD+CNdaIBIAiCIMx99lyxYPL/r3mxQyQDhBnj2gMd8MYKLxkOL66F38cfmgVBEAR5oTRzmDTsuGnqK8AnfvgyTDlxjIQLz3W7OuBKFt7q71vegJEKvvOWIAiXCKIBIMwjOpZWYKiuMGeVj8bwe7v2zXKOhEsBbyyOG3cXdsXNa8BTV6yc5RwJgjBriH7SWXlHL5S+9KUvQdM0fPKTn5z8Tdd13H///aitrYXT6cSWLVvQ1tb2TvN5UdC9tAxDDQXHaHHfOO58mS89FYTppDIUwlV7CiF7WbMJL1y1dJZzJAiCcOkiftN5omnYeuPUqtpPP/ksbBkeDiII08mfvfgSnKfCa3Yua8RoqXyIEwRB+F287RdKu3btwne+8x1cdtll5PevfvWr+NrXvoYHH3wQu3btQnV1NW6++WZEIpHfcaZLCE3DjpunVin92Y9egy0tjpFw4fjEMy/Ali3EQ29f3YiAl2tWCIJwaXBaC2Am/gkc8ZveHn1NpeheXAoAqJ8I4N6t22c5R8LFTHUwiD/euhUAkDGb8Oym5bOcI0EQZouZ9Jvms+/0tkS5o9Eo7rvvPjz00EP4p3/6p8nfdV3HN77xDXz+85/H3XffDQD4/ve/j6qqKvzoRz/CRz/60XO+RixtQ1Y7JVLWGOcGQSoIlmrgQl2eQ/T2wq0GIsKKdmppOXXgJsa4SGutiwr3Bq38y4WtmAqhJXKFvHQ2lKOzpQyLTvhRMx7Ge544gO/efjUAIO+nYmnWI1zsO72B3udNq44ym90/pEptqmhcflmUHTN4iIp9164c5TbDVITPdZwKxMUbeR309JaTtDnEm9yta/eT9G9e3sBs/uC210j68U56j+YYfzdafoDWgf8avp7QNUiPG6nh9f3jfirC/anNz5P013K3sGNMihiq1UCEr3EBLeMzhecAwNTHBVXNipDgbcsPMZvftK0qnH94HB/YthMAkLaZcfSmGtS5QwCAjhO19LxK1WXtvDz1AK27rJWXpzlN85fKcfFksyIk7QjTY+o3DLJjYhnaN158eR2zee+NW0n6Z0euJulcLW+f1iAVWMyUcEFNTRGkNBnUZT5E87d5aQdJ7zrYws+rpH09/LxhqpUJezUV3M/EqeglwLT+UVbExTLjl9Gy0DO8X/b0K31XGT49zUF2TLhTESe/ij8Ql7vo+DMxXMFsMh7atiy99D7tC/ic4LbRihk5Vs5svM0hko4d8pG0w2AuT62mQp3bfsOVMNfc1k7SB59ewmyS5VMn1zISbX6pMRN+EwDEknZk9YJjk23mg5XZT52eaCP3i8r30LR/FW+veRvto85KOs4kh/nHi9pi6jv1WA3GLy8dm5LZQn5fvG4JPnzyTQDAXzz9An52xQbEHKfmyHPxwZnA9tuwMRTyVn40eCCYx88I08qcFuk+g7969nk4Tq2C27+xAe6GDNwozB0DR6ivrAosG4lIW/yK0LTNwHdSRO7zGb6xg+r/2QP0PN6rx9kxsTT1Td58ehWzefed9AXtbw5cQdLxBi7SbJ9QNhUq5/dtUvJrtJGHOUh9j5Uru0n66G7FCQLYUghvB/8wH2yh583X0OcB9HPfVO3vJcXcz4ivV0StDTZ78XfRZyXVdzIt4c9guRNUnyt0Ix+7KxRfLjtQymyyymOjo4veZ7pJKQcAbmVDk9hhH7NJK3nW9tDx3W3g0gQ20Ho58JNlzGb1+7pJuvvxRmYTqzyjLjNzdNAQ3t4KpT//8z/H7bffjptuuon83tXVheHhYdxyy9QDtt1ux3XXXYdt27YZniuVSiEcDpN/Fztbb1yM/Kmnvj/71asojvPd3AThnfLpXzwPyykB031XNiDp5rs7CIIgCBee6fSbgEvPdxqp8eLI8sIOsOXRGP73i6+d5QhBOH8WjYzi/TsKH+JSdgt2XN04uxkSBEGYB5z3C6XHHnsMe/fuxZe+9CX2t+HhYQBAVRV9g19VVTX5N5UvfelL8Hq9k/8aGvi28hcb41XF+NVVha/cpdE4PvbrV2c5R8LFxuqTfbhzR2H1Utxtxb4rL/5+JQjCWZgpYUn5iEiYbr8JuDR9p1eva0HGVHBbP/LCa6gMhs5yhCCcH3/zm6dg1gsD2M4rG5F0yYc4QbikmUm/aR77Tuf1Qqmvrw9/9Vd/hUceeQQOBw/HOY2mxFzous5+O83nPvc5hEKhyX99fX3nk6V5y9ffdyPS5sJSyY/8ZitWdA3Mco6EiwVbJouv/vcvJtO7rm1Exv62olsFQRCEd8CF8JuAS9N3CpS68dhVmwAARakU/t+PHwf0eeyBC3OK2/ftxy2HC2L4o8XF2LtpwSznSBAEYX5wXk+Ze/bswejoKNavXz/5Wy6Xw2uvvYYHH3wQ7e0FHYnh4WHU1NRM2oyOjrKvb6ex2+2w23ksazTqQDpdiCHW4jybmofG2VsG+VeEyEpqYxvmMcl5RQcm6FBi+s3cWWkbrDmrTZESkzoSpdo86wI9eGl9K9618ygs+Tz+62uP4qa/+ltkLFP3GljD45YdXhr/+sLeFcymWCnOnIsG8JrbubZB0Th1XEczvL6sShxwvIHGx9pGeD3pyk91Bvo4++6nejg///d/YzZ/sPt/k3TuJI03NvOiQvfv0Yvb95Ywm9Ib6Bfgwd4yZlPxBj3P1zK3knRxNdeJWVpO9ZH297Uym56d9SRtUfSH/uA9r7BjHn94C0mf1ks6k+//9/9gyUDh+oNVHjxevQ75XuXdcRGtu7yi6VJczMMw4yFa5nULeLx+8pc0pjtTxOPLVV2gZDWtPH+S62pUuWgZR5fzMn/02GaSNjXQvlKyi/d/77uGSLrXz2PS4aD5a1jgZyY94/S4o8Fqks4bjLQmLx0jkrVcB6DCQevBY6XprgpevuksvdjwBNdic3TTslDrAAAqa+jX/0A7vUcjfbmaVlo2wwb9KaPkWYvwwrlh9WGSftVKNahyOf4tZHDcR9LW+gSzCXbTsqheO0bPYVBW2jgdUMMtXHPGZ6FaC7Yr+cqJeNQ5+f/5NNfzmhk0nJvgzHRc59x57bXX8M///M/Ys2cPhoaG8MQTT+A973nP5N91XccXv/hFfOc730EgEMCmTZvwH//xH1ixYmr+S6VS+MxnPoMf//jHSCQSuPHGG/Gtb30L9fX1BlecOS6E3wT8bt8pG7bDZCv0b3Oc10O2mLZfZz8fQ8bX0/HANcDPk1NcrrjdSdKagcZeVw+9H83gk6ZD8Z3GIoq2yGIHwrvt8CRSuPnQEXzxF7/AF973Pn4ilXPSQzqLzTnpLr2NF1wisvTOmIZ3imWRCL78s59Opp+7dhk6+2qYna70n7zit1m9XKMGIdo3ShqDzMT2KJ2TMx7et4NLqE1MGdpyBpqKlW6qfTO0mj8r/ezgJpLWF9L+X7WV+wemuwP0vGM+ZgPl2aN8UZCZjIzQ49on6BihPqMBQLaE5meijuev2EX1horttF76s/x5AIofPBHlPk5xB7XJ1PHTuOupf5puozq7RvpyvuVBklb1KAFguJpe2xrmY/flG46R9DbbYmpg4Dv5R+l9mhZy/SaL8sxVvJnm12/gD1pGaXudWMHrcp2F1tOxLdxvS4anPsSk0wYPexecmfKbTl9rfnJeK5RuvPFGHDp0CPv375/8t2HDBtx3333Yv38/Fi1ahOrqajz//JRocTqdxquvvoorr7xy2jM/33l+4zIMlBcGjVp/CB9/+YVZzpEw31nV2Y+rt58EAGRNGh5/91rkTSIALAjC3CUWi2H16tV48MEHDf9+LrugffKTn8QTTzyBxx57DFu3bkU0GsUdd9yBXG42HNApxG+aXuIOO35y7dTGHe97Yx8qQhe3fpRw4fnHXzyBokThQfpgSy0OtBq8KRAEQRAMOa8VSsXFxVi5ciX5ze12o6ysbPL3T37yk3jggQfQ0tKClpYWPPDAA3C5XLj33nunL9cXCTmzCT+6eSM+9ZMXYc7r+NirL+L55StxpG52v6gK8xNbJot/eejnk/H/r17ZipFKD8AXEgmCcCkyUzH653mN2267Dbfddpvxqc5hF7RQKITvfve7+OEPfzgpev3II4+goaEBL7zwAm699VbDc88E4jdNPweb6rG7eQE2dPTCnUrjgR/9Ah/52If4FpeCcA7cvm8/3n3gIAAg5rDh8RvXSFsSBKHATGobzeMI7mlfuvDZz34Wn/zkJ/Hxj38cGzZswMDAAJ577jkUF/PlcAIwUOHD8xuWAgAs+Ty+8ovHYM3y0BdBOBuf+OVLJNTttc3Ns5wjQRCEd8a57IK2Z88eZDIZYlNbW4uVK1e+5U5pcwXxm86fn129DmFnISzo5kNH8J6de2c5R8J8pCwSwRd/8cRk+okb1yDm+t1aZ4IgCALnHSv1vvLKKyStaRruv/9+3H///e/01JcMz29chlWdg6gbD2Hp8BD+/OXn8Y2bjb/WCoIRqzr78bGnCtsoT4a6mSXUTRCEM5jhFUrqVva/S/fnrXirXdB6enombWw2G0pKSpjNW+2UNluI3/TOOR369pFn3wAA3P+zX+GNpS0Y83rOcqQgnELX8X9//jjKYgUdFwl1EwSBISuUzok5u/WTxZ6D1V54IM4ZiLZqSqmbuIYYioqogG2knD9gOwaoqFmulorI2Wx8tVDKTwX2zDG+NDbopDa2HupE58umrpMH8MgVV+Izv3kGZl3Hx155EfmkBf9x8y1QScWpmJu9PsZsMuU0XWyl97B4DY+BOvoCFb21+/k9xVZSUbs7Vx4k6Sf3rGHHuHqoKNt4lIvR6X9C7+F92z7GbJwueu1UNa1wax8XGixqoA8zV2/uYjbP7FhN0pYobyORO6ioYc3P6T2Em7i43+6lVBzRHeDlGVfamirc/Nt/vY4dE95C7/s9z7XBms3i008/A0u+cL4Xm1ehZ6wBOK03XGWgIZKl9+nqU/rBAP8ynqun5+nr54LLNXdRocaQUX0HaF9YWEvbo9PCO/OxASqOaXHwfnlz8xGSfv44FawPbuTHhBQR7nyMC3c7B2hZ9Ya5UK6tigoJhgK0/j01XEQ8fZQ++JhauVBzShHY7uysJWlvJ599tBtou4+ZeN9wXEb7XHKIP4Tl8vS+s1W0Xso9fOxxq3XnNhg/U7SMdQu/hxeOLyfpok6al5iBz1/eQNteNGUgWFxG8zd8nA6WxXzPAERWKfeQ5mPESy/SjQXMSX5P+hlVp2cujXAKdSv7L3zhC2/7pcn57oJ2rjYXHc4cYCu0US3CxzOYaNs0p3hbtRXTfpKo4is2inpoOl1P5zPNwcXrtTE6FlkNfKe4i/pOat9PVE79f1tpI/Ys7Mf6nh744gn88J+/i0eWb8EP71vDr60KX89kszjbQ8LbEfI2vM78autG2Z2uojgb73ljP9b2duG2g4cAAFGbHU9WbYbl4FT7S3NNbiBLM13cTf+s9/K+EmmkNxXo8TEbz710I4dgmM/bJj89T8UCOue5DHynnt5K+oOD+4NXL20n6a1tS0l65Cp2CKCIcJsjXCC6qJemJ4LcZzTV0Dyn/LT8jDbXKDpIx4jkCu5nJBXfKX6cilxXHuNlFb1d2SjFxMfP7AblWv1cCD2rCF8na2iZF5XQTTwAwGml/t9EMR8/kVDyY7Ah1La2JSRdcpzahBfwTudqov5pLMnbXrqC3nfkiI+ky/p4u/Kvpb9pBr7TjqfoxkL2BL+n9IKp4/IZg3IR5gSyhGGOMFBWgpcWFfQUzLqOP9z3GsqjIjQpnAVdxx+8uR01oYIz0ldSgpeaV57lIEEQhAtPX18f2dr+c5/73Hmfo7q6sGOiutLozF3QqqurkU6nEQgEfqeNcHHyi/UbEbUWHkKXTgxiS+/hsxwhCEBtMIDf37N9Mv2LtRsRVXYqFARBEM4NeaE0h3h58Ur0+ApfzH3JOL7504dFT0l4S25qa8P6U2EfSYsFj1x1pezqJgiCMbo2c/8AeDwe8u98w90AoKmp6ay7oK1fvx5Wq5XYDA0N4fDhw7JT2kVO3G7HL1o34/R365t6D+Jd+w7Nap6EuU1ZJIIPb3sF9lM7QO5e0IT99QtnOVeCIMxJZtJvmmerTM9EnjznEDmTGT9Yex2CjsISyrX93bj/tz8H9HkcVClcMG7adwS37z8wmf7hVVdi2OebvQwJgiC8DaLRKPbv34/9+/cDKAhx79+/H729vdA0bXIXtCeeeAKHDx/Ghz70IbILmtfrxYc//GF8+tOfxosvvoh9+/bhgx/8IFatWjW565tw8XK8tA7PNa6ZTH/94cewrN8gflW45LFms/jW936A0nghZLunpAw/Xb9JdnUTBEF4B8xZDaVc0I6s7VS8qIHGxlX1nSQ9UsE1QDqOU70RcymPmc0Z6JacST7PJ5nrllOtljffWMFsLF30S6z7siBJl1v4dYejFZgocuK7V12Hv3z5OdjyObx3/04cWVCDh6+5FgCwesNJcsymkm52nicHaEzqeJjq2OzrMPgS00Q1irz7+Jfk5Y3UQTseprHZrm4eb7z2TlpWwTRfUnyklwaqW3v4taPl9Nx1TVR3ZzBSwY5Rz9If9zEb5Gj9Lr68l5k4zHSVWMWnqKbSyx2t7BhrF40D99zAhWGzb1aTdLKetonRq3l2vfsKsc2L/cP495/+ZPKN8G82rsKhZTUAsshkaLd2DPPYdpMS7pxoUTSpBngMtWZR9MUGeX0HhqkmjX0F1w6yd9Oy6XVTHSO7g/cNNfbas5/n74WltN1Dye8/Ln2OHfP3h8++nXiqjI4/DYtHmU3fhKKjpbSrcIBrSdmVoSXbUcRsilZOkHRJY5CkE3W8DhqctMwTexuYTbhFaRMuHv8eO+gjaUsL1aTbUk51FwDgt89tJmmjAIJkBS1P3UBrpaSc3kM4RvUPdCfP73iIlp8pwMtG99K+fMN6Gh7zWu1idoy5n96FexFv0+EU1Rwzl6aYjWloakQyvfW0c8HQ9Zn5PnG+19i9ezeuv/76yfSnPvUpAMAf//Ef4+GHH8ZnP/tZJBIJfPzjH0cgEMCmTZvYLmhf//rXYbFYcM899yCRSODGG2/Eww8/DLOZj38XM6YJC8zWwhyQN/CdNjZ2k/RwNfedho/QuV0v4yulo8vfupJ1A9/p8jUnSPrQiy3MpqiDjvX6eqrV5rPyvMQiPrzoWYHKTBDrBrrhSmfw0Le/j7v+z19iorgwLujnIM5zVp0lo1NcqPcQb6efGt3jPP7iPe3oOu7/xS9xeWdBTzPkdOKhW65Gwq0ByCGdoWOFa4CXp0lpfqFldP5y9fPxRrfS+coxxL/lZ4boHGddw7WDik/Sc48W0WNMTt43TEla/+Xb+T29eRnVTNKUqfMf1zzNjvn7vWffOChRQa9dsnSC2YyOKPegaFRlJrgXYVWatO0Y162yrKGSIflmOm/7F3D/oM5Fx5rAjkpmE16m1G8R919Me6m/py2j9XJ91XF2zGu/pDqMXmYBxKrpjeecvC7tlVSfKaromOZcPL/hCWpjm+BtOFdC2/DGK46R9Lb6RewYRy/10/UWrh0VT9L6zZVz387eP9VfzLPgO82U33T6WvMVWaE0B+kvKcNjG6YezP72yV/j6nb+8CZcmngTMfz7k9+FO1N4aN27uAHPrVs2y7kSBEF4e2zZsgW6rrN/Dz/8MICpXdCGhoaQTCbx6quvYuVKqhXncDjwzW9+E36/H/F4HE8++SQTBRcuYjQNP7tsM/q8hQ8UDRMBfPuhH4psgDDJB9/YhnvfLOgmZcwmPHTj1Qi5uaiyIAiCcH7IC6U5yr4FTfjWDTcCKIh0//ujP0Tj2NhZjhIudiy5HP716e+jIewHAPSV+/CjLZfLcm1BEM6OPoP/BGGGyZoteHjDFox6CivXNp/owhd/8qv5/dlXmBauOH4CX3j8V5Ppx668HD2V5W9xhCAIAmbWb5rHU5W8UJrDfO3Wd+GF5YXts72JBB763nfhneBLBoVLAy2fx9+9/HNc3t8BAPA7i/Dft16NtHXORq4KgiAIwowRdrrwkY/9MZKWwrx439Yd+NMXXpvlXAmzSevQEP7j4R/Cki+E+3zn+uuws6VplnMlCIJw8TBnn0QdZTHY7YUY12yev/fadoDG/OZ9fFmz7qaxmCVuHpMc7qKRqloV1b7Q+nj8rqmGvkLMFPNXiquXdZO0RRGtaXu5medX0Ra5L/Aqdt7agMtGe1E5HsWisTF87s+exQc+/VEEigoxr45V/L5DL1JtntQSRTvKzPPrUDSfog3cpq2zjv6g6NpsvJ2H5R37HxqKdftfcseurYOe17tunNmM9ftI2r+d3qPFwfObzdI44IEw14pACS2b40frmYm7lsZeZ0vofVeXhdgxI300pttl5YG/gzVK3WXfQr9B13H/Y0/i7iM7CqYmE35wy+UIWLyA0qwr9tJ7mljFNakqVlIdoPHdNFY83Uz1cgCgTOk/4xlenjYP7T/pHI/FdinyMnqKlqdrF4+HTy2n6cBSviLLrLxrLWsNkvTf7T97zD9MvB2VNtHzDIR4dHttCW0DAxH65dPMhx7kFBkoZxPX5lH1BcxxWlZLlvbzYxJUS6hsE9d8CibouBYd5fpNxaup3oHDQtvr43s3sWP0GiU+32EQD++ifSGV4FoGyQM+ks5X0vOaI7xdFS+g+gchgy89mlK/LxynDcsc4XONOU3bWqyzmNloSl2aunkbPrM/z5aG0oztIiK6LbNHRQqwF/qLbuA7HdhJfY90Ge+jmpv2N2cR1wTLdVDdjUwNbdTObq5zZ1L8irSPt5PFl/WRtEWjeel/egE7Jk/dASzN9eNXN12G339mLwDg848/haTNih9sOWPHP0O5IfrjWTWVjDgXnaVz+Qr9do65CGBF/g7LatHIKB751ndQEi84CEfqanB4YTUsMd43KrZS33NiI1/B5NgcIOnibT6SjizlPnmRhzoA8TSfb+FTJoUMn+MscdoXTEn6CFe5lZ92bC1Nj1/G51trjBagfQXVH/qHHbezY1iRGyxPsLdQn2Zsgs+d5RX0WoFOH81bhHe6nDK95pu5g5UYoteyKPfYsGqIHTMao8c4rw4yG1uCXjw/xOd6bQPVWS1TfKdntq9nx+TraUM30joyu+h59AR/hLftpiGcMeV51RrmFWVqos5zkinQglX4trYlynl5PZmUx4j8cR5eqimXcp7k7ZP4TrMRwTyTu6/NY99JVijNcVJ2Kx593+UIegqD1tLBYTzyjYfgiRs8oQoXJ7qOv/3FU/jQK9sAAHlNww9v2ISuGi5ELgiCIAiXOntXLMBzV059ePy/j/0SH9i6YxZzJMw0DeN+PPKt/0JFpPBio6e8FN+7/kroJnn0EQRBmE5kVJ0HBH0ufP8DmxEuKrzKXdk3iB/823/LS6VLAV3H//fLZ/DR5wsru/IAHt2yEfua+VdaQRAEQRAKvLh5CV7aNLUL65cefRzv27Z7FnMkzBT1fj9+9B//iZpQYfVwf6kP37p1C5I2vnJOEARBeGfIC6V5wkRpEb7/gc0YLy4sM1/b3Ycfff07KArx0CThIkHX8Xc//w3+4pmXJ3/66bUbsGuJxP4LgnD+aPrM/ROEWUfT8OxVy/Da+sUAAJOu419/8FP8wevbZzljwoWkaXQMP/nmt1AfKISnHa+uwn/cej3idoNQHkEQhLdgJv2m+ew7yQulecR4eTHu/es/nXyptKp3AH//F0+JUPdFiJbP4//++Jf4yAuvT/72d3/wHmxbvngWcyUIgiAI8whNw1PXrcT/XH/V5E9ffvRxfOglA8EZYd7TPDyMxx78FmqDhZVJJ6oqcd/HP4qo00DXThAEQZgW5qwot37MDd1yamnqUoPQLuUtnnWIC3nl6qmQZCzFl7qaM1QASxUA1wxeub3c20rSCxZz0dt9vQ0k7ShWxIqr+GtIczm1MXpRufzEKB665np8/OUX4U0ksPDkBP7mo8/gzz5/L/pqSgEARdfT/FxXQUUuX36CC8Ld/N6dJP1s5zJmkwu99dedQ88tYb+t/ZOjJP3Iy9cwm9Vru+h5+mqZjTlMm2puCRXgzfdzsbfkEBUNTTi4wLqjj7ab+973ErP5wVPXk7TtqjGSHm6jgtYAkCujynFde7nY921b9pH0M20rCufPZPGl/3kc791W+HsewE9vXI9YpQWmPBXq08a5gNvwdUq31rno6sBJqr+kbhSXNxCEDMZp+VmivHPUN1Bx6npHgNm83kLblmal9xS+gucXIdp3VQFugIsujowpgvtWLnJosdNr5cZ4Gx8bVoSxDcQ8h5TjLJW0L2esfHy6Zzntc6/7W5iNbS9t1xOX03bVfoy3q7xSdUYihu4GKpZp8qSZzfiQj6R1RdBasxiMYQlaB7kcn2Jqq6nwaVegitkk6mi9rFgwQNIn9vKQT7sifKmneBu2D9HfHKtoew1Z+ThSWkLLatxAWNTupuVX5uINdLRtqs8ZCZjOCDO1Le08/so233EdssNuKYw3kZVnV3939fN+El9I+1Iqxccvu6LTnc7RRm3UxredpILgFa0TzKb9JN2kw+Sh96DVGoj0VlIbs6ogq2lo8zTipZYAbjhxBADwxZ/9Gt5EAv92+02AdspeabeqSLcR5yTcrZ5mOkS6z/W4aeBcvppfKC1Zo/P+rvys7erGQw99D2Wxgn84UObF9951Ba4YaodupSdS/QUAGHx3Gb1O3mCzlxMlJG2zKjbq5ioAYlH6MstmIGBc2kjFqRe4uO+0ZwXtP3k79WlGrjcQXFZOY43za1uj9B7CI1Q0XLdx30lTrm0e5WNEfICeRxX/BoDQCC3PfDXty+kI9yHuWr2HpF8d476Tcxu91tB1NH/9h2rYMbqyYVEmY9D4FAHrrI/7q/F+et9R5RZMBhsjWZR60Qw2VKhQNgga9Zcxm4jiGjUtHibp4Tf5fVutdLxPJ/izkpu6YMisV4S8bfyFrb2U2sT93L9ShcYdLQYC6wd9k/+v86Z44Zkpv+n0teYpskJpHjLi9eKbN96MgKvQORcN+PHTzz6EzQc7ZzlnwjulIhjBj7/80NTLJA340a0bsWOlhLkJgiAIwttC0/DU8rV4dsmqyZ8+9Zvn8a2HHoEzxV+oC/OL923fiR9/89uTL5N6KkrwzbuuR9QlK5MEQRAuNPJCaZ4yXlyMb954M07WF7Y19UaT+M4XH8EHf7MD0OfxK85LmFVd/fj1/Q9ifUcvACBtMePhd1+BPUsXznLOBEG4KDi9/e1M/BOEuYam4bllq/HrFeuQP7Uq6fa9h/CLf/4P1Pn5ihBh7mPO5fB3j/8K//zjn8KeK6wWOV5bif+4cwviDtFMEgThHTKTftM89p3khdI8ZqKoCB/4yv/GK+sLyz0teR1/+91n8Pl/exrWtEGcizBn2fBsN372//4LNYHCsueBUi/+/f1bcKi57ixHCoIgCIJwrrzashwf/viHEDn1wmFF/xB+/eV/x4aOrrMcKcwlPPE4vvdf38WHX53Smvz+NVfhW3dch6RddnMTBEGYKeashlLaC2inYpPtZh6junIVDe/aN9DAbCyKxofbzpc1h5w0VlRX4p91A50QPUdtenu4hk5L0yBJjyao7kbWYIV11q98TanjO7hZa2h86f86sh9v3rIINnsWV24rOEO/9+xBrNw7hP/Zcg0iTie2/wEtG881I+y8oQwtB6+bx7GuqB4i6ZMT5SQdhIcds+9ZqpdjWxVhNgMRqlGTz/D3nJqiSbOuoZ+k2w5y/aZ4M203Vjcv9Mq9tC5/Fr6B2RQnaBvob6dx7I5q/kY5odyCrsbZA1jz214gr+PyF7ux7vUpnavOmjL8z21XImRxAwbyYWdiX2AgJtRL45TNBm1NV3p+zkHzV1lK4/kBYLyzlP5g8Dq6/yCNz44sNfhCqGjxOE/S2PZUBR+W7NW0IIycxVyZUsZKO7IP8vOmKqh+iFFZFfXR82Q3xpiNy0bj/oMxpT+V8WN+O7SSpJM9RcwmR02Yno8aUw8Ax3qoBplWwnVUwn6qL+Y7wiszpxRxpJmWr5GWlE1pNmo7A4AuUzVJ1y0YZzZqb+mL+kg6XcbnhMBRRU+glNtYkvTMoUE6ZjkrDerWQstPz/H7XlZCdesODHMduPwZ+cmmZ0MIAKKhdAmQ9GFSL8Zs4e2sZV0vSbf18I8Wqj6azc7HkKxbGSCU7pY36Pua4jsFTpYwm7pWOh6MxehYBaPotDHlYgu4UVbR1Kx3h/C9+67AfY/vQlkghvJIDD/5+n/hF2s3Yvviwhz/+PWrDS5GUXWWmKYScHbNpFnURzJiru809InA0ygdi+GuHx9AyUTBN8hpGn569XrsXtYALW3gQyr1km5MMRt7N/VXzCleEGq7zrroeb3lfA5JHKfzjJG+WHAP9aejK7nvpB7nO0Z/iFdzPbRcLb3PVIT7TskKOk6YUvS87h4DH7ea2ph5ccLTSc8bupqPIw5lbMlGaIiivYI7wb/tp46RqZOHNUbXK89/pbReKhqi7JjeDqrnmCvj+dVGqW9XcYB/vM876H0HltCyMtKSsgdofo3Gz1GN+jgli4L82ko77w/R56tshcEz7UGlfZZzG6vyHJRQnjMsNbwBOKy0/KIGvlNLJfWdjvVzjSftDN8+PRvRyaKhdE7ICqWLAN2k4ZXrl+CX77kMGUuhShePjeHTTz2DBr9/lnMn/C5sySze9eM28jLpzeVNePA91yEicf+CIAiCcMEYKy/Gf/7R1ehoLDzMW/J5/P6eHbh77y6YcwabQwhzgqb2cXzgoV2TL5MiDju+ecf12Las+SxHCoIgCBeCObtCSTh/jqyoxUSJG3f/ZD988QRK43F86rfPwlsSxfd+/wrkLPzrhTA7XHv0GO750W4UhQuv2/Mm4PGr1uD1y5qndpwRBEGYTmSFkiAQkg4bfvj+Tbj15SO4cndhlfc1HcexeGwUR1srcXgB30lTmB2KEkn87a+exHu2HZj8bbSqCA/ecD0Cxe63OFIQBOFtIiuUzglZoXSRMVzrxb+8+zZ0lRe+uJl1HX/6yFY8/FffR0snD3UTZpbiRAJf/tFP8f3//O/Jl0lJpwVP/eEqvL66RV4mCYIgCMIMkjeZ8PSNK/HjjZuRNRXc4tpQEL/6yoP41JPPwpoVTcrZ5pqj7Xj2y/+Ce7ftmPztxLIK/OTDG+RlkiAIwiwjL5QuQsIuJ/791pvwzKqVyJ16QbGkcxTf/8T38b8f3QpzVpZyzwbXHj2GZ778L/j9HTsnf+tb7MPP/2wdBhZzLQlBEARBEGaGnU2L8fUbb8WArzAfW/J5/NVvX8STX/53rOztP8vRwoWgKJHEA4/9DD/89kOoCwQBAGmbGS/evgS/uWcVsjZZeS8IwqXJa6+9hjvvvBO1tbXQNA2//OUvyd91Xcf999+P2tpaOOziTe8AAOlVSURBVJ1ObNmyBW1tbcQmlUrhL//yL1FeXg6324277roL/f3nP9/N2ZA3c2USZnvhxUc86GR/77RQATubw0AYrZuKhgWLuMidog8MLUSLpLgpxI4JDlMBM5OBGN1wjNpkjlJRbvtSLggXm6D3GQhwkV67Iiwdy3CBvTWt3QCAwWVe/Obqy7DxsW7UBkKw5PL400e24po3OvD5T9yF9qYpcdx9j64i53jus//Mznvn5z9D0iFF9A4eLmBXeiUV2Bwa5i9OUnEqyty8YJTZ9L9OhcXDDVRjKL2Ki1Obh6iN9aSBkPNfDJN0dMzLbOoqgyTtf4WKxqVWctHAu5ftn/x/RySDOz5yAFe0T+0gk7Ba8MsN6/Bmy2LArwF+4C/WPU/O8e2tt/D8VtAyTk9wrSXVvUrV8nqxBGg7L1lMt0z2H1cEuAE4FlJRw1QP/yqYrqD90GYgqL+2le6ksz+7iOat0kCJvJ325aI4XxeaKqGru2pX0hV5fSkung8nzZ/ZQMC6eCm978EJ3kayefpuPheibS0c4GOPNUzza1rE2/ACLx1/Rl+lgtYdq3j9l7TRvARbDITRlfsOreXjp8tFB7YaB90kYDSuiGADiC+gYpSa3UAY20ptxuMuZpMZpL+ZqmheNCsXG/YsoYrgsQN8rIktUeo3RvtBvYeP9yfH6FxTpYwHALCvZwHNX8rgW82ZAsmzpMktIW8XP9naDEynhh9N3egDwEkr7bcmJ+/79k56XKaYu4qqcLMtQGceUwsXJzap/TrJV+SORqjfYztIx7jkKr5ZiT5G85uc4D6j5qb3GU9bmU3zyoIT/esrVmL9a71Y/2ovzLqOZQPD+PWXv4kHb7sB37ztRmQsc9Z1Pm+mS4Db6DzvdAfsa462499+8ChKY1NzY3t1FX6yYTMmioqA9sJvf3bFC+S4771wMztXspLORaZxg13glHuI1/ObsvnpTdmW0I0xUm18c5r8YtpmLQYi0slqOimUWvjc2bCCPuSdyFG/OFfNFYtdbfQ+bTF+T4ky2neL102Q9ESK+4M5F82fbrBRhmsF9Wmy48XMJqYINZsU3zTrN9ikJUjT8VZ+39Ul1B9IPUfvoWcdHxsr99Exwr+CXzvnpuU3tonP9ZYi6md4nbT+Y3EfOyZM3WDodu4kaDZF7DvKfSdzvzJ21yibitj4ec0raT0V7eTPnhMr6X1bIrQf1Pj4Rj59w7TMfdXcpr2DhhRbDJ6n9TOapzYbvtMcDnmLxWJYvXo1/uRP/gTvfe972d+/+tWv4mtf+xoefvhhtLa24p/+6Z9w8803o729HcXFhf74yU9+Ek8++SQee+wxlJWV4dOf/jTuuOMO7NmzB2bzub+wv3hmRcEQf10R/vnuW3Dr3jbcvP9owTnqGsZPPvPf+O7dV+G7d1+JuNPggVN45+g6Vr04gPf8y374RqZekhytq8KPr7scQSufXAVBEARBmD3yFhN23dCIl4uX476tb6I+EIRZ1/FXv30Rtxxow9///v/Crpam2c7mRUt5OIJPP/UM/uDNqfC2pMWCX21Yizdam2Ey2MVNEAThUuO2227DbbfdZvg3XdfxjW98A5///Odx9913AwC+//3vo6qqCj/60Y/w0Y9+FKFQCN/97nfxwx/+EDfddBMA4JFHHkFDQwNeeOEF3HrrreecF3mhdAmQNZvx1MbLcLCxHh98ZQdqAyFYc3l87Gev4/3P7cF/vv9a/MJ+A7JmaQ7TxeJdo7j93w9h4eGpLz0JqwW/3LwW25YuAjQNmsGbeEEQhAuGrr3zZQPneh1BmOcMlJbgX2+/FbccasMtB9smVyv9/Gvfxosrl+Ir77kN7XV8m2vh7VGUSOJPX3oFH375NbjP2B+8vboKP75qU2FVkiAIwkwyU37T6WsBCIfpai673Q67/fwWf3R1dWF4eBi33DIV7WK323Hddddh27Zt+OhHP4o9e/Ygk8kQm9raWqxcuRLbtm2TF0qCMX0Vpfjnu2/BkvAwPvz4G7Dm8igLxfH5/34Gf+zZiQc334anl6yFrsnXn7fL8u5B/H+PPYfrDp4gvx+tr8aPr92IQJGIRwqCIAjCfCBnNuPpNZfh4IIG3LFvP1b0DwEAbjx8DNe3teOJy9fi63fcgr5yHhYknBv2TAYf3Pom/vy5F0h4W9Rux1NrL8MbrbL7rSAIlw4NDTSc9Qtf+ALuv//+8zrH8HBB0qWqqor8XlVVhZ6enkkbm82GkpISZnP6+HNlzr5QykRt0E7FuGt5PpFEu2mccs4gHHrdhpMk3RXmmh/Rdh9JO1roW8HgCI+H1oponK255Ow7gNRvGCTpiSSPfY07aHCo08mXsGQ76Rea4pVjzObQgUaS9pFLm9G2rB5fuvvduH3PQazv7C3kLzyBLz/3KP5yx1N46rI1uOPAH7MJPPs+Gld9YxWN535x90qWF7MSWO/Zy9+wJqqoTae5nNnAQ8vm5G6qWVKzjcdv28dp3PLYWl7mY7toR3OvCjKbYILGu8dbab3c/fhRlEcjuK1tP9b19ZC/DRX78PTSNSh/nx8bNPq3PRP0Hh48dgNJmwx6p3WINvRMNdf80RVdCi1mEAeuhPCblHrSDd4p6odo26vfzAebnl6qUzQU4P1nWKO/5ZV2b2nj9WRbS7Vt4se4jpFupvcwkaDnyRcZaIU4FE2qMa69MRChbXZpwyCzaT9J48B1RTvIbKDx5qylcf+pLI9VdpjocfYQLatojOuA5K+jmg56gJenqvHj6OMVnjPTc0+YaP3nSwxi/HOKLlSA50+rpP1yVdkQszlhqaB52UHbTKSFX3t8jNpojbxv2NT6VuLVi61cnwVjtM8F+vk8snnTcZI2GQTC7xpZOPn/+RTP20yg6dOnmXK26wizRNgKzXrad+J/znfQjxomO6+sxVfQuaozyNu83qaMB8upDkd6kI87OTfNUL6Uz9vqiOG9iuow5gw01xJOZQ5xG/T943TSc67lmnXdu6gTX94zNf6m4MVDW7ZgY2cXbtt/EKXxOEy6jvfu2Ivf27kfbza24MXWVXj49zax814KvJ0P+Pc8uxfr+7twy/GDKElMaW5lNRN21rXg5cYVaLmjB1eDjq97xmg9ffsg9Z2MdLqdA/THRB1ve+YEtTHH+E1lnbS/OE207aUMru1S/F7ntX5mM95JX0j6/Xw1ll+jv6l917OPz7fJTVSTMn+Y9x9dcRGDMeoH5Yr5QGJSdBhNI/zagQj10xob+U7T/ceoD676prrDoJ4aqO9kShv4TmZlDPDTY7QofxYJvYuWVW6Cn1fVfXMP8TaSN9Nzp5V0rpSPuYqrB1OMXztbQ8tiWSX3wTts9Pmp9FVaoBPLua8XG6btSm82qm+awazSaDwW7jvZRqhNuof77Wuu6WK/qewfnPKv9fTM77g5U37T6WsBQF9fHzyeKZ/2fFcnkXMqz/K6rrPfVM7FRmXOvlASLixj3mI8fMNVePGyZbhz1wEsGygMTHWhIP709VewPnASD99zBbavWwTdJF+GfheLhsbwvr07sLmrA2Z9asSZcLrx7JLV2FfXCF0z4Rpt4i3OIgiCIAjCXCZvMmFH82LsaWrENe3HccvBw3Cn07DoeVzT1Y6NvSdRagrgkWuuwKiPPzwJBazZLG47cAifeu0pVEemPhblARyoasTziy5DwCkak4IgXJp4PB7yQuntUF1d2MRneHgYNTVTodmjo6OTq5aqq6uRTqcRCATIKqXR0VFceeWV53U9eaF0idNXXopv3XY9lnaM4o6D+7FwovDlZP3hPqw/3Ie+Gh9+8e51ePLmVfC7JX4dAMy5HG7edxR/+NJ2XH2EroKL2O14fukq7KxtQe481PEFQRAuOLLLmyC8Y7JmM15evgxvNi/GLXuO4trOo7DlcnDksvjE0y/i48++jGdXr8Qj116BN1sXS7jWKWonArh323b8/ps7UBGhOx0frazF00vXYszim53MCYIgGDGHd3l7K5qamlBdXY3nn38ea9euBQCk02m8+uqr+MpXvgIAWL9+PaxWK55//nncc889AIChoSEcPnwYX/3qV8/revJCSQAAdFRV4xs33YrL+vtw+6H9qIwUwmYahoL45Hdfwp/94FU8e80K/PT2dTjcUntJOkgV/gje+/w+vPeZfagJ0NDIpMWCV1qX45WWZUhZrTBY/SkIgiAIwkVC0mbDM8vW4I2mJbjp+CFs7jkBs67Dks/j9n0Hcfu+g+ioqsQPr70Cj29ej4iTh1Rf7Gj5PK5pP4E/fH0bbmg7QlZyA0B3STl+u3QtusoKX8wtcXkbLQiCcC5Eo1F0dHRMpru6urB//36UlpZiwYIF+OQnP4kHHngALS0taGlpwQMPPACXy4V7770XAOD1evHhD38Yn/70p1FWVobS0lJ85jOfwapVqyZ3fTtX5IWSMIWm4WDDAhyuqweWpvG+p/biir2F+FZ7Joe7XjqIu146iLbmavzstvUYf48HiWID8aqLCHMuj42HuvG+5/bixu3tsOZobHFXVRkOVDViV+MixG1vP8ZVEARBEIT5R8ThxBOXXY6XWlbAY4ng3je2oyJcWIHTPDKKL/7sV/ibX/0Wv9y4Do9dtQkHF9Rf9B/lKkJh/N6evfjg1jfROE41gzImE55dvQq9jkp0lVZe9GUhCIJwIdi9ezeuv/76yfSnPvUpAMAf//Ef4+GHH8ZnP/tZJBIJfPzjH0cgEMCmTZvw3HPPobh4KqT461//OiwWC+655x4kEgnceOONePjhh2E+zygbTdf1OfU5IBwOw+v14i9uuwd2a+Flhb6Yiyfm81RYrM4bYjZ2MxXvOt5bzWxKK6iAbSpL37GlunmYl6OJHhOd4CJ3Dh9donJ5BRW5PBioY8fYLFRwbXSIx+C/d8Vukv7FkQ382l4qGp0epV/F8nYuuGYrpoJ12fGCkFtFOIyrjp/Aps5OuNLUJmfR0Lu+FO1bqnD8uio89r13s/MGm2mDjC/nS3c0VRA6wF9SeTroeUJr6T06i7mAeSZN69Ln4e1ovM9H8+LKojiexLWHjuOmfcdw/YF2+GKKqKGmoa22DltbWnG8uhq6gRqlXkHLyuPm9x2K0nopctF7iBi0K1UI0TLAyyqjiD3rCT4o2MeV35pp2eSyXLgvqwgfrl/Qy2wOjNB2rfU7mI1J0UosWhEk6VAHb/dZRZS9oor391AbFbVMl9OysgZ4OZgb6X0nI/yloF1pW7rBJgG5EVVJUvm7i/c5c4KWcd7o9b5FOVGWXnvNkm52yCLnKEk/NcjF8rU2KsybrODTwE2rDpH0Gy9dRtJpDz9GU/KXNxD8VYV5vWUxZhPpp/oZ+SJFmNNg1io6Qes3ushANFwRS0eCFrq9lPZ1AKx/Zw36hqpIazbza58eUwEglc7gv376U4RCoXccJ38unJ5XF3zln2By8j453eQTSfT+zd/N2P0JU3X819fdA7ulIJAbW2og/q6MXxWlEWbiVARt+zormY2jivbbtOI7WU7ydpZrpvNgboyPt1opnb821NB55oC/lh1jM9N+Hevn+jvvWrePpJ/ev5Zf26cI9w7T/BmNZ7qXlpV51AZzPodVA3246uRxNI+PsmOGvR68uGo5nl+1HG8uaUbKygWNzyn04Zxs3vplzXSJzerQsXRwCDcdPoKbDrdhTU8fswk6XHizsRk7GpsRcbgM85+upHXp8HDfKRmibcumzNHZUb4SLK/Mwa4+7g/E65XNNOJ8rHco1ZlQ+pieNShvRal7eVM/MzkyVEPSjh7eJkzqLhJraB/MHePPK2kvPcZdG2U2uQO0v6j+gD3A7ym1SPGLItwX1YqVsjHYJMA6+NYfpXMu3kjMijB23mzQLxV/SlO0nJtX8TpY7KKbHD3Ts4LZuA/Q/MarmAmuXH+UpPc/tYykUyW8PFVRbqONpjLFSr1UcH8l10ufG7JFBoWuUHKEpoOtBkLjyuY55pjSN8rp2AkA6tuF/Dn4TpqB72QenSqMVCaNb/9qZnynmfabgPntO8kKJeEtGfN48MsN6/HUmtVYO9CFa46cwAJ/AABgzupo2uFH0w4/3vWVI7jdcxRba5dja+1yHCltgK4ZDB5zlPrxCdx06ChubGvD5qNdsOX4zhIJtxXHN1biCc9GBN1nPJDPqVeygiAIgiDMFjmTGfsbGrG/oRHVoSCu7G7Hxq4uOLKFp8bqUBj3bd2O+7ZuR8xmw+vLWvHCquV4aeUyTBTPH61KazaLy092Tr5Eqp8IGNr1LfKh7fI6vBhfjbxp/viFgiAIwrkhL5SEcyJjsWB762Jsb1mEhWN+rO/sxZpgH0oGplZ4LA4PY3F4GH987CX47UU4ULEI+8YacKS6AUeq6xByut/iCjOHNZNFc/cYlnUMoWn/BNZ19mLpIN9+EwDCTjvGm4vQs6IUvctKkbeYEDw8N+5DEAThfNAwM9vfSgCLIBQY9vrw88svx5Nr12JdTw9W9fWheXQU9lMvl9zpNN514DDedeAw8pqGAwsbsH9hAw431OPQgnqcrKqYMxt8VITCWNXXj5V9/bisrw8bT3bBkzQWjDxaW4N4sxXH11QhWF5YNZHfKy+TBEGYX8yU33T6WvMVeaEknB+ahp7KcvRUluP1v2pGxckoWl8ZQesrI6g7EITp1HKdslQUN/QfxA39BycP7fOV4mBLLQ431eFQYy2OLaiGv9gNmC9QF9J1FCVSaBryY2XXANb192J5xxAW94zBmv3dy0D7y314fu0yvLB2GXYubcTfDj19YfInCIIgCMJFT8pqxZvNzXizuRnPrV+Oa44dx00Hj+CGw0dQHi2ELpl0HWu7e7G2eyrML2G1oq2hFoca6idfMvWWlyJpu3D6leZcDpXhCJYPDGBlX/+pl0gDqAqHf+cxabMZ25sX44VVy/HiyuUYKC3F3wSfvGB5FARBEOYOc/aFUv3qYTgcheydHC3nBor2xaDGdVcyURqD7DnBv46E3DQuMh+kMfOVS6iYIADUuYIkvW+8idmor0i2HqYxtL56rgETiCmaOap+CrhmkjnK7ymjaPM4gjQ3aQNdhZvqjpH0b+OrmI1DiVMP/UMJQihBBxrw2ybAU5HAstEBLB/pR8v4MOw5GhTcEJxAw64J3L7r8ORvOU1DxO5E2O4s/NfhxESFHSG3E2GXEymLBTmTCVrMjLzJhDwAs67DPJSCSc/Dms2jOJ5EUSgFTzwJTzwBb+zUf6MJ2A1C11Ty0NBXUoq2mnrsX16DoRIvoGkoDcbxru1HEK+njpteRstvUfk4O2csS48ZnuDt06xoZsUSip6EwXu2fIbWt2OCtxHXMG33wWX85Vm6jt6D10rTN9XRGHAAeGLnJpLO1POvphblnkqW8bLxH6b92WunceA1l/G+0dbZQNKhY6XMRv2CYAkrGkX1/Evq5ZVUn2NbchGzyYzQ/qQbfGS1VtFzO+20PItsXONLZWCA35M6BviO0TI/kG9khxytpnonmYyBdpQSDl5cw3VU3hihZbHs2pMkbTKI9Tz0ZjO9dglve/ZRmp+sjxfoymVUc67tyEKSdg6xQ5B10g7j8nF9gXiQ1qVN0boz0tDylVCdilCK63M4O2h/TyzmY6xumyoLHWfXNbgg6NpZNVWm7TrCrODZ5IfDXvCPooN8TFF1YcY0rjeECPWvSo/w9uovon3FMqHoka3gLx/q3HRsbx+p59dWBvI9e1tI2rrQQHNN8Xlg42PT0/uoZpIlatBGlf6vzq+RlYrQCYAbG9tJ+sUY110xeeh4cNezhfl1j3cJ9l7ZgoXj41g23o9l4wOoitMycmYy2NDZgw2ddExMWK2IWJ2I2JwI2wr/9Vc7EHI5EXU4kDWZkDeZYIqakdc0aLoOs64jV56GOZ+HM52BJ5aAJ5yCN56EN56AJ5GAJ55AcSJlOL6rxKw2HKuow9GqehxcVjX5kmt9dzfWd3cjvpD6IukK6h/UV0/wc2boMYEx3j41K22P6SitNyO1BVXfzznKfcOifnpe/2X8RLGF1MZho23i1kZFkAbA069Tvz29kM/JJkU7xnlZkNkk9/lI2utQ/I4NfB7vaafasdnDvDxNeVrXthAtq8QCPp+tr6UaRHtONjIby5DiO5t4m8rUUe0dm52Wp89+dm2eUC/3r/PKGFBxiNb3yTz1KQHgRC31nXIZAy1Rxc8w1XNt1m2D1HdacjPVEzOb+Hja+TL1cVIlzAQuxe9JlfD8Na0cIOnug1TXtLiPXzvjVu6p1MBf9St6cqVKmwhzzS97meJfJfkrB087vYewgX6TfkZdzoprMVN+0+lrzVPm7AslYf4RtTuxq6EZuxqaoel5VEbDqDKPomEsgAVjE6jzB2HPKqKHug5fMg5f8oxBmWs9Txt5TcOIx4O+slL0lZViwFWGQW8p0pZCV8iUcodREARBEARhutE1E3q9Fej1VuDZxWvhzKRQG5lAhdWPhvEJNPgDqIhwIWVnJgNnJoPK+Bkv7rjO8LQRt9rQX1qKvpJS9JeUYshWhglX0eQObUnbLL0kFwRBEGYdeaEkXBB0zYSRYh96G9zYtaSwgkvL51E1HEPDxAQa/BOoCEfhSSTgiybgTicxndH1cZsVYYcTYacTAbcbAyUl6KksxUBJKdLWqWZviczft8GCIAjnhY6Z2URANioQhLdFwmrHydIaHGia2j7KmUpj4UAQCwJ+1AYC8CYShX/xOGz5s6/CPldymoaw04GI3YWww4nRYg/6SsrQV14Cv3vq5REAWMV3EgThUmCm/KbT15qnyAslYcbQTSYMl/gwXOLDrsVTS0IdYyaY8nkUpZPwJBOwF0ULy6/jCVhzOZjzOiwJwKTnYdJ15Ewm5IvzyJlMyJlMiDntCNhdCLmcCLudCLkcyFgt0MK0eavbiAqCIAiCIMxlEnYbTlRX40Q1DV9yDeqw57IoTifgScVh9SbgjSfgTqVg0nWY8nnYEjpMuo68piGvach4Cj5U2mpGyOVEyOYu+E4uB6J2O3STCdYQDcnSDbZlFwRBEITTzNlH7K6+KthshZhMeynXwrC10XjNyAq+vsVTSmPt42u4iKHVQpfpmoaU2OEurkFw9HIqQGIu5jG+iRC1WbholKRXFA+yYyI5esy2/UuZDSppbGvOymOx3UXUxrmIxrpmElwDpDNBdW1a60aYTc8eGovbupHG9B/u5noIFjv9euYr4Uu3g0kfAA0pOOGHE1kfj4fW4sp9KpoEWvCM9pAAtARgUqLXjBZkZ3w0f5qBbtWx7lpqoyztnniaOnkAEFhO00ZtuMRBf7NbaIaH9/LzVq+ju9Hlqni7Hz5M48D/vzXPMJuvvfFuko4P0zL/RXg9O8bTSOPzDx9dyGzMKdp/Rmv4EHP9lYdI+qUDK0laL+Zhh+U1QZIeh4/ZeI/Ta8cvp+WbDnN9nDe6qOYPMgbx2w5a37YA73OVjbRdB5O0Lw/2lbFjTEpZwcVbqKOfll94Pe3b+QQv3+WltI3sG+BaAcqwh1gf11WoXEz143oidCyMtPEg/8xCmj+blX8914apVlwiycflo+O07efttF8uubmLHXNo92KSTkYczMaUov2luYTe45FYDTsm3k77RnGrgTDtaqoVoIdczMScnLq2yUCbYUaQFUoXPSOdZbBbC/OhuYz7Jr59dMzwr+Vt0VZOx86Jy7k+hlkZRIqUcCvLCb4bavs1tK/nvQYh5gE6TlcsoTo7l3mpRggAhLLUpzmwo5nZpGsUP8hmoC3noeWVb1V0QmJ8DumIVZB0/UKuGzixjdrUXE39v84OPu5oyrzjLONaLel4MdKwIQIbBuFFupTPIeYYnWeyXmpjPT2fpQDLqeHbpNx23sbnxbSPdnKjl059J6roD8o9ZX7Ofb3wGtrWzOW8DRe76Hir+k6x7dxvd20O0vzyIkdkHz3urzb9ltk8+BL1nbQBOtb/KkS1ugDAvpjWXfehOmZjVSQeJ+p4+7zqeqp1unMXfUbIePl8W1xPfZM4iphNaRs9bvwa5bkoxPv/3hNUO1b1/QAg56Btwu7nNt5mWjbhBJ23g10G+qNpeh7dydueu0fxRa+kaS3Bj1lWQZ/TjvTUMhstpxzXzef64iVBku6JKL7SXl4H0UW0zDWbge80SOshG+f10pGl/r9J8Z1q7uRxsZ1vLiDpXIj7ZGr91pfTcbknqvR1AKYjtGxsy/gYlqTyYtCC3G8zJ6eubeZyXhceWaF0TsgenoIgCIIgCIIgCIIgCMJ5IS+UBEEQBEEQBEEQBEEQhPNizoa8CYIgCIIwfWg625X9gl1HEARBEARhPjNTftPpa81XZIWSIAiCIAiCIAiCIAiCcF7M2RVKxSc12C0FIa5wExc9yyp6xQ4nV+oyEppVySiile61VHA1MmJwjnGaH5M3xUxuaDlK0ttep8LDgTAVTgOAuKJpli/iryqri6nA3hIPF88+EKCCf+GjVBBOa+LCaMd6FfE5E7+2TREW7HuGCrlhKReE1PNUyC2c5KKWqKLlV+eNMJMSmyJq+BK9dkzJCgBkVTFlPxc5zJVQMUdthIvRWRL0HjLF9D1saBOvf9MYvc9kjJ83eISKlq6+9jhJp1bz7pnN03sYPVTBbDLlVMzv3165ndmUHqf9ZeJ6RRDQ4C15rJv2hbyb17epXBFLH+b1/UJqGf1BEeH2tPH71q6laWuAvwsvuWmIHpOiQq119SF2TP8hqsyZq+V1qceo8GGmmBdOTqdtJBqm13aUcVH21Lgijm+wC3O2OfmWJq5e3qb35alYpipoDgBBGx3D9Cwvz7F2KiSu5RQhTAcvB21CaeeJs4u55g0EqvMJel8NDVTodv+gwQYAir6vo4iLuWYDtMzb2+h5LFW8/s0p2h4jY1xQ06UI5i6s8jOb/tAZY77RDgEzgYhyX/T42vNwmAsNLNjC551oPe2TZhdv8+ih44PVoL2mK2mHS2ymY1xugG/+gRE6H+glXJT7yuV0Hjz4QitJ7wtwkd5YLR0vcgZjdImPbtKyxDvKbPaPU98pf5DOeVoLH1N6OhXHzUCcWltK58XQE8ox1D0EAOjKeBuLG/hOtfS8pSUxZlJip2PTxG+p8xxqMpjPlKpzjPFxPL6Q+hmOIT5vW2L03GkvraeR63jDsg0r/laUCw/nD9J2XX1zN0n3beTzYl7xReN7+aYSyUqa328//W5mU95GffDBdysiwnmDjT1O0v6Ud/Myzyr9yT7A73tbmvYFeGj5le9lhyB9iyKMPcHzZ7kzSNKOJG0APh/fiCK4j27kk6jnfdkcofWQ8fL71pWfskFatyYDUfbcGLXRDZZGxJYYCP6fgfck/609S/0BTwN/FonYaX3rGd7WTG0+ktbUDYL4fgWwKs8nFnUjIgApZW8X1ScDAC1E+2FJY5Ck2/q50HhRmlaCqZg/T1v8dPwZ3K88hNcYHKNsGpMa5nOCpmw0VVEbZDbBiTPE8rlW+YVHRLnPCVmhJAiCIAiCIAiCIAiCIJwXc3aFkiAIgiAI04isUBIEQRAEQTg3ZIXSOSErlARBEARBEARBEARBEITzYs6uUEpUAHlrIT5Ud/JY2KJaGiseMtA6MiuxmRYzj9fOKPGv0TiNj7WUcH0Bi5kGcSYneFzoa3tXkPSCDVTfZSLBdaEsbVQbQI1jB4ChERr3PXGonNlkPPQVp6p/kBnjJ3ZX0/KMBbjN0jKqORC6kdroL3NdqPTltO6YbgwAuGl5DnXxexqLKHH1iiaBbqDD4vRS/Rl9iAcuFxVR3YdA3uAd6yiNZdeV0OZ8jMe6WzNKbHOId7VkI72HnQMLSdoywDUT7M00pjvn4q+zi7roPRRvHmc2cUVb409rd5D0f+6/kR1jVepAN/GyWrSQasecCPJ4bccgLYusoicQWcQOQXiY9g2zk9933xEa050tpe0qaOL1b1I0k/QIr0uzogPkWBhlNkPjNH/FHtquolFFZwFAUQ89b7KMl2cuqdRlHa3/UCPPr62I3tN4H9eKsAfotTUerg+9ifafOm+QpAfDHnZMcwmt/2PtXOsor2ibOdxcIyEZoW1/qJ1qhVljXDugah3VkxvdWcVs9FZ6T067ovm1k+sjRVfQ/BnpTTV6Jki6fZyPhc4zhk/TW8s7XDBkl7eLn3iVCTlroUPnXNznsSxQNBQHuS+SqaL9wmTgO0HxnVJh2me1Mt7ITRY6JpvH+By3580lJF16BZ2/AnED32kf9SuyBholwUE6Rh/azbWYsspQac8p2iLDXJMKdXRMyfv5PS0uH6N5uZ3mt/S3PC+BqxWxkDF+7VwRrZfQCR+zSYTpb/FV9Lxamo+lJsXvNffze3IWU5uEgZ6LY4S2EUUCEqYI94tMynRgDfLxNtxM7+FAbwNJu3oN9CeXKjqGBm3Ed0IZuLZw3UX/cloP/7vhNZL+3s7r2TH2ID1vysTLqr6ZziH9E3wOcffR49JFNB1cwgfe/CB9NrIYuOCBg9TnTpXTdjVk4v4LFM0kc4g7Ear+aH5RktkERqgfYfXRdpWO8HZf2knvM17B20g2QX0jszLuhZoNHn8V7aB4N3+udCvudN7M6zLRQs9TWUI1qMZC/LwLymj9DxyuZjY5uzIeubluUT5PyyvSRge1oghvI64rA/S8r3OfMbycXsvqoH2wdCv3Rf2rFW3WLC+rRh+9dvcIf/4rGZ46jzU7886F7PJ2bsgKJUEQBEEQBEEQBEEQBOG8kBdKgiAIgiAIgiAIgiAIwnkxZ0PeBEEQBEGYRnSt8G8mriMIgiAIgjCfmSm/6fS15imyQkkQBEEQBEEQBEEQBEE4L+bsCqWsR4fJVhDisgS42Fu6h4oY6o1cADKriCVnLQbCkgreQ7RIIk0GeTMrwmgeLoxmmqAihn1BKnKWDXGhOWuzIhqY4ffdXEEV4Ya7aphN2qumaX7L6oPsmNAJmj+7KtwJ4GAXFT60KgJ25o1K/gEs8lKhuREbF6Ob6KcZztt5PW1aeZykt+9cRtKZSl4HmV4q3mniupIIhKnNvc07mM2jyStIuqSSCiPHkvzEtlLaHpPdXOwXcaX7KeWZLldEOQFkVHFnH2/3eT9t94EkV2FMBuh5vj1xA0lbDESPVTFyzaA7+ZNU6VI36HO6iZ4op9xSRT0V6QOA2E6l/6zibW2hlx43+CoVBG+5oZsd0x6gYs8pP++XWQ+9B6eVt7WkjZZ5ZIK2K6uBYGW0iZ7XHDEoc+WVf1gR2ISNl282Q9vV8pY+ZnOkg/ZlE997APkUzXNPLxUJtZVwgc32Y1SEO+/m+dMUofFkiPcfc5TaqG0v18yvnVYUXzOt3MbtoIqvxXZ64wNLeF+xKG04l+f1dGSYCmgurJhgNsHUlEh4bpZEuWds+9t5LCw530n7AM1aqAC7n38ztHXSsSnVbFBZUTqG5C3cRu0F5XupTaCFi7TqFnrenJfPcfZxajM8Qf0DU4C7rallyiYdaT7e1tXQPhk/XsbPU0rvKqVo0zoa6dwPANkjdExON/HB9OQJOhfpXjoAaFfzAWFBGZ3Pxhzch0j10Pk27+D1tGLdSZI+/HozSSer+Rht7aSTctZAkzkRoj/es2Ins/lFYjM9bw31K1MJ3kZyFcq82MEvrs4POWWOTlTyctBVcecS3vacI/S80aiBgvUEPc93/VSE22bkOyn9R+OXxnhc9Z24jeoP5JT6di/k7dP0Om2f4fV8E4y60iBJx56hwsiVdwyyYzrGqe9kGuMZVp89igx8p6id9tXsGK1vR4CXZ0gZs6xhZgKYqE2uj9alZvA8kFfGjQXLh5lNr7L5i5HvpKdoRY13llKDMl4Hg4eUTWWKeBs2K25vPmjwHKn4kXmlWmLLeB3YcjS/keV8PLI56XFFdnoPEyt5XjQrbei62oABdA1Qv7Kyigvh64kp4XZT7uzP8dPOTPlNp681T5EVSoIgCIIgCIIgCIIgCMJ5MWdXKAmCIAiCMH3M1Pa383nrW0EQBEEQBGDm/KbT15qvyAolQRAEQRAEQRAEQRAE4byYsyuUtKI0TPbCqzpvNdfCiBz10R+yPM7W4aXBrbk8f3+WUXSWUptokGo+yuNCW+tGSFo3eKMY8tB43YkOJRifnxYOG41RzRhoKJ3soXG2TrNBvLadxq26euh5/MU8Fl+9UjrOY9sdw9QqlVbi2A3KYcRO47ddVh47HPTS3/Ixfu1db1DNpPxCWrdlxVxTJxCh2gtFi3hsbqTXQ9I/3nsVszErIbuhKNWg0EM8vxmlWv7kyleZzdPjK+l5kzR2vLSE31M8Q68VjnN9gWQLrYh8kNusXdRL0ideaiTpkqvH2DF9IzQOvKQkymwsJtr2NDsXC8g6VX0cWsDj3UpfAeBWwr6zw1zboO8orZdEC40D39e1gB2zYuEASXvLB5jNm0daaf5CBv1nnNaLtYa2Tz1s8O7eqehoGOiq2Suo5oRL0SBI71QE0wDElfj3o6NVzEbz0D63rIprBbT76XG5MJ0uSp1cZ8271E/SXUGuU2LuU+qpmo9h9voYSVsVHaNFxfQ6AHDsDSp4ZzKQv4h4aRk3LlY03oJUOwIA9GpanqYQnzZLGoMk3dPJy9x79RlCD6kMwOXaLjyioXTRk/dkkbMV+pSjjgt8ZA8p45eBnpdJnZMNfCdVZ8l/jaJjFOHHLFg4Ss/LlJiAkJfOV7ZjdI7O2XnjsjnoTaQMNJSGO2jfLuYmTM/P20HTQQ8duwBAnV3zCT4+FCkSNMm0YmOws8+ondaT2859p1gJvbo5wm/q6IuLSTqxmJaV22OgRxem1za38rHe1kXL4vFtVzAbk+I7JRXdJUuItxFVZuX9N77ObJ4cvoykowkqiOMr575TLE3H/mSMz7ch6mbCZKBR07q0n6RHn6qjx9wQZMf4h+k8bS/l5WlR/KC8g2vFZFxK/So6QYlO2lcAwJOhPphl0OC+D1E9pMhyet5gO9VGBIDGFuoz+KoMdFf3L6LnDfD+Yx+l95SuV9q5gV+Uc9GysQV5u9er6HnsyvOVYyvPywRtVuhU9H0AAF7FF6kbZSZdo3SsMSn5Kyri7dO7imqm9fq5H+zqomUR49WC/ELan82K77TEx32nwRfpiRwuPh6lfXTMKltC8xub8LFjUrW07dkM9JBtzVT3a+I4v2/LTVPllUplgDZmcmERDaVzQlYoCYIgCIIgCIIgCIIgCOfFnF2hJAiCIAjCNDJTWgDz+CubIAiCIAgCgJnzm05da74iK5QEQRAEQRAEQRAEQRCE80JeKAmCIAiCIAiCIAiCIAjnxZwNeavzheGwF7I3dJgLnKbLqNiXu5e/G4stpEJ965q6mc2BYSoal45TJdeq3VwIcfx/uUk6ayBYGRmmYtTVzVQIbfQkF6tN56hgmdPBr53IU7G0VGuG2Zj9VLgtsVgRy0zx/HpbgiS9xDPCbPa4GugPYwaqtwr+MVoOfq71hmZF5PxkrJrZ6C1U8O8vF1KR638/cQM75ra1+0j6t4fWMpu71u8h6QMRrnIXy9DyHBuhAotmH6+nXJx2rR++voXbuOjaxjXLOkl63wkqMgwAukMRvTZ4JWwep9d2hHihD1ZT8cboIircl5jgYs+q8H06y4ePYFgRLE9yEb5cEb2WpYi2z5JqLu4YTFBBcKuBTdKriKPnDRqbQuc2KtStGwi1WpXbzHDdS9gbqIi0x0GFEcdqDY6x0LpsXMP7XO822ucCNbTsFlzNBSE3uMdJ+pXjS5mNlqNlc9TPBcs1RRM0r9Tb8ACtEwAYj9IGedVGrp74JpR27eei8fHIW4vNHo3ySnAEaX+yr5tgNsFDdNw9aKblW9PCBStHO+gx+RKuYhxJ0bmmeoHBeUJTY6GRaPCMIKLcFz3lpRE47IWxMLKX99FUOa0c70l+jlAznfOWNfczm469tO/oUdoHKrdS0VYAGP1DKvacMxij8wPUryhaRjfTiB/jc1NW2cDE4uJ+UVan80NwhYG49xgd7INL6RhtSvIJ17yMbk6xroSP4/udtKxMI3wjD5XEKPUzE5qb2dQvpGP9UIRvKhBfRsviL1teJulvHr6JHXPzpoMk/dKeVdzmyv0kvS/YwGziihB2bpDWf7aUb9phitG6/Pnz1zCbjKKn3HpZH0m3H+V+XN5B61s38fq3j9FrOya4zXAdnXtCS2gb1v3U5wUAU5raZLN8/E8qm6eYE7ytZYuUe/DQuchVxAXW43Gan1wtF+oPl9B2r/oHBtr5GH+J+umjBlOazaLct4FbmWuiefY5aTq4gF/crAiYV24cZzaBl6mgdqyetsWim/j4dGUR3Yxm++FWZqMpTbZ/fw2zsSm+U6aY1lu4hxdEIuQj6cuvOc5sdmIhzcuYgWB5iI7DpjAtv/4wf25z+pUNYjZz0XDTXtqOOizUqfUu45se6cpYrT63A0A2Qe/Bu5ifJzAxNW6k02f366cdEeU+J2SFkiAIgiAIgiAIgiAIgnBezNkVSoIgCIIgTCOyQkkQBEEQBOHckBVK54SsUBIEQRAEQRAEQRAEQRDOizm7Qmkg6IXdVogzN3rrVUblceDfwGMzLQEa1Htk22Jmk6+kwa7WAL3a6OU8RvWyokGSHozzeNiYIqszcYjGtluauQZMapQGhpu8XJunzEfj9ccN4rVt1TT+VVM0CXJu/go0vt9H0ttq+XkdPhrb7BhT9JyaeX7NyuvWXII3uZM9NBbbVWagj9NH9QP+LUnj/uvKguyY37atIWndmuc22zaQdMYgxtfVTduRdQUth/wIjVkGAE2J1/d28fMGltK2tq+d6nmV1/MY74kwLQfNbKADEaT6DKYstxnvoNoajrhSl2U8Ttk1RPNrr+BaMhkbLatMlGtFmNRmElZivltjUMnX0bj/UieP8S7zUd2aI32KcJFB/eeW0fOaDMKzF3iCJN01zvXP4nE6TqgaSrkMH8Xyfnrf7Qk+1uj1imZWhmZwKMy1hHoG6FjD9BAAeKsiJG2kA+ew0PpNKZpZmSN8jHD6aVt7vaaZ2bAxwMHrRdXrMidpungV10fy95TQH7q5fszKy7tJ+tjuRpIOebmeU86r9F2DusyM0jE2UMlMoI1M1a9ajzOFNkPb387YFrsCY9zvge2U7+Q0aGZV2+mYN3wNH3fs47SN977MNWly1Ypm2QS92Mh1PnbMIg/1nYYMtNBSKXqezF5qk13CNWBMw/QesiV8vi0qpX5FbJRrEmXr6ORk71XOa+A7mXfS8+xfsIjZaIrOokuRWQq38vxC0fhRtYUAYKhDGesredmYu+mY9s0E9Z3KKulcAAAv7aOaSXneRPDqS2tIOlnBy8bbQdP6Gjqn2Ia4f5BTfCffMT7X+1fT8fb4Ydo+XQupnwwAkRA9xsh3cvppuzdluE1U0YVxR6lNopLXUxGVeEK6mtd3zkGvrUUN9LqUvmEKK77ecl5WiXpa5l43byOlZXQ+7e6iPrlu5eUQWaXo7hgM+jUlYZKOj5Qwm6zqIyoaSkaar1qIHtMT59phmiLVaFJueyxA9bwAYKyX5s9k0C2ttbSMcwa+k82q6NZmqM9jO8D9DNcoPWZ7g8E4EqdtS3fxMtcUjSGL0iS0dbxvBDsVX+4k75eNVw2Q9MCbdSQdLeHPQbkS6tuZDOrSpPj/IS6hC8fgVPlpGQN/8QIzU37T6WvNV2SFkiAIgiAIgiAIgiAIgnBeyAslQRAEQRAEQRAEQRAE4byQF0qCIAiCIAiCIAiCIAjCeTFnNZTcjhTs9kKsZLicxySHTEpMqpvr7mQyNE41W2oQV+9JKDZKHHOKx5IeHKTx2nYn1w7K+Wh8sXOE5jcxROO5AaC4n6bDrbx6gmM+knbVc72ZeITed9niEDV4nmuf+NfQsnH38HeNMdDzmktosKc2zstKU4pcM9DdUWOkMyd4bHNeicU1j9GyGXdS/SkAMEeUezCImc8W0d9a64eZTaeLauaYTTQv2RIa+1yAxjH7N3OLTQtOkvT2DqrxNTbO9SVcPfS+U6X8npKtSrB40ECbR4mJV+/AGjbQiVGqJd3FtcOyblo2vpowswmN0va3oGGMpMe2V7FjNKWtjeZ5Gw5YaRvQ0vQezF5eT7msMrb08zjwkzW0XetpA22DuKK9FqBtRnfzuO+yhiBJj4/x+raElHtQNBTS4Pm1xugx2WJ+7aCfVqaRzlJM0TGChdbBgvWKEAiA3p4Kkl5RyftTME3rqdLB28jBA1Q/IOOj9xA6yvWR9Bo6Dpd4+JzQdmQhSee99LyfaXyZHfPl9lvoDwHenyyKBlm5m4/L/WVT7SiX5uOgIEwHVmcaNnuhryYr+FgV0BT9Djf3XzKK35My0MexKBqPqu5eLsX9l+O9VCDD7OT9IF9K+2TRkJK3AT7meRSNwokV3GfMDNM5w9yYZDa5EO3bllaqN1Lya+7jjGyix6i6QQAQXkRtkuW0rGxjPL+Km4FkJfdf1TnOeZRrs6TKaN05Rum1gi7ui1ojNH+6wafnjIeet75xjNn0u6kmjabcVNrAJ1cZup6Pt6ubukj60NFGko4a6GN5Ouk9JQ10IoMraHu0TPA2rPpOacXXswXZIUgrU3v+BM+fSfFFLXVcDymjPDf4FlGdzfQrXKPIrtxnKM+vHbbRdqPqDeUNNMn0rNL2enhZDdTReVptrwBgidH8xSZ89JgiPvY4mqjuV2yYPzPYA6oOIz1PErwvW6OKfpuHXzs1RuvAZDCVJ7N0jNKVonFewfVR/Sdp3TXXDDGbYIpeu8rJ9c86di+g+VV8Z/sh7jtn6mj9On18bOw+SDWT8sp5P938Ajvmq4ffRdKWCG8jVsVVchbzdj9RMVVX6fQ8Fhm6yJmzL5QEQRAEQZhGZmr7W/H5BEEQBEGY78yU33T6WvMUCXkTBEEQBEEQBEEQBEEQzgtZoSQIgiAIlwAztf3tfN76VhAEQRAEAZg5v+n0teYrskJJEARBEARBEARBEARBOC/m7AqldM4MLVcQD3QM8Gymm6ggZNF2LiwYvIwKjbk6+Xli1VTMrfQoFQ3MbDYQjVTE6JJBLoRYVknF0tI6FTA2V3PhMb2e5lcbNxDuS1LRuFIXP086Q+8zmqKihuYyLgCJPL2253I/M1nspAKViSwVtTvRTwU3AcA2Tq91xQKuWLm1j4pR600GItcBKnKXUzS4yxxcRC65mN7TYg8Xjdx/lIr/dvrLmA0Tbh5SREHLeX61sCIaX8UFgtN5g3o48xwGIuJxpWx8B3ibzg3R+o4uZCbQTfTc1607QtIv97TyY9I0vyaHgUhojOYnvY8Ld5vKFTFPFxUoHPBWsmNsE4pIaJgLdSaU/mMroW2i1quI0wPoO04FwN1LgswmGKT90BwzeA+vCKjmVBFug68O44roupEwa7qajj+5JLXRbfzEGSstB4vLQIxc6U8blp1kNqNJKt44GKZ12TNUzo4xK0K9bQO1zKa6nNaDx8L7rl5Fz+N20HRMNxgbJ+h4FLVx8V6LMu5mB+m88aVjt7JjzMpmAzVL+DjSN0zFR0cPVTCbM4dqc3YWP0PN4y9gwtnJ5cyTc5a7lwsPR5V5sfIVbjN2OW0k3naD89TR/lW5nyr5Dl3PG5qm+E66wYYRrmpFpVWnk32mlouIhxcqvtMI98nMyjBT5ObjzoQyxyWStO9bKnl+Teo0eC3fZID5Tjl6noFuPpY6R2mZb1zcxWx2dTbR8zbzDRjMfjonZ120XopcigIzgGSr4jv5uD94/GADSfePckFoPUPr2zamir1zH8ISUua4Gp6/TJ7ekyoarlt424s003TFLu7bZwfotUOL+HnUa23Y3E7S204qFwKgKRvP6A6DeopSG/sO/kyTq6JtosFNfae2Er5ZhdOviDKHuP8SWUh/yys+bYWPtl8ACLbRa+VX8I0oEKD9UBW9LhxIkzm3stkPLyrERuhzm3OYnzdRr2zko2yckedDBFKqP+XmbUTtT8tX9zCb4QT17cYC1Jca7zfoKyX0Wh29fHOaEuW50mvlz3+pGnoeq7LxQcpgIxf1OS1pN9hgqZb2Q0sfPc9XD97Gz6v4tJ7lBmLkg8ozwl4fsymOT9VLSt0sZqYQv+msyAolQRAEQRAEQRAEQRAE4bw47xdKAwMD+OAHP4iysjK4XC6sWbMGe/bsmfy7ruu4//77UVtbC6fTiS1btqCtrW1aMy0IgiAIwnmiz+A/gSC+kyAIgiDMM2bSb5rHvtN5vVAKBAK46qqrYLVa8fTTT+PIkSP413/9V/h8vkmbr371q/ja176GBx98ELt27UJ1dTVuvvlmRCKR331iQRAEQRCEixDxnQRBEARBuFg5Lw2lr3zlK2hoaMD3vve9yd8aGxsn/1/XdXzjG9/A5z//edx9990AgO9///uoqqrCj370I3z0ox8952uVuRJw2AtxvP3VPNh1XU0fSZ80LWI2ziIa85kq5xolrioa9xtQtDl0ncdrunposXk3jjOb5AtUiyexiebF1KWIAAFAC3UcdSsPHk4r+jMDPTz2Xn3DuXwJjfE9UtzIDllYT+8hmeNNI5KhMbOD+2pI2rOUawdACel+o38xM3E5qSZCo2eC2RwJ1ZO0qg0RM9A2cFho7PDh8Rpms6yVtqPjBxYwm8vXnyDpnflGkraM8mtblaJI+Xh57u2k5zEpsc5GkcK5OD1PcJWBjlGavicuPsnPFF5GG8nW7SupQQ3XqfCW0b4SCvEYf3cZ1YpKe/l950O0vN7opm3CbCRRpIR95wzi321Kfzcfo32sz8sPypfSMo8d8/ETF9OyWrRkkJmc6KX6YarOkrmWx7rXFNP+PjLAY+aRo3XnHKTpRD2vW7OH1l1+nMfMF9VSTYSuCNcOm+jzkbRupeXgq+QPukU2eu2hgIfZDPtpzPzQqI/ZOItpXUYjtO40g3HZqUgbRQ36XEMljeEfSdI2UlsWZMf056jeQf+4j9nUVNLj/KN8XP6Tdz83lbdkHv/2IjMRLlJm0nfyueNwnNLAmKjlc9OKBQMkPbqrjtmYiqiGSryKjyGopRpEY7oyvub53FTcSfut+Squa2f7NfXBRq+j53F28HvKLqPja97OP/MmFVmzdCfX9zMrLlfTCjrW9/l4WZU1UX8lleXjTlTxncI76HhrXcXnh6wyhKh6SQBgcdN6avBxjZLeAJ2bPF20bKI1vDztVnreoyN8bmpcMUTSQ7u4f9V6ZTdJH9Sp7pJjmPvkjiDNX7CU2xxrp/6g7uZtTcWUoHPy2AZ+XlOKts+SY9wH919Gbfa/uoQa1PG82Cto/aYC3BfRKumcFy7hjpApQLVt9p6gbcJqIMuZVao36zLwLIvpvF18mF4naKDNlC5TNGoPc11Di4fWZdWqUWYz2EE7pjlG85dt4L5ohVfRJOvlmkRQtHaKqKuPiIG2aN5H/UHLmIGWUD2ty84Q952SXVQzyaT4TtYa3t/ddnqffn8RswmM0fO+OWQwhnlpO8oq/rY6xgGAe0Ttc3wMK6sJknQsScc0byUfy8fyNH/jo9wfLKmhD0upYR+zufe9U85SNJnHv77JTIQ5wHmtUPr1r3+NDRs24P3vfz8qKyuxdu1aPPTQQ5N/7+rqwvDwMG655ZbJ3+x2O6677jps27bN8JypVArhcJj8EwRBEARhejm9/e1M/BOmEN9JEARBEOYfM+k3zWff6bxeKHV2duLb3/42Wlpa8Oyzz+JjH/sYPvGJT+AHP/gBAGB4eBgAUFVFv2ZUVVVN/k3lS1/6Erxe7+S/hoYGQztBEARBEIT5hvhOgiAIgiBcrJzXC6V8Po9169bhgQcewNq1a/HRj34UH/nIR/Dtb3+b2GmassW3rrPfTvO5z30OoVBo8l9fX5+hnSAIgiAI7wARlpwVxHcSBEEQhHnITPpN89h3Oq8XSjU1NVi+fDn5bdmyZejt7QUAVFcXYrXVL2qjo6Psy9tp7HY7PB4P+ScIgiAIgnAxIL6TIAiCIAgXK+clyn3VVVehvb2d/Hb8+HEsXFhQN2tqakJ1dTWef/55rF27FgCQTqfx6quv4itf+cp5ZSyctCOlnxJEM3hjt+8YFeHWGrmNQxGJy9dyNTKbItyc9FFhtEXlfnbMsIsKoxVZUtxG0ekrcVIBy5p1XJxuJEHPmxng1ZNSRLm9J5kJgkvpffpTSjkYCFb2d1TS/C3mQuPdvdSx1RTBvWySizua+qn44PK1Pcym7TgVwj6R4+85dQu9VuU1IyTdOUDzDwCJqCKMXM2F8E5MUEHAjI8LKu7sa6Q/pKjyoUabEACg/ioqfHpipILZaHnla3SMCgCaYvzLtC2jiDS3ct2M8DAV84vVMxPARMtTU27bZOF95fKybpJ+uWsVs/GUU2G+4B4uTpytoNc22+jFrfVchNGkDgLHuGBhapyKhKdrFNHIEl7/qTQtc91A1BLFtIJVAW4AKFEEqsNRmheLiZdnzwAtG7OX90tLhLbhrKJ7eXkLHwB29lO1Sd3Jr505SseaaAm/tm6nx6mi8ZE+/gCbDNP2ySUtgayTXmvRSi5y3hf2kbTNSUViTW7eRqJOOv4UFyeZTX8fLXO9nLYRu4l3Zns/vYvUggyzGQnSsnAsjjKbb7Vvmfz/dDoD4Almc6GZqRj9+awDcCGYSd8pkrQjfcp3MqqH9sM0NE5r5vNM0T467kQb+IlsFtp3EsoGB3VVAXbMWBEdtyutvC8Nr6J+j9NFN4OovoL7JqMxel5bDxc9TiouQslRPtf7V9EJYELxnXIG2uSBo1Sw2LMkyPPXSYV7NZ8iPJzgI6Wzh/7WvImPk91tVAi7O8sFgtVB2HETFREP9vJjtLBSfnV8vO0eU+7JYA452EXbmlkRxjbx6of3RuobBwe4D6EpU5o5QuvNYuA7mZVbyC03EEIfpPN2eKGBQ6DM5VpWuW+DzXQ2VlK/d2fHMmbjrqLzVXafl9nEFddDt9M2nGvgBZpUfD3HId6Is6O0kcQU7XmtnM+lSNF+mjcSBPfQslAFuAHAVkM3cklEaP6MfKfxbirCbfEZ+MqKRnSaujxYuaKLHXOgiz6LqL4KALgP0r6RNOhy6jNWXhGNN3fzTZlSyiY33MMFsk56nxUGz5GDii+iuem4rBfxewq6aP1bvfyZdqKLlnm+ip6nxMzH06IeZR5p5HUZGKcVY1nC29p/Hrp+8v8LvtPPmc2FZCa1jeaz73ReK5T++q//Gtu3b8cDDzyAjo4O/OhHP8J3vvMd/Pmf/zmAwnLtT37yk3jggQfwxBNP4PDhw/jQhz4El8uFe++994LcgCAIgiAIwlxFfCdBEARBEKaTxsZGaJrG/p32LT70oQ+xv23evPmC5OW8Viht3LgRTzzxBD73uc/hH//xH9HU1IRvfOMbuO+++yZtPvvZzyKRSODjH/84AoEANm3ahOeeew7FxcVvcWZBEARBEC4oMxWjP4+/sl0IxHcSBEEQhHnITGobned1du3ahVxuanXY4cOHcfPNN+P973//5G/vete78L3vfW8ybbPxaKLp4LxeKAHAHXfcgTvuuON3/l3TNNx///24//7730m+BEEQBEEQLgrEdxIEQRAEYbqoqKBhpF/+8pexePFiXHfddZO/2e32SZ3GC8l5v1CaKUqcCTjshXjgWIpHk9YtHiPpvkEeyJpsoTGdepIH+cZS9E2daZjG7/ZYaHw8AGjdNIb2RDmPh7UpWiKxgI+kW689wY6xm2n886EWJ7PRE7TKslfyOHBLF/2iOWinsdi2CI83Tiv6LQMTPH67qJxqGThtNL/pl2iMLQCkr6RaIkfbFjAba5rmJ2Pi+gdmxaZ7nNaLzUBTJZOldZlPGii6KEVRU811HxwWep/DURqjXNnA9VK6ArQ9eot5PQVzVJ/BOq7UbRGPN1Y1HFxb+dfrK+44TtLbOpqZjTlIr5VuoOWnR3lZbR1ZTNJajrejoSHaBoxehNctpBoYOUVLamiEtyNN0VkyL+Zx1i1lVO+sbzsVAtjQ2suOeeMA1TLIW/jnAaeTxpNnhvl4FHLRMcDWRW+8cROPde9TtA3iLl5YJcW0z+XyNEr5ZITrS9gdNGbe5YkzG189bY82A+2g9g5FfEsZK42+pBRfRvU5Qgnel22HaVl1HK9lNo5qet/uN+lYGFrM29571+0k6cdPrmU2ulLmnlJ6nZOjvDw9K6hOmWk/145KNNExIpHlOhUlvqlrpVIG4iEzgaxQuujxupJwnNJWCaS5b+JtoXOcv9/HbEKKDqOW5uoISWU+dfTTOWXQwn0I50k6hgxU8vHBEaJ9W/PTeXLprdx3cprofHtkGT8v4tT/C97AxzxbB70H/yidX90h3rBTynTlH+Nzsk3Rx3EovpPjKe7rTdz4/7f351F2XeWdN/6cO9+qulW35nmUSvMs2bLlGbDAEP/ikIFAmsCb5P2RZZJuh5WQgSRoscB+gY5fvw0vpOlfmjah3bgzEEgwARljYVmWLcuax5JU8zzdue58fn/IkvzdzwFLtqpUZX0/a2nZ++rZZ897P+foPN+DeQYO6X3Sa0id2C59brsN3cXRiTCkrZDeiwo5Q1vQwXc2CbdG1W8BN/bxRMzQH+3C/VdEZMDw7QIOei6ZAo5vYALnZzakx8n0nSqf1edty2/0QfrwmQ5l453BspIdhm8S07dV+0Y68RoOupuRQVwvgYA+48LLcO3mDX8gOqLPJtuHazm5UhfeUofXje7Bm9TV6/QXJA8d6IZ00cG99pTi3PKO6nU5V4K/lZ3HNtXejfd6IiLDrjCks2W68FA5+jhmX52P6rPe1IkMhPXaCLXjuqxx6/4cOo16s64ZY05o115cW1GHM57UfVVxCNs5dkJrx1rNRv2ew3k0s0bP+/ffdhDS/3p6k66fcQR4q7F/h0f0vbJ/I9pUvKz3uehK7Iy8w71HsPJKm1w3wne6AW8oxWLod/r9fvH7HUT83kA2m5Vvf/vb8qlPfQq+Dvv8889LXV2dhMNhueeee+QLX/iC1NXpufN2uSYNJUIIIYQQQgghhBByfWltbZWKiorLfx577LE3zfMv//IvEolE5OMf//jl3x544AH5n//zf8pzzz0nf/M3fyMHDhyQd73rXZLJ6Af1b5dF+4YSIYQQQgghhBBCyM3A4OCglJdfeePwzd5OEhH5u7/7O3nggQekqenK26wf+tCHLv//unXrZNu2bdLe3i4/+MEP5IMf/OB1rTMfKBFCCCE3AQv1+dul/OlbQgghhBCRhfObLpUlIlJeXg4PlN6M/v5+efbZZ+Wf//mff6FdY2OjtLe3S0+PDh1/uyzaB0rpglukcLF6vqiOJZ58DeP/KtdFlE2iJ4w2K7SNGe9u1WJ8pntYPxXMVWPMdHvTlLLxtqBNPIfX+e65TSpP+CgOh+s2B32kabQp9ul4fY8RguoawZhZyyF+t6wBdYCSc7rd5m/t5aiXcmK5g/bNGOofFEMOhccx8tJbpfVxrPOoBbFsNWrSnLqAejkiImW1GJ9v7dfaN4mNqB1UcIgCnUhiH89FMbbZG9LaAbk4DkI0ozUIyitQ2yaWx74qCevxn0vjWEaX63jjfX2odSRuh53QWFKecbxu3Wodtz4Zx/7Ll+rrbujEWPsTwUZlM3oOY9eLPrxOoEa3Oz+E4+9u1jY9fVjWf3rfDyH993+/U+WR23H8rTEdX56KGnHfdQ4x3HM4vukGXP/Zoh7/u+txQ9/94hZlMxXG8fVNG1oRLVo7zNS7KEa0jspMLY6l5XBa2l5cq55ZvG6uCtsoIjIVwbVSWxlXNjEf1sfUSxLRfV67E+fj7LDWP/jn47fgD0FdP8vQk4hPYD/4HfaehLHHFpr1dc19WWx9ZiWCV+ZWJqP/npDrQS7vFpf74lr1z+h1nd4fhnRgi9ZYs0/hWeReo3UCU+Nok27EdREY1HtpugbrU9umNQu9hiZNIot+xw9PblR5ag4amk93az/DN4V7p++89nFMDb2SIdzzrILuT5ehRycJfd1sEvuiLYzt7luj/ThrCPf+XNjhHI/gPlKs0WdT4Axep3k97qUDZ7RYq7sB98HKPXosp7Zh2tT3ExGZnMP9tRjB63jDqBMiIiJx3EvTGX1dXyXWL5PD88JVrcM58insh9nV+kyeOt+OPziJghhbd2AEr1O6MaKyzETxzMuX6bFc1j0C6Z7SemWTP4U+dsGP13HVaX/A04/zMdemz6+RHtRMeviDP4b0P/y/96o82fsMvaERfTuZm8WyC/V6XbrmsJNThiufK+rr3t10DtL7nluvbFKVOPcCxm1aok3XxW3UxZ7Ra3msEcfSdvCdTCkzv+EGpat1nqyhFVderf2ivN/QNmvW/krB6PPiQ7jXFPr1fdozBw3fs0T3TTGAvxVGjTVX4+CLGvdtiXbd7sCksQ4dtrlMyZV2Z3QxRES++c1vSl1dnXzgAx/4hXbT09MyODgojY363uztQg0lQggh5GbAXsA/hBBCCCFLmYX0m96C71QsFuWb3/ymfOxjHxOP58oD2EQiIX/8x38sL730kvT19cnzzz8vDz74oNTU1Miv/MqvXHtBb8KifUOJEEIIIYQQQgghhCDPPvusDAwMyO/8zu/A7263W44dOybf+ta3JBKJSGNjo9x3333y9NNPSyik34p9u/CBEiGEEHIzsFBvD/ENJUIIIYQsdRbyreu3UM7OnTvFtnXGYDAoP/rRj65Dpa4OhrwRQgghhBBCCCGEkGti0b6hlMr6pGBdFOIKbZhRfz81HIZ0ZlyrobsNwbKGoBYAnMlWQLqyBtXTYl4UYBYRcY+j6Nmm8kFl86+Ht0LaMrQSa7oiui5dYUiHXgkqm1g3CqO1rB9VNj0XDLEtQ5w2VK4FjauCKMyZOadfhzPFk4fLsO+8CS00W70WlfCyBT3lkqNhSOcdxB3tNhRZ7I+hsFx1oxbGnhnE6wb1UEoxhfWZyFQom/q6CKSTbrxQf6RK5XEZQpJ2TrcpNWnM2SoUOcwOokifiBZdtMJafNLVj/XLVTgILlfjhGyvwXHqP9YkJg1rUQh9eFJ36OlpFMsvpPV4b11/AdInf4Yi4nXtWgB2oNpQORzWa8NrCB3/P6ffA2lrpR6D25t7Ib0vtkLZ+ELYx6bAqogWULeMpeDUnxcaUVja8jn804TxU6YG13JztZ73HkN1f3xCi3t6AjjXQkEt7pg8HYZ0rhKv6y3TArC2oeU45SAAWTQEy60pLRruqcB5PvEKtqFqVotGxtqx0/NevR+VhLCdcwlcY40OAvt9AZxrnpBut3sK14KT6Go+d2Ut5PM35hUefuXtnU8y45e8XNwvA1sdxLQHjY9TjOj1V2zDOd5ZpsX1BwZw7XjrcG2lvXqf9I7iPr4t3K9sfvzyZki7jOVW0q3bNLsC21S1VwsPz642BMG36A9PjJxBceJCKV7H73DeVgZx74+f0v1ZMLpiqBz9DF9c71WBTRFIZ/L6LLWMMcgV9XWSXdiGwQjuycFW3Z/pXvT/8gG9oN2GZnA8q33G8gbDn/ZgR4xMh1Uezxy2wXYQ5XaNG8LINXgeuPu0b5JvwDOvUJ1XNsHzOD+zDkLo2VrjDG7A+5OZgziHRERqNqFNZEz7jOenMJ81p0XDu7cMQHrw2VZI+5dpIefJWpw3/gG9Lt3GtP7KUfSdvOt1Xba2n4f04WiXsrEqcPHaCT2HlYC6MYWnHPrz2SbsP9+bf1Fd0sZ3PKrr9J7mduE8So1q/8W8nwoGtUq0dRzXZabKmEchPffMjyWlLuh72mITXseacGh4GK+d2YttqJ3SZUeMj/sUfXofcRs+mcSw7LoK3Z+TkzjXihW6bM84zolshS67+IaPGtlZhw87zTM34itvSxG+oUQIIYQQQgghhBBCrgk+UCKEEEIIIYQQQggh18SiDXkjhBBCyHWEotyEEEIIIVfHIhflXiws2gdKyWiJ5HwX4zorGrSGUqgX4yxNbSERkUIe434TeR1vWlaP8eO/3fgSpL+y/336uhUYQ/vMvm3KZtUm1FU6NdYA6emo1sdxG7HEcVvXt6oBdaDO9jcoG7eh8VFMYnzsbzS+qvL891fvwzxVWoPAnOiz0xgzv3YzxneLiJyLYOByJuoQ89uMcbWeEW1TNELi7XNoM9Ws67t8OepL9eYalU1pFeof5M6VKZuJtBHv7jW1ZHRcsKsObbKTWvOnUGbE/Ru6NpXLtebX5DhqL1hZ/ZJh1VpcLw7i/5LIYP+NJ3EscxW6P9eGRiA95NKx7bmIMVAuXbjLmEjpTpyvQ2dQh0lExN2Aa8PbklI26SnsY9csbm9tK8dUnhd7uiFtleqxzBqx4u4SbVM8g/Mm02bEm9c56A1lcH8KOOhoWEY7b69Dzaefnlyr8kgpluUK6TEozmCb4g5SAS5jatluvI7vhF6nDz6A++d3UtuVTXAY2z3XoudaIYax95YhSzKrtz3xxLD/AiMOmiNp3HftTlyDkYxep75ZvG7G61U24se+cc/psczF31Cf7BL2GsiiphDxS/5138nbqLXRwmdxzs+udtAsNDT/Ejm91l1NeO3fa9sL6f/6/HtVnlwYy/7pc5uVTcutuE/3DeE5k53Va9SqxT0vWtRrNNCMvt7IOX1+mb6dO4571YfXv6Ly/M8X78Vr1Oi1beqjFCdxQ+vYrrUw+6cNvyOitW/sDizLP6jbnQ+iTckpwy9u02PbtBr1pSZyuq+sWhz/4GmtW5RMoV/hMqpnhRz2/gbsLNe4bnfOONPsAF7Hu1JrCeVG8Yx2aekb8WxEn8tt6308lcFGTMbxugUHzcr1Feg7/cyjD1xr2ugcLVukNH7M+x7fCa3NZDXh2sh3aF8kb2jx+Kaw8Op1qLEpInLoBGomFUv1PZgrgm2yS/V4Bww/ImGcyflGncf0e/1R3eepdvQZb2vqg/TLh1aqPPmQ0Z9hBy2hSfQr0tXKRAJGtqLhilQc1r7Ju38V95Z/Tt6qbELGLVa8Q5ftiuK1c2VYmWSzLtsXwXTpgG63J43jFEXXWSJpvS/7pzGd8umy8yVYlke79lLwXhlvl4MeLVkcLNoHSoQQQgi5flCUmxBCCCHk6qAo99XBR32EEEIIIYQQQggh5JrgG0qEEELIzQA1lAghhBBCrg5qKF0VfEOJEEIIIYQQQgghhFwTi/YNJXfUJZ7XhbjG/OXq7xvuQZG4+EyFsjGf9A3OaCE8jwcF3/5/30cR7kKnFpozBeHypfqRYtwQALcMobTAlBY9m6vD64TPKxOJFA1R5gotEFxehkLTqQGsy5N736XyGN0gtV1aCH14Mox5fJjp7IwWUy4LoHBjRrQApOXBPva0arXEwgwKPt73nkOQfnm6U+UZeakJ0raDWGamH0V6iy26bPcYikJ2LkPR0MGYnlfhII7BeFALS7qN/jNFkCv9eA0RkbIWFBqcTGkR8ekLWJ/S1riyyRvtdkWwbxq3G2p6IvLiDzZiHq1xLnbRmNcOO8zhg8sxTxj7wXbIU1WKSn2TY3q9e5PYgZUrcQ4PH9EVDq+MQjoS0WL5liECWFaSUTZzHpzXXj+uy0JOK2x6S3CurWifVDbnXuiA9D7vOkgH9PYkc36sr69JqxzOxbG+hbien8UmbGfFYbRJbtX98M+DmyBt5fQ+Z46v26/3sFWt45Du3deG1y3qfwvp3oKKlacn65VNKIRireWGWu7ohF7LZQlcG3ffeULZPNu7GtKFlIOi6hsFSb0OHz1YCPiG0jse36yI33tx3c349flQtRPPg+JUSNmYTEzo/dYy5vC3/9dOSOdWOHyQIYP7Qa5M2ySyxl4awbUUnHAQ4G3A/aDqtBYenhXsi2KF3jyDIdzTXL0onv2d3feqPOZSLu+OKpuZMcOH9WOmvkn8eImIiD+I50PWdhDlNj6UkO3Qe7I1hfm2P3gM0i9Nat8p/hzWx3b6CMIF9MlSbQ6Cy6M4djWr8IwbndW+fagU2xAr1ULjtg/HzjKOg+qgPvNChkjzdFKf9emzRn069XW857HdgRljPt6tP6Zy+B/XQNrV4nAuGt1X9Oh53rOvA69TaYiTO/hOZWXog6eG9Z7gNT5o4VuHbYi+quenby32TWZGi7KbwufeOu1fFz24xixjbZgfCBARcRm+U8O9WjR8/Cfo/x85hiLcQQffKWGoaRda9UcNisYHQ0wRbBGRuVZsQ80B/Pvp23Xh/3wBP1Dg0luYEve2/XrNtXXgGpt+DhevVdBzr/424wNGY1qEP1SO9yNhN5YdGdFnRGUc5+eW95xRNi/0rIC0O6nHu/AGwfdi1mHg5hu+oXRV8A0lQgghhBBCCCGEEHJNLNo3lAghhBBy/bBe/7MQ5RBCCCGELGUWym+6VNZShW8oEUIIIYQQQgghhJBrYtG+oRSYEfG/Xrtsi44THekzYnodHuuFGlArIDarY6aDpRgjm6jDOGDL56B1kcGYbleFjguu9WPZo1mMSc3rcGMRI2Y6skWXbcbVt4R0vP75XtSKcXVgG4sF/RzRTmOse9HUwhERMfIVixjLWkw6xBK70MadcoiPNXQAgiHdn2lDo+ZHAxiTHvTrgOOiEXpvOzw+3bwZhapeG21VNmYsc964UDqqdaHSEeM3h+40dXbSEZwU50cxBlxExD+LF0q16znirjG0F05onYJCGPt8ztBISDpoyTSfmMW63K4bNRvHePhiVmvJ5Ix5HqhAbYNcic4TO14F6bKkgx7WepznkwPYBq/DGESjJfpHg+rmCKQLtr5Qts7QAUpinL07oHWCxLjO0X4998py2M5UJ16nLKRj/D39qJEw56Bb5o4a671E96c1jW1INRj6AjGt6VHZGIF0JKH717vK0HDJ6/E+dQb7IjyL+8jMJh1Hf2oCJ7HtsB9Nz+KcsMxto0Kvpy07T0F6z+hyZSMpLKvFQQ/r16tfvfz/8bQt/1VfhZC3TcmkLX73xfWRbdfrJHYetS48Dueiqwn1MnLTQWXjM/SGkk24H9gOvpM1Z+hPVmqb+iDuD4ksrtl80EmXDfev8dt1o9yG9l1zWGvdjJ1FvzK/zNi38w56LmlDs87Rd8LfTK1BV8LhnDR8J09SXzfnMbRvHDQ1Mz4cl2cvoN6b1+Fs8hlHhu3S58PyW1Gz7vhQs7IxNXQKRrvtiD5DEjP4m+XQna4yQ2dnFvOMDmv9vJIpbEPOYRu3643z9bCe9xl0RSTRbJyLow6arwd6IJ29V+s5JqJYlpXRc8249RArjB2cc9Bq9B1Gf6A8rscysgXbne9FXTWfwxhkZo2bGAebQHsCr+ugfTjXYNQnYZzbQYd7MCPLuV7tK1dm0WjWGG+Pw32bz9AFy4qen94ItqHg4Dv5pnEcEkb1XBHdDyUtRl/16rKz63Ffdjn4TkPHcW5VTWE7J27TflHvMOrfOukYzU3jnFAaT2F91nT/Mt5fvTi0TNl4ElhWuCuibD7S8PLl/0+ki/INZUEWA4v2gRIhhBBCriMU5SaEEEIIuTooyn1VMOSNEEIIITeMXbt2iWVZ8Keh4cobZ7Zty65du6SpqUmCwaDce++9cuKE/toeIYQQQghZWPhAiRBCCLkJsOyF+3OtrF27VkZHRy//OXbsyufNv/SlL8njjz8uX/3qV+XAgQPS0NAg999/v8Tj8V9wRUIIIYSQt85C+k1vxXdaLPCBEiGEEEJuKB6PRxoaGi7/qa29qDto27Y88cQT8pnPfEY++MEPyrp16+TJJ5+UVColTz311A2uNSGEEELIzc2i1VBquGNUgoGL1RtLhtTfZ30oAGb5tSBYYhjzVbZqAevCiyhQWViDAnCWgwCvy9CIK0a1eNpxLwqjBTtQcK3ocN1baoYg/eK5bmXjM8QIB45oMbqODaOQ/lDNQUh/6cz9Kk8gjOK+YyNVysYTN8To6rEupriaiEjaEAQODygTiazCvijxaoHtWSPt8WLZZf6MmIxVohihvy6lbF47giJxtsOKKJTiI+OBsyj+a/n1I+W2NhTl7R+rVjamoHrvsCFoHdDXXX/vOUgfm9bijkVDHTHT4TCHZ1DdsWQE/z58z7TKM/IhXCveI1rsudBkrB+vXpemAKldYRg4PKLP1OF1C3EHcVQj+NhbbQhWx7TAphXHAb9vgw6j+enxtZB2ay1HscyxKkWRy3CpFs+OnsOGW3V63ge2o3BscgzzuMp1XxWMYXESBPeOYruLhgiviEhzOc7PoiFGPzQTVnmmRvC3yu6IskmeRJt8SLehGMI6z6zDsq2UFqN0GyLcOQfBXzGymR8JcJfoMdj/Cn4AIOtw3c3dfZA+dKFN2fz3zB2X/z+TyYnIv+v6zTeLWEOpp6dHmpqaxO/3y/bt2+XRRx+Vrq4u6e3tlbGxMdm5c+dlW7/fL/fcc4/s27dPPvGJT1zHii99St4zLYHXv2iSTJSpv8/5cO8vBvQe7R3EsyjQnlQ2pT9BAdtpUyjfYQ64DHFqz6yDIL8Pz1fPcjy3nYR9N9YNQ/rQ6S5l4zEE92cO1Cqb2q1TkP4P9S9D+svH3qfyWFXoe8QHtCizP47tThsfOPDGHAS3DUHgigt6H59Zh/3n5DuZnpHLOJPLAtp3ilXj2NoN+tA7+2o7pL1eZSI5Y/pNn0DRc3Vuikj1MvT2JofCyqaxEs/FyUEcy0JQX7f9gT5In5jQvpMplp5YpsfFFFwuHzR8nvu12Pvo/xfnY+iAnveW8U0O26fXpfLBw0b9HHynlNHMfNDhPQIL51ah1phHDuLpZl1u3XZa2bx8cCWk3RkHX9QQtTb97dIyPT8Lp3FipRv0mZy9G/cN1xDmcVXq/i0YvrztIAjuGzI+jNOq11x1Bc6BgvHuxsSk3iNSg8b9yuqEsvEexQ9L2eW6P/Pl2K7JLbgw3fqy4jVEuDNVDpu3jb+5U1h2rlTvT0d/ZtzDVuvrrliL971nTrcom29k7r5St0xORP5V128+oYbSVbFoHygRQgghZOkSi6Fj7ff7xe/XD6K3b98u3/rWt2TFihUyPj4un//852XHjh1y4sQJGRsbExGR+nr8clN9fb309/fPX+UJIYQQQsibwgdKhBBCyM3CAv4LWGsr/rP7Zz/7Wdm1a5eye+CBBy7///r16+X222+XZcuWyZNPPim33XabiIhYxvfDbdtWvxFCCCGEXFeW8JtDCwUfKBFCCCHkujM4OCjl5Vde73d6O8mJ0tJSWb9+vfT09MhDDz0kIiJjY2PS2HglfmNiYkK9tUQIIYQQQhaWRftAaSgWFn/mYuxndlxrn7gqMW71t5ftUzbfevUeSGdeCyubTBM+djRj+p00dVx1GNNbSOjg8eWVqEFzsh+1jgIVOi74xd7lkC6v0roFVUGMC56Y07G40R+ik/1vD66HdEfNjMozchADrf3dWm8olzbGwdCB8rToPLahC5TYqttdW4b5RibDyuau5Wch/cq+1ZCe6tIx6aUNGCzcEooomzNJjA0P9OuxDG3B/poYRR0bn8NYDhr6MlVVOnB5W3kfpM/7cAxqmiMqzys9qPnU3TGqbM4OoAZFc5Me7+mAMS5V2O5Uj9aXKJprYZUe70ofai1k83oB1dbh2hg4j/PVCmu9BlPrxtei10ZmBOPL67qwnNF6PbaWB+PNf3pqjbJxVWB9So5oPYHMLaiRlJ3EtRKZNYWiRMyXK97dfkbZPD+EMejbV6CG1oGjWmfNrsBYdvdAQNn4VhvaTGndpryNa+o3al6F9N+M7xQTs02RhN67xdBMal42qUzcFo5L3xDOR0vLH4jtMbQXKrUuVHIG62PqN9kpPUcaV6OuytiQ1pe7EEeNNF+5nsNv1M1z0tB7J1JeXg4PlK6WTCYjp06dkrvuuks6OzuloaFBdu/eLZs3bxYRkWw2K3v27JEvfvGL17vKS57R2XLxv66T5BrRD/CK1agL8tE12nf6zt67IO3fX6JsYu04h33GMaPOCxHJNRh6I3Ft1FGN+3b/eUOz0OF8OHSuE9LeGr32K4K4R6eTem8q/iPqbn73w5sh3VhvqjmKxF/CtZ9a7bD254xxMP61O9+ufQjPAOaZ2qH/ibwshH7FzITWG71l1XlIn3wOfYjZFVpTx9OM9WmpiCibviTuyeXnHbR5tuNXGJNDWD+7SuvPTEzgWVlSo/2MWyv6IP2vftRmKmnV/tbxEx2QburW587wBWxTVYvWXY0Gcd5MV+Mc9p2qVHk8Xhy75Do9RwJ+PLdzee3TVjVEsOwzOPeKVVrHxpPAdVro0HqO3kH0EUpXYjmRZr1ObTe2af+RlcqmYOgNVryqz73ZHYYW6ziewblZrQNnGVPtjuU9ymZfH87zDWv7IH3qNdwzREQKFehYlPRpfyC7AedjcU7b5A29yY/W74f0/z2itdgM6VNJOWh+ekNoFF6pfXvTB5vqw/nopAts7tWuar0f2ZO4H+VM7cukniP+jbh+sv3aF7gQMeZwWO8JRdv5/8niYtE+UCKEEELI9WOhPkt7rWX88R//sTz44IPS1tYmExMT8vnPf15isZh87GMfE8uy5JFHHpFHH31Uuru7pbu7Wx599FEpKSmRj3zkI/PTAEIIIYTc9CyU33SprKUKHygRQggh5IYxNDQkH/7wh2Vqakpqa2vltttuk/3790t7+8UvSX3605+Wubk5efjhh2V2dla2b98uP/7xjyUU0m9kEEIIIYSQhYMPlAghhJCbgYX6/O01lvGd73znF/69ZVmya9cuR0FvQgghhJB5YaH8pktlLVEW7wOl80ER70VdD6+Tnk8Wq/5kzx3K5j0bj0H6hT0blE15J8Z4Rg3Nj2Jex4Wb+h6+SR3rfNKFejiBCbRpbdWx+MMnmiFdsV3HOvf3od6M3VxQNin8sI5ETrdB2qXDtyWwyoh1nyxVNi5Dt2Rt4wikTx/FckREimW4OlwO8bu1AdTDiY5rjZIDpXjtXDle19ejdWLyLvztbLvWibGN8S3fMq1sZpOoH7G5awDSxyZxrEVEAj0Yb5xaq8fpH/u24A9GTLrTB4y8s1jfvgrdV1YRM4701ygblxGmbJfg4HobtQbF8krUHDhxVo93ZRuu1ZiDhk4uaOiUGfoCbgfdj4qVuF6SWT2WYszP6CvY7vpb9djGDmH8dqZLL47CHO418Q06xttlzCO7FLUM7ujQMf4/O4+aA8+e0fpNvinsq1gN9qcroydJIYd18Wi5KYnN4PpubND70Yiho/X1l96PZa/UcfbFHNbHPaHHyZ1Gm2FDb0xExDOE+byG7kPO0roFHkPbLhnVc89v9Ge+FOdeSZ2e97EM7iPVTVpXI3IujNet0uu9+IZ1mXEYN0KuB8EzPvF7Lq4PJz0fSeMa+PvjO5TJXbecgvShH61SNu7luLHMxXHftnIOmjrG+/zBMb0O+lzo45QaMoGVXXr9xQ7jXuW7W/tOM+dQS6Sojy+Jd+K+M3MctS/d+rJSWI8/WmMOwvPGTcLy1nFIDx3EckREcobvZDv4TtUlOAaFY/qNvddK0CG0wnid0lNOQqH4W1+X1lQ0x9e6La5sYnHcO1euGoL0mVHUxxIRqTiJ101s1nv9v5zbhNU1XHDLIW7EP4PtHpoOKxuXsW3HLmjtQ3fW+NqkcYbkW/S52FWDvkffCe0z+rtwHpnrSUQkX/KLfafgkB5L91ocl7mM7k/Td7JfwHaX36nHtrgf51q8WwsbulJY3+ktDuKHeaM/jXm/tRt1I0VEXjmNerMvHdP6TcFJvG60Hv0Bp7WcKzV04WJ6Hs1N4XUqmx10tk6jX/7fn38A0vZah34wHH7/uL6v9KSwPpOTen6WDBhzZBn6q3kH3TrL0LazZ/XcK5nAdK4c6+tq0r5TIo3XCTpom+VPGXtWje6b3Bt8p7zDkUYWB4v3gRIhhBBCrhuLVUOJEEIIIWSxQQ2lq8Phn5AIIYQQQgghhBBCCPn58A0lQggh5GZgkWooEUIIIYQsOqihdFXwDSVCCCGEEEIIIYQQck0s3jeUls2J+C8K2xYK+rlXMYu/uZJawGx3z1pIN2+ZVDYjfSjc648Ywmgz+nFhy3tRJfLC8mplU3YYhZxzG1GsuC+i8wQ2oPDd6Mk6ZeNqRMG/UIlWlkudRaG2rCEQW9mmBfYKhpCzOAhABlpRAPLEGAoLNqzUosfTJ7F/PVVa0PjMyRZI16xxuE4cRYTN6pVvmlF5JsYMwbqcg8hdKdbnriotnvz9FIq5n9rfCemytVqUL7ceRZnldJmyMcUHXbWoNjc5gCKiIiLudmO8HcbJZYgeFx36XGZQmDEwin2TTWtB48GXUcXUU6/Lfm/NcUg/OXS3spkcQoFP/zKcV9lSvS1Nzxr959brMtiC18k14nVCXi2WOVVhCJ/mdZs8Cdxr/JVafDCZMARpDSHvF4+sVnnctVgfe0YLIboM4VtzrZRO6X7IV2AbAlsjyiY1iUKIY/16PwoNG/XdgdeZi+MeJyJi+QxBxQY993JGOz0eLWBdMIRNC0mcr645fSa4RrE+Hj2FxbcS9z47j/M+V9B7RCiAa24modtdqMB2N9ZGlI3ffWVPSGfy6u8JuR6kVmal4Lu4L9gOvpMppuxJ6D1v7ykU4a7c7iCEbQgWlxnHdnBKi6uWPYRGA259xoVfQWHs6DY8F5NTYZXHewvuyZkj+mMV+RZcc4FSre7qOolrO11tfPyjw+ELB8YZbDv8C3PR+KjAuSEUHq9cG1F5rMNhSOdq9Z4xchhFrYMbY8pmzvg4gdtl+B23aH8wMYLng5Vz+IhAGdbn7lrtO/0guR7SQ8/j+eXfrD+4k9yG50HwuD4Xs2VYn2w91iXVp8XJC13GWWT6vCLinjOuW6PPJvNDGaXGOZnO6PpGX8Dx9jbpsj9Qjx8R+k6f/tDQ3EAYf+jGc3IupM8vmTbOKyetfMOvjDbjdZp82nearCrHHxx0pr0xbGehWvsDhRiud3cK8xw60K3y2HU43u5p7TNmjI+GmGslNKbHNluBnZO5Xc9Pawz7M+4g3F7Rh9dO3Wf47VH9EaFCADuwWK47tDCFfpDldfgoU7vxcZ8k9o1nTs89/xBeN1+ibXLrsS/yOaPPHe6vSoK4xybiut1WJda3skHvYV73lXamMw73M2RRsHgfKBFCCCHkukFRbkIIIYSQq4Oi3FcHQ94IIYQQQgghhBBCyDXBN5QIIYSQmwGKchNCCCGEXB0U5b4qFu0DpUzCL3b29bjOq3gHzFWjY3xdIxjLnDhVo2ysTRiPaUcxnjexVV83kcfrpqe1WIev1IjFNm0c4o3jQRwOf5uO33UZfZHO6yFsXD8O6YFB1KyZiTpon5hx9RW63e6XUceobgr7bmKT1mEJLsP4/A82vaZsvhW9E68zpPUPgmPYnxXbpiAdy+jYXN8sxvRe0pV4I7U1EUj/0/ktykYSGF8s7RgXnJvTMfOm5ou0OMT9GjpgpX60SZXpFwgLhv5MS6fWBRu1Mba9qlTrbE1nDI2BaoxJd9LeSG7FeO18VsdM//2BeyDtcpjnuSZsZ4kxp22z70TEG8H6hFZFlE1b6Sykj02gxleJR2tmmJt3e73W7+pPov5BJqvXnG8c65wLY8PbV+KaFBHpHTf2ozKtkZHN4HWrOiOQjmW0BklFHcagz46XK5vAFPZntkKvjdgarE/oJdQKcGuJN9mx9RSk9493KJvaDuzjyGt6X5YVqIlSUYb7yIylNcnyhh6SN6p1ACxjrpl6InMO2gYVQaxLIaXnZ0mFUV+f1tkKuq7051yBGkpknoj5xPZdve+Ur9Nnk3/Q0Cw7ojVp8rcYm/s07imTt+vN3zJ8J5l00scx8kyiT+Z4phi6e1ang/9irPWcg+ZH1RbUYsz04v6ajDgIs5nbTKVe2zV7sD/9Y7ifTd4WVnnsVXhu/3rbQWXzndkdkC44aAeVGxo/1h14PiTSegz8U4b2jV/vpSX12IZ/Pb1J2XhiOCcSXcbgJXFsRURccRzLZJuewy5jeD1B7PN8wUEL0dDZCS+LKJtpGydfSameR3MZ9IOzdYaOjUPZU+ZayGibf9iLfrBby+NIqhl/9Bhz2h3Xc9o3i2W51iWUTWs5+k5nRlBvqMTt4DsZTapvjCiT6Tj68gUHnzEwavgihqZO9Vr09UVERkdxXebLHTrL0LEMrsD5Omf6wCLibTL0PEf0vVLJBKbTlXosZzbib1V70K+wG3U/bNpxFtKvDHcom9DyCKTzhk8mIpJYi/t5MIT7yJyl2+Qy7kX8Eb3mzClrGRtxcVbvI25j/Zh6TiIirkpDF9hBryv4Bt99zqbvtFhZtA+UCCGEEHId4RtKhBBCCCFXB99QuiqooUQIIYQQQgghhBBCrgm+oUQIIYTcBPArb4QQQgghVwe/8nZ18A0lQgghhBBCCCGEEHJNLNo3lCoqE+L3XxQyXFahRdlOTaNQbiquxVQtQ2g40aDVHE2Ra1Oc9t0tPSrPs+dX4zXyWpQtU48icV5DINpy0GiuaEWxxOl+LbjbugwV4UaP1yuboSYcVncIBfVKDmnxtEQbposVWvgsvsEQewujyJ37lBblThjj8u3ztymbjR0DkD5yoU3ZFNeiUNt4FIWGXeNaKLd8RQTrciqsbMYihmCxHkqRUkOwOo1jGRjQZRc9eCF3Wj+7Dd+J87rMi+J5A7Ye/4wb5/DQVFjZ3N7aC+nJjBYwnsmhmJ8dwPpabr1WNtSjuuexyWZlk8tjO11zut2V5Sh8uDo8Bul9kytUHsvQXMw5iIYfMuaNqwTH7diZdpUnaAhWjr/SoGxcy3Hu5ef0eEsVVtCVwfqNxLUwtmWIj9pap1Fchi7/dNwQYWzSYpmRaVPVVv+TR8FoQjHooHRrkOjE69y16rSyeeEk7o1OQuMxN+4JBa3LKiuqcZ+7sBfHrmIT7pUiIslZFNksG9VCnVE/jkOu2eg/h/U/cxr3teXrR5TN+fMoAH++oI/W4viVfTeTy4nIy7qw+YYaSu94fNVz4vdfXHfLwtp3OjOFavqFqF6AaUNoON2sB9QUuE9X4Z53R8d5lWffGdzb3Tm94FJNeF1TINrl4Du5O1BoOH1eC+5WrkbB7fhr+uMfk62Gn2b4QTX79bkTXY55clonV6a2YTpcbfgHR3SetDEu/+v0dmWzYjnuRefPNCmbxCbc4wrG+RAY0wePtRb703u0VNmoc8aBfAjPFZfhB5Wf1/1ZNKajR3/fQKx3RyEd8qHvNGSHdV3cuCdPTegzeUtXH6Qn0tpmLIt9kTd8J3HrtbK6CX2cU2Paz8gZ9xGelF4bwTC2c3UVXvfIeJfK4yoYYvQOvlPP6RZI26U4br0n9LwqmTE+aLFXr6f8KtxHrJQ+FzPVxgeBDPXniahey56oMWcd+tyTxOvMxXG+Flq0f2BNoGC1y8EfKPgMwfrSNz/sIsuxz7dt0PeVrx7qhnQxpH2yuOE7+cy5JyLL6nDPn/gJ+ia+W/SCsqaw3WX92iYfQJtMmzG2Dq+nZI/h+mnaqj8iNH4aP8oykNfzyDtyxWHN5BwE4ucbaihdFXxDiRBCCCGEEEIIIYRcE3ygRAghhBBCCCGEEEKuiUUb8kYIIYSQ64dl22LZ8/9O9UKUQQghhBAynyyU33SprKXKon2gFB8ql6z3YtzkRHdG/X0qEnzTa/hDmC8d19pBUjBiUAMYt/pszxqVxR3EIH7/Bd2NHXdhbPupvKE3U6K1RTIvomaO1ahMpGDjS2W5Ch1n6x3BdmZrsSxTC0lEpKocxVqiPWFdeDPGb88eR22RbI2OSQ72o1iLJ6UXy5EMat9U1sWVTbwXhQk8GVOjSFd3dtTQCWrQfd6w24gD/xU91+JDGMNtRi2na0RRCGFZvkk9R2ZSOIeHohg7bGUdXiA09Jxcs/q6+/LL0ManxyUwga3I5HGcrGrdD6f24nVLNmgdm4wL52Mmp7XNZiKoQfDiJMaOe9I6LjxbbVx3Wms6mO9bFuewbyyHePh0DY6/ryGlbOyMcZ2MHpftqzEm/vA+1ArJhvU4uYwurl+l9U5Gpg1BDkOD4JJWyhvJxHAsK5r0OCUMTSdT401Ea4H4qzGu/sXDhl6SiFg1uLfYDtJMRRsH4s7bjyub/T9ZB+lN952B9MGXVqo8eUP3ZbZbt6lg6BKYemjuMr035suwvsOmjpWIiLHendpNyEJQ7A9K0XtRiGZitda5KU4bfpDDMeMO4TooxrXOkqlrVzBcsn2n9Bq1g7hOys7oTbnyftSFGcih3kyhVC+u6p+Y+h7KRIpFLCsb1r5IcBD317Shuzm1TecpDaPekPu07vNMK/Zn9jXcQzL1+rqhC1hfb1L3VU8GtW38jQ7nVw+elX7j3PHM6bKTQ5in2KJtmr+HOkbTH9VnfaG/RP32RlJaSkhy5djnwXE9QbNJLGtmCPvT7SSzUobX9U3r8+FQHjWIbJ+ea+U4PWUub2ho1eozZOhZ1Cjyb9MaNTnDdyrmHLTNZnCRHR7D+noddJdMH8ee0PdOtuGeKO1LB99prg5/LDZpn1EyxvnqoIe1fkMfpHt+2gHpRJUep4Dh75eujyqb6Un0290JbJM7oH0ny9At87Q5rKeYsZ6mHPzVsPFDLU7IQ690i0nevH9yeK5gPmvYdO8ZZXPy39D3XPZAH6TPPt+h8qQa8cIz6/S6zZWjjTuF/Vko1/2ZDeHEUpq1IlIw1rtF32nJsmgfKBFCCCHkOkJRbkIIIYSQq4Oi3FcFNZQIIYQQQgghhBBCyDXBN5QIIYSQmwDLvvhnIcohhBBCCFnKLJTfdKmspcqifaDkqs2Iy38xmHIy6aCX4sVAy5I+rzLJxo040HIdnLmiDQOi+6OoY1RbmlR5hkZQ6yZ067SyOdWDMdPlF/Dvo+v0y2HxDmMmBbX2zdhZQ7BHh1lLoRljmWtewGHe/JHTKs+e0eWQtn16Vm+qH4b0azMYv93SNKPyDBdRZ+meVaeUzcEpFDy4t6ZH2Xx3cgukG1/FOPXx27Q+1rLOUUj3ntWiVGN3Y/zz1oohZXMsi/2XjWJZnrgeS8uDc23brTrW+cB4O+Yx9LxqWmZVnqlBnJ++mEP8to0x53XdEWUzUY4Tx12Lc8bl0mslZyzD9JjWijCD7W2PQ0B0AfvLY+jW5EWvZf8ktqlx85iymU3jes8dxnjtVIteT+4wlp3L6i3R1F4KN+l4/UMvYdy6GW/uGdHzs9iKQgDD45XKxmNoG+WNPcxJoyJsjPfsrB6n27bgGjv5jI7p71iHfdx7AvU6ypfpfij1Yn8OT4eVTS6HbXp+cIWyca3CvjkVrYd0tsJJYACTHgdJh0KtMQcMnTJrVI9Txxrsh/GXHcTtOrDdLpeu30du3XP5/xPpovztP+rLEPJ2yTfkxeW7uGnNxLXvZJ7toXP6DMlUGjqMDnpDzV2TkB6eQR2bqpDWH5kZCGNd7tJ6iYOnUFin6jSu2amt+ryNdGMbCqV6r4+fMDQq/bpNc62oA9K4G7VPln+iX+V5cQi1Bd0OPtnaJtTUPG34PFWtEZVnthCG9C0bziub18ZbIf2uhrPK5t/HN0G65t9w3CbeXafyNK4wbE7UKpuR92F/rgkPKpuTGRxL1wye7d6Ennu2B8dl1V263YeGsf9chnxLsA11rURE5vrwHPTPOp0hWJ/S1Xp+JsNhSOfrcY64HOI+suV43dyw1jEye8LW0kFK89U2dGtyDrd0wXFMl23Xfnp0DuvjfwXT8Q5dlaKpN5h1qLDRKF+rvp8yNX2ylZgpOKDblO7EsjMjWpsnMI0DYfoMvgsOmrqrsX6ZGT1OG27rhfTwP2rBtsAW7OOpw8b6WaH7odqHbZqeCCmbotHH+84vVzbWepwTp2dxfee0mykuY7v0pPXaMPXkXIaWaGBI++2VG1EXNPmzamUT6zbuERx8p1+/e++Va6SL8v/+QJmQRcCifaBECCGEkOsINZQIIYQQQq4OaihdFdRQIoQQQgghhBBCCCHXBB8oEUIIIYQQQgghhJBrgg+UCCGEkJuAS+KSC/GHEEIIIWQps5B+07X4Trt27RLLsuBPQ8MV3TrbtmXXrl3S1NQkwWBQ7r33Xjlx4sQ89NBFFq2GUlvFrAQCF6t3bqhe/b3lQxWxTKUehRLUQZREUD8/67mAAqv3rEHR6HghoPKMplAYe3yqQtm4DZGzZe9HVe4joyjaLSLimsLhqHAQ/02UoJBcPqEVIAspvM6MIQB+cMZBRO4gis91v++Csun5IYpwl2xHYbmwT4tw+tpRIO7Qv65RNolOTO/zdSmbwDiK0Y3dicJ9D61/VeX5l/ObIO2tn9P1MwTgTk43KJsVVShQ2e9BUfa5Mi1GVxFEReBj/66Fhz3bsL/yAZw0k+N6XtW0RCBdtVz3+WgCBQrHBquUTZkhWlkeQBHkibgWBDQ3OiuvBTUr23DOxk+GddmrI5CeMUSjTaF8EZGeHApC91/Qe4ILtTHF7jZ+cKjv1gYUEp3OahHbsST2ReZVPS6yAcdhXdUEpI+d12uu9Biu5WSzvqy5/ZhCiO4OLe4YHcT6uR100Q8cRRHu6ru1APy5fkN8ugwnwFzO4UMIeeNIcSg7n8R8GzsHlM2JSSw7fTSMBnUOFzbIOAgJu724xvKGSaFUz5F0AeubrtbX9RuClOkGfdYciF/Z1+bSeREZUTaEvF0aqqIS8F9chyN9NervbR+unXStnquhAVwnEQffaeQsCs3euhGF/uM57TvFUqgIG5vQHwzwGPt07a/hxzUmh7Qovi+O+467TZ+LqRL0leyE3r9cSfQzJrfiRw+ikyiCLSJSuQ/zNDyk97OxfzL8vXvQPyj34/krIuJdhh97Off0MmVT7MZx2efXvpPpB4+9D8ftvVsPqTzPnN4Aaasxq2xcxsFyekqLe3fWYhuGvGFIZyr0LUigBMWJ+7/bocu+Hf3KQgnWJTmi51VJB/o84dXaHxyPY75Yr4Nv34n5qgxfbyaqP5RhmbrDDr6IrxPrZx/VbbDX43mfNkSjm5ehryoiMprD8c6c1f6gK4v1ia7G9e/k621owY/0TGe072T6kb592ia2FefWshoUcr5wBn0/EZHK13DNxdp0/fJBPKddGUMYfZn+aoerD+vn1dr+cuo1vGEJ7Iwpm9lzxr5r+E7i8PGXaN4QNXd4sGAZ+1z3Cu1D9IzhOvS8ivMxq7tTbGN7T+spIpbxISy7aPSnwzd60gWs71ydHqeyXiw82aLPmn3RK3tfOpMXEb3H3qysXbtWnn322ctpt/vKPPrSl74kjz/+uPyP//E/ZMWKFfL5z39e7r//fjlz5oyEQvoe7+2yaB8oEUIIIeQ6QlFuQgghhJCrYxGLcns8Hngr6fJlbFueeOIJ+cxnPiMf/OAHRUTkySeflPr6ennqqafkE5/4xPWoLcCQN0IIIYQQQgghhJAlQE9PjzQ1NUlnZ6f85m/+ply4cDG6qLe3V8bGxmTnzp2Xbf1+v9xzzz2yb9++eakL31AihBBCbgIWSt+IGkqEEEIIWeospC7kpXJiMQyl9Pv94vejTMb27dvlW9/6lqxYsULGx8fl85//vOzYsUNOnDghY2MXpUPq61EepL6+Xvr7++el7ov2gVLYl5Kg72L1qmvj6u+jPWFI+xLKRPw7UBfEKriVTeY06s30JjH2tX+sWuUJNGIMdaknr2xignGrJ2fwlTRrUmsfla+IQNpJoyQdxwlV0u/QppUYG+yKYJ6ZSYfYyRUYH3v4mI7FX/YejNc9fxqDcXvO6iDabDPGw5fp6oodxEDliZFKZeMK4Wpu70CNmu/3Y8y/iIi/BGOz0zGt6RAcwgrV3DKhbPpjGFAc8GKbLIedZu4Uxt5nu7Tmi/cCxmu7jb7xOOhAmHOi75QW3il6sT4NK6a1zXexfsN3Yix+bY2OC0/MYf8V9fSU6VlsU1lC9006h9tOVyPG/Z8d1VoMja3YhumkjsX3HcP6JX1YwWCd7s9XR1DbyDXmVzYNa3BOeO/Um82FAazzidF2NAjrPWKuAfsh3Kw10yIxbGcxjS+VZqa0XkNZE9bP2q/XpWsHju/kUFjZSCnW+b2dJyH93N5NKku6xhAdcDiEO1qN8d7bqWw8a1Er4pa7seyhtN4jNocwrv6fTm5TNt5zOEfcxglYtjai8oyOYllWuR7LlauHIH30fLuyGXjuiv5KJp9Tf0/I9SDsveI7zdZpjbXiadwPfDG9SDP34V7pNvU9RMR3FM+MCwn0nZz2FFcz+iZeB5GSnI1r9MwE7q3+Me22utbgnpfO6sPJjqHPVX5emUh0HdbHP2togEzoc2duLabjr2m9vPr/D54hsePYpvGTOmQh2YY+Q7WDt14owbGLD5QrG3c56pbUGNpMz5xbr/OU4B5XjGl/tbQP074dEWUzFAlD2u819k4H38lzBOdVpFuZiL8Hz+mi0Te5Dq2PY86J6aPaD3YZ06ZkrT6TS/8e+3NkJ/Z5Wa1ec2LoBha8WksmNY1nedhhXcZyhl5X8wykhwa1ZlpFJ5710URQ2YQOYgcWfehn2I26P48OoC5YYFhP0PBGrJ/n3dp3il/Ae6z+EfRpC5V6j0g0Yz9423Sfz0WMsz5lBORM6DltteK9XfkebZO4D/siOaDnUaEU1+67VqA27/6frFN50rU43k7alzVd2J9jP9GCSK6NeN+z5r3nID2Q0r7TljD6Tj88vFnZlJ0y5oi5xW5y0PMcwvuMYliPZecG1Ew17ytFRKLPXHkokincHL5Tayvq9X32s5+VXbt2wW8PPPDA5f9fv3693H777bJs2TJ58skn5bbbbhMREcvCvca2bfXb9WLRPlAihBBCyHWEGkqEEEIIIVfHDdBQGhwclPLyKw+rzbeTnCgtLZX169dLT0+PPPTQQyIiMjY2Jo2NVz5kMTExod5aul5QQ4kQQgghhBBCCCHkBlJeXg5/ruaBUiaTkVOnTkljY6N0dnZKQ0OD7N69+/LfZ7NZ2bNnj+zYsWNe6sw3lAghhJCbBOobEUIIIYRcHYvRb/rjP/5jefDBB6WtrU0mJibk85//vMRiMfnYxz4mlmXJI488Io8++qh0d3dLd3e3PProo1JSUiIf+chH5qU+fKBECCGEEEIIIYQQssgZGhqSD3/4wzI1NSW1tbVy2223yf79+6W9/aKG56c//WmZm5uThx9+WGZnZ2X79u3y4x//WEIhBx3l68CifaB0dLJZ/P6Lql/5qBZGkxAqluVzOnpvZjAMadtBh6p0JQp+9w+jqF3JoBajnGs0hHGDWmiso2EK0lMvYMxiya1a7C96HgXMCqX6kejmZajOfjivxV+DPhQty3oMMcpqLZ6WTOHrdFUOYp49fY2Q9s5hh2ZbUAxORCR0DJXbMrfMaZuDKBKYrtEDlS/H8e7vR1HLX1p3SOXZvWcrpMtWaXH3XAjHd6hfixqWDGN9ZmoNg1otWGj5cexsv4P4aBjT65ehMF4qr+d930kcg0C3btPmahQI3nt6pbIJtuIc7mwchXRTUM/P9J0ocj+Y1OJ+0+fwt0SHVhZ0D6Ow6VAGRWIDXXruzaZxjuQntcB6rkX9BKTntFDrhqZhSI9VaFHToekwpIM9DmKOTdjOZatQwL7Br/vzhQFUG40MVygbbw2uF28JllM4rQW35yqwna6taWWjpLyLes1ZUbzOS1Mo1J+t1nM6VIVivqkBXb++IVxAK24fVjYzaazhhSTmGRrXc6/XjWu3pWlG2UxW4NxbWYViucfO6v3UVY77WjGjj81YDuejb1qfR3P1V/aEzM2hK0luAKfHG8X3+gcJXLMOLl45nk2unF772V7D4XT459nsetxXUn24Jsv7dNGJFtw7s6X6fKhvxnMmtxuvm75LC/vmjQ+C2A6+kymc3+NwYHj8hhi1B/vP3I9FRLJJbJO/QduM9OD+5TeOOFOAW0Sk5jVMz9yhPwZQtR/rl6zT+06uAvti6jx+ZOS9W46qPC/+CD9yYo61iEjC8J2s3rCyCRkfE0o1GD5jvd4IXUG0KQZ032SM7b9rJZ63qYI+o6eO4BjkVus2barDOfLa0WXKxja+V9PQjCLnjSX6rM+82/CdEmFlI2fQ94gucxAs78dzJprBtKtb+6LxJNp4xnTfxNt/8esXhaT2nVa0oZjyeKW+SZ2cQJ8mfMpBZQW1h6V+HZ7JTQHdny+fx0HwDOqPk1i1xsdzyjAdOKZDiJKVuJ6mb9c+jpnLchDP9kZxbbw4jvXN1ziMba0xH3u1ePpkH67d5nsnlU1xDvOdj6NfND2q/cwfGB8eqWmNKJuZMPbxshq8x+09qcW0TRFuK6Pvp+NZ7NGAbpIk33DPnXE4r25WvvOd7/zCv7csS3bt2qXEvOeLRftAiRBCCCHXEdu++GchyiGEEEIIWcoslN90qawlCkW5CSGEEEIIIYQQQsg1wTeUCCGEkJsAy14YccnFKGBJCCGEEHItLJTfdKmspcqifaBk9fvF8l6M9a1aE1F/Hz2HcaDV66eUzcS5akgXy3U8bGoEY+/dxmD6Nuv4Xb8x4u4f6djh4c4GSBfWYGxz0iGOVUWXOkysQ4MYcNzYrHVC2kowXvuVVAekswUdx+o/g3GsxW1aB6CqIQbpSArbsLJhXOXp68f6Wg6rJbkeNUpsB80sTxRfpmsw4qx/uB/1kkRE8nU43rVeHa9fU4JiBq11/crmpfQqSBfDhpZBRMdil3WgzkNiqlTZlNZg2cdGmiHtGddx67YP+y93Rs+9vc3LMY9L9/kb9VxERHqHUJNqskpr36RG8TffrI5ldhtDt6pd6+OcPI9zwtOEujvpuO7PX1v5KqSfOX6bsqnYhntA5DWMHc9162D3IwNYl64mHcDt78dG5XW4vojRFeence85m0ENNRERXxDno79BazrkjLWa7cMxCG/Q63/uZYyHr71zTNkMH0YtLo/DSZAz4t8zeWPfcHi/NR43NB1qta6aZegxtARmlU3fEVwLiQ6cI/4yfV2vG+s77KCHZvtwDpwc6MD6mgeAiGxv7oP0/hMrlE3/NGobPHj3q8rmBwf0HkXI9SZw3iN+z8U1Zm3UekOm7lpgS0TZ5E+FIZ2r1OvCGkKtDrexvWZu01p45olW9y/aF4msxL1zbiOua8+QPkv1VTRnenFPCbdr3661LALpo0k8H9zmHigi4ePGHn27Phf9TdgX+RSOQXuz9l+nL+CZbDlIh0xvwXHxzOpx8kUwY9lmPDP2/GyjypNtwOuUerV+U2Up7sltTXofP5pCXyRbZYzljD54isvR93SNa71EVz360z2D6G8HR/U42YZv4juu/YwD7Z2QdjuccUlDKibeh/N1qlb7TvYQtiEw7aChY1SneZM+twdOYzvzrYbvHNO+8y+tRzGunx3eomysO9C3L+5HPaf4au079VxAH6KhVfsihQvon2bLHCaxcU8wOIH+y1BGn+NWEOejK6T9gWIeB8/Tg2NgbdX6o+EXjL3x3dPKJnoA6+N18J0yVdimYhbnY9FhwypGcQLY9XrNueOYsTWo19zUK7hvzCzHtWKV6et6PDi+kfNhZWMby3DQ2E9dDv2wpR3vp44e0ppko5NY1vvee0TZ/PSFTfriZNGxaB8oEUIIIeQ6YovjP1TMSzmEEEIIIUuZhfKbLpW1RLkmDaV8Pi9/+Zd/KZ2dnRIMBqWrq0s+97nPSbF45emmbduya9cuaWpqkmAwKPfee6+cOHHiulecEEIIIWSxQ9+JEEIIIe9UrumB0he/+EX527/9W/nqV78qp06dki996Uvy5S9/Wb7yla9ctvnSl74kjz/+uHz1q1+VAwcOSENDg9x///0Sj+vXCwkhhBCyMFjFhftDrkDfiRBCCFl6LKTftJR9p2t6oPTSSy/JL//yL8sHPvAB6ejokF/7tV+TnTt3yquvXtSLsG1bnnjiCfnMZz4jH/zgB2XdunXy5JNPSiqVkqeeempeGkAIIYQQslih70QIIYSQdyrXpKF05513yt/+7d/K2bNnZcWKFXLkyBHZu3evPPHEEyIi0tvbK2NjY7Jz587Lefx+v9xzzz2yb98++cQnPnHVZeXDtrheF1BtK3UQ+/OgIHT8xWplU7EdRReTWS1Yl/MZXTCNspHRMS16bOK910FMN2mUlcJytq68oPIcn0KRO79LP6pMRlAI0+Ugcu1zGaJrCSzbHtZiz0Xjp/jpsLLJ1qOIcDCKAntDe1pUnsJ67JviiIOicTUK6rm0drpY7SgAOfUqCs/5VmvxUTHEO+9cfV6ZjOdQfHDvgBaNsyuwQm5DfbQQdBB7T+P4r+0aVDYnzrZhOX68bvM6LcrYP4Xiv792yyvK5n+eNgSrHQQAbR/OkcAgToBkTgtLljViH+fq9fNo/0Ec37MzdcrGMqZnqQ/Hv7ERBSJFRP7p2K2Qrt2mBSD9HrywbbS7OKNFON1VKFjYe75B2TRvRqHu+qCu36ERnPsFQ3jaKS56RQsKy58YbVI2f7DyOUj/rAoFoY+N6TzFDpxHyV7dJrdZPZ+D6G4R13ehzxDDrdbijqHTuNeY+4qISG4diq7u27tOX2ddBNIzUSy7IoT7gYhI9jCeCa7ujLJpqcLrTvXj/Mys1nlePop9fsfG07rsIrb7B4O6TbbL+f/JO5+F9J0y1SLivbieu8u173TBY+ztz5UrG89duNfnMw6+kwc3WN80pnPDTl8vQMYf0B/KsBO4f7mTuFhWrRtQeU6O4x7nJK4vxv7vIA8sfsN38sSwbP+A7oeC+dMJfXbONWKbQjNYv9iPa1We5Basi3dYn1+FGrSxCrpV6S48Xz0vouhxfqP2X719qMB7V905ZTOWxXlz4HynsrGqDB/WGJdCqR6n/BweGstXjiqbvhPoK1uGYHD5Zi2mPD4ehvRDd2vf6R+OoO/kdH6J3xAs78M+T+f1OLla8Myba9QHQMV+LKxvUotRe4zx9fpx/YQqtB/8zKsowl26Q7/xGDB8J2PJiXtKd0S+BsuePKvvwcLbI5BuKNG+0/FBQ9w5jmep0xsbne0oYn9uUH/05PfX/xTSz9WuhvTZYZ3HZbj/8R7dJo+x3ot6SxDLuCXwXcA5ka7Tjao8blzXox332Fbs86PP6g+EuDbjHCjO4j1jIKzXu/9l3Kuja/Q9TV0tjl22B/eR6EbtDx5/FTt08y16H8kaCuU/urBW2XjpOy0JrumB0p/+6Z9KNBqVVatWidvtlkKhIF/4whfkwx/+sIiIjI1dvAGur8eFWl9fL/39+utZIiKZTEYymStOfCymNxxCCCGEvE0oyn1DoO9ECCGELEEoyn1VXNOzvqefflq+/e1vy1NPPSWvvfaaPPnkk/Kf//N/lieffBLsLOP7prZtq98u8dhjj0lFRcXlP62trY52hBBCCCFLDfpOhBBCCHmnck0PlP7kT/5E/uzP/kx+8zd/U9avXy8f/ehH5Y/+6I/kscceExGRhoaLrx1f+te2S0xMTKh/ebvEn//5n0s0Gr38Z3BQhwYRQggh5O1h2Qv3h1yBvhMhhBCy9FhIv2kp+07XFPKWSqXE5cJnUG63+/Knbzs7O6WhoUF2794tmzdvFhGRbDYre/bskS9+8YuO1/T7/eL365hjKcmL+C7+y9yJ13Rsthk7nqrWMZ/ZU2FIO2nztG1FB278AsbiBzegDpOISOy8odWhw2zFHcO40EIIY2aPTWIMuIhIYQRjXfP1Ws+jrBK1Q0ZmKpTNZBxj+G0flp1t1R1h53Bcw8cchHfasc+zK/A6y6p13LoZp9yxYlzZjBzFPs8363abfZNtxLI3VGJMtYjI8XHUXfnBC7com1yjoeGQ0e3+5KZnIf3U/3oPpGfX6B2gaGF/nj7SrmxsQ4PGEzA0E8xAbBEJlWL881Pntiub6mqMoU5ldfx7ZhxjptfegfpSAZfWtjg4gZpPK6v0WPZ4ca3mpx10i4xLx8+GIR0pcdhRjUff04amjojIjAvb5DbyOHSnFHM43jWtWnMkncdt8vh+rbPlMnQVQl2oU5Ds01psA3GMQfcFdJ//68xGSA+ewfUUmNFvL5gx5oWAMpGiUV+nvimrSUI6lcZ95V3LtJbQc7IK0pvb9E3uqZdxjqTrdOHpSewvbxn2jZO2nd2C1yk/osUNBtajBllgA+6nhSncZ0REXMZ03HtmpbaZw3Go6NDnhqvjio5GOqPHmrxzWUjfqVhSlMLrZ37/Pv3WUq4B/YEZBz2PkmO41kvyek8uvR117FI9uLYK23D/EBEpnsHrZmv0db2z2E+5CrQ5MaZ9J+8QrvWsea6LiLca/YqZKb2HzMbxDLGM7k22676ycrj2a1/VWiJzXYZm0lrM016nNQEj/airVLla+1exg+h8zjn4dj6jb5ItWJdlVfq6vSOoa/P87s3KJmXst+45/e/Tv7sdNQC/9427IT21UZ9fBeONvKFXtU5godYYhwDWxeugP+oL4fj/7xO3KpvSWpyz6ay+RbJG8EBtvw81vQIePfcOGxqLy2q1vzrhxXa6J3XZLpTDEvskrqfpUq3fZRm6VbGI1jaLG4dcqTGUpiyriIgY9wzBdq3fZPpOvXvalE0gaMyBbjyT7XO6vgPRMNYvqCv43Umcs7MncK1UTOq9x9TdzJt1E5GCsSeYmqAiIu429NMLc+hX3L6yR+V5yUY9pJXLhpRN3tCpTWl5TLGN+x4rhPPRSdsua9ye1Lyi2z2xFe813bfgenKNO9zHG8vwtWPad3ansKzgcj2PXN1X+tOm77RouaYHSg8++KB84QtfkLa2Nlm7dq0cOnRIHn/8cfmd3/kdEbn4uvYjjzwijz76qHR3d0t3d7c8+uijUlJSIh/5yEfmpQGEEEIIuQps++KfhSiHXIa+EyGEELIEWSi/6VJZS5RreqD0la98Rf7qr/5KHn74YZmYmJCmpib5xCc+IX/913992ebTn/60zM3NycMPPyyzs7Oyfft2+fGPfyyh0Jt/LY0QQggh5J0EfSdCCCGEvFO5pgdKoVBInnjiicufunXCsizZtWuX7Nq1621WjRBCCCHXi4WK0V/KOgDzAX0nQgghZOmxkNpGS9l3uqYHSgvKnEekcLF6Rbfu4VUto5Due0VrBfzSffsh/Y8ntIbO4AzqmNiVWFY6orVaXEacbcCrYzo9Riy7z43peE9Y5REflu29oMVPinn87a57Tyqbn51DjQ9XGmOdy0/qWPeE0X3xbVllU4hhLH5gEjuirx/j7kVEXCFsU/9UlbLxtGO8sa9Ht9uM4c43Yv2O9WiNIiuM41Ks0nH1UsC+CFTNKZP/9txOSNfePwnpaG+NymPbGBfsSSsTKaSx/3z9uBx7WnWA9MZ2jNcvhPRYnplGnZ3imI5t9jZhOw/2Yf+5fFqLwTWO49/RpLUXelyoj1PWoOOh5/owzj9fgePiDum5l0+gDpTLoU11q3FcRpqwfxuqta5NpoB9Hk1pDZ1cBm3sRh00HxhBm1gUr+PNOGgdGXMkE9NtGhjHsbTqMG7dmnLQqNqIfT7noJngm8C+WXVLn7I5MY5aJRXt2H97X1qn8viNJTZYHVY2pmZSVW1c2fjd2Mfj0XJIm7oAIiIuQwfCZYodiEj5URwnz12omZELaw01jwfrm57V+5NVh3PWfl5r2wXuf4NuRsFBtIqQ64Ar5RL36/omtpbPk7Y23Cen99Ypm/vefxDSz7y2RdkkpnCOe2twP8vN6r3UZywvn1/vpYVOXMdBYy8ontI6MUVjqZedddCfyeFvWx44p2xeObUc0m5DG63mkPYhosuwkyfu1DbuCJYdNOQHJy9o4XU3bnkyPh5WNlYX7jtlp/SAuwz9q3gL7p0XTjloFFXi/lSocfCd8obvUau1L7/9g3dDOvjLEUhb5/Q+aWoxeVLa/88Zuiul57B/h7u0T9bdNQLpYoU+k89PoG6Vd0T3Z74F+/zkedS1sc1DUEQCo1i/rvZJZTPmxnFwNWun0TpnaImGsW+KFXo9uWJYdmBYr42S9RFIz7TjW5HhWu3HefK4mBMpfd7aho9rteixLDVkFhMRvE6JnlaSN3wnO6r1EmfGUDMpV499UzKuz/q5W7DPcw5nfQlOI2m8Y1TZnBvBPTW4DP2Mw89rHcaSIvbNYG2lspkzbgkCDVqnzmf4K5Fp3C9NPV8REXHjb1ZRr42ag/hb6t3Yn3NVDrq7HqOsaT1Opo5t5Q/1PCr88hvmX8FJ0IssBq7pK2+EEEIIIYQQQgghhCzeN5QIIYQQcv2wX/+zEOUQQgghhCxlFspvulTWEoVvKBFCCCGEEEIIIYSQa4JvKBFCCCE3ARTlJoQQQgi5OijKfXUsiQdK77n1iPrtRxfWQtrvMAjf33sbpEuXaWG53DkULLO6UpAOvqyFJSNrDYHtOS0iFgqiklzsPIoPbt3ao/J8JNwH6UeO36ts3BMoErj/pTXKxqrAzjAnaGyZyiI17bOQnjmnBeH8hkBl27ZhSJ8/qcUdTVHLEgehwRIvihxOe7UQXroZhdisabTZsLJP5Tl+rAPStsP7eGWGwF58uRaW+8Bdr0F6LItjmWnVyyh6Bvsv3eAgwmuICGcqDQHDvBbGO/Myil6bAsciIlYWG2o5aOXZvSjUvHYzin2fOaFF7gu1OAY/Gl2tbNLtxjg5CDVWLtPi2G9kNqZFpE2hzntvPapsTidQsbDsNI7L9CYtsJ/Lok3FET2WCWNa56sdhGSX4by2DMHS0JAep6gX954164eUzYWXcRwyFXjdlNbBF3sG+88T1xO/0Ir709FePd4bO405sR/nXrFEb7q+VhSJnJ7VAromM5P6s+iBCqxfcQ4nsSem22SKu6dvTymb3DD2TaMHBSFnp7VIbKbcEADXy1IKhkBpZIueI5VvEBcuml8ZIGQeuO3OE+q358+ugnSZg+/0k2e3Qtpa6XBun8YzON2N53jtz/QandqCa9ROapHWQClep3gW95AVO/pUnt+tQn/qPx18l76uIcJ77PluZeMO/2LfaWa1Fmku6YrhD6fLlY0pLF19xwSkR49oUW6PsX152rQ6cYkP+yrtCyubZJvx0QvDh+xaZzhBItL3mnGwmF+iEZHQIJ5psyv1WX/H/XhOj6Sxful2fd4WT+B4J5sdJqjxoZ50Dc41V1bnGfkZHuQp/c0TcRvfA7Ed7pAC53DONtyGoszDr+HHLES0n7a7X/tOxWVYZzuh10bJSryHMXs8FdH3K25DwPzWu/SHfE5Gsc7Vhns1s11f1xTcrj2g+zzejjYZB3H35ErjLMwZHxHq1fM+4sX6dGzVwtiTP8MBzhki7Ik2lUWKU7in+WL6sE92Yn0vnNPjvaIb19TIHpx7OQe3qNCB7czP6D53GdVJj2ufNhPGSewyfGenNmUq0WbmHv1hHPcAzrZyH/pF2X7dqHwFznuz/iIitjHe47drm2bPlT63+UGTRcuSeKBECCGEkLeJbV/8sxDlEEIIIYQsZRbKb7pU1hKFGkqEEEIIIYQQQggh5JrgG0qEEELITQA1lAghhBBCrg5qKF0di/eBUjAv4rsYcPmT/ZvUX2/fdhbSB2Z1PLwZ/5xL6ZhkdztqA+SjGCda+64plScyUgXpLQ1a+2Qqg7GtsXqMzT10QNf3oG851s1hYuXLMX40OKJj2wvlhgZBVLfbJLUPNX+Ka3PKxnser3N2AGOUHaR6JF+OMdONpVo/p2eqFtIO4fpSV4s6BRNjqHVyfFzrN1kFDNj9zJ3/qmz+cXYj1uWQDqyO5TGW+fCRLkgXteSTaKUFTX0t9sVkEueVBHWscLoR+9M75aBBYAiKVXXOKpupIa2RBddt0fozds6Ih5/QWkfiNzQyMnow/ZUYg17qwfk6O6Y1KApleN1X/3mdsskFcbwr757E6+7FeSYikjOkg1K3zimb2lLsi/+j/iVl8+Xz90PamsQZENHLXY3TxJyOQbcMyQHLeKfUdulNYlU7xu8ncnqCjp2ugbS3WesU9P64A9K5jWhTSOm511KGGg8DGb0SvKP4W2BlTNkUDqGu0oZ7+iF9bFiLR7lnsT5p0e22DNGJ9tJpSA/5jTUoImWl2O6SSr03Rk4Z+dr1+uk/e2W/zOT0NQi5HhSDRSn4Lm4cL+9Zq/5+445eSJ+a6lQ2RWPZ5pN6HRe6cA5bEbQpfkCf9dYgnttrm7V+z3QafafRBlzH5/Z2qDx/4sffnDQ1c+X4Y6l22yQVxjPXM+vk1SCe53Hfjm3Q57a/BzfuwfN1eA2H6+YMLcyWsriy6Z/AfSfoUN1QPe7JiWHcW8+OaP2mgNGET79H+07fnt4G6bn9Wksmkkcfoecg+leFgIMO31XcUJUbbUol0GcolDho9bSifxAYd9AWNGRrfMt0n6cdtGLeSL5D641J1tDHHHfwyY3jyvRfRUT8XsN38uIazAw76EQa8/7Mt7QzUizD+rl3RiBd+WxY5Yl1Yv2m7tJnWjiE13mkea+y+eKp90LaN4F1mVnjcI8TNHynpNZhdJtTQPlOKou0dqG2WTKnx8k6hr5zpk23e/p7eG+UuMXQEkrqNtWE0GeYmNN6joFx7PPCeu1nBPfjJK7diXtsz6AWD/NNYX1ytkO7jbXaHpqB9Iw/rPJ4Q9g3wWqtzZQ7ims3s1zbTJy44rtncvrvyeJg8T5QIoQQQsj1w379z0KUQwghhBCylFkov+lSWUsUaigRQgghhBBCCCGEkGuCD5QIIYQQQgghhBBCyDXBkDdCCCHkJoCi3IQQQgghVwdFua+ORftAqSKUEr//oshj3KMF9g6+ugLtuyPKJpJAcTJTVFhEpK0ORVlnAigiOHYWxWtFRMpHMX1karmyqVyH1y0aony5BgfR6wD+lk1qYTRPAEX5AhEt3JebwHx2FeZpqY2oPMNitDOuRTjnWrTY5BvxxnVdihn87bRPCze6Y9g3KzYOKJtTEygc6SnFvtrWqPOcLUXhyxNZLcrcM4vtzoX0an5xaBmkfYZgdTqmxX+b16O438CsFsGePoeCmp4c9pUrqscg34WCjwUHFU6rCkXrbFuPy/bVPZA+OoWi5tkRLbjtrseyPVF9XVOaPVup1+70MezzxAoUvvSGtUB0dxUKbJ+OtyqbtpVjkO6fxv4tdum6BCuwTU7tjs7ib4+2P6Bsbuu4AOmZShTH7BnFuSgi4p7C8Z2J67KDOZyP7lFc27lKvSbPnG+BtKtC96e7GdtdX67FR6O34bwuTqIYabBKC5hPJtHGcpgi228/Bemzcd034x04Vuf2dEDa7sI9TUSkaAhuO33VwJXE9Is9hkCpw2Ge7UHBz5qNY8pmsgLr6xoLKhtxWi6EXGcCFWnx+y/uC2mv9iHO7kMRbs/qhLJJxXD+Wnk9eRsaUHR7Noj7V+JEWOWpHML96sJ4u7LxbkGRfss4F1PNes+zTBXppINra3zkInhYm2TGcE/OVuO6rm7QQuMRCUPa7eAHxXUzAX9UbzwFw3caGND+iy+CQQaNt44qmwvDuL9aIdw7N7ZodfKeMizrUEZ/9KR3shrS7grdhgO9ONfcbXgWOX0wJrwVP4QzOq3FiedOo5Cvxzji/DM6+CK5EtudL9E2uRq0cfqczfoNfZA+NoE+rXtQ+4PFJvTJ/Po7Kep8SOvvQ0jmtTCkk2vwDC5W6fuKTuMeZyiqffDq9UafT2A51ko9p12V2Oleh3YXDB/ni8vfr2w2LMMPbkRqcB/pH9L3YIFx9DOTZfq8DRvazYFh46My1Xq+Dp/BtZKv1H6G1YYXrq5IKpv4veiMuEeN+tVqn2wmYfh/Dh9cWX3feUifi+o9IWpqrv8Y1661Ul+3aIrjO/lOGVwvh07ix4nMD8iIiHhP4ZwIbtN9lazEsjzDetU53MKQRciifaBECCGEkOtI0b74ZyHKIYQQQghZyiyU33SprCUKNZQIIYQQQgghhBBCyDXBN5QIIYSQm4GF+vzt0v1HNkIIIYSQiyyU33SprCXKon2gFJkMic93Mf42UJlWf583NEDiPWFlUzaFIxNfp+OLgy78Ld6HsdklbVpfICmoE+IUbzoRQd0N3wR2db7FCPAVkVI//pZNmKIgIvUVqHUytaNU2Xh6MBbX9mJwa+I5HZPs346x2PlBHZPsmcQY5LShZZBu0/0rOXwJ7q7OHmVydLYZ0ifHdIy3dxhjsQvtOP77z6HOkYiI5cd2/+PULcqmZBDb1HSb1kfpG8Y45UwM6xKoRU0lEZHeUczjDuhY7EIQ542vBeOLN9SMqDyRHI5Lb5/WEsp6sH7T+TJlMz1m6BIYU3jn5qMqz0s/2ABp746IsvnlusOQ/sfRLcomZuiUWQVDdymhY6hPZhsgbZfpgO1lpagD0DeJ89xXpteciVMceKoV5/n29l5l8/KAoUsygWPgdbhuwYhb93i1NohnK673wgncn/IZ/ZJpdUsE0tOzevwLxrocHdI6Ri6jOms2o07ZRNphXvWjVpinTussvfzyaqzvmillY+oHvPe9ByD903/aprIkbkVdgoKDZp6JL2TMiT6972VrsCOiGa0VUdsUgfTEuNb9sPxXrmNnHfZKQq4D2fESsbwX9x9Xtd7zzHM6cEqv4+oxnPPTW7SPE3DjdYrnDQ2QLr3245aha+mwRFPT6NOUjOFelXLQcvQb+pOZhNYfrDS0Tibfpdd6ySlsZ6YRN27rB+jXiYgU78Y+9vVpv807jtdNtOHfJzp1/1rG0G1bcUHZHDO0Dy8M6n28ZAA7OdWFZR0906Hy2D5s979N6HO83DgGA/fMKJuJQRQCsgzNJFednp9jQ6jNJKY+logUSrANxXbc+1fVaS2pWcN3mjpbr2yKXuyrRF7rGh4d6lC/vZEdt51Qvx17ehWk0+/SWjIfbD4E6acHtiqbuSCePVbeOP8dtE8vZAwNrXI915aXoUbl6Kih+Vn+5ueV5SCxGke3SOkliYgc6cXFEBzFMQg6+U7G0nX5deHp23FOeA5hpry+rZRAB97vJaf0/ZWp6ZYY0PqobsPdb9qO83EqpffcdC/uLVa9XhunfmbouW7Umm6m77TjV45A+tX/sU5lmbwb03b2zYOXbGNOBM5rv32uzlinae07lbaijxsf03vsG/ejfNZhQpBFwaJ9oEQIIYSQ64clC/SVt/kvghBCCCFkXlkov+lSWUsVaigRQgghhBBCCCGEkGuCD5QIIYQQQgghhBBCyDXBkDdCCCHkZsC2L/5ZiHIIIYQQQpYyC+U3XSpribJoHyhZWZe47IsvUJX6tCBcqAyFvPpz1comXoLNs6JasO60GwXrioauWNHWEY1FQ0x39bJhZXN2CkWZV2xFMboTo1p4Om+IE3ti+gWyYXcY0r5x3aZCF6rNFWdQJDLWobKIPYNiaTXds8qmaGN9MhEUrHNP6rqYgacv9KxwsMGkf0IrdWbqUXTPihvijlk9TrYpWOgg3Lf8rj5IHzvXpmxcebx2+zIU7u6b0nNPCkaeKt2ffUXM5zqM/Xmgrltf19Cjc1gaUlaHgo8JB2HBshq0SWVw7H5yAAW4RUQKhnCoZ04L7P3vf7sH0qW3aaHOXBmKJWbGUfgyWK9Fzst24xye2qjXxk8HcG7Zxrjl5rRYasEUZXbAM4vz8WWrU9nU16I4YvwCju3cMj1QVgz3p2xc16+rbRrSPZ1o4x3UeaaHw5AOTOq1MdeEa6HgIHJeKEVlyZPGnuUk3Fhm6MgnK/QRYzVjn48N6vVz79qTkP7hyFpIf+a3fqDy7HrhA5B2O2g3lhparUlDqDVfp8Xz3VFDqHU2rGxsQwjT05hRNsXiG8ZhoQLyyU2HKyviet1v8fn1vlNWjnNzPBdWNrlSXNueiN5Dej340QOPz5jTDr6TbXyIonXluLLpH8f9oOG2CUhfcPiAQLGA9fXN6rJnXfhBg8Co3r+SK7C/PFO4f0W69XWtadwfvKvjysb0I+1Z3HcC42/+AYGDJ/WHR8wuNvc3EZFUE/a5O4ZlOflORWNvL+qjXureg5v9hdNNysZtnMG1K/EDDKPjWtDY/BhEQ21E2YwWMV/lK+gPnmjUZ7TpOwXyeg92NxhKzeO64e56tMmmcY7s34tnlYhIboUhTpzS5/YPvnMHpIP36g8CFUI4P12jeJ1ik1aarv8edujErVpo/IUL6Gtaxri5ZhzuMyrwrHQ7iL/4Z/DHoz0dyqaiwVgvZ1CUObpSH+Qe40y2He7tGrrQ9+xbgXOkpE/7Jul+FMsO6W/0KEH9XJmeR6Y/1WvsWS6Hj6mEBzDPTFjvCeYHCbK95cpm+2b88NGP+tdA+q9//99Vni88+yDWz0FgvWwIf0zksD/nGvQ4eSPYTmta34soN7LV4abmjfdTLvpOi5VF+0CJEEIIIdcPy14gUW76fIQQQghZ4iyU33SprKUKNZQIIYQQQgghhBBCyDXBN5QIIYSQmwH79T8LUQ4hhBBCyFJmofymS2UtURbtAyVfXUp8/otxsbEzYfX3Kkq9XMdv2n78zZrTL2QVoxiD7DIkNApFncc3i79diFYpm3wSY3pPxFshXXFGBxwnbsH6Fqp1LKlvBONWy0Z0u3Oz2Kb4Sox99U7oYS+0oK7JTEzHuoIGiIjYRhywQwi15FEqQFxp3Z+WqQu0UmsQlLixDZmDYSxHh4WLaznqBGXSOs76+Kl2SPtjuhVmjLRlmLRUR1SeoV7U0JpMlikbl6F/lViGbWyp17pLQ4bmQPnyqLKZTWJn2G69QyWSOEfsLMZrl3fqMYjFcDD9R7QOQD6InTMRCSkby3ins6kTdRXSeT0/pzdgm/y1c8rGXKuWsZjtmIOGkhvHoGOV1vRoC2Is/sCcXu/9ffWQ9q1FHagSl16nWWP825ZNKpvT/ahL4TP0T3KV+rr+CeyHbLfWVXBNG1pM9Q79aWiQddYaek7DDSpPvhTH39/nUzaZDtxrGgydKBGRV6dQqMBrrP+/OvKAylPSgut9blpvCrENhu7DhKHF5tPiAUWfoTnioC9gG5pJjRV6/QwPvUEb5s2luwh5SxQbslJ8Xc+oeEKfOzEbf3OHHTRADOkYj94exDOL+7SpNVgo6LM0aGxxg7VaQ8dK4HX7z+A+U3tCL8CpOzCPXattSoZwHYf69SIMTuN1Ztdh3wRHdZtSNVhWPBpUNqamotv0RR1uIvKlhvZR2kG/yfBXc+v0QAUMMTn/S7gvZvUUkcwK7Bs7rc/kvmPNkA5GdCOyFcYPRhNq6xz8lx6cE9NJvY8HxnAsI4bOTlVTROWZGUG9mZJVeo/OJYyxc7hDKhj6nZapN7Vca0AWI7igKg9ofZyccXbGHfRmTP2YSkPr1Ml3mrgFfTC7Xuv7WeZ9jnHIuSPady56sKzKdfoc7yg1dIyS2neaPoe/FTcZOmYOYoieUey/6pVaq3PgHPpkrkq8bqZKz9egoZkUW6M1Fb2GVmyhUe8jpgZVs6EDNtyP+nMiIllj/EPn9HqPL8O+CHXp9fPaON5rur04lrte/SWVx92OPmJhUvvKU1sxHTBcZdvU0BO5fA5dwpXTbUq34LhUh5PKJtJ3ZSNx5RzEMcmiYNE+UCKEEELI9cOybbEW4CsiC1EGIYQQQsh8slB+06WylirUUCKEEEIIIYQQQggh1wTfUCKEEEJuBoqiPp89b+UQQgghhCxlFspvulTWEmXRPlDyHi4Rr+f1WFUtwyKNW0Yh3TtSp2zcfox/DTvorsyMYJB3ZUcE0tNjZhC4iMcIJ3b16Fhny9Q2KcO6RNbqGGqP8aabXdTxpoFpNJpdrUzEG8F8riSWlQvrGWvNGlonYa3f5O9Hm4KhzVIs03m8Rsx3NqE1VcSD9UkkAsokFMKxy5q6Dw4CTn5Dt6atTmvUnJ1DfYZMs8NqNq7d24+x2VKi46wrmzG2eXa0XNkE2jDW3h5CrYBIhe6HikrME3+lWtm4jC72OazyrBHC3dkyAenB01ofp8SYVzmHdZkxtSty+iVI9yzOx9FprEyxUvenpwbj/pvKdez44LFGSOer8ToeB+0bU7ticDasTMbiOHaZSa2R0dyBOlBjp7FNy9cPqjzRNTinB8/WKxuXoaPmO4pl51bqvsovx5h+/yk9jzLV2PBiv9apqF6Fmgi9szjXTO0IEZHGrbgv913Q80jiuIFGgro/t9Rif706gZpKTpojKUO7xBvT9csbR57PmEbZJn3h0ibU2qgNJpTN+PM49yYc1q68cc9y2NsJuR6EX/GI331xnmcq9HwO3YbremxInyG239BdrNM6bNkh9Ht8y3GdzA1pcZ68H+d94LT2B9JGdQpleCZPbdK+k9i4D1oO66tkAts0tVHrwvhnDK0jQ2YnU6n702PoLuXD+qApu4B7UXI11jet3QOxDN/J3DcvFo42dlz3p6m7l64ytDAd4hTchk/W1KT1cUZSqBOZaH9z32niPA5uoVTnKWkztC+HtX9d6MA2eQdQ8yVWqfdfX7Uxh/fqTi81us928J1SDdhhpgbgzDGtj1Nu+O0ZfVshhisqloPejH8a535sAvWmstV67ll16EM0hLV21OxrWOdMLY6Lk26gqX06Pq37cyqKe4A1rudnhaEDmjwWhrTpU4iIxDbiWT97Qu9hRUPbrPJVXD+za/XcS67G38JH9AQwpr34L+g2+ddjm4anwpB2axkrCe3AeTR5VrfJY/g0sVI9zzc1DEP60AhqKjn5TgVDdzcQ0XMvawQ0BWaMOd2i+9Pdig2tLtX6SHP/ju2cC4eVjfUGvStz3pHFA0PeCCGEEEIIIYQQQsg1sWjfUCKEEELI9YOi3IQQQgghVwdFua8OvqFECCGEEEIIIYQQQq4JvqFECCGE3AzY4qihMC/lEEIIIYQsZRbKb7pU1hJl0T5QSq7MS853URhsdeOY+vueGUMZzXIYhWkUS0sHtGi0uwJFwzpDhsDeYFjlKTRiHtsUTxQRawZFzuwEdnV3pxaaS+Qxj9uhTeP12G47qEV5c0EUo7ML+CJasFwLbM7Noribe1oLQBa7UUQ4P415fA6i58Uilt3qIO44PBOG9OYmLWB8+GgXXtcQGnRP6vomR1EQcCCiVaR9hp6eq0Or5RWNYcgaQtPLa1GQWUSk9wyK9Fa2axFp61msT9oQWM8X9QuEiYghwtepx7+kH+da6YaIspkZQlXIwVkUd6xdrsdpdAxtwid1/bKtxtxLawHVQi3WOXgex87TqueRvIx9VXG/nsN9ARwoy20IljpoudbUxSDtdVCfNIVE373luLI5FUdFzYIxTKMpLVgZOxeG9I5tp5TNCz0rIJ3oQEVCv8Oe5jHE6FP1eh/xxgxhVoe+mZjBOgcv4DgpYXwRSZp7WJVeTxvrUTTytYE2ZfNifDn+UMD6+kIoPC4iUuLH3yK2FgX2RLGhWUMctRDVApuJSWxT3KX3keIy7PPGhlll80bSGb1uCbkezKy7cq51tmjfqW/SFA3W69g3gWdINqhdxYLx8YSuCjwzTvbqdZJuMcSzHXwn9xTuM+4EnjNNK/THNZJZXLcuB98p0YTnV7FEq7umDJFoy/CdXBV6P7OncH/wTevNNLka9ybTXynW633c/ChLdUtE2UxN4h69rn1I2Zx9tR3S6QY84/wTur7FIUP0eMZB5NqH9csu13uabahyF40POTQ3zqg8k8fRx/V36Y8glP8r9t/UJuOsL2hR4fwMtim7XM+R8nPGh0e2aBFh9wCKhI9N4yESXhNReaKGv1VzWPdVssOYa2ntX6XrcewqThs2nXp+hvbg/Kx4SPtXU8Y3OWxD7L3o4B+UNOG4eN3ad0qeCkN6++3axzkRMT6mEsSyxxMO5+1pPNs33nFO2Rw8sQzSUcOlcAV1fV1u4wNBTXrfMz/k4eQ7RaawfuY4pav1/EzmjI8e1eo5srZxBNLHe1uUzWtnOiFt5Y2ynD64ZPiRmaL+SIsvitdJ43YqrlndV/YYrtMJj75uYQWOd0VrRNfvjfXI6PqTxQFD3gghhJCbAdteuD+EEEIIIUuZhfSbrsF3euyxx+SWW26RUCgkdXV18tBDD8mZM2fA5uMf/7hYlgV/brvttuvdQyLCB0qEEEIIIYQQQgghi549e/bIJz/5Sdm/f7/s3r1b8vm87Ny5U5JJfLPyfe97n4yOjl7+88wzz8xLfRZtyBshhBBCrh+W7RwdPh/lEEIIIYQsZRbKb7pU1tXy7//+75D+5je/KXV1dXLw4EG5++67L//u9/uloaHBzH7dWbQPlLwjHvF5L8Zf9l1oVX/vWYdP4HIFraHTtRLjTS+calI24S4MiH11GPU8Hth4WOXZO4mxucmUX9nYRtjq6mWoG3LuNd0mU8og16RjRV1eQycmqYfQjLWPn8Bg1zmXrm95DfZntqADg/N54zcjzrrEp3VNIsMYOz4yXqtsbEO25FxU2xTKMd7ZM25kcliFgUkchPfv3K9s/unwdvxhMqhsQo1xvG4P2pzP64XqncOykyfDysa6B/vcfxpj84s1Os7a8mI/OGlQ2Oswjn5mVOv3BCfw2sEW1CSaPIe6QSIilqGZ4bk3pmz8GZxb7+o4oWxOJbC/BieMGPoeXd/Ge8YhfX53h7KxjZ/cPuyrglevlakpLMuV0i9tFivwOs/2rFE2vklcG+ZulMpqbZ6yZbj3vPTqamXTshr1QiaO4trIpfV8zRvSIN56rTdV2ZaC9GxSx7aLoZsx14n70ZomrQM38gzua/atWtPh4IUOSFterWUSrsS1EY0b7ezV7c514zj5pvQe1r4Z9+HzPXgmKL0B0XvPqmbd7jPnUctgPKrnsP2GZmaz1AEg80PpgEv8nov72PRZfTa5NhsakHm9L9at/8X7joiIbzlqqBztw7X/nluPqTwvjKHvlEnofdE8y9tWog7U+H48L0RE+U6pVq2P4jM2ZXdCr/VAB+479mHUQkm5dH299ahJU8g5iKoYeoi20eV+v94PcgO4J8dGK5WNx4cN75nV45SrxP01MGbUT3eDlI7hde9+6DVl88OXt+BlTJ9MRNwt2DehE1j2WM7U8xLx49Ek1pFSZTP5XvQ1g4asYbJWN8o2zxmH+IzEVsOHHdFllxnbf74d11PKwdcr1uB8TL5Pn4vuNE7Q+1acVTYnojj3Z8ew/9yn9DnufgB1qia/r++D7GXGfYUP+6ro052VHMe14Uk56FZV4XX2nlylbILjhj6i8feZjL63867ESXJs33JlU7UedQxTr+L6yaX0fLWMKZJr0vc03i70p2JxrS/mMXTgoivxwl1tEypP8n/jWMbuViZy4qyhN+nTvpO/BtdcOor1Kzmr251dY+wRE3osq2/HOo+drIO0y0G3LBfG67a1af27oTN4ndlprZkl9J2uimj04j1FVVUV/P78889LXV2dhMNhueeee+QLX/iC1NXVOV3ibbFoHygRQgghhBBCCCGE3AzEYvgP9n6/X/x+/TLIJWzblk996lNy5513yrp16y7//sADD8iv//qvS3t7u/T29spf/dVfybve9S45ePDgL7zeW4EPlAghhJCbgYUSzKYoNyGEEEKWOgv5oZHXy2ltxTd+P/vZz8quXbt+brY/+IM/kKNHj8revXvh9w996EOX/3/dunWybds2aW9vlx/84AfywQ9+8PrVW/hAiRBCCCGEEEIIIeSGMjg4KOXlV6QTftHbRH/4h38o3//+9+VnP/uZtLS0/Fw7EZHGxkZpb2+Xnp6e61bXS/CBEiGEEHITYBW1TsR8lUMIIYQQspRZKL/pUlkiIuXl5fBAyQnbtuUP//AP5bvf/a48//zz0tnZ+abXn56elsHBQWlsdNAifJss2gdK+basuF8XHCwO6ydzVgFF4kor55TN+SkUOSuG9IxoLo1AenoCBcGe371Z5ZnrQlEw75gWjSs0oE1fFAXhslVaNNIK4G9VFSllM53F+llZLZaXMASAsy1Yl81NQyrPsaMdkC7qJok3jqJrpvRkusohU7nRVwEtqLa1dhDS+4+sVDZmWa5W7Ju8gxBmMYnz5h9P3aKrZwhuVwV1n48nsM/Tncarjw5idKZIqLVcX7dYxHzFEsyUj+l539GConZ9Q1qEMxPB8XdVaQHIuQJeO+TCuec0/mIIwN+/4qQy+c6x2yH9w9mNyqaldQrSDYbwdDKnCx89Ug9pWzdbXDnsP48H21TZiiKNIiLRORQsLCS02LMngGLk+biunymg7x9Am3Rcj6W7Avej2pVTyiayz9jDDF1Wp0NOCUtm9TY/nkKxfJeDuGNNC/ZXdg8WfjqmPyzgrsc5bc/odgfqcK92EvPfVIl71Avn1kE6W6P3z5yx3oNai1z6Iig27zbE892dKMorIpIxxDvrfHFlc9qD/Vcd0teZmrjiHNhZPnEh80OyqyC510V0gwN67RcN38ldo8+HoXFc61a5ft2/PYQfFTg/hgLGr34P16yISMYQpy0Z1uf2XBPaDM5iXexqXZdC0LhuWPuD6QzWz6WbLXNpXOuFNrzuqnb80IuISO+ruA866HZLcBbrbBtuW7pW90PBOB/cwbyy2diA++TxA8uUjXlaZdpxv7WzumxPAiv4b0e2KBtfK/ZxOKj7fCqOfR5Zgde19DYOArwiInOr9PlgG75TvtTwwWL6jK5vM8Sp+6qUjTWL/kC+RvurSUPEvtSNFc44jL8nju1+31r9sZJ/efVWSP90Wq+fqk48k0s3RCCdyup2Jw5gO4v1ykQso5ku4zwLdqAAv4hIwvgYkeUksG/c07iiej9KtaBNWS/2VTGmr5sP4+ItWxtVNoWfoo9TNL4z4/g1LeM3O6PXRiyJYuS2T18o2I79FfgxiqUPRvTNvLcZ0x7tDkqxAdsd8Os9YXMN7gmHTuH9VLpO17eYwHlTktY2Q1NhLNtwcbLL9YZqp3C8GwL6Qz6DXhSHLgvre6XU6JU+d7rnvVn55Cc/KU899ZR873vfk1AoJGNjFz9gUVFRIcFgUBKJhOzatUt+9Vd/VRobG6Wvr0/+4i/+QmpqauRXfuVXrnt9Fu0DJUIIIYRcR6ihRAghhBByddwADaWr4etf/7qIiNx7773w+ze/+U35+Mc/Lm63W44dOybf+ta3JBKJSGNjo9x3333y9NNPSyjk8DW9twkfKBFCCCGEEEIIIYQscuw3efgUDAblRz/60QLVhg+UCCGEkJsDW9Rr/fNWDiGEEELIUmah/KZLZS1RFu0DJWvMJ5b3YuxsoUnHZob8GPQ7d1qLV9lhIw54QsdenqtAjRIzdjzn8FaYf8jQR2nQgeBuH/72my2vQvp/jN2j62tjHPjGdq119NOhtZC+b52Oxd67D2OvrTKcoccmO3TZ5kyo1HHrxVq8TnEcY6j9DivBM2bEP3fomPSDP1sFaatUX6esC2Nvk+cwPtqu09d1GeHFy1vGlc25MRTj+aPWPcrmsdi7sSw/zitrTsdZV66bhvT0OR2vb9dhH5d1oTZLoai1mcZfaYC0O6z7qqYLtQImBnTZ/jqMU3Z/G7UDvBt12XljHv3DSzuUjV2J876xLqJsRmaM2HZDk8gOaH0ZTzsK4tiTWpunUIr5TDWByYkKMTG1Ddxp3e5sEq/0/tVHlc0zPeshnTZ0yyyHWPxkzNBrGCtTNsX12O68UZfu5jGVp/+wEYw/5bDNNxp76ojuz+kIapcU1xn7nIN22D0bT0H6ubOrlY11CvUESrZpvaGfHcR9rlBuaBTVaR0jUz8i1ar3e+8g9rmpmeRx6blXGkabSo+O8bfy2BcP1B1XNt8rXNETy2T0fkXI9cA/7Ba/9+Kan2vVGht+Q3fDfbxE2diVuNeX6m1GeitRlMTUWEzr7VbpoyRb9fll+3Gf+XDnAUh/Z+gufWFDlGjT8mFl8srgCkjfuuWssjnyHNpky7FNfRNaN842Dppcle7zvKFb4h3FTA4qjBIcwTMju0xft2d3F6RdTlEMK3D/8p9CXaN0o/ZfPYb719ShBV1GhnD8/8/OnyibL0Teiz8EsR/cSd1y7xb09QqntG+facS+sFfgnux18J3m9qIf5KnSNsEVhp95QXeo3WD4bV9DvZz8bTpPLoRl/eD57cqmWI1nT7hB681MTmFfuGM4R4pBh7vRq9B8zYcwn3lyJhx8E1/U0B900CzMlaLvcd8mfS7+5CSe9cl2oy4OPlnB0FXKn9D+S3KLsV6Mudbcpuf0zCt4P2BNar8t24z9GRjU/Tk3i3MgsdnwKwp6nG699QykXzqutWTLjmG7vTu0btnBlzBfvgLLCjZqfytt6GzGOxy0L/sMbd5l6EO63LpNAUPbuNKryzb1u36p8Ziy+W5h0+X/L9J3WrQs2gdKhBBCCLl+WLYt1gJoASxEGYQQQggh88lC+U2XylqqUC6dEEIIIYQQQgghhFwTfKBECCGEEEIIIYQQQq6JRRvy5mmZE8/rsf6uEzrGP96Nabtcvybmn8LnZfmVOsg3FwniDxUYT76lvV/lea23A9LeiI6zzRv6IiP5MKSLDjox7jms757Da5XNPZtOQnr/c+uUTa7J0JKJ4nWztToW3xPA35xi+gumbk01xrI2hLSuyYVK7N98yqds/KsMTZKhoLJJ5zBO2RfD8Q506bFNVeH0vjBVo2xa62Yh/cUfPqhsSjdEIJ2NYT9Y5Tqmd3wSBSQs3WxxTeGPiSKmg20Ymy8iUlyNfdUa0nH2/ZOobVDRpG2iExjjPfpLOP6uGb2evA0YD52Z1OPk8uHcG50IK5vqamxXrgRjseOTOl7fZWgD+Ft03/h+ivvEzK04Z1oaUVtKRGRiGmPm861aO0wMfRxTL0lExErjHuCvxXGqr9P1nUhiO72n9T4Sj+KccKewLhcSTSpPoQHno9uj95rKPdg307frPcHlxb3QymH9rISu73PnUDPJFdTXnWvDsWwORpTNZAvqfLSGopDuP4daYiIixRJsZ02tnvdTNmpQNJQaGkqWgx6ehfV9LdambErr8Drf7rlN25y+sh8V8zdIB2ChPn/7Fsv42te+Jl/+8pdldHRU1q5dK0888YTcdZeDZg75ueQ6suLyXez/ikP64ImuwfPLU6HHKjiB6fhavY6tGbxOoQrX35ourQF58hxqEPmntaeRy+G5PZxFLbdCia6vuS+++orWH9l2K2omnfjBCmWTNiSSfLPG3zfqvVQCxj6pLcQzgfttttrQGizX58NYDfavndLuenIdnlfeAa19ks9gvtCsoYW5Qp95qRo82yOjWoexpgH35P/nn35J2QS24jmYiWI/5Ct0f8YMvR63X4+3bwLbZBeNdKf2BxPrcc+trdD+6vhYGNKBVq1RkxvFvhn+UD3WbcZBf9LQgXWN63Vpe7CdkVGtHVVSg/2ZLzXeCRjTPlnRXC8duk31z+B1xu7C/qxuwbEWEZmbDEM61abPTsu4DzL1kkT02rXrcT5WN2ndnek4+nr+WScdI2yDWc5EDH0/EX3vZHv1/Gz8Ee6Fo/c5vJdh5suhjTem8+w7iXuWXaL7M96F+TaUziqbY23YN/UV6AdNndb3QUVDH7WkXvf5nI0+WXX5m+tPugzf6eCs9p1chp7nd05ofbGqY1fGzlPQfue8s1B+06Wylih8Q4kQQgghN5Snn35aHnnkEfnMZz4jhw4dkrvuukseeOABGRgYuNFVI4QQQgghPwc+UCKEEEJuBmwRKS7An7fwj2yPP/64/O7v/q783u/9nqxevVqeeOIJaW1tla9//etvtbWEEEIIIW+dhfKb3qLvtFjgAyVCCCGE3DCy2awcPHhQdu7cCb/v3LlT9u3bd4NqRQghhBBC3oxFq6FECCGEkOvHQn3+9lIZsRjqN/j9fvH7tc7L1NSUFAoFqa9HPZL6+noZGxubv4oSQgghhPwcFspvulTWUmXRPlAq8WXF/7qwZFq0KHdrVQTSE+frlc2yHSioPfyDVmUTazcE9Ix3to6/skxXrsYUq9UmVhav+6Pzhhidw7thoVZ0vst8Wiwxlg9AOtWuxTLdPqxf1oPD3FgTUXkmoijSHCrVooa13dOQHoyHIX1hoE7lMUX5XEk95TJzKLLmbsgoG+sUzoF0LS66QkyLETYux/qOzWiRw9hPUJjPf6cW8p2dxL5xG0LDxaQWBBQX1s/2a8G6Yhn+VldliOdd0EKYtjFv+tMOZRtFRWa0yHVVvXGj58Y2TcygsLeIiO8A9nGuRRft9uJ1CtN6XCI+/M3vf3OB4sI4zvtEWM/7hveiQOFfNbwE6b/pv09fN4Dj5PXp6+YE52e5w9qIDeHcsm2c98nvayHE4PtQFDTrMJSeCtwDOjtwTp8d1vueO/rm2/osamdLc40WLB+eCmNdDGFZadX9YE/jw4Ji8c3r8uqx5fo6huB/3wUU4XZVOYinz2FZ0Z5KZdK4cgrrZ4zT4Bkt9l0w9FNLG7SAbv4U7hF2k55HqcYr/5+5QZrcC01rK565n/3sZ2XXrl0/196yDIFW21a/kV+M35eTy8/sHL4GUVeHArvpM3qd1LwLH+Il/7fev2a7jXExxqn3BS3AatXhfutyWAcuw3d67gxuVpaDJqu7EwViS336wvEcniExB9fO9qPvlPZhYRV1Wsg5MotitYGQ9l9qVkcgPRrB82Ligj5vXYYmrzumG14IGh9cadLtDh3DOZBsxP7NR/UD3rBR36zhA4mIWM9gG3Lv1mLP2TH024ql2Ch33GEwjWlVCGiTvOHjVtTg+M/1aF/PbfhO43NhfWHjXi7j4L8EDZFov+HzJI1zU0Sk6kU8m2Kdek+zjLnnndJrN+XHzjA/puOEdxivYwrCi4ikfwXPtL9s+Rmk/6+e+1UeV8BM6+sWMzi+gXLtMxQSuH6Kxhi4n9ITwP9Bwwf36TlcrESbpm70D4f6tSi3N2LemOkbtemNhmB5XUTbGB+9CYxiP2Q69Dp1T+F1i07i08a0OXWwU5kUjfvTybO4t+RrHD6wkMKyCqf0PUP5Ojw3isbNyPQxfb9S9OFgWs16b/QfwbHLt+kHKvG2K2VlcpbIQWVCFgGL9oESIYQQQq4jtizQV94u/mdwcFDKy6/c3Dm9nSQiUlNTI263W72NNDExod5aIoQQQghZEBbKb7pU1hKFGkqEEEIIue6Ul5fDn5/3QMnn88nWrVtl9+7d8Pvu3btlx44dC1FVQgghhBDyFuAbSoQQQgi5oXzqU5+Sj370o7Jt2za5/fbb5Rvf+IYMDAzI7//+79/oqhFCCCGEkJ/Don2gFEmWiD93UbMj4CCh0D+GcaG1wzou9EQPxvB76/WFKrswrnZq2tDCcOk4Vm8Uf8s5xK2X9GDXpoyQ7juW9ag8+wa7IB0VHb895cd4Yyvn8JKZEWvvqcO4Vad4fcsIf04W9b8kRyoxrtadMMqucNBzmsF+KOgmie3Gd/yK07pse3UK0mE/aqjET4dVnjEPdnow6KC7IqgLE5vQscPhszhvsrfheM/l9Rj4xvC6VldK2dzbgHPg5e9ugHRVSusuTW43NChc+v1Ia9bQuqnW7c7kcVxmR7GvPPU61vndW49B+vt9G5SNGJo0pUPaJFaB/VVRgXH12XK9LQX6jDkxrm1y23Hef+EsfjGq6LBWWron8bLHtQ7Y7beehvT+oyuVTVkLamuY/Ru9V+8ROWOvkQ493hLHsZzw4/z0zDroapQZc6Kg973gOP42ckFrpJQaWshzq3FOlBzW6zSxBvcAy0EzbfOKC5B20qnL+TGfZXTN6jot1Dw+h/1Z2ao1PYbjFZBOzaG+hOVwInYvH4F0z4VGZbPz7iOQ3vP8Rn2hVVf2APtGiSjZ9gKFvF17GR/60IdkenpaPve5z8no6KisW7dOnnnmGWlvb5+HCr5zmYsFpeC7uG+UO/hOk8NhSDf2JZXNwEnUEvM16wv5VuCel5xA38R2OZyLEbxOqlXrroRPYr4IVle2rMT9Q0Tk4IUOSKdF667MBtD5cDm4A+4IbgC5RlynqR7cP0RE/KbbM6w3keFq1BLyxrAfcpV67/dNYz8UgnpN2cb275nUQnzJ9bhvm5qFnhPa55l1417qKXXYr2yjr0a1c1d9Asd39l7srLzD2VQyhI1Kd2tf5J7Wc5A++a0VkC5NaH9r9F6jfg5rwzeDZWdrtU+bNc72zJChAeRwP3DrHcch/UzPemVjGcNb3q/XxnQlzomySuybaFj7AxXnjN9GdcOzd+N1P3/8ATTI6Ty1a1B3MXFIa+isues8pI++qs96q90Yqxz279gDDofyFM7ztJZhFCuG+SaDOE7+Gd2mnOE7mfdFIiKlw5iOucLKpnIY1/PsBpxH1a84aTNhHo95fyUiK9aiQ923V+sCFwKYzzJ88uWNEyrPeBLXe7hT+06jUbxHyBvasV4HyafG1ehfj5zVulXb3ncS0gd/uEbZpNZdmefF7A3wnRbKb7pU1hJl0T5QIoQQQsjNw8MPPywPP/zwja4GIYQQQgi5SvhAiRBCCLkZKIrjv8zPSzmEEEIIIUuZhfKbLpW1RKEoNyGEEEIIIYQQQgi5JviGEiGEEHITYNm2WAsQo78QZRBCCCGEzCcL5TddKmupsjQeKK1NqJ+qvChyNrNGiyU2tE5DejQYVjbROUOor4jvtXkSDgJ2NajUZiV0NxY2otDcslAU0qYAt4iI243vuuXT+roZQwjRchDLs81shihb0acn7OplqDTXF61UNvkkivC6sob4d4kWS7OGUbjNrtMCi2IIS9tpLfabncBxsmMocularkUYQx6cI36PFlicaUOhPtec7s9oN9bPbYgyttfjPBMR6Z8zxJ1ntUjoT/tQuDe3BVVCO2v1dVMJFM/LndeCmmUrI1h0rFTZNBvz8WzC6PNBXd+f+FCM2o74lE1jFwr+9a/SNt4JnBMzIygI7aDlKslWHANPUo9T4RDOWbfRhPDqiMozHsP+dGstQjk4icKH7rQuOzaNfVxaiReqLNXCt6kA9sPseLmyCYxiZ2RGcZ/bfCeKk4qIHDyBwpeuar3mvI0417J9IWWT34htsI31Hu/S7+b+cheKU1e4dbv//rW7sS4OYo61zRFIR1I4mMeHmlUeVwIv5OvSiprJmJ7Xb6SyR++NZwMoUFxaq/eaH11AIUlPd1rZ+F1X+svtWsLvNZMlQ2qzXvsBL66Lqc36DAl1RSAdcdibJGmsJcN38qJmt4iIpOuMfTymN/v4NtybmsMxSJsC3CIilsdYT2m9qRTn8Nz2OvhORUPT2jZ8p4JX7w9t6/EDAYOz2neyE3hh03eySrVv4h3APJkGB4Vgw3dyz2lRbmsMz3YrimdyZqWeIz5jjvg9uuzoMhx/t94WZWYNtrOYw/rWN0RUnqkkijtb09qHePncWkjP3Y71a2zQlXHHca75zjicBca9RjaihcabK9B3Goih0HCgT4/Bs370nTwz2revXIEi11Mb9DwKjBli7kPGh2dcDr5Jp7HmHO5pfC/jHlASRBtrvb4Hm4pgnlBKr43Doy1YjoN/lTF8e9NfCYd0plTQWBsj2sc1PwhjD+I9Q+f9fSrPqcMdkM7V6HuaTAv+5jpXomxi24x8GRzvyAq9771vFfpOlQ6+0z+8tAPSXgdfubQVN964sU+f70d/RkTvw6kVer0XjH3DFPuuOqH3keEgrg2Xw8d+9pxejT+sdvi40xs+3GQ5fIiILA6WxgMlQgghhLw9FvFX3gghhBBCFhX8yttVQQ0lQgghhBBCCCGEEHJN8IESIYQQQgghhBBCCLkmFm3Im2vCKy7vxTjZdL2DwVGM37Wq9Gti0QOozdK8fVLZjEyGIW3GWTdvGlV5eodRH8cVziobOYUxvb0hQ/PHIZZUxjHWvborqkw8/4LXmdyqL2MZ4bvFHLbJ9ui+OjWGnWwXHJ41GpoDHetRd2kgpmO+040YD2sVdfy2y4iRDzTp2OG5CezPkjURSK+uGFd5js82QnpqNKxsAk0Ya28d1bHYdTvw2v292Ff9uWqVx3xU63LQ3TH1GOwC2gwdwvqLiGzcjpo5h3ItyqbEixMgFdBx4GcHjThqY0rkG/ScNmOxwy16fo4exb75jbtfUjbfH94A6dZQBNI+l47fPtmL7bQddHdyphbEMNY3mtKaCb/efhDST0/uUDauHBZWCGn9G3cCB7ymGefw9JyOs0/GsT61TRFlE51GPYnSMSz7wPlOlccyNNKK01qTbK7O0Gur0H2ej2E+c2+s6NAiKT8cQm2L4rDu8+51I5DuO6T1kKbj2F9uM27e0nuYXYHzfGRQr8vgOLbBvwHncOw23VfLqwxtix/pdVl1D14n4aADVx64oquUtrROwILAkLd3PP4Jl/hfFyZLa7kMKTuIc3PO4fgqvoBabVV3671+ehx113wxPL8qbp1SeeYGsLB8ld53yo6jPzBZjjoc0qjPM98Iaqp4VmjNl/C3cc2N3xlWNi7z0obPY2t5HOkdQn/Qyccxdfdqt6HW4PCM1gBNthhrqOCgfTOFLnyxRWu3ySiOd2ED+jwbKrEuIiInZ/AcTw1pnS1pxbJCr+o9z38f7p3TPXiejWfDKo/baKY74+A7GUVZRt9EX0HfX0Rkzd19kD6W0+dOtQ8nQCaoB3yg1xhvY5jmmhy0ruJY4WC79nGTB7FvHrr/gLL5fh/6To2VqC/mc+tzpf8MbgJKY1VE4msNvdFBQ6Mopcf2g8tew7qNb1c2xTyet9lyfS6Ymk7hDpyfs0ntO+ViWL/yVu2LFCZxfyobwrE9fqpd5bEMn9w7pcc/U2+0odJBDzGGe5gvamhSLXPQYexFHUb/gING6RZcq9Mv1ymbWAw1qa5GcygXxjkb6dX7Uci4Fc5uwzaM36fr21yLZ0Duu2Flk3gvXmduTl+nPHhlr8moTXoBYMjbVcE3lAghhBBCCCGEEELINbFo31AihBBCyHWEbygRQgghhFwdfEPpquAbSoQQQgghhBBCCCHkmuAbSoQQQsjNQFFEtCTJ/JRDCCGEELKUWSi/6VJZS5RF+0DJ1TQnLv9Fobj8nBZGS3UZYs8prdKb6kSbzDkt1GdXoE3d8mlI9w5q0TN3CebxnXMQvW1EkbPlbSjsPHSgSeWp3IwCZuORcmXT8SGs30S/Vix3ZXHmB/qx/7LdDsKNBkVbrx7vLE6XHg+W7fZrMULzt0JGj1P7yjFI9591UBI1pkBNAEUNXxroUlkCvZipclNE2UQN8blitxZ8GzyD7bSMVWM7bACeChS19oxqceL0MsPGgxeqXIeCiyIir55aBmm3w1BGDWHJXFb3eWl4DtKZQRQjb2zGeSYiEs/gPI/1a+E+aUFh7H84cpsysULY7p7ILxYIFxGxjHlkl+pOdw1hHxcNcWr3gB6D77o3Y56Avu4vtx3DPKe3KJualllID0yhQL2/XwsNukuxfhMSUjZeI1vTg4OQtn/QqvLEbsHxL8zpbd53GIUb82u1CHvRmDdBQ2O3pFvncVvYf1G37vPeYyiGGujWgpoeN453LGEITTrsIxLEfdl264mUMdacncM9Ip/UZ42vBusS3aL3CHsax84T0y//xqeu9EUmfwOEJclNQbY1J/L6vmGl9NqPrjD2Ra1fLTHDxnsmrGysClzrpasjkJ64oNW+7RCupfLTeh0nDa3khmX4MZXoXu3Hebdj2bPTei8t/z3co+3zen+wDN+p/Dyu49jqNxfTt3N67ftm8behfhQatwMOQs5+7F8rq69buxb7ZuJErbIpGkLDNSUognuot03lKe/Bsty3aBHp/DkU6o6s1m3wHTfmgLm9Opz1xUrs49Jjeg7HVhp948W0b7M+U04eQRFmv8OHUmJ+Q8DcwXfyVKGP4+7FM668TQvYm75T4bz++Eu2Hdv9/QPblE2hHNs5cgHXguXgixaC+GMhpDvdvEcoGn5H8II+F//FtQnSdkBf9/3L0Hd6JrFZ2ZR1oJ87MYZ+ZdkFPe9dIRy7uK1F4/0+tCn9TcOn/d96Hxm/C/MUHe4rKw/gfJzZ6LCPGMd76bhhs/rNfae8R/uMkwfxfrS4ek7ZBN14nTlDEN78QICISKHE+ECQg3sVW4HXdWWwH1wJBz+zHuf08G16LK0pXAu+WV0/e+LK/LPpOy1aFu0DJUIIIYRcPyzbFmsBYvQXogxCCCGEkPlkofymS2UtVaihRAghhBBCCCGEEEKuiUX3hpL9+tO5bPbKa205/XagiBGSZWX1u562B1/BdeW0TTGLr+SlM5h+Yz0uX8djhFbk9Ct6WaM+6bQRfufQKLPsjEPZ5nUc62fUp2iYZDNv/sqgnXfoqxw+Oc1ljf61HF7bNq/hME66bxxCSoyHtlfTD1YeM7kc2m2WZWf1K+2W0W4V4uaQp2D0RSGvn92adXYVjDnj1fVVeRyG0mxnJqvnp2W8k2v2gzkXRUQyGWyD0zhJ1uxPh8BjZWMMrlPImxFYbBUdQt7MeW8U7b6Kvso6hBUk0wXDxmFdqusYNg5lm2/uFhzmkbnm5sy14vD6r7lvFM3+FZGMMR+d9hrbWKsZY0/wOsyRrLHmnOaIy8hmOazLghHylsniUWU7nQluY1922Gss47q2be4jevzNPncaf7OsgkPYi/WGy1waN3uh/zWKX3l7x+LkO4nD2jcx900RvWcUHWzyhk3GPHcc1n7R8BnMPeViPkwrv8hhzyu+2f7rdB2H+hXMn4y9KuuwRysc1r4rb54h+Pe2y8F3MobOKeRNt8khdPlN8jj1lXk+5B326LxRVs7JB89hu0yLgtMe7TLPHT2HTf/aMpwycy6K6PFWYy16HuUc/JeCcYC5jfE2fYGL9UGbosM4KX/a8X7FaLdRtlPIW9EIgZKiU4gW2pi+U8Fh2ps+g9N90NX4TuZYmTbmXBQRMZduzmmfM+pj3jOkHSZANvvm95WZApaVdSjbMspWrpLj/MTrmOtLRPv75nwVEXEb4236NG9lXoloH8eyzM1Rj//V7DVmWbbDunyja5cp3ADfiV95uyose8E92l/M0NCQtLZqXRBCCCHkncTg4KC0tLTMezmxWEwqKirkPd1/JB631vy73uQLGXm25/+WaDQq5eVaC5Bcf+g7EUIIuRlYCN9pof0mkaXtOy26N5SamppkcHBQQqGQxONxaW1tlcHBwSXXsUuBWCzG/p1H2L/zD/t4fmH/zg+2bUs8HpemJv1xBkLeCpd8J9u2pa2tjWt2HuG+OL+wf+cX9u/8wv6dP+g7LV4W3QMll8t1+amjZV18ha68vJyLch5h/84v7N/5h308v7B/rz8VFQ5fSZxviraItQAvJTuEVZD55ZLvFItd/GoS1+z8wz6eX9i/8wv7d35h/84PC+47LZTfdKmsJQpFuQkhhBBCCCGEEELINbHo3lAihBBCyDxAUW5CCCGEkKuDotxXxaJ+Q8nv98tnP/tZ8fsXRgzrZoP9O7+wf+cf9vH8wv4lZGnBNTv/sI/nF/bv/ML+nV/Yv+RmZNF95Y0QQggh14/LXyvp+o/icS3AV96KGXn2wn9Zkl8qIYQQQsjNzUL7TSJL23da1G8oEUIIIYQQQgghhJDFBzWUCCGEkJsBaigRQgghhFwd1FC6KviGEiGEEEIIIYQQQgi5JvhAiRBCCCGEEEIIIYRcE4v2gdLXvvY16ezslEAgIFu3bpUXXnjhRldpSfLYY4/JLbfcIqFQSOrq6uShhx6SM2fOgI1t27Jr1y5pamqSYDAo9957r5w4ceIG1Xhp89hjj4llWfLII49c/o39+/YZHh6W//Af/oNUV1dLSUmJbNq0SQ4ePHj579nHb518Pi9/+Zd/KZ2dnRIMBqWrq0s+97nPSbFYvGzD/n2HULQX7g+5IdB3uj7Qd1pY6Dtdf+g3zS/0nW4SFtJvWsK+06J8oPT000/LI488Ip/5zGfk0KFDctddd8kDDzwgAwMDN7pqS449e/bIJz/5Sdm/f7/s3r1b8vm87Ny5U5LJ5GWbL33pS/L444/LV7/6VTlw4IA0NDTI/fffL/F4/AbWfOlx4MAB+cY3viEbNmyA39m/b4/Z2Vm54447xOv1yg9/+EM5efKk/M3f/I2Ew+HLNuzjt84Xv/hF+du//Vv56le/KqdOnZIvfelL8uUvf1m+8pWvXLZh/xKy+KHvdP2g77Rw0He6/tBvmn/oOxFyBcu2F58C1Pbt22XLli3y9a9//fJvq1evloceekgee+yxG1izpc/k5KTU1dXJnj175O677xbbtqWpqUkeeeQR+dM//VMREclkMlJfXy9f/OIX5ROf+MQNrvHSIJFIyJYtW+RrX/uafP7zn5dNmzbJE088wf69DvzZn/2ZvPjiiz/3X9rZx2+PX/qlX5L6+nr5u7/7u8u//eqv/qqUlJTI3//937N/3wFc/vxt28ML8vnbfDEjzw58bUl++nYpQ99p/qDvND/Qd5of6DfNP/Sd3tkstN8ksrR9p0X3hlI2m5WDBw/Kzp074fedO3fKvn37blCt3jlEo1EREamqqhIRkd7eXhkbG4P+9vv9cs8997C/r4FPfvKT8oEPfEDe8573wO/s37fP97//fdm2bZv8+q//utTV1cnmzZvlv/23/3b579nHb48777xTfvKTn8jZs2dFROTIkSOyd+9eef/73y8i7F9ClgL0neYX+k7zA32n+YF+0/xD34mQK3hudAVMpqampFAoSH19PfxeX18vY2NjN6hW7wxs25ZPfepTcuedd8q6detERC73qVN/9/f3L3gdlyLf+c535LXXXpMDBw6ov2P/vn0uXLggX//61+VTn/qU/MVf/IW88sor8h//438Uv98vv/3bv80+fpv86Z/+qUSjUVm1apW43W4pFAryhS98QT784Q+LCOfwO4qF+vzt4nvx+R0Pfaf5g77T/EDfaf6g3zT/0He6SVgov+lSWUuURfdA6RKWZUHatm31G7k2/uAP/kCOHj0qe/fuVX/H/n5rDA4Oyn/6T/9JfvzjH0sgEPi5duzft06xWJRt27bJo48+KiIimzdvlhMnTsjXv/51+e3f/u3Lduzjt8bTTz8t3/72t+Wpp56StWvXyuHDh+WRRx6RpqYm+djHPnbZjv1LyOKH6/T6Q9/p+kPfaX6h3zT/0Hci5AqLLuStpqZG3G63+he1iYkJ9ZSXXD1/+Id/KN///vflpz/9qbS0tFz+vaGhQUSE/f0WOXjwoExMTMjWrVvF4/GIx+ORPXv2yH/5L/9FPB7P5T5k/751GhsbZc2aNfDb6tWrLwvNcg6/Pf7kT/5E/uzP/kx+8zd/U9avXy8f/ehH5Y/+6I8ua66wf99B8Esl71joO80P9J3mB/pO8wv9pvmHvtNNAr/ydlUsugdKPp9Ptm7dKrt374bfd+/eLTt27LhBtVq62LYtf/AHfyD//M//LM8995x0dnbC33d2dkpDQwP0dzablT179rC/r4J3v/vdcuzYMTl8+PDlP9u2bZPf+q3fksOHD0tXVxf7921yxx13qM81nz17Vtrb20WEc/jtkkqlxOXCo8Dtdl/+9C37l5DFD32n6wt9p/mFvtP8Qr9p/qHvRMgVFmXI26c+9Sn56Ec/Ktu2bZPbb79dvvGNb8jAwID8/u///o2u2pLjk5/8pDz11FPyve99T0Kh0OUn5RUVFRIMBsWyLHnkkUfk0Ucfle7ubunu7pZHH31USkpK5CMf+cgNrv3iJxQKXdZUuERpaalUV1df/p39+/b4oz/6I9mxY4c8+uij8hu/8RvyyiuvyDe+8Q35xje+ISLCOfw2efDBB+ULX/iCtLW1ydq1a+XQoUPy+OOPy+/8zu+ICPv3HQU1lN7R0He6ftB3ml/oO80v9JvmH/pONwnUULoqFuUDpQ996EMyPT0tn/vc52R0dFTWrVsnzzzzzOUn6+TqufT54HvvvRd+/+Y3vykf//jHRUTk05/+tMzNzcnDDz8ss7Ozsn37dvnxj38soVBogWv7zoT9+/a45ZZb5Lvf/a78+Z//uXzuc5+Tzs5OeeKJJ+S3fuu3Ltuwj986X/nKV+Sv/uqv5OGHH5aJiQlpamqST3ziE/LXf/3Xl23Yv4Qsfug7XT/oO9142L9vHfpN8w99J0KuYNn2En4cRgghhJBfSCwWk4qKCnlP0yfE4/LPe3n5YkaeHfmvEo1Gpby8fN7LI4QQQgi5Xiy03ySytH2nRaehRAghhJB5wJYrr2/P658b3VBCCCGEkLfJgvlNb813+trXviadnZ0SCARk69at8sILL1z3Lrga+ECJEEIIIYQQQgghZAnw9NNPyyOPPCKf+cxn5NChQ3LXXXfJAw88cPlrjgsJHygRQgghNwML9q9sfEWJEEIIIUuchfSbrtF3evzxx+V3f/d35fd+7/dk9erV8sQTT0hra+tlDcCFhA+UCCGEEEIIIYQQQm4gsVgM/mQyGWWTzWbl4MGDsnPnTvh9586dsm/fvoWq6mX4QIkQQgi5GSgWF+4PIYQQQshSZiH9ptd9p9bWVqmoqLj857HHHlPVmpqakkKhIPX19fB7fX29jI2NLUjXvBHPgpdICCGEEEIIIYQQQi4zODgIX3nz+3/+V+Ysy4K0bdvqt4WAD5QIIYSQm4GF0jeihhIhhBBCljoLqQv5ejnl5eXwQMmJmpoacbvd6m2kiYkJ9dbSQsCQN0IIIYQQQgghhJBFjs/nk61bt8ru3bvh9927d8uOHTsWvD58Q4kQQgghhBBCCCFkCfCpT31KPvrRj8q2bdvk9ttvl2984xsyMDAgv//7v7/gdeEDJUIIIeRmgCFvhBBCCCFXxw0IebtaPvShD8n09LR87nOfk9HRUVm3bp0888wz0t7ePk8V/PnwgRIhhBBCCCGEEELIEuHhhx+Whx9++EZXgw+UCCGEkJuCoi0iC/AvbUW+oUQIIYSQJc5C+U2Xy1qaUJSbEEIIIYQQQgghhFwTfEOJEEIIuQmw7aLYdnFByiGEEEIIWcoslN90qaylCt9QIoQQQgghhBBCCCHXBN9QIoQQQm4GbHthYvT5lTdCCCGELHUWym+6VNYShW8oEUIIIYQQQgghhJBrgg+UCCGEEEIIIYQQQsg1wZA3Qggh5GbAXqDP3y7h17YJIYQQQkRk4fymy2UtTfiGEiGEEEIIIYQQQgi5JviGEiGEEHIzUCyKWAvwWdol/OlbQgghhBARWTi/SWRJ+058Q4kQQgghhBBCCCGEXBN8Q4kQQgi5GaCGEiGEEELI1UENpauCbygRQgghhBBCCCGEkGuCbygRQgghNwF2sSj2AmgB2EtYB4AQQgghRGTh/CaRpe078Q0lQgghhBBCCCGEEHJN8A0lQggh5GaAGkqEEEIIIVcHNZSuCr6hRAghhBBCCCGEEEKuCT5QIoQQQgghhBBCCCHXBEPeCCGEkJuBoi1iMeSNEEIIIeRNWSi/SWRJ+058Q4kQQgghhBBCCCGEXBN8Q4kQQgi5GbBtEVmAz9Iu4X9lI4QQQggRkYXzmy6XtTThG0qEEEIIIYQQQggh5JrgG0qEEELITYBdtMVeAC0Aewn/KxshhBBCiMjC+U0iS9t34htKhBBCCCGEEEIIIeSa4BtKhBBCyM2AXZSF0VBaIL0BQgghhJD5YqH8pstlLU34hhIhhBBCCCGEEEIIuSb4QIkQQgghhBBCCCGEXBMMeSOEEEJuAijKTQghhBBydVCU++rgG0qEEEIIIYQQQggh5JrgG0qEEELIzQBFuQkhhBBCrg6Kcl8VfKBECCGE3ATkJSeyAG9U5yU3/4UQQgghhMwjC+U3XS5ricIHSoQQQsg7GJ/PJw0NDbJ37JkFK7OhoUF8Pt+ClUcIIYQQcj24EX6TyNL1nSx7KStAEUIIIeRNSafTks1mF6w8n88ngUBgwcojhBBCCLleLLTfJLJ0fSc+UCKEEEIIIYQQQggh1wS/8kYIIYQQQgghhBBCrgk+UCKEEEIIIYQQQggh1wQfKBFCCCGEEEIIIYSQa4IPlAghhBBCCCGEEELINcEHSoQQQgghhBBCCCHkmuADJUIIIYQQQgghhBByTfCBEiGEEEIIIYQQQgi5Jv7/xvPGGJ/pzqUAAAAASUVORK5CYII=", "text/plain": "
" }, "metadata": {} } ], "execution_count": 16 }, { "id": "e2bdcc9f-5fda-4929-b4a4-d3ac1085ba0d", "cell_type": "code", "source": "img.roi", "metadata": { "trusted": true }, "outputs": [ { "execution_count": 5, "output_type": "execute_result", "data": { "text/html": "\n \n\n\n
\n
ImageROI
\n \n \n \n
IndexTitleTypeCoordinates
0ROI00CircularROICenter: (30, 30), R: 20
\n
1 ROI(s)
\n
\n ", "text/plain": "" }, "metadata": {} } ], "execution_count": 5 }, { "id": "4da7c606-52fe-43b4-bd30-b2b29a6d91c0", "cell_type": "code", "source": "img.roi[0]", "metadata": { "trusted": true }, "outputs": [ { "execution_count": 7, "output_type": "execute_result", "data": { "text/html": "CircularROI:
Center (physical):(30, 30)
Radius:20
", "text/plain": "" }, "metadata": {} } ], "execution_count": 7 }, { "id": "5b5691fc-46bf-4ac1-95f9-185e076b9fba", "cell_type": "code", "source": "sigima.proc.image.stats(img)", "metadata": { "trusted": true }, "outputs": [ { "execution_count": 11, "output_type": "execute_result", "data": { "text/html": "\n\nImage statistics:\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
minmaxmeanmedianstdsnrptpsum
-36.920799.799.529.93.342449.97e+05
ROI 0-36.919899.198.831.33.162351.23e+05
", "text/plain": "TableResult(title='Image statistics', kind=, headers=['min', 'max', 'mean', 'median', 'std', 'snr', 'ptp', 'sum'], data=[[-36.94278201242298, 206.97318261323, 99.7013735869401, 99.48387112566627, 29.881238335365566, 3.3365877433847775, 243.91596462565298, 997013.7358694009], [-36.94278201242298, 198.32161409918808, 99.0967110400125, 98.78147378989428, 31.34231863604159, 3.161754310226999, 235.26439611161106, 123375.40524481556]], roi_indices=[-1, 0], func_name='stats', attrs={})" }, "metadata": {} } ], "execution_count": 11 } ] }Sigima-1.1.1/pip_list.txt000066400000000000000000000107541514013333200153110ustar00rootroot00000000000000Package Version ----------------------------- ------------ accessible-pygments 0.0.4 alabaster 0.7.16 altgraph 0.17.4 annotated-types 0.6.0 astroid 3.3.9 attrs 23.1.0 Babel 2.14.0 beautifulsoup4 4.12.2 build 1.2.2.post1 cattrs 23.2.3 certifi 2023.11.17 charset-normalizer 3.3.2 click 8.1.7 colorama 0.4.6 coverage 7.8.2 dill 0.3.7 doc8 1.1.2 docutils 0.20.1 esbonio 0.16.5 guidata 3.9.0 h5py 3.10.0 id 1.5.0 idna 3.6 imageio 2.33.1 imagesize 1.4.1 importlib-metadata 7.0.1 iniconfig 2.0.0 isort 5.13.2 jaraco.classes 3.3.0 Jinja2 3.1.2 keyring 24.3.0 lazy_loader 0.4 lsprotocol 2023.0.0 markdown-it-py 3.0.0 MarkupSafe 2.1.3 mccabe 0.7.0 mdit-py-plugins 0.4.2 mdurl 0.1.2 more-itertools 10.1.0 msvc-runtime 14.36.32532 mypy-extensions 1.0.0 myst-parser 4.0.1 networkx 3.2.1 nh3 0.2.15 numpy 1.26.2 opencv-python-headless 4.11.0.86 packaging 25.0 pandas 2.3.0 pathspec 0.12.1 pbr 6.0.0 pefile 2023.2.7 Pillow 10.1.0 pip 25.1.1 pkginfo 1.9.6 platformdirs 4.1.0 PlotPy 2.7.4 pluggy 1.5.0 psutil 7.0.0 pycodestyle 2.13.0 pydantic 2.5.3 pydantic_core 2.14.6 pydata-sphinx-theme 0.16.1 pygls 1.2.1 Pygments 2.17.2 pyinstaller 6.14.0 pyinstaller-hooks-contrib 2025.4 pylint 3.3.7 pyproject_hooks 1.0.0 PyQt5 5.15.11 PyQt5-Qt5 5.15.2 PyQt5_sip 12.15.0 pyspellchecker 0.7.3 pytest 8.4.0 pytest-xvfb 3.1.1 python-dateutil 2.9.0.post0 PythonQwt 0.14.5 pytz 2024.1 PyVirtualDisplay 3.0 PyWavelets 1.8.0 pywin32-ctypes 0.2.2 PyYAML 6.0.1 QtPy 2.4.1 readme-renderer 42.0 requests 2.31.0 requests-toolbelt 1.0.0 restructuredtext-lint 1.4.0 rfc3986 2.0.0 rich 13.7.0 roman-numerals-py 3.1.0 rstcheck 6.2.5 rstcheck-core 1.2.0 ruff 0.11.13 scikit-image 0.25.2 scipy 1.11.4 setuptools 68.2.2 shellingham 1.5.4 six 1.16.0 snowballstemmer 2.2.0 soupsieve 2.5 Sphinx 8.2.3 sphinx-copybutton 0.5.2 sphinx_design 0.6.1 sphinx-intl 2.3.1 sphinx-sitemap 2.6.0 sphinxcontrib-applehelp 1.0.7 sphinxcontrib-devhelp 2.0.0 sphinxcontrib-htmlhelp 2.1.0 sphinxcontrib-jsmath 1.0.1 sphinxcontrib-qthelp 1.0.6 sphinxcontrib-serializinghtml 1.1.9 sqlite-bro 0.12.2 stevedore 5.1.0 tifffile 2023.12.9 tomli 2.0.1 tomlkit 0.12.3 twine 6.1.0 typer 0.12.3 typing_extensions 4.9.0 tzdata 2024.1 urllib3 2.1.0 wheel 0.40.0 winpython 7.0.20231126 zipp 3.17.0 Sigima-1.1.1/pyproject.toml000066400000000000000000000106721514013333200156400ustar00rootroot00000000000000# Sigima setup configuration file [project] name = "sigima" authors = [{ name = "Pierre Raybaut", email = "p.raybaut@codra.fr" }] maintainers = [ { name = "DataLab Platform Developers", email = "p.raybaut@codra.fr" }, ] description = "Scientific computing engine for 1D signals and 2D images, part of the DataLab open-source platform." readme = "README.md" license = { file = "LICENSE" } classifiers = [ "Development Status :: 5 - Production/Stable", "Intended Audience :: Developers", "Intended Audience :: Education", "Intended Audience :: Science/Research", "Intended Audience :: End Users/Desktop", "Operating System :: MacOS :: MacOS X", "Operating System :: Microsoft :: Windows :: Windows 7", "Operating System :: Microsoft :: Windows :: Windows 8", "Operating System :: Microsoft :: Windows :: Windows 10", "Operating System :: Microsoft :: Windows :: Windows 11", "Operating System :: POSIX :: Linux", "Programming Language :: Python :: 3.9", "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11", "Programming Language :: Python :: 3.12", "Programming Language :: Python :: 3.13", "Topic :: Scientific/Engineering", "Topic :: Scientific/Engineering :: Image Processing", "Topic :: Software Development :: Libraries :: Python Modules", ] requires-python = ">=3.9, <4" dependencies = [ "guidata >= 3.13", "NumPy >= 1.22, < 2.5", "SciPy >= 1.10.1, < 1.17", "scikit-image >= 0.19.2, < 0.27", "pandas >= 1.4, < 3.0", "PyWavelets >= 1.2, < 2.0", "packaging >= 21.3", "typing-extensions >= 4.0", "makefun >= 1.13.1", ] dynamic = ["version"] [build-system] requires = ["setuptools"] build-backend = "setuptools.build_meta" [project.urls] Homepage = "https://github.com/DataLab-Platform/Sigima" Documentation = "https://sigima.readthedocs.io/" [project.optional-dependencies] opencv = ["opencv-python-headless >= 4.8.1.78"] dev = ["build", "babel","ruff", "pylint", "Coverage", "pre-commit"] doc = [ "sphinx", "sphinx-gallery", "sphinx_intl", "myst_parser", "myst-nb", "sphinx_design", "sphinx-copybutton", "pydata-sphinx-theme", "qtpy", "PyQt5", "plotpy", "matplotlib", "opencv-python-headless >= 4.8.1.78", ] test = ["pytest", "pytest-xvfb"] qt = ["qtpy", "PyQt5", "plotpy"] [tool.setuptools.packages.find] include = ["sigima*"] [tool.setuptools.package-data] "*" = [ "*.pdf", "*.png", "*.svg", "*.mo", "*.txt", "*.json", "*_test.h5", "*.h5ima", "*.h5sig", "*.npy", "*.dcm", "*.scor-data", "*.tiff", "*.jpg", "*.sif", "*.csv", "*.mca", "*.mat", "*.js", "*.css", "*.html", "*.buildinfo", "*.inv", ] [tool.setuptools.dynamic] version = { attr = "sigima.__version__" } [tool.pytest.ini_options] addopts = "sigima --import-mode=importlib" filterwarnings = [ # Ignore specific deprecation warnings from external libraries "ignore::DeprecationWarning:pandas.*", "ignore::DeprecationWarning:scipy.*", "ignore::DeprecationWarning:skimage.*", # Ignore specific user warnings from Sigima (expected behavior) "ignore:Multiple crossing points found. Returning last.:UserWarning:sigima.*", ] [tool.ruff] exclude = [".git", ".vscode", "build", "dist", "*.ipynb"] line-length = 88 # Same as Black. indent-width = 4 # Same as Black. target-version = "py39" # Assume Python 3.9. [tool.ruff.lint] # all rules can be found here: https://beta.ruff.rs/docs/rules/ select = [ "D202", # No blank lines allowed after function docstring. "D403", # First word of docstring should be properly capitalized. "E", # Pycodestyle error "F", # Pyflakes "I", # Isort "NPY201", # Numpy-specific checks "RUF022", # Unsorted __all__ "W" # Pycodestyle warning ] ignore = [ "E203", # space before : (needed for how black formats slicing) ] [tool.ruff.format] quote-style = "double" # Like Black, use double quotes for strings. indent-style = "space" # Like Black, indent with spaces, rather than tabs. skip-magic-trailing-comma = false # Like Black, respect magic trailing commas. line-ending = "auto" # Like Black, automatically detect the appropriate line ending. [tool.ruff.lint.per-file-ignores] "doc/*" = ["E402"] [tool.ruff.lint.pydocstyle] convention = "google" Sigima-1.1.1/requirements.txt000066400000000000000000000006601514013333200162040ustar00rootroot00000000000000Coverage NumPy >= 1.22, < 2.5 PyQt5 PyWavelets >= 1.2, < 2.0 SciPy >= 1.10.1, < 1.17 babel build guidata >= 3.13 makefun >= 1.13.1 matplotlib myst-nb myst_parser opencv-python-headless >= 4.8.1.78 packaging >= 21.3 pandas >= 1.4, < 3.0 plotpy pre-commit pydata-sphinx-theme pylint pytest pytest-xvfb qtpy ruff scikit-image >= 0.19.2, < 0.27 sphinx sphinx-copybutton sphinx-gallery sphinx_design sphinx_intl typing-extensions >= 4.0 Sigima-1.1.1/resources/000077500000000000000000000000001514013333200147305ustar00rootroot00000000000000Sigima-1.1.1/resources/Sigima-Banner.svg000066400000000000000000000457121514013333200200760ustar00rootroot00000000000000 image/svg+xmlSigima Sigima-1.1.1/resources/Sigima-Frontpage.svg000066400000000000000000000403111514013333200206040ustar00rootroot00000000000000 image/svg+xml Sigima-1.1.1/resources/Sigima-Power.svg000066400000000000000000000475341514013333200177710ustar00rootroot00000000000000 image/svg+xmlSigimaPowered by Sigima-1.1.1/resources/Sigima-Title.svg000066400000000000000000000457311514013333200177530ustar00rootroot00000000000000 image/svg+xmlSigima Sigima-1.1.1/resources/Sigima-lib.svg000066400000000000000000000216271514013333200174360ustar00rootroot00000000000000 S Sigima-1.1.1/resources/Sigima.ico000066400000000000000000003143171514013333200166460ustar00rootroot00000000000000 (f h  L~  b00 %'s( 8hZhؼ̨ȡ˜}ƞɣЮõCLΫbZ4N&N&N&N&N&N&N&N&N&N&N&N&N&gEx׻_ǟd@N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&P)}`׻ I~aO'N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&]9ͪ z\N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&Z5Ե<M~O(N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&oN}b?N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&S,ӳ άP)N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&m yN&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&wX eN&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&jHbN&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&V0hΫʽƹ̨m^:N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&mKhN&N&N&N&N&N&N&N&N&N&N&N&N&N&N&uVƹǟ]9N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&sS~N&N&N&N&N&N&N&N&N&N&N&N&N&N&}_2&mֺiGN&N&N&N&N&N&N&N&N&N&N&N&N&N&pMЯN&N&N&N&N&N&N&N&N&N&N&N&N&Y4aΫT.N&N&N&N&N&N&N&N&N&N&N&N&N&ЯB%Q)N&N&N&N&N&N&N&N&N&N&N&N&bn rRN&N&N&N&N&N&N&N&N&N&N&N&Q) ]9N&N&N&N&N&N&N&N&N&N&N&N&Ŝ'1sN&N&N&N&N&N&N&N&N&N&N&N&qQ}`N&N&N&N&N&N&N&N&N&N&N&O'Ϋ ÙN&N&N&N&N&N&N&N&N&N&N&N&ѱ8ѰN&N&N&N&N&N&N&N&N&N&N&O(չsN&N&N&N&N&N&N&N&N&N&N&\7S,N&N&N&N&N&N&N&N&N&N&N&ϭpqQN&N&N&N&N&N&N&N&N&N&N&Ϋ|xYN&N&N&N&N&N&N&N&N&N&N&~ T-N&N&N&N&N&N&N&N&N&N&]9|$ոN&N&N&N&N&N&N&N&N&N&N&d7̩N&N&N&N&N&N&N&N&N&N&N&ȼY4N&N&N&N&N&N&N&N&N&N&d@\7N&N&N&N&N&N&N&N&N&N&i8A—N&N&N&N&N&N&N&N&N&N&P)ͪN&N&N&N&N&N&N&N&N&N&T.|W1N&N&N&N&N&N&N&N&N&N&ɣLP)N&N&N&N&N&N&N&N&N&N& iN&N&N&N&N&N&N&N&rRE}`N&N&N&N&N&N&N&N&N&N&˦1gEN&N&N&N&N&P) ҲN&N&N&N&N&N&N&N&N&N&m$^ҳV0N&N&N&˜HN&N&N&N&N&N&N&N&N&N&mLJL&M)2M+iN&\7@ M3 @@O(N&N&N&N&N&N&N&N&N&T.lR)M'N&O&N&N&P( 1ö#P N''L)%M'!R$K-bZ4N&N&N&N&N&N&N&N&N&N&{P( N&M&N&O&N&N%M(P( aM&N'.O$*L)%M'!R$J+K-@@U"N!R$P K&"S)%M&(M*+O(-P%0K#3P&6Q(9N';N)>N'A׽fDN&N&N&N&N&N&N&N&N&N&ŹO%nM&qM(tM'wM&zN%|N&N%M&M'O'N&N%N&M%N&O&M%N'O%nK%)UN&O'M&N&O&N&N%M'M&zU+ I$P+0N'.O$*L)%M'!R$J+Q(M P0R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YͫlKN&N&N&N&N&N&N&N&N&N&ɽЗN%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&I$L$TN%O'M&N&O&N&N%M'N&O(GN''P(3N'.O$*L)%M'!R$J+Q(U"UUK-J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%Y׺]9N&N&N&N&N&N&N&N&N&N&ŷ͗N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&O&՘O$*M&N%O'M&N&O&N&N%M'N&O&~@@@ O%7P(3N'.O$*L)%M'!R$J+Q(U"I$N' M&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YȽP)N&N&N&N&N&N&N&N&N&N&پȗN%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'ҒI$M&5M&N%O'M&N&O&N&N%M'N&O&O(-P( O%7P(3N'.O$*L)%M'!R$J+Q(U"M3 U+P M&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YN&N&N&N&N&N&N&N&N&N&Y4ЭN%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'M'N'uM&N%O'M&N&O&N&N%M'N&O&N'\M&5O%7P(3N'.O$*L)%M'!R$J+Q(U"M3 UUF. P M&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%Y׼N&N&N&N&N&N&N&N&N&N&oO}N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&U+N&M&N%O'M&N&O&N&N%M'N&O&M&~UF. M&M'BM$FO&JN'NO&QN'UipuN&N&N&N&N&N&N&N&N&N&vnMN%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&L&6L"%N&M&N%O'M&N&O&N&N%M'N&O&M'M'!O,M&M'BM$FO&JN'NO&QN'Uɰ]8N&N&N&N&N&N&N&N&N&N&ӳO&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&O'TM%YN&M&N%O'M&N&O&N&N%M'N&O&M'P&CN'.M&M'BM$FO&JN'NO&Q_>[׼N&N&N&N&N&N&N&N&N&N&N&ܘO&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\M%N&M&N%O'M&N&O&N&N%M'N&O&M'M%`Q&M'BM$FO&JN'NO&QƺpPN&N&N&N&N&N&N&N&N&N&a=ЯO&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\N&N&M&N%O'M&N&O'N&N%M'N&O&M'M&zU+ P(@M&M'BM$FO&JN'NsS_ʽN&N&N&N&N&N&N&N&N&N&N&ÚoNO&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\N'N&N&M&N%O'M&N&N'\N&N%M'N&O&M'N&J L&P(@M&M'BM$FO&JN'NܽeBN&N&N&N&N&N&N&N&N&N&N&N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\O&DN&N&M&N%O'M&N&J+M'N%M'N&O&M'N&P#3Q%)P(@M&M'BM$FO&JҲȡN&N&N&N&N&N&N&N&N&N&N&oOΫN%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\N%hN&N&M&N%O'M&N%N&N%M'N&O&M'N&P&IP&6P(@M&M'BM$Fg^R+N&N&N&N&N&N&N&N&N&N&N&ؾY4N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\O'N&N&M&N%O'M&M$pM%`N%M'N&O&M'N&P%`M'BP(@M&M'BcBMa>N&N&N&N&N&N&N&N&N&N&N&dAµĖM'N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\N&N&N&M&N%O'M&N%RN%EN%M'N&O&M'N&N%uF. N%EP(@M&R/A|^N&N&N&N&N&N&N&N&N&N&N&N&ؾrTUL&JM%LN'NP&PN%RO'TM'VM%YO%ZN'\O&^L%aM'cN&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\I$N&ØN&N&M&N%O'M&L&6O$*N%M'N&O&M'N&O%{U"J+N%EP(@M&N%>O&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\N&N&O&N&N&N&N&M'VU+ N&ЗN&̗N&ǖN&ØN&N&M&M&5M'!O&M'N&O%{N'vN&rM%mU+ L&N%RN'NM&IN%EP(@M&N%>O&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\M&֗N&O&N&N&N&N&N%vO$*N&ЗN&̗N&ǖN&ØN&N&M&I$N' O&M'N&O%{N'vN&rM%mL&N''N%RN'NM&IN%EP(@M&N%>O&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\N&N&O&N&N&N&N&N%O(GN&ЗN&̗N&ǖN&ØN&N&N&33O&M'N&O%{N'vN&rM%mO$*P(3N%RN'NM&IN%EP(@M&N%>O&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\N%N&O&N&N&N&N&N&N&eN&ЗN&̗N&ǖN&ØN&N&M&N%oM'N&O%{N'vN&rM%mM)8Q$?N%RN'NM&IN%EP(@uS}`N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&hʽaM$+L&/P(3O%7O(:N%>N%>O&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\N&lN&O&N&N&N&N&N&N'N&ЗN&̗N&ǖN&ØN&N&O&N$\M'N&O%{N'vN&rM%mO(GN%KN%RN'NM&IN%E{YoON&N&N&N&N&N&N&N&N&N&N&N&N&N&Q)˧ƞ:N''M$+L&/P(3O%7O(:N%>N%>O&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\O(GN&O&N&N&N&N&N&G+M&N&ЗN&̗N&ǖN&ØN&N&M%mM&IM'N&O%{N'vN&rM%mL&WP'VN%RN'NM&IŚehEN&N&N&N&N&N&N&N&N&N&N&N&N&N&a>jG$N#$N''M$+L&/P(3O%7O(:N%>N%>O&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\K&"N&O&N&N&N&N&N&O(:N&ȗN&ЗN&̗N&ǖN&ØN&N&N%RM&5M'N&O%{N'vN&rM%mM(gK-O&WN%RN'NƝka>N&N&N&N&N&N&N&N&N&N&N&N&N&N&fXR$P( N#$N''M$+L&/P(3O%7O(:N%>N%>O&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\N&O&N&N&N&N&N&O'aR)N&՗N&ЗN&̗N&ǖN&ØN&N&P(3M"M'N&O%{N'vN&rM%mN'iG+K&"O&WN%Rhb\7N&N&N&N&N&N&N&N&N&N&N&N&N&Q)ϭ׵-J+R$P( N#$N''M$+L&/P(3O%7O(:N%>N%>O&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\M&ɗO&N&N&N&N&N&N'L$@N&՗N&ЗN&̗N&ǖN&ØN&N&U+U+N'N&O%{N'vN&rM%mN'iN#$M)2O&WjF[eBN&N&N&N&N&N&N&N&N&N&N&N&N&]9sMM&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>N%>O&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\M&O&N&N&N&N&N&M'M%gN&՗N&ЗN&̗N&ǖN&ØN&N&N&rN&O%{N'vN&rM%mN'iR&5M'BO&WsSN&N&N&N&N&N&N&N&N&N&N&N&N&pPLN' P M&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M(?Q(M&I$Q#N!J G)N'L&R$O#M+J)P( M'!K&"P$#N#$L)%Q(&N''M&(Q%)O$*M$+Q),O(-N'.L&/P%0N$1N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\M%mO&N&N&N&N&N&N'ڿ@@M%N&՗N&ЗN&̗N&ǖN&ØN&O'M(ZN&O%{N'vN&rM%mN'iP&IO'TwN&N&N&N&N&N&N&N&N&N&N&N&N&n'UUN' P M&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YM&]O%aN&eN'hN&lM'pM%tO&xN%|N&N'M&M'N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\N%>O&N&N&N&N&N&N&O(-M%N&՗N&ЗN&̗N&ǖN&ØN&N'iM'BN&O%{N'vN&rM%mN'iO&^I$}_nǺN&N&N&N&N&N&N&N&N&N&N&N&O(̩UUN' P M&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YM&]O%aN&eN'hN&lM'pM%tO&xN%|N&N'M&M'N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\F. O&N&N&N&N&N&N&N&sN&ٗN&՗N&ЗN&̗N&ǖN&ØN&M'BQ(&N&O%{N'vN&rM%mN'iO&dM$2]9N&N&N&N&N&N&N&N&N&N&N&O(UUN' P M&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YM&]O%aN&eN'hN&lM'pM%tO&xN%|N&N'M&M'N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\N'͗N&N&N&N&N&N&N'͘N&ٗN&՗N&ЗN&̗N&ǖN&ØN&R)U N&O%{N'vN&rM%mN'iO&dɡĚN&N&N&N&N&N&N&N&N&N&N&O'ԷgUUN' P M&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YM&]O%aN&eN'hN&lM'pM%tO&xN%|N&N'M&M'N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\N'N&N&N&N&N&N&N&ޘN&ٗN&՗N&ЗN&̗N&ǖN&×N&N&lO%{N'vN&rM%mN'iO&dQ)N&N&N&N&N&N&N&N&N&N&N&̨tUUN' P M&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YM&]O%aN&eN'hN&lM'pM%tO&xN%|N&N'M&M'N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\P&]N&N&N&N&N&N&N&ޘN&ٗN&՗N&ЗN&̗N&ǖN&ØN%M'OO%{N'vN&rM%mN'i—{N&N&N&N&N&N&N&N&N&N&N&mUUN' P M&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YM&]O%aN&eN'hN&lM'pM%tO&xN%|N&N'M&M'N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\N'N&N&N&N&N&N&N&ޘN&ٗN&՗N&ЗN&̗N&ǖN&ÙP&PO(-O%{N'vN&rM%mN'iR+N&N&N&N&N&N&N&N&N&N&hEUUN' P M&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YM&]O%aN&eN'hN&lM'pM%tO&xN%|N&N'M&M'N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&N'\N%͘N&N&N&N&N&N&ޘN&ٗN&՗N&ЗN&̗N&ǖN&×L&M O&zN'vN&rM%meCrϭN&N&N&N&N&N&N&N&N&N&P)N' P M&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YM&]O%aN&eN'hN&lM'pM%tO&xN%|N&N'M&M'N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&L&WM&N&N&N&N&N&N&ޘN&ٗN&՗N&ЗN&̗N&ǖO&N$bN'vN&rM%mҳkJN&N&N&N&N&N&N&N&N&N&—KN' P M&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YM&]O%aN&eN'hN&lM'pM%tO&xN%|N&N'M&M'N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&L(@K(3N&N&N&N&N&N&ޘN&ٗN&՗N&ЗN&̗N&ǖN&fM$8N'vN&rM%mN&N&N&N&N&N&N&N&N&N&T-U+ P M&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YM&]O%aN&eN'hN&lM'pM%tO&xN%|N&N'M&M'N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'N&I$O&ŗN&N&N&N&N&ޘN&ٗN&՗N&ЗN&̘O'ƒI$M N(sN&rM%mӳN&N&N&N&N&N&N&N&N&N&~/I$P M&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YM&]O%aN&eN'hN&lM'pM%tO&xN%|N&N'M&M'N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'M%O%aN&N&N&N&N&ޘN&ٗN&՗N&ЗN&̘N'L(MN&r|^sN&N&N&N&N&N&N&N&N&N&U"M&J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YM&]O%aN&eN'hN&lM'pM%tO&xN%|N&N'M&M'N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&N&N'P( N&N&N&N&N&ޘN&ٗN&՗N&ЗN&ęM"U+ O&jΪhEN&N&N&N&N&N&N&N&N&a>e@@Q(J+R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YM&]O%aN&eN'hN&lM'pM%tO&xN%|N&N'M&M'N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N&O&L(MN#$N&N&N&N&ޘN&ٗN&՗N&ИO&WQ%)öQ*N&N&N&N&N&N&N&N&N&y@@M&R$P( N#$N''M$+L&/P(3O%7O(:N%>M'BM$FO&JN'NO&QN'UM%YM&]O%aN&eN'hN&lM'pM%tO&xN%|N&N'M&M'N%O&N%N&M'M&N&N&N&N%M&M'N&N'N&ĖN&ȗN&̗N&ЗO'ӗN&חN&ۗN&ߗN&N%͘N%>O(-N&ŗN&N&ޘN&ٗN&ΗM'VN&N&N&N&N&N&N&N&N&N&ӴM Q#R!N+$M&(K),P%0P#3P&6O#:N%>N#AN%EM&IM%LM'OM%SL&WN$[O&^O'aN&eN'iN&lP'pM%tM'wM(zM&~M'O&O'N&N%N&N%O&O%N&M%M&M&N&N&N&N&N&O&—O'ŗO&ɗN&—O&N'\M @@N'.N$[N%KI$N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N& N&N&N&N&N&N&N&N&N&N&FN&N&N&N&N&N&N&N&N&N&ɽǫN&N&N&N&N&N&N&N&N&N&ո>ڿN&Q*Ѱ\a>N&N&N&N&N&N&N&N&N&r(T.N&N&N&j?,hN&N&N&N&N&N&N&N&N&Y4vd@N&N&N&N&N&fCy˦N&N&N&N&N&N&N&N&N&N& qQN&N&N&N&N&N&N&S,ԶN&N&N&N&N&N&N&N&N&N&b`}`N&N&N&N&N&N&N&N&N&N&r8s^:N&N&N&N&N&N&N&N&N&N& qN&N&N&N&N&N&N&N&N&N&N&N&v—N&N&N&N&N&N&N&N&N&N&a=oN&N&N&N&N&N&N&N&N&N&N&N&_:N&N&N&N&N&N&N&N&N&N&N&qQ ,bN&N&N&N&N&N&N&N&N&N&N&N&Q) X}`N&N&N&N&N&N&N&N&N&N&N&e'msSN&N&N&N&N&N&N&N&N&N&N&N&N&ѱIN&N&N&N&N&N&N&N&N&N&N&N&uV~ PX2N&N&N&N&N&N&N&N&N&N&N&N&N&rYeN&N&N&N&N&N&N&N&N&N&N&N&Y4ֺG /bN&N&N&N&N&N&N&N&N&N&N&N&N&N&|^Y4N&N&N&N&N&N&N&N&N&N&N&N&N&kJոŹfO'N&N&N&N&N&N&N&N&N&N&N&N&N&N&rR 'پN&N&N&N&N&N&N&N&N&N&N&N&N&N&N&P)tUɣŸʾ̨hX2N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&jHquN&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&c@cN&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&mL$uVN&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&|^"mN&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&sʤO'N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&S,ѱ hFN&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&sTSʥT.N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&d@ֺ=ɣY4N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&dAֹ~.Ӵz\P)N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&N&X2t˿#׻}sTU/N&N&N&N&N&N&N&N&]8cɣʾyE˿*Bqc1???????~??? >?>>>>>??pppppp`     ????????(  ʿśirǢeȡbgEP)[6N&pP˫@̦PZ5tTдRǤmc@lJʿrlLȶƟoN&–uU+ N'uÞ"ҵ>N!@ M N''|qO'y[P&N'O$TN'AN%O(:N'.U3M&M&5hN&z]O&N&ΗN&M&dM'pM'OUUN'.I$M&r{\7sU٬uS%M$2N&ΗM&P%0L"%M%K&=M&dG+Q(&F. —}]8gFѲ8Q(N&ΗM&M%mM%tN%U"N&rM'!jG${T-qRϲ5Q(N&ΗM&L&CN'M%M&dmGDgO(iuYHQ(N&ΗM&J+M&ݗN%N'NfO(ę]:M&5L$MO&jM(O%N&ΗM&N&M&PQ/&qPz]U"M&5M%SN&rM'O&N&ΗM& gDdҳ9Ǥmy[ʥfEҶ?ԴGmKڦhE*˧Nb=X3qQV0b?ȟXб1o}_nӱ.8(0 O5Է|sΩmMU/_:fͨ ɣQ)N&R+fDT.N&N&q)ɣO'U/Û]%˿XǟZ5N&|ոsV0S,ϮҲQ*Q*ԸvѰV/Ě fݗN&}K),M'pmIټr9` R)M&P$#L&/q˗N&lٗM%`N&lN&yN&rQ(O'N&M'BN+$P$#@ N' L)%O(:T-OhN&kܗN&N&M&ɗN&ݗM'F. O'M'N'bM)2M'!M3 D3L)%O(:ǟU/N&wȗN&N&M&ɗN&ݘN&O(-N&N'bM'wUO(:Q#F. D3L)%ÙspNN&|^繆o7M$+N%EM&ɗN&ݘN&O$MO&M$2N'` U"N';F. F. D3ʤjvUN&c>׻eO#M&ɗN&ݘN&L)%N&U+ O%nN'I$N'N'R$N';M3 ѱiHN&^:ԴO#M&ɗN&ݘN&O(-N&N'.O&N&yO&~M$+O$*N'4Ϯ[6N&mMչmO#M&ɗN&ݘN&I$N%M%SN%N'[M&jQ&N'UN'N}^ZqЗN&Q*ØĽxBQ(9O#M&ɗN&ݘN&N&M&ɗN&˗P( L(@O'a{˗N&[6Ѳk^L)%O(:O&DM'VM(gO&xM'N&M&ɗN&ݘN&O&xN&M%@@N+$o_;O'ЮI7L)%O(:N'NM'cM'wO'N&N&M&ɗN&ݖN&O#N&ŖN&fU}N&sSI$N+$O(:N'NM'cM'wO'N&N&M&ɗN&ЗO(GƝN&mǽh̫N&pP&׾fb@t56hDN&w5 ԵhFN&}`)аQ*N&gDj޲|^O(N&uV´GѲqQN&N&N&Y4{4!Ӵ{ˤΫ˾S?>0p???PNG  IHDR\rfKIDATxw|]`o=EP@'(" 7*)Ɓ ^2 -M5!&\~x{<ܥBJMDtlll"-66U[ll0H7& F@=.P-~/ p2> = -U^@7hуa/J r Pii.(>?B` #}ClE+jRKyu?ddp #"7"9U$&*Ԫ@ډԩ@ډ4k/- # j\\Jfզܸ;3ض0YAs/oРv"/=:pgX vF}["˹,  7ot!'ȍp^en_E1]ewCե1o>|Փol4AU&s+"Ҡ(kx9L; ;<[ nԅ[/=jd:17F#P\ɗE$`i>77^i!XA]` ~7>-Vˉ{vnwQ!$+F0 pn3->c LyqMxVbKMm=obdTn~;OrqPJNa8ɬ =P1tN}㧿3?I okި:S_׋p*pUPRR2vL.k1Bg!0ܞ_k9 n kc8 Uh *mZ~Z߼Qu~ioQ"=홎`YRx}=,篕yžE` TY@HXX 0t5oT/DaEaYPUyE#}C…-3ebWϩ|"}G$&i۬VP Ri[boF xj%b=^.xOzRl׆rb:""}#…-s:ᾖʻ4 X Pf5&>׆?(n>^&a(6eh غ+\gOpE}_BT Hh٤X5JMqξQ0k+  8zy^a_+OIwwWm>1vW wl k:9N`qr"y6U86-qźw9W ߧيۇu UUxHgÀ{1b @pxsRmPgpJ/6Bo2[N9\4# ^غp+?ĆX鋍 QWW8\1ѩogTLiK<hFP6mBZxaWe8gJbbwc3Pd.uaJ` yj,oTO?+).tMZ<7wEZ`LTߨ?0D#;>O4kTbkY SشߙytnS\k1 9pʦ@Z Qo v9= Rַ=bEю=0ZatT2H_lяTEpŅ};& -P q%gyf멤HL* t+ kUbE[%#z_Nَyb=/ 'LcFrtB6b y\GR.$TE{ `QWPBBoc-f,y%|T꘭Ʀ,24ݤ"1PDTBfHT}?r̘ >H?ع7zllRn{RyT(BRR:RCVGk^jb E(Žf %BѼqɉ 8g|V5UWtS "]H%ơ +Bפ"588!TTRTRTPcT[QTB (!'EHEET*T@R*!qKUE u ! QTP)B*G"_HT@ ! "A12:E BH QBp}("ThmP2CfP9ⴅkޑojUnS[[Rr#&ԥۭ $HtA čsM2Gc'slޙ8~yp;2B LrI9tU**W+ŝܧK͡TRq(uE"sOUHUKE(x+)󞧣Jo'yOw4VI|M0XRh|]|(Dri8g8ѿҦ8!NGbwzKh{B-KL/k|>F2RK(l鶝*)9S)})$ OSk:j]b)GR9t]}v[džW^.-FSǭ#'8s5{_ys80$?xCh|M b؈a:-1O̕h6|‘<3#1|ZilH:+-lwl)f&Dr-9 6y͗aLb=*T(Bl셿ʎvƒ-b4E\le5s7#V)痥g94lY>w,Y 2ʇMUU=|evGJk=z_sr-7n?߳%{0Ͽ[{$B^׶*HY:0hP Ƒ >rb,w[Wz^_z^{)laWKٙunzd @A]($\v䥻Z_}v\^&*pyhrbx{x륋5]lA ~5`r wxja$ɰLP 65:)\<`BM{qsm3q(8emsidfz:bll&5qfX8:_Ȁ7?5\Dj$2ڗs祟p1<cS90-.}6 SK&ǜJ޴7ܹ/k ABnd3?k¤EETxL V{I,:Rшn*kx^_{q'K"ٷkj:ߢkЦ`Z"̯ LE"j;>rbE}35Y T-QWZy Ð&bɳ)k^+3Uc4 !8stYn~i׼EGKwzTEV+?r!D f,%pGKwt}=o ;2~M[ϰ|t}'MӁ_6Sw:Jab[n +H]fH.ۿMu<qY}7 6USi{Vly{LVѲEaN$VGCEv_nyk-gXj!7[}fb'9 S 1AHVԹAo~ФdvE?$tG\:#o']jv EX[< T\L.tI¡_HS&,?PtW͍͒YRǕ_֞]ME}Nm'͟ʧ ` .B @1e'y!Mf-u15anUMRJT[vlW*B Y[motaj _M8ȩ49s7=쭩?{vVXft7_ƪo^rrd6mMIAS+ z@QtM8 qir\}עheŏ{ !wi`n9 ;bb:bb(a]䛩N"=F7Pp.>/g/p o=r{`&}Gk&fֵ\?},mN@ cHL}7>:QH0[@A .Wzx)t_=zs9ε"x\rvP^߬ݒΥO($>-Mx HQR)uG ij!PHe갥ѧXKPiEޮ6:3`%/w.CFZ7+俽UE8k?xi6´ĻR;l6[r,8ΔƵ͙FYZ̓ }_vf<~p20Fͨ+My[ᬕ\7)"iVMeٻ@y$2cIPӭWwMYb`sO_ uEwFreYc }`/-Kh܃~¿wic ~  dB(Bbڰ>R-W۔ѻe)x BF>3q%PUf7DQ6!oh}重1|bq8%}@8M*erp̹P'_pW/oٕ^-DR,.zrϱu)@Hת;z)@ei0 +6{ zvnW.U!@Y~VbJ;'.]g1*(sOa^!j58ZHn07(z߭k Ϛi硻Bf 3%3ۘ?]ٰ;Laki;CZunMh#\+ubr 8 S_BF3ץd´ቹSѩ>fLƵl~ >k}ֽ4eiob:uOc&Zxp%PТq |)nG K֦1i% $OF]-Idmƿ)ӥ^fV"k"o1E~%K**m? FIq|8bS㑑Ueűcw^yADgS*~ VpEӿOH7zP7$@~8yдM=`l;b.2nOU 7{W>ؠVRLgs ~.Og "Y5צ80g&_kjL^*N |/;=S^BYj7ʢUG@5mX}w\>ᒳD<_c6 cGu̯1|^K1 O!r>Y|b-0աӗ epyL8)!CםvbDg)̎:92 PvR1DQ4?nFH>< \d.yPxhΫm''Sq(o_ !֡]Ĥe۲\ 6…@ֱ=m"@b5S^(0`:}H#E3?tU37fb LvRcf6Ev#-a翷 #ڸ*J/"9f.}AqM~4 V F\MRul@$ \?ޭBt``:봍9 @> ir@/6 &Jo&qŘ]8/nw^l23xsI39H X 11l„ku8ٝ| !D17Q{gZcj\V>)W4|`|ot'W= iށT0 3 B?Pgu^@if< hd:[rIz_R ;^$F(c^ycs//rxC:|u(}N5"6`C3YHN_n94;p~ o(u TA(oє[)rfYzkƏr؄8%) 13"Z|03wp[?SG+U5o Ut{yN,25HPcݯ{z E7Ĥ.VHWY+}/~Lk)2@dxrtS)Ԁ́4,p>]QM " +F+=ž3!hJRy߽QvG)2 %[4"K#e# #-3>e." !i@yC'N,F׃Ѯl@ؙ#`1zB "5M)1۴0s;<& nض?F1(܀[L'K#wCUxyE4\\2&M0D5R@@ Rgl挀dmzVM; _\[wZs"ʜ3o;rr1|Zjt) E h &BJg6HS! Bm.D(sk:2-B 諏K.yg$%^p-iѸw<=L͂"MO}'ӣS#8"Lyȩ4`wB 5v#Zƣ9΀= =Q~tY9LbE^j2GqⰧ\2ah[~pO4=|Y] ^68=/vĕxxRJX}ɹv#E:)@j\ 9 z?7ҫEx?ޏ}ۇ)r7OZ[pYRAJHބ\0G@ %o qå eg |GD~={ ]&wWon%m۵ePc J D1; H(NfR*B SB\2=DNˏXܜy蹷d-6 ؋{:5myjŸܸs $!j@# yqwaœTP\Sfz~#WQ+ϿயF??Svx^amGK%x5&ZZ9|/JQ+En4bc"Z @FV/ٓ;Sv.匰Z ~@4MDhpPQ/e(AUGH(nbرbݚ./we})xsP¨K֦1Cg=6*&j@T07L $fŨ!Y55+u ƎU45ۭ F~ƶݙ{ʆ_Ёg<'#7Xʆ}:`B/q4g;Q_/' O'-M;83$RD,3"_")mS!8H|lAWnJx{uiW>8{,GI;=3sV=)r!ق ;AR!o>`쑷 u*y0;t-9cI:b  IQ|d^_%Lwrټ;TT(R(F(v"P$(HH"PDB(!(BHEJߓRߨhD-[~5^VNN\WФY{rږ\8*Q#^P#7zcn= x> ̕㛇t9;"DgTM D R/1(tTҘÆOyVJ#'Zp퀓,?߮`qMj8oG10Q/۵-7ݚBJcިEn'o9D`*`.&.[mCL5i(w#f Vnyz=8TK͔`-/篣HСE]׫N^7>;V\ckDx;+/@+ (spiR|n[ $kwr}`9kH߇pP_+Չ6iQ X5@J!t)՚=[XzOZֹqj l?<B7]]hɥy('45+X%A<7atSEJuuw& >U !.)L ?|QsRwv&$H(̼s֬WZ>7MlUe*l;2լ٬@i.PZ.@Qs`7("SލN^[{4WH&5,;m hߢN]}*H)%Rgz0`r" F7lۓ;h]`<'-3ЩPDD`J:4,7GHrS/Rt'@8n2#6g=Nj<*A,E(xSm5VdٓjS|ˬ hn4hע qT #̹E-vւJ;0cƄ^˟,FNkN&d:YɰuĝzJ=a#MG !Eyw&p%׹ X~F/n~#ܴxER. ?Q*%a{J6Iߕ)yVk6߮z`Z}#>ծt#QpB TKu.MwC6Âc(",Ӏ%:Rs^ejTk4\O((7V6kɔZ!JxfqɐF>u릗|'kyעn?CB|L-T*;#mW(X[UT6BfdI,Ї+i֗e` 7]3u9{3Tn=WFsIF#R*k|+|@k u\T6R o&njx ;#p@8:[d~A'Ԫ!R} *h JlD@X: ~ ԧ}8wuE-y#xt`y#z5%GCdɆw0mp;I)7_q"wc=3#.֒cYl9-G(X%ݻ8ۥ5vMV$.p`\պYeE`Y7LX8 6kcI yg#vԪ_I@lj}C8’!6)k:dkGlkkqV &anvC '[bR 9THXHP+asH_p;2ESm1HrED8T[}`†#^0YR"}]S+PPxݟکcFd:#uOPبOs\$?4?xoWX2-ouvG8B$c "}%&X yD*|WT+҆*BBQBl%fߔzH iN?X6gD>f+; \nuE}yD/SV uM;RA~l=Rv7IbX*[pi*2h[]!y[?Ta~?nq}J  WtMsn{˟ZŹ9d\g! )/@QK^yES81q:̴1cSGdmJO:uVáx{}+$cqEh7-`T7;획sFFmL:Lk6`+Em$7F>N}n p/$pj%#l6ϻ:]S es$ndYb4 cQ䐊.c*q HAs *R$ Z"A"Cn]$$EB!upJ!HRs =FRw ViWa5Mذ@&$R"B u]"Ѕ0z.t)5!uDH)@.B(*])uTD`2E(R76A s\ i29mtjnChR#хT@ץb+NL:uـoc<inkoN@7٦5_6qn!t1Ks&t%F.kjI]s: rRhg*0 ft]wM|J59L)ܢ ?:uX9 &IoO/yHƮƛ OÐsӘHNOmbVN.A)]EM3gTƔ ,O$tRI;?T/ݻOkB{#=8koRirx~"~\|$Zeg]4|l3u#pSs;bd&aƸA+R)W|Xb>`(h{/(lR,oV޴KnCТ-H_D%:OC~cҵÕu#LXѫ8rSy%t~]Jƾ Tr 6&~Jz%"l(!ė{ 0ؙV w7Fþߡtϋu[>JvD?Aݚo|ʔ*ZH;̜߬K־s"}#x,bAi:2";򂫵-u*-G9`<)n*9T 9"gTO1|8X țb5?<ޥG6F*-ec={AǖuEnn= zC 5uh'PcR(nBן[2eP>`z8[tKc ?0d'7O&spy9U]>HߌH` O5yF|<:[#}CBRE3S~>C{8oUl8HU:VTJx%lԼZgsdCY\aoQ^b}!`ܨ޴ilѳI;).FWS-pp wsյ)Cz4Ug ;3P``D > `gZ=8GiP;S2poN$ p)ҝ9{|K ; =I[aF<&gvF3]ٸ{k붆/ަcqn枢l0G/pQZSj%gpǤ؄ LKvZʗׇ˻qUz3hQ-xźG 6t;Ic#21>pp#{K4W߯+8N'Zrގc @p| Ɯ(+gN)}d3-(w= U5dfGfݴA 3_JJRcyu19٬\\sq'zt:nJ{7Þ`[T | #v-]ߓZ|\6Vln-?-ގ;Dٹ1 9hk>G^}6!$Ñ~L?|7MbB nõw*-BpEX-M ֻ8jD钥kӘV~ZCYnk8T^]3w[lAB191FGP1HĈ9PM,YƯKvxʈâܘ5'Wvatz#-1sY,]%kXS3(( mAtnS.ӣS#ڷ7FDO2*-xlÀK8v{68]ޟ|2>$;HGIԯHIlRk愚H/:Â+E>b @ #6y^ SK&/ttEKbT=5G`v*l98C Nˆo5sΒ5Tю-Ubh\a1ĕxů0<#/M+I$@ @+ M"ȡTÖN&N&V/öN''O'ƗN&ՖN&N%M&5O&M'cN$1N&M&<R)N%>N,M3 @ @+ ոhvN&N&Q)շN''O'ƗN&ՖN&N%I$N%N&M'VO&N'HJ+N&Q'OQ(&N%>P0U+@ ƺyZN&N&T.ӶN''O'ƗN&ՖN&N%M&N&O&xO&K#,N'N$bP(3N%>U ߿fCN&N&a=µN''O'ƗN&ՖN&N%N&ėN&P N&O&KN'oN&rN'AN%>ոV/N&N&tUҲN''O'ƗN&ՖN&N%N&N&N'4N&O&M%YO%tK-O(MǞděחO'N&N&wҰwN';N''O'ƗN&ՖN&N%O&qN&O%gN&ΗN%P&CO%tN'.prxݗN&N&T-ΫʧCO(-N';N''O'ƗN&ՖN&N%O(GN&O%N&ΗO&qN'.O%teAVƟߗN&N&eC³M"O(-M&ʾ؝X2N&N&N&N&fCۺuYN';N&ėN&ΗN&ؗN&N&L'a@ N&N'N'N%N&ŘN'@@N$UN'}O&qN' J!O$MN'A~ΫO(N&N&N&N&jʻfHN';N&ėN&ΗN&ؗN&N&L'aN&N'N'N&N&ŘO&M'BN'}O&qR$M$+O$MȺwN&N&N&N&P)ЭÈM$+M&5N%>N';N&ėN&ΗN&ؗN&N&L'aO'N'N&R)N&їN&ŘN'K#,N'}O&qL&/M&N';N&ėN&ΗN&ؗN&N&L'aM&N'N&N&sN&їN&ŘO&^KN'}O&qL&CȝxȣN&N&N&N&vWӾκQ#P( M$+M&5M$?L&6K&=N%EM%LO$TN$[N'bM&jL&rN&yP&O'N&ėN&ΗN&ؗN&N&L'aO'TN'N&N&ǗN&їN&ŗN';N(sO&qU/]ɽP)N&N&N&iەU Q#P( M$+M&5M$?M&IM%SO&^N%hN&rN%|N&M'M&M'O&O'N&ėN&ΗN&ؗN&N&L'aO#N'N&N&ݗN&јN&ęM&N&XO&qͬ~aN&N&N&qQסU Q#P( M$+M&5M$?M&IM%SO&^N%hN&rN%|N&M'M&M'O&O'N&ėN&ΗN&ؗN&N&L'aN'ėN&N&ݗN&їM&N$1O&qŸڗO'N&N&P)` Q#P( M$+M&5M$?M&IM%SO&^N%hN&rN%|N&M'M&M'O&O'N&ėN&ΗN&ؗN&N&M%SM'pN&N&ݗN&ѕL&WM X4qնN&N&N&pI@@Q#P( M$+M&5M$?M&IM%SO&^N%hN&rN%|N&M'M&M'O&O'N&ėN&ΗN&ؗN&N%ڟP U M'N&ݗO&f3̬P~N&N&N&U R$M$+M&5M$?M&IM%SO&^N%hN&rN%|N&M'M&M'O&O'N&ėN&ΗN&ҘM&P%0N!=lN&N&N& 9nN&N&N&~9ǡN&N&N&QɤP)ϭ{ö֗N&N&N&xZq/پߗN&N&N&eٳүU/N&N&N&ֺ9E´ޙQ*N&N&N&nN֜-ɣN&N&N&P)ѱڐ6ѳǠO'N&N&N&\7קdAN&N&N&N&fDͪĵǺؽ}T.N&N&N&N&W1 ̟[6N&N&N&N&N&N&N&N&N&N&N&N&N&\7ȪnMN&N&N&N&N&N&N&N&N&N&N&xZڏ׻ޤeBN&N&N&N&N&N&N&lLۀڋ׻ɣě˦ڿ| "??aa!!?!!100pppxx?Sigima-1.1.1/resources/Sigima.svg000066400000000000000000000457101514013333200166710ustar00rootroot00000000000000 image/svg+xmlS Sigima-1.1.1/resources/deploy.bat000066400000000000000000000011431514013333200167130ustar00rootroot00000000000000@echo off set INKSCAPE_PATH="C:\Program Files\Inkscape\bin\inkscape.exe" @REM Deploying images and icons copy Sigima.svg ..\sigima\data\logo copy Sigima-Title.svg ..\doc\_static %INKSCAPE_PATH% "Sigima-Frontpage.svg" -o "..\doc\_static\Sigima-Frontpage.png" -w 1300 %INKSCAPE_PATH% "Sigima-Banner.svg" -o "..\doc\images\Sigima-Banner.png" -w 364 @REM Generating icon call :generate_icon "Sigima" goto:eof :generate_icon set ICON_NAME=%1 for %%s in (16 24 32 48 128 256) do ( %INKSCAPE_PATH% "%ICON_NAME%.svg" -o "tmp-%%s.png" -w %%s -h %%s ) magick "tmp-*.png" "%ICON_NAME%.ico" del "tmp-*.png" goto:eof Sigima-1.1.1/scripts/000077500000000000000000000000001514013333200144055ustar00rootroot00000000000000Sigima-1.1.1/scripts/run_with_env.py000066400000000000000000000032311514013333200174650ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """Run a command with environment variables loaded from a .env file.""" from __future__ import annotations import os import subprocess import sys from pathlib import Path def load_env_file(env_path: str | None = None) -> None: """Load environment variables from a .env file.""" if env_path is None: # Get ".eenv" file from the current directory env_path = Path.cwd() / ".env" if not Path(env_path).is_file(): raise FileNotFoundError(f"Environment file not found: {env_path}") print(f"Loading environment variables from: {env_path}") with open(env_path, encoding="utf-8") as f: for line in f: line = line.strip() if not line or line.startswith("#") or "=" not in line: continue key, value = line.split("=", 1) os.environ[key.strip()] = value.strip() print(f" Loaded variable: {key.strip()}={value.strip()}") def execute_command(command: list[str]) -> int: """Execute a command with the loaded environment variables.""" print("Executing command:") print(" ".join(command)) print("") result = subprocess.call(command) print(f"Process exited with code {result}") return result def main() -> None: """Main function to load environment variables and execute a command.""" if len(sys.argv) < 2: print("Usage: python run_with_env.py [args ...]") sys.exit(1) print("🏃 Running with environment variables") load_env_file() return execute_command(sys.argv[1:]) if __name__ == "__main__": main() Sigima-1.1.1/sigima/000077500000000000000000000000001514013333200141675ustar00rootroot00000000000000Sigima-1.1.1/sigima/__init__.py000066400000000000000000000072371514013333200163110ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Sigima ====== Sigima is a scientific computing engine for 1D signals and 2D images. It provides a set of tools for image and signal processing, including denoising, segmentation, and restoration. It is designed to be used in scientific and research applications. It is a part of the DataLab Platform, which aims at providing a comprehensive set of tools for data analysis and visualization, around the DataLab application. """ # TODO: Use `numpy.typing.NDArray` for more precise type annotations once NumPy >= 1.21 # can be safely required (e.g. after raising the minimum required version of # scikit-image to >= 0.19). __all__ = [ "NO_ROI", "Checkerboard2DParam", "CircularROI", "ExponentialParam", "Gauss2DParam", "GaussParam", "GeometryResult", "ImageDatatypes", "ImageObj", "ImageROI", "ImageTypes", "KindShape", "LinearChirpParam", "LogisticParam", "LorentzParam", "NormalDistribution1DParam", "NormalDistribution2DParam", "PlanckParam", "PolygonalROI", "ROI1DParam", "ROI2DParam", "Ramp2DParam", "RectangularROI", "Ring2DParam", "SegmentROI", "SiemensStar2DParam", "SignalObj", "SignalROI", "SignalTypes", "SimpleBaseProxy", "SimpleRemoteProxy", "Sinc2DParam", "SinusoidalGrating2DParam", "StepParam", "TableResult", "TypeObj", "TypeROI", "UniformDistribution1DParam", "UniformDistribution2DParam", "VoigtParam", "calc_table_from_data", "create_image", "create_image_from_param", "create_image_parameters", "create_image_roi", "create_image_roi_around_points", "create_signal", "create_signal_from_param", "create_signal_parameters", "create_signal_roi", "read_image", "read_images", "read_signal", "read_signals", "write_image", "write_signal", ] from guidata.config import ValidationMode, set_validation_mode from sigima.client import SimpleBaseProxy, SimpleRemoteProxy from sigima.io import ( read_image, read_images, read_signal, read_signals, write_image, write_signal, ) from sigima.objects import ( NO_ROI, Checkerboard2DParam, CircularROI, ExponentialParam, Gauss2DParam, GaussParam, GeometryResult, ImageDatatypes, ImageObj, ImageROI, ImageTypes, KindShape, LinearChirpParam, LogisticParam, LorentzParam, NormalDistribution1DParam, NormalDistribution2DParam, PlanckParam, PolygonalROI, Ramp2DParam, RectangularROI, Ring2DParam, ROI1DParam, ROI2DParam, SegmentROI, SiemensStar2DParam, SignalObj, SignalROI, SignalTypes, Sinc2DParam, SinusoidalGrating2DParam, StepParam, TableResult, TypeObj, TypeROI, UniformDistribution1DParam, UniformDistribution2DParam, VoigtParam, calc_table_from_data, create_image, create_image_from_param, create_image_parameters, create_image_roi, create_image_roi_around_points, create_signal, create_signal_from_param, create_signal_parameters, create_signal_roi, ) # Set validation mode to ENABLED by default (issue warnings for invalid inputs) set_validation_mode(ValidationMode.ENABLED) __version__ = "1.1.1" __docurl__ = "https://sigima.readthedocs.io/" __homeurl__ = "https://github.com/DataLab-Platform/Sigima" __supporturl__ = "https://github.com/DataLab-Platform/sigima/issues/new/choose" # Dear (Debian, RPM, ...) package makers, please feel free to customize the # following path to module's data (images) and translations: DATAPATH = LOCALEPATH = "" Sigima-1.1.1/sigima/client/000077500000000000000000000000001514013333200154455ustar00rootroot00000000000000Sigima-1.1.1/sigima/client/__init__.py000066400000000000000000000065411514013333200175640ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ DataLab Client (:mod:`sigima.client`) ------------------------------------- The `sigima.client` module provides a proxy to DataLab application through XML-RPC protocol. DataLab may be controlled remotely using the `XML-RPC`_ protocol which is natively supported by Python (and many other languages). Remote controlling allows to access DataLab main features from a separate process. From an IDE ^^^^^^^^^^^ DataLab may be controlled remotely from an IDE (e.g. `Spyder`_ or any other IDE, or even a Jupyter Notebook) that runs a Python script. It allows to connect to a running DataLab instance, adds a signal and an image, and then runs calculations. This feature is exposed by the `sigima.client.SimpleRemoteProxy` class. From a third-party application ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ DataLab may also be controlled remotely from a third-party application, for the same purpose. If the third-party application is written in Python 3, it may directly use :py:class:`cdlclient.SimpleRemoteProxy` as mentioned above. From another language, it is also achievable, but it requires to implement a XML-RPC client in this language using the same methods of proxy server as in the :py:class:`cdlclient.SimpleRemoteProxy` class. Data (signals and images) may also be exchanged between DataLab and the remote client application, in both directions. The remote client application may be run on the same computer as DataLab or on different computer. In the latter case, the remote client application must know the IP address of the computer running DataLab. The remote client application may be run before or after DataLab. In the latter case, the remote client application must try to connect to DataLab until it succeeds. Supported features ^^^^^^^^^^^^^^^^^^ Supported features are the following: - Switch to signal or image panel - Remove all signals and images - Save current session to a HDF5 file - Open HDF5 files into current session - Browse HDF5 file - Open a signal or an image from file - Add a signal - Add an image - Get object list - Run calculation with parameters Example ^^^^^^^ Here is an example in Python 3 of a script that connects to a running DataLab instance, adds a signal and an image, and then runs calculations (the cell structure of the script make it convenient to be used in `Spyder`_ IDE): .. literalinclude:: ../examples/features/datalab_client.py Additional features ^^^^^^^^^^^^^^^^^^^ For simple remote controlling, :py:class:`sigima.client.SimpleRemoteProxy` may be used. For more advanced remote controlling, the `datalab.control.proxy.RemoteProxy` class provided by the DataLab package may be used. See DataLab documentation for more details about the ``datalab.control.proxy.RemoteProxy`` class (on the section "Remote control"). .. _XML-RPC: https://docs.python.org/3/library/xmlrpc.html .. _Spyder: https://www.spyder-ide.org/ API ^^^ Remote client ~~~~~~~~~~~~~ .. autoclass:: sigima.client.remote.SimpleRemoteProxy :members: Base proxy ~~~~~~~~~~ .. autoclass:: sigima.client.base.SimpleBaseProxy :members: """ from sigima.client.base import SimpleBaseProxy from sigima.client.remote import SimpleRemoteProxy __all__ = ["SimpleBaseProxy", "SimpleRemoteProxy"] # TODO: Refactor the `sigima.client` with `datalab.base` and `datalab.control.remote` Sigima-1.1.1/sigima/client/base.py000066400000000000000000000647441514013333200167500ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ DataLab Client base proxy module -------------------------------- """ from __future__ import annotations import abc from collections.abc import Callable from typing import TYPE_CHECKING import guidata.dataset as gds import numpy as np if TYPE_CHECKING: from collections.abc import Iterator from sigima.client.remote import ServerProxy from sigima.objects import ImageObj, SignalObj class SimpleAbstractDLControl(abc.ABC): """Simple abstract base class for controlling DataLab This is a subset of DataLab's AbstractDLControl, with only the methods that do not require DataLab object model to be implemented.""" def __len__(self) -> int: """Return number of objects""" return len(self.get_object_uuids()) def __getitem__( self, nb_id_title: int | str | None = None, ) -> SignalObj | ImageObj: """Return object""" return self.get_object(nb_id_title) def __iter__(self) -> Iterator[SignalObj | ImageObj]: """Iterate over objects""" uuids = self.get_object_uuids() for uuid in uuids: yield self.get_object(uuid) def __str__(self) -> str: """Return object string representation""" return super().__repr__() def __repr__(self) -> str: """Return object representation""" titles = self.get_object_titles() uuids = self.get_object_uuids() text = f"{str(self)} (DataLab, {len(titles)} items):\n" for uuid, title in zip(uuids, titles): text += f" {uuid}: {title}\n" return text def __bool__(self) -> bool: """Return True if model is not empty""" return bool(self.get_object_uuids()) def __contains__(self, id_title: str) -> bool: """Return True if object (UUID or title) is in model""" return id_title in (self.get_object_titles() + self.get_object_uuids()) @classmethod def get_public_methods(cls) -> list[str]: """Return all public methods of the class, except itself. Returns: list[str]: List of public methods """ return [ method for method in dir(cls) if not method.startswith("_") and method != "get_public_methods" ] @abc.abstractmethod def get_version(self) -> str: """Return DataLab version. Returns: str: DataLab version """ @abc.abstractmethod def close_application(self) -> None: """Close DataLab application""" @abc.abstractmethod def raise_window(self) -> None: """Raise DataLab window""" @abc.abstractmethod def get_current_panel(self) -> str: """Return current panel name. Returns: str: Panel name (valid values: "signal", "image", "macro")) """ @abc.abstractmethod def set_current_panel(self, panel: str) -> None: """Switch to panel. Args: panel (str): Panel name (valid values: "signal", "image", "macro")) """ @abc.abstractmethod def reset_all(self) -> None: """Reset all application data""" @abc.abstractmethod def toggle_auto_refresh(self, state: bool) -> None: """Toggle auto refresh state. Args: state (bool): Auto refresh state """ @abc.abstractmethod def toggle_show_titles(self, state: bool) -> None: """Toggle show titles state. Args: state (bool): Show titles state """ @abc.abstractmethod def save_to_h5_file(self, filename: str) -> None: """Save to a DataLab HDF5 file. Args: filename (str): HDF5 file name """ @abc.abstractmethod def open_h5_files( self, h5files: list[str] | None = None, import_all: bool | None = None, reset_all: bool | None = None, ) -> None: """Open a DataLab HDF5 file or import from any other HDF5 file. Args: h5files (list[str] | None): List of HDF5 files to open. Defaults to None. import_all (bool | None): Import all objects from HDF5 files. Defaults to None. reset_all (bool | None): Reset all application data. Defaults to None. """ @abc.abstractmethod def import_h5_file(self, filename: str, reset_all: bool | None = None) -> None: """Open DataLab HDF5 browser to Import HDF5 file. Args: filename (str): HDF5 file name reset_all (bool | None): Reset all application data. Defaults to None. """ @abc.abstractmethod def load_h5_workspace( self, h5files: list[str] | str, reset_all: bool = True ) -> None: """Load HDF5 workspace files without showing file dialog. This method loads one or more DataLab native HDF5 files directly, bypassing the file dialog. It is safe to call from the internal console or any context where Qt dialogs would cause threading issues. Args: h5files: Path(s) to HDF5 file(s). Can be a single path string or a list of paths. reset_all: If True (default), reset workspace before loading. If False, append to existing workspace. Raises: ValueError: if file is not a DataLab native HDF5 file """ @abc.abstractmethod def save_h5_workspace(self, filename: str) -> None: """Save workspace to HDF5 file without showing file dialog. This method saves the current workspace to a DataLab native HDF5 file directly, bypassing the file dialog. It is safe to call from the internal console or any context where Qt dialogs would cause threading issues. Args: filename: Path to the output HDF5 file """ @abc.abstractmethod def load_from_files(self, filenames: list[str]) -> None: """Open objects from files in current panel (signals/images). Args: filenames: list of file names """ @abc.abstractmethod def add_signal( self, title: str, xdata: np.ndarray, ydata: np.ndarray, xunit: str | None = None, yunit: str | None = None, xlabel: str | None = None, ylabel: str | None = None, ) -> bool: # pylint: disable=too-many-arguments """Add signal data to DataLab. Args: title (str): Signal title xdata (numpy.ndarray): X data ydata (numpy.ndarray): Y data xunit (str | None): X unit. Defaults to None. yunit (str | None): Y unit. Defaults to None. xlabel (str | None): X label. Defaults to None. ylabel (str | None): Y label. Defaults to None. Returns: bool: True if signal was added successfully, False otherwise Raises: ValueError: Invalid xdata dtype ValueError: Invalid ydata dtype """ @abc.abstractmethod # pylint: disable=too-many-arguments def add_image( self, title: str, data: np.ndarray, xunit: str | None = None, yunit: str | None = None, zunit: str | None = None, xlabel: str | None = None, ylabel: str | None = None, zlabel: str | None = None, ) -> bool: """Add image data to DataLab. Args: title (str): Image title data (numpy.ndarray): Image data xunit (str | None): X unit. Defaults to None. yunit (str | None): Y unit. Defaults to None. zunit (str | None): Z unit. Defaults to None. xlabel (str | None): X label. Defaults to None. ylabel (str | None): Y label. Defaults to None. zlabel (str | None): Z label. Defaults to None. Returns: bool: True if image was added successfully, False otherwise Raises: ValueError: Invalid data dtype """ @abc.abstractmethod def add_object( self, obj: SignalObj | ImageObj, group_id: str = "", set_current: bool = True ) -> None: """Add object to DataLab. Args: obj: Signal or image object group_id: group id in which to add the object. Defaults to "" set_current: if True, set the added object as current Returns: True if object was added successfully, False otherwise """ @abc.abstractmethod def load_from_directory(self, path: str) -> None: """Open objects from directory in current panel (signals/images). Args: path: directory path """ @abc.abstractmethod def add_group( self, title: str, panel: str | None = None, select: bool = False ) -> None: """Add group to DataLab. Args: title: Group title panel: Panel name (valid values: "signal", "image"). Defaults to None. select: Select the group after creation. Defaults to False. """ @abc.abstractmethod def get_sel_object_uuids(self, include_groups: bool = False) -> list[str]: """Return selected objects uuids. Args: include_groups: If True, also return objects from selected groups. Returns: List of selected objects uuids. """ @abc.abstractmethod def select_objects( self, selection: list[int | str], panel: str | None = None, ) -> None: """Select objects in current panel. Args: selection: List of object numbers (1 to N) or uuids to select panel: panel name (valid values: "signal", "image"). If None, current panel is used. Defaults to None. """ @abc.abstractmethod def select_groups( self, selection: list[int | str] | None = None, panel: str | None = None ) -> None: """Select groups in current panel. Args: selection: List of group numbers (1 to N), or list of group uuids, or None to select all groups. Defaults to None. panel (str | None): panel name (valid values: "signal", "image"). If None, current panel is used. Defaults to None. """ @abc.abstractmethod def delete_metadata( self, refresh_plot: bool = True, keep_roi: bool = False ) -> None: """Delete metadata of selected objects Args: refresh_plot: Refresh plot. Defaults to True. keep_roi: Keep ROI. Defaults to False. """ @abc.abstractmethod def get_group_titles_with_object_info( self, ) -> tuple[list[str], list[list[str]], list[list[str]]]: """Return groups titles and lists of inner objects uuids and titles. Returns: Tuple: groups titles, lists of inner objects uuids and titles """ @abc.abstractmethod def get_object_titles(self, panel: str | None = None) -> list[str]: """Get object (signal/image) list for current panel. Objects are sorted by group number and object index in group. Args: panel: panel name (valid values: "signal", "image", "macro"). If None, current data panel is used (i.e. signal or image panel). Returns: List of object titles Raises: ValueError: if panel not found """ @abc.abstractmethod def get_object( self, nb_id_title: int | str | None = None, panel: str | None = None, ) -> SignalObj | ImageObj: """Get object (signal/image) from index. Args: nb_id_title: Object number, or object id, or object title. Defaults to None (current object). panel: Panel name. Defaults to None (current panel). Returns: Object Raises: KeyError: if object not found """ @abc.abstractmethod def get_object_uuids( self, panel: str | None = None, group: int | str | None = None ) -> list[str]: """Get object (signal/image) uuid list for current panel. Objects are sorted by group number and object index in group. Args: panel: panel name (valid values: "signal", "image"). If None, current panel is used. group: Group number, or group id, or group title. Defaults to None (all groups). Returns: List of object uuids Raises: ValueError: if panel not found """ @abc.abstractmethod def get_object_shapes( self, nb_id_title: int | str | None = None, panel: str | None = None, ) -> list: """Get plot item shapes associated to object (signal/image). Args: nb_id_title: Object number, or object id, or object title. Defaults to None (current object). panel: Panel name. Defaults to None (current panel). Returns: List of plot item shapes """ @abc.abstractmethod def add_annotations_from_items( self, items: list, refresh_plot: bool = True, panel: str | None = None ) -> None: """Add object annotations (annotation plot items). Args: items (list): annotation plot items refresh_plot (bool | None): refresh plot. Defaults to True. panel (str | None): panel name (valid values: "signal", "image"). If None, current panel is used. """ @abc.abstractmethod def add_label_with_title( self, title: str | None = None, panel: str | None = None ) -> None: """Add a label with object title on the associated plot Args: title (str | None): Label title. Defaults to None. If None, the title is the object title. panel (str | None): panel name (valid values: "signal", "image"). If None, current panel is used. """ @abc.abstractmethod def run_macro(self, number_or_title: int | str | None = None) -> None: """Run macro. Args: number: Number of the macro (starting at 1). Defaults to None (run current macro, or does nothing if there is no macro). """ @abc.abstractmethod def stop_macro(self, number_or_title: int | str | None = None) -> None: """Stop macro. Args: number: Number of the macro (starting at 1). Defaults to None (stop current macro, or does nothing if there is no macro). """ @abc.abstractmethod def import_macro_from_file(self, filename: str) -> None: """Import macro from file Args: filename: Filename. """ @abc.abstractmethod def calc(self, name: str, param: gds.DataSet | None = None) -> None: """Call compute function ``name`` in current panel's processor. Args: name: Compute function name param: Compute function parameter. Defaults to None. Raises: ValueError: unknown function """ def __getattr__(self, name: str) -> Callable: """Return compute function ``name`` in current panel's processor. Args: name (str): Compute function name Returns: Callable: Compute function Raises: AttributeError: If compute function ``name`` does not exist """ def compute_func(param: gds.DataSet | None = None) -> gds.DataSet: """Compute function. Args: param (guidata.dataset.DataSet | None): Compute function parameter. Defaults to None. Returns: guidata.dataset.DataSet: Compute function result """ return self.calc(name, param) if name.startswith("compute_"): return compute_func raise AttributeError(f"DataLab has no compute function '{name}'") class SimpleBaseProxy(SimpleAbstractDLControl, metaclass=abc.ABCMeta): """Simple common base class for DataLab proxies This is a subset of DataLab's BaseProxy, with only the methods that do not require DataLab object model to be implemented. Args: datalab (DLMainWindow | ServerProxy | None): DLMainWindow instance or ServerProxy instance. If None, then the proxy implementation will have to set it later (e.g. see SimpleRemoteProxy). """ def __init__(self, datalab: ServerProxy | None = None) -> None: self._datalab = datalab def get_version(self) -> str: """Return DataLab version. Returns: str: DataLab version """ return self._datalab.get_version() def close_application(self) -> None: """Close DataLab application""" self._datalab.close_application() def raise_window(self) -> None: """Raise DataLab window""" self._datalab.raise_window() def get_current_panel(self) -> str: """Return current panel name. Returns: str: Panel name (valid values: "signal", "image", "macro")) """ return self._datalab.get_current_panel() def set_current_panel(self, panel: str) -> None: """Switch to panel. Args: panel (str): Panel name (valid values: "signal", "image", "macro")) """ self._datalab.set_current_panel(panel) def reset_all(self) -> None: """Reset all application data""" self._datalab.reset_all() def toggle_auto_refresh(self, state: bool) -> None: """Toggle auto refresh state. Args: state (bool): Auto refresh state """ self._datalab.toggle_auto_refresh(state) # Returns a context manager to temporarily disable autorefresh def context_no_refresh(self) -> Callable: """Return a context manager to temporarily disable auto refresh. Returns: Context manager Example: >>> with proxy.context_no_refresh(): ... proxy.add_image("image1", data1) ... proxy.compute_fft() ... proxy.compute_wiener() ... proxy.compute_ifft() ... # Auto refresh is disabled during the above operations """ class NoRefreshContextManager: """Context manager to temporarily disable auto refresh""" def __init__(self, datalab: SimpleAbstractDLControl) -> None: self._datalab = datalab def __enter__(self) -> None: self._datalab.toggle_auto_refresh(False) def __exit__(self, exc_type, exc_value, traceback) -> None: self._datalab.toggle_auto_refresh(True) return NoRefreshContextManager(self) def toggle_show_titles(self, state: bool) -> None: """Toggle show titles state. Args: state (bool): Show titles state """ self._datalab.toggle_show_titles(state) def save_to_h5_file(self, filename: str) -> None: """Save to a DataLab HDF5 file. Args: filename (str): HDF5 file name """ self._datalab.save_to_h5_file(filename) def open_h5_files( self, h5files: list[str] | None = None, import_all: bool | None = None, reset_all: bool | None = None, ) -> None: """Open a DataLab HDF5 file or import from any other HDF5 file. Args: h5files (list[str] | None): List of HDF5 files to open. Defaults to None. import_all (bool | None): Import all objects from HDF5 files. Defaults to None. reset_all (bool | None): Reset all application data. Defaults to None. """ self._datalab.open_h5_files(h5files, import_all, reset_all) def import_h5_file(self, filename: str, reset_all: bool | None = None) -> None: """Open DataLab HDF5 browser to Import HDF5 file. Args: filename (str): HDF5 file name reset_all (bool | None): Reset all application data. Defaults to None. """ self._datalab.import_h5_file(filename, reset_all) def load_h5_workspace( self, h5files: list[str] | str, reset_all: bool = True ) -> None: """Load HDF5 workspace files without showing file dialog. This method loads one or more DataLab native HDF5 files directly, bypassing the file dialog. It is safe to call from the internal console or any context where Qt dialogs would cause threading issues. Args: h5files: Path(s) to HDF5 file(s). Can be a single path string or a list of paths. reset_all: If True (default), reset workspace before loading. If False, append to existing workspace. Raises: ValueError: if file is not a DataLab native HDF5 file """ if isinstance(h5files, str): h5files = [h5files] self._datalab.load_h5_workspace(h5files, reset_all) def save_h5_workspace(self, filename: str) -> None: """Save workspace to HDF5 file without showing file dialog. This method saves the current workspace to a DataLab native HDF5 file directly, bypassing the file dialog. It is safe to call from the internal console or any context where Qt dialogs would cause threading issues. Args: filename: Path to the output HDF5 file """ self._datalab.save_h5_workspace(filename) def load_from_files(self, filenames: list[str]) -> None: """Open objects from files in current panel (signals/images). Args: filenames: list of file names """ self._datalab.load_from_files(filenames) def add_group( self, title: str, panel: str | None = None, select: bool = False ) -> None: """Add group to DataLab. Args: title: Group title panel: Panel name (valid values: "signal", "image"). Defaults to None. select: Select the group after creation. Defaults to False. """ self._datalab.add_group(title, panel, select) def get_sel_object_uuids(self, include_groups: bool = False) -> list[str]: """Return selected objects uuids. Args: include_groups: If True, also return objects from selected groups. Returns: List of selected objects uuids. """ return self._datalab.get_sel_object_uuids(include_groups) def select_objects( self, selection: list[int | str], panel: str | None = None, ) -> None: """Select objects in current panel. Args: selection: List of object numbers (1 to N) or uuids to select panel: panel name (valid values: "signal", "image"). If None, current panel is used. Defaults to None. """ self._datalab.select_objects(selection, panel) def select_groups( self, selection: list[int | str] | None = None, panel: str | None = None ) -> None: """Select groups in current panel. Args: selection: List of group numbers (1 to N), or list of group uuids, or None to select all groups. Defaults to None. panel (str | None): panel name (valid values: "signal", "image"). If None, current panel is used. Defaults to None. """ self._datalab.select_groups(selection, panel) def delete_metadata( self, refresh_plot: bool = True, keep_roi: bool = False ) -> None: """Delete metadata of selected objects Args: refresh_plot: Refresh plot. Defaults to True. keep_roi: Keep ROI. Defaults to False. """ self._datalab.delete_metadata(refresh_plot, keep_roi) def get_group_titles_with_object_info( self, ) -> tuple[list[str], list[list[str]], list[list[str]]]: """Return groups titles and lists of inner objects uuids and titles. Returns: Tuple: groups titles, lists of inner objects uuids and titles """ return self._datalab.get_group_titles_with_object_info() def get_object_titles(self, panel: str | None = None) -> list[str]: """Get object (signal/image) list for current panel. Objects are sorted by group number and object index in group. Args: panel: panel name (valid values: "signal", "image", "macro"). If None, current data panel is used (i.e. signal or image panel). Returns: List of object titles Raises: ValueError: if panel not found """ return self._datalab.get_object_titles(panel) def get_object_uuids( self, panel: str | None = None, group: int | str | None = None ) -> list[str]: """Get object (signal/image) uuid list for current panel. Objects are sorted by group number and object index in group. Args: panel: panel name (valid values: "signal", "image"). If None, current panel is used. group: Group number, or group id, or group title. Defaults to None (all groups). Returns: List of object uuids Raises: ValueError: if panel not found """ return self._datalab.get_object_uuids(panel, group) def add_label_with_title( self, title: str | None = None, panel: str | None = None ) -> None: """Add a label with object title on the associated plot Args: title (str | None): Label title. Defaults to None. If None, the title is the object title. panel (str | None): panel name (valid values: "signal", "image"). If None, current panel is used. """ self._datalab.add_label_with_title(title, panel) def run_macro(self, number_or_title: int | str | None = None) -> None: """Run macro. Args: number: Number of the macro (starting at 1). Defaults to None (run current macro, or does nothing if there is no macro). """ self._datalab.run_macro(number_or_title) def stop_macro(self, number_or_title: int | str | None = None) -> None: """Stop macro. Args: number: Number of the macro (starting at 1). Defaults to None (stop current macro, or does nothing if there is no macro). """ self._datalab.stop_macro(number_or_title) def import_macro_from_file(self, filename: str) -> None: """Import macro from file Args: filename: Filename. """ return self._datalab.import_macro_from_file(filename) Sigima-1.1.1/sigima/client/remote.py000066400000000000000000000377661514013333200173350ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Sigima Client Remote Control ---------------------------- This module provides utilities to control DataLab from a Python script (e.g. with Spyder) or from a Jupyter notebook. The :class:`SimpleRemoteProxy` class provides the main interface to DataLab XML-RPC server. """ from __future__ import annotations import configparser as cp import json import os import os.path as osp import sys import time import warnings from xmlrpc.client import ServerProxy import guidata.dataset as gds import numpy as np from guidata.env import execenv from guidata.io import JSONReader, JSONWriter from guidata.userconfig import get_config_basedir from packaging.version import Version from sigima.client.base import SimpleBaseProxy from sigima.client.utils import ( array_to_rpcbinary, dataset_to_rpcjson, rpcjson_to_dataset, ) from sigima.objects import ImageObj, SignalObj # pylint: disable=invalid-name # Allows short reference names like x, y, ... # pylint: disable=duplicate-code __required_server_version__ = "1.0.0" # Minimum required DataLab server version XMLRPCPORT_ENV = "DATALAB_XMLRPCPORT" def get_xmlrpcport_from_env() -> int | None: """Get XML-RPC port number from environment variable.""" try: return int(os.environ.get(XMLRPCPORT_ENV)) except (TypeError, ValueError): return None def get_cdl_xmlrpc_port(): """Return DataLab current XML-RPC port. This function attempts to read the XML-RPC port from DataLab's configuration file. It first tries the versioned configuration folders (starting with the latest version), and falls back to the legacy .DataLab folder for backward compatibility with DataLab v0.x. Returns: str: XML-RPC port number Raises: ConnectionRefusedError: DataLab has not yet been executed or configuration file is not accessible """ if sys.platform == "win32" and "HOME" in os.environ: os.environ.pop("HOME") # Avoid getting old WinPython settings dir config_basedir = get_config_basedir() # List of configuration folders to try, in order of preference # Try versioned folders first (v3, v2, v1), then legacy .DataLab config_folders = [ (".DataLab_v3", "DataLab_v3.ini"), # Future versions (".DataLab_v2", "DataLab_v2.ini"), (".DataLab_v1", "DataLab_v1.ini"), # Current stable (v1.x) (".DataLab", "DataLab.ini"), # Legacy (v0.x) ] # Try each configuration folder in order for folder_name, ini_name in config_folders: fname = osp.join(config_basedir, folder_name, ini_name) if osp.exists(fname): ini = cp.ConfigParser() try: ini.read(fname) port = ini.get("main", "rpc_server_port") # Successfully read port from this version's config return port except (cp.NoSectionError, cp.NoOptionError): # Config file exists but doesn't have the port yet, try next version continue # No valid configuration found raise ConnectionRefusedError( "DataLab has not yet been executed or no valid configuration found" ) def items_to_json(items: list) -> str | None: """Convert plot items to JSON string. Args: items (list): list of plot items Returns: str: JSON string or None if items is empty """ from plotpy.io import save_items # pylint: disable=import-outside-toplevel if items: writer = JSONWriter(None) save_items(writer, items) return writer.get_json(indent=4) return None def json_to_items(json_str: str | None) -> list: """Convert JSON string to plot items. Args: json_str (str): JSON string or None Returns: list: list of plot items """ from plotpy.io import load_items # pylint: disable=import-outside-toplevel items = [] if json_str: try: for item in load_items(JSONReader(json_str)): items.append(item) except json.decoder.JSONDecodeError: pass return items class SimpleRemoteProxy(SimpleBaseProxy): """Object representing a proxy/client to DataLab XML-RPC server. This object is used to call DataLab functions from a Python script. This is a subset of DataLab's `RemoteClient` class, with only the methods that do not require DataLab object model to be implemented. Args: autoconnect: If True, automatically connect to DataLab XML-RPC server. Defaults to True. Raises: ConnectionRefusedError: DataLab is currently not running Examples: Here is a simple example of how to use SimpleRemoteProxy in a Python script or in a Jupyter notebook: >>> from sigima.client import SimpleRemoteProxy >>> proxy = SimpleRemoteProxy() # autoconnect is on by default Connecting to DataLab XML-RPC server...OK (port: 28867) >>> proxy.get_version() '1.0.0' >>> proxy.add_signal("toto", np.array([1., 2., 3.]), np.array([4., 5., -1.])) True >>> proxy.get_object_titles() ['toto'] >>> proxy["toto"] >>> "toto" in proxy True >>> proxy[1] >>> proxy[1].data array([1., 2., 3.]) """ def __init__(self, autoconnect: bool = True) -> None: super().__init__() self.port: str = None self._datalab: ServerProxy if autoconnect: self.connect() def __connect_to_server(self, port: str | None = None) -> None: """Connect to DataLab XML-RPC server. Args: port (str | None): XML-RPC port to connect to. If not specified, the port is automatically retrieved from DataLab configuration. Raises: ConnectionRefusedError: DataLab is currently not running """ if port is None: port = get_xmlrpcport_from_env() if port is None: port = get_cdl_xmlrpc_port() self.port = port self._datalab = ServerProxy(f"http://127.0.0.1:{port}", allow_none=True) try: version = self.get_version() except ConnectionRefusedError as exc: raise ConnectionRefusedError("DataLab is currently not running") from exc # If DataLab version is not compatible with this client, show a warning # pylint: disable=cyclic-import from sigima import __version__ # pylint: disable=import-outside-toplevel server_ver = Version(version) client_ver = Version(__version__) required_ver = Version(__required_server_version__) # Compare base versions (ignore pre-release/dev identifiers) # This allows 1.0.0b1 to satisfy >= 1.0.0 requirement if server_ver.base_version < required_ver.base_version: warnings.warn( f"DataLab server version ({server_ver}) may not be fully compatible " f"with Sigima client version {client_ver} " f"(requires DataLab >= {__required_server_version__}).\n" f"Please upgrade DataLab to {__required_server_version__} or higher.", UserWarning, stacklevel=2, ) def connect( self, port: str | None = None, timeout: float | None = None, retries: int | None = None, ) -> None: """Try to connect to DataLab XML-RPC server. Args: port (str | None): XML-RPC port to connect to. If not specified, the port is automatically retrieved from DataLab configuration. timeout (float | None): Maximum time to wait for connection in seconds. Defaults to 5.0. This is the total maximum wait time, not per retry. retries (int | None): Number of retries. Defaults to 10. This parameter is deprecated and will be removed in a future version (kept for backward compatibility). Raises: ConnectionRefusedError: Unable to connect to DataLab ValueError: Invalid timeout (must be >= 0.0) ValueError: Invalid number of retries (must be >= 1) """ timeout = 5.0 if timeout is None else timeout retries = 10 if retries is None else retries # Kept for backward compatibility if timeout < 0.0: raise ValueError("timeout must be >= 0.0") if retries < 1: raise ValueError("retries must be >= 1") execenv.print("Connecting to DataLab XML-RPC server...", end="") # Use exponential backoff for more efficient retrying start_time = time.time() poll_interval = 0.1 # Start with 100ms max_poll_interval = 1.0 # Cap at 1 second while True: try: # Try to connect - this may fail if DataLab hasn't written its # config file yet, so we retry it in the loop self.__connect_to_server(port=port) elapsed = time.time() - start_time execenv.print(f"OK (port: {self.port}, connected in {elapsed:.1f}s)") return except (ConnectionRefusedError, OSError) as exc: # Catch both ConnectionRefusedError and OSError (includes socket errors) elapsed = time.time() - start_time if elapsed >= timeout: execenv.print("KO") raise ConnectionRefusedError( f"Unable to connect to DataLab after {elapsed:.1f}s" ) from exc # Wait before next retry with exponential backoff time.sleep(poll_interval) poll_interval = min(poll_interval * 1.5, max_poll_interval) def disconnect(self) -> None: """Disconnect from DataLab XML-RPC server.""" # This is not mandatory with XML-RPC, but if we change protocol in the # future, it may be useful to have a disconnect method. self._datalab = None def is_connected(self) -> bool: """Return True if connected to DataLab XML-RPC server.""" if self._datalab is not None: try: self.get_version() return True except ConnectionRefusedError: self._datalab = None return False def get_method_list(self) -> list[str]: """Return list of available methods.""" return self._datalab.system.listMethods() # === Following methods should match the register functions in XML-RPC server def add_signal( self, title: str, xdata: np.ndarray, ydata: np.ndarray, xunit: str | None = None, yunit: str | None = None, xlabel: str | None = None, ylabel: str | None = None, ) -> bool: # pylint: disable=too-many-arguments """Add signal data to DataLab. Args: title (str): Signal title xdata (numpy.ndarray): X data ydata (numpy.ndarray): Y data xunit (str | None): X unit. Defaults to None. yunit (str | None): Y unit. Defaults to None. xlabel (str | None): X label. Defaults to None. ylabel (str | None): Y label. Defaults to None. Returns: bool: True if signal was added successfully, False otherwise Raises: ValueError: Invalid xdata dtype ValueError: Invalid ydata dtype """ xbinary = array_to_rpcbinary(xdata) ybinary = array_to_rpcbinary(ydata) return self._datalab.add_signal( title, xbinary, ybinary, xunit, yunit, xlabel, ylabel ) # pylint: disable=too-many-arguments def add_image( self, title: str, data: np.ndarray, xunit: str | None = None, yunit: str | None = None, zunit: str | None = None, xlabel: str | None = None, ylabel: str | None = None, zlabel: str | None = None, ) -> bool: """Add image data to DataLab. Args: title (str): Image title data (numpy.ndarray): Image data xunit (str | None): X unit. Defaults to None. yunit (str | None): Y unit. Defaults to None. zunit (str | None): Z unit. Defaults to None. xlabel (str | None): X label. Defaults to None. ylabel (str | None): Y label. Defaults to None. zlabel (str | None): Z label. Defaults to None. Returns: bool: True if image was added successfully, False otherwise Raises: ValueError: Invalid data dtype """ zbinary = array_to_rpcbinary(data) return self._datalab.add_image( title, zbinary, xunit, yunit, zunit, xlabel, ylabel, zlabel ) def add_object( self, obj: SignalObj | ImageObj, group_id: str = "", set_current: bool = True ) -> None: """Add object to DataLab. Args: obj: Signal or image object group_id: group id in which to add the object. Defaults to "" set_current: if True, set the added object as current """ self._datalab.add_object(dataset_to_rpcjson(obj), group_id, set_current) def load_from_directory(self, path: str) -> None: """Open objects from directory in current panel (signals/images). Args: path: directory path """ self._datalab.load_from_directory(path) def calc(self, name: str, param: gds.DataSet | None = None) -> None: """Call compute function ``name`` in current panel's processor. Args: name: Compute function name param: Compute function parameter. Defaults to None. Raises: ValueError: unknown function """ if param is None: return self._datalab.calc(name) return self._datalab.calc(name, dataset_to_rpcjson(param)) def get_object( self, nb_id_title: int | str | None = None, panel: str | None = None, ) -> SignalObj | ImageObj: """Get object (signal/image) from index. Args: nb_id_title: Object number, or object id, or object title. Defaults to None (current object). panel: Panel name. Defaults to None (current panel). Returns: Object Raises: KeyError: if object not found """ param_data = self._datalab.get_object(nb_id_title, panel) if param_data is None: return None return rpcjson_to_dataset(param_data) def get_object_shapes( self, nb_id_title: int | str | None = None, panel: str | None = None, ) -> list: """Get plot item shapes associated to object (signal/image). Args: nb_id_title: Object number, or object id, or object title. Defaults to None (current object). panel: Panel name. Defaults to None (current panel). Returns: List of plot item shapes """ items_json = self._datalab.get_object_shapes(nb_id_title, panel) return json_to_items(items_json) def add_annotations_from_items( self, items: list, refresh_plot: bool = True, panel: str | None = None ) -> None: """Add object annotations (annotation plot items). .. note:: This method is only available if PlotPy is installed. Args: items (list): annotation plot items refresh_plot (bool | None): refresh plot. Defaults to True. panel (str | None): panel name (valid values: "signal", "image"). If None, current panel is used. """ try: items_json = items_to_json(items) except ImportError as exc: raise ImportError("PlotPy is not installed") from exc if items_json is not None: self._datalab.add_annotations_from_items(items_json, refresh_plot, panel) Sigima-1.1.1/sigima/client/stub.py000066400000000000000000001013261514013333200167770ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Sigima Client Stub/Mock Server (Real Objects) --------------------------------------------- This module provides a stub XML-RPC server that emulates DataLab's XML-RPC interface for testing purposes using real Sigima objects. The stub server allows tests to run without requiring a real DataLab instance. """ from __future__ import annotations import os import threading import uuid from contextlib import contextmanager from socketserver import ThreadingMixIn from typing import TYPE_CHECKING from xmlrpc.client import Binary from xmlrpc.server import SimpleXMLRPCServer from guidata.env import execenv from sigima.client import utils from sigima.objects import ImageObj, SignalObj, create_image, create_signal if TYPE_CHECKING: from collections.abc import Generator # pylint: disable=invalid-name # Allows short reference names like x, y, ... # pylint: disable=duplicate-code class MockGroup: """Mock group object.""" def __init__(self, title: str, uuid_str: str | None = None): self.title = title self.uuid = uuid_str or str(uuid.uuid4()) self.objects: list[str] = [] # List of object UUIDs class ThreadingXMLRPCServer(ThreadingMixIn, SimpleXMLRPCServer): """Threading XML-RPC server to handle multiple requests.""" daemon_threads = True allow_reuse_address = True class DataLabStubServer: """Stub XML-RPC server emulating DataLab XML-RPC interface with real objects. This server provides mock implementations of all DataLab XML-RPC methods using real SignalObj and ImageObj instances for maximum compatibility. Args: port: Port to bind to. If 0, uses a random available port. verbose: If True, print verbose debug information. """ def __init__(self, port: int = 0, verbose: bool = True) -> None: """Initialize the stub server. Args: port: Port to bind to. If 0, uses a random available port. """ self.port = port self.verbose = verbose self.server: ThreadingXMLRPCServer | None = None self.server_thread: threading.Thread | None = None # Real Sigima object storage self.signals: dict[str, SignalObj] = {} # uuid -> SignalObj self.images: dict[str, ImageObj] = {} # uuid -> ImageObj self.signal_groups: dict[str, MockGroup] = {} # uuid -> group self.image_groups: dict[str, MockGroup] = {} # uuid -> group # Current state self.current_panel = "signal" # "signal", "image", or "macro" self.selected_objects: list[str] = [] # list of UUIDs self.selected_groups: list[str] = [] # list of group UUIDs self.auto_refresh = True self.show_titles = True # Add default groups self._add_default_group("signal") self._add_default_group("image") def _add_default_group(self, panel: str) -> None: """Add default group for a panel.""" group = MockGroup("Group 1") if panel == "signal": self.signal_groups[group.uuid] = group elif panel == "image": self.image_groups[group.uuid] = group def start(self) -> int: """Start the XML-RPC server. Returns: Port number the server is listening on """ self.server = ThreadingXMLRPCServer( ("127.0.0.1", self.port), allow_none=True, logRequests=False ) # Register all methods self._register_functions() self.port = self.server.server_address[1] # Start server in a separate thread self.server_thread = threading.Thread( target=self.server.serve_forever, daemon=True ) self.server_thread.start() execenv.print(f"DataLab stub server started on port {self.port}") return self.port def stop(self) -> None: """Stop the XML-RPC server.""" if self.server: self.server.shutdown() self.server.server_close() if self.server_thread: self.server_thread.join(timeout=1.0) execenv.print("DataLab stub server stopped") def _register_functions(self) -> None: """Register all XML-RPC functions.""" # System introspection methods self.server.register_introspection_functions() # Basic server methods self.server.register_function(self.get_version, "get_version") self.server.register_function(self.close_application, "close_application") self.server.register_function(self.raise_window, "raise_window") # Panel management self.server.register_function(self.get_current_panel, "get_current_panel") self.server.register_function(self.set_current_panel, "set_current_panel") # Application control self.server.register_function(self.reset_all, "reset_all") self.server.register_function(self.remove_object, "remove_object") self.server.register_function(self.toggle_auto_refresh, "toggle_auto_refresh") self.server.register_function(self.toggle_show_titles, "toggle_show_titles") # File operations self.server.register_function(self.save_to_h5_file, "save_to_h5_file") self.server.register_function(self.open_h5_files, "open_h5_files") self.server.register_function(self.import_h5_file, "import_h5_file") self.server.register_function(self.load_h5_workspace, "load_h5_workspace") self.server.register_function(self.save_h5_workspace, "save_h5_workspace") # Object operations self.server.register_function(self.add_signal, "add_signal") self.server.register_function(self.add_image, "add_image") self.server.register_function(self.get_object_titles, "get_object_titles") self.server.register_function(self.get_object_uuids, "get_object_uuids") self.server.register_function(self.get_object, "get_object") self.server.register_function(self.get_object_shapes, "get_object_shapes") self.server.register_function(self.delete_metadata, "delete_metadata") # Selection operations self.server.register_function(self.select_objects, "select_objects") self.server.register_function(self.select_groups, "select_groups") self.server.register_function(self.get_sel_object_uuids, "get_sel_object_uuids") # Group operations self.server.register_function(self.add_group, "add_group") self.server.register_function( self.get_group_titles_with_object_info, "get_group_titles_with_object_info" ) # Calculation operations self.server.register_function(self.calc, "calc") # Annotation operations self.server.register_function( self.add_annotations_from_items, "add_annotations_from_items" ) self.server.register_function(self.add_label_with_title, "add_label_with_title") # Generic method calling self.server.register_function(self.call_method, "call_method") # Basic server methods def get_version(self) -> str: """Get DataLab version. Returns a valid PEP 440 version string for testing purposes. Since this is a stub server, we return "1.0.0" which is compliant with both PEP 440 and the minimum version requirement. """ return "1.0.0" def close_application(self) -> None: """Close DataLab application.""" # In stub mode, do nothing def raise_window(self) -> None: """Raise DataLab window.""" # In stub mode, do nothing # Panel management def get_current_panel(self) -> str: """Get current panel name.""" return self.current_panel def set_current_panel(self, panel: str) -> None: """Set current panel.""" if panel in ("signal", "image", "macro"): self.current_panel = panel # Application control def reset_all(self) -> None: """Reset all data.""" self.signals.clear() self.images.clear() self.selected_objects.clear() self.selected_groups.clear() def remove_object(self, force: bool = False) -> None: """Remove current object from current panel. Args: force: if True, remove object without confirmation. Defaults to False. """ # In stub mode, remove the first selected object if any if self.selected_objects: uuid_to_remove = self.selected_objects[0] execenv.print(f"[STUB] Removing object: force={force}") if uuid_to_remove in self.signals: del self.signals[uuid_to_remove] self.selected_objects.remove(uuid_to_remove) if self.verbose: execenv.print(f"[STUB] Removed signal: {uuid_to_remove}") elif uuid_to_remove in self.images: del self.images[uuid_to_remove] self.selected_objects.remove(uuid_to_remove) if self.verbose: execenv.print(f"[STUB] Removed image: {uuid_to_remove}") elif self.verbose: execenv.print("[STUB] No object selected to remove") def toggle_auto_refresh(self, state: bool) -> None: """Toggle auto refresh mode.""" self.auto_refresh = state if self.verbose: execenv.print(f"[STUB] Auto-refresh set to: {state}") def toggle_show_titles(self, state: bool) -> None: """Toggle show titles mode.""" self.show_titles = state if self.verbose: execenv.print(f"[STUB] Show titles set to: {state}") # File operations def save_to_h5_file(self, filename: str) -> None: """Save to a DataLab HDF5 file.""" if self.verbose: execenv.print(f"[STUB] Simulating H5 file save to: {filename}") # In stub mode, just create a dummy text file to simulate the save operation # This avoids HDF5 dependencies and potential test failures try: with open(filename, "w", encoding="utf-8") as f: f.write("# DataLab stub file (for testing)\n") f.write(f"# Signals: {len(self.signals)}\n") f.write(f"# Images: {len(self.images)}\n") f.write("# This is a dummy file created by the stub server\n") if self.verbose: execenv.print( f"[STUB] Successfully created dummy file with {len(self.signals)} " f"signals and {len(self.images)} images" ) except Exception as exc: # pylint: disable=broad-except if self.verbose: execenv.print(f"[STUB] Failed to create dummy file: {exc}") # Ignore errors in stub mode # pylint: disable=unused-argument def open_h5_files( self, h5files: list[str] | None = None, import_all: bool | None = None, reset_all: bool | None = None, ) -> None: """Open a DataLab HDF5 file or import from any other HDF5 file.""" if h5files is None: return if self.verbose: execenv.print(f"[STUB] Simulating H5 file loading: {h5files}") if reset_all: if self.verbose: execenv.print("[STUB] Resetting all data before loading") self.reset_all() # In stub mode, just simulate loading by creating dummy objects # This avoids complex HDF5 file parsing and potential test failures for _i, filename in enumerate(h5files): # Create a dummy signal for each file signal = create_signal(f"Loaded Signal from {os.path.basename(filename)}") self.signals[str(uuid.uuid4())] = signal if self.verbose: execenv.print(f"[STUB] Created dummy signal: {signal.title}") # Create a dummy image for each file image = create_image(f"Loaded Image from {os.path.basename(filename)}") self.images[str(uuid.uuid4())] = image if self.verbose: execenv.print(f"[STUB] Created dummy image: {image.title}") def import_h5_file(self, filename: str, reset_all: bool | None = None) -> None: """Open DataLab HDF5 browser to Import HDF5 file.""" self.open_h5_files([filename], import_all=True, reset_all=reset_all) def load_h5_workspace(self, h5files: list[str], reset_all: bool = True) -> None: """Load HDF5 workspace files without showing file dialog. This is a headless version that bypasses Qt file dialogs. Args: h5files: List of HDF5 file paths to load reset_all: If True (default), reset workspace before loading """ if self.verbose: execenv.print(f"[STUB] load_h5_workspace: {h5files}, reset_all={reset_all}") if reset_all: self.reset_all() # Simulate loading by creating dummy objects for each file for filename in h5files: signal = create_signal(f"Loaded Signal from {os.path.basename(filename)}") self.signals[str(uuid.uuid4())] = signal image = create_image(f"Loaded Image from {os.path.basename(filename)}") self.images[str(uuid.uuid4())] = image if self.verbose: execenv.print(f"[STUB] Created dummy signal and image for: {filename}") def save_h5_workspace(self, filename: str) -> None: """Save workspace to HDF5 file without showing file dialog. This is a headless version that bypasses Qt file dialogs. Args: filename: Path to the output HDF5 file """ if self.verbose: execenv.print(f"[STUB] save_h5_workspace: {filename}") # Create a dummy file to simulate save try: with open(filename, "w", encoding="utf-8") as f: f.write("# DataLab workspace stub file (for testing)\n") f.write(f"# Signals: {len(self.signals)}\n") f.write(f"# Images: {len(self.images)}\n") if self.verbose: execenv.print( f"[STUB] Successfully saved workspace with {len(self.signals)} " f"signals and {len(self.images)} images" ) except Exception as exc: # pylint: disable=broad-except if self.verbose: execenv.print(f"[STUB] Failed to save workspace: {exc}") # Object operations # pylint: disable=unused-argument def add_signal( self, title: str, xbinary: Binary, ybinary: Binary, xunit: str = "", yunit: str = "", xlabel: str = "", ylabel: str = "", group_id: str = "", set_current: bool = True, ) -> bool: """Add signal data to DataLab.""" xdata = utils.rpcbinary_to_array(xbinary) ydata = utils.rpcbinary_to_array(ybinary) # Create real SignalObj using factory function signal = create_signal(title, x=xdata, y=ydata) signal.xunit = xunit or "" signal.yunit = yunit or "" signal.xlabel = xlabel or "" signal.ylabel = ylabel or "" # Store signal obj_uuid = str(uuid.uuid4()) self.signals[obj_uuid] = signal # Add to group if specified if group_id and group_id in self.signal_groups: self.signal_groups[group_id].objects.append(obj_uuid) return True # pylint: disable=unused-argument def add_image( self, title: str, zbinary: Binary, xunit: str = "", yunit: str = "", zunit: str = "", xlabel: str = "", ylabel: str = "", zlabel: str = "", group_id: str = "", set_current: bool = True, ) -> bool: """Add image data to DataLab.""" data = utils.rpcbinary_to_array(zbinary) # Create real ImageObj using factory function image = create_image(title, data=data) image.xunit = xunit or "" image.yunit = yunit or "" image.zunit = zunit or "" image.xlabel = xlabel or "" image.ylabel = ylabel or "" image.zlabel = zlabel or "" # Store image obj_uuid = str(uuid.uuid4()) self.images[obj_uuid] = image # Add to group if specified if group_id and group_id in self.image_groups: self.image_groups[group_id].objects.append(obj_uuid) return True def add_object( self, obj_data: list[str], group_id: str = "", set_current: bool = True ) -> bool: """Add object to stub server. Args: obj_serialized: Serialized signal or image object group_id: group id in which to add the object. Defaults to "" set_current: if True, set the added object as current """ obj: SignalObj | ImageObj = utils.rpcjson_to_dataset(obj_data) if self.verbose: obj_str = "signal" if isinstance(obj, SignalObj) else "image" obj_uuid = str(uuid.uuid4()) print(f"Added {obj_str} {obj.title} with UUID {obj_uuid}") if isinstance(obj, SignalObj): self.signals[obj_uuid] = obj if group_id and group_id in self.signal_groups: self.signal_groups[group_id].objects.append(obj_uuid) else: self.images[obj_uuid] = obj if group_id and group_id in self.image_groups: self.image_groups[group_id].objects.append(obj_uuid) def load_from_files(self, filenames: list[str]) -> None: """Load objects from files (stub implementation). Args: filenames: list of file names """ if self.verbose: print( f"load_from_files called with {len(filenames)} files " "(stub - not implemented)" ) def load_from_directory(self, path: str) -> None: """Load objects from directory (stub implementation). Args: path: directory path """ if self.verbose: print( f"load_from_directory called with path: {path} (stub - not implemented)" ) def get_object_titles(self, panel: str | None = None) -> list[str]: """Get object titles for panel.""" panel = panel or self.current_panel if panel == "signal": return [signal.title for signal in self.signals.values()] if panel == "image": return [image.title for image in self.images.values()] return [] # pylint: disable=unused-argument def get_object_uuids( self, panel: str | None = None, group: int | str | None = None ) -> list[str]: """Get object UUIDs for panel.""" panel = panel or self.current_panel if panel == "signal": return list(self.signals.keys()) if panel == "image": return list(self.images.keys()) return [] def get_object(self, uuid_str: str, panel: str | None = None) -> list[str] | None: """Get object by UUID, index, or title.""" panel = panel or self.current_panel # Get the appropriate objects dictionary if panel == "signal": objects = self.signals object_list = list(self.signals.keys()) elif panel == "image": objects = self.images object_list = list(self.images.keys()) else: return None # Try to resolve uuid_str as UUID first if uuid_str in objects: obj = objects[uuid_str] else: # Try to resolve as 1-based index try: index = int(uuid_str) - 1 # Convert to 0-based if 0 <= index < len(object_list): uuid_key = object_list[index] obj = objects[uuid_key] else: return None except (ValueError, TypeError): # Try to find by title obj = None for object_instance in objects.values(): if object_instance.title == uuid_str: obj = object_instance break if obj is None: return None # Use standard serialization with real objects return utils.dataset_to_rpcjson(obj) # pylint: disable=unused-argument def get_object_shapes( self, uuid_str: str, panel: str | None = None ) -> list[dict] | None: """Get object shapes.""" obj = self.signals.get(uuid_str) or self.images.get(uuid_str) if obj is None: return None return [roi.to_dict() for roi in obj.roi] def delete_metadata(self, uuid_str: str, key: str) -> bool: """Delete metadata entry for object.""" obj = self.signals.get(uuid_str) or self.images.get(uuid_str) if obj is None: return False if key in obj.metadata: del obj.metadata[key] return True return False # Selection operations def select_objects( self, selection: list[int | str], panel: str | None = None ) -> None: """Select objects by indices or UUIDs.""" panel = panel or self.current_panel if panel == "signal": uuids = list(self.signals.keys()) elif panel == "image": uuids = list(self.images.keys()) else: return selected_uuids = [] for item in selection: if isinstance(item, str): # Item is a UUID if item in uuids: selected_uuids.append(item) elif isinstance(item, int): # Item is a 1-based index index = item - 1 # Convert to 0-based if 0 <= index < len(uuids): selected_uuids.append(uuids[index]) self.selected_objects = selected_uuids # pylint: disable=unused-argument def get_sel_object_uuids(self, include_groups: bool = False) -> list[str]: """Return selected objects uuids.""" return self.selected_objects.copy() def select_groups(self, selection: list[int], panel: str | None = None) -> None: """Select groups by indices.""" panel = panel or self.current_panel if panel == "signal": group_uuids = list(self.signal_groups.keys()) elif panel == "image": group_uuids = list(self.image_groups.keys()) else: return self.selected_groups = [ group_uuids[i] for i in selection if 0 <= i < len(group_uuids) ] # Group operations # pylint: disable=unused-argument def add_group( self, title: str, panel: str | None = None, select: bool = False ) -> str: """Add group and return UUID.""" panel = panel or self.current_panel group = MockGroup(title) if panel == "signal": self.signal_groups[group.uuid] = group elif panel == "image": self.image_groups[group.uuid] = group return group.uuid def get_group_titles_with_object_info( self, ) -> tuple[list[str], list[list[str]], list[list[str]]]: """Return groups titles and lists of inner objects uuids and titles.""" panel = self.current_panel if panel == "signal": groups = self.signal_groups objects = self.signals elif panel == "image": groups = self.image_groups objects = self.images else: return ([], [], []) group_titles = [] group_uuids_lists = [] group_titles_lists = [] for group in groups.values(): group_titles.append(group.title) # Get objects in this group object_uuids = [uuid for uuid in group.objects if uuid in objects] object_titles = [ objects[uuid].title for uuid in object_uuids if uuid in objects ] group_uuids_lists.append(object_uuids) group_titles_lists.append(object_titles) return (group_titles, group_uuids_lists, group_titles_lists) # Macro operations (stub implementations) def import_macro_from_file(self, filename: str) -> None: """Import macro from file (stub implementation). Args: filename: Filename """ if self.verbose: print(f"import_macro_from_file called: {filename} (stub - not implemented)") def run_macro(self, number_or_title: int | str | None = None) -> None: """Run macro (stub implementation). Args: number_or_title: Number or title of the macro. Defaults to None. """ if self.verbose: print(f"run_macro called: {number_or_title} (stub - not implemented)") def stop_macro(self, number_or_title: int | str | None = None) -> None: """Stop macro (stub implementation). Args: number_or_title: Number or title of the macro. Defaults to None. """ if self.verbose: print(f"stop_macro called: {number_or_title} (stub - not implemented)") # Calculation operations def calc(self, name: str, param: list[str] | None = None) -> str | None: """Execute calculation and return result object UUID.""" if self.verbose: execenv.print( f"[STUB] Simulating calculation '{name}' with params: {param}" ) # In stub mode, just simulate by creating a dummy result object if not self.selected_objects: if self.verbose: execenv.print("[STUB] No objects selected for calculation") return None src_uuid = self.selected_objects[0] src_obj = self.signals.get(src_uuid) or self.images.get(src_uuid) if src_obj is None: if self.verbose: execenv.print(f"[STUB] Source object {src_uuid} not found") return None # Create a dummy result object based on source type if isinstance(src_obj, SignalObj): result = create_signal(f"{name}({src_obj.title})") obj_uuid = str(uuid.uuid4()) self.signals[obj_uuid] = result if self.verbose: execenv.print(f"[STUB] Created dummy signal result: {result.title}") return obj_uuid if isinstance(src_obj, ImageObj): result = create_image(f"{name}({src_obj.title})") obj_uuid = str(uuid.uuid4()) self.images[obj_uuid] = result if self.verbose: execenv.print(f"[STUB] Created dummy image result: {result.title}") return obj_uuid if self.verbose: execenv.print("[STUB] Unsupported object type for calculation") return None # Generic method calling def call_method(self, method_name: str, call_params: dict): """Call a public method on a panel or main window. Args: method_name: Name of the method to call call_params: Dictionary with keys 'args' (list), 'panel' (str|None), 'kwargs' (dict). Defaults to empty for missing keys. Returns: The return value of the called method (stub returns None) Raises: AttributeError: If the method does not exist or is not public """ args = call_params.get("args", []) panel = call_params.get("panel") kwargs = call_params.get("kwargs", {}) if self.verbose: execenv.print( f"[STUB] Calling method '{method_name}' with args={args}, " f"panel={panel}, kwargs={kwargs}" ) # Check if the method exists on the stub server itself if hasattr(self, method_name) and not method_name.startswith("_"): method = getattr(self, method_name) if callable(method): try: return method(*args, **kwargs) except TypeError as exc: if self.verbose: execenv.print( f"[STUB] Method '{method_name}' exists but failed: {exc}" ) raise AttributeError( f"Method '{method_name}' has incompatible signature" ) from exc # For methods that don't exist, just log and return None if self.verbose: execenv.print( f"[STUB] Method '{method_name}' not implemented in stub server" ) return None # Annotation operations # pylint: disable=unused-argument def add_annotations_from_items( self, items: list[str], refresh_plot: bool = True, panel: str | None = None ) -> None: """Add object annotations (annotation plot items).""" # In stub mode, just acknowledge the annotations # Real implementation would deserialize items and add to objects # pylint: disable=unused-argument def add_label_with_title( self, title: str | None = None, panel: str | None = None ) -> None: """Add label with title.""" if self.verbose: execenv.print(f"[STUB] Simulating add label with title: {title}") # In stub mode, just acknowledge the label # ========================================================================= # Web API control methods (stub implementations) # ========================================================================= # pylint: disable=unused-argument def start_webapi_server( self, host: str | None = None, port: int | None = None, ) -> dict: """Start the Web API server (stub implementation). Args: host: Host address to bind to. Defaults to "127.0.0.1". port: Port number. Defaults to auto-detect available port. Returns: Dictionary with "url" and "token" keys. """ if self.verbose: execenv.print( f"[STUB] Simulating start_webapi_server(host={host}, port={port})" ) # Return a dummy response return {"url": "http://127.0.0.1:8000", "token": "stub-token"} def stop_webapi_server(self) -> None: """Stop the Web API server (stub implementation).""" if self.verbose: execenv.print("[STUB] Simulating stop_webapi_server()") # Nothing to do in stub mode def get_webapi_status(self) -> dict: """Get Web API server status (stub implementation). Returns: Dictionary with "running", "url", and "token" keys. """ if self.verbose: execenv.print("[STUB] Simulating get_webapi_status()") # Return a dummy status (server not running in stub mode) return {"running": False, "url": None, "token": None} @contextmanager def datalab_stub_server( port: int = 0, verbose: bool = True ) -> Generator[int, None, None]: """Context manager for DataLab stub server. Args: port: Port to bind to. If 0, uses a random available port. verbose: If True, print verbose debug information. Yields: Port number the server is listening on """ server = DataLabStubServer(port, verbose=verbose) try: actual_port = server.start() yield actual_port finally: server.stop() def patch_simpleremoteproxy_for_stub() -> DataLabStubServer: """Patch SimpleRemoteProxy to connect to a stub server instead of real DataLab. This utility function: 1. Creates and starts a DataLabStubServer instance 2. Patches SimpleRemoteProxy.__connect_to_server to use the stub server port 3. Returns the stub server instance for later cleanup Returns: The running DataLabStubServer instance that needs to be stopped later Example: >>> stub_server = patch_simpleremoteproxy_for_stub() >>> try: ... # Your code using SimpleRemoteProxy here ... proxy = SimpleRemoteProxy() ... # proxy will connect to stub server automatically ... finally: ... stub_server.stop() """ # pylint: disable=import-outside-toplevel # Import directly from remote module to avoid circular dependency from sigima.client.remote import SimpleRemoteProxy # Store original method # pylint: disable=protected-access original_connect_to_server = SimpleRemoteProxy._SimpleRemoteProxy__connect_to_server # Start stub server stub_server_instance = DataLabStubServer(verbose=False) stub_port = stub_server_instance.start() # pylint: disable=unused-argument def patched_connect_to_server(self, port=None): """Patched connect that uses stub server port.""" # Always use the stub server port, ignore the requested port original_connect_to_server(self, port=str(stub_port)) # Apply the patch # pylint: disable=protected-access SimpleRemoteProxy._SimpleRemoteProxy__connect_to_server = patched_connect_to_server return stub_server_instance Sigima-1.1.1/sigima/client/utils.py000066400000000000000000000044721514013333200171660ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Sigima Client Utilities ----------------------- Common utilities shared between client remote control and stub server modules. """ from __future__ import annotations import importlib from io import BytesIO from xmlrpc.client import Binary import guidata.dataset as gds import numpy as np from guidata.io import JSONReader, JSONWriter # pylint: disable=duplicate-code def array_to_rpcbinary(data: np.ndarray) -> Binary: """Convert NumPy array to XML-RPC Binary object, with shape and dtype. The array is converted to a binary string using NumPy's native binary format. Args: data: NumPy array to convert Returns: XML-RPC Binary object """ dbytes = BytesIO() np.save(dbytes, data, allow_pickle=False) return Binary(dbytes.getvalue()) def rpcbinary_to_array(binary: Binary) -> np.ndarray: """Convert XML-RPC binary to NumPy array. Args: binary: XML-RPC Binary object Returns: NumPy array """ dbytes = BytesIO(binary.data) return np.load(dbytes, allow_pickle=False) def dataset_to_rpcjson(param: gds.DataSet) -> list[str]: """Convert guidata DataSet to XML-RPC compatible JSON data. The JSON data is a list of three elements: - The first element is the module name of the DataSet class - The second element is the class name of the DataSet class - The third element is the JSON data of the DataSet instance Args: param: guidata DataSet to convert Returns: XML-RPC compatible JSON data (3-element list) """ writer = JSONWriter() param.serialize(writer) param_json = writer.get_json() klass = param.__class__ return [klass.__module__, klass.__name__, param_json] def rpcjson_to_dataset(param_data: list[str]) -> gds.DataSet: """Convert XML-RPC compatible JSON data to guidata DataSet. Args: param_data: XML-RPC compatible JSON data (3-element list) Returns: guidata DataSet """ param_module, param_clsname, param_json = param_data mod = importlib.__import__(param_module, fromlist=[param_clsname]) klass = getattr(mod, param_clsname) param: gds.DataSet = klass() reader = JSONReader(param_json) param.deserialize(reader) return param Sigima-1.1.1/sigima/config.py000066400000000000000000000372041514013333200160140ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Configuration (:mod:`sigima.config`) ------------------------------------- The :mod:`sigima.config` module provides a way to manage configuration options for the `sigima` library, as well as to handle translations and data paths, and other configuration-related tasks. It allows users to set and retrieve options that affect the behavior of the library, such as whether to keep results of computations or not. The options are handled as in-memory objects with default values provided, and can be temporarily overridden using a context manager. Typical usage: .. code-block:: python from sigima.config import options # Get an option value = options.fft_shift_enabled.get(default=True) # Set an option options.fft_shift_enabled.set(False) # Temporarily override an option with options.fft_shift_enabled.context(True): ... The following table lists the available options: .. options-table:: .. note:: The options are stored in an environment variable in JSON format, allowing for synchronization with external configurations or other processes that may need to read or modify the options. The environment variable name is defined by :attr:`sigima.config.OptionsContainer.ENV_VAR`. This is especially useful for applications such as DataLab (where the `sigima` library is used as a core component) as computations may be run in separate processes. """ from __future__ import annotations import json import os from contextlib import contextmanager from typing import Any, Generator from guidata import configtools # Translation and data path configuration MOD_NAME = "sigima" _ = configtools.get_translation(MOD_NAME) DATAPATH = configtools.get_module_data_path(MOD_NAME, "data") class OptionField: """A configurable option field with get/set/context interface. Args: container: Options container instance to which this option belongs. name: Name of the option (used for introspection or errors). default: Default value of the option. """ def __init__( self, container: OptionsContainer, name: str, default: Any, description: str = "", ) -> None: self._container = container self.name = name self.check(default) # Validate the default value self._value = default self.description = description def check(self, value: Any) -> None: # pylint: disable=unused-argument """Check if the value is valid for this option. Args: value: The value to check. Raises: ValueError: If the value is not valid. """ # This method can be overridden in subclasses for specific validation def get(self, sync_env: bool = True) -> Any: """Return the current value of the option. Args: sync_env: Whether to ensure the environment variable is synchronized with the current value. Returns: The current value of the option. """ if sync_env: self._container.ensure_loaded_from_env() return self._value def set(self, value: Any, sync_env: bool = True) -> None: """Set the value of the option. Args: value: The new value to assign. sync_env: Whether to synchronize the environment variable. """ self.check(value) # Validate the new value self._value = value if sync_env: self._container.sync_env() def context(self, temp_value: Any) -> Generator[None, None, None]: """Temporarily override the option within a context. Args: temp_value: Temporary value to use within the context. Yields: None. Restores the original value upon exit. """ @contextmanager def _ctx(): old_value = self._value self.set(temp_value) try: yield finally: self.set(old_value) return _ctx() class TypedOptionField(OptionField): """A configurable option field with type checking. Args: container: Options container instance to which this option belongs. name: Name of the option (used for introspection or errors). default: Default value of the option. expected_type: Expected type of the option value. description: Description of the option. """ def __init__( self, container: OptionsContainer, name: str, default: Any, expected_type: type, description: str = "", ) -> None: self.expected_type = expected_type super().__init__(container, name, default, description) def check(self, value: Any) -> None: """Check if the value is of the expected type. Args: value: The value to check. Raises: ValueError: If the value is not of the expected type. """ if not isinstance(value, self.expected_type): raise ValueError( f"Expected {self.expected_type.__name__}, got {type(value).__name__}" ) class ImageIOOptionField(OptionField): """A configurable option field for image I/O formats. .. note:: This option is specifically for image I/O formats and expects a tuple of tuples (or list of lists) of strings representing the formats, similar to the following: ... code-block:: python imageio_formats = ( ("*.gel", "Opticks GEL"), ("*.spe", "Princeton Instruments SPE"), ("*.ndpi", "Hamamatsu Slide Scanner NDPI"), ("*.rec", "PCO Camera REC"), ) Args: container: Options container instance to which this option belongs. name: Name of the option (used for introspection or errors). default: Default value of the option. description: Description of the option. """ def check( self, value: list[list[str, str]] | list[tuple[str, str]] | tuple[tuple[str, str]] | tuple[list[str, str]], ) -> None: """Check if the value is a valid image I/O format. Args: value: The value to check. Raises: ValueError: If the value is not a valid image I/O format. """ if not isinstance(value, (tuple, list)) or not all( isinstance(item, (tuple, list)) and len(item) == 2 for item in value ): raise ValueError( "Expected a tuple of tuples with two elements each " "(format, description)" ) for item in value: if not isinstance(item[0], str) or not isinstance(item[1], str): raise ValueError( "Each item must be a tuple of (format, description) as strings" ) def set(self, value: Any, sync_env: bool = True) -> None: """Set the value of the option. Args: value: The new value to assign. sync_env: Whether to synchronize the environment variable. """ super().set(value, sync_env) # pylint: disable=cyclic-import # pylint: disable=import-outside-toplevel from sigima.io.image import formats # Generate image I/O format classes based on the new value # This allows dynamic loading of formats based on the configuration formats.generate_imageio_format_classes(value) IMAGEIO_FORMATS = ( ("*.gel", "Opticks GEL"), ("*.spe", "Princeton Instruments SPE"), ("*.ndpi", "Hamamatsu Slide Scanner NDPI"), ("*.rec", "PCO Camera REC"), ) # Default image I/O formats class OptionsContainer: """Container for all configurable options in the `sigima` library. Options are exposed as attributes with `.get()`, `.set()` and `.context()` methods. """ #: Environment variable name for options in JSON format # This is used to synchronize options with external configurations or with # separate processes that may need to read or modify the options. ENV_VAR = "SIGIMA_OPTIONS_JSON" @classmethod def set_env(cls, value: str) -> None: """Set the environment variable with the given JSON string. Args: value: A JSON string representation of the options to set. """ os.environ[cls.ENV_VAR] = value @classmethod def get_env(cls) -> str: """Get the current value of the environment variable. Returns: The JSON string representation of the options from the environment variable. """ return os.environ.get(cls.ENV_VAR, "{}") def __init__(self) -> None: self.fft_shift_enabled = TypedOptionField( self, "fft_shift_enabled", default=True, expected_type=bool, description=_( "If True, the FFT operations will apply a shift to the zero frequency " "component to the center of the spectrum. This is useful for " "visualizing frequency components in a more intuitive way." ), ) self.auto_normalize_kernel = TypedOptionField( self, "auto_normalize_kernel", default=False, expected_type=bool, description=_( "If True, convolution kernels will be automatically normalized to " "sum to 1.0 before convolution. This ensures that the output signal " "or image has the same overall magnitude as the input when using " "smoothing kernels. Set to False to preserve the mathematical " "properties of the original kernel." ), ) self.imageio_formats = ImageIOOptionField( self, "imageio_formats", default=IMAGEIO_FORMATS, description=_( """List of supported image I/O formats. Each format is a tuple of ``(file_extension, description)``. The ``sigima`` library supports any image format that can be read by the ``imageio`` library, provided that the associated plugin(s) are installed (see `imageio documentation `_) and that the output NumPy array data type and shape are supported by ``sigima``. To add a new file format, you may use the ``imageio_formats`` option to specify additional formats. Each entry should be a tuple of (file extension, description). """ ), ) self.viz_backend = TypedOptionField( self, "viz_backend", default="auto", expected_type=str, description=_( """Backend library for visualization (sigima.viz module). Valid values: ``"auto"``, ``"plotpy"``, ``"matplotlib"``. - ``"auto"`` (default): Automatically select PlotPy if available, otherwise Matplotlib - ``"plotpy"``: Use PlotPy for interactive visualizations (requires PlotPy and Qt) - ``"matplotlib"``: Use Matplotlib for visualizations (simpler, view-only) This setting can also be overridden using the ``SIGIMA_VIZ_BACKEND`` environment variable. Note that Matplotlib backend does not support all features of PlotPy (e.g., ``create_segment()``, ``create_cursor()``, etc. will raise NotImplementedError). """ ), ) # Add new options here def describe_all(self) -> None: """Print the name, value, and description of all options.""" for name in vars(self): opt = getattr(self, name) if isinstance(opt, OptionField): print(f"{name} = {opt.get()} # {opt.description}") def generate_rst_doc(self) -> str: """Generate reStructuredText documentation for all options. Returns: A string containing the reStructuredText documentation. """ doc = """.. list-table:: :header-rows: 1 :align: left * - Name - Default Value - Description """ for name in vars(self): opt = getattr(self, name) if isinstance(opt, OptionField): # Process description to work within table cells description = opt.description.strip() # For table cells, we need to indent continuation lines properly # and handle multi-line content correctly description_lines = description.split("\n") if len(description_lines) > 1: # Multi-line descriptions need special handling in RST tables processed_lines = [description_lines[0]] # First line for line in description_lines[1:]: if line.strip(): # Non-empty lines processed_lines.append(" " + line.strip()) else: # Empty lines processed_lines.append("") description = "\n".join(processed_lines) # Get the value and format it nicely value = repr(opt.get(sync_env=False)) if len(value) > 200: # Truncate very long values value = value[:197] + "..." doc += f" * - ``{name}``\n" doc += f" - ``{value}``\n" doc += f" - {description}\n" return doc def ensure_loaded_from_env(self) -> None: """Lazy-load from JSON env var on first access.""" value = self.get_env() try: values = json.loads(value) self.from_dict(values) except Exception as exc: # pylint: disable=broad-except # If loading fails, we just log a warning and continue with defaults print(f"[sigima] Warning: failed to load options from env: {exc}") def to_env_json(self) -> str: """Return the current options as a JSON string for environment variable. Returns: A JSON string representation of the current options. """ return json.dumps(self.to_dict()) def sync_env(self) -> None: """Update env var with current option values.""" self.set_env(self.to_env_json()) def to_dict(self) -> dict[str, Any]: """Return the current option values as a dictionary. Returns: A dictionary with option names as keys and their current values. """ return { name: getattr(self, name).get(sync_env=False) for name in vars(self) if isinstance(getattr(self, name), OptionField) } def from_dict(self, values: dict[str, Any]) -> None: """Set option values from a dictionary. Args: values: A dictionary with option names as keys and their new values. """ for name, value in values.items(): if hasattr(self, name): opt = getattr(self, name) if isinstance(opt, OptionField): opt.set(value, sync_env=False) self.sync_env() #: Global instance of the options container options = OptionsContainer() # Generate OPTIONS_RST at module load time after options is created # This avoids circular import issues since everything is already loaded OPTIONS_RST = options.generate_rst_doc() def __getattr__(name: str): """Handle lazy evaluation of module-level attributes. This provides backward compatibility for any code that might access OPTIONS_RST. """ if name == "OPTIONS_RST": # Return the global variable if it exists, otherwise generate it return globals().get("OPTIONS_RST", options.generate_rst_doc()) raise AttributeError(f"module '{__name__}' has no attribute '{name}'") Sigima-1.1.1/sigima/data/000077500000000000000000000000001514013333200151005ustar00rootroot00000000000000Sigima-1.1.1/sigima/data/logo/000077500000000000000000000000001514013333200160405ustar00rootroot00000000000000Sigima-1.1.1/sigima/data/logo/Sigima.svg000066400000000000000000000457101514013333200200010ustar00rootroot00000000000000 image/svg+xmlS Sigima-1.1.1/sigima/data/tests/000077500000000000000000000000001514013333200162425ustar00rootroot00000000000000Sigima-1.1.1/sigima/data/tests/annotations.json000066400000000000000000000516441514013333200215040ustar00rootroot00000000000000{ "AnnotatedPoint_001": { "annotationparam": { "show_label": true, "show_computations": true, "title": "", "subtitle": "", "format": "%.1f", "uncertainty": 0.0, "transform_matrix": [ "array", [ [ 1.0, 0.0, 0.0 ], [ 0.0, 1.0, 0.0 ], [ 0.0, 0.0, 1.0 ] ], "float64" ], "readonly": false, "private": false }, "shapeparam": { "label": "", "line": { "style": "SolidLine", "color": "#000000", "width": 1.0 }, "sel_line": { "style": "SolidLine", "color": "#000000", "width": 1.0 }, "symbol": { "marker": "Ellipse", "size": 6, "edgecolor": "#808080", "facecolor": "#ffff00", "alpha": 1.0 }, "sel_symbol": { "marker": "Ellipse", "size": 6, "edgecolor": "#808080", "facecolor": "#ffff00", "alpha": 1.0 }, "fill": { "style": "SolidPattern", "color": "#000000", "alpha": 1.0, "angle": 0.0, "sx": 1.0, "sy": 1.0 }, "sel_fill": { "style": "SolidPattern", "color": "#000000", "alpha": 1.0, "angle": 0.0, "sx": 1.0, "sy": 1.0 }, "readonly": false, "private": false }, "points": [ "array", [ [ 15.0, 400.0 ] ], "float64" ], "closed": false, "z": 0.0, "labelparam": { "label": "", "contents": "", "symbol": { "marker": "NoSymbol", "size": 0, "edgecolor": "white", "facecolor": "white", "alpha": 1.0 }, "border": { "style": "SolidLine", "color": "#cbcbcb", "width": 0 }, "font": { "family": "default", "size": 8, "bold": false, "italic": false }, "color": "white", "bgcolor": "black", "bgalpha": 0.25, "anchor": "TL", "xc": 5, "yc": 5, "abspos": false, "xg": 15.0, "yg": 400.0, "move_anchor": true, "absg": "TL" }, "text": "( 15.0 ; 400.0 )" }, "AnnotatedPoint_002": { "annotationparam": { "show_label": true, "show_computations": true, "title": "", "subtitle": "", "format": "%.1f", "uncertainty": 0.0, "transform_matrix": [ "array", [ [ 1.0, 0.0, 0.0 ], [ 0.0, 1.0, 0.0 ], [ 0.0, 0.0, 1.0 ] ], "float64" ], "readonly": false, "private": false }, "shapeparam": { "label": "", "line": { "style": "SolidLine", "color": "#000000", "width": 1.0 }, "sel_line": { "style": "SolidLine", "color": "#000000", "width": 1.0 }, "symbol": { "marker": "Ellipse", "size": 6, "edgecolor": "#808080", "facecolor": "#ffff00", "alpha": 1.0 }, "sel_symbol": { "marker": "Ellipse", "size": 6, "edgecolor": "#808080", "facecolor": "#ffff00", "alpha": 1.0 }, "fill": { "style": "SolidPattern", "color": "#000000", "alpha": 1.0, "angle": 0.0, "sx": 1.0, "sy": 1.0 }, "sel_fill": { "style": "SolidPattern", "color": "#000000", "alpha": 1.0, "angle": 0.0, "sx": 1.0, "sy": 1.0 }, "readonly": false, "private": false }, "points": [ "array", [ [ 500.0, 500.0 ] ], "float64" ], "closed": false, "z": 0.0, "labelparam": { "label": "", "contents": "", "symbol": { "marker": "NoSymbol", "size": 0, "edgecolor": "white", "facecolor": "white", "alpha": 1.0 }, "border": { "style": "SolidLine", "color": "#cbcbcb", "width": 0 }, "font": { "family": "default", "size": 8, "bold": false, "italic": false }, "color": "white", "bgcolor": "black", "bgalpha": 0.25, "anchor": "TL", "xc": 5, "yc": 5, "abspos": false, "xg": 500.0, "yg": 500.0, "move_anchor": true, "absg": "TL" }, "text": "( 500.0 ; 500.0 )" }, "AnnotatedSegment_001": { "annotationparam": { "show_label": true, "show_computations": true, "title": "", "subtitle": "", "format": "%.1f", "uncertainty": 0.0, "transform_matrix": [ "array", [ [ 1.0, 0.0, 0.0 ], [ 0.0, 1.0, 0.0 ], [ 0.0, 0.0, 1.0 ] ], "float64" ], "readonly": false, "private": false }, "shapeparam": { "label": "", "line": { "style": "SolidLine", "color": "#ffff00", "width": 1.0 }, "sel_line": { "style": "SolidLine", "color": "#00ff00", "width": 1.0 }, "symbol": { "marker": "Rect", "size": 3, "edgecolor": "#ffff00", "facecolor": "#ffff00", "alpha": 1.0 }, "sel_symbol": { "marker": "Rect", "size": 9, "edgecolor": "#00aa00", "facecolor": "#00ff00", "alpha": 0.7 }, "fill": { "style": "SolidPattern", "color": "#ffffff", "alpha": 0.10000762951094835, "angle": 0.0, "sx": 1.0, "sy": 1.0 }, "sel_fill": { "style": "SolidPattern", "color": "#ffffff", "alpha": 0.10000762951094835, "angle": 0.0, "sx": 1.0, "sy": 1.0 }, "readonly": false, "private": false }, "points": [ "array", [ [ 50.0, 250.0 ], [ 400.0, 400.0 ], [ 225.0, 325.0 ] ], "float64" ], "closed": false, "z": 0.0, "labelparam": { "label": "", "contents": "", "symbol": { "marker": "NoSymbol", "size": 0, "edgecolor": "white", "facecolor": "white", "alpha": 1.0 }, "border": { "style": "SolidLine", "color": "#cbcbcb", "width": 0 }, "font": { "family": "default", "size": 8, "bold": false, "italic": false }, "color": "white", "bgcolor": "black", "bgalpha": 0.25, "anchor": "C", "xc": 5, "yc": 5, "abspos": false, "xg": 225.0, "yg": 325.0, "move_anchor": true, "absg": "TL" }, "text": "Distance : 380.8 " }, "AnnotatedRectangle_001": { "annotationparam": { "show_label": true, "show_computations": true, "title": "", "subtitle": "", "format": "%.1f", "uncertainty": 0.0, "transform_matrix": [ "array", [ [ 1.0, 0.0, 0.0 ], [ 0.0, 1.0, 0.0 ], [ 0.0, 0.0, 1.0 ] ], "float64" ], "readonly": false, "private": false }, "shapeparam": { "label": "", "line": { "style": "SolidLine", "color": "#ffff00", "width": 1.0 }, "sel_line": { "style": "SolidLine", "color": "#00ff00", "width": 1.0 }, "symbol": { "marker": "Rect", "size": 3, "edgecolor": "#ffff00", "facecolor": "#ffff00", "alpha": 1.0 }, "sel_symbol": { "marker": "Rect", "size": 9, "edgecolor": "#00aa00", "facecolor": "#00ff00", "alpha": 0.7 }, "fill": { "style": "SolidPattern", "color": "#d574ff", "alpha": 0.5000076295109483, "angle": 0.0, "sx": 1.0, "sy": 1.0 }, "sel_fill": { "style": "SolidPattern", "color": "#ffffff", "alpha": 0.10000762951094835, "angle": 0.0, "sx": 1.0, "sy": 1.0 }, "readonly": false, "private": false }, "points": [ "array", [ [ 246.05373134328346, 126.05269461077847 ], [ 646.0537313432841, 126.05269461077847 ], [ 646.0537313432841, 626.0526946107782 ], [ 246.05373134328346, 626.0526946107782 ] ], "float64" ], "closed": true, "z": 0.0, "labelparam": { "label": "", "contents": "", "symbol": { "marker": "NoSymbol", "size": 0, "edgecolor": "white", "facecolor": "white", "alpha": 1.0 }, "border": { "style": "SolidLine", "color": "#cbcbcb", "width": 0.0 }, "font": { "family": "default", "size": 8, "bold": false, "italic": false }, "color": "white", "bgcolor": "black", "bgalpha": 0.25, "anchor": "TL", "xc": 5, "yc": 5, "abspos": false, "xg": 246.05373134328346, "yg": 126.05269461077847, "move_anchor": true, "absg": "TL" }, "text": "Centre : ( 446.1 ; 376.1 )
Taille : 400.0 x 500.0 " }, "AnnotatedCircle_001": { "annotationparam": { "show_label": true, "show_computations": true, "title": "", "subtitle": "", "format": "%.1f", "uncertainty": 0.0, "transform_matrix": [ "array", [ [ 1.0, 0.0, 0.0 ], [ 0.0, 1.0, 0.0 ], [ 0.0, 0.0, 1.0 ] ], "float64" ], "readonly": false, "private": false }, "shapeparam": { "label": "", "line": { "style": "SolidLine", "color": "#ffff00", "width": 1.0 }, "sel_line": { "style": "SolidLine", "color": "#00ff00", "width": 1.0 }, "symbol": { "marker": "Rect", "size": 3, "edgecolor": "#ffff00", "facecolor": "#ffff00", "alpha": 1.0 }, "sel_symbol": { "marker": "Rect", "size": 9, "edgecolor": "#00aa00", "facecolor": "#00ff00", "alpha": 0.7 }, "fill": { "style": "SolidPattern", "color": "#ffffff", "alpha": 0.10000762951094835, "angle": 0.0, "sx": 1.0, "sy": 1.0 }, "sel_fill": { "style": "SolidPattern", "color": "#ffffff", "alpha": 0.10000762951094835, "angle": 0.0, "sx": 1.0, "sy": 1.0 }, "readonly": false, "private": false }, "points": [ "array", [ [ 150.0, 150.0 ], [ 350.0, 350.0 ], [ 150.0, 350.0 ], [ 350.0, 150.0 ] ], "float64" ], "closed": true, "z": 0.0, "labelparam": { "label": "", "contents": "", "symbol": { "marker": "NoSymbol", "size": 0, "edgecolor": "white", "facecolor": "white", "alpha": 1.0 }, "border": { "style": "SolidLine", "color": "#cbcbcb", "width": 0 }, "font": { "family": "default", "size": 8, "bold": false, "italic": false }, "color": "white", "bgcolor": "black", "bgalpha": 0.25, "anchor": "C", "xc": 5, "yc": 5, "abspos": false, "xg": 250.0, "yg": 250.0, "move_anchor": true, "absg": "TL" }, "text": "Centre : ( 250.0 ; 250.0 )
Diam\u00e8tre : 282.8 " }, "AnnotatedCircle_002": { "annotationparam": { "show_label": true, "show_computations": true, "title": "", "subtitle": "", "format": "%.1f", "uncertainty": 0.0, "transform_matrix": [ "array", [ [ 1.0, 0.0, 0.0 ], [ 0.0, 1.0, 0.0 ], [ 0.0, 0.0, 1.0 ] ], "float64" ], "readonly": false, "private": false }, "shapeparam": { "label": "", "line": { "style": "SolidLine", "color": "#ffff00", "width": 1.0 }, "sel_line": { "style": "SolidLine", "color": "#00ff00", "width": 1.0 }, "symbol": { "marker": "Rect", "size": 3, "edgecolor": "#ffff00", "facecolor": "#ffff00", "alpha": 1.0 }, "sel_symbol": { "marker": "Rect", "size": 9, "edgecolor": "#00aa00", "facecolor": "#00ff00", "alpha": 0.7 }, "fill": { "style": "SolidPattern", "color": "#ffffff", "alpha": 0.10000762951094835, "angle": 0.0, "sx": 1.0, "sy": 1.0 }, "sel_fill": { "style": "SolidPattern", "color": "#ffffff", "alpha": 0.10000762951094835, "angle": 0.0, "sx": 1.0, "sy": 1.0 }, "readonly": false, "private": false }, "points": [ "array", [ [ 100.0, 100.0 ], [ 400.0, 400.0 ], [ 100.0, 400.0 ], [ 400.0, 100.0 ] ], "float64" ], "closed": true, "z": 0.0, "labelparam": { "label": "", "contents": "", "symbol": { "marker": "NoSymbol", "size": 0, "edgecolor": "white", "facecolor": "white", "alpha": 1.0 }, "border": { "style": "SolidLine", "color": "#cbcbcb", "width": 0 }, "font": { "family": "default", "size": 8, "bold": false, "italic": false }, "color": "white", "bgcolor": "black", "bgalpha": 0.25, "anchor": "C", "xc": 5, "yc": 5, "abspos": false, "xg": 250.0, "yg": 250.0, "move_anchor": true, "absg": "TL" }, "text": "Centre : ( 250.0 ; 250.0 )
Diam\u00e8tre : 424.3 " }, "plot_items": [ "AnnotatedPoint_001", "AnnotatedPoint_002", "AnnotatedSegment_001", "AnnotatedRectangle_001", "AnnotatedCircle_001", "AnnotatedCircle_002" ] }Sigima-1.1.1/sigima/data/tests/curve_fitting/000077500000000000000000000000001514013333200211125ustar00rootroot00000000000000Sigima-1.1.1/sigima/data/tests/curve_fitting/exponential_fit.txt000066400000000000000000000317721514013333200250550ustar00rootroot000000000000005.004913e+00 1.471511e+02 5.014707e+00 1.472382e+02 5.024502e+00 1.452679e+02 5.034296e+00 1.428664e+02 5.044090e+00 1.398786e+02 5.053885e+00 1.407199e+02 5.063679e+00 1.385268e+02 5.073473e+00 1.353663e+02 5.083268e+00 1.390431e+02 5.093062e+00 1.339135e+02 5.102856e+00 1.363741e+02 5.112651e+00 1.324572e+02 5.122445e+00 1.309783e+02 5.132239e+00 1.299121e+02 5.142034e+00 1.259911e+02 5.151828e+00 1.281773e+02 5.161622e+00 1.264196e+02 5.171417e+00 1.262349e+02 5.181211e+00 1.265537e+02 5.191005e+00 1.184801e+02 5.200800e+00 1.182121e+02 5.210594e+00 1.171592e+02 5.220389e+00 1.192923e+02 5.230183e+00 1.163910e+02 5.239977e+00 1.136677e+02 5.249772e+00 1.157810e+02 5.259566e+00 1.133827e+02 5.269360e+00 1.145216e+02 5.279155e+00 1.154051e+02 5.288949e+00 1.100147e+02 5.298743e+00 1.083984e+02 5.308538e+00 1.072865e+02 5.318332e+00 1.053069e+02 5.328126e+00 1.043424e+02 5.337921e+00 1.037413e+02 5.347715e+00 1.011943e+02 5.357509e+00 1.071324e+02 5.367304e+00 1.046604e+02 5.377098e+00 1.020371e+02 5.386892e+00 9.975930e+01 5.396687e+00 9.818553e+01 5.406481e+00 1.004033e+02 5.416276e+00 1.013106e+02 5.426070e+00 9.389241e+01 5.435864e+00 9.721194e+01 5.445659e+00 9.615239e+01 5.455453e+00 9.286808e+01 5.465247e+00 9.360621e+01 5.475042e+00 9.193289e+01 5.484836e+00 8.558677e+01 5.494630e+00 9.103474e+01 5.504425e+00 8.707588e+01 5.514219e+00 8.877641e+01 5.524013e+00 8.871684e+01 5.533808e+00 8.780475e+01 5.543602e+00 8.812686e+01 5.553396e+00 8.338870e+01 5.563191e+00 8.085723e+01 5.572985e+00 8.429923e+01 5.582779e+00 8.353697e+01 5.592574e+00 8.094943e+01 5.602368e+00 8.013365e+01 5.612163e+00 7.836311e+01 5.621957e+00 7.613469e+01 5.631751e+00 7.502511e+01 5.641546e+00 7.836203e+01 5.651340e+00 7.946346e+01 5.661134e+00 7.833956e+01 5.670929e+00 7.590017e+01 5.680723e+00 7.486437e+01 5.690517e+00 7.673988e+01 5.700312e+00 7.336346e+01 5.710106e+00 7.186971e+01 5.719900e+00 7.137927e+01 5.729695e+00 7.465528e+01 5.739489e+00 6.940209e+01 5.749283e+00 6.880099e+01 5.759078e+00 6.978579e+01 5.768872e+00 6.922219e+01 5.778666e+00 6.968159e+01 5.788461e+00 6.759489e+01 5.798255e+00 6.563921e+01 5.808050e+00 6.425235e+01 5.817844e+00 6.684058e+01 5.827638e+00 6.527561e+01 5.837433e+00 5.925668e+01 5.847227e+00 6.220826e+01 5.857021e+00 5.910660e+01 5.866816e+00 6.242577e+01 5.876610e+00 6.215621e+01 5.886404e+00 6.127629e+01 5.896199e+00 6.053490e+01 5.905993e+00 5.734789e+01 5.915787e+00 5.897752e+01 5.925582e+00 5.818245e+01 5.935376e+00 5.714236e+01 5.945170e+00 5.704593e+01 5.954965e+00 5.392913e+01 5.964759e+00 5.677171e+01 5.974553e+00 5.680898e+01 5.984348e+00 5.471450e+01 5.994142e+00 5.438178e+01 6.003937e+00 5.493175e+01 6.013731e+00 5.631298e+01 6.023525e+00 5.315258e+01 6.033320e+00 4.751642e+01 6.043114e+00 5.335998e+01 6.052908e+00 5.345484e+01 6.062703e+00 5.080124e+01 6.072497e+00 4.964150e+01 6.082291e+00 4.862310e+01 6.092086e+00 4.597435e+01 6.101880e+00 4.508320e+01 6.111674e+00 4.864574e+01 6.121469e+00 4.634605e+01 6.131263e+00 4.958740e+01 6.141057e+00 4.842580e+01 6.150852e+00 4.132606e+01 6.160646e+00 4.450107e+01 6.170440e+00 4.672758e+01 6.180235e+00 4.284848e+01 6.190029e+00 4.399324e+01 6.199824e+00 4.451498e+01 6.209618e+00 4.831981e+01 6.219412e+00 4.164652e+01 6.229207e+00 4.477469e+01 6.239001e+00 4.076592e+01 6.248795e+00 4.386593e+01 6.258590e+00 3.838075e+01 6.268384e+00 4.210597e+01 6.278178e+00 4.196283e+01 6.287973e+00 4.260147e+01 6.297767e+00 4.040865e+01 6.307561e+00 4.078559e+01 6.317356e+00 3.909961e+01 6.327150e+00 3.957569e+01 6.336944e+00 3.761598e+01 6.346739e+00 4.039542e+01 6.356533e+00 3.860673e+01 6.366327e+00 3.744978e+01 6.376122e+00 3.730138e+01 6.385916e+00 3.462308e+01 6.395711e+00 3.888579e+01 6.405505e+00 3.750241e+01 6.415299e+00 3.584765e+01 6.425094e+00 3.378648e+01 6.434888e+00 3.794292e+01 6.444682e+00 3.519233e+01 6.454477e+00 3.217361e+01 6.464271e+00 3.400605e+01 6.474065e+00 3.464892e+01 6.483860e+00 3.537495e+01 6.493654e+00 3.398454e+01 6.503448e+00 2.986808e+01 6.513243e+00 3.404947e+01 6.523037e+00 3.393188e+01 6.532831e+00 3.261415e+01 6.542626e+00 3.143750e+01 6.552420e+00 2.727654e+01 6.562214e+00 3.013965e+01 6.572009e+00 3.018096e+01 6.581803e+00 3.214625e+01 6.591598e+00 2.924955e+01 6.601392e+00 3.435923e+01 6.611186e+00 2.550641e+01 6.620981e+00 3.056007e+01 6.630775e+00 2.937366e+01 6.640569e+00 2.793182e+01 6.650364e+00 2.736076e+01 6.660158e+00 2.781026e+01 6.669952e+00 2.636431e+01 6.679747e+00 2.663268e+01 6.689541e+00 2.637117e+01 6.699335e+00 2.730475e+01 6.709130e+00 2.769355e+01 6.718924e+00 2.170330e+01 6.728718e+00 2.873371e+01 6.738513e+00 2.247953e+01 6.748307e+00 2.421929e+01 6.758101e+00 2.598976e+01 6.767896e+00 2.367353e+01 6.777690e+00 2.331048e+01 6.787485e+00 2.319857e+01 6.797279e+00 2.348209e+01 6.807073e+00 2.679264e+01 6.816868e+00 2.173251e+01 6.826662e+00 2.078808e+01 6.836456e+00 2.282675e+01 6.846251e+00 2.331214e+01 6.856045e+00 2.657325e+01 6.865839e+00 2.128182e+01 6.875634e+00 2.134561e+01 6.885428e+00 2.254173e+01 6.895222e+00 2.037178e+01 6.905017e+00 2.252907e+01 6.914811e+00 1.904251e+01 6.924605e+00 2.075074e+01 6.934400e+00 2.092613e+01 6.944194e+00 1.973930e+01 6.953988e+00 2.152604e+01 6.963783e+00 1.818827e+01 6.973577e+00 2.111488e+01 6.983372e+00 2.157233e+01 6.993166e+00 2.151511e+01 7.002960e+00 1.857721e+01 7.012755e+00 1.922324e+01 7.022549e+00 2.003253e+01 7.032343e+00 2.026874e+01 7.042138e+00 2.077310e+01 7.051932e+00 1.653551e+01 7.061726e+00 1.726442e+01 7.071521e+00 1.953220e+01 7.081315e+00 1.560098e+01 7.091109e+00 1.514355e+01 7.100904e+00 1.862086e+01 7.110698e+00 1.737582e+01 7.120492e+00 1.892086e+01 7.130287e+00 1.822223e+01 7.140081e+00 1.864266e+01 7.149875e+00 1.325473e+01 7.159670e+00 1.428375e+01 7.169464e+00 1.436022e+01 7.179259e+00 1.806513e+01 7.189053e+00 1.926370e+01 7.198847e+00 1.646983e+01 7.208642e+00 1.151439e+01 7.218436e+00 1.636222e+01 7.228230e+00 1.880353e+01 7.238025e+00 1.448379e+01 7.247819e+00 1.367515e+01 7.257613e+00 1.435617e+01 7.267408e+00 1.688494e+01 7.277202e+00 1.245205e+01 7.286996e+00 1.489008e+01 7.296791e+00 1.866421e+01 7.306585e+00 1.390436e+01 7.316379e+00 1.781381e+01 7.326174e+00 1.139000e+01 7.335968e+00 1.445306e+01 7.345762e+00 1.219185e+01 7.355557e+00 1.321315e+01 7.365351e+00 1.524230e+01 7.375146e+00 1.295212e+01 7.384940e+00 1.357661e+01 7.394734e+00 1.523100e+01 7.404529e+00 1.077899e+01 7.414323e+00 1.569069e+01 7.424117e+00 1.330244e+01 7.433912e+00 1.401417e+01 7.443706e+00 1.174989e+01 7.453500e+00 9.380239e+00 7.463295e+00 1.356123e+01 7.473089e+00 1.258091e+01 7.482883e+00 1.125268e+01 7.492678e+00 1.379899e+01 7.502472e+00 9.073772e+00 7.512266e+00 1.485087e+01 7.522061e+00 1.172269e+01 7.531855e+00 1.499828e+01 7.541649e+00 1.512252e+01 7.551444e+00 8.698802e+00 7.561238e+00 9.967997e+00 7.571033e+00 1.185147e+01 7.580827e+00 9.452936e+00 7.590621e+00 1.102782e+01 7.600416e+00 9.007380e+00 7.610210e+00 1.252655e+01 7.620004e+00 1.043170e+01 7.629799e+00 1.374767e+01 7.639593e+00 7.419494e+00 7.649387e+00 1.171294e+01 7.659182e+00 1.027006e+01 7.668976e+00 9.677913e+00 7.678770e+00 1.261533e+01 7.688565e+00 8.763959e+00 7.698359e+00 1.361440e+01 7.708153e+00 9.246049e+00 7.717948e+00 1.033087e+01 7.727742e+00 3.931677e+00 7.737536e+00 9.989109e+00 7.747331e+00 1.011085e+01 7.757125e+00 1.210029e+01 7.766920e+00 1.074853e+01 7.776714e+00 1.501119e+01 7.786508e+00 1.067911e+01 7.796303e+00 9.558195e+00 7.806097e+00 7.707008e+00 7.815891e+00 6.734959e+00 7.825686e+00 1.433166e+01 7.835480e+00 9.272867e+00 7.845274e+00 1.032756e+01 7.855069e+00 8.966091e+00 7.864863e+00 6.584029e+00 7.874657e+00 8.269469e+00 7.884452e+00 1.274394e+01 7.894246e+00 1.055551e+01 7.904040e+00 7.886202e+00 7.913835e+00 8.928416e+00 7.923629e+00 7.235757e+00 7.933423e+00 7.418810e+00 7.943218e+00 5.796315e+00 7.953012e+00 1.068721e+01 7.962807e+00 6.959070e+00 7.972601e+00 7.112491e+00 7.982395e+00 8.782625e+00 7.992190e+00 4.347006e+00 8.001984e+00 1.058214e+01 8.011778e+00 6.021061e+00 8.021573e+00 6.818268e+00 8.031367e+00 8.935762e+00 8.041161e+00 7.486304e+00 8.050956e+00 4.648944e+00 8.060750e+00 5.723941e+00 8.070544e+00 7.018311e+00 8.080339e+00 4.751480e+00 8.090133e+00 7.449779e+00 8.099927e+00 6.557584e+00 8.109722e+00 6.119997e+00 8.119516e+00 8.087697e+00 8.129310e+00 6.537803e+00 8.139105e+00 9.046252e+00 8.148899e+00 7.247932e+00 8.158694e+00 6.194464e+00 8.168488e+00 8.195018e+00 8.178282e+00 4.920591e+00 8.188077e+00 4.157068e+00 8.197871e+00 5.115394e+00 8.207665e+00 4.852831e+00 8.217460e+00 3.321018e+00 8.227254e+00 4.817385e+00 8.237048e+00 4.264514e+00 8.246843e+00 3.594663e+00 8.256637e+00 7.854682e+00 8.266431e+00 6.607683e+00 8.276226e+00 6.628947e+00 8.286020e+00 4.467746e+00 8.295814e+00 7.995283e+00 8.305609e+00 7.907542e+00 8.315403e+00 5.128391e+00 8.325197e+00 5.203532e+00 8.334992e+00 4.097813e+00 8.344786e+00 5.549268e+00 8.354581e+00 5.814353e+00 8.364375e+00 4.517825e+00 8.374169e+00 4.439681e+00 8.383964e+00 7.840601e+00 8.393758e+00 7.352790e+00 8.403552e+00 7.013904e+00 8.413347e+00 3.683952e+00 8.423141e+00 4.582092e+00 8.432935e+00 5.271809e+00 8.442730e+00 3.037341e+00 8.452524e+00 2.562339e+00 8.462318e+00 2.644062e+00 8.472113e+00 5.064013e+00 8.481907e+00 4.502358e+00 8.491701e+00 5.905939e+00 8.501496e+00 7.900794e+00 8.511290e+00 5.370918e+00 8.521084e+00 3.699485e+00 8.530879e+00 4.632803e+00 8.540673e+00 5.229484e+00 8.550468e+00 1.593377e+00 8.560262e+00 7.549737e+00 8.570056e+00 5.450158e-01 8.579851e+00 6.332317e+00 8.589645e+00 4.786524e+00 8.599439e+00 2.514985e+00 8.609234e+00 8.191060e+00 8.619028e+00 7.050753e+00 8.628822e+00 4.006949e+00 8.638617e+00 3.477611e+00 8.648411e+00 5.786483e+00 8.658205e+00 3.279820e+00 8.668000e+00 3.022235e+00 8.677794e+00 2.390124e+00 8.687588e+00 5.622222e+00 8.697383e+00 5.337656e+00 8.707177e+00 2.420423e+00 8.716971e+00 5.985555e+00 8.726766e+00 4.918132e+00 8.736560e+00 4.181085e+00 8.746355e+00 4.100895e+00 8.756149e+00 2.796584e+00 8.765943e+00 2.227553e+00 8.775738e+00 1.816365e+00 8.785532e+00 2.195019e+00 8.795326e+00 6.077339e+00 8.805121e+00 2.340336e+00 8.814915e+00 3.383655e+00 8.824709e+00 4.280026e+00 8.834504e+00 5.667593e+00 8.844298e+00 4.510272e+00 8.854092e+00 3.673941e+00 8.863887e+00 5.195828e+00 8.873681e+00 2.534136e+00 8.883475e+00 3.646265e+00 8.893270e+00 1.710622e+00 8.903064e+00 4.156561e+00 8.912858e+00 3.110953e+00 8.922653e+00 4.352033e+00 8.932447e+00 3.887345e+00 8.942242e+00 2.951942e+00 8.952036e+00 2.010261e+00 8.961830e+00 3.503508e+00 8.971625e+00 4.304116e+00 8.981419e+00 1.592925e+00 8.991213e+00 -2.948303e+00 9.001008e+00 2.682326e-01 9.010802e+00 5.411964e+00 9.020596e+00 3.727042e+00 9.030391e+00 2.918614e+00 9.040185e+00 -1.301831e-01 9.049979e+00 3.719666e+00 9.059774e+00 2.834387e+00 9.069568e+00 7.048721e+00 9.079362e+00 4.149693e+00 9.089157e+00 -5.718387e-01 9.098951e+00 4.501959e+00 9.108745e+00 -1.097690e+00 9.118540e+00 3.823671e+00 9.128334e+00 2.364617e+00 9.138129e+00 3.464702e+00 9.147923e+00 3.412711e+00 9.157717e+00 5.945935e+00 9.167512e+00 1.965897e-01 9.177306e+00 5.528856e+00 9.187100e+00 2.112424e+00 9.196895e+00 1.175153e+00 9.206689e+00 2.729613e+00 9.216483e+00 4.515973e-01 9.226278e+00 4.069242e+00 9.236072e+00 -1.249268e+00 9.245866e+00 1.512860e+00 9.255661e+00 3.094765e+00 9.265455e+00 2.120606e+00 9.275249e+00 4.317762e+00 9.285044e+00 1.907302e+00 9.294838e+00 1.812566e+00 9.304632e+00 5.740751e-01 9.314427e+00 3.074655e+00 9.324221e+00 1.330752e+00 9.334016e+00 4.181450e+00 9.343810e+00 -1.948346e+00 9.353604e+00 3.636548e+00 9.363399e+00 2.876049e-01 9.373193e+00 4.322147e+00 9.382987e+00 1.767094e+00 9.392782e+00 3.372141e+00 9.402576e+00 2.246911e+00 9.412370e+00 1.085065e+00 9.422165e+00 1.117924e+00 9.431959e+00 5.286048e+00 9.441753e+00 1.454095e+00 9.451548e+00 2.718556e+00 9.461342e+00 3.929067e+00 9.471136e+00 1.687764e+00 9.480931e+00 3.141091e+00 9.490725e+00 5.472377e+00 9.500519e+00 -6.253090e-03 9.510314e+00 7.682379e-02 9.520108e+00 -1.390425e+00 9.529903e+00 1.165148e+00 9.539697e+00 7.117501e-01 9.549491e+00 -1.639254e+00 9.559286e+00 2.059412e+00 9.569080e+00 5.813534e-01 9.578874e+00 1.797586e+00 9.588669e+00 -4.704101e-01 9.598463e+00 9.223612e-02 9.608257e+00 -3.268398e+00 9.618052e+00 3.446785e+00 9.627846e+00 -1.219799e-01 9.637640e+00 3.488014e-01 9.647435e+00 9.474283e-01 9.657229e+00 -1.540287e-01 9.667023e+00 4.592260e+00 9.676818e+00 -1.725482e-01 9.686612e+00 3.081548e+00 9.696406e+00 5.146320e-01 9.706201e+00 3.698340e+00 9.715995e+00 2.804555e+00 9.725790e+00 4.313891e+00 9.735584e+00 1.566664e+00 9.745378e+00 4.478554e+00 9.755173e+00 1.679092e+00 9.764967e+00 -1.559851e+00 9.774761e+00 2.140149e+00 9.784556e+00 3.457835e+00 9.794350e+00 1.422226e+00 9.804144e+00 -1.192947e+00 9.813939e+00 6.381921e-01 9.823733e+00 1.051526e+00 9.833527e+00 8.864191e-01 9.843322e+00 4.811925e-01 9.853116e+00 3.061412e+00 9.862910e+00 3.645097e-01 9.872705e+00 -1.390796e+00 9.882499e+00 2.500331e+00 9.892293e+00 1.367250e+00 9.902088e+00 3.657223e+00 9.911882e+00 1.907885e+00 9.921677e+00 2.258260e+00 9.931471e+00 1.537239e+00 9.941265e+00 -2.747556e+00 9.951060e+00 -2.791090e+00 9.960854e+00 2.200804e+00 9.970648e+00 -4.538760e-01 9.980443e+00 3.612982e-01 9.990237e+00 1.799175e+00 1.000003e+01 1.700779e+00 Sigima-1.1.1/sigima/data/tests/curve_fitting/gaussian_fit.txt000066400000000000000000000032141514013333200243270ustar00rootroot000000000000000.000000 0.124822 1.00000 0.0276261 2.00000 0.226983 3.00000 0.159006 4.00000 0.279283 5.00000 0.115291 6.00000 0.196551 7.00000 0.0206322 8.00000 0.217685 9.00000 0.202687 10.0000 0.117037 11.0000 0.192478 12.0000 0.269803 13.0000 0.162214 14.0000 0.204658 15.0000 0.0844573 16.0000 0.0972682 17.0000 0.254566 18.0000 0.261863 19.0000 0.321895 20.0000 0.0884597 21.0000 0.171338 22.0000 0.388343 23.0000 0.239201 24.0000 0.359172 25.0000 0.371401 26.0000 0.410920 27.0000 0.571987 28.0000 0.787380 29.0000 0.910793 30.0000 0.822383 31.0000 1.28416 32.0000 1.39118 33.0000 1.64442 34.0000 1.68639 35.0000 2.06316 36.0000 2.39519 37.0000 2.86167 38.0000 3.20092 39.0000 3.54784 40.0000 3.73489 41.0000 4.21222 42.0000 4.35920 43.0000 4.80583 44.0000 5.09146 45.0000 5.59097 46.0000 5.62182 47.0000 5.92485 48.0000 5.93114 49.0000 6.19090 50.0000 6.13092 51.0000 6.26484 52.0000 6.10206 53.0000 5.80594 54.0000 5.56592 55.0000 5.44634 56.0000 5.15981 57.0000 4.71125 58.0000 4.49623 59.0000 4.15994 60.0000 3.76281 61.0000 3.36834 62.0000 3.19361 63.0000 2.80841 64.0000 2.41079 65.0000 2.10911 66.0000 1.84492 67.0000 1.62051 68.0000 1.46154 69.0000 1.04035 70.0000 1.07858 71.0000 0.909848 72.0000 0.683742 73.0000 0.597529 74.0000 0.346725 75.0000 0.344417 76.0000 0.421908 77.0000 0.310711 78.0000 0.386268 79.0000 0.314013 80.0000 0.130479 81.0000 0.0633716 82.0000 0.288468 83.0000 0.192282 84.0000 0.259254 85.0000 0.0291634 86.0000 0.0101027 87.0000 0.212925 88.0000 0.00915113 89.0000 0.0749610 90.0000 0.179347 91.0000 0.188797 92.0000 0.126132 93.0000 0.140955 94.0000 0.124994 95.0000 0.204644 96.0000 0.160487 97.0000 0.00815869 98.0000 0.0953214 99.0000 0.0376463 Sigima-1.1.1/sigima/data/tests/curve_fitting/piecewiseexponential_fit.txt000066400000000000000000000637701514013333200267560ustar00rootroot000000000000000.000000e+00 -1.669506e+00 9.794350e-03 2.875880e+00 1.958870e-02 2.725645e+00 2.938305e-02 1.225723e+00 3.917740e-02 -1.981260e+00 4.897175e-02 3.749348e+00 5.876610e-02 5.892621e-01 6.856045e-02 -2.820441e+00 7.835480e-02 2.773519e+00 8.814915e-02 1.819615e+00 9.794350e-02 6.420565e-01 1.077378e-01 1.536713e-01 1.175322e-01 -2.915538e+00 1.273265e-01 2.992417e+00 1.371209e-01 1.383098e+00 1.469152e-01 4.231995e+00 1.567096e-01 2.741067e-01 1.665039e-01 1.736993e+00 1.762983e-01 -8.895389e-02 1.860926e-01 1.434737e+00 1.958870e-01 2.788523e+00 2.056813e-01 -4.320798e-01 2.154757e-01 3.623984e+00 2.252700e-01 2.717241e+00 2.350644e-01 9.466864e-01 2.448587e-01 2.921507e+00 2.546531e-01 2.689894e+00 2.644474e-01 1.656797e+00 2.742418e-01 2.793835e+00 2.840361e-01 -1.113437e+00 2.938305e-01 3.901948e+00 3.036248e-01 -1.215817e+00 3.134192e-01 -2.828728e-01 3.232135e-01 2.873700e+00 3.330079e-01 1.097200e+00 3.428022e-01 2.038021e-01 3.525966e-01 -2.294361e+00 3.623909e-01 1.575447e+00 3.721853e-01 2.630244e+00 3.819796e-01 2.697450e-01 3.917740e-01 5.540818e-01 4.015683e-01 -8.782534e-02 4.113627e-01 3.944937e+00 4.211570e-01 2.574444e+00 4.309514e-01 -1.022564e+00 4.407457e-01 4.884089e+00 4.505401e-01 -7.089320e-01 4.603344e-01 1.607634e+00 4.701288e-01 4.167924e-01 4.799231e-01 1.685165e+00 4.897175e-01 4.582053e-01 4.995118e-01 1.469206e+00 5.093062e-01 -1.308103e+00 5.191005e-01 3.089602e+00 5.288949e-01 1.825378e+00 5.386892e-01 1.596754e+00 5.484836e-01 -9.678042e-01 5.582779e-01 2.386652e-01 5.680723e-01 -1.509464e-01 5.778666e-01 6.371780e-01 5.876610e-01 -4.843071e-01 5.974553e-01 4.132796e+00 6.072497e-01 -1.146315e+00 6.170440e-01 2.601417e+00 6.268384e-01 3.561175e+00 6.366327e-01 4.385919e+00 6.464271e-01 2.540683e+00 6.562214e-01 2.802486e+00 6.660158e-01 3.649197e+00 6.758101e-01 6.313738e-01 6.856045e-01 2.304773e+00 6.953988e-01 1.454003e-01 7.051932e-01 4.715750e-01 7.149875e-01 1.230410e-02 7.247819e-01 4.098963e+00 7.345762e-01 5.942564e+00 7.443706e-01 1.319743e+00 7.541649e-01 2.817722e+00 7.639593e-01 1.295057e+00 7.737536e-01 5.266045e+00 7.835480e-01 5.745618e+00 7.933423e-01 2.813892e+00 8.031367e-01 1.974015e-01 8.129310e-01 -1.403390e+00 8.227254e-01 2.346669e+00 8.325197e-01 3.252584e+00 8.423141e-01 5.102809e+00 8.521084e-01 -8.612098e-01 8.619028e-01 4.500943e+00 8.716971e-01 4.988462e+00 8.814915e-01 1.360711e+00 8.912858e-01 2.189731e+00 9.010802e-01 1.027735e+00 9.108745e-01 2.047813e+00 9.206689e-01 3.296520e+00 9.304632e-01 1.376238e+00 9.402576e-01 -1.150031e+00 9.500519e-01 3.068682e+00 9.598463e-01 -4.513878e-01 9.696406e-01 4.717321e+00 9.794350e-01 2.594796e+00 9.892293e-01 4.764099e-01 9.990237e-01 1.438729e+00 1.008818e+00 4.352637e+00 1.018612e+00 2.225360e+00 1.028407e+00 3.925734e+00 1.038201e+00 5.131257e+00 1.047995e+00 1.522997e+00 1.057790e+00 1.277184e+00 1.067584e+00 4.962197e+00 1.077378e+00 2.734908e+00 1.087173e+00 9.447182e-01 1.096967e+00 1.321424e+00 1.106762e+00 5.385191e+00 1.116556e+00 4.885486e+00 1.126350e+00 3.875567e+00 1.136145e+00 2.557570e+00 1.145939e+00 3.580325e+00 1.155733e+00 4.803984e+00 1.165528e+00 1.547834e+00 1.175322e+00 3.664732e+00 1.185116e+00 3.308235e+00 1.194911e+00 2.114830e+00 1.204705e+00 2.080528e+00 1.214499e+00 3.403474e+00 1.224294e+00 1.471753e+00 1.234088e+00 3.418335e+00 1.243882e+00 1.049799e+00 1.253677e+00 4.559649e+00 1.263471e+00 2.457347e+00 1.273265e+00 1.849164e+00 1.283060e+00 4.947529e+00 1.292854e+00 5.177110e+00 1.302649e+00 3.935043e+00 1.312443e+00 2.235170e+00 1.322237e+00 3.669143e-01 1.332032e+00 3.465656e+00 1.341826e+00 5.176601e+00 1.351620e+00 -1.681671e-02 1.361415e+00 4.539208e+00 1.371209e+00 5.209782e+00 1.381003e+00 6.418733e+00 1.390798e+00 6.979259e+00 1.400592e+00 7.404114e-01 1.410386e+00 2.287799e+00 1.420181e+00 1.941747e+00 1.429975e+00 4.547253e+00 1.439769e+00 2.713503e+00 1.449564e+00 4.997074e+00 1.459358e+00 6.907848e+00 1.469152e+00 4.314182e+00 1.478947e+00 4.729349e+00 1.488741e+00 -2.078294e-01 1.498536e+00 5.601999e+00 1.508330e+00 5.299310e+00 1.518124e+00 2.792637e+00 1.527919e+00 3.090573e+00 1.537713e+00 8.144240e+00 1.547507e+00 3.871787e+00 1.557302e+00 2.539185e+00 1.567096e+00 8.011093e+00 1.576890e+00 6.424655e+00 1.586685e+00 5.653497e+00 1.596479e+00 4.353959e+00 1.606273e+00 7.574794e+00 1.616068e+00 4.702694e+00 1.625862e+00 5.519993e+00 1.635656e+00 6.405442e+00 1.645451e+00 6.736960e-01 1.655245e+00 5.459474e+00 1.665039e+00 4.421271e+00 1.674834e+00 5.499699e+00 1.684628e+00 4.562299e+00 1.694423e+00 4.902532e+00 1.704217e+00 7.714547e+00 1.714011e+00 6.236359e+00 1.723806e+00 5.698043e+00 1.733600e+00 5.511478e+00 1.743394e+00 2.715814e+00 1.753189e+00 5.113141e+00 1.762983e+00 7.516707e+00 1.772777e+00 7.497384e+00 1.782572e+00 4.488045e+00 1.792366e+00 5.146016e+00 1.802160e+00 5.117358e+00 1.811955e+00 7.410260e+00 1.821749e+00 5.162148e+00 1.831543e+00 4.779042e+00 1.841338e+00 7.602583e+00 1.851132e+00 6.454333e+00 1.860926e+00 7.667063e+00 1.870721e+00 6.889437e+00 1.880515e+00 6.536751e+00 1.890310e+00 8.765458e+00 1.900104e+00 3.980165e+00 1.909898e+00 8.367877e+00 1.919693e+00 6.767785e+00 1.929487e+00 8.148178e+00 1.939281e+00 6.955794e+00 1.949076e+00 8.673187e+00 1.958870e+00 7.016261e+00 1.968664e+00 4.835312e+00 1.978459e+00 8.817038e+00 1.988253e+00 8.381905e+00 1.998047e+00 5.872154e+00 2.007842e+00 1.134490e+01 2.017636e+00 5.879958e+00 2.027430e+00 6.301888e+00 2.037225e+00 8.982405e+00 2.047019e+00 6.193756e+00 2.056813e+00 5.311520e+00 2.066608e+00 7.637059e+00 2.076402e+00 5.610865e+00 2.086197e+00 5.156871e+00 2.095991e+00 9.539529e+00 2.105785e+00 9.346240e+00 2.115580e+00 9.965095e+00 2.125374e+00 1.115741e+01 2.135168e+00 7.044102e+00 2.144963e+00 6.254017e+00 2.154757e+00 1.020533e+01 2.164551e+00 6.973787e+00 2.174346e+00 1.193957e+01 2.184140e+00 9.109267e+00 2.193934e+00 6.480505e+00 2.203729e+00 7.664457e+00 2.213523e+00 1.084341e+01 2.223317e+00 7.570281e+00 2.233112e+00 9.244518e+00 2.242906e+00 1.094626e+01 2.252700e+00 1.221627e+01 2.262495e+00 1.010234e+01 2.272289e+00 1.089699e+01 2.282084e+00 1.005600e+01 2.291878e+00 7.501233e+00 2.301672e+00 8.078859e+00 2.311467e+00 8.996957e+00 2.321261e+00 1.143291e+01 2.331055e+00 1.079330e+01 2.340850e+00 1.234540e+01 2.350644e+00 1.089920e+01 2.360438e+00 1.257768e+01 2.370233e+00 1.015195e+01 2.380027e+00 1.043040e+01 2.389821e+00 1.141311e+01 2.399616e+00 8.415179e+00 2.409410e+00 1.080738e+01 2.419204e+00 7.913656e+00 2.428999e+00 1.237762e+01 2.438793e+00 1.236788e+01 2.448587e+00 1.227630e+01 2.458382e+00 1.073266e+01 2.468176e+00 9.397015e+00 2.477971e+00 1.054205e+01 2.487765e+00 9.957353e+00 2.497559e+00 1.308731e+01 2.507354e+00 1.205343e+01 2.517148e+00 1.319172e+01 2.526942e+00 9.233448e+00 2.536737e+00 1.182733e+01 2.546531e+00 8.825216e+00 2.556325e+00 1.379705e+01 2.566120e+00 1.126175e+01 2.575914e+00 1.313590e+01 2.585708e+00 9.430567e+00 2.595503e+00 1.571989e+01 2.605297e+00 9.749521e+00 2.615091e+00 1.621829e+01 2.624886e+00 1.143537e+01 2.634680e+00 1.470500e+01 2.644474e+00 1.319440e+01 2.654269e+00 1.136524e+01 2.664063e+00 1.489735e+01 2.673858e+00 1.649814e+01 2.683652e+00 1.284331e+01 2.693446e+00 1.342498e+01 2.703241e+00 1.327224e+01 2.713035e+00 1.628083e+01 2.722829e+00 1.540562e+01 2.732624e+00 1.476985e+01 2.742418e+00 1.344328e+01 2.752212e+00 1.636685e+01 2.762007e+00 1.795085e+01 2.771801e+00 1.275401e+01 2.781595e+00 1.912796e+01 2.791390e+00 1.770509e+01 2.801184e+00 1.705487e+01 2.810978e+00 1.118596e+01 2.820773e+00 1.924652e+01 2.830567e+00 1.726580e+01 2.840361e+00 1.943820e+01 2.850156e+00 1.838591e+01 2.859950e+00 1.772224e+01 2.869745e+00 1.510925e+01 2.879539e+00 2.087398e+01 2.889333e+00 1.571978e+01 2.899128e+00 1.723467e+01 2.908922e+00 1.862926e+01 2.918716e+00 1.584984e+01 2.928511e+00 2.080553e+01 2.938305e+00 1.815749e+01 2.948099e+00 1.718100e+01 2.957894e+00 1.845913e+01 2.967688e+00 1.968616e+01 2.977482e+00 1.663183e+01 2.987277e+00 1.935144e+01 2.997071e+00 2.032329e+01 3.006865e+00 1.798496e+01 3.016660e+00 1.923646e+01 3.026454e+00 1.708333e+01 3.036248e+00 2.199321e+01 3.046043e+00 2.181638e+01 3.055837e+00 2.394836e+01 3.065632e+00 1.935145e+01 3.075426e+00 2.124517e+01 3.085220e+00 2.225289e+01 3.095015e+00 1.942487e+01 3.104809e+00 2.130900e+01 3.114603e+00 2.063438e+01 3.124398e+00 2.195472e+01 3.134192e+00 2.395534e+01 3.143986e+00 2.416352e+01 3.153781e+00 2.190860e+01 3.163575e+00 2.391182e+01 3.173369e+00 2.700094e+01 3.183164e+00 2.844429e+01 3.192958e+00 2.230150e+01 3.202752e+00 2.747982e+01 3.212547e+00 2.744561e+01 3.222341e+00 2.330571e+01 3.232135e+00 2.588986e+01 3.241930e+00 2.715512e+01 3.251724e+00 2.407930e+01 3.261519e+00 2.554983e+01 3.271313e+00 2.613160e+01 3.281107e+00 2.309565e+01 3.290902e+00 2.712654e+01 3.300696e+00 2.830060e+01 3.310490e+00 2.584386e+01 3.320285e+00 3.070124e+01 3.330079e+00 3.068861e+01 3.339873e+00 2.608056e+01 3.349668e+00 3.032935e+01 3.359462e+00 2.578957e+01 3.369256e+00 2.962532e+01 3.379051e+00 2.675712e+01 3.388845e+00 3.113130e+01 3.398639e+00 3.363467e+01 3.408434e+00 2.973148e+01 3.418228e+00 3.230609e+01 3.428022e+00 3.064265e+01 3.437817e+00 3.032885e+01 3.447611e+00 2.980531e+01 3.457406e+00 3.134510e+01 3.467200e+00 3.163970e+01 3.476994e+00 3.133668e+01 3.486789e+00 3.077437e+01 3.496583e+00 3.550495e+01 3.506377e+00 3.423232e+01 3.516172e+00 3.127223e+01 3.525966e+00 3.647491e+01 3.535760e+00 3.609926e+01 3.545555e+00 3.292977e+01 3.555349e+00 3.536727e+01 3.565143e+00 3.431196e+01 3.574938e+00 3.593296e+01 3.584732e+00 3.566784e+01 3.594526e+00 3.610665e+01 3.604321e+00 3.588001e+01 3.614115e+00 3.706646e+01 3.623909e+00 3.820378e+01 3.633704e+00 3.766664e+01 3.643498e+00 3.708069e+01 3.653293e+00 3.895130e+01 3.663087e+00 3.542595e+01 3.672881e+00 3.812678e+01 3.682676e+00 4.047002e+01 3.692470e+00 4.103707e+01 3.702264e+00 3.903384e+01 3.712059e+00 4.047082e+01 3.721853e+00 3.815228e+01 3.731647e+00 4.217299e+01 3.741442e+00 4.552340e+01 3.751236e+00 4.306316e+01 3.761030e+00 4.482957e+01 3.770825e+00 4.332558e+01 3.780619e+00 4.302230e+01 3.790413e+00 4.339287e+01 3.800208e+00 4.383779e+01 3.810002e+00 4.689354e+01 3.819796e+00 4.794683e+01 3.829591e+00 4.644603e+01 3.839385e+00 4.747618e+01 3.849180e+00 4.615196e+01 3.858974e+00 4.735484e+01 3.868768e+00 5.011103e+01 3.878563e+00 4.906988e+01 3.888357e+00 4.739858e+01 3.898151e+00 4.831541e+01 3.907946e+00 5.137260e+01 3.917740e+00 5.137595e+01 3.927534e+00 5.329468e+01 3.937329e+00 5.053682e+01 3.947123e+00 4.964246e+01 3.956917e+00 5.316254e+01 3.966712e+00 5.264676e+01 3.976506e+00 5.533888e+01 3.986300e+00 5.527729e+01 3.996095e+00 5.510656e+01 4.005889e+00 5.610321e+01 4.015683e+00 5.603341e+01 4.025478e+00 5.719226e+01 4.035272e+00 5.368733e+01 4.045067e+00 5.454147e+01 4.054861e+00 5.948807e+01 4.064655e+00 5.963827e+01 4.074450e+00 5.880629e+01 4.084244e+00 5.672659e+01 4.094038e+00 6.050069e+01 4.103833e+00 6.031021e+01 4.113627e+00 6.232367e+01 4.123421e+00 6.499965e+01 4.133216e+00 6.541533e+01 4.143010e+00 6.132894e+01 4.152804e+00 6.220642e+01 4.162599e+00 6.405510e+01 4.172393e+00 6.594681e+01 4.182187e+00 6.447770e+01 4.191982e+00 6.783734e+01 4.201776e+00 6.774590e+01 4.211570e+00 6.421362e+01 4.221365e+00 6.868811e+01 4.231159e+00 7.028239e+01 4.240954e+00 6.694806e+01 4.250748e+00 7.241546e+01 4.260542e+00 6.952693e+01 4.270337e+00 7.246865e+01 4.280131e+00 7.309664e+01 4.289925e+00 7.417822e+01 4.299720e+00 7.739328e+01 4.309514e+00 7.722307e+01 4.319308e+00 7.347865e+01 4.329103e+00 7.243502e+01 4.338897e+00 7.615109e+01 4.348691e+00 7.418841e+01 4.358486e+00 7.795852e+01 4.368280e+00 7.747418e+01 4.378074e+00 7.938821e+01 4.387869e+00 8.120607e+01 4.397663e+00 8.080466e+01 4.407457e+00 8.326534e+01 4.417252e+00 8.439976e+01 4.427046e+00 8.490712e+01 4.436841e+00 7.954244e+01 4.446635e+00 8.566136e+01 4.456429e+00 8.965209e+01 4.466224e+00 8.477717e+01 4.476018e+00 9.040125e+01 4.485812e+00 8.766908e+01 4.495607e+00 9.124529e+01 4.505401e+00 9.473292e+01 4.515195e+00 9.214977e+01 4.524990e+00 9.383094e+01 4.534784e+00 9.229415e+01 4.544578e+00 9.789980e+01 4.554373e+00 9.511729e+01 4.564167e+00 9.888288e+01 4.573961e+00 9.638032e+01 4.583756e+00 9.894064e+01 4.593550e+00 9.872103e+01 4.603344e+00 1.003795e+02 4.613139e+00 1.022857e+02 4.622933e+00 9.900927e+01 4.632728e+00 1.034879e+02 4.642522e+00 1.025281e+02 4.652316e+00 1.061484e+02 4.662111e+00 1.071532e+02 4.671905e+00 1.069712e+02 4.681699e+00 1.093103e+02 4.691494e+00 1.105836e+02 4.701288e+00 1.125894e+02 4.711082e+00 1.116304e+02 4.720877e+00 1.118801e+02 4.730671e+00 1.122094e+02 4.740465e+00 1.159318e+02 4.750260e+00 1.119969e+02 4.760054e+00 1.150720e+02 4.769848e+00 1.143884e+02 4.779643e+00 1.210523e+02 4.789437e+00 1.212334e+02 4.799231e+00 1.195757e+02 4.809026e+00 1.192345e+02 4.818820e+00 1.245572e+02 4.828615e+00 1.213196e+02 4.838409e+00 1.273005e+02 4.848203e+00 1.290243e+02 4.857998e+00 1.289717e+02 4.867792e+00 1.284174e+02 4.877586e+00 1.300726e+02 4.887381e+00 1.308980e+02 4.897175e+00 1.354977e+02 4.906969e+00 1.390765e+02 4.916764e+00 1.385297e+02 4.926558e+00 1.388218e+02 4.936352e+00 1.365295e+02 4.946147e+00 1.398697e+02 4.955941e+00 1.423328e+02 4.965735e+00 1.463923e+02 4.975530e+00 1.463879e+02 4.985324e+00 1.473006e+02 4.995118e+00 1.460297e+02 5.004913e+00 1.471511e+02 5.014707e+00 1.472382e+02 5.024502e+00 1.452679e+02 5.034296e+00 1.428664e+02 5.044090e+00 1.398786e+02 5.053885e+00 1.407199e+02 5.063679e+00 1.385268e+02 5.073473e+00 1.353663e+02 5.083268e+00 1.390431e+02 5.093062e+00 1.339135e+02 5.102856e+00 1.363741e+02 5.112651e+00 1.324572e+02 5.122445e+00 1.309783e+02 5.132239e+00 1.299121e+02 5.142034e+00 1.259911e+02 5.151828e+00 1.281773e+02 5.161622e+00 1.264196e+02 5.171417e+00 1.262349e+02 5.181211e+00 1.265537e+02 5.191005e+00 1.184801e+02 5.200800e+00 1.182121e+02 5.210594e+00 1.171592e+02 5.220389e+00 1.192923e+02 5.230183e+00 1.163910e+02 5.239977e+00 1.136677e+02 5.249772e+00 1.157810e+02 5.259566e+00 1.133827e+02 5.269360e+00 1.145216e+02 5.279155e+00 1.154051e+02 5.288949e+00 1.100147e+02 5.298743e+00 1.083984e+02 5.308538e+00 1.072865e+02 5.318332e+00 1.053069e+02 5.328126e+00 1.043424e+02 5.337921e+00 1.037413e+02 5.347715e+00 1.011943e+02 5.357509e+00 1.071324e+02 5.367304e+00 1.046604e+02 5.377098e+00 1.020371e+02 5.386892e+00 9.975930e+01 5.396687e+00 9.818553e+01 5.406481e+00 1.004033e+02 5.416276e+00 1.013106e+02 5.426070e+00 9.389241e+01 5.435864e+00 9.721194e+01 5.445659e+00 9.615239e+01 5.455453e+00 9.286808e+01 5.465247e+00 9.360621e+01 5.475042e+00 9.193289e+01 5.484836e+00 8.558677e+01 5.494630e+00 9.103474e+01 5.504425e+00 8.707588e+01 5.514219e+00 8.877641e+01 5.524013e+00 8.871684e+01 5.533808e+00 8.780475e+01 5.543602e+00 8.812686e+01 5.553396e+00 8.338870e+01 5.563191e+00 8.085723e+01 5.572985e+00 8.429923e+01 5.582779e+00 8.353697e+01 5.592574e+00 8.094943e+01 5.602368e+00 8.013365e+01 5.612163e+00 7.836311e+01 5.621957e+00 7.613469e+01 5.631751e+00 7.502511e+01 5.641546e+00 7.836203e+01 5.651340e+00 7.946346e+01 5.661134e+00 7.833956e+01 5.670929e+00 7.590017e+01 5.680723e+00 7.486437e+01 5.690517e+00 7.673988e+01 5.700312e+00 7.336346e+01 5.710106e+00 7.186971e+01 5.719900e+00 7.137927e+01 5.729695e+00 7.465528e+01 5.739489e+00 6.940209e+01 5.749283e+00 6.880099e+01 5.759078e+00 6.978579e+01 5.768872e+00 6.922219e+01 5.778666e+00 6.968159e+01 5.788461e+00 6.759489e+01 5.798255e+00 6.563921e+01 5.808050e+00 6.425235e+01 5.817844e+00 6.684058e+01 5.827638e+00 6.527561e+01 5.837433e+00 5.925668e+01 5.847227e+00 6.220826e+01 5.857021e+00 5.910660e+01 5.866816e+00 6.242577e+01 5.876610e+00 6.215621e+01 5.886404e+00 6.127629e+01 5.896199e+00 6.053490e+01 5.905993e+00 5.734789e+01 5.915787e+00 5.897752e+01 5.925582e+00 5.818245e+01 5.935376e+00 5.714236e+01 5.945170e+00 5.704593e+01 5.954965e+00 5.392913e+01 5.964759e+00 5.677171e+01 5.974553e+00 5.680898e+01 5.984348e+00 5.471450e+01 5.994142e+00 5.438178e+01 6.003937e+00 5.493175e+01 6.013731e+00 5.631298e+01 6.023525e+00 5.315258e+01 6.033320e+00 4.751642e+01 6.043114e+00 5.335998e+01 6.052908e+00 5.345484e+01 6.062703e+00 5.080124e+01 6.072497e+00 4.964150e+01 6.082291e+00 4.862310e+01 6.092086e+00 4.597435e+01 6.101880e+00 4.508320e+01 6.111674e+00 4.864574e+01 6.121469e+00 4.634605e+01 6.131263e+00 4.958740e+01 6.141057e+00 4.842580e+01 6.150852e+00 4.132606e+01 6.160646e+00 4.450107e+01 6.170440e+00 4.672758e+01 6.180235e+00 4.284848e+01 6.190029e+00 4.399324e+01 6.199824e+00 4.451498e+01 6.209618e+00 4.831981e+01 6.219412e+00 4.164652e+01 6.229207e+00 4.477469e+01 6.239001e+00 4.076592e+01 6.248795e+00 4.386593e+01 6.258590e+00 3.838075e+01 6.268384e+00 4.210597e+01 6.278178e+00 4.196283e+01 6.287973e+00 4.260147e+01 6.297767e+00 4.040865e+01 6.307561e+00 4.078559e+01 6.317356e+00 3.909961e+01 6.327150e+00 3.957569e+01 6.336944e+00 3.761598e+01 6.346739e+00 4.039542e+01 6.356533e+00 3.860673e+01 6.366327e+00 3.744978e+01 6.376122e+00 3.730138e+01 6.385916e+00 3.462308e+01 6.395711e+00 3.888579e+01 6.405505e+00 3.750241e+01 6.415299e+00 3.584765e+01 6.425094e+00 3.378648e+01 6.434888e+00 3.794292e+01 6.444682e+00 3.519233e+01 6.454477e+00 3.217361e+01 6.464271e+00 3.400605e+01 6.474065e+00 3.464892e+01 6.483860e+00 3.537495e+01 6.493654e+00 3.398454e+01 6.503448e+00 2.986808e+01 6.513243e+00 3.404947e+01 6.523037e+00 3.393188e+01 6.532831e+00 3.261415e+01 6.542626e+00 3.143750e+01 6.552420e+00 2.727654e+01 6.562214e+00 3.013965e+01 6.572009e+00 3.018096e+01 6.581803e+00 3.214625e+01 6.591598e+00 2.924955e+01 6.601392e+00 3.435923e+01 6.611186e+00 2.550641e+01 6.620981e+00 3.056007e+01 6.630775e+00 2.937366e+01 6.640569e+00 2.793182e+01 6.650364e+00 2.736076e+01 6.660158e+00 2.781026e+01 6.669952e+00 2.636431e+01 6.679747e+00 2.663268e+01 6.689541e+00 2.637117e+01 6.699335e+00 2.730475e+01 6.709130e+00 2.769355e+01 6.718924e+00 2.170330e+01 6.728718e+00 2.873371e+01 6.738513e+00 2.247953e+01 6.748307e+00 2.421929e+01 6.758101e+00 2.598976e+01 6.767896e+00 2.367353e+01 6.777690e+00 2.331048e+01 6.787485e+00 2.319857e+01 6.797279e+00 2.348209e+01 6.807073e+00 2.679264e+01 6.816868e+00 2.173251e+01 6.826662e+00 2.078808e+01 6.836456e+00 2.282675e+01 6.846251e+00 2.331214e+01 6.856045e+00 2.657325e+01 6.865839e+00 2.128182e+01 6.875634e+00 2.134561e+01 6.885428e+00 2.254173e+01 6.895222e+00 2.037178e+01 6.905017e+00 2.252907e+01 6.914811e+00 1.904251e+01 6.924605e+00 2.075074e+01 6.934400e+00 2.092613e+01 6.944194e+00 1.973930e+01 6.953988e+00 2.152604e+01 6.963783e+00 1.818827e+01 6.973577e+00 2.111488e+01 6.983372e+00 2.157233e+01 6.993166e+00 2.151511e+01 7.002960e+00 1.857721e+01 7.012755e+00 1.922324e+01 7.022549e+00 2.003253e+01 7.032343e+00 2.026874e+01 7.042138e+00 2.077310e+01 7.051932e+00 1.653551e+01 7.061726e+00 1.726442e+01 7.071521e+00 1.953220e+01 7.081315e+00 1.560098e+01 7.091109e+00 1.514355e+01 7.100904e+00 1.862086e+01 7.110698e+00 1.737582e+01 7.120492e+00 1.892086e+01 7.130287e+00 1.822223e+01 7.140081e+00 1.864266e+01 7.149875e+00 1.325473e+01 7.159670e+00 1.428375e+01 7.169464e+00 1.436022e+01 7.179259e+00 1.806513e+01 7.189053e+00 1.926370e+01 7.198847e+00 1.646983e+01 7.208642e+00 1.151439e+01 7.218436e+00 1.636222e+01 7.228230e+00 1.880353e+01 7.238025e+00 1.448379e+01 7.247819e+00 1.367515e+01 7.257613e+00 1.435617e+01 7.267408e+00 1.688494e+01 7.277202e+00 1.245205e+01 7.286996e+00 1.489008e+01 7.296791e+00 1.866421e+01 7.306585e+00 1.390436e+01 7.316379e+00 1.781381e+01 7.326174e+00 1.139000e+01 7.335968e+00 1.445306e+01 7.345762e+00 1.219185e+01 7.355557e+00 1.321315e+01 7.365351e+00 1.524230e+01 7.375146e+00 1.295212e+01 7.384940e+00 1.357661e+01 7.394734e+00 1.523100e+01 7.404529e+00 1.077899e+01 7.414323e+00 1.569069e+01 7.424117e+00 1.330244e+01 7.433912e+00 1.401417e+01 7.443706e+00 1.174989e+01 7.453500e+00 9.380239e+00 7.463295e+00 1.356123e+01 7.473089e+00 1.258091e+01 7.482883e+00 1.125268e+01 7.492678e+00 1.379899e+01 7.502472e+00 9.073772e+00 7.512266e+00 1.485087e+01 7.522061e+00 1.172269e+01 7.531855e+00 1.499828e+01 7.541649e+00 1.512252e+01 7.551444e+00 8.698802e+00 7.561238e+00 9.967997e+00 7.571033e+00 1.185147e+01 7.580827e+00 9.452936e+00 7.590621e+00 1.102782e+01 7.600416e+00 9.007380e+00 7.610210e+00 1.252655e+01 7.620004e+00 1.043170e+01 7.629799e+00 1.374767e+01 7.639593e+00 7.419494e+00 7.649387e+00 1.171294e+01 7.659182e+00 1.027006e+01 7.668976e+00 9.677913e+00 7.678770e+00 1.261533e+01 7.688565e+00 8.763959e+00 7.698359e+00 1.361440e+01 7.708153e+00 9.246049e+00 7.717948e+00 1.033087e+01 7.727742e+00 3.931677e+00 7.737536e+00 9.989109e+00 7.747331e+00 1.011085e+01 7.757125e+00 1.210029e+01 7.766920e+00 1.074853e+01 7.776714e+00 1.501119e+01 7.786508e+00 1.067911e+01 7.796303e+00 9.558195e+00 7.806097e+00 7.707008e+00 7.815891e+00 6.734959e+00 7.825686e+00 1.433166e+01 7.835480e+00 9.272867e+00 7.845274e+00 1.032756e+01 7.855069e+00 8.966091e+00 7.864863e+00 6.584029e+00 7.874657e+00 8.269469e+00 7.884452e+00 1.274394e+01 7.894246e+00 1.055551e+01 7.904040e+00 7.886202e+00 7.913835e+00 8.928416e+00 7.923629e+00 7.235757e+00 7.933423e+00 7.418810e+00 7.943218e+00 5.796315e+00 7.953012e+00 1.068721e+01 7.962807e+00 6.959070e+00 7.972601e+00 7.112491e+00 7.982395e+00 8.782625e+00 7.992190e+00 4.347006e+00 8.001984e+00 1.058214e+01 8.011778e+00 6.021061e+00 8.021573e+00 6.818268e+00 8.031367e+00 8.935762e+00 8.041161e+00 7.486304e+00 8.050956e+00 4.648944e+00 8.060750e+00 5.723941e+00 8.070544e+00 7.018311e+00 8.080339e+00 4.751480e+00 8.090133e+00 7.449779e+00 8.099927e+00 6.557584e+00 8.109722e+00 6.119997e+00 8.119516e+00 8.087697e+00 8.129310e+00 6.537803e+00 8.139105e+00 9.046252e+00 8.148899e+00 7.247932e+00 8.158694e+00 6.194464e+00 8.168488e+00 8.195018e+00 8.178282e+00 4.920591e+00 8.188077e+00 4.157068e+00 8.197871e+00 5.115394e+00 8.207665e+00 4.852831e+00 8.217460e+00 3.321018e+00 8.227254e+00 4.817385e+00 8.237048e+00 4.264514e+00 8.246843e+00 3.594663e+00 8.256637e+00 7.854682e+00 8.266431e+00 6.607683e+00 8.276226e+00 6.628947e+00 8.286020e+00 4.467746e+00 8.295814e+00 7.995283e+00 8.305609e+00 7.907542e+00 8.315403e+00 5.128391e+00 8.325197e+00 5.203532e+00 8.334992e+00 4.097813e+00 8.344786e+00 5.549268e+00 8.354581e+00 5.814353e+00 8.364375e+00 4.517825e+00 8.374169e+00 4.439681e+00 8.383964e+00 7.840601e+00 8.393758e+00 7.352790e+00 8.403552e+00 7.013904e+00 8.413347e+00 3.683952e+00 8.423141e+00 4.582092e+00 8.432935e+00 5.271809e+00 8.442730e+00 3.037341e+00 8.452524e+00 2.562339e+00 8.462318e+00 2.644062e+00 8.472113e+00 5.064013e+00 8.481907e+00 4.502358e+00 8.491701e+00 5.905939e+00 8.501496e+00 7.900794e+00 8.511290e+00 5.370918e+00 8.521084e+00 3.699485e+00 8.530879e+00 4.632803e+00 8.540673e+00 5.229484e+00 8.550468e+00 1.593377e+00 8.560262e+00 7.549737e+00 8.570056e+00 5.450158e-01 8.579851e+00 6.332317e+00 8.589645e+00 4.786524e+00 8.599439e+00 2.514985e+00 8.609234e+00 8.191060e+00 8.619028e+00 7.050753e+00 8.628822e+00 4.006949e+00 8.638617e+00 3.477611e+00 8.648411e+00 5.786483e+00 8.658205e+00 3.279820e+00 8.668000e+00 3.022235e+00 8.677794e+00 2.390124e+00 8.687588e+00 5.622222e+00 8.697383e+00 5.337656e+00 8.707177e+00 2.420423e+00 8.716971e+00 5.985555e+00 8.726766e+00 4.918132e+00 8.736560e+00 4.181085e+00 8.746355e+00 4.100895e+00 8.756149e+00 2.796584e+00 8.765943e+00 2.227553e+00 8.775738e+00 1.816365e+00 8.785532e+00 2.195019e+00 8.795326e+00 6.077339e+00 8.805121e+00 2.340336e+00 8.814915e+00 3.383655e+00 8.824709e+00 4.280026e+00 8.834504e+00 5.667593e+00 8.844298e+00 4.510272e+00 8.854092e+00 3.673941e+00 8.863887e+00 5.195828e+00 8.873681e+00 2.534136e+00 8.883475e+00 3.646265e+00 8.893270e+00 1.710622e+00 8.903064e+00 4.156561e+00 8.912858e+00 3.110953e+00 8.922653e+00 4.352033e+00 8.932447e+00 3.887345e+00 8.942242e+00 2.951942e+00 8.952036e+00 2.010261e+00 8.961830e+00 3.503508e+00 8.971625e+00 4.304116e+00 8.981419e+00 1.592925e+00 8.991213e+00 -2.948303e+00 9.001008e+00 2.682326e-01 9.010802e+00 5.411964e+00 9.020596e+00 3.727042e+00 9.030391e+00 2.918614e+00 9.040185e+00 -1.301831e-01 9.049979e+00 3.719666e+00 9.059774e+00 2.834387e+00 9.069568e+00 7.048721e+00 9.079362e+00 4.149693e+00 9.089157e+00 -5.718387e-01 9.098951e+00 4.501959e+00 9.108745e+00 -1.097690e+00 9.118540e+00 3.823671e+00 9.128334e+00 2.364617e+00 9.138129e+00 3.464702e+00 9.147923e+00 3.412711e+00 9.157717e+00 5.945935e+00 9.167512e+00 1.965897e-01 9.177306e+00 5.528856e+00 9.187100e+00 2.112424e+00 9.196895e+00 1.175153e+00 9.206689e+00 2.729613e+00 9.216483e+00 4.515973e-01 9.226278e+00 4.069242e+00 9.236072e+00 -1.249268e+00 9.245866e+00 1.512860e+00 9.255661e+00 3.094765e+00 9.265455e+00 2.120606e+00 9.275249e+00 4.317762e+00 9.285044e+00 1.907302e+00 9.294838e+00 1.812566e+00 9.304632e+00 5.740751e-01 9.314427e+00 3.074655e+00 9.324221e+00 1.330752e+00 9.334016e+00 4.181450e+00 9.343810e+00 -1.948346e+00 9.353604e+00 3.636548e+00 9.363399e+00 2.876049e-01 9.373193e+00 4.322147e+00 9.382987e+00 1.767094e+00 9.392782e+00 3.372141e+00 9.402576e+00 2.246911e+00 9.412370e+00 1.085065e+00 9.422165e+00 1.117924e+00 9.431959e+00 5.286048e+00 9.441753e+00 1.454095e+00 9.451548e+00 2.718556e+00 9.461342e+00 3.929067e+00 9.471136e+00 1.687764e+00 9.480931e+00 3.141091e+00 9.490725e+00 5.472377e+00 9.500519e+00 -6.253090e-03 9.510314e+00 7.682379e-02 9.520108e+00 -1.390425e+00 9.529903e+00 1.165148e+00 9.539697e+00 7.117501e-01 9.549491e+00 -1.639254e+00 9.559286e+00 2.059412e+00 9.569080e+00 5.813534e-01 9.578874e+00 1.797586e+00 9.588669e+00 -4.704101e-01 9.598463e+00 9.223612e-02 9.608257e+00 -3.268398e+00 9.618052e+00 3.446785e+00 9.627846e+00 -1.219799e-01 9.637640e+00 3.488014e-01 9.647435e+00 9.474283e-01 9.657229e+00 -1.540287e-01 9.667023e+00 4.592260e+00 9.676818e+00 -1.725482e-01 9.686612e+00 3.081548e+00 9.696406e+00 5.146320e-01 9.706201e+00 3.698340e+00 9.715995e+00 2.804555e+00 9.725790e+00 4.313891e+00 9.735584e+00 1.566664e+00 9.745378e+00 4.478554e+00 9.755173e+00 1.679092e+00 9.764967e+00 -1.559851e+00 9.774761e+00 2.140149e+00 9.784556e+00 3.457835e+00 9.794350e+00 1.422226e+00 9.804144e+00 -1.192947e+00 9.813939e+00 6.381921e-01 9.823733e+00 1.051526e+00 9.833527e+00 8.864191e-01 9.843322e+00 4.811925e-01 9.853116e+00 3.061412e+00 9.862910e+00 3.645097e-01 9.872705e+00 -1.390796e+00 9.882499e+00 2.500331e+00 9.892293e+00 1.367250e+00 9.902088e+00 3.657223e+00 9.911882e+00 1.907885e+00 9.921677e+00 2.258260e+00 9.931471e+00 1.537239e+00 9.941265e+00 -2.747556e+00 9.951060e+00 -2.791090e+00 9.960854e+00 2.200804e+00 9.970648e+00 -4.538760e-01 9.980443e+00 3.612982e-01 9.990237e+00 1.799175e+00 1.000003e+01 1.700779e+00 Sigima-1.1.1/sigima/data/tests/curve_fitting/polynomial_fit.txt000066400000000000000000000037361514013333200247110ustar00rootroot000000000000000.000000 -836852. 1.00000 -172251. 2.00000 187062. 3.00000 1.61508e+006 4.00000 -177772. 5.00000 651066. 6.00000 -550077. 7.00000 188132. 8.00000 916620. 9.00000 1.19127e+006 10.0000 1.51254e+006 11.0000 -1.37964e+006 12.0000 20115.0 13.0000 980184. 14.0000 -1.27622e+006 15.0000 646826. 16.0000 796723. 17.0000 -879724. 18.0000 225138. 19.0000 79726.6 20.0000 -316285. 21.0000 -488595. 22.0000 -491411. 23.0000 298494. 24.0000 -2.48543e+006 25.0000 -29346.0 26.0000 -411411. 27.0000 -2.00938e+006 28.0000 -117616. 29.0000 -149442. 30.0000 606267. 31.0000 193518. 32.0000 -761751. 33.0000 -1.26039e+006 34.0000 -65085.1 35.0000 -823671. 36.0000 304414. 37.0000 -1.98254e+006 38.0000 -194665. 39.0000 -2.50193e+006 40.0000 -661923. 41.0000 -2.00549e+006 42.0000 -1.04222e+006 43.0000 -1.51051e+006 44.0000 -2.44399e+006 45.0000 -910750. 46.0000 -1.78720e+006 47.0000 -2.81173e+006 48.0000 -2.69147e+006 49.0000 -2.18114e+006 50.0000 -431034. 51.0000 -4.92825e+006 52.0000 -4.28042e+006 53.0000 -3.51385e+006 54.0000 -2.76250e+006 55.0000 -2.85160e+006 56.0000 -846922. 57.0000 -1.50944e+006 58.0000 -1.90790e+006 59.0000 -2.98577e+006 60.0000 -1.20261e+006 61.0000 -4.16554e+006 62.0000 -4.29795e+006 63.0000 -2.83926e+006 64.0000 -4.54534e+006 65.0000 -4.60528e+006 66.0000 -5.12058e+006 67.0000 -4.36011e+006 68.0000 -4.05894e+006 69.0000 -4.79213e+006 70.0000 -7.29108e+006 71.0000 -9.06573e+006 72.0000 -5.16214e+006 73.0000 -7.99719e+006 74.0000 -7.94511e+006 75.0000 -7.76207e+006 76.0000 -8.87905e+006 77.0000 -8.80985e+006 78.0000 -7.85761e+006 79.0000 -9.56385e+006 80.0000 -1.06081e+007 81.0000 -9.63798e+006 82.0000 -8.43446e+006 83.0000 -9.52668e+006 84.0000 -9.71984e+006 85.0000 -1.13906e+007 86.0000 -1.35419e+007 87.0000 -1.35338e+007 88.0000 -1.26804e+007 89.0000 -1.31118e+007 90.0000 -1.28440e+007 91.0000 -1.30189e+007 92.0000 -1.56496e+007 93.0000 -1.40976e+007 94.0000 -1.57705e+007 95.0000 -1.63273e+007 96.0000 -1.68870e+007 97.0000 -1.85104e+007 98.0000 -1.66108e+007 99.0000 -1.76807e+007 Sigima-1.1.1/sigima/data/tests/curve_fitting/twohalfgaussian_fit.txt000066400000000000000000000442501514013333200257210ustar00rootroot00000000000000-5.000000 1.928496 -4.974975 1.976234 -4.949950 1.992963 -4.924925 1.903537 -4.899900 1.913881 -4.874875 1.888370 -4.849850 2.001379 -4.824825 1.997983 -4.799800 1.983119 -4.774775 1.941746 -4.749750 2.158011 -4.724725 2.062961 -4.699700 1.902780 -4.674675 2.044072 -4.649650 2.060969 -4.624625 2.096687 -4.599600 1.898181 -4.574575 2.072864 -4.549550 1.968637 -4.524525 1.941811 -4.499499 1.977701 -4.474474 1.831666 -4.449449 2.025670 -4.424424 1.988876 -4.399399 2.043516 -4.374374 1.989626 -4.349349 2.027860 -4.324324 1.952962 -4.299299 1.983897 -4.274274 2.027318 -4.249249 1.991397 -4.224224 2.101714 -4.199199 2.043888 -4.174174 1.914599 -4.149149 1.969726 -4.124124 1.915645 -4.099099 2.035156 -4.074074 2.100539 -4.049049 1.950652 -4.024024 1.994529 -3.998999 1.978053 -3.973974 2.067153 -3.948949 1.938965 -3.923924 1.953232 -3.898899 1.991500 -3.873874 2.040532 -3.848849 2.100586 -3.823824 1.976317 -3.798799 2.120787 -3.773774 1.913724 -3.748749 2.131583 -3.723724 1.936925 -3.698699 1.936499 -3.673674 2.060345 -3.648649 2.037602 -3.623624 2.103582 -3.598599 1.984621 -3.573574 2.096958 -3.548549 1.942703 -3.523524 1.992747 -3.498498 1.920331 -3.473473 2.043465 -3.448448 1.935125 -3.423423 1.977163 -3.398398 1.944533 -3.373373 1.967219 -3.348348 1.962406 -3.323323 2.058746 -3.298298 2.022378 -3.273273 1.965677 -3.248248 1.953323 -3.223223 2.045045 -3.198198 2.053841 -3.173173 2.084591 -3.148148 2.163196 -3.123123 2.052807 -3.098098 2.066979 -3.073073 1.915403 -3.048048 1.968310 -3.023023 1.934615 -2.997998 2.120860 -2.972973 1.957874 -2.947948 2.133042 -2.922923 2.058226 -2.897898 2.054420 -2.872873 1.938607 -2.847848 2.091111 -2.822823 2.092078 -2.797798 1.970658 -2.772773 1.926553 -2.747748 2.016751 -2.722723 2.099982 -2.697698 1.931187 -2.672673 1.891125 -2.647648 2.014854 -2.622623 1.990586 -2.597598 1.899217 -2.572573 2.011072 -2.547548 1.919399 -2.522523 1.955379 -2.497497 2.048284 -2.472472 2.112852 -2.447447 1.947654 -2.422422 2.092432 -2.397397 2.063469 -2.372372 1.873586 -2.347347 1.984357 -2.322322 2.224478 -2.297297 1.908969 -2.272272 1.975626 -2.247247 2.072054 -2.222222 1.924949 -2.197197 2.002568 -2.172172 1.983497 -2.147147 2.005456 -2.122122 2.010410 -2.097097 1.947859 -2.072072 2.016869 -2.047047 2.007226 -2.022022 2.066898 -1.996997 1.960667 -1.971972 1.964409 -1.946947 2.040798 -1.921922 1.998304 -1.896897 1.960272 -1.871872 2.088065 -1.846847 2.054990 -1.821822 2.041720 -1.796797 2.060696 -1.771772 2.107234 -1.746747 2.103299 -1.721722 2.085293 -1.696697 2.032730 -1.671672 2.032857 -1.646647 1.994311 -1.621622 2.162773 -1.596597 2.041378 -1.571572 2.149824 -1.546547 2.103163 -1.521522 2.187857 -1.496496 2.149630 -1.471471 2.200178 -1.446446 2.251979 -1.421421 2.048155 -1.396396 2.124236 -1.371371 2.241149 -1.346346 2.107806 -1.321321 2.133920 -1.296296 2.063402 -1.271271 2.264573 -1.246246 2.042744 -1.221221 2.291377 -1.196196 2.302762 -1.171171 2.233351 -1.146146 2.247779 -1.121121 2.216551 -1.096096 2.409484 -1.071071 2.329569 -1.046046 2.277762 -1.021021 2.487500 -0.995996 2.388238 -0.970971 2.372260 -0.945946 2.473370 -0.920921 2.530131 -0.895896 2.417541 -0.870871 2.302706 -0.845846 2.456175 -0.820821 2.576572 -0.795796 2.625920 -0.770771 2.619467 -0.745746 2.589528 -0.720721 2.658467 -0.695696 2.650500 -0.670671 2.534721 -0.645646 2.777413 -0.620621 2.837537 -0.595596 2.934088 -0.570571 2.957555 -0.545546 2.941828 -0.520521 3.071053 -0.495495 2.971671 -0.470470 3.093237 -0.445445 3.105546 -0.420420 3.157260 -0.395395 3.111568 -0.370370 3.181561 -0.345345 3.261345 -0.320320 3.293203 -0.295295 3.351719 -0.270270 3.291949 -0.245245 3.322167 -0.220220 3.442427 -0.195195 3.544523 -0.170170 3.519047 -0.145145 3.588649 -0.120120 3.572870 -0.095095 3.642919 -0.070070 3.644919 -0.045045 3.674722 -0.020020 3.748621 0.005005 3.764788 0.030030 3.796356 0.055055 3.970079 0.080080 3.901102 0.105105 4.004909 0.130130 4.101910 0.155155 4.213858 0.180180 4.091966 0.205205 4.235233 0.230230 4.097707 0.255255 4.278877 0.280280 4.383599 0.305305 4.397917 0.330330 4.471471 0.355355 4.492672 0.380380 4.348087 0.405405 4.538729 0.430430 4.582826 0.455455 4.590710 0.480480 4.656444 0.505506 4.637081 0.530531 4.737638 0.555556 4.741381 0.580581 4.781946 0.605606 4.752018 0.630631 4.914563 0.655656 4.805187 0.680681 4.868413 0.705706 4.851993 0.730731 4.959433 0.755756 4.912647 0.780781 4.898990 0.805806 4.927785 0.830831 4.918620 0.855856 5.029512 0.880881 4.918016 0.905906 4.960633 0.930931 4.949794 0.955956 4.936225 0.980981 5.092737 1.006006 5.055513 1.031031 4.891714 1.056056 5.063216 1.081081 4.953098 1.106106 4.879832 1.131131 4.898629 1.156156 5.001849 1.181181 4.910951 1.206206 4.800350 1.231231 4.978681 1.256256 4.839614 1.281281 4.947772 1.306306 4.980963 1.331331 4.974991 1.356356 5.048467 1.381381 5.009836 1.406406 5.060891 1.431431 5.033897 1.456456 5.074517 1.481481 5.088533 1.506507 4.886892 1.531532 4.888431 1.556557 4.973153 1.581582 4.924742 1.606607 4.947573 1.631632 4.952160 1.656657 4.928002 1.681682 5.070659 1.706707 4.924861 1.731732 5.069168 1.756757 4.989887 1.781782 4.991224 1.806807 4.981301 1.831832 4.999398 1.856857 4.878863 1.881882 4.853976 1.906907 4.860173 1.931932 4.947754 1.956957 4.968211 1.981982 4.948494 2.007007 4.872667 2.032032 4.869231 2.057057 4.873822 2.082082 4.850970 2.107107 5.065773 2.132132 4.894972 2.157157 4.813219 2.182182 4.859973 2.207207 4.870739 2.232232 4.865177 2.257257 5.038662 2.282282 4.947983 2.307307 4.789675 2.332332 5.014117 2.357357 4.984673 2.382382 4.907955 2.407407 4.826205 2.432432 4.881630 2.457457 4.733194 2.482482 4.792045 2.507508 4.943105 2.532533 4.828836 2.557558 4.969306 2.582583 4.867318 2.607608 4.809121 2.632633 4.873909 2.657658 4.929847 2.682683 4.936832 2.707708 4.885742 2.732733 4.811414 2.757758 4.873735 2.782783 4.803606 2.807808 4.809501 2.832833 4.765709 2.857858 4.771205 2.882883 4.907575 2.907908 4.838583 2.932933 4.813740 2.957958 4.819446 2.982983 4.748546 3.008008 4.797443 3.033033 4.702956 3.058058 4.773425 3.083083 4.792729 3.108108 4.676079 3.133133 4.719339 3.158158 4.671019 3.183183 4.733313 3.208208 4.703968 3.233233 4.812938 3.258258 4.834552 3.283283 4.723208 3.308308 4.796303 3.333333 4.664337 3.358358 4.732685 3.383383 4.734973 3.408408 4.807932 3.433433 4.695583 3.458458 4.830743 3.483483 4.682422 3.508509 4.689727 3.533534 4.669124 3.558559 4.619484 3.583584 4.590696 3.608609 4.682953 3.633634 4.676788 3.658659 4.654863 3.683684 4.780011 3.708709 4.497323 3.733734 4.599794 3.758759 4.645224 3.783784 4.462903 3.808809 4.558166 3.833834 4.535746 3.858859 4.728312 3.883884 4.537514 3.908909 4.636645 3.933934 4.551640 3.958959 4.484571 3.983984 4.703092 4.009009 4.625747 4.034034 4.588068 4.059059 4.471458 4.084084 4.544684 4.109109 4.504913 4.134134 4.498953 4.159159 4.371916 4.184184 4.505317 4.209209 4.513641 4.234234 4.493412 4.259259 4.631147 4.284284 4.507634 4.309309 4.375090 4.334334 4.423739 4.359359 4.500121 4.384384 4.395619 4.409409 4.213715 4.434434 4.397017 4.459459 4.400713 4.484484 4.412020 4.509510 4.397589 4.534535 4.524993 4.559560 4.281306 4.584585 4.344962 4.609610 4.500206 4.634635 4.366532 4.659660 4.245920 4.684685 4.449563 4.709710 4.260836 4.734735 4.411324 4.759760 4.380948 4.784785 4.412932 4.809810 4.219000 4.834835 4.386333 4.859860 4.312983 4.884885 4.401478 4.909910 4.251288 4.934935 4.171943 4.959960 4.339182 4.984985 4.368568 5.010010 4.260241 5.035035 4.165737 5.060060 4.246147 5.085085 4.274832 5.110110 4.270676 5.135135 4.265350 5.160160 4.200493 5.185185 4.296969 5.210210 4.184652 5.235235 4.157028 5.260260 4.166215 5.285285 4.178839 5.310310 4.231855 5.335335 4.078577 5.360360 4.261717 5.385385 4.105670 5.410410 4.101219 5.435435 4.086387 5.460460 4.083454 5.485485 4.151665 5.510511 4.095810 5.535536 3.948163 5.560561 4.079528 5.585586 3.955769 5.610611 3.983534 5.635636 4.015903 5.660661 3.904442 5.685686 4.105173 5.710711 3.966446 5.735736 4.001882 5.760761 3.928569 5.785786 4.127139 5.810811 3.885721 5.835836 3.921534 5.860861 3.932142 5.885886 3.800268 5.910911 4.046168 5.935936 3.852241 5.960961 3.938250 5.985986 3.901408 6.011011 3.882503 6.036036 4.061578 6.061061 3.951286 6.086086 3.975497 6.111111 3.912243 6.136136 3.823648 6.161161 3.867133 6.186186 3.903630 6.211211 3.795782 6.236236 3.802117 6.261261 3.840194 6.286286 3.707724 6.311311 3.885632 6.336336 3.838758 6.361361 3.636936 6.386386 3.801265 6.411411 3.763488 6.436436 3.680179 6.461461 3.680192 6.486486 3.709714 6.511512 3.867889 6.536537 3.724426 6.561562 3.809190 6.586587 3.755793 6.611612 3.785535 6.636637 3.719218 6.661662 3.571277 6.686687 3.825660 6.711712 3.648111 6.736737 3.600057 6.761762 3.657712 6.786787 3.738378 6.811812 3.661138 6.836837 3.641796 6.861862 3.614048 6.886887 3.686116 6.911912 3.735990 6.936937 3.693427 6.961962 3.621412 6.986987 3.564706 7.012012 3.520342 7.037037 3.582979 7.062062 3.501753 7.087087 3.422844 7.112112 3.619166 7.137137 3.536511 7.162162 3.592710 7.187187 3.506516 7.212212 3.411055 7.237237 3.605017 7.262262 3.504693 7.287287 3.557735 7.312312 3.627074 7.337337 3.589960 7.362362 3.479616 7.387387 3.483588 7.412412 3.517144 7.437437 3.380430 7.462462 3.416772 7.487487 3.384777 7.512513 3.495410 7.537538 3.401847 7.562563 3.510222 7.587588 3.375862 7.612613 3.452232 7.637638 3.506573 7.662663 3.433539 7.687688 3.260804 7.712713 3.373819 7.737738 3.455200 7.762763 3.460694 7.787788 3.467255 7.812813 3.290886 7.837838 3.318640 7.862863 3.360906 7.887888 3.355568 7.912913 3.458706 7.937938 3.377727 7.962963 3.360388 7.987988 3.378994 8.013013 3.295688 8.038038 3.348644 8.063063 3.274337 8.088088 3.209032 8.113113 3.325115 8.138138 3.312305 8.163163 3.394717 8.188188 3.254080 8.213213 3.187897 8.238238 3.294362 8.263263 3.234706 8.288288 3.376678 8.313313 3.277407 8.338338 3.112361 8.363363 3.286872 8.388388 3.179005 8.413413 3.256161 8.438438 3.265850 8.463463 3.304848 8.488488 3.232916 8.513514 3.176505 8.538539 3.165047 8.563564 3.143313 8.588589 3.213872 8.613614 3.123862 8.638639 3.120057 8.663664 3.122116 8.688689 3.125357 8.713714 3.216275 8.738739 3.091470 8.763764 3.184607 8.788789 3.225266 8.813814 3.061941 8.838839 3.189872 8.863864 2.946032 8.888889 3.131995 8.913914 3.074585 8.938939 3.206199 8.963964 3.134474 8.988989 3.059088 9.014014 3.171037 9.039039 3.054338 9.064064 3.153944 9.089089 3.032469 9.114114 3.118716 9.139139 3.031364 9.164164 2.997884 9.189189 2.955867 9.214214 3.199317 9.239239 2.977875 9.264264 2.974149 9.289289 3.046203 9.314314 3.088063 9.339339 2.927702 9.364364 2.945429 9.389389 2.975946 9.414414 2.974562 9.439439 2.931489 9.464464 2.953140 9.489489 3.160327 9.514515 3.111305 9.539540 2.889230 9.564565 2.885199 9.589590 3.013279 9.614615 2.931223 9.639640 3.041292 9.664665 3.071401 9.689690 2.976013 9.714715 2.969785 9.739740 2.777148 9.764765 2.979178 9.789790 3.059212 9.814815 2.985087 9.839840 2.896114 9.864865 2.993379 9.889890 3.070057 9.914915 2.905035 9.939940 2.805621 9.964965 2.938006 9.989990 2.837517 10.015015 2.864906 10.040040 2.933908 10.065065 2.873172 10.090090 2.788383 10.115115 2.828529 10.140140 2.911704 10.165165 2.931778 10.190190 2.843198 10.215215 2.975055 10.240240 2.819625 10.265265 2.841466 10.290290 2.978059 10.315315 2.789690 10.340340 2.895093 10.365365 2.920910 10.390390 2.865747 10.415415 2.913763 10.440440 2.868923 10.465465 2.829036 10.490490 2.717301 10.515516 2.851141 10.540541 2.863892 10.565566 2.795792 10.590591 2.689869 10.615616 2.844228 10.640641 2.834588 10.665666 2.890111 10.690691 2.836615 10.715716 2.776990 10.740741 2.787057 10.765766 2.860403 10.790791 2.815037 10.815816 2.799332 10.840841 2.745325 10.865866 2.897279 10.890891 2.674020 10.915916 2.799196 10.940941 2.656724 10.965966 2.715158 10.990991 2.732412 11.016016 2.743920 11.041041 2.731137 11.066066 2.819679 11.091091 2.824903 11.116116 2.693094 11.141141 2.744035 11.166166 2.646742 11.191191 2.610884 11.216216 2.786403 11.241241 2.721629 11.266266 2.775953 11.291291 2.719020 11.316316 2.735346 11.341341 2.734200 11.366366 2.672903 11.391391 2.614069 11.416416 2.677599 11.441441 2.581514 11.466466 2.723097 11.491491 2.637350 11.516517 2.635128 11.541542 2.647537 11.566567 2.632712 11.591592 2.759495 11.616617 2.637481 11.641642 2.680361 11.666667 2.729112 11.691692 2.628466 11.716717 2.617244 11.741742 2.751749 11.766767 2.627881 11.791792 2.680844 11.816817 2.706527 11.841842 2.658194 11.866867 2.708443 11.891892 2.750589 11.916917 2.705596 11.941942 2.668721 11.966967 2.631610 11.991992 2.552088 12.017017 2.631649 12.042042 2.639708 12.067067 2.616637 12.092092 2.740398 12.117117 2.664742 12.142142 2.661718 12.167167 2.683398 12.192192 2.738976 12.217217 2.642449 12.242242 2.806591 12.267267 2.677999 12.292292 2.613448 12.317317 2.678425 12.342342 2.600747 12.367367 2.562299 12.392392 2.614292 12.417417 2.783930 12.442442 2.645525 12.467467 2.563151 12.492492 2.527154 12.517518 2.565311 12.542543 2.599997 12.567568 2.548230 12.592593 2.596487 12.617618 2.625788 12.642643 2.710328 12.667668 2.543350 12.692693 2.597139 12.717718 2.558479 12.742743 2.692464 12.767768 2.594401 12.792793 2.645487 12.817818 2.627118 12.842843 2.501723 12.867868 2.538803 12.892893 2.652307 12.917918 2.599562 12.942943 2.531194 12.967968 2.631641 12.992993 2.604331 13.018018 2.542936 13.043043 2.701415 13.068068 2.635809 13.093093 2.444002 13.118118 2.572152 13.143143 2.413301 13.168168 2.541577 13.193193 2.668078 13.218218 2.717755 13.243243 2.584467 13.268268 2.682387 13.293293 2.556639 13.318318 2.717309 13.343343 2.670291 13.368368 2.592979 13.393393 2.634084 13.418418 2.617741 13.443443 2.564368 13.468468 2.500765 13.493493 2.536443 13.518519 2.533937 13.543544 2.520008 13.568569 2.497836 13.593594 2.439393 13.618619 2.603198 13.643644 2.500714 13.668669 2.542502 13.693694 2.319101 13.718719 2.613557 13.743744 2.550684 13.768769 2.623725 13.793794 2.606115 13.818819 2.459496 13.843844 2.538802 13.868869 2.544870 13.893894 2.533900 13.918919 2.557967 13.943944 2.474222 13.968969 2.585624 13.993994 2.509671 14.019019 2.552908 14.044044 2.483419 14.069069 2.408122 14.094094 2.548116 14.119119 2.501868 14.144144 2.495173 14.169169 2.515301 14.194194 2.498268 14.219219 2.462149 14.244244 2.511687 14.269269 2.625511 14.294294 2.424117 14.319319 2.420701 14.344344 2.517511 14.369369 2.569930 14.394394 2.557514 14.419419 2.664895 14.444444 2.615953 14.469469 2.556857 14.494494 2.581138 14.519520 2.561739 14.544545 2.582488 14.569570 2.573989 14.594595 2.479769 14.619620 2.381333 14.644645 2.419968 14.669670 2.513324 14.694695 2.651802 14.719720 2.533235 14.744745 2.466773 14.769770 2.498115 14.794795 2.539786 14.819820 2.504284 14.844845 2.518861 14.869870 2.443988 14.894895 2.417447 14.919920 2.493055 14.944945 2.460364 14.969970 2.586796 14.994995 2.560747 15.020020 2.549976 15.045045 2.625139 15.070070 2.523161 15.095095 2.556896 15.120120 2.606243 15.145145 2.641953 15.170170 2.497044 15.195195 2.385015 15.220220 2.488537 15.245245 2.679453 15.270270 2.554691 15.295295 2.395329 15.320320 2.499330 15.345345 2.621803 15.370370 2.471645 15.395395 2.445096 15.420420 2.460528 15.445445 2.504876 15.470470 2.568661 15.495495 2.486196 15.520521 2.421751 15.545546 2.387688 15.570571 2.595142 15.595596 2.564572 15.620621 2.476724 15.645646 2.543392 15.670671 2.482743 15.695696 2.531639 15.720721 2.528600 15.745746 2.580536 15.770771 2.406409 15.795796 2.510894 15.820821 2.552921 15.845846 2.476808 15.870871 2.490999 15.895896 2.532416 15.920921 2.485800 15.945946 2.530729 15.970971 2.460866 15.995996 2.528053 16.021021 2.492219 16.046046 2.426111 16.071071 2.453007 16.096096 2.500551 16.121121 2.564138 16.146146 2.431652 16.171171 2.489356 16.196196 2.489859 16.221221 2.487278 16.246246 2.469639 16.271271 2.486053 16.296296 2.518345 16.321321 2.458686 16.346346 2.564892 16.371371 2.593679 16.396396 2.471226 16.421421 2.540584 16.446446 2.489481 16.471471 2.375229 16.496496 2.565893 16.521522 2.600796 16.546547 2.468204 16.571572 2.653481 16.596597 2.593815 16.621622 2.588404 16.646647 2.570142 16.671672 2.527915 16.696697 2.520491 16.721722 2.523155 16.746747 2.491566 16.771772 2.440725 16.796797 2.576979 16.821822 2.482815 16.846847 2.470190 16.871872 2.316007 16.896897 2.533328 16.921922 2.536805 16.946947 2.551661 16.971972 2.571176 16.996997 2.470201 17.022022 2.548051 17.047047 2.531240 17.072072 2.405027 17.097097 2.435070 17.122122 2.435978 17.147147 2.582808 17.172172 2.578102 17.197197 2.456618 17.222222 2.451342 17.247247 2.535040 17.272272 2.527713 17.297297 2.451839 17.322322 2.480643 17.347347 2.384503 17.372372 2.456306 17.397397 2.598580 17.422422 2.569902 17.447447 2.504949 17.472472 2.529346 17.497497 2.509121 17.522523 2.474841 17.547548 2.580564 17.572573 2.442008 17.597598 2.454521 17.622623 2.448405 17.647648 2.539928 17.672673 2.403508 17.697698 2.612920 17.722723 2.494685 17.747748 2.442374 17.772773 2.429127 17.797798 2.566998 17.822823 2.541518 17.847848 2.505291 17.872873 2.538671 17.897898 2.382947 17.922923 2.404286 17.947948 2.372223 17.972973 2.482368 17.997998 2.476174 18.023023 2.472379 18.048048 2.409926 18.073073 2.437192 18.098098 2.492294 18.123123 2.531548 18.148148 2.481292 18.173173 2.464628 18.198198 2.519660 18.223223 2.460150 18.248248 2.595152 18.273273 2.482642 18.298298 2.583371 18.323323 2.518932 18.348348 2.538323 18.373373 2.554422 18.398398 2.508164 18.423423 2.563516 18.448448 2.426245 18.473473 2.659656 18.498498 2.462134 18.523524 2.513720 18.548549 2.431927 18.573574 2.434184 18.598599 2.515396 18.623624 2.424282 18.648649 2.455423 18.673674 2.469118 18.698699 2.492883 18.723724 2.497993 18.748749 2.450496 18.773774 2.529365 18.798799 2.557242 18.823824 2.535384 18.848849 2.508168 18.873874 2.437512 18.898899 2.500684 18.923924 2.506657 18.948949 2.549267 18.973974 2.422525 18.998999 2.513094 19.024024 2.517863 19.049049 2.407872 19.074074 2.561127 19.099099 2.418998 19.124124 2.427615 19.149149 2.556087 19.174174 2.464948 19.199199 2.471900 19.224224 2.442707 19.249249 2.494617 19.274274 2.441984 19.299299 2.457587 19.324324 2.611808 19.349349 2.463662 19.374374 2.539585 19.399399 2.683738 19.424424 2.510286 19.449449 2.458727 19.474474 2.480986 19.499499 2.492770 19.524525 2.654244 19.549550 2.652153 19.574575 2.458181 19.599600 2.649152 19.624625 2.448039 19.649650 2.444675 19.674675 2.514487 19.699700 2.639292 19.724725 2.707879 19.749750 2.600376 19.774775 2.400829 19.799800 2.506481 19.824825 2.469535 19.849850 2.539146 19.874875 2.599974 19.899900 2.526641 19.924925 2.525963 19.949950 2.453931 19.974975 2.507673 20.000000 2.473500 Sigima-1.1.1/sigima/data/tests/curve_formats/000077500000000000000000000000001514013333200211215ustar00rootroot00000000000000Sigima-1.1.1/sigima/data/tests/curve_formats/bandwidth.txt000066400000000000000000000165461514013333200236420ustar00rootroot00000000000000X,Y 0.0,0.01101664134214625 0.5025125628140703,-0.026256941471082148 1.0050251256281406,-0.08035902589478477 1.507537688442211,-0.16626927101206232 2.0100502512562812,-0.28645762082553217 2.5125628140703515,-0.3880761338774445 3.015075376884422,-0.4864526509656244 3.517587939698492,-0.5914457243887287 4.0201005025125625,-0.6999291883543314 4.522613065326633,-0.7915359026048515 5.025125628140703,-0.8828070206577848 5.527638190954773,-0.9601290396034307 6.030150753768844,-1.0459775066908032 6.532663316582914,-1.120860039367626 7.035175879396984,-1.18403346201963 7.537688442211055,-1.2594122790788136 8.040201005025125,-1.322722875472916 8.542713567839195,-1.3680098901969513 9.045226130653266,-1.4359176983797253 9.547738693467336,-1.487742801086236 10.050251256281406,-1.5377086567837321 10.552763819095476,-1.5859545353546063 11.055276381909547,-1.6315909424947774 11.557788944723617,-1.6817980271774897 12.060301507537687,-1.732663876046038 12.562814070351758,-1.7756192964912154 13.065326633165828,-1.8162111270853145 13.567839195979898,-1.850602340237503 14.070351758793969,-1.896344411515826 14.572864321608039,-1.9296252386308619 15.07537688442211,-1.9601993473871298 15.57788944723618,-1.9983398269373476 16.08040201005025,-2.028478508221133 16.58291457286432,-2.0679067690243147 17.08542713567839,-2.0947156185268825 17.587939698492463,-2.1305479672719665 18.09045226130653,-2.165347370583009 18.5929648241206,-2.1961978304769536 19.09547738693467,-2.218120918488033 19.597989949748744,-2.241362659199219 20.100502512562812,-2.273217980823253 20.60301507537688,-2.3006017092982205 21.105527638190953,-2.3208503787062207 21.608040201005025,-2.349537193969994 22.110552763819094,-2.3764432353548823 22.613065326633162,-2.396764638506112 23.115577889447234,-2.4251921868509507 23.618090452261306,-2.435555669614193 24.120603015075375,-2.46956966679863 24.623115577889443,-2.4834699223574264 25.125628140703515,-2.513910150864228 25.628140703517587,-2.536182167947301 26.130653266331656,-2.5562613000788668 26.633165829145725,-2.5702116468438216 27.135678391959797,-2.6105454409036257 27.63819095477387,-2.610388250708585 28.140703517587937,-2.6269547511183413 28.643216080402006,-2.6573069339543163 29.145728643216078,-2.671918449377568 29.64824120603015,-2.688031460337452 30.15075376884422,-2.698263505601117 30.653266331658287,-2.733291442797591 31.15577889447236,-2.7381889984405574 31.65829145728643,-2.760309107814427 32.1608040201005,-2.7803318519059688 32.66331658291457,-2.790845735741098 33.16582914572864,-2.8141960794575875 33.66834170854271,-2.8332942917977477 34.17085427135678,-2.8454614536686575 34.67336683417085,-2.8591850051536083 35.175879396984925,-2.8764881303981578 35.678391959798994,-2.8972442893625843 36.18090452261306,-2.901685370389972 36.68341708542713,-2.9205462782074822 37.1859296482412,-2.9348809139335006 37.688442211055275,-2.9501936570882727 38.19095477386934,-2.9676464948259946 38.69346733668341,-2.9841428246767734 39.19597989949749,-2.9922630367654297 39.698492462311556,-2.9979368524884245 40.201005025125625,-3.0183599237265537 40.70351758793969,-3.028868942803502 41.20603015075376,-3.0436313765548806 41.70854271356784,-3.0562133400504488 42.211055276381906,-3.0775286124267867 42.713567839195974,-3.0925175798809343 43.21608040201005,-3.095332738970053 43.71859296482412,-3.106985274634089 44.22110552763819,-3.123417563942578 44.723618090452256,-3.136847622772578 45.226130653266324,-3.1418364315914693 45.7286432160804,-3.1685621868836145 46.23115577889447,-3.1725061713262024 46.73366834170854,-3.185924925541499 47.23618090452261,-3.194347213869895 47.73869346733668,-3.207364828148409 48.24120603015075,-3.219352217883297 48.74371859296482,-3.2223066016302044 49.24623115577889,-3.231335666746766 49.74874371859296,-3.2517426488043397 50.25125628140703,-3.2527872107990636 50.7537688442211,-3.2799425167696037 51.256281407035175,-3.289140131096738 51.75879396984924,-3.2849312495241985 52.26130653266331,-3.312137302285429 52.76381909547738,-3.3048783370254755 53.26633165829145,-3.315429605744405 53.768844221105525,-3.333801397190627 54.27135678391959,-3.3428627725536226 54.77386934673366,-3.3653000726964937 55.27638190954774,-3.3579758881666653 55.778894472361806,-3.373885745243737 56.281407035175874,-3.3834773551365935 56.78391959798994,-3.3887762540870634 57.28643216080401,-3.399944257543347 57.78894472361809,-3.416103847554154 58.291457286432156,-3.4237948441703048 58.793969849246224,-3.428304846044853 59.2964824120603,-3.441847680521917 59.79899497487437,-3.450755536257481 60.30150753768844,-3.460052450403911 60.804020100502505,-3.471914755063477 61.306532663316574,-3.47028571907603 61.80904522613065,-3.4790116098064288 62.31155778894472,-3.494067613481827 62.81407035175879,-3.4958395146794374 63.31658291457286,-3.509468377733727 63.81909547738693,-3.514947148655284 64.321608040201,-3.5272143377730325 64.82412060301507,-3.5375919619422103 65.32663316582914,-3.5409541313560364 65.82914572864321,-3.5566695194986755 66.33165829145727,-3.558767583978799 66.83417085427135,-3.5739982895576743 67.33668341708542,-3.5844212624143093 67.83919597989949,-3.5765028343873797 68.34170854271356,-3.587377573325726 68.84422110552764,-3.603487876273602 69.3467336683417,-3.6190885558806336 69.84924623115577,-3.616476817126929 70.35175879396985,-3.619717978418709 70.85427135678391,-3.62541774861356 71.35678391959799,-3.641661246789656 71.85929648241205,-3.6420557371439175 72.36180904522612,-3.6565064654620767 72.8643216080402,-3.656693765613168 73.36683417085426,-3.6757907773839382 73.86934673366834,-3.6781103182248396 74.3718592964824,-3.6845171644473917 74.87437185929647,-3.702510317551251 75.37688442211055,-3.6883154315507434 75.87939698492461,-3.705911308147251 76.38190954773869,-3.7129159683729327 76.88442211055276,-3.7094339117145987 77.38693467336682,-3.7264346706596116 77.8894472361809,-3.7436934881004307 78.39195979899498,-3.7484682581647197 78.89447236180904,-3.7556999310104735 79.39698492462311,-3.749102501291454 79.89949748743717,-3.765140911599749 80.40201005025125,-3.7696507926942675 80.90452261306532,-3.7840132431185594 81.40703517587939,-3.7847552554285087 81.90954773869346,-3.792906782711026 82.41206030150752,-3.7994543962701948 82.9145728643216,-3.797172439899899 83.41708542713567,-3.8089674590231297 83.91959798994974,-3.8126882088912843 84.42211055276381,-3.8123305172845585 84.92462311557789,-3.8310218347570215 85.42713567839195,-3.8422558906068534 85.92964824120602,-3.842829396152168 86.4321608040201,-3.846315806912953 86.93467336683416,-3.855658113829641 87.43718592964824,-3.8605411538326533 87.9396984924623,-3.8715624000535462 88.44221105527637,-3.875367911843195 88.94472361809045,-3.8803496401714233 89.44723618090451,-3.890007109665412 89.94974874371859,-3.885372103059657 90.45226130653265,-3.899386833274659 90.95477386934672,-3.8951707078732944 91.4572864321608,-3.9180640155097115 91.95979899497486,-3.9144591307198606 92.46231155778894,-3.919866921589 92.96482412060301,-3.919138491869413 93.46733668341707,-3.9359222349689857 93.96984924623115,-3.941730627415993 94.47236180904522,-3.940244319703505 94.97487437185929,-3.949471335269994 95.47738693467336,-3.953055950659251 95.97989949748742,-3.965228519536138 96.4824120603015,-3.9685400020449255 96.98492462311557,-3.967373976187222 97.48743718592964,-3.9656929122386693 97.98994974874371,-3.985721857127695 98.49246231155777,-3.9940952821324807 98.99497487437185,-3.995988494522888 99.49748743718592,-3.998222092642212 100.0,-4.007727377870873 Sigima-1.1.1/sigima/data/tests/curve_formats/boxcar.npy000066400000000000000000001752001514013333200231340ustar00rootroot00000000000000NUMPYv{'descr': 'vp|;k肸zg߈5/cgՎ^˔/ZLVF)RMۤ#jI%Ep@<~<8Otʔ3j/`֎Y+.W 'xM"Cw :+W0&|H 6w qf`k#)e8?/ꆾ5_憾Ի;U↾AY ކhG־نMSsՆS'цGYM̆_ʐȆweGEĆ&nkqdqAZwbQ};PGˮ=534/*/顆y )R X#o$7澚؃ʔA{va֎r _nj@e|aՎ0]|Xi{TqwNPg LH^qGTkCJk ?'A$:r7*e6-0=2$6_-Q<ܦ)BY[%H!0MSzSxYM-_YeG kJqA8w};hͥ5b텾/:酾~䅾Au)kW܅a# ؅ XӅjNuυD)˅:ƅI1˔…'G׎( s dͨR|6ꛅ1w{ SƼqZkq$%*e}90y6_Cux`2W4fGR!+lěNk!rAPJxF~;AJm=5"94)/0tݛ?,ӡ)'ʧ#S#]謹2z|/Ǐ˔ [|׎Lr h㈵:_j􄾅UK넾B|焾d8;ㄾ.wބ$ ڄCqYք ҄k̈́"$vɄl*e+ń06_K%wOS:omUм5c[Mq1Za%-NPgG(FmĎ$̔߂ۂӗ؎?ׂ ҂h䈨΂z]ʂpƂGg]|zS.&Jw㴂p@6qL-O# k&i,e.2Җy7_=;CYXI֤OSYU }7[Mxavt̮gG+pmk`sAgyHc;^?~Zt5fVjRa/MiWIM)8EC@H:#<0U8& 4'/qs+ ͔''"P؎ E/zb  |Yw48q󁾂Q́ k끾x&恾an,eo⁾d2#ށZ8_ف@Q>܌ՁGDYAс=J́4PSȁj*V^ā \MbǻI hG|n0sA宁(yr;N܅Ӌ5Qɑk/ 浝Ԑ0){=Ř#򃁾Z[{{wqr9h͔xn^-jTَeK abAJ]7X-TA$gP|LG  wCk9?q:6J kW2& .,e))2t%s8_)!>DYRJFPSVЯ 1\Md|ubkhGbnā[XtA6NzD;퀾:;S逾15倾'/q܀c%؀ )ӀπB#Cˀƀ€!`l͔ɵ~Kَ2 稀创*Pt y|mSo!e w֊[􊆀2Rq?}H}>!ky5'\u\+-eq!3l9_zh;?.dEY_J֗[PSLWdVS\MNbiJChGFnAضtA="z;9m;405Y,L (|/#rv+i)+u_U# LHTB 8š.ffJ)56##$pN Bx |6Nt跛_a+ M7܉:C'O[y[pFg-hr_p~VƊhNE.:=Ë4Xx ,dƔu#QҎ>ވG*ꂰ ?|w~i q~kT~%e~'1_&~=Y~PIS~{UMa~zhaGʳ~UmA3~Ay;~8.5~/n~a)׈~#@~w~o~{f~I ]~ݒMU~rL~lD~X;~0E2~1 Y*~Z,!~ 8+~C֔~O~[f}Ag}֩s8}k} }os})\}HE}R5}!ǔ}|ӎ}ވ}R}:|}w$}cq~}ku}&e_m}!s2_d}_>Y1\}KLJSS}8VMK}t%bGlB} nA9}y;>1}25(}ב/ }\ĝ)y}#}K}|v|Cc |O|m ({{ r{gi{ba{ X{%4P{!G{O-?{9o6{xqE-{ ^QA%{J]ʪ{67i{#u| {`{Nz阬z֤ z°zGzܛȔ[zpԎzu-za삖z/N|z:whzX'qћzk:z(ez3_ z?Yuyz@KSpzԲWMGhzicG_zoAWzx{;Nz'e5EzQ/T=zQ>)4z*#&,zz#zzaz8 z3zayy my |yh"?yIU.yA:yr.FzyRy^Ly1iĵyuyŹy﹍yYywy+oyBlfyXɔ]ykEՎfUy2Ly8Dy) |;yw 3ySqs*yk!y|(eEy4_y@Yy:LSxoXMxc\dGRxHpAx5|;$x""5x/xK)_x#ȺxtԷ1x xx3 lxdžՏx\s=x_~xL vx9xmx%#dxD/J\x:ܳSxmFKxRЅBx^9x+jW1xv(xT) xvx~cxPdx/vӻ;UvgG־vS'v_ʐv&nkvZwbvOGˮv34vx v vov7澚؃vʔA{v`֎rvjv|av|XvqwNPvG^qGvJk ?vq7*e6v$6_-vBY[%v/MSvYM-vXeG vqAv};hu5u/:u@u)ua# uiNuu:u'Gu( uuQuuz Suu$%u80yux`2Wu +lěNuxFuIm=u4usݛ?,uʧ#uu1zuƏ˔ uZ|׎Luh㈵tUtB|t.wtBqYtktk*e+t6_tBYt*NSftZMϢtSfG8trAt|l~; tY5stE/wt:2)Eot#ftd ^tUtLt" RDt;tK#3t*tu !t p^t\%t3I10t5=ܙs\"IsUks`sl=sxsDs٭xsmsJsss+`sL̔sU9؎s%Ws~~s|)vswms<qdskd\sf+eSs7_6KsCYBs$wOS:sc[Mq1sMPgG(s~ZrjRrhWIrC@r0U8r&/r ͔''rO؎rryb r|rw4q7qq́ kq`n,eoqZ8_qGDYAq4PSq \MqH hG|qsAqq;NqӋ5q/ q/)qĘ#qY[{qqrq^-jqK aq7Xq@$gPqGqj9?q6q& .q(2t%q>qQJFqVЯ q{ubqbnāpNzp9;Sp'pb%ppp `p͔ɵpJَ2pߟ创pspy|mpe w֊p1Rq?p>!kyp[+-eqp9_zhpEY_pPSLWp\MNpBhGFp׶tA=pl;4p5Y,p|/#p*i)+pU#pSB p.fp6#o"poL Bovoot跛oM7܉o'O[yoDg-hon~VoEo‹4odƔu#o>ވGo>|of qn%en=Yn{UMan UmA3n6.5n`)׈nwn{fnܒMUnlDn0E2nX,!nC֔n[fmԩs8m m(\mP5mxӎmRmw$mkum s2_dmHLJSSmt%bGlBmy;>1mב/ m#ml@c ll`2WexFe4eʧ#e0zeX|׎LeUd.wdkd6_d(NSfdPfG8d|l~; dE/wd#fdUd RDdH#3dt !d\%d5=ܙcUkcl=cDclcscL̔c%Wc|)vc<qdcd+eScCYBcc[Mq1caVЯ a bnā`8;S``%``͔ɵ`ܟ创`y|m`0Rq?`X+-eq`EY_`\MN`ԶtA=`5Y,`(i)+`PB `6#_H B__M7܉_@g-h_E_dƔu#_8|_%e^{UMa^0.5^w^ؒMU^(E2^C֔^Щs8] \]xӎ]w$]s2_d]p%bGlB]ב/ ]\h`2WU4U(zUUTkT(NSfTxl~; T#fT RDTp !T5=ܙSl=ShSL̔S|)vS`+eSSc[Mq1S5SXȺRz]R-RPI֤RyHcRC@RH؎Rw4QZ8_Q@ hG|Q/ QqrQ8$gPQ& .QVЯ Q0;SPP؟创P0Rq?PEY_PжtA=P(i)+P6#OO@g-hOdƔu#O%eN0.5NВMUNpC֔N \Mw$M`%bGlBML L`SCtL߈/L?YKP)KbaKJ]ʪK@Jk:Jx{;NJ0 JA:IpYI |;IoXMHpԷ1H9xmHv(H`֎Gg5_PG˔/ZGP0GS'FoF@^qGFqAF'GE00yE4EpUD NSfD#fDp !Dl=CL̔C`+eSC5Cz]BPI֤BC@Bw4A@ hG|AqrA& .A0;S@П创@EY_@ i)+@?dƔu#? .5>`C֔>w$=<@SCt<?Y;ba; :x{;N:A:9 |;9`Է18v(8g5_P7@07o6qA6 0y5`U4#f4l=3@+eS3z]2C@2 hG|1& .1创0i)+0dƔu#/@C֔.,?Y+*A:)@Է1(f5_P'o&0y%#f$@+eS#C@"@& .!i)+ C֔?YA:f5_P0y+eS& .C֔A: 0y& .@:& .& .@;& .=& .=D:=& .>0y>C: >C֔>& .>+eS>0y>g5_P>B:>?Y>C֔>i)+ >& .!>@D@">+eS#>#f$>0y%>o&>@g5_P'>Է1(>B:)>*>?Y+>@,>C֔.>@eƔu#/>@i)+0>创0>& .1>` hG|1> D@2>z]2>+eS3>@l=3>#f4>U4>`0y5>qA6>o6>07> g5_P7>v(8>Է18>@ |;9>B:9>x{;N:>`:> ba;>?Y;>SCt<>@<>w$=>C֔>>`.5>>eƔu#?>?>@i)+@>EY_@>创@>P;S@>& .A>rrA>P hG|A>w4A>D@B>`I֤B>z]B> 5C>p+eSC>L̔C>0l=C> !D>#fD>@NSfD>UD>4E>P0yE>'GE>qAF>P^qGF>oF>S'F>`0G>˔/ZG> g5_PG>p֎G>Нv(H>09xmH>Է1H>oXMH>@ |;I>YI>A:I>@ J>x{;NJ>k:J>PJ>J]ʪK>baK>`)K>?YK> ߈/L>pSCtL> L>0L>%bGlBM>w$M>@\M>C֔N>MUN>@.5N>%eN>eƔu#O>Pg-hO>O>7#O>0i)+P>tA=P>EY_P>8Rq?P>创P>P>@;SP>VЯ Q>& .Q>H$gPQ>qrQ>/ Q>P hG|Q>[8_Q>w4Q>X؎R>D@R>yHcR>`I֤R>-R>z]R>hȺR>5S>c[Mq1S>p+eSS>|)vS>L̔S>xS> l=S>5=ܙS> !T>( RDT>#fT>l~; T>0NSfT>kT>UT>8zU>4U>>`2WU>@0yU>U>'GU>Hu)U>qAV>BY[%V>P^qGV>jV>oV>XGˮV>S'V>#V>`0W>~<8W>˔/ZW>heG|W>g5_PW>wW>p֎W>PdX>ȝv(X>xFKX> 9xmX>ІՏX>Է1X>("5X>oXMX>(eEY>0 |;Y>Xɔ]Y>YY>8iĵY>A:Y> mY>@ Z>*#&,Z>x{;NZ>HKSpZ>k:Z>a삖Z>PZ>NZ>J]ʪ[>X-?[>ba[>3[>`)[>nAw[>?Y[>hjq/ \>߈/\>Q\>pSCt\>PП\> \>x \>ב/ ]>%bGlB]>(s2_d]>w$]>ӎ]>0\]>s8]>C֔^>8E2^>MU^>w^>@.5^>{UMa^>%e^>H|_>dƔu#_>E_>Pg-h_>N7܉_>_>X B_>7#_>XB `>0i)+`>5Y,`>ܶtA=`>\MN`>EY_`>`+-eq`>8Rq?`> y|m`>创`>͔ɵ`>`>h%`>@;S`>bnā`>VЯ a>>a>& .a>p9?a>D$gPa>K aa>qra>Ș#a>/ a>x;Na>L hG|a>$4PSa>Z8_a>Ё ka>w4a>b b>T؎b>,/b>D@b>jRb>yHcb>avtb>\I֤b>42Җb>-b>S.b>z]b>b>dȺb><)b>5c>c[Mq1c>CYBc>l+eSc>@qdc>|)vc>%Wc>L̔c>sc>tc>Hc> l=c>Ukc>5=ܙc>\%d>| !d>P#3d>( RDd>Ud>#fd>E/wd>l~; d>XfG8d>0NSfd>6_d>kd>.wd>Ud>`|׎Le>8ze> ʧ#e>4e>xFe>>`2We>heH`he><0ye>e>e>e>'Ge>pNue>Du)e>5e>qAf>YM-f>BY[%f>x7*e6f>L^qGf>$|Xf>jf>ʔA{f>of>| f>TGˮf>,nkf>S'f>ػ;Uf>#f> g>\0g>4W 'g>~<8g>ब#jIg>˔/Zg>|;kg>deG|g>8@MS"g>g5_Pg>k~g>wg>g>l֎g>@)6g>Pdh>vh>ĝv(h>^9h>tFKh>H/J\h> 9xmh>_~h>̆Տh>h>xԷ1h>P)_h>("5h>HpAh>oXMh>@Yi>(eEi>Xqs*i>0 |;i>2Li>Xɔ]i>+oi>Yi>`́i>4iĵi> Ri>A:i>h"?i> mi>hi>< j>j>*#&,j>Q/T=j>x{;Nj>pcG_j>DKSpj>3_ j>k:j>:whj>a삖j>tԎj>Lj>$֤ j>Nj>#u| k>J]ʪk>|qE-k>T-?k>,4Pk>bak> rk>3k>Zk>\)k>05Ik>nAwk>VMk>?Yk>C'ek>djq/ l>8|]l>߈/l>ǔ@l>Ql>,cl>lSCtl>@zhql>PПl>8ͧl> l> )l>pHc l> l>#m>ב/ m>y;>1m>x%bGlBm>PLJSSm>(s2_dm>kum>w$m>Rm>ӎm>X5m>,\m> m>ܩs8m>[fm>C֔n>`,!n>4E2n> lDn>MUn>{fn>wn>h)׈n><.5n>UmA3n>{UMan>=Yn>%en>l qn>D|o>>ވGo>dƔu#o>ȋ4o>Eo>t~Vo>Lg-ho>$'O[yo>M7܉o>t跛o>o>|o>T Bo>(po>7#o>.fp>VB p>U#p>.i)+p>|/#p>5Y,p>p;4p>ڶtA=p>FhGFp>\MNp>PSLWp>EY_p>9_zhp>^+-eqp>>!kyp>4Rq?p>e w֊p> y|mp>vp>创p>Nَ2p>͔ɵp>$`p>p>p>d%p>'p><;Sp>Nzp>bnāp>ubq>VЯ q>TJFq>>q>,2t%q>& .q>6q>l9?q>Gq>D$gPq>7Xq>K aq>^-jq>qrq>\[{q>Ș#q>4)q>/ q>Ӌ5q>t;Nq>sAq>L hG|q> \Mq> 4PSq>GDYAq>Z8_q>dn,eoq>Ё kq><qq>w4q>|r>|b r>r>T؎r> ͔''r>(/r>0U8r>D@r>lWIr>jRr>@~Zr>yHcr>mkr>avtr>U }r>\I֤r>=;r>02Җr>&ir>-r>t@r>S.r>Hgr>z]r> r>r>"r>`Ⱥr>ۮ#Pr>8)r>/~s>5s>|);s>PPgG(s>c[Mq1s>(wOS:s>CYBs>7_6Ks>h+eSs>kd\s>@qds>wms>|)vs>~s>%Ws>X9؎s>L̔s>0`s>ss>Js>ps>ܭxs>Hs>xs> l=s>`s>Uks>`"Is>5=ܙs>8I10t>\%t> p^t>x !t>*t>P#3t>;t>$ RDt>Lt>Ut>h ^t>#ft><2)Eot>E/wt>Y5st>l~; t>rAt>XfG8t>ZMϢt>,NSft>BYt>6_t>p*e+t>kt>DqYt>.wt>B|t>Ut>h㈵t>\|׎Lu>ȏ˔ u>4zu>u> ʧ#u>xݛ?,u>4u>Lm=u>xFu>$+lěNu>>`2Wu>QT_u>deH`hu>x<0yu>$%u>u>| Su>u>Tu>u>, u>'Gu>;u>lNuu>a# u>Du)u>/:u>5u>};hu>qAv>\eG v>YM-v>4MSv>BY[%v>$6_-v>t7*e6v>Jk ?v>L^qGv>qwNPv> |Xv>|av>jv>d֎rv>ʔA{v><澚؃v>ov> v>| v>34v>TGˮv>Zwbv>(nkv>_ʐv>S'v>lG־v>ػ;Uv>@/v>#v>v> w>H w>X0w>Cww>0W 'w>j/w>~<8w>t@w>ܤ#jIw>H)Rw>˔/Zw> ߈5/cw>|;kw>qA]tw>`eG|w>,YMw>8@MS"w>SAYw>g5_Pw>xz)ew>k~w>Pqw>ww>(|Cw>w>qw>h֎w>ʔw>@)6w>Pdx>cx>vx>X) x>ĝv(x>0jW1x>^9x>RЅBx>pFKx>:ܳSx>H/J\x>%#dx>9xmx>L vx>_~x>`s=x>̆Տx>8 lx>x> x>xԷ1x>#Ⱥx>P)_x>/x>$"5x>5|;$x>HpAx>h\dGRx>oXMx>@Yy>4_y>(eEy>k!y>Xqs*y>w 3y>, |;y>8Dy>2Ly>pEՎfUy>Xɔ]y>Dlfy>+oy>wy>Yy>y>\́y>uy>4iĵy>^Ly> Ry>t.Fzy>A:y>LU.y>h"?y>$|y> my>y>dy>3z>< z>az>z>|#z>*#&,z>T>)4z>Q/T=z>,e5Ez>x{;Nz>oAWz>lcG_z>زWMGhz>DKSpz>?Yuyz>3_ z>(ez>k:z>\'qћz>:whz>4N|z>a삖z>u-z>tԎz>Ȕ[z>Lz>°z> ֤ z>阬z>Nz>d{>#u| {>87i{>J]ʪ{>^QA%{>|qE-{>9o6{>T-?{>!G{>(4P{> X{>ba{>li{> r{>@ ({{>3{>GV{>Z{>m#{>X){>Ĕ/{>05I{>z;{>nAw{>tbG{>VM{>H KS<{>?Y{> 03_j{>C'e{>Vk|>`jq/ |>}w|>8|]|>&|>߈/|>xӎ"8|>ǔ@|>PPI|>Q|>(~Z|>,c|>?k|>hSCt|>ft||>@zhq|>\|>PП|>D6|>8ͧ|>X,d|> |>0|> )|>)|>pO|>Hc |>v|>|>K}>#}>`ĝ)y}>ב/ }>45(}>y;>1}> nA9}>x%bGlB}>8VMK}>PLJSS}>_>Y1\}>$s2_d}>&e_m}>ku}>hq~}>w$}><|}>R}>ވ}>ӎ}>!ǔ}>T5}>HE}>,\}>os}> }>p}>ةs8}>Dg}>[f}>O~>C֔~> 8+~>\,!~>1 Y*~>4E2~>X;~> lD~>tL~>MU~>L ]~>{f~>$o~>w~>#@~>d)׈~>/n~><.5~>Ay;~>UmA3~>|haGʳ~>{UMa~>TIS~>=Y~>,1_&~>%e~>kT~>l q~>w~>D|>*ꂰ >>ވG>QҎ>dƔu#>\x ,>ȋ4>0:=>E>ƊhN>t~V>r_>Lg-h>[p> 'O[y>:C>M7܉>da+ >t跛>8N>>|>|>>P B>>(p>#>7#>lJ)5>.f>8š>VB > LH>U#>v_>,i)+>rv>|/#>N (>5Y,>0>n;4>$z;9>ڶtA=>nA>FhGF>biJ>\MN>fVS>PSLW>J֗[>EY_><?.d>9_zh>!3l>^+-eq>5'\u>>!ky>~H}>4Rq?>[􊆀>e w֊>To!> y|m>>v>,P>创> 稀>Lَ2>~>͔ɵ>n>$`>€>ƀ>D#Cˀ>π> )Ӏ>d%؀>/q܀>'>15><;S>D;>Nz>\XtA6>bnā>khG>~ub>4\Md>VЯ >PS>TJF> DY>>>t8_)!>*2t%>,e)>& .>L kW2>6>q:>l9?>" wC>G>|L>D$gP>-T>7X>dAJ]>K a>Tَe>^-j>:h͔xn>qr>{w>\[{>>Ƙ#>|=>2)>赝Ԑ>/ >Tɑk>Ӌ5>܅>t;N>*y>sA宁>n0>J hG|>bǻ> \M>l*V^ā>"4PSȁ>=J́>GDYAс>BQ>܌Ձ>Z8_ف>d2#ށ>bn,eo>x&>΁ k>Q>:q>>w4>Z>|> >|b >2>> E>R؎>"> ͔''>rs+>(/>& 4>0U8>J:#<>D@>M)8E>jWI> a/M>jR>t5fV>B~Z>;^>yHc>bsAg>mk>ήgG+p>avt>8[Mx>U }>OSY>ZI֤>CY>=;>z7_>02Җ>,e>&i>R# k>->6qL>r@>(Jw㴂>S.>]|z>Hg>pƂ>z]ʂ>j䈨΂> ҂>ԗ؎?ׂ>ۂ>@̔߂>">m>bȺ>Ҵ>ۮ#P>娦>8)>2>/~>X >5>`>z);>03y>FmĎ$>PPgG(>Za%->c[Mq1>pmUм5>&wOS:>܀IS>>CYB>H=F>7_6K>1O>h+eS>%X>kd\>`>@qd> Fi>wm>`q>|)v>tz>~>6 >%W>/ >X9؎>C:>L̔>xVќ>.`>ih>s>P}#>J>)>pẃ>&/->ܭxÃ>5ǃ>F̃>~;[Ѓ>xԃ>hrA؃>l=݃>fG>`>>[M >Uk>OS>`"I>,CYN>5=ܙ>?7_>6I10>R+e| >\%>Vfk> p^>yq>x !>.wA&>*>|.>N#3>o7>;>p@>$ RD>׎H>L>F˔4Q>U>Y>f ^>bb>#f>(j>>2)Eo>;s>E/w>^O'|>Y5s>b>~l~; >4vxU>rA>l아>VfG8> `ʃ>ZMϢ>vT>,NSf>Hֱ>BY>N6_>0>n*e+ń>$$vɄ>k̈́> ҄>DqYք>$ ڄ>.wބ>f8;>B|>K>U><_j>h㈵>r >^|׎L>>ȏ˔ >~/>4z>ꬹ>>T#]> ʧ#>ӡ)'>vݛ?,>,/0>4>5"9>Lm=>~;A>xF>n!rAPJ>"+lěN>4fGR>>`2W>DHZM~[>QT_>[NSd>deH`h>oBYl>x

6_Cu><0y>*e}>$%>\kq>>ȼq>| S>2w>ꛅ>|6>T> ͨ>>t d>* >׎>'G>L1˔…>;ƅ>D)˅>lNuυ>"XӅ>a# ؅>kW܅>Bu)>~>/:>d>5>Υ>};h>:w>qA>kJ>\eG >_>YM->|Sx>2MS>H!>BY[%>R<ܦ)>$6_->-0=2>t7*e6>*A$:>Jk ?>TkC>J^qG>h L>qwNP>l{T> |X>֎0]>|a>Be>j> _n>b֎r>v>ʔA{>>:澚؃>$>o>Z#> >)R>| >0*/顆>34>=5>RGˮ>Q};>Zwb>rdqA>(nk>weGEĆ>_ʐȆ>JYM̆>S'ц>MSsՆ>jG־ن> AY ކ>ֻ;U>5_>@/>)e8>#>bk>>qf> >8w>H >&|>Z0>:+>Cw>zM">0W '>`֎Y+>j/>Ptʔ3>~<8><>r@>(E>ܤ#jI>M>H)R>LV>˔/Z>jՎ^>߈5/c>肸zg>|;k>@vp>qA]t>kĨx>`eG|>#_?>,YM>6S։>8@MS">IGm>SAY>X];>g5_P>p/⛣>zz)e秇>.#2>k~>ɴ>Pq> `>w>pŇ>&|Cʇ>·>҇>H&ׇ>qۇ> ߇>h֎> T>ʔ>>>)6>2><>`F#>Pd>Y) >c>6m/G>v>5>X) > |;u$>v(>xpA ->.jW1>dG5>^9>NXM:>>RЅB>LSF>pFK>&@YhO>:ܳS>5_W>F/J\>)e`>%#d>h/k-i>9xm>Bqq>L v>>Vw[z>_~>i|>^s=>}킉>ʆՏ> >6 l>Վ>>VɔN> >ʽ孈>xԷ1>,ޱ|>#Ⱥ>>N)_È>Lj>/ˈ>nAЈ>$"5Ԉ>+؈>5|;$݈>F?vo>HpA>Rj>f\dGR>f^ʝ>oXM>yR4>F>@Y>^:b >4_>ȳ.>~(eE>4">k!>'&>Vqs*> .>w 3>vU7>, |;>?>8D>L(H>2L>; Q>nEՎfU>$OY>Xɔ]>bIb>Dlf>uj>+o>f#ws>w>М)|>Y>򹍲>Ç5<>\́>{;ӕ>u>~oAj>4iĵ>cG>^L>TXM> R㳉>$LS/>v.Fz>*8@Y>A:ʼn>K4_]ɉ>LU.͉>_(eщ>h"?։>lrkډ>"|މ>؅q"> m>Dw>>|P>d>>3>~>: >Ԏ>a>\Ȕ>> C>|#>2!'>*#&,>4q0>T>)4>H9>Q/T=>t[A>*e5E>n6J>x{;N>JuR>oAW>id[>lcG_>"]c>ֲWMGh>QВl>BKSp>E)u>?Yuy>d9}>3_ >-W>(e>: ">k:>>Z'qћ>1 >:wh>|D>2N|>WJ>a삖>Rk⹊>u->~ yŠ>tԎƊ>(ˊ>ޛȔ[ϊ>ӊ>J׊>>܊>°>j̪#> ֤ >ߞ)l>阬>B/>N>5>b>{;1>#u| >-oA>87i>@cG_>J]ʪ>ZTWM >^QA%>gKS)>zqE->0{?Y$2>9o6>3_:>R-?>'eRC>!G>rkK>(4P>qT> X>Hw]>ba>|e>ji> En> r>v>@ ({>)Ԏs>3>b=Ȕ >GV>P>Z픋>8d8>m#>wϡ>X)>f>Ĕ/>z>05I>䱀>z;࿋>Pt+ċ>nAwȋ>h̋>rbGы>&\YՋ>VMً>P݋>H KS<>Eև>?Y>h&9>03_j>9->C'e>@M!L>Vk>`>`jq/ >t z>}w>>6|]>">&>X@+>߈/> 3>xӎ"8>.n<>ǔ@>E>PPI>M>Q>p#3V>&~Z>")^>,c>F6/ag>?k>I5o>hSCt>]z;x>ft|>pnA&>>zhq>bG>\>`VMT>PП>ʪJS뚌>D6>6>Y>8ͧ>2_>V,d> &e> >xkG>.> qŌ> )ʌ>NwuΌ>)Ҍ>2| ׌>p$F낣ߌ>O>Y߈:>Fc >lӎ>v>fǔh>>ғ>K>> >#>->^ĝ)y>Η>ב/ >ዲ[$>45(>,>y;>1>Vt5> nA9>h >>v%bGlB>,/\ʷF>8VMK>BPNO>NLJSS>VDW>_>Y1\>ni8|`>$s2_d>|,i>&e_m>D q>ku>Az>fq~>؂>w$>o><|>>R>^>ވ頍> 5>~ӎ>4̭>!ǔ>+c>T5> ?>HEÍ>vR#Ǎ>,\ˍ>e)(Ѝ>osԍ>Ly/؍> ݍ>5V>n>"y;>ةs8>mA>Dg>aG>[f>dUM>O>ISI >C֔><>Y> 8+>2_w>\,!>(&e&>1 Y*>~;k.>2E2>Nq<7>X;>Tbw?> lD>u|jH>tL>*Q>MU>ވY>L ]>Ҏ/b>{f>lƔj>"o>ֺ]s>w>Bꮠ{>#@>>d)׈>">/n>$>:.5>7P>Ay;>\Ks禎>UmA3>^g~>|haGʳ>2r[>{UMa>OЬ>RISĎ>CCɎ>=Y͎>t7ю>*1_&֎>޿+qڎ>%eގ>J>kT>>l q> 6>w> >B|> d>*ꂰ >b4 >>ވG>G >QҎ>:[*>dƔu#>n'>Zx ,>X0>Ƌ4>|#8>0:=>樜)A>E>R/J>ƊhN>τ5R>r~V>(x;K[>r_>lAc>Jg-h> aGyl>[p>jUMu> 'O[y>0IS}>:C>@D=Y>>M7܉>W1_Վ>ba+ >k%el>t跛>~k>8N> q>嬏>Zw1>|>ĸ|ȹ>z>0_>Ə>݈ʏ>P BϏ>юӏ>׏>rƔ$܏>(p>>#>H-R>6#>@>jJ)5>T>.f>3Eً>8š>{=?\>VB >0G9" > LH>P3bn>U#>Z->v_>Qd'h>,i)+>n!P>rv>wn!>|/#>r%>M (>(t3*>5Y,>ޔ ~.>0>z2>n;4>I7>$z;9>a;>ٶtA=>?>nA>jC>EhGF>DH>biJ>ߋL>\MN>P>fVS>@ӑ&U>PSLW>rY>J֗[>Ǘ]>EY_>a  b><?.d>Tf>9_zh> j>!3l>&n>]+-eq>80&7s>5'\u>9w>>!ky>C,{>~H}>YM>4Rq?>W2e>[􊆐>`>e w֊>zj8>Uo!>/tG> y|m>}z>>>tޙ>u>PnD*>+P>hu>创>bJ> 稐>q\ >Lَ2>'VPX>~>Pӣ>͔ɵ>JV﷐>m>HD:>#`>>\>>8Đ>Ɛ>i2bɐ>D#Cː>,h͐>ϐ>'hѐ> )Ӑ>!Ր>e%ؐ>?nKڐ>/qܐ>"ސ>'>,t>15>`6 ->;;S>@zy>D;>I>Nz>S>\XtA6>7]\>bnā>f녧>khG>p>}ub>Xzߋ>>3\Md>  >VЯ >Íӑ >PS>y!>TJF>.Ǘl> DY>>>>>u8_)!>O O#>*2t%>ȯ'>,e)>ѩ&+>& .>pۣ10>K kW2>&,}4>6>8>q:>2=>l9?>G_A>" wC> 8E>G>I>|L>hz>BN>C$gP>)tR>-T>2nDV>7X>dAJ]>>FbJp_>K a>O\ͻc>Tَe>YVPh>^-j>_cPRl>:h͔xn>mJVp>qr>vDt>{w>>\5y>[[{>68߀}>>2b́>Ƙ#>,>|=>W&hc>2)> 뮎>絝Ԑ>ºn>/ >xE>Sɑk>-t>Ӌ5>ܟ>܅>z(>t;N>Ns>)y>>sA宑> >n0>oV>J hG|>%>bǻ>ߋ> \M>%9‘>k*V^đ>F/ӑƑ>!4PSȑ>8ʑ>=J̑>BǗϑ>GDYAё>gLgӑ>BQ>܌Ց>Vב>Z8_ّ>_ ۑ>d2#ޑ>iI>cn,eo>=s&>x&>|>΁ k>,,>Q>^w>9q>2>>ʣ>w4>8Z>Z>5>|>y>> >s< >{b >VmD>1> g>>aJ> E>w[j>R؎>,UP >">P%> ͔''>JVM)>ss+>MD٘->(/>">\1>& 4>+8/6>0U8>n52b{:>I:#<>$?,>>C@>H&hC>M)8E>R ]G>jWI>E\nK> a/M>eO>jR>ot@T>t5fV>fyX>A~Z>z\>;^>ь"a>yHc>ne>bsAg><i>mk>n>ͮgG+p>Qr>avt>]ދv>8[Mx>z>U }>ґ3>OSY>~>YI֤>4Ɨʇ>CY>>=;>a>z7_>U >02Җ> >,e>&D>&i>v>Q# k>+(,ۥ>->1&>6qL>;2r>r@>LE>'Jw㴒>O8 >S.>XT>]|z>mby>>Hg>#lsÒ>pƒ>umD7Ȓ>z]ʒ>gǂ̒>i䈨Β>DaJВ> Ғ>[Ւ>ԗ؎?ג>UPeْ>ے>eOӰݒ>@̔ߒ>IV>">йCG>m>=\>aȺ>;7>Ҵ>1b*>ۮ#P>+u>娦>\%h>7)> >2>nX>/~>}>X >3t >5>:>`>$z>y);>T.>/3y> 8>Ai">FmĎ$>uKꅴ&>PPgG(>*U+>Za%->^ދK/>c[Mq1>h3>qmUм5>Krґ7>&wOS:>|.<>܀IS>>Ɨy@>CYB>lD>G=F>"I>7_6K>آ \M>1O>Q>h+eS>C&U>%X>>Z>kd\>ɜ,^>`>dӖb>?qd>ݐ2!g> Fi>抵lk>wm>8o>`q>:~t>|)v>y>Ox>tz> s|>~>[mD怓>6 >!g1>%W>*aJ}>/ >|4[ȍ>W9؎>2>UP> C:>GO_>L̔>QIV>xVќ>S[C>.`> e=\B>ih>n7ߍ>s>tx1b٫>O}#>)+$>J>ߋ%hp>)>뻸>pẓ>Jn>%/->R>ۭxÓ> tœ>5Ǔ>kɓ>F̓>!z5Γ>~;[Г>ғ>xԓ>֓>grAؓ>Bۓ>l=ݓ>cߓ>fG>>`>cދ>>[M > F>Uk>ґ>OS>>_"I>9'Ɨ(>,CYN>0t>5=ܙ>:>?7_>ZD >5I10>NV >R+e| >W&>\%>{a>Vfk>1k,9> p^>t>yq>~2>w !>R$>-wA&>8g(>*>~,>|.>rx>0>N#3>(rI5>o7>޸lD9>;>f=>n@>J`J,B>$ RD>ZwF>׎H>TPJ>L>jNO>F˔4Q> HVZS>U>B٥W>Y>=\[>f ^>@7<`>bb>1bd>#f>#+h>(j>b-%hm><2)Eo>7jq>;s>@nu>E/w>Jz>^O'|>8T tM~>Y5s>]>b>gz䆔>~l~; >Zq/>4vxU>{{>rA>ĄǓ>l암>z>VfG8>0^> `ʃ>݋>ZMϢ>>vT>Pё@>,NSf>>Hֱ>ŗױ>BY>rҿ#>L(ܹn>6_> >0>ﭣÔ>n*e+Ŕ>H&Qǔ>$$vɔ>˔>k͔> ,ϔ> Ҕ>j3Ԕ>DqY֔> 2ؔ>$ ڔ>)ܔ>.wޔ>38>f8;>@=~a>B|>Fx>>K>Pr>U>`ZlDD><_j>dfǏ>h㈵>m`J>r >wZ&>\|׎L>8TPr>>Nӽ>ȏ˔ >HV >~/>XBT>4z><\>謹>ı6>>z0b7>T#]>.*!> ʧ#>$h%>ӡ)'>*>vݛ?,>Pne.>*/0>2>4> t6>5"9>pG;>Lm=>& z?>~;A>C>xF>*H>l!rAPJ>H&vL>"+lěN>/P>4fGR>9 U>>`2W>hC݋XY>DHZM~[>M]>QT_>Vёa>[NSd>`;f>deH`h>>jŗj>oBYl>sn>x

}s>6_Cu>` iw>:0y>{>*e}>̚&>$%>K>\kq>6,>>췕⌕>Ƽq>2.>| S>Xˉy>2w>Ճ8ř>ꛕ>}>|6>xw>\>T>.q>ͨ>kD>>f>>t d>N`J>* >Zշ>׎>"TP!>ffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c333333c333333c333333c333333c333333c333333c333333c333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c333333c333333c333333c333333c333333c333333c333333c333333c,j33jvẗI_f+-cfF%>mfffffff%>mf+-cfFI_f̈tv,j33j333333c333333c333333c333333c333333c333333c333333c333333c333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333cƩR(guq{/٘y!VG#"")TD> bffffffG333333ص/3{ݦ)R13 9.3)h-݅3333338ħzޝu<1?G?צh ?\*?=ܫS?@P? e?]d?67Kn?y1@OZ@ЯR2@U]@C @^.;1 @j<"a @ @+\M- @wOy~ @}O @Nl @D0 @m2 @ʅʿ @ 3#r @էق @ҩ( @ @̭w @a"6 @0 @8N}{ @E 1 @F @f! @CQ @4g}1 @vV @ڧ1 @ڡ @{߫ @eu @^.;1 @:  @@F˰ @ @0 @x @J @<ˈ @:X0 @s @ȳ&q @f7 @^.;1 @ h @ ڱ @o{ @33333 @! @\g. @Zr7 @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @!> @sG @’T @4c @THq @~ @Ç @z3 @>ot{ @D' @ ~ @.4w @0Ko @S&mti @B~d @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @B~d @S&mti @0Ko @.4w @ ~ @D' @>ot{ @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @>ot{ @D' @ ~ @.4w @0Ko @S&mti @B~d @4c @B~d @S&mti @0Ko @.4w @ ~ @D' @>ot{ @z3 @>ot{ @D' @ ~ @.4w @0Ko @S&mti @B~d @4c @B~d @S&mti @0Ko @.4w @ ~ @D' @>ot{ @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @>ot{ @D' @ ~ @.4w @0Ko @S&mti @B~d @4c @4c @4c @4c @4c @4c @4c @4c @4c @B~d @S&mti @0Ko @.4w @ ~ @D' @>ot{ @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @>ot{ @D' @ ~ @.4w @0Ko @S&mti @B~d @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @B~d @S&mti @0Ko @.4w @ ~ @D' @>ot{ @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @>ot{ @D' @ ~ @.4w @0Ko @S&mti @B~d @4c @B~d @S&mti @0Ko @.4w @ ~ @D' @>ot{ @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @>ot{ @D' @ ~ @.4w @0Ko @S&mti @B~d @4c @B~d @S&mti @0Ko @.4w @ ~ @D' @>ot{ @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @>ot{ @D' @ ~ @.4w @0Ko @S&mti @B~d @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @B~d @S&mti @0Ko @.4w @ ~ @D' @>ot{ @z3 @>ot{ @D' @ ~ @.4w @0Ko @S&mti @B~d @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @:|a @0\ @SFV @a4O @w}G @UuA @E&< @ 8*5; @E&< @UuA @w}G @a4O @SFV @0\ @:|a @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @:|a @0\ @SFV @a4O @w}G @UuA @E&< @ 8*5; @E&< @UuA @w}G @a4O @SFV @0\ @:|a @4c @:|a @0\ @SFV @a4O @w}G @UuA @E&< @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @E&< @UuA @w}G @a4O @SFV @0\ @:|a @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @:|a @0\ @SFV @a4O @w}G @UuA @E&< @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @E&< @UuA @w}G @a4O @SFV @0\ @:|a @4c @:|a @0\ @SFV @a4O @w}G @UuA @E&< @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @E&< @UuA @w}G @a4O @SFV @0\ @:|a @4c @:|a @0\ @SFV @a4O @w}G @UuA @E&< @ 8*5; @E&< @UuA @w}G @a4O @SFV @0\ @:|a @4c @V_ @V @80CI @m2; @6Ӂ, @R3 @G @0 @P @1AHq @1  @]P2' @. @_v4 @O|9 @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @E&< @UuA @w}G @a4O @SFV @0\ @:|a @4c @:|a @0\ @SFV @a4O @w}G @UuA @E&< @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @O|9 @_v4 @. @]P2' @1  @1AHq @P @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @P @1AHq @1  @]P2' @. @_v4 @O|9 @ 8*5; @O|9 @_v4 @. @]P2' @1  @1AHq @P @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @P @1AHq @1  @]P2' @. @_v4 @O|9 @ 8*5; @O|9 @_v4 @. @]P2' @1  @1AHq @P @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @x @J @<ˈ @:X0 @s @ȳ&q @f7 @^.;1 @f7 @ȳ&q @s @:X0 @<ˈ @J @x @0 @x @J @<ˈ @:X0 @s @ȳ&q @f7 @^.;1 @^.;1 @^.;1 @^.;1 @^.;1 @^.;1 @^.;1 @^.;1 @^.;1 @f7 @ȳ&q @s @:X0 @<ˈ @J @x @0 @0 @0 @0 @0 @0 @0 @0 @0 @x @J @<ˈ @:X0 @s @ȳ&q @f7 @^.;1 @^.;1 @^.;1 @^.;1 @^.;1 @^.;1 @^.;1 @^.;1 @^.;1 @f7 @ȳ&q @s @:X0 @<ˈ @J @x @0 @x @J @<ˈ @:X0 @s @ȳ&q @f7 @^.;1 @^.;1 @^.;1 @^.;1 @^.;1 @^.;1 @^.;1 @^.;1 @^.;1 @!]@y @̓Q @r @ŏ1 @ @7uyq @J, @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @L @52 @~,R @ Y2 @`- @%2 @r @33333s @BM>g @/"[ @ >(N @x9A @M2 @\$H" @>Q#> @ 8*5@zAU@Cͩ@v@0JTz@t O@n倸!@Tg@ 8*5@v,_@2~;@ 4G@u1r@fAr|E@ q4@Ld_@ 8*5;@\@zG@)ODu)@~@J\h@O6@}zDŽ@ڧ1C@\(@,~@ 3@_õ@e)Q@:oT?"U?}iF?.}? ({?d\?ˆ5E!?>cX?G$?F*v?JOc? l4D?,3?VJ?7Gc?;WF?d\̊?ط?g?:J[?eh ?D?I? Y? Ww?lG'?F?bQ?4?1DN_ϗ?*̵G?&!S?dUk?a???skQ? Fg?B$f?ޠk?7/?2}?|RW??<[g??7?E?苔?U-(?N}{2Z?풼?333333?y/?w[3C?5a3?C+?O3I?[K3#?ؼh?333333?ЫK]j?xefn?aUf)?#ͻ?fmfffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c333333c333333c333333c333333c333333c333333c333333c333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffZ_fЕsnf6:bfԑ5̍> OPK̬rt333333cd9gf7?{Ll?xefn{?1433?uZ,3?]^NC3ӎ???]~8,3Ï?EP&3?#1ifs?333333c+$2|!_f& bfffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c333333c333333c333333c333333c333333c333333c333333c333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff bf!_f&+$2|333333c#1ifs?EP&3?]~8,3Ï??Xq?,3?o$3?ffffff~?Vlo?5[133G?refX333333c333333c333333c333333c333333c333333c333333c333333c333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffff%>mf+-cfFI_f̈tv,j33j333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffSigima-1.1.1/sigima/data/tests/curve_formats/boxcar.sig000066400000000000000000000772701514013333200231200ustar00rootroot00000000000000 CRENEAU1?@@& .= g5_P@sW ffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c333333c333333c333333c333333c333333c333333c333333c333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c333333c333333c333333c333333c333333c333333c333333c333333c,j33jvẗI_f+-cfF%>mfffffff%>mf+-cfFI_f̈tv,j33j333333c333333c333333c333333c333333c333333c333333c333333c333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333cƩR(guq{/٘y!VG#"")TD> bffffffG333333ص/3{ݦ)R13 9.3)h-݅3333338ħzޝu<1?G?צh ?\*?=ܫS?@P? e?]d?67Kn?y1@OZ@ЯR2@U]@C @^.;1 @j<"a @ @+\M- @wOy~ @}O @Nl @D0 @m2 @ʅʿ @ 3#r @էق @ҩ( @ @̭w @a"6 @0 @8N}{ @E 1 @F @f! @CQ @4g}1 @vV @ڧ1 @ڡ @{߫ @eu @^.;1 @:  @@F˰ @ @0 @x @J @<ˈ @:X0 @s @ȳ&q @f7 @^.;1 @ h @ ڱ @o{ @33333 @! @\g. @Zr7 @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @!> @sG @’T @4c @THq @~ @Ç @z3 @>ot{ @D' @ ~ @.4w @0Ko @S&mti @B~d @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @B~d @S&mti @0Ko @.4w @ ~ @D' @>ot{ @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @>ot{ @D' @ ~ @.4w @0Ko @S&mti @B~d @4c @B~d @S&mti @0Ko @.4w @ ~ @D' @>ot{ @z3 @>ot{ @D' @ ~ @.4w @0Ko @S&mti @B~d @4c @B~d @S&mti @0Ko @.4w @ ~ @D' @>ot{ @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @>ot{ @D' @ ~ @.4w @0Ko @S&mti @B~d @4c @4c @4c @4c @4c @4c @4c @4c @4c @B~d @S&mti @0Ko @.4w @ ~ @D' @>ot{ @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @>ot{ @D' @ ~ @.4w @0Ko @S&mti @B~d @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @B~d @S&mti @0Ko @.4w @ ~ @D' @>ot{ @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @>ot{ @D' @ ~ @.4w @0Ko @S&mti @B~d @4c @B~d @S&mti @0Ko @.4w @ ~ @D' @>ot{ @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @>ot{ @D' @ ~ @.4w @0Ko @S&mti @B~d @4c @B~d @S&mti @0Ko @.4w @ ~ @D' @>ot{ @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @z3 @>ot{ @D' @ ~ @.4w @0Ko @S&mti @B~d @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @B~d @S&mti @0Ko @.4w @ ~ @D' @>ot{ @z3 @>ot{ @D' @ ~ @.4w @0Ko @S&mti @B~d @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @:|a @0\ @SFV @a4O @w}G @UuA @E&< @ 8*5; @E&< @UuA @w}G @a4O @SFV @0\ @:|a @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @:|a @0\ @SFV @a4O @w}G @UuA @E&< @ 8*5; @E&< @UuA @w}G @a4O @SFV @0\ @:|a @4c @:|a @0\ @SFV @a4O @w}G @UuA @E&< @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @E&< @UuA @w}G @a4O @SFV @0\ @:|a @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @4c @:|a @0\ @SFV @a4O @w}G @UuA @E&< @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @E&< @UuA @w}G @a4O @SFV @0\ @:|a @4c @:|a @0\ @SFV @a4O @w}G @UuA @E&< @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @E&< @UuA @w}G @a4O @SFV @0\ @:|a @4c @:|a @0\ @SFV @a4O @w}G @UuA @E&< @ 8*5; @E&< @UuA @w}G @a4O @SFV @0\ @:|a @4c @V_ @V @80CI @m2; @6Ӂ, @R3 @G @0 @P @1AHq @1  @]P2' @. @_v4 @O|9 @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @E&< @UuA @w}G @a4O @SFV @0\ @:|a @4c @:|a @0\ @SFV @a4O @w}G @UuA @E&< @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @ 8*5; @O|9 @_v4 @. @]P2' @1  @1AHq @P @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @P @1AHq @1  @]P2' @. @_v4 @O|9 @ 8*5; @O|9 @_v4 @. @]P2' @1  @1AHq @P @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @P @1AHq @1  @]P2' @. @_v4 @O|9 @ 8*5; @O|9 @_v4 @. @]P2' @1  @1AHq @P @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @0 @x @J @<ˈ @:X0 @s @ȳ&q @f7 @^.;1 @f7 @ȳ&q @s @:X0 @<ˈ @J @x @0 @x @J @<ˈ @:X0 @s @ȳ&q @f7 @^.;1 @^.;1 @^.;1 @^.;1 @^.;1 @^.;1 @^.;1 @^.;1 @^.;1 @f7 @ȳ&q @s @:X0 @<ˈ @J @x @0 @0 @0 @0 @0 @0 @0 @0 @0 @x @J @<ˈ @:X0 @s @ȳ&q @f7 @^.;1 @^.;1 @^.;1 @^.;1 @^.;1 @^.;1 @^.;1 @^.;1 @^.;1 @f7 @ȳ&q @s @:X0 @<ˈ @J @x @0 @x @J @<ˈ @:X0 @s @ȳ&q @f7 @^.;1 @^.;1 @^.;1 @^.;1 @^.;1 @^.;1 @^.;1 @^.;1 @^.;1 @!]@y @̓Q @r @ŏ1 @ @7uyq @J, @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @ڧ1 @L @52 @~,R @ Y2 @`- @%2 @r @33333s @BM>g @/"[ @ >(N @x9A @M2 @\$H" @>Q#> @ 8*5@zAU@Cͩ@v@0JTz@t O@n倸!@Tg@ 8*5@v,_@2~;@ 4G@u1r@fAr|E@ q4@Ld_@ 8*5;@\@zG@)ODu)@~@J\h@O6@}zDŽ@ڧ1C@\(@,~@ 3@_õ@e)Q@:oT?"U?}iF?.}? ({?d\?ˆ5E!?>cX?G$?F*v?JOc? l4D?,3?VJ?7Gc?;WF?d\̊?ط?g?:J[?eh ?D?I? Y? Ww?lG'?F?bQ?4?1DN_ϗ?*̵G?&!S?dUk?a???skQ? Fg?B$f?ޠk?7/?2}?|RW??<[g??7?E?苔?U-(?N}{2Z?풼?333333?y/?w[3C?5a3?C+?O3I?[K3#?ؼh?333333?ЫK]j?xefn?aUf)?#ͻ?fmfffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c333333c333333c333333c333333c333333c333333c333333c333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffZ_fЕsnf6:bfԑ5̍> OPK̬rt333333cd9gf7?{Ll?xefn{?1433?uZ,3?]^NC3ӎ???]~8,3Ï?EP&3?#1ifs?333333c+$2|!_f& bfffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c333333c333333c333333c333333c333333c333333c333333c333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff bf!_f&+$2|333333c#1ifs?EP&3?]~8,3Ï??Xq?,3?o$3?ffffff~?Vlo?5[133G?refX333333c333333c333333c333333c333333c333333c333333c333333c333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffff%>mf+-cfFI_f̈tv,j33j333333c,j33jvẗI_f+-cfF%>mfffffff%>mf+-cfFI_f̈tv,j33j333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c333333c,j33jvẗI_f+-cfF%>mfffffffffffffffffffffffffffffffffffffffffffffffffSigima-1.1.1/sigima/data/tests/curve_formats/datetime.txt000066400000000000000000001140741514013333200234650ustar00rootroot00000000000000ER SD34,Time,Celsius(°C),Humidity(%rh),Dew Point(°C),Serial Number 1,2025-06-19 10:00:00,24.0,51.5,13.4,010066854 2,2025-06-19 10:05:00,24.0,52.0,13.5 3,2025-06-19 10:10:00,23.5,52.5,13.2 4,2025-06-19 10:15:00,23.5,53.0,13.4 5,2025-06-19 10:20:00,23.5,53.5,13.5 6,2025-06-19 10:25:00,23.0,55.5,13.6 7,2025-06-19 10:30:00,23.0,56.5,13.9 8,2025-06-19 10:35:00,23.0,56.0,13.8 9,2025-06-19 10:40:00,23.0,55.5,13.6 10,2025-06-19 10:45:00,23.0,55.5,13.6 11,2025-06-19 10:50:00,23.0,55.5,13.6 12,2025-06-19 10:55:00,23.0,55.0,13.5 13,2025-06-19 11:00:00,23.0,55.0,13.5 14,2025-06-19 11:05:00,23.0,55.0,13.5 15,2025-06-19 11:10:00,23.0,55.0,13.5 16,2025-06-19 11:15:00,23.0,55.0,13.5 17,2025-06-19 11:20:00,23.0,55.0,13.5 18,2025-06-19 11:25:00,23.0,55.0,13.5 19,2025-06-19 11:30:00,23.0,55.0,13.5 20,2025-06-19 11:35:00,23.0,55.0,13.5 21,2025-06-19 11:40:00,23.0,55.0,13.5 22,2025-06-19 11:45:00,23.0,55.0,13.5 23,2025-06-19 11:50:00,23.0,55.0,13.5 24,2025-06-19 11:55:00,23.0,55.5,13.6 25,2025-06-19 12:00:00,23.0,55.5,13.6 26,2025-06-19 12:05:00,23.0,55.5,13.6 27,2025-06-19 12:10:00,23.0,55.0,13.5 28,2025-06-19 12:15:00,23.0,55.0,13.5 29,2025-06-19 12:20:00,23.0,55.0,13.5 30,2025-06-19 12:25:00,23.0,54.5,13.3 31,2025-06-19 12:30:00,23.0,54.5,13.3 32,2025-06-19 12:35:00,23.0,54.5,13.3 33,2025-06-19 12:40:00,23.0,54.5,13.3 34,2025-06-19 12:45:00,23.0,54.5,13.3 35,2025-06-19 12:50:00,23.0,54.5,13.3 36,2025-06-19 12:55:00,23.0,54.5,13.3 37,2025-06-19 13:00:00,23.0,54.5,13.3 38,2025-06-19 13:05:00,23.0,54.5,13.3 39,2025-06-19 13:10:00,23.0,54.5,13.3 40,2025-06-19 13:15:00,23.0,55.0,13.5 41,2025-06-19 13:20:00,23.0,55.0,13.5 42,2025-06-19 13:25:00,23.0,55.0,13.5 43,2025-06-19 13:30:00,23.0,55.0,13.5 44,2025-06-19 13:35:00,23.0,54.5,13.3 45,2025-06-19 13:40:00,23.0,54.5,13.3 46,2025-06-19 13:45:00,23.0,54.5,13.3 47,2025-06-19 13:50:00,23.0,54.5,13.3 48,2025-06-19 13:55:00,23.0,54.5,13.3 49,2025-06-19 14:00:00,23.0,54.5,13.3 50,2025-06-19 14:05:00,23.0,54.5,13.3 51,2025-06-19 14:10:00,23.0,54.5,13.3 52,2025-06-19 14:15:00,23.0,54.5,13.3 53,2025-06-19 14:20:00,23.0,54.5,13.3 54,2025-06-19 14:25:00,23.0,54.5,13.3 55,2025-06-19 14:30:00,23.0,54.5,13.3 56,2025-06-19 14:35:00,23.0,54.5,13.3 57,2025-06-19 14:40:00,23.0,54.5,13.3 58,2025-06-19 14:45:00,23.0,54.5,13.3 59,2025-06-19 14:50:00,23.0,54.5,13.3 60,2025-06-19 14:55:00,23.0,54.5,13.3 61,2025-06-19 15:00:00,23.0,54.5,13.3 62,2025-06-19 15:05:00,23.0,54.5,13.3 63,2025-06-19 15:10:00,23.0,54.5,13.3 64,2025-06-19 15:15:00,23.0,54.5,13.3 65,2025-06-19 15:20:00,23.0,54.5,13.3 66,2025-06-19 15:25:00,23.0,54.5,13.3 67,2025-06-19 15:30:00,23.0,54.5,13.3 68,2025-06-19 15:35:00,23.0,54.5,13.3 69,2025-06-19 15:40:00,23.0,54.5,13.3 70,2025-06-19 15:45:00,23.0,54.5,13.3 71,2025-06-19 15:50:00,23.0,54.5,13.3 72,2025-06-19 15:55:00,23.0,54.5,13.3 73,2025-06-19 16:00:00,23.0,54.5,13.3 74,2025-06-19 16:05:00,23.0,54.5,13.3 75,2025-06-19 16:10:00,23.0,54.5,13.3 76,2025-06-19 16:15:00,23.0,54.5,13.3 77,2025-06-19 16:20:00,23.0,54.5,13.3 78,2025-06-19 16:25:00,23.0,54.5,13.3 79,2025-06-19 16:30:00,23.0,54.5,13.3 80,2025-06-19 16:35:00,23.0,54.5,13.3 81,2025-06-19 16:40:00,23.0,54.5,13.3 82,2025-06-19 16:45:00,23.0,54.0,13.2 83,2025-06-19 16:50:00,23.0,54.5,13.3 84,2025-06-19 16:55:00,23.0,54.0,13.2 85,2025-06-19 17:00:00,23.0,54.0,13.2 86,2025-06-19 17:05:00,23.0,54.0,13.2 87,2025-06-19 17:10:00,23.0,54.5,13.3 88,2025-06-19 17:15:00,23.0,54.5,13.3 89,2025-06-19 17:20:00,23.0,54.5,13.3 90,2025-06-19 17:25:00,23.0,54.0,13.2 91,2025-06-19 17:30:00,23.0,54.5,13.3 92,2025-06-19 17:35:00,23.0,54.0,13.2 93,2025-06-19 17:40:00,23.0,54.5,13.3 94,2025-06-19 17:45:00,23.0,54.5,13.3 95,2025-06-19 17:50:00,23.0,54.5,13.3 96,2025-06-19 17:55:00,23.0,54.5,13.3 97,2025-06-19 18:00:00,23.0,54.5,13.3 98,2025-06-19 18:05:00,23.0,54.5,13.3 99,2025-06-19 18:10:00,23.0,54.5,13.3 100,2025-06-19 18:15:00,23.0,54.5,13.3 101,2025-06-19 18:20:00,23.0,54.5,13.3 102,2025-06-19 18:25:00,23.0,54.5,13.3 103,2025-06-19 18:30:00,23.0,54.5,13.3 104,2025-06-19 18:35:00,23.0,54.5,13.3 105,2025-06-19 18:40:00,23.0,54.5,13.3 106,2025-06-19 18:45:00,23.0,54.5,13.3 107,2025-06-19 18:50:00,23.0,54.5,13.3 108,2025-06-19 18:55:00,23.0,54.5,13.3 109,2025-06-19 19:00:00,23.0,54.5,13.3 110,2025-06-19 19:05:00,23.0,54.5,13.3 111,2025-06-19 19:10:00,23.0,54.5,13.3 112,2025-06-19 19:15:00,23.0,54.5,13.3 113,2025-06-19 19:20:00,23.0,54.5,13.3 114,2025-06-19 19:25:00,23.0,54.5,13.3 115,2025-06-19 19:30:00,23.0,54.5,13.3 116,2025-06-19 19:35:00,23.0,54.5,13.3 117,2025-06-19 19:40:00,23.0,54.5,13.3 118,2025-06-19 19:45:00,23.0,54.5,13.3 119,2025-06-19 19:50:00,23.0,54.5,13.3 120,2025-06-19 19:55:00,23.0,54.5,13.3 121,2025-06-19 20:00:00,23.0,54.5,13.3 122,2025-06-19 20:05:00,23.0,54.5,13.3 123,2025-06-19 20:10:00,23.0,54.5,13.3 124,2025-06-19 20:15:00,23.0,54.5,13.3 125,2025-06-19 20:20:00,23.0,54.5,13.3 126,2025-06-19 20:25:00,23.0,54.5,13.3 127,2025-06-19 20:30:00,23.0,54.5,13.3 128,2025-06-19 20:35:00,23.0,54.5,13.3 129,2025-06-19 20:40:00,23.0,54.5,13.3 130,2025-06-19 20:45:00,23.0,54.5,13.3 131,2025-06-19 20:50:00,23.0,54.5,13.3 132,2025-06-19 20:55:00,23.0,54.5,13.3 133,2025-06-19 21:00:00,23.0,55.0,13.5 134,2025-06-19 21:05:00,23.0,55.0,13.5 135,2025-06-19 21:10:00,23.0,54.5,13.3 136,2025-06-19 21:15:00,23.0,54.5,13.3 137,2025-06-19 21:20:00,23.0,54.5,13.3 138,2025-06-19 21:25:00,23.0,54.5,13.3 139,2025-06-19 21:30:00,23.0,54.5,13.3 140,2025-06-19 21:35:00,23.0,54.5,13.3 141,2025-06-19 21:40:00,23.0,54.5,13.3 142,2025-06-19 21:45:00,23.0,54.5,13.3 143,2025-06-19 21:50:00,23.0,54.5,13.3 144,2025-06-19 21:55:00,23.0,54.5,13.3 145,2025-06-19 22:00:00,23.0,54.5,13.3 146,2025-06-19 22:05:00,23.0,54.5,13.3 147,2025-06-19 22:10:00,23.0,54.5,13.3 148,2025-06-19 22:15:00,23.0,54.5,13.3 149,2025-06-19 22:20:00,23.0,55.0,13.5 150,2025-06-19 22:25:00,23.0,55.0,13.5 151,2025-06-19 22:30:00,23.5,55.0,13.9 152,2025-06-19 22:35:00,23.5,54.5,13.8 153,2025-06-19 22:40:00,23.5,54.5,13.8 154,2025-06-19 22:45:00,23.5,54.5,13.8 155,2025-06-19 22:50:00,23.0,54.5,13.3 156,2025-06-19 22:55:00,23.0,54.5,13.3 157,2025-06-19 23:00:00,23.0,54.5,13.3 158,2025-06-19 23:05:00,23.0,54.5,13.3 159,2025-06-19 23:10:00,23.0,54.5,13.3 160,2025-06-19 23:15:00,23.0,54.5,13.3 161,2025-06-19 23:20:00,23.0,54.5,13.3 162,2025-06-19 23:25:00,23.0,54.5,13.3 163,2025-06-19 23:30:00,23.0,54.5,13.3 164,2025-06-19 23:35:00,23.0,54.5,13.3 165,2025-06-19 23:40:00,23.0,54.5,13.3 166,2025-06-19 23:45:00,23.0,54.5,13.3 167,2025-06-19 23:50:00,23.0,54.5,13.3 168,2025-06-19 23:55:00,23.0,55.0,13.5 169,2025-06-20 00:00:00,23.0,55.0,13.5 170,2025-06-20 00:05:00,23.0,55.0,13.5 171,2025-06-20 00:10:00,23.0,55.0,13.5 172,2025-06-20 00:15:00,23.0,55.0,13.5 173,2025-06-20 00:20:00,23.0,54.5,13.3 174,2025-06-20 00:25:00,23.0,54.5,13.3 175,2025-06-20 00:30:00,23.0,54.5,13.3 176,2025-06-20 00:35:00,23.0,54.5,13.3 177,2025-06-20 00:40:00,23.0,54.5,13.3 178,2025-06-20 00:45:00,23.0,55.0,13.5 179,2025-06-20 00:50:00,23.0,55.0,13.5 180,2025-06-20 00:55:00,23.0,55.0,13.5 181,2025-06-20 01:00:00,23.0,54.5,13.3 182,2025-06-20 01:05:00,23.0,54.5,13.3 183,2025-06-20 01:10:00,23.0,55.0,13.5 184,2025-06-20 01:15:00,23.5,55.0,13.9 185,2025-06-20 01:20:00,23.5,55.0,13.9 186,2025-06-20 01:25:00,23.5,55.0,13.9 187,2025-06-20 01:30:00,23.5,55.0,13.9 188,2025-06-20 01:35:00,23.5,55.0,13.9 189,2025-06-20 01:40:00,23.5,55.0,13.9 190,2025-06-20 01:45:00,23.5,55.0,13.9 191,2025-06-20 01:50:00,23.5,55.0,13.9 192,2025-06-20 01:55:00,23.5,55.0,13.9 193,2025-06-20 02:00:00,23.5,55.0,13.9 194,2025-06-20 02:05:00,23.5,55.0,13.9 195,2025-06-20 02:10:00,23.0,55.0,13.5 196,2025-06-20 02:15:00,23.0,55.0,13.5 197,2025-06-20 02:20:00,23.0,55.0,13.5 198,2025-06-20 02:25:00,23.0,55.0,13.5 199,2025-06-20 02:30:00,23.0,55.0,13.5 200,2025-06-20 02:35:00,23.0,55.0,13.5 201,2025-06-20 02:40:00,23.0,55.0,13.5 202,2025-06-20 02:45:00,23.0,55.0,13.5 203,2025-06-20 02:50:00,23.0,55.0,13.5 204,2025-06-20 02:55:00,23.0,55.5,13.6 205,2025-06-20 03:00:00,23.0,55.5,13.6 206,2025-06-20 03:05:00,23.5,55.5,14.1 207,2025-06-20 03:10:00,23.5,55.5,14.1 208,2025-06-20 03:15:00,23.5,55.5,14.1 209,2025-06-20 03:20:00,23.5,55.0,13.9 210,2025-06-20 03:25:00,23.5,55.0,13.9 211,2025-06-20 03:30:00,23.5,55.0,13.9 212,2025-06-20 03:35:00,23.5,55.0,13.9 213,2025-06-20 03:40:00,23.0,55.0,13.5 214,2025-06-20 03:45:00,23.0,55.0,13.5 215,2025-06-20 03:50:00,23.0,55.0,13.5 216,2025-06-20 03:55:00,23.0,55.0,13.5 217,2025-06-20 04:00:00,23.5,55.0,13.9 218,2025-06-20 04:05:00,23.5,55.0,13.9 219,2025-06-20 04:10:00,23.5,55.0,13.9 220,2025-06-20 04:15:00,23.5,55.5,14.1 221,2025-06-20 04:20:00,23.5,55.5,14.1 222,2025-06-20 04:25:00,23.5,55.5,14.1 223,2025-06-20 04:30:00,23.5,55.5,14.1 224,2025-06-20 04:35:00,23.5,55.5,14.1 225,2025-06-20 04:40:00,23.5,55.0,13.9 226,2025-06-20 04:45:00,23.5,55.0,13.9 227,2025-06-20 04:50:00,23.5,55.0,13.9 228,2025-06-20 04:55:00,23.5,55.0,13.9 229,2025-06-20 05:00:00,23.5,55.0,13.9 230,2025-06-20 05:05:00,23.5,55.0,13.9 231,2025-06-20 05:10:00,23.5,55.0,13.9 232,2025-06-20 05:15:00,23.5,55.0,13.9 233,2025-06-20 05:20:00,23.5,55.0,13.9 234,2025-06-20 05:25:00,23.0,55.5,13.6 235,2025-06-20 05:30:00,23.0,55.5,13.6 236,2025-06-20 05:35:00,23.0,55.0,13.5 237,2025-06-20 05:40:00,23.0,55.0,13.5 238,2025-06-20 05:45:00,23.5,55.0,13.9 239,2025-06-20 05:50:00,23.0,55.5,13.6 240,2025-06-20 05:55:00,23.5,55.5,14.1 241,2025-06-20 06:00:00,23.5,55.5,14.1 242,2025-06-20 06:05:00,23.5,55.5,14.1 243,2025-06-20 06:10:00,23.5,55.5,14.1 244,2025-06-20 06:15:00,23.5,55.5,14.1 245,2025-06-20 06:20:00,23.5,55.5,14.1 246,2025-06-20 06:25:00,23.5,55.0,13.9 247,2025-06-20 06:30:00,23.5,55.0,13.9 248,2025-06-20 06:35:00,23.5,55.0,13.9 249,2025-06-20 06:40:00,23.5,55.0,13.9 250,2025-06-20 06:45:00,23.5,55.5,14.1 251,2025-06-20 06:50:00,23.5,55.0,13.9 252,2025-06-20 06:55:00,23.5,55.0,13.9 253,2025-06-20 07:00:00,23.5,55.0,13.9 254,2025-06-20 07:05:00,23.5,55.0,13.9 255,2025-06-20 07:10:00,23.5,55.0,13.9 256,2025-06-20 07:15:00,23.5,55.5,14.1 257,2025-06-20 07:20:00,23.5,55.5,14.1 258,2025-06-20 07:25:00,23.5,55.5,14.1 259,2025-06-20 07:30:00,23.5,55.5,14.1 260,2025-06-20 07:35:00,23.5,55.5,14.1 261,2025-06-20 07:40:00,23.5,55.0,13.9 262,2025-06-20 07:45:00,23.5,55.0,13.9 263,2025-06-20 07:50:00,23.5,55.0,13.9 264,2025-06-20 07:55:00,23.5,55.0,13.9 265,2025-06-20 08:00:00,23.5,55.0,13.9 266,2025-06-20 08:05:00,23.5,55.0,13.9 267,2025-06-20 08:10:00,23.5,55.0,13.9 268,2025-06-20 08:15:00,23.5,55.0,13.9 269,2025-06-20 08:20:00,23.5,55.0,13.9 270,2025-06-20 08:25:00,23.5,55.0,13.9 271,2025-06-20 08:30:00,23.0,55.0,13.5 272,2025-06-20 08:35:00,23.5,55.0,13.9 273,2025-06-20 08:40:00,23.5,55.0,13.9 274,2025-06-20 08:45:00,23.5,55.0,13.9 275,2025-06-20 08:50:00,23.5,55.5,14.1 276,2025-06-20 08:55:00,23.5,55.5,14.1 277,2025-06-20 09:00:00,23.5,55.5,14.1 278,2025-06-20 09:05:00,23.5,55.5,14.1 279,2025-06-20 09:10:00,23.5,55.5,14.1 280,2025-06-20 09:15:00,23.5,55.5,14.1 281,2025-06-20 09:20:00,23.5,55.0,13.9 282,2025-06-20 09:25:00,23.5,55.0,13.9 283,2025-06-20 09:30:00,23.5,55.0,13.9 284,2025-06-20 09:35:00,23.5,55.0,13.9 285,2025-06-20 09:40:00,23.5,55.0,13.9 286,2025-06-20 09:45:00,23.5,55.0,13.9 287,2025-06-20 09:50:00,23.5,55.0,13.9 288,2025-06-20 09:55:00,23.5,55.0,13.9 289,2025-06-20 10:00:00,23.5,55.0,13.9 290,2025-06-20 10:05:00,23.5,55.0,13.9 291,2025-06-20 10:10:00,23.5,55.0,13.9 292,2025-06-20 10:15:00,23.5,55.5,14.1 293,2025-06-20 10:20:00,23.5,55.5,14.1 294,2025-06-20 10:25:00,23.5,55.5,14.1 295,2025-06-20 10:30:00,23.5,55.5,14.1 296,2025-06-20 10:35:00,23.5,55.0,13.9 297,2025-06-20 10:40:00,23.5,55.0,13.9 298,2025-06-20 10:45:00,23.5,55.0,13.9 299,2025-06-20 10:50:00,23.5,55.0,13.9 300,2025-06-20 10:55:00,23.5,55.0,13.9 301,2025-06-20 11:00:00,23.5,55.0,13.9 302,2025-06-20 11:05:00,23.5,55.0,13.9 303,2025-06-20 11:10:00,23.5,55.0,13.9 304,2025-06-20 11:15:00,23.5,55.0,13.9 305,2025-06-20 11:20:00,23.5,55.0,13.9 306,2025-06-20 11:25:00,23.5,55.0,13.9 307,2025-06-20 11:30:00,23.5,55.0,13.9 308,2025-06-20 11:35:00,23.5,55.0,13.9 309,2025-06-20 11:40:00,23.5,55.0,13.9 310,2025-06-20 11:45:00,23.5,55.0,13.9 311,2025-06-20 11:50:00,23.5,55.5,14.1 312,2025-06-20 11:55:00,23.5,55.5,14.1 313,2025-06-20 12:00:00,23.5,55.5,14.1 314,2025-06-20 12:05:00,23.5,55.5,14.1 315,2025-06-20 12:10:00,23.5,55.5,14.1 316,2025-06-20 12:15:00,23.5,55.5,14.1 317,2025-06-20 12:20:00,23.5,55.5,14.1 318,2025-06-20 12:25:00,23.5,55.5,14.1 319,2025-06-20 12:30:00,23.5,55.5,14.1 320,2025-06-20 12:35:00,23.5,55.5,14.1 321,2025-06-20 12:40:00,23.5,55.0,13.9 322,2025-06-20 12:45:00,23.5,55.5,14.1 323,2025-06-20 12:50:00,23.5,55.5,14.1 324,2025-06-20 12:55:00,23.5,55.5,14.1 325,2025-06-20 13:00:00,23.5,55.5,14.1 326,2025-06-20 13:05:00,23.5,55.5,14.1 327,2025-06-20 13:10:00,23.5,55.5,14.1 328,2025-06-20 13:15:00,23.5,55.5,14.1 329,2025-06-20 13:20:00,23.5,55.5,14.1 330,2025-06-20 13:25:00,23.5,55.5,14.1 331,2025-06-20 13:30:00,23.5,55.5,14.1 332,2025-06-20 13:35:00,23.5,55.5,14.1 333,2025-06-20 13:40:00,23.5,55.5,14.1 334,2025-06-20 13:45:00,23.5,55.5,14.1 335,2025-06-20 13:50:00,23.5,55.5,14.1 336,2025-06-20 13:55:00,23.5,55.5,14.1 337,2025-06-20 14:00:00,23.5,55.5,14.1 338,2025-06-20 14:05:00,23.5,55.5,14.1 339,2025-06-20 14:10:00,23.5,55.5,14.1 340,2025-06-20 14:15:00,23.5,55.5,14.1 341,2025-06-20 14:20:00,23.5,55.5,14.1 342,2025-06-20 14:25:00,23.5,55.5,14.1 343,2025-06-20 14:30:00,23.5,55.5,14.1 344,2025-06-20 14:35:00,23.5,55.5,14.1 345,2025-06-20 14:40:00,23.5,55.5,14.1 346,2025-06-20 14:45:00,23.5,55.5,14.1 347,2025-06-20 14:50:00,23.5,55.5,14.1 348,2025-06-20 14:55:00,23.5,55.5,14.1 349,2025-06-20 15:00:00,23.5,56.0,14.2 350,2025-06-20 15:05:00,23.5,55.5,14.1 351,2025-06-20 15:10:00,23.5,55.5,14.1 352,2025-06-20 15:15:00,23.5,55.5,14.1 353,2025-06-20 15:20:00,23.5,55.5,14.1 354,2025-06-20 15:25:00,23.5,55.5,14.1 355,2025-06-20 15:30:00,23.5,55.5,14.1 356,2025-06-20 15:35:00,23.5,55.5,14.1 357,2025-06-20 15:40:00,23.5,55.5,14.1 358,2025-06-20 15:45:00,23.5,55.5,14.1 359,2025-06-20 15:50:00,23.5,55.5,14.1 360,2025-06-20 15:55:00,23.5,55.5,14.1 361,2025-06-20 16:00:00,23.5,55.5,14.1 362,2025-06-20 16:05:00,23.5,55.5,14.1 363,2025-06-20 16:10:00,23.5,55.5,14.1 364,2025-06-20 16:15:00,23.5,55.5,14.1 365,2025-06-20 16:20:00,23.5,56.0,14.2 366,2025-06-20 16:25:00,23.5,56.0,14.2 367,2025-06-20 16:30:00,23.5,55.5,14.1 368,2025-06-20 16:35:00,23.5,55.5,14.1 369,2025-06-20 16:40:00,23.5,55.5,14.1 370,2025-06-20 16:45:00,23.5,55.5,14.1 371,2025-06-20 16:50:00,23.5,55.5,14.1 372,2025-06-20 16:55:00,23.5,55.5,14.1 373,2025-06-20 17:00:00,23.5,55.5,14.1 374,2025-06-20 17:05:00,23.5,55.5,14.1 375,2025-06-20 17:10:00,23.5,55.5,14.1 376,2025-06-20 17:15:00,23.5,55.5,14.1 377,2025-06-20 17:20:00,23.5,55.5,14.1 378,2025-06-20 17:25:00,23.5,55.5,14.1 379,2025-06-20 17:30:00,23.5,55.5,14.1 380,2025-06-20 17:35:00,23.5,55.5,14.1 381,2025-06-20 17:40:00,23.5,55.5,14.1 382,2025-06-20 17:45:00,23.5,55.5,14.1 383,2025-06-20 17:50:00,23.5,55.5,14.1 384,2025-06-20 17:55:00,23.5,56.0,14.2 385,2025-06-20 18:00:00,23.5,55.5,14.1 386,2025-06-20 18:05:00,23.5,55.5,14.1 387,2025-06-20 18:10:00,23.5,55.5,14.1 388,2025-06-20 18:15:00,23.5,55.5,14.1 389,2025-06-20 18:20:00,23.5,55.5,14.1 390,2025-06-20 18:25:00,23.5,55.5,14.1 391,2025-06-20 18:30:00,23.5,55.5,14.1 392,2025-06-20 18:35:00,23.5,55.5,14.1 393,2025-06-20 18:40:00,23.5,55.5,14.1 394,2025-06-20 18:45:00,23.5,55.5,14.1 395,2025-06-20 18:50:00,23.5,55.5,14.1 396,2025-06-20 18:55:00,23.5,55.5,14.1 397,2025-06-20 19:00:00,23.5,55.5,14.1 398,2025-06-20 19:05:00,23.5,55.5,14.1 399,2025-06-20 19:10:00,23.5,55.5,14.1 400,2025-06-20 19:15:00,23.5,55.5,14.1 401,2025-06-20 19:20:00,23.5,55.5,14.1 402,2025-06-20 19:25:00,23.5,55.5,14.1 403,2025-06-20 19:30:00,23.5,55.5,14.1 404,2025-06-20 19:35:00,23.5,55.5,14.1 405,2025-06-20 19:40:00,23.5,55.5,14.1 406,2025-06-20 19:45:00,23.5,55.5,14.1 407,2025-06-20 19:50:00,23.5,55.5,14.1 408,2025-06-20 19:55:00,23.5,55.5,14.1 409,2025-06-20 20:00:00,23.5,55.5,14.1 410,2025-06-20 20:05:00,23.5,55.5,14.1 411,2025-06-20 20:10:00,23.5,55.5,14.1 412,2025-06-20 20:15:00,23.5,55.5,14.1 413,2025-06-20 20:20:00,23.5,55.5,14.1 414,2025-06-20 20:25:00,23.5,55.5,14.1 415,2025-06-20 20:30:00,23.5,55.5,14.1 416,2025-06-20 20:35:00,23.5,55.5,14.1 417,2025-06-20 20:40:00,23.5,55.5,14.1 418,2025-06-20 20:45:00,23.5,55.5,14.1 419,2025-06-20 20:50:00,23.5,55.5,14.1 420,2025-06-20 20:55:00,23.5,55.5,14.1 421,2025-06-20 21:00:00,23.5,55.5,14.1 422,2025-06-20 21:05:00,23.5,55.5,14.1 423,2025-06-20 21:10:00,23.5,55.5,14.1 424,2025-06-20 21:15:00,23.5,55.5,14.1 425,2025-06-20 21:20:00,23.5,55.5,14.1 426,2025-06-20 21:25:00,23.5,55.5,14.1 427,2025-06-20 21:30:00,23.5,55.5,14.1 428,2025-06-20 21:35:00,23.5,55.5,14.1 429,2025-06-20 21:40:00,23.5,55.5,14.1 430,2025-06-20 21:45:00,23.5,55.5,14.1 431,2025-06-20 21:50:00,23.5,55.5,14.1 432,2025-06-20 21:55:00,23.5,55.5,14.1 433,2025-06-20 22:00:00,23.5,55.5,14.1 434,2025-06-20 22:05:00,23.5,55.5,14.1 435,2025-06-20 22:10:00,23.5,55.5,14.1 436,2025-06-20 22:15:00,23.5,55.5,14.1 437,2025-06-20 22:20:00,23.5,55.5,14.1 438,2025-06-20 22:25:00,23.5,55.5,14.1 439,2025-06-20 22:30:00,23.5,55.5,14.1 440,2025-06-20 22:35:00,23.5,55.5,14.1 441,2025-06-20 22:40:00,23.5,55.5,14.1 442,2025-06-20 22:45:00,23.5,55.5,14.1 443,2025-06-20 22:50:00,23.5,55.5,14.1 444,2025-06-20 22:55:00,23.5,55.5,14.1 445,2025-06-20 23:00:00,23.5,55.5,14.1 446,2025-06-20 23:05:00,23.5,55.5,14.1 447,2025-06-20 23:10:00,23.5,55.5,14.1 448,2025-06-20 23:15:00,23.5,55.5,14.1 449,2025-06-20 23:20:00,23.5,55.5,14.1 450,2025-06-20 23:25:00,23.5,55.5,14.1 451,2025-06-20 23:30:00,23.5,55.5,14.1 452,2025-06-20 23:35:00,23.5,55.5,14.1 453,2025-06-20 23:40:00,23.5,55.5,14.1 454,2025-06-20 23:45:00,23.5,55.5,14.1 455,2025-06-20 23:50:00,23.5,55.5,14.1 456,2025-06-20 23:55:00,23.5,56.0,14.2 457,2025-06-21 00:00:00,23.5,56.0,14.2 458,2025-06-21 00:05:00,23.5,56.0,14.2 459,2025-06-21 00:10:00,23.5,56.0,14.2 460,2025-06-21 00:15:00,23.5,56.0,14.2 461,2025-06-21 00:20:00,23.5,55.5,14.1 462,2025-06-21 00:25:00,23.5,55.5,14.1 463,2025-06-21 00:30:00,23.5,55.5,14.1 464,2025-06-21 00:35:00,23.5,55.5,14.1 465,2025-06-21 00:40:00,23.5,55.5,14.1 466,2025-06-21 00:45:00,23.5,55.5,14.1 467,2025-06-21 00:50:00,23.5,55.5,14.1 468,2025-06-21 00:55:00,23.5,55.5,14.1 469,2025-06-21 01:00:00,23.5,55.5,14.1 470,2025-06-21 01:05:00,23.5,55.5,14.1 471,2025-06-21 01:10:00,23.5,55.5,14.1 472,2025-06-21 01:15:00,23.5,56.0,14.2 473,2025-06-21 01:20:00,23.5,56.0,14.2 474,2025-06-21 01:25:00,23.5,56.0,14.2 475,2025-06-21 01:30:00,23.5,56.0,14.2 476,2025-06-21 01:35:00,23.5,56.0,14.2 477,2025-06-21 01:40:00,23.5,55.5,14.1 478,2025-06-21 01:45:00,23.5,55.5,14.1 479,2025-06-21 01:50:00,23.5,55.5,14.1 480,2025-06-21 01:55:00,23.5,55.5,14.1 481,2025-06-21 02:00:00,23.5,55.5,14.1 482,2025-06-21 02:05:00,23.5,55.5,14.1 483,2025-06-21 02:10:00,23.5,55.5,14.1 484,2025-06-21 02:15:00,23.5,55.5,14.1 485,2025-06-21 02:20:00,23.5,56.0,14.2 486,2025-06-21 02:25:00,23.5,56.0,14.2 487,2025-06-21 02:30:00,23.5,56.0,14.2 488,2025-06-21 02:35:00,23.5,56.0,14.2 489,2025-06-21 02:40:00,23.5,56.0,14.2 490,2025-06-21 02:45:00,23.5,56.0,14.2 491,2025-06-21 02:50:00,23.5,56.0,14.2 492,2025-06-21 02:55:00,23.5,56.0,14.2 493,2025-06-21 03:00:00,23.5,56.0,14.2 494,2025-06-21 03:05:00,23.5,56.0,14.2 495,2025-06-21 03:10:00,23.5,56.0,14.2 496,2025-06-21 03:15:00,23.5,56.0,14.2 497,2025-06-21 03:20:00,23.5,56.0,14.2 498,2025-06-21 03:25:00,23.5,56.0,14.2 499,2025-06-21 03:30:00,23.5,56.0,14.2 500,2025-06-21 03:35:00,23.5,56.0,14.2 501,2025-06-21 03:40:00,23.5,56.0,14.2 502,2025-06-21 03:45:00,23.5,56.0,14.2 503,2025-06-21 03:50:00,23.5,56.0,14.2 504,2025-06-21 03:55:00,23.5,56.0,14.2 505,2025-06-21 04:00:00,23.5,55.5,14.1 506,2025-06-21 04:05:00,23.5,56.0,14.2 507,2025-06-21 04:10:00,23.5,56.0,14.2 508,2025-06-21 04:15:00,23.5,56.0,14.2 509,2025-06-21 04:20:00,23.5,56.0,14.2 510,2025-06-21 04:25:00,23.5,56.5,14.4 511,2025-06-21 04:30:00,23.5,56.0,14.2 512,2025-06-21 04:35:00,23.5,56.0,14.2 513,2025-06-21 04:40:00,23.5,56.0,14.2 514,2025-06-21 04:45:00,23.5,56.0,14.2 515,2025-06-21 04:50:00,23.5,56.0,14.2 516,2025-06-21 04:55:00,23.5,56.0,14.2 517,2025-06-21 05:00:00,23.5,56.0,14.2 518,2025-06-21 05:05:00,23.5,56.0,14.2 519,2025-06-21 05:10:00,23.5,56.0,14.2 520,2025-06-21 05:15:00,23.5,56.0,14.2 521,2025-06-21 05:20:00,23.5,56.0,14.2 522,2025-06-21 05:25:00,23.5,56.0,14.2 523,2025-06-21 05:30:00,23.5,56.0,14.2 524,2025-06-21 05:35:00,23.5,56.0,14.2 525,2025-06-21 05:40:00,23.5,56.0,14.2 526,2025-06-21 05:45:00,23.5,56.0,14.2 527,2025-06-21 05:50:00,23.5,56.0,14.2 528,2025-06-21 05:55:00,23.5,56.5,14.4 529,2025-06-21 06:00:00,23.5,56.5,14.4 530,2025-06-21 06:05:00,23.5,56.5,14.4 531,2025-06-21 06:10:00,23.5,56.0,14.2 532,2025-06-21 06:15:00,23.5,56.0,14.2 533,2025-06-21 06:20:00,23.5,56.0,14.2 534,2025-06-21 06:25:00,23.5,56.0,14.2 535,2025-06-21 06:30:00,23.5,56.0,14.2 536,2025-06-21 06:35:00,23.5,56.0,14.2 537,2025-06-21 06:40:00,23.5,56.0,14.2 538,2025-06-21 06:45:00,23.5,56.0,14.2 539,2025-06-21 06:50:00,23.5,56.0,14.2 540,2025-06-21 06:55:00,23.5,56.0,14.2 541,2025-06-21 07:00:00,23.5,56.0,14.2 542,2025-06-21 07:05:00,23.5,56.0,14.2 543,2025-06-21 07:10:00,23.5,56.0,14.2 544,2025-06-21 07:15:00,23.5,56.0,14.2 545,2025-06-21 07:20:00,23.5,56.5,14.4 546,2025-06-21 07:25:00,23.5,56.5,14.4 547,2025-06-21 07:30:00,23.5,56.0,14.2 548,2025-06-21 07:35:00,23.5,56.0,14.2 549,2025-06-21 07:40:00,23.5,56.0,14.2 550,2025-06-21 07:45:00,23.5,56.0,14.2 551,2025-06-21 07:50:00,23.5,56.0,14.2 552,2025-06-21 07:55:00,23.5,56.0,14.2 553,2025-06-21 08:00:00,23.5,56.0,14.2 554,2025-06-21 08:05:00,23.5,56.0,14.2 555,2025-06-21 08:10:00,23.5,56.0,14.2 556,2025-06-21 08:15:00,23.5,56.0,14.2 557,2025-06-21 08:20:00,23.5,56.0,14.2 558,2025-06-21 08:25:00,23.5,56.0,14.2 559,2025-06-21 08:30:00,23.5,56.0,14.2 560,2025-06-21 08:35:00,23.5,56.0,14.2 561,2025-06-21 08:40:00,23.5,56.0,14.2 562,2025-06-21 08:45:00,23.5,56.0,14.2 563,2025-06-21 08:50:00,23.5,56.0,14.2 564,2025-06-21 08:55:00,23.5,56.5,14.4 565,2025-06-21 09:00:00,23.5,56.5,14.4 566,2025-06-21 09:05:00,23.5,56.5,14.4 567,2025-06-21 09:10:00,23.5,56.5,14.4 568,2025-06-21 09:15:00,23.5,56.5,14.4 569,2025-06-21 09:20:00,23.5,56.0,14.2 570,2025-06-21 09:25:00,23.5,56.0,14.2 571,2025-06-21 09:30:00,23.5,56.0,14.2 572,2025-06-21 09:35:00,23.5,56.0,14.2 573,2025-06-21 09:40:00,23.5,56.0,14.2 574,2025-06-21 09:45:00,23.5,56.0,14.2 575,2025-06-21 09:50:00,23.5,56.0,14.2 576,2025-06-21 09:55:00,23.5,56.0,14.2 577,2025-06-21 10:00:00,23.5,56.0,14.2 578,2025-06-21 10:05:00,23.5,56.0,14.2 579,2025-06-21 10:10:00,23.5,56.0,14.2 580,2025-06-21 10:15:00,23.5,56.5,14.4 581,2025-06-21 10:20:00,23.5,56.5,14.4 582,2025-06-21 10:25:00,23.5,56.5,14.4 583,2025-06-21 10:30:00,23.5,56.5,14.4 584,2025-06-21 10:35:00,23.5,56.0,14.2 585,2025-06-21 10:40:00,23.5,56.0,14.2 586,2025-06-21 10:45:00,23.5,56.0,14.2 587,2025-06-21 10:50:00,23.5,56.0,14.2 588,2025-06-21 10:55:00,23.5,56.0,14.2 589,2025-06-21 11:00:00,23.5,56.0,14.2 590,2025-06-21 11:05:00,23.5,56.0,14.2 591,2025-06-21 11:10:00,23.5,56.0,14.2 592,2025-06-21 11:15:00,23.5,56.0,14.2 593,2025-06-21 11:20:00,23.5,56.0,14.2 594,2025-06-21 11:25:00,23.5,56.0,14.2 595,2025-06-21 11:30:00,23.5,56.0,14.2 596,2025-06-21 11:35:00,23.5,56.0,14.2 597,2025-06-21 11:40:00,23.5,56.0,14.2 598,2025-06-21 11:45:00,23.5,56.0,14.2 599,2025-06-21 11:50:00,23.5,56.5,14.4 600,2025-06-21 11:55:00,23.5,56.5,14.4 601,2025-06-21 12:00:00,23.5,56.5,14.4 602,2025-06-21 12:05:00,23.5,56.5,14.4 603,2025-06-21 12:10:00,23.5,56.5,14.4 604,2025-06-21 12:15:00,23.5,56.0,14.2 605,2025-06-21 12:20:00,23.5,56.0,14.2 606,2025-06-21 12:25:00,23.5,56.0,14.2 607,2025-06-21 12:30:00,23.5,56.0,14.2 608,2025-06-21 12:35:00,23.5,56.0,14.2 609,2025-06-21 12:40:00,23.5,56.0,14.2 610,2025-06-21 12:45:00,23.5,56.0,14.2 611,2025-06-21 12:50:00,23.5,56.0,14.2 612,2025-06-21 12:55:00,23.5,56.0,14.2 613,2025-06-21 13:00:00,23.5,56.0,14.2 614,2025-06-21 13:05:00,23.5,56.0,14.2 615,2025-06-21 13:10:00,23.5,56.0,14.2 616,2025-06-21 13:15:00,23.5,56.0,14.2 617,2025-06-21 13:20:00,23.5,56.5,14.4 618,2025-06-21 13:25:00,23.5,56.5,14.4 619,2025-06-21 13:30:00,23.5,56.5,14.4 620,2025-06-21 13:35:00,23.5,56.0,14.2 621,2025-06-21 13:40:00,23.5,56.0,14.2 622,2025-06-21 13:45:00,23.5,56.0,14.2 623,2025-06-21 13:50:00,23.5,56.0,14.2 624,2025-06-21 13:55:00,23.5,56.0,14.2 625,2025-06-21 14:00:00,23.5,56.0,14.2 626,2025-06-21 14:05:00,23.5,56.0,14.2 627,2025-06-21 14:10:00,23.5,56.0,14.2 628,2025-06-21 14:15:00,23.5,56.0,14.2 629,2025-06-21 14:20:00,23.5,56.0,14.2 630,2025-06-21 14:25:00,23.5,56.0,14.2 631,2025-06-21 14:30:00,23.5,56.0,14.2 632,2025-06-21 14:35:00,23.5,56.0,14.2 633,2025-06-21 14:40:00,23.5,56.0,14.2 634,2025-06-21 14:45:00,23.5,56.0,14.2 635,2025-06-21 14:50:00,23.5,56.0,14.2 636,2025-06-21 14:55:00,23.5,56.0,14.2 637,2025-06-21 15:00:00,23.5,56.0,14.2 638,2025-06-21 15:05:00,23.5,56.0,14.2 639,2025-06-21 15:10:00,23.5,56.0,14.2 640,2025-06-21 15:15:00,23.5,56.0,14.2 641,2025-06-21 15:20:00,23.5,56.0,14.2 642,2025-06-21 15:25:00,23.5,55.5,14.1 643,2025-06-21 15:30:00,23.5,55.5,14.1 644,2025-06-21 15:35:00,23.5,55.5,14.1 645,2025-06-21 15:40:00,23.5,55.5,14.1 646,2025-06-21 15:45:00,23.5,55.5,14.1 647,2025-06-21 15:50:00,23.5,55.5,14.1 648,2025-06-21 15:55:00,23.5,55.5,14.1 649,2025-06-21 16:00:00,23.5,55.5,14.1 650,2025-06-21 16:05:00,23.5,55.5,14.1 651,2025-06-21 16:10:00,23.5,55.5,14.1 652,2025-06-21 16:15:00,23.5,56.0,14.2 653,2025-06-21 16:20:00,23.5,56.0,14.2 654,2025-06-21 16:25:00,23.5,56.0,14.2 655,2025-06-21 16:30:00,23.5,55.5,14.1 656,2025-06-21 16:35:00,23.5,55.5,14.1 657,2025-06-21 16:40:00,23.5,55.5,14.1 658,2025-06-21 16:45:00,23.5,55.5,14.1 659,2025-06-21 16:50:00,23.5,55.5,14.1 660,2025-06-21 16:55:00,23.5,55.5,14.1 661,2025-06-21 17:00:00,23.5,55.5,14.1 662,2025-06-21 17:05:00,23.5,55.5,14.1 663,2025-06-21 17:10:00,23.5,55.5,14.1 664,2025-06-21 17:15:00,23.5,55.5,14.1 665,2025-06-21 17:20:00,23.5,55.5,14.1 666,2025-06-21 17:25:00,23.5,55.5,14.1 667,2025-06-21 17:30:00,23.5,55.5,14.1 668,2025-06-21 17:35:00,23.5,55.5,14.1 669,2025-06-21 17:40:00,23.5,55.5,14.1 670,2025-06-21 17:45:00,23.5,55.5,14.1 671,2025-06-21 17:50:00,23.5,55.5,14.1 672,2025-06-21 17:55:00,23.5,55.5,14.1 673,2025-06-21 18:00:00,23.5,55.5,14.1 674,2025-06-21 18:05:00,23.5,55.5,14.1 675,2025-06-21 18:10:00,23.5,55.5,14.1 676,2025-06-21 18:15:00,23.5,55.0,13.9 677,2025-06-21 18:20:00,23.5,55.0,13.9 678,2025-06-21 18:25:00,23.5,55.0,13.9 679,2025-06-21 18:30:00,23.5,55.0,13.9 680,2025-06-21 18:35:00,23.5,55.0,13.9 681,2025-06-21 18:40:00,23.5,55.0,13.9 682,2025-06-21 18:45:00,23.5,55.0,13.9 683,2025-06-21 18:50:00,23.5,55.0,13.9 684,2025-06-21 18:55:00,23.5,55.0,13.9 685,2025-06-21 19:00:00,23.5,55.0,13.9 686,2025-06-21 19:05:00,23.5,55.0,13.9 687,2025-06-21 19:10:00,23.5,55.0,13.9 688,2025-06-21 19:15:00,23.5,55.0,13.9 689,2025-06-21 19:20:00,23.5,55.5,14.1 690,2025-06-21 19:25:00,23.5,55.0,13.9 691,2025-06-21 19:30:00,23.5,55.0,13.9 692,2025-06-21 19:35:00,23.5,55.0,13.9 693,2025-06-21 19:40:00,23.5,54.5,13.8 694,2025-06-21 19:45:00,23.5,54.5,13.8 695,2025-06-21 19:50:00,23.5,54.5,13.8 696,2025-06-21 19:55:00,23.5,54.5,13.8 697,2025-06-21 20:00:00,23.5,54.5,13.8 698,2025-06-21 20:05:00,23.5,54.5,13.8 699,2025-06-21 20:10:00,23.5,54.5,13.8 700,2025-06-21 20:15:00,23.5,54.5,13.8 701,2025-06-21 20:20:00,23.5,54.5,13.8 702,2025-06-21 20:25:00,23.5,54.5,13.8 703,2025-06-21 20:30:00,23.5,54.5,13.8 704,2025-06-21 20:35:00,23.5,54.5,13.8 705,2025-06-21 20:40:00,23.5,54.5,13.8 706,2025-06-21 20:45:00,23.5,54.5,13.8 707,2025-06-21 20:50:00,23.5,54.5,13.8 708,2025-06-21 20:55:00,23.5,55.0,13.9 709,2025-06-21 21:00:00,23.5,54.5,13.8 710,2025-06-21 21:05:00,23.5,54.5,13.8 711,2025-06-21 21:10:00,23.5,54.5,13.8 712,2025-06-21 21:15:00,23.5,54.5,13.8 713,2025-06-21 21:20:00,23.5,54.5,13.8 714,2025-06-21 21:25:00,23.5,54.5,13.8 715,2025-06-21 21:30:00,23.5,54.5,13.8 716,2025-06-21 21:35:00,23.5,54.5,13.8 717,2025-06-21 21:40:00,23.5,54.5,13.8 718,2025-06-21 21:45:00,23.5,54.5,13.8 719,2025-06-21 21:50:00,23.5,54.5,13.8 720,2025-06-21 21:55:00,23.5,54.5,13.8 721,2025-06-21 22:00:00,23.5,54.5,13.8 722,2025-06-21 22:05:00,23.5,54.5,13.8 723,2025-06-21 22:10:00,23.5,54.5,13.8 724,2025-06-21 22:15:00,23.5,55.0,13.9 725,2025-06-21 22:20:00,23.5,55.0,13.9 726,2025-06-21 22:25:00,23.5,55.0,13.9 727,2025-06-21 22:30:00,23.5,54.5,13.8 728,2025-06-21 22:35:00,23.5,54.5,13.8 729,2025-06-21 22:40:00,23.5,54.5,13.8 730,2025-06-21 22:45:00,23.5,54.5,13.8 731,2025-06-21 22:50:00,23.5,54.5,13.8 732,2025-06-21 22:55:00,23.5,54.5,13.8 733,2025-06-21 23:00:00,23.5,54.5,13.8 734,2025-06-21 23:05:00,23.5,54.5,13.8 735,2025-06-21 23:10:00,23.5,54.5,13.8 736,2025-06-21 23:15:00,23.5,54.5,13.8 737,2025-06-21 23:20:00,23.5,54.5,13.8 738,2025-06-21 23:25:00,23.5,54.5,13.8 739,2025-06-21 23:30:00,23.5,54.5,13.8 740,2025-06-21 23:35:00,23.5,54.5,13.8 741,2025-06-21 23:40:00,23.5,54.5,13.8 742,2025-06-21 23:45:00,23.5,54.5,13.8 743,2025-06-21 23:50:00,23.5,55.0,13.9 744,2025-06-21 23:55:00,23.5,55.0,13.9 745,2025-06-22 00:00:00,23.5,55.0,13.9 746,2025-06-22 00:05:00,23.5,55.0,13.9 747,2025-06-22 00:10:00,23.5,55.0,13.9 748,2025-06-22 00:15:00,23.5,55.0,13.9 749,2025-06-22 00:20:00,23.5,55.0,13.9 750,2025-06-22 00:25:00,23.5,55.0,13.9 751,2025-06-22 00:30:00,23.5,54.5,13.8 752,2025-06-22 00:35:00,23.5,54.5,13.8 753,2025-06-22 00:40:00,23.5,54.5,13.8 754,2025-06-22 00:45:00,23.5,54.5,13.8 755,2025-06-22 00:50:00,23.5,54.5,13.8 756,2025-06-22 00:55:00,23.5,54.5,13.8 757,2025-06-22 01:00:00,23.5,54.5,13.8 758,2025-06-22 01:05:00,23.5,55.0,13.9 759,2025-06-22 01:10:00,23.5,55.0,13.9 760,2025-06-22 01:15:00,23.5,55.0,13.9 761,2025-06-22 01:20:00,23.5,55.5,14.1 762,2025-06-22 01:25:00,23.5,55.0,13.9 763,2025-06-22 01:30:00,23.5,55.0,13.9 764,2025-06-22 01:35:00,23.5,55.0,13.9 765,2025-06-22 01:40:00,23.5,55.0,13.9 766,2025-06-22 01:45:00,23.5,55.0,13.9 767,2025-06-22 01:50:00,23.5,55.0,13.9 768,2025-06-22 01:55:00,23.5,55.0,13.9 769,2025-06-22 02:00:00,23.5,55.0,13.9 770,2025-06-22 02:05:00,23.5,55.0,13.9 771,2025-06-22 02:10:00,23.5,55.0,13.9 772,2025-06-22 02:15:00,23.5,55.0,13.9 773,2025-06-22 02:20:00,23.5,55.0,13.9 774,2025-06-22 02:25:00,23.5,55.0,13.9 775,2025-06-22 02:30:00,23.5,55.0,13.9 776,2025-06-22 02:35:00,23.5,55.0,13.9 777,2025-06-22 02:40:00,23.5,55.0,13.9 778,2025-06-22 02:45:00,23.5,55.0,13.9 779,2025-06-22 02:50:00,23.5,55.0,13.9 780,2025-06-22 02:55:00,23.5,55.5,14.1 781,2025-06-22 03:00:00,23.5,55.5,14.1 782,2025-06-22 03:05:00,23.5,55.5,14.1 783,2025-06-22 03:10:00,23.5,55.5,14.1 784,2025-06-22 03:15:00,23.5,55.0,13.9 785,2025-06-22 03:20:00,23.5,55.0,13.9 786,2025-06-22 03:25:00,23.5,55.0,13.9 787,2025-06-22 03:30:00,23.5,55.0,13.9 788,2025-06-22 03:35:00,23.5,55.0,13.9 789,2025-06-22 03:40:00,23.5,55.0,13.9 790,2025-06-22 03:45:00,23.5,55.0,13.9 791,2025-06-22 03:50:00,23.5,55.0,13.9 792,2025-06-22 03:55:00,23.5,55.0,13.9 793,2025-06-22 04:00:00,23.5,55.0,13.9 794,2025-06-22 04:05:00,23.5,55.0,13.9 795,2025-06-22 04:10:00,23.5,55.0,13.9 796,2025-06-22 04:15:00,23.5,55.5,14.1 797,2025-06-22 04:20:00,23.5,55.5,14.1 798,2025-06-22 04:25:00,23.5,55.5,14.1 799,2025-06-22 04:30:00,23.5,55.5,14.1 800,2025-06-22 04:35:00,23.5,55.0,13.9 801,2025-06-22 04:40:00,23.5,55.0,13.9 802,2025-06-22 04:45:00,23.5,55.0,13.9 803,2025-06-22 04:50:00,23.5,55.0,13.9 804,2025-06-22 04:55:00,23.5,55.0,13.9 805,2025-06-22 05:00:00,23.5,55.0,13.9 806,2025-06-22 05:05:00,23.5,55.0,13.9 807,2025-06-22 05:10:00,23.5,55.5,14.1 808,2025-06-22 05:15:00,23.5,55.0,13.9 809,2025-06-22 05:20:00,23.5,55.0,13.9 810,2025-06-22 05:25:00,23.5,55.0,13.9 811,2025-06-22 05:30:00,23.5,55.0,13.9 812,2025-06-22 05:35:00,23.5,55.0,13.9 813,2025-06-22 05:40:00,23.5,55.0,13.9 814,2025-06-22 05:45:00,23.5,55.0,13.9 815,2025-06-22 05:50:00,23.5,55.5,14.1 816,2025-06-22 05:55:00,23.5,55.5,14.1 817,2025-06-22 06:00:00,23.5,55.5,14.1 818,2025-06-22 06:05:00,23.5,55.5,14.1 819,2025-06-22 06:10:00,23.5,55.5,14.1 820,2025-06-22 06:15:00,23.5,55.5,14.1 821,2025-06-22 06:20:00,23.5,55.0,13.9 822,2025-06-22 06:25:00,23.5,55.0,13.9 823,2025-06-22 06:30:00,23.5,55.0,13.9 824,2025-06-22 06:35:00,23.5,55.0,13.9 825,2025-06-22 06:40:00,23.5,55.0,13.9 826,2025-06-22 06:45:00,23.5,55.5,14.1 827,2025-06-22 06:50:00,23.5,55.0,13.9 828,2025-06-22 06:55:00,23.5,55.0,13.9 829,2025-06-22 07:00:00,23.5,55.0,13.9 830,2025-06-22 07:05:00,23.5,55.0,13.9 831,2025-06-22 07:10:00,23.5,55.5,14.1 832,2025-06-22 07:15:00,23.5,55.5,14.1 833,2025-06-22 07:20:00,23.5,55.5,14.1 834,2025-06-22 07:25:00,23.5,55.5,14.1 835,2025-06-22 07:30:00,23.5,55.5,14.1 836,2025-06-22 07:35:00,24.0,55.5,14.5 837,2025-06-22 07:40:00,23.5,55.0,13.9 838,2025-06-22 07:45:00,23.5,55.0,13.9 839,2025-06-22 07:50:00,23.5,55.0,13.9 840,2025-06-22 07:55:00,23.5,55.0,13.9 841,2025-06-22 08:00:00,23.5,55.5,14.1 842,2025-06-22 08:05:00,23.5,55.0,13.9 843,2025-06-22 08:10:00,23.5,55.0,13.9 844,2025-06-22 08:15:00,23.5,55.5,14.1 845,2025-06-22 08:20:00,23.5,55.5,14.1 846,2025-06-22 08:25:00,23.5,55.0,13.9 847,2025-06-22 08:30:00,23.5,55.0,13.9 848,2025-06-22 08:35:00,23.5,55.0,13.9 849,2025-06-22 08:40:00,23.5,55.5,14.1 850,2025-06-22 08:45:00,23.5,55.5,14.1 851,2025-06-22 08:50:00,23.5,55.5,14.1 852,2025-06-22 08:55:00,23.5,55.5,14.1 853,2025-06-22 09:00:00,23.5,55.5,14.1 854,2025-06-22 09:05:00,23.5,55.5,14.1 855,2025-06-22 09:10:00,23.5,55.5,14.1 856,2025-06-22 09:15:00,23.5,55.5,14.1 857,2025-06-22 09:20:00,23.5,55.5,14.1 858,2025-06-22 09:25:00,23.5,55.5,14.1 859,2025-06-22 09:30:00,23.5,55.5,14.1 860,2025-06-22 09:35:00,23.5,55.5,14.1 861,2025-06-22 09:40:00,23.5,55.5,14.1 862,2025-06-22 09:45:00,23.5,55.5,14.1 863,2025-06-22 09:50:00,23.5,55.5,14.1 864,2025-06-22 09:55:00,23.5,55.5,14.1 865,2025-06-22 10:00:00,23.5,55.5,14.1 866,2025-06-22 10:05:00,23.5,55.5,14.1 867,2025-06-22 10:10:00,23.5,55.5,14.1 868,2025-06-22 10:15:00,23.5,55.5,14.1 869,2025-06-22 10:20:00,23.5,55.5,14.1 870,2025-06-22 10:25:00,23.5,55.5,14.1 871,2025-06-22 10:30:00,23.5,55.5,14.1 872,2025-06-22 10:35:00,24.0,55.5,14.5 873,2025-06-22 10:40:00,24.0,55.5,14.5 874,2025-06-22 10:45:00,23.5,55.5,14.1 875,2025-06-22 10:50:00,23.5,55.5,14.1 876,2025-06-22 10:55:00,23.5,55.5,14.1 877,2025-06-22 11:00:00,23.5,55.5,14.1 878,2025-06-22 11:05:00,23.5,55.5,14.1 879,2025-06-22 11:10:00,23.5,55.5,14.1 880,2025-06-22 11:15:00,23.5,55.5,14.1 881,2025-06-22 11:20:00,23.5,55.5,14.1 882,2025-06-22 11:25:00,23.5,56.0,14.2 883,2025-06-22 11:30:00,23.5,55.5,14.1 884,2025-06-22 11:35:00,23.5,56.0,14.2 885,2025-06-22 11:40:00,23.5,55.5,14.1 886,2025-06-22 11:45:00,23.5,56.0,14.2 887,2025-06-22 11:50:00,23.5,56.0,14.2 888,2025-06-22 11:55:00,23.5,56.5,14.4 889,2025-06-22 12:00:00,23.5,56.5,14.4 890,2025-06-22 12:05:00,23.5,56.0,14.2 891,2025-06-22 12:10:00,23.5,56.0,14.2 892,2025-06-22 12:15:00,23.5,56.0,14.2 893,2025-06-22 12:20:00,23.5,56.0,14.2 894,2025-06-22 12:25:00,23.5,56.0,14.2 895,2025-06-22 12:30:00,23.5,56.0,14.2 896,2025-06-22 12:35:00,23.5,56.0,14.2 897,2025-06-22 12:40:00,23.5,56.0,14.2 898,2025-06-22 12:45:00,23.5,56.0,14.2 899,2025-06-22 12:50:00,23.5,56.0,14.2 900,2025-06-22 12:55:00,23.5,56.0,14.2 901,2025-06-22 13:00:00,23.5,56.0,14.2 902,2025-06-22 13:05:00,23.5,56.0,14.2 903,2025-06-22 13:10:00,23.5,56.0,14.2 904,2025-06-22 13:15:00,24.0,56.5,14.8 905,2025-06-22 13:20:00,24.0,56.5,14.8 906,2025-06-22 13:25:00,24.0,56.5,14.8 907,2025-06-22 13:30:00,24.0,56.5,14.8 908,2025-06-22 13:35:00,24.0,56.5,14.8 909,2025-06-22 13:40:00,24.0,56.5,14.8 910,2025-06-22 13:45:00,24.0,56.5,14.8 911,2025-06-22 13:50:00,24.0,56.5,14.8 912,2025-06-22 13:55:00,23.5,56.5,14.4 913,2025-06-22 14:00:00,23.5,56.5,14.4 914,2025-06-22 14:05:00,23.5,56.5,14.4 915,2025-06-22 14:10:00,23.5,56.5,14.4 916,2025-06-22 14:15:00,23.5,56.5,14.4 917,2025-06-22 14:20:00,23.5,56.5,14.4 918,2025-06-22 14:25:00,23.5,56.5,14.4 919,2025-06-22 14:30:00,23.5,56.5,14.4 920,2025-06-22 14:35:00,23.5,56.5,14.4 921,2025-06-22 14:40:00,23.5,56.5,14.4 922,2025-06-22 14:45:00,23.5,56.5,14.4 923,2025-06-22 14:50:00,23.5,56.5,14.4 924,2025-06-22 14:55:00,23.5,57.0,14.5 925,2025-06-22 15:00:00,23.5,56.5,14.4 926,2025-06-22 15:05:00,23.5,57.0,14.5 927,2025-06-22 15:10:00,23.5,56.5,14.4 928,2025-06-22 15:15:00,23.5,56.5,14.4 929,2025-06-22 15:20:00,23.5,56.5,14.4 930,2025-06-22 15:25:00,23.5,56.5,14.4 931,2025-06-22 15:30:00,23.5,56.5,14.4 932,2025-06-22 15:35:00,23.5,56.5,14.4 933,2025-06-22 15:40:00,23.5,56.5,14.4 934,2025-06-22 15:45:00,23.5,56.5,14.4 935,2025-06-22 15:50:00,23.5,56.5,14.4 936,2025-06-22 15:55:00,23.5,56.5,14.4 937,2025-06-22 16:00:00,23.5,56.5,14.4 938,2025-06-22 16:05:00,23.5,56.5,14.4 939,2025-06-22 16:10:00,23.5,56.5,14.4 940,2025-06-22 16:15:00,24.0,57.0,15.0 941,2025-06-22 16:20:00,24.0,57.0,15.0 942,2025-06-22 16:25:00,24.0,56.5,14.8 943,2025-06-22 16:30:00,24.0,56.5,14.8 944,2025-06-22 16:35:00,24.0,56.5,14.8 945,2025-06-22 16:40:00,24.0,56.5,14.8 946,2025-06-22 16:45:00,24.0,56.5,14.8 947,2025-06-22 16:50:00,24.0,56.5,14.8 948,2025-06-22 16:55:00,24.0,56.5,14.8 949,2025-06-22 17:00:00,23.5,56.5,14.4 950,2025-06-22 17:05:00,24.0,56.5,14.8 951,2025-06-22 17:10:00,23.5,56.5,14.4 952,2025-06-22 17:15:00,23.5,56.5,14.4 953,2025-06-22 17:20:00,23.5,56.5,14.4 954,2025-06-22 17:25:00,23.5,56.5,14.4 955,2025-06-22 17:30:00,23.5,56.5,14.4 956,2025-06-22 17:35:00,23.5,56.5,14.4 957,2025-06-22 17:40:00,23.5,56.5,14.4 958,2025-06-22 17:45:00,23.5,56.5,14.4 959,2025-06-22 17:50:00,23.5,56.5,14.4 960,2025-06-22 17:55:00,23.5,57.0,14.5 961,2025-06-22 18:00:00,23.5,57.0,14.5 962,2025-06-22 18:05:00,23.5,57.0,14.5 963,2025-06-22 18:10:00,23.5,57.0,14.5 964,2025-06-22 18:15:00,24.0,56.5,14.8 965,2025-06-22 18:20:00,24.0,56.5,14.8 966,2025-06-22 18:25:00,24.0,56.5,14.8 967,2025-06-22 18:30:00,23.5,56.5,14.4 968,2025-06-22 18:35:00,23.5,56.5,14.4 969,2025-06-22 18:40:00,23.5,56.5,14.4 970,2025-06-22 18:45:00,23.5,56.5,14.4 971,2025-06-22 18:50:00,23.5,56.5,14.4 972,2025-06-22 18:55:00,23.5,56.5,14.4 973,2025-06-22 19:00:00,23.5,56.5,14.4 974,2025-06-22 19:05:00,23.5,56.5,14.4 975,2025-06-22 19:10:00,24.0,56.5,14.8 976,2025-06-22 19:15:00,24.0,56.5,14.8 977,2025-06-22 19:20:00,24.0,56.5,14.8 978,2025-06-22 19:25:00,24.0,56.5,14.8 979,2025-06-22 19:30:00,24.0,56.5,14.8 980,2025-06-22 19:35:00,24.0,56.5,14.8 981,2025-06-22 19:40:00,24.0,56.5,14.8 982,2025-06-22 19:45:00,24.0,56.5,14.8 983,2025-06-22 19:50:00,24.0,56.5,14.8 984,2025-06-22 19:55:00,24.0,56.5,14.8 985,2025-06-22 20:00:00,24.0,56.5,14.8 986,2025-06-22 20:05:00,24.0,56.5,14.8 987,2025-06-22 20:10:00,24.0,56.5,14.8 988,2025-06-22 20:15:00,23.5,56.5,14.4 989,2025-06-22 20:20:00,23.5,56.5,14.4 990,2025-06-22 20:25:00,23.5,56.5,14.4 991,2025-06-22 20:30:00,23.5,56.5,14.4 992,2025-06-22 20:35:00,23.5,56.5,14.4 993,2025-06-22 20:40:00,23.5,56.5,14.4 994,2025-06-22 20:45:00,23.5,56.5,14.4 995,2025-06-22 20:50:00,23.5,56.5,14.4 996,2025-06-22 20:55:00,24.0,56.5,14.8 997,2025-06-22 21:00:00,24.0,56.5,14.8 998,2025-06-22 21:05:00,24.0,56.5,14.8 999,2025-06-22 21:10:00,24.0,56.5,14.8 1000,2025-06-22 21:15:00,24.0,56.5,14.8 Sigima-1.1.1/sigima/data/tests/curve_formats/dynamic_parameters.txt000066400000000000000000003562171514013333200255470ustar00rootroot000000000000001.0000000e-010 1.7274961e-002 2.0000000e-010 3.7523794e-002 3.0000000e-010 5.3942700e-002 4.0000000e-010 6.8461917e-002 5.0000000e-010 8.1520120e-002 6.0000000e-010 1.0173202e-001 7.0000000e-010 1.1542831e-001 8.0000000e-010 1.3726969e-001 9.0000000e-010 1.4687884e-001 1.0000000e-009 1.6591337e-001 1.1000000e-009 1.8345873e-001 1.2000000e-009 1.9336629e-001 1.3000000e-009 2.1372385e-001 1.4000000e-009 2.2785835e-001 1.5000000e-009 2.3989954e-001 1.6000000e-009 2.5545600e-001 1.7000000e-009 2.7301975e-001 1.8000000e-009 2.8760731e-001 1.9000000e-009 2.9987573e-001 2.0000000e-009 3.1105288e-001 2.1000000e-009 3.2487617e-001 2.2000000e-009 3.3510852e-001 2.3000000e-009 3.4517733e-001 2.4000000e-009 3.5414587e-001 2.5000000e-009 3.6871117e-001 2.6000000e-009 3.7012684e-001 2.7000000e-009 3.8131970e-001 2.8000000e-009 4.0046291e-001 2.9000000e-009 4.0520233e-001 3.0000000e-009 4.1099540e-001 3.1000000e-009 4.2643237e-001 3.2000000e-009 4.2893179e-001 3.3000000e-009 4.3911078e-001 3.4000000e-009 4.4359998e-001 3.5000000e-009 4.5038612e-001 3.6000000e-009 4.5730721e-001 3.7000000e-009 4.6250408e-001 3.8000000e-009 4.7187484e-001 3.9000000e-009 4.7892280e-001 4.0000000e-009 4.7422145e-001 4.1000000e-009 4.8337065e-001 4.2000000e-009 4.8810957e-001 4.3000000e-009 4.9385828e-001 4.4000000e-009 4.8660778e-001 4.5000000e-009 4.9369554e-001 4.6000000e-009 4.9009919e-001 4.7000000e-009 4.9420104e-001 4.8000000e-009 4.9748447e-001 4.9000000e-009 4.9503544e-001 5.0000000e-009 4.9665545e-001 5.1000000e-009 4.9329277e-001 5.2000000e-009 4.9121695e-001 5.3000000e-009 4.9411582e-001 5.4000000e-009 4.9526644e-001 5.5000000e-009 4.8502940e-001 5.6000000e-009 4.8340084e-001 5.7000000e-009 4.7568953e-001 5.8000000e-009 4.7761414e-001 5.9000000e-009 4.7051719e-001 6.0000000e-009 4.6771095e-001 6.1000000e-009 4.6098378e-001 6.2000000e-009 4.6169463e-001 6.3000000e-009 4.5381008e-001 6.4000000e-009 4.4434547e-001 6.5000000e-009 4.3741016e-001 6.6000000e-009 4.3158279e-001 6.7000000e-009 4.1831403e-001 6.8000000e-009 4.1465295e-001 6.9000000e-009 4.0272978e-001 7.0000000e-009 3.9963393e-001 7.1000000e-009 3.9206390e-001 7.2000000e-009 3.7671687e-001 7.3000000e-009 3.7208504e-001 7.4000000e-009 3.5492159e-001 7.5000000e-009 3.4595959e-001 7.6000000e-009 3.3429260e-001 7.7000000e-009 3.2187756e-001 7.8000000e-009 3.1322103e-001 7.9000000e-009 3.0370308e-001 8.0000000e-009 2.9099498e-001 8.1000000e-009 2.7762002e-001 8.2000000e-009 2.6437013e-001 8.3000000e-009 2.4796967e-001 8.4000000e-009 2.3542110e-001 8.5000000e-009 2.2513031e-001 8.6000000e-009 2.0445533e-001 8.7000000e-009 1.9610575e-001 8.8000000e-009 1.8481637e-001 8.9000000e-009 1.6687636e-001 9.0000000e-009 1.4924310e-001 9.1000000e-009 1.3620162e-001 9.2000000e-009 1.2536569e-001 9.3000000e-009 1.0717064e-001 9.4000000e-009 9.0283381e-002 9.5000000e-009 7.8530881e-002 9.6000000e-009 6.0689386e-002 9.7000000e-009 4.8831599e-002 9.8000000e-009 2.7478322e-002 9.9000000e-009 1.3058873e-002 1.0000000e-008 -1.2505778e-003 1.0100000e-008 -1.6666970e-002 1.0200000e-008 -3.4746627e-002 1.0300000e-008 -4.8469111e-002 1.0400000e-008 -6.7811005e-002 1.0500000e-008 -7.5120983e-002 1.0600000e-008 -9.2325804e-002 1.0700000e-008 -1.1049813e-001 1.0800000e-008 -1.2460473e-001 1.0900000e-008 -1.4175531e-001 1.1000000e-008 -1.5414669e-001 1.1100000e-008 -1.6429752e-001 1.1200000e-008 -1.8450121e-001 1.1300000e-008 -1.9630279e-001 1.1400000e-008 -2.0763904e-001 1.1500000e-008 -2.2085280e-001 1.1600000e-008 -2.3822071e-001 1.1700000e-008 -2.5053417e-001 1.1800000e-008 -2.6200128e-001 1.1900000e-008 -2.7748126e-001 1.2000000e-008 -2.9389061e-001 1.2100000e-008 -3.0108843e-001 1.2200000e-008 -3.1207275e-001 1.2300000e-008 -3.2366899e-001 1.2400000e-008 -3.3542572e-001 1.2500000e-008 -3.4422411e-001 1.2600000e-008 -3.5718422e-001 1.2700000e-008 -3.6859334e-001 1.2800000e-008 -3.7612940e-001 1.2900000e-008 -3.8477158e-001 1.3000000e-008 -3.9670442e-001 1.3100000e-008 -4.0441298e-001 1.3200000e-008 -4.0804902e-001 1.3300000e-008 -4.2326162e-001 1.3400000e-008 -4.2816928e-001 1.3500000e-008 -4.3813617e-001 1.3600000e-008 -4.4334670e-001 1.3700000e-008 -4.4737349e-001 1.3800000e-008 -4.5733426e-001 1.3900000e-008 -4.5831719e-001 1.4000000e-008 -4.6687662e-001 1.4100000e-008 -4.6673504e-001 1.4200000e-008 -4.7901614e-001 1.4300000e-008 -4.7857800e-001 1.4400000e-008 -4.7887566e-001 1.4500000e-008 -4.8732072e-001 1.4600000e-008 -4.8969188e-001 1.4700000e-008 -4.9392946e-001 1.4800000e-008 -4.9988011e-001 1.4900000e-008 -4.9453789e-001 1.5000000e-008 -4.9002262e-001 1.5100000e-008 -4.9345443e-001 1.5200000e-008 -4.9866392e-001 1.5300000e-008 -4.9347317e-001 1.5400000e-008 -4.9318245e-001 1.5500000e-008 -4.9313225e-001 1.5600000e-008 -4.9078544e-001 1.5700000e-008 -4.8763068e-001 1.5800000e-008 -4.8409745e-001 1.5900000e-008 -4.8087678e-001 1.6000000e-008 -4.7768418e-001 1.6100000e-008 -4.7422154e-001 1.6200000e-008 -4.7255826e-001 1.6300000e-008 -4.6331328e-001 1.6400000e-008 -4.6061720e-001 1.6500000e-008 -4.5151857e-001 1.6600000e-008 -4.4369855e-001 1.6700000e-008 -4.4145622e-001 1.6800000e-008 -4.3697032e-001 1.6900000e-008 -4.2484829e-001 1.7000000e-008 -4.1626865e-001 1.7100000e-008 -4.0273164e-001 1.7200000e-008 -3.9936819e-001 1.7300000e-008 -3.8730705e-001 1.7400000e-008 -3.7656485e-001 1.7500000e-008 -3.6530826e-001 1.7600000e-008 -3.5021739e-001 1.7700000e-008 -3.4054278e-001 1.7800000e-008 -3.3406362e-001 1.7900000e-008 -3.2585664e-001 1.8000000e-008 -3.1373664e-001 1.8100000e-008 -2.9558247e-001 1.8200000e-008 -2.8275078e-001 1.8300000e-008 -2.7172182e-001 1.8400000e-008 -2.5540385e-001 1.8500000e-008 -2.3545257e-001 1.8600000e-008 -2.2814190e-001 1.8700000e-008 -2.0884175e-001 1.8800000e-008 -1.9670026e-001 1.8900000e-008 -1.7602146e-001 1.9000000e-008 -1.6349515e-001 1.9100000e-008 -1.5093770e-001 1.9200000e-008 -1.3553625e-001 1.9300000e-008 -1.1577759e-001 1.9400000e-008 -9.9249785e-002 1.9500000e-008 -8.6786673e-002 1.9600000e-008 -7.0717536e-002 1.9700000e-008 -5.1359342e-002 1.9800000e-008 -3.3672006e-002 1.9900000e-008 -1.6430330e-002 2.0000000e-008 -2.9461370e-003 2.0100000e-008 1.2284282e-002 2.0200000e-008 3.0412293e-002 2.0300000e-008 4.4641882e-002 2.0400000e-008 6.5330776e-002 2.0500000e-008 8.4740865e-002 2.0600000e-008 1.0121546e-001 2.0700000e-008 1.1452262e-001 2.0800000e-008 1.2811455e-001 2.0900000e-008 1.4621270e-001 2.1000000e-008 1.6479536e-001 2.1100000e-008 1.7630831e-001 2.1200000e-008 1.9358048e-001 2.1300000e-008 2.0851003e-001 2.1400000e-008 2.2903708e-001 2.1500000e-008 2.3986454e-001 2.1600000e-008 2.4661764e-001 2.1700000e-008 2.6138296e-001 2.1800000e-008 2.7812204e-001 2.1900000e-008 2.9361581e-001 2.2000000e-008 3.0411479e-001 2.2100000e-008 3.2078855e-001 2.2200000e-008 3.3097298e-001 2.2300000e-008 3.4770221e-001 2.2400000e-008 3.5400568e-001 2.2500000e-008 3.6920612e-001 2.2600000e-008 3.7662513e-001 2.2700000e-008 3.9068552e-001 2.2800000e-008 3.9496653e-001 2.2900000e-008 4.0594464e-001 2.3000000e-008 4.1237011e-001 2.3100000e-008 4.3023116e-001 2.3200000e-008 4.2935657e-001 2.3300000e-008 4.4005120e-001 2.3400000e-008 4.4523235e-001 2.3500000e-008 4.5196567e-001 2.3600000e-008 4.6471466e-001 2.3700000e-008 4.7040830e-001 2.3800000e-008 4.7029038e-001 2.3900000e-008 4.7397869e-001 2.4000000e-008 4.7701746e-001 2.4100000e-008 4.7820677e-001 2.4200000e-008 4.8714592e-001 2.4300000e-008 4.9023529e-001 2.4400000e-008 4.9096782e-001 2.4500000e-008 4.9688105e-001 2.4600000e-008 4.9415617e-001 2.4700000e-008 4.9428566e-001 2.4800000e-008 4.9640930e-001 2.4900000e-008 4.9712607e-001 2.5000000e-008 4.9319010e-001 2.5100000e-008 4.9679737e-001 2.5200000e-008 4.9364986e-001 2.5300000e-008 4.9131794e-001 2.5400000e-008 4.8937658e-001 2.5500000e-008 4.8495508e-001 2.5600000e-008 4.8481149e-001 2.5700000e-008 4.7696241e-001 2.5800000e-008 4.7648527e-001 2.5900000e-008 4.7328605e-001 2.6000000e-008 4.6921844e-001 2.6100000e-008 4.6236650e-001 2.6200000e-008 4.5721273e-001 2.6300000e-008 4.5101492e-001 2.6400000e-008 4.4359470e-001 2.6500000e-008 4.3392197e-001 2.6600000e-008 4.3185285e-001 2.6700000e-008 4.1659215e-001 2.6800000e-008 4.1382267e-001 2.6900000e-008 4.0741155e-001 2.7000000e-008 4.0074368e-001 2.7100000e-008 3.8788146e-001 2.7200000e-008 3.7826726e-001 2.7300000e-008 3.7097540e-001 2.7400000e-008 3.5708941e-001 2.7500000e-008 3.4485651e-001 2.7600000e-008 3.3703671e-001 2.7700000e-008 3.2582599e-001 2.7800000e-008 3.0975141e-001 2.7900000e-008 3.0340626e-001 2.8000000e-008 2.8287905e-001 2.8100000e-008 2.7735664e-001 2.8200000e-008 2.5889129e-001 2.8300000e-008 2.4747661e-001 2.8400000e-008 2.3875498e-001 2.8500000e-008 2.2507224e-001 2.8600000e-008 2.1033311e-001 2.8700000e-008 2.0216686e-001 2.8800000e-008 1.8476694e-001 2.8900000e-008 1.6942152e-001 2.9000000e-008 1.5282135e-001 2.9100000e-008 1.3977035e-001 2.9200000e-008 1.2284773e-001 2.9300000e-008 1.0642553e-001 2.9400000e-008 9.4968701e-002 2.9500000e-008 7.4845965e-002 2.9600000e-008 6.2221912e-002 2.9700000e-008 4.5986792e-002 2.9800000e-008 2.8628977e-002 2.9900000e-008 1.3584998e-002 3.0000000e-008 1.2541509e-003 3.0100000e-008 -1.4329091e-002 3.0200000e-008 -3.1231930e-002 3.0300000e-008 -5.1981069e-002 3.0400000e-008 -5.9931155e-002 3.0500000e-008 -7.6438468e-002 3.0600000e-008 -9.2684713e-002 3.0700000e-008 -1.0991282e-001 3.0800000e-008 -1.2353616e-001 3.0900000e-008 -1.3515745e-001 3.1000000e-008 -1.4730530e-001 3.1100000e-008 -1.6575558e-001 3.1200000e-008 -1.7657475e-001 3.1300000e-008 -1.9620667e-001 3.1400000e-008 -2.1253461e-001 3.1500000e-008 -2.2159450e-001 3.1600000e-008 -2.3626122e-001 3.1700000e-008 -2.4885387e-001 3.1800000e-008 -2.6177625e-001 3.1900000e-008 -2.7570784e-001 3.2000000e-008 -2.9029645e-001 3.2100000e-008 -3.0152714e-001 3.2200000e-008 -3.1257587e-001 3.2300000e-008 -3.2248807e-001 3.2400000e-008 -3.3321810e-001 3.2500000e-008 -3.5012232e-001 3.2600000e-008 -3.5435208e-001 3.2700000e-008 -3.6790374e-001 3.2800000e-008 -3.8078221e-001 3.2900000e-008 -3.8559004e-001 3.3000000e-008 -4.0269715e-001 3.3100000e-008 -3.9963128e-001 3.3200000e-008 -4.1337251e-001 3.3300000e-008 -4.2600490e-001 3.3400000e-008 -4.3636366e-001 3.3500000e-008 -4.3871444e-001 3.3600000e-008 -4.4292574e-001 3.3700000e-008 -4.4142156e-001 3.3800000e-008 -4.5542423e-001 3.3900000e-008 -4.6452017e-001 3.4000000e-008 -4.6796918e-001 3.4100000e-008 -4.6671493e-001 3.4200000e-008 -4.7927765e-001 3.4300000e-008 -4.8597988e-001 3.4400000e-008 -4.8419331e-001 3.4500000e-008 -4.8595016e-001 3.4600000e-008 -4.8478856e-001 3.4700000e-008 -4.9281848e-001 3.4800000e-008 -4.9146688e-001 3.4900000e-008 -4.9117397e-001 3.5000000e-008 -4.9151580e-001 3.5100000e-008 -4.9220645e-001 3.5200000e-008 -4.9468052e-001 3.5300000e-008 -4.9345069e-001 3.5400000e-008 -4.9748301e-001 3.5500000e-008 -5.0011387e-001 3.5600000e-008 -4.8888027e-001 3.5700000e-008 -4.8459158e-001 3.5800000e-008 -4.8698395e-001 3.5900000e-008 -4.8141933e-001 3.6000000e-008 -4.7768236e-001 3.6100000e-008 -4.7259276e-001 3.6200000e-008 -4.7334202e-001 3.6300000e-008 -4.6155226e-001 3.6400000e-008 -4.6157503e-001 3.6500000e-008 -4.5493661e-001 3.6600000e-008 -4.4737454e-001 3.6700000e-008 -4.3626820e-001 3.6800000e-008 -4.2732875e-001 3.6900000e-008 -4.1883946e-001 3.7000000e-008 -4.2037426e-001 3.7100000e-008 -4.0412323e-001 3.7200000e-008 -3.9647729e-001 3.7300000e-008 -3.8662870e-001 3.7400000e-008 -3.7700843e-001 3.7500000e-008 -3.6331800e-001 3.7600000e-008 -3.5230933e-001 3.7700000e-008 -3.4542181e-001 3.7800000e-008 -3.3231741e-001 3.7900000e-008 -3.2271170e-001 3.8000000e-008 -3.0652066e-001 3.8100000e-008 -2.9378586e-001 3.8200000e-008 -2.8152615e-001 3.8300000e-008 -2.6770047e-001 3.8400000e-008 -2.5648656e-001 3.8500000e-008 -2.3436825e-001 3.8600000e-008 -2.2741140e-001 3.8700000e-008 -2.0806726e-001 3.8800000e-008 -1.9755642e-001 3.8900000e-008 -1.8122308e-001 3.9000000e-008 -1.6764551e-001 3.9100000e-008 -1.4635162e-001 3.9200000e-008 -1.2955244e-001 3.9300000e-008 -1.1840963e-001 3.9400000e-008 -1.0243483e-001 3.9500000e-008 -8.1601831e-002 3.9600000e-008 -6.8089000e-002 3.9700000e-008 -5.2158158e-002 3.9800000e-008 -2.7800151e-002 3.9900000e-008 -1.4691840e-002 4.0000000e-008 -1.1641137e-003 4.0100000e-008 1.1999890e-002 4.0200000e-008 3.2882793e-002 4.0300000e-008 4.7688536e-002 4.0400000e-008 6.7992299e-002 4.0500000e-008 8.5466672e-002 4.0600000e-008 9.9128758e-002 4.0700000e-008 1.1759001e-001 4.0800000e-008 1.3134888e-001 4.0900000e-008 1.5089656e-001 4.1000000e-008 1.6535071e-001 4.1100000e-008 1.8440231e-001 4.1200000e-008 1.9995674e-001 4.1300000e-008 2.1077798e-001 4.1400000e-008 2.2243165e-001 4.1500000e-008 2.4232075e-001 4.1600000e-008 2.5536138e-001 4.1700000e-008 2.7413689e-001 4.1800000e-008 2.7538773e-001 4.1900000e-008 2.9131296e-001 4.2000000e-008 3.1472941e-001 4.2100000e-008 3.1808155e-001 4.2200000e-008 3.2698633e-001 4.2300000e-008 3.4366655e-001 4.2400000e-008 3.5706191e-001 4.2500000e-008 3.6787493e-001 4.2600000e-008 3.7625458e-001 4.2700000e-008 3.9099161e-001 4.2800000e-008 3.9715738e-001 4.2900000e-008 4.0680654e-001 4.3000000e-008 4.1515619e-001 4.3100000e-008 4.2288091e-001 4.3200000e-008 4.3534560e-001 4.3300000e-008 4.4204860e-001 4.3400000e-008 4.4809074e-001 4.3500000e-008 4.5585836e-001 4.3600000e-008 4.6208157e-001 4.3700000e-008 4.5994549e-001 4.3800000e-008 4.6564093e-001 4.3900000e-008 4.8150607e-001 4.4000000e-008 4.8382390e-001 4.4100000e-008 4.8414010e-001 4.4200000e-008 4.8871810e-001 4.4300000e-008 4.8877114e-001 4.4400000e-008 4.8976201e-001 4.4500000e-008 4.9101124e-001 4.4600000e-008 4.8975817e-001 4.4700000e-008 4.9375651e-001 4.4800000e-008 4.9626118e-001 4.4900000e-008 4.9979316e-001 4.5000000e-008 4.9020198e-001 4.5100000e-008 4.9830785e-001 4.5200000e-008 4.8885957e-001 4.5300000e-008 4.9428844e-001 4.5400000e-008 4.8716744e-001 4.5500000e-008 4.8324927e-001 4.5600000e-008 4.9010054e-001 4.5700000e-008 4.8291082e-001 4.5800000e-008 4.7514876e-001 4.5900000e-008 4.7508744e-001 4.6000000e-008 4.6618528e-001 4.6100000e-008 4.6363032e-001 4.6200000e-008 4.5582082e-001 4.6300000e-008 4.5290593e-001 4.6400000e-008 4.4534492e-001 4.6500000e-008 4.3952752e-001 4.6600000e-008 4.2909376e-001 4.6700000e-008 4.2876769e-001 4.6800000e-008 4.1334322e-001 4.6900000e-008 4.0540874e-001 4.7000000e-008 3.9769088e-001 4.7100000e-008 3.8493850e-001 4.7200000e-008 3.7702157e-001 4.7300000e-008 3.6811836e-001 4.7400000e-008 3.5903157e-001 4.7500000e-008 3.4932003e-001 4.7600000e-008 3.3391903e-001 4.7700000e-008 3.2555295e-001 4.7800000e-008 3.1100499e-001 4.7900000e-008 2.9846533e-001 4.8000000e-008 2.9222925e-001 4.8100000e-008 2.7806766e-001 4.8200000e-008 2.6649545e-001 4.8300000e-008 2.4455383e-001 4.8400000e-008 2.3174904e-001 4.8500000e-008 2.2295290e-001 4.8600000e-008 2.0976228e-001 4.8700000e-008 1.9657661e-001 4.8800000e-008 1.7834090e-001 4.8900000e-008 1.7144929e-001 4.9000000e-008 1.5215266e-001 4.9100000e-008 1.3782925e-001 4.9200000e-008 1.1689361e-001 4.9300000e-008 1.0867211e-001 4.9400000e-008 9.5686027e-002 4.9500000e-008 7.8222040e-002 4.9600000e-008 6.1501950e-002 4.9700000e-008 4.7947947e-002 4.9800000e-008 3.2219135e-002 4.9900000e-008 1.7597048e-002 5.0000000e-008 1.6814541e-003 5.0100000e-008 -1.5895434e-002 5.0200000e-008 -3.1627493e-002 5.0300000e-008 -4.9168553e-002 5.0400000e-008 -6.0494315e-002 5.0500000e-008 -7.7159573e-002 5.0600000e-008 -9.0450736e-002 5.0700000e-008 -1.0736936e-001 5.0800000e-008 -1.2393823e-001 5.0900000e-008 -1.3411733e-001 5.1000000e-008 -1.5130556e-001 5.1100000e-008 -1.6689822e-001 5.1200000e-008 -1.7789337e-001 5.1300000e-008 -1.9314776e-001 5.1400000e-008 -2.0747341e-001 5.1500000e-008 -2.2061611e-001 5.1600000e-008 -2.3762388e-001 5.1700000e-008 -2.5497674e-001 5.1800000e-008 -2.6707186e-001 5.1900000e-008 -2.7762348e-001 5.2000000e-008 -2.9994126e-001 5.2100000e-008 -3.0464279e-001 5.2200000e-008 -3.1241479e-001 5.2300000e-008 -3.2174742e-001 5.2400000e-008 -3.3737459e-001 5.2500000e-008 -3.4913695e-001 5.2600000e-008 -3.5844415e-001 5.2700000e-008 -3.6769321e-001 5.2800000e-008 -3.7553122e-001 5.2900000e-008 -3.9037748e-001 5.3000000e-008 -3.9857531e-001 5.3100000e-008 -4.0190233e-001 5.3200000e-008 -4.1394287e-001 5.3300000e-008 -4.2067725e-001 5.3400000e-008 -4.2558223e-001 5.3500000e-008 -4.3409126e-001 5.3600000e-008 -4.4116771e-001 5.3700000e-008 -4.5368277e-001 5.3800000e-008 -4.5528878e-001 5.3900000e-008 -4.6396600e-001 5.4000000e-008 -4.6385869e-001 5.4100000e-008 -4.7285181e-001 5.4200000e-008 -4.7014662e-001 5.4300000e-008 -4.8018504e-001 5.4400000e-008 -4.8576511e-001 5.4500000e-008 -4.8803262e-001 5.4600000e-008 -4.9120992e-001 5.4700000e-008 -4.9489510e-001 5.4800000e-008 -4.9318957e-001 5.4900000e-008 -4.9213323e-001 5.5000000e-008 -4.9183746e-001 5.5100000e-008 -5.0148879e-001 5.5200000e-008 -4.9675486e-001 5.5300000e-008 -4.9436400e-001 5.5400000e-008 -4.9206419e-001 5.5500000e-008 -4.9316708e-001 5.5600000e-008 -4.9509413e-001 5.5700000e-008 -4.8953931e-001 5.5800000e-008 -4.7898768e-001 5.5900000e-008 -4.8350766e-001 5.6000000e-008 -4.7757476e-001 5.6100000e-008 -4.7396396e-001 5.6200000e-008 -4.6951650e-001 5.6300000e-008 -4.6458073e-001 5.6400000e-008 -4.6070505e-001 5.6500000e-008 -4.5243669e-001 5.6600000e-008 -4.4487269e-001 5.6700000e-008 -4.4120186e-001 5.6800000e-008 -4.3232620e-001 5.6900000e-008 -4.2582829e-001 5.7000000e-008 -4.1088626e-001 5.7100000e-008 -4.0870935e-001 5.7200000e-008 -3.9919761e-001 5.7300000e-008 -3.8720759e-001 5.7400000e-008 -3.7628243e-001 5.7500000e-008 -3.6441643e-001 5.7600000e-008 -3.5676169e-001 5.7700000e-008 -3.4696036e-001 5.7800000e-008 -3.3780775e-001 5.7900000e-008 -3.1975337e-001 5.8000000e-008 -3.0825682e-001 5.8100000e-008 -2.9627497e-001 5.8200000e-008 -2.8637055e-001 5.8300000e-008 -2.6876036e-001 5.8400000e-008 -2.5069102e-001 5.8500000e-008 -2.4224500e-001 5.8600000e-008 -2.2391962e-001 5.8700000e-008 -2.1089581e-001 5.8800000e-008 -1.9855905e-001 5.8900000e-008 -1.8882970e-001 5.9000000e-008 -1.6856476e-001 5.9100000e-008 -1.5035950e-001 5.9200000e-008 -1.3514496e-001 5.9300000e-008 -1.1836208e-001 5.9400000e-008 -9.9724503e-002 5.9500000e-008 -8.2210369e-002 5.9600000e-008 -6.9432522e-002 5.9700000e-008 -4.9885593e-002 5.9800000e-008 -3.0462770e-002 5.9900000e-008 -1.5888122e-002 6.0000000e-008 -5.8179781e-005 6.0100000e-008 1.8756309e-002 6.0200000e-008 3.1958847e-002 6.0300000e-008 4.8347084e-002 6.0400000e-008 6.6276207e-002 6.0500000e-008 8.5292928e-002 6.0600000e-008 1.0033384e-001 6.0700000e-008 1.1719682e-001 6.0800000e-008 1.3403916e-001 6.0900000e-008 1.5083948e-001 6.1000000e-008 1.6712447e-001 6.1100000e-008 1.7441980e-001 6.1200000e-008 1.9554122e-001 6.1300000e-008 2.0945672e-001 6.1400000e-008 2.2293501e-001 6.1500000e-008 2.4433136e-001 6.1600000e-008 2.5802141e-001 6.1700000e-008 2.7140068e-001 6.1800000e-008 2.8584084e-001 6.1900000e-008 2.9230597e-001 6.2000000e-008 3.0745569e-001 6.2100000e-008 3.2307166e-001 6.2200000e-008 3.2981389e-001 6.2300000e-008 3.4209931e-001 6.2400000e-008 3.5814458e-001 6.2500000e-008 3.7165803e-001 6.2600000e-008 3.7833156e-001 6.2700000e-008 3.8128575e-001 6.2800000e-008 3.9734140e-001 6.2900000e-008 4.0633563e-001 6.3000000e-008 4.1372326e-001 6.3100000e-008 4.2294292e-001 6.3200000e-008 4.2909958e-001 6.3300000e-008 4.3784397e-001 6.3400000e-008 4.4611938e-001 6.3500000e-008 4.5028921e-001 6.3600000e-008 4.5231621e-001 6.3700000e-008 4.6692449e-001 6.3800000e-008 4.7017154e-001 6.3900000e-008 4.7277398e-001 6.4000000e-008 4.7521346e-001 6.4100000e-008 4.9062625e-001 6.4200000e-008 4.8450812e-001 6.4300000e-008 4.8543784e-001 6.4400000e-008 4.8985022e-001 6.4500000e-008 4.8859824e-001 6.4600000e-008 4.9113661e-001 6.4700000e-008 4.9587989e-001 6.4800000e-008 4.9192931e-001 6.4900000e-008 4.9913817e-001 6.5000000e-008 5.0050802e-001 6.5100000e-008 4.9619412e-001 6.5200000e-008 4.9394063e-001 6.5300000e-008 4.9002006e-001 6.5400000e-008 4.9100492e-001 6.5500000e-008 4.8851495e-001 6.5600000e-008 4.7831475e-001 6.5700000e-008 4.7639931e-001 6.5800000e-008 4.7785570e-001 6.5900000e-008 4.6636298e-001 6.6000000e-008 4.6662643e-001 6.6100000e-008 4.6035393e-001 6.6200000e-008 4.5917608e-001 6.6300000e-008 4.5047666e-001 6.6400000e-008 4.4424487e-001 6.6500000e-008 4.3481332e-001 6.6600000e-008 4.3148986e-001 6.6700000e-008 4.2369885e-001 6.6800000e-008 4.1667907e-001 6.6900000e-008 4.0883775e-001 6.7000000e-008 3.9786874e-001 6.7100000e-008 3.8919047e-001 6.7200000e-008 3.7577791e-001 6.7300000e-008 3.6686258e-001 6.7400000e-008 3.6012135e-001 6.7500000e-008 3.5111139e-001 6.7600000e-008 3.3389404e-001 6.7700000e-008 3.2475006e-001 6.7800000e-008 3.1089495e-001 6.7900000e-008 2.9888591e-001 6.8000000e-008 2.9279883e-001 6.8100000e-008 2.7553783e-001 6.8200000e-008 2.6435430e-001 6.8300000e-008 2.5175256e-001 6.8400000e-008 2.3553597e-001 6.8500000e-008 2.2813235e-001 6.8600000e-008 2.0341407e-001 6.8700000e-008 1.9205278e-001 6.8800000e-008 1.8515973e-001 6.8900000e-008 1.6555290e-001 6.9000000e-008 1.5198220e-001 6.9100000e-008 1.3993436e-001 6.9200000e-008 1.2524940e-001 6.9300000e-008 1.1331760e-001 6.9400000e-008 9.2262229e-002 6.9500000e-008 8.0048893e-002 6.9600000e-008 6.2029513e-002 6.9700000e-008 4.9557001e-002 6.9800000e-008 3.3436453e-002 6.9900000e-008 1.0845635e-002 7.0000000e-008 5.0572049e-003 7.0100000e-008 -1.8693799e-002 7.0200000e-008 -3.3098569e-002 7.0300000e-008 -4.3214463e-002 7.0400000e-008 -6.0784956e-002 7.0500000e-008 -7.8619829e-002 7.0600000e-008 -9.4339564e-002 7.0700000e-008 -1.0902702e-001 7.0800000e-008 -1.2383186e-001 7.0900000e-008 -1.3784630e-001 7.1000000e-008 -1.5242996e-001 7.1100000e-008 -1.6872368e-001 7.1200000e-008 -1.7809290e-001 7.1300000e-008 -1.9412676e-001 7.1400000e-008 -2.1300469e-001 7.1500000e-008 -2.2847352e-001 7.1600000e-008 -2.4082642e-001 7.1700000e-008 -2.5325522e-001 7.1800000e-008 -2.5733883e-001 7.1900000e-008 -2.7692807e-001 7.2000000e-008 -2.9355755e-001 7.2100000e-008 -3.0265912e-001 7.2200000e-008 -3.1300201e-001 7.2300000e-008 -3.2344356e-001 7.2400000e-008 -3.3891839e-001 7.2500000e-008 -3.5103614e-001 7.2600000e-008 -3.5600991e-001 7.2700000e-008 -3.6752028e-001 7.2800000e-008 -3.7909566e-001 7.2900000e-008 -3.8488404e-001 7.3000000e-008 -3.9831415e-001 7.3100000e-008 -4.0677270e-001 7.3200000e-008 -4.1131190e-001 7.3300000e-008 -4.2666224e-001 7.3400000e-008 -4.2855131e-001 7.3500000e-008 -4.3277578e-001 7.3600000e-008 -4.3963484e-001 7.3700000e-008 -4.5067952e-001 7.3800000e-008 -4.5560060e-001 7.3900000e-008 -4.6176318e-001 7.4000000e-008 -4.6516826e-001 7.4100000e-008 -4.6957853e-001 7.4200000e-008 -4.8008619e-001 7.4300000e-008 -4.7935764e-001 7.4400000e-008 -4.8228465e-001 7.4500000e-008 -4.8228477e-001 7.4600000e-008 -4.8997101e-001 7.4700000e-008 -4.9310167e-001 7.4800000e-008 -4.9006381e-001 7.4900000e-008 -4.8842253e-001 7.5000000e-008 -4.9434963e-001 7.5100000e-008 -4.9333545e-001 7.5200000e-008 -4.9605411e-001 7.5300000e-008 -4.9607009e-001 7.5400000e-008 -4.9142032e-001 7.5500000e-008 -4.9089997e-001 7.5600000e-008 -4.9686434e-001 7.5700000e-008 -4.9131834e-001 7.5800000e-008 -4.8457191e-001 7.5900000e-008 -4.7900910e-001 7.6000000e-008 -4.7279140e-001 7.6100000e-008 -4.7703235e-001 7.6200000e-008 -4.7255278e-001 7.6300000e-008 -4.6599510e-001 7.6400000e-008 -4.5936757e-001 7.6500000e-008 -4.5561810e-001 7.6600000e-008 -4.4568114e-001 7.6700000e-008 -4.4162660e-001 7.6800000e-008 -4.3142656e-001 7.6900000e-008 -4.2335559e-001 7.7000000e-008 -4.1880082e-001 7.7100000e-008 -4.0403604e-001 7.7200000e-008 -4.0018997e-001 7.7300000e-008 -3.9344967e-001 7.7400000e-008 -3.8050802e-001 7.7500000e-008 -3.6376523e-001 7.7600000e-008 -3.5812443e-001 7.7700000e-008 -3.4006623e-001 7.7800000e-008 -3.3508380e-001 7.7900000e-008 -3.2029730e-001 7.8000000e-008 -3.0700288e-001 7.8100000e-008 -2.9412615e-001 7.8200000e-008 -2.8444329e-001 7.8300000e-008 -2.6260113e-001 7.8400000e-008 -2.5438384e-001 7.8500000e-008 -2.4166505e-001 7.8600000e-008 -2.2521892e-001 7.8700000e-008 -2.1018292e-001 7.8800000e-008 -1.9542036e-001 7.8900000e-008 -1.7885834e-001 7.9000000e-008 -1.6656603e-001 7.9100000e-008 -1.4792203e-001 7.9200000e-008 -1.3208024e-001 7.9300000e-008 -1.1830088e-001 7.9400000e-008 -9.8410637e-002 7.9500000e-008 -8.2725064e-002 7.9600000e-008 -6.8236726e-002 7.9700000e-008 -4.3932207e-002 7.9800000e-008 -3.1650006e-002 7.9900000e-008 -1.6911002e-002 8.0000000e-008 6.8464472e-005 8.0100000e-008 1.9594439e-002 8.0200000e-008 3.1583641e-002 8.0300000e-008 4.8970861e-002 8.0400000e-008 6.8124190e-002 8.0500000e-008 8.5411292e-002 8.0600000e-008 1.0455043e-001 8.0700000e-008 1.1587096e-001 8.0800000e-008 1.4015095e-001 8.0900000e-008 1.4618682e-001 8.1000000e-008 1.6219545e-001 8.1100000e-008 1.7753523e-001 8.1200000e-008 1.9104205e-001 8.1300000e-008 2.1171757e-001 8.1400000e-008 2.2816803e-001 8.1500000e-008 2.4553435e-001 8.1600000e-008 2.5182372e-001 8.1700000e-008 2.6872017e-001 8.1800000e-008 2.8086627e-001 8.1900000e-008 3.0116969e-001 8.2000000e-008 3.0408752e-001 8.2100000e-008 3.1984251e-001 8.2200000e-008 3.2940297e-001 8.2300000e-008 3.4532312e-001 8.2400000e-008 3.5783851e-001 8.2500000e-008 3.7315303e-001 8.2600000e-008 3.7826252e-001 8.2700000e-008 3.8742131e-001 8.2800000e-008 4.0314775e-001 8.2900000e-008 4.1102450e-001 8.3000000e-008 4.1564320e-001 8.3100000e-008 4.2275922e-001 8.3200000e-008 4.3001364e-001 8.3300000e-008 4.3667675e-001 8.3400000e-008 4.4435553e-001 8.3500000e-008 4.4989210e-001 8.3600000e-008 4.6015170e-001 8.3700000e-008 4.6262221e-001 8.3800000e-008 4.7080165e-001 8.3900000e-008 4.7548106e-001 8.4000000e-008 4.7706521e-001 8.4100000e-008 4.7887969e-001 8.4200000e-008 4.8633187e-001 8.4300000e-008 4.8385462e-001 8.4400000e-008 4.9303971e-001 8.4500000e-008 4.9474033e-001 8.4600000e-008 4.9297649e-001 8.4700000e-008 4.9221411e-001 8.4800000e-008 4.9649688e-001 8.4900000e-008 4.9663526e-001 8.5000000e-008 4.9382999e-001 8.5100000e-008 4.9697020e-001 8.5200000e-008 4.9487709e-001 8.5300000e-008 4.8936818e-001 8.5400000e-008 4.7994872e-001 8.5500000e-008 4.8510776e-001 8.5600000e-008 4.7904568e-001 8.5700000e-008 4.7442079e-001 8.5800000e-008 4.7831635e-001 8.5900000e-008 4.6980138e-001 8.6000000e-008 4.7063796e-001 8.6100000e-008 4.6127472e-001 8.6200000e-008 4.5075177e-001 8.6300000e-008 4.5294362e-001 8.6400000e-008 4.4938564e-001 8.6500000e-008 4.3729222e-001 8.6600000e-008 4.2572898e-001 8.6700000e-008 4.2132487e-001 8.6800000e-008 4.1660626e-001 8.6900000e-008 4.0485170e-001 8.7000000e-008 4.0170268e-001 8.7100000e-008 3.8507835e-001 8.7200000e-008 3.7729119e-001 8.7300000e-008 3.7616135e-001 8.7400000e-008 3.5801894e-001 8.7500000e-008 3.4917013e-001 8.7600000e-008 3.3478238e-001 8.7700000e-008 3.2824877e-001 8.7800000e-008 3.1494066e-001 8.7900000e-008 3.0591911e-001 8.8000000e-008 2.8788064e-001 8.8100000e-008 2.7286023e-001 8.8200000e-008 2.5882880e-001 8.8300000e-008 2.5146900e-001 8.8400000e-008 2.2880919e-001 8.8500000e-008 2.2018669e-001 8.8600000e-008 2.1045495e-001 8.8700000e-008 1.9105108e-001 8.8800000e-008 1.8607054e-001 8.8900000e-008 1.6642838e-001 8.9000000e-008 1.4960587e-001 8.9100000e-008 1.3833279e-001 8.9200000e-008 1.2071393e-001 8.9300000e-008 1.0572206e-001 8.9400000e-008 9.5534905e-002 8.9500000e-008 7.3353888e-002 8.9600000e-008 6.0979487e-002 8.9700000e-008 4.8376019e-002 8.9800000e-008 2.6548922e-002 8.9900000e-008 2.0232269e-002 9.0000000e-008 4.0395214e-003 9.0100000e-008 -1.2991212e-002 9.0200000e-008 -3.1541184e-002 9.0300000e-008 -4.5105220e-002 9.0400000e-008 -6.4290091e-002 9.0500000e-008 -7.6768755e-002 9.0600000e-008 -9.4991136e-002 9.0700000e-008 -1.0472277e-001 9.0800000e-008 -1.2125556e-001 9.0900000e-008 -1.3763744e-001 9.1000000e-008 -1.5228363e-001 9.1100000e-008 -1.6188817e-001 9.1200000e-008 -1.8097713e-001 9.1300000e-008 -1.9678736e-001 9.1400000e-008 -2.0836739e-001 9.1500000e-008 -2.1800141e-001 9.1600000e-008 -2.3478313e-001 9.1700000e-008 -2.4583286e-001 9.1800000e-008 -2.6470116e-001 9.1900000e-008 -2.7316965e-001 9.2000000e-008 -2.9133590e-001 9.2100000e-008 -2.9954879e-001 9.2200000e-008 -3.1413492e-001 9.2300000e-008 -3.2246019e-001 9.2400000e-008 -3.3573996e-001 9.2500000e-008 -3.4684565e-001 9.2600000e-008 -3.5452967e-001 9.2700000e-008 -3.7268131e-001 9.2800000e-008 -3.7786764e-001 9.2900000e-008 -3.9391642e-001 9.3000000e-008 -3.9572220e-001 9.3100000e-008 -4.1113293e-001 9.3200000e-008 -4.1751168e-001 9.3300000e-008 -4.2249883e-001 9.3400000e-008 -4.2888356e-001 9.3500000e-008 -4.4164861e-001 9.3600000e-008 -4.4129584e-001 9.3700000e-008 -4.5408883e-001 9.3800000e-008 -4.5765465e-001 9.3900000e-008 -4.5441166e-001 9.4000000e-008 -4.6846671e-001 9.4100000e-008 -4.7249500e-001 9.4200000e-008 -4.7695221e-001 9.4300000e-008 -4.8414286e-001 9.4400000e-008 -4.8724219e-001 9.4500000e-008 -4.8946432e-001 9.4600000e-008 -4.8830662e-001 9.4700000e-008 -4.8458302e-001 9.4800000e-008 -4.9337332e-001 9.4900000e-008 -4.9433348e-001 9.5000000e-008 -4.9494190e-001 9.5100000e-008 -4.9540943e-001 9.5200000e-008 -4.9567416e-001 9.5300000e-008 -4.9793527e-001 9.5400000e-008 -4.9264892e-001 9.5500000e-008 -4.8873160e-001 9.5600000e-008 -4.8715821e-001 9.5700000e-008 -4.8598562e-001 9.5800000e-008 -4.8594531e-001 9.5900000e-008 -4.8409126e-001 9.6000000e-008 -4.8422827e-001 9.6100000e-008 -4.7317403e-001 9.6200000e-008 -4.7173061e-001 9.6300000e-008 -4.6470246e-001 9.6400000e-008 -4.5977989e-001 9.6500000e-008 -4.5252746e-001 9.6600000e-008 -4.4667666e-001 9.6700000e-008 -4.3664158e-001 9.6800000e-008 -4.3584451e-001 9.6900000e-008 -4.2644431e-001 9.7000000e-008 -4.1341113e-001 9.7100000e-008 -4.0615326e-001 9.7200000e-008 -3.9395500e-001 9.7300000e-008 -3.8787736e-001 9.7400000e-008 -3.7944848e-001 9.7500000e-008 -3.7115747e-001 9.7600000e-008 -3.5468206e-001 9.7700000e-008 -3.3640456e-001 9.7800000e-008 -3.3654084e-001 9.7900000e-008 -3.2156898e-001 9.8000000e-008 -3.0195733e-001 9.8100000e-008 -2.9278793e-001 9.8200000e-008 -2.8467319e-001 9.8300000e-008 -2.6643755e-001 9.8400000e-008 -2.5455753e-001 9.8500000e-008 -2.3986997e-001 9.8600000e-008 -2.2131497e-001 9.8700000e-008 -2.0518725e-001 9.8800000e-008 -1.9638584e-001 9.8900000e-008 -1.8017168e-001 9.9000000e-008 -1.5972418e-001 9.9100000e-008 -1.5062204e-001 9.9200000e-008 -1.2662724e-001 9.9300000e-008 -1.1355610e-001 9.9400000e-008 -9.7793033e-002 9.9500000e-008 -8.8089614e-002 9.9600000e-008 -6.7093688e-002 9.9700000e-008 -4.9669194e-002 9.9800000e-008 -3.3500807e-002 9.9900000e-008 -1.5935766e-002 1.0000000e-007 -5.6382759e-006 1.0010000e-007 1.4477453e-002 1.0020000e-007 3.3238476e-002 1.0030000e-007 4.6944695e-002 1.0040000e-007 6.1942149e-002 1.0050000e-007 8.0613674e-002 1.0060000e-007 9.6295675e-002 1.0070000e-007 1.1896209e-001 1.0080000e-007 1.3225429e-001 1.0090000e-007 1.5020358e-001 1.0100000e-007 1.6640185e-001 1.0110000e-007 1.7841162e-001 1.0120000e-007 1.9541579e-001 1.0130000e-007 2.1398262e-001 1.0140000e-007 2.2177579e-001 1.0150000e-007 2.4507655e-001 1.0160000e-007 2.5175170e-001 1.0170000e-007 2.6775397e-001 1.0180000e-007 2.8159375e-001 1.0190000e-007 2.9525021e-001 1.0200000e-007 3.0664434e-001 1.0210000e-007 3.1915704e-001 1.0220000e-007 3.3144183e-001 1.0230000e-007 3.4384213e-001 1.0240000e-007 3.5488914e-001 1.0250000e-007 3.6316794e-001 1.0260000e-007 3.7772112e-001 1.0270000e-007 3.9013709e-001 1.0280000e-007 3.9707936e-001 1.0290000e-007 4.0408041e-001 1.0300000e-007 4.1733239e-001 1.0310000e-007 4.1928496e-001 1.0320000e-007 4.3084791e-001 1.0330000e-007 4.3261361e-001 1.0340000e-007 4.4254131e-001 1.0350000e-007 4.6109632e-001 1.0360000e-007 4.6203387e-001 1.0370000e-007 4.6465873e-001 1.0380000e-007 4.7086038e-001 1.0390000e-007 4.7196586e-001 1.0400000e-007 4.7323223e-001 1.0410000e-007 4.8611471e-001 1.0420000e-007 4.8486851e-001 1.0430000e-007 4.8549269e-001 1.0440000e-007 4.9461076e-001 1.0450000e-007 4.9621227e-001 1.0460000e-007 4.9086797e-001 1.0470000e-007 4.9820782e-001 1.0480000e-007 5.0142405e-001 1.0490000e-007 4.9879355e-001 1.0500000e-007 4.9460541e-001 1.0510000e-007 4.9043713e-001 1.0520000e-007 4.9552188e-001 1.0530000e-007 4.9046215e-001 1.0540000e-007 4.9189798e-001 1.0550000e-007 4.8802433e-001 1.0560000e-007 4.8717943e-001 1.0570000e-007 4.7632662e-001 1.0580000e-007 4.7548875e-001 1.0590000e-007 4.7486639e-001 1.0600000e-007 4.7038362e-001 1.0610000e-007 4.6511387e-001 1.0620000e-007 4.5574297e-001 1.0630000e-007 4.4822216e-001 1.0640000e-007 4.4375440e-001 1.0650000e-007 4.4003574e-001 1.0660000e-007 4.2679653e-001 1.0670000e-007 4.2259768e-001 1.0680000e-007 4.1087374e-001 1.0690000e-007 4.0640061e-001 1.0700000e-007 3.9876263e-001 1.0710000e-007 3.8609090e-001 1.0720000e-007 3.7584539e-001 1.0730000e-007 3.6930348e-001 1.0740000e-007 3.5580635e-001 1.0750000e-007 3.4588277e-001 1.0760000e-007 3.3904281e-001 1.0770000e-007 3.2078416e-001 1.0780000e-007 3.1593981e-001 1.0790000e-007 3.0034369e-001 1.0800000e-007 2.8900073e-001 1.0810000e-007 2.7963445e-001 1.0820000e-007 2.6217665e-001 1.0830000e-007 2.4844048e-001 1.0840000e-007 2.3689417e-001 1.0850000e-007 2.2184836e-001 1.0860000e-007 2.0996125e-001 1.0870000e-007 1.9734156e-001 1.0880000e-007 1.7874027e-001 1.0890000e-007 1.6265731e-001 1.0900000e-007 1.5111791e-001 1.0910000e-007 1.3875355e-001 1.0920000e-007 1.2235142e-001 1.0930000e-007 1.0809716e-001 1.0940000e-007 8.8436052e-002 1.0950000e-007 7.6733303e-002 1.0960000e-007 6.4903017e-002 1.0970000e-007 4.3912606e-002 1.0980000e-007 2.8867772e-002 1.0990000e-007 1.7814407e-002 1.1000000e-007 -2.2323015e-003 1.1010000e-007 -1.4573024e-002 1.1020000e-007 -3.7037115e-002 1.1030000e-007 -4.6258890e-002 1.1040000e-007 -6.0860287e-002 1.1050000e-007 -7.2074346e-002 1.1060000e-007 -8.9623343e-002 1.1070000e-007 -1.0879270e-001 1.1080000e-007 -1.2065476e-001 1.1090000e-007 -1.3873064e-001 1.1100000e-007 -1.5490718e-001 1.1110000e-007 -1.6452751e-001 1.1120000e-007 -1.8032659e-001 1.1130000e-007 -1.9817857e-001 1.1140000e-007 -2.1027606e-001 1.1150000e-007 -2.2328157e-001 1.1160000e-007 -2.3395921e-001 1.1170000e-007 -2.5248769e-001 1.1180000e-007 -2.6334990e-001 1.1190000e-007 -2.7203214e-001 1.1200000e-007 -2.8386411e-001 1.1210000e-007 -3.0164932e-001 1.1220000e-007 -3.1133799e-001 1.1230000e-007 -3.3085374e-001 1.1240000e-007 -3.3594007e-001 1.1250000e-007 -3.4502739e-001 1.1260000e-007 -3.5840814e-001 1.1270000e-007 -3.6785421e-001 1.1280000e-007 -3.7954315e-001 1.1290000e-007 -3.8639040e-001 1.1300000e-007 -3.9928720e-001 1.1310000e-007 -4.0742373e-001 1.1320000e-007 -4.1383417e-001 1.1330000e-007 -4.2111116e-001 1.1340000e-007 -4.2869380e-001 1.1350000e-007 -4.3161653e-001 1.1360000e-007 -4.4645129e-001 1.1370000e-007 -4.4801143e-001 1.1380000e-007 -4.5728233e-001 1.1390000e-007 -4.6210543e-001 1.1400000e-007 -4.6842173e-001 1.1410000e-007 -4.7042096e-001 1.1420000e-007 -4.7025430e-001 1.1430000e-007 -4.8443322e-001 1.1440000e-007 -4.8434815e-001 1.1450000e-007 -4.8611211e-001 1.1460000e-007 -4.9065076e-001 1.1470000e-007 -4.9730012e-001 1.1480000e-007 -4.9289441e-001 1.1490000e-007 -4.9810890e-001 1.1500000e-007 -4.9814911e-001 1.1510000e-007 -4.9421232e-001 1.1520000e-007 -4.9085810e-001 1.1530000e-007 -4.9857620e-001 1.1540000e-007 -4.9320495e-001 1.1550000e-007 -4.9328070e-001 1.1560000e-007 -4.9315430e-001 1.1570000e-007 -4.8644858e-001 1.1580000e-007 -4.8590688e-001 1.1590000e-007 -4.8218213e-001 1.1600000e-007 -4.7692140e-001 1.1610000e-007 -4.7424266e-001 1.1620000e-007 -4.6436492e-001 1.1630000e-007 -4.5730712e-001 1.1640000e-007 -4.6124719e-001 1.1650000e-007 -4.4879178e-001 1.1660000e-007 -4.4683197e-001 1.1670000e-007 -4.4259452e-001 1.1680000e-007 -4.2125366e-001 1.1690000e-007 -4.2739727e-001 1.1700000e-007 -4.1320608e-001 1.1710000e-007 -4.0431921e-001 1.1720000e-007 -4.0159451e-001 1.1730000e-007 -3.8262778e-001 1.1740000e-007 -3.7489180e-001 1.1750000e-007 -3.6635013e-001 1.1760000e-007 -3.4950429e-001 1.1770000e-007 -3.4288722e-001 1.1780000e-007 -3.2797991e-001 1.1790000e-007 -3.2094343e-001 1.1800000e-007 -3.1171748e-001 1.1810000e-007 -2.9385464e-001 1.1820000e-007 -2.8258613e-001 1.1830000e-007 -2.6442013e-001 1.1840000e-007 -2.5560365e-001 1.1850000e-007 -2.4046640e-001 1.1860000e-007 -2.2421581e-001 1.1870000e-007 -2.1237478e-001 1.1880000e-007 -2.0180212e-001 1.1890000e-007 -1.8437985e-001 1.1900000e-007 -1.6488851e-001 1.1910000e-007 -1.4618581e-001 1.1920000e-007 -1.2535406e-001 1.1930000e-007 -1.1557893e-001 1.1940000e-007 -1.0218361e-001 1.1950000e-007 -8.6417699e-002 1.1960000e-007 -7.0993823e-002 1.1970000e-007 -5.2772435e-002 1.1980000e-007 -3.7657869e-002 1.1990000e-007 -2.1633224e-002 1.2000000e-007 4.7929954e-003 1.2010000e-007 1.2279810e-002 1.2020000e-007 3.4339385e-002 1.2030000e-007 4.7666456e-002 1.2040000e-007 6.8077403e-002 1.2050000e-007 8.3466114e-002 1.2060000e-007 1.0344370e-001 1.2070000e-007 1.2175151e-001 1.2080000e-007 1.3133893e-001 1.2090000e-007 1.4759656e-001 1.2100000e-007 1.6426016e-001 1.2110000e-007 1.8130318e-001 1.2120000e-007 2.0094297e-001 1.2130000e-007 2.0857774e-001 1.2140000e-007 2.2674802e-001 1.2150000e-007 2.3650891e-001 1.2160000e-007 2.5861073e-001 1.2170000e-007 2.6501858e-001 1.2180000e-007 2.8291030e-001 1.2190000e-007 2.9791216e-001 1.2200000e-007 3.0584309e-001 1.2210000e-007 3.1300105e-001 1.2220000e-007 3.3475438e-001 1.2230000e-007 3.4871490e-001 1.2240000e-007 3.5878716e-001 1.2250000e-007 3.7128466e-001 1.2260000e-007 3.7611305e-001 1.2270000e-007 3.8772530e-001 1.2280000e-007 3.9795577e-001 1.2290000e-007 4.0302790e-001 1.2300000e-007 4.1767179e-001 1.2310000e-007 4.2576743e-001 1.2320000e-007 4.3197793e-001 1.2330000e-007 4.3615905e-001 1.2340000e-007 4.5021784e-001 1.2350000e-007 4.5234639e-001 1.2360000e-007 4.5775504e-001 1.2370000e-007 4.6835354e-001 1.2380000e-007 4.6796949e-001 1.2390000e-007 4.7635639e-001 1.2400000e-007 4.7742687e-001 1.2410000e-007 4.7912285e-001 1.2420000e-007 4.9027464e-001 1.2430000e-007 4.8667317e-001 1.2440000e-007 4.8997296e-001 1.2450000e-007 4.8801677e-001 1.2460000e-007 4.9245859e-001 1.2470000e-007 4.9377961e-001 1.2480000e-007 4.9325023e-001 1.2490000e-007 4.9453212e-001 1.2500000e-007 4.9221011e-001 1.2510000e-007 4.9168906e-001 1.2520000e-007 4.9247529e-001 1.2530000e-007 4.9293351e-001 1.2540000e-007 4.9062683e-001 1.2550000e-007 4.8422399e-001 1.2560000e-007 4.8056320e-001 1.2570000e-007 4.8170939e-001 1.2580000e-007 4.8352234e-001 1.2590000e-007 4.7372040e-001 1.2600000e-007 4.6508877e-001 1.2610000e-007 4.6379313e-001 1.2620000e-007 4.5755312e-001 1.2630000e-007 4.4942784e-001 1.2640000e-007 4.4100575e-001 1.2650000e-007 4.3374296e-001 1.2660000e-007 4.2887809e-001 1.2670000e-007 4.2390097e-001 1.2680000e-007 4.1523395e-001 1.2690000e-007 4.0146989e-001 1.2700000e-007 3.9933340e-001 1.2710000e-007 3.8755784e-001 1.2720000e-007 3.7454884e-001 1.2730000e-007 3.7036128e-001 1.2740000e-007 3.5691518e-001 1.2750000e-007 3.4967774e-001 1.2760000e-007 3.3802938e-001 1.2770000e-007 3.2742479e-001 1.2780000e-007 3.1365486e-001 1.2790000e-007 3.0177378e-001 1.2800000e-007 2.8909568e-001 1.2810000e-007 2.7365127e-001 1.2820000e-007 2.6351740e-001 1.2830000e-007 2.4586821e-001 1.2840000e-007 2.3587886e-001 1.2850000e-007 2.2184675e-001 1.2860000e-007 2.1304939e-001 1.2870000e-007 1.9252348e-001 1.2880000e-007 1.7806331e-001 1.2890000e-007 1.6539604e-001 1.2900000e-007 1.5575807e-001 1.2910000e-007 1.4495160e-001 1.2920000e-007 1.2149843e-001 1.2930000e-007 1.0454663e-001 1.2940000e-007 9.2685405e-002 1.2950000e-007 8.0724321e-002 1.2960000e-007 6.1095546e-002 1.2970000e-007 4.3735698e-002 1.2980000e-007 3.6152071e-002 1.2990000e-007 1.5377305e-002 1.3000000e-007 -4.4458792e-003 1.3010000e-007 -1.8360423e-002 1.3020000e-007 -2.8599231e-002 1.3030000e-007 -4.8500511e-002 1.3040000e-007 -6.6652568e-002 1.3050000e-007 -7.7161149e-002 1.3060000e-007 -1.0040199e-001 1.3070000e-007 -1.1295037e-001 1.3080000e-007 -1.2156517e-001 1.3090000e-007 -1.3863455e-001 1.3100000e-007 -1.5591470e-001 1.3110000e-007 -1.6752551e-001 1.3120000e-007 -1.7963092e-001 1.3130000e-007 -1.9810519e-001 1.3140000e-007 -2.0716997e-001 1.3150000e-007 -2.1865282e-001 1.3160000e-007 -2.3770414e-001 1.3170000e-007 -2.5005965e-001 1.3180000e-007 -2.6722857e-001 1.3190000e-007 -2.7568571e-001 1.3200000e-007 -2.9103123e-001 1.3210000e-007 -3.0136390e-001 1.3220000e-007 -3.1204392e-001 1.3230000e-007 -3.2315204e-001 1.3240000e-007 -3.3806753e-001 1.3250000e-007 -3.4594340e-001 1.3260000e-007 -3.5739858e-001 1.3270000e-007 -3.6660759e-001 1.3280000e-007 -3.8080717e-001 1.3290000e-007 -3.8488943e-001 1.3300000e-007 -3.9525681e-001 1.3310000e-007 -4.0409331e-001 1.3320000e-007 -4.1586716e-001 1.3330000e-007 -4.2712871e-001 1.3340000e-007 -4.2997803e-001 1.3350000e-007 -4.3805426e-001 1.3360000e-007 -4.4299215e-001 1.3370000e-007 -4.5301229e-001 1.3380000e-007 -4.5597499e-001 1.3390000e-007 -4.6026828e-001 1.3400000e-007 -4.6537795e-001 1.3410000e-007 -4.7213799e-001 1.3420000e-007 -4.7301525e-001 1.3430000e-007 -4.8677949e-001 1.3440000e-007 -4.8765083e-001 1.3450000e-007 -4.8578557e-001 1.3460000e-007 -4.8885982e-001 1.3470000e-007 -4.8950637e-001 1.3480000e-007 -4.9352990e-001 1.3490000e-007 -4.8955287e-001 1.3500000e-007 -4.9489638e-001 1.3510000e-007 -4.9714306e-001 1.3520000e-007 -4.9874543e-001 1.3530000e-007 -4.9162591e-001 1.3540000e-007 -4.9409407e-001 1.3550000e-007 -4.9054527e-001 1.3560000e-007 -4.9108845e-001 1.3570000e-007 -4.8650505e-001 1.3580000e-007 -4.8486387e-001 1.3590000e-007 -4.7890171e-001 1.3600000e-007 -4.7839738e-001 1.3610000e-007 -4.7852146e-001 1.3620000e-007 -4.6352774e-001 1.3630000e-007 -4.6345316e-001 1.3640000e-007 -4.5303720e-001 1.3650000e-007 -4.5010382e-001 1.3660000e-007 -4.4641272e-001 1.3670000e-007 -4.4357365e-001 1.3680000e-007 -4.3314394e-001 1.3690000e-007 -4.2207362e-001 1.3700000e-007 -4.2087724e-001 1.3710000e-007 -4.0957526e-001 1.3720000e-007 -3.9740801e-001 1.3730000e-007 -3.8790594e-001 1.3740000e-007 -3.7600799e-001 1.3750000e-007 -3.6527780e-001 1.3760000e-007 -3.5452427e-001 1.3770000e-007 -3.4215076e-001 1.3780000e-007 -3.3247981e-001 1.3790000e-007 -3.2078992e-001 1.3800000e-007 -3.0797155e-001 1.3810000e-007 -2.9648641e-001 1.3820000e-007 -2.8372496e-001 1.3830000e-007 -2.6428880e-001 1.3840000e-007 -2.5701563e-001 1.3850000e-007 -2.3904311e-001 1.3860000e-007 -2.2343341e-001 1.3870000e-007 -2.1364494e-001 1.3880000e-007 -1.9231831e-001 1.3890000e-007 -1.7934785e-001 1.3900000e-007 -1.6603059e-001 1.3910000e-007 -1.4602550e-001 1.3920000e-007 -1.3148768e-001 1.3930000e-007 -1.1357182e-001 1.3940000e-007 -1.0210354e-001 1.3950000e-007 -8.2265847e-002 1.3960000e-007 -7.0816772e-002 1.3970000e-007 -5.0523177e-002 1.3980000e-007 -3.2016391e-002 1.3990000e-007 -2.2979506e-002 1.4000000e-007 1.5188976e-003 1.4010000e-007 1.8935194e-002 1.4020000e-007 3.2752249e-002 1.4030000e-007 4.5763109e-002 1.4040000e-007 7.0945438e-002 1.4050000e-007 8.2497068e-002 1.4060000e-007 9.4726747e-002 1.4070000e-007 1.1859374e-001 1.4080000e-007 1.3315045e-001 1.4090000e-007 1.4952609e-001 1.4100000e-007 1.6403461e-001 1.4110000e-007 1.7970982e-001 1.4120000e-007 1.9445141e-001 1.4130000e-007 2.1084964e-001 1.4140000e-007 2.3166810e-001 1.4150000e-007 2.4531073e-001 1.4160000e-007 2.5820412e-001 1.4170000e-007 2.6808716e-001 1.4180000e-007 2.8369586e-001 1.4190000e-007 2.9585944e-001 1.4200000e-007 3.0781565e-001 1.4210000e-007 3.1877268e-001 1.4220000e-007 3.3187708e-001 1.4230000e-007 3.4246788e-001 1.4240000e-007 3.6031430e-001 1.4250000e-007 3.6612455e-001 1.4260000e-007 3.7341106e-001 1.4270000e-007 3.8658445e-001 1.4280000e-007 3.9828828e-001 1.4290000e-007 4.0686194e-001 1.4300000e-007 4.1494166e-001 1.4310000e-007 4.2552612e-001 1.4320000e-007 4.3373477e-001 1.4330000e-007 4.3714279e-001 1.4340000e-007 4.4452786e-001 1.4350000e-007 4.5491542e-001 1.4360000e-007 4.5707566e-001 1.4370000e-007 4.6991978e-001 1.4380000e-007 4.7138125e-001 1.4390000e-007 4.7808786e-001 1.4400000e-007 4.7588383e-001 1.4410000e-007 4.8043752e-001 1.4420000e-007 4.8686368e-001 1.4430000e-007 4.8379377e-001 1.4440000e-007 4.9051601e-001 1.4450000e-007 4.9270080e-001 1.4460000e-007 4.9284284e-001 1.4470000e-007 4.9957615e-001 1.4480000e-007 4.9463747e-001 1.4490000e-007 5.0303107e-001 1.4500000e-007 4.8999387e-001 1.4510000e-007 4.9287655e-001 1.4520000e-007 4.9130895e-001 1.4530000e-007 4.8719101e-001 1.4540000e-007 4.8417647e-001 1.4550000e-007 4.9343007e-001 1.4560000e-007 4.8824501e-001 1.4570000e-007 4.7844598e-001 1.4580000e-007 4.8217585e-001 1.4590000e-007 4.7100804e-001 1.4600000e-007 4.6438249e-001 1.4610000e-007 4.6369980e-001 1.4620000e-007 4.6020112e-001 1.4630000e-007 4.5194816e-001 1.4640000e-007 4.3898954e-001 1.4650000e-007 4.3243978e-001 1.4660000e-007 4.2913537e-001 1.4670000e-007 4.2366548e-001 1.4680000e-007 4.1493369e-001 1.4690000e-007 4.0840022e-001 1.4700000e-007 3.9666664e-001 1.4710000e-007 3.9074366e-001 1.4720000e-007 3.7848843e-001 1.4730000e-007 3.6734869e-001 1.4740000e-007 3.5547794e-001 1.4750000e-007 3.4378112e-001 1.4760000e-007 3.4359536e-001 1.4770000e-007 3.2280192e-001 1.4780000e-007 3.1682269e-001 1.4790000e-007 2.9975319e-001 1.4800000e-007 2.9026130e-001 1.4810000e-007 2.8315492e-001 1.4820000e-007 2.6541723e-001 1.4830000e-007 2.5558820e-001 1.4840000e-007 2.3632529e-001 1.4850000e-007 2.2199925e-001 1.4860000e-007 2.0986869e-001 1.4870000e-007 1.9892069e-001 1.4880000e-007 1.8661814e-001 1.4890000e-007 1.7431575e-001 1.4900000e-007 1.5262862e-001 1.4910000e-007 1.3561808e-001 1.4920000e-007 1.2341878e-001 1.4930000e-007 1.1006712e-001 1.4940000e-007 9.3260144e-002 1.4950000e-007 7.7081594e-002 1.4960000e-007 6.2470033e-002 1.4970000e-007 4.9662626e-002 1.4980000e-007 3.5686666e-002 1.4990000e-007 1.0887738e-002 1.5000000e-007 2.6770777e-003 1.5010000e-007 -1.6705512e-002 1.5020000e-007 -2.9390254e-002 1.5030000e-007 -4.6130291e-002 1.5040000e-007 -5.7010633e-002 1.5050000e-007 -7.5009036e-002 1.5060000e-007 -9.0086122e-002 1.5070000e-007 -1.0524578e-001 1.5080000e-007 -1.2001195e-001 1.5090000e-007 -1.3451385e-001 1.5100000e-007 -1.5226258e-001 1.5110000e-007 -1.6669179e-001 1.5120000e-007 -1.7975500e-001 1.5130000e-007 -1.9525001e-001 1.5140000e-007 -2.0804343e-001 1.5150000e-007 -2.2444822e-001 1.5160000e-007 -2.3383998e-001 1.5170000e-007 -2.4872836e-001 1.5180000e-007 -2.5894396e-001 1.5190000e-007 -2.7075773e-001 1.5200000e-007 -2.8669068e-001 1.5210000e-007 -3.0065001e-001 1.5220000e-007 -3.1302722e-001 1.5230000e-007 -3.2110244e-001 1.5240000e-007 -3.4312856e-001 1.5250000e-007 -3.5067540e-001 1.5260000e-007 -3.5515673e-001 1.5270000e-007 -3.6642064e-001 1.5280000e-007 -3.7606988e-001 1.5290000e-007 -3.8685396e-001 1.5300000e-007 -3.9694145e-001 1.5310000e-007 -3.9907191e-001 1.5320000e-007 -4.1599805e-001 1.5330000e-007 -4.2531746e-001 1.5340000e-007 -4.2953603e-001 1.5350000e-007 -4.3475209e-001 1.5360000e-007 -4.4515912e-001 1.5370000e-007 -4.5088303e-001 1.5380000e-007 -4.5460037e-001 1.5390000e-007 -4.6298251e-001 1.5400000e-007 -4.7006271e-001 1.5410000e-007 -4.7257267e-001 1.5420000e-007 -4.7859670e-001 1.5430000e-007 -4.8132661e-001 1.5440000e-007 -4.8446598e-001 1.5450000e-007 -4.8664978e-001 1.5460000e-007 -4.9008676e-001 1.5470000e-007 -4.9351427e-001 1.5480000e-007 -4.9373026e-001 1.5490000e-007 -4.9166903e-001 1.5500000e-007 -4.9664958e-001 1.5510000e-007 -4.9090468e-001 1.5520000e-007 -4.9317875e-001 1.5530000e-007 -4.9072606e-001 1.5540000e-007 -4.9792050e-001 1.5550000e-007 -4.9392463e-001 1.5560000e-007 -4.9172295e-001 1.5570000e-007 -4.8597409e-001 1.5580000e-007 -4.8815073e-001 1.5590000e-007 -4.8793973e-001 1.5600000e-007 -4.7686440e-001 1.5610000e-007 -4.8143996e-001 1.5620000e-007 -4.7237739e-001 1.5630000e-007 -4.6560709e-001 1.5640000e-007 -4.5993807e-001 1.5650000e-007 -4.4698177e-001 1.5660000e-007 -4.4198978e-001 1.5670000e-007 -4.4075852e-001 1.5680000e-007 -4.3194429e-001 1.5690000e-007 -4.2333852e-001 1.5700000e-007 -4.1613687e-001 1.5710000e-007 -4.0805266e-001 1.5720000e-007 -4.0060175e-001 1.5730000e-007 -3.9420690e-001 1.5740000e-007 -3.7645868e-001 1.5750000e-007 -3.6155095e-001 1.5760000e-007 -3.5656842e-001 1.5770000e-007 -3.4731353e-001 1.5780000e-007 -3.3326436e-001 1.5790000e-007 -3.2252902e-001 1.5800000e-007 -3.1081711e-001 1.5810000e-007 -2.9168185e-001 1.5820000e-007 -2.8400977e-001 1.5830000e-007 -2.6684892e-001 1.5840000e-007 -2.5055391e-001 1.5850000e-007 -2.3778158e-001 1.5860000e-007 -2.2193855e-001 1.5870000e-007 -2.1218757e-001 1.5880000e-007 -1.9288407e-001 1.5890000e-007 -1.8537874e-001 1.5900000e-007 -1.6848240e-001 1.5910000e-007 -1.4824141e-001 1.5920000e-007 -1.3180573e-001 1.5930000e-007 -1.1292500e-001 1.5940000e-007 -9.8856712e-002 1.5950000e-007 -8.0062925e-002 1.5960000e-007 -6.4901653e-002 1.5970000e-007 -5.1370905e-002 1.5980000e-007 -3.4435731e-002 1.5990000e-007 -2.0417381e-002 1.6000000e-007 -2.5076836e-003 1.6010000e-007 1.5117093e-002 1.6020000e-007 3.3866800e-002 1.6030000e-007 5.1711098e-002 1.6040000e-007 7.6181491e-002 1.6050000e-007 8.5519101e-002 1.6060000e-007 9.6861313e-002 1.6070000e-007 1.1152053e-001 1.6080000e-007 1.3263144e-001 1.6090000e-007 1.4576487e-001 1.6100000e-007 1.7045621e-001 1.6110000e-007 1.8247722e-001 1.6120000e-007 1.9677872e-001 1.6130000e-007 2.0400496e-001 1.6140000e-007 2.2723928e-001 1.6150000e-007 2.4169066e-001 1.6160000e-007 2.6098335e-001 1.6170000e-007 2.6995782e-001 1.6180000e-007 2.8532590e-001 1.6190000e-007 2.9759334e-001 1.6200000e-007 3.1040652e-001 1.6210000e-007 3.2288269e-001 1.6220000e-007 3.3241825e-001 1.6230000e-007 3.4457405e-001 1.6240000e-007 3.5220578e-001 1.6250000e-007 3.6576895e-001 1.6260000e-007 3.8044797e-001 1.6270000e-007 3.9111037e-001 1.6280000e-007 4.0093624e-001 1.6290000e-007 4.0539337e-001 1.6300000e-007 4.1262092e-001 1.6310000e-007 4.2718703e-001 1.6320000e-007 4.3164759e-001 1.6330000e-007 4.3775384e-001 1.6340000e-007 4.4439583e-001 1.6350000e-007 4.4930347e-001 1.6360000e-007 4.6120334e-001 1.6370000e-007 4.6368022e-001 1.6380000e-007 4.7109419e-001 1.6390000e-007 4.7413051e-001 1.6400000e-007 4.7704067e-001 1.6410000e-007 4.8410257e-001 1.6420000e-007 4.8206505e-001 1.6430000e-007 4.8384951e-001 1.6440000e-007 4.9258616e-001 1.6450000e-007 4.9596687e-001 1.6460000e-007 4.9243654e-001 1.6470000e-007 4.9589587e-001 1.6480000e-007 4.8906565e-001 1.6490000e-007 4.9088443e-001 1.6500000e-007 4.9091040e-001 1.6510000e-007 4.9557202e-001 1.6520000e-007 4.9861861e-001 1.6530000e-007 4.8882584e-001 1.6540000e-007 4.9085869e-001 1.6550000e-007 4.8759665e-001 1.6560000e-007 4.8859742e-001 1.6570000e-007 4.8085298e-001 1.6580000e-007 4.7871103e-001 1.6590000e-007 4.6742045e-001 1.6600000e-007 4.6334642e-001 1.6610000e-007 4.6332449e-001 1.6620000e-007 4.5740164e-001 1.6630000e-007 4.4735409e-001 1.6640000e-007 4.4653563e-001 1.6650000e-007 4.3759691e-001 1.6660000e-007 4.2870555e-001 1.6670000e-007 4.1651585e-001 1.6680000e-007 4.1242252e-001 1.6690000e-007 4.0355141e-001 1.6700000e-007 3.9639458e-001 1.6710000e-007 3.8515504e-001 1.6720000e-007 3.7844642e-001 1.6730000e-007 3.6640893e-001 1.6740000e-007 3.5954324e-001 1.6750000e-007 3.4436085e-001 1.6760000e-007 3.3404817e-001 1.6770000e-007 3.2415884e-001 1.6780000e-007 3.1227542e-001 1.6790000e-007 3.0303241e-001 1.6800000e-007 2.9108531e-001 1.6810000e-007 2.7285459e-001 1.6820000e-007 2.6195966e-001 1.6830000e-007 2.4713736e-001 1.6840000e-007 2.3571404e-001 1.6850000e-007 2.2961427e-001 1.6860000e-007 2.1363298e-001 1.6870000e-007 1.9684277e-001 1.6880000e-007 1.8002076e-001 1.6890000e-007 1.6690283e-001 1.6900000e-007 1.4704222e-001 1.6910000e-007 1.4068662e-001 1.6920000e-007 1.2122447e-001 1.6930000e-007 1.0492998e-001 1.6940000e-007 9.5777926e-002 1.6950000e-007 8.0329693e-002 1.6960000e-007 6.4631114e-002 1.6970000e-007 4.7623091e-002 1.6980000e-007 3.0577163e-002 1.6990000e-007 1.7344330e-002 1.7000000e-007 -4.2995699e-003 1.7010000e-007 -1.5410280e-002 1.7020000e-007 -2.7296062e-002 1.7030000e-007 -4.9046070e-002 1.7040000e-007 -6.3956065e-002 1.7050000e-007 -8.0514299e-002 1.7060000e-007 -9.7542515e-002 1.7070000e-007 -1.1225733e-001 1.7080000e-007 -1.2137007e-001 1.7090000e-007 -1.3593843e-001 1.7100000e-007 -1.5283194e-001 1.7110000e-007 -1.6477155e-001 1.7120000e-007 -1.8303459e-001 1.7130000e-007 -1.9856463e-001 1.7140000e-007 -2.0975704e-001 1.7150000e-007 -2.2604310e-001 1.7160000e-007 -2.3340398e-001 1.7170000e-007 -2.5442146e-001 1.7180000e-007 -2.6152881e-001 1.7190000e-007 -2.7833495e-001 1.7200000e-007 -2.8499245e-001 1.7210000e-007 -2.9913906e-001 1.7220000e-007 -3.1472537e-001 1.7230000e-007 -3.2308611e-001 1.7240000e-007 -3.3551597e-001 1.7250000e-007 -3.4598509e-001 1.7260000e-007 -3.5727520e-001 1.7270000e-007 -3.6388528e-001 1.7280000e-007 -3.8036231e-001 1.7290000e-007 -3.8887370e-001 1.7300000e-007 -3.9145687e-001 1.7310000e-007 -4.0995146e-001 1.7320000e-007 -4.1367602e-001 1.7330000e-007 -4.2221558e-001 1.7340000e-007 -4.3181870e-001 1.7350000e-007 -4.3444527e-001 1.7360000e-007 -4.4088470e-001 1.7370000e-007 -4.5356994e-001 1.7380000e-007 -4.5440099e-001 1.7390000e-007 -4.6137304e-001 1.7400000e-007 -4.6797300e-001 1.7410000e-007 -4.6568964e-001 1.7420000e-007 -4.7952037e-001 1.7430000e-007 -4.8455081e-001 1.7440000e-007 -4.8823650e-001 1.7450000e-007 -4.9046749e-001 1.7460000e-007 -4.8391816e-001 1.7470000e-007 -4.9281086e-001 1.7480000e-007 -4.9420267e-001 1.7490000e-007 -4.9086158e-001 1.7500000e-007 -4.9813191e-001 1.7510000e-007 -4.9483436e-001 1.7520000e-007 -4.9371503e-001 1.7530000e-007 -4.9172655e-001 1.7540000e-007 -4.8962510e-001 1.7550000e-007 -4.9510816e-001 1.7560000e-007 -4.9037307e-001 1.7570000e-007 -4.8317712e-001 1.7580000e-007 -4.8610993e-001 1.7590000e-007 -4.8457581e-001 1.7600000e-007 -4.8241883e-001 1.7610000e-007 -4.7345759e-001 1.7620000e-007 -4.6695109e-001 1.7630000e-007 -4.6827233e-001 1.7640000e-007 -4.5945979e-001 1.7650000e-007 -4.5850753e-001 1.7660000e-007 -4.4071734e-001 1.7670000e-007 -4.4038579e-001 1.7680000e-007 -4.3221207e-001 1.7690000e-007 -4.2224328e-001 1.7700000e-007 -4.1818174e-001 1.7710000e-007 -4.0456328e-001 1.7720000e-007 -3.9032041e-001 1.7730000e-007 -3.8937505e-001 1.7740000e-007 -3.7584117e-001 1.7750000e-007 -3.6711773e-001 1.7760000e-007 -3.5621823e-001 1.7770000e-007 -3.4438422e-001 1.7780000e-007 -3.3358143e-001 1.7790000e-007 -3.2015970e-001 1.7800000e-007 -3.1250346e-001 1.7810000e-007 -2.9673805e-001 1.7820000e-007 -2.8644983e-001 1.7830000e-007 -2.6994049e-001 1.7840000e-007 -2.4512074e-001 1.7850000e-007 -2.4546877e-001 1.7860000e-007 -2.2246905e-001 1.7870000e-007 -2.1357124e-001 1.7880000e-007 -1.9755507e-001 1.7890000e-007 -1.8438026e-001 1.7900000e-007 -1.6224900e-001 1.7910000e-007 -1.4886926e-001 1.7920000e-007 -1.3303939e-001 1.7930000e-007 -1.1287176e-001 1.7940000e-007 -9.6054811e-002 1.7950000e-007 -8.5098489e-002 1.7960000e-007 -6.2780522e-002 1.7970000e-007 -4.7350912e-002 1.7980000e-007 -2.9763431e-002 1.7990000e-007 -2.0148287e-002 1.8000000e-007 -4.7453496e-005 1.8010000e-007 1.9183591e-002 1.8020000e-007 3.3175990e-002 1.8030000e-007 4.9456028e-002 1.8040000e-007 6.9900505e-002 1.8050000e-007 8.1989639e-002 1.8060000e-007 1.0349897e-001 1.8070000e-007 1.1619383e-001 1.8080000e-007 1.3009911e-001 1.8090000e-007 1.4903236e-001 1.8100000e-007 1.6006480e-001 1.8110000e-007 1.8193249e-001 1.8120000e-007 2.0050552e-001 1.8130000e-007 2.1231044e-001 1.8140000e-007 2.2960216e-001 1.8150000e-007 2.4108160e-001 1.8160000e-007 2.5546221e-001 1.8170000e-007 2.7155761e-001 1.8180000e-007 2.8186040e-001 1.8190000e-007 2.9122027e-001 1.8200000e-007 3.0772939e-001 1.8210000e-007 3.2038267e-001 1.8220000e-007 3.3380615e-001 1.8230000e-007 3.4667996e-001 1.8240000e-007 3.5459358e-001 1.8250000e-007 3.6969287e-001 1.8260000e-007 3.7705193e-001 1.8270000e-007 3.8627769e-001 1.8280000e-007 3.9460888e-001 1.8290000e-007 4.0386554e-001 1.8300000e-007 4.1801064e-001 1.8310000e-007 4.2291386e-001 1.8320000e-007 4.3165632e-001 1.8330000e-007 4.3881607e-001 1.8340000e-007 4.4617227e-001 1.8350000e-007 4.5311351e-001 1.8360000e-007 4.5791965e-001 1.8370000e-007 4.6733848e-001 1.8380000e-007 4.6919328e-001 1.8390000e-007 4.7360483e-001 1.8400000e-007 4.7590574e-001 1.8410000e-007 4.8555093e-001 1.8420000e-007 4.8655873e-001 1.8430000e-007 4.9194665e-001 1.8440000e-007 4.8507304e-001 1.8450000e-007 4.9247111e-001 1.8460000e-007 5.0207028e-001 1.8470000e-007 4.9317456e-001 1.8480000e-007 4.9785419e-001 1.8490000e-007 4.9493381e-001 1.8500000e-007 4.9608814e-001 1.8510000e-007 4.8874499e-001 1.8520000e-007 4.9377734e-001 1.8530000e-007 4.9005077e-001 1.8540000e-007 4.8344709e-001 1.8550000e-007 4.8512470e-001 1.8560000e-007 4.8268668e-001 1.8570000e-007 4.8192909e-001 1.8580000e-007 4.7522720e-001 1.8590000e-007 4.7142942e-001 1.8600000e-007 4.6842376e-001 1.8610000e-007 4.6452266e-001 1.8620000e-007 4.4956943e-001 1.8630000e-007 4.5136558e-001 1.8640000e-007 4.4260210e-001 1.8650000e-007 4.4033314e-001 1.8660000e-007 4.3186637e-001 1.8670000e-007 4.2202195e-001 1.8680000e-007 4.0745430e-001 1.8690000e-007 4.0764168e-001 1.8700000e-007 3.9636285e-001 1.8710000e-007 3.8534331e-001 1.8720000e-007 3.7947583e-001 1.8730000e-007 3.6650304e-001 1.8740000e-007 3.5838352e-001 1.8750000e-007 3.4910735e-001 1.8760000e-007 3.3282195e-001 1.8770000e-007 3.2486399e-001 1.8780000e-007 3.1214934e-001 1.8790000e-007 2.9923058e-001 1.8800000e-007 2.9325621e-001 1.8810000e-007 2.7620874e-001 1.8820000e-007 2.6546931e-001 1.8830000e-007 2.5339542e-001 1.8840000e-007 2.3334537e-001 1.8850000e-007 2.2023521e-001 1.8860000e-007 2.1427335e-001 1.8870000e-007 1.9660046e-001 1.8880000e-007 1.7967871e-001 1.8890000e-007 1.6710915e-001 1.8900000e-007 1.5306027e-001 1.8910000e-007 1.3524155e-001 1.8920000e-007 1.2126325e-001 1.8930000e-007 1.0903313e-001 1.8940000e-007 9.4469208e-002 1.8950000e-007 7.3823401e-002 1.8960000e-007 5.9820550e-002 1.8970000e-007 4.5205220e-002 1.8980000e-007 3.4044527e-002 1.8990000e-007 1.1735696e-002 1.9000000e-007 -5.6269298e-003 1.9010000e-007 -1.1891051e-002 1.9020000e-007 -3.3096504e-002 1.9030000e-007 -4.9370950e-002 1.9040000e-007 -5.9907305e-002 1.9050000e-007 -7.8862785e-002 1.9060000e-007 -9.2093717e-002 1.9070000e-007 -1.0645525e-001 1.9080000e-007 -1.1862189e-001 1.9090000e-007 -1.3851102e-001 1.9100000e-007 -1.5263891e-001 1.9110000e-007 -1.6880503e-001 1.9120000e-007 -1.7814125e-001 1.9130000e-007 -1.9151041e-001 1.9140000e-007 -2.1110814e-001 1.9150000e-007 -2.2676165e-001 1.9160000e-007 -2.3850575e-001 1.9170000e-007 -2.4761172e-001 1.9180000e-007 -2.6639631e-001 1.9190000e-007 -2.8159059e-001 1.9200000e-007 -2.9120112e-001 1.9210000e-007 -3.0092027e-001 1.9220000e-007 -3.1557437e-001 1.9230000e-007 -3.2395779e-001 1.9240000e-007 -3.4221984e-001 1.9250000e-007 -3.4281196e-001 1.9260000e-007 -3.6286552e-001 1.9270000e-007 -3.6823817e-001 1.9280000e-007 -3.7498043e-001 1.9290000e-007 -3.9065289e-001 1.9300000e-007 -3.9637577e-001 1.9310000e-007 -4.0340375e-001 1.9320000e-007 -4.1016562e-001 1.9330000e-007 -4.2127291e-001 1.9340000e-007 -4.3047787e-001 1.9350000e-007 -4.3788091e-001 1.9360000e-007 -4.4312382e-001 1.9370000e-007 -4.4638714e-001 1.9380000e-007 -4.5492327e-001 1.9390000e-007 -4.6192260e-001 1.9400000e-007 -4.6514545e-001 1.9410000e-007 -4.7010896e-001 1.9420000e-007 -4.7323972e-001 1.9430000e-007 -4.7936153e-001 1.9440000e-007 -4.8004047e-001 1.9450000e-007 -4.8167131e-001 1.9460000e-007 -4.8738683e-001 1.9470000e-007 -4.9453385e-001 1.9480000e-007 -4.9072518e-001 1.9490000e-007 -4.9554048e-001 1.9500000e-007 -4.9355514e-001 1.9510000e-007 -4.9725029e-001 1.9520000e-007 -4.9748411e-001 1.9530000e-007 -4.9373836e-001 1.9540000e-007 -4.9353915e-001 1.9550000e-007 -4.9014119e-001 1.9560000e-007 -4.8955805e-001 1.9570000e-007 -4.9648847e-001 1.9580000e-007 -4.9114402e-001 1.9590000e-007 -4.8513876e-001 1.9600000e-007 -4.7563597e-001 1.9610000e-007 -4.7683125e-001 1.9620000e-007 -4.6781154e-001 1.9630000e-007 -4.6666367e-001 1.9640000e-007 -4.6194801e-001 1.9650000e-007 -4.4870150e-001 1.9660000e-007 -4.4688327e-001 1.9670000e-007 -4.4019481e-001 1.9680000e-007 -4.2553368e-001 1.9690000e-007 -4.2005776e-001 1.9700000e-007 -4.1625428e-001 1.9710000e-007 -4.0637235e-001 1.9720000e-007 -3.9609702e-001 1.9730000e-007 -3.9274869e-001 1.9740000e-007 -3.7999306e-001 1.9750000e-007 -3.7175837e-001 1.9760000e-007 -3.5106328e-001 1.9770000e-007 -3.3837221e-001 1.9780000e-007 -3.3436092e-001 1.9790000e-007 -3.2327932e-001 1.9800000e-007 -3.1000479e-001 1.9810000e-007 -2.9532399e-001 1.9820000e-007 -2.8348331e-001 1.9830000e-007 -2.6443766e-001 1.9840000e-007 -2.4926776e-001 1.9850000e-007 -2.4278035e-001 1.9860000e-007 -2.2087524e-001 1.9870000e-007 -2.1850863e-001 1.9880000e-007 -1.9333166e-001 1.9890000e-007 -1.8237219e-001 1.9900000e-007 -1.6218589e-001 1.9910000e-007 -1.4724537e-001 1.9920000e-007 -1.2578049e-001 1.9930000e-007 -1.1438293e-001 1.9940000e-007 -9.6014470e-002 1.9950000e-007 -8.4905834e-002 1.9960000e-007 -7.0368079e-002 1.9970000e-007 -4.9290227e-002 1.9980000e-007 -3.6114504e-002 1.9990000e-007 -9.8802731e-003 2.0000000e-007 2.8397912e-003 2.0010000e-007 1.7809927e-002 2.0020000e-007 2.8459956e-002 2.0030000e-007 5.2921475e-002 2.0040000e-007 6.3293032e-002 2.0050000e-007 8.1733097e-002 2.0060000e-007 9.5630096e-002 2.0070000e-007 1.2024532e-001 2.0080000e-007 1.3520766e-001 2.0090000e-007 1.4777930e-001 2.0100000e-007 1.6819102e-001 2.0110000e-007 1.7707914e-001 2.0120000e-007 1.9442598e-001 2.0130000e-007 2.1387707e-001 2.0140000e-007 2.2682782e-001 2.0150000e-007 2.3448001e-001 2.0160000e-007 2.5333018e-001 2.0170000e-007 2.6794288e-001 2.0180000e-007 2.8177923e-001 2.0190000e-007 2.9329137e-001 2.0200000e-007 3.0926926e-001 2.0210000e-007 3.1637340e-001 2.0220000e-007 3.3111784e-001 2.0230000e-007 3.4564539e-001 2.0240000e-007 3.5664996e-001 2.0250000e-007 3.6515102e-001 2.0260000e-007 3.7918836e-001 2.0270000e-007 3.8786846e-001 2.0280000e-007 3.9906770e-001 2.0290000e-007 4.0780557e-001 2.0300000e-007 4.1974018e-001 2.0310000e-007 4.2392034e-001 2.0320000e-007 4.2639336e-001 2.0330000e-007 4.3530901e-001 2.0340000e-007 4.4592439e-001 2.0350000e-007 4.5015327e-001 2.0360000e-007 4.5776154e-001 2.0370000e-007 4.6744608e-001 2.0380000e-007 4.7251360e-001 2.0390000e-007 4.7519133e-001 2.0400000e-007 4.7942794e-001 2.0410000e-007 4.8311446e-001 2.0420000e-007 4.8872344e-001 2.0430000e-007 4.8528904e-001 2.0440000e-007 4.8891843e-001 2.0450000e-007 4.9366714e-001 2.0460000e-007 4.9240498e-001 2.0470000e-007 4.9164342e-001 2.0480000e-007 4.9596353e-001 2.0490000e-007 4.9067671e-001 2.0500000e-007 4.9813957e-001 2.0510000e-007 4.9462208e-001 2.0520000e-007 4.9263924e-001 2.0530000e-007 4.8868896e-001 2.0540000e-007 4.8395271e-001 2.0550000e-007 4.8003720e-001 2.0560000e-007 4.8210820e-001 2.0570000e-007 4.8238481e-001 2.0580000e-007 4.7080777e-001 2.0590000e-007 4.7119280e-001 2.0600000e-007 4.6543073e-001 2.0610000e-007 4.5966454e-001 2.0620000e-007 4.5853451e-001 2.0630000e-007 4.4651076e-001 2.0640000e-007 4.3955979e-001 2.0650000e-007 4.4263772e-001 2.0660000e-007 4.2432357e-001 2.0670000e-007 4.2215035e-001 2.0680000e-007 4.1604041e-001 2.0690000e-007 4.0925566e-001 2.0700000e-007 4.0006391e-001 2.0710000e-007 3.8657530e-001 2.0720000e-007 3.7779813e-001 2.0730000e-007 3.6904363e-001 2.0740000e-007 3.6127604e-001 2.0750000e-007 3.4048373e-001 2.0760000e-007 3.3401642e-001 2.0770000e-007 3.3019765e-001 2.0780000e-007 3.1503141e-001 2.0790000e-007 3.0046366e-001 2.0800000e-007 2.9264580e-001 2.0810000e-007 2.7727331e-001 2.0820000e-007 2.6614726e-001 2.0830000e-007 2.4721237e-001 2.0840000e-007 2.3487688e-001 2.0850000e-007 2.2701111e-001 2.0860000e-007 2.1341413e-001 2.0870000e-007 1.9574414e-001 2.0880000e-007 1.8052744e-001 2.0890000e-007 1.6259394e-001 2.0900000e-007 1.5320319e-001 2.0910000e-007 1.3706345e-001 2.0920000e-007 1.2303728e-001 2.0930000e-007 9.9564338e-002 2.0940000e-007 9.6819493e-002 2.0950000e-007 7.7609332e-002 2.0960000e-007 5.7199816e-002 2.0970000e-007 4.9943238e-002 2.0980000e-007 3.1048139e-002 2.0990000e-007 1.6502592e-002 2.1000000e-007 -3.7802616e-003 2.1010000e-007 -1.8784891e-002 2.1020000e-007 -2.6403878e-002 2.1030000e-007 -4.7558261e-002 2.1040000e-007 -6.3822260e-002 2.1050000e-007 -8.1243628e-002 2.1060000e-007 -9.3658830e-002 2.1070000e-007 -1.1019854e-001 2.1080000e-007 -1.2309320e-001 2.1090000e-007 -1.3513621e-001 2.1100000e-007 -1.5511391e-001 2.1110000e-007 -1.7033562e-001 2.1120000e-007 -1.8266903e-001 2.1130000e-007 -1.9718111e-001 2.1140000e-007 -2.0589673e-001 2.1150000e-007 -2.2525089e-001 2.1160000e-007 -2.3864229e-001 2.1170000e-007 -2.5177328e-001 2.1180000e-007 -2.6283849e-001 2.1190000e-007 -2.7901692e-001 2.1200000e-007 -2.9482087e-001 2.1210000e-007 -3.0103803e-001 2.1220000e-007 -3.1314973e-001 2.1230000e-007 -3.2167018e-001 2.1240000e-007 -3.3717186e-001 2.1250000e-007 -3.4868283e-001 2.1260000e-007 -3.6144751e-001 2.1270000e-007 -3.6518535e-001 2.1280000e-007 -3.7508802e-001 2.1290000e-007 -3.8568807e-001 2.1300000e-007 -3.9363420e-001 2.1310000e-007 -4.0826803e-001 2.1320000e-007 -4.1049458e-001 2.1330000e-007 -4.1977147e-001 2.1340000e-007 -4.3055681e-001 2.1350000e-007 -4.3892584e-001 2.1360000e-007 -4.4351698e-001 2.1370000e-007 -4.5214790e-001 2.1380000e-007 -4.5885984e-001 2.1390000e-007 -4.6060867e-001 2.1400000e-007 -4.6448017e-001 2.1410000e-007 -4.7104787e-001 2.1420000e-007 -4.7452147e-001 2.1430000e-007 -4.7964389e-001 2.1440000e-007 -4.8233494e-001 2.1450000e-007 -4.8563731e-001 2.1460000e-007 -4.8843934e-001 2.1470000e-007 -4.9356746e-001 2.1480000e-007 -4.9441706e-001 2.1490000e-007 -4.9568763e-001 2.1500000e-007 -4.9494068e-001 2.1510000e-007 -4.9279858e-001 2.1520000e-007 -4.9561147e-001 2.1530000e-007 -4.9682447e-001 2.1540000e-007 -4.8960463e-001 2.1550000e-007 -4.9259053e-001 2.1560000e-007 -4.9135840e-001 2.1570000e-007 -4.8807102e-001 2.1580000e-007 -4.8132431e-001 2.1590000e-007 -4.8031929e-001 2.1600000e-007 -4.7235856e-001 2.1610000e-007 -4.7520890e-001 2.1620000e-007 -4.7052144e-001 2.1630000e-007 -4.6163370e-001 2.1640000e-007 -4.5892864e-001 2.1650000e-007 -4.5332377e-001 2.1660000e-007 -4.5028717e-001 2.1670000e-007 -4.3638882e-001 2.1680000e-007 -4.2801153e-001 2.1690000e-007 -4.2335652e-001 2.1700000e-007 -4.1677713e-001 2.1710000e-007 -4.0226322e-001 2.1720000e-007 -4.0007837e-001 2.1730000e-007 -3.8560588e-001 2.1740000e-007 -3.7762110e-001 2.1750000e-007 -3.7075634e-001 2.1760000e-007 -3.5766021e-001 2.1770000e-007 -3.4214479e-001 2.1780000e-007 -3.3138414e-001 2.1790000e-007 -3.1706910e-001 2.1800000e-007 -3.0843196e-001 2.1810000e-007 -2.9032401e-001 2.1820000e-007 -2.8374920e-001 2.1830000e-007 -2.6661465e-001 2.1840000e-007 -2.5351973e-001 2.1850000e-007 -2.3886280e-001 2.1860000e-007 -2.2890526e-001 2.1870000e-007 -2.0994396e-001 2.1880000e-007 -1.9617411e-001 2.1890000e-007 -1.7991835e-001 2.1900000e-007 -1.6075270e-001 2.1910000e-007 -1.4697774e-001 2.1920000e-007 -1.3096455e-001 2.1930000e-007 -1.2378673e-001 2.1940000e-007 -1.0497220e-001 2.1950000e-007 -7.8110984e-002 2.1960000e-007 -6.5654772e-002 2.1970000e-007 -5.3602096e-002 2.1980000e-007 -3.1505662e-002 2.1990000e-007 -1.9072398e-002 2.2000000e-007 3.6740526e-003 2.2010000e-007 1.1776281e-002 2.2020000e-007 3.0901951e-002 2.2030000e-007 5.1405080e-002 2.2040000e-007 6.9564168e-002 2.2050000e-007 8.2574518e-002 2.2060000e-007 1.0141836e-001 2.2070000e-007 1.1675674e-001 2.2080000e-007 1.3181030e-001 2.2090000e-007 1.4734254e-001 2.2100000e-007 1.6213389e-001 2.2110000e-007 1.7831984e-001 2.2120000e-007 1.9788169e-001 2.2130000e-007 2.1092046e-001 2.2140000e-007 2.2276821e-001 2.2150000e-007 2.4145088e-001 2.2160000e-007 2.5127900e-001 2.2170000e-007 2.6683213e-001 2.2180000e-007 2.8314984e-001 2.2190000e-007 2.9383564e-001 2.2200000e-007 3.0639357e-001 2.2210000e-007 3.2179551e-001 2.2220000e-007 3.3341503e-001 2.2230000e-007 3.4457424e-001 2.2240000e-007 3.5454606e-001 2.2250000e-007 3.7114100e-001 2.2260000e-007 3.8299485e-001 2.2270000e-007 3.9312667e-001 2.2280000e-007 3.9686287e-001 2.2290000e-007 4.0759158e-001 2.2300000e-007 4.1035636e-001 2.2310000e-007 4.2658114e-001 2.2320000e-007 4.3477887e-001 2.2330000e-007 4.3986859e-001 2.2340000e-007 4.4643217e-001 2.2350000e-007 4.5311137e-001 2.2360000e-007 4.6044975e-001 2.2370000e-007 4.6622715e-001 2.2380000e-007 4.6980346e-001 2.2390000e-007 4.7238208e-001 2.2400000e-007 4.8090110e-001 2.2410000e-007 4.8104651e-001 2.2420000e-007 4.8877092e-001 2.2430000e-007 4.8921622e-001 2.2440000e-007 4.8889355e-001 2.2450000e-007 4.8787731e-001 2.2460000e-007 4.9056665e-001 2.2470000e-007 4.9363243e-001 2.2480000e-007 4.9493072e-001 2.2490000e-007 4.9531616e-001 2.2500000e-007 4.9149618e-001 2.2510000e-007 4.9072091e-001 2.2520000e-007 4.9156118e-001 2.2530000e-007 4.9160707e-001 2.2540000e-007 4.8423788e-001 2.2550000e-007 4.8519574e-001 2.2560000e-007 4.8235849e-001 2.2570000e-007 4.7382440e-001 2.2580000e-007 4.6896314e-001 2.2590000e-007 4.7063388e-001 2.2600000e-007 4.6911357e-001 2.2610000e-007 4.6094733e-001 2.2620000e-007 4.5793743e-001 2.2630000e-007 4.5207507e-001 2.2640000e-007 4.4723329e-001 2.2650000e-007 4.3579367e-001 2.2660000e-007 4.2661826e-001 2.2670000e-007 4.2572515e-001 2.2680000e-007 4.1771173e-001 2.2690000e-007 4.0411283e-001 2.2700000e-007 3.9783678e-001 2.2710000e-007 3.8558947e-001 2.2720000e-007 3.8130846e-001 2.2730000e-007 3.6656034e-001 2.2740000e-007 3.5898622e-001 2.2750000e-007 3.4858877e-001 2.2760000e-007 3.3288102e-001 2.2770000e-007 3.2387231e-001 2.2780000e-007 3.1290488e-001 2.2790000e-007 3.0036801e-001 2.2800000e-007 2.8564978e-001 2.2810000e-007 2.7269853e-001 2.2820000e-007 2.6119494e-001 2.2830000e-007 2.5376241e-001 2.2840000e-007 2.3677259e-001 2.2850000e-007 2.2098688e-001 2.2860000e-007 2.0640764e-001 2.2870000e-007 1.9457804e-001 2.2880000e-007 1.8378826e-001 2.2890000e-007 1.6732232e-001 2.2900000e-007 1.5198977e-001 2.2910000e-007 1.4010115e-001 2.2920000e-007 1.2093436e-001 2.2930000e-007 1.1006721e-001 2.2940000e-007 9.5077974e-002 2.2950000e-007 7.8829698e-002 2.2960000e-007 5.9520959e-002 2.2970000e-007 4.5498684e-002 2.2980000e-007 3.0377102e-002 2.2990000e-007 1.3058801e-002 2.3000000e-007 2.1184216e-003 2.3010000e-007 -2.1512853e-002 2.3020000e-007 -2.5858352e-002 2.3030000e-007 -4.9329865e-002 2.3040000e-007 -5.8281619e-002 2.3050000e-007 -7.4354714e-002 2.3060000e-007 -9.6336389e-002 2.3070000e-007 -1.0753958e-001 2.3080000e-007 -1.2105928e-001 2.3090000e-007 -1.4242334e-001 2.3100000e-007 -1.5582414e-001 2.3110000e-007 -1.7062032e-001 2.3120000e-007 -1.8197209e-001 2.3130000e-007 -1.9276145e-001 2.3140000e-007 -2.0759236e-001 2.3150000e-007 -2.2501546e-001 2.3160000e-007 -2.3966250e-001 2.3170000e-007 -2.5198303e-001 2.3180000e-007 -2.6747479e-001 2.3190000e-007 -2.7596039e-001 2.3200000e-007 -2.8689388e-001 2.3210000e-007 -2.9976722e-001 2.3220000e-007 -3.1274531e-001 2.3230000e-007 -3.2541172e-001 2.3240000e-007 -3.3703680e-001 2.3250000e-007 -3.4597536e-001 2.3260000e-007 -3.5922372e-001 2.3270000e-007 -3.7170128e-001 2.3280000e-007 -3.8072866e-001 2.3290000e-007 -3.8745973e-001 2.3300000e-007 -4.0432426e-001 2.3310000e-007 -4.0094040e-001 2.3320000e-007 -4.1758762e-001 2.3330000e-007 -4.1802251e-001 2.3340000e-007 -4.2868253e-001 2.3350000e-007 -4.3987107e-001 2.3360000e-007 -4.4819972e-001 2.3370000e-007 -4.4893823e-001 2.3380000e-007 -4.5049284e-001 2.3390000e-007 -4.6081066e-001 2.3400000e-007 -4.6482684e-001 2.3410000e-007 -4.7601125e-001 2.3420000e-007 -4.7293246e-001 2.3430000e-007 -4.7569096e-001 2.3440000e-007 -4.8204726e-001 2.3450000e-007 -4.8603658e-001 2.3460000e-007 -4.9003501e-001 2.3470000e-007 -4.9330116e-001 2.3480000e-007 -4.9259675e-001 2.3490000e-007 -4.9407769e-001 2.3500000e-007 -4.9443946e-001 2.3510000e-007 -4.9788613e-001 2.3520000e-007 -4.9782845e-001 2.3530000e-007 -4.9110411e-001 2.3540000e-007 -4.9198738e-001 2.3550000e-007 -4.9601922e-001 2.3560000e-007 -4.9720315e-001 2.3570000e-007 -4.8634499e-001 2.3580000e-007 -4.8478223e-001 2.3590000e-007 -4.8750534e-001 2.3600000e-007 -4.7858971e-001 2.3610000e-007 -4.7499875e-001 2.3620000e-007 -4.6608302e-001 2.3630000e-007 -4.7206800e-001 2.3640000e-007 -4.6239743e-001 2.3650000e-007 -4.5410306e-001 2.3660000e-007 -4.4535451e-001 2.3670000e-007 -4.4152698e-001 2.3680000e-007 -4.3463198e-001 2.3690000e-007 -4.2457640e-001 2.3700000e-007 -4.1192470e-001 2.3710000e-007 -4.0162747e-001 2.3720000e-007 -3.9437345e-001 2.3730000e-007 -3.8427299e-001 2.3740000e-007 -3.7726158e-001 2.3750000e-007 -3.6906879e-001 2.3760000e-007 -3.5820658e-001 2.3770000e-007 -3.4506152e-001 2.3780000e-007 -3.3501846e-001 2.3790000e-007 -3.1927873e-001 2.3800000e-007 -3.0454902e-001 2.3810000e-007 -2.9677576e-001 2.3820000e-007 -2.8091476e-001 2.3830000e-007 -2.6764778e-001 2.3840000e-007 -2.5441022e-001 2.3850000e-007 -2.3697427e-001 2.3860000e-007 -2.2502458e-001 2.3870000e-007 -2.0760256e-001 2.3880000e-007 -1.9197258e-001 2.3890000e-007 -1.8087053e-001 2.3900000e-007 -1.6994935e-001 2.3910000e-007 -1.4818378e-001 2.3920000e-007 -1.3524281e-001 2.3930000e-007 -1.1437140e-001 2.3940000e-007 -9.8348551e-002 2.3950000e-007 -8.0917755e-002 2.3960000e-007 -6.6154935e-002 2.3970000e-007 -5.0954643e-002 2.3980000e-007 -3.2841570e-002 2.3990000e-007 -1.4633736e-002 2.4000000e-007 -2.2444338e-003 2.4010000e-007 1.5741649e-002 2.4020000e-007 3.2870554e-002 2.4030000e-007 4.3540338e-002 2.4040000e-007 6.7615648e-002 2.4050000e-007 8.0021631e-002 2.4060000e-007 1.0327296e-001 2.4070000e-007 1.1953218e-001 2.4080000e-007 1.3032706e-001 2.4090000e-007 1.5194905e-001 2.4100000e-007 1.5909370e-001 2.4110000e-007 1.8104723e-001 2.4120000e-007 1.9218646e-001 2.4130000e-007 2.1181254e-001 2.4140000e-007 2.2568058e-001 2.4150000e-007 2.3683020e-001 2.4160000e-007 2.5961991e-001 2.4170000e-007 2.6826850e-001 2.4180000e-007 2.8233330e-001 2.4190000e-007 3.0014467e-001 2.4200000e-007 3.0907301e-001 2.4210000e-007 3.1450639e-001 2.4220000e-007 3.3592910e-001 2.4230000e-007 3.4286895e-001 2.4240000e-007 3.5716971e-001 2.4250000e-007 3.6119144e-001 2.4260000e-007 3.8002042e-001 2.4270000e-007 3.8809281e-001 2.4280000e-007 3.9966129e-001 2.4290000e-007 4.0769540e-001 2.4300000e-007 4.1199766e-001 2.4310000e-007 4.2351358e-001 2.4320000e-007 4.3062922e-001 2.4330000e-007 4.3862790e-001 2.4340000e-007 4.5174542e-001 2.4350000e-007 4.4810415e-001 2.4360000e-007 4.5666221e-001 2.4370000e-007 4.6494917e-001 2.4380000e-007 4.6598936e-001 2.4390000e-007 4.6777504e-001 2.4400000e-007 4.7952373e-001 2.4410000e-007 4.7985244e-001 2.4420000e-007 4.8634066e-001 2.4430000e-007 4.8722029e-001 2.4440000e-007 4.8898210e-001 2.4450000e-007 4.9308496e-001 2.4460000e-007 4.9095635e-001 2.4470000e-007 4.9171195e-001 2.4480000e-007 4.9214860e-001 2.4490000e-007 4.9594135e-001 2.4500000e-007 4.9822449e-001 2.4510000e-007 4.9461556e-001 2.4520000e-007 4.9713409e-001 2.4530000e-007 4.9163485e-001 2.4540000e-007 4.8854822e-001 2.4550000e-007 4.8798127e-001 2.4560000e-007 4.7807652e-001 2.4570000e-007 4.8243953e-001 2.4580000e-007 4.7412738e-001 2.4590000e-007 4.6837463e-001 2.4600000e-007 4.6602003e-001 2.4610000e-007 4.6131337e-001 2.4620000e-007 4.5661406e-001 2.4630000e-007 4.4553160e-001 2.4640000e-007 4.4234187e-001 2.4650000e-007 4.3631357e-001 2.4660000e-007 4.2935275e-001 2.4670000e-007 4.2144737e-001 2.4680000e-007 4.1556130e-001 2.4690000e-007 4.0556493e-001 2.4700000e-007 4.0003215e-001 2.4710000e-007 3.9331680e-001 2.4720000e-007 3.7694891e-001 2.4730000e-007 3.6601328e-001 2.4740000e-007 3.5668229e-001 2.4750000e-007 3.4718387e-001 2.4760000e-007 3.4064717e-001 2.4770000e-007 3.2238779e-001 2.4780000e-007 3.0989434e-001 2.4790000e-007 3.0333291e-001 2.4800000e-007 2.9280918e-001 2.4810000e-007 2.7524821e-001 2.4820000e-007 2.6432318e-001 2.4830000e-007 2.4033919e-001 2.4840000e-007 2.3736138e-001 2.4850000e-007 2.2120095e-001 2.4860000e-007 2.0857475e-001 2.4870000e-007 1.9393131e-001 2.4880000e-007 1.7939649e-001 2.4890000e-007 1.6398399e-001 2.4900000e-007 1.5612177e-001 2.4910000e-007 1.4233450e-001 2.4920000e-007 1.2256749e-001 2.4930000e-007 1.0534285e-001 2.4940000e-007 9.5826776e-002 2.4950000e-007 7.6203311e-002 2.4960000e-007 6.0122656e-002 2.4970000e-007 4.6823615e-002 2.4980000e-007 3.5784663e-002 2.4990000e-007 1.1838115e-002 2.5000000e-007 -1.5565453e-003 2.5010000e-007 -1.6964467e-002 2.5020000e-007 -3.4531951e-002 2.5030000e-007 -4.4835308e-002 2.5040000e-007 -6.0970047e-002 2.5050000e-007 -8.6881118e-002 2.5060000e-007 -9.2424362e-002 2.5070000e-007 -1.0527731e-001 2.5080000e-007 -1.2516923e-001 2.5090000e-007 -1.4084088e-001 2.5100000e-007 -1.5432349e-001 2.5110000e-007 -1.6672478e-001 2.5120000e-007 -1.7789857e-001 2.5130000e-007 -1.9806251e-001 2.5140000e-007 -2.1062766e-001 2.5150000e-007 -2.3309788e-001 2.5160000e-007 -2.3716410e-001 2.5170000e-007 -2.5361280e-001 2.5180000e-007 -2.6212633e-001 2.5190000e-007 -2.7644272e-001 2.5200000e-007 -2.9098982e-001 2.5210000e-007 -3.0303490e-001 2.5220000e-007 -3.1455185e-001 2.5230000e-007 -3.2873394e-001 2.5240000e-007 -3.3593344e-001 2.5250000e-007 -3.4655220e-001 2.5260000e-007 -3.6017318e-001 2.5270000e-007 -3.6985821e-001 2.5280000e-007 -3.7406281e-001 2.5290000e-007 -3.8425008e-001 2.5300000e-007 -3.9624564e-001 2.5310000e-007 -4.0129703e-001 2.5320000e-007 -4.1565318e-001 2.5330000e-007 -4.2039406e-001 2.5340000e-007 -4.3067566e-001 2.5350000e-007 -4.3487045e-001 2.5360000e-007 -4.4394321e-001 2.5370000e-007 -4.4803098e-001 2.5380000e-007 -4.5452849e-001 2.5390000e-007 -4.6237694e-001 2.5400000e-007 -4.6927118e-001 2.5410000e-007 -4.7492320e-001 2.5420000e-007 -4.8056654e-001 2.5430000e-007 -4.8158310e-001 2.5440000e-007 -4.8124469e-001 2.5450000e-007 -4.8483361e-001 2.5460000e-007 -4.8759668e-001 2.5470000e-007 -4.9440164e-001 2.5480000e-007 -4.9418264e-001 2.5490000e-007 -4.9833148e-001 2.5500000e-007 -4.8944188e-001 2.5510000e-007 -4.9765338e-001 2.5520000e-007 -4.9310004e-001 2.5530000e-007 -4.9454516e-001 2.5540000e-007 -4.9463171e-001 2.5550000e-007 -4.8655893e-001 2.5560000e-007 -4.9360948e-001 2.5570000e-007 -4.8832454e-001 2.5580000e-007 -4.8610160e-001 2.5590000e-007 -4.8598962e-001 2.5600000e-007 -4.7886746e-001 2.5610000e-007 -4.7507182e-001 2.5620000e-007 -4.7177855e-001 2.5630000e-007 -4.6613196e-001 2.5640000e-007 -4.5582682e-001 2.5650000e-007 -4.5591777e-001 2.5660000e-007 -4.4678190e-001 2.5670000e-007 -4.4125776e-001 2.5680000e-007 -4.2965703e-001 2.5690000e-007 -4.2377553e-001 2.5700000e-007 -4.1983786e-001 2.5710000e-007 -4.0987849e-001 2.5720000e-007 -3.9505439e-001 2.5730000e-007 -3.8587294e-001 2.5740000e-007 -3.7600847e-001 2.5750000e-007 -3.7184648e-001 2.5760000e-007 -3.5569545e-001 2.5770000e-007 -3.4445591e-001 2.5780000e-007 -3.3095210e-001 2.5790000e-007 -3.2374845e-001 2.5800000e-007 -3.1094609e-001 2.5810000e-007 -2.9526685e-001 2.5820000e-007 -2.8336106e-001 2.5830000e-007 -2.6258847e-001 2.5840000e-007 -2.4841422e-001 2.5850000e-007 -2.3479641e-001 2.5860000e-007 -2.2969130e-001 2.5870000e-007 -2.0994033e-001 2.5880000e-007 -1.9531774e-001 2.5890000e-007 -1.7381974e-001 2.5900000e-007 -1.6287561e-001 2.5910000e-007 -1.4647335e-001 2.5920000e-007 -1.3434440e-001 2.5930000e-007 -1.1352370e-001 2.5940000e-007 -1.0605860e-001 2.5950000e-007 -8.5627560e-002 2.5960000e-007 -5.9277711e-002 2.5970000e-007 -4.6240385e-002 2.5980000e-007 -3.4572987e-002 2.5990000e-007 -1.5155297e-002 2.6000000e-007 2.8731674e-003 2.6010000e-007 1.8887894e-002 2.6020000e-007 3.3270692e-002 2.6030000e-007 5.1409814e-002 2.6040000e-007 6.3152732e-002 2.6050000e-007 8.0008815e-002 2.6060000e-007 9.7719750e-002 2.6070000e-007 1.2210159e-001 2.6080000e-007 1.3099477e-001 2.6090000e-007 1.4266910e-001 2.6100000e-007 1.6241554e-001 2.6110000e-007 1.7955419e-001 2.6120000e-007 1.8854838e-001 2.6130000e-007 2.0680861e-001 2.6140000e-007 2.2427001e-001 2.6150000e-007 2.4168736e-001 2.6160000e-007 2.5947302e-001 2.6170000e-007 2.7077950e-001 2.6180000e-007 2.8151735e-001 2.6190000e-007 2.9677571e-001 2.6200000e-007 3.0810665e-001 2.6210000e-007 3.1859813e-001 2.6220000e-007 3.3034075e-001 2.6230000e-007 3.4393405e-001 2.6240000e-007 3.5862307e-001 2.6250000e-007 3.6763721e-001 2.6260000e-007 3.7616152e-001 2.6270000e-007 3.8385598e-001 2.6280000e-007 3.9659097e-001 2.6290000e-007 4.0486585e-001 2.6300000e-007 4.1459361e-001 2.6310000e-007 4.1839443e-001 2.6320000e-007 4.3776198e-001 2.6330000e-007 4.4200307e-001 2.6340000e-007 4.4849899e-001 2.6350000e-007 4.5274757e-001 2.6360000e-007 4.5749551e-001 2.6370000e-007 4.6056192e-001 2.6380000e-007 4.6904938e-001 2.6390000e-007 4.6934475e-001 2.6400000e-007 4.8039180e-001 2.6410000e-007 4.7808023e-001 2.6420000e-007 4.8835023e-001 2.6430000e-007 4.8778316e-001 2.6440000e-007 4.9471732e-001 2.6450000e-007 4.9307631e-001 2.6460000e-007 4.8951188e-001 2.6470000e-007 4.9802336e-001 2.6480000e-007 4.9631146e-001 2.6490000e-007 4.9494912e-001 2.6500000e-007 4.9456981e-001 2.6510000e-007 4.9460920e-001 2.6520000e-007 4.9280537e-001 2.6530000e-007 4.9346667e-001 2.6540000e-007 4.8425298e-001 2.6550000e-007 4.8437918e-001 2.6560000e-007 4.8464500e-001 2.6570000e-007 4.7876673e-001 2.6580000e-007 4.7463078e-001 2.6590000e-007 4.7109015e-001 2.6600000e-007 4.6758426e-001 2.6610000e-007 4.6405939e-001 2.6620000e-007 4.5837229e-001 2.6630000e-007 4.4901726e-001 2.6640000e-007 4.4678566e-001 2.6650000e-007 4.3666249e-001 2.6660000e-007 4.3068579e-001 2.6670000e-007 4.2219569e-001 2.6680000e-007 4.1515487e-001 2.6690000e-007 4.0588899e-001 2.6700000e-007 3.9474114e-001 2.6710000e-007 3.9148916e-001 2.6720000e-007 3.7141582e-001 2.6730000e-007 3.6752551e-001 2.6740000e-007 3.5665670e-001 2.6750000e-007 3.4626244e-001 2.6760000e-007 3.3508726e-001 2.6770000e-007 3.3023839e-001 2.6780000e-007 3.0701561e-001 2.6790000e-007 3.0126530e-001 2.6800000e-007 2.9199174e-001 2.6810000e-007 2.7958635e-001 2.6820000e-007 2.6274823e-001 2.6830000e-007 2.4932948e-001 2.6840000e-007 2.3808886e-001 2.6850000e-007 2.2359321e-001 2.6860000e-007 2.1346171e-001 2.6870000e-007 1.9424890e-001 2.6880000e-007 1.8547347e-001 2.6890000e-007 1.6529064e-001 2.6900000e-007 1.5172945e-001 2.6910000e-007 1.3493342e-001 2.6920000e-007 1.2350085e-001 2.6930000e-007 1.0525548e-001 2.6940000e-007 8.8706183e-002 2.6950000e-007 7.5985618e-002 2.6960000e-007 5.8187252e-002 2.6970000e-007 5.1020879e-002 2.6980000e-007 3.1698000e-002 2.6990000e-007 1.5933420e-002 2.7000000e-007 -5.3238377e-003 2.7010000e-007 -1.4137248e-002 2.7020000e-007 -3.1501727e-002 2.7030000e-007 -4.9264901e-002 2.7040000e-007 -6.0656579e-002 2.7050000e-007 -8.2161078e-002 2.7060000e-007 -9.6101783e-002 2.7070000e-007 -1.0281261e-001 2.7080000e-007 -1.1772516e-001 2.7090000e-007 -1.3832103e-001 2.7100000e-007 -1.5896489e-001 2.7110000e-007 -1.6720303e-001 2.7120000e-007 -1.8011335e-001 2.7130000e-007 -1.9274238e-001 2.7140000e-007 -2.0505014e-001 2.7150000e-007 -2.1735247e-001 2.7160000e-007 -2.3848477e-001 2.7170000e-007 -2.5464444e-001 2.7180000e-007 -2.6235639e-001 2.7190000e-007 -2.6863630e-001 2.7200000e-007 -2.8677595e-001 2.7210000e-007 -3.0253042e-001 2.7220000e-007 -3.1436085e-001 2.7230000e-007 -3.2040863e-001 2.7240000e-007 -3.3696522e-001 2.7250000e-007 -3.4807337e-001 2.7260000e-007 -3.5903904e-001 2.7270000e-007 -3.6260460e-001 2.7280000e-007 -3.7859477e-001 2.7290000e-007 -3.9229391e-001 2.7300000e-007 -3.9767323e-001 2.7310000e-007 -4.0373897e-001 2.7320000e-007 -4.0913966e-001 2.7330000e-007 -4.2221571e-001 2.7340000e-007 -4.2687742e-001 2.7350000e-007 -4.3611391e-001 2.7360000e-007 -4.3915787e-001 2.7370000e-007 -4.5125620e-001 2.7380000e-007 -4.5751506e-001 2.7390000e-007 -4.6095526e-001 2.7400000e-007 -4.6362093e-001 2.7410000e-007 -4.7039453e-001 2.7420000e-007 -4.7403551e-001 2.7430000e-007 -4.7837492e-001 2.7440000e-007 -4.8472706e-001 2.7450000e-007 -4.8297290e-001 2.7460000e-007 -4.9052183e-001 2.7470000e-007 -4.9548852e-001 2.7480000e-007 -4.9363900e-001 2.7490000e-007 -4.9586111e-001 2.7500000e-007 -4.9584164e-001 2.7510000e-007 -4.9041529e-001 2.7520000e-007 -4.9565299e-001 2.7530000e-007 -4.9789487e-001 2.7540000e-007 -4.9356463e-001 2.7550000e-007 -4.9267734e-001 2.7560000e-007 -4.8923489e-001 2.7570000e-007 -4.8509489e-001 2.7580000e-007 -4.8818791e-001 2.7590000e-007 -4.8091172e-001 2.7600000e-007 -4.8305940e-001 2.7610000e-007 -4.7118961e-001 2.7620000e-007 -4.7350788e-001 2.7630000e-007 -4.6447100e-001 2.7640000e-007 -4.6354143e-001 2.7650000e-007 -4.5294367e-001 2.7660000e-007 -4.4854567e-001 2.7670000e-007 -4.3684178e-001 2.7680000e-007 -4.3167408e-001 2.7690000e-007 -4.2422541e-001 2.7700000e-007 -4.1462304e-001 2.7710000e-007 -4.0655546e-001 2.7720000e-007 -4.0431162e-001 2.7730000e-007 -3.8909071e-001 2.7740000e-007 -3.8059086e-001 2.7750000e-007 -3.6495368e-001 2.7760000e-007 -3.6076498e-001 2.7770000e-007 -3.4337007e-001 2.7780000e-007 -3.3204042e-001 2.7790000e-007 -3.1818432e-001 2.7800000e-007 -3.0692970e-001 2.7810000e-007 -2.9662833e-001 2.7820000e-007 -2.8076118e-001 2.7830000e-007 -2.7077419e-001 2.7840000e-007 -2.5427896e-001 2.7850000e-007 -2.3936697e-001 2.7860000e-007 -2.2944585e-001 2.7870000e-007 -2.1426994e-001 2.7880000e-007 -1.9390937e-001 2.7890000e-007 -1.7809083e-001 2.7900000e-007 -1.6668282e-001 2.7910000e-007 -1.5056054e-001 2.7920000e-007 -1.3022234e-001 2.7930000e-007 -1.2179034e-001 2.7940000e-007 -9.4882199e-002 2.7950000e-007 -8.4776356e-002 2.7960000e-007 -6.6964571e-002 2.7970000e-007 -5.0337331e-002 2.7980000e-007 -3.6771034e-002 2.7990000e-007 -1.6562977e-002 2.8000000e-007 3.4080830e-004 2.8010000e-007 1.5774834e-002 2.8020000e-007 3.3868491e-002 2.8030000e-007 4.8975788e-002 2.8040000e-007 6.5389552e-002 2.8050000e-007 8.6477959e-002 2.8060000e-007 1.0419448e-001 2.8070000e-007 1.1384141e-001 2.8080000e-007 1.3207083e-001 2.8090000e-007 1.5196306e-001 2.8100000e-007 1.6344125e-001 2.8110000e-007 1.8088491e-001 2.8120000e-007 2.0037389e-001 2.8130000e-007 2.0774123e-001 2.8140000e-007 2.2393592e-001 2.8150000e-007 2.3994863e-001 2.8160000e-007 2.5642653e-001 2.8170000e-007 2.6549124e-001 2.8180000e-007 2.8143148e-001 2.8190000e-007 2.9716563e-001 2.8200000e-007 3.0760984e-001 2.8210000e-007 3.1948795e-001 2.8220000e-007 3.3531503e-001 2.8230000e-007 3.5064358e-001 2.8240000e-007 3.5873153e-001 2.8250000e-007 3.6567343e-001 2.8260000e-007 3.7370819e-001 2.8270000e-007 3.8921182e-001 2.8280000e-007 3.9560596e-001 2.8290000e-007 4.0086538e-001 2.8300000e-007 4.1478379e-001 2.8310000e-007 4.2264045e-001 2.8320000e-007 4.2772434e-001 2.8330000e-007 4.3909389e-001 2.8340000e-007 4.4546194e-001 2.8350000e-007 4.5595613e-001 2.8360000e-007 4.5949103e-001 2.8370000e-007 4.6250139e-001 2.8380000e-007 4.7037961e-001 2.8390000e-007 4.7125882e-001 2.8400000e-007 4.7560139e-001 2.8410000e-007 4.7697344e-001 2.8420000e-007 4.8743327e-001 2.8430000e-007 4.9019216e-001 2.8440000e-007 4.8639315e-001 2.8450000e-007 4.8379327e-001 2.8460000e-007 4.9666492e-001 2.8470000e-007 4.9120601e-001 2.8480000e-007 4.9589976e-001 2.8490000e-007 4.9560520e-001 2.8500000e-007 4.9870484e-001 2.8510000e-007 4.9286539e-001 2.8520000e-007 4.9700279e-001 2.8530000e-007 4.8861606e-001 2.8540000e-007 4.8851236e-001 2.8550000e-007 4.8828219e-001 2.8560000e-007 4.8318796e-001 2.8570000e-007 4.8219613e-001 2.8580000e-007 4.7763954e-001 2.8590000e-007 4.6896889e-001 2.8600000e-007 4.6719580e-001 2.8610000e-007 4.6499457e-001 2.8620000e-007 4.5643594e-001 2.8630000e-007 4.4860292e-001 2.8640000e-007 4.4466942e-001 2.8650000e-007 4.3519109e-001 2.8660000e-007 4.3189084e-001 2.8670000e-007 4.1715146e-001 2.8680000e-007 4.0957729e-001 2.8690000e-007 4.0185176e-001 2.8700000e-007 3.9641691e-001 2.8710000e-007 3.8957408e-001 2.8720000e-007 3.8362954e-001 2.8730000e-007 3.6857913e-001 2.8740000e-007 3.6082320e-001 2.8750000e-007 3.5000725e-001 2.8760000e-007 3.3922077e-001 2.8770000e-007 3.2668350e-001 2.8780000e-007 3.1664296e-001 2.8790000e-007 3.0379811e-001 2.8800000e-007 2.8983335e-001 2.8810000e-007 2.7692997e-001 2.8820000e-007 2.5997870e-001 2.8830000e-007 2.5587383e-001 2.8840000e-007 2.4020439e-001 2.8850000e-007 2.2662983e-001 2.8860000e-007 2.1065478e-001 2.8870000e-007 1.9706663e-001 2.8880000e-007 1.8506158e-001 2.8890000e-007 1.6865884e-001 2.8900000e-007 1.5684222e-001 2.8910000e-007 1.3962043e-001 2.8920000e-007 1.2149177e-001 2.8930000e-007 1.0920959e-001 2.8940000e-007 9.2246428e-002 2.8950000e-007 8.0146197e-002 2.8960000e-007 5.9313419e-002 2.8970000e-007 5.1146908e-002 2.8980000e-007 3.2152794e-002 2.8990000e-007 1.5224685e-002 2.9000000e-007 2.1467482e-003 2.9010000e-007 -1.3403327e-002 2.9020000e-007 -3.0381925e-002 2.9030000e-007 -4.8720784e-002 2.9040000e-007 -6.3556556e-002 2.9050000e-007 -7.5968818e-002 2.9060000e-007 -9.0224136e-002 2.9070000e-007 -1.1437909e-001 2.9080000e-007 -1.3075743e-001 2.9090000e-007 -1.3313974e-001 2.9100000e-007 -1.5403383e-001 2.9110000e-007 -1.7209884e-001 2.9120000e-007 -1.8047870e-001 2.9130000e-007 -1.9794729e-001 2.9140000e-007 -2.1313856e-001 2.9150000e-007 -2.2265202e-001 2.9160000e-007 -2.4011024e-001 2.9170000e-007 -2.5168072e-001 2.9180000e-007 -2.6352797e-001 2.9190000e-007 -2.7431310e-001 2.9200000e-007 -2.9100397e-001 2.9210000e-007 -3.0027703e-001 2.9220000e-007 -3.1525712e-001 2.9230000e-007 -3.1999773e-001 2.9240000e-007 -3.3585605e-001 2.9250000e-007 -3.4761799e-001 2.9260000e-007 -3.5942120e-001 2.9270000e-007 -3.6670592e-001 2.9280000e-007 -3.7870973e-001 2.9290000e-007 -3.8374819e-001 2.9300000e-007 -3.9696797e-001 2.9310000e-007 -4.1059364e-001 2.9320000e-007 -4.0441149e-001 2.9330000e-007 -4.2146035e-001 2.9340000e-007 -4.3550370e-001 2.9350000e-007 -4.3468588e-001 2.9360000e-007 -4.4161793e-001 2.9370000e-007 -4.4886367e-001 2.9380000e-007 -4.5767515e-001 2.9390000e-007 -4.6327803e-001 2.9400000e-007 -4.7067403e-001 2.9410000e-007 -4.6835177e-001 2.9420000e-007 -4.7278211e-001 2.9430000e-007 -4.8120233e-001 2.9440000e-007 -4.8358099e-001 2.9450000e-007 -4.8314076e-001 2.9460000e-007 -4.8825631e-001 2.9470000e-007 -4.9364201e-001 2.9480000e-007 -4.9216938e-001 2.9490000e-007 -4.9782887e-001 2.9500000e-007 -4.9371096e-001 2.9510000e-007 -4.9180381e-001 2.9520000e-007 -4.9696251e-001 2.9530000e-007 -4.9693777e-001 2.9540000e-007 -4.9664965e-001 2.9550000e-007 -4.9362157e-001 2.9560000e-007 -4.9019573e-001 2.9570000e-007 -4.8713605e-001 2.9580000e-007 -4.8256025e-001 2.9590000e-007 -4.7712829e-001 2.9600000e-007 -4.7638222e-001 2.9610000e-007 -4.7248110e-001 2.9620000e-007 -4.6873714e-001 2.9630000e-007 -4.6465749e-001 2.9640000e-007 -4.5698307e-001 2.9650000e-007 -4.4830867e-001 2.9660000e-007 -4.4322501e-001 2.9670000e-007 -4.4331952e-001 2.9680000e-007 -4.3357479e-001 2.9690000e-007 -4.2257988e-001 2.9700000e-007 -4.1592272e-001 2.9710000e-007 -4.1293081e-001 2.9720000e-007 -3.9293542e-001 2.9730000e-007 -3.8681364e-001 2.9740000e-007 -3.7737179e-001 2.9750000e-007 -3.6713124e-001 2.9760000e-007 -3.5540910e-001 2.9770000e-007 -3.5022645e-001 2.9780000e-007 -3.3233397e-001 2.9790000e-007 -3.2657567e-001 2.9800000e-007 -3.0643957e-001 2.9810000e-007 -2.9544227e-001 2.9820000e-007 -2.8250284e-001 2.9830000e-007 -2.6845812e-001 2.9840000e-007 -2.5238823e-001 2.9850000e-007 -2.3886548e-001 2.9860000e-007 -2.2572964e-001 2.9870000e-007 -2.0873982e-001 2.9880000e-007 -1.9522688e-001 2.9890000e-007 -1.8483891e-001 2.9900000e-007 -1.6137465e-001 2.9910000e-007 -1.4900983e-001 2.9920000e-007 -1.3156501e-001 2.9930000e-007 -1.1146528e-001 2.9940000e-007 -1.0458646e-001 2.9950000e-007 -8.6148045e-002 2.9960000e-007 -7.0561924e-002 2.9970000e-007 -5.3695688e-002 2.9980000e-007 -3.2859020e-002 2.9990000e-007 -2.1288052e-002 3.0000000e-007 -4.3055337e-004 3.0010000e-007 1.5911533e-002 3.0020000e-007 3.3309057e-002 3.0030000e-007 5.1031042e-002 3.0040000e-007 6.9674653e-002 3.0050000e-007 7.8322854e-002 3.0060000e-007 1.0121556e-001 3.0070000e-007 1.1560177e-001 3.0080000e-007 1.3748981e-001 3.0090000e-007 1.4523219e-001 3.0100000e-007 1.6147328e-001 3.0110000e-007 1.7826945e-001 3.0120000e-007 1.9572669e-001 3.0130000e-007 2.0376637e-001 3.0140000e-007 2.2562278e-001 3.0150000e-007 2.4205112e-001 3.0160000e-007 2.5935293e-001 3.0170000e-007 2.7404928e-001 3.0180000e-007 2.8093724e-001 3.0190000e-007 2.9714254e-001 3.0200000e-007 3.0477253e-001 3.0210000e-007 3.1714898e-001 3.0220000e-007 3.3198242e-001 3.0230000e-007 3.4751282e-001 3.0240000e-007 3.5299133e-001 3.0250000e-007 3.7502666e-001 3.0260000e-007 3.7419739e-001 3.0270000e-007 3.9251844e-001 3.0280000e-007 3.9591077e-001 3.0290000e-007 4.0090818e-001 3.0300000e-007 4.1688533e-001 3.0310000e-007 4.2767121e-001 3.0320000e-007 4.2886854e-001 3.0330000e-007 4.3880497e-001 3.0340000e-007 4.4546997e-001 3.0350000e-007 4.5173549e-001 3.0360000e-007 4.6050798e-001 3.0370000e-007 4.6683524e-001 3.0380000e-007 4.7115559e-001 3.0390000e-007 4.7350752e-001 3.0400000e-007 4.8366671e-001 3.0410000e-007 4.7955422e-001 3.0420000e-007 4.8535213e-001 3.0430000e-007 4.8900841e-001 3.0440000e-007 4.9078679e-001 3.0450000e-007 4.9454041e-001 3.0460000e-007 4.9352763e-001 3.0470000e-007 4.9214510e-001 3.0480000e-007 4.9620096e-001 3.0490000e-007 4.9771582e-001 3.0500000e-007 4.9210810e-001 3.0510000e-007 4.9332146e-001 3.0520000e-007 4.9443135e-001 3.0530000e-007 4.9281148e-001 3.0540000e-007 4.8319660e-001 3.0550000e-007 4.8407316e-001 3.0560000e-007 4.8936329e-001 3.0570000e-007 4.7806460e-001 3.0580000e-007 4.7284658e-001 3.0590000e-007 4.6708300e-001 3.0600000e-007 4.6740042e-001 3.0610000e-007 4.5546240e-001 3.0620000e-007 4.5078808e-001 3.0630000e-007 4.5108808e-001 3.0640000e-007 4.4054875e-001 3.0650000e-007 4.4096813e-001 3.0660000e-007 4.3175979e-001 3.0670000e-007 4.1838177e-001 3.0680000e-007 4.1745593e-001 3.0690000e-007 4.0751565e-001 3.0700000e-007 3.9741166e-001 3.0710000e-007 3.8870218e-001 3.0720000e-007 3.7539038e-001 3.0730000e-007 3.6748671e-001 3.0740000e-007 3.5327499e-001 3.0750000e-007 3.4719510e-001 3.0760000e-007 3.3568729e-001 3.0770000e-007 3.2373045e-001 3.0780000e-007 3.1162976e-001 3.0790000e-007 2.9836142e-001 3.0800000e-007 2.9103486e-001 3.0810000e-007 2.8074812e-001 3.0820000e-007 2.6858808e-001 3.0830000e-007 2.5222018e-001 3.0840000e-007 2.3731074e-001 3.0850000e-007 2.2529430e-001 3.0860000e-007 2.1427886e-001 3.0870000e-007 1.9645738e-001 3.0880000e-007 1.7803578e-001 3.0890000e-007 1.6546891e-001 3.0900000e-007 1.4954068e-001 3.0910000e-007 1.3534674e-001 3.0920000e-007 1.1736975e-001 3.0930000e-007 1.1053841e-001 3.0940000e-007 9.5097457e-002 3.0950000e-007 7.8762084e-002 3.0960000e-007 6.2720041e-002 3.0970000e-007 4.9492624e-002 3.0980000e-007 2.8975542e-002 3.0990000e-007 1.5793231e-002 3.1000000e-007 -1.0724623e-003 3.1010000e-007 -1.8892257e-002 3.1020000e-007 -3.3036300e-002 3.1030000e-007 -4.9353303e-002 3.1040000e-007 -6.5490250e-002 3.1050000e-007 -7.6745681e-002 3.1060000e-007 -9.7814760e-002 3.1070000e-007 -1.0204465e-001 3.1080000e-007 -1.2294819e-001 3.1090000e-007 -1.3770329e-001 3.1100000e-007 -1.5142785e-001 3.1110000e-007 -1.6567335e-001 3.1120000e-007 -1.8541194e-001 3.1130000e-007 -1.9443334e-001 3.1140000e-007 -2.0584019e-001 3.1150000e-007 -2.2476682e-001 3.1160000e-007 -2.3374633e-001 3.1170000e-007 -2.5126150e-001 3.1180000e-007 -2.6253760e-001 3.1190000e-007 -2.8147038e-001 3.1200000e-007 -2.9570773e-001 3.1210000e-007 -3.0435330e-001 3.1220000e-007 -3.1537917e-001 3.1230000e-007 -3.1794817e-001 3.1240000e-007 -3.3492930e-001 3.1250000e-007 -3.4724286e-001 3.1260000e-007 -3.6070906e-001 3.1270000e-007 -3.6891646e-001 3.1280000e-007 -3.8129178e-001 3.1290000e-007 -3.9014419e-001 3.1300000e-007 -3.9684581e-001 3.1310000e-007 -4.0279026e-001 3.1320000e-007 -4.1820340e-001 3.1330000e-007 -4.2261321e-001 3.1340000e-007 -4.2407061e-001 3.1350000e-007 -4.4153711e-001 3.1360000e-007 -4.4649904e-001 3.1370000e-007 -4.4458912e-001 3.1380000e-007 -4.5844951e-001 3.1390000e-007 -4.6151094e-001 3.1400000e-007 -4.6557002e-001 3.1410000e-007 -4.7053636e-001 3.1420000e-007 -4.7731275e-001 3.1430000e-007 -4.7731199e-001 3.1440000e-007 -4.8073003e-001 3.1450000e-007 -4.8341105e-001 3.1460000e-007 -4.8940265e-001 3.1470000e-007 -4.9371511e-001 3.1480000e-007 -4.9284673e-001 3.1490000e-007 -4.9513997e-001 3.1500000e-007 -4.9432342e-001 3.1510000e-007 -4.9443741e-001 3.1520000e-007 -4.9786719e-001 3.1530000e-007 -4.9535977e-001 3.1540000e-007 -4.9334964e-001 3.1550000e-007 -4.8649419e-001 3.1560000e-007 -4.9019802e-001 3.1570000e-007 -4.8917156e-001 3.1580000e-007 -4.8366783e-001 3.1590000e-007 -4.8172700e-001 3.1600000e-007 -4.8185173e-001 3.1610000e-007 -4.7497949e-001 3.1620000e-007 -4.6845410e-001 3.1630000e-007 -4.6285438e-001 3.1640000e-007 -4.6202863e-001 3.1650000e-007 -4.5339030e-001 3.1660000e-007 -4.4550719e-001 3.1670000e-007 -4.3897960e-001 3.1680000e-007 -4.3086653e-001 3.1690000e-007 -4.2341071e-001 3.1700000e-007 -4.1598679e-001 3.1710000e-007 -4.0625724e-001 3.1720000e-007 -3.9865278e-001 3.1730000e-007 -3.9078341e-001 3.1740000e-007 -3.8592662e-001 3.1750000e-007 -3.6952268e-001 3.1760000e-007 -3.5610471e-001 3.1770000e-007 -3.4291663e-001 3.1780000e-007 -3.3412869e-001 3.1790000e-007 -3.1514380e-001 3.1800000e-007 -3.0555176e-001 3.1810000e-007 -2.9512946e-001 3.1820000e-007 -2.8264427e-001 3.1830000e-007 -2.6819054e-001 3.1840000e-007 -2.4611391e-001 3.1850000e-007 -2.3868156e-001 3.1860000e-007 -2.2554444e-001 3.1870000e-007 -2.1575402e-001 3.1880000e-007 -1.9299111e-001 3.1890000e-007 -1.7648013e-001 3.1900000e-007 -1.6297199e-001 3.1910000e-007 -1.4669877e-001 3.1920000e-007 -1.3382275e-001 3.1930000e-007 -1.1865744e-001 3.1940000e-007 -9.9669160e-002 3.1950000e-007 -8.2586655e-002 3.1960000e-007 -6.5923739e-002 3.1970000e-007 -5.4651391e-002 3.1980000e-007 -3.3605082e-002 3.1990000e-007 -1.5090137e-002 3.2000000e-007 -3.9955788e-004 3.2010000e-007 1.8069836e-002 3.2020000e-007 3.4622707e-002 3.2030000e-007 5.1483634e-002 3.2040000e-007 6.8928847e-002 3.2050000e-007 8.5022961e-002 3.2060000e-007 1.0087166e-001 3.2070000e-007 1.1716920e-001 3.2080000e-007 1.3157746e-001 3.2090000e-007 1.4807904e-001 3.2100000e-007 1.6922140e-001 3.2110000e-007 1.8138742e-001 3.2120000e-007 1.9631105e-001 3.2130000e-007 2.1061116e-001 3.2140000e-007 2.2260994e-001 3.2150000e-007 2.4330442e-001 3.2160000e-007 2.5045254e-001 3.2170000e-007 2.6477539e-001 3.2180000e-007 2.7922530e-001 3.2190000e-007 2.9801515e-001 3.2200000e-007 3.0747866e-001 3.2210000e-007 3.2221345e-001 3.2220000e-007 3.3520904e-001 3.2230000e-007 3.4612790e-001 3.2240000e-007 3.5599994e-001 3.2250000e-007 3.6833257e-001 3.2260000e-007 3.7625178e-001 3.2270000e-007 3.8751320e-001 3.2280000e-007 4.0025664e-001 3.2290000e-007 4.0714065e-001 3.2300000e-007 4.1592958e-001 3.2310000e-007 4.3198040e-001 3.2320000e-007 4.4038353e-001 3.2330000e-007 4.3738414e-001 3.2340000e-007 4.4480033e-001 3.2350000e-007 4.5195084e-001 3.2360000e-007 4.5805924e-001 3.2370000e-007 4.6681886e-001 3.2380000e-007 4.6878315e-001 3.2390000e-007 4.7299682e-001 3.2400000e-007 4.7954036e-001 3.2410000e-007 4.7920187e-001 3.2420000e-007 4.8878089e-001 3.2430000e-007 4.9242425e-001 3.2440000e-007 4.8652998e-001 3.2450000e-007 4.8874483e-001 3.2460000e-007 4.9349262e-001 3.2470000e-007 4.9401001e-001 3.2480000e-007 4.8993469e-001 3.2490000e-007 5.0018721e-001 3.2500000e-007 4.8926798e-001 3.2510000e-007 4.9435439e-001 3.2520000e-007 4.9222270e-001 3.2530000e-007 4.9630813e-001 3.2540000e-007 4.9197013e-001 3.2550000e-007 4.8979994e-001 3.2560000e-007 4.7879785e-001 3.2570000e-007 4.7945081e-001 3.2580000e-007 4.7991638e-001 3.2590000e-007 4.7161060e-001 3.2600000e-007 4.6713613e-001 3.2610000e-007 4.6032282e-001 3.2620000e-007 4.5620385e-001 3.2630000e-007 4.4788162e-001 3.2640000e-007 4.4526801e-001 3.2650000e-007 4.3577061e-001 3.2660000e-007 4.2851288e-001 3.2670000e-007 4.1831616e-001 3.2680000e-007 4.1799512e-001 3.2690000e-007 4.0415409e-001 3.2700000e-007 3.9100874e-001 3.2710000e-007 3.9074088e-001 3.2720000e-007 3.7815407e-001 3.2730000e-007 3.6986926e-001 3.2740000e-007 3.5764440e-001 3.2750000e-007 3.4360626e-001 3.2760000e-007 3.3567942e-001 3.2770000e-007 3.2501266e-001 3.2780000e-007 3.1454362e-001 3.2790000e-007 3.0463804e-001 3.2800000e-007 2.8604521e-001 3.2810000e-007 2.7292171e-001 3.2820000e-007 2.6171215e-001 3.2830000e-007 2.5068930e-001 3.2840000e-007 2.4132922e-001 3.2850000e-007 2.2426425e-001 3.2860000e-007 2.1385806e-001 3.2870000e-007 1.9488836e-001 3.2880000e-007 1.8159819e-001 3.2890000e-007 1.6876344e-001 3.2900000e-007 1.5294247e-001 3.2910000e-007 1.4244886e-001 3.2920000e-007 1.2482439e-001 3.2930000e-007 1.1160103e-001 3.2940000e-007 9.5439579e-002 3.2950000e-007 7.8606608e-002 3.2960000e-007 6.0060613e-002 3.2970000e-007 4.4484501e-002 3.2980000e-007 3.0528281e-002 3.2990000e-007 1.4537966e-002 3.3000000e-007 1.0866243e-004 3.3010000e-007 -1.5989906e-002 3.3020000e-007 -3.4964107e-002 3.3030000e-007 -5.1778072e-002 3.3040000e-007 -6.3066738e-002 3.3050000e-007 -7.2050294e-002 3.3060000e-007 -8.8665882e-002 3.3070000e-007 -1.0623951e-001 3.3080000e-007 -1.2150614e-001 3.3090000e-007 -1.3501700e-001 3.3100000e-007 -1.5450540e-001 3.3110000e-007 -1.6816277e-001 3.3120000e-007 -1.8203072e-001 3.3130000e-007 -1.9965250e-001 3.3140000e-007 -2.1283585e-001 3.3150000e-007 -2.2490887e-001 3.3160000e-007 -2.3812835e-001 3.3170000e-007 -2.5400994e-001 3.3180000e-007 -2.6207334e-001 3.3190000e-007 -2.7371078e-001 3.3200000e-007 -2.9166730e-001 3.3210000e-007 -2.9703431e-001 3.3220000e-007 -3.1035905e-001 3.3230000e-007 -3.2054614e-001 3.3240000e-007 -3.3426957e-001 3.3250000e-007 -3.4321817e-001 3.3260000e-007 -3.6021593e-001 3.3270000e-007 -3.6438496e-001 3.3280000e-007 -3.8021559e-001 3.3290000e-007 -3.8601192e-001 3.3300000e-007 -3.9767224e-001 3.3310000e-007 -4.0674006e-001 3.3320000e-007 -4.0900444e-001 3.3330000e-007 -4.2335082e-001 3.3340000e-007 -4.3285286e-001 3.3350000e-007 -4.3903215e-001 3.3360000e-007 -4.4372298e-001 3.3370000e-007 -4.5467196e-001 3.3380000e-007 -4.5263439e-001 3.3390000e-007 -4.5673833e-001 3.3400000e-007 -4.6883185e-001 3.3410000e-007 -4.7356493e-001 3.3420000e-007 -4.8104920e-001 3.3430000e-007 -4.8086126e-001 3.3440000e-007 -4.8335105e-001 3.3450000e-007 -4.8213261e-001 3.3460000e-007 -4.9094498e-001 3.3470000e-007 -4.8476407e-001 3.3480000e-007 -4.9130529e-001 3.3490000e-007 -4.9355730e-001 3.3500000e-007 -4.9138559e-001 3.3510000e-007 -4.9693956e-001 3.3520000e-007 -4.9469746e-001 3.3530000e-007 -4.9291031e-001 3.3540000e-007 -4.9313985e-001 3.3550000e-007 -4.9289120e-001 3.3560000e-007 -4.8767341e-001 3.3570000e-007 -4.9433305e-001 3.3580000e-007 -4.8235615e-001 3.3590000e-007 -4.7991021e-001 3.3600000e-007 -4.7815040e-001 3.3610000e-007 -4.7456423e-001 3.3620000e-007 -4.7201708e-001 3.3630000e-007 -4.6253673e-001 3.3640000e-007 -4.5459364e-001 3.3650000e-007 -4.5605770e-001 3.3660000e-007 -4.5063618e-001 3.3670000e-007 -4.4049888e-001 3.3680000e-007 -4.3113970e-001 3.3690000e-007 -4.2271068e-001 3.3700000e-007 -4.1764770e-001 3.3710000e-007 -4.0669921e-001 3.3720000e-007 -3.9504224e-001 3.3730000e-007 -3.8825793e-001 3.3740000e-007 -3.7170792e-001 3.3750000e-007 -3.6886897e-001 3.3760000e-007 -3.5421853e-001 3.3770000e-007 -3.4713319e-001 3.3780000e-007 -3.3258475e-001 3.3790000e-007 -3.2199350e-001 3.3800000e-007 -3.0590354e-001 3.3810000e-007 -2.9744522e-001 3.3820000e-007 -2.8121079e-001 3.3830000e-007 -2.6773072e-001 3.3840000e-007 -2.5097091e-001 3.3850000e-007 -2.3923564e-001 3.3860000e-007 -2.2580643e-001 3.3870000e-007 -2.1688097e-001 3.3880000e-007 -1.9805449e-001 3.3890000e-007 -1.8080905e-001 3.3900000e-007 -1.6417408e-001 3.3910000e-007 -1.4633672e-001 3.3920000e-007 -1.3334350e-001 3.3930000e-007 -1.1805710e-001 3.3940000e-007 -1.0025995e-001 3.3950000e-007 -7.8812178e-002 3.3960000e-007 -6.4237094e-002 3.3970000e-007 -5.0441116e-002 3.3980000e-007 -3.3772677e-002 3.3990000e-007 -1.7950468e-002 3.4000000e-007 2.4542564e-003 3.4010000e-007 2.1652301e-002 3.4020000e-007 3.4329732e-002 3.4030000e-007 5.0574969e-002 3.4040000e-007 6.4706010e-002 3.4050000e-007 8.2444261e-002 3.4060000e-007 9.7349276e-002 3.4070000e-007 1.2048413e-001 3.4080000e-007 1.3425472e-001 3.4090000e-007 1.4624150e-001 3.4100000e-007 1.5679777e-001 3.4110000e-007 1.8159205e-001 3.4120000e-007 1.9601493e-001 3.4130000e-007 2.1053853e-001 3.4140000e-007 2.2478648e-001 3.4150000e-007 2.3609806e-001 3.4160000e-007 2.5650500e-001 3.4170000e-007 2.6915387e-001 3.4180000e-007 2.7971135e-001 3.4190000e-007 2.9623154e-001 3.4200000e-007 3.0242818e-001 3.4210000e-007 3.2098302e-001 3.4220000e-007 3.3162008e-001 3.4230000e-007 3.4268092e-001 3.4240000e-007 3.5719499e-001 3.4250000e-007 3.6561878e-001 3.4260000e-007 3.7530440e-001 3.4270000e-007 3.8687364e-001 3.4280000e-007 3.9579674e-001 3.4290000e-007 4.0404560e-001 3.4300000e-007 4.0855108e-001 3.4310000e-007 4.1801616e-001 3.4320000e-007 4.3049147e-001 3.4330000e-007 4.3806759e-001 3.4340000e-007 4.4685335e-001 3.4350000e-007 4.5712029e-001 3.4360000e-007 4.5753619e-001 3.4370000e-007 4.6792552e-001 3.4380000e-007 4.7320445e-001 3.4390000e-007 4.7526827e-001 3.4400000e-007 4.7899291e-001 3.4410000e-007 4.7800369e-001 3.4420000e-007 4.8764143e-001 3.4430000e-007 4.8533810e-001 3.4440000e-007 4.9592398e-001 3.4450000e-007 4.8948894e-001 3.4460000e-007 4.9337133e-001 3.4470000e-007 4.9352723e-001 3.4480000e-007 4.9347087e-001 3.4490000e-007 5.0038518e-001 3.4500000e-007 4.9261138e-001 3.4510000e-007 4.9238155e-001 3.4520000e-007 4.8861916e-001 3.4530000e-007 4.9072689e-001 3.4540000e-007 4.9100235e-001 3.4550000e-007 4.8510290e-001 3.4560000e-007 4.8786086e-001 3.4570000e-007 4.8204519e-001 3.4580000e-007 4.7505859e-001 3.4590000e-007 4.6843314e-001 3.4600000e-007 4.6471680e-001 3.4610000e-007 4.5756399e-001 3.4620000e-007 4.5294083e-001 3.4630000e-007 4.5310651e-001 3.4640000e-007 4.4441162e-001 3.4650000e-007 4.3694891e-001 3.4660000e-007 4.3094538e-001 3.4670000e-007 4.2187461e-001 3.4680000e-007 4.1623595e-001 3.4690000e-007 4.0234132e-001 3.4700000e-007 3.9397155e-001 3.4710000e-007 3.8934136e-001 3.4720000e-007 3.8341991e-001 3.4730000e-007 3.6659362e-001 3.4740000e-007 3.5949005e-001 3.4750000e-007 3.5141807e-001 3.4760000e-007 3.3889032e-001 3.4770000e-007 3.2743225e-001 3.4780000e-007 3.1391113e-001 3.4790000e-007 3.0227979e-001 3.4800000e-007 2.8828894e-001 3.4810000e-007 2.7231449e-001 3.4820000e-007 2.6656799e-001 3.4830000e-007 2.5602553e-001 3.4840000e-007 2.3775564e-001 3.4850000e-007 2.2524482e-001 3.4860000e-007 2.1127166e-001 3.4870000e-007 1.9032392e-001 3.4880000e-007 1.8400068e-001 3.4890000e-007 1.6462756e-001 3.4900000e-007 1.5265460e-001 3.4910000e-007 1.3760217e-001 3.4920000e-007 1.2771978e-001 3.4930000e-007 1.0721745e-001 3.4940000e-007 8.8104732e-002 3.4950000e-007 7.9861391e-002 3.4960000e-007 6.4679915e-002 3.4970000e-007 5.0644606e-002 3.4980000e-007 3.4198378e-002 3.4990000e-007 1.8709638e-002 3.5000000e-007 3.4282904e-004 3.5010000e-007 -1.6395061e-002 3.5020000e-007 -3.3549037e-002 3.5030000e-007 -4.6294829e-002 3.5040000e-007 -6.3366551e-002 3.5050000e-007 -7.8570365e-002 3.5060000e-007 -9.6222516e-002 3.5070000e-007 -1.0709054e-001 3.5080000e-007 -1.2489374e-001 3.5090000e-007 -1.3996499e-001 3.5100000e-007 -1.5281930e-001 3.5110000e-007 -1.6180060e-001 3.5120000e-007 -1.8464011e-001 3.5130000e-007 -2.0381123e-001 3.5140000e-007 -2.1190466e-001 3.5150000e-007 -2.1931336e-001 3.5160000e-007 -2.3736549e-001 3.5170000e-007 -2.5167643e-001 3.5180000e-007 -2.5938071e-001 3.5190000e-007 -2.7913046e-001 3.5200000e-007 -2.8942270e-001 3.5210000e-007 -3.0056711e-001 3.5220000e-007 -3.1182798e-001 3.5230000e-007 -3.2474517e-001 3.5240000e-007 -3.3626861e-001 3.5250000e-007 -3.4664706e-001 3.5260000e-007 -3.5580879e-001 3.5270000e-007 -3.6958008e-001 3.5280000e-007 -3.7250548e-001 3.5290000e-007 -3.9277341e-001 3.5300000e-007 -3.9647199e-001 3.5310000e-007 -4.0660755e-001 3.5320000e-007 -4.1396661e-001 3.5330000e-007 -4.1887735e-001 3.5340000e-007 -4.3328463e-001 3.5350000e-007 -4.3709340e-001 3.5360000e-007 -4.4076300e-001 3.5370000e-007 -4.5012219e-001 3.5380000e-007 -4.5977160e-001 3.5390000e-007 -4.5811445e-001 3.5400000e-007 -4.6832436e-001 3.5410000e-007 -4.7150918e-001 3.5420000e-007 -4.7270776e-001 3.5430000e-007 -4.7681421e-001 3.5440000e-007 -4.8318510e-001 3.5450000e-007 -4.8755574e-001 3.5460000e-007 -4.9117887e-001 3.5470000e-007 -4.8700153e-001 3.5480000e-007 -4.9649830e-001 3.5490000e-007 -4.9542614e-001 3.5500000e-007 -4.9369360e-001 3.5510000e-007 -4.9345420e-001 3.5520000e-007 -4.9819815e-001 3.5530000e-007 -4.9517315e-001 3.5540000e-007 -4.9942196e-001 3.5550000e-007 -4.8542478e-001 3.5560000e-007 -4.9323786e-001 3.5570000e-007 -4.8526699e-001 3.5580000e-007 -4.8759267e-001 3.5590000e-007 -4.8188075e-001 3.5600000e-007 -4.7973628e-001 3.5610000e-007 -4.7162132e-001 3.5620000e-007 -4.6574387e-001 3.5630000e-007 -4.6490034e-001 3.5640000e-007 -4.5960939e-001 3.5650000e-007 -4.5364330e-001 3.5660000e-007 -4.4800011e-001 3.5670000e-007 -4.4489056e-001 3.5680000e-007 -4.3365942e-001 3.5690000e-007 -4.3081139e-001 3.5700000e-007 -4.1658406e-001 3.5710000e-007 -4.0865485e-001 3.5720000e-007 -3.9687879e-001 3.5730000e-007 -3.8926164e-001 3.5740000e-007 -3.7650310e-001 3.5750000e-007 -3.7046745e-001 3.5760000e-007 -3.5809601e-001 3.5770000e-007 -3.4500829e-001 3.5780000e-007 -3.3570872e-001 3.5790000e-007 -3.2109262e-001 3.5800000e-007 -3.0463875e-001 3.5810000e-007 -2.9339516e-001 3.5820000e-007 -2.8184406e-001 3.5830000e-007 -2.7201247e-001 3.5840000e-007 -2.6081639e-001 3.5850000e-007 -2.3959719e-001 3.5860000e-007 -2.2781324e-001 3.5870000e-007 -2.1054362e-001 3.5880000e-007 -1.9638012e-001 3.5890000e-007 -1.8244710e-001 3.5900000e-007 -1.6031725e-001 3.5910000e-007 -1.5020769e-001 3.5920000e-007 -1.2826851e-001 3.5930000e-007 -1.1690912e-001 3.5940000e-007 -9.9539125e-002 3.5950000e-007 -8.2788809e-002 3.5960000e-007 -6.6373264e-002 3.5970000e-007 -5.1911600e-002 3.5980000e-007 -3.3271447e-002 3.5990000e-007 -1.5789236e-002 3.6000000e-007 -2.0861481e-004 3.6010000e-007 1.8443082e-002 3.6020000e-007 3.6444719e-002 3.6030000e-007 5.1356818e-002 3.6040000e-007 6.9448844e-002 3.6050000e-007 8.4419021e-002 3.6060000e-007 1.0128231e-001 3.6070000e-007 1.1797563e-001 3.6080000e-007 1.3141546e-001 3.6090000e-007 1.5170872e-001 3.6100000e-007 1.6721870e-001 3.6110000e-007 1.7971155e-001 3.6120000e-007 1.9294935e-001 3.6130000e-007 2.1095760e-001 3.6140000e-007 2.2757709e-001 3.6150000e-007 2.4345102e-001 3.6160000e-007 2.5144504e-001 3.6170000e-007 2.6963742e-001 3.6180000e-007 2.8454236e-001 3.6190000e-007 2.9599409e-001 3.6200000e-007 3.0711017e-001 3.6210000e-007 3.2527769e-001 3.6220000e-007 3.3059178e-001 3.6230000e-007 3.4650464e-001 3.6240000e-007 3.6022245e-001 3.6250000e-007 3.6706120e-001 3.6260000e-007 3.7866940e-001 3.6270000e-007 3.9122831e-001 3.6280000e-007 3.9441645e-001 3.6290000e-007 4.0490364e-001 3.6300000e-007 4.1801947e-001 3.6310000e-007 4.2561991e-001 3.6320000e-007 4.2985738e-001 3.6330000e-007 4.3634737e-001 3.6340000e-007 4.4562054e-001 3.6350000e-007 4.5170876e-001 3.6360000e-007 4.6052273e-001 3.6370000e-007 4.6375313e-001 3.6380000e-007 4.6819453e-001 3.6390000e-007 4.7919989e-001 3.6400000e-007 4.7778876e-001 3.6410000e-007 4.8455633e-001 3.6420000e-007 4.9248616e-001 3.6430000e-007 4.8911041e-001 3.6440000e-007 4.9157338e-001 3.6450000e-007 4.8550812e-001 3.6460000e-007 4.9283389e-001 3.6470000e-007 4.9552431e-001 3.6480000e-007 4.9622789e-001 3.6490000e-007 4.9496551e-001 3.6500000e-007 4.9664986e-001 3.6510000e-007 4.9596170e-001 3.6520000e-007 4.9004382e-001 3.6530000e-007 4.9407584e-001 3.6540000e-007 4.9151976e-001 3.6550000e-007 4.8201320e-001 3.6560000e-007 4.8505606e-001 3.6570000e-007 4.7929815e-001 3.6580000e-007 4.8170025e-001 3.6590000e-007 4.7309367e-001 3.6600000e-007 4.6603081e-001 3.6610000e-007 4.6384578e-001 3.6620000e-007 4.5719254e-001 3.6630000e-007 4.4861194e-001 3.6640000e-007 4.4552607e-001 3.6650000e-007 4.3779983e-001 3.6660000e-007 4.2450853e-001 3.6670000e-007 4.2553337e-001 3.6680000e-007 4.0964375e-001 3.6690000e-007 4.0792975e-001 3.6700000e-007 3.9924620e-001 3.6710000e-007 3.8616121e-001 3.6720000e-007 3.7523678e-001 3.6730000e-007 3.7570703e-001 3.6740000e-007 3.5456772e-001 3.6750000e-007 3.5105172e-001 3.6760000e-007 3.3435294e-001 3.6770000e-007 3.2516786e-001 3.6780000e-007 3.1087500e-001 3.6790000e-007 3.0292906e-001 3.6800000e-007 2.8626579e-001 3.6810000e-007 2.7539292e-001 3.6820000e-007 2.6274744e-001 3.6830000e-007 2.5674947e-001 3.6840000e-007 2.3504751e-001 3.6850000e-007 2.2489197e-001 3.6860000e-007 2.0535744e-001 3.6870000e-007 1.9197916e-001 3.6880000e-007 1.8298740e-001 3.6890000e-007 1.7144850e-001 3.6900000e-007 1.4895745e-001 3.6910000e-007 1.3820886e-001 3.6920000e-007 1.2368723e-001 3.6930000e-007 1.0181782e-001 3.6940000e-007 9.3158317e-002 3.6950000e-007 7.5733818e-002 3.6960000e-007 6.2972933e-002 3.6970000e-007 5.1624931e-002 3.6980000e-007 3.0569938e-002 3.6990000e-007 1.7172411e-002 3.7000000e-007 3.3051004e-003 3.7010000e-007 -2.1729065e-002 3.7020000e-007 -2.9063450e-002 3.7030000e-007 -4.1691205e-002 3.7040000e-007 -6.3553640e-002 3.7050000e-007 -7.4363045e-002 3.7060000e-007 -9.3940686e-002 3.7070000e-007 -1.0488909e-001 3.7080000e-007 -1.1981559e-001 3.7090000e-007 -1.3860513e-001 3.7100000e-007 -1.5293845e-001 3.7110000e-007 -1.6864615e-001 3.7120000e-007 -1.8156905e-001 3.7130000e-007 -1.9473184e-001 3.7140000e-007 -2.0579881e-001 3.7150000e-007 -2.2000257e-001 3.7160000e-007 -2.3806331e-001 3.7170000e-007 -2.5045697e-001 3.7180000e-007 -2.6162759e-001 3.7190000e-007 -2.7579308e-001 3.7200000e-007 -2.8728692e-001 3.7210000e-007 -3.0184531e-001 3.7220000e-007 -3.1084930e-001 3.7230000e-007 -3.2782109e-001 3.7240000e-007 -3.3764635e-001 3.7250000e-007 -3.4842871e-001 3.7260000e-007 -3.5915895e-001 3.7270000e-007 -3.7136367e-001 3.7280000e-007 -3.8015009e-001 3.7290000e-007 -3.8677028e-001 3.7300000e-007 -3.9135729e-001 3.7310000e-007 -4.0612767e-001 3.7320000e-007 -4.1730986e-001 3.7330000e-007 -4.2339898e-001 3.7340000e-007 -4.3435861e-001 3.7350000e-007 -4.3190153e-001 3.7360000e-007 -4.4262946e-001 3.7370000e-007 -4.4953607e-001 3.7380000e-007 -4.5725754e-001 3.7390000e-007 -4.6405442e-001 3.7400000e-007 -4.6309167e-001 3.7410000e-007 -4.6702314e-001 3.7420000e-007 -4.7715305e-001 3.7430000e-007 -4.7890657e-001 3.7440000e-007 -4.8415286e-001 3.7450000e-007 -4.9121682e-001 3.7460000e-007 -4.8934017e-001 3.7470000e-007 -4.9215700e-001 3.7480000e-007 -4.8894092e-001 3.7490000e-007 -4.9793230e-001 3.7500000e-007 -4.9736738e-001 3.7510000e-007 -4.9783109e-001 3.7520000e-007 -4.9619441e-001 3.7530000e-007 -4.9585963e-001 3.7540000e-007 -4.9046431e-001 3.7550000e-007 -4.9055535e-001 3.7560000e-007 -4.8503539e-001 3.7570000e-007 -4.8445391e-001 3.7580000e-007 -4.8119920e-001 3.7590000e-007 -4.8340579e-001 3.7600000e-007 -4.7644345e-001 3.7610000e-007 -4.7293990e-001 3.7620000e-007 -4.6654300e-001 3.7630000e-007 -4.6304256e-001 3.7640000e-007 -4.6293624e-001 3.7650000e-007 -4.5346461e-001 3.7660000e-007 -4.4549060e-001 3.7670000e-007 -4.3742913e-001 3.7680000e-007 -4.2188136e-001 3.7690000e-007 -4.2389579e-001 3.7700000e-007 -4.1793561e-001 3.7710000e-007 -4.1193660e-001 3.7720000e-007 -4.0235249e-001 3.7730000e-007 -3.8995982e-001 3.7740000e-007 -3.7910909e-001 3.7750000e-007 -3.6576920e-001 3.7760000e-007 -3.5701598e-001 3.7770000e-007 -3.4571149e-001 3.7780000e-007 -3.2906518e-001 3.7790000e-007 -3.1588316e-001 3.7800000e-007 -3.0015053e-001 3.7810000e-007 -2.9640567e-001 3.7820000e-007 -2.7954380e-001 3.7830000e-007 -2.6895114e-001 3.7840000e-007 -2.5070542e-001 3.7850000e-007 -2.3727540e-001 3.7860000e-007 -2.2808691e-001 3.7870000e-007 -2.1278683e-001 3.7880000e-007 -1.9483751e-001 3.7890000e-007 -1.7769468e-001 3.7900000e-007 -1.6192021e-001 3.7910000e-007 -1.4552955e-001 3.7920000e-007 -1.2931616e-001 3.7930000e-007 -1.1343306e-001 3.7940000e-007 -9.7619648e-002 3.7950000e-007 -8.3448854e-002 3.7960000e-007 -6.7779087e-002 3.7970000e-007 -4.9833405e-002 3.7980000e-007 -3.3035088e-002 3.7990000e-007 -1.8734404e-002 3.8000000e-007 3.2141588e-003 3.8010000e-007 1.9713726e-002 3.8020000e-007 3.2105654e-002 3.8030000e-007 5.1998911e-002 3.8040000e-007 6.9607199e-002 3.8050000e-007 8.4432702e-002 3.8060000e-007 1.0148138e-001 3.8070000e-007 1.1681587e-001 3.8080000e-007 1.3318763e-001 3.8090000e-007 1.4539481e-001 3.8100000e-007 1.6003785e-001 3.8110000e-007 1.7875288e-001 3.8120000e-007 1.8889269e-001 3.8130000e-007 2.1207876e-001 3.8140000e-007 2.2195838e-001 3.8150000e-007 2.4506392e-001 3.8160000e-007 2.5811699e-001 3.8170000e-007 2.6651099e-001 3.8180000e-007 2.8404008e-001 3.8190000e-007 2.9675946e-001 3.8200000e-007 3.0778514e-001 3.8210000e-007 3.1465299e-001 3.8220000e-007 3.3556168e-001 3.8230000e-007 3.4678200e-001 3.8240000e-007 3.5573762e-001 3.8250000e-007 3.6757020e-001 3.8260000e-007 3.7682624e-001 3.8270000e-007 3.8456544e-001 3.8280000e-007 3.9858605e-001 3.8290000e-007 4.1151853e-001 3.8300000e-007 4.1755867e-001 3.8310000e-007 4.2836463e-001 3.8320000e-007 4.3651031e-001 3.8330000e-007 4.4140446e-001 3.8340000e-007 4.4106381e-001 3.8350000e-007 4.5599035e-001 3.8360000e-007 4.5709660e-001 3.8370000e-007 4.6033905e-001 3.8380000e-007 4.7361865e-001 3.8390000e-007 4.7013880e-001 3.8400000e-007 4.8299563e-001 3.8410000e-007 4.8371166e-001 3.8420000e-007 4.8557735e-001 3.8430000e-007 4.8913402e-001 3.8440000e-007 4.9167590e-001 3.8450000e-007 4.9427020e-001 3.8460000e-007 4.9173186e-001 3.8470000e-007 4.9600344e-001 3.8480000e-007 4.9629030e-001 3.8490000e-007 4.9682416e-001 3.8500000e-007 4.9736630e-001 3.8510000e-007 4.9566138e-001 3.8520000e-007 4.9182730e-001 3.8530000e-007 4.9328363e-001 3.8540000e-007 4.9162347e-001 3.8550000e-007 4.8592101e-001 3.8560000e-007 4.8293014e-001 3.8570000e-007 4.7574535e-001 3.8580000e-007 4.7553968e-001 3.8590000e-007 4.7234009e-001 3.8600000e-007 4.6476592e-001 3.8610000e-007 4.6538375e-001 3.8620000e-007 4.5331939e-001 3.8630000e-007 4.5136847e-001 3.8640000e-007 4.4312463e-001 3.8650000e-007 4.3451416e-001 3.8660000e-007 4.2605690e-001 3.8670000e-007 4.2366461e-001 3.8680000e-007 4.1529548e-001 3.8690000e-007 4.0772574e-001 3.8700000e-007 3.9171386e-001 3.8710000e-007 3.8433296e-001 3.8720000e-007 3.7132263e-001 3.8730000e-007 3.6707818e-001 3.8740000e-007 3.5108382e-001 3.8750000e-007 3.4232624e-001 3.8760000e-007 3.3717228e-001 3.8770000e-007 3.2107446e-001 3.8780000e-007 3.1115263e-001 3.8790000e-007 2.9854719e-001 3.8800000e-007 2.8943798e-001 3.8810000e-007 2.8102822e-001 3.8820000e-007 2.6541851e-001 3.8830000e-007 2.4834327e-001 3.8840000e-007 2.3316484e-001 3.8850000e-007 2.2942164e-001 3.8860000e-007 2.1008378e-001 3.8870000e-007 1.9499135e-001 3.8880000e-007 1.7865411e-001 3.8890000e-007 1.6683661e-001 3.8900000e-007 1.5361897e-001 3.8910000e-007 1.3836120e-001 3.8920000e-007 1.2705236e-001 3.8930000e-007 1.0396633e-001 3.8940000e-007 9.5715769e-002 3.8950000e-007 7.6437916e-002 3.8960000e-007 6.0670055e-002 3.8970000e-007 5.0142136e-002 3.8980000e-007 3.2665725e-002 3.8990000e-007 2.0084803e-002 3.9000000e-007 2.2018900e-003 3.9010000e-007 -1.8416507e-002 3.9020000e-007 -3.3938042e-002 3.9030000e-007 -4.3061687e-002 3.9040000e-007 -6.1311964e-002 3.9050000e-007 -7.2665363e-002 3.9060000e-007 -9.2907118e-002 3.9070000e-007 -1.0662361e-001 3.9080000e-007 -1.2662930e-001 3.9090000e-007 -1.3589694e-001 3.9100000e-007 -1.5328911e-001 3.9110000e-007 -1.7038675e-001 3.9120000e-007 -1.8185911e-001 3.9130000e-007 -1.9643495e-001 3.9140000e-007 -2.1144961e-001 3.9150000e-007 -2.2476945e-001 3.9160000e-007 -2.4029583e-001 3.9170000e-007 -2.4921890e-001 3.9180000e-007 -2.6112677e-001 3.9190000e-007 -2.7314426e-001 3.9200000e-007 -2.8863322e-001 3.9210000e-007 -3.0311795e-001 3.9220000e-007 -3.0922913e-001 3.9230000e-007 -3.2357684e-001 3.9240000e-007 -3.3645867e-001 3.9250000e-007 -3.4595046e-001 3.9260000e-007 -3.5990586e-001 3.9270000e-007 -3.7052256e-001 3.9280000e-007 -3.7766668e-001 3.9290000e-007 -3.8811537e-001 3.9300000e-007 -4.0263622e-001 3.9310000e-007 -4.0434292e-001 3.9320000e-007 -4.1802308e-001 3.9330000e-007 -4.1959610e-001 3.9340000e-007 -4.3256619e-001 3.9350000e-007 -4.4181702e-001 3.9360000e-007 -4.3870527e-001 3.9370000e-007 -4.4818531e-001 3.9380000e-007 -4.5433380e-001 3.9390000e-007 -4.5956988e-001 3.9400000e-007 -4.6259453e-001 3.9410000e-007 -4.7461326e-001 3.9420000e-007 -4.7096500e-001 3.9430000e-007 -4.8227740e-001 3.9440000e-007 -4.7958819e-001 3.9450000e-007 -4.8489682e-001 3.9460000e-007 -4.9425611e-001 3.9470000e-007 -4.9065946e-001 3.9480000e-007 -4.8834270e-001 3.9490000e-007 -4.9003375e-001 3.9500000e-007 -4.9082620e-001 3.9510000e-007 -4.9335768e-001 3.9520000e-007 -4.9433412e-001 3.9530000e-007 -4.9197817e-001 3.9540000e-007 -4.9821131e-001 3.9550000e-007 -4.9667785e-001 3.9560000e-007 -4.9207815e-001 3.9570000e-007 -4.8855513e-001 3.9580000e-007 -4.8714108e-001 3.9590000e-007 -4.8239418e-001 3.9600000e-007 -4.8237430e-001 3.9610000e-007 -4.7722090e-001 3.9620000e-007 -4.7514323e-001 3.9630000e-007 -4.6402362e-001 3.9640000e-007 -4.5728438e-001 3.9650000e-007 -4.5481323e-001 3.9660000e-007 -4.5167987e-001 3.9670000e-007 -4.4064353e-001 3.9680000e-007 -4.2491801e-001 3.9690000e-007 -4.2721904e-001 3.9700000e-007 -4.1246175e-001 3.9710000e-007 -4.0283074e-001 3.9720000e-007 -3.9814592e-001 3.9730000e-007 -3.8674947e-001 3.9740000e-007 -3.7916462e-001 3.9750000e-007 -3.6759402e-001 3.9760000e-007 -3.5195051e-001 3.9770000e-007 -3.4560120e-001 3.9780000e-007 -3.3264468e-001 3.9790000e-007 -3.2318065e-001 3.9800000e-007 -3.1254524e-001 3.9810000e-007 -2.9512855e-001 3.9820000e-007 -2.8331422e-001 3.9830000e-007 -2.6744226e-001 3.9840000e-007 -2.5130728e-001 3.9850000e-007 -2.3831263e-001 3.9860000e-007 -2.2507855e-001 3.9870000e-007 -2.0838182e-001 3.9880000e-007 -1.9738191e-001 3.9890000e-007 -1.7665983e-001 3.9900000e-007 -1.5922527e-001 3.9910000e-007 -1.4425992e-001 3.9920000e-007 -1.3187514e-001 3.9930000e-007 -1.1584253e-001 3.9940000e-007 -1.0294793e-001 3.9950000e-007 -8.3563816e-002 3.9960000e-007 -6.9791562e-002 3.9970000e-007 -5.1778035e-002 3.9980000e-007 -3.3066281e-002 3.9990000e-007 -1.5360495e-002 4.0000000e-007 -4.0853226e-003Sigima-1.1.1/sigima/data/tests/curve_formats/fw1e2.txt000066400000000000000000000260401514013333200226100ustar00rootroot00000000000000X,Y 0.0,0.21728069632275404 0.033444816053511704,0.24108266352336338 0.06688963210702341,0.21652392636609305 0.1003344481605351,0.1348445813806272 0.13377926421404682,0.24527066967724395 0.16722408026755853,0.22232211144090147 0.2006688963210702,0.17315631226917963 0.23411371237458192,0.22906056856866633 0.26755852842809363,0.21823408593937607 0.3010033444816053,0.21471302476397736 0.33444816053511706,0.20142859694620688 0.36789297658862874,0.22734439330033074 0.4013377926421404,0.16318749909050573 0.43478260869565216,0.19186639580393444 0.46822742474916385,0.1759078816718181 0.5016722408026756,0.22995841508300144 0.5351170568561873,0.20200481395285957 0.568561872909699,0.18539887195467378 0.6020066889632106,0.1609297405057347 0.6354515050167224,0.18716952267892092 0.6688963210702341,0.20044080379098103 0.7023411371237458,0.18625877971386448 0.7357859531772575,0.2647481074937069 0.7692307692307692,0.2503879887189474 0.8026755852842808,0.0645014850120135 0.8361204013377926,0.10561789194928925 0.8695652173913043,0.19134014917736114 0.903010033444816,0.17898084908480943 0.9364548494983277,0.21078573279268364 0.9698996655518394,0.21098469194779843 1.0033444816053512,0.3060275696199771 1.0367892976588629,0.14455390411884664 1.0702341137123745,0.18129655369489897 1.1036789297658862,0.30234010530215116 1.137123745819398,0.2325645953143763 1.1705685618729096,0.2334141109566539 1.2040133779264213,0.1745961125137253 1.237458193979933,0.11793261140984346 1.2709030100334449,0.20875450037079854 1.3043478260869565,0.20588236926374973 1.3377926421404682,0.1391205804455624 1.37123745819398,0.16639015113480038 1.4046822742474916,0.1970201128764016 1.4381270903010033,0.1534638359435348 1.471571906354515,0.1958762146314206 1.5050167224080266,0.20566228123204885 1.5384615384615383,0.20277700699846188 1.57190635451505,0.17580494122948814 1.6053511705685617,0.23094222895013827 1.6387959866220736,0.24596325390991902 1.6722408026755853,0.21761359393788096 1.705685618729097,0.16084365407780749 1.7391304347826086,0.23854111949872026 1.7725752508361203,0.17711095850040698 1.806020066889632,0.24638844789411338 1.8394648829431437,0.1491135301346404 1.8729096989966554,0.24872593400530857 1.906354515050167,0.20232857014270206 1.9397993311036787,0.14125542084984882 1.9732441471571907,0.1883935799400917 2.0066889632107023,0.20722669291674495 2.040133779264214,0.2186344436399411 2.0735785953177257,0.15640214230101945 2.1070234113712374,0.15070621390435826 2.140468227424749,0.21666750012569203 2.1739130434782608,0.1840179063982227 2.2073578595317724,0.21985527905846203 2.240802675585284,0.24684204768990317 2.274247491638796,0.12727837456093694 2.3076923076923075,0.22335872389645242 2.341137123745819,0.2728676165859639 2.374581939799331,0.1978338823076708 2.4080267558528425,0.17332824258583085 2.441471571906354,0.25272863126529543 2.474916387959866,0.2291300203642347 2.508361204013378,0.26269207883607454 2.5418060200668897,0.2021816470845884 2.5752508361204014,0.14700569901094165 2.608695652173913,0.2173654026031227 2.6421404682274248,0.20246454472178604 2.6755852842809364,0.265538413182753 2.709030100334448,0.2386019839053449 2.74247491638796,0.149663432596004 2.7759197324414715,0.17387627541649112 2.809364548494983,0.2804008850967682 2.842809364548495,0.2729305494498606 2.8762541806020065,0.20982012437006914 2.9096989966555182,0.2448340836068371 2.94314381270903,0.27038858158761814 2.9765886287625416,0.2749273319821168 3.0100334448160533,0.29889467805550696 3.043478260869565,0.27166464571120924 3.0769230769230766,0.25804283769137987 3.1103678929765883,0.2539751956948086 3.1438127090301,0.32403046400423413 3.1772575250836117,0.1632211676793554 3.2107023411371234,0.2735484396201048 3.2441471571906355,0.28704667826635777 3.277591973244147,0.21924361080495142 3.311036789297659,0.31246517958524983 3.3444816053511706,0.26877239931936525 3.3779264214046822,0.35016789191346287 3.411371237458194,0.30667048957798515 3.4448160535117056,0.3525046404860941 3.4782608695652173,0.38627487445712777 3.511705685618729,0.3509492654961072 3.5451505016722407,0.29466587626451873 3.5785953177257523,0.2695579951881521 3.612040133779264,0.4399308601561558 3.6454849498327757,0.353842478833972 3.6789297658862874,0.3322730319273502 3.712374581939799,0.3813472060477514 3.7458193979933108,0.3721249417530166 3.7792642140468224,0.43198015128831113 3.812709030100334,0.3988507389483612 3.846153846153846,0.40571337093545 3.8795986622073575,0.37724439086882194 3.913043478260869,0.44446001942686947 3.9464882943143813,0.3773413108171846 3.979933110367893,0.47041024512662144 4.013377926421405,0.5214044729653287 4.046822742474916,0.3770577817422344 4.080267558528428,0.3380391548718019 4.113712374581939,0.5002080033574104 4.147157190635451,0.6047077479240259 4.180602006688963,0.4351308060164037 4.214046822742475,0.43040161989542136 4.247491638795986,0.530018944733087 4.280936454849498,0.4660226838231791 4.31438127090301,0.49007934519613205 4.3478260869565215,0.5051096725448871 4.381270903010034,0.5560432849963767 4.414715719063545,0.5158782975245214 4.448160535117057,0.5564906346155074 4.481605351170568,0.5399564373287097 4.51505016722408,0.5124509142076153 4.548494983277592,0.544291154606654 4.581939799331104,0.5180397080927749 4.615384615384615,0.5708253061757163 4.648829431438127,0.5188930744558389 4.682274247491638,0.524660770113884 4.7157190635451505,0.655991333187319 4.749163879598662,0.5839279538281497 4.782608695652174,0.5869308798372566 4.816053511705685,0.617826506759204 4.849498327759197,0.5734067473612794 4.882943143812708,0.5847916386034304 4.916387959866221,0.6188076541479115 4.949832775919732,0.6125613691790831 4.983277591973244,0.5409216680579328 5.016722408026756,0.6405536342380375 5.050167224080267,0.5689188299024109 5.083612040133779,0.5447462698656068 5.117056856187291,0.5511946534773858 5.150501672240803,0.5749223302709568 5.183946488294314,0.6736146984944764 5.217391304347826,0.5308491858648197 5.250836120401337,0.594590959470134 5.2842809364548495,0.4762520245175273 5.317725752508361,0.5792271419213866 5.351170568561873,0.6200647067079211 5.384615384615384,0.5586663907791564 5.418060200668896,0.5340919451570036 5.4515050167224075,0.5718580206967421 5.48494983277592,0.5896920569477281 5.518394648829431,0.581965978824259 5.551839464882943,0.6412201853079891 5.585284280936454,0.5466017892109912 5.618729096989966,0.49982267569414013 5.652173913043478,0.5162165863797441 5.68561872909699,0.5117556921119782 5.719063545150502,0.5134956325000004 5.752508361204013,0.49906910738259175 5.785953177257525,0.501634704780331 5.8193979933110365,0.40163454542924293 5.852842809364549,0.5187943049518717 5.88628762541806,0.4406271021536431 5.919732441471572,0.40269268161701655 5.953177257525083,0.485179641629264 5.986622073578595,0.5110738976851261 6.020066889632107,0.4617671806133953 6.053511705685619,0.4370926126272097 6.08695652173913,0.3743705992208974 6.120401337792642,0.5565517438111451 6.153846153846153,0.44903882278760465 6.187290969899665,0.34018959630935747 6.220735785953177,0.35039114226568974 6.254180602006689,0.3860444707057443 6.2876254180602,0.296397795044911 6.321070234113712,0.37513279965959206 6.354515050167223,0.33645351070771023 6.3879598662207355,0.4135751842961481 6.421404682274247,0.39338165995479657 6.454849498327759,0.20288766156392246 6.488294314381271,0.3338879156617992 6.521739130434782,0.24445931922238223 6.555183946488294,0.3745288784090476 6.588628762541806,0.3213553872360928 6.622073578595318,0.3344659247070254 6.655518394648829,0.24808021350137013 6.688963210702341,0.3872460108281225 6.722408026755852,0.3915147272059831 6.7558528428093645,0.23215812093584415 6.789297658862876,0.29912196196798757 6.822742474916388,0.242098760013773 6.856187290969899,0.27006482713453506 6.889632107023411,0.2036357499729728 6.9230769230769225,0.3561415303688358 6.956521739130435,0.2103813887959978 6.989966555183946,0.24027837749991485 7.023411371237458,0.276581261745279 7.056856187290969,0.21573186997800248 7.090301003344481,0.23292090194858606 7.123745819397993,0.21365030034414545 7.157190635451505,0.23226926083715366 7.190635451505017,0.17768430151239026 7.224080267558528,0.2117350256415361 7.25752508361204,0.22086124798214685 7.290969899665551,0.21223404129628046 7.3244147157190636,0.22960671982506403 7.357859531772575,0.21010084140451163 7.391304347826087,0.2605265112606543 7.424749163879598,0.20493681640776074 7.45819397993311,0.2126099527723582 7.4916387959866215,0.18465885849740393 7.525083612040134,0.19013195254806578 7.558528428093645,0.15189180036533023 7.591973244147157,0.23980821779160758 7.625418060200668,0.1555843236435699 7.65886287625418,0.1743424482997611 7.692307692307692,0.2286015506711318 7.725752508361204,0.22984641117571097 7.759197324414715,0.18886033401573069 7.792642140468227,0.10711670794751071 7.826086956521738,0.22838105160699157 7.8595317725752505,0.219666446427941 7.892976588628763,0.13545580548902914 7.926421404682274,0.24402765268779317 7.959866220735786,0.1699398866600471 7.993311036789297,0.14821217317050273 8.02675585284281,0.20887508908664693 8.060200668896321,0.19476934379660885 8.093645484949832,0.21346294292303347 8.127090301003344,0.12271517093264758 8.160535117056856,0.2933144067921313 8.193979933110368,0.17229748625252772 8.227424749163879,0.12519999399893905 8.26086956521739,0.23290061473780568 8.294314381270903,0.184014958942264 8.327759197324415,0.21781410299819795 8.361204013377925,0.18442448466455066 8.394648829431437,0.19826780733685112 8.42809364548495,0.21340816633213555 8.461538461538462,0.16366505094654268 8.494983277591972,0.234825109651554 8.528428093645484,0.17729470807005432 8.561872909698996,0.15721705988805004 8.595317725752508,0.20447391795388808 8.62876254180602,0.22280354814838058 8.66220735785953,0.1890342160768591 8.695652173913043,0.15730567551869423 8.729096989966555,0.23137054147509312 8.762541806020067,0.11231993034648725 8.795986622073578,0.14875322429632182 8.82943143812709,0.20223708686451003 8.862876254180602,0.13217647558903056 8.896321070234114,0.2016012381399931 8.929765886287624,0.19743364815032569 8.963210702341136,0.24509193169636911 8.996655518394649,0.15439611427676014 9.03010033444816,0.1688232692145881 9.063545150501671,0.2167626671528031 9.096989966555183,0.07721219015333675 9.130434782608695,0.3550808687258485 9.163879598662207,0.16513601772458444 9.197324414715718,0.16356785632403403 9.23076923076923,0.24310814849884335 9.264214046822742,0.19805332470201237 9.297658862876254,0.11106749404365343 9.331103678929766,0.23138006376969447 9.364548494983277,0.2427980264098249 9.397993311036789,0.17752784994977974 9.431438127090301,0.18594169158832696 9.464882943143813,0.22431793844174622 9.498327759197323,0.15457709195554759 9.531772575250836,0.22193327551616243 9.565217391304348,0.20997681872581198 9.59866220735786,0.1662635726517932 9.63210702341137,0.13040365027911616 9.665551839464882,0.1887271933423627 9.698996655518394,0.15623528701819264 9.732441471571907,0.2500759774140805 9.765886287625417,0.20720893178384484 9.799331103678929,0.23910820016518872 9.832775919732441,0.20673447958992383 9.866220735785953,0.21314793219783962 9.899665551839464,0.1608524970993262 9.933110367892976,0.23340444388553094 9.966555183946488,0.2892366700636567 10.0,0.18451710894363765 Sigima-1.1.1/sigima/data/tests/curve_formats/fwhm.txt000066400000000000000000000121271514013333200226260ustar00rootroot000000000000005.281 -0.0527755 5.306 -0.0527755 5.331 -0.0377771 5.356 -0.0227787 5.381 -0.0227787 5.406 -0.00778034 5.431 0.00721805 5.456 0.0372148 5.481 0.0372148 5.506 0.0372148 5.531 0.00721805 5.556 0.00721805 5.581 0.00721805 5.606 0.0372148 5.631 0.0522132 5.656 0.0522132 5.681 -0.00778034 5.706 -0.0377771 5.731 -0.0227787 5.756 0.00721805 5.781 -0.0227787 5.806 -0.0527755 5.831 -0.0827723 5.856 -0.0677739 5.881 -0.0677739 5.906 -0.0377771 5.931 -0.0227787 5.956 0.00721805 5.981 0.00721805 6.006 0.0222164 6.031 0.0372148 6.056 0.0522132 6.081 0.00721805 6.106 -0.00778034 6.131 0.00721805 6.156 0.0372148 6.181 0.00721805 6.206 -0.00778034 6.231 0.00721805 6.256 0.0372148 6.281 0.0222164 6.306 -0.00778034 6.331 -0.0227787 6.356 -0.0227787 6.381 -0.0527755 6.406 -0.0527755 6.431 -0.0227787 6.456 0.0222164 6.481 0.0222164 6.506 0.0222164 6.531 0.00721805 6.556 0.0222164 6.581 0.0222164 6.606 0.0372148 6.631 0.00721805 6.656 0.00721805 6.681 0.00721805 6.706 0.00721805 6.731 -0.0227787 6.756 -0.0377771 6.781 -0.0227787 6.806 0.00721805 6.831 0.00721805 6.856 0.00721805 6.881 -0.00778034 6.906 0.00721805 6.931 -0.00778034 6.956 0.00721805 6.981 0.00721805 7.006 0.0222164 7.031 0.00721805 7.056 -0.00778034 7.081 -0.0227787 7.106 0.00721805 7.131 0.0372148 7.156 0.0372148 7.181 -0.0227787 7.206 -0.0527755 7.231 -0.0527755 7.256 -0.00778034 7.281 0.00721805 7.306 0.00721805 7.331 -0.00778034 7.356 0.00721805 7.381 0.00721805 7.406 0.00721805 7.431 0.00721805 7.456 0.0222164 7.481 0.0222164 7.506 0.0222164 7.531 0.00721805 7.556 0.00721805 7.581 -0.00778034 7.606 0.00721805 7.631 -0.00778034 7.656 -0.00778034 7.681 -0.0227787 7.706 -0.0227787 7.731 -0.0227787 7.756 -0.0227787 7.781 -0.0377771 7.806 -0.0377771 7.831 -0.0227787 7.856 0.0222164 7.881 0.0522132 7.906 0.0972084 7.931 0.127205 7.956 0.1722 7.981 0.187199 8.006 0.232194 8.031 0.277189 8.056 0.337183 8.081 0.382178 8.106 0.442171 8.131 0.517163 8.156 0.592155 8.181 0.622152 8.206 0.652149 8.231 0.682146 8.256 0.742139 8.281 0.757138 8.306 0.772136 8.331 0.772136 8.356 0.802133 8.381 0.832129 8.406 0.877125 8.431 0.877125 8.456 0.877125 8.481 0.847128 8.506 0.832129 8.531 0.832129 8.556 0.847128 8.581 0.847128 8.606 0.877125 8.631 0.892123 8.656 0.892123 8.681 0.847128 8.706 0.847128 8.731 0.877125 8.756 0.937118 8.781 0.92212 8.806 0.892123 8.831 0.877125 8.856 0.907121 8.881 0.92212 8.906 0.92212 8.931 0.892123 8.956 0.877125 8.981 0.862126 9.006 0.877125 9.031 0.877125 9.056 0.877125 9.081 0.862126 9.106 0.877125 9.131 0.877125 9.156 0.877125 9.181 0.877125 9.206 0.907121 9.231 0.937118 9.256 0.952117 9.281 0.907121 9.306 0.892123 9.331 0.907121 9.356 0.937118 9.381 0.92212 9.406 0.92212 9.431 0.907121 9.456 0.907121 9.481 0.877125 9.506 0.862126 9.531 0.877125 9.556 0.892123 9.581 0.862126 9.606 0.862126 9.631 0.877125 9.656 0.907121 9.681 0.892123 9.706 0.892123 9.731 0.892123 9.756 0.92212 9.781 0.92212 9.806 0.907121 9.831 0.892123 9.856 0.907121 9.881 0.907121 9.906 0.907121 9.931 0.862126 9.956 0.832129 9.981 0.817131 10.006 0.847128 10.031 0.862126 10.056 0.877125 10.081 0.862126 10.106 0.862126 10.131 0.847128 10.156 0.862126 10.181 0.862126 10.206 0.877125 10.231 0.892123 10.256 0.92212 10.281 0.907121 10.306 0.892123 10.331 0.877125 10.356 0.892123 10.381 0.877125 10.406 0.877125 10.431 0.862126 10.456 0.862126 10.481 0.847128 10.506 0.847128 10.531 0.847128 10.556 0.862126 10.581 0.832129 10.606 0.802133 10.631 0.772136 10.656 0.772136 10.681 0.727141 10.706 0.667147 10.731 0.592155 10.756 0.562158 10.781 0.532162 10.806 0.502165 10.831 0.427173 10.856 0.352181 10.881 0.292187 10.906 0.262191 10.931 0.232194 10.956 0.202197 10.981 0.157202 11.006 0.157202 11.031 0.1722 11.056 0.202197 11.081 0.1722 11.106 0.127205 11.131 0.0972084 11.156 0.112207 11.181 0.112207 11.206 0.127205 11.231 0.0972084 11.256 0.0672116 11.281 0.0222164 11.306 0.00721805 11.331 0.00721805 11.356 0.0222164 11.381 0.00721805 11.406 0.00721805 11.431 0.00721805 11.456 0.0222164 11.481 0.0372148 11.506 0.0522132 11.531 0.0372148 11.556 0.0522132 11.581 0.0522132 11.606 0.08221 11.631 0.08221 11.656 0.0672116 11.681 0.0222164 11.706 0.0222164 11.731 0.0222164 11.756 0.0222164 11.781 -0.0227787 11.806 -0.0377771 11.831 -0.0227787 11.856 0.00721805 11.881 0.00721805 11.906 0.00721805 11.931 0.0222164 11.956 0.0522132 11.981 0.0372148 12.006 0.0222164 12.031 0.00721805 12.056 0.0222164 12.081 0.0372148 12.106 0.0522132 12.131 0.0222164 12.156 0.00721805 12.181 0.00721805 12.206 0.0372148 12.231 0.0372148 12.256 0.0372148 12.281 0.00721805 12.306 -0.00778034 12.331 -0.0227787 12.356 -0.0227787 12.381 -0.0227787 12.406 0.00721805 12.431 0.0522132 12.456 0.08221 12.481 0.0522132 12.506 0.0372148 12.531 0.0222164 12.556 0.0372148 12.581 0.0372148 12.606 0.0372148 12.631 0.0372148 12.656 0.0372148 12.681 0.0222164 12.706 0.00721805 12.731 -0.00778034 12.756 0.0222164 12.781 0.0372148 12.806 0.0372148 12.831 0.00721805 12.856 -0.00778034 12.881 -0.0227787 12.906 0.00721805 12.931 0.0222164 12.956 0.0522132 12.981 0.0672116 13.006 0.08221 13.031 0.0672116 13.056 0.0522132 13.081 0.0372148 13.106 0.0222164 13.131 -0.00778034 13.156 -0.00778034 13.181 0.00721805 13.206 0.0522132 13.231 0.0372148 Sigima-1.1.1/sigima/data/tests/curve_formats/multiple_curves.csv000066400000000000000000000037041514013333200250640ustar00rootroot00000000000000time;PT380;TT382;2TT385;1TT385;TT383 -1294.982;1254.853394;26.64377594;35.75617218;32.19374466;32.60350037 -1294.884;1254.853394;26.64377594;35.75617218;32.19374466;32.60350037 -1294.883;1254.853394;26.64377594;35.75617218;32.19374466;32.60350037 -1294.876;1254.853394;26.64377594;35.75617218;32.19374466;32.60350037 -1294.834;1254.853394;26.64377594;35.75617218;32.19374466;32.60350037 -1294.805;1254.853394;26.64377594;35.75617218;32.19374466;32.60350037 -1294.784;1254.853394;26.64377594;35.75617218;32.19374466;32.60350037 -1294.756;1254.853394;26.64377594;35.75617218;32.19374466;32.60350037 -1294.755;1254.853394;26.64033699;35.75617218;32.19374466;32.60350037 -1294.684;1254.853394;26.64033699;35.75617218;32.19374466;32.60350037 -1294.634;1254.853394;26.64033699;35.75617218;32.19374466;32.60350037 -1294.633;1254.853394;26.63676262;35.75617218;32.19374466;32.60350037 -1294.626;1254.853394;26.63676262;35.75617218;32.19374466;32.60350037 -1294.584;1254.853394;26.63676262;35.74349594;32.19374466;32.60350037 -1294.555;1254.853394;26.63676262;35.74349594;32.19374466;32.60350037 -1294.506;1254.853394;26.63676262;35.74349594;32.19374466;32.60350037 -1294.505;1254.853394;26.6340313;35.74349594;32.19374466;32.60350037 -1294.484;1254.853394;26.6340313;35.74349594;32.19374466;32.60350037 -1294.446;1254.853394;26.6340313;35.74349594;32.19374466;32.60350037 -1294.444;1254.853394;26.6340313;35.74349594;32.19374466;32.60350037 -1294.436;1254.853394;26.6340313;35.74349594;32.19374466;32.60350037 -1294.432;1254.853394;26.6340313;35.74349594;32.19374466;32.60350037 -1294.376;1254.853394;26.6340313;35.74349594;32.19374466;32.60350037 -1294.356;1254.853394;26.6340313;35.74349594;32.19374466;32.60350037 -1294.355;1254.853394;26.63006401;35.74349594;32.19374466;32.60350037 -1294.331;1254.853394;26.63006401;35.74349594;32.19374466;32.60350037 -1294.315;1254.853394;26.63006401;35.74349594;32.19374466;32.60350037 -1294.311;1254.853394;26.63006401;35.74349594;32.19374466;32.60350037Sigima-1.1.1/sigima/data/tests/curve_formats/noised_saw.mat000066400000000000000000000177701514013333200237730ustar00rootroot00000000000000MATLAB 5.0 MAT-file Platform: nt, Created on: Tue May 7 14:50:36 2024IMpsig @$hz#Q9#9o#s#I e#s߄#JZp#BE[#߄OG#!2#;ؾD#[ #P9"4͕"!2/"ϩ"-l$"[ "}Ļz"&-Ce"ΕQ"v}<"g("ϩ~"o8T!s! !hr+i!ۗ!Ce^!`ك! So!}!R {!wM3 s KZp( l$ +i De^ ay e^d =Z5P 6W҂; So& 5P x R \ϩUŀ&|:WNtt.mf@l_"=X\Qya2In8B d҂;DY#T4~Nt%-C%8k,.Bef#j< W MtKH"R#5:o§ϩ~ۗU,i,|:W ݫˁnw?l_Qya6`"V Kŀ'AQya6gr+i8k @C d\I U4~NOGr @1I&8k w1ǔ*߿f#h7S|S ǔ*Z|:MttLi^]"T4=\I dԖ>53/ )ؾDgЩ~>!{qL,fcpGcT4~Nwo§Fhzya6QJZp(8S|KqپDg)=X\za6Q[2/F2(< k @1z& x]I e(<aO_ۗ@1InكEѽdJ_cJx4CH2jK[ wM3L*? ̼0ɨ l_"V  w PGr` ^] G 4/F2j ѽ vt. s ! X\ u} gr+ ݫQyVŀ'%8kU:k @1)U`q*8Tu70ɨ-v}@Rŀ'AEhPHn8TR {Z5P $hX*߿o§{x`wM3?l_"OG 2/FhTuJZ`?lHFm#` =] =pJr`p&|:Kq激)z7㿀'APῐݫ@p+i@9o@0VH@V @ef@Lns%-@ˁB @)=X\@hm@U@(AR@m@@DYH@@@`q*?@/@,.BE@|@~ؾDg@. )@53@dԖ>@<\I @"T4@^]@Ji@Mtt@|:@Z@ ǔ*@S@h7S|@f#@Ɣ*߿@v1@$8k @ @1I@OGr@4~N@U@\I @@ d@8k @@gr+i@Pya6@ŀ'A@K@`"V @Qya6@?l_@lw@ݫˁ@ @|:W@,i,@ܗU@ϩ~@8o§@#5@R@H"@K@Mt@T @< @j@df#@,.B@%8k@t%-C@$T4~N@Ђ;DY@B d@0In8@Qya@=X\@@l_"@f@m@Ltt.@&|:W@Uŀ@\ϩ@ @R@4P x @So& @6W҂; @!@Ov1!@XHF!@}]Aÿ7Nʿ&-be,U3ſPetɿdn1?ͽ kB?$ Hk?r6?V?L ?s?F42?4N ? ?>Hm?ۄE?]e~[￭b͝EW6鿳NwOnGdX濄tuRڿqEۿl o޿30Rӿ]LǿN8;.nqkN Fr`:??U?/?3N?Q ?XSt]z?' ,?KB?Uwd?rws?A5rf1Y'<:`E P?-)XN v5߿ c0 0aݿ,nƿ>Z7Oh{uQſ yȚP*%B?$(.?m1nT?<8p~?k;o`?-,T%u?]6(?0o"? ?0"+Y?VW?i=_M?mk9*z) #4"вyw~STwoIoT>OcAtR{`$ kſ+d2ѿ&/пy5xy:!X?:ze8"?zK"?Pq?^K>??$a?RY6?s?5 ?V31+|?]?IGAZ8e jXh8߇Z꿒ePӋVqܿ+Hfݿ*EӿD rƬѿп舫  8&D?D7?Zy?hKR?ªP(?ARxCH?7? τޘ?@l?lQCo? ?cr~??UR/MJzfj!cF=8r{eڿN㿿MٿF[ῧtjiqLпd K+Dⳳ=fF۶?H%?(7}?!3J?6B?"ȣ?J?5H?&͕N8?KVC7?zS?f?ɎDrp@Q`4+y޹6lӲ]d &FQwN4d޿d2 ! ;F9BĿk{1ҿ)aſP:iZUu]_صCe?S/?3u?<͖W?繖*?ԚZ{? ? ?rP?;[\?dlh?C r ?ZG {Ļ.L.e>@8lrM4eSE9=t:y64,̿9ܞۿѿ|PNBIQÿZ4^r8= 6?c ?LxZ?g>IU?ʲ/TB?ETnB?MA? -d?$M?l?Ä6?~V=v?cC1q*)2fd)~mH%[[H࿑nVUܿM~yWܿ!J?ϧɿ[=tɾs̿{hR 5?Vzz?pre?$l?%@?#?0Bc`? !?}E?|xZ?E?¢U?W?FW쿔-#Mi`eKHW=e㿂Q*$~ٿeѿb{п~7NϿ搐ˀ,FƿnZly&H?*L;? ?0Em?KiP]T?iw/?E?$$]k7?ƀ ?B_l?ƃ)?|Zv8|D'[}SRi y ޿zbCCۿ%V" ѿڅW|ԿPb Gl$«yxz'I9g?#@X?q|)P?wM?df?ϧ??Σ??K?^p??dPW?/v?f-2NZfpLF鿝(Q6 vԿ!<ٿHcѿ j(Pgǿ6kJӲ?8TCC]$?Bo(?.Eɂ?^OEc?N g?0 =?x&-SM[盝Mۿ*1ݿ%տ+ܿP2zĿzlÿj"xG?dEʌ#et"?|(?4=z5?Nw$?y@?4@ ?X@9?xj??*?ҏ??4A}8Ý :}_+dr_Q-快"& !&t⿏QSؿ׾I߿WoϿ_ѿ'OT)4Hm?LrIӷ? T?fPמ(?裳r9?Όx? n?Q??aد@J?n%?2^?/?. Я;X:-0ޯ,C B迼UT3Q$.$fӿAC @ؿK)ɿNӿ"3NkĿ(nwZPi7f?ȥ$aO?ߜp?E0*?vF(?tX?~k?{Z ?zJޚ?xCe?nq |?u&?еQKp?Ī+jBu&r> 5V꿆sJ߿LK<Ƥ޿׿տ ]njƿ>T|$Կg/׿)͆?(Rrףղ?K'jp??į? Uhѵ?t?^{-?G?Cƒ?(^? Q?vKS,M?xs`BjfA5g4忮M5⿅yZ ؿfm[ \t?o$ɿD@xѿjͿzGɿrw? q?i"Fzݳ?Ä?|R?dbZF?0"? o}? 3Π?}?V]?}i4?d7H?%S쿔,cEpTF"=YmtῊiYۿk=qǿ8ҿꍙک?׻q!?^qm?KPC?D?ba ?=X?̿?t}?wu'?;|E@X?/!?4=m7ao?ADgZ?QN뿯,yō%9JQn:pVῸzoS%ٿlDygп-Ͽ!S^<?^Fl?^~?]Hغ?aȽ?j 2?O"?JGv֘?iz?pk@ >@>@fffff&>@333333>@@>@L>@Y>@ffffff>@33333s>@>@̌>@>@fffff>@33333>@>@>@>@fffff>@33333>@?@ ?@?@fffff&?@333333?@@?@L?@Y?@ffffff?@33333s?@?@̌?@?@fffff?@33333?@?@?@?@fffff?@33333?@@@fffff@@ @@33333@@@@ @@fffff&@@,@@333333@@9@@@@@fffffF@@L@@33333S@@Y@@`@@ffffff@@l@@33333s@@y@@@@fffff@@̌@@33333@@@@@@fffff@@̬@@33333@@@@@@fffff@@@@33333@@@@@@fffff@@@@33333@@@@A@fffffA@ A@33333A@A@ A@fffff&A@,A@333333A@9A@@A@fffffFA@LA@33333SA@YA@`A@ffffffA@lA@33333sA@yA@A@fffffA@̌A@33333A@A@A@fffffA@̬A@33333A@A@A@fffffA@A@33333A@A@A@fffffA@A@33333A@A@B@fffffB@ B@33333B@B@ B@fffff&B@,B@333333B@9B@@B@fffffFB@LB@33333SB@YB@`B@ffffffB@lB@33333sB@yB@B@fffffB@̌B@33333B@B@B@fffffB@̬B@33333B@B@B@fffffB@B@33333B@B@B@fffffB@B@33333B@B@C@fffffC@ C@33333C@C@ C@fffff&C@,C@333333C@9C@@C@fffffFC@LC@33333SC@YC@`C@ffffffC@lC@33333sC@yC@C@fffffC@̌C@33333C@C@C@fffffC@̬C@33333C@C@C@fffffC@C@33333C@C@C@fffffC@C@33333C@C@D@fffffD@ D@33333D@D@ D@fffff&D@,D@333333D@9D@@D@fffffFD@LD@33333SD@YD@`D@ffffffD@lD@33333sD@yD@D@fffffD@̌D@33333D@D@D@fffffD@̬D@33333D@D@D@fffffD@D@33333D@D@D@fffffD@D@33333D@D@E@fffffE@ E@33333E@E@ E@fffff&E@,E@333333E@9E@@E@fffffFE@LE@33333SE@YE@`E@ffffffE@lE@33333sE@yE@E@fffffE@̌E@33333E@E@E@fffffE@̬E@33333E@E@E@fffffE@E@33333E@E@E@fffffE@E@33333E@E@F@fffffF@ F@33333F@F@ F@fffff&F@,F@333333F@9F@@F@fffffFF@LF@33333SF@YF@`F@ffffffF@lF@33333sF@yF@F@fffffF@̌F@33333F@F@F@fffffF@̬F@33333F@F@F@fffffF@F@33333F@F@F@fffffF@F@33333F@F@G@fffffG@ G@33333G@G@ G@fffff&G@,G@333333G@9G@@G@fffffFG@LG@33333SG@YG@`G@ffffffG@lG@33333sG@yG@G@fffffG@̌G@33333G@G@G@fffffG@̬G@33333G@G@G@fffffG@G@33333G@G@G@fffffG@G@33333G@G@H@fffffH@ H@33333H@H@ H@fffff&H@,H@333333H@9H@@H@fffffFH@LH@33333SH@YH@`H@ffffffH@lH@33333sH@yH@H@fffffH@̌H@33333H@H@H@fffffH@̬H@33333H@H@H@fffffH@H@33333H@H@H@fffffH@H@33333H@H@I@fffffI@ I@33333I@I@ I@fffff&I@,I@333333I@9I@@I@fffffFI@LI@33333SI@YI@`I@ffffffI@lI@33333sI@yI@I@fffffI@̌I@33333I@I@I@fffffI@̬I@33333I@I@I@fffffI@I@33333I@I@I@fffffI@I@33333I@I@J@fffffJ@ J@33333J@J@ J@fffff&J@,J@333333J@9J@@J@fffffFJ@LJ@33333SJ@YJ@`J@ffffffJ@lJ@33333sJ@yJ@J@fffffJ@̌J@33333J@J@J@fffffJ@̬J@33333J@J@J@fffffJ@J@33333J@J@J@fffffJ@J@33333J@J@K@fffffK@ K@33333K@K@ K@fffff&K@,K@333333K@9K@@K@fffffFK@LK@33333SK@YK@`K@ffffffK@lK@33333sK@fffffb@-^`@9vSa@ףp= _@FP`@9v#`@/\b@~jt_@QV`@|?5a@&1`@jt`@Ri`@C`@Hz`@na@K7A_@%a@d;Ob@RI_@ r`@x&=a@ Z`@;O_@d;OC`@Zd;O`@$g`@l^@|?5`@ʡE?`@p= _@p= S_@Gz_@_@V-]@m_@jt$_@/$`@_@t_@/T_@7A`_@X9v_@uV]@jt_@xb`@(\`@|?5`@v#`@̜_@jt`@Q'`@n^@7A`_@S㥛`@1Z_@jt_@I +_@zG`@Cla@T㥛`@X9ra@C`@V-ya@Ma@-6c@zGb@}?5^b@33333;c@ rhc@Qc@MbXEd@NbX9d@'1c@$'b@^I b@7A`db@Ma@{Ga@Q_@SC`@Zd;[`@Gz]@SS`@e`@= ףp]@_@(\_@Q`@l_@(\^@MbX_@\(`@y&1_@'1*_@m`@= ףp9`@"_@ףp= _@ ףp=v`@S_@ rh_@jt`@-]@Mb_@Zd`@A`@I +O^@t6^@uV^@sh|^@m2_@`@B`"_@^I []@Zd;`@33333`@V-_@5^I J^@=_@{G]@!_@$]@|?5^_@Mb8]@I +^@+^@~j_@fffff.a@ +q`@x^@x`@X9`@V-M`@d;O3a@"`@V-)`@oY^@ +`@F԰_@'1B`@Zdk_@uV.^@x`@n]@x9`@Zd;^@Zd;߇]@ʡy`@Dlq_@x]@q= ףp_@'1]@On^@zG\@(\}]@ `@MbX`@ F`@w/ea@K7 `@sh|]@nj_@M`@K7\@~j(`@S㥛<`@y&1(a@$b@Kb@|?5e@X9>i@Sm@q@uVlv@x@xy@ҩz@Zd;|@/$}@^I e{@Zd;z@$x@Ebv@V-u@+p@B`"j@L7A`e@%CSd@GzRa@vb@Zd;?^@'`@m`@-^@Mb^@$`@V-Q`@V-_@&1`@Cl `@#~j^@= ףpE_@^I ]@$W`@ˡE1`@= ףpu^@va@-]@1Z8`@~jL^@`"Qa@Dl`@Va@}?5^e@S[j@\(n@I +s@\(y@V-@Cl@y&1@V-@tO@VV@X9{@zGt@T㥛o@/$!h@ rh}e@'b@`"۵b@K_`@x^c@Kb@7A`xb@vwa@V-b@uV^c@;O6c@ ףp= c@Sd@(\Md@Eb@ʡE:c@sh|kc@?5^Ita@-b@;Ob@ˡEc@ rpf@-g@Hz;l@w/+p@(\r@u@OnB{@bX9@ƨ@/߈@\(Ќ@Qю@;O+@}?5^@~jΊ@ʡ@/$F@Mb,|@ouv@"~Ns@+p@K7?p@\(n@(\fm@E$m@5^I n@)\tk@x&1m@~jtKn@}?5^l@ r$k@j@ʡEJm@"m@Mbm@!rhp@V-r@fffffu@q= ףy@NbX9P|@I +}@jt}@h|?E{@-w@(\r@C2p@Zd;j@Zd;Oh@~jtg@V-e@V-f@Zde@NbX9f@ld@V-Zg@x&1d@h|?f@ d@$d@I +ke@e@ ^d@sh|f@V-ng@|?5^h@ףp= i@p= ?l@{Gn@|?5^q@Au@R{@Gz3@q= ףp@x&1ʆ@sh|ć@V-@S@ˡE@A`кy@Mbs@xn@vfh@xe@&1xc@(\b@Zd;Oya@Mna@d;Ob@Kb@(\}c@Gzld@^I d@ ~c@ʡEZc@p= ׷b@ұb@`@+η`@ʡE`@)\P_@vf`@/$`@A`2`@xi`@d;O_^@QN^@zGQ`@x&1^@x]@w/^@X9V\@v ]@C_@ rhI_@Q!a@Smc@}?5^Me@nf@ʡEh@&1lj@Vk@}?5^m@DlGq@ʡE1r@lt@~jt@nru@xt@Cq@Kap@~jtl@ˡEm@ʡEk@rhm@Zd;߱q@(\q@7A`q@1Zo@MbXk@ve@ʡEb@~j`@J +b`@U_@X9Ȇ^@S^@NbX9_@ ףp=\@n ^@On _@+[@-\@Gz.^@҅^@+]@S㥛$`@$^@S㥛_@-^@S\@Zd^@T㥛Ĉ]@uV`@J +F`@Gz_@`@x&`@y&1T`@w/`@Q`@v`@K^@Gz0`@(\E^@sh|^@NbX9^@?5^I]@V-\@C]@/$[@|?5^F`@c^@K7A`@/$`@ˡE5a@q= ףDc@ˡEe@-j@rhk@x&1(m@'1m@Rl@vl@ʡEn@S1s@Gzv@h|?~@t<@K7@jt[@Zd;O@~@K7y@Sr@Qk@K7d@X9Bb@a@`"qb@9v`@zG`@7A`Xa@J +.c@+f@Gzl@+οt@ +W~@L7A`x@ʡE^@bX9҈@J +@jtՆ@Pn@|?5@}?5^v@Vr@Dlq@+Λm@$sm@S㥿l@n"k@i@e@Onc@uVa@Cda@n>`@ "^@E^@n8_@QX^@9v_@rh]@Mb]@!rhmZ@NbX9DZ@Q[@MZ@SZ@HzY@T㥛Z@333333[@CY@HzZ@x&Q[@V%\@-O\@T㥛H^@~jt\@Zd;]@`"1[@Zd;ߧ^@+_@&1e@+:c@A`&f@p@7y@/$ۂ@Q@K7$@Zd@-9@|?5^@x&#@bX9y@)\o@MbXe@㥛 a@B`"`@!rha@#~je@㥛 k@T㥛q@Gzu@K7ou@&1w@Mbu@ʡEr@Onp@MbLj@%C?c@x&1^@[@6;NсX@x[@bX9PZ@F\@y&1a@7A``@Zd;?c@Vc@V-mc@Ed@x&d@tZa@rh4`@oZ@VY@(~kW@0*W@ +1Y@%JW@lY@T`X@&SW@$+Y@ۊelW@L F%X@>yX5W@;pΈV@{W@33333Z@h|?U]@x5a@X9ve@Si@'12p@7A`r@NbX9s@Et@}?5^v@sh|9w@I +x@?5^Irx@Ony@nx@w/1v@ms@(\q@(\)l@#~jh@y&1c@V-_@sh|]@\Z@镾W@ʡ}Y@(\Y@X2ıW@sh|?[@mb[@lY@:M U@Oe{T@ U@oS@CR@pQ@vq 1T@-V@,ԚU@ݓV@cZW@Zd;?Y@x&1Z@X9nY@&SbX@xz,CV@OjM?S@_vOU@'1R@nT@ɭU@ڊeR@6٬(X@H}8W@ףp= X@Mbh[@~jtY@SU@~:tW@OeT@!uU@z,CV@I&VV@Ș3X@B`"Y@S+[@x&1]@X9vRb@Gzh@bX9|f@d;O_c@Mb_@W[vX@_LU@ +S@,Ԛ'R@d`R@37hV@ +\@/$`@X9v~b@MbXe@ףp= +d@5^I b@tZ`@;M cX@Q&Y@^)R@"uqER@z6T@y)"U@48S@k+T@ZӼR@a+eT@=,ԚU@_vOR@>W[+S@K7A0N@%CQ@`TR'R@ݓS@z,CV@t$V@d;OZ@V-7_@+`@ `@mz_@Mb8]@SY@AfU@ڊe{Q@9m4XQ@`TR'P@(~kAQ@&䃞FP@hsQ@d`T:R@c=y8O@;pΈO@HPN@eaP@H=P@ZڊeP@W2P@B Q@+ݓW@&1Y@FZ@ [@xI\@V-Y@GznY@DDT@?KU@hoT@sS@$(~gS@7ˆW@)ǺdX@S[@$[@Zd;O^@S]@Q\@q= ף\@ClY@p= +Z@ U@WT@ h"R@ƷT@ǘ\T@$'U@@X@h|?Z@ףp= 7\@Hz^@;OZ@{GrZ@Gz$X@&†V@9EGrW@0*9U@ gS@a2U0*ES@ QT@ S@?*T@d`W@/LY@C_@ʡE`@^I Ob@xd@ƣf@ >d@"jd@xb@X9J`@x&1\@W/'X@U0*LU@=yX5S@@P@DRQ@DAO@`"iO@|?5^R@'†WZP@QkwS@d]KKX@T㥛<`@"~a@"~e@d;OWg@"g@Rg@X9Ȳf@Q!c@R=a@R\@QkwW@tS@|?5R@ZB> U@ V@c]FU@R'X@8mX@FԼU@AfU@ı.n}U@K=T@~8gDQ@]m;Q@x $(~@R@L7A`yS@&SFT@#J{/W@ףp= [@X9ȶ_@PnCa@|?5b@5^I Nc@^I b@/$a@ r^@S Y@oŏU@S@nS@!lVS@=U}S@@3S@-S@D6R@|гR@z):?R@U0*P@/n9Q@>yX5]Q@#M@{O@vOjN@Y8UL@oŏ Q@X R@MJPP@HO@ioQ@鷯P@Tt$DP@H}N@m{ZO@1*Q@MStP@ F%uO@.!O@YQ@1*P@W/'kR@rT@gsS@鷯S@ET@EGrIR@nR@eXP@[Ӽ}N@!rhK@vOjM@ q/P@ŏ1?O@bX9Q@/$T@QIT@?߾rU@( R@2w-!T@CloQ@faL@䃞ͪL@jtTO@(~kN@ޓZ O@-S@T@( U@5^I U@_QV@F_LT@}?5^S@}гYR@Ac]/P@M@Q|O@?ƔM@鷯N@Sigima-1.1.1/sigima/data/tests/curve_formats/paracetamol.txt000066400000000000000000000343541514013333200241630ustar00rootroot00000000000000##NAMES=Paracetamol ##RRUFFID=D120007 ##IDEAL CHEMISTRY=C_8_H_9_NO_2_ ##LOCALITY=Synthetic from Sigma ##OWNER=RRUFF ##SOURCE=David Blake ##DESCRIPTION=Fine colorless powder. Paracetamol, otherwise known as acetaminophen, is an analgesic and antipyretic. ##STATUS=The identification of this mineral is not yet confirmed. ##URL=rruff.info/D120007 2 theta (°), Intensity 5, 144.95 5.05, 130.958 5.1, 138.617 5.15, 127.86 5.2, 130.526 5.25, 129.117 5.3, 146.902 5.35, 126.054 5.4, 130.71 5.45, 136.944 5.5, 132.646 5.55, 135.503 5.6, 131.31 5.65, 134.392 5.7, 134.115 5.75, 142.336 5.8, 124.004 5.85, 137.182 5.9, 144.611 5.95, 125.155 6, 133.639 6.05, 137.911 6.1, 130.834 6.15, 127.603 6.2, 130.111 6.25, 128.666 6.3, 131.237 6.35, 123.651 6.4, 133.444 6.45, 129.991 6.5, 124.31 6.55, 125.31 6.6, 127.22 6.65, 126.525 6.7, 118.994 6.75, 127.921 6.8, 124.564 6.85, 133.317 6.9, 127.625 6.95, 127.094 7, 125.326 7.05, 126.764 7.1, 126.101 7.15, 118.474 7.2, 127.064 7.25, 131.091 7.3, 135.68 7.35, 128.569 7.4, 129.097 7.45, 126.45 7.5, 128.518 7.55, 129.235 7.6, 123.793 7.65, 126.139 7.7, 132.394 7.75, 127.318 7.8, 126.314 7.85, 126.112 7.9, 132.29 7.95, 136.732 8, 135.149 8.05, 139.587 8.1, 134.642 8.15, 139.803 8.2, 141.572 8.25, 153.708 8.3, 148.54 8.35, 151.054 8.4, 153.85 8.45, 157.294 8.5, 158.885 8.55, 162.167 8.6, 165.507 8.65, 156.191 8.7, 145.237 8.75, 151.594 8.8, 147.153 8.85, 141.447 8.9, 143.715 8.95, 127.63 9, 130.104 9.05, 130.851 9.1, 118.595 9.15, 130.604 9.2, 131.175 9.25, 118.46 9.3, 126.75 9.35, 126.365 9.4, 132.485 9.45, 126.401 9.5, 122.79 9.55, 126.146 9.6, 133.005 9.65, 126.313 9.7, 124.658 9.75, 128.092 9.8, 129.795 9.85, 124.484 9.9, 126.61 9.95, 131.695 10, 127.967 10.05, 126.272 10.1, 134.518 10.15, 119.874 10.2, 124.126 10.25, 132.356 10.3, 130.05 10.35, 121.237 10.4, 120.844 10.45, 123.974 10.5, 122.742 10.55, 124.796 10.6, 135.243 10.65, 126.549 10.7, 117.422 10.75, 135.101 10.8, 134.725 10.85, 124.339 10.9, 121.157 10.95, 124.966 11, 119.67 11.05, 124.525 11.1, 118.806 11.15, 124.037 11.2, 116.881 11.25, 122.862 11.3, 120.684 11.35, 126.824 11.4, 137.45 11.45, 131.534 11.5, 123.983 11.55, 132.546 11.6, 134.337 11.65, 130.428 11.7, 137.611 11.75, 133.468 11.8, 129.303 11.85, 121.403 11.9, 134.409 11.95, 126.763 12, 130.066 12.05, 125.678 12.1, 120.724 12.15, 133.341 12.2, 118.668 12.25, 129.796 12.3, 120.248 12.35, 118.123 12.4, 131.801 12.45, 125.781 12.5, 118.983 12.55, 125.76 12.6, 118.283 12.65, 122.163 12.7, 114.645 12.75, 117.965 12.8, 132.209 12.85, 133.292 12.9, 130.209 12.95, 139.162 13, 128.423 13.05, 118.367 13.1, 125.668 13.15, 133.322 13.2, 114.769 13.25, 129.273 13.3, 129.894 13.35, 137.251 13.4, 150.487 13.45, 151.853 13.5, 174.944 13.55, 201.962 13.6, 237.979 13.65, 284.611 13.7, 358.771 13.75, 385.925 13.8, 415.682 13.85, 426.614 13.9, 463.492 13.95, 475.314 14, 438.313 14.05, 430.992 14.1, 399.599 14.15, 358.187 14.2, 337.351 14.25, 269.738 14.3, 215.848 14.35, 174.793 14.4, 162.602 14.45, 138.565 14.5, 151.972 14.55, 120.998 14.6, 129.249 14.65, 128.467 14.7, 120.479 14.75, 123.251 14.8, 129.125 14.85, 130.553 14.9, 126.714 14.95, 132.646 15, 128.372 15.05, 123.694 15.1, 125.085 15.15, 118.172 15.2, 130.737 15.25, 129.561 15.3, 121.835 15.35, 142.207 15.4, 119.999 15.45, 129.761 15.5, 121.199 15.55, 138.558 15.6, 133.687 15.65, 143.158 15.7, 168.679 15.75, 210.864 15.8, 240.63 15.85, 316.948 15.9, 401.51 15.95, 510.351 16, 575.553 16.05, 599.754 16.1, 629.712 16.15, 585.877 16.2, 522.757 16.25, 433.674 16.3, 333.33 16.35, 248.149 16.4, 193.047 16.45, 171.919 16.5, 145.249 16.55, 149.683 16.6, 130.978 16.65, 154.966 16.7, 151.103 16.75, 147.778 16.8, 139.722 16.85, 149.863 16.9, 154.948 16.95, 153.706 17, 152.32 17.05, 164.354 17.1, 162.43 17.15, 144.656 17.2, 153.821 17.25, 155.359 17.3, 139.634 17.35, 150.208 17.4, 149.206 17.45, 158.561 17.5, 179.514 17.55, 189.998 17.6, 225.865 17.65, 258.699 17.7, 301.535 17.75, 346.1 17.8, 436.152 17.85, 563.963 17.9, 693.097 17.95, 795.983 18, 922.02 18.05, 986.19 18.1, 997.449 18.15, 913.216 18.2, 857.842 18.25, 704.079 18.3, 552.753 18.35, 450.754 18.4, 359.362 18.45, 308.906 18.5, 271.303 18.55, 259.971 18.6, 247.38 18.65, 235.205 18.7, 233.156 18.75, 240.439 18.8, 219.655 18.85, 238.381 18.9, 242.358 18.95, 224.804 19, 217.139 19.05, 214.682 19.1, 234.321 19.15, 232.843 19.2, 239.377 19.25, 271.223 19.3, 296.601 19.35, 349.65 19.4, 414.915 19.45, 453.014 19.5, 475.948 19.55, 465.006 19.6, 436.328 19.65, 377.371 19.7, 302.985 19.75, 259.159 19.8, 214.726 19.85, 199.541 19.9, 191.483 19.95, 174.363 20, 183.943 20.05, 172.731 20.1, 180.382 20.15, 167.302 20.2, 186.818 20.25, 166.506 20.3, 176.664 20.35, 166.334 20.4, 161.125 20.45, 171.349 20.5, 173.675 20.55, 162.959 20.6, 180.984 20.65, 187.443 20.7, 199.199 20.75, 207.095 20.8, 225.995 20.85, 246.59 20.9, 285.148 20.95, 340.1 21, 446.62 21.05, 582.385 21.1, 654.08 21.15, 729.274 21.2, 760.561 21.25, 725.147 21.3, 657.166 21.35, 562.369 21.4, 411.676 21.45, 317.024 21.5, 244.341 21.55, 195.207 21.6, 173.296 21.65, 155.771 21.7, 144.105 21.75, 139.791 21.8, 139.447 21.85, 148.986 21.9, 151.228 21.95, 155.93 22, 163.39 22.05, 160.719 22.1, 155.959 22.15, 154.821 22.2, 149.745 22.25, 149.557 22.3, 134.243 22.35, 133.744 22.4, 132.446 22.45, 125.265 22.5, 131.207 22.55, 133.317 22.6, 129.588 22.65, 131.296 22.7, 121.493 22.75, 121.23 22.8, 130.54 22.85, 123.753 22.9, 118.983 22.95, 122.956 23, 113.356 23.05, 116.166 23.1, 127.571 23.15, 125.147 23.2, 137.035 23.25, 155.434 23.3, 170.429 23.35, 180.516 23.4, 196.616 23.45, 211.396 23.5, 216.658 23.55, 237.929 23.6, 276.499 23.65, 291.107 23.7, 328.354 23.75, 333.171 23.8, 343.157 23.85, 330.592 23.9, 287.284 23.95, 262.081 24, 224.983 24.05, 232.686 24.1, 221.321 24.15, 239.779 24.2, 283.117 24.25, 272.335 24.3, 273.056 24.35, 252.636 24.4, 220.542 24.45, 172.207 24.5, 150.821 24.55, 133.023 24.6, 131.079 24.65, 125.341 24.7, 122.106 24.75, 122.052 24.8, 127.441 24.85, 115.91 24.9, 120.508 24.95, 124.163 25, 108.357 25.05, 114.624 25.1, 120.72 25.15, 122.091 25.2, 119.482 25.25, 129.144 25.3, 123.056 25.35, 126.572 25.4, 123.624 25.45, 115.467 25.5, 120.053 25.55, 118.137 25.6, 128.948 25.65, 130.204 25.7, 126.32 25.75, 128.999 25.8, 132.911 25.85, 130.626 25.9, 133.537 25.95, 133.16 26, 135.097 26.05, 123.364 26.1, 129.515 26.15, 121.09 26.2, 120.242 26.25, 123.316 26.3, 116.317 26.35, 114.714 26.4, 118.821 26.45, 111.891 26.5, 130.199 26.55, 121.559 26.6, 128.008 26.65, 134.657 26.7, 137.686 26.75, 154.145 26.8, 172.061 26.85, 208.748 26.9, 216.904 26.95, 233.256 27, 238.691 27.05, 231.06 27.1, 228.972 27.15, 246.491 27.2, 307.083 27.25, 367.255 27.3, 494.578 27.35, 583.502 27.4, 662.527 27.45, 683.387 27.5, 628.664 27.55, 527.825 27.6, 412.596 27.65, 289.458 27.7, 222.51 27.75, 165.663 27.8, 146.087 27.85, 143.243 27.9, 147.558 27.95, 133.242 28, 135.915 28.05, 138.778 28.1, 153.454 28.15, 182.119 28.2, 231.315 28.25, 331.988 28.3, 485.443 28.35, 655.047 28.4, 747.839 28.45, 794.338 28.5, 768.941 28.55, 730.637 28.6, 606.509 28.65, 497.263 28.7, 365.608 28.75, 301.191 28.8, 284.499 28.85, 236.869 28.9, 235.612 28.95, 229.989 29, 217.086 29.05, 200.749 29.1, 172.124 29.15, 157.951 29.2, 143.448 29.25, 139.142 29.3, 129.961 29.35, 120.542 29.4, 123.203 29.45, 124.883 29.5, 121.38 29.55, 124.496 29.6, 116.452 29.65, 117.536 29.7, 105.712 29.75, 105.066 29.8, 110.455 29.85, 107.286 29.9, 107.302 29.95, 100.37 30, 104.262 30.05, 108.8 30.1, 102.571 30.15, 107.745 30.2, 109.268 30.25, 112.579 30.3, 113.249 30.35, 121.137 30.4, 115.554 30.45, 118.863 30.5, 108.779 30.55, 122.623 30.6, 127.857 30.65, 175.396 30.7, 153.839 30.75, 177.213 30.8, 264.975 30.85, 403.475 30.9, 603.393 30.95, 739.19 31, 868.527 31.05, 895.174 31.1, 871.207 31.15, 767.671 31.2, 580.394 31.25, 411.294 31.3, 254.655 31.35, 174.042 31.4, 141.004 31.45, 132.848 31.5, 143.299 31.55, 173.763 31.6, 222.379 31.65, 273.548 31.7, 336.13 31.75, 342.951 31.8, 368.917 31.85, 344.129 31.9, 301.892 31.95, 257.527 32, 210.377 32.05, 153.977 32.1, 120.768 32.15, 111.966 32.2, 98.0284 32.25, 110.733 32.3, 105.261 32.35, 115.513 32.4, 136.501 32.45, 133.028 32.5, 153.976 32.55, 158.283 32.6, 155.428 32.65, 166.281 32.7, 160.161 32.75, 138.813 32.8, 129.654 32.85, 107.903 32.9, 102.454 32.95, 94.5222 33, 92.0796 33.05, 100.767 33.1, 93.1643 33.15, 100.026 33.2, 97.5103 33.25, 92.3957 33.3, 100.681 33.35, 93.7026 33.4, 96.3929 33.45, 94.2689 33.5, 91.6066 33.55, 94.2608 33.6, 107.175 33.65, 117.332 33.7, 137.671 33.75, 174.952 33.8, 207.309 33.85, 259.132 33.9, 300.681 33.95, 314.389 34, 329.562 34.05, 361.983 34.1, 371.593 34.15, 395.073 34.2, 391.143 34.25, 415.402 34.3, 393.297 34.35, 355.074 34.4, 304.059 34.45, 272.36 34.5, 225.305 34.55, 192.763 34.6, 152.001 34.65, 127.494 34.7, 118.867 34.75, 105.45 34.8, 94.9779 34.85, 101.963 34.9, 103.24 34.95, 95.7296 35, 108.992 35.05, 109.546 35.1, 102.401 35.15, 84.1487 35.2, 81.9302 35.25, 86.6041 35.3, 79.7155 35.35, 75.6335 35.4, 69.75 35.45, 80.7793 35.5, 90.6558 35.55, 86.4237 35.6, 91.7114 35.65, 95.0993 35.7, 100.998 35.75, 106.753 35.8, 101.731 35.85, 97.5402 35.9, 91.5666 35.95, 76.9891 36, 87.4706 36.05, 74.9705 36.1, 80.418 36.15, 86.7154 36.2, 74.3031 36.25, 76.7863 36.3, 75.0255 36.35, 74.8802 36.4, 75.4023 36.45, 83.6758 36.5, 96.0594 36.55, 106.377 36.6, 111.861 36.65, 123.033 36.7, 122.995 36.75, 121.306 36.8, 104.512 36.85, 97.0437 36.9, 87.2972 36.95, 81.8107 37, 79.5026 37.05, 94.4856 37.1, 88.2035 37.15, 90.048 37.2, 96.6403 37.25, 95.5503 37.3, 98.1725 37.35, 109.631 37.4, 102.054 37.45, 87.1145 37.5, 93.8161 37.55, 82.8187 37.6, 86.4447 37.65, 91.6111 37.7, 89.3556 37.75, 96.8057 37.8, 100.424 37.85, 108.682 37.9, 119.003 37.95, 146.577 38, 169.89 38.05, 187.787 38.1, 222.617 38.15, 246.909 38.2, 280.136 38.25, 307.215 38.3, 355.565 38.35, 374.372 38.4, 396.038 38.45, 408.873 38.5, 405.034 38.55, 364.031 38.6, 301.051 38.65, 237.771 38.7, 205.057 38.75, 155.038 38.8, 125.081 38.85, 125.815 38.9, 111.783 38.95, 112.803 39, 113.984 39.05, 104.173 39.1, 98.8269 39.15, 91.0478 39.2, 83.3717 39.25, 94.2669 39.3, 82.0646 39.35, 81.5847 39.4, 87.714 39.45, 79.3031 39.5, 82.9163 39.55, 74.2941 39.6, 68.8073 39.65, 69.4004 39.7, 66.89 39.75, 71.0475 39.8, 82.086 39.85, 68.7372 39.9, 75.0326 39.95, 82.5109 40, 76.7223 40.05, 78.2051 40.1, 80.0078 40.15, 76.4652 40.2, 79.8017 40.25, 73.8954 40.3, 72.1662 40.35, 69.2964 40.4, 65.2579 40.45, 63.606 40.5, 57.1831 40.55, 67.7481 40.6, 69.2039 40.65, 62.4805 40.7, 64.8241 40.75, 60.5795 40.8, 65.8448 40.85, 65.8946 40.9, 71.5383 40.95, 63.9805 41, 65.4028 41.05, 63.0202 41.1, 70.1225 41.15, 62.9188 41.2, 64.7539 41.25, 68.1278 41.3, 62.0451 41.35, 65.7195 41.4, 63.7496 41.45, 64.7594 41.5, 60.5558 41.55, 58.1129 41.6, 62.644 41.65, 66.126 41.7, 65.2706 41.75, 63.4685 41.8, 64.0723 41.85, 69.7443 41.9, 73.3811 41.95, 65.2524 42, 74.9744 42.05, 75.0714 42.1, 73.2667 42.15, 70.2575 42.2, 84.4453 42.25, 104.773 42.3, 134.644 42.35, 167.51 42.4, 197.606 42.45, 210.274 42.5, 234.61 42.55, 231.426 42.6, 221.562 42.65, 184.363 42.7, 159.794 42.75, 119.036 42.8, 94.3749 42.85, 80.8279 42.9, 68.4195 42.95, 74.1841 43, 70.2024 43.05, 85.797 43.1, 98.0433 43.15, 119.394 43.2, 129.999 43.25, 165.56 43.3, 185.255 43.35, 193.943 43.4, 179.897 43.45, 154.986 43.5, 126.506 43.55, 97.8582 43.6, 87.7898 43.65, 78.8295 43.7, 72.6112 43.75, 75.0684 43.8, 89.6284 43.85, 114.142 43.9, 132.282 43.95, 147.952 44, 170.762 44.05, 161.345 44.1, 144.564 44.15, 130.813 44.2, 97.5477 44.25, 100.605 44.3, 75.5479 44.35, 73.0798 44.4, 80.4792 44.45, 84.5338 44.5, 79.7691 44.55, 83.8729 44.6, 74.8709 44.65, 83.7093 44.7, 86.2172 44.75, 74.4081 44.8, 76.6827 44.85, 60.377 44.9, 70.6135 44.95, 74.1899 45, 79.0239 45.05, 88.2986 45.1, 88.1026 45.15, 104.118 45.2, 124.869 45.25, 134.619 45.3, 128.425 45.35, 125.921 45.4, 116.881 45.45, 100.342 45.5, 87.9974 45.55, 69.9281 45.6, 69.3782 45.65, 66.9399 45.7, 69.0222 45.75, 65.1063 45.8, 71.9017 45.85, 72.9114 45.9, 62.4412 45.95, 62.2408 46, 61.0867 46.05, 67.6466 46.1, 64.9648 46.15, 65.5866 46.2, 67.5901 46.25, 68.2137 46.3, 93.9934 46.35, 102.448 46.4, 107.513 46.45, 111.667 46.5, 113.148 46.55, 103.159 46.6, 101.72 46.65, 81.0757 46.7, 85.1819 46.75, 80.0704 46.8, 78.4372 46.85, 77.6207 46.9, 94.1369 46.95, 97.5739 47, 110.717 47.05, 110.931 47.1, 122.583 47.15, 119.802 47.2, 115.705 47.25, 115.885 47.3, 103.366 47.35, 104.685 47.4, 87.1101 47.45, 81.3722 47.5, 74.6896 47.55, 82.8715 47.6, 81.4467 47.65, 84.6185 47.7, 97.0086 47.75, 106.457 47.8, 112.86 47.85, 123.62 47.9, 107.603 47.95, 105.795 48, 96.57 48.05, 91.9926 48.1, 95.8746 48.15, 84.8921 48.2, 79.4172 48.25, 77.0807 48.3, 80.4581 48.35, 79.6738 48.4, 80.6699 48.45, 92.3809 48.5, 101.201 48.55, 126.071 48.6, 134.366 48.65, 146.469 48.7, 167.546 48.75, 181.118 48.8, 161.959 48.85, 163.343 48.9, 150.591 48.95, 130.337 49, 112.128 49.05, 99.6743 49.1, 85.1887 49.15, 76.8384 49.2, 64.1232 49.25, 69.2962 49.3, 62.5137 49.35, 62.827 49.4, 72.287 49.45, 65.4116 49.5, 79.7283 49.55, 97.1841 49.6, 129.899 49.65, 143.078 49.7, 172.328 49.75, 186.736 49.8, 184.968 49.85, 189.56 49.9, 181.587 49.95, 153.035 50, 137.935 50.05, 114.905 50.1, 95.7283 50.15, 79.9065 50.2, 74.597 50.25, 84.1548 50.3, 90.042 50.35, 87.4887 50.4, 98.7139 50.45, 99.0067 50.5, 86.9505 50.55, 87.7474 50.6, 85.9631 50.65, 80.4626 50.7, 71.6448 50.75, 68.9328 50.8, 73.0077 50.85, 77.8965 50.9, 81.1037 50.95, 95.3779 51, 111.735 51.05, 126.856 51.1, 138.096 51.15, 150.819 51.2, 154.439 51.25, 148.094 51.3, 136.172 51.35, 122.632 51.4, 100.177 51.45, 87.5869 51.5, 78.3764 51.55, 78.2191 51.6, 78.2709 51.65, 77.9636 51.7, 76.8107 51.75, 79.7183 51.8, 72.8587 51.85, 74.4016 51.9, 72.9933 51.95, 66.3762 52, 68.9021 52.05, 69.4564 52.1, 59.9374 52.15, 63.0054 52.2, 61.7298 52.25, 56.6701 52.3, 68.1494 52.35, 72.2003 52.4, 65.2643 52.45, 63.6699 52.5, 70.7034 52.55, 65.9846 52.6, 65.0781 52.65, 61.6054 52.7, 62.7069 52.75, 68.3216 52.8, 64.0696 52.85, 63.1407 52.9, 63.4841 52.95, 70.9688 53, 64.3216 53.05, 73.6743 53.1, 80.1206 53.15, 78.4602 53.2, 78.7641 53.25, 80.078 53.3, 73.1416 53.35, 72.4455 53.4, 66.7358 53.45, 60.9772 53.5, 55.981 53.55, 58.0423 53.6, 64.7429 53.65, 62.4937 53.7, 70.761 53.75, 83.0235 53.8, 83.5096 53.85, 85.7929 53.9, 75.5946 53.95, 82.0644 54, 69.741 54.05, 56.0518 54.1, 56.9974 54.15, 62.657 54.2, 61.1361 54.25, 62.0887 54.3, 76.3433 54.35, 82.6709 54.4, 87.0321 54.45, 86.4695 54.5, 91.7237 54.55, 81.1933 54.6, 76.4645 54.65, 74.3431 54.7, 64.7401 54.75, 59.1875 54.8, 63.3241 54.85, 59.1623 54.9, 61.9758 ##END= Sigima-1.1.1/sigima/data/tests/curve_formats/paracetamol_dx_dy.csv000066400000000000000000000761621514013333200253310ustar00rootroot000000000000002 theta (°), Intensity, dx, dy 5,144.95,0.333385,21.7425 5.05,130.958,0.3012034,11.78622 5.1,138.617,0.277234,12.47553 5.15,127.86,0.217362,10.2288 5.2,130.526,0.0783156,16.96838 5.25,129.117,0.1807638,14.20287 5.3,146.902,0.1028314,11.75216 5.35,126.054,0.2268972,18.9081 5.4,130.71,0.248349,11.7639 5.45,136.944,0.3286656,8.21664 5.5,132.646,0.2387628,19.8969 5.55,135.503,0.2168048,13.5503 5.6,131.31,0.223227,10.5048 5.65,134.392,0.1478312,8.06352 5.7,134.115,0.0938805,8.0469 5.75,142.336,0.1565696,15.65696 5.8,124.004,0.1736056,11.16036 5.85,137.182,0.3155186,8.23092 5.9,144.611,0.1012277,15.90721 5.95,125.155,0.1627015,12.5155 6,133.639,0.1603668,20.04585 6.05,137.911,0.1654932,16.54932 6.1,130.834,0.2878348,18.31676 6.15,127.603,0.1658839,8.93221 6.2,130.111,0.2732331,11.70999 6.25,128.666,0.2315988,10.29328 6.3,131.237,0.262474,17.06081 6.35,123.651,0.2720322,7.41906 6.4,133.444,0.1868216,12.00996 6.45,129.991,0.1429901,15.59892 6.5,124.31,0.211327,18.6465 6.55,125.31,0.25062,10.0248 6.6,127.22,0.06361,15.2664 6.65,126.525,0.20244,8.85675 6.7,118.994,0.0832958,9.51952 6.75,127.921,0.2302578,12.7921 6.8,124.564,0.124564,12.4564 6.85,133.317,0.0799902,7.99902 6.9,127.625,0.1021,19.14375 6.95,127.094,0.317735,16.52222 7,125.326,0.2757172,6.2663 7.05,126.764,0.190146,8.87348 7.1,126.101,0.0882707,7.56606 7.15,118.474,0.0947792,9.47792 7.2,127.064,0.31766,11.43576 7.25,131.091,0.1704183,9.17637 7.3,135.68,0.257792,12.2112 7.35,128.569,0.0642845,6.42845 7.4,129.097,0.1678261,16.78261 7.45,126.45,0.10116,12.645 7.5,128.518,0.1156662,8.99626 7.55,129.235,0.155082,16.80055 7.6,123.793,0.1980688,7.42758 7.65,126.139,0.2144363,8.82973 7.7,132.394,0.330985,6.6197 7.75,127.318,0.3055632,15.27816 7.8,126.314,0.3031536,17.68396 7.85,126.112,0.2648352,17.65568 7.9,132.29,0.119061,14.5519 7.95,136.732,0.2597908,12.30588 8,135.149,0.2432682,20.27235 8.05,139.587,0.2093805,6.97935 8.1,134.642,0.1615704,9.42494 8.15,139.803,0.3355272,20.97045 8.2,141.572,0.2265152,19.82008 8.25,153.708,0.1075956,23.0562 8.3,148.54,0.37135,8.9124 8.35,151.054,0.0906324,19.63702 8.4,153.85,0.292315,16.9235 8.45,157.294,0.1258352,22.02116 8.5,158.885,0.3018815,9.5331 8.55,162.167,0.1135169,22.70338 8.6,165.507,0.2979126,18.20577 8.65,156.191,0.1718101,17.18101 8.7,145.237,0.1597607,7.26185 8.75,151.594,0.1061158,7.5797 8.8,147.153,0.3678825,22.07295 8.85,141.447,0.2404599,12.73023 8.9,143.715,0.1868295,11.4972 8.95,127.63,0.063815,12.763 9,130.104,0.1040832,18.21456 9.05,130.851,0.1177659,14.39361 9.1,118.595,0.1778925,10.67355 9.15,130.604,0.2350872,9.14228 9.2,131.175,0.3279375,14.42925 9.25,118.46,0.082922,10.6614 9.3,126.75,0.316875,11.4075 9.35,126.365,0.3159125,15.1638 9.4,132.485,0.0927395,6.62425 9.45,126.401,0.1390411,17.69614 9.5,122.79,0.257859,12.279 9.55,126.146,0.2018336,6.3073 9.6,133.005,0.079803,14.63055 9.65,126.313,0.1136817,15.15756 9.7,124.658,0.124658,12.4658 9.75,128.092,0.1793288,15.37104 9.8,129.795,0.1946925,9.08565 9.85,124.484,0.2240712,11.20356 9.9,126.61,0.25322,15.1932 9.95,131.695,0.1975425,19.75425 10,127.967,0.3199175,10.23736 10.05,126.272,0.31568,11.36448 10.1,134.518,0.0941626,12.10662 10.15,119.874,0.2277606,17.9811 10.2,124.126,0.2979024,16.13638 10.25,132.356,0.2382408,18.52984 10.3,130.05,0.091035,6.5025 10.35,121.237,0.2182266,6.06185 10.4,120.844,0.2658568,14.50128 10.45,123.974,0.2231532,14.87688 10.5,122.742,0.306855,7.36452 10.55,124.796,0.2246328,6.2398 10.6,135.243,0.3110589,20.28645 10.65,126.549,0.2404431,13.92039 10.7,117.422,0.176133,14.09064 10.75,135.101,0.1891414,14.86111 10.8,134.725,0.0943075,20.20875 10.85,124.339,0.0994712,17.40746 10.9,121.157,0.3028925,10.90413 10.95,124.966,0.2874218,12.4966 11,119.67,0.215406,15.5571 11.05,124.525,0.0871675,8.71675 11.1,118.806,0.1425672,15.44478 11.15,124.037,0.2232666,14.88444 11.2,116.881,0.0818167,7.01286 11.25,122.862,0.2702964,12.2862 11.3,120.684,0.241368,16.89576 11.35,126.824,0.1141416,10.14592 11.4,137.45,0.30239,12.3705 11.45,131.534,0.2236078,14.46874 11.5,123.983,0.1983728,13.63813 11.55,132.546,0.2253282,14.58006 11.6,134.337,0.1746381,6.71685 11.65,130.428,0.1565136,9.12996 11.7,137.611,0.1651332,6.88055 11.75,133.468,0.2535892,20.0202 11.8,129.303,0.1551636,9.05121 11.85,121.403,0.0728418,18.21045 11.9,134.409,0.2016135,20.16135 11.95,126.763,0.0887341,12.6763 12,130.066,0.0910462,9.10462 12.05,125.678,0.1005424,13.82458 12.1,120.724,0.30181,6.0362 12.15,133.341,0.2000115,6.66705 12.2,118.668,0.2610696,14.24016 12.25,129.796,0.1168164,11.68164 12.3,120.248,0.120248,16.83472 12.35,118.123,0.2244337,16.53722 12.4,131.801,0.2372418,11.86209 12.45,125.781,0.2767182,18.86715 12.5,118.983,0.2736609,13.08813 12.55,125.76,0.276672,7.5456 12.6,118.283,0.2010811,16.55962 12.65,122.163,0.0732978,12.2163 12.7,114.645,0.1948965,10.31805 12.75,117.965,0.2477265,8.25755 12.8,132.209,0.2379762,11.89881 12.85,133.292,0.1866088,6.6646 12.9,130.209,0.1953135,11.71881 12.95,139.162,0.2504916,13.9162 13,128.423,0.3082152,19.26345 13.05,118.367,0.1420404,8.28569 13.1,125.668,0.2890364,13.82348 13.15,133.322,0.1199898,7.99932 13.2,114.769,0.1262459,10.32921 13.25,129.273,0.3102552,9.04911 13.3,129.894,0.1818516,18.18516 13.35,137.251,0.2333267,12.35259 13.4,150.487,0.3611688,22.57305 13.45,151.853,0.3492619,12.14824 13.5,174.944,0.1049664,10.49664 13.55,201.962,0.2625506,28.27468 13.6,237.979,0.3569685,14.27874 13.65,284.611,0.5122998,28.4611 13.7,358.771,0.7892962,17.93855 13.75,385.925,0.2701475,27.01475 13.8,415.682,0.2909774,33.25456 13.85,426.614,0.3412912,25.59684 13.9,463.492,0.9733332,32.44444 13.95,475.314,1.0456908,38.02512 14,438.313,0.438313,30.68191 14.05,430.992,0.7757856,64.6488 14.1,399.599,0.2397594,23.97594 14.15,358.187,0.3940057,21.49122 14.2,337.351,0.4722914,43.85563 14.25,269.738,0.3236856,37.76332 14.3,215.848,0.3885264,30.21872 14.35,174.793,0.2621895,17.4793 14.4,162.602,0.406505,9.75612 14.45,138.565,0.221704,8.3139 14.5,151.972,0.2583524,18.23664 14.55,120.998,0.2298962,18.1497 14.6,129.249,0.1680237,15.50988 14.65,128.467,0.3211675,11.56203 14.7,120.479,0.1927664,7.22874 14.75,123.251,0.2711522,9.86008 14.8,129.125,0.2066,19.36875 14.85,130.553,0.2349954,16.97189 14.9,126.714,0.2660994,8.86998 14.95,132.646,0.2254982,6.6323 15,128.372,0.1026976,16.68836 15.05,123.694,0.061847,12.3694 15.1,125.085,0.2626785,6.25425 15.15,118.172,0.1063548,12.99892 15.2,130.737,0.1568844,15.68844 15.25,129.561,0.0777366,6.47805 15.3,121.835,0.1827525,12.1835 15.35,142.207,0.2275312,18.48691 15.4,119.999,0.1679986,7.19994 15.45,129.761,0.2076176,18.16654 15.5,121.199,0.1575587,18.17985 15.55,138.558,0.2909718,15.24138 15.6,133.687,0.3074801,14.70557 15.65,143.158,0.1717896,18.61054 15.7,168.679,0.1855469,15.18111 15.75,210.864,0.210864,25.30368 15.8,240.63,0.216567,31.2819 15.85,316.948,0.316948,22.18636 15.9,401.51,0.481812,48.1812 15.95,510.351,0.4082808,25.51755 16,575.553,1.0935507,57.5553 16.05,599.754,0.8396556,83.96556 16.1,629.712,0.5037696,62.9712 16.15,585.877,0.3515262,82.02278 16.2,522.757,0.8364112,67.95841 16.25,433.674,0.216837,26.02044 16.3,333.33,0.233331,19.9998 16.35,248.149,0.1488894,12.40745 16.4,193.047,0.3088752,17.37423 16.45,171.919,0.1375352,15.47271 16.5,145.249,0.145249,8.71494 16.55,149.683,0.1945879,17.96196 16.6,130.978,0.2095648,19.6467 16.65,154.966,0.0929796,18.59592 16.7,151.103,0.2417648,13.59927 16.75,147.778,0.1773336,17.73336 16.8,139.722,0.1536942,9.78054 16.85,149.863,0.1798356,14.9863 16.9,154.948,0.2789064,23.2422 16.95,153.706,0.1690766,18.44472 17,152.32,0.335104,18.2784 17.05,164.354,0.410885,18.07894 17.1,162.43,0.357346,22.7402 17.15,144.656,0.072328,14.4656 17.2,153.821,0.307642,18.45852 17.25,155.359,0.0932154,13.98231 17.3,139.634,0.1256706,16.75608 17.35,150.208,0.1051456,10.51456 17.4,149.206,0.149206,13.42854 17.45,158.561,0.1902732,15.8561 17.5,179.514,0.3231252,14.36112 17.55,189.998,0.3039968,26.59972 17.6,225.865,0.4743165,31.6211 17.65,258.699,0.1552194,20.69592 17.7,301.535,0.361842,33.16885 17.75,346.1,0.62298,27.688 17.8,436.152,1.0467648,21.8076 17.85,563.963,1.0151334,84.59445 17.9,693.097,1.4555037,90.10261 17.95,795.983,0.5571881,39.79915 18,922.02,2.30505,101.4222 18.05,986.19,1.873761,49.3095 18.1,997.449,0.997449,49.87245 18.15,913.216,0.6392512,109.58592 18.2,857.842,1.6298998,120.09788 18.25,704.079,0.8448948,63.36711 18.3,552.753,1.3266072,49.74777 18.35,450.754,0.901508,40.56786 18.4,359.362,0.2515534,21.56172 18.45,308.906,0.7413744,18.53436 18.5,271.303,0.3526939,32.55636 18.55,259.971,0.5979333,31.19652 18.6,247.38,0.568974,24.738 18.65,235.205,0.329287,23.5205 18.7,233.156,0.4429964,34.9734 18.75,240.439,0.3847024,28.85268 18.8,219.655,0.219655,21.9655 18.85,238.381,0.1430286,35.75715 18.9,242.358,0.605895,21.81222 18.95,224.804,0.3596864,26.97648 19,217.139,0.2822807,21.7139 19.05,214.682,0.4723004,21.4682 19.1,234.321,0.2811852,11.71605 19.15,232.843,0.5821075,13.97058 19.2,239.377,0.5026917,19.15016 19.25,271.223,0.4339568,37.97122 19.3,296.601,0.2669409,32.62611 19.35,349.65,0.48951,31.4685 19.4,414.915,0.248949,37.34235 19.45,453.014,0.9966308,27.18084 19.5,475.948,0.8567064,38.07584 19.55,465.006,0.5115066,32.55042 19.6,436.328,0.3926952,21.8164 19.65,377.371,0.4151081,18.86855 19.7,302.985,0.60597,15.14925 19.75,259.159,0.518318,31.09908 19.8,214.726,0.4723972,32.2089 19.85,199.541,0.3591738,13.96787 19.9,191.483,0.3063728,21.06313 19.95,174.363,0.2441082,26.15445 20,183.943,0.1103658,9.19715 20.05,172.731,0.2245503,19.00041 20.1,180.382,0.4329168,16.23438 20.15,167.302,0.1171114,20.07624 20.2,186.818,0.280227,26.15452 20.25,166.506,0.1831566,23.31084 20.3,176.664,0.2119968,22.96632 20.35,166.334,0.3659348,13.30672 20.4,161.125,0.3061375,16.1125 20.45,171.349,0.342698,15.42141 20.5,173.675,0.4341875,24.3145 20.55,162.959,0.2118467,22.81426 20.6,180.984,0.3076728,18.0984 20.65,187.443,0.3373974,14.99544 20.7,199.199,0.4382378,15.93592 20.75,207.095,0.3520615,31.06425 20.8,225.995,0.542388,18.0796 20.85,246.59,0.172613,14.7954 20.9,285.148,0.142574,42.7722 20.95,340.1,0.3401,17.005 21,446.62,0.89324,58.0606 21.05,582.385,1.397724,87.35775 21.1,654.08,1.504384,78.4896 21.15,729.274,1.0209836,72.9274 21.2,760.561,0.3802805,106.47854 21.25,725.147,1.7403528,36.25735 21.3,657.166,1.3800486,32.8583 21.35,562.369,0.6186059,44.98952 21.4,411.676,0.8645196,28.81732 21.45,317.024,0.3487264,47.5536 21.5,244.341,0.5131161,26.87751 21.55,195.207,0.3123312,13.66449 21.6,173.296,0.3292624,12.13072 21.65,155.771,0.3271191,9.34626 21.7,144.105,0.230568,7.20525 21.75,139.791,0.0978537,19.57074 21.8,139.447,0.2091705,8.36682 21.85,148.986,0.2383776,22.3479 21.9,151.228,0.1058596,22.6842 21.95,155.93,0.15593,21.8302 22,163.39,0.359458,9.8034 22.05,160.719,0.0803595,16.0719 22.1,155.959,0.3587057,9.35754 22.15,154.821,0.3715704,12.38568 22.2,149.745,0.359388,22.46175 22.25,149.557,0.2542469,16.45127 22.3,134.243,0.2550617,8.05458 22.35,133.744,0.2808624,6.6872 22.4,132.446,0.066223,15.89352 22.45,125.265,0.2380035,7.5159 22.5,131.207,0.1705691,18.36898 22.55,133.317,0.1199853,18.66438 22.6,129.588,0.1036704,19.4382 22.65,131.296,0.2888512,18.38144 22.7,121.493,0.0607465,8.50451 22.75,121.23,0.133353,7.2738 22.8,130.54,0.287188,14.3594 22.85,123.753,0.1113777,14.85036 22.9,118.983,0.1546779,9.51864 22.95,122.956,0.0737736,14.75472 23,113.356,0.056678,15.86984 23.05,116.166,0.2207154,13.93992 23.1,127.571,0.2041136,14.03281 23.15,125.147,0.1752058,15.01764 23.2,137.035,0.191849,8.2221 23.25,155.434,0.1865208,13.98906 23.3,170.429,0.2386006,23.86006 23.35,180.516,0.361032,21.66192 23.4,196.616,0.1769544,9.8308 23.45,211.396,0.52849,10.5698 23.5,216.658,0.3899844,17.33264 23.55,237.929,0.4282722,28.55148 23.6,276.499,0.4700483,30.41489 23.65,291.107,0.3493284,43.66605 23.7,328.354,0.656708,49.2531 23.75,333.171,0.5330736,36.64881 23.8,343.157,0.5147355,20.58942 23.85,330.592,0.3967104,19.83552 23.9,287.284,0.5171112,31.60124 23.95,262.081,0.4979539,28.82891 24,224.983,0.4274677,29.24779 24.05,232.686,0.3024918,20.94174 24.1,221.321,0.1106605,30.98494 24.15,239.779,0.1198895,14.38674 24.2,283.117,0.566234,42.46755 24.25,272.335,0.2995685,16.3401 24.3,273.056,0.4641952,19.11392 24.35,252.636,0.2273724,20.21088 24.4,220.542,0.3969756,11.0271 24.45,172.207,0.2410898,22.38691 24.5,150.821,0.1960673,19.60673 24.55,133.023,0.1463253,15.96276 24.6,131.079,0.3145896,13.1079 24.65,125.341,0.0752046,7.52046 24.7,122.106,0.2686332,9.76848 24.75,122.052,0.2929248,14.64624 24.8,127.441,0.2803702,15.29292 24.85,115.91,0.057955,8.1137 24.9,120.508,0.2289652,13.25588 24.95,124.163,0.1614119,16.14119 25,108.357,0.1733712,16.25355 25.05,114.624,0.2636352,8.02368 25.1,120.72,0.205224,14.4864 25.15,122.091,0.2563911,6.10455 25.2,119.482,0.2509122,16.72748 25.25,129.144,0.2195448,11.62296 25.3,123.056,0.123056,17.22784 25.35,126.572,0.2784584,17.72008 25.4,123.624,0.0865368,9.88992 25.45,115.467,0.2078406,17.32005 25.5,120.053,0.240106,18.00795 25.55,118.137,0.2244603,9.45096 25.6,128.948,0.2965804,11.60532 25.65,130.204,0.2213468,6.5102 25.7,126.32,0.101056,8.8424 25.75,128.999,0.1418989,19.34985 25.8,132.911,0.2259487,7.97466 25.85,130.626,0.2873772,9.14382 25.9,133.537,0.2403666,13.3537 25.95,133.16,0.319584,14.6476 26,135.097,0.2837037,20.26455 26.05,123.364,0.0740184,8.63548 26.1,129.515,0.129515,7.7709 26.15,121.09,0.169526,10.8981 26.2,120.242,0.1683388,6.0121 26.25,123.316,0.184974,13.56476 26.3,116.317,0.0697902,17.44755 26.35,114.714,0.1032426,12.61854 26.4,118.821,0.2495241,5.94105 26.45,111.891,0.2797275,8.95128 26.5,130.199,0.2994577,10.41592 26.55,121.559,0.1458708,10.94031 26.6,128.008,0.1792112,12.8008 26.65,134.657,0.0942599,8.07942 26.7,137.686,0.3166778,6.8843 26.75,154.145,0.154145,20.03885 26.8,172.061,0.1032366,20.64732 26.85,208.748,0.3339968,25.04976 26.9,216.904,0.3470464,26.02848 26.95,233.256,0.349884,23.3256 27,238.691,0.4296438,21.48219 27.05,231.06,0.369696,27.7272 27.1,228.972,0.5495328,25.18692 27.15,246.491,0.6162275,32.04383 27.2,307.083,0.3684996,18.42498 27.25,367.255,0.6977845,25.70785 27.3,494.578,0.3956624,69.24092 27.35,583.502,0.9919534,40.84514 27.4,662.527,0.662527,59.62743 27.45,683.387,0.8884031,102.50805 27.5,628.664,1.4459272,69.15304 27.55,527.825,0.7917375,42.226 27.6,412.596,0.7426728,41.2596 27.65,289.458,0.6368076,28.9458 27.7,222.51,0.155757,28.9263 27.75,165.663,0.3975912,24.84945 27.8,146.087,0.2191305,8.76522 27.85,143.243,0.0859458,14.3243 27.9,147.558,0.147558,17.70696 27.95,133.242,0.2131872,11.99178 28,135.915,0.1223235,9.51405 28.05,138.778,0.2914338,12.49002 28.1,153.454,0.306908,23.0181 28.15,182.119,0.4006618,10.92714 28.2,231.315,0.138789,34.69725 28.25,331.988,0.2323916,43.15844 28.3,485.443,0.2912658,38.83544 28.35,655.047,0.8515611,72.05517 28.4,747.839,0.5982712,104.69746 28.45,794.338,1.3503746,95.32056 28.5,768.941,1.3840938,38.44705 28.55,730.637,0.4383822,51.14459 28.6,606.509,1.1523671,42.45563 28.65,497.263,0.7458945,74.58945 28.7,365.608,0.4752904,18.2804 28.75,301.191,0.4517865,21.08337 28.8,284.499,0.5974479,36.98487 28.85,236.869,0.3789904,14.21214 28.9,235.612,0.3769792,18.84896 28.95,229.989,0.5059758,25.29879 29,217.086,0.4775892,19.53774 29.05,200.749,0.1605992,16.05992 29.1,172.124,0.3614604,22.37612 29.15,157.951,0.1737461,9.47706 29.2,143.448,0.143448,7.1724 29.25,139.142,0.1947988,8.34852 29.3,129.961,0.2209337,14.29571 29.35,120.542,0.2290298,8.43794 29.4,123.203,0.1848045,9.85624 29.45,124.883,0.0999064,12.4883 29.5,121.38,0.157794,8.4966 29.55,124.496,0.2240928,12.4496 29.6,116.452,0.1397424,15.13876 29.65,117.536,0.1998112,7.05216 29.7,105.712,0.1902816,6.34272 29.75,105.066,0.210132,9.45594 29.8,110.455,0.1656825,9.94095 29.85,107.286,0.214572,6.43716 29.9,107.302,0.160953,12.87624 29.95,100.37,0.20074,15.0555 30,104.262,0.1668192,11.46882 30.05,108.8,0.26112,13.056 30.1,102.571,0.2153991,7.17997 30.15,107.745,0.064647,11.85195 30.2,109.268,0.2513164,14.20484 30.25,112.579,0.1913843,12.38369 30.3,113.249,0.2831225,16.98735 30.35,121.137,0.121137,12.1137 30.4,115.554,0.1271094,15.02202 30.45,118.863,0.2971575,14.26356 30.5,108.779,0.2501917,15.22906 30.55,122.623,0.1594099,18.39345 30.6,127.857,0.3068568,11.50713 30.65,175.396,0.1403168,8.7698 30.7,153.839,0.2769102,19.99907 30.75,177.213,0.1063278,24.80982 30.8,264.975,0.582945,13.24875 30.85,403.475,0.887645,32.278 30.9,603.393,0.8447502,48.27144 30.95,739.19,0.443514,66.5271 31,868.527,0.6079689,69.48216 31.05,895.174,0.5371044,116.37262 31.1,871.207,1.8295347,113.25691 31.15,767.671,1.6888762,61.41368 31.2,580.394,0.7545122,81.25516 31.25,411.294,0.4935528,57.58116 31.3,254.655,0.407448,30.5586 31.35,174.042,0.2436588,22.62546 31.4,141.004,0.3243092,8.46024 31.45,132.848,0.1195632,17.27024 31.5,143.299,0.1289691,18.62887 31.55,173.763,0.0868815,15.63867 31.6,222.379,0.1334274,24.46169 31.65,273.548,0.5744508,41.0322 31.7,336.13,0.403356,36.9743 31.75,342.951,0.2400657,34.2951 31.8,368.917,0.8485091,36.8917 31.85,344.129,0.4817806,20.64774 31.9,301.892,0.3622704,33.20812 31.95,257.527,0.1545162,36.05378 32,210.377,0.420754,27.34901 32.05,153.977,0.2155678,10.77839 32.1,120.768,0.1932288,14.49216 32.15,111.966,0.2463252,14.55558 32.2,98.0284,0.07842272,10.783124 32.25,110.733,0.1660995,12.18063 32.3,105.261,0.1578915,6.31566 32.35,115.513,0.1732695,10.39617 32.4,136.501,0.1228509,6.82505 32.45,133.028,0.3192672,18.62392 32.5,153.976,0.2463616,10.77832 32.55,158.283,0.1107981,18.99396 32.6,155.428,0.1865136,23.3142 32.65,166.281,0.1496529,9.97686 32.7,160.161,0.1921932,12.81288 32.75,138.813,0.277626,18.04569 32.8,129.654,0.1166886,14.26194 32.85,107.903,0.2373866,14.02739 32.9,102.454,0.2253988,6.14724 32.95,94.5222,0.0945222,8.506998 33,92.0796,0.0920796,5.524776 33.05,100.767,0.1914573,5.03835 33.1,93.1643,0.22359432,11.179716 33.15,100.026,0.1200312,9.00234 33.2,97.5103,0.17551854,11.701236 33.25,92.3957,0.12011441,9.23957 33.3,100.681,0.1510215,13.08853 33.35,93.7026,0.06559182,12.181338 33.4,96.3929,0.12531077,8.675361 33.45,94.2689,0.0942689,4.713445 33.5,91.6066,0.0458033,11.908858 33.55,94.2608,0.16024336,5.655648 33.6,107.175,0.150045,12.861 33.65,117.332,0.058666,17.5998 33.7,137.671,0.2478078,20.65065 33.75,174.952,0.3149136,13.99616 33.8,207.309,0.4768107,24.87708 33.85,259.132,0.4405244,25.9132 33.9,300.681,0.2706129,33.07491 33.95,314.389,0.5973391,25.15112 34,329.562,0.5602554,32.9562 34.05,361.983,0.4705779,36.1983 34.1,371.593,0.8918232,44.59116 34.15,395.073,0.4740876,23.70438 34.2,391.143,0.4693716,27.38001 34.25,415.402,0.7061834,41.5402 34.3,393.297,0.6292752,35.39673 34.35,355.074,0.177537,46.15962 34.4,304.059,0.7297416,33.44649 34.45,272.36,0.6809,32.6832 34.5,225.305,0.4280795,11.26525 34.55,192.763,0.3084208,23.13156 34.6,152.001,0.2280015,13.68009 34.65,127.494,0.1784916,19.1241 34.7,118.867,0.1545271,11.8867 34.75,105.45,0.115995,11.5995 34.8,94.9779,0.19945359,7.598232 34.85,101.963,0.1835334,14.27482 34.9,103.24,0.05162,12.3888 34.95,95.7296,0.17231328,4.78648 35,108.992,0.0980928,11.98912 35.05,109.546,0.1533644,6.57276 35.1,102.401,0.0512005,14.33614 35.15,84.1487,0.20195688,8.41487 35.2,81.9302,0.09012322,8.19302 35.25,86.6041,0.16454779,5.196246 35.3,79.7155,0.18334565,6.37724 35.35,75.6335,0.1815204,8.319685 35.4,69.75,0.04185,6.975 35.45,80.7793,0.12924688,9.693516 35.5,90.6558,0.20850834,9.06558 35.55,86.4237,0.0864237,12.963555 35.6,91.7114,0.0917114,10.088254 35.65,95.0993,0.1901986,11.411916 35.7,100.998,0.0807984,7.06986 35.75,106.753,0.2028307,7.47271 35.8,101.731,0.2543275,10.1731 35.85,97.5402,0.06827814,9.75402 35.9,91.5666,0.16481988,10.987992 35.95,76.9891,0.10778474,10.778474 36,87.4706,0.19243532,8.74706 36.05,74.9705,0.14244395,11.245575 36.1,80.418,0.080418,4.0209 36.15,86.7154,0.09538694,9.538694 36.2,74.3031,0.15603651,5.201217 36.25,76.7863,0.05375041,5.375041 36.3,75.0255,0.150051,6.752295 36.35,74.8802,0.10483228,3.74401 36.4,75.4023,0.06032184,11.310345 36.45,83.6758,0.14224886,9.204338 36.5,96.0594,0.18251286,8.645346 36.55,106.377,0.0531885,5.31885 36.6,111.861,0.1566054,10.06749 36.65,123.033,0.1476396,9.84264 36.7,122.995,0.221391,15.98935 36.75,121.306,0.2183508,14.55672 36.8,104.512,0.0627072,6.27072 36.85,97.0437,0.11645244,8.733933 36.9,87.2972,0.09602692,7.856748 36.95,81.8107,0.11453498,5.726749 37,79.5026,0.10335338,7.155234 37.05,94.4856,0.1417284,5.669136 37.1,88.2035,0.18522735,7.938315 37.15,90.048,0.1530816,6.30336 37.2,96.6403,0.13529642,7.731224 37.25,95.5503,0.14332545,14.332545 37.3,98.1725,0.16689325,14.725875 37.35,109.631,0.2411882,6.57786 37.4,102.054,0.2143134,11.22594 37.45,87.1145,0.1045374,6.098015 37.5,93.8161,0.14072415,6.567127 37.55,82.8187,0.19876488,4.969122 37.6,86.4447,0.18153387,6.915576 37.65,91.6111,0.21070553,13.741665 37.7,89.3556,0.11616228,8.042004 37.75,96.8057,0.11616684,10.648627 37.8,100.424,0.100424,14.05936 37.85,108.682,0.1738912,9.78138 37.9,119.003,0.0595015,7.14018 37.95,146.577,0.1905501,11.72616 38,169.89,0.152901,22.0857 38.05,187.787,0.2065657,15.02296 38.1,222.617,0.445234,17.80936 38.15,246.909,0.3950544,37.03635 38.2,280.136,0.1680816,42.0204 38.25,307.215,0.675873,39.93795 38.3,355.565,0.213339,17.77825 38.35,374.372,0.561558,29.94976 38.4,396.038,0.2772266,31.68304 38.45,408.873,0.817746,61.33095 38.5,405.034,0.9720816,40.5034 38.55,364.031,0.3276279,18.20155 38.6,301.051,0.5418918,36.12612 38.65,237.771,0.3566565,28.53252 38.7,205.057,0.2665741,16.40456 38.75,155.038,0.2480608,9.30228 38.8,125.081,0.1000648,6.25405 38.85,125.815,0.2390485,16.35595 38.9,111.783,0.0894264,5.58915 38.95,112.803,0.2030454,9.02424 39,113.984,0.2165696,10.25856 39.05,104.173,0.1875114,9.37557 39.1,98.8269,0.05929614,14.824035 39.15,91.0478,0.19120038,11.836214 39.2,83.3717,0.17508057,6.669736 39.25,94.2669,0.07541352,12.254697 39.3,82.0646,0.09027106,9.027106 39.35,81.5847,0.19580328,10.606011 39.4,87.714,0.0789426,10.52568 39.45,79.3031,0.19825775,3.965155 39.5,82.9163,0.14924934,9.949956 39.55,74.2941,0.03714705,8.172351 39.6,68.8073,0.15825679,10.321095 39.65,69.4004,0.04164024,10.41006 39.7,66.89,0.127091,4.0134 39.75,71.0475,0.113676,6.394275 39.8,82.086,0.1723806,11.49204 39.85,68.7372,0.0343686,5.498976 39.9,75.0326,0.14256194,5.252282 39.95,82.5109,0.18152398,6.600872 40,76.7223,0.16878906,11.508345 40.05,78.2051,0.04692306,11.730765 40.1,80.0078,0.16801638,10.401014 40.15,76.4652,0.0764652,9.175824 40.2,79.8017,0.16758357,7.98017 40.25,73.8954,0.05911632,11.08431 40.3,72.1662,0.17319888,10.82493 40.35,69.2964,0.08315568,3.46482 40.4,65.2579,0.15009317,4.568053 40.45,63.606,0.0763272,4.45242 40.5,57.1831,0.06290141,8.577465 40.55,67.7481,0.05419848,6.097329 40.6,69.2039,0.12456702,4.844273 40.65,62.4805,0.06872855,8.122465 40.7,64.8241,0.10371856,7.130651 40.75,60.5795,0.09086925,4.84636 40.8,65.8448,0.164612,8.559824 40.85,65.8946,0.07907352,7.248406 40.9,71.5383,0.13592277,4.292298 40.95,63.9805,0.10876685,3.83883 41,65.4028,0.11772504,7.848336 41.05,63.0202,0.11973838,8.192626 41.1,70.1225,0.07713475,9.81715 41.15,62.9188,0.10696196,3.775128 41.2,64.7539,0.14245858,7.770468 41.25,68.1278,0.16350672,6.131502 41.3,62.0451,0.1240902,5.584059 41.35,65.7195,0.0920073,5.914755 41.4,63.7496,0.10199936,5.099968 41.45,64.7594,0.04533158,7.123534 41.5,60.5558,0.13322276,5.450022 41.55,58.1129,0.05230161,4.067903 41.6,62.644,0.1064948,8.14372 41.65,66.126,0.165315,3.3063 41.7,65.2706,0.04568942,5.221648 41.75,63.4685,0.13328385,3.173425 41.8,64.0723,0.08970122,7.047953 41.85,69.7443,0.08369316,6.276987 41.9,73.3811,0.03669055,5.136677 41.95,65.2524,0.15008052,3.915144 42,74.9744,0.187436,7.49744 42.05,75.0714,0.15764994,11.26071 42.1,73.2667,0.08059337,10.990005 42.15,70.2575,0.11943775,4.918025 42.2,84.4453,0.10133436,12.666795 42.25,104.773,0.1362049,7.33411 42.3,134.644,0.1481084,9.42508 42.35,167.51,0.385273,13.4008 42.4,197.606,0.2766484,27.66484 42.45,210.274,0.4626028,12.61644 42.5,234.61,0.375376,11.7305 42.55,231.426,0.2545686,18.51408 42.6,221.562,0.553905,33.2343 42.65,184.363,0.1290541,20.27993 42.7,159.794,0.2876292,9.58764 42.75,119.036,0.238072,15.47468 42.8,94.3749,0.12268737,6.606243 42.85,80.8279,0.09699348,5.657953 42.9,68.4195,0.12999705,4.789365 42.95,74.1841,0.17804184,10.385774 43,70.2024,0.07722264,5.616192 43.05,85.797,0.1286955,10.29564 43.1,98.0433,0.11765196,11.765196 43.15,119.394,0.2507274,17.9091 43.2,129.999,0.2469981,18.19986 43.25,165.56,0.314564,11.5892 43.3,185.255,0.3519845,16.67295 43.35,193.943,0.3490974,19.3943 43.4,179.897,0.4317528,12.59279 43.45,154.986,0.1394874,17.04846 43.5,126.506,0.1012048,11.38554 43.55,97.8582,0.21528804,11.742984 43.6,87.7898,0.18435858,5.267388 43.65,78.8295,0.0945954,11.03613 43.7,72.6112,0.13796128,3.63056 43.75,75.0684,0.17265732,7.50684 43.8,89.6284,0.05377704,8.96284 43.85,114.142,0.057071,9.13136 43.9,132.282,0.132282,10.58256 43.95,147.952,0.2367232,16.27472 44,170.762,0.170762,22.19906 44.05,161.345,0.1129415,17.74795 44.1,144.564,0.36141,7.2282 44.15,130.813,0.2093008,17.00569 44.2,97.5477,0.20485017,13.656678 44.25,100.605,0.1509075,14.0847 44.3,75.5479,0.09821227,8.310269 44.35,73.0798,0.16808354,4.384788 44.4,80.4792,0.05633544,7.243128 44.45,84.5338,0.05072028,10.144056 44.5,79.7691,0.1595382,4.786146 44.55,83.8729,0.15097122,7.548561 44.6,74.8709,0.14225471,9.733217 44.65,83.7093,0.1674186,7.533837 44.7,86.2172,0.12070408,12.070408 44.75,74.4081,0.11905296,9.673053 44.8,76.6827,0.1533654,4.600962 44.85,60.377,0.0422639,4.22639 44.9,70.6135,0.06355215,7.767485 44.95,74.1899,0.08160889,7.41899 45,79.0239,0.07112151,4.741434 45.05,88.2986,0.12361804,6.180902 45.1,88.1026,0.2202565,9.691286 45.15,104.118,0.260295,10.4118 45.2,124.869,0.2372511,8.74083 45.25,134.619,0.3365475,13.4619 45.3,128.425,0.2183225,16.69525 45.35,125.921,0.1133289,8.81447 45.4,116.881,0.2688263,5.84405 45.45,100.342,0.0702394,8.02736 45.5,87.9974,0.2199935,9.679714 45.55,69.9281,0.17482025,9.090653 45.6,69.3782,0.11100512,10.40673 45.65,66.9399,0.12049182,4.685793 45.7,69.0222,0.13114218,5.521776 45.75,65.1063,0.1302126,5.208504 45.8,71.9017,0.12223289,7.909187 45.85,72.9114,0.1093671,8.020254 45.9,62.4412,0.08741768,6.868532 45.95,62.2408,0.0933612,5.601672 46,61.0867,0.09163005,6.10867 46.05,67.6466,0.08117592,6.76466 46.1,64.9648,0.0974472,4.547536 46.15,65.5866,0.03935196,9.182124 46.2,67.5901,0.04731307,10.138515 46.25,68.2137,0.1364274,3.410685 46.3,93.9934,0.21618482,8.459406 46.35,102.448,0.1741616,15.3672 46.4,107.513,0.0645078,15.05182 46.45,111.667,0.223334,5.58335 46.5,113.148,0.226296,7.92036 46.55,103.159,0.1856862,14.44226 46.6,101.72,0.244128,14.2408 46.65,81.0757,0.20268925,5.675299 46.7,85.1819,0.16184561,11.925466 46.75,80.0704,0.1201056,4.00352 46.8,78.4372,0.18040556,5.490604 46.85,77.6207,0.14747933,5.433449 46.9,94.1369,0.21651487,14.120535 46.95,97.5739,0.23417736,8.781651 47,110.717,0.1992906,16.60755 47.05,110.931,0.1663965,12.20241 47.1,122.583,0.2819409,6.12915 47.15,119.802,0.1078218,9.58416 47.2,115.705,0.2892625,9.2564 47.25,115.885,0.139062,16.2239 47.3,103.366,0.2480784,6.20196 47.35,104.685,0.146559,10.4685 47.4,87.1101,0.04355505,7.839909 47.45,81.3722,0.05696054,6.509776 47.5,74.6896,0.0746896,3.73448 47.55,82.8715,0.1823173,6.62972 47.6,81.4467,0.0814467,9.773604 47.65,84.6185,0.0846185,4.230925 47.7,97.0086,0.11641032,5.820516 47.75,106.457,0.0958113,8.51656 47.8,112.86,0.259578,5.643 47.85,123.62,0.12362,17.3068 47.9,107.603,0.1398839,5.38015 47.95,105.795,0.063477,12.6954 48,96.57,0.077256,5.7942 48.05,91.9926,0.21158298,5.519556 48.1,95.8746,0.08628714,13.422444 48.15,84.8921,0.04244605,10.187052 48.2,79.4172,0.16677612,7.147548 48.25,77.0807,0.05395649,11.562105 48.3,80.4581,0.09654972,12.068715 48.35,79.6738,0.16731498,10.357594 48.4,80.6699,0.12100485,9.680388 48.45,92.3809,0.11085708,13.857135 48.5,101.201,0.1113211,9.10809 48.55,126.071,0.2143207,18.91065 48.6,134.366,0.2149856,13.4366 48.65,146.469,0.1757628,14.6469 48.7,167.546,0.2345644,23.45644 48.75,181.118,0.1086708,9.0559 48.8,161.959,0.2753303,24.29385 48.85,163.343,0.1796773,22.86802 48.9,150.591,0.2560047,12.04728 48.95,130.337,0.3128088,9.12359 49,112.128,0.1233408,8.97024 49.05,99.6743,0.12957659,4.983715 49.1,85.1887,0.12778305,5.963209 49.15,76.8384,0.13830912,5.378688 49.2,64.1232,0.0320616,7.694784 49.25,69.2962,0.15938126,4.157772 49.3,62.5137,0.11252466,5.001096 49.35,62.827,0.1005232,9.42405 49.4,72.287,0.0361435,3.61435 49.45,65.4116,0.13736436,5.232928 49.5,79.7283,0.19134792,8.770113 49.55,97.1841,0.0971841,13.605774 49.6,129.899,0.0909293,15.58788 49.65,143.078,0.2575404,14.3078 49.7,172.328,0.258492,8.6164 49.75,186.736,0.2054096,18.6736 49.8,184.968,0.092484,25.89552 49.85,189.56,0.170604,11.3736 49.9,181.587,0.2360631,21.79044 49.95,153.035,0.1989455,10.71245 50,137.935,0.2896635,9.65545 50.05,114.905,0.1034145,6.8943 50.1,95.7283,0.15316528,9.57283 50.15,79.9065,0.159813,6.39252 50.2,74.597,0.0596776,5.22179 50.25,84.1548,0.0420774,8.41548 50.3,90.042,0.045021,6.30294 50.35,87.4887,0.06124209,10.498644 50.4,98.7139,0.23691336,6.909973 50.45,99.0067,0.16831139,8.910603 50.5,86.9505,0.1391208,6.086535 50.55,87.7474,0.05264844,7.019792 50.6,85.9631,0.14613727,10.315572 50.65,80.4626,0.05632382,6.437008 50.7,71.6448,0.17194752,6.448032 50.75,68.9328,0.1378656,6.203952 50.8,73.0077,0.18251925,6.570693 50.85,77.8965,0.19474125,9.34758 50.9,81.1037,0.12165555,6.488296 50.95,95.3779,0.21936917,8.584011 51,111.735,0.1899495,14.52555 51.05,126.856,0.1649128,19.0284 51.1,138.096,0.0828576,13.8096 51.15,150.819,0.2111466,7.54095 51.2,154.439,0.1081073,21.62146 51.25,148.094,0.1629034,8.88564 51.3,136.172,0.204258,6.8086 51.35,122.632,0.2943168,8.58424 51.4,100.177,0.1202124,11.01947 51.45,87.5869,0.06131083,9.634559 51.5,78.3764,0.12540224,6.270112 51.55,78.2191,0.19554775,4.693146 51.6,78.2709,0.11740635,10.957926 51.65,77.9636,0.14033448,8.575996 51.7,76.8107,0.14594033,9.985391 51.75,79.7183,0.17538026,7.97183 51.8,72.8587,0.08743044,6.557283 51.85,74.4016,0.0744016,10.416224 51.9,72.9933,0.15328593,8.759196 51.95,66.3762,0.12611478,5.973858 52,68.9021,0.09646294,6.89021 52.05,69.4564,0.0347282,4.167384 52.1,59.9374,0.1198748,6.593114 52.15,63.0054,0.1260108,3.780324 52.2,61.7298,0.08024874,8.024874 52.25,56.6701,0.13600824,7.367113 52.3,68.1494,0.0340747,10.22241 52.35,72.2003,0.07942033,10.108042 52.4,65.2643,0.14358146,8.484359 52.45,63.6699,0.14007378,9.550485 52.5,70.7034,0.09898476,9.191442 52.55,65.9846,0.11877228,6.59846 52.6,65.0781,0.03904686,9.110934 52.65,61.6054,0.08624756,8.008702 52.7,62.7069,0.11287242,6.27069 52.75,68.3216,0.1366432,8.198592 52.8,64.0696,0.1281392,5.125568 52.85,63.1407,0.11365326,6.945477 52.9,63.4841,0.09522615,7.618092 52.95,70.9688,0.09935632,10.64532 53,64.3216,0.10934672,3.859296 53.05,73.6743,0.13998117,5.157201 53.1,80.1206,0.1602412,4.807236 53.15,78.4602,0.1176903,10.199826 53.2,78.7641,0.11814615,4.725846 53.25,80.078,0.120117,5.60546 53.3,73.1416,0.16822568,7.31416 53.35,72.4455,0.16662465,9.417915 53.4,66.7358,0.1668395,8.008296 53.45,60.9772,0.1219544,4.878176 53.5,55.981,0.0391867,5.5981 53.55,58.0423,0.1160846,4.643384 53.6,64.7429,0.07769148,5.826861 53.65,62.4937,0.11873803,8.749118 53.7,70.761,0.0566088,7.78371 53.75,83.0235,0.09132585,10.793055 53.8,83.5096,0.15031728,12.52644 53.85,85.7929,0.05147574,12.868935 53.9,75.5946,0.0755946,9.071352 53.95,82.0644,0.11489016,7.385796 54,69.741,0.0836892,10.46115 54.05,56.0518,0.13452432,6.726216 54.1,56.9974,0.13679376,2.84987 54.15,62.657,0.1315797,5.63913 54.2,61.1361,0.09781776,6.11361 54.25,62.0887,0.07450644,5.587983 54.3,76.3433,0.08397763,9.924629 54.35,82.6709,0.04133545,8.26709 54.4,87.0321,0.13925136,10.443852 54.45,86.4695,0.1210573,12.10573 54.5,91.7237,0.16510266,5.503422 54.55,81.1933,0.07307397,4.871598 54.6,76.4645,0.1223432,9.17574 54.65,74.3431,0.05947448,7.43431 54.7,64.7401,0.14890223,9.063614 54.75,59.1875,0.05326875,2.959375 54.8,63.3241,0.05065928,8.232133 54.85,59.1623,0.07099476,7.691099 54.9,61.9758,0.09916128,4.958064 Sigima-1.1.1/sigima/data/tests/curve_formats/paracetamol_dy.csv000066400000000000000000000525621514013333200246340ustar00rootroot000000000000002 theta (°), Intensity,Uncertainty 5,144.95,21.7425 5.05,130.958,11.78622 5.1,138.617,12.47553 5.15,127.86,10.2288 5.2,130.526,16.96838 5.25,129.117,14.20287 5.3,146.902,11.75216 5.35,126.054,18.9081 5.4,130.71,11.7639 5.45,136.944,8.21664 5.5,132.646,19.8969 5.55,135.503,13.5503 5.6,131.31,10.5048 5.65,134.392,8.06352 5.7,134.115,8.0469 5.75,142.336,15.65696 5.8,124.004,11.16036 5.85,137.182,8.23092 5.9,144.611,15.90721 5.95,125.155,12.5155 6,133.639,20.04585 6.05,137.911,16.54932 6.1,130.834,18.31676 6.15,127.603,8.93221 6.2,130.111,11.70999 6.25,128.666,10.29328 6.3,131.237,17.06081 6.35,123.651,7.41906 6.4,133.444,12.00996 6.45,129.991,15.59892 6.5,124.31,18.6465 6.55,125.31,10.0248 6.6,127.22,15.2664 6.65,126.525,8.85675 6.7,118.994,9.51952 6.75,127.921,12.7921 6.8,124.564,12.4564 6.85,133.317,7.99902 6.9,127.625,19.14375 6.95,127.094,16.52222 7,125.326,6.2663 7.05,126.764,8.87348 7.1,126.101,7.56606 7.15,118.474,9.47792 7.2,127.064,11.43576 7.25,131.091,9.17637 7.3,135.68,12.2112 7.35,128.569,6.42845 7.4,129.097,16.78261 7.45,126.45,12.645 7.5,128.518,8.99626 7.55,129.235,16.80055 7.6,123.793,7.42758 7.65,126.139,8.82973 7.7,132.394,6.6197 7.75,127.318,15.27816 7.8,126.314,17.68396 7.85,126.112,17.65568 7.9,132.29,14.5519 7.95,136.732,12.30588 8,135.149,20.27235 8.05,139.587,6.97935 8.1,134.642,9.42494 8.15,139.803,20.97045 8.2,141.572,19.82008 8.25,153.708,23.0562 8.3,148.54,8.9124 8.35,151.054,19.63702 8.4,153.85,16.9235 8.45,157.294,22.02116 8.5,158.885,9.5331 8.55,162.167,22.70338 8.6,165.507,18.20577 8.65,156.191,17.18101 8.7,145.237,7.26185 8.75,151.594,7.5797 8.8,147.153,22.07295 8.85,141.447,12.73023 8.9,143.715,11.4972 8.95,127.63,12.763 9,130.104,18.21456 9.05,130.851,14.39361 9.1,118.595,10.67355 9.15,130.604,9.14228 9.2,131.175,14.42925 9.25,118.46,10.6614 9.3,126.75,11.4075 9.35,126.365,15.1638 9.4,132.485,6.62425 9.45,126.401,17.69614 9.5,122.79,12.279 9.55,126.146,6.3073 9.6,133.005,14.63055 9.65,126.313,15.15756 9.7,124.658,12.4658 9.75,128.092,15.37104 9.8,129.795,9.08565 9.85,124.484,11.20356 9.9,126.61,15.1932 9.95,131.695,19.75425 10,127.967,10.23736 10.05,126.272,11.36448 10.1,134.518,12.10662 10.15,119.874,17.9811 10.2,124.126,16.13638 10.25,132.356,18.52984 10.3,130.05,6.5025 10.35,121.237,6.06185 10.4,120.844,14.50128 10.45,123.974,14.87688 10.5,122.742,7.36452 10.55,124.796,6.2398 10.6,135.243,20.28645 10.65,126.549,13.92039 10.7,117.422,14.09064 10.75,135.101,14.86111 10.8,134.725,20.20875 10.85,124.339,17.40746 10.9,121.157,10.90413 10.95,124.966,12.4966 11,119.67,15.5571 11.05,124.525,8.71675 11.1,118.806,15.44478 11.15,124.037,14.88444 11.2,116.881,7.01286 11.25,122.862,12.2862 11.3,120.684,16.89576 11.35,126.824,10.14592 11.4,137.45,12.3705 11.45,131.534,14.46874 11.5,123.983,13.63813 11.55,132.546,14.58006 11.6,134.337,6.71685 11.65,130.428,9.12996 11.7,137.611,6.88055 11.75,133.468,20.0202 11.8,129.303,9.05121 11.85,121.403,18.21045 11.9,134.409,20.16135 11.95,126.763,12.6763 12,130.066,9.10462 12.05,125.678,13.82458 12.1,120.724,6.0362 12.15,133.341,6.66705 12.2,118.668,14.24016 12.25,129.796,11.68164 12.3,120.248,16.83472 12.35,118.123,16.53722 12.4,131.801,11.86209 12.45,125.781,18.86715 12.5,118.983,13.08813 12.55,125.76,7.5456 12.6,118.283,16.55962 12.65,122.163,12.2163 12.7,114.645,10.31805 12.75,117.965,8.25755 12.8,132.209,11.89881 12.85,133.292,6.6646 12.9,130.209,11.71881 12.95,139.162,13.9162 13,128.423,19.26345 13.05,118.367,8.28569 13.1,125.668,13.82348 13.15,133.322,7.99932 13.2,114.769,10.32921 13.25,129.273,9.04911 13.3,129.894,18.18516 13.35,137.251,12.35259 13.4,150.487,22.57305 13.45,151.853,12.14824 13.5,174.944,10.49664 13.55,201.962,28.27468 13.6,237.979,14.27874 13.65,284.611,28.4611 13.7,358.771,17.93855 13.75,385.925,27.01475 13.8,415.682,33.25456 13.85,426.614,25.59684 13.9,463.492,32.44444 13.95,475.314,38.02512 14,438.313,30.68191 14.05,430.992,64.6488 14.1,399.599,23.97594 14.15,358.187,21.49122 14.2,337.351,43.85563 14.25,269.738,37.76332 14.3,215.848,30.21872 14.35,174.793,17.4793 14.4,162.602,9.75612 14.45,138.565,8.3139 14.5,151.972,18.23664 14.55,120.998,18.1497 14.6,129.249,15.50988 14.65,128.467,11.56203 14.7,120.479,7.22874 14.75,123.251,9.86008 14.8,129.125,19.36875 14.85,130.553,16.97189 14.9,126.714,8.86998 14.95,132.646,6.6323 15,128.372,16.68836 15.05,123.694,12.3694 15.1,125.085,6.25425 15.15,118.172,12.99892 15.2,130.737,15.68844 15.25,129.561,6.47805 15.3,121.835,12.1835 15.35,142.207,18.48691 15.4,119.999,7.19994 15.45,129.761,18.16654 15.5,121.199,18.17985 15.55,138.558,15.24138 15.6,133.687,14.70557 15.65,143.158,18.61054 15.7,168.679,15.18111 15.75,210.864,25.30368 15.8,240.63,31.2819 15.85,316.948,22.18636 15.9,401.51,48.1812 15.95,510.351,25.51755 16,575.553,57.5553 16.05,599.754,83.96556 16.1,629.712,62.9712 16.15,585.877,82.02278 16.2,522.757,67.95841 16.25,433.674,26.02044 16.3,333.33,19.9998 16.35,248.149,12.40745 16.4,193.047,17.37423 16.45,171.919,15.47271 16.5,145.249,8.71494 16.55,149.683,17.96196 16.6,130.978,19.6467 16.65,154.966,18.59592 16.7,151.103,13.59927 16.75,147.778,17.73336 16.8,139.722,9.78054 16.85,149.863,14.9863 16.9,154.948,23.2422 16.95,153.706,18.44472 17,152.32,18.2784 17.05,164.354,18.07894 17.1,162.43,22.7402 17.15,144.656,14.4656 17.2,153.821,18.45852 17.25,155.359,13.98231 17.3,139.634,16.75608 17.35,150.208,10.51456 17.4,149.206,13.42854 17.45,158.561,15.8561 17.5,179.514,14.36112 17.55,189.998,26.59972 17.6,225.865,31.6211 17.65,258.699,20.69592 17.7,301.535,33.16885 17.75,346.1,27.688 17.8,436.152,21.8076 17.85,563.963,84.59445 17.9,693.097,90.10261 17.95,795.983,39.79915 18,922.02,101.4222 18.05,986.19,49.3095 18.1,997.449,49.87245 18.15,913.216,109.58592 18.2,857.842,120.09788 18.25,704.079,63.36711 18.3,552.753,49.74777 18.35,450.754,40.56786 18.4,359.362,21.56172 18.45,308.906,18.53436 18.5,271.303,32.55636 18.55,259.971,31.19652 18.6,247.38,24.738 18.65,235.205,23.5205 18.7,233.156,34.9734 18.75,240.439,28.85268 18.8,219.655,21.9655 18.85,238.381,35.75715 18.9,242.358,21.81222 18.95,224.804,26.97648 19,217.139,21.7139 19.05,214.682,21.4682 19.1,234.321,11.71605 19.15,232.843,13.97058 19.2,239.377,19.15016 19.25,271.223,37.97122 19.3,296.601,32.62611 19.35,349.65,31.4685 19.4,414.915,37.34235 19.45,453.014,27.18084 19.5,475.948,38.07584 19.55,465.006,32.55042 19.6,436.328,21.8164 19.65,377.371,18.86855 19.7,302.985,15.14925 19.75,259.159,31.09908 19.8,214.726,32.2089 19.85,199.541,13.96787 19.9,191.483,21.06313 19.95,174.363,26.15445 20,183.943,9.19715 20.05,172.731,19.00041 20.1,180.382,16.23438 20.15,167.302,20.07624 20.2,186.818,26.15452 20.25,166.506,23.31084 20.3,176.664,22.96632 20.35,166.334,13.30672 20.4,161.125,16.1125 20.45,171.349,15.42141 20.5,173.675,24.3145 20.55,162.959,22.81426 20.6,180.984,18.0984 20.65,187.443,14.99544 20.7,199.199,15.93592 20.75,207.095,31.06425 20.8,225.995,18.0796 20.85,246.59,14.7954 20.9,285.148,42.7722 20.95,340.1,17.005 21,446.62,58.0606 21.05,582.385,87.35775 21.1,654.08,78.4896 21.15,729.274,72.9274 21.2,760.561,106.47854 21.25,725.147,36.25735 21.3,657.166,32.8583 21.35,562.369,44.98952 21.4,411.676,28.81732 21.45,317.024,47.5536 21.5,244.341,26.87751 21.55,195.207,13.66449 21.6,173.296,12.13072 21.65,155.771,9.34626 21.7,144.105,7.20525 21.75,139.791,19.57074 21.8,139.447,8.36682 21.85,148.986,22.3479 21.9,151.228,22.6842 21.95,155.93,21.8302 22,163.39,9.8034 22.05,160.719,16.0719 22.1,155.959,9.35754 22.15,154.821,12.38568 22.2,149.745,22.46175 22.25,149.557,16.45127 22.3,134.243,8.05458 22.35,133.744,6.6872 22.4,132.446,15.89352 22.45,125.265,7.5159 22.5,131.207,18.36898 22.55,133.317,18.66438 22.6,129.588,19.4382 22.65,131.296,18.38144 22.7,121.493,8.50451 22.75,121.23,7.2738 22.8,130.54,14.3594 22.85,123.753,14.85036 22.9,118.983,9.51864 22.95,122.956,14.75472 23,113.356,15.86984 23.05,116.166,13.93992 23.1,127.571,14.03281 23.15,125.147,15.01764 23.2,137.035,8.2221 23.25,155.434,13.98906 23.3,170.429,23.86006 23.35,180.516,21.66192 23.4,196.616,9.8308 23.45,211.396,10.5698 23.5,216.658,17.33264 23.55,237.929,28.55148 23.6,276.499,30.41489 23.65,291.107,43.66605 23.7,328.354,49.2531 23.75,333.171,36.64881 23.8,343.157,20.58942 23.85,330.592,19.83552 23.9,287.284,31.60124 23.95,262.081,28.82891 24,224.983,29.24779 24.05,232.686,20.94174 24.1,221.321,30.98494 24.15,239.779,14.38674 24.2,283.117,42.46755 24.25,272.335,16.3401 24.3,273.056,19.11392 24.35,252.636,20.21088 24.4,220.542,11.0271 24.45,172.207,22.38691 24.5,150.821,19.60673 24.55,133.023,15.96276 24.6,131.079,13.1079 24.65,125.341,7.52046 24.7,122.106,9.76848 24.75,122.052,14.64624 24.8,127.441,15.29292 24.85,115.91,8.1137 24.9,120.508,13.25588 24.95,124.163,16.14119 25,108.357,16.25355 25.05,114.624,8.02368 25.1,120.72,14.4864 25.15,122.091,6.10455 25.2,119.482,16.72748 25.25,129.144,11.62296 25.3,123.056,17.22784 25.35,126.572,17.72008 25.4,123.624,9.88992 25.45,115.467,17.32005 25.5,120.053,18.00795 25.55,118.137,9.45096 25.6,128.948,11.60532 25.65,130.204,6.5102 25.7,126.32,8.8424 25.75,128.999,19.34985 25.8,132.911,7.97466 25.85,130.626,9.14382 25.9,133.537,13.3537 25.95,133.16,14.6476 26,135.097,20.26455 26.05,123.364,8.63548 26.1,129.515,7.7709 26.15,121.09,10.8981 26.2,120.242,6.0121 26.25,123.316,13.56476 26.3,116.317,17.44755 26.35,114.714,12.61854 26.4,118.821,5.94105 26.45,111.891,8.95128 26.5,130.199,10.41592 26.55,121.559,10.94031 26.6,128.008,12.8008 26.65,134.657,8.07942 26.7,137.686,6.8843 26.75,154.145,20.03885 26.8,172.061,20.64732 26.85,208.748,25.04976 26.9,216.904,26.02848 26.95,233.256,23.3256 27,238.691,21.48219 27.05,231.06,27.7272 27.1,228.972,25.18692 27.15,246.491,32.04383 27.2,307.083,18.42498 27.25,367.255,25.70785 27.3,494.578,69.24092 27.35,583.502,40.84514 27.4,662.527,59.62743 27.45,683.387,102.50805 27.5,628.664,69.15304 27.55,527.825,42.226 27.6,412.596,41.2596 27.65,289.458,28.9458 27.7,222.51,28.9263 27.75,165.663,24.84945 27.8,146.087,8.76522 27.85,143.243,14.3243 27.9,147.558,17.70696 27.95,133.242,11.99178 28,135.915,9.51405 28.05,138.778,12.49002 28.1,153.454,23.0181 28.15,182.119,10.92714 28.2,231.315,34.69725 28.25,331.988,43.15844 28.3,485.443,38.83544 28.35,655.047,72.05517 28.4,747.839,104.69746 28.45,794.338,95.32056 28.5,768.941,38.44705 28.55,730.637,51.14459 28.6,606.509,42.45563 28.65,497.263,74.58945 28.7,365.608,18.2804 28.75,301.191,21.08337 28.8,284.499,36.98487 28.85,236.869,14.21214 28.9,235.612,18.84896 28.95,229.989,25.29879 29,217.086,19.53774 29.05,200.749,16.05992 29.1,172.124,22.37612 29.15,157.951,9.47706 29.2,143.448,7.1724 29.25,139.142,8.34852 29.3,129.961,14.29571 29.35,120.542,8.43794 29.4,123.203,9.85624 29.45,124.883,12.4883 29.5,121.38,8.4966 29.55,124.496,12.4496 29.6,116.452,15.13876 29.65,117.536,7.05216 29.7,105.712,6.34272 29.75,105.066,9.45594 29.8,110.455,9.94095 29.85,107.286,6.43716 29.9,107.302,12.87624 29.95,100.37,15.0555 30,104.262,11.46882 30.05,108.8,13.056 30.1,102.571,7.17997 30.15,107.745,11.85195 30.2,109.268,14.20484 30.25,112.579,12.38369 30.3,113.249,16.98735 30.35,121.137,12.1137 30.4,115.554,15.02202 30.45,118.863,14.26356 30.5,108.779,15.22906 30.55,122.623,18.39345 30.6,127.857,11.50713 30.65,175.396,8.7698 30.7,153.839,19.99907 30.75,177.213,24.80982 30.8,264.975,13.24875 30.85,403.475,32.278 30.9,603.393,48.27144 30.95,739.19,66.5271 31,868.527,69.48216 31.05,895.174,116.37262 31.1,871.207,113.25691 31.15,767.671,61.41368 31.2,580.394,81.25516 31.25,411.294,57.58116 31.3,254.655,30.5586 31.35,174.042,22.62546 31.4,141.004,8.46024 31.45,132.848,17.27024 31.5,143.299,18.62887 31.55,173.763,15.63867 31.6,222.379,24.46169 31.65,273.548,41.0322 31.7,336.13,36.9743 31.75,342.951,34.2951 31.8,368.917,36.8917 31.85,344.129,20.64774 31.9,301.892,33.20812 31.95,257.527,36.05378 32,210.377,27.34901 32.05,153.977,10.77839 32.1,120.768,14.49216 32.15,111.966,14.55558 32.2,98.0284,10.783124 32.25,110.733,12.18063 32.3,105.261,6.31566 32.35,115.513,10.39617 32.4,136.501,6.82505 32.45,133.028,18.62392 32.5,153.976,10.77832 32.55,158.283,18.99396 32.6,155.428,23.3142 32.65,166.281,9.97686 32.7,160.161,12.81288 32.75,138.813,18.04569 32.8,129.654,14.26194 32.85,107.903,14.02739 32.9,102.454,6.14724 32.95,94.5222,8.506998 33,92.0796,5.524776 33.05,100.767,5.03835 33.1,93.1643,11.179716 33.15,100.026,9.00234 33.2,97.5103,11.701236 33.25,92.3957,9.23957 33.3,100.681,13.08853 33.35,93.7026,12.181338 33.4,96.3929,8.675361 33.45,94.2689,4.713445 33.5,91.6066,11.908858 33.55,94.2608,5.655648 33.6,107.175,12.861 33.65,117.332,17.5998 33.7,137.671,20.65065 33.75,174.952,13.99616 33.8,207.309,24.87708 33.85,259.132,25.9132 33.9,300.681,33.07491 33.95,314.389,25.15112 34,329.562,32.9562 34.05,361.983,36.1983 34.1,371.593,44.59116 34.15,395.073,23.70438 34.2,391.143,27.38001 34.25,415.402,41.5402 34.3,393.297,35.39673 34.35,355.074,46.15962 34.4,304.059,33.44649 34.45,272.36,32.6832 34.5,225.305,11.26525 34.55,192.763,23.13156 34.6,152.001,13.68009 34.65,127.494,19.1241 34.7,118.867,11.8867 34.75,105.45,11.5995 34.8,94.9779,7.598232 34.85,101.963,14.27482 34.9,103.24,12.3888 34.95,95.7296,4.78648 35,108.992,11.98912 35.05,109.546,6.57276 35.1,102.401,14.33614 35.15,84.1487,8.41487 35.2,81.9302,8.19302 35.25,86.6041,5.196246 35.3,79.7155,6.37724 35.35,75.6335,8.319685 35.4,69.75,6.975 35.45,80.7793,9.693516 35.5,90.6558,9.06558 35.55,86.4237,12.963555 35.6,91.7114,10.088254 35.65,95.0993,11.411916 35.7,100.998,7.06986 35.75,106.753,7.47271 35.8,101.731,10.1731 35.85,97.5402,9.75402 35.9,91.5666,10.987992 35.95,76.9891,10.778474 36,87.4706,8.74706 36.05,74.9705,11.245575 36.1,80.418,4.0209 36.15,86.7154,9.538694 36.2,74.3031,5.201217 36.25,76.7863,5.375041 36.3,75.0255,6.752295 36.35,74.8802,3.74401 36.4,75.4023,11.310345 36.45,83.6758,9.204338 36.5,96.0594,8.645346 36.55,106.377,5.31885 36.6,111.861,10.06749 36.65,123.033,9.84264 36.7,122.995,15.98935 36.75,121.306,14.55672 36.8,104.512,6.27072 36.85,97.0437,8.733933 36.9,87.2972,7.856748 36.95,81.8107,5.726749 37,79.5026,7.155234 37.05,94.4856,5.669136 37.1,88.2035,7.938315 37.15,90.048,6.30336 37.2,96.6403,7.731224 37.25,95.5503,14.332545 37.3,98.1725,14.725875 37.35,109.631,6.57786 37.4,102.054,11.22594 37.45,87.1145,6.098015 37.5,93.8161,6.567127 37.55,82.8187,4.969122 37.6,86.4447,6.915576 37.65,91.6111,13.741665 37.7,89.3556,8.042004 37.75,96.8057,10.648627 37.8,100.424,14.05936 37.85,108.682,9.78138 37.9,119.003,7.14018 37.95,146.577,11.72616 38,169.89,22.0857 38.05,187.787,15.02296 38.1,222.617,17.80936 38.15,246.909,37.03635 38.2,280.136,42.0204 38.25,307.215,39.93795 38.3,355.565,17.77825 38.35,374.372,29.94976 38.4,396.038,31.68304 38.45,408.873,61.33095 38.5,405.034,40.5034 38.55,364.031,18.20155 38.6,301.051,36.12612 38.65,237.771,28.53252 38.7,205.057,16.40456 38.75,155.038,9.30228 38.8,125.081,6.25405 38.85,125.815,16.35595 38.9,111.783,5.58915 38.95,112.803,9.02424 39,113.984,10.25856 39.05,104.173,9.37557 39.1,98.8269,14.824035 39.15,91.0478,11.836214 39.2,83.3717,6.669736 39.25,94.2669,12.254697 39.3,82.0646,9.027106 39.35,81.5847,10.606011 39.4,87.714,10.52568 39.45,79.3031,3.965155 39.5,82.9163,9.949956 39.55,74.2941,8.172351 39.6,68.8073,10.321095 39.65,69.4004,10.41006 39.7,66.89,4.0134 39.75,71.0475,6.394275 39.8,82.086,11.49204 39.85,68.7372,5.498976 39.9,75.0326,5.252282 39.95,82.5109,6.600872 40,76.7223,11.508345 40.05,78.2051,11.730765 40.1,80.0078,10.401014 40.15,76.4652,9.175824 40.2,79.8017,7.98017 40.25,73.8954,11.08431 40.3,72.1662,10.82493 40.35,69.2964,3.46482 40.4,65.2579,4.568053 40.45,63.606,4.45242 40.5,57.1831,8.577465 40.55,67.7481,6.097329 40.6,69.2039,4.844273 40.65,62.4805,8.122465 40.7,64.8241,7.130651 40.75,60.5795,4.84636 40.8,65.8448,8.559824 40.85,65.8946,7.248406 40.9,71.5383,4.292298 40.95,63.9805,3.83883 41,65.4028,7.848336 41.05,63.0202,8.192626 41.1,70.1225,9.81715 41.15,62.9188,3.775128 41.2,64.7539,7.770468 41.25,68.1278,6.131502 41.3,62.0451,5.584059 41.35,65.7195,5.914755 41.4,63.7496,5.099968 41.45,64.7594,7.123534 41.5,60.5558,5.450022 41.55,58.1129,4.067903 41.6,62.644,8.14372 41.65,66.126,3.3063 41.7,65.2706,5.221648 41.75,63.4685,3.173425 41.8,64.0723,7.047953 41.85,69.7443,6.276987 41.9,73.3811,5.136677 41.95,65.2524,3.915144 42,74.9744,7.49744 42.05,75.0714,11.26071 42.1,73.2667,10.990005 42.15,70.2575,4.918025 42.2,84.4453,12.666795 42.25,104.773,7.33411 42.3,134.644,9.42508 42.35,167.51,13.4008 42.4,197.606,27.66484 42.45,210.274,12.61644 42.5,234.61,11.7305 42.55,231.426,18.51408 42.6,221.562,33.2343 42.65,184.363,20.27993 42.7,159.794,9.58764 42.75,119.036,15.47468 42.8,94.3749,6.606243 42.85,80.8279,5.657953 42.9,68.4195,4.789365 42.95,74.1841,10.385774 43,70.2024,5.616192 43.05,85.797,10.29564 43.1,98.0433,11.765196 43.15,119.394,17.9091 43.2,129.999,18.19986 43.25,165.56,11.5892 43.3,185.255,16.67295 43.35,193.943,19.3943 43.4,179.897,12.59279 43.45,154.986,17.04846 43.5,126.506,11.38554 43.55,97.8582,11.742984 43.6,87.7898,5.267388 43.65,78.8295,11.03613 43.7,72.6112,3.63056 43.75,75.0684,7.50684 43.8,89.6284,8.96284 43.85,114.142,9.13136 43.9,132.282,10.58256 43.95,147.952,16.27472 44,170.762,22.19906 44.05,161.345,17.74795 44.1,144.564,7.2282 44.15,130.813,17.00569 44.2,97.5477,13.656678 44.25,100.605,14.0847 44.3,75.5479,8.310269 44.35,73.0798,4.384788 44.4,80.4792,7.243128 44.45,84.5338,10.144056 44.5,79.7691,4.786146 44.55,83.8729,7.548561 44.6,74.8709,9.733217 44.65,83.7093,7.533837 44.7,86.2172,12.070408 44.75,74.4081,9.673053 44.8,76.6827,4.600962 44.85,60.377,4.22639 44.9,70.6135,7.767485 44.95,74.1899,7.41899 45,79.0239,4.741434 45.05,88.2986,6.180902 45.1,88.1026,9.691286 45.15,104.118,10.4118 45.2,124.869,8.74083 45.25,134.619,13.4619 45.3,128.425,16.69525 45.35,125.921,8.81447 45.4,116.881,5.84405 45.45,100.342,8.02736 45.5,87.9974,9.679714 45.55,69.9281,9.090653 45.6,69.3782,10.40673 45.65,66.9399,4.685793 45.7,69.0222,5.521776 45.75,65.1063,5.208504 45.8,71.9017,7.909187 45.85,72.9114,8.020254 45.9,62.4412,6.868532 45.95,62.2408,5.601672 46,61.0867,6.10867 46.05,67.6466,6.76466 46.1,64.9648,4.547536 46.15,65.5866,9.182124 46.2,67.5901,10.138515 46.25,68.2137,3.410685 46.3,93.9934,8.459406 46.35,102.448,15.3672 46.4,107.513,15.05182 46.45,111.667,5.58335 46.5,113.148,7.92036 46.55,103.159,14.44226 46.6,101.72,14.2408 46.65,81.0757,5.675299 46.7,85.1819,11.925466 46.75,80.0704,4.00352 46.8,78.4372,5.490604 46.85,77.6207,5.433449 46.9,94.1369,14.120535 46.95,97.5739,8.781651 47,110.717,16.60755 47.05,110.931,12.20241 47.1,122.583,6.12915 47.15,119.802,9.58416 47.2,115.705,9.2564 47.25,115.885,16.2239 47.3,103.366,6.20196 47.35,104.685,10.4685 47.4,87.1101,7.839909 47.45,81.3722,6.509776 47.5,74.6896,3.73448 47.55,82.8715,6.62972 47.6,81.4467,9.773604 47.65,84.6185,4.230925 47.7,97.0086,5.820516 47.75,106.457,8.51656 47.8,112.86,5.643 47.85,123.62,17.3068 47.9,107.603,5.38015 47.95,105.795,12.6954 48,96.57,5.7942 48.05,91.9926,5.519556 48.1,95.8746,13.422444 48.15,84.8921,10.187052 48.2,79.4172,7.147548 48.25,77.0807,11.562105 48.3,80.4581,12.068715 48.35,79.6738,10.357594 48.4,80.6699,9.680388 48.45,92.3809,13.857135 48.5,101.201,9.10809 48.55,126.071,18.91065 48.6,134.366,13.4366 48.65,146.469,14.6469 48.7,167.546,23.45644 48.75,181.118,9.0559 48.8,161.959,24.29385 48.85,163.343,22.86802 48.9,150.591,12.04728 48.95,130.337,9.12359 49,112.128,8.97024 49.05,99.6743,4.983715 49.1,85.1887,5.963209 49.15,76.8384,5.378688 49.2,64.1232,7.694784 49.25,69.2962,4.157772 49.3,62.5137,5.001096 49.35,62.827,9.42405 49.4,72.287,3.61435 49.45,65.4116,5.232928 49.5,79.7283,8.770113 49.55,97.1841,13.605774 49.6,129.899,15.58788 49.65,143.078,14.3078 49.7,172.328,8.6164 49.75,186.736,18.6736 49.8,184.968,25.89552 49.85,189.56,11.3736 49.9,181.587,21.79044 49.95,153.035,10.71245 50,137.935,9.65545 50.05,114.905,6.8943 50.1,95.7283,9.57283 50.15,79.9065,6.39252 50.2,74.597,5.22179 50.25,84.1548,8.41548 50.3,90.042,6.30294 50.35,87.4887,10.498644 50.4,98.7139,6.909973 50.45,99.0067,8.910603 50.5,86.9505,6.086535 50.55,87.7474,7.019792 50.6,85.9631,10.315572 50.65,80.4626,6.437008 50.7,71.6448,6.448032 50.75,68.9328,6.203952 50.8,73.0077,6.570693 50.85,77.8965,9.34758 50.9,81.1037,6.488296 50.95,95.3779,8.584011 51,111.735,14.52555 51.05,126.856,19.0284 51.1,138.096,13.8096 51.15,150.819,7.54095 51.2,154.439,21.62146 51.25,148.094,8.88564 51.3,136.172,6.8086 51.35,122.632,8.58424 51.4,100.177,11.01947 51.45,87.5869,9.634559 51.5,78.3764,6.270112 51.55,78.2191,4.693146 51.6,78.2709,10.957926 51.65,77.9636,8.575996 51.7,76.8107,9.985391 51.75,79.7183,7.97183 51.8,72.8587,6.557283 51.85,74.4016,10.416224 51.9,72.9933,8.759196 51.95,66.3762,5.973858 52,68.9021,6.89021 52.05,69.4564,4.167384 52.1,59.9374,6.593114 52.15,63.0054,3.780324 52.2,61.7298,8.024874 52.25,56.6701,7.367113 52.3,68.1494,10.22241 52.35,72.2003,10.108042 52.4,65.2643,8.484359 52.45,63.6699,9.550485 52.5,70.7034,9.191442 52.55,65.9846,6.59846 52.6,65.0781,9.110934 52.65,61.6054,8.008702 52.7,62.7069,6.27069 52.75,68.3216,8.198592 52.8,64.0696,5.125568 52.85,63.1407,6.945477 52.9,63.4841,7.618092 52.95,70.9688,10.64532 53,64.3216,3.859296 53.05,73.6743,5.157201 53.1,80.1206,4.807236 53.15,78.4602,10.199826 53.2,78.7641,4.725846 53.25,80.078,5.60546 53.3,73.1416,7.31416 53.35,72.4455,9.417915 53.4,66.7358,8.008296 53.45,60.9772,4.878176 53.5,55.981,5.5981 53.55,58.0423,4.643384 53.6,64.7429,5.826861 53.65,62.4937,8.749118 53.7,70.761,7.78371 53.75,83.0235,10.793055 53.8,83.5096,12.52644 53.85,85.7929,12.868935 53.9,75.5946,9.071352 53.95,82.0644,7.385796 54,69.741,10.46115 54.05,56.0518,6.726216 54.1,56.9974,2.84987 54.15,62.657,5.63913 54.2,61.1361,6.11361 54.25,62.0887,5.587983 54.3,76.3433,9.924629 54.35,82.6709,8.26709 54.4,87.0321,10.443852 54.45,86.4695,12.10573 54.5,91.7237,5.503422 54.55,81.1933,4.871598 54.6,76.4645,9.17574 54.65,74.3431,7.43431 54.7,64.7401,9.063614 54.75,59.1875,2.959375 54.8,63.3241,8.232133 54.85,59.1623,7.691099 54.9,61.9758,4.958064 ##END=,,0 Sigima-1.1.1/sigima/data/tests/curve_formats/pulse1.npy000066400000000000000000002736001514013333200230720ustar00rootroot00000000000000NUMPYv{'descr': 'sxЁhhn}hXۅ{hHAlyh*Twh>;uh_"shQҀ qhޡnhոlhjhZhht&fh]Gtdh!G&h[bhc02B`h>)^hJ\h*UYhma Whm.UhyOSh3pQhvz{OhcbMhLIKh=60IhGh6DhWBhFx@h>h˭7h 1JXhMVygbgmgygWfgNgۑ?5g{`g`dgMg6g' gi g&gGng0iUgrΩg._J嵧gqHVg1b'gnHkg7ziRgz텊9g֑ ggAg֔g{/gePgJNqg7rg Yg @gS'gg 8g,Yg\8z}gD{gjPyg#T\ywgf=h`ug&tHsg@/qg-aogo◂lgˣjghg6fgxdgp'bgYHh`g?CiO^g,6\gZgXgHUg&Sgͺ20Qg>QOgQJrMgvVoKg_bVIgIn=Gg[2z$Eg Cg8@g"Y>gdשzgP'gg0gQgY̻r gǓl gޞӴSg :gbq!gZ gC9f)-Zfk{f&f2f2>sfuJZfV BfbA)f;wnbf~`zfIf3fEff({f IbfNjIfً0fӓf}fWffO f81f"!Rf` -sf8ifDPf'P7fj\fhft9f1lZԼfsU{f>f'f:pf|Wf ?fA&fCb ffȈۧf r¥fL[穣fDf-')xf3J_fU?kFfJ-fVfbf_nfzʐfw1f&aRfhJsf3ffMf/4fqff9}f8Z{fz{yf} wffufAP!msf9-Uqf"9!.fmfVe@:eG)[e|e띙eePgeOeՠ"6e'CeYs3de\?eEKe /Wǹecceo ez*oe*ԆKVell=e$e e3yeubeKe42e<Se~tve]e DeE+e!eʕ-e 9;eNhE\ȸeQQ}e:]e$i}eX udeLeߌ"3eɘCeadee愼ϣe(nǶejW蝟e@ e)*le1KSesm:e!ee:'e}3֎e?etK3eD]WTeFcuse/oZe {AeM(e~eԞ{e;yeV\we}ueyΞsecڿzqe_Laoe5Ime"0ke& Diehefe!de-be/9ȳ`erE^eQ \eh]+iZe9RiLPXe{;um7Ve$Te ReBOeMeɰKe 3IeKTGeupEenWCeX>AeTA%?e* =e:e<8e]']6e3~4e?2e$Kw0egW^.etcF,e]o#-*e.G{D(ep0e%e#e!e7Ȱeyնe e+fe@LMezm4eceMeI6 e e" e-4eR9UeEvme׭QTe];e\i"diu dRd#<+ɭd(d3 |d?,cdHKMJdWn1d̢cdodQu{d^dGd14dZUdvjd—Qd!θ8dcddd*{<նdld ^dMd6"d3 .qdv :XdE@dQ$'d=]EdifduܡdßdFjɪdSꑛd< yd &,`dOMGdn.dԏddXdʊd݆dp5daYVdB(wgd+4Nd(@5~dkK|dWzdcwd2o=udt{^sdqduod;_nmd}HUkd1=id$$gdDE edfbd`d ^dMɧ\d Zd{ vXde"-]VdWN.NDTd7:o+Rd FPd RMd`]KdiIduGd'5EdiV}CdwdAdjK?d0T2=dr=;d&9d6d9=4d{^2d0d.dBk,dR*dp(:(d Z4%!&dLC@F$d,Lg!dXdcdUoʤd{dٺ sd-Zd^NAdvo(d_d%Iñ dg2 ddd.5dpVzd xadHc7"/cz|.ce:cNFcA8R>c!^_c jcucJ݁hcƍOcί7c%cSFckgcTɈc>թc\'ʡcc pc#.WceO>cp%c( c,4coq@cZLcCXc6-d6cxpWwc{x^c臙Ec?ғ,ccäccHw>ɲc`_cIۀc3~cQecLc 4c&c["Gc.hcߓ:Нc!}FcdfR˞cO^셗c8j mc+"v.Tcm O;cp"cݙ c4ǥcv׈ccc=l6cUWtc>x[~c(B|cF)zcxcuc (scP4?qc@`ocԈLmcrX{kcY[dbicDpIgc-|1ec &ccbG`ch^cҫ\c)Zck˛XcVcw jTc2a.QRctJO8Pc3pNc Lc;Ic~"Gc.Ec:CcEF7AcRXq?c}^yX=c gj?;cNPv&9c9 7c"4c 2cW?0cޱ`.cǽ,cɢx*c`_(cF&cl.$c'V&"ci?Hc(icc0(cs4̘c@cLgc:X/Nc|dP5crpq c\| cCEc.cc cL7cXnbѼyUbۚM( _bXI\bdjZbpXbG|Vb͏TbˊvRbt^PbP]0ENbFQ,Lb/rJbГGbYܴEbCbAb ?bc 9~=bZe;by#{L9b)c/37blL;5b5G3bS0b3_ .bujA,bvb*bÂ(b;a:r9aÌ[Y7av|@5aG_'3aH1a1 .a,aQ$"*a/C(a;d&aGy$aZS`"a_G a{k.a!ew acN*a7Ka la* al󲮙aܾπag a3O av26 aSajta*s`i'6Z`BA`M(`0Y `re+`qLޕ`}mœ`9`{q`Zz`Da`B-I`30`T` u`K`~`Фٳ|` z`Uwx``$]`8%[`7" Y`z +V`LT`mR`@P`N`řwL`^J`Jl*FH`U64-F`>BUD`(NvA`SZ?`e=`qٰ;`}9`\7`2w^fUt{s^mIo^pk^d:f^y7|b^ ;^^QZ^BV^Q^T,ǻM^&D I^[KXE^s&A^"<^p8^,CS4^ӕ_0^5-,^'^>\#^_2^G2Jf^b"5^Pyd^թ^Z| ^N*n^c!l<^ ]l] 3]uk8uu]=PC]h];]}] |]ZK]-C]]ȵ]& ](w>LR]IV ]1n]];T]Y]Df']8]M \ġ]]V,`]ۂD#/]_U\e]'tˌ]i陈]̣+h]rm6]qӯ|]{Dw]4s]voo] 2=k]J g]abf]V ]xxn]J,b]n0\\\4\gvi\:7\ -\!D=\\\*tp\V?\4)E \\=ɩ\ x\FsNF\E\O3\J\XbV\ݏzM\bb\4\k^\٠\tT\~ %#\}Q!g\$9\P덄\ h-\\o*|\nw\@s\5o\wck\'1g\b\0]'>^\/?Z\9WjV\n9R\CFN\yI\LLʣE\ rA\UN@=\9\^4\h-0\g;EWy,\ ]G(\qt$\\z_\W\*N\%\h \\t3\GK.V[cp$[#z[[-6[cx][66ں+[[? ?[ĭ![H9d[RQ3[R%iG[[[ʘ˝[ߜ l[doO:[A[mֲ[[v'Xs[?A[^W[1oޝ[`[ ֞z[H[{&[Mh[ [큀[)-/P|[Eqx[2j]s[ZʮZZYgZ5ZZZ"-4 ҙZKbZ+cnZ{ìZu|ZG0DxZ̓ stZPf"oZ8:kZZ R9}gZi{KcZc_Z炙ZZlUAVZ'ɃRZuRNZ!JZ~JEZr(AZD@΋=Z XZ9ZoR(5Z0Z,Za(Z3Za$Z(/ ZZ1!Z}.cZ:PFhZ"^6 ZDu)ZǍkZMYloYV?1>Ys Y_YYi4:wY[L|EYr.dY|Y{ӓBY~YxLY KYJY Y"υY:TYgRS"Y$:jY ׾Y.ߙY[[Y7ɝ)YVY@)!ƕYdYI(bYΠ@0YSsX*YEpl̀Y\|YixYe28tYtpYnbkY4gYw;qcY.}?_YF [Y^VYQvCRY$xNYFJYɽ FYKAY!n퍱=Y@9Y*N5Y4T1Y3L,Ydظ(Y=]|$Y/\U YF#YYO"YydYXL \ Y#*Yb:+YRmXkjXhcXt;32X uX}ɷXX;kX X~9X*)X@XXDXprXt@X'G XLݿX0ώXyX9HXcUXB6/XGٲXL^XЭv]OXUXRX^%#XeXgVX$Xqo,XA5n|XzMxXd]tX|4,pXvkX^gX1cXoxWtW)QpWA6 lW&YxgWZqcW/-_W>Y[W8Ҹ'WWRWAwNWIGJWJ`FW/.BWTG =Wؓ_O9W]fw5W8g1Wf 6-WݾW)Wo֙$W۠ WyUoW'`=W5 WMWe& Wr}hvWDDWV.V"pV}V+a KV3$7V5kV}?SVGP!V"VPVGVYZVl(Vc?*VBPŷVlYVqaVu0V[XV~.̢VܚViV a7VxVK0ӍVH'V_ipVw>V( }Vg/xV1:qtV ׳wpV:ElV8hVCzcVV6_VM)N~[Ve@MWVV}SV۠NV_sJVEHFVh݊TBV">Vr 9V$Q5V{b<1V4T[-Vl*)V ڃY$V VݔVQcV$a1VV$ V*(V.nBjjV@Z8U7rU0U@rUŊqUI]?U/8UR{UU\0xUyHAGUeL`UxUnUçIUwNUhU;URUU6UUN$UXfZU*~U!ގUϭ ]U*b+UtݤU3GljU )U=$kdU<2}UFTyUcl1tUO6spUklUX۳9hUݭ9dUa{_UR[Uk%sWU*BASUtBOUZJU}orFUBJzBUH>U :U5UR1U^-U1O)U1%U'H[ U`U0{x߈UM!WU9 c%U UBUǗ)ULjl^T<,TU7TN2T^ftT~eTgY3T+:Tp|TݾTzmTu C;TH% T=TT TlKtTBTeT7߳T# ST{T,ITT6T+\T&CT?ZTr"QTHdTpTQC軅T*TZlX}Tߺ&yTdtT_13pTm2IulTa_hTvx-dT;_T|}[TOWT!gST C5OTKTFTk7 BT >OLn>Tg<:T)~ 6T1T2T-TZƖu)T;-C%T!TE ]Tɤ%TNw=|TIU#KTWme TT`T哴+SifmRS8 Ss S4S|+vSCYSU['S (sS>:Nb:S ,06SGC1S˱[-SPsV)SVi%SY)7!SSc^SꠢSlspSE%? Su2g SIS~aRy-xRboFR 5RR5RwRMRQ R($8>ROR1g†RUR:nF#R@RCʿR RMN\Rъ*RV]&R/>ǫR_VWRmcRh1RyRrL_ΖR͡R{jR%9RhR i,ՁR;D}R\.ryRsp@uRqRlR$X6hR*xydR-G`R\R7?WRt2SR@GJÀORbOKRIyGGRξBRR˹>Rc :R\6OV6R$2Re-R )Rn8X%RRP]!Rw%h+RRʗ`RRod RB&3RhRQ&Q!>/lQ^Vq:Q*1nQQ3֝7QysQ<{ͻAQMQF ?QQO,zQӗDIQXj\HQICQV>Qpnͭ:Q_|6Qz2QJ2Q.Q)Q%Q|Y!QOQQ!-QD Q\bQ#t QkXQ,>('QjP5ӬPP?1`PZs.PH-3PJPQb9P֤z{gPZw5PIPdAPكPmnP =Pvf!J P89ټP QΧPhvPRDP PUP(PZ}P KPP)r'!PD?cP2WPnRP;)!Pk}PDayP3uPN1ZqPs(mPWhP}-dPY?`P݂܁a\PbU/XP' SPk#HOP;KPtShGPqk7CP}DP?P:Pԡ6P p2PX>.Pa *P3%P*!PAawP'YEP}qP0P'P"i P9~PLPC/PO~0hoO#` OȏpOmDOxOƷ}O\NO~O᦭SOK O O<)O;lŊObOˢyO"*&qO+*7iO4tZ/`O>pXOG7 POPc黩GOY@F?OcH6OlRxH.Ou&O~POATO6Y OfݍO0a*NNzicN%NTrNi8NzNqNXNBNrGN HNѓNN$71N-` V~N7uN@&(mNI+eNRp1\N\OdTNe~9LNn_CNwA:;N 2NN=Js*Nl"NRN=HNZN+߁N,[cMъMvkWMMtMeI,M y|MfM U؄M M7;M'Dg؛M0閕tM9MB3MK%"JzMU}UqM^"*iMgǴaMpl2XMzXPMC;GM[s?MC.7M.MJLg&M1MaTM9< M\MփuL( eLOLrmKLLuL b L>~L mZL)QL2 L;/LD@,̗LN[hLWL`/~Li#>vLsymL|J,weLy]Lh4TL ٸLLL=CLW8;LgE"3Lɾ*LFM["LLؐ&VL5V0 Lڅ^LiK$fKKoDo?KtK"wxK+^K4K>2NKGMbKP KY#Kb<Kl \KuPK~+zKЯ%2rKuߩiK.kaK>YKdn6PK @HK>?KSy7K,G/Kڝ\˲&KBOOKKW K1$KJ`J|z]J!hJ$J-k q3J79J@hylJIZJRǁJ[BJeI'ިJnV{JwJ8JPJ~J'EvJt'&nJqeJ/_]JTJ`38LJc4DJݪ@;JOm3JH +J!ͦ"J?QQCJ JY| J.J&bI0x?QI9ojIBžIKgr'IU I^-{`IgV]IpIy6IEҤIoIK I4{I٪DI~ zI# }rI9)jImiaI1SYI߷ȵPI\9HI((@IWB7ILa/I J&IΚI;S7I)E I2u[pI;* HDcHNtEHW4lH`c~HictHrH||THR"HQH *HAƠHcHH0@Ho8Hz"vHϦqnH*fHi.]H^3GUHLHY;DHa@ms@"fi@+ @4qI@=U,@F[z@P@YD@bX@k@u3J@~y-@}ʈ@"ٛf@ x@l8o@h(oC>K'>ZT`>e\>eҤ>wm >CuD>6~}r>ؕa>"P>'lT(@>:a/>L>_Jr >qѸ =0E=(~=rѷ=N=)=P b=l=v=/+f=*y GU=<D=N I3=aW%"=s.+=f6d=5><%G<ɄO<WH<]C`Yp+Y5P835c/<4u̎D4L=4`MUv4]4 f4>kn!4vZ|4)k4 Z4gJ4.G>94@w(4SE4ee4xĹ"3#$[3mʔ33B3K?3x3_3 *o3t$_30} ]N3C=3UR<,3g&3z.A 30Z7z2z?2H2xP%2XX^26a2iЕ27q 2 TzBt22˳{c2ER2W_rA2jћ&12|0_ 2=21N 1C1e |1lֵ11D+'1"`15x1G"Ig1Zl W1lEF1~g~51J!$1%*1ބ2)1(:b0rCC0K0T 0Qa\F0%d07m0I/u|0\y}*l0n=c[0 J0W90[)0뺧G050ps/ߓ/(pW/).Ɉ/NP;g/rĭE/xj$/ )/.5v.+d.P]#)Z|.u9Z.J>9._[.l"-B|--֚-RjYx-wo-ֿ\N-&,-S@ - O,0%,Tw,y N$ , 5{c,3EA,ljV_ , \Hg+2xC+Wň+|'+Bx+@ W+Կ}5+i~+4)9מ)^g(?&( (gg(a+t( K7[&d Hl:&fX&iP%ӎEz%"4%›%BKq%g?O%s-%n %՛{$/:S$ŧ$DX!7$iu2d$4CC$S!$بd#K"O<*"W_"&p !KY!p!֢v!;`!SZ?!d!(> M r N#  H(v ܉9yT qHJ2 *[] 2מZ2gY|4wfc4;]jX2'0ScXRuqϖU^L9@F!QJA>gr_;¸vEE5Z>;0#|"d(9l*Jkϲ$oI,-{U_'~Dcp4( V wNVGoܜ+ueJ@Ia-R9za=t0罷yn t*1 +iLjWSmN{c2h%h=9*#mN1ڤ J+$ {6 q̓yo 7 m ,Bȅ } S_wXy q !{lNlQf`y`5ZBBUZ T]OIG4D#c>f+;8>&3.v-/f'rL""h ; ~m kU ,9陭S>z{ҥλ+_ɽ^7>C}eB1qOd񾴄wRXKضƗ~RЪf꾡)MT}J4=fk侌O⾴7r\߾QD,۾@Do׾[">ӾMxξMžM"r\U2>({TD>Z4<>!+˙>͊>W ݵH> >8>A27A>|I+ >:`>Uv>>s >j1z9>,)>gVk5>@ B> `{N>rZ>!TZg>0-s>|8H9>UC¨>-MO<>Z> f0>iqf>|$>j'E>B>rOIx?!UJ?fZÁ?Ӏ` ??0f=?k(?q`?>wt#?|1Щ?]0?L??6hw<?%?[H?{ ?蹤\VU?Ti?a ?-ȵ ?wP5n ?' m ?rʤz ?߅̇ ?K5D ?L ?$ݾ ?C{?8?i*&?Qb?7M?Wi\? ?ćӠ?z_%?07h?o?M?S,,2? Hu?mc?uE?+>??$c?NA?|* K?S&?q+0B?'^?5zW?x?J;W?b5 ?9Ac?l?"F!?ɯ=-?LYp?Eplu?GRK?)9?hW|??Ԧ]?~F?@Vc8?-`T?i?p?cR?n?ό?dt?<<^?zv?T3?_3O(?kk?r?JϢ?7"4? w?ѐj?ZI?'.A?XJ?}0e?3Á ?ߡM?$?U^?3x ?a֍- ?< }N ?wYl"p ?[ ?NJ> ?: ?&_)Z ?_!?:v9!?j#[!?d|!?A!?ĭ!?);!?\j"?7W$"?]E"?.qsg"?4p`"?O"? >"?Zx4."?5u9#?P 0#?TR#?':s#?{p#?}#?Xk#?3?#?C$?†6=$?v^$?EeR$?zT$?V^Cn$?1 3$? 6K"%?硌(%? I%?y3k%?xP%?SQO%?.ӽ%? )k%?V&?4&?lzV&?vjw&?QD\Y1&?,H&?7M&? '&?ai'?_@'?tb'?O7&'?*gӠ'?.'?z걼'?+J (?Rm+(?qfM(?L*nn(?(1^(?sM(?m<(?+,(?E7)?ox H8)?JY)?%c{)?<)?`~)?̿ )?8*?mB)#*?HD*?#|sEf*?cӇ*?SHRa*?A*?+0}*?j +?FN/+?!o&Q+?r+?FB+?Sе+?^+?h֪+?Cz,?bY<,?͚x],?9g$,?W,?_F@,?f}5,?A$\-?U#&-?dxH-?,j-?ᓋ-?)!-?dpj-??ܫ=-?H.?.Y3.?p}T.?luv.?[.?ac4K.?2?s,,O2?`z$`2?NPq2?;N2?)] ޒ2?2?pk2?%?22?2?̑2?G!ه2?N3?b3?i)3?p:3?^DjK3?K1\3?9Al3?&&}3?Ǎ3?chM3? }3?Ωt3?ʄJl3?:ci3?[03?,S4?\J4?nnB%4?\:L64?I~1G4?74P)W4?$ h4?hy4?U2/4? 4?s4?w4?-J4?U4?4?~O՟4?l8f5?Y-!5?Gqy15?4'B5?"ݺS5?[Id5?Hu5?ׅ5?ش=5?jށe5? y,5?q5?h5?|Ba`5?iXH5?WO 6?DdCG6?2>-6? Є6d>6? %.+O6?;%_6?fp6?֧6?] G6?I6?Գ6?6?z5+b6?g)6?Ul6?BW ҷ7?0 ~7?NE)7? y :7?.J7?0[7?Ԛџal7?Pr(}7?7?7?rT~}7?w(uD7?eޕm 7?R6e7?@J\7?-xT`8?L'8? lC$8?!Z;58?2|F8?э*CW8?C<" h8?x8?}8?e _8?u&8?c_8?P8?>=z8?+AA8?8?_9?$Ɩ 9?Ľ]19?πe$B9?6R9?즤c9?Gyt9?X@9?s9?`)Φ9?Nzz9?;0kr\9?) j#9?a9?RMY9?Px :?߽H?:?s/@-:?)7=:?p/N:?'[_:?K"p:?pS:?^ :?Lmw:?9#5=:?':?v:?E:?Y:?ݰX ;?f;?®(;?:u9;?۱|[;?nk;?\|;?I`^X;?7;?$̟;?@w;?7nt;?f;;?ۣ"^;?YU?zI>?gzAo,>?U96=>?B90M>?0\(^>?o>? [R>??>?>?|>?2!m>?4>?b>?T>?x ԉ??eDP??Sv(??@,8??.&I??ǪlZ?? Nh3k?? {??乩??oJ??%O??ۋx??,p??Gg??um_k??Y+@?W| @?(#@?jC@?"@? +@?z{in3@?q9;@?h1 5D@?^څL@?UT@?LB{}_]@?CKe@?9u&n@?0Sv@?'l~@? P@?d]d@? -@?[{@?tި@?ϞSB@?*oϥ@?݅?K @?l@?;B@?–3@?:@?LQ@?!2^@?@?])%A? A?c!A?xn3OA?o&A?e$Ԕ/A?\z7A?St?A?J5EAHA?@PA?7YA?.F{kaA?%iA?Vs2rA?W'zA? jA? \A?gbA?h#A?9ZA?x A?QNA?.ͱA?zIA?JxA??AA??A?8A?PA?\0jA?-B?ua'1 B?lͣB?cB?Zrn["B?Q>*B?G("3B?>;B?5ޯCB?,9MLB?"PTB? ]B?JyweB?mB?q>vB?Zb~B?2iB?hB?k`̗B?ƣ/B?!tXB?|DB?PZB?2˽B?G!B?ÄB?CV?B?&KB?|6B?sTDzB?j.vB?a hC?Xe8&= C?NC?EC?tC?o_؛C?;C?%VC?C?ONfC?6 C?E-C?zC?qG=C?haWC?^15C?UXC?L,D?CD?:is$ID?0CD?'"D?zs*D?մ2D? 0:;D?U CD?%LD?@eTD?~\D?+eD?QgvmD?ˬ7uD?nV~D?b鹆D?eD?yဗD?sI]D?GD?)TD?D?xߊLrD?o:[D?e+D9D?\D?SK;D?JcD?Am3D?7\=*D?. +E?%ަ E?m"UE?~E? #O&E?~.E?6E?3F?E?䎐 GE?` PE?D1qXE?ɟ}`E?7iE?UtqE?ryE? ClbE?fŊE?c)E?ߌE?w[E?vTSE?l-%SE?cE?ZJ~E?Q>E?GfBEE?>6E?5O: E?,׵oE?#1E?`x6F?H)F?F?p aF?˹!F?&(*F?Z2F?*:F?7RCF?ƒKF?훃TF?Hl|\F?<{dF? CmF?YruF? ~F?~jnF?}jNюF?sb5F?j ݘF?a{YF?X֏_F?N1`QøF?E0&F?<IF?3BF?*@QF? qF?SB8F?{F? /F?cBG?' G?T G?t$mG?%G?*4.G?ą6G?e>G?;6^GG?OG?ց%XG?L`G?wyhG?HOqG?z]qyG?qG?hhzG?_nݒG?UY`AG?L$*ܤG?CWG?:kG?05OϼG?'k2G?;GG?F G? >]G?G?V}6$G?MG? .G?gNH?¾%H?H?x_y!H?/)H?.@2H?А:H? CH??qjKH?ASH?1\H?xPdH?owlH?f[uH?\aSo}H?S#"H?JfH?ArH?7͔^MH?.(eڰH?%5VH?wH?9MH? >H?vEH?IGH?=iH?H?Z40H?ҵH?Y,I?k)Z I?#I?!ʟ!I?|%I?j-I?2;L6I? >I? GI?vCvOI?m|WI?cL~=`I?ZThI?QuqI?H gyI?>emˁI?5^.I?,/eI?#vI?\YI?,ؼI?pT I?@ЃI?<LI?JI?CI?MI?ШR;uI?#I?^2K?LFK?CQ+OK?:K"WK?1_K?'zUhK?\pK?cryK? 4K?mjK?FK?"aK?}u K?EYqK?3ԳK?ˎP8K?̛K?DHK?WbK?'@K?U)K?7K? K?fi/TK?x9L?o 'L?fwڢ~L?\Ҫ L?S-{E)L?JK1L?A :L?8> pBL?.JL?%7SL?O][L?-cL? xalL?`tL?p(}L?o싅L?p?hL?RL?&_L?ɁL?܀W}L?7QL?!ODL?ʧL?HF L?nL?b>L?Y35L?v6L?mԱL?cj-`M?Zt M?Q E%'M?H{M?>$M?51Q-M?,5M?#V>M?B' |FM?NM?CWM?R_M?h hM?9wmpM?c xM?پn4M?ꗉM?tzfM?J^M?*^¢M?%M?UM?;M?\MPM?,ɳM?}LDM?tzM?j4M?OM?En+lN?<ɯN?3$#3N?*P N?! (N?5]1N?9N?둎$BN?Eb JN?2RN?O[N?V}cN?ױlN? tuytN?gD|N?m@N?裍N?xdN?ӅjN?.V\ΦN?&1N?SN?{?N?qK\N?hgǿN?_P8C#N?VN?L:N?CaMN?:y2N?1JO?'r*x O?O?(!?O? $O?[-O?8,i5O?=O?̌0FO?INO?ԤmVO?=[_O?Z|gO?!pO?sxO?kO?OkLO?! 篑O?|bO?vO?x2ZڪO?oa=O?f1RO?]CO?SIhO?JO?ATsA/O?8CO?. 9O?%eYO?0O?BVP?*P? P?%P?wCMWP?p P?nɺP?˛ P?dE%P?&lP)P?[TT-P?ׁ<1P?R$=5P? :P?I H>P?7vzBP?@e4FP?JP?6OP?}nASP?-f,sWP?HN[P?$v6_P?kdP?1):hP?^nklP? VpP?>ctP?&!yP?|2}P?AdP?soZP?ȉP?jʯP?+P?`%R]P?RhP?WPP?ҭ8P?N J$P? VP?E6ŇP?cكP?;AP?P?2쑽NP?z{P?)Gb9P?tJP? 2P?sGP?1yP?*P? XӬP?jP?(@P?qP? tP?v;\bP?hD P?m,8P?jQ?dYQ? Q?[LQ?y1Q?QQcQ?ԅQ?Hn Q?/V$Q??]>I*)Q?&\-Q?6ō1Q?5Q?,@9Q?@">Q?#nTBQ?zFQ?8JQ?gNQ?$PSQ?Q8rMWQ? 0[Q?_Q?cQ?zihQ?4'FlQ?pbwpQ?쏑tQ?gyaxQ?a }Q?^J>Q?E2pQ?UsYQ?РԍQ?LQ?Ғ7Q?B)PiQ?VQ?9̢Q?sQ?0[H0Q? DbQ?':,ēQ?gŷQ??Q?(Q?̻ZQ?yQ? K7Q?xQ?m!Q?}UqSQ?>/Q?t.&Q?[Q?khQ?&LQ?b}Q?Q?X?`Q?lQ?OgDR?OvR?F7X R?" R?=P R?}=R?3OoR? R?*$R?3)R?!ayG6-R?ah1R?IÙ5R?19R??=R?D.BR?r`FR?xJR?̺6NR?wRR?''WR?nUspY[R?[._R?eCcR?+gR?\ h lR?8%RpR?SftR?Γ̡xR?I_|R?R?@JR?Im|R?7wUWR?=R?.%R? CR?$-NuR?Z R?ئR? R?FgŸR?kOѻR?7>R?{4R?fR?r!wR?N5R?h|R?䩨-R?_אo_R?y-R?V2aR?_IR?M1g&R?Ⱥ%XR?DR?꠻R?:C^R?pS?1PS?ˊ S?(rVS?&[S?TCS?+IS?N{ S? $S? (S?7̇-S?eEB1S?~t5S?9S?ul=S?U= BS?lH=:FS?u%lJS?c wNS?4RS?YWS?+ư3[S?PYne_S?̆,cS?G~gS?fkS?>Of,pS?<7$^tS?5jxS?|S?+]S?%S?" VS?MS?{US?xS?`S?IOS?11MS?^ S?S?yS?DHS?ozS?AS?fo~ݿS?r<S?]Z@S?BrS?T%+vS?R4S?KS?ƭ9S?AmkS?+S?86S?cS?/le2S?T#dS?&T?!pT?wߡT?`U?JH[U?zx07 U?hU?qU?RU?g.U?[/ U?^a$U?ڶJ(U?Uq,U?Z0U?L?B(5U?l*BZ9U?B=U?AU?9{EU?"9!JU?0PRNU?}RU?'sVU?k1ZU?T_U?3OW?ӀW?5vW?_OW?+6G $W?c/G(W?"y,W?F0W?4W?9W?G@=W?t>rAW?EW?pIW?XxNW?y*A69RW?W)jVW?pZW?o^W?f-cW? 1gW?];ckW?hgoW?T%sW?jwW?KR*|W?;_\W?AL#W?y ۿW?8W?V#W?/UW?/҆W?&]W?|NW?d W?LMW?5W?@FW? nW?W?FW?|=xW?#W?sQW?~vw W?j^5?W?FpW?a/W?4oW?Wb,W?ӏ7W?NϨiW?fW?E$W?EW?qZ?患Z?5L@վZ?yZ?,8Z?ԆzjZ?"o8Z?/WZ?]?Z?'r1Z?0cZ?Z?Z?@iZ?m'*Z?y[Z?ȀZ?phaZ?#Q[?fQ9"[?~!T [?] Y[?[?T[?4’[?KbPM[?Ə#[?Bz̰'[?b+[?8KH0[?E3F4[?/sw8[?<[?&?@[? E[?)>I[?VypM[?7Q[?tU[? \Z[? Eq7^[?:-/ib[?|gf[?j[?shn[?&0s[?jaw[?J{[?ax`[?ܥn[?WV([??Z[?N.'X[?[[?E[?ߑ![?@\?&>D\?I\?,JM\?zZw|Q\?5U\?qY\?◱^\?hoCb\?=h-uf\?^kPj\?ژ8n\?U g s\?%f\?u&$B\?=s\?]?4]]?+ ]?+Y:]?l]?!U]?g]?P]?<83#]?j Me']? +]?/]?؆3]?D,8]?xM^<]?z@]?oy~D]?abUtY^?=2]^?5%a^? )f^?,k[j^?E)n^?"sr^?v^?Ζc"{^?~!T^?)g߅^?VO^?7[^?^?L^?y ~^?9R^?pg^?딨^?gE^?xJw^?]a^?JIڵ^?Tx1 ^?ϥB>^?Kp^?꽡^?B.{^?[9^?86^?h^?/rs^?[1^?&?C^?l+/^?ka^?(^?^?"̤^? Pb(^?} Z_?ދ_?|l _?UZ _?s3=!_?`%R_?j _?Q_?a"_?'_?XDK+_?qI}/_?N~3_?f7_?EN<_?'7AD@_?ž_`?۲x`?򦚑`?w y`?4 Xð`?67ܲ`?Mw`?ndk `?+{_&`?S?`?GX`?d;qq`?"/P`?#/`?`?[ `?1`?G`?^`?Ruh8`?GQ`?͢&j`?`?IЬ`?ô`?`?`??+}``?Aq?`?Xe1`?yoYI`?6Mb`?A{`?5`?o)y`?-X`?7`?`?f%`?$<)`?RB`?i֑[`?]pta?Oa?ح.a?Ħ a?Tۚa? a? a?w"a?J6kh;a?M_GTa?cS&ma?zGa?A;a?/÷a?#a?za?8 `"a??$a?4&a?q0L(a?/Ge*a?]к~,a?tę.a?hx0a?%W2a?㸠64a?ϔ6a?_9a?|,;a?qE=a?*e^?a?UAYpwAa?XMOCa?nA.Ea?5 Ga?L)Ia? Ka? Na?%Pa?Cg>Ra?FWTa?$%pVa?|;Xa?:RZa?hº\a?^a?s`a?0_ca?Î>ea?ڂ7ga?jvOia?'khka?_ma?5Soa?`LGxqa?c;Wsa?y/6ua?#wa?Wza? /|a?H~a?aa?Noza? Na?/-a?F ňa?E]݊a?ta?a?~(a?;gAa?|FZa?p%sa?tda?2Y㤛a?)M½a?@A֟a?kW5a?)n)_a?>!a?:a?bRa? ka?a?ᘝa?Y wa?$Vϴa?:5a?Qa?Pha? 2a?˕Ka?da?Fvo}a?jNa?^-a?S a?=Ga?4;a?K/a?vb#+a?4ygDa? F]a?$va?ma?+a?a?Рa?da?!/^ a?E=$a?\=a?[sUa?na?֠|a?pa?Qdwa?XVa?L5a?Aa?H)5a?@)5a?VNb?mgb??ob?Mb?,b?x b?6 b?b? b?o#.b?,:fGb?PE`b?g$yb?f~b?#vb?jb?^!b?\R#b?F^&b?;='(b?/@*b?S4#X,b?Kq.b?a 0b?x2b?Jv4b?U6b?ż48b?;b?A=b?8?b?QAb?z.jCb?7EnEb?[MGb?r|,Ib?pp Kb?.dMb?XOb?LRb?g@1Tb?%4fJVb?)EcXb?($|Zb?^?\b?V^b?l`b?bb?U~db?]gb?<*ib?޽Ckb?L[mb? tob?"qb?9sb?BPvub?gvUwb?}j4yb?{^ |b?9R"~b?F;b?:Tb?r.mb?0#nb?Mb?3 ,b?iJ ьb?'ab?wb?ۧb?`φ4b?eMb?ҷDfb?#b?Wb?ᰟb?-ɡb?D|b?M[p~b? rd]b?ɈX<-b?LFb?D@^b?4wb?(b?}b?;v¶b?'U۸b?>3b?tU b?2l%b?>b?ɯWb?kpb?(DZmb?ݥLb?+b?b b?"b?8vb?Ojb?Xf^7b?}RePb?ԓFDib?:#b?O.b? "b?b? b?F}b?3\b?I;0b?`Ib?=wab?zb?b?vb?3ҟub?Tb?3b?l|b?*-p(c?CdAc?ZXZc?cqLsc?!@mc?ߞ4L c?(+ c?Z c?c?c?!c?Q':c?>dSc?TClc?k"c?Hc?!c?ï#c?ƙ%c?>ݍ}(c?\*c? v;3,c?w!jL.c?58^d0c?NR}2c?eF4c?n|:6c?,.u8c?"T:c?3d?Q1Ad?GECd?97Ed?.PGd?"iId?>6Kd?L kMd?cIOd?wz(Qd?5Sd?Ud?Xd?n¤0Zd?+춃I\d?bb^d?A{`d?d0 bd?"Gdd?]{fd?tohd?[cjd?W{md?׸KZ)od??9Bqd?R3[sd?'sud?֌wd?*yd?IA{d?Xr}d?nQd?0 d?@"d?:d?ɼSd?yబld?6d? jd?$Id?o;(Вd?-Rud?hid?]d?fQ3d?$ELd?9bed?-A~d?]! d?d? ȧd?5d?TLd?czd?yY,d?8Ed?K^d?vd?ԪՏd?랴d?Ad?rھd?/{Qd?zFo0 d?8]c%d?sW=d?KVd?q?od?/3d?'jd?Id?h(d?&d?)d?@d?_W6d?nԂOd?ڄahd?@d?Ud?ɤd?ߘd?d?L d? $uzd?:iY/d?Q]8Hd?ChQad?Eyd?9Ւd?|-d?:!d?rd? Qe?s/e?1(e?4@e?KY e?jbΫr e?'yŠe?叶ie?He?`'e?Ԓe?e?{ e?Wo9e?/cRe?EWak!e?\K@#e?Ns?%e? 3'e?ɠ')e?+e?E.e?z0e?X22e?~7K4e?<)d6e??|8e?Vԕ:e?ume?q@e?PBe?kȌ/Ee?)߀+Ge?tCIe? i\Ke?b#]uMe? :QOe?PEiQe?g9HSe?Y~-'Ue?!We?ԫ Ze? #\e?P<^e? U`e?`nbe??de?F4fe?Khe?aje?xle?=oe?yqe?X5se?vz7Nue?4ngwe?cye?WԘ{e?m.K}e?+E?e?[3qe?r'Pe?d/e?".e?߶Fe?_e?[xe?߉e?he?(GÔe?Q?&ܖe?Ve?l e?&e?H?e?Xe?t`qe?h?e??\e? Qe?"Eԫe?x99e?6P-e?f!ye?}X8e?o 7Qe?-je?e?ӛe?fٲe?#Αe?pe?3Oe?\J.e?a 1e?wIe?be?Sz{e?ne?bhe?VGe?JK&e??e?-3e?D')e?A[Be?q[e?`te?z>e?8e?e?e?qǺe?. e?'x"e?>W;e?gU6Te?%lme?むe?tӞe?^he?\f?Ppf?DOf?U 9.f?"- 4 f?8!L f?Oef?Lf ~f? }f?Ǔgf?Ff?B%f?f?f?|,f?9E!f?2^#f?I_w%f?r`>'f?0wz)f?n+f?b-f?iV/f?'J 2f?>x%4f?2W>6f?`'6W8f?-p:f?Cf?Wq@f?Bf?ҞoDf?NGf?M-If? 7Kf?OMf?hOf?D'Qf?>Sf?TgUf?}ktFWf?;h%Yf?\[f?P^f?tD/`f?28Hbf?,adf? !_zff?k!>hf?)8 jf?Nlf?enf?b|pf?٘sf?ݩw(uf?VAwf?X׵5Zyf?s{f?}f?Ҥf?O2f? Izփf?_nof?vbNf?FV-!f?J :f?>Rf?2kf?=&f?f?gf?v,FϘf?3C$f?Yf?pf?m2f?*ǠKf?贻df?˯^}f?c=f?!f?ǭf?&f?Z=tf?Thf?j\w+f?PVDf?QD5]f?8vf?,f? ҧf?Hf? f? nf?7M f?>N,$f?d =f?{Uf?xnf?5f?󿩇f?֝ff?nEf?,$f?zf?1nf?eHb5f?#_VNf?uJgf?>^f?\2=f?&f?f?f?Sf?f?+v.f?BUGf?IY4`f?pyf?ņf?Ѫg?@g?ʗg?ng?yM g?7t,' g?%h @g?<\Xg?pSPqg?.jDg?8g?,fg?g Eg?%$g?g?!g?^ 8#g? Q%g?6~j'g?M])g?Td<+g?{-g?Б/g?1g?K3g? օ6g?yv18g?nUJ:g?Bb4cg?GJ@g?{^>ѭBg?9u2Dg?&Fg?nHg?rMKg?/,*Mg? COg?[Qg?itSg?&+ӧUg?AdžWg?XeYg?_oD[g?#]g?ۜ `g?"bg?V;dg?sTfg?g~mhg?\]jg?M%PDۜg?G2#g?]& g?t%g?O>g? Wg?ʸ}pg?\g?E;g?g?ӱg?~*g?m;g?ag?Ug?wIg?5>g?2!g?/&u:g?nFTSg?+]3lg?sh?h?e϶h?"ޮh?ҍ h?l h?[Kh?*3h?) Lh?@dh?RW}h?nh?̈́sh?gdh?I[Ch?O" h?C#h?7+%h?@ ,D'h?# ])h?:}v+h?yQ\-h?6h:/h?~1h?3h?p5h?-̶ 8h?$:h?t=h?$2o@h?4Bh?KDh?]byϹFh?ymHh?؏aJh?UlMh?TIKOh?=*6Qh?1 OSh?&gUh?KǀWh?/Yh?E[h?\c]h?AsB_h?!ah?dh?z.fh?8κGhh?䮝`jh?|ylh?q[nh?/):ph??rh?Vsth?hmgvh?&[yh?O'{h?Ct@}h?_7SYh?+2rh?h? h?V#ϼh?:Չh?Ph?gkh?L~J h? )9h?h@h@P( @P( @ɧǶ@#h$@h@#h$@B:< @h@ɧǶ@h@h@#h$@#h$@P( @h@h@#h$@ɧǶ@P( @h@P( @h@h@ɧǶ@h@B:< @#h$@P( @h@h@h@P( @#h$@h@P( @h@| @B:< @#h$@P( @P( @#h$@P( @/@h@P( @|b: @P( @#h$@ɧǶ@ɧǶ@h@h@ɧǶ@h@P( @#h$@B:< @ɧǶ@P( @P( @P( @h@#h$@h@h@P( @h@#h$@h@P( @ɧǶ@#h$@P( @ɧǶ@P( @#h$@/@h@h@#h$@B:< @P( @#h$@ɧǶ@|b: @P( @P( @P( @h@h@B:< @P( @B:< @B:< @ɧǶ@h@|b: @T^ Pz@P( @ɧǶ@#h$@#h$@B:< @#h$@P( @|b: @/@|b: @h@ɧǶ@#h$@P( @P( @P( @B:< @h@h@|b: @ɧǶ@#h$@P( @#h$@ɧǶ@h@ɧǶ@|b: @ɧǶ@ɧǶ@B:< @#h$@h@ɧǶ@#h$@P( @P( @h@h@#h$@|b: @ɧǶ@P( @P( @h@h@B:< @#h$@B:< @P( @ɧǶ@#h$@B:< @/@#h$@B:< @ɧǶ@h@|b: @P( @#h$@|b: @/@h@P( @h@P( @P( @/@P( @P( @#h$@#h$@h@#h$@B:< @h@ɧǶ@B:< @P( @P( @P( @h@ɧǶ@#h$@ɧǶ@#h$@|b: @h@h@P( @ɧǶ@h@P( @/@h@B:< @P( @ɧǶ@#h$@B:< @h@h@B:< @#h$@P( @#h$@#h$@B:< @h@h@/@P( @#h$@h@P( @ɧǶ@#h$@B:< @ɧǶ@B:< @P( @#h$@h@B:< @P( @ɧǶ@B:< @h@P( @P( @P( @h@h@ɧǶ@h@ɧǶ@h@P( @#h$@ɧǶ@#h$@|b: @/@| @h@ɧǶ@#h$@P( @#h$@B:< @B:< @P( @P( @h@ɧǶ@P( @h@#h$@|b: @P( @h@h@#h$@h@ɧǶ@P( @h@P( @#h$@h@h@h@#h$@h@h@ɧǶ@h@h@ɧǶ@P( @h@h@h@#h$@P( @#h$@P( @#h$@h@P( @h@B:< @B:< @h@P( @|b: @#h$@#h$@P( @ɧǶ@#h$@P( @P( @#h$@P( @#h$@h@h@h@P( @#h$@/@P( @#h$@#h$@h@B:< @B:< @P( @h@|b: @P( @h@#h$@P( @B:< @h@P( @B:< @h@#h$@h@#h$@#h$@B:< @#h$@h@h@ɧǶ@h@|b: @h@P( @h@ɧǶ@P( @B:< @h@h@|b: @#h$@B:< @P( @h@h@h@h@h@#h$@h@#h$@h@h@#h$@h@ɧǶ@h@P( @ɧǶ@#h$@P( @h@P( @|b: @#h$@#h$@B:< @ɧǶ@/@B:< @#h$@h@B:< @ɧǶ@P( @/@ɧǶ@ɧǶ@ɧǶ@/@B:< @P( @#h$@h@P( @#h$@#h$@h@#h$@#h$@h@ɧǶ@h@| @ɧǶ@#h$@B:< @h@ɧǶ@B:< @#h$@#h$@P( @h@#h$@P( @/@P( @P( @ɧǶ@B:< @#h$@h@h@ɧǶ@h@P( @P( @P( @B:< @h@h@h@#h$@#h$@#h$@#h$@/@B:< @h@ɧǶ@P( @#h$@h@h@P( @#h$@#h$@B:< @#h$@h@#h$@P( @#h$@#h$@ɧǶ@h@|b: @ɧǶ@#h$@P( @h@h@h@P( @ɧǶ@h@h@P( @B:< @#h$@#h$@#h$@ɧǶ@h@B:< @ɧǶ@#h$@h@/@h@| @/@h@P( @h@P( @P( @ɧǶ@#h$@B:< @ɧǶ@h@ɧǶ@/@P( @h@ɧǶ@h@#h$@h@B:< @P( @#h$@h@h@B:< @P( @h@#h$@P( @#h$@#h$@P( @P( @P( @B:< @h@ɧǶ@h@P( @#h$@B:< @P( @#h$@ɧǶ@#h$@h@P( @P( @h@#h$@h@h@h@h@ɧǶ@ɧǶ@B:< @#h$@|b: @P( @ɧǶ@P( @P( @#h$@h@P( @#h$@h@P( @h@#h$@P( @h@B:< @/@#h$@P( @h@#h$@B:< @B:< @h@B:< @B:< @h@P( @B:< @h@B:< @B:< @P( @#h$@B:< @#h$@h@B:< @ɧǶ@B:< @|b: @h@B:< @|b: @ɧǶ@P( @P( @ɧǶ@P( @P( @#h$@P( @h@ɧǶ@h@#h$@#h$@| @P( @#h$@h@ɧǶ@/@#h$@P( @h@P( @h@#h$@B:< @#h$@h@P( @#h$@h@h@B:< @/@h@B:< @h@h@P( @#h$@#h$@|b: @ɧǶ@B:< @h@#h$@P( @B:< @h@#h$@ɧǶ@#h$@B:< @|b: @/@h@h@h@#h$@B:< @/@h@P( @/@h@B:< @#h$@#h$@h@/@#h$@P( @#h$@P( @h@h@ɧǶ@/@h@#h$@P( @B:< @h@P( @h@P( @B:< @#h$@P( @h@ɧǶ@P( @h@#h$@P( @|b: @h@h@P( @/@#h$@B:< @#h$@h@P( @h@h@#h$@h@h@| @h@P( @P( @h@P( @P( @#h$@#h$@#h$@ɧǶ@ɧǶ@B:< @#h$@#h$@#h$@P( @P( @P( @h@P( @P( @#h$@h@h@ɧǶ@P( @B:< @#h$@ɧǶ@h@#h$@P( @|b: @h@P( @|b: @#h$@P( @h@h@B:< @B:< @ɧǶ@h@|b: @h@h@#h$@ɧǶ@#h$@P( @ɧǶ@h@B:< @/@P( @P( @#h$@h@P( @P( @h@| @h@h@ɧǶ@ɧǶ@P( @h@P( @h@B:< @/@h@P( @h@B:< @h@ɧǶ@h@P( @#h$@h@h@T^ Pz@ɧǶ@h@#h$@P( @h@h@P( @P( @#h$@h@P( @#h$@P( @P( @P( @B:< @h@ɧǶ@P( @h@P( @h@P( @/@h@h@#h$@h@P( @#h$@h@ɧǶ@ɧǶ@ɧǶ@#h$@ɧǶ@#h$@h@#h$@P( @h@#h$@P( @h@h@h@P( @#h$@P( @|b: @#h$@h@B:< @#h$@B:< @B:< @ɧǶ@#h$@B:< @h@h@h@/@h@h@h@P( @B:< @h@#h$@P( @#h$@#h$@P( @ɧǶ@B:< @P( @#h$@P( @P( @h@h@#h$@ɧǶ@h@B:< @#h$@B:< @/@ɧǶ@P( @ɧǶ@P( @P( @| @h@h@P( @ɧǶ@#h$@|b: @h@P( @| @#h$@P( @P( @ɧǶ@#h$@h@#h$@B:< @B:< @h@h@B:< @#h$@|b: @h@#h$@#h$@P( @ɧǶ@#h$@P( @ɧǶ@B:< @#h$@h@P( @B:< @P( @#h$@B:< @#h$@P( @h@ɧǶ@|b: @P( @h@P( @P( @#h$@| @h@#h$@h@#h$@h@#h$@h@h@P( @ɧǶ@P( @#h$@h@ɧǶ@ɧǶ@h@h@P( @#h$@ɧǶ@B:< @#h$@ɧǶ@P( @h@#h$@h@P( @h@P( @#h$@ɧǶ@P( @P( @h@/@h@ɧǶ@h@#h$@ɧǶ@h@/@/@h@B:< @h@B:< @|b: @h@P( @#h$@/@h@P( @#h$@P( @ɧǶ@#h$@h@h@ɧǶ@P( @P( @h@h@h@h@h@#h$@h@P( @B:< @ɧǶ@P( @P( @h@#h$@h@/@h@h@P( @P( @#h$@#h$@#h$@h@h@|b: @P( @#h$@B:< @P( @h@P( @|b: @/@P( @B:< @h@P( @#h$@#h$@#h$@P( @ɧǶ@h@B:< @P( @h@B:< @ɧǶ@P( @h@ɧǶ@P( @#h$@#h$@h@B:< @#h$@B:< @h@P( @#h$@#h$@ɧǶ@#h$@P( @h@ɧǶ@#h$@ɧǶ@P( @h@h@|b: @|b: @h@B:< @B:< @h@ɧǶ@h@B:< @B:< @h@#h$@B:< @P( @ɧǶ@ɧǶ@ɧǶ@h@#h$@#h$@B:< @h@P( @ɧǶ@ɧǶ@ɧǶ@#h$@#h$@#h$@h@#h$@B:< @ɧǶ@P( @P( @#h$@#h$@P( @#h$@h@B:< @#h$@B:< @#h$@ɧǶ@P( @h@#h$@#h$@h@h@P( @h@P( @h@P( @ɧǶ@ɧǶ@#h$@#h$@#h$@#h$@P( @ɧǶ@#h$@ɧǶ@P( @h@h@T^ Pz@B:< @ɧǶ@#h$@P( @ɧǶ@h@B:< @#h$@#h$@ɧǶ@#h$@P( @h@P( @P( @ɧǶ@/@P( @|b: @ɧǶ@B:< @/@h@P( @#h$@h@B:< @P( @#h$@h@B:< @P( @P( @|b: @T^ Pz@h@h@T^ Pz@#h$@P( @h@#h$@P( @h@#h$@|b: @h@#h$@#h$@#h$@#h$@B:< @ɧǶ@P( @P( @ɧǶ@h@B:< @h@#h$@P( @h@h@h@/@/@h@T^ Pz@ɧǶ@#h$@#h$@#h$@P( @P( @h@h@#h$@h@/@#h$@h@P( @#h$@h@P( @h@#h$@B:< @ɧǶ@P( @#h$@ɧǶ@#h$@P( @h@P( @T^ Pz@h@#h$@B:< @ɧǶ@#h$@h@#h$@P( @#h$@ɧǶ@ɧǶ@ɧǶ@#h$@#h$@#h$@#h$@h@#h$@ɧǶ@P( @h@#h$@h@#h$@h@B:< @h@P( @#h$@#h$@ɧǶ@#h$@B:< @h@ɧǶ@h@h@h@h@#h$@h@P( @/@ɧǶ@ɧǶ@h@#h$@P( @#h$@P( @#h$@#h$@h@h@ɧǶ@P( @B:< @#h$@#h$@ɧǶ@ɧǶ@P( @h@ɧǶ@P( @#h$@h@P( @B:< @#h$@ɧǶ@B:< @ɧǶ@B:< @#h$@/@#h$@h@#h$@ɧǶ@B:< @ɧǶ@#h$@h@#h$@#h$@h@ɧǶ@B:< @h@#h$@h@B:< @ɧǶ@P( @P( @P( @#h$@h@T^ Pz@P( @#h$@ɧǶ@|b: @P( @ɧǶ@B:< @h@#h$@h@P( @#h$@|b: @#h$@#h$@P( @#h$@ɧǶ@P( @T^ Pz@ɧǶ@B:< @h@P( @|b: @P( @h@/@P( @ɧǶ@P( @h@h@ɧǶ@h@ɧǶ@#h$@h@#h$@B:< @B:< @h@P( @P( @h@B:< @P( @h@#h$@ɧǶ@/@h@P( @T^ Pz@h@|b: @#h$@h@B:< @P( @B:< @h@h@h@h@h@P( @ɧǶ@/@#h$@h@/@#h$@P( @ɧǶ@#h$@h@ɧǶ@P( @/@P( @B:< @P( @h@/@P( @P( @#h$@h@#h$@B:< @B:< @#h$@B:< @#h$@h@ɧǶ@h@ɧǶ@h@h@h@#h$@h@h@h@P( @ɧǶ@P( @h@h@h@P( @ɧǶ@h@P( @h@#h$@h@#h$@h@h@#h$@h@P( @#h$@B:< @P( @/@#h$@P( @P( @#h$@h@ɧǶ@P( @B:< @ɧǶ@P( @h@B:< @B:< @#h$@h@h@P( @#h$@| @h@/@B:< @P( @ɧǶ@/@P( @#h$@h@h@h@h@|b: @h@P( @P( @#h$@P( @ɧǶ@ɧǶ@h@| @h@#h$@h@#h$@h@ɧǶ@h@B:< @B:< @#h$@B:< @h@ɧǶ@B:< @#h$@ɧǶ@h@h@/@h@P( @h@#h$@B:< @h@h@B:< @/@P( @ɧǶ@ɧǶ@h@P( @/@/@ɧǶ@ɧǶ@P( @h@#h$@P( @h@#h$@P( @#h$@#h$@#h$@P( @h@B:< @P( @h@h@P( @#h$@#h$@P( @P( @P( @P( @#h$@P( @#h$@h@P( @P( @h@#h$@|b: @#h$@P( @P( @P( @h@h@T^ Pz@h@P( @h@#h$@P( @P( @P( @P( @/@h@h@h@P( @h@h@B:< @B:< @#h$@B:< @B:< @h@#h$@P( @#h$@#h$@P( @ɧǶ@h@P( @h@#h$@P( @#h$@B:< @P( @ɧǶ@h@h@#h$@B:< @|b: @#h$@B:< @P( @ɧǶ@#h$@P( @/@P( @#h$@#h$@P( @B:< @#h$@P( @h@ɧǶ@P( @P( @h@h@h@#h$@#h$@h@h@ɧǶ@B:< @ɧǶ@|b: @B:< @ɧǶ@h@h@#h$@h@h@/@B:< @|b: @h@P( @B:< @h@h@h@#h$@#h$@h@B:< @|b: @h@ɧǶ@P( @h@ɧǶ@P( @h@#h$@#h$@B:< @#h$@P( @h@ɧǶ@h@B:< @h@#h$@P( @#h$@h@P( @#h$@#h$@P( @ɧǶ@|b: @B:< @ɧǶ@h@P( @h@h@|b: @#h$@B:< @B:< @ɧǶ@P( @B:< @ɧǶ@P( @P( @T^ Pz@#h$@P( @h@h@h@ɧǶ@h@#h$@#h$@P( @P( @B:< @P( @P( @h@#h$@h@#h$@#h$@P( @ɧǶ@P( @#h$@P( @h@|b: @ɧǶ@h@P( @#h$@#h$@B:< @P( @|b: @#h$@ɧǶ@#h$@ɧǶ@#h$@h@P( @h@h@#h$@#h$@P( @P( @#h$@#h$@P( @#h$@/@#h$@h@P( @h@h@#h$@B:< @h@h@h@h@#h$@h@h@ɧǶ@B:< @#h$@P( @B:< @h@P( @P( @ɧǶ@P( @ɧǶ@ɧǶ@h@B:< @#h$@P( @P( @#h$@B:< @B:< @#h$@|b: @P( @h@P( @h@h@h@#h$@#h$@P( @h@#h$@P( @P( @#h$@ɧǶ@#h$@#h$@ɧǶ@/@#h$@h@h@h@h@ɧǶ@#h$@h@h@#h$@h@h@ɧǶ@h@P( @ɧǶ@B:< @P( @h@#h$@B:< @#h$@h@P( @ɧǶ@P( @|b: @/@h@ɧǶ@#h$@P( @P( @h@P( @P( @#h$@P( @h@P( @P( @B:< @ɧǶ@P( @P( @#h$@#h$@P( @/@#h$@| @#h$@#h$@#h$@/@ɧǶ@h@ɧǶ@#h$@h@/@P( @P( @#h$@h@h@h@ɧǶ@B:< @h@B:< @P( @P( @B:< @h@#h$@h@h@#h$@P( @h@ɧǶ@h@h@P( @ɧǶ@P( @ɧǶ@h@#h$@h@B:< @P( @#h$@IM@h@ɧǶ@h@B:< @#h$@B:< @P( @ɧǶ@ɧǶ@h@h@B:< @h@h@P( @#h$@B:< @P( @h@ɧǶ@/@P( @#h$@h@P( @/@h@P( @#h$@P( @h@#h$@P( @|b: @ɧǶ@B:< @#h$@h@ɧǶ@P( @#h$@h@#h$@ɧǶ@#h$@B:< @P( @P( @B:< @B:< @h@h@/@h@h@/@B:< @| @ɧǶ@B:< @h@#h$@P( @B:< @h@h@P( @#h$@P( @|b: @h@h@B:< @#h$@ɧǶ@h@#h$@#h$@P( @#h$@h@h@#h$@ɧǶ@B:< @h@P( @P( @h@P( @B:< @h@B:< @P( @ɧǶ@h@B:< @h@P( @h@ɧǶ@P( @|b: @ɧǶ@h@B:< @#h$@B:< @P( @#h$@h@B:< @#h$@P( @B:< @#h$@h@h@h@B:< @#h$@#h$@P( @|b: @#h$@P( @P( @h@#h$@ɧǶ@/@B:< @|b: @ɧǶ@P( @IM@#h$@B:< @#h$@#h$@ɧǶ@P( @ɧǶ@/@h@#h$@h@P( @#h$@| @h@h@h@|b: @#h$@ɧǶ@|b: @P( @#h$@|b: @ɧǶ@h@h@/@h@h@#h$@ɧǶ@P( @ɧǶ@#h$@h@ɧǶ@#h$@B:< @/@B:< @P( @h@|b: @P( @h@h@| @ɧǶ@h@|b: @ɧǶ@h@#h$@T^ Pz@h@#h$@ɧǶ@h@P( @#h$@h@h@#h$@#h$@P( @/@#h$@#h$@h@h@h@h@|b: @h@h@#h$@|b: @#h$@h@h@#h$@#h$@h@ɧǶ@#h$@P( @#h$@P( @h@ɧǶ@h@h@#h$@h@|b: @#h$@P( @P( @#h$@ɧǶ@P( @ɧǶ@h@ɧǶ@#h$@ɧǶ@|b: @P( @|b: @B:< @#h$@P( @#h$@ɧǶ@|b: @ɧǶ@ɧǶ@#h$@B:< @h@B:< @h@P( @h@h@#h$@#h$@|b: @ɧǶ@#h$@#h$@#h$@P( @P( @h@B:< @B:< @#h$@P( @h@ɧǶ@P( @h@#h$@#h$@|b: @h@h@h@/@P( @P( @ɧǶ@P( @#h$@P( @P( @P( @ɧǶ@P( @h@#h$@h@B:< @#h$@h@#h$@#h$@#h$@B:< @h@B:< @B:< @#h$@h@h@ɧǶ@P( @ɧǶ@/@B:< @|b: @#h$@P( @P( @#h$@P( @ɧǶ@h@ɧǶ@h@ɧǶ@B:< @h@#h$@P( @|b: @ɧǶ@B:< @h@#h$@B:< @h@#h$@#h$@|b: @ɧǶ@B:< @B:< @h@P( @P( @#h$@P( @h@ɧǶ@B:< @#h$@ɧǶ@B:< @P( @#h$@ɧǶ@h@ɧǶ@P( @B:< @ɧǶ@P( @h@h@h@B:< @P( @| @h@#h$@ɧǶ@h@h@P( @h@#h$@h@h@#h$@#h$@B:< @h@#h$@P( @ɧǶ@P( @h@/@B:< @#h$@#h$@h@h@/@B:< @h@ɧǶ@P( @P( @h@B:< @B:< @T^ Pz@#h$@ɧǶ@#h$@h@h@T^ Pz@|b: @P( @P( @P( @P( @ɧǶ@B:< @h@#h$@#h$@|b: @/@P( @h@h@B:< @|b: @#h$@P( @B:< @#h$@h@#h$@h@B:< @#h$@h@P( @B:< @ɧǶ@| @h@#h$@B:< @P( @|b: @B:< @P( @h@h@|b: @#h$@P( @|b: @h@h@h@ɧǶ@P( @h@h@B:< @B:< @ɧǶ@B:< @h@#h$@B:< @B:< @h@h@h@P( @h@| @ɧǶ@h@#h$@ɧǶ@h@|b: @B:< @B:< @P( @#h$@B:< @| @h@#h$@P( @#h$@P( @B:< @#h$@/@h@ɧǶ@P( @B:< @#h$@h@B:< @h@B:< @B:< @h@P( @h@ɧǶ@B:< @P( @#h$@h@h@#h$@h@P( @ɧǶ@P( @P( @#h$@#h$@B:< @h@h@B:< @ɧǶ@P( @B:< @#h$@ɧǶ@P( @h@P( @h@h@B:< @|b: @#h$@B:< @B:< @h@P( @P( @/@P( @h@#h$@#h$@| @h@h@B:< @#h$@#h$@#h$@#h$@| @B:< @/@ɧǶ@h@h@P( @| @#h$@#h$@h@h@#h$@B:< @ɧǶ@h@B:< @ɧǶ@P( @P( @P( @P( @|b: @ɧǶ@P( @| @T^ Pz@h@h@#h$@B:< @P( @h@#h$@B:< @#h$@P( @ɧǶ@h@ɧǶ@B:< @ɧǶ@B:< @h@|b: @B:< @h@#h$@B:< @P( @#h$@P( @P( @h@P( @| @h@h@B:< @h@#h$@#h$@#h$@h@P( @#h$@P( @B:< @ɧǶ@P( @P( @h@#h$@P( @h@h@ɧǶ@P( @P( @P( @#h$@P( @| @#h$@B:< @h@#h$@#h$@P( @h@#h$@h@h@ɧǶ@ɧǶ@h@h@|b: @B:< @B:< @B:< @ɧǶ@#h$@#h$@h@P( @|b: @h@h@#h$@h@#h$@P( @/@h@B:< @h@#h$@B:< @#h$@P( @B:< @h@h@h@#h$@|b: @P( @ɧǶ@h@h@h@P( @|b: @#h$@P( @#h$@#h$@P( @P( @h@ɧǶ@P( @B:< @B:< @P( @ɧǶ@P( @h@P( @P( @B:< @B:< @h@#h$@h@B:< @|b: @h@P( @B:< @/@B:< @h@h@P( @B:< @#h$@P( @|b: @/@B:< @|b: @| @P( @h@P( @B:< @#h$@#h$@P( @P( @#h$@B:< @B:< @h@P( @h@h@P( @P( @P( @h@P( @h@B:< @| @#h$@B:< @B:< @B:< @|b: @|b: @#h$@ɧǶ@P( @h@| @B:< @h@| @B:< @ɧǶ@B:< @| @#h$@P( @P( @P( @P( @P( @ɧǶ@B:< @B:< @h@h@B:< @#h$@h@B:< @#h$@|b: @B:< @h@B:< @|b: @ɧǶ@#h$@|b: @P( @|b: @|b: @ɧǶ@h@P( @h@|b: @IM@B:< @P( @|b: @P( @h@B:< @/@B:< @P( @P( @h@h@h@P( @P( @h@h@#h$@ɧǶ@h@P( @#h$@h@P( @h@B:< @B:< @#h$@P( @h@#h$@ɧǶ@ɧǶ@ɧǶ@P( @B:< @ɧǶ@B:< @P( @#h$@P( @h@h@P( @|b: @ɧǶ@B:< @h@h@B:< @P( @h@B:< @#h$@#h$@P( @|b: @ɧǶ@B:< @P( @#h$@P( @h@ɧǶ@B:< @B:< @#h$@P( @P( @h@|b: @| @#h$@B:< @B:< @h@h@B:< @P( @B:< @B:< @#h$@P( @P( @h@B:< @P( @T^ Pz@ɧǶ@#h$@#h$@h@P( @ɧǶ@h@h@#h$@P( @B:< @h@|b: @|b: @h@|b: @|b: @h@B:< @^f(k@P( @B:< @B:< @h@h@|b: @#h$@h@ɧǶ@/@#h$@ 7?*? 7?T^ Pz@/@/@ 7? 7?/@h@/@ 7?ɧǶ@ɧǶ@P( @#h$@#h$@P( @B:< @h@P( @|b: @P( @| @| @#h$@B:< @#h$@#h$@h@B:< @ɧǶ@h@#h$@#h$@P( @#h$@h@#h$@ɧǶ@ɧǶ@P( @h@h@| @B:< @B:< @h@IM@IM@z/@z/@| @z/@IM@IM@|b: @^f(k@|b: @P( @|b: @B:< @| @P( @B:< @^f(k@| @P( @|b: @^f(k@|b: @|b: @z/@P( @| @| @|b: @^f(k@z/@|b: @^f(k@^f(k@| @z/@z/@IM@H5\@^f(k@^f(k@z/@/H@IM@}@H5\@z/@/H@Z'@/H@}@t)B@/H@t)B@t)B@z/@z/@/H@^f(k@^f(k@IM@^f(k@IM@z/@P( @IM@P( @B:< @h@h@/@ 7?-:Yj?*?*?-:Yj?(1?崧䜘?*?l7?l7?l7?mIF?l7?l7?mIF?l7?w*?w*?l7?-:Yj?-:Yj?T^ Pz@T^ Pz@/@P( @P( @B:< @H5\@}@U]@Uj@+@R\U=@-l!@:X0$@VI/'@V}b)@,@VF/@1%ed0@= 2@|~3@&6@e/~7@`TR'9@#G;@[B>|<@y;i=@~@?@[@@ A@[B>A@QkwB@H}mC@F_C@{D@D@z6>E@Oe@E@ gE@ gE@:F@c]FE@8mE@QE@k XE@z6>E@z6D@ec]D@{D@):C@O@a#C@V/ C@W/'_B@Y.B@XPA@46@@&†s@@~@?@_>@w;S=@[B>|<@4 <@N ^U;@)3`:@ͯ9@:t8@g?7@g?7@AH06@Gɫs X6@CsFZ6@%zr5@%zr5@x&15@+4@x&15@V-4@+4@+4@|~3@V-4@ްmQf;4@+4@g? 4@ްmQf;4@g? 4@ްmQf;4@aۢv3@aۢv3@Y2@= 2@hW!O2@Tt$(1@RI&Z1@3P>30@VF/@VF/@ e-@+@Nё\*@Nё\*@V}b)@ 3m)@>:u'@VI/'@6~$@#Ed&@> $@> $@ڊ"@E @qZ| !@"-@Mƴ@e/f@rL@U]@| @B:< @IM@T^ Pz@ 7?l7?`<`kF=D ^/؍Wc#PEJWc#P4@b$(~YQi$(~Wc#P$(~bhAJi{n/iVkF=Dt//>C5vӿC5vӿ28J^cmIF?oH?w*?w*?崧䜘?l7?*? 7? 7?T^ Pz@/@ɧǶ@P( @h@/@P( @B:< @h@P( @B:< @B:< @B:< @IM@IM@/H@H5\@IM@Z'@Z'@/H@}@rL@Z'@4`T@4`T@-@rL@e/f@-@-@]+@Uj@+@Mƴ@xZy@"-@E @"-@-l!@-l!@-l!@!@qZ| !@-l!@CB#@ڊ"@ڊ"@> $@GZ*oGX#@ڊ"@GZ*oGX#@CB#@CB#@CB#@ڊ"@ڊ"@ڊ"@ڊ"@ڊ"@GZ*oGX#@-l!@qZ| !@ea1"@!@E @qZ| !@!@qZ| !@҇. @-l!@҇. @qZ| !@҇. @E @E @qZ| !@qZ| !@R\U=@҇. @qZ| !@qZ| !@E @҇. @"-@E @-l!@E @qZ| !@qZ| !@E @-l!@qZ| !@-l!@!@҇. @-l!@qZ| !@qZ| !@!@-l!@҇. @-l!@!@!@҇. @҇. @҇. @҇. @E @qZ| !@"-@E @E @R\U=@E @҇. @ߦ?@E @ߦ?@"-@ߦ?@ߦ?@R\U=@xZy@ߦ?@Mƴ@"-@Mƴ@"-@ߦ?@ߦ?@ߦ?@R\U=@E @qZ| !@"-@"-@-l!@-l!@E @ߦ?@qZ| !@҇. @qZ| !@!@-l!@鷯"@-l!@҇. @ea1"@҇. @-l!@҇. @-l!@"-@-l!@E @E @"-@E @xZy@xZy@xZy@"-@"-@ߦ?@xZy@ߦ?@R\U=@xZy@Uj@+@xZy@]+@xZy@ߦ?@xZy@Uj@+@xZy@Uj@+@Uj@+@ߦ?@]+@Uj@+@]+@Mƴ@(@Uj@+@e/f@Uj@+@]+@-@-@-@e/f@4`T@Á,`@rL@-@rL@4`T@rL@rL@U]@4`T@rL@U]@t)B@Z'@U]@U]@U]@rL@t)B@}@Z'@z/@}@/H@z/@/H@^f(k@^f(k@/H@t)B@| @z/@z/@IM@H5\@H5\@IM@H5\@H5\@|b: @^f(k@IM@IM@^f(k@|b: @IM@IM@| @B:< @B:< @| @B:< @|b: @P( @h@B:< @P( @#h$@h@h@/@ɧǶ@/@ 7?/@/@ 7?(1?-:Yj?*? 7?(1?*?(1?(1?l7?-:Yj?(1?*?-:Yj?崧䜘?*?(1?(1?崧䜘?T^ Pz@崧䜘?*?*?(1?(1? 7?*?T^ Pz@-:Yj?*? 7?*?/@/@T^ Pz@T^ Pz@*?T^ Pz@#h$@T^ Pz@/@*?/@ 7? 7?T^ Pz@ 7?*?T^ Pz@-:Yj?*? 7? 7? 7?(1?*?T^ Pz@ 7?-:Yj?T^ Pz@-:Yj? 7?-:Yj? 7?-:Yj?*?崧䜘?-:Yj?T^ Pz@(1?*?-:Yj?/@*?#h$@ 7? 7?-:Yj?/@(1?*?-:Yj?T^ Pz@l7? 7?-:Yj?/@*?T^ Pz@*?l7?-:Yj?*? 7?-:Yj?T^ Pz@-:Yj?(1? 7? 7?T^ Pz@ɧǶ@*?/@ɧǶ@-:Yj?(1?/@(1?-:Yj? 7?-:Yj?T^ Pz@*?(1?-:Yj?(1?崧䜘?-:Yj? 7?(1?-:Yj?-:Yj?(1?(1?*?(1?T^ Pz@崧䜘?-:Yj? 7? 7?*?-:Yj?(1?-:Yj?-:Yj? 7?-:Yj?T^ Pz@-:Yj? 7?T^ Pz@ 7?(1?*?h@*?#h$@T^ Pz@T^ Pz@/@/@P( @h@h@T^ Pz@ 7?#h$@ɧǶ@ɧǶ@T^ Pz@T^ Pz@T^ Pz@/@T^ Pz@T^ Pz@/@T^ Pz@ɧǶ@T^ Pz@T^ Pz@/@(1? 7?#h$@ 7?-:Yj?#h$@ɧǶ@/@/@ɧǶ@ 7? 7?T^ Pz@T^ Pz@#h$@ 7? 7?#h$@ɧǶ@ 7?h@/@P( @#h$@ɧǶ@*?h@ɧǶ@ɧǶ@P( @#h$@ɧǶ@h@P( @ɧǶ@#h$@P( @#h$@h@B:< @#h$@#h$@#h$@ɧǶ@h@ɧǶ@B:< @P( @| @/@P( @h@h@B:< @P( @h@B:< @P( @B:< @B:< @|b: @P( @| @|b: @h@B:< @| @P( @| @| @|b: @| @IM@|b: @IM@| @IM@^f(k@| @|b: @|b: @| @IM@| @|b: @|b: @IM@B:< @| @^f(k@| @| @IM@|b: @P( @| @^f(k@P( @| @IM@h@IM@|b: @h@|b: @|b: @P( @|b: @^f(k@P( @| @IM@P( @B:< @B:< @B:< @B:< @| @B:< @| @P( @h@| @|b: @P( @| @IM@h@P( @| @P( @IM@IM@|b: @P( @|b: @B:< @| @| @B:< @IM@B:< @B:< @|b: @IM@#h$@|b: @|b: @h@B:< @IM@P( @P( @B:< @|b: @#h$@IM@P( @B:< @|b: @|b: @|b: @z/@h@B:< @P( @B:< @P( @|b: @P( @h@P( @h@B:< @^f(k@| @IM@P( @IM@B:< @^f(k@P( @|b: @|b: @|b: @| @IM@P( @|b: @|b: @h@B:< @P( @B:< @B:< @P( @h@P( @^f(k@B:< @| @P( @P( @IM@|b: @h@B:< @|b: @h@| @| @|b: @B:< @| @B:< @P( @|b: @|b: @| @| @P( @IM@P( @P( @| @P( @P( @h@IM@h@IM@IM@P( @IM@IM@h@|b: @|b: @B:< @| @B:< @h@| @IM@| @B:< @B:< @h@IM@|b: @h@P( @B:< @h@| @|b: @P( @B:< @IM@h@|b: @P( @h@B:< @B:< @h@P( @h@h@P( @P( @h@|b: @|b: @B:< @P( @| @#h$@B:< @P( @h@B:< @B:< @h@|b: @P( @#h$@P( @B:< @P( @h@|b: @#h$@P( @| @P( @|b: @B:< @P( @B:< @B:< @ɧǶ@B:< @B:< @h@B:< @|b: @ɧǶ@P( @P( @P( @h@B:< @#h$@h@|b: @ɧǶ@B:< @h@P( @P( @h@#h$@h@|b: @h@h@| @#h$@B:< @| @#h$@P( @|b: @h@P( @B:< @h@h@B:< @#h$@P( @h@ɧǶ@B:< @P( @/@P( @#h$@ɧǶ@h@h@#h$@B:< @P( @/@h@| @#h$@P( @P( @h@|b: @P( @#h$@#h$@#h$@#h$@P( @P( @h@h@|b: @B:< @P( @P( @P( @| @h@#h$@B:< @h@#h$@P( @|b: @#h$@h@| @#h$@P( @P( @#h$@h@B:< @h@P( @P( @ɧǶ@P( @#h$@h@B:< @h@h@B:< @| @P( @h@P( @#h$@P( @B:< @h@h@B:< @h@h@h@P( @B:< @P( @h@#h$@P( @ɧǶ@P( @P( @ɧǶ@B:< @P( @T^ Pz@B:< @#h$@ɧǶ@h@P( @h@h@|b: @h@h@P( @h@P( @#h$@ɧǶ@B:< @P( @#h$@|b: @h@h@P( @P( @h@h@B:< @h@B:< @| @h@#h$@#h$@#h$@#h$@B:< @#h$@P( @P( @#h$@#h$@#h$@ɧǶ@#h$@B:< @ɧǶ@ɧǶ@B:< @h@P( @P( @#h$@|b: @h@#h$@P( @P( @ɧǶ@P( @#h$@ɧǶ@h@P( @h@P( @h@/@P( @|b: @#h$@B:< @|b: @#h$@P( @#h$@h@#h$@P( @h@#h$@B:< @P( @P( @P( @h@h@B:< @h@P( @P( @P( @h@h@h@B:< @B:< @h@P( @P( @h@h@P( @h@B:< @| @P( @P( @ɧǶ@P( @P( @|b: @#h$@|b: @B:< @h@P( @B:< @P( @|b: @h@h@B:< @B:< @B:< @P( @P( @h@h@|b: @h@B:< @P( @#h$@B:< @h@B:< @|b: @P( @h@P( @B:< @B:< @B:< @h@B:< @P( @P( @h@| @h@B:< @|b: @| @P( @P( @|b: @P( @|b: @B:< @h@B:< @P( @P( @P( @B:< @#h$@P( @h@h@P( @h@|b: @B:< @P( @h@B:< @B:< @B:< @P( @| @h@B:< @|b: @h@B:< @B:< @h@h@h@P( @P( @B:< @B:< @B:< @IM@P( @h@P( @/@P( @B:< @P( @|b: @|b: @h@P( @h@P( @h@B:< @ɧǶ@h@h@#h$@P( @P( @h@B:< @B:< @h@B:< @h@B:< @ɧǶ@B:< @P( @B:< @P( @h@P( @|b: @#h$@|b: @|b: @h@P( @h@h@B:< @B:< @h@#h$@P( @h@P( @|b: @#h$@P( @B:< @h@/@P( @P( @h@P( @#h$@P( @h@h@|b: @B:< @P( @ɧǶ@|b: @P( @B:< @P( @#h$@h@P( @P( @P( @B:< @#h$@P( @h@#h$@h@B:< @h@h@|b: @/@B:< @P( @#h$@P( @B:< @B:< @B:< @P( @h@|b: @P( @P( @P( @|b: @#h$@P( @P( @h@#h$@h@/@P( @P( @h@B:< @B:< @/@P( @B:< @P( @ɧǶ@P( @#h$@P( @#h$@h@ɧǶ@B:< @h@B:< @P( @P( @h@| @P( @B:< @B:< @ɧǶ@B:< @B:< @h@#h$@B:< @#h$@P( @h@h@P( @|b: @h@|b: @P( @#h$@| @|b: @P( @P( @h@#h$@h@| @ɧǶ@P( @B:< @#h$@|b: @|b: @h@B:< @B:< @h@|b: @P( @B:< @#h$@B:< @#h$@|b: @P( @P( @B:< @|b: @/@|b: @|b: @#h$@B:< @B:< @#h$@P( @P( @#h$@P( @P( @P( @B:< @#h$@/@#h$@B:< @ɧǶ@IM@#h$@/@P( @h@h@#h$@|b: @ɧǶ@#h$@|b: @h@P( @h@P( @#h$@#h$@h@B:< @P( @h@P( @P( @#h$@h@h@#h$@|b: @|b: @h@P( @h@ɧǶ@|b: @|b: @B:< @h@h@h@P( @P( @ɧǶ@h@P( @#h$@P( @P( @h@P( @|b: @#h$@B:< @h@h@P( @h@h@P( @|b: @P( @P( @P( @P( @|b: @|b: @#h$@P( @| @P( @B:< @|b: @h@|b: @P( @h@P( @P( @#h$@B:< @P( @P( @B:< @|b: @/@P( @B:< @h@P( @h@#h$@#h$@|b: @#h$@B:< @B:< @#h$@|b: @P( @ɧǶ@P( @|b: @h@h@ɧǶ@P( @P( @B:< @ɧǶ@P( @B:< @h@B:< @|b: @#h$@P( @B:< @ɧǶ@P( @h@ɧǶ@P( @h@h@P( @P( @h@P( @#h$@h@P( @P( @h@|b: @P( @h@#h$@h@P( @B:< @|b: @h@h@|b: @B:< @|b: @|b: @#h$@B:< @| @P( @B:< @P( @#h$@h@P( @ɧǶ@P( @ɧǶ@h@B:< @|b: @P( @|b: @B:< @h@#h$@|b: @#h$@|b: @| @h@h@B:< @#h$@|b: @P( @h@P( @P( @h@P( @B:< @h@B:< @B:< @h@|b: @h@h@P( @h@ɧǶ@P( @B:< @h@B:< @P( @P( @P( @B:< @#h$@P( @|b: @#h$@|b: @B:< @#h$@|b: @B:< @h@P( @P( @h@B:< @|b: @h@P( @P( @IM@P( @|b: @h@|b: @P( @h@#h$@|b: @ɧǶ@B:< @|b: @h@P( @P( @#h$@B:< @| @P( @P( @|b: @h@#h$@P( @P( @h@B:< @h@B:< @#h$@P( @h@|b: @h@h@P( @ɧǶ@h@|b: @P( @P( @|b: @P( @P( @h@h@P( @B:< @P( @B:< @|b: @P( @B:< @h@#h$@P( @|b: @#h$@B:< @B:< @h@#h$@|b: @#h$@P( @h@P( @| @|b: @h@h@h@#h$@h@P( @#h$@P( @h@P( @B:< @|b: @#h$@P( @B:< @#h$@P( @| @h@B:< @h@#h$@B:< @P( @#h$@B:< @|b: @P( @B:< @IM@h@|b: @|b: @h@h@h@h@h@B:< @#h$@P( @P( @B:< @P( @B:< @h@P( @P( @h@h@P( @#h$@B:< @|b: @h@B:< @h@#h$@ɧǶ@B:< @h@B:< @|b: @B:< @B:< @#h$@h@B:< @|b: @B:< @B:< @h@h@P( @h@#h$@#h$@P( @h@P( @|b: @h@B:< @#h$@h@P( @B:< @#h$@B:< @h@#h$@h@P( @h@B:< @B:< @#h$@| @B:< @P( @h@P( @/@P( @P( @h@#h$@P( @h@h@P( @P( @#h$@h@/@P( @h@#h$@B:< @h@/@B:< @|b: @B:< @| @h@#h$@P( @h@B:< @P( @B:< @h@B:< @B:< @#h$@h@h@#h$@B:< @h@#h$@B:< @B:< @h@P( @B:< @/@P( @B:< @h@| @P( @h@B:< @B:< @#h$@h@P( @h@B:< @P( @P( @h@h@#h$@h@B:< @P( @P( @P( @ɧǶ@P( @h@P( @h@h@h@P( @IM@P( @P( @B:< @ɧǶ@#h$@#h$@T^ Pz@P( @P( @#h$@B:< @B:< @#h$@P( @P( @h@P( @|b: @h@P( @P( @#h$@B:< @h@#h$@B:< @B:< @h@B:< @P( @h@P( @ɧǶ@h@P( @h@#h$@h@B:< @h@P( @P( @h@B:< @|b: @h@B:< @h@#h$@P( @h@ɧǶ@h@P( @#h$@h@|b: @P( @P( @|b: @h@h@P( @#h$@P( @B:< @#h$@h@B:< @h@#h$@P( @h@B:< @| @P( @|b: @P( @P( @P( @B:< @#h$@/@h@h@h@h@h@B:< @B:< @/@P( @|b: @#h$@|b: @h@h@h@B:< @h@#h$@B:< @h@| @| @P( @| @B:< @P( @P( @P( @h@h@B:< @#h$@B:< @B:< @#h$@P( @#h$@B:< @B:< @B:< @#h$@B:< @P( @h@| @|b: @#h$@h@B:< @h@P( @B:< @h@h@B:< @#h$@P( @#h$@#h$@P( @B:< @#h$@| @B:< @#h$@P( @P( @h@h@P( @ɧǶ@P( @| @h@B:< @|b: @P( @P( @h@ɧǶ@P( @P( @#h$@h@| @B:< @P( @P( @h@B:< @B:< @h@P( @h@#h$@B:< @B:< @h@|b: @P( @#h$@B:< @| @h@h@B:< @P( @|b: @h@h@B:< @h@#h$@P( @B:< @P( @| @P( @h@P( @B:< @h@B:< @B:< @P( @P( @B:< @#h$@#h$@h@h@#h$@h@#h$@#h$@|b: @h@h@h@#h$@P( @B:< @#h$@P( @P( @P( @P( @P( @P( @h@#h$@P( @P( @#h$@#h$@h@P( @h@IM@h@ɧǶ@P( @B:< @h@B:< @h@h@B:< @P( @P( @P( @P( @h@h@h@#h$@P( @ɧǶ@h@B:< @|b: @T^ Pz@P( @h@#h$@B:< @B:< @h@#h$@B:< @#h$@#h$@|b: @B:< @h@P( @h@P( @B:< @h@P( @P( @h@P( @P( @#h$@P( @B:< @P( @h@P( @ɧǶ@P( @h@h@|b: @|b: @h@P( @|b: @h@B:< @|b: @ɧǶ@P( @h@#h$@P( @P( @B:< @B:< @B:< @P( @P( @h@/@P( @h@h@P( @h@#h$@P( @P( @P( @#h$@|b: @h@P( @P( @P( @B:< @h@h@B:< @h@h@P( @h@h@h@B:< @B:< @B:< @#h$@h@|b: @| @P( @h@|b: @#h$@#h$@|b: @h@P( @B:< @ɧǶ@#h$@h@ɧǶ@#h$@h@h@P( @h@ɧǶ@B:< @P( @h@#h$@h@ɧǶ@P( @ɧǶ@ɧǶ@P( @| @#h$@B:< @B:< @ɧǶ@B:< @P( @ɧǶ@P( @P( @h@B:< @#h$@#h$@B:< @h@B:< @P( @P( @h@B:< @|b: @h@|b: @B:< @#h$@B:< @h@h@P( @|b: @P( @B:< @h@P( @P( @h@#h$@P( @#h$@B:< @#h$@|b: @#h$@B:< @B:< @h@B:< @|b: @P( @P( @|b: @B:< @| @|b: @B:< @h@P( @#h$@B:< @P( @h@P( @P( @#h$@B:< @|b: @#h$@P( @P( @#h$@B:< @B:< @#h$@P( @B:< @h@B:< @P( @#h$@P( @P( @#h$@#h$@h@ɧǶ@B:< @P( @ɧǶ@B:< @P( @#h$@B:< @B:< @#h$@#h$@P( @#h$@h@P( @#h$@h@#h$@ɧǶ@B:< @P( @ɧǶ@B:< @B:< @#h$@B:< @|b: @#h$@B:< @#h$@ɧǶ@h@B:< @#h$@h@B:< @h@B:< @|b: @P( @B:< @B:< @h@#h$@h@#h$@B:< @P( @h@P( @B:< @P( @P( @ɧǶ@B:< @h@|b: @h@B:< @|b: @P( @P( @|b: @P( @P( @#h$@P( @h@B:< @P( @B:< @B:< @h@|b: @P( @P( @P( @|b: @h@|b: @| @#h$@#h$@h@/@| @B:< @h@P( @P( @#h$@P( @|b: @h@P( @|b: @#h$@P( @h@P( @P( @h@#h$@#h$@P( @P( @h@h@h@P( @P( @h@P( @h@#h$@B:< @P( @h@B:< @P( @h@P( @|b: @ɧǶ@#h$@B:< @h@P( @B:< @h@h@h@h@#h$@h@P( @h@P( @|b: @|b: @#h$@h@#h$@h@P( @P( @B:< @ɧǶ@h@P( @h@#h$@B:< @h@B:< @B:< @#h$@h@h@h@h@|b: @#h$@h@|b: @h@P( @B:< @P( @P( @B:< @#h$@h@h@#h$@h@P( @ɧǶ@P( @|b: @P( @B:< @h@P( @B:< @h@h@B:< @P( @h@P( @|b: @P( @P( @P( @#h$@P( @P( @ɧǶ@B:< @B:< @#h$@h@h@h@B:< @P( @#h$@B:< @P( @/@P( @B:< @#h$@h@B:< @ɧǶ@h@B:< @P( @B:< @P( @P( @#h$@P( @#h$@P( @P( @/@P( @h@P( @|b: @P( @#h$@#h$@B:< @h@B:< @| @h@P( @B:< @h@h@P( @#h$@P( @B:< @#h$@P( @h@#h$@B:< @#h$@h@P( @B:< @#h$@P( @P( @/@h@B:< @ 7?P( @P( @#h$@ɧǶ@P( @#h$@B:< @B:< @h@P( @|b: @P( @#h$@P( @#h$@#h$@|b: @#h$@#h$@B:< @h@P( @B:< @#h$@B:< @h@ɧǶ@P( @B:< @#h$@ɧǶ@|b: @B:< @h@h@ɧǶ@P( @B:< @h@ɧǶ@B:< @#h$@B:< @P( @ɧǶ@h@B:< @#h$@h@|b: @ɧǶ@|b: @B:< @ɧǶ@#h$@P( @P( @P( @h@h@#h$@P( @h@h@h@#h$@P( @h@P( @B:< @P( @h@P( @P( @h@B:< @B:< @h@#h$@B:< @B:< @|b: @|b: @h@h@P( @ɧǶ@B:< @B:< @#h$@P( @|b: @h@P( @P( @h@h@P( @h@B:< @h@#h$@B:< @P( @B:< @#h$@P( @P( @P( @P( @#h$@h@B:< @h@P( @P( @B:< @B:< @P( @h@#h$@B:< @P( @h@P( @P( @#h$@#h$@#h$@h@#h$@h@h@P( @#h$@P( @P( @h@#h$@h@h@/@^f(k@#h$@h@|b: @h@P( @h@#h$@P( @| @#h$@h@h@B:< @P( @B:< @h@h@|b: @#h$@#h$@B:< @#h$@B:< @P( @P( @B:< @#h$@#h$@B:< @P( @h@h@|b: @h@P( @B:< @/@P( @B:< @#h$@|b: @|b: @ɧǶ@h@|b: @h@P( @P( @#h$@B:< @P( @h@P( @Sigima-1.1.1/sigima/data/tests/curve_formats/pulse2.npy000066400000000000000000011623201514013333200230700ustar00rootroot00000000000000NUMPYv{'descr': ' P',P:MP|nNJPʏPְPC|PcPLjKP r52~PL[V|PDwzP-*wP6uPUBڵsPMqPYoPe=kmP^q^RkP}9iPw gP%aePhJbP3`P$^P/E\PqfZP܇rXPYVP8@TPz'RP} PPf-MPAP$NKP90oIP"MlM?2€MJOM aFMyM)ʹM[ M2.NVMِ$Mp:nM)VjMmeM ΅6aMxs]MsAYMEUM>PMLM&zHM,IDM/bDG@M4\;M8t˳7Mً 3MBOP/M~+MKQ&M#"MTXMWM]2%MmJMf@b` Mz Mp^M&-MyhL\٪L/L /fL q4L8LyPLLh7LymL";Lï L,?Lh߁L5;tL CL>&HLò>߹LGV̭LWn|LP*PJLLZϵLޡLctXLFQLlL,LuDaL\L~ctXL6''LizL ۻvLrL/`nLRr.jL%eL2aL(J8]LbzgYL1oz5ULAQL:@LLHLDnDLȋ=@LM^ I Kb KxzڠKKpZwKCœEKK K cK!~K_9LK!2Q){KikvK*׀rKnK4|1TjKNs"fK=!aK]KF:YK˘'|[UKOk?)QK=WLKXoBHKↄDKbb@K懶1oϘIAڼIGI_YIP.' IՋFIZ^^%I0vgHc`Hե.Hl-HzoHvMHgH~66H4xHLH jdH<|>oH=H HHFH(YvH+ DH2" H:OH:RHuj}HDHLHWHMHҿ۶HVHd_SH`7!H )Hh@&HXh{HrpZwHS(sH{&.nHpjHϲfH abHp60^HCyYH/UHFQH^?iMH$v7IH_EH.2@HG4H@| 0HNP+HJ!5'HLw#HRdFHؘ|XH\kH=ܰHeH`M HnH HxZ#'G,;iGRTGj"G/GwqGIG[G7*G!yGG*f)G8A@cG4 Y1GpG=ξG‚HGFUjG'8GOGPթGXGq/qGbDG@G_YGkvܔGݪGtyG`aGG~3֣GG({G jwG}5NsGPMoG"e0jG|rfGǔbG'U^Gl8$ZG0?zUGQG: MG#A]IGB;+EG[S@GL.kwwEЏ+sEGmhoEu6kEPHgE3bEZv^E޿oZEc6=VEdN< REl7f~ME ~IEuܕwEEDEAE~ņ=ET8E& 4E M~0E$L,E<(EpT#EClUEE(SE"E1]E_㟾 E:2E$[ED*f)DȩBDM|ZDNr,DV!nbD0D`ƹD4DhkvD=iDr7D0=D{HD`DZxqD -E?D Dҿ۶D DwMxDIFD$D6D.NVDfD7f~MD8D@ ^DŠDJↄD΂$UDRU g#|D'%wD\ND3+IDCœEDZkADrF9=D}9D!P4D" 0D*Nr,D@(D4$DlDC C%ÖCV=eC')UG3ClC0΄ϲC C9sOlCȆ:CBCםCLXCЏ+sCUbCAC4[C^s`ވCيChzC~&I|CpQhxC#sCzoC/kC1qPgCnIcC@a^Cy7ZCyVCWRC%NC$]?IC/EC,ĐAC_=C67H-9CyO4C?Lg0C,CHPf(Cî4$CR ChCZ;XC mCd%;C= CmUaCWmCv*tB'CBϴiB̫BtBG/|BrJB+BCB [8BcszB)6QBB2ۺ@B҂B<ĊBRYBD%I'B1BNIîBҜaBWoyQ`BA.B`B˙BjYBgBs^5B0 B|8b҄BOBgn|B {(=xBMj tB oBkB0vgBrDcB&j_B<&ZB/>9VBU{}RB8mKNBJBBYAEB+ABJń=BS9BTI!5Bu0B]H,ν,BD(Bf[RZ$Bs( BpBdBx7ZB ӜaB/ B!BcBT2A&JhAa)7AykA"ApA,C1pAs>A4 AA> :A_8|wAG2PEAhAPBAթAZ|~ANMAb!JAAlϷA&Auk>STA=V"A~nAA[A [AZ)A-!AcƀA|A,bxA(wD*1tAI\loA1tkAgA:2jcAt8_ADfӶ[A8VAM ;RA}qNAV2?JAۂJFA_UbCAA'z=Ahx9A̩ G5ArK1Aqٍ,A{Dϱ(A $A TN A 8APAahA3\AU Aد#A$"A}d@.P@"\@7&++@>m@@V@ln@I?3d@u2@S䵷@׶@\;@[}k@e.9@-@nDDֿ@\@wxtr@J A@L@ݪ@Ы@z@gUH@:@ 3@!J@b]@*zO@V@3)#@e|@=٧x@Vt@Fs ,%p@E!nk@O9g@Pc@Xh4^_@ݏv,[@bbV@4R@k??,7bw?f?vj?L?r?e%? U{"??U[??w?"DC1o?*rf?4j^?>3ҜV?F!M?P}1?E?X"a) \>=S>9mו>ޜ[2>Ѓ>(ck>+>r[l>@>tݥ>by>}>I>$QyO>. {>6؍s>@@%k>H7b>Rg^Z>\/Q>d"I>ny3A>v&+8>Ul0>h3 (> >;B>W>CD{>s=FL=P=ԐU=52ى=a]&==$e_== o n=P4=vѡ=&^m=0~ =8=BM>C=Lm w=T|o=^<g=f^=p,RV=z+\M=Ћ$E=u'==,4=`,=dJ5#= z==6=S =Fo=֝8 -P;\8;X;.q;"`;*x;4KiG;>z;Fgq;P ;X z;bV9U;lh;t;~EȊ+x;o;'dg;4W_;نV;~:N;#E;(s=;mE5;u0,;ڷH$;\8;;3A ;Kcź;IW::;Q:$!,:.QZ:6*e:@ϰb:Ht枿:Rk;:\?׮:dcost:n:v{:RI:-:]|:At:k:Xc:0Z:KR:z{!.J:A:)g9:i 1::2(:i< :Y:: Ⱦu:B:H(Ǯ9&WKK90987S9B 9L\9T&FY9^ud9fp蒻9pl/9z˪9_4uh9d9}9N>9ڀ9" wx9=Rp9g9̇L_9,V9N9v@#"F9p=9+[59fϯ,9 3$9.09 U^<9(i 92D9:DȢ8DM?8NL8V3|Ux8`ث8h}]8r" M8|:f8ljꆷ8n#88[v\8)8X8J28ﷇ|8Δ kt89l8Fc8v@[8(R8ՠyJ8s%B8598d-O18"b(8*5 84$8>Q#>8FR]8PF7X@ʖ7bN37l7t/AWl7~p7y_7A7g޻7h/z7 _p77WxP77С7FM&7|x7쐬 _p75ܑg7 _7;4W7%kN7ʚmF7$o& >7,576)/C-7@^Y$7H7|7R7\M? 7dQ7nGH6v5`gT*55h -5r2+%5|V5;d5B 5ErC594K44r40T4~`ث4#\H4ȿ4md44Nm4\~V4u44L ~,4"<Ʌ4*le}44; u4>ˎl4F;d4P*+[4XZtS4btK4l#B4tI:4~c,14I)4x4!4R43=63_--3v%3=63Nm3>L 3ʘ3=F2+!2[O2,Z2ѺW2wۓ2 `02I2fyhi2& 20p28U>2B7yۖ2Jgw2TD2^}2fMu2p3&l2xUd2}#\2"S2\K2lB2D':2s122[/)2ӳj!2̥82J22a@@2蔑19Hy11 Q1 )PN1Y1 s݇1(a$121:b>j]1Dn1Nr1VQ21`zϒ1h,k1r@\1|y1Aq1/h1z`1yJX1zO1é PG1h٤>1 )61β8%.1Wh1%1^191F 1&B41V06Jm0۵ 0"R0*%B04D[0U--ǂ-\r-c9a-(rP-Ώ*DG*Th{O@n*hWy]*x9`L*Fh;*p$+*Wy]*$ *n)u)՚A) M4z) )4)D+R%)Xu^)h͗r)| pa)S Q).B@){/)1){L )ū'( `(Zj($ (4() (H81D(X9}(lFB(Jv(`S(f(d[aU(cD(>#l3(܈t #(|E(A~(g'$'8^)'HEb'\'p|Ԝ'#ܿ 'm;F{'j'ظY'KYH'ܕ*8'c''*w't'(5 &8H&LR&`S$&p,&05,&zq=e&E&0Nn&XV^&^IM&Mg<&7o+& x&(k- &<ˈf%L_*%`%t%=HJ%%%f%e.s%$gb%ܠQ%D@%B0%,ءK%<"%Pl`$d$t0$J~i$'$<0۩$(8$r@M$ZIw$Qf$QZU$xb1E$,jj4$@/7s#$Ty{$d$x UN#W##r#5ҭ2#1k#ɐ#{# ^Ok#OZ#0 I#Do!ؙ!!-\!xS!$Œ!4 zs!HVb!X87R!lpA!40!~V!ȵ!U \t ܦ 2 ;&9 .r $P7 8? HcHx \nPVg pXV A-aE i5 q:$ Kzs i g&=7($OH!P Y]pLi<zwtI[Ƭ͵(1?PCαrxY#Q/>z!0>2^PyCЇxf8TBfdDu&#"t2 0K|X߯xsn`{-YD8/h )0X'X- x>cOnȨ!`cM (SxHy&p{87\GxX@W7ti52z$(`Ppnz-^lDJhB)(m'!N*IC20SdF{C޿=|`98 D-o 0m2OSp p7- н, 橳 `'c 6 ^! @9 W ט|X < `( PK x @ $ ɇE g> y`B]j|Au%2@v / qQh 4r%`\k~eb\@F_+%; NZ]Ov~ T@NCh?I&L hG0zCi7=ܰ` m18*Y 22mSQa,u5`#'KTs!8=9T7|1@*, z&Eu@ =xlQk ^@^&_@\RPGF%Ah9@ܫh-@311t ŷ%u=R@ƴgIsu;@YiS%%ﾀ(17I<ړyj꾀Hz龀΋n辀\TbڬU`=I@<l^0㾀#⾀#xᾀz Aݾb۾P پ,׾Ճ8řվmDӾZVPhѾ8PξQВlʾ@$:ƾ ¾/7_6KPuϥ ! eG|>xhq>44>,ꂰ >)> T>>%>?,>>B٥W>Ÿ́p>xpc>6B>!>>ov>B߂>uN>7>3->+>) >O5|>@> L[>lW>b:>)n >y>u$>@#{>ʹ>q$>1.#>Z1>@䨒>?e=>">9J>Nq>@ZV>>@\ c> P>No>j >#{>@(/>x.Bg>@(4>9֔>?y>6E6F>J}'>@P>DVm3>@[*%>a\@>Sg>maL>r>0,?`?̹o?ղ?D?g 9? gJF)|?>$E?Pa?`|E?U?؞?u[}? M[Q?$a:?$?@f??[^?lw?[? 3rq'? Oj?w.?@ ?}4?i:w?`AV? r?e@? D?@"?x ?OL?`'? 5?{Q ?YmY ?@"8 ?^ ?5(" ?` e ? - ? ?3o0/ ?@lMLr ?D9,h ? ?`>; ? ǻ~ ?D ?zDŽ ?@RJcH ?)A+ ?P G ?`b?U~T?ػ?`[?@8x?aW`?5 ?`f&?t ?`76?@?`*s!?@bC?Rd?mDA:?م0ȧ?EV??`Jq ?0-?܍O?`q?O?87?ҙ?`S?0|Ux?go:?SV[?F}?+[5?$?P5?0o?`P%?FF?lh?%?f?P?0b鍤?*}2?9ll1?[NS?Jt?p}0:j?Pq)?0U??,6?w/>?ս_?ppK?P;٢?0H}g???Aq)?`J?pcO-l?P??0;G.I?? e?~ ?L5?pVW?Pɜx? .*?R?F?qՆ?vb ?pIXeA?PT~c? !C ?3?]"(?d?D ?p<",?@c_N? o?{?' ?Wi?ê%?p/z?@-jA9? oYZ?sH]|?7?J3'y?t?`"?@"$? 8E?fz>g?ѻ̈?=Z?>?`v?@? o0?XD^ R?ąMs?0<<?,ʶ?`JX?@t ? s?K=?зO؏^?#?Ҷ?`9?@gU?ӖU?>s'?ЪcqI?[Rj?A?`0?@Z ?`7?Qb ?v) ?Єn* ?:3f; ?]~L ?tUE] ?\M n ?xD~ ?hV< ?P~3a ?@4+( ?08# ? ?Vz} ?  D ? !?w\!?-&!?_7!?>&H!?OX!?xϴi!?` {z!?PqB!?@'b !?(Ь!?!?ID^!?%!?അ!?j&"? {z"?gsA""?k3"?BbC"?pIZT"?`Q]e"?PdI$v"?8,A"?(8"?m0y"?<(@"?"?O"?]"?\"?1" #?#?5s.#?pw?#?`>P#?HWUa#?8 q#?(ÖÓ#?y7Z#?/ز!#?x#?#?Pv#?[=#?#?r$?(=x$?poY*$?X~g ;$?HJ_K$?8V\$? `Num$?lF<~$?"=$?B5ʟ$?؍,$?C$X$?$$?$?ef $?t%?hѧ:%?XH&%?H=6%?8G%? *VX%?_i%?ly%? %?؀r%?6N9%?%?%?X0%?xэU%?hq&?Xz}&?H0t!&?0Slq2&? c8C&?R[S&?6Sd&?Ju&?swBT&?):&?߸1&?Y)&?K p&?x7&?h;&?Xm&?@#} '?0R'? .'?E_>'?ݧO'?谠n`'?fA5q'?'?҂Ò'?#'?>īQ'?xd'?h'?P`'?@Gm'?04(?y(?8)q)(?h:(?j`PK(?Y X\(?Ol(?LG}(?{>l(?163(?x..(?`%(?PSp(?@ O(?( (?uR)?+)?j%)?416)?LF)?vڿW)?҆h)?nMy)?$X)?pۚ)?`)?PF:i)?8ڟ0)?({)?h)?)?]~L*?u!*??m1*??eB*?\hS*?aT/d*?"Lt*?pC*?`c;*?H93K*?8**?(E"*?[*?g*?' .*?| +?2i+? -+?I>+?TKO+? _+?pΞp+?Xv-e+?H,ν,+?8n+? +?N+?QH+?+?o+?%3,?zd,?tr+),?Gj9,?aJ,?hVY[,?XiPGl,?HH},?88@Ս,? 7,?Az/c,?'*,?謻,?b\,? ,?ΝF-?> -?:$-?x5-?h aF-?X\(W-?Hbg-?0˶x-? ~}-?4DD-? -?蟅һ-?U&-? ǘ`-?g'-?w-?-.?xIw| .?hnC1.?XOf B.?@,^R.?0Uc.? qmM_t.?'E&.?ܮ<.?O4.?H+{.?#B.?1 .?j.? s .?x^ /?h$/?PBU,/?@=/?0yN/?d7@_/?p/?x΀/?/?;\/?Z#/?/?]/?=x/?x݌?/???B0? 0?9J0?P0?1%0?Qt-0?xa!)50?p;>0?h F0?`rO0?TbfW0?L(3_0?D-h0?8Ӌp0?09x0?(tW0?D0?J{0? 0?r0?ZH0?Vj0?'0?kas0?0?!Y:0?|h՝0?8Q0?2 d0?H0?+0?Cz@1?J1?8V1?xT볹 1?p/)1?d 11?\e\'91?T,GB1?HJ1?@v͚S1?8ѝr[1?,,nc1?$>9l1?t1?=}1?c1?ƍ1?MPy*1? 1?p1?^T1?йh1?b1?o2`1?1?%WF1?ө1?sO 1?6Dp1?G1?72?tG> 2?l2?dU6b2?XX&$2?P-)-2?Hǩ52?Lj3?LC4?DZO 4?8O+;4?04?(2z$4?`,4?l*A54? ==4?q "F4?ݝkN4?&V4?~2_4?Ng4?7o4?̒]x4?4?H$4?`|4?04?YtN4?ﱪ4?k4?jrx4?xBc4?p ?4?d{Z4?\ֳ4?T1Rj4?HT4?@$J14?8BŔ4?,A5?$[5?Sf95?6" 5? 1(5?d׬05?(M95?xA5?tH J5?wR5?*Z5?ȅ>c5?k5?;Zt5?*i|5?̄5?L/5?z5?l5?]7? s7?Z57?ص:(7?}-07?kM97?%eA7?!I7?|,R7?׎Z7?2_b7?/Vk7? s7?xCЇ|7?p7?hp7?`TAG7?Tw7?L 7?Denr7?8ն7?0Sf97?(v#7?]7?,c7? U7?d*7?<5M7?7?DU8?M 8?Ԩv<8?G8?^4#8?F,8?+48?o =8?X#qE8?%)M8?8V8?ɖ^8?x6f8?pjbo8?d: w8?\G )8?T8?H}8?@X|S8?8Lu8?,8?$il~8?Ľ8?dE8?z^8?.\ 8?/o8?S8?68?@pK8?Л@8?Ca9?Q9?:(9?9?bR2'9?"R09?)89?såA9?Γ!}I9?t)dQ9?l4DZ9?db9?X: k9?Pns9?Hu{9?@KF59?49?,{9?$\_9?så9?X&9?m(k9?9?"bQ9?}޴9?iZ9?3:{9?Ў R9?B9?DI9?{ :?KAm :?U:?84:? #:?f0+:?|]^4:?t.(<:?hw%E:?`M:?X-U:?PoP^:?D?f:?<>o:?4zw:?(:? OA:?Q:? "z:?`k:?qϩ:?2:?pci:?3:?&a]:?́:?ܤX$:?7uԇ:?EP:?N:?HG:?;??y;?YW;?|'7@;?p';?hj.0;?`Řj8;?T i&@;?L{91I;?D Q;?81ڙY;?0\b;?(zj;?BK #s;?{;? ;?SM;?;?]x;?c-w;?ܾoۭ;?>;?tg;?n;?*?_i;?;?V0;?;ғ;?N;?PZ;?L!F+8=?$@=?("H=?IQ=?Y=?8Pb=? tj=?r=?I ;{=?ؤ=?a=?Z2}e=?Ȝ=?t,=?k=?sl=?!DV=?|d=?=?|2[=?t=?hUSH=?`C&ϫ=?XJ=?Pr>?DTB >??4 8:>?(e#>? 1d+>?3>? vy)+<>?ID>?+!L>?UU>?]>?<f>?ؗ[n>?+v>?MG>?̃>? >?^m{q>?=Ԡ>?s8>?o>?ʮj>?|%b>?pOb>?h)>?`6Y>?T>?LQT>?DGaͷ>?81I>?0~??(X@ ??E??s8?? iC '??0p/??7??y'7@??ԄH??/UP??Ԋ%aY??a??@ƒ(j??r??fz??Q7S??????by}??x??xIqD??ps??dh ??\)n??T`??HZ5??@:+X??8??0O`??$K??S@?a@?@?n( @?WZ@?v6?Y@?c'@?n@?!"@?dPS&@?*@?\G̶.@?t2@?RH7@?hL;@?HP}?@?*9C@?@X!@G@? L@?6DP@?yvT@?,7X@?;\@?$i a@?zq=e@?b/oi@?Jm@?3q@?Liv@?z'6z@?g~@?Ӣ@?z`ˆ@?/@?p].@?t`@?h\X@?Dě@?^-@?@'@?VnOY@?Л @?L˼@?@?B$G @?QR@?:nÃ@?V@?0>?@?'@?(5J@?bx|@?6@?@?믲@?pC@? F.u@?sh@?P@?~8h @? &<@?t) mA?VA?l_A? A?bߩ4A? fA?X:zWA?gbA?PJ!A?2-&A?FO_*A? .A?>K2A?xӈ6A?4F&;A?ӣX?A?*‰CA?.tGA?"\\>KA?DPA?,PTA?xXA?5\A??`A?mͱeA?oIiA?ǝ-{mA?xqA?"nuA?nPVgzA?}>%B~A?f&sA?A?\^׊A?3 A?Ra:A?ΎlA?JVA?ПA?@hA?DP3A?8r8NeA? A?.ȴA?A?$(E,A?U^A?A?A?y=A? b$A? 9JVA?f2wA?5A?|A?A?rnOA?I,A?hwA?䤋A?`sfA?[$HB?V-DyB?Z,B?N^ B?ȵB?D@B?͗rB?:>UB?k!B?2&B?m9*B?(UMk.B?!> 2B? O&6B?|;B?D2?B?dCB? GB?2~KB?` 2]B?7B?6eFB?xB?,TB?ܣB?" B?H?B?vsLqB?[ B?CԸB?+B?,D8B?YjB?俛B?z}B?;B?p0B?CC?tpGC?KC?j6|OC?c:TC?`6XC?ܾh\C?Xt`C?s2dC?NG[hC?tC/mC?F+laqC?*uC?D?^CD?ڱlAJGD?VT{KD? =OD?L:%{SD?g 9XD?BB\D?ݴt`D?:rdD?0hD?0K mD?x~;qD?(fjmuD?N(yD?7}D?.D?\b4D?fD? ݗD?俛ɒD?YD?~?-D?lx^D?t`D?HQ§D?l0D?"%D?bPWD?}HD?XD?عD?PD?3@PD?FarD?ŽZD?>BzD?*8D?4HD?DzD?*rqD?/D?"ͳD?AD?(isD?Ul'D?TD?<E?$a:E? l E?8ܝE?xfݚE?XE?n3E?d!E?f~%E?IfP)E?\wN-E?ؤ6+2E?T]6E?H:E?J->E?ZBE?@$GE??VKE?8OE?xSE?.>`yWE?kH7\E?$0N`E?dE?qhE?!.lE?OqE?|GuE? hyyE?׉&}E?r܁E?|2ZE?_B`@E?r*rE?ܣE?hՖE?WE?`C9E?pjE?VE?˃OΫE?Nk E?&T1E?DT\E?(eE?E? }xE?e6#E?NTE?H6E? vpE?.E?E?~֩ME?+gE?vY%E?F?lwF?__F F?dHxF?<0۩F?ZjF?֗W F?P?!F?p%F?H )F?MN-F?>{ 2F?q76F?6Yi:F?BF>F?,1*BF?^FF?"0KF?=bOF?SF?WF?Bw[F?o5)`F?kZdF?ShF?;olF?z%$-pF?R !uF?pSyF?f}F?f$F?F?^6F?c}^LF?Te~F?оMگF?L5F?VF?BGEF?tvF?8֏F?ϾMگF?0 F?*=F?&XwoF?_EF?GF?/F?6F?;=hF? iF?иF?ĸvF?|4/F?`F?tLqF?yYnF?jA,F?)'F?`YF?/eF?X]#G?ԊG?N G?]RG?FG?@kٵG?G?}DBG?5eFG?bM KG?5~H?τBH?t BFH?8JH?lfOH?p|HSH?bX:zWH?@[H?X)_H?ItdH?Pw1AhH?̤rlH?FɭpH?ktH?>-)yH?Z9}H?4jkH?RcH?*:!ωH?#H?"> 2H?kZdH?H?ǞH?H?!R+H?O|]H?|dΎH?LH?x4JH?$H?n2UH?_탇H?fAH?ຽH?\襽H?{NH?TCv9H?p^H?JFH?.sH?@1GH?&xH?8T笪H?jH?.(H?ܟ?H?& qI?7pbI?eX I?@I?(8I?ZjI? I?H I?vɓ$I?|Q1)I?Йc-I?r͔1I?+j5I?jYRI9I?:*>I?`"[BI? FI?V@JI?I?~o.YpI?I?vӢI?I?l%P7I?RiI?d̚I?ޭ̷I?ZoHI?X0I?P6@aI?c(I?H@I?ľI?>(I?yZI?6G7I?tI?,I?iq!I?"Q/SI?*:I?X"I? iI?&I?KJ?â}J?;` J?hJ?z{J?cDJ?pKXvJ?4 J?fL$J?y )J?^O=-J? o1J?Tˠ5J?/9J?L]G>J?Ɗu6BJ?B]gFJ?EJJ?8.?NJ?@RJ?0n.WJ?x`[J?&6_J?cJ?$gJ?Qp'lJ?o.YpJ?WtJ? ?xJ?(h|J?5& J?|bQJ?ࡃJ?t_J?J?jJ?EJJ?bsiW|J?ܠQJ?X9ߦJ?!J?N) OCJ?V uJ?FʦJ?ˆػJ?<ߪF J? J?3J? 4J?xfJ?K5J?xJ?J?Ӥo-J?-_J?.uJ?[]J?vEgJ?-%&K?nWK? K?d?^K?lK?\K?ǞPK?RV K?"o$K?HPW(K?}?-K?@'NI1K? {5K?6ɬ9K?3=K?.aEBK?BFK?$sJK?NK?i=RK?DQWK?r9:[K?!wl_K? 5cK?gK?(ڰlK?zUn3pK?,etK?rxK?z|K?h cfK?8K$,K?^f3]K?ړK?V^K?K?L$K?IVK?DwUK?K?:tK?\K?0-EMOK?Z- K?(ɲK?K?DK?HK?>yK?k~K? *L?ٖ\ L?4T$L?&(L?*T,L?z#1L?"bLU5L?J 9L? 3ȸ=L?7AL?eDFL?NJL?ӿNL?}RL?;VL?xH[L?utF_L?n\uxcL?D3gL?f,kL?+ pL?\Yl?tL?؆*qxL?T|L?ᵦԀL?JdL?<"8L?@jniL?VL?8>\͕L?&L?. 0L?MbL?&{SL?ƪL?֯L?)L?1K[L?^h L? PǾL?8L? C"L?| TL?AL?ro|L?:L?jʩL?LL?`%zt~L?Rb2L?VJL?ҭ2L?NlEL?*wL?D6L?cӥM?:c M?!> M?2oM?tM?(G\[M?tDM? ,6 M?h$M?R(M?*,M? X0M?/5M?Ja9M?=M? nAM?v;VEM?h>B(JM?l&ZNM?RM?d{VM?9ZM?ZL _M?yRcM?PsgM?1kM?HhoM?/PtM?>]8kKxM? )}|M?6简M?M?,bM?@ DM?"nuM?M?yZٙM?a M?$J(M?&:&N?gN?a N?JN?{N?N? KYN?x N?gB$N?|Ot(N?8Q,N?t. 0N?[ 5N?j;9N?Hm=N?bAN?EN?X?JN?ly@4NN?NaeRN?IVN?F1zZN?"8^N?kN?IgN?6wOyN?77N?.2N?dN?"-pN?Z.N?N?+N?h]N?y&O? >aO?kI O?1`$O?zVO?܇O?r!ꙹO?NWO?j|$O?⩢N(O?^׊,O?sO0O?V2[ 4O?_C9O?N+G=O?ƺGyAO?BEO?IO?:C̀NO?p>@RO?2qVO?˄ZO?&lx^O?&U6cO?T=8gO?%jkO? poO?-sO? wO?7Ʃ1|O?egcO?~%O?~ƈO?vfO?O_*O?jH7\O?uۍO?bO?VO?Z#O?+TO?NYO?ʆNO?Fx O?`O?>IMO?<1FO?6jO?O?*O?=FO?" wO?MO?{wO?r5 O?Z>O?CpO?1+oO?^-O?O?z7O?ye4P?7 ZMP? NqfP?7BPP?qN6/ P?/e* P?{ P?P?gP?%P?h-P?GFP?_&_P?xP?1P?Hé P?U_"P?v$P?ь`&P?? )P?Kw&+P? k>-P?_W/P?Sp1P?CH3P?,P?@P?s7BP?/PDP?piFP?OHP?i.JP?'& LP?P?=<,P?RDP?i}]P?uqvP?3eP?YxP?MWP?mA6ڻP?+5P?* P?$P?c6=P?!MVP?cooP?zNP?[-P? P?վP?վP?Q첩P?P?g6P?0FOP?GG%hP?^wP?tkP?_²P??SP?GP?;_P?w/>P?5#/P?GP?* `P?oAyP?+XP?nwP?VP?e5P?#P?ɸQ?'Q?[@Q?YQ?$or Q?;}N Q?SRq- Q?ie Q?YQ?MQ?IAQ?5 Q?)g9Q?FRQ?A%kQ? Q?5"Q?yL$Q?7c&Q?y(Q?^+Q?o=-Q?-2/Q?ԦJ1Q?c3Q?g|5Q?%7Q?/ww9Q?FkV;Q?]]_5=Q?tS?Q?يGBQ?;*DQ?U/CFQ?#\HQ?ouJQ? NLQ?K-NQ? * PQ?@RQ?WTQ?AnШ WQ?ć#YQ?f<[Q?{EU]Q?9ɠ$n_Q?ߔaQ?cQ?q }eQ?/$qgQ?:eiQ?QY^lQ?ihM=nQ?'A5pQ?5MrQ?)ftQ?_vQ?xQ?wzQ?U|Q?W4~Q?5Q?KQ?b-Q?MyFQ? _Q?ɦnxQ?MQ?CԎ,Q? ÑQ?wۓQ?}kQ?;/_ Q?ES&Q?\Gf?Q?ss;EXQ?1/$qQ?#Q?⢤Q?k Q?'ԨQ?~Q?]Q?a)<Q?@8Q?VPQ?miQ?WQ?Q?ӱvQ?ȈUͽQ?O|4Q? pQ? eQ?#Y0Q?E:MIQ?QAbQ?g5n{Q?~)MQ?=,Q? Q?Q?uQ?3Q?)Q?eBQ?k4D[Q?)K#tQ?aQ?xQ?cQ?!Q?߼~Q?v] Q?Yj<"Q?_;Q?SSQ?.GlQ?QE;Q? \/Q?r#vQ?UQ?G 4R?R?R?3R?=ۯL R?Ўe R?(m~ R?w?LR?5V+R?l R?R?mR?+|R?p,R?deER?eXD^ R?# M#w"R?"A$R?95&R?[P)(R?g*R?}~,R?] /R?S;%1R?>3R?V5R?o7R?Iʷ9R?;R?3u=R?JT?R??a3AR?wDR?FR?yv6HR?7jOJR?^hLR?RmNR?oGLPR?-;+RR?-/ TR?D#VR?g[XR?#r [R?/]R?dH_R?]CaaR?"zcR?eR?gR?SiR?(kR?>}mR?U\pR?Kl;(rR? |AtR?řpYvR?drxR?AXzR?L|R?@u~R?{ 5TրR?9")3R?8R?O R?qf9R?/}RR?kR?lR?gKR?%*R? ϕR?R?_R?3R?I2R?`dKR?UwvCdR?j"}R?Ѥ^R?RநR?MFǪR? :R?.}R?#\R?C-;+R?D DR?Z\R?}quR?9綎R?ەR?tR?sSR?12R? R?#R?i'UR?T|nR?kplR?adKR?X*R?ۯL R?@R?W4R?(R? 5R?!dNR?O8CgR? O!R?eR?|߱R?EվR?ɝR?|R?}ױ[R?;:.R?GR?_R?u2xR?3IvR?_jR?v^tS?kRSS?)F2S?:S?.& S?c"? S?X S? qS?,kS?YCJS?Z)S?pS?S?OS? S?˫8 S?cQ"S?GBj$S?!&S?&|(S?=pߴ*S?=Td,S?jX.S?L|0S?w@[3S?54:15S?(J7S?b9S?m{;S?+ =S? ?S?7sAS?cNRCS?!e1ES?{HS?)JS?[BLS?[NS?֙tPS?kRS?QJTS?v)VS?1jXS?H^ZS?I_R ]S?vF"_S?Ì:;aS?.cTcS??"BmeS?!gS? iS?y޷kS?5mS?+oS?B{rS?oYZtS?-p94vS?놷MxS?ezS?e~|S?#˓~S?ᇔS?{sɂS?]pRS?&d1S?S?ydbWS?7{ApS? S?S?q޺S?/ցӮS?uS?j{S?g^ZS?%1R97S?GFPS?^:hS?_u.ցS?"S?٢S? sS?UQS?0S?S?/S?K+HS? BìaS?XzS?ojS?CIS?(S?S?{{S?9oS?c(S?XAS?s%LbZS?1<@AsS?R4 S?i(S?i޽S?'S?S?zS?_Y!S?8:S?SS?kS?W6ՄS?MT?cT?zrT?MQT? 0 T?ɾu T?i2 T?E]KT?RdT?F}T?}0:jT?;G.IT?]"(T?tT?u T?1 T?+"T?D$T?ka]&T?)@v(T?*T?*,T?aA.T?X0T?n2T?z 5T?Y{Y$7T?o8=9T?cV;T?Wn=T?OKՇ?T? @AT?$4CT?;(rET?ERQGT?i0JT?LT?5NT?=NPT?gRT?ԊTT?uiVT?3HXT?'ZT?5\T?mL^T?+caT?y.cT?uGeT?cia`gT?!]@yiT?QkT?EmT?[:oT?.qT?/"sT?FzvT?Q] Y'xT?t7@zT?͊Y|T?q~T?GԊT?γT?’T?qՆT??PT?)/T?@ T?wW8T?5n{QT?ojT?cT?oWiT?-KHT??'ΛT?3T?e (T?#$T?:1T?QJT?[h`cT??|T?וT?T?SưT?ڼ߲T?T?yT?IX*T?57CT?K\T?butT?AyiԍT?]T?QT?yEqT?79PT?-/ T?"#T?q;T?-/ TT?EmT?\T?gshT?%GT?&T?T?]ζT?T?4T?MT?U)`fT?@{?T?VoT?mcT?KWT? KT?DZ?T?3yT?A'X-T?7FT? _T?{#wU?9:ӐU?P첩U?gU?q~pU?/O U?. U?° &U?i٤>U?'WU?pU?U?_4uhU?KiGU?a]&U?xQU?WE"U?9$U?Ѽ-7&U?!P(U?M`i*U?  ?,U?.U?.0U?CE2U?\ں4U?rΙ6U?}x9U?;W0;U?6I=U?͞b?U?szAU?1ӓCU?{EU?(oGU?k?cpIU?)VWOKU?lK.NU?? )PU?a3ARU?'ZTU?sVU?XU?WhZU? F\U?"%^U?9`U?OPcU? g!eU?}:gU?SiU?E_lkU?˜>mU?،oU?qU?=usU?iuU?3]xU?uJQxzU?3aEW3|U?w96L~U?-eU?m!}U?)ӖU? U?ȈU?coU?!NU?--U?D ,U?Y[DU?r]U?ՈvU?U?QgU?͆FU?z%ڟU?nU?Gc U?(W$U?>K=U?U?VU?=l3_oU?'>U?U?wU?5ҴU?U?U?m wU?+"V6U?85OU?OhU?efU?#}ҙU?ߓU?U?[oU?tNU?h-U?] /U?SQGU?3E`U?I9yU?`-U?Iw!gU?FU?Ť %U?U??U?'U?٠@U?yYU?7-^rU?C=U?ZU?oqU?-U?랆U?zU?gnw U?#bV9U?V5RV?KkV?]'?V?>3ҜV?T'V?k V?So V?NV?ϯ,V? 2V?KJV? cV? Ȩ|V?!V?A8fV?NEV?e$!V?{|#V?9&V?t*(V?hC*V?q\\,V?/P^u.V?E=0V?92V?i2-4V?%I!6V?_8V?v ;V?_v#=V?Uf^V?3E`V?&'$bV?s=dV?1TgV?j-iV?FkV?i~_mV?']xoV?޸V?2V?&V?Ov)V? &UBV?<4[V?StV?GjV?ХV?ӯV?ǎV?=ŻmV?ۯL V?+"V?w ;V?5 SV?6lV?MtV?mdhV?+{\eV?PDV?D#V?c8V?!,V? 3V?LV?[ ~eV?1\~V?G;V?^V?QuV?V?͢V?V?IЩu,W?TEW?3^W?wW??+zW?AnШ W?Xb W?yoVW?5JmW?>L W?2+%W?o& >W?-VW?oW?W?e%W?#9mW?2RoW?K&}kqW? \sW?;uW?wW?CyW?{W?$߶~W?{;ӕW?9Rt2W?hSKW?2dW?s}W?1W?ËϮW?ǎW?isW?'hlW?\KW?5P*+W?_LD DW?c8\W?y,uW? W?WW?dW?B٥W?!W?M W? #W?/;2gW?kW2W?)n&W?ϱW?W?aW?kW?JW?).W?Y GW?$_W?:xW?QW?OhW? cW?˕BW?!W?GsW?g&W?[?W?PXW?=D|qW?48[W?K,:W?ub W?3yW?W?X?mX?+s8X?RQX?1jX?c X?!/ X?EδX?\X?[sX?kX?ՠyJX?m)1X?QaJX?UbX?I{X?>!X?G)2#X?@&c%X?VB'X?m!)X??,X?).X?B0X?wޜ[2X?5{t4X?Z6X? 98X?o#:X?-:X?g AX?e~"CX?#ss;EX?gRTGX?[1mIX?[OKX?CMX?8ηOX?,QX?S4 SX?KkVX?aJXX?x(4ZX?IM\X?e^X?ż~`X?̤bX?AdX?bfX?AhX?y. jX?7EmX?[,oX?ryEqX?qm^sX?-a{wuX?UZwX?I9yX?g={X?%1}X?&X?( X?]?%X?Vs>X?lQWX?0pX?UX?X?ͺX?޺ӒX?KX? jX?"IX?9(7X?CPPX?fshX?}gŁX?{[X?9OX?Cb̧X?7AX?q+ X?/ X?/X?3HX?iJaX?'azzX?wYX?8X?_żX?ݾX?ҴX?騴X?W(X?rAX?-QZX?Dy0sX?M[mX? raX?ɈUͽX?IX?C=X?1jX?%I!X?}(:X?;SX?'kX?>ĄX?sU꣝X?1lނX?aX?@X?kX?)ǮX?ݢ2X?KX?a dX?"z}X?8sYX?Og8X?Wf[X?}OX?ӓCY?7Y?O++Y? rDY?Q] Y?0v Y?EY?3Y?IY?`ثY?=ẘY?i Y?H$Y?u'=Y?3ҜVY?n!Y?ć#Y?my%Y?)-m'Y?Caa)Y?ZU@+Y?cqI.Y?!=0Y?ߞ152Y?%N4Y?Yg6Y? z8Y?Y:Y?7Y?>@Y?TBY?kƳEY?G.GY?qGIY?ïP`KY?Ɩ/yMY?=݊OY?~QY? sSY?w!gUY?58[WY?NOiZY?eCH'\Y?m|7'@^Y?++Y`Y?qbY?ĊdY?efY?#hY?`jY??lY?[2oY?IqY?_8sY?vQuY?SjwY?yyY?ͺX{Y?ф7}Y?IxY?lY?aY?,UY??CI1Y?Y=qJY?p1PcY?y%/|Y?7Y? Y?ƔY?oߖY?-Y?hY?&G*Y?g=&CY?%T\Y?jtY?ÍY?]Y?Y?~`ثY?r?Y?Sf Y? ["Y? O;Y?7CTY?KN7mY? e+yY?{XY?7Y?AY?Y?Y?{Y?9ؑ4Y?pMY?1OfY?qH.Y?/_ Y?uY?Y?iY?%xY?lhY?`G-Y?_T&FY?I_Y?+=wY?B1ÐY?UY%Y?pY?ц `Y??Y?M Y? %Y?>Y?ѺWY?CƙpY?&xY?/Z?Eu2Z?x(4Z?lA6Z?`Z8Z?;Ts:Z?HxZ?u16@Z?3+%BZ?ADZ?X GZ?ko!IZ?):KZ?oSMZ?NlOZ?c-QZ?! SZ?UZ?WZ?Y%YZ?<\Z?Rg^Z?i~F3`Z?Or%LbZ? fedZ?˭Z}fZ?N–hZ?GBjZ?6lZ?+_nZ?>pZ?=6sZ?L+uZ?cDwZ?wz]yZ?5v{Z?w}Z?VZ?mտ5Z?+ڃZ?Z? Z?e0$Z?!G=Z?]xoVZ?tlNoZ?[`-Z?T Z?׸H빖Z?<ҘZ?Q0Z?$Z?gZ?* F6Z?IA%OZ?XhZ?n‧Z?Z??ѠZ?˭Z?ɹ^Z?y=Z?5Z? .Z?$GZ?o;~`Z?-RryZ?hfwZ?ZVZ?eN5Z?#BZ?6Z?*Z?]'Z?@Z?oYZ?5MrZ?SL,Z?c Z?yZ?Z?KZ?Z?ԧf Z?E9Z?A$RZ?kZ?/xZ?yFlZ?7]`Z?sTZ?H^Z?q<=Z?/0Z?$1Z?JZ?g cZ?%|Z?)vZ?@U[?_W4[?n[?ل[? [?U* [?ɡC[?ߕn\[?Mu[?K ~,[? $r [?:f[?QZ[?ChN[?B [?6f#![?{*E<#[?9$U%[?n'[?)[?s+[?1-[?4~/[?K]1[?ib<4[?'y6[?右48[?M:[?af<[?ԏ>[?v@[?xUB[?Wl4D[?/`F[?ETH[?\HK[?Ms<-M[? 0FO[?ɠ$n_Q[?MxS[?E ,U[? W[?Y[?}[[?;)ݧ][??ц `[?Ve&b[?umD?d[?1#Xf[?qh[?j[?kȉl[?)}n[?q~p[? f]r[?a#Z<u[?:Nw[?PB7y[?g6P{[?Y~*i}[?[?ӫv[?U[?O3ͅ[? [?[?[?G4˯0[?KI[?amb[?xL{[?=+[? [?Ś[?uwޜ[?3k[?`[?Te)[?m.HDB[?+E<#[[?[0t[?r$ጫ[?c[?! [?߶~ױ[?\[?[; [?"[?:[?(S[?Q?l[?V[?lu[?T[?G3[?}[?q[?e[??Y3[? NL[?"Bme[?w96L~[?5P*+[?f [?}[?o[?-[?[?d,[?eCE[?#"^[?w[?3[?]J[?a[?w}[?\[?Sw; [?k%[?_=[?SV[?IHo[?<\?-0u\?D$T\?A[3\?q  \? \?y\?76\?܍O\?lh\?qK\?-*\?' \?>\?gU\?%l \?}#\?qd/%\?]eCH'\?Y"a)\?Mz+\?A-\?U 6/\?"*1\?8}3\?O\5\?Kf;8\? }(:\?Ǔ@<\?Y>\?Cֶr@\?ʕB\?tD\?{SF\?92H\?2J\?IM\?q` O\?/ww9Q\?kRS\?_lkU\?iSKW\?'G*Y\?; [\?/]\?_$_\?-b\?C d\?Zd2f\?WqBKh\?!dj\?ў}l\?ߕn\?Mľp\? 㸝r\?|t\?[v\?C':y\?>+{\?T}C}\?}kq\\?;eu\?Y\?Mt\?sAS\?152ى\?)\?  \?k!#\?)8<\?NU\?ekn\?a|J\?)\?ݩ\?ў\?Wײ\?\?\?c5\?O2BN\? Iw!g\?_k\?v_ߘ\?ES\?Gʳ\?;|\?/[\?=#:\?.\? F\?u,_\?3Cx\?Y蔑\?ps\?mR\?)1\?紸\?ˬ \?c&\?!?\?X\?&}kq\?Y=qJ\?Te)\?jY\?M\?QA\?5\?)\?c8\?GBQ\? !j\? \?7ޛ\??N⽴\?d֜\?{{\?wZ\?59\?1\?֚I\?mb]?+{]?w]?1ks]?eH_R ]?#_S1 ]?uG ]?;]?[/)]?#B]?[]? kt]?SI]?(]?+]?B ]?IY"]?pĤ %]?ņ"']?b;)]??AT+]?ʔ m-]?/]?y|ޞ1]?7q3]?%e5]?]?)L@]?geB]?%~D]?F]?rH]?] QJ]? 0L]?6N]?MQ]?Sd,S]?{EU]?ϑ^W]?jwY]?KI[]? ւ(]]?v_]?ka]?A_c]?0S f]?GG%h]?{^;b>j]?9u/AWl]?# pn]?p]?q ޡr]?/t]?v]?zx]?iY{]?%+8}]?A7]?XO]?_oh]?]?ۜ]?r]?U|Q̋]?p0]?d]?Y]?M%M/]? ^?n|7'@^?̈́p@B^?dXD^?IXqF^?LH^?@J^?4qL^?? )PN^?#/P^?:S^?yQU^?7h8W^?~QY^?j[^?oh]^?-G_^?ٽ&a^?c^?ee^?#g^?4j^?K1l^?]bv`Jn^?yj?cp^?ُ^|r^?Rt^?SFܭv^?:x^?.z^?#y|^?KX^?/ 7*^?EC^?\[^?Ast^?۲^?ϑ^?{p^?7ηO؏^?.^? ^?q"^?/);^??|T^?Vpm^?gmdh^?%XG^?L&^?@Ѥ^?_4^?(^?^? 4^?U#`M^?:>f^?P^?g^?K~۰^? ɺɹ^?ǫ^?±x^?C٥W^?6-^?F^?{^^?94vw^?Jj^?a^^?sxRp^?1FO^?:.^?. ^?i"%^?'>^? W^?p^?a.g^?EF^?[%^?r^?W^?^?Ӷ^?͟7^?M_P^? >i^?|^?(p^?E?d۳^?VX^?lL^?}@x^?;4W_?(60_?I_?ua_?1z _? _?"퐬 _?k9o_?)PN_?f-_?} _?a(_?A_?Z_?؍s_?Yg _?vF"_?j%$_?3^&_?OJR(_? aF+_?w:!-_?.:/_?G"_S1_?>l3_? 5_?7_?=ڶ9_?;_?-ۘ=_?wDw@_?3[VB_?q53D_?LF_?mdH_?+}J_?̇L_?{N_?cooP_?!dNR_?'X-T_?>L W_?[U@+Y_?l4D[_?Ղ(]]_?v__?Qga_?Fc_?$e_?g_?G i_?" l_?8ɠ$n_?O=p_??f^Vr_?|=ot_?v_?wx_?5ڹz_?u|_?i~_?o^w_?-RV_?2F56_?I:O_?e`.g_?#w"Ҁ_?_? _?]nˑ_?M_?,_? _?S._?-G_?C`_?Zy_?Iqf_?E_?Ş$Ħ_?{ݨ_?Ao_?c_?W'_?yL@_?7'@^Y_?=4=r_?T(_?qk_?-ڼ_?ս_?_?gv_?%U _?49_? R_?]!j_?8у_?N_?e_?U|n_?M_?ϩu,_?i _?K]1_? QJ_?Fc_?:|_?C2.f_?H"E_?_$_?{v _?9_?_?*_?s~C_?/]\_?nd?`?y2L`?XX`?\e`?Lq`?}`?x@``?ֽϖ`?64?`?Ԯ`?(`?R뢍`?`?l`?n `?K `?,$"`?/*#`?:$`?HFs ,%`?Qx8&`?]gD'`?fhWQ(`?s[])`?"6j*`?Ov+`?,`?@C-`?.`?7d/`?\ñӴ0`?+C1`?ڥ2`?x"3`?4`?65`?p6`? 8`?RO9`?)$:`?5v.1;`?p@=<`?Kj J=`?,W|V>`?b^b?`?m[o@`?JyR{A`?:B`?FC`?fD`?Ħ:E`?$F`?.hG`?ȨH`?@"GI`?ߜJ`?&K`?\M`? N`? tO`?z)P`?#yS6Q`?6/BR`?:m2OS`?E[T`?TQahU`?\ۀtV`?hUW`?ps_X`?~IϙY`?.>Z`?=[`?젷\`?J1]`?^`?%l_`?fΟ``?Ka`?$哺 c`? *d`?"e`?B /f`?|x;g`?Gh`?^)pWTi`?4`j`?@d6mk`?zKޥyl`?VXm`?8b҄n`?mLo`?xcp`?T@ӷq`?Br`?4s`?p!t`?б(u`?.v`?px`?Ӗy`?LOz`?ꊾ'{`?.4|`?h@}`? M~`?&s|Y`?#e`?.g[r`?B:~`?E[:`?Qթ`?^\O`?gɈ`?sC`?|~gɈ`?ډ7Չ`?8F`?+`?%`?V`?™`?t `?rٍ,`?S9`?0E`?1R`?v^`?Lk`?jw`? )`?h4^_`??Μ`?&KR>`?V̭`?aF`?BmΞ`?x:ڟ`?k`?`.`?J`?" `?|)`?ڼ%`?:Ȑ2`? x>`?ބJ`?VVW`?xc`?5p`?r m|`?`?0#a`?.`?9Uc`?LEҺ`?PIBdz`? \ñӴ`?jg=!`?r`?(~1`?o`?%`?DN`?*`?-7`?` C`?͇ P`?|\`?|{h`?Zu`?:oʁ`?9`?d`?X`?(X`?4`?t?Lg`?J`?2V@F`?a`?l4%`?Nx `?(`? s#`?j/`?ʥR<`?(H`?1U`?a`?D~n`?z`?r`?b^`?gΟ`? =`?~[`?"`?<.O`?9`?DCk`?XP`?[7J`?g`?tr+)`?}(`?25`?wA`?M`?NVZ`?f`? 5s`?l`?u`?(`?i`?b`?F^ҽ`?A`?R`?b( `?3F`? ?`?~J:o`?U`? qa?}a?a?Z{^a?͢a?o=a?v鬻a?ca?4݋ a?W!a?j"a?PL#a?I%a?(@&a?l3('a?>4+(a?*J8)a?U(wD*a?`P+a?HlV],a?wi-a?5v.a?d/a?™0a?"~1a?2a?rb3a?>4a?fA5a?6a?ZZ 7a?ԏ8a?O9a?x n ;a?Ca?8,=?a?RD+I@a?O VAa?[{bBa?nfnCa?qZ{Da?,}ɇEa?9Fa?꓁Ga?HHa?uIa?Ja?difKa?La?"]EMa?״Na?Q$Pa?>˓Qa?FRa?r)Sa?\:5Ta?'QBUa?3.NVa?x>0[Wa?I"gXa?6UtYa?`Za?k[a?Rw ^\a?ͥ]a?<^a?nx_a?Τ`a?,laa?ba?`jca?Hda?TI fa?θga?fH("ha?—.ia?$ =;ja?vGka?!1Sla?@-U`ma?8%lna?C4yoa?\Opa?Zqa?f ra?xqsa?|bta?6{ua?@va?owa?Rxa?cya?{a?pWn|a?}a?.KM'~a?ż3a??,@a?JLa?4 Ya?zea?f'(qa?2Y~a?$>Ɋa?I8a?Ta?@`a?ka?v~ȋa?^eՌa?ra?Da?zfa?د#a?8Za? a?Nr,a?T8a?BQEa?Qa?p60^a? ja?.+wa?!~a?,a?J8]a?Cͨa?Oa?zEvJa?Va?89Uca?oa?.4|a?Ta?"a?'a?r2a?=aa?.I ƶa?T@ӷa?_߸a?Lkxa?va? la?hma?Ƙ`a?&L*a?T6a?+Ca?BHOa? \a?b?j`PKb?vڿWb?bT/db?Ξpb? H}b?~}b?ܮ<b?<\b?0̮ b?Ъ;!b?X$"b?#b?$b?t%b? i&b?2(b? H)b?+{*b?N7&++b?Bo7,b? ND-b?lYcuP.b?d\/b?*pWTi0b?{u1b?K32b?FŢ3b??4b?5b?b36b?¿`7b? '8b?~֡?9b?:b?<;b?b?Zm?b?~#@b?&K0Ab?v1r uAXb?+ONYb?6iZZb?ZB.g[b?M]s\b?Y ]b?vdQ}^b?o_b?4{E\`b?˱ab?9;bb?Pcb?-db?eb?n!fb?ʛhgb?*ib?Gjb? !kb?H&.lb?:mb?xGnb?dtSob?%l_pb?"1Slqb?<`xrb?G2sb?>STtb?^ub?iHvb?Zuwb?<`xb?yb?x0?zb?֢{b?6$|b?~b? b?RВlb? &b?K3b?n?b?z*Lb?, Xb?o eb?xqb?H+c}b?6Wb?BWǖb?dM6b?XKb?"db?o?Ȏb?zԏb?@3db?b?'Cb?\b?"b?b?x,b?Չp8b?6Db?}OQb?]b?Rr.jb?vb?f b?n%|b?0Z웠b?,<[b?GN˴b?R:b?J^Bͤb?iڥb?u6b?fb?ċ*hb?$ b?Gb?⭘$b?@&1b?Č=b?Jb?\ۀtVb?bb?tSob?z{b?i2b?6㡔b?]b?*׀b?T6Qb?A_ƹb?MEҺb?pX>߻b?c9b?.ob?z-b?셧b?J!lb?)b?K6b?fBb?ƾ *Ob?$ʃ[b?hb?wxtb?@b?kWb?ƙb?^`6b?ڥb?%Tb?z0΄b?;Hb?8Gcb?Rb?$ȭb?&0Bb?;c?F6c?BRk c?]*,c?iJ9c?`tEc?)Rc?^c?|kc?ڡxw c?: c?V c?tƜ c?V5 c?hc?c?r\c?c?0Qcc?c?EBc?L* c?59!c? A%c?jL-2c?Wo>c?&c!Jc?nNWc?ycc?D-pc? |c? c?`{!c?w"c?Z#c?|kʺ$c?9%c?:_&c?'c?S(c?V)c? Hg+c?,c?t$c??c?~J Ac?Bc?<?k#Cc?/Dc?)3Jܰc?V c?Џ+c?ZJ7c?nDc?>Pc?vM]c?2ic?4,vc?'c? c?P){c?4ꧤc?@Zc?nKc?V9ͧc?,b}٨c?mc?xqc?Hc?ef c?c?dYE$c?ıӴ0c?"M$=c?ǓIc?AVc?>߻rbc?5nc?Q{c?\*c? 0c?c?x#c?.c?6:żc?E^ҽc?P޾c?R\Q~c?T¸c?20c?٬c?p&c?~c?.c?]c?c?J<d?(d?4}d?f?d?Jqd?$Vi,d?ae8d?lHEd?BxYQ d?'^ d?Mj d?^w d?Av d?d?z5Ud?ǯĨd?8)4d?ޣd?d?Td?d? ad?rd?"@ d?..d?9t%d?D1d?LPh=d?[mJd?g\Vd?hrLc d?}Po!d?&+|"d?D#d?䟾 $d?B8z%d?&d?,Y'd?^ͦ(d? 8)d?䚧*d?|+d?,d?8 .d?e/d?0d?V(wD*1d?362d??k#C3d?rJO4d?U_\5d?0aqh6d?lSt7d?wP8d?LG9d?/:d? ;;d?hd?#]?d?ҝ@d?BīQd?03Rd?2Sd?Td?L&Ud?Vd? aWd?jؔYd?@Zd?(?(\d?}4]d?D@^d?qmM_d?(Y`d?`3eLfad?>߻rbd?JY+cd?|UӚdd?`M ed?:lyfd?wAgd?Xhd?X5id?7jd?)kd?tld?һmd?2Ǘod?epd?݋ qd?ND-rd?9sd? "Ftd?j tRud?_vd?("hqkwd?-wxd?8\Pyd?DDֿzd?OP/{d?[ʞ|d?bfD}d?q}~d?}8d?~\ۀd?ܓ,d?<;d? d? d?Xd?̎%d?i2d?t>d?GKd?2vWd?&dd?kpd?N}d?'_ud? 3䕐d?l>STd?Iîd?(UG3d?`ǔd?k;ԕd?Fwd?/d?`d?b#d??d? d?~+d? 7d?<҅Cd?lPd?y\d?XKid?mud? *d?vbd?! d?4-Vyd?8賨d?CJXd?PO̪d?Z>7٫d?fd?lq2d?|d?*& d?dd?#d?FC0d?ed?.d?Yd?Z' d?2M}ſd?>d?vIA\d?Td?4`5;d?kd?v)d?Pd?(d?h5d?lAd?̯GNd?*Zd?&gd?sd?Hsd?td?gd?dSd? \ñd?"2d?!Pd?,d?>8Dd?Cd?N8`d?ZZd?e,?d?q!d?x| .d?և:d?4Fd?lSd?_d?RKld?xd?v*d?nd?j d?,xd?^d?Wd?HSd?6d?'Gd?d2d?=;d?"I d?T/dd?_&d?>k#C3d?v?d?"Ld?\Xd? ed?pqd?x}d?ֺyOd?6d?m.d?睯d?Ra d?|e?Ue?n [e?Je?,!:e?,>e?7e?HC2e?N+ e?Z&h8 e?feD e?pGQ e?$|] e?&je?ve?@e?|te?e?\pSe?´e?d2e?xޡe?Xe?6Ҁe?Me?_e?TA e?&>e?25$e?p=1e?H)= e?.TI!e?_lV"e?jb#e?JvKo$e?{%e?*&e?f'e?ƣ(e?$sx)e?*e?gW+e?@,e?[6-e?ե.e?^O/e?Ʉ1e? D2e?zc3e? 8)4e?8,B65e?7,B6e?B!O7e?TN [8e?Yh9e?ept:e?pp߀;e?{Oe?v?e?J @e?j|Ae?Be?h^[Ce?De?$R:Ee?̩ Ge?FHe?B"Ie?;.Je?g;Ke?^&/GLe?1FTMe?=#`Ne?zH%mOe?SyPe?8_Qe?j tRe?uSe?TRTe?y·Ue?1Ve?rmWe?ЮXe?0aYe?Ze?U_\e?L]e?I>^e? í'_e?h=4`e? @ae?&2Lbe? kYce?+&ede?B7Jree?B~fe?N)ge?^Yhe?die?pxje?|{|ke?چVle?:pme?5ne?doe?Vpe?Xre?se?rLc te?,ue?0@B9ve?Ewe?5!Rxe?L^ye?)kze? &ow{e?h1߃|e?e?VJe?7FWe?ce?t ,%pe?|e?0 e?+se?6㡔e?NBRe?Mºe? Y1Ǘe?jdӘe?ove?({e?je?^e?D^e?=e?R*e?`7e?FCe?Oe?~:k\e?he?:.Jue?e?#)e?Xe?%e?1we?t< 翬e?GV̭e?2Sخe?^y5e?ie?Nume? e? ae?jb#e?ʢU/e?(Ȁde?Fpe?n}e?Z:މe?Me?.f?vը,f?"f?4 f?{f?f?P Zf?f?%8 f?n0y f?; f?*Gm+ f?R7 f?]afDf?HiPf?tUE]f?ϴif?dI$vf?–Óf?"=f?rf?1f?>īQf?%f?ڟ0f?Zf?f? f?xf?^ f?6| f?*<$!f?5p0"f?RA=#f?LdI$f?XU%f?ncXjb&f?nn'f?,zLI{(f?Ƹ)f?@(*f?H+f?4,f?v-f?d(.f?ɢU/f?"0f?41f?2f?@4f?5f? 6f?\a)7f?$s58f?0@B9f?x;gN:f?F[;f?6R[gf?Rt݌?f?CM@f?Af?p7,Bf?ΡCf?,+ Df?zEf?Ff?JϙYGf?Hf?8 Jf?fKf?"Lf?$.Mf?v:Nf?eGOf?@*jSPf?5D`Qf?@^lRf?\L#ySf?WRTf?cUf?znFrVf?yWf?6:QXf?Yf?.0Zf?T[f?"\f?~]f?p_f?Ԑ]`f?. af?<'bf?3cf?Jy@df? Lef?mXff?f$iegf?/aqhf?$;H~if?FUjf?Q'kf?@]Ilf?hmf?s=vnf?^of?1Upf?qf?z%4rf?جsf?8uf?Óvf? wf?Tڇa,xf?8yf?{@Ezf?pQ{f?p^|f?.j}f?dv~f?)mf?J5Xݏf?@Lf?LLf?hW+f?b@f?&n ΅f?y4zچf?℮f?B(Yf?f?8 f?^f?%f?Ɋ1f?z=f?~eJf?8Vf?rDcf?of?V g#|f?ᒈf?$[f?r/qf?:O᭘f?0FPf?QCƚf?\/ӛf?Lh7ߜf?sf? +~f?hf?ȕ]f?&f?<*f?䷍6f?BCf?΁Of?[f?`uihf?tf?iHf?|䷍f?^'f?:ؖf?)Rf?4uf?V@F˰f?KTرf?W:f?rb3f?m.f?0y f?"f?"f?La/f?;f? @Hf?jTf?af?&xmf?yf?lmf?Dܒf?aLf? ۻf?`U+f?#Ϛf?/I f?|:yf?E=f?:QXf?\1f?g7f?Vs%f?~(f?4f?t@f?Ҡ eMf?2Yf?Dff?{rf?N"f?of? f?jcqf?f?(XPf?ҿf?L/f?D)ƞf?4@f?@}f?`K4f?V\f?b( f?~m;-f?x9f?<Ff?Rf?^f?Xikf?~wf?Gf?trf?&f?2ff?f?Zuf?Nf? OTf? f?l#C3f?.f?(:7 f?Ef?P+%f?F\`2f?g>f?s?Kf?b~Wf?df? pf?~|g?ޫlg?4`5;g?(Ag?Jg?g?Vs@g?vaAg?llBg?4xܘCg?~KDg?Eg?Rr*Fg?Gg?f Hg?nxIg?ZJg?,WKg?NMg?6Ng?HB!Og?.Pg? 7:Qg?dFRg?"+dSSg?"._Tg?9ClUg?DxVg?>P"Wg?[Xg?fYg?\rpZg?}߶[g?uO\g?x]g?֟i.^g?6_g?] `g?|bg?RQ cg?[dg?E&eg?n:3fg?9?gg?,Lhg?.Xig?djg?H("hqkg?3}lg??Gmg?fJng?U &og?"apg?lqg?wxtrg?@sg?lStg?ug?\`2vg?ڡxg?Tyg?x΀zg?H+{g?6_8|g?Q~g?R1]g? jg?%vg?p"g?-lg?.9ۛg?D Kg?Og?J[*g?f{͈g?rډg?f}oxg?Ĉg?$cWg? g?W6g?@ѥ$g?K1g?ń=g?\?Ig?cVg?3bg?zBog?({g?8!g?g?'g?T3pg?>߹g?JOƝg?pU~Ҟg?`-ߟg?.lrg?w g?f|g?Jg?Z[g?)g?hN:6g?ƻȩBg?&BOg?Ҽ[g?6gg?Bgtg?*׀g?Fg?^ g?%g?"g?z-g?8t˳g?8D״g?ORg?Zug?Vf1g?qi g?}g?r]"g?Г.g?0Q_;g?Gg?E>Tg?L`g?9mg? سyg?h-g?kg?&!۞g?Jg?g?B)g?' g?3g?`>wg?Ixg?UVg?|`lg?k5g?:w`'g?4g?T@g?VLg?HcYg?eg?rrg?jI%g?Tf1g?(`^>g?kZJg?v=Wh?DNch?ph?B|h?`h?6kh?ڡh?~*Jh?Ѥh?<) h?蘘 h? h?Xw h?  h?Vh?t!h?,u5h?28*h?Ci7h?NCh?NZ]Oh?eb\h? qQhh?j|Auh?ʇEh?( h?9h?橳h?F-oh?޿h?!Nh?bכ h?-!h? "h?~ #h?{ %h?<&h?xZ#'h?&/(h?X2l9<)h?=H*h?I`U+h?vTڇa,h?_Tm-h?2kfz.h?vHֆ/h?E0h?P<1h?$2h? 03h?l4h?ʺ$s5h?*ƞ6h?R7h?ܒ8h?F 1:h?;h?h? !o^A?h?,M@h?7c=ZAh?vn^h?6_h?M`h?Z*ah?,bh?ch?v eh?{ fh?4ьgh?Z&hh?2ih?R8?jh?tKkh? Xlh?nidmh? pnh?,,]f}oh?7Չph?BQEqh?HN˴rh?YE$sh?eth?dp9uh?{rvh?"-wh?Qxh?!yh?>0{h?|h?}h?\ +~h?փ7h?]Dh?xwPh?<]h?6lih?vh?`h?R&h?1Tjh?=٧h?nHHIh?S¸h?,_<(͋h?jٌh?u0h?Hvh?$h?U h?fh?Į4$h?" 0h?ņ=h?Ih?@zUh?abh?nnh?\@{h? ch?h?x Wh?+h?67Knh?BŠh?M?Mҡh?RYޢh?d3,h?ph?p{' h?Άzh?,h?Y)h?5h?J8Bh?Nh?}[h?fgh?qsh?$eh?eՌh?Dh?@Zh?#h?%Nh?\1˶h?i??i?<(@i?D}4Ai?0@Bi?%\MCi?b0$YDi?;;fEi?GrFi?~RGi?] Hi?3-Vi? 9Wi?l3FXi?RYi?('^Zi?*`k[i?5w\i?FA?]i?L^i?X_i?bc`i?n}ai? zlbi?~qci?ސKdi?mi?457Kni?Woi? *dpi?Ppqi?$|ri?0dsi?l;ԕti?FCui?*Rvi?]"wi?hxi?Fttyi?pzi?h{i?bO|i?¡\~i? .i?Pi? +i?>D}7i?ھCi?8\Pi?Z\i?,;ii?ui?v!i?i?4*i?5hi?@ سi?PLGi?W̎i?cw&ُi?lni?yki?*ti?_ i?Si?HS#i?20i?G$?i? i?i?Z$i?/ i?;lţi?xFѤi?QzKޥi?4]i?hn*i?si?Rb i?xi?V(i?nW5i?̬JAi?,6Ni?>Zi?θgi?H2si?i?&di?dӘi?Ci?"i?"i?)ʹi?>5׺i?@}pi?Ki?\WqOi?bi?ne.i?xyߝ!i?քY .i?6|:i?MFi?[Si?RA_i?:li?5xi?nԯi?)i?,i?hi?׶i?H Gi?i?$&i?f/i?:i?$Ftti?Q i?\hSi?@h&i?s\23i?~֡?i?\PLi?ʀXi?Ddi?x_qi?ط8}i?6ò>i?,i?٦i?T i?i?li?pi? Ki?.i?))i?4wi?J@i?Kkxi?W+i?fb_W8i?mDi?$yS6Qi?ͥ]i?Gji?@vi?;i?ci?^/ӛi?ȩBi?#i?zߝ!i?i?8i? pi? i?TOi?#z j?/-j?p:n$j?E 1j?.Qb|=j?\Ij?gV[Vj?Jsbj?~J:oj?ĩ{ j?h> j?Ơ j?$2 j?g j?&׹j?BΠFj?j?%j?^j?j?tj?z}j?Rj?8)q)j?416j??eBj?TKOj?VY[j?bgj?rmM_tj?x΀j?0A> j?!j?5"j?L#j?)$j? k%j?h&j?ӗJ'j?&(j?))j? +j?B,j? w"-j?t..j?^#V;/j?.hG0j?:5T1j?|E\`2j?Pm3j?:\Py4j?g5j?rDc6j?V~Ҟ7j?8B8j?9j?r,!:j?ҫ;j?0 j?LَN@j?Aj? -Bj?h'Cj?w 4Dj?&{@Ej?kLFj?(ZYGj?D4_eHj??9rIj?KS~Jj?`VKj?aGLj?mMj?|x;gNj?܃ּOj?:/FPj?Qj?#%Rj?VSj?Tj?ȑsVj?t Wj?ޅR Xj?0,Yj?y19Zj?E[j?N nR\j?^]j? #bj^j?j.^w_j?9V΃`j?(E=aj?PJbj?[cj?Dg>dj?rej?~2kfj?`gj?&Jhj?ij?~)kj?ܶ lj?:mj?͈w%nj?1oj?X|V>pj?Jqj?p5Wrj?tcsj?eptj?2߃|uj?(Yvj?3bwj?N?Mҡxj?JAyj? VAzj?ja {j?l5|j?(x}j?)o~j?掣j?DNj?j?-j?b*j? 7j? {Cj?~Oj?sZ\j?jѧj?ZJ;ݨj?UIj?a/j?vl(j?w#j?4j?w(j?4j?P VAj?Mj?4Zj?lyfj?sj?*mj?j?abj?FѤj? VAj?аj?d"J ʼj?-ďֽj? 9>j?Dnj?O2j?>[Mj?f&j?q,!j?Z}-j? :j?{Fj?vRj?֪Z_j?4|kj?8xj?pj?Pj?dj?j?nXfj?j?,MEj?Ǵj?'A$j?H3j?>5j?Jr j?dU)j?`Q&j?"l2j?w0?j?Kj?>Xj?dj?pj?Z]}j?s͉j?0k?I# =k?UzIk?p`U k?kYb k?,w n k?8{ k? k?Jyk?k?mk?fek?ak?$Dk?Uk?#k?@Ik?k? >rk?\k?!2Q)k?-5k?z8&0Bk?CNk?6O[k?Z~g k?es!k?Tq]"k?|͌#k?|<$k?p%k?Ξp&k?.ꊾ'k?d(k?i)k?JX*k?H+k?L,k?f' .k?@/k?$"0k?5v.1k?:2k?@')UG3k?2S4k?=4`5k?^Il6k?Ty7k?`8k?zk9k?va:k?8Ъ;k?s@k??k?[@k?pmAk?OCk?.LDk?CEk?+'Fk?L73Gk? @Hk?,zLIk?h!XJk?, YeKk?&8qLk?C8~Mk?NNk?BZOk?ePk?qQk?^|veRk?Sk?jDTk?zUk?ک^#Vk?8ؒWk?RYk?qZk?VF[k?P,\k?:8]k?r/E^k?/Q_k?0^`k?#~jak?&vbk?L2]ck?=̏dk? I k?b{.Kk?†LWk? dk?@}pk?ި|k?<4\k?˕k?(;k?Z֢k?k?행k?vk?hk?4k?Gk?%k?P1s&k?<k?Hg+k?lSt7k?^[Ck?*jSPk?uO\k?2ik?FCuk?k?7k?dk?¹+`k?"ťϳk??k?ۙl?>l?l?l?Z ll? l? vKl?v+#l?6j*0 l?4B< l?M^ I l?XxU l?RdRa l?oWnl?{Fzl?n6l?̑:l?,l?.l?골l?H"dl?ʜl?Cl?dᐲl? "l?"l?l?ypl?>(l?%mO5l?0A l?\l?4϶?l?x>@l?؜(Al?6Bl?Cl?Dl?RlFl?Պ Gl?KHl?p~&Il?)3Jl?.s?Kl?LLl?gxXMl?J%dNl?0[WqOl?<}Pl?fGO6Ql?RɥRl?$^CSl?iTl?t7Ul?@cVl?+Wl?BXl?\Yl?!Zl?\l?zč]l?p^l?8ہ+_l?N8`l?uDal?T-Qbl?j]cl? jdl?p^|vel?*fl?.6R[gl?Aʛhl?LF:il?JXjl?c:kl?oll?fz.ml?ƅgnl?$"ol?Fpl? rl?B%sl? $tl?Ʉ1ul?^s=vl?xIwl?RVxl?zlbyl?1ozl?8a{{l?|l?$U}l?T0~l?;I_l?Gιl?rR=>Ɓl?]҂l?.i1߃l?tl?%l?Lkl?l? Jl?h )l?Ƹ)6l?&Bl?{Ol?w[l?Bogl?Vtl?cƀl?^5l?Xl?l?|*Ll?5l?8A@c˗l?Lטl?W4Bl?Vcl?n(!l?z l?rl?Аo"l?0.l?N;l?Gl?L~-Tl?`l? r ml?h{yl?f녧l?&Zl?[ʞl? 9l?BOl?$Ĭl?0CЭl?`;ܮl?F7gl?Rl?|]+Fl?hl?:t%l?'l?4l?Vs@l?Ll?RYl?rel?u1rl?0~l?il?l?N]l?^l? Rμl?j=l?Fl?(*l?5:l?@l?DL.kl?Wl?c"J l?`n,l?y)9l?El?| Rl?ܛw^l?:jl?xVwl?Ńl?Xl5l?検l?`l?tڃl?Tl?2bl? Il?Al?N$=l?/ l? ;1 l?jFl?Q%o%l?(]1l?hN>l?sJl?D -Wl?cl? pl?b{{|l?l?oZl?~ɡl?c9l?<ݨl?Wl?чl?XKl?fl?@l?tEl?)4l?25$l?@(*l?K7l?NWsCl?bOl? nR\l?lyhl?ʄ1ul?*~l?l?rl?Fm?f^m?Ϳm?bZ=m?Ԭm? Nm?~ȋm?Cm?< j m?7 m?#I# m?X/+/ m?:(< m?FHm?vQUm?\wam?4hmm?sVzm?~ņm?P4m?um?m?lim?̷m?*]bm?m?QAm?F˰m?E m?m?b: m?n(!m? .4"m?)MA#m?4"M$m?>@,Z%m?Kf&m?V s'm?Zb {(m?m)m?yY*m?vxɤ+m?֏8,m?4l-m?.m?`/m?P0m?Tf1m?2m?nHE4m?´5m?*<$!6m?-7m? 1:8m?HrF9m?#%R:m?/Q_;m?d:km?\?m?g@m?>s{Am?~]Bm?oCm?ZZ]m?_m?N`m?\am?Bn+bm?߼7cm?x6MDdm?Pem?6+,]fm? igm? vhm?R#zim?.jm?:Ykm?nEɧlm?P8mm?,\nm?guom?rpm?J~iqm?erm?]sm?fD um?īQvm?$#$wm?E0xm?Ϳ=ym?@9rIzm?U{m?-Qb|m?\n}m?"0{~m?m?xm?(~m?64 m??]m?Jńm?TVx<҅m?aކm?mlm?pxm?΃`m?.im?Tm?H)m?JH5m?'Bm?lm?LJ$m?U`m1m? a=m?jlTLJm?wλVm?&H+cm?šom?< |m?Dym?0m?Xm?`$ȭm?Ҟ7m?m?|m? m?:m? em?{m?V"Cm?-om?9"*m?tDc6m?OCm?0[WqOm?f[m?qKPhm?N}ſtm??/n? n?j3n?Ȫ}n?('n?\n?n?Dؕ;n?n? n?` n?~ n?h n?~r"n?'G/n?:3f;n?>&Hn?IZTn?XUan?`Numn?lyn?twBTn?҂Òn?263n?n?*n?Nn?n? ǘ`n?jn?݌?n?(!n?"n?#n?F u'$n?l4%n?"i@&n?b-KM'n?8]Y(n? D*f)n?~OQr*n?Z +n?n?2Ok?n?F>Tw@n?I.An?UHBn?b` Cn?k<}Dn? wEn?~0\Fn?ލGn?<$;Hn?In?Jn?ZLn? Mn?҆hNn?v%On?zG2Pn?4>Qn?n&KRn? WSn?PcdTn?!tpUn?-W|Vn?l8SWn?CKÕXn?*O2Yn?Z?Zn?e[n?Fq3\n?|]n?'`^n?d_n?ž?`n? bn?cn?dn?>*en?}l7fn?Cgn?ZqKPhn?\in?f*ijn?vukn?Z ln?4'xmn?2Nnn?=Won?PIBdzpn?T6qn?`6rn?nksn?v*tn?,un?dvn?蘘 xn?HCyn?#zn?"0{n?dƀ<|n?I}n?"tpU~n?an?hOnn?>zn? ].n?םn?Z!Q n?,|n?8E츆n?xC[Ňn?N9шn?6Z:މn?e-n?pn?R|!n?n?hn?n(n?Ω G5n?,An?%Nn?wZn?Hgn?ktsn?n?f_Sn?˜n?"T2n?Ρn?&Hn?@2€ʝn?=<֞n?H_n?\T0n?_>n?k$n?xvn?؁!n?6-n? l:n?Fn?RKSn?z_n?)ln?pnxn?n?,bxn?睯n?VWn?J ƶn?K6òn?!ťϳn?f,?ܴn?7n?$C3n?Ncn?Y' n?@eBn?p&n?{!3n?\?n?Ln?pXn?z}dn?شNqn?6q}n?-n?en?T n?Y|n?n?pN[n?n?.B:n?&n?16n?J=n?H*n?Tgn?f_+n?jF8n?$vDn?%Qn?]n?@jn?svn?tn?^Rn?h›n?1n?z\n?n?8Pn?n? E_n?Tn? 9>n?, n?p7-n?B$n?.N!0n?Yk=n?dIn?LpJVn?{ bn?)on?h{n?Ɲwn?&wn?kn?Vn?B_ƹn?5n?Sn?^n?Gn?n?z o? o?3g"o?` .o?+'F;o?7Go?|B%To?M`o?:Ymo?dsyo?oo?V{}Ro?o?q1o?r렷o?Ҩeo?0o?Y o?^!o?LM"o?=$o? A%o?j&o?6''o?(3(o?*k@)o?%L*o?D1JY+o?o?N -E?o?Q@o? !o^Ao?j+jBo?6NwCo?(BDo?M -Eo?XFo?Dd Go?ow{Ho?{Io?`kZJo?Ko?_9Lo?~٨Mo?ܳSOo?<͇ Po?GQo?f%Ro?X;1So?E>To?/JUo?t$WVo?$cWo?2pXo?%s|Yo?0Zo?N< R[o?G\o? S1]o?l^z^o?i_o?(un`o?ao?b^bo?Fco?V=eo?Ьfo?bJgo?ċ*ho? >6io?~۸jCjo?2Oko?Xko?c<o?n_o?Zz!o?S-o?9o?vGjFo?֧Ro?4;I_o?ko?/(xo?Rթo?#o?vo?n橳o?Uo?, µo?4϶o?$۷o?H0zo?;o?Gno?dRa o?]bo?"i@&o?tV2o??o?>JKo?Wo?>ndo?\po?2M}o?Ĭo?x&,o?ڠo?6 o?zo?o?RYo?o?}8o?n*o?5qo?,Ao?Leo?We+o?HcY7o?nDDo?zMPo?f#]o?ĐAio?$vo?5ro?ಯo?@)Qo?ɣo?0o?\o?o?~o?xo? ]o?6o?$t< o?/o?R;h$o?F0o?R\gz*p?l~+p?r;+p?Lx!%,p?}Y,p?r1-p?[/ɷ-p? >.p?8.p?ifpJ/p?#/p?ȥV0p?w0p?'ZOc1p?ֶ1p?Ծo2p?5‘2p?N.|3p? f4p?Cȝ4p?؅5p?B 5p?QD6p?|6p?y'7p?`67p?#48p?[8p?nn@9p? +9p?M:p?|::p?,brY;p?";p?(ep?D?p?JJ0?p?VPh@p?Vğ@p?[Ap?ea>Ap?gF*Bp?l~Bp?sru6Cp?"x2Cp?}%CDp?]Dp?1iOEp?&Ep?\Fp??Rp?"YvwSp?a(Sp?.Tp?3 Up?o9MUUp?? Vp?DĜVp?}J"Wp?,PA4Wp?Uk/Xp?[Xp?;ax;Yp?f5Yp?lJHZp?IrZp?wlT[p?})[p?W)a\p?a\p?`m]p?f]p?z^p?ğ@_p?tTx_p?# `p?Ӱ`p?ap?2HWap?%bp?ƫbp?@1cp?<6cp?m>dp?N޶dp?sJep?0ep?\LWfp? fp?gcgp?k%gp?+php? chp?y\|ip?(jp? jp?"Bkp?7(Pzkp?- lp?3lp?E9!(mp?>DYmp?D4np?SJȺnp?P{Aop?U88op?a[oMpp?app?foYqp?pl,qp?rNfrp?wrp?~}crsp?- sp?݈-tp?eup?~%Fp?zD;]̅p?)JRp?O؆p?Ur_p?7[/p?uzp?Y餭p?a冕p? p?gTp?p?Vğp?v %p?%3p?k2p?Jp?3">p?'Śp?-JKp?B3>ћp?8Wp?>ݜp?PDu)dp?I2ap?Opp?^Up? [i}p?`&@p?lfwp?lp?q]畡p?{wp?*}Vp?ق(p?QƮp?84p?5p?mAp?GEǥp?Mp?Ԧp?U|LZp?9p?fp?cp?p+sp?-cp?qp?!اp?d p?!Bp?/yp?p?X餭p?=!+p?Xp?7p?L MȽp? Dp?7ʰp?ZoPp? "Aֱp?'\p?h-p?3xNip?85p?v>up?&Dp?Il-p?O)ep?4U朎p?Zp?`` p?BfD!p?k{p?q-p?QwT볹p?}#:p?Zp?_Fp?H̻p?Sp?m9ټp?q_p?̤-zp?2p?8oRp?L>, p?Cp?Ip?[Oc1p? U i&p?Zݠp?i`2p?fWp?kH?p?wqp?'wKp?|Kp?'Xp?5^p?䍂dp??p?Cqp?=p?vu}p?R3p?p?p?`jTp?'p?âp?n̡(p?^3p?k5p?|آp?,Ap?Rp?JNp?:́p?Zp?Fp?H)gp? `p?~sp?W;p?p?!?p?e'rwp?-/p?2p?s8p?#>fVp?C#+p?Iűp?1O7p?TZ5p?ZmDp??`Ԥp?ePp?kNp?Mq L]p?vȃp?|ip?\Bp? *vp?bp?jyp?6p?ɞ p?xAp?(myp?ׯ*!p?p?6 .p?aXp?:p?Dp?јFp?U7p?RoSp?Ϧp?_p?aIp?Nlp?Åp?oxp?>p? ,p?}d p?-up?2p?! p?;'C$p?,i{p?2&0p?I8p?="=p?C]Zp?WIIp?Op?TVp?fZQ9p?`qbp?e˨p?tknp?#qEp?vP{q?|q?2|q?9 q?.q?@fq?pq?-&q?N q?E3q?d}q?\!?q? q?$Lq?kX\q?Xq?q?y׏e q?(L; q? sq q?ƪ q?7} q?@ q?Q q?E q?x q? 5q?S0q?h)q?lq?b!)5q?'q?,GBq?p2`q?8Nq?=q?~C&[q?-IT^q?Ngq?Tq?q?^8>q?!pe?q?&Z?q?l,q@q?2@q?7O~Aq?{=NBq?*C Bq?HCq?N.Cq?8TBfDq?YDq?_)Eq?Gey Eq?j6E6Fq?p|Fq?UvBGq?|mGq?*$OHq?c[Hq?[Iq?’aIq?rhJq?!:Jq?УrtKq?UKq?/Lq?ߴMq?QMq?>INq?Nq?Oq?Lр0Oq?=h,Pq?Pq?Z8Qq? tQq?1GERq?h~Rq?QSq?hSq?w&&^Tq?& ]Tq?jUq?]Uq?4wVq? cq?Vvcq?Ldq? dq?d%eq?Ueq?@1fq?rķfq?"Ѻ=gq?w4gq?4lJhq?0hq?Viq?kiq?>(Kcjq?jq?okq?M`kq? *|lq?amq?[mq? Tnq?  nq?i&@oq?,xoq?1H'pq?w7pq?'=4qq?BWqq?H<@rq?5Nrq?SLsq?Ys6sq?C_0nYtq?dtq?jeuq?Rpguq?v$Mrvq?{vq?`~wq?[xq?,xq?ncyq?yq?͝Ozq?| zq?,B*{q?ۮz{q?C6|q?:|q?꿽!C}q?zY}q?H7O~q?~q?ֱ\q?Wn8q?+phq?q?etq?bq?Oq?s܆q?#q? Wq?.q?1e q?q? K,q??& q?+D9q?1|q?N7?Eq?<ˈq?B#Rq?\Hv[؉q? N3^q?Sq?jYkq?_j:q?d'rwq?xjq?(pჍq?u^ q?{Qq?6؈q?冕q?R"q?D0q?g/q?q?SF;q?’q?FHq?a}~Γq?:Tq?ڔq?oŴ%aq?q]q?.mq?}q?-ܨzq?e<q?"tq?;߫ q?㒙q?Yq?ISq?Ԋ%q? «q?XN1q? 2q?i>q?f ĝq?&BJq?+ўq?t1HWq?$7yݟq?<6cq?Bq?2H'pq?Mm_q?S*|q?@Yq?^q?da>q?Njvq?oۭq?u塥q?]{U(q? Uq?ό4q?kĺq?I@q?ʗ4Ǩq?ykMq?)өq?ب=Yq?q?7Jfq?tq?1rq?Eq?ʫ)q?haq?S%q?q?q?b\@q?xq?֯*q?p簱q?P7q?Wq?~ ˎCq?.ɳq?EOq?6ִq?< m\q?%|q?+9hq?J1q?6Luq?q?iq?oOFKq?Yu ~q? {ɵWq?q?hC%dq?]q?Ƒpq?vzq?%7}q?բ;q?sq?4nq?+q?q?BRq?b(q?®q?P4q?֙1q?ViAq?^q?Mq?q?mJHZq?q?ķfq?{q?* ?'sq?^q?q?9vq?3q?%=q?G+uq?0jq?6'q?U<+q?BTq?G^7q?cMĽq?SCq?X3q?r^RkPq?!dq?i\q?oq?/uFJiq?zq?uq?>}q?:)q?`q?Lq?qq?.q?Z?!q? wq?e-q?h"q?:q?ĜVq?wYFq?&q?Rq?ې5q?4Mm_q? q?kq?Cq?ALxq?q?Qq? y q?6+q?_bq?q?m#q?n%* q?+A0q?0yq?|6ar?2y>r?t??r?$?r?j L@r?'X@r?2XAr?Ar?^dBr?@7Br?$nqCr?*Cr?O0R}Dr?5Er?;MEr?]AFr? GFFr?LGr?kR,Gr?X}d)Hr?]:Hr?yc5Ir?)i Ir?nqCBJr?t.{Jr?7zNKr?Kr?e"[Lr?E"ZLr?ߑgMr?Mr?TYtNr?9Nr?pOr?bPr?MPr? Qr?pOQr? ĄRr?ARr?~+Sr?.ջ.Sr?xf8Tr?5Tr?LYr?Qnjr?W+r?L]wr?b8r?hbpr?Zn r? tߏr?yr?iVOr?"r?NJоr?w.r?&J.r?֛f;r?ĝr?5Gr?> Ζr?DTr?C|ڗr?u`r?2r?Q#mr?Ϭ[r?iyr?_&r?r?: r?n]rr?r?ឝr?|%r?+RQr?1r? r?:=r?F0Ġr?hJr?H$Сr?)}Vr?/:ݢr?V5Fcr?;~r?@qor?dF.r?L%|r?Q]r?sWer?"]"r?br?h<r?0nYtr?s'r?y㭩r??4r?MSr? @r?Mƫr?Lr?A2Ӭr?[iYr? ߭r?xer?i5r?Hrr?Ƚr?xl~r?')r?'r?ԣ_r?5`r?r?r?D>*r?Tvr?6r?R張r?Cr?IUɶr?` Or?շr?[r?o=4r?$khr?)r?}/ttr?,51r?:Jr?@r?;Fhr?K%r?Q)r?IWa r?\\r?b,r?Whr?n@9r?sPxr?ey Er?r?ĄRr?tDWr?#^r?ҕr?{jr?186r?mwr?r?@o݃r?, r?Lr?Nær?cr? "r?\+r? ښc/r?Wr?j;r? r?BHr?yKzr?(Tr?r?!ar?6 @Yr?mr?r?Ewzr?#48r?)or?S/ r?5kߒr?:(r?a@Nr?F%r?K_r?oQ1r?W-r?\e>r?~bSr?-hJr?m r?sDWr?;yG|r?~cr?r?J~#pr?;[r?|r?Xr?rr?/:r?fqr?r?ŷfr?t#(r?$Pr?ȝ4r?Zr?2@r?/r?ߑgMr?@Nr? Yr?r?OFfr?B~r?rr?]r? z%r?7]r?kr?r?#nr?y)+<r?)/sr?4*r?:br?7@7r?ERr?KCr?EQVr?VOr?\1r?Tbi\r?hJr?mhr?bsr?yHur?~>r?pr? r?Ϗu'r?2_r?.r?ݠ r?ir?<&>-r?ur?9r?K]r?Fr?Tr?YΔRr?Qr?^r?g3r?kkr?Er?uwr?%r?|Jr?: r?3r? r?q)r?A.a#r?똩r?#/s?P)es?."@<s?4ws?^:Hs? @Ys?EUs?lKVs?Qas?VMs?z\ ms?*b5s?gmzs?mAs?8s܆s?x s?~xLs?F5 s? s?% s?Ul+ s?)c2 s?暸 s?c> s?` s?±BK s?qy s?!Ws?Ts?!ds?/Xs?Ӌps?Hs?=}s?7s?os?K<s?ޕs?s?ZtNs? 1(s? s?h4s?h-s?%eAs?v#s?&)Ms?.\ s?4DZs?4:{s??fs?EPs?BK #ss?PZs?Vs?P\Ds?bs?g9s?_m{qs?s8s?xs?m~+ s?oP s?̉,7!s?{鿽!s?+C"s?ښc/"s? gP#s?9ݞ#s?諚\$s?W$s?GFi%s?}%s?Žu&s?UK&s?%'s?\(s?dق(s??)s?)s?r;!*s?!vs*s?3-+s?+s?0:,s?kR,s? (F-s?>-s?R.s?_1.s?L#i_/s?(٠/s?.k0s?[4S0s? :Hx1s??1s?iE2s?KG 3s?P'3s?wV^4s?&\~4s?a;#5s?g5s?5m=06s?rru6s?x/<7s?C~7s?I8s?fT8s?Q#U9s?9s?a:s?`Z3:s?kn;s?Ԣ;s?nzs?,ȅ>s?B?s?(?s?:ټ`&@s?y@s?62As?HAs???Bs?mwBs?V*KCs?Cs?XDs?e bVDs?dEs?Es?spFs?"#V5Fs?(m}Gs?.ФHs?14܉Hs?9JIs??LIs??EăJs?JJs?P>(Ks?MV*Ks?[b5Ls?auLs?[g2AMs? m Ms?rANNs?jxiyNs?~&ZOs?ȃOs?x gPs?']XPs?הsQs?Qs?6Rs?Q7Ss?oSs?D˦Ts?ޘTs?EUs?RNUs?ȿ+Vs?|Vs?`97Ws?,Ws?޳dDXs?opXs?-PYs? Ys?}C]Zs?,d{Zs?"i[s?[s?; "v\s?YZ\s?]s?I^s?"^s?(M9_s?W. q_s?4Ǩ!`s?9`s?e?A.as?EOas?J:bs?tPxbs?#V5Fcs?[.cs?afSds?1glds?l)_es?r es?@xElfs?}`}fs?xgs?Ngs?$hs?T\ is?\is? js?js?kH;$ks?sks?ɶª0ls?yls?(<=ms?Qms?ͶIns?6sns?0Uos?0os?Ehbps?gps?$nqs?Sqs?G{rs?\ss?ass? ts?&ts?pP^us? us?"&vs?~(vs?-.D=3ws?3uws?9?xs?fVs?*(ܥs?-bs?3u s?892Eos?>|s?D{s?FJis?O&$s?U[s?U[s?a]s?fs?cl:'s?rrs?wQ3s?q}⹭s?!@s?ЈQƮs?ELs?/үs?ޙXs?|0߰s?=9hes?s?qs?Lps?-G~s?~s?Zǧs? ds?!&s?h]s?ޛs?X)s?vs?&<6s?ts?LBs?4 ȹs?Os? Sպs?BA[s?s?gs?Q"x2s?(5jts?-s?_3ـs?9ls?>)Is?mDs?Js?O`s?{U(s?+[_,s?`s?fT8s?9ls?q>Es?wvs?G}HQs?s?^s?VUs?*s?a;s?㒙s?LOGs? s?@Ts?[xs? D`s?s?i ms?{Ws?8ys?ws?'"s?'o6 s?-,ns?53s?8ݞs?>c%s?CD Ms?I݄1s?Os?QUW=s?[,s?`cJs?`fs?lKVs?q s?nwBcs?}zs?͂?os?|s?,!|s?ۓvYs?3s?:s?餭s?j8s?H'ps?'s?߭s?V^4s?Os?؆@s?eҕs?RLs?.s?seYs?"鉝s?Fes? s?1Drs?}|s?;~s?? s?#s?r[s?M/s?!s?'s?\-f:*s? 3#rs?86s?j>s?DZCs?IQs?xOԈOs?'Us?ZN[s?` 0s?6fghs?ks?qBts?Dws?|Fs?y~s?R6s?s?%s?am] s?*s?,s?os?a<9s?εts?}۫Es?-s?URs?Ss?;ϊ^s?׌s?Ijs?I2s?iws?s?W=كs? t?Ht?fut? 2t?"t?t't?#i_/t?!&t?';t?2-t?2]>Ht?8vt?@>׭Tt?Ct?IQat?NOUt?Tˌmt?Zt?\`Ey t? f4 t?kk t?kq| t?w9ے t?| t?yJ t?(p% t?؍- t?1t?7)t?da>t?!t?EJt?t?X@Wt?Sxt?үct?Ət?aLpt? Wt?Ǝ|t?p݃t?@t?5t?~mt?-wt?4ݡt?(t?<Lt? l4t?)t?J@t?+t?!`cMt?X't?-Yt?2 t?f8TBft?>zt?Cαrt?uIt?$OH!t?TY t?Z t?2`!t?e<!t?k7"t?Aqo"t?vs*#t?|0߰#t?O7$t?N$t?gC%t?]$%t? O&t?-&t?l[e\'t?'t?ʯh(t?z (t?)ODu)t? |)t?ɳ*t?8̆+t?C#+t?[,t?Fݽ,t?z -t?7-t?T9-.t?q.t?n9/t?b+/t?F0t? P0t?qcR1t?  1t?^2t?!/2t?.'Wgk3t?,3t?2w4t?=84t?=KF5t?C~ 6t?KIŵ6t?N7t?T?%7t?YZ\#8t? `8t?ev/9t?gk39t?q;<:t?vs:t?v|jH;t?%';t?ԇUt?B1>t?Riz?t?@t?P؆@t? At?FHAt?^Bt?Bt?}%Ct?l:'Ct?^2Dt?ⴖDt?{q>Et?*.Et?=KFt?uFt?8eWGt?#Gt? dHt?GTHt?ZpIt?It?U!|Jt?'3Kt?,NkKt?c2 Lt?8ڕLt?=Mt?qCBJMt?!I(Nt?NNt?Ty4Ot?/Z6)Ot?_`APt?ePt?=kmMQt?p*Qt?v?ZRt?L|wRt?afSt?St?ZsTt? VTt?UUt?hVt?Vt?ǩ5Wt?vImWt?&Xt?պܤXt?+Yt?4=LYt?7Zt?ѷZt?BtC[t?1+[t?bP\t?Q諚\t?h\]t?% ]t?_Ai^t?y^t?]u_t?m _t? `t?Xat?|Qat?+!bt?&bt?,7!ct?92Eoct?7-dt?=޳dt?HC|:et?H9Net?NFft?VTft?ZpRgt?_--gt?ded_ht?kht?pdkit?rv! it?"|Cxjt?с{jt?Xkt?0 lt?ߒ"lt?Zmt?>Lmt? #nt?nt?M90ot?@qot? t?B~t?zt?r vt?!3t?!t?Yt?/ jt?%')t?+t?>186t?6^pt?<Bt?LBt?GOt?MROt?ZS[t? Y̾t?^gt?hdF.t?jftt?ot?wu}Հt?&{: t?րDt?|t?4qt?.t?#t?C[,t?et?"8t?Qt?:Et?Yrt?_Qt?t?ʐ^t?mMQt? ju?u?|vu?+A0u?gu? u?9x׏u?5u?Fu?H ~"u?mu?*.u?V%u? ];u?%au?d+Gu?1u?6d u?i=2 u?oiu?Muu?ztٞu?1%u?[Hu? 1u?hu?i%=u?'u?Ȣ_Ju?x\u?'Vu?ֳu?>cu?5Pvu? ou?u?CЇ|u?DUu?u?Ru?{u?84u?`ku?'u?oۭu?n-4u? Ju?@u?}du?,!Lu?)u?%aYu?:+Xu?0e u?6 u?I<@r!u?ALx!u?G ~"u?WM#u?S#u?X@W$u?e^$u?d%u?iw%u?so46*&u?#um&u?z6'u?kݼ'u?1(C(u?L(u?O)u??_)u?[*u?+*u?Nch+u?S+u?t,u?\ ,u? B-u?Gz.u?j.u?/u?~!/u?x;Y 0u?(0u?,1u?r1u?6/892u?o2u?E3u?Dg3u?$R4u?N4u?S^5u?[5u?j6u?a%-6u?+ew7u?0O7u?o6 Ճ8u?< 9u?AD9u?}GC|:u?-M:u?R";u?Xz#;u?;^7[/u?zq>u?XT?u?b?u?a@u?fP@u?mAu?ŜVAu?tyBu?$/Cu?ӭgCu?J Du?2גDu?Eu?āFEu?@>~%Fu?Fu?ո1Gu?Nu%Gu?2]>Hu?Hu?]JIu? iIu?&fVu?.uVu?݅rWu?YWu?<Xu?TYu?Yu?JMZu? Zu?3[u?Yk[u?A*\u?ڰ\u?gĻ7]u?xJ]u?5C^u?u^u?$ۯO_u?l)_u?)a\`u?3`u?hau?`au?A@ubu?wbu?cu?OUdu?du?Veu?^eu? %I fu?*fu?l05-gu?6mgu?;=9hu?zAܿhu?*GFiu?LtLiu?R1Rju?8Xju?]^ku?ch+ku?Fi%cklu?nlu?twmu?Tz\ mu?Bnu?y ou?cou?Ppu? !pu?qX#qu? qu?ЧD/ru?ru?/7~u?B0~u?59Ku?;wqu?PA4Wu?G݀u?Ldu?^RkPu?X(pu?]u?mc|u?i_/u?ngu?{tٞu?*z֕u?Su?Fu?9}(u?萊u?G4u?G%u?\Au?~lju?U;Mu?Ԋu?;Zu?crsu?/fu?u?rϩsu?!fRu?#u?u?/u?Z1u?iu?>Ԡu?ؤu?O+u?L Hu? 7u?u?ZCCu? 'ʔu?$^Pu?i*z֕u?07\u?5u?w;=iu?&Anuu?F+uu?Lu?5Ru?WbTu?]u?Ccu?hu?nV3!u?Qtku?zТ-u?ڳu?_J:u?Ju?āFu?n̟u?>Ru?̡(٠u?|`_u?+uu?۲2ku?u?:?xu?iwu?&u?H u?Ԡu?]Vu?Vu?#u?u?dQ50u?mu?ˤdu?su?Yyӌu?u u?2Cu?gzu?u?ƕi+u?u&"u?%Y8u?Ԧu?]Dv?3v?8Qv?pv?AQ]v?v?jv?OԈOv?Evv?v?^v? |. v?9fv?lv?՛v?q "v?z.Ev?* |. v? v?e: v?8"$ v?#[G v?) v?F/YS v?4 v?::` v?U@r v?FMlv?K v?cQyv?WQv?\Av?qb v? hv?mx0v?s5hv?/y$v?~תv?l1v?=)Gv?~=v?v?K`Iv?&v?]Vv?Zv? Tbv?v?h~%v?Ev&v?KD&v?9Q'v?V'v?\{U(v?Gb8(v?g))v?m)v?Uso46*v?y,l*v?~B+v?d+v?cO,v? K,v?r݂[-v?!-v?ѠWg.v?*.v?0at/v?߱/v?Kр0v?> 1v?@1v?Ȃx2v?L?2v?3v?ٹ3v?ZvW,4v? 34v?85v?i5v?j6E6v?'n6v?wQ7v?&7v? _^8v?M8v?5لj9v?9v?#Sv:v?C),:v?.c;v?4 v?Q;>v?V.?v?n\!?v?brY;@v?g/@v?|mGAv?+sAv?xf8TBv?~#pBv?:`Cv?鉝Cv?ZmDv?HODv?ԆyEv?Ev?VNFv? . Gv?eGv?eHv?B՞Hv? %Iv?sȼDIv?"y|1Jv?6Jv?=Kv?0߰#Kv?m[JLv?*Lv??VMv?Mv?a:cNv?MrNv?ܩoOv? Ov?[V|Pv? QQv?ЈQv?j#Rv?)JRv?.0Sv?x4gSv?':'Tv??>׭Tv?E4Uv?6KFUv?Pu~@Vv?V2Vv?D\LWv?a%Wv?gi]YXv?Rm&Xv?seYv?xYv?`~]fv?vgv? ӭgv?1hv?Mhv? U iv?@#njiv?(,jv?.Ajv?N439kv?9kkv??xElv?\E5lv? KRmv?PJmv?jVl^nv?\)nv?ajov?yg)ov?(m`awpv?rpv?xЃqv?6~ rv?T@rv?xsv?Eίsv?"tv?Htv?SW/uv?Žuv?;vv?av?(āv?u.{Jv?$48тv?97Wv??o݃v?2Eocv?J,v?Ppv?@VNv?[c|v?a v?Ogv?l-v?rWev?]xv? ~ԡv? (v?kKDv?|4v?ʔųv?z@v?)?#njv?إZMv?Ӎv?7vYv?3v?9fv?F­qv?jrv?'v?Tv?١Pv?^v?bv?v?/v?pRgv? *v?ְv?7v?. GFv?~Cv?ɗv?<~Ov?";%֘v?(\\v?K.v?3rhv?9/v?Y?;uv?Esv?Jfv?gP#v?Vv?[Rv?uaZv?%g v?lv?r1-v?3xNiv?} 9v?ؿv?AFv?BH̢v?Rv?Pأv?y^v?6'v?^^kv? v?mwv?l*v?=v?Ǥu v?zav?*v?v?ޘT#v?8Uv?/v?v?F3Jۮv?cav?v?"umv?q(2)v?!.`zv?3v?9iІv?/?& v?D?v?Jwv?=P]v?U%v?[v?KaV2v?fQv?l>v?Zrķv? x5Kv?}EmѸv?hWv?ݹv?ǎ|dv?v9Lv?&pv?՟v?p|v?4-+v?bv?v?Bdҕv?! v?Av?P͛y(v?Xv?4v?_ v?XAv?Lv?m Mv?v?7Zv?{Aov?+fv? v?xsv?95Nv?v?"v?G(lv?-)-v?3dv?V9v??`Ԥv?D +v?dJCv?P{7v?UTv?r[Cv?!a"v?fZPv?lHv?0r\v?wv?}9iv?>lv?`DZv?JNv?O gv?oUKv?[sv?`Bv?}fv?,l*v?qybv?w6v?;}јv?ꂰ w?mAw?I*y+w?簱w?7w?Wa w?XDw?ۏw?fPw?Uw?Ļ7]w?tnw?#njiw?Iw?vw?2Mw?݀w?= w?@ w?, w?td w?N1! w?ӧ w? . w?\ iC w? &{: w? w?kFw?"]"w?'ZSw?y-בw?(3_w?8Qw?>9lw?7Dpw?Ixw?OEw?EUw?ZO w?`|w?Sf9w?lw?q.$w?awpfw?}-0w?նw?p =w?dEw?Γ!}Iw?~޴w?-Uw?ݤX$w?\bw?<ғw?뵏nw?Lw?J ;{w?rw?̃w?X@ w?w?ݺQ w?fw w?4&!w?!w?u03"w?$kh"w?(?#w?#w?2 L$w?`G$w?X%w?Aڶ%w?!d&w?'T&&w?O-^q'w?2Ε'w?8}(w?]>H)w? D=)w?It*w?kO*w?U<+w?Z+w?z`S),w?)fs,w?k05-w?q-w?7w2B.w?|gj.w?$N/w?F/w?[0w?[I0w?Tg1w?ո1w?s2w?bO(2w? `3w?ɗ4w?pό4w? C5w??5w?̽v6w?.z6w?7+7w?7w?w?%-K* ?w?2b?w?8ř@w?3>ћ@w?C? "Aw?I@Aw?BOx.Bw?TvBw?Z3:Cw?P`Cw?eWGDw?kjDw?^q'SEw? wEw?|6`Fw?l^nFw?lGw?ˍGw?{yHw?*RMHw?ٞIw?̼ Jw?8Jw?F,Kw?dKw?G$Lw?}ӪLw?: 1Mw?UBMw?Ҵz=Nw?qNw?c.IOw?!Ow?YVPw?qePw?!"bQw?Qw?8oRw?/ZpRw? {Sw?Tw?=Tw?NOUw?! Uw?L'ȾVw?,Vw?2B.'Ww?Z8eWw? >3Xw?CyչXw?hI6 @Yw?ODYw?T|LZw?vZmZw?&`*X[w?e#[w?k[e\w?4qa\w?vq]w?|]w?B:~^w?Ur_w?_w?Q`w?`w?IQaw?_aw?)bw?bw?m=06cw?gcw?Bdw?{tdw?+1Oew?Few?׫~[fw?9hfw?%ggw?%gw?G]thw?\hw?̀iw?Vjw?Ippw?N-^qw?THqw?LZjrw?_drw?e!vsw?[k'sw? q_tw?vX uw?i|Ϗuw?vw?ȇ>vw?wLv"ww?' ww?֘.xw?xw?5@U;yw?yw?Gzw?Cwzw?44T{w?k{w?RƮ`|w?k|w?(m}w?`J}w?ݢy~w?_~w?nw?) w?aw?|Sw?,ўw?%w? @w?:Hx1w?w?=w?H!Ąw?&w?pNu%w?Tw?YU1w?~_w?-eT>w?jĺw?pIJw?w?rw?!V1Kw?пiw?РWw?/ˍw?Jdw?Hw?=pw?ၷw?>|w?L&w?^w?uw?Z2Εw? w? =w?hju(w?'w?4w?w w?&&^TAw?+w?1Mw?47w?Ax?ayFx?x?M Rx?% x?+UX_x?[1x? 7kx?<x?iBI7xx?Hox?Mæx?wS x?'Y=x?^Mx?dx?5jt#x?o1x?u,0x?C{dx?h<x?%x?R Ix?Cx?\{Ux?`x?ax?"x?nPZnx? x?͹z x?|!x?,D9!x?q "x?о"x?:{#x?8#x?O&$x?H粇$x?o2%x?,%x?W.?&x?f&x?dK'x?e !'x? X(x?E(x?sX}d)x?# )x?%p*x?+$*x?11L\}+x?6 ,x?<ˉ,x??B-x?G@;-x?Mr.x?MS.x?Xw(/x?^4/x?\dQ50x? j0x?okA1x?ju(1x?{0N2x?ɀh2x?x_Z3x?(3x?בg4x?G4x?6Ss5x?5x?6x?D&7x?G^7x?8x?S͘8x?~9x?;=9x?at+:x?ֵ:x?r7;x?o/;x?SDx?j>x?; [i?x??x?v@x?II@x?OAx?% Bx?X+Bx?1(Cx?6C`Cx?f<!Dx?BϧDx?Gz.Ex?tM7?Ex?$Sv:Fx?XFx?^nFGx?2d+Gx?iUSHx?oHx?@ub_Ix?zIx?4lJx?NlJx?VxKx?Kx?]Lx? K Mx?JMx?kNx?Nx?ʳ*$Ox?y>bOx?)0Px?ĸѶPx?u =Qx?72AQx?xIRx?۬Rx?EiUSx?& Sx?WbTx?STx?]nUx?Ux?b6{Vx? nWx?RWx?p Xx?Xx?MYx?~%FYx?.+&Zx?0Zx?6},3[x?<<:d[x?A?\x?G\x?JMq L]x?R.C]x?XzX^x?X^^x?ded_x?i""_x?goYq`x?u`x?zY}ax?ubx?$8bx?ԋpcx?Mcx?3 dx?dx?O)ex?AAex?5fx?fx?Ox.Bgx?5fgx?Nhx?]ʯhx? l [ix?)Eix?l|gjx?ᣴjx?`skx?z$kx?)[lx?mx?Tˌmx?8nx?:nx?rox?FIox?+px?px?T%Q8qx?+=qx?0Drx?c6rx?x?v=x?@Çx?{Ix?*%Јx?*wUVx?04܉x?96bx?;x?Ak4ox?GG(lx?L{x?Rx?UX_x?^Kx?cقx?cix?oSx?t*'x?rzax?!3x?хGѹx? @x?/@ƒx?ߖ~xLx?;ғx?>Xx?ߔx?rWex?L/x?qx?x?Zf6~x? #nx?ॊx?h՝x?Zx?Mx?wԄx?&쑼)x?Nx? ,6x?4cx?Bx?Cȝx?C Ox?B՞x?zz[x?Q7x?%gx?*!x?_0nYtx?6+x?;Ȁx?mAx?Gb8x?Lpx?|Rܧx?+Xx?]Vx?cO,x?9iІx?n8x?tJx?Hz.Ex?e˨x?Qx?V>שx? ^x?Dx?du|jx?2x?çvx?s#x?"i[x?Ѹ& x?ʏx?0Ġx?]:x?r"x??שx?ڔ.x?Qx?MQ;x?ˈx?Gx?[Eͳx? 0Tx?gڴx?i}`x?:x?mx?xFx?'q~yx?$.x?*텸x?50% x?5e]x?;"x?DA̞x?F%x?LYx?v@x?έx?sLx?#Hx?UYx?Œx?1ex?x?Zx?Jx?Tx?/Wx?Ngx?b cx?x?ԅpx?pBFx? }|x?張x?~yx?.6%x?\x?x?<n̡x?+(x? ;x?Js4x?bx?@x?Y$x?*RMx?/Vx?g5Yy?;y?@1fy?uFJiy?%Lry?Qy?Wy?3]>Hy?by?hy?Anuy?s2'y?y^y?O*y?iΰy?&7y?^=y? uC y?] y?lO y? y?ˬT\ y?zQ y?*h y?ٽ y?È3u y?8Ek y?y?Կy?F|y?9Jy?y?T볹 y?py?-)-y?c`y?9y?eпy?q "Fy? ?y?wRy?Yy?/$^y?)y?/Vky?=5My?: wy?@y?KF5y?KAm y?Qy?YWy? ]xy?b5L#y?hhy?n/y?sly?vy)+<y?%by?ՄHy?`y?4 U y?A y?ya!y?BT!y?m"y? "y?PXz#y?H$y?Ȇ$y?_ %y?7%y?)y?g)y?9$-K*y?d*y?W+y?G \+y? d,y?C,y?U{p-y?$P-y?) |.y?d/"/y?5Z/y?:D0y?r@ʕ0y?!F1y?K{91y?Q8q(2y?0W2y?\43y?bo3y?>h,PA4y?m4y?sM5y?Lyc5y?~ /Z6y?f6y?Zf7y? W7y?s8y?iE8y?}9y?ǦK:y?w:y?&$;y?ַ\;y??y?>y?߭C?y?Qj?y?'RP@y?@y?_\Ay?^Ay?1iBy?nhBy? uCy?SCy?|Dy?+GEy?#Ey?)GFy?:/Fy?4&!Gy?:~^Gy?H@;-Hy?EͳHy?K:Iy?VQr=Iy?W/uFJy?\Jy?dbRKy?hfKy?m#T_Ly?ssLy?"ykMy?~ZMy?3xNy?0jNy?Oy?N Py?? Py?IQy?Qy?MB#Ry?Ry?(0Sy?[y`Sy? 62^y?4^y?o:*?_y?@ub_y?E2K`y?}K`y?,Q Xay?ViAay?\&ydby?:bby?gpcy?m] cy?IsX}dy?x׏ey?~ljey?WQfy?7fy?ngy?egy?E(hy?Ġhy?tM5iy?#|iy?ұ9Ajy?jy?1,Nky?pdky?-Zly?@ly?ӧ gmy?dCmy?N!{sny?޲ny?oy?\X"py? Zpy?ґqy?jɘqy?Mry? 9ry?yp+sy?(sy?A7ty?#ty?6)ODuy?.xuy?45Pvy?E:vy??.]wy?Elfwy?SK)ixy?Qxy?V vyy?a\`Eyy?b}zy?gڴ{y?om{y?sT$|y?x\|y?~~Γ!}y?-˧}y?݉H.~y?;~y?;r:y?y?Җy?vXy?pvޗy? 3dy?ϫy?Uqy?.jy?ݼ'}y?y?<ȡ4y?^ly?y?Jy?ޕy?RK)y?Yy?̺5y?y?gF*By?bȠy?Ny?u ~ԡy?%; [y?@y?xgy?3#ry?(/sy?.y?A4Wy?9fy??#njy?PEy?J6y?PZny?^Vy? \+y?ay?lgNM8y?m y?rȼDy?zxʫy?*~B,Qy?كc׬y?]y?8yy?6 jy?By?Fzvy?my?*ꂰy?U! y?Yy?ay?cɛy?"y?͘8y?qUp.y?!y?:y?y?/IOGy?Ͷy?þSy?=ٷy?>.`y?ey?K ly?uy?2 yy?ZDy? #|y?(i y?h.&쑼y?4#y?9[y?v?]$y?&E˪y?J1y?P:y?4VQr=y?[y?aIy?Bgy?lEQVy?ry?Pxby?~|y?90oy?_gy?{y?py?m-y?Fy?̥~y?{dy?+!y?ڶ%'y?]y?9X3y?͹y?@y?Gӏ.`)y?3y?9'6y?L?_y?DTBy?Jy?ZPOy? V>y?[Hv[y?iay?ggy?ly?wr z?D/rz?WJgz?PB~z?Uz?e[z?ayFz?f6~z?tl z?#r z?wm%* z?}*] z?16 z?ሤ̼ z?aC z?@< z?sO z? z?NU[z?z?Rhz?\z? Itz?z?j1z?̀iz?=z?yz?(޷z?tH z?1z?6,z?z?h'9z?E&_z?Ez? z?S]Rz?>z?u^z?a"z?(Qjz?-z?p3Twz?9z?>Eăz?~D z?-J3z?O|kz?U9z?<["z?`z?fpJ/ z?Jl- z?q;!z?w!z?X}d)H"z?!a"z?ޘT#z?f#z?Xa$z?ř@$z?uwm%z?$%z?ӪLy&z? 'z?2V'z?⻃ (z?@ƒ(z?A)z?̺5)z?wm%*z?O4*z?1+z?+z?]kL>,z? (,z?J-z?k-z?`+W.z?c.z?z ښc/z?)/z?T p0z?B0z?7"y|1z?'2z?-H2z?F3!3z?8X3z?>4z?TD<ȡ4z?J'5z?O75z?bUso46z?[06z?`@7z?pf7z? lgNM8z?q$8z?wY9z?.}9z?ނ[-f:z?e:z?<՜r;z?쓒;z?O z?YC>z?#?z?Z?z?gz*@z?7ʰ@z?7Az?uұ9Az?%nqCBz?+Bz?OCz?3Cz?bP\Dz?Dz?AܿhEz?Ez?W/uFz?P gFz?ўGz?Hz?^KHz? "FIz?'}Iz?l- Jz?3?Jz?8$-Kz?{>\Kz?*Dv9Lz?I3̿Lz?OFMz?8U;Mz?ZjsRNz?`'Nz?Ff^Oz?kOz?q^RkPz?UwPz?}wQz?Qz?cR1Rz?i Sz?“̠Sz?qTz?!FTz?ФH#Uz?Uz?/}/Vz?޵:Vz?&bz?86bz?Q>(Kcz?D`cz?ImWdz?_O*dz?Udez?Z?ez?m`awpfz?ffz?k|gz?{qhz?+wUVhz?|iz?ŕiz?9jz?I5jz?m(kz?Gäkz?4lz?=lz?VKAmz?mz?tMnz?d1nz?*Zoz?ƫboz?rhfpz?"%pz? sqz?ݟAqz?0\yrz?sz?sz?> tz?PXtz? uz?LǤuz? *vz?E7vz?[o7wz? wz?!|Cxz?i'9xz?-MPyz?2yz?w8p\zz?'>-zz?C,i{z?Id{z?5Odu|z?T!|z?Z }z?C`C~z?eX{~z?kz?Qqz?w"!z?|LZz?` -z?ɳz?:z?n@9z?pFz?̃͞z?|wRz?,4لz?ۯO_z?z?:kkz?(z?.xz?H̢fz?_z? z?V z?Ez?S}z?e#z?쩋z?$0z?sG\z?"z?^~vvz?;z?z?l z?rUz?/z?{ěz?* !z?g4z?$l.z?8ᣴz? :z?&[z?G,KGz?1Ղz?7Sz?U=Oz?C *`z?Haz?cNlz?TCz?Y yz?q_@z?!ezxz?j7 z?pz?/vz?{nWz?+$z?=ƪz?팥0z?b6z?Ln=z?ܥz?Iz?ZVz? MVz?Єz?hbz?Jz?,oz?vcz?&с{z?>z? z?4B{?uz{?2{?B{?!'{?iY{?Q'3{? ȹ{?@{?_^8{?pL{? ا{?m&X{?,R{?1Oe{?|7̆{?+=q{?BF{?H.~ {?9Ne {?S} {?Y: {?G_ {?dD {?jq| {?Vp.) {?v {?{#6{?de[{?"B{?Ì{?rO{?"Y:{?ѝr[{?ө{?0g{?߮M{? Qt{?>Lj{?{?A{?M/{?лg{?x{?[5{? {?F,{?il~{?)8{?{?w%E{?'a]{? Q{?{?5^{?U<{? tj{?C&ϫ{?+v{?1I{?R7S{?=Ê {?B {?`H=!{?N1!{?Si""{?nYt"{?_1.#{?d#{?|jH;${?,ph${?u%G%{?{%{?:'T&{?\_&{?`'{?H'{?m({?P>({?W vy){?ʭ){?*{?eD +{?U+{?Ŀ,{?s{Ğ,{?#8$-{?3-{?ֲk1.{?1o.{?,=/{?/{??JJ0{?c0{? V1{?M1{?)c2{? Xa2{?\o3{? 3{?|4{?j L@5{?& x5{?+Ư6{?x16{?(7@7{?{?oSc>{?~?{?Η@{?} @{?-GBA{?ܨzA{?B{?;~B{?;!*C{?XC{?Iŵ6D{?rȼD{?/CE{?W7E{?ܩoOF{?fF{?f#[G{?G{?NhH{?tZH{?#tI{?I{? -J{?2OeK{? K{?L{?@ L{?%CD M{?+|M{?N1,N{?6zN{?<7#9O{?]BZO{? HEP{?MnP{?kS+RQ{?Y9Q{?^q^R{?ydbR{?)jjS{?oS{?uPwT{?7{VT{?U{? V{?E/V{?JgW{?W{?S"X{?X{?>F/Y{?b}Y{?;Z{?uZ{?p2%H[{?\[{?ʬT\{?~i\{?.&a]{?;]{?sm^{?<]^{?y_{?`{?JR`{?Q a{?’a{?X b{?1b{?Fi%c{?gc{? 1d{?%}d{?u+:H>e{?$1e{?6Jf{?M/{?Rf{?X{?L^S%{?c{?iE2{?Zo}{? uG>{?zě{?h$K{?~\ќ{?Nj;W{?wݝ{?&d{?՜r;{?/sp{?4{?䭩|{?f{?C#R{?{?ĝ{?QZ{?1{?h({?_ۑ{?N4{? {?mGA{?Ǧ{?BM{?|ӧ{?+&Z{?z^{?7f{?9{?s{?n={?H%+u{?*{?0䋬{?V6b{?<T{?A܋{?dGä{?MV*{?R3{?rXj7{?"^{?cJC{?iʱ{?0oIP{?tֲ{?z>\{?>{?(i{?u`{?M2u{?{?{?[i?{? &w{?{?i暸{?]!{?ȾV{?x׍-{?'ʔų{?Q9{?5{?5lF{?̼{?ER{?Cٽ{?K_{?|{?R9k{?{?*x{?`qb{?.{? {?n {?%eA{?*"y{?}0߰#{?,6{?;Y 0{?AX{?:Gӏ<{?L{?RMH{?IX 7{?]nU{?c{?WiAa{?o{?tMn{?ezx{?5z{?ą{?s,{?#ld {?Җ){?{?2 {?`C&{?{{?@ڲ2{?{?T"?{?NZ{?ΑK{?ϋ{?\HX{? 9{?pd{?j{? {?iv{?nr{?bt/{?z${?U{?pf0{? #Ŷ{?ΐ<{?~4{?.ZlI{?ޡ{?U{?<{?NKb{? {?JȺn|?Å|?B*{|?Xa|?ռ|?y |?f6 |?@|?x|?vm&|?$*|?3|?W|?2b?|? |?K|?B6|?VnX |?$ |?P*d |?/ |?5JMq |?^; |? Aļ} |?F |?lL>, |?Rc|?W|?z]u|?*c2 |?hB)|?nz|?8ti5|?y&|?!B|?FY|?]N|?|?T[|?8|?Qpg|?b|?s|?²|?pEO|? |?ÿ|?||?.9.|?e|?ڳ|?P{7|? 8|?8|?L$>9|?)Dv9|?/:|?Z5:|? ;{';|?@8U;|?hF3<|?LĹ<|?Qo?=|?vW,4=|?&]kL>|?b>|?hcX?|?4n ?|?sJe@|?y@|?BWqA|?A|?)~B|?RaC|?KC|?D|?`D|?@E|??xE|?n)F|?F|?̽v6G|?|3WG|?,BH|?έH|?jNI|?:'6I|?m[J|?塥J|?H^gK|?K|?LtL|?VL|?SM|?N|?d +N|?cO|?GO|?rP|?"$ P|?)~B,Q|?/;zQ|?058R|?:R|?@r!ES|?>F/YS|?KQT|?QT|?LWf^U|?\#8U|?bojV|?\hV|? nZvW|?sW|?jyNX|? Y|?ȄNY|?x Z|?(-Z|?֕e"[|?B[|?6.\|?䦼 \|?yD;]|?D6|]|?G^|?^|?Rm#T_|?*[_|?``|?`Ԥ`|?ama|?:a|?nqyb|?똩b|?Uc|?| d|?,Pd|?e|?Je|?: $f|?/f|?g1g|?H>g|?#=h|?)h|?V/uFJi|?52~i|?:Vj|?f@j|?Fi%ck|?K&]k|?tQol|?"Wl|?\]|m|?b<n|?2hsn|?mo|?sQo|?@yp|?~Rp|?'q|?NE­q|?3r|?1r|?\|i@s|? 9s|?Lt|?jt|?pHYu|?ʷ-u|?xev|?(çv|?d'rw|?!_w|?6ޖ~x|?ٛy|?Xy|?D>z|?uz|?{|?RL{|? *||?T||?b6}|? Aļ}|?B~|?p3~|?xkO|?#5|?~)[|?,/|?4lJh|?:)|?<@t|?E|?K`)|?JQa|?Vژ|?\|?XbT|?h@ |?mw|?fs,|?yH粇|?~9|?tV|?$E|?ԏ<ˉ|?Q|?25؊|?sm^|?0|?@j|?|?gLw|?N$|?ể|?Ȟ |?\[+|? c|?՚|?lߒ"|?O |? B/|?zy|?(;|?C|?!H|?8XΔ|? {T|?8ڕ|?F`|?7|?#oom|?T),|?/y|?4|?b:cN|?@ |?Eݽ|?pK|? QW-|?Ve%|?~\ќ|?.b1|?gK |?mD>|?|?м|? K|?0LX|? W|?|?>كc|?@7|?np|?L꺦|?w||?4|?ZM|? |?l|?h )|?,|?d(|?v`|?&#4|?( |?.CA|?44T{|?9M|??|?BE"Z|?JHZ|?Pf|?RV|?\s|?a<9|?`gp|?m|?rs|?nx0|?~O|?̃|?|g|?,$*|?ڔ.|?f7|?:[|?C|? |?HEP|?O}|? \|?V|?Ȇ$i|?C\|?du|?ٽ|?z|?r7;|?"r|?ﱪ|?n|?0+!|?Q|?-|?> c|? 9|?0|?NhF|?"W|?(R|?\.|? 4G_|?9K|?j?k|?E|?J&x|?xP?^|?(V|?[ |?av|?6g3=|?lt|?r#|?Dxj|?}'0|?S|?R<|?^|?H}?`2}?jU}?R}?na}?}?ζIn}?|F}?,z}?}?}(}?::` }?}?޴}?Hq}?.?&}?v}?X2 }?e }?#? }?fU }? K }?Z }?tW }?$4 }?"ld }?(N }?2. p}?3}?9K}}?@?B}?D}?J}?NPy*}?U6b}?[}?\a(}? gm }?l*A5}?jrx}?xA}?}a}?x N}?(W}?؎Z}?U}?6f}?6}?ns}?DI}?}?}?RM}?=}?}?bͷ}?t,}?1d+}?p}?7}?h }?~%CD }?.z }?P!}?]!}?<"]"}? Y"}?i#}?JQ#}?v$}?"8$}?X(p%}?.E&}?3&}?f9'}??|O'}?D9!(}?tJ(}?$P-)}?Up.)}?[-f:*}?2a*}?fF+}?ld +}?@r!ES,}?w|,}?}_-}?NX-}?$l.}?[.}?^x/}? L/}? 0}?l: 1}?r1}?ʰ@2}?z2}?($3}?wQ3}?404}?84}?Ү<5}?k05}?F(hI6}?6}?U7}?T_7}?Gb8}?~8}?bn9}?T9}? &{:}?p];}? ;}?H <}?~"<}?.(<=}?-t=}?3<&>}?<9>}?>3?}?DsS?}?JJ0?@}?O@}?UKA}?X[g2A}?a$jXB}?fB}?hldC}?r[C}?wIqD}?v}ՀD}?$}E}?ԈOF}? (F}?4_G}?♆G}?CH}?BH}?>)I}?zvI}?P75J}?J}?BK}?^nUK}?+NL}?L}?lإZM}?b4M}?lgN}?zܣN}?*sO}?VO}?KP}?8тQ}?Q}? KR}?F*R}?aS}?S}?T"?+T}?(T}?-@8U}?b3vxU}?93DV}?>V}?rDQW}? JjWW}?O']X}?UX}?.[iY}?`^6Y}?fnvZ}?>lإZ}?q݂[}?wR \}?L}M\}?̄]}?]}?ZF!^}? ,^}?c._}?h}_}?::`}?ƪ `}?vBGa}?&qza}?ֻ.Sb}?b}?4Ǩ!`c}?eYc}?"ld}?Bd}?ݜye}?Y8e}?Ppf}?ӧ g}?ߑg}?^Mh}? Oh}?Ȇ$i}?n i}?B0j}?-j}?|e=k}?*"yk}?'6Il}?- l}?83DVm}?8m|m}?>*bn}?HDn}?I#oo}?Oa[o}?VU{p}?[q}?`q}?dfU:r}?lrr}?qϩs}?rws}?"}I't}?ЂQt}?È3u}?0u}?=?v}?/v}?>gLw}?tw}?1Xx}?Lx}?Fey}?h~y}?Z%qz}? z}?̟%~{}?h\]|}?|}?}}?x}}?&P<~}? t~}?ʫ)}?4}?D6}?S}?D B}?|ȁ}?9N}?R1Ղ}?"i[}?'p}?`--g}?3}?8Ht}?n>d}?D!}?I}?|O'}?,UX_}?Z}?`}?:f}?kL>,}?q v}?Hwƭ8}?|律}?@E}?VTˌ}?Q}?w׍}?d4]}?3}?Ĥkj}?rk}?"(v}?ҵ}?J}?0_ }?}?}?>Җ)}?Sa"}?}?N.}?}?G@;}?\x}? G}?~͗}?j<T}? Vژ}?`}?xs}?(0l}?!5}?'my}?6-g}?2$݅}?8 }?D>L}?C[}?I}?RO$}?U+}?ZOc1}?`` }?f=}?k ġ}?nqCBJ}?wzТ}?|V}?~zܣ}?,7!c}?܍X}?o}?:n}?+|}?7}?Ho}?b}?ߔ}?X}?N}?V'}?f}?3}?׍-}?tJe@}?$Ƭ}?L}? ӭ}?2>DY}?{߮}?e}?@v}? 3#r}?Z}?N~}?j}?!'}?\'9}? -q}?2^}?j8ᣴ}?>*}?CP}?xIR6}?(O}?TB}?Z/ɷ}?6`FgO}?eո}?k[}?Dq}}?v:Fh}?|}}?Tt}?q}?.%}?b\}?}?e}?p"}? ; }?ίs}?~Y,}?.}?9}?ƐR}?}?Tw}?PJ}? }?bW}?̇V}?Dc}?p}? ݾo}?{5}?~8m|}?.}?܈}?o}?<,L}?}? }?Jd'}?!+}?b4}?X!}?'X@}?, }?h2AM}?8y}?=LY}?vC }?$I f}?NX}?T@r}?4Z}?_~}?ew7}?Bk4o}?p}?vޗ}?P|k}?(N}?*}?^}?_6}?-}?ldC}?}?̩SO}?z }?*C\}?ں{}?Gh}?8}?"u}?~Z}?F;}?}?}?Tr9}?/q}? }?d}?f-}?$P}?r 9}? }?[E}?/}?0!fR}?&}?,O^}?>2 }?7Ek}?=}}?LCCw}?H}?N$}?ZTz\ }? Z7}?_}?he}?kn;#~?p+s~?vv/~?&|~?ցb<~?R~?4܉H~?䒙~?VT~?B1~?ha~?~?PJm~?~?Gz~?^~?>~? ~?nѸ& ~?u^ ~?2 ~?|% ~?* ~?i=2 ~?&u ~?:> ~? ~?^K~?H T~?؋W~?~?VRc~?!3~?&jp~?d,~?2F|~?7~?r=I~?"C}~?H:~?N~?0T(~?Yq`(~?_.~?>e4~?j~?pe?A~?Lv"w~?{߮M~?~?ZYZ~? V~?Ӎf~?h~?Mr~?ȣ 5~?xl~?&~?ִA܋~?~?4K~?x ~?5 ~?D*!~?֯*!~?lb7"~?R)"~?C#~? #~?``AP$~?y$~?ڰ\%~?n%~? U i&~?X&~?|Ϗu'~?,'~? I(~?&7)~?:,n)~?1*~?7=ޚ*~?H=!+~?BM+~?Ht-,~?VN1,~?T9-~?Y,-~?d_hdF.~?e%.~?jR/~?tp /~?"v\C_0~?{{0~?ֲk1~?01~?P"x2~? Z2~?@ʑ3~? 4~?D4~?N95~?p5~?{#6~?\86~? 07~?ŲO7~?jo<8~?,8~?H9~?xܦ.9~?(cfU:~? :~?a;~?6 ;~?WEn<~?}<~?DҴz=~? >~?L$>~?R \ ?~?Ɠ?~? @~?`&@@~?,:&A~?1rA~?n7w2B~?=4B~?B?C~?~HQC~?,NkKD~?S(D~?YWE~?:_0E~?d_hdF~?jF~?JppG~?uG~?{SG}H~?XI~?ͶI~?J~?fG&J~?^K~?ĝK~?t~(L~?$;L~?Ү<5M~?tM~?2rAN~?/N~?NO~?@˩SO~?fZP~?#P~?NfQ~?2Q~?ZjsR~?\R~? S~?T~?jNIT~? U~? ɸU~?xV~?(C(V~?`+W~? W~?6&z7X~?+7X~?1>DY~?D7vY~?*b~?a:c~?Jc~?uFd~?2 d~?X@Se~?xe~?i_f~?f&f~?lg~?РWg~?t]xh~?$h~?i~?6 j~?2Qnj~?k~?ݝk~?@$l~?FMl~? 0m~?Pm~?}G~?>?v͚~?S~?ٛ~?L w`~?4U~?l~?Z~? kx~?%(4~?h+k~?1 ~?6_ۑ~?v<~?&BJ~?G$~?MS~?4S0~?X)~?^a=~?BdGä~?iI~?oХ~?Pu~@V~?{;xܦ~?b~?`~?ro~?/W~?n{~?~?̢f~?|#6~?,m~?ڳ~?Zݠ~?:'~?L~?ʑ3~?HN~? ?~?+Ư~?VcL~?BҰ~?X~?d ߱~?yBe~?6z~?rq~?" ~?n!~~?+Y~?0萊~?~?%b~?>+8~?0o~?6)~?L~?xog~?&u ~?zuDt~?2|~?6ﳀ~?䋬~?i#~?D&[~?㒙~?~?R]~?:,~?q~?`8~?Q~?E~?nP~?ЈQ~?E~?|]~?,/~?|gj~?9~?:v~?~?pF~?H.~ ~?뵏~?~?Ve%~?"]"~?ߔ~?d%.~?+Y~?0<;~?t6s~?"J~?6u~?澋V~?H~?Dc~?T~?o~?R<~?{~?3~?`sk~?0~?ڔ~?p~?hJ~?%'~?~⹭~?,3~?\)~?a@~?<%֘~?*L~?0P~?J6 @Y~?;w~?Ae~?XGD~?Mr~?RV~?fX{~~?^8~?c~?ti5~?$oom~?t,~?zܣ~?2*~?cL~? 6~?@ݻ~?B~?W+~?NcO~?њ~?[~?\K ~? Bh~?y~?jĂt~??~? ~?zչX~?(v~?3~?~?67 ~?jo~?',~?F޲~?9~?_N~?TE~?ٽ~?Q~?bS-~?%e^~?*͜~?p0j~? 6G ~?;Dw~?~A{~?.G~?L; ?R"??las?J??zW?*VR?c??8o?$J1?*i|?F0Ġ?5؈?;>?TAG?G?Lu?bR2'?X&?]^4?pci? i&@?n?t=M?.z]u?Y??<f?QT?r?L?~ ?E3!?Zk!?"?|ڗ"?h9#?I#?ɳ*$?vp$?&-6%?(%?`C&?4d&?!O'?'?B?\(?Xw(?h)?P)?u*?MV*?^ +?,?$,?l*A5-?0l-?5 .?z;xܦ.?*A5-/?FK/?L90?8Rl0?W)E1?]*1?FcbR2?h`2?n^3?Vt 3?zAk4?Ty4?dw5?5? 6?rHX 7?"7?С8?8?0<7#9?޲n9?/:?>s޵:?0<;?M;?LϪH<?g<?$T=?Z,=? da>?[>?hm?? ??Cz@?vP{A?& A? B?"B?4DZC?C?$%D?B*{D?/892E?5pE?P;>F?AoF?F,KG?`LOG?RWH?WcH?n] cI?c.I?hfpJ?|nWJ?,t|K?y L?EL?:K}M?M?N?H$N??\(O?O?V4P?vP?3;AQ?drQ?MR?jR?r'ZS?"QS?ԡfT?^T?0rU?0U?hV?>RW?؋W?X?LGX?GY? Y?\*Z? ~&Z?;^7[?j$[?*C\?/r\?x5/=P]?&;t]?@\^?Ff^?6L#i_?QS_?Wu`?D]Z`?ba?h2b?Rnjb?tNc?y ښc?`!d?Id?B-e?ne?9f?Λy(f?|6`Fg?,g?ܬRh?mh?:*?_i?vi?äkj?Haj?xk?Uk?Vژl?U m?m?f4n?ln?I#o?tܩo?"0p?Kp? >b?~vv?3n?B?{?jU?P'? ??^^4?l?أ&?l۬?R3?K?ẑ??*ԉŲ?FK?*ҳ?8aX?}޴?:d?F?@q?rx?T/}? ??bfW?#?#?p)? /Z6)?4n?:ԥ5?.@ݻ?ENB?K MȽ?F?d~$?!?L0?%?X]=?Z? I??hLe??v?E­q?:K?P<~?VT?H\?as?g0?Vm3?sk?xg)?d~$ۯ?6?ĉJ?r[B?"?ҚN?)?0Oa[? ?g?>?C@t?x?LȽ?z?7?\V? ߱?n?j+?5,?m?xb8?( ݾ?E? L?6WQ??ʎ.?r?z1?QM?)bi;?A~?؟?"?G?`(?7?.x,?VHT?35d??n9?Fз`??ӣ??Dl *?J'm?|J)C?T_?,Pz6?Ėy?U?؁?[`B?b>?:a"?= ?fYO?u?l?pu ?HrT[ ? 2 ?w ?% ?}8h ?T ?Vp ?.j1 ?Ht ? 'ķ ? ?= ?e ?<3 ?O ?^kJ ?ß< ?" ?s?K(V?"?-?Ұs. ?3RJc?0f?Y9?1,??̹o?ղ?D?g 9?gJF)|??$E?Pa?|E?U?؞?u[}?M[Q?%a:?$?f??[^?lw?[?3rq'? Oj?w.? ?}4?j:w?AV?r?e@? D?"?x ?PL?'?5?{Q?YmY?"8?^?6("? e?-??3o0/?lMLr?D9,h? ?>;?ǻ~?D?zDŽ?RJcH?*A+?P G?b?U~T?ػ?`[?8x?aW`?5 ?f&?A* ?ol]m ?Fy ?r ?l6!?wKy!?)!?}}"?U C"?,<"?X"?܈t #? aO#??#?c#?;$?[$?ꙹ$?7$?vS%%?q"Uoh%?I3%?!(%?1&?-t&?&?3&?Wj2>'?/9IN'?'j'?>(?J(?Dý(?eǡ(?=J)?^W)?O=-)?I)?Ud *?t؀c*?K[*?#ޕ*?`t,+?Ro+?f1 +?(+?ZlC9,?1_|,? r{,?-?whE-?Fψ-?h}%-?@.?"R.?>.?LjZ.? ~v/?v\^/?N;/?&/?'0?ՙk0?0?90?\"rU41?4Pqw1? (/1? 1?-@2?2?j32?B 3?9f4M3?DP3?>#l3?4?yDY4?PǾ4?(J4?{"5?OZf5?8/5?UK5?_f/6?6[Ԃr6?޲6?`6?o;7?fN~7?m,7?El *8?EH8?qa8?}8?w9?{cT9?S}Bї9?+!9?:?$a:?@:? \:?ayx*;?9Xm;?6;?;?6?~O>?V3>?->?9??ݻa6\??>@R??n??dD%@?<ۥh@?J@?̘@?Ow1A?UuA?rU41A?JMA?![h>B?τB?`B?㌼C?fkJC?XIC?0l(C?,D?qGWD?cD?wD?f E?>}_cE?>ӦE?E? -F?&pF?u BF?L^F?$uz9G?S|G?2G?H?EH?[H?2"!H? =I?'iYRI?GuI?-&I?iJ?A3^J?J?8J?Ȼ~(K?>]8kK?w;TK?ODpK?'4L?IקwL?̵úL?OL?r@M?]UQM?5/3M? [O N?jMN?`ˆN?㩢N?kfO?CfYO?lEO?#O?q.#P?IfP?zweP?QP?)}|/Q?[rQ?؂9յQ?Q? z7W?bX:zW?:D7VW?rX?ICX?ҩX?OX?pҏ Y?HUnOY? LY?Z+5Y? QZ?`l\Z?ƈZ?VfZ?.%[?lbh[?@[?q[?/2\?ewKu\?]?ĂV]?5]?s^?K K^?"*^?F^?ғb_?l~W_?J_?Y)_?1 `?"c`? `?'%`?A-a?g-`]pa??>ya?3a?9b?8|b?b?u>c?Mu Fc?%DTn?8o?Dq"Uo?O>o?I.Zo? vp?oOap?Fɭp?Up?׆*q?Zenq?Cq?}`"9q?UU7r?,fpzr?齌r?ks?zCs?qYs?c7s?;w t?3Pt?|Ot?kt?u?qo\u?IMu?! ,u? %v?iv?.v?Jv?Wf2w?/cuw?Aw?! w?>x?'x?f x?=-)y?xEKy?2Way?ĵ5}y?8z?tWz?L>Кz?#z?C!{?l$d{?IK@{?)\{?ZOx-|?1p|? Uů|?ף|?Z9}?`}}?h`?}?@;~?fVF~?r~?k~??vqvR?NT?&w3??|5_?Q?m倀?\(?4jk? I?'?4?x?k0?BL?hA?^?!=ǃ? ?y'M?Q󐄀?(-Ԅ?+?2tGZ?Rc?81?_#?7>f?ҩ?C솀?Ɖ 0?Ih&s?mFB?EO%^?z 2?u?CԸ?Ʀ?I ??Xc(?0OBDœ? `?T{K?ݗ?Zє?fݚ?>`yW?W?e6#ޕ??!?kZd?uv?Lqꖀ?$-?vmp?K泗?|*?:?[9}?2U? q? F?a?@̙?i?AR??4ٚ?ȞP?!wl_?wU?O'4囀?'(?,k?֯?2?/5?]8kKx?5Ig? >(?A?C庄?Ǟ?kI ?C̀N?O_*?=Fԟ?Tb?}Z?zZٙ?Qݷࠀ?)`#?tf?eS ?1%?kA0?`\s?7qx??vເ?$?ˇ#g? ??{[?Rw0?*us?T?٘2?$׀?,Zg׀?m`v׀?E2?׀?0؀?7s؀?̺؀?=؀?{=ـ?SCv9ـ?+TUـ?I3qڀ?Iڀ?Nڀ?ڀ?aTۀ?9׋Uۀ?Zjۀ?H4ۀ?_'P܀?lb܀?pe䇥܀?G£܀?k+݀?n݀?p^݀?<݀?~v/8ހ?VJ{ހ?-|fހ?߀?݁D߀?t߀?R߀?d 1 ?<Q?)?E?a?}]?rh?JF?"!%&?i?&?$?,@3?X}\v?02\x?:?7??˂?=?f ?>CL?q;?HPW?.s?N X?u몛?LT?$ר!?Yd?e?_D6?"R.?[enq?2߉? k?:?p{}?Y?iv8?A1G?|L?h?ȁ?S?wo?O N?',? `?֒+?G?c)?]l?5c? !B? 5?&x? ?l,&?CBB?2y^?Wz?76 ?N?z=͑?R?)C?Ǝ![?Hm=?KY?N*u$?`g?7T笪??Y0?܂t?_a?n?8?FeT=?o?jۋ??pI?|vߌ?TvU?,3?|3V?N?j??bb?: k?I?(+?o?-?qI?He8? {? _?ϣ=?&D??W, ?.(?2DQ?޴t`?7S|?1?e=]?=Ϡ?C?ū'?H#j?h??sNG[?K%w3?#Tv?⮹?Y?ܟ??_~?Y\?1e;: ?VL?jq?֍?p?gX??vr?P?{/"? 5e?P?vl?M.?% q?f?E?#:?~?\/?3K? gG? |?Z?&9?jS?B,??1*?ɴF`?7pb?xN~?P=-)?( l?Bѯ??H 6 ?˅%y ?^NdA ?6B] ?T!yB ? ?Yް ?ܼ ?l_N ?Dy ?eX ?6< ?jX[ ?s ?{pҏ ?R$ ?*vg ?m ?{L ?*1? 7t?aR?8n? =?范?b?@?oI?G?1?M? iV?w?}&V?U4?-,b??1?,,?7Ho?ckd?;=J?(8?B{?Ӿ?H?qˢ E?IN'?!_C?S>_?{Q?Y?ٲ?W_?/]?eu?S"?j2>'?Zj?fpu?=͑?v3?v?{i?G?t&@?L9?#T? p ?ӌL??]?Z<?2X? ?3? O"?ke?h&s?@Q?,0.?q?1??v7.;?NJ~?&=gf?E ?B$G ? ?H ?\˿!?4N T!? |)!?S[E!?9a"?Y}`"?k"?B_մ"?)#?dl#?p#?jO$#?y-@6$?Qp \y$?(w$?vɓ$?B%?{˅%?d%?_C &?7"O&?;&? V&?r'?['?mz'?EY'?7$(?g(?̝(? 5(?|Q1)?S&mt)?+n)?,M)?ڮ+=*?1 ݀*?*?b7+?90J+?=L+?bh+?BA,?V,?pH,?G,?N-?Йc-?Sx+-?VG-?~Y5c,.?Vo.?-_.?ж.?d8/?{/?jl /?dJ&0?&S@5?o5?+j5?ŮH 6?1'L6?uߏ6?M76?$7?<2Y7?ԿN7?B^j7?<"8?[He8?38? N8?ж.9?Sr9?s-9?iYRI9?A0e;:?_~:?:?d̸;?G;?wj;?Og ;?'pF(? #m>?>>?lZ>?Cv6??y??q??P??.B@?z @?R@?)&9 A?UOA?+qA?eA?1DB?`"[B?87B?B?<%C?4hC?B{PC?nYlC?FH81D?tD?MD?D?S=E?|֐E?TYo/E?,MKF?_,gJF? F?dF?ǺG?bjVG?:G?pcG?A* H?u FcH?aH?q{}H?H,I? oI?yѲI?φWI? 6 9J?%|J?W@J?.\K?xEK?ޗK?mK?KL?e *QL?=L?&L?;M?+W^M?sM?s1aM?K?'N?#7jN?N?`?G{J`?e`?ԁa?Ja?a?} pa?UNb?-- Wb? )b?Db?` c?|cc?cc?; dc?B,d?%!od?¨d?+#d?r?9e?I1[|e?!ywe?6Xf?й6Ef?<ˈf?f?WBg?/ŰRg?H:g?mVg?MLrh?*^h?fS h?=h?Y'i?ۤji?^i?a5i?td@Q4j?Lmwj?#jj?ۤj?o@k?܃k?uwk?ZU l?2{40Ml? Ll?gl?Ѓm?Ym?h m?@km?J"n?(fn?+n?Fn?wb/o?N~ro?& o?_o?%>;p?~p?+ p?]%q?41AHq? ]q?6uyq?Sr?<2Tr?k͗r?CBr?s?G as?ʊ{? {?|{?%[|?9J|?p+|?H |?1'}?CW}?6_}?p{}?~?ddZ? LJ4?w??őb?A@?u?M.dž?$J ?fM?Ԣ?%xӇ?V?[+5Y?3򜈁? 1 ?)#?6Ef?a?ixH?X?Ό?^?]T?5d? uۍ?iT;?2Wa?os?l玁?CuΪ*?m?zⰏ?i?H7?z'6z?RR?) m?‰C??ɑ?^ ?`?$?GĖ??bM K?:О&?S}Bї?[^?X:zW??q^ݘ?H ? dc??iq!ꙁ?O=-?o.Yp?W u?.u?ɬ9?z|?俛?e?eDF?="8? T̜?o?R??s{؝?KY?#8^??2垁?N(?%jk?Y?1+o? M4?0,w? ?6?g-A???i큱?} ű?Uoh%?-FAK?u%]?yѲ?z?W?c̚?;~ݳ?\!?; d?‹ظ?<?1_?AM?{i幁?tGZ(?L8k?$M??R4?ղx?X,?ZoH?2^NdA? ,?c Ǽ? ?iM?h?@o Խ?c'?tBCZ? _?zzཱྀ?wݖ#?Nf?&Ω?y쿁?X0?6"s?>?]Y?4u(Ձ?okՁ?Ձ?t|Ձ?Z+5ց?uz9Gxց?Mcց?$~ց?՚Aׁ?ԅׁ?ׁ?p ؁?[O N؁?3-&؁?  B؁?]ف?yZف?ف?iف?Ad#ځ?%Cfځ?!ځ?*!ځ?<0ہ?x0Xsہ?Otہ?'6zہ?X<܁?;7܁?܁?A݁?]I݁?5G7݁? ʏS݁?Lnoށ?LUށ?R+ށ?l ށ?CX߁?a߁?]߁?2߁?cbN+?z@jn?Ri?)?oܽ7?z?t?w?`zV-D?84I?e? ?МP??n?Fl?J ]?)(?͖D?_&?}{i?T?,?%`2?ۧ>u?*?"?c0>??:Z?6v?u?;TK?2ʎ?qA?I? GX?ɬ9?LU?iq!?RHd?W&?.X?-?]p??c4?e]P:?=i.?I ?eS ?$ ? ?t*t ?LR_ ?$01 ? ?5() ?Dl ?;` ?Z| ?2Ah5 ? Fx ?F%л ? ?LB ?h# ?@R? ?}[ ?W\wN?:?]?w?NcZ?&?h?q:$?nPVg?.r?]t ?40? zs???f=?kD5?C#Q?m? I?ʐ??y{?QZU?)8?0?ءK?$gb??_*?7o+?0Nn?,?5 ?*8?m;F{?Eb?A~?cD?FB? ?|L ?S Q?+R%?՚A?Wy]?Wy]?]6?b?9c&?i?h? ?nm<3?pKXv?Ht*t??y??ǂ??~?VaL?.@7?S? n?ۊX??d?<w! ?Ud ?4 ?á2 ?$M.!?siq!?J*!?"!?/k:"?ѲI}"?5("?#?Y;,G#?0H#?Ad#?À$?F_S$?=$?gL$?>%?R `%?Է'%?WC%?t_)&?u]S{l&?M1&?$c&?5'?hx'?'?n"'?[h>B(?3tGZ(? %v(?y )?N)?ɑ)?i)?A~*?][*?;9*? U*?p$+?x׌g+?O+?'+?r0,?Qs,?/,?$4,?^O=-?5*k-? -?/.?fI.?5Eی.?l#.?D;/?.V/?@J/?Ýf/?F|0?zZb0?RL90?*0?R+1? o1?W)1?ڑE1?`]pa82?8N}{2?c-2? 3?hD3?3?nn3?F$4?td@Q4?B\4?y!x4?5?}ޯ]5?Tˠ5?,5?z'6?ۊXj6? 7;6?W6?cr37?:Ҏv7?7?ꛏ7?n?8?L8?q$+8?I 6 9? *QL9?m9?/9?:?5bX:?W@ݛ:?/;:?";?@0e;?úL;?Fh;?ew.?#kcG>?bJ>?(>?h??S??Yn??1 ?? t&@?_B`@?y>^@?z@?h)A??ڱlA?ͯA?A?Ɗu6B? T!yB?v2=B?NYB?%tBC?ΐC?՛C? D?iND?\$HD?4&D? *8E?S[E?/oE?E?j5$F?B]gF?;<ߪF?F?@1G?2tG?xFNG?PɔjG?(Ls=H?QH?Q0H?I?WII?^I?6]-I?IJ?bgeVJ?EJ?h$J?mK?DnbK?K?s K?|(,L?y[DoL?{9`L?S|L?*8M?ճ{M?ϾM?N? qEN?aO#N?9.?N? [O?vQO?ɒO?O?oP?G$e]P?CP?)"P?ά:'Q?/UjQ?}qQ?U5Q?-z3R?;YvR?ܽ7R?@R?@S?cF4S?;ɱPS?Ll T?nLT?QMT?+T?rW U?IXU?!]U?ߥ/U?bK"V?bgeV?hAV?XV?/n.W?qW?sW?W?yx*;X?fVF~X?>5bX?~Y?GY?ѵY?Y?t Z?Ll TZ?$K%Z?)AZ?][?x`[?Ŕ[?Z[?2$)\? `l\?)?\? \?/;6]?iWy]?@5s]?]?:vB^?ǽTDž^?@3^?w _?OFO_?&6_?KR_?΋n`?Qj[`?H`?]W'`?4$a? ]ga?a?b1a?M1b?kh^itb?C#@W[$@ c#@{/L$@X5;~#@s#@|гY#@h"lxz#@B`"#@J$@(\b#@I.!#@ǘ`#@EJ#@ ףp=#@v#@/d#@^)#@(#@<,#@\ Ac#@|гY#@p_$@l#@Qڛ#@jM#@n4@#@@#@9#j#@0' $@Zd;O#@2ı.#@xi#@j+'#@K7#@o#@jM#@ y#@jMS4$@(#@{G#@ڬ\m#@iq>$@#d#@x&#@3#@j+w#@9$@lxz,#@R!#@9v#@>٬\#@ׁ#@j+#@ioD$@镲#@B>٬#@!rh}#@v#@rh#@ ^) $@>yX5=$@?ܵ#@Ԛ#@X5;#@#@+ X#@&S:$@Gx $($@̼#@(\#@\C#@F_#@I&#@p= #@ y#@Fx #@d`#@3#@Ǻ#@ClG$@qh#@x&#@JY8$@9EGr#@sA$@ Ac $@h"lxz#@)Ǻ#@b#@Ciq*$@tF#@Έ#@d`#@|гY#@46#@.n#@S#@#@.n#@o_i#@/$%$@B`"#@B>٬#@\ Ac#@o#@^)#@g$@#@x&#@ c#@j+#@s#@s$@$$@8EGr)$@ڊe#@?#@_)*$@^)#@Aǘ#@$@mV}#@ׁ#@U0*#@Pn$@Qڛ#@oT#@\C#@V?$@}b#@{#@vq =$@ o_#@Pk#@ho$$@y)#@Ciq*$@>W[#@( #@ F%u#@٬\#@ʡE#@`vO#@:H#@8m#@ r#@Ǻ#@!uq{$@Fx #@1#@V-#@]Fxk#@a+#@F%u8$@J$@#@#@ rh#@ rh#@ё\Cz#@p= #@x##@Ra#@d`T#@S$@jt#@2ı.#@U0*#@k#@w/#@}b#@X2ı#@:M#@^)#@H.#@<,Ԛ#@c=y($@S#@^)#@p_$@<<$@1#@N@a#@`TR'#@B>٬#@ŏ1w $@M#@ioD$@St$#@ׁ#@*Թ#@`TR'#@6#@_#@sF6$@Ԛ$@F_#@!lV#@ #@e`TRw#@lxz,#@t#@A`В$@7A` $@X5;#@&†#@?$@J4#@Ps#@۷#@J4#@Ș$@`vO#@0*#@ c.$@aTR'#@}b#@;O$@̼#@Zd;#@1#@jq#@ZB>#@,C#@*D8$@U0*#@/$#@ioD$@ClG$@a#@u$@p= #@:#J{#@*D#@/nU#@jt#@v#@xi#@V-#@St$#@Ș$@ ףp=#@|г#@+'$@:H#@d`#@Ӽ#@H.!#@9v#@d`#@t$#@\mž#@0*#@I&#@io#@Mb#@Q|a#@Fx #@ y#@Dio $@6[#@Qkw$@pΈ#@镲#@#@lxz,#@|г#@ʡE#@:M#@x&1#@x##@l#@N@#@t$@>yX5=$@F_#@9#J{C$@?5^I$@bX9#@u#@xz,C|#@ZB>#@##@pΈ#@ ףp=#@w/#@48#@:M#@0L F#@B`"#@t$@ Ac $@ioD$@m{B$@̼#@*D#@v#@2%#@G$@1#@6;N#@K7A`#@'†W#@y) $@|гY#@\mž#@=U$@.1#@B#@Q#@ q#@X5;#@3#@†W#@NbX9#@\mž#@:M#@xi#@ q#@6٬\#@ׁs6#@B`"#@a#@B>٬Z#@\m#@S#@HP#@6#@]Fx#@2U0*3$@<,Ԛ#@N@a#@( #@ͪ#@\mž#@UN$@X5;#@3#@Fx #@H.#@EGrI$@d`#@H.#@2w-!#@8EGr#@Q#@&1#@gj+&$@6$@,C$@(\#@(~k#@qh#@ׁ#@B`"#@/L V#@{#@8EGr#@'†W#@3#@w/#@+ݓ#@{#@lxz,#@+ #@oT#@48#@pΈހ#@pΈ#@S#@>٬#@鷯s#@M O#@"~#@kw#@~:p#@V/#@.n#@a2U0*#@vOj-$@0*#@1#@oT#@F%u8$@jq#@Pkw#@+'$@9v#@N@a#@+ #@U0*#@-#@R#@#@7#@*D8$@$$@u#@Pkw#@3"$@ڊe#@ rh#@JY#@D#@镲#@8EGr#@6#@V#@2w-!#@H.#@_vO#@ڊu#@tF#@a+#@qh#@7#@46<$@hs$@Bf:$@`vO#@\mž#@"~ $@-!l#@B>٬#@"~#@X#@x&1#@{#@a+#@&S#@[Ӽ-$@䃞ͪ#@gj+&$@$#@bX9#@*:#@[$@Ac]#@(#@:M#@j+#@;Nё|#@<,#@y)#@o$@:pΈ#@3"$@\m2$@-C$@mV}#@{/L$@($@ʡE#@fj#@2ı.#@ rh$@fc]ܶ#@0*#@lxz,#@:M#@9v#@X9Ȇ#@Af#@Oe#$@m{B$@_Q$@#J{/#@LJ#@(\#@̼#@OeH$@:M#@\C#@H#@s#@ h"#@e`TR#@l#@{$@6[#@8EGr)$@a#@b48$@"$@jq#@x##@-!lF$@TR'#@{P[#@?~#@(~k#@t$#@NbX9#@7#@Dl$@ׁ#@Oe#@]C#@D$@n4@#@Q#@q -@$@R#@6;N#@$~ $@x $(#@a2U0*#@#@ۊe#@B#@Oe#@]Fx#@T#@8m#@*D#@cZB>#@ܵ|#@{#@a#@+#@n2$@J +f#@?5^I$@~jt#@=yXu#@.1#@0*#@Y8Ž#@@#@s#@"lxz\#@/'#@\C#@aTR'y#@ rh#@J +#@"lxz#@H}#@a#@/$#@ y#@St$#@eXG$@T#@aTR'#@Ӽ#@ڬ\m#@Ԛ#@t$#@b#@oʡ#@{P[#@>W[#@ r#@鷯$@ r#@!lV#@x $(#@#@|гY#@b48$@St$#@a+#@Xq#@ #@۷#@"u#@r#@(~k#@Afg#@{#@0*#@#@x&1#@ʡE#@Ӽ#@6;N#@ Q$@( #@2%#@:pΈ#@|?5^#@8m#@ʡE#@uq 0$@)\x#@x&A$@Fx #@bٝ#@|гY#@HP$@) 0 $@ͪ#@R!#@fj#@#@S3$@K7#@ΪV#@ʡE#@x#@9vo#@}гYy#@d]Kȇ#@{#@I&#@H.#@n4@#@{#@Ciq*$@I&F$@}b#@Nё\3$@>٬#@lxz,#@`vO#@ y#@ 0z#@7#@Jt#@58EG$@a2U0*#@ڊe#@lxz,#@u$@9#J#@a4#@&†#@{#@aTR'#@ c#@\mž#@ΪV#@Tt$#@/$#@9EGr#@jt#@eXG$@I&#@gj+&$@QE$@Q|#@@#@Bi#@p= #@\C#@`vO#@H.!#@?~#@tF#@z#@ʡE#@9v#@Aǘ#@io#@H}#@H.#@QI&$@jq#@TR'#@Pk#@%u#@t$#@6#@#@ZB>#@Gz~$@:#J{#@6+$@^)#@tF#@jq#@1#@JY#@48$@7A` $@ΪV#@6;N#@lV}#@!rh}#@#@/$1$@x&1$@N@a#@ #@ho#@>yX5=$@6$@a$$@\( $@`" $@ͪf#@Pk#@<,#@Ș#@&1#@46<}#@8EGr#@I.!#@2%c#@ʡ#@( #@ʡ5$@,C#@}гY#@48#@RI&B$@N@a#@Mb#@@#@Zڊ=$@Q|#@ rh#@v#@ #@/n#@ #@v$@$@"u#@##@e`TRw#@*:#@z6>#@J +#@($@j+$@ r#@ y)$@ͪ#@1#@ q#@ec#@fc]ܶ#@R#@Ǻ$@7#@2%#@8gDio$@&Ss#@aTR'#@{G#@z6>W#@R#@ Ac $@+ #@ Ac $@Ԛ#@>W[#@#@E4$@H.?$@a2U0*#@9#J#@r#@ h"lxj#@8EGr#@Aǘ#@"u<$@d`$@V-#@F_#@48$@_#@ #@-!l#@&S#@'†WZ#@|?5^#@n#@Oe#@vq =$@x&#@#@+'$@%#@v#@ F%u#@]Fx#@FԸ#@ g#@ y#@I&#@#@y)#@'1*$@R!#@j+#@C#@!uq+$@.1#@̼#@6[#@pΈ#@a2U0*#@J4#@|г#@ F%u#@#@+#@ y#@ h$@:p($@-#@#@`TR'#@Ac]#@Pk#@V_#@jM#@ y#@6$@ho#@&†#@cZ2$@46<$@Aǘ#@ׁs#@鷯s#@\mž#@z6#@z,C+$@z):;$@7#@1%#@~jt#@&†#@ܵ|#@{$@`vO#@gj+&$@*D#@ʡ#@R#@bٝ#@QI]#@v#@\mž#@?5^I$@B>٬Z#@N@a#@V-#@lxz,#@UX#@L7A`$@B`"#@\C#@n@$@~: $@UN$@ŏ1#@ q#@1#@ h"l#@6[0$@ q#@a#@:#J{#@d`#@K7#@|г#@\C#@:#J{#@3#@ŏ1w $@I&#@Pn$@*D#@mV}#@ׁ#@#@ cz#@Ș#@ r#@+ #@ y#@]Fx#@ q$@ec#@St$#@p= #@N@a#@8m#@#@t#@Q|a#@.!5$@6>W[1$@䃞ͪ#@M O#@( #@ #@@a $@~:#@3#@$~ $@R#@.1#@s$@mV}r#@0*#@Q|ar#@V-#@#@>٬#@H^#@_L#@鷯s#@Ǻ#@Pkw#@8d#@鷯s#@&C$@'1*$@ #@k w#@"~#@(\#@{#@a+#@:M#@v#@a2U0*#@St$_#@2ı.#@.n#@ʡE#@{#@ r#@rh#@Pkw#@&†#@JY#@.n#@ rh#@v#@'†W#@kw#@1#@n2$@[ A#@a2U0*#@V-#@ #@J{/L6$@#@/n#@:#J{#@fc]ܶ#@pΈ#@0*#@ #@H.#@^)ˠ#@Ԛ#@S!u#@~: $@{P[#@N@#@H.#@ Ac $@48E#@?e#@:H_#@n@$@6#@9v#@Y8Ž#@d`#@}b#@$#@ΪV#@^#@x&#@rh#@`TR'#@H.#@xz,C#@V-#@"~#@\m#@jt#@U0*#@B>٬#@ c#@( #@_#@V-#@T#@2ı.#@QI&$@ -x#@ZB>#@Ǻ$@Y8Ž#@x##@h"lxz#@ F%u#@̼#@&†#@#@Zd;#@V#@xz,C|#@0*Є#@6W[#@ڊe#@S#@2%c#@ #@-!l#@̼#@y)#@q -@$@Y8m#@|гY#@ cz#@+ #@#@Qڛ#@J +#@HP$@N@#@ F%u#@'†W#@x&#@^I #@J4#@EJ#@xz,C#@*D#@lV}#@fj#@a+eI$@>W[#@~k #@g$@ #@48#@?߾n#@Oe#@{#@A#@w/#@Ql#@}гY#@鷯s#@:#@{#@uq 0$@m4g#@ܵ|#@c=y($@ #@Q#@`vO#@$#@j+#@^)#@S#@Zd;#@8m#@v#@M O#@/$%$@MbXY#@c]K$@aTR'#@.!5$@ʡ5$@6;N#@b=#@Zd;O#@,C#@Aǘ#@$~ $@^#@O@aã#@S!u#@~: $@##@E$@<,#@qh#@"u#@#@r#@.n#@ #@d`#@/nU#@+ #@~k #@(\b#@ $@F_#@`vO#@:#@#@Ș#@8m#@,C#@xi#@_L#@ $(~#@tF#@x&1#@3#@8m#@Ӽ#@ioD$@#@H.!#@a+%$@ y#@-#@ y#@ǘ`#@ #@d]K#@Q|a#@fc]ܶ#@^)#@|Pk#@2ı.#@\m#@;O$@d`#@Ӽ#@M O#@/d#@#@]Fx#@xz,C#@Q|#@(\#@gDio#@N@#@jM^#@oT#@v#@Q.$@n#@Ps#@d]K#@1#@:M#@ۊe#@ڊe#@/$#@]Fx#@/d#@†Wʢ#@†Wʢ#@J +#@EJy#@*D#@ -x#@{P[#@ܵ|#@M#@vq =$@+#@I&#@M#@St$'$@Q#@7[ #@#@q -@$@C6#@yX5ͻ#@.n#@d]K#@`TR'#@y) $@V#@1*$@Xq#@Y8Ž#@{G#@Zd;#@6$@Pkw#@&†#@-v#@>W[#@V/#@Ǻ#@Mbp#@2%#@#@\mž#@*:h#@ #@#@*:#@A&$@F_#@C6#@r/$@46#@&䃞ͺ#@"u#@j+#@I&#@C$@n@$@*Թ#@F_#@\C#@"$@#@ c#@_)*$@JY#@E4$@:p($@'†W#@8EGr#@6[#@ΪV#@d`$@+#@ڊe#@)\x#@S#@ F%uZ#@Q|#@fc]ܶ#@]Fxk#@gj+&$@~k #@c]Kx#@J{/L6$@N@#@{#@ͪ#@x&A$@^#@6;N#@0*#@/$1$@/'#@̼#@I.!v#@St$'$@:H#@FԸ#@|гY#@T㥛$@ y#@T#@b=#@5^I #@fc]ܶ#@:H_#@:H_#@ڊe#@ׁ#@( #@xi#@^)#@C$@%C{#@&䃞ͺ#@:M#@(\b#@6٬#@8m#@+ݓ#@#@D#@ q#@n#@xi#@xz,C#@Pk#@fj#@K7#@B`"#@<,#@ΪV#@2ı.#@Ԛ#@}b#@$$@b=#@镲 q#@V}b/$@QE$@bٝ#@"lxz#@B>٬#@_L,$@Qڛ#@#@ F%u#@>W[#@Zd;#@(#@X5;#@#@`TR'#@^)#@ rh#@ h"#@,C#@d`#@HP#@Cl;$@Aǘ#@( #@[ Aa#@b#@a4#@Zd;#@ c#@I.!#@J$@ho$$@6>W[1$@.1f#@1#@ˡE]#@|г#@ioD$@&䃞j#@.!#@ׁs#@/$#@o#@1#@ܵ|#@hs$@_vO#@TR'#@ʡ#@v#@Aǘ#@jt#@/L V#@ʡE#@d]K#@ʡE#@Q#@镲#@ #@_L#@St$#@"$@&S#@r/$@HP\#@Ș#@Ps#@_L#@)ǺH$@S$@-#@N@#@ #@ y#@̼#@t#@ y#@Gr#@ۊe#@7#@*Թ#@8gDio$@:H#@Zd;O#@fc]ܶ#@*Թ#@lV}#@#@ׁ#@U0*#@%䃞]#@St$_#@M#@3#@Pn$@)ǺH$@&Ss#@X#@V?$@?߾n#@|a2e#@kw#@ڬ\m#@mV}#@I.!v#@N@a#@OeH$@ q#@9m4#@^#@3#@ʡE#@X5;~#@bX9#@fffff#@K7#@:M#@S!u#@ʡE$@?ܵ#@+ X#@St$#@/'#@vOj-$@JY#@o$@ݵ|Ѓ#@Aǘ#@I +g#@Bf:$@o#@Fx #@ݓe#@JY$@"u#@8m#@d]Kȇ#@Zd;#@JY#@Y8Ž#@ʡE#@a2U0*#@6yX5=$@٬\#@V?$@Bi#@F_#@X#@fc]ܶ#@48E#@|гY#@z6>#@>W[#@?$@Ǻ#@H.#@lV}#@2ı.#@ q#@X#@v#@ŏ1#@*:h#@C#@Gr#@n4@#@e`TR#@(\#@ 2$@ZӼ#@&S:$@$$@H.! $@uq 0$@MStD$@̼#@jq#@Ps#@Pk#@t#@6+$@ r#@*D#@ho#@Ԛ#@xz,C#@48#@8EGr#@.n#@ $@ŏ1w $@ʡ5$@Ș#@aTR'y#@"u#@>W[#@|гY#@,C#@V/#@z6>W#@8EGr#@H.#@I&#@̼#@Q|ar#@Q|A$@;M /$@ ^) $@( #@6#@E$#@C<$@9v#@z6#@{/L$@#@+'$@_L#@#@*D#@HP$@W[#@S#@?߾~$@b=#@^I #@T#@}гY#@I.!#@~:#@n2$@ o_#@(\#@io#@\ Ac#@Nё\3$@0*#@Pn$@ʡE#@ q#@Ș#@bX9#@z#@0' $@`vO#@#@K7#@ho$$@|a2e#@j+#@#@x&1$@,Ԛ#@#@j+w#@2w-!#@QI#@J4#@NbX9#@3#@~8gD9$@#@&Ss#@jt#@HP#@"~#@6#@EGrI$@a+#@1#@A#@NbX9#@n#@X5;#@;pΈҞ#@x##@6W[#@#@Aǘ#@镲 q#@fc]ܶ#@H}#@S:!$@##@ͪυ#@n4@#@>W[#@a+#@ rh#@#@TR'#@8m#@ ףp=#@\C#@Q#@jMc#@h|?U$@ec#@B`"#@!u#@]Fx#@?l#@b=#@K7#@K7#@_L#@9m4#@{#@= ףp#@vOj-$@h"lxz#@6;N#@-#@\ Ac#@6#@ڊe#@8m#@|?5>$@y) $@o#@/$%$@B>٬#@-#@+ #@:M#@ǘ#@B`"#@o#@B>٬#@-7$@.1#@"~#@D#@"lxz#@T#@&S#@ ףp=:$@ y#@Q|a#@ Q$@^#@J$@Aǘ#@l#@ޓZs#@_V#@ۊe#@X5;#@ŏ1#@|?5^#@n#@2ı.#@46#@{#@Ș#@y)#@FԸ#@48#@oʡ#@tF#@e`TR#@Fx #@+#@<,#@镲#@`vO#@( #@<,Ԛ#@.1f#@t$~#@\ Ac#@K7$@e`TR#@"lxz#@#@eaq#@NbX9#@47#@d]Kȇ#@~:#@ףp= W#@d]K#@ׁ#@|гY#@~jt#@.n#@8EGr#@k w#@_V#@YJ#@48#@V-#@Q|#@ y#@#@ #@ݓe#@ŏ1w-#@a4/#@|a2U0J#@w##@ "@%䃎"@\(!@:pΈ!@jM @33333S @b@lV}n@HP@EJ@&@8EGr@z,C@ ^) @]C+@ y@V}b?u?x?V-ӿJ4-!lVpΈ`m4x#<&†' ;M W2dGzo_=yXڬ\m-gz):_vOR!m4@n`B`";6W']C{'9m4'Ǻ'M OO(%'U0*'KY8%(Gz(uVN(Ӽ)(&S(,Ԛ()ǺX)]K)~k *Z* Q*]m*ro*q)Ac])(\?)J{/LF)xz,C(1.)):˯(&S(O@aó(9#(ZB>I)V/(fa(MbX(a+eI(n(n(c]K(('vq (>W[(|Pk()(( (t$.)u( F%u(6[@)H.A)<)F%uH)Ș/)гY(3(bX9) y)R')y))~:p)@)LJ*)V/W)<,4)U0* )h"lxz(N@a#)a2U0*) y7)?|(V-(!rh(eXG(:'6+(Hzg(JY'Ԛ(Ӽ'rh(^K=(!rh([Ӽ}(( q(*:(}b(|a2(H.!)lV}(@8)47(^I  )ZڊM)~j(_L<)jt(!rh(_)z(&†(lV}( c(b='^)'Y8Ž'A`2'5^I r'&Su'9'oT'1%'U0*'3'0*h' &:'ׁ&ۧ&n &_l&x&1&V-& g& 'Hm'J{/L&'$(~'&Su'?e'QI'4@'؁sFF'[B>ٜ'd]Kȇ':ph'I +g'X'TR''_'oʡ'"u,'n4@'9EGr'y'sF&'Oe')'ŏ1w&w-! '2w-!4'0*$&gs%&B>٬J&#g&Qkw%+ H&S㥛4&0*&JY&?W[&pΈ&n& h"&L F%u&h%D%Q|aR%%B% -%46<&鷯&#W% F%u%_L*%z%sh|%}bI%' %JY8% h"lx$^)7%NbX9D%pΈ`%ea%^K=$uV$Pn$ -$_)Ǫ$!uq$|a2U0$_$y):$ΪV,$gj+#ͪ"%䃞}"R!!:M! $(~Y!!lV "ΪV!v!0*!r"R'A"+er"Gz"j+"?ܵ"Aǘ"1%T"ŏ1w-Q"?W[<"}?5^ "JY8"{P+"Q<"=U+"y):"Qk"q"z6>""?߾"*D!o!TR'!~jt Dl 鷯m4V-zGAQI[B>,)\!uiqgs468gDio0h"lxzEK=N@"uqSt$0*tF?BilV}@hsC6 cZB>W[镲 |гJ4F%uH9#*]C+F%u(ZӼcTD4m{2*:|a2UP/$%䃾ݵ|SC6a+N@so_pΈހNё\#;pΈ>#J{/LV}b= ףpk ё\Cz^I {Pkףp= HPsA%u I Ac]m4W<ho$_Qhov5;N|a2%䃞- q[46<=H.\(:MM>yX5H9#J6[ iojtQsp= ׃ q oB>٬sa$;2w-!@Ԛ(M*:&S_vHV-K4:MD_,V'1`"Y=yXhgs57dF_XHPX%&† y 1w-!_~:0Bf bX9z6 cHNMb٬\[Ӽı.n g*oŏqX@NbX9t c3{/L  h"lxH 0"~j%C+^K=Y81 3ı.nk 鷯#H}8G(Mh|?QIK4jMSy&1(\K7Az6>7ڊe J>yX5 g*e`TRjt8!uqlV} MbX lq "u PnC _Q Gz. Zd;O o_V}b `vO* ea [Ӽ] sA ea! aTR' 6@ cZ h/ |a2U0 ؁sFv zG Y 镲 /' RI& 7A`P TR'pJY8V0L Fz,C?a2U0*iOev=y&1St$?5^IV/:#J{/ꕲ q,(~kIn9EGrGx $(1*;pΈec]\gj+6 h"lxPkwC6jMn4@|?5{/L ?L F% Q I&Fec7dj\m2Se Ǻ58EGrEJ /L 378 K= H _vOV <, Q !rhqh-I&FCQ8lxz, Cl;0*9vx#<\CгY[ A6Vm_)Ǻ]K,eX/$~j m{`"yio^)ːy)<,T47Bd]F8>yX5B cH.鷯Aǘ{k ]Fx ho~|a2U0):?؁sFȘJ{/L鷯  qۨo_GjM_v58EG2=Um33333|a2UK7Az6>V5^I ^)H.!}%C58EGra4ͪUXA`"N@#~j.1fJ4y):󿸯(MbX948|?5^:JY~k yQOnHPsǺ io 򿜢#h|?5I.!"uq {|a2U0oʡ o_NQ|jtrh|Xݵ|г<,Ԛ'1Z(\vq -]K/$ -Qc]KH!lV4@b*DʡEs"uq Pkw_QZˡEy&1qhd;OBfj鷯 F%u𿓩QIJ{/LH}8qr-/$Aǘ俸@ǘAǘfc]F뿛Hfj+|?5^ǺyX5;uῆZӼ?㿺ڊeTNԿEJYԿ{Ŀ):ܿ|гY?_vOvAfէ1%??W[?ʡE? ?k+ݓ?H.?6[ ?^I +?/' ?m4@?=U?Aǘv?}b?J4Q?oŏ?N@?/L F?/L F?eaгY?ׁsBiq?(\?ZӼ?-!lV?:pΈҶ?*D? ?9#J?EGr?3?0*? qh?>W[?D?<,?):?c]K?9#J{?l?ŏ1w? q?cZB?z6>W? -?_)Ǻ?Af?X9v?Af? $(~?Gx $(?,eX?9#J{?R'?tF_?K=U?H?JY8?%䃞?J4? q?sF???ё\C?>٬\?H}?QI?Af?ea?(\?!u?QI?z):?"~j?fa??߾?U0*?_vO?jt?O@a?c]K?$?Zd;?"lxz,?7[ A??ܵ|? h"lxz?9#J{?n4@?(\?X5;N?UN@?!uq?iq?_vO?C?1Zd?>٬\?37?>٬\?T㥛 ?_vO??Nё\?bٽ?L7A`e?Ac]?_Q?n??)Ǻ8??߾?S!uq?N@a?I?Af?_Q?Aǘ?NbX9?'i?Ac]?ʡ? h"lx?V-o?9#?QI?io? +? h"l?Oec?Cl?(?HP|?JY?W?ׁ?58EGr?HP|?Cl{?_vO?!rh?"uq?TR'?gj+v?B`"?{0?EJY?(\?x&?w/]?†Wʲ?bX9H?TN??5^I?[잼?!lV}??Zڊ?V-2?+e?x&?C?n4@?n?1*?c]F?gs?V-o?HP?? h"?:p?_):?y&1?J{/L?x#|? r?UN@?D? c?A?x#?K?e`TR'?(~k ?\ AcL?St$?48E?pΈ`??ʡE6?gDio?1?@ǘ?cZ?B>٬z?Oe?-'?jq?pΈ`?|?5^? c?_LJ??bX9H??+e?\C?猨?_vO?s?LJ?|?5??W[??:pΈ@R!u?]Fx@w#?'†WJ?q -P@t.@+e@@D@ )@F%u@PsR@ŏ17@w#@~k y@2U0*S@d]F8@ӼI@MbX9@Q@:pΈ@6@V}b@CiqJ@9#@Pkw\@H.@-C?K=?s@sFF@'†WJ?aTR'?<,T@1Zd? @Dl)@|гY?/n@"lxz,@W[@]K=@\C@:@z,C+@Ǻp@58EGr@?F@y):R@v@r@ h"lxz@ $(~9@a+@47@fc]܆@>yX5 @|?5^: @~:0 @tF@镲@:M@o_@K@Vo@h"lxze@㥛 @h/ @:M@zG@ c@N@@M O @R!5 @,C @(- @ QI @;Nё @ QI @Ǻ@ F%u@ @j+ @'1@b@B-@ @Mb@;pΈ^@b= @e`TR@H}@@a4@Af@H}@Dio@#J{/@!rh@ @iq@( 0@sA@*: @S@@_vO@ h"lxz@}b@]FxK @9m4@Dio@Έ @1%d@Ԛ@ @Qkw" @ h"l@' f@!u @\m> @S!u @Gx $ @378 @Dp @? @ QI @-!lV @y&1l@\mr @Ӽ @eaa @jMN @E @yX5ͻ @ݵ|s @c]F @F_ @,Ԛg @m{r @ޓZS @Y @ @F_ @m4 @k @Ac]K @MJ @_vO^ @z @&S @!uq @" @\ Ac @ @`vOj @h"lxz @X2ı @:H @镲L @>٬\ @!rhm @W2 @C@o_Y @x&1 @oa @48E @ZӼ@Pk7 @e @1Zd @ c @w/ @A @9EGr @jMS @I.! @/$F @^ @]Ck @߾3 @&1 @MStd @X5; @X9v @u @Tt$ @ rh @m4 @c]F @.!5 @D @̌ @x @u @ho @R @W2 @ͪV @JY @kw @w-! @Y @1% @X9v @K7I @= ףp} @= ףp} @mR @37@Q @2U0*S@_ @ @Dio @a4 @JY8V@?߾ @Bi@ʡE6 @hs@MSt@k @d`@C@46<=@b=9@)\@ǘ6@3ı.nc@|г@hsU@镲@-C@oŏq @l@ͪՖ@a2U0*i@o_Y @@[잼 @c]F@7d@?5@tF@F%u@N@@v @гY:@sF&@fc] @j+@+@ @0*@ho@V/{@9#J{@0L F@!u` @d]Kȇ@ǘV@ʡ%@c]K@St$@гY:@0L Fe@T㥛@&1<@@߾@~jt3@(\@6@.n<@c]K@m{@Q@:pΈ@#~j@( @ׁsF@[Ӽ@+eX@~k y@:M$@@?5@V}b@ @C@@]Fx@k+@Zd;ߏ @ Q @ O%@-@ǘV@{Pk@ׁ@ܵ|@ h"l8@q@2U0*S@D4 @k @Ǻ0@2@@ r@c]KH@#~j@K7I@Bi1@t.@(M@QX@-@C6Z@{@sF@6@ۊe$@s@@"lxzl@ʡEs@W[?@ F%u@^I  @_L@<,@:pΈ2@QI`@[Ӽ@[Ӽ@?ܵ@#@V/@46<=@Gx $(@@ q[@K7@p_@yX5{@ۊeD@VM@Hz@8m@b@N@@6@ Q@!lV]@xz,C@46\@ Q)@w#@[ A@?@^I @!uq@d;O@d`TR@H@d`t@cZB>H@ j@B>٬Z@鷯@@d`TR@/n%@Zd;O@ʡE@8d@@Έ@b4@ @=U+@X5;@K7 @H.@OjM@Q|@ZB>@$(~K@Q@ڬ\m@ h"@o@d`@Cl@Y@?<@~:0@Dioi@H.@X5;@?ܵ@I +@~jt@ʡE@B@lV}@(\@7[ @QI@xz,C@7A`@7@q= ף@@ǘ@_L@W[Q@S;@D@Oeh@&S@N@@=Um@]m@_@'1Z@z6@H@fc]@U0*@}b@EGri@gDio@JY8@Y@5@\(|@?ܕ@_vO@1殥@TR'@V @;M @Ԛ@٬\@x#@AF@z6>W@$@lxz,@x#@Y8ō@F@ףp= @'1:@&䃞@\C@@s@ǘ@!lV@OeC@UN`@_Q:@6;NQ@㥛 p@K4v@o/@/'k@B@@"~@JY8@ı.na@j+W@ꕲ q@2ı.@6W@gs@~:@ $(~y@K7)@ Q@q -@K=@jq$@2w-!@ݓE@ŏ1@S%@H@S%@H@?ܵ@ףp= @Tt$p@ -@Dt@_@Gx $H@Oeh@ŏ1@/$U@u@z6@H}}@jMS@k+ݓ@Cl@:H@&䃞@ -@~j@;O@7A`P@v@46@+e@7@QI@Sc@\m@C6@0' U@"u@C6@_vO@H}@Dt@|гY@LJJ@B>٬@`TR' @/L @%u{@㥛 @%䃞@bX9(@?5^IL@9v?@0*@@ +y@^)@@HP@RI&"@>@t@u@^)@-!lv@vO@Bi@ h"lx@.n<@zGA@W2d@"lxz,@#J{/,@ g*@5^I @= ףp@Pn@{P@Q@ yǩ@[ A1@"~J@UN@]K@QX@xz,C\@ c@MJ@ڊ@QI@Hz@*I@6@48Eg@Ac]@ı.n!@ZB>y@QI@@ZB>y@>@:@:pΈ@h"lxze@n @3t@ ףp=@@oʁ@"@R!@ Ac]@=U@ hb@l1@<,Ԛ@w/}@lxz,@L7A`@(\o@\C@v@J +V@鷯g@TN@,Ԛ'@(\•@Z<@S@Dj@3t@;Nё@c]F@/@_)z@$(~+@fjk@u@R@H}@@OjMs@6>W[q@3b@Z<@Bi@;M @3t@ yg@lV}@ΪV@ݓ@Biޱ@1n@!u@]Fx @ r(@&†W@oʁ@K7@s@D4@fffff@0' @St$_@ 0 @<,Ԛ@Tt$0@ r@Grw@@_Q@W2@ 0*@C6:@Zd;@{@6@B`"[@3ı.nC@ r(@Ș@/@@6@+eB@9# @ O@`TR'@1w-!@Bi^@ׁsF4@C@(\o@'1z@}?5^)@d`@_)z@[ A@c]Kh@ho@}?5^@Ǻ-@-@ݵ|3@lV}@fjk@?@_)z@ݵ|3@N@a@7d*@<,Ԛ@}гY@)\@$(~+@_)z@LJj@I&@8gDi@m4 @St$@k g@k g@@镲 @0*@+eB@B @ -@ q@6;N1@Pk7@Ǻ@jM@MSt$@X9v@ʡE6@s@ŏ1w@( @0L F@1*@x#|@0*@Q~@@UN@@QI@U0*@}8g@QI@7[ @'@~k @H.@&†@MJD@fc]ܦ@l g@l@(@r@47B@e@1e@%䃞@;O@K7@/$@|Pk:@gj+@s@Q@Gz@z,Ck@Ǻ@0*@@l@_L5@J{/L@$~[@k+@jMSt@H@T@gs@:M@ʡEs@w#@z@ʡEs@+w@^I @Tt$P@MStD@1%@[Ӽ@HP@Hz@ё\C@镲@QI@Pkw@K7@ho@,eX@(\b@<,Ժ@Zd;@&†@@MJ@$@$@@.1@fa@Έ@K7@|a2U0J@ @b=@??@r@!lV@V-@鷯g@@䃞ͪ/@d]FX@z6>@sK@T$@D4@'1@@ı.nA@^K=@jMS@&S%@TR'0@( @gj+@Y8m@,Ԛ'@B>٬Z@Ș@;Nё@x $(>@\mž@]Fx@*i@K7@+ݓG@K4V@Hz@ OE@/n@+ݓ@Q@6;N1@w/@ h"l8@V}b@cZB>H@' f@3ı.nc@ y@* @Dl@H@= ףp@DT@=U @@yX5{@io@9#J{@yX5{@)Ǻ@r_@Tt$@S:a@9v@d`@T@2w-!@T@ʡ@x $(^@* @}?5^I@\C @Et@@w#y@tN@ׁsF@:M@Gx $(@33333s@Gx $(@ h"lxz@ cz@HPx@R'@ F%uZ@V/G@#t@R'@JY8V@K7!@+ݓG@%>@0*Є@2U0*@6@JY8V@@@+ h@jqd@fa6@鷯@"~ @ q@]C@^ @z):@{0@JY8@@>W[@DT@@a @ -8@q@MbXY@$(~K@~:pn@z6>@UX@?~@K=U@k @ZӼ@x $(^@ C@r_@vOj-@Zd@H.@)Ǻ@ @B>٬Z@n@@ @}?5^I@2w-!@o_y@58EGR@2ı.@k+s@/'@@Dؐ@Bf@;pΈ^@@3ı.nc@?ܵ@x $(~@.!5@|гY@@_@MStD@)\@_L@ec@,Ԛ@ @Gx $(@a+@䃞ͪ@S㥻@l@V/@yX5{@ףp= @9v@'1:@ZӼ#@x&1@48E@b@8d@ rh@lV}@( @C@"@ qh@a2U0* @ү@@B`"@7@@=yX(@ c@58EGR@@JY&@^K=[@8d@Dؐ@ c@oT@I.!6@QI@Hz@V-]@?W[,@c=yx@$@( @n*@%䃞-@3@z,C@H.?@;On@X@HP@!rh@镲 @a+@D@=yX(@9#*@9EGr@H}8@?_@)@ŏ1w-@O@aó@d`@q -@ h"@ޓZ@Z\@I&@=,Ԛ@T@${@Y@QI}@гY@ -8@|?5^@٬\@@1*@ $(~@x@!u@l@=,Ԛ@-@2%@ܵ|P@q= ף@]Fx@tF@ׁs@_LL@Q|@ec]@@Gz@V-@&SZ@X2ı@N@!@?d@|?5@|гY@jM@W@`vO@HP8@Gz@Ac]@.n@mr@ @h|?@s@Ps2@ h"l@&†@Y@TD@QI}@#J{/l@X9v@@:pH@Pk@@@8@ea@$@w/@9#J{@W@6@oa@|гY@_LL@jq$@Aǘ@!uq@_):@Pk@@47@6@46٬@9#J@+ (@q -@ȘO@3w@46<@?@lV}@9#J@4@@0*u@tˎ@ -@|?5@8gDio@oTa@J +6@ @1w-!@B`";@HP@T.@Ǻ@ c@( @\C-@鷯G@Έk@Έk@d]F@"u@0L Fe@\m~@&S@Z|@m@߾@s+@;M @QI@M O/@ڊe7@ho@Hz@|a25@2U0*@O@as@>yX5m@H}@Pkw<@3w@/L &@( ^@|Pk@?5^I@K7i@4@@ʡE@6٬|@l g@Ciq@\ Ac@D@cZ@UN @ h@Nё\c@ioE@'1Z@/@ Ac@yX5m@( @7A`@Pkw@ @6W;@z,CK@A`@58EG@Dp@K@*I@e`TR@{P+@QX@>yX5 @jM@ꕲ qL@R'@gj+@QI@Nё\@ +@鷯@ O%@/n@H@V/@@=yX@?@|a25@H}8@ Ac@(@y@ h@:M@47@Q@Y8M@4@v@Biޱ@[잜@>@PsR@7A`@F@]m@n @Q{@y&1@؁sFv@JY@sF@J{/L@z6>@z6>w@~8gD @&†@~:@u@Zڊ@C @~@;O@)Ǻ@ŏ1w-!@zG@~@ -@ ^)@X2ın@\(@u@q@z6>w@hs@^)@k+ݳ@-罹@Oe@qh`@ -@ڊ@ZB>y@s@58EG2@R'@jq@:#J{@St$@h"lxze@|Pk@=U@a+e@HP@|?5^@X9v@&1@Ǻ@cZB>@'†W@D@&Sz@V/{@oT@jM@QI@@2w-!@q -@u@+η@ 0@K4@x $(~@v@H@y)@Έ@ +@K7@vOj @;ON@}b@Ǻ @W2@/@r?@~@D@鷯c@St$@p_@_L @<,Ԛ@n @9#J{c@3 @u@Q%@ҏ@_vOv@gDio @=U-@b=@K=5@Oe(@ڊ@ҏ@\mŞ@~jt# @/$f@F_@ -@c]F@|a2U@q -p@B@ޓZ@X2ı @ @@x@lV}@@߾|@$~;@ڬ\mu @ @@k g@c=yX@|?5^@ZB>@}?5^)@Zd{@ q@>٬@ׁ @x#|@(  @Y~@7d*@46@H} @F_@{/LJ@x&1@:@ׁs&@$@sAO@1e@T@v@8gDi@:M @\C- @fc]ܦ@;ON@Gx $@EJ@&S@B`"[@gsu@/'@'@8gDi@Ciq@l @S!u! @/ݤ@Ǻ @S!u! @) 09 @ $(~@ @u> @~:P @ hB @ۊe @D @$(~@nb @Ӽ @( @ @(\u @O @Έ @ǘ& @vJ @^K=k @D@K4& @ yY @Bi @g3 @CiqZ @K= @) 0@C6 @ǘ& @ c^ @|?5^* @ g* @Oe( @&†7 @@ @3R @ڬ\mu @LJJ @=U} @z6>W+ @T. @jt @m4 @0*% @a+U @ q8 @s[ @ hB @9#@Q|@Qu @QH @Zd;O- @ q8 @I&@@߾ @o_G@?W[\ @46@nb @sB @(~k @-!lv @KY8֥ @&†7 @x&! @( @ @fj @}b9 @Nё\c @iq @|a2U0 @}гY@ -@x&! @-C6 @v@-!lv @?5^IL @=UK @ Ac@". @F%uh @$(~ @J4 @,Ԛ @vJ @z6>W+ @A @ @>yX5m @s @ cZBN @+W @n4@2 @HPH @EJ@ǘ& @^) @/L @s @:#J{o @_Le @ZB>i @_L @Zd;@ec]| @N@A @Ǻ] @d]F @vq @yX5; @Mb( @;M _ @}8g @ۊed @z6~ @( @ @/$ @ݵ| @+n @^K=k @T. @k @-!lv @?ܵ @ @$~; @ -P @6@ @@X @Ӽ@d`T@OeS @ -@QI0 @X9v @%u{ @ q+ @#G @?߾ @ C @3d @@ @V- @/ݤ @ͪզ @@ @ec]| @K7A @8gDio @m @4@@  @ڊ @e @8gDio@ @|a2U0 @ * @_vO @n4@2 @ @N@3 @ꕲ q @CiqZ @p_ @{0 @? @Nё\c @BM @_L\ @R @?/ @ڊ @sA @OeS @MStt @ŏ1w @O @Bf @jMSd @HzG @&Sj @? @1w-!@2U0*@M O @Gx $X @eX @L F% @:#J{o @". @Mb( @|?5 @k @Oe @d]K @^K= @JYF @aT @ gz @ h @v @ ^) @ @485 @x @.n, @~:p> @6>W[ @*9 @Nё\ @ŏ1w= @E @1w-! @d;O @?߾ @ Ac= @+Χ @ݓ @[잜 @I&v @K7A @vq @F @&1, @jM @Hz @T㥛Đ @F%uh @(\ @ @\mb @6 @z): @k+ݣ @Bi @Fx D @u @St$W @hs @ݓ @/$V @ @' @ @MStt @eX @V @ b @Ǻ @a+ey @$(~ @ͪզ @uV~ @BM @cZ @;Nё @ё\C !@46< @On @1Z!@ @ qۈ @eXw @Bfj @( @33333S @A` @ݓ @D @f @1% @ @^)' @' @;Nё @n @QI @M O @V/w @2w-!t @o_Ω @Z @X9 @=yX @(~k!@_)Ǫ @ cZB @fa @=U} @q @xz,C !@fc] @? @ƫ @V}b @ea!@W[ @uq @V}b @ˡE @s @S㥛 @eXw @m4!@s @ @y&1 @A` @aTR' !@W2đ @?W[ @T!@]Fx @46< @ @r鷯 @gj+ @|a2 @n @Aǘ !@[ A @x @}8g @k @z @46< @6,!@/ݤ @s @{P @) 0 @ -!@2% @8gDio @ $(~ @m4!@m4 @+e @B]!@R @k @&†W!@ Q @Zd @ h @"~ @iq @]m @Gz!@jMS @9vO!@ + @_Q @V-!@s @w/-!@ r!@eX @&S!@_ @cZB>(!@#J{/ @㥛 @}bI!@ͪ!@}гY !@ @9# @m4 @w/-!@lxz,!@/'!@L F%!@x $(.!@Aǘ !@/n @K7A @ʡE&!@ O @a2U0*I!@uN!@|a2U0 @8gDi @_vO!@U @ec] @H.!M!@.1 @lxz,!@U @Zd;!@[ A @Af @ !@w-! @N@Q!@ΪV @I.!V!@tV!@ׁs!@M OT!@uN!@1^!@PkwL!@mV}!@M OT!@a+e @KY8֥ @"uq @Zd!@"lxz @S @ yi!@S㥛 @H} @_v @C6*!@5^I !@гY @HP3!@' @{p!@x#!@uN!@`TR'0!@jt(!@1w-! @ +!@5^I R!@9m4!@ea!@S!u1!@`vOj!@qh!@K46!@x&!@&S"!@rh\!@^)0!@]C !@(!@:M$!@#W!@B`"K!@:H?!@lV}.!@lV} @^!@}bI!@QI!@H}h!@j+]!@n!@Ԛ!@Q!@8gDi @T>!@!@|a2U0 @~:`!@:pΈb!@5^I R!@HP3!@H.!!@`"ۙ!@48Ew!@hod!@0*5!@#J{/,!@ qۘ!@U0*P!@ZӼD!@N@aS!@Ș_!@^I ;!@PkwL!@Xр!@|г9!@I&†!@@h!@Gr'!@On @Dl!@46W[!@-!l!@JY!@_L*!@H.!!@!@FH!@[Ӽ!@`"ۙ!@y&1!@uN!@=U!@^!@ŏ1w!@oş!@ڊe!@ F%u!@'1!@̜!@䃞ͪ!@:Mt!@46y!@ h"L!@B!@Bf!@c=y!@) 0!@6!@'1!@!@ڊe!@Dl!@\(!@hs!@Pkw!@>W[o!@w#!@Y!@%~!@%䃞!@<,Ԛv!@=yX!@|г!@&Sz!@?W[!@a+e!@<,Ԛ&!@!@t$^!@?!@S㥛$!@ c!@.!u!@tF!@W[!@h"lxze!@I.!V!@Oe!@:M$!@ !@=U!@j+!@鷯!@ :!@ı.n!@?!@!@8m!@ F%u!@/L !@٬\!@w/-!@&1!@;O!@z6{!@_!@0*!@t˞!@d;O!@_L*!@_L!@ rh!@[B>,!@Q!@{!@߾!@ܵ|!@S!@UN!@y)!@NbX9D!@ c!@I.!V!@ o_!@\mr!@N@!@K!@ڊe7!@镲!@-!l!@On!@L7A`!@j+!@H.!!@B!@aTR'Y!@JY!@9EGr!@H.!!@*Dx!@E!@UN!@-w!@x&!@,eX!@c=y!@Qn!@C|!@Q!@}8g!@!@/n5!@_Q!@St$!@iq!@uV!@St$g!@Gz"@a+e!@ʡu!@uV!@`"!@iq!@9"@!@R'!@ho!@Ƀ!@?ܵ!@d;O!@I&†!@†Wʂ!@Gx $!@7"@=U!@ F%u!@l g!@' !@uq !@V/!@8EGr!@鷯!@9# "@d`Tr!@d;O!@+~!@(\…!@Qkw!@w# "@!@cZ!@{p!@W2!@a+e!@!@\mr!@.!!@q"@K"@o_ "@ŏ1w-!@-"@RI&!@\(!@~8gD"@*D!@e"@|?5!@]m!@C"@sF"@K!@{Gz!@Qkw!@.!!@):!@uE"@ rh!@.!!@hs!@p_!@k+"@W2"@OjM3"@%u!@9EGr!@&!@Bi"@I +"@sA!@=yX!@Zڊ!@1*!@镲!@gs!@ꕲ q "@!@z):!@Pkw!@w-!!@W2!@ h"lx "@hs!@0*"@e"@ףp= G"@㥛 !@C!@ F%u!@St$!@QI"@!@{!@5;N!@R'!@ZӼ!@)Ǻ!@=U!@k !@F%u!@W2!@9# "@7"@V/!@!u@"@4@""@Zd;OM"@H}8!@ףp= G"@ho!@/nE"@㥛 !@vOj "@V/!@B>٬J"@5;N!@{/L!@鷯"@Ac]!@#"@㥛 @"@H}!@H}!@'"@!@rO"@^K=!@9"@y):"@9EGr!@ O!@):!@St$!@!@&䃞Z"@ʡ!@!@\CM"@9EGr!@Y8]"@\(!@St$!@7d*"@Bf!@<"@-"@("@ "@cZ!@镲 "@鷯"@uV!@&S"@fa!@SK"@~:p^"@D "@fc]V"@Tt$0"@^)@"@Qh"@V}"@3G"@ŏ1w"@Zd;"@9v_"@j+"@46<"@On!@~:p^"@n4@"@Z!@Cl!@ꕲ q\"@46"@472"@*"@-1"@1w-!!@NbX9T"@*"@fffffF"@SK"@u!@gs%"@48U"@ё\C"@|a2U0"@oů"@jMS!@MbXI"@Gz$"@'"@8gDi"@u"@uE"@l g!@+eB"@9"@ı.n1"@5;N1"@|?5^"@47"@w/="@*:X"@8"@fffffF"@FX"@X"@R'!@jtD"@?߾"@C6"@/nE"@47"@~j!@}8g!@=,Ԛ"@߾3"@!@oA"@/$!@=U/"@w/"@sh|?"@Oe"@uE"@I&!@߾3"@0*t"@Gr7"@v"@9S"@~k I"@vM"@-"@ʡE"@1Z"@S㥛4"@X2ı."@K4F"@HPC"@Xa"@,Ԛw"@Pkw"@Zd;"@|a2U0"@Gz$"@N@a"@[ AQ"@p= s"@*Y"@Zڊ!@z6>WK"@ F%u"@&S!@b4"@A`""@(\"@6WK"@z6>WK"@?U"@!@lV}>"@oA"@Zd;"@M Od"@0*t"@V-r"@8d0"@9#J{#"@<,Ԫ"@}b"@!@bٍ"@!@!u@"@E"@OnB"@St$!@jMN"@ǘF"@kw"@"@z6>W"@"@?ܵ"@>٬L"@n4@R"@鷯"@uq "@(\•"@0*X"@"@w/="@z6>WK"@=,Ԛ"@oA"@I.!f"@1%$"@mV}b"@&S2"@ǘP"@'"@/$"@}b"@iq"@9m4 "@r"@|a2"@!rh"@k "@8"@߾!@7”"@镲,"@1n"@镲 "@8gDio!@HPL"@~:p"@Q|ab"@h!@K4F"@鷯c"@m4"@ h"lxZ"@)\h"@"@Q;"@0*X"@c]K"@0L F5"@n4@R"@<,Ԛ"@v"@٬\-"@xz,Cl"@ŏ1w"@7d*"@H}x"@v"@^I K"@d`T"@}bY"@Gzt"@?\"@Έ"@"@Y:"@5^I b"@ea"@6["@LJ"@h"lxzu"@Ǻ"@ ףp="@ǘ"@fj{"@o"@46"@ c"@ŏ1W"@zG"@gDio5"@|г"@?\"@d`T"@n4@R"@`vOz"@ׁs"@ $(~9"@z6"@4@""@:M"@~8gD"@HN"@ q"@ı.n!@C6"@JY8"@鷯"@4@r"@&†"@T"@Gr7"@'1"@$"@`vOz"@3G"@gs%"@[ AQ"@D "@ZB>"@ǘ"@_"@( "@uE"@:M"@!rh"@8m"@yX5ͫ"@A`""@:#J{!@ "@O@aC"@sK"@_vO"@|гYe"@%"@D)"@ rh"@ׁs&"@|гYe"@ioe"@Șo"@N@"@Ǻ"@[ A3"@镲,"@]Ck"@ rx"@OnB"@H}8"@n "@C6"@~jt"@HPsw"@K4"@0*"@4@r"@R!"@t"@%Ck"@}b"@8"@Bi"@HPsw"@"@47"@s"@1n"@z6"@J4q"@ rx"@b="@B"@ec}"@8m"@ZӼ"@/$v"@L F%u"@1n"@fa"@ׁsF4"@8d"@"@$(~{"@~jt"@bX9"@46<#@oA"@V}"@gDio"@ioe"@^)@"@X"@S㥛4"@d`T"@V/"@ q"@jt"@]m"@(~k)"@zv"@w/="@_L"@<,Ԫ"@;pΈ>"@J +V"@ h"lxZ"@N@a"@$(~{"@*ԩ"@#J{/<"@2w-!"@W/'"@ڊe"@V}"@Έ"@8EGr"@Av"@#g"@Ǻ}"@h|?"@s{"@ʡ"@b="@x&"@Ǻ"@n4@R"@Jd"@g"@C6:"@*Y"@fffffF"@Șo"@X2ı~"@9m4p"@jt"@Gx $"@OjM"@g"@C6"@(\•"@Zd;OM"@[Ӽ"@( `"@(~ky"@v"@gDio"@$(~+"@cZB>"@_l"@>W["@6["@\C"@߾3"@LJj"@p= s"@s"@|гYe"@9m4 "@@߾|"@ rx"@_l"@St$"@5^I b"@aTR'i"@~jt"@Q|ab"@Pk"@ cj"@t$n"@X2ı~"@ "@\mŮ"@?ܵ<"@(~ky"@"@ g"@OjM3"@Q"@X5;n"@x&"@jt"@@G#@jt"@#~j"@r"@z):"@Q|ab"@Aǘ"@aTR'i"@p= s"@W2Q#@Pk"@"@48"@]Ck"@`TR'"@ׁs"@V"@(\•"@MSt"@qR"@|г"@^)@"@46"@"uq]"@46"@ׁs"@LJj"@#J{/<"@V/"@Xѐ"@Jd"@$~"@Q|ab"@<,Ԛ"@Gx $"@8mD"@$~"@{"@:pΈ"@nz"@ec}"@ڊe"@ F%uJ"@LJj"@-"@H"@Oe"@†W"@cZB>"@oʑ"@>yX5"@^"@N@"@( `"@0*t"@c]F"@yX5ͫ"@z):"@K7q"@"@N@"@V-r"@jq"@ŏ1w"@oů"@X"@:pΈ"@!rhm"@s"@\("@Gzt"@6["@%䃎"@0*"@( `"@Pk"@jMS"@_vO"@s"@K="@Bf*#@("@ʡE"@`TR'"@s{"@Tt$"@H.!"@V-""@6W"@Bf"@$~"@ec]<#@-f"@>W["@d`T"@D"@Aǘk"@_vO"@M O"@Zd;o"@†W"@}?5^"@HP"@1n"@48E"@Aǘk"@St$"@/$"@jt"@"@fa"@ F%u"@X"@H}8"@z6"@K7"@†W"@46<#@Ӽy"@tF"@{"@oʑ"@\("@zG"@vOj#@j+"@46"@jt"@=U"@M O"@mV}b"@7d:#@?"@|гYe"@!rhm"@uU#@bٍ"@Aǘk"@]m"@) 0"@l g#@~jt"@X9v"@K79"@46"@#@k "@Oe"@ "@46"@_v"@LJj"@?5^I"@q -"@bX9"@H#@X"@ZӼ"@6["@( "@"@?W["@37"@~:"@`""@"@>yX5"@:pΈ"@T㥛#@Cl"@1段"@&†"@]K-"@Έ"@q= ף"@&S"@zv"@W/'"@%u"@<"@Ӽy"@M Od"@M O"@x&"@H}8"@)#@s#@jt"@?"@ "@V-r"@H."@ݓ"@J4"@ec]"@Zd;o"@Qkw"@(\"@46"@MJ"@)\h"@&1"@z):"@ec]"@46"@zG"@c]F"@-!l"@v"@ݓ"@6yX5"@LJ"@^K="@zG"@ec"@{"@jqT"@m"@9#J"@6#@Zڊ-#@X9v"@6["@aTR'i"@Cl"@ -#@W["@'1"@}b"@?ܵ"@ŏ1"@c]F"@a+"@+ݓG#@z6"@) 0"@鷯,#@!uP#@S"@d;O"@I.!f"@Oe"@t"@g"@~:"@Ș"@|г"@I.!f"@d`T"@eaa"@Cl+#@6"@6#@7A`#@"@Q"@s"@h|?"@tf"@Ӽ"@_L"@:pΈ"@io"@""@ c"@_l"@>yX5"@Qkw"@ec"@3"@Oe"@/$v"@fffff"@iq.#@X2ı~"@l g#@N@a"@fj"@ "@b="@ǘ"@EGr"@x&"@cZ"#@33333"@u"@p= s"@"@+"@0*"@("@eX"@"@1*"@ׁs"@Gx $#@鷯c"@`TR'"@8EGr"@( "@Y"@Έ"@_"@ c"@q -"@-"@N@a"@J4"@Q"@ho"@ec"@†W"@l"@B"@=U #@]m"@#@&S##@~jt"@ "@}?5^"@~jt"@a"@Q"@JY"@p_#@sh|"@rh"@ y"@RI&"@ʡE"@(M#@#@o"@%u"@)#@a"@ec"@ۊe"@JY"@JY8"@]m"@W["@~jt"@;M "@+"@†Wʒ"@Fx "@Fx "@a+"@=U #@<,"@) 0"@ y"@Qh"@ h"@Ǻ"@Y"@hoQ#@"@ rh"@ׁs"@33333#@-C"@%䃞 #@Qkw"@X2ı~"@N@ac"@ y"@46<"@$"@s#@$"@鷯#@h|?"@+"@&†"@vq -#@ŏ1w"@fj"@"@ʡE"@V/"@l g#@Oe"@R'"@镢"@JY8"@yX5ͫ"@H."@T"@QI #@Biq"@ZB>"@oT"@ׁs"@ "@Ǻ"@6"@ho#@;M "@I&"@Zd;#@/#@Ǻ"@[Ӽ"@6#@|a2U0"@&†"@l g#@\("@( "@io"@q= ף"@}?5^"@7A`"@uV"@):O#@,eX"@2ı."@t"@m4 #@+"@Mb"@46<#@rh"@ r"@:#J{"@46<"@Oe#@@"@6>W["@eX"@Ԛ"@a+e"@X"@Q"@x&"@ "@o"@jt"@uV"@ cZB"@$~"@>yX5"@!rhm"@MJ"@L7A`#@lV}"@lV}"@q= ף"@?ܵ#@&†"@䃞ͪ?#@zG"@z):"@Gx $"@io"@"u"@Dl"@:pΈ"@ g"@1n"@rh"@8gDio#@@#@oŏ#@k @#@-f"@eX"@/$"@ h"@48E"@-"@q -"@ g"@|?5^"@ǘ"@_)"@ cZB#@ޓZ##@/$"@[ #@_Q #@ c"@8gDio#@Ӽ"@"@Gr"@C"@Bf"@/$"@ڬ\m"@D"@ y"@<,#@Pn#@{/L #@F%u(#@?ܵ"@ ^)"@V}b"@v"@Nё\##@z6"@Zd;"@M#@_Q #@(\#@@#@N@a"@7A`"@[ #@F%u"@ݓ"@p_#@F%u"@\m"@Gx $#@vOj#@St$#@l"@LJ"@lV}"@vq "@|?5^"@_Q #@$"@QK#@lV}"@EGr"@ "@v"@&†"@y&1"@гY:#@s#@46<"@F%u"@Dio"@gs5#@Q"@ /#@1%4#@#"@z6>G#@2ı."@V/"@ec}"@$"@LJ"@-C"@"u"@xz,Cl"@B"@EGr"@Qkw"@Q"@*D"@=U"@_vO6#@@G#@Ӽy"@(\"@$"@#@uV>#@7#@S"@2w-!"@UN"@_vO"@ܵ|"@Gzt"@( "@(\"@Qkw"@Pk"@ec]"@ǘ"@Dy"@|a2U@#@4@r"@Bi"@V/"@H."@\m"@EGr"@2U0*"@Aǘk"@&SB#@Mb #@#~j#@߾"@n0#@1w-!"@]Ck"@ "@"@H."@'1"@vq "@&S"@Mb #@""@ׁs6#@R#@ Q #@ܵ|"@z):+#@iq.#@H."@ڬ\m"@ё\C*#@ͪ#@_vO6#@)Ǻ"@(~ky"@Mb #@}?5^9#@W[#@"@%䃞 #@YJ#@b4(#@fa&#@z,C#@ q"@1n"@RI&2#@c]FC#@JY8"@R!"@KY8"@Ǻ"@`""@R#@"@("@&S%#@Ș"@?"@l g#@<,"@"@F%u(#@C"@+ݓG#@p= "@鷯,#@X2ı~"@"@ec]<#@fa"@1Zd"@2U0*"@?W[#@,eX"@z,C#@ OE#@+#@9EGr"@o_#@x $(~"@ "@V}b"@_v"@&SB#@\("@H}x"@~ #@[B>ٌ"@Gz#@_Q #@R'!#@("@JY"@ y"@K7I#@r"@,eX#@#~j"@q -"@LJj"@( #@ q"@&1"@37"@ 0z#@j+'#@8gDio#@Q5#@Έ"@'1"@Ǻ"@fj"@)Ǻ"@UN"@x $(~"@=U"@_vO6#@UN"@d;O"@uU#@6>W["@H}x"@?"@LJj"@ˡE #@vq "@"@ݓJ#@J{/L"@ y"@V"@ #@Biq"@RI&"@ׁsFD#@Q5#@K7"@ q#@?"@'1#@( #@q -"@X96#@E$#@7#@&S"@ec"@6["@s"@Ciq"@Ciq"@^K="@"@M O"@J{/L&#@ h"l#@_v"@HP"@[ AC#@X9v"@H}8"@|a2U@#@8gDio#@9#J{3#@|a2U0"@.!"@Q#@x $(N#@W[#@ h"@gs5#@~jt"@ y"@lV}"@y&1"@†W"@<,"@Q"@/$"@c]F"@)#@<,Ԫ"@ $(~I#@ 1#@V}b#@Q|"@p= "@/$"@LJ"@/nU#@ /#@Έ"@@a"@;M #@ ^)"@Cl"@ /#@k+#@ O"@ZӼ#@Q#@x $(~L#@d`T"@+eR#@Oe"@46<#@߾"@<,#@46<}#@b4(#@C"@;Nё,#@t"@1%4#@?.#@~8gD)#@+eH#@33333#@@G#@ZL#@' #@c]F"@ 1#@W2#@ׁ#@5;NA#@}8gT#@ "@x $(~L#@!uP#@x $(#@#"@I +g#@z6#@Mb #@zG"@io4#@.!"@6["@z):+#@eX7#@n"#@U#@t"@sF&#@ҏ"@m4#@ h"l8#@Zd;#@V-=#@Q5#@}8g#@H."@W2Q#@c=y#@vq -#@!lV"@io4#@p_#@X9v"@\("@&S##@ׁsFD#@_)#@xF#@"lxz\#@Oe#@ׁs6#@6#@lV}#@S!u#@=U"@sA#@ q"@؁sFF#@ڬ\m"@ZL#@;O"@iq.#@m{2#@o_i#@MSt"@ޓZs#@?W["@Oe#@K7A`#@}8gT#@+eH#@2U0*"@鷯"@-!l"@2U0*##@2U0*##@3"@}?5^9#@$~"@iq.#@!lV"@uU#@ˡE #@s"@<,"@ec]"@ OE#@Cl+#@:p#@/L #@@#@tF"@U#@?ܵ#@]K=#@ "@ /#@cZ"#@Έ"@y&1"@hs#@+#@&S##@bٝ#@Gx $#@6["@ZӼS#@33333"@Bi#@=yX%#@镲 !#@KY8"@#@rh"@<,#@a+"@z,C#@ŏ1w-1#@ $(~I#@#"@a+e"@V#@sF&#@|a2#@MSt"@?W[#@W2Q#@~ #@/L #@ё\Cz#@y&1"@c]FC#@:#@ o_#@S:#@Aǘk"@"@^K=+#@io"@7A`#@}8gT#@o"@_L"@Zڊ"@( #@ݓe#@ׁs6#@:p#@:#@鷯#@|гY#@ -#@Q"@33333#@<,#@ #@c]FC#@0' "@/$"@Z"@J{/L"@/L #@^K="@ 0z#@[ #@ "@ׁs6#@ +9#@|a2U@#@$"@?ܵ"@9#J{3#@o"@tN#@+"@fj"@W[#@Q#@C`#@L7A`#@T$#@|?5.#@6["@ y"@}гYy#@Ǻ"@ec"@UN"@|a2U@#@kw"@@"@V"@Cl7#@Bf*#@~8gD)#@Q"@?.#@Gx $"@?W["@-f"@1w-!O#@"@}?5^"@?߾#@+eR#@6>W["@S"@I&"@3"@?5^I"@?.#@OjM"@ ^)"@7[ Q#@AfU#@9#J"@?߾#@ׁs6#@~:"@ -#@_L"@?"@V/"@J{/L"@io"@Psr"@oʑ"@Gr"@ho"@6>W[!#@ec"@†W"@{P #@eX7#@ q"@H."@x $(N#@rh"@|г"@ZB>"@?"@+eR#@w-! #@z6>#@ "@ y"@Pn#@$~"@ΪV"@0' #@l g#@m4#@ŏ1w"@jt"@W2#@z):+#@ h"@MB#@y&1<#@J{/L"@ݓJ#@T㥛#@37H#@9EGr"@:M"@b4"@1w-!"@ݓ"@ʡE"@9#J{3#@"@@"@( "@b="@|г"@1段"@ׁsFD#@x#@(\#@ZL#@/';#@46<"@:p#@C"@k '#@6"@1%4#@鷯c"@8EGr"@ڬ\m"@_L"@ OE#@R'"@>W["@-"@o_#@ ףp="@_L"@m4 #@sA#@Bf*#@JY"@|a2U0J#@-C"@d`"@z6"@:#@:p#@:"@=U"@UN"@ZB>"@A`2#@R!"@K7I#@UN"@xF#@48E"@(\#@ q"@Dio"@LJ"@h|?"@S㥛D#@HPS#@&†"@46<"@<,#@Nё\"@QK#@OnR#@*D"@jMS"@eX7#@d]F#@<,#@|гY"@H#@N@a"@=U"@s"@x&"@uU#@&S"@x#@c]FC#@ ^)"@io"@("@6["@ŏ1w"@oů"@ -"@:#J{"@v"@Ǻ"@_L"@Zڊ-#@58EG"@K7q"@58EG"@]Ck"@\m"@33333#@s"@n0#@ q"@<,Ԛ"@oT"@ZB>"@|?5^"@"@kw"@?"@J4"@1w-!"@ZB>"@H"@jMS"@U#@ y"@1"@gj+#@1段"@_)"@MJ"@OjM"@"@K7q"@Dio"@o_#@#~j"@<,Ԫ"@fj{"@Pkw"@ Ac̭"@㥛 P#@ -"@v"@|?5^"@n4@"@*D"@0*t"@D"@ ^)"@1e"@t"@^)"@B"@+"@ׁs"@48E"@H."@Cl"@Oe"@zv"@%"@:M"@Έ"@ "@A"@6W[!#@@a"@ Q #@46"@46"@&S##@s"@ݓ"@9#J{3#@DD#@q -"@Ǻ"@q -"@Q"@ Q"@Bf"@fj"@q -"@Pk"@6#@V"@Dl #@ڊe"@;Nё,#@a"@ׁs6#@bٍ"@&†"@T#@ "@M Od"@8EGr"@m{"@@a"@a"@lV}"@J{/L&#@W2#@&†"@MJ"@MB#@ Q #@C6"@;M "@&S##@ cZB#@z6>G#@&†"@Qkw"@LJ"@9#J"@+#@Zڊ"@):O#@ "@?߾#@)#@d`"@\m"@%"@ O"@|гY"@Bi#@Nё\"@\m"@ZӼ"@}b"@6["@I&"@( "@ "@n"#@Mb"@W2#@ h"l8#@m4 #@YJ#@V}b"@MB#@=,Ԛ}#@ʡ"@1*"@Z"@z):"@ y"@|a2#@lV}N#@MB#@HP"@K7I#@2ı."@]m;#@Mb"@k "@T㥛#@]K=#@n0#@d`T"@a+e9#@lV}N#@ܵ|"@w##@<,#@ı.nA#@ 1#@7[ Q#@W2#@h|?E#@Q#@K7"@_L"@D0#@_)"@Gx $"@ cZB"@[Ӽ#@h?#@3ı.nS#@ё\C*#@?W[#@V/"@KY8#@B"@}8g#@ڊ%#@M O"@EGr"@%C{#@ޓZ##@=yX%#@33333#@):O#@|Pkz"@}?5^9#@~8gD)#@y):#@T$#@c]FC#@uU#@)#@F%u"@X9v"@_Q #@?"@iq.#@߾"@"u"@KY8"@x $(N#@oʡ#@a+e9#@( "@UX#@Dl #@Q"@BY#@N@a"@_)"@H."@^K=+#@A`2#@%u"@7A`"@_"@.!"@гY:#@#"@@#@OjM#@-A#@ O"@_#@3"@y):#@㥛 P#@s"@W[#@Oe#@!lV"@(\"@W2Q#@5;NA#@xF#@ׁs6#@?5^I #@UN"@|a2U0"@( "@z):+#@<,"@ׁs6#@_v"@|a2#@?5^I"@JY8"@k '#@ZL#@s"@ 1#@A`2#@(\#@ŏ1w-1#@d]F#@䃞ͪ?#@H#@""@|?5.#@9m4#@鷯"@ O"@D0#@?W[#@W["@V/K#@&S##@6;N"@HP#@^)P#@9#J{3#@ׁsFD#@a"@X96#@ o_#@&SB#@@a"@Zڊ-#@L7A`#@c=y#@aTR'y#@8gDio#@io4#@ Ac"@q= ף"@ "@a"@33333#@z6>G#@k+#@QI#@+eH#@St$"@vOj#@1%4#@33333#@JY"@:pΈ"@Ǻ"@8d"@h"lxzu"@g"@\("@;O"@}8gT#@ׁ#@&Ss#@x##@lxz,#@Fx #@ʡE#@C#@""@e`TRg"@؁sF6"@ۗ!@[ A @ o_!@ @ʡu!@Q|aR!@@aӛ!@N@ac"@/$#@ #@_L5$@:px$@߾S$@$@†W#@_)#@"@o"@vOj!@QI!@_L!@&!@lV}V!@Q|!@S㥛$!@V/!@m4"@vOj!@_vO!@N@!@!@F_ @h @B @T @ rh!@ΪV@v@}b@ F%uz@!u@^I @Ӽ@{Pk@QE@yX5{@>yX5-@vq @UN@&S@ڬ\mE@x&@1n@ŏ1w@9#J{@6W[O&@cZ&@ Q'@MbX9(@cZB>(@[)@`TR'(@߾)@M O)@%)@؁sF)@J{/L)@S)@(@&䃞͚(@r(@=yXU(@|?5(@<&@q= ף&@^)g&@?&@=yX%@ y7%@+ $@/L f$@lV}$@;Nё$@ʡE#@o_W#@p= "@_L:"@٬\!@Ac]{ @:pΈR @cZb@eA@o_@0' 5@Gx $(@AfU@e`TR'@&3@Fx @Pk@:MM@sr@M O@ *@J{/Lf@ec @uV~ @c]F @ۊet!@/L !@_vO"@ "@"uqm#@#@n@$@d]F$@Ӽ$@N@a#%@H.O%@%@%@I.!6&@7[ !'@ Ac̍'@E(@jM(@@a(@x $()@ q+*@tF*@,CR+@$~+@ cZB~,@",@}?5^,@p_-@:Ho-@^)-@c]F-@&䃞*-@6>W[,@ $(~+@ r(+@2w-!D+@RI&*@8gDioP*@z6)@V-})@ ףp=)@Oe)@B>٬(@l g'@d`'@Gz'@鷯C'@e`TR7&@N@1&@ gZ%@Tt$$@:#@0' #@8gDio!@гY!@- @X2ı @9v_@gDioe@ZB>Y@&䃞@(m@Aφ@|a2U@6@?5^Il@8EGry@w#@:#J{@(@\ Ac,@QI@z,Ck@r@ @8EGr9@镲 @d;Ow@鷯C@@Q|@o_Y@Ǻ @x&! @DJ @x $( @Z @"~!@<"@OjM3"@гY:#@0' "@x##@ڊe#@Bi$@<,$@d`T$@Zd%@j+%@c]K%@b]&@=U&@Vد&@!lVm&@W[&@S&@zGq&@vq &@Ș&@u&@gDioU&@d;O%@J +%@Ș/%@ڊe%@Uh$@J{/L6$@Pn$@"lxz#@w-! #@Gr"@)\"@.!!@3ı.n3!@|a2U @^K= @? @Ciq@xz,C@H}@ cZB@s@N@!@1*@3@5;N@@W2@@ׁs@W/'@Zd;OM@:MM@%䃞@Fx @ZB>@;M @ $(~@ׁsFt@ @XQ@ͪϵ@y&1@+n @ @ q;!@!@EGr"@ O"@x $(#@+ #@A`В$@ec=%@:pΈ%@ h",&@ c&@.'@Mb'@T(@Q{(@ʡ(@5)@+eB)@ h")@fffff)@ r)@o_G)@+)@gDiou(@LJ'@( @'@ '@7&@v*%@w-!$@ q#@Gx $"@B"@2U0*!@a2U0*Y"@&1!@Aǘ !@? @ׁs!@Ǻ` @QH @gDio @o? @{PK@ܵ|p @q -p@o_@mV}@猈@3ı.n@58EG2@yX5@@ QI@Z<@" @378@$(~@^) @ @ @L7A` @!u0!@o1!@b=y!@hs!@X2ı."@ioe"@ Ac"@ Ac"@~:"@Ӽ"@aTR'i"@a"@N@a"@n0#@A"@@a"@s#@9EGr"@y):#@ -"@tN#@e#@eX"@:#J{"@Oe"@*D"@37"@6["@Nё\"@zG"@"uq]"@Dy"@ǘF"@c]K"@aTR'i"@ h"\"@-w!@(!@ cZB!@1^!@:pΈ!@Vm!@W2 @ r!@j+]!@uV @DZ!@U @I.!V!@H.!!@C|!@oş!@d]F!@Q!@ݓU"@{!@ǘP"@H."@n4@R"@ܵ|"@6#@0*Є#@UX#@X#@ -x#@k#@x##@D$@}гY#@x##@S$@sk$@鷯$@$(~$@T4$@Uh$@Cl$@#~j,$@ $@d;O$@,C$@~:p#@) 0 $@oT#@j+#@Q|#@H.#@TR'#@iq.#@T#@Q|ar#@kw#@yX5ͻ#@1Zt#@jt#@lV}#@0*h#@xz,C|#@X5;#@ F%u#@{#@J4#@}b#@٬\#@Q|ar#@'#@bٝ#@##@2%#@xz,C|#@!uq+$@(#@a+eI$@-!lF$@St$o$@ׁsFT$@[B>٬$@C$@9$@S!u%@z6$@K4%@|Pk$@*%@oʱ$@=,Ԛ$@V/%@$@]KM$@ OU$@V$@o_$@|?5$@hO$@Ǻ$@QkwR$@Uh$@ڊ$@ׁs$@Onb$@$@-Q$@,eX$@c=yx$@gsE$@F%u8$@Ș$@`vO#@[ Aa#@|гY#@:M#@I.!v#@) 0"@w-! #@Gx $#@hs#@QI #@}гYy#@|a2e#@uq #@ݵ|Ѓ#@1#@U0*#@u$@|a2e#@`" $@EGr#@@a[$@$@d$@"uq$@ec=%@p_q%@46<"%@LJ*%@,Ԛ$@V/W%@}?5^Y%@:]%@V}b?%@a+eY%@-!lV%@ǘ%@|г&@37%@%C%@]m%@9%@U%@HPs%@{G &@S㥛%@ h"l%@h%@ZB>I%@mV}%@QU%@.1%@ B%@ rh!%@v*%@ $@S%@io$@):˯$@vq =$@`vO$@1w-!_$@$(~$@Gx $($@y&1L$@Gz$@Yڪ$@Gz$@䃞ͪ$@NbX9$@!uq{$@OjM$@<,4%@a4%@S!u%@Gr$@v*%@@߾$@S%@/'$@= ףp$@-Q$@#~j,$@[l$@i$@mR$@[ A#@F%u8$@ho#@' V#@ڊu#@Psׂ#@jt#@jMS$#@Hz#@-"@[Ӽ#@$"@""@V-"@$(~{"@\mŮ"@ "@Psr"@("@-!@]m!@1*!@oŏ"@Ac]!@HP3!@/$!@Oe!@+ݓ'!@~jt!@aTR'Y!@ S!@ΪV!@SE!@=U!@d;O!@޲!@ho!@ŏ1w-!@p_#@x6"@xz,Cl"@ŏ1"@ׁsFD#@Q5#@ı.nA#@xz,C#@ q#@tF#@48$@NbX9#@F$@jMs$@+eX$@<, $@,Ԛ$@ׁs$@ $(~$@ܵ|%@8d$@jt%@x&%@zG%@V}b?%@ y7%@b=$@ q%@Zd;O %@ڬ\m%@;pΈҮ$@3ı.n$@%C$@xy$@?ߎ$@ʡ5$@ #@68"@yX5ͫ"@AfE"@"@^)"@8gDi_"@ o_."@#J{/<"@5;N!@!@-!@ͪն!@ !@?!@Y!@W2!@)Ǻ!@o_ "@33333!@T!@_Q!@_v!@H}8!@2%S"@6>W[!@AfW"@Q "@[!@OnB"@="@HPsw"@0*"@#g"@&†"@a+e"@'1"@Y"@v"@z6>#@-v#@W/'#@|Pk#@m4g#@Q#@1%#@:M#@_L#@?e#@#@ʡE#@J +f#@#@|г#@D@$@V#@H}]$@a#@ׁ#@Q#@ q#@JY#@:M#@ y#@ h"lxj#@o_W#@۷#@9#J#@ݓJ#@%䃞]#@OnR#@vq -#@~8gD)#@\m"@C"@9EGr"@Ӽ"@"@oT"@"@*D"@ho#@6["@3"@qh"@"@e`TRg"@6;N"@@a"@aTR'y#@QI #@%䃞 #@jt#@&†#@M Ot#@S#@$@-Q$@$@DioY$@鷯$@aTR'$@1$@Q%@&1 %@QI}%@}?5^Y%@W/'$@Ux%@:#J{O%@ qh%@l&@h|?e%@ rh1&@%@%䃞}%@y&1\%@%u[%@1w-!o%@ͪ%@d`TB%@#~j%@?W[<%@ʡE#%@vq M%@a4%@= ףp$@L F%$@"lxz$@v$@St$o$@]$@X2ı$@H.?$@-阮$@Ǻ$@ 2$@#@6[#@|a2e#@fffff#@I +g#@B`"k#@&S#@V"@y):#@=yX%#@o_#@0*h#@W2Q#@r#@(~k#@+ݓG#@I.!#@MB#@|Pk#@aTR'y#@^#@\ Ac#@.1#@I.!#@ioD$@c]K$@o$@Mb$@1*T$@-$@K=$@M O%@[ A$@ZӼ%@9#J+%@:pΈ2%@d`TB%@QU%@?W[%@T㥛p%@!lV]%@Mb%@ͪՆ%@2U0*C%@Ǻf%@-G%@9$@O@a%@ OU$@гYJ$@%䃞m$@N@a#@W[$@}b#@QI&$@R!#@3ı.n#@mB#@J{/L&#@m4#@"@QI #@ "@6["@ׁs"@:M"@C!@0*X"@K4F"@!lV!@=U!@V!@X9v!@I +"@JY!@ F%u!@J"@гY!@/'+"@u!@fa!@Zd;"@MJ!@2w-!!@x6"@9"@7A`"@x&"@ o_~"@J{/L"@ "@MSt"@3"@|гY"@ cZB"@s#@0*#@1Zt#@A`2#@z,C#@F_X#@C6#@Oe#@ݵ|Ѓ#@ʡE#@{#@V-#@ h"lxj#@+#@K7A`#@:H#@d`#@'†WZ#@C#@St$'$@e`TR#@Qkw$@ g#@j+$@H#@@W$@hO$@gj+&$@"@-"@Av"@0L F"@ۧ"@K79"@)\"@=,Ԛ"@ZӼT"@9EGr!@|a2U0"@Y!@E"@9"@ݓU"@ -"@Psr"@%Ck"@x&"@uq !@_vO"@7d*"@ׁs&"@ c"@~:p"@u"@0*X"@̬"@+e8"@鷯"@ o_."@^"@jt"@&1"@ o_~"@>W["@W/'"@ΪV"@/$"@.!"@X2ı~"@n4@R"@ c"@@߾,"@<,Ԛ"@m4"@V--"@D)"@)Ǻ!@cZ!@Q|!@ŏ1W"@ڊ"@a+e!@*D!@ Q!@$~!@k !@ y!@ܵ|!@):!@ۗ!@x#l!@Bi"@\mN!@jMS!@2%C!@R!!@<,Ԛv!@St$g!@W[!@=U[!@[Ӽ!@V!@޲!@y):"@v!@:M$!@"u|!@QI"@ǘ"@~:!@=U!@}8g!@*"@~:p^"@ǘP"@uE"@!rh"@N@"@aTR'i"@T"@d`T"@}гYi"@?"@M O"@@߾|"@fa"@ݓ"@$~"@Oe"@S㥛#@W2#@6#@~:"@X9v"@=U"@zG"@ڬ\m"@(~ky"@|a2U@#@Zd;o"@z,C#@46<"@( "@Q"@2U0*##@-"@Dio"@""@ r"@K'#@b="@ZӼS#@ OE#@镢"@"u"@YJ#@;O"@jMS$#@ݓ"@sA#@c]K(#@/';#@8#@F%u(#@~8gD)#@9vo#@V-#@ q#@ /#@S!u#@7[ #@\C#@x##@S:!$@= ףp#@cZ2$@\(\$@;M /$@]$@hs$@"uq}$@4@$@X9Ȗ$@猨$@Pkw%@~k %@r%@8d$@v %@[B>٬$@ cZB~%@a+5%@Y^%@V/%@( )%@hoq%@d`T$@_)NJ%@k `%@Q>%@ʡE$@ y7%@Ac][%@s"%@o%@ $@B-%@oʱ$@a2U0*%@H$@Zd;O$@B$@Q$@9m4$@Zd;O$@K7Ap$@($@E$@ǘp$@ݓ$@{/Lj$@T㥛`$@ҭ$@@a[$@ݓZ$@-C$@?5^I$@ףp= $@)ǺH$@}b$@Ӽ$@Y8$@oŏq$@ h"lx$@aTR'$@$@On$@Tt$$@\m%@}8g$@ꕲ q$@V/$@LJ$@ho4%@ec]$@ڊ$@$(~$@J41%@ʡE#%@w#%@xz,C$@0L F$@Ps$@ˡE$@$@6$@7[ $@V/[$@ c$@]Fx$@cZB>$@-$@$@B>٬$@$@ec]L$@-CV$@Tt$$@HPs$@oŏq$@QIm$@Bi$@6 %@&S$@[B>٬$@o_$@d$@JY8%@ׁsF$@gj+v$@V-$@37X$@sk$@U0*$@6W"@p= s"@JY8"@Ӽy"@l"@ "@|г"@6"@Gzt"@jtD"@MbXI"@3G"@^)"@X9&"@\ Ac,"@ۊe"@0*"@<,Ԛ"@,Ԛw"@@a"@ho#@!rhm"@[ A3"@jMS"@$~"@9EGr"@(\"@@a"@@"@ǘ#@q -"@1%4#@ #@BY#@x##@iou#@ё\Cz#@a+%$@Oe#@?ܵ$@#@B`"#@/$%$@~: $@V/[$@uVN$@B`"#@Uh$@9m4$@ c$@9#J{$@ׁsFT$@ŏ1w $@a4$@z):$@~k $@٬#@ 0z#@v#@o$@8EGr#@"lxz#@x&#@d]K#@^)#@Gr#@_vO#@s[#@?F#@~:#@h"lxz#@Zd;#@33333#$@?l#@ #@]Fxk#@Bi#@+ݓ#@ $(~#@9vo#@ rh#@ʡE#@/$#@#d#@_L#@' V#@|гY#@_vO#@BY#@c=y#@_vO#@Zd;#@o_i#@S#@B>٬#@_L#@A#@Afg#@a#@镲#@o#@9v#@@#@ h"l#@lV}#@D#@W[$@ˡE]#@ׁ#@r/$@St$#@ h"lxz$@9EGr#@gsE$@Bi#@D#@镲#@R!#@&†#@6+$@H}#@d]K#@6$@X$@ǘp$@~8gD$@EGr#@o$@H.?$@$@d;OW$@,C#@?5^I$@hse$@lV}#@_L5$@hs$@6ٜ#@Q#@ͪf#@ o_#@?ܵ#@8m#@Q#@V#@٬\#@= ףp#@48#@]Fx#@^I #@ݓe#@uq 0$@9#J$@mV}r#@ y'$@)\x#@Q|a#@y):b#@Q|ar#@kw#@x&1$@u#@C#@J4#@<<$@X#@B$@ y'$@H}#@d`#@A#@eXG$@xz,C#@#@##@ŏ1#@.!#@tF#@^)#@}гY#@x##@ZB>#@e`TR#@†W#@ho$$@#@{#@|Pk#@K=#@TR'#@ #@y):b#@#@[B>ٜ#@X5;~#@b#@9c#@/$#@Q#@{G#@*:h#@ۊe#@;Nё|#@1#@w-! #@Pkw#@_V#@5^I r#@a+e"@`TR'#@ q#@YJ#@ y#@=,Ԛ}#@6W[#@Zd;#@7[ #@3#@/L #@Q#@ #@1%#@-#@z6>W#@ZB>#@`vO#@ʡE#@=,Ԛ}#@@߾#@Y#@_vO#@j+#@+#@pΈހ#@eaq#@Y#@#@Pk#@ׁ#@FԸ#@Qڛ#@X9Ȇ#@MB#@鷯s#@ʡE#@OjM#@^)P#@ y#@U0*p#@d`T#@'†WZ#@oŏ#@9v#@B>٬Z#@z6>W#@d`#@aTR'#@T#@/';#@jM^#@0*#@ q#@鷯|#@v#@ݓe#@}гY#@%C{#@|a2U#@Ș#@V-#@D#@B>٬#@W/'#@~jt#@ޓZs#@Aǘ#@#@B`"#@ZӼ#@~k #@ܵ|#@.!5$@X9Ȇ#@NbX9#@V?$@I.!#@Ӽ#@x&#@x&1#@q -@$@#@Ǻ#@u#@;pΈҞ#@7#@EGr#@qh#@&䃞ͺ#@rh#@@#@\ Ac#@lxz,#@e!$@ y#@S:!$@ #@jt#@QI#@J{/L6$@kw#@aTR'#@:M#@= ףp#@ q#@bX9#@|?5>$@d`T#@xy$@Dio $@#~j,$@sA$@_L5$@QI$@S#@V?$@;M /$@K7Ap$@sk$@=yX$@9#J{$@~j$@?#@T$@t^$@58EG$@ףp= g$@k $@V?$@~j$@6>W[1$@#~j,$@ʡ5$@ΪV#@6W#@+'$@^)#@۷#@Q|A$@b#@ #@†W#@2w-!#@= ףp#@io#@p= #@@#@_Q$@m4g#@z6#@xz,C#@&C$@6yX5=$@ #@yX5ͻ#@xi#@ףp= W#@46<}#@5^I r#@6;N#@(#@K4#@,C#@ݓe#@N@a#@x&1#@I.!v#@$#@##@xi#@W/'#@A#@K7#@F_X#@QI#@#@ףp= W#@Zd;#@UN$@m4p#@\m#@Ps#@aTR'y#@a2U0*#@Aǘ#@ c.$@ y#@M#@T8#@䃞ͪ#@a#@:H_#@c=y#@Fh#@{G#@ˡE]#@ׁ#@#@ #@m4p#@Ӽ#@/L V#@Fh#@jt#@ͪf#@#d#@Zd;O#@"uqm#@eaq#@C6#@BY#@z6#@>٬#@(~k#@pΈހ#@)\x#@ΪV#@mV}r#@fj#@C6#@bX9#@ #@X9Ȇ#@l g$@Ș#@St$_#@#@\ Ac#@ׁ#@ZӼ#@:#J{#@T$@lxz,#@t#@/$%$@:H_#@ -x#@x&1#@ͪ#@"u#@Oe#@ڊe#@E$@[B>ٜ#@Af#@xz,C#@X2ı#@N@$@T#@(~k#@=,Ԛ}#@鷯s#@kw#@F_#@pΈ#@.1f#@Aǘ{#@&Su#@}b#@ǘ`#@Gz#@R#@\ Ac#@}гY#@F_X#@AfU#@2%c#@?F#@z6#@6٬#@9vo#@D#@C`#@ףp= W#@+ X#@Y8Ž#@;pΈҞ#@Ql#@&S##@T#@C#@#@Mb #@sh|#@Zd;#@Pk#@ޓZs#@镲 !#@J{/L&#@ OE#@Y8Ž#@io#@0*#@Gr#@O@aã#@&䃞j#@]K=#@Aǘ#@{P[#@[B>ٜ#@ q#@/d#@Y#@z6#@(~k#@^K="@?.#@*:#@= ףpm#@)\x#@ #@mV}r#@6#@B>٬#@ׁ#@L F%#@-v#@V_#@|Pk#@X#@X5;#@|a2U#@Mbp#@z):;$@( #@@߾#@V/#@ͪυ#@;M /$@E4$@ΪV#@B`"#@B`"#@ rh#@_L5$@pΈ#@$#@6;NA$@Ԛ$@@a $@ r#@d]F$@:#@H.!#@(#@#@3#@LJ#@8gDio$@7#@Zd;#@( .$@|?5^#@( #@!uq+$@eXG$@^)#@Ǻ$@o_g$@fa6$@ޓZ$@1w-!_$@y) $@uq 0$@{/L$@6#@m4w$@r/$@W2t$@}b#@Zd$@;O$@ rh$@`" $@&1#@%#@2w-!#@ŏ1#@vOj-$@Q|#@M O#@S#@( #@D$@+>$@H.#@C$@lV}$@iq>$@r/$@#@S#@Q#@}?5^I$@{#@Ș#@b=#@H.#@LJ#@LJ#@~:#@lV}#@$@ʡ5$@(#@ ףp=#@l g$@.!#@Oe#@*Թ#@#@3#@J +#@`vO#@Ciq*$@&S:$@ h"#@B`"#@ʡ5$@$$@*Թ#@fa6$@:#@Pkw#@'†W#@33333#$@$@ q#@H}#@6[#@_#@a2U0*#@6[#@xz,C#@?#@u$@ ףp=#@48#@Oe#$@HPs#@ڊu#@ h"#@Aǘ{#@(\#@Y8m#@St$#@jq#@@߾#@1*$@x##@7#@x##@M O#@ h"l#@ cz#@†Wʢ#@jM#@Y8Ž#@6٬#@C$@:#J{#@HP#@C6#@,C#@U0*p#@l#@-v#@?W[#@ׁ#@-!l#@kw#@+ #@†Wʢ#@"lxz\#@ F%u#@6٬#@Ș#@"lxz\#@>٬\#@t$~#@xz,C#@ h"l#@AfU#@ͪ#@HP#@;pΈҞ#@I +g#@D#@v#@z#@k#@fa&#@8EGr#@h"lxz#@x##@ec]<#@jMc#@6#@c]K(#@/nU#@ڊe#@W[#@#@Bin#@=,Ԛ}#@@G#@X5;~#@UX#@ı.nA#@Q#@)\x#@o#@:pΈ#@?l#@I.!v#@c=y#@鷯|#@ǘ`#@Mbp#@\ Ac#@|a2U@#@HP\#@jM#@/d#@Oe#@Gz#@o_i#@Ql#@H#@{/L #@St$#@;pΈҞ#@t$#@kw#@|Pk#@( #@#@-#@Aǘ#@_V#@8EGr#@%䃞]#@`vO#@k w#@aTR'#@Bi#@ʡE#@0*Є#@#@9#J#@xi#@ͪ#@#@ڬ\m#@ׁ#@0*#@[$@ܵ|#@ q#@%䃞 #@D#@d`T#@(\#@Έ#@Mb#@^K=;$@N@a#@lxz,#@_L,$@k#@Ǻ$@ rh$@&䃞ͺ#@ y#@ڬ\m#@.1#@\C#@ #@Q.$@|г#@xz,C#@ʡ#@2w-!D$@B#@S:!$@Ǻ$@%䃞m$@&1#@37X$@(\#@58EG$@Ac]#@fj#@1*$@镲 $@Q.$@EJ#@H#@X$@Qkw$@W2$$@T4$@|?5^#@1*$@Ԛ$@m4p#@hO$@T$@9$@{/L$@9$@6٬#@a+#@JY#@|гY#@Ciq*$@St$#@ $@d`#@,C$@t#@a$$@ c#@ͪ#@$@z6#@fa6$@Dl$@]C#@+ #@ F%u#@ #@z#@ioD$@a2U0*#@ c.$@St$_#@u#@镲#@' V#@OeH$@Q#@X5;#@l#@Pk#@NbX9#@w/#@]Fx#@D#@h"lxz#@C#@Ǻ#@Gz#@^)#@'†WZ#@Gz#@Ș$@j+#@`TR'#@Pk#@eaq#@`TR'#@t$~#@~Z#@46#@:#J{#@]Fx#@]C{#@>٬#@U0*#@?ܵ#@H.#@2ı.#@-#@H}#@F_#@$(~#@ y#@n#@d]F#@|Pk#@<<$@jM^#@Fx #@N@a#@=yXu#@٬Z#@K4#@^)#@fffff#@{G#@1Zt#@ׁ#@5^I r#@K=#@ #@d`T#@"lxz#@S:!$@|a2e#@BY#@FԸ#@ $@Q|#@jq#@Pkw#@e!$@JY8$@Ș#@x&1$@w/#@&†#@+ X#@]C#@io#@8d#@-!l#@:pΈ#@yX5ͻ#@fc]ܶ#@ r#@:M#@ڊe#@0*Є#@X#@Mb#@#@RI&B$@M O#@6;NA$@( #@n#@K7#@EGrI$@^I #@ec#@#@jt#@N@a#@C#@~jt#@8d#@Ԛ#@"u<$@QE$@3#@_L5$@QI]#@8EGr#@ h$@7#@w#)$@46#@2w-!#@}гY#@]Fx#@}гY#@z6>W#@ h"#@:pΈ"$@A`B$@) 0 $@5^I #@ o_#@|гY#@ZB>#@ׁ#@H}#@t$#@vOj-$@ڊe#@}b#@d]K#@ $(~#@ #@ #@#@fj#@ۊe#@\C#@J4#@*D8$@D$@x&1#@Bf:$@oʡ#@a#@$(~#@+#@A#@ё\Cz#@n@$@d`T#@0' $@ʡE#@UX#@F_#@"lxz\#@y)#@UN$@V#@B`"#@QE$@ho#@M O#@C#@OeH$@H}8$@|?5>$@~k #@Nё\3$@ʡ5$@/$%$@n2$@}гY#@R!$@Q#@9#J#@#@cZ2$@KY8%$@8m#@8m#@e`TR#@\C#@\ Ac#@Q|#@۷#@H.#@6$@Q|#@9#j#@M O#@:H_#@ y#@*:#@[ Aa#@ec#@EJ#@'#@Oe#$@ˡE]#@ʡE#@3#@T#@#@ec#@ -x#@_vO#@xz,C#@0' $@NbX9#@$@]C#@Fx #@H.! $@-7$@48E#@{#@&S#@8d#@N@$@t$#@n4@#@{#@Gzn#@#@$@ZӼ#@1#@䃞ͪ#@ y)$@ׁ#@_L,$@9#J{C$@#@F_#@6W#@`vO#@Q.$@F_#@r#@8gDio#@aTR'y#@= ףpm#@T4$@ #@s[#@|г#@ۊe#@F%u8$@Έ#@V-#@I.!#@N@a#@ y#@NbX9#@_L#@:#J{?$@a4#@Bin#@0*#@{#@ڊe#@n#@X#@\mž#@=,Ԛ}#@c]K(#@NbX9#@:M#@ΪV#@9#J#@xz,C|#@8EGr#@a4#@}8g#@_L#@1#@Aǘ#@'†WZ#@#@9#J#@:M#@-#@ׁ#@鷯s#@(\#@ڊe#@n#@N@#@2%c#@^)ˠ#@,C#@^)#@a4/#@~: $@6[#@u$@ё\Cz#@Jt#@K7#@K7#@/$%$@^I #@ꕲ ql#@&†#@ׁ#@#@*:h#@Zd;#@U0*#@<,#@/$#@v#@B`"k#@d;O$@$#@ y#@xi#@^)#@#@FԸ#@d]Kȇ#@Ra#@ 0z#@ q#@:#J{#@48#@(#@\mž#@Y#@V?$@ $(~#@ $(~#@,Ԛ#@ c#@ #@#@O@aã#@ʡE#@oʡ#@4@#@+ݓ#@Q|ar#@^)#@ q#@#d#@rh#@ h"l#@jt#@F%u(#@~k #@ˡE #@T#@8m#@AfU#@Bin#@~:#@ݵ|Ѓ#@H.#@= ףpm#@(\#@ŏ1w-#@+#@z#@8m#@LJ#@u#@ F%u#@ʡE#@?ܵ#@m4g#@|гY#@&Ss#@o_W#@M#@{P[#@V#@l#@Jt#@@#@.1f#@+#@d`T#@l#@($@,Ԛ#@鷯|#@lV}#@2%#@}b#@8m#@Y#@l#@(#@3"$@46<}#@)\x#@]C#@†W#@ʡE#@RI&B$@]Fx#@y)#@ o_#@*Թ#@Bi#@9v#@JY#@aTR'#@]Fxk#@l#@H.#@,C#@Pkw#@/nU#@Zd;#@:H#@<,Ԛ#@t$#@ F%uZ#@+#@<,Ԛ#@#@`TR'#@46#@K7#@~jt#@v#@a4#@8gDio$@ʡ5$@8EGr#@\( $@~Z#@z6#@ǘ#@X5;#@Q|ar#@?~#@l#@v#@.1f#@(\#@ q#@z6#@pΈ#@}?5^I$@ܵ|#@S㥛#@镲#@{#@ڊe#@H#@d`#@v#@xi#@|гY#@^I #@J +#@[ A#@ʡ5$@9vo#@6W#@̼#@=yXu#@W/'#@=,Ԛ}#@}?5^I$@鷯|#@kw#@#@\C#@{#@N@$@8m#@_vO#@Zd;O#@(#@cZB>#@Y8Ž#@=yXu#@M O#@AfU#@h"lxz#@ݓe#@|Pk#@K7#@3#@:H_#@Fx #@3#@#@1Zt#@U0*#@S[#@:p($@U0*p#@Oe#@48E#@#@ڬ\m#@z6#@H.#@k#@tF#@m{B$@|a2U#@mV}#@tF#@>yX5=$@Tt$#@ҟ#@ͪυ#@|гY#@Q|ar#@ q#@ cZB#@K7A`#@j+w#@BY#@`vO#@K7#@cZB>#@1#@Aǘ#@:M#@ #@46#@!u#@Ӽ#@_L#@5^I #@ #@tF#@)ǺH$@u$@=yXu#@?ܵ#@(\#@7#@%u#@H.#@ڬ\m#@6#@ZB>#@io#@†Wʢ#@pΈ#@|г#@#@xz,C|#@w/#@ y#@mV}#@S!u#@v#@NbX9#@ F%u#@<,#@Gr#@*:h#@ZB>#@0*Є#@\m#@V/#@R!$@QI#@o#@:#J{#@b#@c]Kx#@Zd;O#@( #@{G#@ܵ|#@2w-!#@pΈހ#@{$@Gzn#@ۊe#@†Wʢ#@oŏ!$@kw#@V-#@d`T#@%䃞]#@ -x#@Oe#@`vO#@Bin#@:M#@|гY#@= ףp#@Ps#@(\#@Gz#@F_#@jM#@s#@"u#@ʡE#@Bi#@Xq#@x&#@ͪ#@= ףpm#@ h"#@Ș#@ݵ|Ѓ#@|гY#@<,Ԛ#@8m#@ZӼ#@I.!#@B$@-#@aTR'y#@!uq+$@ڊe#@tF#@d]Kȇ#@^#@Af#@&Ss#@ 0z#@J4#@L F%#@6$@ݓe#@#@_L,$@5^I r#@:M#@{G#@6٬\#@C#@ q#@:#J{#@iq.#@2%#@ׁ#@"lxz#@|a2U#@Ra#@0*h#@.n#@KY8%$@y)#@Q|#@Pkw#@HP#@^#@ҟ#@lxz,#@D#@:H_#@<,#@B>٬#@l#@9c#@Ș$@Zd;O#@K4#@Fh#@S㥛#@0L F#@+ #@#@̼#@鷯|#@L F%#@/n#@z,C#@l#@?l#@z6#@Nё\3$@j+w#@A#@b=#@Έ#@S#@Ps#@Oe#@ec#@|a2U#@#@B`"#@QI#@lV}#@ё\Cz#@ ^) $@<,#@x##@ #@h"lxz#@x&1#@d;O$@(\#@Oe#@Dl$@w/#@/$#@ۊe#@TR'#@R!#@fj#@(\#@TR'#@*D#@d]Fh$@Gz#@ʡE#@J +#@Pk#@{G#@-!l#@X2ı#@F_#@Mb#@/$#@rh#@_L#@F%u8$@d`$@+>$@:p($@X5;#@X#@=yX$@T4$@:pΈ#@a+eI$@~:p#@"u#@5^I #@J{/L6$@( #@fj#@ʡE$@;O$@6#@ y#@7A` $@:M#@TR'#@镲#@^I #@:p($@!lV#@H.#@]C#@{#@a+#@"$@)ǺH$@jt#@FԸ#@{0$@a2U0*#@9#J$@H.#@ڊe#@̼#@V#@fj#@l#@NbX9#@`vO#@jq#@jM^#@J +#@0' $@3ı.n#@ q#@_V#@Zd;#@|г#@:pΈ#@B`"#@B`"#@"uqm#@~:#@~k #@jt#@ec#@b=#@Q.$@/$#@B$@H.!#@X2ı#@6٬\#@ףp= W#@y)#@d`#@O@aã#@' V#@uq 0$@D#@~:p#@fj#@ F%u#@#d#@ǘ#@~k #@n#@Bf:$@St$#@#@#@&䃞ͺ#@3#@a4#@Fh#@Ac]#@Ӽ#@7¤#@ ףp=:$@X5;~#@ #@.n#@h"lxz#@ۊe#@D#@b#@T#@9v#@B$@X5;~#@U0*#@ cz#@Q.$@aTR'#@fc]ܶ#@}b#@!u#@&†#@}b#@V/#@rh#@[ Aa#@ͪυ#@X2ı#@Qڛ#@lxz,#@V_#@;M /$@t$#@6+$@}гY#@?~#@#@Bi#@ZӼ#@H.#@†W#@r#@@#@a2U0*#@`TR'#@sh|#@H.!#@"~#@48E#@U0*p#@Ps#@U0*#@|a2U#@ʡ#@6[#@jM#@xz,C#@&†#@/n#@V-#@B>٬#@NbX9#@EJy#@:pΈ"$@x&1#@R#@2w-!#@( #@6#@Afg#@o_W#@bٝ#@ŏ1#@1%#@ #@x#@J +f#@Q5#@ŏ1#@Gzn#@b=#@bٝ#@A&$@J +f#@H#@QI#@T#@0*#@/'#@bٝ#@B`"#@U0*p#@ ףp=#@jq#@0L F#@ 0z#@r/$@xz,C#@p= #@/$#@ cz#@LJ#@(\#@=yXu#@b=#@8gDio#@\ Ac#@U0*#@qh#@v#@R!#@aTR'y#@1*$@##@٬#@^I #@ʡ#@2ı.#@b#@T#@ŏ1#@yX5ͻ#@y)#@3W#@mV}#@n4@#@Q#@z#@K=#@ͪ#@(\b#@+ݓ#@#@8m#@`" $@xz,C|#@-#@\m#@W[#@h"lxz#@'†W#@{#@io#@|a2e#@z6>W#@QI#@QE$@ ףp=:$@ho$$@*Թ#@}b#@]Fx#@K7Ap$@= ףp#@`TR'#@#@鷯s#@lV}#@|г#@s#@:pΈ#@o$@z6#@鷯$@2w-!#@C`#@|гY#@^)ˠ#@Zd;#@6[0$@K7#@ h"l#@<,Ԛ#@Q#@N@#@ $@LJ#@fj#@<,#@V-#@6[#@*:#@^I #@H-$@ׁ#@o$@H}#@H}#@s#@&Ss#@ r#@QI]#@W[$@B`"#@Έ#@@߾#@&S:$@Jt#@V?$@:H_#@a2U0*i#@l#@D#@B>٬#@K7#@OjM#@Ԛ#@n2$@^)ˠ#@5^I #@`vO#@2ı.#@}гY#@鷯s#@OeH$@]C{#@:#J{#@#@Q#@Bi#@'†W#@X#@&S#@*:#@3#@b#@&䃞ͺ#@1Zt#@_vO#@x&#@Ac]#@:M#@s#@Zd;O#@S㥛#@sh|#@̼#@M#@ F%u#@mV}#@#@K7#@ΪV#@*D8$@N@a#@ -x#@^I #@v#@/'#@H.! $@V-#@gsE$@Ș#@t$#@:M#@|Pk#@z6#@"u#@x#@?߾n#@b#@OjM#@x&1$@X5;~#@;Nё|#@N@#@oT#@S!u#@NbX9d#@_vO#@46#@I.!v#@.n#@"u#@*D#@ q#@ZB>#@pΈ#@A`B$@(\#@48E#@Q#@B`"#@Pkw#@|гY#@|a2e#@ y#@R#@_L,$@jt#@fc]ܶ#@U0*p#@.1#@8m#@?e#@^)ˠ#@*:#@Qڛ#@F$@H.#@#@EJy#@3#@d]K#@kw#@x&#@r#@M Ot#@uq 0$@x $(#@d]K#@}гYy#@d`T#@ڊe#@U0*#@#@ZB>#@xz,C|#@*:#@H}#@uU#@)\x#@jM^#@"~ $@n#@ #@D#@]Fx#@xi#@(\#@[ A#@ΪV#@K7#@Fh#@8m#@z6>#@S㥛#@p= #@= ףp#@Q|a#@?$@#@ y#@ y#@ZӼ#@^)#@fj#@\C#@vOj-$@/d#@( #@o#@%#@Mb#@K4#@,C#@`vO#@ #@^)ˠ#@4@#@_vO#@+ݓ#@n4@#@X5;#@ΪV#@6٬\#@ͪ#@7[ #@ё\Cz#@Ǻ#@r#@j+#@Ac]#@pΈހ#@&C$@-!l#@3#@ #@7#@:pΈ#@V/#@z#@\m#@T#@=yX$@/$%$@Ql#@fc]ܶ#@0L F#@ZB>#@B`"#@B`"#@|гY#@ʡE#@2ı.#@ h"lxj#@K7#@:#J{#@]C#@ q#@lxz,#@ho#@LJ#@0' $@:H#@}гY#@;pΈҞ#@(\#@48E#@ΪV#@ׁ#@-#@y)#@^)#@"uqm#@_#@a4#@D#@ڊe#@鷯s#@\C#@|a2U#@=,Ԛ}#@HP\#@St$#@vOj-$@ F%u#@K7#@J +#@iou#@@#@9#J#@H-$@Gz#@lxz,#@%䃞]#@2ı.#@-#@S㥛#@8EGr#@e!$@u#@ #@lV}#@3#@y)#@2w-!#@Ps#@Bi#@:H_#@6;NA$@+ X#@H.#@#@{#@k w#@*:#@vq =$@\ Ac#@#J{/#@R!#@x&1#@NbX9#@_L#@%#@\C#@|г#@ݵ|Ѓ#@(\#@QE$@Q#@}?5^I$@b=#@F$@X5;#@&Ss#@2%#@#@H}#@ͪ#@ۊe#@ 0z#@^)#@xz,C#@58EG$@۷#@jM#@^I #@D$@[ A#@Oe#@2w-!#@$#@ y#@jM#@H.#@e`TR#@T$@Oe#$@]Fx#@&†#@8d#@(\#@mV}#@ #@J$@ʡE#@4@#@_L#@V-#@?W[,$@K7A`#@h"lxz#@'†W#@8EGr#@X5;#@*:#@ʡ5$@+ #@m4p#@kw#@~:#@eXG$@~:p#@|гY#@<,Ԛ#@ F%u#@jt#@M O#@) 0 $@^I #@;Nё|#@F%u8$@M Ot#@@#@:M#@"u#@aTR'#@?e#@a+eI$@C6#@3"$@{$@S#@2%#@qh#@H}#@$@6;NA$@Ǻ#@ׁ#@&†#@&S#@##@io#@jt#@5^I #@St$#@9#J#@.n#@ y#@X5;#@#@Zڊ=$@ʡE#@6[#@†W#@l#@V}b/$@1#@{#@~jt#@3#@St$#@W/'#@N@#@!rh}#@"lxz#@:#J{#@yX5ͻ#@R!$@I +g#@2ı.#@B#@Ӽ#@ y#@QI#@3#@^)#@St$_#@HP#@TR'#@۷#@T#@RI&B$@:M#@&C$@%䃞]#@ʡE#@†W#@ʡE#@xi#@H.#@{G#@ 0z#@*D#@lxz,#@U0*p#@@#@ $(~#@H.!#@ y#@1%#@&Ss#@ y#@ʡ5$@Ps#@v#@Mbp#@3#@:pΈ#@\ Ac#@]C#@ #@_L,$@Pn$@.n#@`TR'#@o#@TR'#@/$#@aTR'#@ǘ`#@Q#@z#@AfU#@S#@jt#@AfU#@ͪf#@n4@#@TR'#@EJy#@ZӼ#@+ݓ#@ͪυ#@H}#@:M#@V#@ʡ#@JY#@' V#@j+#@B>٬#@ׁ#@QI#@'#@ #@ h"#@B>٬#@ #@qb#@Ps#@pΈހ#@>W[#@jM#@ rh#@ h"lxj#@v#@jt#@a$$@Aǘ#@G$@(\#@s#@H^#@4@#@(~k#@F_X#@*:h#@?$@#@H.!#@ꕲ ql#@/n#@I.!#@QI]#@&Su#@oʡ#@V/#@<,Ԛ#@2%c#@_vO#@I.!#@kw#@H.!#@ףp= W#@y)#@{#@Q|ar#@,Ԛ#@2w-!#@oT#@Oe#@V-#@U0*#@J$@ǘ#@St$#@W[1$@ ףp=#@&†#@>٬#@1%#@#@Q|a#@s#@r#@{#@Onb$@Έ#@Nё\3$@Fx #@Q.$@؁sFV$@ͪ#@!rh}#@>٬\#@ q#@I +g#@8m#@!uq+$@A#@jt#@qb#@Oe#@y)#@x##@s#@NbX9#@9v#@ڬ\m#@6[0$@St$_#@:M#@[l$@C#@w/#@Ș#@(#@kw#@Afg#@ y#@[Ӽ-$@-#@9$@!uq+$@Zd;#@'1*$@)Ǻ#@H}#@&S#@&†#@#@ F%u#@b#@<,Ԛ#@1#@Ps#@A&$@ͪ#@ q#@m4p#@lV}#@tF#@Ș#@F_#@^K=+#@Qkw$@ o_#@\C#@##@%#@ΪV#@3#@s#@ q#@X2ı#@JY#@y) $@t$#@Pn$@-#@/d#@S#@:H#@ʡ5$@#@BY#@Oe#@{G#@t$~#@Q|a#@ #@7¤#@ZB>#@ܵ|#@d]K#@HP#@]Fx#@&†#@Pn$@NbX9d#@H}#@|?5^#@j+#@ rh#@xi#@2%#@;M /$@>yX5=$@=U$@`vO#@b=#@#d#@#@ rh#@lV}#@( .$@7#@/'#@s#@ׁ#@!uq+$@aTR'y#@%䃞]#@##@x&1$@N@#@N@a#@(#@镲#@>W[#@ׁ#@8EGr#@:p($@H.!#@v#@*:#@|Pk#@.1#@!rh}#@Pkw#@n@$@r#@_#@' V#@(\#@<, $@-#@|Pk#@/$%$@LJ#@ c#@?e#@}гY#@x#@p_$@Q|a#@46<}#@fc]ܶ#@ c#@F_X#@TR'#@U0*#@lV}#@D#@B>٬#@Q|ar#@rh#@^I #@n#@yX5ͻ#@qh#@O@aã#@iq>$@j+#@QI#@x&#@|г#@1#@bX9#@+ݓ#@ͪf#@&䃞ͺ#@8EGr#@Mb#@#@.1f#@5^I r#@?e#@St$_#@n#@X5;#@=yXu#@#@`TR'#@jt#@-!l#@jt#@%䃞]#@L F%#@&Ss#@H-$@*:h#@^#@^)#@2%#@Tt$#@S#@I&#@gDio#@v#@ y#@bٝ#@-#@h"lxz#@V#@K7#@3#@|гY#@Zd;#@jq#@_#@Ș#@`TR'#@' V#@C`#@D#@B>٬#@&䃞ͺ#@H.#@MJ$@LJ#@H^#@"u#@Bin#@^)#@/'#@ʡE#@K7#@N@a#@|г#@lxz,#@"u#@[B>ٜ#@Ș#@ c#@ c#@3#@<,#@o#@OjM#@ c#@w/#@ c#@ h$@LJ#@jt#@EJy#@ +#@&䃞ͺ#@_L#@t#@#@kw#@oT#@鷯s#@]C#@~8gD9$@Gz#@ڊu#@䃞ͪ#@aTR'y#@Tt$#@ΪV#@= ףpm#@St$#@&䃞ͺ#@{G#@St$_#@#@鷯|#@٬\#@ o_#@ܵ|#@H.! $@*D#@o#@鷯$@ݵ|Ѓ#@Tt$#@^#@X5;#@ݓe#@W/'#@Q|#@ΪV#@EJ#@X2ı#@†W#@۷#@@#@H.#@ g#@V-#@l#@b=#@:H_#@x&#@Pk#@V/#@( #@8gDio#@3ı.n#@?l#@D#@B`"#@EJ#@mV}#@n#@6[0$@D#@( #@*Թ#@Psׂ#@M#@:M#@n#@8gDio#@-#@I.!#@c]Kx#@z,C+$@鷯s#@ ףp=#@|гY#@3#@S#@X5;~#@_L#@0' $@Y#@|Pk#@`TR'#@,eX$@<,#@b#@Oe#@|гY#@3#@2%#@ F%u#@h"lxz#@46<}#@@#@Y8m#@jq#@h"lxz#@{#@ǘ#@Zd;O#@[ Aa#@sF6$@S㥛#@|a2U#@s$@Cl;$@Q|a#@ClG$@#@T#@Pn$@|гY#@M Ot#@kw#@3ı.n#@S㥛#@X9Ȇ#@(#@2%c#@Oe#$@V/#@ F%u#@B#@+#@ͪf#@Afg#@qh#@3W#@#@s#@鷯s#@&䃞ͺ#@jt#@ho#@9v#@t#@/n#@'†W#@v#@Q#@2w-!#@B`"k#@tF#@<,Ԛ#@Q|a#@fc]ܶ#@#J{/#@ c#@ܵ|#@Mb#@ F%u#@oŏq$@۷#@St$#@ r#@(\b#@"~#@V_#@ rh#@/$%$@H#@io#@( #@y)#@|гY#@ClG$@.!#@Q#@V#@A#@"lxz#@ q#@S!u#@Mb#@_Q$@Ǻ#@q -@$@Dl$@K7A`#@Ǻ#@6#@2ı.#@jt#@2ı.#@Oe#@a+%$@{0$@6W#@8EGr#@Zd;#@p_$@:M#@ˡE]#@ׁ#@&S#@v#@#@v#@lV}#@Q#@8EGr#@:M#@Q#@aTR'#@[ A#@ۊe#@Qkw$@(#@6;NA$@|?5>$@"lxz#@u#@~:p#@ŏ1w $@s$@ۊe#@o$@+ #@t$@Pkw#@_vO#@U0*#@I&#@A#@~:p#@8m#@?#@J{/L6$@<,#@^)#@ڬ\m#@[ A#@p_$@( #@J +#@T#@۷#@A#@̼#@H}#@#@Q#@t$#@2ı.#@ #@~k #@+#@H^#@;Nё|#@s[#@gj+&$@&†#@H#@H#@:pΈ#@D#@`vO#@:H_#@`" $@Q|ar#@2ı.#@H.#@a2U0*#@ F%u#@\ Ac#@n#@JY$@Fx $@|г#@#@:pΈ#@48#@ #@r#@\C#@|?5^#@:pΈ#@EGrI$@\mž#@Oe#@48#@:H#@D$@ڬ\m#@ ^) $@fa6$@F_#@"lxz#@&†#@ŏ1#@1#@Fh#@r/$@a2U0*#@ F%u#@:M#@_L,$@a2U0*i#@sF6$@V-#@̼#@Ș#@z6>W#@d`T#@v#@%C{#@Ǻ#@:M#@~:#@#@N@#@HP#@ q#@|гY#@镲#@n#@"lxz#@S#@ͪ#@iou#@ #@#@Q|A$@9vo#@M O#@`vO#@ r#@v#@X5;#@7#@H.#@sh|#@v#@ZB>#@V-#@&䃞j#@w/#@<,#@QE$@S3$@B`"#@ #@;M /$@R!#@:p($@]Fx#@7A` $@ʡE#@~:#@>W[#@ Q$@x##@H^#@47#@K7#@ΪV#@B>٬Z#@^#@#@d`#@ۊe#@oT#@#@c]K$@Dl$@{#@a+#@%C{#@EJ#@l#@Ciq*$@uq 0$@Ǻ$@X2ı#@h"lxz#@J4#@|г#@ׁ#@w/#@*:h#@fj#@u#@fj#@ho#@n4@#@Zd#@/$#@ q#@MStD$@]C#@S$@,C#@'†W#@Q#@:#@N@#@Q|a#@ܵ|#@ y)$@ݓe#@6[#@S#@kw#@&S#@J$@ǘ#@ڬ\m#@1%#@$#@*:h#@V?$@+#@ rh#@-v#@Q#@n#@T#@33333#$@1%#@}b#@ y#@'†WZ#@oT#@LJ#@x##@,Ԛ#@Fh#@#@*:#@:pΈ#@lV}#@Fx #@X9Ȇ#@2U0*3$@X#@o#@Ǻ#@ rh#@zG$@K7A`#@V-#@Y8m#@X9v$@ׁ#@:#J{#@ΪV#@2%#@ڊe#@Zd;#@ΪV#@a#@N@#@EJ#@tF#@\mž#@JY#@:p($@-!l#@|?5>$@z,C+$@.n#@ q#@H.! $@.n#@lxz,#@#@۷#@qh#@R!#@ o_#@p= #@@#@?ܵ$@}b#@4@#@ y#@ h"#@&䃞ͺ#@<,#@|г#@ y'$@_#@ʡE$@ cz#@JY$@ -x#@H.#@#@q -@$@:#J{#@ q#@)Ǻ#@ho$$@FԸ#@_Q$@ q#@jt#@MStD$@Pk#@Q#@B`"#@&†#@y)#@EJ#@Dl$@|г#@s$@&C$@m{B$@ʡ5$@fa6$@eaq#@:#@x&#@u$@_vO#@ #@Fx #@3#@jt#@%u#@Έ#@s$@x&1$@z#@ y#@9v#@3#@n4@#@vq =$@ŏ1#@#@-!l#@EGr#@:M#@0*Є#@ h$@^)#@tF#@,C#@1#@1#@镲#@H.!#@H}8$@C#@T#@5^I #@Ԛ#@$$@#@X9Ȗ$@.!5$@p= #@\m2$@9$@ Q$@HP$@io#@S:!$@a+%$@d;O$@T4$@x&1$@.!#@0L F#@a+%$@JY#@J$@&†#@( .$@2w-!D$@|г#@!uq+$@D$@e`TR#@g$@Zڊ=$@ #@z#@H}#@Pk#@EJ#@xz,C#@V#@+ #@zG$@.n#@l g$@k+#$@@a $@Pk#@V/#@( .$@_vO#@N@$@46#@t#@Zd;#@Zd;#@33333#$@n4@#@N@$@ʡE#@=U#@Ԛ$@HPs$@|Pk#@ ףp=#@ʡ5$@=U$@^#@"#@V#@$@~:#@zG$@Pkw#@Dؐ$@:H#@6>W[1$@{/L$@ y'$@3W#@QI$@$@p= #@g$@!uq+$@A`B$@ r#@Q#@S$@ c#@7#@t$@^)#@|Pk#@1#@n4@#@-7$@V?$@x&#@Ԛ$@mV}#@}b#@48$@:M#@UN$@ʡE#@q -@$@l#@sF6$@ͪ#@t$@ŏ1#@) 0 $@)ǺH$@_vO#@p= #@6#@$@H}]$@#@<, $@0*h#@w-!$@;M /$@"$@^)#@ʡ#@mV}#@B#@ y)$@|?5^#@\mž#@,C#@]Fx#@D#@LJ#@$@"~#@QI$@S:!$@( #@F_#@ q#@ #@v#@9$@C#@x##@†W#@ͪf#@$$@B>٬#@St$#@F_#@EJ#@k+#$@鷯$@lV}#@K7A`#@JY#@ׁ#@= ףp#@vOj-$@48E#@ZB>#@n#@:pΈ#@ q#@v#@9v#@ClG$@(\#@sAo$@mV}#@r#@JY$@Έ#@Dl$@Pk#@[Ӽ-$@ $@N@#@TR'#@ۊe#@{$@ZӼ#@OjM#@6;NA$@d`T#@x##@ y#@|Pk#@%#@#@/$%$@\C#@*D#@@߾#@jt#@( #@_vO#@J4#@H}8$@ ףp=:$@n@$@{#@5^I r#@ c#@}?5^I$@Pkw#@Ǻ$@V#@:#J{?$@T4$@d]F$@J +#@z6>W#@6[#@.n#@JY$@9$@#@I.!#@z,C+$@ rh#@Ǻ#@,Ԛ#@#@Pkw#@lV}#@9EGr#@ZB>#@B$@:#J{#@Cl;$@MStD$@M O#@7#@U$@8m#@ F%u#@J{/L6$@bX9#@_L,$@j+#@~:#@Pkw $@}гYy#@ΪV#@^I #@MJ$@3"$@Pn$@ZӼ#@I&F$@ y#@Q#@-C$@a+#@]Fx#@ c.$@Fx $@qh#@io#@{/L$@,C#@c=y($@8EGr)$@JY$@Ș$@58EG$@6$@oT#@ʡE$@x&#@Ԛ#@ʡ#@JY8$@xz,C#@uq 0$@zG$@!uq{$@r/$@.!5$@d]K#@v#@D#@~:#@.!#@H.?$@lV}#@"$@\m2$@V?$@ClG$@.n#@#@%u#@ec#@{G#@+ #@镲#@\ Ac#@>yX5=$@h"lxz#@ #@d;O$@,eX$@Cp$@B`"#@v$@_)*$@ #@)ǺH$@H.#@`TR'#@/$%$@v#@|гY#@Έ#@bX9#@48$@tF#@Sk$@>٬#@9#J$@Ԛ#@ʡE#@FԸ#@[ Aa#@yX5ͻ#@mV}#@Pk#@w-!$@Mb#@,C#@ё\Cz#@X9v$@t$@}b#@!uq+$@B$@ܵ|#@#d#@{G#@}?5^I$@) 0 $@8EGr)$@ׁ#@v#@qh#@_L#@48E#@@a $@ŏ1#@ g#@Ac]#@ZB>#@6#@#@-#@ h$@HP$@?5^I$@B`"#@48#@46#@鷯|#@ h"l#@s#@Zd;O#@a2U0*#@K$@j+#@ZB>#@I.!#@m4g#@o_W#@'†W#@`vO#@ec#@a+#@m4g#@\C#@Ș#@46#@*D#@$@>yX5=$@48#@Ra#@JY$@ڊe#@`" $@Ac]#@##@u#@aTR'#@#@>٬#@t$~#@a2U0*#@#@vq =$@:pΈ#@w#)$@Hz$@Q|A$@fc]ܶ#@Ǻ#@ڊe#@K7$@`" $@\ Ac#@n4@#@V}b/$@S$@鷯$@:#J{#@\mž#@w-!$@6#@-7$@ q#@ڬ\m#@n4@#@6#@t#@M O#@fj#@Έ#@Ǻ#@QI$@yX5ͻ#@~:p#@H}8$@vq =$@9EGr#@+ #@ Q$@[$@ F%u#@3#@j+$@Ԛ#@ #@ڬ\m#@Mb#@d]K#@x##@:#J{#@!uq+$@Afg#@46#@HP\#@33333#$@o#@[$@2U0*3$@#~j,$@Oe#$@8EGr#@#@\mž#@2w-!D$@8m#@^)#@fj#@N@a#@x&1$@sF6$@_L,$@~:p#@sA$@b#@:M#@ڬ\m#@+ #@~:p#@ΪV#@46<$@a#@*Թ#@eXG$@$$@ r#@;O$@鷯$@gDio#@ #@n#@/$#@N@a#@镲 q#@n#@<,Ԛ#@r#@Hz$@+#@Qkw$@R!$@;M /$@u$@EGrI$@/d#@n#@xz,C#@~8gD9$@V#@2ı.#@##@x&1$@w/#@8EGr)$@.1#@ea$@ZB>#@?#@$#@46#@}гY#@S#@V_#@JY#@mV}#@|гY#@ rh#@M O#@!u#@H}8$@Xq#@' V#@ r#@x##@lV}#@(\#@2%#@ۊe#@u#@|?5>$@ܵ|#@p= #@EGr#@J4#@:M#@ʡE#@ F%u#@.!#@#d#@(\#@UX#@D$@a+#@B`"#@?ܵ$@D$@}b#@Pkw $@:#J{#@2U0*3$@V_#@Gz#@{G#@E$@lV}$@ q#@v#@2%#@k#@_vO#@۷#@"#@x&A$@Ǻ#@oT#@aTR'#@ʡE#@=U#@+ #@48$@Pkw#@_L,$@'†W#@H$@ec#@ڊe#@̼#@9m4#@oŏ!$@Zd;#@H.!#@Ps#@( #@_vO#@R#@Afg#@g$@\m#@)ǺH$@b48$@ё\Cz#@z#@ ףp=#@#@3#@)Ǻ#@_V#@s#@#@aTR'#@lxz,#@Ș#@ͪ#@tF#@) 0 $@ʡ5$@o#@%#@cZ2$@(\b#@?ܵ$@Qkw$@Q#@48E#@QE$@I.!#@Ǻ#@ cZB$@St$#@S:!$@[ A#@OeH$@&S#@I&#@kw#@z,C+$@|?5$@6[#@0*#@9c#@Q#@St$'$@%#@:p($@ޓZ$@QI#@镲#@d`T#@H^#@&†#@Ԛ#@5^I #@Έ#@Oe#$@,C#@,C#@1#@yX5ͻ#@_vO#@F%u8$@{/L$@jq#@_#@^K=;$@NbX9d#@]KM$@x&1#@ q#@̼#@ q#@Ps#@ y#@R'!#@ y#@:M#@ #@%u#@tF#@k+#$@io#@ΪV#@Oe#@2%c#@*Թ#@z6>W#@:#J{?$@*:#@\ Ac#@lxz,#@xz,C#@&Su#@M Ot#@H$@ q#@JY$@pΈ#@?ܵ#@ g#@ܵ|#@Ǻ#@qh#@Gx $($@Qڛ#@v#@ho#@:pΈ#@#@m4p#@Pkw#@p= #@=yX$@_L5$@ZB>#@ r#@"u#@Ӽ#@ #@j+#@#@( #@Ǻ#@>W[#@S:!$@?$@oŏ!$@#@ #@S:!$@io#@\ Ac#@R!$@2ı.#@s#@a+#@E$@`vO#@]C#@#@ۊe#@U0*#@T#@S#@LJ#@)ǺH$@z6>W#@{#@Ǻ#@?$@@#@St$#@2ı.#@fj#@/$#@Zd;#@|Pk#@>٬#@t$#@w#)$@St$_#@"$@ ףp=#@x##@:pΈ#@ ףp=#@xz,C#@( #@#@ͪ#@&S#@:#J{#@۷#@vOj-$@'†W#@:#J{#@[Ӽ-$@ʡ5$@8EGr)$@z6>W#@#@'†W#@h"lxz#@#@&䃞ͺ#@d`T#@A`B$@Pkw#@B>٬#@?~#@Ǻ#@lxz,#@(~k#@##@ΪV#@-#@z#@&S#@:H#@+ #@fc]ܶ#@7#@l#@2%#@J{/L6$@a2U0*#@fj#@3"$@ ףp=:$@MJ$@qb#@( .$@+#@x $(#@ʡE#@Oe#$@^)#@ h"#@ y#@ y#@b48$@QI#@Mb#@H}8$@eaq#@Zd;#@ec#@#@Q#@*D#@Έ#@= ףp#@Ql#@j+#@z6>W#@H$@J$@Hz$@pΈ#@ڬ\m#@b#@ZӼ#@{G#@_#@R'1$@jt#@m{B$@= ףp#@a2U0*#@d]K#@#@a#@t#@l g$@^#@ʡE#@ŏ1w-$@ڊe#@{G#@ioD$@j+$@+'$@(\#@=yXu#@T#@ F%u#@%#@0' $@cZ2$@ cZB$@<,Ԛ#@($@S[#@N@$@b=#@(\#@=yXu#@Q|a#@S:!$@V/#@ #@ #@ #@Qkw$@E$@/$%$@r#@H.! $@JY#@A#@A#@+ #@46#@6;N#@ܵ|#@m4p#@v#@Q.$@9#J#@ y)$@( #@= ףpm#@.n#@zG$@:#J{#@"lxz#@tF#@`vO#@V#@33333#$@lV}#@QI#@B#@2ı.#@Qڛ#@(\#@J +#@.1#@jt#@=yX$@ܵ|#@>٬#@mV}#@= ףp#@V?$@ q#@yX5ͻ#@oT#@ףp= W#@H}#@٬\=#@fj#@v#@8m#@#@u$@fj#@uq 0$@%#@W2$$@{$@̼#@ #@bX9#@ $(~#@z#@N@#@I.!#@镲 q#@<, $@ZB>#@k w#@^#@.n#@_L#@#@JY#@jq#@&†#@r#@{#@Ǻ#@_V#@t$@:M#@ׁ#@ͪυ#@H.#@&†#@T#@HP#@#@\m$@-#@b#@X2ı#@H.#@##@Tt$#@Psׂ#@B>٬#@3ı.n#@:H_#@ q#@ F%u#@H.#@٬\#@B`"k#@)\x#@:H#@Ǻ#@s[#@"lxz\#@jM#@#@`TR'#@>W[#@Gx $($@V-#@2ı.#@#@T#@N@a#@3#@X5;#@]Fx#@B`"#@$#@}b#@46<}#@##@1#@^)#@6[#@jM^#@HPs#@ y#@47#@:M#@HPs#@ g#@Xq#@LJ#@B>٬#@Fx #@R#@3"$@H.!#@a+#@@a $@oT#@*:h#@R!$@Nё\3$@#@|Pk#@ #@/$#@:#J{#@"lxz#@O@aã#@n4@#@۷#@mV}#@ q#@k#@pΈ#@`" $@V#@R!#@.1#@镲 $@qh#@†W#@d`$@a#@e`TRw#@Ԛ#@(#@ Ac $@/L V#@\( $@$$@%u#@x&A$@Fx #@ݓJ#@ZB>#@/$#@:pΈ#@[ A#@]C#@R'1$@(\#@*Թ#@_L,$@aTR'#@w#)$@ g#@]C{#@E4$@1*$@?ܵ#@t$#@W2$$@jt#@+#@8gDio`$@&Su#@St$'$@{G#@u#@ܵ|#@:H#@ Ac $@]C#@ q#@&S#@ŏ1w-#@ec#@2%#@) 0 $@+#@Ǻ$@"~#@ޓZs#@mV}r#@EGrI$@@߾#@\mž#@ڊe#@&$@mV}r#@=U#@"lxz#@Oe#@ʡE#@\mž#@!uq+$@+ #@#@6٬#@ q#@eaq#@ڊe#@#@io#@B`"#@46#@ q#@(~k#@-!l#@QI#@2w-!#@3#@:pΈ#@W[$@~k #@Zd#@Bi#@>٬#@S3$@jMS4$@+ #@w#)$@:M#@ q#@'†W#@I&#@"lxz#@k#@*Թ#@F_#@TR'#@jq#@ r#@\C#@EGrI$@QI$@MbXY#@;M /$@Ǻ#@:#J{#@yX5ͻ#@ #@_#@Aǘ#@ޓZs#@9#J#@Mb#@h"lxz#@ ףp=#@x&1$@ǘ#@ho$$@1#@ h"#@jt#@w/#@E$@Psׂ#@I +g#@%#@:H_#@ y#@%#@Qkw$@̼#@eXG$@Zڊ=$@t$#@H}#@~jt#@]C{#@H#@Q#@/$#@"~#@ q$@*D#@z6#@*:h#@&1#@Y8m#@qh#@'†W#@j+#@q -@$@h"lxz#@ׁs6#@|гY#@@߾#@d`T#@<<$@ܵ|#@z6#@St$'$@_L#@K7#@=,Ԛ}#@0' $@ y)$@d`T#@"u#@z6#@LJ#@= ףpm#@9v#@|г#@_#@q -@$@ #@R#@N@#@2ı.#@Gzn#@eXG$@K7#@#@EJ#@6$@ܵ|#@]Fx#@s$@a2U0*#@"~#@>٬#@L F%#@ŏ1#@xi#@鷯$@X9Ȇ#@鷯|#@#J{/#@v#@#@|a2U#@B#@ F%u#@cZB>#@g$@{G#@ y#@\mž#@mV}#@$(~#@$~ $@= ףpm#@Ș#@{$@YJ#@-!l#@ܵ|#@lV}#@ۊe#@1#@I&#@Aǘ#@B`"#@ +#@( #@W[1$@v#@|гY#@w#)$@}b#@?5^I$@z6#@8EGr#@N@#@,C#@Zd;O#@w/#@e`TR#@7dJ$@h"lxz#@mV}#@d]K#@<,Ԛ#@9$@'†W#@oŏ!$@aTR'#@R#@Nё\3$@j+w#@ۊe#@HP#@#@w/#@ q$@d;O$@7A` $@qb#@iq>$@.n#@FԸ#@:H#@b=#@d`T#@B>٬#@ #@~:p#@V#@fa6$@"lxz#@x $(#@A#@R!#@[Ӽ-$@z#@QE$@)ǺH$@Q.$@#@48#@&䃞ͺ#@w/#@镲#@ڊe#@u#@St$#@ q#@X$@(#@2ı.#@48E#@48$@8m#@T#@ h"#@d`#@gj+&$@ۊe#@,C$@ʡE$@ǘ`#@ͪ#@6ٜ#@:M#@H#@Gzn#@鷯s#@ ףp=#@h"lxz#@F$@]C#@/nU#@St$_#@]C#@j+#@9v#@:pΈ#@3"$@[$@|?5^#@v#@bX9#@^)#@*D#@Ԛ#@>٬#@HP#@.1f#@ho$$@:#@##@T#@s#@3#@_#@ۊe#@&S#@C<$@m4p#@ܵ|#@y):b#@S[#@Ԛ#@-C$@#@ #@`TR'#@$$@2%c#@xz,C#@]Fxk#@o#@=U#@y)#@MbXY#@Q#@0*Є#@U0*p#@:pΈ#@\C#@鷯s#@S#@46#@6#@58EG$@R!$@"$@pΈ#@&†#@F_#@N@#@( #@_L#@^#@#@Bi#@}?5^I$@ZӼ#@[ Aa#@"u<$@#@NbX9#@u#@) 0 $@*:h#@Y8Ž#@M#@5^I #@jM#@J$@oʡ#@ё\Cz#@|гY#@I&F$@(#@?߾n#@Aǘ{#@"~#@#@6;N#@$#@2w-!#@a2U0*i#@/$#@|г#@x&A$@镲#@9$@L7A`$@X5;#@bٝ#@\C#@?e#@a+#@&S#@"~ $@:pΈ#@Oe#@W/'#@&†#@N@a#@ ףp=#@D#@xi#@&S:$@#@I&#@_L#@9vo#@ rh#@ F%u#@Oe#@33333#$@_#@EJ#@$$@aTR'#@-!lF$@V#@x&1$@St$_#@u#@.!#@Q|#@ʡ#@K7#@j+#@.!#@ rh$@B`"#@a4#@Y8Ž#@ F%uZ#@Oe#@ۊe#@.n#@kw#@/$%$@2U0*3$@^#@S㥛#@s#@T#@ r#@s#@V#@lxz,#@e`TR#@3ı.n#@Zd;#@]C#@|a2e#@ŏ1w $@n#@+ #@]Fx#@)\x#@ۊe#@ F%u#@ y#@ #@&†#@7¤#@lxz,#@_L#@#@.1#@sh|#@jM#@|?5^#@ y#@_#@H^#@mV}#@H.! $@H.#@ΪV#@kw#@v#@6#@:M#@2ı.#@6+$@ec#@gj+&$@hs$@kw#@\m2$@\m#@X5;#@I&F$@K$@X5;#@.!#@z6>W#@1#@鷯$@`vO#@48E#@gj+&$@ q#@&1#@Ps#@k P$@Fx #@pΈ#@Q#@+#@~8gD9$@aTR'y#@ F%u#@H.#@z6>W#@@a $@= ףp#@Q[$@!uq{$@@a $@ #@Ciq*$@镲 q#@lxz,#@\mž#@:M#@tF#@I.!#@2w-!#@ F%u#@pΈހ#@V#@Gr#@n4@#@sA$@lV}#@= ףp#@9v#@qb#@0*#@z#@>W[#@"u#@ F%u#@{$@u$@M#@ F%u#@u#@lxz,#@6#@EGrI$@{#@H.#@^)#@6W#@d]F$@BY#@$@+ X#@x##@ׁs$@s$@J +#@u#@ 0z#@:#@#d#@~:p#@H.?$@l#@D#@#@O@aã#@Mbp#@V?$@&Su#@t$#@X#@U0*p#@= ףp#@ho#@g$@ۊe#@9c#@H#@ΪV#@$#@OeH$@pΈހ#@\m#@+ #@Oe#@B`"#@{#@b#@ - $@fc]ܶ#@$@&S#@I +g#@2ı.#@t#@0' $@T#@.1#@bX9#@A#@'†WZ#@ y)$@H.#@9c#@N@#@io#@w-!$@:H#@:H#@]Fxk#@\m$@ q#@K7A`#@3W#@ F%u#@HP#@~:p#@Aǘ#@tF#@\C#@d`T#@{G#@Pn$@|гY#@>٬#@oT#@FԸ#@HP\#@~jt#@>٬#@V#@`TR'#@cZB>#@a+%$@%#@<,Ԛ#@~jt#@U0*#@U0*#@J +#@?|$@lxz,#@!uq+$@'†W#@S:q$@1Zt#@Ԛ$@aTR'#@`vO#@Q|a#@b#@X#@.n#@OjM#@_Q$@ho#@w-!$@J$@U0*#@#@48#@y):b#@h"lxz#@|Pk#@ڊu#@1#@.n#@0L F#@*Թ#@t$#@zG$@o#@`vO#@ rh#@2ı.#@Q|a#@+>$@aTR'#@}b#@Q#@|гY#@ c#@5^I #@l#@F$@48E#@JY8$@#@$@9#j#@B#@D$@0' $@0*Є#@s$@鷯s#@eaq#@B`"k#@b=#@?~#@z6>#@:M#@D@$@x#@qh#@( #@B#@St$#@6;N#@,Ԛ#@= ףp#@gDio#@\C#@(\#@ڊe#@ꕲ ql#@QI#@ y#@J +#@鷯s#@:#J{#@z6>W#@:#@>W[#@3W#@\m#@1%#@N@#@oʡ#@a#@M#@'†WZ#@Pkw#@&Su#@F_#@V-#@M Ot#@R'1$@}гY#@>W[#@镲#@V-#@fj#@x&1#@ h$@ho#@ #@C#@B#@8m#@^)#@B>٬#@~: $@<, $@#@I&F$@,Ԛ#@^#@lV}#@Q#@ c#@^)#@9v#@D#@\ Ac#@e`TR#@l#@%#@R!#@( #@d;O$@Pk#@|гY#@Zd;#@\C#@z6>W#@uq 0$@X#@ -x#@Mbp#@j+#@H.#@vOj-$@a+#@ ףp=#@]C{#@W[$@$$@($@j+#@Ql#@#@_L#@jMc#@Oe#@]Fxk#@Ș#@S#@_#@X#@lV}#@HP#@6[#@ rh#@!lV#@C6#@~jt#@ׁ#@_V#@J{/L6$@]Fx#@U0*#@ǘ#@H}#@R!#@qb#@0*#@ͪ#@UX#@b#@-!lF$@V-#@*D#@Ӽ#@|гY#@2w-!D$@o#@tF#@ #@#@\m#@h"lxz#@xF#@ͪυ#@X5;#@33333#$@8m#@' V#@jt#@I.!#@EGr#@S:!$@\C#@ʡE#@Oe#@D#@ #@s#@=U$@9#J#@Fh#@2%#@Q#@t$~#@Gzn#@7#@ŏ1#@X#@_L#@}b#@H}#@B#@}?5^I$@Aǘ#@( #@48#@/$#@ё\Cz#@ cz#@:H_#@*:#@{$@xz,C#@2%#@lxz,#@ F%uZ#@ r#@d`#@xz,C|#@a4#@B>٬#@T4$@Ӽ#@fc]ܶ#@ۊe#@M Ot#@}гY#@S#@Pkw#@$$@jM#@X5;#@~Z#@0*#@x##@~:#@z6>W#@.!5$@<,Ԛ#@&†#@X9v^$@/$#@̼#@ʡ#@ZӼ#@d]K#@JY$@?ܵ#@l#@Aǘ#@~:#@r#@*:h#@ͪ#@lxz,#@lV}#@QI&$@Oe#@\mž#@]Fx#@[ A#@Mb#@ŏ1#@#@Q#@.n#@Aǘ#@a#@:M#@#@B>٬#@`TR'#@6[#@Fx #@a+#@io#@HP\#@b#@ h"#@jM#@Zd;O#@yX5ͻ#@(\#@ڊe#@C#@a4/#@&†#@(\#@JY#@#@gDio#@V#@jt#@H.!#@.!#@n#@LJ#@\C#@^#@Ԛ#@.!5$@8gDi$@ #@N@#@oŏ!$@St$#@e`TR#@6;N#@R!$@:M#@U0*#@6;N#@ʡE#@ r#@7[ #@=U#@?ߎ$@y)#@]C#@۷#@L F%$@+ X#@ rh#@ q#@2w-!#@X5;#@%u#@Ciq*$@a+#@ΪV#@ΪV#@3#@cZ2$@ #@48#@ #@48$@6W#@&S#@Y8Ž#@v#@1Zt#@}b#@B`"#@EGrI$@6W[1$@h"lxz#@oT#@Q#@St$#@#@5^I #@I.!#@p= #@mV}#@Ș$@a2U0*#@1Zt#@aTR'#@=,Ԛ}#@\ Ac#@2ı.#@&䃞ͺ#@ #@.1#@?ܵ#@ -x#@Ps#@A#@gs5#@|г#@Mbp#@H.#@ׁ#@8m#@Y8m#@jMS$#@ y#@>٬\#@#@B`"#@Ǻ#@z6#@X9Ȇ#@*:#@w/#@xz,C|#@:M#@S!u#@ڊu#@n4@#@]C#@H}#@ #@io#@ #@`TR'#@/$#@{#@.n#@?߾n#@H.!#@MbXY#@8d#@%C{#@M O#@C#@B`"#@mV}r#@\mž#@Psׂ#@\mž#@o#@*:#@aTR'y#@M#@8m#@JY8$@n#@&S:$@?߾n#@:M#@.n#@z6>W#@H.#@|гY#@"~#@|гY#@F_X#@ʡ#@-#@t$~#@L F%#@ҟ#@o#@s#@Ӽ#@R!#@7[ #@t#@ o_#@jt#@Q#@7[ #@Q#@u#@ׁ#@ʡ#@ͪ#@b#@Q.$@zG$@-v#@}b#@_vO#@$~ $@fffff#@/'#@}гYy#@ y#@yX5ͻ#@x&#@3ı.n#@Q|#@Y#@.!#@o#@ $@y) $@,Ԛ#@hs$@R'1$@h"lxz#@ y#@g$@M O#@#@۷#@ F%u#@fj#@46#@ZӼ#@fc]ܶ#@ r#@St$'$@ rh$@MbXY#@sF6$@ y#@lxz,#@7#@C#@Q|#@x##@<,Ԛ#@9m4#@6;N#@oT#@5^I r#@k+#$@#@hs$@s$@:M#@{G#@<,Ԛ#@TR'#@H$@:#J{#@N@#@,C#@48E#@٬#@#@Ș#@$@ۊe#@V-#@:#J{?$@'†WZ#@\mž#@iou#@($@ y#@##@w/#@V/#@lxz,#@b#@X#@8m#@jM^#@fj#@#@ŏ1w-#@_vO#@ܵ|#@Ac]#@Q|a#@ho#@Mb#@3#@#@a2U0*#@lxz,#@l#@_L#@"~#@镲#@t$#@D#@A#@ #@ڊe#@Tt$#@Έ#@w/#@]C{#@ 0z#@&†#@0L F#@JY#@ǘ#@)ǺH$@lV}#@s#@bX9#@I +g#@A`2#@.1#@OjM#@9#J#@D#@ΪV#@T#@x##@-#@_L#@q -0#@gsE$@Έ#@oT#@U0*#@#@uq 0$@"lxz\#@_vO#@##@Q#@1Zt#@ c#@p= #@4@#@Fx #@=,Ԛ}#@TR'#@Ӽ#@Tt$#@Ԛ#@z6>W#@Oe#@;pΈҞ#@5^I #@Psׂ#@ F%u#@ o_#@Έ#@Pkw#@48E#@n#@V#@ h"#@kw#@R#@oʡ#@RI&B$@_vO#@hs$@(~k#@( #@2%#@ h$@(~k#@l#@d]Kȇ#@(#@B#@9vo#@Gz#@ʡE#@>W[#@<,Ԛ#@Ș$@:pΈ#@ rh#@d`T#@I&#@}гY#@xz,C#@Έ#@Y8Ž#@B>٬#@F_#@ʡE#@Nё\3$@ #@Y8m#@H.#@M O#@K7#@mV}#@9v#@R!#@Aǘ#@.1#@ y#@u#@kw#@%#@Q#@#@B$@eXG$@_#@+ݓ#@3#@lV}#@jq#@3#@&C$@v#@+>$@?l#@(#@ۊe#@N@a#@48#@"$@(\#@B>٬#@ͪ#@*D#@St$#@c=y($@}b#@Bin#@"u<$@l g$@h"lxz#@$#@D#@x##@St$#@\C#@k w#@"lxz#@ F%u#@QI$@3ı.n#@b#@B`"#@ZӼ#@Oe#@B#@^)#@`TR'#@,Ԛ#@C<$@M O#@ rh#@-7$@"lxz#@#@ʡE#@ۊe#@9#J#@!rh}#@3#@fc]ܶ#@$~ $@9m4#@ݵ|Ѓ#@' V#@-!l#@n2$@`vO#@z6>W#@v#@ۊe#@S$@8gDio#@ q#@\mž#@b#@s#@fffff#@p= #@$$@ q#@\mž#@aTR'#@48#@47#@k+#$@ q#@QI#@-#@x##@jM#@ʡ#@KY8%$@l#@ +#@.1#@Ǻ#@:#@\m#@ׁ#@8gDio$@J +#@M O#@St$'$@{P[#@ҟ#@_vO#@lxz,#@ΪV#@y)#@"uqm#@O@aã#@ rh#@B#@MbXY#@+ #@ʡE#@{#@V}b/$@mV}r#@\m#@n4@#@48E#@[ Aa#@`vO#@+ #@K4#@C$@H#@2U0*3$@)Ǻ#@HP#@/'#@ׁ#@]C#@Mbp#@' V#@z6>W#@Zڊ=$@h"lxz#@HP\#@eaq#@Ps#@$@Y8m#@&䃞ͺ#@ͪυ#@J{/L6$@7¤#@qh#@3#@t#@x##@Oe#@#@x $(#@= ףpm#@Fx #@)\x#@ 2$@Q|ar#@Hz$@z6>W#@Bi#@6[#@|Pk#@Ǻ#@ ףp=#@8d#@^)#@xz,C#@@#@NbX9d#@.!#@:H_#@RI&B$@bX9#@/'#@&†#@_vO#@1#@Y8Ž#@sh|#@JY8$@Ra#@#@{#@]C#@x&1#@ rh#@a#@C#@_#@}гY#@̼#@O@aã#@ rh#@jt#@u$@xz,C#@K4#@X#@N@#@3#@]Fx#@2%#@ rh#@Ș#@6;N#@aTR'y#@Q|A$@Qkw$@Ԛ#@#@&†#@MJ$@ͪ#@B>٬#@\C#@H.#@48#@ q#@&†#@p= #@_)*$@@߾#@St$#@gDio#@lV}#@ʡE#@d`T#@Af#@HP#@B`"#@#@ZB>#@ꕲ ql#@>W[#@{G#@y)#@[B>ٜ#@kw#@]C{#@= ףpm#@ڬ\m#@B#@-v#@w/#@*:#@JY#@E$@<,Ԛ#@3#@Ps#@Qڛ#@H.!#@ё\Cz#@St$#@Bi#@W/'#@:#J{#@ΪV#@a2U0*#@zG$@AfU#@ۊe#@V/#@-v#@_vO#@U0*p#@*:#@"$@T#@j+#@[ A#@~k #@{0$@#@I&#@U0*#@u#@x##@p= #@j+#@.1#@†W#@U0*#@Y#@;Nё|#@ h"#@ꕲ ql#@/$#@H-$@|г#@J +#@io#@۷#@n4@#@!u#@̼#@Ps#@&S#@\mž#@_L#@lV}#@ꕲ ql#@&†#@BY#@jq#@۷#@^)#@.n#@>W[#@z6#@A#@g$@ŏ1#@c]Kx#@#@qh#@`vO#@S:!$@{#@+#@S$@A`B$@Pkw#@6;N#@_V#@St$#@K4#@x&1#@8m#@ F%u#@ #@"lxz#@+ #@E4$@ $(~#@EGr#@\mž#@.!#@qh#@B$@o$@Pn$@Aǘ#@h"lxz#@U0*p#@fj#@qb#@ͪ#@8EGr#@d]K#@_vO#@_vO#@b#@.1#@j+#@d]K#@ʡE#@|гY#@ec#@#~j,$@Ș#@a+#@+ #@yX5ͻ#@w#)$@48$@NbX9#@Q#@b#@&C$@Q#@S:!$@,Ԛ#@B`"#@&S:$@}гY#@}b#@ڊe#@Ș#@^)#@S!u#@M O#@Ӽ#@Ԛ#@mV}#@r/$@H.!#@ r#@Fh#@x&1#@I.!#@2%c#@\mž#@Pk#@~jt#@{#@|a2U#@B$@Zd#@|г#@b#@|?5>$@\m#@vOj-$@(\#@B>٬#@*Թ#@D#@٬\#@ͪ#@UX#@|a2e#@oT#@V#@2%c#@@#@@߾#@ y#@ h"#@H.! $@#@ h"l#@##@N@#@j+#@p= #@Mb#@#@uU#@EGr#@l#@H}#@&†#@y) $@X5;~#@_vO#@.!#@6#@z#@=,Ԛ}#@Zd;O#@io4#@a+#@ho#@V#@6;N#@#@p= #@x $(#@#@ #@6#@ h"#@V}b/$@b#@z6#@l#@{#@.1#@]C#@N@#@0L F#@M O#@3#@3ı.n#@}гY#@j+#@]Fxk#@k w#@#@}гY#@kw#@Ș#@m{B$@oT#@\ Ac#@a#@qh#@ F%u#@V-#@#@3#@ #@`" $@|Pk#@Pn$@:#J{#@{/L$@S$@٬\#@k w#@= ףp#@hs$@2%#@\C#@B`"#@o#@{$@a2U0*#@Έ#@oT#@X2ı#@/$#@s$@ q#@:M#@ y)$@St$'$@_vO#@v$@ʡE#@E4$@{$@' V#@&S#@ #@V-#@a+%$@̼#@2%#@Zd;#@Aǘ#@M O#@#@ׁ#@|г#@ c#@&†#@+#@{#@>W[#@N@#@"~ $@!lV#@2ı.#@r#@Q|a#@7[ #@*D#@X#@io#@-#@ۊe#@j+#@s#@(\#@Ps#@&Su#@ c#@n#@w/#@:H_#@Aǘ{#@~k #@o_W#@Gr#@JY#@(#@B`"#@n@$@( #@ $(~#@ho#@|гY#@UX#@H}8$@{P[#@I.!#@z6#@HP\#@%䃞]#@Ș#@ҟ#@AfU#@ΪV#@/L V#@R!#@|a2U#@K7#@ۊe#@J +#@#@JY$@8EGr)$@R#@6٬#@ioD$@۷#@#@1#@6>W[1$@jt#@jt#@M Ot#@<,#@Έ#@|a2e#@zG$@QI#@.1#@ F%u#@H$@8m#@ho#@ZB>#@Ql#@+ݓ#@&†#@D#@Q|A$@Pkw#@NbX9#@6ٜ#@<,#@Q|#@(\#@HP$@#@"~#@~k #@^I #@m4p#@HP$@Af#@TR'#@:H_#@ͪ#@ y#@?e#@6٬#@]Fx#@8m#@&†#@ F%u#@47#@۷#@1Zt#@I.!#@I&#@UX#@~k #@1#@/$#@[ A#@ڊe#@.!#@R!#@HPs#@ $@^)#@ y)$@1#@|г#@9v#@fc]ܶ#@ $(~#@5^I #@~:p#@:#J{#@D@$@ׁ#@Ӽ#@$@&Su#@a$$@J +f#@ cz#@镲#@$$@`TR'#@_L5$@l#@Ԛ#@Fx #@=U$@mV}#@bX9#@z6#@a#@#@jM#@?~#@2w-!D$@Oe#@Ӽ#@N@#@ y)$@Afg#@d]Kȇ#@{#@Y8Ž#@{#@tF#@Ql#@'1*$@NbX9#@J4#@M O#@Zd;#@<, $@ F%u#@\m#@`vO#@ZӼ#@(\b#@mV}r#@Aǘ#@S#@&S#@HPs#@D#@Ps#@|Pk#@H$@Bi#@$@8EGr#@H.!#@s$@;pΈҞ#@/L V#@/$1$@k+#$@Tt$#@V/#@Y8m#@X9v$@ڊu#@48E#@xz,C#@^#@ŏ1w-#@Aǘ#@#@LJ#@v#@Gzn#@[ A#@z6>W#@X#@C<$@U0*#@ #@HP$@HP#@-#@`vO#@ #@LJ#@vOj-$@3#@Pkw#@k w#@;Nё|#@S#@H}8$@o#@^#@J4#@b#@ʡE#@tF#@8gDio$@z):;$@s$@yX5ͻ#@<<$@?~#@QI#@鷯$@UN$@Ǻ#@ ףp=#@H}#@ h"#@qb#@vq =$@2ı.#@Af#@V}b/$@ׁ#@Ǻ#@#~j,$@io#@( #@,C#@z#@io#@>٬#@UN$@[ A#@7#@~jt#@#@T#@a+eI$@cZB>#@ cz#@QI&$@镲#@Oe#@ #@##@w/#@^#@^)#@lxz,#@B`"#@Ps#@eaq#@Ql#@N@#@TR'#@yX5ͻ#@6>W[1$@p= #@<,Ԛ#@۷#@R!#@*Թ#@†W#@H.#@|г#@J +#@=yX$@HP#@cZB>#@ܵ|#@Q#@$@(#@##@y) $@"~ $@$@QI#@6;N#@_L5$@ y#@|?5>$@<,Ԛ#@Q#@Zd;#@u#@\mž#@io#@+>$@٬#@w#)$@ #@/d#@d`#@o$@ #@C`#@Oe#@48E#@v#@=,Ԛ}#@~jt#@H.#@ͪ#@Q#@%C{#@ʡE$@x##@ Q$@+#@JY8$@+ݓG#@+ #@`" $@=U$@ ףp=#@9vo#@3#@d`#@pΈހ#@(\#@?ܵ#@o#@S#@H}#@H}8$@镲#@o#@}b#@_L#@d]K#@pΈ#@ #@[B>ٜ#@ q#@|Pk#@lV}#@V-#@Fx #@_V#@H.!#@(\#@{#@|a2U#@#@ZӼ#@3#@oʡ#@M#@xi#@:M#@'#@*D#@†Wʢ#@S[#@t#@z6#@Aǘ{#@&†#@`vO#@(~k#@7#@{G#@J4#@"uqm#@ +#@6#@y)#@d]K#@Q#@l#@z6#@#@HP#@ׁ#@#@e`TRw#@6#@/$%$@UX#@d`#@ʡE#@d]Kȇ#@1#@bX9#@T#@?~#@[ AS$@镲#@2w-!#@M#@&1#@##@ǘ#@ rh#@.!#@o#@V-#@L F%#@QI#@Q|a#@m4g#@Zd;O#@eaq#@<,#@) 0 $@Y8m#@x&1#@eaq#@?~#@H.#@z6>W#@+ X#@(\#@Xq#@o#@z#@TR'#@R'1$@z6#@B>٬Z#@ͪυ#@ʡE#@_)*$@#J{/#@H.!#@M#@^#@ͪf#@"u#@#@ F%u#@1%4#@1%#@#@OjM#@j+$@Pk#@ F%u#@H^#@'†WZ#@w/#@h"lxz#@۷#@ h"lxj#@K4#@.1f#@#@V_#@( #@ o_#@AfU#@N@a#@lV}#@Zd;O#@tF#@lxz,#@{#@ݵ|Ѓ#@St$#@48E#@TR'#@)\x#@d`#@<,Ԛ#@( .$@+ #@9#J{3#@jt#@j+w#@m4p#@v#@†Wʢ#@= ףp#@Ș#@xz,C#@pΈ#@K=#@d]Kȇ#@Έ#@ q#@[B>ٜ#@s#@O@aã#@ǘ`#@V#@( #@K7A#@ݵ|Ѓ#@ec#@Ra#@T#@H.#@Oe#@jt#@qh#@#@ #@\C#@Oe#@JY#@z6#@48#@lV}#@!rh}#@L F%#@*D#@6[#@6[#@y)#@=,Ԛ}#@†W#@|a2e#@䃞ͪ#@N@#@#@jMc#@EJ#@bX9#@ףp= W#@ y#@K7#@X5;#@6[#@?߾n#@xz,C#@]C#@%C{#@Ș#@io#@^)#@.!#@Xq#@b=#@ y'$@(\#@z6>W#@Ciq*$@S:!$@鷯s#@HP$@>W[#@M O#@Ș#@yX5ͻ#@z#@v#@x##@v$@^)#@.1#@%#@0L F#@B`"#@0*#@Q.$@(\#@bX9#@`TR'#@rh#@Pkw#@_vO#@?~#@Jt#@3#@48#@lV}$@Q.$@(\#@33333#$@B`"k#@?ܵ#@ZB>#@F_#@z6#@LJ#@^)#@X5;#@ r#@ c#@ 0z#@_#@pΈ#@U0*#@fc]ܶ#@mV}#@~jt#@0*#@:#@Y8Ž#@xz,C#@8m#@|г#@St$#@x##@{#@<,Ԛ#@H}#@jM#@#~j,$@h"lxz#@6#@<,Ԛ#@R'1$@JY#@( #@QI#@:pΈ#@H#@aTR'#@EJ#@5^I r#@~k #@ #@M O#@0*h#@#@n#@V-#@#@X5;~#@>٬\#@t$#@a2U0*i#@X2ı#@h"lxz#@W2$$@9#J{C$@X5;#@A#@V#@'†W#@I&#@|гY#@Fh#@|Pk#@6;N#@{G#@xz,C#@ׁ#@}гY#@$@+ X#@6#@_vO#@( #@n#@L F%#@#@(~k#@U0*p#@$#@k#@Ș$@X9Ȇ#@X#@z6>W#@|гY#@z6>#@#@/nU#@=,Ԛ}#@+ X#@Y8m#@`vO#@;pΈҞ#@F_#@ʡE#@k w#@pΈހ#@Pk7$@5^I #@Oe#@S[#@J4#@S#@6[#@R#@9#j#@ZӼ#@6[#@gDio#@#d#@x&#@-!lF$@n4@#@_#@9m4#@h"lxz#@t$~#@|a2e#@ #@T#@Jt#@L F%#@yX5ͻ#@rh#@K7#@St$#@]C#@jt#@S[#@{#@&1#@n4@#@#@I.!#@ #@\ Ac#@&S#@~k #@=,Ԛ}#@ rh#@ˡE]#@r#@|гY#@۷#@Tt$#@46#@\ Ac#@LJ#@-#@t#@9#J$@qh#@ q#@5^I #@;pΈҞ#@Zd;#@0*#@V-#@H.!#@6;NA$@2w-!#@u#@}гY#@z,C+$@ y#@LJ#@,eX$@-#@HP#@=yXu#@ׁ#@Oe#@fc]ܶ#@2U0*3$@Ș#@[Ӽ-$@Ra#@+ #@(\#@= ףp#@*:h#@#@Fx #@٬#@#@>٬\#@Gzn#@ʡ5$@JY$@;O$@^)#@2ı.#@8m#@6[0$@;Nё|#@ZB>#@$@46#@Pkw#@Bf:$@!uq+$@}гY#@ -x#@B`"#@.n#@v#@$#@|г#@X#@jMc#@_vO#@(\b#@xz,C#@*D#@<<$@9#J{C$@d`#@!rh}#@ʡ#@"u#@8gDio#@qh#@\C#@x##@s#@xz,C|#@B`"#@ cz#@ y#@ #@ݓe#@TR'#@jq#@FԸ#@Ԛ$@EGr#@tF#@R#@H.!#@QI#@(#@#@ y#@Mb#@2%#@ h$@(#@x##@Oe#@ׁ#@ #@Q|a#@Aǘ{#@>yX5=$@l#@^#@#@A#@@a $@`vO#@8gDio#@EJ#@D#@|a2U#@ʡE#@\mž#@B#@w/#@w/#@B`"#@St$#@+>$@<,#@&S#@$$@}b#@D#@jt#@EJ#@( #@s#@Ș#@C`#@St$#@:M#@}гY#@ Ac $@Zd;O#@tF#@fffff#@+ #@D#@2ı.#@y)#@|гY#@3#@5^I #@xi#@J4#@Zd;#@Q|ar#@D#@.!#@K7#@m4p#@+ #@aTR'#@#@.1#@K7#@:M#@̼#@/$#@>٬\#@>W[#@K7#@-#@3"$@ܵ|#@ŏ1#@w/#@S#@\C#@M Ot#@{#@lV}#@_#@,C$@9$@\ Ac#@Q#@X#@:M#@( #@&†#@r#@z#@k w#@$@ё\Cz#@k+#$@"$@fj#@6[#@E4$@ҟ#@0*#@n4@#@_vO#@mV}#@OeH$@t$~#@ZL#@Zd;#@#@~:p#@A&$@Oe#@Zd;O#@s#@+'$@6[#@~:p#@E4$@u#@##@-#@y)#@=,Ԛ}#@ y#@ׁ#@ZӼ#@H}#@ F%u#@x&A$@-C$@d]K#@S㥛#@*:#@lxz,#@##@`TR'#@ܵ|#@ 0z#@~:p#@Q#@) 0 $@ŏ1#@/$1$@B#@ $@{#@ׁs#@鷯s#@-!l#@ΪV#@M#@#@۷#@#J{/#@|a2U#@?߾n#@W/'#@o_W#@ 0z#@3ı.n#@( #@H}#@R#@#@b#@v#@K7#@1#@.1#@`TR'#@JY#@`vO#@ClG$@~:#@+>$@a2U0*i#@Cl;$@ׁ#@S[#@[ Aa#@%#@U0*#@d`T#@Aǘ{#@V-#@"~#@:pΈ#@3#@#@= ףpm#@{/L$@ׁ#@46<$@B>٬#@J4#@U0*p#@b#@Y8Ž#@N@a#@S3$@#@H.#@{G#@:M#@鷯s#@N@#@ׁ#@<, $@a2U0*#@d]F$@?߾n#@_#@ 0z#@|г#@ #@&†#@##@V#@bX9#@&䃞ͺ#@( #@^)#@ܵ|#@6$@ׁ#@d`#@~jt#@_L#@3#@io#@H.#@s$@ F%u#@QI#@Pk#@d;OW$@s#@`" $@h"lxz#@= ףp#@-v#@ #@<,#@bٝ#@N@#@ʡE#@^)#@z6#@t#@B`"#@ F%u#@J +#@46#@2%c#@9$@ec#@6#@1#@NbX9#@Fx #@JY#@Pn$@rh#@ʡE#@9#J#@Ǻ#@R!#@fj#@Q|#@io#@QI#@jM#@~:#@( #@G$@Vo$@kw#@V_#@ZB>#@ #@/$#@io#@h"lxz#@ #@\ Ac#@V_#@ y#@ZB>#@Ș#@Oe#@?W[,$@}b#@a#@ Ac $@̼#@r/$@mV}#@Ș#@ʡE#@x##@ڊe#@6;N#@6+$@Bin#@FԸ#@Bi#@ y'$@e`TRw#@3#@~: $@Zd;O#@Ql#@۷#@io#@{#@ܵ|#@d`#@&†#@/$%$@"lxz#@{P[#@8gDio$@}?5^I$@}гY#@N@#@Oe#@ #@'†W#@n#@;pΈҞ#@T$@V/#@ۊe#@BY#@;O$@{#@xz,C#@_L#@lxz,#@D#@N@a#@N@#@.!#@T#@Pkw#@9m4#@z6>W#@p= #@k w#@Q#@#@"lxz\#@d]K#@ $(~#@I +g#@Xq#@\m#@t$~#@kw#@8d#@+#@mV}#@۷#@n4@#@&†#@\mž#@Pk#@B`"#@Sigima-1.1.1/sigima/data/tests/curve_formats/simple.txt000066400000000000000000000001121514013333200231450ustar00rootroot000000000000001850.0 -0.443 1851.0 -0.288 1852.0 -0.289 1853.0 -0.333 1854.0 -0.304Sigima-1.1.1/sigima/data/tests/curve_formats/spectrum.mca000066400000000000000000000145021514013333200234470ustar00rootroot00000000000000<> TAG - live_data DESCRIPTION - GAIN - 3 THRESHOLD - 0 LIVE_MODE - 0 PRESET_TIME - 0 LIVE_TIME - 30.000000 REAL_TIME - 30.000000 START_TIME - 06/19/2025 16:22:57 SERIAL_NUMBER - 0 <> LABEL - Channel 504 5.89 553 6.49 1480 17.48 1659 19.61 <> 0 0 0 0 0 0 0 0 0 0 6239 3708 487 57 14 4 6 1 1 1 4 2 1 2 3 1 3 4 1 0 3 3 2 1 0 1 1 4 0 0 3 2 1 2 0 1 3 2 3 0 1 4 3 1 0 0 3 2 0 2 6 5 5 4 7 4 7 8 15 14 7 8 5 11 6 5 12 13 4 10 8 7 7 7 5 8 5 6 10 10 6 7 5 10 11 5 9 9 2 6 3 10 8 13 9 13 6 11 17 15 23 14 15 29 24 28 21 40 33 54 51 86 167 351 696 1152 1810 2495 3152 3645 3535 3210 2445 1748 1156 657 390 193 79 54 19 11 9 2 0 0 0 0 0 1 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 1 1 2 4 1 1 2 2 1 2 0 1 0 1 0 1 1 1 1 0 0 0 0 0 0 1 0 1 0 1 1 0 0 0 0 0 1 0 0 0 0 1 0 4 1 4 2 0 4 3 0 1 1 3 0 0 2 1 0 1 1 0 1 0 2 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 1 4 1 3 4 7 4 4 2 3 3 0 2 1 0 0 1 3 0 0 2 1 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 1 0 1 1 0 2 2 1 0 1 0 2 0 0 2 1 1 0 2 0 0 0 1 2 0 0 0 1 1 0 1 1 0 0 1 1 0 0 1 0 0 1 0 1 1 1 1 1 1 1 1 0 1 1 0 0 0 0 0 0 0 0 1 0 1 0 1 1 0 0 1 1 2 1 1 1 0 0 2 2 0 2 1 0 1 2 1 0 0 0 1 1 0 1 0 0 1 0 1 0 1 1 0 2 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 <> <> RESC=?; Reset Configuration CLCK=80; 20MHz/80MHz TPEA=1.200; Peaking Time GAIF=1.0998; Fine Gain GAIN=12.819; Total Gain (Analog * Fine) RESL=60; Detector Reset Lockout TFLA=0.400; Flat Top TPFA=50; Fast Channel Peaking Time PURE=ON; PUR Interval On/Off RTDE=OFF; RTD On/Off MCAS=NORM; MCA Source MCAC=2048; MCA/MCS Channels SOFF=OFF; Set Spectrum Offset AINP=POS; Analog Input Pos/Neg INOF=DEF; Input Offset GAIA=12; Analog Gain Index CUSP=0; Non-Trapezoidal Shaping PDMD=NORM; Peak Detect Mode (Min/Max) THSL=0.500; Slow Threshold TLLD=OFF; LLD Threshold THFA=12.12; Fast Threshold DACO=SHAPED; DAC Output DACF=50; DAC Offset RTDS=0.0; RTD Sensitivity RTDT=0.00; RTD Threshold BLRM=1; BLR Mode BLRD=3; BLR Down Correction BLRU=1; BLR Up Correction AUO1=SCA8; AUX_OUT Selection PRET=30.0; Preset Time PRER=OFF; Preset Real Time PREC=OFF; Preset Counts PRCL=1; Preset Counts Low Threshold PRCH=8191; Preset Counts High Threshold HVSE=-130; HV Set TECS=230; TEC Set PAPZ=OFF; Pole-Zero PAPS=8.5; Preamp 8.5/5 (N/A) SCOE=FA; Scope Trigger Edge SCOT=12; Scope Trigger Position SCOG=1; Digital Scope Gain MCSL=1; MCS Low Threshold MCSH=8191; MCS High Threshold MCST=0.01; MCS Timebase AUO2=ICR; AUX_OUT2 Selection TPMO=OFF; Test Pulser On/Off GPED=RI; G.P. Counter Edge GPIN=AUX1; G.P. Counter Input GPME=ON; G.P. Counter Uses MCA_EN? GPGA=ON; G.P. Counter Uses GATE? GPMC=ON; G.P. Counter Cleared With MCA Counters? MCAE=OFF; MCA/MCS Enable VOLU=ON; Speaker On/Off CON1=DAC; Connector 1 CON2=AUXOUT2; Connector 2 <> <> Device Type: PX5 Serial Number: 4521 Firmware: 6.09 Build: 7 FPGA: 7.01 Fast Count: 27944 Slow Count: 38575 GP Count: 0 Accumulation Time: 30.000000 Real Time: 30.116000 Dead Time: HV Volt: -130V TEC Temp: 230K Board Temp: 34C <> Sigima-1.1.1/sigima/data/tests/curve_formats/square2.npy000066400000000000000000020002001514013333200232250ustar00rootroot00000000000000NUMPYv{'descr': '㿀_x]F\n@׾$ Q(  Jʽ8k`D}a{E{*8)v4RU򱻀zpwn혺+j躀ۂefbCKl_@/ܹaYU֤ Tƿϸ5磌]N I*lHLP÷m4B='O=බws70ȴ61XqyUgA,9$iᴀ&Z ! BԳ3d[vNZ >Ȳ" B$ -MNϻupx5{򰀿{_Cl>v()g8 毀pZ𢯀{_j辜ٮ0eXeS_#ID-ͭYfևF"TJʽrN} :H/jPNCr2q<.d=ꪀާ7dݴ!2;ީ-\oV,~SX~7&Ҩϣ K%HGŧpht?X< v9 3b1鹿Sͬti&|y㤀+]SvA]|&p= ף^jP衶 EeÚʢm~_cD'GYI+j{7T7_ѭNϻnH+3h蟀(CULQv0by=۞7ܘU2B?ϝk,amQI&5Ü !4<\*KmsՒr0V횀&:N gw$6ǁW˝xZ|@wԘhv[?Np $ Aȗ kc섗2AZeǘ_|x a5Y,E򕀿#M)LTo ltѐ(N唀ӹH_=C8fٓfYJ={.S7̒ډ/2FW",Dek}&O:3!!Ipq -.ꏀPqdp!;Tގc 8X܁:э[Ɏ-|}KU}vuŌYp>?$"kFGguoe2⪲_̖ziZ_&80C㉀aTR's ]N˶ֈIط*PRC {B|`j=e_!seAI0eiƢdCͩdfd=#d (zc28J^c[kBZc2&c b,bMb$' bL4au!VawcAaG`+`x`>4`f_@_ bk_߇(_h^0L^X0_^| ^*]vLݕ]mR]"q]J\rkm\QF\e6\6[`X|[VaU!9UZ}uU|a2UET+)TS iT{%T#S ESf\SSEfRmJR|.PR  Rv/QPۆQ7qrCQ_QkPkzPeO7P4O(`;OQ\mOyZ~*OןNTNaNOqNB%UMkIG9MhUMCML >ɋL4HL\8L1vK2SZKկt>@I|@q89@?26t?WXp?-y<-?; >c'>c>! >ܞ =B=-cyW=U]=}A<%<΍ K< <,;GN;oo>;~:|b:Fu:w*2:89aq89Yh9k{%9蜟8f8*g\8R`L8{"07ZD7eO7T 7Ҩ6DOʤ6lC6I m6.Q5CP5z5 q756>4^48m4*423:r3(-\Va3P}:3x'22!T22%1BF1jhwH1[1?0#0 <03/\1е/Rr/s//||.`.%wDf.M(#.vq -<-k^Y--f,?,g`eM,J ,Z'.+H+Uj@+1ҋ*YO*΢w*I4*k)C3O)"T3k)K>v()s(8ߡ(ĵ^(2('<-?p'e`TR''8'&!&E&.&V)%K|%lu9%Y$=$ !p$H-$q#5Φ#Vc#|x #z":w^"bBW"q&" !kA!bJ!,f!T㥛 |` c> Z H+,UMuFn1nO̱IӠh%Di77M`>Y1\z8ٵݒ3O) Q-"zCn'eRCʤ6!yC6k .Omqs* W5 ;]a9̗|[T'|Owxw\q@H%k$ E~Afg;i㈵`}rZa/ F2U0*[QfOs"̔IמY$DLgu>@f-&'HlwߤiP4"40Xj' ѓ2 T^ "uq J U r9 R   }>ʈ <_E dw v qZ| >9 l# -( VfJo ~k, `ݮZ{c_ GUDp4(OV WwIǺ9DܜJa>e@I8b->+3St{-1 '+Ljh"nN%E2m[77XO_ zo S7؂CQByXmB !N`ݑ4yTBZ H&ǝv;ǻ#cf+/h" /ZrL L;~m5w=}wGjq/lV^f`SQ![qUwEO@J_9cDв>,9(aU3k) -'F"4wJ8 @tk*3h{K[lTO WB^ؚu6 >Pc*ΣA,_o'㪲38~ԙ{H%ruƈDeig}1Yw rPLYlfR@`K[\3UOs'̔.931]-t% ({p"=~oFbc IVTg/JFT=闈P17`$ң)qz):l ʅk5[y x#]lA|`OD T AMG}ew-;2rlY.f$aN"u["UePfJo D.8?qX9v3-:YjJ(}!"]׻<FzQB˺ E-Ӿ~R8c+,p]䠄aL&iSͬm26tEug6>W[հ؟N(ȯyJxBɎ@6kѯ}V) xa\r)lfbNa[JU+~@PnJqDk1?74e9zަ3X#.ҥt(CUL"Ƥ?e Ov3 >W'ϠZI_'#;fީ{H,/o}rǵbiܛo;2V~ϚI`ÙGS=R0St$D<}͑6x_ r]l%'g(xxak[~lVFjP4`Jwِ ES[?g͏9@0G3M.:( "LQ.?!1 Xr: " ˂sc[v#e,ioٲ|]VDׅ8 Q{ʄH¾DfD.8:ʾ+ۥ ,PO|͔n\p8~~}`x%s}rh|mYg|Qg!{a1Z{[tzCVzNzPByJ= By5Eӻx?Û5x9dw&4I,)ww.v(ϼv#uiUMut t[ }sanr6qrLq)dqlp>WXpo5Ko0xnӻx?n@m!A 3mr„ѬlüǙ&l bkdM*kjӺ jUiYKi{hGg"ngelf9~4bfxer.Ue+mqd{gUIdac\:-WӁVt!VK=UJU͎T=ЕT^SޫV&R/uRܶQКiQ!bGPq]P‰O+POc~nhNx0DNsMUm77MgzLaQ+LF\KVCKPJ8KrJE ;I?OI*:Hz4ՓG.\sG)[$Fl#fFE $}ZE^gED NDCP0ACrfB.5BAA;(A~@3O@?G?%Ί>up>9}=S<gp<ّ;Zd;Y_":W:9J({K9kC8쉮 ?8<Ӹ7~427xwd6.s,&6m5g@5 b4p\M 4V 3QL3bKz2En1@7n1T:X04a0.ޏ/E)!XU/#d .H.7--y<- pA,) 0,yѩ+8#+{b*k**) D )]߇(K' x'OP&ȓk&l%@5_%\$ⱟR$2#%VF#Ӡh"$9"t!ŏ1w-!t? f! ~Ϛy=Xs`m(gJbI\uVI;QiKUE\-@j~:3P4a/Co)狽#*T7ma* 6uSy=͋EA^&6 rMِf(GyZYÜMjh "1A  e \4 뉮 .R( Nq   @:s };~1y|sFm\p#h$tbc\RW}WeQEKKF^W@>:f4'/2I/j)%#~:3P~v~ ~, ~}?q~9z~~om~J~Za~`"~T~V~Rԙ{H~C~ <~DbԵ~/~d~5+-#~n~צ~'~x7N ~ȕz~~iw~Co~ 7k~[y~s ^~mO~MhXR~b ~\E~?W[~Qy9~KA~0F$ -~@gҦ~: ~"5b~s/0+~)s~$~d~$|o~~c~0EH~ W~~!J~rPi~1>~~d1~\~R%~U~%~h~Gɫs ~;~1~9ty~~ڬ\m~*=%~{`~̛õ~~T~mIF~H~~_;~yUg~t//~Pn~h"~ba~B]P~W~Q* ~4Lm~Fq~@9w~%;6~v5yj~/~*Z^~h$B#ظ~Q~ ȳ˷~Y |E~ ND~ 9~KԲ~,~Ye~=- ~~"~/e~ڨN~~ .~qqt~ôo~7h~c:~}[~խ~TYO~F!ɬ~B~F̱~z6~RB~8 *~ң~y~*t^c~zn+~h~c'~l]j~~WL~ Rr~^L3~Fve~@mߣ~O;5Y~5?Ң~/L~A*Ŏơ~$W@~K~33~ѯ~ x'~%W@~u~Д~~gba~)~{~Y+~no~ԱJ~Jc~7ܘ~zV~~ ~z΅~Tt$~ng_y~h'~Ecl~]0~Ws`~7RHڍ~LT~F<͌~)AG~y;i~52;~0H~k*.~$Ί~ S"~]T~~ ګ~Ot ~`<~~@v~(~k]j~2%~]~4ׂ~$w~Q~tϺFˁ~E~@׾~f8~g~ 0,~XL~~~~҈}~IQ}~X|~됛|~;ީ{~!rz~d:tz~-zy~~tgy~n-x~ip[[x~oc#w~]Nw~X9v~aR||Bv~LDu~G 6u~SAEկt~;)t~5es~D0.s~*Qr~$r~6׆q~Oq~]~p~(o~xqo~&pn~h8en~jm~Xm~ 1l~\tYLl~!k~?k~N=j~πz3j~Bi~? 'i~IӠh~Ḍh~1cg~,g~ҧUf~#f~sۄ{e~ĖMd~aod~ec~bc~*nb~Wzm6Vb~ta~nIa~Ii6`~cyW=`~]_~:X0_~RB^~Lx$^~,G@]~}A ]~;Nё\~6 \~n0a[~**Z~%ZxZ~`Y~lY~#KX~Rf`X~W~SW~D.lV~q4GV~U~5:U~:T~}U.T~'S~x!S~FR~ʉvR~i>Q~ Q~ RςP~[O~_vO~(N~M^iN~M~]M~?'IL~jQL~K~0DK~z3jJ~tv28J~"oI~si+I~c?H~^SH~dXG~RG~MKF~VGtF~A~z0)>~_=~=~C<~QۆQ<~;~ ;~CO}:~Ēr9~:q9~48~[d8~֭7~&[X7~w$$6~ǜgK6~5~h|?5~0E4~ s 34~Zլ3~z&3~t^H0~XO0~R{/~/M.~GTn.~Ap-~!<8b-~r6,~0`U,~++~c%YI+~)"*~l<*~U)~z0)~5C(~Gx $(~ӝ'~'~9@d&~, &~%~* $~{Lx$~ՏM#~l#~m"~X_"~n!~^6S!~! ~dF ~P~W:~- ~Bp-~~x!~49A~| ~zю~%u~voEb~i*~du~h^~XQi~ SK~YM]~G~A]P~K?~~~c~I`s~( ~Tf ~ ~UZ ~FИI ~N ~ ~8aA ~j ~ٳ25 ~)*~zm(~ˢ~S~l6~y~ ~]t~B=}~z~Oup~o ~iN^d~Ad&~^W~X~3SZK~MG}G?}$B#ظ}u}k}X32}1}%}!}#dT}s֧} }-}epu}=z}}W9m}|}^a}H'}ET}ꗈο}:H}H¾}ۆQ<},ص}|{נ/}ui}p]1#}nj}d}_&}`YiR }S}N}RH2w}Bus}<;k}C7}1>^}+ص}5&\R} %̴}JE}'}w}9} F}V-}i֦}۞ } g}[a/}}}M*}mP}аu}>}6h}߿yq}09\}֪}ѮBO}"ɩ}rZC}Ý #}N6}d}{*}D}VZ }{ԗ}u}Hp#e}jf-}d~}9_}Y/r}SrN}+Nf}|Hߠ}B;Y}=~oӟ}m77M}1Ǟ},G@}_&} X4}!}QS'}} y}CB}^ }҈}4}'c|}j+}&o}w}3c}vLݕ}h˹W}Д} ?J}Zmē}5>}}LK1}}V%}=}W}ߌ}/w } @}{c}!vy}rp}j,am}eo)}c_`}Yڊ}T8T}UN{JΉ}HH}B}G=D;}7k}13/}8, }&P"} }*T}{}\ } }lu}$>w}g}^j}}0_^}Ps'}ܶQ}~}BY1\}Z![}XT$[}NZ}HJzZ}JCBY}= Y}7ӅX}<2VW},cyW}&+V}-!lV}~bU}`U}LT}p +TT}nS}GS}bmR}66;R}yQ}S.Q}P}BW"P}EׅO}O} N}7Nx N}@M}غL}(vL}yZK}ʩajK})J}k#]J}fI} QI}\JH}/EH}r۾G}N|8G}vkF}p;4,F}@k~E}eE}_D}2ZGUD}TC}NC}#IB}tCSvA}=>tA}8@}f2g@},_?}'_[?}W!'>}(N>}k=}IB=} H<}46<};vٯ;});}i:}-?2:}}9}9}8}oKS8}ю~7}6}aq6}Wt5}"D}i8en}268} -}['.+}!q}W}L}:} } }>x }A }E }0s }˙ }bg }"Q* }rݔZ }׺}N}d]K}ƠB}ۻ}V&5}il}4)}G}2}u}9U}}ڍ>}+}}{v}|?q}wJ|mqd|kЗ|f`X|_`V(|ZK|Uܸ|QO?|IbI|C3|B>٬|8+&|2nj|4-2|'|!7 |&z|vS|{| C|hn|t| =b|ZN|U|ԕ|L^I|Z&|ם<|=බ|#0|fG|/$|ם|е/|!rh|q0 |¤|;|c~x|Q|l|UG|_||r|Gw;S|qS|kF|8fٓ|`\:|Z_$|*U-|{O崧|I(}!|DkE|l> |8Վ| 34|^-wf|'.|!u|P@|i|O|A ]|L|P|3p|9D|W|%7|vݑ| Z+|c"|gҦ|鲘|,{|YoC| ||K8|{ds|줾,|<f|D|ޓZ|.M| N|ςP| }A|pwn|q75|l\|bf(|`⏢|[%X|TUh |O|I|FD1y|>tA}|8 |73p|-=|'bd|)"*|zW|I|K|k K|?| Uܸ|]2|l|5&|O`||捓|A)V |l|̯|2z|5w|Իx?n|$|ua|ŪA۽|`U|f(ϼ| H|M»|X<|I|0|J}Yک|w#|qj|:u|9}=_|a3ٲ|-R|(F̱|S"^F|&|9|ER| -|G|7!|]ؚ||(h|y&1|i|ެ|ku|2R| ui|\Ǹ|\|>s֧|N;P|ʦ|C|@J|\7|$|1*|V|ӈ}|#E|t}|wb֋|r|flf|f+/|anr|W[|Uf|O7P|IJzZ|DӜ|>M|;9CqǛ|39A|-|,( 4|}"O|Z(|"|o| [|{|`C|# |f||R臭|dp|/-|Drc|صݒ|W|6;Nё|~K|Đ|'>|xGo|ɰ72||j%|S| X|[ | |_|My|}Az|w( |?rkm|l|fba|1a4+ۇ|[wT|UΆ|"PH|sJ@L…|D<|?ܵ|e9 /|3Lm|.5#|V(|"|X|HV || !|:dw|w~|?k~|,,}||o^}|鲘||`R||n8){|{E{|Ӿz|`9z|DJy|‡-y|Qڦx| x|Pkw|C3w|v|v|5\u|Tt|֎ut|'%s|whhs|}ur|x=\r|ir1q|ltOq| gp|[a^Cp|[='o|U6o|LP÷n|J*n|DIHm|>?m|9ؗl|3l|0.Uik|(1k|"~j|!i|rari|Rh| fh|d*g|mYg|sf|V;Mf|5e|x@e|G仔d|\4d|A%c|9ӄ'c|ǵb| ~b|+MFa|{a|̶ֈ`|`|mYg|_|/^|o^|_"]|ec]|P\|PW\|.[|}qJ[|BxqZ|r9>Z|l:Y|4g}1Y|aX|[[%X|&VF#W|vPW|J̳V|E| V|h?RDU|9 U| 4yT|Z.S|(^emS|"-R|K`R|'Q|jTQ|= NP|HP|3O|/u;O|oN|7/N|!>M|q"M|ĐL|YL|cJ!K|͍ K|бJ|UzI|VBwI| H|FjH|G|bc^G|8+F|QF|ٔ+E|*nEE|zLD|˃9D|~7ݲC|lxz,C|rmB| m6 B|^gCA|aA|[Ɏ@|PV W@|PO?|J>|AEկt>|?x=|9[@h=|34<|.[<|($;|%#gaO;|u):|B:|09|g s69|J8|*8|Y;ۣ7|~7|k6|K46|G5|ފ5|<͌~4|U3|Sr3|.Ȗ2|٭e2|ϼv1| _>Y1|p0|L0|(/|bk_@/|'.|3.|T4-|w'-|H,|F~,|x@ٔ+|r+|7mi*|g 2*|aL{)|)\(|zVҊo(|PS'|KXc'|kE&|?ޫV&| :!t%|]4dV{x{VI{噗{j_={({ b0{[Υ{${+I{Mn{ّ{ {?7j{z2{࠽x{0{Cl{ҏS{"`{s {~OS{yt{dsyX5{sp{m8){0h!{bd{\{!WY{rQ-"{Kp{F}{d@z{:9Cq{5| {U/d{){#EdX{G,{K{{9 Q?{M{3{+ެ{{\&{n{6{m%{h {ګ{_W{1 {{t{P÷n{x{=Ab{B ܺ{U{Ϲ{4IbI{*ø{Օ<{%{vU0{DŽK{${hyܝ{sa{ nl{Zh4 {b*{\m{KWx{QU{K6l{=Fy{@_{:vٯ{/5B?S{/ͮ{)F{ $ {qN`:{({-{c {Z!{I{T{"ڎ{e{Fj{2{.u{8q{Դi{S{*:]{z}֤{˽P{uʣ{lF=D{{ 7{^{R^+{&{O{{^{AG{y{s'{3nj{hhs{b0{%]3f{uWv{QZ{LQԙ{gF?N{@ǘ{;ŪA{Y5s{/K;5{){J$({{W\{<${ { {.c}{~E}{ { +p{pn{fd{.ޏ{b7W{zю{ϽK{TPō{C?{ฌ{Eɨ2{ q{O9&{7{{؛{)[Z {y"{ʊ{$z{kg{{yCn{ t {]n0a{hsۄ{bdU{O],σ{WW{`tysV{n;2V{iU{RcB%U{]T{W\T{DR %S{LN S{FR{5A}R{;FzQ{5ZP{'0mP{x*O{$#gaO{f/N{iTN{M{ /HM{[rPL{{+i7>{|c={]K={X<{nRX;{L!u;{GW:{_Ah:{;y9{6 B\9{Q0c 8{*O8{$7{C,cC7{o+6{66{45{8*5{{L4{&4{wݗ3{C3{m2{h52{ ~1{ O0{ZՒr0{V/{f/{L[.{Y.{w-{>$@M-{g,{ߧ@,{/혺+{0a4+{іs)*{!'*{r){…<){J({cz({tۈ'{oH'{Uik|&{c3%{]o%{GXT${Rc${LT#{9GW#{A`"{;J"{*6u!{{0)>>!{*l {%1 {m{5_%{x'{^{{A {PH{{ y{BL{im{1{4`{X{ϛT{%R{v!H{ƾd{;{hs{-[{#{{*t{zI|{Dh{ {l[{U{ eO{^-{B{a{Oʤ6{Nz**zAmߣzzoz368zyzԜz$~zuBYzƋ!rzzg ezzNzzuBYzXo ziLzcZzJ^c@zX+zR#3z;ziz$d .zt^czX_"zS'zfM,zGozB zX٬z Йzb.zV*z0!z ܺzz"aKzr zۂz*zdmlvz4zizV6zy]zʼUסzHQzBʠz鹅Dz9vz ?8zڨNz++z|ԗz̗`zZ(zmzฌz#z_{fIzuzpszQj/zdrjgz^2zCYZzS;ԖzM~Nz4HSȕzBBzdz3ތzvhXz/ܹ0ҋzKz?Ŋz!˂?zrQz¿3zK⬈zc&zrz;zUWz zݓzG \zc${z膦z8nz{,}zuoEbz*p ܁z{jUzd8πz_{fIzmY.zS<zND~z^H0~zBO}z< $}zP7P|z1|z+p{zB&9 {z \zzyz3xyz%Zxz h"lxz%wzv_wz0{vzsCSvzg uzFuz uRzj=&RzeQzp_QzYJPzT^ PzbN&OzHOzCVzNzS=Mz7GnMz1LzE,baLz&Kz hUKz7+1JznHJzIz( zŒr9>z=zf-=z;PzH2wz,?2z&1z:!t%zz`z,=)z| zùzznHJzzzmz`zTkazݗ3zRTzz`HzCƣTz<z)z5l/zuz֩=#z'5zwxzȘz^ ziA'z z Ƿw z[| zvMHk zp zLk^ ze z_YiR z>Z1 zTE zN"¿z0Ie9zCRz=-z"8.zr2q z,sz';zd!:z}zzV]z F%uzzG˵hz~zQF\z9yOyy+]gCy{נ/y6y&ymi*yPyy_2yuyqyQ9y>yyBĒry[yJ#fy4y|гYyv|y&qVDMyvk ye@y`yhZbe4yT-y O'yZI+yCny=NyL8y27߈y,zy='o|y!8yCpy/yɐcy Yy!O!WyqyԱJyzycZB>y y1yU#yfc%yѩ+yGy/yr y8Lyyٯ;yy*~y{mmy˞6yG`yly͎TyWy^SHy|yvٯ;yPqxyk_@/yeyB`"yZ(yTkay3O)yI yC4y%>wyv8Jwy2y-@jyg'y!k^y 4yYLQyy ҌEyKUyW9yy<ݭ,y vyc> y.yy,y o_yq̲'yy8tyb{yHhyyTD[yyiOyF 2yPBy獓¼y7֊6ySy|\*y)wyzqyk%tyfh<yk`yZy U1~y]Ot]yI%ryCyO>=ey8~߿y2FYyA-Ӿy'ILy!ƽy2g@y0yU3y$ yuۈ'yQy`yfᔹyy)ryXl:yݯ|yyJ5oyx[yƻ#cy<ܴyAVyݵ|гy-DJy~ IJyϤM=yype1y.yY$yay߆y}"OySwe yq߅ykyEf.pyy`q8yZmy7UyO:`yI}Yکy(D!Tyy>ͨy8FGy3zyk-B;y' y "R.y\yc"y,yN ^yy y@&Myiyvy2y2njyu6y#ظ]ytמy>QyǁW˝yfEy辜yJ8yWxy@,y yIVyyay;*yby܂y,}y}w+Ktyqnylgyofy`7l[y[z4ՓyaUNyOȒyJCByRDUy>6y8 毐yD3O)y-vy'>y6"y[yy'_yx $(~ygyqyjy/Iey r߉y[Xy҈y;jLyM~2Ƈy?yùy?G3ySy'y1䠄ySyҪty"<ysyę_y{ye]y(&oykyV}byw~~yq4GV~yHlw}yfI}y`|y:[@h=|yU0{yO0{y,J zy|DL$zy>Qyy9yyn3xy-X xy(rwy`":vy!yvyduyQluy [ty-$`tyCpsySsy|ry58EGry{ qy:qy'pywDf.py҇.oy!oyi nyPny Omy[ myly\kyLpvky8jy%jjy>hiy]iy߈Yhy01"Qhy}tgywDgy"rzfyrl=C8fyf eya+eyd[dyUIddyP,cyVJcyDby>UbyG9May3`y-s`y9(a_y"ng_y6^y+*Z^y{m]y N]yW\ym6 B\yx[y5[y_xZyAA)Zy YyQYy XyMbXyB͐*WyWy}Vy4YUyKqUyհTy&"dTyveSyǟlXSy4Ryh.KRyqQy ?QyZUPy}:3Pyw}OyKr&OylwNyfF?Ny=aMy[ MyULy/PR`LyJ({KyDJy!?nJyq9^Iy3IbIy.Hyc('UHy"jGyjIGyU2Fy3$Dy8CyĬCyuBy*J= ByzލAy@yx@ylV^?yǙ&l?y >y^_>yb=yGS=yPx0{xD2xb x"ߥ%xs蜟x+exn-xeȱ xx7xVzNzxxmxHCxoax7x: UxOxۉHx+Xx|~!4axw)uxºx0hx@xѱJ\x!xr OxàLxkCxd3x6xXİxU*x~Txx!xGsdxmxgux9b->x\pxVx+Qrx{K9_xE|'fx@߼xm:Yx4Eӻx/HMx_)Ǻx#@xQxPi4x1x 'xB]¡xxRx4%xh㈵xꫫx&s|xv1xx1x=Uxg%xޏ/x/xax~ x yPxqs*xmmyxhxcbqmx\6:xWyaxUQڦxKTxEB[ΥxF@#Hx:x4 ;x8/N|x)D/x# x*"xzZxex -xl# xfx x^Nwx.xqjxO崧xo^x:8؛xA}Rx˚xEx3FYx!9xԷ鲘x%,xuRzxƦB x xgx^xcxY+x'x~jtxJyxsLhxm3xx|~x$}x2go}x_|xӄ'c|x$0{xtysV{xszxnHJzxfh<yxb=yx]¡xxXWj1xxQH2wxK$wxJFžvx@vx:TSux;5 ux/tx)sx-$`tysx~xH?=xRy=xԕ*xD)x)x/Q(x 'xOs'x!撪&xrrg&x;%x[[%xdϞ$xN$x$\#xUg$B#x"x5"xG0}!xsE)!x衶 x9 x<xڐfx*.x{xH}xzxmtOqxnxiTdx^cx]pXxX9xPR`LxLxF?xBA)Zx;l"3x5x40&x*5{x$xCx% xv xAxdxh,{x x LnxYxMbxxKXUxxnIx=!7 xd< xɧǶ x/0 x-X xиp $ x xq x9y x|A xc xxExxTbx*lxxFzQ_xtxnKSx8ixc]Fx]x*Xl:xzR&5xLi-xGŧxlA!x;2Vw 6uw^0w*w$>wwO?wvwwAJiw`w(]w3wUPww%IDwuwa7wۤwgj+w*3wmwYİØww6TwJywwwwwiQH2ww %w[w]iw1wM w&†wziw>uRzwowi2mw0duw^sawX;ۣw"S>UwrM΢wGĔHwB]¡wdB͐*w<Yw6S!w/1闈w+ٱw%zw! _Bwr ww(rwc kcw+fw߃wU3YwvӂwLMwGǁw?@wۂw9m4w6wK'w*Ŏơ~w{ю~w˹W}wW}wm|wݯ|w x|{w^c@zwpzwywP,cywoaxw)WxwB{wwu8Jwwo{vw3jJ>vwduw^D1uw%YtwvSk%twM 4swHPswhBĒrw<֌ rw 7UqwY1\qw+ypw%owK %vmowh>nwanw=mw 1Tmwt_lw.'Hlwkw<;kw jwqH/jwiwH"iwb֋hwihw2gwTT gwƒfwڊewFSwew`dw稣jdw8cw)t^cwٗl'Iw{YHwu!Hw7pGwjJGwdzFw)_BFwyY |EwSVDwNoDwkHcCwB,cCw =bBw]7VBw1Aw++MJAwN&n@w =@w?w@7n1?wz6>w $>w2Ǟ=wB=wW-wS^-wDN_,wHQ,wB_+w6=((E+w7k*w18*w(,)wx&4I,)w w(w(wj'w@j'w 2&w\&wÀ%wK$wMSt$w#wg#w?W"wܚt["wxw wߣzw0ACw ywђw" lwrMdwÁ,`w|wdvSwpYwkMGwVev_":vYevGTn.vN6vH.!v9CqǛv=v7Wv+2: v|,}v&v!yvvmFAv jvv_ ]vRbv*QvQvDv]vBK8vv&+v4ivѬlv4v&2vvuŌvǺvUvh>vsv ĮvZwgvJ?v[vLvNvV`v=|(Bvvvp5v/kbveI)v_v!Z+vqTnvNjvI2vcC7v=z}v8vU2Tqv,Cv&dvG!ɬv uXvO=v8Lv v?v*Z^v{&3vv#&vlfvGvv^/ vrv˵hvP0{v;v~nvBvRbvGv3UvͪvԘsIv%S;vv=vƇ˶v0vg|_\vv$$v qvYk(vek}v_E vKZ vT4vNwxv=IfvC.lv=@v.8_v2Ƈv, PSv 'Lvq!FvҨvq:vbX9v .vɧvT !vcZv"vFv,vo{v7ݲCv vv8v){ivzƾdv-]vDvlPvʅʿv NDv]Pv7v֦vOo+v\7vvAǘv|%vvhXv2q vkve1v$`tysvuZAvT gvO=vfIZvCbԵv>+NvX8IǴv2Av,σvJ'L5v!Uv(v<ۤvmv a5v-v~ʼnv)vlV}vpvpv5vaxwdv׻?ޫvXvSAѪvƄKv`ũvE )?vMv毐2v7ӁvJ&v؞Yv(vyߢvʍ"k ve3vkv|zv w.v\qqTnvkveavN`:۠vZ}uUvT=ϟv@OIvIFžvC^v8'0v2R臭v#-#vt'v!Hv^vf v䠄v 'ivWj1xvvkvI2vuR_vٕv;Rv>̔vׁsFv-;v}:vJ̳v-vo\v%!vV횐vav}vFvRbvvuvD+gvn/iv|v6w\vq7֊vkzPPv'fʉvx`CvZCvUq7vjO9vI +v DOʤv\>v8Zv2#vM-[닄v'v!{v?$Dvg svv1 fv0evr-Zv"vsMv;~v~NA~ve}v4}vG|vVҊo(|v7{v{vHSȕzvzvXyv:!yv_|xvۤwv,ypwv|(Bvv͓k dvvuvnWuv4ctv}w+Ktv`wsvq>svl@rvQfL2rv`qvZ %qvCULpvOmpvI5ov5D ov>XƆnv8nv'3Vzmvw-!lv'dmlv"kviwakv-@jv pUjv[ ivHiv8ahvL{)DfvJ#fvev0 evPdv̓k dv"3cvrbvû\wbvavdTkav%`vh^`vV_vuR_v1>^vGtF^vο]v9]v9}=_\vw'-\vq[v+l [v{fIZv`HZv[YvmUYvOUXvJiWv_D1uWv>Vv9ahVvQ3Uv-R\Uv'*TvB"mOTvSvsCSv46-W?v*9'>v{3jJ>v-=v(N>=vl"3vOCv(ϼvk6vA_v'*v4v2wvvӟHv$@vuvŎơ~v jvfL2rv}vxevXrvlXSYvfvJaLv[!vUdt@v#uT:uu0r.u ;u`"u!˛uru(\uk$ uduu4}vuUwEuӺ juuG@]uƒf׽u.Qu9 ʼuLDuګu+O8u{u̚X+uumpu!9udu_~Ɍuxus-ZuPmp"ugsuauB\9{guV|CuP [u4KԲuEENu?dȱu&:,Buv4u.Q5u)uh#M)uu ]uZu nu&7uKiu}uu=1Xqut udu/ިu=yXuӀAҧu! LuqŦuI?ubuc*3uuU&uUuKuuFa uulu8*5{u~muxnu*suzm6VbugyܝubUul\ϜuVBwIu Q?Ûu^K=uE жu?N0uP:`u4($u.uA)Zu#uI u3#ufu xu%juu/3luqu_ugْu:TSu}͑uYFuuFu:uJΉ=u.uΧu+NuΤMuDÖMu_LuI'Lu5KuϷKuJu'UHIuxԘsIuHufHuiaiGu1ZGu Fu[*MFumEuRAEuMDu64DuyCu?s(Cu;BuBBu0̕AuyȔAus ]@u"nN%@ush|?ubԵ>u]~p>udWZF=uQd=uL:u)r9u:$P29u8u;%8u+~7u| q7u:6uG 6unʆ5u̒5u[z4u_R#3um3uس2uQ|a2u^D1uΡ U1uC0u'H0uje/u5-]ݱ&uW zR&uQcB%u0L F%uFҿ$u@,9$u!;oc#ur5+-#u/"u*8 "ud${!uL!u uUD u umuG 6uuOuhu9ՎuW\u[u*Ou{u$xCug@umɪ7uаu0*u_sau)uuP<uuJuBuHu㊋ru4ku4fuyTu%tYuvnڌuhUMuc`uh]@uW歺u R)v4uYLl> uF( u@Ρ uK;5 u5x_ u/' u=* u$A u| u/Hu pu Mu cuqiu2WuXucJuފu!S>uTduڧ1uꫫuF-t%up<uóu8̒u9 uٲ|]t*%tzytˡEt~mtlFtat Qt^Ttgty0HtOt]tn;th㈵tAc&Q/t]itW"t3R臭tL2rtFu:t%A tu;ʃt5>t0[wtg*#t$jtJtY|^tDt  RtJVtEtet<.9tat뤾,t.熦t~*O tmt հtpt6pty8tbtttBtTYht!t [tENtzOtBt7 CtZӼt6t)zctyt#,*tnftitkc섗t]/Mt Xrt]RtL~tF;ntNA~6rt;t5et@0Gt*WYt$t2LtStx@t$@tt 4t_ѭt'tfat'*tjtX歺tt3KtIv|tϹtot;?lt4ctܸt-Vt}KtΧUJtto=tWtv1ta>t %tcϞtSztt_tn,( tDiotct]yt6X8ItR{mtLt(G`txADjt;2Tt6tj0 Gt*Pt %S;t\t.t\tNt"tʈ @tӹt3t0Qdt,'tѭt"ts]tÜMttd&ti{tntV6otz2ttubtHoܚtiWVtc> Йt9^ItXİØtRy=t+MJAt|G 1tAѪt<$tm6Vbt0*t+t_% tbtKtQyt+tnltClt4`t6ُt4ySt켍͎tUGt&Btwۅ:tȮt w.thN?tđ"t ϛtZtZ`t( tLt#tfvt>Itjtߋ/t/r]tjׄtz2Qt!u;ʃtro~DtitdT8tc^GtX+tSͬtUMutGS=tAtG<͌~t6~t0_^}t9+&|t%s|t({t*kg{t{Gzt[zt 4ytmwNythxt0Bxt^?wt5wtʼnvtPR)vtKutՎutBѪttsttW;st4st}rtճ qt%c\qqtv$ptƢdpt,otho}XotEnt LntY8mt{?mtzfltKu/3ltoDkti&kt=dʇjt^ PjtXPit.S itM֨htGqht B\9{gtq<ft6nft1%etc+hZbet%"dt UdtT1ctt{IctCbtF =bt=Զat0at8d`t-$`tH_t)狽_tz΅^tN ^tT]tlЗ\tڦx\t o[t]`7l[tZt_ZtO)YtlXSYt XtAFXt5Wtxy:Wt3AVt .VtԀAҧUt${!UtuubTto +TtjMStgdSt^ӃRtYLQtXSYvQtMPtGߤiPtJB"mOt?t]u?t=>t>tN{JΉ=tu=to^}UWtkt3Kt0t`>t磌t"T2tr)sl%sѯsdus5>sx sVΆssA_zsH'sms s9MasHsڌUs+s|YHs{isv1:ussдhs!sqJ[\s£#sOscsV|CsDsU 7sհs{b*sGvesp-sj+s8ens_sYNs*T7s{NzsHrsCpsl=C8fs7s2Ys^, s&OYMs !sP@ss[z4sB Bs (s#ӡs3fscs+s%/svrsܵ|sLsg;ps~s csYnsG6WssKJssSW>s=s1sޒs._x%s@sρs |(ђsqvk spask)sbe4ys_wsZmsTTJsN@asHsFCƣTs= ls7L4Hs82s,;s&s)!XU/szs"s!sl dvs>s  s],σsos_wsO's8js{sA׾^sIطsDRs2Ƈ˶sʡEsԺ js$P29susũ,ssg\S sssX%shtsGs聏sW;sD sJ.sэs6x"sAsV s(яsxܙ sɯbsb*sjvss +js\nKs^sׁsM7Qs|zlˀsv4Es?qskC8se~s1`U,~sZ }sTO}s"O|ssIv|sC?{s>[{se8πzs2ys-$`tysW'g(xs!gxswsH0[wssIvs Ovs:us;Bus~jts,26ts|ssG)ss㊋rsnSrsqsSqs`̖pstps=~osQ_nsqnsmsC(^emsk&ls䞮Xls5ks4Lks֍wGjs'@jsw׹is|@3iswhhsiq0'hsk gs fLgs[`fsZQfsTesLOXesI{dsCrcs>>!;ocs8dbs2bbs0-as'-\Vas!p$`s"I`sr_s9}=_s |E^sd 1^s֪]sD$]sVf\s.\s [sGP [sݓZsOYs9yYs\XsƟlXs+pWs{%9`Ws̵hVsSVsmUs1ZGUst"Ts_:TsSs={.SsQCRs "Rs|ԛQsBwIQsqdPsk, Ps4fOs`UNsZvNs&UMMsvOjMsIaLsD]Lsh>nKs8*7QKs 3mJsZ-DJs'Is!6X8IsLy Hs+HsGs= ByGsAFs Fs/ ҌEsMEsbDs!*CsqsCsYBs؜gBscKAs"[Ase@sUN@sl?s.5B?sGq>s5>s=s8:V)=s}?4s8j3s333333s-v2s'&2s%"1sv?T1s0s 0sg /sKu/s={.sY-sn-sV,sK^b,s&+sU+ss֧s 9!s]3fs-9 s79|҉s3s-c}s((E+sy"ps˻sdskQLs Xs r\Kr\mr5?rNr%2rhr@ޫV&rr1r1trǷw r?r#=rtzrİØranreI)rarϹrWUrUJrIrIr}rՐr Y2r[[!r%rᱟrL$zrgBr} r>x҆rr0rlsczr0g+ramr[urhxrrhr m9rZg|_\ra'֩r[OrKVEɨrPCrJHr=E7r?Qٰr9*r/4ir.2r(]r!#rq㊋r&Srirc rrr2trUtr%\#ruV 1rPNrK|%rgEDr? r:ZՒrY4 r.er(#.rK#fyrrmr</Or rarډr.Tr:pΈr}8Hr ‡rp;rFr߉Y/rb!r"rRrTȕzrBr rE^Ӄrrcwr7',rjjrؚr)^rz3M~rʉvR~r}rk~E}rx?n|r s69|r]m{rg,{raKzrO\W zrVyrPyr@KWxrExxr?@wr2: vr4ctvr.ur$)ahurt#,*tro[trsrfOsr 8Krr{CrrXۼqr6qrClprJ4*pror or;OnrْUnrmr-mr~[~lržvkr>rkro$jrgejrira_Yir0(hrsLhrSgr@gr"DrDr IJCr[{CrJCBr BrMӀAr@rUdt@r?,?rg?r>r0a[>rΤM=rO=r"*j#r2#rߦ?"r0 "rŋ!rѕT r!Ky rrr„ѬlrurdyW=`rsrnSrUh rbc^Gr\&rGW:rQ,rKo.r9FGr@"r:8؛r+5{r{/hr)1 r$Drmrʉvr Rr_ Pjrr֪]rPsr[;QrrBDr$rg\8r4ڪ$r+r0r%s}rvöE rǽ  r<֌ rh rf r / rZHs r r·g rKPrT[r섗r=ڨNryqrs`9Br/nrh5rb)r ]lZ)rqW"rQrL5rcFx{r@Cr; rT5A}r/q)dqqF$ -qMdqq8ӅXq NqYLq*qzަ?q!oqd73qlq&q -q^pXqԳ q qO9q|yqA{qA qEnq⬈q3bbq+qԛQUq%qu׃IqƊLq]=qgܶqy0qt&mqYni5$qhqbqJ]2qWuV qQqxq@wq.;?lq~5q/J_q *qp$`Sq)qVFqbq ܁:qJqTb.qڧq!qE*kqm3qq7q6qyTq)ϼvqyqBiquqk=]q q NPq]q^Dq'qOZ7qq+q@#Hqfqyؘq2tqn/iqhr1q$cqt]qW;sqR~RqfLgqFqAGZqX;sq5;Nq/qI*SAq$q\5q;%q_(q q-}q~(Fqjq։qoq3g}qv/qapqq?dqSςPqXqqDKKqqq9?q6qW2qסq(Z&qx #qɐcqqj{ q,Dq zo q\tzqnqh8enqNc{-q]aqWۼq?RDUqLNϻqFIq1A ºq;PZq|ԛqMqdǚqE_Aqۈ'qV4qqQ(qHĔHqqٕq9]qiqۧ1q+&|q|iq̖pqRqn2dquݑqWq_zsѐqt>qcq]J]2qCX%qR%qLq4GV~qAFq; q&6׆qw0bq*gzq%/qh+mqnq aqZPۆq7Uqz΅qLHqq„qB:q/q q/N[#qՑ#qq!qrZ| q¾Dq ~qc#w~qf}qek}qU-|q/^|qr{qGR{qNzq;Fzq9~߿yqz9yqtpxq*oG8-xq{iwqc wq^vqmXSYvqR!uqMuq^GtqA_zsqW[q0Zq+1JZql%tYq_>Yq 'Xq^=1XqWqÀ%WqOIVqHVqْUqAΡ UqjTqT2Tq3ySqRqmRq$`SQquʣaQqPq)TPqgltOqqQ =qkt=qם6q$5qtY5qő"4qJ4qf~3qz2q{Cr2qXuV 1qoe1qiܛ0qIddY0q^b,/qXL/q;S.qM+@.qGnM-q-B4-q}<ݭ,q67',q1zn+qo+6+q%*q C*qa)qW)q |(qS O'qo'qx&qDAc&qZ %qV%q6$q#bJ$qf*#q(֩=#qx캷"q/1"qrK!qj%!q۞ q ; q\~lq4 qqNGqyqUq?mqSq`q1{vqu?Tqo_q#jGqsdq^(`;qYk(qeS.qMqH4"qWBwIq<q6ُqH1@ q+jq%2q: vqLqjq,Sq} ^qXqQqntq =Eqc q`8 q镲 q,^, qRo& qв q qC8 q{G q幾 q5؀qDq֨htq'0qw gqȗPq[qiQqOq \q[{Bqurqo%;6qMjhqd)q^q>Y1\qSt$pMp0HpB=}p&Rp bGp*p/:p^p .p!Kpr&"piܛppclp25 pupUܸpvp>VpGˁjpp]p8Jwp?Qpڮp*Dp{Vp˝`8p(pl+pbpp^Ip{+punڌpPppjjpd73pB_zspYpSgp3NCTpH[pBp%= Npv7Oup1=Bp,pg&5p [p ^)pY&p$p gpKpGp/p=r}pphqp.;1p~dpp XpqGRpŊLppb?pSsp;3pTp&p_pF\p$p( p8kp}p{E{p)v4pzpwnpjpefbpl_@/ܹpYUp Tƿϸp]N IpHLP÷pB=pO=බp70p1XqpA,9$p&p !p3dpZ p"p$ -pupxp{pClpg8 p{_p辜ٮpXeSpD-ͭpևFpJʽp :pPNp<.pާpݴ!p-\op~7pϣp%pphpXp vpb1ptip|ypSvA]pp= ףpjPpEeÚʢp_cDpYI+p7T7pNϻpH+p(CULpy=p7ܘp2pk,amp&5p !p\*pmspVpN gp6pxZp@wԘp?NpAȗp2Apǘp a5p#M)ptѐ(pӹppfYJppډpW"pek}p3pIpp.pqdp;TގpXp܁:эp-|}Kp}vuŌpp>?pkFpoe2p_̖pZ_&paTR'pNpIطpRC p=^Hp7pD2zp,'p&jinp6!1pap3ۃp(vUpx RςpIp>pj4`p@_p߇(_p0L^p| ^pvLݕ]p"q]prkm\pe6\p`X|[pdZZpTގpZpO!WYpVIddYpCXp=WXpG8-xWp2p@KWp,Vp9'>Vp!9Up|a2Up+)Tp{%Tp ESpSpmJRp  RpPۆQp_QpkzPp4OpQ\mOpןNpaNpB%UMphUMpLp4HLp1vKpկt>@pq89@p26t?p-y<-?pc'>p! >pB=pU]=p%

v()p8ߡ(p2(p<-?p'p'8'p!&p.&pK|%pY$p !p$pq#pVc#pz"pbBW"p !pbJ!pT㥛 pc> p+,pFn1p̱p%p77Mpzpٵݒp) pzCnpʤ6pypk pOmp Wp]app|[TpOwxpq@Hpk$ pAfg;p`pZa/p2U0*pOs"pIp$Dpu>9 p-( p~k, pݮp_ pp4(pwpǺpap@IppStp pLjhpE2p[pp7XOpSp؂CpQByoXmoN`o4yToZ Hov;of+/o"oZrLo o~mo=}oqofo![oO@ocDвo9(ao-oF"4oo @to*3hoK[olTOo WBou6oPc*ooo'o3oԙ{Houoiow oYlo`oUo̔o31]o ({o=~oobcoIVo/JoFT=oP1o`$o)qol oko x#ooODo o}eo2rofou["oPoD.8oX9vo-:Yjo"]o<FzQo Eo~R8o+,o]oaLoiomoEuooհo(ȯoɎ@okѯo xaoloNaoU+~oJqo1?74eo3Xot(CULo?oOv3oW'oZo'o;foHo}roiܛo~Ϛo`ÙoooDo9}=ogp$|oncn Wn!Jn1>nd1nR%n%nGɫs n1nn*=%n̛õnmIFnnyUgnPnnbanWn4Lmn@9wnv5yjn*Z^nQnY |En 9n,n=- n"nڨNn .nôonc:nխnF!ɬnF̱nRBnңn*t^cnhnl]j~n RrnFvenO;5Yn/Ln$W@n33n x'nunn)nY+nԱJn7ܘnnz΅nng_ynEclnWs`nLTn)AGn52;nk*.n S"nnOt nn(n2%n4ׂntϺFˁn@׾ngnXL~n҈}nX|n;ީ{nd:tzn~tgynip[[xn]NwnaR||BvnG 6un;)tnD0.sn$rnOqn(on&pnnjmn 1ln!knN=jnBinIӠhn1cgnҧUfnsۄ{enaodnbcnWzm6VbnnIancyW=`n:X0_nLx$^n}A ]n6 \n**Zn`Yn#KXnWnD.lVnUn:Tn'SnFRni>Qn RςPn_vOnM^iNn]MnjQLn0DKntv28Jnsi+In^SHnRGnVGtFn;Dn0Cn9% &BnAn|,G@n׻?n7h>n_=nC?nnI`snTf nUZ nN n8aA nٳ25 nzm(nSnyn]tnzno nAd&nXnMGm$B#ظm6hmg+/m m;mJ zmF;nmam.R\UmHmp^}mX32m%m#dTm mepumm|mH'mꗈοmH¾m,صmuimnjm_&mSmRH2wm<;km1>^m5&\RmJEmw}9mV-m۞ m[a/mmmPm>m߿yqm֪m"ɩmÝ #mdmDm{ԗmHp#emd~mY/rm+NfmB;Ymm77Mm,G@m X4mQS'm ym^ m4mj+mwmvLݕmДmZmēmmm=mߌm @m!vymj,ammc_`mT8TmHHmG=D;m13/m&P"m*Tm\ mlumgmmPs'm~mH}m3ٲ|mմi{mvzmymxmYtwm{)Y1\mXT$[mHJzZm= Ym<2VWm&+Vm~bUmLTmnSmbmRmyQmPmEׅOm Nm@Mm(vLmʩajKmk#]Jm QIm/EHmN|8Gmp;4,FmeEm2ZGUDmNCmtCSvAm8@m,_?mW!'>mk=m Hm{vmwJlkЗl_`V(lUܸlIbIlB>٬l2njl'l&zl{lhnl =blUlL^IlםtA}l73pl'bdlzWlKl?l]2l5&llA)V l̯l5wl$lŪA۽lf(ϼlM»lIlJ}Yکlqjlfel-[닄lOqxlpDkl9}=_l-RlS"^Fl9l -l7!lly&1lެl2Rl\Ǹl>s֧lʦl@Jl$lVl#Elwb֋lflflanrlUflIJzZl>Ml39Al,( 4lZ(lol{l# lR臭l/-lصݒl6;NёlĐlxGollSl[ l_l}Azl?rkmlfbal[wTl"PHlD?ml3ll(1kl!ilRhld*glsfl5elG仔dlA%clǵbl+MFal̶ֈ`lmYg|_lo^lec]lPW\l}qJ[lr9>Zl4g}1Yl[[%XlvPWlE| Vl9 UlZ.Sl"-Rl'Ql= NPl3OloNl!>MlĐLlcJ!KlбJlVBwIlFjHlbc^GlQFl*nEEl˃9Dllxz,Cl m6 BlaAlPV W@lJ>l?x=l34Y1lL0lbk_@/l3.lw'-lF~,lr+lg 2*l)\(lPS'lkE&l :!t%l.$lO#-#l%"l 9!l2F lDׅltgylPllֈ`lX\TlGlh:;l;.lݚt["l~l| lx lamlb.lVlEKOl?߾l4*p l() l6 lj! l B lBtlNMglc[lYNl1߄Ble6lt)lq6llW}Wkk~xk;s kgk}\*kQkE'Kk`:۠k/3lk#kD?{k okKbk'>VkVIkj_=k b0k$kMnk kz2k0kҏSks kytkmkVbkV$&kKk:@0Gk4ׂk|)Wkn;2VkRcB%UkW\TkLN Sk5A}Rk5ZPkx*Okf/NkMk[rPLkKk}qJk?IkډHk#Gk"ĕwFkøDkEkd^Dk'eRCkEBkH39Ak-@kt? ?k+i7>k]K=knRX;kGW:k;y9kQ0c 8k$7ko+6k45k{L4kwݗ3km2k ~1kZՒr0kf/kY.k>$@M-kߧ@,k0a4+k!'*k…<)kcz(koH'kc3%kGXT$kLT#kA`"k*6u!k*l kmkx'kkPHk ykimk4`kϛTkv!Hk;k-jf-=j|~!Z1 jN"¿jCRj"8.j,sjd!:jj F%ujG˵hjQF\jOi+]gCi6imi*iiuiQ9ii[i4iv|ivk i`iT-iZI+i=Ni27߈i='o|iCpiɐci!O!WiԱJicZB>i1ifc%iGir ii*~i˞6iliWi|iPqxieiZ(i3O)iC4iv8Jwi-@ji!k^iYLQi ҌEiW9i<ݭ,ic> ii o_iib{iiiF 2i獓¼iSi)wik%tik`i U1~iI%riO>=ei2FYi'ILi2g@iU3iuۈ'i`iiXl:iix[i<ܴiݵ|гi~ IJii.iai}"Oiq߅iEf.pyiZmiO:`i(D!Ti8FGik-B;i "R.ic"iN ^i iii2iu6itמiǁW˝i辜iWxi ii;*i܂i}w+Ktilgi`7l[iaUNiJCBi>6iD3O)i'>i[i'_igiji r߉i҈iM~2ƇiùiSi1䠄iҪtisi{i(&oiV}biq4GV~ifI}i:[@h=|iO0{i|DL$zi9yi-X xi`":vidui [tiCpsi|ri{ qi'pi҇.oii ni OmiliLpvki%jji]ii01"QhiwDgirl=C8fia+eiUIddiVJci>Ubi3`i9(a_i6^i{m]iW\ix[i_xZi Yi XiB͐*Wi}ViKqUi&"dTiǟlXSih.KRi ?Qi}:3PiKr&OifF?Ni[ Mi/PR`LiDJiq9^Ii.Hi"jGiU2Fi vöEiSDi8CiuBizލAix@iǙ&l?i^_>iGS=i+FhD2h"ߥ%h+eheȱ h7hhHCh7hOh+Xhx[hnmyhbg hV횐hQKs+h?wh4Lkh5)^hmRhwEh9h-hZ h(@hٮh>4ahºh@h!hàLhd3hXİh~ThGsdhguh\ph+QrhE|'fhm:Yh/HMh#@hPi4h 'hh4%hꫫhv1hRy=h:ؗlwgvgAJig(]gUPg%IDga7ggj+gmggJygg=g. gυ^gpzgogc#gSXgL/1gAg76;R}g*pgyGsdgXgSKg]$?g^2gE&g@jgf gvg$gŭgfg9ggIZgt gi{g-^, gRgoG8-xguRzgi2mg^sag"S>UgGĔHgdB͐*g6S!g+ٱg! _Bggc kcg߃gvӂgGǁgۂg6g*Ŏơ~g˹W}gm|g x|{gpzgP,cyg)Wxgu8Jwg3jJ>vg^D1ugvSk%tgHPsg<֌ rgY1\qg%ogh>ng=mgt_lgkg jgigb֋hg2ggƒfgFSweg稣jdg)t^cg)Rbgˆ5Eagl{%9`g pA,_gdF ^gOYM]gMg\gBYZg37߈Yg+eXgu Wgq:Vg ʼUgX|[TgSg|Rg< QgД~Pg~.rOgeNg&OYMgbLLg2p@Kg4JgE>'Igu!HgjJGg)_BFgSVDgkHcCg =bBg1AgN&n@g?gz6>g2Ǟ=gW-gDN_,gB_+g7k*g(,)g w(gj'g 2&gÀ%gMSt$gg#gܚt["g1 O!gŦB gs,&6g)g8GgWgDhgg:vPgjg|_\gT:gHh˹g`=[g2tg&|gC g{g.og'b gOV giI g ףp= g)1 gM$g5"g g0ACgђgrMdg|gpYgVefYefN6f9CqǛf7Wf|,}f!yvf jf_ ]f*QfDfBK8f&+fѬlf&2fǺfh>f ĮfJ?fLfV`fvf/kbf_fqTnfI2f=z}fU2Tqf&df uXf8Lf?f{&3f#&fGf^/ f˵hf;fBfGfͪf%S;fƇ˶fg|_\f qfek}fKZ fNwxfC.lf.8_f, PSfq!Ffq:f .fT !f"f,f7ݲCf8fzƾdfDfʅʿf]Pf֦f\7fAǘfvhXfkf$`tysfT gffIZf>+Nf2AfJ'L5f(fmf-f)fpf5f׻?ޫfSAѪf`ũfMf7Ӂf؞Yfyߢfe3f|zf\qqTnfeafZ}uUf@OIfC̔f-;fJ̳fo\fV횐f}fRbfufn/if6w\fkzPPfx`CfUq7fI +f\>f2#f'f?$Dff0ef"f;~fe}fG|f7{fHSȕzfXyf_|xf,ypwf͓k dvfnWuf}w+Ktfq>sfQfL2rfZ %qfOmpf5D of8nfw-!lf"kf-@jf[ if8ahfgf>DffefPdf"3cfû\wbfdTkafh^`fuR_fGtF^f9]fw'-\f+l [f`HZfmUYfJiWf>VfQ3Uf'*TfSf46f-=fl"3edWZF=eL]ݱ&eQcB%eFҿ$e!;oc#e/"ed${!e e eG 6ueheW\e*Oe$xCemɪ7e0*e)eP<eJeHe4keyTevnڌec`eW歺eYLl> e@Ρ e5x_ e=* e| e pe ce2WecJe!S>eڧ1eF-t%eóe9 e*%dˡEdlFd QdgdOt]dh㈵d]id3R臭dFu:du;ʃd0[wd$jdY|^d  RdEd<.9d뤾,d~*O d հd6pdbdBd!dENdBdZӼd)zcdnfdkc섗d XrdL~dNA~6rd5ed*WYd2Ldx@dt 4d'd'*dX歺d3KdϹd;?ldܸd}KddWda>dcϞdt_dDiod]ydR{md(G`d;2Tdj0 Gd %S;d.dNt"d%d d10&dබdsdu=d@j';d^:dSH9d$H8d<+i7df16d&75d4dIC3d;2dNz1d-\n0dZa/do}U.dfI-d<,dSr/0+d#*d~P)d6 (d׆q&dx{%dp$dd##d\Y"dM(D!dBԳ d?74ed+d @d#d Lude7idW\dXPdHcCdy7do +d,dͮ{+dndLd dRmdu dj d5_% dS dwH1@ d=Еd1=ad[&|dIpddd>UWd3Kd`>d"T2dl%cducx ccH'c cHc+c{icmp"cecY.cQNcB:[{c2ycW'g(xcwcsIvc:uc~jtc|sc㊋rcqc`̖pc=~ocqncC(^emc䞮Xlc4Lkc'@jc|@3iciq0'hc fLgcZQfcLOXecCrcc8dbc0-ac!p$`cr_c |E^c֪]cVf\c [cݓZc9yYcƟlXc{%9`WcSVc1ZGUc_:Tc={.Sc "RcBwIQck, Pc`UNc&UMMcIaLch>nKc 3mJc'IcLy HcGcAFc/ ҌEcbDcqsCc؜gBc"[AcUN@c.5B?c5>c8:V)=cٓs֧c]3fc'ccAvcic9]c$PcZDcf(7cͮ{+c4 cJc@-cƽ c-LN cΈ cp}Xo cr cfdcS[ cOpcDAc79|҉c-c}cy"pcdc Xc\Kb5?b%2b@ޫV&b1bǷw b#=bİØbeI)bϹbUJbIbwakblb,ambUboJyb?=xb3kbR( __bRbFb6:b"-bx1!b.bشRb[:bsbFb?̔bR%bصb"^Fb}֤berjgbgb[vbHPsbDfb9:Zb,.Mb"[Abn4b |(b bQ+b-b7b5ӽNbCbwobObՐb[[!bᱟbgBb>x҆blsczbamb!VabJUbd?Hb46ubrhbZg|_\b[ObPCb=E7b9*b.2b!#b&Sbc b2tbbF=Ӟb%ǝbIb*Fb˼Uסblgb ab|bPmpbcbxy:Wb3mJba[>buV 1bK|%b? bY4 b(#.bb</Obډb:pΈb ‡bFbb!bRbBbE^Ӄbcwbjjb)^bʉvR~bk~E}b s69|bg,{bO\W zbPybExxb2: vb.ubt#,*tbsb 8KrbXۼqbClpbob;Onbmb~[~lb>rkbgejba_YibsLhb@gbE4fbx'ebm2db(bcbVSbbjK`b @t_b4)^bN)]b5&\b[b1AGZbמYbtLhXbWbXyVbWmUbd`Tb:TSb;pGRbܠ[;Qb}|.Pb}"Ob~ Nb`s Mbh.Kb\JbDQOIbE&Hb:pGb'/2Fb#Ebj>"Db IJCbJCBbMӀAbUdt@bg?b0a[>bO=bsmBxa.;?la/J_ap$`SaVFa ܁:aTb.a!am3a7ayTayaua a]a'aa@#Hayؘan/ia$caW;safLgaAGZa5;NaI*SAa\5a_(a-}ajaoav/aaSςPaaqa6aסax #aa,Da\tzah8ena]aa?RDUaFIa;Pa]J]2aR%a4GV~a; aw0ba%/anaZPۆaz΅aq„a>a aՑ#a!a¾Dac#w~aek}a/^|aGR{a;Fzaz9ya*oG8-xac wamXSYvaMuaA_zsaP6 ra*kqa+pa4woaLnavݰmanlakaYjaϚia rha=@fgaޭ,YfaaMea 8@da4cacD(bauʣaaiP4`aF^_aR\U]aG\a)akt=a fh6atY5aJ4az2aXuV 1aiܛ0a^b,/a;S.aGnM-a}<ݭ,a1zn+a%*aa)a |(ao'aDAc&aV%a#bJ$a(֩=#a/1"aj%!a ; a4 aNGaUaSa1{vao_asdaYk(aMaWBwIa6ُa+ja: vaja} ^aQa =Ea`8 a,^, aв aC8 a幾 aDa'0aȗPaiQa \auraMjha^aSt$`0H`V``8Jw`ڮ`{V`(`b`^I`unڌ`jj`B_zs`Sg`H[`%= N`1=B`g&5` ^)`$`K`/``.;1``qGR``Ss`T`_`$`8k`{E{`zpwn`efb`YU`]N I`B=`70`A,9$` !`Z `$ -`{`g8 `辜ٮ`D-ͭ`Jʽ`PN`ާ`-\o`ϣ`ph` v`ti`SvA]`jP`_cD`7T7`H+`y=`2`&5`\*`V`6`@wԘ`Aȗ`ǘ`#M)`ӹ`fYJ`ډ`ek}`Ip`qd`X`-|}K`p>?`oe2`Z_&`N`RC `7`,'`6!1`3ۃ`x Rς`>`s`\J`Д~`V%}`?ܵ|`bFx{`kz`#ng_y`ĘRx`ezFw`:v`v-u`Hk :!t`_s`T[r`,Ip`=$|o`n2 n`'0m`-l`R4``߇(_`| ^`"q]`e6\`dZZ`O!WY`CX`G8-xW`,V`!9U`+)T` ES`mJR`PۆQ`kzP`Q\mO`aN`hUM`4HL`կt>@`26t?`c'>`B=`%<`GN;`Fu:`Yh9`*g\8`eO7`lC6` q75`*4`P}:3`2`[1`3/`||.`vq -`f,`Z'.+`YO*`C3O)`8ߡ(`<-?p'`!&`K|%` !p$`Vc#`bBW"`bJ!`c> `Fn1`%`z`) `ʤ6`k ` W``Owx`k$ ```2U0*`I`u>9 `~k, `_ `w`a`` `E2``S`QBy_N`_Z H_f+/_ZrL_~m_q_![_cDв_-__*3h_lTO_u6__3_u_w _`__gp<_W:_쉮 ?8_.s,&6_p\M 4_En1_.ޏ/_7-_yѩ+_)_ x'_@5_%_%VF#_ŏ1w-!_y=_JbI_KU_4a_m_Sy=_^_ِf_ÜM_\4 _ _~_#h$_eQE_:f_#^, ^om^T^ <^5+-#^x7N ^Co^mO^?W[^@gҦ^)s^u^H5\^VC^΢w*^^Q^^s^]^ZF=^/^|^c^!J^d1^%^1^*=%^mIF^yUg^ba^4Lm^v5yj^Q^ 9^=- ^ڨN^ôo^խ^F̱^ң^h^ Rr^O;5Y^$W@^ x'^^Y+^7ܘ^ݲCÖ^ O^b[>^ng_y^Ws`^)AG^k*.^^^2%^tϺFˁ^g^҈}^;ީ{^~tgy^]Nw^G 6u^D0.s^Oq^&pn^ 1l^N=j^IӠh^ҧUf^aod^Wzm6Vb^cyW=`^Lx$^^6 \^`Y^W^U^'S^i>Q^_vO^]M^0DK^si+I^RG^;D^9% &B^|,G@^7h>^C<^CO}:^[d8^ǜgK6^ s 34^Lo.2^XO0^Ap-^++^U)^ӝ'^%^l#^^6S!^W:^x!^%u^h^^G^0&^.2^q>?^I`s^UZ ^8aA ^zm(^y^z^Ad&^MG]6h] ]J z]a]H] 0]S.]O]؀q]j]]S ]<,Ԛ]%8]$Di]fO7P][X7]gy]-s]o]]o]6Y]xB?]+`p]ǁW]?Ң>]%] ]]H']H¾]ui]_&]RH2w]1>^]JE]V-][a/]mP]߿yq]"ɩ]d]{ԗ]d~]+Nf]m77M] X4] y]4]w]Д]]=] @]j,am]T8T]G=D;]&P"]\ ]g]Ps']H}]մi{]y]Ytw]p[u]YBs] C*q]b,/o]Pl]qj])h]lf]Քd]{b]3&c`]uv28J^]_>Y1\]HJzZ]<2VW]~bU]nS]yQ]EׅO]@M]ʩajK] QI]N|8G]eE]NC]8@]W!'>] H<]i:]8]aq6] X4],?2](8'0]jkD0.]TPQ+]=\r)]1'h']st%]Ց#]x!]:̗`]|8G]Y.]z]CqǛ]ZӼ]C] -]L]A ]bg ]N]V&5]2]ڍ>]wJ\_`V(\IbI\2nj\&z\hn\U\ם<\/$\q0 \Q\|r\8fٓ\{O崧\8Վ\!u\A ]\9D\ Z+\,{\K8\D\ςP\l\\TUh \>tA}\'bd\K\]2\\̯\$\f(ϼ\I\qj\-[닄\pDk\-R\9\7!\y&1\2R\>s֧\@J\V\wb֋\anr\IJzZ\39A\Z(\{\R臭\صݒ\Đ\\[ \}Az\fba\"PH\e9 /\"\ !\,,}\n8){\DJy\Pkw\5\u\whhs\ltOq\U6o\>?m\(1k\Rh\sf\G仔d\ǵb\̶ֈ`\o^\PW\\r9>Z\[[%X\E| V\Z.S\'Q\3O\!>M\cJ!K\VBwI\bc^G\*nEE\lxz,C\aA\J>\34<\u):\J8\k6\<͌~4\٭e2\L0\3.\F~,\g 2*\PS'\ :!t%\O#-#\ 9!\Dׅ\Pl\X\T\h:;\ݚt["\| \am\V\?߾\() \j! \Bt\c[\1߄B\t)\\[;s [}\*[E'K[/3l[D?{[Kb[VI[ b0[Mn[z2[ҏS[yt[Vb[K[4ׂ[i[_Q[:8[[[&|[i[ [~[0h![rQ-"[:9Cq[#EdX[9 Q?[{\&[h [t[B ܺ[*ø[DŽK[ nl[KWx[@_[)F[-[T[2[S[uʣ[^['[%]3f[gF?N[/K;5[W\[.c}[pn[zю[ฌ[7[y"[yCn[bdU[@L…<[5Φ#[ ~[{[J y[*w[ Lu[ms[S!uq[-\o[h9Cm[RE*k[\;Qi[$]3f[ iTd[#tub[e`[Ɍ^[겘|\[,cZ[nKX[n;2V[W\T[5A}R[x*O[M[K[?I[#G[øDkE['eRC[H39A[t? ?[]K=[GW:[Q0c 8[o+6[{L4[m2[ZՒr0[Y.[ߧ@,[!'*[cz([c3%[LT#[*6u![m[[ y[4`[v!H[- Y o_Yb{YY獓¼Y)wYk`YI%rY2FYY2g@Yuۈ'YYY<ܴY~ IJY.Y}"OYEf.pyYO:`Y8FGY "R.YN ^YiYu6YǁW˝YWxYY܂YlgYaUNY>6Y'>Y'_YjY҈YùY1䠄YsY(&oYq4GV~Y:[@h=|Y|DL$zY-X xYduYCpsY{ qY҇.oY OmYLpvkY]iYwDgYa+eYVJcY3`Y6^YW\Y_xZY XY}VY&"dTYh.KRY}:3PYfF?NY/PR`LYq9^IY"jGY vöEY8CYzލAYǙ&l?YGS=YAh:;Y!9Ylɪ7YV4YK?2Y( 0Y..YP,YTqs*YZ(Yض(A&Y4($Y]@"YrLY[X7Y$EdXYf.pyY|YzY-aYoӟHY0Y? Y6` YyxρYaۢYJóY@4YY 'iXHPXI"i7X.Xͫ:XFXR~RXg^XPj/X:vPX[#qpX WX>X"ߥ%Xeȱ XX7X+XXnmyXV횐X?wX5)^XwEX-X(@X>4aX@XàLXXİXGsdX\pXE|'fX/HMXPi4XXꫫXԷXZаXXޏ/X yPXcbqmXKTX4 ;X*"Xl# X.X:8؛X3FYXuRzX^X~jtXuRzW^saWGĔHW1е/WHWWW9̗WQ [W|WՑ#W{/hWZd;OWMG7W6S!W! _BWc kcWvӂWۂW*Ŏơ~Wm|WpzW)WxW3jJ>vWvSk%tW<֌ rW%oW=mWkWiW2gWFSweW)t^cWˆ5EaW pA,_WOYM]WBYZW+eXWq:VWX|[TW|RWД~PWeNWbLLW4JWu!HW)_BFWkHcCW1AW?W2Ǟ=Wt ;W m9W#*T7W;/K;5W};l"3W{G 1WeS.WDN_,W7k*W w(W 2&WMSt$Wܚt["WŦB W)WWWWjWT:W`=[W&|W{W'b WiI W)1 W5"W0ACWrMdWpYWYeV9CqǛV|,}V jV*QVBK8VѬlVǺV ĮVLVvV_VI2VU2TqV uXV?V#&V^/ V;VGV%S;Vg|_\Vek}VNwxV.8_Vq!FV .V"V7ݲCVzƾdVʅʿV֦VAǘVkVT gV>+NVJ'L5VmV)V5VSAѪVMV؞YVe3V\qqTnVZ}uUVCVV'*TV46]ݱ&UFҿ$U/"U UG 6uUW\U$xCU0*UP<UHUyTUc`UYLl> U5x_ U| U cUcJUڧ1UóU*%TlFTgTh㈵T3R臭Tu;ʃT$jT  RT<.9T~*O T6pTBTENTZӼTnfT XrTNA~6rT*WYTx@T'TX歺TϹTܸTTa>Tt_T]yT(G`Tj0 GT.T%T10&TsT@j';TSH9T<+i7T&75TIC3TNz1TZa/TfI-TSr/0+T~P)T׆q&Tp$T\Y"TBԳ T+T#Te7iTXPTy7T,TnT Tu T5_% TwH1@ T1=aTIpT>UWT`>Tl%Sx SH'SHS{iSeSQNS7wS ^S FSZ/-SPSqS!ScSհSj+S*T7Sl=C8fS&OYMS[z4S3fSvrS~SS=S@SpaSZmSFCƣTS,;S"S  SO'SIطSԺ jSSX%Sv1tS_=[SIICSa2U0*SaQSmrS(xߢSkׄƠSխS臭S2|St|8cSeYJSNz1S;8؛S}!S S͋SD SASɯbS +jSM7QSkC8STO}S>[{SW'g(xSsIvS~jtS㊋rS`̖pSqnS䞮XlS'@jSiq0'hSZQfSCrcS0-aSr_S֪]S [S9yYS{%9`WS1ZGUS={.SSBwIQS`UNSIaLS 3mJSLy HSAFSbDS؜gBSUN@S5>Sٓs֧S'SAvS9]SZDSͮ{+SJSƽ SΈ Sr SS[ SDAS-c}SdS\KR%2R1R#=ReI)RUJRwakR,amRoJyR3kRRR6:Rx1!RشRRsR?̔RصR}֤RgRHPsR9:ZR"[AR |(RQ+R7RCROR[[!RgBRlsczR!VaRd?HR(/RR+Rm)RJ̳RkR4ތRvꭁRrhR[OR=E7R.2R&SR2tRF=ӞRIR˼UסR aRPmpRxy:WRa[>RK|%RY4 RRډR ‡Rb!RBRcwR)^Rk~E}Rg,{RPyR2: vRt#,*tR 8KrRClpR;OnR~[~lRgejRsLhRE4fRm2dRVSbR @t_RN)]R[RמYRWRWmUR:TSRܠ[;QR}"OR`s MR\JRE&HR'/2FRj>"DRJCBRUdt@R0a[>RsmBxQ/J_QVFQTb.Qm3QyTQuQ]QQyؘQ$cQfLgQ5;NQ\5Q-}QoQQQ6Qx #Q,DQh8enQ?RDUQ;PQՑ#Q¾DQek}QGR{Qz9yQc wQMuQP6 rQ+pQLnQnlQYjQ rhQޭ,YfQ 8@dQcD(bQiP4`QR\U]Q)Q fh6QJ4QXuV 1Q^b,/QGnM-Q1zn+Qa)Qo'QV%Q(֩=#Qj%!Q4 QUQ1{vQsdQMQ6ُQ: vQ} ^Q =EQ,^, QC8 QDQȗPQ \QMjhQSt$PVP8JwP{VPbPunڌPB_zsPH[P1=BP ^)PKPPPPTP$P{E{PefbP]N IP70P !P$ -Pg8 PD-ͭPPNP-\oPphPtiPjPP7T7Py=P&5PVP@wԘPǘPӹPډPIpPXPp>?PZ_&PRC P,'P3ۃP>P\JPV%}PbFx{P#ng_yPezFwPv-uP_sP,IpPn2 nP-lPNjP5ohPwِfPfdPMbP>4`P| ^Pe6\PO!WYPG8-xWP!9UP ESPPۆQPQ\mOPhUMPկt>@Pc'>P%9 P_ PaP PPQByOZ HOZrLOqOcDвOOlTOOOuO`O31]OIVO`$O x#O}eOPO"]O+,OmO(ȯOlO1?74eOOv3O;fO~ϚODOW:O.s,&6OEn1O7-O)O@5_%Oŏ1w-!OJbIO4aOSy=OِfO\4 O~OeQEO#NomN NWs`Nk*.NNtϺFˁN҈}N~tgyNG 6uNOqN 1lNIӠhNaodNcyW=`N6 \NWN'SN_vON0DKNRGN9% &BN7h>NCO}:NǜgK6NLo.2NAp-NU)N%N^6S!Nx!Nh^N0&Nq>?NUZ Nzm(NzNMGM MaM 0MOMjM<,ԚM$DiM[X7M-sMM6YM+`pM?Ң>M MH'MuiMRH2wMJEM[a/M߿yqMdMd~Mm77MM yMwMM @MT8TM&P"MgMH}MyMp[uM C*qMPlM)hMՔdM3&c`M_>Y1\M<2VWMnSMEׅOMʩajKMN|8GMNCMW!'>Mi:Maq6M,?2MjkD0.M=\r)Mst%Mx!M|8GMzMZӼM -MA MNM2MwJLIbIL&zLUL/$LQL8fٓL8ՎLA ]L Z+LK8LςPLTUh L'bdL]2L̯Lf(ϼLqjLpDkL9Ly&1L>s֧LVLanrL39AL{LصݒLL}AzL"PHL"L,,}LDJyL5\uLltOqL>?mLRhLG仔dL̶ֈ`LPW\L[[%XLZ.SL3OLcJ!KLbc^GLlxz,CLJ>Lu):Lk6L٭e2L3.Lg 2*L :!t%L 9!LPlLh:;L| LVL() LBtL1߄BLL;s KE'KKD?{KVIKMnKҏSKVbK4ׂK_QK[KiK~KrQ-"K#EdXK{\&KtK*øK nlK@_K-K2KuʣKK%]3fK/K;5K.c}KzюK7KyCnK@L…IjIùIsIq4GV~I|DL$zIduI{ qI OmI]iIa+eI3`IW\I XI&"dTI}:3PI/PR`LI"jGI8CIǙ&l?IAh:;Ilɪ7IK?2I..ITqs*Iض(A&I]@"I[X7If.pyIzIoӟHI? IyxρIJóIIHPH.HFHg^H:vPH WH"ߥ%HH+XHV횐H5)^H-H>4aHàLHGsdHE|'fHPi4HꫫHZаHޏ/HcbqmH4 ;Hl# H:8؛HuRzH~jtH~QBH$@H߆H ĭH|~HnHJzH@vH)qH@mH(XQiHpQeH1]aH/\H:YXHϛTHDXPHy'LHMLbGH/CHVF?H^(`;H_vj.7Hh2Hi;.H 0*Hrrg&H5"H{HX9H*5{H LnHd< H|A HtHGŧHvG%IDGG. Gc#G76;R}GSKG@jGŭGIZGRGS%RG !G\bGGeo)狽GAA)ZGnYk(GpGxĬG1G^saG1е/GG9̗G|G{/hGMG7G! _BGvӂG*Ŏơ~GpzG3jJ>vG<֌ rG=mGiGFSweGˆ5EaGOYM]G+eXGX|[TGД~PGbLLGu!HGkHcCG?Gt ;G#*T7G};l"3GeS.G7k*G 2&Gܚt["G)GGT:G&|G'b G)1 G0ACGpYG9CqǛF jFBK8FǺFLF_FU2TqF?F^/ FGFg|_\FNwxFq!FF"FzƾdF֦FkF>+NFmF5FMFe3FZ}uUF#-#FF-;F}F6w\FI +F?$DF;~FHSȕzF͓k dvFQfL2rF8nF[ iFeFdTkaF9]FmUYF'*TFvA]PFYrLFq@HFr#DFDe?F ;Fy7F+H3Fn/F a*F30&F)H4"F_vOF2wF}F]ݱ&E/"EG 6uE$xCEP<EyTEYLl> E| EcJEóElFDh㈵Du;ʃD  RD~*O DBDZӼD XrD*WYD'DϹDDt_D(G`D.D10&DHh˹D:`DcxgDD6.6DpDMۿҤDѭDV6oDRy=D_% D6ُDhN?DfvDro~DDAD{GzDʼnvD}rD LnD^ PjD1%eD=ԶaDT]DlXSYD${!UDMPD. LD`HD7ZDD(@D@j';D<+i7DIC3DZa/DSr/0+D׆q&D\Y"D+De7iDy7DnDu DwH1@ DIpD`>Dx CHCeC7wC FCPC!CհC*T7C&OYMC3fC~C=CpaCFCƣTC"CO'CԺ jCX%C_=[Ca2U0*CmrCkׄƠC臭Ct|8cCNz1C}!C͋CAC +jCkC8C>[{CsIvC㊋rCqnC'@jCZQfC0-aC֪]C9yYC1ZGUCBwIQCIaLCLy HCbDCUN@Cٓ"DBUdt@BsmBA¾DAGR{Ac wAP6 rALnAYjAޭ,YfAcD(bAR\U]Al%tYAْUAuʣaQA]/MA~oӟHABDA$@A fhV@{V@unڌ@H[@ ^)@@@$@efb@70@$ -@D-ͭ@-\o@ti@7T7@&5@@wԘ@ӹ@Ip@p>?@RC @3ۃ@\J@bFx{@ezFw@_s@n2 n@Nj@wِf@Mb@| ^@O!WY@!9U@PۆQ@hUM@_#I@kD@!>@@%<@*g\8@*4@3/@Z'.+@<-?p'@Vc#@Fn1@ʤ6@Owx@I@Xj@>9 @a@@Z H?q???`?IV? x#?P?+,?(ȯ?1?74e?;f?D <>mO>u>>]>!J>*=%>4Lm>=- >F̱>O;5Y>Y+>b[>>k*.>tϺFˁ>~tgy>Oq>IӠh>cyW=`>W>_vO>RG>7h>>ǜgK6>Ap->%>x!>0&>UZ >z> = 0=j=$Di=-s=6Y=?Ң>=H'=RH2w=[a/=d=m77M=w= @=&P"=H}=p[u=Pl=Քd=_>Y1\=nS=ʩajK=NC=i:=,?2==\r)=x!=z= -=N=wJ<&z9ù9q4GV~9du9 Om9a+e9W\9&"dT9/PR`L98C9Ah:;9K?29Tqs*9]@"9f.py9oӟH9yxρ99.8g^8 W88V횐8-8àL8E|'f8ꫫ8ޏ/84 ;8:8؛8~jt8$@8 ĭ8nHJz8)q8(XQi81]a8:YX8DXP8MLbG8VF?8_vj.78i;.8rrg&8{8*5{8d< 8t8v77c#7SK7ŭ7R7 !77AA)Z7p7171е/79̗7{/h7! _B7*Ŏơ~73jJ>v7=m7FSwe7OYM]7X|[T7bLL7kHcC7t ;7};l"377k*7ܚt["77&|7)1 7pY7 j6Ǻ6_6?6G6Nwx6"6֦6>+N656e36#-#6-;66w\6?$D6HSȕz6QfL2r6[ i6dTka6mUY6vA]P6q@H6De?6y76n/630&6_vO6}6"~ 6%6l5N ^5}5[5ݗ35 5 K?03ۃ0bFx{0_s0Nj0Mb0O!WY0PۆQ0_#I0!>@0*g\803/0<-?p'0Fn10Owx0Xj0a0Z H//`/ x#/+,/1?74e/DY1\-ʩajK-i:-=\r)-z-N-&z,8fٓ,K8,]2,pDk,V,صݒ,",ltOq,̶ֈ`,3O,J>,3.,Pl,() ,;s +Mn+_Q+rQ-"+*ø+2+/K;5+yCn+ Lu+ iTd+W\T+'eRC+m2+*6u!+=E~+Oʤ6+bo*t^c*Ÿ*!*)q4GV~) Om)W\)/PR`L)Ah:;)Tqs*)f.py)yxρ).( W(V횐(àL(ꫫ(4 ;(~jt( ĭ()q(1]a(DXP(VF?(i;.({(d< (v'c#'ŭ' !'AA)Z'1'9̗'! _B'3jJ>v'FSwe'X|[T'kHcC'};l"3'ܚt["'&|'pY'Ǻ&?&Nwx&֦&5&#-#&6w\&HSȕz&[ i&mUY&q@H&y7&30&&}&%&N ^%[% %k$ %&:,B%8*5{%JΉ=%]E~%obHN&n%V_]%_L%@fg;%o +%$xC%| %h㈵$B$'$(G`$:`$MۿҤ$_% $ro~D$}r$=Զa$MP$(@$Za/$+$u $x # F#*T7#=#O'#a2U0*#t|8c#A#sIv#ZQf#1ZGU#bD#8j3#Os"#ͮ{+#d#,am"?̔"Q+"d?H"vꭁ"I""g,{"gej"מY"E&H"8" I'"$D"/n"A !Tb.!fLg!x #!+ٱ!*3!t>@ 3/ Fn1 Xj Z H`+,D<iUMu^SEn1ِfmO!JF̱k*.IӠhRG%z$DiH'm77MH}_>Y1\i:z&zK8pDkصݒltOq3O3.() MnrQ-"2yCn iTd'eRC*6u!Oʤ6t^c!ฌy]pX-C6RTvk W9.'> Om/PR`LTqs*yxρ WàL4 ; ĭ1]aVF?{vŭAA)Z9̗3jJ>vX|[T};l"3&|ǺNwx56w\[ iq@H30&%[k$ 8*5{]E~V_]@fg;$xCh㈵':`_% }rMPZa/u  F=a2U0*AZQfbDOs"d?̔d?HIg,{מY8$DA fLg+ٱt>@Fn1Z H+,iUMuEn1mOF̱IӠh%$Di m77M _>Y1\ z K8 صݒ 3O () rQ-" yCn 'eRC Oʤ6 ! y -C6 vk . Om Tqs* W4 ;1]a{ŭ9̗X|[T&|Nwx6w\q@H%k$ ]E~@fg;h㈵:`}rZa/ Fa2U0*ZQfOs"?̔IמY$DfLgt>@Z HiUMumOIӠh$Di_>Y1\K83OrQ-"'eRC!-C6.Tqs*4 ;{9̗&|6w\%]E~h㈵}r FZQf?̔מYfLg]/M!>@iUMuﾐIӠh_>Y1\3O'eRC-C6Tqs*{辢&|%h㈵ F?̔fLgᾍiUMu߾_>Y1\ݾ'eRC۾Tqs*پ&|׾h㈵Ծ?̔Ҿо_>Y1\;Tqs*ɾh㈵ľTqs*ưƠ@Ơ>ư>Tqs*>>h㈵>Tqs*>_>Y1\>>?̔>h㈵>&|>Tqs*>'eRC>_>Y1\>iUMu>>fLg>?̔> F>h㈵>%>&|>{>Tqs*>-C6>'eRC>3O>_>Y1\>IӠh>iUMu>!>@>>]/M>fLg>מY>?̔>ZQf> F>}r>h㈵>]E~>%>6w\>&|>9̗>{>4 ;>Tqs*>.>-C6>!>'eRC>rQ-">3O>K8>_>Y1\>$Di>IӠh>mO>iUMu>Z H>!>@?3ۃ??C8 ?]/M?t>Y1\ ?m77M ?$Di ?%?IӠh?F̱?mO?En1?iUMu?+,?Z H?Fn1?!>@?Mb?3ۃ?ti??hY?C8 ?1zn+?]/M?Ln?t>v?9̗?AA)Z?ŭ?v?{?VF??1]a? ĭ?4 ;?àL? W?yxρ?Tqs*?/PR`L? Om?'>?.?W9?vk ?RT?-C6?]pX?y?ฌ?!?t^c?Oʤ6?*6u!?'eRC? iTd?yCn?2?rQ-"?Mn?() ?3.?3O?ltOq?صݒ?pDk?K8?&z?z?i:?_>Y1\?H}?m77M?H'?$Di?z?%?RG?IӠh?k*.?F̱?!J?mO?ِf?En1?^S?iUMu?D<?+,?`?Z H?Xj ?Fn1 ?3/ ?!>@ ?PۆQ ?Mb ?_s ?3ۃ ?ӹ ?ti ?70 ? ?{V ?hY ?VL ?C8 !?1{v!?1zn+!? fhv'?! _B'?9̗'?1'?AA)Z'? !'?ŭ'?c#'?v'?d< (?{(?i;.(?VF?(?DXP(?1]a(?)q(? ĭ(?~jt(?4 ;(?ꫫ(?àL(?V횐(? W(?.(?yxρ)?f.py)?Tqs*)?Ah:;)?/PR`L)?W\)? Om)?q4GV~)?'>)?u6)?.)?I%r)?W9)?)?vk )?d!:*?RT*??{&*?-C6*?G*?]pX*?d7i*?y*??Ŋ*?ฌ*?,?3O,?̶ֈ`,?ltOq,?",?صݒ,?V,?pDk,?]2,?K8,?8fٓ,?&z,?N-?z-?=\r)-?i:-?ʩajK-?_>Y1\-?Pl-?H}-? @-?m77M-?[a/-?H'-?6Y-?$Di-? 0-?z.?0&.?%.?ǜgK6.?RG.?W.?IӠh.?~tgy.?k*..?Y+.?F̱.?4Lm.?!J.?.?mO.?#.?ِf/?ŏ1w-!/?En1/?rfB/?^S/?{gUId/?iUMu/?VDׅ/?D@0?_#I0?PۆQ0?O!WY0?Mb0?Nj0?_s0?bFx{0?3ۃ0?p>?0?ӹ0?&50?ti0?D-ͭ0?700?$0?0?H[0?{V0?r&"0?hY0?_ 0?VL0?Mjh1?C8 1?: v1?1{v1?(֩=#1?1zn+1?J41? fh<1?BD1?]/M1?ْU1?R\U]1?ޭ,Yf1?Ln1?c w1?¾D1?n1?t>+N6?֦6?"6?Nwx6?G6??6?_6?Ǻ6? j6?pY7?)1 7?&|7?7?ܚt["7?7k*7?};l"37?t ;7?kHcC7?bLL7?X|[T7?OYM]7?FSwe7?=m7?3jJ>v7?*Ŏơ~7?! _B7?{/h7?9̗7?1е/7?17?p7?AA)Z7?7? !7?R7?ŭ7?SK7?c#7?7?v7?t8?d< 8?*5{8?{8?rrg&8?i;.8?_vj.78?VF?8?MLbG8?DXP8?:YX8?1]a8?(XQi8?)q8?nHJz8? ĭ8?$@8?~jt8?:8؛8?4 ;8?ޏ/8?ꫫ8?E|'f8?àL8?-8?V횐8?8? W8?g^8?.8?9?yxρ9?oӟH9?f.py9?]@"9?Tqs*9?K?29?Ah:;9?8C9?/PR`L9?&"dT9?W\9?a+e9? Om9?du9?q4GV~9?ù9?'>9?܂9?u69?8FG9?.9?9?I%r9?9?W99?Z(9?9?ɐc9?vk 9?mi*9?d!::?[| :?RT:?H2w:??{&:?6Ko.:?-C6:?#fF?:?G:?T^ P:?]pX:? .V`:?d7i:?Mq:?y:?uoEb:??Ŋ:?+=):?ฌ:?4:?Y1\=?Քd=?Pl=?p[u=?H}=?&P"=? @=?w=?m77M=?d=?[a/=?RH2w=?H'=??Ң>=?6Y=?-s=?$Di=?j=? 0=? =?z>?UZ >?0&>?x!>?%>?Ap->?ǜgK6>?7h>>?RG>?_vO>?W>?cyW=`>?IӠh>?Oq>?~tgy>?tϺFˁ>?k*.>?b[>>?Y+>?O;5Y>?F̱>?=- >?4Lm>?*=%>?!J>?]>?>?u>?mO>? <>?#>?~??ِf??4a??ŏ1w-!??)??En1??W:??rfB??VCK??^S?? [??{gUId??r„Ѭl??iUMu??`x%s}??VDׅ??M.:??D9 @?Xj@?I@?Owx@?ʤ6@?Fn1@?Vc#@?<-?p'@?Z'.+@?3/@?*4@?*g\8@?%<@?!>@@?kD@?_#I@?hUM@?PۆQ@?!9U@?O!WY@?| ^@?Mb@?wِf@?Nj@?n2 n@?_s@?ezFw@?bFx{@?\J@?3ۃ@?RC @?p>?@?Ip@?ӹ@?@wԘ@?&5@?7T7@?ti@?-\o@?D-ͭ@?$ -@?70@?efb@?$@?@?@? ^)@?H[@?unڌ@?{V@?>V@?r&"@?+S@?hY@?M@?_ @?@?VL@?A?nA?4GV~A?t>"DB?E&HB?`s MB?ܠ[;QB?WmUB?מYB?N)]B?VSbB?E4fB?gejB?;OnB? 8KrB?2: vB?g,{B?)^B?BB? ‡B?B?K|%B?xy:WB? aB?IB?2tB?.2B?[OB?vꭁB?kB?m)B?B?d?HB?lsczB?[[!B?CB?Q+B?"[AB?HPsB?}֤B??̔B?شRB?6:B?3kB?,amB?UJB?#=B?%2B?dC?DAC?r C?ƽ C?ͮ{+C?9]C?'C?zUgC?Os"C?p71$'C?U+C?g /C?8j3C?^f(7C?ٓ[{C?kC8C? +jC?AC?͋C?}!C?Nz1C?t|8cC?臭C?kׄƠC?mrC?a2U0*C?_=[C?X%C?Ժ jC?O'C?"C?FCƣTC?paC?=C?~C?3fC?&OYMC?*T7C?հC?!C?PC? FC?7wC?eC?HC?x C?`>D?IpD?wH1@ D?u D?nD?y7D?e7iD?+D?\Y"D?׆q&D?Sr/0+D?Za/D?IC3D?<+i7D?@j';D?(@D?7ZDD?`HD?. LD?MPD?${!UD?lXSYD?T]D?=ԶaD?1%eD?^ PjD? LnD?}rD?ʼnvD?{GzD?AD?ro~DD?fvD?hN?D?6ُD?_% D?Ry=D?V6oD?ѭD?MۿҤD?pD?D6.6D?cxgD?:`D?Hh˹D?10&D?.D?(G`D?t_D?D?ϹD?'D?*WYD? XrD?ZӼD?BD?~*O D?  RD?u;ʃD?h㈵D?lFD?óE?cJE?| E?YLl> E?yTE?P<E?$xCE?G 6uE?/"E?>]ݱ&E?o +E?5-+NF?kF?֦F?zƾdF?"F?q!FF?NwxF?g|_\F?GF?^/ F??F?U2TqF?_F?LF?ǺF?BK8F? jF?9CqǛF?pYG?0ACG?)1 G?'b G?&|G?T:G?G?)G?ܚt["G? 2&G?7k*G?eS.G?};l"3G?#*T7G?t ;G??G?kHcCG?u!HG?bLLG?Д~PG?X|[TG?+eXG?OYM]G?ˆ5EaG?FSweG?iG?=mG?<֌ rG?3jJ>vG?pzG?*Ŏơ~G?vӂG?! _BG?MG7G?{/hG?|G?9̗G?G?1е/G?^saG?1G?xĬG?pG?nYk(G?AA)ZG?eo)狽G?G?\bG? !G?S%RG?RG?IZG?ŭG?@jG?SKG?76;R}G?c#G?. G?G?%IDG?vG?GŧH?tH?|A H?d< H? LnH?*5{H?X9H?{H?5"H?rrg&H? 0*H?i;.H?h2H?_vj.7H?^(`;H?VF?H?/CH?MLbGH?y'LH?DXPH?ϛTH?:YXH?/\H?1]aH?pQeH?(XQiH?@mH?)qH?@vH?nHJzH?|~H? ĭH?߆H?$@H?~QBH?~jtH?uRzH?:8؛H?l# H?4 ;H?cbqmH?ޏ/H?ZаH?ꫫH?Pi4H?E|'fH?GsdH?àLH?>4aH?-H?5)^H?V횐H?+XH?H?"ߥ%H? WH?:vPH?g^H?FH?.H?HPH?I?JóI?yxρI?? I?oӟHI?zI?f.pyI?[X7I?]@"I?ض(A&I?Tqs*I?..I?K?2I?lɪ7I?Ah:;I?Ǚ&l?I?8CI?"jGI?/PR`LI?}:3PI?&"dTI? XI?W\I?3`I?a+eI?]iI? OmI?{ qI?duI?|DL$zI?q4GV~I?sI?ùI?jI?'>I?aUNI?܂I?WxI?u6I?N ^I?8FGI?Ef.pyI?.I?<ܴI?I?2g@I?I%rI?)wI?I? o_I?W9I?-@jI?Z(I?WI?I?1I?ɐcI?=NI?vk I?I?mi*I?QF\J?d!:J?N"¿J?[| J?֩=#J?RTJ?ùJ?H2wJ?_5!J??{&J?cM*J?6Ko.J?4-2J?-C6J?p;J?#fF?J?$xCJ?GJ?&KJ?T^ PJ?u?TJ?]pXJ?E\J? .V`J?z7eJ?d7iJ?qimJ?MqJ?g uJ?yJ?^H0~J?uoEbJ?UWJ??ŊJ?L'J?+=)J?CYZJ?ฌJ?9vJ?4J?0!J?L?lxz,CL?bc^GL?cJ!KL?3OL?Z.SL?[[%XL?PW\L?̶ֈ`L?G仔dL?RhL?>?mL?ltOqL?5\uL?DJyL?,,}L?"L?"PHL?}AzL?L?صݒL?{L?39AL?anrL?VL?>s֧L?y&1L?9L?pDkL?qjL?f(ϼL?̯L?]2L?'bdL?TUh L?ςPL?K8L? Z+L?A ]L?8ՎL?8fٓL?QL?/$L?UL?&zL?IbIL?wJL?2M?NM?A M? -M?ZӼM?zM?|8GM?x!M?st%M?=\r)M?jkD0.M?,?2M?aq6M?i:M?W!'>M?NCM?N|8GM?ʩajKM?EׅOM?nSM?<2VWM?_>Y1\M?3&c`M?ՔdM?)hM?PlM? C*qM?p[uM?yM?H}M?gM?&P"M?T8TM? @M?M?wM? yM?m77MM?d~M?dM?߿yqM?[a/M?JEM?RH2wM?uiM?H'M? M??Ң>M?+`pM?6YM?M?-sM?[X7M?$DiM?<,ԚM?jM?OM? 0M?aM? M?MGM?zN?zm(N?UZ N?q>?N?0&N?h^N?x!N?^6S!N?%N?U)N?Ap-N?Lo.2N?ǜgK6N?CO}:N?7h>N?9% &BN?RGN?0DKN?_vON?'SN?WN?6 \N?cyW=`N?aodN?IӠhN? 1lN?OqN?G 6uN?~tgyN?҈}N?tϺFˁN?N?k*.N?Ws`N?b[>N?ݲCÖN?Y+N? x'N?O;5YN?hN?F̱N?ôoN?=- N?QN?4LmN?yUgN?*=%N?%N?!JN?/^|N?]N?N?N?VCN?uN?@gҦN?mON?x7N N? O?rfBO?)[$FO?VCKO?+POO?^SO? WO? [O?:̗`O?{gUIdO?{hO?r„ѬlO?lpO?iUMuO?J= ByO?`x%s}O?ۥ O?VDׅO? O?M.:O?[~lO?D9 P?R P?XjP?3ۃP?IP?`P?OwxP? WP?ʤ6P?zP?Fn1P?bJ!P?Vc#P?K|%P?<-?p'P?C3O)P?Z'.+P?vq -P?3/P?2P?*4P?lC6P?*g\8P?Fu:P?%P?!>@P?TBP?kDP?Z GP?_#IP?կt>4`P?MbP?fdP?wِfP?5ohP?NjP?-lP?n2 nP?,IpP?_sP?v-uP?ezFwP?#ng_yP?bFx{P?V%}P?\JP?>P?3ۃP?,'P?RC P?Z_&P?p>?P?XP?IpP?ډP?ӹP?ǘP?@wԘP?VP?&5P?y=P?7T7P?jPP?tiP?phP?-\oP?PNP?D-ͭP?g8 P?$ -P? !P?70P?]N IP?efbP?{E{P?$P?TP?P?P?P?KP? ^)P?1=BP?H[P?B_zsP?unڌP?bP?{VP?8JwP?>VP?25 P?r&"P?/:P?+SP?BlP?hYP?&pnP?MP?,P?_ P?˻P?P?3P?VLP?&feP?6Q?268Q?N&O:Q? fhQ?$@Q?E+BQ?BDQ?XFQ?~oӟHQ?<~KQ?]/MQ?Q?z΅Q?nQ?w0bQ?4GV~Q?]J]2Q?t>xQ?J]2Q?t&mQ?ƊLQ?+Q?A Q? Q?&Q?zަ?Q?8ӅXQ?)dqQ?@CR?qW"R?/nR?섗R? R?h R?%s}R?g\8R?[;QR?_ PjR?$DR?:8؛R?Q,R?Uh R?uR?ѕT R?2#R?L1%R? I'R?b)R?ͮ{+R?C-R?5l/R?KK1R?|b*3R?:y 5R?8R?y):R?smBR?Udt@R?JCBR?j>"DR?'/2FR?E&HR?\JR?`s MR?}"OR?ܠ[;QR?:TSR?WmUR?WR?מYR?[R?N)]R? @t_R?VSbR?m2dR?E4fR?sLhR?gejR?~[~lR?;OnR?ClpR? 8KrR?t#,*tR?2: vR?PyR?g,{R?k~E}R?)^R?cwR?BR?b!R? ‡R?ډR?R?Y4 R?K|%R?a[>R?xy:WR?PmpR? aR?˼UסR?IR?F=ӞR?2tR?&SR?.2R?=E7R?[OR?rhR?vꭁR?4ތR?kR?J̳R?m)R?+R?R?(/R?d?HR?!VaR?lsczR?gBR?[[!R?OR?CR?7R?Q+R? |(R?"[AR?9:ZR?HPsR?gR?}֤R?صR??̔R?sR?شRR?x1!R?6:R?RR?3kR?oJyR?,amR?wakR?UJR?eI)R?#=R?1R?%2R?\KR?dS?-c}S?DAS?S[ S?r S?Έ S?ƽ S?JS?ͮ{+S?ZDS?9]S?AvS?'S?>s֧S?zUgS?7l[ S?Os"S?CR %S?p71$'S?.+=)S?U+S?n-S?g /S?%"1S?8j3S?OI5S?^f(7S?}:S?ٓS?UN@S?؜gBS?bDS?AFS?Ly HS? 3mJS?IaLS?`UNS?BwIQS?={.SS?1ZGUS?{%9`WS?9yYS? [S?֪]S?r_S?0-aS?CrcS?ZQfS?iq0'hS?'@jS?䞮XlS?qnS?`̖pS?㊋rS?~jtS?sIvS?W'g(xS?>[{S?TO}S?kC8S?M7QS? +jS?ɯbS?AS?D S?͋S? S?}!S?;8؛S?Nz1S?eYJS?t|8cS?2|S?臭S?խS?kׄƠS?(xߢS?mrS?aQS?a2U0*S?IICS?_=[S?v1tS?X%S?S?Ժ jS?IطS?O'S?  S?"S?,;S?FCƣTS?ZmS?paS?@S?=S?S?~S?vrS?3fS?[z4S?&OYMS?l=C8fS?*T7S?j+S?հS?cS?!S?qS?PS?Z/-S? FS? ^S?7wS?QNS?eS?{iS?HS?H'S?x S?l%S?`>T?>UWT?IpT?1=aT?wH1@ T?5_% T?u T? T?nT?,T?y7T?XPT?e7iT?#T?+T?BԳ T?\Y"T?p$T?׆q&T?~P)T?Sr/0+T?fI-T?Za/T?Nz1T?IC3T?&75T?<+i7T?SH9T?@j';T?>T?(@T?yABT?7ZDT?ׁsFT?`HT?p ?JT?. LT?6NT?MPT?gdST?${!UT?xy:WT?lXSYT?]`7l[T?T]T?H_T?=ԶaT?T1cT?1%eT?GqhT?^ PjT?Ku/3lT? LnT?ƢdpT?}rT?BѪtT?ʼnvT?hxT?{GzT?9+&|T?AT?X+T?ro~DT?/r]T?fvT?Z`T?hN?T?&BT?6ُT?+T?_% T?<$T?Ry=T?iWVT?V6oT?T?ѭT?ӹT?MۿҤT? T?pT?OT?D6.6T?M OT?cxgT?}zlˀT?:`T?TT?Hh˹T?sT?T?ܸT?ϹT?X歺T?'T?x@T?*WYT?NA~6rT? XrT?nfT?ZӼT?ENT?BT?6pT?~*O T?<.9T?  RT?$jT?u;ʃT?3R臭T?h㈵T?gT?lFT?*%T?óU?ڧ1U?cJU? cU?| U?5x_ U?YLl> U?c`U?yTU?HU?P<U?0*U?$xCU?W\U?G 6uU? U?/"U?Fҿ$U?>]ݱ&U?sѐ(U?o +U?wN#-U?5-VV?mUYV?+l [V?9]V?uR_V?dTkaV?"3cV?eV?gV?[ iV?"kV?8nV?OmpV?QfL2rV?}w+KtV?͓k dvV?_|xV?HSȕzV?G|V?;~V?0eV??$DV?2#V?I +V?x`CV?6w\V?uV?}V?o\V?-;V?ٕV?V?f V?#-#V?C+NV?T gV?kV?AǘV?֦V?ʅʿV?zƾdV?7ݲCV?"V? .V?q!FV?.8_V?NwxV?ek}V?g|_\V?%S;V?GV?;V?^/ V?#&V??V? uXV?U2TqV?I2V?_V?vV?LV? ĮV?ǺV?ѬlV?BK8V?*QV? jV?|,}V?9CqǛV?YeV?pYW?rMdW?0ACW?5"W?)1 W?iI W?'b W?{W?&|W?`=[W?T:W?jW?W?WW?)W?ŦB W?ܚt["W?MSt$W? 2&W? w(W?7k*W?DN_,W?eS.W?{G 1W?};l"3W?;/K;5W?#*T7W? m9W?t ;W?2Ǟ=W??W?1AW?kHcCW?)_BFW?u!HW?4JW?bLLW?eNW?Д~PW?|RW?X|[TW?q:VW?+eXW?BYZW?OYM]W? pA,_W?ˆ5EaW?)t^cW?FSweW?2gW?iW?kW?=mW?%oW?<֌ rW?vSk%tW?3jJ>vW?)WxW?pzW?m|W?*Ŏơ~W?ۂW?vӂW?c kcW?! _BW?6S!W?MG7W?Zd;OW?{/hW?Ց#W?|W?Q [W?9̗W?W?W?HW?1е/W?GĔHW?^saW?>uRzW?1W?W?xĬW?5|ݮW?pW?dW?nYk(W?,+MJAW?AA)ZW?X5sW?eo)狽W?#ƤW?W?W?\bW?AW? !W?9W?S%RW?4aX?(@X?-X?wEX?5)^X??wX?V횐X?nmyX?+XX?7X?X?eȱ X?"ߥ%X?>X? WX?[#qpX?:vPX?Pj/X?g^X?R~RX?FX?ͫ:X?.X?I"i7X?HPX? 'iX?Y?@4Y?JóY?aۢY?yxρY?6` Y?? Y?0Y?oӟHY?-aY?zY?|Y?f.pyY?$EdXY?[X7Y?rLY?]@"Y?4($Y?ض(A&Y?Z(Y?Tqs*Y?P,Y?..Y?( 0Y?K?2Y?V4Y?lɪ7Y?!9Y?Ah:;Y?GS=Y?Ǚ&l?Y?zލAY?8CY? vöEY?"jGY?q9^IY?/PR`LY?fF?NY?}:3PY?h.KRY?&"dTY?}VY? XY?_xZY?W\Y?6^Y?3`Y?VJcY?a+eY?wDgY?]iY?LpvkY? OmY?҇.oY?{ qY?CpsY?duY?-X xY?|DL$zY?:[@h=|Y?q4GV~Y?(&oY?sY?1䠄Y?ùY?҈Y?jY?'_Y?'>Y?>6Y?aUNY?lgY?܂Y?Y?WxY?ǁW˝Y?u6Y?iY?N ^Y? "R.Y?8FGY?O:`Y?Ef.pyY?}"OY?.Y?~ IJY?<ܴY?Y?Y?uۈ'Y?2g@Y?2FYY?I%rY?k`Y?)wY?獓¼Y?Y?b{Y? o_Y?c> Y?W9Y?YLQY?-@jY?C4Y?Z(Y?PqxY?WY?˞6Y?Y?GY?1Y?ԱJY?ɐcY?='o|Y?=NY?T-Y?vk Y?4Y?Y?uY?mi*Y?+]gCY?QF\Z? F%uZ?d!:Z?"8.Z?N"¿Z?e Z?[| Z?^ Z?֩=#Z?<Z?RTZ?mZ?ùZ?Z?H2wZ?IVZ?_5!Z?v$Z??{&Z?o4(Z?cM*Z?xWf,Z?6Ko.Z??N0Z?4-2Z?o,( 4Z?-C6Z?Y8Z?p;Z?f-=Z?#fF?Z?E_AZ?$xCZ?]EZ?GZ?IZ?&KZ?S=MZ?T^ PZ?j=&RZ?u?TZ?JiWVZ?]pXZ?QZZ?E\Z?A9w^Z? .V`Z? "5bZ?z7eZ?8N gZ?d7iZ?{PkZ?qimZ?.noZ?MqZ?,sZ?g uZ?%wZ?yZ?1|Z?^H0~Z?_{fIZ?uoEbZ?c${Z?UWZ?K⬈Z??ŊZ?3ތZ?L'Z? ^Z?+=)Z?BBZ?CYZZ?psZ?ฌZ?|ԗZ?9vZ?ʼUסZ?4Z?r Z?0!Z?%:Z?\?aA\?lxz,C\?*nEE\?bc^G\?VBwI\?cJ!K\?!>M\?3O\?'Q\?Z.S\?E| V\?[[%X\?r9>Z\?PW\\?o^\?̶ֈ`\?ǵb\?G仔d\?sf\?Rh\?(1k\?>?m\?U6o\?ltOq\?whhs\?5\u\?Pkw\?DJy\?n8){\?,,}\? !\?"\?e9 /\?"PH\?fba\?}Az\?[ \?\?Đ\?صݒ\?R臭\?{\?Z(\?39A\?IJzZ\?anr\?wb֋\?V\?@J\?>s֧\?2R\?y&1\?7!\?9\?-R\?pDk\?-[닄\?qj\?I\?f(ϼ\?$\?̯\?\?]2\?K\?'bd\?>tA}\?TUh \?l\\?ςP\?D\?K8\?,{\? Z+\?9D\?A ]\?!u\?8Վ\?{O崧\?8fٓ\?|r\?Q\?q0 \?/$\?ם<\?U\?hn\?&z\?2nj\?IbI\?_`V(\?wJ\?ڍ>]?2]?V&5]?N]?bg ]?A ]?L]? -]?C]?ZӼ]?CqǛ]?z]?Y.]?|8G]?:̗`]?x!]?Ց#]?st%]?1'h']?=\r)]?TPQ+]?jkD0.]?(8'0]?,?2]? X4]?aq6]?8]?i:]? H<]?W!'>]?8@]?NC]?eE]?N|8G]? QI]?ʩajK]?@M]?EׅO]?yQ]?nS]?~bU]?<2VW]?HJzZ]?_>Y1\]?uv28J^]?3&c`]?{b]?Քd]?lf]?)h]?qj]?Pl]?b,/o]? C*q]?YBs]?p[u]?Ytw]?y]?մi{]?H}]?Ps']?g]?\ ]?&P"]?G=D;]?T8T]?j,am]? @]?=]?]?Д]?w]?4]? y]? X4]?m77M]?+Nf]?d~]?{ԗ]?d]?"ɩ]?߿yq]?mP]?[a/]?V-]?JE]?1>^]?RH2w]?_&]?ui]?H¾]?H']?]? ]?%]??Ң>]?ǁW]?+`p]?xB?]?6Y]?o]?]?o]?-s]?gy]?[X7]?fO7P]?$Di]?%8]?<,Ԛ]?]S ]?j]?؀q]?O]?S.]? 0]?H]?a]?J z]? ]?6h]?MG]?Ad&^?z^?y^?zm(^?8aA ^?UZ ^?I`s^?q>?^?.2^?0&^?G^?h^^?%u^?x!^?W:^?^6S!^?l#^?%^?ӝ'^?U)^?++^?Ap-^?XO0^?Lo.2^? s 34^?ǜgK6^?[d8^?CO}:^?C<^?7h>^?|,G@^?9% &B^?;D^?RG^?si+I^?0DK^?]M^?_vO^?i>Q^?'S^?U^?W^?`Y^?6 \^?Lx$^^?cyW=`^?Wzm6Vb^?aod^?ҧUf^?IӠh^?N=j^? 1l^?&pn^?Oq^?D0.s^?G 6u^?]Nw^?~tgy^?;ީ{^?҈}^?g^?tϺFˁ^?2%^?^?^?k*.^?)AG^?Ws`^?ng_y^?b[>^? O^?ݲCÖ^?7ܘ^?Y+^?^? x'^?$W@^?O;5Y^? Rr^?h^?ң^?F̱^?խ^?ôo^?ڨN^?=- ^? 9^?Q^?v5yj^?4Lm^?ba^?yUg^?mIF^?*=%^?1^?%^?d1^?!J^?c^?/^|^?ZF=^?]^?s^?^?Q^?^?΢w*^?VC^?H5\^?u^?)s^?@gҦ^??W[^?mO^?Co^?x7N ^?5+-#^? <^?T^?om^?, ^?#^?:f_?eQE_?#h$_?~_? _?\4 _?ÜM_?ِf_?^_?Sy=_?m_?4a_?KU_?JbI_?y=_?ŏ1w-!_?%VF#_?@5_%_? x'_?)_?yѩ+_?7-_?.ޏ/_?En1_?p\M 4_?.s,&6_?쉮 ?8_?W:_?gp<_?%Ί>_?~@_?rfB_?^gED_?)[$F_??OI_?VCK_?Um77M_?+PO_?КiQ_?^S_?K=U_? W_?Y_? [_?B#ظ]_?:̗`_?Pv0b_?{gUId_?9~4bf_?{h_?j_?r„Ѭl_?0xn_?lp_?anr_?iUMu_?&4I,)w_?J= By_?a1Z{_?`x%s}_?_?ۥ _?f_?VDׅ_?#_? _?!_?M.:_? ES_?[~l_?r]_?D<_?_?~Ϛ_?}r_?;f_?Z_?Ov3_?t(CUL_?1?74e_?U+~_?l_?kѯ_?(ȯ_?_?m_?aL_?+,_? E_?"]_?X9v_?P_?f_?}e_?OD_? x#_?l _?`$_?FT=_?IV_?=~o_?31]_?9 `?<_E `?R `?T^ `?Xj`?'Hlw`?3ۃ`?u> `?bJ!`?bBW"`?Vc#`? !p$`?K|%`?!&`?<-?p'`?8ߡ(`?C3O)`?YO*`?Z'.+`?f,`?vq -`?||.`?3/`?[1`?2`?P}:3`?*4`? q75`?lC6`?eO7`?*g\8`?Yh9`?Fu:`?GN;`?%<`?B=`?c'>`?26t?`?!>@`?I*SA`?TB`?=`2C`?kD`?vE`?Z G`?H`?_#I`?v/J`?կt>4``?wcAa`?Mb`?[kBZc`?fd`?_!se`?wِf`?Sg`?5oh`?Gߤi`?Nj`?R`?x Rς`?3ۃ`?6!1`?,'`?7`?RC `?N`?Z_&`?oe2`?p>?`?-|}K`?X`?qd`?Ip`?ek}`?ډ`?fYJ`?ӹ`?#M)`?ǘ`?Aȗ`?@wԘ`?6`?V`?\*`?&5`?2`?y=`?H+`?7T7`?_cD`?jP`?SvA]`?ti`? v`?ph`?ϣ`?-\o`?ާ`?PN`?Jʽ`?D-ͭ`?辜ٮ`?g8 `?{`?$ -`?Z `? !`?A,9$`?70`?B=`?]N I`?YU`?efb`?zpwn`?{E{`?8k`?$`?_`?T`?Ss`?`?qGR`?`?.;1`?`?/`?K`?$`? ^)`?g&5`?1=B`?%= N`?H[`?Sg`?B_zs`?jj`?unڌ`?^I`?b`?(`?{V`?ڮ`?8Jw`?`?>V`?Uܸ`?25 `?`?r&"`? .`?/:`? bG`?+S`?L7A``?Bl`? N} y`?hY`?dq`?&pn`?{eު`?M`?CY`?,`?M`?_ `?A{`?˻`?|5Z`?`?9)9'`?3`?@`?VL`?X`?&fe`?r1q`?6a?28*7a?268a?ĬC9a?N&O:a?۠[;a? fha?) ?a?$@a?}Aa?E+Ba?6qrCa?BDa?bMeQEa?XFa?dY0Ga?~oӟHa?zM Ja?<~Ka?A"La?]/Ma?X5;Na?a?q„a?z΅a?ZPۆa?na?%/a?w0ba?; a?4GV~a?R%a?]J]2a?Qi>a?t>xa?Qa?J]2a?ha?t&ma?gܶa?ƊLa?%a?+a?⬈a?A a?|ya? a?^pXa?&a?d73a?zަ?a?YLa?8ӅXa?Mda?)dqa?T5A}b?@Cb?L5b?qW"b?b)b?/nb?yqb?섗b?KPb? b? / b?h b?ǽ  b?%s}b?+b?g\8b?BDb?[;Qb?֪]b?_ Pjb?ʉvb?$Db?{/hb?:8؛b?9FGb?Q,b?\&b?Uh b?sb?ub?rb?ѕT b?0 "b?2#b?v$$b?L1%b?j=&b? I'b?i^`V(b?b)b?&R?o*b?ͮ{+b?G,b?C-b?);.b?5l/b?_@/ܹ0b?KK1b?W#2b?|b*3b?m4b?:y 5b? y7b?8b?VW9b?y):b?66;b?smBb?g?b?Udt@b?MӀAb?JCBb? IJCb?j>"Db?#Eb?'/2Fb?:pGb?E&Hb?DQOIb?\Jb?h.Kb?`s Mb?~ Nb?}"Ob?}|.Pb?ܠ[;Qb?;pGRb?:TSb?d`Tb?WmUb?XyVb?Wb?tLhXb?מYb?1AGZb?[b?5&\b?N)]b?4)^b? @t_b?jK`b?VSbb?(bcb?m2db?x'eb?E4fb?@gb?sLhb?a_Yib?gejb?>rkb?~[~lb?mb?;Onb?ob?Clpb?Xۼqb? 8Krb?sb?t#,*tb?.ub?2: vb?Exxb?Pyb?O\W zb?g,{b? s69|b?k~E}b?ʉvR~b?)^b?jjb?cwb?E^Ӄb?Bb?Rb?b!b?Fb? ‡b?:pΈb?ډb?</Ob?b?(#.b?Y4 b?? b?K|%b?uV 1b?a[>b?3mJb?xy:Wb?cb?Pmpb?|b? ab?lgb?˼Uסb?*Fb?Ib?%ǝb?F=Ӟb?b?2tb?c b?&Sb?!#b?.2b?9*b?=E7b?PCb?[Ob?Zg|_\b?rhb?~p>ub?vꭁb?Քdb?4ތb?Xb?kb?PLۿb?J̳b?@شb?m)b?4b?+b?)x b?b?GW#b?(/b?46x҆b?gBb?ᱟb?[[!b?Րb?Ob?wob?Cb?5ӽNb?7b?-b?Q+b? b? |(b?n4b?"[Ab?,.Mb?9:Zb?Dfb?HPsb?[vb?gb?erjgb?}֤b?"^Fb?صb?R%b??̔b?Fb?sb?[:b?شRb?.b?x1!b?"-b?6:b?Fb?Rb?R( __b?3kb??=xb?oJyb?Ub?,amb?lb?wakb?Ib?UJb?Ϲb?eI)b?İØb?#=b?Ƿw b?1b?@ޫV&b?%2b?5?b?\Kb? Xc?dc?y"pc?-c}c?79|҉c?DAc?Opc?S[ c?fdc?r c?p}Xo c?Έ c?-LN c?ƽ c?@-c?Jc?4 c?ͮ{+c?f(7c?ZDc?$Pc?9]c?ic?Avc?c?'c?]3fc?>s֧c?JEc?zUgc?`$c?7l[ c?w!c?Os"c?T#c?CR %c?&c?p71$'c?ϻ0(c?.+=)c?ҥI*c?U+c?K^b,c?n-c?={.c?g /c?0c?%"1c?-v2c?8j3c?ADj4c?OI5c?Z^6c?^f(7c?qR8c?}:c?{Fw;c?ٓc?.5B?c?UN@c?"[Ac?؜gBc?qsCc?bDc?/ ҌEc?AFc?Gc?Ly Hc?'Ic? 3mJc?h>nKc?IaLc?&UMMc?`UNc?k, Pc?BwIQc? "Rc?={.Sc?_:Tc?1ZGUc?SVc?{%9`Wc?ƟlXc?9yYc?ݓZc? [c?Vf\c?֪]c? |E^c?r_c?!p$`c?0-ac?8dbc?Crcc?LOXec?ZQfc? fLgc?iq0'hc?|@3ic?'@jc?4Lkc?䞮Xlc?C(^emc?qnc?=~oc?`̖pc?qc?㊋rc?|sc?~jtc?:uc?sIvc?wc?W'g(xc?2yc?>[{c?sIv|c?TO}c?1`U,~c?kC8c?v4Ec?M7Qc?^c? +jc?jvc?ɯbc?(яc?Ac?эc?D c?聏c?͋c?aunڌc? c?jMc?}!c?,^, c?;8؛c?CR %c?Nz1c?WZF=c?eYJc?q:Vc?t|8cc?Ӈ.oc?2|c?"c?臭c?Nfc?խc? Ec?kׄƠc?#ӡc?(xߢc?c?mrc?Ec?aQc?'c?a2U0*c?=ϟ6c?IICc?~T~Oc?_=[c?d?3Kd?>UWd?dd?Ipd?[&|d?1=ad?=Еd?wH1@ d?S d?5_% d?j d?u d?Rmd? d?Ld?nd?ͮ{+d?,d?o +d?y7d?HcCd?XPd?W\d?e7id? Lud?#d? @d?+d??74ed?BԳ d?M(D!d?\Y"d?d##d?p$d?x{%d?׆q&d?6 (d?~P)d?#*d?Sr/0+d?<,d?fI-d?o}U.d?Za/d?-\n0d?Nz1d?;2d?IC3d?4d?&75d?f16d?<+i7d?$H8d?SH9d?^:d?@j';d?u=d?>d?]u?d?(@d?uT5Ad?yABd?عi3NCd?7ZDd?]gEd?ׁsFd?SQGd?`Hd?EИId?p ?Jd?:Kd?. Ld?+.Md?6Nd?JB"mOd?MPd?YLQd?gdSd?o +Td?${!Ud? .Vd?xy:Wd?AFXd?lXSYd?_Zd?]`7l[d?ڦx\d?T]d?z΅^d?H_d?8d`d?=Զad?Cbd?T1cd?%"dd?1%ed?q<fd?Gqhd?.S id?^ Pjd?i&kd?Ku/3ld?{?md? Lnd?ho}Xod?Ƣdpd?%c\qqd?}rd?W;sd?BѪtd?Kud?ʼnvd?^?wd?hxd? 4yd?{Gzd?({d?9+&|d?6~d?Ad?UMud?X+d?dT8d?ro~Dd?z2Qd?/r]d?jd?fvd?Ld?Z`d? ϛd?hN?d?Ȯd?&Bd?켍͎d?6ُd?Cld?+d?Kd?_% d?0*d?<$d?|G 1d?Ry=d?9^Id?iWVd?tubd?V6od?i{d?d?s]d?ѭd?0Qdd?ӹd?ECƣd?MۿҤd?9"ߥd? d?i-d?pd?'"d?Od?*)d?D6.6d?A Bd?M Od?`X|[d?cxgd?o[td?}zlˀd?ۅ:d?:`d?d?Td?Wd?Hh˹d?׺d?sd?Wd?d?}Kd?ܸd?;?ld?Ϲd?3Kd?X歺d?'*d?'d?t 4d?x@d?2Ld?*WYd?5ed?NA~6rd?L~d? Xrd?kc섗d?nfd?)zcd?ZӼd?Bd?ENd?!d?Bd?bd?6pd? հd?~*O d?뤾,d?<.9d?Ed?  Rd?Y|^d?$jd?0[wd?u;ʃd?Fu:d?3R臭d?]id?h㈵d?Ot]d?gd? Qd?lFd?ˡEd?*%d?9 e?óe?F-t%e?ڧ1e?!S>e?cJe?2We? ce? pe?| e?=* e?5x_ e?@Ρ e?YLl> e?W歺e?c`e?vnڌe?yTe?4ke?He?Je?P<e?)e?0*e?mɪ7e?$xCe?*Oe?W\e?he?G 6ue? e? e?d${!e?/"e?!;oc#e?Fҿ$e?QcB%e?>]ݱ&e?hW!'e?sѐ(e?ZK)e?o +e??,e?wN#-e?֬3/.e?5-e?"nN%@e?yȔAe?BBe??s(Ce?64De?RAEe?[*MFe?1ZGe?fHe?xԘsIe?Je?5Ke?_Le?ΤMe?R =Ne?uOe?$Pe?o/iQe?:Re?,F]kSe?QTe?\QJVe?Ih˹We?sE)!Xe?-Ye?e9:Ze?ĕwF[e?#-R\e?V_]e?!k^e?@Û5x_e?`e?ُae?\ be?ce?bde?yxee?Afe?6lge?) he?4`ie?S@ke?KTo le?Wme?obHN&ne?m½2oe?-y<-?pe?Kqe?0 Xre?J{dse?$pte?Z}ue?fʉve?Ȓ9we?$ xe?߆ye?ze?@z{e?f|e? o}e?]E~e?#ce?/$e?y:We?Ee?7QKs+e?\7e?g?RDe?TsPe?~31]e?ie?p've?Ϡe?.e?^e?Χe?JΉ=e?e?}͑e?gْe?qe?%je?fe?I e?A)Ze?4($e??N0e?^K=e?VBwIe?bUe?zm6Vbe?xne?8*5{e?e?e?Ue?e?be?qŦe?ӀAҧe?/ިe?t e?e?Kie? ne? ]e?h#M)e?.Q5e?&:,Be?EENe?P [e?B\9{ge?gse?s-Ze?_~Ɍe?!9e?e?{e?ګe?9 ʼe?ƒf׽e?e?UwEe?e?k$ e?re?`"e?0r.e?T:e?(QGe?L4HSe??0`e? Kf?De?f?O@f?F[DAf?fCf?r#Df?c}Ef?ˆ}(Ff?!q4Gf?q@Hf?ުPMIf?=eYJf?/fKf?YrLf?ZMf?M~Nf?Of?vA]Pf?̰Qf?46Vf?JiWf?mUYf?`HZf?+l [f?w'-\f?9]f?GtF^f?uR_f?h^`f?dTkaf?û\wbf?"3cf?Pdf?ef?>Dff?gf?8ahf?[ if?-@jf?"kf?w-!lf?8nf?5D of?Ompf?Z %qf?QfL2rf?q>sf?}w+Ktf?nWuf?͓k dvf?,ypwf?_|xf?Xyf?HSȕzf?7{f?G|f?e}f?;~f?"f?0ef?f??$Df?'f?2#f?\>f?I +f?Uq7f?x`Cf?kzPPf?6w\f?n/if?uf?Rbf?}f?V횐f?o\f?J̳f?-;f?>̔f?ٕf?I2f?f? 'if?f f?!Hf?#-#f?8'0f?C+Nf?fIZf?T gf?$`tysf?kf?vhXf?Aǘf?\7f?֦f?]Pf?ʅʿf?Df?zƾdf?8f?7ݲCf?,f?"f?T !f? .f?q:f?q!Ff?, PSf?.8_f?C.lf?Nwxf?KZ f?ek}f? qf?g|_\f?Ƈ˶f?%S;f?ͪf?Gf?Bf?;f?˵hf?^/ f?Gf?#&f?{&3f??f?8Lf? uXf?&df?U2Tqf?=z}f?I2f?qTnf?_f?/kbf?vf?V`f?Lf?J?f? Įf?h>f?Ǻf?&2f?Ѭlf?&+f?BK8f?Df?*Qf?_ ]f? jf?!yvf?|,}f?7Wf?9CqǛf?N6f?Yef?Vef?pYg?|g?rMdg?ђg?0ACg? g?5"g?M$g?)1 g? ףp= g?iI g?OV g?'b g?.og?{g?C g?&|g?2tg?`=[g?Hh˹g?T:g?|_\g?jg?:vPg?g?Dhg?Wg?8Gg?)g?s,&6g?ŦB g?1 O!g?ܚt["g?g#g?MSt$g?À%g? 2&g?j'g? w(g?(,)g?7k*g?B_+g?DN_,g?Y>-g?eS.g?ap/g?{G 1g?2g?};l"3g?ܝ.4g?;/K;5g?G6g?#*T7g?X˝`8g? m9g?xy:g?t ;g?Wg??g?N&n@g?1Ag? =bBg?kHcCg?SVDg?)_BFg?jJGg?u!Hg?E>'Ig?4Jg?2p@Kg?bLLg?&OYMg?eNg?~.rOg?Д~Pg?< Qg?|Rg?Sg?X|[Tg? ʼUg?q:Vg?u Wg?+eXg?37߈Yg?BYZg?Mg\g?OYM]g?dF ^g? pA,_g?l{%9`g?ˆ5Eag?)Rbg?)t^cg?稣jdg?FSweg?ƒfg?2gg?b֋hg?ig? jg?kg?t_lg?=mg?h>ng?%og?Y1\qg?<֌ rg?HPsg?vSk%tg?^D1ug?3jJ>vg?u8Jwg?)Wxg?P,cyg?pzg? x|{g?m|g?˹W}g?*Ŏơ~g?6g?ۂg?Gǁg?vӂg?߃g?c kcg?g?! _Bg?+ٱg?6S!g?>B͐*g?MG7g?XoCg?Zd;Og?oN\g?{/hg?w-ug?Ց#g?4 g?|g?릔g?Q [g?ʅʿg?9̗g?myؘg?g?+mg?g?bg g?Hg?%VF#g?1е/g?dUg?^sag?i2mg?>uRzg?&†g?1g?[g?g?g?xĬg?_ѭg?5|ݮg?=g?pg?Rg?dg? g?nYk(g?4g?,+MJAg?6ǹMg?AA)Zg?IMfg?X5sg?dwg?eo)狽g?zVg?#Ƥg?5g?g??g?g?g?\bg?sg?Ag?xgg? !g?6\-g?9g?PoFg?S%Rg?0DN_g?wg?^0g?;2Vg?Gŧh?zR&5h?]h?8ih?th?h?Tbh?h?|A h?q h?иp $ h?/0 h?d< h?nIh?KXUh?Mbh? Lnh?h,{h?Ah?% h?*5{h?5h?BA)Zh?Lh?X9h?^ch?nh?zh?{h?ڐfh?9 h?sE)!h?5"h?Ug$B#h?N$h?[[%h?rrg&h?Os'h?/Q(h?D)h? 0*h?L8+h?$,h? 0,-h?i;.h?F ^/h?&R0h?]=1h?h2h?Ct 4h?5h?!6h?_vj.7h?:8h?jIG9h?|S:h?^(`;h?:ؗlh?VF?h?U@h?;ŪAh?s4Bh?/Ch?0*Dh?5#Eh?@Fh?MLbGh?WIh? c AJh?inKh?y'Lh?'y3Mh??Nh?mnLOh?DXPh?aMeQh?ۼqRh?`U,~Sh?ϛTh?I Uh?}zVh?=Wh?:YXh? 2Yh?8Zh?W$&[h?/\h?;]h?tF_h?Qf`h?1]ah?hE,bh?s|8ch?N#Edh?pQeh? ^fh?jdrjgh?ɬvhh?(XQih?jh?L0kh?EƟlh?@mh?~nh?a4oh?]ph?)qh?~4ah?ٮh?(@h?Z h?-h?9h?wEh?mRh?5)^h?4Lkh??wh?QKs+h?V횐h?bg h?nmyh?x[h?+Xh?Oh?7h?HCh?h?7h?eȱ h?+eh?"ߥ%h?D2h?>h??#Kh? Wh?dh?[#qph?.|h?:vPh?xEh?Pj/h?6\䞮h?g^h?r}h?R~Rh?\h?Fh?o;h?ͫ:h?,h?.h?ͨ*h?I"i7h?Ch?HPh?e\h? 'ih?#uh?i?(yui?@4i??mTi?Jói?\Va3i?aۢi?mUi?yxρi?؃I i?6` i?= i?? i?S1#i?0i?%<i?oӟHi?mUi?-ai? Lni?zi?J +i?|i?# i?f.pyi?9i?$EdXi?Pi?[X7i?AgҦi?rLi?}ƅ!i?]@"i?d#i?4($i?zC5%i?ض(A&i?7¢"N'i?Z(i?ؖg)i?Tqs*i?+i?P,i?p-i?..i?.s/i?( 0i?3g}1i?K?2i?J[\3i?V4i?gaO;5i?lɪ7i?%xC8i?!9i?7-:i?Ah:;i?+Fi?Ǚ&l?i?x@i?zލAi?uBi?8Ci?SDi? vöEi?U2Fi?"jGi?.Hi?q9^Ii?DJi?/PR`Li?[ Mi?fF?Ni?Kr&Oi?}:3Pi? ?Qi?h.KRi?ǟlXSi?&"dTi?KqUi?}Vi?B͐*Wi? Xi? Yi?_xZi?x[i?W\i?{m]i?6^i?9(a_i?3`i?>Ubi?VJci?UIddi?a+ei?rl=C8fi?wDgi?01"Qhi?]ii?%jji?Lpvki?li? Omi?i ni?҇.oi?'pi?{ qi?|ri?Cpsi? [ti?dui?`":vi?-X xi?9yi?|DL$zi?O0{i?:[@h=|i?fI}i?q4GV~i?V}bi?(&oi?{i?si?Ҫti?1䠄i?Si?ùi?M~2Ƈi?҈i? r߉i?ji?gi?'_i?[i?'>i?D3O)i?>6i?JCBi?aUNi?`7l[i?lgi?}w+Kti?܂i?;*i?i? i?Wxi?辜i?ǁW˝i?tמi?u6i?2i?ii? i?N ^i?c"i? "R.i?k-B;i?8FGi?(D!Ti?O:`i?Zmi?Ef.pyi?q߅i?}"Oi?ai?.i?i?~ IJi?ݵ|гi?<ܴi?x[i?i?Xl:i?i?`i?uۈ'i?U3i?2g@i?'ILi?2FYi?O>=ei?I%ri? U1~i?k`i?k%ti?)wi?Si?獓¼i?F 2i?i?i?b{i?i? o_i?i?c> i?<ݭ,i?W9i? ҌEi?YLQi?!k^i?-@ji?v8Jwi?C4i?3O)i?Z(i?ei?Pqxi?|i?Wi?li?˞6i?*~i?i?r i?Gi?fc%i?1i?cZB>i?ԱJi?!O!Wi?ɐci?Cpi?='o|i?27߈i?=Ni?ZI+i?T-i?`i?vk i?v|i?4i?[i?i?Q9i?ui?i?mi*i?6i?+]gCi?Oi?QF\j?G˵hj? F%uj?j?d!:j?,sj?"8.j?CRj?N"¿j?>Z1 j?e j?p j?[| j? j?^ j?wxj?֩=#j?5l/j?<j?`Hj?RTj?Tkaj?mj?nHJzj?ùj?,=)j?j?&1j?H2wj?=%j?IVj?eT j?_5!j?#k "j?v$j?%j??{&j?b('j?o4(j?\AA)j?cM*j? Z+j?xWf,j?r-j?6Ko.j?ދ/j??N0j?R 1j?4-2j?!3j?o,( 4j?7{5j?-C6j?NZ7j?Y8j?Ie9:j?p;j?|~!j?#fF?j?fR@j?E_Aj?@ZkBj?$xCj?NDj?]Ej?BsFj?Gj?y7RHj?Ij?7+1Jj?&Kj?1Lj?S=Mj?HOj?T^ Pj?p_Qj?j=&Rj?.v2Sj?u?Tj?KUj?JiWVj?jdWj?]pXj?gI}Yj?QZj?$([j?E\j?]j?A9w^j?_j? .V`j?]aj? "5bj?,cj?z7ej?Bfj?8N gj?Yb+hj?d7ij?TpxADjj?{Pkj?l ]lj?qimj?Н`unj?.noj?Tގpj?Mqj?KHrj?,sj? $@M-k?Y.k?f/k?ZՒr0k? ~1k?m2k?wݗ3k?{L4k?45k?o+6k?$7k?Q0c 8k?;y9k?GW:k?nRX;k?]K=k?+i7>k?t? ?k?-@k?H39Ak?EBk?'eRCk?d^Dk?øDkEk?"ĕwFk?#Gk?ډHk??Ik?}qJk?Kk?[rPLk?Mk?f/Nk?x*Ok?5ZPk?5A}Rk?LN Sk?W\Tk?RcB%Uk?n;2Vk?z6>Wk?nKXk?͐*WYk?,cZk?ip[k?겘|\k?IH]k?Ɍ^k?'_k?e`k?ak?#tubk?ck? iTdk??ek?$]3fk?/עhk?\;Qik?Fˁjk?RE*kk?y]`7lk?h9Cmk?6t?Pnk?-\ok?ipk?S!uqk?rk?msk?oܚtk? Luk?-σvk?*wk?wxk?J yk?kyzk?{k?f`X|k? ~k?$*T7k?5Φ#k?@H0k?@L…Vk?Kbk? ok?D?{k?#k?/3lk?`:۠k?E'Kk?Qk?}\*k?gk?;s k?~xk?k?W}Wk?l?q6l?t)l?e6l?1߄Bl?YNl?c[l?NMgl?Btl? B l?j! l?6 l?() l?4*p l??߾l?EKOl?Vl?b.l?aml?x l?| l?~l?ݚt["l?;.l?h:;l?Gl?X\Tl?ֈ`l?Pll?tgyl?Dׅl?2F l? 9!l?%"l?O#-#l?.$l? :!t%l?kE&l?PS'l?)\(l?g 2*l?r+l?F~,l?w'-l?3.l?bk_@/l?L0l? _>Y1l?٭e2l?Sr3l?<͌~4l?G5l?k6l?Y;ۣ7l?J8l?09l?u):l?($;l?34l?PV W@l?aAl? m6 Bl?lxz,Cl?˃9Dl?*nEEl?QFl?bc^Gl?FjHl?VBwIl?бJl?cJ!Kl?ĐLl?!>Ml?oNl?3Ol?= NPl?'Ql?"-Rl?Z.Sl?9 Ul?E| Vl?vPWl?[[%Xl?4g}1Yl?r9>Zl?}qJ[l?PW\l?ec]l?o^l?mYg|_l?̶ֈ`l?+MFal?ǵbl?A%cl?G仔dl?5el?sfl?d*gl?Rhl?!il?(1kl?3ll?>?ml?J*nl?U6ol?[a^Cpl?ltOql?x=\rl?whhsl?֎utl?5\ul?vl?Pkwl?Qڦxl?DJyl?Ӿzl?n8){l?鲘|l?,,}l?w~l? !l?HV l?"l?.5#l?e9 /l?DMl?IJzZl?Ufl?anrl?flfl?wb֋l?#El?Vl?$l?@Jl?ʦl?>s֧l?\Ǹl?2Rl?ެl?y&1l?l?7!l? -l?9l?S"^Fl?-Rl?9}=_l?pDkl?Oqxl?-[닄l?fel?qjl?J}Yکl?Il?M»l?f(ϼl?ŪA۽l?$l?5wl?̯l?A)V l?l?5&l?]2l??l?Kl?zWl?'bdl?73pl?>tA}l?Il?TUh l?`⏢l?l\l?pwnl?ςPl?.Ml?Dl?줾,l?K8l? l?,{l?gҦl? Z+l?%7l?9Dl?Pl?A ]l?il?!ul?^-wfl?8Վl?DkEl?{O崧l?Z_$l?8fٓl?qSl?|rl?UGl?Ql?;l?q0 l?е/l?/$l?#0l?ם٬l?IbIl?Uܸl?_`V(l?kЗl?wJl?{vm?ڍ>m?9Um?2m?4)m?V&5m?ƠBm?Nm?rݔZ m?bg m?0s m?A m? } m?Lm?!qm? -m?i8enm?Cm?'OYMm?ZӼm?eM,m?CqǛm?|A m?zm?`5!m?Y.m?):m?|8Gm?Sm?:̗`m?l m?x!m?Wf"m?Ց#m?D$m?st%m?#&m?1'h'm?2(m?=\r)m?MI*m?TPQ+m? `-m?jkD0.m?v/m?(8'0m?~31m?,?2m?D]L3m? X4m?m?,_?m?8@m?tCSvAm?NCm?2ZGUDm?eEm?p;4,Fm?N|8Gm?/EHm? QIm?k#]Jm?ʩajKm?(vLm?@Mm? Nm?EׅOm?Pm?yQm?bmRm?nSm?LTm?~bUm?&+Vm?<2VWm?= Ym?HJzZm?XT$[m?_>Y1\m?k=]m?uv28J^m?ԁV_m?3&c`m?oam?{bm?Oecm?Քdm? ƈDem?lfm?|#gm?)hm?pim?qjm?F ekm?Plm?!Ynm?b,/om?7Mpm? C*qm?NA~6rm?YBsm?=e5]Otm?p[um?{)m?mPm?m?[a/m?۞ m?V-m?w}9m?JEm?5&\Rm?1>^m?<;km?RH2wm?Sm?_&m?njm?uim?,صm?H¾m?ꗈοm?H'm?|m?m?epum? m?#dTm?%m?X32m??Ң>m? MKm?ǁWm?\ Acm?+`pm?75|m?xB?m?M)m?6Ym?dm?om?S{mm?m?Lm?om?Ψ*m?-sm? m?gym?I*m?[X7m?Cm?fO7Pm?ʦ\m?$Dim?um?%8m?@1dm?<,Ԛm?GCm?]S m?^"m?jm?yum?؀qm?7m?Om?v m?S.m?j#m? 0m?p^}?n?n?.2n?%n?0&n?Kn?׻?n?|,G@n?An?9% &Bn?0Cn?;Dn?VGtFn?RGn?^SHn?si+In?tv28Jn?0DKn?jQLn?]Mn?M^iNn?_vOn? RςPn?i>Qn?FRn?'Sn?:Tn?Un?D.lVn?Wn?#KXn?`Yn?**Zn?6 \n?}A ]n?Lx$^n?:X0_n?cyW=`n?nIan?Wzm6Vbn?bcn?aodn?sۄ{en?ҧUfn?1cgn?IӠhn?Bin?N=jn?!kn? 1ln?jmn?&pnn?(on?Oqn?$rn?D0.sn?;)tn?G 6un?aR||Bvn?]Nwn?ip[[xn?~tgyn?d:tzn?;ީ{n?X|n?҈}n?XL~n?gn?@׾n?tϺFˁn?4ׂn?2%n?(n?n?Ot n?n? S"n?k*.n?52;n?)AGn?LTn?Ws`n?Ecln?ng_yn?z΅n?b[>n?խn? On?~Ɍn?ݲCÖn?n?!Jn? Wn?cn?>$|on?/^|n?:pΈn?ZF=n?Qdn?]n?whXn?sn?5Lkn?n?@Jn?Qn?4)n?n?n(n?΢w*n?+6n?VCn?On?H5\n?hn?un?dn?)sn?"5bn?@gҦn?KAn??W[n?b n?mOn?[yn?Con?n?x7N n?צn?5+-#n?/n? o??o?~@o?AAo?rfBo?Co?^gEDo?Eo?)[$Fo?z4ՓGo??OIo?8KrJo?VCKo?aQ+Lo?Um77Mo?x0DNo?+POo?q]Po?КiQo?/uRo?^So?͎To?K=Uo?ӁVo? Wo?huXo?Yo?&jjZo? [o?^I\o?B#ظ]o?.R( _o?:̗`o?_EF$ao?Pv0bo?\:̔o?9 p?v p?<_E p? p?R p?J U p?T^ p? p?Xjp?"4p?'Hlwp?f-p?3ۃp?8 p?u> p?T㥛 p?bJ!p? !p?bBW"p?z"p?Vc#p?q#p? !p$p?Y$p?K|%p?.&p?!&p?'8'p?<-?p'p?2(p?8ߡ(p?K>v()p?C3O)p?I4*p?YO*p?Uj@+p?Z'.+p?g`eM,p?f,p?k^Y-p?vq -p?%wDf.p?||.p?Rr/p?3/p?#0p?[1p?BF1p?2p?2p?P}:3p?:r3p?*4p?^4p? q75p?.Q5p?lC6p?Ҩ6p?eO7p?{"07p?*g\8p?蜟8p?Yh9p?89p?Fu:p?~:p?GN;p? p?c'>p?-y<-?p?26t?p?q89@p?!>@p?CmFAp?I*SAp?/ORBp?TBp?Za^Cp?=`2Cp?eikDp?kDp?LqUwEp?vEp?|HFp?Z Gp? IGp?Hp?h'Hp?_#Ip?Ǟ=Ip?v/Jp?&Jp?կt>Vp?,Vp?2p@KWp?G8-xWp?=WXp?CXp?VIddYp?O!WYp?TގpZp?dZZp?`X|[p?e6\p?rkm\p?"q]p?vLݕ]p?| ^p?0L^p?߇(_p?@_p?>4`p?+`p?wcAap?L4ap?Mbp? bp?[kBZcp? (zcp?fdp?iƢdp?_!sep?Yep?wِfp?'ݖgp?Sgp?8hp?5ohp?ip?Gߤip?C+jp?Njp? 7kp?Rp?Ip?x Rςp?(vUp?3ۃp?ap?6!1p?&jinp?,'p?D2zp?7p?=^Hp?RC p?Iطp?Np?aTR'p?Z_&p?_̖p?oe2p?kFp?p>?p?}vuŌp?-|}Kp?܁:эp?Xp?;Tގp?qdp?.p?Ipp?3p?ek}p?W"p?ډp?p?fYJp?p?ӹp?tѐ(p?#M)p? a5p?ǘp?2Ap?Aȗp??Np?@wԘp?xZp?6p?N gp?Vp?msp?\*p? !p?&5p?k,amp?2p?7ܘp?y=p?(CULp?H+p?Nϻp?7T7p?YI+p?_cDp?EeÚʢp?jPp?p= ףp?SvA]p?|yp?tip?b1p? vp?Xp?php?%p?ϣp?~7p?-\op?ݴ!p?ާp?<.p?PNp? :p?Jʽp?ևFp?D-ͭp?XeSp?辜ٮp?{_p?g8 p?Clp?{p?upxp?$ -p?"p?Z p?3dp? !p?&p?A,9$p?1Xqp?70p?O=බp?B=p?HLP÷p?]N Ip? Tƿϸp?YUp?l_@/ܹp?efbp?jp?zpwnp?)v4p?{E{p?}p?8kp?( p?$p?F\p?_p?&p?Tp?;3p?Ssp?b?p?p?ŊLp?qGRp? Xp?p?~dp?.;1p?hqp?p?=r}p?/p?Gp?Kp? gp?$p?Y&p? ^)p? [p?g&5p?,p?1=Bp?v7Oup?%= Np?Bp?H[p?3NCTp?Sgp?Yp?B_zsp?d73p?jjp?Ppp?unڌp?{+p?^Ip?p?bp?l+p?(p?˝`8p?{Vp?*Dp?ڮp??Qp?8Jwp?]p?p?Gˁjp?>Vp?vp?Uܸp?up?25 p?clp?p?iܛp?r&"p?!Kp? .p?^p?/:p?*p? bGp?>&Rp?+Sp?1 p?L7A`p?Y1\q?^q?d)q?Mjhq?o%;6q?urq?[{Bq? \q?Oq?iQq?[q?ȗPq?w gq?'0q?֨htq?Dq?5؀q?幾 q?{G q?C8 q? q?в q?Ro& q?,^, q?镲 q?`8 q?c q? =Eq?ntq?Qq?Xq?} ^q?,Sq?jq?Lq?: vq?%2q?+jq?H1@ q?6ُq?<q?WBwIq?H4"q?Mq?eS.q?Yk(q?^(`;q?sdq?#jGq?o_q?u?Tq?1{vq?`q?Sq??mq?Uq?yq?NGq?q?4 q?\~lq? ; q?۞ q?j%!q?rK!q?/1"q?x캷"q?(֩=#q?f*#q?#bJ$q?6$q?V%q?Z %q?DAc&q?x&q?o'q?S O'q? |(q?W)q?a)q? C*q?%*q?o+6+q?1zn+q?67',q?}<ݭ,q?-B4-q?GnM-q?M+@.q?;S.q?XL/q?^b,/q?IddY0q?iܛ0q?oe1q?XuV 1q?{Cr2q?z2q?f~3q?J4q?ő"4q?tY5q?$5q?Ӣ>6q?6q?28*7q?up7q?268q?@߼8q?ĬC9q?iO9q?N&O:q?:q?۠[;q?]].;q? fhq?y|?q?) ?q?F@q?$@q?7[ Aq?}Aq?%:,Bq?E+Bq?0:9Cq?6qrCq?S<.EDq?BDq?GREq?bMeQEq?S"^Fq?XFq?p^jGq?dY0Gq?ihwHq?~oӟHq?.u׃Iq?zM Jq? GJq?<~Kq?닄Kq?A"Lq?J%Lq?]/Mq?xMq?X5;Nq?Nq?Yq?l%tYq?+1JZq?0Zq?z6>W[q?)q?B:q?oŏq?t>Zq?"uq?fq?qq?0.sq?Tq?q??eq?$"q?*3q?M0kq?5Yq?;ۤq?[A+q? GJq?LM7q?iR q?XCq?])ʥq?xcAaPq?'i֦q?n\q?txq?5z5@iq?wq?uq?Dlq?)q?Vq?Rq?`q?q?`5!q?mq?T-q?nݳq?:q?ɋLq?}HFq?,̰q?Rq?+ٱq?:xq?j#r?v$$r?3ڪ$r?L1%r?ȭI%r?j=&r?Z'&r? I'r?ߡ('r?i^`V(r?(r?b)r?w)r?&R?o*r?w*r?ͮ{+r?5 ,r?G,r?V-r?C-r?#~.r?);.r?Q/4'/r?5l/r?:r30r?_@/ܹ0r?F@1r?KK1r?nQfL2r?W#2r?\X3r?|b*3r?+hZbe4r?m4r?sq5r?:y 5r?~NA~6r? y7r?HȰ7r?8r?B 8r?VW9r?9r?y):r?d6:r?66;r?÷n;r?smBr?>r?g?r??,?r?Udt@r?@r?MӀAr? Br?JCBr?[{Cr? IJCr?Dr?j>"Dr?Y,Er?#Er?x)u8Fr?'/2Fr?48EGr?:pGr?5@iQHr?E&Hr?K^Ir?DQOIr?V]jJr?\Jr?RbvKr?h.Kr?mQfLr?`s Mr?yՏMr?~ Nr?oEENr?}"Or?͏Or?}|.Pr?,9$Pr?ܠ[;Qr?Qr?;pGRr?-Rr?:TSr?IrSr?d`Tr?!Tr?WmUr?ԛQUr?XyVr?eVr?Wr?0 Xr?tLhXr?# Yr?מYr?%Zr?1AGZr? ~1[r?[r?@x=\r?5&\r?#]J]r?N)]r?.lV^r?4)^r?\:rkr?žvkr?~[~lr?-mr?mr?ْUnr?;Onr? or?or?J4*pr?Clpr?6qr?Xۼqr?{Crr? 8Krr?fOsr?sr?o[tr?t#,*tr?$)ahur?.ur?4ctvr?2: vr??@wr?Exxr?@KWxr?Pyr?Vyr?O\W zr?aKzr?g,{r?]m{r? s69|r?x?n|r?k~E}r?}r?ʉvR~r?z3M~r?)^r?ؚr?jjr?7',r?cwr?r?E^Ӄr? r?Br?Tȕzr?Rr?"r?b!r?߉Y/r?Fr?p;r? ‡r?}8Hr?:pΈr?.Tr?ډr? rar?</Or?mr?r?K#fyr?(#.r?.er?Y4 r?:ZՒr?? r?gEDr?K|%r?PNr?uV 1r?%\#r?a[>r?gBĒr?3mJr?rѓr?xy:Wr?A~6rݔr?cr?r?Pmpr?*Qr?|r?^r? ar?0r?lgr?r?˼Uסr?z(r?*Fr?͌~4r?Ir?8@r?%ǝr?]Mr?F=Ӟr?Yr?r?Utur?ǃ-vr?vꭁr?&r?Քdr?!Ur?4ތr?㥛 r?Xr?B4-r?kr?9r?PLۿr? Fr?J̳r?_ӃRr?@شr?^r?m)r?wakr?4r?{wr?+r?l@r?)x r?9 毐r?r?`r?GW#r?"ڎr?(/r?U.Tr?46x҆r?} r?gBr?L$zr?ᱟr?%r?[[!r? Y2r?Րr?i>r?Or?ȶ 8Kr?wor?'†Wr?Cr?dr?5ӽNr?zpr?7r?C|r?-r?ner?Q+r?ԕr? r?`cDr? |(r?ݳr?n4r?W#r?"[Ar?|(ђr?,.Mr?3Kr?9:Zr?:?qr?Dfr?J?r?HPsr?UPr?[vr?Va3r?gr?l/r?erjgr?x'r?}֤r?s+r?"^Fr?Ҏ~7r?صr?1Cr?R%r?]Pr??̔r?\r?Fr?M9 s?DAs?EJys?Ops?U-(s?S[ s?aX5s?fds?al!A s?r s?w7N s?p}Xo s?Z s?Έ s?~g s?-LN s?ݙ s s?ƽ s?<s?@-s?ds?Js?wԘs?4 s?XCs?ͮ{+s?ks?f(7s?"s?ZDs?u_s?$Ps?s?9]s?2Tqs?is? s?Avs?HPs?s?O"¿s?'s?-s֧s?kD0.s?JEs?O}:s?zUgs?)[$Fs?`$s?f\S s?7l[ s?q_!s?w!s?F};l"s?Os"s? x#s?T#s?$s?CR %s?b%s?&s?z&s?p71$'s? h's?ϻ0(s?nض(s?.+=)s?G)s?ҥI*s??4s?ADj4s?I'L5s?OI5s?PUX6s?Z^6s?`d7s?^f(7s? l`q8s?qR8s?lw}9s?}:s?˂?:s?{Fw;s?*;s?ٓs?Gq>s?.5B?s?l?s?UN@s?e@s?"[As?cKAs?؜gBs?YBs?qsCs?!*Cs?bDs?MEs?/ ҌEs? Fs?AFs?= ByGs?Gs?+Hs?Ly Hs?!6X8Is?'Is?Z-DJs? 3mJs?8*7QKs?h>nKs?D]Ls?IaLs?vOjMs?&UMMs?ZvNs?`UNs?4fOs?k, Ps?qdPs?BwIQs?|ԛQs? "Rs?QCRs?={.Ss?Ss?_:Ts?t"Ts?1ZGUs?mUs?SVs?̵hVs?{%9`Ws?+pWs?ƟlXs?\Xs?9yYs?OYs?ݓZs?GP [s? [s?.\s?Vf\s?D$]s?֪]s?d 1^s? |E^s?9}=_s?r_s?"I`s?!p$`s?'-\Vas?0-as?2bbs?8dbs?>>!;ocs?Crcs?I{ds?LOXes?Tes?ZQfs?[`fs? fLgs?k gs?iq0'hs?whhs?|@3is?w׹is?'@js?֍wGjs?4Lks?5ks?䞮Xls?k&ls?C(^ems?ms?qns?Q_ns?=~os?tps?`̖ps?Sqs?qs?nSrs?㊋rs?G)ss?|ss?,26ts?~jts?;Bus?:us? Ovs?sIvs?H0[ws?ws?!gxs?W'g(xs?-$`tys?2ys?e8πzs?>[{s?C?{s?sIv|s?"O|s?TO}s?Z }s?1`U,~s?e~s?kC8s??qs?v4Es?|zlˀs?M7Qs?ׁs?^s?\nKs? +js?s?jvs?b*s?ɯbs?xܙ s?(яs?V s?As?6x"s?эs?J.s?D s?W;s?聏s?R>Gs?͋s?6Ts?aunڌs?3`s? s?oms?jMs?'ys?}!s?-'s?,^, s?2ds?;8؛s?=Ӟs?CR %s?IICs?Nz1s?Ts?WZF=s?`"ĕs?eYJs?fk}Жs?q:Vs?vݗs?t|8cs?#qps?Ӈ.os?s?2|s?eOs?"s?@߾s?臭s?Y.s?Nfs?ӝ's?խs?\M 4s? Es?|@s?kׄƠs?ALs?#ӡs?y[Ys?(xߢs?5es?s?7:rs?mrs? *~s?Es?s?aQs?S!s?'s?,s?a2U0*s?8hs?=ϟ6s?pC׼s?IICs?NGɫs?~T~Os?-Zլs?_=[s?e%s?s?l dvs?!s?"s?zs?)!XU/s?&s?,;s?82s?7L4Hs?= ls?FCƣTs?Hs?N@as?TTJs?Zms?_ws?be4ys?k)s?pas?qvk s? |(ђs?ρs?@s?._x%s?ޒs?1s?=s?SW>s?s?KJs?s?G6Ws?Yns? cs?~s?g;ps?Ls?ܵ|s?vrs?%/s?+s?cs?3fs?#ӡs? (s?B Bs?[z4s?s?P@s? !s?&OYMs?^, s?2Ys?7s?l=C8fs?Cps?Hrs?{Nzs?*T7s?YNs?_s?8ens?j+s?p-s?Gves?{b*s?հs?U 7s?Ds?V|Cs?cs?Os?£#s?qJ[\s?!s?дhs?s?/>:us?qs?˸s?=us?2s?Ps?L⬈s?i s?&s?Z/-s? gs?]9s?h׿s? Fs?Fs?wR~Rs?&s? ^s?&%s?4,F]ks?1s?7ws?C=}s?B:s?dus?ѯs?l%s?r)s?"T2t?磌t?`>t?0t?3Kt?kt?>UWt? t?dt?MJt?Ipt? t?[&|t? ,)t?1=at?i7t?=Еt?Bt t?wH1@ t?'Nw( t?S t?Yh4 t?5_% t?dVA t?j t?Cp\M t?u t?{5Zt?Rmt?Pft? t?`st?Lt?Dt?nt?t?ͮ{+t?|8ct?,t?ۿҤt?o +t?:,Bt?y7t?֦t?HcCt? !t?XPt?W횐t?W\t?t?e7it?ot? Lut?s t?#t?Nt? @t?1&t?+t?1w-!t??74et?<- t?BԳ t?MHk :!t?M(D!t?S{F"t?\Y"t? __R#t?d##t?jjZ_$t?p$t?uSk%t?x{%t?(9x&t?׆q&t?G't?6 (t?(t?~P)t?D;)t?#*t?*t?Sr/0+t?/g+t?<,t?aũ,t?fI-t?#F-t?o}U.t?ܝ.t?Za/t?}%/t?-\n0t?0t?Nz1t?; 2t?;2t? s 3t?IC3t?4t?4t?X zR&5t?&75t?+26t?f16t?7n1?7t?<+i7t?tBK8t?$H8t?MbX9t?SH9t?2Yd:t?^:t?dVp;t?@j';t?o^}t?=>t?]u?t? >?t?(@t?k@t?uT5At?ʨ2At?yABt?)Bt?عi3NCt?&kCt?7ZDt?ʠDt?]gEt?EJEt?ׁsFt?ᔹFt?SQGt?)Ht?`Ht?bIt?EИIt?Jt?p ?Jt?}w+Kt?:Kt?~7Lt?. Lt?%qVDMt?+.Mt?<1PNt?6Nt?It?fvt?#t?Lt?( t?Z`t?Zt? ϛt?đ"t?hN?t? w.t?Ȯt?wۅ:t?&Bt?UGt?켍͎t?4ySt?6ُt?4`t?Clt?nlt?+t?Qyt?Kt?bt?_% t?+t?0*t?m6Vbt?<$t?AѪt?|G 1t?+MJAt?Ry=t?XİØt?9^It?c> Йt?iWVt?Hoܚt?tubt?z2t?V6ot?nt?i{t?d&t?t?ÜMt?s]t?"t?ѭt?,'t?0Qdt?3t?ӹt?>ʈ @t?ECƣt?{Lt?MۿҤt?|Xt?9"ߥt?[Yet? t?pqt?i-t?8~t?pt?xet?'"t?t?Ot?5%Yt?*)t?0t?D6.6t?;Mft?A Bt?RGȮt?M Ot?RAEկt?`X|[t?^t?cxgt?ni5$t?o[tt?tt?}zlˀt?,)t?ۅ:t?rt?:`t?t?t?IQ,t?Tt?8t?Wt?0Et?Hh˹t?eQt?׺t?^t?st?v1t?Wt?o=t?t?ΧUJt?}Kt?-Vt?ܸt?4ct?;?lt?ot?Ϲt?Iv|t?3Kt?t?X歺t?jt?'*t?fat?'t?_ѭt?t 4t?$@t?x@t?St?2Lt?$t?*WYt?@0Gt?5et?;t?NA~6rt?F;nt?L~t?]Rt? Xrt?]/Mt?kc섗t?it?nft?yt#,*t?)zct?6t?ZӼt?7 Ct?Bt?zOt?ENt? [t?!t?TYht?Bt?tt?bt?y8t?6pt?pt? հt?mt?~*O t?.熦t?뤾,t?at?<.9t?et?Et?JVt?  Rt?Dt?Y|^t?Jt?$jt?g*#t?0[wt?5>t?u;ʃt?%A t?Fu:t?L2rt?3R臭t?W"t?]it?Ac&Q/t?h㈵t?n;t?Ot]t?y0Ht?gt?^Tt? Qt?at?lFt?~mt?ˡEt?zyt?*%t?ٲ|]t?9 u?8̒u?óu?p<u?F-t%u?ꫫu?ڧ1u?Tdu?!S>u?ފu?cJu?Xu?2Wu?qiu? cu? Mu? pu?/Hu?| u?$A u?=* u?/' u?5x_ u?K;5 u?@Ρ u?F( u?YLl> u? R)v4u?W歺u?h]@u?c`u?hUMu?vnڌu?%tYu?yTu?4fu?4ku?㊋ru?Hu?Bu?Ju?u?P<u?u?)u?_sau?0*u?аu?mɪ7u?g@u?$xCu?{u?*Ou?[u?W\u?9Վu?hu?Ou?G 6uu?mu? u?UD u? u?L!u?d${!u?*8 "u?/"u?r5+-#u?!;oc#u?@,9$u?Fҿ$u?0L F%u?QcB%u?W zR&u?>]ݱ&u?b^'u?hW!'u?LnYk(u?sѐ(u?yw)u?ZK)u? 8*u?o +u?i+u??,u?Ǜ,u?wN#-u?&v-u?֬3/.u?.u?5-:u?H5:u?:/K;u?@fg;u?VF#Wu?bԵ>u?sh|?u?"nN%@u?s ]@u?yȔAu?0̕Au?BBu?;Bu??s(Cu?yCu?64Du?MDu?RAEu?mEu?[*MFu? Fu?1ZGu?iaiGu?fHu?Hu?xԘsIu?'UHIu?Ju?ϷKu?5Ku?I'Lu?_Lu?DÖMu?ΤMu?>+Nu?R =Nu?u7Ou?uOu?`2CPu?$Pu?)TPQu?o/iQu?5&\Ru?:Ru?}@3iSu?,F]kSu?KuTu?QTu?:WUu?\QJVu?bVu?Ih˹Wu?mWu?sE)!Xu?WyaXu?-Yu?|гYu?e9:Zu??Zu?ĕwF[u?tp[u?#-R\u?Ҧ\u?V_]u?1d]u?!k^u?^u?@Û5x_u?Xm_u?`u?N au?ُau?LLbu?\ bu? ƻ#cu?cu?j@+0du?bdu?#u?(QGu?.u?L4HSu?9u??0`u?ZEhu? Kv?_vOv?]v? [v?v?kSUh v? v?t!v?z!v?)H4"v? l#v?£#v?7$v?<$v?"J %v?F(%v?-s,&v?30&v?T9)9'v??a'v?DgE(v?bJ$(v?PR)v?U@)v?p[[x^*v? a*v?fj+v?l+v?.rOWw,v?w ,v?}ƃ-v?< .v?C6.v?n/v?K/v?z"0v?70v?YL/1v?1v?n;2v?g+2v?+H3v?c3v?ubT4v?%4v? a5v?ؙB5v?3Vzm6v?6v?y7v?A!8v?JY8v? 9v?PȒ9v?:v? ?8:v?^o%;v? ;v?v1=v?-=v?{3jJ>v?*9'>v?>-W?v?De?v?8J^c@v?O@v?U pAv?F[DAv?`R||Bv?fCv?UlCv?r#Dv?wF[Dv?c}Ev?ʡEv?ˆ}(Fv?q::Fv?!q4Gv?ЙGv?q@Hv?/.Hv?ުPMIv?Iv?=eYJv?"Jv?/fKv?LǜgKv?YrLv?Lv?ZMv? ސFNv?M~Nv?h Ov?Ov?%Pv?vA]Pv?&*Qv?̰Qv? y7Rv?46Vv?_D1uWv?JiWv?OUXv?mUYv?[Yv?`HZv?{fIZv?+l [v?q[v?w'-\v?9}=_\v?9]v?ο]v?GtF^v?1>^v?uR_v?V_v?h^`v?%`v?dTkav?av?û\wbv?rbv?"3cv?̓k dv?Pdv?0 ev?ev?J#fv?>Dfv?/gv?gv?L{)XƆnv?5D ov?I5ov?Ompv?CULpv?Z %qv?`qv?QfL2rv?l@rv?q>sv?`wsv?}w+Ktv?4ctv?nWuv?uv?͓k dvv?|(Bvv?,ypwv?ۤwv?_|xv?:!yv?Xyv?zv?HSȕzv?{v?7{v?VҊo(|v?G|v?4}v?e}v?~NA~v?;~v?sMv?"v?r-Zv?0ev?1 fv?v?g sv??$Dv?!{v?'v?M-[닄v?2#v?8Zv?\>v? DOʤv?I +v?jO9v?Uq7v?ZCv?x`Cv?'fʉv?kzPPv?q7֊v?6w\v?|v?n/iv?D+gv?uv?v?Rbv?Fv?}v?av?V횐v?%!v?o\v?-v?J̳v?}:v?-;v?ׁsFv?>̔v?;Rv?ٕv?uR_v?I2v?kv?v?Wj1xv? 'iv?䠄v?f v?^v?!Hv?t'v?#-#v?2R臭v?8'0v?2>^v?C+Nv?CbԵv?fIZv?O=v?T gv?uZAv?$`tysv?e1v?kv?2q v?vhXv?|%v?Aǘv?v?\7v?Oo+v?֦v?7v?]Pv? NDv?ʅʿv?lPv?Dv?-]v?zƾdv?){iv?8v? vv?7ݲCv?o{v?,v?Fv?"v?cZv?T !v?ɧv? .v?bX9v?q:v?Ҩv?q!Fv? 'Lv?, PSv?2Ƈv?.8_v?=@v?C.lv?=Ifv?Nwxv?T4v?KZ v?_E v?ek}v?Yk(v? qv?v$$v?g|_\v?0v?Ƈ˶v?v=v?%S;v?ԘsIv?ͪv?3Uv?Gv?Rbv?Bv?~nv?;v?P0{v?˵hv?rv?^/ v?v?Gv?lfv?#&v?v?{&3v?*Z^v??v? v?8Lv?O=v? uXv?G!ɬv?&dv?,Cv?U2Tqv?8v?=z}v?cC7v?I2v?Njv?qTnv?!Z+v?_v?eI)v?/kbv?p5v?vv?=|(Bv?V`v?Nv?Lv?[v?J?v?Zwgv? Įv?sv?h>v?Uv?Ǻv?vuŌv?&2v?4v?Ѭlv?4iv?&+v?v?BK8v?]v?Dv?Qv?*Qv?Rbv?_ ]v?v? jv?mFAv?!yvv?&v?|,}v?+2: v?7Wv?=v?9CqǛv?H.!v?N6v?GTn.v?Yev?_":v?Vev?kMGw?pYw?dvSw?|w?Á,`w?rMdw?" lw?ђw? yw?0ACw?ߣzw? w?>xw?5"w?Yw?M$w?lɪw?)1 w?[8 w? ףp= w?` w?iI w? w?OV w?wT w?'b w? w?.ow?5 Ifw?{w?w?C w? =Ew?&|w?R,w?2tw?71$'w?`=[w?C3w?Hh˹w?nN%@w?T:w?YrLw?|_\w?,eXw?jw?pQew?:vPw?{ qw?w?H0~w?Dhw?w?Ww?{w?8Gw?e~w?)w?Ĵow?s,&6w?#]w?ŦB w?c w?1 O!w?-w?R_vj.w?eS.w?jv/w?ap/w?vU0w?{G 1w?oŏ1w?2w?Ό~42w?};l"3w?-3w?ܝ.4w?r4w?;/K;5w?5w?G6w?If6w?#*T7w?a7w?X˝`8w?Z8w? m9w?f@9w?xy:w?N:w?t ;w?# w?z6>w?@7n1?w??w? =@w?N&n@w?++MJAw?1Aw?]7VBw? =bBw?B,cCw?kHcCw?NoDw?SVDw?yY |Ew?)_BFw?dzFw?jJGw?7pGw?u!Hw?{YHw?E>'Iw?ȭIw?4Jw?Su8Jw?2p@Kw?Kw?bLLw?iLw?&OYMw?pMw?eNw?Ͽ]Nw?~.rOw?.eOw?Д~Pw?QQw?< Qw?DRw?|Rw?JESw?Sw?#*Tw?X|[Tw?:6Uw? ʼUw?gCVw?q:Vw?.rOWw?u Ww?$&[Xw?+eXw?1"QhYw?37߈Yw?nw?K %vmow?%ow?+ypw?Y1\qw? 7Uqw?<֌ rw?hBĒrw?HPsw?M 4sw?vSk%tw?%Ytw?^D1uw?duw?3jJ>vw?o{vw?u8Jww?B{ww?)Wxw?oaxw?P,cyw?yw?pzw?^c@zw? x|{w?ݯ|w?m|w?W}w?˹W}w?{ю~w?*Ŏơ~w?K'w?6w?9m4w?ۂw??@w?Gǁw?LMw?vӂw?U3Yw?߃w?+fw?c kcw?(rw?w?r w?! _Bw?%zw?+ٱw?/1闈w?6S!w?<Yw?>B͐*w?GȰw?MG7w?LS8w?XoCw?^~Ɍw?Zd;Ow? j֍w?oN\w?hurw?{/hw?ǀw?w-uw?&few?Ց#w?w?4 w?ZDw?|w?CԳ w?릔w?N#-w?Q [w?Ȓ9w?ʅʿw?_BFw?9̗w?ۼqRw?myؘw?6^w?w?|Pkw?+mw?*ww?w?9 /w?bg w?w?Hw?w?%VF#w?V+~w?1е/w?6w?dUw?X;ۣw?^saw?0duw?i2mw?ow?>uRzw?ziw?&†w?M w?1w?]iw?[w? %w?w?iQH2w?w?ȳ˷>w?xĬw?'E'Kw?_ѭw?ʿWw?5|ݮw?9dw?=w?Cupw?pw?-|w?Rw?Tw?dw?`"ĕw? w?3w?nYk(w?w?4w?}%w?,+MJAw?0 Ƿw?6ǹMw?:<Ӹw?AA)Zw?G`w?IMfw?Rxw?X5sw?W^?w?dww?ilw?eo)狽w?uw?zVw?s`w?#Ƥw?ҋ*w?5w?1Tm7w?w?Cw??w?HLPw?w?N»\w?w?<+iw?\bw? жuw?sw?j0 w?Aw?yw?xgw?($w? !w?Xw?6\-w?ȳw?9w?D7w?PoFw? w?S%Rw?+w?0DN_w?a6w?ww?*w?^0w? 6uw?;2Vw?lA!x?Gŧx?Li-x?zR&5x?*Xl:x?]x?c]Fx?8ix?nKSx?tx?FzQ_x?x?*lx?Tbx?Exx?x?c x?|A x?9y x?q x? x?иp $ x?-X x?/0 x?ɧǶ x?d< x?=!7 x?nIx?x?KXUx?x?Mbx?Yx? Lnx? x?h,{x?dx?Ax?v x?% x?$xCx?*5{x?40&x?5x?;l"3x?BA)Zx?F?x?Lx?PR`Lx?X9x?]pXx?^cx?iTdx?nx?mtOqx?zx?H}x?{x?*.x?ڐfx?<x?9 x?衶 x?sE)!x?G0}!x?5"x?"x?Ug$B#x?$\#x?N$x?dϞ$x?[[%x?;%x?rrg&x?!撪&x?Os'x? 'x?/Q(x?)x?D)x?>*x? 0*x?{h+x?L8+x?+,x?$,x?Z*oG8-x? 0,-x?5D.x?i;.x?Ac&Q/x?F ^/x?wLݕ]0x?&R0x?WWj1x?]=1x?5ctv2x?h2x?nK3x?Ct 4x?yS4x?5x?Q?Û5x?!6x?26x?_vj.7x?37x?:8x?n8x?jIG9x?̲'9x?|S:x?+:x?^(`;x?`;x?:ؗlx?뉮 ?x?VF?x?@x?U@x?d~$Ax?;ŪAx? 0Bx?s4Bx?"rl=Cx?/Cx?$IDx?0*Dx?/fKVEx?5#Ex??;bFx?@Fx?FZ*oGx?MLbGx?Qԙ{Hx?WIx?[]N Ix? c AJx?hxJx?inKx?tBKx?y'Lx?xWLx?'y3Mx?׊6ǹMx??Nx?56Nx?mnLOx?*Ox?DXPx?Px?aMeQx?RQx?ۼqRx?ØRx?`U,~Sx?dTx?ϛTx?nڌUx?I Ux?CVx?}zVx?,)Wx?=Wx?!6Xx?:YXx?uBYx? 2Yx?IOZx?8Zx?ip[[x?W$&[x?*g\x?/\x?e5]Ot]x?;]x?@׾^x?tF_x?#LQ._x?Qf`x?W˝`x?1]ax?bE ax?hE,bx??n|bx?s|8cx?y9cx?N#Edx?[dx?pQex?\-ex? ^fx?:fx?jdrjgx?!gx?ɬvhx?yhx?(XQix?׽ jx?jx?6ɏkx?L0kx? h"lx?EƟlx?߃.mx?@mx?SF;nx?~nx?wGox?a4ox?%Tpx?]px?o l`qx?)qx?mrx?~x?[vx?x?O唀x?x?OUx?] 'x? ĭx?Ά3x?kC4x?l@x?߽Ƅx?yzLx?)7Ӆx?JYx?߆x?7nex?,x?)rx?E ax?c~x? x?Tx?$@x?)Wxx?b/x?5磌x?:*x?p@KWx? F6x?KƼx?~QBx?.W?6ɏx?\mOx?bՐx?x?I~įx?Jx?Zаx? À%Wx?=]ݱx?hcx?Էx?tpx?v1x?gux?mx?Gsdx?x!x?~Tx?U*x?Xİx?6x?d3x?kCx?àLx?r Ox?!x?ѱJ\x?@x?0hx?ºx?w)ux?>4ax?x?ٮx?Lkx?(@x?wx?Z x? _x?-x?iVx?9x? Tƿx?wEx?&5x?mRx?#Hx?5)^x?.x?4Lkx?C:x?Vx??#Kx?Zx? Wx?MKx?dx?9x?[#qpx? )?x?.|x?j4x?:vPx??3x?xEx?'Kx?Pj/x?V'g(x?6\䞮x?a4x?g^x?DmFAx?r}x?xMx?R~Rx?%Zx?\x?`fx?Fx?sx?o;x?}sx?ͫ:x?}x?,x?ܼqRx?.x?;x?ͨ*x?e1x?I"i7x?ߠx?Cx?WYx?HPx?x?e\x?Nx? 'ix?t ^x?#ux?Bx?y?1#=y?(yuy?.6y?@4y?9!y??mTy?NE*-y?Jóy?P9y?\Va3y? \kFy?aۢy?jgRy?mUy?rJ_y?yxρy?(~k y?؃I y?)x y?6` y?攀 y?= y?E y?? y?tw y?S1#y?y?0y?ahVy?%<y?y?oӟHy?\5y?mUy?~֤y?-ay?Py? Lny?;ʃy?zy?Ey?J +y?b y?|y?X9y?# y?(A&y?f.pyy?4-2y?9y?u? ?y?$EdXy?J!Ky?Py?2VWy?[X7y?aody?AgҦy?lpy?rLy?Ox N} y?}ƅ!y?!y?]@"y? ,"y?d#y?kw#y?4($y?ʥ $y?zC5%y?)k{%y?ض(A&y?&y?7¢"N'y?_Z'y?Z(y?F(y?ؖg)y?S9)y?Tqs*y?ͨ*y?+y?bG,y?P,y?‡-y?p-y? <.y?..y?f+/y?.s/y?"070y?( 0y?<.ED1y?3g}1y?9$P2y?K?2y?D$]3y?J[\3y?YPi4y?V4y?[v5y?gaO;5y?g s6y?lɪ7y?ur7y?%xC8y?}R8y?!9y?3z9y?7-:y?0:y?Ah:;y?n;y?+Fy? >y?Ǚ&l?y?lV^?y?x@y?@y?zލAy?*J= By?uBy?ĬCy?8Cy?>$Dy?SDy?F0Ey? vöEy?3Uby?Dby?VJcy?P,cy?UIddy?d[dy?a+ey?f ey?rl=C8fy?"rzfy?wDgy?}tgy?01"Qhy?߈Yhy?]iy?>hiy?%jjy?8jy?Lpvky?\ky?ly?[ my? Omy?Pny?i ny?!oy?҇.oy?wDf.py?'py?:qy?{ qy?58EGry?|ry?Ssy?Cpsy?-$`ty? [ty?Qluy?duy?!yvy?`":vy?(rwy?-X xy?n3xy?9yy?>Qyy?|DL$zy?,J zy?O0{y?U0{y?:[@h=|y?`|y?fI}y?Hlw}y?q4GV~y?w~~y?V}by?ky?(&oy?e]y?{y?ę_y?sy?"<y?Ҫty?Sy?1䠄y?'y?Sy??G3y?ùy??y?M~2Ƈy?;jLy?҈y?[Xy? r߉y?/Iey?jy?qy?gy?x $(~y?'_y?y?[y?6"y?'>y?-vy?D3O)y?8 毐y?>6y?RDUy?JCBy?OȒy?aUNy?[z4Փy?`7l[y?ofy?lgy?qny?}w+Kty?,}y?܂y?by?;*y?ay?y?IVy? y?@,y?Wxy?J8y?辜y?fEy?ǁW˝y?>Qy?tמy?#ظ]y?u6y?2njy?2y?vy?iy?@&My? y?y?N ^y?,y?c"y?\y? "R.y?' y?k-B;y?3zy?8FGy?y>ͨy?(D!Ty?I}Yکy?O:`y?7Uy?Zmy?`q8y?Ef.pyy?ky?q߅y?Swe y?}"Oy?߆y?ay?Y$y?.y?pe1y?y?ϤM=y?~ IJy?-DJy?ݵ|гy?AVy?<ܴy?ƻ#cy?x[y?J5oy?y?ݯ|y?Xl:y?)ry?y?fᔹy?`y?Qy?uۈ'y?$ y?U3y?0y?2g@y?!ƽy?'ILy?A-Ӿy?2FYy?8~߿y?O>=ey?Cy?I%ry?]Ot]y? U1~y?Zy?k`y?fh<y?k%ty?zqy?)wy?|\*y?Sy?7֊6y?獓¼y?PBy?F 2y?iOy?y?TD[y?y?Hhy?b{y?8ty?y?q̲'y? o_y?,y?y?.y?c> y? vy?<ݭ,y?y?W9y?KUy? ҌEy?y?YLQy? 4y?!k^y?g'y?-@jy?2y?v8Jwy?%>wy?C4y?I y?3O)y?Tkay?Z(y?B`"y?ey?k_@/y?Pqxy?vٯ;y?|y?^SHy?Wy?͎Ty?ly?G`y?˞6y?{mmy?*~y?ٯ;yy?y?8Ly?r y?/y?Gy?ѩ+y?fc%y?U#y?1y? y?cZB>y?zy?ԱJy?qy?!O!Wy? Yy?ɐcy?/y?Cpy?!8y?='o|y?,zy?27߈y?L8y?=Ny?Cny?ZI+y? O'y?T-y?hZbe4y?`y?e@y?vk y?&qVDMy?v|y?|гYy?4y?J#fy?[y?BĒry?y?>y?Q9y?qy?uy?_2y?y?Py?mi*y?&y?6y?{נ/y?+]gCy?y?Oy?9y?QF\z?~z?G˵hz?z? F%uz?V]z?z?}z?d!:z?';z?,sz?r2q z?"8.z?=-z?CRz?0Ie9z?N"¿z?TE z?>Z1 z?_YiR z?e z?Lk^ z?p z?vMHk z?[| z? Ƿw z? z?iA'z?^ z?Șz?wxz?'5z?֩=#z?uz?5l/z?)z?<z?CƣTz?`Hz?z?RTz?ݗ3z?Tkaz?`z?mz?z?nHJzz?z?ùz?| z?,=)z?`z?z?:!t%z?&1z?,?2z?H2wz?7h>z?=%z?WCKz?IVz?N\W z?eT z?Zc!z?_5!z?sePmp"z?#k "z?p|#z?v$z?1|DL$z?%z?%z??{&z?8+&z?b('z?M'z?o4(z?, (z?\AA)z? y)z?cM*z?j *z? Z+z?˚X+z?xWf,z?(,z?r-z?7-z?6Ko.z?/z?ދ/z?D0z??N0z?1z?R 1z?w*2z?4-2z?ad73z?!3z?&kC4z?o,( 4z?2CP5z?7{5z?}=_\6z?-C6z?H"i7z?NZ7z?;TSu8z?Y8z?_9z?Ie9:z?jGq:z?p;z?Wv;z?|~!z?t//>z?#fF?z?ӣ?z?fR@z?2#@z?E_Az?}Az?@ZkBz?Bz?$xCz?Nё\Cz?NDz? Ez?]Ez? ;Fz?BsFz?k#Gz?Gz?y0Hz?y7RHz?( uRz?.v2Sz?{Sz?u?Tz?<2TTz?KUz?Uz?JiWVz?&3Vz?jdWz?XWz?]pXz?Xz?gI}Yz?Zz?QZz?u[z?$([z?ֈ`\z?E\z?3(]z?]z?|?5^z?A9w^z?A_z?_z?OqN`z? .V`z?Zaz?]az? efbz? "5bz?l&lscz?,cz?1Ydz?z7ez?)=Kez?Bfz?HMfz?8N gz?S*gz?Yb+hz?F_Ahz?d7iz?j iz?TpxADjz?v5yjz?{Pkz?bkz?l ]lz?)Xlz?qimz? mz?Н`unz?7nz?.noz?ޮpz?Tގpz?=qz?Mqz?ŋ!rz?KHrz?-sz?,sz?Yd:tz? dz?z?jGqz?L'z?}z? z?Z_&z? ^z?ٕz?h z?&Sz?+=)z?w1tz?&75z? Йz?%:z?+J z?M1AGz?6xͫz?٬z? H`z?MWz?iSulz?Y2z?^xz?wd6z?'jinz?o& z?uݑz?5{z?]Mz?$z?C׼z?0z?Q,z?Rd=z?˛õz?Iz?`E жz?CVz?zܷz?n|bz?9z?!oz?}гYz?,p{z?-z?z?:8z?dpz?!z?Hߠz?'z?YOz?W 3z?Ӿz??z?eM.z? fLz?%ǝz?s+Xz?#1A z?6Dez?<|z?1Bxqz?G5z?M#~z??S[z?Xlz?^)z?Ndz?i:z?o`rz?\u)z? {z?6z?jTQz?Bz?ɑz?xNz?(H0z?עh[z?Ÿz?6gz?<z?Ftz?D~z?sz?0z?S%z?֪]z?gz?a$z?z?<,z?o[tz?8z?z?}Ez?- PSz? Qz?z?;]z?D2z?%jjz?I+z?0{vz?68z?X;z?2uWvz?zGz?z?@Tz?KUz?`z?Nz?lz??4z?]kyz? z?vۅz?k3 z?Jz?ĭz?yjz?)'$z?)z?ۡa1z?7^z?=z?z?E@Jz?Rxz?Vz?Sz? cz?GWz?boz?z?~{z?p%;6z?+mz?0z?~6rݔz?.[{?{?{?F%u{?*2: {?0q {?T6, {?>!{?*6u!{?;J"{?A`"{?9GW#{?LT#{?Rc${?GXT${?]o%{?c3%{?Uik|&{?oH'{?tۈ'{?cz({?J({?…<){?r){?!'*{?іs)*{?0a4+{?/혺+{?ߧ@,{?g,{?>$@M-{?w-{?Y.{?L[.{?f/{?V/{?ZՒr0{? O0{? ~1{?h52{?m2{?C3{?wݗ3{?&4{?{L4{?8*5{?45{?66{?o+6{?C,cC7{?$7{?*O8{?Q0c 8{?6 B\9{?;y9{?_Ah:{?GW:{?L!u;{?nRX;{?X<{?]K={?|c={?+i7>{?no>{?t? ?{?:zަ?{?-@{?vN@{?H39A{?A{?EB{?Vj-B{?'eRC{?C{?d^D{?^ D{?øDkE{?s{E{?"ĕwF{?RF{?#G{?0Z H{?ډH{?FI{??I{?9#J{?}qJ{?M:/K{?K{?W{?W{?nKX{?mRX{?͐*WY{?}Y{?,cZ{?ܡa1Z{?ip[{?:۠[{?겘|\{?U]{?IH]{?^{?Ɍ^{?WI_{?'_{?^(`{?e`{?=4a{?a{?s=Ab{?#tub{?1Mc{?c{?1Zd{? iTd{?&fe{??e{?rf{?$]3f{?N*kg{?/עh{?5ڋh{?\;Qi{? AJi{?Fˁj{?jLj{?RE*k{?W)k{?y]`7l{?(c|l{?h9Cm{?nm{?6t?Pn{?ypwn{?-\o{?Do{?ip{?dVp{?S!uq{?q{?r{?aX5s{?ms{?Ҥt{?oܚt{?L!u{? Lu{?~ƃ-v{?-σv{?@9w{?*w{?;bFx{?wx{?4Ry{?J y{?A_z{?kyz{?X)k{{?{{? x|{?f`X|{?}{? ~{?t$~{?$*T7{?/o{?5Φ#{?2;ީ{?@H0{?FN{?@L…<{?Q‚{?WyX5{?~{?B{?LO{?LN{? {?ZZ{? .{?@fg{?i{?s{?ȷw {?w4E{?&|{?Ȯ{?k{?5(${?[{?ߢ{?C_+{?{?:8{?Qr{?SD{?{?_Q{? Q{?H]{?n{?i{?#0{?|)V{?v{?Kb{?5{? o{?U{?D?{{?{?#{?R)v4{?/3l{?4{?`:۠{?@j'{?E'K{?oK3{?Q{?V^?{?}\*{?,baL{?g{?mRX{?;s {?x@e{?~x{?IFq{?{?~{?W}W{?:{?|?e|?q6|?ı.n|?t)|?#ݯ|?e6|?"M|?1߄B|?Ӝ|?YN|?@,|?c[|?ꐛ|?NMg|? |?Bt|?\z|? B |?  |?j! |?yY |?6 |?y# |?() |?.m8, |?4*p |?6:8|??߾|?EaE|?EKO|?PۆQ|?V|?S\U]|?b.|?gej|?am|?sIv|?x |?o~D|?| |?Ή=|?~|?-#|?ݚt["|?1|?;.|?뫫|?h:;|?J%r|?G|?Ÿ|?X\T|?Q|?ֈ`|?fٓ|?Pl|? 0|?tgy|?$|?Dׅ|? |?2F |?|~!|? 9!|?@$"|?%"|?p]1#|?O#-#|?(=$|?.$|?]4dY1|?ϼv1|?٭e2|?.Ȗ2|?Sr3|?U3|?<͌~4|?ފ5|?G5|?K46|?k6|?~7|?Y;ۣ7|?*8|?J8|?g s69|?09|?B:|?u):|?%#gaO;|?($;|?.[<|?34<|?9[@h=|??x=|?AEկt>|?J>|?PO?|?PV W@|?[Ɏ@|?aA|?^gCA|? m6 B|?rmB|?lxz,C|?~7ݲC|?˃9D|?zLD|?*nEE|?ٔ+E|?QF|?8+F|?bc^G|?G|?FjH|? H|?VBwI|?UzI|?бJ|?͍ K|?cJ!K|?YL|?ĐL|?q"M|?!>M|?7/N|?oN|?/u;O|?3O|?HP|?= NP|?jTQ|?'Q|?K`R|?"-R|?(^emS|?Z.S|? 4yT|?9 U|?h?RDU|?E| V|?J̳V|?vPW|?&VF#W|?[[%X|?aX|?4g}1Y|?l:Y|?r9>Z|?BxqZ|?}qJ[|?.[|?PW\|?P\|?ec]|?_"]|?o^|?/^|?mYg|_|?`|?̶ֈ`|?{a|?+MFa|? ~b|?ǵb|?9ӄ'c|?A%c|?\4d|?G仔d|?x@e|?5e|?V;Mf|?sf|?mYg|?d*g|? fh|?Rh|?rari|?!i|?"~j|?(1k|?0.Uik|?3l|?9ؗl|?>?m|?DIHm|?J*n|?LP÷n|?U6o|?[='o|?[a^Cp|? gp|?ltOq|?ir1q|?x=\r|?}ur|?whhs|?'%s|?֎ut|?Tt|?5\u|?v|?v|?C3w|?Pkw|? x|?Qڦx|?‡-y|?DJy|?`9z|?Ӿz|?{E{|?n8){|?`R||?鲘||?|o^}|?,,}|??k~|?w~|?:dw|? !|?|?HV |?X|?"|?V(|?.5#|?3Lm|?e9 /|??ܵ|?D<|?sJ@L…|?"PH|?UΆ|?[wT|?1a4+ۇ|?fba|?l|??rkm|?w( |?}Az|?My|?_|? |?[ |? X|?S|?j%|?|?ɰ72|?xGo|?'>|?Đ|?~K|?6;Nё|?W|?صݒ|?Drc|?/-|?dp|?R臭|?f||?# |?`C|?{|? [|?o|?"|?Z(|?}"O|?,( 4|?-|?39A|?;9CqǛ|?>M|?DӜ|?IJzZ|?O7P|?Uf|?W[|?anr|?f+/|?flf|?r|?wb֋|?t}|?#E|?ӈ}|?V|?1*|?$|?\7|?@J|?C|?ʦ|?N;P|?>s֧|?\|?\Ǹ|? ui|?2R|?ku|?ެ|?i|?y&1|?(h|?|?]ؚ|?7!|?G|? -|?ER|?9|?&|?S"^F|?(F̱|?-R|?a3ٲ|?9}=_|?>:u|?pDk|?J|?Oqx|?~U.T|?-[닄|?` |?fe|?tA}|?FD1y|?I|?O|?TUh |?[%X|?`⏢|?bf(|?l\|?q75|?pwn|? }A|?ςP|? N|?.M|?ޓZ|?D|?<f|?줾,|?{ds|?K8|?|? |?YoC|?,{|?鲘|?gҦ|?c"|? Z+|?vݑ|?%7|?W|?9D|?3p|?P|?L|?A ]|?O|?i|?P@|?!u|?'.|?^-wf|? 34|?8Վ|?l> |?DkE|?I(}!|?{O崧|?*U-|?Z_$|?`\:|?8fٓ|?kF|?qS|?Gw;S|?|r|?_|?UG|?l|?Q|?c~x|?;|?¤|?q0 |?!rh|?е/|?ם|?/$|?fG|?#0|?=බ|?ם<|?Z&|?L^I|?ԕ|?U|?ZN|? =b|?t|?hn|? C|?{|?vS|?&z|?!7 |?'|?4-2|?2nj|?8+&|?B>٬|?C3|?IbI|?QO?|?Uܸ|?ZK|?_`V(|?f`X|?kЗ|?mqd|?wJ|?|?q}?{v}?+}}?ڍ>}?}?9U}?u}?2}?G}?4)}?il}?V&5}?ۻ}?ƠB}?d]K}?N}?׺}?rݔZ }?"Q* }?bg }?˙ }?0s }?E }?A }?>x }? } }?:}?L}?W}?!q}?['.+}? -}?268}?i8en}?>"D}?C}?wIQ}?'OYM}?T]}?ZӼ}?5`i}?eM,}?k dv}?CqǛ}?vӂ}?|A }?QB}?z}?x}?`5!}?!}?Y.}?nl}?):}?ͯ}?|8G}?,`p}?S}?}?:̗`}?TO}?l }?Hξ }?x!}?H.!}?Wf"}? #}?Ց#}?e< $}?D$}? |$%}?st%}?#10&}?#&}?![='}?1'h'}?,%I(}?2(}??8:V)}?=\r)}?Cb*}?MI*}?No+}?TPQ+}?\Z {,}? `-}?e-}?jkD0.}?qh.}?v/}?x|{נ/}?(8'0}?ׇF0}?~31}?6o1}?,?2}?%2}?D]L3}?c3}? X4}?R4}?}?W!'>}?'_[?}?,_?}?f2g@}?8@}?=>tA}?tCSvA}?#IB}?NC}?TC}?2ZGUD}?_D}?eE}?@k~E}?p;4,F}?vkF}?N|8G}?r۾G}?/EH}?\JH}? QI}?fI}?k#]J}?)J}?ʩajK}?yZK}?(vL}?غL}?@M}?7Nx N}? N}?O}?EׅO}?BW"P}?P}?S.Q}?yQ}?66;R}?bmR}?GS}?nS}?p +TT}?LT}?`U}?~bU}?-!lV}?&+V}?,cyW}?<2VW}?7ӅX}?= Y}?JCBY}?HJzZ}?NZ}?XT$[}?Z![}?_>Y1\}?ge\}?k=]}?pu]}?uv28J^}?$|o^}?ԁV_}?i_}?3&c`}?N`}?oa}?A]a}?{b}?-c}?Oec}?Qd}?Քd}?] e}? ƈDe}?E|'f}?lf}?׿3g}?|#g}?z9[@h}?)h}?Li}?pi}?8-:Yj}?qj}?ek}?F ek}?"rl}?Pl}?T~m}?!Yn}?&n}?b,/o}?2go}?7Mp}?q= ףp}? C*q}?HFq}?NA~6r}?.Tr}?YBs}?_x%s}?=e5]Ot}?jt}?p[u}?Kvlu}?{)w}?lu}? }?\ }?{}?*T}? }?&P"}?8, }?13/}?7k}?G=D;}?B}?HH}?UN{JΉ}?T8T}?Yڊ}?c_`}?eo)}?j,am}?rp}?!vy}?{c}? @}?/w }?ߌ}?W}?=}?V%}?}?LK1}?}?5>}?Zmē}? ?J}?Д}?h˹W}?vLݕ}?3c}?w}?&o}?j+}?'c|}?4}?҈}?^ }?CB}? y}?}?QS'}?!}? X4}?_&}?,G@}?1Ǟ}?m77M}?=~oӟ}?B;Y}?|Hߠ}?+Nf}?SrN}?Y/r}?9_}?d~}?jf-}?Hp#e}?u}?{ԗ}?VZ }?D}?{*}?d}?N6}?Ý #}?rZC}?"ɩ}?ѮBO}?֪}?09\}?߿yq}?6h}?>}?аu}?mP}?M*}?}?}?[a/}? g}?۞ }?i֦}?V-}? F}?w}9}?'}?JE}? %̴}?5&\R}?+ص}?1>^}?C7}?<;k}?Bus}?RH2w}?N}?S}?`YiR }?_&}?d}?nj}?p]1#}?ui}?|{נ/}?,ص}?ۆQ<}?H¾}?:H}?ꗈο}?ET}?H'}?^a}?|}?W9m}?}?=z}?epu}?-}? }?s֧}?#dT}?!}?%}?1}?X32}?k}??Ң>}?}? MK}?M J}?ǁW}?}?\ Ac}? &(}?+`p}?j1x}?75|}?<}?xB?}?(Hlw}?M)}?S}?6Y}?^`V(}?d}?Dj4}?o}?uT5A}?S{m}?ΤM}?}?aHZ}?L}?ƒf}?o}??~? v~?~?u~?.2~?U+~?%~?=+i7~?0&~?64D~?K^H0~?c 1~?i1~?Lo.2~?t~?7h>~?m5?~?׻?~?oB@~?|,G@~?+~NA~?A~?cZB~?9% &B~?*]gC~?0C~?H6WsD~?;D~?AQ~?ʉvR~?FR~?x!S~?'S~?}U.T~?:T~?5:U~?U~?q4GV~?D.lV~?SW~?W~?Rf`X~?#KX~?lY~?`Y~?%ZxZ~?**Z~?n0a[~?6 \~?;Nё\~?}A ]~?,G@]~?Lx$^~?RB^~?:X0_~?]_~?cyW=`~?Ii6`~?nIa~?ta~?Wzm6Vb~?*nb~?bc~?ec~?aod~?ĖMd~?sۄ{e~?#f~?ҧUf~?,g~?1cg~?Ḍh~?IӠh~?? 'i~?Bi~?πz3j~?N=j~??k~?!k~?\tYLl~? 1l~?Xm~?jm~?h8en~?&pn~?xqo~?(o~?]~p~?Oq~?6׆q~?$r~?*Qr~?D0.s~?5es~?;)t~?SAEկt~?G 6u~?LDu~?aR||Bv~?X9v~?]Nw~?oc#w~?ip[[x~?n-x~?~tgy~?-zy~?d:tz~?!rz~?;ީ{~?됛|~?X|~?IQ}~?҈}~?~~?XL~~? 0,~?g~?f8~?@׾~?E~?tϺFˁ~?$w~Q~?4ׂ~?]~?2%~?k]j~?(~?@v~?~?`<~?Ot ~? ګ~?~?]T~? S"~?$Ί~?k*.~?0H~?52;~?y;i~?)AG~?F<͌~?LT~?7RHڍ~?Ws`~?]0~?Ecl~?h'~?ng_y~?Tt$~?z΅~? ~?b[>~?v~?խ~?p$~? O~?ϡ U1~?~Ɍ~?.=~?ݲCÖ~?4J~?~?rPi~?!J~?~? W~?0EH~?c~?~?>$|o~?)9'~?/^|~?L5~?:pΈ~?@-~?ZF=~? Lu~?Qd~?iW!'~?]~?bT4~?whX~?&n@~?s~?y3M~?5Lk~? Y~?~?Cf~?@J~?r~?Q~?w~~?4)~?_`~?~?kЗ~?n(~??~?΢w*~?|_~?+6~?~?VC~?:S~?O~?~?H5\~?Hm~?h~?V ~?u~??F^?KK?eQE?W}W?\R?tbc?#h$?m\p?sF?1y|?~?};?@:s ? ? ?Nq ?.R( ?뉮 ?\4 ? e ?"1A ?jh ?ÜM?Y?yZ?(G?ِf?M?6 r?&?^?EA?͋??Sy=? 6u??a*?m?#*T7?o)狽?/C?4a?~:3P?-@j?E\?KU?;Qi?VI?\u?JbI?g?m(?Xs`?y=?~Ϛ?f! ?t? ?ŏ1w-!?t!?$9"?Ӡh"?%VF#?2#?ⱟR$?\$?@5_%?l%?ȓk&?OP&? x'?K'?]߇(? D )?)?k**?{b*?8#+?yѩ+?) 0,? pA,?-y<-?7-?H.?#d .?E)!XU/?.ޏ/?4a0?T:X0?@7n1?En1?bKz2?QL3?V 3?p\M 4? b4?g@5?m5?.s,&6?xwd6?~427?<Ӹ7?쉮 ?8?kC8?J({K9?9?W:?Y_":?Zd;?ّ;?gp<?S<?9}=?up>?%Ί>?G????3O@?~@?;(A?AA?.5B?rfB?P0AC?C? ND?^gED? $}ZE?E?l#fF?)[$F?.\sG?z4ՓG?*:H??OI?E ;I?8KrJ?PJ?VCK?F\K?aQ+L?gzL?Um77M?sM?x0DN?c~nhN?+PO?‰O?q]P?!bGP?КiQ?ܶQ?/uR?ޫV&R?^S?=ЕT?͎T?JU?K=U?t!V?ӁV?Z>-W? W?S:X?huX?2FY?Y?v2SZ?&jjZ?'_[? [?4l\?^I\?x]?B#ظ]?(^?.R( _?P4`_?:̗`??ϝ`?_EF$a?K?a?Pv0b?mV}b?\:WXp?lp?)dq?Lq?6qr?anr?[ }s? t?t?iUMu?#u?(ϼv?w.v?&4I,)w?9dw??Û5x?5Eӻx?J= By?PBy?CVzNz?[tz?a1Z{?Qg!{?mYg|?rh|?`x%s}?~}?8~?n\p??͔?|?,PO?ۥ ?ʾ+?:?D.8?f?H¾D?{ʄ?8 Q?VDׅ?ٲ|]?o?e,i?#?[v?sc?" ˂? ?:?1 Xr??!???"LQ.?( ?M.:?3?9@0G?[?g͏? ES?Jwِ?jP4`?VF?[~l?xak?'g(x?l%?r]?6x_ ?}͑??D<?St$??R0??GS=?`Ù?I?~Ϛ?o;2V?iܛ?ǵb?}r?,/o?H?ީ{?;f?#?'?I_?Z?Ϡ?W'? >?Ov3?e ???"Ƥ?t(CUL?#.ҥ?3X?9zަ?1?74e?Dk?Jq?@Pn?U+~?[J?Na?fb?l?\r)? xa?}V)?kѯ?6?Ɏ@?yJxB?(ȯ?؟N?հ?6>W[??g?Eu?26t?m?Sͬ?i?&?aL?䠄?]?p?+,?c?~R8?-Ӿ? E?B˺?<FzQ?׻?"]?J(}!?-:Yj?3?X9v??q?D.8?fJo ?P?Ue?u["?$aN"?f?lY.?2r?w-;?}e?AMG? ? T?OD?A|`??]l? x#?5[y?k?ʅ?l ?z):?)q?ң?`$?7?P1?闈?FT=??/J?Tg?IV? ?bc?F?=~o?p"? ({?-t%?31]?.9?>̔?Dh??u6?^ؚ? WB??lTO??K[?{?*3h?k? @t?8??wJ?F"4?'?-?U3k) ?9(a?>,?cDв?J_9?O@?qUwE?![?`SQ?f?/lV^?q?wGj?=}?5w?~m?L;? ??ZrL? /?"?h?f+/?ǻ#c?v;?&ǝ?Z H?B?4yT?ݑ?N`?B !?Xm??QBy??؂C?7?S?_ zo ?7XO?7???[?m?E2?"nN%?Ljh?'+? ?{-1?St?+3??8b->?@I?>e?a?9DܜJ?Ǻ?I?w?OV W?p4(?GUD?_ ?Z{c?ݮ?`?~k, ?VfJo ?-( ?l# ?>9 ?qZ| ?v ?dw ?<_E ?}>ʈ ? ? ?R ?r9 ?J U ?"uq ?T^ ?ѓ2 ? ?'?Xj?0?"4?ߤiP4?'Hlw?&?f-?>@?3ۃ??8 ?]/M?u>Y1\?77M?Di?%?IӠh?̱?nO?Fn1?UMu?+,?Z H?c> ?|` ?T㥛 ?,f!?bJ!?kA!? !?q&"?bBW"?:w^"?z"?|x #?Vc#?5Φ#?q#?H-$? !p$?=$?Y$?lu9%?K|%?V)%?.&?E&?!&?&?'8'?e`TR'?<-?p'?'?2(?ĵ^(?8ߡ(?s(?K>v()?"T3k)?C3O)?k)?I4*?΢w*?YO*?1ҋ*?Uj@+?H+?Z'.+?J ,?g`eM,??,?f,?-?k^Y-?<-?vq -?M(#.?%wDf.?`.?||.?s//?Rr/?\1е/?3/? <0?#0??0?[1?jhwH1?BF1?%1?2?!T2?2?x'2?P}:3?(-\Va3?:r3?23?*4?8m4?^4?6>4? q75?CP5z5?.Q5?I m6?lC6?DOʤ6?Ҩ6?T 7?eO7?ZD7?{"07?R`L8?*g\8?f8?蜟8?k{%9?Yh9?aq89?89?w*2:?Fu:?|b:?~:?oo>;?GN;?,;? ?c>?c'>?; >?-y<-??WXp??26t????q89@?I|@?!>@?A?CmFA?K7A?I*SA?WoB?/ORB?ŦB?TB?ׂC?Za^C?f?C?=`2C?M(D?eikD?蹅D?kD?tv4E?LqUwE?#3E?vE?,AF?|HF?dF?Z G?2kMG? IG? (G?H? ZH?h'H?@CH?_#I?_{fI?Ǟ=I?!I?v/J?N'rJ?&J?,"J?կt>ɋL?L?CM?hUM?kIG9M?B%UM?OqN?aN?TN?ןN?yZ~*O?Q\mO?(`;O?4O?eO7P?kzP?kP?_Q?7qrCQ?PۆQ?v/Q?  R?|.PR?mJR?EfR?S?f\S? ES?#S?{%T?S iT?+)T?ET?|a2U?Z}uU?!9U?aU?9'>V?V?,V?$W?2p@KW?pN\W?G8-xW? X?=WX?˚X?CX?~ƅ!Y?VIddY?-B;Y?O!WY?r-Z?TގpZ?׼Z?dZZ?4`?x`?+`?G`?wcAa?u!Va?L4a?$' b?Mb?,b? b?2&c?[kBZc?28J^c? (zc?=#d?fd?Cͩd?iƢd?AI0e?_!se?N>=e?Ye?Tt??I?6?x Rς?Pn?(vU?T?3ۃ??a?^?6!1脀?M+?&jin?H?,'?l7?D2z??7?˺,D?=^H?{??Y?}vuŌ?U?-|}K?[Ɏ?܁:э??X?c 8?;Tގ?p!?qd?P?.ꏀ?q -?Ip?!!?3?&O:?ek}?,D?W"?/2F?ډ?7̒??={.S?fYJ?=C8fٓ??H_?ӹ?N唀?tѐ(?LTo l?#M)?Y,E? a5?_|x?ǘ?Ze?2A? kc섗?Aȗ?p $ ??N?hv[?@wԘ?|?xZ?ǁW˝?6?w$?N g?&:?V횀?Ւr0?ms?K?\*?4v()?Cl?{_?{?5?upx?MNϻ?$ -? B?"?>Ȳ?Z ?[vN?3d? BԳ? !?Z?&?iᴀ?A,9$?yUg?1Xq?ȴ6?70?ws?O=බ?'?B=?m4?HLP÷?*l?]N I?5磌? Tƿϸ?֤?YU?a?l_@/ܹ?CK?efb?ۂ?j躀?혺+?zpwn?RU򱻀?)v4?*8?{E{?a?}?`D?8k? Jʽ?( ? Q?$?n@׾?F\?x]?_? >㿀?&?|&i?T?,,?;3?1uWv?Ss?72?b?€?:=Ƃ€?€?BÀ?ŊLÀ?Hi6À?qGRÀ?HN&nĀ? XĀ?S㥛Ā?Ā?Y!ŀ?~dŀ?W_]ŀ?.;1ŀ?eM.ƀ?hqƀ?jׄƀ?ƀ?ep:ǀ?=r}ǀ?vQǀ?/Ȁ?{,GȀ?GȀ?scȀ?ffffffffffff濚鿚쿚333333333333㿚쿚ffffff333333333333333333333333ffffff濚ffffff333333333333333333333333ffffff333333࿚ٿ333333ffffff쿚ffffff333333333333333333333333333333333333ffffff濚쿚鿚ffffffffffff333333333333333333333333࿚ٿٿffffff濚쿚ffffffffffffffffff濚쿚ffffffffffff333333333333ffffffffffff濚鿚쿚ffffffffffffffffffffffffffffffffffffffffff333333333333ffffff濚쿚鿚쿚333333333333333333ffffff濚ffffffffffffffffffffffffffffff濚鿚鿚鿚ffffff333333333333ffffffffffff濚쿚333333333333333333ffffff濚쿚ffffffffffffffffff濚ffffffffffff333333333333333333333333㿚鿚ffffffffffffffffff333333ffffff濚鿚쿚쿚鿚쿚ffffffffffff濚쿚333333333333ffffffffffffffffff333333333333ffffffffffff濚鿚鿚ffffff333333333333333333ffffffffffff濚鿚鿚ffffff333333333333333333㿚鿚鿚鿚鿚ffffff࿚ٿ333333ffffff濚鿚鿚鿚쿚ffffff333333333333ffffff濚쿚ffffff333333333333ffffff濚鿚ffffffffffffffffff濚鿚𿚙333333333333㿚鿚쿚鿚鿚鿚鿚ffffffffffff333333ffffff濚ffffff333333333333333333ffffff濚쿚ffffff濚鿚쿚鿚ffffff333333333333333333ffffffffffff濚쿚ffffffffffff333333ffffff濚鿚鿚쿚ffffff࿚ٿٿ333333ffffff쿚鿚鿚鿚鿚ffffffffffffffffff濚ffffffffffffffffffffffffffffff濚ffffff333333333333333333ffffff濚쿚鿚쿚쿚鿚ffffffffffff333333ffffff濚鿚쿚鿚鿚鿚鿚鿚쿚鿚鿚鿚ffffff333333ffffffffffff濚쿚ffffffffffff333333333333ffffffffffffffffffffffff333333ffffff濚鿚鿚鿚ffffff333333333333㿚쿚鿚ffffffffffffffffffffffffffffff濚쿚ffffff濚鿚鿚쿚鿚쿚鿚鿚鿚쿚鿚ffffffffffffffffffffffff濚쿚ffffffffffffffffff濚鿚鿚ffffff333333333333ffffff濚鿚鿚ffffff濚鿚ffffff濚쿚鿚쿚ffffffffffff333333ffffff濚鿚ffffff333333࿚ٿٿٿ333333ffffff濚쿚333333333333333333㿚鿚쿚ffffffffffffffffff濚쿚鿚鿚鿚鿚鿚鿚鿚鿚쿚ffffff333333333333ffffff濚쿚ffffffffffff濚鿚ffffff333333333333ffffff濚쿚鿚ffffff濚ffffff濚쿚쿚ffffffffffffffffffffffff濚鿚쿚ffffff333333333333333333333333ffffff濚쿚ffffffffffff333333ffffff쿚鿚鿚ffffff333333333333ffffffffffffffffff333333333333333333333333333333333333ffffffffffff濚쿚ffffff333333333333ffffff濚쿚ffffff333333333333ffffffffffffffffffffffff濚쿚ffffffffffff濚鿚鿚鿚鿚鿚쿚ffffffffffffffffffffffff333333ffffffffffff濚쿚ffffffffffff濚쿚ffffffffffffffffffffffffffffffffffff333333333333ffffffffffff濚鿚鿚ffffff333333333333333333ffffff濚鿚鿚鿚鿚鿚ffffff333333333333333333㿚鿚鿚鿚鿚쿚ffffff333333ffffff濚鿚鿚ffffffffffff333333࿚ٿٿٿ333333333333333333333333333333ӿɿɿ333333ӿ333333ffffff濚ffffff333333࿚ٿٿٿ333333ffffff쿚333333㿚ٿ333333ӿ333333ӿٿٿٿٿٿٿٿ333333ffffff濚쿚ffffff333333࿚ٿٿٿffffff濚쿚鿚ffffff333333ffffff濚鿚쿚ffffffffffff333333ffffff濚鿚鿚鿚ffffff333333࿚ٿٿٿ333333ffffff쿚鿚鿚鿚鿚ffffff333333ffffff쿚ffffffffffff333333333333ffffffffffff쿚333333333333ffffff濚ffffffffffff333333333333ffffff濚쿚鿚ffffffffffffffffffffffff333333333333333333ffffff濚쿚鿚ffffff333333ffffff쿚ffffffffffffffffff濚鿚ffffffffffffffffff濚ffffffffffff333333333333333333ffffff쿚鿚ffffff333333333333ffffffffffff濚鿚鿚鿚ffffffffffff333333ffffffffffff333333333333333333333333333333333333ffffffffffffffffff333333࿚ٿ333333ffffff濚쿚ffffff333333333333333333333333࿚ٿ333333ffffff濚鿚ffffff333333ffffff濚쿚ffffff333333333333㿚ffffff333333࿚ٿ333333ffffff濚ffffffffffffffffffffffffffffff濚鿚鿚ffffff333333㿚ٿٿٿ333333ffffff濚鿚ffffffffffff333333333333ffffff濚鿚ffffffffffffffffff濚鿚鿚쿚ffffff333333333333ffffff濚ffffff333333333333ffffff濚쿚333333333333ffffffffffff333333333333333333ffffffffffff濚333333333333333333333333ffffff濚ffffffffffff濚ffffffffffffffffffffffffffffffffffff濚鿚ffffffffffffffffff333333333333333333333333333333333333࿚333333ffffffffffffffffffffffffffffff濚鿚鿚鿚ffffff333333333333ffffff濚쿚ffffff333333333333ffffff濚鿚ffffff333333࿚ٿٿ333333ffffff濚ffffff333333ӿٿٿ࿚ٿ333333ӿ333333ӿ333333ӿٿٿٿٿٿٿ333333ffffffffffff࿚ٿٿ333333ffffffffffffffffff333333333333ffffffffffffffffff333333㿚ٿ333333ffffff濚쿚ffffff333333333333ffffff濚鿚ffffff333333333333ffffffffffff濚鿚鿚鿚鿚ffffffffffff333333333333333333333333࿚ٿٿ333333333333ffffff濚쿚333333࿚ٿ333333ӿٿ333333333333࿚ٿ333333ӿ333333ӿ333333ӿٿ333333333333ffffffffffffffffff333333333333333333333333333333333333ffffff濚쿚ffffff333333333333ffffff쿚ffffff333333333333333333ffffffffffffffffff333333࿚ٿٿ333333333333333333333333㿚ٿٿ333333ffffff333333ffffffffffffffffff333333࿚ٿ333333ӿ333333ӿ333333ӿٿ333333㿚쿚鿚ffffffffffffffffffffffff濚ffffffffffff333333333333333333࿚ٿ333333㿚쿚ffffff333333333333333333ffffff濚ٿ333333ӿٿٿ333333333333ffffffffffffffffffffffffffffff333333333333333333333333ffffff333333333333ffffff쿚333333࿚ٿffffffffffff濚鿚ffffffffffff333333333333333333ffffff濚鿚鿚鿚鿚ffffffffffff333333㿚ٿ333333ӿٿٿ333333ffffff濚쿚333333࿚ٿ333333㿚ffffffffffff333333ffffff濚鿚쿚ffffff333333ffffff쿚ffffff333333333333ffffff濚鿚鿚鿚鿚鿚鿚鿚鿚ffffffffffffffffff濚쿚ffffff333333333333ffffff濚쿚鿚ffffffffffffffffff濚ffffff333333࿚ٿ333333ffffff濚鿚333333333333333333ffffffffffff濚ffffff333333333333333333ffffff濚쿚333333333333333333333333333333ffffff333333ffffffffffffffffffffffffffffff333333333333ffffffffffff濚鿚쿚ffffff333333333333333333333333ffffffffffffffffff333333333333333333ffffff濚ffffff333333333333ӿ333333ffffffffffff333333333333333333333333㿚쿚鿚ffffffffffff濚鿚鿚鿚鿚鿚鿚ffffffffffff333333࿚ٿٿ333333㿚쿚ffffff333333333333ffffff濚鿚ffffffffffffffffffffffff333333333333333333ffffff濚鿚鿚333333࿚ٿ333333ffffff濚쿚鿚鿚鿚鿚ffffff333333333333ffffff濚ffffffffffff333333333333ffffff濚ffffff333333ffffff濚쿚鿚ffffff濚쿚ffffff濚鿚鿚鿚ffffffffffff濚쿚鿚ffffff濚鿚鿚鿚鿚쿚鿚鿚鿚鿚ffffffffffffffffff濚鿚ffffffffffff333333ffffff濚쿚333333333333333333ffffff濚쿚鿚쿚쿚鿚鿚鿚鿚鿚ffffffffffff333333ffffffffffff濚鿚ffffffffffff333333333333333333333333333333ӿ333333333333ffffffffffff濚쿚쿚333333ffffffffffff濚쿚鿚鿚鿚鿚鿚쿚ffffff333333333333333333ffffffffffff333333333333ӿ333333ӿٿ࿚ٿٿffffff濚鿚쿚ffffff333333ffffff濚쿚鿚鿚鿚쿚鿚ffffffffffffffffffffffff濚쿚ffffffffffffffffff濚鿚鿚ffffff333333333333333333ffffffffffffffffff333333333333ffffff濚鿚鿚鿚ffffff333333࿚ٿ333333ffffff濚鿚ffffff333333333333ffffff濚쿚ffffff333333333333ffffff濚쿚ffffff333333ffffff濚ffffffffffff333333333333333333ffffffffffffffffff濚鿚鿚鿚쿚ffffff333333ffffffffffffffffff333333333333ffffff濚鿚鿚ffffff濚鿚鿚鿚鿚ffffff濚鿚ffffffffffff࿚ٿٿٿ333333ffffff쿚ffffff333333333333ffffff濚鿚쿚ffffff333333333333333333ffffff濚鿚鿚鿚ffffffffffffffffff濚ffffffffffffffffff濚鿚쿚鿚鿚𿚙333333ffffff濚ffffff333333333333ffffffffffffffffff333333333333ffffffffffff濚鿚鿚ffffff333333333333ffffff濚ffffffffffff濚鿚쿚ffffff333333333333333333ffffffffffffffffffffffffffffffffffff濚鿚쿚ffffffffffff333333333333333333333333333333࿚ٿ࿚ٿffffff濚쿚333333࿚ٿ333333㿚쿚ffffffffffffffffff濚쿚鿚鿚鿚ffffff333333࿚ٿffffff濚鿚ffffff333333333333ffffffffffff333333㿚ٿ333333ӿٿ333333333333333333333333ffffffffffffffffffffffff333333333333333333333333ffffffffffff濚쿚ffffffffffff333333ffffffffffff濚鿚쿚ffffffffffff333333333333ffffffffffff濚鿚쿚鿚ffffff࿚ٿ࿚ٿٿ333333ffffff쿚ffffffffffff333333ffffff쿚ffffffffffff333333ffffff濚鿚鿚鿚鿚鿚鿚ffffffffffffffffffffffffffffff濚ffffff333333333333333333ffffffffffff濚쿚ffffff333333333333ffffff濚쿚ffffffffffffffffffffffffffffff333333࿚ٿ333333333333ffffff濚鿚鿚ffffff333333ffffffffffffffffffffffff333333333333333333333333333333333333ffffff쿚333333ffffffffffffffffffffffffffffff濚쿚鿚쿚鿚鿚鿚鿚ffffff333333333333333333333333ffffff濚鿚鿚ffffff333333ffffffffffffffffff333333࿚ٿ333333333333333333333333ffffffffffff濚쿚鿚鿚鿚ffffff333333࿚ٿ333333㿚333333333333ӿٿٿ333333㿚鿚ffffff333333ffffffffffff濚쿚鿚ffffff濚鿚鿚ffffffffffff333333333333333333333333㿚ٿٿٿٿ333333ffffff333333ffffff濚鿚쿚ffffff333333333333333333ffffff濚쿚鿚鿚鿚鿚쿚ffffff333333333333ffffff쿚ffffff333333333333ffffff濚ffffffffffffffffff濚ffffffffffffffffffffffffffffff濚鿚鿚쿚333333333333ffffffffffffffffff333333333333ffffff濚鿚鿚ffffffffffff濚𿚙ffffff333333333333333333ffffffffffff濚鿚鿚鿚鿚ffffffffffffffffff濚쿚ffffff333333333333ffffffffffff濚쿚ffffffffffff333333333333ffffffffffff濚쿚鿚ffffff333333333333ffffff濚ffffff333333333333ffffff濚鿚ffffff333333333333ffffff濚鿚쿚ffffff࿚ٿɿ333333࿚ٿٿ333333ӿ333333333333333333࿚ٿٿffffffffffff333333㿚ɿ333333࿚ٿ333333ӿٿffffff濚鿚ffffffffffffffffff濚쿚鿚鿚鿚쿚鿚333333࿚ٿٿٿٿ333333ffffff濚쿚ffffff333333333333ffffffffffff濚ffffff333333333333ffffff쿚鿚ffffff333333ffffffffffff濚쿚鿚쿚鿚鿚鿚鿚쿚ffffff333333ffffffffffffffffff濚鿚鿚ffffff333333࿚ٿffffff濚쿚333333࿚ٿٿٿ333333ffffff쿚ffffff333333333333ffffffffffff濚鿚鿚ffffff333333333333333333ffffff쿚鿚ffffffffffff濚鿚쿚쿚ffffff333333ffffffffffffffffffffffff333333333333ffffff濚ffffff333333࿚ٿ333333㿚쿚鿚ffffffffffffffffff濚鿚鿚鿚쿚333333333333333333ffffff쿚鿚ffffffffffff濚쿚鿚鿚鿚鿚鿚鿚쿚鿚鿚鿚쿚鿚ffffffffffffffffffffffff濚쿚ffffffffffffffffffffffff濚쿚ffffffffffffffffff濚쿚ffffffffffff濚쿚ffffffffffff濚鿚쿚쿚鿚쿚鿚ffffff333333ffffffffffff濚쿚鿚鿚鿚쿚ffffff333333333333ffffffffffff濚鿚鿚쿚ffffff333333333333333333ffffff濚鿚鿚鿚鿚鿚鿚鿚ffffffffffff333333ffffff濚ffffff333333333333ffffffffffffffffffffffff濚쿚鿚鿚鿚鿚ffffffffffffffffff濚鿚쿚333333࿚ٿ333333ffffff濚쿚鿚鿚鿚쿚鿚ffffff濚鿚鿚鿚쿚ffffff濚鿚쿚쿚鿚ffffff濚鿚鿚鿚鿚쿚鿚鿚鿚鿚ffffffffffffffffff濚鿚ffffffffffff333333ffffff濚ffffff333333ffffff濚쿚鿚쿚쿚쿚ffffffffffff濚鿚鿚鿚ffffffffffff濚쿚鿚鿚鿚쿚鿚쿚鿚쿚鿚鿚ffffff333333࿚ٿ333333333333㿚鿚鿚鿚鿚쿚鿚鿚鿚ffffff333333333333ffffffffffffffffffffffff濚쿚鿚鿚鿚鿚ffffffffffffffffff濚鿚쿚ffffffffffffffffff濚鿚쿚鿚鿚鿚쿚333333࿚ٿ333333ffffff쿚ffffffffffffffffff濚쿚ffffffffffffffffffffffff濚쿚鿚ffffff333333333333333333ffffffffffff濚쿚쿚鿚ffffff濚鿚鿚鿚鿚쿚ffffff333333࿚ٿٿ333333㿚鿚쿚鿚鿚鿚쿚鿚쿚鿚쿚쿚鿚鿚鿚鿚鿚ffffffffffff濚쿚ffffffffffffffffff濚ffffff333333333333333333ffffffffffffffffffffffff333333333333ffffffffffff濚쿚쿚鿚鿚쿚鿚鿚鿚鿚鿚ffffff333333333333333333333333ffffffffffff濚ffffff333333㿚ٿ333333ffffff쿚ffffffffffffffffffffffffffffff濚鿚鿚鿚ffffffffffff333333ffffffffffff333333333333333333333333ffffffffffffffffffffffffffffff濚鿚쿚ffffff333333333333333333333333ffffffffffffffffffffffff濚鿚鿚鿚鿚鿚鿚鿚ffffff333333࿚ٿٿٿ333333㿚ffffff333333333333ffffff濚鿚ffffff333333333333ffffff濚쿚ffffff333333ffffff濚鿚鿚鿚쿚鿚鿚鿚鿚ffffffffffff333333333333ffffffffffff쿚鿚鿚ffffffffffffffffff濚鿚쿚ffffff333333333333ffffff濚鿚鿚鿚ffffffffffff333333333333ffffff濚쿚ffffff濚쿚鿚ffffffffffffffffff濚ffffffffffffffffff濚鿚쿚鿚鿚𿚙333333࿚ٿ333333㿚鿚ffffffffffffffffffffffffffffff濚ffffff333333333333333333333333ffffffffffffffffffffffff濚쿚ffffffffffffffffff333333ffffff濚鿚쿚ffffffffffff333333ffffff濚쿚ffffff333333333333333333333333࿚ٿ333333ffffff濚鿚333333333333ffffff濚鿚鿚鿚ffffffffffff333333333333ffffff濚쿚ffffffffffff333333ffffffffffff濚쿚ffffffffffff333333333333ffffff濚쿚ffffff333333࿚ٿٿffffff濚鿚ffffffffffff333333ffffffffffff333333333333࿚ٿ333333ӿ333333ӿ333333ӿٿ333333333333ffffffffffff濚鿚鿚鿚쿚쿚鿚鿚鿚鿚鿚ffffffffffff333333333333333333ffffff쿚ffffff333333㿚ٿ333333ffffff濚鿚ffffff333333333333ffffff濚쿚ffffffffffffffffffffffff濚鿚ffffff333333࿚ٿffffff濚쿚ffffffffffff333333333333333333333333333333ffffff濚鿚쿚ffffff333333333333ffffffffffffffffffffffff333333333333ffffff濚鿚鿚ffffffffffff濚ffffff333333333333ӿٿɿ333333ffffff濚ٿٿ333333ffffffffffffffffff333333333333ffffff333333333333333333ffffffffffff濚鿚쿚ffffff333333333333ffffff濚ffffff333333333333333333333333ffffffffffff濚쿚ffffffffffff333333ffffff濚鿚ffffffffffffffffffffffffffffff濚ffffff࿚ٿٿٿffffffffffffffffff333333333333333333333333333333333333333333333333ffffff濚쿚ffffff333333࿚ٿ333333333333ffffff濚ٿffffff333333333333ӿٿffffff濚鿚쿚ffffff333333333333333333333333333333333333ffffff濚쿚333333࿚ٿٿ333333ffffffffffffffffffffffffffffffffffff333333333333333333333333333333333333333333ffffffffffffffffffffffff333333333333ffffff쿚333333㿚ٿٿٿٿ333333࿚ٿٿٿٿٿٿ333333ӿ333333ӿٿ333333ffffff濚鿚ffffff333333ӿffffffffffffffffff333333333333333333ffffff濚鿚ffffff333333333333ffffff濚쿚ffffff333333333333333333ffffffffffff濚ffffff333333ӿ333333ӿ333333ӿ333333ӿɿ333333ffffffffffffffffff333333333333333333ffffffffffff333333333333333333ffffff濚鿚ffffff333333333333࿚ٿ333333ӿ333333ӿٿٿ333333ffffffffffffffffff濚鿚ffffff333333333333ffffffffffffffffffffffff333333333333ffffffffffff濚ffffff333333࿚ٿ333333ffffff濚ffffffffffff333333333333333333333333333333333333࿚ٿ333333ӿ333333ӿ333333ffffffffffff333333333333ffffff濚鿚鿚鿚ffffffffffff333333࿚ٿٿٿ333333ffffff濚鿚ffffff333333333333ffffff濚鿚鿚鿚ffffff333333333333ffffffffffff濚ffffff濚쿚ffffff333333333333ffffff쿚ffffffffffff333333ffffff濚쿚鿚鿚ffffff333333333333333333㿚쿚ffffff333333࿚ٿ࿚ٿٿٿٿ333333333333333333333333ffffff濚쿚鿚鿚ffffff333333333333333333ffffff濚鿚ffffffffffff333333333333333333ffffff濚鿚鿚鿚ffffffffffff333333333333ffffff濚쿚ffffffffffffffffff濚鿚ffffffffffffffffffffffff쿚ffffffffffff333333333333ffffffffffffffffffffffffffffff濚鿚鿚ffffffffffff333333ffffffffffffffffff333333࿚ٿٿ333333ffffff쿚鿚ffffff333333333333ffffffffffff濚쿚ffffff333333333333ffffffffffffffffff333333ffffff濚ffffffffffff333333࿚ٿ333333333333333333333333333333ffffffffffff濚쿚鿚鿚鿚쿚鿚ffffffffffffffffffffffffffffffffffffffffffffffff333333333333333333333333333333333333333333333333ffffff濚쿚ffffffffffffffffffffffff쿚ffffff濚鿚쿚鿚鿚쿚쿚쿚鿚鿚鿚鿚ffffff333333333333333333ffffff쿚鿚ffffffffffffffffff333333ffffff濚鿚鿚鿚鿚ffffff333333࿚ٿ333333ffffffffffff濚ffffff333333333333ffffff濚鿚ffffff333333࿚ٿٿٿ333333ffffff쿚鿚ffffffffffffffffffffffffffffffffffffffffff333333333333ffffff濚ffffff333333࿚ٿ333333ffffff濚쿚ffffff333333333333ffffff쿚鿚鿚鿚쿚ffffff333333㿚ٿٿٿ333333ffffff濚쿚鿚鿚鿚鿚ffffffffffffffffffffffffffffff333333333333333333ffffffffffff333333333333333333࿚ٿ333333ӿٿ333333ffffff濚쿚ffffffffffff333333333333ffffff쿚ffffffffffff濚ffffffffffff333333333333ffffff濚쿚ffffffffffff333333333333333333ffffff濚鿚ffffffffffffffffff濚鿚鿚ffffff濚쿚ffffff333333㿚ٿ333333ffffff쿚ffffff333333333333333333ffffff濚ffffffffffffffffff333333333333333333333333ffffff濚쿚333333ffffffffffff濚ffffffffffff333333333333333333333333ffffff濚쿚鿚鿚ffffffffffff333333333333ffffff濚鿚쿚鿚鿚쿚鿚鿚鿚鿚鿚鿚鿚鿚쿚鿚ffffffffffff濚쿚333333333333ffffffffffffffffffffffff濚쿚ffffff࿚ٿٿٿٿffffff濚쿚ffffff333333㿚ٿ333333ӿٿٿٿ333333333333333333333333333333333333ffffff333333ffffffffffff333333333333333333ffffff濚ffffffffffffffffff333333333333333333ffffff濚쿚鿚鿚鿚쿚ffffff濚鿚鿚ffffffffffffffffffffffffffffffffffff333333333333333333333333ӿɿ333333ӿٿ333333333333ffffffffffff쿚쿚鿚鿚ffffffffffff333333ffffffffffff쿚쿚ffffffffffffffffffffffff濚쿚ffffffffffff333333333333ffffffffffff濚쿚鿚鿚鿚鿚ffffffffffffffffff濚𿚙ffffff333333333333ffffff濚쿚ffffff333333333333ffffff濚鿚쿚鿚鿚ffffffffffffffffff333333333333ffffff濚鿚鿚ffffff333333࿚ٿٿٿffffff쿚鿚鿚鿚鿚쿚鿚鿚ffffffffffffffffffffffff濚鿚ffffffffffffffffffffffffffffffffffffffffffffffff濚鿚ffffffffffffffffffffffffffffff333333333333ffffffffffff濚鿚ffffff333333333333333333ffffffffffffffffff濚ffffff333333333333333333ffffffffffffffffffffffffffffffffffff濚鿚鿚쿚鿚鿚ffffff333333333333333333ffffff濚쿚鿚鿚쿚鿚鿚鿚ffffff333333ffffffffffff濚鿚鿚ffffff࿚ٿ333333ӿٿٿ333333333333㿚ffffffffffff333333333333ffffff濚쿚ffffff333333333333333333333333ffffff쿚333333ӿ333333ӿٿ333333㿚鿚ffffff333333ffffff濚鿚쿚ffffffffffffffffff濚鿚쿚鿚ffffff333333333333333333ffffffffffffffffff濚鿚쿚鿚ffffffffffff濚ffffffffffffffffff333333333333333333ffffff333333333333333333333333ffffff濚鿚鿚ffffff333333333333333333ffffff쿚ffffff333333333333ffffff濚쿚ffffff333333333333ffffff濚ffffffffffff333333333333333333࿚ٿ333333ӿٿffffff濚쿚ffffffffffffffffffffffff濚쿚鿚鿚鿚쿚鿚鿚鿚ffffffffffffffffffffffffffffff333333333333ffffff濚鿚ffffffffffff333333333333ffffffffffff濚쿚ffffff333333333333ffffffffffff濚鿚𿚙ffffff333333333333ffffffffffffffffffffffffffffffffffffffffff333333ffffff333333333333333333333333ffffffffffff濚鿚ffffff濚ffffff濚鿚鿚ffffffffffffffffffffffff濚鿚鿚鿚鿚鿚鿚鿚쿚鿚ffffffffffff濚鿚쿚ffffffffffff333333ffffffffffff濚鿚ffffff濚ٿffffff333333333333333333ffffff濚쿚ffffffffffffffffff濚鿚ffffffffffffffffff濚쿚鿚ffffffffffff濚鿚쿚ffffffffffffffffffffffff濚鿚ffffffffffff濚쿚鿚ffffffffffffffffff濚鿚鿚鿚쿚333333333333333333ffffff쿚ffffff333333ffffff濚ffffffffffff333333ffffff濚鿚ffffffffffffffffffffffff濚쿚333333ffffffffffffffffffffffffffffff333333ffffffffffff濚鿚鿚쿚ffffff333333㿚ٿ333333㿚쿚333333333333ffffff濚쿚쿚鿚𿚙333333࿚ٿ333333ffffff쿚鿚鿚鿚ffffff333333333333ffffffffffff濚鿚鿚ffffffffffffffffff濚쿚鿚鿚鿚鿚鿚鿚鿚鿚鿚鿚鿚鿚鿚鿚ffffff333333333333333333ffffff濚鿚鿚ffffffffffff333333333333333333333333333333333333ffffffffffff濚ffffff333333࿚ٿ333333ffffff濚𿚙333333333333㿚鿚쿚鿚鿚鿚쿚333333࿚ٿ333333ffffff쿚ffffff333333333333333333333333333333333333ffffffffffff333333333333333333ffffff濚쿚쿚鿚ffffff濚鿚鿚鿚ffffffffffff333333333333333333ffffff濚ffffffffffffffffff濚鿚쿚鿚鿚ffffffffffff333333ffffff濚鿚鿚鿚쿚ffffff333333333333ffffff濚쿚鿚ffffffffffffffffffffffff濚쿚ffffffffffffffffffffffff쿚333333࿚ٿٿffffffffffff濚쿚ffffff333333333333333333333333ӿ333333333333ffffffffffffffffff濚쿚鿚ffffff333333333333333333ffffff濚쿚鿚鿚鿚ffffffffffff濚쿚ffffff333333333333㿚쿚ffffffffffff333333333333㿚鿚鿚鿚鿚鿚ffffffffffffffffffffffff濚鿚ffffffffffffffffff濚鿚쿚ffffffffffff333333333333333333333333333333333333㿚쿚ffffff333333333333ffffffffffff쿚ffffffffffffffffffffffff濚쿚ffffffffffff333333333333ffffffffffff濚쿚333333333333333333ffffff濚쿚ffffffffffffffffffffffff濚ffffffffffff333333333333ffffffffffff333333333333333333ffffff쿚333333࿚ٿٿٿٿٿ333333333333333333࿚ٿ333333333333ffffffffffffffffff333333࿚ٿٿffffff333333333333333333333333㿚쿚ffffff333333ӿٿٿ333333ffffff濚鿚鿚鿚ffffffffffff333333333333ffffffffffffffffff濚鿚鿚鿚ffffff࿚ٿٿٿٿ333333ffffff濚ffffffffffff333333333333333333ffffff濚ffffffffffff333333333333ffffffffffff濚鿚쿚ffffffffffff333333ffffff濚鿚鿚ffffffffffffffffffffffff濚쿚333333333333ffffffffffff濚ffffff333333333333333333333333ffffff濚쿚ffffffffffff333333333333ffffffffffffffffff333333ffffff濚鿚333333333333333333333333333333333333333333333333333333333333ffffff濚쿚ffffff333333ffffff쿚ffffff333333333333ffffffffffffffffff333333333333333333ffffffffffffffffff濚ffffffffffffffffff࿚ٿٿ333333ffffff쿚鿚鿚ffffff333333ffffffffffffffffffffffff濚ٿffffff濚쿚ffffff333333333333333333ffffffffffff濚ffffffffffff333333333333333333333333333333333333333333333333333333333333333333333333࿚ٿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿٿ333333ӿٿ333333333333333333333333333333ffffff333333333333333333333333333333333333333333333333333333ffffff333333࿚ٿٿٿٿ333333ffffff濚ffffff333333333333333333ffffffffffff333333333333333333333333333333333333ffffff濚쿚333333ffffff333333333333㿚?鿚ffffffffffff333333333333333333333333333333ffffffffffffffffff333333333333ffffff濚쿚ffffff࿚ٿ333333ffffff濚鿚ffffff333333ffffff濚쿚333333333333ffffff濚ffffff࿚ٿ333333ӿٿ333333ffffff쿚鿚鿚鿚鿚쿚鿚鿚ffffffffffff濚鿚鿚ffffff333333333333ffffff濚쿚ffffffffffff333333333333ffffffffffffffffffffffff333333333333333333㿚ٿ333333ӿ333333ӿ333333ӿffffff濚ffffff333333333333333333ffffff쿚ffffff333333333333ffffffffffffffffff333333333333ffffff濚鿚鿚333333333333ffffffffffff333333333333ffffffffffff濚鿚ffffffffffff333333333333ffffff濚쿚ffffff333333333333ffffff濚쿚ffffff333333333333࿚ٿ333333ffffffffffffffffff333333333333333333ffffffffffff333333㿚ٿ333333ffffffffffff333333࿚ٿ333333ffffff濚쿚鿚ffffffffffff濚쿚鿚鿚ffffff333333࿚ٿ333333333333ffffffffffffffffff333333333333ffffff濚鿚쿚鿚鿚쿚鿚ffffff333333333333333333ffffff濚쿚鿚ffffff333333333333࿚?333333333333ffffff333333333333333333ffffff濚쿚ffffff333333333333㿚ffffff333333333333ffffff濚鿚ffffff濚鿚鿚ffffffffffff333333࿚ٿٿ࿚ٿٿٿ333333ffffff濚鿚鿚쿚쿚ffffff333333㿚쿚ffffff333333333333ffffffffffffffffffffffffffffffffffff333333333333ffffff쿚ffffff333333333333ffffff濚쿚ffffffffffff333333333333333333333333ffffff濚鿚ffffff333333333333333333ffffffffffff濚鿚鿚鿚쿚鿚鿚ffffffffffffffffff333333333333333333333333ffffffffffff濚쿚鿚ffffffffffff333333࿚ٿffffff濚鿚鿚ffffff333333333333ffffff濚鿚鿚ffffff333333333333ffffff濚鿚ffffff333333࿚ٿٿ333333࿚ٿ333333ӿٿٿ333333ffffff濚鿚鿚鿚ffffffffffff࿚ٿ333333ffffff濚鿚鿚鿚ffffff333333333333ffffffffffffffffffffffff333333333333ffffffffffff濚ffffff333333333333333333ffffff濚쿚鿚ffffffffffff濚鿚鿚쿚鿚ffffff333333333333333333ffffff濚鿚鿚쿚ffffff333333㿚ٿ333333ffffff濚쿚鿚鿚鿚鿚ffffffffffffffffff濚쿚ffffffffffffffffffffffff쿚ffffff333333333333333333333333࿚ٿٿffffffffffff濚ffffff333333333333333333ffffff濚쿚333333333333333333ffffff濚鿚鿚ffffffffffff濚쿚333333ffffff濚쿚鿚쿚鿚쿚ffffffffffffffffff濚鿚ffffff333333333333࿚ٿٿ333333333333ffffff濚鿚鿚ffffff333333333333࿚ٿٿ࿚ٿ333333ffffffffffffffffffffffff333333333333333333ffffffffffff濚鿚鿚鿚ffffff333333333333࿚ٿ333333㿚쿚ffffffffffffffffff濚鿚쿚鿚ffffffffffff333333333333333333333333ffffff濚鿚鿚鿚쿚ffffffffffffffffff濚쿚ffffffffffffffffffffffff濚쿚쿚ffffff333333333333ffffff쿚鿚鿚鿚鿚ffffffffffffffffff濚鿚쿚鿚鿚鿚쿚ffffffffffff333333333333333333ffffffffffff濚鿚333333㿚ٿ333333ӿffffff𿚙ffffff333333333333333333ffffffffffff濚鿚鿚鿚鿚ffffffffffffffffff濚쿚ffffff333333333333ffffffffffff濚쿚ffffffffffffffffff濚쿚쿚333333333333ffffff濚쿚ffffff࿚ٿٿ333333ffffffffffff333333㿚ٿ333333333333ffffffffffff濚鿚鿚ffffff333333333333333333ffffff濚ffffffffffffffffffffffffffffffffffff333333ffffff濚ffffff333333333333333333333333333333ffffffffffff333333333333333333333333333333333333333333ffffffffffffffffff333333333333ffffffffffff濚鿚ffffffffffff333333333333ffffff濚鿚鿚鿚ffffff333333࿚ٿ333333ffffff濚ffffff333333333333ffffffffffff333333333333333333ffffffffffff濚鿚ffffff濚ffffff濚쿚鿚鿚ffffffffffff濚鿚鿚鿚ffffffffffffffffff333333333333ffffff濚ffffffffffff333333333333ffffffffffff쿚ffffffffffffffffff濚鿚鿚鿚쿚ffffff333333333333ffffffffffff333333࿚ٿffffff濚쿚333333333333ffffff濚鿚鿚ffffff333333࿚ٿٿٿٿ333333ffffff濚쿚ffffff333333333333㿚𿚙333333࿚ٿٿ333333ffffffffffffffffff333333333333333333ffffff濚鿚鿚鿚쿚鿚333333࿚333333ffffffffffff濚쿚ffffff333333333333ffffff濚ffffffffffff333333333333ffffffffffff濚鿚ffffff333333333333333333ffffff濚쿚鿚ffffff333333ffffff濚鿚ffffffffffffffffff濚쿚333333333333࿚ٿ333333ӿٿffffff濚쿚ffffff333333333333ffffff濚ffffffffffff333333333333333333ffffff濚쿚鿚ffffffffffff333333333333ffffffffffff濚ffffffffffff333333333333ffffff쿚鿚鿚쿚鿚鿚鿚쿚鿚ffffff333333333333ffffffffffffffffff333333333333ffffff𿚙ffffff333333࿚ٿffffff濚쿚ffffff333333࿚ٿ333333ffffff쿚ffffff333333ffffff濚鿚鿚쿚鿚쿚鿚鿚鿚ffffffffffffffffffffffffffffffffffffffffffffffff濚鿚ffffff333333࿚ٿ333333ӿ333333㿚쿚鿚ffffff333333ffffffffffffffffffffffffffffff333333333333ffffffffffff濚ffffff333333࿚ٿٿٿ333333ffffff쿚ffffff333333333333ffffff濚쿚鿚鿚ffffff333333࿚ٿ333333ffffff濚鿚鿚쿚鿚鿚鿚鿚鿚쿚鿚鿚鿚鿚쿚ffffffffffffffffffffffffffffff333333333333ffffff濚ffffff333333333333ffffff濚鿚鿚ffffff333333333333333333ffffffffffffffffffffffff濚ٿ333333ffffffffffff333333ffffffffffffffffff濚鿚쿚ffffff333333ffffffffffffffffff333333࿚ٿ333333ffffff쿚鿚鿚ffffff࿚ٿٿٿffffffffffff濚鿚ffffffffffffffffffffffff濚ffffffffffffffffff333333ffffff濚쿚ffffff333333333333ffffffffffff濚鿚ffffffffffff333333ffffffffffff濚ffffff333333333333ffffff濚쿚ffffffffffff333333333333333333ffffff쿚쿚ffffff333333333333333333333333333333ffffff濚ffffffffffff333333࿚ٿٿٿٿ333333333333࿚ٿ333333ӿٿ333333ffffff濚鿚鿚ffffffffffffffffff333333ffffffffffff濚쿚鿚鿚쿚ffffff333333࿚ٿ333333㿚쿚鿚ffffff333333333333333333ffffffffffff濚ffffffffffffffffffffffff濚쿚鿚쿚鿚쿚ffffff333333333333ffffff濚鿚鿚鿚쿚鿚ffffff333333333333333333333333ffffffffffffffffff333333333333333333ffffff濚ffffffffffff쿚ɿ333333ӿ333333ӿٿٿ333333ffffffffffff333333ffffffffffff濚쿚ffffffffffffffffffffffff쿚333333333333ffffff쿚鿚ffffff333333࿚ٿ333333333333ffffffffffff333333ffffff濚鿚鿚ffffffffffffffffff濚鿚쿚쿚ffffff333333333333333333ffffff濚鿚鿚鿚쿚鿚ffffffffffff濚ffffffffffffffffff333333ffffff濚쿚ffffff333333333333333333333333333333ffffff濚鿚鿚333333ffffffffffffffffff333333333333ffffff濚쿚ffffff333333333333333333㿚鿚ffffff333333333333㿚鿚쿚ffffff333333333333333333ffffff濚鿚ffffffffffff333333333333333333333333333333ffffffffffff濚鿚쿚鿚ffffff333333ffffff濚𿚙ffffff333333㿚ٿ333333ffffff濚ffffffffffff333333ffffffffffffffffff333333333333ffffffffffff濚쿚鿚쿚ffffffffffffffffff濚ffffffffffffffffffffffffffffffffffffffffff濚쿚ffffff࿚ٿffffff濚쿚쿚鿚쿚鿚ffffff333333ffffffffffffffffff333333333333333333ffffff濚쿚ffffff333333333333ffffff濚쿚鿚鿚鿚鿚鿚鿚鿚鿚鿚鿚ffffff333333ffffff濚쿚鿚鿚鿚鿚鿚鿚鿚ffffffffffff333333333333ffffff濚ffffff333333333333333333ffffffffffffffffffffffffffffff333333333333333333ffffff333333࿚ٿٿ333333㿚鿚쿚ffffff333333333333ffffff濚쿚333333࿚ٿ333333ffffff쿚ffffff333333ffffffffffff濚쿚ffffffffffffffffffffffff333333333333333333333333333333ffffff濚𿚙ffffff333333333333333333333333ffffff濚鿚鿚鿚ffffffffffffffffffffffffffffff濚鿚ffffff333333333333࿚ٿٿٿٿ333333ffffffffffffffffff࿚ٿɿ333333ffffff333333333333333333333333333333ffffff쿚ffffff333333333333ffffff濚鿚ffffffffffff333333ffffff濚𿚙ffffff333333333333ffffff濚쿚鿚鿚鿚ffffffffffff333333333333ffffffffffffffffff333333333333333333ffffff濚ffffffffffffffffff濚鿚鿚ffffffffffffffffffffffff濚鿚쿚鿚鿚ffffff濚ٿffffff濚鿚鿚鿚鿚쿚鿚333333333333333333333333ffffff濚鿚鿚ffffffffffffffffff濚鿚鿚쿚鿚鿚鿚鿚ffffffffffffffffffffffffffffffffffffffffffffffff濚쿚ffffffffffff333333333333ffffffffffff쿚鿚鿚鿚鿚쿚ffffffffffff333333333333333333ffffffffffffffffff濚ffffff333333࿚ٿٿٿffffff濚쿚333333࿚ٿ333333ffffffffffffffffff333333333333ffffff濚쿚ffffffffffff333333ffffff濚ffffff333333࿚ٿffffff濚鿚鿚ffffffffffff濚ffffffffffffffffffffffff濚쿚鿚ffffff333333333333ffffff濚쿚쿚ffffffffffff333333333333ffffff濚쿚ffffff333333333333ffffff濚쿚ffffff333333㿚ٿ333333㿚鿚쿚333333333333333333ffffffffffff333333333333ffffff쿚ffffff333333333333ffffff濚쿚ffffffffffffffffffffffff濚ffffff࿚ٿ333333ffffffffffff333333333333ffffffffffff濚鿚鿚鿚ffffff333333࿚ٿٿ333333ffffff쿚ffffff333333333333ffffff濚쿚ffffff333333333333ffffff濚ffffff333333333333333333333333ffffffffffff333333333333333333333333333333333333ffffffffffff濚鿚ffffff333333333333333333333333333333ffffff濚鿚鿚ffffffffffff濚쿚ffffffffffffffffff濚鿚쿚鿚ffffffffffff333333ffffff濚쿚ffffffffffffffffffffffffffffff333333333333ffffff濚鿚ffffff333333࿚ٿ333333ӿٿ333333ffffffffffff333333333333࿚ٿ333333ffffff濚ffffffffffff333333333333ffffffffffffffffffffffff濚쿚ffffff333333333333ffffffffffffffffffffffffffffff333333ffffff濚𿚙333333㿚ٿٿٿٿ333333333333ffffff濚鿚ffffff333333333333333333333333333333ffffffffffff濚ffffff333333ffffff濚쿚ffffff333333ffffffffffff濚쿚ffffffffffff333333333333333333333333ffffff濚쿚ffffff࿚ٿٿ࿚ٿ࿚ٿٿ333333㿚鿚쿚ffffff333333ffffffffffff333333㿚ٿٿ333333ffffff濚ffffffffffff333333ffffff濚ffffff࿚ٿٿٿٿffffff濚鿚鿚鿚鿚鿚ffffff333333333333ffffff濚쿚ffffff333333333333ffffff濚鿚鿚333333333333ffffffffffff쿚ffffff333333࿚ٿ333333ffffff濚鿚ffffffffffffffffffffffff濚鿚鿚鿚鿚鿚鿚ffffff333333㿚ٿ333333㿚鿚鿚333333࿚ٿٿ333333ffffffffffff濚ffffff333333333333ffffffffffffffffff333333333333ffffff濚쿚ffffffffffff333333ffffff濚쿚333333㿚ٿ333333ӿ333333ӿɿɿ333333ӿ333333㿚쿚ffffff࿚ٿɿٿٿ333333333333333333333333ffffffffffff333333333333㿚ٿٿ࿚ٿٿ333333ӿٿ333333ӿٿٿٿٿ333333333333333333ffffffffffffffffffffffff333333333333333333333333㿚ɿffffff333333333333333333333333ffffffffffffffffffffffffffffff333333333333333333333333333333333333333333333333ffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff濚ffffff333333333333333333ffffff濚쿚鿚鿚鿚쿚쿚鿚ffffff333333333333333333333333ffffff333333࿚ٿٿٿٿ333333ffffff濚쿚ffffffffffff333333333333333333333333333333333333333333333333㿚ٿ333333ӿ333333ӿ333333ӿٿ333333333333333333333333333333333333333333333333࿚ٿ𿚙333333333333333333333333ffffff濚ffffff333333333333333333333333ffffff濚쿚ffffff333333333333ffffff濚쿚ffffff333333333333࿚ٿ333333ffffff쿚鿚ffffffffffffffffff333333ffffff濚鿚鿚ffffff333333333333333333ffffff333333࿚ٿٿffffff濚쿚ffffff333333333333333333ffffffffffffffffff333333333333ffffff333333࿚ٿٿffffff濚鿚ffffff333333333333ffffff濚쿚鿚ffffff濚ffffffffffffffffffffffff濚쿚鿚ffffff333333333333ffffff쿚ffffff333333ffffff濚鿚鿚ffffff333333333333333333333333333333333333333333ffffffffffff濚쿚ffffff333333㿚ٿٿٿ333333333333ffffff333333333333ffffffffffff333333333333333333㿚ٿ333333ӿ333333ӿ333333ӿ333333333333333333ffffffffffffffffffffffff333333333333ffffff濚쿚333333333333ffffff쿚ffffff333333㿚ٿ333333ffffff濚鿚ffffffffffffffffff333333333333333333333333333333࿚࿚ٿٿٿٿ333333333333333333ffffffffffff濚ffffffffffff濚ɿffffff濚鿚ffffff333333㿚ٿ333333㿚쿚ffffff333333333333ffffff濚ffffffffffffffffff濚쿚333333333333333333333333333333333333࿚ٿٿ333333ffffff쿚ffffff333333ffffff濚쿚ffffff333333333333ffffff濚쿚333333࿚333333ffffffffffff333333࿚ٿ333333333333㿚鿚ffffff333333333333333333333333࿚ɿ333333㿚ٿٿ333333ӿ333333ӿٿffffffffffffffffff333333࿚ٿٿ333333㿚쿚ffffff333333333333ffffffffffffffffffffffff濚鿚쿚333333㿚ٿٿ333333㿚鿚쿚ffffff333333333333ffffff濚쿚鿚ffffff333333333333333333ffffff쿚ffffff333333333333ffffff濚쿚鿚鿚鿚쿚ffffffffffff333333333333333333333333ffffffffffffffffffffffffffffffffffffffffffffffff333333333333333333ffffff쿚鿚鿚ffffff333333࿚ٿٿٿ333333333333ffffffffffffffffffffffff333333ffffff濚鿚鿚鿚쿚ffffff333333333333ffffff濚쿚鿚ffffffffffffffffffffffff濚쿚ffffff333333333333ffffff濚쿚鿚ffffff333333ffffff濚ffffff333333333333333333333333ffffff濚鿚鿚ffffff333333333333333333ffffff濚鿚鿚ffffffffffffffffffffffff濚鿚鿚鿚ffffffffffff333333ffffffffffffffffff濚ffffff333333࿚ٿ333333㿚ffffff333333㿚ٿ333333ffffff濚쿚ffffff333333333333ffffff濚ffffff333333࿚ٿ333333ffffff쿚ffffff333333㿚ٿٿٿffffff濚鿚鿚鿚鿚鿚鿚鿚鿚ffffffffffffffffff濚鿚ffffffffffff333333࿚ٿ333333ffffffffffffffffff333333333333ffffffffffff濚鿚鿚鿚鿚ffffffffffffffffffffffff濚鿚ffffffffffffffffffffffff濚쿚鿚鿚ffffff333333333333333333ffffffffffff쿚鿚ffffff333333ffffffffffffffffffffffff濚鿚鿚ffffffffffffffffff濚쿚ffffff333333333333࿚ٿ࿚ٿ333333࿚ٿٿ333333ffffffffffffffffffffffff濚ffffffffffffffffffffffff쿚鿚ffffff333333333333333333ffffff濚鿚鿚鿚鿚鿚鿚鿚ffffffffffffffffff࿚ɿ333333ӿ333333ӿ333333ӿ333333ӿٿffffff濚鿚鿚ffffff333333ffffffffffff濚쿚쿚ffffffffffffffffff333333333333333333ffffff쿚333333333333ffffff濚鿚鿚ffffffffffff333333ffffff濚쿚ffffff333333333333ffffffffffff濚鿚鿚鿚鿚鿚鿚鿚333333333333333333333333333333333333࿚ٿٿ333333ffffff濚ffffffffffff333333333333ffffff濚鿚ffffff333333࿚ٿ333333333333ffffffffffff333333333333333333ffffff333333࿚ٿٿ333333㿚ffffffffffff333333333333333333ffffff濚鿚ffffff333333࿚ٿٿ333333ffffff濚쿚ffffffffffff333333333333ffffffffffffffffffffffffffffffffffff333333ffffff濚鿚쿚ffffff333333ffffff濚鿚ffffff333333333333ffffff濚鿚鿚ffffffffffff333333333333ffffff濚鿚鿚鿚鿚鿚ffffff࿚ٿ333333333333333333333333ӿٿ333333ӿ333333ӿ333333ӿٿffffff濚ffffff333333333333333333333333333333ffffff濚鿚鿚ffffffffffff濚쿚333333࿚ٿٿ333333ffffff濚鿚鿚ffffffffffff333333ffffffffffff濚鿚ffffffffffff333333333333ffffff濚쿚ffffff333333333333ffffff濚鿚ffffff333333333333ffffffffffffffffff濚鿚ffffff333333࿚ٿ333333333333ffffffffffffffffff濚ffffff333333333333ffffff濚鿚鿚ffffff333333333333333333ffffff濚鿚쿚ffffffffffffffffff333333ffffffffffffffffffffffff濚鿚鿚ffffff333333333333333333333333ffffff濚쿚ffffff333333㿚ٿٿ333333ffffff濚쿚ffffff333333㿚ٿ333333ӿٿffffffffffffffffff333333333333ffffffffffff333333333333㿚ٿ333333ffffffffffffffffff333333333333ffffffffffff濚ffffff333333333333ffffff濚쿚ffffff333333333333333333333333ffffffffffff濚鿚ffffff333333࿚ٿ333333ffffffffffff濚鿚쿚ffffff࿚ٿ333333ffffffffffff쿚ffffffffffffffffffffffff쿚鿚鿚ffffffffffffffffff濚鿚쿚鿚ffffff濚鿚鿚鿚ffffff333333࿚ٿffffff濚쿚333333333333㿚쿚鿚ffffffffffffffffffffffff333333㿚ٿٿffffff濚쿚ffffffffffff333333333333333333ffffff濚鿚鿚333333333333333333333333333333333333333333ffffffffffff333333333333ffffff濚鿚鿚쿚ffffff333333333333ffffff濚鿚鿚ffffffffffff濚쿚333333ffffff濚쿚鿚ffffffffffff333333ffffffffffffffffff333333333333333333ffffff濚鿚鿚ffffff333333333333333333333333㿚쿚鿚鿚鿚鿚鿚鿚鿚鿚쿚鿚鿚ffffffffffff濚쿚鿚ffffff333333࿚ٿٿٿٿٿ333333ffffff濚鿚鿚ffffffffffff333333333333333333333333ffffffffffff濚鿚鿚쿚鿚ffffff濚鿚鿚鿚ffffff333333333333ffffff濚쿚ffffff333333ffffff濚쿚ffffffffffffffffff濚鿚鿚ffffff濚鿚ffffff333333ffffffffffff濚鿚鿚鿚鿚鿚ffffff࿚ٿffffffffffffffffffffffffffffffffffff濚쿚ffffffffffff333333333333333333ffffffffffff濚鿚ffffff333333333333333333ffffffffffffffffffffffff濚𿚙ffffffffffffffffffffffff濚鿚鿚鿚ffffffffffffffffffffffff濚鿚ffffff333333ffffff濚쿚ffffff333333333333ffffff濚쿚鿚鿚쿚鿚鿚鿚鿚鿚쿚鿚ffffff333333333333ffffff濚ffffff333333333333333333ffffff쿚鿚쿚鿚鿚鿚쿚鿚ffffffffffffffffffffffff濚ffffff333333333333ffffff濚쿚鿚鿚ffffffffffff333333333333ffffffffffffffffffffffff濚鿚鿚鿚鿚鿚鿚鿚ffffffffffffffffff333333࿚ٿ333333㿚ffffff333333333333333333ffffffffffff濚쿚鿚鿚ffffff333333333333333333ffffffffffff쿚ffffff333333333333333333ffffff濚鿚ffffffffffffffffff333333333333333333ffffff濚鿚鿚鿚쿚鿚ffffff濚鿚鿚鿚鿚ffffffffffff333333333333ffffff쿚ffffff濚쿚鿚ffffffffffffffffff濚ffffff333333333333ffffffffffff濚쿚333333333333㿚鿚鿚ffffffffffffffffff333333333333333333ffffff濚쿚鿚鿚鿚鿚鿚鿚鿚鿚쿚ffffff333333ffffff濚鿚ffffffffffffffffff333333ffffff濚鿚쿚鿚鿚鿚쿚ffffff濚鿚鿚쿚鿚鿚鿚鿚鿚鿚ffffffffffff濚鿚𿚙鿚ffffff333333ffffffffffff濚쿚ffffffffffff333333ffffff濚쿚鿚鿚鿚ffffffffffffffffffffffff濚𿚙ffffff࿚ٿffffff쿚鿚鿚ffffff濚쿚鿚鿚鿚鿚鿚鿚鿚鿚鿚쿚鿚ffffffffffffffffffffffffffffff濚鿚鿚쿚ffffff333333ffffffffffff濚쿚쿚ffffff濚ffffff濚鿚ffffff࿚ٿffffff濚쿚鿚ffffffffffff333333333333333333333333333333333333ffffff쿚ffffff333333333333ffffff濚쿚鿚ffffff333333333333ffffff濚鿚鿚鿚ffffffffffff333333333333333333333333ffffff濚鿚쿚ffffffffffffffffff濚쿚ffffff333333ffffff濚鿚쿚鿚ffffffffffffffffffffffffffffffffffffffffffffffff濚ffffffffffff濚鿚쿚ffffff333333ffffffffffff쿚ffffff濚鿚鿚鿚ffffffffffffffffff333333333333㿚ٿ࿚ɿ333333333333ffffffffffff濚ffffffffffff333333ffffffffffff濚鿚鿚鿚鿚鿚鿚ffffff濚鿚鿚ffffffffffff333333333333333333ffffff濚鿚鿚鿚鿚鿚鿚鿚鿚鿚鿚ffffff333333࿚ٿ333333ffffff濚鿚ffffff333333࿚ٿٿٿ333333ffffff쿚ffffff333333ffffff濚鿚쿚鿚鿚쿚鿚ffffff濚ffffffffffffffffffffffff濚쿚鿚鿚鿚ffffffffffff濚쿚鿚ffffff濚쿚ffffffffffff333333333333㿚鿚鿚鿚鿚쿚鿚鿚鿚鿚ffffffffffffffffff濚鿚鿚ffffffffffffffffffffffff쿚쿚ffffff333333ffffff濚쿚ffffff333333333333ffffff濚쿚333333333333ffffffffffffffffff333333333333333333333333333333ffffffffffff濚쿚鿚鿚鿚쿚ffffffffffff濚鿚쿚鿚鿚쿚鿚쿚鿚鿚ffffff濚쿚鿚ffffff333333333333333333ffffff濚鿚ffffffffffff333333ffffffffffffffffff濚ffffff333333333333ffffff濚鿚ffffff333333333333333333333333ffffff濚ffffff333333333333ffffff濚쿚333333333333333333ffffff쿚ffffffffffff333333ffffffffffffffffffffffff濚鿚ffffff濚鿚鿚鿚쿚ffffff333333333333ffffff濚쿚ffffff333333ffffff濚쿚鿚鿚鿚鿚쿚ffffff333333333333ffffff쿚ffffff333333࿚ٿ࿚ٿٿɿٿٿٿٿ333333ӿٿffffff濚쿚333333333333333333ffffffffffffffffff333333333333ffffffffffff濚ffffffffffff333333333333333333ffffffffffff濚鿚ffffffffffff333333333333333333333333333333ffffff쿚ffffffffffff333333333333ffffffffffff濚ffffffffffff333333333333ffffff333333333333࿚ٿ333333ӿٿ333333333333࿚ٿ333333ӿ333333ӿ333333ӿٿٿٿ333333ӿ333333ӿٿ࿚ٿ333333ӿ333333ӿ333333㿚ٿ333333ӿٿ࿚ٿٿٿ333333࿚ٿٿ333333㿚ٿ࿚ٿ333333333333333333333333333333ffffffffffff333333㿚ٿٿٿٿٿٿ333333ffffff濚鿚ffffff333333࿚ٿٿٿ333333ffffff濚鿚ffffff333333࿚ٿٿٿٿ333333ӿ333333ӿ333333ӿffffff濚ffffffffffff333333333333ffffff333333ffffff濚鿚鿚ffffff333333333333333333ffffff333333ffffffffffff333333333333333333ffffff濚쿚ffffff333333333333333333333333ffffff濚鿚鿚ffffff333333࿚ٿ࿚ٿٿٿٿٿٿ333333ӿٿٿ࿚333333333333ӿ333333ӿ333333ӿٿٿ࿚ٿ333333ӿ333333ӿ333333ӿٿٿٿٿٿ333333333333ffffffffffff333333333333333333࿚ٿٿٿٿٿ333333ӿɿɿ333333ӿ333333ӿٿ333333333333333333ffffffffffff濚ffffffffffffffffff333333333333333333333333ffffff濚鿚쿚333333࿚ٿ333333333333333333࿚ٿ࿚ٿٿ333333ffffffffffffffffff333333333333ffffff濚쿚ffffff333333333333333333333333333333333333333333333333࿚ٿ࿚ٿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿɿɿٿ333333333333333333333333333333࿚ٿ333333ӿ333333ӿٿٿ333333ffffffffffffffffff333333࿚ٿٿɿ࿚ٿɿ333333ӿ333333ӿٿٿٿ333333333333ffffff333333333333࿚ٿٿ333333ffffffffffffffffff333333333333333333333333333333333333333333ffffffffffff濚쿚ffffff333333333333ffffff濚쿚ffffffffffff333333ffffff濚鿚ffffff333333࿚ٿٿٿٿٿ333333ffffffffffff333333࿚ٿٿ333333333333333333333333ffffff333333333333333333㿚ٿ333333ffffff濚鿚쿚333333࿚ٿffffff濚쿚ffffff333333333333333333333333ffffffffffff濚쿚ffffffffffffffffff濚쿚ffffffffffffffffffffffff쿚ffffff333333࿚ٿٿٿٿ333333333333333333ӿ࿚ٿٿ333333ffffff쿚鿚ffffff333333333333ffffff쿚ffffff333333333333333333333333ffffffffffffffffff濚鿚ffffffffffff濚ɿffffff濚鿚鿚鿚鿚鿚쿚ffffffffffff333333333333ffffffffffff333333333333࿚ٿٿ࿚鿚쿚ffffff333333ffffff濚鿚쿚ffffff࿚ٿffffff濚ffffff333333333333333333333333ffffff濚鿚쿚ffffff333333㿚ٿ333333ffffff濚ffffff333333333333㿚쿚鿚鿚쿚ffffffffffffffffff濚ffffffffffff333333ffffffffffff濚鿚鿚鿚ffffffffffff࿚ٿ࿚ffffffffffff濚쿚鿚鿚ffffff333333333333333333333333333333333333ffffffffffff濚ffffffffffffffffffffffff333333333333333333ffffff濚鿚ffffffffffffffffffffffffffffff濚쿚鿚ffffff333333࿚ٿffffff濚쿚ffffff333333ffffff濚쿚鿚ffffff333333333333333333ffffff濚쿚ffffff333333333333ffffffffffffffffff333333ffffff濚쿚333333࿚ٿ333333ffffff濚鿚ffffffffffffffffffffffff濚鿚ffffff333333333333ffffff濚쿚鿚쿚쿚ffffff333333333333㿚쿚ffffff333333333333ffffffffffff쿚쿚ffffff333333333333ffffff濚쿚333333333333ffffff濚鿚鿚鿚鿚ffffff333333333333ffffff쿚鿚ffffff濚쿚鿚鿚鿚쿚鿚鿚鿚쿚ffffff333333㿚ٿٿٿ333333333333ffffff333333࿚ٿٿffffff濚鿚ffffff333333333333333333333333333333333333㿚쿚ffffff333333333333ffffff쿚333333333333ffffff쿚鿚鿚鿚鿚ffffffffffffffffff쿚ffffffffffffffffffffffff濚鿚鿚鿚鿚ffffff333333ffffff濚鿚쿚ffffffffffff333333333333ffffff濚𿚙ffffffffffff333333ffffffffffff濚쿚鿚ffffffffffffffffff333333333333333333333333ffffff333333ffffff濚鿚鿚쿚鿚쿚ffffff333333ffffff濚鿚鿚ffffffffffffffffffffffff333333ffffffffffff濚鿚ffffffffffff333333333333333333333333ffffffffffff濚ffffffffffff࿚ٿٿٿ333333ffffff濚쿚鿚ffffff333333333333ӿ333333333333ffffff濚鿚쿚鿚鿚鿚鿚鿚鿚鿚쿚鿚鿚쿚ffffff333333333333ffffff濚ffffffffffffffffffffffff濚쿚333333333333333333㿚쿚鿚ffffff333333ffffffffffff濚쿚ffffffffffff333333333333ffffff333333333333333333333333333333333333333333ffffff濚ffffffffffff333333࿚ٿٿ333333ffffff쿚鿚ffffff333333ffffff濚ffffff333333ffffff濚ffffff333333333333333333333333333333333333ffffff濚ffffffffffffffffff333333ffffffffffffffffff濚鿚ffffff࿚ٿٿffffffffffff濚鿚ffffff333333333333ffffff濚鿚鿚鿚鿚鿚鿚鿚鿚鿚鿚鿚쿚ffffff333333333333ffffffffffff濚ffffffffffff333333࿚ٿ333333㿚쿚鿚ffffff濚鿚ffffffffffff333333333333ffffff濚쿚ffffff333333333333ffffffffffff濚鿚쿚333333࿚ٿٿ333333ffffffffffffffffff濚ffffff࿚ɿٿ333333㿚ٿffffff333333333333࿚ٿٿ࿚?ffffffffffff333333333333ffffff濚쿚333333333333ffffff濚鿚ffffff333333333333333333333333ffffff濚鿚쿚ffffff333333ffffff濚鿚쿚鿚ffffff333333333333333333ffffff濚鿚鿚鿚鿚ffffff333333333333333333ffffff濚쿚ffffffffffffffffff濚鿚鿚ffffffffffff333333333333333333ffffffffffffffffff濚鿚鿚ffffff333333࿚ٿffffff濚쿚333333࿚ٿ333333㿚쿚ffffff333333333333333333333333333333333333࿚ٿ࿚ٿffffff濚鿚鿚ffffffffffff濚ffffffffffffffffff333333333333㿚ffffff333333࿚ٿٿ333333ffffffffffffffffffffffff333333333333333333333333ffffffffffff濚쿚ffffffffffff333333333333333333333333333333㿚鿚ffffff333333࿚ٿ333333㿚쿚ffffffffffff333333࿚ٿٿffffffffffffffffff333333333333ӿ333333333333333333ffffff濚쿚ffffffffffff333333333333333333333333ffffffffffff濚ffffff333333333333㿚쿚ffffff࿚ٿٿ333333ӿٿ333333ӿ鿚鿚333333333333333333ffffff濚쿚ffffff333333333333ffffffffffff쿚ffffffffffff濚鿚ffffff333333࿚ٿٿffffff濚쿚쿚333333333333333333333333333333ffffff333333ffffffffffffffffffffffffffffff333333333333333333333333࿚ٿٿٿٿ࿚ٿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿٿ333333㿚鿚鿚ffffff࿚ٿ333333ӿ333333ӿ333333ӿٿ࿚ٿٿٿ333333333333333333ffffff濚ffffff333333࿚ٿٿٿ333333ffffff333333࿚ٿٿٿٿٿ333333333333࿚ٿٿ333333ffffff쿚ffffffffffffffffffffffff333333ffffffffffff濚ffffffffffffffffff333333ffffffffffff濚쿚ffffffffffff333333333333333333333333ffffff濚쿚ffffff࿚ٿٿ࿚ٿ333333ffffff濚鿚鿚鿚ffffff333333333333333333㿚鿚쿚ffffff333333333333333333ffffff濚ffffff333333333333333333333333ffffffffffff濚鿚ffffff333333333333333333ffffff濚鿚쿚ffffffffffff333333ffffffffffff濚鿚鿚鿚鿚鿚鿚ffffffffffff濚쿚ffffff333333333333ffffff濚쿚ffffffffffff333333333333ffffffffffff濚ffffffffffffffffffffffff濚鿚鿚쿚ffffff333333㿚ffffff333333333333333333333333ffffffffffff濚鿚鿚鿚ffffffffffffffffffffffff333333333333333333333333ffffff濚쿚鿚ffffffffffff333333333333333333ffffffffffffffffff333333࿚ٿٿٿ333333ffffff濚鿚333333333333ffffffffffff333333࿚ٿ333333ffffff쿚鿚鿚鿚ffffffffffff333333333333333333333333333333ffffffffffff濚쿚ffffffffffff333333333333333333ffffffffffff333333333333ffffff濚鿚鿚333333333333ffffff濚ffffff࿚ٿ333333㿚鿚ɿffffff濚鿚333333333333333333ffffff濚ffffffffffff333333ffffffffffff濚鿚ffffff333333333333333333ffffff濚鿚쿚鿚鿚쿚鿚鿚鿚鿚ffffff333333333333ffffff濚ffffff333333࿚ٿffffff濚쿚333333࿚ٿٿffffffffffff濚쿚ffffff࿚ٿٿffffff濚鿚ffffff333333333333ffffff濚ffffff333333࿚ٿ333333ffffff濚쿚ffffff333333333333ffffff쿚ffffff333333ffffff濚ffffff࿚ٿٿ333333333333ffffff濚쿚333333333333333333ffffff濚ffffffffffff333333333333ffffffffffff濚鿚ffffffffffffffffffffffffffffff333333333333333333ffffffffffff쿚쿚ffffff333333㿚쿚ffffff333333333333ffffffffffff쿚ffffff濚鿚鿚鿚ffffffffffff濚ffffff333333333333ffffff濚쿚333333333333333333333333ffffff濚𿚙ffffff333333333333ffffff濚쿚ffffffffffffffffff濚쿚鿚ffffff333333333333ffffff濚쿚鿚ffffffffffffffffff333333㿚𿚙333333333333ffffff濚鿚ffffff濚333333333333333333333333㿚쿚鿚ffffff333333333333333333ffffff濚쿚ffffffffffffffffff濚鿚쿚鿚鿚鿚鿚鿚鿚ffffff濚ffffffffffff濚鿚鿚쿚鿚鿚鿚ffffffffffffffffffffffffffffffffffff333333333333ffffffffffff濚ffffff333333ffffffffffff濚쿚鿚鿚쿚鿚ffffff333333333333ffffffffffff濚鿚鿚ffffff333333ffffffffffff濚鿚쿚333333333333333333㿚쿚鿚鿚鿚鿚쿚ffffff濚ffffff濚鿚ffffff濚鿚鿚鿚鿚鿚ffffff濚鿚鿚쿚鿚ffffff333333ffffff濚쿚ffffff࿚ٿffffff濚쿚333333333333333333㿚ffffff࿚ٿٿ333333ffffff濚ffffffffffff333333࿚ٿٿ333333㿚쿚鿚鿚鿚鿚ffffffffffffffffff濚鿚鿚鿚ffffff333333࿚ٿٿ333333㿚鿚쿚ffffffffffff333333ffffff濚쿚333333࿚ٿ333333ffffff쿚ffffffffffffffffff濚쿚ffffff濚鿚鿚鿚鿚鿚鿚쿚ffffff333333ffffff쿚ffffffffffffffffff濚鿚鿚ffffff濚鿚ffffff333333ffffffffffff濚鿚ffffff333333333333333333333333333333ffffff쿚鿚鿚ffffffffffff濚쿚333333333333ffffffffffffffffff333333333333ffffffffffffffffffffffff333333ffffff濚鿚𿚙ffffff333333333333ffffff濚鿚ffffff濚?ffffffffffffffffff333333ffffffffffff濚鿚ffffff333333ffffff濚쿚ffffff333333ffffff濚쿚333333333333ffffff濚쿚ffffff333333333333ffffff濚鿚ffffff࿚333333ffffffffffffffffff濚鿚鿚ffffff333333࿚ٿ333333ffffff쿚ffffff333333333333333333333333ffffff333333333333333333ffffffffffffffffffffffff濚ffffff333333㿚ٿٿffffff濚鿚鿚鿚ffffffffffff333333㿚ٿ333333ffffffffffffffffff333333333333࿚ٿɿɿɿ333333ӿ333333333333333333ffffffffffffffffff濚鿚鿚ffffff333333333333333333333333ffffff濚쿚鿚鿚ffffff333333333333ffffffffffff濚鿚쿚ffffff࿚ٿ333333ffffffffffffffffff333333ffffff濚쿚ffffffffffffffffff濚쿚ffffffffffffffffff濚쿚ffffff333333333333ffffffffffffffffffffffff濚ffffffffffff333333333333ffffff濚ffffffffffff333333333333333333333333ffffffffffff濚鿚ffffff333333ffffff濚𿚙ffffff333333333333333333ffffffffffff333333㿚ٿٿffffff濚ffffff333333333333333333ӿ333333ӿٿٿ࿚333333ffffff濚鿚ffffff333333333333ffffffffffff濚鿚鿚鿚鿚ffffff333333333333ffffff濚鿚ffffff333333ffffff濚쿚ffffffffffffffffff濚쿚鿚ffffff333333333333333333333333333333333333ffffffffffff濚鿚ffffff࿚ٿٿٿffffffffffff333333333333333333㿚ffffffffffffffffff333333333333333333333333333333333333ffffffffffff333333333333333333333333333333333333࿚ٿٿ333333ffffff濚ffffffffffff濚鿚쿚ffffff333333333333ffffffffffff濚鿚ffffffffffff333333333333333333ffffffffffffffffff333333333333࿚ٿٿٿٿ333333333333333333333333ffffffffffff濚鿚鿚ffffff333333333333ffffff濚鿚ffffffffffff濚鿚鿚鿚ffffffffffff濚쿚ffffff333333ffffff濚쿚ffffffffffffffffff濚쿚ffffffffffffffffff濚쿚ffffffffffffffffffffffff濚鿚쿚鿚ffffffffffff濚鿚鿚鿚쿚ffffff333333ffffff쿚쿚鿚鿚鿚鿚鿚鿚쿚鿚鿚鿚鿚쿚鿚鿚333333333333333333333333㿚쿚鿚鿚ffffffffffffffffff濚쿚鿚鿚ffffffffffffffffff濚鿚鿚ffffff濚쿚ffffff333333333333ffffff濚ffffffffffffffffff333333333333333333333333ffffff濚鿚ffffff濚?ffffffffffff濚ffffff濚ffffffffffffffffff濚鿚鿚鿚ffffff333333ffffffffffff쿚ffffffffffffffffffffffff쿚ffffffffffff࿚ٿٿ333333ffffffffffff쿚ffffff333333࿚ٿ࿚ٿٿ333333ffffff쿚333333333333ffffffffffffffffff333333333333ffffffffffffffffffffffffffffff濚鿚쿚鿚鿚쿚鿚ffffff濚鿚鿚鿚ffffffffffffffffff濚쿚ffffff333333333333333333ffffff濚쿚ffffff333333333333333333ffffffffffff濚ffffff333333333333333333ffffff濚쿚ffffff濚鿚鿚鿚鿚쿚鿚鿚鿚ffffff333333ffffff濚쿚ffffffffffff333333333333ffffff濚鿚쿚鿚鿚ffffffffffff333333ffffffffffff쿚鿚ffffffffffff333333333333ffffffffffff濚鿚鿚鿚ffffff333333333333ffffff濚鿚鿚鿚鿚ffffffffffff333333333333ffffff濚쿚ffffffffffff333333333333333333333333333333333333ӿffffff333333333333333333ffffff쿚鿚ffffff333333333333ffffff濚쿚鿚ffffffffffffffffffffffffffffff濚𿚙333333333333333333ffffff濚쿚ffffff333333333333ffffff濚鿚ffffff333333333333333333ffffffffffffffffff333333333333333333333333333333333333333333333333ffffff쿚ffffffffffffffffff濚쿚333333࿚ٿٿٿ333333ffffffffffffffffffffffff333333࿚ٿɿɿɿ333333ӿffffff濚쿚鿚ffffff333333333333333333333333333333ӿ333333ӿ333333ӿٿ333333333333ffffffffffff濚鿚ffffffffffff333333333333ffffff濚鿚쿚ffffff濚鿚쿚鿚鿚鿚ffffff333333333333333333333333ffffff쿚ffffff333333㿚ٿ333333ffffff濚쿚鿚쿚ffffffffffffffffff333333ffffff333333333333ffffff濚鿚鿚ffffffffffffffffffffffffffffffffffffffffffffffff333333333333333333ffffff濚쿚ffffffffffffffffff濚ffffff333333333333ffffffffffff濚鿚鿚ffffffffffff333333333333333333ffffffffffff쿚ffffffffffff333333333333ffffff濚鿚ffffff濚鿚鿚쿚鿚鿚쿚333333333333ffffff濚ffffffffffffffffffffffffffffff濚ffffff333333333333333333333333ffffff濚鿚ffffffffffff࿚ٿffffff濚ffffff࿚ٿٿ333333ffffffffffffffffff࿚ٿ333333333333ffffff333333333333ffffff濚쿚ffffff333333࿚ٿ333333ffffffffffffffffff333333333333333333ffffff濚鿚쿚ffffff333333333333333333333333333333333333ffffff濚쿚333333࿚ٿ333333ffffff濚ffffffffffff333333333333ffffff濚鿚쿚ffffffffffffffffffffffff쿚ffffff333333ffffff濚쿚ffffffffffff333333333333ffffff쿚333333ӿ333333333333333333333333333333࿚ٿ333333ӿٿ333333㿚쿚333333333333333333ffffff濚鿚ffffff333333333333333333ffffffffffff濚鿚ffffffffffff333333333333ffffffffffffffffffffffffffffff濚ffffff333333333333ffffff濚쿚鿚ffffffffffffffffffffffffffffffffffffffffffffffff333333ffffff333333ffffff濚鿚鿚鿚ffffff333333333333ffffff濚쿚鿚鿚鿚ffffffffffffffffffffffffffffffffffffffffffffffff濚쿚ffffffffffffffffff濚鿚ffffff333333333333333333ffffff濚鿚ffffff濚ffffffffffff333333333333ffffffffffffffffff333333333333ӿ333333333333ffffff濚鿚쿚鿚鿚ffffff333333ffffffffffff濚ffffffffffff333333ffffff濚鿚쿚鿚鿚鿚鿚鿚鿚333333333333333333333333333333ffffff333333ffffffffffffffffffffffffffffffffffff333333ffffff濚쿚鿚쿚鿚쿚ffffff333333333333ffffffffffff濚鿚鿚鿚鿚鿚鿚鿚333333333333333333㿚ffffff333333333333333333ffffff濚ffffffffffffffffffffffffffffffffffff333333333333ffffff濚ffffff333333࿚ٿ333333333333ffffffffffff333333333333333333ffffff333333333333333333333333ffffff333333333333333333333333333333333333㿚ɿffffff濚쿚333333333333333333ffffff濚ffffffffffff333333333333333333333333࿚ٿٿٿ333333333333ffffff濚鿚쿚ffffff333333ffffff濚쿚333333333333ffffff濚鿚ffffff333333333333333333ffffff濚鿚쿚ffffff࿚ٿ333333ӿɿ333333ӿ333333ffffff쿚ffffff333333ffffff濚쿚333333333333333333333333ffffff濚쿚ffffffffffff333333333333333333ffffffffffff濚鿚ffffff333333333333333333ffffffffffff濚鿚ffffffffffff333333333333ffffff쿚ffffff333333333333333333333333333333ffffffffffff濚ffffffffffffffffffffffff濚鿚鿚쿚鿚ffffff333333࿚ٿٿ333333333333333333333333ӿ333333ӿɿ333333ӿٿٿ333333㿚ffffff333333㿚ٿ333333ffffff濚쿚ffffff333333333333333333ӿ333333ӿɿ333333ӿ333333ffffffffffffffffff333333࿚ٿٿ333333ffffff濚쿚ffffff333333㿚ٿ333333ӿٿ333333333333333333333333ffffff濚鿚鿚鿚鿚鿚鿚ffffffffffffffffffffffff濚鿚鿚鿚ffffff333333333333333333333333333333333333333333ffffffffffffffffff333333333333333333333333333333333333ffffffffffffffffffffffffffffffffffff333333ffffffffffff333333333333ffffff濚鿚쿚鿚ffffffffffffffffff333333㿚ɿffffff濚鿚ffffff333333333333ffffff濚쿚ffffff࿚ٿٿ333333ffffff濚ffffffffffffffffffffffff쿚ffffffffffffffffffffffff濚ffffff333333333333㿚쿚ffffff333333333333333333࿚ٿٿٿffffffffffffffffffffffff333333333333333333333333333333333333࿚333333ffffff333333333333࿚ٿɿ333333333333ffffff濚ffffff࿚ٿ333333ӿٿ333333ffffffffffffffffffffffffffffffffffff濚ffffff333333ffffff濚鿚鿚ffffff࿚ٿٿٿffffff濚쿚ffffff333333333333333333333333ffffffffffff濚ffffff333333333333ffffffffffff濚ffffffffffff333333333333ffffff濚ffffff333333333333333333ffffffffffff濚ffffff࿚ٿ333333ӿٿffffff濚쿚ffffffffffff333333333333ffffffffffffffffff࿚ٿٿ333333ffffff濚鿚ffffff333333࿚ٿ333333ӿ333333ӿ333333ӿ333333ӿ333333ffffffffffffffffff333333333333333333333333333333333333333333333333333333333333࿚ٿ333333ӿٿٿ333333ffffff濚鿚쿚ffffffffffff333333ffffff濚鿚ffffff333333࿚ٿٿٿٿٿffffff濚ffffff333333࿚ٿٿٿٿٿ333333333333333333333333ffffff濚ffffff333333㿚ٿ333333ӿ333333ӿ333333ӿ࿚ٿٿٿ333333࿚ٿ333333ӿ333333ӿ333333ӿffffffffffff濚쿚鿚ffffff333333333333ffffff濚쿚鿚ffffffffffff333333333333333333333333࿚ٿٿٿ333333333333ӿ333333ӿٿ333333ffffff濚ffffff333333333333333333ffffff333333333333333333333333333333333333333333333333ffffffffffffffffff333333333333333333ffffff쿚ffffff333333333333ffffff濚쿚ffffffffffff333333333333333333333333ffffff333333333333ffffff濚ffffff333333㿚ٿ333333ӿ333333㿚鿚ffffffffffffffffffffffffffffffffffff333333333333333333㿚鿚鿚ffffff333333࿚ٿ333333㿚쿚ffffffffffffffffffffffffffffff333333333333333333ffffffffffff濚쿚ffffff333333333333333333333333333333࿚ٿٿ333333333333࿚ٿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿɿɿٿ333333333333࿚ٿ333333333333333333࿚ٿٿ࿚ٿ333333ӿ333333ӿ333333ӿٿٿٿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿٿ࿚ٿ333333ӿɿ333333ӿ333333ӿٿٿٿٿٿɿffffffffffff333333࿚ٿٿٿ333333ffffff333333࿚ٿٿٿٿٿ333333333333333333࿚ɿ333333333333333333333333ffffff333333333333333333࿚ٿٿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿɿɿɿɿɿ????????????333333?333333?333333?333333???????333333????ɿ??333333?333333?333333?333333??ffffff?333333?ffffff?@ @@333333@ffffff @ffffff%@ffffff+@fffff0@L4@ffffff7@:@<@>@fffff&@@33333@@fffffA@LB@B@@C@33333C@fffff&D@fffffD@333333E@E@LF@F@333333G@33333sG@G@@G@ G@G@G@G@G@G@G@333333G@YG@ffffffG@33333sG@ffffffG@ffffffG@YG@YG@YG@ffffffG@YG@ H@̌G@G@YG@@G@333333G@333333G@@G@YG@G@fffffG@G@G@G@G@G@fffffG@33333G@ H@fffff&H@@H@LH@LH@@H@333333H@fffff&H@333333H@333333H@@H@LH@@H@@H@LH@LH@LH@fffff&H@33333G@G@fffffG@G@G@G@33333sG@YG@@G@fffff&G@G@33333F@fffffF@fffffF@F@F@G@̌F@YF@@F@333333F@333333F@333333F@333333F@fffff&F@F@F@ F@F@F@F@ F@F@33333E@F@F@333333F@333333F@@F@LF@LF@YF@ffffffF@33333sF@33333sF@F@̌F@̌F@F@F@F@fffffF@33333F@F@33333F@ G@ G@ G@G@G@333333G@LG@ffffffG@G@G@G@fffffG@G@33333G@H@fffff&H@333333H@333333H@@H@YH@̌H@H@33333H@ I@fffff&I@333333I@@I@@I@@I@LI@LI@@I@@I@333333I@fffffH@YI@33333H@fffff&I@fffff&I@fffff&I@I@I@fffffH@33333H@H@LH@fffff&H@ H@33333G@fffffG@fffffG@fffffG@fffffG@fffffG@G@G@fffffG@fffffG@fffffG@̌G@33333sG@YG@@G@333333G@fffff&G@G@G@fffffF@F@33333F@33333F@33333F@33333F@F@33333F@33333F@fffff&G@G@fffff&G@G@33333F@333333G@33333sG@G@fffffG@H@fffffG@@H@ffffffH@33333sH@33333sH@̌H@̌H@333333I@I@I@fffffH@fffffH@H@H@̌H@H@fffffH@fffffH@H@fffffH@̌H@H@H@̌H@̌H@̌H@̌H@̌H@H@H@33333sH@ffffffH@ffffffH@ffffffH@H@fffffH@H@I@ I@fffff&I@fffff&I@fffff&I@I@I@fffffH@333333I@@I@@I@333333I@fffff&I@I@fffff&I@@I@YI@33333sI@̌I@I@I@I@I@I@I@I@I@I@̌I@I@I@33333sI@33333sI@ffffffI@YI@@I@33333sI@YI@@I@333333I@333333I@333333I@@I@333333I@I@I@33333H@33333H@fffffH@H@H@H@33333H@fffffH@fffffH@fffffH@fffffH@fffffH@H@H@̌H@33333sH@ffffffH@LH@@H@@H@333333H@333333H@@H@@H@LH@LH@@H@@H@333333H@H@ H@H@ H@ H@H@fffffG@fffffG@G@fffffG@33333G@33333G@fffffG@G@G@G@fffffG@G@G@G@̌G@fffffG@G@G@fffffG@fffffG@fffffG@fffffG@G@G@fffffG@H@ H@333333H@@H@333333H@fffff&H@H@ H@fffff&H@333333H@@H@LH@LH@LH@YH@LH@LH@LH@@H@LH@YH@ffffffH@33333sH@H@H@33333sH@33333sH@H@H@̌H@H@H@̌H@H@33333sH@33333sH@33333sH@ffffffH@YH@YH@YH@ffffffH@33333sH@33333sH@H@33333sH@ffffffH@LH@@H@LH@LH@YH@ffffffH@LH@@H@333333H@333333H@@H@@H@@H@333333H@333333H@333333H@333333H@333333H@fffff&H@H@ H@H@33333G@G@G@fffffG@̌G@G@G@33333sG@ffffffG@33333sG@G@G@33333sG@ffffffG@LG@@G@@G@333333G@333333G@@G@@G@LG@LG@LG@LG@@G@@G@@G@@G@@G@@G@333333G@fffff&G@ G@33333F@F@33333F@F@̌F@F@@F@F@33333E@E@YE@fffff&E@fffffD@fffffD@LD@fffff&D@ D@D@C@33333C@̌C@YC@333333C@33333B@33333B@33333sB@@B@ B@A@A@YA@ A@@@̌@@L@@@@?@L?@?@33333>@>@>@=@ffffff=@=@33333<@L<@fffff;@;@333333;@;@:@:@ffffff:@9@9@8@L8@333337@ffffff7@7@333336@L6@fffff5@5@5@4@3333334@3@ffffff3@3@2@3333332@2@1@1@3333331@fffff0@0@3333330@ffffff/@ffffff.@ffffff-@,@ffffff,@,@ffffff+@*@*@ffffff)@(@'@'@ffffff&@333333&@&@%@%@333333%@%@#@#@"@!@333333!@ @ffffff @@ffffff@333333@@@@ffffff@333333@333333@333333@333333@ffffff@@@@ffffff@@@@ @@ffffff@@@333333@@@ffffff?333333????ffffff??333333?333333ӿ࿚ffffffffffffffffffffffffffffff濚鿚𿚙333333ffffffffffffffffff𿚙ffffff333333࿚ٿٿ333333ӿɿ333333ӿ333333ӿffffff333333333333ffffff濚鿚鿚鿚ffffffffffff濚鿚쿚鿚쿚鿚鿚쿚쿚ffffff濚ffffff333333333333ffffffffffff濚ٿ333333ӿɿɿ333333ӿٿffffff濚ɿffffffffffffffffff333333333333ffffff濚333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333󿚙333333ffffffffffffffffff333333333333333333333333333333󿚙񿚙񿚙쿚ffffff333333࿚ٿٿ333333ffffff濚쿚鿚ffffffffffff濚쿚鿚鿚鿚鿚쿚鿚ffffffffffffffffffffffff濚鿚쿚鿚鿚ffffff333333࿚ٿ333333ffffff濚쿚ffffff333333333333333333333333333333333333ffffff濚ffffffffffffffffff333333333333࿚ٿٿ333333ӿ333333ӿ333333ӿ333333ӿɿ??????ɿɿɿɿɿɿɿɿɿ333333ӿ333333ӿffffff濚鿚쿚𿚙񿚙333333ffffff333333333333333333333333ffffffffffffffffffffffffffffffffffffffffff333333333333333333333333333333ffffff333333쿚鿚鿚쿚ffffff333333㿚ٿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿɿɿɿ333333ӿɿɿ???ɿ333333ӿ333333ӿ?ɿɿɿɿɿɿɿɿɿɿɿɿɿ333333ӿٿ333333333333࿚ٿ333333ӿ333333ӿ333333ӿ333333ӿɿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿٿ333333ffffff濚鿚ffffffffffffffffffffffffffffff333333333333333333333333333333333333333333ffffffffffffffffffffffffffffff333333333333󿚙쿚鿚ffffff濚쿚鿚쿚鿚鿚鿚ffffffffffffffffffffffff濚鿚쿚333333ӿ333333?333333??ffffff??ffffff@333333@333333 @ @@333333@ffffff@333333@@ffffff@@@@@@@ffffff@ffffff@333333@@ffffff@333333@333333@333333@@ffffff@333333@@ffffff@ffffff@ffffff@333333@333333 @ffffff @ @333333!@333333!@ffffff!@!@!@!@"@333333"@ffffff"@"@333333#@ffffff#@#@#@333333$@$@$@%@%@%@333333%@ffffff%@ffffff%@ffffff%@ffffff%@ffffff%@%@333333&@ffffff&@&@&@&@&@&@ffffff&@ffffff&@333333&@333333&@333333&@333333&@ffffff&@&@&@'@&@&@&@&@'@333333'@'@'@'@'@&@&@&@&@'@'@'@&@&@&@&@ffffff&@333333&@333333&@333333&@333333&@ffffff&@ffffff&@ffffff&@&@&@333333&@333333&@&@%@%@%@ffffff%@333333%@333333%@%@$@$@$@$@$@ffffff$@$@#@#@#@#@#@#@ffffff#@333333#@#@#@#@#@"@"@"@ffffff"@ffffff"@ffffff"@ffffff"@333333"@"@!@!@!@ffffff!@333333!@ @ffffff @@ @@@@333333@@ffffff@@@@@ffffff@@ffffff@@@333333@@@@ffffff@ffffff@333333@333333@333333@@@@@@@@333333@@@@@@ffffff@ffffff@@@@@@@ffffff@@@@ffffff@@333333@@ffffff@ffffff@ffffff@ffffff@@@333333@@ffffff@@ffffff@ @ @ @ @ @ffffff@333333@333333@333333@333333@ffffff@ @ @ @ @ @ @ @ @333333 @ @@ @ffffff @ @ @ @333333 @333333 @ffffff @ffffff @ffffff @ffffff @ @ @@@@@@333333@ffffff@@@@@@@333333@ffffff@@ffffff????ffffff?ffffff?ffffff?ffffff?ffffff?ffffff??333333????ffffff?333333???333333?333333????ffffff?ffffff?ffffff?ffffff?333333???????333333??ɿ333333ӿ333333ӿ333333ӿɿɿɿ333333ӿ333333ffffffffffff濚鿚鿚𿚙쿚鿚鿚鿚ffffffffffffffffff濚쿚鿚쿚333333ffffffffffffffffff333333333333333333333333ffffffffffffffffffffffff333333333333333333󿚙񿚙񿚙񿚙񿚙쿚𿚙쿚ffffff濚鿚쿚𿚙333333333333󿚙񿚙񿚙333333󿚙𿚙񿚙𿚙鿚鿚鿚鿚ffffffffffff333333333333ffffffffffffffffff333333࿚ٿ333333ffffff濚ffffffffffff333333࿚ٿٿ333333࿚ٿ࿚ٿ࿚ٿٿ333333ӿ333333ӿٿ333333333333333333ӿɿ333333ӿٿ333333ӿ333333ӿ333333ӿɿɿɿ333333ӿ333333ӿ333333ӿٿٿ࿚ٿ333333ӿ333333ӿٿ333333ffffffffffff濚鿚鿚鿚鿚𿚙𿚙쿚ffffff濚鿚鿚鿚鿚쿚鿚鿚鿚鿚ffffffffffffffffff濚鿚쿚ffffffffffff333333333333333333࿚ٿ333333ӿɿɿɿɿɿɿɿɿɿɿɿɿ333333ӿ333333ӿ333333ӿ333333ӿɿɿɿɿ333333ӿ333333ӿٿٿ࿚ٿ333333ӿ333333ӿɿɿ333333ӿ333333ӿٿ333333ӿ333333ӿ333333ӿɿɿɿɿ333333ӿٿ333333333333333333333333333333ӿ333333ӿ333333ӿٿ333333ffffff濚鿚鿚333333࿚ٿ333333ӿ333333ӿ333333ӿٿffffff濚鿚鿚鿚ffffffffffff333333333333ffffffffffff࿚ٿ333333ӿ333333ӿٿٿٿ333333ӿ333333ӿ333333ӿ࿚ٿ333333ӿɿɿɿɿɿɿɿɿɿɿɿɿɿɿɿɿɿɿɿɿɿɿɿɿɿ333333ӿ333333ӿ333333ӿɿɿɿɿɿ333333ӿ333333ӿ333333ӿɿɿ333333ӿٿٿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿɿɿ333333ӿ333333ӿٿ333333333333࿚ٿ333333ӿɿ333333ӿٿٿ333333ffffff濚쿚鿚ffffff濚鿚鿚鿚鿚鿚ffffffffffff333333333333ffffff濚鿚鿚333333333333ӿ333333ӿɿ?????333333??333333?333333?333333?333333?333333?333333?333333?333333??333333?333333?ffffff????????ffffff?????333333?333333?333333?333333?333333?333333???333333?333333?333333?333333?333333??ffffff?ffffff??333333??????????ffffff?ffffff?ffffff?ffffff?ffffff?ffffff?ffffff?ffffff?ffffff?ffffff?ffffff??ffffff?@@@@@@@@ffffff@ffffff@ffffff@@@ffffff@333333@333333@333333@333333@@@@@@@@@@@@@@@ffffff@ffffff@333333@333333@333333@333333@@@@ffffff@@333333@333333@@@@333333@@@@@@ffffff@@@@@@@@@@333333@333333@ffffff@@@333333@333333@333333@333333@333333@333333@ffffff@ffffff@ffffff@ffffff@ffffff@333333@ffffff@333333@333333@333333@333333@@@@@@333333@333333@@@@@@333333@ffffff@333333@ffffff@333333@333333@@@@@@@@@@@@@@@@@@@@@@@@@333333@333333@333333@@@@@@333333@@333333 @@@@@@@@@@@@@@@@@333333@333333@333333@@@333333@333333@333333@ffffff@@ffffff?ffffff?ffffff?ffffff?@@@ffffff?ffffff??????333333?333333???333333?333333???333333????????ffffff??333333??333333??333333?333333???????????????????ffffff?ffffff???ffffff?333333??ffffff????????ffffff????????????????????ffffff?333333?333333?333333?333333????333333?333333?333333?333333????????333333?????????ɿɿɿɿɿ333333ӿ333333ӿ333333ӿ333333ӿٿٿ333333ffffff濚鿚鿚ffffff333333ffffffffffff濚쿚鿚鿚쿚쿚𿚙񿚙񿚙333333333333󿚙񿚙񿚙쿚鿚ffffff333333333333ffffff濚쿚鿚ffffffffffffffffffffffffffffffffffff333333࿚ٿٿٿٿ࿚ٿ333333ӿ333333ӿ333333ӿٿ333333333333333333333333333333333333ffffff333333333333333333ffffffffffffffffff333333ӿ333333ӿ333333ӿ333333ӿٿٿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿɿɿ333333ӿ333333ffffffffffff333333333333333333333333333333࿚ٿٿ333333ffffffffffff濚ffffffffffffffffff濚鿚鿚鿚鿚鿚鿚鿚쿚ffffff333333ffffff濚쿚鿚鿚ffffffffffffffffff濚鿚쿚鿚ffffff濚鿚鿚鿚鿚ffffffffffff333333333333ffffff濚ffffff333333333333ffffffffffffffffff濚ffffff濚쿚쿚ffffff333333333333ffffff濚鿚𿚙񿚙쿚ffffffffffff濚鿚鿚鿚쿚鿚ffffffffffffffffffffffff쿚쿚ffffff࿚ٿ333333333333ffffff쿚ffffff333333333333ffffff濚쿚ffffff333333333333ffffff濚쿚ffffff333333333333ffffff濚쿚ffffff333333ffffff쿚ffffff333333333333ffffff濚ffffffffffffffffff333333333333333333333333333333ffffff濚쿚ffffffffffffffffff333333333333ffffffffffff濚鿚鿚쿚ffffff333333333333ffffff濚쿚鿚333333࿚ٿٿ333333333333ffffff濚?333333࿚ٿ࿚ٿٿ333333ffffffffffff濚ffffff࿚ٿٿٿ࿚ٿٿ333333ӿ333333ӿ࿚ٿ࿚ٿٿٿٿٿ333333ffffff濚鿚333333࿚ٿٿ333333ӿ333333ӿ333333333333333333࿚ٿ333333ӿɿɿɿ333333ӿٿٿٿٿ333333ӿٿ333333333333333333㿚ٿٿ333333ӿɿ333333ӿ333333ӿٿ333333㿚쿚ffffff333333㿚ٿ333333ffffff濚ffffffffffffffffffffffffffffff濚鿚鿚鿚ffffffffffffffffff濚鿚鿚ffffff333333333333333333333333333333㿚ٿ333333ӿ333333ӿ333333ӿ333333࿚ٿ333333ӿ333333ӿɿɿɿɿ333333ӿ333333ӿ333333ӿ333333ӿɿɿɿɿ333333ӿ333333ӿɿɿɿɿɿɿɿɿɿɿ333333ӿɿ??333333?333333?333333?333333???333333?333333?333333?333333?333333?333333???333333??????333333???333333?333333?333333?????333333????333333???333333???????333333?333333?333333?333333?333333??????333333?333333???????333333?333333?333333????333333???????333333?333333?333333?333333??????333333?333333?333333?333333?????????333333?333333?333333?333333?333333????333333????333333?333333?333333???????????333333?????????????????????333333?333333?333333???????????333333?333333???333333?333333?333333?333333?333333?????333333?333333?333333????????????????????????????333333?333333?333333???333333?333333????333333????333333????333333?333333?????333333????ɿɿ??????ɿ333333ӿ?ɿɿɿ??ɿɿɿɿ333333ӿ333333ӿɿɿɿɿɿɿ333333ӿ333333ӿ333333ӿ333333ӿɿɿɿɿɿɿɿɿ333333ӿ333333ӿɿɿ333333ӿ333333ӿɿɿɿɿɿɿɿɿɿɿɿɿ333333ӿٿٿ333333ffffffffffff333333333333࿚ٿٿ333333㿚쿚鿚鿚鿚鿚鿚鿚鿚鿚쿚鿚鿚ffffffffffff濚쿚鿚鿚鿚鿚ffffffffffffffffffffffff333333333333333333ffffff333333࿚ٿٿٿ333333333333333333333333ӿɿɿɿɿ333333ӿɿɿ333333ӿ333333ӿٿ333333ӿɿɿɿ333333ӿٿٿ333333ӿɿɿɿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿٿٿٿٿ333333ӿɿɿ333333ӿٿ࿚ٿٿ333333ӿɿɿɿ333333ӿ333333ӿɿ333333ӿɿɿɿɿ333333ӿ333333ӿٿٿٿٿٿٿٿ333333ӿٿٿ333333ffffff濚鿚鿚鿚ffffff333333333333ffffffffffffffffff333333333333ffffff濚쿚ffffffffffff濚ffffffffffff333333333333ffffff濚쿚ffffff࿚ɿٿ333333ffffff濚ffffff333333333333333333333333ffffff濚鿚鿚ffffff333333333333333333ffffff濚鿚鿚ffffffffffffffffffffffff濚ffffff333333ffffffffffffffffff333333㿚ٿ333333333333ffffffffffff333333333333333333ffffffffffffffffffffffffffffff333333333333333333ffffffffffff쿚ffffff333333333333㿚ٿ333333ӿɿɿ333333ӿٿٿ333333㿚ٿ333333ӿɿɿ333333ӿٿ࿚ٿٿ࿚ٿ333333ӿ333333ӿ333333ӿffffff濚ffffffffffffffffff333333ffffff333333࿚ٿ333333333333ӿɿɿٿ࿚ٿ333333ӿɿɿɿɿ333333ӿ333333ffffff濚쿚ffffffffffff濚鿚ffffff333333333333ffffff濚쿚鿚ffffff333333࿚ٿ333333ffffff쿚鿚ffffff333333333333333333333333ffffffffffffffffffffffffffffff333333333333333333333333ffffffffffff濚ٿ333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333ffffff濚쿚ffffff333333㿚ٿٿٿٿ333333333333333333333333333333ffffffffffffffffff333333333333ffffff濚쿚鿚쿚ffffffffffff333333333333333333333333ffffffffffff濚ffffff333333333333ffffffffffff濚鿚鿚쿚鿚ffffffffffffffffffffffff濚쿚鿚쿚鿚쿚ffffffffffff濚쿚ffffffffffff濚鿚쿚ffffff333333333333333333ffffffffffff濚鿚鿚鿚ffffffffffffffffffffffffffffff333333333333333333ffffff濚쿚ffffff333333ffffffffffffffffff333333333333333333ffffff333333333333333333333333ffffff濚鿚鿚鿚鿚ffffff333333333333࿚ٿٿ333333ӿɿɿٿ333333ffffff333333333333ffffffffffffffffffffffff濚쿚鿚ffffff333333333333333333333333ffffff濚鿚쿚ffffffffffff333333333333333333ffffff濚ffffff333333333333333333333333333333333333ffffff濚鿚鿚ffffffffffffffffffffffff濚쿚ffffff333333333333ffffff濚쿚쿚鿚ffffff濚鿚鿚鿚鿚쿚鿚鿚鿚鿚ffffffffffffffffff濚鿚쿚鿚鿚鿚쿚鿚쿚鿚333333ffffff濚쿚ffffff࿚ٿffffff쿚ffffffffffff333333ffffff濚쿚ffffff333333333333ffffff쿚ffffff333333333333ffffff濚鿚鿚鿚鿚ffffffffffff333333333333333333ffffff쿚鿚ffffff333333333333ffffff濚鿚쿚ffffff333333333333333333ffffffffffffffffffffffffffffff333333ffffff濚쿚ffffff濚鿚ffffffffffff333333333333ffffffffffffffffff333333333333333333333333333333ffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff濚鿚쿚鿚鿚鿚鿚ffffff333333࿚ٿٿٿ333333ffffff濚鿚333333333333㿚ٿٿٿٿٿ࿚ٿٿٿ333333333333ffffff濚鿚쿚ffffff࿚ٿٿٿٿٿٿ333333333333333333ffffffffffffffffffffffff333333333333ffffffffffff濚ffffff333333࿚ٿ333333ffffffffffffffffff333333333333333333ffffff濚ffffff333333333333333333333333333333ffffff濚쿚鿚ffffff333333ffffffffffff濚鿚ffffff333333333333333333ffffffffffff濚鿚鿚鿚鿚ffffff333333333333333333333333ӿffffff濚ٿ333333ӿ333333ӿٿ333333333333333333333333333333333333ffffffffffffffffff333333333333ӿɿɿ333333ӿ333333333333333333333333࿚ٿٿٿffffffffffff333333333333࿚ٿ333333333333333333333333ffffff333333333333333333ffffffffffffffffff333333࿚ٿٿٿٿ333333333333ffffff濚鿚鿚鿚ffffffffffffffffff濚鿚ffffffffffffffffff333333ffffff濚ffffff333333࿚ٿٿٿ333333ffffffffffff濚ffffff333333333333ffffff濚쿚ffffff333333㿚ٿ333333ӿٿٿffffff333333333333࿚ٿ333333ffffffffffff쿚鿚ffffff࿚ٿ333333ffffffffffffffffff333333ffffff濚쿚ffffff333333333333333333ffffff濚鿚鿚鿚ffffffffffff333333333333333333ffffffffffffffffffffffff333333333333333333333333333333㿚ٿٿٿٿ333333333333࿚ٿ࿚ٿ333333ӿ333333ӿɿɿɿ333333ӿ333333ӿ333333ӿٿ333333333333࿚ٿ333333ӿ333333ӿٿٿٿ333333ӿɿ333333ӿٿ333333333333ffffff濚ffffffffffff333333333333ffffffffffff333333333333ffffff濚ffffff333333333333333333ffffff濚ffffff333333࿚ٿ333333ffffffffffffffffffffffff333333ffffff濚鿚쿚333333333333333333333333333333㿚ٿ333333333333333333333333333333333333333333ffffff濚𿚙ffffffffffff333333ffffffffffffffffff濚鿚鿚쿚ffffff333333࿚ٿ333333333333333333333333333333333333ӿٿ333333333333333333333333333333333333333333333333࿚ٿ333333ffffffffffffffffff333333࿚ٿffffffffffff濚ffffff333333333333333333333333࿚ٿ333333ӿٿٿٿٿٿٿٿ࿚ٿ333333ffffffffffff333333333333333333333333333333333333333333333333333333㿚鿚쿚쿚ffffffffffff333333333333333333333333࿚ٿٿ333333ӿ333333ӿٿٿٿٿٿٿ333333ӿɿɿɿɿٿ333333333333333333333333333333㿚ٿ333333ӿ333333ӿɿɿ333333ӿ333333ӿ333333ӿ333333ӿٿ333333ӿ333333ӿ333333ӿٿ333333ӿ333333ӿɿɿ333333ӿٿ࿚ٿ333333ӿɿɿɿ333333ӿ333333ӿ333333ӿɿɿɿ333333ӿ333333ӿ333333ӿ333333ӿɿɿɿٿ333333ӿ333333ӿ333333ӿɿɿɿɿɿ333333ӿٿٿ333333ӿ333333ӿ333333ӿٿٿٿɿɿ333333ӿ333333ӿ࿚ٿٿ333333ӿٿٿٿ333333ӿɿ333333ӿ333333ӿ333333ӿٿٿ333333333333࿚ٿٿ333333ӿ333333ӿٿɿɿɿ333333ӿٿٿٿٿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿɿɿ333333ӿٿ࿚ٿٿٿٿٿ333333ӿ333333ӿٿٿٿ333333ӿɿɿɿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿɿɿɿɿɿ333333ӿٿ࿚ٿ333333ӿɿɿ333333ӿ333333ӿ333333ӿ333333ӿɿ333333ӿ333333ӿٿ333333ӿɿɿɿɿ333333ӿɿɿ333333ӿ333333ӿٿٿ333333ӿɿɿ333333ӿٿٿ333333ӿ333333ӿ333333ӿٿٿ333333ӿɿɿɿ333333ӿ࿚ٿ333333ӿ333333ӿٿٿٿ333333ӿɿ333333ӿɿ333333ӿ333333ӿɿ333333ӿ333333ӿɿٿٿ333333333333ffffff濚ffffff333333ӿ333333ӿٿffffff濚鿚鿚333333333333ffffffffffffffffffffffff333333333333333333ffffffffffff333333333333333333ffffff濚ffffffffffffffffff濚鿚ffffffffffffffffffffffff濚쿚鿚쿚鿚쿚쿚鿚鿚鿚鿚鿚ffffff333333333333ffffff濚ffffff333333333333333333ffffff濚쿚鿚鿚쿚쿚鿚鿚쿚鿚ffffff333333333333ffffffffffff濚鿚鿚鿚쿚鿚ffffff333333࿚ٿ333333㿚ffffff333333333333333333ffffff쿚ffffff333333333333333333ffffff濚鿚ffffffffffff333333ffffffffffffffffffffffff濚ffffff333333333333ffffff濚쿚鿚鿚鿚鿚ffffff333333333333333333ffffffffffff濚鿚鿚鿚鿚鿚鿚鿚ffffffffffffffffffffffff濚鿚鿚鿚쿚鿚鿚鿚鿚鿚鿚鿚쿚鿚鿚鿚鿚ffffffffffffffffffffffff濚쿚鿚ffffff濚ffffffffffffffffffffffff濚쿚鿚鿚鿚ffffff333333ӿffffff쿚333333࿚ٿ333333ffffff濚ffffffffffff333333333333ffffffffffffffffffffffff濚鿚쿚鿚ffffffffffff濚鿚鿚쿚鿚鿚쿚鿚쿚쿚鿚ffffffffffffffffffffffff濚쿚333333333333ffffffffffff쿚鿚鿚鿚鿚ffffffffffffffffff濚쿚鿚鿚鿚ffffffffffffffffffffffff濚쿚ffffff333333333333ffffff쿚ffffffffffffffffffffffffffffffffffff333333333333333333ffffff濚鿚ffffff࿚ٿ333333333333333333333333ffffff333333࿚ٿ333333ӿ333333ӿٿٿٿ333333࿚333333ӿٿ333333ffffff濚ffffff333333ӿٿٿ333333ffffff濚鿚鿚鿚鿚鿚鿚ffffff濚ffffffffffff333333333333ffffffffffff濚ffffff333333333333333333ffffffffffff濚鿚鿚쿚ffffff333333㿚ٿ333333ffffff濚鿚ffffff333333333333ffffff濚쿚ffffff333333࿚ٿٿٿ333333333333333333࿚ٿٿ࿚ٿٿٿffffffffffff濚ffffff333333㿚ٿ333333ӿ333333ӿٿ333333ӿ333333ӿٿٿٿ333333333333333333ffffff333333ӿٿ333333ӿ333333ӿɿٿ333333ffffff쿚鿚ffffff333333333333333333333333333333࿚ٿ333333333333333333333333ӿ333333ӿ333333ӿ333333ӿٿٿٿٿٿ333333333333333333333333333333ffffffffffff࿚ٿٿٿ࿚ٿ333333ӿ333333ӿٿٿٿ333333ӿ333333ӿٿffffffffffff333333㿚ٿ333333ӿٿffffff濚鿚333333㿚ٿٿٿٿ333333ffffffffffff濚ffffffffffff333333ӿ333333ӿ333333ӿٿ333333333333333333333333333333333333333333࿚ٿٿɿ쿚ٿٿٿ333333ffffffffffffffffff333333ffffff濚쿚333333㿚ٿ333333ӿ333333ӿ333333ӿٿ࿚ٿ333333ӿɿ333333ӿ333333ӿ333333ӿɿ333333ӿ333333ӿ鿚ٿٿٿٿ333333ӿ333333ӿ333333ӿ333333ӿ࿚ٿٿٿٿٿٿ333333ӿ333333ӿ333333ӿ333333ӿɿɿɿɿɿ333333ӿٿ333333࿚ٿ333333ӿɿɿٿ333333࿚ٿ333333ӿɿɿɿ333333ӿٿٿٿɿɿ333333ӿٿٿ࿚ٿ࿚ٿٿٿ333333333333333333333333࿚ٿٿٿ333333ӿٿٿٿ333333333333333333333333333333333333333333333333333333333333333333333333333333ffffffffffffffffff333333࿚ٿ333333ӿɿɿɿɿɿɿɿ333333ӿٿٿٿ333333ӿɿɿ333333ӿ333333ӿɿɿɿ333333ӿ333333ӿ333333ӿɿɿɿɿٿٿٿ333333ӿɿɿɿɿ333333ӿٿ333333ӿ333333ӿɿɿ333333ӿٿ333333ӿ333333ӿɿ333333ӿٿ333333ӿ333333ӿ333333ӿɿɿ333333ӿɿɿɿɿ333333ӿ333333ӿ333333ӿٿ333333ӿɿɿɿ333333ӿٿ࿚ٿٿ333333ӿɿɿ333333ӿٿ333333࿚ٿٿ࿚ٿٿ࿚ٿٿٿٿ333333ӿ333333ӿɿ333333ӿ333333ӿ333333㿚333333࿚ɿٿ࿚ٿٿ333333ӿɿɿɿɿɿɿ333333ӿٿ333333㿚ٿ333333ӿ333333ӿٿٿٿٿٿٿٿ࿚ٿ333333ӿ333333ӿٿ࿚ٿ333333ӿ333333ӿٿ࿚ٿ࿚ٿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿٿ333333ӿɿɿɿ333333ӿٿٿ࿚ٿ333333ӿ333333ӿ333333ӿɿɿɿ333333ӿ333333333333333333ӿ333333ӿ333333ӿٿٿٿٿ333333333333333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿٿ333333㿚鿚ffffff333333࿚ٿ333333333333333333ffffffffffffffffff濚ffffff333333ffffff濚鿚쿚333333࿚ٿٿٿٿٿ333333㿚ffffffffffff࿚ٿٿffffff濚鿚ffffff333333333333333333333333ffffffffffff333333333333333333333333333333ffffffffffff쿚ffffffffffffffffffffffff333333333333ffffffffffff濚ffffff333333㿚ٿɿɿ333333ӿٿٿٿٿٿ333333ӿ333333ӿ333333ӿ333333ӿٿ333333ӿɿɿɿɿɿɿɿ333333ӿ333333ӿɿɿɿɿ333333ӿٿ333333ӿ333333ӿɿ333333ӿٿ࿚ٿ࿚ٿٿٿٿٿ333333࿚ٿ333333333333ffffffffffff333333࿚ٿ333333ӿ333333ӿ333333333333࿚ٿٿٿ333333ffffffffffff333333333333333333ffffffffffff濚鿚ffffff333333333333㿚鿚ffffff333333ffffffffffff濚鿚鿚鿚ffffffffffff333333333333ffffffffffff濚鿚ffffff333333333333࿚ٿ333333ffffff쿚ffffff333333㿚ٿ333333ffffffffffff濚쿚ffffffffffff濚鿚𿚙ffffffffffffffffff濚쿚鿚ffffff࿚ٿffffff濚쿚鿚鿚쿚쿚ffffff333333333333ffffff濚쿚鿚鿚鿚鿚鿚ffffffffffff333333ffffffffffffffffff濚鿚쿚鿚鿚鿚鿚鿚鿚鿚鿚쿚鿚ffffffffffff濚쿚333333333333ffffffffffffffffffffffff濚ffffffffffffffffffffffff濚鿚쿚鿚鿚쿚ffffff࿚ٿٿٿ333333ffffff濚쿚ffffff333333333333ffffffffffff濚鿚鿚鿚鿚쿚鿚鿚鿚쿚ffffffffffff濚쿚ffffffffffffffffff濚鿚333333333333333333333333333333ffffffffffffffffffffffff濚ffffff333333333333333333333333ffffffffffffffffffffffffffffff濚鿚鿚쿚쿚鿚鿚쿚ffffff333333333333ffffffffffff쿚ffffffffffffffffffffffff濚鿚鿚鿚ffffffffffff333333333333333333ffffff濚쿚ffffff濚鿚鿚鿚鿚鿚쿚333333333333333333ffffff濚쿚鿚鿚ffffff濚鿚鿚鿚ffffffffffff333333333333ffffff濚鿚쿚鿚鿚ffffffffffffffffff333333333333ffffff濚ffffffffffff࿚ٿ333333333333ffffff濚ffffff濚ɿ333333ӿٿ333333ffffff濚쿚ffffff333333333333333333࿚쿚ٿ333333ӿɿ333333ӿ333333ӿٿٿ333333㿚쿚ffffff333333ӿٿٿ333333ffffffffffffffffffffffff333333333333333333ffffffffffffffffff濚鿚ffffffffffffffffffffffffffffff濚鿚鿚鿚鿚鿚쿚ffffff333333333333333333ffffffffffff濚鿚ffffff࿚ٿ333333ӿٿ333333ffffff濚鿚鿚333333㿚ٿٿٿ࿚ٿ333333ӿٿ333333ӿٿ333333333333ffffff濚쿚ffffffffffffffffff濚쿚ffffff濚ffffff濚鿚ffffff333333333333333333333333333333333333ffffff濚鿚쿚ffffff333333333333333333333333333333333333333333ffffffffffff333333333333333333333333ffffffffffffffffff333333ffffff濚鿚鿚࿚ٿffffffffffffffffffffffff333333333333࿚ٿٿ333333ӿ333333ffffff333333࿚ٿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿٿ333333333333333333333333ffffff333333333333333333333333ffffff濚쿚ffffffffffff333333333333333333ffffff333333333333㿚ٿffffff濚鿚ffffff333333333333ffffffffffffffffff333333333333ӿ333333ӿ333333ӿ333333ӿ333333ӿٿ333333㿚鿚ffffff333333333333333333ffffff쿚鿚쿚ffffff333333࿚ٿ࿚ٿٿ333333ӿ333333㿚鿚ffffff333333333333333333ffffff濚鿚ffffff333333㿚ٿ333333㿚鿚鿚鿚ffffff333333࿚ٿٿٿٿ333333ffffffffffffffffff333333333333333333333333333333333333333333333333࿚ٿٿٿ333333ffffff333333ffffffffffff濚쿚鿚ffffff333333ffffffffffff濚鿚ffffff333333࿚ٿ333333333333㿚쿚ffffff࿚ٿffffff𿚙ffffff333333333333ffffffffffffffffff࿚ٿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿٿ333333ӿ333333ӿɿɿ333333ӿ333333ӿٿٿٿ333333ӿٿ333333333333333333ffffffffffffffffffffffff333333333333333333࿚ٿٿٿ333333333333333333333333ffffff濚ffffff333333㿚ٿɿɿɿ333333ӿٿٿ࿚ٿ333333333333ӿɿɿ333333ӿ333333ӿ333333ӿ333333ӿٿٿٿٿٿٿ333333ӿɿ333333ӿ333333ӿ333333ӿɿɿɿ333333ӿٿ333333ӿɿɿ333333ӿٿ࿚ٿɿɿɿɿɿɿɿɿɿ333333ӿɿɿɿɿ333333ӿ333333ӿ333333ӿٿ333333ӿɿɿɿ333333ӿٿٿ333333ӿ333333ӿ333333ӿ333333ӿٿٿٿ333333ӿ333333ӿɿ333333ӿٿ333333㿚ٿ333333ӿɿ333333ӿٿٿ࿚ٿɿɿɿɿɿɿɿɿɿ333333ӿɿɿ333333ӿ333333ӿٿ࿚ٿٿ333333ӿ333333ӿ333333ӿٿ࿚ٿٿ333333ӿɿɿɿ333333ӿٿٿ333333࿚ٿٿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿɿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿٿ࿚ٿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿٿ࿚ٿ333333ӿɿɿ333333ӿ333333࿚ٿ333333ӿ333333ӿ333333ӿɿɿɿɿ333333ӿ333333333333࿚ٿ333333ӿ333333ӿٿٿٿ333333ffffff濚鿚ffffffffffff333333࿚ٿ333333ӿ333333ӿ333333ӿٿٿ333333ffffffffffff濚ffffff333333࿚ٿ333333ffffff濚鿚ffffff333333ffffff濚쿚333333333333ffffff濚쿚333333333333333333ffffff濚鿚鿚쿚鿚鿚鿚鿚ffffffffffffffffff濚鿚鿚ffffffffffffffffffffffff濚ffffffffffffffffffffffff濚鿚鿚鿚쿚쿚鿚333333333333ffffff濚쿚鿚쿚ffffffffffff333333ffffff333333333333ffffffffffff濚鿚鿚鿚鿚쿚鿚鿚鿚鿚鿚쿚鿚ffffffffffffffffff濚ffffffffffff333333333333ffffffffffff濚鿚鿚ffffff333333࿚ٿ333333㿚쿚333333ffffff濚鿚ffffffffffff333333333333333333333333ffffff濚쿚ffffff333333333333ffffff濚ffffff333333333333ffffffffffff333333333333333333333333ffffff333333333333࿚ٿٿٿffffff濚쿚ffffff333333333333ffffff濚ffffff333333333333ffffff濚鿚ffffffffffff濚鿚鿚鿚333333333333333333333333333333333333ffffff333333333333㿚?ffffffffffffffffff333333333333333333ffffffffffff濚쿚ffffff333333333333ffffffffffffffffffffffff࿚ٿٿٿffffff濚鿚ffffff333333࿚ٿٿٿ333333ffffff333333333333333333333333ffffffffffff濚鿚333333ӿ333333333333333333333333ffffffffffffffffff333333ffffff濚鿚鿚鿚쿚333333333333ffffff濚鿚鿚鿚ffffffffffff濚鿚쿚鿚쿚ffffffffffffffffff濚ffffffffffff333333333333333333ffffffffffffffffff濚쿚ffffffffffff濚鿚쿚쿚鿚쿚ffffff濚鿚鿚鿚ffffff333333333333ffffff쿚쿚쿚鿚鿚鿚鿚鿚ffffff濚鿚鿚쿚鿚鿚쿚鿚鿚鿚鿚鿚鿚鿚鿚ffffff333333333333333333ffffff쿚鿚鿚鿚ffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff濚鿚鿚ffffffffffffffffffffffff濚쿚ffffff࿚ٿٿٿ333333ӿ333333ӿٿ333333㿚쿚鿚ffffff333333333333333333ffffff濚ffffffffffffffffff333333333333333333ffffff濚鿚鿚鿚鿚ffffffffffff333333333333㿚ffffff333333333333ffffff濚鿚ffffff濚鿚鿚鿚鿚쿚鿚鿚鿚鿚ffffffffffffffffff濚鿚鿚ffffff333333333333ffffff쿚333333㿚ٿ333333ӿٿ333333㿚쿚ffffffffffffffffffffffff쿚ffffffffffffffffffffffff濚鿚鿚쿚ffffff333333333333333333333333333333333333ffffffffffffffffff濚鿚鿚ffffff333333ffffffffffff濚鿚鿚鿚ffffffffffff333333333333333333333333ffffffffffff333333333333333333333333333333333333333333ffffffffffffffffff࿚ٿٿ333333ffffff333333333333333333333333333333ffffff濚ffffffffffff333333ffffffffffff濚ffffff࿚ٿffffff濚쿚333333333333333333333333333333࿚࿚ٿ333333ӿٿٿ333333333333ffffffffffff濚ffffffffffff࿚ٿٿ333333ffffffffffff濚ffffffffffffffffff333333ffffff濚鿚鿚鿚鿚鿚鿚ffffff333333333333333333ffffffffffff濚ffffff333333333333333333ffffffffffffffffff࿚ٿffffffffffff࿚ٿ333333ffffffffffff333333࿚ٿٿ333333ffffffffffffffffff濚ffffff333333333333333333㿚鿚ffffff333333333333ffffff쿚ffffff333333333333333333ffffff濚쿚ffffff333333333333333333333333㿚鿚ffffff333333㿚ٿٿٿٿ࿚ٿٿٿ࿚ٿ333333333333333333333333ffffffffffff쿚ffffffffffffffffff濚鿚ffffffffffff333333333333ffffff쿚333333333333ffffffffffff濚쿚鿚ffffffffffffffffffffffffffffffffffffffffff333333333333㿚ٿٿ333333㿚鿚鿚鿚鿚쿚ffffffffffff濚鿚쿚333333333333333333ffffffffffff濚鿚ffffffffffffffffff333333333333333333ffffff쿚鿚ffffff333333333333࿚ٿٿ333333ӿ333333ӿɿ333333ffffff333333333333࿚ٿffffff濚쿚鿚쿚ffffff࿚ٿٿٿٿ333333333333333333ffffff濚ffffff333333࿚ٿٿٿٿ333333ffffff濚鿚ffffff࿚ٿٿ333333ffffffffffffffffff333333333333ffffffffffffffffff333333㿚ٿ333333ffffffffffff333333333333333333333333333333࿚ٿٿٿ333333ffffff濚鿚333333㿚ٿٿ333333ӿ333333ӿ333333ӿٿ333333ffffffffffff333333333333333333333333333333333333333333࿚ٿٿ333333333333333333333333333333333333333333࿚ٿ333333ӿ333333ӿ333333333333333333࿚ٿٿٿٿ333333333333333333333333ӿɿ333333ӿٿ333333333333333333333333333333ffffffffffff濚ffffffffffff333333333333ffffff濚ffffff333333333333࿚ٿٿ333333ӿٿ333333333333333333࿚ٿ333333ӿ333333ӿٿ333333ffffffffffff濚鿚ffffff333333333333ffffffffffff濚鿚ffffff333333࿚ٿٿٿٿffffff濚쿚ffffff333333333333ffffffffffff濚ffffff333333333333333333ffffffffffffffffffffffff濚쿚鿚ffffff333333333333࿚ٿٿٿٿ333333ffffffffffff333333333333333333333333333333࿚ٿٿٿٿ࿚ٿٿٿٿٿٿ333333333333࿚ٿٿٿٿٿٿ333333ӿٿ333333333333333333㿚ٿٿٿ333333࿚ٿٿ࿚ٿ333333333333333333ӿɿ333333ӿٿٿٿ333333ӿ333333ӿٿ333333ffffffffffffffffff333333࿚ٿٿ333333333333333333333333333333࿚ٿٿ333333ӿ333333ӿٿٿٿ333333࿚ٿٿٿٿ333333333333333333333333333333࿚ٿٿٿٿ333333333333333333333333333333333333ffffffffffffffffffffffffffffff333333333333333333࿚ٿ࿚ٿٿ333333ffffff쿚333333333333333333ffffff濚ffffffffffff333333333333ӿ333333ӿɿffffff࿚ٿٿٿ333333333333333333333333333333333333333333333333333333㿚ٿɿ333333ӿ333333ӿ333333333333333333333333333333333333ffffff濚쿚ffffff333333࿚ٿٿ333333333333ffffff濚鿚쿚鿚ffffff333333333333ffffff333333333333333333࿚ٿٿٿٿٿٿٿ333333㿚𿚙333333㿚ٿٿٿٿ333333ffffff濚쿚鿚ffffffffffff333333333333࿚ٿٿ333333࿚ٿɿ333333ӿɿ333333ӿ333333ӿٿ333333333333333333333333333333333333333333333333333333333333ffffff濚쿚ffffffffffff濚쿚ffffff࿚ٿ333333ffffff濚ffffffffffff333333࿚ٿٿ333333333333333333333333333333333333333333333333333333333333333333쿚ɿٿٿ333333333333ffffffffffff333333333333333333333333333333ffffffffffff濚鿚ffffff333333㿚ٿٿ333333333333333333333333333333333333333333333333333333333333ffffff濚ffffffffffff333333ffffffffffff濚쿚쿚ffffffffffffffffffffffff濚鿚쿚ffffff333333333333333333ffffff濚ffffffffffff333333333333333333333333333333333333ffffff쿚ffffff333333333333333333ffffff濚鿚鿚ffffff333333ffffffffffffffffff333333333333ffffffffffffffffffffffff333333333333333333ffffffffffffffffffffffff333333333333333333333333ffffff濚ffffff333333࿚ٿ333333ffffff濚鿚333333333333333333333333ffffff濚쿚ffffff333333333333333333ffffff𿚙333333࿚ٿ333333ffffff쿚ffffffffffff333333333333ffffff濚쿚鿚ffffffffffffffffff濚쿚ffffff333333333333࿚ٿٿ333333333333㿚鿚ffffff333333333333333333ffffff濚쿚鿚ffffff333333ffffffffffff쿚鿚鿚ffffffffffff333333333333333333࿚ٿٿٿ333333ffffff濚𿚙333333333333㿚鿚쿚ffffff333333333333ffffff濚쿚333333333333333333ffffff濚鿚쿚ffffffffffffffffff濚쿚ffffff࿚ٿffffff濚쿚ffffff333333ffffff濚쿚ffffff333333333333ffffff濚쿚ffffff333333333333ffffff濚鿚鿚鿚쿚ffffff333333333333ffffffffffffffffff濚ffffffffffffffffffffffffffffff濚鿚ffffffffffff333333333333333333333333333333ffffff쿚ffffff333333333333ffffff濚鿚쿚鿚ffffff濚쿚鿚鿚鿚鿚鿚ffffffffffff濚쿚ffffffffffffffffff濚쿚鿚쿚ffffffffffffffffff쿚ffffff333333ffffff濚쿚333333ffffffffffff濚鿚ffffff333333333333ffffff濚鿚쿚鿚ffffffffffffffffffffffffffffff濚쿚ffffff濚鿚鿚쿚ffffffffffffffffffffffff쿚ffffff333333333333ffffff濚쿚鿚ffffffffffff333333333333333333ffffff濚쿚ffffff333333333333333333ffffffffffff濚鿚鿚ffffff333333࿚ٿٿٿ333333ffffff濚鿚鿚鿚鿚ffffffffffffffffffffffff濚鿚ffffff333333333333333333333333ffffff濚鿚鿚鿚鿚鿚ffffffffffffffffffffffff濚鿚ffffffffffff333333㿚ffffff333333333333333333333333ffffff濚ffffffffffff333333333333333333333333333333ffffff濚鿚쿚333333333333ffffff濚쿚ffffff333333333333ffffff濚쿚ffffff濚鿚鿚쿚ffffffffffff333333333333ffffff濚ffffff333333333333ffffff濚쿚鿚쿚ffffff濚鿚鿚鿚鿚鿚ffffffffffff333333333333333333ffffffffffff333333333333ffffff濚鿚ffffffffffff333333ffffffffffffffffff濚ffffffffffffffffffffffffffffff333333333333333333333333333333333333333333333333333333333333ffffff濚쿚鿚쿚鿚ffffffffffffffffffffffffffffff濚ffffff333333࿚ٿ333333333333333333333333ffffff濚鿚鿚ffffff333333333333ffffffffffff濚鿚ffffffffffffffffff濚鿚鿚鿚鿚鿚ffffff333333࿚ٿ333333ffffff濚ffffff333333333333333333ffffff濚鿚鿚쿚ffffffffffffffffff濚쿚ffffffffffffffffffffffff濚ffffff333333333333ffffffffffff濚鿚쿚鿚鿚鿚鿚ffffffffffffffffffffffff濚鿚鿚쿚ffffffffffffffffff濚鿚鿚鿚쿚鿚ffffff濚鿚鿚鿚鿚ffffffffffff濚鿚鿚쿚鿚333333333333333333333333333333333333333333333333333333333333ffffff濚鿚鿚鿚鿚鿚鿚鿚ffffff333333333333333333333333333333ffffff濚鿚쿚鿚鿚𿚙333333࿚ٿ333333㿚鿚鿚쿚ffffff333333333333ffffff濚鿚鿚ffffffffffffffffff333333ffffffffffffffffff쿚鿚쿚333333333333333333ffffff𿚙ffffffffffff333333㿚鿚鿚鿚ffffff333333333333333333ffffff濚쿚ffffffffffff濚쿚鿚ffffff333333ffffffffffffffffff濚ffffff333333࿚ٿ333333ffffff濚ffffffffffff333333333333333333ffffff濚ffffff333333333333ffffff濚쿚ffffffffffff333333333333ffffffffffff333333333333333333ffffff濚ffffffffffff333333333333333333333333333333333333333333ffffff333333333333333333333333333333333333333333333333333333ffffffffffffffffff333333333333ffffff濚ffffff333333333333㿚鿚ffffff333333࿚ٿٿٿffffff濚鿚쿚ffffff333333ffffffffffff濚쿚鿚ffffff333333333333ffffffffffff濚鿚鿚鿚鿚鿚쿚ffffff࿚ٿٿٿٿٿ333333㿚𿚙333333㿚ٿٿ333333ffffffffffff333333333333333333333333333333333333333333333333333333ffffff濚쿚ffffff࿚ٿٿffffff濚쿚鿚ffffff333333ffffff濚鿚쿚ffffffffffff333333333333333333333333ffffff濚ffffff࿚ٿ333333ffffff濚ffffffffffff333333࿚ٿٿ333333333333333333333333ffffff濚鿚鿚鿚ffffff333333333333ffffff濚쿚鿚쿚쿚ffffff濚鿚鿚쿚ffffffffffffffffff濚鿚鿚쿚ffffff333333333333ffffffffffff濚쿚ffffff濚鿚鿚鿚鿚鿚ffffffffffff333333333333333333333333333333ӿffffff333333333333ffffff濚鿚ffffff濚鿚쿚鿚ffffffffffff333333333333333333333333࿚ٿ333333㿚ٿٿٿ333333333333333333333333333333333333ffffffffffffffffffffffffffffffffffff333333333333333333333333333333ffffff333333333333࿚ٿ333333333333333333333333㿚ٿ333333ӿɿɿɿ333333ӿ333333ӿ333333ffffff濚ffffff333333333333333333333333333333࿚ٿ333333ӿ333333ӿٿ333333333333333333333333࿚ٿ333333࿚ٿ333333ӿ333333ӿ333333333333333333ӿ333333ӿ333333ӿ333333ӿٿ࿚ٿ333333ӿɿ333333ӿٿ333333333333ӿ333333ӿٿ333333333333࿚ٿ333333ӿɿ333333ӿ333333ӿ333333ӿ333333ӿɿ333333ӿٿٿٿ333333ӿٿٿٿ333333ӿٿ࿚ٿ࿚ٿ333333ӿ333333ӿɿɿ333333ӿɿɿɿɿ333333ӿ333333ӿ333333ӿɿɿ333333ӿɿ333333ӿ333333ӿٿ࿚ٿ333333ӿɿɿ333333ӿ333333ӿ࿚ٿ333333ӿ333333ӿ333333ӿ333333333333333333333333ӿ333333ӿɿ333333ӿٿٿ࿚ٿٿٿٿٿٿٿٿٿٿٿ࿚ٿٿٿٿٿ࿚ٿٿ࿚ٿ333333ӿ333333ӿɿɿ333333ӿ333333ӿٿٿ333333ӿ333333ӿ333333ӿ333333ӿٿ333333333333333333333333࿚ٿٿ333333ӿٿ࿚ٿ333333ӿ333333ӿɿɿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿɿ333333ӿٿ࿚ٿٿ333333ӿ333333ӿٿٿٿ333333ӿ333333ӿɿ333333ӿٿٿٿٿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿɿ333333ӿ333333ӿٿ࿚ٿ333333ӿ333333ӿٿ333333ӿ333333ӿ333333ӿ333333ӿٿ333333ӿ333333ӿ333333ӿٿ333333ӿ333333ӿ333333ӿٿٿٿ333333ӿ333333ӿٿٿ࿚ٿ333333ӿ333333ӿ333333ffffff333333㿚ٿ333333ӿ333333ӿٿ333333ffffffffffff333333㿚ٿ333333ӿ333333ӿ333333ӿ333333ӿɿ333333ӿ333333ӿٿٿٿ333333ffffffffffffffffff333333333333333333333333ffffff333333࿚ٿٿ333333㿚鿚쿚333333ffffff濚鿚ffffffffffff333333333333333333࿚ٿ333333333333333333࿚ٿٿ333333ӿٿ࿚ٿٿٿٿٿ333333ffffff333333ffffffffffffffffffffffffffffffffffffffffffffffffffffff333333333333333333ffffff濚鿚333333333333ӿٿٿ࿚ٿٿٿ333333ӿ333333ӿ333333ӿٿ࿚ٿٿffffffffffffffffff333333ӿٿ333333333333333333ffffffffffffffffffffffffffffffffffff濚쿚ffffffffffff333333333333ffffffffffff333333333333ӿffffff濚鿚ffffffffffff333333333333ffffff333333࿚ٿ333333333333333333333333333333ӿɿɿٿٿ࿚ٿٿٿ333333333333࿚ٿٿ333333ӿٿٿٿ333333ӿ333333ӿ333333ӿ333333ӿٿ333333ffffff濚ffffff333333333333ӿٿٿ࿚ٿ333333ӿɿɿٿٿٿٿ333333ӿٿ࿚ٿٿٿ333333࿚ٿٿ333333ffffffffffff333333㿚ٿ333333ӿ333333ӿ333333ӿٿٿٿ333333ӿ333333ӿɿ333333ӿٿ333333ӿ333333ӿ333333ӿɿɿ333333ӿ࿚ٿ333333ӿɿ333333ӿ333333ӿٿ࿚ٿٿ333333ӿ333333ӿ333333ӿ333333ӿٿ333333ӿ333333ӿٿ333333࿚ٿɿɿɿɿ333333ӿٿٿٿ333333ӿɿɿ333333ӿٿ333333ffffff濚鿚ffffff333333ffffff쿚333333࿚ٿ࿚ٿٿ333333ffffffffffffffffff333333࿚ٿٿ333333ffffff濚ffffff333333㿚ٿ࿚ٿٿٿffffff濚鿚ffffff࿚ٿ333333ffffff333333333333333333࿚ٿٿٿ333333ffffffffffff濚ffffff333333333333333333333333333333ffffffffffff濚鿚ffffff333333ffffff濚쿚333333333333333333㿚쿚333333333333࿚ٿٿ333333㿚ffffff333333࿚ٿ333333ӿ333333ӿ333333ӿ333333ӿٿٿٿ333333ӿ333333ӿٿ333333ffffff濚鿚ffffff333333ffffffffffff濚쿚ffffff333333333333ffffff濚쿚ffffff333333333333ffffff濚ffffff333333333333333333333333333333333333ffffffffffff濚ffffff333333࿚ٿٿ333333ffffff쿚ffffffffffffffffff濚쿚ffffff333333333333ffffffffffff濚鿚鿚ffffff333333333333333333㿚쿚333333࿚ٿٿffffff濚鿚鿚鿚ffffffffffff333333ffffffffffffffffffffffff333333333333333333333333333333333333333333ffffffffffffffffffffffff333333333333333333333333333333ffffffffffffffffffffffff333333࿚ٿٿffffff濚鿚ffffffffffff333333ffffffffffff濚鿚ffffff࿚ٿ333333ffffff濚쿚ffffff333333ffffff濚쿚ffffff333333333333333333333333ffffffffffffffffff濚ffffff333333ffffff333333ffffff쿚鿚鿚鿚ffffffffffff333333࿚ٿ333333ffffff濚鿚ffffff333333333333ffffff濚쿚ffffff333333333333ffffff濚쿚ffffff࿚ٿٿ333333ffffffffffffffffffffffff濚ffffffffffffffffff333333333333333333333333ffffff濚쿚쿚鿚쿚鿚333333ffffffffffff濚鿚鿚쿚ffffff333333333333ffffff濚ffffffffffffffffffffffff濚쿚鿚鿚鿚鿚ffffff333333333333ffffffffffff濚ffffffffffffffffff333333ffffff濚鿚鿚鿚鿚ffffff333333࿚ٿ333333333333333333㿚?333333333333333333ffffff濚鿚ffffffffffff333333333333ӿٿffffff濚鿚ffffff333333333333ffffff濚鿚鿚鿚쿚ffffff333333333333333333333333333333333333㿚鿚쿚333333333333ffffff濚쿚鿚ffffff333333ffffff濚鿚쿚鿚ffffff333333333333333333ffffff濚쿚333333333333ffffff濚ffffffffffff࿚ٿٿffffffffffff333333333333333333ӿ333333ӿ333333ӿٿ333333333333333333࿚ٿ࿚ٿ333333ӿɿɿ333333ӿٿ333333ffffff쿚ffffff333333333333333333333333333333ffffff濚ffffff333333333333ffffff쿚ffffff333333333333333333ffffff濚鿚ffffff333333333333333333ffffffffffff濚鿚ffffffffffff333333333333ffffff濚쿚ffffff333333333333ffffff𿚙ffffff333333333333333333333333࿚ٿffffff濚鿚鿚鿚鿚ffffffffffff333333333333333333ffffff濚鿚鿚鿚鿚ffffff333333333333333333ffffffffffff濚쿚ffffff333333ӿ333333ffffffffffff333333333333333333ffffff濚ffffff333333࿚ٿ333333ffffff333333333333333333ffffffffffff濚쿚ffffff࿚ٿٿ333333㿚쿚ffffff333333333333333333333333ffffffffffffffffffffffff333333333333333333333333333333333333333333333333࿚ٿٿٿ333333ӿ333333ӿٿٿٿ333333333333333333333333333333333333333333333333333333333333333333ffffff濚ffffff濚鿚ffffffffffff333333ffffff濚鿚ffffff333333ffffff濚𿚙ffffff333333㿚ٿ333333ffffffffffff濚鿚鿚鿚ffffff333333࿚ٿٿٿٿ333333ffffffffffff333333333333333333ffffff濚쿚ffffff333333333333ӿɿ333333ӿٿ333333ffffff333333ffffff濚鿚ffffff333333333333333333333333333333333333ffffff333333333333࿚ٿٿٿ333333㿚ٿ333333ӿ333333ӿ333333ӿٿٿ333333ӿٿٿٿ333333ӿ333333ӿ333333ӿ࿚ٿٿ333333333333㿚쿚ffffff࿚ٿffffff濚ٿ333333ӿ333333ӿٿٿٿ333333333333333333333333333333333333ӿ333333ӿɿɿɿ333333ӿ333333ӿٿffffff濚ffffff333333ӿɿɿ333333ӿ333333333333333333㿚ٿffffff࿚ٿ333333333333333333ffffff333333࿚ٿ333333ӿٿffffff濚鿚쿚ffffff333333ffffffffffff濚쿚ffffffffffff333333333333333333333333ffffff濚ffffff࿚ٿٿ࿚ٿ333333333333ffffff333333࿚ٿ333333ӿɿ333333ӿ333333ffffffffffffffffff333333333333ffffff濚ffffff333333333333333333ffffff濚쿚鿚鿚ffffff333333333333333333ffffff濚鿚쿚ffffffffffff333333333333333333ffffffffffff濚鿚鿚鿚ffffffffffff333333333333333333333333333333㿚ɿ333333ffffffffffff濚쿚333333333333ffffffffffffffffff333333333333ffffff濚쿚鿚鿚鿚鿚鿚ffffff333333333333333333333333ffffffffffff濚鿚鿚鿚ffffffffffffffffff濚鿚鿚쿚ffffff333333333333ffffff濚ffffff333333333333333333333333333333ffffffffffffffffffffffff濚쿚ffffff333333㿚ٿٿ333333ffffff濚鿚ffffff333333࿚ٿ333333ffffffffffffffffff333333333333㿚ٿ333333ӿ333333ӿ333333ӿٿٿٿٿٿٿٿ333333ffffffffffff濚ffffff333333ffffffffffffffffff濚ffffff333333333333333333ffffffffffff濚ٿffffff333333333333333333333333333333333333333333ffffff333333333333࿚ٿ333333333333333333333333333333ffffffffffffffffffffffffffffff333333333333333333333333ffffff濚쿚鿚ffffff333333333333333333ffffff333333333333333333333333333333333333333333333333࿚ٿ333333333333࿚ٿ333333ӿٿٿٿٿٿٿ333333333333333333ffffff濚𿚙ffffff333333㿚ٿffffffffffffffffff333333࿚ٿٿٿٿ333333ffffff濚鿚鿚쿚ffffff333333333333ffffffffffff쿚ffffff333333㿚ٿ333333㿚쿚ffffff࿚ٿffffffffffffffffff࿚ffffff333333࿚ٿٿ333333ffffff濚𿚙333333࿚ٿ333333ffffff쿚ffffff333333ffffff濚쿚鿚쿚ffffff333333333333ffffff濚쿚ffffff333333333333㿚ٿ333333ӿ333333ӿ333333ӿٿ333333333333333333333333333333333333333333333333333333333333333333333333ffffffffffffffffff333333333333ffffff濚鿚ffffff333333࿚ٿٿٿ333333ffffffffffff333333333333333333࿚ٿٿٿٿٿ333333333333ffffff濚鿚ffffff333333࿚ٿٿ333333ffffff쿚ffffff333333333333333333333333ffffffffffffffffffffffffffffffffffff濚쿚333333333333ffffffffffffffffff濚鿚鿚鿚鿚쿚鿚鿚鿚鿚ffffff࿚ٿ333333ffffff濚쿚鿚鿚ffffffffffff333333ffffff濚鿚鿚鿚쿚ffffff333333333333ffffff濚鿚鿚ffffffffffff333333ffffffffffffffffffffffffffffffffffffffffff333333ffffffffffff濚鿚鿚鿚鿚ffffff333333333333333333333333333333ffffff濚ffffff333333333333333333ffffff濚쿚ffffff333333ffffffffffff濚쿚333333ffffffffffff濚鿚ffffff333333࿚ٿٿffffff濚ffffff333333࿚ٿٿٿ333333㿚ffffff333333333333ffffff濚쿚ffffffffffff333333333333࿚ٿɿɿɿ333333ӿ333333ffffffffffffffffff333333㿚ٿٿٿٿ333333ffffffffffff濚ffffffffffff333333㿚ٿ333333ffffffffffff濚鿚ffffffffffff333333࿚ٿ333333ffffffffffffffffff333333333333333333333333333333333333ffffff濚ٿٿٿ333333333333ffffff濚鿚ffffff333333࿚ٿ333333ӿ333333333333333333333333333333ffffffffffff濚ffffff࿚ɿ333333ӿٿٿ333333ffffff濚쿚ffffff333333333333ffffff濚鿚쿚ffffffffffff333333ffffffffffffffffff濚ffffff࿚ٿ333333ӿ333333ӿffffff濚鿚ffffff333333࿚ٿ333333ffffffffffff333333333333ffffff濚쿚ffffff333333333333ffffff濚쿚ffffff࿚ٿٿ333333ffffffffffffffffffffffff333333ffffffffffff濚鿚ffffff333333333333ffffffffffffffffff333333ffffffffffffffffff333333333333333333333333ffffff濚쿚쿚쿚ffffffffffff333333333333ffffffffffff333333㿚ٿffffffffffffffffff濚ffffffffffffffffff333333333333333333333333333333ffffff濚ffffff࿚ٿ333333ӿ333333ӿٿ333333࿚?333333333333333333333333333333࿚ٿٿٿ333333ffffff333333࿚ٿ333333ӿɿɿ333333ӿ333333ffffff333333333333333333333333ffffff濚쿚鿚ffffff濚ffffffffffff333333333333㿚鿚ffffff333333333333ffffffffffffffffff濚쿚333333333333333333333333333333࿚ٿٿ333333ӿٿٿٿ333333ӿ333333ӿɿ333333ӿ333333ӿٿffffffffffffffffff333333࿚ٿ333333ӿٿffffff濚쿚ffffff333333333333ffffff濚鿚ffffff333333㿚쿚ffffffffffff333333333333ffffff쿚ffffff333333333333333333333333333333333333ffffffffffff濚쿚鿚鿚ffffffffffffffffff333333ffffff濚쿚ffffffffffff333333ffffffffffff濚鿚ffffffffffff333333333333ffffffffffff濚쿚ffffff333333333333ffffff𿚙ffffff333333333333ffffffffffff333333333333333333333333ffffff333333ffffff濚鿚鿚鿚ffffff333333࿚ٿ333333ffffff濚鿚ffffff333333࿚ɿ333333333333333333333333333333ffffff濚鿚ffffff濚ffffffffffff333333333333ffffffffffff濚ffffff333333࿚ٿٿٿ333333ffffff쿚ffffff333333333333333333ffffff濚鿚쿚ffffff333333333333ffffff濚쿚ffffff333333࿚ٿٿ333333ffffffffffff333333333333333333333333࿚ٿ333333333333333333333333࿚ٿٿ333333ӿ333333333333ӿٿ333333㿚쿚333333࿚ٿٿ333333ӿ333333ӿٿ333333ffffffffffffffffff333333ffffff濚鿚鿚ffffffffffffffffff濚鿚鿚ffffff333333࿚ٿٿٿٿ333333ffffff쿚ffffff333333ffffff濚鿚쿚ffffff333333333333ffffff濚쿚鿚鿚鿚쿚鿚ffffff333333࿚ٿ333333ffffff濚鿚鿚ffffff333333333333㿚鿚ffffffffffff333333333333ffffffffffff濚鿚鿚鿚鿚鿚鿚ffffffffffff333333࿚ٿ333333ffffff쿚鿚鿚ffffff濚쿚ffffffffffff333333333333ffffffffffff濚쿚ffffff333333ffffffffffff濚쿚鿚ffffff333333333333ffffffffffffffffffffffffffffffffffffffffff濚鿚ffffffffffff濚쿚ffffff࿚ٿٿٿ333333ffffff濚쿚333333333333ffffff濚쿚ffffff333333333333ffffffffffffffffff333333ffffffffffffffffffffffff333333ffffffffffff濚쿚ffffffffffff333333333333ffffff濚ffffffffffffffffffffffff濚쿚ffffff333333㿚ٿٿٿ333333333333ffffff333333333333333333333333333333333333ffffffffffffffffffffffff333333333333333333ffffff쿚鿚ffffff࿚ٿٿ333333ffffff濚鿚鿚鿚鿚鿚ffffff333333333333ffffff濚쿚ffffff333333333333333333ffffff濚鿚ffffff333333333333333333ffffff濚鿚333333333333333333333333333333ffffffffffffffffff濚鿚鿚ffffff333333333333ffffffffffff쿚鿚鿚ffffffffffff333333ffffffffffff濚ffffff333333࿚ٿ333333333333ffffff濚鿚쿚333333㿚ٿٿ333333㿚鿚쿚ffffffffffff333333ffffff濚쿚鿚ffffff濚ffffff333333333333ffffff濚ffffff333333333333ffffff濚쿚鿚鿚𿚙ffffff333333333333ffffff濚쿚鿚ffffffffffffffffffffffffffffff濚鿚鿚鿚鿚쿚ffffff333333333333ffffff濚ffffff333333ffffffffffffffffff333333ffffff濚鿚鿚鿚ffffff333333333333ffffffffffffffffff333333333333ffffffffffffffffff333333333333333333ffffff333333㿚ٿٿٿ333333㿚𿚙ffffffffffffffffffffffff濚鿚ffffffffffffffffff濚쿚鿚鿚鿚쿚鿚쿚ffffff333333࿚ٿffffff濚鿚鿚鿚ffffffffffffffffff333333333333ffffff濚鿚鿚ffffff333333ffffffffffff쿚ffffff333333ffffff濚쿚ffffff333333333333333333ffffff濚鿚鿚鿚鿚鿚鿚鿚鿚鿚鿚鿚ffffff333333ffffff濚ffffff࿚ٿٿ࿚ٿ࿚ٿٿٿ333333ffffff濚ffffff333333࿚ٿ333333333333ffffff濚鿚쿚ffffffffffffffffff濚鿚쿚鿚鿚鿚쿚333333࿚ٿ333333ffffff濚쿚ffffffffffff333333333333ffffff333333333333333333333333333333333333ffffff濚쿚쿚ffffff333333333333333333ffffff濚ffffffffffff333333333333333333ffffff濚ffffff࿚ٿ333333333333ffffff濚쿚333333333333333333333333㿚333333ffffffffffff濚쿚鿚ffffffffffff333333333333ffffff濚𿚙ffffff333333333333ffffff濚쿚鿚ffffff333333ffffffffffff濚ffffff333333ffffffffffffffffffffffff333333333333333333333333333333333333ffffff濚鿚ffffffffffffffffffffffffffffffffffff333333㿚ٿffffff333333ӿ333333ӿ333333ӿ333333333333333333333333࿚ٿ࿚ٿ333333ӿٿ࿚쿚ffffffffffff333333333333333333ffffff333333ffffff333333333333333333ffffff濚鿚ffffffffffff333333ffffffffffff333333333333333333ffffff濚ffffff333333333333ffffff濚鿚ffffff333333333333ffffff濚ffffff333333࿚ٿ333333ffffff濚ffffffffffff333333࿚ٿ333333333333࿚ٿ333333ffffffffffffffffff333333ffffff濚鿚鿚ffffffffffffffffffffffff濚鿚鿚鿚鿚ffffffffffff333333ffffffffffff濚ffffff333333㿚333333333333ffffffffffff쿚ffffff࿚ٿ333333ffffff濚鿚鿚ffffffffffffffffff濚쿚鿚쿚ffffff333333333333333333333333ffffffffffffffffff濚鿚鿚鿚鿚ffffffffffff333333333333ffffff濚鿚𿚙ffffff333333333333ffffff濚ffffff333333333333333333333333ffffffffffff333333㿚ٿٿffffffffffff濚쿚333333333333333333ffffff濚333333࿚ٿٿ333333㿚鿚ffffffffffff333333333333333333ffffff濚鿚鿚鿚鿚ffffffffffff濚鿚쿚쿚ffffff333333333333ffffff濚쿚鿚ffffff333333333333ffffff濚쿚ffffffffffff333333333333333333333333333333ffffff濚鿚ffffff333333࿚ٿٿ333333ffffff濚쿚ffffff333333333333ffffff濚쿚ffffff333333333333ffffff濚쿚鿚ffffff333333333333ffffff濚鿚鿚ffffffffffff333333333333333333ffffff濚ffffff࿚ٿٿffffffffffffffffff333333333333ffffff333333333333333333333333333333ffffff쿚ffffff333333333333ffffff濚鿚𿚙ffffff333333ffffff濚鿚쿚ffffff333333333333ffffff濚ffffff333333333333ffffff濚ffffff333333333333333333333333ffffff濚鿚鿚鿚鿚ffffffffffff333333333333333333ffffffffffff333333333333ffffff濚鿚ffffffffffff333333ffffffffffffffffff濚ffffffffffff333333333333㿚ffffff333333333333ffffff濚鿚ffffffffffff333333333333ffffff濚ffffff333333࿚ٿٿٿ333333ffffff濚쿚ffffffffffffffffffffffffffffffffffffffffff333333333333333333࿚ٿٿٿ333333ffffff濚鿚鿚鿚鿚鿚鿚ffffff333333333333ffffff濚ffffff333333333333333333333333ffffff濚鿚鿚ffffffffffff333333333333333333ffffff濚쿚ffffffffffffffffffffffff濚ffffffffffff濚鿚ffffffffffff333333ffffff濚쿚ffffff333333333333ffffff濚鿚쿚鿚ffffff333333333333ffffff濚鿚鿚ffffff333333ffffff濚鿚鿚ffffff333333333333ffffffffffffffffffffffff濚鿚鿚鿚ffffffffffff333333333333ffffff濚쿚333333333333333333㿚쿚ffffffffffffffffffffffff333333333333࿚ٿٿ333333ffffff濚鿚ffffffffffffffffff濚鿚鿚鿚鿚鿚ffffff333333333333ffffffffffff濚鿚鿚鿚쿚鿚鿚鿚鿚鿚ffffff333333333333ffffff濚쿚쿚ffffff333333ffffff濚鿚쿚鿚ffffff333333ffffff濚鿚쿚ffffffffffff333333333333333333333333333333333333㿚鿚ffffffffffff333333333333ffffff濚쿚ffffff333333ffffffffffff濚쿚鿚鿚鿚쿚鿚鿚ffffff333333333333333333ffffff濚鿚鿚鿚鿚鿚鿚ffffff333333333333333333ffffffffffff濚鿚쿚鿚鿚鿚ffffff333333333333333333ffffff濚鿚鿚쿚鿚쿚ffffff333333333333ffffff濚鿚ffffff333333333333ffffff濚ffffffffffffffffffffffff濚쿚ffffff333333333333333333333333333333333333333333333333333333ffffff濚鿚쿚ffffff333333333333ffffffffffffffffffffffff333333࿚ٿٿ333333㿚ffffffffffffffffff333333ffffff쿚333333㿚ٿ333333ӿٿٿ333333㿚鿚ffffffffffff333333ffffffffffff濚ffffffffffff࿚ٿٿ333333ffffffffffffffffffffffff333333333333333333333333333333333333333333࿚ٿٿ333333ffffff濚쿚鿚ffffff333333333333333333333333ffffff濚鿚ffffffffffffffffffffffff333333333333ffffffffffff࿚ٿffffff濚쿚ffffffffffff333333333333333333333333ffffff濚鿚鿚鿚ffffffffffffffffff濚쿚ffffff333333333333333333ffffff濚鿚ffffffffffff濚쿚鿚ffffff333333333333333333ffffff濚鿚ffffff濚ffffff333333333333ffffffffffff濚ffffff333333࿚ٿ333333ӿٿٿ333333ffffff濚鿚鿚쿚쿚ffffff333333ffffff濚쿚鿚ffffffffffff333333333333ffffffffffffffffff333333ӿ333333333333333333333333ffffffffffff333333333333ӿffffffffffffffffff333333333333ffffff濚鿚鿚鿚鿚쿚鿚鿚鿚쿚鿚鿚ffffff濚鿚ffffffffffffffffffffffff濚쿚鿚쿚鿚ffffff333333333333㿚𿚙ffffff࿚ٿ333333333333ffffff濚鿚鿚鿚ffffffffffff濚ٿffffff濚鿚ffffff333333㿚ٿٿ࿚鿚333333333333333333ffffffffffff濚鿚ffffff333333333333333333333333333333ffffff濚ffffff333333࿚ٿٿ333333㿚鿚鿚鿚ffffff333333࿚ٿٿٿ333333ffffff쿚ffffff333333㿚ٿ333333ffffff濚鿚쿚ffffff333333333333ffffff濚쿚ffffff333333333333ffffff濚鿚鿚鿚鿚鿚ffffffffffff333333333333333333333333333333333333ffffffffffffffffff333333333333ӿ333333ffffff濚ffffff333333333333ffffff濚鿚鿚鿚ffffff濚鿚鿚𿚙ffffff333333333333333333ffffff濚鿚쿚鿚鿚쿚鿚鿚ffffffffffff333333࿚ٿ333333ffffff쿚鿚ffffff࿚ٿ333333ffffff333333333333࿚ٿٿffffffffffffffffff333333333333ffffff濚鿚鿚333333333333ffffffffffffffffffffffff333333࿚ٿ333333ӿ333333ӿ333333ffffff쿚ffffff333333333333ffffff濚鿚ffffff333333࿚ٿٿٿٿ333333࿚ٿٿٿ333333㿚𿚙鿚ffffff333333ffffffffffff濚쿚ffffffffffff333333ffffffffffff333333ffffffffffff濚鿚ffffff333333333333࿚ٿٿ333333333333㿚鿚ffffffffffff333333ffffffffffffffffffffffffffffffffffffffffffffffffffffff333333333333333333ffffff濚ffffff333333333333333333ffffff濚ffffff333333333333࿚ٿٿffffff濚쿚ffffff333333333333333333333333ffffffffffff濚쿚ffffff333333333333333333ffffffffffffffffffffffffffffff333333333333ffffffffffff濚鿚ffffffffffff333333333333ffffffffffffffffffffffff࿚ٿٿٿffffff濚쿚ffffff333333333333ffffff濚鿚쿚ffffff333333ffffff濚쿚333333333333ffffffffffff333333333333333333ffffff濚鿚쿚鿚鿚鿚ffffffffffffffffffffffffffffff濚333333333333333333ffffff濚ffffffffffff333333333333ffffff333333ffffff333333333333333333ffffffffffffffffff濚쿚ffffff333333㿚ٿٿ333333ffffff쿚ffffff333333ӿffffff濚鿚鿚鿚ffffff濚ffffffffffffffffffffffffffffffffffff濚쿚333333333333333333ffffff濚ffffffffffffffffffffffff濚쿚鿚鿚鿚鿚鿚ffffffffffff333333ffffffffffffffffff濚鿚쿚ffffff333333333333333333ffffff濚鿚鿚ffffff333333࿚ٿffffff濚쿚鿚鿚鿚ffffffffffffffffffffffffffffff濚ffffff࿚ٿٿٿffffff濚鿚333333࿚ٿٿ333333ffffffffffffffffff࿚ٿٿٿ333333ffffff濚쿚ffffff333333333333333333333333࿚ٿ333333333333ffffff濚ٿffffffffffffffffff333333333333333333333333333333333333333333333333333333ffffff濚鿚ffffffffffffffffffffffffffffff333333㿚ٿٿٿ333333333333ffffff333333333333ffffffffffff濚鿚ffffff333333333333ffffff濚쿚鿚ffffffffffffffffff333333333333333333ffffffffffffffffff333333333333ffffff쿚ffffffffffff濚쿚ffffff333333333333࿚ٿٿ333333ffffff濚ffffff333333࿚ٿ333333ffffffffffffffffff࿚ٿ333333㿚쿚鿚鿚鿚鿚ffffffffffffffffff濚鿚𿚙333333333333㿚ffffffffffff333333333333ffffff濚쿚333333333333333333ffffff濚鿚쿚ffffffffffff333333333333࿚ٿٿffffff濚쿚ffffff333333ffffff濚𿚙ffffff333333333333333333333333333333333333333333333333333333333333࿚333333ӿ࿚ٿ333333ӿ333333ӿٿ333333㿚쿚鿚鿚鿚쿚333333333333ffffff濚쿚ffffff333333333333ffffff濚쿚ffffffffffff濚鿚쿚ffffff333333ffffff濚鿚ffffff333333333333ffffffffffff333333333333333333333333ffffff濚鿚333333࿚ٿ333333ӿٿٿٿ333333333333ffffff쿚ffffff࿚ٿٿ333333333333ffffffffffffffffff濚ffffff333333࿚ٿٿ333333㿚ffffff333333࿚ٿٿ333333ffffffffffff濚ɿ333333㿚鿚ffffff333333333333ffffff濚쿚鿚ffffff333333࿚ٿ333333ffffffffffffffffff333333333333333333333333ffffff濚ffffff333333࿚ٿ333333ffffff濚ffffffffffff333333࿚ٿ333333ffffffffffff濚鿚鿚鿚鿚ffffff333333333333ffffffffffff333333333333333333ffffffffffffffffff333333333333ffffffffffff濚쿚鿚鿚ffffffffffffffffffffffff333333333333࿚ffffffffffffffffff333333333333ffffffffffffffffff333333333333333333ffffff濚鿚鿚ffffffffffff333333333333ffffffffffffffffffffffff333333333333࿚ٿ333333ffffff濚鿚ffffffffffff333333333333333333ffffff濚𿚙ffffffffffff333333333333333333333333333333333333333333333333࿚ٿٿٿٿ333333333333333333333333333333333333333333333333333333333333333333333333333333ffffff濚鿚鿚ffffffffffff333333333333333333ffffff濚ffffffffffff333333333333333333333333333333ffffffffffffffffff333333333333ffffff濚쿚鿚333333࿚ٿٿ333333ffffff濚쿚ffffff333333333333333333333333㿚鿚ffffffffffff333333333333ffffffffffff쿚鿚ffffff333333333333333333333333333333333333333333ffffff濚鿚鿚ffffff࿚ٿ333333㿚鿚ffffffffffff濚쿚ffffff333333333333333333ffffffffffff333333333333ffffff濚쿚333333333333333333333333333333333333ffffff濚鿚鿚鿚鿚鿚鿚ffffffffffff333333333333ffffffffffff濚쿚鿚ffffffffffffffffffffffff濚쿚333333333333333333ffffff濚쿚ffffffffffffffffffffffffffffff333333࿚ٿٿٿ333333ffffff濚鿚ffffffffffff濚鿚쿚ffffff333333ffffff濚𿚙333333࿚ٿ333333ffffff濚鿚鿚ffffffffffff333333333333ffffff濚쿚鿚ffffff333333333333333333ffffffffffff濚鿚鿚ffffff333333333333333333㿚鿚鿚鿚鿚쿚ffffff333333ffffff濚ffffff333333333333ffffffffffffffffffffffff333333333333333333ffffffffffff濚ffffff333333࿚ٿٿٿ333333㿚ffffff333333333333ffffff333333333333333333ffffff濚쿚鿚ffffffffffff333333333333࿚ٿٿ333333ffffffffffffffffff333333࿚ٿٿffffff濚쿚ffffff333333333333333333ffffff濚鿚쿚ffffff333333333333333333333333ffffff濚ffffffffffff333333࿚ٿٿ333333ffffff濚鿚쿚ffffff333333333333333333ffffffffffffffffff濚ffffffffffffffffff333333ffffff濚鿚鿚鿚ffffff333333333333ffffffffffff333333࿚ٿ333333ӿٿffffff濚鿚鿚ffffffffffff濚鿚쿚鿚鿚鿚ffffff333333ffffff濚쿚鿚ffffffffffffffffffffffffffffff濚쿚ffffffffffff333333333333ffffff333333333333333333ffffff濚鿚ffffff333333333333ffffff濚鿚鿚ffffff࿚ٿ333333ӿ333333ӿɿ333333ӿٿٿٿ333333333333333333333333333333333333333333333333333333ffffffffffffffffff333333333333ffffffffffff濚ffffffffffff333333333333333333ffffff333333࿚ٿ333333333333333333333333333333333333ffffff濚鿚鿚鿚ffffffffffff333333࿚ٿɿɿ333333ӿٿ333333ӿ࿚ٿ333333ӿɿɿ333333ӿٿ࿚ٿ333333ӿ333333ӿٿٿٿ333333ӿ333333ӿ333333ӿ333333ӿٿٿٿٿٿٿٿ࿚ٿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿ333333ӿɿٿ࿚ٿɿ333333ӿ333333ӿٿ࿚ٿ333333ӿ333333ӿ333333333333㿚ٿٿ333333ӿٿ333333ӿɿɿɿ333333ӿٿ333333333333࿚ٿ333333ӿ333333ӿSigima-1.1.1/sigima/data/tests/curve_formats/step.npy000066400000000000000000007642001514013333200226350ustar00rootroot00000000000000NUMPYv{'descr': 'z>mM>¢>!Fԫ>2䀹>9Ս@ >3&>M:B>x]>< 4y>A8锬>H->Nˬ>'笔>>WL!>Ow9>V U>i7p>>ɧ>rí>^Ѷޭ>e&K> v> 1>86L>čg>^@>sA>>#Iծ>*J3>Ҩ >z5(>\C>]'_>1z>n>Hֱ>ͯ>w诔>83>@+>G\;>އV>=xr>G>>NFİ>2lఔ>ư>O[>2>U _N>\aFi>d脱> >s1S>ŗױ>Z>k|>۰F*>0EE>Îp@a>|>rB0:>y~>"3ϲ>)Kx겔>ѩ->Cr!>]o'=>lX>0/!t>7fe>>_Ƴ>xⳔ>BY>?,n>FS4>-P>4Lk>>F>=>TA@ٴ>l>P:> ~+>3G>[bb>c-~>j r>k@'>kе>!쵔>se>qҿ#>1>> Z>(Yu>9?>xjì>ȶ>BL㶔>/>>T~5>@Q>>l>6gi>=>E3>oڷ>>#}>x'->L5hd>>'>>϶>SҸ>Z{>Q~ > ;$>gx@>Y[>b&rw>i >lk>zɹ>e幔>t:>pe_>w(7>%YS>'ܹn>.1N≺>֏y>~L>C9ܺ>>5>U$@/>媸J>Le>^x~><3>D8x>Kg̼ӻ>qﻔ>$#' >yk&>KA>R-we]>y>6_> 6ˣ>X˼>Y!缔>`HR>hJ>uL9>ZU>5Fp>ʊ>oc?> ½>9޽>&lI~>t3>v)0>}~4-L>&_g>-2&>Րܞ> >Dվ>s>4 >;M3(>^C> _>_z>>C޼>JhrͿ>Ɲ返>2>z]>:>Q.V>Xq>ܣ>7q>->0>_I\>g>n 2>RM>ۊi>pτ>Z>u/ɻ>[~>%m>,ƒ”> )”>|qE”>n`”>){”>3.”>Ye”>;”>ꐂ”>ﭣÔ>:NX!Ô>Am<Ô>IWÔ>V-sÔ>XLÔ> 퐪Ô>_Ô>PÔ>?Ô>qlĔ>3Ĕ>%,~OĔ>WW3kĔ>^wĔ>8-Ĕ>qĔ>&Ĕ>@kkĔ>f Ŕ>m*e+Ŕ>SVGŔ>^bŔ>~Ŕ>[XŔ>t Ŕ>{jRŔ>$nŔ>+)LƔ>!U#Ɣ>vE>Ɣ>YƔ>*?uƔ>2Ɣ>9h9Ɣ><Ɣ>(3Ɣ>wƔ>E,ǔ>@5ǔ>H&Qǔ>ONg ǔ> գǔ>`'ǔ>^ǔ>Vǔ>rȔ>Ȧ -Ȕ> ;RHȔ>{fdȔ>]ڑȔ>d/&Ȕ>lEȔ>Ȕ>AȔ>Öɔ>99$ɔ>sJe?ɔ>[ɔ>"$vɔ>*S,ɔ>ұɔ>zɔ>eɔ>8 ʔ>1dʔ>w7ʔ>#Rʔ>+Onʔ>ȉʔ>8~ʔ>?4ʔ>wʔ>bʔ>Fq˔>".˔>GMkJ˔>NOe˔> e˔>˔>a^˔>a˔>UX˔>\j! ̔>LR&̔> A̔>| L]̔>Ѡx̔>c0E̔>k`̔>r̔>9 ̔>—K9͔>}͔>At8͔>ywT͔>!,p͔>)T_q͔>0͔>k͔>fJ ͔>d͔>sΔ>7o^0Δ>LΔ>"^XgΔ>wΔ>RΔ>>5IΔ>EKΔ>MqΔ>=E ϔ>'ϔ>\?Cϔ>F^ϔ>T9zϔ>Hϔ>Y2ϔ> pwϔ> ,ϔ>[kД>b[&Д>jj:Д>t VД>FqД>'Д>jϨД>qۚД>:Д> Z Д>є>B2є>xEMє>iє>(Uє>/є>ůє>]Yє>є> Ҕ>6pD)Ҕ>=DҔ>#`Ҕ>x{Ҕ>ÖҔ>,X۲Ҕ>DҔ>LҔ>S5Ӕ> Ӕ><Ӕ>GWӔ>+ sӔ>ZVŽӔ>ZwӔ> Ӕ>Ӕ>bֵӔ>akԔ>i3Ԕ>pk*NԔ>UjԔ>(^Ԕ>}Ԕ>ҩԔ>w1՜Ԕ>RԔ>&唖Ք>.:)*Ք>֘TFՔ>~EbՔ>L}Ք>ΘՔ>5ԃՔ>^8Ք>䳓}Ք>(֔>gSw"֔><~,>֔>CqY֔>Kpt֔>j֔>-֔>d֔>K֔>R6R^֔>}ה>X5ה>H= Qה>Qlה>Yה>`QKה> ה>QEה>c|ה>?ؔ>h<,ؔ>ol8Hؔ>cؔ> 2ؔ>~ؔ>O,ؔ>(pؔ>}&ؔ>%:ٔ>-;$ٔ>4cd?ٔ>[ٔ>Mvٔ>Nٔ>Wٔ>;V ٔ>9ٔ> ڔ>^bKڔ>7ڔ>BRڔ>JqMmڔ>Q>ڔ>$ ڔ>8ڔ>ڔ>-a2ڔ>X۔>뷜.۔>@LI۔>%e۔> ۀ۔>_R7۔>fԷ۔>n_۔>[۔> ܔ>K%ܔ>c Aܔ>u \ܔ>!6wxܔ>$vʻܔ>pܔ>)ܔ>|jܔ>Iݔ>,3 8ݔ>4^Tݔ>Dɢoݔ>Wݔ>ݔ>:WQݔ>AHݔ> tKݔ>_ޔ>3E0ޔ>ȉKޔ>Ir>gޔ>PLJޔ>%8ޔ>zG}ޔ>r2ޔ>.wޔ> ߔ>^p'ߔ>A%Cߔ>j^ߔ>yߔ>IFdߔ>eqߔ>m^ߔ>tRߔ>W> >dQ:>ӹU>{EKq>#wp>+E>2!>>>>38>}1>9C2M>Eoh>,>p>N%>@>G>OWd >B)>nD>i`>W{>V >{>с>/>A>]l >d8;> ,W>r>J쨎>ß>l>sS@>k>">e+3>ҺN>zj>nԅ>)ͪ>1"?μ>8w>>4*}>*>RF>?=~a>盩p}>=>E>>F)d>NX>UQ!> }=>jWY>>\s>'K> '>|P>{>c9>5>j;P>rk>B|> &2>v>JO>yzp>!%>(]:j,>0ήG>cc>o%>Ĺ]>0#>7xyW>֤ >+9Q>d$>J?>>>$[>EDv>>Fx>>>78>MYc>T1> #6>b+R>m>w%>[tڤ>b6> (b>}>Ҋ]>0.>iI>qu e>x9 Q> 5>`>K>נD> >'^%>/t@>6 8\>f4w>_>>o+>=γ>,ߕ>s>8>53S>D^o>K͊>S>>>|>Pr>>Z2/>c]pK> f> >k>ac>hq>~]>0 >1\W'>džB>pQ^>w:y>J>&o>LD>֡/>~[>>U>.8:>5 |U>g1q>nv>+>p.p>C$i>>׭c1>,BL>m]h>J>R?-W>Y>P>Q>J >@(>`ZlDD>_>,>{>c>7>g >nu1>v?v>)k+ >Ƈ;>*%W>1ir>}>%ԩ>,D>4>]>i>V>) 3>PN>;_j>>>g=D>h>B%>Iz(>S*>-E>a>|>Q@ӛ>Xg>>I'>R>!>_[=>fX>҂t>dfǏ>‘|>&>mvQv>u>| z>$4>iP>2ek>ۇ>$>+EP]>3>:x>M>P,>dG>Vb>A#~>OD>h㈵>w>>H{7>Ob|#>W%>>"vZ>M+v>7o>v>^i>J> ac>>R!]6>eLR>lVm>t[u>P>>m`J>t̋>{! D>#K->*=I>3 d>ڈ7>><_1>2>9+>NJ >$%> @>W\>@w>G ^>iͮ>>I>r >N>V&8>]{1JS>\n>8>>=>dA> >>J01/>è[J>kf>s\>z$>"ٸ>n>Ú>/ >wZ&>)օB>0+]>8 y>>=v>>->?FY>礄i>9>NT>اp>F ]>Ma>U,>X>sP>>U'CJ1>\|׎L>Dh> 0>=>V>cB7>j|>A1 >Ku(>©+D>o_>r]${>yUi>!>(fc>@>\>x >͔V;>/, W>7TPr>>蔍>4J>?>C>=h>E=>2>OS7N>{i>1>Lb>>T*>[ go>k$>ɽ>R*>sbE>ba> 1=|>>eV>9 >i>pP>xBI!> <>;X>Ts>שd=>>'g>.O>{>o>:4>#O>6k>=׎ن>5>Nӽ>y>>>D9>K+>P{G>b>u~>YM>Sxo>Z >l8i> ̭ >b# >t> > Y >h(Lu >wV > >1 >Ǐ˔ >oI >wC >~5 >&JQ >Uv=m >֪ >ƣ >^{ >-0 >5u >Io- >$u$I >y id >Ν >C-b > >\ >5 >HV >Js % >QHP@ >Y[ >Iw >Z >C > >`cG= >r >7 >u27 >0S >g)n >n~* >ݱߥ >2F$ >Ɛq > >vD1>}/>%J>,Mf>իƁ>E >_p>>40>;h >BXC&>A>z]>Cx>$6>I>.>6>W*>>PI9>XBT>_p>RӋ>->>ZV>f>{>mA0>L> g>m,o>t>|)U>$>b>;@ >ې'>C>+N+V_>2z>:Sߕ>V>I> ?>:ijC>A>*=;>qV>6r>%~{>H0>O=u>7i*>n>($>@h2>WN>^|bi>S> <\>h>[U>e' >lO>n*>{IE>#`>v;C|>sf>{*<>>*޺6><>ڑz0!>u<>E:*X>1es>9#>@Nh>謹> >`y> \>G94>rdO> k>O>{>N㹽>U/x>] C>7>Ac+>F>6b>dJ}> ⠙>v>S *>ñ6>kb>re">!>>"Y>wu>u̐>z+>5>)`{>04>ْ u>紹5>FnQ>tl>8h>?O4>_b>>a\>>FU->MjsH>ȞOd>3>sؚ>>T0C>\>cF> 9r$>6@>1{[>Aƿv>jt>*>Tn>!E>qh>qf>y0b7>ŦR>(o[n>>"U>wD>oO>/5>6/I>>Í.>=BJ>e><>FC>En6>>X.0>t > )&>LkA>S#]>x>tm>Ҙү>'->[X>b > : > 9 >׿T >Blp >i >p+ >UW > > >]!>w֦0!>kK!>f/g!>.*!>#V!>x޹!>~#!>,!>5Ս ">=i'">D5C">)^">Tz">Gŕ">} ">K">Yt">h#>#>b(:#>RShV#>Yq#>ak|#> ʧ#>([#>}g#>#>h1'$>RO2$>M$>:{h$>ǘ$>oB$>vLf$>~$>&&$>^Q6%>ճz)%>~0E%>gt`%>-)|%>4en%>y#%>$h%>-P%>a&><!&>C6[<&>X&>cUs&>H &>#O&>JN&>QQH&>&>B'>c3'>bXj'>`l"6'>gz'> /'>~ '>ӡ)'>(6n(>na#+(>F(>;!b(>%a}(>(>uM ̴(>}(>4U(>,V` )>Դ")> >)>^HY)>t)>3 )>:q)>B3<)>$_)>)>*>-/5*>IP*> l*>?އ*>2#*>]ؾ*>PR*>W*>_+>[,+>H+>c+>_mz+>f\+>!t+>v+>Gn+>)ܲ,>mh$,>tݛ?,>$[v,>[,>D,>|FU,>ڙ,>+WO->2-> H7->_ZR->Bn->->9rE<->Aـ->Hn->zz->/.>.Yt..>I.>One.>@D#.>g.>l.>Ia.>V.>^W[ />eR%/> UA/>C ]/>dNx/>Ĺk/>lH/>w/>VB/>#!0><0>sA80>z35T0>jzo0>*/0>E0>ٚU)0>m0>N#0>1@1>801>`K1>赔g1>˂1>iT1>@Ź1>G 1>{?1> 2>/'2>B2>N㾲^2>U8Sy2>~2>2>J>2>2>]3>dS3> :3>RU3>e}q3>ú،3>3>rn3>3>""3>)w%4>P14>y4|zM4>h4>ޤ4>0=и4>؛m4>4>E$4>O 5>7{a)5>?XD5>F_5> ϟ{5>jT5>5>#5>MsN5>yH6>& 6>|;6>͆W6>T9;s6>[6>c!ũ6> BMz6>x/6> t6>J7>jm37>"O7>]gj7>»7>La7>qow7>x [7>!#77>(xT8> +8>+NF8>b8>JH}8>/>v8>6 B8>58>F;8>9>5"9>>Y=9>EI/Y9>Lst9>a )9>4ޫ9>"9>j]g9>SɈ9>':>}H5:> ZP:>0l:>Z3Ň:>b :>i9\N:>:>:>KG;>ȠA,;>pG;>^2c;> ~;>'[5;>f;>wű;>~F;>o(<>.#<>,1?<>݁Z<>Yv<>5ё<>5<>D><><>/z=>Pľ6=>XR=>Km=>bm=>C=>og=>k=>R.a=>Yå>>~Z.>> ӂI>>1Te>>B>>amN>>h:>>-H>>>>LA ?>ǡ%?>o;A?>vUA\?>l5x?>& z?>g,/?>ռs?>}(?>pm@>@>4$@g8@>܂kT@>`o@>,@>Z@>;@>C?T@>J@>>NA>Qj0A>GKA>fA>QZAA>A>~;A>cA>=5A>X i B>_u.'B>gʑsBB>)(^B>yB>|"B>1gB>n<B>gB>DC>%ZC>:C>uVUC>|{ qC>% C>,_;C>ԽfC>C>q&C>ƺD>3%1D>:zzLD>إhD>-:D>eD>D>B@%D>ID> E>Hy(E>DE>8_E>P[d{E>WʖE>$E>dE>L E>xF>^vs F>f7;F>m VF>rF>"gF>2F>̇KF>tvF>EZF>$6G>+2G>MNG>{!NjG>G>VJנG>2uG>AG>h5G>H>*H>9{ 5FH>@дyaH>H%I|H>tsH>(H>74mH>ȱH>OfI>I"I>`=I>GXI>RsZtI>VI>]3TI>e^ I> MI>I>mGJ>e4J>l!rAPJ>kJ>1;J>3]J>ˈ4J>sJ>z<.J>#K>*p(,K>NGK>٣0"cK>\~K>WK>`K>8 K>iK>oL>T#L>r/ ?L>?ZZL>G&vL>N{GL>ٮL>8ڱL>nL>;L>UA.M>Y6M>QM> J.mM>M>\٘M>c\mݿM>k"M>-M>nXN>-N>IN>rwdN>N>!+lěN>) N>+N>y=WsN> O>$O>0F@O>ؤf\O>jwO>X`O>*O>7 VZO>>aO>TP>P>sM8P>iSP>F'GoP>M|)P>TAP>/P>;P>P>TB4Q>[hy/Q>.KQ> K(sfQ>Q>lQ>b]"Q>jfQ>qfg` R>Ē'R>'ZBR>n]R>xSyR> , R>(MR>/:R>4fGR>S>%AS>=9S>6:US>pS>O4S>9yS>e.S>=bS>D$(S>L lT>j!1T>LT>hT>s8`T>ScT>0ʺT>#T> ۷ST>9 U>Z(U>aDU>iB7G_U>bzU>U>T"U>iMU>pU>g V>V>͞;V>oaVV>wΌrV>~#!ݍV>'LV>.V>5 V>݊V>˅W>>`2W>5NW><iW>PKyW>߽W> sW>YW>ClW>K _X>Rb)X>EX>J`aX>tޤ|X>rX>Y(X>SX> ]X>1Y>!Y>`HG=Y>hC݋XY>oqsY>Y>U:Y>ƪ\Y>Y>v^yY>G.Z>%r4Z>-gpOZ>ślkZ>}$!Z>y[fZ>諾Z>4-`Z>܋FZ>Y[>5o+[>SG[>;c[>BHZM~[>J[>G[>ZE[>@[>J\>Qc:#\>>\>Y4Z\>uu\>.\>X)D\>_~'\>\>2!\>]>W6]>gDQ]>nm]>Bʈ]>M]>ūĿ]>]>U+M]>|V^>$-^>,hH^>3@d^>^>z^>ϕ^>$*4^>:U^>သ _>6$_>'@_>[_>AIw_>I֒_>P(_>QT_>_>`>Z`>W7`>xS`>mn`>'`> S`>^~l`>e`>m)`>Ҫa>_/a>;Ja>̐&ea>tQa>N}Sa>#a>=Ma>Vёa>{F b> &b>+i@Bb>2P]b>|:yb>qb>;4b>%xb>9-b>@ُrc>7'c>Ol9c>z!Uc>@fpc>H:c>O_c>VIcc>Yc>c>[NSd>0d>]MLd>n9hd> Fd>bd>v@d>dոd>l*M:d>s~ e> 4(e><8Ce>ˑ-_e>`rze>zE'e>"ܱe>*K!e>1Nee>٬ f> 7f>`;f>_YVf>8rf>rÍf>Jf>Lf>{ f>?5f>F/g>N^@2g>Mg>Aig>Ig>3g>UJ g>4g>g>\h>)h>\Eh>ceH`h> s|h>Зh>w3h>h>k+~h>ri>߲x!i>!4GʒrrXi>si>yF2li>ưi>)ei>0Oi>ح_i>Fj>aqY4j>Oj> jj>>jŗj>Lj>j>rj>Dj>E0p@k>M+k>TژFk>8~bk>3~k>xk>Ak>[Crk>n'k> Tll>"l>e>l>bfZl>i_ul>ql>oBYl>ml>"Sl>wl>xLm> 56m>'FQm>/lm>=A@m>lm>:m>/P,m>63m>n>X--n>Hn> @'dn>=kkn>D n>+ֶn>sn>n>' o>L$o>S>@o>9j[o>wo>)o>Bo>Zo>a}o> Up>=p>97p>]Rp>h(np>pp>wfQ-p>|p>#p>x

q>~,.q>&'Jq>.eq>55Pq>ݓ{ɜq>~q>G;q>q>< r>Y&r&r>뮺Ar>O\r>bzxr>Cer>J:r>Rkr>r>(%Ys>}s>M8s>Y1yTs>Lps>8s>:զs>s>`#@s>gLs>9t>x~0t>^3Lt>Ƴ7xgt>oc-t>vgqt>"'t>%kt>y t>ve u>}-(u>6_Cu>-a_u>46Xzu>ܔ!u>Ru>Hu>uLu> v>BQ5Fv>`:v>?Vv>Yqv>9v>Iv>Qlt3v>Xxv> 4-v>~_w>&2w>(kMw>_ iw>Մw>;sw>_w>2w>fM^w>m x>uR)x>VEx>Ŵݼ`x> r|x>^Fx>|1x>$]x>+qx>3ƅ9y>$ y>ܣpWy>--sy>:0y>[y>?y> y>y>ARۊz>Ho3z>Oz>Z/jz>Z~z>¡z>Pmxz>W®z> qz>vn{>ԙk+{>).F{>^Yeb{>e}{><_{>{>A{>Dm{>lR|>t,"|>{M=|>#Y|> Fu|>_|>ڴ@ϫ|>l|>*r9|>2+~|>9}>zw5}>-Q}>.ql}>?}>@jk}>@ }>*e}>꾩}>I^~>G-~>NXH~>VR>c~>iR~>~>d)L~>~>]E~>w> ̨?$>!=?>h9[>dޓv>k3(3>sw>,>E>ʚ&>s>zNg 7>"R>)'n>`Rω>ٵ>>i ܀>1>8f>{.>%J>/Qe>>?>F8>ЩӁ>d>J >$%>MOA>US\>\x&x>ۓ>eϐ>cʂ>悕>cn#> N>"8>ww T>բo>j4w>rb>yƒ>!="݃>ɛMk>>Ev/>K>(^g>/Xa>7睄> !>jLRՄ>>u >>s'>EC>&`^>{y>>E9K9>L}̅>Ts煕>Aw>,>^q:>TT&V>[kq>J > ]d> Ć>^߆>bo>i]X># 2>xRM>Hi>+K>q>xߜE> >և>'\?> >F9)>ޛ}D>2`>.Y{>6,>=0q>a[&Έ>鈕> >jd >D<>'W>|s>.X>0Z >Kʼn>Sቕ>Z9K>>3>KN>-?j>aX􅊕> ^>>2؊>f>h>o*>wo,&F>Wa>,}>΁՘>֫>~5ϋ>&닕>->G}">ݜV=>wY>Pt>5Aq><ֵ>bknj>뷕⌕>d>kU>Cʀ^5>JP>}@Xl>Ԝ>1R>>RKڍ>Y:T>`>,>L??H>Ӄc>g~>gU}>2> Swю>^쎕>Ƽq>n>&$>vpj?>}fZ>%$dv>͂>Q^>,ȏ>X䏕>,< >4?Q>;e6>KR>Qn>PE>䉤>BZ?>;ې> 8>bd}>2.>I I>PuO,e>Xp>)&>:۷>ӑ>1cd>_ >%>DNA>y\> x>fV9“>m> ʒ>_撕>Ž>M>uqx8>| S>$%8o>+z튓>>->ݓ>K>3@w>: />6K>Hf>>Ν>Q>HJԔ>v}>c >'>ʻB>Ovp^>Wˉy>^ >I>td̕>2 畕>>eȢ> EW:>U>p>MH>lsK>sÖ>{Vޖ>#lj>>>h1>ڽL>G}h>*{r2>1w>9%>p֗>%>7j >(>@EdD>Iq`>^{>0>RW>G Θ>NQ阕>d>DK >p<>mEW>V/r>]!>>󩙕> Ճ8ř>3>C2>dn>k<,3>.N>%j>"EWj>ʣ>rԼ>zWBؚ>]>) >i-*>پ F>VQa>r}>0Ѭ>8&A>?{Dϛ>ꛕ>8,>!>T8=>FAX>t>?珜>I+>Ɯ>M+✕>T\>\S>4>nP>>k>>cwǢ> )}>+ٝ>R>}>j=p,>q=G>hjc>!F~>ɤ(d>>yX]ў>|잕>( W>/a<#>ؿgQ?>Z>s'Kv>Ȼ>7'D>>|{ȟ>ڦ>䟕>/;>f8>|6>8Q>Lvm>+>Jzp>>9j۠>S]e>[c>b-> f]I>e>yW>n >i8Q>,dӡ>J> ֌ >4D%>p@>xw>\>= w>'78>b>O1ʢ>ޤv墕>+>.b>5v%8>= jS>j6o>aԊ>>s]>Dҵݣ>0>u > Q/>95K>K`f>R>K >>߮Ԥ>Tt洛>Z >a4&> g_B>]>y>o>hޕ>o#s˥>祕>2>&,>Ί9>vU>~>p>F >-q>Pvæ>ݥ1ަ>>Y>4j1>< L>CbEg>p>]>t0>է>J(>Q >ۯ(>1DC>o_>QD{>XC/>`ͱ>ͨ>U8騕>|>B>g^nv;>+W>.pr>g´>i>n$ũ>uyc੕>}A>%-m]>͋3>,WN>}?X j>P>,>3HJ>ܦת>kD>Z>+>*>;WE>Bc7a>|>1>u泫>j+ϫ>I)꫕>P~*%>U!>2=>X>t>WD͏>_i>fVƬ>M) ⬕>T>>U}J4>mO>Դk>hh>$=>(󽭕>tzS٭>|>$|1>++>қG>6gb>$~>&ڙ>2IR>9Ю>Az쮕>Q>т#>f>>Z Z>H%u>Qv>l庬>yǯ> 㯕>Oi>Vd>^)5>$Q>O]m>;䡈>^W>e> NP۰>c>J>V#->lNDI>s d>i>>#>7>qb|ұ>{Ѝ1>%"v >*M+%>1o@>7 %\>ጡiw>5>@ac>8ʲ>@ ]岕>GI>V> 8>[PS>4n>N`J>m>D>ܳ>v=>U >]*7/>d3|J> ^1f><恴>+>o>kE$Դ> ﴕ> >"N2c&>ʬ]B>r ]>y`y>V>) >r˵>ǜ絕>1J>{\>0ڇ9>7/T>Gp>򋶕>A>¶>?ơ޶>FJ[>>0>\FL>g>M>TeӞ>ň>Zշ>w> >\+E|(>cC>jm_>4z>o>X>≮>q踕>Cc>!Oا>(l:>V>xaVr>W> ߨ>/jĹ>BJ๕>׎>rk>і2>60=N>>Vi>EƄ>8|>A1>u׺>Aj>Lo>$*>SUiE>`>c|>Sf@>Z\>biλ> oV껕>Ϳ >"TP!>w<>iJX>5?s>C>>==Ƽ>pἕ>wR7> P~>'14>>O>X*k>߆> $>.kٽ>5Qٽ>}>s>ȥ\+>'G>=b>Dې ~>9>P>{о>B뾕>C>R">T>>Y> #7u>]O쐿>Yz>aǿ>hf*㿕>>#>x5>"Q>o,Nl>y> ͣ>&5>Γ>v{>}G>!->-LH>Yxod>ܮ >>b̭>4b>;>Ck •>K$•>(wV@•>} [•>ҟv•>J1˔•>I•>䊎•>CC•>JÕ>Qu=Õ>XL 7Õ>57SÕ>{nÕ>^0Õ>uÕ>`*Õ>ggIoÕ>t$Õ> iĕ>y4/ĕ>bJĕ>n-fĕ>u\ĕ>ĕ>%6HVĕ>,ܚĕ>Pĕ>|H3 ŕ>I&ŕ>[Aŕ>3QC]ŕ>ۯxŕ>G=ŕ>Yہŕ>7ŕ>:2ŕ>Bl0ƕ>IZuƕ>*9ƕ>~Tƕ>E$pƕ>(hƕ>Pƕ>0ƕ>:ƕ>Y\ƕ>Ǖ>WM0Ǖ>^D LǕ>fOgǕ>VǕ>/Ǖ> Ǖ>^XCǕ>mǕ> ȕ>qC'ȕ>$6Cȕ>$^ȕ>t.zȕ>{ȕ>$7ȕ>+ȕ>ꭔȕ>?Bɕ>mɕ>:ɕ>2R-Vɕ>9qɕ>큍ɕ>Zƨɕ>{ɕ>Aɕ>Amluɕ>Hʕ> ,o2ʕ>uMʕ>hiʕ>)ʕ>~ʕ>V?ʕ>;k\ʕ>ʕ> ˕>D)˕>]OE˕>e~`˕>lM{˕>>˕> jC˕>_˕>˴˕>s̕>r6!̕>#}{<̕>*W̕>z=us̕>zh*̕>.n̕>̕>1h̕>@̕>|b͕>3͕>I<\O͕>8gk͕>?U͕>GR͕>ﰻO͕>͕>d{I͕>Ε>N;C+Ε>vfFΕ>!}Ε>6Ε>UΕ>\3z0Ε>Ε> 9*ϕ>Ee"ϕ>#>ϕ>d$Yϕ>kNuϕ>Ґϕ>yϕ>`ϕ>ʵ8ϕ>rdϕ>yi Е>"#5Е>)QЕ>0rLIlЕ>wЕ>/Е>7Е>0bЕ>78Е>ߖ"ѕ>,ѕ>@K0Hѕ>vcѕ>>ѕ>FS6ߚѕ>M#ѕ>ѕ>e!ѕ>ҕ>J$ҕ>Tnu?ҕ>̠[ҕ>"5vҕ> w ҕ>ҕ>[4 uҕ>bҕ>jHҕ>=tӕ>h7ӕ>3Rӕ>Emӕ>qӕ>\ӕ> Xӕ>(Gӕ> sӕ>xjOԕ>2.ԕ>Iԕ>/seԕ>Cԕ>&ԕ><ԕ>qԕ>696ԕ>=1{ Օ>\0&Օ>AtAՕ>*]Օ>nxՕ>ET#Օ>LphՕ>Օ>\0bՕ>[֕>[֕>So9֕>ZįUT֕># p֕> xoO֕>֚֕>+/I֕>aZ֕>iB֕>p4ו><0ו>Kו>Fn6gו>ϛ{ו>w-0ו>YYו>')ו>.nו>a# ؕ>~'ؕ>mCؕ>jb^ؕ>5,zؕ>'Xؕ̕>|ؕ>рUؕ>0 ؕ><׿ٕ>Ckٕ>K9I:ٕ>+Uٕ>Vqٕ>Kٕ><ٕ>Rٕ>]֦ٕ>jٕ> /ڕ>f*1ڕ>YUMڕ>`hڕ>ho~#ڕ>Ω؟ڕ>,Սڕ>iڕ>hڕ>o5) ە>T)ە>Dە>G{`ە>Μ{ە>vtە>}Phە>&nە>-(ە>bShܕ>ܷ ܕ>b<ܕ>kWܕ>4[sܕ>;gܕ>}Uܕ>&ܕ>'ܕ>ܕ>BIݕ>J:3ݕ>Q:Nݕ>ejݕ>L<ݕ>%ݕ>żݕ>XUzݕ>0ݕ> tޕ>^9*ޕ>dnFޕ>_#bޕ>gp$h}ޕ>nŸޕ>$aޕ>ޕ>ף[ޕ>,8ߕ>ucU"ߕ> >ߕ>$?#OYߕ>,tߕ>Hߕ>|Qߕ>Bߕ>6ߕ>3Zb<ߕ>۸> "65>bzP>/l>: >Au)>I5n>(a#>> >I;L,>PH> c>C>Ś>_ >WV>^> K>_#> ?>Z>fqʬv>m^>t5>z>I>->t >{6>#@ɓR>+]m>2>HҤ>H>>Qq>9>z.>c\I>e>>@vGn>H۲>O p>~>a >2[%>@>V\>DFUx>ڙ> nޮ>M>]H>dZ>lV>8>Ehـo>˽mŊ>sz>{/>"Xt>.)>҃n>zC#0>7gK>*g>1a>I>W[>>RU>8B >?N'>dC>﹖H^>+y>mVB>Ǵ>N!<>A>5>3>/:>)tU>\ތ> #>Eg>>c>kW>r([1> TM>ih>ʾ >N>yr>!>)&>0{'B >R(>8~D>_>5{>7A>ߟ>>I&)>Q>>} >E\;>MW>r>n>Ð˩>%>TwP>{z>+>;t3>ϸN>[=mj>b> g>FO>za>>jX:[>qΟ*> TF> aa>ɿN}>N>xsyH> >('9B>/|͆>6a!>/=>5Y>Lzt>8ᾏ>= t>7)>Jm>`>g>D]5>LKaP>Sk>e [>6>T>n_>Z͊N>,> JH,>ތG>4 Bc>a5~>h;>p=^>5>>OI/>Ϥs#>w )?>b4Z>&"v>. ]g>j>~ɳ>H>.}s>5>036> R>m>9><>CF>Kr>>1>T->KI>Rd>f>E>q>o>ę">`# >%>ׄ@>,\>Dw>go>o>Ů>v >þ>Ps>Υ>7>}YCS>%ngo>- >4b>¥>Z>t>>;(B/>mNK>f>0ׁ>>BA>IC>Q>@ >Ul5'>zB>]>X^sy>(>m>g>?g>_$k>fy`>*:>-ZU>q>~T>n? >u>N>i>$HG>ͦ)>A1>|ZL>};h>,>3c=5>:y>.>u(>ʼ( >:)(>A~|"D>ܧ_>1<{>`>>HD'>P>WOT>L{ >;>;W>UGr>^>&>h>N;>z>ez>l92>t$.N>i>$>6ݠ>ӋM">{x>#I>*8>2*>QE>#a>|>ZL >9w>s>l7>> !>@"g=>GԶX>2`t>v>Z>;6>OaT>V>M!N>4>GP>Vuk>]A>d 5> i`;>> 5>qy>k.,>s%tsG>zzb>"3m~>7_">Ҍf>ᇫ>@`>)>1rZ#>8I>>2TZ>^ v>[M>>?G>m>qA>>v1;6>F\Q>M*4m>Uy>ݰ.><>p(>m>\E0">[-> I>N`d>>c ʛ>j`o>rT>/ >rZ >%>r&@>y{[>!ٱw>(/n>э>->AY>>0>7J7>ߨؘS>ln>\>,ץ>>X>Ee>>>m@/>kJ>L+yf>T+>[տ>4뷸>m>窱>bj&> `B>O*]>x>ꞔ>iaT>q>x >> ji >ȔG >)9 >rT >p >'0; >. >6< >8hy >. >'s >A0 >=lL >"h >Sf >; >g` >Df >K&Z >S >nS( > D >"M_ >S{ >ZeG >5 > %A >P >=: >a >h4; >PV >d.r > >X$( >pO >w ! >~axf >& >2 >scN >~Ҏi >'# >-NĠ >5 ><0wM >䎢 >ͷ>Bb)>@E>C!`>TM|>>u4>]>J̞>Ra>Yf'!> <>#LX>xs>t>`,Ъ>˅>_>5>>gJy4>nG߽O>vsk>>Yl>ͮ^>>}b>%I`>,ޤ+>t ZG>ɝb>(S~>}]>4܈M>;1>HG>܋>CA#>>>B:Z>IL\u>4>y>U>r>Q(>Xgl>!6>Q>ym>`>#>fY>>6S>.>YM->mHI>uGd>|>$Q@>̯>:>Y->X4 >+$>3l.@>:r[>'w>~ݒ>ӗ!>(,f>AW>>:>Y7>S>HMn>O>W*M>UV>> >^@>^.>J> qe>>$U>e>l>7@> >&>?A>t]>{Sx>#R>*ʯ>?>Z>x>>2mr9>9RT>@o>u>=f>)Ҫ>~f>Gݑ>;Y>Q0>K>Dg>NVБ>]Meֹ>> @>_P >'>dC> r;4_>xz>d>zr>kٺ'>r.Ol>z>"f>@:;>ѕ_V>bq>IY>)>0MS>8R> M>9>dF2>aM>?@i>v>L:>*x> 4>F7>M3->)>'E>E`>K!|>Uv֗>\N >6> >`>!> S<>jiJX>us> >!rF>>q/>y>: >(8I3 >ЖtO >j >@- > >/ >7S >>! >H!>es+!>F!>b!>En}!>~!>!ô!>v!>F!>L4rr">S"">[ޚ=">=ưY">eu">">E">bE"> qY">X">#> ŗ5#>ijLQ#>pl#>F#> sD#>o@#>&#>x/:#>~$>'93-$>.xH$>-d$>ACr$>n'$>l$>6T.!$>=e$>DV%>\_$%>@%>BY[%>Domw%>KS%>"-%>wL%>U%>+F&>R&>Z@@7&>a4ՄR&> :n&>+&>F3&>Tx&>h-&>Y&>?''>k.'>a J'>o*e'>w'>~jS_'>&~'>''>|>'>R (>0&(>-)A(>4](><9RFx(>}(>(>K=(>9(>C)>]()>8)>Q-T)>f|o)>Jŧ)>Q<ܦ)>xg)>)>,')>*>Y0*>`5{K*>~g*>:Â*>Gfx*>*>g%r*>nP*>k +>z'+>beC+>ͷ9^+>ve_z+>}k+>+>,+>}R+>x,>' ,>8:,>3cFV,>;:q,>Bό,>,>L9,>w~,> ,>IU7x->b-2->qM->^h->k->P ->Wpve->_ ->$6_->a.>X).>,D.>fR`.>|.>?uL.> .>4F.>mQ`.>t?/>| />$Z9̸W/> t3s/>|l/>3-/>+ _/>2u&/>/>( 0>30>rO0>:;j0>A20>]ɡ0>C 0>0>0>HVݼ1>Oq+1> F1>^1a1>?}1>1>Vq1>^ư1>eE31> zp2>؛"2>-0=2>Ă&Y2>lt2>@2>ի2>#C2>Ho2>s2>{.3>Q 53>*P3>xl3>c3>B3>n3>1vk3>8-3>@ 4>~,4>_H4>2c4>A~4>Gl4>DR4>,4>4>M5>NF$5>U?5>]V@Z5>kv5>95>h+~5>]V35>dw5> {-6>Ъq6>.&76>ÃjkR6>k n6>r7*e6>U6>"^6>I6>ўX6>z 7>RiR.7>I7>0)Le7>dT7>E7>7>m?7>77>?!h9 8>Fv}%8>'3A8>3S\8>,x8>{q8>M<&8>8>f 8>Ed9>&9>TR89>\WT9>czXo9> 9>i¦9>e9>K9>jr%9>P:>&/:>!{y?K:>٤f:>q8Щ:>xd:>2:>(A$:>ПO:> ;>Ix&';>B;>/ϐ^;>6\cy;>>;>#ϰ;>nN;>;>>"~<>Ew<>w:<>*bU<>qq<>!<>L=Mk<>S<> e<>F<> 5=>`1=>[XXM=>b h=> LR=>a=> L=>=>i4=>p_ >>'?)>> |D>>'ѳ_>>/}{>>w 3>>w>>83>>.^q>>&?>Jk ?>埲;?>dW?>5] s?>=^?>D2?>e]X?>Ĉ ?>R?>n@>KK3@>+O@>Ej@>0@>4\?@>R@>Y9@>a=}@> 2A>*A>O,FA>/qaA>h[&}A>bۘA> A>FA>jA>oB>v"B>}=B>&Y YB>0tB>ՅB>~DB>9B>-B>4B>KįC>X4C>PC>TkC>CC>J]l,C>C>ÖC>oWD>,D>Q#GD>BcD>~D>,kD>ȵD>X}D>`>VD>gE>#E>PAq?E>յZE>iuE>nYE>dE> UE>%bE>E>u@XF>|tԜ6F>hQF>,(mF>ԆKF>SF>0ԿF>F>3>?F>:CӃG>Bg-G>}IG>U2eG>RwG>滛G>I^qG>=&G>jG>p H>őd%H>P$AH>WyQ^\H>|xH>-XH>< H>QH>_?H>fKI>I>HPE8I>{SI>?oI>PI>t8I>I>$c2I>+#wI>O,J>{uz/J>&KJ>jfJ>2~J>ԝJ>1J>"^J>MJ>9Dy K>A 'K>HQBK>L^K>yK>K>U!EK>OLK>xK>g L>8L>9L>VzUL>]ϋpL>e$ ,L> KL>vL>6 L>ċL>lM>I1M>LM>#hM>QJȃM>su}M>z ºM>#d5wM>*ɻM>p N>l(N>˴jDN> I_N>1td{N>8N>24^N>ȢN>WN>;O>@Q O>GG;O>NDVO>rO>3EO>VljO>N>O>U O>h8O>F}P> 2P>qwNP>\1,jP>d%pP>kzZP>مjP>7P>ÌEdP>٨Q>r@^*Q>0FQ>"WaQ>)IY|Q>ѧQQ>yQ>[DKQ>؏Q>0ER>m/!R>>=R>XXR>v8tR>7ծR>>*C2R>FvR>,R><.R>%S>Vj4S>MEPS>kS>AS>N]S>S>T -S>[` S>T> ,T>rGT>@cT>c&l~T>j{T>+T>/T>T>U>qA#U>x?>U>!jZU>(JuU>Ш*U>ڬU>\U>~U>U>6e>V>i6V>QV>m mV>̽V>=+vV>E}V>LV>3=V>hjW>-W>SdW>]W>O|W> W>ZagQW>a X>i $X>j@X>D\X>{wX>rΒX>p:X>0f8X>|X>'ڎY>8vY>w+8Y>~ypSY>AnY>.9jY>dY>ScY>娍Y>]Y>5fZ> KZ>n8QfZ>cZ>"JZ>D#Z>KַDZ>4Z>w> [>&[>=78B[>Rb][>Y1y[>P"[> +[>Jp[>Xv%[>`\>h 6\>oac9\>U\>!p\>s\>IW\>v'u \>\>&4\>-0J]>Վ0]>}L]>Bg]>H>]>4s]>T]>3]>1]>] ^>;(^>BC^>JfG%_^>rz^>#^>x2Ա^>^>Q,^>_>_>5F ;_>qV_>Xvr_>_G1_>g_>_>Yj_>_>g c`>nbp2`>]N`>0i`>t[W`>`>u(Q`>|}`>%J`>,1oa>ԏD*a>.Ea>CZ>aa>|a>Ǘa>:L|a>1a>mva>^+b>-p!b>AY%=b>IgiXb>Psb>cb>yb>l]b>#b>W,Wb>W c>6P4c>Oc>Jkc>^Hc>fkDc>mc>Q+>c>Vc>7d>Y|+d>t1Gd>bd>#lj+~d>+od>*%d>{~Ud>d>(~ce>2#e>>e>:iZe>Vue>( e>9MTe>@e>H|Je>Ue>Ӵf> h5f>HhQf>O'lf>Sf>pf>f>$f>Vқf>]fg>7-g> &Hg>dg>?g>eg>lͶg>Rтg>eg>| h>Z%$h>ү@h>z[h>"mpwh>*¤h>19h>udh>ԏch>)$i>~i>87i>;WSi>萣ni>7i>Dci>?Ji>G"i>NMi>j> >/j>_Jj>6ej>Ub|j>q1j>!vj> j>zoj>\ % k>c.i&k>k5Ak>`c]k>@yk>• ]k>괡k>rIVk> k>!Pl>[l>Ѱ_J9l>yTl>dDpl>)Jl>0=l>v l>˞7l>*l>^1m>7މ0m>>3+Lm>Igm>$m>E ڞm>m>Fm>MN]m>T\ n>(n>`HCn> _n> qPzn>[in>Ǻn> \n>rCn>o>b/Go>j:o>qo7Vo>8qo>ơo>Zo>@*o>xo> Eo>(Sp>/n2p>Mp>eňip>Ÿ́p>p>6nǻp>D|p>!p>vmq>՘)q>=4oEq>DX`q>L{q><q>Ccq>קq>Elq>Sr>V!r>XWPXr> sr>ZjBJr>a֎r> Dr>sr>=r>&Vs>i74s>p|Os>9A1ks>us>+s>Aos>֖)s>~Tis>'Tt>.c+t>5Ft>\\bt>~t>Vt>e(t>"t>wJu>̧"u>+C>u>CYu>Kߒ=uu>R4'u>R7u>}u>F1u>uu>Y*v>Y5v>$Qv>&ilv>aQv>`|ӣv>gv>oj\v>v>'w>| -w>$PHw>v0Pdw>{w>%w>-9Cw>՗w>}w>Kx>-$x>4N?x>]z[x>vx>:x>f߭x>;x>Bx>xy>My>,y7y> Ry>J8ny>Q5Ɖy>Xa y>y>Guy>Ly>Xwoz>_P .z>7iJz>̭ez>Y`z>z>f\z>nkKz>uz> {>}6P&{>ʔA{>'_\{>|x{>$C{>,:J{>3{> {>L57|>{|>]8|>:UuT|>⳴*p|>Io|>]ݳ|>i|>A4|>Hpb|>P\}>#\0}>L}>GVg}>,ܚ}>WP}>2}>?I}>[}>C ~>^Q'~>eF=C~>r^~>Z7z~>1~> 0~>ml~>t*~> >#uE$>p:>(V>{0q>>+;̨>2>>CD >o>2>LIM>@h> ﳄ>^>=>Cր>Gqn>O >V0)>yD>`>-{>$>]Aٲ>@m΁> 遖>>H >d<>lW>sQ s>@>lu>cł>Ҹ>z>"vh>)3>1 N>~?j>j\>2>弃>8澚؃>DO>~>*>M>F>?iCb>F}>_)=>>6Є>h}{넖>NǨ0>U=u">zh*>>nY>.($u>h>\>c7|bDž> ㅖ>;\>@Р>žU5>j& Q>rROl>yO>!{I>d>ѹ:Cچ>χ>m<>(%,>0!6H>7vN{c>y0>3嚇>9*>nч>><#퇖>$>$>DMb?>x[>Ev>LW8>TU> Ɉ>i#䈖>>LI>[rw6>ѢR> &7m>{<>񤉖>b8">iۉ>qJ0>Av>.>5I>qSae>x؀> !>'\ҷ>кӊ>u>n >4%>/"`{A>6w\>ux>*>n>sʋ>3勖>D3>^b>E8>\T>o>KXU>Sr>Z>a2݌>]I>>i/>aȱK> '|q>Ɲ>/1{>h\0Ս>pt>w8 >n'>#C>Jph^>֟y>~/b>&][>-[̎>5玖>eU> >oO:>nU><.Iq>+Z>B>ՂÏ>4<ߏ>C>Jm6>R={1>-0M>Xh>O)>Rߟ>Y#>b֐>l> >j,)>`WD>g`>}{>ҫ >'@O>ƅkΑ>o䖹鑖>v9+>V >%;>KW>ՠr>>6>Tj멒>,Œ>4*>;])>>3>oN>=j>B#i҅>ꁔ>(̼>+ؓ>>I{>Q>*>X<F>ga>Pn}>'>>_Yϔ>b딖> >b;!>f=>fUY>mt&t>uɺޏ>(擫>ņIǕ>ۥ╖>0:>|e>$<5>+C%P>ԡP6l>z>U0>t>3 )ږ>:^dn>⼏#>$h,>pOH>ac>A$>Hy[>>,cUї> 헖>"O>P?N$>WH?>^vZ>HBv>>a<>PȘ>e!6䘖> M>c/>ut6>)R>lum>t`#>{g>#~ >Kۙ>1>چt[>.>*DI>2_ e>9N>L>J>Қ>UsB>@ >ʬ%>g^@>5\>w>GzI>N䮛>V$r)ʛ>囖>ȓ>6]>8>]S>IHo> ˊ>>Q>dzݜ>k\>dt>/>GnK>l۲f>sh>z >"a>)Zԝ>2[>ه >ܮ&>;ڙB>1O^>8y>?D.ؔ>Y>B̞>V瞖>>F ـ>h6:>zU>-p>qXt>MЃ)>U%nß>\zޟ>g>7>a1>+L>c@W[h> >U>I>§N֠>j>q[H >y*(>!VBD>m_><{>>v5>(͡>/*/顖>7)t>T) ><;>#W>gr>>E>ѩ>Ţ>W࢖>S>E >L` 3>>N>j>r>ǒ>T&>[{Rף>b;> />=*>E>bAa>i|>>JQ޳> "Ϥ>ꤖ>p\<>x!>e=>'eX>ût>Pŏ>m >ƥ>.+;t⥖>6ϸ>=c>34>gP>Nk><>D>9[>NΟ٦>b>>KaN,>RMG>Z b>j ~>8B>͆>raЧ>aь짖> 05>Lz#>>>8 tZ>h7)v>om>K">gȨ>䨖>SKa>wv>~ [6>&f6R>-Tm> >nN>͵>"JH۩>5u>< B>45->;I>d>=5>z>JH/>OtҪ>)>m >X"%>Q@>Y \>`aaw>G>sˮ>sʫ>țT嫖>g' >>ۆ8>0HS>ƎFn>nq>vB>};>%ܬ>T>ԩ>//>]EJ>,pf>3ށ>;f">׸>#ԭ>xﭖ> >B,D&>oB>]>4 y>þ>Is>PGˮ>m箖>B>Yng>9>X .aU>_b¥p>fVꋯ>>tTï>Aޯ>f(mN>m}>,H1>1L>$Ug>䀆>uC;>|@>$k5ְ>+Lz>Ӫ+/ >s(>TTC>m_>2"{>:g?g>Aӫ>`ͱ>y*鱖>ξZ>#S>H~T;> W>5>Nr>Ғ>G>OH)IJ>VAಖ>^Q>Q};>2>=5N>Yyi>e.> (䠳>l(>Pm׳>|">l~>s;*>{(`E>#a>&|>:>{ij>z ϴ>*M괖>1:>f!>U<>%X> s>9h嫏>@y𪵖>Ƶ>p9ᵖ>d>$>y(4>NظO>6k>x׆>꣌>?8ѽ>Ucٶ>]>dH> +>yG>Zwb>ï ~>k7>mbm>з>"뷖>u>r`#>z)v>>~ Y>)5u>;aT>ِ>Ǹ>D㸖>0G>7t>?M 5>4Q> `;m>_>ģ>Fy>q.۹>ss>>z3m->M^"I>T.fd>\>`>@>rZҺ>\>cI2T > ] %>M@>[\>°Gw>j>qdqA>Üɻ>!1;廖>(m>4>y*7>.S>(n>/3p(>ؑݥ>/">;fܼ>>6>>N/>ECZJ>of>`ā>. > M>LiԽ>ｖ> >rBA&>mA>S/]>[-x>b4> 8鯾>˾>澖>@A(>il>9>S,T> p>Ћ>pe>w¿>@޿>'nk>̖y>!+0>vL>g>.4m>5>=>>`>) >=OUZ(>DC>T_>Wz>M> i>`>R(>TA–>s–>;;–>&V–>Z4r–>agy–>h/–>'s–>R(–>Al–>h"Ö>of2Ö>TNÖ>f`iÖ>&Ö>\&ZÖ>vQÖ>~SÖ>ezÖ>-ĥMĖ>"*Ė>weGEĖ>`Ė>+%A|Ė>4PĖ><:Ė>C4yĖ>뒤4Ė>Ŗ>Fd.!Ŗ>r<Ŗ>J#(XŖ>XOsŖ>!Ŗ>xfŖ>aŖ>QŖ>XcŖ>`jYƖ>"4Ɩ>'NOƖ>|kƖ>vMƖ>g0Ɩ>ͷƖ>aƖ>BƖ>Ɨ!ǖ>nL+ǖ>uKFǖ> bǖ>%}ǖ>]̞ǖ>Բ`ǖ>}ǖ>f ǖ>,KȖ>3"Ȗ>x >Ȗ>͟YȖ>"4uȖ>_ʐȖ>;Ȗ>B5Ȗ>JyȖ>޽Ȗ>G sɖ>5ɖ>2Pɖ>PP^lɖ>fɖ>ɖ>Yɖ>ݤɖ>W Zɖ>_kʖ>f1,ʖ>]Hʖ>}Mdʖ>ʖ>'֚ʖ>m܋ʖ>Aʖ>:ʖ>$0˖>[$˖>tL4@˖>{y[˖>v˖>+Ur˖>ӳ(˖>l˖>]/˖>Zf̖>2̖>9p`7̖>AŮR̖>#Yn̖>̖>יS̖>,.̖>HYM̖>̖>>G͖>D.͖>@J͖>OQe͖>V:͖>͖>ZX4͖>͖> .͖>^lC Ζ>e'&Ζ>lllAΖ>u!]Ζ>xΖ>(WΖ>lЯΖ>sΖ>;BΖ>#ϖ>*jSϖ>C9ϖ>zTϖ>Upϖ>LFϖ>1ϖ> Aϖ>^ϖ>i:ϖ>Ж>8q0Ж>@TKЖ>G-gЖ>yЖ>?Ж>-ܹЖ>h!Ж>NЖ>? і>S'і>Cі>H^і>U>zі>\Õі>dQgі> і>rі>cRҖ>øҖ>k:Җ>v=fVҖ>ѪqҖ>" fҖ>~Җ>rݼYҖ>y2QҖ>"|SҖ>)Ӗ>DؙБMӖ>FiӖ>MӖ>0@Ӗ>7PӖ>_{:Ӗ>Ӗ> Ԗ>hx)Ԗ>?-EԖ>Fr`Ԗ>z'|Ԗ>NlԖ>.z!Ԗ>fԖ>آԖ>T7_Ֆ>!Ֆ>Y<Ֆ> @"WՖ>MSsՖ>[xՖ>cR MՖ>jՖ>FՖ>dՖ>¹@֖>!3֖>qmL:O֖>wj֖>!! 4֖>(vx֖>-֖>x3֖>'֖>lז>/ךvFז> bז>D_}ז>ז>6ɴז>=Wז>ESז> Jؖ>iu"ؖ> >ؖ>FYؖ>Lrtؖ>ؖ>%ؖ>{:ؖ>Hؖ>S8tؖ>Zٖ>35ٖ> APٖ>lٖ>܇ٖ>bSٖ>iG־ٖ>pٖ>\ٖ>2ږ>,ږ>pn~Hږ>wÆcږ> "xږ>'wFږ>.ږ>*ږ>1lږ>Űۖ>.=e$ۖ>5?ۖ>_[ۖ>EEvۖ>ۖ>ۖ>Dėۖ>KYۖ>`ܖ>F7ܖ>DRܖ>imܖ>Rܖ>&/:ܖ>|~ܖ> Wܖ>/xܖ>Y-ݖ>`Br.ݖ>h8׶Iݖ>leݖ>-!ݖ>Jeݖ>ǟVݖ>o_ݖ>]ݖ>AY ޖ>&֝%ޖ>eSAޖ>v,]ޖ>}Lxޖ>nUޖ>-̀Fޖ>+ޖ>܀@@ޖ>Ԅߖ>4:ߖ>4+8ߖ>;3Tߖ>Foߖ>-ߖ>ߖ>O?'ߖ>Cjߖ>J ߖ>a*>0>K>j~g>Y>X>>}iù>>0)> >_'>g9}B>n@^>Kh>Ơ>3>uT>>%|>,]':>Ի;U>|gq>oՌ>ď>3#>ہ>z>+>:1>:exM>A>h>I>񹶟>Pk>y> >PY9 >d_)> D>b_>{>WR>^tx>f >(8>cF> >f:#@<>mW>9s>Cw~>š3>6x>tUb->{q>$ "'>+^k3>2JN>vej>p>5_>2$a>9yX> >,R>I*>tLF>@?b>H4F}>OȊ>G?>>9>PH~>Vs3"> =>c3-Y> qt>&>]uܫ>eʲ >lGe>~r>ܝ>125>ˆXP>s l>DÇ>">*EL>Lq>z>1>U?,>1G>c>g~>D3>p>8z>?/>G$&>#>?>6Z>Gڊv>Nnϑ>H>.>Y~>Q>>\6>dqR> mm>k>l->dXe>k >ru>Ԭ>2X.>ʇlI>rRe>y;,>!WL>)됷>0D>آ>? >Vk%>@>7 +~\>hV3x>w>>qq>>&>F%jk>Mz>)e8>7UT>^o>}>T@X> >hR> I>(L>[T0>b[EK>j|f>?>m>g9>}>qv'3>R > *,'>ɈB>ݦ&^>xf >(հ>/E&>ףQ>>W> :>6 U>=`eq>澐>%>hE>>E&>L{>ϩ1>.dL>h>#>7,>Z>> J>7 >b(>a\D>i"_>p{>eȖ> ~>>m6>wa>+q >'!;>.յV>3r>~ e>砩><5>5`>X>N >죴2>N>C>K 4ՠ>i_>Ȋ?>>r>R}*>/ 3F>wa>,}>8^q>Y&>`k> KI >d>">S^=>hY>o]Xt>v\>R>H>nK>v>}"E>&4>-[?P>4+k>܉9>F>=2>ow>;,>O>Z&,>jG>X c>BE~>J >Qan^>>>sY >Q#>X'?>DZ>v>0mE>>_ï>fBX>n8>>TC6>ũQ>k,m>u]>–>$Wۿ>,f>>|#B>x->jI>3,d>ۊ}>U›>>w>>:@q>AGյ >k%>@>O)[>Tw>I ^>Pb>?X>Ԝ>tQ>ɓ>(7>^}SS>~Eo>1>Υ>҃>eC8>m}>t&>LRw/>Ī},K>qf>T>{j>#>+gd>2%>Q^ >y|'>XB>#]>9Qy>>5K>$>OE>@H{>G?>O9>P8U>p>2>Y#w>VN,>z>l&> j>1>]~L>dӍh> 2΃>M>xȺ>: >l8>s >M(>"D>_>ULz>zw> >*h7>1>8`2>p>϶;>$KV>8vr>? ۍ>66>>^>?>F>NI2>UH N> i>5w>Zɻ>]>\>mj> H>)>uE>c3^a>k)Ȣ|>r~\>݇>;Q>ɐG>>yD!>!2E=>(ƉX>0M[s>ث> 8>_F}>>7w>q1, >p4 >ZO >zjk >>ٰ >E.Ed >p >^ >@0 >W >M , >TIQG >c >CK~ >[o >E > >bd> >  >8# >v> >B2Z >i*nu >q, >xԖp > 3% >ȑ > >;d >A6 >'lQ >/Nm >6W > >` > > K >=i@ >k- >H >q>d >п >D/먛 >K >S2 >7? >j >$>@%@>Z[>w> S~Ԓ>>>>aei>h>p >n7>vS>!}n>pp>w<>4hj>&>'d><>~]/>{J>.OWf>5;><>W>&K> >Cz&>>B>r:]>x>&|>J%2>Rڹv>Y/N>yp>%>A9j9>ͮT>`cp>T$>]>L>\xW>g >o8Q>ve̕0>JL>"#h>wD>K>}+w>>%>,68>44| >ܒ1(>!C>F+_>Jpz>;u%>Xڱ>5>c>a>B >I;>QjIWV>t r>'>|4>Q_>X0>>>B߮2>sM>8i>fK3>^>>]>Ų>nޕ>ufr)>|E>$2`>x]|>͗>|,>>+|>35q>:!>0<>G\pX>s>>AP>c>p>X>/>H[W4>PkO>Wj>>}J>n>'>^.>Y>> :+>F>|b>eL1~>lmv>t>U-p>ijX%>i>]">{c>>#Z>*pl]u>Η>#,W>W >P>26>9J>5>>kDQ>l>*>>@QV>G7>>Y1>>v> j+->OlH>V)%d>U>u>Զ>(>}=]>dh > ;$>( @>P[>Cw>k>s>zL"g> >^'>ٳ77>R>)qn>1Ʀ>8;+>yf>ؑ>-&> >?. >?J >e >9 >Heǜ >F| >M$ >UQ > !>p&!>cA!>8\!>\dx!>vc!> #!>)O]!>~!>cW">j2">P9">bT">DJp">ə"">rMD">yM">v">(">_7#>شa|0#>1L#>h!vg#>0L+#>7o#>>qu#>Ϡi#>.#>`c $>'$>E7 ]C$>K_$>Vz$>?t$>P$>L$>TR_J$>[%>D%>dJ:%>=V%>sq%>bm7%> %>!^1%>vu%>+%>i3I&>p$2&>xqiM&> <i&>Țӄ&>\&>D\&>&>'H&>.W '>6pP)'> E'>iǺ`'>[{'>C'>=r'>F'>%'>(>ٚ (>D8ơ<(>KZW(>녛s(>@(>$(>(>SS(>Z(>ň)> \Y3)>O)>j)>d )>h)>"v)>w)>,)>*X*>oi+*>wF*>~3a*>&ק}*>]*>E*>ݚ+*>V*>-XP+>5"+><=+>`֎Y+>Du+>+>i*ͫ+>CU+>&7+>{|+>Щ,>/u5,>J+Q,>Qol,>Y8),>Ti,>,>Jc,>,>`\->]-->VH->(c->eSP->g~->nJ->x>->C->+.>̀=$.>v߽?.>}4R7[.>%}v.>,1.>F=.>ܛ*.>.>O$/>4/>;Q7/>BXbR/>n/><͉/>j/>B/>I />|/>O0>'I.0>I0>P:e0>X90>_c=0>0>K0>N0>0 1>fT%1>9A1>\1>]b$x1>Żٓ1>m1>uoM1>|1>$# 2>́82>82>+a T2>o2>+u2>2>L2>:2> 2>P7i2>˭3>_/3>AYK3>鷶\g3> K3>a3> 3>H6P3>Otʔ3>I 4>''4>CC4>I^4>W:u=z4>^ 4>474> C{4>04>u5>K5>lHo:5> t$V5>^iq5>ļ35>b5>tp5>{Ň\5>5>*yGV6>r 26>,PM6>ၛh6>I6>1?6>9C6>@6>GF=6>q 7>7)7>P{D7>G0`7> {7>b*7>o7>E$7>Nup7>U8>]b 8>~<8>W8>1s8>V8>dC 8> Do8>8>I8>L9>k39>rN9>zU=j9>"B9>n9>g9>z-9>9>)z:>0ρ*:>-F:>Aa:>l}:>6Ә:>8,:>?:>F?U:>;>{";>Q@=;>FkuY;>Mt;>c+o;>;>T;>l;>T˪b;>\ ?<>cu4<> P<>2*Vl<><>Rߢ<>j;~<>I<>=<>!D=>ɢ,=>q)=H=>yVc=>Q~=>( }{=>h0=>ؽѹ=>qn>>/'$$>>6%h?>>>zPZ>>{bv>>7>>;\>>Ϡ>>E@U>>& ?>O?>HO6?>zIR?>Lm?>S[:C?>[·?>m%?>¹6?>[!@>bvy0.@> դI@>*9*e@>d߀@>#@>2h@>p@>@> Ex A>ȣ%A>7AA>xWc\A> xA>OA>.`A>׾A>wA>rB>6B>5&b8B>={SB>DЊ6oB>.B>ᠦB>uB>7 *B>K5B>`C>I/C>KC>fC>R\C>Zt̝C>a C> e4C>_{C> D>m'D>h̳BD>+n^D>syD>D>33D>o^bD>vD>~<E>&E>U:E>NrUE>ݣpE>2E>-a]IE>4E>< E>iE><F>q1F><|6MF>C0{hF>/\0F>tF>*F>8nF>J#F>Qoh G>J)G>/bDG>æ_G>S[{G>YG>`UG>f G>nOG>H>n.I H>;H>n"BWH>rH>֭%+BH>͉m6H>uH>}=-0H>tI>,)3I>ONI>ܤ#jI>@hI>XlI>3ҼI>; ,I>Ba[I>J>*J>s FJ>?OaJ>I'k}J>񅖹J>*J>0BJ>J>PK>WB!K>_>6=K>iXK>TtK>)K>)K>f]K>K>K>oԍL>h4L>m#PL>tx(kL>SL>$,ŢL>̊{L>ߧL>|>tL>gM>+M>2G'GM>ۥRhcM>~M>YbM>M>: [M>AbfM>HN>&#N>tQO?N>ZN>zuN>O}N>BN>0eN>N>$N>VCP6O>^z6O>exQO> LtmO>)O>cnO>TO>l#hO>OO>gaP>#w-P>[IP>syeP>zbUP>#P>*"OP>MP>5HP>v Q>B%Q>1H@Q>8a<\Q>@wQ>P!6Q>LQ>/Q>YutQ>G)R>R>k`#8R>ʋSR> oR>N~KҊR>UR>1 R>R> 3UR>:_ S>]/S>dKS> MJfS>S> S>US>ʪ2r ^S>h T>"&T>IBT>p]T>yyT>$ޔT>y1#T>0\T>6T>U>U>?9U>7UU>?pU>FH0 U>[U>tU>ZU>U>M۲V>lh1V>LV>/gV>uZV>Tԅ[V>[)V>c~V> ٙV>;O W>(W>-CW>jDY_W>B{W>W>!M˱W>ɫ؀W>q 6W>x_zX>!/ X>(Xt;X>q)WX>nrX>%C#X>zgX>/X>6.aX>ߌX>V[Y>@3Y>UNY>>A jY>EINY>LjY>HY>[Y>UBY>LZ>Sd<*Z>@EZ>5aZ> miz|Z>˔/Z>Z*Z>bT)Z>imZ>3#[>?![>=[>;haX[>pt[>ˏ[> NS[>'T[> [>w`>[>\> gH4\>.iO\>ǽk\>R\>q;\>\>5/=\><\>De/]>7+]>G]>Pb]>@"~]>Kؙ]>;]>R]>d]>^>Re#^>YO>^>{zZ^> nu^>:t^>!ϸ^>am^>hՎ^>4g^>N_>ya6_><Q_>Αl_>v͟_>OT_>&_>N_>WM_>~xH`> -`>`H`>4̆d`>;`>r`> Ŷ`>&Lz`>;w/`>C t a>J/$a>m@a>"\a>Agwa>a>QJaa>Sva> [a>b>\Tb>X 8b>_NSb>genb>IHb>"ub>w Bb>̝b>n+;b>c>߈5/c>%4zJc>͒H/fc>usc>|F)c>mc>,"c>Xc>ۭ d>a&d>aGBd>3r]d>:yd>s2Ŕd> d>'d>|d>B۱e>I0Fe>PA9e>Te>B1pe>e>Pe>WKe>e>De>T(f>0f>^0Lf>ffgf>mXf>ўf>xf>Cf>"f>t g>.z(g>$5þCg>+W_g>肸zg>{Gmg>Bg>g>2Pg>ڮ-ah>¥h>XV:h>Vh>9Trh>@kAh>Hݨh>h>},Hh>h>'Ui>O2i>;Ni>9@ii>Ąi>yi>VL+/i>]si>eSi> Umj>"*j>?gEj>egjaj>l`|j>*j>pZj>j>#~Tj>xk>z=N!k>#6i=k>*GXk>(sk>>Ak>k>|;k>Gk>8<5k>hl>Y.4l>'Ol> (kl>?l݆l>G{"l>Ngl>t;l>fl>(m>}Z+m>UܺGm>:bm>z ~m> Nm>C:m>\em>dm>kLAn>"n> >n>^yYn>ʳ 5un>r9n>qdn>!n>)(n>yn>yo>-x5o> Qo>07lo>?co>ߔʣo>o>Ho>7yo>>vp>FQ -p>6Hp>bmdp>cp>F!gp>Mp>u`p>up>)Z q>~5$q>T`T@q>[2[q> Nwq> 洒q>;I׭q>tq>cAq>jM4r>_;r>7r>_5Sr>ɴynr> Hr>xhssr> Ǟ(r>(3mr>/qDZr>fs>./s>`Js>Fes>67rZs>ޕs>1Ts>?Ƙs>Ms>= t>ERG&t>LEAt>qA]t>dxt>0;t>t>Sm4t>t>!.u> vDsu>o(9u>Z3Tu>a/"pu>ifu><u>u>u>DCZu>pnv>0v>W. Lv>ȵYgv> v>wiv>~v>'ٱv>.rmv>И w>%-'w>XCw>^w>..zw>טw>@lw>w>+x>DSWx>K:x>RVx>[qx>x>kĨx>dx>Y*x>"Vsx> wy>~1y>*My>`fiy>hiy>o3y>)y>TZy>Ey>Κ} z>v)z>XMEz>&h`z>-{z>`(z>}SAz>z>i|z>4ȧ{>&4!{>{gy<{>W{>/'ss{>;R({>Bl{>J8{{>f{>{>Jf`|>3|>Q%ZO|>\Qk|>S|> |>eM|>X|>_eG|>x}>$A+}>"F}>:b}>g}}>n44}>}>c.}>F}>͛#(~>l"~>|O!>~>%Y~>,u~>aА~>۶b~>~>j"~>S~>:>| 5>ѡQ>&6Gl>a>A䌱>I9!>P:>>K >,>4.H>WT`c>> ݚ>]!>р>^ 퀗>eo>m3$>#_?>[>v>+>t޽> sɁ>#>䁗>+2>]>{Pf7>R>m>2Yݤ>ڷZ> >kS܂>\>9M>@t.>GGJ>'܋e>A>ۛ>H::>O[Ӄ>V>By >F.&>rA>VU(]>]lx> !> ^Zf>ʄ>`愗>dpE>lY>sn8>yST>p>,YM>ҁ푦>zG…>"?D݅>*@>1l>G:0>K>W4g>Px>8.> C㹆>b'Ն>kl>! >?u'>FVC>N_^>}z>Aʕ>1>jṠ>U臗>C>U> F:>LU>\@q>c> _>È>߈>gT>k>r1>z?M>!h>->т֟>'>6S։>)~>0 >H>)>ߝD>x`>Q{>&>>R>c}lΊ>銗> >lѪ >E_<>M W>Tu%r>P>2|S>ŋ>ܤ>[;Б>F> 3>D$N>Oj>b{:>jV>qü> x،>h->Ƚr>#*>xqNlF> y!b>'%f}>/z>_>7Ѝ>Y덗>!>6@MS">ޞx>> MY>Ht>F>=>D[@ǎ>⎗>L:>mw> 45>L!7P>Sv-l>Z_r>*'>ܾ>J!ڏ>Za > 5,>EH>^Yc>>hWÚ>pI>wLѐ>` 퐗>Ǿ4>#>h]@?>~LjZ>&&v>.{H>53>.ȑ>3䑗>>7\'><6>R>IGm>>Ф>C\2>Jے>R[>d>ñx.>FI>me>Y>+1l>Ű>Yғ>3>`_ >gD%>o<@>\>/Sx>Nė>oL>vʔ>aF攗>%C>o@>i8>ܾS>~o>-|3>4тx>/-•>Brݕ>m'>8l>/>BeK>Jg>_>>SAY>IlՖ>QS>X\ >L'>C>nF^>y>_"@@>k>9̗>+~痗>3>f>n=-:>urU>>'q>Oj܌>ͤ >eØ>|Xߘ>$>+ ~>3aY1>ۿ=M>ih>s>ȑL>:'>֙>|>/@ ><(>AgD>HB_>P3{>薚>T睲>{͚>P隗>W];>f >;>o&W>ĺr>^#愎>exzɩ>ץ~ś>,:>>>m>%r3>tN>kj>#Gy>̥e>8>Oל>>* $Y>2b*>9LE>xa>tL}>7>ճ>@}ϝ>"@띗>0>K!>v~=>GC3Y>O6xt>Vʼ>Kq>!'Ǟ>k➗>TJ>]ue>5> g5_P>ɣk>X>dy >kδR>s#Iٟ>tL>>54F,>ҊȊG>z?c>"H~>)9>1G~>Ps3Ѡ>젗>3->1c^#>8&?>Z>k v>Ց>r>t_ȡ>F1䡗>1]> >6>:R>Nܼm>Up>\CF>0>\ۢ>U>9>c -> hۣI>od>->p/⛣>jZ>r$ң>yy >!خ >6ڊ%>ыn@>\>?.w>(Y~>0®>7Hʤ>ߦ夗>q>Zm>7>>-S>lXeo>쩊>>u>EXݥ>L)l>T~>+/>;WLK>f>Ձ>[D>?> jԦ>V9>*~ >b V3'>i_wB>-^>qy> h>>ik>q% ̧>xz)e秗> T>'.^>Ќ:>XU>6=p>hR>/>6I(Lè>ާSߨ>E>[>?1>Ddg9h>’>'3>lw>,֩>K*>S& >Z:k(>3f D>_>%{>;^>a> ͪ>N 骗>9R>e >h`;>o$W>w Er>i>>ī>q89૗>~c>&/>-#2>5ٷ,N>7i>>۠>@7 >>R">M*>E>Ce ~a>J|>w>ma>̌qϭ>!!ꭗ>RLk>Y!>`*u<>X>^t><`>`X>gƮ>OKR⮗>ߖ>s>W4>nEP>v _k>}`Ά>%>J9>r}ٯ>r>&w>,,,>4]qG>;/b>k~>H >Ad>qа>B^찗>S>\X#>>>\RZ>IGv>PK>Xep>ěEȱ>"㱗>w[?>>_+96>FQ>2m>4ow>,>fῲ>mFZ&۲>> >XE->̭I>u d>|a>$ț>+Y >sҳ>>K >|%>3@>:0[>ïw>W>B>ɴ>2崗>HK>>7>S+&S>Vn>O>Wfե>^>ܵ>x>͕>"* />eUJ> wf>5>>Ե>lGkԶ>tﶗ>{( >#PT&>ˮ^B>]>Xx>Ӝ>*Q>1k˷>9'淗>S>}~E>9>'T>@҃p>8>9}>&¸>Qw޸>GL},>Nq><&1>TjL>h>d>Vg>]P^>dչ> pX>; >#Q(>dD>k׏K_>6{>OE>"㉱>>?ͺ>s:躗>z8>Gc}>)2;>V>YN,r>p> &>0l9Ļ>8໗>?bd>t>Ӹ2>(MN>}Wi>F >:8 >>`K׼>C>M>TK)>\L>E> `> 7|>^헽>_2>cν> q꽗>J>%!>y <>j5X>q-s>y^>!Ϊ>?ƾ>ДIᾗ>yt}>H >(4w4>/ȻO>Zpk>߯>>cH>7sdٿ>>>u3^>Ǣ+>)WG>~b>}>L2G>rK>>D2E>Ɖ>S>#>[M>>bY> F}u>_q2>w> >ihp>%>j—> q5—>DdQ—>p.pm—>x^—>ؘ—>'7W—>ϕ —>Q—>?×>CK-×>.nI×>5REd×>=×>>×>d×>8×>}×>DmB2 ė>m$ė> ,@ė>up[ė>%wė>K3ڒė>Rė>Zdė>lŗ>ŗ>ZN,7ŗ>a Sŗ> nŗ>Wŗ>ŗ> @ŗ>hikŗ>oŗ>+Ɨ>r.Ɨ>&S8JƗ>%eƗ>wƗ>~>Ɨ>&8jƗ>-Ɨ>)Ɨ>@ Ǘ>R&Ǘ>}AǗ>4S]Ǘ><=xǗ>CǗ>[ǯǗ>(}Ǘ>Ǘ>dQȗ>J|ȗ>!p9ȗ>voȗ>*ȗ>Q'dȗ>Y޻ȗ>`3Pȗ>{ȗ>Wɗ>E;0ɗ>Kɗ>ggɗ>X&Kɗ>ɗ>OԹɗ>`zɗ>n>ɗ>u: ʗ>}i'ʗ>%|Cʗ>&%2_ʗ>{vzʗ>Mʗ>/ypʗ>,%ʗ>38jʗ>;8ͮ˗>c˗>#;˗>J]V˗>;r˗>BwW˗>\ ˗>7Q˗>c˗>eJ˗>̗>PD2̗>wM̗>v>i̗>+̗>68̗>Xa̗>_41̗>fv̗>+͗>F)͗>u%E͗> j`͗>mO5|͗>`ԗ͗>͗>$X]͗>̶͗>tΗ>|jt !Η>Q<Η>+4XΗ>|_sΗ>Η>&DΗ>Η>2ޮΗ>:9sΗ>A8ϗ>23ϗ>K^Oϗ>jϗ>+ϗ>HTϗ>ݕϗ>rϗ>\ϗ>1З>O]+З>VoFЗ>^ąbЗ>#}З>|З>pЗ>+З>e0З> [pї>>"ї>j>ї>Yї>lPcuї>soї>]ї>#Y/ї>*ї> ї>{kQҗ>5җ>*JQҗ>1tnlҗ>ҙDҗ>'.җ>|;җ>җ>9:8җ>@|ӗ>1-ӗ>BmvHӗ>+dӗ>,pӗ>Kӗ>Niӗ>ӗ>]cӗ>@ԗ>l]$ԗ>Up@ԗ>]+W[ԗ>dvԗ> yPԗ>ԗ>,Jԗ>Á?ԗ>kjD՗>?՗>*>7՗>"龂R՗>G7n՗>r՗>y1՗>P>v՗>)i+՗> ՗>b)%֗>෽i.֗>J֗>0ue֗>7ʨ֗>?=]֗>}h֗>ܓ֗>1( ֗>P ח>F&ח>CAח>\ח>Ҵxח>Lgח>Mח>T'ח>^Rח>ؗ>ؗ>g8ؗ>\ћTؗ>cfoؗ>jp$ؗ>%ڦؗ>-Qؗ>‚ؗ>jؗ>q6ٗ>Ђ0ٗ>!dKٗ>(? gٗ>Н$ٗ>xOvٗ>Q亹ٗ>xٗ>/ٗ>ci ڗ>߸c'ڗ> Bڗ>l#^ڗ>6N]zڗ>> 㡕ڗ>Euwڗ>Ӣڗ>2Pڗ>bۗ>ۗ>L;":ۗ>MDVۗ>qۗ>Dv͌ۗ>ۗ>S7ۗ>ZVa|ۗ>bۗ> !vܗ>hL+2ܗ>oMܗ>uhܗ>iqiܗ>ܗ>%`cܗ> zܗ>]ܗ>p7Kݗ>wV)ݗ> Eݗ>'@P`ݗ>Ϟ|ݗ>^Jݗ>Rݗ>Dݗ>.Jݗ>5[=ޗ>޹ ޗ>7<ޗ>c2|Wޗ>]1sޗ>=!ޗ>Dv+ޗ>Hޗ>)$ޗ>ޗ>ݜߗ>21c3ߗ>R\Oߗ>jߗ>Eߗ> Vߗ> ߗ>YWߗ>aߗ>h0J>`[*>F>a>h=}>o>&>{>&.1>.Z>v">~=>7$Y>-t>>Iӫ>->X>4\>;>C 5>dP>vl>>m,>JW>*i>>ի>3ק,>Q]H>X疡c>FV>V>P>N>`AJ>g֎>nWj#>?>=[>iUv>nȀ7>u|>|@1>%u>,&i>Ԅo>}$7>8TiR>m>3c>J?>\>g>SV>: >BSP.>I\I>Je>>>nC>f>P"=>>Q7 >+{%>1A>W<\>_=*x>feo>$>O>P>b>mX>;8> T>$adVo>̿ >t>{sO>I>+'>Ӆ:>/>/c=K>f>2>9BN>y> >J*> >A'>H]B>𻸎^>My>ox> Ͱ>>Vx>{>,>u:>KU>]>woq>e >l>G˭>b>>O>sJ1> vVM>#b h>*߃>ʔ>ztI>ɉ>>1}I >t=)>0 D>腝_>{{>8C0>?u>G>KHo>s$>i >T;>NbW>s>f\>>GV>Uyr >\P>d#> I3>N>5Cj>d>kE=>Hq>7>0>P0>r*>y*F>"ca>)D$}>0 h>k>/>>0~>7Ӄ">1=>C Y>Ot>:>>.>F>MCWC>>>UB4>6P>T k>g->> V*>p>[Ϭ>c$A>jy,>G>6,c>‹~>T>q?Ƶ>{> ?>(H>Ц#>x+o?>ZZ>Su>/>lb>>>>u>6)V>=)6>E~RQ>}m>;I>=>EhC>LD>(=>>V6.>|{I>d>Z_g*> n>q'$>ƻh>b% >iz{b%>p@>.;\\>fx>U>6>wO>>'IzI>.>9C8>~[eS>>5d6>>y0>l u>8*><*d/>D#K>KԌhf>2>ҝ>w>; \>R7>b >N '> OB>^>Y`y>`v>h C>i6>a>>q6>oе9>/U>up>⠚>75ߧ>v`>}>&J >->4H1>RtL>h>4ƃ>4e_{>;>u>m>G >!s(>ChD>J2_>3^b{>>\><>F>Xq>OO >1;>V>Wr>_C>g >n`E>p>6>r0{>Ŀ2>u&tN>*j>%گn>,/D>ԍoh>|>A/b>æ>3[*>SF>⨮Ua>B|>\nO>:>A.I>Ie>B>"!>w<=>AX>P+m6t>>,0>=X>)>W>^F#>4>kP>Xk>+>f W̢>ma>tU> >sֿ>j,>t'G>{|*b>$U~>+0>2~<>>Bզ>i>/#>9K)>>TZ>u>S}#>ج>@ԍ>Hfh>O>(>xS6>Q>"| m>V>t>5g> >&>]GRh>d->lzH>Pd>[>f>X>s%>QO>"k >*y$>@>z}B\>dw>'˒>1$>O6>9z>0>t>8L)8>?cnS>#o>T#h>>a>Gg>N[> >obU/ >΍ K >#"Of >x >\H >6 > B >5 >>a< >c& >k 6B >rGz] >/y > >Y) >Ѯ4n >y `# >!l >) >0a9 >tU > p >( >}3U >7^ >: > >H >C0 >> L >Eg >ML2< >] > >^ >/ >T >p( >ƜC > 1#_ >y\z >[؇ >b-ұ > G > >?>>jz;>qH[V>xr> >ZFn>Яڲ>xh>c>(a>/Z2>6lM>i>)EU>~ٙ>m޻>=2>H>X>:)>E>DCLM؀|>Slŗ>z>_/>Wt> >Zhn!>B#=> gX>qks>ϖa>a.>iV[>p>7U>A >N4>?jO>wHk>>&RUB>.醽><>~d@>5>iz+>5m/G>˿b> T)~>um>#><3?>C>>;#>'[>>RZ>KN~u>R >>>W>> >_&B>`Q5> }Q>rl><>%>h>oِ>v.%)>P>{->@H>Օd>}>%S>-˶>4#>[O>zz >$>d@>;θ[>!mw>v>">*N>Bya>I >Q3>͟7>TS>En>!މ>XL>XxH> >>`̆>_;/>fJ>ni e>Kz>&w/>{ t>n6)>u/m>" >$g&>AB>ԖJa]>|uy>J [>,5>3T>:S^>ⱉN>>eIH9>:tT>A Bp>w4>;>!]>5>H߳>P4H/>Ws0>)L>F3g>">[g>^O>>G>XZ >(>e2C>mj _>tZNz>>|>E>&A>{>#0>*9:>2Y5V>q>K>D>(>9T>/>>\X2>M>@i>GoC˄>O>"Ż>.z>¾>O5s >V) >mE >>B` >mg| > >F >d > Z >Y!>T!!> AlklNX!>ss!>z׎!>"t!>A!>'!>|!>?">):k54">1yO">8䓾j">Bs">(">~m">K">?>g">j#>]`+#>F#>Zb#>Fp~#>N}T#>U#>x=N#>h#>,G$>"$>\A>$>?Y$> |;u$>$>G<5$>cg$>j.$>rPs$>(%> 5%>b{"Q%>ѷgl%>y;%>!ufѣ%>(%>0Z%>}%>&>1z -&>0H&>79d&>>:G&>&>$&>L&>>&>Ey'>^$'>8?'>.['>gv'>M#'>Tݭ'>y'>w'>-(>7(>7(>b6R(> "n(>ĉ(>?K (>v(>is(>qQ6(>x)> .)>c!gJ)>иe)> J)>lu)>'ˠZ)>/ 5)>6u)> *>2 N&*>A*>H\*>=;tx*>噟A*>3*>C*>*>D5+>KVy+>SG8+> ssT+>h(p+>2m+>DZ+>Zqf+>+> %`+>,>qZ0,>a7L,>h1Tg,>\ ,>@M,>,>G,>pR,>wpA ->~'->&[0;C->Ϲ[^->4z->~m->¯.->.!->5vo(-><m.>)/".>Z:.>V.>2`q.>C.>ʨ.>Dn.>T.>- .>JWY/>R2/>YGM/>`h/>ر/>m/>h;/>`,/>&X/>{ 0>Ѐ.)0>.D0>gט`0>nk{0>v7"0>+ײ0>V0>I0>՞1>} 1>%\<1>,jW1>4s1>d*1>Us1>1>m~1>;̩1>*f2>i32>ޔ`O2>3)j2>BTZ2>I螡2>ET2>2><2>Nh3>QG+3>X(F3>aSAb3>}3>;3>i3>;3>fgy3>|.4>&s"4>&=4>ńlY4>m"u4>u8f4>|:4>$e`4>J4>ԟ%Z4>5>SS55>+ Q5>3Ml5>:\95>dG5>5>n$A5>ø5>A":6>,6>գ4H6>*8yc6>c.6>H6>O=#(6>Wl6>!6>O7>$7>6`?7>^Xb[7>v7> "7>aS7>7>e 7>ls8>̷8>'a68>ąR8> m8>t9L8>{8>t48>*B8>Ӡ˞8>_9>T.9>I9>2Ke9>9]ր9>@s9>з9>oʅ9>^9> :>Gx%:>IyA:>+޽\:>rx:>ߝ:>N>l:>V]:>]:>G;>H`;>ܤ8;>OqS;>do;> S;>b\;>;>;>ktGG;>sۋ<>zp/<>"}K<>:g<>0[<>مÝ<>y<>)CF.<>0r<>8n =>Kl'=>!C=>Yf^=>Ty=>?`=>E=>fY=>m=>S>>Fy>>MXM:>>,V>>Gq>>׬>>5@>>U>>\:>>H>> W4?>1?>P.M?>¥rh?>j'?>cݟ?>!?>?>kV?>rʁ @>y)@>tYD@>(`@>1{@>؆@>)M@>:U@>/@>7A>>C@ A>;A>WA>UrA>(4A>E TA>gA>A>'A>pB>L3B>S$NB>[y'jB>RЅB>6~B>ʼB>B>b?B> xC>*C>H&FC>QaC>i}l}C>pZC>xC> ѪC>l_C>D>%!D>uP=D>'{SYD>.)tD>ׇ;MD>ϑD>;FD>D>6@D>=DOE>D4E>PE>V:4lE>xE>D -E>K_rE>'E>NlE>hF> f,F>R%9HF>Zz_cF>aa~F> .YF>F>LSF>6F>h MG>7$G>IF?G>`ZG>@vG>o[G>wK:G>~~G>&d 4G>6G>-H>l_r6H>ˊ'RH>-*mH>4J!H>2 H>5H>H>;^YI>C.I>II>MIeI>LI> I>J`4I>QI>Y ]@I>i J>dz%J>H@J>Y{s\J>`wJ>/3J>J>J>7J>ƌ!K>nFK>Jr8K>SK>1oK>RɊK>v~K>}K>[K>,EK>qrL>m/L>™JL>!ŰfL>3eL>;ՄL>B*L>DL>oYL>< M>&M>I×BM>NL^M>yM>֔M>WCM>Pn@M>X M>_`N>~N>3:N>rxUN>pN>f&BrN>m'N>lN>/N>ōeN>mO>tA_1O>|LO>$@YhO>SlO>ӨSO>O>\LO>+O>2F P>:e(P>?@DP>"k_P>w9{P>:*P>A+3P>HSxP>~-P>=Q>>' Q>Hi;Q>OF WQ>)rQ>Q>OR_Q>}Q>W Q>^a=Q>hR> 3R>s(NR>ȼjR>QFR>l||R>ۧR>0#9R>S>sB'*S>{ES>O-aS>*K{|S>ҩS>:ܳS>S S>S>1&T>9f!T>@N=T>zXT>x~tT>9ÏT>"T>GT>$rT>4T>MU>x4U>NGePU>U8kU>]U>PU>#YU>U>XLU>dwV> L,V>k7GV>bFcV>~V>k}"@V>rҶV>19V>"v~V>3W>96x#W>za-?W>qZW>BuW>0kW> W>TueW>W>5_W>8g`X>?X6X>FQX>oRmX>X>#tLX>xX>M3FX>5_X>?Y>-Y>>9IY>TdY>\r3Y>cGxY> 2-Y>^Y>Y&Y>®k Z>j %Z>l@Z>q\Z>!_wZ>t1Z>q\ɮZ>x( Z>}RZ>(ܰ[>:ܼ[>׏p8[>FS[>C0n[>/[[>6[>>L9[>檯[> ۣ[>^o\>-/\>E/J\>pZf\>ہ\>$\>yո\>Lي\>S-n\> ]>-&]> 6 B]>]]>[xy]>bH]> q]>l]>Zk]>,^>^>pc9^>_U^> p^>'l@^>k^>w)R^>~+^>ӿ^>.2_>֐F1_>媊L_>:?g_>j_>59_>=M*~_>D_>w_>_- `>q(`> >C`>Khik_`>Ɣ {`>)e`>q`>^`>R.`>YXa>a<a> 7hR;a>Wa>'Lra>?a>hEa>a>R?a>;a>g9b>od2b>v&3Nb>~wib>&m,b>b> &b>~b>e b>)dc>4%*c>PEc>;ac>|c> c>Cdc>JKc>V$d>O!d> _x?Xd>Qsd>ϩd>rcd>2d>%#d>XNd>`e>g.w&4e>Oe>͐ke>@bՆe>ƕe>n!Ͻe>SMe>e>%u f>[+f>uwGf>}abf>d~f>, f>!Lkf>vf>tf>*g>3^#g>:_>g>B3Yg>ug>JRg>Eߖg>sg>Ig>WEg>^h>5h>`Qh>PI9mh>W}h>s 3h>ȝwh>2h>{]qh>_ڈ&i>f/k-i>H Ii>ddi>Ai>Ŗ^i>0i>tJ\Xi> i>$R j>\G%j>ӱK@j>|\j>eEwj>/j>2[?j>wj>9j>!}k>2k>97k>A4,Sk>H.qnk>Y&k>Fۥk> k>dk>OOk>l>/l>X-XJl>X fl>Vl>^jl>eKl> l>|l>ї m>&,?&m>lWAm>䂩]m>9xm>#2m>m>sKm>zm>*&n>*TVn>Ҳ9n>Tn>\pn>΋n>1n>8on>}n>"Un>wo>0o>@5@qLo>GԵgo>Nho>=o>do>So>NP^o>U p>?X(p>YӜCp> g^p> zp>\kKp>dRp>kp>tp>=?q>'҃q>|f:q>rۑ}Vq>:2rq>"Qwq>)廨q>Bqq>y<&q>jq>Ker>0d2r>Nr>]P^ir>䢄r>Xr>7p; r>>Qr>Fdr>xKs>׺*s>,OEEs>`s>M?|s>>:s>8s>b}s>G2s>Tt>[M,!t>cPp &Xt> 9st>bt>cԪt>jt>ut>Lt>(xu>} 4u>ҠQOu>x1ku>!u>(u>Cu>טKu>vu>L v>8+v>6Fv>^bv>泊}v>,v>gJv>=uv>E v>Lpw>"w>->w>Yw>uw>S6IȐw>t}w>w> ?w>Ȼw>Zpx>bQ5x>iPx>Hlx>csdx>x> x>plǢx>Wx> y>'u,y>FHy>w2rKdy>~y>ܚԚy>.;Ɖy>֙>y>y>Cz>E}$z>5q2@z>Dvz> pz>h%z>jz>Dz>KqDd{>Rب{>$^7{>/S{>Wn{>R7 {>YQ{>{> @CK{>׏{>E|>aR..|>h>J|>e|>[8|>|>B2|>cv|>v,|>!- }>&v%&}>-UjA}>)]}>}x}>@}>2]}>4}>+}>D ~>TQ~>9~>;WT~>C?p~>JD~>_~>*~>~>hS8~>Q~>%0>{>K>+g>.>X)>_ڹ>g7R>}> >I='>ƞC>n^>\(}z>>v>d|̀>uçp耘>|<>%wgj>,:>*'dV>q>]>3{>Á>::߁>EfQ>>%K2>NM>BDi>Iz>PWΟ>9>e8ׂ>i|> >Wv)>{+E>xp`>& {>8j>^c>f8c΃>m郘>]>J!>şwW<> W>tS7Qs>b>$J>+\ń>ӺDᄘ>{>nv>> 3>2"68O>ڀaj>1>*v>+>9؅>@=u%>H j>4+>O`F>b>]}>OX>Ǵ> t І>j놘>3>V_">]s=>Y> 't>|G>>r󫇘>e9LJ>l2⇘>]>B>Ġ5>P>JF%l>zqڇ>#>*]1Ծ>1ڈ>>o>İ,>E H>8xpc>֛v>+0>>щ>?>j퉘>G>NC#>Fo?>][>.v>O摊>U> QɊ>b䊘> B>n>\tD7>c-R>km>}킉>8>0|>ʅAۋ>rlv>C+>!,p.>)I>Kie>y>c>T@>0k]ӌ>>f+W >V &>PA>o\>>ΪJx>,>jD>ʍ>5*>捘>FU>M7>T>~|8>1T>o>Pi+>o>[)%Ž>cTݎ> > }c>k0>bK>jhg>qtV>' >1S>ɆՏ>{J>x: > Ҵ'>(fB>/C=^>ס&y>R>U찐>z1̐>6 琘>gћ>e>$:>p%U>=Pq>D$ӌ>Lyy>פÑ>6Ђߑ>d> >S?$1>OvM>h> Hx>>Zi>aZc֒> c># >lN])>D>i W`>pu{>P>)b>ȇJΓ>!铘>1>~ >' ><>.DW>֢7s>`|>V1> vŔ>><_o> %>i3>g4N>_cj>C%>Kz]>Rϳ>-Vؕ> >P>63*>Y^JF>a> ID}>>=>`[ ϖ>h7떘>o2|>d]1">ˆ=>+Y>lot>v$>*ګ>%Ǘ>-0c◘>2\>}>5>;VP>4 l>>M>/J>[٘>;`>B>F,>hG>c>~>J{š>QY浙>X%*љ>왘>D>7#>X?>_Z>JĈv>X͑>>RȚ>gC|䚘>n>u[l>6>oR>mWm>>|!>$Bc>,֧ۛ>3*k>ۈ>V.>d>:>NAJ>Վ>iҜ>W>A= >H U%>P`@>|\>@1x>ru>h>W&oʝ>$杘>Si>/>c8>^>T>eA\o>mg>V>S ž>ĨRPݞ>m~>t\J>=/>#CK>nf>Ñ=>&>wQ7>+|ԟ>2+1>ډ< >*'>=B>$^>$iy>@FP>{Ӱ>̠>N\砘>>G >Oa :>V#PU>Oq>sz>>Cá>]|ޡ>> 0>"71>ML>dByh>l 惢>s*>Kߺ>é֢>>S! >zL(>"xD>)f _>1{>Ɩ>x{>͋ͣ>" 飘>8K>vo >4 ;>V>ʭr>?Gb>F>NĤ>OJघ>uV> >Nb5P3>UɔN>\ ^i>k>ɴC>I>\}t=إ>c> 147>{*>\E>9ua>k*}>rGo>Ls$>!iϦ>2릘>Tb>ة[!>\=>(gY>0FVt>7ۚ>oP>1ǧ>#I⧘>xZ>>ׅC>54>E=P>فk>>7>E0좨>M0>TGYu٨>*>>YD$,>hG>[ c>l/~> >X\>tѩ>bӮ쩘>i(C >q}O#>?>:.Z>ȏu>VC>xC> Ȫ>'A㪘>/L6>ת> -6>^Q>/m>6߈>p>@ٿ>$l۫>y>Δ>D-->I>d>?{>?>Lju>SHҬ>Z> >Zh%>~@>Zb\>ac>w> i\>>lɭ>ʽ存>h)O>p~}>w7>2=S>ǐhCo>>:̥>~>&6ݮ>.M|{>5>_g*K>nf> >>{bԯ>pﯘ>:\ >C.f'>JUB>R؎]>6Oy>>yI>?˰>Y9C簘>`͇>R<>$9>6U>`dp>gx0>姱>m8*ñ>nޱ> #>o#>vԷ1>3L>%wh>̃>;7>ܐU> ֲ>-N">4 >(>VvC>_> 6z>_<>B񱳘>!ͳ>q賘>I0>%u>I;>Q4V>X.#r>؍>>@Ĵ>Hഘ>_s>S>32> N>[i>fu>m>udG>r׵>!h>v2>)>|*E>$\a>+ޱ|>33F嗶>ۑq>ζ>E1궘>>:!>WC=>鬰X> `p>ƪ>H0{Ʒ>r[0ⷘ>t>&*>{n4>P#P>W/ohk>^>.b>AZ>[ٸ>^>eJU> ,>mOG>Sb>ı-I~>lY>teB>{й>#<치>w>l6#>!{>>,0Z>*Wu>24)>9n>#Ⱥ>F㺘>k>a>@O+6>VQ>m>WU> >Gֿ>Njjۻ>VH>*>|U->H>&~]>Ԧ> 9i붼>/Ҽ>(>dKT >k$>@>T[>"<w>hҒ>sf>z'ɽ>"S彘>)o>{>"7>w;S>fn>15n>8&>Qh>=ܾ>b>>F:.>FeJ>Uf>X%>PO> 哸>MkIԿ>U￘>\9 >td&>ҏ'$]>|x>cz> :0>t>7>Bcn>j#>r"h9>yKT>!ap>>][>ز6>bU>(p >/!O˜>70˜>xHL˜> g˜>,B˜>5˜>>`<˜>>˜> 6˜>z Ø>G/(Ø>ttCØ>L)_Ø>YzØ>_#Ø> رØ>bØ>TJØ>[Ę>bks[Ę> ʞ;Ę>(VĘ>}^ rĘ>b܉Ę>i1Ę>IĘ>Ę> :rBĘ>ȘŘ>qȬ2Ř>xL]MŘ> iŘ>'Ř>^HŘ>׳Ř>q)Ř>gŘ>.ǓƘ>6\)Ƙ>=pEƘ>`Ƙ>-G|Ƙ>˗Ƙ>oƘ>D6Ƙ>zƘ>Zǘ>>!ǘ><ǘ>KEnXǘ>RQڲsǘ>Znǘ>ǘ>caǘ>Yǘ> ǘ>alȘ> DU4Ș> ٙOȘ>umjȘ>ӘȘ>h2HȘ>oXȘ>wȘ>;Ș>&ɘ>׀+ɘ>ClFɘ>~zbɘ>&/~ɘ>-VWtɘ>ִ)ɘ> nɘ>^ɘ>gʘ>5#ʘ>ʘ>Zʘ>$V[uʘ>ʘ>Uʘ>-ʘ>JNʘ>ʘ>?H˘>5˘>TBQ˘>QRl˘>Y<˘>`˘>[5˘>˘>/˘>c(t̘>gS)-̘>!H̘>v#d̘>˧g̘>)̘>nѶ̘>vݒ̘>}2'[̘>%R ͘>}$͘>D @͘>ܙN[͘>w͘>,W͘>3͘>;&B͘>_Q͘>|Θ>Θ>h57Θ>BRΘ>%nΘ>zΘ>$)Θ>.PΘ>"Θ>PΘ>X7Ϙ>.Ϙ>JϘ>IeϘ>XϘ>_NŜϘ>fR Ϙ>Ϙ>:tϘ>dθ И>fm&И>mAИ>wg]И>MxИ>$!И> И>u8[И>|3͟И>$Tј>+猙ј>EN9ј>ۚLTј>oј>N ј>27Bј>:̆ј>`;ј>鵋ј>5Ҙ>iKz0Ҙ>߾KҘ>H tgҘ>{6)Ҙ>mҘ>%_Ҙ>gҘ>OҘ>W8Ja Ә>^ޥ'Ә> [CӘ>J5_Ә>TzӘ>]Ә>eSNӘ> Ә>IHӘ>\݌Ԙ>ĺBԘ>l4:Ԙ>sn;VԘ>{\qԘ>#"5Ԙ>ˀԘ>G/Ԙ>*sԘ>)Ԙ>*2՘>1="2՘>9[gM՘>i՘>Ea՘>F՘>9r˻՘>@X՘>1՘> ֘>j)֘>E֘>H`֘>NsE{֘>p֘>&֘>0֘>֘>V9ט>] ט>d/<ט> BDWט>osט>ގט>dT/ט>kט>ט>]ט>"ؘ>C3ؘ>ronOؘ>zjؘ> ؘ>)x¾ؘ>sؘ>+ؘ>ؘ>A٘>0>mg+٘>8F٘>?a٘>F}٘>Z٘>٘>O٘>F@٘> lNژ>a"ژ>=ژ>Yژ>MtAuژ>Tژ>\˫ژ>}?ژ>j5ژ>0yژ>ۘ>cs5ۘ>j9SPۘ>~mlۘ>"ۘ>K>gۘ>jiۘ>q`ۘ>^)ۘ>!Zܘ>(R,ܘ>f}THܘ>yŨ dܘ>=Nܘ>(yhܘ>/Gܘ>,(ܘ>߁Aܘ>Pݘ>5|;$ݘ>7?ݘ>>;5[ݘ>Ggvݘ>.ݘ>&ݘ>P(ݘ>Omݘ>L{"ޘ>bޘ>:7ޘ> `Rޘ>knޘ>S%ˉޘ>[ޘ>btNTޘ> y ޘ>1ޘ>9ߘ>G.ߘ>i:Iߘ>$eߘ>ߘ> CM;ߘ>ȡxߘ>pߘ>wU8ߘ>. >' %>g#A>ּ\>L"x>pwד>.Ϣ>5$7>=y>>,>8>J T>D?vo>읡s>5>Qam>>>RZ>`0>uK>lZg>4>Z `T>au>hʈ>)>G >s'>h;AC>o3^>^;z>D>&İ>y>vV.>~rs>>-_2m:>ս]"V>fq>g>Ʊ`>4%>C>-1T>\ 2>MM>6h>JG>>HpA>>/;>Q[[ >X4)>`yD>d.`>{>o(>lm>g.">*Z>>Ԃ` >2<>nW>ums>};T>%- >,M>M>}>>,`ر3>3lN>j>h,>4>>;{>BЫ>.ט>k*>▒F>7+a>}>PИ>I>>>Rj>Wy">_*=>f[Y>t>m>m>=>m!i>`>(>$*4>̈P>tTl>|<><ݢ>+g>NG>ڣ'>>W,>2;H>9 c>A`;~>fy>.>r&s>Ǻ>H&l>"$>٥f?>.:Z>e`v>>VA%Z>P>S>S >M>^7>e\dGR>lm>$A>nO>:>l">sw4>>#+c..>*rI>"(e>{=N݀>!>* ׷>1F>٤>a >NY%>!A>8 M\>@ax>GuM>>s̷>`>@>N| >K8>/S>t4o>>UB˞>]_>d'> K>J>/>SsK>kf>ʅ>f^ʝ>">>rxIy>yݽ >"r'>)B>01]>4]y>>>0GH`>7ܤ>Z>O>09>\U>?bMq>F>GG>jۋ>A>>s/>TZ1>04M>yh>E.>9r>[(>cl>jB.>Yf >)>T`D>ɩ_>qY{>g>!S>(->oXM>x΃>#G >x;>/@W>5r>ߊ:>+>>W4>6>=.>EGr>'3>N>Y!j>*f>L V>kм>>Y>t>S*>Z(F>b})Ma> T}>:>>b?>iC>ph:>!>U=>ȪSX>p t>w^> >>'>.gg!>Œ>$>yR4>.}P>5-k>ދ=>â>5f>>DHQ>|l,>G>ZЪ~>e>Rc>Y>P> l>#>Y);M?>a~ϑZ>hcu>2>@>N>:>o>94>Mx6>&bQ>rm>v_'>}Ml> ⰿ>-h f>8>_>pa->όYI>4.e>;LS>C>6 M>򋠑>F>CI >J@%>@>QK:\>vw> 4>Zx>X->>m'>˵> J!8>`uS>g o>n)_>>>;>n>uH>Nt/>%K>,Ff>V>|> >_:>3G>s >q&>ƛ-B>%]>:y>Bنܔ>I.!>F>q>@>>P9>R~U>p>>[E>Wpr>^>fd>İ>!e1>vL>g>m*D>t>>$3>̑×>tL >{E(>$FD>+B_>2Nz>ڬ> .:>`~>23>9x>r- >Ar;>ֶV>{lr>A,!>H/e>>_>A>@Y>ԝ2>VJSN>+j>L> ST>F>]>ee?@>lӄ >9* >w*E >̾3a >!Sx| >s~- >ߩ >#4>' >*k >  >zF)! >= >Q_X >1O}t >٭ɏ >= >WR > >8( >?j >GPF4 >|O >r@k >; >&9 >N >& >8 > >z+ >A'G >\:b >e~ > Tՙ >% > >df >ky >r# >o9> >dxZ >"u >r$r >yָ >"5k >)x >0 >=8>c_6>Q>Fl>7>R>Xw> > 7>>kbF>F->MH>sd>9>'v~>| ö>T5x>9a->q > 䉶$>Bk@>[ \>btew>jK >4_>`>]X>ɲ>qR>p8> sLS>(n>x3F>x^>,?>>/9>65G~>ޓr3/>J>G2-f>6]>=&>Yܸ> >Fe>bq >E&>L1B>t\]> y>(Ô>}>DL>Z1p>> />C[9>T>ap>iL>pC3>o>^>ȳ.>&>wg0>L>'g>.pB>mϞ>~->-> >56 >ݔx(>鬼C>>A_>lz>CQ,>K>>c_>> @:>RlkV>ʖRr> +> uۨ>>(>`> ?>;j2>9N>)~i>hMU3>ow>v}>Vq>Ǵ&> ik>vh *>}(eE>&Ta>-q^|>4|>$X> >gR>47>;'L!>R=>?EX>{s>?>BR>Jf9>Q}>Z&3>Q>,4>czqO>X¥&k>!ۆ>ve >d>)%>_P>g>n2yX+> G>b>Dd~>͙K>u#>WO>$>,x?>_">|Ω>>cY>h2u>3">:,>z>v&>.>:͐>Aa5>@Q>!l>>Iȣ>I ~>P>[w>`>q->d H>c>^>w e>̟>*^>_>fފX >m3$ >t? >ޖ[ >E Lw >̚ >2խ >{N^ >#? >+!>2W!>ڵ}7!> 3S!>iwn!>1!>9]q!>{&!>k!>%!>d">@/">G8^J">O0e">[X">J ">R">">VSK"> #>E&#> \/A#>Z?]#>]x#>dn9#>lî}#>"2#>#>ՙ,$>l4$>sY&9$>zjT$>"= p$>˛DՋ$>$>zO$>$>*$>1XX %>8Q0%> L%>jCg%>%>8%>?s%>¯%>&W%>{8 &>'&>F9BC&>N^&>z&>A&>&>U&>J&>\'>A'> ]:'>iV'>q'>co}'>kT¨'>r'>x'>?q'>+Ե(>рh1(>yߓM(>!>di(>(S(>0(>F(>>X(>Ҝ(>Og )>7))> KE)>aR`)>{)>)>>t=?)>Eу)>Mf)>|}*>% *>0Qw<*>M|,X*>Tqs*>B<&*>j*>*>Kd*>$*>bO^+> ^{4+>XO+>; k+>fQ+>j+>qK+>xo#+> NE+>,z,>Ё?+,>x9F,>58b,>'},>/2,>6>"w,>ޜM,,>x,>P &->j"->=>->bY->u-> !^->kL->Dw->L ->StQ->.>15.>Q.>El.>Z:K.>v.> .>C8.>.>a/>hU,/>p,H/> Jc/>gu/>Ǽ ۚ/>/>wp/>~]/>&$0>.y$0>H?0>~6t}[0>v0>.3w0>5?Ȼ0><\0>0>Qj1>G1><sd71>CZR1>2^n1> Ǣ1>b[1>1>K Q1>RuF1>qK2>).2>1EJ2>ʼne2>1Z΀2>`2>82>DE}2>2>w 3>gV0,&3>opA3>vY\3>_jx3>ƽ3>Dd3>gب3>}^3>%%/4>-zW4>4W84>-QT4>p4>BK4>6׏4>;E4>-4>H>4>V5>805>B[K5>IA2g5>Qv5>c,5>p5>%5>lUj5>Xˀ 6>*'6>@C6>k^6>2z6>W6>f 6>E6>6>7>M?7>nj:7>uU7>|V>q7>$7>ꨨ7>h~7>|ǩ7>>7>,{i8>318>:%%M8>⃽h8>菄8>7}ԟ8>8>A<8>Ih8> 9> )9>RD9>Hv`9>P|{9>W[9>;9>gj9>m9>:>^! :>]<:>zW:>*r:>::>eeQ:>l<:>t:>:>ND;>ˣy3;> N;>{W9j;>#d8;>* |;>2`;>ھv;>+;>rxp<> *<>9&8jF<>@{̮a<>c}<>8#<>]<>@<>GAwW<> =>6Q"=>I˕==>JY=>O"u=>V\D=>=>v>=>n=>58=>|>>dw15>> P>>++l>>>>t%>>k=ھ>>s4>>zc>>"F?>ʤ,?>H?>NHWc?>s ?>) ?>1a3?>8J?>?>s@>Ȳ#@>G>?@>?|rZ@>ڝv@>/2@>1@>@>FB@>M@>UE%A>Jq6A>RA>0mA>SA>\ͤA>A> fA>D A>pB>n.B>j/IB>,[peB>ﴀB>jB>4B>rcB>ynB>= C>(.%C>YWAC>O\C>QxC>C>0bJC>7mC>> C>j-D>X>D>8D>>}8TD>EҬ|oD>01D>lvD>D>9,pD>LW%D>TiE>[B/E>cKE>gE>Tk]E>E>b+WE> gV E>PE> F>oJ'F>iBF>q#jD^F>xxyF> )>F>5UF>ϊ7F>}|F>>1G>'G>.h+:G>6GoUG>ޥ(%qG>TڌG>YG>|cG>= G>Db<]G>gH>V1H>t' MH>DRhH>K(H>H>ۦH>1;DH>fH>S I>ZC&(I>QDI> _I>U{I>I>9+I>h^eI>I>%J>pP J>;J>p$WJ>wyrJ>~8J>&-dǩJ>΋|J>#J>5J>K>-p3K>5HNK><7iK>bK>ZcK>"K>K>CcK> WL>*L>k6EL>aaL>J)J}L>Q~!L>YӵӳL>2L> >L>堂M>:5!M>``|=M>1YM>M vtM>M>oM>g_ %M>niM>v 4M>h_cN>Ɗ5N>]PN>pkN>}VN>$sN>,PN>N>6^JN>O>D,O>4IIGO>;=cO>Bq~O>Q7O>O>]1O>BdO>I+P>H#P>l$?P>piZP> vP>PӑP>X[P>3P>P>FP>; Q>oP6Q>fRQ>NƺmQ>ZQ>CQ>VQ>mEQ>u Q>|_n7R>$-R>šIR>qYdR>*R>%R>+DR>2R>:.mR>⌘ S>È%S>@X@S>\S>AwS>RC|S>S>kS>[S>HoT>OWT>Wd7T>ST>nT>v֧T>W]T>^*T>VT> UT>/U>JU>lEՎfU>DU>U>W=U>ˬTU>t 7U>{`| V>&V>*uBV>r*^V>ǓoyV>&$V>{SiV>1~V>9/cV>@W>\W>A:W>VUW>&pW>GJRPW>}W>JW>RW>CW>NX>Ve=1X>]%LX>Q7hX>w|X>1X>!uX>d*X> X>4$ Y>$i(Y>ODY>kF{_Y>r{Y>z\Y>"OY>ʭY> Y>W#PZ>N Z> I;Z>0jVZ>8CrZ>Z>|Z>эZ>80Z>?MZ>F0[>8 2[>8N[>i[>FK[>M٠[>[>SL[>[> \>Uf7*\>\E\>{a\> o|\>Ͷu\>"K\>w\>j \>56i]>ʭ!]>!^<]>=X]>q\t]>yI]>F]>( ]>5P]>Xɔ]>߭]^> 4^>/kCP^>7Hk^>>̆^>s^>37^>'{^>|\^>Eۇu_>9*,_>GoG_>۳b_>Bi~_>L2_>Sb_>[K[_>\_> `>]FV#`>ښ>`>bPZ`> p1v`>I`>#`>xC`>`>p,E=`>pa> 76a>>0Qa>ϓ0ma>xa>G*a>oa>.C$a>Yoa>ޮb> /-b>bIb>6db>=b>DkVb>B b>(nb>}b>ҖI c>K1$c>@c>[c>:=wc>Ac>Rlc>ZLc>a0c> d>^d>7d>$Sd>hg@nd>kd>ӥd>pd>οd>o-d>ve>~ /e>&6?Je>Δjufe>e>>e>e>-he>4Q~e>< f>>&f>ci\Bf>]f> xf>Clf>JQ߯f>}f>~If><g>J2hCg>Q9g>'=Ug>;pg>PƋg>{{g>YM0g>`;ug>g*g>Vnh>&$1h> hLh>^Ogh>nzbh>h>q:\h>eh>$Uh>u% i>}عO(i>-NCi>,yI_i>zi>?9Ci>͇i>3R$i>;6j>BL{j>Zx0;j>Vj>8*rj>cnj>I#j> #j>uj>Kbj>)wk>P2k>W6Nk>_2Uik> k>!k>Dk>JIk>fuk>Wl>5)l>_`l>̴6|l>tl>|hI0l>$tl>%l>z4m>|_!m>.Xm>2sm>@߇m>s̪m>m>I3m>:^{m>An>HR4n>𰲹On>nkn>drn>HÝhn>O2n>v]bn>n>!o>+o>VUGo>^3qbo>e}o> 0o>E\Io>o>o>lNp><#p>p>p>#WYp>˵/{up>s[0p>{itp>p>*np>{#p>nhq>%5q>.bQq>1Ymq>88[q>@q>Uq>J q>mOq>r>GS-I-r>NHr>Bdr>[r>Nr>Unl6r>̗r>",0 s> wt$s>)@s>]4[s>d#ws> ؒs>=ks>s>*s>E[t>rt>7t>"X St>ʶտnt> jt>zjt>)t>Bt>0st>u>&.u>{=6Ju>heu>79u>?(u>F)u>Au>u> v>J<&v>MgAv>]v>\'xv>v>ův>To{v>\Ħv>c;w> xfw>֑n9w>+&Tw>€ow>j嬋w>>bw>w>!9w>Few>qUx>x$0x>OKx>(gx> Ix>ax>߶8ҹx>dx>jx>6# y>'O6(y>|zCy>0_y>0tzy>>)y>Ebny>L9y>"hy>Mz>Kaz>L ;z>S[Vz>]rz>aUz> z>f!Oz>[Lz>bHz> y {>ΠB2{>,M{>`{>p5 6{>K{> /{>'>tt{>Ϝ)|>w)|>P_#E|>g`|>.||>bJҗ|>޷|> s[|>k|>5}><^ !}>DtN<}>X}>1Is}>}>qB}>K:}>Ȭ}>\}>C5~>3~>RHO~>YUj~>ap)~> ޡ~>^0#~>[~>a~>hp>F+>$F>b>ך}>,/ >vZ>t>&?>ΝEn>ٲ">~Qh>>Y>-t>4ZY>ݸ[> ǀ>lDU〙>ؙ>; O>Cu5>J,P>(Xl>B>>1˾>Q׀ځ>6>Dz>+,>VtH>XV)d>`n>g>_g>҂>a킙>g*>nU[$>%@>zU[>%ϩv>-N>u>|HɃ>6)䃙>,TB>>H<7>㝨R>5n>Qhz>:/>B(t>cS)܄>~>#>Bv>.>IJ>P gae>~>ݽ˜>2R>P}Ӆ>W >E= >&>eHA>M\>_x>fQ>`|>ʆ><憙>h>̽d/>t8>{T>$Oo>+%">Ӄئ>{:‡>7݇>c>2>I0>NK> g>R>99t>Aθ>H[bԈ>𹍲>g >mM'>B>O! ^>8[z>̟>*a䰉>̉>VN艙>]e> :>EU>ˆq>_ˌ>lW>5Ċ> Kzߊ>#`߾>˾ t>1>zrmM>#"i>*&g>҄>Ia>8u׋> [>❟ >8AT)> E>N`>S|>HH>@t>G\BΌ>N錙>;>n >Ç5<>zW>UwG/s>r䎍>+)> mō>"ፙ>\=>d>ka3>FFO>qj>>NT>r > ؎>"a>)H>E*>yspF>a>;}>0|𘏙>若>/Ϗ>/동>C>7Bo">>=>F"Y>Jt>>ѫ>Sǐ>MB␙>T>e>-z5>¾P>Txsl>[́>,m> A>ّ>4>c,a>j,>GZH>c>T>O@>Фݵ>xђ>!b+H풙>(>A$>j?>ɪ;[>?v>sđ>6y>0*/ɓ>慾s䓙>R>9~m>="7>E=gR>LBҫm>`>(>TZ>Q۔>S}T>f > ђI>oGe>Z'>a#A>ixP>{;ӕ>5>;5 >y%>p>.A>&\>(x>'GOm>ϥz">gʖ>~Y:料>`>. >k%8>T>o>ty > N><(9—>dݗ>>:$>/>DK>KCxf>R 5>7Ꝙ>Uc>Ԙ>R #>Y^ >'> wB>g ^>6y>`$b>hyʰ>oΊ̙>-癙>y>u>5 :>v5U>`mq>&H>->Ú>}Z`ߚ>t> >4c41>_TM>h>k݃>ʳ>;)G>B~s֛>J>13 >^;)>D>:_>Qy{>XF>Mrs>͜>2m霙>X_]">_f ><>h`W>Er>qZ>gz>n0Tŝ>.\ ᝙>M>>6G3>ԋDN>|oAj>%I>,/;>Z𼞙>Q4؞>>.>ZCs*>:n(F>a>l."}>f> >Aϟ>Iԭ럙>P)BZ>m">=>;- Y>Mt>W>M>Ơ>@A⠙>Vl>^>f ,4>m_4P>k>>q㢡>?(>t%k١>>#*>+.,>ӌG>{c>@~>>>2iĵ>RyѢ>)좙>>[#>}>>@Z>mfv>h>!`>v(ȣ>HSZ䣙>O*>V|>ݧ6>gm>VG>]E'>RA> ۤ>N{>>e 4.>l`fyI>.e>&s>rQ(>l>zҥ>z{f>" >*/e`%>1@>$Z\>APx>S>x>8JMʦ>榙>cG>R>#A8>?OS>Fe:o>Nw>4>w>b.ݧ>!r>U"(>M/>4!K> vff>>\FН>ca>kYԨ>O!>S >'>WuMB>r^>̷y>!j`>ȋ> ˩>r:穙>>)0 >09>ʞU>8_p>>ݧ>A!ê>>ު> >S>Ʌ1>^L>Efh>Mă>T>nݽ>s֫>">w1 >[\(>5fD> _>߰z>=ܤ>bZ>jͬ>qF0謙>[>M >X;>ЭV>x ۋr> kA>'>//ĭ>sZ୙>҅4>'y>|2>6rN>9(j>厙l>->BYf>׮>D`>LK>Y*>F>]Sa>L}>SXM>Zf쑳>Gϯ>#Cꯙ>x@>Z!>a,:=> X>V4t>5x>.>iAư>pG'Ⱉ>>!>Y4>ϮUP>_k>~b>&@ʢ>.>5kiSٱ>ɔ>(>}T,>FG><1b>?~>>9h:>в>C척>KLS>R-#>>>^>Z>u>g!>Yg֬>ƽȳ>R㳙>p>>`-=6>gQ>oem>6>%>P>>ڴ>v>;f>%QЪ->-dH>d>Y$>O>-{S>4lҵ>:M>ϑ >~F%>ӎ@>(#[>BNw>y:>:>94ʶ>x嶙>JM->Qr>X!7>VMlS>x!o> f>^>__>ݷ>qY> >$LS/>fwK>n Mf>u->F>>?@Ը>Ԕ︙>|J: >$Rv&>, 4B>3x]>Z-y>┹>'>cl˹>:I!繙> u>u >ʝ_9>)U>Ap>H݈>P2S>Hú>s޺>D>F>W0>^M\@L>g> >_G>^r>eջ>r2> >['(>zC>mٱ_>t.Fz>q>#б>@1ͼ>ӕ輙>Y>I>+x;>2DV>[prr>>0l>dİĽ>X߽>@>v_>C2> M>i>G.S>O3×>VWܻ>悑׾>EF>B>)>]NE>-:a> ~|>WV×>x>d-Ͽ>kiAr꿙>sն>l!>{,!=>eX>%Us>z_>">)8@Y>1ԝ>R>@>L4>SO>8SFk>౪>?@>ej>9>~>Fn3™>+™>!~-G™>b™>='~™>N4iܙ™>U ™>\ޑe™>=™>Ù>|#Ù>\O>Ù>c<ZÙ> huÙ>XÙ>LÙ> Ù>jjÙ>r{Ù>y@ę>!s;5ę>fQę>&lę>{3ę>ںę>(9板ę>0zę>7'ę>A:ř>e-ř>Hř>Jdř>>ř>儛ř>\yɶř> ř>9ř>Eodx ƙ>L$ƙ>T@ƙ>w[ƙ>kwƙ>+xƙ> ƙ>[7ƙ>b4ƙ> Ǚ>Ǚ>F7Ǚ>bRSǙ>ivnǙ>YLǙ>6Ǚ> Ǚ>aǙ>q!@Ǚ>xș> t9/ș>'u~Jș>'3fș>|5xș>ɼș>0qș>/ 'ș>6kș>B ə>te&ə>Bə>K4_]ə>ȣxə>DXə>]ə>Rə>Hə>fsLʙ>KŞʙ>S3F9ʙ>ZoNJTʙ>?pʙ>,ʙ>9ʙ>F~ʙ>a5r3ʙ> ʙ>1-˙>>q0˙>&L˙>hg˙>pP ˙>wEe˙>q˙>b˙>η0˙> X ̙>~k (̙>&C̙>-_̙>5tDLz̙>o̙>1̙>/̙>?̙><:͙>͙>:͙>BC3V͙>nq͙>-͙>JU.͙>Y͙>͙>g͙>Ι>Rي2Ι>YpmMΙ>`iΙ>$-ɄΙ>X~Ι>»Ι>`6xΙ>gΙ>qϙ>?l)ϙ>Dϙ>+`ϙ>oQWe|ϙ>v멗ϙ>_ϙ>%Zϙ>͸Xϙ> kЙ>b Й>*<Й>, VLXЙ>4usЙ>;~ՎЙ>(Й>?Й>iЙ>1Й>B)~љ>T34љ>CwOљ>}jљ>qљ>IV&љ>Qhkљ>Xљ>_(eљ>Sҙ>^+ҙ>g|Fҙ>_ƧXbҙ>% ~ҙ>zgRҙ>ҙ>-'Lҙ>fRҙ>mEә>u6{"ә>?>ә>$:Yә>Hf9uә>ԝ}ә>|%3ә>$[Qә>+,ә>ә>c&ԙ>9k5ԙ>e Qԙ>3vlԙ>:$ԙ>)Pϣԙ>~ԙ>ԙ>2 ԙ>8Rՙ>Hc-ՙ>DHՙ>#dՙ>Nՙ>Mՙ>Oՙ>Wՙ>^V79ՙ>b֙>$֙>h"?֙>,[֙>ev֙> { ֙>Сۭ֙>%6 ֙>ăa֙>l⌊י>t7!י>{7י>#Rי>I ~nי>Ӟ‰י>4י>R`י>*qי>1 י>9[ؙ>߯.ؙ> eJؙ>meؙ>3ؙ>@!_ؙ>Xؙ>ؙ>)ؙ>ޖ ٙ>r%ٙ>NV2\ٙ>]xٙ>N?ٙ>ٙ>VI9ٙ>]W}ٙ>dqڙ> wڙ>i,9ڙ>\qTڙ>d&pڙ>krkڙ>G ڙ>&dڙ>"{pڙ>ٛ^ڙ>s8ۙ>z[X0ۙ>" Lۙ>)ARgۙ>ҟFۙ>Kۙ>Ioۙ>Eۙ>0ۙ>8\Z? ܙ>?'ܙ>9Cܙ>nE^ܙ>2zܙ>nwܙ>Fw,ܙ>ܙ>*Y&ܙ>jݙ> ݙ>M=D:ݙ>UVݙ>\l^qݙ>Fݙ>Ȩݙ>W ݙ>NQݙ>cݙ> Cޙ>a2ޙ>kEMޙ>hޙ>js¯ޙ>qVޙ>y8ޙ>!|ޙ>(Ѫ2ޙ>/ ߙ>؄j,)ߙ>Dߙ>(B`ߙ>/U{ߙ>7ߙ>Jղߙ>柩ߙ>ߙ>7]>> >}<>eTW>ws>>n>Lӵ>+j>>߾d>4S3>T~^O>[j>b=> Ҝ>Q>O>&>iR>b}E+>F> a>jу}>p8>x}>s%>'Pw>0|,>ׅq">ڤ=>9jY>.u>6d>=B$>O^>z>TX>>DQ5>fQ>Kl>#>oNE>Ky>R#?>Zx>8>5,>2H>!wc>a>M,>hp> &>P8>>h>oY$>?> L[>&bWv> >w7­>~t>&>-(>ֆ>J6>0>R> m>55>>>U>I>%.>J^ I>4e>Ԁ>g]>ňη>Q$>YyH>` >-%>3wA>ǻ\>5\x>g>j>HG>>>nZ2^>uƢ8>}[S>%co>Q>F>k>>,)1E>3~ʼn>;Y/>1K>f>D}>:>Bw>/,>Lp>% >j'>UB>PCd^>oz>h^>.>W>Xz >_ςQ>f$>BK:>mV>6Eq>f->m>>I>8>$}>QA2>tl1>|,M>Zph>+%>ڟ>l>d> @>2k >:)>A)WD>釿 `>{>;>K>H>>Mj>>> >V;>OW>V ~r>^_2>=>i>q>Ƒ%>e%>lzQ3>|N>.j>Č<΅>lg>s@Ǽ>{ >#>*IP>ҧ{*>{pF>[;a>*fj}>1>m&d>º>O>vz>9եW">@*:=>eQY>t><%K>>M>NEy>>>8>N4>|P>U $2l>]`v>dL> xp>r%>7j>̮>k{c,>"H>/]c>"K~>vW>rA >z6Q>ʕ>)JJ>Ѩ!$>D?>RJZ>u>v>0>7e58>?|>1>w >̴+>!Ip6>Ft%R>ޟm>34>c>><]>T>>Os .>I>3e>\a^>c>j D>j>ݮ>r >j|%>q1@>0]\>!w>(څ+>8>yܕ>p>(K>/0>[8>SS>樄o>NJ>6f|>>o>E>n/>Zp>"/>wJ>L֮f>4c>n>>=.>SYW>[ >bF&> B>J^>Xmy>Ԕ>i ->kX>>> >s|>p1:>w'lvU>|p>'+p>.0>֎i>>Bc>.>5j]1>TM>*Wh>>]P>=>DJ>o>iD >#(>x)>D>ͽ_>R,7{>>1>>>h+>Z>aG(% >hi;>W>Yr>><]>obg>>' >&kP>3>v(N>~}i>:D>-1f>Տ>%>97>>4*>;LE>C9+a>d|>^>$ڳ>>Jg>>!>p8=>cX># t>X#>`׷>6>p>颴>`Hi>gb4>nO>Q"k>M]>⡢>nc W>u>P>%la>,+>!G>}~LDc>~>,2 >>3>7>:`|>>v#>:MK+?>BoZ>Isu>Ui>> _c>^>P]>J>qV6>rQ>$Pm>W>_]J>f->D>H>?=>Ŕq->m7I>Rd>\1>$u>Z+>tG>{$>cpi >+›% >20c@ >u[\ >\w >) >2FǮ >9 >A2oP >鐚 >.J >DZ7 >AS >Hn >VE > >  >_ >-1 >VY >q/ >J >%Df >zف >^ >e.Ӹ >l, >W >@ >ĕ& > B >sI] >vy ># >*R+ >ҰV >zi >d > >1֧9 >v]U >˕p > * >U >8ހP >@3 >G >Ԏ>ED1>L>(g>NNT>7>|>W>u>U* >\io(>d'C> Si_>{~{>c>%>k\>rf>8V>"&>QP;>rJ}W>yJr>"<>)SC>0e>=>e>P7>0|2>7n1N>;i>!*>vdo>Տ$>?4>FO>z><*>:E>a>EcV|>T >>XN> I> >[j9!>c<>jb=X>ss>Ѹ>&M>{0>q >98>!>(`$4>AO>xk>Kӆ>J>/ ͽ>7>\>_ >+>6ouG>=Jb>E}>w >̞>+ʭ>^>L߉>=\#>I>>tVZ>F u>ߐ>ZȔ>YI> > C>aH>bs=6>iQ>pjl>{>'0>|u>p۲*>w0Go> r$>'i->.9H>֗bd>~>K\>>5EV>]q >P >$>fI@><[>DCw>Ko>D=>,p>7>֘{>R50>7>*S> >on>C$>Yn٥>`P>hb>>b>/> VJ>okB f>vO>>&tI>>v1>} >=&>-:AA>46]>x>L,>>4>;U>䳫>@>]9>T>C+p>Jp̋>ꁧ>#>{>>>,>X0>)oL>?g>R>}>_Qb>g=>n>Z >(V(> C>bQ^>u|z> I>%u<>,>(>|'= >ܻ >1P: >3{{V >0r >C;u >Ϲ >n >:V&$ >Ah >IO!>^zb2!>N!>:\i!>gΠ!>PU!>$% !>yO!>M!>-yI"> )">^8CE">@d`"><|">#">H6">f">mw0">tQ u#>7*!#>c<#>c#X#>t"s#>{#>$vҪ#>+v#>2 \#>~6#>a$>2 4$>2!O$>9k$>DṆ$>u$> C$>M5$>@`$>H%>OV6+%>F%>b%>ht}%>*%>V4ߴ%>z_%>%> %&>"&>]އ>&>e7sY&>lu&>2Ɛ&>I^{&>Þ&>&>sR&>n'>"r5'>*[P'>ҹ1l'>z]b'>m'>…'>1!'>8vE'>p(>),(>0H(>8[Id(>?<(>C(>﯇(>DD(>o(>G6 )>NW/{$)>Z0@)> t[)>i*w)>n)>C)>\rnh)>љ)> &.b*>Y*>[7*>d8S*>kUn*>rA*>AmO*>Ÿ*>,I*>I*>yB+>!.+>)\0@e+>l6+>n+>+0+>t+>7w)+> ,>*#&,>?hA,>j],>>=x,>E*,>M[,>E,>,> ->N>O->Ti9-> T->a)o-> B->->i}<->bȨ->j=6->|h.>ړ0.>/(K.>Ʉ)g.>qނ.>x8|#.> ع.>ҍ.>Jg.>x />&'/>(]RC/>/^/>6{ z/>e/>t/>f/>6xn/>=%0>+Qh0>:0>yU0>4q0>D[0>Ld0>S=0>$0>OO0>O1>x11>ZM1>bBi1> c1> ˟1>j#1>aN61>iz1>psw 2>Ңt)2>0)E2>ȅbn`2>{2>w9"h2>M2>&a2>.Bv2>֠[3>~!3>TaU<3>W3>5!Os3><]3>H3>u3>oB3><3>C#`<4>Kx34>6O4>+zj4>/4>K 4>R>)4>4>^#4>P5>+5>aF5>`Yb5> }5> 5>kŴ5>] 5>h5>ot6>vɱH"6>(=6>džY6>ۜt6>01<6>}\6>%6>-C6>4/6>7>U57>P7>/#l7>;^[؇7>㼆7>Ҿ7>f7>7>B$8>Jy,8>Q. H8>,Zc8>t8>8>58>Xٲ8>h8>H9>-#9>X?9>_Z[[9>fv9>n9>cؙ9>O9>9>k,9>uW:>|6:>$~R:>,ӫm:>1׀:>|6:>z:>,D/:>3Vt:>:;>Ln.;>A#J;>ge;>:_;>Aa;>;>gU[;>;>U <>Iz@ &<>PNA<>-]<>Hx<><>6TB<><>^<<>I?=>5=>gz8=>Q/T=>eo=>mS)=>tZm=>#=>>=>l=>fa>>{ 0>>#K>>+Qg>>2)T>>ڇ >><>>;>>eH>>9 ?>M'?>PB?>;^?>Vy?>@;?>G ?>O_d/?>?>$)@>qO@>":@>V%U@>:q@>ь@>7@>@>"@>d@N@> yzA> 1A>R9tMA>ç͸hA>lmA>s[A>z!A>"MA>mxaA> B>z!8[)B>v̟DB>*T`B>1*{B>8 ޖB>KB> B>C>?Eˆ C>;WC>MrC>JzC>F v/C>N` tC>UC>mC>r"D>ljg3D>ND>\{IajD>tD> / [D>D>TD>cA D>jNE>r*E>JHHFE>¨saE>B}E>RE>y;E>\E>(e5E>0zF>G/"F>wr=F>)YF>!mtF>7"F>>ZgF>3F>F>EF>>FqG>E5G>0PG>N lG>YNG>G>MaG>TDG>pG>jH>/,H>GH>rX5cH>bу~H> 0H>CH>(H>8H>i.I>q#I>xAW?I> ZI>vI>SBˑI>רI>I>'f-zI>/I>6VJ>n6J>ͬmRJ>"AmJ>wJ>=J>4,aJ>J>TJ>=K>DT.K>K?IK>SFdK>K>+HK>XK>SK>Z K>k; L> >%L>@L>sy\L>ȒwL>h'sL>p|RL>}mL>9"L>ǎ=gM>phM>wB`8M>~SM>&ZoM>TM>֩|TM>~ M>].gM>5GN>ĻAKN>#fN>x{;N><צN>C,;5N>fN>.N>4s O>('O>JBO>RGz"^O>YgyO>9O>YeѰO>O>ZO>`bP>P>y :P>k NUP>8qP>g(dP>o}P>vҌAP>1P>ƏP>wQ>9 51Q>}7LQ>%bhQ>,LQ>4(Q>ݺQ>^Q>vQ>  R>;g6(R>BDR>_R>o{R>εĖR>B-yR>IuR>sR>55S>S>;S>QH gWS>XrS>`S>QtS>ZS>4S>YS>fT>N3T>lNT>GjT>sT>n~AT>u2T>|(T>$T>5U>:y*U>ۏFEU>qsaU>+M(}U>31mU>:űU>UfU>U> `V>^E!V>ApZ=V>YV>p0TtV>ĘV>$MV>HV>PدGV>W-DV>oAW>4W>?/;PW>kW>^4W>RW> .W>BsW>Zn(W>įmX>l.",X>tcfGX>cX> ~X>uX>AZX>{)mX>~TX>*, Y>;X#Y>ڐ?Y>ZY>DuY>2ױY>9kY>@M;Y>+Y> WY>_Z>@6Z>GQZ>q֘mZ>j݈Z>!Z>z*׿Z>NUZ>V.Z>]~[>-[>@I[>id[>[>dI)[> Ts[>[>R}[>ð \>kf%\>sdh@\>z[\>"(w\>vSZ\>瞮\> |\>\>)M]>03g]>87]>&S]>ERAo]>慊]>zʥ]>?N]>F:]>fy]>V^>%s/^>FQ(K^>Milf^>Uy^>f^>r9^>d`^>U/^>\$Z _>O'_> 8SB_> ^_>My_>@8_>jcG_>_>S#A_>±N`>:`>re9`>y4U`>7yp`>(nb.`>̍`>!"(`>M`>!`>/4 a>71a>>5`La>ʃa> a>ESa>Ea> a>W b>4G(b> `Cb>Lj_b>Tzb>[:b>sb> b>&b>{3.c>b^c> 9;c>Vc>!rc>A֍c>i c>pc>xJ2c> ]c>d>\2d>ױNd>ݽid>eqd>.Ĝd>61d>w\d>ևfd>+e>6G`*e>=ۤEe>D4p`e>쒛|e>Se>F[e>DMe>Ke>XFGf>ڋ!f>oaXf>S:tf>ZZf>t4f> yf>'E.f>|rf>mg>h0l4g>!Pg>Xfkg>9g>Ǘ`g>oCg>wKYg>~lg>&Sh>],h>ֲWMGh>bh>fG~h>-Bh>5@h>͖:h>,i>V4#i>x>i>C5.Zi>Aui>'i>=jli>!i>Ji>QPUi>Y_j>6j>YYQj>mj> iSj>`kj>ʿj>Tj>tFj>k>'@-k>nHk>dk>:k>Ƙk>Rk>vL~k>}k>' l>,U$l>ճ@l>[l>gwl>QВl>4}l>;pl>Bťl>#m>xm>א7m>,%Sm>IPnm>{lm>>m>m>Ϫm>PQ_m>Xn>_#.n>ZOJn>zSfn> n>bܜn>fΑn> Fn>un>" o>(N&o>my:Bo>t ]o>|1xo>$xo>-o>Cro>ۘ!o>Llp>Lp>2 f9p>:Tp>^_pp>p>Yp>g p>AKSp>Hp>y Mq>61q>-FLq>Hgq>O@q>?q>J:q>~q>H 4q>W5 r>^-(r>[Cr> '_r>zr>cI!r>ĸer>l r>v4r>s># ]Ys>~;s>sݳVs>{2Hrs>Ls>*s>D3s>ڙs>[@s>Mt>12t>9GMt>@V3it>t>2t>ht>Z't>Gt>zu>E)u>$Eu>`u>N0|u>U7ɗu>]Yu>u>Ixu>Dv>!v>dR /lXv>İsv>v>ùv>v>rmCv>zv>"!w>.S4w>—Ow>z3Lkw>w>֡w>0ٚm@w>w>N-:x>~+x>83Gx>?Wxbx>F}x> Arx>il'x>lx>F,!x>Mrey>#y>%_>y>{Yy>?Yuy>T8ky>\Ry>cⓗy> ALy>y>~Fz>I5z>j>@Qz>jlz>\9z>!~z>3z>qnz>y}-z>r{>(w='-{>hH{>* d{>e{>޼{>/=϶{>6|{>>Y{>E< |>g$|>@|>NL[|>Ew|>LPF|>`{|>@|>;|>Lsf}>S}>&&7}>|R}> N-n}>/z}>[}>b9}> Be}>}>$~>J.~>ȟMJ~>pxe~>]~~> 8Ü~>dx~>e~>x#r~> >nL%>.wA>+e]>ހ7x>>4>5"Y>=趝>D=K>v>L9>O6T>o>K>a!@>€> J݀>ju~>Rɠ3>Z5x0>asɼK> qg>0 '>k>H>h9teՁ>>3_ >Bȣ'>ǠXC>^>vTRz>~G>&sL>f͂>ջ2F肚>NJ>o?>Ć:>4#9V>݁q>q3>5訃>1-ă><\߃>C>&>Jk> 2>PM>pi>Jτ>QY0>[ɻ> ׄ>bR>>Yۼ)>`toE>gF`>(/{>Z>>09΅>n酚>٣>Cn >%-<>-W>uUYs>}ێ> >,^ņ>Լ؊ᆚ>m>f>,3>3$X~O>:yj>B΀>,>q>k؇>5>I+>Ve+>GF>a>}>PZX>Wj>_ψ>c*눚>>">_uF>>fʩY>)?u>~i>ܔ9>1)~lj>̆≚>tw>D->$q5>&Q>Lhkl>| >(e>U>2^ڊ>>gX> ->gRH>9zd>A&L>H$>E>ы>6?틚>:>Oe9$>H?>%3[>wv>Q,>V⭌>^&Ɍ>eZ9k䌚> d >>l$7>^R>l n>ɉ>ԣ >#)8R>ˇc܍>s掼>z;#>E.>*I>Me>٢􀎚>69>Vb>2ӎ>8 ">@_, >%> A>q\>@̐x>G%aՓ>Nz> ʏ>7L揚>>N ~>U@8>wT>_o> I>>]Kk>d[߯ݐ> e>>m^0>^K>f>rv>IR>"*ޖ>)rԑ>ݝ>y]'>B>0E^>أH9z>}>Mq°>w̒>7 ,蒚>?`\q>F>k:>rG V>dq>p>M{^>ē>.[Xߓ>>R>TAF2>[KM>cnh> JE>.>Y?>R֔>j9>E >e2)>!mwD>,`>m-q{>xX&>!+۲>( Ε>C镚>3> ><><,XW>6W s>Ž>N>BŖ>ᖚ>>a>E>L +?3>iVN>ȁj>>r2>S缗>/ؗ>> )&>8U*>ZF>ba>iA}>Θ>>SϘ>Ȩ( 똚>pT>fw"> =>'Y>nӵt>wj>~">w'ƙ>.R♚>4~^>݉>ަ4>=ҜP>fk><񑖇>DF&ۢ>Q>}Eښ>X>>K у,>RaeG>}c>2>sPw>R{,>Y'qћ>;&훚> j>0d#>d?>a[>hBO^v>z>X>T: ɜ>ǩQ䜚>b>v]K>7>&NER>-fm> ?>}#9>x8>a}۝>4,2>܊>L,.>4pI> &e>;7ۀ>CG>J`d>Ӟ>Y>K >W%>Qb A>6\>x>k_K>Ɋ>X(ʟ>_}J埚>g>>1 >58>S>9^2o>n犠>>LI>%%ݠ>>T>|/>]K>,gf>ų>Hȝ>ys}>ԡ>#>:ǻ >p'>5B>j^>Fy>BHrd>I>Pˢ>PƢ碚>W>>PcQ:>WEU>qKq>l>ԧ>ʼnã>^~>ߣ>fӄ>m(>D}1>o2M>:wh>̏>tp>M%>$j֤>+>UCd >{n)> ^D>^_>2W{> >pQ>ͥ>$BK饚>9m>@E >H-;>>W>r>?8>}>O@2Ŧ>VHvচ>,>p>Z%3>VN>]j>mԅ> ?>]>uا>e*>l) >*>~F>;a>ː>}>D>zD>#)Ϩ>*ꨚ>V>٫}!> =>_=X>+t>8>q(>ƼƩ>Q⩚>z|>?٧>G.<4>NP>k>@'}>>O>UI{٪>p>:> R+>G>\&dc>dd~>kN홫>z>vWѫ>9쫚> >r#>$K?>!3Z>)Mu>x>; ά>8Ȭ>㬚>0N|>ج#2>v6>VLQ>wpm> >>i7j>b>cۭ>{">ж]>F/.>MvWI>T d>76Q>a>J>TJ!Ӯ>[D> > Su>%> @>58\>ce`w>j1>qv>n+ʯ>寚>!t%>vj>x38> 4_S>(o>/އ]><>>r ݰ>EQ>62>^/>WJ>Df> >=jݮ>Dq󸱚>L8Ա>r1ﱚ>\ >&&>{+B>Sڰ]>8ܕy>pڔ> >A0˲>Z[粚>a>iJ>9>C U>\op>ȱ>p/>oZpó>޳>"j>w>B0>~+nL>']h>.->=YW>ݒ훺>Qִ>F>A >XDD>,_> X>{>a삖>C8>K|͵>Rj@赚>kv>'+ >|+p;>ѿV>Y0ir>> c>9?Ķ>j]ක>`>hK*W>o2>PN>]j>DzJ>>>vfiD>Ŕ׷>%)>>-o>7*>},E>1a>45h+>ܓ೸>'%ϸ>=i긚>>{c!>BP=>J;]X>gt>bǏ>& >JRƹ>Qk⹚>XzJ>>}Ѵ4>eO>X1k>_%󆺚>P>:콺>y1ٺ>>gLЛ>nd+>G>U$b>ƳO~>ә>]x>|л>$ς컚>,pc>3 #>##>>NvZ>u>,w>:>iȼ>>b㼚>>!>AQM]6>IQ>Pul>Y>P> a>bڽ>W >LD>u->tH>(d>^7>e_|>m1>vҾ>峺>Co >̘s$>ti@>V\>#^cw>+󧒿>^]>ڳɿ>V忚>+q >2ƝP>$8>y]JS>؈n>-D>>@=>?>7>>H\1/>HJ>O+f>VQo>$>ڸ>c>/c>][ š>v&š> Bš> V]š>~ yš>dš>l2š>s.Jš>Yš>DÚ>˙Ú>=9Ú>zMTÚ>"pÚ>*Ú>1V-1Ú>ٴXÚ>Ú>hÚ>$Ě>80Ě>zLĚ>ϗgĚ>$,Ě>W͞Ě>Ě>F7Ě>N Ě> Ś>Iv(Ś>CŚ>*^Ś>URVzŚ>\Ś>Ś>dAcŚ>էŚ>\]ƚ>cmƚ> V;ƚ>!UVƚ>vqƚ>ƚ>k3@Jƚ>rԎƚ>Cƚ>!<ƚ>ʚ=ǚ>S2ǚ>DMǚ>|iǚ>)?1ǚ>0Wuǚ>7gǚ> oǚ>i$ǚ>RiȚ>)Ț>>rcEȚ>=aȚ>%\|Ț>zfȚ>ّVȚ>E8 Ț>MQPȚ>Tɚ>@J!ɚ><<ɚ>CXɚ>Iesɚ>[=ɚ>ɚ> \P7ɚ>{ɚ>1ɚ>bn;ʚ>i*4ʚ>qdoOʚ>w$kʚ>պنʚ>*Oʚ>bʚ>xʚ> =:ʚ>'˚>/bV+˚>E G˚>ޚ"Pb˚>M~˚>NI˚>6 ˚> 9˚>`˚>̚>"̚>i!7>̚>DLY̚>&xu̚>{ ̚>7̚>/̚>L̚>S̚>Z8 ͚>K5͚>vQ͚>J l͚>Z6͚>aƣ͚> ]{͚>͚>͚>eJΚ>huo-Κ>p HΚ>wncΚ>ɭΚ>+bΚ>πΚ>Κ>~4IΚ>&tV Ϛ>.$Ϛ>5=?Ϛ>ݛȔ[Ϛ>IwϚ>OϚ>ӭϚ><HϚ>as=Ϛ>К> К>j{7К>C0SК>JunК>RsК>FoК>0r$К>iК>ښК>Y9bњ>`Z.њ>\Jњ>Beњ>EVњ>`p њ>gTPњ>oњ>Iњ>]Y Қ>ƻC&Қ>oAҚ>voD=]Қ>oxҚ>%#7Қ>΁/Қ>0Қ>+XuҚ>*Ӛ>-Ӛ>4>C$9Ӛ>ܜnTӚ>pӚ>P.ӋӚ>Ӛ>V\Ӛ>BYӚ>귭Ӛ> B Ԛ>aO0Ԛ>LԚ>I-gԚ>QtԚ>XUCԚ>(Ԛ>Ԛ>@Ԛ>06 ՚>_'՚>+C՚>C^՚>T*z՚>ߕ՚>fU՚>n?՚>u՚>^֚>ż*֚>:֚>fSV֚>|~q֚>$${֚>+y>֚>3֚>,֚>⁒֚>ཱིך>5R1ך>:}Mך>biך>G=ך>ך>ך>Pך>Hך> Oؚ>b|)ؚ>IEؚ><`ؚ>PugC|ؚ>Wؚ>^ؚ̲>~ؚ>6ؚ>1{{ٚ>^0!ٚ>e:u<ٚ>Df*Xٚ>nsٚ>ٚ>Lhٚ>mٚ>tzbٚ>{Uٚ>#9\ښ>e4ښ>gUOښ>ڼjښ>Oښ>*zښ>2xIښ>9$ ښ>8Cښ>cۚ>6<+ۚ>Fۚ>@6bۚ>H}ۚ>w0ۚ> uۚ>Q7*ۚ>Gbۚ>O#ܚ>VZh"ܚ>>ܚ>Yܚ>lvuܚ> \ܚ>] 6ܚ>aܚ> ܚ>)Oܚ>ݚ>d5ݚ>k;uPݚ>s Clݚ>4ݚ>"D<ݚ>ʢݚ>6ݚ>zVݚ>"ߠޚ>) t,ޚ>hHޚ>ٽ3cޚ>#ޚ>qؚޚ>1ޚ>8%ޚ>އޚ>rߚ>7$ߚ>2?ߚ> [ߚ>F@vߚ>uߚ>󱹭ߚ>Rnߚ>qߚ>Nh>U[1>\6>R>m\n>°>E>cvp> ՛O>*0>>.>j<CJ>re>yC̀>!Eo>ɣ6>.{>Mÿ>t >( *&>/`nA>7B\>nhx>r>-b>¦>>{[>>.U>A8>lOT>7o>L,I>T>IB>><>T\>[k60>b{K> e+0g>V>)>bw߹>i̪#>+>j > a'>3*C>qU^>xz> Fƕ>' >Կ>Ni>ޣH>)>.aT:>6U>= }i>Ӧ>h>r/>D'>/S>1>{#M>8h>Kҍ>Sfҟ>ZA>&>Q>S >z )>aD> ft`>e{>>n%>hPh>o">wwy>֤ >&+9;>ΉdW>r>~=$>&OO>->5Fx>ݤ>7>Xc3>5< #j>jN6>z>0>st>6>J'bn>#+>!hF>9Mb>a}>R >YB[>`5>`U>T > O">=>g]HY> t>B>f4>_<>n#>vx6>}ͳz>%,/5>͊ P>ߞ)l>43n>^#>,ؾ>4G>;a>>Y ,>H>2Uc>Bb] >>>jH>>qB>P}#>X01\Z>v>>9/>_>fo)>L>/#>Z6>f^R>mm>F>gˤ>$n>>uyz>|Y>$-t.>+I>Dne>5ٲ>m>阬>3Ha>:X>A >P%>CUA>ؙ\>Ylw>H>H>kW>>>O~B<>Wր8>^(kS>zo>/>:Vt>>en> MA#>g>i/>UaK>lg>s U[>{^韝>#U>@ >pN>h >$H'>*B>1SB^>9-y><>ী>?5>gz>@/>Q>R):>~U>Z#q>g>N>l>> >uQ>V|1>]) M>d~Nh> >;>>dﻲ>kDP>{ >(>"M5D>ʫ_>r {>z_>#)>)O>qz>> >z;>0W>8.r>?">Mũ>@yz> >>FI͸>m3>N>Q!i>L>Mxa>Td >\>̟>vT>ˋ*> E>cKa>j|>3 >ѳ>ʆ>jE;>q>y!>!NJz=>(޾X> tt>y`5)>m>(">/ig>Ǵ>Ia>qݥ4>[P>7/4l>>T> >7N>>GH>@܌>LB,>2G>R;c>[~>5>Se>[F/>bs> n)>1#>!"?>vZgZ>iՅv>4ё>E> Z><>p0>x >EYN6>'R>m>WD>ެA> >.j/>5>=X5>r->/I>&Cd>{(>Dޛ>8.>>V>A >%>RA@>Sm\>w>-z>\>Zs>a>he>@>"lg8>wS>h+ao>o+>Z>>&4>Β?>wjN>~F/>J>-f>XA>ݭ~>˸>a>>4i5><y >Cj&>ȽsB>'(^>|}my>>J0=g>h>`>9>Z>Q:>YK|TU>`p>;N>]g>G>>gfA>>{;1>oL>:5h>n,f>u.>}֎s>%5(>,Nm>y" >=g(>9D>,d_>3P{>ܮ$˖>>XMT>x >; >Bk8 >c; >V >}#r >ҷ >'L; >Pw >䢥 >:7 >b >2 >XL"N >_i >fJ" >Uvנ > >6 >] >m >!* >pE >$I a >#u| >ts >|4 >, >+ >g >>! >H< >sX >2QZt >93 >A >Y >N > >bG >Hr4 >AP >t2k >ʆ >( >}Ľ >Vܱy >^1F >qs>(,>C1mG>űb>ef~>lL>`> >^pZ>l>s0T#>q[ ?>#MZ>*u>yG>{>-oA>*>1.;>?Z>46>yQ>H.m>8>@m(>GQm>-">Y>c>`->NI>ud>l> T>~, >UW>]2>dG > $>Dױ@>k[>:w>kM+>V>>"V.>ʴ>r֘>yhj7>!S>)*n>0q>Х>$~>>0>77i>?/>(J>?f>跁>?m>FR>f>h>d` >'&>A>Tm]>Ty>!>M>f>\3G>c&>jݺ><9>;U>p>D:ċ>qey>.>!W%s>(> l>xi"1>fL>9g>/rd`>Џ>%$Z>z>S>68 >>M(>E7C>@cG_>z>"A>I>L:>>[4>6y>b.;>drV>Z!(r>bl> w!> >*>5`>i`>p3Y2> N> Si>E>p >w> X˷>'_>.@>`)>JE>`>.s |>5Ȟ>&ʞ>{^>'>/>=I!>D<>K8rX>s>ȅ>J]ʪ>>R>\Hy>ܽ> q4>eO>Ylk>a\>hn>>+G`>ۤ>o>o4+>SG>Zb>&=}>Λ>vEG>}Oڋ>n>->a:#>ܶY>> Y>jyu>4D.>;r>Csm>јl>&->Xf >5 >J9`Q >Cm >Y >K >S >+ >XTWM >!>G-!>fBH!>@d!>`!>go:!>n*!>#V4!>!>. ">n5A$">u'@">[">%>!w">,)f">T">|P">">Y#>3Y#>۷7#> S#>a(Mn#>S#>:#>Bt#>Iɧ@#>'#>$>ے.$>0'4J$>PRe$>}$>C$>'$>$>WU$>^ %>f%&%>^QA%>|]%>x%>f%>mï%>te%>y%>$$&>,P&>t{l9&>{T&>5o&>+Ϫ&>2c&>G&>Y&>N&>2ZzS'>90'> :ML'>bΑg'>bւ'>'>Au@'>HM'>(y:'>}  (>84((>1xC(>a^(>Vrz(>C'(>Ll(> (>L f(>]7)>e_)>lU`:)>YV)>r)>gKS)>˼ߗ)>s M)>z6)>#F)>*$_*>҂@2*>zM*>6J:i*>~*>1 4*>H5*>-*>]r*>Q'+>8)+>?I!E+>GZe`+>|+> _+>l+>\Y+>N +>~,>G!,>)L<,>X,>ܛFs,>\;,>,> ,>M,>F,>dr->kV3->r-O-> j->h->ʽܡ->r->yqE->"p->)%.>0z+.>F.>7~b.>}.>.>7@D.>ߞor.>.>H/>ð"/>>e>/>F[Y/>Mt/>C/>mnY/>/>/>Tv—/>L0>*50> P0>Al0>[c0>jɾ0>E~0>30>x1>M,1>q@rH1> l'd1> `l1>(1>e1>xr1>_1>2>/{?Y$2>6ӝ?2>.R[2>惓v2>L2>6A2>=~F2>2>I>@3>҄3>973>E\)R3>L3n3>3>d}-3>è3>='3>mk3>Z 4>+(.4> J4>e4>3|4>bɜ4>i;4>p4>& 5>N&5>ϣOFA5>w{\5>ax5>':5>. 95>i5>~%5>6>rN-6>5y86>/T6>9o6> 6>8զ6><$6>D6>KAM6>x7>~07>S8K7>g7>R7>e#r7>7> L7>nw7> 8>`"7'8>hwB8>^8>4"Yz8>8>J8>o=v8>v 8>59>OaF9>Τ:9>v!@V9>}Xq9>&99>- u~9>4a 9>ܿ4x9>`-9>sq:>4'2:>;'kM:> i:>se:>/:>3_:>B^:>JBX:>Q ;>R);>TE;>rL`;>{;>X]2F;>];>?;>f;>ı9<>_# <>gxq3<<>nxW<>,1-s<>\<>&<>4k<>u <><>$Gp=>,_3=>/O=>|Y[j=> =>R=>3b=>:CL=>o=>jF>>.*>>:(ZF>>A}a>>I҂9}>>0>>B3>>m>>IC>>P-?>X"?>K=?>Y?>t?>TA?>^lϫ?>?>g,?>W~?>@>fyx5@>mΫP@>t#@l@>k@>k@>5+@>ӊ@>{@>#H_A>+,A>2>GA>PjcA>RA>*A>Y۵A>9A>FA>kB>=#B>i?B>@~9[B>H(~vB>O(‘B>wB>-B>:qB>VgkC>L 7C>'eRC> mC>U^C>{C>d XC>l^;C>fRC>D>p&L.D>źID>s$EeD>zyzD>"إ?D>*-:D>ҋe9D>zD>?%3 E>*P%E>1,AE>8Hyq\E>ত&xE>ۓE>Zd E>8E>?$E>lOF>F>xX8F>u TF>GoF>N)cF>U~KF>"F>;NF>F>v?G>\D/G>ͩKG> afG>M2G>!G>c MG>k_G>ru&G> H>q̐'H>`BH>^H>yz yH>!KH>).ȰH>0t H>H>@wI>_I>:I>7IUI>ߧJkqI>ޯI>QsI>I>>^I>Ed^I>MJ>1J>lLJ>ݖhJ> rۃJ>TJ>EJ>3]J>?J> K>;(K>b}DK> 3`K>Nw{K>,K>\qK>j`&K>qkK>x L> id L>^WL>x{sL>ZXL>(/ L>/RL>6ٮL>7KL>M>E3M>@.NM>=Y?jM>M>R9M>}M>2M>DeM>L,N>S-q*N>mX&FN>̃aN>! }N>vdN>ZN>4N> N>+XO>a=O>hYO>pEKtO>O>O>WO>Ϭ*?O>w VO>~`8P>&4P>.2PP>rkP>~P>&P>{)&P>5TP>Q>?,Q>AGQ>C~Q>S}Q>SµQ>Q>\Q>K>qR>Rӵ#R>nj?R>ĒZR>"dvR>wRR>R>`+R> =XR>ќR>4fS>6S>gKRS>oFQmS>vԈS>S>XέЃS>eS>}a}T>%2.T>-PwIT>4jdT>qT>';&T>|jT>cT>;0dT>㎺ U>N^%U>8@U>X\U>B9 xU>IKQU>QbU>KU>T"U>MEV>V>Xf ?8V>8SV>8oV>oa}V>͌2V>"!wV>fL,V>npV>5 &W>7/W>KW>nGfW>uW>|^W>$PKW>ͮvW> W>|b6 X>'X>,BX>3k^X>:EyX>JX>}uX> X>'8X>AY>Y>99Y>,UY>HpY>HLtY>PۧY>WY>TY>Y>Z>]1Z>^GLZ>s}hZ>pƒZ>śZ>#ǻZ>epZ>m׆Z>t, [>F([>qdD[>>_[>ӓz[>{Ţ[>#QW[>*[>2[>YE\>pK \> ;\>bV\>9ĉr\>@Y΍\>t\>\>(D}\>@o2\>Gw]>:/,3]>pN]>Wi]>Cj]>O]>VBd]>Un]>^]> .^>^W*^>VE^>dQa^> q}^>AK^>$m^>yE^>l,^>s->_>zU!_>"8=_>?X_>Ҕ@2t_>v_>H,_>)+_>1%_>8QTj_>`>4`>c?P`>]k`>?`>u*Ȣ`>ʾ `>SQ`>~~`>Fݩa>N2>,a>UDGa>]m?ؤ?>F?o&?ɰ72?amb??Z`?Ud?Ìȏ?fe?`?za?efb?vih?Dw?8?[uZ?/*?r?>&H?=}?ؤ?lD?%tY?O_J?u?Vj?aŒ?Ы?죮?+t?y):?OҲ?+ϒ?&fe?+UX_?6;Nё?H:?&??+ٱ?VŐ?[;Q?aWI?b+ ?&?VF?0Qc?Cʒ?=gz?^ ?[,?6's?`--?ńē?Y?䨒?8h ?\?2H\?h%?-?ډ??՚?u? Q?؇? ?s12?ܣ?M?B?Za/?[`-?J?Rd?=d%A?5e]?Iط? s? K?.??B?,,?Ɓ?sLh?l.??2-&??y'U?X@W?NC?t&m?@?pA?_b,/?^ ?u[}?c?n2d?M R?6's?:?"?*h?U\?,?-?;Ϗ?f=?g\8?!ͳ?*!? .?*h?dC?n(?~d?t|?h)?cx|֐?m'?$@?J? 6?8(z?gE/?_ ?H8?{Fz??n~h?Б?2]?L?/X?VS?R^?O|?ߤiP4?ĕ?܍O?Q?nO?VRc?b?Ecl?M -?Dϱ(?П?2̐?mT`? c? ;?FVɑ?ԅ?> ?JF?4*p??]?w?8oX?-?p'?M??PS&?h0?v /?M?K?EѨe?9u? '8?t?M?Eh_I?QT?cpp?G?n)? ?+?wr?ٯ#?uoꨏ?t ?PX?L]w?A+?Ԩ?yWؐ?t'39?b]E?y-בُ?Tݎ??(Qj?}ݭї?Bƕ??Mpj?|G 1?Ǟ=?0Xsۙ??iq!?LQԙ?Av?)'?Jk¬?I8?6@aę?c&?%?RӖ? F?: w?#?`Q!h??`LD D?-Θ?"Å?n儿?i?齌r?E™?^&_??pz?EI?jbo?|o-?:H??'x?pZw?(&o?.?/I?o??" MȘ?{q=e?1Z? x?wV^?=N?@m??d?LB3??|X?T$?vp?l{?yޡ͖?`??҃'?g ?p힗?ʜі?ԏ?Lq?j5?Rz?4+I? ?[}uU??^FV#`?P-?~& ?0OBDœ?Y?B{?0e?]?I:?hO?5`i?$L,?}aǕ?vӂ?m]r?1c?"Ĕ?`=[?rq?s݇͑?rw皓?~༓?v^?f?"=?D%dA?Ή=?4HSȕ?R臭?s?t L?6Gh?ͳ?Сǖ?~g ;?C3?Av]?O|k?u? =O?uH J?'lU? ݗ?g?{̇?_jT?GH?~l?؉&}?Y?Aė? ?"?U? $r ?&<?.苘?;G.I?[q?U{K?h՝?@m?9?"mf? E@?]U"?ns?Kó?}|/Q?x?Y:?ʌ^?W?eDF?Λ/?(SJ?_-]?6-g?㳆?G\[?o?! ?]\,V?x?x??r蜟?ϝ?VM?n?*?1K[?`?tgy?eDF?a?Ri?nu?k,am?_ߘܜ?['?u?P\D?VM?;Qi?r>+8?7?k,am?}֞?_W*^?h:;? ?QS'?J?.0?ӑq)?橳?VR?&ZN?f@??ʖ^?(ϼ?Hj9?;Qi?%z?>;?ឝ?a ??l#?nC1?Lm?rj? jX?q6?Qg?Dί?[2}e?[닄?̃?&u?UPQ+?S1i?@Q?gU?qmM_t? ǘ`ݝ?OW? n u?RO$?K8]?OW?E-o?ܖmL?[A.̝?r?}r?[؟?rߊ?6S!?~ ?Gҟ?(CUL?$P?,!L?qџ??aod?[o@?dg?y|?a>N? Z ?*X.?ڷI?`*X[?Xm?ަ??3k'?oo>;?}k̐O?%`?so?9[K?>Rp?m8, ?S{/?eުP?WԻ? W?W?֩=#?Ȳ`"?J kW2?dVA?! iQ?ؼZ`?Jp?C8~?d?b冕?,?q;?T?+?-?dis?'3Vz?1`U,?J ?Y?oU#?(܆.?:??G-hJ?DͮV?bE a?m[o?.x?۴c4?y?:ܳS? ϕR?!?c*3%?N-)?XF4/?I?3?ѡ8?.W;?jA?l,D?ggI?I%dN?4 R?y·U?BDZ?,R_?mc?#HJ_g? 4sk?r?yxӈt?K^w?ΐ|?/?[!Q ?$or?^?,PT??f)ϗ?GW:?%?wNyt?(?iN?rOg8?4F?!ťϳ??jT?$-? mW??D4=?Iz*?`R!?y?U?U3?˔ m-?2H ?I?;ғ??QВ?oNW?jo1?]?Chݫ?^xh?vg0?黶?ׯ?SOf ?"퐬 ?J`? rh?*2f?_{fI?[?4 ?(`"?$?S{l&:&?K>v()?5ҭ2.?/?O-}2?yӋ57?49?Sj;?d(;?WoB? ;B?e$1D?+j0 G?1BJ?~ N?qu[}P?x!S?iU?xhW?B[?;"]? i^?*`?Njf? `3g?xl?s4j?>Eo?n?#t? v?͹z?cJ>z?r:|?#u?@s虃?ٸЄ?͑_??h@ ?D?'QA?؞˒?x?FI?q3]?IV?77M?)鼡?/?զV? A?o Խ?^'?$G:#?(٠?a?U!/??4?mA6ڻ?/HM?~}?2k?~eC?׎=?+bs?bwz?J?}Ӫ?dif?Q? u?N"?7X?'?#:?Ad??PT?ԋp?MM?YVP?SQa?L?O[#q?0U?G{??'G?"8?(]?+g?Li? ?pEO?&2s?͔1?I?r~p?g4?qy ?W?t^? Pj?w?H?Sk? ?JzZ?83U?%?%?k ?t#?f4M38%?Ye0F$?%BO)?E )?)?i+?T-?c{`0? /?uh3?׹i3?a 5?C6?!pn8?7?Lp;?A>?z)??\->?swB?GC?ЙG?_LOG?`PH?I?&ӲK? h}%K?P?)P?nS?:KT?z?'39>?!a@@?.v??9g"A?nk KE?T\ iC?,LC?!G?簱G?1H?4BWG?!F?^c 2]?Vu?e7?{H~? ?#?"QhY?&-{?*s!?_ Pj?7G?ɵ?!Z?9]?"Ɩ?# ?"`?5 ?{N՘?Jc??;;t՗?9(?sqe?ȣ 5?(s=? ~??#BȞ?%?aJ?Z_'P?S??*ҳh?N;?~?w诡?!z?;J?A֮d?Z -?=۪ڤ?joK??K MȽ?bVD?Z{?qޤ?im?]4w?Ρ?Y?QN?Lr?kOO?w?p&?! ??AMG???vd?yFN? "3?d?ӗ?E 2?*?q+?(K?̯GN?,?3+?!^2?d(?V{?J93?fp?? ?[ 4?w5/=?D`z?^?Sg? >?Tg?2x@?kH??4?Y!?Md??Mx?^q'?gR?(J7?,P?q?9́?adnc?$K%?8?Р8?n? n? 1MR?Rw ^?}<$;?CB?Q諚??妼 ? Hf? p`?2)?ƒ(j?XqF?Q??Ll?\?s37:B??{mm?9?b.?M?/U?aT/?m2?FP?QN?IVE?pQ?a?+rq?'??凌?XZ?6o?S3?k ?p.) ?,e|?d&?X?mo$?Gä?? ?s?ߗD?Rh?4?)X??,?'d?7?: ?%q?B?mL?N?CW} ? 5?ъ?u?ǯi?Ä,f?p5W?bę??$?r?lS?d k?'j?l`q8??5p^?J%?vS?g?K1?X9?>G.?X?9?g? ?,B*?˗a9?̶.?[ +?3?m#?K?{?Z᧻?:?5-g?D*f)?Z?#6?q?M?`e~?jh}?^x?M:?}?j?w)0?i#2?"A?%Lr?o0?X??b}? ?DN?q?&S?8\P?mA?sy?`C?ي?)V?"Q* ?gg,?Ҿ^ ?T p0 ?e?-?`1 ?`?*& ?y ?¬]n ?/H?))fs ?XoC ???u ? ?F( ?; ?SW?{Q?׼O?/:?0E^{ ?&?~ת?is?5i t?*?`z??=6?ށK?eп?@j?C 5?UW?+?HD?Lp? ? x?x ?#/?^D?cM K?Mr?5eF?ͥ8?fݚ?0*?/HM? u?PW(?iC?{N?/?U?U?,?2?^???!'?? 7?!?u?m w?]M?p=1?7h>?H ?q]!?C*!?T!?9Zz!?M!?܃kI"?lG' ?')>"?܈t #?AF"?#uL'#?##?{Lx$?j־%?KR%?($?J/ j#?u]S{l&?V*(?_'ei'?]2%?)'?+87?c3?8Չp8?7?7?Tm77?*~7?FL&8?f|7?A=?zV>?b\;?4w>?]S{l&:?tQ>N=?i? IA?UKA?P??NA?b?B?ݻa6\??ٳB?{Z C?}A?w_B?=bA?)+<B?w$)D?V@?q53D?q*QD?kCE?aMD?;BE?|__E?F?DKKF?d\*G?m MC?)E?#EdXE?WgF?"jGG?{q>E? F?RF?6EaE?{p-I?Bc I?-^q'G?)QFG?-@6$I? {I?TFsG?PoFWI?Ѷ.9I?VJ?I?ΝK?nLTJ?euJ?JAL?{sI? K?`0$L?؞K?bwzJ?'LM?L%M?2SZK?% N?Q293L?$bJ$K?+|M?NN?v:N?CO?xBhN?Z9Va?Ӟsb?YvwS^?х,c?M1b?v&'$c?ca?gc?c?y.c?Ċd?ƗNb?JEb?p+c?h8e?T\b?yyd? kYc?HÄ,f?Jy@d?G1e?h8e?kRf?me?c+hZbe?[e?Feg?Mlgf?f!K0f?M֨h?5 h?R5f?jGh? }f?7^j?ki? )bi?mi?^ Pj?d,i?[%k?Ml?yi?ᣴj?~:yl?t k?Όm?̓k?2ʎh?on? `l?OiZYl?4"1l?@vq?߫n?/m?Dn?mm?CYm?m½2o?0Kn?kp?fOsp?Cop?1hsn?-nr?hKgq?$:ps?xup?Sr?Jq?r?]r?ݢ2q?%Xrp? OTr?B&tr?S?g|7?@hҁ?Wm?-4!?ۏʃ?sB?$jf-??!.J?bvy?_?z?x?,s?^5?jJWUԅ?Anu?%?7pb?Pn?+,?ۜ?c&?^^?g†?h@ ? \kF?W??9l?1CJ?F?Q0c?l҉?`1?K_탇?"Q*?*‰?`1?)7؍?qh64??eF?2?}֞?YNB ?7 Z?{鿽?^?rӟ?O|k?X_?.*?=Ԡ?A@?}??W?`{?ѡ?Sr4? n u?ԣ?'Q?wܔ?w롢? ?j%?LKˣ?*7?}zܣ?1"?"o?``AP?x?.%?D:=d?K|?aɰ?(?M?E˦?cl:?E^?|\pS?K-x?J ,?}^?#3rq?(?? K?g?:_Ӧ?Nx?@m`v?,j??3l? P?3tGZ?8賨?җ?Y?jB?۵?a?K?C?9E?՝?1ҋ? ګ?'Bn?lF?wū?䱰?:?K_? +&?ZR?k ƭ?Q*PJ?ϲ8%?Y,?}_c?aV2?u?2t?g4|?*?X?$Sv:?*|? c A? pz?#E R? V?:l? "`?rGIY? "F?ET?P?'t?>??u?r:?y?!u;?r f?͗?O_?|'f?D9?{y2?mO5|?w -?1?ǎ?-?$?7,8?g?:ڟ0?7P?؁?}?A?$Ħ?UX?.=F?%"?FsG?9g?r?R?CE"?Q9?2BN?6 ?h$?F}?ćȟ^?Ke@? f]r?u?NA~6r?_G ?u*r?Ms?۲?;eڣ?js?{*2?'@^Y? í'? W?-Wc?0L?UuE?^w?)ϼv?ͥ? ch?1?9mו?6@Z? 4?6id?M?u?"?{1?E`o? ?MG?n2 ?ȀG?[{?0?OFO?z㭩?({?K|w?fE?Vk/X?6͖D?IC?J_c?-o?S/?aP?ܵ)]?IX?H'p?U? L?[}?4I?Y?G?9??b֋?o6?vs?U<+?ʲq?;7m?|%?kX?8?7?M N?FP?f!K0?pp3&?p ?(Y?)?0?Ҭd?FXT?f,?U??Y"?]kSU?/?\?4?2>')?cO?Iط??N?քS???0V??n[o@?yj?c?Y1\?1mIXe?H("h?<?^*,??8M?xc?>Eiʩ?"?\?SPF?1Vr?a?bQ?';?ݑ?ڱ?l?4v?k?!o^A??Xh/?5,?-?v D`?1e?kJC?A?&az?P\?!asiW?6?`w?ƭ8?LHT?Md?r۾G?CW?a?CM>C?9by?rĵ5?}?K&?zz?P)e?B֮d"?mM?gE/?p0j?|?R@?MY?M?mY.?#u?]d?NSd?n/c?,^R?v%?p(?8ho?aN?q3+?=?j? F%u?qo"?R?}Ԝ?'B?XB?'?Ȓ?&ÖÓ?@.q?BL?Fo?? ?x? ?$b.?OGq?]lM?I]?e9 /?o_~?Zc ?Tȕz?숞? \?{2Z?@?Vx?ĶR?V?WW?Vs>?OS?C #?yU?ʀ!G?.Qb|=?ߦ?ū?ݝ?it3?k t?&s,?`H?щN ???Ƹ?jO9?Pp?xs]?n?aOB?O(2?q?`7!?N~ ?`jY?$Ί ?e ?[?8 S?^U" ?~ˏ ?Z ?2d ?LT ?"uq ?L?4BX ?n:]q ?ݬfB8 ??֬?1 ?0l-?L ?R$ ?{`?}[ ?H)s ?A C?rO?F%л ?cfU:?<5M?E?, `o?W?MX,?$?ߕn\?v,[?范?Nj? Ӝa?CuΪ*?Qb ?WB?l.?)TK?6Jm?9?lp?7X?aq???*w?Qtn$?[?cU)?YT?{L4?Z?aWI?ˆػ?&?m+ 6?Os"f?LQ?u{?R? ?L$?iq!?Kub?&5??X:zW?HP?Q/S?yCЇ??)L???F?z??߲T(?C{d?7?^l?\?9͂?͌~4?ݤX$?S?9?? jX?Y}?.?"a)<?|ԗ?Pl?ˮj?y?>???*PJ?->0??g'?S] ?)[$F?ca?Ϣw*?3ҜV?W?u&#?9U>?)?׏e !?%?b% ?Z ?-!?NJ~?+-#?9B8z!? Tf?0̮ ?f\S ?t?tx)5 ?()?X%I!?y\!?+K ?Ώn!?qV?=I e?ͦm "?0e ?"> ?wT볹 ? ="?l!!?_5!?H$!?)"? O"?٩^#?P.!? [i}?r0@GP!?D#?`1!?)c2 #?|G#?^#?T!?o*Ral!?RV ?A*Ŏ!?VwvCd"?}#g]#?BZc !?H_?Qv0b?8\"?$\#?ΔR"?6v#?VE"?9#?/ز!$?ϡg$?5f"?:$?vS%%?A"?+!?Ds)"?;J"?hwH1@"?B$?}Ȇ"?\#?##$?3)#?l8$?i54?#?Av(T$?_H@#?]V$?2#?f#?##?,#?I +&?Ghp"?.$?|֞#?F;?k#?о"?L"%?"?eG&?c%?$$?d%?q"?Lm$?4ݡ$?-&?w"?43%?d#?|X%?Qf&?T#?Te)#?֫#?9*&?D$?ٹ&?ӪLy&?5$?&?P7'?!;oc#?#?u%?oe%?9 V$?&nv&?¥&?^ %?QI&?۫E#?dxG!$?P}1%?.y$?Ku\%? {$o&?[Ye&?d311'?(:X%?3&?>%? k%?,Y'?~{%?d%?Ø>&?i($?,Ԛ'? %?k@)$?yL$?Ǟ=)?u]S{l&?9f&?_&?M(??޸(?[0'?,ud&?M(?Sx+&?q'SE'?*2f)?-k(?8~(?zz[(?\6:'?5C(?.P&?b^'?DgE(?b^'?Nr.(?՝(?^Q&?t3'?أ&?ͩd(?&?{(?'?-Y&?b '?Cy'?,(?)\\&?Հ'?:Ȑ2'?&?Q'? 'ķ (?((? ,6)?Cs)?d'?TԪ'?Lw&+?̝(?63D_'?.v(?E(? *?U[*?Tߞ(?[G )?U*?BM)?T9)9'?p>(?O+? \(?[ }*?.'?y`S)?⻃ (?: ,? fM)?wՅi)?93Lm)?>5)?,?ؓe-*?q%(?Ey,>*? cU('?/*?y)?2>DY.?o5)?~ +?ͮ{+?-*?p7-?.@8U-?g ;*??,?Ov+?˹",?~B+?&)?.Sx+?(*? /)?7]+?,g*?çv,?+,?1x==[,? N-?p4-?eD +?+?T-.?+_j*?m"*?i,+?b.)?{+?Cr2q+?s(?B,? 6e-? =,?B[,?d_ +?`A,?K_+?΢w*?9ew.?;*?̧d,?P)/?x(+?P-?9Ht-?B-?2h2-?:,?m*A5-? #,?IZ;,?w.?$!,?) |.?LjZ.?Ħ:-?/C-;+? P.?C -?5*k-? Y|/?NI.?wzТ-?nݳ.?j.?6G .?*.?w4i.?2r1?G0?:m/?5Eی.?One.?7d/?ne2?_.?BRU0?'ķ (/?J.?dn/? N-?K-?FC0?Uu=,/?\0?5l/?z0?`2?(0?.hG0?b`3?*& 0?KK1?Tg1?!0?G/?'}*J.?ZsO2?ôo/?J5#/?Yή1?]2׳1?6S\0?3.NV1?P0?KB1?c 1?ؼm1?TR'0?z*L2?jzG2?:5T1?5/?i!1?0?+B1?N [85?\o3?AXF4?ޞ152?ڒUn2?h3?N.|3?(X3??q[1?D4?A')UG3?-[닄6? 43?=bO5?U%5?PIB3?_ӃR4?> c3?GUj6?DP5?h3?J[\3?sa5?a4?=186?J[\3?t32?p\M 4?za!)5?!8)45?5?3?㗰84?A6?\o3?M4?5?]!5?#5?]!5?m+ 6?;gN:6?UlB5?.,KH5?<`4?+g6?5?s34?g4?.,KH5?[dQ5?E K7?^5?=84?"6?E6?&g4?#4?35?6?=s5?$5?M4?%e5?ד t7?/3$8?bUso46?==6?0萊5?y@d6?95?56?36?%K6?M2u5?Cb5?6?uwl8?X=פ6?5?B_4?]9?4?bBo8?)ƞ6?y7?| q7?46?7?~KD7?GG6?$[6?HCϬ6?}Z8?3=6?x>]8?xӈ6?rXj7?C?(iT;?rKPh=?Gn;?*@?^|ve?F&;;?>?Wcd$=?! >?t?$WV?? s@?E!Y>?\i>?k9R>?WmHA?&Z??K(=?L3>?O0A?Bdҕ>?T@? '??}EC?gly@?OI A?z@?.A?Қ0A?ZV@?Q,\@?w]B?,?ܴ>?FHA?B?ZV@?!pe??r.(B?iZY@?]@? ޡr]B?P[~;A?;@?ICYB? `@?pSB?B?=PA?* D?& cC?2B?iA?*PA?0CKC?XA?B?xnB?gldC?C?d;F?%\MC?aW4B?xʴGE?kD?5gE?#E?q*QD?]TAC?mS<.E?rBtC?}eD?}D?n)F?|__E?$fQ3C?rC?4G?/%G?.;1E?jdWZF?ʲUuE?uoE?t}zG?X7E?95NF? m H?Gz.E?.hG?z{F?N!F?ѬfE?TG?IfPH?.IOG?/I F? {I?A*ŎF? H?F?RD?<:d[H? QI?][*J?HIOG?6H?xgI?+TTJ?trJ?>5K?=]H?PjzG?^pI??}*I?/EH??LI?X G?93 H?{jPH?8SJ?|wJ?,qAI?iOI?O L?-I?lQ J?bx6K?B!J?dEh_I?!J?&XI?JH?YI?npJ?kDTK?AI?8KrJ?|'fJ?@ L?bx6K?8xK?=IM?OL?+K?8$-K?"HJ?XGL?^XL?d1K?j L?Y&J?B-eO?GK?PM?`⏢N?#M? K?%WM?:L?˄_M?帮J?AP$NK?)JSN?bM?)1tN?O L?„vM?ftQ>N?b L?H[pN?Fc_N?M?qN?}ӪL?#J{/L?ӳj!O?l~W_N?:m2O?RmN?7$L?dbRK?&L?ʩajK?s1aM?B`L?L?&K?NITN??I&L?fO?O?vN?rEN?gM?%= NN?BP?4RsO?`~M?xU M?6I=UO?6hM?$OP?fZNO?mK?2L?vM?wO?آ`!N?UN?`N?l[M?*ɕO?Du{N?M?[#N?خuN?eުPM?3׳1O?߾P?΢qmM?5yoGM?O?}KO?MqP?7BP?+Q?M?M- N? N?N?.O?NN?~:N?U;M?*1O?^RO?~N?M?R{AO?qO? CO?prdN?kN?eM/O?YQ?Y5Q?e2P?w5/=P?/GlQ?A,^Q?ŐO?t_N? 6P?-P?*mqO?BZO?CM@Q?ZZP?M?ZR?YtO?2/Q?MeQEQ?O?LsR?N?Dj4S?~)MN?}9iP?O?U*P?#)O?ܠQ?$OP?*N?R?o*R? @fP?.*wP?We:3Q?kYcuP?XO? !p$P?&ZM2O?\^oQ?dHP?ǞP?janR?bkQ? S?00[P?_YiR?)K>Q?P?KP?4S8Q?[\R?td@Q?YQ?ܵ|P?8cR?-P?W9R?첩P?kYcuP?=-Q?*(N? tQ?!P?k#O?xQ?#/P?j"}R? Q?IfP?mY5Q?xQ?ętS?4k_Q?̍P?"T?@'R?=^+R?^ZS?i S?3\S?kplP?ցӮS?p0wR?"Q? ;@R?яS?YaP?j}]P? Q?>rkR?ϢR?p94vS?lKS?}nS?)}|/Q?&)R?!P?&*Q?/JP?aS?]T? D`Q? 5R?vb{R?dS?Q{T?W\T?72AQ?́S?#$U?9R?xLCS?KT?8@T?v] Q?cT?6R?X S?C!R?3BS?@D!S?o!T?[S?"T?j tR?ΜpT?Ti0 U?oS?3BS?]_5=Q?(A%S?EИIT?S?U?Q?0:jT?RJT?5S?KT?R?>jQ?E+R?SVS?i<T?)QGU?RR?S?I}R?VHT?sCS? 8S?}RR?GS?)YW?4^S? SS?TU?S?r [R?ÁR?F2S?m|S?FmT?^0S?`(S?jOJR?@S?HɲU?T?cEh_T?2 HVR?1ZGU?\qP?Q?oS?LycS? S?ӖU?iW!'U?ΨT?HXT?hC%dV?''$bV?CaaR?t U?E2U?SC#W?{ۦS?EɚGS?ӖU?)(iT?QKs+U?? U?(A!T?|V?W;sT?W?9́T?KU?t؅U?3I]T?W?!Y:U?No5T?(S?oS?EeT?t U?~U??lT?iJWUT? -)XV?U?QT?&8P;W?TV?OBT?E,T?u=,/T?p X? T?eU?C"#V?ٝV?ŽT?U?{nW?Qm#T?vVT?g#W?ZMPV?xDkT?WW?C &Y? <2Y?Y?+7X?&†W?ۓvY?ƔY?%ZxZ?[d7X?6!Z?W?0'\?Y?#eZ?F \?}[?BnШ W?Z?$Z?z19ZzY?KX?}qJ[? $M\? Y?\_Z?iZ?0Z?-UY?EJY?_>Y1\?澋V\?9g[?\5tX]?u[?{5[?':y\?eqZK\?^}:k\?7$$Z?T|2[?Rd[? Y?A۽\?fz[?8CTY?Y?Q\?j=\?hoZ? JjW?k]?WZ? [?§2[?{S\?ZB>Y?70^[?pG]?Ic[?"l2[?P,\?\?kq\\?elo\?#&]?_tg\?NK[?W\? r\?T]?H\?W[?'6z[?=Z?RgI[?QWZ?z]?m炟]?FsG\?`?]?)J8]?ٛsK[?Ϭ[?kVY[?Z蔑\?G\?:M]?']?sEYd`?҉Z[?8s\?Rd^?s)Sq]?wdQ}^?&\R]?/\?_'P\?.h^?ye~\?d_ \?Ċd]?-|f^?)\?73B`?pc]?K_?"wy_?# pn]?c_?u_?:X0_?C;Y]? a? .`?_P^? ;1 ^?\_?G4&i_?u\?2݆b?WU `?ɣ^?}^L^?3_?c?m>d?*b?b?Qm`?,q.c?Ɋa?Z{c?n8a?Jb?nIc?b?ΨTd?*jd?H_c?2a?>Nb?ݙd?f?~OSe?{ fe?~٭e?[e\'d?=5d?,e?qVg?7 d?3b?(C)ke?ee?f;{e?/ŰRg?HPWe?g?<ˈf?MTf?Pe?RsOkd?_g?f?r(h?fB,c?TYf?SĎkh?B(Qe?nCd?Tbf?hTf?⦫\h?٦nh?Gw;Sh?;*H}g?Tog?8di?Kg?:Tg?ۍXi? \:h?|%j?v3i?jGh?vՅi?Axg?Ki?Tk]gh?Yg?kh?i?Pֹh?Wvf'(j?X ]i?uOpVi?[}h?0֒i?j.j?޷j?nm?:j?8Xj?'h?? j?j?ut\l?l? Wl?_5j?6m?礜Lm? L@5k?tl?g3=l? 翬j?Hl?3k?Rm?!wl?x"m?{eުk?Tl?qέk? :n?v] n?^o?.hm?y Ep?8<~n?:KTo?*[_m?!.l?7Bbqn?I.Zo?`3m?0Nn?vIkp?ɣekn?Eo?61m??o?aC n?wҁQn?^]n?!o?% $p?Fx{r?~,n?=,/TYo?6y%$-p?nn?yQp?Co?1Ղo?a>n?|ҔSq?mfn?IEco?ufn?&o?W.q?o?G1/$q?^jGq?wDf.p?/q?r?PE4p?%>;p?{_q?Xq?3p?[n?tq?o?W+p?gܶo?Ϗu'r?o?Jq?xcp?`s?ys?vX u?6Lu?et?=t?W֑~Vt?횐t?6t?< v?Ngu?E4pv?/P^u?ee`.s?e/t?|5ۍt?p[u?p%t?It?:<&w?LVu?6p0"v?j_u?"It?{ ~'w?A'Ru?"t?9Gxt?@v?iv?ke/s?ghn*w??s?#tQt?^L^v?9bw?|Ft?Mu?4u?6t?t݌?v?J`Au?4Pqw?Lev?&Ոv?Tqs?#X v?J]v?)u?oaxw?c^'u?]lv?042#w?tt?Wt?-!x?iv?ƞ6x?$x?O9v?jv?[pP u?Qx?F0Zu?ٶlw??եu?RKv?R Vw?~-x?DY4x?>Eiʩx?W"w?9bw?Lx?;t?ZXk8v?Fw?E8w?Pkw?KqUw?qx?Fzv?J]v?k%y?MȽx?v?*#t?>Zy?~jt?pBv?ʍ}$v?9bw?Ww?-z?|?Gy?&My?%D{?$z?Py?Py? Kx?uw{?>@{?EAw? ?x?J)x?*Wxx?fs|?SL{?®7{?z?x}z?aHl{?}?j y?!\zz?i,z?z?K=f{?&xz?4v{?pf0{?mz?bsy?body?-wx?=|?؁sFv? qbYz?/m8, |?/hG0z?6g3=|?'y?,z?RGy?aH{?M4z?XDw?8YJz?t..z?F&d1{?7{?iIy?F4Sz?z?٬z?;z?vWz?,fpz?oz? y?g6P{?C6wOy?\/z?Fey? :Hx?Di7x?1)|?=D|?D|?7=|?Ex?N\{?Pw?kX[ y?*x?042#w?g4v?4u?<" w? w?'Hlw?n#w? w?'Qx?Q cw?hx?{' x?bw? m!x?o\ux?ox?"{v?Hx?v?5Eӻx?I)x?0Qsx?¤Sw?Nՠy?tPx?-x?۟0v?tWNw?]ov?ح y?}d w?D״w?! ,u?v? x?Ϟ$x?x?Q1)w?ȂZt?}oxw?y?94w?>6dMv?2zw?FD2v?Yw?!=@w?J= By?v?"\v?4w?sCSv?dv?7At?3Yw?U x?ju?R'kv?;x?]4u?"k v?x8v?"&v?Gѽw?S7 v?iG5w?ܒv?Ojy/v?G?x?iG5w?z'y?lx? -x?B9vx?Qw?5!Rx?3cv?Shw?~-x?WXw?) x?9Qw?EȊ+x?5@v?c w?_|x?Hx?*Fx?\y?@֬w?ERxv?sqXy?`"y?Gx?rSly?*wz?hju(y?ݒ8x?֘.x?3+w?몛x?Lx?k%y?imv?+#v?*{?L/v?7a{?2njy?➝x?hx?I|w?}?iA}?YX }?@,Z%}?!Hy?}?Z:މ~?N}?5T?(`^>~?D6~?eAr|~?P?b~W}?3ٲ|?99~?c?C|?p?{ex?_?9 ?mM~?`p}?|?5?T"?5 ?_r ?q`(}?^Mk ?**?7Ggq?)h?țW~??(yu? 8?j&?0,?#48?t?xdq?Q?K_?Uԁ?c#w~??P?n??#zR?QM?%۷?V8?N?URY?'?˻?8i̓?>Y1\?r(f?KJ?X?zח?s܆?暸 ??q?jEp?lFar? `?jh}?4 ?Xp??+Z?*dp9?R!h?Wy?ό4?9U?c]F?B|?V]?`?[G?W%6?-RV?{X?Qew?R‚?I.?' x?2?H ;?E[:?rHÄ?~\ۀ?H>E?uI?(j'?eQ?/?\ǁ?)?Ù_́?,ԝ?{a?d{0?8i̓? iA'?aM?iQՄ?v?t?ʀ!G?3?3mZ?w?Ai ?-Ѵ?;ךR?>g4?Æ=?$b.?W?'My?bWӄ?8?"i[??''?4?H^7?8ڕL?b-?}(?5K]G?0AC?.X?p?hG/?so?,3?0:ݢ? iA'?@9ew?~?{a?!?r(f?p?c?*u$?z-?+V]?!E?d2f\?=-Q?A"*݂?}w? o{' ?A5q?Ն?/?^5?.ߚ?^2D?Q7S?-G~?e?i$w?VS?bn?q\!?-?N?BDœ8?OU?D?3?e9 /?{Ԅ??fir?jJWUԅ?Oc?-z?!!?gV[V?W?X LJ4?Vx?*yQ?S[ ?p'_?me?sO?{C?Hhp? ? ӭg?9?>7e?/?}(?@,Յ?il? \kF??Po?W ?L?h6?3 ?c LJ??ڄ?)@o?U^?a?A?~?yH粇?uQy?ù?-"և?Z3[?"d&?\Hv[؉?۴c4?q?8}@?o`U?ש? ].?Vg)??g?d>{?~31]?\?%Ċ??O$?ae8?Ĭ?7ៈ?Xl8S?ͨq?э??I#j?C?Nݦ?hjv?.V`?\A?G4?04܉? rc?)T] ?ŚΈ?T'?lRv?ݮ?Oe?^F?m܆?~ˏ?ˆ?%?j0?6S!?ua?C?9?b?ه?~Ӆ?\[?Vx?TgZ?G? !f@?Bѯ?s? ?I?C?fba?f߈?T?J'm?m$?)?̄?ɗ?B/? f4?Ð?7A?\QJ?i2?*?wp"?YVP? #|?rʒ?iΰ?Ur_?g*?j J=??han?7uԇ?j0?,i ?t 34?[L}j?Io?c?ܩʈ??f6~? V?B@?ox?B1hs??n?5"?fM?CN\?i7?B>?8"$?'J?K`?cn? -?eh?6?"`I?{}H?y͆?UI f?gmdh?~xL?==n ?ʏ?;)lj?2?S?r.)??g׽?%qy?H?WEw?+?Y?o?}?mX?Hb?x?Ȝ¥?X?Nݦ??b?=% ?O&$?%?ZU1?ג?ڗ"?*l?m(?L?͆?2C?BD9?5ԁ?y ?1~uY?0=?ܿhE?T6,?4?O?%?[wT?BҧU?B@?%UC?-+? ?~އ?(}I?? rc??@?ost?Ȟ?%?mX?}?2?U,+?v~ȋ?04܉?P?^NdA?|%?mM? u?>G?u?N)? #m>?v-5?S?f!܉?Ë?M^ I?d>{?i$J? ?aY }?aq?c_`?sAX?aSB?@?Jĥt?V?ݹ?sY??+T? !D?[?e?? {? ?"-?E? 蝊?5zˋ?1pq?^U'?z|?"퐬?콝ʌ?om?. ?#d?{`?"D? 2?X??P?ۙS?I:?暸?zԏ?Sn)?F?6i?_,?G ?]n?ӏ?X^Mk?K?KTo?UB?;+?v{Z?vih?p??cL?6ڐ?98Sא?HțWЏ?Α?XV?.?&?Jp?,?EKOˏ?)F$?;t]?pn?c?r8Ne?޻ΐ?Ȣ_J?bЮ? .?yՏ?_?P7?/?!ͳ?J{?bt?J?|=@w?1? |(ђ??8 S?y2Iv?,d?F&;? ?t+ߎ˓?/*?=9T??O黶?#i`?YՑ?mg?zϒ?ۿҤ?ݨ_3 ?~9?N*?2L?c`?ݝkN?rJ?ZtN?/y$?Xm?l?!Z?qh?F}? ?m6Vb?e?Y?ĐA?/ز!?7G?E?/y$?+{?M%M/?1/v?F?Ho?NV?M O?-,b?x?v?UI7? ^ꌔ?HQ§?ːt?V ?^?qvR?Q(?1*B?},R?~͗??ظY? A%??U^?v<?2ԗ?(?NLrh?X?\X7?4DZ?)^Ҙ?O>?.B@?ϫ?g͙? ^?_sa??|T?ad?gM?u!?() ?"և?|Pk??)q?~P??rՆ???[?7=ޚ?Sul?蘘?oۭ?#bQǙ?B?@ǘ?{vIm? C"Ȝ?L^S%?"dT?Q]e?K? ?8.? ?Ւr0?C*a?T^ P? }UӚ?"R.?:? ?tن?䱰?ұϘ?lg? !ʗ?<",?Řj8?]pX?t"f?/ ?p힗?5jt#?Q1)?"dT?-6?Й?Jtd?ә?r'?k=&R?PL?L?'c|?4J?}|/Q?AȘ?qEO?R??y?4?:ܳS?pO? 2&?() ?xρ?ÍJw?^M?K2?/"?K?#jG?Q#>?7C?G )?/HM?t:5;? h]?W u?W\?㳆?P5?W\?q?}nWi?y3Ke?ㆄD?Jt?n-4?V0?cm?O崧?:&?ȯ?Cœ?,RV?M?sڝ? ?a7?T?6Φ#?Sb2?s ?R(?->0?Zta?KX?K3'y?7ӆ?^ ?;?D-p?'NI1?O,?PDu)d?V-?b?5 :?5ׂޛ?Q?xk8?qj?+?:4R?L?"$?c\?#2?h$?V0?(?R?ȣ 5?D?UZ ?}r?ߴ*y??aF?gP#?Le?5_%?`۝?܇?'E&?_2?#]?0?A*?QT?V?2Lb?Y?nI??W?Ƶﶜ?%?=?Ud?gK ?a]&ԝ?閝?jǟ?-"J?f_?= ?x?)ckǞ?5_%?Iɼ?[7Iq?j5&?/,u?<0?x?"?ZflC??f ĝ?@b` ?X1d?W0?ސ?*, ?%+?ErC?xJ?cϞ?7?Hh?H@O?Z}uU?R?Yѝ???֘!?\g?p=1?|?f&?p7-?dӥ?ؤ?S ?NVV!?>s֧?ِ$?Esr?f ?=S?͟??p=1?PZ?~}? &Y\?4k?7e?O_*??fB8 ?b,xv?Kw?qj?Zڝ?Rr?Eiʩ?ۜ?\ ?ǂ?7J*~?VR)?J]? /f?"\_?#F?PDu)d?,?> ?,/o?k1Qi?hQD+? W?r驟?fL?q?k6?9Pb?z#1?? ǘ`ݝ?H[??zТ-?m77M?2>^?_-]?Cαr? ?&v#?[h?fٓ? Kݜ??| ?̄Z?QW-?Xs`? 8:?<g?M?t ?2 ?="8?`[ڞ?{>&?y?bg ??!ʝ?Oq?Ԋ%?tr+)?VY[?$$D?+\M?J?jJk?yג? Lu?Kw?25$?ң?anr?UX?ƕģ?,!L?ͣF?gED? iz?*n ??ZBs?B ?Ž?2 ?e_??sn`{?Z ϟ?DJy?},3[h?x!?I?S?T㥛Ġ?P?Le?mMP?gŸ?j[Ȟ?-O1m?%?6_ۑ?k?t4;?K?碡?OL?:6?TO?)H0?;_?𳀿N?쨠? n u?^ZӠ?`TR'?+,?*'끠?*1t?Tq?%I(}??Y6sHj?m?7T7?v+?iI8>?_N?SrN?pG?e (?3á?4ݡ?ӈ}??m)_e?ZOc1?`G?b%?c݉?e??#ӡ?b? |?W`#ɠ?r?C?cklex?Wc?(Τ? X?@ڷ?(/s?֕e?C ?^a=?9ݞ֣?j?{滥?=@,Z?MP?J㼤?j!ϣ? ?բ?vp ???ǣ?}3֣?U?y4!??.q?N8Q?m?4J?m?{ݩ?!d?S";?KQ?0?n'?_T?ڰ\?Jí̥?tu??L?|WNv?RKS?gߦ?U|LZ?]$ɥ?T?G'G?M8?魦?cuP.2?J6?5]?@x?O-^q?6?a?L:I?T?g? ?X?t矅?KVEɨ?ҿ$?=q?7ʰ@?|\?9"?2?_??7mi?[G ?`ME? «?=Tdͬ? @?Ʋo?OQ?iԩ?I*y?Q?:t? *x?Te?)?x嫉?}Ӫ?h?f|?\?d?B?$L?mBֵ?"lxz??GY??Ҫ?P?T9H?֞X?_ѭ?Քd?*'ȭ?4;I_?jU?7r8Ne?ܝۮ?*'ȭ?`??t?T?O?'`ˬ?z ?$?F Uů?)?*ѫ?fI?-B4?0y?HQ?BMЮ?e%?խ??) |?qs?׭?(h?<ˉ?wӭ?@A?5 ?Bm?\z?F Uů?V?@A? pA?v1t?ӎv7?r鷯?#P?y?d?t< 翬?X)E1?S?R` ? h?TM?TUP?.2?0CЭ?IGڮ??+??JJ?%; !?ڠ@U? =?-{?E1/v?xU!?s߉Y?XtF?W$?`w?s춰?7_ۑ?#+?I*y?(?~p?X?y:ڟ?R ?3?t. ذ?4m=?].;?l?x?Fzv??Ul?L?iʱ?a? dװ?bKz?]3ޱ?vU?ً ?Xǰ?21,5?r@H?3Z?߻rb?.Y?ߖٱ?tֲ?7\?"07?TR'?U(?,?\X?.?l?v4?VG)? "6?ɹ^?ԣ_?L?vv;?V7Ʃ?,Ĵ?'3@?j[%?$?\#??r$г?K]? ?,U?JQʵ?$Qܲ? 8)?d?"I?2gWL?},M?},M?JQʵ?V7(?x?OٟzZ?3ʷ?[?Ζ?P?ak?H?=Uϓ|?N?ʡE?fe?L?*?,?\c??ޡ?mH?خ?\8੶? u1?$д?]!?sm?=bO?$?aR5?E K?FP%?N?KԲ?`6쭷?Vs@?sv?k0õ? |V?#+dSS?f۵?_d?mXf?W? 2L?dT??ap?~ /Z?C2??W+?et?ŵ?خ??s?5r'" ?$?HE?iTd?Zg??6;?? 1Tm?`^۶?3Pt?`` ?I֪?MA?&ow{?%?0?B*a?f_??:f??o?|?yg?F ?9ahV?) ?*?) ?^?!o?<`?gŁX?f}s?;%?n?k?q/z?f6?+|?$s5?x}O?-`]pa?MFĹ?7,?li?6&&?_߸?MFĹ?qs?r37?~?`@?,¸?81$'?OZ?+9h?]Hʷ??aU1?~?5g? [k?_??Bus?0f???mտ?;U?~}?M⮹?=tZ?I`U+?0@B?fQ? u1?V pA?)r?*3?)?%?3^J?{욵?7FW?1lނ?!?k?-@?lr렷?Z?-]?20?`ڵ?~ ?Eƴ?*?9?'?ap?k?Ŗyh?iTd? %vmo?za!)ص?*D? ?f?qGQ ?ᩑ?r*F?Nش?i}`??=bO?oZr&?ơ~?w$$Ҷ?b$ґ?[?fĻ?,?*ѷ?sa? ܮ?C9,h??=? ,%p?$?NPֹ?a ?Nٸ?>m4? ,??Cؾ?m{?l*A?jׄ?:t%?ȴ6?‹m4? B?zf ?m9⪲?g??˵?% N?jg=!??X?狽_?rdP?9D?m)?R?wV^?;̺?3¶?>:u??گ?g|?" ?!S-3?YW?41?jׄ?D D?sl?ŲO?1Jʹ??jzݤ??w??0W?IV4q?X zR&?T-?[:?#?Vj?,ͳ??-W??x?r?y\?7rĵ? ĸѶ?k?2*?}%?a?O&ζ?h|??g@ڶ?' ? 0?=yX?l*A??x]`?[ ?T?%?^afD?,K?X8IǴ?0O? {?R[g?f9 ?V?&hm?sQo?-?FV#`?7k?W$U?o?^')?K ?DM?gnϽ?JxB?!yw?g?Dٽ?ӣX?勬?c_H?~V)?RH?y'7? s?ސ?N?d1V??Uu?a?Vn?o-x?1i?Xe+Կ?ŗ?^? I?𪽾? !o^?\sW?_;?X1?G? !o^?G?O@?éŖԿ?f2g?2#?Lẑ?Dn?Uۨ??q2*?EK?&Z?U?VUyL?H'?"? mJ?M?7a?o7w2?Ov? `?bVD?U|'?Nё\?&?=b?Z{?xe?y-?13}?~ˏ ?[Iw?f?(+?P`?0/?C? ?px0?=.?7F?BȗP?6De?=5b?|?T?=ˈ?tZ?c,?T?̈́p@?0@?ǢD?&??/!0 ?'Q??8+?4?0CK??I˒J?Nm_?ΐ?3?b@?gF?<?o( ?C=ؽp?H G?ƐR?'eR?U(w?(?ư?}e?uO?G?"??r?I>?V?є7?H G?Bb?m?B?}n?ડ?י-?Y?߭C?@f ?[?e~"?O?xe?/?X.?62A?  ?w/R?eik?3 ?Nq?!?<?̵?*TU?Z,?_w?Z}-?r#?Y/?qXu?^ud? y ?>$?%Q>?ʡ?t?l.H?cC?_Ub?MZ??rL=?/OB?_S$?1iO??P6@?l.H?Xr?ư?`?h??Kx?)0?*h?$B?R?n KM?;T;??TA"?LqUw?)w?^*6u?X0;k?'q??"$?G+v? \k?p1?/C?.l?>9?ܘ?}2?:ج?q,!?5]?zc?4yo?j{?˽f?yEq?j5$? ?(O??z{?k]g?e?Cœ?S㥛?d^? -?z?`?`hQ?7~|?Zˮ??x7?9i?S?UvB??RM?U q?G/?RSI?έ?@_?"j? %I?)n?qޤ??q "?7F?@$?%)D?4>8?R?FXT? 7t?aw7?qvk ?4e?oLT?ua???Bފ?be4y??49?vܕw?b?#dT?qq/?0Ջ?&!۞? -?'&?hD??ؾ+?|V?5=((?|ݩ%?#?:gU??n2?[C?Rg?d?R~?qP?(@ ? ?(;?̽v6?2L??q,!??pY*?l:'?䬙?T?;j??|ds?WO?k?$͢?uF^?_g?l#?w 4?MK?+[c+?#3?pOb?#o~%?6?}y\? 4x?mS<.?h??&!۞?`8?R?ljD?iZ?YeK?;d?RNe?&{@?o?b%W?l? %I?8AX?M?+f?/]z?A?|Z? z?p?S? ?=?Q?#ss;?r?I?)^&?c}?0Y? k3?lܬ ?'? 3a? %qV??H¾?*=%?M:?YoB?8?)xer?Lv"w?/?z?+f?@p?6Sd?k?)?-Sm(?V?̩ ? /w?gv?8%?Ɔn?;i?[??eT>?(?Jx?K?rdN? %I?@?A-a?r-?簱?$.[F?צ w?zz?dX?/YS ?d1V@?ry?G#?p8?Cœ? k3?2|?āF?KTT?d\*?_?!?\V? -?H;ɱP?lY.?͉?*5 ?C ?)JSN?c>??dҕ?ӷq0@?q?(G`?gc%Y?;;f?kk??j? GF? ?pR=>?W?5?l?+j0 ?)lP?T?GG?_T&?M5?)dB'?)?n/?nk K?  ?49?[]N ?YR>?#?gRT?@?/L ?;_0?vGj? ?]"?]y?#pB?SςP?Fp?"?p?C?c?3_?d?J?@ C?W?R?2]>?Ϋdx???{"5?iC?8$(?W'`?A"?zz?CBJM?E=? C"?`U+??b4?Kv?i[?ܒf=?ūm? i?82?ޥylp?I:? ?b?L+?jMN?)]? n?QS?MZ??!Ma?vY?X2?e^X?L?|?dSS7?g4|?c5w? жu?O?vb?-Zl? ?4/3?^Y-? _^8?&^TA??t.{?j{?+B?~Γ!}?j^?P75?Fġ?dz?_0?H[?Q/?E?.h? 3? x#?;<ߪ??£?Q?^kJ ?`?"x?nb??N'r? ?o3p??{"5?[1m??cT?NG? {$o?C/?*? Yް?~!=?gc%Y?*?T^?z!x4??W)? ?b4?iQD+?g&5?w(?E#D?=?b?;?_L?K ?eu? M?.H?j1 ?>??eqZ?K[m?("?6?:l?@b ?^?$u?:յQ?1c??cT9?E/r?ذ?C?Y #?K?˗?,?ԕt9?P?tDK?L{91?l?%?xԘs? ?t_?t K?a?)?b ?L&]k?ݼ ?z9Gx?Qn?)]?3E%?+}?!6X8?Ԧ?ϱ?q>e??Op??Ѷ.9?(0S?@zԩ$|o?[?2d?%B~+?.LK?$?5Z?:?{?y)?$n ?@?#eZ?)"?%0?Xȷ?O? wҁ?fBQ?\/?Ўe ?7?YL?e/?辜ٮ?eYI?}߱?4S8?>?q]?9u?Q_?u?Tg? ?︗?r [?*z?dH_?~\??:9?$O?`h?8c?p?U*?ɒ?=3?o?M?j}]?8Gc?ە?>U?A0H?q|HS??=3?; 1M?P? q? /f? (?1Y?(%?)—?nڌ?^-?|K?=pߴ*?'?ï ?gi?pG?:?l.?\{c? (?-h?)jj?ڬ?HcY?u?Ȩ?cM)?5^?`(?? S? _? #s?W?^i?@/?93D?s#v?Oj?Cb?㼤֠?Df?f?C_+?hA?@/?o[t?Ą?>3-?GY?J2?+,?oX?* ?Wj?@/ܹ0?1?χ¤?!F?a3A?Pcd?ixiy?K?UR?c.?Rj??|.L?퇎?Ll ?#?<@As? ?JD?JE?dH?]?L?q?Ć]ʯ? t?uPw?u?o?E?+"? 6?j8v?3Pl? ?ù?Zg?Mr?p?`⏢?U q?;%?Dz)?䃞ͪ?ku?V?v$`? w??Q?+P?ꬻ?C $?ާ?u*?HA%?~.r?Q<~?7 ??tN?Ié ?! i?6??N?\sW?2`$?"j?DÖ?Jb?4?glt? =QȄ?g?܇rX?;` ?3?1>???aܲB? 0F?SE?VnX ?2?e=km?K?>Żm?v1?Rq- ?:0oI?y?!'?ܳS?-4?~$ۯ?f?>?S#?xB??LN?:a?_W/? l%?'?~2k?fZ?Ӹ?"k?;p?}޴??ݾX)??$l.? ,?f?Du{?~?4?*Y?*ME?? qQ?SU??r\?Ы??զJ1?? ?^`V(?=If?Hʸ?KZ ?V[Vz?glt?%`?q?f/?*?u7? ,?G!?Ƨ[?^9?j}]??Y?Q^?X1?9?u؎H?=If?Nu?wS?xfݚ?v$?8 ? $?"$ ??0?^O*??E#?5?wzJs?{ I?I/?r ?;[/?M??Ui'?˖??FM?ܽ7?~?t@<{? Хn?dY0G?5'?Yh9?S i?8y? IJC?bp? ?^?w`?!&?mr?o?LN ?h)?_!se? 6L ? w?1?-h?̇?7/B?מX-?rm?`G \?~]?ֆ/?v?q?{\e?NO?'"?8Ԍ?z'U?JQxz?!P(?mm? mP?-,n?.?J?j?@qG?vV?9 ֓?V?]%?ypw?>f^?D\L?Zs?=4[?,l?|t?ZF=?z?+1?T!?'>?)J?-@j?0O?OJ)}?Q?y3?!9?2t?,3*?*D?.&I?OJ)}?+p ?-!l?z,?躕ʀ?)Y?A9?M?ޝkN?l3_o?8s?Ue? i?z?U?-@j?gRTG?#]?(?RQ?k?_ꌔ?k?3Tv?lR?Ѡ?&?I~į? ?4g?[;?hD(c?2Ro?M?TVD?rA?aR?-B;?A>2g?hu?=]ݱ?[v?OU?Xy?f_?t?U꣝?aMeQ?S"?5Lk?d?lJH?8?76?b('? ?@?'>??2݁?S:?@)?Z6? a?`l\?Ks+?2?Ũ4 ?l ?O>o?l4D?Q?T#?`NP?Zb0?^6Y?+gC?׼?J? '?{?'x?Us{?1 ?Ot?/??_>/?׎?xD?)?kO$#?$?w`?W??\?~2Ƈ??O N?37߈?VIdd?Tw?mZ?`?a?6?{?[u?=W?lbh?>@?wr?mUa?M?6l?$K%??+1J?o?ZV?|آ?.0? a?im?Z=qJ?'? S1? C?T#?qN ?z19Zz?X?Y*?>=e?l ?\ M?:́?`D?=lإ?Ey0s? 3?w?V$?_?ulNo??s?%(Z? ]?$YD?FOl?#v?A?6?~ /?vZm?q6Gi?hu?mR?㮹?\+?4 /-?hI6 @?qh?R?Ũ4 ? Y? &Y?i/a? \?>5b?=^?KB?֐E?<\?Ю?T?!gU?iE,b?o?E7v?[?1dd??,Q? 7 ?azz?|=?pM?<2V??e&? ?Cq?mo?b]F?bg ?@?y?* ?(IL?;x?gxXM|??j? |?n̡(?Q?PU??A>2g?^=1?\C_0n?Cѯ?]p?%w3?KqU?Ue?ؑ4?(k?Dh?_>?yؘ?#PX=?߃?D2?e䇥?yx?mUa? AX?#PX=?6Y??Ԋ%a?a?QUW=?a2v?VZ?h?>p?}b?\,o?z'U?Z,?7?Cb̧??,8r?|??,PA4?'>?i ?sD??8+?C*?[Q?Ti0 ?ꨴ?e䇥?b uA?+ct?GU?R?Gzt?:T??H??Ub??q4G?bzg??Do?Nfr ?e?!JjW?:Nw?Р?y%?T:?dh`?gfk?,)?^?75?CM?-@?K?c??V,?q?S6? ?G?ǂ??e#]?)yu?|~!?0?8V{?O? 1??l?03"?k?A??a?>F/?vݑ?X?$)D?E9?A*??pM?IoN?u?r߉?z]y?48?#.?;ۣ7?Ho?[Z?_+??Sg^?>˘'|?%? G?j?F0?wޜ?<)?b(?0E?d_ ?j<6_?x"?=?@)?6},3?gI.Z??<\?v^?4?u?,BV\?G*B??<۪?٠/?x?<8? 0L?2BN?E)ƞ?ZE?+? a?[w?_"??zx?M? W?K w?[*? ?w>?bQ+L?.?^N??AT+?( 4?^O*?e?]u?~qJ[?U?"1A ?AR:?"*?Mt?KF?5j?^`? ?2%?`S(?[nK?%Eg?Dh?$,?#Y>?>q?6?6o?m?"Ha?, ?[7J?c?%P6?OG?eҕ?0j?wY?0?;%֘?Qs,J?G0Zu?f W?< ? ?K?"!%&?\)?7?* P?Dg>?Y?5H ;?O\?_? x??CV?? 1۴?Ak?eI%?Hڍ>?[,?7ݙ??qTn?Mlg?m?凌?ų?^ؚ?*??k̐?I2?\)?2lނ?%?^<?/ ?B?Nn~?kN?}l7?GC??#K?:O%?"?1^N?J#?kmMQ?q?r5 ?1%?9?8?Ƅ=7??t ??a%0?_Q]?f*i?kR?? d?-?ur+)?C7Jr?_uH?1gl?'ݖ?/?N'4?AA?˭Z?I?U~c,?稣j? \?-3?a?a? `3?NP?]w?[5?6? .?bmVc?b?Dlp?l;?C</O?W=`2?qV??o?E??:ԑ?a=I ?gX1??I{?ڴV?q*?a?•K??0f?JN?6Ҁ?{{?xؓ?k?yB?2, Y? ?頦f?p0?k̐? ~Y5?˭Z}?k̐?Vgz?.1v?8?msq?Ff?g؃?-ב?;?+?f$i?(٠?;gU?^'?-?6?_l?*^?*p?t?iggm?oI?Wޟ?{{?"`?mͱ? 7*?,?+rq?CҰ?rƋ?5)%_?v?C`?i?#g]?`6?K?[?@1d?}t?~٭?E? ?a=I ?xNi?#Y>?N?l?ilTLJ?xPC?vW?XA?稣j?-?yՎ??Md?ƒ?T~N?ː^?7]?^?Z6?DQp?Ǵz?''?+k?fI%?4 ?S66G?Hg`?(?&?ޭ,Y?jdrj?` ?ApS?•K?g?՛?X;?D)X? cm?6`?$?Ty4O?xs?f??]K ?fa?YmY?vC ???5?M?|?n?&UC?%Eg?1qP?)%?U?$/!?6l????b?m?V?fS ?_Q!? ＞? ˽?]w?0g?4~?Rxu3H?a ?ή?#O?On?L_?G-y?R5?E?U?O??S?(;?M,;?N?x?q?`q99?!:>?Bѩ?T?f? ܁:?7Iq?]=?\??D6M?&f?veR;?_O*?C`?H}8?=u?z?J[?I>?p?N>=?S5?u]x?ܪ5?РW? ?ez>?,r?b?"-??p$`S?0?Ѧ?w2??FSw?~ԡ? *?CҰ?L{)s?Ug?oq?1%?k ?]N?]N?w2??)*v? /|?zAܿ?S:X?0j??-?pC?"Ha?R?k%?71m?BÑ?!?&7?g ?YVP?*b"?Qs?؉d?L ?L?ě1?#?|WE?0$q?'ݖ?܌?5M?'c?ǡ~?G^?cZB>?˕?頦?"`? V?+?Ej?tB?vF?i ?t&?n? R?_?M5i ?kh"?8?SEL?vՅ?MY?ou ?01"Q?MQ?/?/D?r(?Q^? ZH?@ƒ(?x?;k?j?ɐc?"Z?'d?Aʛ?Rew??Rew?q?݇rX?j-?Ȇ$?ASe?(?p?vs?- J?Y"pi?jv? Qt?r„Ѭ?(I2a?P?^?f*?n?1AHq?:͂?@jn?8?}W?|{?̷>7?4|??ޟAq?0c?Lpv?-4K?(XQ?^?Dl?Ц?!?M{?5?wJ?+?i?- ? F?.{?.4?'7?t?a?-?Rμ?t&?3DVm?08?.? {T?\E5?üǙ&?5Wr?g&?ԇa?aQ?cy?Ysh?,L?/?p3&?'?c#?yNX? p0?e-O1?Vl0?oUfJ?9a?}Q̋]?N0?V?)9<^?Ʌ?0x?3DVm?Uv ?;?Yni5$?ӧ g?@a?'?PS&?/uFJi?e?+k?n`?QBU?&u ?Ehb?;?\/W?8Sא? /f??\͕??/b鍤?H\?sb?- ?!rh?zR??T?c?0?%T??x? sQ?g^?mL?x"??Ƙ$?>D?O2?3Q?4,F]k?dtS?XZ?w?[k9?W+?!?Z?ǯi?i޽?~?mh?)>>!;?+?T-?u%!?CO?Ʌ?--g?#?wҁQ?غ/?QahU?1mIXe?:A?DZC?2+[d?i?",to?V^?MhXR?&%?g'?*?>l3_?E`?X?j?W+?Cb?w?B?xЃ?&x?y̛?U?5?0?xl?փ?c?zܣ?C@t?&ˤ?]?9Epm?=,/TY?E?5K?+qU?}[T?s>ت?B޼~?f?j_=?/`?8o?Y? 6?v\C_0?W̭?mc?IG?B?H?724CO?n?aҪ?yg)??B޼~?Ue!?6D?>?H("h?LP÷?(?=7?N?5`j?!H?* `?C '?J?DZC?"ͳ??xZ?\?޿? #b?m??nt) ???+C1?b4M? >U*M?TI f?>rk?k ?ې?R?s=v?yB?qt?cI?{?%UM?Xu`?uel?C\?np?h?DZS?iƢ?*`?P o ?k ?O?# =;?\3?EG?<;?|?U,?v4@?©ja?.?c?S?atlN?gu? `?vPwT?zB??l?JEc?'dm? 9X?Q?XQ(?eEҹ?suM?@-U`?e#kh^?Ӷ??6?c?;?o-?lgf?;ݨ?-ic?-ic?V`??'?Q?"?tQo?ݘ??x? Qt?]!?L? Z?u2ݐ?O:7?3u?@"p?A7t??j?J?=٦?@?}G£?r[?G1?-?0?5?W0;?b/o?i"?OVZ?}-? u?kծ ?- ?jB?EGr?}LZ?)ՙ?V?Eٶ?g??gkJC?o@?a(?+?u6?^'e?l???>:,A?G0Zu?ch+?]?Q?2,?;?@??g?o?f$?]L?Jbz?&9 A?? ?ə%?k"]E?m??e@?@#nj?$ר!?)s?I?#@s?1 ,?@Q?.|?b)?:?gw?jy?Fd~?Ec?ŕi?]u?|i? k_?ت? 1T?9 S??ыD?Nگ?ъ?g'?>=s{?hy?֗[? u?-5?{ _x?E?{L?H ?cO?/Fj?^jG?o9/?>Ώ?r?a??W[?2e?>vz?)X?MhXR?VP?H?sǬ(?| 2?wt?h٤?O?@\? ]?അ??W??-)@?)&o?98")3?=?2?_U' ? 5s?um?*k? T?? ?B#3r?U]?'>V?=i%?9E?O[#q?:?W+??n[o@?$?\?UtY?J?2ۺ@?8gDio?N?&j?zBen?\Fi?T m[?4O?s?VU{?d\qqT?XY=?%?l?<-M[?b?/?A?KgWK?&ˤ?m ˟?/?>?:hjv?0?2?P?U|?cS3?T??H?y?M?f}?x7N ?>vz?g?l?6fgh?%?M?,am?P?>?;s?flC ?AV?f r?B(Y?se?!?+?flC ?1?%UM?yVҊ?#0?Z ?o??W̭?;s?!V1K?`6?'?-?`6?p*?늾'{?O`fN? ??͉A?,QX?ZS[?mf>1?h'?1:9C?'?bb?h?9F?q/?eO?-~?0?V?^G?l1. ?%Z?z??yq?AQ?"6?ze?v?VU{?^?Fj?.??@<?)ahu?#N'? f]?YT?G?)kz?+?? ?r~C?H<@?LB?}~?Y;@?0(h?h*?Џ+?4ۈ?vk ??{?1?iE?,c?6?9?}?P? x#?}*?;s?F`o`?!?E\˿?6 ?f$? ?S?>6? 4?&l_p?H ?{Z4S?NA~6?Qe?ZA??y UN? X?U?whh?A_z?1?͢?-n?)ahu? ?)?w"?C=}?oܚ?,ONY?m?.?߻?6? *?&1?|??]ƨƦ?5I?˧})?O?}}c?~#!?*ecos?OeK+?# ?6 z?M?Z?Dͨ?)?*kt?؏^|?*?y?>?L?AC?Zh9?Ь ?O? ,??;T?pj%?<:.?EMO?f r?p[?]?)}?(_u?yl?e!v?D0.?[flC ?wF?#fy?U??GO?o?a?6^p?m/?Xm_?{V??ߎc? 9?~d? <9c?^?l?/s?5>?<]'??)?kZ?5n?:?jrT?qp?&.l?K?]lZ)?ҕc r?C?fʉ?N ^?pq?W~?-?L?;s?N?Jy?H?F}?.$?;f?qmM_??s*#?w[3C?*kt????3?+b?Ϧ?_jO$?#pBF??.A?:=J?~#!?_?y,? }f?/? ʷ?mpX?cF?H?\A.̝?H~?A8? ?S?=?r?lU?wYF?׾^?3eLfa?%?w)?;B?@3iS?0m?~?A?{?U?AL?AҧU?F^ҽ?AHq?1?@2x?s5 ?_ѭ?nW?U/d?_?rLc ?t?ZS[?C? 0jRe?Jy?b?T{߬?";&?:8XI?mXSY?`Y!?qp??:?K/{#?b?kj4?v?s?:e$1?\Ϝ??ߎc?q?YİØ? #s?o^A??ê%?#?Li?\A.̝?cXjb&?.?do?U?_\?kĂt?;":_G?v?W"?Ԩ?]/ӛ???V ?V ?2?-o?V?XD?P?z h?'??QJb?ΰ?-w?9~߿??VX?̀N?{@E?Q?2&0?R `%?6u?ouJQ? ^?gg?tT}?;?{?|?4Qd?z'6? 2?_?p& ?Ӗ??By?]?-$`t?(??f g?L?7P|?2'L6?8YJ?&?aHl?,?[z4Փ?!?dbN+? t}?C]Z??isۄ?g?V(?.}?m?$8??9"*?WJ?ix'?[.?x ?&u]S??!Ӑ?}M"?{n?(,L:%?͹?t..?%k?C6{?VK?Vs?5[?y?YL?_#u?w ?,?zذK?bo?z?%=?J:o??r?',?y+{?z?h9u?N\?A?a ?7a?^?zަ??I?@=lإ?Ƌ!r? >r?/\??aK?-?A{?yO?ze?1Mc??ڱ?BX?\5ܑ?ΐ?qQ?*U?V?s#?>Z?^?byz?9?#$w?x\?[?P?!o?I)?:?}?F?l7 g?z'6?Hg+??DZt?"0?iN>?z?1Vr?isۄ??R#??U' o?O ??a?R8??%7?s?.l?2,51??9>?|:?IyR?>0? P?n,?[.?5?yf?lk?s?B@>?C6?xP?^? ?Ah5 ?(s=??+y?1?rH]?vv??73G?̊Y?&?7?bx?1?+W?P?T ?24??>Z?jG?aY?v D`?[q?κX? e?2Iv?࢓?S*?: ?S?@ۤ? .4?=?Il6?eO2?Ŕ?SPF?1?ZTz\ ?a? ?=2 ?P?dl2?jG?gl?5?r??N;?*?^0?L?=ot?]W??+?ȃ/n?lOe ?g>d? wo?lje?7%j?4R?HZ?L?WS?>? ?4$??(?G'k/? YZ?g?J3W?(h?+p?]?,#?*Vh?LVqLj?;x?N?Ш?[Z ?1?%M.!?>Jۮ?,E?f? ??ݗ3?7Ʃ1??Hq??UR?=F?kk?h?˜?[?Qu?+W?C[,?~7??>$D??fs?A?s?R @?> ??H+?}A?GC?rET?V l)?td4?&D?w! ?uBY?:ݢ?v`7~?C3?+$?JJ?*f? ?"E?.?Qu?8:?PB??x ?%q?JcH?}\*?P%?]?P}@?D}7?He8?XX?\~?@3?37?εt?,"?ZJP?b#?HĖ?`:۠?D?AO?XP?g? e?E0?&-?y?x~~?jWW ?;bF?{?Si?h?0B?WJ?}?-n? D2?WJ?`9?B?z h?VuQ?:ݢ?/?V?oJf?ݜ??*8 ?3]?~@VN?9H?r?1h??hV[V?U?~2kf? ?2i?F4S?-σ?3Y? ?fs!?\X?y19Z?hԆ?JS?3\rV?9y ?Mno?Xh?z??&!od?մi? ez? O?8+&?T?a?V0?*?jDzH?)?X?l(??jѧ?Ax?J? N?I|?8?K?q? 2?C[,?O?>?P%? *?^?b?ï?UU?5?9"*?@?B'X-? ,U[?\Y?f^? v?Nՠ?_=?B?ND~?!r?wM?fm?lz ?˕?n'[n?+2? Q?_=?Ri?䖠?㖠?ٽ?ӧ?9CqǛ?Ul'?byz?qh?͑?p+?CE??*?U>?L>К? ?%r?,^m?Å;?xP?^?=D?-gm?0?3?FH??td4?qQ?vP?d^?m%* ?~ro?e\?3S4?鲘?E9K?&hPB??UVh*?+3?pf0?K? ´???Ш?V%?h@?AZ]$?3?N?_[C?U-?~ro?®7?O"y? jd?- YeK?aa)?gdt?*a\`E?l(?k$?.?*Cfx?_~?Km?^G ?`Y ??)m?kFar?H?V`m1?>@?7N?H#j?Y?T%?P7P?P?̅2|?*?Ho?7 ??wӂ?P~A{?1CJ?$>w?wP?^?>7~?QBy?`6r?]iI?p0j?d%A?A:?Y?f2g?Tw~?h6?/?U?U|'?BQ??&`6?C?Ɋ?yL?a?؋?M?$cW?=?[*?)QF?֍??+A͟?:?J_9?,;?M(D?Zk?lm?a?x2C?d1V?d)?eiL-?J2a?55?wc?F?e?R/S?TJ-?mIXe?̘?z?:Bp?C?d?#A?|,G?F)n?L ?F?̯??_?O?q }?^|?q $ ?Q?h)?L?QV?g?pUj?[A?t//?Uu?g??XE?W;? G?[mD?+?J?j)?;͆F?F"?U?75+6?̮ r??J?j=?C 8? wx?3;?>z?̕A?b?Ϸ?ڍ>?*v?YvQ?\(?[A?ę_?-?a?YR?o? 8xp?<?a?|??,q@?Ϗ?w]?EXQ?/??fd5?(~?E ?nLOX?~J ?^a?)?cFx{?Dg?raI^?qMY?F2?l? YK?B~?J7z?FD?1?@_?ƪ ?TOf ?(bl|?4[I??ff?WmH?4 Y?i?3+%?Ϡ?Q?;Ug$?o7w2?ל(?*-m?R@?_ zo ?̖Q? ? ?iY?N=?dJ&?%v?H1?hRTG?J?h%? ?rxRp?cZ?ټ`&@?*KC?)&9 ?_W4??~?1[*?R.?R:?Ϳ?W??e?u?T|G? ?WO?{og2?+V4?)"?x?E^Ӄ?.?A7׌?r?{,}?(Z&?P?W?d1?l@?&t?,ԝ?X??+9?/k0?f?簱?ƹEr?VHT?H? ? ?Q?U3Y?` ?g?X???δX?g? ?$?MZ:?ZJL??(9q?x?'??|??0?? ?mNI?FXT? "`I?wN@??ŊL?E?A$?'?-?8TBf?ӭg?4g?h4??q,!?'2?UW=?v?KK?m{q?o<?Gey ??#N]?[p?8v*?k?186?_qc?h?+ ƈ?F U? W?6 Ճ8?x+7?s?~d?\~q?G>?+?@$?yY |?pi?kh?M ?b?t?-^?> LJ4?DU?t}z?/?z? ezx?Q?:M?sd?SV?186?l1?,s?7g4? ا?YW?8\P?S?a? ӳ?8\?a?L/v?܅A?e?ӂ}?,}ɇ?"}ҙ?G+v?9?ol?9w?186??#??ʫ?P)?Q?A<?wh?OS{?䢵?Anu?e7?'?A_?,ⅾ?J'z?RA?YD?AN?hb?5?i22?JV?>?K?Au8?|__?2:=?ڗ"?eN?N,?X? 1?X?V=?! ?}e?5 z?kC?Ԭ?A?#\mj?%?"?I?P?6h? V0b?ۂJ?(n2?[?KJ?*t??btp?H԰?zi?qZ{?R?>"?9?D8?/?d<?R!h?z=N?J? !?(n2?L$z?2/)?!W??fL?>"?kk?^Cp\??AE?Ƥ?-y?l7?S??'ΐ?mw?Ӝ?h5?gDio?ϑK?vܕw?V6?ɚG?ﲺ0-?pDRf?V|P?;?,Pz6?&0?TY?Ŧ:? #n?m;m?LqUw?#?}?E?n/?µ$Qy?,s?[?ДB?b?3??S"^?8Lz)?9?ȗP?L!?لj9? ӳ?Q7?}(?QJm?#Ϛ?|W?*.?y|1J?͑_?j{`l?NE?#/?A?#?|h0?lܬ ?w>X?K?q "?ݝ?`?ҩ??>I?*M?*.?5?;Z?f ?zТ-??I3q?R&? жu?h?9?[&|?x[ ?8Lz)?v?CTY?qй6?XM|Z?P?Z}-?%V? E˫?aۢ?ZP?b T?lg?wh?q?RkP?->x??RQ??G?N?U6?ǣ{?a?lH?43????e>{ ?} yP?@I?UQ?E8w?p,<?;I/?a.e?Ӹ?8v*?xADj?wk9?8c?@v?C,d ?8%?V?xf?[s?S"^?=e??5Ƙ?P g?SV?&!۞?Oz:M? ?jMNH?+3?df?}?RSI?n[? ?8Z?>Ӧ?rP?=?3W{3??fnO?ڡ?l,??2*_?)_e#?KW?/n? gG?Ml?YN?&aY?7?1\F?&I?`?tPr?81?e%??5Ƙ?g)o?/#?yk??hr?[[!?$ \? Ϳ?ost?I9Ne?s1-?<K?L?]6?m TZ?w?LQ?+?hI?!E?_K?ٲ|]?8b->? 7hT?e?r?,?/?ʝ>?1t?i22?ahur?F6??؁?`?̎%?h-?)r-?j6E6?FE?+VX?l6?7) ?sI00?;:` ?'O?J'z??R>0?R?iyy?3 ?\zf?+?vP|?&ޝ??& ?yӌ?sTx?aę?M:?aę?C/?? c?Ʃ1|?U? ӭg?ZhB}?wS%%?jI?\[?mU?jft?df?ݹ?^ͦ?Vs>??Kk?p ?m;m?i-U?%?!Y?~{??KFU?)?Mh?&p?YoB?48?/L ?TY?j?b#Z<?m-8(?WEw?Nǭ?U\f"??yͫ:?.<?(#?%"W?|?jdWZ?3 10?6&?n)??! V0?VGt?'%N8?w>Mw?k ?!?B?Cg?Mh?0D\?F?M N???&7j?~هs?;M?AE?WJg?ٸ?f?D K?D_'?FMl?zD;]?,\j)?M?4)?C?.??"`cM?٩j{?WJg?s{???s ?sTx?n[?AE?eM.?^H? 5?W2V?2J@? l?wE? Tk??ވ8?F?5&?* ?ߣz?J65?’?(r?fnO? ?J?KY8?ʱ?H0!?n?fP?cI?Yz#;?{]+?u.?z?2F56?\@?"?,z?EwZm?U~N?J0?F U?#?Pp?C?xV?KŶV?*nE?3?Hr?xQ?> ?C\4?>5?0? Tk?:R=?9.?q?1?V?VA???7Ո?O?k7 ?ކ?HO?u}Հ?I"?5k:L?Y!?❍?uR? `?pDRf?G?ha?)3J<?g?h#?\??;?G4??7r?d?ģC?kk?m-?m?&ݖ?_zu? ?KY8?j?0Zv-?L\}+?jD?b-? ezx?o??$??|wБ??x[ ?BD9?&4?{? :?S+? Q?Uˌm?ho?6?n?C*{?/?Wd?Dh?5h?+f?~?fAr|?-?Y-?ӳ?M#~?M#? N? :??5?q::?E8w?ݝ?sJ@L?}M 6?+VX?Oz:M??'2?=(?h?G}HQ?jft?/L ?GG? ?bmg?(r?df?Ʃ1|?J?e7??`8?`_F ?/]z?gW?}5Q??: ?@,??VX?Ő?2b?! V0?ٛsK?I'u?O?Jn^??m????q]??G3?U?kw?p?zD;]?n1?@ub?ꐛ?k?'>?D_'?l8v?k K?`Jn^?,uW?X?fc]?ut?/o?\?n8? ?yY??gRT?cI? U3?)|Ȁ?P#?Ih&s?<1?a?2l?Q&?a?@ ? k3?JA4?C?t b?g?=8p?/I ? b?,?1y,??ߠbA?O??"~? )6?j|p?w>X?mX?*?e?_#?5?.h?`jY?CL.k? .??uߔ?lɪ??}?0?TFs?"~?-^q'?-+?F?[$?i|p?` c ?Iq?] ?E?Fj???xq?!?B?,/??>U*M?,g~5??I ?cm?7L4?f ?ƳEY ?(Ls=?1?`#?eF ?%?0"?N?:6U? ?.& ?~ ?Ԣ?t+:?Hb? p? ?oWm?v??&p*?’a ?- ?3 s ?֕* ?'<? ?Ȩ?簱?9^&/?=]?1j?}?5^ ?5م0?tZ?=  ?pu ?`+W. ? Z7 ?=٧?ҿ ?H$l ? ?;. ? #m> ?T8T ? ?*gz ?&k ?[8 ?.dž ?Ll ?W< ?VfJo ?q:$ ?K7 ?{ŮH ?,KG ? ?UN ?TKW ?EИ ?  ? ?Q] ?kzPP ? ?)i ?Z ?կt>< ? sq ?c?zi ?8 ?(}I ?xr ?zЈ ?bȠ ?3V ?xR ?2vW ?j?cp ?VnX ?j?cp ? ?q  ?63B ?[ ?3 ?K^ ?/GL ?bP\D ?V ?| ?QZn ?}i ?  ?dv~?=Ei ?=q ?E#D ?M ?m(k ?"(?%C ?E ?( ?>S ?}h ?4=K ? {$o ?gh6 ?bڒ ?:9T ?ժZ_ ?[?e ?t ?\4d< ?oT ?qQj ?0 ?` ??]$ ?n,( ?h; ?m[ ?w( ? ?K` ?/ ?F, ?r? ?(dg ? K ?Nq ?tD\ ?K ?bÉ ? ?b ? ɺ ?Z ? B ? DO ?̩ ?t˳7 ?yhi ?,4 ? ?~+ ?R% ? ? ?L ?we ?g ?M ?) ?-I ?HEz ?> ?)t; ?lf ?;i ?3FX ?C߂ ?T ?K ? / ?l ?2vW ?+$ ?ܼ ?f! ?QJV ?1 ?v5y ?eE ?S ?-X ?r% ?_eH ?h&W ? ?[ ? ?pM ?ng ?): ?-Q ?C ?6]- ?\٪ ?=qf ?;, ?뉮 ?5 ?M J ?@{ ?3B ?!*C ?0p ?h9u ?, Ye ?AJ ? ?q ? #m> ?[06 ?Wc" ?H$l ?S ?J > ?Kcj ?έ?0Vp ? N3^ ?4c= ?yS ? ' ?s ? ?yK(3 ?:$ ?W/uF ? ?܃k ?t.{? "` ?w%n ?Dio ?6< ? ?BH ? ?Uz ?73p ?xb ?euaZ ?$A ?z3j ?'f ?=?yB ?f?[1m ?+!?`V ?Ĭ ?d ?K* ?0oE ?.\ ?YW`# ? ?Dio ?c~ ?SOf ?bP\D ?Z` ?#S ?NG ? ?^NdA ?0|DL ?eF ?.u׃ ?_ ?]Fi?>(? uC ? x ?G4?6 j ? "` ?Nݦ?3?K* ?g* ?E:MI?ͭVc ?-QZ ?14܉??K?~?B5v ?b ?yc5 ?3E% ?ש?i ?gڴ?'?J ?-U ?A-a?ڷ?$E ?80C ?T! ?O?"Uoh%?Yo/E ?MR ?~U?Q(Uy? ?翬?91?i?fu?4ٚ?)y?wu؎?P ?eH_R ?l6!?Yr?(X?-Ԅ?A?zm(?g4|?Q?ƛF ?º?Ӝ?F 2? sq ?}lܬ ?$t ? ?'aK4?&p*?fP=??|k ?Eͳ?u?eF ?1? @?';G. ?{p- ?Ex??cf]??'<?4 ??4RJc?@ub_ ?ȭ ?dr% ? ?lɪ?tV?qEN?xf?IʸN?r?rʒ?ok ?~ˏ ?`< ?jl?|k ?<+J ?ĩ{ ?+?h\W?iO ??{Y?f{? ?|T j ?H\?$?o& x?|[ ?| ?Ҩ ?`?H7 ?Cd ? ?q{}?;M ?Bt?{SG}?[]N ? ?5? ?b ?}:y???(+??Ң> ?NOU?\J?<=n ?9y ?@?Qԙ{?Hb?#ZL ?, ?!)ؐ ?{,G?k ?K ?3Ib ?_c ? m ?{Y?0e;: ?sT$| ?|ȥ; ?f`.g ?p'v ?d+G?ג?uQy?q9^ ?!ח ?k ? `N ?l? " ?G; ?E ?m ??0` ?zߧ ?I2 ?J?HZ ?, ?} ?'t ?`~?͕A ?f ?\1 ?<?e ?֠ ?ND ?vX ?D~G5 ?%N/?pצ w ?F! ?GYS ?M ?I2 ?o ?n3 ?׺? @ ? ?tZ?..?S ?͕A ? K ?$* ?[]N ?|L?g~5? ?ݮ? ?]R ?:'Q ?FͳH ?'- ?z ?f ?_L ?|k ?f׽ ?Q/ ?GZ( ?-c~ ? r ?w<?W ?3w ?q  ? ?6 ?W"P?mѸ& ?A6?u ?Ҩ ?~H ?BWǖ ?q  ?ӏ< ?*ꂰ ?~ ?e| ?Zd?t˳7 ? ? ? B ?{$o& ?W ?K1 ?>?Dվ ?ֻ ?/93 ?U M ?.u׃ ?yK(3 ?lz ?ҥ ?9 ?| ?i0 ?0h ?Y ?iDz?*ߋ ?qN6/ ?r~?CW} ?Dio ?9a" ?/1?"y|1 ?_9 ?M ?V]j ?\K ?  ?98X ?d ?q: ?j ?aq ?qh ?\`Ey ?nC1 ?T ?wP ?ܤji ?mwj ?8Kr ?3l ?5' ? g ?s ? s ?'Nw( ? ?O? ? ?EN ?Ɖ ?{֚ ?º?ft ?wR ? T̜ ?הu ? ?'3 ?$* ?bS. ?=  ? ?0Vp ?K4 ?3y ?FNG ?6jO ?C{ ?k#] ?Z ?f ?kt ? $7 ?WiAa ?A` ?SMi ?"o ?4|k ?z3j ?V ?ӏ< ?E/r ? ?A ? ? T̜ ? ?S`\ ? ?ѫ ?XE ?0 ?LR_ ?/GL ? ?n4 ?OWw, ? ɺ ? I?*ߋ ?A ?0M^ ?cZ@ ?T3 ?H? ? ?Qr=I ?VBw ?E ?ɘq ?}lܬ ?鮑 ?l?Go]i ? ??9e ?3l ?W ?@S= ?ny ? ?c"J ?u ?NT9 ?*ߋ ?'iYR ?#k$ ?ݼ ?R<? ?zچV ?n ?O X?al!A ?o~& ?Qu? ?h??f  ?\](?ڶ%' ?KL ?ުPM ? ?u6 ?, ?ΰIU ?w0b ?IuKM ?Go]i ?;QX ??Ӥt{ ?`aG? ?sL ?)"*?$ ?/xu ?wHl?b ?pcG ?wp" ??Ͷ ?3d ?r ?c?v] ?.T ?*gz ?Ǔ ?/I ?S\ ?-U ?* ? ?9? ž ?C{PC ?5 ? ?` ?;QX ?'D?y? ? ?#E ?sL ?6jO ?._x% ?!dj\ ?-]6 ?׺yO ?i2?I ? S" ?0 ?:Jo ?k?2? ?!iV ? I?Q ?@YB?} +?3E ?]H ?\K ?Qs, ?<$| ?ND ?H\?D?r ?i0 ?oK?< ?HFs ?NG ?Y ?v+. ?6"s ?Ui?$ ?J. ? ?2DQ?}?7k?Ru ?Q" ?%e ?cm ?u?-l ?k@ ? ?AKi ?$哺 ?΃` ? ?ժZ_ ?;` ?Ѷ.9 ?Z-D ?>h ? ?#r ?Ϸ ?+o ?YyV ?R ?! ?*2: ?pĤ ?FNG ?3Tw ?d/ ? ?-= ?}*] ?;i ?, ?uۉ ?$or ? ȋM ?͕A ?M ?h; ?ejl ?, PS ?!WY ?64> ?+$ ?̪cq ?'O ? ?#po# ?nH ?kk ?$ ?i ? ?8A@c ?ٗ ?.& ?w? ?Ep ?zv ?Oh ?Ԧ ?/xu ?hUK: ?G+/ ?#΁ ?H\?x! ?P ?`1 ? { ?T ?m[ ?K%Z ?1 ?n ?9# ?PO ? ?zv ?'kv ? ?͹ ?  ?f ?ʩaj ? ?TX ?.T ?T ?ϛ/ ?v ?S ?hUK: ?'†W ?iO ?J ?9X3 ?Dվ ?Seh ?nx ? ?|ȥ; ?t?Lg ?Sfx ?t ?̩ ?h ?AP$N ?nH ?E ; ?\ ?%e ?O\ ?Z ?+o ?Y*R ?w? ?eH_R ?.x ?%| ?ӗ ?n@ ?B ?n@ ?( ?⋛ ?rVg ?5ӽN ?yhi ?9X3 ? ?) ?Ԁ ?: Ai ?u ?s ?D + ?; ? ?jE2 ?Qf ?v_< ?@ ?vk ?ǣ ?NnP ?3D_' ? ?DKO ?J ?J ?yPq ?Jez ?|AO ?m ?^ ?J ?ٽ ?qkw ?># ?Qf ?VZ0 ?eD ?gI3 ? 9 ?MΚi ?e- ?<, ?s_ ?!> ? ?Kt ?˙ ?gI- ?~ ?/ ?I ?O= ?3އ( ?Ԧ ?U M ?VkL ? r ?d ?D ?g; ?J ?n& ?-/ ?P ?Lk^ ?5z ?Rbv ?}lܬ ?snn ?Dy0s ? ?d ? ?fh ?Ӕ ?ME* ?Hwƭ8 ?qh ??5^I ?8*7Q ?Sf ?c ?e *Q ?_ ?[n ?6w\ ?bJ ?,et ?s ?!\\> ?0 ?M ?hR ?LtL ?_? ?2 ? ?뉮 ?^S% ?  ?3A ?`Aj ?%F ?&WK ?kF ?tDK ?FD ?뵏 ?J({ ?D ?dw ?-/ ?)n ?5 ?s ?ڎ ?cGP ?VZ0 ?Y ?z| ?_=i ?Z| ? ?^U' ?T ?m ?)fn ?7S ?w ?kt ?tv28 ?Ht ?J({ ?ޒ ? ?[w ?pM ??֝8 ?FD1y ?y_ ?BA! ? M ?/' ?B)r ?(K ?8zo ? ?UT{ ?Db'a ?Hֆ/ ?:9T ?0" ?ߛ ?A' ?}8h ?(Qj ?k ?&9 ?>N) ?\bv` ? ?3އ( ?.R( ?pq ? ?.H2 ?[o ?vJ1 ?˙ ?ܩoOF ? k ?JLK ?EN ?b6 ?/}R ?_ ?s ?T] ?fKVE ?; ?#po# ?fc ?i-q ?g H ? ?Z ?ҌE ?0 ?\KmN ?T ?Ϸ ?ުPM ?l ?G ?Ciq ?Z&h8 ?Ma ?3 ?Z y ?QAb ?7uyq ?'iYR ?r ?Q ?ƙ ?>-z ?e: ?k55 ?RHd ?'†W ? ȋM ?kzPP ?’a ?>/&G ? i ?_{v ?h'9 ?tH  ?$ ?_ ?hlTL ?_V ? Tf ?7B ?o~& ?\+? ?` ?qQj ?u ?W` ?:ݣH?* ?P ?* |. ?tv28 ?h3 ?T?gg ?xR ? ?S4 ?~ ?0Nn ?pĤ ? ?z3j ? b?B" ?($ ?Y& ?E7v ? ?V m ? ?'bd ?W ?XU ?($ ?0{~g ?B" ?ɘq ?V ?x ?Uq ?懶?x ?! ?3d ?[ ?ъo ?XU ?J. ?K? u ?%8 ? `N ?{ŮH ?'{y ?7` ?г;G ?Yr?AJ/ ?HrT ?Z ?sO0?$; ?Uq ?E ?AxYQ ?e ?H, ?-l ?i SJ?ê0l ?? ~ ?#8?r ?ox? &?_B?섗?%8 ? ?FͳH ?Qu?:?U{" ? ?Wc?TI ?qEN?TcS} ? µ ? u ? ?W+ ?{U ?b ?XR ?>C ?G\ ?1+ ?yB ? ?ou ? ) ?5&? ?$ ?3w ?̀i ?'A ?kbt ?mq ?<'b ?5^ ?vx ?K} ?eU ?B. ?0s ?{d?lh?_{f ?k#] ?y}Af ?c ?8 ?3y ?U M ?,1 ? ?Ӥt{ ?qh ?KxB? ?+Z ?..?  ?m[ ?jN ?’a ?6 ?4 ?'{y ?80 ?(w ?S ?o ? ?a* ?3( ?#E R ?[ ?͍ ?eif ?q:$ ?F, ?aSB ?KB? ?tMn ?kP ? i& ?a* ? ? ?7uyq ? ?qHX ?g!X ? ?9f ?S} ?i_ ? ?jE2 ?bg ?6]- ?`+W. ?80C ?ou ? O ?H, ?ŀ6 ?)t; ?O ? d] ?پ ? { ?ڻP  ? ?j! ?M ?蘘 ?FW5 ?rFU ?_B`@ ? ?|n ?HK ?f׽ ?GYS ? ( ?hS ? V1 ?l ?d ?_? ?S ?v ? V$ ?z ?nZ:0 ?X ?ay ?k ?<$| ?b ? ?^}t ? ?yY ?NhH ?P ?xM$ ?OYq ?'UH ?Fh ?ٗ ?]R ?nLT ?P_ ?K ?(K ?q>e ?Ggu ?) ?ݔ ?Ϸ ?&K6 ?V]j ?($> ?hx ?2SZ ?~/ϔ ?VqB ?x8v ?zGז ?%eA ?A ?_̖ ?f* ?~\v8 ?k! ? ?4 ? [O ?G ? ?m ?’a ?iv ?Έ ?Pt4 ?wT ?%F ?J%q ? ?%C ?&< ?`4[ ? ?Jĥt ? ?J ? $7 ? G ? \ ?JgW ?U& ?A="K ?F/YS ?2l ?dw ? { ?3 ?8ڕ ?Pr% ?Mz' ?52; ?P{7 ?k/ ? _C ??J6h ?c}^ ? n= ?Zy ?㎒ ?H ?^U' ? ? ?2l ?DA: ?%eA ??I& ? ?7; ?  ?& x5 ?zj ?&B ?6 ?—ӯ ?ނ ?g ?֚ ?肟 ?=q ?5yoG ?fʘ ?Yf1 ?qh ?B " ?@ ?_? ? } ?ܥ ?F* ?R ?ù ?Bdzp ?eD ?3 ?Y\ ?Y. ? ?k\\ ?GV ?W ?@Ŋ ?U|Q ?0v ? Z ?, ?n~h ?gm  ?bx6 ?To ?qyb ?CH ?k] ?oS ?J/ ?K ?{>?Jez ?l3~ ?i# ?غ ?}I't ?jX[ ? ?L%M ?Դ ?m ?* ? +N ?UZ ?w-5 ? ?j^e ?m|m ?MpE; ?1B ?&d ?X- ?(C2?Uc ?yp ? ?XΔ ?O ?X ?xc ?V ?() ?S ?4v ?lMK ?vMHk ?CCw ?Ia ?:(< ?C ?^ ?To ?^w ?S ?a+ ?qy ?N ? ?k. ?'_ ?RӉ_ ? ?S Xu ?QC ?4& ?5/3 ?U@r ?Xg ? ?S ?@ ?<^ ?(H0 ?DÖ ? e ? ?DÖ ?_j: ?g$ ?F ?L%M ?Z_r ?}ՀD ?x  ?CԷ ?P ?78l ?S ?PoF ?L ?1pq ?4 ?r9 ?P! ?.o?eg/ ?N ?՜w ?0:4 ?_ ?$5 ?8{ ?Vp.) ?Wo9?!/ ?|?p ?3Pl ?yrM ?az ?xH ?"5H ?1B ??CX% ?6 ?d< ?B@ ?ڨM? ?c ?@ ?>xH ?l ?C ?(7 ?$%= ?X.e*?ۖ ?js ?% y ? ?N?gm  ?n ? n ?wۅ: ?~֩ ?Ta} ?U2[ ? ?r( ?f ? 4?c?m ?a ?i ?4G_ ?8=ޚ*?́y#?Z?WA t ?\s ?<^ ?{O ? ?K-? U i&? ? /H ?B ?F4˯0?"1A ? ?g֭ ?Ԑ]?( ?$:\?x|, ?͗ ?u0 ?r[C ?'?T^ ? ?z+\ ?z?C? ?jM?- ?[ ?$T8 ?1 ?{ ?4& ?! ?]j)3 ?^@yi ?3?Fഅ ?Q2 ?YLl> ?75J ?mO5| ?-2?o?rg&?=4B?{5Z?xCu?m K ? ,?+>O ?hur?_, ?xBh?%K+ ?ub?)? ?!W?6t ?fC?'%?JH5?T-?\ ?B ?g"A?R:1?`ˆ?E;?L%M ?n ?:(< ?( ? T?-:J?36?i ?{c?iV?#Og ?4Kj ?"և ?@g ?2X ?S ?U&FY ?Đ ?=0V ? ?ON ?Xf,?`[?g ?^ ?Qa ?(ac?Z ?TUh ?Ix ?rp ? /H ?4Kj ?8,8 ?E ; ?@ ?P ?B@ ?xc ?s.) ?C ?ka9 ?C? ?7 g ?r f ?wg ?] ? Z ?g ?#; ?v6G ?Uu ?镲 ?g# ?)n& ?4q ? ?3 ?- ? ?eo) ?Sigima-1.1.1/sigima/data/tests/fabry-perot1.jpg000066400000000000000000001035241514013333200212640ustar00rootroot00000000000000JFIFHH ,http://ns.adobe.com/xap/1.0/ C    $.' ",#(7),01444'9=82<.342  }!1AQa"q2#BR$3br %&'()*456789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz?f(S8 ը$քWS(:Κ>RNOsU^B{E0!>4QFh)iiE(iP5b8Iq}BGsSONGΚg#Q=7Pxu\Q4uOQO7y}i7ZM֍֓qw&z7Z7Qgލ֌њ2}hɣ'֍Ɨwqqw.Fz]֍֗.KӄӄӄħcR,u*7Rxu*7ROK$2/=WxVxWxBiaIIE%QEQFh.}C{ZzR;ը#jH' 3DjEW`j3HiRQFh.iA{ԩ!SSl}Ձ!=LpXu5QERJ< EMhA]U )ITީ.{g|DsIBi)(()hS3S$Ub83ڭmVTX uz ?@{m/FdI3ILњ3I3Fh4f3KE-4fњ\њ3K3K\J$*R*R*Rd0 1P9AUbd"J(J)hZp4i2In9zsVQOPER$x5]"i(( Lv'X":(QOU1EЂ S$)fRI]-M&J)(()h8 pZRH1[ )`*&UzZ_zQ-HM74f4f4fQ3EQFh((4Q3E.h4f4f4f4CSSOzeV_zf_zdz>{ɚVxj⫴x*2)((3KPiԊ*?ZZe_5'QQIEQ$xj2)(ZZPjEj7Wc|1ERҁNUZ,ք*$SMך$4iQEQE-Rp)jT5b8Iq[YXӋ`;y'?Wyޢ2{ SKRn&i3I3Fi3E4((((((Z3K3K3KP Y*UIeަY*PiHhi!@ɊE4JJJ)((PiAOVrU(:HJhjeȦJJ(Z(R+UX4QKJ)Tf(ZWUvd`U9eRIU2isIE%QEQKE--()jEJfEor+z-FҁޫI?Uy}jޢi)酩 &h&i3EQIEQEQEQEQEQEQERER3K3K\u858==^Y*UާI}tY3R+!j5VHjUvJE6J((\҃NS#ոIe["5ZhYE7\aQE-LOQSF5vEhH́Ueި%UwDM0i4RQEQE- x"LE{UmWӋ*cSz$]Y酩fLњJ((((((((()h((Z(4Ӂԫ%L{/XI*uz6iO5jU9!BQM"IE%QEQE.isNVVޮ&j¶iYr*g54x5UM()< HcUyd2UYM()h)TŚ ~1(XUqQL4RQE-JV5XC *dz,M550ni)((ZP)SQ*qfC_ EC$wRU$=ɚޣ-L&4RQEQIEQEQEQEQEQEQEQEQE%QEQEREfKFisFiA 85=ZWJ՘悹^,IaTY"E%%%QEQKE(4jEjȥɑSDȪ3Y& WaL"i(ZLVbLЂ*(JY}ꔏQM&J()h P*EZ5j(rzU`X(MTު<]fM&LIE%QE%QEREQEQEQEQEQEQEQEQEQE%QEQKEQKE4N O R+%XI=IV`٠j'5RXjUWLTL)QEQE-iԊf91WbޮFԽEC,yTdLT )RRRQEr4ɫEҴ#P+*d4i)((ZpOU3V5~* QҕU%I7Uy3ޠgSI4QIERQEQEQEQE-QEQEQEQEQEQIEQEQIKIE-%QEf斗4iEjG'YZTF隩,5JX*Za)))((ZQJ 8E%]Jq4yM֡"i))(a5` ,FY=꫽BM4i(Z)iœ=VD[І cS^@7R_z{ ji4fLIERQEQKEQEQE-QEREQEQ(()((((((4J 8pjZWJj9=ulӺ2*UbXSJJ)((zn)*RdU9"Og*-DE4QIEC*,j@L&i((QN)j@sMuT*,XStBQM4QEQE-iԨj'Wᒮ#dRȪsǑYGUTdS %JW a4J)((=EN Y5 8lL 4JI3Uja4i3IE%QIEQEQEQKEb.pZ]i)vR|_.ˣˣˣˣˣˤԞM'Ha*ic)) SJJb%&)(((()h.iAO R+T%ZOze"2*uUqQL4JJ((p5"O^JTEA2dVl⨺"i)+NW4i)(()*d\ըc5y(LFi}ꌲgUwBL&M&i(J(((ZZ)qK\RN#AH> S4;ɥBʣʣˣʣʤ T*iaia1S Uc"LRbJ)(J(((iԊ:IVޮG'ZF❌DȪSETeU֢"i))((N8ҮdSdUY& VaQi a4IE%QE-)Tj(kBzViR4FY*jja4i)(J(()hZ\RJ8 pZpZxJxXEXjUڥX}EڤӄB#l()vъ1E!bbR`PTRl) t4Q6h&h30QM"%RQE%QEQEQKKPiӔԪb7ZOze["FEA*qTfȘM(Z)iAW!_LJsQșqgȸ5)*v54h(SUjIЂъ=́U&5BY=꛽BQM&4QIEQERERK\R pJcV*aVjaVbvӱE&7Rnu&7RowRu.3KE&(MM)Quh6Z*TeiiSH"RQIEQEQEQKKPiTb9*Rެ+qJFEV< )]0a(Z)E8ZFz:Uڥ<hT*)()hNSRUB=6E#EgGYҮ* am%QERp:.j1d҂, >QPK&3T&=ꔏ֫f&M6J((Z(QK\S*UHt$>2RO )sIޚ^d=Ozaޚe}jQUL̞EqRKJ)T*)i}WR54IE%QERE--(< V*QsWbbNDUfj"iJ(Z(SHAVbZ VIҧ ێNWR=UvXd IIJJ)(((((((((((()h҃N HVѪoӚՔjtV:HYB˜iQIERE J֍8"aT.Sdμ4IIIEQKKJ)*Eb%洭ӥiF0j#sUd %%RQERKE8RxTrZ cUz+֪H]cL&M!%%RQEQEQEQEQEQEQEQIEQEQEQEREQKER҃Nx5"F*mW#na[Z֩ʕBT-@¢"iQE%QE)jmW~Ej@*9Zu5pk>AP5Fi(SEeTdY#L4IIE%QKEQKN婐ZҴ\ǹ^Mf9Qm%%QE-Nrȭ[uU՝3U75S %%%QE-RҊpAV9TT j"iM%%%RQEQIE-QEQEQEQEQEQEQEQEQEQEQEQEQE-Rp x5*D蚭<:jam%RQKEQE-( [ZӚԈQ0k"rk.QɪQiQERՔEj8ہT51j#L4E%QE-RӅ8T*x]kJU)JU@ƣ&iJ())i)h(((((((((((((ZZQJ)jM^f*9PVtíTq@iJ((R)1kJ٫Z⥓ֲfmQE-[Uqҵ!k:SUFiRQIERE-( x* iB0*A)FCU$ 0JJJ()((()i((((((((J(()hZZZpR)ըڮ*GVM~Je閩H9*#M4JJ)()iiEHb3h["ۊFEg]-c95ML4(kFt8 PN*?4iJ)()iiE8S֥AVnTU53U) WcQL4M)()((((((((ZJ(((J(((Z)iiE(x5*U4*³j8M0M%%QKEQK@ zjZNJ9Zt3XT^5)jCҷ+I>E)Z/5Q))(Z)iE( jdnZ0╏NfY!D !QIE%QIEREQEQEQEQEQERREQE%QEQEQIEQEQKERKE8Rp4jE5b3Vj UJWV|g*i)(()REkZv\ b܎Mg9iQEJ-A1Z! 6)()iE(jx\r+JSdd](檽DiIEQ[EjTj泥QiIE%QKE-)ž*Tq Ѐt#t1Nj0M%%RQERQKEQEQKERQKIKEQEQEQE-%QEQE%QEQE%QERERӅ8S֤ZW"< W5!Uf͜uj-L4JJ)((TV#cȭck*uyW0RRQEoV=J*gJyQiIIERE(OZ*=kFtxSϔ74M4QIERQEREQKEQE%REQEQEQIKE%QEQIEQEQIEQEQE-SZ Tfi)()hZQJ*E5nylxmeݎ7STޢ4Hi)(ڷՇI'JϟgKU4IIEQKESH2Uz֕jЏt3wM4M!J(((Z(((()h(J((((()hZZQNR-Nj#Z5?j5gOYWZiJ((S=jxVթWOܬ?ZJJJ(Ջ:N9YJ)(Z( jtp;~z>IT&T%5Q4M%%%RQEQKEQERREREQEQKEQEQE%QEQE%QEQE%QKEQKE--( pVCV5~Ҵ" Vl>^Qa()h xW";Uk6b7M4i)(ܷ+V.t|jTfi)()hSH:UkJJlFn-T~ Tfi %%%RQE%QE-QEQKIE-QIKEQEQKEQEQE%QEQE%QEQEQE-QE----8SH:U=B*:T2lQiJ)(Z(NkگY}~IL4QEn[ݥgO޳U4IIEQE-*Eӭ]iAگ'Jl*BZS 0RRRQIERQEREQERERREQEQKEQEQEQEQIEQEQIKIERERҊp jdQU+F*:TR6^Q4i()hZ8S֦JQ[6ZuzşRzM6(~")dY5/SU4IIE%QKE*E㫰(;UMPT%UjaJJJJ)(J(Z(((ZJZJZ(((()((J(((Z(ZZZQNR-Lj*jІ ^q޳eUjM6J(()S%^Nգ5w,MRzM6(~"K'CYjTfi)()hRpJQZPvқ%PKUjaCIIIEQE%QKEQERQE-%REQEREQEQE%QEQIEQEQIEQE-RKJ)E8SH2UEhCVJnn+6^Q4i()hZ)ž2U~m: ̻XOPiJJ(-"aK'JϟgUZ4IIE%QE-*EҮCZPvҒJ7z-Tz3L4J((((Z(JZ((Z((((J(()()hZ)iiE8SH2UF:Tt:SUj !()h zEmZvk2cO֩=BiRQEoڵaOg޳U4JJ(Z(*EҭzVQPTz3L4J(((()h()i)h()((J(()((Z)iE-8SH2UUJыXPLxT/ZTfiJ)(J(((ZJ((((J(((()((Z)iiE8SH:UBҴb1Ug=k.sֳU^jM%%QE-QKKJ*EZEm]YcLyQa+bҵ`< UZΚ=DiJ()h)ž*T5j#Z0nRaYU7QaCIE%QE%QKEQERE%-%QEQEQEQEQEQEQIEQEQE%QEQE-)¥Z*]kBҴ"Tҩx59T%5Yi)h)iE(-ܴ*ԧkɬ5Q#M4(h"ݪSٺGM4MRQE-RJ)ž*d1V' ΘU)*TFiJ)(J()h(ZJ)i()h(((((J((((Z()ž*EGJрtӛQ&Hyj#L4JJ)((S=jul9j8Q֪H* 4RQIE%RQEREQEQEQEQEQERQKEQIE-%QEQERQEQERERӅ(jtr!ȫ/JшtJ;qYsZϔW5 S 0J)(Z(NR[r+bx TøQU4JJ(Z(OCV5t()UYZϘU)WaQam%RQEQE-QEQEQEQEQEQEQERQEQEQEQE%QEQE-QKKKJ)E8SJb1W!сzUk2v4M)h)h xR9f:VDXMQsPiRQEn3_nEk@xJ8G5U3L4RQIERE--8SJFy5i@*PJBeaQi)()h((((((((((((()hNR9Я"*z|ֳfnFCP14i)()hZZQOZ1^ܴ^^sXMSsQa)jVnJqֳf4MJ()iE8SH[ҁUTXMRsPaJJ(jx_nEj+ϸk:QUXTFiRQIERE--(R)ը`ndT2*PjUTDS 6)(((((((J((((((()hRӅ8ST*x\kFW8NwYZ+Ug5 am%QEQE-("ъж^Em'pxyyUXD %%%QKEwfJFj2iM%%QE-QE-( jCӵ^En[.\6ߓeyj3M4)(ZZQRP"޴jZ͝z 5 aRQE%QKE)Ԋjtj tU9J9S 4JJ)()(Z(((()((((((((Z)hN*E:r%JщqRU6w[cQM4RQE-QE*DnZȭ]+5!cQm%%QE--(kFHE͝k>QUڢ4IIE%QERҊpPը@ *9 2UV: )i 6JJ)()()h(((J((((((((ZZZQN*E* R!Nq$T'z͝ꔍUD JJ)(Z()iž2 +j>R/5;rjjiIIEQKK@<ַlS7+TgZΘUG mRQERKE(OSOU_^FȥaTJ2U9aQL4MJ((((((((((((Z()ih pR(jIү*K>gO'gJQڡcQL4RQEQE)*cжNEn&Yvk"f1&i))(Z)i hA'hF^TQ:"UgZFE4iJ(J((((((((((Z(p)*eZUS_>uM%gO'&J5UڡcQM4IIEREQE-8SJD5i"\.j+0 a>Iƣ&iRQERpE8Ty5n+N&ȢUȬֳZ£4MJ()h <ZFv:V2g[SCjT%J"T )IIIE%QE%QEQEQEQEQEQIKE%QKEQEQEQKE-NJSոCJ`T*^瓯5+IHM6J((ZQJ)*tvgJYuY$'5 aRQERҊQQ҃OCW`~EjdNtY-SqPL4RQEQKE- 8MLV~z$hE'XDR:*rjBQL"i)))((((((((((()hZ)iE8SR(jiWaD*Ҍ kR_zΚJ#gjFM4JJJ(Z()iE8T*KZv۶LObɬ[&M%%%QE--( pR)Q7"ߧ5#G2Vl֨H]Fi)((p4jU5:5[N~=oR$yJX):,*2)SM%%%%RQE%QE-QEQEQEQEQEQEQEQEQE-RӀ*EZF*QVqq8Vi1޳5FWUvY2iI((pR"-"ZэTb\ɒycQM4QERҊz4Rp45TjDE0RRQE%QEQKKJ (4iUj91ޭ.;&EK5ZHUY#-FVE4LRbJ)(((((((ZZ)E()SjTJ՘qV CQUc)6SvRmFMmm&]mmiv J#*ER>*S,U2ŊRd^lUi'Uozg@{,jaja4i3ILIERQEQERE-R(L"ZGU2isUPɤ6J()iiE8T*)Zp+aDXɒyn\JJ(Z)iӁQRci[ӚЍ lY֨JM)((Z(48pjpj^Y*dެ$=jsՔެ$ޟcEQ4>CQ45CQ*ict'FMle(F]];˥T 4IS| !R:]p) Qyޠyޠi}&/L-L-M&iRQE%QEQEQKE8 p*-Z<֌UEE,k>iTd|vji4IIEQE-HB",Zy?^ki2MTf"E%%%QESOV|5 j 4Y5I i((Z(4f4J 85<5=^Y*dYާItzfAQi@i:azSL4 !iգ 8 ҁY͜T$5Y&M&i)((ZpLoOJڵh E[O5,=j5FM4JJ+FPT推ȕ]FE4h(ZZPiԊ2>*3c֔+iF P,UYҡeL"J((()h)h4f4QK3K3FisFisFh4n4fњ3Fh&h44f4fQ(((()h)jeJYІ QPM0f?^k>I3ޫ3TD &J()h*TZY"- i "Vm^kyrz7ja4Q] ["3TeJ" )SM%QERKJ 8ZGpF9']G )$"P,vJM4RQEQEQEQE-QER(.h44fњ\њ3Fh4ffњ3Fi3ERQ(4QIEQEQEQEQKKN=VD1Ś 8a* *:l %VgM&J()h*EZy"-`+Z$\fn&<{MBƘM4QE 5 js ,uFXꫮ*)()h =[2=\lV#i)汮2zlYM74QE[W޴""ˑU&IUuCIIEQERp4jj)޴ _Pi̡T ,8TJI Ƣ$M6J((iqN'@Z֍*;N>u)<OZj"M0h(Sigima-1.1.1/sigima/data/tests/fabry-perot2.jpg000066400000000000000000001167131514013333200212710ustar00rootroot00000000000000JFIFHH ,http://ns.adobe.com/xap/1.0/ C    $.' ",#(7),01444'9=82<.342  }!1AQa"q2#BR$3br %&'()*456789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz?B֚M.hԊ Z \HjmR?VyOOsRޭFՀH:kJ@i'??Tb{Πi˟ZacIIFi3F}sGKҌӅ8R*Gެdw5:wiOLi#MpZcFfB{Κ\MѓKϭ(ŸSR*F}MJ}MHΞM;$w?ai9:OsQ:ZSP:dSi}i)3Fi3F}sKJ81SS,֬$Մxu2H'魟Z}MBHYextt'W TB;gM4&Ԩ֬G)VΧY :V$jH=MHGsYQNEY:x.p*7zQ@3Rdը Ly1ު/Uy3ޠfSI%QE-(SjU5:CV,`SZcIZZъP"R5*RO )x,4L2 S /0M2L'4IRye7oF7}.<]e/N{҉)Jxޜ$ )OzxHVRh61 IJ 85<=<=H c&jUGFE4JJJ(p4j^I=ISS#.je 8T 4PIj2dRRQE(4jTlդzF\銏(*E\՘]< 껽DO4fD[e"J P< IL-MN O RU2CS,U @)x0L2m7Fe̾-4L2SL nu&Mnu&7QnuwQuwR}8=(zP%8IOSĔ'QLwVy=>j2i)@&TX*MgWyqU_z2i3ILњJ((Z()qEbQ1KLQ1F(&((()sFiAN N OWUeY*Uz5?4fd@Qr)AUz5HiȨ*U]&ja4IE-( zLVKTN%@QOULueT R I1Uޫ=FZM4nh%%QEQKERъ\R PiBl K%/Kt]]]]]]'GIlHRR&nMi1F)1IJ1IEQEQE(4iEj^I*eWCRt9սUozZ ) EU:P2QEԊ2=YUz]r*PUlT2qZXꌩ£"EQJ5f$*0)IUjLRQKKJ=ELV⊮KTO&*T )깩㏚u:-VZQ3eI%(Z(.)@ N N N N Nӄt8ENS^/KQRTyTyTyTUU'Hb1SLT4M1 tҔҔҔii1ILRbJ(J)h4ӁT2IS#*;!\N]Ң"i*JRJG ET:銅FE%%%-ӁtzՔzcUCOF0Mךf=TwQCIIE-8 p2-Z*IdzPm9FjiqSD$UޠfɦM%%QER p"JS$ua":(^2S2ԛ3Fi3FhQEQEREQK3KPiwRKGZiZc%B/B,Za)(\ӁOVU=YGѪPxaҫ:DbjEjSJEA"UI# aZp5"6q=ZFSE0iyUY*Yڢ&M%%JVcJ| 8UjfiTѦM[*|UI$Uja4(ZZP)SU*e$u:GS*bҐS 6z004!jLgޓ4f)hhF(F(F(&(&(3FisJ (jvpjxjxzpzxzxjpj\M+Q2T/@,-00i(4T:=YG٩#*Uj.qRT.xa$yr%VumQJ <n7*ʜFVEOC{Հx:U$U]4iQE-(U&[AH튫#vjP*dZUn*UITDI撒(Z)iS*eJ" NR\Zi=&Q&i3Eb.]iBRKe(F6Rle& Jmm!ZLRbJ(;4҆{ԁAZxJeM"i)()h8p5"JV=XF:x%We2FѪAȦUYcR%WaQMZPijtj"*)5Q8525YF^dg]FM4QEOQS"ոF=Vv*-Z*.)Y*UIYڢ&M74(QN=EJSub8GS*SR&z/L-L-ILњ((ZpZpZpJpJpJP](J](F6Qe)6Rl)MIRR4!QIK3J 85<5<58=Hޤ N NW5%@@QȦM4RQERӁR+Tb7Vujj֫H])枦Fո,uQ֠aL4QKp5*XOVJ"JXR1XSHXn 4iQE(RըDTC#Yc6VbJ`TUi$rVvKS IIEQE-P)SjeJ#)XDJ('~*zgS7Rf4b p8GOӂSRm(Z1K1&)HomHR4040444LRR (4 zzH -!Tl U:Q2dS"IE%QKE8p5"NVczSS5 Uj0hVѪu9#"ʙ2UumQNFQ=]pr*)H5J61jn54QJ)@U֮•mF5VGU5r$ GjUGjFM74QIKE-< VDVR:Rt&z/L-M&4RSSSR(44g7Q3I3K(R`Rm+L)M)L)L)L)L+M+IJ3FiӃSS@ jxjp41t:PDSHM( JS#ըެ5U]q9MLV`sLuȪGTLUvQE(OSV#jմlӘdUiVSVcji)œLW!JTqUzQ@*.jIVT`S]*u5FƚM4QEQKE.)SjtJuj8®;1 =BQ3esIE.)@*@"O R7RnIޓwIowR@j\њ1F)S b3N O O R+T j~iM0j'JwJ"E0JJ)(ZZPj@jTjVcz㊭"Uf*Ejެ+fTR.EQ:7^jIIE JVnjoVTr.ESpj.QshZp"U蓊TR=UT3VbJVl ,jUݪ"iRRQIKE< WJ긥$ c=@PLi3IKJ8-<-HRT<%?m.)h&Bԅ woGIKoK}(zpz]ԻCR)VWc%FR)L+L";њPi@"HR+THD隯"UwJaL"i(SԨf7QXVڢuRUjM+ 2U S¢"i(MOsW"zf"ʵU *V 8STj)ҮPVGsQӔT5r4 GSꫵBL&IIEQE-(OU*qդQ3. =DL&M%S*UX@ғ4/M/L/M/M/M/M/H^}!zMo}}wѿޗ}.pzvPԠ1M+M+QTe*6J4mfjZV@i3Q:T%Vtj&IIE%QKJ <MLVzSȥ#"ȵUJrRcER*P0ȤQOFQ=]9T\ujŢ)E8Tj$^p*s$zP@*-[*Ҍ dT~QڡfɦIJ()iE8 zVDQVJ)Kbwoz0i4QNTU*e O N&i7S K KKKwIu&7Qnu.7҇NJޜvii1HV+Ld*&ZaZiNVP")ԄTNYҫ:T  aIIE%R)oVzL 1jUb)a)<*T%J"cLWɧKJ*E5U檸6)E< [MV:=jh]*cUm=[jڌ lTzPɦ撒(JjIW#ZDU5Dƚi)žU*¯(TL @Q3Ljaja4sILQE%RRQEQEQEQEQKEQK)sFiisJ 8pjxjzHR*LRKM"ejZe/zp5"LS#TҚ֪ȕRE*&M4RQKE(RnjOW#jr*9Ƚj LVj:TREgNIBE0RQJ)¤SV"j tr+"jKWZ8U$j*h֮ĵ1Uy^YBM4m%QE-(R(jIW"Z)VvX *XD0wz-L&M74f4RQEQEQEQEQEQEQKER)sFi٥p4j@"JS+*<wZk ֠uj2)ӁdjZA"UIR:,*2)RQE--(՘i8SqeHFi2*Y WaQm%Zk*j+WZ !ɪy*KW`PNFj2iQE-( " W"Nm8ګ;T 4Zp*NVQj`1JO5Bϊޠf2i 744RQIEQEQEQEQEQEQEfKFh4f4 8x4"LS+T2<TN]֡aQJPj@jdjSNLqUdZ"g ShQOSS*-WcjC*TZSSn3Su^egL7RQK@Rp"!n-OBu5VCUELDcdj+UW5 4M4QEN"5ĕr5v]&)T*t\Մ^jŠjvDQL&M&i3IIEQEQEQEQEQEQEQEQEQKE(p4iԊ"LST2<1@Uj&Jp5*#Tj5RU-@£"i %%RPj@jd5j&5YSH"JQ 4TjmVLqYZ JJ)i¤SV"jЁV*Y* TiTUF0)p*TjƢ&i)(ZQN*Tf5%ZQy;T iRzVQqRt3T.WfY2i ILf4QIEQEQEQEQEQEQIE-QEQK(4(4iӃT*LS#T*4qQ: m(Uuoz[ޤMq"98XS 0QIKEiԪjmW"jp*CҪʽj=iy15[COnERk:U*3MSzr)qUj棩U(HJVnj54IEQKNR(n%MT25Vm*UaRDUݪjcLcL&M&i3IIE%QEQEQEQEQEQIE-%QEQEQKFiisKKPiT25XFժ@i WuTdRSѪtjM)dZ*WZ£4IIE%-)jt5n&7JEE R5\OsVjUy͙y5MDi)E< \bBqF#! 1ȫ*~FVj4iQE--8ST*k]jҌ U4S=EXjkVbTn]ګT i4i((((((()i((Z)is@4iAOVQ5LSTT]֡aM4ԪjtjMIXUYVHUD£4IE%- Jz&hxETjiT5n&KȦʼVt֨H*JJ)E8TjMG½*T24b!Wc8NVRƣ&i)(ZQO"\zUؗ7JڪYFM6SU֬iVv54iI&i((((((((J)h(KE.h(4ӁR)Uej#TQ:wZ"J*E52NSJjRjFiJZ)E8MXMWcD8*#IJ H!(jQMaUZ*W S 4))hOSS!_#UFQ@iVjFnFu⳥U3MSCcWg4"jB UBƘiQE-( jtn% ɺV|Uh@zU7=.nU#M4Rڒ?ZhR֮SZSTeQaZZpNnXPT֣4SJ[NҠU$PDii)))()hZ(Z)iiihZ(J))(J)(((SH*Vc5n3VUI*TfpS!QU)ҪMިKUjM%%-RӅHf#_RKҳjSEMڮ SYSuQm%%V~֦]=*FZJJ( zVtTUI*TfrVIҞzTU9* Qam%RQERE-RKE---RKEQERRRRRRRQIE%%RQEQEQKKKKN֥Z*un:IUۭDi)Nj*UfzGZ4IE%-R-XڴD+:~QjX5~x}ڥs޲jTfi(*u4}j]*cҪҨU4IIE)S\ES$rUvQN^2UU5*Y0M6J)()h)hZZZQKKE--QKE%RRRRRRRQIIE%RQEQEQKKKJ)ž*VcqՕJj*Y#INZ:ոt7J5PBJJ(R-XڴK'JΟSnR֯;7ZJ)EmIU*hتcҪTeQiZZpNr*J%rUvQN^ҪҳoPFiZ)i¤Z_iE҉zV|jSGZ>~ߵ^vTjTFi(*u4}j]*cҪTeQaZQNj]*~NJ9jdqUO<trUgP5FM4)()h)hZQE------RKE%RR))) %%RQIE%QEQES~D+:~7ZmKZoگT{TjFi(*>v.1Uf0RQE(OZ*5~.?jJ%Vje婒EVӥ<UI* Qam%RQERE-RKE-(ZZ)h(JJJJ)))(J(()iiE( xVJ\-8J%Wj p['Jstϖ=BJ))hR-XڴD+:c֪54TNLǚm%UzhWaJ-Q=Di)iiž2U_V;T2U9*Tf*USA%T=Wj 4i(((Z)ihRKFhJ(%%%RRQIE%QEQERҊpJ:UuazPƠI֫5Fi)§Vӥ+tV|UzIE%-R-Xh[( IzVlu,}kBߵ]rk*nU#M4RܕY郭KZOګҨUZ4IIEZ*FҬdUf%8TVqjrW4M(()ihZ)h(RRRQIIE%%QIEQEQKE-(O*VVֆUI VcL4qUJ*ƨJj-L4JJ)h j}kBߵiGҙ7J͘UZTօj5B\jTFE%(**X5vV;UyzU jFi)(pLj#W5htTQJpRDjfQITU^ji %%%QEQE-QKKE--RK(J(%%JJ)(((ZQNOZ*un>n:R5VI WjeS֪DMu8TV"~եJcfy5Y4]kFߵ\?vOZ˗Vji(*u"u:T iZ)ž*TQj&*=Di)¤CYǪ 'ZiCIIE%QEQKERKE--RE-f)(JJ)()(()hN"Ԫ*}jc[MsUd5RC@J)SW"izSd,fDjj(2m%RҊpP՘^r)[UUG Rz3V5iҠUIUqPiIEQE-QEQE-RFihE-4QFh)()(((QJ)œ)QSQn1VV*Hjj"i)EHf!Wb`T2ϙ10JJ)h p9 qҴ͘UOZKV\ZʘUXfE%-(A Qwq*9BaUT&iRQKE8SH[^TWUIWaLS!1[RUIUqP0Tfi(Z()hZ(Z((QE%QIERQERQKEQKKE8S8T*Ub1V*b"j-VJQ4MZ)E8Tjt5n&5X*Tjj3M"jxZʚqPH*Uj aM4RQEQKEQEREQEQE-%QEQE%QEQEQERN)*U: ո֬(*HYBM6OQS*KWR՟+f 4hp EYsZVҴPNج[XTkFzUk>.VV5RQKJ)an*jAU$=jF!AQU7S 4RQE-(NCVj U9UYVM6CVcjKlUiȵ]B˜E0i %%%QE%QEQEQEQEQEQEQEQEQE%-QERQJ)žHAV#ZդZqMfVUdREYUȗVG*TdjƢcL4IE2 VV TgjϐQb!iێM!]g5!iIE-(jzU9STy5v3H"̵JAUڢ4IIES8TjmWajqRUZ *3INSV#jU4T-Uj@£"E0JmQEQEQEQKIERRRQEQEQE%QE-QE-N*Uj5QYQN@껽WwY2iJ)Tb4qN)VY*u檻T,4i))()iEP2TLµZiZibRQ(()hbRJ8 pZxZxZRXTDUj@1NL-JޡfɦR*ՈҬƝ*®)⠒J,RGɪ4ifJ)hNAVLЂ>y2WY>MTfSD"`Lb9ڵs/^k2Wɪj2iJ)E8S֧sZ6XԪ2qY6McQKNFثп\CI"ʵY4ޔjlr*TZ£"iRQE =MLVcE'm=dT.Ε]֡"E6p5*L{%NR-4DT-BMDRVVVLRbb(bRRR P)BӂӂӂT*JJRcfgz%@QMSjtJt(GSJ#vj0i4J)(STj1֔)R`U)26jH*TGZ6y0:TdZ0m%H¹5kJjuˉ9Ly)iARsVzu"JREѶ*OVFeJ*UG\T,*2)(PiԊةrUȤ*PUiEiRQ\ӁԪa$J_x9D-DM00044!ZM&(&(bQ\Q\QP(.pZPJRXUTib4FP< ?BQIJp*EZ"U\ ~qPU$;TL4iRQEQJ)žLVNEh]QT>;|ƛNQVbL֌)h+6Wɪj2iZQOQSƵ~9 \waz\PIE-8S5v*RUU`)jOҮ# 2U¢"iRQEf (4jEjG'Je[43PUgL)))sNRԫ%NT NiM(*&h61f:aJiJiZiZMi6mh.1F)vѶm(ZPH#:R RK-c=DT-'BQ3eQJ8-HSUҧU?8LUI%IUja4i Z)E(R_:Љ0)d| 4I=, &@*Ue&MSvcQIIE-(* ֥}*;RdTLi( JVb~ V:Er.*)JVzLr*r-WaQM4J(Z3Nx5"NVcG'JR3PUwJQMiAԫ'52S,*HRbRRh3Fc:iJiJnM)6mmhF6m.vPMW&SU&aL tuۉ}>Gɪj2iJ)iE< n"L <3j9( %%]JdRȪUuT ]QPJFT m%%QE--(4iԊ:=YOz9*c"tWdj2)QKP"JT%L{ԡsF)i):acc:oILt](GF6RDt:pGOӄtQ5L,kYFE% J^J"jPMbWc|{ ,uFDUj")IIEQKKJ 8p5"NVcޭG-YGOlTWdY*2)(pjxjzJ{ԫ-J{ԂAR("SJfR]4Hc<<< t]]8GJ#ӄt)i)2)0FTm%D{e2i3IKP)Sʕ:GV: PN*'RIj{v|L4i)h)Tb4%\ACɁT嗯5Q54E\laEA4k:i2O5MڡcL&IEJV$Vxejtg<&94ږ5ɭxU`Y2hjU\b"i)( 8Z=j2U9"H])5n)=ҶE#ES:"bdSQIEQKE.iAN OVeާI}MSS.F-Dc*2Ҵ)1I((44fn.i3Fh&hQE-.)BTJJ< RcH*]J-L-M&4)()iE(NU*qդLSTzNrj1I֨M.sT|]M4mRӀ1&MhEҴPmZ<k:GɨsNQVLZ1ժ2uɭ3UJ"⫰0QE.iAR`ըIT2%T0j1L)|UȤ*r)rU9)RQERK\҃NR,2IVoz{&j@—TmBTf:QILRbQ((((RRS҅EXET0*&ޠy}ޠi*zFZM4Lf4f(u(*EZG[j AVL֩M/RLvji4QKNLW`$V |VldF942kF*ijU̹=k>Fl)ȤuʕQ֡aL4J(8z%^@jR2*GJRSS&*RUr)NX"E4QIEQE- 8pj^Y*eާItާYHi\ uEQ30L)M)M+Im&(&(bQ1F(iv҅ N OӄtH"u  pQSKD--@ -DTE酩f4RQERҊP)T:%Z*x/T2>*UfldSjiWbLT*dzQL&)iE8 D"⫙ڵJZQyVךʕjּoS"UWZiPiԊݧғ`уIF 4QG4sEEsK/4sG4sKQFM4d4dd'4Q'4sG4sIsG4`QF . 4>JPҜTHCS$$n5j;v)J j}곳Ƣ9=&ކX5b8 q)qQT>JG'֫L9據NhҌRSJPU'[)ptTjd)=J#W`c'2pd`\I5Uɨi44 Sigima-1.1.1/sigima/data/tests/flower.npy000066400000000000000000010002001514013333200202610ustar00rootroot00000000000000NUMPYv{'descr': '|u1', 'fortran_order': False, 'shape': (512, 512), } LJKIILOSV\ckulmnnliieeb`_]\ZVUVVWVUVUUVVUWWXXWXZahls~{rpprrnljijhgedbbdihkorvzuwxvwpolkid\RF/!!! !"##%%&''''(((***))))('&%%%%%%%%%%%%%%%$%$%$$%%&&&&&'''')*+-./11224444566548J]uoVXUW\gmige_YZXZXWXXXUWXYYXUVWYXXUWWTTRLQaswwoh`\dqpb]acde`[Z[]_lxyjY]\^[YUSGFJEEHA=@<:9>Nn|iOIPRTTVTPRQOIJGC==;9::<<7567645988BQrgTVPUVUVVWXYWXXXXTRUTUUVWUVSROQTWTQNMMOJB>@??A@@BA>====;;=:@V[]an}~{rQLOUUX[\YXYXY\[XW\[USUVPT``QMPNMLLNMPQVYTQPRQRRSRPNHGGEEBCBDFEDJLKKKJIIIJJKLJHGGGGFDEDCBDOQJB@BOKKIKMPSV]eowjnnnljgdcb^]\YVWVVUVSUTTUTUWWWXXW[\cjqywprrqrolijihgcdcddghglpr{|vsuwxwrolkg`YO@#"#" ! !""#$%&&'''(((****)*)('&%%%%%%%%$%$%%%$%%%$%$%%%&&&&''&(*,,-./01334545677873@S_sgXUTSW_egee`YVXYWXXYVUVXZXVVWXXXUWXWUTRNN^wzusncnxpe\^bce]YZ[Z[is}s_____\WWLHGEIKCAB?:<9@]yXNPVVTTQPORPJIGC@?<;:89:7665445887@Tv[VUSUSWXVVWXWYXUSTSUUVUWUV[SQQPQQQMLIJKG>;?A?@ABA@=<==<;;99MSetoz{yXIPVWVY[\ZWWX^\Z\YYXTSTRPS]RNONNKJKLKLOPPSRSSSSSTSPIIHHGFEDEGFFIOOLKKIHIIJKJHIHGGGFFFEBBB@GIB??CNKHILNNSV\epwjnnmlifd`_]ZYVVVWVUUTUTTTTUVX[YXY\agmt~urttsqplhjhgfgddeffdimnqxxsstwywrmlje]UL6!$##"!! !""#$%&''''(((***)))(((&%%%&%%%%$%%%%%%%%$$$%%%%%&'''''(*+.../023554567788965ETfbTTSPU^bcb_YYZXWXWXVVWWXWUXWXYXXZ[[TSSPMOaw{xvrnmjbWZ]\a\VUWY]gm}vab_]_^X^SEEFHGFEI@=@9;SxePMUVSRRQPOLIHGBA@<<:9997674554775DRxcSRUTTUWVTXUUXVUSTRUWXVUY]^QQSQPRQKGIHFC=:>??@@?>>=><=<<;9EUTxuz|xuu^HRV[ZWXZYZXUXac]a^TSTSRRQQOMNLKJJIHJHKNLQUWVTUWUWWRNLIIHIHHGGFHMPONMLKJJHGIGFHGGGFEFFCABDDA?>?CHLKHGJLORV_hqy~nnpnlheb_\ZZYWVVWWVSTTTSTUTVVXZX[^choz~squuusnnljhggggggffeilmpurooswxtpmkicYPE*#%$"""" ""##$%&%&'(((()**)))(()%&%%$$$%$%$$%%$%%$%%%&%&&&&&'&&')*--./123465566899::955L`t|~`UTTTV\__`][\XVWWWWWVVWVVWYZ[XYZ]^UUTQONLd~}}fcaZUZ]XYYVUVUZ`mypb`_[\\\fVFIGFEFLMD>B?:KpyYSVQSQPQQNLIGEABA=;9;:84533442567MTzqUORTTTTSSTVRSUVWUSSUX[US_gZOSTROPNIFGCDA<<==<><:;CA;@`tm^XKQPPPQQNJGE@A@?:9:97453333357>R_]CPTTSRQRRSRQSUVXTRRU[[WVZ]ROPRPPNJFDCCB=====>>@B?<<<=?=::;=>>CFM^ztcPMNRTWUTWVTTTVWVUTYYZYMNLIQSRNKIKHFECBBEEDHLMQRRPOMINNRW\WLLKLOMMMNNRRUXPEEFFFEDCDFFEEDB@@JRLJE@BGLMQWNKKKOPSV[alvupvonkgfb^[ZYWVWVVVVTTTSRTRTVY_``bkmuzqqtvsrqpolmhgfhggjgikmptuqsrtwurljhdZPE12:<:5,!!#""   !! "#$%%&&'''((()))()(((&%$$$#$$%%$%%%%$%$%%%%%%&&%&&'()+,-/22244567899:::;<=::926Rcws^QRSSVYdd[[XW[Y[XSTVUWY[WVVWWY[[WUTRQPQQQjt[RMQRQQTVXW\bdaa_^\[Z[WTLMKIGGJKKIGFFE?AXtl\KKMPOKMLIIE@A@?<8864542333554GU{oBSTQRRPQRRQPPPRQQQQPXYc]NQSSSQNLJJGEA?AA=><<=<<===:98>@DROUw~~bNIPUUVWUUUVTTWVTRXXVYZOILIKSSOKIHEDCBCDCDADFMUUSNONLKNNRUWLHLNPQNPSRQQROIDADFFDBBBDDDEDDD>FSPGLI>DMOSZ]NKLKMPRV[bkwsqtmmjfda`[[YXXXWXVVUTUSTTTVXY\]]gmry~vrqsstsqpnmmigfgggjjilprvuoststrpmkibXOF=EIJKIF>0! #$" ! !!! "#$%%%&&''((()()(()((&&%$$$$%%%$%%%%%$$$$%&%%&&%&&&'(,-/012344578899:::<<=;;9818Rhzs[QTSST[___YZ[Y[WVTTTVWYYWVWWX\\XUTUTRSQU]~nbSMKNPSVWY_b^^`a`][ZZXVMNJJFDBEIJGDFDB?Pj|}ndPIFHJKKLJHDAA@==9755533335758GU|dDRQQPRPPPPPQQPPRSSROU\eUOQRQQMKJIEEB@=?ABA;;<=<===:98BHLZ[jnNLQRUUUXVVUVTTWUTRYWNNOKMGEKQQMIGGEBDBCBCCABCHJKOONMIJLNTWPHIIKNQSTUUUTQHDBFFGECBBBDDEECDB>NSKKRJAIRT[^[MILMMQRV\ckxqqrmmkjeba]\YXVXUWWWVUTSUTUWXZZ\\fms|ytrptrsqopnmkkggfhihoilrtytotvtssrlki]URJHTZ]\[YUL@0! !!""""  !#$%%&&''((((())))((('%$$$%%%%$%$$%%$%$%$%%&%&&&&&()*,/00124456789::;;;<<<<;::5-7VkzpVSUSRSWWZWWWZWVXWUSUVYYXWYXWZYWVUWWVURT[t|tfSMMOSUYa`a\\_^_`[Y\ZUOLLJHGGGHHEDFC?=;65544334772?F`[FSOONQOOMMPRQOPORRPOTZ\VOPPMMIIIFEB??;9CG>9;<<====87:JTamsxysOMUVTTTTWYWTTRRWUSSQNJJMNNGEFKNJGGEB@CCBAA@@DCA;@KOPKGHJNTOGGHHHKMSRTVVRKFCGGFFCBBBBCDCBBB?=VYKURGHQV[^ZQLJLNNRSU[blvoqppnligda_]ZWX[YWXXWVUUTSSVWZZ]chnt}vtrqsrqponlmlhgihikkqikrz{tpvxtttqmif\WXOUbltutsodYN@-!%"!  !"#$&&&'''(((()()))((('&%$$$%$%%%%%%%$$%%%%&%%&&&&&(*,./0122556789::;<<<===<;:874.5QhxznWPRTUUSQSUW[WX\[[WVVWWWWYWWWXVUUUWYVVVXbk}^USMNSW]^]Z\\]]`]Z_`XPKMMIIIJJHFEFB>>:?Uqyy[LNEKIJIHHEE@B?@=75663333685ADj|FLTNONPOOIJPSONMMPRQPTYWSPNNMKIHEEB??=::=:;8;<;<<;:9:BOg{xsrmSPQUUTTURRUTQORUVTSQMLKGHJKGDBCFGGFCA@@AA@AEGC@A>CLRMECDGIIADFGHFGJLLNPQLFGGGDBCBB@AAAAA@?A@8UmfZJIRW[_[MILJLMOQTW]`kvoqqpnlgeeba][YY[Z[YXWVVSRRTWXWZ_ejpwzsqqrrponnmklljgijkmpplot}wsvxvusrmgc]ZYUcpq\P=+  !!#%%&&&''(((()(((((((('&$$$%%%%%%%%%$%%%%%%%%&&'&&)*-./01235556799:;<<<<=<::98754.5Qgu~}jWRRSSRQPPRUY^\[]][ZYVUVWWXZYXWVW[\VXZV\hnj\PLPVV\[Z[[^^`^Z^`YRNMJIFHJJJHGGDAB=8D[n{nVR?IHIGGGFGBB@@96776233314C>Gnm>TRKKMMLKIINQOMMNRSSQSUUUMNMMKHEDB>;<<;;<::9;<<<:9?BCJb{rcWKHPUVTSTUURRQMOTUVVRQMNKGGGEECB@CFGFC?@A@@?@DB>@=@EHMHBABCECBDEEFGIJIIIIJHIIIGBCCBAAAAA@@@?BC:Fa[IJSZ__\QKKLKMMOQTV]clu}nrqqnkhddba][[Z[[]]ZWVUQRRTWWVY_ejrxwqrsrqonmlkkkkhghigimnnrz|wtxzwuspmga\[V^srWG5 !   !"#%&&&&''''(((((()(((('%%$%%%%%%$%$%$%%%%%%%%&%''()+.//113455677:;:;<<<=<<;98866650:TgszwiVQSRQQPPQQU[\[\^]`]VUVXYYY[[YYZ^^YZ\Z]bt~}qaYUY]]\XWY[`f\Z\]YRONKHFHKLJIGHEAB@87K^vvjW9DCDCDEEGBBA?879:72232.0=:Qx}yXCTNKKLKJIHHINMLLLOPOPRUWRLNLMKEEBA<;;;<<=>;9:;:97>?BAA?===>88:::4.1//3;=\~snQEPMKJKKHIIIJMLLKJJLJLOUXNLKILGCA@?;9;;;=>?<99;:?@EJICA=>>@@A?>>;<<>IKC??????@>?@BDEFDEGGGGIJIIGEDC@@@@@@?>=76J]lnWHC?BFFFHGEB@?;7:7::)//.0:C`ypPFPLGHHHIHGGLKJIJIKLLMMRRKHIIGA??@A;:;;;=>>:66=@HRTXmz||]LRUSSSQRRSSUOLPQVYZVNHNMJGFEDB@==<;@><>>>=?AABCDBCCDCEGJIIHFB@@A@?@>=>ACJLORW_ltseXVTVWVOKLNNPTZ^dmswnqtsokhdb`a_^\`_]]YZXVUSTVVWX_bgkqvtsrrqomnmlkiiiiihilkkllqwzuvvvwvwtrpkdVKJSow]A( !! !! !!!"$%%%&&''(('))*)))))*)('&%&%%%%%%%%%%&&&&%&&&&'()+,..0223567789:::;;=====;:98677777521@\`l}seSMPSRRSTTUV[`cgjc]\WWXY[XURQSTTRVUSSSRNKL`{n`TYWPSUVVVX[VUSOMIJJOLIGFGGD@>?76A'./.-?GkvEEMLJHGEHJIIIJHHJJLNNONPLIJHFA?>>?=;:;;;<<<734DLOWk}vykRUTUTSRRQPQYVLLRV[\ZQLGIIGDDDBA@=<@EHE@?><<=>?@@><;>?=;====?@@ABAA@BBBFGJJIHEB@A@??>>BEGKNMN^bnrrj^YYWVWWOLNMNRSXadluulrurokifdba``^_a[ZYXWUTTUUWUZ`bhoswmssrnonmnlkkhhhihilmkmpt||wvyzwvvtqqh`QDBQlmP8*$  "!!"$%$%&&'((()))*********('&&&&%&%&&&&&&%&&&&&&&'()*,-//123466778:::;;<===<<;:87878866661.?SfqrudPNPRQSSTWZ\^^_g]QQQSUWVVTUTVTQOSTUUUSPLHH[q~gNQOMNSTUWXWTRQQMLJLKLIHGEEC@>@862DdsqaQ??CACDC=?@?:8:=I@%-0..@Qzb:EJIKFHDGJKKHJJHGKMNOQPLFHJGD><=<;:999:;9<<55>@EFA>?><<==?@@=9;>AC@===<<;<<====?@??@@@ABFGJKFDEDAB?>C@CKMMQRS^qrpl`X\g`\Y[ZOMMOOSSX^douxmrsrpjggbbb`__ad[YXWVUSTUVXWZ`eipu~xprsrooommlmlhgihhhlmlmsx}}xuy|zvuurmg]L96Md}yWE<80  !""#$%%%&'''())))*******)))'&&&&&&&&&&&&&&%&&&&&&'()+,./0123466688::9;<====<;::8788887666412?VirutaPOOOPSVX]^\Y[`WOSTUWXVUVWTVTQPSTTTUQQONKIPsrPIIOQQTTUWSQPRRLMKKLMKHEEEDAA?855B^s|nYN=?@BDB???=;76?>?BGC><>>;<<>??=;:>>=<=>?A@ABEEBFCBFEDFCHMJOOOQVY]kqjcTQSVdgc]\\OMMOPSSW`grxptvuplihcadb__a^ZXWWUUTTVVXXZagms{ssstspoommllnlihigghjmox~~ywxz|}vtspje[I/,I]ueUPL?1!!"$%%&''((()******+++**))'&&&&&&&&&&&&&&&&&&&&'()*,.-02123556778:::<==>==<;:9788786655453/.C_ouxqdXQOOQTWZY[X[bWOTTUWXVUVVUVVSTUUTTUQQQQQMJNo~dNELPQRRRSPPOQOONMLLLMJFDGC>?;:847RewuiX3IOc{~{ogXHKNLJJHPRQROORSWTOMLKLNIJHFEDB??>>>@@BEA><=<;;<>><::;:;;;;;<<<<=>=;;<==@AAADA>?AFGHMKHQSRWVX[]_^a][WKQTPT^]\WZNMMONSV[`hr|uvyupnjheccb_^ZVUWVVUUTUWWZ]^dfpvtssssqnnnllkklljihghilmtyxvxz{|}xsomhaSE&'AWn}mj_N@#!"%&''(())****++++++***(''''&&&&&&%&&&&&&&&&'')*+...121244567899;;<<<>=;<:978777655444430.-CZhqwoi_QMORUWT[[]g\PTUWXXUUVVVXYVVVTTTTRRRQSRNKIc}w]JFJOQPOPQOONKLONNJILLFCGG==<:86/>MqoV;<>>AE@@=;84131/0/-19K\|ZPOMLJKJKKRRVQFMPMMLOUXM@DEEC@99;:995559969;BNW^u~vrshZ[SKJMMMJKNKKPPSUVXUSOJKMMIIHIFB@??>=>ABDC@=<<<;:<=<;;9;=>=;;<<:99;<<;=?<;;;<:?DLNRUPRY[[^_``\ZTSTWOOUTSSPSUPTNNNNNTW[`ju}~wxwupmkgffec^\ZXXWWUTUUVWY]afhepy}tttsrpmlmklkjknmjiihilouxwsz{|{~|qolf[N:#);RfxmfO0*$#$#&((())*++++++++*+**)''''&&&&&&&&&&&&&&&&'()*,-/01223565689:9:;<=<==;:88778655443333220,)<;83221310/4ARfrWRNNNLJILOVZ\LJNPNMMORRMDBCA@:79:;<8235786=CQZ_q{qgeVERWRLKKIJLLLMLKNPSYZVSPNMMLLHIJE@>@@?=>ACC?;:;<;::;<;<<9:=>=;;;;;:::;<<=<<;<;=;A@=76778:3243567DS`gq}qihS>CLMMNNIIKKLLMMMLHJOUVRRQOOMKIHGFC@A@>=>CDA=;:;;:999:<:78;<<<96764113755=Ni|hDJNONLJLQOLIJIJJIHIEHOKHA=>?:65622223306=EP_qqws\_RBEJKKJKLIIIJKMLOMIHHHMLMORRQOJHIJIGFDA?=@A@>;;::99998;<737;==:89:;<;;:88988899:9:;>??A=;FV]`hha`b]VOIEHKNQPS^ZOLOMROMPONMPQRTU[_gpyxxzywupokhdaa_[YVWWUSPQTUW[adinx{xytromjkjjjknqssiejjpuwvwyy{zyutpmfXL=#,7BL[m{oeTOMG<6.)''*,--,,,,,+*)(('&'&&&&&%%%&%&&''()+,./-/12334666779::;;<<;;:877764332222102111110//,7Uegnqni_VPQTZ^ee^TUWZ[XSUXZ[[[ZZUUUTTURSTRUUURNW}}h`OAEMNOLIKMQSUTNKKIHHOI=>;99;;9=MaljbI39;=;8674100277;EP{{dCMNLLJEIKMLJJKJGEEEDFNML@><<85432124525DOUYjvtuVLE@GIIJJIIIIGGJKJKNKJHIGGGIJGJRPHHKNNKKHGA====;:;:99977899537<<:877;;=;8876666999989:<BBGIHGGGHHFFEEHHGGEIIEEEDDGEDBDECEGHORROK?:9:9987887766656435::97769?=554544459;86788;9;DIONYdbVNGDILLNLKKKLOQPHHJKKJMMLKLMJKORTW]chpz~|zvutrokdb`_]ZWXVTTTUTQV[bdhlt}}zwwwtqmjgfhgifgfedhjmrwwvz|{zxtrqog_QJ7:DLPYdt}q\PMF?5*)-.-,,,-+*)'''&&&&&&&&&'&&'()+,-..012333565677999:;;;;;98765432200100111111101110.)(4MftppnjdUMQW`][ZVY^WSUWYX^\Wb^QWTSVVTTSWUUVYQP_zdQECHIINOQQUUSMMRPFM?@GE>;8:=<6;866653135:8APhkAGGGEBDGGHHEEEEFCA@DCEKF@<;99931..58BMY_ammcXO@?===GPRPD;978887565645542333489766669722342245874469888:HPPW_aSFDEILPPNKIJJLMLMKIIKJIKKKKKLKKNRTY`elr||zuttpmkd__]YZXXVTSTUVTUY`gjp}~yxwwvtsolighiigfegfkmqsuuu|}zxxtrpmg^RL?ENU[ak{th[SJA6*+,-.-.-+)(('&&&&&&&&&&&&'(+,-/.-/022335656679:::;;;:9865542221110001111111111111/,,0Kfostpni[RQRX\\XYZQPRVYW^]\kcTZWVWWUUTVWVW[XU\ovaJCEGJNPQRVWRIINPNTGDFGC@;<>>A>H[ee[OG868765542469:GPsuzd:GFHGCCEFGFEFDEDC@?@BAAA;<;6650-15:::=EKI?:74675534443343112336754443231123224453124545:>ERYabXB@FIJLMLLKIJMLKLKIIKJIHIIJLLKILNSUY`flt}{vsqmkhe`_[XXXVWVTTSWVV\^cir{~|wwwtsqoomjihfhheeiikruvvvvz{|ywvqnkg`UJDOYbgkzufVK?.)+-.-,+*()&'''&&&&&'''')),.////012244677779:::::::976454321110/010011111110111010-.6L^mtpnqo`SPR\c^[\WOPSXZ^]^ke[YX[YWXXXWWV[XQPRYpwnXIFAIMNQTUTNIHHJKRFDFFE@>>==@<=MZbcXQ@85666853345>=>9<;532/4:?HTdeghh]D??@DCB?FEHGEECDFHGID@@BBBBBA@?>@@?>===9;=;>EB=762541232332222111335443332122112123431//033;CIO^edTC@CGIIJLKMLLJMLKKJJJJIIIIJKKKJHLMSVX^glu}}xtpjgfcb][YWVUWVUSTVVX]acipv{xvvvtronnljjidfgeggjnt{vvwwxz~zwwpljiaWMO\hq|zdWL7().--,+(''''&&&&&&''((*+,-00/0122444777889:::;:::8644432111001000111111110111011/+*1@Peomnqmd]RU^a`c_UQQV[\`\jk`]Z][[\[[VTTVOKMNLWhy{mXOEJLOUVWSMKIFFFG=@BCB??=>=><=FO]ee\H?3677:55435:>>=>=<:8:;9<>;74434201112222221011443322221111122212202239>DLSZbbL7<@DFIJJJLLLLKNMJJJJIJHIIIJJJIIJJLRVY^fjv{yrplfeb_[\YXVVVVUSSWWX]afkrxyutrttqnnojjkjdbfhhikpx}vuwyz}{wwqmkk`XQZixwfR>*'+*)(('''''''&&&'(((++-///00133455677888:;:;::9744432110000000001111101101101000-*'*=Sbmolln_QT\ghh`VSXY\d\ni\a`\_bb_[SPTSTQPKHEM`t}{i^UMHLXTXSMPKDD@==?@?>@><==><@HDP_ieRJ74:;;8765;?TkreN:DGFGBABA@@BCB@?><<8<==<9:604;;;;<<=><:9768888:;:874410/./2111111110013221011/01112220.036;?DJT[_aZF8@BDEFHKKIKKNLINMJJIIIJIJIIIHGHHMNOTVYagnt|{utpkgea^\YYXWUVVUTTWXZ]dhlv{{vutqrroljmjijigeehkmnr{zsvyxx|yvuokki_UViy}sXI710-))&$%''&''&'()*+,-.//00022446578899::::::9753322000///000000001111011/0100010.-+$*CZimkpp^WW`ipiYX\ZX`^e[X_^[Y\c`VSSbkeb_ULKENar~zmaROLVNTQOULDE@???>=>?><<<<>@NBARag[MC6;?=8;87@CVsyc_>;;85;;?<72226@IPT[cea_S;8;??@@@@ABB@>??ABCEHJKHC@?>=<;:98:;997765677676<;986210-,.01000111110/0110////0112220./-4=DHLU]ccZI@BDCCEFHJIJMLNKKKJGHHJKJJIIHGGGGIMNPTXZbgptx~zwupheb^][YXXWVUUTVVVXY[djoxytsrqqnomgfjghfggfhkmqvxurvzxxwxurqmiie^V_ut~}zfYHDC=72+"#$''&'')**+-.//000133475788899:::::88653221/0////000000000110000100011110/0.*(9Sfjmpqg\^gnke_^[WZXWYY`b\WVVVPVk}tgeadmu|qYWROKSPOVIDD@???>>>>>;985BJJ=:IVbgSMA8?;6<:6BGZ~ojR8@BGH??=>ABBDA==;:9657:?=7558FSZabeg`^W:7??@@@@??@???@?>?@CBEFJJDA>=;:997578855455556677<<87640/.-/00/0011111/.1100.-./02321/-29:>FNS]aff^I@CDBCCDFHIIKNNMKKIGDDGIHHHGGGGGHGGNPQTX\aiqx|}ysnmjec`^\XXWXWUSTVYWYZ\emr|}vtrsrplmjfbfeeffgfhjnrvwttvywxusrqpkhfa\Xjswwwx}zi^YUNHB7+ $&'(')*+,-../001145567788989::9:887643210000///000000000000000000000100010.*+4Oepptoigacfhdaa]]TSZ[af_ZZYTXs}e]RFEKKONEFD???@B@<=<:962=MF@7AT^l`WI4>;5>84GNjha<>ABBA?><=?>@B=:;:889958==<:?>>=>??>@>=@=?CKHEC><<9877657644444455566;;:::5.../..///1110110/0100/././010,.7=BGJQ]eged]MBEECCBCEFHIJJMMOMHEFEEFEEFFFFGHHIFFNQRSV[`irzztlmkfda_^XYWYVTRPTXX[^_goszvuttrplkiebbcdedffgkptxvrvxyzxutrqnjhdaZ^vnrsw|rrk\VMA1 %')(*,--.0/011234567888889:::988653411100000//////0//0000000000000001111111-)+AXinomqj__fgjlhe[TZ[cg_YXU`trbVGBDBDCDEBAAAAC>=<;:96689@D66MZigbL8>>?D59EXw`Y6BAA=>??>=>=?>>>;==<=@FIH?:99975455442223433454268;=9/+-/.--..01110/000/000//.0.-.32:EFIMS[gmd^YNJIGFDDCDCEGGGFFFIHDDDDDEEFFGFFHIIIFFKPRSW]`jt||zzsnjgd_]^YVWXSSTRVWZ[_ejou~xutttroljhecaceefeghksz|truxyzxvtrpnkidaXfnu{xeP8#)*,./00/0012335566778889:9998655231100000///////0/000000000000000111111011.-(3Ohporwl`cfmomj`WYX\_WXV[xr[Q=CGCBECA@@ACD?=<<:87545;?31AUdgdO8;<<:6=CZrtiT3>@@=<<;;<99;889859<866?DLQS_dlorfSF>;?ADD>=>?>?@???==??<<<<;<=@FE=:77:642542/0013334431226;91,+-----..0121/0/0/00210.142/2;=ITVVY\[[WRNLNPNKGFEEEDFGDCDCCBBCDDDDCDEFEFGIIHIFFKORVX[`gqzzy|zokid]Y\YTVTRQSSUWZ]`flow}vsssqqmjifddcddffghjnt|zrrvxyzyvuqomkfea`rz}_>%*,./00/0123346666879989;:999544221110000//000/.///0000000000000000101111102.,0Mkuw{{redflokc\YUSYYalxjZBAFBAEDBAACDC?><<:9754569326KbhdUB>@47:AK[|vjJ0;;;<;9788988778><:?ELY]djiinfSFBB?AFHB>>>?>>>>?=;;<<:;9999;ACD>:99844341.../2334321100/-+,/.,,,,,--/131/////022220478;>CFM_da]YNA>ADHMMPNKJGEEDFGECDBCBBCCCCCCDDDCFIJKKJFDKORTW[cdky{}zzsnhe_]ZXUTSSRTTVX]`cgnu|ystssolkihebbdeeggfgknrwusvxyzyxxuoljkec_kj@ %,///0011134556767799::::8864431110000000///.//./00/000000/000011112111122210-0Hbt~}uibfijle^WRXq~nOCB@>BACDCEC?==<=<:756666666D\eg_QHD>;:HPisfA2>><:;;<:645588748=>@AFP[ceeba]ZOKDEB?AKK==<<=?@><=;69;98776876=DF>59<411121//013420.....0-()--.,+*)*+,-/00////.034869;>BDCNVXbh^PA?@BEGJKKMMNMIGEDEEEDCBBABCCCCCDDEDCFKPMJECDONSRU^chnx}|yxuphb`\YXUSTSRTVVXa`fjo{~xttsrnliggebaedffgdgkmswttvxyzywusnkihec\vlC#(///012224656677789::::88744321110000000///.../.00/000000/000000211211122212256>Tnwgbdimf_`mzXHD@<=<>@BB=<>=:;;9978777774=Vcmg[SI;<>K\xvc]86>?:899:953334462:<8@MY^dhe`]WNB?EFE@?@@<9:;;=>?<;<968:976677747A?830430./000//144/-.../0/,**,,,+*)()++--..../.,/39>@DFFHKQ[``ZQH;?CEEEEFHIJIKKJIGFEDEECCAABBCCCCCDDDCGKPOGCCCOORQW]ciov{x|{wupke`[XXUTSRSTUXX^bglr|yvsstqmkhffebacdddggfinvvsuvwxywtqrnkjgfegnD%)/0012335545677889:;:8975431111100000000//.//./00000000//0000111222211221355=ADFVp{mffc`i~½xHHGGIGD@>:;B?49=88:9:987866;T\qh]WS2BENdynZN19>?:8769853321147?=FO^cbdec\OA;7:>?@@?>:::;;;;;;:9:866874656761/3761,.//.-./..1230+---/00..,,+*,+)('(++,,---..,.9BCGJMSTQSY[]WA;??BDEDDCFHGFFEHIJKKHEDDDCBBBCCCCCCDDDBGJOLGCDDPRQTX[bglt}{{|~{xrmi^]]WVTQSUUXZZ`glqyuvwsrpmkdedabbcbeehohkrxvruvxxwvrppnlidecrſnD$,0112355555689999:::88643211111100000000000////000000000011111022212111058=CGMNVYo~|lbYiiMQTYYYTLBHLKB<636<9;978876@UZljc]T4NKWmt{hX=4==<:7655541221278AHVbdb`a]RB6489;:;>>==>==<;99888676654434311/,.046/))*,,,++--01.,)++,,..00-++)*++(&'**+--,+.+.7BMPPVXXVROJBAA>ABBBCCDCDFFEFEEDDDHOMJFDEDDCCDDDDDDDCBBIMLGFCCCRSQTYZaalr{~~~|}vtnkd]_YXUQSVWZ\\ejnvy}uwysromkfebbacbcdfjslmuxutvwxwxuronljhfdcyǿlB$0122544557799:9:::878542210000100000000000000000001/000/0101111222222228<@GKOUZ`kuxoiÿanv^\ilbI=919489777985AZdjieN@OHdwuvaT48=><:76544423478;DT]dfcaa]J647:<;;::;<<<=<>;;8775777755421011-,,+/10)&')*++++,,+-**+,+,-./11-******(&'++--,-*/4:@ISZ[][RLF>::@CCBBBABCDDDEEEEEEDCCEMPNKGHIEDECDDDEEDDCDIJGFEBCCRRRTXX^`jrz}~|z{zvspje^_[YUSUWZ\]`hkrv|{vxysqnljgdbaaccbefiomtwvvuyxywutqmkihgebhûh4)113455666899:::::8765331101001100000000/0///00000000000111111222222234:@EJPU\`fpvzw¿~_L81.476778;41HZiofNGNOrvp]I18:<=:567564454;=>Sghea^[TB47;<:<<<::::<:<=>=::865688<5220----,+**,/,)''()++,,+)')(**,,,-//21,))+**)('(+-.,,.06=DHQ[][XNB=869?BDCCBBBBBDCDDDEEDDDCCCEHMLLMNKHFDDDDDDDEEGKHHHDCCDUSUUWY]cgoy{}||zxtomjfb`\YVUWXZ^`cinvx~vvvtnkifeea^^aabdfjlmy|vvwyzyxvpnmiefea^s¼zW(033555778:;:::::988532211011110100000000000000000011100112222222212/27=;;96568;7/0.--,***)(),-,)'&'(*+,,+)(('(*+,-,/0-,)'')++)'&%+,(*.08@GNSXZVOG=988;ABBBAABBBAABCBCCCDCCCDBBDDDDFJKJGGFEFFEEDDEJMJJGDDBCWUUVWY\afnx{}|||xsmjkhda]YUUY[Y`ddlsw}zyvutnjhedb_]]_`bcfjkny}wtvyzzyvnmlhcbc__vn>*44666689:;;;<:978552221011110100000010000000011010111112222122221226:69999888<975999::;=>?<876533-,,,,+**))(()--,)&'&'*..-*'&'&%'*--.0,*$&('''('$&&+--76=CJRUUQF@;7679=@ABBAAABBBBABBAAAAACCDDCBBB@?ABB@AEFGJHGHFDHLLLIFDCDDXUUWXY[agmu~}{{{ysmkifda\YUVZcabfipx~}yzwsqoheec_][\]_ccejmpz|xvxzyyxvoljfc]ZYf~ĺxV'3556799::;;;<::9754221110111011000001000/00011011111112233222222125:@DJPUZ^foyļ¸^B1079;:9Kaoqm_Wo~ue_G;?8887326;>BFM\`^a^VVL43:;:998789;864688879;?@::741/-,*,+**))(('(),//('''&+00-'&&&%$%',./,*'$&(('$#$(()2=@>BEKTVSH<377::9;@B@?@@?BABBAAAAABBBCBCCCBAABBABCDCBCCDGFGIFGJLKLKGDDED[TTVXZ\`glu}zxywtsnkhfb_ZYWY`bcdintyzyywsopieca]]^^__befknt|{wxxz|~zxojfb\YVViǼ{d0155679:::<<;<98764321121111111100011111111011111212222233333233334:?@JNTZ`gnw{ľxN2.8=<9IYkuofa}|~~oaW>;>77:75;AGMQRX]_ZVQI;-58;978877888655566433688:=820,,++*)''(((''(,-/-%'''%%'((&%$$$%%&+/,)(%&%'%$%')16;AEGKSRRUQF845===CDEDBAB@A@@ABBBB@AA@ACBBCCCCBABCBCFEDIMMKHGCDHIZVTUXY^bgnu}zzyywstolib`_\Y\[`bdglpy{zyywtmnlfb`^\]^_aaegjoy}zwxz|zwqjf\WVQVmǿ|i;16778889;<;;::9664311111111111011111100101111222222323233333444556DIPX[bepvV/695;Oftplu~toWI>@??==>HOW[[VVZZLLA*378:985456553444543422100,./7<1&%&))(&&((''&&&(+)&''''&%%%&###$$$$%$%,0.)/02659>DLV[Y]d`VK=4457:>=@AA??@??BDDBBABAAAABAAAA@AAACCFFFGMXWTVYYZahot}~yywxxtrollg_]Z\]accglqxzvxutrnkhfda_^^\_behjnswurvyzzywwvpjePJIL^rżvj>0567<@@B>7577664322222212111211101111111111333333333434455565566;?DIPTX]d`tǻƿD-989KcrttywqbZD?D?CDGKPXZXUQPQE<;-25776644554433122265101/.-++-1.'%&&'&&%&&&&&&&&('&%%%%%%%$$$###"""##$*5:98BBBDBEKQX\\\^^THD>=:778?DDBA=:;;;;:99;;>@ABBB?=>==?@?@@>>BDCCA@@@AAAAAAA@@AAAABCCEOJYZZZX\Z]emr{xuuwwusnkkia_Z\^afchouyyzxvrpnjigcb__^\_dgikpwuttwwyzwtvyph_LFBK_r|qc74:@BIOLOOH@8542112122222211112011222122322333343333434456555665;?CHMSWY[]d˾ùr+556H]qss}x~}{kjcTSMHHKMPRVVQHCA>421245654444434422222353/10/,+++040*'&'&&&%%&&%&&&&''%"#$%$#$###""! "%(.7?FJNPSTRPOPRUTSSQOOLFEDA;97=EIE@:9:;::9::;::>AAAA>====?B@@??@ACDA@??@@@AA@A@@A@AAAA@?BWN\ZZ[]\^[aipw}sswywtrmlf`^]\^aedgnvy||{yvrmmjgdcba`_^aehknuytrtwwxxvuuxogYG@9G^uľ}slX3=DHNUYa^Y[VIBA70/0222222111121111123333343443444334445666666668?BFJOV\cuɼǻE,58FZosw|{~~pV\lfep|~eVF0*.14314433333322221320./.-*)*+063+&''&%%&%%%&%&&&&&%!###$#""!!"! $*23:DLRXVV]ZTQHEBC?76;BJROIHCA=::BGB=989:99::9:88:?CB@==><<>@@?=?>>@@????@?@@@@@@A@@@A@@@@<<<<<=>>=<<<==>?@@@????????@@?AAAA@@;@HXZVWZ\_acjoxurxyytljedc_Z[]bcelrxz|uywusnkijdaa_`^adegknx{upsvwxxxtswtj_P>=<;<<<=>>???>?>>>=>>?>?AA@@@?=:8WYXX[\^afkpu|{wvzzxsnkgcca]^`bbdmuy{xvutrolifd```___bdgimp{zqrtvywwvutrnhYI5#0BTf~{|xne`LT]djzycN64/-/3444444555556665556566777677788888988=BGT^wp~233CXfrpsyO&$$%'*.343/..-+,,--,*))+21(%%$$$$$$%$%%%&&%$#"! !%-378<;DLPSQMIC9395204654558999::9;AJKJGA<:84335577778877789968:;;;<<;;::;<<=<>@A@>>>>>===>??A@????>>>ZZ[Y[[\^dgptwyyyzyvtokjc_ab^_cbemu{}zwrqpligbb___^_acegjov|upquxxwvutrnjeR?+(>=>=<<=>?@@?>>>>?>\[]^[V[abbkv|xyz{zutqkib\]ea`cdhnv|}wxrpokhfaa____^`dgilqy{oqsuxxwvtqpmg_I7$#*6DWfy{h`\egurdTE7,1566566666667778788888888888998779=NVh}Ľ{hjI9@Ugs|ĵvL*(()($""%))('''(''$$$$######$#####')))*+.//3<:8532467877666676898;::<<:::;;;;<==BB?>>====<;<=???=<=?>?^ZY^[ZY^bbhtxyx{zvspjea]]bbbddlrw~}ytqoljgd``__^]_bchkls{wppsvxxwwsonmfXA."%,7DQatycZdxwcC,0236776678888888888889:99988895AELKIA80470((-/01210144343336@8@:488858<=>===<;;;<<=<<<>>>a\W[^^]_cgltyvx{yxtngbaZ[_^beipuwxwvrnkfca]^_`]\^adhnpuwqqstuwwwyvnmkbQ;%$&.;FSdw|jzM874147678789899999:99::::9:877:GV\oyž~gg}ĽqZ|ľD"##%'&#"##""" ! #)-16=@?EGKJECA@=3,'&(,+*+,,.11211134341110EGA/177878;9888656556665679;;;:999:;;=;:;;;;;=?>=;;;;;;<<<;<;=>=c^YY]]_bdkmr}zwzyzwrid`]XY]]`elqvyxwvomida]Y[\]_^]_glrwxupqsuwxxwywkkj^L6 $%/=HWizx}`HC:0288889999999:9::9;:;:::98AQl~|žj]jyý{T\X@("%%""##!!$$'.5=865655666666889888989:==;98987;===;:::;::;<<;;;=>;ca][\]abfjjoz{xzxxwpkhc^\[^_cenqs|}wvnlhb^]YZ[Z]^`bims~|spstvxwwwxvkhgX@/!&$.>;8220,,.0223891.3250//010-/0.......///./1124544788>CHMLA=::A?>645444456667777799886568:;;988999::9::9::9>GLffhfb`begjkpwyywxusplhdedafcbgkrz~xwtid`^[[Z[\]_fjkqyztptuy{xvsrqmhfQ>1$%(%'1BRdyvutoqxuM-8:::;::;:;;<<<<<;9ASpxfXTWTVpqj{|}fQRý̾ƻ[49DIOPKLH?95342389:658:8840/0033332+,782,//.,,,-..---,-,---.--.013444886629BBA==AD@7453334666566676777666789=;989<<9::9:98;=?EMPehgfedefjkntz{xwwurpnjadfcccefmsy~}}yurib\\Z\ZX]a`diorzvpovyy{zutsonk`J9&$&(&&,=;62133566655666677877668998989<<99::;:=??@@BFIPV[abeeghikmoru}}xvxxvpigfacgddflkqx}}ywrjec`^[ZY[]]cglqzysrtyyyzwvtrokbL8,!''('',AECCCCAEIOUUTZ]fghhjllpqsyxvxxtrmggddbdfinuu{~||wrpga____[V\_]clpr|xoouvuwvvtsomi\G3$#''&%&,=Lbw¿wqefgftŹq];5:<;<<<<<;<;<8@IWblPbrqmorolprqpmnocUFS[gpb\PPT?CZk{tprvmhf][_]YLOE?OĿûhkvƹ{)-.-.211/./3225542114;=940./-,,++++***+*+***))())****+++,,---.01434325788:==;=B?=;96534444445555776544555666:=?DGJFFFFHKMKGB?fYbfjkhjnopv{yxxuurkfecc_fhkpvx~~xtrpnf`]^\\\WY_bekuy|wopttsttsrqmmhT?)!%&&%$,;IVg|üskacdbm}øq[<5;<=<;::;;<;;:864433344444345322345667:979ve\fkjkjorqwxuuuslgdcecdgkpux|{xromlc]]\WZa_V_ekkt~ysqqsrsqqppnnmdI5$$'&%)7CN[htxk_]^`ivļoX<5;<<<;<<;:9::CSov{Nq~|wsoga[WNCEVdZSLFCGLXbi_U_aVXYVUUVPFJSE˻ÿ¼YYož¿ºF%/0/1455/,,+++,,-/1234644311220)*++))))))))('()))++****+,-/00..0211//25679:;976=EC>:863103433333334479;::;=>>@EPWUQKC>><<;===tt_ejkklouuy~{tstroldfeddhkotxzxxvpkib^\YWXbeX^glnt}smrqrpqqonmonm[:-"$&$+;O\gt{ve[Z\`fnlV:6;;=<<<=<<:85479742345669;=>?@@??BCELTUNC:988;<<===uvhajlmnotyz}vtsrolffdfehjpty~{xutphdb][ZXXcd\bglptvpkpsrpqolmkkmiM4%"##(:Oaq½{|sh\TZ]ak}kT86;<<<<=>=?=EHVzjvz}qqqpje^VNLQRRLGINMZl_^\X[dkni^TJDKLbͽ̿{II^rV*./0232/,+,,,++**+-01/..19;::989;@@ADDDDDEFJJI@6239;;;<<=<<|smfgnqssvy||wrusolhfdceghpt||{ztqmga_^YZZ[___egkprrooqsrrrpmmlhk`A1$')+7H^sƿz~urcY``Ze|xjR48;<<<==<::;E_|n{ʯysvwsppggddgggceeZT[XVZWX`hhdZOFEMFptFNUh|·½j1#)-112110/---++***,-/--,,15;=73,,)*)+*++)('&'())*+**)'(()./.,,+++-.-/331245555558<>>AELLGIDB???:;@GIKMJGDEB>=<<98878;=<<;;<==:9889:99989;:::;;BFHHHJILMMMOTW]_UABGJJFCADGIJMƱǹulgH(7ACDFHIJIIKMOONQRSVQB?BCBA@DJGIL;ſŰž|hsi;&.:CDC?EHJLþ¿{nwhH+"(-/.-,++*))(***)())))()))++*+,///..,)'&''''(()+-,--*))*+,,+++,+,,,/0,.9@DH<)+/02335778:9876688999999999:;}|vz}{zywvtsrpnorru|{{ywwrme^]ZZXWW\[_glrxsorqrrppqnqtyulewž~zqek|ſtS\`dhozti_YRC17888899>CGCD]~|r4@@ADDDEGHJJKLNPRNLLNLFA>@A<==?|~{|{zywutsrrsttw{{zywvqnib`[YYYY]]bilruqprrqqonnnmvzqfsþ|wrslvOPVZ`gmw~~xobWTN>48888878AGGELry|4?A@BDDEGJJKKLOQTSLLNQPD<==;=====@AA~}}z{ywvttstuuz}{yyvvssjeb\Y[Z[_abgmsuprrrrqomnngtzlo¼ynquw»yPGORU[blrzvleXQNF46988979=EHDCNuuyxy9>@@BDDEGHKLNOQRVWSLMQUOD<::>ZUJEKNJ>r~ztkNMTA2/,++)*/56855pù¼¾ÿfn1'-01.++***)'''&&'(('''&&'''%$&&''&''''''(())*,,+*(())))****)*.37;655656778989::<@@@A@@ACDC{~~|xywvvtttz|wxutttida\[[\\_bcdmusprqprqomijmy|qw{jnowQ?HIJOU_houw~vjaKCB8599:;8:@FKJBN`sfgt{>9?AACDFGHKLMLMNQSVRNOPUVK86:YZQIHHFIqo{rlqmfTEHA;2-*()((*,035)_¸m\|$(31-+)(())'''&&'''&&&&''&&%%&'&&&%%%&''''(()*+(((''&'))+)'*169;653123011544445556669:;<;;==@CC@CGFHII}|zxxwuvx|xvvtqkhfec[YY][_ahikprqqrponmnu}r¿úwJ5>>?BLZfjo|}U138897ACDFILNKISumWINL539ZbUKB;ÿxORQGB>VryyQ.QYf-#+)(()))''&%&&&&'%%%%%%&&&&&&&&%%%%%$%&'''&(()('&&%&)+-/5:=GLI>854=@=;87655310124323566778:<<==>??CFHGHIHJKL}yxywwuwrtusolhca][ZYYY]`djoopqrrpmkjs}~ļvK2;:;BM_jk93357@ILNTJS¾ǿj[7?AEEILKKGZgD>/25W\WE7Uźt=C=:]PXzRX}¾T((())(&&(%$%%%$&%%##$%&&%&&$#$%%%###$%$%''''((''(,./444==?AADGMNLIHKLJ~~}{{yxututqplig`[WWZXWWY]cipqoqsqoligt¼¹uK.;@HQ^lvO=5:FIMT\VWºûw^BACEFHGGE^h4036PXT;6ñ¿O75Uba}~b=Dpǻ½l)*-.0-)($#""####%$!"#$%%$#$##$#%%#""""%&%%&),-04698588;AED:--11422:>>99886531101124556787;<>=>>@@DFGJLIGEEB~}{xwtusonjee_ZWUWWUVW\chpropqonkievÿľžqL7EOZcphFBIQ[b[S|aGDGFILVbmW#:LMPJFûĽ&B{aFlz}~uvs`C**[|ǽŽv1268;83/*)'##"##%$# !""!""""""##%! !!!#$%),036;@ABDBB?:83*+../332144458::76444211/35556789=><=@ADHLNMJEA>=:|{yvrppoldc_YXSTXXVW[_iqqpoommkihy¾ſĿ{kRJ]nePTdg]Py¿uFEHKc[=NPEdƽȿDiJ2\h~~mx|vuVNI=,*3d÷z&8:@EC=874310/-,-,,)'&''&(('%%(*()))(()*,+/16<=AHHILD93-+,,,./0110000/.26988776420024455678<=>@CEJNRQJE=52/,~{vrqnmlgd_ZZVTUWWVY]ksqpppnkkhl{»wj\gvalj[cŽSFHhr=@nŶŽqj.;W\[\X[doquxusvujN-! $&%-5eŽ¾q1CBBEEEB?;;;7776632221/1222231002331/013559==BEHKIF?.''(*,--.//./0//1//36579:75432435545457;?CHLMNRPJC;0(')+}yqqpomjd[Y\XTTUWY\^hqqponkihelyĽuoorrpXm`lü^LTojƿ¾}zD5cCCLIIWhqrtskd^S7/+*+( @@?BCB>>@?=<;:989;=;;:<<;9;;:868:<<;?A>>=<;71*'(*+,,,,------.///0264547:743478865658:?CIPVQQOH@;-$'+,.~||uoppoje^XWXTTUWY`acopqnkhedemuvɿƿĽý|}vn{tx\q`ƻcVfŽx}U0@=DA?89>DGONGE92(00*)'#6A]ο¾k!-**+-.02324<@@?<;;;=>@BBBBABBA@@=:969;=;44552-)(+,,+))+,,+,+,,,-..///12223//564489::9::=??DJRZYQPK@:+$')++.|zwrqprlgcYRWVSUXY^b`lrrokhgbahfnżǾĽywqƿxt{lp~hKgq|qS2;:;>:652*.*+),1,..,)'&'4Wxѿ}+,,----,,*(.010.,++-13898;=@=:331/+)--//+(*,-+))+..**)+,,,+,,-,,-.//.230100//036:<<<:;=BCBEMY^[SJ=/$%)))+-0}zyurpspie^WWVVVXW^dgjrspkigb\`[hÿ»¾pj{üwp||pýſiCmȿĿültc?'005::83.21//53,-,+(''-0LpǼ"+-0/000...,,.,**''('&&)+)(,30+('%%'%(''()*)(**++-00,**++,,++,-,,-/0//1320.1100048=?>?ACFIHBEV[YK7("&***++.3}zzxursupgc][WUWZX`glkqtoiigh]SZjÿ}zbftfs}oȾh?nƷhs½[/3764/,($"%(&'*))'')2*BC@?<>NVLA9.%()**,03:~}{zwtsurnia]UTVW]`bdjtqmmjhcQU^ht¿}~ŽĿpadý~oZwxbapv~ĽøroYǺõ\N,)!>jj9!'&%-2?>>?==;JO|z{||ywvurqng_^^_bfkppr{|znWMDFVm}|v|~veUKKNJHWrxcTPfy|jP=Hqû|r_JXwv}KRļŹ}̿ʽZyz,75/ITU_l_(3422334444420../0-,,++*+,,)*-5972,*('()(()()))))*,/1243../433214568>>??ABA@?>=<?>DHINdȼkWMKba`}zwhP88HpŽytn`Q`}ʽJS¹q˾øk\ĽL'4/4LYbg|4/2320112456750./10-,.///./.--/5<93,*))**),.,,*)***,.1333101226887899>?>>??>?>>?@AAAB><:988878:BKVYJ6$',+6;:::;=>?@AAA@?>>?A?<;64333445459?=>?>F^Ǻ}rgQFJ`ciu|]\eggehZJ@-,26ĸ¹pfȽV!1.G`_Wm~}>14014348:98=DB=:887434577520232/+(*+,,,,054750,-,,./024764459;;=>??=:;<<@AA??=<;;:7641//000.---+(&#%')-038AKZj}~zuqromfgjswzskhg]TOHDFGGJNJJKLOOPcwǽseeb[jxyy\FLLTaV@,,1047>fž¼ĺ¿öf:6w̿zgN98[ƺÿ{Xyȿ¿H)11NWKO]fox|}y|^7>>GB1.39<<;>DD??=><8777<:62110--+,-*)*+*,3894/.....0026<:7569;?@<9989;<=;:9886310-*(*++*+*)**)*,/..025=GO^n~}trompstz|yy||uogcb`c[RTbkmkc[QRSVY]]eqļwe`iq{g==GIC8(-/1367Hx»ʾT=5bϿU1=f^6Ƽz~+445Hf{twul|~jOkrw}wfT@;:<:;9898563212210/,,-,-/3552000122012578555899<=;:::::988643/.-,*)*,,------./001258>>>>A@?==;;<<=;:8665311100012101244333101223235667:>?B@?<;::::9896420.--,,,--,,./011122347;@FOZhr{ttxz~½nd`\_dhjmnlf_XUSXdgwzuiVQV\X\[dpvnlxÿp/+.))*,.1656>bý±¼ǿĻ|ZELJBFFFCA@@@><=>=<7325541//00/.....2550--,+-,,,/123478999;;;:::9::8876410////013333455666689;>DMR[hsmUSRPOQRQNKKKLTdszqiaVTUPMNXpshjn|ÿU#$*+/25434:]÷ſſøľkPTUUULC8?W¸dewwmc_WF=@;>ƺ}th3@JRZbnsqnx~J.7@<82.001111121+--001.-.------,,.,,+***)***+/012478889;::;::9::97754311212456656778878:;;<@GLQ^gq¿xaKMMJJJHCAACFP`~lRDCC@>GR_o~z{oa\bmýg($,.265335R{Ļûþ»zYTXWVTQD;FKCaonsl^E;3L]E¹ýu|xkhGZdnstktzi2+1-*(**+++,---,./00/.-----,,,+,+*))))(((*+,.01257888:;::::::::977643344457688899::;::<=>>BHKQ_hpkJGEA?===>@CKUhtP<;<85:Iafdilni_WPZh¿j&(/4642/.Nr»ƿĿvd]aea^ZQE:IRKFhýo}lerqgX?:=2MgTĽ¹¿znjĿPepw~9"))++,-,,-,-----//.------,,+*++**)((()))*-0124577999;:::::;:;9876435667899::::;;<<=>>??ADGKQZfqy~rSFB:7038CIV_ftnJ57808>HMQSSSKGLasÿY!.642/*'Diʽ¼ynkgcekpmcXQL6GSLHbƾaowna`okYF63594M^XŽȾƻ`x^mr~4 )+++,--,-----------,---++***))))((((((*-01146789:::;:::;;;;::86656789:;<=<<=>>???@@AAEDGLRUbmvy~t]HLBB?AGPetlJ7532-)(-7ENLThĿv7,541/&%2Mqžsioi]juurj[NH7=NKAĽwEVflkibUHELSYJ<81Lejfhcrý˺|aqk{t '***+,,---,----,----,+++**)*)))((()(()*-021457899::;;;;;<;;;::76779;<===>?>?@@ABABCCDEFGKQS^iy{}~sf[^^_`ahmxſe>?@=869>GY[j}½}S*341*&'&2U|ûÿuhif]fqz{ogWD539?D|T'17;9328<9<=>;>dxxvsyv~ȿļŽso¾t~L*+++,,-----,,,,,,,,*****)(())))((()))+/023466789:::;;;<<<<<;:::9;===>?@AABCDCCDDDEEFFFILORZb}|wqnr|Ĺ¿ÿlEJS[addfjrľzY)43/)*&""3Zÿ{ypogiimpqu|iW\kv~zp3156<659:;;86Grxtuú·û~kľ~o(+,,,,----,,,,,,,,+**)))()(())))((((),/113567889:::;;;<<<<<==<<=?@@@A@ACDDEEEEFFFGHHHHJLNQV]}~x|fTikjkjlqx¼vX)42///%'#'1^}~züxui_blnnquwvtrlngȿ¼R/58CG=8743?>>?@BDCDDDFFFHGGHIHHIJIIIJMMNRY¾¾ûkknmnppx}qP'1144.()&')*Fhv{ut`[es||p\?1.)'-BYfmqqpmfsǽh04;DPR<+2U_bûļƿv{{y]|~"'+++,-----,,,+++++*)))(((((((((((())*-0023677888:::;;<<<<>=?@@BBEEEEFGGHGIJLLLLKLMMJJIJLMOORÿýžüvoqqtuuýpN'2220-))%$%,/>P^u||~zvwƿufXFBIlpV)////,&3C?@BCBCEFGGHIIJKLLMNONMNNNLKKLLNOPPÿüĿxqsvxxzúpN(110--+'!#%).279BR_hghotpkls}ĽrdZJHPe`N+222111-'&&,*5¹}Q5AKSW[_cƽfryolyy]mþzz((****+,,,,,,,+++*+*)))(((((((((((()))-0134677888::::;<<=<>@BBCCDEHIHIKKLMNOOPPQQPOPMLKLMNNPP}~¼º½}wqsx{|~únL)31/0/*! "%&*09@??G[jqylq|sg[OEA;92232112210/-,'[ý^5CPVTZ\nĹnplkrz~wim¼}~q ""(,--,+++++**)))(((((((((((())+/01357778899::::<=>?ACEEEEFGHJJKKLMNPQSSSRRQPPNNNNNNNOP~~}z{{|~|~zurty|}ü|hC!+-)&& "$%&*-4DJRWfot~jhŹxugVH@=7;9332222210/,+!zýƻƿ|d8DQSU^atǿſrY\`iotvwvdYtĽ|{nY`nz{ynV(%,,,,+++**)))))((((((((((())+.013577779999:;;=>?@CEFFEFGGIJKMMNOPSSTTTTSQPPNMNONNMOQ}|{{{xxxv{z{yyxy¶zoopv{w_5&'$ "$&'(+/ES`fjkmhSEy~{5$++,+++*))()()(((((((((('(*,/02467777899:;<<>@ABEFGFFFGHIJLOOPPQSTUUTSSQPPNNNNNNNOOyzyzxvurruuvxxxxuuvw|¾ľ~nggpy}º~qZ*##""###&'*.1;KQR\djs}|b`ûvdRRL72101479;99:<950.y]HKaigp|tĽq::;ANUZ[ZO5?¿wz)'*+++)***)))))(((((((((()*-/02467788899:;<>?ABCFFFFFGHHILLNPPQRRRSTSRPOOONNNMMMNNNvuutqqrsssrtvwxwussuwxz~rc^grv{ûzjP "#$##$%&')+FF$/G¿o{e+++,****)))))(((((((((()*-/024677889::;<=?@BCDFFFFFGIIJLMNPPQQQRRRRQONNNMMMMMMMMMssrqonrtutssuvvuvvtuwwuwĿqcX]kqt|ý|ubA #$###$&(()(5GMPZdot{x_vż|i_g\B:;<>;5133688875.yjbgw|{ul^pĹzjvyznJ "$8M¿~n7'+++****))))))(((((((())*-/02467788::<<=?@BCDEFFFFGGIJLMMPPQQRRRRQQONNMMMMMMLMLLLsrronprtvusstttuuututvuvyz}¹~paQTbjnsx|zz¾wvtjT*"%(''%%(()+)*KZhpuy~ezĽrhkfOHLMLIB<4136887523~how~~{{|yqj^NZļqz}}xW*5;Owºżqt,******)))(())((((()))*+.012357788:;<=>@BDEFFFFFFGHIILMNOPQRRRQQQPNNMMLMLLLLMLLLqqpnpqrtutussstttutttvwxwz{~ȿ}ss~Ž}n]JMZdnolpno|¼úwlh[<#%&*)()+--.1+?[juzo{üvqmgZX]``]UJD:114787621|̾rkvy||x~~vnrqicYN@@_{>0;>OoĿjſ%"+++**))))((())())))))*+.01235679:;<=>?BDDEFGFGFFGHIIKMNOPQQQQQPPONMMMMMLMMLLLLLopomnmoqrrtqrsttuuuuuuuvwxxy||{ȿ}l`hzyjXDEQ[gkcZZ\iƾ}teXC %')+)*/0/01/*$ 6Pgzzyk`bmvwusmcRI?2,378775-hʸ¼xgsvvxvuponf`\TI9<61[|`7E?Paºqzø{9(****)))(()()))))())*,.0123568:<<<>?@CDEEGGFFFFGHIJKMNOOPPPPPPPONNMLLMLMLLLKLLlnmllmnnpppqqrrtutttuutsttsotvv}žziYM[gttbM7;ERZ^YLEERpĿyo]A%')*-0/0.++0/-.,*6Nf~{yrz~xnZM?1+.36664/K´ƾ¿lfqrttpkrrcTJF<461*(Oo}~?4=>V`vĿwnQ$())))))))())))((()*,/0113578:;<>@@ACDEFFGGGFFHIIIJLOOOOOOOOOOONNMLKLLLKKKKKLlllnklmmmloqqrsttssssuutstsqoyzƾwcOCFMbȻ{hS?)27;U~ľö|ueM"$&'),020,*+*+//150$6Jaw}}yv~ugWK?3,+16866/+kvyùŽ¹\ilnje\cga[QF?:91*#125Vjxus|unqr}l+^{wm\=$%&(+.2324886-*15::-%)=M_qvwvsln^Q90-*.3860'ExyhvǼža]cde`SZ]XVWOA=;2'&>/"#*8GRW`dhguL8KX[et¿lpƿƻ8 ())**))))(()))))+-/113578:;=??ABDCDEFGGHGEB=:>DCEIMNNNMNNNNMNNMLLLLKKKKKKKjkihijhkllponnnnorrqqrtttuvxyƽ}dVeü|gbWOFCEEKRYfzzibm½{rlaM'!%&&+/-/4;BB@?<0/6763/,)+2>R_dXlzyhbjcQ-./,/3/')#0Zvh^yĻ¹ûqNX\]WORVNIQQB>=4'5I%%+(%!>XXAjJ7JT]cy¿˳Hǽ*%(()))())(())))*,.0124569<U^Y^nxºƼNMSSKDPTKDCB?=;1(CF%((&">Zd[Tul6AJTYm~ƴe>ùº_()))(())))))))+-/013578:;=?ACCCDEEEFFD:DmLCJKLKLLMMMMMMMLLKKJJJKJKefffilkklklooomnqqprsrrsspozļľux|rm}ĿĿ~qjcX?'+*++07?IH?:@GKQTZI71029:9>CFJNN^kogo¾¿qP341.++' -MR]iju{x}Ľ`?FF@>KOI<8;:<7/'C8&+2;GKUJ?[up;AKW[{ĵ}1Mƽ %*)*)))))**)))*-.124589;<>@ACCEFEFDD@6`aBGMOUbekq{z{¿¿oA871,)((>88=87<=;6-.$$%,36=:32U^fvl~Y;HOLg¹C(:Q#%)*)))))))****,/02568;<=?@BCEFFGC7Yl>CGGIIJIKKKKJKJJJJJIIIIghhjkklmmnnmomjijhgggffdhnvøø{sv||{}nTFVnxeU@!$%+16:BF?668>CJSZ`jr~|eZRGHSZ^bl»_3752+*0DKFKhkfU?<<:7,Esºn*59>>?B?87;==91$#&%%+.-0(?W`gmlf½v9ADEBTz¼zF)+6LĻM(***)*))'(('&'+,1579;;=?@BCEDF@@rU>EHHHHIIIIIIIIIIHHHHHHjkijkllllmmlmjfdfeefecbbcn{̽|tvľŽ¿sdjlloqqruuyvbG;:DchzveO4 $$)19@GOY`fqycHQ[][cyh^gquF0561249HNH<><=OJLH=5,#/5f¹¼w+37=9898/$#$$!!!)3MW`imjnwøG+24856;?9/&%)%+7<5o¾u:*15;97:;<;8630'%%#  6JV[`fmlp½M#/37872/-4B>AFUmy}t^A/BXb_D*88_¿h)&+==,Bq}z||}|?CFGFGGGGGGGGGGGGFGGGGxuvvunffhddcb```^^_`]`^\^hv|Ʒ{og^bpúÿ¼ýW6<:>M`ÿtW@B<500,)---00-,&',/68EF:3779@IPU^hoxyoĺĽsXR2/444/6:0/221*)'*1996:½½tR+34798989:851-((%" !,AOW]]flkuI&0/10.-..)'Dcu}z\Wjrg73Jqƹ`!#9Ui|||{|>EGGGFGGGFGGFGGGFFFGGF{xusplfhfdba_][]]\ZZZ]]Z^gr|¾s[U`l}Ǽ}M19DRm¿|fB9:731,**..0123+'.25?F;1654>GLS\ems{tiiļŻſtc`;,44561431/..+,28:962_˽ƽtd155469878772/)&'#!#&6JTY^\bgedt{A%,-+,.00),Xu|99b½¿M8Xnw~w~}yw}};IGGGGGGGGFGFGGGFFFGGFxtqokiiged`^\ZZZ[YWVWZ[[coy|a_j{ûpCAPc¾~nP*48//.,()-00441..2:FF7386;EKQWcjqy{ofnú·qb^9.5455545676346<;876/{Ż¼zj_2370.5775530-'&$"#%*"Ek}a5gѼûzoklhpysou|z}w|}}U@ILJGGGGGFGFFFEEEDEDEFonnqmiec]]_[\ZWXXUUVVV`kxývvĻü¿cEXo{vk\F7911//.,/32113::;>CA935CJ83>FKOX`mx}|ujbXOpxmP&15545655677887::::877v¸P%LNSbRGW=CHKKD?GVɼx{;OZc{ÿajjkmjrknutrruwzv{zvqy{~zs{}~}tGEIKKKLKIHHHGGGFFFEDEDEEefedc_]]Z[YYXY\]\_`cit}Ľ}zzþ¼|dTNE>;8-26778><9659>?EIA8BHOU]lu}yrmd^QId~vlZ1-455556677778899::965KͿļD*RaYIg5=?CAASt7EU`ieknlqllusrvvssq|yqp~}~~xy|}ywA=AEFIJNJHIHGHGGFFEECCCEedbc`^\ZYY[YZ\]`]_bkvx{ywtps¼v^PJA><>102229?=>:8;?@DFC>EJR]jrwob`XOJ^ü{le\?+565666778778999;:9987iǼs($3QE`Ƽi.7884Nºc5Ljtudqkfpojippllvuvzyss|ux}z{{x}~yzih]J>=CHEDFEFFEEBA;9989@dcc^\^_Z\X[]\]^a``cpyþxqo¿rSKYcmYPF??;>:94339;8;9:99@FBAAGNYfru~rUTKGjtjdXD,565556777788999::9;97GƿŽc&' &8¼ÿ](00,cľ¿~I?R^q¿^flkikripwtuoxwsvtpz}xxz|x~wkVOSE==>@FFGXvnD`bb_\\__]]\^acegjiltȿvgboƿzV7IZyĽgUPGDB;>EB:;9446979;9:EGGFMYcmuzĿzNCGzujf_R@-4566667888888899:::78:ʿ³O'&%9¿6+-(sſ|z'HS\dbihmpfosptv{qtywts}|yvzztvz{~}}{`aaa^]__a`bcdhikijrſya\fsýzY678957>:9FQOLR`ks{{CGqstrkcZSK;/565666788888888::99689Zø²v[U;#(cõm,84y¼r25GGmg\glklneqwrrxxvtyxx{~~w}{rw{{{voqosxz{x``aaa`_\acfegihkmpwÿyd`c^iwT66;Iqºy`KCHQKH=7;=A<@8;:7549<@IUPPWdoxŵſwKýtZ\a`VQKB42656676678888889;;;9;:;:zĻ̾~cinlS4T¶;55ÿtH#4BLuc^eghlmfnsvut{w|vsty~{yxqytqx|z{lryxzuw{wzyb`abadb_bghjknmoqw¾}uobUSaxȿúsL**)9PxvtfNLGJPBFH>7<<9?HBB9499>FLWSRamt|İtiIPOJGB:145566777788898:9:;<;<:;;?·ƻp`jlnkhÿW:[ƾ}w}}W")0:Ks|^Zchiiiihtsuxswtwujzz}trwvtu{xoyyw|}|sw`cbcadhheghlntrrwx{ph\SSXdŽ¹rJ$'!'=Musii\LALPCELJ99<9>D??;:?>SSG@BEB;64966;=CFE9AQcfaku}øżýùS>EB<36766888888999999;;;;<<<;8;8vƿqhhw|yÿĿ¿4¾un{T&-+*'"Abt}|dTZ]bebeilforqooiwwrk}xuuxxrjjjxvkq}y}{qz_bejtplnqrmptuxpllyĿueZayûürM!,(!(6AX|ulmlW@BZUKGGKKJE:60354786789989999::::::<<<==<<:9bĹldqyĿɽy;ľj}A*),7IRPJHGO\hpplisr|}gZX[][accehjjmmnqsiowhy|rmstlgiy~}wmokjv}cdhjzyiotvtmlmokint{¼udaký¹rO!*$"",4@X~~ysql[E>DQWWkz}yqf\M8+:9=><:BPhmqwĽŸ÷ƿ`04678888998999999:::::<<<=<<<;:Hº³z`^u~¹oJ̿Ʒl{u,1;LYckqqneF4CHJP[~S_lnf\RSZ\^_^`_dggiinqmmptnikwmpdfpo~ql{z|ehklvunpmmpljgggeddjsºþmfg~ĿzmM%#!" (:B^ryyoprmaRN[mttv}tlgX;457==;FcxrtyxqihdbbhmmgxzpfV9/5989:QqþžX*7999998999::::::;;;;;;;<<<<:>EQugikn}÷¿gȺr`nty~}c7JZiu|{qFAB?0 -fea\^`^___`a^`ffjeahgcbf^mzgvxtfjmrtnjaadadihe^ZRLN_rý~lR+&$#$%'%/:C\yvqpk_OOZcls{qdM35778;Vnĵ¿ĸa+899:::9::9::::::;:::;;<<<;;YtҿܼzlG8699;;::998899999::::::97:BIYVXZ]d`RRRSRURWccJf{hTù~UE=Yýzw¿¾ygyxmjQUWRV`jfjlqqovvwyz}zpx~~pEOQPgffec`bfjlWMS^pýûwv~x_TQQMKHJI@983-*&"/Ll|damomlgc`XMD80384.6Po¾æؿuxoX359:9;;:;:9789899::::9::87;FTYVXXWe\QUTTPU\b`VF_{iVHxŻi;7;QożyaW]dc^XUNF8.,...-1?ay̼jf\>09:9:9:99998788899:::99987>JZZUWY]bSUUTROX\cUHM^yvdP>DgĻz=1;944H|FxƼ~zxrhomydZ\fmsoqxx}{|vr{}}}DMPOPfecbaadgeSNXds}m^SP_s}rtz|xvqjcZOLQRRRMGDQkǽsYPVVQME9.*+-+/44Q_^Sa|ſ]=˽|~{o^mq}oedhrsu{xwy{{erz|~||@MOPPgdcbbdg`UMT_q{fRM]v{eN;*.8JWeo|}th^X\_^]YOOcxxWELPP?-('&+,288;BLapykɿqc;0979:9::9:999999999:865300/5?OTQVSYZVSMQTRPVZZPCKD`r{~}ueOjeM?g½tC-/Ffuyi|d)W½vxvzZjpt}wqz~z}lpv{|~~gBNPPPdca`beaQLP^m~vfQCCFVlÿp[D*2>M\nulafiecd\aqøtR;GF>5(#$()-26=Vvýcºo\`wfa908989999:999:9999:87745@QY^ejlcWOOZOPMLPNP\]WPORQANelttr}|yywkZKWWG4Gfj2'-Mn|hcisP*)h½r{sqx~^jktplr{}~JHNNOPaab`__TJJWhy¾}pklaKEFSax¾r^I.2@Vi{rqsk``cak}ƻ{fA;:64($%))),FTjĿtdR73?[n~uc\\^onT4..+'-,+'%3`½nl}l`a_Sq½ĺ¿v`UVD8978778888898999:9767YrzucZQUGLJG83CBHP[]ekmrusttmknl]NGTX@1CUdb}cW0,Y}~~{xg:-1+;geylbmgtbgrrhq{y}^CLMNNNa^adZLIIOarÿ{n^VRI=2?Vnria[Wd}}jW:#" $%&6j_a^z~zogk`OIGQpq\H:2/45;95777777767888776AĿVA<:=F@=5/=9BJSTX[]\ZVOFA@ME'K^diiecsa=""# C|jN"$&+/1130kzgflkuŻ}lfs|okvREKLLLLe_RJHJKJScswj]QIGB95E[or^=2>Pn|wrcZkvcR4#"%GuH==88CTXLHLPMJE@9:>7!3W^bgijekqkl{x^=',-)'%pyf903653330c¾wahprtz]lxsilwv^CKLLLL^WKIIKKKRaqƽwlcWOEDA8/5IYpžq[=3@Ttzwyte\hɿþ|n\L--^÷d<8EXpyyumaV[kj^aTLHOWZUTSZyrcUD<42,,)*058666677657664Aoo6<<9AD;=>5OUOIDBAA<520.&&"@Y]_ejlfkvqi`\XO<'((+0*#@qJ&25323/#a¾{|}~[lqsyp~nkxxljv}}}MDJLLKKTPJIKLMKO]m~ƼvlaXNG@@>61/5FYo~p[73B[xrffec^cy¸ľwiXH( 7pwK2GF@HOQJKS\d_XVSPKNSZSI<3Dh~k_QC6/8DX`T9(276566666555AĿO4>B@67B@-8?DIKJE@50/-())+GX[[`ihienplf]SB-%,,+0.9ovY&*---(TĽtytXott{vxpvwtnx~~T>KJJJJIMMLKKLLLKUeuƽ{oif_XPFA=<;642/1CZrü}lO84C^zqcY]c\]qľwfYG%$''F÷xX0:87765402Kb|w_F;6D`{q_URSTnxĹxdV?!%.kļŽs_:7?;96631/4=EKPRTUVTNLB8634.Ainu|v_(385456554WÿL;?'09;681Rk~qYFC86F`wrdYROJ?YƳ|lZK+!1m»¹t`NE;:755431.*'#*=IMJFA<::;787624\ksyrim¸T&145412:Ž{7;-,;FJ=/ )<8?>.,)19%&93'+56CTUSQGG\NKA3-,.>9<~j)!'(-/!j¾jr~~}vWKNUast|Ϭ|sty{~~>FGHHIHHHMMMNPNMOZitȾ¾|jE-488999967H\xƿ~hUN<17WjpyobZ`ZD6Orm_TE & AüĺnWIF@>536432.'(#*:CEB?<=:6;9850?\jmjd|C'35541?;:Tqv`6'&020<3056065).-.>89>>77OQJA0/,)*)&?u8 )*,+$gjsz}lMJVZP_ru|ҽx}{{zx9IIIHIGGGMMMMOLKSbr~xdB-6799:982;Nbx^F=3:S]bk}ymbbj^?1Mtƶ~}vg_SK<"PźûqaNAC?G@22122.)($(4=@A>EF;:8550@[_\e'0464/BýGl{M-+,;.*3578/-63&9F=82.5DA5,0))1=?,@yE(('*(_þjunUCGMOQMcos~yO@GIIIIGGFNNNOMMR[kxo[;-38999745F_toL:BIUUTZbr~sfcgbL93QzǶyrnaTF ! $TŽ¸kN4;LA0.1/*)*% !)2:@JL;:96245IZ¿ƾzA,4310>Ǿ¼|mI$*29/;5142/1(!'&240/+*//,41+:<<:(CzK&(()%Khy\,',+(*'!!"$&(+:B=@<94-36R`-140/:|ɿÿ}~B-731764++0&"-30-&&%(9D7.2+-9;.-*Ew|wN+*)'%.ºaffP:CJHIRQNJK[au{zK@FGHGFGGGGPPPNNVco~ÿuoeWJA7887E[osUIVUROLKLKNVj}~wnims\G8001HpĺĿzn_B$'&" IñpAHZ<&%),+$$##&((**+7<977410<ļl/.31.6qwk&05.273&(/25<=/*8>>EMB21.6206?5?Ai~}pO''*+)$a`GB;CCAJOLQQORNKAJTRI^~lC$%)+*(-y:@DBHH@CLKIMPNZb^Wmz9DEFGGGGFGGFPONUcn|ÿ|jXUPIHC>=Ne{ývT9KLGFECB@@=9;;;@GLMIC9;CGXu¾¼{m`J $#&%5týpPME66;99659;=:6651031/CÿtE&22-/Kĵgs~]*'60&27,9EKLECEC:6<8)%*15,18.'-Pvf. !$$ P?=?AAHDCJNLLMRPOYWW]l{}J@FFGGGGGGGGGPNP]ix¾n[UPFADBASi¿lKSijhd[QF=7765/.,()'&1EWi{naO( # #%-[ĽfKBCCKJEBBACB@AA8'13*`½wF&240-8m¹ÿ¹hw~{sF"#)7<@HEHLHC:(%\zS!$!$+66uJ9?BADB?EGHKNPQONOVY\dgps:EFGGGGGGGFFFOPRdqÿp\ROG?BCEXlýſmsf_T;,1200/.06MfĿǸxn`K$&)%"#;}û|TFMMNOLMKFIIIJO6)1$n¿ûzF&240,.L}l{}~D2CD87?>=-#"!ak0#"!!->ACG~¿L6=ABEFBABFIEIMPTZZ[^_``puk{9EFGGGGGGGGGGPQSds~kXLNF:;=396- !_oD " ")4?@DKKk¾ý{A39@C?BCBBBELHGKPU^aUV[[[\efr}}s_>GFGGGGGGGGGGPPScs»wbRFGE:9:Kcv¼|rdJ*/2+3LfǾô{ocP0&&$()&%3gÿNM\aaba^YRQWQQE+&sʾĺ}U+.().=BECDMGGNQN[XN[fXa_]dbpzu?CFGFGGGGHHGGGSRSaruaNBE@<99Iaw¾tcE),5Kd~¾|rgY?$%%%'&%'5nſtFM^eihjhaZYTWV7%nȾP"):IQTKWxk7EEC9$!"! ! "&Zrxt_& )7EIMTP[_byps8EOTXUPKJHA@FLFKOJIWUOOQQXX[_`cs~|QAFGGFGGGHGGGGGRRTbp{r^MJF<:98H^v¾ÿqW46QhľzuqhZF"!$'('&(+-(6ze?MTbinmeb`[\[K2`ŻpGT[XUPHSo{DD=&!!!!!$  6]XlzhE -AHLTT]db`vymwzh!$.HGGGFGGGHHGGHGSSUdnseYTUJ:::9E[rxhRQhƿĿribVB#&'&''&')-,*(:|¼»{J=AJ]iqmgccbaR=PĺaMRQQLFVvP:(!""!!!! $/5<=3#0=OUTPYupj]&"!2>ISW^c]brpjsw~c""%728ELNMMV[]_``decba^cfojcimtq{|{yuy~??BMYXWZ_\R;/tȾ½ZHKHGRrz~~ľw9$$$""#"!! 1htdNLSH1.5(/"!'&&$(""(HW_fclsprifus)->DDDDDE>)! 3GYf~v}~rqozz=JKKJIHHHHHHHHIIHSTS[jw}{lQMA6;;7>Of}·¾r_K9(,4Mkz`9 !$'%%((),**,,,,,)#$TǾe2>>;==Mfw~{wph`cǽqNLEDcrtwy}¿y."%&$###"!!! +msI""0377 '$$&"!$* !DW\bdhfm`j{j.<=CJK6 !""""!!!!"####$%%"!7eootuqw~|-...03BQW[[M1"&+(()#"&*,./-0/,+*''%(%6¹ƿd/==4ChrfzĹþtJLBLimmqt{`%'%###"""" hzL%$!247<!)(+(!%';UX\ednohz|S?HEA>=><5//-,.*(*..-1/++,..,)+.*aƾ_-;2Gsyhaz¾¾lFE9Lcffjry~syżS&%$###"""Pt1#' +.70 (#/."+#!/OS\cp~o~uCCDC?====QS]zx{v:AB>>===>>CDHLMLRWSC*!""$$#$%&'*,+,3cmjdlokkq~y~BIJKLKJIIIIIIIIIIIIIITUTUUSesĿ~p_ONFC@>;:725EYożļs^G.07BKSXZVRLHND70-122/121,,*-2552251-lüN#,YyvbRF>;35KU]cgjlid]b¿L&%##"""_w2'%-$&"""$-(!$*HQ]uyzj9DDDGJJKKJHCFKIIOV[^Z5 ""#%#$%&(+(Aakkkeijlojwx|}^DJLMLKJIIIIIIIIJIJIIJNOPPRVfoyufVJGCCB>=<975:H[lÿ¾~p\B,4?KU]ba]XQNK=2.*1<>:;8523323135103I}Z!6j{xeiýl;:4..6<@FKIGFLee&%$#"""*s~T&.'$ %(#"#!$&(&(,9SlwzyCCJKKMPPQPQPOLFDGPTX]b_5!###$%&'),,9nsej|lp}{n@JLMLLLJJJIIIJJIJJJIIIegghhkq}ǽwj[KDBCCA=<;=>@DGVrſtfP8+5AHU^bba\WVOG?4+/@GB<:<<;;:8878994fºud6Go}}^jûźP9600,# "!#0M|o%%$$"#"@y}j=./)$ 2;,&!$ !"%)-0.SxsCCIJKLMNPPOQQRQI=BNU[_bjb,!##$%&(+//5ztpvyx}s{zj?JJLLKKKJIIIIIIJJJJKKJJu~ź|p`QHCDFDB?@CELT^oþ{kZH:0>O^bb_Y[\__YOD;206::;:>>><=<;=>=;4|ýkgQTpks¼Ź¿o6910-$ #%%!4Z¾y'#%$$#""Sv~pTE+/+":>>'!&34)+33,Rt|~zg<>A>:;½{mrZSp}ŽµD322-!"$ >j¾=%$$""`r|~]_C11(5:40BE@/*696/-26619Om}{ld^J5CFEFHLNPSVXVSPPRSY[ROW]eirl&#$$&'*-23-yzy|{u~~a?GKKLKLKKLKJIIHIIIJJLKLLLLxjYLGIKJIILR`q~¼ſſsb_i~maWTNF=99FVUTPB42965;>B=:@isWQmsyb,34* "!BsÿN&$$"!Biq|~bhW681!14$*>DHMML2(,/10/126<9CQoytiUNH;>@?AC̿ĿdbMQlw}Ļz8.4($FÿX&%$"-dgp}zjx_A;7)*);O]ddh_MKC5%'//-05@GIHOOSdq|}{|eVYY\XPJIQUUSPRUXZ_`a\W\cdluK"$%&(,.041Dy}{R6@Vbfkuvzyh?%(5K[^Zcn}PQVY_bfehori_dlnsi)$&'),/1598?wqP=;AFIKLLLKLLKJJIIHHGFGGHHIIKKLLKLLLsigbZTTWSOJKPX_guwh\Wbruigupho¾J7Ierisſƿq8+'$4?sž7&&&fpmeivxzuJG?*5@:RckpuqzqR$(@MP\fpxOY`cgggjtvpefmrtuH$''),015:<<3}c8;BEFIKKKLLLKKKJJIIIIHGGGGFHHIJKKLLLLLþwu||ukbYMNX^k{zl_X_r~lUM^¿|so0;Dewgoĺ\)-%-(0[Ľt' %&Cspoiivzwzz{~zGG607BB\lrxx~|s^3#COYsoiXcgigiouvxlgqvvw_#''(+/16;'36;EYmx}tfA&>UvrZciijhry{zojs|}|n*!'()*037;>FKIBpgBJMONEHjt[K;5;CEGHHHHJIJJKKKKKKJIHIIHGGGGGGFFFGHHIKKKLK}rcUZ_XVVcwĽu`I)',)*5DTuszľleĻv@;IMWlytƿwA!&& -_ƿþC$%"duqooooljnqruwry~S*FY`dfuxpG+a}v¿v_klimxyv~|q+!()*.03:?EKNRQRNGFWjz~m{iXMD?:8%%#]spppqwpeehmttv~` 6O\gnknt~|gCFy}}`lnkl}wq*"*+-/13;AGJNQQQQPNJGDCADFCDDEFFGGGFGGGGGGGHHGIIIIJJJKKJJIJHIHHHGGFFFFFGGGGGIIJJJ¿kL1/05>TntbE"&)+++))(-26AUq¿ľ|o]roB!2OSYn|ȾƽmK$&"*(!/YĻ{/ $&#Lpnrqqxuieebhqw|j&"=RZgqttrvwWJNljlkp|}q*$+-/124:BHIMOQQRRRQQPPPPONMJIJIJJIHHGGGGGGHHGIHIIJJJJJJIIIHHIHHHGFGFFFFGGGGHIJJI¼xeL=BBE>BP_xzfL&"*+,,,+***-3De¿ueVhö~U/""@SXavaM /,"(&(@ch$#%#;inqqrwtlhhefstw|j%(>PZdpyyv}ydYQM{¹vfhmv|~k#'+.0346;BGJLOPQQQQQRRRQQONLKJJJJIIIHHGGHHHHHHIHIIJKJJJJIIIHHHGHGGFFFFFFFGGGHHHIIýwriq~[[{ygH&"(***))*,,-8ASuƿſ|m_VWgÿx^6"#$""DVapſfZBT[]\S;('"$:nK )0Upmoqsonjjmdkrtwy{|||~T)5HZgoz~ukibPIrþ|ajtyzX&+02589>AFKLOPRSSSSTRRSRPONMLKKKJJIIHHGGGHHHHHHIIIJIJJJIJIHIHIIGGFFFFFFFFFGGHHIIý}y~yunZ9%)**)))'',.:CIeqhvÿ}adu\C)"$%$!>ib`e_jok`XNA)(Oƾu-$2ccforolknpifrrtvwyyz|}{wwy|~u0"%-?Vbls{~ypk}zxwtjOQþwfmtww|A*.148:Ldvȿɼ}taH2.221+)$(('%#2Eh¿ødx}|}yupdUF'4dƾ}]utccbbfhiddknqstvtvy|{~~x7$!1LXafpz}~ws|{jzjTtirpu~~yM)046:=?BDFHLMOQTUTTSSSSSRPOONNNNMNLLKJIHIIIHHHIIIJJIJIJJIJJJIIHHHHGFFFFFGFFGGGHGG½ÿlURPLGC@9362,#$&)*.7@IdwyòƿpM83))-01.,*)(&$#5Cĸ÷}s|sc[M3&Mżr|tdad`aikopquvvwvz|~Y=9'!#;V_fmsqlryzxeb·Ŀgrr{vz}d)&/47:%Bi~v^b^^cfkljkmotx{|aNRQH3*?PU^cirzwdlżdrz|voz}n;#-47:<@BDFHJKMNPRUVUTTTUTRRQPPOOONNNNMLLKJIIIIIIIIIJJIJJJJJJIIHIIHHGGGFFFGFFFFFGGGG_LOIC?=82*&$(/6>DRmknzö}u{źsX=$!" !!! $%\½~{{vo^O?':Kw[cc_^`eedioquwzzlVVbcb_SA'$3@W]jrx{|~frerwyskrwymA#/36:=?CDFHJLNOQRTVVVUTTTSQQQPPPPPOOONMMMLKJJJIIIIIHHHIIIIJJJIJIIHHGGGFFFFFFFFFFFGGG½cNLIC:0%#)0"0369<>BDFGJKNOQQSTVVVUTTSRQRQQQPPPPPPNNMMLKJJJIIIIIIHHIIIJJJJJJJIHHGGFFFFEFFFFFFFGGFûxobP=-/>G^nnr}Źya`}iM*$! $! mǾļɼŻ|o]R;%%0AQiƿĽkYehfcceiinqtv}iJNZclrvyxndV[6C\flrttz~xorws\h\j_UYj^L@,&0448:ADFILLNOPPSSTTTSSSSRRRQQQQQQQQQPOONMLLKKJJIIIIIGGHIIIIJJJIHHIGFGFEFFFFFFFFFFFFFĿyk_doxĶs]jƼƾzoW6/*,(&&(#!LŽwlZL'"$$""#*67>IV`ly[EYelmj^RVn\^hkqvz}MCP^gkpw}~mW^L5@O\bkqriYEGEHWZÿKQVTQD'&01479:;=?ACEHJKLMNPPQSSSSSRRRQQRRRQQRRQQQQONNMLMLKJJIJIIHGGHIIHIJJHIHHHGGGEEFFFFFFFFFFFEFü~lfq}żncnƾwd@2696:>=>6Xüx|rf^W5#$#""""&(+--4>MM2,.0.*-8\ôYairwy}~PAABDFHJJLLNOPQQRSSSRQQQRRRRRRRRRQQQOONNLMLKJJJKIIHGGGHHHHHIHHHHHGGGFEEFEFFFFFEFFFF}qq|~hX`пû½~nQ573/7A@G>Nȼ~sow{}u{uhcc\G!"#"$$$$$$##$&$  !&8vĺzYcmqswmE:IQYcfm|]d^N;F:79;6.0>:4*0naWR\ghhf_PHPnt[?`~spjmry|~{mcdg`O!""#%)$#! "$(HĿe^jjfR37EMU\dpu|}frT"BF>@BEFFGIJKMMNOOOOPPPPPPQQQQRSRSSRSRRQPPNNMLLKJJJJHGFGGFFGGGGGGGGGGGGFFEFEEEFEEDEDEEFøxpoms¼{lW?SǾĿz\D?;4*&!!!tºr]H5/10-.,)'%-CV_[B4Cv~rfdkruvmcaffaT1!#%''!!  !!@stED9..9=GRZafnz~u]_S!#FGCDGMOMMUZ`cfmiaiiZ5),/1368;=>@DGIIIKKKMNNNNONNOOOPPQQQQRRSSSSSSRQPPONMMMLKKJJIIGFGGGGGHGGGGGGGGFEEEEEEEEEEDCDEEEýÿynb]cp¾}pZD5eĽľz`ND:;0%'(%QrZ=)$)+%1?8=>X}lbhh`adec_V:!!#%! :mžü~0'048?LU\enfwlWC!("$AEBHKJHMSYadlolh|mortj= ,.158:rzĻ}eXO9;7+((%$/}iO8#!'/.  0=5IqþbX`abba\S7!!##-Yſ}/)-34>FLU[cps|}{mC(''!*:;FKFGNQX_alnljbl{}rovj4(148;=>ACCEGEDDEFDDHLLLMMMMPOOPPQQRRRSSSSRRRSPPONOMLLKJJIHHHGFGGGGGGGFFFFEEEDDDEEEEEDDDDDEEErbRKOXetukS?B}xýºg]V<67/(''&$]ʾt]ID=-$%'&@:IzýgX_a``YO+ !! >|q'-014BLQT]dqsuwu|xZ9$&%'=57@>HMOW\]ckjicb{|}zssw^*59<=@@CEBBIScmtwtfOFFCBEJMNOOOOPQQQRSSRSSRRRQOOONMLLKKKIHHGGGGGGFGFFFFEEEEDDEEEEFFEEDEEDEEE}tdO@EEJS_syneUK99Y}soǾĿia]E33-()'$'<ɾujS96AACC?GYgqvzukfZLADLNNOOPQQQQRSRRRRQQQOOONMLKKKKKHHGGFGFFFFGFEEEEEEDDDEEEFEFEEDEEEDD~~~ſubK==<=:>CN]ppcdd_RKA=86B_~ynixĽjb`D12,)'!5WhƺxgW;1>BK5CMj½ºcNUM>')Wxy~W'018>EMPUWX]erxy}v_&3$$ &(..*@QPQNZ\\`cihfupwM5?BDED?Uiqvzv{~~z~}mLALNNOOPPQQQRRRRRQQPOONKGEDBBCCBEFFHGFFFFFFEEEEDDDDDEEEEEEDEEEEDED}}}~}}}ü|p^J51333//09FUfluyx{z^[[XRNLGB@BQd~{qjbk½~pl^G62/+#Go}sƾumfU< (>D7##?S}¾¹R7&#-&1dºqx~b%-.7:CHIMQYdnq}|u[$8'!!% !',AQQQUWVU\dikfqzsxX8@EFB?[muy|}}}}PALONOPQQQRRRRSRQPOMKFGJMOSRPMF=<@EEFFEDDEEEDDDEDDDEDEEEDDDDDDCCC}}|zyx{|{y~uiZF-+/00.+.17AUcgmk`WS\b]RNPKGFQDvyrldXVXtuvvbO;30&ExÿxeXOD%( @LKGP½d$%.*7süxu~j&.-/05ANSV[`cmxz~zqO$91"!!##++:INOQQSX^egh^Ik|uuU:ABB@Zpt{||yDGNOOPPQQQQQQRQQPKJQYdow||lYF;>CFDEDDEEDDCDCCCDEEDEDCCDDDDDD~zuwvuquvtu}vobS@*-1231--/28FOOOSRMQX\JINTSIFG9~upic]VKQŻspcL54.4oyhUQK;  5;=A{u'&/*=r{f*2)&Get|qfr}|{zyrnA/4$"!"$"%&05:0,=PZZYO18}wmga[SRKFAZ|aJ533,\l\^ec\Q>61 10-**+-$0uľ:!*.1/%!Hskf_XQMHA?;Q~T45524n¼eZjU:+)"%##$&+&3<  ,203/)=iüjS87ayor}~|m#:1" %)! +3'!"')+#=>BEDA;:>n}ojdZTNID?>:7`}J3873Zxt|Y/$&*)'**#0yüÿwK*40/41$.;VcJbetv}~xD76'! "+)&"!))#())$=I@S`lrx}uo>KMOOPOOOOPT[bhov|^@>ACBBCBBABCCCBCCCCCDCDCDȅ-:;:99ILMNOOPPOOOUYbox~R?>BBBBBCBBBCBBBBBBCCCCDCޢ7755358877FoiaYRLFC><:73:qŻ\/307|½i/  " !$(''WN<+*# %,/351.("#BBBABABBCCBBBCBCCBCC~yvtsw»zv5Vino~udQCEDE@=9876543118ZûsF#)-,+uǿS&%#(-(""$+I¾¾_")541.+(-;9-Lm}oZXɾ¾qNh|C'70'%'(&% *,))''((+**)*,=@=HNQNkqv]imrq[@BHOPS_hwbC=ABBBBBBBBBCCCBCCCCCC}wx|wuwUmnYO=;>:87755542/4Lm@$+,-,,}q2!*-2*! $%'3wÿ}D,((58(*+"Ciz{halƽ{OPhzO "&17)())" #(,.)&'*%')*-,#1EA?FB\{zvimp{vPBCDJR_hwfC<@BBBBBCCBCBCBCCCCCCB|xyxu{¿żzws_QG=967765442/.@a¿b3)+*'(+K.+('+#)Nƾÿi+ .3")?<(*0=Ŀ\"! ')0gú}S&+'-)%1BA,'Nmyvf^o·~j9Bh}U   052/.)( "%)(/03-$**)'$,;;8mjptqhpmIT]gz[?U_ejovz^zf3.6)^ȿkuNS[pO>CEEDDDCBBBBBBBBCCCļ¾xeZLAjgJ33342/PL)1//+5bǵ½dB/Q\\hw{}~~}{taS_jOKV\y¾iUegoyh/*9L_r~|VAi*  !! 8Q]ckxt|xps5,)GýrmuNJXnT>BEDDDDBCCBCBBBBCCC¾yrui^QDr}hJ22451/JP).+;cþ_/%8bszpZOY^\ZYYUI919GDkcSZbuf.!-=HXvz~kMBcxĽ1 !!  GVamy~{xu1)7¾gqyTDXmU>BEDDDDCCCCCCBBBCCC{zj`SHt{`B02341-CO*.Yþc,KRenlZS?LU~,! ! &QTcs}{l'7^Ŀwihp\BVmR?BEEDDDDDDDDDCBBDDCº|rj`TSnnS<12310/@L@xkDh|~kiM:1C_YTL=Kd½oOOQ_mypU&#,TXcr@jrknzsW[ej{X@Ri}nH?CEEDDDDDDCDDCCCBCCqf\MCRx`LB83-)15/[ļznsW4Ehl`fYT]^hr{|pV('0@IIJcq~~`/6Dbyny~}qK"?RVcn|RFqż~ar}_MV`dm{P=Ndw`F>DEDDCDDDDDDEEECCCCƽtcXDBHYjw~l=IGVq~qi?JVak|c1iľ[iu~Q?O\adn|wH?JXk}|RAADDECEDCDDDDDEEDDCBĺs^S@8BY~s]BzĿƿwqQiksvJY___dluyyvhM%!$'4AFQamw{yk=IIMduwwKUaon!a¿ƽ_crvsaC6BPW]ds]ADJUfwdG>CDDDDDCDDDDEDCEDDCBǾǾmXL?=?My{qƾ}zS^j{LS^cd`cfieS< ""$*;HMXemrvwvv|{|~u~aEHDEQq~qnsXV_jy~oyz\.<ý´KA:,'*.>EBCFO\kz~V?;JW_aotRB@EEDDDDBCCDDDEDEEEEDEsZPKGACLu¾Ⱦǽp¿i[nſQFR[ab_XI$ "! #&9JJPY`gllosy|ztryi6=CE@??Kcuwvmk}f^o{}}NI5¼µ{*)',21-8B???HQ`kozz[A59BS]citpR@?DDDDCDCCDDCDEDDEEEEDE|jLNJF@@Km~ĽƹĽhp¾qYpD/=DCB;131,% %.30'#;GMPQV`eimpmjp{~~uL469:98:72Bedu}{xxbq^r|fMVF_Q!+,/53/39;?ELPXbn}uqjQ<59<;CPX^^gt}|~cNC@BDCBCDDBCDDDDDDEDEEEEEÿ}rZDHGD?=Ea¾þƿl`½wUqž½w3/7;<=FXaeik\EK^pzveG&8ISYRT^dgjnsv}~pNINJ=/3110-=DEINWZ^eqwu~ytp{[r|{wOPUPDĿz''**-33149:@IS^jsy{psvaPE<=BDC@AIPW]\`mtw}o`OECBDEEDBCDDCCDDDDDDEEEEEEE¹yhOGJGB<8CIJGNWXY[]VHGIIJJJKIIHIIIGEFFGKKFECA??BBCCAA@@>@BDDDDDDDCEEEEEEDEĿsZHKLKGB:4CVfþúʻĹrytwȽ}Muôk>HTj|WS@<=<=738BJLQTZ]^YXB$+;DMT[akqt{}~{zK^m~TLPNMLDGT,-./-,/38;ur%)./..+&.678;AHIHMRQKHIHIKIIIIIIIIIIIHHIGGGFDDDDITWZ]_`aaafdYJ;9>@CDCDDEEEEEEDdURUPPPSW[WNIO\`hm{ûõźs?)**6úżbAbyb|ÿz_gcK-7?FHPSTW][]][XQ."2DRXclpuz{{~kWg|s?BFC@;<;85[:"*----)$-5555:?CFIJJJIIJJIJIJJIHHHHHHHHHIHFFHLRU[_aceffgiknqnfZOC?>>?ACDEEFDAB~{zy|{uaY^^babggf^VQMICHSpugºžŶƿƿtB#&$)+oƽſ|L:M|½zejd;4CHOOSUZ]]cdb_\K(/ET^gpuyzw{vUk|`498=963.-5ASiszwE(*,+**(%-421/36;AFHJJJIIIJJJJIJIIIIHHHHFDCDJQTXY[Z[]_aceehinoooleWRMB;:=@?@>?C~}|}Ļ~nec][`^\_a^]YTPNMIIKMc¼ƺ·{÷pC&'%%+/Sn83>V·wlqd9CIORVYhjdjljgeZB-FXbivzxvzvPftoG/:?=7=UpxLAQPbyzX1&')(''&&$.851.07@EIHIIJIIIJJIJJJJJIHHIGGEDIMOORX^^WV\]a`_cejmmkswxuqldXTMGEDIMU||}sw~þzY^^[]\XVRLFFGCCGI]ƺynxɾkYS?(&$'+-/=ľ¼f+-7@Xÿp|~W@PV]bckjnqttrhdS2C[gmx|wwsJ[gquuQ,6^jGkZ40:JVahg\I/!%&$##"$&,.3=BEECDFGIIIIHHGGIJJIJJIJIGHJKIIS\be_\_ba`bcbdjmkllonlmqstvyxtkgfcdfkntsu~v|ЍUWT[\ZTRKEEDBB?@[ŷ»wqd[½eMEgƿUN`ggnqxx~~{xzraBAOhyG((&)'),*(.2+$39@=iÿa!#%)3=Eiû}¸jIXejlqvvjJ6Uirpw_=]rnW6eu7!"##%,+*9kþľºvLXaaeow~~zmO.OcgqF##Cbv`1& oij_1@BDGHHJKNPRTVYYTLC@CGFB>>;>==@>Fu¾ļywzsX;@KQP_ghc]RG@72,.1.*(%&+.($-=AA-',AoĹt@ $#$#$'#"'5auûxWcgnmktuzpP!9S]v~-"#%;\q|pN%+'^¿¿<;@AAEHKLMNQRUYZZYUPJC:9CPW[\gxuUVec\_eid^_\WTTYY]decb`]\`aa`gqw}|{pidbkyzyxwsqommmjklkit~xkc^PGIRLHVsĿ|qaNIFFC@>>@>:Mw¿ºricJ:GPUZ`rutpj[MF?8124,''%(**%):AD4$')*Ob]emqwƿa4 !"!!%''$ #/N~mo|x{žu\msvxxxxvzoG"&8Wsyl!*.1' -EVZYUO@+$.%Uüút1C>>ADIMOPQRSTV[]^]N6-@U^dlsz{gTGKKHJKKKOSVWVVWY]^[YZXXXWWZZ]_eqrvwuuv{|zlopromrz|xusokj\UU^m~yqkecbedfimjfaXOKMSHYykYFCFDA@?@?:F^zkXBBQ^gidl~xgXRMC<2'&('')+)+3CBAABA:>Qľ{zýgg`S_ov|{v|~l_`^OF;+(&')()(+8?@1$'&&&&''**$6qnvzlZB.--)')(&#!!'8>IgwxnR8(##"d}~x]qxz}sc%&)55ayk7FU_fnupZ>%#'*282(NĽǾ8HQTXUUWPLQSTYZP?40/FXZYamyyFCJOKJNSWZ[\]^`ceeeeec__beccgjlmkjhbVTW_o~\^_`chhdcdaaWXVX\\\lpwgacWTUVUSLFMKNcnS;58:=?A=99Lr~}womqĿfWZgnwqknj[NE3&%))'*)2>?8$%%''&(''&*=Yv_JPB,#&(%"!33;5/0B=' $$T|}ľ^pt{sK'')/JnzyMexsO2 *32#kȿoE[dea]o\HGMUUE6-.15MTQSclyRGLMKMSX]_^_`adhijijijllkijlnortvvtvjWVYhz^_ad_[^_gngd_^^^`]`kruqcSNMRSLBBB@RwtaH=53764563;dŽ|rf_ZTSWlſj[fzrfYN;)(('+.5>@=(&&%&&%'+Ba~}ik]I0!'(&! .11(%%!FQ) # =w}`jy|{="#''/1Yqy~TfuwW)(2)~¼¼ŷY^nw~zvk_RD<30113;MNIP`oyYFLMNOU[````adhjmnnpopsrsqpprtuvxz}|iVW^m``a`^^aa_elhc`^^``dmt{oaVVZZUHB?:IgþwobQA22356526\Ƚzqh\QG8+;cq[Un|qcSC0+%%+2=?<, %&&%&)+@k¿mWSK+(+)%%,*)'&/@D$!'oƾ_lzK+ &(*7[mu{xZm}o6+-ļ[r}iE'0369;AV{ÿteYL=1268734Syof[O?.&(:\outqs~|thN0-V~ugXG1)##-6:95 $&&%&(/Xƿ~ZOO>),+'&(-*%-FA?0`żaov~S!!!%#$.H`nu{ptvqf\dq3'½Ľgv}S)28<=@>DPZbq|RFLQTWY[^`beghkmpstux{|~xxzz~~cYYja``a`a`]_`dfg`^ZYbgiq~žľugYMHE>=H`zj_UH;257742OsyqeXI5*,*+6664/-.35775-#0g~wi[J1%$*4;<9.#&&%&':kǾxcB0.-*(+6*#GMBB:!TǾybou|Y!!$(%,;Qbkw~wglQ'/@Wnc'ù½{t[,6m9iĿw|E2=JJCJU`jvp[TSVWWZ\]_fhfjqutqqrzcUZ_^``_^\^__`ceca`\bnr½yl]LDBWqwkfXHGE=68BK]|uoponmkny~|xsoi`R@0/1246/#%;UjrsokbM3%?UYbimqszz~~{vsl`R6(26:+$(((&'3{yb?2##'$(?@DB7.?ƿg^dqyzQ ".0'#,78/2;Fu>K{s77IPGHU^eq~{tj`QTVV\`fddghjqsqpopx}}rXO`__`_^\]_^]`eea^]eqvĿuhWIAWrþxig`PJLZwsa[^`iotwsspmhba]M8--/,138Ut~q]MLORY_dhkioqnq}~}}vodU:*682%'))('&EʿyZC;$"%%)-/)'2' ! ;ķxZbiovx~~x=#!4B>=AB75ALUyHG>>B66BGl{c7`c|{DOUQLTWWbcgs|wxxzzz~{~vymUW[cilinprsrrtuy}|~ifgda`]]\\\\`cie]mu|¼{mYWougcZddKTRTW\^ZRNPK=)%Kfhjv|oaTSVRQOXelx|uiU762#$'((*(('jûŽt^^I%$'''()')-(%%%#5oŽtbfhgqlqs{vC 4459>mFJKYdkyxvvrrtspomopqssxz{{}dca\[\\XZ]_`efkz}^NZwǽ{yeZĸpO$ #"! /Uþû|viXU][Xcqw{||wsoeW?3-%%'''()**))rɾǿwY.3995+'(*'%/14JY[c~z~xgwt|{yyytb2 "#/"';FAVVhvu=@i}l?JP]k}x{zrqrvqnorutwzzzy|}deca_aa`\[_^bftiejimorrtvl[QRT`{żs^s`,##!!4iü|tdYX]YWdmvyywslZ@05/%&('(()**)'o|iH4@DA6+(&&(9N^gkkqmyzxwwlN  , %9ECSV_wzo@A`zM?J\nty~{y{}yqqv{yvxzyywwx{z~effc`^`kfZ\\aewdUUae]W_bd^SQUTUTkÿünfg2"5or`WZ[TUdmqsrm_G)49@/$''())))+'jŽſ~t^>AGH@40(/@^rzzxw|~~rssojX1!2) (?GBJWQgmzx}w_CEQxº|;?Un¿xr~~|~}xvz~}yxxwvvxtsrx{{}ceed`^aa^^[Z]hu]OWZ`b_\^ZXTUYYSTWi~Žh|j38sľ|jVW[XT\chii_F(+;=7%&('((())*(Xûǿ~oO@JKE:68IcxLG;) 13( *>EBFNFTYarwx{vyzfHIIGc}qr9Hh¿pw~|||||~{ywtswywrpvyxy{}|}hjh^^__[Z]_`ftwrJ_cab__ba_]\[[\^[Ycusm½Z-gſpXUZZXW[][S:"*273%%'(())))(*+DʽƼ{XDMLIAIUgƿ@195& /8<=<UyĿxnx~}}|}xtwzxvvutuy||ywens^\[W[^beepKXjhdba_]\[Z[[[[^^WZqÿ¿wxĿnMsZOUWXTSG5%!'-55+$'(((())*))-2ƻ¼VINOJBVj^'"'76-)Pity|emusstz}zf[BMNLGD_tvflqp|YEjþluz|}||{|yyzzvrrw~|x{inmcekmkinqsQPbkeba`\WWVXYZXX[ZSXm|{~ſuyþÿiÿx`GRUTO8$$&+54'&''((())**)++jž{NOQPLHc¿s#$'<5%?ow}u~wRILMMMKDK_n~SVhy~{}~v{tNN~þktvwwx{zz|}|zyvstwzyzyw|{~ssrorwrqpruwzüaO\cccca_]YWXZ[[XYYWVWhvÿrszy¿z~eEMM?& &'%%*121'&(()))**)++,QĿjNVWPNg½~. $ 65#S}qkreAKNNKJC?HVkpsvvyyxwy|{tpsyrgflhhjhTUSQQVUSMLNOKJUajt}mIGQW[jv~zoYINVUfhUWSV[XUV[mqZHDTkÿ˿ĿuMwƽ¿rlY.#,*,.)+.25--.&))(&" !#$)-(]pmomp}yoøg@_x[l[N>20.'BNMO_·9"+97YvuV62868=?@A?757@HOU[]__O3&)'&&16+$(+;Ŀwv~}|wtr}ɾnFeEG<:=988/& "_zz½ǿſR!GJGj|J0>?@AAB@748?EDEHHFB?7)))))*3Ojotwy{yyx~~egbcafhfYZY[[WVTPNOOPQKHJKJJC<:@DJNSPNRV^hnnqmqy|}vdUJKRdgYVVT\vr[=+),6EUfqvz}sh]`;{eP8)*46,+**//10//&2N[ahigb\RA025eyttgPop+0HSXXYULF8'Ghtqùƿk$WUXp]/;?CDC?:8>FJHAA@@>CB1'*+-(0Wo¿pnuvy{z|~}gdf_`df[[\]\XWTPPOMNMMLIEDDDBABBEJJJMUVY^[VXVWY_pwz~|vpf`[UMNSRWmĿrX7/+,059AGGJMRS`us]@oǷ|^3350260..01-13/%EpzslaUS[[U}zpƼ¼SZsWThoqrmjf\YXN>&1P[_¿ļ¶|+GLezY%.-132019FLICCBAABF>)')/*5Zt»r^iqvwx{ziqpgdfY[YYYWXURRRURJPOKHHGGFCCBFHHHLMPVXSTUUUSQNQchmsqv}{o\HKOQe|pM20.0478CD@C>E]þsdG:973172622-3joqzlþyLWkzhlqhcgfU58ýj;^nrpf))'%# #%$$%&*2;@ABC.$1-@\ot\`ejqvx~~z^^____[ZXVYWPSUUURPPNKJDCDDDEHKKIFFHIJKLLNONNOR`jjr{~}x~¼n>+.28>>=DHDD@T~`J:@JRvƽǺ^:@:>=941640654(Gz{}rÿkI^o~s}~rmlkcNĸżkSlu~&#"*19-"0>KRSOC97:B6&2/AZj{fZabgntx~___```\\_`^WVVXUUPRSONMKHHFDFIKHFC??FFGGEILLLLOVRQR[`jv~tOK`mqrngbXJB>IktP=>EEGctIFJ?8-557<32722,N|~sɾþôbN]p~x|utrax»fZpv&-@GL`VPer}xeG7:-/0?Vcp}XY_chkqx~a``ab``ad^[YWWVVTPSSOMMJLLHFHLLFC??>@=>==DHKKOTWSWajd[^enu}¾ztxnbSETwþ^BEIVUIbĽgHNJB33943337462Kvzmv^_Zmzy||utgɽƽU^q|9@^ksxa8313;Q]ew|yVU[^adjp{dbbbbaegaZW[\][ZVTUSRQQPPPLIMNKGECA@??<<=>ADGJLQOS\bigXVWVX]mzļ{tg\f¾RHMPQNO`v}_DH>734?=61./2364Tw{mh^^i{ľuv¾_kdjxwzzqz°Ļg`p|O_s}s<.48IV_q}eUVY[^`cdl|fefffegfbba_aba_]\XXXWRQSVVRONIGDC@@@AA?C@=;@DBECIJNUXSQNNMOQ[l{qitƿżyRQTX[_]awÿùgNGNYcimnmid[D)13@fzndjdYG6?=Fte\__UHùlduvyyƸ]kw`j{}9=BMW_lxk\Z\]\[_`ab_bmtijmjhgfeee```_]][ZZZ[WTTUUVTPOROLJIIJIGDDKQUSI@A@?DC@D@BDCEBDSi{Ⱦû}qrqtĿp]qxI7Qj{wlcR3/232?buaOA7/7=e]luut~¿nfp`i|u4AFRXbmxo`ZZ\]]^___aca_dflrlnpkljeffdcbba_^_^]ZZXTSTSSSSQONNMKNNNMFDGGHE?BFBABA@;9:9=A?BNexȿ½þƼ|~|xt{wDKgu~wm[>-//01..+,7OHBAAC<5MnxdN=<:767==>L\oſµ¿ǾĿqH\my}pcF(.../.0-+7RH?=<99[tbRG^[Yov{{wuT1]÷Xosbz6;CQY^ckxfbfb````_`_aaa``__`^_es~wnojljffegfgfddbdd^\\\]]^bdfbYZ[ZXVUTUROPPPHDAAFIGON9=?;78888:DXnʿĿžp`PivrdJ(0010/00,6LD=TTPkvc\Oup4Pisxyyx|V!Ap¹^ltfR4;BPXais{fO_lgba``___``_]__``ba`hmuxpprzsijgkfggedcdabba__\\cpxr]Z\Z[\YWUPOPNMLHCBFJKLCAA?>:8;966ARjž¿ƼybbsI^nwpbI*0122120.3:=UyqbbTL'Qhrwyw~~|{~zhF+Uü˿fhqqni-<:=GUdmt{nICPckgccc`_^aba^^_`adceflqxqrtwqnv{vnjiihidbccb_^\^bjkie_[YWVWUTRQROKKIHGHHHIHGCAAA?>;88<<;9JZk|ÿ}x|gI=AdoÿýcN`fqZH115554404oumqR#PpP60667:ADCA<0$4MA41)&''''*04*)^ûloyh|y,;=<:;8888Lg{}XD=9;;;;DKVbknklja\mlhlsxzzxwxzmmhlnqx|tqstuojieggfgjhhfnqnpoqe`be`_]XWVUVRQPMNQPRVTUOILMHA<>;@ADCIMVXWROJMROTTZbiry|{lhiklmpfeoqtuqlgedbabeektw{rnr}ygiidc_X[\^`WMNOTVY[X^kiWMMTTF=:8=KPexȼ~K246:>B@Q`Ļɽſ½SKg~vaC*297885-O}yrT'043-+,4<>:67133320,'%'(%%d{~ſĽenM2;::;99@FGHIIMNQQMGD@=:9::<9:;=BJKIIGDCBCFFC@>ADDDCFGILLMQQQONLJHEDI_~ijjjijfeecbb`cgotuz~{|yxppmekmnhhgliikjigcd^[]^\][TONNNLHFHJJGKh{½tmgm~ybC3:DJRNRSHIJOaú¼tBOk|zywo_E28=;88872]wld?*7;:7;AA87CIKPTSW_edc^S4").1=99>Kbjjkhgggc``ac`^billruwzz~smffhijhihjjjnkhcba`bca][YUSOOKGCCEIKIHZkwǾż|jVJORRQSUWD3/39:AEEMVKC>BCMfý¿½yO;Wlz}j^ZO81;>FH97867hulo_23====@?:?IMPSXZajppng_F*18DPY``]WO?+$&&+o|kRTɼþȾ|Ľl|½ĿO0:AGIJIIIIGGGGDC?<977-6;>:99==:8=79=>=UlĽúz}Y0@Vhqux{~{ujYG=1,;=?GC88868nwmrnK+;???@??96/4<9339859>>Um}»|^*,>LX_abcb`SH:0-'-36=?8897,8oþ{xwwf55@ABB?@HORY`flqy}zwmW +9GVelsxtl`M2$&&"CvfXnwµ\|nĿe:IKJIIGEFDDCB@;5679@EECCCFFFGGFFEA?>@AABAABEFFFFFEDAAA@@@@>>=<:;?CHLUlmmlnojdghebccccbaaaahdVXX[_agoxummkgeilqtypgfdehca`_]^\[Z[a[ONQQOMNQJLV`isľyy|gSHJQNLLNME.%*/6<81-02;@;63DYefa\SC607=:- ==<87<969=J`v~v]bŽ»yZ& !0GHTpydE-42& >k~{zo<6>@?=FOTZcmsx{s]627L]elonolhSCO7&& RtdmvqwļJ3½ºa@HIGEDEDCA<:7667@GJHFECCDEFFGEDA@BBBCBBAABBBCEEEEECA?@><<;988ALTTVTROqonnnjgffeeegk`Y\XWZXYYXYXWVSSSSY[_ksyvqoqkgfdfefa__^__[YVSNLLQSOMMONFC>9;fǻs[R\cba_cs~rQ($%%;e¿xL4=;9;GNQY^hlqyxz|}xlP76;Qfpx{yvphQ@T:!&"+alUi}y|úh:"#J]?EFEDCCB?;7669?EJLIGFFECEEFDDBA?@@A@A@@@@?@ACCCCBBBA@?>=:88;CRVTRSSSSppnookgfggghiieb^UV[VTUWXXWVUVTSSRS^erzxtofegfhgkmga^^]XTQLIHEIPROLKHEC>=A=74335359BD72369Hfwypb]^[^cZJ=774eƾĹ~yZ(!*9`~]8C?:DIMV`dinryuuvsncI24=TixyqbR@N:$%$%3\qPFq|pvQ5#"%"[ſ}ýO>EGDDB@=88558AHKKIIHGHGEEDCB@A@@@AA@A@@@????@AAABABA????9;@IOVUQQQRSTromnpjeghhijjife^W[YXVUUXXWWWVVVSTSX_cfjrtmffeeejqj^\][VQNOTXafPRSMKFEB@@A;5534814MiuldYSQSPSOHDHOWa]OJKKF9( !#$$$##"#*2F^gfcbWP;7HS@6752>h{ytprvtrsl[D/1.1_Ļ}W!*6\rui?ICALSZafmqx}xqhR0.&%'%(.PsiK66~mi{aG|wK(#%'&"!Yisþy?@EEED@<75668>FIHHHIHHHIHDAA?>?@@AA@@@@@??@>=>?@@ABB@??=;;DOTTUSQQQQTTtqqpqnklnmmkihfda][VWUSUWWWWXUUTVWTSWXV[cilpmhfghd^\[XWTRQTQQihPOMLHEAA@>9888;>95Jj{si^PIJJC;:>BJPVYYLEF5+'$$$#####$'1:CZgkgdcWQB=II:3-,?mx|~~|zi_E*&-UĿzI':Uym?EDHS`efksw{tjX4/=Ser~|ztlZG2<9%(0&&2;C?AC=-!%/÷~rgU`u|t[@&/}G'%(*)$ =frV96448<@DGGGHHHIHHIGC@@>??@@@@?@@@A@@?=<>>???AB@?<:>IOTTQQSSRSSTUvtsrqqwvsx~qmlhdcb[XVTSWVWWWYWVSUTTUUTPTX^bmuuqng\[\YWTSSRPNQYZONNLKGA@?=<99788:71Fd¾{qbWLD@;36>BDJPSSJ<78/+*'&%$###$&(17@[hifed^V@?<:?>Yn~|{~{x{oU;)CsĿm6csyy_B><;=810ChzfC@BE@;63468>BFEFGHGHIIIKIFEB@?>?>????@@AA?>?==>?>?>>?=<@ELQQSQPQRSRSSSSxyutqsvvyqopnghihjlh]]\]\ZZXY[ZXWUSQPVWUW]q|zse][ZXVTSQPRSUXQKLOLKGDD??<:9534762CbzuhWNG=4029=@BDE?:532///-*(%$###"!+25>Wifcde^V>;15Ww]HV¸[1IbuaMX[Y[fntx}}{n\<7DUekkgc]SE5(&'*0'%.7@C( %&%aſûs`L)"%&$%"&J|eA!++-,(%)54/0367778:;;=DG662Uob@DDF>:7448>CEFDEFGGFHIKLIFFFDBA?@?>>>???@@>=>>=>@>?=;<=AJOPQPQQQRSRTSRRPy{vtuvww}}ppsqmmlnv~qfic`_^[YXYXVVVTRRSSQRRbnfgmg\SRQTTRRTWXTRNNOLKHGFA?<;;963577@\pƼyn`RD6)*/7:??@>;7432321-+(&$"!"%./-3:SkffilcU:2Amudgı}?FbwX\aeeajy~znZ:AJVeljbUMC4(%%)/,&03@G+%&=¹ſznmY3&'&&$#3hn2#*-.,)),-124562-5>=A@ES>2-7Tf~tyN:BA;73359?CFFEEFGFFFHIJHDEFGEBBB@@??>>?>>>>>?==>?=><;>GNRSQPQQRQRRSTQPNMxvusuuwy{yywy|jkopqyyghmme```]ZXURSVTSTRRQRTVTQZgqi`WPOORVYUTRRROOMJIHJGB@?>>=A?=8:Unı}tcPCDHD@???A=:998530-+(%#"#+FMRPVgys|N065445;@DEDDDEFFFFEGFGEDFFFDAAA@@@??=>>>??>>><>==;>FORQRSSSSSSRRRRRPMKJvsvvvwz{xwwv{}omqtvynhklligba_\^ZUTUUSSSQQQQNIKNU^cjfaZUOQZ\URPRPPMIGGGFC@?;9:>966;61-+($"%4DGJ1$0;PrhjhdVP{~jr·ŸVZoi]inrwysw|wpcD.ERSPQPRX[YF2+0/'%&3>=BN?$4ļķ~uZ  $&$!/`a'0786205977:IMW_bjTTjzxg_h{yv~I(349>BDDDEEEEEFGFDDBBCCFFFEBBAA@@@??>???>?>?>::@EOUXWSSSTUTTSRRQPNMLJIrpswxzz||vv{}|xsvwvtomlkhifcb`\[YXXWVQQRRQOLJHHJNOT^gje]XQRQQPQSSSONKIGEE@>:86546;J`uĽ|ustk\SODADHGB>93-)'#'8HEFP9 /:Hqqhh_Yhva{ȾÿhNh{|\hmtz~~|xzshW.(,G\_hrxzztj[NK7+%/98;MC$[Ƚ¸o=#&#!&?oU,;9:GPYhvy{{qinzw70>>==>>==:BOTVWWWUVTTTSSSRROMKKJIHpmprtwvvvuxyz~|vywtstnlllpmeeec[WYZYWTSPPPMKLKKKIGINQW[^chok]ZVSOONNLJFGE<<:88;BL[juĺ~iXVPIFIHFA94/,+(3BHEIUC#.4Aitge^a`Ŀi_ȿƿſtJ^td_mpxueHDnxuzp^E<88524GA$rù{V#%!,Mr~.<>>=<<<99IK?Ljl_djpq}x~C>DFFDDEEEEDDCCAAAABACEEEEDDEA@@@@>>><;:8>DKRYWUSSTVVVUUTSRQNLJJIHHHHmmmlnpomnpsut{ztstvxyxvz|nsqlhddba][XXVUVRMJJLOLKKJLNOPOSckYU]_ZWSORYJABBA>CHQZg¼|pbTLEFDA=:40./16:AWZN6)2;GrtcWqŽüfGb|ƼôY[nS`lq{ta3P}|xm]9~üżtG$$#I>;B=@FTt_R]cmzv\8AEFEEFFFFCAABBBBBBBBCBDEEEDB??@@====:9?KPXYXWVUUUVWVUVVTQONLJIHHGGGwoljiimmmoqrttssuvvyzzzvpkkmhddca^[XXYXWROKKJKKJKKKIKKJPSQLRZWQWXWWVF@==BNV_nx||zĽ|paNEDBA?;41,(+14=<;:;ENQTXXVWWVUUUTWVUSQQPMLLHHHGGGwqlfcejijoonosrtutuxvrpnmmieeeb`ZYYZ\YUYPNMLKJJKJIJLNQNHPVY]_Y\[[UICBHO]oul}{uŽ{n[KDABA;41+*-/49N[U@0/7?Ren¿e09@K_xȿȽaWkus#'A^s~roqhYF.s|`$cþ}i",7("8zE>GQ]G]jpyy{x=?HHFFCCCCCCBBBCCCCCBBCDCCCBBB@?=<:Hj¹ÿzA.13BVuuKwɿyM^ju[AD??NdruwwnW=132."7qAIým,GXP (LGBKXvW?OZ`fhdkzBAHHGDAABBBDDDDDEEEDCCCCCCCA@@>;;;?KRUVUUTTUUUVUVXUSSPPOONNMMLLLIIGGyyq|uaec_bfhlnpqoqonmjmonlnjhe`][[YXXRPQQPLMLJKMMJJJJLOHMTUXMMV_etiissdUE@<74456423451042/5[kpxxW]gjlmkf_K(%&)+*&!#%avQqƽav: "#=gZRl¿pCPUX\dly_?BHFEFEEEEDDEDDDEECBBABB@>>=AGOUZ\ZXWVVUUUUUUTQONLLKLKLMKLLJJHJKKLLLknmqvyvwwtnbcahdacgllnrknjeeeca]ZYZYYTRPOPPMKJILKKJGHIIKY`fvzSHcþ~seTDA@BB=1+)),--.../9nŹ¿[*4443249<:?_¾f&8KT\ju{|k_[cikonopoj\H))+()($"#"%iiSſĴnj#%%"+DNgvôxEY[\^bgsP@AEEEFFEEEEDEDDDDDBAABA?=>AHNUVY]YXWWVVUUVTUUROLMKJKLJKKJLKJJIJKJKKKkklpqrtssnpsopn}}rh`[\_dffhhnkhgeeb_]XXXUUSRPPQQPMJMMJJNFFENYipwt\UCHMVWXXYZXXXXWVVTTTSROKKLJJLKJLJIJKJJIJKKJJJkkkmnpojhllojhksy~ja`_`cfimkijgcb^\XVTSRRQONNONJIKJJMOLT_lho|vXJDEYoûýrbODEDGC:5442/..-+'7k¹ľ|H-4431/,-LYIKB@FE976=aǿt2*,.;HXil_ap}qXMOZblpqtt|}}{||ukZK:F:&#!!"djȿpx4&-.,)EǾQcgjjoux^EDHIHHHHHFEEEDDDCDB@@?@CKQVWZYVXXXXXXWWXXTRPPOLLLMLLLLLKJIIHJKJJKJIIIlkjkmopmlkjiffjnkptwk_]]^ciljhea`_[VTRRQRPMMMLJFHIGIHJ[qnp_MLHIZr¼zjTCC>><9773/.,+*+(;i½yM*5530.,8^WLLBB?8;GS`ľE)25AQepl^bdfnnc]CAK\bfqwy||ojhbXO;)# !# Es|ƹs`&/10,8}ƸUgjnpx}||oPCHJJIIHHHGFEDCCDDB@ABGMRUYYWWVWXZXXXXWXVTROONMLLMLMMLMLKJIHHJIIIHHIIIjiikmmjkljggiihedknqwxwl`[\`ihec``[XUSSRRQONOPOJGGCFIMWew|qi^QNMIF\sĽƾ~mSGB<8;:851.**().+9eÿxO+5532./AXOLH5/-+*+)(/:DaĿ½wI,4432.1DI@DMXcq[*9?IXhjcZ^houpkgBM^ils}~~t}yqgY<"$Kľh÷A]k023.:µhdlpvyfHGJKLKIHIHGHGED@?>DJOW^\[ZYXWWWVVWWYYWVUSQLMMMNMMLMMMMMLLLLJJJHHGFGFFFEjikllhfggfehjikkllldiowwla]_beZRQPNMKHEEHGFJNVbujcfc`Yaf\OQLJVm}źmd`MQYM7/.0.*/8@LOGZ|¾s@+4330-3D>FetxĿU.>DMYeg[X`krunn]BSclq|z~{sl[<$qû½ahȿF.iN-2+Zŷpbhntt_IIKLKKJHIHGFDCEDHMRX]]][ZZYXWVWVXWWYYVSRQPNMNMMMLLKLMMMLLJKKIIHGGFEEEEEllmnmlihihghiiillkhejnpmm}|eZacWRQONNJJD@CGTZe|eSRSXU[fgaVUSLThz»~m\NN\W>,-43(+IX_`NAVp¾e3.5220+4@HrĽ@6@HPYd`W\dmsrqpGIYhrw~}xn[;"+ǾÿM:ǽb$1ih/5)wĶvrxzTHKMLKJIIIGDDFJPUZ^_^a`_]\[YYWVWWXXVVSROOONMMMNMMKLLLLMMMKKIJIHGGGEEDDEEoppkjjkjihihhggkigdinnoppxjlw~|r]ZVMMJKIFGFCQ`nty}lURLRSV`ge`YTOMOawzn^QQYG,,/.,7^okiZCGKcyû~K,1331*0FEmùt.;BKQZ^YT^gmpowZ=R`nsyzkX1GĽz&'`ù:+3gtya392ɿ{ybPGNNJIHGFGGIKSZ]aacbcca^^_\[ZXWYXVUTRQONOONLLLKLLKKMLMLKLKIIIIGHGFFEDDDDtwtmnmmljhihgefihedjkhjmppmojkry{rfWLFGFECKVhxvlbLSWQSOW^jl_XTPPLZq¹tf\OE4/102;jzk\MPPNUk~p:/032./GHVǿº¿ĺV28ALRZXVV]fllrh:FTeorzub?ab5B̾Ǻ_;-4fgm|L7;<ɽ}ePNKMNMIHGLPRW[]_``acccbb`__][ZYXYVUSQQPPNNMMMMLLKKLKKLKKLKJHIIIHGGFEDDECAstrlkmnlijkhfcffedefgfijjgjlou~vj\NZ\aky{`XQGJNPSRRVZjm_WRSTOYox½üzpfP>;<:DKNQTV^egmnJ9MZfnw|~yhMlÿ½_1BEa˷ǼxUO43Zemw}?8F`wz½uA45421;E6LǾžbage\J:ALSX]bej_4>T_ir{~}}qXgýa>IJYyʿƾgfaJ.@MWek|e4:>Fǿru]XVSUZ]`aaddaacdcecdedhmjhfe`__[YWUTSROPPOOOPNOLMKKKKJIJIJIFHHIIIHJHDBACBINQqpnlnljhjnmmjgdecba`^][]acbceijp|owpSUTTRQLPQRSZ_d`UMRQQJLQdxüt\LFFI[v\667526C8/dĿžuks|zvjQT`kt}}|vb^¸ı\FOR`rqnpl[9)4>IKUdy_/@FFƿÿwy}ojfeacbfhjhggifiecdcbdefgfglkjiga`]YVVVRQQOPPOPOOOOMLLKKJJJIIIIGHFGIHGHICFNRUZ^^onnnnmlkloqspkfdaa]]ZXVV[[^^bggs{{v}eTUWUOJMNNPQUX__SQRRPMLIbtſyhWNNWpĿwC=?;88FD+8}¿}|zqWEMV\abR8:>Rbksz}p\¾TRY`l{»¹~{yysgK$()14:ENVje:KMHļ|plhhkjhimnljjjlllhhfeffhhjjiiihhg`][WUUTQPOPNOOONLMLMLKLKJIIIIHHGFEEFGIKNOW]_befbplllmnlllmosmhgc`_\ZXVTWUV^[]epx~xv|r~SSWYVJJLMMOOQT[XNORRONNNauǿzgc[XqĿS8>><@:6?C=Lnp̿zuttstsuuuurrsssrqommlhec_\_`][]]\[[[YXUTSURRQOPMKKLLMNPWY\_`aejklmlmmjikllmnrspmmmssspmhmkebcca^\ZZZ[ZURU^iwrf_XVRJLMLQRRTYY_cl^TZ\ZXUSPNPPOZhf`WVXZXSTSTQMWdqrzy^ƽz\?89:778@CBB>:98675315eýlZcd}JRTTVZ[XX`{c=@::_ºsc2?KPLGLTOU¿~|xtrvuqqoplkkmlkecbca`[Z[][[[[\[[ZXVWVURTURSY^edghhhjjmnlllkkjgihhhghjmnmmqsqrnopojjkidca^\Z\[WX[ZXZckpzmid\UUURSRRROOQLPZ]adp}`T^]\ZYURQSXWXggi^PSWZWSUUTSRNONNWely½ixźukh]I@DC?@B?:<>?@BBB?;:97666-8yºŽlXPL{ƻRY^bfikhjmqVK=03@`ĽV|øZ4@INPRTXOq¿ż}xtturnlmkihgilfabda_\[[\Z[ZZ[\ZY\[Y]^]^bcdhlnmmmlkihjjjkljjigghghegkmnmkpmnoklkheggeba^]\\ZWUWWZ^fkuoeccf]\^[TVUSSPMOMT[^^bwoTS_`\ZYWUTTUUU]_cZPRVVWXWWUVTSOIMUP_o~npɿſvsoaI@KGJMJE=;>?=?AB@><:8872'BtN@WZeilnpsuxv{u[a:8==H\4úN>EHOW^`VY|yvqplnkighif`abac_ZY[Z_aaaaacdhgjjlmljlrsrmkllmjjihijkkhgfggiggiihhiggdebblkhhfcca]\ZZ[WSSY]bnv~hgkc`_`cl`QWTTQPMKMWZZ]hfMY``]YXXXUUSPSVT\\VVXVWWWWUUQRPKWXIVhrs|sl¼{{yiO@QWWRJGA<=??@DEB@=<:962,GļsC=j|closwy~nk\5BFBB_ľ~Q+6ŽRJuƼpnuwz~z\=?IMLEHuý_`]QD40>x¿|M=HPZcljWƻê~}{z{yzyxxwtqqswxwtquy||{wvtrspoommooommomjjiihhgghijhdbaca_]Z[[[\\\\\[lggjg`^YXYZ\]]csmg\]]eg^^acb^YYWTQPOKKMNRX_lyQP\``\ZZZVVYUQLKRd]VYa^UYXSZXTOQWXRKKIB>DJP^m~¿xĮ~jV\nkdZUPMJGHGIGD?><:86741CegER{mv{}M?JQUTLFS¿tI55+(),1@d¿¿ÿ_ABKVckogb}{yz|}|yvuxwvustwwxwtstvtqqqrqqopmmookjjhhhgfddca__]\[\YXWVVXZZ\[Zlfca`]YVTWVRU^ibX_dccfccfdfd`[XWSPQLIIILUY]h{iFQY__][]ZVVXROMLZg_Z^bXUXYSWUQQUTONLJIFD@>>I[cu¿Ǽ~hevrlge`\UOJDFGA===@AEOQK@ERnĿZKTx{}ENU\a`ZOM`¿|i[R9(' $,2=W{ABHOYemoevʿƻ~}}{z{yxvvvutsqqtsttusvwvrqrqrrononopnligggdd`\^^][ZYVXYXWVVVXWWWYfee_\XWVTTW]kox]UXY`adc`cfbaa^ZYXSOMKJGHOUV]oWMY\^^^__^WUVQQPS`oc_`bVTW\a]SPQSSRQOLHGD@<65@Qf̼ý}ih}wke_]XOKRZ__\\_`]ZZ`mkTNNUxrVKU|ùsG[chnpk_OQapmYVUTPP=&)!!#(06Hcn:HOSVcnocŵȾú~~~{}}|yxwtussprqsssstsuuuqqqprrpnopqomkfccb`_\[[ZYYWUUVXXVVUUTVVVXtn\][YTUWX^fp{r`[]]_eb_bfca`^]\ZZZTMKLMQY_X^yuUWkd_a``a]ZUTSTSR]jdZ^\WXZ`f^TSQRRSRQPIHD=;853Lhɽ¾Ⱦxjk}ld_WL\t}{wy~xpkzyfSJP[|½|^RQWpɦwwgVjonwzwi``[YXZWROMHIKLRSVD'+"""$/46K_¾OAMKPU^jjcƻ~~~}{}}~}z{wvtqpqqqsrsrrqsrpppoqrrpnmkjhd`^]\\[[ZYXXXWWVVVWVTTSRSUWYxhY]]XVUV^go{ynqh^^`aacccghiihfb]\X\VIFJKQU[Ym|}eOYjb`_`_^[YTTSRRS^llbbab^XbaPSTOPOMNMKIIG>;:02LkƼ¾Ǽwonoi]ZpVHNXj¾|aVT[Vfgmblz|{pwvgWLD;8@FHKMPTVXD%)!$!$.638BY~5?FIMQYcdaŽý~~}||}~}~|{wtqqsqpooqprqpqooommmnnjhffd_\[ZYZZ[YVVVWVVUTUVVUTTSSUV\hY^^ZZ]ak}u\]^[Z_abbdbdfhplfeb_\ZXOIHIJLOR^r}hL^d`a``a]\ZUUSPRW`nneccfbZ]XQSPPNMLKMJHHE<;9.5Wvƻþvuoudkvihnqou¾Ŀh[ZY`V`^luvlxiWK<4ENOOPRTY[C'*#$#$-5430?W¹¿]+8AFGMTZZ]Ž~}~}}|}{}}z{wusqssmlnnpqonmkkkhfgfhfcaaa\\\ZYYYYWUVUUTTTSSTURRSRSUUV^]^]\iuobWca[\_`bgdbfgfnjedd_ZZUKJIHJMQYbnaV_^_````^\ZXWVWZ_kqo`\YZZXXRRRPQOLNPOIHE?:82-9\}¾÷ÿxozzus}|xga`ZYU[ps^ikjs{iXK:IRPOPTWXZA)-('&'03231/@jøy>37@ECJQVVYʿý~}{||}}}{zywzwwtpoolkmnlmkjgfeea__]^__^]^[ZZZYUVUTTTTSSTSRSRSRRRRTTTT`_]di~}fc`e`[]_`ccbafikrpsvna]XRKJIKNPT[[jxT[_]`aabab]ZXWWYZckqmSYY[ZXVRTTTRNOMQKFGB=84/+<_¹zqļ}tslojheaaZ\\^p¾b[```fnzucRBISSQRTZ]Y?+.*)'(-332302K¾SHHHGIEFLSUS~{}}}~}{yzzyzxxwwvsronmjiijjjhfcbccb_]]^^_^][[[ZZYVVUUTTSRSTSRRRRRRRSTSSTaefnz{v||iaab`^_acfccfmkmru~ve^]UROJKWNMTY[vcQZ]^_accbg`ZYXY[[aergNZ^^[WUTTWYROOKIGEFA=620,A_xžxx¿~xr~Q`rlkhde_aUQd|RU[]afhijnz~jYFHUTUUT[^O6,-****,231330:Yÿ`Y[b_[RPPIQSSm¿¿|{~|{zxtvxwxwuusppnlkiggffdedbaaa_^]^^^]\\[\[[ZYUVVUUTSRRSRRRRQRRRRSTTTdhvmbdtjfbccaacdghhkoojmtstie]\ZTKGKRLTXYp{UUZ^_``ab`c[WXYXW\\bmfX[][YWTTVTTNMKJHFIID<410,A\yü¼xĺve~n@8[sqlgeec_TSUr^N[]``_bba___bktxzzy|q^GHZXXYZ\N8--.+,-.--122453@]k_eqxuqd\_WQVZat}zz|wuyyuwwwwuttrnljigiifdccbaa`_]^]][[[Z[ZZ\[YYYWUUTUTQRRQQQQQRRRQSSSSSu{mZakqjjhfecdfhiijlnlmwonec\\YRGFLQOUW^zoRW[^^````_`YUWXXXYX^idVWXYXYYZ_UMNLMKHHHD>633//D\wĽĽyǿżkScqy}|{whT30;MmsliefjlplhlqIV]^__]a_[XTSOMKHHHIOW[ys`HH[]\\WJ80//.--/..,.124742AWekyzllg^XYXv¿ýqm~~|xu~xvtuwwvvwvspnkjhggjgecba_`^]\[\[ZZZYXZYYYXXYUUTTSSQQRQQQQRQRQQQQSRR|dWdkiotrkihhhghllnmkqxokkd]XVSLEGKOOTWk_OZ^^\\abaa^YUVXYYXZYefYV[ZYZZ^cWGNNOLKIE;:432/3AVrƾĽ¼¹ƽyK@HHIJGC<.(38?`voiieoz}}{~žNPX\^^_`a_[ULHC@212116Jfý¿|jŻe0-..,,,+.-28>Vbzmlory~Ŀkju|wdNJQVY[]]]_^]XTQPK.**-,,+'H{{pcDEmcE97565750/2453.+-/5:96/*+>_uIINTbw~b^ffmy}tlluy||sspprpmmnkkgfecbeba_\[ZXXXXXXXXXWVVTTTUUTSRRQRQQRQPOONNNQRSSU{rz|_goormnnolkjkjoqqknzmeibQMKHHIMMP\l\f[[[\ZZ]_`ba_\[VUTUVUZke^`\ZZZXSJKONJIHC?::84129CL[}ýüĽ}[ƻp?2.10/--..0<>DNtvopnu{}}}iLHIPROKJNSVWYZY[][YXUUS=$*+,,-)(O}sd;HsU8:7656642587432.+-267710,*On{aBQUUekrq_^`dfgpysljmvx|~xvwwvurnjjkhhfec^a]ZXYZYYWWW[ZYXWUVWVXWVUTRRRQQPPPOOOMNQSSUVwvqu|xdjqvsltvmmmmmpolioqijnfOHHHHKOPT^ixO`\[[]Z\`^_fea\YWVTTUSZhfba^]\YWQKORKIHEB>>=9654+./..//006>BLt|rmkrx|knjmru~oSB>@@@DIMQQRUVWXTZZYZ\[ZD'&++++,'*RwZ1VtA4868AE>723/),0498420*JVdxIQYWWX]bpyy|wgYYZ^bfikrwoiiouxy|}{xxxvuprsokid_a_\W[[[ZYXXZYXXXXWXYXXWVUTSQQQPPPQONNOQTTVV}rtx|{dfluslqronrooonlkkgggi^JKKIINQVY]raTZZ\^^\]__cknf_ZVVUUT[ikfaa`]ZWUQNPNKIEDA=>>8476=HG]wsrÿ~yvľWa¼üX<,./--./-+,3BEh|uppstx}yeI;AGLLMMKFEDEDDKQSSTUVXXX\]]]`_K(%)***++&,OuD/dp1.45@MMCHQMMLIB;3*(,5:852.5JMhZIXYZXSQZfugcddcZTPX]afgjowriejosuy}~y}}zxwvsrrjdhfcd`]\\^^[VVVWZYYYYWUWWTTSQRRRQPQPPNNQRSUV}}|ouuvxhgossmopqooqonnlmlfbbb^QMJIHKPSVYfZZX[]_`__abejrjc^UWVVT_mijca_]YVTRQOKIGFC<;;;530>Fz{usrplkswh; $*.3:GMHHIKMOPQSVX[]_aefcK*"&()))**)(,Bhs6#@OPNX[\[Yo~fxyrk[RN9/7861BF]xJTZZ[VRLJNRWYW^`aeebccb\XOPX^bdinryrfbdikouw{{y||}|wursojjjdcd_]bda[YWYZXXVTSURPOPQSRQRRRQR}}~~pruyurx{lhmqwtpomkmmjjid`a`\XQNMIGGJQUWbysW^aaccabcdadfca^\\ZVRT__lue^\YWTVTQMHHHD<998578?CJWossZPdnzl??Pr¿yp¾Ƽ{e8.210,))())=8Dvutqnlmgvu`83"%)/29NMHIKNQRRSVXZ\]bf]B*"$(()())))((:Omy='EW]fmuvtpk{vsjg[>0644IOgSQZZYWSPOMLKOQSYahhdddb]YSNQ\`dhkovvkaafkpstsz}zy|{|}}}~}{{zwvqkjiiklkke[Z\YZUWUTVSRVSRQPRQS}~|}~wvw{|wuykirwsnnqpklhige`^^YUTROKHGOU]clkTccddhdbghmqica]\[[\ZZ`fuxhe`\WW\RLIJFD@99966:9>@J\lvrSP]efo}q>:GKb~}|½lgĿútO)12/,*)+)-<6Adwstpmphlq}vJ7#%,0/AOMILPRTUVYYZ\aaQ9)##%&&&''((('&0>MiD4Tfgq~~xoaD/34DTtbKZ]XUTQPPMKOSVY_fhicba_ZVQNV\`dgluvrfbdhjmmqv|}zwwxwwxy~}}ywwrssqruvtpjfeffdcchhf_\[\[ZZYV{|}{~z~{zxwv|ypnvwxmljrkjhgcca][WTTQOJFKRQY^oWXadcceecgjruhb^[[[Z^_]bj{scifcZX[RLEHGD@<98789;ELTarvsPVV\`blyļm;:DGM\woxbqhú~a+/2.,,+*,25.A\zrsmifjg}~^.#$).,0AOSRQSUVZ\^`_VC0(""$%%%%%%%&%&%%0HUiY;bv|zwf@06@X|nJY_ZQTQPONKMTWZadhkcaba[XRNQY]adjptsh`bdfgimpvx|}yvtxyyxwyz{z{zx{xvtuuvvrtvvw|~~zvqmppqopnnfcdfgfewxz|~}|xwwxuvwsvzs~rjigda^ZYWSPMKGHQSS]]rP\abadddefhpoaa^[ZZZ]\Zanwd^bce`_XOIFECA@>:8799;8778;>KTSi|ylVbZXUVZgtlM<4EFHUomC[LMSY^\WYRQWX\rt]~ük3010012222+3EYy{rkii_[q|`?"%%#%')*()(''(&&"!"$#!.@<9542/.,,+,--'5^mnklvs_S@ZþsN;[eU\YUVTTSQOLNRVX]ciigfd_\YVRNJR[^cemsyvkfda\`cbadjmv|}|ywtxvvvutvxwxxu{{vsrsuuttvuvxvwwwwvuvtturqqqpmnon~}y{}~z{xx{zxvuwursyupnkijmdba^VQMLJJNNWag`]fefffgijlgedb^]\[ZYU]skcc`_[ZXGHHIJFBCC<79877?HQXh|ymdV][WY[XVXX^TU`eludPIOT8?A@>EHLYshATKLOSWVNURSWW]rncºÿf4/-**,2005+0>OaxjklohfwuV$%$##$$$$$"#"!!"!! &9GE?=952/.,(''&##5_jhfjwz||wrh`SAqĽN7V~ÿZW][UTTUTQNNORVY]chkjhd`\ZVSPLMX]beiovwsmli]\`_]`cbnwz||zvwwsuvtttuvxwuprwxvuttvusrvwvuvvuuuvvxusvspprpnopp{{xu}||z{}ywvtrqrqsnmmigg``]ZXSLKJJILQ^fs\bhfghihhiihgkf`\ZYZWXgocabc`ZVNFGKNE>A@>:799:AGJRXiuocNZZY\\\^[[YXWZcdaPEKOJ=@??=BHM`sXDOQQSUWYWVSVUW`nboľƿaGG@7343--.&6FEYzqmjlpt|\,!"#####$#"###"$$# &AQWVNE@:63//,%$&&##7ahgchxyvz~|xrpfVFzýa7PtoZX_YTUTUSQNOOQVY\afhhieb^[WROMJT\behnuzrlinh\^]Z^__fmqz{}{xwwutussrqrrrsrqrqqsvuutstrpptxyvwwuvuvx{ywwuussqooqozvxx}{zxx{wusrqqmmmkjifgf``^YVQMKIJLRXcdntahfhhhighhhgege]XWUWT\rl]_aa^YTKGHPV89>>9998:>CGKQWjyqtYK[[Z^a`_^]]\Y\ed^RKONHB>:9=AFKfkFIOOQTTSTXY\\P[gk_vƾ|bUTXYZXOD;8BTYYeqpmlinmtdA$$$$$######$$"=W_`][RIC:74/.+&$$'&&5`gfdjxwtw}xxwsjXN|HFla\^^WUUTUSQOLPRUY[`eggggdaZZUOMKO[adirz}tcaild]\Z[]^agkt~}zywtutqrssoqsronnomponrsssttrppquvuwwuvvvwyzyyxvutrpqqozutw{}{}|xz{urssqonklnnkhhgbba]\WNMJHJKSY]_sngjhighjjhhgdcc_XWZZ]^ntfafc_]WRMFFVT1@C?9:88:?DJla?KPOORSRSSU_i`_bd]||jfjjhgc_`\]]_^cjikonlooxiD"#%%#$########Kgkkhd^RKB;:611-*'%(')7\gfdivvxz|wy~}xnWd½dAbgZ\`]WTUUSSRMMQQTX\`dedded_\YVPLKLXadfjuyfbegd_\\[WY^bblw{xolrsrrrssutqmmkijkmmnmooppooooooqrstutsuvvuuuropnppnwurvy|vzzzyzvrpoonkjlmnkiifa`_\ZTNLIIMLTY]dujklmifikkjibbba^]adbhx~o^cgc\ZTOLHIVH4BD>::7877;8432,)&())1Jcgfktvxz|~xy~xm[}RS|j][^`\WUUTSSRLKQRTV[^bdabaa_\YTROKJU`dehq{{ldded`\\YYVY``hny{qipttsssvuusonnjhiiihmnmnlomihhjklmmnnnmppppqmilkkmmrvuw{zxwxxwvtpomnlklnmjijfb`^[UUQLIKMKT[_jrccilnidikkjgccb`^_b^^apug`eg_][RLLJMN56>:7;96556>MUYjsvz]OWYY\Z]]\[ZZ[\]XU[YSLHJB44;;=DThFELNPPPRRTURWdjodRdzǾþrusqpnljiihiiijkrxxvxzwoJ' -#!""""!?lz|yqle_UMHC?;774.+),((-9Veikqvwz}zvzwjj¸qKneX[YaaZWVUSSTRLMQTUVZ^bbaa^_^^YUSRMLR_deiqu{ridgea]YWWWWZ`ehnyyvhgkqttstuutopnkijhiilmmmjigihhhhggefhhghjknmkjighhjtuwx|~zzyzwvsqoonoooqskkjhda__\VTNJHJLOUY`vrb_cjlmkdhklhhfcb_^_`^\bpl`cda^\XOMKLNA38:77<75234AQXfuvtmWX_WX[Z[^^]ZYYYWTWXYRLML<28<;@BT^EHKPOOQSRSTTY^ek_Odzƿzwrrponnnnlmlmpsvyzx{}y[F2'+"!"#/8Ebs~pxtm`]SMMHE@><:40-0,+05@Qfikrxzxwx~xl|ĸW\}d[^[[a_YXXWRRSQOOQTXY]_ba^_]]]\ZUQQPNO\bdhpxytjfhgb]ZWVVVT[cggs{uccjtuttrqrooljjkjjhjjlmjgfghjgceeedcdccfghhfedeeef{st{|w{|yv{rlommnmnyqmlgcb`^]ZVTLIILMSSZembakoopwzigiggfbb`]]^Z[end`db^][SLLKLI98=<8;<7631<8<64503CLRXnvrZPVa^^]ZZ[Z[]ZYZZXXXVZZRHA=;;99?BTTIKNOLLPPPRTSTSW^VUYożyxyyvvwwvtsrs~jOK+"%#Hafkmpw{|}}yrdTQPMMJHFED@==:4/119Pa`Zaqvz{vp÷WkuTPYYW[afd]YYZVRSRQPOSY[\_bf`\]]\[XVTRROKHU_cejr}zkgggb^ZXWVWVVVZdit|~|qihpspqnonoljjhffeejkllkheeec``^`_]^^aaaccecba`__ys|}xx{|{ztrrssjmoqupnnkc`]][URMLHIRTXajmflnpklkvunjcccca_^\_^\dmnfd`][\TONKHDB@@:9;<52219CKOXrtcLNVZW]_\ZYZYZXW[[YXWUWXPB;56659=DVPLMMNKKNOPQRQRSTWWTWlʾĽ~{zzyzyutu|t]P#$%%Leknpqtw{~~~xs`LNOMLLLJHFFC=5200C\_Zcnv~~y~fk~kFHOSWY]die[XZ\YTSRRPQUZ\`cdfb][Z[YUUSRPOLFQ_aejoypdffd`\XVTVUUVT[hqy~|rijprtqonolhhggcdehiijlidc`___\\\\\]____bad`]^_^tsxvx{}{|vusvsloqqpnkjidca_[WUQOLW^]bq_fmnmhinrpkqhdddb`]]]\]qpdcc`][WPOMHECA@@;;>97805=FQTiwmRJPUXRT\_ZWYZXXX[\[YVSQPJ@62366==K\ONONMLLNOPQQPQQPSZUUjƿ~}{|zxw{uaG(!1Sbkmopqswz{yYKQQQQQONNNLE;3108NZZcnu~¶syvC=@LV[\]emfXWY\ZSRRRQTX[\bdcda\[VWWVSQQNMKHL]bfgny{scdeea]YWUUUVVUT`mtzyoignrsrpnkgececceegigigd^`^]\\\[[[[\\\\^]^^\]\]rrvwx||{zzvttmissommjhd`_`_ZUTQOVccgiol\ilmjlklnggkjddcb`\^[Y`vmbca`\[VQNMIEA=;<<>?<:99S?JP^wvWENUVWWPUZ[ZZXWXXZ[[ZSQMJEA50048??T[ILNMMLLLNMOONPQOQ\YTi|z}ueN/%=Wajllooptwz}sROUVVWTUUROKD<338?OVaptx¼~O;2ATW[]^gnbYXX[YTRTTRV[\^`ceg`[ZUUVUQPPMMJGJV]adirxvjefea]YWUVUUWXRXerx|vncgnrsrokjeacbacefeddgd```]]][\[[ZZYZYY[[[\\Z[rpqxxyxzxzzxustmlpnllihfd`__[WTQQUZ^apenegnomlmnoulcghhfba`]]Y[isdba_^[XWSRLHC@=::;?><:7EQAEXeJAIIKLNMLMMKMMMMMVaYRb~¿zpg^`eegilmmpruwx|z_Za_^ba_[YUPJC??DDGTRkv{þ|p[G5-9Q\]^bgnkUUYWWVUSQPPW]_`aceha\[XUUTSPONLJHDP\\cekpunfefc_YYSRSSSTURXgt}~zqljnqqnifccaca`cbbbaabba_\\\YXVWWWXVWXYZ\[[iomnqz}yquwxwuuspppnolihfec_``WVXUU[[W^hhzoglmnmljjoqvvhuseib]Y[ajmc_a`a^YURQNKIFC>99966414GDEKdvpFEOUTSVXXX^o__bkjRVVSPOPLGGR-08=FSccBFIIIKMNMLKJLOMOOYcaV_s}{vjhfbikmmoorvvwz{w``bfhdb`^ZSPJFDFGGRWimqxļw\VY]_ba\[WND6-1?V]^^ckofUUWXWVSSPPTX^_bbcfe`\ZVUUTRPONLJHDM\^chmovoeeeb^YXRORSRSTTU`py~|xnjknmjgdcccbbaaaa`a``^]\\]ZWWVVVVWWZZZ[[Zoohjpwyruyywuvtrqomokigfdba`]YYYWZ[Z[bcf}nimnnnmlpsswwj{ihnolpkejeddbaa\YWTQLIHA=87::42.2BEEJ[sq\>KQTTVWVVY]fXV_lsZQRNPONLKMR,0;FUbjX?JKJLLLONKKIJMMNPV_d\YjyĿ|tojejlnoprtvwy{|}v_fjiheeb\VRPNOOKIMVhlkoty~|uvmhf^QJCGHHHKFB@;30/3K\_baejmbWUXXXVTPOOTY^`cedda^[XVUTTRQPNKJHEKY]aerruogfeb^[ZUQQQQQRSSWjw|~zwqeinolfgbcdaaa`____^]]]][WWVVUUUUTVYYXXXwtmjqyyruwwsuurqnllmjhfgcba`]YYVTXYZ\\Zfygmmowusrwxtqinobiimzljfaefa_^YVVUSIFH@?9755332011/21/=S\^_bgmh]WVWVTTTPONS[^`dfeea`\ZVUUTRQPNJKHEKY^`dotuqjgdc^[XWSRQQQRRRT_q{}{{uwkflpokie`cab___`^^^^^\]ZWWVUVTTTTSVXWWVtrmipwzstvttrqrqmkjkheeecaa_][ZUTUZZY[^|kgmpy|vuxxtpmhomhifesrjhabcc`\ZYWVUXS?KHGHHH?126BJKKatoSCLTTUUUUUUZYUVTW`nm^RPROMJGG99FFTegJ>FIIMMMNONMKIKNQSY[SRLMQfux~¾wpklnorrttuyzz~yiijida_^__a_^[LHTiiloqrtsrpnzsb,.10./../00201FY_^_cimbYWUWURRRPNNT[]adgge_][YVUTTRQPNLKHFJW\`biruojieb`^YUUSQQRROPR_kx}wty{{vlhjlmmhb_aa`_`_]]^^]]][WWVVUSSSRRSTUUUqqpnpz{mpsrqopqnlmjjgdc`ba`^]\YTUV[[Z]lxhipu{wqprqmhgkkgggedlfghdbb`_ZXYYWS]R?GLLC>:622=FHMYou]DGPSTTTSSWXXUWVW\_`id[TTMIGED=EIOclX=CHIINMLNOMMLIJORSY`[TNNPV`jrxv|ſhaYf{rkjmossrrtwxx{}|djmjfccbbdhjh_NL]liknqssssrlt{fs~a'0323333331.2L\a`bglm`YXWURRQQPLNTZ[_adfb_]\XVUTTRPONMKIEHSY_cgoqniihda^ZVUROPQPPPMWhvzzyskz}zmaknpljdcc^]]^]\\]]\\[XWVTSSRRRSTSTTTssqrw}prrqnnnqkmliieefdb`__]ZVSSV[]bhuidkrtwtqorrnhkkhefddicbddcca__[ZXUQQZGBDHE961204DGKXgulKIPSTTTTRRVVVXXYXYZY]ZZWRLHCBEDMT`jsQ;FIIKMNMNMLMLKKONPU][XWZZVV_hkcejonnroLLJGwvhjnprqtuuvyz{knjjkjhdglopl]NPbkkmnrsrsusnv{e_jz]#245433330.:T_deginiYYYWTSQQPOMOVZ\^ade`\Z[WUTTTSRQPNLIFHQY]bcnspjjgcb^ZWTQPOQOOQOOdswpqqilpy~{ohjnmoifdb^\\]]]]]\[ZYWVSSSSSSSSSRRRqpnr{~vppolonokjjihfhhgbb`^\YVVWXZ\gmyyhcoutvsrrrnlmliigfbhe]``bbb`_`^YVSPSTBCBE;20013>VQYmuq_MJRTTSSSSTVVVYZ[XXWWYXWXWUMGEKMT[bemSAIIJONNNMNOMLLLMMRTXWWX][WNINQJNPSPQ]uZ>;==[wjmqsstuvsuxz~wrimpplfnqsulYPXekmpruuutvusu~xha`dtM#234445401EZ\afimqbVXZXURQPPOMQWXZ^aca_ZZXUVUTSSSRPOLJGJSW[aejrqmjgeb\YVRRQNOMMOOMZmvlgmlknt|}zuljmqmihdb_^^]]]\\[YYXUTSSSSSSRRSSSrpn{{yrppopnlkjigefffbab`]YXXUUY]ajtxtlgqsvvrrqmmkkkikiffe__^]__`^]`]YWUROKDBCB72244@P_R_u}dVXKQSSSTTTTSSQSVXVVWWVTUWWVVSTZ][bcRVQLOLLPONOOONKIILNOUUTSRRTUNGB@?67787@PbnjyzgO>8::Ixylnstuvvvtwvyylqqpootwwvj][akoosvzyyxvwvr}~tgaacdn~L*22556538O_]`dkrpaVYYXTPPPOKLRXXZ]___^ZYYWVTTTSSRQPNLIIRY\bhlttpjfdc]ZVSTQMMNLONLSht}rfddbhpu{ynhonmjhb]^^]^]\\[XXXWTTSRTSRSRRSQywtvxtrrpomhghheefhee`aa_]ZYXUXZ`elxyonrssspqolljhhhffcb_]]][\_`^\\ZXWTRKGCCA<33359420/-1?VSU^ddfgea[SG;578;86410000/++))(*,/112234444Jqvsy}{|~}~~~~}{vy{z}sidfkqv{~~|yw{}{ypoorrnmikzW>?18Sabdgipr_[[^YVVVUROKLSXZ\_`a_ZYWVVVVUVUSRQPOMJELX]chlnqnkggc_\WSQPNNNNMMMNObvw`ZXYZ\_aeqy|piikijhedccbaaa_`^[URSSRSRSRQQzzy|z}~}zrtttvy|shjohddcca_dieknq}wuuxwwvpopkihfda`_\YSPTYZcbZYWRPNLNLH@9431/9GIPfxdIIOQQQTWWVWWWXXYYZU[\SRSRSTTURSW`l_HNOMNMKJLPQSQNLLMNNPPVZ[`]XFEEA@=<965200...,,-,+,./1133332134Mrwu|||||~}~~}y{ytkhkqw{~|||~xutwwtqliv~8<2?Ybbdikpo[Z^_[VVVVSQLNTY[]^`a^[YXWWUVVVUTSQPOOKFMY]diloqokgeb_\XTQONNNMMMLJP`tz~}g[WYZY]\\kryxqibcjifeeccba```^\YWTSSSRQQQPz}{{{{{{zvswtwttxxkjlkcedbaa^cebgls{|}yuxwwysolhgfeb^[YTTPSWW_o`XXUPPQONKC961//5BHK`sjJEMOOPRTWXWZXX[ZXYYZ`YTSSTRSTVSTV`kaHIOPNMNKKNOQTRIIMOPQSVWZ[[eWABDA:;9520////.----,-.011212224:7Hfxwz||{}}{{{~}lbsrv{~}|||wyyztolo~I35H^bcfjnqkZ]^]ZWVVURPNRVXZ^`b`\ZZXXXVUUUUTSPQPOMIOX_ejntxslefc_][VQOONNLMLJIMXkt{j]WZ\Z[Y]fjlvzvkdcgjkhhhfdc`^_]Z[XVSTSRRPOzz{|yy{zzxuvvuyrqrtlgmmgdefcbbadcdhiq|x}yxutuwslhgeecb_][VVWZYYaiQQUSNQQNLJB;83/7BEJ\puSBMQSRQQSVVV^\W\][^Z\bYUUTSQQSTTTWgnmTGPQOONLMNNPTVNJJNRSRXZXT]hgLFGC9:8521///..---.--/011121234;8Dnuz}|{|}}~z{kMMwz}~}}y{{~~yromwP.8O_edhlqqeY\^\ZXVVTRPPU[]^_`aa\ZZXXXXUUTUTTRPPOMJKXabkpuyvlbec_\ZVPPOOONLLKKKTfp{k`]Z\]\Z^`cdiw|ujflkjiihgfb`^][[ZWWVURRRRvx}~|zz||xxysvvporokknihggffebddbbikvxqwwzxtssnggfffgffc]^]\]Z[b\KPQOPRPMKHD=<74AGHVlxj?IOQTTRTVWXYabYYZ\`[]_YWWUTRRSTTWVfnbLMSQPNNMMJMOPQQQOQSSQT^^Welo^MOE7875210/0...----./01010123469K|z~}|~~}{cHDEsx~~~wsqxK-@Vcghlntoa[\]\YXVTTQOPW_bddba_[YZXXXXVUSSRSRPPOMHNY`djov{xqieb^\ZVSPPNONNMMMKPbpx}}mbaZ]\\X[^_bbh}xuolmlmljihe``^Z[ZXXVTRRRSw{|||{xxvsvspopnllkiihiffeedcegin}ynossvwqppljjinjgje`\[\YWWY[POMKLNQPLHFB:;8CLLRfvrNAMQRSSUXWXXYac[WW[[Z\[ZYWVTSRRUWXYhqVIPSQQONNMKMMMNPUWTTOUZ`kpwxzrc\F46543100///...--./0//0001441;dy~~~|}~~{xfQD>@Bg~~y~~ytxB.D]dihnqvma^]\\ZXWUTROP\bbcdfd^[YXXXXVVVUTSTQQONMJQ[`djpv|ysmgc_[XUQPPNMMMMLMKM\nv|{z}t``Y]^\YVZ^^_]n|{zumnqnnnlihec`\[ZYXVTSSSSu|~}}~||yywvxsqqqmlkiiihigggdbccdgj~qksrrqpqpoonmlykeha]\\\YVW\TMMJGHLNNIFEB=9>JT[dspTEKQRSTUXYXWX\a`\XX\\YYYYYWVUSRSTUTSdjOQSTRPPOOLKMOLNPSWRRNY^`ksvwxzqeB35543100//...-.-./00//002331@n}{u{ki[OGA:47Acz~~uyC/Mbcghnuxk_^]\ZYXVUSROV^`_abhf^ZYYYXWWVVVTUSQQONLHQ[`djprywsogb_[XTRPOMMMLLMLLJWfq}zxzwd[Z\]YZXUYZ[Zdry~|zqmrqrqrpjiea_][ZXUSSSSSy~{||~ywwwxwuplmnmmjhhiigdedabcbbi}{mnrqqttwusmjjkqhfd^]]]\YWWVONLHGIJKJDDC?=?EU`kwy[HJNSSSVWYZYXW]`]ZY[][ZXYYYWVVSQRTRPWjiVWTVRQNQPNKMNNMNSXQNQX]gksmg\^^V946643210///.-.-./000//011316Ge~YKOJB:3-,3A\}}yxG3Ubcglnuvg^]_]XXWXWSONW^]]_`gf]ZZXXWVWVVUUTSRQONLIQ]bhknrtuqnib^\XUSRQMMLKKMMLIQ`kvxz{{{k\_[[YYXUSWX\_fnt}xqrruttrqkfb`][ZXWTSSSS~|z{{|vvtuxwskllnnolkjhgfeeecbcads{mnsrsssvutmhejjeea]]]\YXWVQOLJIJLNRP7;;?KV]fpw~nIINRTSTVXZYYXX^_YXY]a`[[ZZXWVVOMRTQRWha\YTVSQOOPONNNMMNTXSOV]fijreXQKMF446643210////...///00000111/8L]~~BA?;5/+)&1@Qv~}yO9[`dinqys`__`]YXXVVRMPY^]]_`df]\ZYXVUUVUUWUTSRPONKR^binqrrspnjd`[VUURQNMJIJKMLJL\jtwzz|t`\^^[YYWSTUTZagls{}zxwuuuunjdc^][ZXUTTSS~|{zzyyyzzvqqpmnmjiihfeglfbbbfl~xkpqrqqrpopoifkhgeb_]\ZYWTTRNLJNRQLZY/:?FWloisxvWDNRUVSVVYZYXXW\]ZX[\_c]_[XXXYWNOQRSSWa\ZXUWTQPPNOONNNNQTYUTYahejo]SNML?357644310//////.//00000/010.6Hg\151,+)**&.9Mb}}h<[egjouym^b`^]ZYXVSQNR[^]_``db\[ZXWWUUVVVWVUSRQOMMU\bhmpssqokhda\XTSRPMLKJIILJJM\gnvyywzd]^]ZYYXUTQNR[bdhq|}{rttrpngea]\[XTTSSS~}|zzzzuwzyssoookihihefflhedbep~|sprrrooppooouwlieca]]\ZXVUTQQOPQRNM[N2AJR]pzpplnQHQUVUVWXYZZZXY\[YXZ[^_^`^XVWXWOORRRPU[^ZWVXRQPQPPPOOOORTYWU[`fafkXQNMD85877643100///////000000/04529Qz0)*('(),+(*4JT{}~E\iklpvyf]b`^]YYXVSTOT]^^_`aa`\ZYXWVWUVWVVUUTSPNKOX^bhlptspmheb_]WUSQOKKJJIIIHILXelsuuz~xle_^[ZYXVSQOQVZ[^et~|{yvqpplgc]\[[WVTTS~~|||zxyxwvwyxtqppqmkigeeddfhfefp|{sprrqtroruw}txxjfcb`\\ZYXWUSQQRPONLJPC;HOXdt}q`^PNUXWUVXXZZYYZYZZWY[Z\Z\\\XVVUURQQRQRU^`TVXWTRSTQPPPOOOQUWZY\ajbaaSOKH=:999765321000/00000000///133.>]K &%)*()**+)/DMj||P^jmosxvb]``^\ZYXTSRQV^``a`ab_\[ZYZYWVVUVVUTSRQPMMY]bfnrwsqmiec_ZWURPOLJJJIIHHHGQ`jpuvy}}pe[]^\YWUSRRQOQX[]ht{}{vtrnje^\\[YVUTSzyywuvwvwtpppomliecedceffehyvqorrswvu{vpqqpfccb_]\ZWWUURPPQNNLKLE>CJTXly{q\PUWWWYZVVXY[[ZXYYXXXZ[[ZZZZYYVVVVQQPOOQS_`TVWXTQSRQPPPONNOUY`]\akcZYRKD=9;;9876432110000000000000012/-Hq}'"))***)*++'+>>><;::977654321110000000000000@Z{/")*****+,,++')8Gy{dvw{ta^_^][YXWUSPRY]\]^___ZYXVWVWWVTUTTSSSQQOMJMY`ellpsrmjihb^[XTQOLLJHIIFFFEDET`owux~zk]Z]][YURQPNMKMPQPRYbkuv|~yvqijhe`\XWW~}yxywvuvvwsrrpnmllkfdcehefeeo{|zwutwvpqpnnnnlkjmmfb`^]Z^\YYWURRPLCDEFJKWmlYPOPSTTZ^_\YZY\\\^_^_^`^\[ZZZ[YXYZ[VUURQQQSUY`c\[VTSTTOLIKNOUY\`dfjdYZYUNI?@>>=<;::97654322211100111111012?[{i')+++*+*++++)%3U}hu{|o]^__\YXXXVSRW\^^_^^^]YXWWVVVUUTUTSSRRRPOKIP[bfloproljgd_^[XSPNLKIHGHGFFCEEP\ltuuy}zpa[^\[VTQOOLLLNNNNPSZblluzxupmlgdaZYX~}wxwwuvuvtrqolmlkihe`cefcfkoz{ywvzvqpnnlkjjifghd`__cf\^\ZXURROE?FEFJOfnZNPQSTSSTZ^aZY\[\_^`_^^b_][[[[]YXY[[XVUSQQPTVUebUUUUTWXSRT[^^^[[_bchj\VXUPH?A?>><;;:98755433211100111111121?YwA!))*******+,)'9rźqo}~i]___\XYYXTRRYafb`_^^[WWWWUVUUTSSTRRQRRPOKHQ\`ejmpqmhgfc_][WRONKJIHFGFFEEFEKXhrstx{yqb[]\ZVTPONLLMMMLNPPS]gdmxytqmmigc][Y|zuuxwuuvuvrrqlmlkjgddgjjhorywywvvuqqoonlkigfdcdbb_]fk^_\YYVTTOFBFEEE]ncMOSUUSTSQWZ_[W\Z]_^``__a`][ZYZ\YXYZYVVURNOPSUWhbPRRRRVVSW]ehik`Y_ceincXXURF>A@?>=;;:99865443211111111111031@Wsu*'*+))****+++("6qɽtm}~`^``^[ZYYWVRT]cfdba__ZUVWVUUUUUSSSRRRRRQNKIRZ_cgkrrkjhea_]ZWRPNKJIGGGEFEEEFK[gtstuzzmc]^\ZUTQONKLLKKLLLLRY]\ds{uuogglgd\Z{vywvxytsusrpmoolmkifhhkomksyzvvvuuwnmlmjhjgggddfea`aff^^[YZWUULHHJIK]tkRNSUUTTTTTVX[\Y]]_`a__^`_^[[Z[[[YYXXWWVWVYPRSR\j^QUSRRTVWZ]ghiz{ijlkork]XUQB@B@?>=;;::987544321221111121012/?VqŽ\%,-,,,+))*+**&)Rotp||^``^_[YXXVTQX``bbaba^YTUWUUTTTTSSRRRRQRPNJHS\^bhlqrlhedb^\ZWRMLLJJIGGGFFDFGJWguxuvy{o`[[[ZVTROMLJJIJJJJJQVWWamt}}z{yknffb^yuzyyxtwvppomonlllljjikomkt}usqtuw{unlmikigggeefb_`bf_\\ZXUUSLGJNOOUty[NRVUVUTTTSUUX^___`aa`_^^_][[ZZZZZYWXWWVWW`UOPUchXTUSSUVYZ^apru}xx{q_YVP@A@A??=<;:;987654322222110221111/=<;;:87554322222111221011-:PjǺn'/11111/...,++,/@~ÿźȷxqe^c``[ZXZXURV\cbaabbfZTVVTUTTSSUVTSRRQQQPMJJV[^cglpslgdb__^ZVSPLLJJGGIIGFFDEHS_hrrtw~yd`\[[WUSOMLIIGGGGIKLMSW[[fr{zwvpmn~yvkjmokifhggggedeedejqrzotttttstrpjiigggfbbbca]^`^]Z\]ZXYSEOPPUaprRMUYWUWVUTUUWWX^dca`cb``][\^\[Y[XYYXWVVVUTV]WXa^gRNRUUWYZZ\envnghabkxp`_KACCA@??><<;:98764423221111111110,8Uy»T)0111111000..-,3NƾƽȰxsd_cb_ZZYZWTSY^aaaaabaYSVUTUUUXYYYWVURQQSOLHJW^`dgkoqhfd`_]]YWTQMLKJHHIHGFFCBEO\fnrtt{we][ZZXUPNMJIHFGGHHIJLMPSV]gs}tpoi}~~wsniedbea`_b^__dox{}xpuvuutspnjeefffgdbcdcbbdd_^^]TVXVMRPSWfouaPTWXWXWVUTSTUWY^dea_aa__]YZ]\YZYXXXWVVTRRPTWTX`hfNRUWTY[`cikoqkeb\cchq{tcHADDB@@?><<;::9675332321211111110.7Ww»w7.012111111011.,<<<::876433322111111110105Nd¿E,0333323321000.*?NÚ pr]bca`ZZYZVSYacbbbbba^XVUTUUUUWWXWWXXVSSQOMIKYacdhknmgceb_]\ZVUQNJIIGGHHGGFEBEMXbhorwywph__]XTPNLJIHGFEDDEHILLLJPWes~|~{||{{x{{|}}~~rrsrssqonmlhgghgkgaedca_cd`^\f^OSTZgpz{SS[][[Z[XXXVVXZ[^chkia__`_[[[\][XWVUTQR[_ipthhours]QWVVWZadkukggda]``aaeiibaaOBEFEDA@?>>=<<;8754444421112211122.5Pna/.22333333333110-@QŠȽwue^db`_X[ZYUU[aedcdbaa\YWUTUTUVUVXVUVWVTTROLLPY_cfikmheba^_]ZXUTRMJIIIHHGGHGFEEIW`klpvzyrha^]ZXTOLJIGFEEEDDGGIJLKLQ\l||xyxz{~}|w{puz{zz}~uvztnstrqqqqpronigfdgb_```_`_^[YZ`QLX`fy}xbQV]]]\Z[ZXYWWYY]^adeea^^^]\[ZZ\XWWRU\^bijkooeejtmjTRVVWY^aciojhd_^]]_`cfc]YXWHFFEEDBA@?>><<;76544445411122121205Mg~:.033333333333222,CWŧǸmxy`afdd`Y[YYVW_ffdeddfc\YXWVVUUWVVWWVUVVTSPOKMT^acgflpgdb`_^\XURSROKIJJHHIIGFGEDFV_koqtwvsnc^][WTPKIIGEEECCDFGGJJKMNSf|xvw{}}{ytr{sotwz|~|yy{{rswxorzvpqqonnmgefdcfa``a`_^[[YWY[RYhlhy~vmph]\]__^\\[YXYYXX[]^^`^^`c__]ZWUVYXZ^bejjkib^dc^bdmfcVRTTVZ_cejkkh_[ZYZ\_cd_ZYVPEHGFEDBA@??><<;76555544311122111038AQ\}¿W*1231333333333332,D]ŬýƳi|s`ceefc[ZZXZ]ciigfedga\YXWVUUVWWVWWWUVVTQQOKMXbdcghnogbb_`^[XVTRSPLKKHIHHGHGGFEDT^jrtuwvsng`[ZYUPKJHGEDEDBCFGFIJKNLP`wuyy}~~yqurvyystvxxz}xutztpuwtpu}wsqppkkifffddcbbbc`_]ZYWWYWV_ihjvymljb^a___^]^[ZY[[Z\]]^^_`_cge^WWXZ`gggfffdcda[]b`\`cfbb[XVYa^^chnlg]XWTSVZ]__ZYXRHFHGFECBAA@??=<;976776433212222211488ESe¾2.0333333333444333*F[IJ½®jtheeeeb]YXSWbijkkgedb]\ZWWWWVVWWWWWWWXWUSPNIN]dddinolgbb_`_\XUSRRPMLKLKHIHHFFFFJR`msvuzypmj`][XSOLIIFEEDECCEFFHJKLLLVswzz|}~ytvx{yutwvuu{|wtvwssuspoouyqsppmkkihhhfebbabc_]\ZXY[WVZ`eluztihd_c````^^^\\][]]]]^_``_``chi_aekroeab`]_^^^\_`]]^ad`^a\X^g``flpnbYVSQQSWY[ZYWTMIHHHFDDBAA@??><:975777443212322112589=M[tĿúf&01222232222333320+PYĵ»þxp|mjifdbb]XWSXgmknkifd`[ZYWWWWWVWXXXWWWWVURQOKR`dfgkmokfbaaa^\XUSQQNMMLKJIGHHFGFCEP^gmtt{rlib_\YTPLJGGFDDEDDFEFGHKKMLNkw{{}}|zy{|{yquvuux|}wxwusromrqrsqqsomkjjijhddcbab`_\\]]]ZY\[[kruujha`a`aba`^_``_`_^^^__`_^^^_biwvnlkln^Z]]^^][^_`^___`]\`d^Z`dcdiopj^XVSRQTUWXXWUOJKIIGFEEBAA@@@><:9767864331122212124688ESm@*/11112222122322200O`õsuwiggdaaa\WUT]ilklmkhc][YXXWWWVVVXYYWWWWVVSPPLVcfgiklpldaa`_][XUSQONMOLKJJHJJFFFBCO\fjrszxnge`]YTPMJGFFCDDCEFFEGHJJKMK_{}}|||{}}zvuvvxz}|ywuutolmqpsopsrqmhfgghebb``aa__^]_`__d[\nz{xpb_X[_`abaab`aecec]__`_^^^_`dhksxlcbbg`Z]^_^_`^``__^`_YZ^dbY^dehlnkaZVTTTSTUUVVURNLLJIGFFFCCBB@?=;9887786432222222112221/;Nc¿u&/0221111112122211/.HdĶysrffeb``a]VSWckjiijnkb^][ZYWWVWWWWXWWVVVUVUROMXekjklosna__]]\[YWTQNMNOMKJKJIIHHHCES]fkqrv~}phgb]YTQOKGFCDBBCEFFEGGFHJKNYt~}}||}}}}zvwxwx{~yyvrssonpoifehkjjjb`babd_abaa`^^^]\]bbfcq||zneb^]]__abacfbbedcb__`b_^``abggkpvg\cbc^]``_```\^`^_`]YZ]^ef_aefhkmg[WUTTTTSTUTTRPNNMKJIFFEECBB@?<;:88878654332222111110.*2F\ùC)011222112111211111-HY·}qife`b`_`]SR[eghhhinog`_]ZYWVWWVVWXWXVUVVUTSNO\fhimpswp_``_\ZXXVSPNMMNNLKJJJIIHHFFO^elsuwz}tnhb^XTRNKHEDCA@CFDEDDGGIJJKQk}~}~}}|}yxzxxzz~|yxurrrqrssrydju|upliif]\\[[ZWXXTWZ_afs|}wnb_`^^`_aab`dgeddccaa``a__bbcehgkuzi[aa`^`aaa`_]Z]`^__][^_cimgbefhlncUTTUUTUTTTSTSPOMLLKIGFFFBAA@>;;9889877644322221121110++>Vwżg*+011111111111111112+ESwy]cdab__^\VQ\fefgginogba^\XWWWWVWWXWWVVUTSTSPQ]gjiorrwobba^[ZXWVRPNMNNMKLKJJJIGGGEL]gjqty}~tpje_XTQOLJHFA@AABCDBDGHJJGIKd~yyx|~~~~~~~||{{{{|yxtqruvutptuy|zwqjhc]]^a]XW`flpy~piddda__`b`aadfifccc`aaabaaccdhiin}whcg``_a``a_aa\]a\]c``abeiqncfhjliXSTTUTTUTTTTTROONKLKKHGEECCA@=::989877655432222122110/+):Pqȼ<*.010111000001011112/?Ovu]Y]`_^\YYY^fdfhihlmfc`^^ZWXXWWWXXWUUUTTTSQPVakopssuvodea^\ZXVTRPONMLMMNMLJJIHFEDK\ejquy~~smif`[WSQNKHGCABBBBDDCFFHHIIKa}|uropp{~~~~}}|~{{|{}{yxvtprrpjpv}opysvrrpopw{{xy{zx~}ydggcdbaaaaa`_bdhdddcbbcbccddcehihk{rbhn``__a_^`ac`cje^_aaceehupafijj`STTTTTUUTTTTSRPOMLLKKHFEEDCB?=::99:877655432332212110.+&3Lk»K,-0000000000000011111/:OtſnVTY[ZVW]aeedegighcaa_^[YXXXYXXXXVVTVTSQPOZgorssvzyogda^\[XVSSPONNLMMNMMJJJJHFFJ]fmvux~ulhfc]YUQNJIFDABCBBBECDFHHIFJ^~riegbgs{~|}}{}}}~zzyvtnqokiqwzrx{hmnnnqsz}~srvvz}u{v~ui`hedbcbbaaa__aeigeeefffecedefghgflzg\fi`_]``_bbefgku}b]befemzvbgijeZTQTTTTUUTTTSSRPOLMKKJGFFECB@><::9:988775543333322201/-*$.Gdºſ`/+.0111000000/0/011111-7PjlTQUVS_bdfeeefida`__^]ZYXYXXYXXWVSTTSROO\lrqqtxzynidb^[ZWWTRPOONMMMMMNJJJKIFHK]foxwz~~snhda^XWTPJHGFCBBBCDCCBEGHGFH[~qb^\[^krv{~{zywwtqqomlqvusveedllnnosuulnnnrwrt|wtjdgbd`addaca^acfkldfhggfeeeefffggfjq`\dda`____`bhnrzibedep}ybdfe^VTSTUUTTSSTTSSRPNMLLKKIHFDBB><;999::9786544334331221/.+*%+DZy¾v8)..////000000///000110-7MbĻĸcHPVbdeheefgga`a]^^]][YZZYYXWVWUVSTSPQ]qustuxwsldc`][ZXVSRPOOOONMMNPMIIJIJIK[grywyzzrlid_][XVQLKHHHDBBBBBBBCFGGFEX|uf]ZXZckmsz~{xwwtqonmtwsoou~|ghjkiimsryllqpnoqot~{{yghfeigbdcccbbcdfklbfiihgffefeefeefhoa_fdcbbbehgkx~~|}x~rilkp}zb_caXVVWVUUTSSSTTSRQONLKJKJHIFCAA=<:::::98776544433221111/-*)&)=VtC*,..0../0000/0/000/0111/6H\ûĸoGSdccffedfc`__^`_^]][[[ZYZWVWUTQPQNT_ntvxwyvphea^][[XURPOOONONNNMPLKIHHKHLYmx~{zz|smjea]ZYUPNMIGGDDBBBBBCCEFGFHUwwgaYYZ\gjlnvw~|wwvtqonnwrpqrw|snjljgjlmrzerrlqriirvuqs|fheejleefdedfeejmjfghjihfefdcddegiqxdcheeefbeoqzvvlba`s|xtts|{d^`]VWXXWVUUTTTTTSRPOMLKIJJHHFCA?=<;::::97876554443221100.-+*&%6Rj~J-)-../.--/00000000000011.3G[½|P\fbbdea`^^^^^`dd]\[\\[YXWWVTRQONMYclpsv{yuoiiea][YWTSQOPOONNOONPNKJIIHHN^qs{}|}rlida^[YURQNJIGCCBCBBBBCDFECHVuvchZZ\^acjhjnwzywtuuqpopspppqsywnkjjijkjjqshpnjnpmlrtpqveeffiigfgggehfeorjpqkjjg`cgfdhghkmye`ddefiipuypig^^__gzyrvyzi_^[WYXXXWUUUTTTTSPONMLKJJJHGEDA><<;;;;:8876756444222100/-+))'$0F[jyM1&+-------///0000/0000110-.D\|tqtskolorvS_aaba`]\]\\]_gg_\[\[[XWWWUTQPOLM\elrvz}~xnjjic^ZVWTRPPPPPOPPONNMLKLJJJP^muw|{~ukiea^[XUSQPNKHEECCCCBBDCDDADVyygf]Y\\\]fjgenqw|xwqssrrppqpqprrstmkkkjiklknmhmmllopqplmos|jfghihhifijhiggrsmxwmkkmkpuojmihjnvzlbdikiot{y|shi_Z[^adcu|yt{|j^]\YYYXXWUUUUUUSRPNNMLLKKJIGEC@=<<;;<;:8777765542231100.-*)(((-;R[{ĽmJ3&*,,,,,,-----.//00/00010/,+D\|vg`^`]]]\]^bjvùR^aaa^[Z[[\^_dd^]]\[ZXWVVUSQPOKM\elswz|pkkhe_YWVURQPPQPPPNNMNMOMLLLJP]lzzw|wkgfa_[WVSRPMKIFECBBCBCCBCCADWp|wmga^_][[`fgdjisy{zvroopppoopqsrkjlmllmkikkkmkllmpqodelrsjhhiihhhjjjkkkouuptupoqsvzjehhfjqtxvkfkoosvyxxtnsmcVXZ]`clw}~h_]\[ZYWWWUVUVUTSQPNNMMKKKKIGDB?=<<;;<;98887665543222110-,))))*+2APfriF2')+,,,++++,------///000/20.'C]wlv|_XYXVURSRRTTXbktƾhWeb`]ZZY[\]^`_^]][[[ZWWVUSQPNIP_fmsw{~ukjfc`\XVTSQPPOPQPPPNMOOMJJLKO[lywyz~xmfca_[YUSROLKKGECBBACCCCCDBDSh}yjjd^__^`^ba_bdjorw}|urpqqomportqkloolnnljiiimmkkmoutfdjpokhhhijijkklklotyppsvruur~~cfgmszqqvxoejptyyyurrswncWUWZ_ekp~ja^]\[YXWWWVVVUSQQPOMNMKKKHGFC@?<;;;<;;9988866654432210.,*()*),..3FUbzgD1*+,,+,,,,,++,----.....///10.)D[ujc]][]MKMLKJIHGILILSU\hsRab^YYZY\]]]]]^\][ZZ[XVWTTQNMMQdhkqry~ytkd`_]XVTSSPOOPQRQPMMNNLJIJKNXnwvyz}|yqhdb^]YUSROKJJHEDCBBCCDBBBBDNbvzkhc\^_aa_^ZZZY`djnt}}~~z~{sqppppqprvupmolonmopkhehplhimpsxleiqoomihijkkjkkmqrz{rtw{y}}|wpwy}zpsytehr|~zsqtrrpbXTUX_ejmuuc_^\[ZXWXWVUVVSQQPNMNMKJKGFEB@>=;<;<;;898876655443210/-,(()*)-/01>964112578788;BFGMQUs}´ZZc]XXXX\[\]]]]]\[[ZXXVUUTQNJJTbgjnrtzzsqnnf]]]ZXWUTSRRPRSQPPMMKJIJIGK]kuvw|vriea_\YVTRNMKJFDDCCCCCDBBAC@HZm|~mlg`ab`_^^[XUSVZ\\ahytuvwzzxx}xpqqpqnnsuyvsrpqqonnolhhjoxlknnqqxvhhikmnihmljloutvz~{xz{xtupxmsv{spnooniifYSV_bdirvw|s`^_^\[ZYXWUTRQRQQPONNLKJIFDB@>=<<=<;;;:89876655543110-+(())),./2211?P_|_D6-23343221.--+,-,,-,,,,,----.-/,)BU{vcWTFA?AA@ABD<;<;::9988>EJm{jyĬ\[`\YWYX[[\\\\]\\[ZYWWWSTTQNHKXaijnrsusqolkke_\ZZWVTRRQPQRRQOMNLJJIIFM^iwwy{wsjfba\XVTQNKJIFDCBBDCDDDB?@>AUg{pmh`cc`__]YVVRNU[\]a~|}ysrttsqtsqz{qrsrrstx||qqplnpnnmlnmilwljpoqosokjimnpprqtwxs{{}}}{toppunrxx{ynqoppqnji`VU]adgjiflf``^]\[ZXXWUTRQQQQPPOOMKIHEBA@?==<=<<;;:8987766544322.,)()()),/023212CVk\A30244433343100/.-,,,,,,,--,---.-,(@Txy_MF?7;IK@AA?ACT\K<;;;;;;99856HOQVYZfw|{}Ź][^[ZXXXZ[\\\\\[ZYYXWWWTRRQMHL[djjnprsqnljhifb^ZYWWTRQQQQQRQONMMLIIJHM^luvv{yshfc_[XVTQNJJHFDBCBBCCCCBB>>BTfy~}}olh`bdc_^]XWUTQLSV[\}{yvsompoomllpw|z|}wuutttuw}zprqnopqppqpkllsvpmnoqopjlnjlourqsy|zoz|{~||w{{xv~srt}psxwxsnrpqrsqlje^WX_cdefehea_]\\YXWVVUSRRQQQPOONLKIFDCB@>====<;;;99988786645300.+)()()*-/022322;L_o~qTA203555444444333200/-,,,,,,,+,,---.(;QmdL=41AIB?:;;::@EFA:::::9;:::95>ADHGKS_adf^r·z]][Z[ZYY[\\[\\\[ZXXXXWVUTRPKIR_giklnrsqlijgfcb^ZXUTTRQQQPQQPQNLLKLJHEL^jtzx}zqjfd_][VUQNJIHGDCBABCCABCB@=?P_w~~~}tlcabdba^[ZXUVSOMOV\}ywspmjhijihhhmosqqw{z{ywyxxuorsqrpqopqpmkmqsppqpkkgkopnosxusrvvyvq}xyywtsqx~wrx~|{puzysppusttsrnnje\W\`bbcddda_]\ZYWWVUTRQQQQQQPNMKJFDCBA>====><;;;:888777654430.-))))))+.01122333AS]huúymaP@4145555554544443332010/-,,,,,,-.-..(7Me|N;13;A?:<<;87<>=?>::9::9::9:89?<=?;?GNNMOMkr[]ZZ[ZZY\\[\\\[[ZXXXXWVTSRNJIXgkijnorqlifhfdba]ZWTRSQQQQQPQPPOLLKLJFEM]ftx{|xqkhc_]ZWUROKIHEDBABBCBAACBA>>IZs||z||wmb`baca^\ZVUTSRPPQT{vqmjhgefedeffijlkkp|}{|qsppqrrrqppoqoquoojhhjmnrtvuux~rswuruyvqogjpty}|ysu~pw}zpluwvuturrrkhbZZ\_`accba_][ZXWWVTRRRRQQQQONMKHEDCB?======<;;;:888776554420/+)))))*,//12334336BPWbuyaYQH<2254555556555654444432220..,,,,,.-.,'4Jff:/58:;;;<:999;<;?<8::9:::99:9:?@A=67:7;:>@_}}~{|~yg][ZZZZYY\\[\[\\[ZXXXXWVTRQLIO^hkkknoqnjfedca`_^YXURRQPPQOOPPQPMLLLJHDL\nuv{z}xkedc`^ZWTQOLIHFDBCAABBABB@@=>>>==<<::9987776654420/*())))*,/1122234455>JWexeVLD;41255444555656666554445442221/.-,,..--(0JeP.059889898888:;:<:9999::998999;??;7898855Df|~vxzwywutywl__]Z[[ZYZ[\\\[\[[YYXYXXWURPMHV`fjmmooqkgeddb``^][YUUSRQPPQQOQQQNKKLIIDL^orwxy{xmdbc`\ZWTPOKIHECAABBAAAA@@?<:BUhvy|y{~xjgefgea`\[XVUTRQPOO|xsqpkhdccbbbddcbcfimyz}{~styzzwwyxvutx}zw~}vpvx}uux|}}|wt{nbdedcfjnpuwtsqtz{yxtprwxyywxxwutpomeXW\^`_ba__\ZZXVVTSSQQQPQPOONLIFEDA????>?>==;;::98987665431/-*))))*+-/12223345353=MXblx¾^QG=513565565555666666666555555444310.....-/)-Gdžs;,246779776676889988889999898999;:8::::975Op|zqttprrqkoyx}smb_`][[[[Z[\]\\[ZZZYYYYWXXVROMKYceiknpokhebbda_^][ZXVUTSQPQQQQPPQOKKJJGCL_kmtwzx{togdb_ZYVSPOLHGFEABAAAAA@@@?=:?Qds{yy~zjggeghe`_]YXVRRQPNOxtqnlhddb`a``baacffkt}{}wswxx{v{tqw{vw{{ztmlphbcaabcfjntuuroqx{|ywqsyy{}yywxvuqpoj]WZ\]_aa_^]ZYXWVUSRRQQQQPONKJIFDCA??????>==<;;989987665431/-+)**)*+-0122233455635?MUZeus[OC8446786556555566666766667655655533211/....**D`û]+0643577655444567777888998898989999899::5=^v}yrrqja`deaimpsqfabc_]\[[[Z[\\]\[ZZZYYYZWXWTRQMO^cefilmpic`abb_\[[ZXWVTSRQPPPPQRQRPMLJJFEJ_mpsvyz}sljgb_YXVSQOLIHGFCABBAA@@@@@<8=Qfuzwy~}ifgikifa`^ZXVRQPOON}xupjiheab`__``_accclw|~tv{}}yzytz~~tx}zvsmjkig__^^a`chmptvtpry}~xtqvyz}}~vtwwvtqqleYW[]_a``^\ZYWVTSSRRQRQPPOLJHFECAA???@?@===<;:998988665310/-+*+***,/02222223467657;BKVdxiZNA<88899666554555566666666767666655544432///-,'F[vůG(24334554344445566677778788899:9999::;;85Eh{xssmd``^[[_cecfccdb_\\[[[Z\^\\[ZZZZZYZYXWVSRPKT`cegikmng^^__^^[[ZYXVUSSRQQPPPQQQQOMKJIHJO_mquyy||ukfea^XXUQOMKHGFECBBBBB@@??@=7;Odsxxz|qebfhhed`^ZXWURQOON|wupihgebb`_`_`b^bbfuz|z{yyy{{{}|vu|~vsuz~vy|ztpkighfd`]]^`adgjnrvvrty{|zsyz{}~}~yuwwwtsrokbY[^__a`][YXWVSSSSRRRQPPNKIGEEB@@@??@?@===:;9:9998876431/.-,,++*+-01223222335666545;IXbho~|hYOEBC<:8887555555545546667666776677556555443231-'BRnȾg3-233433333333455556666787788898:999:9<;57Sq}}uvsjabb]\_cddbcccda^[\[Z[\]_\[[[ZZZZZZZXXUSSQKWbefhiimoe`]]]\[ZZZYYVTRSPPPPPPQPQPNMJKIGJS_mrxx|wnedb^YWTPNLKIGDBA@BCBB?@><<=9:J\oxyy{~uidecceda\YXWTTROPN|wvniheecb`_`^_aadgox{vxpnosuz}|zss{{vtrps}ytvurqmgfdab`]\^cadfilquxurvyyx~~}}~~|{wvvvvttrpi\Z]^``_\[YXWURSSSRRRPOPNJHFFDA@@??@@??===;;::99998754210-,+++*+,-012323334355666445=GORWaoveVNKFGD?<77655555555555466666667667776666555455431+8Niƿ~P*1233323334333355556677777888999899:99;93Bcw|rrsri`c`\^bfffddcce`]\[[[[[]^\\[[ZZZZZZZYXVSQML[dgiihhond`]\\\[YXYXYWSQRONOOQPPQPPPMJLKEHU^qwxy{}{xogea`ZXTPNJJIGC@??AC@@?@><;;89I]hquwy|~wmhhdcdc`]\YVTSRPONzuomiffda`_]^]]bgkqy~~pkjlmmpssnloqqz{ursppxtqqolkiigc`a`][`ccefinqtwyz}~x}|||}~~|{{uvvwvsstpb[[___][ZXWVUTSSRRQQPOMKHGDCBA@@??A??>=<<;;:99898876221.-,**+*,,/12432333333566776458=@HR[_eqmaTQOOMIEB=;865554334445556666666767677666665555554514N^xg<)233333333433234556568887778789999999;966Lm|}omoog`aa\^dgfedeedb^\]\[[[\]\\[[[[ZZZZZ[ZYUTPJPagghjkjpl^^^[\ZZZYYYXVSRROOOOPOPPPPOLJLJEHQaruvzz|ztnjh`^ZXTQMKJHGC@??AB@??>>=<<:7EZjtxy}~~{qkjiecba_\XUUSSPOM~xtpnkheeb`^^]^^cglpw{|{wxysichkkmpkgjiknqtzuponnpt|}tpoifhfdbaacg`Y_cefhimqx}~|yy{{}|}}|z|vvwwxvsttk`\_^^\[YWVVUTSRRQQPOMKIGFDBAA@@@@@??>=<<;;:98899875200.,+++*+,./12334343333556654422./8EMLR\pweZTQRRPNJFD>=865444334344456666666667777766666566666653FYhujM,-233333334343334555568778777889998989:74>Wqz~nkmleb`][afgfeedfc`^][[[[[\\\[[[\[[Z[Z[[YYVSOLXhlgfgijlg]]][YZYYYYYXTSRQRONOPPOPOPNLHIHGGQdpstyy{xrkiia\ZYURNLHHEC@?@A@??>>>=<<;6BWerxz}rjiiheb`^[WUTTRQOK~xtnolhfeb`_]^_`dhnquvsmpqqmkkgfghhhffghhmrqtsnjilnsz}wvphffc__abfnqiddggjmpsv}}{yyxz|{wvz{||}||||{wuvvxxwvwsf^\]^\[ZWVVTUTQRRQPMLIHGFDCAA@@@A@??>=<<<;;98898774210.+++++,./02244444444445654462.***27956333333334435656666666677667777766667651;RZdmmmpodQ9*1333333334443444465567777787887899989954I_tytmjheb`^[[bhigedeeb_^]\\[[\\\[[[[[[[ZZZYYZYVRMN]kmjjjjlh^_]\ZYZZYYWWWVSQPPOOOOOOONONMJIHHHSdotwyy}vrmjha^[YURPMJGCBA?A@@@?>>===<;7=Sanv{}snlmjgc`][WUTSRPNN}|xsqpmifeca^]]^adgloosz~zkghihjgejhbeddddegghmnpsrnjklmpx{xsfaba``abegkqojhgjknooqy{{yuvsvyvtvxy|{}}}}{yvuuwxxywvvm^Z\\[ZYXVUUTSRRQPOMJIGFDCBBA@@BA@??>>=<<;;;98887642/.-,,,,,--/12234344454454544442/+)((),6EOkRRPRTVTSROMIFB>:764333333334345556566667676667777777777744DTY[ZV\\RA,.3233433444343555556667788888898889898939Tn}gjfdb_\]\]kmlifdfcb\YY\\Z[\\]\\[\[[[[[ZYYZXVRMSchilmlmmg]^^[YZYXXWVVUUURPONOPPPQONNONJJJIJReqy|{~tkdeea[ZXTRNKIFDA?A@@?@?===<<:8=N^nz}~vpijnia`][VUSSQQPN|{yronmhffd`_^]]`dijnopvxyodbefefdcecaaa``bcdggegkqrmmlnnpx~vjb_`_`aadefigfgeehjjkjos{{yusrrssrsuxy||~~}zzywuxvyzwxuqd\[[ZXWVVUUSSQQPNNLJHGEDBBA@@@AA@??>>=<<;<:98887631..,,,,,,-./22233454455544444441/+)***)+5H`\LOQTUTTSRPMKGC?<8652233333333446565666666666677777777777546AKPOPQMC2-1322343344344444555667677888889889999982Cexzfieda^]^agqqlkjgd`XVSPTYZ[\\\\\[Z[ZZ\\[ZYXWUQO\ihhlqsspd\^\[YWWWWWVUTTURPPPPPQQPONMNMKKKIJSdty}woggea\ZYTQMKIGB??A@A???>=<<;;:;L[oy||}ypiilhaa\ZWTSSRQON~{upommhffdb_^^]`dhigkoopmgccbcdc_]]]a`^^^^`bdcbginrolloprx||}ib`a``aaaddceefdbdghiiinqu{ytrprqqpruvx{||~}|z{yuyyxxyxvtj\\[XWVVVTTTRRPONNKHGFECA@AA@@AA@?>>>=<<<;988877530--,,,----.022234444445444444421-,-+*+)'%=WþEOQSSSUTRSOMLJEA=:74323333333344555666666666676778777777788527<<>>:3133222334333334455555676778888888889999955Qkyqdgb`^__admnlmnmh`]du~qXQYZ[\\[[\[[\[[[\ZXWVSNTakfjntqopd]_\ZXXWXWWVUSTTTPONPQQQOOONLMJJKGGTiywutqjc_^ZXURNLHGA?AAAB??>==<;;;85FZkuzz~yunlkhba^ZWTSRRQPN{yrqnljhgdb``^^adfhggihhedc`_^]\Y\\\\\]]^`abaabeilssnloqstttwvqgdbcbbbabccceffdccffghimpsyxtrlkmmlnquxx{}~~{xwwyzz{zwto`ZYWWVUTTTRQROOMLIGFFECAAA@AAA@??>>==<<<;98989742/,,----,--/12324444445554443431/-+,,*)'),>_µĬ\HQRSTUTTSROOLHFB?;8633233212333445555666656666666777777778898886445577754533233344345566667777888887889999:85@\s~|occ`_^`ccdiijkjldaqvXSZ[\\\\\\\\Z[\Z[XVTPMXfjjnoqqpkd^_]\XVVVUUUVUUTSQQOPQQPPPPMMLIJJHJWo{{xoolfb^ZVTSPKIGDBABAA??>>==;9977@Yjtz{~~unnkfb`^ZWURRQPONz}yspomihfecaa__`accfefeba^]]\\[[ZZ[Z\]]]_``aaadehlssoloqqprtstndbbbbabbbdddddedbcdefehklpsvupjekmmlosvxz}}}}|zyzzzz{z|wsd[XXVUTTSRRRPOMKJHGFFEDB@AABBA???>====<<;89999730.,,-----,./23334444455554443430/.+),-36=;:857>Ufpyx}vonjib_^[WUTRQPNN||ztpnmhggfca```_`_`adc_]]\\[ZYZ[[ZZ[\\\^_``aacefgmttpnponpqrusnfcccbbbabdddecdccdddddgjjnpvwqlgkllmmotx{~~~~}{|z||{|z{xi[ZWVUSSSSRQPNKKHHGFEDCAA@ABB@?@?>>===<<;9999872/.,--..---.023334444565554443420/.+-48965.3Lrƴ_EMQRSTSTTSRPONKHFB=:7322233333333454444555555565665565778788::::;99898788988753333234556666777888888789999983;Yqz{oea`````_`cfglmnor|}qsw_VZ]]\\\\\\ZZ[ZYWTSOR]lpqsqoqod`a]\YYWUUUTTUUVUUTQPPOOPPONMMKJJHEO\qzsnkfb_[WURPLIHEDBCA@@?=>==<9:67?>>==<;:999:971/---..-..//123333445566654444320.--02100/+,FkºƚDLOOQQSUSSTRQONLJGC?<85233333334333444444444555566566777787888999;;:88888899:::9775445555666777788888889999883Igv}odbba``^^^^adfkprt|{snkq}{kYY\]]]\]\\[YYYYVSONReqqquurpkcca][YYVUTUUVTTTUVVRQQQPPPOOLMKJIKLO^w~wtqfd_^YWTPLJHGDCCBA@@>>>=<::76;N_muxy~|qnjgea`[XVTSRPPO{tsqqolmigdc``__^^]]]\ZZZZY[Z[WXXY[[\\^_^a`acdghkputsolooqqqmkjijhgfefeeeddcdcccccdeehjjmsutqlkmmmnoqux~~}~~|~~|{wyycVQTTRRQQPPMLIHGFFEECAAABBAA@@@?>>>==<;:999:751/.-...../.0234444455676565444320.,-.//000-*@g÷{?LOPRRSTTSTRPPOMKHEA>:7423222334443435444443555455566677877888999;;;;:999889:::<:88775656556677777888889999967Vmu~xedea`_`^]\[`dgjnot~zplijwznZ[]^]\]]][ZZYZWVRONYmsqprstqica_^[XWWVTTUUUTTVUWURRRQONNNMMKIHGIOcy}xsrmga\YXUQMJHGDDCBAA@?>=<;;;879KYiw|w||rnihfca\YVUSPQPP~}wtrqqolihfba`__^^\\\\ZWZZYYZYWWWZ[[[]]^^`babfgimrttqpjlnomkjjihhgfedefdddddddcccccdffjlmovuqmlmlmnnqux}~~}~yyxyi[OSSRRRPOMLJIHGFEEDAAAAABA@@???>?>==<;:99::740/.....././0245544555666566544320-,....../,(:_ǿưWEKPPQRRTSSSSQPNNLIGD?=8532222233434443444333444455566677788877999;;;;;:999:::9:;<=;;:888646566676778888999885C^mt{ldmja_^`]]][_dgjmpqz}vnigkwylY[^^^^]^]\[ZYYWUQNRamssrrsupfbc^\ZXVUVTTTUTTTTUUVTRRQPONNMKLKKGFQf{}}wqoojb][ZVRNKJGEECBA@A@>=<;;8878LWcuxu|~uoigfda]ZWUSQQPNSigima-1.1.1/sigima/data/tests/image_formats/000077500000000000000000000000001514013333200210575ustar00rootroot00000000000000Sigima-1.1.1/sigima/data/tests/image_formats/NF 180338201.scor-data000066400000000000000000165540001514013333200241460ustar00rootroot00000000000000[Header] Version=f4.00 Date= 1/ 4/2019 Time=10:52:21.15 PixelBitsFraction=7 Interlaced=0 EnergyOfBeam=0.00000000000000000e+00 EnergyOfFrame=0 EnergyUnits=6 Flags=2 AC=4 RS=0 GC=0 CommentLine=NF 180338201 WriteProtect=0 [Camera] Name=SCOR20 Path=C:\Spiricon\LBA-FW-SCOR\cameras\ File= Resolution=-1 FrameBufferSize=97552 NumberFrames=26 FramesPrecedence=1 SyncSource=1 PixelBits=8 PixelHScale=4.40000000000000036 PixelVScale=4.40000000000000036 PixelUnits=1 Gamma=1.00000000000000000e+00 Lens=0 SyncPolarity=0 ERCPolarity=0 TransferMode=2 ScanMode=0 Shutter=0 ShutterLabels=,,,,,,,, Integration=0 IntegrationPolarity=0 PLL=0,3,6,0,1909,1489,1024 HorizontalStart=0 HorizontalSize=1600 VerticalStart=0 VerticalSize=1200 [Capture] CaptureMethod=0 CaptureInterval=1 BlockLength=32 Integration=1 PostFrameBuffer=1 PostFile=0 PostFileName= PostStart=1 PostNumber=1 CameraInput1=1 CameraInput2=0 CameraInput3=0 CameraInput4=0 CameraInput=0 CameraShutter=0 CameraShutter2=0 CameraShutter3=0 CameraShutter4=0 CameraGain=146 CameraGain2=0 CameraGain3=0 CameraGain4=0 CameraGainEffect=3.16720724105834961 CameraGainEffect2=1.00000000000000000e+00 CameraGainEffect3=1.00000000000000000e+00 CameraGainEffect4=1.00000000000000000e+00 CameraBlack=76 CameraBlack2=0 CameraBlack3=0 CameraBlack4=0 TriggerType=1 PreTrigger=0 TriggerOutAlways=0 TriggerOutDelay=1 TriggerPolarity=1 TriggerInterval=1 IntegrateInterval=1 VideoTriggerLevel=2 VideoTriggerLevel2=0 VideoTriggerLevel3=0 VideoTriggerLevel4=0 Summing=0 SummingFrames=2 Average=0 AverageFrames=9 GainCorrect=0 ReferenceSubtract=0 Convolution=0 ReferenceSource=0 MaxFrameSize=1600,1200 ZoomIndex=0 NumZooms=1 CaptureLocation=0,0 CaptureSize=1600,1200 CaptureResolution=0 ZfX`\\RdbX\bbd^f\T\bbf`VTd\N^B\\\VRNZj`^T^^^\`ZT^\bZPTZV^bZVb\NP\LN^^R\N^ZJRbbLT\PXXZNVhJPNTPZRRPPVXPZVFP^\ZV\TbZP\H\HPZ`^LPVlZ\<V<JbJTZT\VPRBRRLPNJNPF\DTLNTZR\PTLVNPXTLT^NTVLXZXVX`.lXRNLT``LNZNZL\T\PFXNXVTRVXZRJZNV^TJZTRHXZZfVPVNbX`\PXfNTTP\RLJZ`BXh^fTVX^VXVbXjZVRP\T\BR`JP^^VXZZ\TV\RXTXXVZTXNFXPV^bTVRZf\FNThR\VjR\f^^RXRRHJ`fJTLJTRZXVRR`^R^LVX`RbbX\dHZTJhF^NN^JjJFZ`HXXHLX^F`LNTXLXP^V\NV^LRV\Xb\\\jbR^RfZZdfVRZNX^NRPHNX^TX\XZ^TNRjJNhRZlTD^LXfV^P\Tb`ThZZTV^Zb\^NF`DRNRHPXRR^TRXXVb^P\\\`VTXT^VTLZPVZ\DPJZVXPRRZLLR`LXNPTHfLV*ZXZLN\VXL\HRDRTbRTL`JNX^JZDJR^Z\TZPRNRH`TXZRJXRPR`TXLRLbLTXZZ\ZD^HZTf`LNT\Xf^\TVXVhVRVBDhRX^L LbHJ\`^XTVNXNhZT`Z^\PZZRZRXR\NVVbTPZX`VV`^NbfR\dLTNFVHZV^^\VZbZ`Z\ZRT\dXVT\\`P`TTdVTLZ``XhRZ^N`\VVbR`bHLXVTLXXL`VT`J\XRT^dXR\XVbPP^JJRZXZRV`\Z\`ZX\\TTTPV`XZ\P^^TbRPNVdVTX^RR^RX`XZPRTXPLJZR^XRZH^ZTLTbLRT\\fPTR`JfLXFRPVXRVfPbdnhXhl\^ZZT^VNXXb`^V\dVX\RbVZ`hN`\PXLlRDfbTP`ZXVZTjTR\^ZXV^ZR^`TTXLTV\VVVLXHVV\JRRhRX\^`^\ZNR^RbRZHhRH`dR\ZX^ZVNLZZ\ZX\\ZPZJ^LR^TZRRVTPVRddPNPZVP\TZX`LTP^bRThVhVTFV\\ZD\^X`R^ZTPLbL^TfLXX^JHhNRPDTNH`TPP\\XN^ZhTTJZJHTJRTXVVh\XbJ`^RJb\`X\FVbVT^^\NXVZ^hRZL\RZBV`LVPPN^^XJX^TZbXZ\HP`f\XZNNN`TTXJV^^V\VZjV^ZX\\lLVT^P`hb`ZXRV\VNTVTH\`XTRXRZRTPRV\V\VbBTR\ZNdXZLTVdZ`XbT\RJH^ZHXZVbTZVVJZXPVbHXJZZ\T`RPDZJ^PbHRPF`RXXNVZdVZTLNfXTLPVVN^NTX\\LVT\D`ZTRPhVhfH^RNPVRX^TPTNTdLZJRb`TV:XPXbXVVZZPP`V`^XVH\`XPZ\FVXJ`ZLVbDfRVRRNfH`Zp^TLXN\dFfFTT\hZTXXV\XXZJZ\RXH\\PRRL\^TVVPXXXDZLTbhLVPXNZP^N\XVfXRXf\TXbTV\PVZXXXbZNXXVXdX`JR^ZNZ\XbLZXZNPV^bVV^R^`N\j^dVPT\X`\ZRNX`\VfRd^VZ\P\ZBXLVLZVP\dZbXVbVr^dTTTH^fPZ\T`^bbT^Z\^bRXX`VNd>^d`ddTTZXX\L`LPZ\b^TV\\^TVX`TRJN`XPXL`R^BTXf`NV`PLXRfFT`^dZLZ^Tb\NLZTVR\NXRbZXXRTXPP\ZZTZTR^ZdXRXPb\T`bTbf`HVPd^LZdXVNTNTJhZL\\N^bR`TJ^d\VXb\VHR^ZNVdRR`XdXZ\TNP^fRbNfNPhNbP\VN\ZV\d\X^\ZRTX^RRdXdZLRP`HbPVRX\`LN\`ZR^dZ`PXNPHL\NBVDVTNJ^FdNNVJRT^ZPPVXPP`\TXJN`TL\TTPb^R^VTTVR`TVRP\BLT\bR\`XPXX`PXdZR`TVRRRV\\LJHVdBZXXL`V\JPbVNdNZT`LbPhbZTLJZXT\VPJLfTLZVbPTj\^PTXBXPLXTTT\ZPJZNLZPZ`FRR^Nd^n\`TZf`^N`TXNX^dTTJbbNJR`ZVN`T\NTR\RHHZTNXT```VRX`TZdNLVFRXNZXLBVJHFRTZ^JVb\VVRL^HbTFPJVNHVRf^RXJ\DPPVLd^\TZZTLRVZ\T\JRD``FVHP\^VRNZJZRddPHdRRRbHZ`XPNPLRXFZ^N@RZXZT^NfPJZbTVJZNXZ\dVP`BR\P^VZDTTP^VblXVRVNZ`XHNVJhPZVZThH^Z^XVJZTP@PbRXX^hNlRVVbN\TVP\H\X^VVR\^RZXXV\TXZBJVJBdZVLZV`NPfB^^\H^XZ\TZN^NV`DPfXTb`LPVXTXVBdXXRX\XVZJVZL>VP^T^ZPTT^FPRNJT^XJ^\HVNb`^ZNV`Xj^JhZXZZVNZV\PZTZJTdV`TVNZRN`LNVPL^JdTRZZRbbdH`FVJ\J`DXV^Jb^RhbRL^@Z^b^Z\H\T`Td^F`XdLZT\VZbRPVTT\^^JZVV\BZN\PXZ`JnRbPHTXH`P`ZXdHLV`R``jL\VP^LT`^X\TJfR^ZVNNbLXLJbVZVT\XdhPL\d\XV\V\ZZXNRZZ^PL`VRXJZXNVNXTHdP^XF``dZTbb`j\NfRlb``bZ^V\\^Vb\rXl^T`VN`XBbXbf\LXbRfjJdX\VRN^NdHdZN\VJXPPX\THJT\d`JL\\ZZVVbPL^XRZRLZTbVZVd^JL`\fTRTT`JFT^PRXdPZTTJ^NbLN\JXBTTHbHhXPXFJbRR^NXPLZ`\NR\bXL^bXbVRV^\bNPPTNN\RXLXZPhRZJXDfTNfTTZX^\ZbTdXVh\XdRN\ZZZ\D`Rh^hR\VV\XThP\PLRPTRJTTNTVRZ^Xb\\X`^VTH^PVZP`PZRNNV^PVXZbRN`RR`ZZZhZ\VNXPX\NfXNXVX`^^PTZ`DRPXP\RT\\V\XdXPX\RPVR`TR\PXVXXZ^V\X^TV\XNPX\XPbfNZXNXbF\bXbVJjNN\TZ`V^TXRPPXPXd^`VNNVL\ZHVXVT\T\VbTR\Z`^R^^LN^bNZZTLhR\d`\ZVZbXVT\LZbLT>R^XNHhTVVLd^ZD\Vd`JP\^XVVTVR`^`T^XPN`V\hVZXh\VVZP`FXZbPPXL^d\\dVV@TPdVhVZXVN\TVNTTfTJ`NZT^NV^VfRPPbN^NR^PbfBHVVPZbL\PTJTVXZNZZbR`fV^RTPh`VTVVZLTVbT`P`XRNnR\\\b^dN\`NbX^VPVTRNTZVjXJXXR`VLdVRNVZ^RNZX^LVXRXVRTh\`T\`^\\VXT^TJV\\ddTT\JP\X\`^NXLXXRZR^P`NVN`RX^\RTJTV\\XRdTPPPZL\PVZLV\dRV\PZdTVR^R^XNbZR\f^VZTNVbPLXZD`XRT`RZP`R`\HdXJ^ZXbZNPTVR^TX\VXXZhXJ\P\`ZTL`XVTZNTT`ZDX`TZV`XZVPVRdN\N\XVTVTRhfL`Z\hR\ZRVZV\VRhTPZZh\H\\V\XXR\`L^dVXN`HLPRPHbH\RjNPTPZBH`HXbTTXTVX\VbXPVRbJVTZTNZVTPZ^VVRnP\TL^F^ZLRRTP\VdVRJH\PVV\RRX\TZJZb\VTZRR^^ZH`ZZT\X\`X\LJ\``N^X\\FV^^PV^Z\>ZRJZJpLJ\ZRhZPRPTLTVbTX`ZTpXNbFlP^hXRbL`V^XXdJR\ZRbTPRPTTVRTX^XPNTVJN`X`PNT\H^\F^XFVJJRNV^JXHbb^HFT`Z^ZPVT^ZFNX^PNdRZJNXNXHXHHbTXNLZZ@PXdRN\LX>^T`RPT\JTJX\RJRVP\NTVNDT6JZPjbLVZLVXV`XV^Z\XXJXNT`R^XNf`V^bNV`h@P^PNl^H@fPVFPNLRTHP\\PJ^TZT\P`JP^TdZRXVZVHVVTVdRJXX^VFXddd\XVF^RXLX`NZT@RZZLRP\PJ\XPZ>RTPTTTT\dXRbXTZVZVZ^TRNXXTVRX\VHf`^TNZRFdV^FR\\TNRN`PrT@>TZPL^PXVL`ZNdb`^FXNTLPXVHVXVPXZd`TBZXXNXZ\RNHX^ZFVJfdJZ\^T^NXhZhL\ZVL`LTHfZTJL^BVRXLJRRTZTTXZPfZVRVVRRTL\ZfNP\``XPTTXJR^TJH`XTNlbDVPZdZPTZZRXZ\ZT`ZRXlT\VR\\X^^R^`^VjPRdNLZVXPXJ`ZLbVZ`RdTbPPb^^VrF\LfV`XVjFlXdTRXTVT\dT^``dNVZT\Pff`b\^^VH\VbZ^X^\ZZTX^fRT^P\`TRXVRPZVZ\^`NRJ^f\JdZ`\Pd^\d\RZNjTVLV\ZXR`bT\jZPbVT^ZZRVX^V`dVV>^^RR\X`bTRdb^L>VZ\XVZTZJ`X^`ffd\hbb`jRlPdZVP^h^dX^\hZPbbZ\blTb\Zhbb`RXVVdZP\^b`\VjJVdfZZXNhPVRRPL^PTdRZZfl\RZXTZ^bJR^ZRR\Z\bVTTJVbXTbTHVX^VdbbdHLVTdRRb^^PRJXZbHD^JPR\fZTVTPRV\VVXTfd\L\dZ\V<\XZR\Z\`PRb^PVLLPRN^LPNRRXbXXZRXbP\\ZX^VZVXNTN\X\J^ZJXL`PZJHbZXRTVJ\BJ\LbPLRbR\^@f\X^\PX`@b\P`jTT\l\^ZF\jb^N`X`VX^PT\Nd@P`TN`^bbZbRTRfT^L\ZPXTdNj`DZZNVXP`HRZbVRRLRR^PN\^\RZJRf\`ZXNZVNhR`N\V^Z`HRXXFd^XRRX`HLPP\JTb`T`RTV\XF^ZhXRTX^NPPbRZhRHRZFPVP^RhBbPT^\ZHRZ\PbF\TR\^RVTVZXLRT\XXZPPTPZ^RVZJZJ\TTZ\X\ZV^hL\LZTX`^Z\VVXVZZ\P^VRJZ^NLXTPTXZPVFLTXNbTTXXZbNbLfbZbLpL^\fTXJRTXX^RbJdRVLHHZZTXVVPVTZVLTVRN<fX`PLVXZRbVDHTTX^JVVXHHXPRX^RXPXVXXVbdRPPR^L^^V`ZR^NRJPZXRTVPLTJ`DPNRP\JVXZJL^`dFVZZ^NJ`DZRZ^RRTN`TB\RT^RbPZVVTVT\`TXTJRVVTX\V`PXd^Z^J`NXHLdfP^D``XXZZD\P\Z\\TV`ZVFXVV^ZVVTZVRJT`F\TRVXXPZlL\RR`ZTTRh`VXP`Z\R^RdjVZTVZ\XXbNhXl\bV^PZXh\ZFfP`R\X^dHPdXVb\bP\XZVR`X^ZL`VVXZbbV^VRB`ZXB\ZR\RNZZRV^LRTZBZTV>T^lRTXZjTRLdZZT\TVlNZXTZXZX\Zb^ZTZ`Jt^\^P`T\RJDZL^RhV``^L\P\ZTRR\X\XbRZXZPTjN\bNVf\^^\^XJZblVXVTfVZJJVdRXZ`LTPPXN^\ZfJVhTXZXT^b^`V^^\PR\d\VPT``NbFZTLPXLZT^NVPV\dRPPTbZXTVVVTTTR\\\RLR\`^`^NZRPbTLdNdhP\TBbRHZVL`HVTHdfRTHhVTN^RL\TRPXN\`NbPJTF\NXN`VV>ZR\jN\XLTPVLZVJT`\:^JZ\^VXRT\TN:dP\NR\^ZdPR^FPRN^bb`PTZXdPJVRHb^PdZVTdL\\XXF\hZbVVZZTT`@LNVF\JVXHXFLVNTVVRZVVJbHR^`RH\RfPLjXTZ\ZT@VVX\\NRJXRTRRLRNPb`PZL^HLZb^XZXZX^DhTZLDbZ\JRTfJ@JrRZ`XVnXNf\PNN^\^dRZXRPHTTHNRXZRb`PZR^F\HXTRT`bXNXPPLbdZbP`LZF^TNJRRZTRVVLbVTVVDjVV\:JXN^\bZZTNLXT`NbZ`ZFN^D\TTNJRbhXV^JLN^VXX`RVDD^@\NPTZZZRJPPVL^ZV`RV^`^^`TVb^PN^TTPL\BbnHZRZ^V^ZPVZPdRZ`X^XZXLTJVPVR`^\VbRhH\\RlNdNdZTPX^^T^^hVN\VXZL`RPT^XbZbV\Rd`bTTX^hRRXPT\RNX`d`NN\XZT^PRPdVJRXZjXdPZRVTZ^\XTPX^^Xb^TZ^LZVTXT\`\RJ`PZ^F\\^dbVZR2ZL\NTJTL\@\RLZTNZhLPPRR^\PT^BR^TRhNdZ\PX^\XXd\XXNRJb^LL\`ZXJJRfXD^`b\LZTNXPN\V^bTT\h`HRThZb\`VdhfZb\ZX^`\VZXNZ\f^V`jXPR``dF^^`\VbbVXX^XPdXf\Vf\LdZfLNVVZf\^TVV\^^lbRZ\TTNZ^TbNXb`VR^XPXRV\LZbVXLRP\ZLBXR\VPZbBPXR``TdbZnJ\L^ZRPVTZPbX\TRTZLZ^\TD\\PNPRTD^ZTZXdN\T\Tb^JDHJ\L`V\`VLdjVhdTVTbZV`ZZ\TdTLLfZVFRTVXXZ^HXL\ZbPPbT^T^lNVR`\\Z`Tb\H`TT^ZJb\n\LdZVZ\DD`Jd^\RBN^bN`BbB^ZRTZXL`PVXNZV^PRNRZ`bNN^L^`^PTZXHR^ZNPb`LXRPR\NNh8PRVRZdRRb>dLXRJZZR\ZLTJXdHXZ^VbZZJbPRJX\\Ld\RXVX`VfZh^LJR^\TX\^LTRXL^FRPPLdZZNZTRJTLR^b`TDP\P`\HT\BNVL`LTJVPNhLHT\VZV^bRHBT^@\BVJXZVVRTVLHlZXHl`NfPXBRRXP`^RdTZ^PJXPHdVN`@NFdTPT8FZVP^PT\VR\XZVJ\RdXNRVZ^`dXLRRLVVbRL\bP\^dP\XLZVTbT^TLT^PPJVNPTZb^JNVXR\^\PVPNdVbXdNTT^fL\ZT\TH^VLF\TTR^dRPHbXbN`bP^bXTZPR`Jh^ZZZJbR^`ZZLZbbDXXTDfb\Rh\T\TdT`PTHPV`PZTP\RZdV\VN\RdZdZTRjd`XXbZ^l^PRJbXRb\jbR^NVR\Xb^PPfHVDb`\\lJdXTbVLXTVTZ\R^dX\bX\PX\\ZTX^\bZ^P\TTfXV`Vb\`NN\ZVP\Nd^VXh\X^ffPbZLZ``^nL^hbXV\T^ZRZ`TfZbFX^TXZJVLXVTVVTLXV^XLRVNbRXPJNVZ`RfjR\b^`b\V`TRbVXTp\^RbTTh`^X^bVZTV^VbZ^TVXV\^N\RH\Z\^JFh^LZLJTNL\@\JRNXXL``PPTf^L\J\ZR\FRR\`NJ\XZRL\DVL`JRVPPLpNZPZVPN\PRNXTL\RLXFRXTTV^TN\PXRRZ\L\PfNHRXPTTPNVN\XVNZ@lRJRd\LTJ^T^VVNTNXJNXb\b^PDLNX^FVNF^V^TZPJRTJZVTVRHNVb\XTfXPPNZbT\TRTZPVXVZ`BNPZT^`TNXXPVXHJLVNXN`\TLX^TT`VZXVZV`RV\B\XX^NRJ\T\PZXd\PVX\TbZXRTPZPXT\XTb<Z\JZX`^^TdXVVTZFHNZ\XTHZX`X`Jdb\b>RFH^TLVTTZHXLPP`ZN@RFFN^PVXPXLbJ ZbDZ^X\VJbXX`ZPLd^\\\P\^VZVVFZXRfLPLTfRbdT`XPVfPVLJLVbF@L\XXVRJbX`XV\bXRJPN^hFT`TL\Z\VV^TVT^RV`BVZR^XRNPXL`hV`d\XZ\TZhRNXRVTX^^^^^XZR\JZ`dNTTX`Z`PFXTP\XfNTP^fBXZP`^\dFJR\T^VTRZ``VPTX\HJbRT^LZ`TZRPRTD\ZR\V`dNLTHVVdNV\LXNZJ\VRRFPZN\^\RVdVFHLZVXTVVPTPR^R\V`RLjH\hF\TNTVTdPLTVbNLRdRZ\V^HVbZVLdXZTZVVTXNX^RhVTNVLRDZX\T^f^NT\T`R^XRRphPd`JfbHZ`\JXXZTXR^`NZXJb\hXNZ\X\b`DZ\ZVFJ\Xb@d\\PdNbL\XbP\TN`T`V\D\ZLRLZXZVdXD\T`JT\hVVZDL^PLN`ZVX^^NjZZf`^ZVVXRJZ`VZdZPbV\NHRNXZRPdPVRZVT\RNrdHZb`^V^dXbPV`Vr\FpT^^VhbVbbZP^TT^bTb\T^^X`V^XbZXRbX^bVTV^bZbZV`Rd^`\ZdT\ZT^``DTTdZ<`ZHbfTLNF\TXZZN\PH^LPHV\PH\JlNXR^XbZZV`P\ZdZbNV\\b\X`Z\d\VP`LXXJJRh\`\dLJZ^T\ZX\hVV\`VHZfZV^PXRXPXRTdRZ\NXVZFP^RLXXL^`\VRPR`XRZNTVXN^PR`h\RRXbPRRRHT^^T\HbRbVPVTZV\PXFNVTTT\PPL`RPXTHXLZJPN\R`Z\VJ`ZZ\`VR\VHD\JbXN\PPXLXRZ^N\ZTNNTD`\X@PLDTdPJ\bB^`LFPVJTJNTXPTP^`RVdPX:XLPJL^JV\VL\HTPV`L^dbVZTTRbXZRRZNXVNZZPRTTX\HNdB^fZ\d\H\NRPTP^ZXXXPZ\\NJ\Tb^ZHXLVLTVVT`PRZP^NRPJNV^J\RP\VVdT^ZFfV\X`VTLL^PZDVT`ZJbbHTVTHXLVXR\ZNVVJ\VNVF\bTT\^XRdbTR\TdHVZVFVVZ^TXVh\TXV^fLbZRTRR\VT\fTVLR`Z^VZZLH\\ZRdX\f^RFPZZfRTZTTJ`ZTb\\fVTVRd^8ddVPXXHXDLVV`VRNVbR`VX\\\Vb\PNXX>XJ^\VTLjb`ZNTRVZPVTJ^\X^R`dNZX\\ZTXVTVXl^X^^X@^^ZN`ZZR^RN\P\R^^b`T\Tb\PJ\\\jJZ\h\ZVRTPbTXRVfPbT.\ZjZNVLV\f\\L``R`VN\T`R^\`^H````^b^VZJZ^ZVZPbXV\LVTV^P^^LXN\\L`\PTbZ`bT^b^XZbZD`NTrZjTb\Vb\ZZ\^bhH`XTPT^^RTJZRTP^RXNL`^\N`VLVV^HL^TPZ\bZ`f^FTdfZTVfPLfXVV`RXRTXXbPbNTVT`^JTPdR>X\bJRbRhdVdXVT\&XZ\T\^PXVbXVXdTVfNN\f^ZZRn\L`\V\NRN^^P^JZN\^J`\LbZZZL^F\VLPXTVZ^bR@XN\ZRTNbDb`LJLXVR^NTZh^\FFhBPLXLRT`@V`VTNTLLXXZTPd\TZVfPd^LPXXXPPRjLVTb\TT\TTRfTjXXb^FfR\Xd\dNZX^\XX\VbHLTJbD^TPXR^VTZhPXLb^JNN^VVL\TZVR^dFV\\^\RTZTXRJR\d^PbRPZRfXTPTTLVJTNPf\ZLPJXRZHZbLLJZJ^H`LPTXTNNZH^^bVLP^PTdPPZfTTT\ZNP\l`JPNVNP^Zj\\`b^^TbZRTfZXVf`bJ6NNZNXRZT\ZR\N`PXJX^ZTLPZNRNhPXHZZPb\b^bVNTZ\JTPF`\XPZVJVVbX^\d\VV\TBjJV^R\VjZRb\P\\ZbPFLHj\V\\TRZV^VLNT^JNXLTZTRDXJRXJFZXVNLVTT^T^NdD`^fPXN^PXPZVZV^HZTVdPNdXTV\VVRB\HZ`L`TTNT\ZbP^V^VRfTRZ^PZfTZTV\\XP^TRZPbPbPL^N`X^\R`bH\VXXZRXTT^X`VRXRTbRRXf^DZHVfVVX`XPZX`X``TRdNXXbP`\LPTPZ^\RNXRfLdTH`^LZ\Z\^HfVXJbPXdNXjRNV^ZTbPVPlTNTNVVVVdTdRXRVfLVZXZ^RVT\NJVRVX\XpV^`V^NVL^XTXRNhbZX\`fVVX^\VRJhnZVRTNLX\bXNTRdZV^VXRbHbLVTbHJZJbTPPXTRT\`Zb\Nddld^tNdj`^ZZLV\JX^N^XTZ\X^Jj`\X^XPRZjPVXNP`V\R^VTVbXRnX^P<V\L\HT^TN\^dV^XJ`TRbVXT\NV`VXV\JZN^P\TRZPJPTbL\^Hd`^^bRRRXR`JV`L\X\VFP\HZT`T^VZXbTL\TVHdVT\P\\`N^RZ\RfZ\`ZZVfRN^XZbP\TZ^\\XZRbT\bZdXRTZNdNhLT\ZPX\dh\RZXJLJTLVXXZNhX`RTVTTTPZPNPXJ`R`XPV^LVVBVjVRTbTPdPRXdPPbdZXl\HPVfFbH`dZXPP\\dT<V`XNj\bP\VRF^dNfZh^^RLLV\LRRV^VXX`ZFXXVRZVNTXXXZV\XDJNPZHXXV\VR^VZ^ZXJTZJHXN\dZ\T^PZZVTXZ^RZ\\PRXHR`XN``TX^RXTPPT`LX`ZRZX`ZNZVbVRXNXVPb`TZVX`NbRP`ZbXR\ZTVLNFRV`RZ^\TPDfRjTV8fXZX\X^ZVX\VLRVZVXTbRRTH\XZJTfRRbRLXfTXPT^P\XX``R^X\fT\LXV^XNJ^\^dV^XHZhRXJVRTL`XZ^TRPbPT\dPRdXPXRXTfPT`F\dP\^XV\\Xf`b^ddbXX\^LX\^P^d^bHX\NP^\^Z\fPdHX`\TZ\RRVR^V`ZPZZRVhRV^HT\\^TXhLhXXdXbX`ZT\bTLZPZ\bbVJTX\P\h\dTR`RZbH\XVH^TZP\Z`ZhdZ^X^X`\VXdXTPNZV`LVRPTPVPd`Pf@bRBXP`b^RX\PBhR\XX`\VjXZ\NVZXRRTPdT\^Z\`ZjNXb\bVZPJ@VXP`Z\HVTBPTLNXTZ^`TZ`ZfX`XlFRT^^fRZ^\LXNPLPVB^n^P\V\RVZD\^bb\\Zb>^FZP\D^\j`PX^TZPJ^LRRfXRN`VbZLXTPXPTPRXTNVPVXNZBZVTNTV\hBPZNVR^RhRTL<^RfVdHZ`RVhX`F\\RbVPVd`Hd`VTXbfXTZZZh`R^Z^RPPNV^PV`fVX\XDV^VZX\ZR:P`^PPXVFJ`RXN\D^V\\Fb\`B^\HVXXX\RVPXXRTRbLdXPbTTTLZNXLVRV\fZPBNZVXRfXXZ\ZZFDXFb\TZHTPJRT\PPXVRT\ZDTZX``ZNbL`hXRRJPJ\ZZTXL`J`ZRV\ZXR\VHd<`PRT^LdLT`THHVNZfPTZXRNfX`\VD\ZT`ZTNJRP^`RVNJZZVVRXRXZT`Td^JXX^NRPPR^Jb\ZRNP^DNPNRPNLPR\LXFR\RPBNTVPZVVZVPPNbN^XPZ@L`:FVR HRdXf^`VR`VXRN`d\Jf`fZTXdZ`TPZTZLf`N\RN^R@VV`<d^P^^VVTXTP\F\`\LJ^RF`\\ZNFVHPFRbZ\NRZVHj^ZTXTbZZ`RNTPNZ`TXVL`X`ZVRXfXZZRPPNZR^P\Jpb^PJNTDNP\JNVdL^XNTLN\XLHdNZ`VNVV^R^XPXV`\bRd`VXRXPfHhLXZTJ`NVR`TRZRVZ`fJX^Xb^T`ZRbVTPTXVLdN`ZFZ^RdV`VNd`VZ^ZZZZX^dRdXZ^\N@f^Jd^LdZbVFn\ThLhhVXHTVfZ`@`\XdJT^ZRLZVZVdVT^TNXRZR^J`X\TVXjbXXLXZTN\\\Z`bXV`\XPTXTT`fTZZTZVdVbVD\`^^VZ^\VV^LZdPNPbbZ\VZVPPXVXXV\X\dLPhd^ZhXdVdX^VbXHZdV^bb`\Z^bXPZ^TXhbRXRTVZd^fdZ`NFZXh\^XVdR\^fj\RRVXjZX`VFXbV\nF`RVVZXRXLV`XVddTVVVRdR`ZTVdT>hJV^VN^P\ZL^ZZZBR\VPRTT^dX^JT`JLTNRV`V`JdH\^N\XXXRFXHZ\bZ\NXZlXVNXdXNPHTbP^DV\ZVB^NZT^jbVXVfTXXHNXH`H`ZX^XbV\\PP\LR^NVZbXL`D^LTP`NJZRLPb>bN^LT\XX^`P\TRP\ZLhPTJXZX^fPV\Z\JdF^PP^HXNXXRd\TfZ`bNF\J``b\JZTXdJTRNXVZHR\TXXVTVdHJ`RXZfL\JR\\VJ^bRRhDV`PV`\RZNfR\VNFXZT\PHVBTdPVTN^ZdB\HHR\N^XRZJP`NNXXTN^\VZ`VPNRNXTbTNZTNJdR^\\NjXbRZPZbPZNNRNTVRHZZ\TLHJVRRVVVfZ^XX^T\Z\`^\P\VV\J\T`ZPTVZZP\Z\TVdBZRVP\^\\DFRZfX\TTP>RL`D^TVLTZ\JL^XX`TJ`fXTZ`VX`b@\Z\TXV``R`HZNVfJ\N\^TJZXX`bRNN\Z`VNFZbbVZVTVRPV\\H\RTV\\Tf`XTbZTLbZPH^VTVTPJZ`RHTbVbHH`Z`TVT4ZRXXJ`J^VJNTXXRP^RZ\TNLVZ^bNZ\fNVP`Z\JNRXZRNP^R^TN^RhTVZZTZR^V`\ZXX^^TVVfd\\NPFTVTX^\ZH^ZL\^XLXjJ^JR^Z`XdX``X^VT``ZRP^ZZTF\HTPfFLZT^:X^ZPfNTZbTd\VVRVV\^\`J^\V^NRLTVXX^T^jN\PbVR\Z`TLZLZL`Xb^\`f\XbjfVZV^T^VLVZXR`ZdVbPXZfbXNbpbRXXbPVT`XRVfZTV^ZVZjVbbPVR`XZPZ^`bTVdXP\P^`NXN\ZXPPfVTd^HX`ZZZXVRZ\TPPTTN\TT^^JFbhJfNVTbXLRZXZFHVhR\Pr^N\\dHhXZXfTTXR\NNdZLdR^N^LLPdBZTZ`NXNFJT^\PZVlbFHTL`^ZVHPJ`DXHhP<dPbT`LF\FbVRZTHVJ`FLX`LfPXhD`H\HDVL`RNX\NVZ\dFbTTXZVJ`R^fRd\PTNHVZ`VZNJjLDZZbTfXP^ZZNHXbVdXTXTPN\ZVb\PXPPV^PVTVJLZPTX`PZVNBbZT`NLXLRNRRNLVTPZP`TX^L\JN\NdNRXZbPZL`PX`RZX\V\T\RTVfVR`H`VX\LVZRPX^T^V`TFJXR\NZTNFX`ZLVP\Z\VTTTT^TPR^PJTVRNJLL^TTRZJRL\XdZ`lP^P^\`\T\JR^ZDXR^XTL\RX\\VX`bXTDb`^PTVTRPX\RbdXV`R<\\T\XNbVLDR<\PNXPPXRbTNXT\PXVT`HN\^^dXLdXVLZJhfLZFTVVVF^^VZRZJXFX\VZR`JLTJTXLZf^^\XRVPZRj\PR\NX`bH^DbJT^VRVXXVZ\:hNRdXTPV^ZLXLPZRN\RZ\`Z`X^\XNXX^VVJ`VbN^fVbZb\X^``ZNdTZVR`VZj\PVVZL\\XRTF^Fb`N^PT^NTTX^ZRfT`Z^TVPVfbZd\hTZJVh`@Z^N\JVf\dNTXbX\bf^bTdXbbRXVfV^NZ`Z\PXffL\TVNXV`^R`\\TPTTRfVV`\b\f^^B`TZTd\RlZXRJVTR\dNb^ZXTXVT`LT`\NTVdLRPXZVJL\\X`hXRHTNXjX\Tnl\`jbRT^db`d^XZbZZNPZ^PTFZPRZPVP^^VPXPh\b`\PTZJ^VT^Z\Z``VZb^Z`PXNNdNbXXHNVV^bTXZZXV\bX^ZZXXb\\RZ`Z4ZbVf`PZVPXVRZTHZJJJT\`VZVRN\bL^RTTRP`PTXT^PXDXXZP\ZN`V\RV^VV^LbffTNd@V^\XR\XXV\LX`XZ`TpbRNRXT^VJT^R\R`ZVXPX`TTJPXRf^TNZDN`ZN\HdN\H\jXXBP^ZT^VHXVXfXXRTXJTTXZZVRL\ZNDN`XNhdVR`XTP\Z`\VdThFRbRTfTT\\^VBZLRh\RT\^T\NVVZRPPJZZZX\TRXPPVL\PLbTRRV^PZ^LZXVTRNNZRVTLR^R\TbTTFVXRHD\LV@ZdTfJTVHVNNPPV`LbTTLLd`N\ZX\RRN\VTN\RRTBb\PjJZ\ZX^^RhPNRJ\bPZNfPX^`HVJf\Z^TpJZPV\XNTNXVRTXPTX\f`^PTfTN^VVVbHDVXTRdXVPXZRLVTZX`XTTV`X>VRRLXLNRTfZZR`DXNXZVTTZXZ\VTRHJNX^HLFhXVPV^^^RPZNRV`XZXV^bRlTNNVTNdVVVVbDRL\NX`HVT`ZPHLN^X\RZLP^TTLdbTPZT\^dThTJhJbNJ`^LRbZRNRJ`ZX`\L\PVb^fRLPXVhXXZRX`X\RTXP^X`TdHRZRX\JTP^fVRbVfN`DV\fT\RZ\XZLVV^PXjZVVbbZ^ZZbLdZRJP^Z`RDjX^^F`\dhD\n\\RJZTTPTTVd^LdZTbPV\T^@X`XLdVJTZVf^Pb`JPVZ`\dZVV\TV^VPZp`FbZR``ZT^PTd\6TRdXfRV\hbdB^NXbVRNpZ^NTPbfXXfTZPPhZX\\LTTbbV^HTPXVfXXfXRdNHdJ`XNTXdbFJZR^VLXV\\XhJZTX`LjX`LX\XT^ZP\TTJPTRD`pNLHRP^ZT^^JPTP^hRXZVPd^N\@VVfVNbbNNNVdPTXVDj\R\XLVXPJb^NN^bVdXLV\R\`@R\RP\Z\dPX`b\R`JVf^LXR^RZZ^LX^RJJPXr\\\PbTbTVF`LbfT\RNN\XVNTX\T6XVbZVR\J^JLVNRPL`T\PHPPHXPZB``TPNPPRTX\VPbT^V^`ZTZVVRFd\PLTPJ\ZL\\NPhRb`RXLTRV^NTd`dTV`PZZRZXHRXNP\XXTRR^Z^X^@\V\HbX`\RTLTTXbZXd^^\^@XLLDXFR^PRP`LJRXDTXT\^`fN\T\fJ`TRN\V^\dfR\VV\XXNbZXXV\dR^jNPPXd^JbPJNFXN\NZZVDTZLTjThTT`\XTTP^RNNT^XVBNP^Z^FZ\X\BRTZT`LbXVdPRV\ZTP\RTVT^``VJbV`^RXLJ^V^NT`NXXTBb`VRZZBhHXRVbV`F`Z\ZZVV\Z`NTRZRR\P\XV^PhD\XPNXb^`\6\P\VXbf\Rh^bT\bVLH\RN\^ZF\TRVbVHdVLZVZTT\XNdPTN\^`bb^Hh\HdNH^^NVbLbXLNNZbPTZh`XLXZTP\RbZTRPZPTNN\\NLJ^\ZRXTR\\PZXZZRN`TZTZZ^d`VdR^RL\LXXL\`^F`T`HdNVNXTPPbZL^FVZ^LhZdX^HFfTbXThTZdVRNjNhTXZPTZZXFh\PbTXZR\VTTZZTRVTjXRVX^RRXTLdZXTNfPVd<PV^RdXZT`VTLTHb`\VZ^PPb\NZZXT^ZLjVXNVR^RPXXXXTP\bVVRVXNLPNNVVPRNLRVT\^PLRVR\Z\ZhZ\\b\^\Z\VPNVXVX``bb\XV`VfTRV\`ZP`^`^P``n^`TXRXLRRHjVV\bH\PZXXHZB\djZR\VZZVZb\TNHVNRVPNTXpZTZLVTJZ^PVTPHbZRRF\XL`jN\FRXX\\TTXXN^XFP\P\XJbVdXPH^THZJRNVPTV\T^D^FRT`d`h\Ln\`VdVVLVVZVDXRTLJLNPbRN@XTXhPbTd^`FPX\TZ^jNXLRZRNP`X\N`PXPfTRTTVXPfdXLPB`\LTNXLVZRRZNZJR\N@VT`XBdRPZVZVX`d`NRVTb^RJN`XHbNZ^N\RT`XXX`\ZPV`JTX`\NRRhb`\RZPb\TL\PVBPPNb^PHT^TJDZLZDRf\dLXZXTfXJ^TTFZXVZZVJRfZZ\BRTPPF^DZX@TRXTTXP`^TL^VfRPT\`T\ZZ`^TVTRPRFRXVTX^JPTXPV^PZLTHHTZ^TTLZFH>ZLVT`TbVRZLNVRDZVb^DPRZ\R^\JPdHJZTT\`X\XTRNRNTTNXPfXVVTX^T`PTTbVXbJVRHPZ@PZN\TZJ\bT`RXTRRTdTTdX\XZNFPXTXVZR`PX\LJ^HPFZTTZVTV^FPV`TTZR\V^ZXd^TF\XPNRNXZV`\P^R\ZNR^\XVTPbbRRZPVPVNVTXRZR`^b\VV^J\fVL\ZPbdX``\\JTZTPn`LZ^V\VR`hdRXVJdVRTZN\dP\ZLTLVfZ\bTdb\bT\Z`ZN\\XZ\P``Rb\VZ`\\VNVR\T\`b^\X\Rd\LnXZ^H^PZdhZPh\VD`VfX`RPXRTX`VZHVVPRXTP\JTPRT\`XT`b\^f`RZVVZ^RTXjbbdfVj\dVrFLXJT\^^XV\fZb\XZTdJNjRVRXXZRXZNTTbTJLTLRNLXJPDF^PV\jXf\\\V\dZbdb`hT`lRRTNTVRV\XbZ\lXTfNR^dTR\ZfP\XbRXBXR^\N`RRPPZNf`^^VZZ`ZZZdVJLVP`\TFT\XJ\Z\bdLXNZRN\^VL\P\RXZ`XZLZ\LP\TRJZR^RXZTJNVRTRLDRRNTZ\PRZLR^NVVX^`N\PPVTZVNXNVbB\PXPPXZFfZVFZVXPV`ZfVR`^^HT^\LbNJTXXJZTTbXN`NVRV^N^VZXNNPF^XLRbHT^PTJ\bV`^\VTJdXPTPNJXRPZVTTHXF\DTP`H`\\T\NVVZLPLXRVJ^\ZLZPPRVXZ\RXbRVNZRT`R^V^H^JPP\XNXZVRJD\XP`R\VJddTZdTHd`XZZPhRPhZTJPR^ZPP^R\bRPP\TPLFdXdTT\RVNhZLXP\ZR^HZX^VZRX.X^VP^`ZNRL^VZ\\LRXHVdRXPVPPTL>ZT`PPZLTNZZTPJLVVTXRZ`bL`XXRfBTX^bT^h`LXXVZP\NLVN\dZDPT<ZX\^TJBDT\`FXVXP`>P\Z^XVXTRZVTXZNZb`VTfXPLHlVNbFZNXTVXbNRVdFVXRTXXZLZNTPVZRNZXPLbV`LXbNVTTT\R^V\PLZPVZRRH`hHXXNTPNFZRZJRZ^\RbXXXR^ZNHR\BTbLBP^RLDXL^RX\dDTTPjXZV^RV^RH\TXNTP\R`T\Th^VZPX`D`PZ`Z\P\\Z^T^TXV^\XfRVRBX^Hb^\ZZdT^RZ\DN^^TdPVL6LTbZNVTNL\PbXTX^dTb^P^LJ^XVLZ^ZbPRX^D\V\PVTF\ZV\XXJZPZJXV^J\RRZdXbTf\XXbT`P^RZXNdR^TVZRF^J^ZXR\PTXN\XNVHZ`NfP^f`\ZNZh^dZr`^FZZXZjZV^RbXXhh`0^RT^JJ\\\ZjR\Xhjn`N`d\jT`Th\h``bf^RX`TV`ZZ`T`TJRPVPX`VXVHd`TVbB`LPVJPb^RXd\\XjV``PV\TXZPTZlVRVVdPZ\ZXVNXNdbT^VR^\PVN`VVXH^VVNXJ\NZdHP\\XdVV`^\bTT`FN\`R^VXTLZZDXNb\Xbj^X\RX\R`L\HTdPJ\PVXTNbPRVVPXXbR`PXPTPVH^ZbXTdVRXbdNJRXLLj^Z^TTdR:FLVb\LVZhLNXh^TV>X^bRXPRV^PPZTbPd^RPTVNV``fPZ^RbZL^`TdPbTfbTFRf`VZbPBfXL\\h.ZRVRVDfNXLFbRR\\ZLTTjDT^HPDdT\PV^LNN\hLLTZD^RLTNRJX^RN\RP6PVP\rJTRLNLX\NRJTNVRLXZTBZVbR`dRVV`TV\NZLZb^PN^V^T^X^V\HTVdVVVRZX\jZ^HNZ^Vd`bRTT`RPRVJbZ^BZTZHNbLT\`VVTbXRPTTT\XNVR^RP\P`VPRRJZNNVJRZR\\VV\VXZPTPXTFZVPZX`fN`VX^TV\NR`X\VTNLX\R^ZP``T\`VVVTXTfTbHJX\JX\\ZTNZ^dRV^PVNLfPXNZdN\b`lThV^^TX^PVVZPfNT`^TRJN>RZVVZTZRVPX`^\`hL\b\@XPZ\dTffR\NLhXVVRXdNf`^Z\T\VfbRp\\\LPRR^\XXZV`bZ\^RZJbbd^`d\XPX\Rjbb^^hbP\\ZPPZVZL^^JRVVX\PR\RN^Z\X\ZVfNXTZ^^VLbXZ`T\T^lXZX`X\^ZbbT`dTf`NVX`\hP\`V^Rd\XbX^TbdZJNN^^\Z^```hRXdTTTPZZ^TPfRVRdZJdLLVLPNN``dZTV`N^XNLRVdRVVFbZZ^`hRb`bR`Zb`TRXZt`VJT\\TVbPXVVXTHjTPFRRVZTV\NRbX^XXLTZ@dVX^hVXPVJLJ^VRNZNPPJVXRDXXd\LXNN\PZV^NHV\J\B`NVTRVZRNTXV^VF^^TJLRXVZNDLRRXJPbV^\bHTRTRNTPXb^DXLT^DZfX\XdTVFb:df\Z\dVTXPP\TNZTJRTZ^RZ`VNPJFNPVP^d`VZJTjhFVRXZbTF`NNZJZVVXXVJZ^L^PLRPP\TPdPbLXRVRPTZXRXV^RJXdXVfJ`Z^VP`PNZ\V`^XDRTVTVVTZFhTXZXffdb\bdTfbXXJF^NZPXRZVd^VRPN^\LTV`TJZRbT^R\HTRbVPZNNZP`NTN\ZTVV^RRXZLbZ^\T<NPHT^TTd^ZRRJTJTTZH``\hDlLDLNRVT^\JPbLTTR@X^ZNXVXXBLVN^TVLZNPTXDdPNP\`TLZL`F^hNRZX\RRPVTD\\NLNbZZXTPJVFZX\RZVPP\PRZTTZTR`P\bNZD\bXTFZPTV\bPJZT`NJV^^R^Z^LZRVJ^VbTJ\NdVbNXbZXZNZLfTRXZXXJLZ`XNXB^ZZ^NbdPdRRjLNPPb`^^NXHdJ`XZVZbRTZ>VHLNNZhNNFZPPdVZbTTPLbVLdNXHVZ`Rd\X^R`L^ZPVVN^HTbXdVRfj^dJZLVV`TTbZRTVPNL\`j\NZT\^F\RbX`NfTfNfR\PZPRbTTd\`VL`XX`PNPN@VZRjRTdP\PRdbN^JVXXXdP\RXXLRZd\XTVV^^RVbVRZZ\VhFh`bLNRZVP`T>VZX\VRjP\bVdZb\^PbPVXXdVhjjP^\R^\\RRX^JR`bpPZRXhR^PbZX\PhTd^PT\bXNPXNL`b\TfXPRZdh`\NZTR^PTVnHXnTTR^ZH`TPZXVdXLf^jfZ^X`NjVXRVZXXT^^P`FbLTP\`H\XVZTTPTZXhZXF``L`V`ZT^hVBT``fN^PRb\VTV\RF`FP@Z^^NTTXJLVbPTRF`XXNZTP\NhZDbZJZXXB\NTZ^RVXVPTLZR`TBVTNVZ>NXDXPXVVHZXPVXTbdXX@LZRl`ZVR`RV^ZRV\fDP`XR`\TZJ\dZNbZVH^\\VdLbXXPR\PNX\\VXTVN^PfVP\bVdL^^RLdL\R`XTL`JJTRNRNXZ^RXRVPVTZRXVNPXh`VDTZ^XZ^JVTVXZPDT^ZNJXVfJh^V\DbV\ZVXZRXTTRdN\\XR\`VX\fRZ`ZdTXHTNVRPNVL^>JX^ZRX\Z\TP@LZ^RTPT^FNbJZbDRVF`VZTNT^^PNJTXXX`\NTPX`\N^\\THbL^dTV\VZP`VPLX\Z^^R^XP\\RXXVT^ZTVXXjLXNZbd\\TdJ`NbZT\LRVZPN^fTRhLfPJ\jZRJ`XV\VRVZD^TVbb^bJXXdHVZTbVVlbbNRVVZVXT\^NLXL`V`LPVZXV\ZZV^^\ffNT^XVZ\^``HZNXR^`L`T^ZZdfZ\\TbV`^bdRbTdVZ\\NTPfd\T^TfV`N\Zjl^VVZRRVJ`RNJbdV\PZ^ljb`\PfZTR`VbXTP^JdZ^l`TTT\\XLfTb\\\nZbNLRZdPZZVbZR\L\XTL`\hTnZdNT`@VL^TTRLffZZTT`^d^NZZL`LNXVF^fPTX`T\NbV\ZJNXXLT\PN`ZRbZPRLTPTdLLVTRXPXdZ^``NbT`^`f^dRhN^ZBRdVXXNdT\RXnVZVR`b^\V<ZN\J`NNZ\T^dZN^TXRhV\PjbXZRTJ\RRLZNRbLPZH^P\JT`\bX`X\TX^`RNZXX`PZP\RX\T\XXJNLZPfV`V^bPXHZRV^X\V^pd^fZXXVVJZLT^`LR`RVDdF\bRNXX\J`V\\RRX>\XTTLhL\TPHJNTZZdZXdTX`^TPVVNX\TZ^^PXVjJLZl^TTJRTXXVVJ\ZRZNTPXVdNbL^VVhLLTX^dNX\@\R^PT`ZZRXNXXRZPZbdNX\^PHZX^ZdRXL\>TTTLZ`J`PXXRThV^V`^TXTRVP\PZ^bZHf^RL\XPNLZFRXX\\RP\`XVXTZZRBPXVPRX`X`^N`d\bL^PZdPdRLPjLLPHR\`RJRZVV`V:`D^<RR>TZZ\VF^^LVPR\Xf^fVTR@RZXTF\VVRPJRJRPZ^PXTV^TTPZRJP\NPZP:^F\VN\HbTTVdR\``\bL`HT\H\TRHbZVP\RV\V`^BT\RTh\LXZZTR`bBb`NRZTRFTTH\XJ\VDNZH@\`NTTRTTVLT`Zf\PXP^X\RP\RZfNjbTdRTJXb`Vb`TLPV^\\^`VPVZNZNXZX`TZZLN\ZL`ZRXTNX`Z\VJRNTVT^TX\ZlLZP\\LXXfL^XZLX^TRTXb^V`VXVVVZbXJR^^h\`V\\XR`hDlXVdVTZHRR\dRZVZhV`\Z`H`V\VZd`V\bV\RRXNXRZXPH^XRTP^R^Z\T^LdV^T\`bRVTfVLb`bFVPZPVV`b^RNZL`XRXPV`ZjjXLXN`hH^j\\`\^T\XhRbX`^ZX`^\ZRP\\FTP`R\RVPTD\^N^R^RNVRXXdT`\PffZXRfTXTj\VZ`LbZ`XLZVP^Nb`T^hRRb\^^`PPXNfPb`TVVfZ^^TPVbRRVf`XTZR\X^VRV\bXFdRl\VNTZ\\\&bdXJPZ\\JLTXTZZJZR^JbT\ZZJ\`PLPHFZ`\DDRT^VHVTZRVTPZV`ZVPjXl^PRXZ\TRXRVdZ`NXTHfNTXXhdXHNRZlRHNPRRVZJT^bVhXLZL<RRNT@ZT^ZJJZV^NZZ^JZPX\XZVRbRVVBZVZJZRVP^VdXVXNXXVZjP\Z^bVbbZZVdLZJVT\BNXZL\V^J^bHZNXNXhRd\PXhLXTRbLZJT^VJXVXB`@d^bXf^VRVPTFRJX`T^RRX\JdRRd\HZTb\PPRhTVbHVdNTX^^dTZT`XDZT^`dP\L\\\\XX^RRX^TN\R`RTXVdf`VXJXXVPX@fZ@VHP`LPZLNRR\R`^lZTb^VHLVXZNXbR^TXJdhXZ\VPddRXXJHXbZ\`ZZZPfRVZN^NRVdLRT\^VZPZVNZ\TZ`l@\NRTVNZPfBV\Zf^dXB``^\L`\TRZPVH^T`d^FXXTNVZP^ZT`VLXZD\H\FRPXRF\XRXZTNbXR\TPRVZ`ZJR^ NZT\XRPX\JRRVV\ZbLXXVbRV\NZNHRNZVdT\X`HhXVLNTZRZ``Lb^TTVN\T`XdTRRX``NTZV`bX^ZbNVT\ZVXZXJXZXfPNVZNTLb\X`ThP`RN`ZhVNZVX^VVRRZ\XRTnZZbT\\TbX\LVNNl^N`L\NXR\\LZHf^HTL\TXX^ZZbXN`TZXXPJJ`^h`VDX^TZ`VTbTTFXZRV^T`NV\jTTVh@XbLZTjTXJhPhNT\LZ^XLPLHT`^R\\PZ`XhJ^fT\`dXRV`TT`T`NXNZPX`^^RdTNNb^P\^bXV`V^d^\PZbXRlfN^ZbV^RPLRf`VhRVTX^^\RTJZNZ`TfPd`N^LV\LbVFPT`\RfTb\\XXZRdTRJVVVTNVV^RZZXRdd``DZNRRNDVVLf@VbTTRVbNZVBdJJRVd^VX\^NRXTFZfXV\J\TVXhZ\`XTTRPRVZX^`RdN\Th`HP<N^^VHRZ\LZV\XPXR^VXNXTFZN^ZPVN\PRTRTNJLX^TRRXXXTT\RNVXLNRNXT`PXNVPT>^\FTTNNJXV\RH\bNZVTbP\LTR^X^\^VXF\`TZJNRN\FD\ZNXZJ^X\\VLVZRR`NLPDTVVVP\RVZV`J^bPXTNRZNPX`ZHRX^RPNdN`PL^VLTVhJLB^VVXPPXf^JXZNZ>ZRP^^LZZPT\N`^TZb\`^VT\RZPXN^^fPT^FZVXTRbFXVVNbN^\RZXbNRV`PNZB`PJ^hPj^LX\VNVTXJJhXHZVVVRPZLPNPXX\FX`LX\RN\N`PZHbPPRV`f^dFJ^VTX`\V`fhTVVFJTV\ZPZR\N^BTJdRN`P`ZJ\XXTLL\XZT`J\RTTThDbFRV\\HXF^`\RZ\XNZZbH\^J`VLRXdZH\dP\Z``LT`TN\RfbXZXZ^JZThXRTJdLXhL\R`XLbJJ`JhVjNRbXZRXR^ZVjTHhdZPPZ\\T\^VP`ZNPRpRT`LPVZ^H\Z^ZVPXbVP`ZX\PbNVVH`PN^`\T`TTZL\Z\RLbRXNRb^PHP^R^VH`bXVVXb`VVXF`Vd^^^FV`VPRVZXl\TJT^Z`PD^R^^V`XZXZjTNRVRPZR^\VTT^TbPPdLdV^XfL^TD^^`HVZZbX>l^R`X`XVLZRT^dBN^^\X\pdXZXXfhfL\d^T\Z\XX\^V^Z\NXXVPTTVNZ^TPb^\dZHTfRbdT^ZXR^TJXb\fJTXTZP`\X^ZX^XVRX^hT^jJ^PZ`ZRLN^`ZPV`PRhVVVTXVTVZZT^dX`fVXPZXHXLRLJX\HPZfDLRV``FTV^XZTfXX`XfTRX`fXX`X`bTRP\LLPV\^PT^\ZNV\NZZ^NZXRNXV@^bRTHR^VbNFbTRd\X^XVV\\\Vb^R^\`^PdXFR^\^hXVXL^^ZZ\TZR`PTfVdVd6jhN\Nb`\RPdRVXRXddNVVZTX`RTPF`J^\TVTRd`J`\TZX\X\^^H^X`XN^PP^Vb\N^BPRX\V`XHRZb^ZPNFfdXTdVZZRVTP`T`NVTTTPRZPPXXXFDZL\TRN\`RFXXJRRXNJLTLXP\\PXRHRX`VjVVXTX^d`\^FJVZNVPZRNXhV`RZVb^ffRXPZ\ZdXVVHV\\VLNXfb^L^VVJT\X`NRVTTZTVRVPV\X\fLjd^Dd``BRbHbVVJXTZ`RPTP^V\^D\\J^PZL`R`PTJbhJdVPTXNPN\NXV^PThTZXZ\PZhZdXXX`TPVTV>XXTRRVZV^JRZV^L^^\VbfVXTZT\NRVVbX`P`\P\`bFfZP\^\PN\T^\\\TTTTbR`V^VZZTV\LZnRZRRTVZX\X\XdP^N^VTZPdT^V^\XZPd^\lRdR`bZDhL\X\ZT^NZXFZfVPbV`bZ\`\NbVVV`lfbLVTbZFhZ`hFZXTddTZRXhT\PZZb`\\XbVZJ^\TV\bJNVNRX`^^fN\V\ZZ\bRXfX^LZR^\RZXVVJbZ^Vb\XTbVZLRhTVb`F\^RLZLXN\LfT\dZ\RXX\p^TZd\V^dVdP\^\jZRT\^PfV\L\hZV`NVdZdV^TbHbTXR^JRhLVPTfVZRV`^L\XTXZDfPNZTPbXV^fZRVLbHT^NZRTHRLHRXZTXJ^X^FTXRJ^l\\P^JXb\NddV`XVVZVXTNN^``VPXVRVN`J^`R^`PTNJLLbHV\PbXXXHNPTNZTVPbRZXXRVZH\VPBVJfTTPTP\`JHTPXdf\Td\XNlHZdZZdXT\JVZdNVX>PFZVRFTPNHXbdZH\^PT:^FVVVF^TFTLdV`fd^XHb@XLH`dLVNTTD`ZVTLZZPR^R\XXNb\^ZBTRVVNJVZTX\VfZL\PRNZT\LZZFVXZXRDZLTZNX\NFVTVHZTPHZRZNNbXdPVZXR``TJ^NTTH^@PDXTRZV\HXLZnZT^XXXXdRJRNbVV`TddNZZ\`XTP^NXF^DP`LfDZPXX``^BPTPPf\ZR\^XL`^VXbH`VfT^DnPXB^\\LZ^``d`ThN^NRPVPFTVJZV^TPlRVRbPXbdj^PVXPZbVFZV^N\^VZLZZZR\FfJRTZV`VPZ^RX^^^Hb\d\RV^^^JTTLNJLHZ^D^H``X`RXHT`JVRb\J^RX`NPZPLTXLRJ\X`\^`T`TPVZZT`^NT^VXXbZZ\XdRPbfZ^`X\L`Zf\ZXPHV\VT^NPNTTVZV\^^LZbT\ZP`X``XNVbVZ\RTV^TT@`\BfBfT^d`ZdXPfPT@XRPXVfTThXPHbThRf^VdTV\VX`N^RfV`bb\ZT^`TR^XZ\d`TRTTN\XVBJPVZN\d`N^`^LJVTXPbZRPNTTL^R^VPZHZPVnXdJPXTZLbVBfZHV^XVJX@TPl@VR\TXJN^H\ZXZb\JXbVTVZdXZbNRPXTdX`d\dVbdbV\bTfRfdTVbf^`PL^N^b`\XZTVXd\XNXX^VJP`hPdbJ^j`Xd\T\R^VZdPZTJLPT\TP\VLHTTLT\LVLPVLXVb`X\hHT\\LVTRNZ^NVZXR\L`ZbVXZ`dXXbXdZVZTRV^XRX\RhTRRRRVXNLT`hXJ`Hf^PZ^B\JP^XVXPRXX`PX`^JTP\RZTZdJ^`\NZJNl@bL\TRJRbPBJTTfdVhTbT\T\HbZ^TPhXXXX\LJRTTX`P^RfRZHlZZ`PHbPd`f^F\`VNVdJ\`X^VdRX`^XVbNPVZdXbDJNXX^VX\Z\TZX`VXVRZ`^`V\LNBdPThR\^ZhR^fNZPdT`PXf`XP`ZP`fPFVVJTTVZ\TTLPbFJLRTNJPJVfPRTNb@R^TZRZZ`ZRLXVX`\RD\P`FJXNNRVNRZ`PJ\ZRX`FRdB^Z`Z`ZVXfJNXb\\XFfRXXTPPR`XfVbT\TRZbTNX`\JbVPZVNTZT^\R>BPJPTZZTTRP\\^PZ`^PdZ@`NX\`XRNX`DTT`H6LRFPHNLTNV^XTZNZRXPJV^bHRXH`bVb^PLNdT\\\XLR\NVLRZ^ZPR\\NRPL\FD\PTNRlXP\\L\b\VXZZJ\b\RVTZNZhXXT`TZ`\^VL\T`RNNfhZVXX\P\F\^TP`ZTR\L\JP\R^XVhT`V`j^VR^^b^L``Pd\RTX\X^P`Jb^bX^TVfbPbNnd`RV^XTlZNdT^^X`RZJ\`TVZDdV`TTdTbDXfNd\VRXhVRb\XFZhTRldd^bN\XRbLZ^ZR\dRX`fTPdTlP\VX^fTbZ\Nb\VRPdbZVb^RT\XXVVXTPNdRVRV`D^JNXhdlJRb\h\hVf\ZZbJV\XT`VbPVVJdHZJL^d^```dVZXT`ZVX`XJ\^NZ`Rb`^PHT`VXXPdZ`fZLVTZ`R^X^^J\hZfXNRZTLR`P\DVdHbTZVX`HTRdN\\VZTNL\LPTRTH\`ZXBFRLVRFNNZPZV\VZNXTRbRVX`Z\XbLJVPXTTb^bXRTT\H\ZL\JBXTP\bTbTjTTXVRZRXLNL^Z^F^X^T^RTZVXV<ZV\PTVV\PNJNLZP`NJ\LVZNJbRT\JNj@BFVTVZNL`F\V`bVTLVHT`VVNbP^RNZNVLfTPXTdVBZPTXPXTPXTbLZJXHVZ^PTbPJZPNVVT\ZVVLXFfDVVT`XFh>db^RVF`JRV\TRZJX\Z>fV`JFP\RZZN\T^PRH`TXVNRDFTLdPXPdJPZ`F^dP^VTTVh8jPZR`VZ^NTHNXVV\\Z^bP\TPRRLXRFjP^ZZRPBNPVVVNTPPVNL`PNfTN`\NRTJP^Rf^VVNb^HZRP\NnVXVRJdVfPRTHVJZVbTh^VZJXbNJdTjT`^ZNJXLdXf^NZ`@`bRXR`ZJLZRVXZRLRTfPTZT^\`bTVbXbZXVL\XP\\RVbFPXVVZTRbZ^R^XTNTTb^Ph^bFL`N^Z`THjNbJbZ`ZNLZJVXVT``JXZ^RVZTRXZ`VVXLR`TVbR\VLZXV^TP^Z\XXXZbRd\HTZZ\`TXZRlV^^RTbT^F^bVJ^`VB^\PXLV`T\^bbZ^TPPVX\J\\NFfPbX\PjNTNhX\V\b`HLPNhRN\fRZ`XVZZ`fNTHVZV`XPN`RTPLhJT^ZZNbRXbLX\J^RPTPJlRXPJR\PfZj`P^HVX^TNZZVZbJRXPLTf`^^bjVfH^Tbfd^^fZfXV\JZZP`V\^BV`Lh^PX\d^\b`TZNf`hN^ZVbLfZPRd\TT^dZfV`Zb\^XPPZV^JTTjRR`JdVZZPVbVTP\`^^\VfXb\JJRXbhTX`dJ`RndXTZ`R^RJdXbXNVXR\bL`^VL\V\bVX`XbPRTJXVPPVTLXTX\\^VV\J^VVZXNP^ZRXZXZ\^^PTZ\dRXLZfd^RhXZTbTXfTRddZPNVhTVZT^ZbLZ\P`^^jVTNXNRbL`Z`ZVbTZJfVNZd`ZVXZ^TdXRN``Thj`J^T\XRRVb``NXLNZJ^X\dVZV\J^dd\L^ZVJR`VXXTL`RXTRLLTVbZfRPJRP^JRP\d<dXVbN`T\>VTPZPL^TD`bLTXVZ\^TZXXZ\f^\`XZHXTlL`^^FZTXTXXNLRd^VXZdPdNhNNThTRVRZdd\^`NZVZHLRbXZbVRbFRNJRZR\XRTVTVXdF\\^^ZX``XHNTZPTLR@VN`FTHbVPP^NbXXVH^ZNhLfNX`JVJ^`F^`XRdJNTPXPNHD\ZV^LbFV`L`ZZfH`<TdPX\dV:`PXXVVbDN\\^`>J`ZbnTRbPTT^PXRTL^Hd`XT^^N^X^^RL\V^^hZ`DtV^TRHXRZXBlV`JFTNJLVDR\NVVV^V@`XdTR^T\LbRZ^\XRRVRZdXZXRVZZZXVVVXHdNZNdXXZ\b^\^XHPTj`\^\XXH\`TR\\fR\VbNdN\RTZXdHTR^PXXRTbZVN`bTTNNX`L`LbZLd^\RTR`XZ`^T^VnTdNXPNVXJ^X\4Tf\L\XNbVfZV\\TT\X\ddZ\dPRLTZPTbXPbTVVl`fNfH`\^NRbdRVJhP\XXVXPPd^Db^ZVRVHZZdRXZ`XTXNVXVVRXTRVHLRNP\XZ`\`VNhP^dbd^bddTRZ\hVLZJfZ\\db\XPTTTbR^R^ZLbX\TVlNHX`PXZXPJTJPZD\TV`^J\`LVX\HPTFPVbZTNPXR\d>XRHVLVXVVPLJ\FNL\ZRXZRV`fTTV\fPTFb:X`NfNLbRZX`^@\FTL^Z\ZX\^XNbFPX\PJZLTT\H`PHXVXbLTdTJ`TdJVVZVN^\^\\DH`\TBXNNDVdL\RdX^NPTNZHH`LJVVTVT\`b\TNZ^PR\ZVTXZPXfTZdXVZbh^HXZNhhPV^RPHZJ\JPTRPTH``jZDb`^TTTFVNHR`ZF^X\TPLT`XRVVZRTR^\^V\`NVPZTVRXNVRZRPT`TN^P\Fp`hJRLPZRXRXRTXZ`TZXdZ^`ZPXPPXVhdXdZPVLXTVNVZRb`H\TRXJfJ\TVXZVRX^bRPb\RJTTLXZLB^d`P\ZV`dJZV^ZfNNNXTPXPXbXLXX\jbPV\XdH`NXTbhVVR\VHNTbXV`TfZTbdHBjHHR\J`^VTB\VNbN\RVZPXJTVHZZ^\bVZZ\\^HNXZTLRZNJPbL^ZTXPJ\LNZfNTX\LFJZLX\ZPbXN\XNN\J^`TP\PLJT^dRbLRb`JRhTR\\XZbVPNXXBZPNTNbLb`RLP^Vb^\XHX\Z`VVPTRLNRVPLZRd\JVRVRTJT\\\^f\PZX`ZVX\X\XZ`\\`\d^\`RPVVTT`^ZLZTTXTVX\^HTX``\\`HZNRV\fL\bVZb\^ZPNbRbRPfJ`L\NX\h^T\JZXX\NHTZNPZfTTb`PRV^TRLdRZVZdV`LVbDZR\VZZ\HVdNPRZZZTZHTRPPfXlhJfbRbTZfV^bN^NTVZTNZ\ZJPZ\JNVLL^ZTTT\ZHfZ^`jl\ddb\P`^^^V^dNZXX`dXTXTR^PVZ^dPb\V\bZfdV@bXbN`^dbRZ`JXhbTV^TRXVZTV\VXZ^R^RVfdVRbhLFb\dR`dhbLTTl^fTXT`N\^LR`hL`TR^ZbVP\Xb\pV\VhJ``\VNTZLVXRXT\P\RTZTRHP^RTZ^NRXP\ZZNbV\JPdT`X\VbRJTZV``Z^Xf`HHTRR`J^ZRXXPX`VLTLNbPX^N\PfZXP`\N^`\PLZVPRbPdP\^bfNTRFVTbJTRNHTZTZXPVRT`TVbPb^^^VVjNL`ZL^L`TPXXRh^TRVdZ`TV`VLRJ^b^NjbXNXBbRRL`Xdh\H^PR^X\bXTZXRXV>ZXV^Z\NTZX\\JbfPRJXTZRZ>^LTTLB@^JZN^\PNP\PZ\RPdZ\VZ^NTZXTPTXZRPVdXV\fPHLfL^^TXVTRT\R^NV`F\T`Np`TR\XVJZb`ZRPT\NLhXDX\PNNXTZdRPTXXR^j^\RXZjLJZPRVbfV\\jVV^LX@DJTfNJV8^VLNPRJXLXTXjX^bNZRXJLP^VL`XdZ\VBd^hTVZdJPPVhZPLXRVZLV^HVTXPRFX\N\RRRXbXVN\\PfNPXTVTN^VhT`LdVbb^`VV^`J\LfPRX\\PZZN^RRdXXbHT\dVVXlPNh^Z\dXPFT`XXbTbPR^Z`ZH\ZZLZXRdR^d^V^^V\f^ZXPVTLPZPZ^d`ZR\^^^RZLTZ`ZV^bXVR^X^`Z\ZTVPb``VVZbR\T\`N\bbbV@^bXN\`h\ZfR^PXjR\fXVTR``XRRPXVXZRDZbT\ZPXXLVLXNTTHT^TTZPVP^dLXRPBXTRF`Z`^ZVPRRV^X`bTL`PPZ\LV\RV`ZNfZTb\N`TLVbL\LhPXRP`Xb\dNNRVbV^\JR^fZVZVVHd`^`Z^X`Rbd\Z`HT^XR`ZX^RXZ:XPVTNfhRJVPhTfXT^Vb\ZZX`VHXHT`VRdXZZPTNTZ`TXPNDZT^^\PRTXFTTn`PT`ZXVbVRVTbJNJPVd`NRRXRL\^ZXRbZXVNTZVX^TXdLTb\VBTZXTb^VXPPN`ZVb\TTXNTNPZTTVNFVZ^Pd^Tb^HRRX\VRfP`XZd<ZX\XZ\L`LZb^Z\^bTXBbR\NlTVXZVNTj^^FfVZbJT^XVZNZX`RZHZ`T\HR^bRHLTXZfHTZXJVLTVVRndRX`T^PP\T`RXP`VL\`ZTbVZVdRVXL`PPXZdbV^PLjRbXdVRXVX^\NZZZX\HTJLXZ^XVRpVVLH^FXhdbNXNR`\PVJX^THLVTR^DNVXXHVJTRb`HNRhjTfR^Z^VX\N^XJV`XHXNTXNjJJ`L\PJ\@NNTP^VXN\TZLJPJNN`XXbVLXXTJTdPRRVd\VNbFRLJ`ZVR\XJVZbLVRTBTPbTdVTXTTV^^ZZR^TJPNhN^LRZRbT^PNRVNX`VPP`NPlRJBZPdZ\^b^`R\V^\ZbJT\^^PF@TZXP.FNN^\`L`^dJRVR^TVRXZThLDVXXJNNXJXP\\\XRTPVTVTXPRXJRRZbVLZPVbb^VT\`\\Z\\PXhhXRXXPTVPT^\RdZhP\PP`V^VRZZVR>Z`@\VZdT\XV\VhRXdR`Z^fX\^T\XT\Z\R`XRRR^N\NbXNRX`\VZN^ZZTLNR\\\TTfbP^LVTP\LXPfJdHTPX^`\ZXPbJj`RbbZ`NRVbP\NVXJTBXZ`lR^XTTLd`fLZ^TXF`TT`\PTZTZXXTR\RD`^ZZf`TXZZRNR\P\RPJ`ZXRZVF\TZXXTV^jPd`h\fZX^pPd`Z\XTRbTTXZT\^XX^bVTHp^TddRfXPX\\XX\RT`L`dVX^``XZ`PVfRbVXXTddXPZXVTPPZ\VZTd\VX^HTf`TZ^RDVPZTLXNR\VVXV\BHPXZbJ^PTFPVRTV\\JVRlJPRZTR\\T`P`X^\bLJXB`RHdPTXNZJRFlLVJNRR^ZVRhZRNhT`^PTV`PRLRfVP\^TTXZPNVbP>Z^TVTDZP\^Td\VR\P^Lb\:VXLNNV\NLNRTTNNJ^ZZTJXZPRXXbV\T\X\TRVZB^XRXJD^FZVVTX@^\TXTZ\RTT`TbTVDXZN`JbVVTdRL`VV`NZNB\\T\VH^R^ZTVZ\N`fNfXJFTNZVfRPpLdXdXXT`P^PRXRRVZPT`^RPfbZNRN`dj>^VPZVJPXb\RNV\TL^\RV`dXVbT\TVdRXHLZ\bNLTL`TZXfVTLXDbRTZNDZNJ`XfPTP^VT\X`bTZdndTZZRb^lFLdT^^T\`^LXH@RRPNjN`TPVX``P`ZPNVfPZPZFTHT`VN^XLNTPRPT\BN^\bbTXd`PbV^V8ZjNfXXBRVTbD^R^T\^PPVPR^VT`RT\fb<R\`JRHZ`VNJT^T`8PN^NjJ\^NV`\jTPLVRRN\F\`RTd\PZ\T\H\P\\R\VL\NZ^^`\^XXLTVN^ZXZTbXTRZZZ\b^\^dXRJfb\Nd^TTRZNPP`LXFTVTXdRVN`d\T^\PZfRFTXV\XJXTd^TPX^`bV\`hPXJ^VX`FlRb\VZVTTD^XZ^V`Z\hXh`XLR`V^dfTL`TVXb\^XNV`\hNZdZTN^`RDbfZT\^dVXNZXZN\RPX`fNZZRF\ZR^ZTZHRXBN^X@PdPXPDjXVbT`VbL\^^hVRl\P\^T^VJVdT\V\ZRXdVV^L`T^LVf\bVd\XJLDLX^dDb^XTNXZ^`bdZJ\NPbhL\PPNlJ^ZNZ`TXXXVR`N\\^d`b\bZXdP^PN`J`\JXR`VR`VP\RHFbN\X\`V^TL\P\RdHFZVZVZZVJdLXXXRX`NbHJTXVTXRPh\PLH^VP\`LfNXXTd\V\HHPJ\PZfVLTT^LXRNbRZXRV\^LLXZL^XPHb`TJRXXPXdXTbV`N^RJddP\RRTFBJTTjLR\V^RZVRXVfDL\^ddFV^`P`bZV\PP\J\bZLVXVRZRVXZPfXXbDTRRXTJTjZBXXL`F^^NTX^TVXJ^^N8bPXJRNDXPVVNJFXTXD^ZXZTL`VTR\NPTZXVT^NZVL^JN\JZTBXPRVZNfXPJbXTP\D`ZZRT`N^\^dTPV\RfV`V>VTXXZHV\TXdZ`VTR^d\TV`VNTdVP\LPXLPTPPRV\XTRXbNV\ZXJVRTf\PTTVFVTRNZHdDNRN\RZXJRP^XTZJRdXV`\`V^`\`ZV@RXVNNVbXXT``Z^bNTNTTbLXXVbLV>R\b^TPLJX^^BT\TJPPX\HVVRZXVL\bbT\PRN``HdVZLPfJdXZRTVD\PLXLTZHV\N\H\bXbhbRP^LbRZRXXVTV^X\^Z`b`^\ZVR\dRVVbZVbNhXNbZL\Jb\FV\V^`TJdbbV``Rd`RP`^R\dTXXbVPP^T\jTTX^VF\`NRTTRbXTTb^TP^V\\bbbN^N\PT^^V^XZ`\\V\XL\N^D`R\RNT`Hd\XBR\`^RPT^ZZN\NP\PZXXNXFRNT\ZVX`XbVZVVXTJbZ\RJT\L`P^R\RRLZdf^fZ``bbRjZfRXbfVPVR`b\^BZTNbddNhN\ZZTLD^bLLNfNVjTRVjd^ZVVbP\\`XPPdZT\^bXB\R^\VJT\N\NVVPR\VNZZTbdLJT\XVTTT^ZXVXZRhXL`b\XLTbVJ\\XPVT^LhJXR`TXRJL\ZN\`RPTRXJTXhLPNJf<X^PV`V`TRTV^ZNLZRTT^^XVRPFVZ`VX^L\fV^\VX`X`PVRRdZVJZXTP\ZR@NZRLVZXdLZ^JXHZLZbbTTT`JPNj^^\^X^RZN\PTV^LZjZNRNVBX^NNH^jBT`V\RZVTNRLVTZLJdTV^JXVTZZRfHVfZ\HVVXTPbPRXbZZTPfRD^hRVN^XPBPN`HZT^H^F^T\XL\bPdVVJ^^^D@JVbBLL\FNpFX\^`\HlP\XFdFPXN^PZDRFZJ\dXVLdLNNPX^Z^NVjV\TPZXXVVP\VPZRTfTVRZVVNJP\P\^TXJP\ZVRVXJ`PVZdX`<RdhFZTBfR`\TTNR\PRdHJ\XXRNJT^XZNRj\VTNVV^X\`\VdTRZjbHZ>XTb^TRFb\\^T`P`ZXRRNTVRZPZXZTT\HPdRJNTZ^`RZVbTX^hVN`^d`NfRVRVRRdZLT^dPP\ZV^DXPXTVRP\\TZTZ^N\dP^Nf\XT\ZLN\H`XXZbPR\J\\RNZ\\XNbT^XbL\TLXP\XNbXFjLVTVVNVN\VdRfPTRD^T^bdZ`ZZXP`VfTV\TXRPV\\djT\\XZZZFr`\TTlFRXNd\XZ^VThV\jTR^jJ\FVbZXZXXZJVXX`Db\J\^d\T^HVV`\PhLbTbL\f^RVbPX^ZRRF^dTjP`ddXVNZ^XFVb^\P\VRPVT\PZ`VTRZfPLNJ^TZ^VJnLRTFbNLZL`VJRPXFfL^hbfdRd^PTd`dZ``XZ\\X^Z`Zf^PVT^VVVLZ`\VVXVP\RT^`TLVJ\H\RNTNRZX`VXX`ZVbfZRb^bLZTN\ZbVJZXbXL`PJ\ZVf\VVZN^VVLJZXRfJ\JbJTT`TRHRLRPZ^\V^ZJV^^VDT^LVhZfPXVZR^ZdLbRZ\PdTZXRRLTHRRT^VRTR`RVZbLXFZXRXRX^\DVTVT\`LP\^VLNVVd\^XT\\XJRdRV\V\\TVJNTZT\VRVPXRFR>dRXNZ^TV\TRHXTXTVXXVNfNPVVHXL`j^bVXH\LTXbNVTVZLNdT^ddNPD`\XbZNPbB`TZRZRV^V^VRV\R^\NZ^`FVX^PR^Vj^TTN^^HLRVNTXJZVXZPV\NNLZNXR\VNTVD^T`hXX\DR^R`fPN\hRZXZH`RV^TN^jPZTNTR`RRZT^XRZ`ZT^ZPX^Z`RXRZZXT`RNZPXVXNXJ^bLZXVPXXR`T^NPJLDLXXZNLTLTZLbJFV`HNdPR\ZR\J`X^^ZVND\\\XPVVTNPdRXVRPTDbbPLN^V^<X`\VPRZRXXR`RTZNRFZT\`THHZRHLNP^TLbV\^^bVXTV^ZV\TRHZRVZR\ZTXNh`V@VLdRX\VX^TR^X^ZTZVXbbRPLLZJbRDJRRTVDJdFXP\RRVBRX\HVTVRZ^^bJVdR^R^TX\ZPVZVV\VPXR^HT^^L\PNPRPZdbZdD^RXRZ@NVLH\Nf^PTRVXbdh\T`JZXVf\N\LT^ZVZRR\fXfTT^\TR`PXNdRRZR\LRZ``NfXTNRV`T`VV\RTPNRRZX\N\``ZTX\^N\R4\`TVPdddRhD\V^TH\TjZRRNXdVdfZ\jLVJ\VV^ZPVVHjRXVPV`H`V\LT\FJThV>`XZZNbVdf^V`X`N\XVXH^\XbVb`TZT\blf\ZX^b^NTTZTXZ^DPVLHbTbVP\hR\Z^XPVTXVDTRXXh\XX^VJhLNVR\Z\VL`ZFPRJLXXfN`\dZ\^PJZ^N^^V`jLjRJjZ`VXRbHRXJ\XJbNZNlNLPXHd`LjL^VVRVT\LFTNPNdZ\HPRZX\JL`d`TbRTZh^VHTHHVTZZTZTbL^Rl\FJfTXTFlPT^DZZ^RVXV^R\fNVVPbR^PVDdXXdT^VDJVdPVNdD^NVRXPLVLPNP`\RfXVZbbXP`bP`L\XLTFN\`PVLZJLVZBF^RJ`\VBFfRPR^\ZRP\\jRV`XNXTPdPTXPVZLVVVXb`RZPLZX\`VZVP`ZXRNT^`\BT``T`\LNXXdZ`VRVNTNZ`XXTd`F\^\\Xd^TZTPV\RLdRHTP\LVN^PPPdDTVddPTTZL`NRfTRT^TX\\VV`RBh`ZN\PTXVVV`6TX\JhZVZXN\XRT@VbPZF\VNXXBN\Rb\Z`ZP\\XT`VhJZZZJ4RZXTVFfR`^PX`VZF\XFV\TRVXPXP^TTT^hL`VXfFVTXRZJNdRjT`ZV`Z\VX^^Rb\V^NVXXZXTJ^b``bbRdT`pTRP^X\L^b^NNHNRTbZZ`b^HZ^ZVdNJVPP`T``XXPT`ZdZXV^ZRX`Vb`^\VVZRXRfVVZXXPdR\LXVTTJ\PZZbfj`^Z`pNRbLJ\^Rf^hRB^\HJXRRbL\@PZf^VTZ\L\XZPlHXJZ\VRlRXHbdfdX\NLNT`ZVld@PRZ`\\RNdTpRnXPTTX\R^T`^VT\NTV```TbXN`VT`\P``TTRXX\f\^\XVLVV`X`hP`RD\Vd`d\``\Pj^RZV^VZVbbXZTRbZXJ\VLl^`TRT\hDTfHRLdVV\LbXbZBVdZTTX^TVPZf^PXZRXPTVdJXTFTZNVRXbNB^TLbVR^`^ZT@TR^T\TZ\Tf\PNTVRN\LVZZRZJPH``JNVRXVLZVZdV``Hd^`d\RH`lTVP^LVZN\N^\NVTXPRVH\^DXJHVTXV^L\\fR^fRHLZJXRZXNRPbPXNRXZfXPTV\T\d`VNPZNV\`X`RTRJLP6J`PPRXZLbNZFfLTVTVRJ^Rh\HT^`VfbZ^ZT\b`ZVNPTLP\X\NV^XdPN^@bZV\^TXPX^NNXNbPZTLV`R\TbDXT^fT\RRTRPX`R`PZ^PRX^\PRXP^PVZVXH`ZbZVNVNj6TRHTVRlNbT^PbTXX\^R^DdX`VNTlR^`RHZRZR\`VP@NXZZZR`VN\JfFBRR\bPP`P`dVRFbNNRRRPZTXPRXTXXXXZbJRjV^XTVTbPZV`R^`ZT`RFjXTTPTVZLXXZX\bV\\LRXZTV\TV^XNPZZJR`PVVJ`VH\JdP`NT\TVP\^XP^ZZXHRVF^XXHXPX^V\PPR\T`LPX^PPZ`^h^PVV\RZZXNbTX\P`ZD`N^\d\X`\\XRFZPVZRz`VZZRNTFZLTTV^ZXXXFXRRXDZXHXfT`^HT^ZNR`RNRT\`JVbRVZNVPRNVZdRRLRXZFTZXXTJZN`LZ\TLPLVJHLN^XPZVBhTbXP^T\RPV`V`VZZ\bdNTXZbVNbPR\\Td`f\NT^X$`TXfTXXJdfTRbZTXTfJZPNNbZP`XbZZ\VDfVH\^TT`\\bbfNP`X`jVfLX`XZVbZXf`\^NVV\V\X`T>DPPVPZJNbdBRNHRTRXN`ZhZZbR\VZX\VLPbPTRTX\LZTX\ZJ`ZJV\LL^T\VTLThRX^`XbL^`HTN^NXVnRR\`hLXj\RRbRjZZZdTbTJ`dVV\TfRZJ`VT\RNV`b\\ZbbVXNTLXTR\RbNXXL`\PRZZ^XVXdPLTdRL\`TXdR\Z`\HPLZblTh\VZZNTZ\\T<hT`NjXRN^fNb^HZ`\LVJbFHLjTbb`DjNRRhXdZRbJR\P\PR^VP\TPTRXdPVV``RVVb`ZbVZd^hXJVTb`P\LbXXFT^`TT`HZ:\`RVNT\^PV\H\HX\Pf^Z^^LRPVTfXbVXZTVZbRRfNX\ZVTV\VV\\bVTZXTR`NbNRTLZ\T\bTVT\VTTXT`b`HRZX`NZ`XjbVVTXZZ`FXR^P`PVbZJRTRd^VXXFbNT@ZRVZVP\^LTLLLVZXhJPXPR\H`VTR^FLVXbTJVTLXFBJdX^XBVR^`\\PfX`^LdH\NTLZF\P\DhZXR`^`TLRRZPPXRRXRVBVHNVTTJRNXTX\`PV\P\VP`TRRRNRdV^\N`bRZXb\VXXPPR^NVVRTZZZZbV`XVF^T\VVXXDJ\Zb\X`XZ`RZB^X`TTXN`X^HldN\TPT^PL\\XFl`PXN`ZVXNJ^P\ZHVNV\RL^XbZTN`RbRRT^NNZh\dJHRZ\RVTRTXLdV^@LTVdj\`ZFZTZX^TP^^`X\HRhf`VTTXN^8ZbZ^^`XXhLP`bZZF\^NP`hPVdR^\`X^\bf`^PRZjTR\VZ`bRZ`TbRhZXRbP\HNZPTZRbZPTZ`N^TRX^Rb:JTXXP\ThTXVF`ZZTPXhnP^\DTfVVNDJ^`T`ZZZ\ZNFbPn`^Z^^^PNRT\VbRhT\bdX^VZRRhNPRdNDlZTfHZ^BfP\NP\JZLTbX\RR\``Rf`d`f^dPZh^Z`V\PRNTVPbRL^NVb^TJ^\TNdT`ZRX^\TXVV\T`R\^\^\^ZRRPL^NLFX\Vdd^X^L`JVVNXHXNRJR`PZTJ^NXXTRVjZbRL^Rf\LXNbFfRVXZPPRTNNTXbBDRRVPXbVHX^\PNVVLRVbHXb`TPT^L^L^^XJV\PZ\X\`^VRHdb`fXZX^fdLRbXTTPZ`XXT\L^NVTPH^T^HZ^b`\PbTRNVbZfHJ\bFf\V^LZZ`VVZXR\XB^H\\HHRbbR\R^BLPbRVdFdNXT`LZRTX`RVFP^FXTTdT\TbPPJ\V\PV^RR^D\P\V^Vd\NR`LZT`NZ6ZXJdLRJRjL\VXXLLTT^T^NdRPLPLTPTJNPX^VZXPX>^VNVZ^XRVNb^XZRP\VF>LXRN^R^RLbTRTP\RBRRTXdJJ\PVVLVZdPJTTPNXXNT\TLP\PRNF\RZVX\\ZZNP^``L`TP^XXdVT^RXXPL\FLXPN`V`PVZZ\T^RVPd\RN\`\XVZbZRNRT^X\Z\XZNRNZ`H`XT\`NZV\N\HfTRT^P`ZNXTHLPH^NfFfTVLFZLN^bRZPPTJX^RLX^LNTVDfJVR`RP`TLRbP^BZN\ZDVVL\XTZDZfVTPPXJTRLZZ\RVXVNVTPPBZTV^^4\JPZXRTd\X\VLVVVVT`bNTPPjX^PPRNbVZd^T``HVd^VVTb``NbNhbH`RLTRd\^XVVVV@b^VVXN`^X\L\P^^\ZRR\PNd``^TJXTVV^RjVZX^ZPdTfbXP`PPXNTVPRX^ZPLZ`JbZ^ZP\RPhZLPX\VbZV^^X\RX`NN\PP\\VVTdXXVNRhdXN\P\`TVfJdZ^X\R`VTZbZfZHVTTVnPZRRV^\NZRZXhN\RXb\bTbNffbPdTd`jXRXXf`V`V^hV\\Ld^RTTbfXf^VV^XVX`\\RTXRf\`H\RLbT^R`RbVXZRRdddZTTZV``VX`RjNXX\`RNbZR^`TVVZXRLRZ^JZ\XZfTVNF\RVV\LhNPRRZTfZVVXTZVHPRVVVZTJPTVXNFVNL^\VL`VR\^D\RJNNN\V`ZdPnTXNjN\VT\TP`TLFbXZXPV\PJL\bTZVXXXXX^PX`NJ^ZVX^ZVL\Zdb\ZR\ZNb`^XTPVR`RNPJXRfNXTRRhV^LVBNVNPZRPTTVXPHXTRTZV\^RXTVFLP^RbTbL`LVT\VTZ\d\PXV^Z\XN\X\X^PfbX^DXR^VPPLRX\NTbVNZLZNHZV`jRhPXffJZRRVVPPZ^RPPX>b:^\JH:\PXTRPVRXRZXhRP6dNfR`dTPV\`ZZ\TVRTP\Z`LFJZVPNRZPTRdP^TPbZVJVL\`RBThJZNjPNb\PVXTZ^LRTT<bT\VZXLTPXVN^RTNd`TRLZR`XDZH`Z`^RTd\XTZTZLVTdPZ^RXTNdRHhLH`H^\HNZZ\Zd\@TNV`VPVV^JVJ^^X`RVhPbPPRRb^`VZ^XbHHNPZXPVbfXPXZPRPPHHPXTXDHD`^X\XZZZXRdTNP^bX^V\TXXPd@R\H^^\ZRZLZPJXd\V`\8L^lT\XFfXTLPThX^PN^JTTbD^@VZJXJnXTB^`PFR\V\`NX\^lb\P\\JVR\\NbXZ`TVhFjTNTZRF^b^X^TVlLbRf^`ZR\VfP`P`^VR``PP^PfZRZZFPPZTTVVPLRXV^NRZVZbRX^`N^NNNbP\TVH@bLhN`LLbjPXPRN^L^^VVPXTZPPZLVXTTH^`VVPdJTV\T\`Z\NNh^lRXZFhTTP\TR^hRXRdNR`\N^RhTTdXNLfNXThb\JX\\TV`RL<LVXb^TZ\b\ZRPTXZV^Tbh\bfVXLT`TFHXVJf^P``PJRRRZJJVHLPVNLVV^ZLXdXRHTRPZ\Pf^\J^PTXRPTbL^ZLbZHX^D^DZbJF\VNXHTXTVZPRb\N\RNLJTT@NTXRFX`X^RZTXZF^PT^FJ^\PNT^LTRXZRVVZ\\T\VH^NV`Td^VTPRNXZN`VZ^T^XV^VPPRVFB\VTVZ^LZVJTX\NVV\`XTZRVV`ZXRX\LdRVJbXPNHTTHVXR^L`dVH`HTJhH^VJVRT\^JX^V^FXVXTTRL`HDPLXbZZL\NN^XVXPB`ZTRZTVTZVX\ZRFVJNPNTPjXX\LXbhLV\NR\ZTNXV^TJ`\LHVP^V`^^bRR`\ZLVZLVHN`BVLXL\ZNZLTN`H^XHTjNN>^HTPRXPHTTJZXPRZJDZXRTZ^TR`XVPdZTV`VVZR\TZR\P\V^ZLPN^VbRZN^ZNhT\Rb\XNRTNXNVRZP^RTXVN\`XP@LN^JRR^LPFfVRZ^\\XTVTZZVXZ\LRTTZT`XNdLTX\ZVXfbL\VT^XHfVXbVN^PTTZRLX\V^bV^^TRDbP`bXZNZfRLV\V\lXlNV\ZRf^NThT^XZZXR\\XZ^N<`X`NNZTZ`\XXVZN`fXbZZXLR^\XXXJZR`VX^H`b`\TpVb```ZXD^\TPNZXZPdXZXdXVRfLVTTfP`XXbH\TZZVZT\\BhPVLXRL`nJVRfLdTXh^JJfXTjVFfbL^^\ZFfNZXZPZVTd\`TRbZdZPfR^TdZ`RZVf^\\VfT`RFXXTTVVVT`pbRLXb\NFT^J`VZLbN^^VdXZT\`FVHTRZVT8Rh^fhjbbZRXbd^XnZXN`h^`Z^`VTTr^bPZVPnTPD`fPZ^dVVT^dNXfXNT^dRVZbXNVd^R^`ZbXXXf^VPd^\Vfl^`XlhPZbTLVbRbBX`V\FTTPZJ\ZXBVPVX\LVHTXbHR\LR\JfTLT`TX\XNRfXRV`JVdZTD\Z\d`h^N^dRX`XJNfNH`PJNTNHVN^fL^J^^\RXVXHX\TZX`FN^XPN\PHP\`\ZRXRTR`\ZTJ\ZX`XN\RTNP\J`\FV`PZh\`TdJR\VTVJ^^B`PNTdLXX\V`X`XRT\Z\XPb\PbhTZTVTXRZfVX^NN`ZdT^NVNhFbVZ\XXLJ`V^\bNZVHXR`P\\JbfXRTNRHVHhNZPbTTXJFTVbZTXLP`ZRLDXLHLT`PPbPN\VhbT^PJVXT`bVR\Z\XTXLVTPRPPbXVJPDZTPH\\^BHXZ^PdXdNb\TTdh\dF^RbZNVR^^bfZTJLJTPNPVd\XXPR\ZVh^JF^Zf\PbRFDVTTVd`\`^XbTHP`VPZFXVRZ\NXZ^PNPRRXX\LFV\H^Z^ZXNZ^LZXZXPbXJbZ^PfPN^ZDTTZXXPZX^`JJVTZHd^V^XXrNXN`\R\VTZLJbZT\^T`Z\RZbTNTT\RVRZTD<LV^`R\NZJLTPVdNHTV^D\ZN^\NPNZTRLTXV^NLXVDJ^d^PdZXV`P\PfZV^RXVJNRVNTPN`LLV`fZ\ZNRXTRVZT\RV^`ZVLZXTPT\R\ddVXVRV^L^^R^L\PRXFbbPJ^d`HTZ\R\X>\ZZVhVBTZZXZZdHPNXV^RLJJR\H`PRbfRdJbT^RN^PbVZdJ^T^^bXN`RVL\JV^L`ZJXTL\pTTTN\bLLfbV^d^Xd\XbZ^`hZ`nHdTZ\NTXbZ^V^X^LXZdbZT\XPd^NTffL`bV`J`\NfRZTZX^XbdHZjZ^^`\NTXVZHRPNXFXb`ZRbX\pRV\\^``Xd\V\\R\TZV`^R\ZJRRX^VTZJ<J\R\TNdHZXlJTTVZLbVTTTHZTZZRZ\PTVZPLZHTXNJL`PP^XV`ZV`^H^TT^RVbT`JVVTjVLTPRX`\RbTZRLX\HR^VPZXbP`N\\LVZLZP\\RfXZJN`LR^TT^\RNPZdPdZXZR`LTRPX`V`\RX`DRNVT\N`HZZ<TRZTZ^ZXXPTbRXXTX\V\ZTXf\ZJTPNX^X^`ZV^TR\TZXLRZTLZbZ`XNZTRTXHH\Rn^ZRhLZLP`XTJXHTLRTVPZ\JNVNVNZTT`P\ZP^RZTXRPTN^TNXVZRdRH^bT\X`hLV`b`LXXTPRVJZ^ZHZVPdRPPHTTVTdXH\ZVXTH\JLL`\XPbTTJf@bXRZZB^R\NBLTZXFLJdPVZdbbZR^bXVN\VTVPTZVV@\VVVXZRFBfT^FTZPHFTNbHDNfBZVV\DX`PZV^^fV\T@^VPR`VdbT\\ZRJNTZnbXXNZLTTXZf^ZbRNNXTXZ\DRRTL\\NVbLZ`L^PV^XVJXXblRRT`^^RZ`lVFTPXZLPZZ\T\VHVbFXfL`RhXZT`LXRFZX`X^RfPVTjXXRRP\dTRVVP^R^`VZTPRPZZV\bT^TbNXTZ\XTRXZbJRX`VVXZ`TJ`^LfTTT\^fP\Hl`RTVfJPd^^VZ`\Vl^^T^djLfdNVZ\PN`^\Jd`dVR`RVV`VXRV\ZZT`dX\Z`R\RRTVX^PLL\\dRRZdRfZVLVHTjRPJZbXZPVh`VX\D`RZNfZX\P\LVjXJVXXNXbXfRZ`V`VTNF`XTXRj`^\hTZhfbB`RL`L`RVjTZ`Zb^d\`dXXJR\ZVZBTfVLRVb``R^bZVXXf^ZbVbVXT`PVXHfPTZ^^^\Z^T\N`XZb\Hf`THRNZdbZ`VdNPjTPL``^VXbRNRZ^\^b^H<b^PZnL`ZbRPbRPTbTJ^R``L\NXNN^RVVZL`JFZPR^NP^XPTL``VPNX\NRTL^RT`X^L\XV`VbTZdXVNXTV\Z`Vb\\VZ`Z`X^PXT^ZV``VNX\HrT^Z^PHRRPB`ZX^XV``N\TZTHVZ^\^NNVXXZ^PPFVP`^VT\TL\PP^V\^NRRXZZVdPVVZXXX^PRTbRdT\^bPVLTXVNdP^`XZJNJZ^RbVTV\bTXdb\XV^VVZVhHdfVZTTZT`PZ^VT`\\PPNf8VLTDPFZb^FXNZ\D`XjZVVNRVT\N`TP`Z\`XXbPLPTTTL\RPNTX\bRLXZ`RPZPTbX\```ZHFXZdTV\X\^^\VZJ\FLPVXX\X\RZ^XTPRJbVLZ^^`N\lDP`Z^L`\ZZTbRPRX`ZX\XN^VbZRLVXTj^R\XNZRXdVFPdRR^PLNPTNTTbP^T@<^PHVLRXHV`V\\^NRhLPL\PP^\^RbZVZXZRVXRfTT^XTJXRdVfRRPR`DN\^XV\VXTZPXR^TTZXTTZRXX`NT`ZP^d`R\dRXV^d`^RRHbNbTZPJZRhXZRXJ\RHjXZRV\N^`LRb`PTVZ^fNh^bJdfXL^RZ^VVTNRNZXVHb\\PfNh^bV\XT`PP\`NZ^LR`dX``ZV\\ZPZJ^\VNZXX\TRfZVRX\`RZZPR\^bTP`bNThLTNbTV^XNXZfTbXbZZVdP\XV\NVLRRZ`VXPRfR^RbZrTVRdZ\P\RX\X^ZP\TZVhRfX\VTT^X\XbPVXZZRN`RNVZNRP\\fbVb^`PfZTb^`\Z``^Z^VVTTdZdP^ZdfjX^d\dbVN`hbNVVZZJVV\RJVVjbPVTTL^^ZJVZTd`L\NhXThVJR`XdXJ^Z``VTRbHd\^RRPTbPJD\J`RZZTRT`<^R\ZZXLZ^ZPZd\HdXlRD^\XTfZJ`V\^NPVDVbR\J`Z^\FPVVNJXJZZP\HjZbNX^ZTZ`\bP\\VPTT\\XZLHVT`\NTX^^ZPN`XNFPL\fPV`VNjZVLP^b\XdVL`TRZXXTVRPJFZZJR\RPVXJRP`HRTLVT>b^VP@\PXTfTP\\VXLZPPJVZNRjXT\^fdPZZZ\TXRdV^XTZNRjR^PTZZ`R`PX`ZD\NRTZbNVRRRRbLb\F`NFNRN\VLLbRTXXRPNTPRPPFVZ\TRR@VTb\d^TH^hFN`jRRTPVTZ^V`TRNRZ`^\P\RD^PVZ@`PLJ^RRVZVbVXdL\0NXTTL^XRRL@PpHLbR`NPBFbTVNDZR\ZXX\bRLHbNH`JVP\dNXR^bT^PLFXXbd\d\PLD`VT``VPXJVZRHRRN<`VZTNJ\^PHVT`R`dNHPXVbPLPFNd\`fX>`Xd^`ZXRRVR\XXTV\`\RLT^PTRXRXdTJbPHZR^`DTJRThNVRT@\FTRJTNfHjTZXPPZZRf\Rdd\lbZR\VbVfRfRXZZdfVd\P^FZ`T\LZV^ZZZRZF`hZLfZVT\\ZP\^NbRX\`NXZNJZbZZR\V`X\`^\RjR`RbT^hPHdVZZTXHhR`XXPZNVTTZ^PHXHXTNXXN\\bX^ZhTX\dT`XXXT^^ZTTlDV^LVR^^XHhN`RVdZjL^NR\NjJV\J^J`\^bPZVZTNRX^fVTlX\NN\\FVR`ZPLVFXZLZRFXJZ\X^PVXRXNNRdL^XZ`l^XVXh^FT`\XZT\bN\V\VdlLRR\PpZNT\^RVXVfPbXZ@\hTdNLVPV`NV^\\HdXX^XVXX\bbP\ZZ`RVRTZVdX`ZLbTV\ZXZh@\^HV`LVVTTdXFVHPFNXNfVPPZ`Tj`ZhhFbTRd\X^^hX\VTRZVTZTP^RPVVFT`hT^P\VRLbZTVH\Tb\BVNbXZJfR^\ZV``dLZZZ\`@PbZXHTPTX`TDP^F\\PVbXNLVPTT`DhTVf``Z\RH`jNTTZZZDXXV^bXRBHVLHTPPTZLZpXNZT^NHfX\Z\R^\ZLRb\J`B\^JLJX^NFbdbD\\XTfNXRZ\TXjRTDXVXLZPlb\^V^`VZPTZZTZXbFRV>`TTXZ\Hb@NV\\XTZ>hRXRfNXbLT\\^RZLNXXXdT^\JZN^\P^LZVLTR`PXN^Xh^XdR`TbNTTZN\b\T^ZVJ\XHRTZXXFXBTdLLXj^PZRVNHZZTRJNX\XXPLNZXP\F^X`PZRTRnNbTlLd\T`P`R^NND^TRT\XZVVVRZ^LNTL\XJTPZ\`T`D`NPVRVVPPPXPbbbRTJ^TRZT\VP^Dd@XZ\VTVNL\H^f\T^XPd^TRTTRXRZ\VZXT\PR^TRNRLRR\\:XJZfLVV@PVRLLbBVVJbPVbNP`^dVZ<bLbRT^`jN`PXHVb\NT^RXRVXTbVRP`^RRb\TbVV^ZVP\ZNLRXZXdR^XZVXR`ZTDXJb^FRNN\ZRJ`NV`TXRhV^XVbPTHb\^`ZTLTN\XDTXRZbT^d^lN\`VLRNNZ`TJZZTRXXTRnLZZ\LX`P^VNZVP^jTVd\ZVbPb^``PVRVPNXV``D\TXTd^dLbZ`F`ZX^TfRb\T^ZVXB`P\NPX^ZbdL^PhLR\VNbP\XfP^`DXLXVNf`X`Pj\bVXdTh\hNXZ\^TXjXNdVdNL`RbbZ^ZJTXbZT^TXdXf\dZXV4^P\X^bN^LNRJNZTRPdNHZ`FX\^VPfZ\ZbPPRPNbFLVPHVTV@JPVPF`dJHV\N`ZZT@PFTXTPPTTNNVJPZVZNR^LX^^TN`LRZFPbRV`NNTNXbTTR`\PNTVZXXhbFRPPPVPTDdNBVHTZPDHF^PZ8\F`RVHNBfRRZLHLVV\LfL^T^\T^PTbXDTRPb\\XNNZ^FN`RZ^bZVT^R\NTVLbRZVTdXhVNTPZLLP^TRVPP^ZXF^bXTN\\`TL^^\TT@\NR^`ZB^\V\XFTVVBTF^hRZNVbZLL\\T\VRRNXF\ZHTXlB`TRZRRT\LVRdZN^\TPJ\P^d\VNNLDVXbRZR`JZL\bXL\\VTbBZJXTThN>TZRfL`NNPNNbHRVVXN\N\P^PTJP\JTLXVZ^TZdVVBZR^`TVZP^dVRXZPTRVVZNhXDL^L\TN`ZJVL`XPPPPZPXRZPVfFTVXJTZRLRRPF\J`dLpFZVNZRXZZJZPLZHj`^JVRVRNRjTbh^P^\R\NRR`\N^RXTR`RDRF\fbVX\^NhTXFX`XTZLdZZTXVTVVT^ZZZ\VNTfXNN^\T`LVT`LV^HhZLTLVVTXRNVXTT\XV`ZJLZhV\^bRR`RRXdHPTfV\^bTPVTTR``Tj^P^bJXV\VlRbVRXbFPXD^TZTZZVp^\VL\XTd\bXHZ\T`\^f`\\^R^`FVT\\NR^\P\X\RXjZT^`LVPJ^VTbTbhFXdVNXX`PX^lNVTN^XhhP\`TbT^VZJLXTbT^dJZ\bPDdRlPLjbPNZZJ^`HXXRdXPP\VNZ^^RT\b>ZZN\NXf^``NV^hPLHJ`PbJTPXZZnPXffdZdld^`^`ZZ^fJXNfVZ\RdTZ\bXbLLNXX^\^^H^\PZVRThRR^ZL\ZZT\NNR`RXRTR\BDdTXTXVVPVXRVd^``V`N\JR^RlFXXdP\R\\NV\RT^R\hTRd`LZ`NRH`P\V\Xh`hTbFZZNRRV\\RVL^\^RVX``HXNfdXRZVV^ZJVX\NbHH\RNVP`VVNb\bTXbTR`XLbZTb\BZLT`bTfTbXRTNX^Vh^\\XXZ\BZZLTPfZb^BZZb\ZR^T\nV`V@`ZPVV`ZHVdLLNTN^PZJRZNFfTDRZ\dP^BXP\N^NhRb`\^NPPT^XZZXTXJ`\P^PNJ`PXLbV`DVd^fRR^^LZb^F\PRLXXZVV\hV\PTTRHRbbdR`BZ^P^VJT^XdVVLVBN^XVRFVZ^RHHXdXRPVL^VPXT`JT^\RXfR`T\RjVZNHZ^VDTTZZZVNTXRPTfRPPZN<ZLHL\V\\Z\^P\X`RNNXZbPXPT^ZRPXPLZXJ^bXR>VJNRfZVPdjXTPlBVXV<JVJVdTTX`ZTPZ\RZVd^f\R^^XPNHZDbX^XZd^\V\Z^lD^^PbNDVVbXL^Vbd^JJ^^`\N\\^LNVPVZ^ZNT^XPfXZX``RLT^ZRZ`XXF^XXNL\V\LVT\VXRRdjZ\T^X\RVVXVL^TN^JXVV\XTVZVZZ\b`TRR\TPVVZ^TjJ^XRXVTbZZR4X^RRTR\ZZnbZZ\^HHX4fJJ\\jTVdVXHP^R^NJV^:`TXR\HTXXP^LTR`\TRX:jf`RTf\VdR^H\ZVX`NbRZRXZZRLHZNRPXbZ\X^LbRVX\PdbZJ^VZPR^NZ^RTR^RJTLhZZb`RX^ZZ^VVXTTZXbHbL\\T\VfVJ^dDhT\6XPVRZJ^TX^^RJVLNPXVTFTPZVXPLH\LLRPLRLRbj^`^\\jFLZZR\Z^L^ZVLTPZhVP^bb`X^ZbZ\LX^Nf^^\VPJXhPZX`ZXPhRTfL\Ph\XZR^XTZVNNTRJXbV>ZVPHXJ\\V`RJLX\VXTNVL\\XLXTVPTVZ^VlZLHDHHXVX`ZZHRVR`XLPXXHRZ\VVdDPZTLTP\ZRPfXVRL^V\XXPj\HXF`PNZd\XFFZRP\P^^XPVVRTPPdPZXXT\\ZXJLZPJRXPlVFnJZL`LZRZJHH^dLd\FVJBN>F\hN^X^T`H^ZdL\RV\NNFHR^PTXTNPTVdZTJVPVZRRZbNN\NLLNfRLN\bFFb^TZLNbZRTRPPP\ZZPNRFNbTVZV`XX^VT^RV^TRTR^NNNXT`JR\XNDNN\ZRd\ZTRRZLVXLV@R^XV\ZPbVXNZ\\^^\JNXJZ^ZTLJP^ZVP^8ZVBJNNXLJVRVN\jVfbVNbZTVZ`LN\\FNVRPFLZBZT\``VLRd\PZHVZTfHVLXLPTbVXLNR^DnVPfRNJT^fZ`VNNHZHRR^X\LTTJTPP`^Z@VPVV`TdXTTTTNTZ\P\NPPdfRfRL^\X^XZZJTL^Zr`NN^\X>l`TX`VRh\JRXJPTXVLZXV\X^PLVTN^^VPP`VTXT``RVJX\HJRJ\VXTZPX^\DNV`V:`HTJXNR\BXZ\PRbVZZbVjPV\hP^Z\JVT`LhV^\bTTRJXddZX\``X\\bN\^VPX\RXNR\\NZ\hRNT`^LXZ\bbRVT\LZNP``P^XX``Z\ZPJbHXZTVfXXTdhVZfbVTpX\TXT`Zd\l`XXTXVZhTZ^XVXVN\Z`\XdZPLTXbT\\TRP^ZNBTVLbNTLHTddT\PRZ`BP^VVTbbd^lblZ^ZhZ`\TbTNd`Jb^^V`F`V`TXZd``ZT`X`bZ\Hf\`X\^`\TVXPX`XTX^`nR^\PT\VhZ\NVTRTVVNVZZRTfV^XR\^NVXbZV\VLZVPZNTRXVN\bV^TZbb\V^VTZ`ZbTVbPR`^\XPnPR<RjRLVL\PJ^VXbV`N\^TJPfLhRThV\b^P`RLZ`RX\ZVVZPPfN`V\^PV\VbNV^Z`VVDTNZb\ZfF^VXNj@VX\ZXRL`VNZ\VLTVbTTXRN^^J^Z\^LNVL^ZbXXH\VNFRXJNXP\VZVXLRZZXVXP^RR\NXTXDd^ZTP`HR^^PJ^RT^V`bPRVfndVZRFbZN`fRTTZZPDNPTVT\VTVPPX\XJ\H\Z\HXPRVJbF\PT`ZV^L\XDZZVRNVLP`ZXRNNV^bJL^T^XRP^RLTP`XRXP`^`PPTJTXdHXL\XZR>Rd^LRXFNR^^RfNVT\Z^ZVNXR`NRN\ZRVXNbTRT`V\XV^bZNV^RRNZTL\^TR^TLdN`b\PVVFb`R\D\VV\^^XRRVZLR\XdXVTTTfPVTHPXL^JVNdL\>VTXbb\ZdFRTZTdbB\\RPLR\NZfXd^bXZRZH^TP\PVZVfVdD\VLRXJ\`R^\ZPRJN\Pj`^RTH^\NHXThbTT\`LPPTT\ZNV^\ZJZVL\NPTXTRlR`VR\Z\VRVRZ`bZZJV`TdVXZXB`\PH\XZZRDZT^VThPTbNZVf\d`PX\VHXL^bR`XXT^ZTL^bT`VZZ^VThN^FP`XRhT`RZNdZR^PdZZ^PZP\\PXdRVXdLP\^VZ^BXVVJRZV^ZJHbXPPHT\Jb\\^PH`TXH^`PNPXZVXH^ZVZ^RT\PdX^NH^\dVXRT^\NTHd^VPVX\TNXXJJJBPFTV\XbJpZ^TLJ^b\vZT^NjbTVTTV\HfZVTf\RTV\VfZ\bFNN\RdX\NT`JZ\V^HXX^TV>NPPDdJTLXVTTf^HVVZRRZVRfZTTXZXVNbZ\TVX\H^VNPTNT>^ZRN^RTN^NNT<VV\XTLjdlV^X`^H`X`ZT`HZDX\^NXPTXZVJXPZ`FfRTVN`XRN\ZNf^Z^XZTbdRh^VZXRN\TTX@NL`TF^P^NF\hPXLN^TRJ^XTVD\dJ\TZZTLXTdN\JRVVVJ\LJXZRT^^\ZP^XPPXFFVT^ZV^VLXRJRTLZVHV^PdXbVVLRbXXTTR`PVZ\RXRNPLPNb\Zb@JRFXNNZVH^N\RXVLLLVXX`X^PZNR\TXXZPLVTTR`dPlVXZ:JX\J`T\PVX\T\J\RNXXX\XVTL\VNT\PVb^P\\Z\Z`LZRfTX``DdL`LTNd\`T^Z\^XVVRRTT\bRXNVF`<`LVLRJbRV^PVHTNP`PXLR\TV`PPFN\N\PV`JZ\f\RVTT^`@XXNR^D\jHZPZFR\HTZT`VXVVTTNP\Z^ZL^V`@V\^L`ZTXPLZJVT`TRVP`JV\@PVFbNHNDXN^VXXBd`BNVNXXXP\bbZ\dRN\ZbTXRZRV^L\PH^TZRV\LXZ\FLXR\N`T^P`XT\T\VZLPZXRPRV\TRdRZPZVX\V\RTXTTVXV\\^bVJPX`\XPPX^ZPhTVbTZVVbb\\V\H`L^ZVT^^LVPV^J\XdNVRXbNZhTV^X^V`N^^XRXT^R^Z\NdL\ZVVVZbVBdV^XFPR^fZDVPZ`P^^V``\VZ\b`f^LPTZ\bN\bXdfV`RJdXNN\RdT\^XPZ\LTP^\NTnV^PV\^^XZV\fTHTHT^bN\\R^dZ`RJ``b`RNVfR\T`PPHRZ`VP^dFPPJRR\Tb`XVd`h\\^\RlRVbbZ`^hPVbhPZdd\ZVTVb\\`bX`Xd\\\P^P`T`V\^`p\\V\bNV\X^RF`\J^T^\d^TXJTJTFRX^RNTd\T\TbVXP`\ZPTJV\XVRZTPZH^XL`TPRVV^LRPHTTPRXN\dPjZVXd:dNZ\JNL\TPR\N\LTV\RNPR\RVPVTFX\Z^XTRhVLRJNT^VX\\ZZ^@VRNZbRXRLRVPXT\VRTZJ8f`XJ\ZdLJNL\LL\XJVZNJ`^ZXPbTV`PXZTVPV`bRV\X^Z`^b`ZXXLXNTbZH^^b\LXTLPD^TH^HHTNVZNXTbN\b^\TZFLbLhdhNVNdHbZ\PR\`RHXlVXNPbPTLF\PTTZfZVTPf^TR^TXPHZ@P\HTVHX^T\ZRHZ^b`XRRXTX^RRZ\XdT\ZHTVF<T^LT^TN`b`TdT\VHdVXPZTNd\Z>XPZ`XXZTV\Z`VZXTHP^`\TPRZPTXX^\XTRNRbPPLbb^N^DLd^\XXRXZJHTbbFRRN`bLXTX\V^RLVXLF`VbLVXVNZLPdR^TZdXTbXVXddX\PNPb^RVHXZZPjTHZPTTZX\L^VPVT\fRdPbVb^\bBdT`^VNRXZZ\TLPFP^dL`\^TfRZbF\TZN`XPL`^PTLF\N`XT^RXNNZLVR`ZTFTVZTPR\\ZZZXhTNT\LpbbVN\bTX`\dT\ZZTXh\ZXL^XR\RdXV`^RHXZ^XXXXTZ^ZfBZ\V`dT^P`h\\\^T^bTTNZ\^^bTXX`bP@VV^T\HXZf``\PVdhTVTXf^T^>\^NXV`ZZT^X\\HZ\RbHfZL^pZX\\DhL`bRFTZNX`TL`d`PZX^HhZXXXRPZRTZdTRVN`\\ZZ`LPbNFZPPVD`LPFZ\LP``XXXbVhdRb^b^`\PZLJhNTLXV\LZTBXPV\DfN`RTVJVb\bV`N\^TTdTVZRVTVXPfZjVZVXP`\NRNHRVZRT\N^PTXNVRR`FJJTDTZTZHZZTZ\J`^Z@XXJ\FF`B\XNTdZTZXXdfT\NRTXZRdNT^`TVZTRRVJVNdNbV`T\^LZXN>XRTb^ZZXd\VT\BR\^RX\^Z^`bPVZZbNXJZZFB^^ZZ\hNJVRfXH^XZBVJfPPRNRZ\^^:bHNd`P\^LPbRTZhZ\f`VNFRdTbT`N\^`^hVbNNLJTnPZR`PfRT@dTR^XNPZRNZP>b^RFDV\`bBn`JRRHXL`TNZRTV`VV\\^FVRNLXZ`ZZTV^RJ\N^DTLXLVHX\P`T\FFXRR\HTVLTR^JVTPZB\B\JfTLXVZbX^Rdb\BfPTTNPPLNVbTL`VXT\ZZdV^LRVZ`PNXTN`XVN>^L>fB\VP\VP^ZVP\`HZZRL`NXJd`P^VL^NFb\\LJRb^X\Pb\ZXXLV`RNX\\``LJR\HR^VX`RLZJbPV\^RRFVT^ZJJT^\ZXZbbPXTZf^fZJdXP`JZT\T^XPVZR^F\J\^P^HRZdXV\V`TZVTTLdDb^XVXTXbRTP`XTZbPJ`^`Vj^\@PVXTXLdLNXJ`bRX`\XNj\RZfTZVZN^DTZR`XbT^PVZLhRHTXdXbT\bNZjPRTRXbNR`RJRR^`NVTPRVRfPXbR^RdTdjXPVH^dLHXhP^VdZ\R:p^bTXb^`HDZJbbjR\`T`\NZV^TRTXV\Nb`\XZ`NXFZ\PV\dP^`TXfN^VbXHTRVPfTZX`HXbTdL`XLP\LTZV\^RfLZTdXXT\^VX`RdXVPRV^\NZXP\XLJ`VZV\R\Vf`PLVVDh`TTR8VL\J^B`b\RbTZ^d^fl\nZT\dXNbP\hbTdNTRTVb\RZ`XV^\^RVXLTZ\PRVJ^\bZ`^^^Z^VfNdbTjZX^HPhRZfZbffHZddV`RZNRdVRRZZbTZLPXZN\P`FV^HTTV\ZL^VbXX^ZPbTXJ`JRTXdbZPNLHL^VNXRP`RZRX^ZdN`PTRVT^`NX^ZX\NfLZNfRL^bJV`X`T`Z\bjjPR^dbX`PTV`dHV\NbVPVVXPZdZjZ\R>Z`ZHpVbV@X^PRXVPX\HZlLbTb`XVZNV\RbFdBTRPVTT^XbV^`DX\R\PTVR\`ZZXbXFPL`NRZfN\NPZDNZbFRZP`^`X\LT\XVT^FXVTZ\R\\VJjPTPLLZN\\hL`RdXXLL^PPZZV^^`VJ\ZZZb^ZXVVbZVZPZXLRZRXZ`RPR^ZVRPbZL^XXNRJ^TR`XZf`RT`RH^P`RHN``LXXFdPJTH``\`LdR\TZNZbVRnRfRXZXVP\VJfTPTP\FTfTXdT\V`T\RfN\NHV\XNHh@fPbX^VPbXTdb\XNVRV\dPVTPVRRPVTVXRVZP\BXVVZXZJVPJ^\BNRXNVPH\PjTXJHdbX`TfV`RZTPPfLLPhLdP\RNXVdZZ\^bXVF`JPXb`BR`VTJDXbVZJfH^NVNZdVVV^>LXXZ`^RLXR`R`^dXdLX\bFdJRVL^PZ^b^B\XRNNZb\^T^dD\RX`NZZ`PnTbRNFbZbVdZNZVNTdbZTbRRXZT\RLXX`X`PhTNVHdX`T\\^LbX\dTbRR\XP`VTXN\NZVLP^HV^`lV`P`VhZTbZXVR\J^`P\V^^TXRXNXRX\fRjR^^\ZbVRNT`\ZV\ZdVPdNXDJVTZ`ZX\VfZX`P`R\TXR`P\XX^LTN`VfRT\`TRTbJPP\Zd^TVp\fnZ`XdjV^`XTRjh^^XZ^\RZ`ZXP\NfVZXDHLX\P^^R``H^bP\Td^VNZR`VLf^hPZZVV\X\BZVXV`V\\bbJVXZ\\`TXP\LTNXRVFb^L^XNZp\VZ`^HVN`D`RLRVFZPR`fNZJ\`NbPbVVTVRXZNTHPXTJZP`\ZRDFZ\TXTZVT\h^NN`^ZPLf\Z^N\fJ`PNT`ZN^VRNJV\X\VFZHLV^PNJZPXZ^Z^`RTPPbPdR^P\TZ`JRJlJHjJ`TVLVTVHTVDBP`NTFVLVLRRP^ZXLZXJPNd^fTTbTVZ\`PPZTN\XfXXVFRTVRTf`NRXVNbPX\N\:bZNZj^ZlLXVX\VR`RfVPVVXJD^bJZTVBbXfZJZVVX`ZJN`P\PPVhPLF\NVXZHRF`RF\\NTVDTVTJRX^JL^\VX\``RVVRTZPf^J`NVTRRRn\Z`^XXTNNFT`ZDTPNBPT\TPZVZT<\NNVTTNbX^VbH`Z^VPLdZP\`RRNNXdVV^P\dV^\PRfJ`H\VbdN\JXFHPR^j\`PTZF^ZXV^`TX`RZLRPVVXFX@fLbNTTXdNDRbFPLJTPT`T\BP`R^TZ\^bTV^ZR\Z^bZTXFRVTPTRPTVd^V^V^FVLR\VR\RVVN\VbX^T\RV^`NVJp\dVRVV`ZXN^P``d\LfRNVXVTbLdT`R``@hTLVVLXVb^LTJZRX\ZTNTZhPdZ^JTbLZdNfJ^TNNZdTV^\XThPZVTRZZVXRXd\X\`TXTNVbVP^`NXJbXJTfR`\TTZVXXN`bVXZjd`ZZZT^ZZX^^FLVTf`LhR^^ZbZJX`XJN`hJ^ZLbPTVHBZdP^X`LRVVZJ`TT\^PNPH\H\TZLLbZ\RFVb^XX^VVZPXFXHHbRVPTbX\R`^ddNhTZfXX^bdF`^`fTVb`b``T\`d\\VdZRVXTd`TZ`^`Nb^\Zb`V\LLf^\DbhRTJ`b\TRJ^RNVZRTLX^VXTPXT\PV\ZTFR^RdPfN^bNXZNHXT^VPVJZV`XhLXZZd`\^^BXXZXbVPTTH`V^Z`LLVX^XRD\\XVR`PN\VfPTPbX^NRV\LJRRTRTZ^JX`^^ZpR`V\VTPVL\VRVV^VR^\\`HVRNLX^PbbRfTP\JR\TLPbZTJXZ^FTVdPLX`VVV^RNPT`PPTVTNXZVP\R``Pb\FPVd^JTXPR`\h\X^V\T>P^rNN`\XVbXP`PdFZ`\LRTPNR\TLX\NXJVTXRZVRhR`NVbL\fLLHXTl^TVTTT\J@ZLRNVdL`Z\bXZVH^\XVPXRRL\\ZTVTHV`PRXLXVZVNVTR`RVT>^fJ\\DXdVZPdVFfJbZ^Td@^ZXVXZJ^TPbTHDVFNPFZR\XT\XPTRRXVjX`XFPT``VF^XTZNT\2H\VPTVTX^TNTbVVTVRJ`TZ`XRTLVZXJfR\BdNLXXP\NRTRFZ`JZ\JV^T\JRPVVT^N`TTXT`^F`Rd@dXPPNT`\^VLPHTZJbRTR^HNP\HVNZTbVjZDPh\XRR^`RNbVRZN\bPbXNdZPfT\ZVZXTJ`ZTF`PZV^PR^\ZZXVtVNZF`VZHnPLR`Td^Z<\ZPHV\XVNbZZTbZX\ZZVZhPhHdTPPZXRPP^R\\\PVlRTff\bXRR\fZXT\^fP:T\^VZXZRXdZZ\J^`XRfXR^XTR\HhZfbdPbZZTVfhXRPjFdfRXZTVZTNX^^PTb\LhRRVRFbRV`X^^`\bRfFRZ\Z^`T^T^dZ\h^F`dZ\R@V`TVVZhZ^\ZN^DfT^V\HTLbTTNVPXVNd`bX^\Z\pVbPb`Z\\VX\RV^T\d``XblTX`b^PX^RVNVVXTV^XLZXN\TXXPR^\PVTVX^LTL^Z^RTfTXZPZNVBXZVlRXbdHV^TPbTPXTXXD\TRb^RTbR@Z^RNTP`dRJ^VJVR^JVXBXVVZ@\^VXVPPTRZTLR^Nd^VR\PNZ@VdbXDVVTPTZTZnX\>XR\RTL^Z\PRRPTN\NRbTT\\PXVHPLNVRH^bNT\VRNHh`N^NZPTXdNFZ^LTNVVPXTNXbVPRVJT^NfRLJZNVTD^VJVXJHPXVVZHZZN\RfN\^8d^\RZ`^XXVP\R`bN\TXHXTP\LZFVXfFb<XPRLPH^^PLZXN`XFLT`XNVJVLjbRJRhVNRbNTXT^PNXP`NTFVVHZ^VP^N^R^RT^ZR^VfddRRRJPTZTLbbXJX\R`TR\RX`NTNT``XLXXXN\B^Rf4NZPDX^bF\XPZNLTRTZ\VfFPRT`bR\fVP`PN^PX^^VbP^R\VD\BbLNLV\VV`^`^\^hNbZRVXR\XRPNT\LVXX8TdV^T\X`V\TRV\NRNXPZNTTRZXRHZF\Z\bR`PVRVPbVX\`NLfJVNJXLL`J@\`\fRNPhZZZbHXbfZL^\JbR^X`LRXTTlZ\X\PXJZT\RTV^PhV\FV^V\NX^^PXPV\ZZTVVP^\fhP\T\\VXRPLbX\^fPRLZZdP^RPZJ\VbPXBVLVT\XL^L`ZTV\ZF^bVR`Jf\JPNTH\FTR>ZRZXTVZRT\^PbVZNTPRhXTVXVT`^HXXTZJXXXV``TP^HfTD^T`n\F`\PTXRfh`dRXdPf`^\J^RBdJR^T`ZnR^DP`fRbV`ZR`^\VdPLRTV`TbbTVZRVfXX`ZZ^^VRPTZ<TZ^R\PRV\L^\\bV\^Xf\Ld^R^ZdNVXTVdR@T\X^NPXVZ:ZVN^\ZN^T>\V`bXdd^dVZdPVTX\jfTblZV\d^Z^X^PPT\HXjZVXTZ`XT^bb\dPFZRdTLd\`PXRV^jfZVP\J\`^P^T\XVPnNRbbdbVbLbVNVXZVbdX^PfT^ZfVZZjLTZd^ZjVVT\VP\`\XVTd\Z\\V^XXVT<^P\X@h^hd^ZZ`bT`TRbNZNR\ZTZ`PfR`XZ^\\jVTLNVVRZRLTJNVZV\ZX`JVH`PLZ\J`@Z`^PNXXP^`PT^dfdX^RP\^NZbLPZRPLLZPHXJVT^`L^JFZPZTX\TPPP\TN`VT^LrXNNfXd`ZJ>X`B\LVX`TLFT\R^ZLZfV`\VTZdHRVVXbZXbPLVV`T^TdVRZVTPPdXJPPTXV`JNXRNZVT,RHTRN`\`XZHRR\JN\`XLVR\PP`XV`FPVT\dRNRXN^JZRR`PRfRZZV>\j``T\X`L^XTV^b^RXbZ^XRNT\\P^`TZH\^LDRdbfVXbLX`X`PXfb`bZXXXXN`\TX\TTNT`FDTfL^^\^Z8TZT\dTPPdPNfd`b\X`RP^`b@\Rd`\^JRPLXXfXT^DdR^b\ddVZP^`ZFfT`TZ`PZRVfXVXNbPF^BXZVZPR\LbTRNLT\TNP^XZTfTZ`bhTZb\RZbXPHTf\RZ\`VVVX^LFXRZfXVR^bR^RZXTZ`RXLVTZ^L`^TX`XPfZ\\V`h^VdPR\l^Z\XHbXbPfdLP\LR\\\HZTZVh\R^XLXRR f`ZfX\bV`ZZXfVVVX\d`V`RVZZXbRX`\`LbVVTZ^b\``LbZRDZ`\Z\ZNh\ZVZT^T`R`RjTZ`XV^`bPZRfVXTXXZbRHRDXdZN\ZPNXF^TX\fHN\`\XVP\PL`PTPZNb\6V^dRPLNnX^fV\bTTVXXXXVNT^>`\V\^\Z`^PBXVZXXbT`XhfbXNZX`H`bRNb\LdPbJXXRFVDJN`jVfZdZZPNX^VZZVbXdTNLV^NDTVTTVVXN`X^PdPFbVVBTLV\\RpRZZ\ZbDVVTTRP^VPJVJ\RJJLfXfXR^TV\T\X\TX\\VFRF\Zb`PJXPJb>NV\J^HTN^bR^XRT<T^\fRhTTZV^RLZNVZ\RXVX\HLJVTVZXbXTNNXF^h\\^FTPbPXTT\DZ^NT^TFZTVbXVLPLZZFRRN\T`ZLVHNZVXbDFZPXRTPZ@`T\NVDVP\<XRT\bHXXZVRT`LL`XZTFNZZPLZXLZJPH\\PXVPV^@`TJVLNRDZ<^J\:RPTRTPXX\f^\V`HXZV\XTVRZ`fBjP\ZbRXHPHbH\hNXX^TXbV^JdR\\RTZP^bL\TZTLbVPXPH\JTfXN`XV^^^ZbR\VjV^Z`bJZdNXTPPVVFXTJdTXPTV^RT\RZ`TRPLTXNLLdVP^fLXJXRdVVVR\\VNPhZV`NTdRVRXVPRVRZVZZZTJXTXZZTXXFTHL`VRZXX\ZDRTNZVJbfHZb\`XRZVXNRJ\ZJTNJPTZP`^TNNJV^X^`\`bTPV\^HXRRTJ\fJR`TVNLZXXVNBPP\JXXP^R`VRJXXXJX\\FVLRPL\JbfRZN`bZ`^FV^JL^\PTV^\RPh\T\V^TRVT\F<R^bF^R`Vd^^X`NPLVNRPN^`XXZX`\XXZ\XN`f^VnVTZPL\jNRXRTVbZVRhVFX\JJ\bVPbPR^RVPTNZPPP^R`VX^\P\^VXPPdRJdV^dRVJZPVNZ\\\N\XVJf`TXRRVNRX\X\ZZ\L`f^NZ\\bLRPRZVbRVP`V^dT`N\XRVVPRZ\`D\dd`hnrZbTf\VhZdPPZ\V`fR^XJ^^dTPXRfRVJfbZ`XVfd`RF`TXXb\\Pb^dPbZR\dVTdR`X@V\TZR`bRfNRP\VR`ZXXXTN`VJH^T`8`^\VhRTbZ`\bfZVT^RNdhTfRBjHVXVR\TfVLTXPRXZPTPBTNdDRTTbXNPHXZZXV\\^RT\`R\nNVLjNZLJfPDPPNXXhdB\RZd`DZTNTX\RR`TVLRV`ZXhPf^XbVRZFdZDL`^:dJ\JNNJRbDhLZ^BDZP`V\PVHbRHT\Pf\HDPNXZT`TfPHNRTP^fbZZVRVVLX\XXNZTVj\ZLVbXXP`fVfh\TPdNR`VLR\lTTdVP\VRVLbPNfNbRTJJ`Z`RXd^\TP`NRX`f^JDVFV^FNNXbT\X^\P`HTT\\RRBPNRVNPXP^VHXXZD`V`ZJj\T`V^ZVV`PD^P\lXLJ`bZ\RFXT`Z\LTNR\hLPXLRdVTXTXNR\VNVZVRLJdTNbVNTPZZhNbVTNT\\FbNJfZPPX`NLXNVV^\ZRNHVbNTbRL^\RLdZPV\dRb^PRVPHHVRhJR`\N^ZZ\NZjP`P^VZ\RZdRTXdV`NRRXhL`T\V\XNLTVNbZZXLVXTTHJFTZPPN\HR\XfDf``RVRfTT\NRZ\F`bJZZXPRRZbRVNNZRl^LVZJZFdJXbLV\\PXhV`P`LZX\`^XVTVZN\^`PTVXTbf`R`Hdbd^Z^dXXnVZZVV\TZf>^TXZNd\PfhBXj`X\Tb^HX`R\XR`P^Vd\XZ\P\V\^LZN\jL`TRbPVdNPXXLbVTR\^bR\^^T^ZVTPX\Nd<PZ`ZXVZZT^RNTXL\TfFdT\VNb\HZP^XBX`LZdLP\\VV\VRZ^RHT^\ZRLR`TNVHfJ^^LR\PLLZlZXV\\jZbRXVjV@L\Z\VJVXZNVZPVb^ZX\`ZZ^\\bj\\XV`XfZ\TPJNRRRTPZXZ\`XP^`VhLN\VhTR Z\h`P\ZRZXZNbhPXZ`Z`TXdVPTbLLV<RHR@^\PTFZfN\LhDJ^fVT@XXL^VNTBX`R`\VPFVX^T`LNVhHVZ\NJHbJVJHN\P\LNLbXNRdXhTVJ\`V\P`JNT`TXbZB`bHLdJ\VpD^PVP^\``VTLVL^RFN\\ZXNVJbZNZZZTb>\ZTZPJHnR^PPXZXTTXfTVRRZXbN\NjPVX\\RX^TPdRTZNVPJNR`dXhTVPVXHNV^X^XZTfRXXbXXLdNNX\fRNZZfTHjRR\RdXXZ\ZHJXnTX^\PRPZ\^`HLbJVRXN\ZPRRL^NR\VbVPZ^\TXTFTP`^ZZLVbPTPVPLZ^RPb\VV``V^dZPZZ\P^\T\^LVLJZ``hRXXLZJb^NZ^flNPL^\TVZ\TTLVRR@\PTFTTZ^JPXVTXXfJR\XV^\bbDbPNRVbHZXLVZNP\`RJZVThVRJX^PTLZPPVLFN^XJBd`LVTPV\RVNTZZXH^^J`LX6hPV`\PLXPJ`J>^RJRLLVFNHbJVXFVZTX\XFXVPT^XRR\XZFb^XTVdVZHVXT`NZbVVX`PVdTT\XXRb\PVP`TH^b\bd\@JDVV^TfZT\DdHV\^NZhJX@RPXZHPZJF\\XN`LRPXbfT^VZR\bHVX`bVLR`XZVZZJXPXdH^Z`\dN`JP`P\^``R^JTH^^VJPXLNRfZV\VTjZT`T\b`ZZZdT\NZ`BZVR^R`Vl\flZfV\\RdNPZlHfXdXdVVJXdRX^^Zd\VR``VXXPbV^ZXT`XNVP^XJZV\L\\LVZ``ZT\\^fRVXX^\TbJ^^RVXZ^ZLbNbX\d`VXVfHFRZdh`Lf^\\VT\l^VPZb^j`\`b`^^R^\lZXZXXXRZ^ZLDP`dLZbbVT^VNh^XZbd^NVXLTPX^LNPTZ``Zf^NhLXfTXbP^\V\\jTT^XXXLLZRNdFRP`VJPZ\\LXTZXPNRZBV`TTNZV\HRhD`FRPNNRNNTPP^TFZPXPZTVJTP^RVRTZFXTPXVfNVbVN^VTTRTjVZ^\R\VVXX\\TRZPN^PJRVZNlVZV`Nb8Vb^hJLVb`XL`@VTXR\ZZ\`TFPLb^Z^^V^XZRVVTNZXXPNTJVPTVbL<\PZNVVP\TXXZXbVLRXP^PVXd`ZN`\J^^X`XVdRV\FPDbbd\\THV`Z\`V^TPDXNJTR`HZNR\X`N\NXPVdN\N\lLVXR\TV`FJNZ`T:^RXZPJ`l^bXXX\FTD\hHbTP``VVPRNJRZbLPb\TRRZfZXXXZV\RdfXV\PP\`ZJXXbXRXFRNfbHXHX\dTXbRhR`^LVZfLZJZRPNXZTbb\PPPXTH`LZVX\VRR^`^VbTX\V^JNZZVXHVTTPXNRVJT^PZPV\TN^`V\hFlPXRddT,\J^PfVXXZV`ZbTfZ\\TX\LRJVZPTPXnNXT`VVV\XJN^T\\^X`H\^ZNT\PHRXbZ`\^XP\LZXVf^PXR`^LNX\\VXRdXPd\RR\b^TVJ\TRXfDhLXD\\hJPTVXR^PbLZZZX@VV\TjdJ^RdLNnNbLPZZXLpXLRVR`VHdR\V^TVZbdRRZXV^X\XX`d\Xb`H\VV\`T\Xb^NLTTZR^\NZ\J`ZX`Db^fVjTRNbTf^NV`Z\XPTNZbX`^fZVV^^RTN\^^PX^XZ^TXTX\RVHdNZZJ`RRNJVZX\b`\R^\Td\PPV@`PV\h\HXJTPXXZdbXRPVZL\dThZ^ZZh^\Z^P^X^\bVZP`ZZN\^Pfd\NX^fXVbV^ZZT^\ZRRXTPLVZZdH`VTTTTTPFTBTN^L\\RNV^VTp`RXVdPdV`VRbfVVZZXbPXRHfXH\PV`VTV\ZVRRTHV\PHT\LZVNbXTPJLNTZJbPRPhL\RLXVVN\NLR`RX`R`VFL^XdHZV^T^bL\THRPbNT\b^bTRX\bLTNX6TXVPNfV^T^`\PX^V\VV\VbL^HfN\JVbXNTNVPX^PTDZVTP`NVXT\HbXVRRPb`dF\XfV^TXTRNVN\XZDNLZ^RZVX\V\TNdPZPTXfVXTbPP`PTTN\pRN\PZ^JVTZRTVTVX^P`RVTJZNHNbZFVR^^VPRXXDTJRRVVNVNRHR@^LPJT\V`bLJRFXP^\NPFPN^VnX\ZTRhNJHdXbfh^RLJ`J@N^NLRRNddhTVVJNZVV\ZVR\H^LZRBXX^fbVJZTL^HVTPVP\LVVNT`L\VPNZTVNVZLTX^R\VR`R^ZRRX\XP^LVV>T\TV^TVVXR`LNRPZNX^XV\VVTRX^JLT^XXL\JTZTPVZXRX`R^RT\XZLRPb\`XJ`VDXLT\RZRRPX\ZT`XHXTRZ\V^RVFbTTPdbLL`fZZTLR^HVZdZHRX\bZZP\Z\LXN\RR\\V^\RfXX^TZVLf`VRFV\F^XPX`jJVfXRThVVPlTXf`ZLXXN`L\ZRdVJFZXJ`TfZbN`L^hdbTb\ZP^^Xb^\bNVRXPZHVVVZXXNVlTLX\F\ZbPd\`JbbZJfRXH\`X^bTVFPdjLVf^ZTX^TXHV\PXVXR^P\HZ^\TPV\VdPRVZR^VTZ^XZVV\LXTZT^XX\^X^`HRNZ^XNN^`XPNXXRh\XfZ^lj\ffbZ\X\^`dNfNXDR`DhRVlTX`TN\\\^R^RZPZ\\XVVRdTZPVTTVRjdRbXZVL`bjpbbNZ`TVR\NX\N\JbRbRbXXXZTjh\X\^`\XZ^VjZ^bV^RXRNXXbPVP^HLdZVFTNPTVXV^PZZX\VVPbV^\JNTRX\RXP>VZXLXPVPbPXPTXN^PVVZ^Nb^Z^^Vb^NHRVLLVPVVZNTT^V`VjbXbXVR`JRRRf\TLZTJNRHRVP^X^VdT\TfTXV\ZN^dPbZXPjVZTR\bbTNH`N\jRF@TLZX\JV^XPVH\\PbZT\TbTZT^XP`PLLVLRRRd\VXRdVHBJfJTNh^T@XRJfVZJTVh`HXVRdP`V\PXLVVbPNX^XH\PZTVPTVPPhX^T\`VXFV\XZ^XRZb`TdN^NbL^DNVDbPPf`Z\V\VPLZX\TH^`b\JdNVZRN\JT`VTNVNPXJNP^bdRRXZLVRH^NLbJZZNLXZLPP^ZdNXfhX`\DLVdTH^lNP^RXV\PZdV^VXBTRZVJ`NFNPZRTXXJN``^bPZV^Z^`RXRP^VVZXDVZ\`P\\T\NPV\PbPF`PR`HZ^TZbPT^\ZPbX\FRXRXRZZ\TFXf^ZLV^L`H`Z\ZBPPT`XRVTPLLL^XrJ\F\^T`RPVVZ`^b\\\bbfNVJRTVXJ\j^ZP`X\V^\TT\VJVJRX\ZVX\`TTF\dPZbbR`\`ZRjVdPZ`<`dZXP\Z^RP\X`TRZhVTZTb^Zf^DXX\\Z^TLVjJR`^XR\Xd^Rh\RRd^VNfZVDT\VZZTXZXV`L^hHbP`TZVPhVR\dXPR\\\lbFTZZdTXVVNBX\VXZP`RRXRdZd^\dJbZZ\X\P`RPTbPbFPdPZRPXXVPZ\VlThlZnbdZd^^^Z^XZh\P^`ZZR``R^h^X`XRX\P\VVdZ^Z\bTJ^dNNVZ`dZVZ^R^NhhVdVRTH\XVP@`VXXHVXPZJVHhR^L`ZTbZ`\NbTXP^ZfPPT^\ZfTNV\bRXVXX^TbN``XP\RRTbJZLTTXPXFPR^bTZPPZPTPLF`\RNLZZbVT^ZP\N\LTXXRJPVHVPdTdZPLXR^X\XRVbT^\RPbXTTbHfTXVZP^TfHTTXP\VXXTLZP^R\XRTXNZXLNZXfLDRVJ@TFPRXNfPN^JVZRRVBZ\VFb`HFV`fV\L\VFV\ZZTnVX\bZJVTPlZ`XR\RHN^^jZX`^JJH`bTT`XTbDTV`TXVBZ\XPV^PTXPXZTVHZJPVXRXJLNPdFXTTT\VH`jJT^ZTXH\^\d@XHZhHhL\TLPRZRNTRVRPPLddXZXRTV`XLVZT``hNR`NXdL\XVPVPNZNVJZXN`PPR`TR\`V\XTDFNZ`\ZFXLX:VTHbNjX`TJ`TTZ`TXRZL`VbF\RbP`ZZ`\RLdNTBVHFTXL\&R^TXLTdRLb\XN^TT\Z\ZVTXBPPRdZXT\\f^XbVNT^PXVXXVZfXb\NPV\LPVLTX`\TRZPRHTZT\TV\\\V\\Z`TZLRTVJHT\NX^ZZRZXR\LbVb\TDZ\bZNRZLXjhbHP\HXVLTZb\Z`JVfRZZTXRfV\fP`^NlVRdVdVbXRXPZLLVXVXV\FT`PHPVP\^bXZH\\V^LT\VTRV^PVbZV`T`RXXL`X\\VTTTXR`NRbV\\RDPN`LX^TV`RVZNZXRXHRXNJZ\L`JXZ`JP`P^R^FRVNVP\PVBTJ^TX^NZTZJLRX<d^PZRd`TVPdVPRZb\dV\R\X^JT^^XJfDXLRP\f\\\\ZNfXZZVf^TRbTjV^jj\fRLNXRVNVXV^\VLVR^TN\hHT\h^bP^N^NZXVZ^P\P^VhPJh\fPR`\d\bRXdXXVbbPZZNRTZ^^P^L\\ZHVbNZ\`R^HVX^XLdX^fX`^ZdX^b\RVVXTZZbfNXRbPVJV^dTVJ^PXXVX\L\PTRbNRZF`PTVbZZ^NR`NV``\TBh\``PbZXVZb^XZNTLPVPXb\Z^LTLTb\XXPL`X\THXhX\VXZbPPXZ\\HPPdR^TVZXX\dX^bLXZXfX`NZ`ZP^FTRZLRX<dbRXPPHRB`VZV`^PVZ^PXHNjPZZX\T^Zb@\RR^f\H`HbfVTNR\ZRRT^VXZTdTTPXZX\HP^bThTPRPT^ZTVHXd`LR\ZfTTNTbXTVd\R\TR^ZXd\dbXLLJLJdXNZXbTX\dL\ZfRVRNLTD`\VL`VXX\LNN\^NN`\VLRHfXL^L^LRRZZ\LTPZRTfVTVTbBNjXPfRZX\ZL^Vbb@V\N^VRPTdNXT^PHf`D\LDZHZP^RTXb^RVNLXX`HJ^L\TJXRRVVTZDXVRZP`bPXRTNV6XVl\bXTRbTRTT\hZZ\VR^XRTfXThbZFR\VX\^Z\XPdTHRXTDT\`ZZbXXVVXNP\T^T\NbN\LPXb^RbTXP\JN\\dPRTVLPXNbXVXP^TbTJPdX`PZXZL\\PX^^PfTdLRbT\Z^\RTbdN\TP^b\`^ZdJTnXVZV^^XfVdZX`fN^TZbVdbX`RPZXN\dNbXP\fXV\bR^TPPV`X^`VXN\NJFVX`ZZ\P`XXTjNV\RZPfXfjVV`NPXbLZfdVXjZbTV`T`VfR\VZP\V\L\T\VB`hT^b`NZ\XTLXX`Zdh^V\^VP\dTRX``Tf\ZdZ^ZRbP^TbNN^fJT\LZX^bR^VTPVXR`\VR`^bbRbZZRV`TRV\FP^^PVTRZXVV<Vf\DRV`TN\bLXdJTR\`\HL`R\T^X`T^`RRT\ZPNRRTVP^LVdPLNNPLLTHNXLTVdZFXF\PLXP^XXFPbXVTRXL`ZPX`VHFZbDTXZbd`LZHbZNVTNDR`H\NRVTHPZVZTN^T^RZNRJP`VVbZ^VbZJ^NR^V^RTNTV\XXVXHVLRXPR\LNPTVR^`VTRR`bLVVLfVfdRRT^^XNjPRLRZZVX\RXT^`VZPRHXbX\LN`RXXTTLVZNVPdR^TN\T`fXZP^ZPVXdZN\@X\RVZNPlNh``\bRTXZVZPXZdTPTTdVVXNT^LZVVVN^\LVVRRB^b\F`FRTNJ\TPX\LVXNJVXTHdd`TZPTRVPF`XHVPXZJJVbTXX\XV`^XLbXP\P\RLXbZPJT^FVVJNXZTN^LTXJVVX\RNTV\TLZZ^TRJNZ\JZZZRT`JPLXLP\`ZVTZV`NPPNZ\R`\Dhd\X`TNZ^dRR^PNPPPRT`PXVRNd`FV^R`TXTZ`V\P\R\`TZVZZ^fRF>VTFLR\Tf\V`X`XZNLVRVb`XXNXVZVLZRP`XT`XNVNZZZRbXTZN^\XTLPdZJ`Vf\NdLRL`ZbX\VRX^PLX^VdPZTLZVX^PHXNNZ\PT`LT\Rh\VTPXPRhT\ZN\Z\F^\R\dXZ`f`^fVF`XVRNRJ^RXJJ`d`\XXTTLXRZb\bLVV`P^`LVZVHXPTd^LPHVNX`TPVNl^Z\VHbbJ^FZVTRRJb<LV`TNL\RF\\`<TTT\RTZPRfXNRVPHXFHR\DbNbXdNBJXfNNj`^bdd^ZPfbbPf^VVfZZZN\P`ZRRTZ^VDPXNVXZH^^VZ^\XTFX^XVPTLdZXTT\PhVXfV\VfdbVVdXLhRVR^RL\T\VdhbT\LTj^RN\^Zb\\R^X^Z`ZVZJb^X@NXNVbhjZHdXRZHbPR\dZRVX`JjTVVRTNZV\TR\TVX^ZXVZdTVVZJP`^ZfRXXPJ^R\bXRTNLVHfRVTTTVXZb\^PXT`\RfNVXPTJNRXR^PL\VVL`bdXVVJVZPdVXV^`XTVRXfLX^^`lVTPT\\Z^Z^TZbPTNZZ\VLL\^X\VTlb^RdXJjR\Tb`\ZVdVRN`^THVbZ\bNRPLRTZ^d\fRRZRNVX^bV\VZZPLZV`NFTVVPPfLZRVb``dZV^^LZRV`RPf\PJFTXV`LbJZPXTHTZTT^VX`^`TNLTJ`XTTZVTN\ZN\JHR```XXHLZT\bf\V^LVZTVLJ\PPV^\VVPdVTHbNZ\ZJd^^JXRRXL^`TXTV\Z\XXhRXX`V^\LZRPXZVLVXVVJP\ZNZR`TfJTVZ^NVXZZRRXZX\bPT``N^XhNTVNR^ZZVHHVPXPTZ\F\VX`ZdV^@X\TRZTV^LN^b\Z`RT^V^b`jZZ^TZRhZfH`^RLTRZVfTPN`VTLRNZX^fV^\VRZN\X\J^RTJdXTRXZT^Z`HfRRd\Phd^L\V^hRXZLjVX`RNLL``bRV>ZPP^\^V\fNP`V`R`\blZZZ`VNZZ`T`^`V\XdbV\fJ\h\Z^T\`VR``VJN\PPZbBNbh\TTTVXX^BVNZRPXZZV`\^`RVX\RVLhV`ZbZRVb^RVPVZ`XXNLdZJPZRJZ^\NRRNZZ`VT\^hZFXZXL^VZLNdX`RTRhTL\hfZbbDVdPLdfbTLT^^VVV^NZBHBZFV\ZHZZ^XRpH\Z@`ZXXd`PN^\RX\`Rhbf\P^fLdbNZ^Z@b\@ZdV\N`XR^PdP\^RhR\^XX`RVXVZR^TTT\PRZZRX\RH^LLBDZ>VL`T\Nf\ZXJVJ^VZVXV\X`NDFTVTdJJZXV^J\RJ`:fH^PfdP^NVZZTJ`VXZPVVlbTP`HV\NT@TdbBZTFP^TZdLJZVVRV`L\Tb`Z\fP`JLnHHRnN\^FbVPf^`JVPXTZXVLRRZ^ZLdRLbJXPRZLXH^L^\PVV^J\PN^NJ\\dNDJ^B`Z^XlZbdT\NTdRRP\HZP^X`\Z\`TFVXZd^\TZVVdRVbVbT\^dLRXfR^H^XVRJPNRP\R\\D^N\ZNXdP^JZJ^ZLTTVfLNVXXdLN@TXT^FP^NZVVdXZRT\\JbVDPbfRRFRTZZTV\PXbXTPJPZXJPXVHZVPV\ZZ\XFR@RPNTbTTRVRL\VNRRTdX^X\VVVPVVbRR\Z\Z^PdRXPDVZ`XLT@NPJ`VRdXZVPRNVbDLLTN@ZP\V\dVVXXLHTHLLX`\ZPPF\LVZFPZ^P``V`\TV^LTZRZXTPVhZ\\Z\PZLR^FXb^VZJT\RNXZNV`HB\`\L^XdRV\`R\RNXTVX:`PTV\NZZRdVdZVPZLRV^jXX^\ZTb\ZZPnRX^Z\V\N\TXRRVTN`XPRRZXNHTVPXZNXT`HRP^XXZRfVRNZ`VX\ZdbPRNZTTfVb^fJLl\bR\^Nhd`bNbNV`^f\ZjLXFTLdPXRZV\`\^R^VPXZ`^PPPXXZVPbVNXXZTV^PX\^VNZRVNfNJfLdVXJNh\^T\ZZbX`Rf^FL``^XRPPBR\^ZTJTJXVR^ZVPLRTXPX`VhX`blj^fdZZ`\^bRdZ`^\VbhbNb^P`^^h`V\hZTD\fP\Z``ZjRdZNNR^b`PPHXlN\NVVPbNbRZLVXZRf^PbXX`Xb\VPXPX^PVVVbPXZbNZPbDZH\TXRZV`RRRNV\N\ZRTLZTL\ZPL\Hd\TZLRf^LVbZV\FH\VVPR^`XVZ\LdfN^D^RX\P^VLZFZ^`XTRJZ^NbHdH\HZVPdZZ\`XR^dX^`fRZXZZTP`TNJXZXRddTVTZXB\^RNZdXP`@RTRbLLXVHZXVJFTD\nN^dPV\XFXT\\bRVZVRVXPT^^\RXPXbVbXVZNLJFL`ZTRRRHX\TXVVVTP`NZNXd\`VPJRPXX\\^LXXPXF^NT`NXTZHVTVTLZPVZJ\\RPbP`\`F^^TFNRPFXH`DPZfLP\ZRP^FbVP^NV\HRf^JVVfDVnRT\XPJX^XTPRT^NLRPN^X`NV^ZP\VZPB`XTZNXJP^@V^^T^\TVP\VZPZZLFVNXHjXXDHPZZRVPVVV`PdRR\ZTRVTPfTTvXVXRPRHb\VRHRZXRbX^FZT`VT`JTVPXNZNbT`VRPX`NHVPPX\VTR`XPbXVVP^ZXVZTX:ZTfNRZ`RNTRbTV\RV`VTVdZdZ\VT\XLdZX`\XZPH^PV`PXZdTV`R\P\NZNHTRP\bXRJN``XLPVZP\PVNPdbfXRX`V^PbV`\`TVZP^\NRZZ^TdRHT^ZNZRR\ZZdbXd^V^RTbb`\dPV^fbTVZ^NXbP\V`VXd^PNRdVVX^`dXVTNZ\f^T\dR`XZT\ZZV\`ND\\LbP\LVXPRVLR^RXXTNbN\V\NRT^JR^TbTTVXLFPRZVbX\\^VZZNVVXVZRN`T^^PNRLdRRTd@ZJ^dTZ`^\\b\XXJhP`JXZ\\P``^VZLT\HLZR^VX^X^\^RXPJXZNRRZZNPT\^ZfVRTd`XNPTNbdXX\Pf\R\VZ^\PZRRfPVVHZTRbHXNPXZ^PTLFR^ZhTZFHRd^LPT`NVXT^ZPbN^^ZR^BRRbPV^JZ\JRZVdTRB\^fRdLPbXdN\dTRV\ZLNb\TXTlVHbbBdVRTNbNNVRP`XTTJfV`X^PF`XNPZ^JN^hTR`Z`R^jN^RRX\PV\PZ^\`fZL^TXNNR\RVX`NVVTZhFZ`vRLh^b`Z`LPXPTTRNPRbTdJTXfPLVVlRZXTTVfJV^NNXZ\Z:BT^\TXJL`PdNVLbdRD\bV\\fV`JRVZRHP^\V\T^ZV`R\T^FZTTX\hNR^R`LF\ZZJJHZ\LRNTZTRXRLPPbVLN`Z`XNV`\^`bRX`XbFfP^^\@f\\ZXPN^^LFPJVRbJLNVRlFVVVLT\VDVJN\T\TRJXVVVdPRZZRXHbRPfTXPVZ`ZTJRLVTZf`T\R`PPRVPHVbBP>PTPNbLHb`\`HRTdTfFXRPVPN\JR\XNVbFZ\P`jPVJTT\XNJXR^NbTL\J^`^TZTVPTRTXZR`JPT`^T\XL`NdR^hhJjRTR^dNLJZbLPPXRPPNPLj\F\HZVJRVXZT`\VTdXXTLTR\RRX`RTPbRLXZ^XXRLdLfbTRd^ZJVPPbVZX\VX^^PNFL`V hTddbVXTT\LdPVVVPXTL^R`\RbdbVfpTbTVZRTZ\XZPZV`RNX^J`VZlTXdVJ^LVTLTZVPfT^JbZPTfHVVX\Z`X^ZN\Z`PTVNRhNJbJPNVP^R``fVRT\RX^f^\LjVd`HJXJV\V`TXTbTNbZVXXZhR`ZPXFdPfTVVJRXJXPV^^fXnjXjJhnN`PJbZbfdZf`VdTd^RhRl`bZXf`V`Z`\^Z`^^dZR^VV`VjXH\ZXd^bNRXRbLTfZ^`\VTZ`XLPlVZ\R\TV^ddNPjJT^VLVPh\`RFdRRVZHZRXHX`\PZb\^TP\^V^VZTB^RZDTLZT\N`N`ZPjZ^ZTF\X`NR\\NVRTbZP\RTb`\N\\XX^J\Zb^XTXX`b`R\\ZJVTNPTPLX\R6^VH``\LVVRTdPR`<Z\RXZ`^VZhRZXTd`VXT`L\ZVNT^V`H\RHHbZLRLfbRZ^Xd^VVLV\Z\NZTJZJ`TdLNRR^LPPPV`XPXL^FR\hPRZ\XJXRNZXLXXfPZTZL\LDPZRZNNXBXLTZR\LbVTbXP\XT\Z\^ZVRfPNd`bVJPXXX`FP\\XZRXb\^XVVZTd^\f^ZVL\VbZNd^RhV\\XX`TTb\FTV^\RZNZRTPdHZLb^N\JR\^XVPRF`LNZPVPZNZT^bTXT\LLRJbZPRJLbR`Pjb\^VVRV^N\bJP^ZZJJTfP\XLT^PdTPV`RPLXTNP`RbZ`\h^HdVTTP^\VLZ\`R`bVXXd\bLZdRRb^NdX`VlZH\ZbPTXXRNRT\RXRXLN\ZVPJHRVNTN\HTTNLjd^bLZXPJZZPLXTTJVV^RZRR\T^XZJVRVZlRJN`FX^^T\VLNZp^V<TV\LZXjjP\VXZ\fRPVZ^\VX^\bVVV^`J`VRZ\fPX\dRT`T^RX\RX\^jZT`R\fPdPXNVT^JhRN\PVFZT\LXVVXVZTTR^V`PLT^`XZPN`ZLXXT^bTTXP\Z`R`fJPhJXPHbRbTT`^XJZBXL\VLPXZT`dZhH`P`\^PbFXTV^PRRPPZLN`XbLVV`RX\V`PD`NbdXb^j^N^ThRdD\LVfdVTTZX`hZ^\\`fT^ZN\fPdP\dZ^dJLRfNbLV\P`\NT`PR`\TNXhF<RFVNNTFXZL`^ZLFPNFNPXHR`ZjZVZNFbH`bXPJL\TT\TPNR`@RPVXZ^XbN\N\VDX^ZHR^Td\PLRd^\RRLXHVRNTRPP`PTZZ^J`XDbZT\^TXZZTd\RHTVP^RN^LfPLRZ\``ZZpT`hZ\Ld`FTV`ZRPbTJ^\TVZNVP\PXXZNd^VVJ\NPRJ`XL^LJNLLd^RNV\R\R\\^\TZZV^NTTRVVVfJ`RZTF\^`R`RXTZ\NfNX`Zd^^ZRZPPbLZNb\\JbfdJZ\J`VNN\:TLR`R`:RbTRFRFX\J`BbZNR\L^JR^VLLTfP`HZRRTJT\`R^bdD\\NRVPNJXXdVXPNDVJTd\f@HPTTfR\NTZV^VTV^ZTVZTPXRZX`RPVLFVNRTT^LRR^`ZbVPLVXZNPRR^ZRX^DDX^VXR\XNHXZXZbfPdLZhbPR@PRLXFTBd\pXRLZb\RZ\NHVbB\ZTPVRd^PJDRP\XP\R\VdP\LLX^R^RZ`VLRTfVb\PZ`RPfTX^T\jZJRXPNVTT`^VTZNXVZDVZTVH`XZD\XNbTH\P@jXLdB^dTJ^VhR^bVTLbLJ^P`DTT``RnTfDRZThXdRXBNZ`ZfVfX`R\VbZXZ\lZbRXTbVV^TZT^^TZJZ\L^X\B`\XdDFXVTZZ`ZhLVTLbX`RX^ZZZPVPJJZd\V\PTPV``Xb*LVfZZXTV^J^ZdL^XV^^P^Nd\V`TPjVR^h^TN\PdLbTZZXVPfVTRbPNZT\bRVZ`^dT\XTVX^^V`V`NbPNXZXbRHL\Z`^bX\bPPbRdVJVFj^JH`RfVTHXPRVh\VXZV\\XZdhdf^XdN`fVTj\TX^`V^VZVd`F`Z^BrVF\`TXZhddVZRXT\f``bR\TTP``XRRdV`PRZ`ZVV^VZR^\NRT\X\ZbN\^JfJZdfVXTVTflV^`h^RHR`VRZLLRXXhjNX^R\LRVZ\ZZZVT^Z\\\R`\^RNXRTZN`LbZX\LdVXN\ZN^bXPP\LVNLPnVXZVXTVXV^XVZ`ZXVT^V^TXXFRdZJLZb`RTZ^PJHL\`RVVFLZRXJT``Bd`ZXRdLTbR`XhTTLV`@LdZ`D^XZ\^LHTT^Z^jfV^TPV\T`VbTdR`VJdBZV^^ZP`\^XVRLT`VdHZFN`JF\ZXX\X\VfVL^ZP\^`XTZNZ\NLRZ^VN^Z^XFRJ\PXZZHLF\hRZN\T^HRXNV^RPR^NP^LXVN\VZBHLV\\ZfNXdLfXdR`TNRNl`NNPN\jVXZXVJLLdZNT^ZX^Z^LZ^TNPTR`Hdd\XhVV^ZRPZPFZRVdRdX\\\XVRNL^\JZb`RVNVJBXV\X\XVHRbPTNLJVTNX^^\PPTT`^`H\XXVbZXLXTXZT^bTJVRXZT`XPVTJZJTFR\TT`\bL\TPVH\XLhXNXP\V\`FXTL^PD`VT>\VPTRPPLRVdRT`R\XN`dHfLh`\F`f^`X^R`T\ZTXT`F@N\ZXZ`R^RRLLFJRXR^Z`RbVZXT\`\bVXVXL\VVT^V\L\VbZZPLPVr^TZFbR\PLb^Z`^Z``PTRJ^`\X\Z^ZZbXN\bTZN^VbbNjLHPjP\VjVJ`ZXf:\Z^bVVPVZXb`XHVbR^TZZ\X`^HXL`^dPXRRPXRH`V`JRbRT^TZ`\bXbLXHjVfXXVddRTVdZBRVV^fjVFHhPPDTRRVdT\>\NTRPZPL`RT\VZfbb`XX^r`Vd`bZXdZ\T\ZXTZTZ^Xf^\TTVTbLVZLXZT`^`^^TTXbPXJdPdPT\TJX\THjR^VV^V^ZJbPPV`T\BfJ`X^\^TX^HZTXXHLFD^ZZTXP\Z`XNRR\DTTTN`VDNdTRf^bPTFX`RLPVPVNR\hRP NR\NVRHZ\bRPH\lNRXX^RRXPhTXX`TVXVV<b```^XPT^\XZL`PNLPbTLfPTTPPLZVXLNRfVZBZHXB^XRVNV^\VPT`VXT`fZVX.XLd>\XRX^PP\PVX\Pf^TTNFNRZTNdTh\HF`VbZJXX\ZXPTXZLJ`RlPTHPV^NTFR`ZZbVb^B^L\ZNRJRZ^fZZ^Z`dTVVNZPLZNXTV\PRVbNHFdJVLXTLXZXXRXN\ZbB`fLPZ`V@b<TXPfbFbXTHRXP`VRXRLVXfZVH^FXNTbRb`DP`bXTRPNJRNZLb\JNbXHR^\RXTTP\X^XXfHHPPbXTPP`XfPTLNRPVVXVPFXTNXdNNLPLfN`Z`TX^dfXPXHZZVTPPL\Z^VdD`TV\dVVXj@PPbNX`N^\NLPXJ\Z`R^T\\fPdZH\^LJ^dJV^VJV``\VRPVB^RVHXN\PjP`VL\TVdPVNR`TNZX\ZZZPXJ```NRhNhTVR\XRXJ``NjXZ\XX@`^``\^XTJX\ZX^ndZNTV^bXVR`d\\^^RNPPbbNP^bV`TV^XBd`hR^TfTVR`LLBZ\VN^^^RXL\ZNRZ^Z\VZP`RZ^ZTDZV`\RXPVJVdDbRLf^NJfHNT@jXPXH\dVJf`RNZRX`dbV`^\XZf^R`RT\F\NZbLRV^`NXPXdVRZTJ^^ZLZTVNVRZPZ^RNZLXTXTPT^Rlbjb`b`Fb\`V^RTXd^RTh`RZjR^VR^Zd`RTRX\`XhLB\Fd\ZRfV`lVjPXZZZbPNRhZVRdVLX@^PTRTT^Rbh^LhV\R\`PTX\RRPVXRTRVb\V\`\VPVV^VPdL\\NZTV\TR\\PZ\X\RTVfL^^ThPLXPRR^bFf`ZZjDZ<\VHVPLR`lXVbVTVRVZXTXNTbVN\LZVL^PNX\`JV^RZ^XZX``XLXJZ^NB\R`\\ZTXZXVNJ`HXHVXNZRTTVNJR\XTXVfZbV`dTPTdbPXb^PN^HXRZHf\RVPRfPRNT\^``XXbV`NP^bF^HFZRdTNVX^\\H\RbbnT\\PP``Pf`^VVVZ\JPDJ`PZTL`\R^\j\NZ^FPXJdRZLJbBNVXRVRP^VDT\ZHR^^TPJNH\^P`TXVTRHZX^NPL\N`HVNHZ\LFZVVDfPVXL\V^T`TN`RPXdZRThR\NTLT`RZLL^NRTRXZ\F\NZBT\L`ZV@XXX\ZXX\fZXNbZj^\HHT^^TNNVPXRRPLfN\`\LR`dHPTVRVNjTTP^V\THPHLfVTXZVXbXPZPRZZ\V^XX\RVPVD^TTTTRTVNJbNXXHVNjbX`@bZJPdXV`Z\L XXdN`R`NJ\ZTT\`XZRRZXTXRVTTN`NVPXH^XVVfLH^NXdhPZZ^\P\R\TbXHPh\ZNPXZVnBdV`RRVTR`@^X``TZffZ\fRVVVTZ\RP\TZX`X\Z^PLXXZh^R`RRZNhT\TT\bXX\P\RjR\\b`T`h^LNhTX`^N\^XZfbNNRLTb`XVPNVZPh^ZhZL\dh`PbP\T^V^X^DbTbXVZ^LXRP^dTV\N`ZXZTPRF\RXX\f^\`L^JXfbX^VXRR^HZXVNfNTRXTNVX\`ZRVdlbNVZRP\TVRRNdPZ^^\hVb\dNTR^fdTXbXVVdJ\V`^HjRPdPZ^V^VT\T`\X^^DdXdR\VRbT`TFNR\\RXPVHVdX^ZNTHT\d\X\LF@bPHZ\fTTfT`R\DPZXRL^dZHHFdXPLRbPLJdLZLNPR\FZ^LHPNL\DTXLbVhJjLVPTLZfbRP^NLPLFXR\bP\ZJXZX@XHbJTNRbPRPTTP\@ZTNZ\T``NDPbLXXbTNP`RZLVXLLNXXV\XXVXDTVHVRZL\LZ\LLTRNNP^PTTDNZRXV^TLHlHT\VRRZLdP\PZ^TLRT`VNXTTNb^RPV`TXJXNHVTj\b`ZPFTNJ`ZLNVXHVXTZ\\XNdZDZXRPR\TRRZ\TRTXTTVL\BXHZXZ`R^LLLZXbTJfDZRhTXbZ\HHPJZJjRNXVHVXPNZLVDZP`NXVZNHZXRbVR^X\XVZN`X^JTRZ\XVN^ZPXP`TFNHZR\^bZVT\TV\VfPXNT\LnNNTdbVHP\NNRL^R^PRV2V:dFTb>bPX^TZZ\LTPZZDV^JXNXXbd@TBXVLbV`VLVXX^Xh^RPX\NRNbN`ZZ\bVfJR^NHPRZVXLRNVVJRXVTfTTXXRV>PXZVZRV\HZXZDVZTNN\\`TTT\NVl^X^bd`bZPJXZX\bJ\LX^bdbXVNTNZ^VRNRVVLfbV\fZTTNZT`TZTNX`R^R^PfZb^TRRZVf`VXRbd\ZRV\b\ZNXTbfDTR\TTlRLd\TF^NN^TZV\X^Ph`\NJXNPNNXXLXdLXXX\ZHPN`bb\`XXPbZLTRdbLn`hbZJXRFVT^JfZRVJPZZP^\`Z\ZX\LTNZJH\RTTRX`PRLNZTV^RTT^XZFRRN\TTJ<ZRbb`N^bPTT>^blfZf`^TdRdXd\T\RZXTZTVXNb^^ZJT`Z`X`bZXVVRR\VN\Z^^JV^VRj^bLVZPV^P`PNXXbf`P\RPXLZV^RZPlJjX\XXD^LVfRZRJZPR^jZLPbVXZVPXX^\dPRLHVXZ\T\HBX^^PLZXDX\RbNNfbTZ^TVXPN\P\d`ZRVJPTRXVdT^ZR\TTXfNZP\^VZXZHXZRRR\TR\dX>d\fFJTZP\ZL\VZ`T^P`Zd`RbZXV\\`P^HRXRVd\H^VfXXN\hVbPbb`VRh^XbZTfZZJ^XfZ\fZD\ZTXVRXR^F^^^Z\L:\VVVR`ZNNTPVV\JPZ\LVRPVVd\Xb^FTR\XH\VZZ\R`NRTVZZXRTPPP``TRV`Rf\d\LNVd^X,ZXVXXJ`LZJRZZ\JZP<RZTTRTXJNLPN^DXVbZT^lZXX`D^J\PXRBbV\RXd`TTXHRZVNNRT^LZXPLNTlXTFhVR\T^N\ZNV\`R`ZNPVRPPPX`X\\>T^LZLTXdVLbZP^HfVbZ\R^bZbNZ\XdNXVRRRZPh^ZZ`bNhXVPbZb\P^VTXfbRTZ\LPN^RhR\ZPNTNPT^*T`LdJZVXPZd`RL^JXXTZfLZR\R\LXX^RPP\VPZH`\VLVXfTXXR^`V`R\\TTXbbXRV\@LfFZ^NZV^ZRRdThPLJrhT^R4`dB^f6bX^VJZ^Tb`FJT^NXZfXNRfDLXTZZbLVXLT`\`b`RX\LXZ\VdHVVXbPZVTj\NZ`VZd\X`\NFdJNPd^ZV>`X`\TRn\Z\Z`^NNRZ`d^\^d\VR^VHH`bXTPXF`X`VPNhJ\\NV`RP^XV`VZbVddbfJ\LbR`L`RZPT\XT^^T\B\JLbVP\P^LXH\HhR^b^ZZPTVVVP\\`VXX^X`bZ\\ddb`XNZbThNVNV`RTRNRR\XPLZXdN\LP`V\\TZZZV^NZZ^PR`\lTZX\VbTNjNNbZTTVZRVTZRTXT\\RZ^RVXRPF\LZT^NNXJLhJdVVZTPdX^VZbH`VPZNTTPZZ^RBdJ`HT^\X>TTP``LVZP\dXZV^XPRd\`LRd\XVX\Z^LDdbNVRNZ\TL`RXFPPTL\ZLVVVZVJTXd`P\VTjJ\XRVH\HHPTNXPLRVVLB^NX^VRJXTN`Z^FTJNVX^RVXXXDd\NVV^fPPVXZVPP^FP^RPZLVbF\bHJRNX\VVXTH\LXPTd^VLTRTV`JTZV`LTVZPPXZTdXV`V^P`N^V\N\bLZdP^Ph@VX`TPTXPdVV^T`RdVRLV^^DZ`T^V\ZL\HT``JRNJR^b^RP^FVZ\fVXRNVHVVTNTPPTTRTXXRRPZJPNbV`dXV`ZXPVXJHVPPTZ^X\VZRDdTHVZXDZNdZRLRXbX^J\fJRNJXPZZLTbTb^\VTL`^^P^LNT\LZRRXH^RZVNVTZHZT\Vb>\TRL^PTXRbJTNXVLPR\ZLNX^P>N^PXT^ZZT\TNX\ZPXRXN\bPXdJ\PRPXLTF\TRZFXRXNZXRNT`PZX\XTLXbTZX\^T\RPZRJVR@NHVDRhVJVTXXR^ZZbJXbTZRTLPbVbVT`H^NTL^RTLPP`XZR^bRVhRT\Z`bPTd\`^\VN^\R\ZVP^N`ZPZbLV\PTfXNnTR\ddR\N^XRZ^XT^XbLV^^N`\N^ZTV`XXT^X\^ZZlHnVV^`\LJ\VHfRdHb^V`LX`PbLbZJT`VdNTVVbXRTZ`VPZ^RVPbVRZhZT\ZNRLPZZV`XNZL`\TTh`^NVDNPT@JPFPJ`PVZNbT^NP^ZdnhVTVfXlfX\JdZbZ\n`^`V^l\X\b^TVPVfRV^PZZNjLddV\N`Zdh\ZT`VH`VTNT^^bX\NXdNXZNNZVVRLJ^RLVP\ZT\LT^XbTVhbTJVR\\Z`T\RRZNV\hjXHV`X`\T\LJ`^LVXRVXXX``TTTHP`PRbPJFj^RFdXVT^XTNZX^JPHTLVXXTVXPd@ZdXRfT\hNXXZT@f`\H`TpBPTZZXZRXT^\\XbbVTZZ\TThT^VNT\VRfHZV^HVXZ^XXZVP`TRRLV\V\\XRX`R\`H^LZZPVVVX\TNLhRdNRTRV^XZZZNJ^VX\\\XXdZdVT^^b`BNN\RV\X`RfTf<V\VNVLNb\H`dNN^ZP\^PZV\LNN^ZVPZbXZTP\@DXVLVTTVZZZX@XLX^^V^ZVZLVPNNRVVZVdPLNFdXVpZZZbTXZBXJTTZVFPTZTVZf`LTV\b\ZRVJV^XZXP\LlRT\TXTpbRRVPNZPLRZR\NVTFfTL`P@`d`N\`X^FLXbPV^ZZT\XRR^HXNVH>Vf^ZPbNbVZZXL^V\Xdb^ZTX\\X\^\NNTZZXXH^nTdXl\LH\XX`fXR`\XX^^XN^JNRNTNJTXXLHZbTV\JT\PTFTN\@RJZRXDP\X\V\`NZHP^\\PTV\^\L\dR^Z`THRNnR^NX`dVPXRXPZT^TfXNf^^\RR\XXTHRXR`RFNZTbVfXNVLV^TTTVZZ^JX`TDTLN\XRHh^`bLVZXXXV\R\`L`XL\^`RXpdPVTb\`\Z^Vf>\V\fPVV^\bNfXJ\P\XTTR^dZHXFThXnb\b`h^\FdLTdRRZlZZ\RXDdTNRXXVTbb\TbXNXXZJZZPP`\ZPZfVJZTPVVX`R\NRP`\VfLLbRPRXNDXLXdNZjdd\>XRXNVZTf\hffVXRXRXddPD^XfT^PhLTdLV\\TDRdNPfX`RZNXbXPdVTdJ\VVTRdLJZTRVPRVRfRf^\bV^nTTR`TbfbV^HN\dTRXV^ZVZVHPVVT\NXXbVP^ZZLNPJJVD\X`^RR\\XPP^ZNVNTNZPRb^LXZ`PTR^LVX\RVNVVLNXJ`VZRNZVRh\^LTRJ`P`LF\VJLN^THX^VNXN^fN\N^N\`NVBRNR`XVFRX`PNVZ^XXV^ZZT\TTVZVXXbVXLb\^ZRVbHJT\L\LPZVZdZh`V\^PZ\^X`R`RXLTRPZVVXXXTRRX^PNVZ`ZRJ`bbJ`^RVH\``NPTLJXRXVRZDRVRTBPPJdTRBVLX^PVPXN\VFXVV\ZT\VTdPVPXVXZLTJRPPVPVVPTTVfJHVPXFFnXTFRLRHBT`P`RXXRLTRJd\ZZTPTXZTNZhJTRPXLRN^TNTJ^PV`L^^bXDRNP\N`RVRZTVTT\TPP^\^RTXPTN\V`TLVPdVRXZ^VTXTX`T\bXR^XTJZ`JRR8ZVJ\D\PXZZ`NLZb\^TRX^XT\BTbV\\ZLNNZLLNNR<JRXPTH\LVNRPN^H`VPV\\ZLL`\ZJR`\ZNbRT^J\Hd\JX`^RjT\T\JT\NHf^XJXZ\PN^RVZV\V`NX`\ZH\RR\VVd\\DN^\V\VRXVTNTJXbR^LR\VXdJ^hFNbb\XN`ZdZ`^LRX\`bN``\^RNPN\P`ZX^NbNhVX^RNRlfbZ^PbVR`V^dXV\TZ^ZVVZJ^\XTVTdTTX\^VTVLbZ^RRVP`VTHV`XPX`dN^TXR\`ZPdXX^bZ`T`^N\XNXVZNRbDdhF^X^f^dRZZZ`^XTNXRZ^R@V^LZNbXZZZL\N`LXbJH\VPdlblbfJ`^`^FRTZdN\X``\bJdjhTJ^Xn\hVTN\`l^Xf\\bZd\RZX^\VfR^\fJNT`dVd^TjHLVfP`hTbd\L^\fVLLV^bRNZTPP^NTPVRd^JVVXZ\VR\RLNTH^JNVRPVTDbPXVTZ`NfRHZ<R^VD^\TLV\\R`TVRJTRVVXRPZh\RN^TNPVZ^RXXZNZVRJTPhH\V`ZZ`N`X\XDXVbZXfbZZL\\`TLPNRX`RHd^\^VR`T`LVV@TVTXLXf\^\RZfVTPTTZjHLZ^ZNXTZTJ^ZRRPHTNTNP^^XbPR^^FbVJ\R\TXVVXNTXXVTTXTVRXV^PRVVTh\XNV^\BTJ`D^\Nhh\X^VXRdJT^bXTZRTTTTRbTNXRZ^Z\VLTVHP\\J^Xb`bNRVXTjNRN`^BVFTTZ\LHPVZNJTPTXTRRZLXFNVRLdXT\NVVF\\VPZ^XXRR\HbXDPR`fjJRVV^JTL`RJZVZdRZ\TPTT\R`VPPNTPXNV^XZZZdXNX\P`\bPJJX`TVfTbXNRL^VV`fRX\RP\X\LTLPD\X`XT\^ZXVZ\LPZDVXVHb\b`HTNVPNL\^N^TPVRZT^XLR\LN\VNZ`LdHPRXZRR\\VP\RR^VZ`TP^@TXVNbV^R`LLRTPZNTJXL^`^T`\XJVRf^TXPHdjP^bZ`TTFPnRZVZTRZRTX^VbTfdXVJTX\RNRRVVN`LVZJ\TXTLbVH^X`NPL\PZFd^^RZX\\XVTNV\PTbTTV^^VZd`ThV^\\TNf`^`LZ`PLj\VXXRbZVP^RPfnPThTZ^\PjX^TbP^PZ^XZZXVTZfN^^VXVL\T\X`XbPVZTP`VbXNhZTXjZVN^TfXTZ^^TbX^R\T\ZVX\dR`LZ^d\T^VXR^XFVTThTXdNLZPZRX@PX\JVRXRR`RTTNXXX^`TL\XVXZLN\JV`RhR`PJZ`fhh`^P^db^^TJZZ\XPX^`XbP`TZH\VRXdThXZRN`Rh^ZTXX\`ZPTRjTX^XV^DVbVZJRdbTNXd^\^\VTZ^X\RT^VX^dTdRhTTXbX`\T`RRT\ZBZ^FXVjXbhLLRLLLZ\XV`\ZN^JLdV\Z\^JRLHdZ^Z^XdVXN\TPThJZ\XHfNRTRVX\XTPLbVRPVVP\JVPVRZP^ZVJVTNTVLVZbJX^XLXZNTPN\bRV^Td^XnTTLVVPJNNV^NbZXV^NJHR`VR\NNV\RP\PDLRHdBNTTZ\`PVTTX^J\`f\bVdJ`bDRdPJVfFXXPPPRZPHZ\bVVFNT>fP`X^JXPZRfVVRjP`PNdZZX^PTZXThVTRVVZZ^dNPPLPRZXRVPbL\JPTDTXTJX8ZPLTXX\P@`R\TPJd^HdTNXLTZPPRfXRZFVNVRTRdLTd^RNHNlJ<fPVTTHX`RVRNNdZRP\RN^TJVLd\ZR`VHVXRTN`RTJbZBT\`XDTJ`^ZPXd\bPVHbNj^D^dTZbXbZZNXVhRdNJP\jX^J`>>^XNRPVdHX`PP`PP^`R`PZPRVRZ`VL^ZTXdZR`TbXZXRNXX^D^ZXZLdX`ZNPXNhb^RH`RT\>XTPR\XRZ\DRTD\VP\V\VPPTZ^TJ`VZjTRRVXXh^`fTT`RPVRPTJdVFVVXFZVVVZZN>NZJZTZTVRVXXZVR\XNHbXFZVLX\ZZPNZTTbVd\BZR\TBjRR\\\dPPR\VRXVdfRdN`fLZRXhXPTb\FVRJ^bVT\PdNZJhP^^RXXZXb\HVZXb^ZRRb`Rbfb\\bVRT\\X\VZZ^`TXPVZ^FNTVPLRZ\RVTVZRbD\^\^RZ^\^`Z`V<Pdh\Z`H`XFFZN`ZX`h^FZT\JTJhX^PXTLVX\TNV\FfLVT``bfbdXZ\N\@PVTXVTbhVdX^ZRZ``XZZNfRj``Z\NX^JNXNbTVTT^bd\\V\NLP\L^bXVRPJ`ZX^LXNVTXX^X\V\X`JZbJX\^ZV\``TTHN\``\PRVV`^N\V`RXbJ@VfX`ZTX^JV\XVZ\LJLZJZdP\`PTVRdJZRRVL`PVXXDfJZ<bN\P`PDTVDTVbbXT\NXb`VHd\X^\HJRdNXZT`LFX`X\^HbD`FP`V\Z^`ZPTb^`XP\bTXRHL\PbX\Vd\\\bRX^^^^TXVDZXV^Z\XVVPXVXVPR^Z`X^`VXZNbPXNXbpdVVV\D^V^X^R\V\ZV\RZTb\bbRNb^ZNZPR\V`ZjLLdThTZ\ZXXXNJd\bT`TVLVPZVNbZdXTNX\VRNDZVZ`T`\ZX`ZLR\PD^XXV\\LXXLRT`^^PTX^B\RV@VPTFPRZ8bP`\VB^^TTLZRXbRRZlRTPP`XXXTRT@ZHNRHJZTXZVR\VbZJPdPdb^jTbLDVDNTRV\PV`TVR`H^VVVbfhRbVR`RVN^NFR^^JX\R^\j\N^PXVTTN^`^TND``HRfbPJLPTTVXVL`VdH\VPJZTRH<V\LP\bJ^DfR^VTRbFXFPPP\TH\\\d@LhXfTXXdZPT`R^JZVbFZPZR`^VZPTZZ^`TTPP^R`NNf^VT`^NbXVF^ffZX^LZJVPTZ^JV\^Z^TNT@FZPXb\\NR\bZNZ`XZXNTRN`P`VP`TRZJX`TNR`VN\bX^\\bR^dnTJfL\V^bP^^D`LTXTT\``PT\Z`HR^`XP^LVRFhhN^b\\b\Vd`TTXTfDFV`fZRRfV`lZVTR\XZL\JVVZ\ZPZVbH^P\V\ZXVbVXT^`\bZRXVhBN^Z\FXB^TVZdVXZXF`ZP`\XRT`NffdbZXf`LRZ^VPb^\PhNdDZ`ZdHPXh^Xb^ZhVZZXbV^bZRbbHNX\T^PVL`^TNVZTfVNbbJ\DXNRVNZXTNZNXTXXXLZPbRPRZXVh\VDXJNdJ`fVRXTPZNHZX\ZNTV`PLZZVDVN^N^JXZVRVXX\LRLDZR^N^TTZPRVdVRRVNXRVZTVR^B\ZXPT\VhTl`TLBXRLVN\TNL@PbVZR\\L^PVR`RP\TXRNT>PbRTRL\JXZPNXHbL\XPNVXDP`PPZPXPN^LJNRRTRHZVHZNRVJRDZ\`b\PDV^XVRV\bTF^\\RRTZ\PLVZTVVh^\XR\L`ZPTTP\NRPdV\LhX`ZbVRZ`^^PP^VXRV^XXDNX^PRVFZPdTZX^>B\bFZJZLVTLJN^RTRDJ^ZBVH^XZbRXPbTRVb\RJ\\^TV\VR\FPdXN`R\F^NBf`NPZVPLjX^PVZJbfFXT\\N\\bPLXHV\HTdbTXXL^\^X\VRVHTZTTVPV^VVfRXNb^dPVJTBLdVZ\V^TlNRZVN`\TTJN\X`^LPd^XLRdPX`TZXFNHTNP\Z\XbRJX^XF\^LV\VRJhPfZT`RVNX\PNbVT^VXF\TFRLTdRX>XXD@`Vb`fV\VN^L\bfP\\T`RPTVRJTP`B^TT\N\Vj\XPPT`ZZTF`NVXZTR^`Z^`VPb\TVVLbRN^RHPFVPX\TZRZ`\XXdXXRP\bZdPRZLLV`\b`hX^Z\^Tj\LjH``P`dXbNfNZXL\b^VTTfHbPXXXZ\XPbLPZLR^XVhl`\N^\N^LdTT\ZR\^Vf^JZRTHZ`V>bXPZRZ\h^Z`bZTHbX\bVRB\X\XXZ^ZlVfXNL\\XFVPbZZNZNXV``NT\R^\NPVPXPZTVXNRNXV^T\XH`Td^NZVVbVPZTdTZT`T`LPNXJ^fd`^Xd\^LlVX^P\l\XZff\bZ\ZZT^^X^XjT`hNZ`^T\RTdLhLHHR\TRPRXTXb^XXP^dbPXdZ^T`Z^b`\X\FZXZXP^LXJ\`BNTVddPRX\\VXZTV\\bRZV^\P`RTTLNP`JNLD`DTb^L^TVhJ^VDb^RTPNRHF^ZX\Z`R`D^^ZJ^@JRTPTVLRRZZNRbXtNZTDfTRbZNb\\HfXfRPfRRZXHFZVRbRVdf\\\\>\dNLhRjHBVVJRRdbRPNL\H^LXXXZN\\TPFZX^RPZTTNTZ\V`XVH^X`^\JXPVZDPTXb^^Rd`RZRPXZXbffN^XRdJdH\XVLb^R^ZjTVZPf@\b^\XPR\B\R\LX`N\TTJbV\T^ZR\Zb\VV>TV`ZL\XTZZBXHPTR\R\NZ^N\TTTdTZHP`TZ\TXNX^P\PZNVVRR`\NTVVPjPX\dbbZ\LH\NfNPZVVN\ZTZNJ^b\>VVLV`^TLbTVLRLXZR^<P\XN`PRZf`NTRTRP\<\RbRVTVL``LdR^H`XVfFNTbZZ\^\PRRNPLbBHZfX^BRR\^VLLRRVVXXFZHJNJRTRHPNbbTVZ\ZPFXN\NX^RHbRTZLPPNPT\R`ZZTN^L^XLdVNNZRJ\JdV^V^PTXRZB\NfHRZRLZ`N^VNDZRHR@VVpVL^^VTf`TV^NVdJ^TXPT\X\PTRfZV`\P^T\R`bbTNVNNZ^\b`LVZNdNJZh^FbTTN`fXVX^TT^`\\`LRXLbVdX`V^hRh^^b^T\XTNVRhZ`ZZfbZT^VN\dT^`\VXV`RXZHVVbNdZVV\T\RjZNTZXRZT\XVT^bFVTVXZZPZZR^d^ZP^HZ\VH^TbRRTP^`R\Z`PbLXXPTRH\R`RHVTVhLd`\BX\RV^jbZ^^l`Pbd^Z\VhZXR^XPPTXVfP`LVVJPZTP\Z`ZTXRZ\TPVZ\\PXRfJRXPhTXX`^d`b^X^RTVVVZ^P\PPZdX^\XfJTP\PddXRJr^VRTZTPBXXfZNRJ`dZFRLPF^RNFV^@\N^TX`^ZJJVNLRRZDRZBZ<XXLT\F\^VZPZNTRZR^@PZ\`NXPVhVZZ`RVPdNL^dTP\X`ZRD^ZDbVZDTXRR`P^ZVb`bTPJTZfTZRXhN`\VRZR`NZJ^X^RRJ\VXbTZTZ@^XX^LTZXRRb^N^Vf\VRHZNVNRPVVbP\LZR^`VXVLPH^P^P\XfNVFZV,RJd>NbXH^JXNXP>LLXZ\XLdLT\ZNT\FJXTV\\VFVXHZXNVF^dbZ\XVZTP`ZBZV\ZXHZNTRZV^R`\j^^\LVV`dJZBNRVLdZbd\Z^XVLP\VNX\dVdTbN^HXTZZVPRV^VTTX^DHhZRX`NV\R\\TVL`TPVd^XPbZLZRTPLNLfXR`RLX`TRLZVVVZbPB`JfZTVZXZR\RRTPNRZbPbRXTRRVd^^P\b^`XPjR^``RL^H\^PVRJVL\\\LbZZfPVdNVZFV^T^RXXX\Z^V^PXVJ^PT\PXPXb\`XV\J`PRXLVN`h`X`^hT^\VX`ZPRfZTVL\fXLZVV\^VZXTLT\XR`N^\P^ZZPLRVL^T`NR\PBRXVbJ\RZX@\V\fNX\NRVXXP\`Xd`\TTLVFZXdlVdF`T\jH^^Z\Z\\TZVNR\T`TNRLJfLT^RZXbZZPXd\f\N`^`XHZZRXXZVTjJd\\XNRb\V`Hb`RPZ\VV`PT^\\XPfhJTF\XZZX^dXLT^NXJLR`PVRT\VLJ\`RfLZRR\XT^^d^RX\LNZT\b^HV^TTbRRpJ\RTNP`TT\R^PTXXZXbTTT^TfbB`TXL`bhb\bp^dRfVb^T^`\L`XhL\^VL^\T`ZZLhVZjNRLfpX`RNT`ZPTV`NTfdhZDVZ\LbZflTR`jjj\PbdVXNT``bdN\PZVhVZZJTTXHdNdRhZ`NJ^bNT^Rbf\VTPRNRhPTXXRLXNP^ZTPPZP\VjNT`LVbTX^PVP\Z`X^\FJZ\ZX\Z`dTdd^XXR`XHFZbLZPZJTd^NLThVVdV``TT\j\ZTTbZ\^b^XNd^ZNNL^TJ^X`\PXdbT\NT`LXV^ZHdPL\V`Z`TVVVR^PX`LRXL\X`TVRJ^ZT`VTZXZbT^bXb^JHVZT\\ZTLFV^XVZRXXVRVPRXZTTL\`JXF\NB\`R\HDdH\RP^T\TTN`bJLP`LPBPL\NVNZXPT^VLZ^TLdFVRhXLTVXTTDPVTXRNNPXX^TfB`P^VV\T^JVNVRNR^lTZDLFNRX^TPb`V`Z\TTJ^PJXVVb`^`ZT^H\XXFN\dJDB\XTTbH`RLVTVhZNTbJLTLRTP`VTNNT`b^f`ZR^b`XPRjNRb^RNPTXRfVhV\XNdVbRPZ\X`RPZHHR^NXXbX`HPTTZfNVXTZTRPdN\NXJ\db^XZ\LNbV\PTTZHdd\ZVRVP^XVVVVZZZRfHVTXXP\\\fZ^Z^dRDRVNJ^Pb\\ZRZVZbPR\\VZVj^XRVZXVV\\XTf`V\NVdXVJTVVVZd\\NX\b`NdV^LTZ`T\PVV``PP`^N`RRVVX\XTVTR^TNV\P`VPRbnVRPR^ZfPJ^TVPZPLd``TjBRbZ\X^T``bZXZL^bXbXZXbXRLfTNb^XbZRVVbRPdTf`LVZ\PbHXTNd^T^`Z`XRJ\PbZJ^`X`XDVHhfTTTNb^PVX^^X`PZTjJNVRh\XRVXX\VXVbT`XbZZV`fX^P`bZZbJZVTP\L`ZNRd``R`XJFZr\XRVXjZX\XjBXXVfXJdPd`^ddd^FZVdRDT\`XNVHV\NZZ\\T\ZRVbVbVJTZT`RXVPRb\`VZbLNTXX^PXVdZXh\XVZD\bTJ^R^VJ@\LX\X>NTTbTZXRPX^VJbRR\TZ^`TV^ZLPbHTP^RfPTZZLZR^PN@NPbTXFhRTHFXL^J`HbRZfZPTfR`HVR^XbRNZ\VJPLVTPZT^PR\VLPhHTTVRb\JLTZZHVNZPTLbdNNjNVDRP\VX^\LVTP^ZhZX@P\PNNT^^\PTJRLdX\VPVB\XdTTbNZXbTPRT^VJZfNTNJVRRHFXNX`PTf^N`RLVTTZTfXH`V^NNPVBRdNHXXRVRT\VPZdXXVfNHVP^RTTVDTZHZRNXRRPV\PXFf^^XHBVX\ZXH\`NZ^RVJlPZRTV\J>`ZF`\\FZXLZRX\V^ZV^TTXVNT^X`^RVPbR`T^\T\Z^BTLR`H\JLZ`\R^f\P`FNZ\ZPHR`NL^NdXRV`Hdj`ZXXJZTVT\HXZbdTDN`^Z`XVLNhHVZZTX`N\fVVVdZlZJ\J`VP\L^TZdTZ^RZdVNjP\XPTLZlfJ^\\V^XbNXVf\PVZ`ZTZXTNZXRVdTT^HTX^^ZVT^ZR^FPLNTXb`R^ZPTVZRZVd\TZZ`DNX``XbZ<NJPXTZTVTRjVNZPTXTfTJV`RTR`bX\NR`HRdP\bXVXRZhPZ\hTP`N`\X`PNRT`NXXZbdVhT\\RhZV`ZZTbXRJdbRRTfTRhRfX\FP`\ZRPbXTN\^`\R`XRXjXR^FZ\`ZXTpNbNVZfdTZ`ZZ<nRHXbTb\dNV\\bdNff`VZNX\T^\\XV^hb^ZTZX\b\DdHfXTZZVV\LXZLV\ZNL`RfPPNn`JVv^f\dl`^X^XZN^dN^VRHd`L\ZXXNPZVbL^^ZdPdP^V\RV`\^Vd`PT\RLZPbbVZXRVXV\`T^`\\blXVbPZZlXLVPjVZX^N\ZdXVdLHXNf^VPTRTDZZP^NNTR`RX\V\VX\XbP^Tb\ZrLX\RZXZdNXXT\bLbXdRR\\VTNRfHbL^`\Z^dXLd^LbZRTZhXZ^ZPf\RV^DLdRTZTfTTZJZTfTd\V^NZ>V^L\R`HbbXVZLXVPfXNNf\NVT\P\FfLZT^LXL\dXfTZ`LJVPVRPRPT`\R^PNNbX^NZZ\XjRTT`d^RRTRRjZ^RbT`VTJXP^BZPZ`RRXRVV\``VTXZLdJ`VFNJ^RPLNT\ZJRVVX^DVjHRRN\RjVRRTRPNXZRZVRZXTL\ZNVXJXVXRNZ\RPP\TVRPR^^\PVZZdHRh^^^XZT^^TV\`ZX\VNRNRHNRTX`PPPRJZTXX^VZVVLPfV\dN^^RZ`N\PNZVRNV@hTTRThbTXTP^ZZPZX\TXPLfT\\dTN\^HZJVXRZ\PR\VNXN\`\dH^dJZP^VPVZ\L^^XNRXL^XXjT^\`NdB\ZX^PN`JNN\RXTPLRNb``PTTXNb\VTNXTV`\ZVd\lZTj`^^XR`XXZRh^XlbP^\TP\V\VRX^^P`VRVRVjLdF`\`Z`d\BZZTVb<ZV\RHd`fZXF\XP^RZZdRfXVPlLXPNPPbR^BdZ^^fZNLZPdX```TdjRR`Vf^P\^TTPhV^\\\fPb\X^jVXfTVPRb^ZdThdX^R^^RhR\hbXR\TTVLVV^RNXV^RfJXZRZ<RLPfL\HP\dVLRRNVV^^`jNX\J\\J`Z`^ZVJRZPJTXPL`\\PZVfLhPh\ZbdfVZj\ZTXZ\Xb^`RRXLT\ZZNZP\\d\\^^N\XZL\Z^ZPb\LX\RRTX`XLP^`ZZP^^BVXNPXH`fpRPV\PhVhTTNTRNRLXXRPNZ^PXVDRPD\RTZHVXLLNTRV\Z\VHXRPJRdVNZXfZPLT\ZRXH\TRRTNFTTdTF\bRdXVV`\LVVj\^XFVVLT\RPZZP\RPfJ`^b`ZJXNZ^\VNX<HPVVbTP^PR^NRTZVjZXJVHNJ^ZJ\X\RLJVRbPXZV>T@VTX\ZZTR^hN\XNZNbPP\X^^H\V\PV^TZ^HTV@LPTTdNZV^XVVTPRNPV\^dRX`NbLT\b\XPVhTXLRXV^L`NRZV>fNHZH^<DnD`:LXVV^P^VZXBPRJZPNV^NND\ZVfVdTP`PTVfXXhPNP`N^RRL^ZPdZBXXPdNPLTX^RX`fNT^`TXPPPZXlHZJfLPV`ZTXXJZ\fXP\TbR`VNHJLVLNVP^.\RVTPRJV4\PTBBNVbTXdJ\Pf^V`JjJX\^d<LNXbNR^BdLRFlNZ`PTPXJbZBZNdTV\BZ^JdV^^TPNXZNVZdLZ\N@Zb\N^TP^XF^XTPVV^fbP\^N`R\`NT`ZRTFT\J^XbXV\F`R^^HNP^\ZPZf`PNj\VBHVbNZZdh\XXR\Z`XHZPZX^dZh\RX^TZXnVXZ`JX\dV4VN^^PN`LZT^R`NRZVZVjT`\^`JVjNZZbVP`\VN`X@^XfN`\\ThhRR\VZHfX\H^ThTfXX`JX`JXZV`XL^LTTV\VZZPXZXJdTV`NVLPR^ZZ^VRZ\X\Lf^ZV^ZXdZPR`ZjdJfTlX\bTJ`N`ZVTdPZ`LVb`VRj\`NLT\LdR^^\RZP`X`dV\V`Rf\V`bNXT\H^XbTVV\\NXTZJXJ^\JJ^ \^PbZX\R\ZNX\\VVNfXbbV`Zbd\bjl`bdZlfZ\XXb`VXVTZHdZh\Z`P\bZRZZbR^d\VV^`VbjD\PbXTBXdR^bZLT`^VX`P\RP\JVf^VZbV^ZZZVL\\TRLdRV^XXT^dTJ@RVVZj\HZVVZXVLJDdDPT\PXVRLXT^RZXVX\`ZVXVR`XLFjR`PdRTNdZZT^LbTXT`P^TbbZTPXZbXh\TXfNR^XXTVR\VbXV\Z\VbVN`^RTPTXLNPVLZXhhVHbPP\JPh\VbT\X\TN\\^TFXT\ZdHZRNTbXZbBXXT^nZ\\bVPZ\L`ZX^`f\Z`NP\^\TPZ\`^TV\TP^LXZ\^ZPVVV`TX`hBZXVTRdNNbb^\R\XbPF`NXVTPPVRTXXZTV`B`RTP\\XTTVVXTL\PVTXZJ^FXRFZZH`\HVVNTX\R^RVPRRH`ZLPLZXZTRLfHXT\`TjTLNNZXR^bP^VRL`TTTVL`ZV`X`JLVVXZXN@ZDLl^TTb^X`dX`\X`TPZZVVVZ\FRPXZX^b^PfHTP\hFXDXbXLXXRTR^bPPJ\T\H\ZRbFTHbZZhTlP^NRZfVX^lPZXNVRJ\NXdV\dR\ZPD\TZTTZ`NNPVZDdZTXTHbZTZZRXZJRVB\^>f\h@TTLVjRR@bFdVZb\^\RdLbP\RRLPFNVPTNdT^PJJL^ZTZd\N\\VLNXH\VbPJ\bPPZbJbPbXdVJbTd\X^bT^JZPdJ\ZPdR^\\D^VL\LZRT^bT^\JRHbZ`d^^^hZXR`VV^^ZdHT^VR\bX\bXVhRXZTbRN\X\b^HfVj^\P`ZZ\XbTZLVbZHXR`^ZPZ\bXRZRbT^TXTRD`Z^dPXZ^HTTR`J^bdL`^N\\^TPBXP^X\X`\\F\bPV^JZXZ^VJZ^PNVXFP\^FN`lTN\jLXbdPfTPL`XR^\VV\XFT`NT8^X^f\dHbZ\dPVTL>RVbPbTdXRfVRFXTbNHTTZ^T^ZTXbbJ^ZbVP^ZDNPT^bT^R\bT`V\Rbdd\RHXXLfRZ^Rj^PXbRJZ`LXZXdHl^VTZd\JZP^TH\RZJbFVX^VTZT`RXZLV`Z`PTj@VJL\TT^RPNThZXJZL`fPXF\PRHZTP`DTPTX\^R\VlD<HNXZN^PPRHNTVJPTR^^PRP^R^b`HZDh\XXXPf^VR^VXHZXZLTJX^VDXT\PVVZJdZLPVVZ\ZJRVRR\H^bRV^TP`PLP\PTZFZHJTNVPTLJ^VT\LXJLVTXj\VLRTHlX`NRJR^dPZ`R\VPLFlNVNXV\\\DP`FR^PTPXLVV^PTVPXRTVVVX^RP\\X^LP^\^FfPLTVRVZN^bdNXXRTF^`ZbVTPNNbPTJX^\ZLTPL^NXT\P\PDVVBRZPFdTJPHLjRXN^nPL^NRXVTFZDbTTLZ<XLNR\V\`ZZNXPJTTZJJ\VbJLVXPTN\PZdVT^hJ^dVbXZX^TXXXV^^`VRRB^TT\RT^FXP^TVVXf\TZTZX\:LZN`JTVFZVV^bZZfPZPRX\VVbjRPdbZP\V^^XNZFHZVTPVPTN\V\Zb^TXXVNNbbTNN^JP`TbbVXP^dPZZB\ZZXVTFJ`\PXZb@^ZL`XZZ`RNPbVZXXXZRV^HdRfT\NdJV`bRZ<NRVX^XPb^ZJZJ\XVZbNVPRPf\P\\`X\bLb\^ZRlXfZ`X^\JZ^PJRVZfR```RlTPXXV\dfddfNNXRP\RfLP\T^TRXfJP^ff^VbdRd`R`VPH^dfV^^@TZRLXdN^JfhNPTNTJPTbVPNZLZBZXLVTVfT`VZDpl^hRfNT\^\l`bffRRRdXVNd`LdLdPZldXTTRNZ`R`\XZfXbXVRTBV`^Z``VVZZ^ZZZbr\V^PPNR\LPPJJZ^fFLRLV\NLT\TRX\^^VNRLPPPTRbDJ^VTf`TPJ\\J^\DTPNRJL^V\NN^`HHPJ\NT^`V^XXP`LNNV`RNXZRT^X\VZlRTJhPXZPdP`NV`ZPXPTDRJTLLbPZVL^Lb\PRX\JbRPRZjZVXT`VZbJdV^.b\VTXLVbTZL`LbbTBZdf^pRXZ\`LVbX^P\L^JV^XT\XFd\^XVXP`XR`RRLNDlXb\LVXT^T^TRX\LVZZ^NVXdH^JL`ZVX\VXh\PhLZVVLTf\RZ\^bVJXPZXZXPNRNX`VP\XRbbXZNVJh<VXRZVXR@`HLJNL^XLPVJZ\^^X`NdP\bRP<^FTVPhP:jZTPVZPZX\XH\ZZZZTThVNHb^TNX`XVPZVXVXLLTZP\^XTR^bBRZFJ`ZVNbfZXVV^VPVNXRNbFdhTVLb`NV^NTLP\d`XTXT\XVR^FXLNN^VXLRXF\\DRPhRXVTfVTbJPVZLPXRR\`ZVT^VH`Pd\TZXVR`TRhVTPT^R^PRjVXdXT^\VbNd^V^`XT^V`VHVN`NRT`^`RV\`dVNZVTXPJR^X\R^XH\V\ZTVXV\fRVVRhL\Z`J\bR`PPN^NJXXV^Vj\^Z^b\XP`XVTVZXV`^Nf`X`PTX\bRVdVNRhL^TVRLV`LVbP`^ZZdX\Z^Z\\T^Lb\VZNRdVRRZBXZNdZPZPZZR^b`\NTXVV^\TdTVXbTXZ^XXL\TX\ZZ^\HXR\LRR\^JrR\VX\ZT^V`bTTN^HVPZbXb`VPZ\Jh^Jdf^dVj^`bNZLV\\^VPZ^\``^ZhXZ\\\dZ`VX^fTbX`d^L`XZ\N\b^ZRT`\JZZJZTNb\^RT\\LNfX\PTXbdZZNL\L^ZZ^VfPNTZ^VV`R^^XZN\ZVRXNLXRTZZFTVPRXLPPZ^BbR^LRZP^NXVNXZTXTVjVZTjBX`ZPPRR`NV\VR\dLdZPVXZHR^XRR`NfTPL2Ld^XT`RLhVV>^N`b\XJhR\R`^PDb^`ZbVZ`\RdZ>`FPLVTXTXVR^NXZRP^VXLRXPb\LXfRFLjTVPV^\PZXRNTLLTHRV`T^`fRPPLPRX^RLNdRTLRTXrR\TZ`TXV^b^VVRP\bZ^PNdNRVTTVPN`XVh^Tb`XHhP\P^\RT\>bVP^TPRXfJJTVBXRVXPJ^JPLXHPPTZf^RV`H^VVHVRVfV`\\H\TRTTRVTRZTPJVTfPTPV^dNTNVDL^\RdPTXTNLVT`XXf:ZL^PPbT^^N<hLbfTXNVh\H^VXLV^dZHNRBTTVRHTVPXTPX\RVZXPTVdb^\NJXZDd\(\R`PZ\dZ\RVPbTVdL`P\\NRL\hPVRVFH\NXVTRN\`Z\ZRdZbX\^j\\^\ZNVJXPRD\R^dLb`XXVZZBXPNPZ\^RPL\XXbTXXZVVLZ\`\F>FN\ZZ`DZ\L<\ZZXTRPTDjZZ`NZZL`ZR``XJXVX`@XZVPVRPT^bPbP^P^Xb^N\HTT\X`NTVdT\JbV^bb^N`^VXDZTZjXHV^bVXRRRVTNP\bVZV^V``ZdVbZRTdT\h\VTXNXPfZ\f`TjRR\ZVR\`PZhbT\TVjVTVRRN\fhLXNVRLd\RRPTTPdJL^\VD\P\HVVTJRXZRLTRVZXPTXNNFPTRR^XRHX\XZJVZLTbR`PHPZNZTJBhP^DJX\`hbjnX^NfNfhb\NXPZPRbJPZV\RdH^NZ^PRV^XhT`d`V\PPVXRhVDl\fVZNXR\VT\V\\Z\`^fRZHTXRVJV\\XNPb\\LNbNJXPT`:TTPVX\TVT`dL`\XTXXZ^XTVNJTbbbV`T`T`JTNXZHZ^^V^FNf\R`ZdhXVb@TRbHZ\bJ\P`XNZPXRXNVZbP\NJbJ`ZNN^LXVTTLV`P\LThR`PT\NTZVXHR\^ZR\\ZPTPPhX^PZ^lRfVX\RT`dR`LXVNJdTjHf`NRV`VNP\bLZ^X^\bHZPNX`bRVdRdLb`V`XRZ^ZVNPRZfbbVLH\ZNXV\dHZPb^\ZLTHXLTXH`fZ`LbTZVRTX^ZRR`RZfNXJ\VRRJR^Z\VTPZZXTTNZR8J\\jNTZX^R\LZ^XTVVZZLRVZVPZPRPXVVJZVP^^P2RX\hLZ\ZT^Z\R^TZH\RVdPbLbX\TdH`^Z\NbjPdZFNXVJV\Z\\VRVBRbNJ\ZRHHPRRTdB^H`X`ZPZZXhRFPVRVVVTTNV\NXBLVXZZN\VPRXLL\VdpTXNPV`Hb\bR\PNR^PfNb^dXV^LdXNTLXFVHL\PZ`XXZZXT`NNV\JNRVTJ\RHZbVZTZR^lZBPZVPT^TfbX\bXZTZTTZ`jT``ZXh\XT^N`ZL^\lfTXPX\X\\Vh\nVZ`d`^^JpRbj`JTZjT`p^TTVjbH\VN^T`^TZd\HZ^XX\JXZXd`LVZhZXNPZ\Zb\ZbZdZ^^^J\ZNZX\N`Zf\Nd\\R\\R^^RNbPn^^`J\NVL^RPXP\XVX`VTXZRXZP```^PXN\B^XXZZR\TfR\XPXdhTNVPlZRP`P`ZdFRHdLddP^RRPXP`XT^X^X\J\P\^^bFRL`^XVZX\d\VVVX`RdfbX`PX\RPVR@RZRT6JTPT^TXVfbVZFfXdZVdVVZNpZTl\PTZjF^dRNP\^^ZXjXVTZ`hN`XT`RZPT^HJTXdZ`RR`XNHXRZZJV^VXH\JZ`ZVV`N\Dd^dR\Z`X\VTbN^NV^FZd`^BbPNTNXZLNVbd`V`^\TXZFPZZ\NPXTPX^RdZNNTN`LP`HX\TRVNN^JJXTVRRJZBZHLPbVZbTDbbTP`P\VJV^^LD`TT>bLTZbNH`TTjZN\Z\VZ`ZNJhVZ^R`\TX\RXLbLFhdZb\ZJdPVH\ZbXLRbRTLnLV`XTh\PVLHlT\RNbTRL`TZTXb`NRTJJ^\VPZXNXD^T^JTZ\PJJTT\\ZJZNJXZPd`Z``RVT\dJVXLLhR^bjXT\J`Z\VL^^PFVbVPR\^V`XTRL`Th^VR`\\XR^TP^RNbL^T`P\XTZPLbN\ZZR>ZRZTXR^Jd^Z\FJTdJP\RhT^XTV`TNPPZF`^^LFRNbVP\LRb^^\NHZh`bbPTRVVd\VHbV`^fXR`\`ZTTV^JJXdTfXR`PRVZXR\JNP^^^VL^XTRdLbNVVRT\XLXV\T`RXN^^T\T`FVRXTV\VP\^\^VVJ^fZd``bRf`bX`ZRPRlXZNZZXLZFZRLNbZHX^\NLJZRNLHTRXRRVTXX^RLR^ZJZV`dVNV^^X`FXVH\^dXXRTPZTLbN^VXTZPZRRTbL\XJb`TZXTTNPXP^NVTN^LHLX^PPRfZV\RZV`VNNZRXNVdTPRTVPRXP`ZZ`ZTZVZX`RZTPRVb`T`XZRJXXZ^XTNN^\NZ\f^T`d^Lf\\VX`R^XVZXVZR`dV\fbVXLXTb`\N\bXT^ZV\`PDZ\bD^LPXN``^ZZhDZPZXD^bbTRb^dZ^ZX`XVXbl\RLXXZ`LH^N\TZ6\XZJ^LRXXP\TVbR\PZN\TdldjZXdVX^VX^jjhTPjXTRRZV\NTX\NdZJXR^Rdb^XbZVX^T`ZRVV^^NZ^b\^ZX\\\R^bfRZ\XbX`Vb^TfRZ\^VP\ZXNP^NZVbLTXNN^VNVZ\`\TRVZTR^j\d`XVRdfXRVRXVXHd\RjTX^RJTJNV`XTTPL^VFTPZVT^^X`R\Hb@jPPVRZHN\TfPZ`XLFbPZP\ZLRZRPRbZLZXVdV\RPTP\T^XbVB`PZRTfVNVt`BLJRbFNJdLXbJXRdHdV\\J^\TLfX@XVRXLdbV`TRPX`PXDHTJ\\PXX\\fTlLfX^P\N\XNVJ\P\NTZ\R`PTZZ`XZ\VVhJRV`LBPPFRN\PPT\XVZR`T`^RT^NXXXbTjVh^VXRdZ\RTV\J`DNfT^D`^NRZVR^ZJfZV^VPTdXVZXZZPZbFb^J`^\XNV^Z\b`\HhF`RXPTTbPfXHHZbL`XRLPLNNR^bTJX^RPLT\`LXTXNP\\^\\PN^^XLHR\X`Z^`R\LFZbdV^bVNTNN`VLNdTfb@RZZ^`VXVNN\PV\R`ZZ`dZN\BXXT\LLf\bVZVdNTTX\TXX\ZTTJZVZJXDb\VZZ`Zd\`JRPT<\ZbZX^fLXX^\\NZVlbZNfTRNP\T``FZ`LVTVZXT^RVVVPZ^N\`TP^PTRTZdNT^VTddLVd@TZXbZTXdTPZRR^XV\LXZRTHZTHdR^nV\ZdN`R^R\TP^\XVTJZLXVdP\^RTJ`XR`VdP^ZNvTX`TTR^RTPnFTVh`PR\fb\hdRT`X^ZNV``ZTT\^f\RfXhPVVbZTj`ZZZdRVTdT`X^^T\TVVdVZ`ZjX^PNXbF^XT`ZXVXdXbNb^TL^bRZ^\^JRhTT\LVZPjT`XP`ZZ^`RP\NTdTVf^`bhZ\RZVTZ\`\\`XXb`\PZ^fVRP^dVVNT^FZ\NVZT\XP`T^Nh\^VZZZP\XLTZPRXRJ\VRNd^XLTR^T\V`LPXJ^Vb`V\PT^dRJXNVdXZbJZXLXVXTTLJTXJbRJT@JHFV\P^JXTVRJNZLRZNNVXJHPLXPZXZDP\TT^JRJ\bNZN`JV\\TPbVbLXV^VXPFZNX^\NbR`PNd^RPH\TND^\PZ`VN\XNNPZNX^VXVl\VRdhR`VTRP^Nb^LLZ`VRjRVNJ\RTR^`TTNJZRFV\\RPNZP\Z\BVVd^`HNXV\VXVNVVR`X`TZ\`LX^NVD^fJ\R`XXPTPTZ\T`Lb`R^VXRTXNRPdNXf`XX\VZHP>ZbRXP>`VNZ^RRRRVbHbfHHZP\H<X\TRVNbZ`ZTbHVRRPLVLbDHT^\`LX^NV8bRXXhd\ZdLT\dL`FbLTRJTPHRVVbfZXZXV\XX^^>\bR\VXPTV\P^RVZ\Z^HbNNXXTVZX\RXPXXTPXPXXPV\TXdX\XL`NTLNNZTHJPLf^NHRP^HPZNfPbJNLVNXZBZR`VNZTNHPL^^PR\bXP^NbVZRlTJ\LTVRVL\TH\bTNZT\TH\b\f^VTXbXVNVNVTRLV\dRdVdZTV^DXNXZfDZP`N^XH\LThP`J\TPXLZRTRL\LVP`XnTVTZ`R`V`H`XdHhVNXfZZ`XdNZXXZ`XRN\L`^hTTR^PPP\V^TTTZpX\TZXTNXPNdH\LRXT^d^Z`^NPd\VDhPHTX\PT^TX^lN^\\Z`fPZ`RbN^PPh^VLLVZbXJRhZJNZZdP\PXXZR`bTRV^`V\TXPbTj\TR\JVP^L\F^`ZX^X\\<^PZ\ZRTN^P`R>dfVl\^bdlV^j`TVZTfVTpZb^P`\hfR^VP\TTjTR`^H`d`bX`N^dlZj^X^TlVhRXHdXL^PL\LdPb`VF^RdZX`HXX`V^<lZZdTTNRVJbdNP^^F\N\VNZLVZZNL`p`XV\JVNbVTVXZ^VXbRHTJN\`\RH`bRVTj^PlZbTTbXVVNTX^LRJ`XLb``PR`jXLJPRTbJXbVPRXZT\^Z^RX`L\VTXRZ^JdX^\V`^bLXRZRXNTdPPHbNTX\\hJ\RRF^\^X^Z@Z`VVVVLX\THbLRNNZZZ\\X`TJdN\fDF`JZ`TDjLFNVP\VR^^LTPZNLb\NbRTT`LVVR\h\bfTJZZ\L^`TRXTZXfNTPXJRjXZV^JXHTV\`\VXR``\JVTTTRXJV```\XbH`VRVV\FVXPfRT^`R^VZ`TTf`ZJRPVd\VbP`VZHdDPJ\VFZRVXRZb\`\dDXPVTZL\bPTVNT`V`NfdPVNP\^`TPd^PZbP\\^X^LPZT^R^T`JTdR^NN`TZdRXRTJVLdP^\ZDRPnVbXdZbJ\TP\DX\JZZXXVnTHVPP`XXFJ`XXHZTVR^\jNLVbZRfD`XTLbXTP\RXNVV^T\Nbb\\VPXfVRZTXPNHPPPVVV`ZdbRVRh\PTfPfd`NddT`\XL`Z\b^XXpRTXRLXXNNZV`ZZNVJ\ZNbbNb^^HTNRP^TVVPT^VJb`PZ^LXVRXRXXfZ\JjPRRhPJZNP^dTX\TPV`PV^XX\\ZJXNZLNVRZTlXN\bPj\RPVXTfbPndF^VTXbfZZP^bZ`Tb\TX`VP^RbXL`T^RZZbV^L\\RZFP`TZP\ZZR\fV^`fdX\\XVXR`TZbVVddT`RJ^VZZLX^T^PjNPdHVHTJd^HbRJX`PFZLbLXPJbTPXVJ\`VVHX\VVXPVfb\RV^XZ^ZP\hPXFZbVXdR\\^bhP\R\`RbZ`PTlXXRL^TjVVD^bThVNNbRJ`VPPN`dTbVRdPVZTXDVZRX\THXV^bXfTXVJT8ZRRPJXLT\TTFRPNVNPPNPVRRNN\ZRLXTF\V`JRXfThN>TT^^TLTJXXbTFRjT@dTRJRT\VPd@\BXLbB\\DdZDjNPbX\dNX\RTT\R\FXNXTJVXLJhH^D^LR\PX\HRVXPVZRX\XRR`^dX\VbJVZ`XZ^VR`VXT\VHV^Z@ZTLh`P\RP`NlJZ\XJTR\\T<ZRZLXNTXL\TlLf`bVPPT\TPZZbRZPb`VX^JV\VTJNVR\^TNb^f\VNTZHTbZVVJf^\RTTdLXJR`DbbRNXVRLdVTd^HVRdhRHPVT\dTVZ^TTPVX\XRN\ZXLZ`N\L^JHRbL`HRXV^PZZ\Rbf^V<RPXTLTVLbTNP\`RjN`ZbjVPXR@bFZFRZP`\\nVT\NdZXdXZT\`H^RTN`dRPdZTVPV^P^NPZXL8ZZV`XNP^>XTZNXN\N\L`Xd`\JTJPZR\T\RPHdHXVX^^ZVNT\hZ^dVF\T^PPZF`XRZP\\LNVPRT`TNRNRHTX`VX`ZLPLPN^^\^\ZTR\VVNPT\^\Z^JRVX^JLVTR`P\TV^DbVN\FVbfRXPNVXPRJZfHfN\`^XTRVPb`LVR\\fZbR^RR\HXZZ\PT`Fd`L\XTdVRbT^VDZVdfXRVT^ZT`ZZdPVZ`VR^bTbXVLbHVbV`TTXVjPRR^TbNXdZXLP\X`JPXVV`V^HVV`XHPRb^TbRJZVNHHPLd\T^^Z^X\LRfF\^b^NVZZfLTdbb\RVZXXPbRPTNbN^bhFPbVbVTb\PTT`PTVXVZT`Jh`NjRXPDd`^VZPNXZdZRJPbRVXV\``RJbRLL4RbH`Z\XHLXfJR\RT``\\bbNll^NX^\\dl^VZf\f`bVbbZXlfTPXdVdH^bbXPNXRLPhLVdR^`RTHV\`DPT`fFd`ZVN\\^ZTTF\\TX^\N\n@\NdRb^RbHdNbL^RbZfRRTXV`BLVH\ZP^PPHFXP\PJVb\\\P^\N`LV\T^V`VVbVXZVF\^XVNdTVNV<p^`RLX^VTT`\R^FRLV^bZPZB^TVVVNTVjZ\PHVTPbRJZPZBLfVJZ`\ZZXTb\VZTRHRPV^NPbZPdTR\ZNXRZ>^DVZ^VVRRRX`\JTX\XV^L\XZ\ZTXRZRRRJZ``R\\TJ`PZFXRXbTZPbH\`XRZX\hT\VVPJHb`XT\PRZ\RP`V^TPLVRP^TbVP\XL\TfVdZZZ`^PPHhVP`bVdT\TTVN`^RPVd^VTNXZV^RZVPRZTTZbPRNRX\^^RTJ@hXPVNR\\TXRLVZR``PZXFZ^TPbTL^JVTPbbLNVfVhNPZ\XZPN`VVTZL^ZfTTJVVRP^N`TPLXVXRJHdPVRbR^PXRbVPL^LPR``JVPXX\XTLRT``TXZ^X`TV\fT`VThRX\\H`RbR^VRPV^Z`^TP\T\NZF`rVZP\ZPH`bL`ZNX^`^RT`\NXNP`PRTXVX\LN`ZdZH\X`RV^\LZb\XZdRXPVdbXTRTdJb`XTdZ^TTZVXLRVVZNF>N`\\VZVNdbTR`ZTT\VVHZZZX`TZ`P^^Z\NX\`PXVX^`X`^dVXPVV`ZV\VV`NDH\XHVTXXDdVT`^`XZd\Pj^LdTXJX\pLp`\\TVTPLTJRJVZVTVVdfZ^ZX^bRJf\R^V\RXdPNTV`T^ZXXRbBVdN\V`TLZ\^Rh`ZVdFZR\Vd\L^nLHRJdFbXJTPVLPVZRbJT\RVDVVXRX^TLPPN\\RdV^pbb`HbhfZRVddfXNd`X`bhZPP\X^dN\XNd\RbNfL\V^Z`dT\VP^hdVdd`ZVT^RRLX^L`\VZZV^LVR`VNPP\^XXdTXJ\dZR\\lTZN^`bPZN^^XX^JPLTPTRZ^HXJL\XHdbZPRXJ\FXZJPB`ZV\ZJdPZfZXTHR`bVNH^`L\NRb\^PVPJJ^XXNZP`VXVPPTVVPZV`LVTHZV^\TXXhRV^dVT\N\XNZZLbX`RbLNDJX\bPBTRfZR^RJL`P^JNR\HdL\PVZ\RNNVZ`PXPJRXTNT<`ZTTJVP`PTR^PZ^`NJTFX\XLhTTNjZLVHZZNLTJRPRXPZRXJXHbRR`TT\TR\T\N^VXPZHRTT^N^^RBJP\bPPZNPXD^VXVR^NVVNRV>TZ^X\\RH^TVXR\N\TVXV\TZF`LLTVRV\XRXLXZHXRJXXJTJ^R^bb\L^PXN`RTZPRZT\V^fT\\RVdVLPdZVHd>bV`NH^V^XLPNXZ`VJ^NXPHJN^XR`Z\bfNLTTbD^ZPX\^ZXLhTX`HXNFPVTNZL>XN`LRZ`R^VJVXTfZTLTZZRF\ZXVX^^TRVN`VTZXVb`\VVV\TTXX\Z\PX`PN^fTLZ^N`TXZVPPTTRNXb\HDV^X\HZVZfHZT\\XXNPPL\bTRNVTZdTRTTTPbfTbR^b`XNhZPV^D^bRRLXV\XRTP`RL\JXHZ\`R`XRXPNXZZ`^T\XT\VPZ\Xf^XTV\Z`H^pXXDR\XXTVRTbP\T`P`NL\LL^\FXVL^PT^`\XZV`TZTR`b^TjTX\Fb`VjXXP\ZlRZVjZPZVVZPTPbf\TTL`ZRV\ZV\RTbFFP\^V``TZbh\Z^RVXZZVRNRPVVbPRRXXRZ`bTVZF\NHfJTNf^VRTXX\TPPVZRJPXVLRX\RXPZZXLFdbfXf\\Pdh`TbbRdbVX^bZPPjdVbhXVf`dX^^FVZV^P^NddX\V\\d^PfXVLl\T^NPZLNZTNR^NZZbZRfFNfRVTb^`RTJX^RfN`DZXXZPZ`NTPNZ^V^VRf^VlRN^PhLHdJ\VTHNdZV`PPfVHLZV\NFP\RZTT\X`ZX\VX``\hXL^b\NZR`VNXNXVhJRVXPTLRfL\RXTZbVZ\XVZ`T\LdHHf>HVVVT\LJ`RTZZXL\PP\LZX`TbPdT`FTbPb^H\XVNb^X\^T^RVb^ZVJLZH\^`XXTX\TXTZRHV\TRT^\^RPVRHHnTP\^NXVZRXlTdXbRXRBX\^V`R`XVRVTbTLZ`PXXXTV^NVdN\ZbXVPVTR^hZTLbDXVX^JPTXVL\dZ^RNP^TXZXT\\^VVb\tZXTVRfPZTXbJZTTPNhZZ\ZRZPbJFT^T^LVNRHNJ\DXNZX\JHNVPVRT\RXTbVTbZ\XXJPnRbPRT^\^^N\b`X^`VLNR`Nb^ZRLTVd\^\TL\\XD^ZLR\VPTNhJX``^d`XFbX`\JZZTV\XXPT`RDTPVRTTTFLh^XTPP^JVVhTFVLRbJRZdRZZbZL^FTVR\^TF^N\fRXNdVHjVFb^dTTX\ZXRTRhTT`R\`fB^LTNbVV\LVZRVRH\PbPT\R\^RJ\^ZTZPHR^^X^bHVZh^`JV^JFXHR^bVP\XbjPZLVRZ^`^J^dPXbTbT`dbfZVfR`NTNZTT\XfRZN\ZXhNXT\NP\VJfZXf^X\^`TPZX^RTXVVh^``R\d`Nh\TXVpXFfjVVPZPXVZbFVTT``dN^R`TV\L\`Lfb`VXffTT\ZT^XXVZRV^RNlJZRVPLZVRV\TVJXXXVbDTLdL`ThTRfd`\\dZRZT`^V>XZTX^^dJV\X`ZXfTJ\\XVX\Z^LbX:^N\\f`V^fdbZN`ZRN\bR^\XNZLZPZZNRZTZZ^`NVXNVV``PPH`bPLVbRF\bjXRVbLNX\dPfRbRZfXTZ\VV\ZVdHP`bJVLRTHLLZNTFRTZLVfZNRZ`NXPXVP\RZZ\JZJZPXVVXFN^dFVRN`ZFZXVdNdD\VJ`LZTRVV`PXNRbNdZTfZZPZ@\bL`F\^XVV^>\ZLXLPBN`VVP`N^VLRTFRXHPL\RTZ^RZLXHNX\ZXRL\\V\^TLVR`RX^d^PZVFRbPL`VPLdNRTb\`PRTNR\j`F^JLTdb\ZNNLVTV^^P6NR`PZb`PNPLLVR^HdTFT`^bTHNPPT^HZNPJTTFJ\XRZX^RXZRZP^X\BPT\\NVF\VV`\ZV`fFP\RJRPh`^XPPXbZ`jRlfVPfBTVX`dVPLXDVP`NfbXZHVJ^TTVVJRN\ZVVVX@bTXNPPJVhJLFbD\RdLZX\PXTXRVVXHZLPRbbZNPLXRJ`Z^VX`XLPRZ\ZZVTR@PZR`NdRV\NN^VLR\@TPXXLX`VdTZT^VXTX^@XVT^VLbPP\ZZ\`RVRfbRdVRFTT^LTVVR\`^PfNbNXRPXZZXbFTZNP\`TTTX\`J\^DhXH^PVPbPdNR`^T`VV\RPV^^T\nXL^ZdRX`\VX^ZV^Zb`TTHPZVdV\TVbTTTVVbTDfPdNPVVNVTTVLdJdN`NJlZNXNrNb^R^Zb\hV\NV\T`lR^TVZVZ^hNPVbf@Pd\ZXXdRb^XZT^\TVRjhTT\XXZT\bZb^lDPR\`NTX^V^ZFRFbL\LfPTXRZTRZRJRNXXVTTRVX^ZZP`PVLVHP`P`T\XZRdVX^j`Z\`pRZLhNTZ^hRFZ6VdTb\PZ`^`LXb\T^\ZRTTR^dX\HLbVN\VdP`dR\HbXfX^`V^VV`Phb^XRTTXZXHRdDZZJVT\TP^TX`XX\RT^XZ`^RhTPRXdLXPXXJdZXZ\bJV\RN\^PH`TTXV\RfVZDZfNzJRXXZZ\HlDdRLXJ\NfJT`N`J`XTZVJNdX\bX\^NLdZPPVVXL^TXZ`VPPbTRTjVNX\hbJ\XNTVHfRf\@V^VTNL`fX`bTPXTTh`jVTVVLLbRZbNN^T\JLNHnPT^VZZBfd`\ZbPT^\PJRPRlX`P^ZPJZRTTRJ\ZPZPRZRRN`<ZZRRRPPF\PZBN`NTbLhTLPV\nXb\`LbhLZR`^`HVb`VXbRXXLJ`ZPXNRPRV``^ZRNRZZn`Nb^d^TT\VPTP\^.TRN^RVfTZVXNbNJXR`ZZJ^\L\\^L\LFRVRZVZR\jTNZNN\JVFNLbRNRZ\VRZ^TRPRXTZdZ\\R\P\\ZLT`^^``XXZP^NZPN^^TTVH`\JTNP`L<V`RTZPPZZTN\PRJXTXVZ^RlbXXd^V`T^LNNNbdTVZPV\RXVJ^R^dD`NZNX^TRXRNVXPX^RNhNTLP\T^LJ`ThPT\\RLbNNTf^RX^PJ`ZRP\^ThPRZ^Z^H\RD^X^XdXJZ`N^TDVThfbFNN\XjHNPZX`\^\^V`XXZX^^J^L\T\TbVV`Z`VL^X\XjR`ZZbbVZZ\R`NXZTZF`HVfJdbZRjf^`RjXJHjRZf\XbTT^L`PV\VdVLVXVDVT^fTVR`^\dPP\`PZRNXRX\RX^TZVXbVfPXLb^RXZZ\VR`PV^T\XVDRVLZFTR^P`ZP^VZZPXZTZ^VTZHX^`RTXTNbLXJV`hV\RZlZfF^^XVRZ^L^>T^TRV\VTRR^ZPXZR`Z^^T\`XfVN\VhXRdPZXTR\TPb^XVZXRX\ZVXRTRNZTZN\VRR^JL\bZ\TV^DPd^NP^X^XJXPJL\`<jTT`\N\TV\VLTLN\HRXhXVZ\RTZZHX`ZJjNZPRfF^\^bZVBbJN^TJVRNTHR\HRXNRTfV\PZf\bTVHZZZPHXN^NV`TZZPTHXVbPXTVH^L^dRJpXZ^\ZNZ>VTTTP^VZB\b@PTdFTL\ZXFRDTFfbPHTX^VH^NT^fV\\B\`NTH\PVZT`PLRRTLbPNRXVVXFNVZNZXXZ`LVfNVZJRTRLXTJdN`XXV\ZJXNXRZRRFLZRRPbJ`ZXZN^THPjZPRJNPR^NT`ThVP^T^DJXX^b^R`\PRNL\RL^`P\^TRNZDRbZVRNBb^bVdZR`\P\j`RZNRBPJRVTZXjV`P^jXP@dVL\fhHN^L\XR`bPJZV<XbTRhNJTfT\b`HXXTVdZT@^NXfXHV\^NZf`d\L\V`ZVXJ`ZXRhdZ^bRTfZ`ZRdR\X\fH`PTNF`NPPNRTR^^XNLZ^FXXdVPNXX^TT^J^PL`HTV`LLZjV\`TTR\LX\^VJN^R`XNRXR^dhXRJXZTp\ZZbT^NNZN\LVVZHZLbLL\ZP\TXTZVZ`Ff\VP^T\\`FVB^R`VR^VJbH^NZX^P^^^HPXT\TT^RZ^RZZPLLNH`^RRXZZdTJbTT`^^^XbR`Z\\JZBVT\X`\Z\NPXZ\\\fTXVR^LVTVP\VLXR^XZd^XTPRdR^RLTJXZV``bNb\Z\fN\TRZN^XHJPXNPFZTT@DXb\Rd^NRXDZ^\BZ`TRdLVHh>LV`f`^l`hBfh\X^Zb\ZRZdTR^R\R^\bbV^\R`PnRRVbX^\Rhjb\ZXbfZ^^ZPdVdTPRXVZVXJ`ZXR^ZRNTH\V\Hd^^X`bXXJ`\bZZj\FZLV^`NPbLBTTNRfh`JXP\R\ZdRVVNV`TVVb\PHj`PZ\b^`TN\`J^R^Lb\HXHfhPRVVVXdLFXXLjPVfZ\T\ZZZJVXLTRVXNXZ\L\hXLVfP^ZTPfX\JXZ^^``ZjZP`bZ\XJ^TZdZRL\FfZJZLHLZRVLXXT\^L\N`^ddPbTRZV\\`\VN`Hh\ZPlT`V\PH^XRRfPJ`NVX^jZ^PLfTjTVXJXVZbZJRVXRRRbbbNdHbNRZVXfhPVRNX^ZNJR\ZRNV`dV^PNBJ\TF^XZ`HfTLHHTRL`\TPFTRXZNLPLVTT^ZNT\T^\XTVJ\b\PXVPXTN\\Rd\X`hVbTJTNHT`ZN`ZX\dXPZRbTZXXLNTVXXJdXb^\ZTb>X^`RTPZXVdZPXhVJ^\R\BVTPTTTR\LXRTRTXZZTRhR^\X\^Z^VRT\h^fTZVRZdNZT\NPZHTDJTdXVLZ\PNPZTX\^N^NpXNLVTPRD\\N\PN\Z`FNRHXPX\X\L^ZX^RVb`VXXXXXT`VZNX4VVdPZTb\HXLZdZTRVRZXRbJ\^ZTRXX\\NVdTXbRfZZVT^>bVTRR^`TVZRRT^JPVNXJV\F\Z^dV\`\PV^Rd`TfH\NT^`RX^^`T`PZL\fXPdTTZZ\fRbVHd\NTRXVPd\TdhX`dVRL`\Z`PZVVP\ZT`Z^bVPZNnZR\^PlFVLZddJXZ^`VT`\TV\\`V\VRV^V\RXTDLVbd^FbVRN\b^ZX\N^XTNR`F``dfRlRZXXTZ\T`dTDbdJ\TZ\T`\\dRbrZX^bbXX\X^nbPNb^ZhhjbRdJd@Z`bdRJNfjR^XVZ\V^fX^T\VRVPbZfhBb\LVVVRfJP\XNVZXbFZ\VPfZdTLHRVN``XNT^NThTZ^JJD`P^LRJVhTN\`RTPNbVT\b\B^RRXJJLF^P\ZV\VRRJLTNPPTXTRV\\TXJTTNVrRJBPHVZJdTV`RZV^LNV\P`PZVDbRPTL^:XHV^XNZ`dR\R\LLHNZ^RV``\`LZRRF`T``Z\VX\Z\`ZNZV\\LJ^^XTbZL`TZNNRZPVPLdPVHZTTHL\HP`TNR\\TBXVZVL^XbRXRR\PZ\NNbNTVZXVJ`Ff`T^`RRdPRTZVVN^RX\fNNH^HZ\H^bRZNNL^NTb`V\jXN^X`LV\TVL^fbV^ZPTBTRbLXd>\TN8V\XZVHPX\HNXb\H\nZXTVTTRLVVTVdXZP\VdVR\XZRRNVRLR^PXZVZD^RFHT\VVR`VZ^ZZTLhXTZJVXL\RNXV\FPFdPZPfF\ZN\\RTZ`TXJdVVTTb^PLTL\NLLZNBXBPRPXfT\DJT^jRHZ`ZZDHZ\RRR\XZTPVTfdPLPPRZNHXRTTFZVNLL\HLZVVTXZTFTN\NLXXRN^FVdJZRTVTNb^`bJPVZTTTH`\`^bTZV\ZR^bRJVJdVXLVPTXBPPPXJd``dTP`dHbJ@hPV\TV`H`VXJTZFLVhRZTJV\dZLXTX^Nf`fPbHL\LRbLVNVbNZVbPTXTdT`\Z`JRNP\JN\bDRZb^VdPTP^TRPNT\ZTVHP\V`ZHZJ`J\BXTVb^LXdXbPbZ^ZRRZRPDVd`T^NZ^H^NX^FhZ`LbF\NfH\TJ`dVJ\fZRXPfZZR`^X\RR\HVZLXJ\L\fVVhTR\RVPbLXLF^TT\``V`^NX^\ZPNJb`^>^fPP\bZHVJZTH^V^d\fvN^d\``PZRf`PbdfT^VfZZXdNbLdPZ^bhZPTXTTjXZdP\bRfXRfPZd^R`XXbPTdVPHXV`PdJ^bjN`RJ^PVXRbRNT\hLLJDVR``TPN`LdTPb^VTZFfLR\VZ^dPLVfRZdRRTX\VL^dLVN`DbLLX`ZbbPFZFRXZPPTTRP^ZZVfLVbbTNP\ZZV\`XdFd^^^lX<ZV^\Z`JX`bVXVX^FDXXdNP^`\ZXPd\``VR`lVVVZ`TXb^`b`RVRLRfPdZ\LVTV\V\R\FNPRNZTL\^NZRVLR^PZRZTVXVZlL^ZXRfdTPTXPTRXNFR^RVBHXZhZ>``RNL^FZN\TTdTRPR`^`RFXJVRRZRZJRTVJZXR\`LJLR^TZRZNZ\bLV@`TXVVJXZN^T`NRHZZdJVZFTXJ^NdPTXVZ^PVLLNZ^HfZj`f\ZTPR\XPXL\`PVZXP\\NLXPF^PXZXX`XXP\PV\\bNV\T\TfRVD\\^TJ^\RfRZZZ\XPV^Z\X\XLH`\VTVVT`j`FVdTPZJNNdVZTVT\\PTFPZbZTTfPPPXT^XVh`VNNfZXJJ`J\L`VZPV\^H^RR\PT\^X\fPN^VVR^PPLN^j^TdTL^`TXVZfPZ\TdZVPP\`\DTHN\^^XJ\RX^`^ZRTfJVb`\dX\^H\RfFZfDZZHP\PTLfXXT\`HfXZXdTN\DT`ZZfT^\`XXJdTdZfP\VR^`^\^VX^VDZPVLT\LbX`^b^TVlVV`\`ZZZXZj^VV^Z\XLVHTPZd^Pj\PT^X`NZ\bZZ\P\PNPZPNd^VXTZX`VHTN\`V`PTTXVLVR\dNXTXTdb\TXT`dVNb^T^ZVR`\hPP^\XdPX`T\XhLVRDZT^ZZRV^NXRNV`ZXVPPPFNZXXRZZbR^bfT^^\XD^VTPVV`J^ZZNbV^J^^hd^^R\TZ\^\XbRPjVZbf^Rb\bL^\ZPVl`bTXRXbX`L\fVNNTZpJ\`\TPP`RNZZXRV\P^VXfVP\V^\Rh\R^T\pLJVPJ\RDPTRBZRPJXHLPXNPNRLX^RPLRBXXV\TVT\\TV^\NbZZ@VXJ\XHL`^XZPN\fJRN^PTPXLPXLVfPbPRX\RRZP\RRH\VV@VXVfVLPPNPLP>b^TR^bBT:^XXRVd^dPRTNVVTXVVX\bJTVZN`PbLPN`^X`Z``HXbL\DDNXVH`hJ\bPNL^dJT`JJ^`LNX^ZPZPVRRbNX\VbXfZLJZZLfR\ZNP^PZbRbD^\`Rb`ZPV^NRDRT\^VbXRTbVbVFR\VTTNZX\XJ^TbPX\VdZTFVJVPX^HRTTfD`VbJHdTRFVLZdLZ^fZ\TRP:^^XPZ`TR^PLR@`JZX`\T^bXPLPXRRNJbLNNVXNTT`VRRXJTZTRNLXL\\`NHV\fNN^LXPNdBZBBXPV^`NHRVZVHX`PXZN\RFVNP`VbPZZR^L\H\LJZNNVXNbJXRPXHNBTPTRX\RXTXLVLjZLX\X^TbPPVD^NVhFXbLj^^NZbVV@LXVRHTRTVT\VV\R`Z`X^RTZ`\\^RRJRZNfbb>lRZVT^X`XfXPJRZ``XFXdTXhDVNN\\ZJLRTTZ\VDJjd\`\bdPXV`TH`ZJ`VZX`X\B\NR`LLbZJ`HTZVNVPRTZbPNXfPRNXZ^XTdTd^\^VXdLRZT^VfXRX\fVVbN^XbNX\Vf^\VZjdd^^\Z\\N\R\ZZ^TZP\\JfNVXLf^Z^\hDVNX`ZXbVT\NLZ^fZRPR`Xd`bZTV^RHR^TXZdTfLf\`^\TXXdRDZXX\bZTBRVb`L^\`PfRNN`TVbT`Pd\TNR^NbTRZPVrXfZf^fbZ`ZZNP^TbVXZT^^PNfZ`\L^Lb^NVZV\P^\RTXPZ`X`bV\bb^bTbVh\JRXZVLX\XTf\H^VV\bZ`BnZZf^\PbNPbX^b\`ZJJV\T\JR^RXT\^\R^VDTZ\\RV\`PHh`VZJV`JJDRTX^VXZ\\\NTPRTTTV^LfNX`NXXN`f`P\VXXZR^ZPRXXfV^X4RPP\TdHJLf```XNjR`LfTTXRRZfTRVZ\NZPfPP^PBPTNRP\XHTbLV\T^JR`TbdN\XVXfFX\JPLPZ\jRRXPXHdPTXZFHZZ\\TVNXPVXR\RNX^NJPTZLPRPRT^J`P`TjXTDZJ\hVZV`T\ZTRVTdJZT^@dNNbX^bVTPL`\L\bXXZ`P`VL\J`ZFVVZRVJXL^H\TPV`N^RLNXFPb\^PT^LTT^JR\HXd\lXX\N\`ZJfVb^PPV^VRRVR\ZPBVVLbNPXX\XXPLVP^L\R`bJZVXTJRJVT\PZP`\VNdRLRRd\ZXVHXbVd`dZDX\VRRTVZTTJRNRfV^ZRBN`ZH\LfNPXXLLfXTRRh>PNXZ`ZXdZLfRRTHXXZXRPRZPVTZTXNb`RTPZJ\HbLHlRTn`TX^JR^FJZRPT^RTHVXZXPJ^T``TRFZ`^NPZ@VTRXPZTRLNRNRVPbZNFJPTZ^JH@PVPb^^\\XJ\`T`^VVPd\ZTTVRXLV\TVVLZZRLX\HZ^XV\XR^TN^`T^fXRbbXXJff^TXn`P`\`TVXh^Z`XTTVXPLVdTbfNTZhT^`fVZV^X`ZVXVV^LNbVTlB`L`dpfdhRXPNXXXZ\X^PfPTXbTT^Jjd\\Xf`\NdVXPZN^TRPXVZ\ZdPTXZZ\bV^^RdN\VPT^fXdP^nNVVVPRZN\PJXJPVRHZdb^\XZVXZT^FLp^^Z\f`^v^^^^VZRdTNddPdRddl^VZTdPPZ`ZVVVZVbHZV`ZTLdNNRRNRFdZX`R@ZJPVXXZPXRLRP\NHBJ^ZdVL\JdPNVXH\^HJRPLHVZZRFZTZX^Z\BPRL\PZRNZ`RNXTPfTHTZLNNRRPbVVRVVPVNNVFTXXV\RLZRRRPHTH`NR`D\JXDLNT\RTNXH\ZP^VVVLXZPbJ^LZZVZVRV\TJXTRZXZTLb^hPXbVPJXHHXZ^Th\VZX\fT\JZPVNbT\ZXRNhXZ`TXRFVdLT`ZVZRLNZVV`^\N`JZJPNTVXXXJLZLV^VfHfHLVVL\^PNT\P`LRRZNVZZXVXd\JXXPPDF`LLXdLJPhXNhLfXXRPVXBJVNXRXdXRLT\N^NNXZ`HfZfJZRTPHTVLb\hTdTjXR:Z\RdTVTNVZT^^RPZBfPHXZXN\X^JDhXVdP\PVTZTHfZ^LLRVPPLRDZVX\XPVVTdDXRTP`VXJ^R`^JXbZTJZXXP\T^\X\Z\VPPPXVJL^PRFZ\@\VLJ\XLZN\JX\fZJZVXLR^ZVPP`X`LR\RTR\PV^FTXT^^VbTJVRD\Jb\R\RZ\PP\^`H\T\XLZhRJ`VRVT\`NH^RTRJT`ZT\VbdXbNZXXXZXXdlZ<``\\L`VNHX`NZ`PZVNhTJL^VV\RZNdT\PZTZ^jZT`RbTVTXXZ^\V`JZVZXR\^V`RXdFVHXXZ`\RZXdb\ZZ\ZX`XPXb^T`PZZjb^PXX^TLfXLRbHZb^dLLP\L\T\FTRTT\\HPZLbR^^JXT^R>XNjV`V`bXdTNZ\VLfVZR^X\\bhdbPH`^RLF`^V^VdfJ^fbXZV^H^VJhhTVNbXZ\\RX`lbddhV^\fXXZZXT^dR^V\dbNLLX\XXX^XVbR\TNbPb\`bX`Zb\ZTP`ZZ^bZ^JdRXV^^^VddL^f`TV^DVZb`X^^`D`RTZ\X\VT`ZRT\NndbJZDPVVTPP^NZRRVZZ\ZXF^\\X\XTbRZTN`PNb\fTVZVVjPZPRX<XNJLZRH^PJZZ^LRLVdXRdVFRXZPD^\XRRL^>Z`PP^HVZFV\dRb^TLT^ZRRP\^THPZXVVZ`PPPZ`\NX^LV@ZLVRdVJdZZ\\R\Z^NZJV\^\TPVX@TXZbZPZfLdXNRRZV\dVRHjXdP\ZZT`XPRVRZT`\VbJX`RHXV^ZRlV\LTVLTR<HV`XNXZTRJZ^NhlXX\Z@TT\ZbLVJZPFVNN\b\ZTdT^X\XdZZ`\PVX\ZVfVRTJLPVXV\Nb^N^NPT`fT^HRVLZ>D^XZhF^JLVj\ZNXZTXVXZ\RRbXbPhRflVZZ^Jl``NRTN\TRJXTZ`hVZ^Z\bPXT\bPTLTVZZ^RXRFdLPTP^`RXPZ\ZPd\RRT`VfX`VdRdnVVVNd\RFHJVNb`TTZPJh^J\PZRP`F\RRRLbZZ\Z^NXBVXNXJP^VfVVJV`Z^NXV`dXXTbbZZPXVX\XL^bZTXJ^ZTXbXRPPPbbXZT\hZZ\L^PN`JRX^P^d^ZDVRjZVRT`RTfN`VRFD^ZXXBR\`JZNPXH\ZbNZNfVR^J\dTZ\VRZ`VJf\XZV\`ZRbf`hJVf\^^`X^b`XN\VNT`RXZ\^Z\`VddTZNX`R\PLdb`RfNfLZfThVVb^TdP\R^^\ZXVZXZLHNFTf`N^TTZXRdVXTfLTT^Z\NTdXVR\TTNRZ\PPRT\N\NZZJ\RPTZVRdb\ZPT\^Z\HjPZb\VNZj`j`VbjR\TbTFdXVTl\FbZ\bZBJZZb`PLbJbVVT^XLfPfRRZHTT`\dNV^ZX\H\ZTXTRRRhXTf\X^\Z\PN\VZH\PTPjHZHbR\VT^BTVbL`RPLD\J\@DFVXZPR\`TX\VVXfdXNVPP^PRZb`VjTVP^PF^TZTPXPDXJHVRPFVdT`ZbVNPRLVTl^XNhXVRVXN^RR^Td`FdTP\FTRNV^>VLdPdL^b^XfZjPRRLZRNZNZTPTPNTbZPTRXNXPVPVVTVRRRL`RTRRTX>\J\\\`TRX\NJV^TZ^PRVPZ`ddZNTXLPRZP`DVHdVPFB^VVPPVRZHVdN^\PXVNXR`ZPNZHTb\\\VdXXTZ`VPT^TPBXJ^TV<\VXFJVZZRZVPRZDhVXRJTdFL^ZP\V`bZH\DNZPbZJ\hXVLTLRNPNNR^XNR\H@RbTbXVRPNFRZ<\PZVRTPB`@PNVdT\RNRVLNXHT`RXXT^TXZZPPNZPX\jHHNT\PXTZd\ZR\NTVNXbTPZRX^VNPRVXR`NN^RTXZV^NZRBlXXZVZfHZ\ZRPXd`<bV^VHZ\^TJRnXV^ZD^HHPVfTRVLXVNhJRXHTNX`fPJ:RZ`PlPV^ZRZR^\XVV^VX`bfVV^ZTHbVX^ZFVXRfXZZX\d`ZXb\\f\NPHTVb`NZNNRL`Vd\^TVZ^RH\^TbV^ZR\XVnP\ZTfP^\d^LbZTPjNRT``dLVPXV`RTPRN\LN`Vf\dZZJXNHf\PRZ`ZVPXZTNZJb^FVXPXTThRR`dPVRdX`VP^Fd^JZBTXlV\^ZVDjPTbJ^^jVR`XDZ^bPTNXPTHb\^ZbT`VNH\PTH\PLN\VZZ>DVd\>ZPTVhZRLVT`@^V^bTXRP`bPXXTPRN>Njbb^`T\XZZXb^fRVXVJXdJTVVVf`dbf^XPXbJbVXZd<L^TZR^XRhTLTbNR^^DdZPNZBZNXH\\`Z`J^XVh^ZPVVl\L\^LNZR`NZ`TBPRNPVN>XNfXL^b\lNXZZ`VR`R`VXX\VNXJLZRVVVbVVNPbVd^PVPXJ`TTfZTPVPZ`NTP^J\LnX^ZXXJb^TbV\\dZVV`LLH`PTBT`RRZRDNdRX^ZXX\P\bRXXVNPZVbTTb^PLj^V^`fZ\RBPXLVXR^`RTZZdV\X\b\TZN`fdNL^\d\\L\^XZVVbHPLTPbZV``ZP\ZNVbVRNTPZP`XXVPTVRTBVlXddbDTXVTH`ZVR\RZVN^P\@ZZZ^TZXfRJhVRJNJdbTdLdTRRVT<\PbT\RRL\^ZdZbfJdJdDfbfLLTJVLd\ZVHPT\J^VFTHZTRNVPZT\TVTF`TT^RT^bJT^XJPNXVHTXJPXZLXPT^RR\XPjJRPVVb\fTRFFdVVX^LRRNRVdVVZPXLNpTZ`V\`NVRbXTX\dTRPb^\LV\LBNPT^fVXPV^HV\J^VFL^VTBRDNd\VPJXRH`N`XXbLXPVPH\NRP\XV^ZFhPNHXZRZRHTPPVLPNbf`XFJHbPNLdPNRX\XNTZ`0^ZP\^ZX^PbFTH^T^LZZbT\TXPRTddXfNjVLX``\NXX`XbFRXZNnZVVV\\HNHlZZ\`V\`b`XPXbVV^TL^:dDXHfZV^TXVbFfHdVRb\ddbThRh^^X\VPfPb^XP`RT\P^RTfRZLlNXdXZ^bVJXX^P\TL\PTNTPZ`JV\dfR^PNXZXXbX^^fd^XdXX\ZRNNP\VJJ^bVXb^JbFLRX\ZPlP`ZVZVVfTbT\RXTJbZ\hTPbfRZJDXBZT\bVZVdXbX`j\hZXRNh\\JZ\\d`\bXTPPV\TZ`TPZXTXZT\XdP^NLXJ^V\`V^fTNb^\X^\RXZ\XTVV\TJdX`Xd`^TJRdTTX`VTBXbZXXHfXNZNZP^R`N\XTP\Z^RZXL`\X^^DZ`PTRfTPLLTXHVRRR\^RZh\ZNXJ^LVJb\`X`Z^R\TP`VV\VDhPLXLZ\ZV^HrHJZRVXTTd>bFNbPXRRX\XZRT\Jh`VLNRd^RbTDbVNTVhJbRZNbTNRXRZTN\XVNRNR`^BZ^J^RR\RbZZV^NV>LVR\PZL\NLTNlRX`XNTPHVRRTPPNV\RpZTRZXVR\RT^\PTVLZ^HTJJJ`0VNXVXHPFNRThJ`\XNPlTdhP\XX`X^J^HXFZdR\RDH`V@NTFT^NVNjNXbNVXZBNZLR<RR\RX\d:bDdNRhPXZJNXTT^RLJ\NZNTTVZZVX^RPXTTX\VJVVTdVVXVXPLLbFV^VJ^bdTZR\HbRD^^`\LR`XNbHVb`ZdR\XFTHRZZXVPV^JfVLP^VNHF^ZRLRJNVZbTNJXTXDXRPDTVLXHPVRH`TbX^XZbXRVXVV^VPVbLZRJd\VRDHTHZh\^`f`F\`dbLPZVVLP`XNT^PRZH\@Hb\\VPTNj^Hh^LZ^`ZZVRZNL^\PV\RNTZR`F\RTPFX\XRHH\HTVXZTX`HVPP\XNZVVZTNN^NV^bR`VTVDVLZRRR^T``P\<LHdRTXT^VlZR`bbRZ`R`TTvXXZXF^X\LVbfL\ZdN^^\V\ZNP\HfVNP^VbLZ\D^LXb^RlLP>ZXXPZPRbRbdXZLRRV`^^fTb^R\`bdZXbXZNRP\LRbZRLR`JPTPTbPbNL\NfRXTbpNTVhp`d`Z\dV^VRRdRT^\VLLdVZV\HdV\Td\Zn^Lhd^hT`BRdTbNbT\^XbZXLfVR`N\ZXHRh^\`^LVZT\\ZTb^nbPRVN^L``RLFZ`XN^ZT`ZHV^NT^N`bV\XZl`TZTTRTPZHZbJXVZLf`dN^VLXZNlVF^R^NPX\bT`ZXT`TV\JV\TVV^R^fVNffXNTP\JTVbZ^PVT`VVVbT\\`XJ\HVTVdZRb\J\bVXhVfJNXTbVPPT^Vb\Vb`RTTXF`\NR^LhRLXVbT\jZLXhVlTTN\XVNTZXZZFXRRTbjPL\HNl`XXPVbN^Bh\J^T^LXXfJXNXTTbXNP^XN\hBPdVBPRbXR\\TPNVfXbZ^DZjTbV@JF\`NL\ZZRNV`bPVXdbRZXTLXRZZXZZ`LJ\VTXT\fVPZJ`XVT^XJ\^V\LBTVjVTZZ^dTTd^JTZP`\V^XT\@\RRVRPZVRTLJ`RLNhX^^\V\ZJRZZb^`lPT\XRfRTPX\^ZVRXRX\NlFVP`XPPHPhTFX\`ZRVFbTXHXXVX`Z\ZN^XRfRT\b\T\ZTVZZPXPVNZ\nZhXLVRTVV^ZRTPTXXNZZJX^bJNVTNP`TR^@\dZ\`RP@ZXZDFV\b>^V`RH^VXb@NbR``NLdP^PRRZRLV\VdF\JlZZR^\J`TZNfdZ^XXTNPVVbXPV^VZXPPPXVZP\R\\\Z`b^RbXdVVLbHTX\RhJXPXb\XZ\`ZV`NRZV\ZV\PT`TL`\PrZ\R\ZN^RVV`ZFb^NZTJVX\ZJXP^NhPZZNXVTfT^RZRJ@X\\TZfZLN^ZbXVdZXNH\d\Nn\ZRZ^`TPPNNfPRb@LVTV`ZTdNVfJVZP^^ZTJJ`^``TbXZfZPf`\\llbdfVNb\\XPZPXNNRfPP^TF\P`ZVdLddZL^NRNdVV^XTP^^dFlP\`RPXXRPVZRLX\^PN`^VP^P^`LPZTXVbPPZ^XTFJh^VXVXXRbXL\VZJLTV^``XbNXbTX\ZRd^HPPPVP\^Lb`TZNVPP\XJVTPN\VhL`X8LTf4VHHXXPZJJT^`bVVRZFPVVZPPRNX\N`Z\PbZNNP^T\XPPVTP^bZ`VTNRT\ZJbZLVLZ\ZRB`HdVZZZ`TZfT^\BVXP\JRd^XNVLTF\NZ`JPRZT`Z``RXNTTX\Z\HXLfbbVTXZdN^TRNFPV^Z\V^Z`LVXT^FX^JXdTbTPX\HBVPXbTFRbLdLTRRdZb\NT`JR^HR^DXZ@VX\VLT\VL`XTbN`\F`LdLFLL\LJLPN`ZVT\T\NV\XNV\ZNV\^Z\N^PVT8^PTXP\\VVN`TXNN`NRPVXVVZRNTHX\XRLXZNXR\ZVRPfJPZNTLTP\XVX^X`\VVdJTL`PTTTRV<LRNTPPZbVVZLNTTFV\TPNTTPVJZZZ@bLXTPXZLXdNfXjTZXDVTXLRX`RZPRXJXHHLH^V:ZPf^T@\ZP\dXNL^LPBPRf`P\fVPXZPFVL^TXZ\dT>V`\TDPN^VbZZZZRDXVL`VHJ`ZHb\RX@^b^Z^d>P^NRL`HPX\\hRTXRdPTbRZP\TXXZRdZJH\``^fX\LXZNTbVX^d^`bF\dP^\TXjT`X\Z\^dZ^bLRNTfPLLJ^XN\d`JZbHV`FVB^V\TT\`XVbL^`X\TXP^ZdX\^H^ZPTZ\`bT\V`^ZLVh\XR^PbP`RXV`X\ZP\XX``ZZjPf\P^bFZLXnXRBbT``ZZbVZZZXL^f\djhjP^^j`TX`b^XR^p`^T\`VZ^XT^bX`ZdTH\ll^`V`TV^V`T^ZbdXXPPf\\bP\`b`R\XHXV^^TZX\XhPHbZVXZTlP^R^J\LN^PHXNRT^VZZN`VZLdfXj^N\TZpR^d\VTVRfRTXVdNBRZXVZfXLHZNfJ^NVFbJTPRXVZJ\TVPdZTPbhZV^P\P\LNX^\VNVTf\\PL`VX\JZPTVLTTXffTL\`VX`TZ\JVHb\NXb\J^bPV^T\ZXRZ\XVDLRZRT\VRX^JVXfV\XZZT\Nf^T\hVPdJJbJN^TTP\NdL^PV\^JVbH\XVX\N^\`FZDZXFVXZTV^Z`RdVVnNLVFXb^PPXfbTVPTXXPPN^LXLf^RVPZ>\bdZfZXjDNRVPV`\J\XVJLJP`XR^FT\\X^PX^VHJZhZVZRTTNZ^VZR\\L`VR^`VDTRXRhN^`LFVXP\\NTNXbLZJTLZ^ZXV\^ZNXTVRXTTNhNJJXf^D\XNdTN^RV@LV^NVZFZfb^FRTfV\\N^TNdXH\hN\\XVTLD`VVZ^`ZV`LXTfdRTPVVXVbVbRTLZd`L\TPb^VPZ^T^^^H`VZjNVTFZZ^XR`dPTN\\TZbNNTJZP\h^NTNT\VNVlVN`\fBbXRZT`Z>`ffR\TTZNXHNX^V^bT`TfXZJPZ\P`Z\LbDVbTN@``ZHhL\XFVpRdRX^bVh`R^ZZbZJTPZ\V`NXNPV\Jb\^`PbZZjTNRZXZV`JX^VLT^@dNV\VZ^`\^XNdT\TNZbR^\bNVTZZN\V^^ZNfRXRZjVTH^`\TPZ\dR^NTN\X\TF\XfZbL^lRPVRTXZZVRNHRRbD`T\NTPdLZNPjXZ\h^`>Z\PbXRbXVVXd\\fZVdfbRHbVXdRVN^^Nfb\bRXRfXTZpPRTjLNTR\R^bdH`R^HPjN\fN\PTjZPVPlR\RT^bN\XFXRTJ`XV^ZPP`RX\NXb^XTFPP^LLTRR\R^fXbVHh^TPZX^\LVb\X\R`TFHXPPRZRLXNN\XLH\N\RVdX^TVZTVNTLVZd\V\NXbTZXNX`NV^LTR`N\TZdXPLX`ZPXPRXRRX\ZbNLNbbR^ VZ\VTN`ZRNVXjT\Z\XN`T>J``NPNFbVXRPN`H\RNTNNTJTNZVZNP`VVT>\FRTVhJZNRRbVZ`T`\X^PZNZ\FPPV\\VZLTPTZ@J^VN^HJLRVPHZDZ^\^Zd`PVLRRXRL^`^^ZbNZTTTZTT^NRVPZR`H`JbZPXbNNTVVXRLjVVXBbVPXZZXVF^XXPXNfH^fZ\`FJ\fDTVf^TjLb`ZRZbVZHJPRNBRbZDZNR^ZbRTRRJRZVNXZPXT\PT^PPL\XTXNNlVVVD^VV\`PdT^^T`Z^FLbV\R\JN\F^TVVjTPZP^^TZR^F`X`TXVN^\RX`PZBTXXVVVJT\P`PPZZXVZNPTRLT\ZJ\RXT^NZXPNT^XZXH^bNLNX^Vb^dZb^XRh0\Z^b\TNR\LLVbLRXfRZTNFZPRTXPLZRjJVTPDh@XdZ`\\DV8fVT`h\TNbZRRX\XVV\RZVVRRTVP\dT`Pf`^ZV`^dTXHbZjRJP`XZTLb`XZ^XPZZ`\V^^LLPZd^^JXXRZPhT>P^XX^RL`JXbVJhXdZVV`Z\dLLZ\hhZ\PTrR\X`^X``V\\XVhV^ZXNZnP\TZNVTZN\\PTPZbXV\\P\`VdVX^FPRZ`XTVXHVJZ`RLVPZXZPTdVjTdbfTVh``ZTTRJj^J^`FbNj^HLfX`^Rd`dXNV``dR\X\dTX^hbH`ZXhZZPNfNdXVZJPR\^HV^bJXTZRdTBX\PVXV\XL`RVXVZ\N`^ddNPHJZH`RN>^LJTVdfRPTH`TP^Z\RNhDRPZLXTNRTLVRhZ^\LVT^THXRPVZXXbV^TNZRf`ZNRZ^VXP``JPfJ^\ZLNLJVNfR^VX^V\N`RbVZNRdX^XZPXHPXPbRTZ`hZjVPVdXZNVBV`bVd`TVNT`\VbJZRVL`RPRNdBhRNNNXLH`d@f\\TTb^NX\\XbPXXR\PXZ\P`VhHRNNd`BdXXVJTVT`RPPNXXRflTX\:fJ`PZ`fZFNn^VTNHbPXXT\N\TVRVBRfLTXLNJZ`V\Z^PZZdRNRVXZLXNXPTRV^fT\\XnV\PN^TP\VfR>T\X^\FT^bNTVVHfNXR^VRLXXLPZdNZP\P`VTJLV\XV^TTdJXZVV\^LXVPXZdTLb\JRP``\RbbjXXTfNXJfL`NR^VTZ\dH`\JPVLJ^fTVVHR\PNZTXRR`VJTL^bTH\fFTVdVD\<XdRT`V`RTZZRNJTP\NX\ZXRTXRZlPNT`bR\XX^LTbZXVhXRhVNPNTZJZXZNXZTfPTTXXZ`X\^TVVRZdTJ\Td^dLLVXb`>ldPTT\X`PNJT^\^P^\dT`TZ\R@^T\VdPTVV^RZZNRZN\Th\\VRTbLVZNXbfTPXbPRLVb^T\XRL\VV`XTRXV\TVhT^TVZdT\bXTT\VZTTjF^`fV^\RZf\XZXbbZVLRfVX\XJNRX\`\XTRVVj\bN`NHNLT^\bV\VFDfZ`f`^hTXBR`\`VJ`ZdTJRXHXL^NVX^`ZZRRVV\X\ZNVH\XJL\l^`PddXbbPdV^RBZfVZTZ^dTD^\`PT`V`^^^TdVVRTH\NNNZTXZhVT`P^PVZXXRPTZP`TTXJ\TH^\\VTPVF^^XXT`TTTRJNPVTbPPPVVHfX^ddXHdVZ`TZVVP^Z\^RJXPfTRR^R`NF\TNZlPXRTbPT^NbTZPV^VZR`ZXDZ^RXPX\NZlL^LP\TLXVL\Tj^TPTRVPbXZ`bRZP`VVLbVN^XdFl\^JDd\VbTV`TZVPfLT`LXTNXZhVZ^PnNHRfRJ^LDbJRVVTTRPhVV^V`ThJP\JRX\XLRX@TfZN\T<VXTNPZVT`RFVVHRJTb\ZPN\J`fPPTZVVf^BXfRTZLXXLTTTZXRRP\TNZPDP\ZXRZFRJPPV^TXJ^L^P`f^^ZPZPZPZTXLXR\VRV^XX\XT^R`PJNd\RNRD\L\PVL\VJ^NRPVZRbVRTRHpVXTFXJLRJP`\LdZRX\ZRZNJJZZNJVVX``L\\V^RTXbL\TPT`hLZR\XNPLRXXPP\LT^F@VN^fHH\b\`TVZZLPPVRZbXRh\\JVRVTPVTTLHZFbXZTVNZV`VXT\HLPPXTX\`XZX^RX\B^TT\DPNLP`L\`V^VVTTLbZPPP^jZdTHZ`^\`^d^RD\HVR\\PR`VZbLN^bZ^\T^P`NRdH`hdXBhVNNN`XPXNVXNbRFV\VZX\T<PX\\V\fZT\\dH\XRVV\PV`\V\Z`XPdHR\\^NNTPZ\ZVZRT\TbL`\NXTNT\XXbLXb`\P`ZXVfNTbNbXPHdVZ\hZTTf^FTXNf>ZLV^NZTH`Nf\XL`bZbJ^TZZ`VTRZRhf`N`^TVVTVR^HXRb^hJ`bZ\f\VR`ZXLZZPbNd\\fRZTfXVZZVbLVXV\dP\^P`\\F`HPpRRh\TR\LPTD\bP^XX`RZdjhfZ`h`bhXZ^d`XVbXXXP`fTXT\\^XJHP\ZT`j\BRbZ\X^Rb^f^j^JhZNbJjRFN`X\XTbl^`P\fXfV\bZ`bTNX`ZXRbTNZT^V`LH\^\`XJTRNdbbJTTTL`PZZV^Z^DL8^LN^VRThHVVLJdTLRPZTP\jZ<^XfZZLbTXZ^NR\:L\LfLH^Rf^VJXb`TXRVV\Z`JTX\NXJf^LZ\VVZ^`VZR\ZPRVTbHXbP\VLZ`@X\X\VT^RZRZX^P\`PNTVRNVRT\Z^LPHVTX^VZ\``bXXVR`HZRVXXR\HR^XXfBZl`\^^ZNZBZZN\H\f`NDX`LV\RVTVVHf^`TX^\P\\NNV\`RTRZbVTTX^VVL\VRLLX\PVRX\bNJZ\\`PR\`V^V\DHhRPVTPZDXVP^PTT\NPT^`TTTNRjVdNRNTRbRXLXdTP\TJNPPjPbVHbXVLVdTVHTX`XX\NhZd\FLT\LTVDTNXV\ZPhVX`VN@bVNVPJ`T``TDRdbT`Z`@VZZX\RTRdN\XRHZX^VHRTP`NTfRXXJb^TTZRVfNXJRdR`XbZVjTRXZTTTTTNHR\NVTNV^RZPPT`Bjd\VZ\hNP8XTTP\:PR^XRNfRVPXXDNDPRTPXb\LZZ<XT`V^\R<dNTXXZHT\ZT`LhbXVVdRLJ\Tb`@ZVZPRT\Z^Hd\VXP^\JRTVZPTfRf``VPTNdX`\XLV\bXN`VJXVV\^XH\TT\RRJ\Jj\b^XPVZ^\P\VbVVNNb^\V\N^bZTRdZTV^RZ`dN\@db^TfLT`^`^dXRZVV^Z^`\XX\ZTf`RVTXN^`LX\TZ\LZ`ZV\ZV`PRPXP\R`XTr`\XX^ZVZJPVJjX^ZL\>hZX\^LVPhTJ`jbd^ZTXTRF^PX\\bdbhdbhN`d^X`^TTTdR```TPdVTVXhT\ZD^lR^^NT`V^hLRdbXNVN`VR`^NVXRd^LX\dR2\\Rd`ZT`NVZXRT`TDNRTRbF\ZRVZFZfT^`FVXP^JDRX`Z\RLN`^TR\\P\H^R\N\V^R^V^RJ\jTVb:RTPXbLX\RdVTPVVThZRLNPX\XTXV^R^ZLV`\TZ\PdFFTZd\ZVP`L`T`THVRZVZXL`TLT`VNV`TP`bN\dH^XVVPRT\TVL^VRdLZbTVDTb^XLRNNVJLRH^@fX`ZN\HXHVR^RTLPN`RZdHR\VLRPVTTf\ZRTZTPRN\X^R^XXVTPPJbDTZTXV\PV\BTZBR`^`X^XZVRVTXVFJPVDV^FNNVPTdPVN`NRZRV`\PHVPZRZNZ\dRPNVPHdZZZZ\TbhV`JJ`^bXV<b^^DTZVbNVDVZTVbLLVTbZLf\@JNXVPjJXP^TVZbTRXbbTX^NXZN^TVNTPTLb`RTXZ\TPHPXZP\BZbFLVP^R^VX`XP`Hb^`TZX\NVZXJPXX\ZZXXRZTTdRXPPbTTZTfbRXT\d^TbVH\NVpZTPZfVTRJVXdfN`fT`LLTTdj\Nf\T\VZ>fPVHVHNTVdTVXZLj`ZTLXZjZ\`RTZTLTZTTTZN^hVRVTR`HdXX\TPJXXVj`PXbbRFVTTbTFTPTZLbVb\RRb^Z\`RbXbVXRXJbR^R\XV`ZZTVZZVJXbdH`TP\`TV\``b^bLf^RX\^T^VPTTRf^XXXR\\XRN``R`Nf\\VXbZbbVJ\``HNfRXPfdVTZdbf`PV\^FZ^\V^VR`\LBN`\TL^BdTZHRbXR\VFR^RLHJTZ\VXXXbX\L`bPXJXZL\XZPb^dZZVb`VXN^^HffTJ\F`TLpXTP`\VXXXVf\RPJXTZhN^^hnfbJbLZVFZPP^`^\R``V\VZ^XTTXlXH^L`TPfL\PDPTZ@PXFZP`XZPNbLJXdbVZVVLTXNb\bVZX\PTV^^TdZHTTjLXjFZZjTPLXbTNTh\ZFNV`T^TTJFRVdV`^\ZbHLJZZPZ\VXR^L^ZPXX^\NJ`TXXTNbPXP`PT\X^^P`VZXXL^`>TV^bRfhLVXXXVh^VJ\`bZT`\PZ`VfTN`N\ZR^NXRLZXX`XZlRTbV\\TLbX\NbTPbRZVZPR\RTZZbHXRdZ@`LRRL\FPHTLX`RP^TRH^H^R\>F`b^d<T^PXZTj\NX\XDRZVT^Z\NJ\^N\PVVTZXLb\\V^L^ZDJf\bf\NRTVdX^TVPTZRXFNRPn\VRVXbJRTT\HPLTThNNLDbX^bZZbX\^XNXPX^JR\VPbVNT^`TVXVVVRNX`LVNN\jbVhTfN`TLNXjZ\`\ZVXX\T^FZTTZRfXRNDRNRVXR^jVX\bbL`XX^hRJLdZXjVLRJVLP^TF\ZJVRTTb^dXRZ^PVNZNPV`TLV^\TVRJdRXPHHPF`VNR^^T^FHbV`\TV`\NHf^TZ`\LDHjNRN\\ZTRhfX`XZ\J\ZJdVR\TPV`ZPfN\NZhXR\^XH``d>ZbP^\LPXLJXTB`VXFX\TdP\b\\fZXLbDjZZRV^LPL`VJ\NZ`XT`XfLdTfXfV\V`Tp8`PTZP`TZV`RTdZ^\R^\NfVRVP`PZNbX8VN^XZjNV^`F\RJ`dVT^bZP`VXPTRPZXVT^TdZTdTZVX\V^LLdT`XZVPVT^d^Z`f`RlPXXTRN^bVjj\ZXLNZ\NTZNPTTLX\PTV`ZNR^XZRX`DTdZ^jfTZPh\VPV``N`Z^`bXVddfd\^R`^X\XPV\NjB^X\PN\``NPLN``XT\RZb^VXVpTXV^TXNdRZXfRRdHPRJTR^dLV\L^P^XZ`T\TTNZLdPXPXP\Pn^\XNX<VbbXP8`VXVZHNRBdLNbRXDRRJNL`XPZTJ\ZRTTVRRZJTdL<VNR^^^dVdTXHVNPZZTdJ`TZVXXXPZPV`ZNXFZXRNLNZXH^ZP^RT^RVTV\VPVZJV\VTR^\TVTLJJPXVdXXVNTPjPbXX\HPZTTFTFZ^Nd^NVHdbPZRZRXZZT\RT`NVfX\XRf^^dJTNXDVTTBb\XTbRVHZDb^HTNX`^VJdRZ\LHPR`RV^\ZR\RD\VZ\VVhNTFLVdRR``XXRTZNXZR^TVFZVTP\J\ZV^R`LbV\ZLLJZVPXPHXHd```J\VT^X`JdTbVVTNbLVV\ZTXXXTXVNZXHTHRVPV^^dLJVJRPT`L`b`N^`FVXl\ZJRZVJ\bRhNZ`PT\ZPZ^\ZXXXV\dFVN`ZZZP^\dTLd`RRTR\^HHX^BT^VTZTR^RHbXZVT`ZTPdTbVVVPZdNLZTh\`PLN^^RdZZVZD`bTRPXT\TTN\^PXPVP`Z\VZ^JXdXVPZR<TT\XdhRD\Tj\\f^bdhNZT\\Z\VXTP^HZP`X\^^D`FX\\rX\VLLRNJbH\H`NPTbbLV^FjT^ZVTVbRbBRVZVThPXPLV\VP\VTPTL^DH`ZPP^RPLR\ZZTXbfJLbbhJV`LXb\^rTTjZT`\R`ZTj`NL`bRTdXH\dZX:h\d^T^Z`VHR`^^dVZ\\VLNVTbh\P^`TPX^fVNfL\`TFdLXRR^ZRTLZXbNNPNRZVP^NLXRLTPXPPPNXTbLfPlRPLVTLjX`R`dbH\Bhb`hdbVZfPT^hZT\Xb`\XT`^R^V`Vj\Z`Z\\\dhZf^RRT^N^`^`\Db\X`XTVTJTZX\^ZX^`XVZTJT`b`LbPJfZVJjNlNHZ\X@hZV`b^X^ZZd\XXHZXd^VVRLPVXZ^`\bXZTZX^XTN`Z8XRZ\V`PXfN^RRTZRbNVJRfT`VRNbZ\HR\F^P^T\dhVZ`V`RVVV\PRX\TJVVJ^RZbXFLVNZVVBZXTR\pT`HXX V\NT\R\ZPTfRPVJX`FdfThR^JXXLZ^VNNZ\D8fNTTRjPB`T\VZZ`VD`^VT`^NjPRPdHbdZV^XT\JRTXD^dXLVNTRRJPFXR^P^RLTTfPNXdJRNVZdLPFRVTRhHJXX`NLRTH`X^^FRTb^^RRVX\VVFNV\^HFTRNVP`ZVZ`H\RXVLXXNXVP`ZfXRTXVTX^TbRNdPRVVTJZ^bVP^TLT^dXTZ\XNTdNHPVFVZD\RVVVf\NVTXXR\LbVJ`VJb\PLRVVZX`RVX^XfZZ^\\BZN^DZPV\TdLVXLVjNV^VVVZPTVPXF`JVPVVRTZTRh^HVbNT\dLP^RZRbV^RZPV\`ZPHXTNTdP\VTPPJXX\\\TRRNTVZbR^Jd^\NRbJP^lB`jN`TZPXTZbNNVdJ\^ZbVNVX\Z`^VZ^N^Z^XbT\L^ZN`PXTNP^`ZJNL^LLTf\dT`NZVd`PV^J^ZNPXZ\T\XNZXZ\ZXVJ^LT^XVXXZfL`ZRj`TPbbTf`DZR`PbXRRX`^\P^b\V^T\`hXP^XNbVXN\VX^XbPRPRdVP\ZNfV\\L^\\fXX^dL\HZ``PV^RL^<b\VPLTJZJH`PbNf`bdRXTXT^`XXHfXVTRVVX`TZZhR\RPNbZ`RRRVFJXbbXJdJVTdLZHdbdVdTb@Nfn^jH\\RNVPf^fhZd`bVZH\^ZT^T\T\bfTRVVXVTT^d\P\T`TLdVNXR\VRDZX\NL`TNXZP`TRVRXRPPRVZVRfVZNNFXb`ZFTNHVdTVJXVZPXX\^Z\^PVRjLVXZ\P`JX@VJHJVTfV\ZTXXNRRXTHbTTR\T^LLZXV`NP^X`HVNZBNLJTXRJ\LX\XZ^L`RRHVV^ZZNXDL`ZdPRV@NL`\FXZNTHN^`RVLPhPVJB\`VZ\N\RVXJ\T^PRLNh^ZZ^JTXVdTTD^ZR`JRJbJN\dLN^RZP@D`fVXTXZfXHTP\VZZ\^T\`VTNN^\fTNHRPRLPdXTX^N\PRXRPJZRXhVP^NJTFXNbT`PX`\VVXNPTX^ZXVRXPXLV\NPH@JR\ZXTLVXNX\RN`h`RXXNV^@\L^RZXJXFVXXPT`TVHLRZT\X\T^JXLT\ZR`V`F^^V`^bTRJdVXZbPPZVRTXPRXVb^XXJPJRTPPL\RbPR\P^RZXXJVXPNVJ^PP\PPZF`XLP\TNfVb`\PVP`RTbT\RZVTJZVXVTLZNNRDfRXd`XVNV^TTRL^NZ^RR\PZNR^V^VJJbL@N^PPX\TX^RT\PLjJ\PRPZ\\\PfFZLNZTRR`LX^ZJ\^fTBZRL`\RZVXZXV\^JVXRTPLRd\ZX\ZhV\^VZZ^dTTRLHLNhP\bZPX`hRTVZ`TTdXRZ\`JL^bV\bVV^TTZZZ^^H\D\RXPZdT^LVR\LZ`TTLJZRZ`\N\RZT^bPbFfTR\TThT`J^VTfTV`T\RZHPdR\V\`VVJ`PZLlXX\N^HZPFdZ`ThVRXLX\N\fXRVZNRXXHRT\VnZTXVNV^\TZfVf\RX`RZ^LR^b\\`\RPRZ`\PT`Ld^Z\`VT\bh<`JJ`R\`dbb^`lRvl`d\hfP\dTbTbNfZZVHbV\ZXTTX``ZZ\JbJ<PTJfTbTNH^Zb\TTbRXX`\dbbZNH`hdP`PXRZP\\Z\^ZXb`RZVT^Z\NVVHRPVR\\L^\BPPj^JLTRRVXPVNdVVP^^`XTTTTLP VRN^\DR`R^RZZ`TdVlPPXd^XHf^VZVLR^XXPbXPRNbfVTTXTXN\VT\XR`jHZdX\NT^\\XZPV``XTX`T\dFLZ^F`ZZP\LXVLNVRRJ\RN^RTZN`XZTN\\`\THdTVZR^N^`PJFPRZRVbPJdJXZZ`NZVHdHPPb^dXNVZR`bVhNXZd\BJVZLRRLbRXZXXLDhZZnTTVX^JR>RNJRd\LZTJZRPXPT\Rbd`^bJXfVT`ZXR^`VbV`R`ZXTPZRTDFVVhHZ`\VRhNNNP`RVVZ^^V^Z^PVTTR\XbVVPT^bT`XH``PZLP`\RZ^TfTTXVPPRXbTLVRbNbbFPN^LLD`HdT`\X`VR^V`LPL\LNjT\`dZPXb^Z^TRJR^TNTRdNb\TJZXZRXb^`V`NTZVPZ\VPNLXP\HLRJ\XVLRTTL\\RdV`\ZZ\LTL`\PbhTZPjPbLTZbT\JNZ\ZPVfXNR\XZR`N\ZdbNR\ddXV@F\VJLXP^\bP`XdT\bP\bXRXRf^XRNT`VZZhN`ZXVXVL`RfRR\ddVbXZRVFp`PJVZTLPPLZdZTVbPL\XH^TXXRXPHZdfL`RT`ZP\jZV^^V^LVZjPBb`@Tb^NLl^LfV\^^`ZTZ\JX^^RTV^RZZZJZ`XbXT`ZT`VR>TXVd\ZV^`dfVZhd\bXVdTNfTV\ZXXPbhZRZXZ^\`P`^^\`PXTV^P\TXTVXX^TVV^T`PfPJRjTV\VbR`LZTPXZlPPXbBN\\bVR\f`^VVV\VbZT^ZPVfRZ\`^RdLdRVVZPTV`hXb\TXfL^\XRXfd^XbdPDRfZ`^NZTZPb`fTPbTPZVf\FTVXTVP\VN^RR\RZRX\FTPR\`\XbZjVV`RT\``NXN\^VRVNPRRNVJX^RN\LLVJLXbPFbXPZ>ZJbXVTH^VV^JZTVXRX\Z^ZLZRZ`HNNdHfVPPZPR\ZTN`X`d^LHXRPRRb\VZTRHTVfV\Z^bVT^LZ\T`^RVXV`NXTbPHVRLNZRdR`VPPLXLJT>VTBV\NTFVTRTRhXTbJdNT^VX\VTXb^PZRbXNNN\RBXR\LVRTVfHfXFNRVPV`PTP`bVJTVFfHTPJT^H\ZPbZ^VHVZb^VPZX^TXV^^PFpVFZTTTZLTPbT^XV`XXXRP^^\LjZPLLXTTXRTV\bbXH@dbPbLTXXV`VPJVT^^ZZ^X\ZJTV`XZLPP^TZZVXXZX\ZNXRDVbPT^ZVXTXLXDPFZRFZNRDZXJRX^VPf`bPVZV`bPBbRHV^ZFVdDPV\RXX^<\XFbD`^VbTTVXZPTNRRT@:LLH\ZJXTRD\HTXTV^`ZbXZRXRVXJ\ZTTNP\PPlXTdL>>\ZTDb:LbTHTTV\Vd<ZbRPDXTJRJXP\TVV\bTRVXP`\@TVJPXT`RNVRX^P^ZD\\RRpPXfX^\P`\P\RbfVXRXdR\jTTJVbfTR`XR`T`NRZLZVJXZ`PTL\bXXP^XNLfd`FV^jVRHTP\TR`ZHddVJVLfVH^ZXN\dfTbTRXNdZZXZTZHRb^bVV\VRXb\d@XXNVTXRPhZVRVTPTT^RH`RTbh\TVNXP^R^VdPTLX^\RZTXdXRZZJd`LbRXZZVXXbXT\RNTbJNPL\P\PHVLJXVVhTPTX^JZ^HdTdRZfZXdV^\l^dZZZh^\JVR`^X\bn`TRRbRR\\jj\X\\LLb^^TZPJ`R`N^VbNZTNd\ddNdd\FNRXZZhVLTXRlNVFXRB\\ZPX\ZNVLT^`RT^N\VNjHNPhL6HVNPRJ`@JRZRZRVTRPTZZbZRFNL^^Z\NXT^VdRZ`RLZ^ZRH\N`TbVP``JZVBTPDdLXdXZVZXVRR@^ZJ`LPX^VHNP^hPR\LNXF^PVbPZ\LTLPXRTbhfd\RJ\bDPL@^\`Z`P\JTZZPJXN^R^RXXVPZbZN\HTT`XFXNZXNVTLJ^ZNZNd`NZXRTP\`RTVXRlbZHVPfNb\\T\D^PXRXD^jNT^N`P^`TJPbND^XTXTPNZTZTVJdZTVdpRRRPT:d^`JP`VXT\TJL^J\PdTZVdPT^TZXZJTPPT\fbXZX^JXVN\FH^XRP\Tl^Z^XDTVRTZR\JZDlVJZ\VV`\TZP\V\ZZRTJTLLN\NZZZ^P^HZRRVLN`DVV\Nd^TTHVTV`JHTLVVDLVhT\VVXZ\XPVZ`V^T\V>^XhTP\PbZNVb^P^HRHTXT``V`DXPbPXddT\XT`^\L`dJdL`LZR\BTRX^J`VP\NVlFH\JZXRVN\XFNXXZZdThLNVPZXLNPb^PfTNZP^PXbRPfNXDd@XRVVVXbXTTTP\XRVXVhNRNRZPFddL^BXXNLXX\ZR`PP^TVT^Z\FR\HV^ZfLd`PNTP^PhTT\`N`NbLfH`jbZXTT^^HjN\``TbRX^PZZT^RPTVNTVVZnT\ZXPdTZH^PTZ^ZTVPbZTfZPX\TfJ\^V\b^Zf`\RVBTT`XZZTN\TlT@TXRNJNVLXZ\P\RZ`TXjXZJT\bLT`dXFXLVT\TJV\>^ZN\R>bNZH^XbXbhfj\VhZPfVPX`bVNX`X`d`^ddXT\FZRfhN^RdZ^PXN`FNDZ\\TTP`\\hJJZZ`NRbbDZLLPZ^`^^RddRXXHNLTVNXP\TTTX`LTFPTPRPZNHZdbTbHV\f``^NHbXZNVXLXR``RPZXZNVRd^XTfRFd:NVVPT`VXDN`TPTdRX^VT^XHVVV\VX^ZR\V^DP^XTRN\H\R`\NNlNVN^TdXRPPT^XXTX@\VXPRDX^lH\bPVVTXPTTX``fHZfTJD8XPP`V\V`TVVjXLV`b\^FXVVPR@FPRVT\XLR`PLTPLRL`Z^P@XPTVPfXbVZ^RZZZNZb^TRdN\LPVbhZ\\BN\\bbXZRPdPVRNPJHZ^PFPF:JLBPP^\B$VXLRL`XRTLTHTVLFJV\TVd^XRTHFLD`JNbXXDTVLRLNTR\`JJbPVV\R`ZVVNL>ZRXH`@\`VHNVP`TZ@XTZZTT\ZFVR\NP^XLR^\b\PXNRXTVPXVN^VbH^`XP^\P`^XRVRVNHFbXP^ZPZV\XXjPJN ^fN^ZZ\N^HZ`ZL\ZLPLL``ZVNZ`RRZJZXZTXdJVR\TP\VXL`bjRdXNTNRV^T\TXRXT\TJT\^bdX`PXZ\^^RR^XFTRL\v^VbPTZ^PDVX`RTRXPX``RRZb@TZf^LNHTRZNXXZ^RZRV\XZbZP`Z\VT`>X^`bTbP`R`d`HVPPJ^^V\XFV`NTN``b\TVN^X\ZfN^R^T^NTVhTV\RR`ZhN`XTZX\TNX`L\LZR`PZ`T^^ZJdL\TZ\^HbXPhLbPLZTZHXVZV\RPVZ\RfbVVF^^NZfXRR\V\b\bb^NfX`L\\VVVR`XVPZ\ZZZLXfTHXJVRRRZ\F\PNZ`LhhXd\X^`fZXXP\XhbTh^db^VXVTZf^VNFd``ZfVXd\XVPXNNfZV^PNTL\PR`lJN^LPJTNbX``L`X`LZZNTR\fZ^dVXVdX`^`hbL`T\VZPTDVbfZLR`ZZbZZZV^^VPLXbXXZPTPNVPVXZZXVT\^V\ZLVNZ`HR`VVPN`Z``bNd\ZN\PNXRRXNV2V`H\LVT`\P`HVNNXPRdPTXV\fbTT\\^RZfdX\\DZbL^TVT``R^TLjdVVRV^TVLXZVd^RRZZVRH``VHRRRJZVTXZHV\LF``^ZP`\\dF\XTLbXRbVLP^\T`XT\\LTTVPTR\\`^^XJ\T\NZVZ\DXJL`\RRVZTHHTVX`dZ\Xz\XVP`Z`NHZL\\hZNTN<H\V^VRV@XX\\L^X^^TbV\dZX`B`L`^RTRN`Z@^bVRTTPHRZRNPNRbPLZXf`ZVPP^FHJT^RL\Z^VRhXVXV6\^lXF\NTHbZVVRL\R^\PDZNVXXVL`NVfVXJTL\NV`ZZ\^`T^PNPD\TV\dhP`VdZP`JP`RLZ^`^\ZVZ\RTR^TXVPXZPV^HRPTRTTZV\TbXVTN\XJNP>\NVPVbPV`TJXTNV^VNVXZNTXVTdFNXHbZ\PX`T`RTTP^NHLZTZJVb^X`XH^VPRXdPblFdTR^TTf\NTP@nX``Nf@ZRXV<\XPhXVZPRbN`NbT^\T\VXFTJJTXVP`XNRVNPZJB>R^hXZ`NdbVbVRZZ`bNRTZ`XbX^Tb\RRT`ZVTlNf^fJT`NTfVRTVb^P\``Z`P^hRZXjVRJX^Z^^\VT^XZP^\P\^R\bbhL:\PLb`rRZThT\PZXb^VXL`JR\XdZdXZ\Z\TR^`\J\VHbX^bZPV^R\DRTT\N\JX`X`^\hXVHZRT`XX`dpRbXL`fJD^F^XR\VjVXNPZT`TDZRVNPbZjTX^hJTZV`\TdPTR\d^FfTRTRb^RRPT^P^\ZLPZ``^`TZlHL^`\Z\RNVVbVP^NJbPHXP\\`RFbZFb\NPT\RNRRbPXPRZNbHJVPHhNXT\`PTfT\VZVbPTRPPfLJ`ZJVRVdT\ZRHXXNXN^LbXZ\V\^ZXfFP^XN\ZRL`^hX`PVXN`\RB\^RX`XV`NZXTPZN\\FjPNZTVTZ^VNLZFPNX`Df\NVDL\^TJRLTHZjJbXXPRdJZ`XN^FXVHNHJVNTTRF\DbRTfVTRJbLP`LPNRVP\ZPFNX`HRLVVNNNNdTVZLLT^XbTfP\Z\XPRZP\VFJZFZ``R\TRZN^^RTZ^ZHRRPXNV^XVTbRNZ^NTVZPLZP0PX\JZ`JTLVTPRRXPTTNP^LX^VbZLP^RHVLXLPJNd\ZRV`LTdJXZT`bJdHXJPbJLVTPJ^TFPVLjXFZbXTN\XNb^Z\XV`XT^R\XHf`V^PbXT\^LR\TXTR`XPdZ^ZNZ^\TLXNTZ\:TBZVb`RbPT``R^XR^ZF`TVRXRRZDXLZDJP^FXPXhXPXTVL^RbVdT^`^Z\`RZPZFVdVTbZJV`jR\HVVRDfXHVVT`ZfL^NRNVNXZTRXJZLLR`JNZZLL^\FBXfTVV`^\TZT^RVZXRZJVTTVZ\DZPdJ^RXPVNL^J\RTTZhLZX\XV^ZLPZZXR^\bHd@`^\`NdVXLTTNP^PVZR^PZVVJTNF`RXfXNLfRbTN`ZRZRXZdNL`RRXb^R>\X\\L^TR^bTZ`RTXX`ZL`X`fdf\TJTRRLVT\XFV^^DVJZNZTVX\6VVZXVFLbPJZTRRPVRXNR\HPBZRNR^TPX\^VZhHHdLVLXN^XjNFPV\hRNjXTfZTVfZZR^f\ZTZ\\J^`VHnN`ZPffJfb`P`HZdTJXdLZ\\jXZ\NVJ^bPP\ZPXVVJ^T\^LPHZRXVbdVTXRR`^DTfRFNX`TLVZThTP\L^F^`Hh\^ZPdVX``PLfZNJRLHXXRPTVZV^TTJbN\RHZ^VXVXPfNZ^V\TRNVbJ\`TJ\XhT`VZX`^PP\dZ`V`RVZLT:J`Z\XXb^`VLHZLdXdL^ZPPRR\ZbHT^Rdb^XR^Pd\LVR`Z\X\VdN^@\XjLXZf^LbPRV\VX^\N^dR\PPTTPLZTX\JJRfNVTXJNPL\^RXXXPTPVX^PfPTZZNTPXXdT@\FT\bX\Z^T`V^`TNHVZJXVRRJTRJfRNR`^\^RVH`VHPZXNXVPV\T`RXFZX\R`PZNRZ\XVVXTXRTRTXJNNN^\HTjVbJZT`V\XPNP`Zd\VPXJDHTTTXV`RNV\RbZV\LRDZ\TVN`LVVL\ThTZZLP\bZ>XVTVVbFT`NPR\XPRZPRNVTZZNZLFZJ`RNTTX\VNVZXXNVBZBJjPXXL\PZ\RP\L^`hVPZ2PVbZRN^d\HRTRFNdLZV`\RRRFNT^XNPDTP\PdVNZ^b\VlVDnJV^PhHVP`Z`j`^ZTVVRXbN`ZVV\nZFXV`LZTZ^RVT^Z``dL>ZPNHbDZXPT^dVZ^TP\ZHRNbfV\fR\d\fBL\TLTZ\ZdjX`XFRbZPFRR`bVjb^HNhR\D`PNZ^LfdRPPdZ^`j`JNX\Z^ZT\T\PT\PR\VfbXZ^ThdZRX^TNXJZZnNZXZXL`VfRLZ`\RJ``PLN`ZhVVVZ\PRLTZL`dNTTPJZhZVdV`d\fXRXLTZTfR\\bZRXXNTZLVhNPV`NNXXTLVRbh^fZd\Th\ZbZjZLRLdXL\^ZjVFb\VJNH`ZXRV^ZTbXZ\\VVP``TNVT^VTR\Ld^TVTTNbJPVPJ\\^VPTH\TJNPRPN^RXDb\V\Nb`bdPThXTP`Z\TBPPHLFjTXZ^RNNTRN^^`XTV\RP`DZL`PXPZTHj<VH^JTVbLVT`bVNPZ`XL`VXLZZF``R\HRR^RZVTZ\FRXFJZPZ\TXPHTXPVP^T`FNTZZNJ^NTRnZJRThPZTXXZ^\N^ZZ@HbLPR\TTLX^XPX`VVRJNVXXV\<XNTZPZ\TXVL\ZZTTbfZRT\RTPP\T^hLT^R\dPPXZZN`\ZTT\`XVTZXTbVZb\\HJVXL\ZbTldR^pJRd`\^ZXRX^T`VbXH\XTVVTRXRJ^`XXPXZT\P^R\L^VNPR\`DfXRJXXX`hXJFZJZ\R\VDb^TRXNZVXXRPTLRPVZPNT\TVXVTPTVXVZT\VN`RHN\X`NVJNXXVLVDd`RZT\NNXVRZVR^R`RXTZXZRDNT@RN`VVLZRNR^`RXXTVdT\Nb^\PfHbVFjPXFbTNXPRZTZbTPL\VBHZ^R\LZ>RLJVVDXPZLTVbZXZXTRD^TJXhRZB^PRVHZTXVXPTN^LJJbNVVRX`T^V\LZJX^P\RTTf`\L`d\R^XJX\RPH>hVR^LdXVfHTXXJVZ\\NZT^HV^LVZRbZZPLRTHfXFDVNVZXT`^VPdVDP\LVTJD^^VL^L^HPZ^\X\dTRZRZ`RZPVZVVP\^TlVRNPZP^ZZVTbf`ZX\XVLRPR^\HV\RVN^XZjXPb\`F^VXd\VbJ`BbXT^TRTZ\RdV`^PNZX^f\HZX^ZX`Fb^X^VTbVRN^XXRXJZXTX@RN^R^\VPd\dPVVRPF`XLNL^ZFLPLJV^<TVT^VfZbdX^b\XV`HRj`RTdXP\^dFT`^^`jTf^dZTTZ`X^\f\NbVXRT\Z`ZdbJbfXR`TN\XhJN\TXLNfTVRL^XTZJ`^ZR`NPVVXLTX`XT\PfL\T^dTTRdXR`X^dVH\P<VXJT\NfNbRdPPLVVV^Xf`VRbR^NH^h\^`N\\VRLX^VJRVZD\ZZhRD`J^RTPTHVR`ZVZXVZP^T^PPZ`^ZXX^bXRN`bP^JP`VZTf\TfJNVRVVVRLHXZ\RVbVH^V`RVXRJbZZfLRXbPN`VVNNXJPXPbRPTL^\`^VRdP`b\HZLdTP^RZPhNb^ZXXV^RFZR^R\hXV\T\\JF^XP\ZBRRHT`ZZJVX\HZbTPNRP^JV\fXL\DTHJRRHV\\\b\PPZTP\N\PVPRJ^`\bXZPRPR`VXHjBVXdR^LPVXZVTHZ^X`PfTNNZfT\Ndh^PPdRPPXRXNF`F\JVNRXJZTZZZLbXZ^NNLX\\J`P^XbTJNNX\TV^XP`TJbLXNLP^PXXdbPT\^\L\DRfRNPXPVRPTLTJNV`bR\ZfZVVZXT^RjLXXVV``RVVZJZdT\TXVfPTZX^PVXXR\`TXZfZVTTJP\^PXTRX`ZZJX\RV\ZXTV\X^Z\V`VJ\VZRVXLf\JVLVZfZNNNZ`VTJZXT^X\NRLXRN`LZR^b\Pd\fVJVTF^PbZPf\JV`dXX^PbJ\JlZV^BL\`XNZVRRTR\b`V\PZVRT\bVZhLd\VTbR`RVdXTbPT``VRRJZNNT\\\dZVVLNT\\`TjfPXRVfTXhXR\fdH\\tRLPVZ\Rd`bT`Vd\VNhVXNZ`RXTVZ\ZXJTVH`PTLVb`P.R\^TLLRXTRR\\ZjRbbPVZdjZbbZ\`^ffR\Z^fV\ZXTDVDTLVL`f\`fZfPbVXL\RXR\V\DZdRHTjXLbNb^bXVLTX``RZHX^TZZVZNVPJXN\LZ\^RFVNVR^V^ZbHNVfVVPRXP\TNNX^JNNHPTHPV^DZ^RJNRNPFJLHRTN`J`V\DV`VZZ`\ZNXXTPXX\RXPRVVHNX`VVZHV\XVPPLbVTXTZFX\\TXFFPNTZhVNP\XVJVTNhZ^VVPRRRTRb\ZP\VTVP`\V\N`ZD`VLPZRVL@TXZTTTNV\VVFR^^R`LVLVNZV^ZJRNhP^ZVNPXVdTNLbTXD`dTVRRXPX\XNPbPJ\TX`^PN\dXPZRJVPPJ`TPPRFNB^^`D`dZRJZP`HL^RZVDdPPPDVjXZ\\ZHPLLLLVNNTZTVX`f\ZR^VNRhF\ZHXZLNPVT\V`N\ZVnVJX`LRVTPN^ZNVPRHTNXLV`>NX\TVVRX`^PZZ^RL\B:^ZbXR\TPTN^XP^VZbZZFXJJRPT`^`P`RVTdRRNTNXXTHRZZFLVX`R\VXTbP^TR`\LVTfZVPXNZX^bVX`RPZR\`VLf^bJXVTPRdLT\BNTT\XZP@dTbhV\Z\LVTTZV\VJT^RDPPTLTZjTFXXRNFVbPTjRVVHP^ZVJR:PL\X\BXTTL^VRhR^V^ZNVXTXZ``NV\\XXJb\TN`VXZL^TTJRPXh\VTZPJNPVR`\NX`ZVRXf^jBXPX\TTF`TZZXfX^`N\XVJV`\XX^HZPPZb`TVX`ZVRTV@VZTXXJ^R`T`FVbbRPj`XL^V`ZJXh`LTZd`\L^`VP>hLXjVfVZRNZ\VNXV\fRRV\VXRZZdRTVRPHRRXXLTVNXXF^N^\VP`JNRZ^TXdTfd`Vb\ZlPV^b`Zj\PV`ZZh`bdfNZ\\R``\ZXT`hlh@X^`Z^X^NNZ^TTbXNL`ZPfHRXPHXF\@bXRZ^NfPh\`RVbNbXRTXXZVRR\d\\\PJZ^\XVRNTDZ^@BdDPT`XTRT\P^\`V^\TNR^VXZ^ZLPT^^V\Db`T\\PXV`fLdTX^\\P^^ZVJR`VPRVL\VNT\j^\\bPhR^RXVZPN\XT NHb^`NZ^Z^LHZ\\`TVJPTPVHZZPX\\dTZXVXV^TNThLXZTf`LVJTLZJ\\\VVVfPXLN^NJVZdLHXbRdRT`PRP\VPTRXTJ^RTVBdZRVfHfTZdXVTbL\ZRP^RN\D^\dRLNPdNRLbBVX`PZNZ\NBDRL\RdRRDJLR^RBJ^VN^LVZPJJZXVPZF\LZJT\ZHVJZT\NR^Vh`RNRZNfXLZTVZJPTZXTfRZZ^VNX\VVhVPTR\FV`J`d\T`\RLZJ\P^NL`X`^L^NhRTVJVR@\`fd\^TVf`LX^j\Z\:`\TBXX^\VRNT\ZFLZ\DfPdb\^RfV\J`B`dHX^`VXBjRdV^NPThTT\`X^T\Z\ZPX^LZZd``N`PVXTVZhPT^L`\XLNbdb^P`\X`JFf`PVVTJbXZ^``LVRXXNTTR`TBP\V`ZR\RVXN`l^fPZZZP^NZfRZZRT\TfRJN\XZRVPfTR\RXVPfRTPZ\XRZbX^TJXXV\fVJZDRTLRfXV\b^PTPdXbNXRb\\ZfN`XXZ\b\dJb^LP^bT^N`JZHdTThDbXFZ^dRNhP\BTbRTJPVD^\TrR\\^bP`TPXZZVNZ\dVfVX\X`Tb\XLVV^V^PZZZRNNTXLRRV\TR^VLV\\`ZLX@TXN^RVJXZLdTdb^`TZ^V`XXb^\TBffZh`T^Pb\N@THJP`PVX\^bTRTbR\RVJVf^\N\VVZPVXPj^bTZLTNRXJP^NXHPTZXVdbVXbTXTLNbP^\VP\\BbN\V`PP`NZNNLTN`^PNLTd^PL^\B\X\TTHPLH\\LHPTVP^^V^N^RNdTRNB\RRPPXd\RPNX^PXbZ\HfTRZPTRV`HLX\FRJR`TZ`NN^PPTb\`PZTLZbXTRH\TJRJ`T\@VPZ\NPTFV^VNLTRH`VVTL^VPT\\PVXVH\bJRdXX^NV`TZPRZ\RN`RTR\`Z\TV\ZPjbRTJT^TX^TP^dZRNVPNBL`X\\R^V`XP^V\L\\^ZZP\VPXdPVZdRTXRNJPdT\TJX\N`dFZ@^\`R\T\VZV^NVPZ<\P^RVZ`ZTZ^RVDVPRPT\ZTLZZJZZVPj\^R\X^ZXXNPZNd`NTfLPRTTFRNRVT^PPbB`JP`ZXRbRZPPZTVX\R>^NHJ^PHZPXHTTRTdPX\\TXT^V\VLTNL^N`ZT\TVZ@HbNRZ^BRdVLbPXXT\XR`P^R`ZTNRVTJLTLHJ^L`\DN\HNXNTb@^ZXXb@Z`FRR^XTZX^RFXZ^\ZZ^Z`ZZPbZZXZNTbBVL`JR^VVPRT`XLTRR^XPLPHZXX\TNfX\NPJ\`VPP`TXVVXJRVddfdXT^ZLVRbdVVRbZRZTRT\JZXDNZ\HVNTRTZ^N`R^VPTPZRZV^T\V`V`XZP\P@^V^b`LJfPTdVXPXTX`Zh\NV`PdVRXbXTPXPhRDXPhZPb^VT\VbhTRPN^XbXJh\RXZXbVNjRTVVJV\XRXZJRfXT\VZFV`P\TXhRfjZ\fN\R\\\L^bX\XRHZdZVXbZXNVbfVXdbL^PdVVZh`^bNdVZZ`VfZ\^ZdbZBXVZXdVdNZ`TVTnbLHT^\T^XR^PZbB\^`RbXTR`PfXLbXVVbXTV`ZRXLLHPT^PRT^T`JVTNVX<ZTPV^^PZFNRR^PN^dH\LVV^\J\bTVRJR\PRVXb^L^\bH`NXRPTd^NP\XZT\PRZfPZ`VLXZVZ^LL^\fVfRRd\ZL`TTPXVNhNXVZLH\VRfRLjLNZLZdRPRLTBP\XXLPVHH`ZJhX`dHZPR\TH\ZBDLX^VNX\JNbXT`X`ZRZXbbPLXNJdF\XTVZXNZ`fNVLV`^BTRZFNdb^ZL\ZfXTNP`ZTT\R`LXTXLJZTTTfNb^XJLPPNNPRNJLdFf\XPX^RL^XB`VLT^fTVTZHZXV\VZNRXPRXRdZTVfZNNZJV\P^`ZPTNR\VTX^Z\\bPNPTP`THRNVPF`VF&Tb\JZZZhLN^NPXX`VV`\LbHfbV`d`TPPbXNHRRR\ZVRbBZV^PTRP\PVT\hb`VRDbZTbVbPNJRRX^ffLVZbTP^D\PPZLVRXLT\^V^TVRbNPRTLRRLX`NPV^N^VZV\NVT^PbHhXXVTVR`X^^`ZTZJ\V^LRZfLfTL\BRXP`NbPZNPdb^NRR\R^^V\XPZZL\\VFXX^\TZVJ\b\PZZR`\RTlXR\P^bZbHVX\X^ZPXTRF^ZVTTbVRJZ\TVb^TTJJ\\bZVf^^NVnJ`Pbb\hPbf^^hTRbN`XXRL^NdJdVbRRhhT\PTRbHHhV`RZLTZP^\TXVLVVVfhPL^VRfX`TJd^TbZ`XJ^JHRTP^ZNX\ZTNZdXX\X`PR\XfXZ`VLZTR\^V\TXVRhDd`RVbJVTZ^dRVVdJHP>VT^T`JVZLV`HNTZZLHdXRR\XZXdVlfZ`^dX^bR^TXbX`\\LfdV\V^ZPNJfNVH`\XHbTTdRTTT\^PZZZfVPl^^TNNPDd\RLVR`TNZ`FVPdFTJhDNZT`TFFpRLXZbVLVVVP\JZJRPXdJPZLNXdJVZTNTVVJTRT`X\ZVP\RNT\^TJNN`ZRfVZXZND^PfTPJXXVTFV\LZ`TTTPPR^RVTTf\RPZJdRFb^Jl^VLLB^VZJDLbLRbTV\\X\hTNfJZ\HVT\\XXV`V^NPZP^TZRTPH`TPZXT\^PbPdTfT^^ZZhJfLRV\ZRRZJZdjJdXLJHVVTNXbPRNVP^X^TVXT^bV\TTZTHLV``XXHTVPRLVZR^TNVXTPNLZ\T^RT^d\^TdT^LZPRP^P^NNVN^^ZTXL\LRNLX\ZNRR^Z`bZfTRLZN\HPNXnPTh^VTJ^ZVFX\TZHX^N\VZZJNbVTZD\VTLLZVNVNZXVZLd^:XRFlNXVT\X``RP`ZXFVRV\P^RXLPRHHHXFLX\`RJ\fNLVV`HZLRT\^JZPZVd\^P^L^LXXV`T`ZTVLFTZVXVV`\Z\RNZTNfZVTNVPXJJ`NR\^PTfPXTPX\NZ`X`XLZXPRVPXVXPR\^NbRBJL:PdlXJ\lRNPTVN`hXRdZRVb`RVZVN`^bdZ\`dR`PFZVVPPZZXRVVPfRV^HZbZNXRbRZX\TR\VZPJNT`\ZJZ^P\NZV\L\F^fRRLRXXN\V^VVZdHFZ\`JHdRRZ\PL``VbTV^XZVb\VNPbRT^\XNZVL\FbX^\TXV`R^T^bV^\bZXV`FbXVTV^XTXLdVV`bPVVXZP`bdLRV\bRVNJL^\ZVHX^ZTbbZRbPLfTbBN^Tp\\DbZdPpN`X\fbPTRTXV`XN\ZbXVXR`TVZTXTZFVdHZ^NTTZ^lVVhbV\Rh\dN`Z^TjX\^\XX^J``fRZd`DXNdbNJRTRPPbZZTNZjhTVXPfdH\X8f\\XZf^N^PXZL^dbTZTZZ^ZR^XdZNTHPJVVVV^NXZdTN\NX\NNVJXPRZbTLZV\TVRTR\^TdRHTZFfdTTJRnNZRL^hVNZJlPVPXVXT\PXXRP^XXbXH\TTP\VZFb^^BbPdXPdNTVPdRJX\XPZTNZZXJ\TTXXdP\XhRLRTLXXTR&jX^\ZbP^\BXZJZXTVJDXT`Z\VV^^X\TJL\TfT`\XTTRHLfZR^fX`\ZHLT`fNRXZV\NPdfVPf\\XJTX`L^PPTV`XTXP^^LNDLRZJTP^`LZZTR^^\XZ\XLXNRXLBZXV^PhTVZR^XX \^ NN X ^XNN ^VTXXTHV HXV TVZRFRVRZTR^VV:JR^TR^RVb\^^J`NPVPZDNbbXPLZVbT\N`dZPbRX`TpVN\H\XXT\`^ZX^^dZRXR`LTRXNN`XV^HNRdLXTR>f\TJRZ`^L\L`RXT`PXRXT\NTVZVPRZ`BZVTXL\JPN^TTbD\TXZZNNR^TZ`PXXVLPTbZZ`J^RZfZTD\Th^dFRPZR^NbP\`VXZ^JfTVTVVP^T^RL\LNZNVNJfHTXJRJ@dfNDPZ^bJPNX^ZZZZNVN\VdN^VP\`bPPVVZRX`XVNf\Z^ZX`NN\`Vb^\X\bNX^``JZVb^P\NT\NL^`\H`VdJTbTXX`\LR\RTZJTTZfJLd^X\\N`VTNRVfR`VX\Nb^\bbTZVbZZZNdRbXXhZ^D`\T^`Xd\ZT\ZDVJbVTZZ`RPXR@PX`\^RdPdT^NN`ZRJdZ^b\`\ZLZdVTXTZZ^T\^PbRbXRVDNHZ^LZnNZ`LdJTZZR^XTVDZTPnZV\\fPPdVVRZPZNLR`\VTTVTRX^TXjbXhj^T^`XfT^hh^bLZThbRfHNX^VVfTPXVVR\ZbdZ\Xf`NZNZ^VZXX@\\TRPZZ`VdJ^Hb\TVXRJRZVZfHZXXRJTL`TNHRPRNNPNNbTVZJTVZL`@RLJ^T4`V^H`Rh\RRZ\N`^JLb^PLVRLRTXXfTXbVRPFbVTRVLVHNTTf`XN^```XbPV>RTZZLZ^XTF^TNXVNLVPTV\^\DPVL`ZTPPVPLNVP\^RLFLZTf^FRXZN^PHXRV<XT\V`RVHRbXZ\VZLJ\VDbbRZTBPVXPVTLRXVPLRZPNLPZP^PRT\HDTXZZZZhNZJPVT\PHZVPRZP^RJVhhZJTV`bVJ\^@^NXT^^JNHbfLTHNNZVTR P PL TRFR\ XR `TLZL T\V\^NTJZVPPLVL^NNXZVH \T@RV\JV\VZZX\R^LbHXdPJTXLZFPRTP\`XFNJVNV`bTLLXP^\dR\NP\VV^TVPXPTZXL\ZV^TZDXXLZPP\XLXZ^NXZ\Z\bXVbZ\PRfZTXdB`VNXdVbRNPXVPbNdXRJXVTNdNR\F`DXL\dRT\Pb^LbLbPVR\R`JZJ`XX\RR6B`b^P^TXfR\TVRLHRDR\Z^V^XPXNVV\NNZXX`TT^`JXVRTT@P^JPPPNbTh\RVRXbTXN`\ZPT\^PVPRJVZRTXZZRVRPb`NRZPVXPdJPNTTR^JTZXPbVPHfPhLV^\\dd^TX^`\LbTPN``NbTVHT`RbBV^XZJ`XTRV^dRZR^NPd\TJZ^lFb`XZ`bZT\PLbZPR\XZXT`PR^LXfP`RfVbRPLXPZZFdB\P\bRR\Z`Rd<VX\PZdTRRTTXXJVVXPR\`R^VTX^NT^VZVbb`ZZNTRT`L\VPLP^^dRHXJRT`^>XVLXHTZL^H^JVNPP\dXXPRZbbLX^ZfXZZ\`V\^ZZ^V`TTb\\d`VT\^`^^ZPZ^\nb`^JZJTXX\`\`VZbZVThLZVZXRVH`LTZdL^b\J^R`PJ\ZJ`RRfRJVHZZP^HL^XZ`^XTbJ`VLRLXN:j^NLP\T^T\\dX\ZNHLZPTX^`NXXPFnVbZHZ^HVPVXN0HTNRXZXfN^T\hRH@X\TXZXLJb`b`VfVVfTZZ^X\\hX^hjNb\^^PdbVPXTjX`PTXhD\^\`T\LfP\R>bTR^^RRXdPXT^2R^`b\ZjZ\LD\\Jd^PJT\`PP`L\ZVR`V`JLTTRN^b\ZPX^PR8XX`^bB\b`RVNd`TfTdTdNfNL\Rb`RZR\VTZ`LXVN^PTJPRRZL Z` T \ RR^^\TPX \ RfJ^V Z\R\^TPTTL^TR^^ Z X^RH^V\Xp\PF`XP\VX\ TVXfZVd`P\fLXLdRVbddbZZDT^JJ\ZPXdHRP`ZDZ`bRHNVF^TLL`RbJH^`RNZHZZJHTZ\VRH\bJff@XRTVbnbTFVZdXJ^VfHlV^TXbbLXhRXTJRdNTZdTZTbPLRTP`b@VXVfNLV`TRFRLP^NVHRJ`LVNNTXXNXVJhX@bdRPhLNRXPXrVR^LJTJFbVN^JZRPbN`TJNNNVL\NZT`XTZNVT^fZdPb\^bZZVR^`TZN`VZZV\ZXPXFTVdXNL^Jh\T`TjTRbTNbZ`^Z^nFVRrTTDdVNVPVNTdbNbZF^bfPXRVRJTTV\\\TTVRRP`H\\XRhX`PTTHl^T\RVLZVTZ`TV^XVRZd^h`Z^XP@fZbXTNPP`ZfVRZXVZPTZL\\PdPV\XTXZRPdTTX^j`RTX\\ZVd\NT`d\dZZPXLRbLX\V`XZLVfRXVfZNRLhVNTZFPPZDfh`\BffXZlPVXZ^R\TbPbj^TZLRTN^Nl\TVXXjVJhVL\RVZLZXRVT^dNNX\jPVTZXdP`TV`JRRXbHPbXXNRbb^\`\V\Pd^PFXfj\fZZT\T^J\TJDZPZPTfVZZT^V\dLRPXTHDdNTT\V^RLN^>TX`J\RJHN^PPLHZZRb@TZNF\NH^pXFTfTfjVRVRZZV\DPVbXXbRNbXPZR`PXZ\dZLRZFZTTJD`^RT`PHdJRZ\HRPXRVNdd`T`RXb\THRTLTjbRNVRVTDZZXRbR>d\Zlbd\VTfVJTLXNJXDhfLTNF\VVZXPVXZ`J\PRJXLVPHRJRZPXZV`P\^\TNV\XV\VTNdbVPFVZV`VVdPVTPTJVF`bPJN T H h X   Hf  XN XXH ` ^ N X T P  RPP NNHTT `X NXVVPH J RN \ZTXXV P\P P T\LL^bNZX\\TP\ZRN^XPLTRPVTHDH\VdTTThZf^FT`^RVPVXTXJLdPZ\VNT^ZJJV^T^R^\NXFd<PP^TT`TdPL^RPXZZZRTXTXN`VP\ZD\^bRDLHdVFPRJT`VbPZVTX\LP\PZ``Vb<dTJTTN`h\D`XX`LBXTRNZbV^`^NZTdP`^VXP\RRdPVLHXX`PVVFZZH\bVJ\^^dFfVR`ZZNX\VTlP^\^fLTV\X`PNJ\PPdLX^PXVTV`X\FRLfRTXNbT`VVZbNXDTRVH^TTTV`\X`PTV\R`VJV`\LPVZ^RZ\dNhZZNRV^HZ\dLbdTZbXXTXb^bfXbDRZXLZ`ZF`VV^`^^ZXN\^ZPZXbZRPZR`\X^ZR\JTXfTT``P\^X^\^ZdX^H`VRnjP\PXRZJTZRbXXPNH\bFXZVRbPd^LLd^^PPVT`XdRb^PRBTR^HLZTVbHRdLZXLRX`FXXT``d``b``dVZXZ``^`ZjTVXX^N`XVZPZj`^Pb^XP\T^dTPZh```PfTfVnX^LdRbT`RX\ZXXVdXT^VTFZZN\``\fffbBPb`\XZbVJNpNZ\\jdTN^ZhNVfTP`Rb^NVbj^NZJ\^NVLZR@TVTL\RXXZRP>HjVVhVRZVLZ\\^\^JVj^TX^\ZVNTR\TNVPh\TTRPTZHNbbNVZZ^TLXVXR`RV^d^V\XTX\VXVTNZXLRPXT\\\ZZfb^PN`HbZRJ\JJZXXVdZTPLZnXVX^V\TVPfPZbL\\VTZXLZ^VV^V\XT^XNZF^b^JXVTNT`JNXZRXXVV^\JR`^TRDd\bRZZ^F bBZbVNRZ P  \ X  X V ZV J  ` NR H T J X P R Z N  Bb Zh`^LbN `bLTN \NZZJ^HLRXXR\`X^Z \X X\bV^J^ J dNRLVXVXV^RRZPL^ZD^TRPNhT`TPNTdPZT\T\`Ld\f`\RJXPbPVT\THPVRfR`\V^PdXZ^T`JRNfRHP\RTHZ\@n\hN^PNdZ^XPVXZZ\V>XVXJ`Z^PPXb`^`TL^RPNZVV^X\VZ\RPVLL^T\Z^PhVRRTPbJ^P`XXPVZdTdLZXNbTJThT`L`VZb\P^X^\V`ZZf^ZZdXTTNNjRZ^ZVVV\\NdRXTTTTVZ^\dX\`Rdn\P^TTRV\`ZPTTV^^ZVVn`ZPJPXZ`TlZZZ\\V`VdZ^PR\Fd^X`VTbh^jfJNflRT\hZdXNb\NT^bbTdHT\\\PZ`bf`ZbP^^VZZ^RBLP^RdPT`hRbVTRVb\T`TVL,fVXXXR`XX^VdP\T^NTLfV`bVZ\tRNLZH\T\f\VXTRZXT^ZJbZ^XV\TNfRXVLPbVPTZVXTRRT^\j^\f^hl^fR^T\RZPNVVPjXdXTTXXXRZX^bNXX\DLVPHRXZPVRR`b`X`XVJZZ\V`JTbHNHLZbXPTNdVZbXR\H^FN^Z`>PZD^^ZFVZNTZHHXJ`R\V`RTX^VXHVbXZVPZTZVZ\JZT^JLTHXLNTRRPJVZRPXbVRTZL\`\ZP\TFPdF\\XLZHHR^ZNVP\^d@LZX^VfP`V`N\bXP^\RdV@XDXRLPTT^PZPRVPdRLdZdXRdHPTTR\TZXnD^P^TZ\RFLTN\\bVbPVJVN`V\N^LRX`RFTLPXJHTV``Lb`RVJP\^XFPVLNV`LLTVFVT^RPRT\PTD^NTPXRFXbHlNXPVZZH\`DJ \V PR bJ ^ T H \ X  N X N ` N J` T Z T X \ H X J V ^ J T ^ b P T T `  V V  `ZV L T L L ^R \ X RZT\ZLHFF^R\bL \V Njd RZPh LbXdT\NN\BbZF\`HPLTZ^XT\ZX`L\P`RXRTTd\ZTbX`NR^\NZZJd\NZTVJ`TRXPTTb\RXJ\^TLZZTXfV^PNjHXRPTHTVXTbZ^LN`XVXRV^VTJ\XX\`V^^RP8VP`VR\BdX^JTVRPXd\BTLVZZHNVZFZ^ZVZ`VZRTVbP`ZZd\\PXV\N\LVPNVV`dZ`PRRXZXLV``PRTZZN^ZZV\``XTVXDLFPXf^hX`dRXdTLZVV`ZZT\RLbZD\RTN^XVNRbZL`XVbZZZV\LTZP\`JlNjHZR^XVPVXN\XdXV\\\VT\X\`fN`lL\XTN^Z\dZZPVZbbT`Nj`LR^TRVXRdZfXV\X^ZXddTR\FVXRDVVTZ^RTbR`XTZZ\RV\^T^N^R^^TZ\X`^V^ZLLNZVLX\ZTbdJTPXfTTTTRN^NHRP`J\Nnd\Z^dVbTF^XRf``V`bVRNZ\```lbJZ``dZT\NnN`fXd\T\V^\bb`TNZVLVNTDLJ\RJrJLFbbFbPbPZZL\\RdPRVTZ\^`HXRTZZJRXP\Z`^V^XJ^Vh`TNZHRb^F`VhRVLVbX`LVTPNN^j`Jf\RVTN`\^^ZNRb^VP\b`RTV\XTTXRPVVNZT`PL^VXTPbTLTTTXP\T^dRVVZVR\hPXVXV^T\R\ZbVL`XP\ZRFHXXPZbRbTF@`VVPVTdL\PJX`TLXFVVZJLZVHV^TLX^XPX`b\Z\ZRTR\`PTbP`NXR^f^NTZRZVT`^T\`R\`TLb\TZTTVX`VVJLPB^VR\`X`b^^V^ XTX `Z T N j R ` T L V ` X  \` X Z b N Z \ V V J V  T P `P Z R \ \ ^ D ZX Z ^XX^\P Hd` J\ VJN X X PT R f Z X ZX\ ZX V N T >^hf \RPB^PPXfVX`\TVPXZJP\TXPPVlD\RXR`jNLdJTPTlTPdXTJRVHh\VZL@ZPbPHTHZRR\N\ZRPXX\NP`FTVT`XXhRX^ZZ\ZNZFZ`LZNP^\XV^XnNTLNH^`Z`RTXTTfP^VXRJF^LTZZVP`TVTVJZXRVBZVhLXFfV8bV\bRNZVXVTVVX\PdV@^PTZ@<NTFRXRLdXRb^^\RFP`\bTTTXf\`ZdN\XR^JZbZfXNFfLb\ZZJVhVdTTL\X^`Z^^TX^fVNdP^Z\BfXRR`ZfV^Z^f`ThTjNXZLTbjRPbdb\P\PP\f^PhJZXTR\ZbLX^VdZZPl\ZV^R^L\RX\VTTX`^ZbRXZNTLR\ZJRTPZZVLb^XRNH\^bd\VVNP^B^bT^RT\Z<TJ\RP`^PfVVbZX^ZP\^PL^RL^dLVZNNTZRN<dRdRRdJVVZ\HR\`ZRXbTTN`XNnNNj`TPlTXZ^Bhf\RPTR\XX\LZVhPb\TZZXRPL\HHFVZ\TRHXRNNN>XNXVPVXF^ZP\dRVNVHfZdXFRZVNVLVVTH^TPF`VbDRJRTTFZPTTZ`^RDVRbVTXVVZZTVLTRZVT`PTVRNXRZBZZNLR`RPTPPZbVLV`VXbL\fX\TJLPVV^N\V^N`TDXTTPRVZLR\^TbRXVf@^PZbZJ\PXJTXPX^PddJTLR`\LHPZVN\\dV\ZRXJVT`\hTZLHHVN\PN^\HVLNbV`V\N\XRPJXRVNXZNRXRVRXPZ^NR^FbV`\^D\LT\\V\VNTZFTTRZP`\\\Zd^VZb\^\VVNZR>bRFNR\XDP `Vb ^ T X \TZ R X P J L ^ P N N R T R R  V d Z  J  d ^ ^ \  ^\ b Z R N Z X ` ` h P T\ X T  `H XXRV  LZ ^ X R T V R  X V Z P VTJP X\N PPZNDJPTPZNPXPJTRLJRVTJ`JV@FV\N`N\<bRPV^:V^V\LJhJLZXT`V<bRH`PZZfVNXJVXHL`LXVNXN\NHX^HL^NRPVLbPL\^H^ZP^VH\XRVJZZ\PXRVRNTDTRXF^V`ZRN\TXRLbPPNLVLLVbJNVLfFDVXR@HLRRXLNDZTTT\DXTT`\bLVLN\bVVRNPTZVR\VXJTd\RNV`ZTTbdRXRJV\PZLX`LT`XfXT^VVTPFZn\VX`XTPZJTVTXPVR^TVV\ZX^VXTXDRfTjVPXPTP`ZVNXVhRT`RF`VRV\dP^LLfVRVVbbPZ`TZZb^L`VT^RV^ZX`Z\Z\^^T^ZPbR\ZVdXR\ZXTFRT\RZZ@djdRXVTRTT\TN`NdVVf\ZX`ZfV`b`RP\VRVX^RVh^ZTZRbTVb\PhHZZd^X^HPhR^PTfF\PZTV\P^bPVVPNV\jhbZTd`V^N\LZXfR^bb`VXXNh\n^^\T\hbV\bZXRNH^bJ\R X`\\XbZ`b\hPVNn\`VNT\XXd`R\\VZXX\`^\X\ZLX^VRPVR`dZVZVPTdjZ\dRb``XPTRbX`\FbTRZZ\d^ZZTPX``RTZPTTZPdTJFZR^RHZTX^R\ThJRLNHTZJbTD\\^V\V\XNRRPRTTTXPfXVPb`PHL^\\LbNLRZ`PVTjTVXlXJhLNF\ZZXNXZPRRPPVPNVTTVD\ZTZ^RXVR^ZP>FVNV\RJZXZVPT`TV^NVN`RVXjRHV`\RX`NXZLPXBdF`VVN\ZZZTN\PVXRBRTdF`^T\fP\ZNZT`dPXXN  ` R dX T  F \ h \ T R P f b  X N V T R \ X P R \ R V T h L P ^ P \ L B P ^ R R Z H Z  H R  J ^ B \Z T X ` `^V N V P ` \ \ B b V \ D H b X ` T Hdb  F ZXbV^ZdLRPNZPZ TFVX\RX\V^^TNVNbVBXV`DFZXbf\R^VZR\PZRHNRVHNd`\RTRLbJTbXVdbXZJV^^lZXZLNXVT\VR`NZPJbTb\`dJ^VJZTVjPLV`H`PNFBXXPN`RNTPVRZLXLZbX^XX\\T@RNXFR`RPTVVRX^`VRXXPP^NVPDNdJLdVL\fRVVJ`X\RNTTP^X^bZXP\^RbZTV^X`VVX`RHZ0BXP`TT`d^T\4V^>Tb\TPVPX\VP`\ZXTZTZR`ZV@bPPhP\R^VRR^VX^ZTZ^^`\bZPP\hRRNd^^TN^NXR\Z^JfTbRH`TLTRVXVRVVVVRj^\NNXRNR`^Xl^^\X\XbRXLbZTHNX`PRZZVXHTHFPbZV\VZ`\Z^XLXXfNVZbZJL>dJTXVRXVVFN`XNFZPb\zTfX\^V^PXPP``RR\VfZ`P^^TZJ^XVNFPF^Z`<TTf\FfXbTZRTRZjT^RP`b`HX\bV\fPfXZ\Rf^R\TZTV^XXNZTRNRRVHHFJVRfZTHd\RRXXJPb^^Rd`PRVVHZV^VN\TVbTXRf\DXZLLZHTd`T\fTXXLVZR\TDbP`ZP\PRZP\^VNXdVVVR\`JFT\XVPJZZV^NXbJdJPXV\VRbTZ^RLPPLJV`V\\^ZXZ\TTFT\PRXJbVV`hL`fXPHRZRXP^j`VRb`J\XHJT^NXVXRFVVF\VVVVXZRXRLXP\\LTLV`NZNZbNLTPH`ZV^RJPZPJX^RdHP``L\NH\`TTb`\\LTVRP\RX\V`\LbPN D`V @ \HN X \ ` F d R d \ D X D ^ B \ ` P T b D V X R J Z Z @ Z R V T N J T J h T N N P P b ^ P R ^ V N J P D L X ` Z B R V Z N \  J  \ P P Z Z V ^ V P b N Z N L R  ^ P \ X TN\XZV X H VLNNRhHNT XHTLXhPRZRZdFT\FR\\^XVR`TPBVVV^l`XPLRLPFhVXX\Z`NT`d^RVVbJPTRVDXZPfPVZJfLT^^`hdN\DPVVRRNbTPNPDVVV`Z\T\XNNXVNZRL^^T<V\P^JD@RRTPdV`ZNX\JTTVXRLXR^J^VPXTj^TL@\VZJVVRDhTLT^`ZXZPTRXRP^Z`TXlVd\PTLR^JTLZ`\JZ\ZRdPVTXTX\R`L`N\dPH`dPT`PLbZLXXP`^RXL\LR`PXTVd\T\X^^LdV`FR^XV\RHh`^P^BZZZP^RPPdV`XVZ\R^X^RbXN\hR`RRXl\dT`f`fT\RTbTdR`d6VJ\fRbZdVXZXX\`L^V^V^^XPLhdXVXZTTjJZZTbXV\Z\TX^ddJTVVRZ``R`Xdb`bhPLNXFVHZbb\VZZPPJ^^\ZTJ`bXbJRVL^NFbXNbZ`pjZVxbZ`\R^PZb`dX`XZfRPdXb^XdVZ^P\H`<N\LVZ^fVPJ\`VRX\X`b`^LXN`VTXNJ^^VVjVZTTVT\ZT@VX@DFRHLVRR^DP`XV^bfNZfXP^VZNHPRN\NVXZXXVLV^P`TZZLhFFVVRjNPBdJNZ^RZLfX\N\T^f\XR`bR\\VZbJ\\L\dbDJZLN\V\L`P^Z\ZXT`XnH``VbRNTVfVfLXfT\D^TRR`h\ZdT`\VNfbVXRZPZXXLZT`VbVLNVT^VLZTVHVLRVPTVZT\RVRVPRRPRFjZTPVZZRZd^X\^VRZZNVRL`^PXVZLXJH\Z<LL^PjZXTXNJZ\LXhZZjVN^`LR XF P  ^R P  H ^ P Z H \ X L V V ^ Z ` B R J N V b L V P X Z ` \ R T b T P X Z Z V H V J Z L Z R Z X J ^ \ R ` T \ \ J P X T N f ` T ^ Z V X ^ V X f P T  h P TT T TTN FVPd NDFP N^ XZZ@Z\Z^Z\:X`RXRPLbTZXPPXVJNJ`RTRX`dZ`N`ZNZRP\RZXZT^TfNRJR\VVZRNV\VbR`bXX`Jf`RR`^^RdHPVJXLXHdNXV^\`TZbXZ\PfXJPZ\T\ZTfR\\PXVXXX^`Z\\JZPbVb^ZZFRHXZJV\ZX`Z\V^NNVZTVFJbLXbX^TbNZXPLX`RNDTTZVRVT`ZRXZ`RZVN<HR^XTb`PXVfXJJ\^Z^\TTL`d`ZHXXX^\HZJTNZZ^DVb`\J^TTVb\T`JbJVjVZX^fTRXF\TVZfV^ZRJndZX^\\`PThVRVZ``T\T^X\BbPN^ZPVV\RRPjRhLZX``PTVZXH`TZVR\^\ZTXTZRRd^RfVZJVVdX\^R6f`T^bf^ZLZRVlJ\\R\<dVNPZ\T`VH^TRbVTXP\JXXh^^`V^Xb^^b`^`\VZ^\dZ`dR\\Nn^Tb\T^RR^bbJZJX`X`ZVdZLT@XTPVD@\dpZ`V^T\TVVV^PZb`N\\HT\NV`L`X\XZHRRV^bTPLZRdTVH\XRXHRTZPF\T\XZV`TZZPfXXZ\TLXhXXdVVXZRVb\TVJBdN4PVRRZT.dZ^FfVTh\TVNbTLZBT:`XRZ`BVVR\NRdTNXVBZbXX\XVTFLdTZRVJ^H\lTPBdN\TRP`TFVVLdRVXN`P\RZHLXZPL`JLFXR@b@XJZNHVPdNHd^TRNVTR\VD`H\RHVPT6bRTTNbLZRR`VTJ^VnJPV\T:^XRJX\RZfL@FN`XXPdJZNNRPVLHVVPTL\TN L T Z d  @^ \ P N R L N D ^ R > P f X ` N X V \ N P R Z T ^ T N D V Z ^ Z V X X \ \ J V N Z ` J V T X b N X P Z ^ N  H T T R f X \ ` X T ` d X @ \ V X L VV Z R NP V R V JZ XVT Z T b P^^@XZZPXdHPNbVLNZNVTTN\VDHTVPZZVPbbPBTT`fRdhfRTXTZVTDXVV\Zd^fJTZVRN\^PPJZ`TPXPX`hZPRRVf^^PXNb`dVVFR^RT\^bR`T\^ZZ\\DRNV`RNHVPNZ^VdXXXJdRPRTdNZL`PDLPPZRhXXVXD@ZZRbR^XH^FHVZNNVLTP^\d\`dXJTXJZRdRNL`^fDT`TN`\H`PPZZXH`^fZd@^XLLZXNblRZRXVRZRNXX^PZNPbbFXdNP\PTXLZV`JNVP`PXf\PR``N`XTbZLPTZXHRX`J\jX^`XLdPZbZT\PfhVT`\bX\\LRdf^V^N`\\hZ^VfR^V^VPlVVZbV\`b\\Vh`LVRVTn`VFR`N@ZNLZP^XRZV\V^`XZZVP^NTLTRN\P^R^TX`PVXVL\VZPHNTR^`Phf\XFZNr`LXR`\X`\\bh`Tb<`PVXhN`JTN\Z`V`XT\\^\d`Zx``^VVRN``\LZPH\`NZ\TXVXLVLhXZZbZ^PTVXRXN\NLXPPX\VRVVbTTRbTHPVfZXTdPZRdXPTZVPRFP^NJRRbT`^^Tb\`VVZX`fbLTX\RNbP^`VR\RVbVRXXLVJL\PTZJddLVLVdThXP^R^L\HXfPL`F\RZ`VXhX\ZZfPRVTNVV`B^RdV\VPdVFjNX\LZVNV\PP\f`TbfRVPT\P@TZnN\V\bPRPPbVX^T^^P\^l^TdXX`^bfbdL\TT^RT``ZZVPRfZ`VdX`\Z`bbh<XT^LJfRX\R\VDFX ThRV Z b ^ \ @ R ZT b P Z ^ V R H J T N T V T d ` R X Z ` Z b T b \ P \ T X T N ` \ N X X X R V V N J ^ T \ Z R \ Z T \ T Z V Z L Z N P @ T R R R X T X f ` \ X R L T  T^ \ L  ^ TZ b`` Z \PZPVHBZR`LHZLTNP``T^RNdFPLVZJ LVJPRZ`RN^^PNVTTV^`ZdVTZXX\XbXdLHVLTPT^\^b^f`T\TT^P\ZX`RPTLT\ZV^RTJFXTZTPT^Xd\RX`ZTRhTVj\^ZV^^NRL``L\VjVNjTT`RVNH^`ZTRVdPVH`RZRJZdXLJhJV`^`PTXPbVVdhXV\R`PVXZZVl`VRVTZXVdZVX^JbNdR^V\Z`RTVTbZb\^XTfRVP`fZXXJbXP`R\LT`LZXVhXNJZ\ZX`N^`\ZZfXN\Z`LLdN^PZ\F^XRX`XZ\`RP\bN^XXZZdT`^PPZTdPb^P\TXdDZfRTTNdL^RV\X^bXdRZbTR`b`NPTF\ZT\dbdTXfXL^^XfbR>Z`d^XbVT`HPTNVRVTBPXbXRVTbRXf\NT^\\f`VdTZ^NZZPNTLXdXXZBbV\X^X`XJVbT`ZNPVPRZZPT^PV\RbTfbVjPZ^Zf`NRRd\\L\b\XJZJZZTPZ^L^^\\LhFXZFFL^^XRZJNZTRR\RVP`RRbTVZhNLfRhVPJTTdLRPJZX:V^NVTL`TZNZZdZ^VL`XTLZNXLXbJZZVXZNJRXdN\ZXXB^FLRRTVPZRRRTFL^HVXXRJJrR\VTbXVVT`\TXVTXVRf\F\^X`fZRZZZZRbP`V`N\^TTN\VZVVV`HPLD`TZfTX^^RXJNNZXXLT\`JZ\HP\LFZLVRPLXP\TP^HX^HRL\X^BTbhJTdb\R\XNNH`@\\TVVRFPXVbFPbV^X\Xd\RNVTL^bL`HV^R\^LTNLDX \ T L ^  ` X H T Z \ R V F T f ` b X ^ R J R V \ V N X R ` 6 H X Z ` b R L V ^ ^ V \ V ` N T ` T T ` P ` N N L ^ b R d Z b T R ^ R b J h \ T Z X N^  P \ L P \V N V NNV Z PTV\TLLNPTTVVHXRNTVZZVZN\\XZLNXVRLDZPHJN\VZVBZZRRVXJR\ZZTTPHBX`ZDR^`PX`HTJTVlXN`jFFZTbFLXDd\X^lNTXVXR^HH^\TXT>XBPbNNVRJZXZVZZZ^ZbNJN^^TP\XXX@XP\\JXZVNRXbVFRFPf^PFX\\XZF\fVZHhXHT`R^J\VZNRb^b^`VL^VRRLTdTN^^PTXZVZHHVZZZTXVdXT\NVZ`V^VZXPPVZbJZR\8V\^LPZ`F\NLTLTHXR`HhRVVPZLPBTRRT^\R\`RTVBXZXLXV\TPJTP@ZVXZZTVR`R\ZXRZhZR``LVPPXVLbZX^VVbTZTbV^XRR`FVPXX^P\VZZVdZT^T^X`TX^VF^^VR`VZVPT^\Td@LJN\NXZXV\RZNNJFf`VV\LN`PT\dPFV^TXbRNXX^hjbVj^ldVP\\fZNZTbTdVNfnlLb``V\TT\^X\`TTXTjVnVRf^TZZ^ZT\TVJ`XZT\V^X\P\df`lVbbZ``ZdV^`TbXP^XXX^N`RTfVNVRZP\XV\TVRLVX^^JRH\RXZXJXRV`HZT^XTRFXJ^RVJ^J\TRN^LbR\\`Dh^ZTfTVXnR^\FV`^XNTRTTTJb\RTXN`J\\HVL^dPTZLVbbZRL\XRBZR`VVR@Z\V`P`RdVZXP^PRNF\LTfXXPFR`RNVN`RL^T\LZNLHTZZXXRTZX^V\LbZX\VPL^T^\^dZRLVTXZ\XHR\VP`RXbL@TRXXVR`\`bL^\FVbHTVXZNLLFVRLnNHTPT\T^VP^j LJ T  V R f T P h P R Z X N R L Z b ^ T f T b X Z P L Z P P J\L X d N Z @ ^ L ^ H b P H \ R ^ Z N T N d R V Z Z P J T N Z b T Z V P T R T ` X N V V Z ^ Z P X f L V V R T P N d R Z T T \ L X R \ R F R V X > b R T TV V T V Z ZRNR`H`^NJbhHfVX\NRLjRbTXFZX\T^fTZFVZZN\XRXP\TRVVDbbVZ^\VndJLPLRFdfJFP`TJbjVPVXHPJ\LV`XZf^HhPVFTBXbVTTV\NLZ`TFD`RRbJh^bRbP\RRTPH@PhDP\bLTVX\Z`HVXTTVXJVdVLJP^RXTZ`\ZZ^\ZVbTVNZVZXZPF`XZT\lRXVP`ZJTXXXVR^^^RNbXXV^LbJ^PL^VR^V^NZD\P^\ZTX`XVP\bP^TP\ZX^VZpPZTXXXfTZdTbZNL\V`ZhVZbbZBPLTNV`XXP`\TLX^F\^hdFdXJdhV\\V^R\\XXd`LZfX\````XVTNXd`^^NH\\fXX^T^VdNb`X`\`dFNZ^RZV`ZZL`VL`XnjXZ\RVb^^\RRTTXXZLPXJPXXFVJXdLRVTRVZVfJRZ^\XV`bZ```TV^f^`T\VBRbf`ZZ^XT`V^ZbZLZXVJ^fTVR`TPRT^ZbNZBPN`\N\dZZTTL^>XLP^@V`XT\\`b\^FR\JV\VZH``DZNXH\VTVXTNbTLRZXVHRNXL^V^\d@ZVZTZZXHVRd^\PTRPTRT\JRVPV^ZR>TB\TRLRJBLTZRT\TNhPVVHZRL\\P\TRXVTXZXVNVXbV^bNR\RP\JZd\^F\RT\ZTT^NNV\ZZ\RV\^LLPNTVX\XX\ZPXXTV\dPV\\LZVV^P^RV\\HLP``VH\`V`PHVNBV\NTT\TJPd^LXZZ^TXXdLXTVb`VTDPRJ^PVXR`\LNPT^XVVZZT^bVP`THbZjPH\ZTfP NZT \ b T ZbL  VT N N \ X P X X F L R ` T N L T ` d \V X V X b ` X Z ^ P N ^ L T P R ^ P Z P Z D \ Z R T ` L L ^ R \ V d N X ^ ^ N ` J X X P X R N b Z N HR V Z T \ Z Z ` f Z X ^ L X J T T L` V V  \ P X JbHVXXPZXV\bTRTbTD\TRRXdTZ\fPXX`VVbRLPPjPdR\^b^TP`NVTZVNddNXVVbDTL^Z\^TLNXPPZXNJN`JXT`PLfZ>RJJ`Z^PPZZZRNP\PL\\\LLPPXVpJT`ND`XB\Ld^RFbZ`PV\NTXbRfTTH^VNHZLXVN`PZVZVP\ZX^^fPB\PX\LTJVN`VPXRX^JfX^XPF\JPVZTLVPVP\T\N\XPPbTT`^bVLXV`V\``R`PTZXPRVTjddLX\X^PJTXZRHNB`RLTLRNDZPZP\bFXPTVTZX^PLbR`RTZ\bRX<h`XXXRZj\LRT^hTHP\RhTTXR^VZXL`ddH^XPd\NZ\Lb:VdZFT^ZZ\X\V\XVHR^LVVdVX`T\RT`RZ\JdbNTPTVZVTVfT^HNPD`VTZXXNThTZRP^\\dXbVZR\Xbf^bZ\jVblRZV`XXTXbHVVXZRT`fbRRLV^\V^dFdb\LXbfRXZ`\VRRTdXVT^V\LXTlZd`^VJDbXJbV\\ZRNPT`T\RTTT^VFbZVbXNX<VXThfLDT^\RZPTRbb^RbN^V\RVTNHP^PR`\\VTVZ\VNd:^\R`JVZP^LXZVHNdTf^bL^PNHThPNR\V\TTLPXVP`JR^V\XHX\HTV\TPZLVR`ZVb^Z^TPVjTj\RNVVZTbPT^DTdVTNJX\ZPZXd\TN^RNXVTHNNPVZLNXFZP\dPhFTb`NFbXRPRTbXLXVNVNR^ZTZfX`VbZZTRTXRHXR\\\X VVZTVP R X d b V X L b ^ T V b V P V N X Z N ^ T P P ` ` X V h N T D V b b ` X P R P X N L R T R Z b N T D JVf P L ^ f P f ^ R ` F R X b R Z Z b V J X ^ Z P X T L l T B ^R X d \ L \ f \ Z R ` R d D > X V P V ` X X  L X R J \ ZR V P X^bN\\ZXXbTXVXnTfN\LP\^\HP^TXVljN\\DXZlRZ^T^XHXPTXXPTXXVL`\Xh`^XPXRTRNPT\H\\TdVh^^fdH\TV^`Z^XNZn^\TNhF\LT`\PdbZT\RPRN^^`V\NZZhNT^TVTd\VPT\Rf^VPP\N`dRVbhTXVdT^XTJPV``R\PV`TH^XVND`^PLFLXVXbJXXLT\R^^PX\TLBnJd\^NT\R^^\RVVVLH^HZZRZ\PVdPZTZLRjTT^T\`P\HTjJ\RRDV^XXVhR\XX^h\V`LDfT`H`P\^R\b^TXjPPV^Z`VbVjR\bH``TNNVZH`N`PXX`hLX`P`Z\FX\Vfff^Z\ZTZN`^dRPZZV^\``\P`XR^VV`RZTZRdVTL`\^PTNFRZRLF\\^RR^bZ``T\VTPX^\TTbfVXTVdRPZRR\@RZLNPLbN\`ZR`fVN\bRbRVVHV^RXbXdbPVXZVVRT\^TZXRd^D`JPNVPR\RbH^T\HH^bd`\^\JR\ZXLLZVTZZVTXT`VZZTRDPHVPRZRFJTLRLZ<PVVN\ZPDLhPFRR``PbTThX^THXTVdTVbb\LXXJXRJNP^`dTVXRXPfXPHZVbPbZTXTH^NTb^VRFL`NX\VRTTPNNFPZ^\FBX\ZLTRf^`hTLTN\XPT\ZTRbXBR\PLL\^TfRX^RDVNl^HJXV^nZTjX^RT`HR\fNTPJFBfT^THJLjXPPXZR^VTN\H\L TTHP \ J T V J \ \ R ` R R V Z \ T f J ^ ` V J N ^ Z \ P ` ZF V R F X \ \J F X PPP V Z T XP @ P L X T Z b T ^ R X Z \ V L \ L Z V V R X TL X R R ^ V V V^ b ` T R R V b XZ Z \ R L R J ^ ^ \ L L ^ X ^ L \ H R J L ` R \ V T X `bT6X XPP dZT D `TZDL\hXNRTPLLPTVPVVNXDN`^VBXRXVVVRBXPNL\JbVJ\\RHbNNN`bLXVfZJbJ\P``\ZTLHRXRdTZ^ZZPTPRNbJPLXXZbVPXXVddZX^VRZb\^RbF@fP\ZT`X\XPRRVPbhVPTRnPdRZPfZR\HJT^`TPVVVXFVX`XX\bTTTRNVRJPZTFdV^RVRJLNZ^TZ\\RXRThZZlTZ\ZTHdT`P\LLbZPTXHdDNJVdTHVP\NPTbR^PR\P`PTXT`VTZNRP\d^TNdJjNdJbVd\jNVT^hRh\V^N`N\J^bb`JNf`bJVR`XZTVRZVLNR`Tf`P\Z^LZXR`Z\^b`ZhNP:RLVTVXTN^PXbXT^b\PZPR\VVZXXZLZNTTNXTVRR^VXjVdn\XZNZV`dZP\^H^ZblTVTVZ^d\VVTTVLZdNXRNPLb\PHRNTVRd`^TZTRbZRZ`\T^VVPT^bTRVbTVdZT`^`lXZb^JV`VJP`PVTXTPXNhN\VRTbP\X\Dl`\^JXbTRRTbPV@LPR^T\VLTXPbVZTL^JPRXP^HVRdH\R\VT\LT^VXV^\TRHdPVNTfh^LXTT^TTLZ`\XVXR^RZXZbD\l\VhZNRHbLHTTX^TRdZXdPTVVXTTd^RNNNHbfRXPRJZV`NdTPXZ:bbBZX\PTZZN^``H\VNZ@\VTXTTbNFRXVX^PVRZNN>VRdVVZ^HR\VTNP`VZZJ\R\P P B T PT X X R R \ P \ X b X P V R ^ P Z ^ V b ^ R  Z R j \ P  J R R R ^ \T R P R ` d Z N Z b ` R V J \ V Z J h Z b L R V ` b V  ^ L` B d ` R ^ J \ V ^VV \T` < X b X XT R Z J X V \ F ^ T \ L X T X ^ T L H X T ` J   L T N Z X ^> PbZTZPfJJJJVJl\TRTTRV^ZTXPXdXTR`TPfPHZN^D\ZLT^NPVfXPXR\^X`\NZbZNJ:HfTR@ZPdP\\T`V`XVXPZRbXR^^HNN`\bJ`T^Nf\RdblLJ^b\`XRRTN^RdZVZL^PdTlTX^^^LhZ\TRXTbXNZP^bNR\TdVfRd^T`ZZ``ZZ\NdFXV\NT`NZZX^XP^PZVJV^ZP^RXNf^^TXTV`X\h`\\TPRJXVVRXJXLJ\XTJDf<`h`dVJXZX^NVbRb^J\Z`^f\TNTXXZRbRJ`ZfRRR\NZXJZRPPR^XVXPJ^NXXV\R^f`RHZZ`XbPVbJ\VNZFdN\TlZZRZNT`RR^\BbRT\XZJh`L^NfVVV^@VZ`L`^RPVPXVTX\HPR`P\NRN\6RFVZRVdBZT\\NNTbDXTbTbb`T\\R\N`^T`Bl`^\`PTR\NVHXNL`XRfLPb`R^JDVNVLNXb^P^`RTRZZFR^^\TX\^V\VRT^RVNZZ`\^TPT>`VX\NJbJRTZbBXFlVZTT^Zh^PVP^VJZfBTbNX`TP\RZ:VTPNbRRZTZLPZVVNd^D\FPRRXLLZbXJR^\VrDLXJLVNZ0P\dDTdVRNVDb`\^RTZRNVZR`LNh\PXdXP\XTVNRLV\bdXPVZNf^NV^LVbJXBb`FVXNbT`ZZDZRhTX`VVNJPPDT^T`LVXjRJ\ZRbPPF^TZZJZRXLTRPTP`RJVXdT\X^\T`fbHTZTRXTdFT`JXdJ\RPVT\dJVbZV`BZ hL L T X \ ^ T P \ R T X T d R R P L ` V Z \ dD R Z \ P \ ^ Z ` R ` P \  P  B  P R \H J V8 V XV d P \ J R  ^ ` J R \ dRZ R N L d L NV T ^ d : \ b V f R  d < Z XPT NX R J X^ D Z Z Z Z Z N \ VJ P H ^ T \ b F L T ` ^ R V T PH ` H \ ` P HVPX`^NNdVTNbTThTTTH\LTbP\^nXPFXJNHLPRXRXZVZVD`VN^\`NZ^R^ZVf\RPNLXZTbbTb\`XXXN^VPTLVZXZZXNPLVhPZJL^PLLVR^XT\TZbTPPVRNH^TZNR^H\XLF\Xb\`VZRTRTPbL\XVhTRJLZZH\NVBVVVXZ\VXPZV^VR^X\RZNVRNNZh``DbH^fXLRZVjZf`ZZbV```RZ\RXX`NZTX^NXRVRX^^^f`HZPRZ``h\JhFdFZ`VZVXdR\ZbVP\TVRRbdDXRXRbZ`\XBZ`dTVF^VLbTTVdPJVZ`FZXRTXXXZZ^^VXdjHR``ZNbZT^Z^\\b\^`XXXVVTT^\f\P\R^LD`^ZRFRZ\NdTXRXj`^h`TN^b\T`Z``V\f^DX`LP\NXTLjZZbllZJbbV\Vb`^dRfTVL\fZXV`bP^R\ZV\PXVT^`V\Pd\TNT\L`P\Xb`^`^XPZR`XdXTF`PX\Tb\NP^ZRZX`R\bRLRRXJhP^PRZ\T`XVXTJZNJTLRFZhTNfN^XZ`XThX`PVbVJN`LNRV^T^X^^PFPRDVPRXjPTNTPRXNVXXRbTJVLPV^`DTV^PZhPXbrNZfNTNbZVPfffVPd\b@\X^nR^``TXV`NJX^VRVPRH^TVHZL^\^^@bLD^RL`RJN^ZV\ZjbRZXJNbL>XNXPfX^LJJTPXRNPZVTXLPL\ZZbN^TZX`VRXNZVTZJHZ\`XBbX\bHfNRN^N\Z`XVXfXPTZNXRTF`PdRV Z V TR L Z Z J \ d V V  V R Z H X Z T V f N b R  P X \ T^X H LP H`T R Z L J T \ N \Rd Zb\ V V X RV Z`H\VTR TX L X VH ZRT\X`X N`R L ZR d L ` X T R \ N T V T VR \`TV\ ^TX` \ T Z \ Z V V^ d h H V T ` L \ R X N F X Z D X h \ X b @ X XX PZ^VhRTTX`nTTdVHd\NVdXdXZZb`JTV`V^PdhZlZ\LN\J\LRTXNNP\NZ`DVRZVJfNbJF\LZTbRNH\b^X`DX^NPVRRNZdXZZdRT`^VLRTLNVTBRPRVRPZT\LDdXZ\\FRRPVTLNV\RZPZ\V\NbLV\XhTT\^R\ZfbFdbbNZXNV`b`^X`RVb^XVFZVRPXXXV`RTTXZZZX`LJbTTL`NRj^`\ZZN\\^VX`TTbX\HTVPXRP\ZRXNR^\^dRTP\`\NdPX\NNP\ZLjX`RZ`dbN`Rh\`^\^h\fR`\^^\V\LT``bb`dPZRVTLdT\d^RPXXVTV`XRPT`Z^nZT\b`XTRR`bR^TVTTZdVZRTT`^V`TPRXZT^N\\`VPFRZRXV^NLdV`h\``TT\dVZlVd^VNX^`dZdZ\j``VZ`XL``\TLfJJRRZP`b^ZDH`^@^V@^ZNZZHVR\XN\JZT`XVZTdRX\\LXfXZTNLXV^XN\TZXHZZV^\LT^\^TT\ZXP^TVZJPXVXRNZVZJ^\FXVXTL\`TZ`RHLZFRNdNJRLR^\`RZ`VPbH\VRLRF\VZHZbV\XZRRXVNVTVNVRDTb\bZV^RL^NTXXZT`VTJXPV\H`\JXPHPJRXPF^Tb\L\VT^T`TVPJ\N\`J\V^^VNT\LVXVPXXTJP^RLHLXZ`ZXb\X\VZV^FTVNNVXZJRN\`NV`V^RdHnFTVVTNZRVf\bRR`PZ XL LbR ^ X F J Z L P ^ ^ J L Z B V T ^ N J X X R Z NT\ L TP` ^ X ^ T T XT\BZLP H H DL\J FZ Z V f L NNXRX`X L`TVV LPR ` N RV R T `PTV X\JZ\T P  ^ N  Z X : R P NL V N J \ ^ d R \ V b b \ P ^ X R P N Z d N J^bHZT^N^Nb\\NR\Z`XXV\VVTdNV^T`ZT^V^VbX\\L^\b^d^XRNZXV^^^NZLDXTd`ZPR^NVXhNXNPZRRVf\TfTRbRNXZf\XR\NVZZ:h`XX^RPdLPLbXXR\PX^ZPZTFb`PT\Z\X^TXTHVlTdVFLLVNT`Ff`XRLTNVXPR\Vd`LbNVNVhZZNRXXRfJ``^FVVV\PBXVRZ\\^PRXbRHRb^dZ`T`VVLLXV^V\ZPXPRPX^JPTXRZ\JTNVJZ`RRff^P^PTX\^XTRTbZTXVN\ZXPZV^N`R`dPnNfPfBbDZTLZR\^JX^VnTNX^`VJdXTV`T^X^TZL\ZT^P\NRTNPVZ`dNN`LjZ^LXRVT^XVVX^PLX`VN\XLXTJ\JZPRHV^NZXXRR^Z^b\`hf`R^d\\PjXZV^^RPV`Z\f^V^VV^^VbTZd\ZZ`P\ZV\P\nVVJP`b\LNN`fZfXFV\R`\XVZRPPTVL\TJJ\^\NZbTZ\`FhJRTP`PPDRTBVRPNPnRLZNRZZVJRTXbf\XXDbRlX^dLPZ`XPL\VTRTNZH\PH^J^PZRRXV^\HR\JbXXXVXVVX`XT^FTXZTbPVVTRXL`RTXT^VPRXPXlPT^TXfVVXFHbP\HVVT^RPPNNRRTVT`B\XbV^VhZPbNPR`\FR\PXjP\^XZPVXPL^NV\T\VRXbTVZJN^TJFRdRTNZ`LV`NR\V ZV LRH  T d T ^ Z Z H Z L F R T L b Z P H N R \ L X P Z T T R X\V V ^X Z P``^J `R\ F RR Z RNd\R^PPNX V ^^ TPdVP\RT XR\XbVVZLZD fN V  F  V X@X RT X^\NXL Z  L^ b T XZX b X X X J V X N T T R V \ J d J V Z ^ T ` f \ L L L ^ TR XRRJXNPRP`T>^ZTR\bP<T\V`RT`VL\PLRRZRVLJ^RdZVVNXRVZPVJ\^NRRVZ^HPPR``LRLTX\F^VdN`XXXPNbHH\dVdPR\L^`fF^\HPTLRFVZJRJLNXHTPZ`jR\ZfHR`\\NNJ^ZR`V^V^fT`PR\fRTLXZD^P`bRhJ^PnXV\V\RV\X\\Z`VR`\Z\bVRZZVNb\TXTPZ`^`^hDV`\d\Pf\V^^^LXXfZZfNN\ZVbT`FTZ`P^dZXd\PRTd`TRZ^PdJVNjbTZX\DV`Z\XZ^XVV\T^VVTJ^ZNX\R`fVNLhPZhPL`RTT\lTXPRZdVTXbXdJ^`TP\TPfTf\RFXXVdLR\j^\RPNV^NZPJP^ZXP^\VX\bVfN^bdbXdXVVZTPZdDbLbR^RTXdTF\XTZ:\`\VPNR\T\F^Z\P^^L^ZX`TT\RRZXZ\VnXTZTNV\XR`lJX`^jPTJRdX^\bTZXXZJNhZJJTHdVV`VP`^VRZlX\P^Lb`ZPNX^XNXRLJL>RFDR^VPPJPF>`RTfJP`VP\LR`RD^P\RNZZZL\HTL`\ZPD^P^VRTVTTNRT`PT`TZdPRRTT`VV^XXVJ`\XJHRXTP\V`RZRNTVNRXRX\\NJN`H`fVTXTRRZL^TL^\XZNdXdXN\DFPZXHZDV\\VPNZXXhV\ZH\VbPRT^\P^T`JXTNVBZZPHJ lVV DXR P X X L \ T F V V X T \ T ^ P \ N P L ^ P R T Z LD N NDXd LX\R N NP`TR fV P VTRNdZVPLZX\V`VRZPHZTVhdPPXR\XNVF Tb R j VPND\VVRHXR\FRHhR\ JNT PZ>LPX XZ P X T ^ V ^ V J \ L N Z X J L X ^ T V ^ VXPRJZN\ZL\ZPXhXP\ZFZTTPFn\NVT\\NLXLV^`TTXVLVXTZ`bVVbRVLPNTP\VR^XZ^NLVTV^^`TZRVNXV^TbN\TV\RXbZX`X`JXdRPdZHXRdZ^bT^RVhJVRTRfNTZT`HT`VVPXVdfXRTdbZNfRT\XXVTXX`J^VbHV\TZNTDJZXNVHhVR``TZZ\NbXPjfVfVZZdHXXR\TdB\RZ\VVP\\TP\X\PNPTXFZ\N`H\``ZRRTVZ\LdNPfLNTVVR\`J\PPT^TR\T`LbTb\\TP^VZRVL`VNVVVXZ^RZhZZ\`ZRXbRXLVNX^d\^X`hRdPRhRP^JRhH`bNV\^Z\RPZXXXVJd\VNXXNZ`TX`^dFTRJfZTfLNXbZjN^ZTVZdNZhbRPRJ^RTHXLPD`P\PXNXN\LRbh:JXZTjXTlz`fTfX``TfXXV\`ZjF\TTZ\^LXTf\fPVTRV^RV\PVXLP`\V^bXT\L`nRHVNPZXLRdTZXHVVVXHP^XJZ^RR`XXZ\\Z`XR`PXDbb^f`@`bZ^V\ZZLfVXXT^fbNZ^>`^VVTL`JjP`VXRZ@\^\`^^RPVTTTRZL^P\F^TXZXV\LTPTVd\\RVXZNdVhTVRXRZ^\P^NZZNTR\VRTZL^fh\T^ZRXhPDbRXVZXXTXZVbPTZPR^PL\^XXZ\TLTTVZX\L\Rd^bVVJbZ^R^\`ZZNXP\ZV^fZRL`ZTX\\X\fVV^fRVPRN\^Xd`PZVZZNPXXZP`H\VXZPR^F VZ   H h R f b V R P \ X b ^ T ^ T ` FJXdPPP PTb \JTPZRV N T^LP\HNVH^VLPPdXLZRRVZVXVZ\bJ`VXT\TZbVRR\ JhBNZ`@TTbJ\TPZZVXZ^\`R J` VXbV ` L X D Z b P F N T ^ J T T R ` T TXN ^XVX T`^JNd R XPf^RN\XF\RVZHZNDLRVRXZLbTPXLN^ZbNVVRP\PVXdJNN\L\TX^`RV`Z`PZ>XXV`VZfX^LZTTN\TZ\T^P\N\X\TXbPVbX\\\XXHdFRPTXXDR^JXPRZDRVL^V`P`^`RZNZVVV\XRfXZNPN\VT\hJN\JdR\jdXf\JF`b^ZRLZPVZXFfpPjV`N\P`^P`d`XXbNPfT\`ZN\VNVXXZPZ\P^ZXVTFXPbTVV`Th`L\ZXHZRV`VPLRRVNf`ZVhXX^ZXV^VZ^^b\Ph^d\PXVVJRTb\V\ZX^dXRbbVTTXXTNPb<NZRPXJZ\^NPN\l\dThZX\`NXRXbP`HPPf`TTXVLVLX\RhXdR^NXJ^R\\^hR^J\bV`J\VRXXVP\^XVVZXXfb``d\XZ\Z\XX`Nb^TTLV\bT\ZVX\X\XXXVPZNNL^PRZVT^ZRHVJPT^\HVZVDNT^@FdZJPN\TXX^^fTJXPbPVTVZL`XVZPPPRZ^T^N^XTR\\RZdX^RRb\PVVVXX\ZR^ZVVT`HJ\X@VTZZHfTRJRTXJbRF^NNRXTN`XTPh\TVVNPZTTfT^LRVZLVJXPZTFJV`HZ\RJVNTJ^NV\TXPV\ZjPL\P^ZNDdVLLXTX`R\ZRXVXTT\`V\T\XPVPTbVXT`PFZ\\^^P\RVVVXhVT\XTVPZRVZZbLNT^TXNR\ZX\`\ZRdXRNTRVZPLRT\TNPXZXTP`XhRLHV^R LPR bZ  P P ` T 6 f V V P N b B V V \bN  LJV`R\ZR^P^ jZXZTXRdZTRRVRLZTRXbVT:NXbNZXVJJXXVNTTP LLD^@dZ `JXbNTJHbRZ`LB>ZRPVVZT^FJ \ N P V T X R ^ ^ ^ \ \ R \ \ \ Z J P VN N ^ dhLXJ Zl VP PZR`N^R\^T\N^PXX\TJLVTRTd\VPPNZRLR>^V^VVbLTVXbX^ZZZ`X\b^LD`V\LbdVXZ\Z\lXV\HlTHdZJ\P`HXL^T^PXZPPbTXhXVL^XXRd\\TJT`VZ\X>RTRLPVRZJZNHN\XNLZTVZ\Nd^ZV`X`TVR\Z^NV^ZXXT\FV^P^XLNHZTb\FXPLTZ\RFH\ZR`V^VJXRTX\LRF^RPT`TVR\LXTN^PVLRHdV^^^TTVH`XVXTJXHVHXbNXVTN`NZ\DbZH\HNZ`PVdPRbJPdZ`PTZd\RN^\TRRLLVbNJRZRNRTljZVB^bNbTPbZNVPTXXNVZRPRXTfX`\bRVRTRJZ`RLV^PZVXZ^LbXJXPTXFJ^ZVX\VZR^RLXT\^b\LT\L\TXF`^lXlJffhZRblZXTB^LfRV^XVRX`\FXLZRP`\nNh^`N\XLhZTV^T^fNbJbX`L`TXZNRXXZVXRHRhRdZNJb:^N@Bd\R\TRZh\DZbXVPVbRVN<`PRPV\ZPBZXTJNLXXJLXX`^TLXJL\XVVPVNJJRL\ZfZV\V\N\XPZNVbZLPP\bH^Jf\JVZZVP\T^PZ`NDj^\VHbV\hNLfVV\NTLZ^LT>T\^bV\PXdZN\H`XV^XRPPR\ZfTPbdNFf\L^T^\^L``JTV^VdBXJLVZV^ZZZTPZdP`RR\VV\HNTV`Z\JT^^fZPbPHRTRLRJZXZTPXT VJZbb V X T R ` R d R ` L T V T P V V T Z J T > N dT ^ N XTb^ J b^Th\HRVVP`VVVRV`P`X\HZXNXV^Z^NXLTPTJDZXdJRXXNTPZVVVdVRLF\LP\X`PNXZTHbVTXRD\ RR RZ\^FNV\ XN \ V V X f H D J XT b P ^ ^ D R F L N B d X V  H ` R D R XXT ^R LH ` NTFP\^d^JDLN^Z\RLZRZR`LNdN\`RfHRN\BHX^Z\\\ZHHVZRHVV^VXPNZN\TTJ\Z\fXR^RLPFTPJTXJP`T\RTXL:dXXRfPX0`RdZ^ZLV@`ZXRj`XVZNhThVRXL\VZPR^PXV\\\^TZdVVZRX\PN@VNP`NPZPbZHXXBJZVFLZPX^XPTP\NVJTbVJhXdRLR`PTNV`XL\RXRX^TRbRdZ`RX`bTPXbN`^\bPNZZ^VLZPV`V^\h^^TJ^P`\RJRZ\ZLXbVZZbZNb`L\R\X\R\NZbRjP^`^TXf^^X\Td^:fL^lXXfRXZbjPPb^dJP\X\JVTTRZT\VR^bT`TRdR\`TXXLRTRTZZTXTPVN^TRPVhXNN`V\\T`XJVFZXXPRXPZPdR^VXVRVdFNdLPLN\PbRbfb^VX`ZZVX\R\^lJ^V^P`XZZbRVVVfPV^^XPPZJTVfVLlT^`RTTVhTT^^dZLTjVZVZXjRR\T`NT^V\PTbZFX\ZZTXJJZDJRPZRZP\JLRZT\T\^RZdJF^VNb^ZZ`H^TNTNH\XfPhX\RZXV\VTNXDVZdd\R^VX^R^RVVJV\VDXTZTZVRhTT`bdPZLZfNR^\PPVNXXBb^RHXF^HRTZPZTLZ\XZX``NZff^XZ\ZTVVX`RNNX`VRJH^D^XPRPLV`RVT`fPR^V`NLlTTNNZZVZXNZ`Zb`R8^\H^NT^VDRbJZ`^XPRb V`T L@bJJ \ H Z V V L T f Z V \ ^ T Z T H f V T P \ N X \ X R RBX ^ ^dZ HZRVZ^ZVdfHVdNLVf\^NNXbX\XDZVJT`DPPV``P\LXbPVXfZT8RVR^\bL\dbV\XFVNXN\XZXT\ZJdRT H T Z R b  F \ \ f H ^ V ^ X ^ P Z T T \ R J X TPR \ ^ R J T Z ^ P VRT\J XZTZHRTPR\XRXPRJfR\TFXbPhTVbR^RZbPdPbXNRP`PLX^R^VVN^fV`fPVJXRP^NPVNZVTTLRT\Z\`PZRb^R`XbRNdRVHNNRRF`H^`ZVRJBT^dX`R`ZZL\XTNNPTTNPZF^NZT`VhRV\Xb^P\XNX^XXN\LPdHVRP`^TZ^fXV^TNVJRdT\Z\\Z`PT\`8VRBJ\P`VZhTXRXdbP^XPPXRVVRV\\HdFbNZV\RXPbH\RZ\FdbZZTZZNf^XbV\Xh`^dXlPdZTXTrXRb`dJ\TbZZ^Hf`XX`T^^dfZd\VRVXXTj`X^\`^hPbVZRR^LbN`Ld^^ZPNV\TdXbJZNRVVPVTNV\fZN`TT^XZRVVPZPN\`VNXhF\FbF^NP\^RR\bTfX\rXRXfb^fTf`XZPlNhbh`^dRZN^^X^\VZdXJV^T^f^`JT@XX^ZZHdd\fJThXVPbZXRPTdRZ^XVJPfVb`dZPVVLbTZTV^^RLPVR`TPdjRfR^d\^^VVVXl`\^V\^TLZNHVPT^RX\PZJH^PZHfLVZVjNV`ZZFZTT\PfNXZfXNXNZRVR`TV`NXTTTZZXZXXT\XT^H\ZVRR`ZZ`BVRRXXNTVNTV\RJLTTN^TTdTVbX`T\^Z\NXVPLd\T`LZNJTb^hVRRDTVJPdZ^\\FVTJ`HHXVPbZX\TRRV\^^RTdPfPX\Zb J` ^ TZ  b 6 Z^P  \ ` ^ X Z H X b ^ L R Z P V P X V R P R TR ` V \dXRT ^ ZZLZdXfPTHRTLJXbZXVNFXX>XXP\^Bb0Z^NT`TLJNJR^VBXTdVJNXRZbXbXfNXRZbPPddZL LBLV VHPR DP Z` Z V Z P T j N T b J L J N ` L \ H P H ^ L \ \ \ d \R J V ` Ld T\ ^>\6X\ \H\TNVV\`P^VPRXb\T^JhPZ`T`^PPZX`NfbTXTZZ^RX`TRZXRVNZdThP\VdT^``VTVdXZX\FD\VRfR\JNNHhVb^NfVRL^LJH`NdH\Tj\TZPXdX`RXL\^HJH`TPXnTfJ^ZZNXXT`VdTXLXdd\TbP\T\T\XXRT^\X\PZ^Zd\\JfPVNXJfF\\XT\PdRNjJT\TXXbN\RL^NZ\`\V`XXNZJHN`JNXTPF\J`V`\TTZTHZXD^ZXVRXN\RPP`LNT^V\Z^^FhLXTP^`PPV`VRZTPX\\ZV`H`RXH\`XZj\LV\^\\V\DlXjP\ZNfP^RJX^JX\FTXTfVTTZJZ\VfDTNXNhPZbb`Z^\`P^NVXVXd<\R\HNNZTP@XRT^JndVjbP`P`dfTjb`XJ^VpRBdXJNR`V`L^dVZ\VNDb^PLTbbTR^DbRPnV\ZTf\TPTRVTNZTR@N`^Td^@VnJ\ZFNR^FRRZVZXbPVN^PN\\\ZTlldTFVP^TXT^VFV\RZDV^NThT\NPXRRRVPVjFN\ZLX^ZZRJD^`PVR`RX^TPTFXLTNZZVPVF^Z`T`TP`\TZV`NT`\TZFVVXVPTfTXVTRfZV`^`V^j`Hf^LV`T``\ZVZP\@VPXRbNpNZ\d@`X^X`TTVf\^VTX^XfHV`ZN^FT`N\\PTVPVXZRVL`ZVTPdRPXTTPTR\Z TZ T @ X T P `N V ^ d ` Z \ V ^ N N R R < V T B X V^ V \ XXVdRP\XP`@\NRXXPbNHVDHDFVPT`FFN^XZRVHTX^JbPZB\\LdVRVbTPT^FT\RRRDBHbRXRRXTL^NLJNVb `fH^PNh`dL ZJ  T ^ R P XX N N d l T D \  Z R N Z l P Z V T ^ J L Hbf ZJZLHNRJ RbPZTBLTDXdXXX@\VRTVT`^^TZJRPDH`FPLXPdXZTd`TNJhLHVT^XVVXTdfT^`\\dRXDhRFRRdPRRZ^Ph^R^\\RXN\TRNXTFP\LV`JLVZLXZZ\X`VXRPdJ`VT^DZRZdNVPRVLT^PRNbV\HP\T^L\RbPZXdXVLhXNZ`RPXRNbTPVX`XZXVZRVRTV`\dRTXVPPTZP\XXJbPbN^LVhbRNNfLBTbdXZVXZbdPRZNbRL\XPLXN\fR\NNTNH\T^NZPXXT`hXTVTdVR`TNXZ`^\\bZR`PVf^\LTXPf^NZLV`R``ZZTRRXl`hRXNZhT\NbJXRb^@dTRZTJ^dLVVFZZ\\HPXNXNP\NTTTHNVdbjR^VdjZnVDTRXTZX\VhX\ff^FZhb`N^JZP\TZPRTXZTP@Lb\V`^\PHRb^NZT``TZbLjbdZZTZX^D\X\^T^XLfXVdDZVTVNZXXZX^XVdZPTbdR^`Zd\PdbP\LZ\XNbXJVVNZFZR^\T\^LJPdP`J\PVBTfXTNLV^ZXTZLN\\^RPZX\ZZXPXX^TXPZLLbRTZVFPTR`NR`JXbN\P`fX\\HP\FPXRP\XdN\XXjxbVPNfP^T`\b`TJZZdZ`LP^PPX\PHVN\ZhZTJTdRXRXVFRXRTdZLnPXb`H\PXV:R^XbNVddX4\^\JPRPPhRR`V VPR fV \ T h R F Ld  h ` T V \ N T b T ZZ X R V V Z  ` XP R XTZXdT`R`TTVLH^d\TZXVRLbVPPTbRT\TPXPXZNPRPJZbNPXPZJNXNPFTbb\bT\T^TNXJZTXTDbTVNLTV^TTLPd\\\^T^ ^b ` ``\V L FT b ` T \ d N V R X N X b ^ ^ Z P h j P ` D XNXb \Xf T ThTh XLZX`R\Rb\PH\P\^Z`R^VPLJdTT^dZTZNbNfR\N`HZPTfRZ\P^VT\RPLF`H`XXdh`RVVZRXJ`RTVTPNR@X^RPLX\`TdbLFTPRVPRVZNL^\RLPDXX^TZRXLZXPbV`D`^\HVN`ZL\R^NPXVZV`Z^NZLLVdRT\J`TdXBR^ddX^HLTR^\XZRXbVRV\dTLRT\V\VPZPX\fPZ`PVTR\VXXRVXbJXVDRVXVRZb^R`VVRZZT\BLLFXbPVTHVNJ`F^ZT\^^b`^`VHNP`N`VT\Z\LdJ`^T@TVXPZXR\d`Tb\VTVXVdLZ`^XNZ^RTXZ^ZXZRVf\bPZ\XFbXdLdH\RfXTVffdZZFZdTPVX^NJdb\XXFNV\Tlj\b^j^Zb\L\XhbXZ\\HLjTPdTZ\``\JXP\XXZVhL`R\^bTZNfRRJ\XVb\RJXNhR\TVH`VVDRPZNZPRNT\^VD\dZ<fPbPVbRVbTDRRTXH\LdXXR\\FZXLRRTDVXbHL`JNbPn\JNR^HR`J`R`^NJZVVP`FP\@ZLTXTR^X\Hd@hVTTJbPRJdP^`LXVTXTR^PTVXNVXXHbHHhNJhXLNPL`HZTVXLVVT`PNXRLTPZ TVFHXRNZTZJJPPN^VZFfTVPLDLJZXRPJXNJTJVTVdPJNPTTBVVZ X V N d ^ Z X X L T R ^ J N P R T j  F  V ` H `\LPJNLbT\PbPVLTZV^b^PVVVPVHX^bb^RVVDZ^JPZHLFX`NRRJJTXXPPXPXNJZJXBZVNFPLZJPNJbN\JXV\F\\PXJ^TF^V\NX XT\bJVZPJJNd TRFTFJB` P F D V \ V F \ R T V J N < X T P J J ` X L T\ V`XZR T B LPLR\ZLBJHPZPRTZRHXNRRL^XPFNLX^ZPR@\PT\ZZLZPPXZ`NhRTfTZPTLZPVVRLhRVPVJX\TVTVf`PV\VhRZFH^jZX`TJB\NXXTT^NfL^RLd`NPVNV^P\XZZHZRVNRP^`bZxXXb\`ZV^PR`X`TPV\`DbVZfXPPVbPV`V@b\NVV\RdHR\X^bV\LPZXJ^<L^PTZRThHlTRRNNPdRZ6VRLbVP^^bFbf`XXXP^TPJZZHZ`dLZf^`XTXP^dLbJ\J^L\Z`\TT^>LHXR`\L\R\TD\ZXVXFT`bNdV`^f^`TZPZTV^R\DRTVVTLVNXTPTfbhZZHJTb^V\RX\LTZPZXZJNR\^L\^NPTPPPJRR^LRVlFZTZLfVN^\NRRXdHXXJ\HN8XVZBVRhV^l\VPfTfX`TVT\\\V^ZTd^fVV`P\XfZ^L`XTP^VPVN`ZB\bVZbRRV\^ZbJ`\`ThLLZXXNDLPVfVPRLH^ZVZZHLbRbTLPTZTVTV^`XXfTBlRJHbVTfX^RDT\VVLXXVTD`@`ZRV\VT^TXVV`TZT^TXNPR^hNZJ\P\TZd^TfZZX^FXfVV`TXL``ZXDZ\TVZ^Z`PZdbPdVTZTFDX`PVbJVXNVVVJb\ZNZZRfNX\XRPdhRZ^XVTV`\V`\`TRZ\bZ`^\Vj\VRVL`T\L^`^d\`HPV^BXT\ZV>^VTZ^TBRLXXZ\^V` RbJ NJ T P X P X b R J Z Z V R V R ^ P R T T ` bVR P` T X V\ VPdRdVNFZRNT^R^TV`X\VZTbX`P^R\ZRVV`V^Z\ZX^ZVJ\bX`VPRbRTRjVJ`LTN<^\\Z\P2`RHZVZZVVXPJ^NZZZRLP`LbX^^\^TJNDT\  JLJZ RL P T Z T X N X b X R X b P P R ` d N b H Z R X V Z P NTL R^N Z L b d XJT R\VXP`RN``V\RXTZHVN\H`RZPbVVXLXVZXP\bRXZ^HZHRX`bZZ\PLLR@XRPTPTXXVXRZTVRB\TVZTLVVLRX\bVbVXVfXZVZRNdZRf\`\LXTVbXZR`PVHVTfNFFVXDP\VdVLVNXjNNTTJ`NV`\RXT^ZZV^NVVXRPXJPT\XXNHdV\\N\^PT\JR\VZb`PTZ^ZP\XZNZJdVXdbV`XH`\HPdFXXZTT`XNNX`X`Z^`TNhXB`NVRZV^^VXdJ\bPVTb^ZXbPHfR^j^Z^Z\\\TjZT\^hbZX\ZThVTXXV^ZbbbbRLRVpPZbT\`T\T\XVd`bVhFRNZXJ\FTPZ^XXTVbJl\V^bTZPJ`lP\VVLTPT`PJTV^R^FZRXJbfJdZPbdnXdjbdXRT\\bXT^NZV^\RRJdTXTdRRXRNV^^VZbPTZ`\TN\ZVXRNdPN^Z<^d^XZRRbRdZZdXNL`TTZ^XX\^ZF\PRd`R\ZR<\b`^JVZ\^VF^\^HRRZBNhVT\XV`hN`R\Z\HD^TRdDNHHV`XTDRTbP^V^JNXRPXLTZ^RXLZRT^ZRTTPRV`^VTX\NPLZ\^R\LXfVVDdXVTZPVRX^FddR`T\XNV\VPN^fTTTTVVXRNZZ`LPRTf`VZ\TVZZNRLXJ^dHNTR`N\ZZNPZXdBRL`XZNL\N\>HXLVZNZXRZZZVZVV\fZfH`bVRXXTTRFT>bT Pb\d Rf P V R X X T R R P Z P J X T V \ P Z X X V T V T P \ Z N Z TZZ dN XDLZ \P `VRPL^NV\H`LTHVFJXXb`Z\H\T\XL\^JVJL\TVVZN`FLXTT\N^Ll`X\VN^PHXTZXHTTZVZJRLTVRVTJbXHTVLTTTXdTJZNRZJhVdJX:PL\R\f\BTR T  V^ R h R D l j V P R X Z X P n T Z Z R ` L X L ^ ^ XN  R Z H hNDTPZR^JH@ZP^V^JVZRL`P`ZdJZTNRTLVNTPXRZRX^\TN^LHPZT^`LRdPB^TRLR`dNXTVNZZHb``RLZPTVVTV\XZPPVVfPX^X\ZVNPNJT\\h^JL`TTLR\NZ\R`Zh\VZ`fBT\XXXbJ`^V\NZZb^TLZ^VTZ\XZ`>^^XZ\^PTNLh``LhZZZT^P^^VdTHZZDZRVDLhZVTZbTZ\^ZPJ^^VXT^XbRN`R\VHXRbJNT\dHT\dNPbTT\RNbRP\``dZLR^LR^JbfP\TVXfRVVR\XVVb`JBR\RRL`NXLNRTZT\VTX^\N\RbPRZR`LP`N\LXZ^HZhZNLPX`RZDF@ZVPPF^XLRXLV^b\^ZPfjRX`PTXZb^`^V^`^:ZThVVd^Z\PZfXXLPZ^ZPRXTbX`ddVH`VffTZ\j\XX^R\6Xf^`PN\X^JTZfVR`Z^VfVXTLP\NTVLXRL`b^VVTVRXf@Rb^RV\RNXPZV\T^PRPd^^f\VbbFb\^LTLb`RZVBbZ^PR\\\`VdV\PTXVRN^XhX\V\nXnFpPZ`bRTX\P\b`TLTN^PNNX`JZL^\TXRRTLRF^bVRZZF\`f``PXV^`ZZVXNPLRLTf^ZVJRTnP\j\PPfVVZZTdR\\P\T^RdRVbZRZZ\T`^P`bNP`Xf\h^LZ^LV\bhVTZ RVHX Lb`XX `  \ Z T T V F ^ X P T ^ X P V ^  T R T Z VN T RJ ` d\fTT`XTR\bJR\PJZT``ZJLTXRJTfFdPRLHVP\VNFJ`TNVRTX`\ZRd`XZNXRbTRRZ\P`PjJPXP`RVRfVfTRPVZVPND`JTNPP\XZ\^Vb X ` ^ \ X R X T T \ X R X D ` L P ` J N \ P Z J V ` N \ T  ` < d PR TdJNZXLJZZVRRNbbLRZNZT^ZjhVZdL^dbXbX^NPFbLB\fNXX^^R^TTR^dDJBFRZXRXRTXL\^Z\RXRjN^P\FhNZ^^fZbdXVbfRZVPZZTbTTRZlRZ\Hb^XT\T`T^nXdVJ\LhbLfXTPV`H\d`\H`NZ``VVRXTPPZdV\XlXTNVR`R`dTV\bP\N`TXP`TRdJVX\XXNXV^PXNPTNTNhLXXd^V\fJXVbZNRdT\R`fT@N\XldXdhPVNXd`R`bV`Z`^\`JVT\ZPVX\TL`bNTP\bT`V`Z^ZVZ\T\dTTN\RdZ^PX^^Nr`^^RZLHNJbP\PZP\\ZXZRTXl^PTVb^dJV\VPTPPV\bRZZjdLHNZ\bRLT\D\^bNbRf\\HhZhRXRZZXX\\l^TZ`T`P\TVRZ^^LdV\XNVTX\RTP\JRZ`TZVNVR\`ZbTPVdTXT\XPNJfZdfPNPXXPXPVTZZZ^^Z^PNJVV\P\PbHVXbf\FRRXVfVFZ\L`TVZJZH^h<TThTbVhLPZ^XXPLRZVVZ\LTFbFXZbNZLPVbJFZRJXN\\TV\XdRV@^2`X`BRRVF\V\XLTdVXZR\RHRbV^ZXLJ\TJT\`XB^dNXVXH@DVLXL\f`XjLXHBT^H^NX\^ZbPTRZN\V`VjZL@XJR\VVX`T\RfHRb\T^VRN\ X \ZdVfV P V V Z T b X X Z X P R ` J H V d Z ^ P NL R \JR N V X bZ\X \NL`RRL\LXRZF`PJ\NXZNP\VR^XTPTXXX\NDdVPR\FZfLdXZPbXZZXH^`TVVVVTXV^f`HNPF\NXN\XPb`LHTdTTXTX\JZ^Z^LdFZZVXXdlP^ \ ` X N Z N T P V \ T L R H X Z L Z R \ J Z ` Z N f \ Z Z P V ` L J \ TPbJZPXRR^RR^^XF\`RR ^\`\ ^ jPXXLXTRJ\`JPXVTVd^R`F^RLN`ZRb\`HT^XHbRLHTB^RP^RTPD^PTRXPRhNLZPVTNV`X\NLBXXL\T^HLXTT`ZTRNTdJXJH`ZTfTVZVRXHBPb^TVRRVRZbTNRbTTZVNVXTJVTL@Z`VTP\`^NVZL^RTVfZXPHR^^VPfTLNFPXTZPdP^ZRVZV`LTZPZTTPZR`JPZLZ\JTT`VRRRLdTjTL`PlVNV`RbP^XDP`^TdNZ\PZJXb^hbXRXT^ZT\XJZZdPJfN\NR\^^TbFbBVFXlPTVNdLh\JVZbV`NPN\XVXf`\`T\JTTXH\\\T\ZLhJPZPP`TRXV^XbbXdVVbTZZf`X``bbZJNZ`ZTZ^PZR\dXX^^PVZfjL`\`XRdfLTLTT`V\XZX\\bLVZ`P`ZZ^VTTLTVbXfZXX\^hJbRV`RR`RZFRhVXRP^N\^HdRXPVJ\nBPLRTTXTPTbVVRd^ZVVRVVd^^\RPHZPdJZRbNPPZPXXNVbTZL^PNZ^VXJ\L`RVXT^FZ\LFR`V^^V`PdRTNRZZRZL`PZPRZ\J\ZZPhPVPZVTPJTZZXNJLR^^VPL\V^FLPVNDj\\TR`FRLdTPXTXTT\@ZV`ZJT^L\Pb\NT\RX^TLbV bJ ^\ J NX \ f d ^ N d \ H ^ \ R f ^ ^ R R Z VFV ^PZ L XX X^RZVVPdVZ^RZ^ZbXVHXbP\XN\LPZT\HTVX\N^\^NPP\@X\ZNTXTNLR@ZVTTRVdZ^\\XLXJbVP`RZTPLVnDXXXXdfX\h^\Z\^HXXJ\XTNXT\R V ^ Z V P V V bJ T V ^ R V T T J V B L T R N \ T b P \ N X \ Z \ V\ZfR V T dNZ\ HVZ^PbVZN`X `VX``\PLNB\XVP\LRVZRP`ZRX^^T^V`fbZ\`PfPT^PdFbN`^^XPZVJRJPZVRTTNbDTN^LRR\X^X`XRFT\XdRV^^LXZZZ`PNP`H^LZ^d\TP^`L`dZV\`JPX`X``Z\P^d^RHFVZLV\ZXRPR\VFNRHZbV`b\PXXXL^NR\`dPZH^VFbVdT``TTfTNZVJ`Xb\XV`XT^Fh`ZNdVbZPTdX\TRfT^P`ZNZlV\Pfnfb\X^Tb^`TZZVR^N^`LX\V`Xbb^ZTVTV\^TZZX^VXb\P`^RT\ZXVVhXLVVZ`nZTfTPdH`TPRFNN`LVLbJPDPLRLNNNTN\HZh\JVhTXTN\XXT\R^ZRP`ZZ\TTjTb^TDd\V^PRX\\J^XJVbZjVRXRVZfTRDLXJ^^ZTfHRTRhfDJZPRZRLPVP\VNXPRNHRVPLNJVVDZTXH^XVRVPZHVFVVT^XVZTF^fZVh\X`DN^TbTPL`PdRdVTRRVXTNdTZJ\TNVRVPbDbZRP\XNhFD\PLdRZbN^LX\HfVV\X`TPZ``VPT^\R\NdPVZ^PTH`bVXZXJZ^ZTDVVVV`VLZXRTXZN`\HLV\VXPV^XB^PRRPJJfHZNTVXdLZ^R\V^TTLVbPHPRXdLdR\XX H V~ d h J H \TV Z V T \ R H ^ \ ^ X Z ` P \ \ Z X X V  T^X dPRXXXV HPVXXDbZXVXLZ@XXTfVVHPRRZ\R\ZJ^ZPZR`HLPNX>ZV^XbDRLJ^V^^Vf\NPPVFVJZP^^TRZNJ`\ZRRFLXN`d<RbNP`RHPNPZFXXTPJ^VTP\ZDNZ` V H P  RV D ` T Z H Z L X J Z d T Z N R V X L X D N T H  P TNX \ ` b V FNZhN@NVJBL^\\VVZ^RVLZ\^PLRT\LRZdF^XV``P^^XNVXJHBZbPZ\\NR^XJVNZb`ZZ\XL\PRTXVZNXRHTL`TP`JR`XNHNRNVXXZbP\TbPbNb\NPTRPVT\ZX\PVTRTZDHPZJ^ZXXPRJVXZ^RdRZNRXlV`^RXTVRZJdNVPFTP`^^XZZXLVRX`ZbVZZP^^^LVXbB\NXbdZhP\VFXXXRHLVDZRNZPbNLXXZLT^TZB\PZTV`\H``XbTd\`LbbV\`PPX\\T`V\ZP`Pf`Pb`RbRbRX^ZPZXZV`Z\^ZX^bTT\Jb\XHZ`TZNLV\\V^ZPP`R\NNV`VZXXX\T``jXHZjVH`\P^@T`L`Pld`X\`ZTZ`T^P`hb`VdbZZVVdLL`^p^dZRbjTVV^RTLN``J^\VTLRPP^TXVPT^^TXTLZT^dDZdLPVFXZV^ZVRRRX`j\LXJ^P`dZZnXBp`bR`HVZNd\XJHR`jZTZPNfTRVL^VJXLXN>RVRJPRJT`bJN^ZRVRJhJVRDZR\XPdRRb`JNZ\XN`fT\P\D\R\LZFZXPNXT^\Z^fXL\jNZRVXf^\D\RTX`RT>VXRT\P\\jXFNLXfVLL\XXDXVNXH<bfVJPXJRPNJTT\`^TXTZbR N\V\P` f V L ^ Z ^ N Z P X H R Z \ ^ ` \\ X PL\TNXTVTPVZVbXbR\LVJPdT\FdFVB\XdVZZZZZT>^VbNZXXV\FXXFT\XZXfRR\b`b>Z`XPRZR^@^\\X`JTdhRZXJN\PXXbRXPZLVP`V^ZD^TPV^8NXLdT P b ` L `X  N T R \ Z X R R ` H T \ Z N ` X T Z V Z ^ \ H R T \ LX\TT f dTTXZP^X \ X VZ^bhXJRT^NR^PPXZR\VXX^LRXP`Vb\`RXVBP\TNd@ZTNXZRZ\HDPZZN`VZVLXPV\XPRXD\XbXNTNRTTV`J^d\ZbTdVJ^PV^NXLZXZ`XRP^PV\X`ZV\VXHVXFZLZLR^R^`RPRVRNTVZH^J\TTXV^bTbVX\hPTR\XXXLbNF`\V\f^PPfHZXH`TZRPbNPV^FRZL`ZT\VZZRPVXJPXVTPNXTTV^\ZJdRVPZ`dPXNb\VP^^VdBfB`^\FTXd\XPTR^FJV^\dXX\`\XXXbddVh\\R^pdHX\R`\RP\fTVPZZXdXHZPX\ZZ\PXLTTVPNVXP^RVLXZN`J^LfbNdjlX\VV^\Rb^Zbbd^\jjXRNR^TZZ\T`RbVHXVRRfX`TTTRZHR\\`LRfZTd\ZT^``XV^RZT>VPTTbTNj`PPVXF\^\\FhZZ\VTbLJT^TZZVRX\VDXX`\^\TPV\TRRLRZXT^R^N\XfRHh.TT^X\JXHTbNVTLTLN\j^TZR\ZLb\BJ^XfPPXT^R`XdXBNVZRT^PLX^PF\T^ZVRTJZ^TVXLTbZPHNXRTLlRTXN\PXL^RF`FPVNdLdNPPTXHN\FLZFZPFTPHLPZ\TR`ZV`TPJfXXXZ`LTP\\NLb`VPLTRN^RFXRLV^b Vb R T P V R P ` V \ ` X \ f X Z X V XZVTXRRLR\NdRNNXPXP@XPVbT\XPjPfR^ZPNPFVXNNZHLbFFJ\PZLZFfZJN\H\RXZHN^@HHZV\R>b\PRRPXRRdZRTVVHVVXdZZL`ZDTPXNZL^^VRN^L@VZ\V^fZRPZJ\VZXTZRXRJ^XPNLLR\ X ` V ^ H J T LD R T R Z H V X h L ` \ N \ @ V X D P   ZP V R VFR XVP ^ \f F Z \ R X ^^bNT\jXRXL\VRZTHXbPlNTZHhdPNF^\XXXX^RVFjRPT\LX\RR^JPZXFVFZV\ZHVXZ^ZR\R^``ZXNV\Z`HRZRfN`RL\PXLLbZ\LdLTZLRFfP^ZZPRXPfbVLJJ^HP^F^bPTVT`>j^PLTXXXJVTNR\NLJ\bfLRNjTXPPXRZ^RVHVTZLTRN\PhdP^VbPP\bL^\VVnh\V^PXFVV^TT^^THZdLPRRXZPVL^JRVZVJd\XVhR^Pf^ZX`^HPf\FbZRXdR\TbPBV\\XTXZXH\VbRT\fbHfXPRNZRT\^T^\TnR^RJfFHbPHbVTdXd^`d^Tdd^^hd^^rj\fTTf\Vd\Zbd\\XbTL^LdZTd`XRVJj\Zd^V\LPVT\^dhd^bh^\ZTX^JX`bRbZ^RR^TZ\Xl`XVZZTZhVZVZTjhRNRTXN\.^V`R\`LX\PbPV`ZN\\PdT^fPXRR^V`\VVJZ^\^P\XX\RRXZPN`PRh\TVV`JJThHbRNTNVVPPFX^^THPXVTPbX^\RVXZ^NXZfV^^^ZJV\T^LZ^RPdLF`HNXNPVT^THRXXL`jVRThDVF\\XDdZHTZfJZPR^\TPbTNJ N ^ P \ Z H ` V X f X V  P Z P Z \ T \ Z ` LLFbVTRJbJZP\\`P`\ZVbVFR^T\ZPX`Z^RTR^PTRNN\ZVXXVTTV`JZR^H`ZJVXVVTZX^V\PX^T\TPZXXXVPHX^V^R^HhVR\T^\F^TXPRRN\TVT@\J`VN\JZPZX\XZPVZHXZ J f T R R N T Z V X J X b R ^ R T V F Z f H V T R ^ bV ` Vd d P L V N Z  N X Z  T N ^hPZdLPfP`RbRVJZZZ^PVHXR\VNVNVVbRRT`F\TRVTT`P\XFJP^ZNLRVbV```Z^LTRLbJXZZZV\NVN^HX4LfRTRf^^bLD\fVRZL^LnPPPVR`LXR\XTTVbNjbXVPN`J`bbRRTZ^bJXdPRPbPbPbTLTHVNN\VTV`V\XJdRZZ\\^fRTVZX^\XZ\PnJRTRVV^\L^\VH^R\PJTXjVPTZ`F\ZlX\Vd`ZZZZfJTVb^`ffRT^R`bV^Z^N`RfNRXPTZZTZZfTP\^ZXVZXXXT^V`T`RP^ZhR\X\VVR`P\d^ZbZXXXTfVV^PP`d\PPZHNRN^@\V`NVPBPNPhh^\N\\TVb`ldXZ``ZlhXHZjZBX\bZ\XNbDZZZT`ZdVL\djTNP^T\TT`JZ`NfVX\XZXNVX`PVP\PVZL`RVDXZPXJHPBNF\JZNZX^JTL^T`NVRVZdTTJjTLZTD`ZZZNLRHJRZL\TR`bLX^FJD^XRZLXXTRdT\ZHXbLXNHZTXRXbJPTFbV@\N\RV`NPVXTX\PV\^PRRJXVNZRfZHV^`XXNbfXZRBVDVTX\^VVRHVPBTPXXXX`RlXVVhXHbRRNTNTL`RTVHZNZ^XXHV`NR`D\NXRVbVPRRTVV`TVVVV`bD  R T L T R R N P V V X V X X X R V \ P R T ZTRXX^d<^TFZVfZXRJXHT@X\ZPVTPZdRZD\@RPX\\F\`NRF`PPJRZJVVRL`TPJZVXNJVbHTTX\XLPFLdZVXVbZ`PRZXZVT\PhL\PbTHhdHN\PRP@\\JBZZJX\`XPTN\HFXVRH V X Z h ^ R T H X V Z X J d T R J b R Z b j d \ b ^ R R N l T \b R T  ^Z H  f ^ R \F VNPZ\RXZXZ dV^fLb^RZN^JbPb\^Z^XVDbRPTL`N^ZF^^`VXZJZVPHVPXNVXX`NZdTRZRVTRJZFbVNVVbXJ\PhdVBVf^^`XDLVXNDXHXV^VNVTZT\Z^RVZRRBb\ddjV\`TZ`\DZLZZ\bHRTZ`Zb\VTbVbXTL\PXlZVBRbZ`@bTPbfVZNfPbRT^^X`XfLjPVRPVZ`^LbZdP\XVdhfTRPXVJj\^LZ`JTNXRd\\^\Z^VR`ZZDNZPR^XT^Z\VRPRVNVdL^\V\TRVPP^X\dZbX^T``ZRTLdXlZ<XPVlRR^XXLRZ\bZXTPPVZDLP\LLXVVRNDLZXl`ZbhXXZPZ`XdZXZddT^^TRZPd\\nThbLjR\^XZR\^ZFfPP^^VRZ\ZZX`d^XN^\ZP\fL`^^VTdLH\bbVjH^^FT\L^VTPPD`JVZRPXhTJTVTTbTXZRZ`HVPLFR>HVV^JNh^Xb\\dFZVXb\LbfRVVLRLRTXTd\PTL\LNTRNVLZTZfZbPTXD^fPZPfZXV\Zf`^bXb`^RV\bLdXbXJVTTX`\J\T`XVRb^R^T\ZdTJZ`ZJZXVX^HR``JXJHVbh^NLRh`R^bbJTTZTRbZPZZ\hZJZV`dDXTX\^R@^X RX Z H Z V T R N X ^ T \ j V `VL h NLX\Z\VPRR\VNXX\LJRPP`VD\\NPNrRPP\X\RdR\N^`ZXHNV^bbRPZZVVTZ\bX^THTDbXV`VVXZRJLVTJTVJLTJZVB\^HVhV\P^PdPLZP`^X\Z\RZLb^^VfTR^DlHXZLPT\NVjTZZ^^VF^XPdN VD V d ^L ^ \\ V T d  X RJ VJP P X P X P P H X b L V T P V R R L X Z N N ` X J J ` L X X P b N^ ` T LZX^b `NbbVFTNTT`rXVbXP^Rd\b\TNXZPZHDbZ`\\T`XHPVDbbPXVXPbRV^J@VV`ZZ\XXX\ZZZ\\TLVZVRTRTZLLFFdZZT`Vd`NRLjTd^Z^VRXVZ^VbV`VV^Z^bRTRJZP\NVRR`X\XT^bZZXbFZV\NdXJb`b`ZTd\XTLNZ\\ZXXZPZXXZX^NlR`VLXXZ`dl\`L`ZZj\`^dRZXNNd\JR^hV`RdTLLbPXPXbVXNXX^PZRTVPNbRbNdP`^\fLNTbLL`\RFPXVX``LR\ZLZ``\Vf`L`T``XbPZ\ZVLfXTZ`\ZX`V\\HdPh\RJ^PLfNbnbdRdZPJ^RXPZpHX\bPZbhJXPbVhdXXPR^ZfZ\\NRXVNFhRV^Z^RVV^f\Xd`PRdVV\\VRVRLT^XJPZ\RdNXT@V`FTX\PfRRZRVXNDPTZhbZ^\XfRTFZRXRdfXJV\VZXZXVXb\bZL\\RVLNXPlBLTTX^NX>VXVXVbT`TT\VH`RPhP\RTN`HP`FTVZVP`PdVTRTFPP^RVZ^N`R^^HHJVbL`bTR\TX`PP\XBZL`TPF\\fPX\XVXdN\RVJXNj\TNLRVd^R^H^TNNTLTXT`dRXPV`RPNRPbRVHLDNXBJ\XPTPdTPJDVZFX X ^ \ R ^ ^ ^ Z \ V V L @ P Z Z X V B V ^ L ^ ^ ^V d XRT^N ZV`bZNDNRPHTZ\TPTX`TZNbL`ZXVL\DLTTdNJRVTP^`XbPPTRLh^NLNZXbP^NNPLbVXZPN\R\VV`TPXPPLV^^H`bPRRFBN\XHPVT\TF>T`Pj<PNR\XN`NPPPV^L`^TP\VLRNRVRRJ T R P R b X R Z Z P \ Xd J `P \ Z V \ J X b X d P P T ` ` J \ Z T X V P P JZ X DPbNVf ^R`RZRZdRdNbnN`ZLTR@ZP`VLXNNbRVNVXXZH^XJPXL`ZbTXbR^^HRVXLNX\LRHRNTPRFVP\D\\XVL\`R`PJTT\ZVTNX`VZNHZVXVRVLVP\ZZRJTZPZZ\RRVVXLhPb\T`RVfN`RNZLfVZ^XPTTP^^PZTXPbZ\LLXPbJNNN^XFRDNZ`V^T`VV\H\VDXPP^ZTZ`^VTZX`TfdnFRNbV`VVfPf\`b`ZT\TZZ\ZPXVV^XNfZPbXhJZZXd^^PP^ZZJXdLZNNZffRL`ZRRRTZjRVZR\X\^bVVNZRNTPRRVNfB\T^VPNTRPTNNNNXZ\bX\TdPbjJfT^\\TTdbnHTRP\XTZJ`\\PTRbXfHZLTLL\NTX`Xd^JZPZHTT\<PbVJVV^X^blVRZbhL\XVRP\jR^NRbTXpZRXX^RR\XbfZLR`X^`bXZ\RXT>fb^TjV^ZJTLVZVT^NT^,XTTTJRVf^NXV^bNPXVbZ\XTXVL^bLXZTN\LNL^NPZ`T`VRbRbH`XX\DX\N^TVXVVZTT\VRNbR^Jb`bVfVdZ^XZbTZZTT\:`NZXRP\RJV^`V\XTPbPT^FZD^ZXDZ`VfLR\`fZRVF\LTVVPPXTPZT^JNRbVVVJNZP N XPH T N R ` Z P ` J N h X P \ X XV Hfd^  NZZZ\TjbZJXVL^VbV^XVP\`RXPBZRVZbhR\``VXVZXPJXLTRVN\PNVXbJVZ`LTR`HNL^\RTZ`HZPXVNN`^RNLLV^T\XbXXNVFXRT`RXXZRTXH\FNX`\TTPXZTNZ\LPXP\ZL^Z^TZPP\L ^ \\Z P \ h ` R ` N d^XVZ d H \ L P X \ H ` ^ d \ P \ b R T ^ F V T ^ T ^ L L T ^ PZ `JRXFhbP\Z\XVX`ZZTnLjXR^@PRd\TXXPFZJTTZXVdTXTZLTJHb\ZP`hXT\TPX^LZ^X`LXX\b^`VZhVVXLTd^PVVRVHZRbP`VXPZhV\^RVXZTVV`R`RdRRhXPdfVT\XN^`^TdbHR^dXfHHNbfHZRZVTRZTVXTJXZ\VLT^TZ^R`XNPbTXX^VL\\TZN`THbZ\VTdRdZT^^lHVPfRJHZTZPdTZ^NVR^VZd\VT^ZdXZh\hlR\ZXP^R`dLb\XbTdXVZ\HN\\bR^VZ\N`\dJFPdX\dhZV\R`<TXRTNTJVZ`VXXdbdVbT\\TRPL`jRXFVB\TZ\R`^^\PVP^ZR\ZRdnTfj\X``\^PL`ZNX`ZbZVZT^L\^fZ^`X^X^XXPdZTfhhRNTNTHLFZRTZT\>`PPJPVBR^PV`ZTXbR`PJJRX\b`PPR^`\bDRRNTTN^NTJXPZJLXRXXHLZFNNVXNRVRZHNTRRVHJPZbZL^PZPPVV\\L\fVZNTXJ\V`dRR8RRbPNZ\NXRHP`HNPJLPd\`PVFPTVTB\NjTZXZJPhVPRZ\NTTJPRVFdRHZR^TJ`^LBRZ^NfZTVf4TN^dPNVVPXjTX`BPDT^F^\TfPNRNTZ`VXZL@TbP>XNHZRBT\VHHJPVTFZT8VZb\TRVTdLJ\X TLZ\P ZPb ^ V \ X T X P Z V V T Z P R XV\ R XT\h\Z\JZXVRR\NHRPX@TBTTXR\RTFVVV\TPVHfVLX\N`LdZVPfTTPjTRTNPRPLNVBTLJJPZTN>\^LZPXZdT^J^dRZZTXTZRJVNHNRZNRPR\fJZPZ\^`\B<T^VPRRRNTV\N\`H`RNTXP\XnhPTZPRLNP\XbXN J ^ J V V JR R\VRT  V X V N N R J b X Z J ` f T \ P V R \ N ^ V V V T  \DXN ZBFT^\ d Xd TL`TR^RXJZPdRRX\TVZVTT^TXXPPbNV\^TVN\L^hR^LT^JH^RN^^NR\N\`VN`RDXPVPVPXNL@XLVPNBZR\HTdHXVNZ^R^TRZX>T\\TXPXZXbZ^ZZP>RV^TfNJVVV`XXXP`RVPXT`ZXPTh^XZZ`\VdTV\``LdRJ^\\V^T\XPRZNbTZ\hPT^X`dfPNZRTZLRPJXJXPTRTJ\JLTPhPP^NV\LBZ\Vj^TZRRRV\XNfPXb^\`\VdPP`Zb^PZ`bVV\R^LLV\PTNT`LTNPj\VlZVb`X\^N\TZXZbXJ`XPTRV`L@\Vb\TZXdFVZPRL\Vp^T`p^\ZXh^^ZX\LfX^R`d\ZVX^^``VdTXP`\XRNVfXZhLPZdT^ZZT`XbHbTNjPFXTJN`lR^RFTTTFHdTHPVV``H`RbXVT^`d\N``TZ\R\TV^bbRPLX^bLbXd^ZLTR`Z^TVTXbXRRZFT^FRZP\XLTZVHFTVbPRJXZT\RTZN\RRTNbTVJNT^`P^LTT\bLLVPNZ^hTVfXL`LX^PPTJ`ZR^N\R\ZbP\^ZVZTRNTTVTXVVRbRTPF\RVb^```XTJ^jTJ\ZFZXJTR^Z\^N`JPVVR\R\bXPXTT^T`JZDR\VTDRZLT TZZbTZ \ P V \ ^ Z T X \ ^ d J X R H L Z ^ \ T T \ \ Z V N H b R bZ T\JhV^ThfPhVJFRHNTZRXTRNhL^ZVJXT^PRZ``RZRVT`NVPTLXBTd\^f\\HbLd\T\Rd`VTLFZZVTJXR\^TPRV`R\T\VLLX\H^hZXbVFTZJfJZV`\ZTHD`PTRL^TbXF^P^BhVXZhRNb@dPLRX^bNdZD\d  \nPVZXN^R X T \ H \ l V P X \ b\ F ^ F V X b X B V Z L ^ R H N J L R \ RbD PPR VT V ^RNdPZ`Zb\NRXZV^\V^dZZVL\RPVTVdLVVZXL^HdP`Z`P^XVRLRhDL`XTdr\TJHPDRV\VXZRPV^TXVP^f\^RLZNNX``X^P^RJlV^`TRX\XZ^^\\VT`XNFJRX`Nf\RVfVZPTV\XPFdNfRZV\XHXdb@RXXRV^TdTT\`D`XTRR\V^TfVdbT\ZZNd\hPX^Ph\fP`DZ^FbT`bbZThZbH^NT^\RPPZ\LXZV^^RT^PbRLRXbTtTX\X\ZTT\TTXJP`T`\DPR\J``\XZV\\bXTNHTXdNNRZ`RR@TLX\RZZHNNXbX^`XXdX`X\^\d\XRZjZb^\T`T\RX`TR`fNPVXT^bVbZNPVTXfVN\X^PVTT@^f\L\XVTD\>d\VT@XT^N\TTXHRZXHZXXFjT^VLNT`\J\RX`H^\N`XRJXV\\^bDPXV`V\\`H^T`V<VfLXRPJTVVNFPXTLbLP\XLNbJ`\^2T`XJXVNJbPTTZ^^TT\ZH^`R^LZN^VZZFNRR^VNZ\LLdRRTX\^TZ^LXR\PNTL@XPVbXXFZ`RVZZT`^^N\ZHTXXXTVVNZ^LPZ`PL\bXdb\ZZb^TBPTV\\ ZPP F d P HX N L \ \ d T ` N ^ J V Z ^ X T T R V <X ` NZR\NHFT@ZZHXNHZB^^VZRTXRBNVNZbHT^\ZXR^\XZPN\JXJ^\ZF`X\LVLVTVXZJRXJTVPNNRFLJ\N^PJZVX`RPNN^lRPNbPVNP^RXP`RT\X^TL`TVZZPNZZhLRN`H`>\ZX^dXPZ\XRTLN\VNTdXVDNLTZR\XN^LR^ZVZVZL\VH`XLLLVLLNRPV V P H T ^ P b X J \ \ T J d R ^ T T R b X T \ Z X V  j T d ^V\ \ N h T Z X X^TXZ^VNNVTNZZXTJZRRP@\VTh\PNRVPNRNjVLfdbTRVJPP\TVRZP^NZV\TDPZHNPRVj`NPRF\R^ZVP\bHVRNZT^T\\V^\P\Z\BX`XF^LJ`jXNRVVDXRj`BZh\X@hZR\FZ^XTPRVRXTTXTVVVNNV^XTRPVV^F\ZZ^XPnVbPLblPPfJP``RhDXbbPZX^PVRPX\PZXZ`RPTRNPjVNfPPbLj`VbXlbXXRV^VVXXRVZNXR^R\``N\LVZNRV^XdLXVVZTX`VZDV^XXXXXTRNVV^\VLTNPXNHLPRZX^TDbTbl`ZbjdZ`PV`^X\J\^j`T`\ZpZjhfTV^``bRVHl\XbHXbNTRXdTNXZ\LV^\ZdT^^VZfRfh`V^bZ`\`Rlfd^VZfZ`VXLFrjXbhD`Zj`T`dfJVVZR\XLVJZd\Z^VZ`bL\\l^Pj\XX^\RVZ`PDT^PTVXRVZJ\N\LTVDTTR^RX:^P^\ZTRVXVRPTT\N^`\`^RZTPNZL\VRJ^`\TJ\ZTHV^NddLXR^NRZbXZPVZ^\`ZV\TLPNL\PXZP>R\N`VZVN\bT\L\XRVTfZJT``bT\X\ZTP\RVXHP\TNT \ TJRN^\V Z X R ^ f X X L ` Z P ` \ Z X  Z P TV Z\\Pf`bDLdZNJR^VZXZ^j^VVdLZRTTHRL^^\RTNPhN\J\PfdXRXRHNhLLLdJLPZ^HXPhXLRh\JVT8PTRPd!NFTH\PPFfZT`RZHZPfNLZ^XXXb\ZR`VRTh`\ZJZd^\JTBZR^THX^\XLVH^LfV\Rh`TZXZTZRfXZNhPZZTR  P R \ D X T N Z \ T \ X V Z X Z P @ J N ^ L P ` X d R Z N  f P Z ^X\`XPRdJbPZH^ZXZTR`JjLT\TR^R`fbPZb`TR\X^^JZN\`\XTR\^NTZVL\PPFfPVXLHPZR^bNPLZXfbXRLT\\b`ZTV\ZZbVXXXTTRZhF^PNdPTdVT^XfRfP\PRfXXZZZ`LTTLZ`NZbXZVZPdVbXXNdXZ\Pb`LXVZ`ZP^NTLVVJXZRDZV^VP`TJZVVLVJJb\TT\\VNfdPX^X``dRRdXVLZNXL\VX`Pd^^XRTfVZ`ZZX`^^ZXZX``X`X`TdNVLJf^ThRV\\^dNH`VZRXZTZ`ZZdZZZbRNZRdNPNLZNdR^RPPbN\\j^`L^ZVlZRbd\dZP`P^\ZZl^VT\\dXbJT\PX^RR`NPdRNZVd^RbXZbbZTZRXfP`bNT\ZPRNTPHP^P\RVRLRRbHLXD`XRFXVLXPZZLVZRVRR\JVZ^ZdF`N\RZLdXRZZRRXNP`XX^RH\VVZVXNT^B^TXbfL`bT\\^PRPV@^JNHNVVH`PbXLR\lZ\RV`Z^P``XTRZ^ZZT\@V@bPPb^LTRVXRVFZ^\^bJZJVPVJZJ\JR\LFZHXNXXNLRJff`bjT`\LHhJZD\XZZVT hFRF TdRB  R V X ^ ^ N R R L P R X V Z P P T ^ J R  TN RTNZX`ZJ\LZTPP^ZhP\JLZN\XXZDLhN^HNLVL^ZVPLdTXH^^NJR`L@V^HZV\dR^bT^VFd>FLVNVRZZbTPVJ`L^T HV^R\VNNXTXRX8p\NZVPPbX\\X\T^ZVNPP\ZXN^JVRRhFXHXXVXPZVZLP\VJXNT^NHLLHZLHZL`LXVNhbX` d \ N Lb \ V T X f T d V X V : \ N d R V V Z T N ^ J Z V  n R T V ^X`PRRR\VXZH\X`dVNT\JXZXPRbVPRVPTZ\HhN`ZJ\LTZ^TTX`TXXP\RT^N^RPVHZ^RZb\TT ^XNFbTDJXR`LZXZ^F^L`RXFVTbf\VZJPbRVJ^TNPdd\FLPNRZ^fPbPZZR^`^fX\JXZ\dZ`^NNFlVHLZZLHTbVVVVXLTVZ`TX`^hZ\VVTfbTdZR`ZVTJHZLV\V^TZRZRj\XXRZlP\LXR\TVXVbbLTFZ^VZRPXLTPX^Rb`ZPbP`^V^Z\V^V^^ZfX^LRNR^^VVRRPXV\XP^TZRh^P^^NbbHTBZZV^\VVL`VRRZdNXX\bdX`ZV`jXZbRLb`R`h^T\LjL^RRZHhZVbX`\TR\j`ZPTVZhTZ`R^DdPX\XX`b\ZPXdbZRTPRT`\TNPXZR`Z^TT^^bP\ZZPLPTVPPZZhRNTTdZVXXLJVXLBb\ZX^`TLXHlHZ\XfJ\hR^PZLdBTXRZFdR`VVXTTVZ\`XVNTJTJNRXTR`dNTDJTZVLRZhbZ\HRN^L^V^VRdb^PjT^ZRVXXPP^XNXVNZPVNXXLXR\ZbhZRRV`RV^VN\Z`T^XPZVLdDXL^TZ``@J\ZRPbHVZL`^ RVJ  XZ ^ Xd J  V J \ P T ^ V T Z L b R P d ^ b P  \ F^fZTd`VVZP^TbP\XXdZZd\bPXZXT`b\JDP`RVHT`bVRTXRTbRfT`f\XVPVVP`RNNTPVLRP`PP`XNTT!XZJFZ\PfXR X!TLbZdX\XZTZN^^`B`D\\VPLVVXTLXLZ\X\^VZTNVTX^ZVV\VX^TRLH\\fRdVZZVZZZ\bZHfXRLX`F`BN\TPVT^ZRb PZ XL\d ZL R ` T ^  V R \ R X \ Z R N d  V T P b T b d X  X ^ZRXdJ\VZXRH\^PLVZVfP\HXTDTZLRF^N\^VXbbV\V`LTZXRVHN^bFRXZH\`FVX@HLVLL^dRPT^RRT\J^P^Z^\RXVThbFbZ\^`TNNTXdb\ZX^`Tb\T\R`PLT`PZR\ZDPP`TX`VVT^TTXTPdXXZZNVFPN`NNRnJ`VXRXNd^XXVZZ>hLTRJV^TZVTZZVdFT^LZdfZTLd`^PRTXThRZ^XZ\X`VPZXf\^dbddV\ZJbTTT\ZXXZVVV\dTV^ZZX^^VJbNN^dPTXdZZJLPP\^JX\\Td`bXTRXNXdHV^ZXZFPPD``@JHfLbXThT``XV``^XjNJZd`PRZbNV`TVV\XfZZd\ZZZTZZVRT^\PXVR\Z<^RXXN\`T\d`HHbVXZTPVdNLLfTNVRbP`NHXRTXPPPX`VR`\RZRLPXLZRfPbDPRHZDVVZRVXPTRRXZ`\NZ`JB\\LLVdJPT\Z`T^ZZBVZNR\^FVRZNZZDXd\N^LRZLd`fDV\THTZLV\^XRZVTV^VT`\B\HdRRT\ZXTZZPRZNJTRH^TPTRRZX`\Z`dVLRbXbL\RPZN^ZVRTT`NR\XbZNXXTLTVT\VTT`ZbVXHXbTJRNH`PDLZPJJJPPNLN VT XHRdT ZX PZ T\ T R ` P X V X N J Z P N N Z P Z H LJbPZRhTDZXZNTR^\N^T`TNN`T^^RZNJNRB`DHVL`dRFXZL`NTRLbLZVbV`ZRR\R\RZPTPNJRRRJXZV^^LdR `\V N`FTTLXFNPFXVV`\LRNbVVPbZJZLLV\Z`^RRP\Fj`TRTfLX`Jb>`RT^L^L`V`Z^\N`ZRVLH\:XLTNXH ZVRR\^bLVL L \ b d \ b ` T bL R \TP f P \ P V L X R ^ N R ^ J ^ T  VR b ^V\`HPL\BDVZNZTX\XbXT\^\`ZVZFLTNl\VZ\TZHbTZRT^`NLlV\\``\P\VPV^RXTLbZHRPR\^b`X\ZdL`L\ZTL`JXXjTPPRbHNhHVZH^HTPjRbF\JZdNfDPXfVNTZTT\TZZfZ`VV\N\`f\T`ZX`NTV\`XVRL\T\\^P\b^VnVHZ`RZZLTNVXRRZ\VbJZR`V`VThRZLZRNZTRT\^RVX^PZfVT\@X\VfF\\XZ\PX\dZVDZZ`^`ZZ\bb\\TTb\TVV\LN^RZPRdLbLXVVPVXTZXRNH^\NZ\T^PVXX\N^R^NJ\VNPFTVXVfRX^\n`bXXT\H`dVZXZ\b`X`j\\XffX`fVP^X`RXVPPdF^Rb`XTTX`\XbVPXRZ^`RXX\ZVNPNXNh:XRPXLZZZb`X\VXVXR`V^LfLDbX^XZFPPhRdX^PVl^fP<V`^ZN\`fRTJ^TZdDd`ZVRV\d^VTT\`fdTNHVNXZ`PfDRLPDVVRTX^P`\LV`XRZRV`R\`^`XPT^PfXVRZfXX`^bLPPN\TLVnT\NJb\L(ZHPjVT\TJHfV^TLZ`R\ZX`VZZ\df`^JXXTT^VV`TNX`LXL\hZZLXdRR`ZVdVPh ZTbTJV^V T T ZF Z \ T T B Z R R Z ` P H ` J X T ` X XZ Z ^\NT^Z`V2XTZXV\FXZTPN`XdTbJXJVZRPRPX`^RXTTfP^ZP`RfNL`FPLfNZ\ZPPfZfPXLR\RRX^TVXVZZPVZ ^Z!VJ "P! h X Z `b ZX\RR\XTP^`^XNPTbZTZXZJ`VXdVd`hZLdT\fBV\XZNjXVR4TRZ\ZRTJ^^LZTVNJ\NZf^ TT P R RdRXV8 P R D R Z Z R P d X L R Z Z X T f T V T XV T TZXdX dTXVZVJJNX^hNZZJTXVTJR\VFTTlXRNXRbVHZZVRXPVVTZBdTT^R\\bb\RTHNPNPPXNVXFbRZ\R^lTDNPVR``VdTPVF\TZddTVVT`VVXNdXJZHR<^HT^RHTXXdPbZXbZV\XZ^bXdXbZBd^X^LdVF^RPTP`\NN\RXb^\`ZXNbPVRNbD`NXZ\LV`VZXR^`XbdXFbfP^^ZTdZhX^X^\V^dbFT\\N^\\XJ\VXN\b\XZ`PT^Z\XdJVX``l`VXNVXjV@b`Z\PbT``RhLPXRRfLZPJN^ZThhV\RbZ^b\^ZZXVVVhX^RTfZ Nb`Z\RR^ZZPj\VbXZZVTT`XJT\ZZDZdPf\`LLP^RTTZZ^\PHPZ^ZbfN^H^^`^\FX\ZPZ`X\ZRR^\RRXHZjNTNTJTNV\XZZ^NP^XFXRZXJHPT\ZTTVZFFV^L`H^JPTRPVFXZVXLNXhNJRLLNZPH^`HNT^JVJbP\JRXX^`XVbZh@RZT`ZTh`N^dXbR\VRdRVPRPBVP^f^B^RR^fRbLXTdZR\``\P^RHT`PVdJfPT@`XV^R`XTZbXDL^\NL HV N XH ^ X R T P J  X L Z ^ \ V ` V R F T  X X N NZFR\XPZXXX\dPTXNRXXPRVFXTVT\PZZVTRPTfTVNXNZRb^ZPZNPXDDHVRVZhhRVXJ^RN`RZZNJ`hPRRRTRD XZP\N!T! J#Z"!f!!PbN ` Tf^NdP\RLNVN\NPfXRJP`ZHXTZ\d^ZTZRF@`VVPZTXZVNJVLVXZX`\VV\Z^R`PbP^TTT`NJTZPZTTZ NV<TVXPRV `T Z TR VN\L ^ ^ Z ` V ^ \ T \ J ^ P N Z X L R T P PdRZP>^JdL`RTbH\X\d`V^PJBT\RZPPLJXTbbd`JV\^b\VJVTRX^XTZH`HX`R`F^\VXPXbBZf^\^ZZXJ^FbR`ZNP\NXZ^X`TVTPRRLVhRLVjRZVTdfZ`T^L^NT\VVRZXX^RZVXRT^T^`FR\RbZ\\RPP^\LhVXNZZVNJ\Tb>X`TZZ^ZB^LXRXRXZ\RTNZPTNXRZ^JPRR^V\\XVXTXL`b\RHPbTZZ\^Z\X\RX`ZFZpRZPL^dTXX\V^VVP^PR\P\VP\RTP^RX\`VPXTLVXNNHVTLPV@TXPTTh^hf`f`jl\PXh\bj^RLXnN`d`RTTPTbT\FNJL^PVVV^fNZNRPjbThPX`^XPJ`R`RZdXXTRVbXbPJNbbNT\NVPdV^^dX`\fVbb^RPfNVN\`P^dJbVZf\X^VRPdd^^Z\\Z^bThhZ\b^RZ`^ZXfHPPTVNbRP\lPXP\f^NXZLH`XR\\XTVLN\\`VJXXb^VTZbVhP^dbX\JTZZZbV^N\ZTZNdRZ^Rb\N\^RNTH^\^XNPTP\\RJRVNd\`ZNJTjZP`VNhR^RPVbLT^PPX\TV\ `PbPT X PR B V P \ L X L \ \ ^ Z T ` V V T L V P ^ X P ^ V X T Z V\RLP`JJ`LdbhZ^B^^NVF\\TPR\PPbRX^XZVN\XdXd`XPP`\V`XNfXP^TVZZ^Z@NBR^\`>TPX^`^ dXXT\ZPRTNTNJ\^XLR X!V !ZN" N V ! T Z!J#""!\! F X DRHN XVRZlZZN^^`HVVXPFhHXP^R\bH\HRR`XTbZbbXf^^H^R^VHVTNRNRZhF^^LN^TTPVNDXHbbPTRVZ ^V `ZT N L\ T T \ X L Z T P T \ X V b V \ Z \ ^ V ` bXLLJXRX`TVRf^V\dZdVXRZLRd^N\`NRXXPbJbVZF\d\RfVRdJfRTZVbDZVZTR`N^HFddV\PbX\PZbXfV\NV>VT^fnXPTNJZbP^TP@TXV\TT\Z\hPL`ZPPVVNN\NHZdNXfRVZZPP`JZ`VVZPPVd\N`VZPTVZdTZhdX`\`d^XV\FdJVVVZBbTRVX``bJTP^^ZdL\Rd\N`TXV\\PZL\bbZ^TNjPZ^ZJXLfT\RdZTV`VXX\F@nbZ\^FdP`XNVZXVFXB\Z^l^`^XNbVNHTVbP^N\TdT`\bT\XX`N\b`VTNXZ\R^XVZZN\`dZZX\ZZLTfVH\RXVVTJTTn^VbR^TXTbjVXFVfNZZTPHTb^^XVZ``ZPXXd@TNXVZJ\VZPP^ZnZ^b`j^F\^fBVL\H\XNRdTPhZRT^bdPX^PRDP\bLHdNV\TXXP`bLVND`ZBL^PLXP\DVZ^TjNJJVZJPVNjVbh^L\XJVfFXR`PRR^TJFNLJPTTVTVPdZZTDNLJZT^RVTVNL\^RRRLHZTZ@PTVZ`TT^\LTT\XTP\Rb^\XXVjP\RRNPXV`LVTb`DZF\VTZbVhLVPX T V ZbVh JV ZZ ^ ^ N F H ^ T T P d V b \ ^ Z Z L ^ ^FXTT`\RXV`TNZ`X\\VfR(PZFTT^VZBVVH`D`LXTJTXXRPZXXRdPLXJZNTPfVNXNZ\T X RLR`FVVV`RL! b d! V!T"! T#P$ @!" d "! "!`!N"T!P ZN V!TXXN\ZLZTJLLPDXX@NdbZPNNN^NbVZRXTbHVRZR`DTX^NPPZP^^JRVZVL:^TX`VZ\^PNVVVVbDX^P^T\fbTBbRVZjTBRJ VP ` R P T X L \ N X R T ^ Z Z P Z b R XL`RRP^T`\PNB^LPPPXVVXZ^H<bfLRb^TN`PTPDZT^^^X\VTdPHNXJZ\\XLRZTHTLLNNTbTLTDHZPXNhJZLRRHJTT^X`TNTRTR>VRPPPbZVP^PL^N`LVdBRPVX`RH\\R^^PTXVLV`NLTPXZD\RRXX`LV`TFZ^NLJh\NRXPRTd^LLTZVT^^FLJXTH`LXf\^V`RTTR\b^`ZLf\R\PZV\X\dRXZRLVRXZNRVhP\bXNXXXTTRZRVH\^PP@lZXV`lPXR^Z^RLbNNTT\NXX\P\V^RNZ^RNRB\fRV`VZ\\Zd``ZjJhJX`T`h\djVX`b\ZbZP\Z^V\VTRV^\Z`ZbT^XXfDZ`T\X^J^BR^^XlXVTT\Zf^ZfVLVfbZTLZhZ^XR\\Vb`^`HZXbTZVVDT\\VNb\VHPXNfRTRLTVXNXDZXJXLXZZRL\JN`FTRX^bXPLJX^TXbVRTP`bfXVdTN\XNLT^Zj8RNNXRZLR>LRPZV\NH\Z\HDd^JXZV\\VPP^NXhVV@\X\ZX\V\VD`PR^L\FPP`XX\^NdTL\\XNVT^Vb^Rf@T^TJ@ P T R X X J Z Z T N ^ J b b ^ ^ R H ` T L LT Z V Z  d `J`XZPNR^JRXFTXHXX^\XN\RV^`DV\ZRT\NZNF\^BVVVNNZpRVZVPf^VLT\ZVVb`R\LZTX!HTX^P!`D!"R !T XP T! !# P"R#N"T#! "R#!P"!h!T!J N#X RH"P Z"L! X` TN  V!^V^TNRXXXVLZZZV^`T`LV\TVLbHVbNdPZRX^hdRRT@X@VVVPTXX\^RjRZ^NRNL^RR`^TRb`fXb`R`^HN\JXJNRN V V b bF ` P\ L D ` X L T ^ T R X Z Nb T VbdTPd ZRZRbPN^NRP`Z^fPDhHfRfXVfLRVXV^TXBPhR^RZPTN^\XRRNPPXZVX8VZV``N``RPVbTd\RVdVR`ZLNb`V^\`b\P`Z\TTPLdLTNRbPFVT^JXZnbT`VPbZdZ^^RZNF\\X\TPV`XPRLZXTVVXNX\\X\`ZP`Xb`bRVL\fTL`^VNR^TV\VR`NXVT^^hbTb^HVTTZ```^bT^^T\PXN\VbXXRTV^XX\XP`nTVTXd`XZVP^LR^X`LLd^XZLVb\Z\LVXP`VZXXF\ZhNZNdXfLRZhZR`HXZVV^Zd\TXHT\PbPTTN\\TR`hJ`HXb>XRXbV^T^XV\lbTPVVhN\T\\T`VdZbZ^j\X\\fXRJ\TZTNV^`XTVPPTFb`J`JRdLHTTXRZJNPR\bNLHXV\\`XXT^JJ^JNX\V\Nb^bJ^JPPh@VLRjNNL^XRVXbXJTT\ZBTTTNPPJZTRNVJ\XZVNTT^D`FFRTX^`\X\JF`T`JN\TVTTVLfLTf\^VZXX\TPT^\\`ZXR\`FL\PPPRBPZZL^P^^JRPTf^NNVZ>XPZLD`ZTXRNdJR\NLbLJJFLVRVV\TRRVRXbXJ\@\\b^TPX\ZRV`X^XZ`NVTR\HJPTL>FRdZ\R V  V Z  X X F V F P \ P Z Z V N X ` R ^ ` R T R b VX  RX P \DXT^VdHPXVTPRFVZ\HjJJ`ZTR\VRN`LZPNPbN\T\VXXRb\JNX^`\T^PXJ`LfbPRFTNdZTZ H!!N N^X X^dj ! f"L!!!Z!  !P T"b!z"#N!V"L"`#^ \!V""L"Z#X L"b"X!#X"T !N T R!TB R!R  P\ LZV\ ZX\H\FZPJXZZ`^fRTXNVRVLJPXPdNTLRNbdJRJ\ZTRVLTHVVNHLLLJ\NXZVFXJJ`XTVNNXTTHNNZZVBP\PX L H b X T ` L P N ^ L T L N V T V \ H V ^N L TPZTZJXZ \XVDJVR\XLRRf`XT\VTh\`\^PR`T^VhNVbV^`VVP\NPZ``ZRV`RRJRh`VPNNZP\\@NZ^RFTPZ\NXLPXXVHlZbR\V^VXXPTPdZZNRb^PZ\JbNZX`L^`RNTbTZ`\lTZ`ZJ\ZXbVXb\LbXN\ZRVLdT\TT^FV^N``XPbXhNP`XXTZN\ZJ\bXL\ ZTjVT\TbNXPRFTTLJZTR`V`X\PlTTRZRVV^RTVNX^\RPZZJ\b`TTVV^X\bV`T\ZLd8XTZVV@V\^LXTH^RXLTXNZXZdVT^DX`VVZTR`BT\h\^^dTdf`n\ddhTVX`Zp^dRH\`XfTnZ`T^dZ\`\bZZVZTX\TZ``Zf`RfR^`XbbR^VBfLTZ^NVdXX^^N@fj`bVd`>^X^RVbVRRTNLdXTZRRPVRJdZVbTF^^RH\`RTT^Vb`NJZPV\bJ>Zh^\RTN^PNVXXfVRPZ\Z\^TNTXZ\RTPLVXZ^H^NZXRRBNVPRdXPTXTTT\L^NPNTdR\\Hb\TPXXT\P\ZLb\R`ZZZ^^ZVLTXH^VRZ^VNZXLVZZV^NVRXLVbV^^df^^ZbP lb J N T L f X ` R \ T \ F J H \ H Z Z Z X F T  V V J XZTP`b`VT`fZPRT\XVP@RdXPJFTXTVVN\Z`R`PZVT^^X\T^ZXLLNRT\XLZfZPbZTJ`R\^^>ZL^ bLDXbV P J \ !!\"j"Z!TH!<" L!X##b"!!T#N$!P! X"#!\#"#!Z""\! D!P d V!\!T!!! ` \"^ ` D! XRLVXdTBT dPVXVZ^HHLRR:NX^P\VPPdNdNRdTHTRJXXD`XfRVZZR\T\f`PHXb\X\VR\XVZPVRV\L^J R^XXV b  \ R T T N T b R P Z Z ^ fZZ^VL ` T TNXPbTPfZb^VXV^RTVXD`^NVNBXJPNVDL^XVPTbfVNbV`NXFb^NbNb`XPNfPZXdLZXRVVBRb`JVXTLNT^^\lX^hNX`b^XPZ\TT@bLX@XTRVbT\XR^VNb\T\ZPVVPP\X\^`VLXhNT^X\JPTXNN\^N\XZ@j^XTZVT\RXJXN\dVN\NJPJ^hX<LVL\THVXXZZXTJ\V^`RHZZbdXRbTbZ\dXZ^^R\ZTffTTjH^ZPVHdVRZ>`NdZT^Pbj\XT^XPd\`NTVPRbRDNNJPDRT`RHVZZR\LZZ``\RZVbXPfPZ\XXZV`ZX\\bRVP4^X\TjfP`TPNXLF^TLPNTV^X^TPHHTZJRNNZZTBNXh^RRfNPRPLb``J\T\VPRVTLVTVRZVVLVfLPTPZVVRT`PR\PP^H^\ZHZfTTRV\ZXLZ^VdZV^JXRJRPZZT\R`PdXXNRN^NLPL`@jVXVRRL`VbRR>\L\TTR^b\NXLJTRbHX`JX\ZZX@RV^\R`<VPXNTZPXRbX^VfXZBTPRF`ZVZhTLXPNFNZTXTZRTNTRTT\ XRbVT Z J F Z \ F ^ P T h J L b R P H f ` P V N N ^ RRdXLVX@jPXHVZTDTRRVPZ\`R\FPNZRZLZ^HPH\RLJ\VNTTJb^JVRRX@TPTPR^`VbFZdPT@TJ!` JJ!T ! @\!\ !P!D !P"R!F \!N#D" `#!"!R"T"\ $R""T#Z#\! ` V#H P#"#!##V#R"Z#T!V"V ^ ` N !Z#T#"`!X!N!D#V!T"!R"N!V!ZJX L ^H!Rf R`\P Nh`LfZ N\Ld\TRRLPbTRRXXP\RdRZHLHN\H^RZ<PBXR^PRbfLTL`JXLRBRdX\VXXJZD`\^VPdNVPf RJ PTNTZ T \ R N Z P ^ T ` Z Z L V ^ XX VXJLRHP\VRT^TLRVZNFP^NNRLTNFJD^^ldP>bL\PPVhLNVZXTb\RL\dH^fXbLLBVX`JVXfNRTZTTXXhLHbJPbVVRPZVJLRRhLX`\V`NPZbR`TP^`XXXXVJRVPVdLX\ZVTbZRRF`Z^d`XLZRVV\PT\\\VTPjNV^TZPPFVF\TPfVN\`NdVRRZTZT\R\ZR`VdPVNn``PXdLh\jTXXL^Xl`NRXVZ`X^dNd\`VTLP`bZDPZVNbRTXVT\hZ`ZXXX^TZbZZ\RVTbbV`ZTdVZZ`j^\fXj`\RjZNZ`JTPVRJLfRNJTZZXVX^PdNXN\TPZRNZVHVZTVRNZZ\^`ZlbJXRZ\ZNb`PX`fLJV\dFV`VRV\ZTZ^NRVVR^ZbR`T^J^BZZXVTRRLbTbH`Xb`T`XdP`NV^NPTTLJVVRN\^TX\L`TRZZLjPLXVXRNTZRXRjF\\db\VJRLRPXXP``Z\NTLTPRb`JVDbXJbVNTLVJZn^ZXNZ`TRbTPjTN\R\``ZXTPTR`LZP ^nN\TH jF b V ^ Z X Z ` f P N f L X \ l \ P X T f T T R Z R VZ JZV\XV^VV\dTbh^RXTRTNlVbRVN^bJ^ZR^RbTXLTVXV\XTN\T\\R^bXRVNb`bJ^RT`b\ZfR f ^Z!P^LJ^!P!P#T! \#!"`!N!"L!##^"!!"V!V"!V"#"!"$P#`!"#N"T#"f#"h#""Z#!!"T!^ V!R!Z$h"P#V!Z"P!`"VJ!P ` N! b b NdTPLNV Z`T`PR^nHZ`L\\RR\ZRbLZVBVXdPdTLLZPThTVJbP`V`FZRRZLL^`VXNVX`@fZP^R`ZZN\V PL N\ ^P J R Z f N ` f P P b J b L F R R V b ^ L XL f XR^^TZ`RR`V`XHZ\ZZb`lHNPPNNZTNVRXT^NLbTRNnZ\\fXLNDVXLbL^ZH^H``R\ThZb\N^VHJ^ZR^`^LRP`Z^^\^VTJVV`\^\VRb\Z`j^PXTZ\^Tj^dNPRbbZX\VP\L^JVdT^ZXXV`LbdZZZLX^^TPNPXTbZRP`B^L^NVdRPNZZRNhT^RbXTZXNdbZZ\Z``XNdN^\Z\TVVbTZTZl`ZhZVJ`\VbP\\TXX\RVbJd>NXLV\H`b^TRVL`LP\^VN\LJV\XTTTVFbVZZbbVRNZ`dZXZZj\VHb`D\ZXbbVTRbNPPdZZV\ZX\XZZZb\H^R^XZLXL^b\VJXPRj\ZdT`RVDLTLP\JXFL\VRXJfXR\ZHZXPT`JDVTPXP\R`VVLRLJfNTRNTXPNZPRNRVPFTV\RFNPdPTPZ\ZNXZNNBbTbTVNZLVXLjZ``V`V^XJ^`P\\RHXXL\TLVbXBRfZTbPDPV^TPHPFTTP^R^NjZTZTF\PNb\NFbZXZ\PXdRT\JbTXPTVRZbTXjVVNNNZRP`PFPJ@TX `\ PLL b Z N N ` P V N Z \ L V X ^ P \ d \ R Z X L R ^X F\^VZJLLJVRXVFRFPXXZTXJPZXVZ^PRLTNZX\PbFLVRPZV\PJRhPjRVPZdRVT\\LPRVbZLVVVTXT!d V^Z6T !J R!PH! Z"!!"!" V "P !##b#P%B"""X"#R##"L "J"^"b"J#X""!"L%d#N"L""@ !V#B""V"#T!L%$"R"Z"!X!\" T!! !JPN JZZV TL\H^ R VTRJLVRVbPT`XLRNRX`TdTVN^TJRTR\TVZTV`VRT\bFZbT`RVVVNTXXNVTXZV X ` ` V N T h P Z F T Z Z N \ T V V P Z ^ : \ R\b` RRZP^hVH\Z\FJVVZP\T\^JBV\RLdPZ`RVRTZRFZJVPNTP\^T^FhF^TfPZRbV`HZV@P^XJ\ZVZN`NVXjTNHjNXHThNXVXNR^JZXXPTVZXTTZVHbZDRNX`hDZ`Pf^X\`RZd\VBZbP``RLdV\\VPT\NJ^RFlLVdVP^VZVJZf`VV\X\Z`fRNZRZZ`\ZT``Z^bVZP```Zb\TbLNZLLX\\VNRNPTVV`HPfRXVb`\dV@V^Xb`VVPjVJRZXNNRV\Z\dRVV^ZTNLLRVN`TZbbFbFRH^XTX^dRZTfVfdLXbfXh^bNr^`XXT^\`J\V^XLN`VZV\dNPfV\nTT\\P^J`TfbhLTZTfV``^NVjfL^XF`b^LZNPZdTL\VNTZdJdZT`bXlXPRZTVLddV\RXJXbVZV`^^VXVPXTVNR\LPN^\^NZZ`LPZR@V`HTLVVNb\PZZNXTJLLVZHdZdVVJRV`PTZHJHVXPVP^P`LN\RP\ZTPhXPJRRNThTdH\VdVZVZZZP`PR\^TP\Z^Z\T`\ZPNPNRdZNXRL TVN TPfZ Z T X \ R D X \ d f b T P \ T \ ` X ^ f  \ X R T F `V RPJ XT^L^\VR^b\ZDZPP\HXLXXbRL`\bHb\PTdj^ZZXZZZ`ZPX^N^ZHXjXZJ\RHdjDLV`dN\ ^V!!`Z\!V V P!^! N"L N T"P$^!X"f!^"B!`!V!""N"V$!$#""$$P###F#^"X"^"R#%Z&`$$$`#T"Z#N#$!`$\#"$#% #"V" V#!V!!" ! N!ZP X T RPP V \V\VV JNdLh!Vh^XL^HZb^N^R\RTdZhNVV^RV\ZLX\^XLV`Z^VRhTXVJ^HRRVZ\XJbNXXJZfR`NZHP jN X ^ P R T V T V L R T ^ P P X R T d \ VV\ \ fVNVLHT\RJFPX\NFF\^bZhP^PZd\``VDbfPd\HZHf\TJPfPXN``XV\HTfdRH`bLbZVdLR`NLb\THZZ\VdNbXVZTFP@ZXR`Z\TRRZhRV\XZTbZhXRPZV`V\^\dZbRZbV`\NTj\ZVXTZj^ZlhZNRTNZ^PPVXLXVHVT\ZZXHfH\ZH`TbVX\NVX^XVXdR^PTXP`X\T`RZ`\\ZVHX\XTVNV\T^TJZPN`Vb\RbdVRVXJZ`XLb^VTPZRZ`^ffX\bTZV\\dRPT\`dXVT^4Z^RZVR>NPTZF\^`NZNV\rZf`X^Jjbb^dRTZXNb\ZR^Xd^b^NTL`\`^bJTX\nJZZ`ThR XRRPVd\ZVZZbX^XbR`bHFXZ^FbRbbZTN`XX^ZNX\XZBbZTV`VTRRZX\P`NZPVdZTXZBLN^^T\J`bJJVPbJRZV\RbTF^XJ\XJ^rLRPT^^RRZ\ZRPRPH@`NXDPVRBLZRNDfJVVXPZJbZ\R`NPZV^DV^ZbnV\XTVNLVV\PVRXVTVD^NHJN\^PPRT^b@ZVHPX^XNVX^V`XXjTb^T`Z^\XZfT^PXTPVTZPVX TPN d P R V P L ` J P V T T T T T \ N N H R ` RR j X `TV^dRZPZBRZ`TbVPXL`T\nRR\PHX\VfXZVV:JX@VXLPXPVTVTVNZJX\TVVRXL^X  T V X!dV!R`!FZ!"T!^#P# " \"V!"J#X!! !R#! P$J$!Z%P$J%N$"""J#^$R#V"!T%^##\%#R%$L#$#$%$V#%"$V"^""""^#!R!P"V" ! P !XV fPPL\ Z!!^"VZR VXZ PZ  RVLZNN^LTfNZNVJNVPXNRFH^HTHPbPVfPZR^NZXFRZ\R\PVTRZdB^Tdb^TPTZZbd^PJVb^\X N R P R ` b P V h d P N V h F L ^  T hX NV^ R`VRV^TXlTPLRTTNbH``NTR`\fT\^NN`b\`XTX`RRfTTNbJZVVbLZ^j^b`VR^V^PZNX\N^`\^P^PXPHZ\RPRRXTVNLZLNXdJZdTR\lT\^TVT^Td^XVV`VPdRb\>X`RTZPbXVPbP^\PbR\`RLRTbTb`RbT@THVTL\XRZTNV^ZX\RT\PTP^ZjHPXT^ZL^ZXV\TZfVJ`BZbVN\VXHZRLRN`P\L\fVDfP\VX\BL^\XPRZPbJRbZZXVNT^^`X`XTVNj^^JPb^ZT@RPD^RXNRZdRZRVR\lZ\`N^\lfV\XnVbZTbZZZXT^b\TP\ZP^ZRZRj`TRdPRX\JT`V`XfVXTdN`\hF\VZZLfZTX\LbRZXV`RRX\VPLRfZZJZLNTfL\XZXPVVJVRPZZZRNbPbXLfXZbT\XVTJX^N`XJ^ZXN`XLFXVVZR^\T`VJbZ`NRXHh^TbVP`JTfRZ`HZF\\NPNL``TTLRZVZT`PTTNRFJRLRRVVHHhhVJZP\`DZ\R\`^ZX`TdN`RXLhT\PTR\^XZ^TLP\Zbh^R RN h R V ^ V d b R ` \ l Z P Jd FL \ B X d T  XZZ`L NXPJ^^^FRVZTdJXNTRT^ZFPPL^FLJ^J^R`PNXXJRPN`hXBVL^V```LZPlTLPdT LV!^!^ !NP!N!X J"X!!T!  V X"\!F!N"l"Z"T##" F! !H#"R#\#T"`%$$$$$X"$N$Z$L!"$\#H$b#P#`##@$###%#P&T"#^"\#$\#L""V"H# N#!$!N b !Z" X!^" \P  f T J X!P PV" XP T!!!VNjdZRnPPHZDNRVNJ`nVFP\ZTRPTRX`R^H\TJbVZ^DNN^RTdXThRV^\NVTVXTPL\RP\V ^ X \ ^ V J b Z f V X Z N d X Z XZZXNRZRF\PDHP`ZTPNNPLNTRZZZPLfbXRZRFP^HRRPPLNfRf\PP^LTRbLLVN\PN,\^Rdd^h\XTdRXbd^`\PXZTVP`XT^TXXLZT^HbJTJ`VNRNTLdbPVT\bTV`f\PTL`PNFPRRX^ZVXVVfPVdZhZ`TRVZ`JVRX\lN\V\ZV`XTZ\bVZZZZV\XPb`PVTNXRVXZZ^D\V\^PZH^\hRT^jTXTZXHXZPH^\XT`PXNP`ZZ`T^TVXXNZdR^b\fj`T\XZPldjTX`^TbRXR`RHTZHVTTfRLXL`TFhdhVZXj`\\Zf^^\Z\^l`X\`Jfd`THP`dZ\XTddTXZfTXJlNTLJV`JLR^bTR^TT^PPNN^X\RLhTTbLL^VTXJ`PXZTTNJTZZPbbNTXFJTVVPXN\P^b\R\B^HTdNRZTd\ZHPP`RP\FR^HRJ\fHZH^XPNHPfVLP^V\VPZPHLVTRVRTR^V^XPbVJRNN\^VXTX^RRXfHbXZP^ZF`T^L\F\hH`DRT\L`fT^^H`b`NTRbRJ`bH^`bLVhLLf\ZVT^XX`XT`^ X` X F` ^ \ \X TX N Z P N \ D ^ V ` J b H L X ^ Z b ^ ^  T \  RT<TRZZJ\NVPbT`ZFNRV`b`^`X`ZV\VPT^TZZXXRRHTPPZFTRPXlNTb\J\RZXDXbRdJJZTLJXJT!R` P P! X! R! R \"Z" !F"! " R!$^%"^#R#X$f"#"F `$P!"@$d#T#T$$H$&#T#N$`#"\$P$%#%#R$V"%%H%"##<#b$#X%H%P$#%#N#Z$"f&P"##`!!!!Z!X!Z X NX` N# N V T H ^V FXV"!\!T V P! fBV"\LT^d XX<>VdZJ`H\PP^^`T\bTJ^ZVJV^VX\ND\^RXZ`^<R^`PdP\T\F^f\`PbPjXR^\XPJPRZV`\X\b B V \ T Z X P f T X b N P T R R ^  L N ZT LVRN LRR\PRJP^VRXdTTdTJ\`^ZNPXLVJ\PPHbZHXTPPVPRZLJ\JH^LTZVXN\RNLXFVJXNVPhNXV^VZ^FbL\jPT^RLHL\\LTVRdTZT\XJFNP^\ZNVTTPX\RdD\^^T\lVP^PPXRVXJVNXPL\hR>T\FT`N^bRNXhN^TVZT\VZ`FdVPXXTXZBV^ZZb^PVLRVVFdbPdHT^XXHPl`^RXLdTLP`XTZNh^\`^XNjPZXVX^`RVVTFZZPVTTh^fd^hXX`^VXflFjX`bbVTX\RVTRPVTfdZ\\hNbX^^^fd`Z`bX`f^`Tj^d\\RXBVVPdXL`dR^`dHZVPTPZ^hTd`XXNfPLXP^P\PTdRTDTTTTbNRPPlXVbXbTXT`^XVT\Z^^HZ\jXbZL\ZRj\\T`PRLbJ^PV^`XRXZ\TZZ^Z\bLXPZVX\TRX^PVRRrT\LP`TXHPhVTHTVLNZ^d^H`NZL^P\Z\J`RN`TbJNPTZb\`XbX`VVTP`PXZV\FPT\RNVZTJPV\Z\LZVPVZTbV^L^HZJRRVNH@\RP^`XbJX\LVR^RNPJbJ\`PZ\RT\\L`VNR \ L P \ V d V Z X H Z X T Z B V ` H P X P P T R T  P ^ V\`bRXRTRLDZTPV`JT^`RZ\VXLJfRbJV\JLXP\LNRV\T^LbRTZTXdT<\bVRNLLbNdX^L dLR\VF RZV\XRV^\!"f"" fN ^! !\!!J!T#"\#$%Z$%#>$$R#V#!"R$R$T&$#T#^$$T$%P%""P!"V"\##%$R$"#$#T%#%Z&Z#$T$#%P&#&$Z$#!\!###$P"P"X X#P!b !R T !\"!V !V N!j" !P! !V"Z T"XNL ! T VJ\T`jfhPRN\HhRVZLXbRZXXZ^X`ZXLX^dZ`VXXN^\^RjVN^ZFdVJZLZ`\`NV`  \ `` J N L\ V `T  H P X J @ b ` N J N < R\T\JTRN^Z\dXXRRZPfVJJFRRVXV\TTXXL`b\\TNZ\VR`^RTDX\TRR^\V\bbJ^XX\HZVPR`PXP`NdVTZX\ZVT`^ZXJXXfX`VPT\XVZJ^bZX^NbRZVX`JHdbRXRRRHTPZTPR^LV\Jd\Nd^dRdZRdVP\RPdVZVT\^DHhTT\XXj`JT`ZTV\X\FTfZfbZd\X\H`bhZRj\L\bH^dXVNPT\\dR`FV\bLh`V\dRZVXXN\LNdTV^NVZT\L\`TT^DhLXVZZ\XZfT`RbLDTTJ>hLLPTTJB\FV`Z^T^`fZXdZ`PXRPhZ`XJVhTXXT`hPRNTZfX^\jX^TbXXRVZT\ZD\\^^`ZRLbD`^FB\NbXX`bPH^RZ\ZVR^J\HNRJRDXRZRRV\TVLRTrL^ZZNZZXbRJXTNbdL^\RZbJR^VVP`RRTXT\VZZBH^fZFTVZ>LdTVP^XRZVNXbD`TTZZJZ\HLLXBTRlZJbZ^PJLXTRP^XLTLXFbH^TRRT>HHbXRXRPDf\VLTTXh\\TJL^VVNXLfR`XZLRRTRTXVVDnPTZVVL RVP PXd ` L < X T J \ N V b ` N Z ` ^ X Z ^ ` T`X\`HRbPRL^b^`^XNXFfR`dNVP\NN^R\PZfL\ZTPL\VLNZTNh>\Z!RVVV`X`\XZ^VXZNTVF h#J" J# \!B!^!J  P \" P$X!!j""P$#^#Z%%$V'^$$^#\%#N$Z!%X#\%"d#R%N%#T%R%\#X$Z"R# "P"X%#$&%$&P$&V%P$b&L%$R#b%J&#X%\%#N%#$$#X%!%d"Z!!"TT!X#^ !"Z! P"b!! J""!"!J!T RR RJ`V" X"TPLVR R ZXJ\ZVJXJ\\XPV\`ZX\PXHJPfT^RXF^DfRbJ`VZXP\HX^PXL^TFRTPPX^P^^LN ^  bV T T^ XV h V \ X V X d PR \ T X L hDTJZ^V^TTR\T\T^N`PNVZNT@`NRb`VVlHPXX\XV\XHdXjH`VXLXN^RPJXPZTHZHZbb\\hTN\ZNVVHfRZLX`NZbV`P`VX^HTDVV`PTZ\Rf^TH^JFdb\```T\VRfZZN\RTfNNXTV`^^L\`^VRTXHPX\ZT\NRXTNL\^TVV\^ZNR^fb^VT^T\bPNbZT^T`XbX\VXXJZ`^P^^\RZh\X\Z^ZL^`P@`TdXPXNZ\ZTdZXVhbbhTRXHLR\fVTRXZPT`VRR\XX^V\TPN\ZZThVb`XR\hj^VZhVVVfNbTldhvbR`TfPVbRh\XTV^b\VXNfpTTZTh\\b^V`T\ZrL\L\`NRPVlHXJZN^`hLdVd`ZVLXVJdXF^\VXp`TDRTX\^RBRFPfLVPZP^ZdTZPR\\RL^\Rb^ZVJLLLPFJdR^JfRR^VZJXVPVJXR^RZ^PRX6XPNFf\ZXV\B`NXX\PPH^NTDPP\L`NHPT\THHN^VV^fVRR\\\ZZR`fFbJ\ZXV`NFZ\^ZVH^V\dLT\RTZ\XTXVLXR\Rl^HRZT\VZHdVLZFLVVPNdT\ZVT R T \ b h ^ ` Z D ^ T P ^ \ X X ^ X V VX X Nd Z `VRTd^ HVXJ^hNPTPZZfV`RLZX\^Z\bVPZNXXZhN\\P^L\L`DJRNJbR! Z`f `TZ\TX^ZPd^^VV\!bTJ \ f\! T L!`!X!X L ^ R#`!^#$ ! !!!F$\#$\#T%##V%%^$L%X&\&##^$%R"V$X%Z##`$%#R$"#!^!!Z""$b%^$\#%#P'%'\'$$&#^$$$T#l#R#$%b#R#$!##T"^&N#N"!!T!F!Z! X! d#"T"P$R!!j$T"X!! H"!J H#X! NZ !! !TP"L T`\\\fXN\^PZT\VDN`PX\fV^PZ^ZZHZ`HXddNVJXd\\bNX^fHFZXNRXTRVZZd ^ R XH R B  P T V X b \ Z L J h b N \ \ R PR^NV:T\RR\r^LTbZRbZVPLRR\h\Vd\b^\lNRLZVVRN\ZFNjXPl^TXT\\RTXRXRF\`TVX^ZNP^RP^R`VH\ZP\\f^Z\d`RVdRV^TR<\VRZVf\TXXTV@XRVXZVLXHPPPhNVVZXZ\V\B\^N^V\LT`L`RXPTZTZ\TZD^D\NRX\^ZJVZVVTN^hRP\TRlNdLLRZ^^jRNVNPF\\VRXVTb`^X\ZR^Z`ZJ\fH^fb`PVXJf`RZZ^X\b\\V\TNXbZbRTTf\Z^d^fHPddNTRfZPNTT`JRPBR`dfXf^XbX`V^dhT`^bZ`XfVXRbR`L\N\P`VZZXP\VJNHTR`DP\^T`VZHbXRFXTTNRXbXRNN\\PPf\PbT\ZTZRbVZ^VR\JP\ZVTRZ^XV\\XRJN^LVZP`XfRPZN^^ZXPLFTXdPX^\RZPNRhJRXZ^\X\TVZX^Z`\NVXPPFHPRRXVR^VVX\\VPVfPTRPdLb\DJZZ\XTNd^X\VFRVPVNRVTTXX^\\PV^nZR\FTVTTX`XZhNbZJ\XXdV\ZZV^NRRZXXRT`X^`V H  b V L P L J Z R V P ^ ` X J ^ T ^ Z T  P TP bNXVRTPVXRR PdVFXPV^bTJnN^X^bJ\XZHLVd\ZHRJ`VbL^LJ`RZZdX\NVXb D !PZ`TXTVf T\VV^ZL Jb!L!J!\ !RL \ F! ""Z#Z%N%$ `#J%J#Z$"%$X%'%V'&%V%P&&Z$\$$V$%%P$#J$`$$H$J#X#Z$!D#%N#J%$#$X$%$\%T&^&%&T&$$V$V%%%R%$$$"L$$$^#!#L&#P! T!P!^#J!"b" V!\"!!^"J"$!"!P! ^ V"#N!N! RXNX^ZNXdTRVXZRNTZBh\bFR\ZbL`JPHZ\6TR@LNPVVf`TRRRbNZZNZL^L^PJXnZP`ZZT`fVZ\NZRVLb\XRVZTl@NXT\Z^XTPVRLBLTVVVVXJTTXN^\PZRTbXXT`X\L\JB\RN`L`\^JXNTRljZ\X\fTdZLZX^bLVR\b\XVTX^d`\fX`VJb`jZPJRZVZVXD^P^VfNTpFL`JP^TZ`LRTPRZXHVPTTJ^ZdX^bLfX`fTbHVlZRfLXb\^X\n\VZ``XR\L^TPVRbLZdX^ZX\D\^bTVPX^VjVPNRbPJbVTV`N\VV^P`X\NXHNbZL^JRT`TTLZVR\\LLbRTZ`TFR\\^NdT`VRXRNXbHXV`b\fT`VdVPTNb`DbTbPXPdPT\VbPXXbJV^ZP^F`Z`NNNTTXXP\RRVdZ`X^bZ\PPLbT^^bT^ZZRh\N^JV\R^X^T^\^`HTX\TZ`\NbPXTL\R``BJf\TfVP`dHjV  X ` \ R ^ T ^ H D f b \ T b  b\  V \ VdN\R`RlPF N\TH`ZLdJT^VP^RF`fP\bZJRfffXRTX`NZV\dJ`TTNd\TP\bZ^NVbNbVX!\ TTRVbBPTV^V`N h!T b X X!^ N !LZT : bP N"#V%`"L#X#B#X"R""R#""%N$#\&Z($%T'%\%$X#`"f#V!Z$\$$`%^$T$\$V%#`%`$##h##V#R'$^&'%N'%Z%%\&H(^%$&%P#"$"$X"T##X'T"2#H$V""\#!# !\""! N#"`""H$"8#!T!V#T$%"!J"!\"V"!^" X!X! d"! ! \!TT^^N!P "^!L#` RV V! PHZ`TTT\NX J XXVLTXV`\XZ P N ` \ ` ^XV\VR`RPP`NhVXRF\XXLdJZl\ND^T`XdJZ\RT`PV LRTNV`ZTJ\V T F V ` \ V d P ` \ V P H L @ Z X ^ V \ Z \VPfTV`Z\Jjb^F\\RRVRV^RVVVZRXTZTTPZdZRJJPZh\XP`XTZXVZLVX\PHZNXVNbV`^PVXdFdZR^\RL\\@XLfT\T^`PT^V^N\ZjRLR^\Tbb^RRR^^VTbZDTPZZRPZbTZV^VhVXX\JP`VLLf^RdX^NVfHT`TfTP`LXTV\RX^^J\TPVTXTJNTV`XPbJV`Flbb^^ZZXB\`N^ZNLZR^LPVV^P`\ZR\f^P`R`XXVT\d\^b`XVVX^ZNXbZR\TX\VV`ZdBNjVH^P``\`ZbXdhPfXf\\\ZjXRNdTXVbhRXL\\bJ\^TPTH^\^:P`Z`XFZTXTVbPV^RTZ^JZP^TVJb`dfVb>jV\XX^V^VTVX\VVXn`\`V\Z`X\BJVLFfRVTJLbHfNX:ZbVRVP`XX``V^^XlVfVVJ`LNXVdLpLZ^NXLT\bd\RTL^PPTZlVXVbT`Z^V^@d^XR`bjRfTTV^^Z^ZRX\RV^NdPZVTTPPZPVXHJZZNZNb\R`V@LRXZb\ZbNLRTZVJFbHR\PXLXZPZVNZZTXXVRX  N P D F \ R T T N N f J  XRZL`Tp \ `ZbNVj^Nb\THXZ`ZZVT`XTBNRN\ZP`TRTPT\bZ\TdXB^X\TTTJR`P`dTNNLPXR Hb bL R`HR`dRVNX\ZV\^T  "!Z !` R L X `> ZB^ R!"P#!\$"$"%#%f$J#H#b#H#$&$P%%$H##"#"d#P##$%#$T$8$%B$%"j$L$#$%h&^'(L'%L'&>%d&$^%$J&$Z$##R!"V#`"V##j" !$`#R!! X"RZ !N!T!"T"d$R$"f"#\"N!X"d$T"B"V!R"! "J"" ^"N$#L!"D! ^ ZZVV H! Z L!d!P !" \!PL!X bPR^T T TfjZJVRXX^!X  NRN  \"Z! R\V\ZRTZdXPXV^^Z`TT^Rb\\\VlTNZdThLVXZ\RNTVX^Nf<hX X b V T R D X ` V R f H Z T H ^ ^ ` D  ^^PdVVR^V`VNPZXbPP\^VbJVZ^VRZbBbdNZfTL^VLVX`R`ZhTLT\NZRNHZXTXRVJR^b^hL^fTZRZZZ\^JTZVNRRPZV8XPFZZRRHNFLVdT^NdV\PLXVR\VL^hR\jTVVHRNjZXZTfLbNL\^RJTH\PVD^TTVPRNNX\`\RJ\ZXT\PTXT``RZZ`TR\ZJZZ\NTVbZRLZNT^ZR\^XZ^TTRlbld^^^VLXZbZ`ZHRZVZPT^RVXZR^fdXZXhbTPX`bP4LRZ\TLPP:TXRZbTR^`hd`jfTbZZXlbJR`@PRf\VL\X``TTTT`NV\nVZNb`HZZPTT`Tl\PLXdX\X\\`R`^LT\LVXPR^V^NRdJLPTRRXJPT^RnNTNV`ZdTRXVXXf``L`^LXZ\TZ\^PB\^^XPT`^T^VbfTZ^XPXVX\V\RPNR\ThPZZZPZJZZZdP^VTRT\LZ`VV^NbZVVXR`RZXN\F\X^TRh\P`\ZRTXR\<TZXZJZZXRX^ZTZThVPTXJNTfTRjTFb`HJPZTV\TPT ^N f R h V P j V J ` ` X V T f f P D Zf  ZZVJbRT`N^^^PRPTTBPdVRb\R\pNVZ^VbJhPLPZHbRLR\TVjT^^\Z Z L!RZ `N N#R BdT^R `JTH N`TL LV^! \ Z J!ZZZ J "b Z!!T P Z H"^#"R#%f#V#J""P#R##$X$H#h#V%$Z%b'P&%`$L#$<$f"#P"##$###N$$^$#$%###%b%&R(&T(^(&`&''&##&%%%X#"$V"^"h$T#Z%\#^#F$#" RZ"T#"""!!""!#^!"""d%P!b!h!"P""R# \!"!!\" P!!R V^TV !^!!V! V "\"T! ZR V V X JR"^NdVXTX ZT @X P!f!N" \"L" !b L!Z"R H fbPX!TTZH\N>`X^\RND\\XRFNHTR^ZH`RXJJ`V\VTTXP\PTX^RRf`R X H Jd V X \ F T N Z \ \ V V T Z N J X ^F ^T^ZJZXPJTRVLPV\TRT\FR^bLVT^J^XLVVXTZ\^FZVH\^NHJR\L`ZZRPPZN^N`P^Z\^LZfTXTVf\RT^\JZNRVXj^VPdF\XhF\JTTPTPjTXbN\hbH`fRZ\^V``@X\f^PV\bT^L``R\VT`X^ZXZ\b^`XPVXL\hLbHdb\RdVZV\NX\HL`NNZ\TX\Xf`LTZZ\TZZV\dX\\XVNV^bN\ZL`ZL`JPVZPV<PNXd`\fXXX\bPTXDTVZNbN^TPXVZXLNNd\XhT^VdbZjTn`^bRZb^jLPR\JTZPb\Xb^\XNNRjTVZTVLRVXPXbVVRT\Z^V^TRNNLV@JZVFJZTRTRTRZNV<`\\RP^JfXZT>PTNRXXX`@TbpTNjVVbbJb\RTVV^^\VRXVZHZPddV\RV^NXNV\N\`JfTZF^HXdXZPLZPJ\VF\VZTZPLRNNLT`NNV`R\N\NDNR`DRTZVJXfTT\PjLNXRNVTR^ZXLXRfRPJVLJd`PVZNP``RbZ\\VVF\`VP^f`XVX\b^R\ < ` ^ H Z d V f N X Z d  F N ` \N\PXV TPXL^L^bXXRPVF`FP`PRZXZ`^\VTPTP\XT d^LZdXT``NXL^H\TFPZLL!JZ` !Z ^ ! \!P!BPbXNLDXTRNXVNZ#N!\!`!"T ! Z !L P"V P!V"!ZT `"V!d!"b##^!"h#$\"V#%$`$Z#%"$$N'T%'\%T$N#$^%"Z%D%d"$H#$"V&#f(&H&&$P&D#$N$^'$%'%&\&^%'$$Z$$P$H"R'##"!!L##L&&$"!\" P T L!T"P""" Z#!!^!V""J#!Z"""L!d!P"X"T#"X#"F#X"f" ! ^"T V N!b!!!T$N"\!P"b!T"V"Z!P !^ X" f!N#V!Z dNH  \RR^R VRXX hL^F!T"P J#Z !F"X!b!X"T" T" !T"PX VH Z J ZVfR\NVX\^VVTLdX`ZRVTDP\RRXNPXTPXRHdTVPX`\RJX F R P T \ V f J R L T H ^ b N P D b P D ^ b ^ ^LPZVPL\^PZVJbhRPXRVThNZ^R\bL^VTRXTVPF^R\ZX^HRdXT\X`VT`TTN\NT^bTH^\`ZdP`BfT\TP\\HTPFHTXTTRNHT\FVVbVRNRVfJVXX^\XLNfX^L\\DV`NL^N`\R\bb^P\HXZZHLbVPV^NR\ZfJ:ZVJ\TXdBZXRfVfV&PPXDR\^ZV^PXVVTLZ\V\XfXRLX\NThXN\VTVR\hJbV`dNdZVp^RXZTd\n`^VXR``B^JHZbb\N\P\`VJNbTNZRHXV\lZh\hZ^b`^V^^\XPbbVZ^bd^Vb^``ZbXD``RZh`XVXPXJVF^NP`N\\\`PPf\Z^^ZXhNNVLZX^HNJVXXT`\^P`TTfXZ\VTXdJHjTXT^TXVJfZfZT`N`^T\PVZJP`RTddV\TRRPdTTXTZ^^J`b^TXDZNRH^X^LZNN`PRh\NLZTJbN`^fLHRXVTV^`XZV`LVHXVVVPbPHN^XTbTLdd`XTZV\RXTVL^\<Xd\H`JdRRZZ^VBhP\\X`T\\`nJ^Vb^Z`@RL\NVT`TXJZZ^ T b  R ^ X R N T J D Z b ^ j V \ V Z P PPP`ZRPPT`Zd\ZTP`bXV^XR^XH^R^^N^L`Z\`PbTRNPRNXXXfPNVX\X``LJ`RVZHPXLTL!d!B# `N \RRJd^@T^N Z !R!!NP!"!N"#V"X\X!V!P"JV P !L!!R""$%#X%%$X$$N$N%F&J&#%Z&'P%$b%&#D(%R#"R$$^#Z%$X$$^$$%Z$$'&#X$\%&%%&\&&%N&\'&$R$###Z$ R#V#T"X$Z#$T$R#!R!b"!`#! !Z!!V! X ^#X"^$R!#d$V#`%D"Z"b"! Z"J!!$!$"Z#!X! R F#R R h!J P"H""!!#""V!" `!J!P!b! Z"\ T RJN` \!V" T"Z J"X"B" \RT #!X"X \!R"F" `#!!^ X ^ R!N!!!" F! b!\#X!^ R`^XbXDVTTRLJ`JTLbD^HRXL`lT`RTV^bTfJRL V VT R N L Z ^ N \ N T  XXNN`fNZT\JZVTdZNbJbZX\^`dR`TRVXX>VV^VN^PRPZ\XbZZZ^b\TNVPR\PJZF^\LbdZRJRTPLbDRXTNLdXV`PTPRJ\RRRX^RVPTXRZRRLRbX\VRP^d\h^ZTTRZJZJ^X\TVR>XVNPbX`bRfL^RTh\`\Xf^XXXdXZ\`Pbbd\d\T^L`bbR`LXVfV^^^b\V`\LRZfNdNV`ZZZRbd\^`TXXL^`Z\bRZ\Vb^h^ZZT^fL^dVbZVL`VXXNVVTX\PXlZ\^X`L\N\`^`^bDf`ZV`RRX^dfXX\XTRVV`TJPPZ\N^T`LPNV^Rf^VZXTP\^VTTRR`PZX`\bXVZH`dVNLFb`VPVVfRVRJNf@VXbTNVbV\J^TN\LV`\N\\`RT^VZF^b@`LTXVV^>XLTdTXHVT\VL^^NbbTNVZJZZBNPJ`V\^PZLPNLZFTXbT8N\ZTZRV^dJZXR\TPXXVP^RXdZHLNZBZhHPNX`RVXXjRVRPNTNFjTTTTLNNPRR\^RPT PZdV V R R Z X R T N ` \ ^ P N J ZX^^LPdFZ`ZN^XXPRH^VV`^PpNPVbTVT^jZPVZ\T\`\R\P`^JTJ`N XV!X ^"` R "T!^ V! V!ZVR^TX^ dTX X^R b! V d!j!""! Z F" !V!R#P!N Z"T"! !$L"!!"T"V%&$X&$R#$N$N&&L&T&N&&%$\%#$$`#T$P$Z$T#:$%X$N'$%R"&P#%Z'&`%L%$j$H'`%T&'P&H&b%^%N&R$T"!#P#J#^#X!"B&!#R$$R"!H \ "!!P" ^!T"R"d"P!"L ^!V""""B!"V%Z#b"`$"L"T#P!!H!!!X"P!!T!T!!>! R#R"L"fX"V!"\!#R#V#"d" B!J!! L! \!! " R N"f" V"Z #X F P!!L"^ P!P!^ L!N!Z^!\ !V #!H"$H#^"!L$X!" L Z"X" H $" !"X""!J"N"NR^FTX\ !T^N8`ZV`VDXVZRLV`\ZNVZVXNN T Z V V V \ N N R T ` N @`^ZBNXRLZ^Rb`XTPPXTvVPLZXJ\LLTDRTbHRdXXRPXXPNTLbBNXZdJJXBBbNV\LP:dZNL`RR@HHXP\LZVZ^jTP^XbdfVdfL\bVdPZZhZZV^TPFRb`H`^^bHdNRNP\VTTbXZTZ`NfbFRZLHTNTNLhRdT\XXPTjRNTVVXNNV`RR`ZfNbLNVbP\\^TXJPTJPRVZ^n\X`^bhRPXTfX^V`PT`VVLPbRdRPfRVVRTVZbTTTN@`ZZPRHb`NH^Rb^hZhZ^Z^^ZZ^ZVTNbTN``^T^dbf^^Xl\V\\`VXP`T\N^VJd\V^bV^PXL`ZXR\LP`^dDJRNhX`TbVhVTlZRbVXN^ZZJTZXV^V^`RZ`JTR\ZPL^TTXNdVTN`V^fPZTRTPRTZ\^V^XjbbTLLJ\bRTVJTNPFTfX`\jZ`T^6dLRPfRLNZRX\`VXTJTLTb\f^VNTRTBb^XZXZ\dPVTZRP`L`T\ZTPdXPZZdX`X`\`VRV`\TP\\JNZTXjV\ZVF^T`\VXX\`^R VR Z Z J V p P ` V R T H  L R``JRNHHZXJdJV`TXPTdRfRV\BXTXPPf^^XRVR2ZFhhPd^@PRPPPPZRRVdTX!j!XXLZ!^ JR"!! X T \!P"!  V`VP ^JZ R\TNV^" VZP ^ F"P "! \ !\ \!"!"#!!\"^ \#P"J$V" V#P"Z$%R%#&V'Z$##%&b($%X%P&H%V$\#N#\%%L$$V"^#$%%T'V%b"T#%P&&R%$#$$$$P%f'(J(&J&N&Z%Z#$h$V"^#"V%Z$P&#\#&f#V" T! Z! ^!!X!""\##\"Z"^`!N#\"%Z#`#$X$T$Z%$\!^"!!$V"^$%#"R"\"N#"^!n!H!d!! T !!!R$N#b""!V!\#!"V"V#"X!!" Z P R"X"L!"\# !Z!T!!!R L!H d#P"" R DZ !!\"$b N!!"\#R$h##P"V#"!^!! \! !!b"P"X###"J"""^ !X L `RNX\ T \ZRL\R\NRT^XTdVLbZ8`\Z^J\L\VVb8T\RXN f \ H X \V d d ^ T X V b ^ T ZRXRXHXTZb\NFVZV\RT\R^ZXT^dLVTTXfVZfPZZ\LPbHLf^X^RL`ZVRJVLRZXP\X\XTVR\\ZbJLZXPVZXXR`RRd`ZLXNrZbbhRXT\VTjP^`\PZD\\J`HZXRJZRZLbRb^THVV\VRVdTN`ZTTT`^^LN^HVVRX\`\hdN:^V\^^ZRPZX^P``PXTVb^\H>ddTJhRZT`\^V`TjXbP^ZVPb\RXX`RZNX\PVd\`J\Rh^HJ\ZdRTNXZTXZNXX\\TPBL`RRRNHXVZ`Td`dNTRVXXZ\d^fRb\^ZPdZbXNRTF^X^PbDX@bNL`n^`V\\bV\VR\NH\PX^LhPdD\dPTfVfbPTRXLLJJRd\`bXbP\VP\XPJTLTLjJVVfJHVN\RH\XLZXXVZXTXTRNVNZPdTFVFZPNTF`V`XRhTNVX\NZB^PZXPTX\TRHRDR`NdJHLPP`ZXXRJTTTNT\V`XZVFb^VTNL\H\PrTRTHZRLVTZVRVXbZ\dNVVZZZVPTT^FJPTTVPNRNVfLTN\L b T ` J P V ` T j L J P P R XNd\bX`PZZXV^jZT`\RdTTTTbL^XbXZTT^X^ZTbRXNTZRXTPTVTRbXZHDHT\\ L R fR!!""!! R N ^VT^L < V!P ^RT T d ZVZX T!b V"!!N#!#` `#N!#T!!d T"N"f%!"R!"#V ! !V"\!!!#$%%%J&%h'Z'&'b&N&X$d$`#V"V%Z#"^$%l$L$d##%"\$$''%%%$#V$#$%\&'%P)&&'\'V''V#$V"#"V$J$V%l$^""B$"V#F#!N!! J"#!V""L!T#P$f# T%R%V$L%#T$L%T"#"P##$#H$$#L$N$R%!$b#"Z$"!!"X#Z#X!"b !X!""T#T$#"$ V#"!" T#T$N"#@" Z ! Z"!!!b!`#"d"N#"f"#!" V!f#X^!"Z !"^!R"b#Z#"$X%!P&P#V$#$%V !!N$R#\#"\$V#`%F!$"V#!"X TZ^ PV TFNNZPLVPP^PVNNVLV^\P^HTH^RNVNT\JDb\ f X H T R PT Z ^ J N Z Z > XZ`ZXj^TNZ\LJT\XPTVPJh\RV`BL\JNL\VTPVTVX^^VdN\ZHXNZLRHPXNNVXTLP\N\TT`VJTfZ^>VFR`X\T\ZPXfVPV\dLNPRT`LLN`XZZ\`XPVbJ\PJV^ZTVTZXTZF\RdZVZ\>PJNNdNRZPVZ^LLVXXTRTVVT\b\XX\TX^dR\PVX\`bhdN^R^jNPZbf<vN\^XHV`R\VVL\ZV`NbVXNZfZ\PL\RXN^VbRXR^\\Z\^dfP`XPfT^\^nh`dP^NffXZTZfTXd`ZXb`TfZZRTX\`RdRP\hPXdZNXP`RVXRRL\PdVb`FL^Tb^V\ZTVFPVTZLPTF`RPPNPbPVX`R^bX`ZRX`VhbJVVPR<d`X`^`^XLPXP\NBbZTRVVRN\PRRPLdNNDTXbTVX\<^LPVV\RRPB\RNNXbTX^\RVLV`ZVXT\RL`ZTLbL\JRNV\TVZZPNT\ZJ`T\VVT\dZR\VND@P^T`\ZL  ^ T N P F N ` @ `bP L Z NN b \ RXd`TNTTb>@ZR^P\h^XTV\THdTZX\Z\\PbTZJLNLPX^\XfTJXR\^VRJNVT\fTZZ\^VTLTXRJZ ^ T f R"! !T" X!J \ VVVXV N T!^XfV!\ d!f^ !l"$#"` Z!L!^!!d""V!!#!! !j!X"` ""#X"!P#Z"#%$%Z''%%\$`%$&B%%T$$#$L"N%%`%V$%%%X##$$$R$%&#b%'b#$L#L%#L%V&D(P'X&'%V%&V$#X"R% V"#^##D$`#T!d"V" V""P!! J ^V!"!$%!"P"Z%f%V(T&R%X#!""^#b#$#"h$#V%%`#R$b$&X$`#L#^"$j!Z ^"#J"X#$!V#"#P$$Z#"!R"N"!f#T#"N!!! !N"!%""N!^!"!\$Z$$Z#b$"l$$$X#!^#P"N!""Z"X"L%^%#%$%%#$R$N##$P#%##$X%N%%%Z%@&##R#T$!X##!T\X Z"R!` R"Tf HZTZZV\\b\\VdNfBH`R8Z\\^XX`L^XPRZLRRRTX^ H   T ZT@ T V d P P XRZZPV`XLbXJRZVV`JPf\VTHDP\VPfT^NZhL^<TbLP^VZRFPnR\H^VbXT^RXNl\TVVBVXZZNHRhF`lL`^PjVPNX^VNR`ZVZTRPVZXZXXZLfXPV^ZNX\PNHZ\\\jjR\^VDdZRPZbZ`^PdP`TP^XTFXPV`RNXTXN\\\\\\XXdNZPRZfZZVXZX`XbTfd\NXP\XZZfdXX\\^Jb\ZRTTRZlNPTNVLNXJhLNV^fVbZXfZ\\bXd\nTL\RHV`bNTNlXdZJhPZNdXTHNbTTVXVNVbRJVTbTdRVTJVbXfXFRNfPRVXTXX\DXZN\NTT@`Z`ZVTXjR^VbfX\ZNf\\HNTTTZh`4XT`TRb\ZNJNTXbPXRTdTPV^JZPbLZLD^ZTNZPbPNhLR`RTVJLDZPRXbRRHZ`XXZXZXTLH`RVNZPXbF^RX^R^VJX<^DXNPBNTJXd\`R`VXTRXPT\DB^JRNXN`XPPPTFXXTXRTRLP\RPLZTT^Tb^`bZbdNVVTT@ V R P b ^ T X R R ^ X b P VL Z ZPb`TNTHbRbNXbJRdPX`XXL`RZVTPPXN^dRFZ\V\X`\HZLTPZPZTVP ZPd\B\TR`P! N""J Z !R H Z!X `#! ^ JT\ Z! T X`Nd XV!R"N "##L%X#! L " J$V"L P D T"N!H"V""!!"R!!V"#"$L%#`&$P&R($R&$$#$L%#Z%"##b##$\$B&$$#L%$R%&%^&V&P%&R'J%\&N&$N%%'j)L&L)(\)L&J%\#T$P$$"J%X%\$L%R#Z#R"R" T `L!!\"" !!T!##`"^"#X$&$b%R#`$"X"!$"#$%#P$^$#d&H%h%J%P##P$b""""R""^%%&X$R%R#H%$""Z"## !V!f""!@! ^!Z!X##V$#R""#!"V"$V$"T#P%d%Z%^#T#T##"F"L%\%#X%$X%Z&$$&'b##L$h#H"%T$$Z%%%D&%T(\%N&b$H%$L" b!J P!!T#""L!b!X H ` X\THX^`TPP\@XR\JT\NNZ^HNZbNXXZ^NNHP^ bN RbZ ^TJPT d N V R ` b V ^ RZ`NTbB^XDL^VJZRVH`ZXR`\V\^XNJTZhHZT\XTPJH\DZRPVRPXL\\VXNRTHPP^B\ZFZbZZP^fjVN^\\XZZXL^^PXJjN^`ZZ\`VZVHTP`\TXRVPXVZX^bLV^TZ\PbTb^`DJPRbX^R\\VfJTTTZZVLXVd@`fZ\LNlP\\TXHNfVTHd``HNZhX\\\RNZZT`V\bTX`VtP\^LZLXX`V`RZd\\VRRb`TFXVPTTDbPTNnXXJ\bbhdf`fbXXbb`dNVbZRX`XP`XpPjXZXVTdZVlX`V`PhXdF\`ZX^ZbdFV\^XdVZZb^PVdZZZP^^XZVPPN\T`RTLRX``ZN\ZZZZV\hhPH\\PbTTbRXVTRPV`TV\PXVdRRfFdRZdZPLfHVPXVPTVTXT\^Pf\ZTV\PTXNV`RHR^TT^RNVJPdZZFPb@X^`N\FNlVLZP`ZBdHP`\^FZVT^TZRV^XHdXPhND^lVL\RdJZRZXXPXThP Z^bL b J J X J ^ T T \ Z HZPVVjLN^bZ`Z^^ZfLZXRNVd^Z`ZRRVdd\X`Z`PF^TTfPLTRVVXT`bV\ZT`PVV ^TV\R^Z:DZ^^T !L!^" R L!V!Z RR PR \ `!R H!\XPLd P` "!V X!R ! j!`#V%$" b!!!V"X#P"T \!N!X#\!""$"R!Z$#%$%%b%$H&$#$R$T&%J&#!X"L#^#%$V#R%R$&&%P(&"$b%P'V'%T%R$'b%\'\&&f%&&^%&R'^&Z'(&(&T&b%Z$#H#R#Z$#### !V!RR!X!!"!d!X#Z#"!B!#b"%X$X&#$\#T$`"##!V"b"##$\&^$Z$#\!Z"""$H(d#"#Z"N#""T%#%$R%F&#T#d##N##"#!D V! !X#"!!"T"L%"h"P#X"###X'#R%%$>%^%X%$P%$X&X%X$^$R$^%d'$$%X$$P&$$d&V$$B&T%\$F'X%&'\&X(H'^'N'\$T%V$"R R!Z !"!N$^#"X"V" N ZPbbL^TRdTLNPP8N\`RN`X\XT\N`ZN`TXV^X\`X RVZ^VVXH T X ^ T \T LRb\RRVX^PZTZRZVTPZ\`BP\RX\VXLTZ\TVZbJZ\Z^X\XVNJP`LP^\RNLL\ZTH\P`R\FVTP\Z\XZ``TX^bVV.`RXN^RPNZRV^V`V^^^^`Nd^NLZTb^L\LR\^^j\XV^bXJZTZbJLj^VRdZ^Z8fVVN\TH^XP`^^PVPNFVdPRL`^\RPXZZ^\hVRTdb``LfFbVXZPXZVNZ\HfZZTl\NhVN\X^VdRdRVXVR`Rfb^V\Vb\LdT^^^VVXTH`Vb\V`\\VXXDT\bR`V\ZT`^\bbZ\fl^``hbTfjbXNb^\fRT`VjVdbbXRNTT\JXZRHZRVRh^\\\ZZVN\NXZ`D^dJ^XVbbLTPDZVTZN\\Z^VRVV\F\PXN`VT\NLhNB^HXT^TTLJdVXdDTPZB\LH^VZbLV\NT^VZTRTVb`RXV^NZTPhbZRXV\ZVNV\PTVbZNRT`NTNNV\lbZRH\VJTT:dJPVPZHbTdLVRbhbXZZRR^RNLJBhRN^XRXLZNLV\HXZJ^T` f\ D   P T ` R R J V P T V V R Z RZRB D^VP\FPLVbN`XJ^\ZZVLN\VPdTVXTbJT\^ZTPP\PVbRHXN^TdRV \ RdP^>X XLRVL ` T!H \ d P"T `! V R T VN!X"RXVT PHXdRXb!X J"!T "`#L$P#$"#N!P!!!X#`#D!"J"##V"N#b""R$"h$%&&H%$$$$P%$$$T$T#"#P$V"#N#R"$`$#$&L&$&$#T%F$b&#$Z%\#`%'&'V&#%$P%&N&%&T&%%R'b%P$J"#"R#"H"#J#N!T"b " "V R"D "\!^!!#!!"V##\$#$^&L%X"b$#h!d#"L#%%$J$%X"$#Z#T#P#X$L#\#$$R$"V"R$N$\#%N'%X&b$%&"""P#\$#T T! `""`"P$"V$Z%$L#R&R$R&X(X&'^%T'R%%%X$N'$N)R%T%%&%V&h'%&V&#"V$`&P&$&T%#&%Z%\&`'''R'`&\'&&T$T$T!N!R"Z"V#!N%!##Z%%"! !Z LTZ^X^X R`RT^TPDF^lV\RJ^NZ`^PRVR\ZV^J P LV X ^ X b d F \ T d X LZNVNJT^VXV\P^NZVLlbXZ^ZRPdHXVRP\^P\^JNRZVLfJ\<\RZdRLTVTJXZH`PLVHXZ^Nb^TZ`ZT\\PZVR`P`L^PX`VT^\`VVdP\RRHZJVZ^fX^ZTZZ^LbTXVZdLbNHPRNPPRNT`XVLXNXZZTldPb^VTLb\JbP^lVjZN`X^NTPZ``J\`XXZVT^bXZTNXZVRXHdRRNTTPZVfdTZdTZPZX^TZXNbR\dXTdR^Xf^\f\RN\d\JTN\^P\JVH\Z\fX^Z`bXX\XTLdd`ZZb^`^ZLZTb`\ZXbdThV^Z\fbbVVTZZXVdZXd^\dPZP`^VdbdVR`NZ^jVLfbTVXVRTXXV^<ZZLbNZ^VHTVXVfJdTdP\\LZT`P`RVdV\X\ZbdVTfZT`f`Z^RL>LRVRVRRFbV``PT\RVZRRNd`TN`Tn\P^Nd^R\ZP^bL\Z``RNZZRJB\TNNfV^`VTX`\XPNVZb`RXNVX\T\b\V^`\ZV``\HT\^L^LNBTZd^^^PbHVPPT^Xb V P \ N Z L ^ b P R \ T\ R  R`Lb^ZJVNTP\XRR\JVPXfRRXN`XZZPhX\VR\N`\TdN^\bV^fRTZbXXfZPN!D!JV VL` R ZT BP Z\ P V" L\Z!X""d P XZZ!N\XX\ TP Z N""H!\#P# $!J$"!^ "VN#^"!N" !X#F"N"^##B!T"F$"$%N%V'%#"Z$#^$#&#L$"`&#^"d'F#$J$Z#$$$X&Z%%$#'&b'&Z&%X%V%&&R&V'&$Z%Z%'P'R'Z(&Z&\'X'%#\#N$L#d"`#!#d"!! T!R" P"h "!X!!P"Z!##X#`%$#%X$^"!!N# "##$$%#$V#F%"V!""#&#T#"##&%T$&n'%b%%##`#T$#^$#Z"! "\"X"#T#Z%"\&^%F$^$$`%^%T'%V&N%^&&%`#N%^$D%\%$b%`'`%P'R&T%&L&&#$V$T#`$P%^&P(&Z&Z&'T'(R(+'(P&&P(&%`#""X"V"#Z"%T$T%&H&J%\$!! \VNTVZV V Z ZXRTVTPVT\TPZTNT`Rb`JThZLH\^\J\ZZHN VPR T ` P \ T X N J RPVHZ^Tl^DX`HX< `T R bNXhZRZFRfPVl^dXNbTPPNPZZVJP^HLZZXFVpNTXV^TZ\XR^Z^LNXXb^\XLNTXXXddRTXXZ\NZVFJ^LNN`L^VTbVjBPX\TdRX^RT^ZjFVPXZ`@dPN\PZLXdVPZ\N\R\VLbVLZf^RPZZ^`T^`ZT\XL\dT\Z^^PTTZ^NXFNVZ\^LNZ\T\ZN\`ZTV^XjhNlXb\ZlRddHX\`dTdF`\d`XbRLP\XT^TRj^LZVZ`^NfRnPVbPbVdRhZ\NRTL\`L`XfZP^XTfdr`^XV`\d\PjRbb\JLfH\VbNPNDZTbRR^dNZXfd^fV\RZZV\XXHVVZ^RLZ^X\\\JVNJT`^hXXXRhB`Vd\JRFJZf`PJ@XTNTXJX@XZHHX`PdHV\^^ZNTJTFZ^\R\FPHRXTNbHdJ^JLP\`LRbX`PRZTV^\\X^XFdVXXPF\RZRPXPL\ZLXVLVXX^ZPT`ZR\PRHJRTNRPLXVR`XT Tf @ Z d V ^ R ` P X b T P Z \ZZ\TJ\VZTRN\@FNJZBRVHTZ@RTPVVRXZTdVTT^VPPZ`^RTNTT`^ZRH\NFTXZ HR!^ J^XH R` V!!B"b X\HR !> \ NZXF!NX R Z \DNfX !T! dT" Z!V!P!R b!"^#N"P" ^!!Z!Z%"X"H#^!B!`" \!h"d#P# #"&`%V%%%h$J#$$L%Z%#V#$#"V#N"Z$T$$d%%$X$#$b$N$%L%L$%`%f&^($&)('L*P''Z$$%&&L(\(T'L&&$$T&P"!L$H#""`#L"!"! ` ^"T !\"# #Z L \""""#$T#$V#$#" !L"!P$#L&&#$P%Z$#""""V#^%L%d"T"T!#d#N%%%H&`%^$V%%P$X%"$b$%#P!##!\$`"\#L!^""$&$Z&N%&f%'&%V&%'^%$`$&^$N'\&X&V('R('^)%N'\%N%%&&Z&B'T&Z%%&(V&'P((V(\*'&&V%J&^"$$T###$$&%b$V%%"J%T"" P! XVZf Z\! V !D"! ZX!V^TTR^RTJRJZTJXfbPXZL\RRZLFT`HHdb ZNd ^ R > Z P ` RR^XX^TFbPZPRdRR`X`\TdF`BRN`\D`VV^TDfZLRZPb^NT^PXDHVXXXRVRX^TZH`TXLVLRXfBVJ`fXXH`XPVPTVT`XPN`NT\bN`RXZNTVZ\^bVXPZPRX``V`XRPZZ`P^ZTPPRRJ\^XRdXbLPb\\VfRX\d^TfTXFX^TPXX\ZTZbnLfVXfbVLXdRVRRXNX^Z^PPh@PR\N`ZbZNVTP^`XZRd\XfVZTbR`TXZ^Zb\^T`XTTh^n\ZD^T^TbTTRZX\dVhF`dTlV^lbj^ZP`F`dRXdD\bP\`TLLZbTVTj^HPd^V`\VV^VL<>^RRVZRT`FPRVXh^VRZZTZNZ^\BL^^PV^JPZ`\X^TVRNZJF`\Pj^TdRhRJ\VJVJVX^VVbTVdfN`T^V\ZJXHHTdNTNRZP\\VfPXLN\NL^PZ`\tXbLH^\^TZ^HFdTVTLVPRZXHfZZZX P X T ` P \ R Z T ^ b ^ X P L T L PL TXR LT^TLZPVXZP`ZLZPNbNPdF\nTLT`^^:XZTfTTRVTR^\bZ`TTJ\d `V`!XT 6 Z !"b!! X! ! J""!!T ZXdN X" J\\ P!X P`! !R!X" #T!T!F N"Z` X"R R!"F#"N!T"""B !d!X!! @#\ "N$$d%L%$F%$X$V##J%&`%Z$#"Z"N#N$L'%&Z%#^$$$$T$$%T%&$&&L)^('\&)Z'X'R%$\%$$Z&%L&f('N&P%#T$#P#Z#Z"P"\$##!!!P"!"V!T"N!` ^! T !\!"N%$Z"Z% #"R!"^"!\!#$"X##"P#""L&X$%^$L%#@$""$F#N$"#R$H%%%`$@$Z&$%##^&#N#J$%#$#Z$P#d%#X#"T##$\%V%Z%%%%(Z'T&%L'R$J$X%$'V&&&(P&b)Z()L'*R(%'&%\&&N(&(V((N)&`)Z)P(X'\')&%X$"#X"^%\$&H&d$d$%d%%"#^$T"\##V"V P ! !`@"V!J!V!V \ F\LjPbVVTP^VNRR^Z`LfXXFd`LXVXPH\T H T T V X T V  Z TZ ZRH H`Z\NR JXN JRfR ^ JpT\bLVPF@b\RVNZJXTZbVJ^VLL\XZXVZPXdVb\VlVXXXVTTJ`ZNdPRRNddbLVLTbR\X^TXT`PbXJL^bT`TTRTHfJZZVDPVTZjNP^d^^\\X\h\@VbZZPZ\`DJZZVbZLfRXVTX^TZZXNRZVfR^RdVXVHX\PFhdZVbT`^XfJFVP`^XT\\\^L`FHZRdZ^TXZfPV\XXdPV^N``RTT^\XfZTRDbJh`T`J`R^hP`\T^XLVZPRR`R`RVLVb\ZZldX^XZZf\b^XP^dV^TfXh^ZLZTPT^\bRZN`TfZTdbZfZd\TTX^NLPTFX\LJFLZPP^NTJXTPdT^\`bPR^ZRRP\RNJRX^dPdPLTZbTFZVX^PTVV\VZ^`JXTb`RXJdbTNLTVLPTZbVRLXPNN`^b\BVDLHJTPNJbPXRFDFd^PTT\TVXXRHXLRZRP^nZ^DPf\R^`HPT^`RNXVZZ`X^ZZNHPLbJTLZL^\bZPVZX^R^`ZPbV`X^\^RTP Z V Z l d R V H P V \ T Zh X V  ^<@TTR\R\RJ\ZVNbL<^PT^Jb\DRV\XJNhNPVTVZ\HT`\XP`\^TVZZRdd\b\T Z\!J \!^T "V!"! b TB \` V!"V"R" ^"!b!PZZf!d L!V!PL^N FH  ^ X X V!R !!!b!P"  V!P!f "X!V!!#V!#""P!#T!j!T#^#"H !^""Z"Z####\%T#P$^$$\#V#X"F$`"X""V"\#V$V$Z%%P%Z#Z#P%%L"%Z#R%^$#T%\%N$V'&V&`'J%V%R(N'Z%H%&#V&$T&&&$h%%#"f"b%"R"X"!!# X#"!!P"!Z T!N!b#P!R"#!Z"X$R"!"! Z$!!#$##`$$&%X$"R#f$X'&"X##%\%&$$&#D'$L%`#T$#\"&T$V$"b(Z$N"#X$%'T'$%V%P$Z&T$%V%%&'X(b'L'V'&R'T'V(`'%f&P%''`(J(R'')((&&T(&Z('(((P)+())N,*H+)'P(Z((%&J$^$"$$J%J$%T$Z%#N$#Z$P#!!V!^ !X!!!P"!Z! !"!"  X V !RdH\XVP\RX^T^`hZlNN^lNjRPXXT\^`VLVZR Z X P ^ V Z X T T J V J ^f L ZVZZPn^R\X``\TZbTZTRNRZT`\TTPVVDXVX^VXV`JJP\\VPN`8LNhTTbRlNRTNV``VPZ^NP^VT`ZVXP\R^VRVPdZZZZdZJTLTZRV`NRNZVTXPZLRVPZJbVZTT`VPLP`VR`TTRTTdTRXXVZTV`Nh`BFZVJXL\L`V\X^Z`FfP\`^VXHhRZ`RXTXTVT``\\N`T\^TPZVdHTZTXR^NXZN^`P^BdNd\ffbfl`Rb\bhfbdV^b\\L`Td`hd\\RZ^ZRR\\`jPLZd`PbVRRP\R^dVfRXPdZZ^j\ZXVhXdZZdZNVTbVXVZT^RNLRdZZbVVZ^JZP^XhT\NX^R\bRXZRXRZ\VTPVR\bRPTTVVRXdJfVTV`^Z`^T^PRZVZXPTVXJXbJRVJZZRV\h`X^`NTT^hVbP\\J`XNNPXPd\ZL\ZRV\NX^dHPTLZdTTRX\ZHfNXTNL^XPR`TBZVNHfPVfNT ^ X X d N F P N Z Z Z Z L P Z f FX    LfXV^LLZPf^TJVbRR\TlTZ`N``R^P:TVBN\^ZFXTR\L\JbJX\NTb TTNX\PZ`XVdbN R\PN Z"Vb!`FX !T Z N X T N #  R RbdJd P!^"!X  N dV! #! X"" T!" L!!V! TbV V! L b!L"!X#"#`"d"!!X#!\" "T!N"#""X#T""##$$$#R""$X$L$%V%$P%'`$D&b&\&P$"N#L%`%$$%T'&&P&Z'V*V*T*%^(Z%Z&&J&$\$^%X'Z'Z&'L%$l$V&#J$##\"Z"\"L!!!!d#$!N"! !"L H!H!d"H#V"!b$X"P ! f!R!V!`!R!H#$R$\$^&&@%d$^%!L"L$^$#P#X&J#b$P''&P&\&'V$#%R"#$P$&>$%$&b%%L#T%$%N'Z'T%%h$P'&%%L%R%V''%`)X*R&^&$@'Z'`%(N(b*'(*T*((Z,(T((''''(*)`+(`+T++))^*R)R)^*''''X%$H$^%%Z(T$N''^%'$$X$\%R"# V#N X R#!!R""V"L" T!!R""! ZHVPJXf`^XZ``RP^ZZXdTNRXT^XX\T \ R \ N \ X X \ ` \ j P f T V\Z^ P X bV ZPRVR ^Vn`NbJN`X\R\\PNlPHV^VP\B\VT\PTdNZRZX`VV^J`\\N`LV^TD^RRZRTZdJXb\ZNfRXZ\LXPZd`b`V^XZV^VTj^\N^b^\hZF^\Ld`\VdVV^HdbP^RhVTV^T^hVTVNZTR\f\HNbX\bXdX^ZXVPZ`ZJXPTfdVTZLTXVXZnNJbRJbNP^\ZL^\Z`RVbTP`\d\\JPV\fR`XbBVTNPZXXZPXND`VZR^TV\TX`b^Tb@T^^JT^XN\bbdTZ\L^NNZN\RL`XVZXVdVZNVXZNffRdHfR\PFT^^LNXTRT\Hfh^VTZXDVRR@L`PRLLD\XHVTFTXXB\fPLVZV`TZJ`VDTVPPXRHhXX^ZLVTXbVZRVLblTH`\VZVHPXHT^R^\XNLF^NHThVHZLN^HbXFPRVJT\TdRF\Z\^X\V^RTTVXX\PLXhND^TNjRZ@VZNhV\Db`R\VV\XXPZVVZ  X D N R P F ` J V ` L X R Z Z P b d TL V X\`PPVJV\TR\RNNh^\V`ZVLZXP`XJZZ\Tf\PDXbN\b\NPRT\\VP RZbZV!Z\!`VRPdVP Z!!T X"\"Nf!"V! !d!! N J R! f!!! P"^ R h VZ N T H!#H"!J!#!#!! T !"!"P"XX ` h \!!`"!Z#H R"X"\! P#`"Z"V!>! "T"Z"N## "R"f"Z"#"#"#"Z"R##!"Z$$^&X&`&$$%&##V$V%V#T%$L%#V%&&*R%'&T%l&J'(&D%L&&Z%%j&H&Z&L%#"Z%P'%$$X$"!!!!Z$ X$%&N&Z%R'`*l(Z)(*()('''P&#%$(%P'(\*J,*R+\)R((('\(V*)P*^*P.R*T-D,X+\,*T+L++(T+')b&%+`'&'X'%%'$&T)d&b%&$H$\$X$X!L!#P#""X#"\$#%%%^#R"#`"J#! R RLXXXTPXbR^`PZBL\<b^NXVdnPhLZVVHNJ f V \ R L R T R V Z R X N Z L T J ^ ^ b ^ H \ V RNbDZZZhT\`DPZXVZdJX^NHZT`X`RdLVbZ`\ZLfNZXfPh^DZZX`V\PbJRRPbZ^XZZVR`bTX^XnXVddFZP`X`LXbNVNX^dPRVZV\VPZ^ZPR\PHhR^RZZP\V`XbNPPXVdTb\NZ^VVJ\JVP`RZPXXZDB`L`^XXVZ^TXN`ZV^RP`\^RLbP^`NPPTT`NZTL\FN^Nd\LhbJ^bbVXX^X`^dfX\RNbjb\XT\\ZbXb`X`R``P\^TXPdVXb^^Pd^ZXfLR^\`RJTLRRVXTJ`TL`RZVZdZT\RdVZRXLhNZVHXRbPTJ^JVVTRRfRbfTXTR`^`Z\NPb`jPXPXXVFTj\FdRFX\lVh@`FbNZVXLV``bZJ^PZXTPXR\XPRPdRNNVRRTZL`RTL`\NXVVZVRHRRRTJVTjVX^PR^LTbVRN`VLLZNTRPXZ`RTZZRLVHTT^b\VRRRbPZ^TLTfLRPb\ ZRJ R P X V d T H ^ T ` T d Z \ TP XRN^XXV\P`HVVVPP`FZXTJPT^RRXLVH\`L\XVRDTJdXNbJVfZNb!Z  XL R!^ !d#N# !"!N F R "R b b""#"!\!VN!` \ J!!B$ !X"XT!X T N"V! !!"^!N!h RVRT"!X L!!"b#"d"N""""!! R# Z ^!! T!!T"!!P `!V!"L!!H#X V"D$!J#%$#$"N"P%\"$R$"^""N#R"N#L%^%#X#"V##J"V$$##"T$##R#R%J&V&&%b&<'%%'Z&P%P%P&%%$%R'N'%T$X%&H'^%&&%X&P%#B!V# `$^ !!f"R!!"b! J!\!<"T!`""\\!V ^R !!H$$##h$P#^#T#D&Z$R&!^&R&%%X%V&T%$%'`%&'&(&R%#Z&$$R%P%T%R$Z%#%\%T&%^&T'R&'T%&&*)P-Z))\+()@(N'P'^(P)\(L&X)T*^)+V,*J*F+'(*+*f*),-**+L/+V)^,T*\+Z+F+T+)R)`)P&&H&b+&&R&`&&Z(Z)&&b'D$P&$Z$V%F#f!$$H&$%\&'`(R'Z%P$J#N%""$N"X" B `FZRVZ\RZBP^V\VHPPfN\L\RTXVRZPZPTZV\  X f X P V Z T D d T P R R R f ^ X  dHZ JRLH^LVXNXTZPbTZBfLRZPPZHPVFXVTZVRP\RXNdHVh`\ZXZR^T^VRVVdXNfHXN`JPVTTbRbXZNPVZXN\X\^\ZZ^P^`Z^ZPfVPZZbRVPRTZVLVN`BX^^NR^bNJb`FH\XL\ZXXRHhT`LbT`^Vd`\\X^RlXPNldbd\Z^XNTdXTXFZZ\RVTN\Z\`NhX\VTLHX^DPDVbZ^ZX`R\T`XX\NXjPZbPd^ZX^\bbff^``f`TX\`Z^`^Z^VZRVbTfb\dZP\R^R\RNPbXj`DRbVhDXLTZZ^bZZX\JJXRJTPVJ^PP^Z\^Tb`RTb`FhZ\T\PVLJD\LRH\Z^NTN\L\ZR\TV\FZ`TfTXbXZX\P\J`\Z^^fRbJVP\VV`R\XXLVX^XPRLVXLVZZXXN`RVPJN`dXfR\HJf`ZXbHXTLZNT\VRV^b\bL^^T^LbVVZbN\^dPPZPPbZ^JRJbVZLVV\JP\ `T  ^ T ^ ` b f X D jR \ TR  HLZVT\ZPPTRTHdTPTRXZdZT^XPZTP^BXTZX`Td\ZN\RVVfJb^\PXXXL!T HP!" ! !P T##R#`#L#` X V!X! Z!#" ""Z Z"T"h V \ L"f!!T""X \N^! Z J$H" Z! R P X ! P`!P "X" Z!X"!^ X !H!X X!!R V"P""F! !#`! T!T PZ N P R#"Z!f$#$$^$!J%\#P#!""\$!#$$#Z"#V"$J""%#"$X"%$V$###R#^$#V&P%%%N'%f$$&V'$$$#$$&`&N%%V('%V'\%#%Z%P#T"%#` f# !^ "X! L" T!Z! #X!"V!V!RP !TR h!#^!T"L##T$b"#%V#%Z&$X%T$$V&R%P%$&%X&F&T%P'%L%&%&$&&%V(\$T'#$J&V&V&(T&h)\)&'X)\)(F*J)b()+6)h)R(H)T)')h'R(P'\)`))))d+^)(V'@))P)^+N,\,X-D-,,./++X+T)+,*)+V(&Z(\('N'T'&H((Z'f'V(Z'Z(%`%Z$R%&%#%`#%#%T$%`%^)&f%V%P'^&#X#"" N!XZTLLZ`RX^X^VTT\NPX`PZdPbNFRFTLLFV \ B P T R V P V T T ^ b J d \ V X V b \ L V L Z Z Z X >P^PPRV`P\bXV\NJRTfdbVXX\F^^VT\N`R\Z`^`RXdPjPNBb\\ZXR\PZN^JX`b``RV\PRXRbV\^RfTZN`PT\ZTXPVdNXTVTPXZX\Vd\^HXR`BLZb\DZ\TN`NbPfNnTRZPZRbLTL^\LJbRNTVXf\RdX^\`X`XDfZZTTXTPTXFXZ`bXZ\d^TfTdJ^`TVTPJFLfF`VVXP`VVX``fVRNTX^TndZjXbhfd^Nbf`^^RZJ\`dbV`ZVd^RTZR\PJ`\RRbdRfZXP^B`\V`bVZVXXL`RJ^FNVHfZTZVZV\T^V\RXPfT\bT^^^\TNP\P\bTbbVHdVZTRV\RbJLPR^VTZTPd^R`VLNHfJXJ\XZ^HhZPNTP\XPN`RVVJVXVhT^RL`JVNTPNVZRLHXPj^ZbT\P\L^dZNTdNP^TRZ\RP^bPR`XZdXF\LP`Z`V^Xd\FVd\TNNJLVRRTNNTXd\^H`L^Vd V XZ h P T P \ R \ Z D H X R R R X R  VZ\VVRHdLXH`NL\@dPb`bJh>XHF\RP^^VFTV`D`ZVhTTRV\^DTVf J!!R `"Z#R!H Z!R #X!V"N N!#P"Z!V!R ""#b!#N%!"R#P T! R!! N $P ""H!JRRX!N `!#X# T"\! \#X!!"! J!  "V!!R h!X!"!"#!^!P#PR Z!\!Z#T"!R"R$N!"N!b" T"X "\#P!H"%V#"L%Z$#`%N%Z"!"""$b#V%X%""T$F"N$#!#"$X$L$V%$F#$L$J#H$&%$L%%(&%P%f&L'#P$P$##F#d%%"^$#$$%`&P%`''#%P%X$#V!P! N" `F! V ! L P"R#R!N""H" PV ! !`##!`&!R$R##P&&'&Z%V%$%$$N%R%P&D%T'(Z&V%P'$&V&%&T'%%&X()&&L'T'&(T')))(*(*(X*T(X)V(@)Z*R'\('&%&V'()N,)*T*L)T*(R*P(P+Z-+-/h/Z.`.-L/,1F.*T,)P(J+)V(R*T+'b*T*+'T(`&'T)P(()H(`'&%&N'R*V&&'&Z'\'X'`%&'&(X'F'h&%"#! \RV`J HZRZ`\\Pb^<bVL`VT^V\VfTX\XP V V V ^ F Z b T h H L X F R \ J L : R n N P P T ^PPXdLRfZ^P\L^XVj^^Z\bTZNbTNPNZNRTV^TPTTh^NZ`Z^ZTTdTbRbTV\\XTJ\PbBbV\\ZLLZLVLVNZNd`R`NTbXdV^rRJTP^fVTZTV@ZXXJdJVb^RXXZVXN^X\TV\ZZ`V\`^TL`NbNNXlJVVJDRb^R\R`\VR^PnVbZ^`^Lbf\ddddX^Z\XXR\TbVD\TRVXT`ZdfZ^fXRHbVPFdZZ`>^\jbhT`^Pd`^VVZXLZ^\ZZ\\ZZ`TRTfZ^`h\P^\`fZHXZh^VdLb\X^\RV\^ZT^^Hb\^\VVDNRdDXZhbT\HT\Z^bjbTXZLF`TLXXXPVVT\`VPRnFRR^\`XPZ\PXTdNfRXPNPNRNP\T^PVR^JfhPVD^`^LZPRVT\HRXZLX\ZT`FddhZPZR`fT\bZ@<X\hRRZJP^RZ^^TJLXXZRRTNN\``RVTN^\NPTV^bXb\^^^RVXV`dTV X ^ Z Z ^T ` ^ N P R T V Z H d V b X Z\XTZ4dbRTT\dZVVJL^`\ZhVNXJV^XZdbPhJh^TTLXRRJZTfNRNP X T ^T `"!N!^!R!Z""" "!\"^! X " "V"\""R$X#"X"P"!`##`"V!Z Z!J!!!"T!!! N#X!T Z"!b V ! d f"!` J"d!N"!!b#J"!\$ T!"b%P"" PN H""X!!P!!!b! L!^ TN !X"X"R$V"X%##%$V%"! b"D$J#b&'L$\%X%T%N"V$V$F"$T$R#$`'$d&Z$"#$R$R$F%J$$%&L%&'V'$X#L##T#F""h$Z$%`$"$%"L%Z%X%&$^&$#P"V&P!J!b!H!j `!V JHV VZN N!\!T"R!`!L"^"X#V f"!R#Z$##L#T#%R%P&#V)P%X(%P&^%"T$^$$%%V'%L%Z'&^$b%'&')^)'f()'X)'T))X)Z(X)X(d)*`*\+**\+J(')))&&&j()\(R*d+*\*+j*))T)X,**X+,./-T0^.Z1-X-T0,+),Z)X*N*\**)H,P*)(('&h)*J((*'L)^'^(R)^(P(T'('^(('`)%R'f)P(`*`(V'(L'$Z#!Z\ PX T LHZXd`hZjP\F^`XfZXR``R\NRVVPV`RTJR f R \ T L X ^ Z T X \ P ^ N Z Z Z ^ R ` V L Z R \X^Rd`BJV``PbRVZP\NjZX\NVH^dDhXR`XRP\N\T^X\VPVL`XXVTZfXP`TVRTRjP^Z^bTPJZbZX`XP\VffXH`TRdZbTZ^RZ``\PXD`VbZVZXPhT^RVZbd^VR`\Z\dVVVVRVXX^XX`fJ\XXPXZ^VT^^TJdR^^`Xbb`Rd\^\VVP^ZDfPXfPbNbL`F^PNVNVNhVJZfXXhbh\fbTXdZ^^b^dPVP\XTVPVT^PXVLXPPRRX`HVbPRZHT`XdHPR^ZTdRLbX`ZZTZB\RZ\RbD\RZfZPNTV\fTXd^fJZRRPf^fRLTR`\pJX\^RRV\TVdH@HRZPT^PVVb^ZX`VZ\Z^Z^JVbFZJR^fX`VRdZZbTjTbH@TJZ@RFLTL>fZ^RXTZXJ\N`^B^TRVXVX`bZXLZB\fFXbHFPZ\X\THRZNZV@PZD\fP^`LVV^PbRTLR X X R R ^ N R T P T \ V  T \ Z LPTNXVJXbTFVJTHVZNfH`VPTXJ^HTj`FL\\VTRJbR`VHVRZ`F j! ZV f!!"\"!Z d!T ^""! \" "X"!"P!\#%J%T##P$`#!J#Z#!X"#!Z!F#V!"H"Z ^R!!  J!X#R J !!V""R !L"$#T"\$!R!"Z# !N# `" "V!`l!V#!V!N""" V"N#\!LRZ F!V!#`"%"#H%X$V&#" !"J""Z$$$$&R$L####$"$b%R%Z&$&&&&F%`%$#b&Z$%%X%Z(Z'%%$d"$N"N"#h&##L#L!$R$R"%&%^%%b'#$V$"Z"T"T Z T!X \ZV !V"R F!!j" "T R""\#%$"##"$%b&%@%%f'&T%&`&%X%$$^%Z&$Z#T&P'R'&&&(((X((N(Z(&)))^)(*(B'Z'T(*'&(\(^'X&^(V('`)J*V)*Z*B+T-*+-**P*)`+T,`---.\-d-T.\-P/L/*V+`+)R,)-)X-)**V**)h*('(R)*X'()))'(D(\*Z'((`*(((R(n())+'&Z&'""\#L L T R`! NJX`T\X@`VJTPHPZFVNTTb^HF^R\ f V ` \ X X Z L f X b F f ^V `  R ZXV`RN^ZNJN\`HXVPVVN\hN^NXTJZhTPX^`X`TP`^hPPVVZ^fRJTTRVZ^ZNd^ZVR^Z^^\XT`F^Z\TZVRZbTVZbZZZXP^XV\N^TZ\f^HVRTNTZ\XLFVNRZfRXJTfHJ\hJZ`T\JZTNZVVVZX\NR^XRLVRTZbjZLDZ\\THTTV`X^ZTJXNTVTZP\TLfVP`JLZfRjlZfbddTdj\l\\b\LZ\d^`TfRXd^^\\^fZ`P\J`XVZbZbXVN`L2\X\XTXV^d\VZ\Z^TT\Z^R^T^RVV^^hRZNfT^FTVR^VZHPXTFTbb\hbLZ`dTZRLXP`V\NbbLdPRTTZf\XLR^TP`NTTTRJTP`ZVPZXXdVTbTTRRVZZ^hZjNJZ\T\^PT^VXBX^bNZ^XRTPXZ\dJhR`V\VN\X^`\HLX^PTH\VNPXNVZP\N\RX^fXR\XZZX\ hXb P X B V \ \ b N \P V X T R RL ^ R^RP\^RNdR\\hT^VbTTdZZXXdNZR`XjnVXZDVP`XV\X``NlJT^Z\ZhVPfPbPJ P ` "^!!L!Z" b R!R R!! !V"$#"^"F$"`#""!!\!#!J!"!!\!!Z! L"\!RZ!T!L!^" !X Pb V"!X T V! L!\#b"!V !J!"P!b"R#n!!""Z#T"!b"Z!^!X R d f! !N#!"V!b!T"T T#R""N$!R#$"%#\#f#X"#!b!!P#R$#&$$$Z%$T##Z$#%$%#R&%\'V&X'$Z$%`%$&d%&Z''\%%%L##$##N&\$"##\$T#^$N%#$#%T$\%#%V$#H###N"\ !  ZV fXRV Z <" P R " !T ^#%&&#P"^#F""X#Z#L&$V&N$`%&%%%F$$'#`$#V%$X&'\&Z&'P*V)`)('T(V(P(V+Z*+L+^+,(*(^*h&)+*^+(&%('(P++V,R0,L.X.`,,P/*d*,+-+,V/T..0.N0N+`++P-b+*),+P+\+V+j+,D(V)H***,*(b)X*P)d))R)\(J)^+)X*H*f(L))\()*f*F+R+,R)))$#$T#$R"Z! P !! L ^ V"Z TN THPZXZffTH`hZ`TZZ\NVX^ T^  T L N f T R h P T R h P H b R R ^ H\N^LXdXl\d`TjNRXTZL\bNb\X`TLTTH^bfbRV`\TXDf`ZTf`Z^N^N`TPZZRFhDFXN^TBZXRb^XJ`XTJXV^N\TX`RbZXRXNX\ZTdbP\ZH\b^T^Z^VNRZP\RbD``\V`^TP\X^PZXdXTj\b\RZfHLPJh`TldlTLX^T`^J`Z\ZPTXNRdLZRFTb\P^Rdl`XXX\`h`\ZXPdPfVZLV\V\^X`PZ`XXPXL`Xf`NRXZ\\VjZZ\TX\NH^^XVdfN\XJXbRT^dXdNZnZRXZNTRNT`RX^d>TnLbb`NPTfVbFrL\\Z^^VLfV^Vb\JjX^F^bR^RT\JVHZRXHNZPN`JZLFV`DRTZHX^\NbVj@^\NNPRTPXXLP\\VRPNHJZTJPVdXXXdFT\FZVNLJNTTPPZRT\^T`HRTTTNVlPRZTR`TLHFXPH\b`XLTVVV\T`NV\\fXRR b P N H ^ b ` R ^ R  Z b\P0 X P V @FV`TdVPj\VZ\NLTT\^\TBLdRVZDZDXX^d^\LJX\d\bRJZ^\^X\XZT VZX"T!T ^ !` ` ^#!"! f `!Z!#Z!F!$L$V#$N""!`"!P!!!R"h#$H"d%"V$`"!F#T!"d !X ! d""Z"N Z P !^!R"#J!B!T#!"$" !B! d!R#H#`#!%!!X \# <%! T#\"V!!#L"! !\ J  ^! Z!$""V$"^#H$b#\#!N#" "#"F#`&T%%^&V%X$#P##J%&#^"R&\&$%'T(Z$%V$P&$N&$&b%#$^#R%P#P#F#J#T#"##Z"%"%J#^%`#$$N$$T$V%#X#&$$# !X T V HP!N!!F ^ X!N!V\ VJ!!P"d! \!! B$R#$$D""!Z$\$%X&T'(N%%R&V&N&\($`%%X&^%V&$L(`%'&T'T(^)(F))X'R'Z*P(L)-*V-V,+)((V*R(*()H)(&(^'V(P(b+V+,-+,-T,++L.Z+d*V+d+D./\//1j.-N/+,+,)V*H.+.P.+d-B*L,*n)Z*X+R)(-`(^*T)Z)T+J*\*R*)T-J)()'N)+X)b,Z*+\*N.X+V'T'T'\$<#X"P"!!"! J!V !L b R!V"V XTL^VPZ\TXPVTVXRNThXTXZ^ZVV \ ^ X P ZT B P ` T \ R F T R d ^ d N Z R HV\8Z\RPRJR\dZbT\ZVHZZRVVL\NRXPTJTPX`Z\DXZPPRX\LVRTFZNRXFdR^\TPb\PZTDdRTTR`\XRR\dfVPLZVRHJNZNNf\T:LLVbRPXFlTZT\RRVVV`fXF^P\VN`ZVNVTLZ\^XRXVZPbHR^VXN`TJfdFVPFVTZZZ\PZNZj\`LXJPZZ^^NXN\f\\XNbVRd\Z`\PXPNJN\X^PJRT`h\^^^``bZbZ^d^T\^n`VVZlX^bZhd\TXZ^T\h\XTd\T\\ZRRX`R^JPVZZXT`BN`hVbfRZRZdXR^ZRH\^XP^^PNjR`RT`fZZ\Xf\l`NbX^NPV^`XdHZ\ZbVTXb\bPZdT`dLVb\bdRZXXdbbLlNPXbbT\``ZXXPRZTL`^fJZ^\TNVJ\\TXV`VdZJTF`LP`ZVVZRZTX`dNTV^dZXTN`dZT`XVXTTDZfNhLF\\V`dnH`^LZ b VP \ \ T h N X R d f ` X P V d R XV VV`bN^TX^VbPZZ\HTL`RFNbXTZPZRZHVRXLPNZZTVR\VPNZ Z XNbVTPRT" "N! !B\""Z!"!!! !R##\"b#R$T$"N"!!J#\###"R$\$`$V#$ !\"T#! \" T!"N##`$R V `#!" !!J#"$L"X"V#\!"X" "!"`!V#Z$"T"!X""H!P"\ V"f"$R$d#""" d"V"R!!H! !!`V#N!`! J!"#Z#X""!" X H"b#^"f%R!!L%&T$&%`%$R#%Z$J'P'\&L%$#R(R&N&`'\$$#P$"%J%$%X%%^#%\$\#Z#`#$R#N#h"P!"H%!#Z!d$P&$^$%H%X$##Z"\#""d"R#\#f!PP V \T `"J"`!H!d!T L P!^"R!V$V"T"!!T$!T"Z#"$L"Z"\"$Z$#Z#$$L&%%'X&&^&\'$X(R%X)\'^&(V'd*N*P(()Z*)'T()R,,T)+,+,Z*')'*f)`)T('()f(N+X++P-N,,`.,,+*+-T)^-,..J0..-.f.+f+B*+-N+`-+T-.-,`.,+^)X+X,L+X-,H,Z+++))P+d*J++T*,^*B)*b,P*V*D.-)T(((T')&T%#V##"P#!X$R#"!T!"R# !h R VP P^^HZVVTX`RR^RfTXRlRT\\RNTZ\bR ` Z P \ f ^ V P ^ J ^ F R N `  \T\VVTTDHNHVXR\PT`PR\TPRTR\>P^\`^^ZfbPPV^P^d\bXfVVZdXNRX`LDdX\^RXZRHTXLJZb^bPhVb\TbRRTb`\\bbZLPVTfjR@R\RP``\PVXRdNZlPXV\^^TZd\dJ^hVZ\^RNdNRP\b^TV^NPTRbRhZ\^VPVTTV\fTTb\Rp^jTVbXf^Z^RTN\`LZ\V\^H^XVlX^`P`RTZPhLZPZbX^TR\V^^`TX^LPb`ZbLXNZ`\dTRVNVVRR\P^ZTdPPVhdfZb^RXhVfVTF^V^^DdXXbXRh^\H\XXV^JdHNXRZ\TZRVN`ZRV^LTLVTZJV`ZXN\LJDZNTP\ZR^LRPF\PTJR\JZXZTTPLbZVVHTNTTT<TX``LVZVdFbJ\PbXThL`HdJdLZZXPV`ZVVN`^R\XbPNJZ\NX^fXZdPBVRRVT`LDV^XXVBTXZ\ZLNRNXVVT\TZN^NZPXV^RLXLX HR \ H b ` f R d N R \ F Z L L b X P ^LZPt  RVRV`RdNFHNV\\Z^TTR`TVRVVRfH^Z`TVNPNVRVR^\R\ZJ^P! ``!!"R!R !N>Rb X!! \R XT" #Z!"!V"J#!"#P!L"$P#R$"R#""P"#"R"N#R$b%V%#^"R!N! !"#!$"#P# V!D!^ b N!T!X"\""!`"#"Z ! J!\"##$`"!X#"N""j!!Z" "`"%"Z$X#" @!h"N"!#V ^ b V!!R"D"X""V!Z"#P"\$N#X""P!V!X"N"#N##T&d&%%%F%#%`%T%b)&&L&P&$%%%%L#^$#\#$P#$V$\%##$#"J#!#J$Z!#!L"T!"R$"!$#%f%#T""Z$R#`$!L#$b$P" !  R!#b!!# XPXV h#$"f""###"\%#T"^"#N$N#X#\$Z%V&#(L%'&'f%R%&%f''d&%''%Z'X(f'P(Z)()R)()Z**V,**\*X*T+'X)T)**)+V*`)J))()*,X+-..-T+-,X,^/T+-X10\-F/Z..V,,V,*)L,\+-,f,,-X.-^/Z.Z-/N+(,,+R,N*N+T,*Z+T))+^-R.+**+-\*\+b+,+X)*N((T'X''Z$L$$###"#N#!X"R"R"f#4#$Z !b H!RR^HlRbf^VRbJZ^HV^\ZTP^V^HfJP\\R ^HPTV ` X b T V X V ` T V T X \ ` T H N N L XRbZ L XJ `XN^PdXbFjVd`N`^P^``FLXRJN`RJZNXL^\XFPbXV<NXXRVdbRdNb^TZ`V^`ZfDR\VTNhJR`XXdJbTNXTbZTPVTTfb^D\XbbXbPXNlFb\ZVXRNXXRThXbbZVRNjPHVZ\NNZTT^\ZVJdPTNLbRbTXZ\HRVZ`^JVT\Zb\PZPZPVRbVXPTTTPTX`L\VHVNfHXVDXd`h\\`^h^dZZbTZ^H\ZRZfHbhL`XPJbR`RFjLXbR\b\ZfHTV\^`^\RLX^XZVTV`TJbbLZNV`^\TV`^XLNXTRfRNZX^R:XX\X\XXfXR\ZTbdR\TZ\XV`XPbh\PXVnfR\f\ZRVXLZJVdbV^J\RRjJ`$X@bLVNZdZJRVDNPPPVNLP\L^`PbRV\\HRZFTZbPfPRjZbfPHNbXjXZZT^^XT\`RRZXRTRV \ V T T X R T T L l V T \ ^ X b T JV  dT N`Z`^ H`P\ZTd`NP^RZZTXV`^h`^X\NTXbN>RV\T>nHVXXXX FJL`TV^`TZ \  V"h! F! !JP V!`F ! F!d V!` !Z!`!T"`!!V#D#B#"$!N"#X#V%&^$N#d""!#X#Z" #b$L$d#!>"\ "!T""!N#N#n$#J""L!Z! N!!#P T"!L#"""%L!^!Z! !!!"#f#Z%T!\$^""$`"V"#R$!D!b""P""!!V!R^!! T!#!J! T!X#!^#T! ! b#"#$b"Z$V# N!R"!!T$#%#X&%Z%Z&$"T$"`#V$$#R%J%d%%X&R$&X%R$"#$#L$#"#$P$"#"N"V"!L"T!X# V#"F"R!##"X#$ ""V!$$"b$b$!T! B"!b ! F Z#!X"b\N Z #""T%^"#T&V"L%V$V$d"R%\$L$L$P%\"V$P%&V'X'T'X%V%J%f%$%Z&R&X)L(V'T)(R('T''\*\*\((+Z,+*,X,Z+X*V*R+X(*&((+,P,d,*(T*+)T,)\+,.\,N,,,Z-\-\/X./0/`2-^---+b-P*T*`+X,T.^1J-H.^/J0Z.b/P-,-J.*)+-\-V+L+\+*X-.L-Z,*+^+,+,T,-*,+H,b((*P)'X(\&f&#$R$$$P#"!R"L&!Z#!"" P!  ` hPb\RbX^PZhRTTT\bV`d\\V^LVbRdbjL P V f` ^ P f X Z X L H \ P L ` HR \VZd bZhX\bLL`dRPXZXVX\TNV`RbVRXXbdZZ\`TZPjZ`NTPRHJ\RfZ^XdP^TXHN`XbhX@HVRVRZZPRPVXPP\`hHPZhLb^XXT^hRddTTR`^f^PhRNHRZ`RRBXZdTRVZfXFNbXHHbfX\Zfb`J\TXlPT\\TnVDZZNdTXn\PNRL\PNZV\^ZVH\ZX^RRXlnVbhdZZ^d`ZbZXV\^TZbVPXdJVJVFVbNLZPPfPXT\LbVTR\LXNZbZVTXNN\VPPb\jLPXTH`NPPf\dVN`\TVbPP\T\\\^P^ZXXXV^NVRVTZNP^TT^PRRT\Z\TTRNhNbf^TZ\^ZRDTfX^^fZXhd`R`bZPl@RJVLL^JdXX`NT^VNVPTd\\X\`RPTN^XbVPVZL^PVbPhNX\V^ZbZ`ZRb\V\RTTXLV\dZ^TXNNPH^PZT`FXf\Pb Z ` ^ P b L R Z \ ^ Z T P` L hL XXT`d^bXDfTV\h^^\PVTTb\@R`RPNbZVVZRNV`PZJb `dXZVV  !T X"X"Z !P!T !l"N"V ^ !P "P"P$!"#!" !^$""$R$^$\" ^!#J"H$$Z$H#"N$T$Z#b!P"b"N"#N&^""$"!\""!b$"Z#""Z$!T! R"! !H X!!T"%#%"`!P"T! !H##"^"X$X$""V"X"d! P"P#V!!"X"!""V#J "P#V# P!!"Z!V X!V"""N"T##L"""""R!"""b!V"d!!X"P$R##H$N%\&\%$%Z#$L#Z%$P$X#N(T'%%L$$R$T#$R%%\#$$%X"\$X$!Z!\"!#R##!!"!!!F%"##f""V#H"R#!! "N"X$" T "R!\ FR"!T"J X#\! `\ \T#\"!V$@$#R$"b""L#V%$$T$R##R$T"#T$%$%'L'X$b%R$&'J&(T'&B&'V)L((Z(R)(Z()&X*Z*T*^,,D,)*H)((J*D(&'J'f+*J,V+^,D-T**R,**T-,,^,R,T,.-X-R0P1-0/,X/T-.X+*T-,,+V+*V0..2Z/L.f,L,,.^+*P-X/B-,,+X,+.*J+L,T.Z+-d-T*P,.X.N,\-+*N,)(T&P&Z)L(T''R%%P%^%"$"$R""!T$d#X#!R!!T" PN b NZTTRPX^Z^LbL^`XRT>RXP\jXRZ b Z \ V Z H X b \ PVR X ^ P \Zf^N\\R\TZJL\N`DTVfNVfVJRRDNTR^X\PL\RRXJT\XbX\\`V`bL`JD^PXDXf^^VX\^\PLXXTXV\L\\`b`\TR\HbbZLLjPTXXTTbVVRVfVR\`JNb`VXTRbVdVZbVVbTXL^VT`\`X^RZZ\TRZR^TbX^VTfRTZbXV`V\\dVRRVVZRV\XXR`lhnZj`\RdXPVPjjN^d^P\jVZXTJ^jPVTjXV^XbdNV`b\hV^VL^TVdZLXTHLTTfXPdVJVhXJ\XRXP\hDdRZLTZLL^LPZRJ`N^VJXR^\PZ\VbP^^dN^P`f^JPVb^^LXZP`PTR\RXVFPTXNPNVRV\Pd\NHPZPXP`^R\^`b\R\^^^THNT\N^V\TdVXNXV<dVdRLR^ZT`hX^`NTZbV\VdXZZ\VPZNXP`NTR\XTXR^^f\^ZNTVPVTPV\Hd L X Z T b L V d H `R T\ ZTd \^ PV\`^`dbPL\dHT\XbLV`\^dNPRVh^ \RNhNRL  \ f TZ^Z X"!T!\ "H" !R" !\R" !f!^ ` ! L"X"""J!^ V ^ H!\#J"<$#"#Z#&^%R"`%#X$#%%Z#$Z#!#!"H#b"`#"^$X#L!#`"L$"T%R!V#V"\#X#"X \ P !! !X"#V#P#T$X#R$L$^"Z!V#!`"!#""!f F"d #Z!T"Z"!#b"##$\"H"d"!\!"N H!!\"!!$b"V"#!""#!$V"h !P!!! b#X!#"L#"%\$##b#'Z#%T%#\#&T%#^$\%>$$##%#T#Z$P%R$d"Z#X"b##Z!\!H!T#"!X$T f!X#R"!V"""L$"d"B""X#Z#Z$#X!F$ "n H!`" V\L!V X" D! PT "Z"$Z#V%"X"Z"P"!T#&d&%X%P&f&#$N$%!%V%%'`%%T'&N$h'$N&L(&&\)V)'R())L*'b(+**\-*)(d)T)(d)R(^(N(')+J-+P,`+,\+X+j+.,+,N,Z.^-/X,\/./0.-Z-P-P.,T/D,X*^*,+Z+V,\--T.V0-T-R-,`.V,,,V,F,^-/,\/^,\-,,Z.+b/-.X+^-Z-,0n.,X,,\)(V'R&%'%P&Z&%%X(Z'$N$P$V##"`$!`"R#Z"!J^!^ Z!RV \RbVZVPRVVTXLRPZVZ`ZX\\VZPZVTf Z ^ T R P V R T H V b Rb ZZJ ^TTZPLPXZLfBbRPJZfXXbPNPP\\ZXdJTNR^PZ^VJJVbPLddDd`T^JTJ^`XPNZTThb`X^Nj^Z\XLjTR\VZd>ZZ^ZXhR^RTR^P`VVJVVZTPdLP^\bdZLXTTVdXRfLbLRZPH`TVTXTNBRVZ`\`RXJ^^^Nb\X`L^NfT\`TZLhV\RV`TVb`VdPR\XZP^RZVN^TNZTVNTPTdTT`VdfhddXXR^^`bZZZbRTTdRZVfj^VbX^Pd^hR\`FbX^XL^\\RbZZR^TZVPXLZ`\^RN^`^N\XVbHdJT`^\XVZPZNL\NTHLRTZZRXRNXLXbbZVF`\NRZVZHVTNTXdR^JRdXNVX^^`NHNXPVPLRXZZLXXP^\VVTXRP^TL`ZLJ^`bRTRX^JpPP\FZ>jVT\RR\dV`TPHZTXPF^fTXbf^PHTXVHNBZTRJRZX\LZTRXVPf^T^XDNVT Z^V P ` V V  ` R ^ X J \ RPbL^ V ^bNXTN@ZXb\JXZZPRP`VZXNJHFPRRNdP`hPTNZT ! J!L^!f T J!!\#H!b!!!"V#H !^#T!X"^ l!X!P$V! T!$""T!"H"T#d"!""##"##R#"$#\%$&^&"P%`#H#T"^!^#Z"X$N$"X#^#Z""Z%!"#V#F!Z! !"V! R!^""T#! N" !"!#\"#""""!$!V!!V# " d!!#j"X%""!!"!J"!!X"!" ^"`!#\#X"##Z#!"!^!$!T"!^!#!V#X"h"!#"L%%L##%\#"##V%d##"$Z%"%P%N'%P%V$L&L'N%&P&"F#L$"Z!!R$J"#D#R%%L$ P""!#V!Z$"T#Z"!"N#%X%h#"$T"!V!"L"V!J"TP \^ TV H !"$#!\%"#Z"Z###T$&J)R#&%""#"%"b'J$%&^&')b%N(\'&N&X'%H(X'&(X'Z)J-+X+V,+N,j,X.N+V+&V(b'N))*Z*,-Z-+T/,,F-,,/Z-,-+T/^/^+0.R/\/,Z-T,X,0`,V,*^*^)T-+-`*d-R,,/.X0R-,+N,R,-N,+J.`/^-/P/T.V0V0T2-V,-T.T-0Z.`-Z-N-Z,)^+N)T(&(&N&&^&'%&%%&N&X#V$X#Z$#"T Z!""!!"N" X! V `Z b Z!H^TTT^JTdZPZ^:X`VNPn^L b ^ V ` D b R X F NT ^ T P fN TZ~N^N`J\\RRT^d@bR`dTVZZVZ^T`XRJb\VXVTJT^RPZTZ`^JhVF\^fJ^TdR\^dTX^R`NVdFTTbL`^`^Rb\NXHVbLd\P^X^VL`VN\TXXZT\ZbX^PfXXNTP^R\\R`TZ\\ZT^fTTPNVXbV`^N`ZfRX`^\T`^TLDVNLZRPRbRj^V\j\`dP`TNTXV^Zl\`NRlf\ZXZZh^f^fXXL^V`\\ZZ^\NLNfXZXPZ\XZZbP\XTJXXdPZTbXR`Z^TXV`\XXjXXbP\RXJHR\PVRPdRXdRbT^VfZT\\N\Fh^X\V`VVHNVfLRb^`ZZj\T`d^hVRDlVh^Hf\ZTX\RbVfdZRjZXRTZJdXTRHZXXJ\Z^XHXjbVbPVZXZVNP^XVPZ`RV\P\RLb\`ZbNVZJlXVb\bRXXVL P T b N b J Z \ T V Z T b V X Z VLZ P\JXXJ`dPZR^fXRTNTVVJZRJ\\HZXL\bZZHhXXHRX`XPb\H `R b` X\L R\B^!Z ^ P"N!V !!!!!Z!X""b" Z!` " T"!J"#"d$Z$!"b#!\##Z!\$#$X%$T$b&%!#b%#J&^$R$P%"V"#Z"R"Z"$N#d%#$Z#^#"!d!^"!V!B!V!!!!P `!V \$"T$!"Z"!X"Z!"L$#$X"P"F"!D!"!T!P h!!Z"!"T#P$^#%T$#" `!V"N"R$!N!j#P!\!L"$`#R"f"^"! ^ T V!Z""P""!T"!T!P$\### "V##Z#H""D"\"#$#^$\%$$$%T$h$%^&R'&%$P$%%$X"P#f$P""!"T%T#"$T$#!V#"!XBnTPXFjb`XRJddRVjTVpV\\`P\dTNNZNZ^NTLHdVTZXDNTXNfXTXT\RZ\RN^T\\ZTd^^d`RT^PP^djd\RbPbZ^VTTdbTdb\dRXX^ZV^FTTZdLVZRL^RRPpXX^ZfTNXN\\VpRF^RNTZRhL^bJ^TV`@LX^VZZLTh\RRVPNTTdNTNVZddT`PL\dPdX\\H^fZZZ\Zj\jZVTT \ X  P T \ N N ^ R V X  TbXb \ZXNjZVfNZd`ZN^PRHR\LNb\bdb^P^Df`PZ^Z\ LVZ!j!bPZ\J ` !T! N!R V f"\!H!X! "! T!!!T#"$^"#\$`$V!!"!^ # j!#\#F#"#b" #!X""""Z$R#N#$##L%'D%%$L'#V#X%\%$d"$$"L"$"^""#"%"%$n$J#@"N"R X! #\""!L!V!"V$"%T"!L$\&"X""R$V$"R$P%"X$!"!^J !Z#"#"""D$R#P$T$T!R"` #R!`#X"^$$$R!!\!V# X" R!!Z!"!#T"L!T T \#T$^$X##P"Z#Z#R##%%Z"$$"%#T%$R#Z#"$$$%&X%$X#T'P&'#N"!T"X!b#Z"N! Z#^!F"""L#P$"`#d"$T%"`"h# ""^#L#V##!P!\!Z!J!T X#TP \ 2 VX NP F!X!Z!Z"  D T!\!!Z"#R"X$V%R$#$P$%Z(b&#B&R%H&#$$'`(X'&&^')('R)R''+d(X'X)P*(R)X+**\*,+**P*P*R**)*,**-N-^/b.T.-.T1T.+\+\/-/R.,.0b/J0V-.`,.X.*^*+\.+R*d,X*J-+\--\-V/b/+b-,/H-,D.Z-N/\..Z-0P./f.^.X40//1b0`-,P..+*X*(L**V(F(b)\&Z'&&X(T)'d'J(\'\(%%&D#J%$$$`$$L$"\$!!T!TL d"R!b X#f ZFbfPVRL`RTNP^VVbdD\b^`^H\TXRX f \ \ \ j b D d \ P ` V \  \hVVPXF^`dZRR`TTZ`dRTXV\VPdPTZ\TPfTRbdX\ZF^`Ln^^PVTbRV`XTF`\ZNXX`Z^TTV\nThZT^bdN`JX`^bP\\T^^d^RZVJLN`XVXfRdR`\^V\bRZNTHV`\R\R^\X^J\`L\^X`\d`Tb^bRRP\XV^ZRRPDT^ZV`JRRZ`RX^ZZVTX^fVR\PdZVXbTX\\lPNLZTR\PRPPTN\`\Z\hZVTT`l^^`\bfPb^hVXbV^lbTfRVX`RVPVHXPZ`dNN``PZNVRJRVF^>\XVTLRHJPPFZFTVJhXZVTFPJ\VbHf`\dJT^ZRPNJnHT\^LffVL\\^VT\\L^LD\LL^ZNT`VVVPLZPX`TN^XZN`PFXPXRTVV`TZ\PfXZ^\TljR`X\V^Xf\^LZ^\H`TXXX^FF\XPZZB\JXVf\\VrXXVVRXVRV`ZVV^`NNT\RXTRVF `  B ^ b R ^ T N ZRRbVP ZVRVPB^ZL`VTDVNR^VZRH`\bVNTTbfLRHTTR Z T" J  R"f!f V!""!N Z!T "Zb Z \ X"T!T"V#Z"H" X"X"V#$R" n#\$`$^$V$V#!J"b$!X!#>"\!P!\#Z#V#T$%!V#R"^!\$""#"$^$#V$#Z$$R&)#$N$"N#V!#H$$d#"\$"^#V#^#N$T$"&$L#$R! !`! !!# % d"X"#"H"!^"P#"!"#N"T#J$"V#"J""! ^"R V$"$@##R$"$"$V$$V"""#`!\ #B$T#P$Z%#T#Z"T!T#L$T#"! `N#^!!R!!R""V!T!""P"X#""""$V"%T$$N#`##P%%P$Z(R'R&"#P%Z$##f&N$%V&'$D%"R J#!"L #!P! N"#>"%F"!Z#N"#b"J#$ N 8"%#X%d##Z!ZZ T  X\T^ ! T!T Z!P"!\%"V"X"b!"#$f#`#J#Z##T&L&X$$J$%$%&Z'R&X))V&L('^(D*B*R(*N*Z(''P((P*T)`,+X+T,`+T,)F)Z(N)\,`*,P++,L-/N-J0,b,V-.R0T-.X0V11.-///P,d/.V,N,,*)R+T+*-`-)++T-V0N-j.Z/.T.-\/^--R+-N1V.V//1.P1./T0/P/0..`.T-R,Z+V*P+R(^)P**V(P('N'`'T'V'(T'\(H'&\&%X'%P$\&!V$T%P$V"" !N"f#Z `X! Z"N$D!V!P#R N!ZpNV\\N\LZ^X\TNDN^XVZZT^TZZNV\TVVd f f d T J d F b V Z ` X J V \ TLXTZNXPNPT`Rb\TRTPPPbR^\VVNRVX`LHDdLR^VPL`N^RBZF`jRTRZPHbTLPZZPT^VRXPXNX\T^NR^ZTTd\P\PnNbTfN^L`X\PVXJ\^X\NX\d^J^VTNRZRZT@PVZbTRR@T@RTVXNV`\j`V`j`T^RNPbX^VdbZZbZVTTXZTHV\FFTZ^bd\bV`XNPLL^dL^R\X\XXD^RRbddRbZ^rT`R^`X\`TP`XddRXtLn\T\^fNhX^^PJVpZRRVRZPF`VVPRTRVV\VTVZ^PRVZb``RP\fd`XXZVdRXLf^VLVThVTTZTXR^^VPJ```TRdP`PTb\ZXbNRZPZhLXbbTdXXRVVjZLPLT^R\XX^ThV\X^V\PRVN\VdX@fbRLTXXFTZNR\f\^TZbR^Z^LTZXNV`PXX\RbRZVPbLNJX\LdPX^^VXTPT^NbXVX^JXRbP^XVjV j X ^ b ^ X X T T F f  fVZPXX^`V`DJ\XLXZTPF^ZVbPL^PPZRJ^ P R T D P!b !^ RHb!"X!! !Z""#P" ! "T !R!L""P#"""!X#L !`""\$`%P$N&V#X"d"P$$#T$R#^"X#"#&V$X%P%"N!!"b"\$#%T$$#^$X$%%$T&&%b%\%%N""R!\"\!#"!V"$V#Z$ h$N$V$Z%^%#b%!"8 !J"T##X"F!#! !Z!V$Z$L#!L#"#$#\$X%$X" R"!T"!^" #V##%&###R"#"##^"d$L#"""$##V&Z%$$"#Z ! !!!!!!`"P$T!^!Z" X"!T#"`$Z""#\#Z$V#P#"h#L"f&$P'&`'H(P#`##"%^#H%"T%$B$#$"H!N"^ ""R!!! J#T#b##Z&V#!V"!\"H" !!"`"""X"!"T !>!bh!b!VT! V N!X#B"X \! H"V$Z#R""H%!X#\"!T$$#Z#T%L%X%"%\$Z&`&J'T))J')V)''T)P*('(*f)V'H+)**+P.+P,T.R*P'(\)(*))-T,..^/R-L,R.V.X-*P-*b.-\11X/`./-/`,--R.*P+,+,^+Z*)f,V+X-/N-Z-.h/-.--J/T1-.-/V.//0D/3/213f0L2./.V-+*H*R*V*(d)N'L+)Z(&V*)&P(^&('X)$Z%^&L&T''X$\#F&\"!Z""!"T#T!! T ` V#Z"!\!!#"! `RJ\P\NZLTT^hRRZZ\XTJbfHbnDbJ\^ F V Z \ F T X b Z ^ F V H ` X ` X J\\F`:^`L\`\TRZV`ZLXH\^TVVLJXP^h`VbZVP\ZXXV^RXVTRdZXVZHTB\Dn^FNZRPLZHP\XLb^XVJVRl^PjTPRT`ZZX\PF\Pf^HXXVVRXdNX^R^VXP^V\PDP^^XdP`TP\NTVVVTZRZ\V`ZRhT\X^D\XX\LP\db\fVbV`Z^V\ZZN<\TRVVHNL\RLNbZRX`RJ\T\hZD^LLd`^L\p`VPhJZfP\RT\X\\\TX`Z\R^VHbbdP``^LdjXVJ^`\`dXVbPV`^TV\FTVdR^\V\ZTXRNPPTN\TZPJTPdPV^^\DVPLTR^JHPTTPZPTTZFRP^NXdZP^`P\NRTPPPLZjDNVP^dZXDVLVPJ\\NRTVJVPRV^`TXJPR\THR\V^\L\NXTLXR\X\\\BLbP^ZbLH`\VRRT\FJZX^ZbXTZLZ\RXXXTRN NPZbPP T b ^ H0 Z L b N ^ L X \ V T bZ^   H`RL\RL`JZ`VVNV\fPZTPT^TZ\`L`NNRXXPX! ! T"  V! ^!T!! P!"""X%!#f#" ! R X"#^%<$P V! #R!$"""V#V$Z$Z#"$f#P##$Z%P%#T%V$T#d$#T#$#$X&%X#X$#R&%T$b&">$X$Z%P'`$"D%'N%J%#!X#"!"V#X%#"d"N$L""`%$^&%J%Z#`$V"L!Z""X###J"\"\"!#N#b#$#T#L%P#X$J$T$"V#V"##T"!b"Z"!N"$R%$T%\$#$d#Z!!\$#"N$\$`#$$""$T%V$%N$"T##!b""!X!Z T"J"!N# X" N!!R" !#H#V#!!$"#H#h"$$V%$V%P'N%%$R%Z&%$#V$#V#^###" V#"!J"!V# ^ T"Z"X%P$J#Z#!!^""  b#Z#!R !"V `R Z!^R VJ@#N!\! !^b! !N"\"J$#X$N"!V$!"V%"V$R$$#%$$%R#V&(&`&f)(T)()\)(()^)\'P)N)(+-B+\,R,)+^,+R)*J)(L))F+V*+P,.-,.N,P,X-V.++,.^/P/0-L-.-J-.R++V-`,+H+`+*++*N,Z/,Z-V-T-T..-d/Z.Z.f.H-R-V-F-V--X/L/-f2/0R1212.N/+/+p*X**)*))'T(V''(()J'(&&B&V&\(D&%%h&&&d$#$#D$R"#L"L"T !J L"""!T!V#f!!b$R!BdJ^L`TPZX^JLXTNV\^`bFRNJRVb `V X T R V V X B H X L V ^ f X ^ XV\LJZNP\^TZZVNVLT\`JPVPV^\\\ZFXRVPH\ZPbPbLfPTVTVN`bRThRT`XfNTXRXNRHPJ\PTN^^RLXPXTTJ`^ThLT\^RRhH`T^^Pb^hFX`DZP^Zd`F&XlRVXTLXZ\^J^RP`fZ^\^RZX`jX`XHVVVHLdT^PR\XP^TfDV^RhL^J\ZLZ\`bZXbXNVNP\P^LRd^fbTTVPBPjT\\fTXT\b\VZbL\nbPXPhTdZZT\dN`NVXV`PXTXRVZR`V^\b^R`TDfTXDfNV^XTfVTb^XbX\`X`\^TFVdT^P\X^LRZFRVVVZVLZfVNdf^`TbZZJ\RTXNLVN`\XZ`H@^ZPVVTP\NV\\ZfdTPZJR`JT^NPZRJT^PNTPb`@bVP^PZ^^`ZTVfd\LJbNbV^bTVV\`PV\TbVRTXL^XNVPTLV\VVfP`b\THP\ b ` Z  Z j \ F ` V b \ R Z VT VRVZVNRRVN^NV^`^NTd^NbDTHVPVH^\XFTP N "X T#R"P "Z!L! VZ H b#Z X"N!T#b"J#"!V"Z#"P"$f""b"P!#R!L! !Z""P"`"#!\#X$P"#Z#`$T###X$h#T%"P&`$P$L%$%\%Z"V$#^%%\%>%%V#\%&X&#$>$Z%Z$N$$V#$V%\'$$b$#V"Z"#!#Z"L#"X#""#"$H%d%d$$T%!!Z"#d$T"`"F"R"#"! !d!#X$h"X$Z#T## !\#!N"!X#V"#"#T"$\%T(N&X$D$^"V!!#R"#\$f$$V$##$^$T$b%@&%#6%#H#>#"V!!"d R J!!X"!!" T"R #!!j"N#"!f$!`#X#P$%8$X%R#$!%%L&$#P$$T%%%$%Z$R%$&#T"#b#"^#B!"`#$T"d&#b$Z%f#Z!f!^#H ` !!"L"!^%"" !T!VXZ^ZZ!P \ T\" ^!R H! T T"X!T#V#P%%%#T%T%R" !Z"L"#Z$$V%V#$'''*'X)b(J(&T&d&%&'()(*J)'*T**V-\--,*)+)V)+`,--,V,*V,,+V+*+-P,>,..\..0Z0^/01V0^2J..,T/,+V+L,**P)**+L,2/-/--0T.-P,\,0P/b0.J..0R/100T2X0T2.0R0+R-Z+))R*V)(+*^+T)R+(P)N)P((&R'V&^'('V'')X'%X$&J&b##V$^""##R"H"b!N#!J!X#Z!!b"P!$\"!V#VP T Xb\PPP`XN^HP\XRV^XNVXRL\XRZR b Z T Z R V Z ^ P V V V ZTNZdVTZZ^ZRTZXL\T\^RTRVVZbTXbTZ\Z`PTX^J^PTbPNdNb@dPTHZ`HPNfNVTNRVVZ^bVPRNPljN^VV\ZJVXfNVPbT`jLhTLP^`ZfTVnNXTb\\^fbTdbRXPXR`R^^\\X`RVJFNDTbR`\FfdPTVbdX``VT`V\V`PbNZb^hLXFRPVd\fb^VRRXD\DZZ^\`n\Tf\XdZbRZ\V`RTXR`XLTTTbZVTXV`RhPhHRZ`TTLX`ZVT^TXdXVZTH^PPbTP\VNbZRdVLXH\^\TRPbVXZR`XhV^d^dTbN\N^T^XR\`dRXjVfbLH`XbbXZPXdZXVXTZV\ZPRV`TXZJPVTlFTL\L\^\XRfTTNfPfRX^JXVLRjJ`P\^DXL^X\TR\TNLbdRV`Lb<PPVVTRH^\TLLTZXVRfJ\PJLdBTVdRRZF\`ZX X P Z LD V J R L N X T N \ N R RZ L`ZHRTJ^\NZTTfHN\^ZV`RVZXRLZPZTRN^T V""Z"!##H \# !P f P!!! V""\# `"\#R%V$"T%^ ""#!!V"T"!J#T"\$"X$V"$#P%#b%`#H%#P$V%&$\'#d&T%$$`%^$Z$#&#$V&L'%V'%$\$$$T&X%V&`$$%%$$N&Z$%#"#!X!" \"`"R$#d%V%#N$#P%$`$P#$Z#V"f%!P#""H$N$!"T"!#B"!T##$%f%#L# !"J#R"^!Z$L#V%%\%%%R%N$$R#H"!L!$$F#Z$T%####l%%%$V$%V#$#$\"T">"`!V"R N X!!J"N! N!! #H$J#"""%#%N%J%$$d$$T$N$V$X$J%\$&P$%%J&\%$Z%L#"Z#Z"T$\#"P"\""\#N""$%P$\"X$#\ R" V""!R!X!!#T"N"T"  N P X!F T""hV T"!T" F!P#"Z$"V#`"""X"$#%#>#f"J"!!"Z"$\$R$^%$$P%d&T(&''^(&b('N)P(&T&\*)*)V+)T,*^,*+)+*)^+T*)*+R-T-R.,+P,)L(),)+X*N+`-f-Z.V../0^-`/-.X.Z..-V,)+T**R)*,*P,,J//X10f.V..,,+R/\,-J,,R1/T1`2200/V0.\1-,-.>+*V)R)P)\**+\**+)^(T**(L(L&'&(R'H'R(&P()%X&%V$\%P!R#\"#Z$!^$Z"T!#d!"b###V#R$^$#L! XDV`hLbVXVT\hbHdNZ`ZbXZZPT`ZVRP b \ T R \ X \ H X L @ Z T R V h V f T J ` RRX`PdV `VV\JRVP^ZJ\\\RXHZPTVdN\\XP\T\ZZZJbPPX`VNTXLR\V\P\PbJPTN\^TRbZ`D\`XPX\^`X\NZJ\LXV\Tf^PLZfF`BVNVNFR\VTVXRXXhRXbbhV`R`N`ZVVVJj\PVXTP^\^lbZPX^Xf\V\^ZdTbX\RZ^bLZ\`hbFV\^VV^PZd\XHTX`TJZTdZZTZ^TT^V^LhVDbXdlb^^PbLR\^VTbbNXN`jLLXdbjRVxbRV^`^\VRTR\^RLPXPXVZVF\RVX`\V\bTVZP^hRfTVDT^LTZZL^PbHZPXPN\\^HZP\VTdDRX^\R^ZDVNXZZZ`FZTRZRXh`NNdHVP\j@dTZVV\VXPXN`LVL\^X^>J\^TPZRX\\VHTb`X\RFb\jZX\N\HBP^RbRZJN`Pf\NTZbJNP\T^VV^VV`dJ^N\\PX`^RNfHh @ X P V \ \ < P b J   X XdnHPNTlVVVZ^N\VRX\T`h^TJ^^!bL PJ R"^"T$#d"`"Z!"d "\!V R! Z!X"X" X#Z!T!#$$V#^%V"P#$!^##V""#T"Z"#X$X#^#Z#"\$j#%$#$^$L#X%$$$V$h&%$$#h$\&V%R$$##N$b$\'('%$$%X%%V%X'#Z%Z$$#b%'%F%V%\#\! ` `!Z# \&"$R##@%$X#V$L$Z#T$L#X%$X#b#X#^##X$#N$#!X#X#"$#V%"Z%V%T##!Z# R"! $&#&$X&N&T%j'R%Z#Z"#!"P%#"V$#$$^%'T(^%%V$N$X$$"Z!!^!"V" ""^"!R! Z"d \! !!!P"j"!X!###X$#V$#$V$J%&\%#F%###R##&$b%$X&X#&$H$"Z##"$@#L#Z##P#$T$"^#"`"N#" ! R#N!V"L#X$J$!d P^"!!^"@!N# !"b"L H P H!^" P! Z#V&!"#%h$&X$$%"V%%""!!V#N$%J&T%R%'$X&J&X'j)'N(R(&N&X'&&'n**T,(+V++`*Z+V,b*(Z*)J)V+')X.+`-,,V,R*,^+*++`).,--X//1T01X/-.f,d.//^,*-+**^-L+T-B+,^-P/0^.X/0^1.R.-b-Z,R-`/-N-^.-P1.d00V2Z0`.L0`.X/N-\,*+R,+)*T**)T,,R,-**X*(T)J(b'%&P&(&'N('V*f)&R&^$T$#L$b""^###""!T""Z!!B$X"!"" H VNZ\fT`V`T\X`JDjVV^VZ\XZ^V^ \ V T X ^ ^ Z R ` \ \ X R h T b f b ` N N NbTXPHXVVXRDPRPRZR`T^PPVRP6X<TTTXPRZX`PTR\\\b\T^R\TTPVFTTJXVHbV\PF^ZPZVjNZT`\bZXRTVVPTVVfPX`DdNLTX`T`bL``PRZXb\ZVXZ^VVfR^XX^RJbbXLZT`JfV\\XZVZbjXXTVX^RRZ^db\\`ZNRTP\`Z\\X\NR`^``VVnHX\TPX`TJLRRPFXlTT`Bn``XfRZ\V`lPVPLfbfJVb\fP`VL\bPhfTNFZ^V`Nd\DXXVNN`H\\V^hP^@Z\\X`HXZZXXNN^bL\PNPVVb`@ZTLPV@^`\^`N`JVV\ZR^hVF\Z\VXVP\FTT`ZPVZ`NNTDJfTNN^VFf`d`R@XZbTXPZJRZ\Z^LbJ^PTX^V`H\R`P\RhP\H\bZ`bTJVTjDZNZVLX>L\XdRRNRLVV``PZPXR X X P ^ L ^ ^ Z H T P \ ` N P^f X FXZXDVXVVVTfPZPV`TJNH^JZZPTXXJPT V L !L N h!TT"%!X! X#!!!^#T" X# #R"$""#$V#f#X""^"N$!#L""V#N""#X#R&$""V$X&#R#H$$R$T$$#T%$V$%R$&'%%$#&Z&%%%D&%%T&#X"#X$&V(%Z&Z%$$'$`%$P##$#T""N"T#"N!"Z#T$j$F$$$P%""T"R"$X$\$D#d$b$$#&%\$$V$J"`%Z%P%X&X%#P&"V#^#!\"T" !##$%R%L&R%&P$#&Z###R$%P%V$%#$P"V%L#%d%X$P#^$R#D$ !!@!!#^!" J! ^"!!^!`"\!R" H!X!`"L!X""N$!#P%%L$#$N$'L&#"T#$$&d$'%$$#$$T"%N"%P&"#$#L%#"h#b#T&Z$"$!T! Z"# X"###!P!"VV` Z!!V"#!#Z"!^! !!X"J" L!L"P#$$%h#$\$%\#T$$Z&%R$L"P#d"R$"%P%R&&d'&R%P%%P'H(b(h')'&*%&b)\)F)V)T+(+*)+)P+Z,()*T,)P+X-+R-R-V.,\-\+`+H**)\*V(P+,.J/`0.R0^/X/V0+X,-.*+T++)H)*N.,R.-R/-Z-^0H1V0-.b0Z.,N+R,T-J.R0.1\./001^0-1.X/^-d/b+X-,))-++Z++f-,\-+X+,\*))V(&\&N(L'(b(X'(Z')R'%##$"V#V$P$!V"%##%#"""$J%"!! !\!LNLRNVXPZ\XVRR^PJ`TTX`VVjZNT \  L N T N d Z ^ Z LP F h N T V Z N P b V b Z R Z ` \ dX PV `N\dZVRVXXXfTVRVX\d^RT`\^RV\FVZ@R\\VVVFPPbhPNjTT\PbZHVNfZ\VdZ\bTdXJRTTVZRNXV\RJTTZRVN^PRTPdPZTZJNNLZ\XJfXTVRPPTdVV^HVVX\PhN`XTZ`Z^XfLfP\VZR^X^XPX`L``\hXVXRfFd^V\J^VLfV\dbVb`DZTTL`\VXL^\TXLPTPdTP\\f\PNV`HR`b^LZ^dLRN`fF`V^NNVJfHZX\^bJbbV^dTdXL\LNR\`VPf`NHhRXNTXbP`bbh\TTd^PhXVbX\ZZXfTHZ6bLLZ^bVTN\ZXZRLXbRfbj`jT\V`VVV\``\\VdR`LTXXXVTTPXRX\Z\`TNXXPTTZfVh\ZVbVT`L\RTPXVH`JJTTd`VT`bHXbPb\dRX\ZbT\ZZ^^JPRLX\ZLV`TRXVdTLJbJJVTZXX`TXVRVNXLN`JfN\Z Db L T d V L Z TT  4 lJXNPVXHZVN`FLFdZZ^XTdTPPVdTR Xj ^!!V! `" V!"#! b!"!Z""P$d"#b#R##X$J$%V#^""T%"#!Z#^%$R##Z$P#P##P%#N$$"\#^$X#&^$R&%$Z'###`#P%Z&T&&'&J'$^&J&%#Z%L$Z%V%P&&\'%Z)&'&(R&P&P&H&$%T%P&X$^$$^%%N%R&Z#H$B&Z#^#V#"##%P%$#b$L%$N"b!X%$%`%%%$L%b$%$H&$$V$#%`&%$T$"!\"\"F"#!"$R$%V%$V&%X%&%P&$\&"$$#$'%%%&%\&L&T%'%V&H"T#V ^#J"^#d#Z"#\!N#\"!Z"Z#J!L! ^!Z \$!#T"#%l%%'#P#"T##P#R$X%R&\&V#\$N$&Z%#V%$V#\$H%$$`$%^%T#\$J%V&T#`#Z#X$"%V%J#V"^! #T$!X""b"P! "Z T T P!!!R"N$""P#"T#Z# X#"^%" !T$"T%"`$J$\$$R%##^"h#Z"`"!#^"L$$#T%^'V%T$%L(j+'V)%\&&D'X(`((X&Z()*Z**)*+*^+Z)L)())V(X**++L--\-,J-*)R+`,L.+P)Z-T*.Z-.,f/X-D.--B+T*R-+D/R-^.++^+*\--.B.\/.R1D1\1V0Z..--V/++P,0-L2T21020.J1/T-V0^.P*++,+T-V,R,*,\),.--J)J,N*N*(Z&(`'%'%'`(X'F'&%b'V&V&"X#"Z%Z$^$$@$f$#R$"\#P"T$!"Z#"N#P!!R" Jd\\PZ`N\JfRZXX`\ZNbF^PVRRRZX\`X R bP N T ^ V N ` ^ T d  T  ^ Z NHVN\XJPNPb\L^^NN^`TNJTXdTVLLbZZTHN^bdRL`Z\PZhV^XRN\ZTNdNXVX`ZTTTTTFXLjN^Rd^ZbTZTN`VP\NZT`Z`hN\VRPZHhJ``X``PVZ^ZXhhP\VJ\Xfjd\TH^\dXL^dVJZ^VL\bTH`\^PXpNT^V``RN\VfJ\ZBD^XT^PVXTRTRLHRTb`b\bT\X^LR\XV`^\\jZ`\RTdNbZNVZNTPbZ^hRb`\TJ^^FPR`^VVH`^`VP`^\RdTfVZTTTF^^XZV`ZVbT^PHbVVdVFN`XZV^VJRf`Vb`JhTRb`Fb>HN\ZRTbZLTTZX`\XXZd^TJZ>VP^fT\RnPVbLN\LV^`THPZPF\TX\XVHPNhTZT`JVDNf`JbDVTP^LdRXb\P>THTVVRZJDTXRXRT\ZNV\NRVRRX L P V X L \ N X R V P V V F \ N Z VZ P fRRZTXPXV\DRX\J^VJV\XFXLZdH\X !H$Z! l"X!!"^ R" N!!\ !D#!"X#8%^%$b%$T##""^$P&N%$H%R&$h$Z%#Z$$&#L&R&`$%$\"`#b#Z$#R$Z$H%&%&%&\%&X%R&#%T%$&T&Z$Z(J&`'F&Z'&$H&(`*(&J(X'&P'V%&N&'$V)`%Z&$^$$^'H%##J$$H&&#$^##^$""$%X#X#L##!V%%%R%$L&\$D#R#T''R$$%$"#R$"f##$^##H"\$X#"R#`%%"d'$'&$B'X'\&'\(Z'"$\&##%N(L'&X&'d(%&R$"P$#R!!P""X" "#P"R""# V#!"Z!!`#L"^$$X$""%F&'%&"#X##F"%#X$"$Z%&^$%$%V#$Z%F(%$%#%#%$Z'J%V"^$$#$^$L#  ` N V !V#T!\"Z`RR!PV!J"P" #!!"D"X!L##!%%"d""T#X%"#\#""%$$##"^"L!#""%R%#%J'&J'P(^&L%((>+X)'T*L&N'()'T*+*+D*'(R+Z()&T*)*d+F+V,,L/d.\-.V*Z,R+P)Z)X)X+Z*\**^+*++,X.-^-T-*+^*V+Z+/*X-J,.,F,`+,L0/Z/.^//J0N0/T->0/,-+^-V/P0R2P/2P2H2X1\0@0-.N-,)V.,*V+-+d-T-P,-,+-,)*`+V+(b''\)('X'%V'&%')^%%%L&%X$^#$##b##"Z#R#$"""R$V"X$%d"T"V$"!bNV\R^b^TRNXVXZ\FVVXXThR\TP VXP Z N f \ N N \ \ R \ l Z P \ V X f X Z VX PLR TT ^NRT`VVZTVZ\XXVX`VVPR^NZPXRJ^TdTT^TXRR\^VNPVP\V\XNVFRf\JRJZTXFXTZX\FJhVTTb\RTbFTPXVXR^XXXR`LRZJf`Z`Vl\\Z\V`PJZbR^TJVPRXVXL^VbJ`ZNL^\JdbTXR`NPRRR\V\P\ZVZZR@\XR\bXb`ZdXX\VL^TRXTN^Rb`ZVb^RTl\j`XbdZVfVjRVNX^fR\VPLXZd^^`\XRRX`j^XZ\^Xld@PZDXTf`X\`RX`XVbbb^PFbVV\LHX\^\Xd^JhVff`NTfZRh^Xl`THVRRPJXVbTX`P^NZ\^J`TP\TFVPXdX\^RZPXZ\^PX\\R`PNTVNZZhJVZRTJVZ^`TVTXL^NHRLVLV`XPdZ`hXJ\fXTXfRXbbHhTJXd^`XRZ\\ZPTZLXVXNXVR`` ZTXP Z  T R R Z J X \ r P T ^ X ^ T RR`<VR\TDdffVZZn\V\VZV>N^\R^^Tj! !"^"! "!!T X#d V !!R"Z$P#&^%F%Z$%%T#R#X$R%##T&R%^%@&L&F'%$^&N%%%Z'($%%T&N#\#f#`%$\$X$'V'('N)P&%V%N%%$%b%%%V''''#$P%^'V'\%`)T'`'V(`((%Z&'P''H&%V'V$P&R&#$%`$%\%%R%R$R$$T&T#N$##P&$J%d##$R"R"V"$R%\'L$%d###^%X$#&#Z"Z%Z#!V"#P#V#Z#"#F%f##$#T$`#&T#$%$%%^&T&P%&X$L$X#b"$b&^&'%b&%P&$$R&#Z$N#N!V!V"R%"X"Z$X"$#Z$#Z$P"#! J!#F#b#`#T##"Z$V#$$D&#V&N$X%\$P$V&##H%V$D##X#X%T(%%%%\$R#&\&F&#Z&#P$#$X$"Z$N##d"H!!N#\!V$X D$!`" VV"ZZVF \R!F$V \! !Z!!!X""P!b"X"T"Z$V"Z#R$N$N#%$J#X#!"J#$R%#X#\""\#F"$$$\#^%%%R&&b((^&L&X)h'()L&n'T'L''`(L+),P+)X)(L*(X(Z*(*)\)T+*+,b/,-+T,B+X*R)((+`,P,-X,++,\-+Z*R)*`,^,,R++N*-+X,--L-/N.\0-+1R20T0/N//-d-/0^02/\012H31^/.-,/X,.R+.d-+-X+-/,-N0X-`,.,++^,b)+P)(()H*&$b%#%$&^&R$'^&R$%V%Z$$\#\#"^$Z#R##%$""X"$Z"T" ^!!!XHXV`PPVRZ`RVbTHRN`h\H\`N^b@VX  l N L V L Z D X d ` P Z F J ` T VbJ\dX\RD`RXNNZLTR`ZPVRR`HfRLZRTLdjVbTN^HlH^TbRT^NLPbZXX\XfV^VRXP`RRXVTRXbRb\Hf`^N\FVRRZ<`ZX^DXbNbb\<TVXZVVVZZV\Vf^R\^ZP\dNZ\\VZ`XVV\XXhVRTfX^VPTd^\`R`b\TdXP\b`Zb\^PNXh^JVNXV^XdJfj``dbdXfNfV\RVPfZZZ\DX\^XD`^V\NZ^\TR`LXX^BLRFTD\NXNLFXBXVPL`LZTR^Z\P\b^`P\RX\VXRXJNFRHb\b\X`NNfHRT^XT^TNNXbJZPVTPPTZ`VP\HZVJXX^N\THVRTPVZVPT\ZT\VXR`PPL\X\DPNVTTJT\NRTP\LRXbHPTTVX`XJZ\`NTbVPZfd`Z\HRLXTZZPTTVXJLFNX^^`\^@XbPZZP^ZZ X ` P X P d V \ L N J V  fZXFXRX^VbXXN`fZNXVVRTdBX^T V!!^ T"T!!J"!Z$J#$Z#T$"" N"N #!Z#L%'%&'$P&$Z$Z%%`$'%$Z%%$&\%%N'Z'H'&X'h'%R'L'R%')Z$%^#%$%T&&%X'$d$$%#$V##^&Z%'b&%%%&$&'V''(X'(V(L))('\)H%'F'$R%$R%#&$"%%&Z#$$"Z$\$$P$^$$T"^$$P$$##%V$&$"$"T&$B$%#$Z%`$^$#Z#X#X##j"L&$^(\%$$#V#$T$$$H#%#T(%L%'Z&`'L&%^$##$#&^&R&(T(`$J$$R&""F$L$!!#"N$J$P$V##Z `"T% N"!T"!"T#$X$$%#&X#%X%&%V%^$J%X%d%V%V%R#$V"$`%%&T%^&T'N''%'T&$Z&$$$J&b'P''##b#H%T##Z"!^"#R D !"Z!VPX R"Z#X  V" P! `!X$R"T" ^#""T#^"B$R"N"#T$#""$`$R"!$L###^$V&#\%V$$X''&((P'')*&P'`(N((V('*(+L**(((X+)(b+Z**V,V*(D)P*,P+-.X,++,++*P-X,N,++++P-^++***V(^*+++-R/,/.T.T.D//^1V0\.-0f//Z2X0.-../`10V21232V/f0/`.,-,/),,H.V/V.d--.X/V/N0,++-J,f,\)'(Z*\('&V%%^%`#N%'Z&R&H'V'^'X#L%%T&#%X#T%%X%L$Z%V$$F#"R%%""#$V"bRb`TTXZZ>V^ZX^RRlHZXPTRRHV`ZZNP`RdZX T Z T T L d V L P L ^ L X P  RVXNNHVTFXP@H`RLVTJbhHPT^VNXPLV\bN^VPXR`TXN`LXVhZ\\bhRBRT\^BbPVBZL\^\RT`XJ\^F`Ff^bf@XRXL\RbjTZdTTbZ^^`\``Phb\VHFlPXbXP`D`VV\XN\\LTHTPZ^X^hJZXbb^ZVZTPdR@N\L^V^Tl\T^\\RN^PZN\RnRdTVTVhX\ZPZ^bfNf\bdbjd^bf\bZTbl^T\\\VXR^bHXVX^TL^NRVLZ^dX^X\`TbRV`^\XNVdPb`JLZR@V\FR^fJZNVT\RVRN`XP\RddZ\PTZX^PP\ZXNP^PXVHVRLVNZZRTX^JT`\XZ\R^T\PPjR`\L^V`T`RXRZHPN4RLX`VRRJ\JXTX\RPZNVXVVR\XLTPPTVXL^dXXP\ZTJXZ^VdZZ^`^LZVZN\^VZLX`XTLFTbLZ N h T Z N \ ` f T N T XR XdVLVVbXVfR`J^bXTTVV`DP`^Z^\LRbH^!d""`"X"R"!\$"!"##L##h$V"`$F#X$J!D#X%\#%%R%F'T$$T%X%Z&$N$$V%T$R&^%\&T'&d&Z%j'F(Z%R%'V''`'N&`&&%$%$H$$L#%l&%%$H%^$R$X%%#\%R$'^%\&&T&'&'T&Z&'Z&')\)')'Z(''$$$#V&%X$%%%#%$R%$%V$$V'b#J!Z$N$"$$`%Z'%$&#X%P$&%$D&Z&"Z#T$V$"T$<$^$J%^##%T%F#$J%#j)%H$&"T&%#\$L%`%$(&N&h&\%$J(%$b%f$V$H$T&X%%'V&X&"Z'`&N%"#T"V """J%J&`#b""V!!T"V$""l#"\#$Z&`%$%#$#H$P&%%%%%F(&%$$"Z%P#&%N&(P%J'%D&('$%%Z%f'R'%'V%T&T$T$T%Z$"!T%!"V "X"T b \\ ""\!! !Z!^ `#^ !P#T"^"X!" D!^!T!f!T##V"#"!!!J#d"%%%T#N##P#"R"'$%$%j(b(%)(\'(R+`)'&P'&X'()X(Z*)*)(J)()P)***)P*))R*^+,Z+*J+-R,+*)V+V*,,H-`-,P,Z+-*J,V)*\*++N-,+,b.---X000X1L1R.-//L/R0d--/\0R3/0h1b431f41.X/d/-^+^**,V-,.d-0X1X0f/P.N,Z.X-R..+f,,b()'*V'L()%%h(T$$Z%%'&(X'''%P%%$b$#$X&#J%#X&h#b$X$P$"V%f"X"!H!d\VXT ^Xddb\XTXZTVJVN@ZRZ@^ V VX V N Z R X R V ^ T ` T ` T ` Z bR ^ZRNTJ`RZTP\N`XNLRZT\TPVR^VVbLHfX^RVZZZNJTLfb\V^hb`ZXVfV`TZV``R>FXTXXbV\Zdd@dJVZRdL^dZVhPVVZTZVdP\bVTZbX\RTTXZRZT^XR`ZV^TdhTTf\bP\`RP`N^\XNRZZDbT\HZV`Pj`LfX^bV`RTXX`P`R\XZdVbXdHFV`fdTh\PT^VZpRTPPVTR^p^dTh`N`TTfNZhL\>RNFRZbFJRPJXfX^FbPPd^Z^b^jTX\NLdRRRP^lZTLRTRJ\DLFXLf\lFZRh\VNRTbNXfNbZ\NZZVZJbVTRZ^Pf\fXXZRhhPXhPR`PX^\TRPT^VTZPVNH\bFR^\T`RNTXRVTXRFR\LRhRZ\\VTN`XT^VRNX^ZX`TPV^bXhP^ T@ T Z R R T d P H \ V N LR`H`J PRXPRZXfRVXRHHLTXJHVNV\D\ZlPPV \ !j!H"!V$X#"H#"#d$"\$\#""#!Z$$\%%R&V$$$R&Z'&&f'%N&Z&Z%$d&L%d$N%&&L&d'R'R((&R''V'X'\'&%R&%%$$%#$&^&R'`%$J&%&\$`$%b%F%%'X&d(X'(^'^)P(^'&((Z()Z'R))L%')8'%\'$%%#"X$Z%$\"`%V$&Z#^$X$'T%T&%&%"R%%R%H$J(^%$&F&#^%H'l&&$#X#L$T$$T$#V$#P$#$T$#$N$$%X%b%\&&&&R%''d()(T'N'P&R%$^'R%&'"$P%%%%%^('`%R%'&#!#$\$##T&N#\#P!!Z#L$$P"%$"$%$V&R$'$&V$$J%P&''J'N%$V$T'V&\%X%`%J#X$$%N&X%\&T%T#(V'P(&P&H'b&&@&J%Z&\'%&H$"Z !!T !b"#T"P#!# "XN X F!V"b%L!L!!!X!L h!$#Z"Z$#"V"!#P!V!N!#Z#$!"!"V#"P#R%"$#H#&"!P""$X$d)%V('H'X)X%&%l(&'&%%J$P'&&\)'Z)V+*^)))J+*H)(,h*N+)*J)b,+,H,)V-*P-\*+*Z++R***N*-*b+J,R*)(V+*^+-`.T.,X/F-00N/\2F0d.0-.0R0.F.X/.Z00V3`1225252B1/0-@,N,J+h,+P-N-\..P1J.0Z.0.X.,V-.,***)J'b'V)L(`'&b%T'$b%^)%V'*Z*\*(&'%$R$$$#%T%\%"$^%P#%$b"L!X!Z$"X JbJd<XPR^<P`d^LTh^TPPZ^P\TPTN\LTd R VZ N T H ^ R H R V B X V ^ \ \ d N R R \ 0`JXRN\LbdL\XRX`LhNRX\RZPRXTPLRT\TJ\^RZFJ\PJXX`VT^XVT\NXLPPTV\\^bPZZ\`Z^V`L^^R\TXJ^`RXNP`T^TZbZTZP`RXN`hL`XX\ZX`Tb^TT\X\VfT^BHfPZX`VbbLPdJPRTZdX`X^dP`\dFXX`\XThPPHTNNhZ^`bVVV^PLRfb\^V^V^hZ^TZL`VX\VRLL`\XbPlR^RNfXn^N^f^XHJ\Tb^ZXV^^XfLV`bPRJ^ZXXZ\jDRRPbVTZJLTRhTRbdhNXX\T^TlfR\N`RZRZX`\HfZVXXTTNXZRHVPPXD^ZhX^V\N`XRZXfZV^ZXZV\TbZThXHF`XNXLT`\LXTTXRRFLTTZPPZZVJPbJZNPTNTVPXDHXXjJb\LLZP\RRTZTRRNZZZXVVZhjTZRTVLNRXV\ `X L ^ X Z X T R Z X \ V  NVdR^PdZ\jR`^L^dR\Rn^R^\VXbhfTLTX V  ""##"#P$F&%#b$R$"V%%T%$%&V%J%J%T&X$&'L%'P&T)%V&&P&X'%%`%^%%T'^%'X(T(R((\(Z*T'X)V(&&V&`'$d$$`$$`%&$%N%&&#&Z%$%%$V'\%'T&&'\*L'B''V'd(('`)^()L)\&&%(N,^'&^(H$Z$$##T$\$T%$H"V#T$$N%$h"$$f%#d'$#N'%"\(N'$%T%$^'b'%f'&$$#R'X&#V&#R#!N%#F$$J%T&&&%$'P%%L&('''Z''V'j&V'('&&&V#%%%P%V%%%&&$J&^&\)X$$\$$P$X"D#X#T"f$"!"R$%$$Z$$\$$R&&#`$V'&&Z%J'\&(Z')`&F%$Z%X(B'&%X&$$V&V%'%\'`$Z''\%F%\'B()F(V'J(Z)j&'Z##T# !`!Z! !J"" X! #`!#%V$T$#!N!V#"H" X#f#\#V$d#!R#b%T!H \!Z#P \!X \$X$"Z%$T$##"X$R#"X"R#V%L"J""Z%L%P(&^'`('R)%'*(Z'\('%(V&^)b('R((Z)X,`*+f*R(P)),P*`+P-)X*^+)V+*X)X)'P+*\**V-N-+Z,R,-)+),+`))))(H*-^+-J+V..R0Z1^0R1b/\0-\.---/0.H211`4352J34\1X4^1X3//,l.T/*N---,00\.00.-T+\.X.,-^+*)\*T(R'L'Z)B(b&R(%T&)&\('(('%&^'%&%\%$L'&$&D%T&#R$!#Z#`$!!!d!R!X! T ^TTd `^PRT`ZVX^`PVh^bXR^R^THRVV\L^T^VTb dR j ^ b \ T ^ d P L ^ T Z L R T @ P TX\\NXTLbXNZZVdZZZNL^X\bffR^P^VV^fVNPV`XV^HXVbR^TTN`^JTN\^PRXTblRZRRV^ZZ^bRX\VX`V\Z\d^Z\^ZTT`XZX^Z\Z`\FZ`Vb^VF`DZRbP\XLhPdHRZLTRNXbdTV\fNX6ZLVbjXX\bVZV`b`PPPJbbTJTZ\TVXXLZNRdRh`^fffB`\f^p\bVb`^Z^VjbRN\VdVbT^XXdRNfLbLTdNbT\X\ZTRb`XbZXXXP\XZT`ZLRP\TVRRXTRN``PR`PV\TXPfLb2VRdZPZN`TZZVNZXVPZVXT^TFPVN\RV^fTPZDdHXPZ^ZNLXV`BTXZRVZ^V\T^ZTTPbJ\NHTPX\VJbhZNXVVXHXRXVR`\L\RVRPTdJXRfPLRVPVNFZ ^R  X Z J Z R Z >  NRZTXNLZ^V`PXHZTTXPVZNJdH^^TJFR`hPNV !#Z#V"X"L##Z"X&f$H%X$f$%^$#Z%R$$%%'&%X(&(`'N(L'Z%T%Z&$R)&%`'R&P'`'&''%&')(J*)**P*f*P(T(&%^&V&b$$&%$&P%V%$J%^%X$X$b%T$\'$T&&&&\'$Z((()R((N')')'R''f)((T(^'L%&$"!%%$Z%f&%V$\%#P$P&T%%L$`'$&\'V%$'^&T&'R'J)B'Z'T%X&%%&'V&&b&#^%J%R%'Z&#L&R$#`$J'V&%T'T%%''%&(&`&)P&R'&L(X%'b'`'R%X'$$b%V'd&&N(Z('$$%^'%(%&b&#$b%"Z#^#%#\#\"B%%J'X'B%R$H$X&$R#X$$'T$(L)Z(R''P'L&V'$N%%'\&%$J'R$L'$&\('J&V(L$%V'&`'`'d''X'&''`"V##T"P!"P!"$V$b$"#\V J !X""&V&$b$#"X$h#T%R%#T$$#$L$N"#T"!# "!"\#8$^#N"R# #" !R$T"V"R##V$!J!#H#&F&&\(T')Z(J'T&T'&`'T&Z'X'H&P''(V$V(^''*R*+*,\)L+d*Z*N+J,+J+*V+Z*P,T-(Z*Z))J-))+-@.-+b+**T*X*\++b+)Z)+R,L+*X,P.\/R0X/1/\0/.\0d/-1V-12\23\2V537\42342T5/V0\2/,d+-T+P.-.+@.-.^/>/+^/T,P.L-V,^.\-*'T)b%&V'&`&d(N'T)''b'(+(F*'@+X((P'&L'J%R%%L&%'X&&X%&#V$R#!T d!\"J"P \ Z ZX"^N!dTFX^VXZXNTLn^^^ZR^\J`bdLX\PX X T \ d Z N X b L ^ h R\ ZXJ^LbTVVbfPRVdPX`PNf^PPTRNJn\X>`ZVR\J^`^XN^ZPZR\Tf^V\^THbX^F^L\HV>nZPLZ`^^`LFX\Nh\l^P`BVVVdfXVR`PjhPPL\dHZb^NVRfT\f^fVFVTXVLZZbZ\dV^bVX`\TX\^Td\VHl^RXT`PPTV\^Z^VX`\XdV``LTfVZdZRVTbV`\bTjXdbTbbf^VZ\fpLZVTRTX^X`ZZ\\bZbjXHZXd`Xb`XP^hNRbBR^TbXdbbXd^VZPRXXTV\Vj\PNbPT^ZVXNR^N^PfhZ`RV\\PZ^ZZJV^bV`RR\RXJdVTLl\THXbN\XT^J\^`V^XXbZJ`ZL\PZ^\XdZXT`ZZ^f``RXJZbNV`RRRT\XJ^\VP`LX^XT^T\PTZ\P^\ NZF`VX^  N X JZ T J Z X h j X b X ` R b ZVR\ZJVRNZLVLZTdXZRX\\fNX\Xb\^bLD\`bLlRZ\!Z ^ ""P"P$#"&`&P$P$%J%$N%Z$#&$$%R'&J&(V'&X)&X'&%%%F(l(V&T&Z'V(&%V&&&^(N'(\+X(X+`()L))(^'&'N%%\(%R&^&\($T$T&f'%T%N%$&"&'Z('T(^&`&H(()(((Z*')P)R()V((X(R'(b*T'V'T$$##""b$&`$%$\%%N'&R%&X&$$%%P%'X'&R(Z&%`'Z&('V(%N((N)&&%N$%%R$$(R&\%X&X$f$%X#V$&H'&%&N&\&^(&d'Z(V&''')\&%T%%$N'%`&j'&$%X($&(%''%T%d'B%d&R$#X$f##&T&$%%^%X&`&'Z%%&&$^'Z$&L&b%$&Z$H'L&V)X(`&&%%&X&V%&`%X"T$X%%%R%Z(&%^&%V'%Z)&'f(X'%^$X#!"V"#\"X$X"R!#%#X"#^!!N!Z #X!#%#%&&R%X%#b'(%#"F"%#"b#!\!!!N!^#^#"%X!X%\!d"!!N$"H#""#L#"%$V%$L&&b('(J(j(&&&X'(('&'''@('&&J(b)^,,\,b0.\+X*R*+*++b,+)P)))')R*`-P-X,,+,^-++)))`+f*-V,*+*L*^+^-,^-..01\21T1/^.0X/,0//0^0123^722N33H0n4\/0..\.Z,,B-X.^+^-@0T0X---^/X-+d-J-H-\,N,\+T+'T&P%&&&T'l'(((R*(T+V*(\'F*(R(&(%&L&b(V#X'%&L'b%P%V%\$%d# Z#!V!!!T# D \ N P! R! VVXVP@XTbZhVRZT\NPJT^XRVTVjD L `R X \ ` N \ ^ X T P P V R T N Z JT \\ VR`TJZb^RRTVTdXLPNXHHPNTb^b^\LJ\l\ZP^NLNVZNRVbPZVVRVJNVTZPRPZbLVPTR\dXZJD^ffJT`dZV`XJVRVTVTZ`P^XRHTVTT\bX\hbdXNdXZXL^^L^TXLDHTZ\Z`^fb\\\L^TfXP`\\RXP^\hZ^PZThbVh^\bZTZVTTRD^VXLNZNRR`TR`PnHZffXH\fXVR^hVJV\`T`T^ZVbRJ^`JV`VT`L^PVVTd\\DRRVVHPZ`X^\PVbZVJp^bTV^hN`VfV\JXNVJF\\NRFPZTX^f`TTZZJTVXJfJ^F\RbN`bLbJ^TRNLZ^NX\JfTX\VZJPZZV\\RFfRT`VPTb\RZRfXTRfNPNNPLTTZXJ\RZZbP\`RdZTJhTR\Pd`TT`ZNPXPTRDTZdFVV`RVZP`XXRNHNHVV^ RZZ N   N P \ Z Z R R ^ ` LV b`\ZVVLbR^RVVdVPXX^X\bVJJVNfHZPVJb ^ \L!Z!"!$#h"%%F#L%R%%%H'%&%'X((%\('J)'B)T&V&%N'#^%%F$`&'J((''''J(&&\')Z(R)*^((`))L()'T%$b'J&&N%%#b$P'Z(R'b&X&\&$R%$$^(F&(R&Z'%'(R&&))N'Z*F)R&`))(()X*\)(T&)X(N$^$$%H##%&b'X%&&%&&%R$Z%H%'Z%%'b&&b&Z&&&J''X)'V((`)'Z)((L$N%T'%Z$D&$b''$#:&$%'R(R&'X'&%&'''((N)Z(')P''%%^&N%&'T'%&&`(J''H%V(T'`'%X('N(X'X$&T%&^$%N&h&(''N(')'\%J'%R&%R'`$V%&&P&%%$&&)P'V(%P$L&L&`#$`%##T%$N'Z(B'&\&8&%%&N'L$^&$T$R%\$Z$b$R##"d# L$d#R#T"!V"!"T"L##Z"L###%L##H$$'#T'"\&#"$X$"h#"N"b"X##%!J##$#X"`$"^#$T#"L##P#X"V$P$%h$Z&V(&&%P&%V%R&`'T%''J'Z(b(\&Z'&L(^((R+V)T,,*+-Z.,Z*R+-+\+V*+*)R+)*P*X-,+V,+,,+V+*V)+Z)\)+X**X,+*D+T+*Z-N-\,>--Z10\1V0`/T0R/T/0R0V/J//211^30Z2T12`1`1T1H/b1/P0`/^/T,*/-X-b,+N--Z.-Z-N,,.R-,-+'(^)(R#`&(X(b'*R*'Z*Z'V,(^))+'R(h)R'('P&Z$$&&Z'%&X%P%$#V"H%#R#!!Z"!!b!!` X!! "X"X$ P\XVRLfHJfN`^^`NVdJb\ZT`^RhV\TXNXX^ ^ d T T Z \ J \ Z T VPJTfJLTJZZ\ZPbVPVbPVXVTRPXR`VRfXRLL\P`bR\T`b^^TPR\PRX\TXbZZXP`RL^JRJ^TXV\PHH^VZTXfT\L^X`Z^NXZT^NXXVP`dP\PfHRXZ`bdVZ`\TVXNXZR\Z^ZRX`VdZNVZR8bR`^fX\NlR\P^X`V^^TZXP\\bZRPLdV\X^hV^df`J\bV`^rVR^fZTRXVjZbX`ZbX\fXRPPdV`VV^`XT\Z^bX``RXbXJdVXN^ZV\XTTFbd\VTX\dX^NVTRXZTbXVV\JHJXNX^^@ZJ\VZXVfbVZTRRPJ^XhRVPRP\XLHh^VDT\b\^^\P\ZX^b^RdRbRN\FRXLP\NFT^JVbbTNZXbTH`N^^^RVXZTRb^^ThXTTTH\JNT\bZX^TTP`PPT\N\Z Z X N P P ^ \ L Z T V^VXXZJVV\bXfXZVXd`VHZZVVZdJNLF`XRNTV T N b!!X"\&\!b$&&&%%%&$N'N&X&L(%'J'''X(R(X'&'@&^'X'\%Z'&T'Z'(&V(H)'*N(Z,(V)(((()N*+(^)R(h(&V%`)Z'&&(N%R'&d$Z%Z&L%'`%`%X'^&&'&P*^'J&'^&N'\&Z'X'))P)J(T)d((+**(*'&%'&P%X%%X%%T%&V)\&(&%'%&'R'N%f&T&d&<*((\'R'(\(d)&J('(((X)&R&>'$X%%$V&#&%X%d$J'J'&&R)()&%&(d(*)X(\'))X')N'''&$B)X%&^&j&L'R('**\*'\)+D*&R&^&%'X%%#%%&'&X'Z'(('\'N%$'f(\&(N'%Z%#^$$F&$%T&V'%N&V$&\%$R$X$$N"`$##Z%T&^%'T&&N($j(L'X&%^&'b'\%X&V$#""N"#"d$P#R!J!Z!P"""Z"P"#R"T$"T&%$J#T$B#Z#F&N&#X&"P"X$##"V%!T#X#$#V$b"P#b%P%H$#Z(##%%#L%Z$N$#d$&%\()V%Z&&R&V%%T'%b(&T''R('J*'L((R((d))X*\,**+T+*L,\-.X.,N++J*Z(R*X)T**T+b-Z./T.N-T-f+X,V)P+^*T+*Z(+R)^,+R,0V/V,J.T.R.^0`.>1R.Z/V1.,T././X/Z2244T0X020X22d304P12`/0..P-+,Z/+J+-V1D-0/,R/1L.,*V,T++\)L)Z&&^'\'T(F(V('\(&R()*(Z)^+X'R(X*T)\&'\&&`%Z'Z%P%&R$$%6%#R"#$"%`#Z!V$J!T"!Z "h "! !Z! \ N\\VZNbRTXN^bVTZTXXT^VbR`ZJbnJ\TZN V b b F f R P Z d R Z X N ^ Ll PFZPXZXNT^TffTXRPXbLdNTZ^NPPZV:`L^ZZXZbblbVPbfVP\PT^NX^\ff^VTRZ``NhP`XdXN\\ZdL\XRdXVXVXP\N`RXbJJP\PRd\FVTLjTLhX\R`Z^TT\`hZRXZX`VP^^V^bfXXdRZ^ZZPd\\HRhbFbZb\ZbXZbRPFjbJ^\lXL^`R`RfXPRTHNh^ZXL@^Z^`XXTLhfXLfR`THZZ\LX^b`JVRTH\`LXB`VTX\NZZNTVVX\RT\T\Z\ZNVTTV`LRXVPRPTD\Z`HdXZ`\bT\L^LdZX`Z`NfTR^\LPfPThlH`b^XHbJVZVNT\ZP^`PfJXXJV^NVJL\TXDVR^ZXJ^JTRFP\PbDPJNXXh\TX`\LTZ\\XPT\XNVRZ`VR@^\R`^NRd`P`ZP ^N \ Z \ ^ \ f \ \ \\ \TTZT^\`hLP\\LfT^XX^Lb\^T`ZZPRFbX\d\\VX\ !N! !T#X$F$D%Z$&$V$&%%%\& *('''(\('R'Z(Z(()\'V'd'D)Z$\(V'\&'Z'((j'J(*(L**(*P+*Z(F*N('(H)*(V*N)R&`&'X'F(J(&`%'`%$%#P'%f&%\'%V%&V%^'T(&(T(&L((^%(&T()'D(T(R(^)*R(&T'`&(\&%&%%%\&%)'(L*)R%Z'$R&$R%&R(&(b('\*J+X()'R()('\'H+'>*h(J'T%&$\%J%H%L$%P&&@&P&&(N)(b)'&'&`'Z*&'('R*)(f,)R)V'(&@(&%\%%%'d((*\)H(V(D(b((%X(&P%'V'D&%Z%N&'%&&'&V)&Z(&N'P(R(^%%&V%\&#%^'&'&f'L(\&%Z&%%^$&N'$F&&%'&(')&'b'R''&L(%X%R)P%L&#$\#"\##Z"F"%!"V""!X&"X"!X#T#^%'%d'V$L"#"%V$$&%&#%"X#"#$##Z#L###$'P'&#Z%&%"$$$#%%%)%d)%X%R'%d&b&L&T&)(H)((\)X(R))(V)*(P+^*J***T+,(++\/L,/V-T+V+++*+(+,R,/+,+,*V+-*T,*++h.Z,,,-,R.T,R--V..-,.0//V-,Z//1P10H2300X12J23B4Z11\/X..1f0/h/P,,R+B,,X,J./N+Z20.-T-Z,X+*V*L*'''X&)F'f&T*+^)X)**T*)X(V)X))\*N)`+J)T%'X&$%%R%^%R&H%H%%#""%&R#&F$"Z#P"$V$"!N# f!R$T$P!N$bfX\R^Fb^RR\dbNJXVVXNZ^\V \\V VXR T  P Z V N ` V N X X P J XdD LPV`J TDNLbTRZZH\N\T\TDNZRTTFVLR^NV^bdVXXNLTLZX^TTLPPTZHV\ZZLNPNbdH\T`VRZPVVbVRVVZ\JN`d\^\RVNT\`TdR\^VRVH`T^\bZX\NT`TXRRXVbN^`dZ``PZTNZbXbRfZZRPbVfXRjZdRXVHTVJXRTZJ@P`TbV4XVb^\b8R^\TN^\R^X`H`VNdTZRlXXXT\VLR\Xd\`ZTZZNZ\J^TfX\VV\RL^VbVN`TR\Xf\bXTZRL`X\VTRh\bT^NbTbPTN^\nTdVHLZ^TdXbRnHXFX`XR`dXJbP\\PV\XTLJbVNZZ^PdVhTTZbRZVPVJPVPZ^P`PRJVd`PPR\ffdX\ZXXXbXZVTXVRNXdVVTZ\XXPLbFHTXL\\R^VRXNN>\ F ` R Z L ^ \ T Z ` N ^  TPZXbTZN^LP`VPRjXZRXXT\ZX^^\ZNZVV" \"Z"X%V&$$V%'#X&%%&$V&(&'('N(V(\()))&`'&'h'J'P&%%(^)P'(`*Z*)')V))(+*\++N)(^)((()`('(&d)L))'X)&%Z&P'%R&R&L%&(&P&%%H&%'#)&N'%&'X()^*R((('b)'T)N'd&^(&'Z')R((Z)Z&%&''Z(&'^%T&%^'P(&((X'J((X)Z**()d('N(T*`*X(N'J)X)'%V'\'\%%&\%$%&%`&\'T$V'R%V&(T)d*P(b''(P('\*()Z))b*^*R(*L))\&(%R&$&$(\(V((*)R())V''`)J'%&&('%)V((P)'P'\*((Z)^(X(T)\'%L&^&Z%X&P&%&$N'&'&P'&%Z&$B#$$%&b(H(R()N)P'H(`(H'X(L)'J)f%&R&(&%%&##N#f$T"%#R$V&#$Z&\$R$T$!$N$T%&T%#"Z"%d#%$^$P'#\%P%\#""d#!T#"T#$%R$j'%'(''$%%$^%%b%h%P&'&Z(P&&&(&J('N&&R'X&%'b'Z(b-((d)))X*T)N*d,)R,\++,))-P+-+/+*T,++X,*`--+,X+/^,*+)d,+,+,b)R/-N+X-P.\-Z-\,Z+J/P--j,-,,^.-^02f////J4d31P0`2/2132100X1`/d/.L/V-+Z+,++.`,.R-.H1\.V.,+,P+T+T),'(V''+Z)(*R))L+,<*()),*d*H*)J'R(^&(L'%"\&P$$%$`%%T$$$`&N%T&$X#`#P'#$Z#N" X"L!!X""V$V# \ZFLbVXF\NTVdN\HbPVH\\\N`V\XPPX\NR ` P Z N ^ VR^ P J `XV\XZPdXb\HfVHVTP^`ZRV`fJb\ZRT^HXNhVDT`HJdVZFTZbJTFdHTRXNV`TNXRbfZV`VThBN\ ZRXZ\ZNX\^bNT^VT\bR\XXdZPfXh\\ZXZ\Z`VPPV`F\^dX\\\X\XN^XdTNNLXZXVVPZLD^`bXbdbP``RXf^^N^RVdZ\^TbFVLXVT`TZXdTTPbX\RV^VRLRP`N\bRbdRbXhRh`Z\hZRZ\\`Z^X\hZXVT\Z\XbNVdVRFRP^NXXZZZJNZLNZPHR^`PV`TLVXTbTFTHdVRXXVPRRhNbHjLVZ^XPTLbHRFV@ZTLRPPHXTHV>jZL`ZVVZL``Z\TR\TXdbLXVHX`PRPL`X`VZHTXJRVRN@JJ`P\XZVVNXTHXPNTZXbR\ZLVR@XZT^THZ^XbH`VLXZTRdT T X L \ \ R f TNVXH ZXRNZ`\ZZTZ^^XR^LVPVRN`J ` Z!bL#$"T#b%J$V%H$$%P$\#$&\%P&%R*&(N&X*&d(T(^(L*h*(T(Z'P('\('('(((V(H)(J(b)*(T+*\+,,d,)J,T)((X(F'(N()H'X)X&'(')&&&&$T'`'V)(V(&&\''(X(^'''(&)J*(V(()'N(T&T('^((V'J(b('%(\'''T(R&%$&P'R%R'Z)\&f())X'R(X(F)L((R)(X)'\((&(B((P*(l)P(J(X&&T'X&R& (&'&^&Z'%%'$(Z(Z(+**()b((X+)J(R(^))*+T,P)(\'N(&&R&(V&'H)^(((F(X(L)(^(X)P)(P&&\*()(*R)'((P)(X)X)V((R)T)T(&^'R&$\&'&(('L(&\((d(^(T'\&h$$N&d(%(R+'P)'(')\(X('*d&&)&%Z&%$'$$%X&$$N%&$$D%%%$#R"#$$$P%%$#b&$b&$#P$#$Z##\##"T"H"L#L$#$%T&'%H(%Z%Z&L(%V&'$&^(V'&N''(Z(&)'V((&R&N&&b)\*H)X*T(\+X++R(L*'(H('N-),-*,L*N**,R,+h)X+D)X+Z+\-+\+,-,P++++R-h+\*\++*j+X.V.N/-L0-/-+,L,*Z+*+^-P+`,..,./X0X//V11Z10b2X10V3R3200\0.d/X0T0d.R-+\-\++R.\.N.b.\0\//X,+P+V+`+*J(L(Z'(&T(P*)(*)(Z*)R**R**Z*)F(+*R*\)('\%%N&R$`#"H"`##N$V#'X$X%V%N%#$R#P%b$$"F# ""V$"J""Z!!VVXRXX^PHbN`ZPR`\XJRNR\X\b^VRd^N \P ` \ D V H R T Rb L Z XL ^ TRPR\L``>PRN^^TdXPXZDfT\`RFNVXNR^f`VfPRZ\fTXV`PLVbBZVLVZNbPRPJV`Xr`XXRdXN^ZNVd^LlX\RN^RXXJZRVXfPJbXbVXJ^XTTVZP^ZZPFjLPZXRV^bTnRPd\LRV`JTd\RNLZdNRjRbhNPRXXXTZfZRR`NJjfdVZZ`R^^^bXjVZ`XdNfb\N\\X\RZXRjVb\fb`TdTTPZ`TPX`PfVjTVjVDXVd\fXB^`ZZ\^X``d\ZV`lXVRZ\XbPPTV``V\VZ^LZZ^NfRZT`\X^`L\ZTZ`^RPdfbL^PTR^dVTPbXbZPXDTVXXVRV`V\NVXZ^ZV`XHfVTXbb`\P\RZNPVXZHPVbbFVZLR^XJRXHlVPZfRLfVTZJ\FRXXXJRf^VT\d`PL^`VN`TXRLRdhR L f  b d l b N X R X N\dXLdTJHPTZTTB^h^TXZVRT b \! ` V"X $X"#b%`"B!X$%%b$###$$%T'''V&Z('X''(''*J(R)B(*R'X''D*((X)\*)((*P)H*^)*X*b-,+P+)R+)(P(&&Z'V*((*V)+P)*'V'&\%&R+d(&T)&`(P)(@''**R(b+P*(J((X(X)((F*(P)V(Z))L&'%V'P)'Z(T&(\''b(&R&V'V&Z('')*b)V(\)X))'F(*)X+R)H)'`&\)`)(T*'(^(Z*^*P)h'R&'R%((&%X%%T&Z(T'('Z(Z*N-))X+X(R))X*')+R**,,V+((V*N'((%((R&(V'(R*N*b(\)T)X)X''*T(\+'(&+F**()T+X*\)(^)(R+L*+)*\+T)(Z'H''T()(X(N&L%V('(T('%J%d&&%H'\(&P*)(\((R''*F(^(\()&T)V'%)'N%N%d&$f'#V&$N&()\&V&%T'%^&X(X&$%P$#\#$"$$#&#%$$"b%b%#^$$#L%Z$\&&%b%&T'$%R&%'J(&N&V()(X*T)D'P)V&&'D'^''((N'&\+V)L**V+*P()f*F()('X(X(++h+h.*)+*N,T*)B,*+H-,,H++-/N+T/J/-..++)\-V,)X,+.0/,/\0-R,d*)T+*)^,Z*Z*Z,V/R0\0L.b/.R10/\3Z2P/T210T1h0/1011Z1b.0-V-X-+,d,^//P-.0-`.V-++*P)N+)^)V)')Z(*)V)H*^*+*-T+T+V+*)D*^*)X((`(*V&`%T#%R#$#"V$V%%$V%T%%P%$\'F%#$R$%%$\#R$##$\"$!H R!FN\`V`PPZ\TZbN`P^TBXN`\bJRNP^PV ^ ^ \ V T ` ^ R f d  d NZZd\R^XRVTT^\J^NTR^nFXN^ZTXXTRVXb\ZJ\NXZ^TZRRRnLX^Z\ZR^T\DVV\VZ\\NdRd^XPJ\\`^PXZV`NXZXRZNVRdTVLdFRP\L\\Z^^^Tfh^VXLZ\^`R\T^TZXZdJ^hVVLXXVNZXN^fXV^T\`bbXV\XXfVRPddPb^JX^Td\dTH^XTPPXVndTf\^`T\\TX`XXbXZ`XZTRRXXNlHLXXXFhP\\BRN\LHfV`NT^X`dFP`XR^NZL`V\dThPV\RF^PNRTHV`<RNRXVVRTJhV^VXPN\LVXTXRVZ^TN`^XVR^XRPT\T`TTTPBPPPfX^FN\R>fVV^d^b<TD\^\TbJRLRRZR\\\ZRPHNRR\^^dPR`XdDX\ZX`NT`ZVPXRVX X b Z Z X Z P R T b X R\bZZ\ZX`dZTXHNVb`TfdBLXV^XL ^b \"Z!!"!"B$!&#"$%R%%$V(`%\'%h%V%X%Z'V'\('(P(`((Z**(F)*X)^)P)))(N*)J+V+'(+',`*N.)*L*X),+T+N),P*T*N((R((P)D+)(N*V*T*b*J&V'N%%f'X&%(Z(V)'\('\)`)((\*)(N(L)X**P'')`-T)'+X)T)*'T')T&`()'^(&'h'L'^'')R'V()T+L)*)*'P()(X*''(J&''Z'V(R&&*Z*J)V'T'N*'(&V)'&&T&&J(%R&(L'h(L(Z*'))T*J+(R)J)*T,\+*,+,),\*,d)T)'V'X'''*`*X)V+P-)\* +L'*(*T**B+*j+X*X,(X-R+R+,))\)*)V++*V+Z)(T(X'P*'@(D(P(X&&R'V)'J'\'&\'&(R('`()'))D(+(,'>''L&(X'b%%b%%%P((^%J%$\$L%%V%Z(&''%N)'$\%T$#%%$X&%V%$$F&$X$N#$&f!b$T$^"&\$b$$N$%b%T$R&$h&N'$%%Z(''N))(d(**((L()T(V'T'R)((T)T)T+`(Z))()J+(Z()*Z+,N(V*V*^+*\*+*V,*L)+V+*T,V-N,<0X-b++Z,b-/Z-D-b+-`++V*)R+*V/V/.R/,/\--Z/,X-)X*)()V,*\,d+-L/,V..,B+-01R10/X/P2/11/R1^1T110F0b1L-Z++.+P.Z.0J/V/X-R.,\,V,+*F)N*V*'\()N)b))-H+N+V*`+F-+\+N-,P+*)'()(@'&X$Z&^$%#&$#$V%'%P&\&$&\'H(%R$&$&D&h#@$`#%\###\">"` " NNPXT\\V^TNPXRLXR`B^BHTR^T\^X\`XJXXRTX R Z ^ P f P : R d R nXDZTRFVfXNTJR8NTbV^N`P\LN\XT\TF\Vb\fRRbP\n^^\BZ`XVTbX\ZN\TZNJbPV\VdXXZ`^JVLbT\fP^\VbNV\TPPXXLfbXVR^ZRLNT^\hX\NbX`LXPXX`NbfX\^\Z``ZZR`ffZX\LNFX^^N\Tb\\\PVRhdN^N`X`TFTLVV\BZZTT`Z\`P\^v\dl^ZVd^```^bTTZbZJZd`dh`R\XP`ZXH^NRXRVVf`LZpXPVT^JRfRfdfdR\RRTV`B`RTZfFLfVZ\VPXbVXZ\VZTPXRZ^fX^\PNXdZ\NNbZX^V\RXDZJ`RVXhHV^b\X\l^jZXX\VZR\TFJZXRdTTZFL\NTHXVXXRXRNXVTPVRXRZ\XZPRdbRZNJF`\FT^^VNjPTNZV\Vdb\VXl`fN \ V Z  V P T T^`V^RXJ\`\P\N\ZNV\FhbVJPVbV   \!!#^%$`$'`&N&'X(T%V&`%\''`'R&Z)&''&&T,*R(L(D,^,b)L****\)L+*N)\,)F*X*d)Z)((R+(X+*B(V*)X(T.+h,(+J(V)\+T(`)T,R*b)+N)b(V)'&R%'D&Z&d%D'^&&T(+N(\(R(,(b)H)\)*R)\)T(^(T+X*T(*V)R()V)^)Z(R'R)Z((Z*J(N)'N'(`&%(('`*)Z(Z)*((X*&('('&J'\''X)T)'X'P&\)T(X*\)*F'^)b')(P'V)'^(R'&V&b'`)('V(V(()V--*N**R+*+,-R-V,\,Z+++*Z)T)V'd'')&(Z*)\)Z,R-Z++*V+V+X*+-*++\,*d+*R+*N*L*Z+P)d)^*^(J*T*()H*b)N(P)'L(N)'\'L&Z*J('J&'&((V(*)(^)()L*(**X+V(H(P%T&T%X'%$P'%Z%Z'j(%\&%('&b&&'%$X'Z&''(D'X+'f(N&%X$\%P$N$\(T%b$L$^$$`%#L%Z#%X#$X%R%#%V''j&%X&^%%^&^&d('+X)*)*b+Z*)()\'J*T''(*L*+(')Z*)^)V,V(('()+f+J-+`*Z-*\*(P*H)+T,*L*++T-X*l-X0+N,J,,d,-*V++b-P+X,+^*-,+Z+.-P.^/\.^.++()'J(*(\*,-,\,T.V+P.-`./X1X/V020N0/R01Z1/0T1\/J10/.,D,Z--/-P-V0`..d.+,^*+L)Z+R***(()\,,\-\+,N+.*,+T+d+/X++\+*''>&h'F&$Z%V$^&f%$Z%%$%Z&&*^(N&'$'%&"P&Z#$f#V"X"R"Z!L#d !"V bXRZ@TNXP^^Xd^VNNR^^BVVT^XhVJ`LZT^`Z \ b d f ^ b R T X X ` N N RbZZTVVXXRb``V^NNPP\`R^VdZb^TFPZbRVbXVVRb`ZXVTVNVV`\\NZJNJXTRXR`NXXf\Z^RJdZ\Z^ZlR\`bVdbNRdbVDXZVXbJ\`ZXTLbL`\RRXdnLZTTPJ\RXNX`\VJZbbXRjXfXZZ^Tf^XDb<hhRD\Z^^dRbV`FPXV^R\`\\bZdVTXR`LRTL\LdNFRZ^^TP`\\NL^`XJ\ZRTjVP\XhTZXZD\^`VPTZ`PbX^T`LP`VNfjBVhVRXb\`LdPZNZ\NXTN\PTLPL\XNVP`XXNVZVZFbRdJ`JdfVRfNZX\H`^LZ`XP\LPVJXVTb`ZLZbXRTTNZ^HRVX\P\R\XZX\NNZR^DZNR`\ZN\XDZTJ^FZR^NdPVLZVRPNLT`JNPTRL` f T V ` R \ R L Z NZLFTJN\J\V^ZVR^F`XTT```RV\ZPV`Rd^ P  ^!#!$#P#$'$%f&J'Z&V$&%&J)&D''Z(&(P)'(')b(*,--P,V*T+Z*X-)\+)X)Z+)*)^*Z(J*b*\,R**`*+^)-R++++P+'R')*Z)*f**X+*)'L(f&\)P*'')%&Z((X*Z+J(L*)J(Z)(h+(*(T'X(V)f)T-X*T)*N'&'X'T(R()(P((X(&''&Z&P(`*F().`-((P*'V'R%&R'`()*T,X((Z''`&&&'&&&'$T'^&&@(Z((&&V&L'\((J)V)'')(\)>+*\---Z,+X--,*X*).)^(((T,^()'(X,L+)V,,P.,+L,Z*L+.-b-.X-,.-\-\-N++`,N*L,*X*V,L(V*L)T)R)Z)F)'P)X)L(('\''N)V'(X+)P)&V('&(\*(N**'&N'*')&V'V('('\&#%$N%&\('(h)'\(L(&R%R&&H'R'Z'T((`&$'&%T&&X%L&$$N&T&^&%%$##X$&X&V%&&%Z&\$Z'D&b''V%Z%\(X'V'\&'L(T*P+(P+***T)'`'R)(X*(J(+Z+,*N,Z)*^*H)+)`)N(*^*h-(*Z,R0,F,h+*V'L),+^*b+\+++\,R,P-^*V*+*,/T,,V,R++J)R+H*R.f.@--\.^/-\+T,,D)h+(<()'),T+j.+^./L,X0..T-.P1X1^3`/11Z4R3`11//T/^.P.D./d,.+N/0-,d,N+,**F+*X*j*++,*+\))V()V+,*`-,Z,Z+++N),*d)+-*L*\''R%&T$$$$%X&T&\'H&@&&\''T)&*%&&$$\$%Z#!b#`"R$"Z%P#P! f"LPXRdbHTbV^PZV`PjNX^J\NV`XXLbTRTZRJXLNVNP T Z V ` N d V V V H F  ` Z \ ZZ H XfZZNPRFfZRXPXR\J\PRTTNP\VfZ\T`\TZ\NbJTR`ZVb^LdPRNZV`b`P^\TFd`LbTX\NPPTRPZ@TPXRXZTH^T^X^^Vd`ZXV\fN\JPRZVZR\\VPX^ZXXBTh`Z\VZJT^`TP^\RbJXZ`PdNRTRPN^NPNPRj\pbV^`b\j^bRX\dPZLZZV`^VhdZ^J\\^V^lVFjVXNRR^VV`dZ\ZV`^JjDVTHTTfRdHT\NZTVLV`XTXPNV\TdJNVX\V``PTPj\XXXVdVHR^VRN``T^^ZVFZXRdJTP\bTLXTLXZXZ`VTLTVZRZbXdP^hTXRZPNXRLXfHRbZZ\TVR``TbbRD^^HVZVRRXLX`N\@XPNZZFfPXZR``ZLhfb\H`XRRZTRF RXD f  ^ T R T V V `\PTZRRVVRRVTXRV`XbVh\dVNP^ZTX ` Z !!T! $T$`%#$$J#`%&'&Z&Z&X''`'V''^(>'R'(R&(()T+)+V+R,X*D+,,+R-T+,)R)V,*+f,R-T*+)\*(R*)+*B+++F,^,L*B+)\))**+P('X)X+'\(^&Z(&Z&)V&&&)N+(V)())(***R(&X(^*b)(+V+F-T,D*P)P'%''b('(N+^&V*)B'N'&()N()((X)(*b)(T&d&T&&^*++N+H,f)(Z(&&b)('^'b'V(Z&%F((&H((`)L'Z)*(\***)V('L)Z,X*./T.R-V,,,-h,++\*f)T*)`+X*V+))+d+n+D-Z,Z-`-T-R-R/,\+,T,Z-,T-+.//.,F,b,*)\)V*)T*^)`*,*^()V*T*^*R)*P)N*(*(,^(('Z)L(&h'P()*b(T('\'(&'L(P('P)(P*((%Z(^%`(Z&'V'&(`'&^&\&%&')Z&H*)'^(Z'%'$#%T%V'%R$X(&"^'$$d$&%$f%V&%T&R'b(&b(`(b*L&N$L&&`'&'H((Z'R,R)b)T+L)*L)('N*(+J)(\**d*,))+X)*L+f*+(P)L+\*P+)+Z-Z-^,V*'V()P()P**)`.L-\,,-,X,J-V**V*V.,,*b-+-^,X*,V-^-.R-,V,+\*)'X'(R'(R*(P*Z*+,\-1R/T+T/-0X.-.0Z/2122.R0f/.,R/^.T...,/-,,+,T*H(*N+,)L+`-R+^-*()Z*T*-+V*,+,H.^/,*.Z+*j)+`*()T'X''^%%V%^&H#%R&X&(('$^('\)'&&Z'T%Z(D%d&h$L%#b%$^$!$X##! X!FR ^lV\DXRRVjPfPVXZ^NRlTVZVXbXbTRRVTN\ X L X T P ^ j VbRRNRLPRdXjTBPL^TZZPZVL\X^XRTRRbTVjNLXbXZVR^NNbPZ`ZVTRXRVVVZXRPVT`XTbdRbfTPLVZ```\XVX^V\VZXXbTbPNNRRX^LJVfVVZVVn`R\dPR\HZRddbX^Zd\X\THTXd\LdZ\T^^Z\ZTfP^^ZR`^P^V^\\\V^dbT`VX^^TZZdZNjbXTT`ZZJR`ZZZfZ\PLf^^VVRZdXT`\TZ^`\\VFVbRZZ@ZTTT\TbPPD`T^Z^ZDLR`NZZX\NFVPVPP^P^L``ZXbR^``H^\P`LPXZFZTf^PR^THV\JZT^ZPbbdVVPX`Z`FbhJfPPRF^\ZTbL@LXVN`<R\LZZ\^HXHT^VTPTPNZVZf\\ZTXVZb^`V^RTRF^hXVbZXZP\LXXLZT Z\ T ` \ X b V T X  Z^T ZbHR\^XPTJFT^^bRH\ZXZL^J NbT"X`f "Z$!^#!L"V$#$<$"V#b$$$V'%'V'''''d)(()*^+(R,\*f,D+`*,V+,+,..-R.\,T*F,J*\++Z(++J,T)R,R*))T*V***b+-,R+*R-)X)*+N+(V&T)L((*'P'P'Z&Z&&b'')*L))Z-^)V)T+((&^,^)()P)'P*Z*L+P)&(T&'R%b(T)J(&&\'Z)%P'&X)&Z(^)F&(N'b)`&N')V+('%&^((+,,*R*N*d*\'J'T(R(^(R'(R)H)%(\&&((Z*T)^)')*)X(+*V-`-*+f,P2,,-N-.,X..-.(`+)b*\*(X(+)b,`-J-P-+/J.F1`0J./-+N,d-,.-N.\/-/-++,*X*X+T*b**T*+)'\((()*H+(R+X**X*b.+),V)((N*(((%'\&&L&&)N'T'&H'R(&V&`%Z&R&P*&*'`)(V(&\&R&^)''P'&(\)Z+(V(R&X%%^"\$T&&#%%%$F%$$&%h&V&^%N&'T'X'\'N'()(\)$^&%L&&(()Z*R)*\,(N+'*T'')b*+\)T))**+X+*b**)*^+)-*,+T,Z0V-j.L/X+V*Z)(R&&P()H)L,d**-,V.Z/V,+Z,X*+)L*P+X,T.,+T,-T,.T-T-R.++*d**((')(^*T)\)+@.,\--P.^1\1V-.-N.R-.T.V1R10/00P/./1T0V11R0/T//,+*L*\**N*+^+**R*Z*.,**T)`,+Z)++Z+,`,1,*R-*+b+Z*)N+)Z'R*%%'%f&#%%d)T'(^)h(X'R)(')&V)J(&F&J%$N&d$#R#T%P#"##!!R  XHf!fH8^\VT@V TP^L\V`VL\B`NXJRT\VZ L d b N T L X ` ^ b T R d L f PNFLH\RHX^RRZPRPR^XRVbBd``ZPZ`L\`NbbZNVbLJV^`^VPRP\VlTRTZ\VTPPTfHZNZNXL`H\F\^^RVbZhDXPRPXZPZhNZRV``bZ`LT\HV\RbbPNPPF`l`Ph`jTR^`ZfRJ^RnZXPT`^Zb\NRVLP\^Tf\X`\XR^VLdN^LX^`dTR`\b^bdRX`Zbdh^\dZd``Z`ZZ\^V\^XjR`bFD\`VXPZ^TXVVR>VNZXR`^RVXL`TRX^ZZ^\VR`VVJP\bDRXLb\:R^\ZP\\ZJ`NL^^dPVdXXdZR\^TXhdPPVN`VTR`NPPbdT`JZ\R^RXHZRhbXRTTR^VT^\PfN^VVRXfP^\V\bT\\XXXbBb^JXHRTLbLX\LPNNb`L`Tj^PZRPN^X\ZHVXPN\^ZPXTX Vh L  X ^ Z L Z T V ^ ^ ^^ P^Rd`NVfZP`RXHR\bT^VTT\bVPV`dTRV` `L!R "\  \#!X#j%N$b%$\&%j%%%'''\(((`)'(P*P+P+b*,T*L*\,*P,+,,+Z-d---h0.L-)\+Z+-H,+P+V+*F-d*+**L,+)+,T.@.V*V,l,P)))X(D(V))'Z*)(\&&&%^('Z(\(X(*b+V+***(+(')T(^+(+J*(\''N'H&)&')f)&%N&X'&(((P(&'P'V*%^'N'N((`()P'V(()V(\*T+**T,P*+,\)Z(P'^'X()V(<)V'(F(T(f('b,(*)'*(Z)*)*V+`+P-,-T.+--P-`0T.X--++,`,+d*)Z+\,Z+,,`,\.Z-\.\-.^,Z///.Z/L.P-\,..0R/.b4\/.V++.*)T+d*L++))f)')'(X(j)H+`+J*R,+'*T+`*P,+Z-*)**T(Z((''\%V%'\(X(X(('X''(&%'X'*V)\*X)*''&@(Z((N*b(V)X*R-*^*H(L&^%$#%$^(j&^(%\(%X(`%Z&%&'%P%'^()R&\'(&()`)V'X'V'T&Z)(()(()')N+(^+'(P'T(),(\,,,\+X,Z,F)\**`++,J,*b,/,..+*X((^'b&'V(X**(T.X,`,,\,X,,+,b*)\,-J,*,+,b-L+-J+,^-,+)>*P)N)<,Z*'&(L)(R,,/,,V0V-0X-H-*V-P,X.R../00110T/Z4N0^1b-1//@.-,++X)Z,)+*`*+*Z+)*L**,+)(,,\,/T+L++,/R-,`,-d+T*P)(f*\+(&&N&X)V(&&%b%N*)b())X''))T*\((^+('%R'V&#&Z#'\#!&R"!R" ^ VRP^Z\X^`\b!hZd RX^`Z^XhZVP\ZNZZR^P\R\ Z` N H F T f d P Z X T R ` R R JTLFTfJ`PRTdNdT^XXT`H`PNTLDTTZPbZ\bRTlZZ\ZVDLTjZTTbLXNRTLRbZLZhbL\NV\h``RHVX`hZNVV\NX\BXJbZFb^Z`X\VZZNTlX^JXVVbTbP^VVT^`\FXbdZRR\`ZbTVZPHLT`P\T:F@TXZdTT\fb```\`dbbb\VfP\LbPRl`bb\PR^h`NXTHVXZHbZZ\dZLZT\JdbZVF\VVHTT`X\dFJTVVPZTPXXRN\ZXV^D`\bXRNBbRRPHVLVVRV>RRN^PRP\dbb\ZdVZRVNR>NNj\NTf^Rf`TN\XbL\ZT`ZR^^XP\\L\TRV8XZ^ZLP^`PD^XZ>XTZZVX^PR`b^PX\F`^PPVLbbRRZRRHPRTP\`dN^LZLVV`N^PlLZf`R ^ P F b Z Z T ^ L X V \\ X \^b`XTbF\dX4`H`\Jd\XVN`LZPPJH``RT\!\!! R!d"!V X!N'!V"#\%$L$%^&R'h&b&%'b)(L'Z(''()H+b(^))X**+)*P)J++--./\.h/,-R,N.,H,Z/-V,R,**,<*+L+\,,R*+,f,\-R.,,.X/*P)P('*N)\*V)(F(`(X(()V((X*b'((P,T)R,()('X*J(\+*(**(T*%'('h'L'Z&R&&&d'`&N%`%V&d&V'(N(h(V''X'L'R'&'P(\*(***T*F*)R*F,l,*P*)+X(\''d(')'L)(')'(D(p'('Z)J)+(b*L(F+,`*+R+,R-.0^0^--N/P,-(+**L+V-X-^,+R++X-T*,R.R-./J...T/10X/V/,.,T0\/D00X/b-,,^,X,L,^,,R+V((N))V*)''N*b*R/+*X+P*)N+T*X+N,V,-***)'^*\'&P&'&L('4+P)Z'Z(H')R''')Z()b*@+*X)*)*)*)-J())Z*J''&&#&'V(&T'%'X)'&'T'h&T&%&V&Z&N&R'(((D&P'R(\'+X*P('P*'V*F)`((H)(*L)V))(T)+(b(+,T+V,Z)P+V,+**^,V))N*+*>-`,N.-,+H-^+^+L)N&L''L((Z*+-\++^++L(,,^-,)+X,V**F-,*X,**--,L,*,L))(X+P*'(&'`,V)*+)N,,+T/--.V-+^.0./X2R/V0/V/-0H.V0010V.-,,.*R)R*(,R-*R*P*+`)\)*-)*,`*T)L*V.L,*j*\,,N,T.-^+X+*'d(T(j)^)'*('f'&)''(J&'**'Z):((X*'^*N&(''H%%H%Z%%X%##X$V#`"b"!!V!H d!P!` Z!RLX ` L !JZV \ TVN`^fFXdV`dHd^Vf\`T\^XTXNT P Z X X T \ T ` J P T XXfVV^TTZbVZXTNPdVZTTNTZ`dXR\ZTXPNN^TVXVNRLZ`ZXbNRX`VN^T^N^RLPVF\\TRfZNXZNjdXXVT\PRf`XFPNdNN\V^`bVVf^`PddZXRDf`\PX\ZXVL^jZVTPbDZRXL^`XRVVTdXTjddRPZT\VHHXHVRT^lXXhb\dXZb^flF\f`fVVhZ`f\^hdZRdXZhRZZ\VZbTX`PR`^VhTX``P\XTP^f`HV`d^PP`XVf^VZXT^^Z^\TNP``DT\^bfVVVVh^XRTX`VLXVXbZJXP\R\\TXP\lRX^VVP\bT`XPRZbbX`RRRTHVbDbf\VV`fRJ\XH^HhdNZRX\``Z`TXVV`NdxZ^\\fNZZVVRJNbHTXRRf`ZNZR\ZZ \ T Z X V ` < V L Z`Z ^Zf\Vh\N\Rb`N\X\\``fF\P^XN\`XbZDVXX ^"T T! !`""b#J!"F%#&L&L&l&&&Z&T&'^'X)R&J'(D*N(((*V(X))+f,N,,^-*N-*)*J,Z0-.-,d-f-,.N-N-,+Z++\-*R,T-+P/J.P-+R,+H,0,X.V-R,*R,*((&(P)^(R*)Z*b)'`*R)V)Z(R(()T)L)b**(+))F*j)('T(&''%'P&R%'J)&%P''''%T$''(R(\)(N(^)((R**X)((T+N)N+.D++N+)',N*,R+'(T*()Z(X('((T*^)X*R)('(^(N(P+\+X)V+('+`-,,T-L,T//Z1-b/--J--N..R/.X.,R,.`,+^,T--N++,R..N-R/.0//,-+-.-d2.1^-Z/+,-X0+R+\+'V)()')((+,*D*,*T+`)+d+T*L,J+*+P*+P)(('%^(&V*'(T&*'L*X*`**X(')(*)T,,)`+)X)Z-X*,,,Z*()%&\(P''%%&'&&X)V)`)V(V(&P'J)&j((&%R'&R('b*T'\(\'&^))'&((((**(V)&'%(()*)T*^*)**R+V-*V*++Z*\+\+`,*,Z-.,*T*,*V((\(N''\)V)*V*f,N-+b,+\),F,+)V,+/+,j,-Z+R,N-P,.+,+N*)('*)V)\+'Z'P(T+*Z+V+b+**J.X,-D++--P0.1..b0V1Z.Z0^/0Z1V0^30X.-+X+V,+)*^*F)*+),T)+\)H+L*,-b--,X,L--,+\+T.Z-J-\+,V,)^)\'\(\((R(\))*)`)(b)(()()*X+*)(J)+'((R*X))%'N%#$%Z%"R%D$R#^#V!R X !^^ dR!R >"  !"\ T D"X "P! LXNfVZTZZPf\ZPTLJVZ^XJ TbTX^ XV P ^ Z b N J ` N b P P X \ ZH ^VV^Z\ThVLTFPN\VV`VZZVX`b^VX^LjPP^^XZ\lZXPf^RZtZXLD^V\`RjVTP`XRTTZ^\FXbVXTNb`R`FZF`\NTV\Z^X^TRbRXTVfh\\\Z^Zb^Tf^P\XRXf^jT^^\bTTP\RN`\HZNZPFZTZVdPVbVPXV^VVH\RVPTPPV\ZX``d`fdhXhlZZhLXRfZbrbLd\Z\NZfRZT\Zbh^VR^ZXfZTTJ\VZ^R^^`R`^^RTZP\TXVTLX^HRXJ\T\bVLT^LRdRRRNRZPDRVhRV`HNNTRPJLb`P``^V@L\P\RNL^VX^FV\RRbJ\PV^TTXXTdZ:dD`RNLjPZL\HHVZT^bfPJTRZRT\bXHZVLVNTRRNV^RVPJVNbZP^ZLVVB\VJJTTbb\FRVTP`Rj^F`PX`ZR\PR\THVP X T Z ^ 6 XL X`VXPBVLPJ\\XP`dLd`JVZT\@\ T!P"Z"R X# #V!!J%"X$#$%$d%Z'N)''N*'X)+('Z(N('R+*T)T(*)Z+T+-\.V*.+*,P,b-R-X--V.T.X-,R,0-,V.T/-T1P.,R0*,P,R.+^*Z+\-L-X-,P--P-h-+*D(Z)N)V)P)'+N,P+P*^*(`*b+d,)V*+:*(\++)\)Z*V*b*d*'T'B)&T'((&&&R&N(%'%(R'%&'%)(T(J(\'X*&'R)&'d(T**X)V+X,+N+^)R(*\+^(X)X+Z*^,N*,`))('R(+R*'^*b*(V()R*(,*+('b+()X--R/\/-h-0/.-L.N/L/@..00/2/d-/X0.-`,-b,+,-`-f00/.P,0-P.-,V/T/X1T/1X-,J,N.P,*`-\*+T)'(>+N*(P)T)+T,N+X,Z-X,,+P--Z+b+J,*N+F*,J+f+^*(P)N&J(\'()J)(*H+)P+T,-\+^+`++*H,X+-b,-L-*.P..-,`*Z(&'&V'V'T'T'Z)V(\+N)Z'b(T))&%V%`(\%&'^)R'B)^((T*R(j'N+P&X'&H)P)&&L()T,)'N'T)(`*Z(L+R*X(P)'V*l**Z+V.\,,\**^*\*J+\*.+-\-X.N,,\,-*+J)N*V*('V(T())\*F)J)\*Z*b*++X-)X+T-Z+Z,R-P-^./0^.L+,X*+N(V*)`*'R(`*T&(')b()*V+^+Z++,,-L.`-,-+b,-.V/,...V0^.J/100X-/+Z,d,)R+h*\**+((*+(()\)(Z).*++T-b-,+^+N-+\*,+X-+)+**'Z&J'\'b*P+`,V*,((*V)R,^)(T***+d,Z)T)'h&X''b+L'l)&%$$%#X$$R#Z#!" X" !\!R!Z "#V!FP T$N"P$!!"R! h^\ RJTD^fZT`PRVPPR N H Z ^ \ V X b T P H \ Z < h R V T \ XTRB^LF`b^LV\BRRVJ^PBXVFRNFdLRn^R^LV\ZdZVH^ZFV^^X\NLZJVfZVVXbZVT\Z`\PZVVZRd\TfXJbTXVRNPZ\hZPDVZT\XTXZVLVZVTLTPRXLbZTT\F^J^P\RT\T`b`bT^Z`^PfRRT`ZLR`Ld`^`d^df\jNdrjbVVXbdZTTZh\`XTfNVbVbVXVZVfT\ZVj^R^bd^ZZ\b\^nDN\bR`dbfZXR^ZRZJXN`d\`^hVVVR`\RhXh`XZTZZR`HVZVTVdXTZPZN\dTTZj\LLRXP\\Z`bbJ\FNXVVXRXtPbTPRVT`@RPNZZ\ZPZZNX\VVRdLRJjZZ<P\ZPJd@VVTRRV\`RJP\JLVT\^hZN`RZT^b X  ` N b L Z N \ R \VVNVTRNZRXddXVNPVfPZ N`T !N"T!N \"\"`!!"$^$##J&\(P($%$P%%Z'&R(b)\)*'(R(d())'H))++,,^,,,-+*X+--^+.V.^-V.^/+T.T/1.b/1h.N/Z,,T.-H.X-`+,*V,-b-,,R.,`-*+))T*V*+,+*P,^++Z+)L-^*Z*P)^)H+*,T*+)*\**('$Z(%%X&&''%V(&'F'X&)&&'F(\'X$'\)h''D(P(V('\'f)^)()*N)Z*,-+'('X)d)&\*N+,Z*R+Z)L+V+()*T'*''(()Z)(\.V*)V+*))+\--.0.L.-T,^.,-/`./V1\/1P3P20R-N/X1L.^0/.b,:,.R0N/0`0b0-0-+,.X/0X1X1V-T0-P.P,`,V+J+d,d*V+)V)T)V)X)((\+\(D-+,-J-V*^..Z,f+-,V-B.\++T+-Z*(L()X)\)R*V))()b*V,,N,/R+*.V-N.N,+*+*\.*,-L,+X,)T)(N**Z)()N*Z(j+)('X')(&''f()(l'R)(Z)+Z)(b(&N(`'&'f)V)(P&T*'+R)*N(f*((T*Z*)+*^,,^,V,+Z,*\*V)T+*L,)V*f-Z--+V-*-`+T*++R+'(`%b*R((R)V)\**^++*Z++J,-P)\++.,\,.,,+X++f+V*X)X(X*J(Z'(*('(H)^*X+)**X+V,)+*,.,,^,Z*Z+Z-R-^,.T..L.Z00^/---,,**\'R+*`***+*+L))X*,++^*X,\+)\*+.-,P+Z+`+R*+P,+X+N,)\)J(b)N*d%\()^-+,R,)()Z)+,+)*+*)>*(())V*(L'B)X(b(\'Z#$$$&\$$!#%$"!Z!N"!R ^!"#""P#"d$! "Z!V Xd!ZXZdVNPXZXX\`Z\L\RhXXTZPXVHZ^\XZ ^ Z d T j P N ^ \ V ^ ^R bX\PZJJ`N^RTZZdPX`\ZdVXfZ`bZRFnNd^fLZbVTZ^`dXZR^V`\RZPXNjVXPXNFDTPf^b^Zb`dXfhZZRRRZPHLRX\^TZZ^f\`Z\\VV`d\JR`PTXTNZflb\VPVdFbNlR^XR`VRJZVVf\bbbHRTVZ\RLRDdR^XZVRhXdP`hf^`h\bXV^PZR\``\^Pf\N\TVXVff\Z\^\XV^Xh^ZRTZbhVX<Z^FJ\NTZ^NZ^XHXRZbRLL^^TRR^JTN^ZVTVN\jX\RT\J\bVRbXTjL^XL^JR\X^HR^PVPVT`B\ZdRLZVbbXLXL^bP^JZPTR`PXPTDHPVRfNXXNZZPR^XZRVL\V\TVXZTTZFXRf`XJDTHXDRVTDZL^ZbRbTN\bTJRT^Jb NX V  N \ d ^ R ` Z Z `TjP^VFTRfZRV\`ZTNdXVVZDZZLT^ "!%P#!!"!"^#f$%^&%p&%f'%R'X&V''&'R((`()(+(*,V+R)R))-X,B-N,T.b.,+,V,,+f,N*,,D...0.J//P0.`.N..X+N.X,V0*^,\.,,\,b.,-P.-L/L++H*,+)Z-+*^*^+Z/J+h-J+,\**))**P-***+\)N)X+'&&&&()`)V'V('T)^'''Z&%P&X%&&\)''`*('Z'R(V)Z(&L(()(N((+)(*(b(`*2)h*++Z.P-H/b,)T)'X)(Z(Z*'Z(P'()()(V)L*)*b+P-+//`/R0^-J,T*P+Z,J-d-R0L/2/22Z31`0N.1H/^/P/V.X.-`,,P./\/.X2-^.T,//T/-.1./H-,T,,X,V,R+**)'((N)Z+*R(`)*R+-X-,++-V+V+Z,T-^.L-+X,\--*++('%(R(()X+Z+T*,J,T+,++R.\+X.J,d+*X*\+*R,^-,d,,^*Z*Z*('R+X'V,))+d)'X((V&&T()&L+2)),\*)+Z*)H*((Z%X&%N(T(`')Z(N)&)`)b)(''X(L(R((,X+,+`*N,-@,+Z+R,)H)f())+*+/-,\,0b-F*b*(*H)Z(J)V'&P,)+Z,Z)*P*^+)(+*-*,)N,T-`0/+0+-(V,(Z)&'V')H))*P+(V()Z+/L,/+*+-,J,--),*N,T-L,+-Z-0.1V0-Z/b,N,-*V*)R*)**)P+P)Z+)8*P*X)P)*T+X+b**`--R-`-J-d1,P+*+(-@***)''(+)`(N+T-V-V*h+Z-b,+**)T,)P))H)R*T'^((^)(*'J*j'*`(J'%%\%Z&#T'Z&`&$`%!N$J#T#!J#X#^$P""L#R#T"!V%@"d"T# " "J!RbTRVTTFZZ^RFRX\V^ZJLV N R V R ^ H L Z V ^ TV bX\ZNdZZXVLPRRNZ\RhRPXXR\\ZN`VVL^TV^\bRXVZ`ZVX^VRXfZbT\bZ\^V^LZTXVZV^VV`RVdPPZNZZZ\`^RdbdNVRlRHLX\`ZFdN\LXbThP`VbFPTb`RR^X^V^`XfZb^^VPV^dXNRfTPdTVV\Z^`n`ff^`Zb`TXfZVZ`XVbXP`\XN``RbR`XVVhfX\fL`fX^VVnJ^\TNHXPPL`DZL^^Vh`^^\V\HN\\^Z`P\DTbP^ZVP^PjPVB\b^XTjVTTNZZXbdHTFVLZRXLf `djdZVVZVX\NZVTV^RHVNPX`^bRRX`X^PXLP\dX\JTNbbdL^PRdTP\ZNZZLVTTRVbJZ^TZXXVF`PRZX\Z`RLZN\Z`RHLVZP@Zb`VfZV`PR < L f V ` d XBZR\NZ\\VXP\PV^TTdJ X\XVH\Z!## T$^!\"J"$Z#$V#'t&P)R(f(&Z'%(&R))(N)'R+)J,)H,r*++)+Z)*,+`/P.P0J-f,-,`.R-Z+R,R.P0/L/./11N/2.,.,-,P.R.-F.+-j.L-.,-.T-Z.,,Z,*F.b.`,B,R+H,P++^,P+P.Z**R+Z,^*V*)T*N)(^+*R*b)L)T*L(%'f&'N((N+'b*R)V)&&N&Z$^%T&')'R(&P'j&&)'%(''^(*N-****'()*+&`*^*+V*T+*d+L,)()Z(P(*')Z''(*Z)P,*J))Z*T,,V-R.@,B1/T/-R,+,/.`/.b10Z3P0V1\11T102/1/F00/^/11>.//f01^/10T.V,\0V+..J/\,*X,L+*`**+^-L+)X+Z*\),\.,+R,,R.^.X0/T-,*\+X-,-`-^+,*,H*-T+,`*N*Z-*R*+V)L*(T-+N+R*-+)),R*N*^*d)R+L,V/H-/T--)\+`+V**\()())V')Z)(H'\*b&)(`)V+)*L*J,P-)T)P+X*V(\(X&(@'T*R(V&\)')P(&\(X(&'L(d(+R))*),\,V+,`-V+*\.^*)D)R*R-d-*T*-+d1Z.,`-*b+^+X(T))'''*())T,+`,\+*T+)X)**Z,)*.+V/R-^.`+P+(Z-T+'&'%X')P'V)h)Z(*,T-,+^-T.-X+*d+V*^-*Z,N-+J,*+D,,V-X,P/0.0-b,\.\+V)\*'`)()+P+N**-V+V**\**f)X*^*^,,Z+b,-R,X-L/h-L,+*P)f*`)P+))N+)(&J((`*H+,\+,+R+b-+Z'-)*X-)b)Z++V+N)*('(H)R&(&f('Z%&$'&$%%T#N$$P#`%N$^%#$V"#$T#V%$"b#`"H"!T!\ \ R^hNXXT^HRPJVLR`RVVZ` PVZ TZ ^ X X f RX H^b^RNHX`PbZZ`XZ\R\\HZbZZLXZZN\T\TX`XX^^PTVN`\TJhHZPT\VZdd\XZPbZdbTP^fPVLX^PhZhbNTRdTT^\NPZT`VRLhXPNbX^TRXZhbVR\^hX\V\`bPTT^L\^HRZLV\XXXLXR\\TJ\`XZXRZ^XXPh`VdJVZ`n^bh^Xjnb^Z\bLpbTTVfXlj\^\P^`^^R\hRNZ\V^T^`RdTNRTdRXZPT`RZTNZTdTfd\JNdZd^LZZJ^NXV\T`V^ZVfNVRT^X>XZRVHXp`RTZTX\RJb^`VZ`^d`RJNZLRV\PVPbRZLJX\\^dPV^VX`PLRVPLXTPXVTB^VdVFd^TVRVV\N^RTd\DJRXRVHJHXRR`T H L \ d V Z J ZX \XRbZZPTbZXNZJPVL\XfLZRdJ^X\PVX \R"^!"" ###"%j#$Z"%V$V'V&R'%N('((T)(X'()P(\)*`*T)V)*T,Z*T,*+X,-+T+R.,\,/N,L-.b.,N,N-Z-J0/V0..^10T0X0\0.R.-V/N-/D-X.b-Z-^/.-\,\--d,Z,*d,`,L./X/^./f-,+V**R-V,.+\,R+*P-(()R+P,))V+\+X*(&'(J%((Z)J*%D)\(P)&&Z&\&V%`%J%'`)'H)'&(V(P(X'N+R+')X)P(\)V((L(\)X'T(P')\),P**N++X+P)V)'^('L(\(&P(Z&^&X)*N)X+T+`)++H.L.P-P.`.1X-+Z-B.+N,.R./01\32214^3T1P11432V1V/0-/Z//\-/>0V.//010.2.--^1X.@.V-/,+b.,-,,+^.++*Z-,L/+,.T.00N/.-L-P..V.d../D-V++\,R,\+Z-*R+@)R+R*-**+-N...,V+*^++*T,*\++./..Z,T-+N*`++^(X+\*+()(X**(R(\)&X)X(Z*)(J*T,Z*R*L*\)R*')^)&(b(`)'L(()(T)T((^)^)T*\)R)^*X*\*),X/,+P,*))J(*+^+P.Z,.)X+,+++*R*+'(X+F))@'(T'())P-,+)^,F))N)**V+),.`-,-T.P+\+\-*F**F)^)J*N(P&T&T'X'(Z)b()^+X+,`,++-+,+)T-*V*)*Z-++L,R/.V00Z/Z.H0,B+Z*R)X*Z*T,)D****P+Z*+*))b*(V*L+\+V+d,+,,L0++X+)J,X,d+(`&T)Z)V,)T(*X*+J*T++,*,.N,+J*)L*(*R)^--)Z+R')`++P*(''T)Z%H%$%&$&&F%`'R%L$V%f&`$^&#$%%%##V$&$$V$#"!!!R" ! H\V`J`VbRX\NJH^RLTJ\X\^JPZXVX R J Z \ b V X L h N R bRXd^XVXLZXTZHZ\bVZJLTZFP^^\TVJTPTXNbXBTVXTPfbbRZZfVTRTZNVJZXZ\\TTZLjZdRH\T`bNP`V^Z^PVZh\VNVldTTdZ^fN\N\\T^fDNZTdVPbNlPZTF`TXNXXbVfNTZ^\b^bR`\XXXR\L^VZb\NVRZ\ZVXNTnbV^\\hdhR^l^Tbhd\\hV\^ZRXb^Xb`\bPbX`R\T\fTPZRb\bT^\hLhZFX^VRXNXFP\`NdfZ^XD`b^HRZNR\f\dXd\V\`P\bTTZVPh\TNX\ZTX@bTfZT`L^V`^`ZT^VTJHN\D\\ZZX\^`f^Tb`ddJ`ZTZ^V\^Z^bTRNjhPh^^JN`R\FHX^XHNXFXJXTP`bRVPX^RdVF\VXTRRRR\^`Z\RP^ZRVXTVRZ F \P ^ \ P T X V X L X V T T XNn^ZTHVVXLbJDDXPLT^VRJ^X\PPfZ\`!V"!""L"J$R%`""#%R$#$$&Z'j(^&V'R)))(&)b(N)d(\*)V*T)(-D,+X**d+*.++N,^,V*^+,^--R,,,P,-\/P,X2-V//L0R/11L//X0/J/L-.,*J-/Z/.0L-Z/F.`/,/R.,,X+X/..R/-+,*+V*+-++)T*P++((^+(Z)X)(`+P)T*)%d'&T)Z(h(\)'L)R)Z(T'R(R(R'`%'T&Z)\)V)^('''L)\)&L('l(V)&(R)V)('L+d&('')+L*X-T++X**R*^)Z('))'P'^'&&`**X))^*R.+.-P/T.P/-X.J,\,`-*L.-////`311L31\21\2Z24d3N01f0B1V//X00N0//d0V21\2`/.h./-.V-R--^/,P-J-,V-T.`-N/-^/H+V*Z.-,R/--1//R0l1.p/0Z0/^0X1^1T..,P,+j,+*V+^-R+,Z-+L-+b,-.b/P.,X+Z,+L,J,,`,*^-,.X/,,*Z-V+\++,^*+)V))(\)j(''''V)b((j)((P(,*X+)`*Z(&(b*X(&)'T)X*^)'X*D(+'('V'X(P*,++P,,D,V++,)Z)j+d+))Z.N,-F,R*-P,X+\+,P**b)(')T')P*>))**+^)`*^)(^**)(R)(D+*+*V.*+)P*N,(J+V+'*R(*&%(Z)Z'F((f(R*,Z,,+-\/Z,)R+V-\*+F+*X'V,)d+-/L0/1R/-Z,-+V.')()\+)N+*,Z)`*d-d-R,,J+N+*V.P+++,+.L+N+T,V(+`))R(N+R(L+V*`,d*X,T+)*+*b++*+b-V+-T,+*X)**(V.8-X**(()*X(T'L'^'L'&R&%%$%X$R((J&L&&\&\%P'H&&$#%#&#^&#$^%!#P# "  F !`"X L\fV``Z\^ZPVVXbRRfZ`VNTX  \ R T R V H ` Z R P ZlPTVX THNZTPVDTNJJFdDL^ZXF\NR^PXVDdh\L^TfN`bVFP\bZL`R`ZVRbj^TXh`^`dP`\bVdLX`ZZVX^\NRdf^XZP`bXn`PPZbNRPRRRXLDV^R^^T^ZXZN\f^RJ\``Z`TbZRZj^^`PRl\LbVRZNZ\X^d\h\^`P^ZVlTXXbZZlVdbL\Tb^ddTT\\TJRRXV`J\^RZ\PZ`VN`d`fT`dNhb`ZfXT\XTNVR^ZLTNTV`VR\JLTXTZhXZX\JZTJ^VLbXZZZTXfR^FVXRfTX`T`NfNN^JZ^XZJfRH`T`\RbJXDLRVXLbdT`JXdJXRRX`PNTT`HN\\PVZXR`LZXTZZXN`TVZZVZPXfV\PZX`RPP`XZXP\XXXZX V F ^ ` L V R H ZLbbPR^^^`JVVXRBfb^TVTVPpTRXb !Z!"R! "T"P%Z#T"`#\###d&%T&%)'&\'X(\(f&*X('(N(d)^)X)X((T(***+N**+d,+P-+*T-+Z,Z-R,+/X,X-/Z0-/.:/210\0T1/J0/.//,.\++-@///T/-b,0^-/,.-b-,0.1L/Z/B-b,R,-+,,)+Z)&+X)V)L)T*''(X))(\)\*Z()J'('L&V'&&\'('H&(b&%%X%$&\(%&$&X(J(R+R(b)&'(T),)P)'L'&&&(R))*(*N)L(P)R+X()b+*T(P)V(%&\&X'V'***\--T,.R12T,-P,X+,,+/^.`0^1B12L141`03/440T22321/V01f1V30b31/\0Z/X/R.L0^/L./P-0--,R-\/b00T,P1/1P0Z/b...T-P0b0V/.^0V/R/./V10.`/0X01`1D-,0.-,D,\+*T,*/d,+^(P,j-H.V0\.X3N0.T,N-P-,T-,+*T-b.:10.J,+++Z+H*()+f.N+)+(''Z(%V'h))X((X'X*(Z+(`(L')V('V)H,((J(X(*)R*)X)^)'^*P(''P+,+`.-N-*\+,*V*N())X+J+,,>,Z*V-+P,^+*)^*(f()T(D''b)(,*)X)***\*Z(6)+\)(b*V+&`)V)`*T+*,++*L**)\*'Z(&(f(&L))')*L*+P,R,b,,.-*T,,,X))J(*+),Z..T-X.J/X.+,:.)*,H)'\'\*+X+.*++))T++R,-\-d,*d,P,+)b-+,`*-)'T(((H(('P*^,X,*+X*V**,Z-T+,V.-Z,^,+Z+T**Z*b,Z+T*,)*(F(\+('N*T'(&P)$^'\$`'\&&%R&T)'R&&'P(^&&%X''&$B%"Z$%P#"\#! \" b  F ! N\JP\P`d\`^\PVXRX^^HjL`TJXZ R\ F ` X ^ X V V Z ZT>VHV PLZ^ZR@XPXZ\ZhTZTNdLTVPfNT@ZTXZXN`\TTZXJRXNZZ^\`JVPTZPN\RRXdXVfPL^b^\L``\RJVV\bTLRNNX`JPV^nZ^RTdPN\L`^LT`NT^^Ppb`^\\rP\ZDbRX\ThXnTPZVTT\VbV^\`\\JXT^ZFVf^XdTdd^\^`X^`X\XfTLPXb\XRbbbXhj`^XjbZb@hXFfZPhN^LbTX^^JfdTVRR\\\HZN\ZRTV\^hZ^V^Rd^VhN\RfjZTj\dNTXTRVRRXV^HT\XZRTJZbZZVXVVTbZTPXXVX^^\R\X`f\VR\X`VXTZ^LV\JZL\VhNbbZ\LNPXL`>V^^RRR`RTd^\ZZ^`PXXZd\RNbPhPN`TL`fXTR^XPddH bZX ^ X X T X ^ \ V \ NdV^HXTXbPP\\TVRL\PnLjd^X^\HRR^d bV Tb `! V!#\"P"$f""!J#V""h%V%$&j&V'X&%'p'J&P(`('d'\()V()**V+*V),j-L**Z**\*--*+J+`,L-,^,>,,,T2Z-/N/T0L1.1d3j2P/\0.b../,`-,./V.,+Z..n.-`-d-^.-/.--,,.Z-`/.`.X/,+J++b**P,*P+**J*d)R()Z)'))R('R,R)^,(*\+\*'T)X(L*'J*&P)P(V)J&&l$&%d(F&\'$J)()))())((&V)b)%H&'%%%\&(P+)N*)Z**))\+'(,X*L''^+R)V(&V)\)+Z,N,+,N/`/-`-V.+,d-J-//0^./P1//1V4^21X0113`234D43^0J1J2X/T32T2R52/f/-P-Z3X-.00/--.P..0//1//1b2R/V//0H0j0/Z/-`.,X/0.^//d0H0d/-V00/.-+\/*^,-V,-V-.`,.\,V+,Z10.0d/X/-..\.,V0Z.f0-/,P-,Z-/,d+'Z,L+*Z,)\),+(P'R*)H)'V(X*))')(P)J'('(d)')V)P()(Z,*(&X)(^))(T*((+N+T/--Z**)Z+)V+d*V**H-b*\-N,,P.,L*V+.X**((%\'$(()(Z(**))+j*&'\))(b)R)('X(L*Z*l+J+b-,^,++*P((%)(X)X(N)d)`')P)T+\-^,,..f,,V-T-f+P+X)L,X()X*T,*P+L,L,/R0/T--,b,`))*^)Z)()L*.*+)*P++D,R*Z,V/+T+T*L-\,P-P-,).J++(&))T(()*`)H)R*)Z-*X-++*l,+\/+--\+Z)V*+X))+*)X+Z(V,R*V)X*'(X((''V'&'&'^(P'(('*R(%Z'T(*'%%T%%`%(%%"F#b!N#T$%Z#^! P! b X^PJV^dBb^T^dP\RlR ^ T V \ Pf J X f P T N J` J HRJPbdVX\\JXJ`D\XVXVRZLTZXPNfPXHZV\\DVVTTTb\hdXP`jZZPNPZ\TfVRdLR^`fb\NXfR\Vf^^b\XZVjVRN`RP\TPXRVTjdbVNVV^XPRZZZXV\RZD`DXfZ`XRPfbZVdNTbPX^XVLF`X^PbP``RRVRLNbZNLfNd\d^b^ZZZhTZjZXVhVNXR^\\RZNlTRJ^LTZX^T^PfbN\T^dJ`\VTVhZ`ZdTXXVZbTXP8NPZTbLTbRRZLhZX`ZZNbXRVRZJ^VJ\ZXX\RX^PXbTXRRTTZL^VTLNXZFTfPTPJT`PV`V\X^R`XZ\VXLTZZ^PXPZRJ^P^LPL\TXP`TVPXXH^ZVPTNbdRLRLL^fLR`T>TTJZ\J\PXZD\NXXVXTZRR`R l N ` ^ T R Z R P ^ \ b V XV^RXNf\X^RXZ\^LPTPPXZT T^ \! R"R"^!" R$P"X!!b#F#R$#'%%%P&Z(R+L&&b)P*b+^((*p)L)+)(R+\*++Z.,*N*`+*`+J,+,L,^-H.-,h-N-/j001/R0P201Z0F-V0Z0-T/`/\/X+\-/.-`.X-X.\....d.`-/X0.R2V0.X/-.8-X/+-,R)Z+Z*^*)X)`*-P+)'N((R*(V')\)()*P++(*)(Z((@(^(Z&Z)`'L'V)X(R)T'L%`#&$$Z'F&`&'()+)(F*+)X)(^('&d('P*'^))`)V)(')h+P*'\)'*f)R(d*(*L)R)+*V+,+L-n+L-`+-h-,V/,,.-T/./Z1/`/30P552^2100`2X6P5\5P5b61V2L2052L4P2T2X1/>/1/Z301/.d-N.L0,1V.0h1P3\20X132L001\3J0P01V1/V0.R-\01.V/-.R/Z//P.P/^.+++-.F.b0N--h-.Z-.T0-0l0R.1`/--,+P..P.>.T,T/R/+d0.Z-,*\,,T+T..+\,@,d,*Z+d,J(H)^)T')L*P+,R*X(P'&T(&X&L(N(*@)P('N(T(N)N)`**R(V'P*(T++\.V,b+R.N..**V+J-^+X,*T*)X-*+*-\-,+Z+-+(*(T+$P''P'''(`*\(d)V))R++\+\)R(^)'(Z)T(^*(R+))*L(X))+*f))\((''%R&'Z*\)(V*Z+Z+N,N.-b0+\*T-b+*T+(T*,*))*,R-,/V.1V--P+^*)*T)'`*(Z)(Z*,++--J,\)+L,\-,,J+,-)\))L++b*(T)b(f*\)(X(D()D)\)*V)+X,,T+*.R,*0^,-J-+J++*R*(*j+R*(*)P*R*)\(*)F*J*h*'\'%)V&V(Z)b,`)X+Z(((P('&X)'R(X'''%T%b(Z#""D"#J!!!"`!J#\fDnLZX`bHPVZ\^XXhHPLN\RZVX  Z DP ` H \ Z R f P X X \ b^ \ R ^ TR`ZLT`VdJVRX\V^HJZR`ZL\NRbBZ`VFR^\PRTR^XL`bXZRJTXVZ^dVFXfRRN`PN\VLTN^hbPL^X\ZdXRTPJVb`XnVPdZb\VRZTXFXFRVR^hX^VT`h\XPbV^TLTVT\Z\NRZ`HRVhBP^ZbT\NXLbfZP\FP^Z`P^PDjjXd`\\jhZXZbTX\\RNPVXVRd\^^Vj\hX^^DZJ`VhVT^\^HZbTdLPL\^R`fTZpZR\T^^R^V`VXb\RT>d^X\bPhT\`RR^RHTN\RdNLZZd\NTVN`Xd`NbXdZZXf^Z\TTbTNRXVdTLXVT\LRN^HL^PTVNXTTXXNPX\PX^NRLTX\ZbZ\TTNTT`PXPZ\VXLPbTXJB\TlTRL\f\bZdPVRdZNHPZ  N X R Z  J \ Z ` ^ \TNTPZNp^NRXf\PX^NZXbPVT P !"#P""!V#d$"Z$b%!\"$^&`#%V&X(&\&'&L'&h&^)'N*P+(J))`,^-R)\-,l,\-f-+R,\,*d,X+R,,Z,V+X-/b,X,-\/L-,.V/0/X0d1`12-.T/,\-.H-R-/-d-.T.T-D-//Z1`1/T.,\,^.0.^/X-.J/-L.,-Z+Z+P+X-L*++N)X*f(X')X''^*(+))\)(*T*X*+)\+*)*Z()V''^(X&^('P&^$b&'%$$#%Z&J&%(L(^)(\*(T+\()%H)'X(&V''(N)V*\*'\'\)((^)J))T*`))*P*f+Z+)V*\,+-+R+V,+P.J.L.0-/,-.1X101/T212Z21L21^32T001233J4d2H3^5L42Z3R433L52`111021\1Z20///P.12^3\6Z43H02X1\321/\201/-.0f0.`-V//R0V0R10.0-R/V**V-V*,.V/,D,-.-P/R0V./^-R-L/.b-,+-,R,,\,^/.Z0.-/f-J+.L.b.N/,`,-*\,-,,R.X-+,F*((+*((+F)f)\''(((X+R)+&)(P(N+*N*+d,\+J)R,.<,-V,+.-Z,*,*,*(\(d***^+D+-+J0\+V+L)+(R(`)Z((&P'Z**(h)\+((\**))'^)Z,^*P(R)(D))+Z,Z+X,J,T*,))(*^*(N*Z(V(Z&(^(X((^+,*,R+*+H.Z+,V**()\+`))(,^,P,+Z-\--,P+Z,j,P+,^)*\+Z(n':(P(**(J),*V,-`+P++N,+T+N),),+^(>+h+)*')()(('F*+V*T.+*f+*P-R,*-,,X/Z-P,,V-**R+X)T*\'**d)\+V)X)*+T)+Z)X(R+)('X)J'Z'))T**(P(`'X(^,b*X*()&&%&$T%Z%N$T$#"\!R$H! "V! P XHTLPDT`TVT`X\`^^>f\\ TL d Z R X Z X \ \ Z LTV\R b\RNTTXTRTHVNTZZTRXZ^ZJRT`PJJVddPRHbdbVZX`TTZ\hXL\^`R`JTL\VHPNZZbRVbXZVN\dV^`HXLVbT`h^PTTdXhVZ\T``ZX\dRZNL\^\fbTXPXZbZ^T\ZRVRRbTLfRLXV\JVXhTnJNJLhZX^f``bZVX`Z^\```V\TPndZ^Xb\\HP`H^^VZPb\PPTTRLTL`ZR\bLPZV^dRBTbZZB^LVNV^XBZ^dRNZ`bPjXb\XTDVXbTTPTP\\PhfZLP\VT\PR\TVNV^XJRXLVXZXXHHV\ZZ^PX^VXZZPVJZH\Hb^VXT`RdNJPXJ`V\BFVTXRVVP^VRRlVdV`FT^VPLJZPNZL\PXJTNXJF^TV@^NTZ^^XJZLP \H V P Z X T H b V N ^ZR\XfJFX^TRZTXFXfNTPRPVN`\RT`P^@N T\!L !"J#f""^#B$$#P%Z$%P&L$Z'%P&d'^)))'&T'b(T(&^)T(*T+*+V)+\.F+h,,+,+Z-R/L.h-,Z,Z,.-,L/R/P.-/V-.b/.0T10X-0/V-T/H,P-,+-L-V,Z-/X.b/L.R-Z/.L,0h.,\1.b/0`,R0/N+,L,`+X+*+H*b+T*V*)*)N))X(f*L+d)P++)(')Z)Z+X)+b*\('&&X)`&N'(Z&&%&%b((P$%\&$X%'T'R+(&V)T((P(+V*Z)R+(Z&P(Z&Z)')R(P*`()X*+(b+***H*b)R+b++,*L)*+,R*`+X--X.+,-V00.V/V,.V1X1031^1`3^1T022j1^2X2n30X2\2365L4d5V3N3R45d4H2F4Z3j01^4V1/3X1X131\4L00X2P21P0N2d351J0`143X2181V1//V-.T/0\/.d.J.X.-/\./-Z.R,R)X,)`*\,,,D,N-/+V-T--^.\.//V/.H.R-/+,R,D.H/,.X0P.R//R.,+,D,,/`-R,-N0X+\.P,,J,-P+R.T+*++)+)`**()(*)Z(R*))`(X(N''V*(V+b*P).-+-*V++^-.0R-,*V+D-,)+`*,Z.R,X0^-0,+H*,)(^*'+&P()X*P++N))V**(d,'(T+Z*T)H)(+)&N-Z*++f,+`-d*B)X*'('P(`*P)Z((`)J)n(()))X-H+^+T+)N**X+*N+`+R(*Z*N,*,^-V,R+N+X+*,V*V+T,X((('&R*)(^(\))N+*,,V-Z-f-V,,**.V.*Z-N+H+T*J))'\)'H(b()P)(T*Z,J.-**+-,,+X.,X-R-,,l-X.\-T-R))X)f)X)+^)**Z*\-d+P*Z*Z+R*b*++T(h)*f+)b*P+,(V)\)`'L)T)'P''\'%&H*'%d)`%#&%P"""!R !V`!XX\PZ^NJP`VRVZfVZXV Z P ` ^ P V PJ Z P T Z P R T d X ^  VPR NPXP\PRVdXTJhRXR\RT^HRZ^XRbTZJXTPXZ^^TTNXbZTTRRZTj@PXhNXZVB^RX\XP\VR`XR`RTNT`hR`RVDTT\nH\VJVRZVVVPVXZX\HZXZ`T\PV`bJXNZNTNXdTZdR\bTP`\hVXZZV\@\\RXDTV^JZVV\ZVRZ`Z^bB^XVfRP\TNVldZVjhH`bZrbhXJj`LTT`bZflTZVlThNX^jZTNNT`VbXb`bf\`^TRRd`Z`\bTX^X^dXTX^RV\RRZXXdXN^ZLXPZ\ZJRXbdT`N`TT\L\F`^RXNVZN`TbTX\^TXdPTXZXfHVfNTVTV^ZV^PXTNVD`ZVVN\T^`^RVZfXTVPX\ZZ^RRVbZj>VR^\ZPbRjVbXR`PTZX^^lNPTT\LNZ N Z ^ X T P T J Z V Z f ^  T\Nfb^fNd\bNVVZbNZRFFPR`bJ^"!`!T#%T$`%&#\$X$#X$\%&V$%#X&^'J)&%*V&&)R'*(X)(*P*X-+^-,R-.L,-V,..R.X--T-).---^.-./.X0./..201`0/L,+X,-V/J/R,R-.`-Z..N.-X0-0\2.-H00P-P0-T-++,+T,+)Z*+T*`+Z+H)H)Z)^(`(V'N(*h*)H*)((((>*R)X,J*X*Z*\(X&H&&V'`*X&&(T&V&&V%&T&P$'Z&N''T'^))Z(V(%&X'(P(X(\*J,\(D)('(b*^**'>('\*)T-,)^+X*)Z('`)(F*\*)-/^-*R+^.+,--.0^0T1Z.V..T.3/1V310P10002f11`2V33Z3d2^6V6J5^3H456T3T5\5524X/0B0f3:1325J13N3d0R1N1`2J5`3X32X32B1221V11/,-^-Z/-N/.-\/-1-R/.-...,L-P/,L0T--F,R.^,,P.+.H,,V.R0L-\0/N-,,,/-R.P0./.0`/V.*L,,+X.`+J-1,^/,P-V-\+`-.*,,R-`-+b)X+V*+())Z()*)D*X+)'X&'b&)L*V,*,`,++T++-.T-^-F-b/H+.^,+X+,V+\,Z-N,d.V-`+*,T,))*\(P(`*(((*)*+)X*V+J*)\('D+'Z)R*X*L)b)P)\**,+>,T*R*+*'P(P('(P*'d+T+Z)++T)\-b*V**^*+*+**(*+R**Z+*B+P,)*,R**T+N+-+*T*N)V)(X)V&''L)*()(J)+,P,*+R++T+,+*^*T,*,)^*)*)(X(&N(R)X*+Z)\+T,\.F+Z-N*-\-b.\--.,/+-)Z,*)B+))V)`*h)+),(R+*+V+)**)d*d+\*)*,*,)`-R+'P)T(R'Z+d())'^'L%%&%&J'#V%"R#"<"H!T!Z!j HP`\VZTPVNVbP`Z`N lHbX TZ ^ ^ X Z H V ^ R R N H ^ZVZTRVXTX`fLH`PPd\\N\`NPX^fTTPRR\^lbb@ZbBXN`L\XZ\PbZ^`Z\^\\`ZVXT\VZV\V`X`^X\fZbVbJL`LbPVV^^b^N\P\JRbd^\RjVTN\X\PjNHdXhXLT`PFXjdfdJ\V`XP^ZbfTb`^`X^VJVPFVN^N\ZVVb\`T`Rd\XdVD\\J`VTT`R``ZX\fRZPZXRL:^`LZ^XdXRZVRXRZ\\\`NRb\TRVX\JLRZ^dRbhjfZLLP^flPbXPVTN^XZTZPDVX\VTZRdNX\RTTN\TJhLZ`V^ZZ^ZN`dP\XPTN\ZfT\XNZDR^VTRR^ZXfVT^XZT`^ZBP`PL^P\`V`dVXTX`P\X\RPXJVXXND`^H`TPTJhP V d B f V X L fP  X bLbN\^L\h\FZTRfVXTbR^NXX\b T V"D"!#\""$f&"#%&&P%&V'P'\''d*))V'')$b(&Z'N(V(H,^+*,b-+b.-f+V,*-h...---^./.`.T.0H0`0H./T2T0.V0/`0N/0T/,+X-f,/X0+,R/.V-P-/`-R-H-^.N00`///.--T,+\.F.V+)*)F*P)\))\*())))&N'f*T(*`))*(,P(T(*V)N)+N+^+)V)P(`'''V%^&X%'%L&d%Z'R'&$$%&\&%((&(%P&&%'T*)(,*V**P*\+*)b)()V,T,^*V'L)((Z)N*+)(V*V),-`-R-d-R/V,`++`+-R/j/1/^0/P/L3X2`422J3X2`03`1P21R3344R454P7X54`54R445X3V7311J-^0/T0144R3V74d131233X5301^1V1X2V26\51,P/R,\.-^,T/,1^0R-,h..R0H,h-,V10L0R.R0/.1.X0D-X.f,-,T-.,\+./R-b.X/.j../0310/X.V,.B-P,P,^,`-R-Z//T2/Z.Z.T-V0.,P.Z,--/-,-`,*,*),V+X))\+J+(P()*L+(*,+.^,,-,+h+.->--X/J-J.,.,P,*+R+-L+-V--,^-R.*D*)Z*R+*H)\)((L+V)()`*N+)P+V,V('(N(J)(**+T,,*R-+))*)&&'Z&)*((X)*T)^*P))\,+V+R,(V,)Z))'(V*N+++++**()Z*N*b,+*L,)'N((^&P%L))R()T)b*T*P,**H,*R.Z+N,X+F+),*,+)*Z-T*P(+^()`'H(N'b)J**+^+,R-`/.N.\0d-,b.J.V--,f,,)T,)D))(+^+-d--+*,)+*+V-*N*-*+P,`,))V,++N,%\)(**`*\((%(d&F((Z&X&#"L&%^$L%T#V"!T ^ D! X Z bLlHPXT^\VJ\PZbRbR TNb \ ^ R N R Z J l R ^ n d VP RVBdTbXXRXXPXXdTbVFB^\V\NN^T`^\TNVZV\\RVjHRTdZ^\RLRPPdXTZhLNH`\TTT^ZjZPT^XT\NP\\ZVXVXb^XZXV`R^\ZbJ^ZZZN^R\ZbPdV\XLPfDNZZTZVRNPXTVZhZPPXRVZbXZdNbdXR\H`V\VLVVdTZZZLPTZ@`\bLjTjZXTbJ\X`\JTfb\\F^dnX\\PdVZZh`Xb\JTXNfVVZTPVXZR^VdRbTdDXN\TlLXbBZRXdV`\VVdNX`XRXRV`^\XVHX^d`^XF\ZJdRdN\ZdTZZBLZ^`PV\bVTTTJNNN\PZN\\TZR`LpVNRL\Zd`\ZXfVJZVNBZLVV`VR^LX\PVVNVjLZ`TJ^VP`TP\LTX`dXTNLH`RF\PPRPhPP^`XNTP\L`P V \ ^ L ` T ^ f T Vf\\ ZPVFbfV\ZXTd`NJZZXZZ^`fV^\V`! Z ^!`"!$^%%$%`"B%(%Z(X(R'X)(&'^(''L&^(\&P&(R'(`*N'Z++*-,\.\/-`.X,^/,T,+,L/X.T./j/J1f1/1R.^0H1.2P2T31b//,H-*,-V-:-+,P/\/V.,Z-J/T,0Z0.R1^/-..-Z-T,/Z/-,*))V+P,*^,T)P)P)^)P)(\)P%%('(*(X**b(X'(&P(\(J(*(+(T)'X*\'^%Z&`(&\%%f&P'b%&&&%$X%%&()R(%P$$L%'^')@,X,T)-,))**T)*T*^*P+b*+,R+T+V+b++V,-R+++f-\--N-\-`,h/+T-d.J10H/j11/\1P3X141\2R5P3213R4V4Z312b5335N4X3N54X422X6V443`2R32`2.1V1X3174X3N3J543X4^2L35T3N4P2202T10`0N1P/,^/N0R.-T0F.,0L/h-.-b.,`-/-1@0X.2H0Z0j021.-V/,-P-T0.-`0/Z,R2T-b1.N1d030V1Z2X1R.\0P-/P/T,@,,/X.Z2T/R0-N2/L-L.X-h1Z0./-1.+T++*P+,Z+B*)H*(`**F,^)(N()V+b*,+Z-T-+0T/V-.Z-d/.V/,X,+,.V.*,^,X-h-N.b----V,*F-N)*,**f*X)R)++*R*+,)+R,N)(()'`(^)V-,D+-R,(*(((`''Z)&&V(T(((\+`)-d++Z*)Z+*R)\((*+(')j((*f(+**()L+X)(T)d+T*+R**X**)X(%)(X&*Z*)*,*F+T-X--X,,Z-\-`+)H++Z)P(*)n')*R))(^)X))`+,,++V.,d--`-.,-T.T,b--`,-+-+Z))+*R,R+b.^,`--\,R-,-*B.,-L*,-.V,V.`/,*\*J,R,D*)P)'f*V)(Z''\(f'X'%R%d%$"Z%#H%$!"V#"V!d XX\LhRTRRhZdXbVTJN`ZT`LXRZ \ P T V N V P NTTTRXTLXNPT`NfhbRX`P^\^LPd\VVXNdTX^XTTR`VNZPTbRZZRdN^NRNRXZX^DVLTX>TXfXZL\R^T\`fdPXZXX`^Z^\`\TR\VL\bR^fTVTNPhPTH^R`NRfXTLXThVV^\RXR`j\`Rb\d\R@\``\Z\VXX\\bXNR^LZLVZXT\ZPbT^PbZhXR\p^d\`\Tbd^L\bRN`^b`fX\VXXX`P\V^N\ZVV^dX^HVbRHXPNJX\XTXVjXV\ZVX\NbPV\`PZV^^bTXVZZXT^`ZRVdJVXRR^ZbZJTVPLJX^^`^TZNV`RJ^\`VZTVdVj\\VRV`dZP`TP^`RP\TLLVJTZPP`T\PT^RdRT^XXNNRZXHTNLZ^b\VTPVdVXJZTVRZ^XNZLVVbX^R`bBbDTTlPXZT^RXJHXh Zb N B V X N \ X TX \Z\F\XZZPZRX\\^ZP``Lhb^D`TXPV b$\!\!"X"$P$Z##b'^$&$&''R(`'('D('\'f)X)(''&^*R'(+'Z+P*),--./0,\,-,T-...X.T-`.,b00V0^2/Z2\11N2/B.+-^*.R-+\,,T-N-,,`./..`0,/.-0..T/\//+/--\.J,+*Z+^*+\+*\)Z*^)R(N(&'P&^(&N((L)`('Z)X'(D'*J()'N)d))('(^(%N(&%X&%%%%V%X%%Z&^%$%&#'%^&L)N&(&R*()V,-V.`,V-*)Z*^*\(P)X,X++-f-)`,N,T)*,,*,b,.P,-b1X-\-.,V-,,P/\//X0/0`000^4113F22L2X145X675\5V54X4X4Z5L7Z53F6N4452^31\1\1/L30316F5T402N1R1N4^45T4Z53R44T20R2V1...T...V0,.J0T1V.1/,P,-V/V0V/b2V1/D2V1R1T4H1V0/.T/T/-Z..H0T/`2R2.L-0./0\1J0L3\332H40/`.,.,0\-L.0`..1T/\/-0-.0/N//-0..\+\/,--X*,B+,T***R+*)Z,++V-`-J-P.D-h-,V,,,/.T,--.+,V/.-F.P-0-,/`.d/.b.+T+^,,N)L+,*J+T*-P-Z*Z.**+^-R)(V)()^(\)+X**Z*-(*V()X+\+V*R(b(R(*R&T((^))*(//\--`)'X()R(^)\)R'T)('R'h*N(),+N-f+*V*+R,X()(Z))V)F(J*')N+()+*)X(J*P-,/-+P,`,H,b+**)J*R'(),(X)H*`(*'F)(T+*)+X-X++N/@.-,.+Z-P/^/^-X1,b.+Z+*Z*V.),\-R/`-V.P/R-N0R+N,+b,-X.,X.d-D-R,b.J..Z.)^,-h*^*)(*(T(`)V*`+N(*(b(N'&N&%V$F#$##"T!V" L!LVbPVTd\TdPXVfRPd`J\XNPVRN` J P X f D X P LXTdPTd`ZFhHTbZT\XVRX^TLbPfT`bNL\TdN^`bP^N8LXZJZX^V`R\HFZTNf\\bPVTBVhVX\TX\ZP^HJDPbVhL\LLRJ`PT^N^NZNBVPLPb\V^PXL\XbRd`T^Z`Lj`bdZP\XfLVXXdRZJN\fV\TNLHfDZ^`fTV\hfFh^lRHX\^\bdh`\bTRbh`ZV\RZ`fVhVXRVR``d^`ZLdP\`j^dFTNRZLbVXR`\VTX^LZXVVVfbTZJdL^TVZNNZ`XR^X\NdbPNb^ZV\TPVfHVZZVbZVfTXVV\^HfNhX`R`FbTNJlXT\hDf^FPhTLXbLbNVJHZZ`dHd^TdPRLXbRTNHLR`JXX\L^\RHTVTJXF^b^LTJZHNdR`X d  T ` f \ LR d ZZdVdT`\RVlXTZHTHhRVRB\`LbPPVj` !!J!!!b"L$%$$%%b%%*R&''(N&L'`))'\')X)X*T-*('Z))V(J**-H+X,b+\0-0N0-\/1.X0b/b//.R.Z/2Z.0X011V/2`0/-X,b+X,X)T++,-L/-,-d.0Z..T-b-H.0/V.d0-/d.+X/-/.Z,/-V-d,*d+L+*T-D*L*d)'(*&&^'J'X()(>'Z(N((())((N&&&''*Z'(&N(`(%'N%&^%^$$R'&&\%%%\'V%V)`(%'V'''((+*R/*-/D,+F)^,X,**,,.+b*)+^,R+T+D*V**b,*.X.,+D1X.,P-/-J.\1Z0Z01/b0/0d10V13h4J5X5R4X33\66X:T6^74f5f751N622`4N2\5T3P120b1X2122X521\2T1J2R3N3l27d3R3N4b543`2Z10T0H.0.-N0.R1/-V0/-R06.-1/1V0Z003L/1\21>4X0R0\10/01\1Z1P2\1\2T1T1/P/1N12T101^22R42....0X/.0V121R0Z.\.-/R0321.-0\/N0.d,X00R.-^.R,,V,X.J,.J,Z*R+V-R+V0//N0H100/.R+-`0-`0-/.-/.V/T..-\0.\0L203L.f,+.T,,),,,)j+X.T*b-+-V,J,+)X+`)X('T&*^*R(*L+,/*+)+T*R)P('\)H)'\)j)B+P)-R+*+V,\.*)V()\(T)')'\'V(')T,+)+-N**L**)P++)T+')(f+J)'(()b*\(P*X++*,-^-.X0X,V)Z+J+))b*&(V(\)^*V+&))R)L(V-\*)(T+N+d-+h,,Z,V,R,,P,-.Z//,.++,+-(+X*,/H.R.,N-L+`/N,,b0V,R-/^0+X,/d1-.N/V/V.)*)**R***R*X+**^*P*V)(T(%^'T%R%$"X%V&!P"X""XDT^\VTThTNXXbVRRdP\Z Xd V T f J R \ D b \ F J N X X `L^LLXTRXTjXRVXXFHHRZDNPbRXbbXXPTbR\P\\NVZ`^Hlbd^fZRJdJZTdTNbVX`\VZ`VV\\VV\hXTJZHb^bLFVdZX^T^T^N``^`NP^VXTb`b\TXXXVPT\NbRH\b`^fZ`XdTVTT\RH>PbLX^NN^X^ZhXTrf`lLd\`Vf^^^\TXV^P^Zd\\^Z\^\Vbb\ZHPR`T^PDR^`BVZXPLRN\TFZDX\VfVXXPTT\ZX^T\PTNXPXRXV\^RVXP`Z\LlRHVRTRZDPZTXVXXNT`RdZ\LRZTVZVVV^J^PXTXV^NXhRVb\ZV`RJNd`^TNPXLLXZ\NLXNZZ\LX\PTRHXRXXPTPfH^ZTNV^NNRNFFTVT`bZdDPP X Z V P X F X  T \T NHXNZHbBV\`fPRXR`\RRZ^XXPV^!` !`!R"b!!J"L"%%R%V&&\(&f''%'^(N(R((N&'$T'H(&*T()L+-T*`)R-X))*^+++^,^/2X/.../f..X-0././0Z/T-1:00H1`1J...*H+T*P*+*+//-B-N.-Z.N.X.V-L-.-Z,X,,,.F-V,+,N-N,,,Z-T,+T+F)b,+*(L+)N(%&'&&&R((&P'(&(T('J)T'X)b&T'R&&(^)P(L'X&D'%(Z%$$%`$%$`%F%Z$X%%`#&R&V(T)X&&\'N*)H+,L--Z,V-+P+'*R*R**V,,,,*^))+T+P+Z,-`+..,L-P.`,,--L/^-\-1D//0/H0n0/110X04^233J5\5P7Z4735L64V6^65X4R3P22X4T6\33\6X544V444N333V545^43\6X6X5T3X5J44313V1101/Z-V/Z/./0N/X.,X.b0Z-Z10V3Z0F11V11T31X2R2Z2P2L0\0V2/J115P12R00J/0T0h2D421P2>112N3J2Z2J2^0.Z./1.0`01X20Z0J/^-R.b2\2@232`0R0R/`-.X//.X10.,R-,.0F,+`+L,.+.Z2/10T001--1.01N/-X2^10L/0P/R.0Z//X0P5\/0b-,-b--P.+-V.n++P,R+*.V.Z,.`/+-,)P(T&&j'V)P++*V+++N+^+)L*R)'(T&^)L(V)`))Z**(+N,*h**f(&`)N'V''V*L(b(&)N(\(F*)+^*,)(+*)D(V*Z(B,T*V)')(^+Z*)L)P)V)'P**+-V.+/\+,V,l(L,(^*(&^(*Z)*V*T)+'(R)))*J+T-H--J,-.-,\,-,-+f.-d.N.T--+Z+`+,+h,.b,,/-,^/,X-/P.N1d0N,//.d.-X0V/.Z-+P+J,+,+J+**)'\)V')N(N('X&'`&Z'$V#$$#f$V!^ $ T`bVRZRP`LRXZNNV\R^VTXN b H Z V  T d L J RVPXZP^XPPXTPFjPN\Z\VXRbLJdVRXZHdNH\\HVXLfNNTXVVTNVdX\Zb\PfVbX\Rb^^\\hRX``\N\VN^PJRPbXfLZXdXTTNbVT^VDnFRZHTNdRVfXjNT\BbL`RNRRddXLNZV^Z\TXXXLTXJR^XRX`NPRd\\X`\^^\T`TdddZTV^XZ^R^PTRZH^Z`\`NV`d\XdbZhTbXXR^ZZ`ZXVRVLLVRZLTbV@bVRfVT`\ZP\X`bT`PbNTZRb\JTVX\XNXB\fVV^DPZ`TJ`RXRXV^hZZXVZ`ZVN`TpP\TPXV^\VLVL\ZPTT`P\bdL\\RV\PVdLTL^VJb`L\LVXfVTTVZ`hXHVP\VVXFddV^\Vbbb^TdXZ`XX`\T\RJPNZT X \X V Z ` Z V T X X X `^XXVTZXXlPJR\P\`ZXZV\TZ`lXbT\  L!"T"P$Z#X#P'b$Z&('Z)&''N(V('\)((+'R)'(R(\)R+X*P++Z*()(,*-R./J-./062Z/H/Z-N-f/\1/N0P10.b2R1/`/-1J,.-*+T*+b,)>++,-Z0,`/T.f10.Z.Z1++,`+X,H.,-+N-,,-+*-+.+V,N+V+L*)'(Z)J(&''\&%J*R'T&Z'^&\')'V'\'')%&P(T)X(X++V*&V&V(&J'%%%H$V%#b&%&$&%&&L&V(J(`)J)^+T+T*))^+V,N-,*L+^,+@*X)X+X-.X-V,R,,-\-R*R-T,+Z(,T.X+,,Z-,-.P/.N/.0.3.1Z1J0Z02Z32243X4`4224T6L4b62433V4455J7544\55R5X5544V6^2345R423R4N4T4^2/V1102X3X21H1Z0J1^/`/N/Z.P/V1/Z/`0.R-f0D002P0P111^1L3014/2243/42\5132f10D1`00/2T2N223d3R2J1n310/.1001B3`1^/L1Z020V.227V3\122Z/N3V0/Z-L0/\2V1T-P-\-F,Z.-,-^,R0V.`/\11Z3V242V4/01R222V10L1b1/Z1.^0//Z.T0V12/L/.V/Z./^/Z,X0T.Z..+/+h-b.,J+-/+*h)L))''%)X+D**,+,X,**)P'N'P'^'L((V)J*+X+Z,*^*\*P,R+*R)N&%J)%%\(P)P)N*X('(*Z**J(\))V*+*))*'())N*(@'''f*)N*\**R*J*X++H--,*,\**)*')(N)Z+*d+)+(()l')^,),L+,V--R./,+R.+,P-Z/*,--b,,@,T)V,*b+R+d/T-T/L/+/-0-Z,T//-f/10///0.R/-T-P,B,+V+,V+P,(*)'Z)R(`)(`'\(\*(*$%L%b'R$T%j "V! J`\P\JXZZ\XZTTHPTPV^`^XTXP^RP`` TN d V P R V LX^nX\\^R\PbX\VLVXRZBZJBPXZV\^bNN``XXVZHXNXX`X\XN^XdPNRR`V`\NZZTZ\X`hVbT`X\XbN\TLVVX`\D`TXTTJfh\`XVL\PdPTXThV`V\XFfX\ZVRTPdZX^\6f\ZhZZTjJTTTVHJLTRLV^VbN\dHLLVZX^Xf\\h`Z^Zn`^h^^XbR\dfPdbP\VbZLhldPV^XV^^TNR`TZHVXZNPTT^TZLdLVTR\^VbVR`Z\h^hd`P^ZJJ\`X^XZR^^X^\RZX`\N^XRDdRV`\VZTJh`\VZ`X^NZTHZ\TThTfHfNZNZ\h``VRPTRPPXjXZPT^`ZZXRZDTVV`\RN\VN`NXXNTXFZ\LR\VHNP\JVNRRVTLXNVbPdTTdZVVJPb \N` VB P V L ` \ V \ ZP TZXjZ^NXVdTVZ`TPT^T`hTZJNLP` \J"L!!!"#$%"F$#N%V'&(X'L(d)\)))+N&''&T(*F(Z(H+`()Z+Z,R.+L+*,P*H))*^,Z,--V-.L/./.01R2/.6/00Z/L0/\/X/P0\-X,V+*J,V,)T+)+X+T.H.N,,\.,L/-+/J-P.T/,D.,-V+R,J++L,V,Z,R-P+T,R.,.,`*()b(Z'\'^&%$D'$$&&&&&J)`)R(Z'\($(L&(%L'(&R*\))(R*\'^'F&Z%%$%X$R$'%%T'\%`&R'V')('^)D()'P+)P*L,^*\+\-,L,\+X*++-^,-b..X++T,**P,`,,-+-H,,.H-/T00/.1`0/0P0V2T11V0\11L15V433\1R53X5D52454^5T3H33H566657\8J6R5564864633N455N2>5445h31R3P0001X3R/10..L0T3R021.-T00^0P1L0^1f22T200/`01V5b2V3H2T2X31P3/F5^2V2^0T3^420Z0D1d101315530\3N10R1R/J62V4T2N201^3X0/1Z320H2T12V01/X6`02N50`0X2P1N0N0,P.f0R.T/,X/0/2/2J202d4L2\22V51Z1X12F1^/0/202X0V/Z3J1/Z10`1H,.-R..X..d0P.-b-J-V/--+\--*+)''V(X))P'P+N)X*^+**R+V)*(*Z)'^(R$\&\'Z'+`*\+-V*()+)N'&%\&<((D(&'&V)R(&)V)X(()b,\*+*)()')F*(*L(*&d*&&b'Z++T)F,L+,b,X.V,`.+*+*`)X)^)Z(Z+,V))b-*),*)X)Z,J-^-X-X+N./,,++--+N,X-X,-+,\-X,-X*X,^),V+X-+.+-/N..X1-20.1^3N1V01j/L0^--/V-^/,*T+++*N--+P*+Z)(&R)+'(^(N(^&R&R$$X""#^"R#f PHLVPLlXJ\ZJbd`TRLbRhb`XNN R` L Z X X d R ` P ZPP\\VTXdT\RXJJn@bNXXXR\F`RZ\`bTRTd^\^PbZH\^bVd\`^P\b^N`^XPbX^ZT\\\VVXhZ`VXVNLRl`\Zb^T^ZPHRVZZb`d^^V^^JbVLjBR^N^>bRFZZTNVPX\T\RRVT\`NZTRXXJRZV\N`TJRZPP\V\P\P`JZH^XF\RJbPFLZXTXJXbh\db`VV\d^ZbVnRfZ``bZb^P^TbfLX\dXhXTbPVXVLNXL``nVPZXRZVVNP\hXPdZV`N\bV`N\XRHZpHRVNNjLDZ\T^PVT`bN`H`ZFZXbT^HfVhPfbPVHVjZNV\Xj`bN\Zf\^VX`ZVTRf\R\PRNV\PfVb\dTJRVZB\^X`ZXX\T^jZT\ZTRfZRXPbdLPRPJTX^`TRZN\b^\TbV XZ T p R P V R T VP ` Z^`PTRNH\XNXZVZ`LXDNZXTV R"f!T$\"%Z!L"N$T#J%%Z'^(`*Z(F,T(V(^)(X'P*)Z(%''Z&(V(^,^)^*N*^-+*b-V+f-*F,+R+J+`-Z-R-,J./0V1-Z/^/\0-V/.N/-Z.P-/b/L,,+^+^*+**X+Z*-Z-X-,d--.b/^2Z-.--,+f-.f-X.+.D.,R.+*/H,++,)+P**(`)Z'X%'$&#P''Z%T(L)V'&%%^$V&%f'%^%X'R&H&'`'T(++`(()(^%'T%%&H'&$J'Z&J'b&X(R&&&''T*`*)(d''+*d,\,,*Z,-++*J-b/*,N+`.P++T+*V*)^)P*J-P-+V-+R/N-.T/\.T01.1f1h.H0^.t2B02Z023N3V3P25^44235V46433`1345668X8D6f9N9V9H7R97X8b5R53356453b4^5`3N2Z1H2V111.00/20N00/1.X0L-.-0L1.@4/L230.N1V0P00`0/P2V22N2^22V1T32`3^1210T202Z2b03L21502b1V2N4N3N202T522V1T/L002V414\44R532\53^2b21L3321R4./\.-L0X0.N///0R2Z4\2T2T54`3h34Z5331^2Z5X331//10/2P/B1V0^1/.P/Z0V.`00,Z.\..B0/V1/^..,+`.,b+*)()((X&'N(V*V*d,V*++)(''d*J)&D%%$\)Z&)Z-+-\*X*\))X('&#f&R&&P('&N)T(V%Z(#'T*X)V+)R,,,`+X,^')'(T*X(V(J)\'R&&L+Z()T*)*++,b,T+R+)*`-N*F*X**((P)\,*(*N*^*X*R)*H,X,,,T-`.+-J,+T*R-/+/\-+V/-.+++*+P++X.H+f..\/.^1...Z2N00j3`2\/b0X01//.1Z/0T,++T,+L/.,Z,J-.,+*L+*Z&P(T)P&&&%#X%V%$\!N !RN T`PRRP^JRPh\d\PTVf@bHV\FPTX N J Z J X \ V N<NVH\`fLVN`VNT`ZLBPJLXZP\b\\^ZZTLLZPRNjb\RXTbV\ZTZVbXd\NT:`HV^TT\d`VZPNNVH^\\X`LNbT^V^ZVX\\B\Z^Z`L\dVTZN\\^VZXPVRVRZXXX`bZX^XN\dTRPL\FR^HRTnPV`T^\VdX^d\H^\T\d^RZNZXXl`XRZLjZZRf\T^`L^XVnTTTV`fP^fb\NhPV\jhd`XfH^>VTNTFTFTDDZPR`bTPVZ`VXRlTXdNV^NTXP\`\XZZVNLFZLXVPRbJ\X^\XNTNRNTVP`Z@d^RdNJXnPZPhRZHTFZNp^XRXN^LXZ\FTZZDZ^RT\>PPNTVHXTZTJZPTPTTVPHXPXV>ZLVP X Z^ ` d Z ` ^ T V XP \ XZPVZ^FZNRV\H`D\VRL`VbT\JFVVTRV T !\!"Z%`##L&$N%X(X)h)(d)R*\+)P(+V((((Z(((d++*b*P+)V(*P-*V-,*^+,+`,,X,T-^0-/+b-/1100\11R//--.V-,,X+-)h,^-)),+-\.D.^,-V,.V/,V0X/X0-,,P,\,P---b.X/\-,F,P+,V,-++**()(P('(Z$X&Z$'#\$`%$R(X(Z&(&d%d%&$%V''Z&Z''''Z((*')R(T'@%%R&&T&Z'$$X&&d(('R(&J)&&`&`*'T()J'X)\+T)V+T+H,.,.J-+,^*--+N,*+^+**((,*J+,+-**T-`/.F2b0Z0X10P10X202^4\4d232224^43\55575^6422N5R136Z7N6Z97P8^9V:b98T8798453\5>4T856454^734\01X/P/1F/\/.0B1/`/b10/T.X-,0\/1V311V/^0.^-L110.3\111b10L232Z603\4110R00P1^2V11Z1Z3R2V3L21R01V354\2X33^42b10D3J3Z45Z56^7F432V3R13F4b3>2^1\2X11P0/Z11h22H0`3P3X111332N4486T4V6646T424\5R22T1P02d/L2P3/23L1T.`0^.0\/d0/T/.-N1R0/.R.d/N,-Z+*)`+)(l()()()\)X*\*L+f*^,`''&T''%&\(^)b+N,*\++\)H)X)'L'f&R&V&&)d%R&^%&P'`*''h)f(**T*(Z)*@+Z-^+(D*('T)((T'N+*\(Z())P++,b,X+Z**^),),)*,)V,)Z)+^))*V))L*Z,Z+-b,N,-V-N--.,+-X+*Z-T*Z,.*/T-,L0T*L-*`.-P-^-P//02V0V/\/.30\00d2Z10X220^1N2f/R0.---V0.T0^/0f0T.`/X,V,.)+**('V'()&R$F"P##^%L Z" VT Lb\ Z!^Rj R`TTL^NZVVH`PZF`R\dXX`L^T\N X R D N J T J ^HDJ`T\P\R\VHL`P\VV<LdT`^RbZX^^^T`ZVN^NVbhVfJZX>dVZNPR^bNdVPVPTPRT^TTd^TVR`TD^^bX`Vb^X^XVXVRRPRFhZbV``PP\RXNZ\VVRV`ZXX\`TT\TdVXZT^b``XVHhP`DJTXRdPZb^`^b`V^RPh^^Z`hZ^VRX^V\`dZVPTb`VVV`XRVVZP^V`ZZ\DZXXT`N`\dZLX^^X``^N^Z`V^VP`N`^TR\LTbPRXVLPNh^VX\Vh^HZZ\JR`ZZfZX`^N^PVPRLZPX\RZX`VllZT`P^ZPbVZXPZRLXbbRdPLhRRT\ZJPNdHTVTTVXhP\TbRfVXZPR^Jbb`XVXdRnT^b`LTZP VTdZ ` V F F Z R b ` H ` P NN`R`LN T\^ZbdP`Zh`XV^XLLXbN^bLZH\  !P$!"R# "`&J'^&%&J'X()^(X+X)+V))&))'N+\)V+R))V+T+T*)`*\**+)`*N+R)++,,b-,^,-,-b/.R.N.\/01/.-`0+b-Z--\-V,Z,V,`+B)+,T/.,V-V+*+,T-V/10P-R,J,+N+\+J.Z+-T-D/f.L-+d,P-+*+*H)Z)X(X''%'X&X%f&T%$X$R"P#R%$'(l%$R%&&&#d%Z&`'(*(d(X(N(Z'')T)&&Z&&N(&b'(P&V&&%&$Z&$'(\)%$N(\'N(L)R))*--T/P,+V,-*X,R-\,,.//L-Z,+,T**))P)Z),T+V0R,J.Z/P1X120P50V2^0/2X2H433R1h1X114Z5V4P354F45T2R33f5^303N5Z7\9T99V99P:V9;886L:7Z62X47573438Z41R1N3P1/0\/`//b/V0//P/R2L0,-+-T.-V1\0Z32F20052X3N0V/Z100\11J23\022J2F27V2L45Z2P1304134V422V62\4R324R111422L11L35X4^5;P5^631N1Z1J22R2V30N03L2R1P2N00b44J//1N3H012L5\675444F5^446362d302^22N2V42P4P22Z3V1Z400f2b00/V01N1N.V/T1/1L/Z.+Z-*Z*`*)*(D')(R'()X('R,Z)V*\)R+R(X&T&\'&)(j((*^,)T+`(Z)V&(^&J&%\%%\%%&'X'R%j'b(`(Z+(P+-V*)V)b*)*)*V)X,P'L*H(()T(\)*)**('R+Z*(+*T(^+((**`*+*X*\((X*T*D(N)*-P,*Z+,/0.+`.*.^,+*X.L-+Z++.>+\--,`/R,.+.-/-0D10^31Z11Z0/P31H14P20b/T32N1^3N2---.X0F2/b.\0/--J.,`-,V-`*)H(T&L()&J'X#Z$$f#!Z!#R!"!ZT V^!h^FZ^VXhN`VVVJ\ZZLJRLRdZZV\dN`X d L P \ V R L P R X ZdLPfVHVZ\XXLVhVPZ`\ZVJV^ZjRPb^jRZV`dZVdVVfZThNRNX\VbZPX`XNhZ^\J\^`RlT`\NR`V`\NVXT^bLRVXfN\JX`VZ\`PNV\fjZ^V\RTV^TX^Z\VP\b\NZ\L`PbVbbRZ`RX\VbVZ`R^PTDV`RL\FbT\XZ\ZPLNVNLZR\bVX`fRbbHZdbT\D`T``\VXT`L^Z`b`ZT\BRVZL\PRHfTV\XFJVXRP^P`ZXLXVPdXVRRRLTTbR`X`RP^RNTLZJZb^T^>ZPJVZXNRT^`DVZZLjHNDf^XHLbV\ZRFTT\XXZN`b^RX^XZbV\NbN\NLXZL^PTHVH^LhPH\LZZPXFXZLX^`^XTHRVRTLX\V`LTRR P J \ d R J RP PRHTbXRJbLZ\P^\VRRV^XVXXZdZXD T"R#!^%#!"T$&#P$`&'(V'(''\)*\(\)V)(Z+T)*^))*)T+**X++T.R*P*Z(^+Z*X,`,N+,-T,-++,`,`-*`-0-Z2P0.L20^/.-,-Z,X-V+V-.,\,,-,J/,P--^+\-R+`-,.^-1R-,X,,,Z-^,h-,T0-P,T0Z-X-,X*-)+*(T&P''N%&$$%\%Z$!$`$^&$T%%$&L&%X$N%%$&\''+d('\'%V(*%'&$('%$R&%%H%&%\&'&(V(R'%(\*R)P')V)L*)V,X,,^,+`/+^-+.T*/V//J.X0V.,^0T*X+))*\*R+-\-^-J./b.1V0P33\2N0V2h0P0041\2T3^2F35V3145764V422440/33J34554679:T:889N:53X5P6D54T365Z4311214/J/V1.^2Z0P01`0N1.\,.0/Z.-H.V00T130P0L1/1163Z0R3d122`4T43X1`011L1233\6V362V2F12@3R33T67Z563P222f211R31b34j4X4655X7f6555V120^3T312P32203b45P41^4<2^/V243V35R6Z5P8b59Z6R32Z5Z4V551d52H4331N47X42J124b2P0//Z//2/0110/V,J.-+V*\(,+V*V-H''Z'Z*V'Z*L'D(r(V())((L*(`'V''X(,d****X,'F'R('$X&V&Z$&&%(H'`(%&('(Z'J(')+X+L,b+N***X*'(((X+&&)\)L)R*R+J+\)N)\)+)b(Z)X*'((N'**P,H,*X*)'R)\**))L*X,,+L0-^/N,+-H-^,R.*Z+-V,\,,\+Z.V-/N/-b-,V+Z..1^.F3011T0//0X4\21V16P3^3>4102Z1X10X0`4./.Z0./,^/-^,R,.,,,(\(''(X'R%%&##F"!P#!" ""V!# XRP"PtFT`RdJRDVXNfN`TN\H X Z P \ ` L X T R^N^`VRV\NZPTFPZPXZRRRRTTfNPFRLZ^V\bVZPZ`\Rb\J^H`\VNV\NXbT^hN^PjTDj^Z\VZ<Z\NNN@PX\lN^ZXjR^^b^T^XTPZ\^`Zj`Vb\ZhlbZZPPT^dVVPLRbVdPThfNPLfP\TfR`f`VZZh\Xbd`bXXfXp^\VZ\T\\V\RXN`HX`NZfb\bR\T^``PX`P\^VbNdXHZ^XNVTb`X^d``XV\``\bNJdXTZLj\bJRNT^RRR\X^^XN`ZVLBZTXHPRXb\L^`N`@PNRd^b`bPVN^\VPT\V`VV\TNPRPd``R\TT`HRH`T`\`HTbJVVVPRTd ^R T N V R V Z HZJVR^Vb`hLVV\TRNLV^\TTTHZV\fLZRLVXN^hR!Z V b"\"\#V$%X$b&'R$%X(X'&)()+V*(+L()R)V()(,')^*T**)*+P))b*))X)T+h+**F+l+X-+-,h/T.,,Z0Z//N//1Z-P-X-`,-f,(,+X/V*-`./b0^/Z--,,,T+F,+R.J--+^.-,,,J.l-D,-P-.V,+*F-X+X+))'T'(J&`&(&&X($%$f%Z#$V$R%P$R%&#&$Z&&V&&Z%^&&%V*R'$&%&&V&^%P'%Z'X$R'&%Z%(&$&P(&'L(R(X()P(''^'((),*+J-R,-,,X.+T,-R-X-X/H/N1\-V.V-V,*^-*d*V+L/X/R/.,/R1V1033/0Z0//14101B3`5511\5T445\34Z43V322d3V5334\6^6^5V5T47P86977T97P54^442f33R64T33h30V/1B0`2T0/.X/\/.Z/0V0L0/H/0X.0b.-0N/Z2/1\/H21X1`2P1V10/232P133d32X233^4R2535J3N2V1|3L25D4X45l4T5\432X1^/0V01F3\5P24V484P5T3V642Z4^3d53<5X53434546R543423112/R33\7`68h8^56546\95V5R42N41552J6Z6R6\6T5X45T2P1..H3\/P2113V/1V/,^0V.X++)H)+P-*(^'''R*X*R'Z'\)T&(R%j'H(\*L(&&T'P('Z(R((N+d(:(b'&&L'X&N&$%J%P%X)\'D&%Z&&(\'%Z)'Z))\(**))T''%(&^(Z'*)`+(()*H,`+)'Z+V(((R))Z()(())**+X+((((X+)+*-*-^.-,\,X,,Z+,R*-,\,\...,,Z0/,.-,L0.Z.T-00X3^12X1//2012b4R40Z522V3^/234L3T2V31-R..T0j--V.-+/+V+.V,f(^(V'%%R)h(n$%H%b$\"@$^"!#!^"N$Z!` b!H ^XTVXXd\^ZbN`RbVP\ZXV ^ \ N F ` b T`bbP^f`R^^TPVP\TXVf\RXZLPR`^^RRRZZV`TXVDTPTZVZPPXbNRZXZXL^RZ\\^XZdZJR`ZR\J^`VVT`N`Z\XVd^R\RlZV\VRX^B`b\X^Zd\P\TVjHRZTVXXX^\VPd^^^`VF\H`XHNTV\JPDXTRVbbVTZTRjPR`^VZTNTRNRd^\dX\V^ZXld\dZPldXVf\XZ^^L`dd`X\bLdTRTH^XTTT\RNRJ\RJ^XZ`JT\RRJT`RdZ\R`NJRVPdZV^VPLTZXVP`\V^hjJNTVTTfZd\FVL^LTbRXRT`:^^XH\VRZ`PR^PbZHfHXV^ZTTZ\RVTTXR\NNPPbfPXPTZ\\VTTdTZXPXbN\j^TZXTJb\^NTT\PX\ND^RPLZT\ T L V ^ P N N ^ V X^ XXVNfXZ^VRVJ\R8XZVTNZVVVXVTZRbVPV\\` b!!N! V$`"P"#d#"#P%%T&'&'T((D-'V*T(+R&(\)R('(D)))*^,.`,X)+`-f*,))P+P*'`*X((X+R*R+Z.-,Z,-P-\-,b-H..N11F.X.^----d*--R+.,L+.-.`-T.T,Z-N,+T,T+,N.V,T+,+V-F-+--d,,X.P+N+,+\-P+T,N,+((X&'V%\$%$\%L%l&$h'`%R%X%J&&'%$h&B''T&R%&V&N&D'V'Z&J&(&V&&%&&%Z&Z#%##&&R%T$$X&h(F&Z)`)N)(X(&b&()D+P*d))**,N-**Z-L,*++*^/-/b/.-Z0.N,V+^.**----T/,.1X3V10232002L/L32643V4\4^1`334Z6f5Z3P4T71Z1P1X3N0V3153b436F7;46798L85T464b5N243T55^51R2X2N00f0/b0-,R--P,--.Z./d//N//L/X.-H.-2114\32P241N3V3H2T0d2\32414P4T66N6L8462b22R3P4V2@2`4X6N7676644R5X5f3:2^256Z6Z7b7P8P5Z4444R45\7R5R4Z2Z7b34d8V55R8\55V856X633213f4L5X9h6Z7R5H8^866:7`75^74H2`4\5Z5^4d645D3P2N4\4Z40N41N1/X1F2Z1X42\02.,V,,\+b,))N-*R-V,)V+T)\*V)+`))d(V'd('&(&X*''(`'&b('*()'%P$%N'F'%V&$\%%%'$&$R%%'('(^*(*(N*d,'\''D%&&((R(((*X)V,(P*F*\*V'\&P()B()'N*X))T,()R*^,L*)L)*X+\*)V,*P*`+L+R+`-*P*P+X*+,-+,f,,0Z.Z--N-V0@1X1f0-+/.^-/-Z2Z11P41Z21T3`0Z3^332R2V50/\0/J2L31/\.L.p0Z.Z0P-/X,,/`0N/,X.V,d.L+*'\'R(`(R&%`#Z'$T%V&^%!J"Z$!^#^"!R ! T ^PNdRL`Z`ZPXhVT^ZRdT\VZ h V N X \ F VN\L \Zb ^TfbNNRF\@bTPDTNPVTbNXNR`fLLJZ^bhZXT\^Zb\ZXTX\N`^LR\`V^P`RPXhZPbR^^NHVTXPJRVJTdFV^\RTNj\X`^ZXJTb`^\LZ\Z\P^\RT\TZ^TZZZ\P\bT\ZfXZVfR^PZX\\X`^XJjVZdJR\BN^N`fhf^`fhTfZ^^\\XbZlPX`b^`\bbZXrPTTNVXLXbRb\ZV^XR^JPV\PZXdVVRTTXZVbZVTL^X\\TV\VPTbVRdZZXdNPFNRbVX\\LZDR`RLZdPVZVb^^XTRd\\^T^ZfNVVZXRVNX^NTXZ^RXZ\NZX`PXbT^TZPPHVHfJTfRJ`ZZRRH\LRdTfP\V`^TXPJV \VT  T J j Z ^ ` T X ^ L`TTRRhR^VT^`PjZfVXP^l`^ZDFL V  V"!V"Z"H$"###$\#'&&(^(Z(T)&()+(d+T,^*T(b)X)V(()**T,J+)+X)T*)L-(,J(N*&(X)^)T,+,+V-.X-T.-P-/R,/P-0L0,-Z-N-0,Z.,N-f-b++R,T+----T.++H,--f,,V-Z,+P++\+,Z,,T,L-b,P+)*+N-*^+,P*^(&>(Z&&j&%X%&')&d&X&%#%#$R%%'&%@&`'P(&'T(%&H%%%%'D'N$$R$##R#$$J$&V%f$$R%&'R(j*V+N*X(P*+@)V)R(T+*))****)*`,-.*R,,..H/\/X/-,X+P-Z*X,P,.^,-*--N/0h1X313^5V3J2Z4V3214J4541L7`73Z3R4746P644X2b2T3X55R6T4P57N66V2^46b8Z67562V555Z5V3Z53J412321/1V/20^/`-Z-Z-R,-V.b1T./\0/.X1/,.1`.Z1P13T1N2R1Z5d1X01/X-00V24244^5X7\64Z5D554f68P737V4557T8H77944R6\3T7\4R84R345886J6V6`53T63V6V33R45X61Z75896 :78`6Z4P3H44133^89V9\6X87`78R86\97V7\58354^75695P73\2N4H34D0\/1211L21`1d2@./-)L-j-R+V*X)+T-\-L*R*L,Z,)((N)^()F)V('b)b)R(`*,(+N*P,(*\)&b(&T&&(%'\&B(`&$&V%&&&&&%Z'*T*\(*(b(J+h))(&d$&\&V%&Z)'V**V)''N'''$Z%(X)(b*H((T**X)'X+)**,))(h*+)()*+*V*L0X++**b++,T/\.,Z0Z--/,T1.Z1Z/\.-V0-N/P/.0P2T32V2X432\3h51Z10L3^5/0/R221T6T5X2B0^.-X/\/h0`./B-Z-F.l-.N,N-+)Z*&((&%&f&%!T%T&#J%$$"V$!! Z X!\ XZRPfJPT`\Z\VXF\PjJ\Z R P X Z X X N N ^ ` V  H`XFZNTjDVTX\FX`NVRhT\ZZXZRTZL`\LTXdXbZTRVbJP^T^\NbXZbR\X`\d^ZVX^Pb`TdF\DZ`b^dVVP\NTP^Z@lL`bd\\`VVhXTLbXPVXblXX`R\fNT^RZZfPNV^NXbZ^bXPbXTHZ^XL`T^bNRLhVLhVXZV``\bVX^VfdXV^\VPZbbbbXf`XXRbV\Jdb^Z\`RZRNVVPXRJTZ^dX`JR`ZL^XJhVBRPVXRPXR\RJbZ\^VZDX\dLTVZZ^\NPP<dTVRLfVPR`^\F\XNPbN^XbT`XJDVNX"Z\\XhRHXdP^XPVZZXPXRTR\P^LXb^RRP^^VXLFXZ^ZLbJR`R`X\bRZ^NVP\NT`NNRL`Z`^RdJfN\F\Z  P d L \ ` \ d P  ` N^NRZVd^V:H`XVJbPF^VV^ZZ\!! #`$^!R$^"%J$"^&V&&Z(j+X(+*+V)*))f)(d)R+Z(*Z*'+\++'(*\(j*)*N+(b))X(b)))(J++H-h*N,-`/Z/X1V1X.-`.,0X.,L.`--,J/-.,`-\.-,,-J-/R,+,,L.T,+R)R+\*,N++T,D,X-+Z-++X-)L)Z+J,*,J*^)''`&V%$R'P&^%N%%d'&&&&$%%^%%Z(%V(V&V(Z)l'V)^)L'Z)\('&&$%'R&P%L%%`&N#Z$N$V#V#V$Z$F##R''('J**())V.+***(L*T*))J-+d+++X,Z.,L,^--T--,,b.\-h+*+/V/./.,-//0\0F5J44X333J320F3R3Z25D3h6X4J2P5X64P433945D3H5446Z7P6X73@54X56N368X7X533Z6\43Z3R4Z3P11N0T200H2f0/-X/V1`/.\/^.0,b0-`.\.0/.b/B/\-P,,+\/0L35H13d04N/^3X2X120V24V5J44V3@5R5346667X7R;7Z5236J57V7P5545T5T6V76P645P5T7989`:d:7\6Z7T73646N5`44H5858B8d97J5T6J575626^545N9^9X7d8L9766P69V6b8T7433l6T56N8B6P763`51F31F3`322P4/P/X/T3/P0.Z++`-X+N+)Z,V,P*X-*P*R.X+)P(P('(''V(X&''*(*)))L)'Z')&`%`&^((%N$T%$%$#'##%V&T&X%%(d(*P(f+L**)('&\%^&%'d'('(,&R&R('%X&L'\'(X((()d*'P(V((*)(,'(V,T*)V+X*X*+X*+Z,X,X+^)X-)V*R,++L+N-R.-,.X,R.-.0N-/1..//B0121234X4L0B35f33J0522Z/f30X/3V3P5X2T4/V///.b.P/,T0\/-N-^.2Z-`-*'&)b'&`'L(X'Z%%T'%\&%`%##!Z"!T">#!#f" ` VZNb^Jd^RNRVJV^VX\V^ZVZTV ^ P T B V B \ V V Z  TVX ThL\V\\VbRRdVZLTRTfRVb\ZPRXLTZRR`NPdZV\R\d`X\NZXZLL`VblZ@bLZLXR\PPZZ\VVfRXj\b\^j`RXPdJX^b`PR`dXJ\ZLdPX\dT^Z`F`PXfZJZf^Pb^P\NTbjRZ`bTVZ^b\fZFVVRDRjT^^HLVL^hZTfdV\Xf`P\^R\^ZVRTbX```VRVRB\JDNPRX`dZ^Vb\XX`TZXJV\R^\XRXdX^NVVXdVJN^X`XNd`XZ\PLdTJZPdbJR^JP^^JPNf\VV\TXVP^NbP\NX\RVFVPRbPZXZF^`RV^V\<`TN^HRTRXVPfb^LXXXVX\T`LPZXVV>R^JdbbHXPZrbZ\ PX X H  \ \ f ZRNZ\^^DL\JNJTXTfn ! ""%#V$\"#f&P$$\&('R*(('V'^)T*f(P,V+V)`))^*N*V*X))+*R+)^,(+V*d))*T**R+Z)N+V)\),+*-+,/b.-T0--Z.R+,V,+,-+.-R-.l/-X/V,N--,-*-T-J/,b++\,T+,@+-X+^*X*N-+V,N**^,++,*`(T+X+J((X)`(^(`*%V%^%&^&%''b%R'&%&N&X&%V%V&V'%&`&B''T(Z('`'V(`&>%%H%d%h&N&$^'R#R#H##$P$Z#P##Z$P##$X&L)\')b+*^*+)*T.+Z+T.*V*X)X-Z,N+++X--.V-J.-T,b.P.-Z,*+,,^.^0./,-d/\/X/2b122`4N46L3V2L4^1P2T255X6^6X63d3H3X1^54h6L5335L4Z3R4585T66V36J865B73P5b425Z5X6X5V42N4^20Z1N.-R1-@0.X-./-Z1-X0,^-P-d.+.\1\-T0.P0-.X///b.1d3h5311.^2/3^1R1^4B3H45R44P7P4P6\3225f6678V9R65Z45d67N76P6Z45V476V8\76`8\78^8X:h:88V788J7X68555J7\855\99\8F6X7786b55\6Z84R6\8Z5J8X5Z7T777P7X58V665X66`89865R6555X203d001^0/2T1N0X000.-+T+R.R*,,\,^,X-+)J+.+*T('X('J)d'('^)(H)b*P*'d,T)V+R*X(&&%%%&N%R%%`$Z$%X&%N$f'\&'&X'T%%\'^((*'N'%J'b('&%^%H%X&&(T)&%J'%%#&V&&('(b)'b))b&`*&(\+N(V('(b*(Z'+))()*()L*J+l-*)&*T+V-P,,X/T-T-^-Z//\-0N/2R/T0V.-//^3.V213X3Z4^31312H22P1R2Z0R24Z33`2Z11/V00X2/N/`/N1V.b.N-/0,^1R1.b*X)(N+T*'N&\''&X'\&$\%%&\%Z%"$#X"#"" N!Ll!LR XVfTbHdV\ZPbD `Z R \ Z L X ^ V \`\XJL`XNXZTTLNLVTX>`ZX^`NVZ`ZV\XV^T\ZPb`ZXVTHLf\XbLV^TVZPVd\JdXRNHV`NTXL`JX`NdZVb^R`P^RXXVL^ZXXX\fXT`XZh^`d8\\V`RPZZ\PVdbX\HL\`^\P^Tb^bfX^^\Z^RTVTRX^`ZVZdZb`lP^\`phbRZbnbT^`Nhff\^VPfTJNRTX^J^jXZVdXN^R\bZXLR`P^V`V\XP^\\V\VXX`V\\XT^TZZZNVZ\PbLfXfNXHTbNP\PTNN`RZfRRZ``PVl\LXXR\TR^TZTXLTZ\JT`ZbXJFPRVLT^LhNTXXPN\F`RbTVLdR^TTFPP^XZN\NZPN`X\PRV\TRLhLNbV\Vd Z R f L \ `J b\RPVZLB\T`XNb@XXNfT\B\N XXfNX #"!R""$V%T%V&%$''N()'`*Z&')+R*b*\(+))T,+T-X+)*X,\)),N,N+,L)V(*H*L*J)+`+,R+)++,X/V--X-`-...+\,,L(X+,,--X/\.-/b0b/V.N-b-L.\+H+^+J/,\.H--*J+P,-+\++L+H,X****V-+H.(R))Z)b)'N('X(&'$N'h&(&&%&^&b&(N'&^&Z%$^%%'\(B'`'2)T&`(\'T(d+''$$%`'&'\&d$`%L$$X#$X&@##f##%%b(b(Z)(V+)'D*L*-F.X,-,-,X*T-,V,,N-P.R0R.T.X--P,X.-,Z++.R,--.-.-000-/X/01Z3\324P6\5Z0b3X24433V34553X4V4J0302b4H53265L6N5R8\6N5T4^64X3P4X44T5V655^4Z64P35V2\2X0----R-,.-^0\-0R-0`,0V-J,.-0N310X1R/R0/---f12H3J1410.b/10P3T2f4T5X56^4R41`3`033b4T6X6L8Z7T7D76P54Z7\:876`979P675X:N:6H8:59T8\<7^:77896N5`7R7V98h78\:H9R5`9679X786T57Z7^:T:T87\6R;8B:664X6N7d7L76^=Z9L8857\57`6V4X3b102d20H/f4/V20/R3Z1-^/F+^*\+L+*T*+J+*R--+T,-^+*j,'L(`'&Z''&h*T(`*(J(b'Z'N)')L(P''&&%L%%#X#X$#L%\&Z(%%d'V'&\%`&R&&\'R''`)$X'D%%R)(d&''&(^(\)V%d&P%#V$d''%V%(J(\'X)%b'T%('J(Z(R(\')'j)+T'^)N)N)V*R*)+))'d,+\*`+X,)X+/.T/-T-.,0L/\2T100F1J.4.X/12P24H3J54L1332P1\4X61Z0H3V11P1Z1Z231T133/X1^0./\/^.P0^/.T./-X,-X+H,T+\-R*)V'+(J'X)X,%p&X%T&b'T$%J'##!%R#\$X!R" \ \DVV\PRRjPZbTfLVPTVV@b^VT  F P R Z Z T X R \ ^ N Tb`TXNT^dPXX`X\\T^LX`X\`nZRTF`RVPbPV`LP\V\\b`ZJd^RXP^RXXZVhXVZNP`JV\FXZP^`PVNPZZd^`TfJ^T\T^VZ`PbBTTXRTRXZNR`\\\ZVZ`\XDRNd^\ZLNRXb^ZPN`TRPTVJXR`\`LPNPXVZZf`bVTZVT`^d`hbVR\`Zd\ZPVTZb^^DVJNV`NJfP^V^VX`d\TNPZbdT\JXbRV`XV`Z\ZJVlZnTVdXX^V^Z\\RLTZj````PP`X^b^^\TZTZL^VV^XN`bb@XJ^^PX\XX`PL\\RV\X\X\T^XXV``ZfVFZD`V\NX\XfZN\R^bPJR\DRVdZ^\\XV`JXNN\dTbb^^` X b Z T Z  V \ V dR`\d\J^LVTT\PdZVTTFVB\LL fT!!\!"#Z#P$#T$R#&&'&'((L(*J'*X(&R((Z'b+\***V**X,(*L+\))Z-V)^)T)N)^)(()+)()^.+f-*T*,T-H-\-B,X.,Z/+*+^+X*,+T,+.,+,-L-.`-b,R-,+*V+-*+\.\,T..-+Z,+X+V-^,Z+-+)X)X+V*)Z*''&&'&'(V&h&&Z'&'%h'$''`(P'$$d%d&R&V&&^'H&\%&`&\(&'H&&(f%X%\)$'&Z$L#R"Z#$$#L$b$P%&n$X&%')**'^,V*X+d+H+--,R+d-+`-R,+*V,^-V..f0.+,,*++X,L-T-,-f.H.,-T/0T2/0/Z0L3N1237X4J3`7^4Z25X2^7P554\7h3X32\21N32P2Z6\54V2Z4f66433L45\44R35V63^645122\4d3X4\400^,-L++F-+++^.-,-T/+P-J/d--Z/.Z10H00V1N01/4.b12T1Z4N34R3L/220\20134X5X66X4F4\4b4T36`4L6V776756T5^6\69788V99V7T7N785R7^8T9L;P9P:8Z:Z7T8F86T9577@6L8`8N8P76V7Z7T7P78H;`89L8X8F6j:^65\7L:F879L777f767N86`69:`<86P7V7H233Z4224`3f3`3^0Z11B121T0.b./f.T+,Z*T*Z)*,-,`/V,,/-V,(N(H(&\(&L))((()P(b'))'H*'V'(T&\'X%b&$Z&#V%`#V%$$'&Z&d'&'$b(%$&J#j)$B%R%^&%`$%X'Z'&X'T&'P'&P&T&$T%%%'T&J'X)&(V'T'%R(N'f*L'`(()(N)T))(D)'R*'(L+\)\(P+Z,p,***^-V0.Z..--R-Z.-d3X0/0Z/b0R30`0N1V/2X31\5`413^20/`4`3X1V01Z3N212`2\1N24R2Z21`41b1L/T0V20-\...,X.\-L*d,*+(Z(>+d)+\)X)(`(V&`&b&&&$'X%&$T&X##D"#^" \ !PdRVRJPXfXVPNVT\ X d V P J d f R  \V J  VXd`^XXPTH>VNXT`P`TTX\`HH^\TTd`H^DVP^BT`T^RF\P\H\^b^TRfhZLj\TX^`ZBTLTJ\Zjb\\`Xb\VNdT^HJbff\TV^VVTlZXVXR\TbThVJ`\V\TRLhd`hTXRbZV`X^R\VXP\^dhVdZ\`VN^RZf\DVXXLNRZF<R^Bjlf\\^XZbjTZXXblX^PfTbfXVVRjP^TbXlhZdbL`LZHN^XbTF\ZRN`\XTXV^XTZNRNVJNXL^DNZ`VNR^RPRTVXXXZfVVFhPdV`RRT\*TTbLTVPRRVZThJPH`RNXdH\TTZRPH`ZPPZ`RTbRfNPNHZVTXV`\P`fPLXV^X^R`VXbFPTdVXXN\hZVVZX`BZ\RP^PVDPTPLZXJVNd`H^TJ R P b J Z R N D ZD T X^ZRVTVJ\V,`bVb\RH^ZF^VTZ^f!RdRV!V!#"X$N$V$T$%L(X')'(R)Z(&'*V'&Z)L)H**N,*,T**,**R*X*J(()`*T,j*R((Z**R+))T,*-T-P.,+R+X.b.`.,,+X-*+Z+,Z)*+X.+,T/,Z/\-.,V-,X+*+-V++..Z,./V-V.l+Z,-.-,P-++,`)))T)^*&\(B&%^&%V%%T&T&X)Z'V&N&\$R$&R'$&$^'N%R$$L&&f%'%&b'&'&\(T'`'T&V&$R&L'$%$^#"$!"#^#V"`&#&'&'((*))(+,T+,+F-H-++++,+R-.P/Z0`0X/,Z+*b)V+*+J-V,N-.^,b,,^0./N/1.R4d0^40X33d3345R4214`37`76B7`7322J1P2Z22X5N3V24H67^448P4N5\254T7Z3553X3X7T4P7X343Z0P40-R-V+),-.,`*R.-,`-d,R-+,R/0/11/\0R//X/T0P0//1^22N5P2\2121R2/01`4345F4354N1P53J88R;n786T5574R456L:Z8N886P76V9V9Z679f7V8`97d:T;\87878X:T<:L;V8L:;8L97X:7^9Z;`7:L:854Z5Z476Z8^985\997V77Z68d8T8^8`9885b9P5P542323V433^3`10\33Z1R1J0n0/.j.+L,,),-+\-/Z,\/-j*,X,\,(&J(^(&&f((*X)'L(b('b+@*f('\'^%Z)Z*T%R&#$%%\&$R%'&&b&`%V'\'&^$P%$&%#%&$T%T%`&%^$'V'J')(&P&$'%b(V(R(L(\'&&\)'P,^&L'Z''(')'(X)((')+&((^,('(^,**N.*P*B--P.d/0R-.^,/-/11X2P121f1R3\3@4X40^43\1L52@1/f124`2203T3f4\4\12N21232//1L1Z0R0-Z-/P-/<.X-)+Z.Z*R*)*d*<+T(N)d+X('\(%)\&(&(V$#J%J$#T%$"b#"f!f ZXVRXFJPZTJNVhVLLXZZV\TP b @ N X Z N V L \ d J P X \F^LdPRF^TP\F\\J\FH\^V\\FZ\\XbF\VRJZ\HRZ^bVRTLj^NZ^TXb`VRFVhb^PT`Rlf^R^bhdXT\^\XZNR^^X^\T\XbVXVT\`^dZ^XbR^bPPDbRR^VfVdT`PbVV\H\TP\\TRfVb^PVfNTVZZNNdffd`^`bfPfLdTdfl``bhdPXdNbTVH^\LfXdZVb\ZP^R\THPLNP`Bd\X^Xf`\V\FX^TZJP`^HfNXN^ZVTXZVb\`V\XV\d\bTTN`\jd`X\\V`LV\dXZVX^LHXVX`ZX^ddJZPhPh^^bHV`P^Z^V`X^bTX`JJNVDVTL^RZXTN`Bdd```XLXT\TTpP^\\VZ`ZXjXZZf`N^VJNZX^dbRN\RVX> X ^ X \ TJ^^f^dFBbZbVTVJh\JJ^fL\V\T\R`h\ ZfR!R #"b"^#Z$#P'Z&X&d(^*\((*\)T)+Z)))b('N(V+X*(V*+`+V+J+,N,\)*^+(`)(,Z+\))J)Z*-++J-.T+d+h/,-+L,),--+,L+N+V+^,)N+,+,^-`+V.d,,\-P,,+V,*^+,T*P.-,+-H,X/+++,,V-L,X,V+*d)))J('X*'P&X'Z'D%&R(&&f'R('%`$##`%R'X'X%P&\&D$%$L&T&Z&R(\%&%&R&\%&)f)T&&\%%%X%%`$L##Z##j$N$&%N%\(&('(\(b(()L,,\,*f+*J++L-\+,T*Z,^*L,P/.d/-L+,V-,+T,+d,-,R/V.`/J,T,/-.1R.0V3231\22F34134@334497667f403T0L/1l2T2`331645366J3^4R3V5X5R7H65T3X2334b3R231\2Z1-Z-P.-F,X/P.+T,-R,h-b0R---V,N1/b/b/2/D2R1X22/V1L0^/20N3X53^4V3L11^112^242`1R2`44T3223P6\577;P7V676\84R5Z555d87\8^766R786667P767P8R8`:T97T;l;Z:Z8T8:67N9F7\88V59T8P:7\9T768V86867N99T:88Z79R65V6Z;7;L<98886>7R9V53T34^33`32J2X4321N00Z2Z/,X.,,X/*)+,X+--R.J,+*X*^,N)h((Z)d&&%'(N'&((&'*')P'&Z(&'&b%%%Z"b$$$V$\'%f'`&)'L)%$\$$$"!L#%%V&^#V$\&N%%\%'T'b'Z'(P)L&L'&(%%N)()'L'j(&(X(b(N((X(Z(((\*V+^,*X()P'R+*>)R,R++`+H,T,P-+T,`+,.D-T./^0V.L0.0R12X3301203P3L44`105R23V21V10V1T2b12V1/0\25312V21P11Z1\/.0P-1T..Z.V.-*,b+`-)\+Z+)-(X(P+P(V)('^)X)')\'H&^$%\#X%H"&V$#^"T"L<hTTZBbXRTjNTbRP\R` Zj b V X \ ` ^ T T d X J Z \X\\JZR^NbZ^Z\\^dT`b`Z^`TPbb\NTL^RNVVPZfV\\P`TTVblbdVZ`^\^X`\dZNN\`\L^R\^^V`VJPZXXVdL`d\L^`dNFfZbNTZ^LZTTVT\dXXXNV^ZblXJNPfNh\jL^LF^VV^^T\XbTVX`ZV`ZXR^XXH^XRXTTPhVJZ\RVT`PbZX`jTZN\L\^`TVTpHRLb^XVT\`XXPRfX\DXNN\`V\HXN`Z\ZVLT\Vdb\\fXV^TPj^FLJHb\^dLNZNLRfb\^fPZ`\TbVJ\HJZXRTXPLNVF\JPTVXRPXVRbXJ@NXVT`P``VnPTPXTbTTXX`NZ\JJ\VjZTb`NVXR``HXddZXNZLVRFTZ\TTRTfX^P^VNLTVXNR V N T P R d R Z \ PPZTX^JZ\\bVJV`BVTNbZ^P ZJ^`TTZ N!T P!`$F####d%\&V%^'&f+f(Z**F+R*\,*J(V'L+Z*)(R)Z+V+,b/-H/P,^*)*)V-V*,L*+b*j,++,R,\-.-.-,b,X-X+P-*Z),)H**+T*J+,Z+T-+-V+V**/,R,,-R0Z-P/V,*+Z,L,+,/b,+-X/V*L.+-R-,+V*)(Z+*X(&('&Z'&Z&D)(\&&b('$%\&$T$%\'%Z'^%R%d#$b&T%L$''&'&f%R&T'h'R&\&L&&\&'Z'J&%%J$&X$T&$'T&&'(Z(P((Z&'X'*+R*+-,*-,Z+,b,.f-\,P-.R0^-/.\-f,+*++Z,V-,T.\/T.b0N//J,`...0P/^1X2L3302T21^4`3^222`45575^5R5X20\122J1P3f3Z1L5f1T43T7F8Z765X4R36P5D5d53P3V2T52^2V25Z42\..b.R-,Z.V+F.)N,f-T--Z/-..`./.0`1V0202Z340X211X2111V5P3P72Z2F0022V5L22X42Z3R2<4534T3257X78H99V5Z58^6`86T6`99P88^75776d6T797V9`6R:<8Z:;6Z89N8Z<;Z97B:b8:;`788R9H:\;9;8J879X;j99`::777976V86\98^8X8^:L8d7735543X4Z54R22244R23P21R/Z.X-P-,,`-,.V,T1.V--J.+*)P+*X)X+T)T)'d&R('J'`((')(\*'V(%Z&'Z(N(($Z&&$#`%#^#F$T%X%(R%(`&&\)J%%$#\""$P$V#T$X'$%R&$$@$T%&T&\&F''R%*''T'Z)(P)Z'(J(N'&\(&)Z)V*(\)')b('Z*+**&)R*(T)N*T*X**X.Z+,,V,+.-Z/T0..-\1/R2H22Z3^4B605\3X1T4b3D4b15/^0\3X4204`4J3V5\233V30510Z111111R/`/.-Z//N..V+*V-.V,V0P,+*(F*-'N')J*'('h*&&\%$d#%$$`$V$ >"Zh !XPNXXXJHJZPRV\DPBR^N` P D N \ V L `PVZbbPRVTPj`XBZNJTZbFVZ`T^TZ\dLXLVLVTL^Pd`\\T`XXDXVVR^`bPHLRj\TPTR\jPTVXV\b`Z`PTV\N\\V\XbTfVVH^VJHd\VdRfXb^Jf^VnRVNZHf^^\\`\^h\`V`XZX^fXXL\Vb`HRXNPRFTXPRbX`Zf^V\`N^h^Z\`ZnhPhNZ\`PXJ^`X^^`lb\T^`PZ\`^VhdVbPXdXX^TdNTZTVXTX^\ZTZPjN`NTFnFZ`n^X\T`\R^DTXZZVRXXR\fbVPfXN\PPTNZRLTRTTVLVZBT\4fHZTNVXZX^XPZ\P^\HL\TbJ`RXNfX\^^LR\fVVX^PVFV\ZNfb^PZZ^LZbH\TPRZLRH`\FZ^b \ N Z Z T ` XPXbL\^LRRTVHZNZPTPPX^V`^X V!N ! "T##"#"h#$%&\&H(&X))P,Z+)d*Z)*(V)V(L+^+)(X+P,b+N-X*V.@,Z*+R**+h+,^+,F*,-L-V-..R-V-`.*X--\-+,Z,+Z*+J()()T,*+^*,*\,^*+)R,,,-++`/V-R,P-b-F,.,-T--.X,V--P00+V,)R*)N+('*V(%&%L&R''X(^'(X%(T(J&&&Z'$T%''T&T%\&$b$#`%&$X'L%&%Z&&T(V'T(*''Z&\&&\%T'\(R&X%%')%('X(Z''('T*\))V+),-+P+**f+,.,+L+,L.,-^,V-,-V,`*J,++T,Z*++R-.-`-X..V.-b.V/^20\2f4Z3R1V3\213V23V2d3^35V5P5\3\5P12R1/212V1f/0H33b32V257L44432T444V333X20T2432J1-\.,,,--N,^..X../,/H0//.X1N.X4011R21N1N52P3012\23L4N3^5b21R01J3Z2^45Z54X31F03X3\47V6`6767T9N6`94X77X:7`7V9X7T8;6N:^76`:78R9^>7:R888789Z8L9h9<:N856^9V7^8H86::V9P:8f8V::8P6h8T8V99X<9:6d8X7\8R77`67,`+-,+,^,\,,J-/+b0/1X0014T3`4\6P342J2d21\0Z55Z53f433^3V32X84T3f2\1T1431.V01R2P1\1/.`1-P00^1-//.-/Z-,Z/\,`,X+P-V,+\*L.\,**T+-)L*(^'N'^($X%$$"\#L$!P V#R!T\VTT<\ZRVXPTXR`\XL TZ H N X V P P D Z N L \ TPVPVDFHP^PPVT^V`FV\P\lTXZTbVnVTRRVb`\^NTTPb^P^`F\fb\bXZZT\RZVRN`V`X`TVZVT^XRZ`pL\ZVRP\^`hjXX^TRh\XRZR^`VV\VVRfPPX`L\TZNPZ`^`T`T^\\P\ZXJ\\^TPN^^XVXNb\PVVX\XP^L\XZdT`\\bXZT\`XZ`XXbZffVf\^XXXR`bL`^RJVVRJ`ZXTRbRXJPRR\V`X\JXPV^^ZbLNRP`N`RV`HdRV`\R`NTXb@R`TZ`LnVRZ\\XTJdRfZPZVP^NfPVRTJVdbVXX\VTRdLXR\ZJbdJbZJXFbXFH<^TLL`^RZNXZVVZL\PZZ^`VVNNHjX^PLZL^bFRHPbFTR^V^BV\TT XT R R b ` HN hRVX\NXJVHPZ^DhNPPDTbdXNTdTP``X \ \!!$Z#X#$$X&P&%()'P*P*)+h*L,`-+,+)`+,V,Z.^,<+d,P+*P,)L-)X,b+H,T.V-+-V,-+J-R-,-`-P+++,,\-T-X/H-X-+V+N)*Z)*T)^+P*N)+J+))*'D(X,T)^-V,+D,-V,@-,V+P-*,*R+*++\-/F.\.+X,T+V(J+'(*T)))P('V&N'R)(''<''\'R&P%%(`&'%&b$J%$R%%H$P&$T&P&$P'%`&$P&%`(J$'\'\'(D*&@'$T(&\((&'(J(T)N),R)V)(^))))\+`*V+T,L-++P.J+)-+N-,f+L-,P,/P)^+)X,+X,,V-+..H.R/-.0/1X011V//43L33X222^22d52P1X01/P0/101Z040f1P2X00Z.13P4L15\5V54V4P4f642Z4X223X3V4J00X/,P/D/.-\,R*B,+,\,,V.0.P-.0d210/J/-V.//0.J2R0f3Z0/21Z21H/.X.10L2P00/T/L/.T1`1.H-X1.P2V24347D57V96X67P6L799h97f\JF\^^R^RTd\bPNRhZX`^T^TldfXZV`\Lbb\JZ^dZRTVZRTT^^Z\\VTRXVPXThZLLVNXHL\fZ^VBJLnjVf\XRZVL`PbTLR\P`LdXZj\D`HPF\djXVf`\^XdZP\dTPX`VXZbZLTZXX^PX\ThZ`TRZRVPRhZbHd\Rf^PTL^LVLVZNfVX`LVbT\T^\RPPT^RXbJZ\ \ X H P ^ X T VVXXfLZZPXNTRTH^`TR^XZTTT\P\ZX!XR`X  ^"!!d$"b#`$&l&'d(X(&)X())(X*(f+`*(R+**)R-R-L,+.V,-.@+Z-*,*,N..P,-J.d/T-H,*+Z,Z/`,R.*X,-@,.N+@.+V,+T,)+))X)H)T+T+P+*(+(R))R)*X,N+*\++-X-Z,,-+-)Z+\,-,V.P,-P*P***T*V)`((V+P+^-^*))V'(Z*)H(`*&P&&&V('')V(%Z'X%$$L$#P'L%'''(`%b$$^$N'&^&&T%'X'(\)Z(T'&'`(Z*Z)*d)V()X(X+^),(N++*\,@))^,`,V,B.+-+,+-/,R,*P-T*N,+f,X+-@(+*J,V,H.T-R+P-V-d--T2/202f111T35D3b4P0\32`0X21`2/013X12//2H00D11X13123X121R2\3R46P7433V3N2212D4X02Z0^..V.--/.**P+V-V,.-T/.-.\/./3F3-./^0-.`/J/1/.h1T/\/-J-..0f/R/02b3P2Z0L1Z0/..,^./R1Z33\244T6Z3\6V7d74>4^8N98V867Z788V8\7^99J87T9X;R8H:7X9F8L9`VXVRTXV^ZX`X^XFLT^L`Pd\ZTNV^XN\^RfZPX`Z`VP\^T\L`J^RNV\LVfX`ZZ^fLf^ZZTXXX`fPRVVLXRJT^T`V\PPRT^`^T^VXhXXfT^\\VZfT^TdRLZTVVdR`BfbJNjVTnP^Pf`D`dZ\f\bZZR\ZVj\bVXXfRXPPXZNN^ZRFT\\ZRPT\^TZXZhh^XVNVVN^RTfFPRVXZVZN\ZXXVPdRTbPRJ\ZT^VRPdXLL^PXX\HLb^NPP`TZTTVlZ^^DVXLX\VbP^NTFVNPLNXH^X\Z``ZRZXb>@VdJRXbXP^HZPLTJPVRVX\^RP\THPPVXP\ZXZNT \ X P V b PX LT^dT\Lh\^P`^\TdZ^ZT X `L^VZ#X!"D"b"^$Z#X%R%^&&Z')'V((R*)Z+V)*())V+,B,V.Z,.\//Z.+T-X-,P-V*R.Z+R+*.,.^-X--^-\,\*N*^+.,*R++^+++N-F,^+V,*+f,)+X)R,^*d*Z())`)Z)P)V+**T*d*)X.^0+-^-,-`+H,)B**V+.+H,+b+*P,\)))H)'N'))V)Z''l(((b((H((&'$T&L%T&P'V)X)($'&%&%%$'&&&'T'&&Z'R'(&+X)&X*)(X'((''('T)(P,((@)+()+)^*))d+)P*T.-^,T,L.^/X++f.T-R)R+-.+T*-+R+P*++`,,,N,-+.^-d0D/R1R0Z3P5P43T4222`2223P2N2X113T21P2R0.-P0131^2X2T/2/4T101H4N42T33h523Z44V3201T0X2-0/--R-R,V-T*\*F++-N-,X-f/..^0/-b0.-T.T/\,.`,V0T.Z./V/\0`0T1/X,/.1-/\/P1.F.b/\/h/T..V-R.,1Z/L2\54T54h63X5N4Z4T644P9T9677V8898R87X455L9d6^96V:58V9@R<;::\<67T6`75Z6T3\4212T5Z3b2j6>32X62T30d1T2..H-`/`1/.-../,,X,b++))R(,+(,*+V+R,Z++^,,N*+')Z'H(%P&R&b(V&&\%$V'd$B'%&$^%"^%T$$L&%L%Z%#$`""T""$P'f'%R(\&%'R)b'&'N&T&%T&$F%N$%V#X$$b&^#J$X&R%&b$&&'&T'\(`(b*(^)*+P+)P(T)^(Z))(+V*h+V-)J-^-/..P0131015N45322\0/X615675X6V8V:5R3P3Z7T5b53\34X3R201`1X/11b.L/11N1/1^.T.-P1V/N2.D/N/R1.V/-.*V/N-*1^+--P*R+*+')\'P%&\$`#%X%%X$J"H"N#X $N !` T""dNP\^NRXXTTVVTRVR\P^J\ f X dV \ X Z \ NZ ZZ bX X V\R R\TFXNVR^bPXZ\^V^XfVXT^TPdl\X^XPTZbTf^bFP\FDTLPL\RXZR^RXXNb\R\TN^T`\bfHVZRbNhXXTbNNX\PRfJT\V^VXZV\`Vh`Z\dTZT^`\X^Z`VXhPVPP\PZhXfRb`NRdNXRdb^VRTV^ZFN\PTPdJPTNX`jn^ZV^hVX`bZnZZV`V`XdjLbVTf\^FdTV\`\JR^`dbP@RR^f`D\Xl^THVJZXbV\ZPfPPVZXZZ^RXTRNZ^NJTXTNZNRdTRN\X^RXL`XR`NZbVZ`T\d^\XfdRZhFXrNXLVhX^\Z`N`Z^hVZ`d`D^`VXVVLnfRV\Vf\ZLTXZXZ^ZZNRV`X\VThVPfVbZ^T V N d V ^ P ^ T H X`X`VZ\ZN\\TXPP^Z^XTdfJZ^ F""X" #\!X%$&%%&&&R(V(V())(T)()*),^/V+X,/+.//V-,,X*),**\,+Z-h,\+-.-//,-++,+`*P*^**)T.++,^+,@+b*)+b*)*R+(()\+X*N+R,*,^+X,,N,T+--`+^,-Z*T,,+*,\*+N*)*`,)^+(^)Z*d,)((R'()T)')V(X&^(\'%$&V'&(^'V''()R&X(P&B%'&$T'T)J&$P%%T%N&\(^(X(\(T)\&&))Z''(b(P(V(Z*X''(X(R*\))R-f**Z(*)`**++`+*.P/T,0`,,++P,`-+d--V-.R,).P+,^+-+--/`0/H1X22L2f6T12N2\21R25J4P3V3\4X2h433L0Z2h1Z0Z20`1/3R23D1d3V40`132\2311@3211200Z2X1\..R-b0..T.`--R.F++*R-F*,V---+J--R1.R/.0/\0-,P--X.1T/b.X0b./L/d.X.T//,1R2X.0/--L.f-0\-R-/L1Z3T22`13`2P3P3V35P4Z5N5`4N6\3V5P6L6\6Z7T7T9^9`65Z95T4T765T9T669P85:9L;;;:d96859R988887988;6Z79R:9X;9^99Z;V;P=;;<<>`<\>N;:V9T7T7^6Z7`53342N33L6R5b5L654V3Z3^6V1V2F/`2R1N.1R120/0/-J1-\/L++X,^)N')\*@,`+**R+*+,)T**++X(&&X(R&'&H&(%&P'%X%X$$L$###$L$%>''%"R$# ^#"#V'%b'V'\&X&&'V'(&T'P'X)%%^#!X#$Z%T%b"%$R"Z%F%%`'F'(&(V(^))`*R*(P'+)D,&(^(Z*))(*,R/.^,..H/P.20302066T32Z3Z12R55R56J756^948^35V5R64b4L7R4V0X2Z/V1V0\1N0V20J11T21N1`0V-.b0Z1X0//L20^0R//H/J,.Z/,1+/@-,,R.Z)X-V'F%V)&Z'#T'X%$$\%#Z#X"T!"!H# d !Z!N Z X\`XXX^\RFfHXXR`VV VV Z V L ^ P P V X RH H VTXV \L N^Vd`T\f>\P\\NT^JXPXX`HTXfZR\dV^`TPJLThFbhT`\VRJN8X^RZnPRfR\F`^TbTP`TX^LbZF`NdlR`RrTNX^``lN\fNbbR`TdNdNpdX^TX\XdbZlZVR\dNNNfbXJRNRVRZ\NT^h`Pf^XdpbZLVfhNTVZ`FXVlNZTXXLR^XdL\RVN\J\\PZZVX@R^ZPXTZP\`VTRfVVT\PNZJXRT\R^dBTNHdLXT`HN^XXZLTRX`V@HVN\`ZV`V`<PJ`LR\RbVXNLVPPFfVFdL^b`D`ZZL\jXRX\\X^RbPVVXX^TVVL\P`^XRVDRZfP`PVV\^RJPTLXPP^Z^TNR R  N P ^  R^@^PRXHNFfZVdHTLTRR\T`T hd\ fVTT!Z"!"H"V$"%^&%%H('T+\*V(X(P*b*')^*))P,N+,P+,.Z,.^--,*,,,f*R++P,X.,,-,`-X.-V/\,-N-T-\+,*P.-N,^,^+V,V-R,L,,\+V+V/B+X-Z,)\(+*\+)f-\,,X,^-,Z+-\-Z+R-T.T.+Z/++)P-R+X+\+(N)('V)X(*T)D)(,'Z)(*h(V(^'^)'()&'X'^(N&&)T''*'))(L)')(''&&T(`(&J(')&V&(*)^'X)D)%T)'V%d('&Z(V'R'V(L(L*j)R)X-*N+^))`+T)-J,Z.,R,+D,R-L,V,V---*T.\.,,+`/`/-R-,--V+-/J00.//T20Z124V3`35Z33R323Z213T3B01P0.N30R100d331T2H2^4V40402212X2V2001Z/01H2X1/b0/h-/,Z+T/X/,^-H/-^,N,,T,-P.X-X0P/0b1L//H1T0//.P/h1-\1.0R/T0F-Z/N--.<-d/N.1X/H00.-d-T.Z.-0/X03R21203`22P3454\5N2335\4J5R97X88T77664^8P5R9\7P666;H<;X:9R;89898X96R98^:9=V9:b6L78X:b87J:R8L8N999J9^9:;;\>J:=N>P?`TdVV\TJXRTRXbZfZZPbbHTV`T\TRV^TRZ^VP`TJR\VNJZ^VPVV\`RRjZZJTPVXXZJX\bZX\d^ZZ\P\dNZ\RdN^\RfNPZTZdTRV\^^Xd`f^XbbHddNVZ^RVTRdhZXdbdbd`\\V\\X\bLlVl\fTbTP`TjRVLXXTTNH\\dV`XXdTdb`PZ\^R\RNf^fR\Nj\Z`Lb`\T\RRNTTZ^ZV`\PXPhNV\XJJZTHTXTVX^PR\Z`HRZ^LX\N\\VfX\Xj^RTP^fPbbfL`PXT`XRVRRbTZH``TbVZLXJPTPfHVRZPdXVPjZ\ N \ ` F ` b Z X LZV\PRZJ^FX\NX^D^VV^bhRNNVZNdXTbX!L ZX!\"R X!!P!d"X#!P#Z%`$$b%L'(\(&(\&&(N()*T)'R+R-*,+,^,T/\01-P.T.,-R-P-.-+*Z,T,d,Z-,X-Z0-.+P,+2-^,+*R+R-R*`,b+Z+T,)\*V)+*\+L*X**(`*V+V*N++P**T,T++V.+-/H+V+`-+V+*X.)H*\*+T+)V''N*'()(*J+V((X(P)\((H''(N(*V'&H(&'(&(`'^%'P*(V)\(`(V*)'&J'V&Z''R)(L&R(&%Z%J'X(('Z&*((`(d&V&'b&%f))'V*)b+J*N*)P)**)/T,**D.+*Z-..0R,V,b-X.Z-h-H-^-R-.P/H-T0/J..R0T//0`01T3F/1Z11V23X53\523233H24\42L53X31`2B2\10T3T1N4X013Z5N523L0T3Z21011L0h3Z00^1113\1/.J.,H,^-Z,L/++/,\-L.N--,.,P.L11P//J/\02R/10/^/2/\00/H.`,-V---N0/-R-Z-J-`/0B.J1X-/N0T311N/1/2Z43Z3L5Z1P31342P3144N6^76T9:778763X7H6H:6X769V66R9P78L7`9d:8d8T88b9J7h:`9^;d9T97X8B888H96X89X:8R;88H:R<<\<?\;`===P:765P554h3V65X4V4T45:T5`6T5R5142B0P3L2T1202T2`23R1Z0//,R+\*V*,+++,X.L-^.,V.*h+)+*+X'L*b(N('%Z(')%N&X)&X'R&&V&d%L&$Z'$b&$^##$R#P""""$\&%T&%'%'^'%R$R%X%$#%$"#X$J"$Z##%#X&Z$R&^$L$#X#X%&'L(''((V(R(X)&(`'&T)Z)J-+)+)R+b./T--0030010Z1D14P625T3X3N6^457:d8R6V75^444443P6b5N4`62X4d62P4N3R2T/2\00.b0/00d111V/^1Z1`02T42X..R1./b//^/.P2.-+`+\)Z)f*&'%&&%Z%$X"R#X$#d"X$"#V%$!V#!X P``\HXVLT\XP Z \fN ^ X b P J P ^ LX P l dH`L \PRJNFfVRfVTXVN^X^TXP\\TZ^VPZbVZRVZHXPJVR`RZHRfXTNTZVPhZXR`ZZ\bX^hXhFTJTffXN^R`P\`^\h^N`RRZP^`ZPZZT`\`XRB^\^V`^`X\Z`TXVZXTXZZVbXdJ^VV`RZHTNJ^PLbTbX`FT\^\XFDZ^`^V8bfZXZTTVRPbdN`^d^dNZX``RTZT`TVB\`\T`RPZV^ZPZTXXXX\JdRLbVZ`ZVbRTX\ZR`RZLNP\f`dRbV\VXDXJZXpRNbT^LbVNZ\\J\TbTFXPdLZ\LRbZRTZZX^TTV\dZRPZRT\^\NZFXjFd\bXVPV\VZTN\R`T^PRTNRRZfX^dTH^hVL`\TRPRR\V^PZTP^^jLJ^PT H d X V X F J NXLT@^X\ZTVNPVPT`F\T`\b^\`\!B  @V `\!Z"!"%^""P!"#^#&#%T'(T'J)J()D(Z'F(X'*L+,V+X-V),+-/^,V-,h.-/P/J-.V//-.--R/+Z-0F/+R.-Z,-+X.-)+X)`*\)**^*^,N**\*)-V,@,P+R,*X+)`*L,-B,-F-b.J+Z+^-.+F-++V*N+^)(+Z+b*+V)h)H''X*N'N)+*())(Z((J)J('%)&T'Z)T%^(b'\)''L'%T'b&(((**\*-'L(Z'\(&T''R%P&V%&`'X&Z&'d&Z*'H)(V*R+N'()N*'(P(\*^)J**)d*)++R-T+-V.Z-,-1L,^0--,-X-/N-,V/L/.../130T/2J2P232L40V421F.V0X0f01534P54V53335R21V2V41B5222R3\3N21123R43X40Z133122\121P21J2V1R/00R20h-.+-V,V1`.J,-`.H+d/T.d-.,..N0-0-L2.Z00P1/..V.N0X/./-.,,\.B-.@-.-//T.P/1-`//H1Z22^131P22N3121Z235F435X3P1X5R776788L8R857T3R87777774665;P88V;8P89Z7777:V9:\>P=>;:P<<;R>\:<9Z:;8Z;9==<@R>`@<=9X9\887P8b9T8T6R4X5753`775\43X746T7N41434R4N332Z22\--L,,(^((),H---+,-T.,N,*b('b'V'Z)'R'd)^)R))()X'd&L*P)V(B)N&V'R%%%&%V$Z$b$$f%&$%F%$#R&P&V(%d&%$&f&T&$`$$T%%$^"#!#%X&$R'`%\%$$R$T&#P$%(*R(X)H)l&B(*&)**+(*,P+N++-L,n-L,+,b1Z/Z/R0/R/`.11d2H325^464R5X45X7:L4d6843T61P86^523\4Z523V2H5R1T1X./^0043`23123T23X01d4h1V26P1:02R.\0.V./b/`..V)`+^,L,\+*Z((&D('Z&%%#$$$X$$D&`(T%`#$T$ ` T V"dJN^\^ FbRP\XVN \Z R L f P  ^ Z X\ ^ ` `PTbRPhLXd^JDHNZhhjNJjVTbRhNL`VH`VPZVZ\^VPV^JXdjTbXR^TZTXV\X`XbPPT^V\^ZXT^T\XfV^^^^V`Tbb`bFHbRTP\V`Z`jN^\Z^VJTRVZVRPX^^XZJPdb\fdlXf^bX\^Tb\`ZV\\\FNPTRT\FXTPTPVX\\6X^XfTPJXZTh`j^NLJXNT\PXRTj^fZLN`VThLZjR\NT`TL\RfZfTbP`TXb\ZTNZPVT<V`ZT^dZHPVRXZ`JP`XXRTdRFRPTVPRZLbPNJ\RR`JT`RX\V\Jj```X^R^VLB^Z`PVNZ`RTX>fVZZ`P FT j Z R P X N d RF R ZNT\^Tb\HTXTfRZL\L\VZj J`"XF #^!#!`$X$N#R#%&Z&X%T%''()V*(X&J)'^)R*`*V-**++T/X,,X*L+-^0Z+P0,/R0,<0//0,J/Z-,\///L/-^.V.\.j,F-*L+)*L,'\*+*)b+*T-h**-T-*L+**`,.-Z.J/,)F,b,+@+R,T.-N,Z,\,`**\++Z**T,L*V,(`,Z)P)(b()(Z*R(`,Z,(T*^)'N&N&Z'N&%'(&(`(&T)('''&X'\(*(`))d*\(f(%&'()^)(\'&&<')'n()*(X)*T+X)+))(')j*+)L*,^,P-V,,-1V0^1-P/V-T-H-h-T/b/.X.L.V0V/1V/.X//2V22V1d2R14^2224P20R33^1`23F6\4\6496Z445Z4J540\3^32P3N445421V6244X4`434P511/0^0T/R1\1R0J22\221/F1R0,\.,Z/L----+D,-N-D.V00-1R.T.-/1/2/.R..`1/.+.P.X+P-P-D.-V1L-,X-,+)N+,H.T00///X21R01R1N122L4333V40^111V24\2`4535665T9X63T8R6R5R898f776V7475799R9P:P97:T8989X9X?9X<:8L<^;?X@V?@AP?P>X@<:b;9:>R8`97Z876765:T4X66R6\466T65L58X4X5X4b3^4100.P.+T*V+)D).J+R/R-\/T/P/-f+Z-R**J))N(f&T)V('Z(((Z)*V)(''T'Z(N(R&^)<%&P&&T$L#%&#X$#R$%D(`&&Z%X'`&V&'P#&#"%V%#%J##""#"Z%&D%T%d$#f!##%$$&%'<(')B&Z'T((P'`)^(')b*\,*T++V,)/+Z.-N.0L0/0.J0Z31N5R7\45D76N3X499R9P998P7J4V644N93664^3N4l3Z3R0210`1P0X2Z226P30V3D2d4d4314b322J3111\1Z23-^0X0//\-V+N+**X+`**)&)^(&&%#%&T(X)%'&^&R!!"R \ !V ZZJNpJLVNNXTNXV ^ b L V N X Z R T V \ R \ P PPR\ NVVN`^Zb`bVNZVR\TTVVVTRXZV`RRbJN\\D`ZVVVPPHZPbX^TP`ZVPRZb^\TVZ^Fd^^BXZLZNpXVHZ\VRRXNX\NfJXXT^V`d`TTZTXZnXVTR^VfJZZZRRL`JZXR\LZNDFXRZbTddZfX^`hbbXhbdRfXXpLZb\hTbXZNBVVZLZ\jXhR`ddN^Z^bPVTVJPX\NTZRVPT`NTX`\VVXdRVLbH`TNXZ@`T@jTbbLdHbPXJHZ\NjFL`VdN^ZP^ZVPVV\XLbHTPXbZPPH^T`ZT\Zd^NT\PVVR\LnVJLThH\V\\HRTR\N`XHTHZPTXZX^^ZN^ b T V X F ` X ` L R L ^DVd`^PVJZZVVTTP\^HPbbZfB b!bRb^TV` 6 l !V J!Z"!T"#L"d#L%#\%&%X$T&\'X))^+R(*))(X)P)+)b+N--f*\/**+R/b0X.^+.-/J/X.\0^0/../N0L1\/.--T0X-^,+++`+N+`+R,\+V+*(`+B)`+*))`+*+*R,,,,V.P0-,,N-+.V.T*++b/,(`-*+T+*f**V),+`)())X*''''V'*N)R('J)&Z)'%'&`'(X(R))*V*)V()V(^'`(h'V(V))F+`,^*X*'R*)()P&'\'&X((`)*b+(R))^+T+*(Z'N+)T(R-`),N*-\,-L/\.*,.0.1/-0b/f/.1^/..\1^1F//H0/L/211`3\4h352\134X30F3`22415R228f6D7`8b4H6f433P3R112X24T42^3P4424R4\4N4\3T2R3T5d3Z522P0b3000/3T3T6Z50N02R/Z..Z-T-N/0-V-+.,P-^-X1h/..P,,T/^10///-R-L.h.P-R-++L)*,.`-0\-L.T1R-,*)-P,p-N-/T21/1X0/V0f1d2\31\4343T23h30R1V0\3V4d1^3X44`665443T5Z4P866T9\97876P7^6V5b6X9d8`;85R<999V:^:T>;R;`=>V:;`>=?J>=B;\=d>@L@^CZ@Z@P>P==J<999:;L:8:X98J8:8Z8Z66Z7^7T6V98b555^7971V4H2D111Z/b-V/N+`.*T-,Z.X./L0^..-V,^+*))L('b*N()V'^)(),V+\*+'(*T+Z)J(h''%&V%$$Z$%b%$&H%`%^'&l'V&(&b'$V&&%#$\%N$%F$%\#$b#%N&f%T&\$"#"#"$&#Z&^(^&('(V(N')((F),(V)N*)**^*N+,R,,-./.V11R1.32D24N5d45\4P666N9X7T8X:;^:R7^5H7P5V8P6T8J5F6P42T3^1R41R12N31P4R1R7T5214V4N4`41X22Z3N4V6T313d4120`-1+/.P-/++^,\,,R)*`+L)(d+X&'N((X&&(&L'V(\(## T!V XPTVXNPVFTRZRb ` R ^ L R L V T ^ P Z ^P V PV Z>\dZ>ZZJT>d`VfH\`ThVbVj^JbX^XFP^dTVVZLVTRZNdXVVRRf^TbJ^`BRXZZZFVZHfVV^\JFP`T^VhPXNTPPHXJPb^^^JJd^VVTbTPL^ZN\b^fL^Xd\VJbdBVRb`^^X\`T^jJXDbTT`TV\TPNPZTT`LNTXbb^ZVdlXFl^LfZLlZ``VL\T`ZRZX^^T\JJ\V\`\\\XR\XP\V\ZPZTPX^bVXTDP\`NVT\T`^\XN\HLN@VT`VnXL\T\\bTRRfJTbX^`LZXTbJZVb\R^VRVVX`^XRT^TXBTV\Zh`NRVLX\^hdFVRV\^ZJTPXNdb^R\PbbPVZVX`DjFXVHTNVPbRLZ\^XT\`RX \ X P P P L ^ \ J Z X ZJdL`bJ\^\^T\ZPZ\RZRRf X\R fNFZN!P \ N#`#P!#"#^!$"R"!P#%N$'N''(F+(^*X()T)b*()++++-/,\.,N,.,N---+.Z1T/\/T1X1///Z/R10..-N-^/`.T.,-*J*X+)P*F(^*)V))N)V+^(*B,,b,-F,,\.-`-.R/\.L.P,+d,++b,R,T,V,+F*V+Z*H+L*)X**,*Z+/)R+J*'')V)(R*b(()H(V'&N&T%`&%&V('*,)`)X))*(h*(N)X',N))))^)(((b(''^(L'`*(N((,h)R*X/,,,T,.())J+R+*R**J-L,\,./b0P0\/N1P-f202\12//L/02`1L0T12X30313b22Z64342\44T44322L0`35V4>4X4Z47V55V23636d64L3P6T531L32X5N3V3V54F74233\532B2T4Z1T12V2^3142443P2F2b/--.V--//T/F-`,N.T-,T-..X-P,\-Z,-./-Z-\-X.Z--+,f,R+)-d,-H-,L/.+.<+\,*D,,,X--\0P0R-.Z-/0^0N1/4b2R3Z544P50.>0^1P21Z1J223V4534545R9T7T6V97N8X86Z7R85N7P6\6X95P8Z:D:6P:V;T<\:T7X:;P9V9;Z;>;=>=??PAR>V>=87L:7;97:6D766R:X6T75P9951D22D1f0V1V0h0.T,Z,+L,V--^-N./,\.0-*)(Z*b)V)^')*X)(,R,T*L-*`-,L)X*+(Z)%'%j%T%B'&V&&`)%%Z&H(*'%&L&'X'T$d$$R$X"#N#T$d$f$T##d"!V!&^"J&\#"#"#^$\$#'$&Z&&P''&X(('T'd,N*\++d)T)P*V)*J*L+,T.d-/b-1^110D/02P45^5V54^6558\8H66L:8N6H6L5V675X777T726^3V6T0X43`2F552Z4T414f5H7T33X3b8N6h43X7\3R272R51-0N0Z.b.P,\/Z-1+\/B,-T,N-+D*'*V(-^'`(&*`*`)V&&Z&$h#`"F!!V!d R"LRLXZZVVZVh`RTNLZ X Z ^ V N b L X L ` R V XPT^NZ\VVRVJfNPf\JL`\RZNZTLZNXRNVbX\LT`8ZRV`TXXXXbTNRVXhZRXbP^bZ\Jl\TT^bjT\VX\\TZ\XZPVZVRbXZ^\NHXfTdN\nZZ\P^`^PXVbNZTFZZp^^T\X\`R^Nj`^^dVV^f^^jVZhjVVN^`Z`hZ^fNZXbb\f^bbXXZTLd`dXTXXZVRVbN\RZ\JhZVVZ`fZTHTHfR^V`^RT^Xdb\`bLfR`\XZN\V^J^TR`Z^PRbPPVRPP\ZbZ^^ZX,FRZDZZ^V\VP\VR\bXPXZN`LbPVVLXRZJdR^ZPT^ZR^LjDZTXZNTZV^bFXP`TXZXXhZTZh Z X T \ V T  LXZXDVT\LJFTFbZZTRXN\NZZ!P !  !X#\! Z! "\$#R$b##"#%\$$%f&N&X((**\*Z+V*`*R**L(b+P+R+R-T.+++--+V-^.+-\.L/P.V0\.h//0/2L1X0`10P1^/.-b,X1,f.,L-X+**N)+*+*(**j*R),+P,\,`.R,R/-,T.Z,b,---R+T,+-R-,T..+f.-^*+-+T+N-Z-X,R+)J*)))V))^)`)Z*^)'((`(&d%)'()`)j)X*+)*P*(*&)N(N(R)p(^(b))Z(H()((^(\(R*)H+P*T+^*^+R+Z,\,F/T0X.+/+R+,*+V.-R-X-P-/`../h120J02/X1R2V/\2\0Z/J45L2/Z4L/22324X31X2j5\2L3P2Z2R32T463X4413d3J5V4N4451T1V4V2T4P3\4J4X42334^6J75^5434P3T32X431L6`222P10Z1N4N22\522N3`1J1R1/Z.j/X,F,..N-/X/,+`/.+R0-0/H.N-\+,,P-Z.Z,\,P.--,P+-,`.^0./Z/.*---**`-j.,L/.P//P0..d0.X0/202X212211R0V001N/T002T4L15T33X4Z67V6799R9L:V;f7P8Z74`44P447:T88P98V9X:Z:9;L;R;:?X;Z@ATA@X?X<=:NRAVBF>@DEAVBA?CX>V<\:::<8:<:<:8;:<^8785\6J;8d67f8685:5Z87410/+T/T,X-+,J,Z.*-d--`.-\/,V.X*`**`(()X,,(\(\+(P**Z+L,P,+b,)**)N&&'J&$%%)\&R'N((T$X(&Z(X'J&%Z'Z&'&##Z"X&X%P%%$R#L !#\#$"#"T$$P"#V%D$T&%'&X(\'%'P(P()T)(F*+Z+))T**+)+`+++N-/1^1^0/0V1R32^384L87`55788P7`7\8J:\:N7J7Z4\55H8^7685j63X55X8H34V433P24X957\22R6V62665Z67501`110B/`/`,/../R.R.h,^-T-X.,-f+*,*)*)R*b)'Z)X&P&Z$"#" Z#! `rV\^VZVTV`ZHhN d ` ^ X \ V Z h ^ ^ V @ J JZ TVRXVX^F\RPVVZ`RTb\NPXjZPN\N^jTXX\Z\X^jLN\JXZVXTLX`RP\NLLbPhXPNPXVTXRZZ\FVX`VTNF^dHNNVT`XR\dXRL\XZRVT\`R@^X`XTPXZ^ZVVNLXT`HhP`N\Tlbb\hZN`Z\TT`VR\hXZVZ\`bPZ\VX\^PNZ\N^JTTVXRBhNJZXZXVXTRXTV`N\XL`ZZ^R`JRZRX^VTZNNP\V\XB\\\RXJVPhZVP^DnF@^NdX\RZ`XD^PTNFXVV^PJRJVfVXX`RTXZFXVPVTTXVZJdbVTP\\VRRXZ\P\RXH>XL^T^J\X`LTPP\RNXLPdN\RZRJ`LDRR\N T X V V R ^ N ` < ZP R PZdPZXLTVbVZ\RZVfLP`Nj#^!T X#R" PB!H\!P!"R"!N#"$R""j#$P&L&$$(V(%&(((b+((X***V)*)Z.N-+X++T+-*V,`-H---^,X.^.-.V/^0Z0Z01/22X1X11/V0T/,R.-,,V,,\,*`,T-Z*N+(T),h,T*\+,--L-Z.V.R1P0..l/R,T.R,V,V.+-.V-,X+.b,+V-D,,X-+*Z*^+*R,+\-Z))**(+T)))**(\*(j)R)((V)X*)`+\+)R)T**((H)\+@))T)Z()J))b)`('T(*`,J*(+`,T)*R-.V/N0Z0J/1Z.0f-X,+-+-d/H0//J//L0X//H1^0F0^2/N1V110f2N2P5Z44X21T1V23N2Z3V3122T5V5T233455486\4P45H3Z4L85f3311/D42H3l5Z4\63L33L6567J7453R5433425Z3\2R30T2^2/R211N1T2/./.V2X.,--...`/./T.-.+-,--,,Z-`--V,.+V+.*,-\,+P-./.P/-X.,****N.\*-L-b/`0L2D0,Z/^/-/2.b01P2Z4Z32J1^0..P3L31f1V22^21542V4L4356P6\7b9>8\7;T8N657V853687T:8X:8R7Z:;V:8V79Z9=N;d<<PB^BNBT@DEB?>P?:?X;?V=V@AT@@DB`ARBBV==@>^;==X;N?;T<>^.,+++)V*)^+)`,+*)^+T,R*X,+R,.,`.D***)(Z&`'F'd(&'(\'&&%'''^'%^&L%T($%P&$T$R&'$^%L###\!D$T#P"R$J$Z#V#X&T%Z$Z##X$T&J&X'^'%L(X(X'D)+'(T+()R*b**T****+J,,T+T/./b/V/X.P1J4b234^44`5T7V4559T775`874b7R866Z7R776Z64N33P4`65X14Z5`76N6Z7Z57X9T5833P6^7D7N666Z252T40\01Z10./f0L41R/.L/V..X-+Z-+b+\,R'*++\)R(R&$#%T"^"Z!""!\ ^PTJ\TXrN\`  X \ R R X R T N ` V X V T RX^NZP^VV^NX`PV^db@VTPLZbXd^VP\^ZFTVV\bdXbT^RVZTZTP\`bTR^bN\`LLZ\fRZ^VVL\b`T\VP^^R\VRVXbTPD\`H^\VTLZ\P`RLVdR`VT``Z`LRfPZJfd^TXfT\^RL\ZPNRbT^THL\PXX^ZVRPb^lhT\VPHVNd^hLddZPXTT^XbV`^Z\`PRHJbX^PP^TXh\VNVPbR\hVB\jHFXR^\bXVPTXXRX^RXBfd^T^Vb^XTRRXfZL\PX`Z^VX`^T\\\V`NRRNr^VLZT\f^T\ZN`\^\XHF\`^ZV^T^TVZV`T^D\Xb^XXZXbZbLPJZN`l\`RRRfX L^ X b P R^ \XX^X^X\fT`HfVN^VVFZRTfd V R!X ^ Td!X `#R#L"P"P"`#X$\$R""V'd"T#V&&X&&'(V))b)d++Z*P)`*)H,,Z+L,N.+L+L-,,T*R+d+T*`0,*P,.-T,,020R1`.T0/2Z1f11.`00/-R--,V+^,,X-,`+**++T**N*L.F-*.,/-T0/0--P,T.,V-.-+-X,**L.f,-.V.,,*V+T+P+)R,-+X*P*`-*,(R)*b-R-))\*`*L-Z)B*Z+(T+).+*\)+)R+Z))N*)b)*'Z('\)V)P,R)`)*V+*)R**R,,,,././/-R0b-.,,,H-V,/+2^/0R/f1.^1.`1\2Z0\00F0/0V1\4N4N3X44^1N31^2V24R3^33V4456b34L4Z3P4`2Z65T553Z632`4P3^4b32//14552H3V3J47564Z764V53H5\531L4V31Z11V234F4V40`3f1X0/^/F...X0b0///X0//N,-^-/^.@/V/-.+,X..P-\---V.R,-+Z+.J.+P.Z-.@.N,R,,,R,\,X,P+*,P*R,+/.h/`.-V.Z...Z/./0X431`1Z20R.N.V0./N141..`327X758F677X8f865`8R7645R7R6@76P99;:T8^6^8`58P8X9T9:<=V<;T=APA@?>?\?R><^<:;<9?=R?P?f@=H=9Z<;T=^:8`889L8h9:89R9:<753563h400/0V-Z//d2/.X/--^--.F.^,`.Z+-b+*)X*+,+V++d*P-V+P+,-N.P*,D)P)'&\%&%'J'(T(L&X('%'V&f)Z&F($X'T&X%P$$#T$'T%#Z%`$R$\"J$$R#%^#$"#Z$"P"$#$R#Z'%V&'T'''V+'V*N+)+R*`+)\,:*V+R*Z+P,d/H-V0,\0//0b10V01`5T65`55T7346L876P4\8Z:R:7Z88:R4Z7X4d533Z64P6N4T27\66X6J55\7N87X7Z64d7415T9R5R76X32Z2V032H13N2Z02T2Z11P-,L,Z+V-\-,.*+Z.V*`-))L*)(N$`#%"N"X#^""J!"T b TZPZPTNRVVTZPNTXZ X Z R f J ` b Z R ^ J P L \ P  VVRTJPTVXZNNVPVXXV\V`ZVXJJZTXfTZVR\Z\NZ\ZJPb`X`T`TffVXV`\d`RVXRXN\Rj\bdZ^VN@\XR^L`^T`b\XRP\RVbZXHVRjNZd^dZVVRVTP`TV^\ZRZJZPLVLRhTH\VR^BV\Rb^^dJ\VbbdX^dZdNVFXbRLPTn`NbVRTThFZLDd^ZPZP\ZblVPbF`^TTV\TNXVfX\fTFT\\HL\JVLXNVVJVNPXRPXXPRPRRZPfN\TZ\V`NTPVJdPXXTXVRTV`RP`P`Rb\VLR^X\XLfJXRP`L^N^RXHZJ\PVXJ^PdTfd^^bZZZ\TXL^FV\RPXZTVV\NfPPbVXRNRd^RV b X X @ Z ^ ^TbRNTRXdPNTTP`TPdVZVTX^B^XT!L# Nd! b b!V!"V#"""V"$#`#"#T&R$&)'(P(D)X*^(H,(N-L+b*V,H-V**,+^-`,*R-\+B*T-,T*Z+X+,`0b.H-d1N00///1/^032T0T/h//R0f1/R/H/-V++b.(**Z,H)**`+Z+,-P+*R,/H//V/-N-/V0N/+N-X-,+V,@++.+,,P,V.-.+d++J-*/Z+X*+F+)T**V)V+-*V+\+*P+X+)R,R*T,,V*Z,.-+,`,V,,+P-J,\*P**()V*R(Z++`*\+)-,+R0b)R,P,,T/\/L//0R/V10P31\/X/.^/-//00b10J2Z0///02Z2012T11D3443j534b3P32Z5Z435X7V4N333\2f4P52Z5854^5N64T7Z4V6R4\0111Z2123`5245P5V4X9Z8526Z5T1V5d4P34Z3V4334Z422X324P751l01/1/-^-.Z/.T-Z../J/-.-../-J/X.V/Z-J+,B,,^,F.-*R,,-,^.-,L-+f-D//V.^,N.b-/N.T.+X,-T-T.,1-Z+/j1Z.V/.-Z4/R321b411b00HAZCT@@>Z>;R@V>V>A>??\>?X@>=Z><>\=?T>V<;9;Z<^97:\99T<=L;X<`98R97b86453b4d52P/,^..X/\0<20^2..,`.Z-J--\.V/.L+T,^,L-(+,(++b-,,Z,P-^-,+*P(l'&T&`&F%&R+()'(d((\'R(N&X'L)\'T(n'%P%`%X&\&P$X%&`"b#"X$b$N%#P$%h##P%P&#$#$%$X%X&%(%V%\)`,N)`)*P)`*J+l+T)V)N))*d+R+f,,R/\/V.0`003P11`2023Z644N55L3`8T5J7L7`76V7L85:655P854^545T36H55T67h5Z6T75=8X7756Z:64T75R8H87P5J6L12T311f1Z4b110X101X00T0/L/^/X00V,R-l,,-)'H*'$%b#V#^#F#b!Z&!^"pPTdTfHLRJFNVLP`T ` d \ L T N N  d XJbTZLRZPdXTXTTRfPPJNPRZTTV\NT^\JV^R`ZlNVZZV\ZZNPNR`P`X^`VL`PVR^bJX^TfVXRZf\XVb\XN^fZbXXZP^LZd^RbNX^R\V`Z\^ddP^PfDNjbPfJXRhTTTBZ@bLRDLbPXXB`RX\fZ`R^dZ`dhlddpZ`fTZh``HVLbhLTR\^V^X\^Z`RL^@hZ`$ZXP\VZ`\TZfF^bZ`X`^T\HTVVb\PLNXd^bX^ZTX^T^XdVNV^bVF\RfNFZbJZTTV\bt\R\Xf^`VPZV\RRVNX`ZVXXN\T`\Z\XHdZ`TfX`XNRZ`N\THfTTLHR^R^\XJRD^DRZHZP`j\b^ZTVhZPXbTPh\bRZXTV XX F V V X H ^ ` Z d ^d RPVZX^\dRVZb\N^XX^RL`HPNLXX !@"V ^!\$!!T$V#R#$L"V%%""H%`"P%Z(R&'`)*'d**++\,T,,b.*T+b.X-+++*+V+H.T+X+\,X,+,,`.1,T////0N-1/3T4V0V/X00^,^/.n-R,P--Z,+V*L-+b-)j)*,f+R*+V*l++,*+/-/Z,,d-^,V,/-N-X-,-Z*+-P,Z-R-,N.R.-V+V+L-H--T,L*T,Z,R)V+)+X+X,**P+X-,+H+N++P-T-L,\,++P+d+T--X+.\-+\-N(,V)P)F()),R,V*,Z/.J,,T-b,V/-P/`/N03002151h1H1H0/`/J000L032V231b02352333536331X4434Z24b24V234V3V32333J46X5L85R5V6L453L320\0P1X5^11X2T2R3T3`64X66f45R64X7T44P52271B3d1\1L7R453441Z45\3R3R3^1/\10F0/-\-F/R/,T+b.--+,1j./-H0d/T0R2^//\,V-X-P.X,*++,f,Z-+P.f)V*N+-,X+Z-+++X++,-P.-X--/\-P/-\/-B0R-R/\11113204Z00.R./P2h1^1L2N0226T3L3^6564Z45Z6Z4576b663N7N7R56l7889L887:7X86Z8V:X?@?>>FRAB\@B>V<\Ad>=L@?\?b?XA<>\B?V??AP=;R=X@`?XD@N?LB>P>?>Z<=<9;999:^%T&$%&>$%Z$&V&'N*V+Z*+*'d)'T*'T)+*Z**P,\+^/-^03N1223003b5T52H34L55F536f7R9\87^4434V8645P6`7J577F7`585T7F6767h7`985L68^685J57P84d8323-22V151R32V31X020b0Z0/b0////+,+R++T(R))$\'J$T#$"L#Z!" XR!T`\R^TVjJ`JfTXHfT bX V^ > J j V V H H  Rh`XXPRV`XZZ^bP>bXVZJDRP^VN^VXXVXRb\L\RR`\VbTPPhP^V^V^ZZLZV\\XPLHRhTVdZXXZ\XPfV\ZTTTXdT^LZ``ZPVLJ\bPZXLZVN^J\`RLJTXbPV`XTZVhXdfP\VHVPXPHBZf\^\X\^X^`Z\P\fdXV`X\RP`^\PfVR`RTjfNZXVZNZRZ\XLVTZ\`Z\TZTdVb^\JPV\Xf^^bXR\ZVbF\LRTfNTTTXLN^`RLRRb`j^`\XZRd^VFVNdLLJ\Lb\TT\XR\^VX^TZ\``RHNTRLbVD^HTFZLJDbP`VXPTRTFVNJhR^XLNbDVVHbVXZ\ZRZRVNVR^bRP DNh L ^ V Z R X P  ^FZRX\\ZPZ^`TZRbRbRX\XPPZVZTZTTPX`P^N ^ T!h#@ V"h#\!"R"j#$%%N%$^%#L$d("'R''')T*^+Z*)*+^++,T,,+X+V,,*T+X+T,\+*N,+Z,V-f,+0F/80.0V0..-0T0/0-^0001/d/V/.Z0`.,J+Z,P,,*\))J,,J-**\+X++-d/,-R--Z.N0^,J-,,L.-Z/^-+X.P,,+\,-\/-P0..Z.T.*)*)Z,**\-)f,,,.H,+b.*V,L-+V,X-,/*d*N-L,f/\+b0R/V-+b)(T''\'(T)(+T-H,T.V,N-.+*X,,.01N102J5466j55Z5V311X3R/214\3P52Z23T343T444V5Z6P573R23F21L3X3f33V4`5d4R4J4Z3P3353242476\44\5f3T2P63Z0T2Z212`23V5263367Z5V46Z44555R4632\0T1//137h4L7\213D5^4V2L21Z10L200\/T1R1-,P/N.N0Z0T.//Z-.0X.T2V1\.--\,L/X-/,\-,X,J-,-\...d-R+,\*,F,)L**,*R,,f,V*@.N/.-1/V.+T+J/\.^0\1V01\22030/R//H//^10/Z222675X7L54553V4T3X65V7Z6\5L55V546R7^96T7X87\8d7X79=P;=;R@?T@@LABAC@BXBTBH?b=;V==>@XBTATAA`@@@P=?d=N;J:0:;V:;9:Z:;8\:8643223233P3R4X5>21\/P/.-.b/.X0/N.h,-\.+.-,+-^--V..-,/,X/^.X-+N,(('X'X)Z&())+(*L()R(b(H&&Z$&(^(V(L%R&R%'$'R$f#V#"Z$"\%b%"%##%%$N&H$B%R%Z&`#$X$Z&%''V,X))'(N+'(`+B*X)((,)+N++R1N02545R45R2^23T2\5223\5V76N9\7P5L:98:6\2464T95b6T6\7J8T7Z4\456T=67545X7h;6X5P8:b4T6\7T5d5Z8\6463L492\56T656V3Z2h1T2`14N3b110^310T,+,+R+b-()&R'V&T%#%#X$"V!HRX^RR T\ZZHP\VVZ\NfL^H\T L \ P Z Z ^ X R P H ^ T NThNNTTJZXVVT`RRTLPPPbdNXRPRRbFNNZZb\LZNLVZdbPdJd\Rb^T^NTPThZT`\dbVRhZ`Z^`TTjb^X^Z\^PXV^VTN`jD`H`jL\NhPbJZRZ`JTZfRXdHRR^ZT^\VTZN`hLTVd`RJZRRn\dPN\```\bpR\b\RFR`XZZRbV\Zd^d\XdhJ`d^dTh^^TZXDT^ZR^JVT^^\XF\^^VhXL^PZZHZFRDXd\VZ\LTH\TXT\R\L\V\RPdH\^bTZDRNRjLZTb^JjTTRNRdTF^N`ZX\TJPZNZrT`XRV^bHdVXNRRBhVX`TNXFPNTdbRNV^XRZ\bJb\H^\fRTZNVTL^\V ^d X ` D X \ VXN P N\ZPjfZf`JbLRf`VVRRb`PTF "X"dL\! #P!#V#R""X&#$$V%P$F%h%$$Z()&('&)T+*T+R*N*)+X//\/--,V**,-V+,)H+,^,-T0V/Z1Z1`01/0-/0\/^0J1/--////l/.V/\0^--\.\-`.,^++^*-.,V--+Z++D+f-+N.X-b/V/-`-..0,T0,N.^.,+*D,/,X0/,V,.-..-,V*P*R,+\*V,.-X0.//J/R.F,N+,L-,-T-,T+,,,-,..b-V*V*P''J)d)T(P(+F,\.R0-,,F,X-T-///2\31X24V435554541V223111\2^143V3V67435P86P5J5T7^2N4315121434V6N55T3T63X4445b6Z6R8Z7T6`83X2D33Z4h30T321T3R3d13457H:`65N633\644V5b5V33L1/Z/P212T44P5X4223X44X3^2X0J2^10d0L00N-R/L1F/Z1\/0.P0`/0021b00,,-*F-X,+.\.^.R/-V-,L--*^/R,X*,^+\.+T-`-Z)Z+R+T++\*\,+V---\1,R,-\.L/2/V23202.20X/P.30X11P41L4337T5481`6L7Z24N5J7F7889h5X6^7X6\7X;R88b9J74T9N678V:T<\>V@`APCA^?XAACTCDLAAb>X<=P?^A=?\=X=d>dZXR^BXX``NRTJPVjTR@T^`NXbVThZNVXVbVbZNNdZNZXXLVL^VZHb\dPVXPfVX\TXX Z D d H ^ L  B N\X \PTVTbFbNdPXRNNNPNT\VDXP P ^! R" ` !T ^"H"!#!!$#R&V'Z&&V&b%@$N&T%R$#&%T&'(`++*L*T-*b*,R,X.T,+V+T-Z-*N,Z*Z**,++,X0,Z1T.h1P140N0R..//1//`1T./...1V0/R3-,-T.b.-L,`.,^,V...,d/*+*,-\.P/T--`.0b104V.V.-X.N+R-,V-+,X,T/.b--,Z,,\,V,*`+,L+),\,-V---J/R-N-V-b-X-,H,V0.-T/R,--P.+Z.^/f.-X+)(F)**N)(N+P,R--.^/b..`+T.j/f/2211X522f4R4657R655\3311R1125T33545\6d6F66L976N8\775X424d442L5\3J6Z4N643\3373Z41d65L5Z95L7V5X5`32\51125R14V3P5V4\7\6R57J55653N54V6V53V52/1.J03T6T54Z23P3N5`321`2\2-B//N10,0/0X0.13V0.-P.b12T0^0/L/d,,+Z-J+,P-Z,.^*T-+N.T,-,+^+T-,*J-L++X-J+P,++R+P,(^,*.@,.Z-T*+.-/V0/1.1\00/D.,\1-1T1T3N24346X4`67R43V426535856Z5R45P8J7^6576f8P6664X3479;Z??P??@@?@??>>@TB><\=j>;N=R@T@??J@>=>=>dND@@ZDVBAZ?@ZAP><;:P:T;`:P9Z:9f;J;T:9787R8V86752^53V84765T5Z2X1T10L/T/Z/.X.+N-/,\+`+N-d1F.Z,R..`.V1T-2//\0L.-X+P.*(V((())B+*L*`,V*N(`*b+N)\+^(^(j+('N(V'%%J%\%P#V#"F&$%\&##$Z##P%%&&N&J&$$#!%`"V&P&R((((')'d(&)X(N()Z*`**+N-`.0R0V2T5Z3322\21f4N14H3`44Z34N55N9^8555V44348T488996;N7V8:5H7869^768\8L8;984X657F85P773763459f5T66P6Z3X5T23T654X3J4R3R000N,,N/N--Z+)Z*D'&N%%%F$#\"R$R$T !!L RN bfXb^`P\jTR T R\N f P X X N f V X VT b FZ\ZT`HXVXlfPTTJVLNL`\`T`RPR`ZdPhZXPTX^Vh^`HZ^RVl\^TVPZB\X\X^ZJRjXRbZVd`VR`bZBX`XTF`bZVb`R^XPP\V^JTPhJ`b^ZV\X^R`XPB`R\\X\V^R\ZNRP\b`NNPNdNTfTlNd\ZT^NXbhdVVHVTh^d\\b\XVlLl^`^`NlPd^Z\T\P^TXd^`^VR`XLX^XXfV\VT`^X:XPDXT\f^\XZRf<ZZNZPJZVZhXLPPFX\Z\^TZVZbTXZZPVPRZVZTPVD`fRPRP^`JPV^VPhdXJVThL`LjddPVVRHDLZFVP\RhZTZFVZ`RXNV^TLjRVT^PDT`TdZRVb ` T F X T V  J` \XDVNVZP\`XTTH`\\R!ZP TVJ#N#Z " Z#""V&#"#$&X%$%%\'%&P('H)()*)+Z+*P+Z+X+-,^+L*+R,-N++,Z+T+,\.R,,-`0//V01P2^/H0N1N0R/^.-/0Z/.-/b0N0/3.R.N//-.--,,,+-d-P,V.R,h-+P0,V+L.X-+-^-\.j./1/X0/-,X/F.V+P+P,*+.-,,Z-T-..---*,*+T/P.,X0X.V/-/-J-\,0R0+.T/b/,+N+F/X/.-f-,Z,T)X)`*V)+,L-0X,L/V1b0/1H/X0T/R/112`2T37b3^4N63N4L6^7Z63R84X4132L2X4`579^6669776h:6P6T65R444`44P546434^5L513J33R234566X6V96T443`4X4554X54V465j5F557^56R6^663`5R2^3Z4^433T3Z4^03R21N34L52d62L3L5P431T1X0V1-`/L0.`.1.<11\//`0.`.0V./V2-d.V/V.T.-,,\,-^-,B++R,,R-\,-+\->,X.b,\,).T)P*(\,Z,,`+,X,,*N,-+^+X-h./1/0X0T/-V..-\0X0.b1L0V2V4\44X2N63T54R3^857Z873^5Z3V4662R4V7987L67^8\857557P9d:`=X=V>d@?^BX@RBV@@TANBA?@N?<;X=>P?^@TAH??L?X=?<=T=P=T??ZAJ@d@CJDJAX@`BL?RC@<^?R>=;?:;b;8;;N<==`:`8N:8L8R375R54L5d4366J5L9V33\33f/0Z1.^,X-`/,+---L/`/0T01P/1X0H.10-.R,J,*\/R+D+^)&P')+),++Z,*R)^(X*V*R(**V((f'N)^$%H$$#%V%$X&$$$$&V$%`$'$X%$Z&b$&%&%b&%%P%'R*N''''^'Z()((T-+V*T+D/.^-/23P173412T025Z4`4\5X5F4V34V95Z7L6b532X3Z34X757T8976V5`75F5P789Z7V7688775f6T6^779p8d8R8Z6P6\7X47`6H;R98L6^7H345866T4V5N6D6\1R31R3,^-P--+V,\-^)F*'R(&T(d%#$!"V# L!V !J!ZdZ^`>H\PTV\TZT d R N j ^ ` B R N J ^\ LDVTDZVB\XTdTZ^LNHRZX`NJDPXfTVhZZV`\\TXPXPT\NZV^PX\\dP^TRXXJXbhP`NTdTTZTXZTZX\VP``X\VPP^TZD\JV^jX^X\XJVN`ZPPh`ZT`bPVVZNL^T`\XhhRZb^^Z`b`b\hbbX\d`XV\XVpNL^PPlZ\^JhRTZX\NVXf\\d^fZd^\V`LRb^XVRRBZZbX`fFRTfFVXPH`ZXbD^XX^XZ^XTVX^bXZTX`VZFNVdZRVVPPhRPXXTVTVXRTZ\ZRDTNVRZZdTj^VNN^TN`\R\TR`R^^ZRTZ\NVbXVXVR^RRXbNfPNTTP LRd \ V T Z D LP\ZVRJRdX`\Z\V^bRTHPTZLVJXTRJTL`PPVVnTR!!V"X "! V!N"#\&#^#^"X%%J%$b$%R%T%&(R''d(J()\*Z*\)`*V+\+P+`+*,^+R-Z++B.-)\+**+.X.J,-/.,V/2R031/R.X./..\/`.0\0V/.-b0X-0/0,T/Z0^.,/V,\.+H-\/>,T.-R,T+*P,++,,R,,N0/-./D0\-/,,N-X,+8+*X-.,.T.*,+D-,Z/,+,Z,-+H0-.-J-^-.N/J1/..Z.-J/+/@-Z.F/\-R/L.V.L--T,+)d+P++0+.//V00X23N/1/1J0\32X2V384X6P43635R8Z97Z623P4h3255R76878\96:9Z77^533^56\87^3N4652Z6T4Z442R3\5R344J5697P5^56T3\4L52D6\5`8\8^6V56d8683P66J7:866n62V5d3^4N4:3V32Z7L302j13`34^2V33V1R3V21b1312/d-/`/2111/T1/P...V/-h0/1-N,.-+P/V.L--/`++Z,+,+T,--*.,,V-+-T+)*,`+T+F*+`+L+-,V+-,F,,T,P.-/X0V2N0-F///,^1X0.T/\1Z3T4R748Z77N643\4F4P55X54T3566l7T5P8Z4,6R7;65T7X9P::8P8L=V:F=V@@h?AV@VCXCN>A=>R@==;V=8R:b9T:8H98b;PP?P@?>T??;B>R@R???>T>b=<@`AV?J?;?=<>l=T?^>?=h@V=?@\ARAV?T@=?d>Z?:>T=<:<968:;V67P;`8T8N68T8b776T8X9:^;T8\45^4\21V1T1-d/T-B,Z0,X**V(`(%(X%%%#J#"X" "!N!V\ VTVVRLbXVVTZX`Jb N d \ Z ^ ^ R N ^ R Z ZPJVTXRHFd^ZPT\NZ\VPPRXhLTTdd`bR\bZbXZ\LXVNLp^jJZRN\XNfVRNRdl\R\XRdXXZd^^^XT\Z^PV^bddRRjHRX`nbTZh@Lfd`b^\`\NX\JX`\T\@^TVZ\N`\`VbTnXXhNXJ``fddNP\Bd\PTXbZVXbd^Z`^h^\ZV`f\X\Z^Z^VXPV\`Z\RfbLXJ^JXhNLNbZLTVXRVT^T\NV`jPTRXBZP^HNTPP`\ZPPZXX^LNZVRTNVZFjP\ZP`PdfDfTbRZXNF\HZ`XNbFNdL\JTXbP`PZF`L^RNXTRP`VZRNV`R\X`V\XBPPTV\XLRT^`VN\`\JVbNPNH\RLTZ\VH^LPXPPL\TFX L Z X P F D F fVRHRJHRFLR^V`ZX^XVbZVbN VZ\jP` !H"\!T"""!"^#N#L$&$$%'%b%#$'X&V)b)X((J))(,`+)R(`*Z+N+,N-V,T/^-T+R*-,+d0/+--P-,,P/-0-X1L0T1/1/R/.L/V0Z./.,.V.0L.d-/b-J--P0./\-P0T0.B.V-,.+/Z-+N*V+R.*J+V/.P-..1N/\0--R-+N.*R+N*)X,V,T,^,,,*R,-`/.//-Z-L/-030200.1N0/0b/1----0R2/....---Z-,X,-,N-B-./D-V/^0J3d353J344V14Z34X3N535J55X76L878P88\6565N645R6V8`>A>X<==?`@=f?;:L9:=X@\;T=R>^?VB>==T==AL6:V;6J7:\84Z76P87X65666\6J54D43b5T4543^4N3/X1R0^1J01\1H/-V1T/X0V1Z2\30301/0X2\20/../.-,-1.-.B00`0Z-:-)J1T-/N/d.00P...T-/^.,*d/.V0../B0Z-D-,,/.0/2V1X10-T0X-P.-X/N/1P1V43H4^6b6V751T24V9H4T8X66V6d7`87^74835N755T6h6f6;N:N8V:V:f=R=P?>Z==?=J;l?H:R:\<^;\>X@@>X@T?V?X??X>@9>;V?;R@Z>X?R:b998;<;^=B?N=X=977d8\511V220Z/.X/V1R1X4`112Z2d3543l3T202V5V//,1Z/^..N//V-J,,,X,L*b,T,+0X-+P,+-*-*'%N(T':(P(\)'&*`(*(T&))(*&T'(#'V&T&#%X'L'&X&T''^''\$'X)Z*B)f()Z,,,-.H/V1134J63^95523X7778V679T7^5^5788\6L75L6R7P6J9Z::\8d7V;8Z97<69Z9L7N9P;T:96T8d6N89V8`8T:X6`;\:R8T=8;V6X98N99788Z4^5410X.0/V1V0Z0R.N-X*+'R'V(X(X''&N'b$&L%`%V#P! !`!TX\Tb^ZRTR\^PZX\LT^`RPNfX N ` \ b \ P X N  R fXZd ^^RL^FVR\NR\^ZRN\T`VVRHVZ\VZFPdPJNfZ\fNX\VXXZXTVR^PVXN`ZbdNP`Zd\^b`VHLZZTV\RZbdRP`TT^RXNPJ`JT`X\T`\f\XZVbh\P`RFPXXNV^X^RTThbXfP`ZTfbNRTV^\R\\ZXVV\bV\^`T`T`ZTX\TZRX\bVPRdJZV^LZZNP`df`Tjj^`LVV`ZRVnLfhVZ\ZPbTLbJXR\X\fRVfN\`dNZRRRV\\JRNfPb\TT@bRVPRPVX@T^b`RLXVXR\JZV\ZTXV`XRTJLHX^T\TN^VZ>bRV^TVVJ`\BNTd^L\J\Z@DPBPf^LZXTZT.R>VVVPNF^bJfX\bZP\bPXPZPhPZXVX`^NXLXR\X fR X T R Z R d  TTFJbLXN^RbPVRTLRNLbRRNVLVXVZ P `L\ V"R R\ $%T!J"P"##T%T&%T%''&`%$$$V&&b('*(\)+H+P+L,R-\+J,V,*V,^.X,/+*,\-,,-+N.P/-0.\1-0,-,Z.1./^/H.-.R-.,Z/-T-F-..-0\.-.--,L.b1-,-X.-.P,\,H,\/J+P+-N/`,./Z/L0N//L0-X/R.,,R,R.,V+^-*,*Z*+*)*,T0/J1V2T0R/T02/1..d/F-/.1Z0-\0P1R//\1T0P/.//X///\0^0^1Z02`1J20\01P20P2d01243V5N78V7V4V534`40X354T64b6T8Z8V8R86^5F7666J9T88`78:98h9T:T9;T:N89b88X898L9:H6R8Z8J8X8V9R7V9:878P64T44P35\3V7P86V9`:\8T6d9T:;Z99:7^986X87R7@68N4d4768555L4^5R4T4D5V43P2T1T530L1Z1/P./b/Z0`24.0//T12X2P1P3h1X01N0R/V1F0.-J0,/>.^/L/.,,\/0V-/N/V0--,P,-b-.Z/.Z..-P.-+^,,N0+V-H.-L-Z-P0/N/b0Z/2//^001.^/^.+/./^05F5L36`4P24V323T4P7657866X:L6\43f34@575T7N5L8J:\99b;<<;T:`;:;N;`?P=R>A^=\>@Z>^>L=?d=L?hBR?>\==>=Z?V?TA?f>>>T<d<Z><>\<:J;V:F7<::R>J=X>?==J@?`EC^@^@^=@B?Z><`=;>>=L=;@P>A@X@L>?B`>P@X@?=<::<`AX;=R=<<N;96554b15/1V0T02V1l2V1R3d3D5P623^632d2/\2/,-1^0P0N2/Z0Z,T.`/-X,)*b.X*,+++T)+\*l*)*$L&R((\'V&%'Z)J(\'(T$%%V''(V((N&f'`&$(Z&f%Z%`'J%%Z&X'&'X&B&&%&()T*++f--Z/P1H1>4L246f4d56P532P6`4X5\4P5434X5T5T654h444^44T5599855J6Z87V6F8T4h63R8R8745V7`964R4^5^6V<`8:R:<;:R:D<;7:::<;PAX>A?`@P>d<=^:V<^>N?=>:f8<;N>d?TBV?VA:F?VBZ?X=D?@AZ@b?RA\??CL@>b=@^==HZ>>\?V@?\>Z?@D@A`AAN=Z>TT=;V>87V871\31H2f10L1V4h1V42N53Z57D634`525R201.R/0\/V1N100H/`,-@,+,P,+V-,,X,R-T,*\++**N(Z(%)P('T()\(^)'%''X&%R*J((\)V'&^&'(&'&V'T'%V&&'^&&R&''''T)+X,+.V--..2232P53642V4L20`512455637\5T4J758N4697T99:5J=Z6\9V5N6^56R7N9:X9^78:L6^45\8^56`9P78:7T<67;D9`;\:;L<:H:T;X8V8Z6765X3361\31P0..N0-+--\-,Z*)(&N'*J'X*&%N&X$V# X !T ^R^X^T^XX^^XVbXR R T R P D \ X T T T ZJ X NfNVVLZRXXfhZNhf\R^`^lZ`b\TLR`TRVbJ\RZfRZLT^VVNFdR`RRXVjTbVX`HPjbPXd:NdHbjZfL^`RRVVTd^PLjN\^TT@dfVTX\ZVZVZ^\\LV\^TXVXRXRVV^TZPZZT\\Znfh^VnbVnTZVVZ\hZ`bZbVhXZX^Z^b^^`\^X^^RZJX^TJ\Z\d\`RTR\bZTRVNN^RPZDPHTTPPXPb^JNZbPFZPZX@`VZbLbPN`L^dPfXL``ZL4^HVRNR\THbVNXXTXX\FdVV`ZZ`dL`dT`P\@PR^XHnLTLRJ`\L^`PRT h ` \ R P N H b VVbZRd`R`T^PXXZh\X`ZZXVXV\X`VpZV"Xd !N! #R#V"&^&d%R&%X(T'%6&'d(`&Z&*B'l&&&T'(V)P)()V*\*T,D++R+P,-+Z0.\.,-P-\,V/0,P/T0,.X1,-T1,`,T...N.R.\0R2\0X/1`2-V.V-+X1X+V-X,,*-,Z,X..,n.-^.V0-T,,+++^---,Z1^01T0X0R0Z.0j/V/,,+^+P,+T.X-J--\+,P+T-N-X,P/J.//X01P0\2V31P0F.n/L--/R.-.20F1T0P1T2V01/0-1F.R00Z22f20112R43X4\5Z3T34T6\5T65P7\465467b6b65L778F9T65T85N6456`68V9T9X:\;>R=Z?@@A@A\AR?\@AF?>@V<898 ^ @f VPXP^V^ZhLTHV\PV`LXN`dLLNJXHNRXZTJBLhXRZPbNbd^VV\PTTT\XT\\BX`PVddd\RN^R\TVJTTH^LLV\TNP`bRd`PPTT^TPRXdVZV^RXRR\HZZXRTXZTTRfVTVRZXRTHRLDX\`V`lhf\bXZ^djPpHX`jZPd`T^\\XVVRPdbh`Xf^ZXbRP\hbNXRZV`LhZNN`\V`V^^BLPV@R\bbZDRRZfVRVX`XZVVZPDdTbT^VF`Tf\ZdR^TTTRZZPbD^lXVT^fNB^XP\ZVJT\VN\X\PZTTXV\bXLZRT\VHXRZTRbXTjRbXXT^XZPLX`JRZZNbPD ^TTX^Xf H V P V T ` J ` d \TLHRT\dR`XVX\\LZ\RT\RT^RV\ZdNRbP`T \! "R##L$N#$&%&R)X'%T(T%J'&F)L'*')('H()(')(b*,R+,,R+,\0Z/-`-,L,X.,P-V-P*Z/P1X/.Z/J/.X01^-^/R-+\0,R../^/0V-B0.^/--`-*-(+)`,L-L-,,/-`.--.,N-+,.\-/0.2-.Z1/b/0/-d.X,+X,-,---..*,`/,@.h/--0Z0D/X1V313Z10H/Z.X.--1L0000/0V2001P1T331h221412^343R5225^445V6f785B8V5Z537F4447X65\6T75T7B44V454X64L85Z969V8N::;9l:\L211121355`4444433P6Z6364N87P9;Z:9;9P7765^5\8P87768L97;X:;V?9^><\;;9<\<:=T?=;?X==l??=N@P;=<=H:P9;d9H;X>?<=>@?\>T@V?V@C?CT<@A\>\?\=9<9V=J<dA@A@X@@JA@\?=?==ZXRVZJ\NTdR\V\^` h Xd\\ X ^ \ \ \ ^  Z^PHZH\VZT\dXRD^LPRdX\JR`P HXJ HZ\!R!!V"X!#F" !#%%J&%R'V'T'%T%^&^))V,^)'((V(R(N+R*((^)*Z*)\+H,X,Z+X1\-V-Z/h+V,Z/\-.1b---^.0/V0.X/P./+H,f,N/R/Z./L2Z2R0P0../,\1\,J.+X+X*,\,*R.-.+X-Z.\-R-R-^.,T,X,--00&/V00\.+V,V-\..N0R+`-*N)j+,.Z/.-/-,-b-T.N.,.-d/X3/T2^11X32R00,/N/0/X//P/R/b3/L32V6`3L536X43V42`2T4442X5\6644L44R55X7N8X5R75V454^6N56J6974;X7778N95X7T4d6Z46T89<<8R<:;9:;9:XR=;;@=\979^8:b<^;T;J;R9X=X;`<:6V6N635T5R7J6f5Z7Z7^;:64`4P46T2X4L6`5443243d3`4\3413V2J2R3V41\5R4111/V0T/h0-T1.B-.0X/--X.V.X.Z-.`1/3.X0/0/0R.1`.1//R/R.R1X2P3\.P1\0F/d0P-/V014`1/..1j1/0R1:02\32^3h1X5V6Z4R5R76d8P79^7643b426Z85P7V:::9^7V9^7V9T96R8Z87R;T;=^:H:9<;Z;T;:;9P9T;T>@Z@VA\?ABVBB?X?Z<>\>^=;<<;^<<;>?ACPB^BLD@ET>X@@BbA?B;=<>AZ?@@TA?=;;P9R;`75`53461Z5R4456h76V:7766V6d4X4724X35V4F422\3R3`2.20,-V-R-P-.L/P2,^/P,*Z-,\*F+R*Z)(d*R*)*L)'')Z'V%(`)((*),R(&P&b'(%^&'P(b&Z(%N&'&L&&*(P(X-X*,+J+X,P,+N.^/N02\332^3f2P3`13^22X4X3L634^356P6\64Z6T4D79V:Z979788H577j5L79R656V87R46V:V8T8b77^99^9:P9Z;989^;j<\=:L;;T--R/-*-`-/,,+,-N3L02R10/\4/\2Z1001R-.R.V...N0//01312V13V4F6P5J5P34P24V6^6P6Z6R5Z7J563554d96Z856T533`7F86\7\:8J:X;Z:P7366b7775N5V6:9;R==L98`89X:<:97\9X<`:7Z:D88:98H98<799687^96X;V96N7B78T=::6Z7566^7X56P676677@7L6V7T645P4N4R5B6P45^56J721`2b3`011X4443Z2\64V6J10T2..P2X,\,-X,+\-L-N,h0\-J.-V.J./1T1R1T31R2Z30Z1`1X/22/0/1T12`1V/F/P.b/V.025D33/L0.d0/020@/F1T225<3P3655F577V79T6534D5\4X6X56::`;;R=H8B7\9J78X9T8V;@:9^99:L:<::X<9=?>X=d?H=P=LAV=;;?=X>^B@VBRDXA\B?>>V>=VT??P?@@AVECCAAZAR@h@?<<=N><>V@@NA?\??BAT<:8X86675R5X4P8\5Z66\767\9\7b6776^965V53b43V22d3D32X2T2L/R31/-V.T-..X/1-..,J0\.*`,-))T,,(N+'((Z'+^'X(P((d')(`)(R('J&&\'&'N)'&Z)\''&V')L*J((N*((*b,^,,,-T.2X2X2V4N557f3Z223\1`427X3N232\27Z9V6V68f6N8V8X876`;Z7V4P6b7T786X7668^57b4595Z766V;X8P9:X976R8V695Z6^5^3354320/N.--N.Z,+.+L.--J))'%^$d#L"# T!\T T`PX\RZ`\\bPTP`ZP F V b ^ Z ` F ^ J X VLVT^XdP\R^`^\\RJP^TPLZXVVVTPVVZTXXVfLNdRX^`VVdbTN^NZRB\HRZNJJX\dNb`b^NJP\`Rb^ZZ`ZLVVXVRZbR`PJX\X\bV\JTT^LbR\V^V^`JL`RRZ\RTPVZ^n^fhdZ`X`f^\b^fXV``\ZXbJJZ`hZXbRVRRZ^PXRZZJbV\VlNTdFXZX@XFT^^VV^ZXNZZZDjLddTJZNZL`PpR``VPNbJZT`NHJT\VR\b\^R\L^ZP\V\PZVBXNZZVP`^XdHRdTRfRfTZ\fZXDbX^RVZRDLZ^XVX\ZPV`TXPR^dVTZZJTZXLVHXVR f X X P V L dV hXTRPZRP\XPZTdTT^NXZRTHL ` R TNX!T #R!"Z!L!"b&\#T$\%$V#&$V)%Z&%'&h)'*)+V*Z(V*(P*'L*((*()\*+,-h-L/---T/X0T0R.R/21R-X/0T-Z0R--T,.`+R.d,P.-R,b///P.+L-N,@,N/L,+R+X++++*b,T-,D0V-`,/,R/\+++-`,`+P.\--X-R,-.,,X/--X.,,+R-T/`/d-X/--L0P..P..H/00N1/X2-0`201///./T/T.10R/11b2F01P12V35N5Z664R35X2Z433R3Z647V76L8`:P7\6767P778V6P55d8^7^:\9f9P<`:R7;H84J55^7T748F7d889;H<:R=:9<;N;P<=:Td>R<^;R;R<9=\>N=R:=;9<>T=\?;f<<=X?=A>@RBBTB=T@X<`=;>:==;V=>V?HC@AZEEBCTCPBZ?X???=L?=>@>AR@RA;8F=V;b;R999P765R3R824R793R8V64V1J/N2/`./L.H.R*,+Z-/,F,)(j%Z"$!`"Z$ f R ^\ZVZL\fV\VhVDVXbdX `  D T L V R L d Z TZZZB`\^NPZ\f^TVTNdPH^JZV\V`X\VVFZ^bbdR^hPVZ\XTXTVPPPbVRVPP^ZVN\VX^`\`ZZ\X\^VVTbR`PTbRRhXXRVdZ^^ZVNdTV`T\XdT`\P\TR`ZVJZb^T\XLhT\X\LRFNPBTTJfbTVRZVXRbhPZRL`Tfbb`XVX^``VXXhbZ^V<X`\NPl\VTTXbXFRZR`bXRXX^XZ\TXVVXZZ`V`NPTVVNVX^TV\XTfVTNTTFZNX\bXTdR``T\FdTdXTd\P^TXXVfDJlXR`RVZXNLRLZ>THZbT\T^^P^VXZT`RRX\Jd\fTL\^VHLLV`^ZRDJVZ^VXJVPNZ^^^L^ T P X L L XdRNT\LTNXTT`\TRLPLPV^Pf!bX V!b H\!N! R!Z!\ ! !V!!d"$%^%\%V%%P&V'$$%%%T()()(()L,X*+)*(+X)L+*,\+X,+P..,R.-..F0Z0L23./-T.T/.\.,*+\,V-)d,N+X-/T-/,\,T./-,\,V,,-**T+/+F--^----Z,*Z.\.X,Z/,X,+,-+/Z*+6,R.+,V,N-,-Z.-P/-/B//0b/0X0/J/Z/\0V13/1.Z3/X0^.0X1L12//2X/N020P2X/02P1R3V44588344<55b3L2`4F4X59F46D:647H577X98`69X::V87b9N:?;9b=?Z=X=T>>?@>;T?=;^;?9:F<9;V<=\?@X==R;L=T?;\=?P?>?X@VA>X?>>X<==Z>=T=BA^BJB?@RDRCRC`BHDB?H@>>=V?>L?R@@=?D?V?=T=<=;99^T=;fAX:<8L;X59^6\7X7V565N7H6b44Z1L1Z2N4-R/0-h/V-T.-+-)\*R'%#L#%\"Z#T" \!XPZZXZZX^P``XHJPJT ` Z ^ X L V ^ V Z Z V \VRJ^RZ\V^\HXNV^:HbhRV\^hRZ^`NVNP`Tb``TZXbNhZ`P\`LL^ZPTXh`@^Z\\L\V\XX\fX`XDPTVZRX`RZJR`\XT^V\Z^`ZZZhX`P^hh`^X`Xh^Td`\LNTXZL`VbbL\Pj\Z\ZZRTXb^V^^j`^hR\n\ln`\r\fdNd`^\bhb^VfF`\XdH`\bP^^dd^`RdXbRf`VNfTBXZBHZTXP\RZ`\XXV\T`VdXLLrZ^P^T^Z`VVhRZJ\N`ZT\\RTfTZdV\NX^RZN^NTX^TJ\`PbZ\TZFbB\^\TdTVVVHX^ZDN`HXhZXJfZ`XRXZZ^^`V^` N \ T P H RZV^lT`bTX\TfbTVjJNP^^XVHd`\ZR NT"\D N!!R X T#!!`# !^!"@#$X$&V&&T'&d'b$'%`&f&P+'T),\)\+P,\*P*^*\.N)X-V**+V.*,T1R+Z0P/^,-/3V/f2D2/112/V1Z.^.--B+,.,*V-f-.L0J./N,R/L+`,X++,)\++X++-N,,V0/h-V/X.T-P.V,*,T+X/T,X-\.-.X.**+,N.*)h+.`-,L-Z1P//..^.X.V/-/1/2Z2R1`11L0Z2b0V/`1F1/2126X22Z4h2Z21`21/1P3d5Z446:6`75V5X4N5T4X44^57>7P7@:R9L96b9X7^7P78R7j77879`889X9X=9<:;8T:P=\<=X?T?=><9V<8X7Z9:P:P<8:6^9;8b8X:\:V9:88`9\9::X:\8Z969F87b9L7:78:95V8^7^55:89b88T964d5434F6556V868P565434R2X42V50V1/H3X2V31P42V6X3J1X0/X.-.,,,T.P//+/P-^,`1R2H402535X02F5V3R12N3L213B222Z3<0N1/10T0L14T3214`2P1h1220L2X232R36T85V547P6\36^7V7J6b74R6\6N54L678V9\977X66R8\548:T;>R@;X<=@X>>=J<@N<:`9R9;R9P:X:V;\=b:;d;PZ=>D;J;;==D=P<=>X>=T<<<:;=X=??\BEBCDDBZEJAV?BB@\@AX??A>bAC=\><>Z==`?Z<R97T9J9Z76896^8<;R;:Z:\=:b9;:<:L:6554F42R66Z43421\/221X/0^0T2\-Z1-./,.R,.Z,H-H++R-N*'*)>)d,H,`,**+)*-Z(*)N*+)(&'V)V(P'R('`*P(Z(b+*,R*Z*J*^,F-*F*V**+D./-/..`1L1-20T0X222X4R5Z6X42T2X7424`9^8666\68V:798`67677N6b79Z8666:7D9R9Z:f>H?V9:H;;=?>:\>7N:6`6R6L4L8X7<583674V4V1T2R02f2R//Z.P./R,..J,`-+'%%V&V"L#X"H"#"Z!"TTV^TPbP^JNZXVTTZ\^VTTT ` ^ ` P N R ` b l X R h HfLVd\TZTXZ`XP\\VNVb\fZNTD\VRVZTH`VXVb\X^H^d\fT\nL`RXHRRP`\^P^R^VHbRdh\RP`PX\VTZbXV^hR\d\RT@L\`BRXRRV`^VLX^THTbJX^VFLJPH^XfVdfXVTf\Zdpd^^dRJ\d`V^ZX\HPPXPbPPXVPN`PPLfZHV^``VPfT`XL^^Zn`\Nd\NV\N^JVfLTNXRP\NVNfLLVXR\ZHXTZ^VZPTN\\PZPXFVPLZ\b\fX^VT\`HZ6bX\`RVNP^PP`H\`TX\PNRNTXT^``LXTJH`J\RPZ`\PXXdT\`RZNVLXVVN b X ^ P T RP ZZTZbX^H\TRLXLRhZLVH^JR^RRRT Z R N! L""F V"L$%"%\'V%V%f&&R&D%R$$B%&%)L'*')T+)H-*X)+\*\-,-*Z-)J-N,-,-h/-f2\0P0/30Z0P/1.0-.,d,V.,R/-/T,N,-\-,\,*L-T*P-+X,*^++P*,-\+P,P+T.0R/+L.V-.\,+,d---+,--R-X+-)*T-+X+T+T*F-+L.Z/-Z/..2/.X1/10P2X123R110P1X0^0T12\233422X20P10X1X23\43^54R4464b55J65554V6j5X4X86H7Z7786V9X6Z87`::X788P6::Z9L:X:l=;X8;8P97;b;Z:R;;9X:T>;7V7J9X:N9`Z?V<<\;Z8H8N9V;L;L976V766Z8b7P8L;69X9:X8:8:\:8`9R77J74:N675X9N7^:8P6T6:7>9d8J996`64Z4163L4l3<5f45546Z5T7T65Z4R4T54\6J2^1T51L2R3X43f22202/-/V.N0-/Z-0/X01003P/X243N454X5X5L3211P2h011B4X24X3H2P2232R1V32.L2b5B3Z5X52^21`2b44^3R57V8\56P6T87V45`7V9\9Z87Z8V:R7X6N5T6X67P7:^\=<9X:V<;Z:V9R:b;8J>9f:;T<==P>D==L;:P=N>\=;==R;?:HC\==L==?L?=X<<;R??B^DBCBVBPAV@A@R@\?L?\C?;=Z>=H>?P??>=H?Z><=:b<987T8:T9`:9P:<;;9=Zf:>\>8J?\:96b6689J67T6V7V76R5J51Z1X52/11T-^.^0^-`.,,^('%\&N%Z'#R"""#V!N !d!``bjR`X\^RLXZ>XV \ T  L ` ` V Z L H N F L V N TXT^\Zf`Z\bXX\V\NPTVLNVNbDXPPbZbRZb`XPTZh^ZLT\VNNfFRT`V\XVRFP`PZfTT`\Z\dXTb\FdV`\^ZD^\^\Z\VZZZ\Vf\PX\TRZTVZTLXNXdPPZb``bP^LVZRfPRDZJ^Rd^XXTVnPfdl`V^TRjbhfTbjVZV`\`LT^\JjRRjRbbTZ`\jTX\L`VXT^VPN^b`H^ZT^RNPdXDRT\DZ^LRbTRZZPbb^ZT\XLPjTbZXXNXRXbPdbZ^TLX\VVZN\TfZV^bTLVdTXbffVh^THdRdPNP\RTR\\BZdFTRVd\lH^X\V^jZXXVNbbZbXZNZhVZ\ZV` V b b F d ^ N P ^ dRjXZPZ@P^^RPVP\VVNZZRTbP\ TX $ J#! !N!R"!!!$"#`%Z%`'&Z%'%P''\&Z*'L''T,'())Z(H+Z*Z)P*`+P+)+*`+-+-N-.-X/b-.2/b00^/`..,0J/--N-\,,-J+,X,0L+,H---`++++,*T+,^,\-R-N0R-/.X-.X--+P+X,Z+,b-V->/--N-/T++X-V-),-X,)*X+.`+\-N.\./1/\0`/0\1J232V2R4D01Z10^22^02J321D2331`1R31\322L3\4354X33263V5T3V35X566385T6765657Z7X76X79V9J;P:^;;7;;;:V89`:b<9N9:9`<:=P<;99:R;;\`>:X=d:9=;L<<^=R=;T>Z?;X?9^=V9X;9F;J=;Z@b:<>:Z??<;<VAT?^?T>^?R=T?\>Z=>>>?Z??BN@V=>TT<999<9X:Z;;`;T>^=T>R==J<^;F95`4L73^77T6V6X66V57b5P3Z3R52V52\421Z01/\11800^2-Z/X+P+N+X++D,)*)^+\,+,T++N-b+,,R+*R**V)Z))T)+H%l*)T),)\**X-*'(f)**R-X+,\--d-T-.b,2,`/.,`0b..Z01P2X56N413X3743J689D6b4N9Z7H7R874\696576;7:V<9987b?=`<:9X:N@;<=X=?J=^>>Z<;::R;9V9`986p8^77P8R7V6:V77R<\9;T9b;886:88T7;7\9h87P8R76J7568:\99Z51^4\4T3476774f54Z4\65X736P22Z2R2V434^45`12b1Z/0V/0P0.^.T/-/42N3Z23J3`6R8R48\64V7>3X44^663J430X11`47P4P33b233H5`4T5P645Z4Z5^4L21\3^6N85L8N6L757J7p856P98R9:9J:B:8T9\<>9L=j<8`:\=T;V;^<9`:PN@T>R>b@9?\<=?BZAB@^E?CR?RD?\AP>VBZ@?=?Z>\=P@=?>@>X>?====^9T@>R:N;===R=>V==T<::>:\:V:9b;NV?>T>d?;9Z>^<<=T=:;N:`:Z:898T9L7R7V764T7P67J:9V:99T9L9Z9X8`8X9J<;L@H:8R8^8;7H776`7:=88T78^;7935332P335`4L5V16N62Z3T6T6^66L4\6Z533X2./H2/0b3342X2Z1N2X1\0./^.V.X/0J03P333b45L6459Z76L83^6b9V645X4b4X52124^4V4T4F3^41J45R54l44`3\25^4354H78T7T758d8:^88P8T888R;8R;`7<=9Z:Z;88^889:7L785\8\8889V>;\<`T:R;Z:R8:Z9=b@=X=Z<;\;<9:`9X>@`@P>A?d?FDAj@TA@dAA>==V>=\<=T?=^=N=;P?X@>A@=^?>R>L?X=:V;@`>;;R;;Z?@P;R98N87f5f8Z57687N7`776T66N4b523T5R44X5Z5b43b4V121b.\/*J+)*\+N)V-^/R.X,,+^.Z,^*X+H*\+N++)R)`(`**)X*(X&V''()*X)`+),(b,')\)V+J/P-^0,+/X,N.-,L-`/.V0R/X10^0X4Z3\735R324b655^7L86J6P9J77D758:6^9T86d89>^:`:X:8;b;NV=P=>J>V=;:==9:N8H;99J9;L8`:Z7=`9X:V7h945V73V23P4`7L40V.,d0R+^+Z+(\&)V'(J'h'R%$b$&b!!X^\ V`F!pTL RP`ZdXbXR^N^^XRL X T VT JT Z T T V X P V b V TNRT\HT\ZZR^dNNTZTbNbTXZTTZPTVbHRf^RVf`V^f`VTbF^TTX`ZT\Zd^bX^^jL\RX\Z\NbPH^db`J`\VXPZV^LZZ`ZR`P^LV\V^RVjFdR^hX`Z\R^VTJRVPRVPN\NX\hNhXT\TPXL^Z\X^\jZFfR`dhZPRLZVZXZTNTZN\TfNRd`ZRPP^PRXHXbRX`LNVNZ^R^HN^RHhJ\^N>bVNPlNVVVbDXXVJH^Z^NRTHdLJT`^bfVJ`ZPL`PZddTPRdZLRdFhRVZVR`PDTX`X^PXZ`RNRNVTRPZLZVV``^TVLLPLfLT^^VT\^X^f^VHLP J d V P V ^ V T V d ` L\b\RP^`N`R^RfX^\ZP@fZdV^TNXXVX!\B!!"X!X"Z! "J#!\#$`##&%R%^''V')&@'^'D'\'*T)Z())+T,**(P)X,T--,N+.,\-..d00*,0`/03/F0.`//^,b.-/.0/0\.0V-\.d/N+\-P+V.X*N,*,H+.R++*+X-+R,-X,T,:,,++R.`.-T.V//R/\-V,Z+,,R.V,\,,.X,Z,.P/\/X,+`-.`-^.-/d0N1Z1R433242N2P2N221L1R4X3X354X563H5V564432464F6P6d66L452Z4V23b6447T88778J9d5Z86899VV^<>\;f>;;V9;<;\Z=:8N:N8T=\^88b7R8:Z88b9J9;:P=9VR;>Z==\@N;;:;9=b<@@Ad@AAC@Z>?PAC@A=;N=H=\@>T>^?VB?CZC??@?P?X>X@>AVAX=<^?V<<>X:^9J965P:656857R67d87767453h45N5X4X3T4N3..1,*X++N,P,+Z,,,..Z-.*,-V,Z+V+X)(N-T*)H)j*(*J*(()\***)^*+^+++P*R*V+H+*-,T-T-V,+T-.-\/V.2,^1P./\1f3R3P7^3^323Z7Z5P3d745`64;X8X8P6X5687:<;9R9V;V:`8N:>>7R:==>\@d?\==P<=Z>?V89X8X8`7X6`7V95H937L431/P1T+L,+X,,`,()'X(N&T&b%V#%#R!^" RV  LTbPXTTZ`ZVPZV^\ l b b X Z V R bT DRNVJZVV\TXT\\XR`dVb^\^Z\\ZTjdF^XJXNJTHPXTXXNbP\RZZ\^D\TNLVVdTRN^`XLXNVPfXXPhVTTJdVTX^\XbZXRL`ZRL\\\LdPfZNXVTTf\bF^Z\X`JTXP^lV^\`Jbd`PVZVr^\J^fXTRZ``^NTFXXTRZHR`LVd^dbjPVVR^d`ZdJ^Fh`dVFXVX^Z`X\Z^TX^T\L\6\Vd^Z`^J\Tb^FV^\\ZPRTHdRV`XXT\PLZLZTXLbZZP\LXTXRbTZPdFXV\VNN^PRHVLTb`RZ\TflTR\LZLhZZb^^HfRPVRVTNXRZdJ^FTd TbTJ NZ ` R j ` T L d \ P R H H XR ` \VNRXP^VPNRfRTRTLX\Vh Z PN`@^X \!!# !X"T##"Z$##^##T#Z$V''%'%P(V'''h*T')L)*Z*(R)\()`'N*)X*,,.^*^,,P--Z,V/+-,Z/0X/Z.V0\-/N.f,T/T/,\-Z/X,^0..Z/Z0V-T.\+T,R**N,N.T*X*,X+,P-+R-+*+,d*,T-*X,P.-//V..-/b-Z-\.T.-+.*J/-\0-0h+T.-,.T,b.V11//0N3Z2R5P3`6L540`2Z2^10T325T62X3P7P5758b4\92556d4576V55L66X5f4V4^253P7Z776V7`98P;N=<<>;<:T>;T<==T;bX=J=X=L@R?;^?V:9X=^>@@ZA^BR?D>=@?T@d>VB<=Bb=N@PB>@\CBV?A\@FD`CHAXA`A>?XCZAT@\@PB^?99B;d9:Z:N89X8P7:78P;`;8:^7X:V:N799754P754`341P10N0`/`--+V-L--,-/\-f--^-0--,J,P.X*,R-*Z*Z(*b(P***,)P)**X-+X*,*(T***+N-X+d-V.b.^,/T-^.,-.X-/-/P1R024N332\3X3P04Z5V6P664X5J6X5R6^757P69L8V7b<:b=;=V;`;\:>87;=V<:R?<V`<=<;==N@R>=H<;X;R:;9=P>N`<::9:`=L7\:77779T86J89998T>9^::V96T:T:b:N879:T9T77h:^:V9Z7776564Z6V45V4P47R2P33235X64669T9T6P7`646`45Z6123P3^1b13P23Z31T/X1B2R2X10`355L46T74X76868\66T76L5698\86223/0Z1142\73X8P7T7467N4V5R26^5N57X657R6R8D;77:J87:6P<:<:b<<<J<:9F8<997V::89N<:XV>R?=J;:P;>@>XBETD\B@N>A<\>=>V>\=AbAb?\ADE\@AC@dCDTC`A@H>X?FB>=J>R=>XAh>XCfA?A\?=V>X;H<=b;;:9\;87989:N99:J8;D;;R<8^:X8T855X652Z2N2b.,L-R-,$-R..P1D0/./Z/R1X/N0^0.-L,`,T-*+L*)f(X*X)+P-j*H+,**,^,,Z+++`,L**+,Z,^,-0V-+b-N-,T0^/000.101H2f24R14f3J4X45Z74Z7^6J734665Z49\86L9h79?Z:>X;J<:8V;N=d;\

\?N=<;P=X=N<<<:b;;:9=9P8^:X;<9:>=<;8R96d7\8`:9T7^6634V3T/.-*,,T-Z.'T'V'P)V+P'&&%f$!$#  T P`TZRfTTX^^NdPXXd\^TNN ` N V T R N Z ^VLRXRPVVf`LlFbR^\NRTZXRfPT`ZPLN^VXRRXjZVVhP^R^XL\fRXP^PVVZTbZJZZPRXZRN`PF`VPbRZ``TbV^PT\RL`Vjd``TT\ZP`ZLPd`XT^Z\`X^bTXNLFVdRdhj^bbV^\T^XZPRV^^`bXRfZXbLR\ZX\R\VZZVdXH\VTlbZZ^ZXXVhbbbTdVbPZddZdZfPL\TV\VL^b\Rb\NZ`VbR^P\Z^NXPLTVRZ\XZ>XJ\TZPNLTZ\ZZZ`R``ZX\PNZLVX`L\ZXTZVNHP^R6XRhbLZRXVJPPRhXRNTRXN^LHNZ`XJ T \ V \ X T \ T H \ J XP L  Rf\LX^`dTZ\NbZdXJ^JTXTLhN T PZ! ^ #""P#"P"f$Z$T#V#%#b&h%&%%V&&&%N)R*N(()*\+*T((*'V'V*N*^,T)J-+T.+--.+..f/Z-F/Z2^0n3H0Z-./,T.L--,,,P--J0T/V-b.V/---`++\,+*\,V,,/,\,X.,-`,R+Z+*+\**L*,.--/N.1d0\/N/.V/*D-+L*,+*+++,+,.V./-V2/T0/22N334Z0R6d3R6`2Z4P3^7555V5775N7^5^7X5668R:5\955766Z6d58L56V5Z6Z8:X8T9X898n;:d:Z::<;V=h:F;\<==>;`>P=?X<>`=;9V98N:;;<>R?Z?R>:X<<<<;Z?;V=P99<:L=L:999X6N:V:<;99X6X46X5X6421R42221V1222J/h3X1f12\1013j52b5N23L4D6T7T9B8d;6J8968Z87`7V:5P87V65\2/111R34\6^5P75L666V47P5V4765b876977:9^<9f;J9;Z;F96R;d89=>ZT<;8^9:V<D=>P?>N>T=<;=X<@LAdFPBBH@\?N>>=V@>?^<>ANB?B?>AABBAbDBALC?>NA@XA@^@A@>?\>P>ZF?=<::9^:Z<;@>T;^=H=\;R;:^9N99:8X7\6X63V5T2\03.R/V///0../R04V3^11P/T0.0N0N-+Z)L*)'('(T))*V+V+)P,+T+<.R*d+\)*L+,V)^,T+N,,-L,L,+../X0+\///01R23f21353T2Z12V5`4^423L46R643X:J7Z6L:8f:8;:V=d;9`>X:P<=;N=9T=;=;=>J<`<=T<`>Z=:\:<=?An?X@Z;<::D;V>:;<=T?;=P>==b@D>R>d;=>:N;9;T::\878\:d=;8;V8R;8Z<^:;9\:P:88\:8N6V6P8V7798Z;X=T^;N;J>=;<<\Ar>=><@V=\=;d;V9P:<;V8`:L<<\>L@X>ZA=>X?X:^=<;^>T@`T>N>Bb>X==b?@DTCZC\=T>>;>P=^?Cb=?NBXAPA@BJEBEPFbDEG^CXAL@?@V?@==?ATA?>?Z?`>>Z@?BN@@>>^?>\>\>R=Z>R<;>;T;<998;V:`974N2F2^41X/D0//V/Z/.\11`0R3N3L4^/0/00/V.Z0N-L*,H))\)T*^)P**+-V+Z+R+b+*)`(T*`+++T.-*\,.-,.-V..h-L0N/L/-/d2T1T4V2H0f31V/2^2331b22X43T24T4`557X77X7T=8^8L@^:8<^<<<6P79F7>8T:65J3J2\1.b/d0H.L+-T.^,++`+P,(((R'&T%H'##`&#Z$!^! `^T V`TVX``ZVHBb^L F ZV \H Z d J N  XJXRLdhPPJNVVNXZNlPdPNdVVTR`V<XhRVZH^`bPTfZ`bbR\X\^X^bTXbTXVRXVXZP^dfV\VX`Z`Vf^\RX^\RVTdXRTXVjfZXXRNZ^XVNVbXVTXRlPJdZ`LXVFZZ^VTHVXLb\XhbTZTV^fRZjb\h\\\VXbllX\^f^ZPPbPh``NZZLXhbRbl\T\`N\\jPV\Fb^dX\X`^TTT^^VfVVVD`\NRZdVVTnZfhV\dV`^TdZfTVXXVXTpJZT^ZLdV\TbLb^jL\RbXdP`\TVLL^VZPX^LXZ\ZVX`N\LjPPRZfPZXJT^LT\HTX`^`VVT`LR`NVHjV^ZTT ` R ^ L ` R Z X f ^ X LXV^X`\TLPV\dDVRZbRV^`TV^X^!! R  V"!X""T$\#d$L%T&$&$V''&%$L(%N&(Z(\()*)),**+)`)V)R)+T+X)*+*h+^--,T,f.T.,Z1.V/-Z0,\/N0T.,+.Z,,`)Z*`*4+X-b,P/^0--N//,X,,.P.T/.-X-f-H.-/-b.0\+\*T**X)X(J,N+,*+T-Z,X,-0L-T.-X,*N,V()+d+,++,\,T.\/X/T.2P.B22221V015R43R551P3Z355678V7R7V9T8P7P8V8V7f586\6F9ZN?@Z?N>=L>Z=b:;8\:;:T:Z9;R?<=\?;>V<=R=J><=\=\>XR9V9V:R:P;8T8P9L667L5L656^6T42X5J4\4V3556R:7\7^7L9568X8Z;V==J;;;9::<;:>=X=<=J>L?RR;9\:P:`:R979^79\987;77:X8;X\>;\>T=>;T>L<>T@X@@@N?PBT?@`A?A?CjB\FETCbECX@L@T@V?^AA?V@R=XAZ@R?`EC@A`?d?bA=@CA?ZAA\B=P@\BX@P@=Z>R?>=L@T>T?\=X;\:;;898X865Z6b5`30T32P2F/11/0^1P11T1N0X21/03/.+`-F.X+R)'^)B)(\+R**.\+Z*,**++,(*\+d*+)V+Z.R..P/V/\./P/X/Z1/1F122`/22^3Z13P1`33T3X4P3f3^5V435\36D8^5787J6\8^;89J9:l<:N;R:79R9V9Z;;;;V:^=\<;:;@=P>`8\;`:L>>T=Z9*`*j,(T*T'X'`$R&L&`%Z%%%!T$!`"\ \^RPXd^bNdLPhL`d F\ \ b J Z bPRXbZ`XT\L``VBRZRXX\VbXZR`^N\Tf\ZXVXZRRZRVTLNTdf^P`V^^Z`FbNNTLXjNH^fXb`FN`RTXZTTTX`hhN^VVV^PV^ZlXRfJ`^R^ZT\\H^Z\VTPTXFTdNXT\Z`RT\`^ThJT\b`bb^X^dP^`^R^^ZXr\b^R^PXXbZ\\PP^RVXTJJfLPd^\TZVHPbVPTTLJVRXb^XTZH^FBRLLL\PFNZVXJPXLT^VZP\XZB\bNZ\LXHXVZNV\ZRbJVTZP^>\bRfTHTX^PLLRZ\PJNZLdfPLZ\jLdZV\XbVJH\\R\ZNLRdRX  Z R X Z \ X L P Z V J R RHRTR`^XRFVHPVNLN^LPXVX@NTZZVPV X!H!^""Z!"`#Z%#%d$R&%%'V%H&T'B%$T'V&((`(B(X)(*L*\-)+)J++L)\+@)*L)*+F,-d*,,,\,b/V/0\-X/Z1X0.,T-D.^+N+++*)()^*D),`,N+--.+,L,\+/,P0V/`+-L-1N.Z..`/R,j-^*J+H)'),*X.\*.+*+\-,P-V,\,*X,+^+N),`+X,++*X/^.0/0d01X2111024L4324T1b3N34569V877L88^7N;;8Z5L7d68:T9X8968L:P;7T:F988`98:=:;\<`@R?V=>L@>nBPAX><=:<^==X=R=ZAX>j>B=>>=;Xf;N:9L=<==\=N>>?\C\AAPBA>>\=;X=>;=??V=X@>@H?R=>P:N9R86^9h89;b<:X?J;T7R:b:J<8R8f9^;X:Z8d:V9Z9X:\>:^;J<<`:7R877687^99\9J66^96L89P;R;@H>^==<<;:8V<>N??\>=AR?=>>T;;T;\@:V>?@P??XBZBBJBDVBVECDRERBB\BTB`@T@^<\>?VB?b>\@BBCVCA@=?@@DCDCDDPBTBRAB@ZCdA?@?@@=?=J??>Z?=99j;j9V944f4L341\32L300R1Z23R4`1L632H2R3N1010T.T.V,\)N,\*T'V*F)+*X+*T+-^++V+)*T))P+L)P,J+,`+^,T,,T...V/0Z.N11R30012^3N3^11132d53350B1364J5b5R7L5V5T86d6R9L7^99;N89:N9d<<:T:;R<;R==>R=;9^ ^FVV^bL`NnT\LTZN^HXTVXNbHZZXfhLNLZbVX\Z NVT^T\V^XXdPX\R`VVdP^ZRJfZjTd\V`P`bLZbHNTP^T^ZPLf\X\TZLT\dLPXR\lNNTLPdTZ\XZV\nbfd``dZ\^V^ZZb`f`NhDZ^`VhTlZ^XdZVTPVX^Vb\^Lhhb\Rb\\lXdT^XZXdJV\T`HTXRV^RVZX\^VZ``\Z`RP\LdPRPXTVPXZ^BTZ^T\ZPTVrZRfN\`\TL``VTRhPd\TRRXV`ZXZTVN^ZNP\XPRZXZH`l\RV^XbTR\H\VVTNXX`XbHPTP\hX\ R X ` N P ^ R ` T VX T TfbXVT`XZXZTPXTPXT^PTdNPZRP^ZVPTZ^P N !`"#X"#b#P#V$%%H#$#'P'R&\)b('R'%%X'V&*(^((*V)(,)V-*T*Z)+F*d*,+T+f-`,V,T,--.+-0-b//.2/Z//-+*`*Z+,,Z)^**++P.).-`-P-X.V,,.^-.V.V.L-`/,V.\.^/,.-*))V)\*`**)*V,,,R-Z-.V.P.--+`+N+Z+^,+T.+R+-//R0J2`1V51T6^52h3\0X3522351L33V47N7T7\:`8\4b78`=L9T9V5;T687V8T9Z:X87V;V;<9=V<<9F:9P;R=RAZ?=N>Z@>?=^?R>=V?X=><`;<:TX=?>;Rb<9N;8:^:8N8^9J4Z;76R7L7:T:89X:X:Z78P7R79\8:B<`;N:R76V:R54Z7V756F;^74T8X89T64R66F98X:N9^;`8X869D=:N;<@?RD@RBVCNAZ@XA>A^C^>@T?@R=d?^<>B?V<:R=;V8<`:^:;8H9Z8T;Z8;V:`;;P;8P9^B@N@Z?B`=`=R;b;?T>TAX?Z@`C?CADCDC@RC`CBXEABC^AB\@@B@?XAC>BCVATBfCZARA^@Z>?VBBZCENE\CPJB\@L?CDBCR@>R?XA>A@>=R:;;>`>9X:X;;::9R=T:R9N;:V>>b?V@>=>V=AZ@X?Z>`>;>9X<<<^==8@R>?J>`=N:N=P;=T=V?P<;X=:^:V;\;f:P:B:9X:^9L9:;V=9:^8T9P7:Z6T8V6L87T7T;b87N88777R6T6^7J7`6T7R:Z9R:99:Z85\77F8h887H665T8N:6V8T66L68J867T56V:6P8\8^7\756657Z86\7^7R563X54212\4\4N545N5V5Z75696B9Z:;^:<>=X?L>jB?R=L>?>R@CEPGB@LAAR@B>XAR@@TC>P?=^A???;A>9:N>??=R=9R9Z;H@;<<;=X9X=9>:P99R;:Z=VAbA>ABDFDpEHCCJC`CVFDNC@B@BT>>@BN@VDXAABA@BAdD?BFLD^ECCCBBPFZCC`CA@`BXCAZA@PFRC?b?:AT=N:Z79X:\^>RTN Z P L L L D ` R >L^T`TdRLVHdZdJbD`XXRd\Ph`^V\b`\XZXfZ`PTTR`Zd\NTX`TZVXZbNZTV`Tb\X^^dbbXXX\\TTV^ZZ`T^VX^ZXXZRNX``LZ`PdNZd\VfXX`b>b^JTZ`VTFL\XVNPbPXXd\bdVdr^RN`XF^dddXPN`Z^ZR`hNbb`^Tb^VbNXTXRZ^hXZTRX\TZZRdLTPZP\fXZ\dZ^RZXZT`ZvTLTP\LVl`\\XT```LbdR^HV^^XTV\XX^LX^VR>Rd^^TbXXd`XHfJ\NbTXTV``Z`^NbT`T\dF^HN^V`RPZ`^TRVH\R^\b^bHRNLTbDb^VR \ d d Z V b P Z P : L f R ` TPPPZZdVNTT@^PNfJd\XHTZ \PL\TT!R!^ !!#"Z!Z#h#V$`%&"$&b&`(&%H)L*^(%Z'b''^)'&(f)L-.P+h)+V--+*^+.*N+,Z-N+N--,+.^-L-R-..T-`0--..\--,+H.,,R,L+(N++^,`/,R++`.b,,.J.R/N.N/P//X/P-+/+h-.L-X.X,+**,+.*,Z,N**X+^,,X-T+f,b-.*,@++--0.^.//`0T30^411P0`2J10X1P44N544644H4X5\6X665T67X:;:^:8H9\9b98\6Z86:X9=Z=PV?\@^>>^??N?>>P==B=<><=V=H;Z9T;:N<;789R779:P:X;R?V=L>f@b==;P;<AR:5\79P;V<@T;\:<`Z?N?C@A@?=B@R@d@A`BBPE`CCETBPABZ>@^AZ@X?ZAL>BZ?TA?;=ZA=V??b==TB=R>=?R??<<:9f;\=X<;b;R<:9;=V<88^7V:V9Z98;T<\;`7X:`;L7778X8X:\8N9T8R:98Z=T9`9H96X9^:9`>;^:`>;:B?TAl>==N=^>B:N=B?;\;9L88988T:^768N443\3\4T6L5N73655L1P2Z1X0f0P/.J.H/-R*)`-J+-P,,T,X1*`*F+d.(T)V(+*,H+X+J.X,`,,.H/`-X..^/.b2-232R4322X44310Z35T3V3\21V32X7N5^78J9`74P596V79T:787d:Z9j;9`87\>X:9R98`::T;:9Z:;=X>b=<9N?d<:T97X?T=\=:X;868=6N:7Z62R20H32L12^.1V.\0/T0R-***H*(('Z'X'&&Z%$X"R""P!!f`"T XXRRjVVfNRXDXdTNX@ `T ` T V \ VjV\^`dLPlTNZXTPVPV\VRT^X^Z^^N\Z\VRPZT^\hVJThR\Z\bR^\R\`XVfLLZRZdRVVXTTZLTZLTT`TdTRPPVL\N`T^jPfTZ^TRP`^jVVT^XRfj\ZbRVZLRLb\ZT^T^\JRJTR^VHTdNDRRZVRXXZ\X`Xddf\Nbf^`Xhh^dTZX`Z`\X^^R\^FXjnTZL^ZTZX`bZZ\Ld\RF`dPNXRLNRVhXHD\dPTFTV\\PTRRXZTXRbRTL^bTNZZ\JdTX^LT\NPL^JNVb^HN\VPLVHfN`PZXRXPVZ\`X`HD\FZ\\VJZ^TZZF``XLX\VLj`hTPNX^\T\LXVZDNf VX N \ \T F V h TZPXHZ\`\XbZn^B^ZXXXZN\NR\ !V!V"T!!Z#"L$""\$#$f$<$N'\%(&d'Z)*&N(T'%n)V'X'))(P(`+)`,T--+(X**Z+X-D,-++^+,H++V0T1P,,-/.D..b/R-N.\.-,N-T*^,X/J-)N+J**P+V.*++)^+P,,V.0N0X0^/10.P/P-,V-L---N++,N0+V++X,Z)X,V-*j,,N*`+^/)-+`-,`./.0L0/-b/P/N330R3//11/V1P323R6R5656R46R7D7`5X55768F;:;9P9b8J;VR=:T?=AR>T>X@^?VB\?b>bA\B^?hB?PER?AA\@V>RA>>\@=\>V=N=\;T;:9L9P;;T;76J<;:NT=`=T==>`D=@>=\;H@;;:V9H9V9X:8T:N;9b::9;99L9:V:9V;9:98988Z76P9P854578Z8J6::85^66`66^546R44T768B5d67\59Z98X8:V86\7T:T7:P;\88865V645T7L:8:8l64b6V5N7J5V6L53^44T5X96V8:V78\V==J>=?\?>?PCP?`>@j\@?>>=T??Z>:X;^>;<AXCZ@VDVCBG`DNECZALA@CdB?\DPBRBL@CA\CdCBTBNBTDXBALBBVEVDDDTF\EIHLFRHEZEXFDZBLFACFBTGPD@?^@A=T?>=`>\?B>A<@P?>Z?@APA@`DLA@?`Ah=N>\?=L?T@J?;>X;V8:^89Z:T8N9L99Z:\;;`=;V?X?@@=P>=PP==d:R:8877`9P;V;8=N:d9Z966`9Z7:`:P:999:\7`9V86Z5H7\7`6\;7T8:X7L:T8T967565655^5X5b5J6N88X8^57Z:`9J99N8V996^:V9H;T:X>T>;^>L;9>;\@d?>BZAVBCR@C\BRA`BABBFF`FTFCXE\DRERCC\BZD\CB@BCdBNBV>ZA?X==Z?>>@A^A\A=AT@\?^>>?<=@;J:^9\:X8;X8R8\8:`:N::X;N7;P;R;::F::9:=<>X@A^?NA>X>@=>T?T=X>V=P@L=`BACEGCBBBEXECAd?B>ABVB@?AfAE`CTEEFVADPADRDCRDhELGDfHFHEXD\EZEGDDBCBZDfDVE@B^C@<@?=X>V<=<>P@V=b;>;T:8T<8699J5R34T3P5N3f7R3X202T..D..,*Z)L+)(^,\)(\'N&`%N&L#X!!R"!P P X!`VPTTXPJ^N^T\DRXXZLT` TV b V ` P R b dLNPXT\TRRTNfRNPb`PTJDPNN^^`fPXTXNXZZfTdVXd@^^ZfXFNNdNVbRTFXD`^lRNhb^L``dRRZZXfPXZ\JTVTPVRP`bZTPRXXNFbddTbJblPTNbP`dXZ^L`XTXXP^PbZjRTHVRRXXX\`TXVZRVPB\```VfbbbZbT`\\Z^^Xf\PNTX`X\PV^VXd^^T\fJLPTdNT^fh\dDZXDRNXVNVV`PVX\RP^XDLNV\RRZXTXVbX\ZT\RZPfXPR^RTNRbLT^Rf\HZZTZjVVfh^`T8bbRTZJlFRH^XNL^bRZLTLdTTPPX^^XJXRbV\:ZTN\RVH`DTTTFZdV^V^ N Z Z R ^ P X T ZT^^@\TH^PRX`VZZXFfFZTF^JJVP` \ ^ !"R Z X ^ R%"P#N%P%#$#$`&N%T&(\((Z&$(b(&)(\))L*('R*b*T*)X*,+V*+*)P,\/T.,,J,0/--R.,.0//\..T0^0//.-.P.-,.,,V+*V*+\-Z*X*,R---*Z.-/-011J0P0-/D.\,-R,+-X-+.N-*H,+*\,T-j)R,:))L+d-+.R-,J...//0\0^1/T0d020P2111N22V52\533375P855658T7R5V6T788L::::>`B=B@A\CBL@C>@X@?\@TDABB@LE?@T=;>b>===DBj<><:=L;X?@=?f<=X99Z79Z9V;R:P;9X8:f9;R7R8:;N=f:P9:69J9T7N?\=T>X;=F><P<>\?T>A?XEB@Z@PBP?=@T<;:8V899P;V;;R>AVA;J=T?X;;><\@NA?R>V@T@JBj?V>=<=N<<@=ALCXBDCXCbENBCFEVEC`D@APB`ABA>V>F?>BDdGD`HEBGEZGBFRDDFJVFTGdHLKhG@EDZFDBDDEDDBRA`AAP?C?R=<@=J;^<;d<`;89:J8X9\67L45P7X94V76453d11b00b0N.V.+X-,L,++-,.*b-*,()*R*^*,+R,,.,-X.+,.-/P/210N2N635`5452`222V33F13643Z2V6657L8l77T79T7X7R97876^6P8::::J9;9d\>;d???V@H@\=Z?A==<==^<;P?X^@A=T?RB>L=>?==;TLA=L>V=@;V:;8L99RC>>Z?P@V?P>@CBXBTEBGBBPCXEEREXHGFELFXECDEBEDAXDBLFBZCVCD\@@T=@?AT@BP>P?CCZAZB?X?P>>?P;;99>H?`=J<^?;;;8;Z=BD=XDR@A?J?`@?J?Z=V=;L=<>\@ZBT?>=NA<:j11X4\023R4X45X3V52d23/T32`634N4d55T7N46R7`8:6V86:58H65V8V67^7d;T7<9N;^:9f^<<<>P>T>>@==T;`=L789J::9X7P7X75X5\2T5N2232Z/d/-R/f//,\)^-L*'^(($%X&&X#"P$#!\%f$V"d X P `XRHXJ`\d^Lf^PJL B R R T \T VTZ\L`^NbfPRdVRPTRZZbf^JZPTVLdJPTPbTjVF\Z\`TZZ^RXbJZT\XPXVF^TVZXLZZbXDfh\VjZb`\ZRbVNR\jV\XRVXZX^T`XdRTVZX^\`fTbZX^ZR`RHZLR`RVJ^b`VP\PHbdhdTfVdLX\T^^D\XPV\PTLZ`fbTRPR`PZV\VJ^X\VjXTPZRLXbVNZXV^LT^V\RZdbjTZPRd\TVR\\RXHV\RZRXZNTTR^RXZ\Z<hXPRTXXh\HV\RT^BTRX\d`ZVVXTNZHfZ\VT`^T\P^Z\bR\bVRJ`^NTPPHJRDN`XPNPJ`XHZbZNZ  R V V \ ^ JTD   RXZTV\\NLRPJXPXVX  D!N P#F T H!\!"L ^"N!Z!R"P!#$P$\$L$$V%$Z'R&%L)T'X'F'T+`('J)&*R)*()V))N*V*Z+V**P-V*)X*`*P**-J0L,-.N.,X.,N10X1H0.V..F1V.X/-,Z+P.,-B,-T.\,,-T,,P/P+-+-+^)Z/,+N.d--1/V.0-/N0-B.`//R-V-+L,\*,)\-D*X-)^)V*,Z*R,^++V++-X-V0/T12L00>0b.P//T1V0f00X2./@2T2N06`757V5^6X546V8Z97Z6^657N9Z878R=<?R?X=T@;H?R?RA@NA@B:CTB@EXDPA?AAXCBAD`BBCAA?>L>>\?@PBB@hAZAf=F>P;B=:T===>F=R>T>jP>?T@?V?X@T@`=>X<9T;;b>NP;:=>V@XA>\=R=X>>R=@>BBDCRECCDTFCDGZEENGFPEDVECD`BPC^DHPDCAZCNDN@B@?P@N@VAXAL@@CAPA?^BA=@LA=^;R;`;;=T=L=X@\>T??d?>>>@;R;V<:;N6R7J5^978V;7=;>N>^>@>J@T?=T>?9;`=R==X@@EECGEJC@CVDFE^CA=XBBRAN>AXCZFPEANCDFVFDFZGDNGDXFHGGGTHJbEXGBGHVHTGRHGFGVCECC^EdADDD\BXARBZ?P@??J@@C<>=Z=b=?@@?:>^=NCZ>?TAV?Vd`b\\\\\TVfLV\d^XPNVTTP\\VR^Tb^LPd^dJ`^TRR^^V`V`^RFf\jXPRbVVRhZHT``RP^JJ\TVNZ^\XTTP\fZJZZPV\LZV\bZ`^X^XZVPTXVJXhf^`Z\dTZVRZXVPd\ PZ X Z H R b H h X V X XTRT jdZNNbfTLTLTNT\T XT FJT!!!#T!V! \!"X"#$P$P"&R'&'N%#Z(&N&(V(\)B)&&)'H&&*T(R)\*N+^,\()T+*h)\))J**)**+,N//Z-.T.b.+..L.X3T/P0/,-^--,X-R.-.T-b2---\0P.V/+X-,X.-J/d.R,b.V.P.Z--R/J//P3P10-.,.-+++*+N-Z*)P+N,*X*h+T-R+**T*V+T,,P-../T1Z2N1V0-N./^/-d..`/\.0P4246Z67X57437Z8Z5P::8R98\<8Z8\;<<>V=@Z<=>>`@@<==>@L?@A@`CDEXCAB@bDBTAL@@PEfCBBRAAVCJ>H@A@@PDB`@V@P<=b>X><<>`>Z??>L=;`>TZ=<=AP?>N;N=X=Z>^?;<<R;X=V:F=V:V?@B@>@@@T?A\?>CBDBDEDFGLE\GVHEXGNIVHGGGbHEEHPGPGEEXEBZE?PFBB^C@ANBAdAVERBA`B??>PA=XAH=V?:9R:T9>VBB?@;D=:V=H;=?:;J87:V:9b;979T8T:57N898J8f<:X;R>\<<\VANBX>^=>D=;;:;<:T;X;R=?CEHE^DZ@@DDXDAFCZAZ?T??X@N?`?Z@bDD`GZEDERDB\AD\ERETFbFBjEFF`IG`F\FHIPJ\HTIRJVKGF\ITJGZGEFE`FXBCDCD@R>^@P?\A?Z=H>N=P8R=A?>B=^=F=`;?>`>;^B>V?@bZR`F`^fd\N\bRhbVVZff\VXd`^d^\ZVXTlX`b^`RZTZRPZRZVZPV`ZZP\HXTX\dXdX^D`\JX\lRd`JT\ZPN`XTXTTTPFRVVPX\PVdPbF\R`TbX\RFX^T\TJXNP^HX^Xd@\BVfHX`XTVVRP^PRVLXXLNTXDNT`TT\b`^\NZRFVLBRXXJXTPP\XR@XdVZ^RRNZ```\NHL T V V V `JX V\^ XNVZVN^^\V\bJdVP\PRL\XRL"L!J$P!Z"$$Z"!F""b"%%'Z%$%#%X%%T(R'&Z)X)'`&+'`&))**Z**.+*)X)b*X*P*X)`-**,b./R,-.T2P0R1-\-V/F,V./R/Z0.L-\,X.d,N.+*-V-/.Z.N0P-V--,N->.b-V,+,V.P.V-Z-`-\.Z/0-\11/-X1/-\---*R.L*>*R+b*X.)X,N,R,*+-J,,V-,+P+Z/.X/L/`02/1<1T/.F.-\.N.T/J014548R75V7Z6D8686N787R98:V98R9X;:9:XT@?R@@PC=>T>\BXBPCNBbDB`EXD`CNB@@AN?@TEPABLAhBF\CNCVBAX@J>X@V@ABBTAZBb>>T>?<?\:;=N;B??=?d>?=TAN98P:V85\88V6b7V7\:9X95P884435V5V6R75V8d9:Z9T6877T8P:V7N8V69;\;Z;T9R9;:T<:;N<>9<^9:Z<:>>\?\;:::<;\<;=<<>;L==XPAjB=PBZ@@d>?>TA@@DBC^HXHIIPHjFRECJFXDRHbFXGNHJ`ELHMNFdGFBfFVChDBHF@R@?ZCP@T@?N?A@`AbAHBRA@`?Z@ANA>T=;9:\<=N>>dATAV@L@;;:\;R::f<=V=:Z9>T9=X99T;T88XV9;9T7T7;:9Z=Z=>T>>;;;:L:`;9`:\=V@\BJCCFEDbEbB\AXA@?TBZC@D@CZABFGDCDRG\EDTGVFIDVF^HFHJGLGHIRJ^JJLJHXKJLGXH\FZJFELHXFTFBVCVDD`CRB@f>B^?B@B::T;:>^=L;:\:75T2N522J43P0\..\/.-R-P/T..Z0H//N,L,V-J-V*.*-L-j+-/0,Z,,d..\/P/J2Z1V2T4T1121N3P3X3230N12587\8V5J57L975N78J63\56Z:8@8Z5D767R5:d9V89:;Z<9`@X??RDdAN>>`>N@X=`?N;;:<=?`>BAfA@@=V>>>BCPBPBZC`DDdBBEVB^DVCTB^@NB^@ATCA`BVEPCBVBALBR@B?bAAB????T?ZAX?=T=@<>X;P;f:P==X>R><`==`;f;<9;<;Z:9:@9X78^86697P685`7N5D96T537R67759b8^75h476J9F7J7b8P85Z65Z6H67675d9^8b89;7T6677X8V86^76b99:^:^;X<`:;J>:P?`Z>>T::T;V=<;\9R;T:7V:d?@P>T<>>lB>L>>TCJ=A;;9:;N;X;9T;7`7`:97;V>h>:;@@dAACEZE\BEB>@>??BA@PAlCCFFCDGDNEDPEDJHEbFFGHIZKTKJVLMNLMOMNNZL^KTJVIZLJG\H\IPGGDDZCBPBHAVARBBP>T>TAR@;^=d:^>X=Z>X?T>^;9L8Z5V7d35P243\2h1/f/...0V1X.\2/N.Z0Z-N/.T-Z,-+,X.L/\+0T-P/,.000f21/13`5d4/02^5Z3P/d21P1V74T57Z8R4J5685V69H5H65;4V56Z7X756`877T8P>9d;N=@>Z>=@@V@>R>>Z>`>TAR>CVA>^A@=<;T;9RVFX\NLT``bDbVD@ZhR P d L b R RR >TbJ\ZRXZVRL\XP^TZXT!\ V VD Z d"R!b""!"Z"R%"$X&Z$$&X'#X&V%$'P&&&V('V((\*R')L(&)()L(X)\+R+(\,+,++***H**V,*,+,Z-d-\.--X+-T1T0T0.h1@10/X,.P.T)(R+-\0-`--L-,--X--f1.H/V/^//`-R-b0N0F1/12/P11,-j-L-/++b+***f+,+Z*`-X**D-4,..\0X+.`.0/\/1Z1D1V20\1Z1V...8:J=T97R:V;`:h<:N=`=XAX@R?AX?N@BVCX@DP@?`BVCFHRDDXDCLCAV@bBDC\E@BTA6DANDFHEbGBCDBVDZEBAR@ACZ@D^AV>@L=>;V?^<<<`;;<9\8V:86Z8J:V88V75T5R54545V7\5345497Z:L97`55X7`68Z6`9:Z7h5b7`6:d7P7T5d87T8R:::99898P:F67758T7d:::9X9V=?:>T<9:;A>>Z?T>P>>^@L>?^=>AL?=>`@>Z=?J?>>N@>b>`@=h>ABXB`ATBZEbC@@A\@AbA^CBDB`EEDFHHTFVDVDGTGdGHGDNHHVGDVEVDEdBBXDED\FAPB\?`AVBJBTBjBAPCCCPA\EHAAZEL@NBJ?T;>V?N=X??fAJ@PABX?@=>Z<<:::;88F<<99R;L8f=L9:L8^8R8\99LV>R<;:X?@RDLARE^BVF\CDAXBZC>T?^@`ABERDACTFbIHHF`ETIFNF`J`JRHHDJG`EHFKGHRLRGMLRQKhMJLHRNLLfPKLXLKXLLLVF^FDBCDEFlEPCPEA`@AJA=>P>X?=?f>@>L;V896X6X4\6V45^341\1/T0\/P-X2//0\1T1P-V..P.Z,-+V,-b.,/1V10P/\0-//T3\0300-1/L1100T2Z3N3b235D7P4T6\56F4H7D9P85:Z84T57:^734P6Z65`65^6::\A?`@=>;>R>@P>=>?h=\?N;d>=R=:9677\9L7:T97f8L99V73Z5\212>1V2Z0P2d1H0L.^1X-P,V+f*L)R,\'d(')H&N%$\%R&"">!# Z F` Z`LLbV\^RZ\>R\^ T X P N b N V P`^NXNP\LP`T\D`VHHb`JT\NZXN`P\NLVVXbVL\`PXTVVTZ^f^d\^f:fb^f\HZjTLbVdJ^^XVRPVVbZbT\X\\^ZXVZ\bRXVN\HHXVPZ``n^X^VVRN\TVX`V`N^P`XTRZ\Z\p\ZX\\\dRX\XR`bTV\ZR`fRPdX^R^XRNb`RB^`PhXTRVLZXTJNZPVPZLRNZPZRX``LRPZd\R`J TZ4d\VZ^\b`V\TZJZ`hZT\T\R\^TdXVVNRZRPZZXNZZX\^ZTD\RjVTX`X^XZZNTTZ^TZPXPNZHbfTRPNZJbDHJVZVZTHLZTNf XP X V b \ R N T  X H VbLP^RZDRPJXh\ZVHTRT!`R \R X!!"X""$b!#"$V%N#^$Z%V$$&$Z&$N%V%&%&T('+(+X(Z'(X()T(\)(*R*R+,*+(P+`+++)N.)**J.+-/R-,,--T0X.H./N3N.\0V/.X/,,+X*T,)V,Z+R,-..T-J.d-.T-N-d/R.^-R1-/\//10.b01Z1X////\.V.P-X,T+**X,V+R,H+++\)T-0--/\/-,/.b.R0//P21X431\0P0/R/-/112\35N79879^998Z8V;:88Z9F8N:8\;;=X=HANA^C>B?\ERBAZA@CNCRBFNEdFHEPC@ZAPABRBL??RBPCDDRFDCDADRBCF`CBXE\C\CE@CBXBTBXBP@N?X>;;;D<:;;=N=@^=P<=<:9D9h;<\\=9@98X:98X;8;<;>XT>`==J>N;;J<?=?T>b@=@>X?V>A?`>b=V?:R=`=<\=X>R=?>X@XC\@J@>>XAAC\=ANCVA@JA>?Z?LARCFVDEFVEDZDXEECNCE\IJdJPIMXFLGJGGERCPCbFGPHZFPCFD\BhBbBBCC\BbCTC\D`E^CDBPAEbCCAAA>?@\@XCB@J?b?>R:<=F:97b9T78T:8R8L:b::L:\7f7D8\<:Z=>Z:Z<9L9f<<<^=:;:P@`BVFbE\EJFXJTFbHHFHZGXGGEGHEDZEGHJ^JKTJTLVO`QLN\MMbNNNbO\MJfMM\KHVF\GVEDCBJDRD`BTDPBB^?>>B\>Z?V@A?^>R;Z:B=b:\6465L8J4R4.2\/4P0R1X1T1N1^3L0l/,V/Z0>/X1.\.-\/R,T//V11^1Z/.P/-/01^01T3J0P1`2X2124L1135T5R7\35^55V4J57^7759h7d:Z75d876^5T6485X9Z99X=L;>VR>X>X?Af@?A^@@A=! VLdZNZbXTVZ LN H N R Z N V FVXZZRZbFhZhZPXP\^\XV\ZZVZ\RjZNLT`X\R\`bN\VdTfJRX\RXPVZdV\J\\VRVVbRVXPjLRV\H<L\VLPRPNVXXb^`VNTNXlPXhHZZRT^R^bTdX^`@RTL\\XRbX\NRT\ZV\DTZZhXTTdLV`\bVLXTR^XNZ^`fN\h`V\X^\RPRh^Rb>fVj`HNd\PfVRZTTVTXdLNZTLRdbXRH\fT\HTXZLTRL`JXfXTPXXRXPXdH`TZVTRLVTbPXPfNPRZJ^LX`FX\TVPbNXXdR^PXVXVbDVPXTVBZ^hd`^XTXVPfN \ ^ V V \ R d Z J RH \^ XRXF^RV\F^ZfdJ`ZPhVTPLb!`! Z"F" X!!P#"d#!h#"#J$$f%P&%V&%(P%V'd)&&(X&(d&''H()P(T((()()L((Z+X*\)+)P.+R+,Z*,*)+`/,,\-,R-R--,\,L--/T0-.T,-b--f*-,d+),N-f-L-X.,.J,b.R-,-X.0L.d.D/\20d201^//T0X0/T/L.J...Z,V,H,`+,,+X-X,V)^-,,P.Z-T1/+/F2/N00/1\1\1Z0P1J/3R3R01N0d.X10123<7F7878`;9:^;99`7h:6R99<;N=TAbBbBCCTEbCCFD\AAV@`EXC^DPCELDTCBBL@PBTBXCREBDCD\DFEHBEEhENDBTCF`@RBADE?DLBbCT@^=<;N<>T>;f>==V@^:Z:N:Z8V<8J=T:9;`9<\88Z9<`::R=<>T?`==?XC??N=>?T<@??R?X>>>T?VBXANA>R;X>`=R?A>?PCPBL=>=Z=N?V=>V>V@A?BRCXBJ?RD@=@@?EELDEPEFF\EREBIFHEJLHTMIKHIFFbGHDVGRDdFEZG^GGECZGTA`CCTHFBFCZBAC@REHDED@AATA?XBRACBZB@>?X=;P=R<<=<:=9;:R;^;`:;R:Z:97Z8N:8;7N8X:T<:^9?B?N=<<<@J@>`<=<<;\?;;^:`;7:9:798`9L9P7T4Z7j47R1L03T42132-.L-.,,)**)+<)@&R%%%b$%T$T#"V!V"N`N# VfNb\dRjfb\^Z``\Z`P^  N J \ V ^ f \ J RXPPN```NPZZXVb`@LdHRPVLLZXXR`F`^P`VJZRXV`TNX`N^fXTRXRTV^NjZVTVVRbRVZRT\PZN\jZLDXffZVZV\lXX^P\P\VTLZ\VZ\`X\dVZVlXbRjNVXZVZVXfXPbRT`\^NTXNbLR`NZTNBRbbfVbZ`b\N`^`Z\^jZJZ`V\ZTL^\VD^\^Zb^RfbNfZbd\XX`X\ZP>^\^TRJVT`XXVZ\Tf^TT\X\VBL\TX\`RXV\NTVVZ`^XPRTV^VbZZZLP`Z`TZHbXFdNF^LZbN\NPXBVJZ`^\N`XRZLVbTRP^ZjZ\VXbHfLT^PVPP\XTVh\V\VfZZ R N ^ ` ` Z b VbXNT ^TXbR\ZXZ^PVZZJbH`T!X"^"^\"!X!\"!V#"#P$#^$%#b'(Z'(`'X&N&%T&('V'))((((f(((X)'')T,*T*R-X***P,N+X,d,^+d+N-*.-T-,h,/,J/`0`/-0P20N/2.\.\0.T..P0R,,-+,,.b+,L.X.,-X0T.d-V.-..f/^2/V1T01\..P0T0/T./L.V/V/`-,/N-+,+,T*\*N),V.P-+.R.0P0\021R3J2R33>30F1000R00Z1V1P325N75L5`6R7Z7P9X9:Z:99`=98N:b;L9>N??V=R>T?NC>^BAAACTCCTEXB\DZDNABXCBdDD\GFFAVBZDCAAZC@EF^FGLGdFHRGGGXGDZC`CCBVABpB`D\CCTCX?@@`?=X>?<<=;;\=\>9=98J8:T688N8L:R9\987D77N68J6J6`8\5\7d558888f8b7h64j56L5`886P665799H7:Z<::\<\<<586\5R567Z7b7P<9;;8>;`9JX=X>?=<^>@J@<@?^DL>VBB?b>@^<^=F>>??>?`A?>\>T>j><\>C@XAECBBACV@?VBPBBCLFFETFDTEVFTFEFGHJMVNIJFDZDNGXFdGGD\GEZFNDVC\BPDZECCEDVCF\DPGJCVAZCCZARETDE`CZIDXBLCZABB@A>T@R?=:\?V>:J:<;;Z<:9R;V99b<`:P=\:;;:\79:d;R9Z;=::V;;:>R;<88^5`799X=P799L<\==B=;<8h56^68644X3V22Z43H2231/0L.-/N--/j./\1@/V1R20.T1X0110b.f./T1//1/P0J.1T4R1\33H22R43L344\6\2T755X6X7Z7X;V7b6N6T7\7N257R6V896`<9898h<;=`>P=X>`@=X=L<Z?X9`:Z8d85T64V3X5b4342V2\50V11Z120T-+,Z*X)R),(\*&&X$V(#!Z" T$\"F#\ R#`^VXdbVP`TRJTVT\JdT Z L \R b V T VFZ\>TVVZZTX\bTZRVRXTZ`L8bN^Xd`XZfVfZbZVRBJf^Nh\TV\b`DXPT`PTXT`TPPhb^X`\BXRTXfX`bR^NlHfJZ^Nd\b\\TDPV`HTZ^T^`XXZZZR^ZXPjb8ZZLd`F`XV\dJXJ`d`dhdlZNb^rZFbfd`RTbdXVb^TfX\j`ZTXbFV`RRbV\R\X\PRhN\\VdNFPHPP^RPVXVRpbX`X`LX^^XZZlnVZF^ZTjjZZVV\LT^TX\N\JVX`HXbfP\NT\HZHZb``LNT\PVVdNTVP`ZNZ^fZNNjJXbNbF^ZlRRRNV:Z^`FJ^bV\ZDRLRJdRVNNbX^ZJX\PR \ V X R J T  \RPRZTVD\dVRJbT`TR R!Z T!!"V"!R"L"D#X#"$$&$#$V%#%Z*')T)&N'P'd*d(R%Z(X)*V+'((''T+d(Z*^*)Z,Z,Z+T)+)X)*^-J,-,*H,^.-+h*^/N--*,,/^0V./.^1N-.D-..V.L-L/--`/\0Z./0F/Z.--N,/Z-,-\/T/T/V/22\3L4V2V1T1h0N00H/<0.+V-X/L.+T0^+R-P**b+***X+X,-R/1d/1X4H213d6^503^2//F2452`2221Z3H654457J:^:`;9T8f::H9V<8R=V<;>P>L?R?=??PBV?V@CRCTECB@DGLDDCJDPBJD\CECBB@CVFPBTCH@HA^DPADVCRDZEEJGPGdGGXDFVC^FVDDBTDBABTC@R?\=X?=@`?=R<\T:==V<;Z;F=^<:P<8;==:N=:V;;X:X7;T7P78T8X8\65746544\4T8T76X5`8\7Z6V796H8875L759;9Z9J;Z:Z4T7\6^8f:X7X<:V<;==;^Z?AR>=V?@=d>bC?ATAJ?^??\=h=H?V;>?N=`>T>^B@RAlD?<`>====;<::b9R9Z:V9R>F=@:<;9V:8><;V9;H;:N;;779599T8V<::;=<`<;N::\:9:=^=?C`BD`EE^BXF`CVBARB@ACBABZDRC\CAVDEHKI\HRFZFTJHNFXEEGLIXJLJM\LPQ^QNPOQPVNTUPQTQOdOXMJdJG\KIHMJZFdEDJGEjDPFFFFNEVBFACdDGJDPB\AL?Z;T;^88f9F86L8d6T5X31Z42223d42P2N.\..0R,.L0d.\.N//Z/L/V1-1X3Z1P1F/d/N.P02`1j1T2H1\3N31^04^2X2T23X5X84B6T3L5d4365Z35X6b975R422^7f7L67Z6T9P:Z98X?<:R;:::;@J?=\>=V<^>`A^?><;;;Z?f==\>??Z<>jV=Z><;;;^:b9N9:\7:R7f99V:7\975\5^56Z7X8P7V:N:H97N669R:=;Z;4T7\9X8N;9;8`98P8V97V89X<=V;\;^=T>\:`<:R6Z7V85f9N:8R9b=9:b:==l;N??X?P@=>V?>`<<;;F=;??VBJCZFPEPCB>Z@T?V>?A@@@?T?V=T>=N=?T=X@?>L;Z>T@>>?^??ZD@PCCLBAA^?dCV?PBFD\GFZETBBAVD\DIZHJKK\NZM@OKXJ\HFHJGHGG^GbF`ERH\E^GVGCEPCB\CPGRDPHEZIDCZHHRKHKEH^DFLAAX@PAVBJBRA@ZATBPC?<=;<=T>\>^>P;F;;:R>Z?L=X;P;f;C@>`ATBJFTCRCTBB\AB@AARBAZANBXAJEfBX@DPEdDGFGHIG`IHVG\FEFGEGKL\O\NPVQbULSTQRRHOdSVSQ^O`RNP^OPhPNIIRKHHXHTFHGFFFFBFCNCZEDGE@D^E\BR?d?V>H;7R9;8T98B6^44R1J5113Z62321F/0N.-3X/-0/d21/2X//0H0//.Z0\0`10d4T2d1H3223034R2323D953R6d564L9X6T7T788X543V5F66\7H98T8T8R;^>::T<9@N=>CPCA\===>Z@X>:<;V<>@^V7X665\68V665Z86X55b32X10T0/0T-,d+++J.X,*(X'R'\&$$%V#T#!N#V$T"Z$! JRVNXRRZVVVjR` ` J \ LV\d`JXb\P\PbJfVXZZdTZ`f`^T&TZ`VVT`RXTX\XRLPVJ^^VHDTJb^\XZRR^NRRPhPT^`ZHRXf\^fT\D`ZVXfPb`XVVb`^p`RpX^\\\ThXfbfRTZV\`\LXPPbPVXV\T\`Zf@RTj^TVZX\ZXVR\`J`\TP^`Fb^F`PPNT\TRT`R\JfLdX^XVXTT\L^P`VZRVNJRVNXVRTXZbZTXZ^HTZTJ^R^@RZfXVTlZ`\T`f^JZP^TXPjHZ\\XNZfTZV\bdX\V`ZbFXXNHTXTb^R@XRb^djR\JNXRfHXX\``TR\ZXV\VbHVP\XHZRfZPTJ R T \ L b b F ^ d TL Z R`VZRTFPXTPLJVNV#V!P Z P P!\! P#T N#P"""V"V#N%X$F%P&H$&%#&L&)X'^(P&)`)')P'('N')*N*+*R*))&L)-*P)+H,*,*)+^**J+,X,,X./2.R0.P-.-R,Z//P..^.L.^-\-^--,,+b/^-0^.T0H-.1+0,,T,`-,R-Z.+,.00L11V3530T0^0d.-/R/-.-\/b/T0Z.,--.\.D-,,T)b-P..1R0Z/R0P2X5L1625\3V3T/R2^4X30R4X2d1241P416J67R6L689\:J;J9:P;:b::^:?J@^>?Z@@?BVBV@C`BH@CXETEECBBdDDEREBDTFCR@@A@AAA@XA>B\?ZBBNEPGZFPLPH`HVDJCZERGBDT@FDDDXCbF@BPFLA;P=9=;Z>X<9<<98d:P9;T9V:9855P57:5Z7R7:6:X8\6:9:V=N:\;N:9:Z=<;8b=9J886P;:J;D:9<:P:b98N9757V8ZX=X?>Z?P@J@\BRBX@?@>XB?J@?AbCTB@>@B?P@A>`@PBNAAb=T;Z;:<=;Z@?X@==X?N=Z==?X>=A@XB?TB?@AVAB@A@AZBDBTEHBFLIHTJVMLQNNLKVLfIPFJXGRIKTGJIHIHEPHFTCDPDRIBXEGfHGFG`HGEXJVJKLJVCJF\CPD^CCAAZADBZCZBC^@P>\@L?VAh?X@^<=@d;L99==Z=V?X==P>\===:BZ?DPAAPACA`CXCV>?^=>\EC\ADNBA\B\CFjFIXFPGEFIGTGZF^IRHKJGXHIXMLVOVQPVT`UTZOZURSRdQ\PXQQbMZS`OKJNMXL^KI^JIJfIREHPH\FNEI\DCVDJDEDZGEj?@R?Z>`:T::9D<`986\55X52P22^46N2N0^1.H11b01.^//`1V-/L0..T2N/.N.0T.N10h1`21123H2V11d2`32N562Z125b564\4T649Z7\4^5R4X5754^5P779R:<:X8:7:R<8Z=Z>LV@D@?V=;=:;:=X=;D99X:^786P58f7N7T9478\4^334V12Z0`20T1.-++^+P.'X&H&\&%%N&$$T%b#!!"" XZRZV^\\b:\ZLb ^ V ` L H f Z ^ PT^VZXV`LNbTPXZZXPV\V>TbXdP^^R\L`^\R\LTXNTP\d^PRR\PfJPT\ZBVHfVXLTRPbP\VZZf\TPN^ZTfTTVLjP^XTVV`Z``H^T`Z^RTXZb\bNXXZ`ldTTLVZhZXPZXXPNPTV^LLZHfVd\V`dV`ZjZVFVNd^^dX^Vd^XPX\PZ^XN\X^BLfPJbVTRjZ^\^T\\ZPbTZX^^\VXXj\\bhRNJLVRXVVV`fXNN``^R`VTVdZdZdVb\R^\^DdVPXTXH^\`N\^\HXbLNZFLNb`R\XNZPTb``\^XTX`ZRXPZLLT`TVPZJjNVZTTVRJ^RNF^XTPb`ZZXNRLT^jV` \ J T ^ R V ^ R b N d VN^`JNTTL`FZTLh  X"##^#J$" T!`"&#P#<#)V##T&Z&Z'P($&'&(d&'N)(Z)X)X(P*\)((j)N,))'(P+P*f+^,,*T**\+-,*V**Z*`,`--D/N/V-J./-\.`,...-T12T-..*X.X/Z+-^-d.,-0^/1.,\-P+++Z.-+,,.^-R-/V0V1P332114j1/2d0-P-P.`00T0`.1-,^,V/,\,,+,X--\,/Z00/21T3Z2P32R31V312^3h1T2Z2b23d4P23T58b657X98<9\;;^;:\:F:9hLB>@N@XDHBCPCB^GDE^BZEJECRG`EDEFDEBB@dB?@^@AATC`@RBR?AHCDGGG\KGREZFTD^BDDFPGC\E^DBAL@@>Z;R;\<>b=?`?P==<<:;;;;;T;R88Z9:\;:<9:f86N8R;;b8Z<:8X;d7Z7J7:?<>V<;>f:>;T>@NBA\BA@>hB?R<=\?>Z>XB\@@`>ATALBC@HA?9^@R<^<=\?:Z==R=?>P>R?X@J<\>T;T=>J@EJBA@JALAT@B@C`EETBVEGDTEBFGJMVL\K^LN`KLN`JPIFGRGLIGH^JGGdKJHITKHDfEXGPHPFLFLGH`KHTK`IJGIRJMZJVHGNKEPHDJDCDABVCZDDHBLC?>XBVBXA==>X@@=?X?LBT=;^8R;V::==BTAV?@L>^AA?>fAN??Z<>RBAVBFADAdCFbG\HGCEDGZHJNGIJZMLZGKMMOPRSRTTQTSTQP`SQZTRTRSTQRQRPZMXLMKIJ^III\IHhG\GF`GE^G\GGEDDBZC`@N@b@>P;`::HN=<@\?=<^?X=R?@@04/1V1V1^0Z2f0T.N0T0h1,-R.+,V.-^.1^.,,Z.Z--R/,.--/2f435511R2P232N2\2224X3R3^437887<;9N9b;V:9P:b9N;;^>b>\@?\?B\@bA?E\CHNEFjCFDBCXCXBANDEdGJEETC^A`C??bA@RBCA^BJACNCPADEPFTGFD\EbDCED^DTE\CC@VC^ETDfAJB^B@?XBN??R?X;\;>;d:@;\;;RZ=n?=?V@<`=P==R>P==?TA>`?N?b;:F=N<>P<:`A;N;V=>@AR@VF@XCA?X>P@AL>AfA@ARCbARAN??=>X=Z=?>?V>?>=@ALAXCNCTC?VBLAHAbA\DDPHVHVDNFGTIZGNIdKZLKJL`MLKIH\GIGFIFXHHHIKGJH\IFEIVFHHFKTHZLIKNIIHIJJHNKIHLPHXGGPKHFDZEXFVEBBANBTAXAJAAPA>P><@=>F?XARB^>\<^;L;\89;\779P7T637\<^;\8;=@9X:=L;X9J=99\;H8`79::;P>=>X>Z@X@@`@B>??D>f<\>X=LAFAV>@;X@V;R<=>P;`?d<VR XL X h N T R T H  `TVZBTNRVDfHPXTT^HZ\RJLNR^bVV`P`ZZPXT\Z`^F\VX\XRXbR`TVL`JT\^TFZ\hXVN`\ZhT^\VZ^Z\VdXfFXTZ\RLX^RfPPpBjj^`V^TZTN\ZR^X`ZD^ZXZbP`hB@ff`ddbb^hh\\ZbVbT`bZbNbZjRhRdfZ^ZXZTbXj\hTXRV\XbVRN\hlTNVT\hLLVl``Z^NZ\TX`R\V\TLXDTXPVZ``V\VX\^Dbbb\VZLTLVR^T`VDb`H\bXTLTZPNnV`VbZ\`V\PR^PT\XX^PPRdPXVfTVLVNfLZdL\LPXT`NNZ`jTNZ^XbZRF\RZXVV N H X H N X N ^ P ` P T \`J P\dRZPXXhRfVP ` R!P#!X"R#`#F"$R&!X$b%T'\'`&`%%Z&Z('J&()F'\)')P)\)V*d'^))\)J*R+H+*R**L+Z+-b++,`+R-L,F+-,-X+,J+,+,\*V-P-N..R2-\3V0/T0/R2R0T.Z0X0^/b.-b,N,`/N-+X,,d-R0R/01X0R-N,,P-+L+-`-V.V0X-Z..f..\0L1f3X1\230R131R/.N2f/J//^.^/X+.L/j-h.,`-^/0X/N/-.Z/^1.V0\2231R4`7f1\6215J3^336226<5Z7`7R75T;7:\:Z9V:P;T99X:;T>T>V>H@ABABCVCPDBPD`DZGVECERCBLABPFFZGXHVFCAZC>P=?Z>J?ARCBRDBEPDVDCJCGbCCETFRDFVCD^@XCbCZCHBPFZD@=b@AV?=h==9^>T=?@^?H<\=^>L>:>:V=;<@;:N:=9^==P=V==?^ZV==?@>H?XA\@\A@@@R<^;;f<:Z:d=P^?V@=AV@XAAVCA\B@@H>Z>;=Z>\>F=?V=<`A>\?>V>?^?d?bAAP@ATBD@NBBAARDBEFHD\ERGJG\LKHLFLPHJKZLFFFTH^HGTGZJJKVIJHI`EE^BGJIFKIKMBLKJ^HMTMdLJJTIL^HIbHI`IEFD`BD@APBAAVCJC@@>\>V=T@?Z@?Z?==;<<\;<9;P;P;:T:786V87V54Z79P<`9;P=T;R:P;Z:878X9V<9d;<<>Aj?V?J?\>^A?P@>>L?>A@^BBFLCXCGPDEFJKFFLI^LXITMKIJJKKMPPNJQORO^QOTPLP`RTTRU`UXRPROQMMMLVMRKZILZIRMbLHHJVGEhIEJFTGFE\FAJCXBXBD=;<=P>:>V=T@??\@j>X@?=@Z>L=><A^?X?Z@AA`EEBPAZCTEDfFC\EATD^DdEVCVDLEIXERECDA=@?=AhA?bBBVD<@dCZEXCDTFCFZEPHFCETBA\AP?A@DAVBT>N?`B?`<>\;d9;\D?@@`><=@X@P?=><=N?R;;V^<;R:;P=<>D>d>\?Z>>X@=A\A?X>@\=R:X;H:<<:<=T<=<:87R9:8=9TBNA\CADC`??:N;=^:;L:T=X=@;T?NB\BBEBL@NBR@L>AA?f@BBf@@?\?P>=<=\>>NABA@\EPATA@ZA?BNA\BZCNBDLHRJEFFIIfITQTMXKZM^OGGGZFIbKNJGJXILFKRIKIGEEJJJKKOXMZMHZKLMJKJJJbL`IHFIHFTHD^CF@BPB^A\BCV@^CbETA?JB?bA@Z>C<@\?=ZAL>X<>>T=V=>L=>Z<;X=Z;;;:9X8V8R77Z7\8:9=8V=R@V>R@>;T>V9;67627X4R2Z52N4T0/0X0Z/J/\.0V/R0P0`.Z-N-+L./.\20P41Z65234h4Z4P4X43F474533Z4J444f5d6534J5158V3V2f5T6X6Z687b87:\88X<;R;8^::N9R=<>;;>d=T=XCVC=`>@V>b=?\=@V=?=R?=;;N<;=>X?XZ>R?@bCDV@\@^AZ@T>R>@Z?@R>`>=J?\=;<^>?Z=P>=X=\<:j;F;=N>?<>H@<@ A?A@XBAC>=>T;<9R;=N=V=P=Z><`>f?RCZBRBB`BB@j@>?N?<=:`::Z:X;:<^9=>^>>\ACZBFA?CL@?L?X@@bACVAC=>R?<=;Z;R;R>=\=<@X@PCRB??B^A?^CB^BNBbDGbGXDCXEFZFFRILGTJZKIjMIKGJHEHTHPJJHNJKJZFGFVFKRJHNOTKLNPNJKMNFK\QOMPK`K\GHRG^GIXIXIGDRDRBBBN?@TAB\BVCP@AAF?XAA?=>T==d==PB?AT>?@N>;;N>T?Z>9N;;899X9Z9F998N:8:;d;=<9\9T9779:T97<;^<`=;;>h?^>==>LA>FA;T>=?ZABV@LBZDCBFDE`HVIbKZJFJ\LJKVIJVKHJH`JLKRMMQQPPVRXP`RSQRRQZUTUNWQfTRQZS^QSMLJNIJ^IPI^IGGDNIHXG^JPHXHPI\HIBXCBA@PBR>J>d>:887`63L3N34\4\3T10/V1/X0.^0.T0.X0^/,+,0.0H4Z2B3155X34544d64X657Z5\34^34423\67X748b5X7V5\96^66656h8:d67P7T>R=9<?@??B@Z>?;;Z;:8;9\9T9N:9:9`57^45V4N4V75P401/\1/X-`.\.,-f*+J++((X*V*(R'&h&$#\$!#\!b ^!V"TX `ZPXZ^VLZ\\`VJJ D X X P Z R JRPXZRV^XPVJT^LZZb`VlJdlP\ZPRZ^^VRdPhTJlNPh`fZZH\J`NfddZT^bfLTV`\lJbRZ\^NNZNTZfXJRR^ZX\RT\FZVJH`R^NNbVZTRZNTbRPTNH^TXXPX>VRRXV\XZXZXDZh\^\Xjj`db^N`ZTb`VfHVZXZ^RNd\PRXfNR@dTlR^bRlTX\ZdVXRHXVNFdBDfhT\TXFXPJHVZfPXR^^FZXR^TVPfXTf\NX`^PNZjP^VPV\\^VVVdbb`XPbT^HV\bXP^ZZ\LL^PZPPXNPRLRRTJD`RLNVZ\RfVT\VfVVHbVPV^l T < ` V T R P N P \ \ @ b J f Z T   PfZPLRZNLXTVT^X \" ! V"\#J!b"R$""$$$$R$H*P)l(N))**()H)J-*^*V+*h)((f))R+R*(R-R++*+`++-+,,.\--L/X--/0@-P--\.,-+,/L/R.0-,0R1X3.0J3X01/P1/N.,V-N.V..+N,,V,,`,N+R-`++,-L,.-.+-R/^.,-R0P2-.P0N...X0-R./b1V23N/R1^0T,Z.,.1-Z0/Z/J200Z0/\1^./N201`2^4142d33T54N5L66T56^79<:8f997;7LPAZDBBAPAVDDCZDTGEPFFGGEEZENECEPAXDCFNFDCTDTB@BVAZF@HDEElGVBD\DDDD\EDFG\GVCbBRBPABANFCRCAd?B?T<>VA?L>=h=TX=Z>d==;ZA=P\C?@BV@DZCPB>A`>N>??J:P;P:R:;9`;N;T;V>=\;=::=>AE*CZAZ@@@\?J@V@?C?`@VAP?DCV?VD=T=PAD><:@V?R=>Z=?P=H@X>=V<??`B?V?@C@BE\ENGHFPHHHEFRGHIFPJBMJNMIGHJTGZFVJHGDH`FIFZIJXHJGLIZIK\L\MJVMKTKLJLTNZMLMZNNfIXGJJJXHZHNDGNEVEHEFDB>P?@BTDCVCBBC\BPA@V@A\?N?X>Z@@===@@f>:R>:=b>h=b><;8P8V;\:T7N:P:d:V8Z7T8X;;8\;88Z888;L98;R9;;>Z;?A>@Z=\@?>RCX<@P<=R>@N@BBCEFGFTF\JnHLGXHNJXKKZIJIHJJRLXNLQNPOPQMLRNHU`RQBPZTVVUNXHRUR`RXP\RfQPLZKKXMTLJLIHIKGTHNIHKFbJHDE\DAV@XAA?=88;877\6R5N51Z31P/^22/P1..h/X/b-/\,X/L,/10V2f41525L4`4X5J25373`5T3`354L584N3^22T:65Z5764T8544X6Z998Z999Z::;::@\9X9>;J=@Z<:V>=^?N?@X@\?LBT==:d?J=>;<=9R<=H7:;88R8N9V6V5F5\4T6\953Z320022\0+Z/.T-.T+,\*d*T*\,+`+H)V&V$###!X! Z"!P X!^FdXT^R^^JPTL\VVZBhV n ^ T L T Z X^XTXPZf\X^`LPNRLXPTdTLRZV^Z\dZZ^PRLVP\NRTPNN^XR\XPbZBPRT\\^PZ^bJV^TBZXZ\`X\^FHTjXPX\TZ`bZdLh^R^D^\BbfpPTXNLZZJ\JRT`^dLXTXVPB\hbVjVbVZh^dP\`VnbdV^d\JbdZLP\PN\RL\bVT`XX\P`XFhXZ\XVdfVVRV``\Z`L^^X^`V\ZLZPNZ^VRZfDXh\VTTXRHRbLZ\ZZR^\Rb`ZZPRVR``JVLV\\XP\XVNR@H\XRLf^bVHRPVVZF^^ZDRXZTZXVbX\PJVXVT\XVPf\`RJP\R\ R j L ` Z b d h T Z ^ X Z ^ X \ XX RZRfZF\P\XZXXXRHbbN T"P!T#"X#Z###T#Z#X%%$Z&\&L)'B)L**)(+--*^+)b*:+X*'P,L*V+*V-)J,b+R+b-+*T,^**\,../N-.Z/-L//J-/V./.`-X,H+^+--T/T-\-`/Z.L.N2-0Z/l1X/R.P0R.^,,f-,L,X+-+++,-^,*\,+V)-F-X-b-P./..0/,.H-/V-N,\.Z//Z-.V2.N1^1L/.T2.+../.T.R210001.b0V./T0T2N0\1H22J4X45^544Z4V76`5`7N6\9H;`9H9\:T;D:P9P::Z<^9P9d=V=h?X?VDhETAXECACDF^HEIPHVHXHF`DHFRFhGPCTChACACDNFDZALDAHFDDfFECDFEHBFZHZELCVEC`DNDBBNBA@CBVDAAXAZDL?@@NA@X@B><`CA@A^BBBVCDRB@^BBV@^C@^B?>=?b?=?@@T@=P=N?X9\?;N;L>j;=>>T>>AP@VABADCNET?\@>h@>=R:?j;@?dAb@T@\=;;\=R<`<;`9V>;L>L<^=;>?=T??A?AJ@^?^@>>X?V@J?N?@>>H=P?\B^@>@EBVAB@A??>JA\@APAX@TC=R>>>;<`?<<=J<@A=^>?=>X>Z?>@>T?X?AVCXCREXDRG^GTFdFF\ILGNF^HTGKVIDLNIHPJHdKIHFfEDFZKGGHGVJEEGLHXIZKJJXKRKLZKXNPXN^PbLMMJOKZLKLVJRJXGJJNFVKEPCBRCXCN@BAdCBBJCBATD@XDDRB@@?>`=b?>VD>=;=:<;:^:;:F;:J;9:V:V<:R:R?<>A>\>ZAV?=N>?V<<>DA=?AAJFdEE\HHFHLFJHJJdITIZHHLjHhMJKZKNKXQ`NTOXOZMXQRQP\RTDSTUT^TbTSXTTTQRTRXORNJL^LKXKGMI`FGTIFHJJIXJJdHCBBXB@^>dB<=V><\;8X7R986^6X4X44V3d2Z2N12R4T3T0/1X.H-P,\-X-X0J/f3J2Z03P02\4R4434P64Z5J46X45b6V3^6732^33J5b4N9^7H3Z6H89T:9X93^85V88V798:X;T:79<;V>T@;^?;;?BAZ>L>:T@;:9^;;8\9:d778:677467T75635Z22/2/L-P/.L,-R..**J+`-+\,'%%R%%V$"T"!\!Z XNbXLZRPXDV R N X P ^ ` T X ^ ^  \VV\V\bNl`LlPX`jJLDRXHbJVZHXP`ZPdLPR^X\V^\`\`dbLXP`Jb^^^dXfTd^ZRPVbb\H`bNXVLVVT^\Vb\TZfF^bV\VVd^bZ`fX`PXZTZRTXLbHNNZTN\HPhj\X\ddN^RbXLj\\LbTX\TTTZVf` VfbTVZXfdXRXfTZf`X`FV^fdX\VTZP\T\\`dP`^\\PfTTZd^\T^P`b\DTXPT\VVPZXbPP\X\FX^N\XT`^Z\NR<NbTZXVVjFPL^TPNdNZNBhHVbFN\VFJFTXXRRP\FXR^\R^NJPX^\HPHTZ ^ X ^ ^ T N T \ V P d HN NhVdX\RZ^N\`RVVZ\^N \ Z!N!! T!"$N!V""!#X&%$%%(P(()V))V*+f*.\,+b+N,*,T*`*R)V*,+R+**+T,,P),,b++,R/.X.0V0-X1.T2L.0---/^-T/--/b,/\/P/X3`//^/.b1..V/.V,/Z.V-T-*-,`,*\,Z.+f+R)V,.V-R-X/.,1.,-T-X+^**N)V,,^-X,,0J/\1/^1L10300T0-R.-.R0/b.T02/d/L0R.1/0.2H1b43^3V66d4T65\746P3J6`8N:X8:7^:8;;9ZX:X;H<\>B?^ABFEGD\FE^EGLEJJIXF^GG\GFZDERC`CCbBDNDCZDBCDE@FEFCChITFGGEFNGEZCD@BPBXBTAARAABVA\D?A@?L>=@ZBC?\?^?=V>=BB=@\C?H@>XBd>AA@CNFTBBCBTB>R@V@RAbBR??b>D=R>=RB>H@?Z>T=b=;;>T<\?==@A@@@CDZCBB@\?AZ=?>?^@TBXDA>l?VAR<^>`;Z=:\<;@>R>\A?C>TA?ZBVCNCAZ?@XCT?@P@F=?T=\?R>A=?=AT?P@BRA`BRBXADEB\B@@N?\@?R?d?\>b<=Z<>V@J?h=<D?<X;Z@R>T@^ADXD^FbFHVHFHHGHPHLILK\IJJNNTN^KNNPMURPRURSRPQ`UWZVRUSXUVRJPRNMN`LMDLTLFLPHHVGGTJJKKIZLJXHLGEEB@BA@>R><>;8;D8T69J8\8T655T42L2P0^121h1b2-N//./0\0R2V4L3\4^22444P677R54Z3L4613R415X34L54T6T6P657656Z9b7V96696P9^9L<9R77;P::=9;;ZN<>Tl`Tb^PNThZVFNXZ L X h V f X TV` \VTZX\\L`L\L\LNdTbXbV !R "T!"T "!Z"R$Z#"^"R%%$V(b(&D)L((^*`+J(*.X/,,V++N,T/N,,R+P*b)-X+R-X)(*,+))H+++^.-020-X./../J0V21X.Z-0\10T-/-..Z/`2-T0T0L,.V.-X--/-P,-/V.P-F,\,-N+L.b(*P+P++N--^/+^/--T/1.b++(*X,,^0*b-,V//X11\20Z4R2^2X//-//\/2\0V/3X0\4-1\.^2131N6b3T4\8L4H5\7R65Z8R7h94R6T88N9`:J>P8R=:T<\>:<\\ABPEZ@NDA@=@@@=@@\ARD`@@AAZCZCJD@CVFXBNE@A@>>Z>?T@V?PC=^B<>V;J?==\=V@T>N>?V>@ZA?P@RAVBCCXBBA@??\A\=@?X@@RC`?>><<=>=^?=F>>b>=BPAABAAd>?><@X<\<;@?>=NT?J>=V;V>?ATCAB\CPCbDDGDRCNEGlFLGVJKFPKGVKJHFIZFFGfG^HGHXJ^GVIXHHBITHDLVJLJ`NHNMXNNKVOPJLJDMKfKLLKLHILM`IGXIRDC@AEDFDD`DCRCZCRDN@`EA@V?TAT?=`=V?>V>=T:;;=<^;;9>V99L::97H;997L;88X8T7P86:d9:X>98;d88<87^799T<^:9J<==N@N=@\RB@?=P?\@:=?\;<:\;9b=>;R;P97:795667H76X6P65Z352R23V00P-./.\/R--Z-P+f+.N),L(Z&h%b&#L$#\$X"R"N V X VZ^PPTXLV^XbDZ`LZ D ^ N R ^ R ` RPf TXRVRXRXZTdVNVXbhbHhVTbNRXT\\`RdR^TRV`RVH\VVdZVVRT`^f\`T\^XR^Tn^d^VZfbZXXXRVRN\P\bPPVRRV\Zdb\`l\PTZTZ`\LTVZX`ZV^`LZTN\RXPV`\VJ`XZVHPLhRbXZ^ZdfbdRZh`ZJHZ`bb`TZ\PZ`^T\nTXLbRbVP`VNh\Z\TX^\TLZ\PVNLRPZZR^bH^X^LbPVVdZ^NbRTXXTT^T\TXXdPXLX\^VdXJTT^RVVVjJ\@LT^bZ\JLTZDlbXZ^X^H\^fN`^RBP\RJ<h`VV`bPJNTPNZRVRXLJ^ZT\NXR^`T X R T Z ` R J \  VNdZ\Z\ZVH^`T^X^X b L!\!! F#"h$P"V!Z#L&V$"T$R&('T&'T*N+)Z-*h*T+V-.,,P-.,R,V+Z.,+T,,,)+-R-b+F,P,*H+*.//.T././P.T./R40.0\/-^4V10/0/0T0/X0/J1Z.^-f.P//.P..\-T-T.P+J0R./+^+,*X,*\,+Z.V-^/.X/R/V.N1d/.*))T*R(\*,--,V/V.P/R01V1/V/F/-`1.T/X/.0/\1>5Z22V/L0J2b132X53B3Z3J5Z7f7777678N85P7X9=d?V>X=?==\ARBRACCGNFZECRFZFFHFI\HPJHFFVFdCHEADTCCENEACDGE\JGGEPF\FfHDND\EZJ^DXD@ACABFA?@?PCNABBT@Z@DD?A>4AN@AR@A?A@XCF?A^BAFBf?>hA`CLEDA^BBCCVDHAT@A??\<>BCXBR@=ZT>?`CABZCEVGDHCTDbC>T=N=>@ZAAh@P?@::\;V@d;X9:==X===?TB\@dADZBCTEdCDECDAFCA@=Z@?=^=R=>>?@?X=?=V>\=R@`@V???ZA@?^A@TA>>J@=N<>=j=<>Z:;`;R?=?b=R>?=?>>?V@?B?P>hCPE^EPCDEDJF^CFJFGHHGGVFNFdIIdKIJG^DEPHCGITJTJJL^HMIHTINH\IRIZOXL\NROVNNRJLKMNJINRKLJKVM^NV?AN@@X==;<>X=;L<;:^R:X:<;:V=X>@V>N=;`:V;;V8V4Z4X657X3V4L4N30Z3X0`1X0L02^12V4R5^1Z353H33Z1P152L5P453324`36`4B3`3V2314f65T5655Z655L8`6R65V8X<7:8:8N:9N>T=;:;T:X>;`;9d=VAT>=X?b@AV;X=989>Z<=^:;=;:<`8:776^7T6\5b9X7Z;8757553\20Z3X00T///Z1`0T-,-+T+V'V&('%$\'j$""#`"!^ !Z f`XTZ\ZX``VT\ \ N Z R ^ P P T X X PX ^R@ TdJJ\FT\LPLN^Hb^``PfPbXFPZVTT^RLVNPXT`fTP`PNXLZhLTPLX\VHdVZNdZZ^\PXHfJR^LPZ\XVV^HPVTZXZZZnXVLTZZ>ZZ\fRPTVRVZHZPR^VVNTJ`T`p^Zb\\`\fVZr`NbL^hZXhZTVdR`fV^`PZ\ZX`TXn^^V`\XZVZdZN\Z`J\\THb`Z0fPZXTjTRdNZV^VZR\XXXNd\XVPNXLTVT\VVjbf`NV\`X`TRLZhNd^P`db`ZJP\PZVT^ZN^`TZ^TXP^ZPLVZ^NJZV\PTVXPVpZDnXVXNTFV`^X P Z V  ^ \ X P ` H ^ d  \ VZRRZXP^R !"X"T"^"""#T#P$Z"$$%J#P$%')J(\*`*P+V)R+P+b,\*-^2^,,,.-,X,)V*X/T-+*V*(d+\*X,Z,L),++-/.^/-,Z/,H..1.\1.3/V1201N2/.R1l1/0P2V20R.j0d/L0R-H/-/-\.L1-Z/J-+Z-++P-*(\+X/-/0,\-T/`+,T-+P*Z*(X*Z+.,,+,R-/^0R0d//X0`1V/J020.^01\1X0X2R0R/1R1T1P2f2Z3l345J34F55\576X:R7576b9>:b:N;X:b:;X=>N??=BXARAF??CBDCCXHZFICZG`DD^F\IZI\DDDZF\CPEEpCEJFDC\B^FCXDbHGFTJIGZEdFXDVGDEDC^FDPFBdE`=^?`@b@?VAbBDDXA@ZBB^A?ZC@>??ACTAVAR>@TB`@@BR@`EB^BFCAF`@ECRDDA?\ABJ@CPCVA@HBV@X:=Z<:>@Z=>?\=A=X?=`>R@L@TDAVC`CD\DEGRCAC`?JA@R>\AXC>=?==F;;^;><=T==Z=`??@?\@RDAAFCDXB\CB^BBTDAJARA=T?VBb?L@A@XA\@T?;:X<;;H?R>XB@\?TBXARA>ZA@?hB?R?<<`;L=\>V??=>;J=f=;T=^=N?=:L=N;=?>A@D\C^BADBD\CDEETGVFVFIGPHGVGFKHIJ`IPGXGJGGIVHLRGFdIXK^KIRKbLK^L\INNJMMKNOHVH\JTJ\MMMIIITHITJ`IKLFFDEEEDF\FXEXGF^FVCEHDZBCZERDA?N@>?=D?>?>=R;V>?=P99X:^;9T:9\;L;`:P9V<9:F8<`:R85988\:R8Z7N:d;:=X;?P>??Z9V<\\?X=\:<:;?=@=X?Z<;`;<:=>Z=ZX^PLPVR`HZPLNPNZPZLJbTRRN`DXJVbX`PL\FJLBRVZZdhPX`V\\LLZZP\\\`XLXZdPXXVPR\RLVb^Z`bLHPZ\TR^Z^VXPX  ^ H V P Z X N T T F T \ N  ZPR^LVJRT^XXTT``PZ\Db!X ^##V!T"d#N#V"#b#%#f&%(D'\'^*(T*X*L)*+-^-*^/D--,R.+,L.R+*/-.L/H+N+R,*++V+*R,^)T-+P-.d/X,^/Z1V.V-T00N1Z1Z0b0/3b2/200/..T0J1T0\1/0.T/J0T.-\.X0R/X1-R0/T0L-d+Z,Z+*R*T-)R,--X,P,.F--`,,+)()*N-T,*+N,\-\/T0.\/.\2T//R02f/N/V1/3Z3d432//0221P1`444Z54T5Z78f6V678Z8b77\;d=9P:=V:;:^@R@`B<=bBFBT=PA?BRERCDFG\CG\FVDHJHGHDFFCDDChCCNHEDEC`EfDRCEXEFVFZJGJGNGHTCnDDAVDECDBLCfCZ@V?=^AA@ZCAVAB@XCA>`DCA?CRB\CFACB@ZBA`BPE@R@AC@ATAJ@TA`E@HARCP?^C@LC@@XDJCL@?>\=V=P;;\=L>>?=d@?NCA@P@?\>N>A^@D^?\@CDZCTFZDAZ@\?@ABBRA@\AT?===Z=Z;^=V>=j>=\?^AL>BR@FRB@CTBRDZBfF^AALD@P>dCP>H@@X=TCJF^B\DAXBF@@?R==Z;P:T==>@=<=?T?@NA=>f>>>Z?=T<;V<=@\?R;T:;Z<>b=>HA`@@TCVDEVCXCFFNEZEGCETFXG`EHZFFFVHHRGVIGFDE\FJGRJXJPJNKVIHTLM`LOZMXKRKVNXNdOTN`LJIGZIZJLLNIXILJHGZH^GGIPJJJPGF\EPE\H^FfGCGLFDDJCZDJA@DERD?LBAC`@=@P>d>V??<;b;=T?:b99;`:8<:9J88Z9R:978P9;=P9T;:VD?AAECCRDFEZFRHTIHJZGVKTLHJ`JK\JHNNQPRPQNSTUVU\TVWNUdUURU\TVV\WTRRSZSTQMMFNOOZONQ\OHONKJTKVN\MLXMMTKTLGEEFPBLCAL?ZACATC?R>J;Z<=:\<\:F9\8X7T4X846T333T73\52X1Z5J4^7\95664V2R53j6T3X23T1V6Z22L2151N2f4F130H1N4\53V5\466P4l45`65N7R4657779N79:R7b:Z=:<9:9\:;V>X?A=T><\=Z-d//d.V/.V.1R./T0`21N400///^2d0J/\0-./B0-.d1R.0^-T00.0T/T/L.,,+Z++P,-`++Z.X-R-0T+L-*`/++T,Z,+R+Z,+,+F,-,L0b1.^0/X/.2T0T/L/^//^20P221Z4043d42X44N5\66547^46R77:X9h7\8;Z:::T<:b<>>=\@BDBC\?@ZDBNB\DTCECTLFIVG`GVJEKHDTFNDEDVEBJFETG\GRDFVE^H^HVJHGNJRGIGG^FFJETGVEEGTD\B@X@Z?b@>?ACEXEAA^DD@LBZEEHCE\CREDDEbCAARCA@XEH@`@ABFAL@AA@ANDXBB@@^@B`BAADRAb>P=><=<@BR?@C@>L@>=TAZ@TCZBPBB\@ND?@ZCPAC\AAV?C=`A\<;H<;X;T?>=V?^@N@J?@BBFCXBDVA\CZDBFXCP>@d>PAAZ@>B?AATBVC@HAAPBP=V==b<=T??F=<=\><=^?J=RBb>R>P=>>>X=X`=>:X=<==VA\=A@bAJ?BVBBNB^ECXDCXCXE^FDbHXF^HGCHDFXHHFGHEFFGRKPI^KK^JNHKMRJXLPLRKMOLMbNXIHGJH\KLTMJXKTHTHHGXHHTJVGIPGZH`JXJXHH^IXEZDdCDFBC^GCCRBXBPC@`BZ@>>?Z@LA=Z:P:T=;N>;N@>T?P=Z=^:P9;;H@V:X<9T:T:R:::\:`;9T;:9N9T9<9;`:P<;\;>V;X?@@CbDTCfD\EGGLIZNJ\JNHJKLOHKLNRVP\QR\SbXRTYTXVWVUUXUXVRPWXTbPTRJRNTPNQON`PNXMLNTKRMLMO\OBOZMLRIVFFFjDPDAZERECTAAP@T?=^5V633V6T7\6554334J4b2X7V6X5H2h2T2H4L3^0L1\31X1/.X3J3443Z532X44f465467F7`79787N79X998N;7:9;>@^>9^:L=;Z==Z@==TV\\PZXlPdD`bLVXDZV^^TXHZRHZXTHf^XbT^T\fH\JdPXPNd^Z\hVZ\^NbN ^ ^ R T ^ V P R X X X J L ^ PLHZNZZXfRDXbXTFZ!!H!#$j$%P&#R%J%V%R(%)&d)Z)X)(,V)*+`/V-b.-+X/*,V.\.,++-0^0-.b.X,N.N++*^+J--X/R.V.-`,\,/X0-+X,/./X1X/30X2X4L000`1V101^01L0T..,P1.R.,T.0.P./T0`0^/\.N,,L.P-/+N*+V/V/0-d--X,,+`-b+*X,R*+-/.V.-d/-X-/^.,.\-Z/X1.X.P//N/003Z3D6Z2d022Z133423T3b7T6P689`7788R88X:F??BPB\D@C\@BP@AREC^ETGFCHDFGJJHPEZCDC`BETFBPEHDEGNGEJDLFHbHRHbGXMHLHDXGE\EPCRDLCVCBB^ARA\BR=J@V>F@?V?AEPF@ZBPAhBZDB^CEFTDGTDbC^BZBCfABJBRDAVDA?CTD@DCCAPBB@^ARDBbDBX?AHA>h?X=;;V?9@@@??=L?A@BCVDXAAX?BN?JATA@ClAJB@BA??AbBCNAZ@H?;P>>`<:;;;?^AZ>?^B?BP@BRECELEFDCDCXA?RA?=A?>?@R@@PBAANA^?RA@?<\@;@X?@P?f?H@>R??v:=V=f7F:b>ATA@BfCVGFDACANEEEVEHEEbGRGEKEEFGJFZGhKHJKPOJ>`<9X>>N;`?@=h;P>=>>@?@;TL>@?BAFZDDIFJK\MFZI\HRGJXIXNLQPMTPTSUVSTRVWbVVVTXYVVUTPR^TTPRPSQPLSRPQZTOPHP^PP\P^PONKRN`MIXFTEHGNEZHREZFCAGLCVBA>=V@\97Z8797V67T576`4P5V742446P558T6D5X6N1X211Z13V4Z0X032L/`2.0L1T2\/P2321L2d34H2`2Z243\577`8V8T:V9V:74R:6988V;T8V;:=:j=\;:V:9T>R@>@J><>V==7X<;Z=X::T9Z88R979X8P88643\2L5N5123`13T1X1`0-/T,*J*\+\)Z*T'f(N&'(X%P"\$$X%#"Z"L ^ b!^J\\XXZVVZ F X L R N P ^ T R NT RPJRFXVVXXVZJX\XR^^TPJ`\\`NX^^RJ`VV^RZ^FRVhX`XRTZXNbLf^`N^^FXdTH^^BdVXd\bVXZbdTT^ZZbXb\XV^b>^`XbRB\VPJZbRTVhNV\fLZJ^VbbT`TjldVhpbhXhRPbTZV\jn^dfVXRXfNTTXHR\TRVXX^ZT\NN`L\P^d`^L`\VLfF`Z`V^fXPf\TRhJb`fZJLd\RT`FfNZfRX\jPfXJ`RPdTV\bV^b\JXX^`b`ZV\lZX\^NNjTZR\\TZT\\VTX\^^RXPPR^`T^RLNNh\ \ P  P P Z Z T \ d HXRHJT`\NXTRLH^ !T"^"F"#P&Z%&%&T&V'&N'&('T)*)++,`-X+.\/V-R,-T,+T,Z+/Z,P-,+,X,H.\-X,P,,++P+V.+N-.+/,P/,+V-1X./T1/d01Z0`2J2111N2.R0`0T5d/.^//P2.Z/R/Z+10+-//f.,Z/--V,+)+N-Z0,\/.>-`,X-T,+R+Z++*N+++.P.\.R/T/..,-V.-/-T-T00D0./P0b/Z222\00`3R4^33V6^3N3R45^5559757R8F8F:R89\9:R:b99:;;<=AT?\@CZDEDDJBBBCXEHVB^DTFHCGGFPFTEfHXE\CDBEdDEFDFXIZFNHZJGTJTIXJJLJZLIVKFTIDJGbDPD\EXABBP?A@?V@NA@AD`@A@NCBXFTEDLC^DXBBG@RHXDTA@V@GEbCTCEAAB@R@@TB`CZAJ@JC?V@RBARHX@CAA@<@;V=:X:^?VARABCNC\A@JC`CDB@AZ@A>RBXC@CBHC\BT@\>=AR?>?>`AN==Z;`;P:9;ZR@>\=d@XBBCCFEDfEEDJED?AT?>D?P@J?BH?Z>A@C^@?P?=`?B=X@^==T==BNAVA@T>\>?=^?A?X??=R>::;===>d<9B>=d;<=\<:::P\@RCNDNC^ERIfFBDDCJD`FZFI^EEGBB=ZB^V?V>Z@>f@>>=VV9Z;<^;X98;:P:TV>L>A@NCVC`FFVJVF`JHJFBEJ^LRJLLTLNR^RQQT^SUXYXTNTUTVTT\VUVSTZRRSOORORPTQXN\RPQM\PXRRVOOXNNNNIIPIHF`FXGDDGZBHDD??`?=\<;:R<8L9`8Z49N7Z787:55446T55Z5V3N6V8V463P6d0T4\144Z11..V0./^1N011113J54731V0`4N3Z7R3\4775X8Z6X9Z:J6b8V8V7\8:V:`;9\PZ``PZLXFRTVPXZNRTTPTZbZP`RbTNVV^RdR\Z^NVN`VPjLbN\XZP`V\XZbX^^RVNRL\XNVZP`RTPZNVT`\dfhVbZVR`fZ^f`Z\X^NVZVNX\XhL`R\HffXT\f^JL\X\XfLTX\R^^bRZNV`J`h^HTT\R@NdJ\VZbB^XZRDXTVPLLjLdVRNVTPRL\LZNTVL`PdJbVj\`XP^\TLRTPPXb`^NTP`JB^LVPVXXVVZNRDV\V\RR\NRXTfZRR`JRZNLZ^ R V N T L  T P P V V T ZRLPbTXVP`bLbNTJXP FZ!Z"T"$X$^&%#N'\&%%T()R'F*\(R-P*')++T+B+-L.^..R*-*.R-R.,---0\-N-X.,T-`-Z.+-X0*X,N--h/-b+V,/P,,R00X0.-2`/V1Z01\420P0222V2P/3X/Z.X.X-V0d/b.L--.V/.--Z-/R/.,T.J,Z,-/,V0+f,P/Z,--)+)P+X+T-R.N/-,X.d-V.V.Z-b/--V-./.`////`2V0d0H21T4T1N4^643J4`46V5R3V9Z:6^6Z64P68J;Z=J>>??CNB^BXBBB\D?RA@DBPEGJG\GVEDbCRCCHCDbDJETBZCFAB\BT@BBPBRB@J>@d@ZCCEBPFAA??hA;N>;?A?VAHCEFTB?fCDBVCB?@PAL@AR>@AAT??X??R@TB@R@?`B=;H?h:L=T<::;R>X>T@??BN@ZAXCC@?@CFLBRA>VD@A?Af?J@?V@@NB?bC\?R==Df;>?T@>PA@==>L?V==V@AR=H>R>=>R?H@>b=J?N??<;:J<89Z<=>=;=;N<^=T<9b;N:<<^>\?;=J>V>CGZFHHLHJJNJE\MEHHRHJNLKNTKNR\NZRbOVVRRSZVJTSPTXVURXLR^VRSTVZXVUPR`PZORO`SJPTO`TPSNVSPPOXQZRPPQZRHOZNKKJIIHNFNIEEPETDdCTBRB\AN??;T;<==X:8\:X;;:b<87T7b9`664T:6b75V56d6R5.0/^./B,--`*L,Z+V+'(L)Z)X(h&'T&T##P%^#&Z#$V$"T \ZR`VTVdZVXZfP X R V V d ` J ` T R V X X BJFbPfRR`Z^XLdXRZ\RVR\PdN\BZ^TZJXXRVVdf^XXPRTb^XXRXRNL\LRZV^VNTZTV\ZRRVbfFTRXNVL^`XTVZNXb^RZVZVTVX\B\TH^`bRNRPbThbhfZX``Nb\Rbbf\Z^\tfbXN````XXbbdP^b^TVbVP`\ZVZX\NZ^VXJR`TTV`ZTP^`T`^XJPfRLbXd\V\ZdRVbXX\XNXXVFVTTZRTH`TRTjRZdN`RV\R^B`dRpZT^R`\B^ZVNZd^VRVR^TZXXZXPVT`VH\T^RZRP\TPPZRN`F\L`FL`\RZZ ^ ` ^ J Z V X \ N P R X PFZ\ZT^V`TJXdXVPXZ H R X!T!V#`!V%L$\(^&R'%&X'P%R(^(^*f'X)+*D-V+P-V,b,.+Z-Z,-F,.\.B,*,0/,0.P1T.@/./-,V-X,,.1R.\0P.N-T-T.N./d21/01T3.0d3\1\0//.R.P1T11.P1N0,V.^1...-J.^2N/-,P/,--.-,-Z..Z0d1b-X.^.+.Z,*Z*,+V,N**,-l/,X.-.F/F-\/+N-,F+-/P11b0/1110142V32\3Z4T34Z5V5R3b6N66899D9X9T<897:;:H;::J;R;`?HA@@@APDVFFBCGXCDBCEC`B^F\BGNHTIFdFLDECAFRDZEGE`HVEVFJGXFXIPGTKFEdEVINGFGGHCFEECCBBRAAd>??@L>=R=^B`@N@PDDDDElC@XCDB@BJBPBX@CLBNBCB\BVBXA?V?>??^BZA?<\;V9j;V9::;V<\<=>?V?R@?BX@@B>Z>>A@@@b@ZALE?VA\A>RAAV@BAB?VAR>X>@Z>L;R>V>Z>@`?>@`>=d?>;h=?V@>^@>9\;T8Z9Z<;=>===<`?>^@==<^\Z>P=T=?^?<<>??>N<\BZC^??=L<\==N=b9;<::R;=::;;9V:<`;T>@P=CREDNILIGFPIHHGGGI`FXL\HPMZNQ`NRN\Q`SVQ\SSVVVTVThYUVUX\SDSdUHSLR^USdOVRONRNPORQSXRPXQJPVRNPONLMKJJLHZHJGG\FbFTD@NAPB=XB@<>T9:\=L98869^988:X6\45b55L5N57N7R5P5T444`112f1/0V0--.Z0T..X01/00L214N62P3`24\5`4b6^4V863866Z6^76T2;\8V8^79V9<9Z:P:=:R@PB>>HAX=T>?`=L=R<<;V<@V987;Z8V98\7T8^6^8L7F775X6312R/2L1^.)Z+X+V-F+-L+T*)P*J+'''`&$$"$^$F$!"P"X !LJVNbVNVLXZ T  JL ` ` ` D ` H R D N VjJbVPTP\^BXb`X`XNZVPdX^`Vj`JdJ\Z\.NJP`VVXL\`\VTX\VNTp\\XXZVbl\bL\\FfT\\ZLR\bT\nBX^ZZRTR\XnN\XXR`T`X^X`ZPJX`Zd\VZTb\RTPNb`XZ^nJZ`d\\dbVbdX^`RThP^p\:RTdTXH`V^XTXNP\dVRV`XXVRT`XXR^LbR^T`PHdPRV^fV^bFV\NN``Xf`R\^TX^`ZPVVTbFTTlTJZLhZTHTH`TdNZT\\Z^\\^bVZZJR^ZXd`V`HhP\N\H^dLfHXVH`TTVNP^N\RT^F`LV^RXP\TNVZLRVH T ` \ Z V P Z T  \\J\ZZXNXZRLRXZTVB ^# "R"%%N%R&&X'N'*''V,(,4.),+,V*V-F,.N/-0`.N/.R0,/./\-Z.b.,P-V+V.Z.+..-R/-/X00Z..-+T-\.Z/\0010L3/d1H00X.L3X11X//T.d12V/1./f.0h0*X--X.,-,.X/.1P.X,L.R.--`0V1,R-`,R+*R,-,.+R+*,,V+/X/b.,,\-T/-,T.+\.\.T.F0/2^/H0Z01T214T441X2^3H4F4466R887P9R8X9;:Z;`DRBZD@VEAVC?@>P?>TBXATFBVBRDBTDCEFXGNGXHIDTFFXDB\CACEZBCLBLCAAZBZCHAAdGABZBECC^FZC?NBBAT?B@?`A?@EbCFF\FCVDADATA`FB@@dAP@T>V?^?@ZATBA?DHBAT@RABZ@>>P=>L;Z;JBT??P@X@APCC@TA==>@>>Z@H?dATABZ@PBAfCCADLB@BRB@@Ad=V>>`><=L>P?`==>>>;^<<;;X;PAT@\=@P?=>><`>V>dAT??\>>?BC\BRDAbABFAG@CfEDFZDPBRFRFFDCZCDDFHJGFFIVIVGPKFVJIZMMLZOVNbRHOVPKdJnJHFlHIJPHHbIFIGDGPG^LKP`LPLFLIHPHMVGJJHHITIIKVIZGGJJGVGHVFNFDCBEVDGfEJBBBB@RA\@X>TA?=TC=;L><\:9H:8:R>Z;==L<V;<;;9Z>D?\?X@L?ZADDGEFEENFPG`ELEDFG\ILTKJZLMQPXTUQT`UPLRhURTZX`TU^VTZVZWV^OZQVS^PQbTPNSPVQRRPhR\QTORPQNK`MM\MRLVITE`HEBDCAfB?^??=L@R;:d<\;H=9@88N8Z7V9P6Z9R7N7335795575^63V4J313X3V0V/T/D0.\-P0/Z/11V3X.h3X14X3N12L5`63T673L4\8Z7`86R7T566D7457798h9R8X<<;T;;9\?<<\R==;?R=?B<>P;<9P>;8V97R69664T65R:695722`11^0../-^+\--+J*V**d)*N'b($^&R%\%$#T$J$P$X#"hRLV\RRX`FfT`hX\ ` F D T ` T R\VP\\ZNZRPH\XZVPFRRXTfZ\HXVFV^^PTPfbZP`Zb^J`L`VXRXb\^PR\XTRX^^VZLJ`\ZXVVd^^H\ZjJ^`V^b`VPbTbHZHVRXXjZLXVRJZ`RJZZNb^PbPTdX\XRbVRVVRT`dT^R^b\N\dh^ZZh\j^\jdfd`\ZNfTZVf^ZXXRX^bNLhXV`V\H```hH`ZfZRNR^N\Z\bVPF`X`XNPdVRRVZfXJPRXRNP^NTZTZZTZT>`ZdZTR^XV^VRDJ\P`Xj^TXZXLNZ^ZLbXZ^JVPJ R  ` T V X ^ \ X F R N ^ZJZZh`VZbTR""N#f!"X%$`&R'%&T''X*(()T*,Z*(^)-*R+/`,P+/R.-.-,`-d/V.T/1../.V,L.-J/0T/J//00/V1V0.^.R0\,.N/\0X3`2201`.V/b1R/\112/-h2Z0^12Z5Z/`1-`01/L/H-/X/T..\0X--,b/R-T0V.N/T.-.^-/R,+N-,Z-++^*d*V+,*N,,V,Z,Z//`/.-/,.-B,X/X,N/2X2\0Z0V1X3^34432\5435`626d5^75B7l8`;8;^::d<;H>\:;=Z:X?\AC`DTBDVDXDEDHH^FDCHVEECATAABTBAABB@LDCAAC`BBBDDVCE\FFBC\AC@?AA@XACAJCDFXF`EDBBPAA`FPCAANBARAR?>N>ETCFEPATFAAPAZBC@BN@^=f;=b;V=V<>:<^?@DRAD@AZ>J=Z==F>==^@ZCZ@D=\>?CVCBX@C?>?APB@Aj@P>B\<>J>`@X@=?VAX=>=^>R?TB=X><:f9>P=F;\>?<@>?d=^<;TA>X>@@>>`=`=>>T@?B@R==>>XEPC\?A>PC\?ADBVCTEDFCC`EVIZEFZEDHD^CTGGZHGJRIdLfIIZOTNNLLLOOORQPLNKGXGFG\LIRJGHPFHVIHMLdOKPOJZIXNLPMRJKN\OGXI\HJVLJI`LJKHGVGNHJFHGTJEDCVCCJBXCXCPD?@?>>@`AGjCCAZC?@R=P>T>=;;:=\=<<@=<>b==?d?ANEDTF`EHDFTBG\EBCDDDFETLPJXKONPVRPPXSRRQTVPYXYNXdYVVUSRVUTTQTQTQSNT\SQRPRfWUJRSJVQRPQNNNTMJL\LJPHTGLIZEFTAZ@P?\AVA@;:9L1T22H422`5T44266Z645V7J4`66R85B5457b7X9T;9^;\7;=9=T:J;\<<<;=`X=Z;>89R:7H3677V5V69`9\88742B/^2/N/-,Z..f-.-N*d0-)\))(&$&T&`$%N##"X$N R RLPZZTL^\V\VNJTN^^db X R V Z T H Pb\\PT`\RRb^XRVX\^LbX\R^VZRFT\V\d`P`VdRZR\^^Z`NRXP\RT`VVX^h`hX\j`Vf^TPDTTXZR^TVXb^VRXbR^VX^FbRT\X`dPX^XRLRVbXJbZ\XT\VfTh\`ZP\bhfT\NTXffPZR^XbTHh^XT`^RNVNVX`LT\bTZPd\Z\NPFjJPPHRTV`\\VVX`PPLXJTbZJ^HVRRPTVX\Tb\TfH^NRPXTRHTZZLVX\T\X^hVVJNVR@`VPXNXT`TNFjXB\NVNNXPRbVPZZhTdJZRVh\Rb\`PXNXZTHfZV^`Vd^fRZNNdHbH\ Z T Z J Z F ` X X R T L N \ ZbXZ^H0`ZXZZVRTP!P "Z""#$'%'&%'V&'V)\*)X+,@+L,T.\,/>./,N,Z/-/h-2.0T1T-D/.\-,X+0P1/Z..Z/N0/b-Z.V/0/T/,X/0^*^/\0N.Z2X01N42V/F.0X10\.X/L/.L0N302b01V3/.`.L/.^/.0H0^0B.-V.--\-1T/.//-\.R.,*R+.f.-b+J.\+^++*b(`+*H.Z,+D+L,R/P,b,-R.T.--R.//032X32T2P3031Z123d8J6`44H6^8X;<;\:`;8Z<\BCAACHEFCREPFLGLHIEELECXB@D`CCNAATBNFBCVAh@B@BRBD\DDdEFEBHDCDDBAXEB`CCGRDBD^GC`JTBEVCNBhBAAEBDB>@@?X@CCjECRDA`B@T@>??>??A=<=Z<=f>??CV?PAF?A?>Z=>J?ZC@^@TCN>A??^??^?N>;=N;<=\?^AAR?B?\@J=Z>=?B<^>J>h<`?>==;:V<==PR:J?;V:V<<:=\>LCA`?BCA@X>XAB@>?R?>h>P@VCBJBALBhA@T@^ABNCDHCTDPEBDGTHE\EXEVHGHHEFGRIHTH\JI\IJIJK^MKTLOKVJIJXIGGGXJVMRIZLGRJLGZJVJGTFXNIJZLXJMXNTIKJJIRJFKZLbLHZHJTHIFGEGdIGFZFGXB^EB^CDbCAC^C>BCbA>DE\EBA>PB@V=V??>X;X><;>R>TA`?C^ACBDZHdFXCRDFDDHDRDXFPDVHbGFJ`MTOLRROVRTQdTRRTNUWXVRUVWVYXUV^SLRPRRSRSPQRQHSVQRQ^SPVLPSSLRRQVTXQMM^JK\HI\IXFFC\ElD>^A>A?@L=L=;9R:78L7X8n6N8797N9543734F4h4T41T21V01..R-`2T0R/./043b1F002T31X633B7l4H348b5^855L44445664^7Z8\7D8:b>NBZ@R@>@h@=,Z++')Z&$f&$Z'X%"""V"\#NPZRN\\ZVLPVRTV`RX l H L V T T LV`JZV\VfPjVLH\N`HT^V\RX\VRXHNZJPJXZXJ`TRdZ`VdTRbF^^b`dJXR^^bLTfV`V\RN`LX`PPTjZXX^jTZZ^FP\XP@VPR\F`ZZV\NX^N\VX\ZZXbfVPTLP^^LHRLX\jRbPVR^V^Hr\ZdddN\XTZZdTZ`ZfRZNjX\XXRX^T\hX\\bdZNXR^P^\D`TVVL^PbT\ZZV\ZJXNZ\PRX`TNPf\L\Z^D`bNJHRdXFRVR\VXbVdP^\ZZVVT\\TZPT`TNV^\PNFVP\VLX`fdNZ\TZXNjRTX^LbV^FPVVV^TTb`bR^ZRhZVVD\XV RB P P N X f T B l X \ H RRV\TN^RV^VNbP\^XXVb "L X d#""^#$$l')^')((V(')*b,`*N,,\-V,\+*,-d.-N0.1/^,.J/T/..T-Z0-L/T.,`0P/Z20L/P400V/V0Z1X1J0`-T-Z..1V21R3`2X4R2.T1^0P1V2\30X1/21\34V0.P-1T/0X/^.V0D0-,--,+L/--Z..V/R.b0.R0,,R-+,**d*V+N-*X(\,P(*X*d+++Z.P,V-D-V,V,X/R--12h30\10f02X42202\33N9V544479X9\:R;>:N@ABCZAPCEAC^CFdFBdINFGERC^A@?^AVB\EVEB`EEEVFCDEBDEGZGREIFTHJFHGGECDRBZBGGETGBTEBDBCfBD^DCRA@??>?@BRB\DCFDHNGVFJDGTJFCVCFhFBJDREEVBD@BBXB\AEALEdDXCVDVFGJJF\HZHVFDfFCNCEA\CTEEHGbFbGEPFXDHGXDRDCTCCHACRBZENDC@VACVBAdCTBDbBEbC^A@?=Z@\@N>;;;;:N:V<?=<:J;^=:@>>>?b@??>N@=>?f<^@=>`=@b=F<<=>\=N=V?A?=C>^@J>=>;Z?N?>P?N@><=D<;R>V==Z@L?@?@@NC>^>@L?XAV?\?>`@b>^@?>>???CAAX@PBPE^EDCZJEENDCENIIGRNTKDJRIXJVGJTIPG\MM\OPLTNJbIDHDEGHJKJZHGXHHGPKNLMHLH\JJIDH`IJL\NHOJZLJL\JVKRHNJHLVGFKF`K`GFZHC`FVFZFEXCDCECAfACVCLAC?BARBAXBZ=R>;>T?=^<<J?Z?R>J:>;;P:::<<>Z::V<9:>:BRAB?LBBVCZDFGXEEjGFFZCFDDGXJPIIOOZOONNOZPQLTTT^WV^YXTTZXWbYU\SZTXSVTTTRTRUS`TWTLWSXSLVUVSUSQXPBPL>NLOZNLKRGEPGCDBZCGfBB@V=P;j==<@@AB`A>N?^<^<;A;\=;;;;:6b;F9`9658>76b567Z58`85Z32V3`14210/....L,+-)T)N+d*F'\''Z($%##H#"\"!P\R^V\VRTVbP` \ \ X J ` f RRP ^NXVZDXR^RdRTXXR^h^\fVTZRbXZ\HVRVbTb\ZTVZ\T\ZXLNd^TZbZbPP`nJXX\VbRfVP^^d^fbJRRZdTbTP`X\`ZZP^\RT\XbXXTTR\LZTLR^dF\\V\TTVXX^^RVPTHN^bVPTZX\\JVX`\ZPLXTbXbjZd^JTPbTV\VNbTVV>XNLV``XTTdP\FXZZVdPbNlRDTdJpbRJfTRR\RTP\6ZZVLZLbbTbPRTZ\TZRZXZVDfR^TPXRTN^XNR\ZRLPL^bNXXVVVR`JTZN\ZXVPZNNNLJXR\^VHXX N P V N R X V L R X X X d HRRR>fTRd^f@DTHjPPVR! R !""$$$l%&X&)(V&'(:(\)X++*X.V+-X++P,d--+,./f.-800R/T2-/Z0R--/L/Z/R-/V1/4/L1/b./..^./T..,Z///3/V310.2/00N1X1.V1T44^12R/21d/^1L/2/N...`.X1/V,+^+f+*,Z/\.1/\.b,-,L,+h*P.**^*T++P+*)P*))++b-N+N.Z-L,F,.R/\.P/133435b442`3315Z4^5487b8889;=f?F>;\=B>@R@AX@XADFNEDRDPEDEECD`CNA^D@@JAABDHDLDDJGFDEDfCND\H\ECTHFFEJGfJDJEEGED`DIZEHDC`ECCBDBBVBABRBRA@d?XAP@V?XAB@FNFHdG@JXHFDREHGZEBDCAbDXCD@LBDZDN@DF^DPCD^FXDHEJETEPGDDBPEdBBEE\FJHFGXGEFHFGGGNCEDA?A\FEHChEAPCBRGBPGRCACBA@X@?L@^?\?J?=;;V;b:R;;`<=V;X;8LXAT>R@>?@P?V>X?\B>X>==9T?N@X@=b@>J<@b>\>R?b@`>JAH?P>>:>>;=?@b>;R=P?P@TP><>>d?@=@=<=`A=b>?@^>>\AC\AAAb@ZB=T?@?>D?\ARB@DXFLCDJCCFENDLFLFECGHNHTHFJJIHGHLIRHGNI^JITMTLHIFFCFGH`JKHIRIZJ`KTKJLIH^KVIHZHLJJKLPJFJKJ\ONILPIDLG^HNIPLFVJLI^MPLHFXHLHDDZE`DNEHECTDACE@\>AV=P=X>R=TCZAP?AX?=P>;d:L>:9V;9^:9:D7f755P5X34b555d3L331X52V1/2.1T/./@0f3N1V3T2b10N2Z42H2R2433N0b4L4133H573H1Z4T3\454^65N8X5T:X9:T6H88@:Z8;^>9R>==Z=>N?T?=?VAd>P>\>?=;d;@R@T?=^:Z:<9;8997:b86::6V9T685>6\22J12\2L1`0P02h4L0P2X0,R+,)*)'Z)&X&('$#!# "Z RT V!VTXPJVTF>\PR R J N Z X^ Z V`JRR^NNfb\RTRVFRT`\HPVXb\^X`P`^^Rjb^V^PXPL\P\`ZVVNTTXVbdJZN^RZf\LbR`TTPX^V>V\JPPTXZRVNFZ\ZV\`ZPTTRT@LX@T``TRVFPdZBdN\JXbdZXl\`hZPJddb`djV`PV`^dRdbb^ZVhZ`N\dXddV\TR\FX^VP^hVTXX^XjdN\\`f\VRVLRVf\^XT\bZPZfZTXP\^d^^PbdVhVhPZXXZJXRR^lRHZL`VRXZL\ZXZJX\Z^P\dTjVRVZVXj`VVdJFXb\LhVT`T\H<PRf\ZHPXPNjb lTX\ T L \ R \ Z b Z Z NX b V Z V\FT^TZXhjLTXLFXThR  \"X#$P$T#$"\%&&T)^'T$&'^'X()),Z*J,L++T-`,++-P,b,,-R1B..N/`.N0L2N./T1-/V.`-/f,L/00R1/h1*\.\/T/0\.T--P0/001R2T210.01/00/P30/L4N01L0Z0R/0N.\40B1./-Z,+N*++*R-++.T,,-T-Z+T.,+\+Z,n++)*b-X,X+b,*+R**,^-T-X+,-,V-Z,+J./N32X3F2T4J4V7P505d3T3\54575X8V87H:T:^9\;`>^>T>N=Z@RA?TDXCFCEXGFNFREFPERCCBRBC?`@\AAAGTAHCDZCTFFFDPFVHCDLEXDXENFCPBZFDXCABTDVBXDBTEE\GBCCZCA?B^ACBZBR??VBX>J>?BA8DbIFILJRHG\GFCACDCCDBDRDDC@HFXDCZEDGFDbCE\DEZEFFEAFCCPEC^EPDNIIXJNGVJPIfFEJFNIfHCPE\CAA\AZDC\CPCDDBBXE`FB\DZAVBPBAA@b?NAB@\=X<^;:;J<`>=RA`>>Z=;f;;P7`;XN>Z>@XAA>T=<@N;:J<=T<<=`=R?@?`>T?X>>>??>X@`=R<==>?@A>L=@b@PC@h?JB@T@TAZBXC\DABFHFIECBDG^EHEVFFPHVGFFTJHIIIKZKPIJFFPJZFHXFNJK\O\JIIZJZITIHHNHRGBGZHHKKXNTNPNNOLKNTKKLLILTGLI^II`JFHI`JHIFG\EVFEHdH>IfHE`EVCBAPA^@FA>@T>NABTBAP@@T@=X?V=<^:9J9^89h<\:;P>^>N?n?T@ZCRBPAVCVFCCFGDJDZDBEDELIII^M@JXMVLLTNNONNRQP`U\Yb[XU\YSVUTT`W^STSLSUQRSU`UX\VXLTRVWUTRQXWR\WfUUNNONRLMM^NJLHFG\JBJTECDAP?\=\<^<8X8L;<;9`4N73L75V55\4n5J1V2L1342h/Z/L/0/1H00X11P0/T32/P0Z22`00^33N6223434X64b8H7f3f3V2J53R9^7X:R;79`<56795:R;f;Z=l=>?N@=>f9b=T=L>@?^>\?A:99896V7f69:R8\9:7:6R6R8N84d32\3^4V23V/N100T1V20b/T.\+*X,V*)^('L(f)%R$"D$!!""P"X V^PLDLZVXZZVRXd `d \ \ `  ^N .NPlRb\BZRpDVf`\PbD\bTTTh`TNVPT\\XTXJ^DVZTZT^dPZZ\`dZbVjFb^DVhdd^`^ZVTX`V\TdTbdFXTZb\\\R`PZHTZ\``^TTR`TZdHNVf`XTTXVZfRPX^Rf\Z^T\XbXb^\VVbXbT\ZRPR`NHhVZRdR\hVRXXRTdVPZRVNdZTVV\N`\Tb\R\VP\`NR^^`R`RTZ`^V\BNT\^bRVJRN\H^ZVdL`TLV`XL`P\XJTVZZhL`\`\`\TXFZ^Vj^LZVL`TTZP^PVPbRRPZVdXhNNXRVVHZRLBXRXRVVJVTXXPRXTNTFTHR ZV P R R f R Z L Z J`RXX\V^PVTbXXBRH!R ^"`!T!"B"b#V#V"T$L&V%\'V&&&('Z'L*T)+\+R.0,\.d,P0-.P-H.Z,Z.F.V-/J-2^/T0Z2V/./Z/^0N/\...J.3R/\-/b0.\11F/L/./L./\03213P/.F/22T0./1Z1P2P.\0`30P.L0b.///002J/`1N.d.-Z-^+`*+-,P,N/+-`,,>.,P+`+`/N,Z+\-P*+(*Z-,Z**)+)++R*,R1-N-h-L-.^0X0T1V21\2323242H2V7T5L896V:86h9<8d=>;=:::RAP>A>\D>h=h>>BV>VD\D`FCD\DDVDEBBDF@DVBEACC^CRGXD\CEFFDEdENFFPE\DFDZFTDFBJEDAD`@V@ACBBDXDXEDD^BC>XAXF\Cb@@R@T@VAP@C\BXC\CVDEZF\IZII\INIHRFFBCAZGCFZBBbD`DVAdCLENETFPFEC`BZDCDGRERDETETBVEEDGFD`HPGDGI\GHNHTEHTFF^EERBA?F@AVAEXED`FHECCVCLCZ@X@V@N?VB>X@\?FC>N>H>X==b>:L:D;L;;>T@>@=>;^=R;P>V@Z?`>L::9N:f:>?<\@^>>L?@>?><>:=hd=N>VB?VD?B;=b?NB?ZC?==>==:9X@R?ZB\>V=Z?N@V=R=@=`?@`?@RA^A@BAAAEHXFEG\DGXBbCFRFBGGRGG`JJDFF HTKKbIEVGHLFND`CFHHPG`IPIVJHIIJKJbJJ^II^IXMHTK`LNMZONZNXKJPKFJFEIHIPJLVIH`MXKVIGNEFI^EFFHXHHC\EXCRAXBBVBLCA?dC^ATBARB?==b:>?A@fCZ@ACVC?BHAf@<:Z9L<^=;`;;T;F:8;:Z=<=V>A>@RCADFBPCXDGD^GCERFDBCREVJHKHJKRdNPSQLTSTTNT\YVRUUZQTS\VPDT\TBWPSSUUJ[YXWZVVLVST`VDXUQRQRUP^PPOONLZOHTJGLFTEEFDBh@H>P<\<\:9N9X:V:98:6b3T4R6H4432100Z0H1/--/L4V01N11V0`/X0N/T122P10/T15643d1^226J42522N2R34249Z68X:8R77`89`7X8:9;@T:>L?N==Z@VH;@;>=9h>=9:X98:6X7V:`;V8<7\8V8T6X965J41\1P1X52N3V2N120./X/,-,J**)D()`(X'N(%h$""##!N P!NR:PVR\\ZH R \  Z T N `H XVLBlTXRPVVVLRVZVTXbTZ\X^XdVJbT\VRPXXTRTfPZV\\RTXRTTX\VLZJXP^XdZV\RNd`XRVDTLHLjZfLfZJ`XZXXV\HPTbTjRbhZ^VZNRRXNdbT^bTVVbZXVRbRbXZ`fT`JbVbTZT\``TdVPZb^lL^TfjVTh\\dZTX`X\ZV@dbLZT`ZP`Z^x\b\ZRVPjdJbXPTZ^\ZVTZX`\PRVd`J\XV`Jb`RPVdLV\R^PTZ`^T\\`V\TTbVXVV\`b`\`P^\B\^NN^ZPjNV`PJX`dJ\V\HPTN^\X\ZN`PRP^VZXhHTb VZN RT T T X d  R N L TRZZ`h`ZT`NRV^TfPZPRV N"\"^#"R#Z#%$R#X(%$V&@'(&(()L,,^+\-Z.-X.+.+1N.R-Z.N..J/L//1.V0V41/P0^//.//X.R1\1/T/-Z01X/R.0Z0/..20J20R/\1V110Z//T1T.0^2L/\0-^00.-.`1.L/.11^0^/-.L/N-V,,J+P+/*,,V*H,,V-`--*B,+P-+-j*X*+\-+,Z-d,*(^-,-^-,.X,X/.020/T2`11\3511P21V3^3P3P6@6`:7Z8Z;V;`<<^<;X>>;:X>;GbED\FBJDREVDbENDVDDZDTEAALAZAPARAA\CHDNEGFCTEBACEPECHC\@A?\BA@CDVEVIJIKHGHGGbBNFNDTEEVEPDXENIDEPBDjENEFEDbFTE^BJFRDFEJDBCdEPEHCDXDZG\GHI\KbHXG^GHNEVIFEEXEA@@VAAFXFFDZ>=\;V;L<:<=T?P?AT=;;<;?B><`;Z==>`>=@bA=`>9:R;:j<;:R=^==^B:N:P;P:L?Z>\==^>?V=\=>?>>;T>V>J=R:V>XZ;==V=\?@\@\??<=X>>==T>=@D??L<=>?\?X@AV?f?A?CXDN@A@D`DADPFDCDBfEEVDEZC^DETDCCREDHPIFFJFVJREGFEREVFFFHH\JHITLG`ITIGNG\GRJ\IPIHJTJ\LJKL^LRLHMMlLHHJHbJ^JJJRJLKTIdHGRFIZGVEH^GGFFfDFB`ATBVA^B`AHC>ADB^E@BZDTCN@?T@VA`CLDBA?H=\?X>:;P<\<`;b<`=9;::R:\@F>?Z?@\AXBCRE^FEbFCGETCCLECDFHGXGHKKdLKXJ^MMHPTQ^RRULWXU^VVSRUUZUVULQ`Q`UZTbRZT\V\XYWHXVZWVUXVbSUNSTTRT\RTRNOORPQXNXNJRHGFFGFD@A@AZ>J9^;L:9;98^9B6^57T44J4J5\5h2P100J0X0./V.R00/L0/V20600P3T222N4d25R4Z6`222`4P52N5L35^22\32237X4R6^7T77X78R9R5Z88;\8VL>>=;J<=V>=T>=^?P::V;^:::8X:=X=Z:=`9JZVTFV>`PVVXNTbN`T !"P#""R#$8%Z&%(V&%&b)J&+V)+*+++d,X-/`1R/N--L/N/+T,b-N.`0Z.T/02./.2Z/P1V./1^/0^/Z1R0/.L12./0L1^2/\0//T10J2V3X/0X3\//X/1X3/2J/,Z2X//J./J,X/N.\.-P0/F/f.T.N-+X,X+N+.*+,P-L.,-T-).\,+)+\++V*\)N/\-/d,.V.J-V+,.,X.\-T.--./R2N0Z1T0/002X11N22V3h6H657b7V9T=R<::>;\;;b<9?X>?>A?@?@<=;L=<;;L\=^>@@?=T>T:R=X<=V;;N<:H9^9X;N:9:<<>==>P=;=;f>=X==T?\>=<@?=??=P>;<^<`>:N>`>>=XA@RA=>X@?\?VBA?@B>?T@@T@=P:;J@N>L>Z@@P>N@R?DV@P==Z?X<=FJEZFG`DHIPHGGPJGJIL\NSbRTSTSbSUSUThWHVhSPSRUTJTVSTT^WHXYVTTTRVRTJTTRVTVUPVVUSZSJTMXPLRLOORMLH^KGTF\FPE^FVCTC@?R>^>=V=R>f;9977\65b7V73T43N5Z2^2R/00^/H/R011J2X0R1b/Z0/1X1d2223\12^16P3^1324b4\51Z21H3Z145T56396R85^46h6:87X:PAT<T=;R;>X=X;;T;Z=899X:8:R9;:88565X7:f76N4\5354Z30^03R2X00`0,R-,.+,\)(&&&L$N$X!"P$"P"RX ^V^VTL^PRV`^VZVR`TZ B\ b Z \ P ^L ` ZPR``TF^`TfZHbRbL`Z^XHbLVVVjRZ^`H\HRjPfZh`TRXTlPRLXXLD`TH`T^J^dbXX\l\`Rb^VJPdLZN^\\^V`NVVXn^XRHXJPb``VXVPjP`X\^LV`JPVZZRZd^\PfbjVd`^`dV`VVXZZdjb\P^`VLXfVd\b^jVNd\`Xhh`TrNd`ZnNZjLXVT\NVbTpXX\RTLTZTV^lPbZXR`RTZZbTjdXZ^ZTNTN\^RbLRh^JbT`T^RL\`bHZZT\FZVZ\NR^ZXR^XV`RT`TTVVZ^dHXXNTXNbP^ZT^f^LHPXV<VbbLPXZ^XVP d V Z J P J R V T R Z V d R TRXV^\JbdNPZTJ !!T%#R#"D$%^%^%&N&T%&h(^((P((Z(L++-,-V-T.R/f/T.-X/-J.X../0.-10.^/0\1110`2V2H00N/J/N1L2T0.000X3,Z./P0/0P.10/`1-./^0X1b0X2Z1f1-2^0^0Z.--.-\1R0-...\/J,J.V0,H,X+\.b,,,.,^.,+P-T/N,X*X*V)*+h,+,\+b-Z,.-T.+X,,T,-^///R-R0X0/d2/500V02f0T0P3P333l56h;T89V<:;L:9P<=`>=;^<<;`>A=^>L>V>A=TA\j:<Z=R=?;Z==dA\BZ>??>R=A@J@T?@Ad@BXCJAR=?PE@ACZ@TAAEBCPDDRHET@FDTC`A\CDDEHLGIXGEHFDEZFDHXGfIGRFFGDDRG\GVJHHNH^IFHXLVJ\IL\KJTLIJJXG`MHJ`ITH`HRJKMMIFKJG^GTKGTHVHHIHGTFFDVBCFPFEBTEARDD^FRD^B\DBTC^@BDAB\AFDbAABfCV?R@AP>>JR<;N=>AADAANAbECbDXB@ZFLDCDEXCTGGD\GTHJFGPLKLTMOZRRPVRRPSHRPRVSXUVS^WTST`WRXR^RQXUPXTRNUfWRXTTRRVVUXXNVSU`TVVNRXO\OPRQZMVLHHIRF^FVHdEBA`A<;:Z?V2Z3V3342P3V3443T1h344T524\0Z1\32^55L64N7\794L788\9^8n::;P?<=;L;ZA?;b?;\?n9Z;X?<;T<99T:;\:X;d:::\;T@=`:7d89P8X75^7^7Z7754l34`633020R0-J---`-+()&h&F&$b%""F#`$!^PbJXX^bLNZP \b^L n V ` ` P f H \ dT RZXTH\JZ^\\Pd\VTHXLdZZZH\L`\VRf`\HZ^^V\X`\\ZT^VbRVX\TN`VJTNZVdN^^R`PZdV\ZZX\NLT\bb\JX\Tb`RTXZZX^dL\PTRZTNd^@TZTXX``NVPTbbFZPR^T\ZfV\`jhhR^XZVXXPVRXTRXH`\PL^hRbZZFlZZLV`N^VbVZZfN^JT^dd\R:`hRV\b^ZZX\HZ`TZ\`RZ^`\^LHRZ:\^VdX`^\L`ZNdF\Z^X\TZ\jhTPZRR\VZ\RR`T^ZXTFTRfRZVN^RJXbXXRRN,T`\`ZZRLdb^ZR\PTNhRHbbZVP\XLN\Z`VPVPbTTVR`T `F  \\ L H ` D Z P T \X BN`Rh^P^^dJXL\\ThRXf!P$X""$T$\%Z&X'%R&&'`$R**^,*V(*d-\+.R,T/T.b.Z1T.P00R0./V-\/.+J-^.l3N02D013L11`441V21-`01/N.1.T/2/Z0T.1L1.0R1X/11-L10P/V1T.03^0Z0b.L2d/N4V/.--`.-P.1d.0/-0Z/\,*,X+,.L+/X,J-^.-V+Z*L)*+Z*\+*\)*T*V,^--,0,Z,/-+\+02^/f/./Z.J101V1X0/T/V..T-T1135J5\66V7Z9N::<=N@P>ZAN@FB`C^?VAAf@FPELCLIXDCPETECBLDCDBTEjCXCBDTC?`FACBBVDAfFGFFZIEGVAC@BRABCTD^GHE\DFB@DDBCCFPBCREERCNEdCRBBhCV@TAJDCAVBd@?CRBDfEZF\FETEEEEC`EXGFGVI\JGLHGFPEDZEG`BVEEDGDCA^CGEDGGCDZDdDFGFRFVFIRHHPFKVFTHfHHFEGXFHEZCBZBEFJCXCRB@=>P<`@V?>>=A@>P=P>:>;=;::b8:<<<==99;F:T:P;V:;;J<8d;=N@B@R@>P@==\?N>=V=L<>TA`@ZABC>D@\@N?<@>?ZAA=\?=?@?=H@<@V>AN>?RBL=>A\>\?BBL?RBJBDDDBAX?AR@XATBL>AbBVB^ADEDEGPDZDFJDE@XGZDRBCEdHFTDCE>DbGHZJNGCPFFDCXDNHRF`G^IVFGTJHLGLJHKFLPJH`JPJ\ITHRKIZGKIPJVMJPLLILXGVJK\HINJXK^HEGZGJGXFPFLFGZMXIGPF\FbE\FCGHCJDC^DTAAXAZFDBVDdDRBA^?@VAR@T?H?L?\@=X<P997X6H84V733V302X21>..b/2T23V0N1R///.2^/0\3^0`3T3^3621B3N42D2\02523.0^1L6Z54f53535547R756:;=P:X>\:T;dBb>:<<9`9T:9V:V9H<;8b=;Z8`5 5Z6^76\46R5644\5V3b2N1P4P01.J//^/1/\.-(+(@'X&T$R$$V###"PR\HJXLDVbHJZdVf V \ h X ` \` \ZbZ\LNF\\\RXLfN\LL\^PZTRXZ\HVX^T`\VVXTX\Z^ZR\PXTTRbVV\ZTX^bVpTZXZV^Z`JXZZZXZbTJTXZJP^PV^RP^T\NRTjXTbZ^PP\TPTPRXPP\Z^^LrP`X6`jf^^L\^dZ^\`Xjfd^XZ\VVTTdV\`RTLHbL\NZP^dX\P\^PZ\JhbPP``Z^JTf\VVZRR`TPVX`TbXTRRNd\RdLPTZbLdVTbhJXbdbdFfTV^V\bLXHNR`VhhXjXB`PVhVZDRL`VLBd`\PRXTT\dVXR\R^X^FZXbP`PHRZVP^ZTV`\\RZR`b\RRhF^ZdL ` \P bP \ V T \ P J V VVTPTRPXPX`LdjTZV Xb !$$#$&'%Z&H(&'Z(`(b))&^,-\++-+N/Z.-\/Z,Z0H///d/@-/0^--L00.^./^1R0`1\2V42/00^211L/V.P40V.d0D/.0/.^.j02^110f0V2`3V0R.j02H1V/.0///Z0.0,Z/b/P.\/R-b+`..d.\,T-J+'R,+,X-.--R,+T*X-\(N,^*Z(\*P+n,*+R,d,,,X/P/-,+D*,+P,/---.001h20V/0\0\.Z1Z1Z1d3L6X577;9^=;=Z;;>N>j?BBB@RAA\ABERDBCBCD`DNB^E>D=BBCDAABZATBZEABbBBbBJDNDPIHFEFHEVA@TC?PCCPBTCBTCLACPBVCbBETEBbBBDbD`BBd@`@`BC@@B@@B`CBCDRDBFC\DRCCZCDDVEBHBARENEEEFDETF`H`GZFTFdECFBEEEG`EXFGXG^ELIZHTDFJEZCHDFHNIFXJ\KZGHPFJDEEGFDFBbBBCLDD^E@>?H?=R>@@@`Ab?>P?R?l>>?=?^;>F:V=`<:<:<;T:b9Z;Z8:P::Z:;Z:;::<`9Z;=V:\9:H=9D:T=T;;L<;`8;H;X;f;V>X?>>@d@T<=R=X=>b==R<;^BAR@@HCRB\BE?Bb@\GVBLA@@A>>=R@?b?<:bP>\>X@T@Z?R>?TA?AB@PCBBTBXCBEXEPCERCBZGEEGZFVFRFGJEDdCVEJEIGRGCZDZGEFDLFZJZFHRGIFIJIIJKdMTII\G`HLK`HKZKVJTK\KTLXNLJKILHH`LJJK^GRIHJGXJXJGXFGJE`HFGGDFVDVFZGHVE`DfDCNB`DDFA@DABXDf@XA<>=R>X>X<`BLA<<;RJ=P:7`87`9P7R8h5X5N22`101X-/P-31H2/2R--./0^1J523.\1005R1P331J411P3R2\3P4104^7X4Z63Z334316Z7H68R9`=^:Z=Z<<9:J=:=R<;PD=d:;T;:`;8;X8R:V6D9\8T6Z8X7^8P5X4Z6646X2T21H2/./0X/1Z/Z/V.,X*(X(%$Z&T$d&"b#\ ZNZZ^\NTNLZRTVNbF X V F N h V \ Z XdZTRDPZXTT``fVRd^VVRNVV^TRXZ`ZXLTfJXRX`PX`RHP`bPRPRHZVh^`VVNZZ`ZL^RTZ^VTbfTTN\Z\TZRfZNRdZZ`^ZZPXXZP^hdLR\ZDdZHXXNJZVJ`ZLP\hV``bRXn\\XL@ZL\fRVd\^T`XRLTZ`PZRfXZXVL\bVX\^V`Rbb\Z`NbPRLTVLTnRXHJNV\FVRXV`Z`NZZZP\RZRTXRP^`V^`XTXZPTZNRVP\j\X^NXlhTNN`ZTXd\TZJ\JZTRdXRTXXVVTdTRTXJRf\f8NPXZ^X`^RVh``Z R J bT H Z N T h X V Z PZd^hTHbRRTL^F^Vd^!N"R%"$F%^&&%'(^'\)(,Z))*H.H-l+.0-^.N-/\.//X/`0F1T11R4000\.P.X0031J/2V44Z2L241R00V4Z4/1.`0H/\1b0-X10/X1b./V/V/0/-d2V2J011/L0-T2J/0\0N0/`/0Z001.b-T,-/.*H-,++,V+-^-^-L/++((b((,D+X)*(-d.*R/L-X---+L0L--X/+f-,`0..F23X5T0b2/\2^.X0/\3032\4867:9989V=J=>J=?X?<^CB@?XCBA@ZE`CXDZD\FEDCHATCNDTD@ACA@CAB^DLB@NAVBBDC^@XDCCXGFHHFBE\CCX?D@\A?R@CVCdDPCBD^BD\DD@dDEXCXBC^CBNA`CADPBhA?XBRCERDAFFC\EBLFFFVFBBTDDDXBABBDXEEVDPETKTFCFDTDCDJ^IHdFJHFEG\DRJ`IE\HJHEjE\GJZIHFH\IZHGZKGGEEGVDLHERAXCZDAACBAZDX?J>N<<>=>A??XERATB`BPAbA@^==N?=R>T<=\><>:N>T;=;P::R?=?=d?BH>>=@\>Z?Z@V@V@@FBCA^@Z@RBAB@JB\?@^?T@AA@?j>R>`=Z>?b@;>Z@?A>=?L>==Z@>P@^DbFEXF`CJA\???=?=XAR@?PALB\>CVATB@DXBAPCDDCDNCPECXDRHEFHCJEGDTEDTFNEC`EPEXFTEEDBNGRDHDRG`JVJHVKJLbIHXH`HHHVLJHIHHTLMIMXLIMVKTNIFIILJILKGGFG\HRIHJKIVHHbIHFJDGRGFbECBDBNCLB^B^?^AHFTCVCL@?\=D?\@R?V=R:^?V:9:88F7`6N6^3D30Z3J/L10V//\12b41`20N.h/.T/.221/X304411j1D0J41V/L2@1H.1503^4\6566b3T53\5N9N6V8`:P;Z;Z:T;;\9V99Z:7;9\::9Z:;Z=;l@X@@\A?RABFPBCC^FNCFdEDD@TDBZDVEBDACB^?NB@VADCPB`BlBCCJHXFCTEPFDTCBVAAV@?ZC\A\CPCXEZGJHZEXBLEEJCPCRF`EHDXFITFNEIFGZJZIXGHFHXKHHHKI@GVGNERG\FE^FFFTD`DJDDRD^BBC@@A?NC=P?V>RXD\?VDb@`C><;@:f=B>Z<^;\?^;=NAR@ZC?=>T?f@<@\@>@>d=>=d>>ZBD\FCbBAJDCAABVBR@NCR?CP?\AB@?\=R>=V?@H@=`>LA@;=?T=N=P@RCCA`@@A@BJ@L=A>@??L?XD?@^C>?fD^CABDVAPCFTC^FEDBPECDCVFGDCBCE=AN?h>R==L?<<@\ACLE`BBD\EChECEDVFZFDD\CbFERHZHdMIJLOZQJO`PQTRSNQXPNPPQPXUS`SRZTPQ^TUJ[UX^VLQXRQQVRTTURbTVTWUURTURVJSOQUPRbUPOLPbKJ\HDIHNIG\GFRDRCV@@X=>D;P<^;<:;;^86N8632//0/Z0T0^3L10X1T1\/1P-d01.L1Z222R20/2f13\1/220Z3Z21/1P2V4P4N3T63Z43Z53\7^76f5\8Z9;R9L;T:7X8;8`9^>:;::J:XT?>X<>=>\@Z==VBVACA\D`EEAGHEEDF`HFEXGZHD\BXAZ>@D@CC`A`ALANDBDARBhBNFBGZFd?EbEXD\DDC?JB@B?@?@ACXBXCVEBCREVGFC^F@fBCB\BD@CBC@AADdABBB\CEZDPDBZGdBBFATGZDVDLCAN?^@CCFDVGGF@TDBDTDREXFPFFTFFCRKGVFRHFbIIFXIJGZIFIFG\GRHRETGTHdJDVEXFDJD\ELBCAA@??T;=\?=^=X@V>>=?>>Z?P@@@V@T?`AZ=V@R<;99X:;:<;\@<<<:Z<;H<;;;?^B@T@R?@A>>V@C@ZB=A@VBJBAE`CCB>PAXB\B>`@C@?DAPAdA?V>=>`=T?@`=><>L?=b=<\>T<`=>?=Z>BDZBD@FA@?AP?A`>N@\?@ANA^?PAD@`C@TC??P@C@RCXAJHTH^DZIVDDfD\CGXEPELIVGVFVE^BbAZDLCFFVFDHBPDRBCVCZF^F`GRLTJKTITGIVGKRKK\ILLXIILNPNKJ^LLL`MZKONNLKJXL`JHGPIJHPJKJJMIJ`MGTIJPJFGREDD\FCDXCPFRDCA\CT@XA@P>H=N>\?=\<=?J??@^?\?==R=d>R?`A>@AJAABXBJBCEE\EBTC`EHDDPBXENDFDDVIFKXGVKMOVNMXQVQJWVUbRRLPQTRNQQXRbU^URUdUQT\RTUVROQRQT`TRUUVTfWLSTQWNSRTRRSZTNNJ\MIHGFHHFZHXEDDZ==X=N<:<L=Z<\>=<9:^:H:P98R8T6P9R:P988J8b9d7P7^6T:6"5X845231112`00Z-\-,Z)T)\')R)R'%D"$#T bNBNRLNTNR\HVJ`V\\RRBH`NL X N T V  ZL^Pb^FTVLV\RdJVR^\`LZNh\RZ\VVZXNXT\V^TTXZZZRLNHRbHL\@^PbNRdPX`LddDXTPVVXZT\T\PNZVTNTVfZ`VTf^XJRXTXZ^NT`ZTFZf`db`bZ^f^Rr\`ddbTV\VZ``^ZZbdd^Vf^bNd\XXjZZ\V\^fXZRVdXP`X\Z`LNVTZTb\Th\Z`TLjVLTP`NJX^`H\D`ZX^N^PXd>VFd`TNT\PTbZbPd\j`\``\P^XVJ\VVZXP\TLTVh\VJ^^hNF\JVZRVPZ^fXT`BNZJZVZZXlR\VZX \PXTb  L \ X \ N X f L ^ d P\b^VRR\XTjPRLZ^VdXN!\ !!#"&%&&((+D+^**T--j*P).,Z--/j-/V/Z,0-R/P/R0/0F0R/^/0V00Z0J2X121f/X2J4b1Z3T1\6331J1V0\1X1100T0-P00-Z.-`/-.Z//^///N/h2T0//1020L21T..N/11-.d.+b,J+d+N+\.+)+*H+,T+`,++*+Z+V('))(Z+V*+,^*+T,/-/P-`-,X,X.--L.^0T/0P.340&1V0V/d0R0^/N4X2b444\5L46T:F6:T9h;V=;==^=d==X??PABPEVFLFTCHECEFdFPGdGbFFEPE\E@PC?A?PB@NA\?fBA@\BZB^DPE@E@C\GCRANARATDVBVBZ?A>^BPBPACNB\AHABVFHFCPEPF^DVDHGTGRA@=VABAVCCB\@EdBNAR@R@LATD^C\CTCbFDXCRHC`CVDRDCPDCDCNECE^FTFRDIVFZHDDDJHHlGEPGLHJH\I\HFGHHH\IJNJEJXFPL\FEGCDPFRF`HFGXDVHEEZFTE^E\A>^>>^=@@?>>f=P?^=N>?F?>>?L>Ch>?@X?=P;H;R:;:;:@>9:J=<b;Z9\9F:R:T<887<:R>D>V=X>X=\<>=>VBBFBXAbA?XC@@XB@@`=<>?T@\B\AVCDPE^ECJEC?@H?^BDVBANCBXDVC\D@Bb@A=`=;T?`<=>Z><`=:\@D>AP>>VBXARAC@PARCZCAA?=V@@Z>HA@T@EF>TCRBLFRB^CEBXCRDVADAEXFGTHFbGNDbEXBCCZEGZILDBHCCABJBTDPEEDAZDLEEPEIIFLLGNGdM\NRKJJMIRJJRKRM`MLNTQ\NVLTLNRQBMLNRITMKHIZI^IPLZLIJNHRJZMVPMPJLVHGIEVGDE\ETDCGVB\@^==Z=`=X>T=\@>@@J==>Z=`APAZ?BD@RCP@ADD`CXFECALDVDPDZACVCDFDEJXIHITGRLVLPNNLMQZQR^USPQOhRQVSXWXUUZXTS\SPORLRUS^URQTRRfVVWZUXRUVRSRTR`TVOJPRVOVMKIGJKRKTHHGRC@A@=?T==N<:;J;8^7X743^4`3`2\0032/\2`11P/./X/^2\../L1.L2.P0P/L11X/-N/Z/0X011V43\2012T627H5\66X7d3R7\:J:898\8696d77f:;;9;Z<^:b>=:L;;<>;>^=<==V>V;b<=R>=788Z:T9V;\9Z:H99:D87X7\75V6T64N2H51\43113`0/X/+\,\+P+X)h(N)\'P$T# b ! RN^L^XdZVLRfV`\^^LXT \ R R P \ Z N X Z HRVTRV\VdRVZlHVdbNNb`PbNd`\VX^^X`XTTX``dZLX``TTXTRVX^VZRN\B^j\\VLHXXZXVJV`VXbRTfRJ\Z^bTT`\Vd\bV^dXfLPLVThRZ\VRJ^FR\ZdbZ\\n^^\P\TP\XZV`T^VXZb^bZ^VXXTfNVfL\d^PPXTN^^VZPPZJVZ\bX^RRVPLdRRV`XXTZJ^ZTTPZJ`FZPL\ZTNT^RX`\bLXTRX\`N^VLPPNVpRNb^dZ\XXThVTdRRPRLXTPNTRPNRZL\`VZ^bVHbZbRXbRfJXZNdJV\bJZTFdPR^TTRL`JdXXFDZFR VL X X L^ R F ` H Z JD RTVLP\fNHdTR` LD \!J#R#b"f$%V&(%'*\)L(*,+\,\-L+P+.-V/\-Z.\.-V1L-d.\//H1/`4N01//J010304/0^1V3R033Z32T4Z332\40Z30b0J0/P1/X.-0F10P.P.1b0/11V02b/0X2R1\2D0^0Z111J2/0`0N/V.,*,)Z)T+T+,,-,Z/,+N.,)b*-T)Z(((*l)P.+J**T/\-,-^.P-J/N1.X.^.R.-0-.1//0T2/T/\1T01V4244X4L7879Z88^==BCVCC\DFICLEEGZKZFIVD\@P@T?T@V@>RCBBdA?B@BbARA\BLDCFZCCJBC@XC@RD@b?=@dB@AZB@TBbDCVBTDbD\DPBEFVEFBB\D?ATACTDfDHBTBANB@PBB^@JBBHCFdGZFEFFE\DDBDXGPEZFCDZGHHdFG`HXDTGGhGFKI\IVGHNILLJNNIXJGGPLJVHLFFE^HPFGZEFGXGXHEVGVECZCBEbCAC=>^=\>dET?@>P@>CTA^@AA=@^@?=T<=<;Z=N;b;899P;:\:999999=V::`>X=D=?J?@AC^@@T>XATAJAAR@^=D@`ANAZERD^DNCEZELDBdB?L@ZCBFBCREPDFLDRCCfCR>@=@N=\=V=;V=<`@J=`=P@XA?=P?`ATAR@\@TA\?B?VBXAC`@`>T?AH?\C>\B>?PA^ARCLB?@bAFDXA@CNCEVEJNIFDGFFCPFRHFDfCHCDF>@?`@T?^BD=`A>?\?N>ZBVA>Z?b@X@>@VDZD\DXFNELDD^BVAZATADB\A`@VEPDFE`EHLHKK|LTPMNOQJRVSLPTOONVO\QLSSTdVFW>UN\ONSUSVUXSFR^OT`UNWPSRUYTS@STQPQQOQSRLOPL^LJITJF`FFE\B>b?XEP?V<==P:^:Z=875H8f6Z6B4b422\.\.T2^0Z3V1V01./Z-V,//X1R/V00h0D200/\1T-T2T/P/1\14P4T1133\35T4b3555<6h8Z86T:f;P:8;;5X6L7J97Z;TH=r<<;F?>P;T=A=T>>X>???ANBVCBDDDHEFPE^EG^GJECCA@PACFDADPB@ADA`CA\DZBTC^CPCEVDTEZBABB@?j?@>\>AA`AXCCNBREFBXEBNE^GFVEZEjEBB?fBABXA\CBDTB@AN@AELBNEERDLDEDEDTEDJEFDNG^DFFDPFHPHNEEJRFLG`FGdHTJHZL\LMTM\OLXNFJTHHNJXJZIFNI\FDTEZDETEFFVFRGLDdEBEBF@fDCRBBN?\BJA?V?=>\==@V>Z@NC?BX?`@@`??`=;;;X<:9R<;\:99J;P=9V;R=;;;<=>?>AJCR@?BBRC@CTCAA^@@DZBAA@XGCECVBAXDB`BEZCCdCCZDBbCPCVBN?P@RB?>R=>B>^>VRBb>@VAVAB>XA>NC?ADC@CBCXBCR@X@?@RAJCA?bB`CBAP@A@lA@A`BbDXG^CTJFVHXGHEDNFHDDF\GCTD\BFGDD^DPC\CTAXBBBZF^DFEFRK^JJ\LRILNNXMZNKK`LXIK>NMPMUfNLMONNNNJLTKLKJbJRKXLJ`MJLMVKKFMM\LTNKHXIFELEDfEGRDCZE^BTCC`DDVAVAA\?TBN@==;@X=@\@\AH>T?^BJA@??L?XBTDE\F`EXDEA?BNBCPA?\CBBZEjDXFEGGHGIL`MROLXSVNPOQZORSQXQORRR>TVSQfPQXRQVSTST\URTT^VTXRS`QJQZQPZSZR`SNSPTOOZIKGH`GPH^LTHDZED?AR>Ad?>f=L;99b9\9B362b44`3311000P0Z01P,0+-V0200Z02T1/+//0Z4-0106n6F33L4V3L6X453N8J73659899879N8`99d68:N99\;;?X>V\<^A=?Z;<:>9<8j8\:^:^:9<:;8\899b;`865^6T35J42V3\31\2\1Z1V0,*T,`('\%&\&V$%"!!"TVTXTd^bJ^fRRNdNdb \ P \ ZV^^ZjX``\\XV^R``RbPVH^`PdX`TTpRZTP\fNR`\\ZNVbXJ\VdNXZbT`\dL\\fPJJXJPbV``X^XV^f^XP^\ZdXLZZZT\VfX^V`ZX^TZjVXX^RRL^X^XbTZ\X^jRdT\RR`dZdbX\P`V\bd`TTHbR\LJF`\DRZbZXV\^P^ZTZVV`dZJ`RV^^XTV^``BZXTRDbNZRR\TXPXZNR``JXXX\`F^XRH`^LP^TT\VXhbTTR^VVHVXTTVfTPXPPLHVP\NL^NDPTVfZXXN\V`TZZbTVf\ZR\bbdjRb` dV Z  Z T P F P R `P VbZPPTPVRZRTXJPRVd!#Z##T#%b$%)X*()*)),L,V.Z,d.P.,X//b.-.-Z/../00/d3-B120R2b2R./X22N3b2L2016L21`2T32311510^3X./1T/0Z0/.L/b.T000/H.P21.Z1\0R22V001P4//T1V112///+P+`-V)R++T+*`--\.X.++*^+b*)\*J,N'N)@-X,+P,+++`.,^--,+/-\1V1F/-P./T2J0D0H./.J.b1L//X3J3^5556X:N8V9Z89N=d:Z<`<9<\=T=<\@=>=Z@ZCZDD^GHFTHZFF\FFGLFEbDBD`CT@@AA@^ATCHD\BBBC@@ZB^CA^BNFDDRCDCVA@Z?=X>R>@L@DRAVBVCVDDDDGNARD\D\EbEFTG@A@AC>BXEBXGZCTBADTARGBLGZDDFEFNFXEPEE^GGHTHHFG^HHGHFVJHKdJJJRKVN^NLVMNMRPNZKIJdJJ`KJHZJ\IHDFNIBBPDEEpGFGbBBZCB^DDZCBPC\B>?TA\?T@bCZ>P=>^>X><<<^B\@P@CbB\>A@R;X:\?P@NCNBA\AL@VBLCTEXDCXDFEbHFZF^EdFPEDLGCDXGbFDDDBRE\DELEHCXB?A@?jA^EFFEFNHLJ`JKK`MPLVMTJTJZINNJN^PLNPNKNMXMMhLL\LKbPHMRLJ\LMKPOVMLTK\ILMKNMhM\IKNJRJGLEBPBZD\DVCGFGDXELCA\BCRBdAT==>^>T?R@@`DN@^?>A=Z?XB@V@?9=L=d<\=N<<;:::=8<\=>b^fZNLPRfXLdX`T^R ^ \ \ \ T V b `V fV\bRXR`LZV^RTXZ!#\##$\%&'T&*))),F+.N/--^/-V.j/b/P/.\/F2j00/d/1/J2^.T/f0\001N1b0L11132112/^21V313\1/T2J102^1.^2/Z1/2/V/V.-.R.\/1/V01/^1V0F1X/\41.R/N12P31F1V/1D/.X,+)^-T,*J+f,P,V./++*N,**`*P+)'),L-T-N,+F+-,-H.\,T-P-^11^/\2\12L.V/\/X0d0/N/.0/N217X5889T97T88N;;^;N=X==b=`>?P@^?>>JBR?f?C^G^DGZKGPHXHGCD@ECA?XATCAACVERFCTDABBXDDRC^GRGNGTEEJDXEC?V@\B`=@X>??T?AED\ERFVEGDCbCDEJEECAPCECZANCDICbEFEAD^?ARC\CDZEZJ^HIEEEJGIGVJ^KHTHKK`MXKJHPIKIKMNOLOXPOLNMNKIPIbHJIGGTGVFXDEFFAbDFF\FRCDRBXBCVCBCTD\DCV@b=:;`:Z;>fAA?Z?PCP@?`=>^?:\::J<9\;j=:<;:8D::;;;\<<>X=:;?9R=:b<;N<9=>===><;==f?b@?=bA`ADX?^?VALBC`AEFFDDVBZDDCPDCEDDVDCBAATCBDXCXCPBZHHFNDbH?\CT??>N@?R>T@T@R?LB=X?Bb?V@ALC\A>V?JCB@PBZDZE`@CAbCCbBLBLEdEZBZBRA@HGjA@bAX@CCTE`F^HDTGIIbGEDAFGB\E`EFZFNEAADBDbI@bBLDTB\@?A@IEDVJLLJJ\M^MXM^JDNJKJRMKTKNMMMNTLLLQ^PXNbNNLKTN`LdLOZKNLJPMXMOHOVMJPM`L\LJdM`JJ\NGfIDRBDE^GELEGZFGCXCBC?NB?AZ=A`>AACP@f@XC?@A@^ATBCV??N?JDDRC^ACXBfCVCNCGZFfDHEDIHVLJJZMJ^MMMHT`OObPPPVQTRPZUOPNQPZP\QQlRQbPS`RUJSSSXT`TTUHTU`Q\TdRJUR^TS`SPROXNPZOMTJHHI`FE`GTFCZAP@:@?A<=R:Z9VZ::X9996V:V9^99;9:Z9X:9Z:88X98486V55N5b4\4Z3P0d1/b/.+)*))\(%Z$#^!X"^"\\ XPTd\d^FPJXRZPX^L\ Z N R P T VNRbfN`VX`DXN`^PTfNV\fdPZXXRNfXNZJXRHXbb\^hJTn^T^dbLL`TdZXlT\bJFTnl`R\TX\\T\d\PV``P^dNbXTZZXVdXZ`fFZPFLJZTVNFFZhX`pR\dV`f`\\`fRfdd^V`XbXbVRRdXX\RZ\`P^RZ:X^VTRT`T\VP\TV\L^\^R^RL\hXTdRRT`bVfVFPdfFNRVZZTRVLR`\^dbVTXTVTVNNRl^VZT`VTHTLdXdVXZbXXdb^dT\VTZJ\Z`X^TXTfLRZR\^TVJXTVbZJTVV\\\^XRVL^D N X X Z V d T L RJZJNVdRHNX^ZXVPZ " !Z#R'&$&Z)^)L)f)R+)^,V-^--V-,.+..P0.0-Z0V2/V0-3J32/N32X0^2^41X553R753`2L220b0T1b1\4R3X2F21T1Z5Z0P2X0/L/J.V/0`1T.0/-,0P3T1 0J00T12202/.\1Z2T011\020...T,V+\*-\-,H-/\.-,X)V*T*)\,B-*X(+*)J+P**P,,V/`.D+-,.00/1`03/T10/-Z/L0`/V222b3b535L4j798:^@>d@VAA:FTFEEF^HNFFFG`IFDTACB@XDVBB^BNCANDLBCDCVEZCHNGBEDC\EEVDC@H>=L=T?R@@?DCZCGEVDEDEJDCGEXELEFbFPBNATAAVBPC`FEHHTCDBJB\DfAERH@JNGGbGXGVGHTILHJK\LMXL*KLNLLOJLIJ\JJTM\MZPbKM\OZONPfKMXMRMdLIKKZGTIHXGVHG\GEXFAAABJDCZDZBBZAACBBDB@`A?>>>AP?<;;\;;N;V>^=T=?`@A^>\=;?:X:P=H:9P9V;8>?:;d=V>=\C?NBA@AD@ZB\CFEETGZHFZEFEEGDFVLFCDBX@DVBVCDECRDD^DZECC@VABPAA@ABRAVBAB@>@LBT?CDAFB`ADJ@ACA\C@BPCXBDNFDDDAV?H?\ABXAC^HFFDTDdHHJ^GHKFhCHCAZCC@FDDbBNB@AAdCBBTABV@V@^?ACEREGRJH`MHRJDHNJ\LJKZKLKK\LJLVL\MNPLXOPQMNRMTMMOZOLMVPMVNMMdQ`KOXNN^L^LLLZJZKKJGLHXFDNCBE^GPI^JINGF^FPDBCLAJEB?Z@T@^@dAVBRAA\@AZ??A@\B>AAbBRAATC@VB?XCD`FBHRFDdFNGfGXHJdHhKHNIJLPKMSXQONRPQPVRPNQPRXPTObTRPXPPPPRbTSLVRT^UHVZVUWTS^TZVSNVFTWTPSPTPQMMKIHNIZIPF\DD@CB<@T;V;V9R9685T446T45R2^4L11202/0-.P/`.N0/R1X0/\.X..^0.V2N0f1T/T11`15V41R2J32P1P42N5X7X5P7b7T8\6^6344Z4J5^4766889;<=b99=ZA?N?`AC:GRHXEZEXFTIDbEHFVE^EBBACABDCNBC^CVBXDEBDZCBLHZBCBZCTDNEENECLGB`>R?N@n@?VBbDPAF^FHDGBJFEDLGEGDCZCEAECAZFbEC\DTEZFTBbAADPEhFERKHGFFHGRGTKKXNTLN`NL^POQJ\P\PNbL`JPP\NZNS\OZO^QMJPNL`NZNNHKKJFKXFNF`DEZD\DDFXFBGEZEPDBXBNBDDbDDCbBAJA^A?>T@b<^<>R<;\>^>X=><<P<=>H=\;Z?Z=Z@F?VBBBVARBZ@XBBCALCRENGVIFFGDZFTFdEXIRIFPILHfKZEJKDXDTERB^BBBBFVE`EFFC@CFAEjBDB??ZCN@ZDJ@BT@@P?^@XBREN@ABB\EBB^CRBAXDXB^CARDABbBVC?T?>NALCXBFVEBCRGB`CDTGTFXGHEPFfBCCBHA@DD@b>RBZ>RA?XAB>@`B>`?DCFFJXJGIRE^GGGZKLHIKI\JZKJN\LN^MOMRMlLO`LZKPM\MM^NNPOZN\N\MPdMZNQVNhPQMMLXLNNMZLPITGLDCTDDdIKTH^MEFDCVAA?ZBbCA^>\@@dA@NAD>V??@@@dA@@lBAZA>B@ACDJE\GBEFHGEbIIGGIRJHJKJNHQLPMhONMQ^QPXSPNTPOTPPRTOTQSQQRJSUTWLVTQUVXTVTTTR`RSSRRPVfQLPQ`NMKJhGHFDBCNBT@n??;N:9:Z5644493X52V53/P0\30X//-1X1//-0\20N1N0R.V0Z00`110/,\/3012P021R2Z54554R41T49Z4V52834^5547;\9<;Z<=8:d8`<9V;<;D8;H9d=H9^::P::99;N89Z6X8569j677`5f31H0X-//`/.,+b)V)()d'%$"!Z"\ Lb\#Z!\JZPVRbPXJ\\^PR V ` T Z N H ` H  ^ fRHPVJ\TB^JXVdRVP^T\XXXVZ`LZX^T\PXVXV``dbdN\^`ZdLPP^dTVbRb\bT^T`TZTT2RT\`\fRZZ^P^X^\T\VX\Z^jbXN`Z\^^f^HXb^VbRLbR\ZXP\`ffJ\TTZDbf^VTXbbR\\Lf^h\NVd\bXZZdVZ^DPVTNhLFNVhfP\ZRTZP\dZT^PVXT^VdBVDZPFjLTVXVVFT^\f\F`VV\TZVTXLdZPZT`RRNZJNRZ\dXbZZVX`PXR`VTZPXZJTN^NR^X\nFXZPNTTR`PJF\TV``TLF`JLV`N\VV^NP Z V ^ b N \ V RXLNV^ZRPLPXH`V T^#P#Z"'%^%%\'b(R(R,+*)V,X*++*--\/.R1P0.Z0../H1P0L3b31Z5J05F21J23R61T44N7R23T6b6^11221X/D/0R2P2H1V21b5.`./d00D0/.010N..`.P//P2003P1X.N3^3Z1.V.B0./00d0N-Z-L-`,V-b,+P+^++*,h*+T,+b*+T++*X++P+*/-/,d.\.Z-N100R1H/Z0.11R2V02Z0J/22`112Z2^11P25T5357L78>P;889H76R9P<@A??=;V>>R=>=V<;`>Z>H:Z?<=<>;=>H?jCB@\CPENCNEBLEATF\FREITETFHETFFLJ`KITGRJHJGGBENAdEHB`CETCEXHGERGPDBLBCZBVCEPCXBB@AV>?TCPC`DAXEDZFAbFRDTGCLF\BETCbBDXHVCDXBPBR?RCPCZBCJERFZD^DJC\FDCRG`DCEGJEDCBJCBXB>C\F\EhDAP>B??X>C@LABCLGCD`FTHFITIEbFJGRMG^HJJVLLLK\MPNOOLKPMLZJZLTONTMTPNPPdQNM\MMNbQRQSTQQPNNMLLJHPHHDHFKBINLLLPJE^GCXCE^ACBLB\EAA?@BL@CAXBNAZB@VD\A?DH?XCADDBZCBAEFDZEXKLLFIFFHVJIGJHJXMQXOXQ^ONM`LVNHSRPNPPPRPbQ\PQFP^QZO\SRQnQTSTWUX\VTVRYTTNSTWSVTQSSZQNOQJTKEVIRG`HCFbCZCdB\?<;9Z8\89\55345Z7F31X342V1L1b00///l/N4/Z/.-T-N-N0Z-Z3b01b131D0V..0V2/11H14\447R643354^54Z56344Z5V9J79X<9:;<;\:V:V9h;^:V:T=;>`::;9;pdD^VJ`^PPZ^\H^T\X\dTTZ`T`VRXVVVXTZV\\`\RXbZL dT X N N ` d X X f X NLHd^T\ZXJTPPTfJ!T!#H$$Z%^&)(b)`(+)\*))F-P0+H/h/`.R-0`/`1101Z1423^3Z5N33`3144^35T43\3V4`4R3T33h51T21V101/P12T/Z.1Z1T1/0N3//L/^.N0/\0`//T0-0P2\3//1J/1/.\-/+-N0J02X0X,N..--P,V*V*+X-Z,*N,b+\,b-*^+T*^*\*+Z+Z*-X,.-J+,0//.X/`0V/10P2N1423L3//0Z2\3Z24T4Z23\4^5V4\67^:9`;T@=BPAL@dA@CV@TECVFETDDDCC^GXECCC`ACfEDBV@AB@CbCTDAdF@b@CXARCNBA@BCAfB@`@@@P?Ab@AbDDVBH\ECEFLHDEHDZFVDNHDXCDCbCTDGFHFRHGDDBNGEHHHRJJ\GEHHRIRIJJKKlII^JLJPKJbLNO`PFPSPOZO\M`QJVMVLONXKVJ`KH\JHNFNFPGXFDZFCDXDAABADbADRBBREXECfBDAAA@`AR@?=?>R?X<;X;>Ab>N=P=>X=;Z?RAT?H?T??>V;;>=d=>n=P=;^==L??\?CBBdD@PEfDHEBETDLGFTGDDfHJ\HhGTF\HLG`HTJIXHHBHDVCXB\ECAGB`CE^CTC^EGCREB\CDRDCFVCVEBCBCTCZECBBBRDNEELDXGbGGRF\BDZEPDGDEBD\@?@@dCCXDJFVEGDNFD^CXBB@EVCXDbBADAAV?>B@dB@?H>=d=@>=A>>Z@P>ABZCCFDLEhEETEFRCHGLGJREZFGTKNO\NNJMJNJ`JKTRXG^NVNBONRP\Q`PnOLS^PTMSPQdRNUQSQQPL`OVLXJZIGXE\JNGZIXJKbJH^GGDDXDABDXCbCCVBACHBCCPCAPC@@P@`BRAbBbDLCBC\CbCCTFVDB`F`C^IDIJZFPLIHHEGHIKdJ\QMPMQP\NdMNXOPQORTPRPQPOfRPRTVRRRSRV@UTRXVVUTVVPSbUPVTUQfPTUONOLNMKIRH^HD\BPCRCBBX==`=L:;9995:66P425151L3T1V/^1R-.1V.1F.,T/Z/2.L.-L/d0X3P02P/L./F/./P/V0.Z5V34624X4231H5N7T6h3`32Z4`6J9V7P7N:h:d;TV;X97;<6:Z886<976R7V8R5344V1..L.X/Z.b.Z+@*+^'&H'%$#T#P"!N!\Z"L "JdZhTZZRlNRXP\XX Z ` J X  d`bL\T`FP@\TL\PdVXVLHh\XR^\R`dTX``\XVXbVNbRV`ZRbhVZT\TPVTZR\ZjV^N\FV\VFbZXdNVT^`VTTVPFTPPZ^FNPLVLDVTV\bVVXNfNb`X^dRd^Xdd^`F`XPX^b\PZhhjLLZ\TR\XZN^\\PRRXVRbd^fVRTRVFl^\VNDZJhLV^VldTnVZTj\PVVT\JXbjVfZ^hR^ZXbVVXF^`\jDXLPRXPP<^`TTPZ\TXV\RbZR`DTZ^`ZZXXL`NRVbRZDTBF\TVVdZPPTRXPPXTXVPRJP \ J X X P N XJ PZ^bLZX^XRPV\ "$#\'N(P%'F(b)),R++Z,)\,T,-/.1/H12/H02/`31d4R22^6^5F34R3317Z2N33J2V7`753313b213V//10V03//\0V0..0.V3Z-0V10/L0V/../Z0.Z012\0.1./,b-V0.0X-.-,,,H+*,X+L,,X..R-f,*),*,`*,R+R--h--^/^-.f0Z.Z.X0^0N.J11d1R0d11P3T35Z2P2V211L5121R5Z4V5754N9:<99PBBRBEBCRF\CCXFRGBBD\BRB^ENDBEFCZFGBHB^CbC@BCVE@RDAhBPECC@@FATCAJB`AZ?X?XBPBCTA>@HCACLDCF^D`ENEEFEVFCbDGFEDFRCF^DVEE\FGZGdGbIDI^FGHFVG\HLNKGHGH^HHGFFVIXIXJPNNLLMJVJRKJONNhOMPNMN\LO^KZKLIJJHTJRJDLECDBEZEEAAA=?VAZDBZCDLFbCJC`C@CB?@A=

>\?R<;;;>^<@?=<=L=`X<:V=X:V988N;ZR?@@f@H?T@?>V=R<=V?=X@C^@^AXAN?@NAC=AZ@BCZCNDJFJCE`DFlGFF\EPEDEFZJJKLHL`MKLITILHL\NJMRMMMNZSTNR^PJP^STQ`QHQRTTfTRRPXPQOMKVIXKJGIdMLLIIHHHGPHEEXETFbEC`BACEE`CPDACAXB?@BVA^@DAZBBABjCEBH`EPFVFFFXJTIFJIE\FVEFdGXFJPJnKTKMLOVNMLMJPdPPPPQ`TPQXTVRdQSNQSPPPQUSTYRRUVTUSNSHTRUJRZUS8QTSQNONLTLL`JJMHIH\FTDCABA@=Z<;R9J9886P7X8^5P441J31Z231011\4--T010-Z0V/h.X10//^0R13J1\10/0\00.341233`1\1\4Z4Z33J457T6598R7T;7N7\7\87678^;F;9V9:;V=N;=V:9T9f8;b9=;R=9;L;T=\?;L8T8\97T8`87Z9^77\966655R42V230-L.d.D./T+)'*R&Z%P&%#R%d"#! b Z! F^XHV@`LLXJ\R`^PTXRX Z^ X J L L H \ ^ZZPnRH^\ZNVdTZZRX^\`VTJ\\Lf`ZVNPNX`\XZZZ\XVR^bZLPLRNbVP\RXV\\^`fXdbXR^PZPLR\VRRb^J`LdP`fRN\XZPXVXTjTdPL\TR\PZfN`RfXjj\bX`PVZTZZ^`HhDTd\XX\^XjVjb`jVZV``VfLT`^\`X\\\RRVZ^VXb\VTX`ZX\J\F\Z@^^TV\\\XFbZbZ\H\\^HZ\\VX^R`b^ZP^VXTTRRZbXd```ZZPRXN\XTJN`Pd`VVZHTLTZ@ZN^`^ZXd^\Jd\T^RNZVdVRZPd XV  Z T ^ ` XRJ@NTXRVP^ZdP^VR`\VX T#"""#&d')',)-)^*+b+,f,P.X-/-b/0P0/0Z12323d1^24Z2X75V24N1\35506574T22X321212^2/12/Z.L1/2X/V,\0N30.b1.b.0N2^101/`2R///1.03P/^.V1R1\./N/P,,P,V-+d)T-,P+b,-X,T*F-V,\,,,+\+X,X--*Z+Z-T-//X--F,-.F,N1/d/00^2H24b4F4P521.1f3V2R6R54R33P67b7R9Z9b9:Z9H=:<<>>><;@T>@?jDCFCE`CRDNEELGD@HEHFRIFDVHTCDZGDPKNIIPHFGXEDIJHNKKJIIKHFPHHJJPIMK\KZL@MKNJPLTJK\NNLN\NNdJRKTLTO^MdOKZKPKHITHRF`FFHGLGHH\GDBDX>PA??CH@bDTBBFCX@NG`BB>RA?TA=Z?X@=P;=:;;=P;TT?=@Z@@RBHCV@?N=\?X>R=`A\@?`AR@@=V>>B=R@X>AZALAZBACAVDBDRFEVKJHHG`ILPLGGLH\GCG\IFJHRIZKJILFEXFVDBC^FPDDC^CbECBFDTBZDBDdGERFTEZEDHD`D@DDCPDBTGRCETCVGGJHbEVCfDJFTEEZFARC\@CRBDPDLDXEGEHFJPEdHBXFDTDCCD?F?@X<=;L=^=P>Z>R@\@Z@A\>>N?PAZ??@H@XDTDBZ@>^DBLCRHAXFCNCDEVDZCRE`GFHTKIOLZORJLTLhLTPXLNPM\NOJN\NTQRLQUQRRXTZSS\OWXRSNPPRPNPM^IKJM`MRJRKLZIPIVIJNIFGPEHVF\DBCVCB@BREdC@CNADAABAAdB^EZBEAbDJBZDCCBBZCPGEGIVHfE\FGREGMTITMJ^LK\MNXQQNORNPQRROTRS^SXQPS\QNVOLOQSRVQUVSPVZZTVZS`RRPSLTQRQ^O\NMNOLNLKJdJIHIXETBEA`AABV>9Z9\;T8>765R5X3221R3111110Z/0b/0R/T/-P.-/01\.B2X2L0b1.0T//,.1/V24P2412J3Z4033N4T66T6F76R88P9`=:6`777b:L9VNbdPXTPV`XZNBl^TVJV`PZVV^J`TTHN^XRVZ\\d`R\JXTZfLVZTXRZN\V@T^TXTdffDLhTP\RJ`\R\TPL\ZZTT`NXL^NVNPZR^ZT\ZJ^NT`TRZP`ZTPZPLTT R V ^ R Z T F X P \^RTVXdPTPZLZN\J^PVZXRJ N Z!V"X$&%&%D))X'T***,`/-T-*N-0,V/P1P0/12X502h2N5X2P3^5\635N43J53P2h7V6P3P46^341T13H23L5b211P0b0/.`.^/V-L/0T0b/1f0/b/-32X00./P1J/21//V.T0/R1V0^-V/T.V,.\,,*J**`++)P+H,P+N++\+*-B+H,L,*V(\+,+^---J/.^-L/P0./.00/D/0X21\2V3P2Z21J223\436376`8B;7V9H9FL:;Z>=`L???BNGPDDNDdEDPADFF`FNGXFLFTEXG\HHbHTFFVCDTEF^ITIH\GdFGGJJJKKKINKNIPGHIVKKDKGPJHXJ^LOPNLK\IRLJPLPPOFOXL^JXKMZJdJJLJRIPFLINJ^G`GFDXGGTG^EjE\C@J@@@TCBBLADVCDRACRCAABCTAJ>H=N=T=<\=<^;X;;V;FZ<<;:=<>>?\BB?F>\=H=N>b=L<=?^@RB^AZ@>ZB>>PCDCZATBNBBCZCTC^G\EFG@IZIVIXEPJ\JVLGZKXHPGDGTJRH`JKPNNMBJfLELDPFFFBCZFDZEFFPGDHDDE^EXILFGGZIPHZHPECDZCDFEPFNCERCZGTGH`HTFGDEFFZB^B\@@CTGEFTFDFCGTFHFBTEEZDHTDRE^A@P>P=;?bV=T?=b>N?@@@A>f?@^>X?`BVB?XB^?BA@BJAERDTBXDXEECCLF\EPHIKXKLJLMZJJJM\PVOOQ\PPONORQZQJSPTVQNTLTTXRfRPVSLOOPQVPXN`OLKJVLTMMPLLXNTIHKTHZHTHIPDGDVEGTFAEVAD?TAXCCdCBfD@ACBECPDJBbBDCDNBVFCE`EdE\HLG^E^FXJTFPHXGVIZLVJZHLKNLQRQPRRXQPRNbRPVPRTLQRTQQXSTPRPUTXTFXXRRPRTRRQQPRUTQPRNDOKXKPJRLMKHHVH\FXEEDAA@B`@?;:9;P8\8X7854Z2403j6Z21N3N4V02V.V1V0X0..D.-\0R012V2P//d2H.-X00D2V0.T0\/b1T24T3R3H1b10T3333P7F67689T:^8T8\6X5R6P6R8L:;^:XAV<@8;=:XB:;R<P97\8P65`532L2T0\/0f01,R-^*V'\*((P*&N%$\%V$V#"^"Z" !"T!dPZVVN^VdXN\HRTB  R N H ^ X R T ` V T D J\\VRZ XFNZb\b\<^X^hF\LP^TT^`JLbZVRThTHXJTVVVLRPNP^ZTTP^JNVRZTPNffVTVHP\LXLVhR^Xd``jZN^bVPPX\PRZ``\T\R\\fTbfZV\hPZPbZP`LV\VbTjblfdZbbZd`h^XZhZZbdj`XjdVNd^^^VbZdRbZ^Vb^Xb0bb^fPXdLVbTL\ZVVF\`d\^VL\PrVTRPVRX^^RjR^XZX^RdTZXXVTPXVTZTdXZZd\LLXRffXT^LX`bRNHl^VLRJZH\`RTXbTDLPT\ZF^Z`RP``\XPFRVbrXHZX j X \ \ Z L b ^ PNTPXZZPTfPZVN^R^`fXXdZ !X"#`"\%J&H'()T''*R++d,++-,-P-/L100/^2T1V2\422F4F4V64V3J5Z49>54^6d664V54512313L21/V5.1d..h.F-^2.0-.^..0P/0X.10N1111\/X0/2-X.,,/3/J,,T.Z-,,(++R,J*R-**J,T-H--N*'*+r+`-L+-,H+/H/-,-N10.X0X0///`0X/1.f203X3Z4623V424344^55\78\999:::T>T9:;R;T;;=b@`?B`BB^GGHDPEHEVEGAAECRCVCF@DFA@DADDGZGBEXEPCCEBCD@@>@NB=AJChAR@F?X>\AT@@RAZ@@A@AVF\DCLCEHD\EHDRHEDFGNG^KGEPHXFPF^H\GETGTFNE^IDIIGKZMTQMJJPMIHIJIIHXMLTLQOLLJKLK^LZLPIXJH\KNLVMLLJHJMKDHdHF`FLF`KGLKGEAXCAJ>TBLC^ABFDbCE@BRA\AAT@AAR@B>=>V>bA@^BV=Z=;=<^;:\<^9:99L;XL;=R@<\@d?Z@ZBPB^AB@R@X@?>V?@V?L?RBA?J@X>=@>`DdEDRDXDDTEFDZGF\JI\GGXHXGG^HIHIF^KITHXGKZHKLPMXMXLJXGXERG`FKDEFRGFEIETF`ELDEIPIHJIHTKDFPD\FPJEEDREE^CLETHG`KbHVJdHPFCDAP@AALCF`EJHHGC\HDFVHTBLBZEBDCAdECRDB?j;=P@N==P=R@D==B@D@N@=@?>Z?@^BJB?`??@AbDXBRBDTDREEDLHZGZJGIKPJMO^OR^RPOOTSPQSP\ORRPUTQTQVQSQNS^T^PXUNTLRTRNNOPN\OLM^NPOMPQMJHLJIHH\JIGFNGGZDTFBGATBR@ABPCdDAACBCABZCTATBABXE\CDDE\EGDGGEFVHGI^HRHZMTKJL\NTMDPNONPMMOLMXMPOJNOONQOOVROQ`XZQUTUXRVLVTQZPNSORSOOM^NRMVLXNTLNMJHFRHEPDDVDLIB@@LB^CX=?L@^AjAVCF`CTDZE`GPELJDREA@AEAFDXDEXB?hGDbJEEGPDZC\F\C^CB^E?\BAA^@@HADCTD>@@T@T@P@RAP??^>AA>DNB^CAD`GEJFIGHHF^FH`JJLG\GZFbJPHIGFHLFTHGGFKNLTLNL`NXKVJLPMVM\IKLZLNMMLRKKJHH`JKMRKKZNZMROLMVLPLGIIJTIXHVFGRIIHF`GXEfGLCXC@X@?RCXAEJDECFRCbBA@ABAC\Aj@?>?V<;P?<<<<=V@BBA??Z<:`<\=H=D;`:V;;N;R?B;=;=>dT>X>XAb@B@NCAA>>=F@^?<>VC=P>=b>AR?^?ALCAPEDGDFVKGKPFNEXIITGPGXJFTFIVFTJ`KTGFVGINKTLTKMKLOLMZKRLZFFVGGEGGIJFPFVEFXHZFJEZGJTGHVFTJKDRGVFTEEPHJEICLFFCFNGGIVHFETGFHEDCBBZIJDGH\HVIGZETECXDZELDDNDELBC@VAZ??=<<\@XAB?>>=J===??>TABhB@@d=8X86L686P:8T;:::7R:N863N5X231Z0/`/L/+,T,T)'Z((()Z(&&$#R$\"^$R!V#R!f T\!\XRNPXN@VVVPXT fZ B ` V X P P b X V ^ZXRZh^ZZdJbhTB\NXfV\\X`\RVNR`XBZHT^T\LTZbLT\`Z\bRTdVh\bZPf\VZ`F\T`TL`RRVnJNbPfN^dHhZTN\XdZT^RT\^ZTPZ\TZjTJZdT\XdRPNXHNLTXTZLDh^`d`^\``\XbTRZL^\RfVV\RVZ\NTjd^`Zj\^lJR^V`fL\XfXZNNRVRZ^VTJRVF`NZNV`bTdZ`bF^T`\VdJVV`^ZX\bXdbPZb\`dHb^^LJX^^`VX^^L\LffRZX\XP`R\DVBZ`RVfb`R^LJ\PPJVVXXVTL\V`\P`bFRXjNX\NXJbZb V L \ \ N N N X N `Z f  \XJ`^db^NXdbX`fZVl H#P!$H$L'$Z'V&f()&+J*-D+-Z.V-.--h/P0V11.f2011L03Z5\43b4J7T556V33F6T9J6Z8^768V562450j553P3122R2J0\1R//V.b.-1T/,/V.0B0b/1N.//T2R20R/-X/+J0/.^/0h1,V.X.-d-^+-P-X*R)*)^-`*X*N,X+)+L,P*`,'^+R*R+^*,X+,`-H/R020T4110101//d14N22T443J4R32334V677\75:Z==L<9:VAdB^?VEPDBCPDECEBVDRDDLAZ>JBC\F`EB\A@EBDJDGFEPEBHECJDBBTEB?`=^CT@ZA@BCZB@@XD\@=>@?>\?X@JAXBDRBTBAXDRCRFXEPFVGVFVJPJVKFMKIKGZJJMZKTF^MTJKLLJ^JPI`KZIbM^OHLZMTJMNORKRLILPVMZLRMNLFLbJDKLJPLNVKLKNN^MXLLOJFJIRFLHJGHIHJTFE@JEbCD@A@bCATDDREGCDCB?@L?L?CPB?B`?ZA?L@>@@=j?X<;:\:X;<>N>`=J?=R>PA?bA?b?B@@PCAR=@b?V@HAXBVDBT@?V@@Cb@C^BDJDREG`EGG`GVGGXHdIMLJNHRMKHVHTGLM\GFIHZJHHXMfM`KTNVLLOJGbHH^GVGVHFGLFJHITGZIPGdGZGHF\HHHIK\KbMPH^FPD`EEEHDFEJGHFHGEPHEVIGEdDNENJHTJ^JXILHRFECPDC`CEPCB\ADACXAF?R?V;d>R@X>^@>@@=b>>NBTC@\A?d?Z>^>>=RAP@P@AA`>V?@NDBNDAVEXBAELFFRFH?:;T:T9V<7R727Z5R63133X11P4X30J1100//L1`02/V/T0\3.0.X..j//^/F0H/R/Z00L/^1Z-0.1D3\3T3`4536N6b8X6l66T7T5P74J7P8667^97b;\8Z9^7:P7:V::::X;BPBBACDEB^DEBCjETEZBC^BPBDCVC@BZAJBDDNFEXFRFHNEFZFEXFRBXB@;@B`@NBBRDRB@>VA>V>AN=L??@>AVBJ?RB@ABDRELHRGFGHIIPMHKOVJKKPNXINNVNTKPLPNVMLJKINXMZILKRKI^MJKNLKZMKLRNRNNNOMZMXM`MMLI\MKPNLLLHFHGHXFEGPLHbFVJHIRJNGLFTADTBN@B@>BBLAZCDAREVDAZC>N?>B@hD@bC`?;X=>;>X?N=J@d=\@=?=R>J;:<\N>=N@T?@>T@P@=?@PEPDP@>@@CT@P@CBAE?TBTABBRCHD\CDDVFZIIMLVHVHTNJRJVLLLZKIZHIPLLVJBHFLEIIKLJLKOLLTNNXLRIL^IGRIdHHNIZJVJFI\GGVHFHHFLKKTJHKFHVHEFCRILGLDGGHbGDIIbHFHGZKFFPDEFGFHFFKGHFGPDGHHRGCFEN?ZDA??<=P?F?=B>N>R?ETAA=D@@@>?Z>AbALC=>=h?@AA>?BB?@JA@DCAPIIGJHIKZOLONQMPMTQNO`LVPTQfSRRJRQRHPP^RQSTRQROMZNMKPLMN\PPOXNNMdMVMKJHKRM\IKJXKXKILIZFGECABNANDCBEVCDTB@DCRD@BBACCBFbEFE^CFEVGRGRHCNFENFGHHHINNNMMRLKKTLXLTJDK^MVKLTLMPNLSP^URXRSdVRTHXZZJUSOFSO^SSPQRRNPPTNTNLKVNVOJJJEGFPHGTIJEFHCZALA=b=98854L6X7N4L4T3\40J0R2T231Z12N30Z0N/22`1V1V3b0F02V1,`1/1T,/L1-20/0/^/b./01\1V6J57T53H5T4776Z5V5T6h5566f68V77986X:8R8T8<^:=7J9d76N5677::;Z<8867V5N43H3L2R12/`.-T/V--.()(*R+)R('&Z%$$`#V#!!!!Nn^\THTTL`RbZT R T P V h P Z X  R Z\NLZf\`LLLdNZL\bTRRTbRLXRLRZ`N\``h`JVPP`^f\ZXfZ`P`XT\bP^VXRhX\\RRZffVRT`X^PZX`RT^dVdVPRT`\XPJ`TXN^TTHX\XZ^fNdXRhZVXHf\d^PXd^\dNdh>VfJXb\XbL\XbpPbXZVNZZRbR^PXZ`ZZT`X^X`jfbdXbRRRT\XbT\PVTXfNVZ`PP^hVRLNXJZTXVLLTN^TTlNLTJ\f^`R^TZZ\^`d^dNN^\ZPV\NVHT^RVXB^`^\VbV`H\XRVLVVd>LJV^Rd`VLX^NbV bV \ R \ H R X X V RX\VZRT\R\VZd@XPZ b! h$H!#$$V'%X&(Z)\(^)*(-P,`.X-N/V/--Z/N.0V1/02/33F6R5V51V4N775R575^7P6;L97>Z7844V4J441V3T14510-.b.R0N-.\.H.T-/^0P.T01V.-^3^0F0R.P1J./b/.T.f-,./\-,D/T-R-\/Z-+V*(*)Z+*+*+Z+\.+*,Z*T*)`*N+^-L,X-,\,^0^32/.^3P/Z0`/R1^2f0T3b1V2`6R323P3T4T24R538`5T5Z566X7:;X=T<?=>AAd@DRDfDRBZBFCVB\DBBFEbDAPFZFTD@@ADdDFGIfIHFFVFZGCEXDPC@@@V@ABD\CT@@>;?d>>d>>\AVCV???Ad??C\CIZGHEERJ\JRJVNXLJKZKLRJLJJdLLJTKZILNJZNJL\KNNNLJXNNLZOLVLMTNNQ`NNMbOMRN\NVLIKJITJXLLJZJIVHGZHNITFdGVIHJHFEXFDDZCBCAL@VA\AA@`DDBNAXC@>=?PBBD?R?X<<:;^>=R@^<==T@=X?PAZ?Z=\AHFAB@b@VBR?X>?@@b@R?N?XAX@BhE^EVAA\B\BFbFECZBZFLFNFVLEFPKIL\LJKVKLLKILNJJMVKNJIZH:HZMZMRIIL`NRNXNM`KRLKJGXH^IGIbGLKJFILPPVLHJG\GPHTHPJL\JPKVHIGG\FFDEDDTEFNHPGFIHGETGJKFFHEIGG\J\IbHPIGETD\BRETFdEXBE@BCA>XA=P<>>T>?J?>LC@?>\?`Ad?F@>@`>;=L==:V=:T:`74Z74X56\3241Z3D2T1/33/X//b0Z0V/X1.d34N-/1\/^/R-`2T/.+L/.-10^.`..-Z/17J35X6H5528H1`2P2\6X6`6N5V6b95f:76L:Z7R7Z8\8`7H7X979:\8:79^:<7:8^9^9X57X95Z=<:T:\8\8Z465P742b2J21T/.,d+X/)*b*L+(d+b*+T*()%'L$^&`"!!"#R"` T V P!` NT`TVX^bTT\RTX Z D ^ Z R V ^X RTZ^TRZZRJN^ZVRXVXZLVPZXZbT`H^jnBTLVTTTPPVVjRNX\RZNVZ`X^PPXVZXZXNXV\ZVPLhLZXbHJVX\hV\\VHbVR^\TP\Z^jhRRXVZTL\`B`^V\Tb``Zd^^\f`ZPVjXdVRV`Nd^XbbNJPXNX`NVXN\T\ZNXR\RbPPN`VL``V^ZBXFJRZ`\TRTVP\\Z\V^LZTTX\T`RXJdRDZVZR^\^Z^PTNVTPT^R^XRXHZZXVRX\L^PHZJRPJ^\ZHP^PVVPVVPTLNFT\J^XRNTPL^T`XTT<f<TVNVVXV\`X B P V R V b N \dVTVPRZ\VZ>Lbd"X $\#P&V&X'`'N())Z+)P+*+,R.^.\,F./\././.2X2V335V67V512\4T:6V6H68P5776Z7:566R6`4H431313230/\//0-f.L-d.T0/.V/P/P/`-b-V/H//T0d/X1..0P/b.X,V,-.,T,R0,b,N+T(X(`(X*'N)X**N+*X**Z+,`,R,Z*B)+X+-P.,,-N1/10\/.Z/\/H00>/1V21T1V3233T4Z5\6d43T54`5b78L597=<<;;N=\;h=ZADABPCDDABRFdEJBAFJDXACRF\DFBAEFE\BD@FTFEGTJIXHHDDDCbEA@ABRDZAAA\A=V>?CNBHEBA>><;J=@R?N>?A>>b>;X>b;:^T?F?\?\@ZANB>?R?f=N?>`A?H=>V=R=N;?N=V=R>?>J??AA?ATBV?>^@APCbAPBBRERJITJIKTKJHXKNZJNLJLOVPOXMNNNOPOPRQSZQMO@PdORPJLNOVN`MNNPRS\P>RfQPNOKMXOZN\LLXNPLLPJIHEXFTENCEZEAEDEHXDVFZHXDCEFC\H@RBCJEDTCJEEEDNEAAXC`ECRJTH\GGJ`JJKRNVKJIKTNKKHMMTKZNZOFOQPVUTQBTObQQRPVQTXQRPQPPRVTZTUTPTOLNTQMJLMPLJKKNKFHGH\HHIFDD\>r?J<^=;;T;R8566D74P320X0`2\/^01P52d0H/0V2X/.02V0T2h.N3X/.Z0T./`-X-R.d--.,.Z/Z-b.04P31P5\5P42\03Z3Z3`4X63`4`559F955354X8`:\95f67999;X:P98<98J:;96^:9\;N9T=:8X\=T=Z>R;;=V=?@\=V?C?XARCbAXBTAPCCDIHFHHHITJNLHLdKNLZKXM`KfKTJJXJ^JHJhMJXNJK^JLJXHPKJMHKHMOO\OOQMRXMOLLXPNRKKVKKbQKTHGIVLFNIGRGVHXFTKHHGNHVIFGVHFCPCZCPD^DCEDGCECRDCHC@BZBTB^BABLBXCZ@R>X=T>b=X?\?=b>>d>=T@;=>;=\>^>XA@LA>>JA@BECECXD@L@LAVD@@@bDTA^BBDPCXGE\DDGDCjFDFFDJJI>IXJTL`IKMMJKJbLXKLJJTJJJXIBKKJTGHRJNJLJPNPZMMPN\IHIIJGXJJJIGJ\KLIJXJLIIIPIfIJFKKIIPIHHHVJBGHEJHRFTIHXIGXHHGHRKPJXIJIGIHZJJJGIPEVEBDBADdEBDDPBTCR>=V@=J?>@N>d?\?P>T?^?R?=A><>:P<@?=>T?=FAdA>N?=>X@A\?\?T@R@N?FABRDPDFGPJlLPGKHGXIGIJVNKbMNXL^POM^PROZPQS\PPS`RNLNRMNRMMRONLP^OjMRQQTQhRTORSNfQ^NMK`QPNNLK`KVLXJFGTF\GTGDFEFJDFFIJXIGDTF^FRCbCEBXDRD`EFE`FETF@V?ZCAG`IIHKMNIXN`N\NRJ^LLKKLNVM\KORQL`PNPZQOXNRPLRNRRR`ORZPNPTSQPTT^SVORPRLMTKLQLJbMJfLVIHIRLVL\HFGDA@=<=J;;7855X8P4T6V51F0^3010X21L010Z0T./H11/1.../f1Z-.^/-.,Z.J--,Z-Z/.-0P3311L522V031Z2X3N7R265746\6245P6f56V;T6:R<\9^8:X:X88;:8V;N7876:9^:R<\:79T6L8^4b4V5T3^14b40..--+Z++R+T,))*)P+b+Z(&&b&V'%$#!!f#P#!Z!!` \PJ^VTT^RT^N`NX V T L Z b V ^ P X NX\`\VbZHZ^fNTbN\ZXdNZR``\bHR`VX\dbRVjN\TjPL^\\ZbHZ``XjdV^XRVP\XThXZN`bP^ZTFZZN^ddRHT`ZZ^VRTXPRZXZ^^VXVHNVZfJXrNfXRfRb\TVV^b^Vj^`XbDTX`^TTD\TVXJV`XTZJZVZ^PTP^VThDBVXT\TR`XNHd^\\`PX\VNNVXRVLXPVJZVTX^\^TZR^TNbTH`PZPb\VRVF\RN\TZPH^VJB6HPjfVTPLPZdRPBTbfDP\XP^@f`VRN4NZRFZ\ZRRZZRHXXrT^XDP L ^ b N \ Z d RXTV^XLN`VPXH`VZFZ !\"#`"H$&&\)Z&')(P*'\))*)+-,,R,,H2\./Z01T32`4Z3554\444V97P885Z8H:Z7f:D:f8J7V8R7P65<8P4\4T4b23530Z0/R1/P0\0R1,1Z1-0/-L.T.\-.N.J//J.V/^/--..0X2/.0-,^+,)*^)Z*V(',))*F**P,^*Z+`-*+*b+J+`.,L.+*.b,R0,,D.`/X/120\11^2T4X24^26124L5b4b78789T:7:::<;Z;P=>Z?X;VVBL@@^AV>VA=`ADX>\=@Z@J@Z?@P<\?P@V?>??X=Z=\@^>>JDB^@PB@=XAAATFTDZGVD`BC^EABJDC\DDZELGXCRHRFRFJFFRGEHDCTCAXGPHXK^HJLLNKHMNKN^NMLZJGZMVK^LLJ^KHFKJKHGGGGLHMNLXPFPMLHHKBJJGHJNIfKHHXGIZIRJKZMRJLGHJILXLdLVLRKVJIKXIXFIJ`ERFTJJJLHGHRFHHPJJXI^JVJMJIVJGFKJZIHFHbC^A\AE\AB@BLCd@P?P=>AN=P>JBAfB@=J?@X@CBbA=V<<8T=>;;P=Z==R?>R?B=@BACCH\JFERGZDLFLH^EHIJHJKLIXJLNNNSTQdPRLVMTNOXNPMVMMPVMNOVPQTRXQRSOPPZPPPjQO\NPPPNOLJVMJ`KVHHFREDHGVFCGEDNFHEVGTIGGZFFXCLDLETEELE`FFLFXCZBXC\B@>\CHLHGGXGKZJIIKKVMJNfMMVNVNRLRKdOZNPO^MPTQO\Q^ONNRQPRQNOVQPQPNSXR^QQVOJL`KL`PONJlKI\MdJPKJ`KLdLNKIFC?FX\fZZXR^HJRdFX`RTPVXX` b T Z \ X J T ZPb R V bRfPDV\X\TfZN\^RPjX^!#!##Z%%&'(P(*Z(+(),T*Z-X.+\/-V.L//3/L5N20^42V34J72^586L7b7876b6X;`8T86J776R6`54b5633T3P5d4V02\01V1\0V0/2//F0\1/P/d,H//X/V.d.N.Z.R.B0f.01.J.X.-V10,,,,)N)^+T(T(d'R))'(T+)j*T**>*)+-^,R..,,+f.,\.0L0/00V001v233L1`2N3V3Z03R3\3d58`88^988^77X;Z9X<=r9<:H<==fDBEBAVACEBB?`@CB\BhBTCCB^CBDA@CLEGFBPFBC\CLDCTCECBVAV@@@HC@@?ZA=T?=R???@Z@?P@NBA@ECGNI^ILJTI`JZMILPHJdKTMKTMLMNRLHNMPLJLKPOKNKXLNJLKFHLJMRONRO^PMDPKVMLLOJ`MMP^NLPIIIFG^IHPIbFEDEE^FEZHbGPHGNHZEFJBBXEDDZEZEG^ELEEEbFbBNFCbCLEZBEBDZBPEBHATBV@P@TBX@NA^?T>T=H=`?>?@B?P@@?@@RDVACF@APCTEL@BPE^DJGRB?CdBHBCEFG@IEHFHRGPJRHMHEXC`DFEDVG`HJIXOFJZJ`LVQKKVMVN^LHHKL\JLJKIdJFGPFDG`IG^JJZKNLZMJTLHPIfLHKIPIGZJZIFJGL^IJ\HHBHbJRJJJTJNKL\HKIIBJFLKZKGBLJPHG^=>=J;A^@@>VA>PA?>L@X>??<>;=\>X<<=BPCA\C\EEZEFHHTFIJJ\JJJELGHXOKXNMZNQRPQQRPMQbMXOMbMJNNL`MPNZQMZSRNZON\RONZP^TQLMLZNRLLMMNHNH\IFEEDZHFTIPEDF\GJJIEDVEERBAEEJEEPGNGfDCEECCBPACEEbK\GKIIIKVLNNLMMZMXKPJMKVMXMNLVLJN^NQPNdQdOZPRR`URPRXPFQSNQSUOdNMNJMQNOPN\LJJNNJbPZKRL\JHLK\GEND`A??\A>RBRAZA??P?`BA@V?Z@ARCXEB\FRCDGHMJZMXLZLRLTJIXLKML\ONPNRM\R\M\KVNLNNNTMMFORKfNKHXHXKN`NNRNP\PZOQTMK`SKKOVM^NPMLNLIIHHGI^HJGEjFHLFXDHGEPFXERGdGXGZEPC^BPECE^DBEFAEDDC\EGENC^D^CCC>DBPCRGCCnACNAC?>b<;N>@@@BBAXBABXAXABVBdFHGFHCD^BBfCBV@BBLCBEDBG`FHDTIFXGJNIHXGHHECGPGHCFFNIJI^OTNbLNNLTLnLPRMTNLKIKJIILFHFE`FHGHTJI^LHTLMVGRKHLPJLJJBH^IFHHZGfGGHVILJJKNKLJNIXPDJGIIRGF^GRGG`JJH^HVJPJINKM`KZJRLMTMMNIXKPLZLbJPHI\GGCDNBRBZA??FCJ?BT>L>?=R=>b?>>?>R?l<=>V?b?;=;:P:;N=P>R@=f<@=J?P?`@XCDCHDND^CE`FDG\EPHK^KNFHFGZIHIPJXNFMPRS`POTZRbOOMPNdORNhONMLPQRORPOQQXQOZQNPLPNLM^LNHZJJL^LIFEE\F\J\IFTMVGHJHFJZMFHFREEDZFFdEbFCBZCCAZDJFPECDGFGVHIL^KJHL\KXMMLL\RMLLNJMLHRXQPXL\QN\PJNRPL^RJQ\QRRLQPXTVNVPTST`ORNOMNKNM^QRVPKTJNJKNIRKJFJHEJB@\?AV=L@P=d^^dfHZR``b^^FZX\bhLbPVZhVRZVdXdZT\XVNPZdZPVXPX`bNVZVPTPLdP\hHTdNNj\fPPf`hP\XT8LXRVbZR\XZTXPdHbFbPTXXRRXJZHTPFbfXZ\XbTPTbVfNT`\RXVXHJV`ZJRZTJ^PdPX T Z ^ P Z XNF d \NVXNLR`hXNVbHX`J RN#d"X#^$N%\%X)(R))+^+Z,**T++,++T+N-.H010P1R1V21Z32\6b6`648H666V7R56T56L85X8274`47P7L4d4^3463`61Z2`2N0V/110h3Z1..-//T.-h-+R-N.,P+,,*,X.V0R..Z0R01b/-V-L.b,-H-Z*)R)'\)(V*L')R*P++,T+*))+T/P.1.+^,R/-,T.0,///13H35N423474b33Z58Z7V9X<8;Z::;;b?::d:::H;>P?\Z@A@XABB\DVBJBBBBNCD\DDCBA\CJGFTGHBAAA@f?@bAAVCTAfB@?A?AV>LCfBXDZCCRDFPIIJKVJNMPKHZLJfJINRMZOQ`OJNZNPTODNdLOHNZMMNLPK\JLHMMKPPPQTQNTPVNXOPMMTJLOLNXNPRITHG\JGRLHE\GDGNHdGZCPENGDIGG\HXGFCDDrCCCBTF`BENHREVDDZDE\EVCbG\BAZBBTCBAAVB@Z?P>b?>\@N?AXB`BB@BBLCBABTE\DTFRHEFECFCE@NCNDCRHVDFFLFZGbGFVGFG\HI^JZJ\FXFRGTI\IZFZFJIVIHJ^J^N\MLLbNKRNRNJJIILKLJJVJJI`H`KFIJGLXHIRL\K`MNJJbJKHPL^KbKITIbHEGIKHVJKIJJZIJLMKTMLJ`KINIbEILJTJFHZI`LXMJFKZK\JLKTL`MJNLTMTJdJJXJhO`IFDXAAZBBbA@A@A@N@@><@>^>@?T@?B;@^>X?^=:V;L<:>V>;d><`?=T>V;V<;N=XAT@@ABBPEdEBCDFTCD\GVFPLFLdILGFHIK`IHMPXSRQQPPPRVMOQ^QQOM^MNMOQPLQRMRVQJQSQNVOLIMLNPLTNTIRNTMbKFEGVHHITLDK^JNIZKFFZIFDVGAXFfDLIHbJGDZBVBB`B`ECNDREFFRG\HVHHK`HGJVLPJRONXNKRMMFO^K`NORONLOPQIKRN^OHS^SNSQTQS\SR`SBOdRRQOMOL`OVOOQMRLM`NTJ\MTKKVILHAFERBA@C>J>;;8N852Z53\1326P1N4n6520.`0^/.T/N1P.d40T/.///X0b-V-V,\+/+\-H.-01P1..T.V0b/N0/V.4V25`3\64\435444R4X4T60X446Z6Z5N97684777;67H8\899X;N8:6d5b653\615f51L2>3P2X0X0+0.`/0+b-*X,Z-X))d++)(('V'$H$L%Z'$V#$V#%"X``VhV^`RP\Z\\XbRV ^ \ Z P b P \ d d VPZ\Xf^^LhVd\fTXXZHbRVR\NTVlRRVbPT\^\JJ^\RXbbHV`T\Z\b\Z^dZ\dXd\fZThd@dRN\ZXb`PbRVTZVXPdZTL\fXTXLZHZTVZVfb`HjZX\`d\BP`TTZT^XXBXTJTPfhdPJfXDHRV```Nd^ddNXd\bDZXVP\ZTfLR`THjXTRjRTfXJLTf\H`T@ZVXZTXZXd>jNbJXZbZbBZ`VVXZTNRN`TTZRLV`ZVNTT^HZ`LVZVbRXTN`V\HRNV^NPbFdTRLb\R`RTNXTZdf@fTRZ\NRT^ZZVT^NRbLT`XTZ^ZZNLXXDN`NZP^RRVJ V Z X N P X d TN LjNXFRVNPfRZ\XNHXVPH!N!V!J#$"R%V'N*b())(&)*L-+V,-,V-^+.Z00X.J/0Z3P2V3P32P255V6`5X76X7^7T5V988:74H8b54R6V5H5R6X4355^54R41V2\2/3T1R2N/0L0/Z1P/T2-T.X,-,J+;:^<:?T<>=;b=B>>?P>@@XBBDCV@XBbBN@@?^@>@ZDCCh@:@X@N@ABNFRDVAACGAGEDEF`DDFPDRENCB\CZAB@fA@JA@^B?X@R??C@VAFALC`FZEDIHMJ^ITIIHZJH\JPJNVMXOR`ORP^PNMNOHJVMZMJINKMKLLJXKbJJJ\K`MVL^OTP`NPOVKOTROLR^PRP\OK\LNIRIHJNHXFTLGZI^JHEG`ELHPGVIZF\IVH^FGTFKE^HXIFG^EJbHDEZCPFXDF`ACXDDXDBJDVAEZBB@Ab@=Z=>=`?BB\DE@FFNEVBFTF\CDEJGFHJPFTBBB\CEDAPEBDETDREGTGRIJGXG^GNH`I:HGHEGXH`GVIGHGJK^KKZMJNLPQKTLTN\KQTGIG\LRLVNNLNIXLHIHTJHKVIEIJZJJJKbNHPHPNKLZJFJJFGLIRGNIHFIHI\LMKZKKKKJZIHHH\GHGHINJTLJXKRMVLJPJbLJNPLPKLIIPKK^N?V>:\<;=<=;T====;=;N?@@BRFETCABBXBCEBDXEZEEGRGLFRIII^JPNM^PTA>HP9<6^8R97`75643N321V42130-j.,P-,-+^/L+`+--^++(V+)\*R*)^(%&%&$#X$#Z!J!RTZTPRND`\TXPbH`X P P ` L \ \ J X R Pb`PX\P\T`Xb@PXfVVR\X^HV<VTfVZ^RVTXX\TZXb^Z\V^`TNRddNNTbXTTXh\XVXVXh`ZbX\`\ZV\LXTTfVTXXXXbNTjbHTXLdZZPR^^Pf\ZTNZZLdZdXTb\d`TddLVd\FV^VRjdTdJV`XT^`ZVfVZTlJX\RR\\l\VZbbTX\`Tdb`fNPPP\XPXZTRZPZ\ZRVVT^PVd\\``XdRVV^^\ZTRNVRdZXTHRhNZ^XPNfTh`RPXPPT\H^hXHTZNhL^HX`T\ZXXZPRR^N\\TVPJjBf:N^hP  V d R R Z \ X H ^L\^\XJTj\\TLfJ^TXN^T"X X \ RT"#T&%%%F')('\,,+V*d*+,V,*X/P-/.\.,.0012X2V56747H7V767^7776`7N:7V6R7V4>54R44B3X3T4`3`4R5d552\2^020@30N210/-.`/./\/-/+V-\,)D.N,,b/-\/Z./R//b1R../+V*+*V''^*X(L)(R*)(*V*+,P*-+,V,R/,,--V+.\-Z-,H-+d0./0b413456T4N558`5X76`;H:^:\;<9B=Z>^><;:9>P9Z:=;==T>?=>?A`?\BBTBAVDTC@F`CVAZ@BNABA?`?V@NAAX?VEA^DFPCXECVFhBTDZFFDFTD`DLDCR@N>A\@@P@@?V@ZB\CP?BD^BNC`BLE`D\DCLDFGJIHXLHTKHJJ`LPM\LLXOPL`PFNOPMNZLVJRJ`HXJVJVKPNbONNINKJHLQM\PQROOOMRMKNVQNMVOXQ\NZK\HK`INHGIPKTJHfGPIbIVFHEFHKGHXHTIZGRHG\FPJRJTJZHKVHI\G^GDTCBBZEfCZECBCDEZDDBB@X@X?X>?`C?AAED\B\CGCCEPDGHVJFH\GPFG^DC^FERECVEPEXFPGTEFFEZGRGHGHHRIJIGREFHHFIHJVKJNKPPINHLZPO\OTMXLKRGTGEZGGGNKKPJJL^IHVHPIEHJTJLNPLJRKJ^KMZJPOJXNGGNLIGHGIZLKHfMHJTJbLKZKMKXLLIPHbGdHGIIdKXLZNKVKVJMKTLVLZML\OVK\IIKKIHDDRB^BLBCP@AT@BP@?>CHBBX@BCJBR@R@R>Z?P=P??>^f>XA?VC`CEJCDBRBABZDVDXEC\FPD^CENGTIZLLPL\MVNHNOODP`QOP^OLQMXQJHLMRLVNPTPZMNPQMUNOMVO^NPNjPbL\MN`NMJLMXKXNVJZJKIIGIJZLHIVHJJ\JI^HGNH`CEEERFGfDPCNEEXBDFPEIKZHHKK`GLKJHLJ`KLMPPXOMDONMROQOMPMfLPQLQXQXOPOZQUPQhPZQQOZNONKKOP^OZLXORLVLXLH\H^JVIFTHDBNDVF\B?R=<:d;N755R544Z5\6772333f2/R/./4L2b001.D--R/N1V0/X-,+Z*N,R-1\0b/P/^.X.L1L/.,.20V010P6N3322244H7T33\213f41^6R65447332\478L87V98\97V9\5b5R93Z4R25P6R3T4P112Z6`0V.\,R.00+V0/-+,,f,,b)*X((P*^'P(&&$$\&P$#V$R"T!! VT\XV\XLJdXXNVZbPV N ^h ` R ^ N X P bf `T^\\b`XVP``NTJVXR`\^NdB\RjbZRVVTVVX`RF`N\TTRbR`\X\hP^XRbXVPZX\TV^PL\XTfHP^PXNhZ`PTb\R\X\ZZVdhTVXZfP`bZ`FVTjLP^`FLNPXVbNdPX``\f\V`^b\T`TVTPb\P`Xb\bX^d^ZXVPf^T^^`djZXRFTbXVZTNfVbRNXT^\X\jNb\X`^X^ZXT`n`ThZZNRd\ZTdLZPXP^PVZb``^dNV^4XRTZV@ZXXlbDNXLR<ZPPbNZd\NZPTbV`V^`bjVRNNTLPVN\\PTLfTTZZP^ZZPF^PPLbJ Z  X P N ` Z J J T`:PhN\R`ZVR^TNRlNTdT Z!^ L!R"`##Z%^%'&(h(V()-(*,,)+b-T.,.V-T/.T20036P4R5h5N7X5^7X6P8N87^897Z7@6b6R984Z35F3J4b43R355333Z21X1\510`1X/.200V,X1,/\.R-\,.V-,X+)-*-T-H0f./,0/>/..,\-T,*P+)Z+()^+((-),V+,)*P*T*^-\-d1Z/P/T/Z/,T/,P.N/V.-^,T1-H2R2X2Z5R4^55V677X865L77;X:8d=<`;P=V=L<<=P;A^?@?A^DAAj@L?X@`@ATC^AJAdAVBAA>AP@@`BJD`@JAANCRD`FAEDVANB\CDDAC@T@^AR@?@Z@J?HAAN@?@BPC\ERCBATCDCCDVHIVHJHVIFGXKLKRKKOLNbQRSWRQ`ODLbLIXJJXLKLJ>LXNVM`LPM`JNMRNPZRFQNDNNTSfLVNNHOMLMJBIIHNIXIXJTKMLhLTFHIEXFG`GF\HHJIRHNKdGGKXJIIKIVJJFI`G`GEFA^CATCBECGFHNCHVCB^CX@dC\BCB\DVHCLHlGGGZDIFFLHVIFFGFFGRFG\GTGEZD@GVHHNEDZGIRI\HGFIGNJH^JKlJ`HGXJ\KTJZMK8M^M\M`LKNKNMLZM\M\OLLIdGETETHVH\KGLHPGVHHJFIJFZGHFIdJMVLLTNMLJJXLIXH\KFLKHFDhEdFVJbJVL^IJZKXJPJJJIXH\HHFPJHDBXB^BB?^BL>XCB@ZBABJAXA?T??^C\A@PB\<^@

=@V=ZAd?PBAZ@bE^CRDE\AVCECFRGDXGEZJE^JPJ`MXKNLbSFOFMdRNPdPMRObQPVNdMPKTN\MLKRKXKTQM`OOOVRQ2OfMMTMMN^M^ON\SZQXLMBKdJdMTLPKHINJLZILMLNPLMdHREJPJFFHFRIXFG`ERFZDNEREhD@XDFRGFRFFTHHJJHXIHNG^IVJ\KTMRMNOMSVPMOMSOMbLXPMO^PJQPNP\QROZQVMTPOOPbOPP`N^NRMVLMO`NXNZKKPIJBJTKTGKHPHBFFVCZDTB?\B>?X;Z;887V6\56X665L94X2P82l13^0`2V/P00d2d3/T/\-V//-,Z/1P0T+P+*V./X//.Z-+Z/V.-`0.P1/V1/1P3^4J2V0R1L2H1b32-0R.J3X13F44P3N3^34^5355R4T5R7N88Z8f9:Z76962T4212T2`420V32V4b1Z.R-f,0../f,P-,T+Z.Z-b-*`,(N*P*X'%Z'b&P&R&`'#"" f"L PXZ\bT`dV\TNV \ \P R  T F P R ` ` d JTH\P^XbX\PNZRTPZTZPN`XhVJVH`PZ\NVLNR\N^VN^XNLZdLd\XRldH\^PLTZdT`^NV\fX\\J`\LT`RTRXZVdXV^X\XXZXN\TTV^^X^Z^PVTZHNPZFbblTfdTbdV`^NXTN`N`X^VPRV\RZZbfND\b^^TTJ^XV\RXJXTLPn\jT\`bZL^TbN\VVH\XR^T`h^ZR\R^PTf`T\ZRVRf^ZR\VL`ZVZ^ZR\^DTXV`VX`dRjRP^ZX`^RP^NZZXVTPLR`B^\T^\XX\R\JbdT\\V\P`T^JdV\^LlhRLF N  d R X f H J NZNdZVfXhRT^XP^^^X!R"V "V$\%J&V#T'd'T&''+^+X,b,,T**X-\.-X-,-X.-,d/0P4X2T524X55Z56V65X:9^:8P6b77`97X7756`2\2X1141V54\65b7\2/L2P22200`12`/1.R-\.^.Z0-^.X-0,-V+H*T*^-V/\-+,L0...Z/,`,P-Z)+,N(Z(**('P)V**V*8)L*\**Z)X-P0T,X-h-X/-V/.P,/V/\).X-N...Z2T2R6X6\65675999Z9X9\;=X=P?>\=?>=R><9T;Z:;;T;<\=;@`==T??FE`C??N>>>V>>H?@TB?D^C>?l@A>@B\@`B@DBCTDDTBPDBNC EXBC^BBCL?AVAAV?\B>JA@^?>f?BR@J@PDVBT@VBbBAHCNANHREHEfJ\FVJJ^J\JI`J\NJTP^N\RO^PRPMZNLJJZJXG\ITGdOH^JKZJJZKJKLOONORNDOZPFRPJNXLTOXMIM^KLIKXLKKLKNIJTGbEGED^ERFEZJHFTGZIRHdKGfF\IHXHJH\HVGPGFG^CEBXANBPFEDXIFFEVIFDEVCAABCJFCRETEHbK\FdLICJbJF^GXIFJHPHCHPH`EZFHdJTFGGFJTIZGTFVGE`DGXIZHHGIJONJIHLIIKZNKLZPKMLNdLVLPTPP^NNJGEXDGERGKTGFPFRIXIEHGRIEGFNMLLM`NMLdMKTLZKMKVLIFH\FJZEIENFLG\JJHFTIRIIXGZLNGF\LFXIPIKbLbH\KKNLNMLJTJZKLROPbMHMK^L\MPIGRJXENDC`DB^GAB\CTELC^DCAC@@BVCBXA?^Bb@T?\CJA?>P><<::;`;R:9T:?::R?>?VC@HBAZCZBNABCCPEPC\CDXFTITJJXJ^JPKLLPPPPXMNXOKTLfO\LNNONLNJKLNVLQRORPObT\N^ONTNLPQLbQFOPRNbLRMONNfOLLPKKKF\I`K^JJRNTIdIZKGNGH^JGF`FLHPFHGPFPEFVDRF`EFIPJHFINHGZG^IHF\IFIKLTN`MTNVPNTNbOLPXPTROO`PQPOZONQRRTO`MNNMbTTRJQORPNdO\OLMLJNTJPLJ`KHHIJHZGGHZEZGCJD@B=>VN=P=X=A;`>^<>J=b>X@VACRANA?>X?R=>??;=>R>bB?@V?AAFAARBNA\AB^CBPCBZACACjDEC\EPE\AD\ABABAR?P=Z@@=@T>BN=AN@P@?AZBBJCDXEEZHDGEJGHdJNMK`LVODLXQ^OOQNPRTPXMHMJMIILINGRGLF`HLIJXNXNNJLROPJQSOKNLJVOHMMLLPMKHL`JJFPGZGVJGbEIXFVEbDCFGELFHZHGZJGVIGDZEFNIFHGHIXFEDHBBZBDERF`HXG^FHHF^HDJGBG\EC\C^CTCCBVIGGGZGFNfIGEGLIJHDXGJGPHFFEEZFLGPDG`HDCZHNFRDDEPFZIIJHJhHLTLZO`LIFPHIKRHHLL\MLLTKTKNPDPLVMTIKFIGRH\HHPHFFGJFEFNJJGGNI\JNNNJVKKKJ^L\MI`IPL`KVHLGKRFDFDHH`IHXLF^LVFHGG\IFFNFHJGHJHFIK`JIQMJKLNKPLRMKLfNMMJMGIGFXAZBREEDBXGDFFFNCB\BAR@Cb@=F@<^>Z?`@FCZ??>X?J=:>D::>;^:<;=Z=;^=>V>>R>XATAh@ZDA@>\APCTBCVDTDCGFJIK`H@KLHKNJP^MRNbMHPdMJMRMRPNLXPNNL`LONVM`MXQVOPTOLQNRNKXP`NTNPMOZRLPNJOM^QdKTNTMKKLIIJKXLMHbIGJZIGFGGH>JDRGbGFHFZGREEXENFJTIIJJTHTGEEFZIKRLJJRLJKLbPMNPOTO^NOjMZNQOKONOONNJNTOVQbO^OPMJZKFOXKVJ^KMbITGJVG`KDGHfE\HFdD@@\?X?T>V;99X;5\888F5h5X562R1V32Z31^2Z2P0001Z40L00T-V1R-/\,+T+\,*.-,,0Z0*d,^--T1X01031220P3`0/Z10T0X12V0H2/1T1R41H34Z30Z2^55586^6j68=89X43^75135X3`23114V1324Z/\0./f/X-T-X/X,,)Z,,V+++)\+*V*(J&P(%\%$R$P#P!#\  \BTVZVXL^TVbTfTjTVPL^  R V f P X R R^PFbVHHdT\ddPL4<TVVbV`HVTTPZ\\TbbdLVZ^VZNTNdTjTbHR\XNXb\bVZLN`XFLTbJ^RZ\B\Rd`T\FVFJX\`VVX\lV\`ZjXbL`H\LhZ^TVZFJbJbRTZZ`XbVbXT\h`VZ`lRF\T`Z\^PjPX`\lTbVP`V`\VbL`XX`P^PX\\PXPb\RRbHXZ@Rd^ZR`\dXLLRXRB^LT^Zb\Jl>Z\LV^PZHVTX^^DPTVV\bfPXVH\RT`\XN`^VPfNVPN^\\VPLbXTT^T^P^V`PRRVTT`VTXRVTRd JX L Z N HXRVVTFTNNZXVP`DJJZVX!V V"" "T##(X'X&%R(`(T(T+*\,,X)+,R*,V-*\-,/0H.0V2b023b4Z5Z764F76X979j5L7768V:3N7b66L4541Z6T3f6X2^5^2/V5V20N21V2\4`201.`0J/-\0/Z.P/-,,+f+`+H+X,^-P+**N+X,Z,^..L-.*+T)+))J,R*-++H('*^+P*X*N*,)+h,,^-R,++-0X.X.Z-+N,P-f.X0H0b1H4L13h3V975@7X88`9Z6B:;::=V<;V>AZ?=:<:R>A@P@P=X==X=`===V=;:C@D@@VB@NAfBbAZEVDBCTFPDCVCdF\CLD\BRABTAZA>Z>T>PBRB`CCRC\DFG\GHbJXHKXKTJ^KMNPL^OFNQQ^RNZP\RJVIJRLHGbG`HJGKZIIHLJZKPMHMTQNQRRPLL^OIZNNMTNLNNJILEEITJFXMIEbHbERFEIERIIZHGGGZFHE^EFEXIRHEFEI`EGND@\BBLFbB\DTECEDGFFEHETEBVDDXCTDGEGPKbLLL`G^NMKTLGEXFVFEFHFFFFRHXFPD`HRDXD`CHCGGEHDJJGHJIMLZLJFOZKJJ`JKJKVOKZKKNTNKNJPJ`KRJFRIFfIFLHPFJ`HDEAJCHFNIHXJJKVLIZMIJJIXFJKITMI>LKGPGGXBJFDFIJHIVGZKdFVIKTLRFZIZHXIFVHKRMLGIKDKJXMNJVMKPZJROLNIZPBLIJGHFXDNDE@ACVEEGGVFhDFCVFAAXBRA??b=F?P@b@JCA\A=^?Z8L=;;;Z9<:@=;::R:;VH?T?fD@B?LBTATCBCZB@NCEFFRJfGDKFXMIKXMlMMMPLLMOMRKZKfLnOM\MTKPONJOVQNOTNRNOOSVPQO`OOXNOOVOPMNKMNLXKPJJJINKRLKNJJVIVHLGVHGXFJLIJGFZHHXEXHGGJCFGFTGJIXHfKLH`HBEFDGHPJL^KNLKZJVLbLbLL:8:86R97X96^53J42^3J21^12.2011X1.,+b+,,,.^,^,X+V,-Z-+R.,*,B*-N-/N/0/Z1\00/V241/R10/1j1Z.h1-^.L1121/2T34^/Z477`:58667R8353`54\5f2R1X5Z1L2X3^01/X410V0F0.`//H-R//Z.T,X-`,*^))))`+*+X'b*%&## V!#b R^  ZZP^ZPTTVRZb Z` T f X Z \ N H Z ^V``\T^J\d^N^ZXXVV\dfXZXTZZdXPTRZBVP\NXRXRTJPTX`P\^VZTVbTPPVXhXTTDRXPV`bPbV\JbXRRX`VTVXVZZ\^^PVPRVXN\`pTR^XHTR^TXjXZRfb\^Zbfp\TZNV\fVb\dd``Z`XZXR8``ZVT^XRV^XXZZ"ZRTNVdTT\bfLZlNPVXPdVD\^`\VB`dPVPh^d`LbPV`Tb`XdfDLZTLTVVTJ^ZLX^fXbXJLXZ`TXN`RNHR`TfJ\JRB\NZV`TXPZ:BJHVR\BJ^VNXZN`VXPVZT\XV\fbLZPbnL`NXPL`XX\NZ d Z ^ < n b d V XbR LXTXRVd`Z^XXHX\<bZVdVV!b Z"T$R"X#V&%H$R&X(V)**R(Z(*+++H+P,X,P.,X0T.V-0L1/R122J5F34d6H7N648\8Z9^88D79P;P8^8^8V8H8^8Z863V3T5`3`3D4Z3T2R52T4h0B15J1L2\2^10V30R/L0T1,.T,,,,Z,V-Z,*Z,+,B)++,,\-/,+\+,R-,))X*Z),T(*(^)N,-P,T.)+F,,,X0,.T+P,^..H/-.-^-V.-0-^/V1V2R3Z73675:77;9=:N>;=>^>>J;V?>J<8:\9\;VJ?:9;FVAABTAP@`?X@@RCB>LAVDRDR@nDNCTFPEdFTDEVCZEXBZDA@TAPBXCH@R@?=`=P<==?n@@VCZCBCBXCNFBPDLGJXLIJJHJJJ^NOXNPXRNMTQMXSJOXKLJZHXK^LIJZINIKZLNIIILK^KJLMNPLL\K`IKGROTL`MMVI@I^IKXHGHGNIZGF^HLEGTFETEGRJ^G\FPFXINKJKFFJDGGHGIjIBIFBVCFBLAAfEBDCdETFFEFZGLGEDCBBLDE\F\IJGLNJVHZKTIGGZGGEJTHGGNF\ETIEGFZGdEREC@HD\HJRHK^GKJRILMXJLMJMFJLNL\MVKJXMLKKMKMNJNHVIKJHXETHTIEDTIDDELDRFFGKNJKRMZLPJMNKHdJdHIINJRJLKNIZHHPJZFGGLGTKKZFGIXGDBHJH@GHIZGRKJZI`GHKIJZJKZKPMLPRJKM\KJLKLNJJKIDGDCA@XF\BPGEGTIRICEJFV?BBAV@A>JBZ?NA@\@C@=P@:N<<:>;:::P9=VR>T=;N?<==<>A@VA@\D>>R@@>AEGVGEfGTF\ETGRIKPLKZP^KKKLJbNLLNMTR\MLNTNOVQMLRZR\MNMdPOURVQORPVRPSSbNRP\ObQVLKTMIMIGXKRMKMJ`IIbHEHFBEGG^IFGZGJECE^FHVGXIPGLIHhGNJZHHRHPG`EEDHHVKTKOHLKNKNKIbLLKNMVMPKMMLMLNNPN`NNNNPRPOONR\P\LRMLJJKbNHLMPKRK\JHRHGFTFRHVCbDfB?P>?V<^:9<>9F;7V=7N7b5121V2Z1D1d./0\/\.--V1F0,,)H*b,-T.R-*+,,T-R+X-,b+Z*,+`//0R/0R2^-H0J0/.Z0/\/H.3/`.\.0,V2Z/1X/T0.02Z3N4X7^77:X766X73F2X535T3b.24R31f32J12X1H10P1b0/b.X2Z.0.L.V,.,P,T+*R+^)P+))*)&h%P&T""" Z!N!"\! V\L\LVZX^R\JPPVZ` \ V N H D L \TV^\XZ^BZjDdNRXd\^F\XZRTTVRJZ^FV\\dZ^LR$VPjdF\Z`Rb`LTXTN\XVVb\^\JTZV\fZZ^ZZRTZVR\VXRR\jX^ZTVd\XLdX`d\Lb`dP\NbHdBTVZZB\HbLTfd^nV^TV`jT``lRjf`^X^j\VN\RZN^XVVZZTRXfTjTTRXZl^ThP\fZ^Xd^fVZZ\ZXZVV\J\\bJVN\Vd`LZDTdHV`Rb\`^^`VVDZ^`ZXXfbLZHZ`VT\TZRPJTVnJRTV\`\`^bVd`PZRdXXPJbLZf\bPLRZdRXTLRZP^`JRVXbNLN^R b N V N T Z ^j N^TDV\VPZXLN^R\VP^V! N!f#$##D"#F&%Z'`)&)L)+)+,Z+*(b.P....F1^/0/F/R.0125X67`7T55^88J6`:Z87X9;79D:\555N6H54`5565234X5@43^04\2V2V2J2X2000`0/0+T1--h.J-Z-R,Z*\**^,)**d,L*l,H2Z.T+,b+Z,b,P+^))'V*d**)+N*\+)**)^(*Z-Z,^,J,,X,Z.^.,,X,/,V/--R/,Z3112^4N4^7X66Z898J::9R>?>>?\==9:=H=X=>?AT>?A=ZA?@@V?TDA@XBfACTCDA>DC^D\E@^@?@A@ZA@?R?=^;V==>?TBAA^EZAdDXDZCXBDTDEIRJZIPHI^JbLXKLMMMLNPZOOPXMPLLJ^IJLLbJHZLVJTKJIVIJHLZNZOFMTNRMZNdKVKGIIKOhLIJJHHH\ITGGGECHXIHHGVGNGIZJTFKLHHVHF\KZF\IXJVHLHGFPIGFDBTCFB\BCCRCPD^BERGHJGGGKHEDCBVFDbCHFHPNVOH^IbKPMJJZIHLGBIHNHJJJfGIETJVIZGCGBE`HHFGFD`ITGXJI^HKNMFNOTONLXLRLKJPKVKXHXIJK^J^KLIPMbHJGIIEXFbEDGFRHGbDCFEFHJhLLLNM\KLJH\HHPMLZJRKHHFGGHFHZGGD^GZHDDEDGRHJGPKJPK`HTH\HKFGFHGHJRMKZMRKINIMJVJ\J^IJLJGbEE^GFDCEXEdFZFHbG^EFFE\BB>L@Z>RA=lB@TBLAVA=R@?T>>Z>Z>J=?L:V=;;^;:H;h;?9`=F<>:<<;;>>Z<>^C?@l=?L?>V@BA\EfFDHND\HLGJLNMJdKJNILNMJIONXMONN^LZPNNOO`POPPOUVOZTPVQ`QTZRNRRPPRMNNKPRKJJNJLJZMHKdKJLFGFNFJJ\I\FNDBTEfE>ClIGGGGIVGJVHIF\IEE`FHIJIML\HfORMODLLXMdNNMZObMIXPNL`MZNVQPNO\PQZORORLONPMMbLVLNL(K`PKJGKKGHDNHEEND`?^A>=<=:P;;b;8V995X666R22Z1L10`011R.H/f.-\-+d,-*b.H/+d*+P,,T,,V++*++*+j+/0.L/,.Z0f0V-T-V./0Z00/L/d1,V0H0/0-1X.N.1\253\455P665V5432T3N2^47\5X13^11^3^1L3R2001J2/R/1X2/N.\2N.X-n//+,+^(Z)))H))X(%#%#%R""V f!R `"VVV\RR`JhNZX\X` T T T J N fX `^NT`XhLx^VPj^fV^bfRb\\JbTRP\\\ZXNRZRdRfbXF\VDf^PZL`T`^`Z^TTTr`d\b^bPPT`Td`\bPX`RfXJZZbbN\X\JTF`db\bZb`TdnRX`TX`JTbbR^<R\PbLZXVJZXLXNdVdJV\``RHVXbZfPZTd\d`VHb^TRV\ZRT`RVdTRZ\@J`\RZ\XXRrPRdRVV\`VTP\N^Z^bN`\`ZHX^R^^HlRVfJ^`X^R^\LZVZVVfZVf^VPX^VVbX\\XnVZ\^RLL@DP^RNd\V\ZZJ\LVTZ@BLHJJV^XfNN^RPVX^PZVTRX^ X T X X X X N LRXZNTT^DJVT^R^TN PR$^""N$L#$$'((T()))-*\0,,f,*,L-//X-Z.X0R2003T443^2P64R5275977P8b6J99R88P5b8N47P5P45D0h6Z4\62V44^32X5L0\2\3L4d10\1f./Z.N.2Z1/\,0^--`,T,X.R*+`*-j)P*P*)\*R-+\+,^+*Z+,,(()`)+R*)T(L+J)\**)+F*L,P+-T0+P,-T,--\/,^-\/L,N1`.X/\-P2/V/D4N5Z6R7^98V8R97:V9T=J:;B=R@>P>=>X=@X?^AX?CFA>\AZ@VBFDDCRDhAVB@@RAA\AAZBZ?`A\?CCbAZ@T?^@>b@X?NBT?BhCAC`DECPCBCD\I`GNJHJ\JG\KXLVOMXORQVNfPK`MBMPLRL`MLK`NNRLLLLVJ\JGRIJKZJbM^NNRNPKKXLJKNNTK`MJNJRIdKHGLERFKHEJ\GZGJHHTFZJHLGFGTGJVLdIRMXJLJKLFFIFFFCCBbDDPH^F\CTFVFFFTIVJVIIIEXEZFCCAJETDDHIJKN\MRKMJJJKKVKPKZNKZIKFGJPHFZHKDFEPDPHfGJIIKHHRLZLMJNNLXNOLNLPLMXNJHN\JJFJNKKXJFK\HIEFHITDD\FVGGdEDGdDRFCC\IJJMKKLdJINHXHZJJhOZJHVHFE^FFFVFDjEFH^GDGNFETFRKFHNII^L^JI`IKHI^KDKHIbHKGIKXKdJK\JLZIRINHFGJXHEFFLEFNEBDGTEPGHZFCLDZFCBJ?=X^=T<@=X:V;P<;V@=?J>^A=R>Z==\=X@@`?TADETDCXETF`G\NRLJJGTIHKVOVM\LKTLNNLbLTOVLTMPP@QTQPRTPRdRVULQTUSQPOLQR`RQOOJIJVMMO^MKlJ>I`MJNjHZIJFKIGHGFhFPHJGbDCRFGJHKGHPGLFJFTC`EBDG`EPGIGIIMNNJMJKLLfONL^NPL`R>NL:MFJTNMTNTOPQTOP^PVMKVN^NOZLKZMMNXKLbJRLZJHfINIEFDCXBCB?>;`<;@ Z`T^ZJXHdTVhNTRTPL^ZVJ^dDRPNTPDb\^ZV^JPRNbR\XX^LP^RN^NZLffXN^\ZVZR\TbVX^RZbRR`^LVXX^L`^XXjVX\PFL\ZFNPVdXX^NJ^NX\V\NPLZd\djdblL`fhV\VVZVZRjTP`XjXX^XdT`V`d\`\^TX`T`n\V\J\T`VVVV^XZH`LLRV`RZPXRZ^bZHNZRTR`J^^Td^dLVfZJbN`\`^ZTZVZP\NTL`TR^TLRXRZXPlLTRNhV\PVRNP*PZPdZNRfVZBTFPD(TN^\>TPZdH Z \ d Z ` b X V  \ ZP\TZVZRLNFRXPZVZXXR`^ T!L!!R"V%#X%%\&X'&R(^('(*++,+,-...1\-R./P0b10Z2101P61N544J5T45N7:3^69T587:8H54N4B6b4N4^5`5N6H7`6L5H3H6d5P3P21L0Z31b20T03T.N3P0^-J---0d,V-^.)N**++*T)F+++*+h-+R,)R*h))X)Z(**R*,*X*)*(-P,,X*T*Z*H-.-R+^,N-,\-V1/N/,..-\3V.b3/11Z5^6Z6X5Z6Z9V6V99P;<;X=^;^=V;?;N:Z;^;N9:d7T6V:::::^>P:X>\A\=V=XV<`?X?<`:B:V ?>V@L>?`@\BDT@DF@CC@>AP@XB?>B@@DEA@?fA?R@AVB?R?AZAR?TAV@ZBR@XBPB@RA\C`DVBBHHFGRJBJKK`ILJJPLVRTM^MVK\OM^PNQZMbMMOJM`MMKTMKLKDKIKNNTKMHObMPXNOMKK>IJbMLMRMZK^OLGHGJDTIRFRGXERGEGHEZJTFLF;P==>XA?TBACPCA>?=@=b;V<:N=L;;`;?=:B:T;9^::T:Z=V>^<<=Vd;?@BCBbGPDRFID\K^IZIXJHNHZMH`MNLMKO`LIZLL\NNTXQVRVSZSSTSQLRRTTQ^QT^RPZRRNNPQ`QNKKNZMVPRLOMKKPHXLJPJIGXGECFGDHNBNEfFEFZENGJEDVDGhJZCXDBLF`CTGTI^G^JKIHMKJPJLRKLLJLZLOVMKMPLMZQPZLMQOTSOLfO`NPXPMMXNZNXNMMVNVJNKJZJZHVFdFCEC^BNARBCT>;XA`<9B;P;8V4X3X3N4T2321N41/b3X2V.(X,+,`+*d,N-Z-+\.*T),+*X-,D+++--.V.F0P,B-Z,X,.,-*b-,..-T0L/X2.-21-R0^00V1h4b55l75f5X3`63^52323Z35\311T2^204140b2X/3/T0/P0`1R0B.--.-T,/T,+'b((Z+*%%L'Z%\$Z"# Z"\!"Z T^\ZLTb^PZPLNTH ` Z X V L X T \`F\VLNVXbN\^nPjZLdVl\XZTR^\`PX^T`VdN^bXVV\^VTLfZ\bLXVbV^ZZ^DfRVVTNLZXT^D^JXRJR^TbNPX\PTXZl\dLPRXdV@XNZZVPZJ\NXVRL^VTZZ\N\^ZV\djl`b^T\Vd`ffVPR^^VHdV^`ZLfd^\R`XbbVVdN`H^lN`ZZbZh\\jFZLbT`dTRZZZVbTdXbR\ZdX^PXV^b\fbPVVRZTXdJ\^XLdNLbLVZhXF^XT^\LnFhNLbF<bTDbXNTFXXZRfZ\`TV``VT`N\bRVXfPVZPX\PLRVPVZXZTXL^JRHZ`PPNPbTHVTJNT V T \ X X F N P P RPDdLT\f^TbF^ !T!R L!!!T##$%T(J'%)*()*@+Z---N.L-,-L./R-.N11N11X1\31Z44423T556Z5P78V786b9V88:6b6Z49R7757R7L7\6V5542R6J3012/2X1^3X1^,P0^10N-1,X2V-L-,+),V-X,***,)T-V-N++*T*V+(X+(*(R,P(,Z,P)R*)R-T&\()*D-b+R-N-V/-+,+^-//--,.0,0d2J/Z1Z4\1N3N6`4X6J6:79f;T;L;=;Z;N;;8Z::6`;H9V:Z99;;;X=V>R==\>PA=^=<9`?V=;Z<><;<\=>P>=?X??@bATABV@@?P??V>?V=V>=N>A^EBDHARCB@BAECR@R?@?R@\AB^@\EDEX@BXCBVCTD\IILJPMJJZKMKNMJLZPXOLM^NJOOjRQNLJXLMH\MLKJML\OKXMIXJXKKNMKP\LVKLHKJLKIXIHEFZCEFZDEPCXDF\GBDGHENFPFEGRCGETHGFZJGhDGPGEERERETCDbEBPIJFVDCF`BXCDFKHXI`JGGE\DGJCZGFFCKRJKHNbPNJKNJJNOL^HJJIKPKZJJKLPGINIdGFHFPDGXIIH\KITJNHMNJLLLIILXIPNMKTLRNKIJ\MTJPJENHFFRKIGFhERE^HDHVGHXIREELEGZGGFITJHLTIJHFPFDjHGJFEFLFRJDFEELFFVHF\FXGGXGFLJFJZIIXJJHJHHEJNKJFFEDEFFJHIGGRGbHVIFJjITFI^DPFCDDFFHREF`HRHbJFGCDAXBT?;Z>X?h?PB>@@`A@?AXAZ?Z@<=X=`D>>@ABbDEDXEEXFEfIXIFLZH^JBIZLRLdLLKOMN^KLPZNO^QJSZTZWBSRZSZRRRRSQVSLQXUTTPNXUSQVRNbNPNNNTSLM\LKRL\HFLIGGGDbENC\FGVFEXFGDVDPFERGFGGNGJCVEEEXIHXHTGPIJJXJIITIJHPM^IPNJKJLL\MKKJKRN\LMNNNNHN^KTPbN^LMOO\OL\ONLXPQROLJJFFTGFFZDC`A\APDb?FA^@==\>J;?;Z:Z8X8F634F4141J2\13\.X/T0--+Z,*T(^+R+P+*+p,+(,f,\-T.X.R+*P+L-X0X/V/,,,`,b+.\+R+J.L*+./-d2/-\120\2R60V003657V6Z2\335V31\0V2Z3N2V6V73^3T5N3\2P52T2d422/L01R./0/T/,J0\,+0+Z,R,)')'\)&'&$N%$#D$N$V#` N!Z VJ RZ\`bF\\dJPTRNVd`@TZd JN ` ^ N PXZJ\TRJTb^XZR^ZT^P^\\XXTbP^JdNLVP\NNT\NXH`NR\^dR@ZR\fJR\ZT^ZnXVR`XX`RX^TRdZ^V^ZV\Zb`^X`Z`Rdf``lXRT`P^F`XZNZ`\RVRD`PZNVZ\fVhbfT^^VZ`XRbXZZ\f`VX^^^ZT\fVdVN``^f\NFd^XPPb^f\Z^hZH\XT^`ZPPRVV`VdPVVdT\fRPd`^X\Ph@^F`JVdXX\RTXTdTRR`\hHVRTPf\RN\^ZX`LbFVb\RXTTLbNRRVL\PVLZZDTVZXbT^\VXTTRNZVLTb^ZbbR>\P^^NNRFXVX^N^V N ^ ` \ X N dTVT\bP`^h\R`dLVXb :X!Z\ \H !V""`%H%b(''^,*(*X+(+V.+----.^/`001F1L24T54N2V2136^2L5h545\4866V5n657V8:X5^8X;f6R6685Z4\6N7X7N6V6T33V4P5223V32V1-X/V-P/P.---.b-N.-T**Z)**R**`++-X/R+*R.+b**d)J*D(j,V)R*)*V*),*)+^))j+,J.+R.0..-+-P--^./0T..Z/<001`41T3T2R257V64j9;H?>R=>VT=:V;<98P78T;8^99N<`ALA=\>=`==R>X=X;T9^9>`?<=;;:;P>^>R?>=R?=X=b?BZ?\Bb?>=\>T@P@\?B^@`AHCDDTE\EdFTDGZFVKLfJLI\IJLJhMNRMORNNMNOQXK`LXOXMNXJXN\NK\MZOMNLPMJZJJMXLXMPMZMNIbHXINTGHLIGGIIFF^HBTBJCACCVGFEEdDDIEdEEXHE`FFVFZDEND^EEPBDJCZEDbD\FEbEE`EVCCFBdCRDbCDG\HFNIfIH^GXECBGDTEPDE`FZJKLKXJZL\KFJVJKLPIJZJILGGFXDVHGPH^HVKFLGEJRHVHIGGFIHXKIJJLMXJJIK\KHVJJJLKKGGIHILHGVITHGHFPHGXDHLHPENGIJIHFGGEJGEGIHHDE^ENIEDIPIZFREDTGXEE`HLGCECHVHIE\HPHZFDGFJTITHTHZHZHHF\HZHVJH\HERKGGbJKJVE6HXGVGPFNDFFCDZCPEFDPDDDXEFZF`EZETE?ABP@A@<>`>R@@^CDVAVAB?@>=T=;P>N>>h=Z>L=;@=T<@R:98R:=X<=`=P?J:=T=J<L@X@`>B@^ECNDCVGCZDH`IIJJILJ^MHNJPHZKKJK`MXPNNOXPQPPSUTWQPQfQLTQPSXSTSVRPQNSSXTVROMZQPNORM\NLKGJIZFIXJDbFGPERGFFXIEREDDDEFPCPHXFTCTEbDCCRC`DD`E^FTGERJJXGZILKMXNJ^MIROKbKKPKKpNVQMPNRONdQJ`PMNHPPM^MNNZMHMNMPNPOIHRHGNGE\DCBZBNAA@>?=P<=L:V:Z<8956P23T01T3\30X01.H.V/`-+*V-b+J,*,*(*L.*`*b+V-,`+\.-)^+V--F/R,X+(++,`,P*+V+N-/-./.`0.0/Z0@11T0T12^4445530d0L2^1V41F34^753^4V2Z2V2V4V5N12/D151b0N0T11X1V0R-,,*-,R.F,Z.X*L(&'L'T%T$$V$P&$#N#^! N R\HRX\TbPJRXR`ZHVb ^ ^ D P Z Lb XZR^LLV^N^JZTTV`\bbPLZXfRNdbZdLXX^bL\ XTJDb<NPVNX\hZf\^X`f^`NZbfTXZdRdXTTL``R\bXJZf\b\\fT\XXfJXL^N`FX`RNJN`NXXTZ\LX^RTTR^PX^`\R^^`Zb\hXLVV^LRX\^NTZXX^f\b\ZTNNXbR`TZX^PfV`X`TbN\F\dNbVXRbTXJbX^jTRZXZV>R\XXPJLP^\^^PVN`hXZPZV`d\JdV\ZX\Vhb^RdDdZJLRXTL`P`XPhLJ^FTZR\RZT\bVLR\JRX^N R T N R Z R ^ V X\ XNNVThRFR\HZFR\NrDP"TX!RV"P !" V#%(V'\(P)Z*b+X,++`+Z/--.-.-N/H0V004T21\2R3V2X45P4`2R2R2P5L4^:N4P24X9d6L7787X96:b6692P5566Z58d5V5F4V8R222V4110T.^,b.R/P2..^-R,Z+R,+P,Z+++*l++R-+-+..^+R-X+T,V)f-X+++H+-,X+Z.*J**L*T)(-)+P0b3D-.`/R.---L0N/X/.P2J/H0011V0L222\5X5`47L9;9<>?D<`>X;\>?`?=<9P68@:T799;:;?=`=>9\=;=J=A@?H?=P@ZA\FBA\HB@RANF\D>>A@A@@CAAGACGPDZB`CH`FXGPIVJKMNKVKJNLOKNTN\PPXOOQPOTOJOFMLZMKNL^KbLK`LFQPLLXOTNJLILFNTO`NTK\KRLKHIIJFJXFJKVGbGPHEGEHDDDDDLIFDbBVEVDCbCEhG\HGGIHLG`GE\BCTB@BbC\CCAJBDNGEbE^BBDRBbCTECETEEEREVHFF\HFVEVF^EHEPRLNMS^N`NVNLZNPMNIVJINLIGTHI\KFhG>FG^FEHFFEGbGHGIIXIJ`IZLXLNJJJ`I\HVH:KI^KLHXI^IPLHRHGbEE\JZGEGHFFTKXG`FHFVFF^FJD^FLHII^JGTGRGFTFGE\HHHVGRDDFDDBPDBE^EFGTEZDdJLFGGEFJKJXERGGRHBGFVFFEGCNGIPHELJGGNFEHTEZDXCCHDERFDEbEHDPC`DGD\GJINCVCDACA^>P?@?A?CVDERBERATF?`A@>T;X=@\?RAV?>N=P=R>f>=<:PP=^@R=?@@B`DBDCCFFRDGCEEGNLIKnKHJ\HLHRMTJJHLKPNM\N\OPQ`PPZTTPLTRQPQPUQSLTbT\QOP`RTPPVROPPTNFL^NKXKXJFJHIXGFHDXBEE\EVEDGGNGEZDZGDPFNEEDDDDCCDCGDEHGHJ\FJEEFTGGIK`IJKVJHPKJLL`KRJVNVKNPKNK`KJMKPM\NTSNONNMKLNXPLPLKHGfFTGEEDTCCEAN>>\=<:V:8:Z7d7P855P623132.//,X,T-0V,+J-+L,V**L*V,*R*+*L.`+H.,,+,^--X,`*,P+)()*\+**^++./J/Z-\.-X0//0^2Z15X3R5P6T43H30L1424223b444f62P421214V310T2\1d0\00R//2.Z0.T/P*N-+T-\+*)T)&T'(f&R#&P$#""!N"T# Z!PZTRPXTTNfTN\^R^ Z N J R VTXffVV\^T`^dRNZhPX\^d^Nb^\^ZZTfHR`R`PVTXTjZ``Fj\dN`LZLLRldX\ZXTPTNbXZPdNNbZVTbVHXXZBl^RTPb\VbH^T\ZNP^^XJ^XRPVPTZZ`fhP^Xd^ffP`d^Z^bTd``XVPdZbNfNhZ^^bT^^ZbZRf\PVTdVJ`ZTPZ\bVPZbJjb\VV\LTbR`RZRRTdVlLV^^rXhRVhLHJVX\ZdTb\`^\jTbZT^VT`VZVb`\hR^JZ\^PX^RXVbLXjVVZ^D\V^LXfXXDXVHfNZb^XX\HdT\TVVTVN\\J` N \ V V \ Z Z ` ` T ` X T^V\\NNbVXXT\ T!` B#\!!$%&h$T$N'&'X))).+B.,L,T-1^.V/0P/\00/1<21L32`2X43^4`21R2L4P348P43V35^345X8V7J7\6B6f85R4\43R4564Z9R834J64X3N34V00b1--J-./--X./,Z/X/X,V-`)*L*,Z+T-,-b-/X/,,)T.,X,\*+\*+.**V**,+P)N-\(N*)+V-d-`/-h0,V.T/-/L/`/V3.T1^1L2Z33\453T5P5X367L6:9PH<\AP>J:T::9Z<:P=;;==>=T?L??F>L@b??T?\@@NDAL@jANEbC?X@C@J?CXCR@CTB@TBVBf@VCVBBNCEDCE\II\HLKKOKdOXMMK^NKTMPLSL^PVLL`KJPJNZMLdOVNKKLVNPKRNLLRJXJPJ`NLNXMJHK\JDOHHLIHHJFVHZIF\GG`ENCEDIEDVF`HDGTHHCEDHDJEbK`HLGhHVKXFFPDCCZEAAPBEEZEVJTEDC`@TDXBdEBREFCEETEDRDFDDfD^DVEGfIIMJLVPPN^PNNXOK@MhLjLJLGJRGIG^HIDJDNFCFFNG\FNJ\F^GXGVILIdGKMTJKHKTIIGRJFE`HTHJEHbIIHHIbEXEDZIIFFJHFLFITFVIHEEGEhIHDHTFTHG^FFFVGVFXGGGDCE>FdED^CPGBEdGXG\FIXEFC`FEGRFXJH^EVETFfEF^ELEDZCFDZFGRILGKFNIhFVFFDFDFTGhDTDXDLDDLDFECVFDFERETHPC`BAbDCPD@X@VAX?@@VB\@LDJCA?@@@Z?`>d@>PA==?<>><=R;N:R9X9T:9:8V:\>`:;>V=P=^V>P@>\?J?;8N36574R7Z3131202/.-.-.Z-.b+,-*,^,b+^*R*H+R**N.`-J-Z*`-+)*\+)L)*)(+-*J*j*.V+R.00--/J//0N004b17H410H3/0^3^/0V32\3R35P45J4X22440R3^/215V2f/32f111./+,b.,L/*^+**N))&%&T#8$T&R$$!Z%b"#!L XLbPTDR^\^JLB` R d Z V J T H X` X\` PXVRRVZVTRVPlhfXT\R\BRbPRTfjNNTbPVVNL`\\NXHXD^^LRRXN^^ZZ\dPZPTR`PPdZRRZV`XVT\dPZ`VTX^XZV`J^dZTZXJXZRRPVPdZPJN^\XVXb<\ZFZTb>VZNX^bdZdd`Z\fZJVX`X^d^XZ`df\`TfhVTR\VV`Z\XT\LfX^`Z\^ThP\V\ZZRXN\ZFhR\ZTZPHTHJZ^\^ZT`\P`dP`TTD\`TVTR^NjPBTRL`NZ^^NTJ`RR\LVNTVJTTLXbVJ^T\PT>bXTbVTd\TLRN``J``NbVbVVJJbX^`TPRTFXXP`X P Z J T b T \ R Z PJ<Z`jTTLXPZTVXXXXHh"X T#!Z""d#N#%&H'P)H)^)-.,R-L.^-N.b,b0010\0022/\1V2P3\6\5X211V3\3R3R8V5V34244R5254H7H6X7Z6677T6d5F64R5^56Z755333V5N41D2J1....0/X.P/,*N-P-P-X(V(Z+(*`+L+-X,R-\-L-+X*Z-,),N*+T+X,+^*-P+R+R*,+(),L+Z*X*-R.//.l-..\10\/P/01^/0N1N03J524B64V6589^Z=Z=V?>Z><><<9V9X7T:5P78d98L<;Z?<@AA?Z@T?>=?=>@BA?^AXA??BCAH@CAJ@bBBBXCR@XCHBCTEPEVFFF@DZELHZJJJMLPLROMJLJIHOVONOK^QJ`LJLNPM^NNNNPMLHJMXKPJBMNKNJZIRKKMNLNDOXMXNTMPJJIHGGTJNGEChKGPHGCDEHFZI\GDDRFZDEDFVFVJ\FTHFEFLGEDFABBRCZBLCPCCFRCB^D^E^EPHRGD^FVHEJBCD2CBVDFXFHDXJdLXKZKXOPO\MMMlPLLOJNLLIHFJLTGH`EEXC`EZGHEXEEEZG\IFXF\GRHdKJI`GNF^IXGREHVGVHEF^GEIRGGTG\EVCXETEDJEVGJDIIHZKTKfKGHFFVGBEFEHGLHHI^GDTEADECECRCBFCC^FRCLCCDDXEVFF FhHCVKPDbFBD\FHGGGVF@ACAAGPFXIFXIRLXJEGFLA^FTCVBBZCCbCLFFDDTEPCG`ECXD^CCBAPDCDX@\BAZ?@@ZACP?VBBXER@h@XCXB@?RA?R>L>>;\=X?@>R;<`=V=R>`A@T@\CLCXCXAADAPD\BBENIZETIEZGH\FFHG\HXHGTHVMNNOfKOPOVSVTJWRLUNPPSdURRJTOTRVPQPNTRPMTPLITN`MMJIGKHHG\HZGEdJHTGnFPGPED\CTFPDGEHD?RBbDBVCCGACPBVFVFDFbDGHH^IGKMIJHXKXLJJ^LKLKKOJMVKKKLONNQPPODPRKIJJNZNLNbKPLGHXHD\ITEPGPDZCP>H>T>R;L>Z=?X;>:874588R8V:T;;<=\9:F;=N>b=d?:VT;AN@T;T>V?H@VD?TAAJBXDXBT?RETB@BPCLAXBTC@CVARCVBZADXHFDEZFHGHITOJLKZNOJbM`LXM`LLZPOZRL^MMNNTLLNLRN\MIPJjJXKPJ`MBLNNNJMEXMKJZJJL^NfQNKLLXKIZI^JRFXG^GPFFHhEEGEXGJFENKVH`DEZDECJG\G\GRHLFPHXJEPIECCCDE\AAD\EDdBC\EbCNDVC^DZHEEEPFHEBBATEPGEFGKIHLGMMMQZLPRVPZLTMJJKVKHPK\IIXJBJPIJTHNETHVFHDEXELCEXIDFFTHFJNHHHE^GNFHGDREHDGNLPKGEFDLCF^HPG\GREGHJZHJG`HIIPHLIFCALBDbDNEHDDHH\EGZGFCCVCVDCDCCZE@FXGRCZCBEBBCTELFBfCDC\CHEFTDEEEECAAPDA`@\DRFVDZDGBINELFEFBC^ELCEAACLBBNEACdCXCCFTEEE^DFEJCB\ENDVB^@Z@?AHAB@?TC`?\@b@DPAT?B@A=<=>V?\=T@Z@V@HADC\DD@@BBE\FE`C^ELDH\HG`E`FPIFGEEF^ENIRKLPNZNJL`PRTPSSZSQJS\OQdQORTRSQN^PONHRPKJVNIJKZKKJJGjGGHIHXI`JFTG`DNFTFDEVDNGEZCDDVEXCCCAVDFBPCfDRHPGGTIDZMGKGIXGHJIZINHPKNMIMFKXJKHMKTLJIBKKJFLVNZNPNNMNMIILNKLORMJLTIRJXGFHHDRGD^@?X;X<;9X==T>^8X:P7P:85N8V63f2P1/-.///T1T2b/\/H1,,`,V.L,-N*)J*.H+-+*++b+Z**N*`)'f*\,`*+,P-P+F-+,X,Z,\.----Z/2121H0V0Z3X2T0\/.\001F24R22`4T37332X42N4P51X1//120b3X22/\1.d/L/,++L,.**)\*()'%''Z'&X$$T!" P"L V B \^VVRfZXP^`d\VbT\ L R ^ R XZX P\bXbXXZ`PV\`\NT`RHVRRP\fdXRR\`XZZVbZdJ^bXVZLPXRfj\R^TVbTZVVTVV\^PZjdDV\TjZbX`TZ.VTPLT\hLLHRTRZ\^TRLZTTX`fHX`XXPX\VLRb`bfVFL`PNXd`\PbP\\^db\TZhfLT^^VfHXVdbVdbT@TVPH^hTZNPPJDVPV`RfjRbTPbT\PNR\RZ6j^RP^X^V\N`NXZ\h`PhPXb\`Td@TVVbT\XPT^N^TLZ\PVL\LXX`PZNVJZDVXJRZV`fJNTbbdLj@P^LPZR R f L X T N b 2 Z \ ` X T@X^ZRZ\NRTV"ZT!!V"!"`"$`#\#X$J'`'(T*P)*X-+,N,/-V/N/12R2T.32N20F22R25X3333Z21N845R4N5P2R8^3Z522625Z4V3535Z785b4P6643`5R6@75N76H3/V331/-P2//X.R-*\)-*T-V,*,*(*^)+T,V,V+-.X,f,R,)),*\*,H+V-.N-T*.\)h-T*B,*((+\.-20V/,Z.N12N1/`1H20Z111R4H2\54V8P645T:b87;:R9Z==>>N@=@7Z7:X:h7R;^8::\>V;=>>V?V>X?N>j?P>PA>@@\C@PB`@@BD`GNAVBA^BT@@ALB^B^@\AX@BEPFTFPFHHdGXKK\KKJOITKXJKVKKNMNOONNMFHHJJVL\KZIILINJfNXLJMPOKJXKPJdKKKHLNMKJPMKHKXIHVIHIHbF@GEPDLE^ENFTFbFHJVFRFZE\CJHFGD\FNHGDTGVG`JEZFFVDbEACTDVC`DVB`BJDVABLCTEdCTDZGPDRJ\FHECDCRDFVDHTGIEZJTKKZNKNdLXLOIdIJIEVLPGHJNKLNHVNGbGFEENF`HTGEFEDEDFEZGEZHJFDXAJGRFRD^FEBFZBPEENIXG`DCDXGFPFLDXEFXDGRGLFVH\HFXGXHHB\BZCVBCVCFEGGEEDTDCPDVCBCJHN@CADBHCARBXBPBTA@TBBVCZA^BZC>CAC\BB@C`HLB@@AN@@FDDTHCDC`FF^DDRBDDJBBZEAB@@RA^CD\D`=\>=>X>?\;b>d:N8b9T:T:=;`:X>H>T;?PdBZDZAJ@AE^DNCRE\H^FHCVBXDXGEDHLJGDZFRFRFXHVJJLNPMMXORP\PRPPSSOLT^RRNhRTRPZNQZNTZLPZNTOXKMLZKJHJHdJZLFFFKIIZJRKTJFZE\HFHVE^BVCRCBRDB@fB?REAXBHFBTHBFHDFElGHJDRKJKIBIHJNIPIJNnKLJKTKbKJPLdINJOJIRLbNN`LPL^IPNIJNLMHJIXITLRFHXFEEJCdDAAP?PR`DPFXJZXbL^bXPXRNJXZ^Hdb`NXZ^XT\^b\ZXXdTZ\`ZdP^`VZ\fTZPRX`L\\>NZbT\\ZTJXL`ZL\RRPJZDf^bXV\Nbb`dXTZHVV\XfPpLDbHTTNXNdXXXfPPT\Z\XXN^N^ZRRJ\XPNNZRHX`TbVN<bXX`bV\ZRZRX^NNTZ@^TZXZXVN`PZXFRZLX^\Tl  b R L L ` X \ d P ^X THZVX^NLXRZ\RbRXTX\X"V$!R"`"" $T$&&\'(^+()*Z.X++Z20.D0/2b32T35X45P1V0f5R3T5465\4P3`25^7V5N5\6N2N3N12245J63R7N6H6b45456Z3h7T56R65b546Z434T2/1\/T-V.-+R*).N+,*T*-T***^-B+R-\-b,V+V-,,J*@+++^-)\,^+L,,,D1,,+R+-^*J,T+-.-,-`/2R.^3\/f02X1d30X11f14R22Z4328L5b5^6;6TX@?@>R@`>>V?`;R=L8d978VR=>><:=T=:=Z=X=A??RAR>VABARAPETCXDC?HCB^APETEC\B\?@TBBG`FTIRFdFPI\GI\GJ\LJKTJTLIbLIbMMNXNP\RPJZLG\FXEFIXJIK`JJZJRLXJPMHNLKLNKHH^KLNXNLLM@LMjMGI^HGI^EDGZGHREREBEEXHRGPH\JXGDTDECDD\APD\DREFRHH?\>TAd@R;Z=99Z<:V>P=<;9T>>;X>XBN;==b@?VBAZ@C@C\DDARENBhDVE^GVGXGCXEHFCCCTEDbHFGXEXGKHVJXKNKQJOPQ^PNSTSUPQ@QVRUSTOFQJLLLNRMfPPRPONbLM^KXFJITKFXKII^KH^IRITF\DPGFCVCJFDPBRAAP>@X@BBdC\DfEPCRFVDDTCE`FFHNJI^J^HJMJM^JIVLITIVIJdJIKXJJJZIHVLPONKZJIJ^IDKZJTM^HIHIRFXFVEbEEBVATA;X<@9=>X=R;7b88d76962V7P2^3/R3./0Z/..T/T2,,d+X-L++^-^,,\.`.^--+*\*)R,V)N*`)`((^*')-R,X.,,.h+/d+-T-\/.\-`3R10R1101\0/h,0-1d21V1P14`/N1R63V4T1n1L102X1X0T2^11\2^3R130N.N-\.`-+L,T,+-l-Z,X)\(T'P(&V&`'P)X&^'&%L$V&#R#Z"X !V!P `VP^Xb`ZVhR\LXPVHRZd` \ Z N N Z R L T `XfXT`XZNLbZLbXNjNRR^bZTNZZTVLNJXXZf^X\TTFNL`L\jVbV`RRV^PLLbT^VdX\bFXdXjbXZPTR^P^fH^HdN\XJVFLZVdZZN`JVZVRZNZVRPVTXVX\4^`XRnPZLZRZX\`dH^JTRRXXZdPTZ\Z^TPVR^dVL`XhVdNb\LXZVTdJZRRfZ\^ZdNXXRVNVJdV\\^\@dJ\RZVbNPRTVVZXRVRP\XTN^RbTXTRN\\^ZX^BZ`ZXTLXbX@ZTBdFjRR\TP\^NFR@Z\X\hH`XNLF^XBVF`bRX^TXPZZRT X h \ V Z J ` d H \ R j `DPNZJFRPVRVPfB^ T!!b"h#!N$"`"V$b&$D(T(b'H*(Z).T.R.`.^1/20\01V3324V3T3T634X42>3Z6\32^456J7622`2^8P451b2N444V25T63R56P6`6Z676X5J56P6h4417N4^22/0^.-+J.V.J.R,b+L,X,)++T(L,+^*+L..,+b-X.++,++*)V,*T/L-^,X,`,P,V+L+*\,,f,B+-R-^/P.^2B..0L112j2J3@5R36N705Z43L7X65\8b7\8L9\;;X>=>>Z@RA\=N>N@?R@PC@DbCLBBD`AC?A@B\C\E`CJCBXDZADDHE^FFH\GI\L^OJMLJILJ^KMJJbKNOMNKLHDHHGF\LKBMVH^LHTLLLZJZLIIPOMKZMJJHMNJDNdKJILKTGKdFHTIFEVGIZJEVDEBDbFHIGXIRFhHEPFTGERHPDXGRERGZF^GXFENCTBBVDBB>>ANABTACFNBLDEDBCBBEHEGRGED^HVBDZGFTFEjKHKIJL:MLPRZLRNLVHJJFCCFHTENIHETF^FENE`HZGRF^HNEBRGCDDEHPGFDBEVFPDRFC`CANEBTDZDDCTCTDDTCDDVF\DGFJDJGJGXI`GHHHFEZCBECEVDENECXCXFCDBVBTCTB?BADVBCC@@ARC@E\AA@BVD?X?P@VC@B?NAL?LE`@>BA`?VAXCFCEXA@B@PALAXD@CAVGVD`ERARDAZ>RA^=NECRDCZCBTABCC\CBE@?Z@ZBDCBVBBATCJ@VDBCVANBA??H>TB@L>X>?^<@T>PAPC@>@ZABCRDBVDCCDDEHLE`DEBdC`ELH`DGEZHFFHHL`MP^RTRMNPTN`QOUQSXOOJMQNNMLLLPRN`PMMLGVFNGKGJPJLKPKJPLPKJF`FFVERCjBbDBFBbBB`?Z?V=F?P@RCE^EZFNDGPGXEEEGNLIPMJIIEJLL`LDIPMKNfJNKHKIMLJPJ\JJJTKLLLNJVKGJZKJ`MXKVLJJGFHC^DRFC@RBH>\=>;\;>R?=V>R?dBAA=^:X;8;X8R;d;L;`f>:J;=?=\><=>XAANBdDB`AE>T@bC>C@B\B`BHDGTC^BFDDTEHG`ENJdIVHHXKIMI^J\OHMTKdJ^N\JMKXNVMMLJFID\EK`J^KL^LXOPKFL^KRIKTJDIZLMMKXJRL\JbL\KZIIdLHNTJPEZE\FGDFFhGdIVG^D`DPERDCbFIGDFPGdIVJVFRGfGVDCGXEE`HFRIETDDAXBTCZA?`?>A@AA?ECAETBA`CDFhGELFFbFECDGJGJVHLJM^KPLLPKJKZIRFVIVHPG\DVFDfCNFGEDDRG\CCTDE`GRCENBEND`DELDGXEFNFRHTFXDFFCV@ADZ@bDJCTFVE`GdE@ZCFEFRGXHDELHdGGGFGDLHBZFBRCBBFPCXCDBB\BZGEPBZD?ZB@PBACBA`DJBRA\B?>?XBDBZBXDNBZ>@@TA?V?^?;X=V>ZAA?JACBP?N@VAATAJBTCEBRCNA?f>V@J=Z=>`@VA?CRCLBR@ADDCAbFBJA>X@bEV@XBVBZCZ@ATC^CBEC\B@TFXB?=`?D>>R>d?@=V?D=L?=T==<;\<=V:;<:N@T==@;T?@D@TB=Z@>BbDLE^BFBBAAH@bBPDC@FDVDF`FLERDCIHGFJF^HHHMLTNKMPOINOQTNNU\SNNMONTNXLMLTLXPZONPNMOTLVLIHG^KNJJpPXLZKPIHTKEEDTD\GBPB@ZBZA\A`?AF?AX?bEDBGXGVEETBDCTEPFHMTHJhHHNKbJZK^IJKVJKXJ\HXGH\JNJJ\IHZIMbKIJ\JGLGjIIXJ^HZJHFTHFCFD\FCDBD?><<;T<;=V=;Z0Z44b568T4P956X6>:8:8867Z=<<<=>X>>=X;A==?;;<^PA^AV@?`TA@CVA@FC\E?DNCDZCADXCFDFDGCDDEhFHGHZKKPIRKPdLVLIPMdHJIHDXIVCGEC>CXEVDHHXFVDBPDECVDDGCDNDZEILHBFBFDLDD???P@BCRB`ELEBBBPEEBGGNHXGGVHFEDFDNBDXAD?XB^BBDACCdBD@?ATAR@=@RABAXA@T@B@F>>^>FAFA@F@^AJ@^@JA>P??\=\@;R;T>N>>>ZBR@>NCZCJ@R?FAJCP>L>=L>A?L?X?\@DAAC@bCTBABlCDB?LARC`@?D@CCBFjBCDANC@@V@@?^=X?J?Z@J>V?=NA=<;X^?b;>==\?>>>L>E`CDEACVBZ?J@RB@fCEZCREFGZGXDZF@IE\GRJHHJLLPLKjP@JTMOOSOVSSNQNVNRNdONMPNXMhOJQN`OPPLRNMTKVGXH`K@KNNGJXGIIIHXEBRE@PDX?B@PA@VD?V>AdA\APDLBPDXIEFZHXDPELDFbDXIGZITFFG\FIKNJTINHTJXJGITGJHZLJHGdJJTMKZHPHIGZGVGdGIHVJTJVLDB\ADZBD\?^??\@=>=>>L>`H8^<;J9X<99T9^9;^=;\9X??J@`D@TBBRCZDVCD@ANCECDVBTGPEZEbD\EJLI\IEGFLIZIIFJIKJ\OLXLKNLLZJLLROLZMLVKKFLGXHZGZJ@HKIZIRLFGGJHJdLMNNLBLINJJHIPI^JK\KTHFG`J^IJZKNFZFHEEXDXHDRE^EVFGF^DFPFBRFNCHFDFJIRFHDENJbG\EJFCA^AT@A??LCDLECXDB^EPCTFZDTDXEBCDGREDFDDFREGTGHK^IITLdLDKRKFGGXIDGHD\GTFGGLHDGLJDETFFDZDAPBA\BLDEBPDRCCD`BNFE?LAb@@@dA@DB@BhDDC@CNB\FRF^FZFPHE~FTHPI^EPDDVCDAA^ACfBC^AA`BDGAACBC>BBB>AZAD?>H>?=R?HC\@`@RBbA>Z@T@ZBPA>X=N<AR?N;@?BBBTAN@`>V@?>^=?D?R=L?>R?V@>@@V>\?`=R>J=X<;^:;:R=P;J?^@;XCb@J?V>?f?R@?T=@>Z??EA?bDDbC?A@bB`GCVDCH`J`DGdFPIF\HIZKNIJLVLLPLTMZMOZLNQQLSPLO\NHNTLN`OOPS\NOVKMJJLJFEHHGGZKXJHGEDD\DB`CBP?NBC?R??f??CBLF`BNCG\DTFFDbBND\BENHXGG`H^GEPGEPE^KFIHFRHFTJJGDPLDHZJGJIXFZJLFRHVG\F`GIXHTGGJIFVGE^C@JE^DBFBZ?><>V;X>\;66D43342101/10R/T0P,\0.X,*)Z+)\*Z(P)+*L-\,-,,P,V-R+b.,//'^->-P++*+/,,.P,Z.J1d,N//\/T--.`/^0Z/V0Z/T2V4N555P666`6`:7;:V<@\=T>V<>>=>?>^=>?;H:97N79X::?b?F=Z=<@?=>T=>`?@@DBBDJALDC@TDBBBlCBCDFGHIVHEIHJJTLZNLNOFMFTKMLMLP\NPLMNKVLNTLOOVHKFJbHIJDFHKNKFJXJVJFJILJMNOMTMRKMPK^JMIVNJ\JJK^JHXGKG\EEDXECCCFFDGPGVGFXDEXFVCCRE`ETGLGIDHGbGJFCHB`AT@AB\AVEEPF`DXCCZGNB\CCBCCHFXEHPEDTBJDCE\FNFG\G\HHZIbLVHJHHGJFXHDDFGI^ETHEFVFNEGbGEICZFVADTBXBBbCEZATDZCAX@@CBC@A@ADB@RA^BDZBTDB@GZFEEGCHIXFRFNGTGREHCCGAFBAh?APEA@ARAJBZBTBZ@NAV@PCX@8AV@B@??V?ZA@@>@?=^>AR?XA?=^>F=P?=NX?@BZ>PC?PB?<<\;?N<@J@V=>=R?=?@@@=T@TCPAA`CDBXC?BHBC`CbFGENFVC^AND`E?N@P??>^=>J;8>P<9V=<>=^?V?>?b=V@>=><>V>B?XC@\BV>@f@H?@?\C^CXFPGPHHDFEEbFLFHJHZKLGNIHKHNIPPNN\ROdPQXQZN\MNKXOLOOQZQMMRJdJLKTMKJGJZIKVHHJHHHD@CXCPC?BV@PB@@A@V>=?P>`BCTCRBBCHBCbBABHEF`EXHEFNHHREdGbFFGDZGPGGCEFEXKIEIHNIHEFJEVETHHHJIIERFEDAVAA?X@??ZAPBP=<;\=T==?=>V<;R;7:^98X9T:T=;:9P89;T>\>;d=TNAPABTFAVG>ZCDdDFA`DB\DTCLCEJGFTITIZIKNKKMLbK\LdLKJP`PLQfOLMKPKTJ\N^NhLOMdRKXKHI^HJJHZHL`L\JIKPLbJHJLMNL^LNNVLVKHPJILHJJJbIbI`JJIRD`FTEbDCFLFbGE`EVHFBEdFXFEbEC^ECNECVGXDVFNEGdITGEFFfDCDB^A^EABXCBE\BEC^DPCTECEDFVFDDFZCEELD`DHENGFJMbGLJJ^JFJECDXCCDHEDEGNFGZFDLEEDFRFBNCGRGBDCVBDTCBXECZABAC?@N>@VAHB@hEA^CXBRCCCND\FPIXEB^FjFJEVFFI\CPFD`BDPBDDbEAV@XABZBRCBTBB@AA?@A?f>PBV??>X=@\>R?>>>NBTAH?VA=;P=R9^;;Z=N:b9?<==>^==f<<\?TAP?R@H@\?N@>F;;L9\=;>=;>X=R;:;\>R>@=T@?BBPAhCCADCCCPFZGbFRCBBPCdA>=:T?Z;=<=@?V?T>LAT=>@>R?;;:=<P=TAT>=b@\>=\?@Z>T>T>?=J?=\?=?T?T?Z>L?CBAPA\CJEDJFLGFVCGRGGJIRGIXLFIZIJLLJONTPXORO\NLLNKOXNSLPNO`PNbNJLJ\JKVKPHIXGHFHI@HHTGEXDCATA?bC\AADAV@N@=\@AXAJEZCF\CCRBRCRBADDDZGEFHEIEXEGDHZFHDFRFNGZGEDLEFPFDFGEFFHEEPJJEGHFRGGDHVDDFBDZBBV?TA>NA>C=`<;::67\6T7X6\731X434T1Z3/R-.,/T/V0--R1V0\/-Z++)++Z*R*d*R+^,*-,-,J+,-+.d.*\/Z+N*+`.P.X2X.P.`/0L//01X,/\.X/0R11.H2`0/^3H1X40H.0/30^01b2R2X24T31f5V3d11.0.,X.--.*(+R*H+^)+`))\&)\'P'&(N$J%L'`$N$N%$"^"H\ ` V"L J\RVbVVLdFdLTTZVh L P Z V H V H d V \ TR^TXP\LTHZXf`fZVVH^fd^`VR^PLZ^ZPJXTbX\XT`fHXV^XNPVP\N\^fP`PHNNX\RX^LXX\LZ\PRVL^`PPZVXRNTbTTZVbbZV\\\b`Rb^VBXP`\XDN\XT^\`fd:^jJfRVbTb^Vr^NbX\dTfdT`R\LT^HRVJ\\fRVXHVhT\\bP``XTZRZZPNLVNZVdN\HZRZN\\VV^P^^^TTPDZXZXXZj^VXPVfZJTJV`PbXLBRfV^VhT`RVPRLbbVH\\fXPZF^``lPTTVRXZXPNTJRTfRZFV\h\fF\VXX^\Vb FX \ \ \ T J X f Z FR RNP\J\RZXZ^\ F!R X!H#b$\#R#R"J%^%P(Z&\,))+N,Z0/f1/11144^43X5\4L9R5p67\8\69\7^7Z978X5V74h644P6^57R49V6T8573T6L434T46P343Z3645V54Z66Z2P3R40R0/1R/D0^/V//L.\-b*d,X*L,-b*R+\,J)V.-<.T,R-/-V.-+Z,)Z.V,X,-.,L*T.,.T,-B,\0V--J001V1.Z.b1Z1X3^223H0J4J65V8^7=^9H<>9;;<RA=R?\>?T;88T:T:N:888:T<V=b><^>=@X>\><;899V:98^9;;;<:\:Z:X=PACCCCTFfA?BVAA\D\DVD`DAhBZHEdIFMIGLM`MNTKLL`NK`L`MMORNPO^LIZMLM^MRNKZNJIJRJKKJKMH\ITJJ@JXJJFMKJ\IZLNMPKZMVHNKIIIBJ\JBINFGPGGVHNDDEfFD@ENEC^GXCPFNIEFDdDBFRGGE\ENCZCFGRIDRHEFGDCAVBDPDPDNAACZ@@ZCA\DDDE^FTEF`HZJHJGTGCRF`FRJFVHTIPHGfHHXFFEXF@TBLB@A^BB`EHGbGFHEBFFIDAHETDbCBPFZDGPEDDRCCDRC?VA?LAC??@XCCCAXBHDLCDPCLDDDFCHCXCNEED^DHGCBCAC`DX@ACAVB?V?XBBAX?FAl@?ARCBFBB@N>T==@A=;R?>\<=;N>===`=;J<^>:N;=>HA>P>T???==V:`9B9V:Z;>=X>^<>T>@\AX>?R?dA?BBTBZBBEFDCAC@@L<>><\@;;Z>>@d?>@=A@@R@??<=\?;><>=R>>h=`==d>@>=N?=?Z><`?Z=V?P?dC^?\ACADETATCD^GEVEG`F^FVKG\KKPHhIJLHGRM\O^NMLTNTLdRNPZRRONLO`PPMLRQNRXNPVOROJNKKLXMJGHVJFHDHGVJGCEZBZB^?@ADAZBCAP>?@CCbDRBA@@Z@>?A==T;PLd^`ZNbrRfHZRLTTVBTT\TXZPXT^T\dRLfP\bPXNVJT\PZX^fbPTTPTZP\VTNdbfT`XJ^`^f^T\XT`ZF\PTV\VfRVRjZVbZZN\^V\TbjXf`\XdL\NXb\`ZVZXR<^TPNHJ^X`ZNVP\`NNXNT\`ZJdZ^\`LTXPZP`b\RRXVZRZfZXZ`TH\ZL`Pb\T`ZXXXbDT^VXVVPPPPRRPDT\bTLN\\PZZ\`\F^PT^LRN^ZP H d P R R N X T \ P^ ^`\dZLTHP^`R!Z#X"`""$^%N'#&Z&+P)-N-X,\.Z/P.P02H331Z3V583H4d7R57X5\4L9R726F45554J76P456V5`744X756Z6X75X4X32431354J5T5V44335`4\33220F-,.P.-^.+*++)T-\+*L-R,T,V*+^+d-\,.>-+-R+R/\,P,+\.J.V.`-Z.+T+,+,+,b.f1.P/0.T/F20b2L22/22X87X98Z8P:9b>V=^?;^=6:;::A?H>T?T>N@AV>=d=R==`=V=R=;:\=9Z8X<:89:L<\;P?N==

`>N?VB?CPBCrD@A^AL@DREC\B\BNECXCCGfGVGTL\LMKLLMOLLKILRLbLNPFPPJJ\LLMHLKRKKXMJLLJM^IZJLIJ^IGXGKOXNTJPLHJKKIKKKJJJM^JLJGIIIIG\HFEdDFVIDXEEDTC^CDTEPIGJFVFbJ\DFZFCGDCFGTDGGIEEDEERBCFA^B^BLBXBVBjA^CRCBDEDZEF^GDJHNFEFZHCXDFRFPIGRGFfHGPCTFRHFPDCX@P?@@BTCZCEEDKFDGZEVEFFDH`HDFEHGEXDEBC^@@`>P>R@XBATE>ZA?BR?dELFZDH\DFEEECXFNFEVBGCVFBZDPBXAbC??NAA@?@V@\@T?XAN>T?ZBBA^ATB>?=X=;=>D>L>Z>V;=<;T<;@V?=<\=N=99P?=?H?Z:@;:;D`?PAB=?^?>P@>V@N@\>>>X@L?R=H>PA?N>f>=?L>^=^@P>\>?V@@XA==T;:>R?T?VABTCBRCNCZFXDFZFDFFdERDHIH\IHJKXKHLXLVOXLMORMMMQQPPZP\NVNQVM\LVNM`MRLKJJVKKXJPITHVGRGFVHXGCTDZB@?RB@TAAN@`AB\=R>^A@?>VEBEBCdAfAA\AEJEVFbCLE\ECDCTCTFJGVDCFTDDEFZDGFRF^DVF\ETHFXHEEFHIGEECXEDC`DD@TD@?J>\?@P@==:``J>>>T@@X?>=<:P=V9;R?T<`>>J;:999`9X7D;7`j>HFFPGCXEVDLEGVEGbGBDCVEDVCBAD@B\AL@CPBHAA?AA>ABZFLCXFEGTIGAVBVFBXANAfCA@PB?DTFT?@B^@X@\@?Z=;`:<;V?f@N>?R@T=T<\<>;N>dL;d<P:=^@;R<;D;\<:98L8b=<=N<:;T?>bAZBATAZCCBFDDnEFDAEDBPAl?>N=B==;Z?@?BAJAj>A?BB?`BX@@X?@?T>?=T=?R@?@V>=\==V?RA=X@\=\=T?T>@>CbBVA?@AZC\@VBTCVG^EFFVEF\CREARCXEVEKCC^FFDFEH`EFZETEVDBHNGdFPGRFEDFPGfIHNHPGEHA\D`HCCbDB>?X?R>b@>V=>9:f8L8@:L6`84l7R3h52R3b2R0\1//P/Z.X-Z01X/..,\/P1/,+N-,N+,*+N.)+Z-,J.+*J/,-T/d/R/-`,0^.R0.T0P.\.0J4/N.^-b/Z1X.4P1\/T0,`./3/^3/T/R/Z1V10P40430T23X2T0X..T3--b..0b0L.+P+)*)Z*()d((T)(&R%%T&N$'b'#@$$## "V P X TX \PVHPXfJVLXRZHT P J R T Z T j V J \ ZR X`:X^D\^V\PLV\Xhf^PbdXX\PlPX^Zd^XZXRfRPh^JPTNVdjV\Vd\HNHXZh\NTHV\\ZTNV\VDZZRRZfTLXP\FVJl^ZN<P^^^ZVBV\TN^Z\VRZRXZJPn^\nZNXLdZZhZ\^dbTP^b\dZPb\`bl^^Dd\lbXbb<P\^PdTJdRndT\Z^`LPTZhVVZV^`NL\J^RjNTVPVT\VXXZXZZf^^JZ>``\XZNXNbZPZb`ZVNDX`H\ZZXXbRTZbV>XPH\FbTbNTXPdhJfVPT`TVNVJVR`^^f`^`XXZ^R T X R P X X L ^ R Z TV\PL\dRV0VXRbbV^:Z Z N ^N$^#^#L$%P%\&&&*V*X,Z.-h0V1Z30T30T3P44H337<77>85`75X9T7V;36R5\76V7X5F783376766T6^952T226523J5X4\21\5X553526`3b4V401T////+J,X+T-Z*-N-j,.,**\,Z+-R++V,V.*.J*-L,+X,P..V-\--T0-,.X-H.\--.\.X/X2/P2R01N010X1`2P2Z6^678:78:H<;\<>X@PAAXACV>T?>=P:;<9Z=X;D9:;8Z<:@;?T?h>H=b?:R=^:TLJJ^MHRJNJITK\JIKKDKOLNNLKKKPOLNIJJHbHXFJH^EEVDPEPEXFREVHHXIFXEFHZDTHHPI^GNIJEFDGEDBCTCZCRCGVEPDRFFEFFFdFHD\DfCEH@RHIDFZFDBR@dCVCDDZENHD\EDXECIILHXFEADZDXDEXFVDdEPEPGDXFTGGHVKEXF\EGZFREXCXD`ECVCA@AP?@b>HBbACZARCR@>d?L??>Z?ERE\C\F\FEPFF^DBVB@@FEA?ZAR>BZE?BB@>=^<=R=R@N@PA???\@T>V@DAX@?:V;=R::T;T==F=<;R<9;J=;?R;=:<\:R=?L?Z><:LABVA>>>>ZB??bEfFCBVCLFDEDDCZA>=J@=?V?T>>>X?ZB@^AVACFCV@RCXBAXBXCdB>NC^@RAF@R@RBXCC>b>V<>=<=?L?=ZP=^?dB@CC`ELCVDA`E`GENFCG\DVDDGININHIKMRJMfOLNMOVNIL>L\MjO\LNNORMXK^LJdMRMLLGJJHJKKIKHFhIZIGDVBPBA?RB@CZ@A@Z?X?X=P?P>A\@?ABV@XC?@>AZFFFZINFJ^DPFVEBETDPFFPDTDCTDTHFHbKF^FCBDF@FEGGLE^HCJTHVGFTHC>DXBZELBRAVC?>>@R=D? R P ^ T ZVZZZ^FX^P^XZLXXTP  #\$!&%P&%N(\'J)R*^+R*,d-R.0//B232X3X2344R854h877V;7Z88D6F8T7Z8655^5\7f864V9`6L577R565P5R4\35d645T6F523Z5X431174T2J10L0<2-P,P..,,*`,Z+-,,/Z,+\*+T.B/Z+)*P,-^/,V-R-)X/L0\+-X.D-,T-.T0R1f/0-//T/T2P2^12^2Z1^3`3X5^4V34V7^87T7;n;N<:;X<<<:X=b>AVD>><<@;b;9;:9Z:XA=>@`=Z;;<8=@<:V?@=X??^=b<\::R9X;8R?ZC@BVCPAbAAENB@TCHA?PARDAXCJDZDEXFEhGDITIHbJRJKMMOPXDVB?C@^AT?`?@?EBFXJEDFEAbC@A\AAZACTD`BTDBBNAH>X@P>R=V@N>A>R@@Ad<@A==f@>::J:^8D;=^;P:X8:::Z>L;9;;L;`<>V;>N<<=b;:;R:;::;\::Z8T=8:NA?\@VC?BXCXFBEEENFNFPCLDD@R?@T=?F?<>BP>B^A?CPBACEBAC\DCL@CP>RBAB@V@XBZDBRA@Z?NAZP>><<^?J=F@D>??ABXAJFDDC^DEBCFfFEEDLHHGJJRLMNOZMVLRXJLLPKJZNZJ\LKJbKKPJXNNXPKINKdJTNPJHJHGKPI\HCTA@Z=^@A<\DAABV?>>>>L?ANB@DAV?@?@L@DCHGVF^E0DABZCFBEPDEGHDGLGEFFKFFJFTEFFbELFFEFDHHGVGE^FDVEFC@@@AT@?R>Z@;=^^PZb^LZZVXXVhbRLTX\TFZ\`VZVZ`X^ZVXX^`R^LX`\VbZD\JZ``\XPV``\hLLNBZX^NVP`TVZNRZ\Rb L V Z V ^ X `  N TV^`RXZXL^VL hP! ^ T!T!"`#%X$'Z*^''(X*T-R.,R/\1d00d4Z1V1\4J5`5Z3N7Z7Z58Z7R67;8J:P6N7^6H6N75R8Z5Z859V;T6n8`8:7N7T6633J12b7D44\641P6R431p321R55X5//,R/0/P//T-R-.P,*`--X+X.,+X+,R,T/X,P++N+\-*-Z,Z.N-R+R,d-Z//d.P02R/X0Z/./.X/.Z/Z1V5L301R2L0Z22Z3b7V45Z555b:X9^;;^=\==;?=V=B?@AZ>?^@T;H<>H::9b;9>R?@;\@TBXBd?\AR=9T?:`XNBRCTCVCjAD`BjCDdCXBC?AT@VBFCDDITGfEfJFHGZHEIRKM`KTPLMNNQLMZKbNJPRNNOZOP`NMVNbNMPL\MIbKXHRIHXIZJHIIHZLdJRIKMGPJZKVIXKXIDJJJNJMKLRKVMXQ`NLKJHLIRNIFXJFHDH\HCLElECLDZFVEPFG^GdDBDGEZIF\FPFFPJJ\JTKJIFRG`ETECGCZGVDCRFFIDVG\ECCEEFTHXG^F`EDDPBBTEXCJDTECC^EEXEHREEEND`GJF^FTEVIFRD^FCEJRF\GEGIGFGEFElF@RCB?JCXBLAT@DB\BA>@@LA=>?\AVBRAZ?ATB`CNF\EXGJFdEERCVFAHBNBCA`A`EACABl=;J=@:<=b>bA@P?X@?V=N@T>=<=;Z:;:b<;P;=\=<;=X9f:;;DP8X<::N;N6^<:d=\:9X:;7;=9>=8^:\;78X9N9:<8\;X98D7P<^=N@?b>V@?@^AJ@AA\CLBR?^DC\ECfERDCNB\B@X@RAC?AbDDDNDXD^DTCVGAfATBVAX@b@D?H?ARC\?C?@P=R;^>=RA`?P<>=XR=?>A\CVCBVF\CJCTDECTFDXC\F`G^EHbJJDKRLNK`LOPKNXKMKRJbHJVHbKK^ONLRKXMXLVLF`NKRJKfKJI`LTHGIDERC\DBJAj?TA\?Z>BABA?R?P=^DL>ZA\>VDDBDVB^@JB@`ABdD:CDRFdE`B?CXB@XEFFG\E\FLEF\FE^DHEFNFPFDTDTDTERFHLGH\FVGFDCC\EB\?CZ@@V?f@?=X?;7P:Z8N:6Z6Z69V8d84T64P3\20^3X0.d.0P1l-R/0f.N3.X-/X-T.V-,,X+`,R-d-+,\-\.P,+)V)**V,*^*-Z--<1.2f21V401^/X/T2./J-\/^22R20T.Z-+Z,10,0f-V-\3/3210d1.P--b/T.R.0./R.//R.Z,\0V,-+Z--+(P)R+P)))'(X)&%(P%$#R$%`"\##"!L N"fPTTN \b``X\dRLTF  ` N R V RVbNPd`TR\^L^@^NV`RZfXZ\XlRV`RRPNbPZ^X\PV^^PLRb^bRV\XTZZ`\N`TX^ZVZTRPPZdTPT`Xl\^dfZT`FR\N^RPN\JT^XJNX^\RRZLVXVbJZR\`ZdVVRXRhLTbPTdTX\`P`Z^ZVbbjjdZZVNd\XTN`V\PP\TVRLhNX\ZXVdZVZRZ\\XVTZPRN\^fRVd^VNhPXLdT\PfTXVLVXVPVVNXZNDbj\J`^VT^\TRdfR`XZd^Z``X\X^H\`PZ^RRTPZZbPVPPHXVVTNbRZVZVbZXPTX`\^^TLPLL\ZZL T \ D f @ ^ V \ \ Z @^NVZZZLbdPH`VRR\ZLVXV` R ! B"X"Z&#P(J&T)*`*V*V'R*,,/^///0F01Z322T667\1H8\976F9987676P<64=7:Z7=>=L?T?d>f?`?=<;<8Z=:@>?d@J@F?>A^>@?^?h>=?Z@?>^?P@=?BJ>X;V?b=R==V:V;9=<896X78TFZGEXFGFPGEFE\FdERFG`GDTCRCXFFHE`GHXIVIVJFKGEGEDDD\CZDTAP@V>T?Z@VAAZ@@N?Z@XBZA>^BN?CATDP?VDT@T>BCDJEBFD`DXDBVBDB@VDC^DX@CB?R@=@P>TA==H?AA\AT@P@V>?f=L:;f?==T>ZB?BXCA@AP?AdAABDPCN@ARA?bAb@AAL?@F@@@NADBbBRECTDXGRFTEPFBDABBCVA^AZ@NA\@RCBT@XAA^><\>X?R?h@VFJEGGFCCnCBdCTFPKfHGGHZHKJHOOTLPKMKK^MML\JhKRJLLN\ORKTIHKdIH@LZIhKNJ^HGZHIINGXG`FVIVB@?>>F@NB?ZBZB`A=@>X@Z>==AN?V@=9=<:=Z9X9T<=>@AA@XB@b@=?P>V===P>;@=TCdE@DZCZGPCZBEZA@A\?LA\BBbCXHVGbHF`IJGG`KHLVJOJQ^INOOZLPVMHQ\LbLMJ`KPNdOPPTR`KLKHLNMVKFKRJJKLGKKOJH\IFEVFHFfGPHGRHHRLZNNIJPK`KJIMLRLRKNK\JINKLJTLZMHHIJJPHG\ETEETDJFGHbHTGDVGGXEZE`FLFETDEJGJ`HTFKREFD`HBTCD\HG\DHZGVHTEGFDRFTDCVIHfGGbFHDCDXDCAL@bEFEEGHHXHVGLGZGHZFZEF^EENICDZEfHDXJJ`HFDGJIHVIFZFZIFDDRD^BA?B\?ATB@VBjD?TAPA>^@V@XBDnFAfABX@ZBRHEDfFNCTAADCCED\EAXCPAh@?^?=>L@Z?BjAALA\?X?@>Z=>=d=b?;X<:P:Z8H9\9;\;X?L;:TX<`@?\>=X?^CZAbAXDl@HBjBFBJD?`@A\DCCBPCTC?\@V?XADVCE@nBZ@`AJA@FRCJENEGPFDDE^CB@ClBRALETBPC?V>J@XC?T@AX=>>;N::::=T>d@<@p??@EF\DFXDdDVEPDFT@EHGfHBHZHHJbKLGJLL^LTKZKVIZMJ`MbJJILRK`JITHLHHIZJLMVILLKKZKbD^GIGFDBfBTBB^?^=>ZBbACB\??>h?@^>ATA@AZAZ@Z@@RC@TC`CEEECbAP?ZB?CNEFHBFBTBDFjEHEVIdGVFPIFFLBEGFRF`G@GEIG`FDBXBTB\AD>^@>P?L>>==8V7d9762\7Z6d56`8P531Z4P7V24T0d3.6^1.b/X6P-2`/T00/Z-R,,/*+,V/X.\.,T+L+b,F,X+.X/T-X.+`.R/-/,d1J2f3V102/`0T0Z.V/.02/0,\.`/,/.P/R/-/01Z10.//d2/d10.0H.\1P//Z-R/\/Z.,b*`)+b,*X+Z+(***X)N)((%Z&$V(''Z&X%$X#L""!T!"!Z! XXZb!XLdjZbRRf>`J^  T R Z \ R X ` ^ LTZh^bhV\LXZ\R`\bNXTXP`\ZHTdT^NJVRZN^bR\hZ`nNPhZZTZ\ZNX^`^TXJN`Z`^^d\hJlVbZ\PZJZX\^bZVRbHRNVV`^\XNZ\T`\\\`VJVLPZTZd^RTHZP\b\V^dbjZbPP`R^dT^HVdXPXZfTNLTZ\dZR\fRf\^LZ^^bZ`PXRd^hZJ^Z\`ZLHdPVVh^XZNL^Z\\TdLbPDLVTN^\`ZZ\`\VJZTP\^NPX^XXRRVTVbV\RNf^J\V\fPH^Zf\^bLHXPJLZXZRPH^R^XR^^VX T V ` Z V ` H P TZT\XPTXPbTVVdV\ZHXPZ` \ \"T!!V#P&%$$T'',P)T*\.--\///Z0T.0N1^1X2\2R5Z45\5P9b66R8Z6R77V:d8L99\;L886P9V89P9V::9R:<99Z8:b99h8J6V6b7L75\5N552X4\65`32//B02X4/Z//1^.V-/+++-b,0-.-.X.+Z/,^.-.-h+-T0+,/-N-J/P21//-Z01-.T-021\13B42756V7625\5P6R9^68P8688<9`;<<\:P:R;^<=N>>=?><<;<\><P?TB@RABACB?T>V>P>===^;P?<>=X:<A@@AD`GKHHHHhIHJMTKLNZO\LXMON@MdMTNRQNPTMOPPQPNSPLRLMJVKVLJJKnHXJIJHMZJNL^GXGHHFEGTIGbHHTMLTLLJKPJIMLSVLMJLLJDPfLNNIIZMTH^JJKFGGFJ^IVKTHHJG`IZHXGIDFXFDPEbH^HZKBHDXFHLEPECDDDCH^F`EF^GLDZDBETBTDbGTG\GDGEZFFfFhC\ER>D?TBVDEIBJNKbLIRHIG`FZFHPGHCZCTBDDCNELEFFVJLGHJGRIhFGDLJCDXAAD?VA@@`?BCf??`B^@@A@@XF^CAAR@@@DNCFF\EP@BC@>ECPDCFBJDT???>fA`CFAVBCN=T?>PCADRCN?^==X>B>L=:Z9R=d:R:X<878X89N:7`<88L:P9;7J5^7N7R9V9H779X6\7R6L5X6::7j7R:8888N=\?<=A>B>A^?BZ@RAB@X??R?N=AXABZ?XDNBV@T?@J??P?XC@d@@@A\?^ACCBTETDCFXGC\GVJTFF^C`FBZE`C>DA?L???>^@?`=<>J>A`BDNDEFXEFXEREhG:DJCGHGHJZHdGVHFKHMXHJA^AR?@Ch?Z@?`???A`ARDZA`B?>@PBLEVCCBABA\CPBAA`FG\DEDDABbEDHTFZFPH^FJGbIVFTCVFRHbGRGZHEFCZA^C@^DBZ@PB??Vf=B>=^@b>;:v<Z?h>=^>J:;R;P<<9P;9L;<\:V?@AANCTDEnDD\EZD\FTAD?A@@CNHZLXINJVJILTLKI\NVMNSZM\OOXOPSXOZOKVNTOZSXQQQTPPLJJRJJNIIIIHHHIKZHLPK\IJFH\FGNLZFFGIpIVKMKJKRNXNZNPPONQPLhLLMGTHKPIIGZG\KIGZJEVHHKJHXKHJGFGTEDC^FHIVLJJIbGE`FPFXEFRED^GTGjEEVDDNHXEEJFFDCZCCPFFCACAXCREACTAEEGNJ^JKZL\JHIGJGVH^FVEPFLCDCCDTE^EDDPGNJDEFHEECAXCbBLBBFBVAP@@?F\@A?`B@B`B`D\CbDC@AAPCDLDZEPDE^CBCNCBF`BXBbC@^BPAA`C>?BAX@DbCN>@XA@V=@LAf?V>`@`;;P:T:Z:b:9T;;\9\9f7X;X:BR>N>\?AX>?@?N=VCR??X@@>C?@L@A@@>@>BBZACPBABFFHREFbGCDCVG`D\BAARABbCD@N?@LC?X@\@AV>R<??V@\D@`A>TA^A@=@>L?VDX@ATB?V>@AEADDVCCZDZBTBCBNCCCLDBTBPBCDEZE\HFFVGLIRFFPF`DGRGTIJFPFBBE^BRFbB\@CHAZBD?>`^9X;@L>;:9Z9X=N:977B6N:2P6d5337X560F4`3333\1X0J/\/N0P/1.+\/V.`/L,*b*J./V.b0N+-b,P.R-+-X*X*-,-^..-X2P01..V-/.^/Z0-L21T2D01\3V3V5R58N4^778N7X8R9T8Z9`9H:79P<898H9V=\<:@>H=?LAX>P<Z=:9:\BBP@ACRBTA@@V@V=:N=;CDRDVETDCVDNGRDdDNEDCTC@TB^BTDDTIJXKIIbKJJ`KXJJTNLTPPO\ON^MTOPZSPOMVRORQXSBPXPL>O\LLPTLTLKIKXHHKLXLHMJJRGfGFHbIGXHJXMILJMKLNKMLNPQPQVPNL6MIJLJKTMIJbIIGEHHTIIBJZHJJJJHFDTFDFFLHLJKJTLJVGRKFETHFHXEG^ETCPDLE\EVDFHCATCfA^DC@TDNDAZAZBB\ABVCLCGXJHH^INLHKTHRIJGPEGXDLCRC\E`EREDECPEVJPEBEFTH:=9:`:;;=b<<>??R;V=?>N?>d=?b@Z??JDCFAXBZB`ADA@`ACXANCAZCTBDDXEZHTG^EIFhCHXCEEB@CPBAABP?RB>=CBZD?X>X<^?Z<9Z;P;;?R@>?X?hBADZA>?>BPATDRBFCCb@@ABd@DB\CCERC@CbDEPHE^GJEVFZGEdIFdGfDTIEVENDACGB`FVA@A\AA`DXX\XP`Z`PVZ\^ZNX`VdT RRZP V @ \ T \ X ^ FHZRVVTbR^TZ@\Z`ZZV b! P!V! %'T''\&\')*b)V-.-J/\0T./L0b0`332`463b437:N7b=D7:X998\8^96\99<`9V7;;D=T>J<\;;X;R;`99X:Z8R8Z8R9H7^54X5V4D2b4`3P5V3H12f62`321b/03.....T,P/T//.,R,\+.0.`,/+N./R+,,++.D/P/,-T1..0V0\2.\1-3P1^202`42Z55386J7V999T:T9:Z88^79V;9\876R9:>T@H>Z=<T@T?@TBX?PA@>`Z=?T@AZHGfJGIVJbJTI\OKJIMZMP`NQ^OOQ\UTPPNfNNOXOPOXR^RPSMLONVLLRL^OJKKRJXLHVKNJKZJJbHHZHGH\JKNKlLMZKMNK\LN\QBQPNPNMZML`KHJKFJIJXKXJRK`KHRJHXJLIHGZJJ^IZLVFNINIHLITJKPKTLZLJLJZHTIVIGBIDZEdGEVCGJFRGFHTHFENBRCTB@R@@h@NCZD@HC\ATAETEERHGJIGHRJXKFLdHLJXEFTEPDCB`CDRCNDCDND^FGHEKXGEF\FPDRDCBBVD`IBA@JDDEVCB^?B@hBA\BATECNABZEF^FZHTGZDDEDNFEBE\D`F\DABBDNDNB?BCFERB\EB@R@L>\J;D=;=Z:<<<=9L987L8:Z9L:<<:L=:d<\;T<9F8R:R:L68\6^546^665V:L4L4P5V3T9^656X766X3\55468:`??R=?`@=?V>Z>R?H<;>R=\@@=N?`@@=AZEVALAAPET@6BCA`DBHDXFERGbG\JRKGJFHFJ^ETFA^BR?`A`BBDVDXD@V@TB?Z@F@P?R?<>V=V@:T=>=JABDCCC\ECFHFDVEDAVATFCCCRGBEIREELFDETFNFEHD^JKKPNKJOI\K^I^HJKGXJI^JNKFRJHGND^FEC\ETENCfA@XEPCZB@^BhC?@`A@J=N@`<=TAZCB@lA@?@VC`FC\EFXEAA@ADXEDE@EBDBTDXBAZCRDRHNFEVEVG@DIEJETGDDLGCBADDBACBRB?@D>VXVJ^DXZF^XRTVHDPP@Lh\NVPbR^TR LR V ^ V H R X J T T L P`PTfR^PdRZTN\T"!V"R$"X!#R%$^'J'N*\)Z*\*)X+`/^0001143143V45V4648X77P89969V88;9N:<^;9=T;\=V;j:\9X:?X<=><@A?=>>>N?@RAN?\AA?L?^>N@D>\<<;;=\>>Hb>Z@Z@ZBbCBT@T@VCXFPFDXETDDZHDDRBbARDlFXEHJIRHVNMJKJMKLMPR^NHNXN\O^M^RQPLN^NNOlQOQRQBOTZPLQNLLNJXLNL^L\JL^KLRK\LVIKGFZGRIFETIXHVJJPKTOLTLNXKJNPOTOTOXKMVKLbJXJHIEJVILIIJIPIILLILLLHFdEFIHGXHIH^KbNZIIJ^M\ONLJVGGGGXHHPEFdDJGVGNHHVHDNFEDDF@@B?PABCVCXBFFC\EFGZEGIKFbJJZH`GFJILEjFXCREZDCDVFHPFhFBXEJG`EFIIGLDFCTECFNCVDDFEBXCAREFCLA\D\CBRDCAXBCTBZBCRCXDXDZHFBG\F2GBZEbD^GBDXDND@FDTBHBBBVFXEA@=X@Z>=P>???==^>T=X>R==N=R=>>F>^B?@TBRDA?@C4BZFPDNDF\CGEGIGFIEF\E\CBA?@@FB\CNBVAV@?AHB@Af@A>NA==V<;P?AC\B\ARCXDND^GCVBRCXCBFFD`GCPEE\DPEFNEEJFGFH\JILPJMbMJHHbGHMFJTGRGPHIZFNJTKXEDDDCbGNHDBBATBDAXDfB@J@?>\=;<T>X%$T%"`'$&T#""H" !JXN\>HTRRPNZHZV`TPNL@ T R @ V ^ V N Lb`HVRX\PV`Z\Z\bLVPTPTVRHLdTTZHR`^TXVbJX^ZbXlT`f`PfLTZXZRVT^XbbT\bRJDTP`dZNJ\VXLfTVFZZLZZLVR\Z\hPLTR\H^VhZLbV`\jVZFZ^T`ZTf^PV`RVZdb\ZbdXdZ`TbRZPZbTPT\PjVJXTXZ^XnZR^\`TTHZXVbbRVT^j^^\bRh^V`\dTXdLPXf`\XRXV\bbb`Z\^dNVX``Z^Z^jbRVfNXXRT`TZ\\XNJXd^^TLZZ`^VRdNZ\XNbX\dTVP\PL`THVjTT@` Z Z V R T T l N T \LTJNTZZVTFZT #" Z!%R$'`&)(H+d+*\-V-0T1\20J1102R5Z46f4Z3T2^6T9^8X6V9F7X8V8j8B;`87\9l9:Z;:=^B?TBJ@CP?RB@A@>ZAXA`?@b>?AV@d>>:::>9;R=T;;Z;T>V@=\;Z=\>=N:N`=dAA@@DBDVAZCXFVHCEDVCGC\BAB\GVEFHJVJKTKKXKMLIVJNLdNLLMPPPdPO^NFONJP\SQ^P\PPSTONMJNIZNLRITJJKTHTMTHdH\FKFZJIJGVGJKPMMJN^LTLKLHLJ`KDKKFKJJJHIZJNHbJHIHJRKJKIIG\HHRJJHGJZITKZGDJPKJMPKRONKXKHJDGPJ^EHH`EJERCDCEEHHTHREJECBREB@RBTE\ATECEEFVCD\ETGZFPHLIVIHNJNGbFFTFlDDRDEHREFIVGLFFZGFFGGHI\LTLGZGXH\EXEB\BXG^DBTANGZDDBTEFLBDDDBB?HD\BDD`CTEAERG^DHVFH\FZECFFGRGDCfGPIhAVB^CCNBDEDRB@??>B>T@:\<:<`>N^X<;=T;89L;898F5V5L65P7H68J6^7X66N53`55X7V77P6T758`78;>==;=;:d==@PAV?DAC`DDB^BDbGHFGFfLNFGdLG^GHFENHRD`BJFEP@B?PAJAVAJDB`ABVD?A<^B`>>N<^=T=;Xd>AA@`DBCDB`@DBFDBNCGRGBBEPDHDFC\DPHGbJNGRFZKKL`KRMVIIGIHHHHNGFFHGED^GCbCXFPCEXENDREBTDBBGR@PAP?hDJA=T=>T<@@RAA@`BPCDL@DdBZBC?AAADBbHDEXFCVDRAXDADXDEVHJ^ITGIZGGPHDZELCPBZECT@DB\BRE^BV@DC\C>>PAj==N?V<^A==R=8l=:V;\6756H4\5\5D6620..,V.X0-1V,^,,,T++,+R.+T.R,V,V-T,Z,\,R**L+^+\-J/.b-^---,Z,,T,.T--N/X/-.<.^.1^/R/T.N,`-R0R,/V13N120//X/10,`/Z/@.\12-0`/`10b00J-,,0R,,/-L,+h,H+,V*'*`**+(()N'b+*\'%%(l%$$^'V%'%#N$"`$J#!!bRdVZZVdR^TZ\` R b Z T R R R X ^\ ZdVPZ`\VZ\dPV\RX\^V\ZXT`dXLLVTLZT^bb\XTTN\N^\bXNh`TPT^LLVfV\XH`X\X`fbJXV\`RZb\ZLVP\T\^RXZZP\TddZR\XbXN`X@JX^XX^TN\@R^TZXPLZ\PT^T\lbdlffFVVXLXXdPNZPTXTfZZlb`d<`X\jXTVRLTVXV\LPZTRT^^^\VT`TVdPZX^ZZhb\bdZXP^J^dTb^VhZVN`RXZX^XPR^V^\XZVT\bXN`LVT^TR`ZfTHX\J\ZTDbHNTV`T`RHNh\Z8VNPTX`PBZZJ:bZTRRbXV@^VF\FZXRTNHZZRP\F ^ R X N H R \ Vj\^Xf<ZRPHXXZVdbHXJ"P"P!$D$\%&X'(N((*,-H-,b.21\0^13/0\3355\7947\757R7V9R::P8X9::;PJ=:>=f::;7\7Z:66V:;47X54326P442H4L31/1.X1/^00//,X0-.---L-L-Z/P-+P/-R,V,`,b/\.Z.h,-+--P-P.-.V1N3\00`2241X235355<3V3P548`779f99L=::R@@9<^;9V<^>`=?Z=?f>V;\<:9`;b>Z8X@VAZ>@?^DFDA\E@NFDFFXGD`EZD`DTDEEEJMJKLKXO^LMOPRNNNMZNOVOZOTVSQ^PVOLSPVRPQLQZPjMJNKKZLOZNKdKKVJI`GTIHIdHGTIEPFVKGHLM@MINLZLJKIPLLZOOOKbLJORJXJNLI\HbHbKZHTLITKKLXM\JG^FNJFHHHHBGfH`HGVJ`KKbLPMRKMXMZIKbHDXEFHEFbERHZEECEZFEXIBPGVCRFBBBBABAVEENGFHEHELDHGHJHFVHFZFFPEDHGXHDGJXFGLGPI`GGZGVHKRGJGJIFPH\IPDPEGEEXFLEFGNEEbDC^DBDEPCB@F@bEB@bBAD@EHGdFGI>FTHHZHFRFRERDNDEJECCNCBDAZB@@TA>@?9;=f=b=N;;8>T:X;:P:89?<>J;<=Z;?>>V@@=TBb?HACRDE^BLFEVENDCEGJFRGTMXGXHNGEE`GCNDXEZEB^@@RBLBBB@^CPCA`@d?X>P>>==VbAT=AP?N@RCF?ATALA?XDFCPA>BAAD@PB?TCFTDCFTBRAABFDREZHPC^HEXHEDFjFJEFHDC`BBCGXDRBTCNDD`DRCT?=@F;<;V=:Z@@J=N>;9b85V73X34J0`2Z3R2J110V-f/+,,\.,,h,*\+@0-Z+`-N+F-+R+R,+Z,.V/V*-/d/-.+.,.+,/+-X-\..-Z1N1,\0/b-b././-H0d01N13/N0H.//0P0002.V1/V-P,-X0Z/0X/>-//-/T/+-,,^,+V*)(R+L,-H*)\)P*+Z)+J$R%^&#'%Z%#P$d%&Z%P%!X"V"V T!V^^XdZXTRVZN<pRXfVHN\ T T \ N b NZ\ZVbPdX\ZVNbLVR^^`^L\BXPR`\f^Xb^^h`Z`P`RZ\P`hbjRjXhTbLTTVbdPdTX^XbTTJVZ^R`XZN\b^NTbRT\XTP\\JXN`bF`RRZTNfRD\b^`fjZfl^`ldTTZTbfXZV`VV\V^dVbZj`Vd\\^PfXPfVPfTZTjVbPdT`TXT`^Z`fZL`ZhV^X\Xj`b^\TfZZP`NZ`PXV\N\Nf^`LTb^Z``Z\^TR^BPfTTH`bX^\TRhZ\Z^^bXTdNTZZV^bX^\TTTTVbTZ^PfXV`RVZTPVdZhTTXPT Z V V Z X J N R`d^VN^ZXhLTX\NX"R\B!R"^"#"b#X#J'&\(R(Z,P+')X-,N,1311Z01f12\4^35346X5844Z8\;R86P:88b7d:^9X8^8N63\4\4311X223241.01V1F/P1P2/.J-R/@/.^.,.0//P--V.0F,P,P,,+V-^-\.-`-T-T+d..1N2Z12T1X2V3T651^34254T6546d3B97;8^<8;P=PAR@H>>Z<>;P>d>J=J>\@J=<@>?D@ALBR@C@>ZA`=N=T;>=CBLCT?@>AAVA\>Z99d9T9:;:;:V>N;P?`@`=\:9`:X:Z;;T:Z>;^<=@X>?Z>h@DBBbE\F`FCCGNJdFZGEJE^DdCPHTJXGHJIRHIMVMZNPVQVOJMNLON\PLO\OPQRPJQOOQVPPP\QjNNNJXMPH\JJKTHGJIGEHG\JFHFGGIJHJHXKLPMZLMPKJMVODLNXM\K\LVJXLI\IIdKPIXGIK\NFPPLINZHIIINKTHGGTIJ`GGKKRINHLMKXJ^FbHBXC@DNEDdBGNDDXDPDZEE^C^BA>`ANBACD\CCCVG`D`GnGFGPGRFFJKKFINJbHCZIFPHEVGCVGEJEJINFCHJHGIFDLFVLLKRGXJ\F\KDDFFETFGZDFPD^CdDVDDEBPCRDPDRABPACA\BBH^FRD^GEENECZHJTKIDEDDCTFREB^B`AAXBAXAJAZAZBL?@?=;;Z;^=;^;<^=T99H8998^:<8R?<@N=N;=?>?AP@`DPDTG`G\FTEDJE`GTLVFTK@HI^FHIFFZHLEGC\HdDCCPA^CDDEFCGBXAB>>=X=;;\A==;@TBCCDCEND\EBFEEPDDVGPCECXDDDXCGFJ\JKINIJXJIVO`OTMIZHF^FRE\GLC`EdHRGEG\FDDTEBRC^BTCVCETEBDERB@??X@PAP?><^@`?Z@AVA@fBV>`Al@N@Z?AZA=>?@>C@EFbELCRE\BB@V@RCCAEFTHDEABCdF\GZFEZF^BXENCTDCCCBDCDAV?\??X>J=?R><>==899^85j65b2Z485\21N00/Z,X+J-.R.L-*\+`-B-`+,0Z+J.-,T0J,+*l+L.,,V-\,P-,+T,R+\+^*+d++,\.-0--.H/T2X/-\+/,N01+N.N03/01Z1R.^0T.N-.f1R01Z1J5^1/N1.-.H/,-h0V-+--^--.-\-.T+(\**,+D+(())*(X*L'(%V'Z&$^%V&J&j%&Z#!N X" fTdZPTTHT\`XVRbT\X P ` R T X \b \VTVPhBbVf^\JbTVTVP`bRdNTRNZXVXN^``Rb\T^`VVlX^^TNX\nNXT^ZJZ^^TXPZVLZX^LVJdbRTZ^PLXVZ\JTPT\P\T^`NZ`lZltdTf\RfXlVZbZTbLPT\`d\bZVl\V^RLljRTTXH^VPPRdZV\ZPZJh>^VDVR^^bLZPV`RRRRRTR\ZNZ\TfDZZXR\FdX\jLTJZZXFHDblLVfVZbZZXFVXPRPLTXXJPZ^RZRNR^VRNVLX\\lVPVLL^Z^XVTXXLNN `T ^ X X P ^ D X XXLZ ZN^dLJRZRL\RVZLZ   L##Z%b$%N'Z&%)*(++R0b.^,R1240R5b2D534249X686P5X86d67T::F;`=788Z;9^;:Z=\;X<`?89\<:L=T:T;6^7N5d:V:V6Z7P6\:735D5`8R0^1P4234L200/00N1b10V/1D-R0//0.V.+T,h-Z--f-N1T,+,j--Z,+L-/--X1V.\334323T5>445448Z795X:`6^6`4T7N;Z9L9J9F9=D=V@X?F>P?>H>PA?`B?`?XB@VBBVA>L@\A>?;<>ATA>?>@AB>T?N=8:L9<7R<:^:9:`;;R<6:^8\9P8V;6;b89V:<FVHCRCDXBTA\AZB\E@TFBFFVDGKFIHVIPIGLGHIIRHLGGELFGNFJFE=bT>;?X=P;P<=J?V?P:b<<:::N7T6N6J7`55;P78988P767V6@87Z77X76N8b::d=;><8:T;===`>F>@V>==;X<@^>@A^EBRDZDE\DZEJF^ERFTEGDDF\EXFFFGXEDXILFLG\GXHFVLZJHXHIMKKGJBJCPH\GFFFPIVGdGXG@ChFT@^CFDACXEZFVAB^E^BXE??d@V@H?AR?R@@?A@?b@:Cd@RC@@?ZAd?PBTBDDAXGTDGCGLEdFVDHbCGVEC\GXEFREZBF@DLBTBAL>@T?=@==.X,,-R-+++J+X--b)H+/V.L.V-,Z/,-*P.-`*))*X)+-,J+P--\-V00--F0,-/0..V.`.J/Z43/H1/..b/`0/L1/F0X0n33L/P1+.-0-T/+,/.L1--\.T/V,,,X*l)(^*-+\*)\*X*\*('V&^&%(Z&N%&"%"$%R"T"X"PR LThRZ`TL\fRLPVL Z X P H P b T X ZVdfP\Pb\P^`NP^^R`NJRZRX`^Z\bT`ZTbT^``JL^b\TLdZZbPZ`\LVXn\NR^\\TTVbRb^^bPNR`PbLRPL^\\P\VbZTXfnNZPZLbV<`PNLXXTPbVPTbLVVJRbNZdVTNd\Z\\V\hhXd`fTd\XdjbTT`^T^V`TR^\^`b\f``ZflLTPbd`d^h^P`ZZdV`ZbL^\T^^\TX^\\R\ZX^`h^VVHVLdXR^h\VZJNVRTT\Z`NRN^dTZTVdZTX\PZbbHXXXDTRjZZJ^X^TfPPZNbX``\fXNfR^``TPPV^``ZPVZbVZZLJRV d V R N P D Z \  P LVVN^TZXP`bT^XRP`dX X!T!f"#`%Z$T$J'N&%*Z&T),J-V-P,/d/T1R20Z3P3b31d76T5\7P5b57P76b76V:Z8`8h98H:<:X7H8X:d<`:P=;;;\:N<=J=:V<66X68V:\9736^7^52b7\421V34X21V5T12/^-T.X0.Z.Z.N.P/-Z0V.1V..b/Z,X-+Z-L-R--+j-.-,d*V.H-P-/.\/P4R21H2P2\23446457X4\7;Z9F84b38T7\8:9;===>@T=X?<>>>\@Bb><PA\=AAT@PDJ@?^<;Z=?h?H=V=R?@A@AR@?`A?Z=;<:P9V9;H<;889V=X;=^<\>>^B>H@EZC`CGDXIJHXGFHNGdGNERHRHJJGRHFGGFCZHHDGfF^FEVEEJFHJGHGHbILZKJIHZEGJFFJHFG\GEBDNEZGFG\DRDFHRDPHTFCZFJIE`DGRFFDHKVMLIZIH\G^E\EDC?A^A@B^@?@TDVAN?R?==R<TZ>XBV@JAXBDDFXGXGJHTEFFGHZJGHDGEIPHPEFDCREjFVGTENECHFAdATBDCRB\AZ@?V?=<;==T<<>\>ZA>=ZCTB`DV@DdDDG^EbDFLFXEDRF`FXIDEERFLGJEDJFVF^KNHJIIKJ`KZGJZKFHJ^FE`IRFG\GZCGPFGB^CAB@BBPB`GXEXDLAVCbAZA?ZDTC@`BA`@Z?A>BX>>H>X@A`??>>D?T?>>V@T@XBXDC\@?XAALCb@A@fADBZCPELDDVC^EGHNIFDTEDDILH\DDFENCVBAPB??RC?@f;=^A\=T:T9b:9775d7N4522`6R30.N/^,,`+^.,P-R-.^/L+.Z-/d-L/`+-\-f,L+.T/-/`.*2R,+,J*d**+V,`,++V,T-./.P0./-..^/..V0\.T/0T/00,V.T/R000`0`0/2\00-X.-+,f-P/X-V,.-0J00d.Z-/-d,b+*Z.X,X)Z*)J)*)*('(&)J&`&d&`'$$$"T%D#"T$!XLVPJR\\bTLLN\TXZLnPPL  L Z Z V ` R T T Z \ \X Z\^fVNTXVhH\TTN\V^V\VPXXXX`XX^NRfH`\^R\bL\HVfTTPRbV\XdRZZT^hT`HfXbV\\PZZNdRX\\NF^Vd\RZJVLZ`XTbR^Nd^X``T\JZNXX\T`Z(V^\`VLDVTT\LVPZ\FNXLdNdX^LJTTlfHbPZl^d^XV^`TVVbb`X>LVb`^ZP`XTRJLVdRbZTbVZbRfbfdZdb\\^ZRhVZ^TT\dLjJVTZTR`JRXJXZXNf\d`VJT^VdZfd@^LXVXJXJ``VVHXnRFHnV^T`RXZbLRZX^V^VRL@N`ZTX L J R T b N V\`T`RVh>^PV^dXRb^LVZR!"T!$\#Z&%Z&(&*(R+V+-..1033R5Z5\433P56V69768P9:99J9X<:V::P9X9b9858N6^6V8X44T7L85643b101213R52/V/-^./^2/10-^-X2V/T/X0/X.N0f*+Z+`/V0d/P.`,J3X+R+^)F/P-,N..0b0T0/1/Z434L6^5X66J6b7X<9L6P76\68P9:9d9H:=>V>R?;P;X?@@VBVB>><>==???=>fA>N?`?RAP=>=\AAAR>>T>T>>X=8R<898:;99:8Z<<>@><<;:>X?A@?^C?BZA@;<<<>N==X=L>R=:V<7L7<9b>\>L9b<:F<>;<<\?LAVBCZEDHEEbFPHEBIHnJIHRFGBTFGVGHKFTBCTDE\E\FFC`CJEATCNENAZANCR@R@<\R;>A>b?X@NA>@RABEDGTBTFFVEE\GHTCLGLHbE`ETCFDELHRHFDXHGIFLJ^JJVIIHRHEPIHTDbFHPIHFGFETCDLDXCAXCCAPEDDEATBB@P?AAX@ZANA?>X?=fA??>VAT>Z??f=X>Z@D?L@?C???@@\?@BDBC^FZCD`BRC`GJDCdE\E^EhEF\F`F\FFVFECCRAABXBNCN?XDC@R@V>==;7977R67Z6T7R6432//P/^/.X/b/P,X.*-b-,/-/Z/.N*.-L+/V.\.1,1-,V.+N+R0^*^,j,R*Z-Z,T*^-P,V.-1^1,V.\---\/L2Z0V1X2./b/.0X0/N-.X0/`0X0N1D2d3\02X..,X--+,b/Z-R-.^/1/P21\.-R.*+)+,Z+,,+R*h,)))$)X'(R)$&$$&V#^"X!! J!VLPZL`VTRXTPZ\FZ b V ^ Z P T J ^TXNP\bTNdTZVjPHfT^bZXNXZ^JZ^VRLRhZN^l`b\PHPVR\dJNX\FXbN\PXbRTNZ`ZPHLbXJPdVPV`TbdTJ\XLZXTfTPZXLRTHXLd^d^bhLdld\`\TbbR`XVVRXTZX^NL^FVXXbldTPXLbZ^PD`RZT`VRNV^NNDX`^LRJ^Z^^^XD`XXTVb^^HZRXTXNP`P^RRbRlLjbdR\\TLLLXTdbT^^Z\X`PPTfL\PX^PPVV^bNLXTXVVR\\ZR\`\X^LN`\PPRdV\ZF``ZJZVR\BNXRLRXR^TN^bR  Z X ` L  b\\PVRLZ^ZjbNZ\VT P!T h"\#X%$%%L*&',d)D)J,Z,^--/R202`5Z33`54X38d:4X76:`76:X6:P67:j;9Z;X<;X<>6L77D7\8:T9J87:9^:X97V9L:N>P<<=ZA=A>T@>X<\>F@?h??b?=N>P>Z@A>f@>\>X@<TAJA??>T=X;V<<:<:P8;;R:^8N99V:V==>?N=N:\<^=\>L=9:;<<>PAXCADbCHDCZITGZFfEXEFDREVGE^FXEbFFJGL\L\LJMXLTMVLL^NZQRdTVOXN^NKNROQZLNJVLLJbLVMMbKRPITKMIjIKJIEVGPHHHHJGDIZHHHGHHFGJbKZL^MLKNJORQTMZKKPL\KXKLLVKVJ^MLXJIXHGKXLRFHJLJJLLRILIXIIMVKLKJJ^ITJMMPPDQMNMVLbJGIZFBCDTB@TBECDEhETEEZEDCXD\ANDETAdFVDCVEXDbE\EHHGRJTHFChERFHNMEGFJDXEREEJ`GHFENJVGNEHTHLILLIJTLLJDKMBNLJPLVLLpKIK^JKGJTGJDTFHFPF\E\BDEPETHPFNENFVD`EFVIGJHTMXJJ`JRKXHRFFRFFRDdFVATCB@@X@??>AXB=B;>>>T=H;=Z><<:P;X<:L9`<<`>?B>P=;F:9:R:b<:<VBN@BTD(DXCECVD\F^HTGTFjFFH\FRHEZCJKXHFFDZDTBTDZEFAPEHDBZF?DDDB@?ABZ>><=b=P??Z>\B>R>ZATA=Z=`?`@?L??@@AT?@?RA@BVBA@AXE@FDZDERGDVGFGhGE\D^EDJLFdENDCBTCCB`@XA@\>RB?F\`hDXXbR\dTPRNXT\ZVXHT^PZL^^Z\VFZ^dDPhX\`^\ZPVT\PNdZbTVTZ \N \ \ V R Z X P d`\VTVXNXNXPXR Z "\#%N$\)%%^(^'(+)`+P,^--F40^124b51T55V56P8Z5\88`9655\89X7T:9<:<:Z9\:H?@^@PAC@?P?>P?\ALCZ<;J@?A<\AR?=V?`><<=T>N@=?^>=X@><;=;d9L;N9R8J9d:8J?;DE`G`DDDFFGGbIRLI@GHFGJEGfHG\HGPGDGJDIRGGIXFDFGGLIXHJL`KZKIL^LNM^OOTQ\LPMHIRJVIJJ\LHLTK\KHTFE@VG^FCZFVGZGF\HNFXEEEXHIVKHXLGRJIRKPGIVEPH^FE\A@TBNC>BAB?ABT??\>X=;>X>R>T=;B@f=;X=>=P;9:LAX>\<;d;R88H:T8\;T:8`:9:8;8V8^9T998V7T:V;=X;78:\X>P=>?=>AFRENDC@TDJFRHFJHXIEXEGDEGZHE^H^GD\DCXFVETEDEDCACCBjA@>B??bB?Z@?N@N@?BP@AAPCBXFFENH\DCLBhGhDTCJFED^HZEENEZFBCAbETCC\IHGFXIHVHTILGZJbFFJRHHHRGGI`JGFHC@^CDFDRCBAFDDRB\C@ZB@T@@BH<@AZ?`AX@XCTA^?N@>@f>F>j>D=XA`?=T=N>VAPBB?>NBbA\??BC^DANBVDXFCRDCFFFGFDEPHdEDIZBHDBEVJZVNX`ZZ\ R` ` X \ D X`>T^JjRZRT\PVdXV #"#%^)R(P'&Z+j+)*T-*b,-X0`/b1/V2V32^2443R5F5779b:6^9F6V87F7l:9:=l>R:f;8V:HN?R=;N=`X=V<\@J@PA@ZA>A`>h@N@L=AT>>?H>;<>>;::8:;8Z::98T8<Z?;;<=`=V?\>??TC\@VCZC`F^CCCbEEDZCFFTDC\D`FHHGNINLRMNZJIXMLORPTN\QJJLXNPTM`MMONXLILKPROKNJZOKJHVHNJD^GHHRJLJGI`IfIIZJLGK^LHJRNMNLPLdB>P=>>R@V=>>L>@\;N;V=T==X>X;P:R=`;N>\;:X:N?9N97P;5^:8X:L9\P\=Z=^>R@X?R>?^@>XECHDPCDVDbFKTF@FDECXEZDEB^FTDbFZIIDEPFGXEPDV@TBD@A\ARB>ABA>AX@V@VCZBAB^Ab@XB@VCACZCRERADEBPCGXD`EbDAFVFCVBB@@\AZBFCFDXFGDHLbKJNHFXGIGZJIRHEVGLK`FJGRLCBDETDECCDZCVD`CD@A\A\?DAABVC^BAR=>>B?T@?@@T?R??<=>;X@>@VBZ?V?>X@Af@D>VFBREC@`CANABDHhFD`EHETDdDHETGEF`FBCGFZCDFDCGPBRAA==\;98986T778322d1R11B/R1\0-Z62/f0T0N2/0/00..R/0.-V/0d-*T,+)N.)L+\,,V,*,^.-+,/+\+R,T/-J.d+P.0200`/X12.0Z4./V-/Z/1X20/.\003/0d-+.P-\/\..`/01R11\.--+/-+Z,++N+\-+.+Z+^(')L%'N%'%Z%%"#&Z'%b!!P!X"TL ^T\\VLHd\VVRXR^  Z Z ` L \ ` j P TTjRT^LNZT\\VbL\ZV`^\V`L^TTX\J\XX^XdVXhTXZlJDhbX^^TZ^NR\NH^lXTZN*b\VVP\LL\^T^ZX\R`XX>^\RXj`XbdJX\TZZBRZNRNRJTNVfb^Nb^Xbb`V`VP\`bXTNT^bd`FPN\ZZd\\ZhZX\Vdb````ZZdFf^^XbZ^VZ`@hLX\XXX\L\LV^TbZ\f^PbVN`H`LZNNRRVRXPXVVnXTTDVNVR^`XdTZP\NZZTLJb\RVLbT\J``JNZTZPHNLXZX`TJ^HRVDRnRV`R\ZPbPFTR^HRTDXT X ^ b F ` P VTVHXNLLJ@d\V "Z#!%J%`&L')b(B*\)`*P*)T,-`-.10235N55d64T8P857P68Z687<9P;6::Z;V<\=>J>:R=96Z;::;P:88b79;7V7P7Z864R3\6J4421N5Z52Z4T3V346F442/.^-B.T-0/0R/P/.H-V0,T/-,,,j,T-P+N,,N++,P++/-T,R.0V1R6R36T4\4486V8X8:65P89;R:T;9=9;<^<``=>P>??^>A?\A?F?X?AV=N@N>@T@LA=?AT?BJ>b@`??==?>`;\>;<AT:\>:P:>A?RBV@R=;=X?=BCPDBRBBCNDZBGTGdEFZEEEGJ\GKHNPLPN\LKHJZNPRPOROOPLPTNO^MTOTNLZONPP\MPJMJOLJJHHKfKFDLEFRIHHZIZKIIITM`LMBKJMK@PMZLNPLKLTMKRMNTLRNM`LVKNZMMJ^LPIVKVHGKJLTKKLJTLNJHJLHIIGVLRJTLKRKPLIXIJNKGIDCEZFJAJFN>AZDAZ@LAABRA\BE\ELDACZBLDLD\FRFEPG\FE`FVJRIRKKNLJJDCTGVEFPDFPEbDRDfCHDbGNG\DFdG^E`IFIHFHLIMRNSPONOZRQfOQ^LRMLXLJIJKVKMLXINKXITEZHZJG\F^GKNLGHGZHVJTGKHKJVIM^KKNJLJGIJGE\CDAA^B?N?\CVAC^AJAE\B?P>F=@RA?>?>=?PCAT@R=<>\>\A>>Z=R:V;P=P;`;H;Z9b:P<\9b:X=PBPATDZDBEGC\EZFCGhIVECEVDGRChDDXDVDGEE\FGDCFDRDZCED@XEDLEB@TB?D?V@PFEB`@?@XA\C\@VABNBhBPDNBECEGE^DBXBLDTE\CRBBDdGBRFDLFPIdHHGGJZHJdIZMBIZIIHNIPIFKJFGF`GXFCEZDGDPFLFDDBEPEN@V>@AXDC`BJBEEEZAXA?NC@dBAZAB@T@HA>?@X@>>X@AALBF@T?H>BX@B`@fDAbDABZBPHCDELIZHCPCDNG`HHIJGdELBTGGEBFHEC^C@^B?<=:=<:9R;8X867\44323P01X0021/T/1Z.Z1V,.^.L,h./1P1^.P0,b-/^,`*-X,+,Z+X,,J,Z-.-+-N.N/X+j-\.X--`.V-./X32X0//X/T1/F30.^0/2Z0Z1N21X/1\/0\0.`-Z,T-N.L/0/1J313Z0V/-L/,Z/T,Z*++H-^-,-*Z*R+)V)'H&(\%($^%$%$%$V# !V V"RZ!RVLHR^RL\RNHH\PZ L V T ` R T V XN P NL^RRdhbXRPN`HXTPPf`TZPTfDTjL`NR^RN2\hFXVTPR^RTVJZ^N^VDX\X\^VRPVdR`VJZ`JJJ`VTVNVXTT`XbDZ^PN^TVfHTVTJXPZTNdVLdVTNJhD\``hbjTTd\^\dhThZZ\ZRjfPJ`TbLXNZPLXV\TZTTTNpVbZT^NfPf`PN\^\\P^F`NZJX\Z\PfLdPVXX^ZXFPVVXDfZ\THR`^TX^LX`dZ\Z^V\XNd\^VTN`fdhZVfRTR`ZRLRZ`D`\VRVTVZXdRTVbVXT\TH`\PV`TZbbZZ ` Z L R ^ h TNP^XV^L`TV^bXLXPXXXRXZL^P !%`#%T(R'L'^'Z(J))L*),T/Z+b/^02/Z22315P5\4X767\5567V:8`:9P>\=V=;b;d:N:9b;;9`;9:8:9;:R6^8\8F5L41642b32/2P4X2f4R121T02400T,/.>2Z,-X-f.--0\.L/X-,h-+J,,P*N,\,,+X-P0\,-T+\/0Z024J53N6X63L9H4<8P8Z8V9h;N=:L:>`<:;;<>;@Z@;X?@P=@\A?b@=>>>>L?V=^BAB^B?Z@@@@\?LB??=?Z?>==;Z@V>@=Z<=;^>b;L>>>\>T?N?Z?>?ALBX@BAbEJE^ERGPFF^EZGdJEZGbHJIIIZKLLQNLbLZKOZPbPRBBV?CZ@fDXBBFBTE^FTCdDEDXDD\GIGVKIJIZHHEDEPFJEF\FdFXFH@bDFCGDXGCCRF^GIIJJJJKVOMO\TLPTROMNPPOOLKKJKLMZLPHJKIETEPGJI`HJJHFfIKHKJIHHLNTLJNJK`HPKHERFZGHCTDbB@bBAjAX@DR@D?@Z@BR@\@lBN@BVBDBAV?P@?>=?T?hZ>F=Z=>J:9L;b:;;J<\><=?>>=f<=>L??RCZFFEDEFXD\EFZDPFCBCFZDDREPCPID^FVHhDHFGDNCATDfGCDbDVCA@PA@@fCTAB`EVDXAX@?@BVBC@AJCTEFENGDRFNDZDFBPBZER@ACZABARGEEF\HLG`D`GJfF`LGTIJbHIXITEG`FbGVGHTMJERFGXFEGTFBGEGF`EVDD^ABBBCCATANFD@VA@BABRBAHA?^?\@=P>J=?BBT@N?NBV>N@>BXEE@EBTB^FADNBCZCGFEBFCHDEFVFHBTFEGEBVDXHXGEB`CH@Bb?R@:?9<9N97P8^:8\6R2T01112f/T3X13L0L/^.f/H,-.,0R0R2^20V40-f/,++T.h,^,)Z,-.1-^.,/L-T-V.--V,T,^-,^/.0\1R1V11X1/X301T0/2130/0Z11\0^0\1^0-`-N0X0T./22J02Z2\0`.V1\.,,+N.^+*-\-^*P*L*+)N)+N,T(&&T&'&$$%N$X&#P"!!! Z XLZV T`JN^RVPb\T R R f X \ T N b Z b T X PTh\Zd\PXRZ^^`VjXLPXPXXNVZNN^\^ZdZfJRX\^hTTVPTT^nhZd^db\XRVb`RRPXbZRVVN\ZV`ZP^Z^f`^NZVLTL^\V^PXFPZXZRb^ZFX`dNJNVXH^VR^X^fb^^TbXZb^b`Z\XbT^PV`XdP`VT^hZVZVfTbB\\TBTX^^ZTX\N\jZX`ZRTPXPPXR^\J\R\`TdZXRXRZ`FPZZ`VR^8\^L^VVTbPJT`ZTHVP`P\^VNX^VpJJXRPRdPdLZ^RRZTLJD^T\PPHPPRVPH\dPT^NLV`bRPLX^LTLX T \ B \ T P `TVlTPVZb\X\\^V^NL !!"T%Z%b'T)')b(R,+V,.P+`..T1Z/Z32P3T23N4V5Z74F7775^979V879:9D;;LAP:?<\><99:d=T@N;?P=\=?FAX@H@AP@LA=BL@RX;NB=Z?RAVC^A@F?A?XA`?R>P=V=T?TBZB`A?=><>;B;;<>>P?Af@B?L??BBLF@HA\ECTDGHEGEJFCFHXLHLXHIJJMMLM^NSRUUVURMdOOPLZLJKVObQbPNPVMdOLbM^IJGbIIIFGJRENEGPFPILH\KLLXK`O^LJMMMNOZQROTPPOLPNdJMLNPMVNZQKLNZPXQTOLFMTJfKJNKIKIPNNPOZOVPMPMZMKHTKMJXKVLLNLMIIGbHTGTJF\E\F\CPCf@D@V<`A@`AXBBFCA@@BCPDCTGCRCDBCVDTGKEEFdGFXEZBLCBfFEPEFGGLH`DD\GbIECbFLILGNIKITLIDMKTPONROQR\SMP@TQORKTLNNJVIJLIfJH`HGTFLHMHXLNJBJPMXMDIJKIRKJRK2LMMJL^KHJIGJ\DEBAJ@ZA@A@V@?@J@N>CVAB@BA^BD@JB@P@>@Z>>V?><@;X?>=J<;=T97Z;=X:P9Z9R9:;\9`:>b>P>;R;D9V99:V>:X;:Z;?;9>;P=`>Z?R;<=b<>=;>F=D>NBZBDXETEZH`EE\CCRDE^CFXEDGIRGJFTFFNGZGEDGEEDBBXFbDXCBCXA?\?L?XB@`ARAVERDd@BJCTCAZBBAV@?bA@^CNAdEGD\IXFFERBBVAEZCXAACEDFRFFEXIVIFHEFRGHHJHJVIZHJGVHZKXG\IHZHJGIZJ\ILGGEbDCHEGCCAAABh>CRCDXB`DBPEA@V@AZDPCZEZFBPB>??P=P?T>AZ@RBA^@T?@T@AZF@FCCEDREHDNDEJC`FZEFADDCTF^GFFDFDDE^JTFEJEZE\HBCARAX@R=L;<9J;d?:9V<<;T<7Z8Z975X9\65^95594Z63P333R3^5012Z225h3\2P2H3f2L2.-F.F,.//,-1+\+,.V,T,b),P,+,+V+D.*++^-T..B21V114`4`968^6V8V;X8X=>\@N@T?PBB?TA@ZA`@>Z?NA\>L>=T?V?ZA^?CRBX?`BZ>=>>N@CR?>`?=\EABV@XDTAAAVBVCBFDBRGJEGJDF`FFDGNEGXJGFJ^JRMXNRNNNLONMTQZULQRQhSXNPZMNIRKZMLLLMLFL`LJHHVHFRIIIDFEFRIGE^FFNKKZLXMbMRP\MMfNLKVLMPTMORRXPRMVKKKNMJJLNLVMOORNLKMLZKFLDKLZKMKMNMRKVM^IJNOQLPXLMJNM`KHG^E^HXEJEGNBPDnDNDA=d>AJA^@AC\DA^BACbDDDXDHA`CBXAA?E^FHE^JPF^GRFhIVDVFVGDEZFFPGE^EIDF`H\ELDFDdHHJIINHGJPPKRQhQOOPSJRQdOPbNK\JTMG`KIZHPIFVJ`HNJJHPGLJ^KNNQNLNLHJXLbLNbLKTKZJGIVKHDHVFD?@DRCAAV?N>H>V?NA^@@AbBVCCECDVBRC@HA?J@ZAXB`?n@@^A?>NAD>L>X<;\B=V=^==F:b=:;999R;<9<<:H:8;<\@`<;NZ;V@:>>JT>=@^CRDATADPBBBAXCAAT?RABNA`CdCFCLFDERJfENF`CFhCADTCTBTBD`CTGFLERGD\FFBGbD`GHEGZFZFVGVFIRJGJfGZHTLJhFfGFCbECEnGGEA@BZ?AALDBPDLCEC^G?N@ZFTADLDHA@\@A?<>?Z@>RA`ATA`BP@=AbBdFDbDXDAHCCTAEBDDCDCXDCBDZFXG\BEZFCVH\GEGFFDBXHRCZBfBTBR>>?L@b;:<:86`324R0N23\223`1R0./,.D/V/1./^/V//01.-.h,^-V+H+*,--P/h12/b/.//,H+.,-H,b2Z1.T2^/`/^01P.1^01/R0V2H000T11/\3L12P1X/Z1`//02/0.R2`5X31V/L0d/,*,,1-^,)+J+**,)X)\'Z*Z*'X'&$'T'V&f&X%&X%T%P%" T#! b\T^ZJbZJT\Xb`FPTT V \ R P ^ V N b d TLVHRBfR`\TVXBPRffTDRTZdVfZTT\XN\bDfPhTZPNTN`PVBTX\NVbXHJ^T^`\^XVZ^ZT\\R^lXXJ^`ZXNZLV@`LD\ZXd\RVbVV^XVh^NdR\fNZ\RNTdRXZbZRXLNLVFVRb`Z``^PXFJbVLZ\X`fV^T^b^fNbR^^ff`dTRV^`TF^fjTdVdTPNTb^V`VNDTR`XZR^ZZf\^V^dR^\@Vb`VfZNR`D\bXVLbZbPZZ@LXVTZLZT`^dR`VTXRXbZZRZZJ\RJ^PJRTZRJL\HN\XL\XN`\BRPXZXJVR`VP^fb\P\ZfXPV\ V J Z Z N P P T \ V PZPXT`^VXf\VTZb\B!bV!D!!#V$(T%R*)`('()\*,Z-N,`-Z.V.<0T/\2R2R6V3J27^7T878X7R88V8d9V;N9N<;V;V>AT>L==T?AA@@N>X<>?@=TB?=;>Z=B>b?P>T>>;T<=>JADZCP@PBABTC^D^CDBbDGCjBBdHEGFDXGFKLZI^JNFMMMZPNPNNMMNROdMOHOLNLNIIJLNRM`JLKKHHDIlHDJEZHFKVGHFEF`KG@KbLKK\NPhNN\KMVOMQOROPMKI^K^NNLLJXNKKL^O\OVPLNLLLXQMLHMFMKLHMTN^O^NNJ^LKKJMVNJXJJL^HGGZIRHEDCECAV@?@>H@@BFCbBN?=R>V>A>P>>?=R?X?Z==>J=R>R=R?>=H<`:8Z;T:;;Z;h?;=<<`=<\:=X<==N=RbAB@T@FDDHFEDVDNERFDLEbBCVEbHZKVFJEEIHVIINHJXFGRFDPHEEDBRAVDFD?TBRCCbERCBTAC`A^A@@RA?L@VBBJEPERF^HB^FDGFC\ETD@RBJFNFCECZEbHZDGPGZE^HFEXFGLFFVFEXFTG?=N@Z?=>AXAbAALA@bA`?R@^BALCNDCEFCRCJCPE^BNCDlCTDRE^CAGLDIXFFZFTHCXETHJIFDXGXDNCBVC`DAB\BL=^>TXfVN`XT^`X\H^JT\X`\^fT\bV^\VPbRdXPN^\bbZLb\XH^X^`^\TbhDTVPNTXPPPPTP^VP\PbR^TVXPR\HdZ\ZR^Z^ZF\\XDTVfN`VVZT^^XdZTTd^bFXTPhXVPF``bPNdJXZJb`XNV^ZTRPRX`JZNVXPT\VTPRVbXVf`\ZZ`\^F^fdT \ R L F V B X PL^ZFL^HJTdTRP`NLdR P"Z`!J##X%&^(T)'N)Z)(*+X,.,Z/b0/.X3N3^1`275T7D85Z6d;778:::R;:=:<`=?Z;;PCJ@\>>?@X>=b>9F98X9V89;:88L8T97L9\;9;J:=V=:V?AN>>>?=J>A@@VALB?@??TELBCBBNC^CDTDGRHXGFTG`GJRJHJKIMFPXPFLOTMKXOMJOPROHKN^OKJHHbIJMNPLKGIZHDVIJTGETFbDFFTGIRIVKJOZORPLON`MXPPVMPMOPOZPFNXMVOXMKIHRLNKZMJRKKKPPOLHJJXLRLPNZLOZLNM`LNLVKTPXLKXIXMK`L\LVITJ>INGGEECEZECZE\CZDB`@V@`?>AVBJACB\@DbFRBEFFDDJBABACFEZDNG^EFEbFbDGGZDEDBAPGNH:FXEVGIEXFE\DXHFLGbFVGXHHNKZMNRN^NVS^QOXRLQ^OP\KNNNQBLXNHHbLJbLZHITJTLGIJHNII^KHMXM^NZMNPOLNTNKKK\KROKdLfIJF\LFGC@>NCJBB@@>?T?R@PATABITGbGCTCT@@>@R>AP???>T=>L<=b<>X?Z?=T;;Z;X<=Z>D>V>??PAH>`?TA`=ZAV?<^;:P=`:;X<<;V>X>`=d>;:;N;X=d=\@J=X<;F\@PA\>>>l@AX@BRBVATCC^FE^DCFbGCERFAB`GNEHIIJ\HFVIHPHGITGFFXFfCCCED^FXAPCNAAB@H@CDA^CB@BRA`C\AV@DTCETGFFEHDFFECCTA^ETDGB\GXDNCLEXENA^BNCNE4D\DDRENGXHFRHIFFhLRJPJGTGjJXEG`EGVGXDCBE`HLCEARB@TD^A>VD\A`EB\AHCANANAXAAXEBTC@=\=@>>L@?DC?\CT?AX?@L@D\BH@CERBDXCCNETBNBB?DCBZGRFETE^FFFEPFG\IHJGDEBBELDV@V?>R@=88R9\;^77X6Z442233\7J0/---1L.//R0T/2V3R0V0Z2/X//D.*d0--p,,P.0X10V5V0J2f.d,/V0.\01V13L3112V.\0/b0b2P0/0V2X/^2Z4V100221V101J1.h00L1V2`0050/f0/Z01-T0\,/T-h.,Z-,,J*Z.`*V)P('(B)(N($J&$^&'J'%R$$^%$"#V"H"Z!R#\!^ V "\RXR@^V^PZRRP^PdXZNR Z L ^ N V \ Z D P ^ T bbPj^ZJZXT\PjZZd\Vb`JXXbZJDLfT^ZbPZX\X\^V^bRXTX\P\`^PVTZVZ\NXXXddP^Xbf\bT\HZ8fTZPXR`ZHP^P^lX^dJNVX^J`DbTH`bPVRV\VVT^J\PX`\^RPNP`\XXZlbXhP`VNHXLjXdDbPR`dXNVX\RLVb\VbbZj^J\`ZBbXZ^bZ^bXV\^T^T`\VPd`^ZXN^hH^\Z\\NPPZL`Z\RJ^XbPTFPDbVTJ`JPNVRRXTRXJ\NBX^LZVRX\T`^VZNT^FN\RBRLdPNP\\ZP^VTZZPJXPR>\ZRXT^ZX \ R R R @ X V R TTVVbTXhFZZLVZNTZV`"P !"#T$&Z&'b(&*L'V)Z++B+,-T--R2\2/0l336V5d6\86J8H9Z88:N<8=9J=7;;T?=??V><?@A=VDERDZ>bF\CN@B?>?^>@N>T?>V;^?Z@:@@??N?<;V<^:=L>;^Z?=;?N>@;>@@^@?PB\?>>@?R?RB?^BBNBZAED\EEHEXJMJZJPLLNLMLOJMM\OJMKLMNL`MKHFNG^JPL`MMMMRJHGGIHFbFZFVFVFTGRIGXGJZNPIdNDLONONXPO\NXLMZNONObPQLH^KHIZIM\JJ^KJZOLNBNPKVNPMNNVLVKbMLMK\KXJLPNMRMPLMVLKHH\HFGHTF\ECFNDFDTC^CEVC?B?J?P>\??`A>FARA=X?T<^=<<@?X?H>V=\@ZAF?d@T==8:\=T=T=^=?^>NXB?=H?>NC=bAP?PC@XBRDTAZF@VCTDHEPFGB^E\J\EPDbDGEXEIZHGLIGJ\GPGRHHZJHTJEDTCbGC?APD@TAVD@BB`DEXCZGPEENBA\@A@BGCTENEDDFFZEGXIDBCBDAXEDGCPAADPERDPEE^DLHCTFDPHNHGTGGbILVJXMJNGVIZIHFDENDbC:EBVDZCZCBZCTC\BXB\BC@EBbDCAZBLA@@AFBBT?>N?D?`>AB?JB\??ZAVEC^A^>A>RD`@XDCBBBB^DFCbBDEND`HFD\GIZEEFRENEjFJBhB\BRB?`@d@@>Z<;L9\9J98\5R874\4X1\3R233T01/01`0Z104218/b223N2P2.1--Z-R/^/L.T0./0\3T0X...01-H1/P/0Z2^61X40N1/1P010T50R4\2/10P1.24T/R2`0`1J23V11R2F4N1X2211\1^/12`1-/Z2N-b-T-X-+)X*Z+P+'J+N(*'(*&R(R$%R'^'Z&L%$$!"V#"V#!T!B"Pd PRPRfZTH^L T X T V \ j T L RR^P\X\`^PDRbRNLPTZbbTJ^ZXJR6ZdXZXZ\^T\\X`Dl`b`XT\NNXTb^XPVb\PR^P`N^d\Zh\ZT^fV`X\`LJVdJZJ\^^T^XPZZbDLJTNLXRTP`^PPXJXPJTVDf\\ZZ`Zp`\VVXXPf^Zbf\bXPVTR^VZ^^^PfbPb\XbL^`V\TVR^VJRTbP^XT\X\XR^^ZN``XHT`RXXV`NdVdZbZfZNXXLXfTX\X\F\JdT^Xh`dZZfFZXNVRJ`ZZ^PXXT>ZTVTRf\^N\XVbX^RJZTRB`VRJTZZX`RXZZVVZJX`T P R Z J L \ ` P^ZRXVZ^\D^V\LTPPRLV!\L !L"!T X""V$b%T'V(Z')(J)*X*,P,*.-X0..Z3^2345X475T9Z9X87T:7f<9X:;\<<=N=:`;>`Z=\==>`?AAZBB@dAAT@T?PBR@??d=V=Xf;`AB==>^APD>=<;<>@XBf@<;;X:8V<57V:8V9Z7f:;<;T<;N<`@`ANBR?@bAV?`>P<\>L>@@ZANABPCACIHVKJTJJHRKLXMZILLKNMXO^NTIMZLVJTMTOXNPVLNGLRH`KLIKVLVOJJ^JEHVGGJHdETERFHFEDGFHHJZLONO^OP^PRPJMbOPXRJQOLPTO\MfPMHNTKKITJJINFNPM`KMVKLMOMK^L^M^NZJNLLPNJPNZHVITHNEFGFEXGCEBA^CBNBCTBTF`C???>@CRE\C\CTCBRDDGFTDLI^DZEBRCVA\CDBBVC@EPDTHDLHEDE@BXFbCPEE^DXEDLHbHGGLIFVHII`KKLLVPMbPPOHSTSROZNLMTNJNLOPTLLZKNIGGVLJHHKVJJPJ`LKNROJKNMONP\LOMXN\JVIHII\IJCEECDDAVF@ZEVDTFJC`ATDCX>@XCTBLB`BCCbCTDCC@C?f>?>ZAA>P==`@>\?=Cf@`@?L=<:<><`R>l@;T=;;b>;\<\;\?R@^BZ?NAZ?X<`?;R;:;;^==<@`B>L?^?;=A^?AbA?B?ZACbAVBBCEZFLGFDLEXGF`FEZE^DXHFIHHRLZF\HTI`IF^KXJRGVDDCVC@BBD\A@ADCXDZH\FC^CdCPDACCDDbFTA^G^GDEB\F\IHJFRDEZDBDCFJCBTFC`CFDDCDGEDEFFKjJKRHMIHGfFNGFHJHCfBCRFADVC@^FRCTDCCBXCBA\GBVCC?PB`?D=BXBXAPA=A@>J>??>?CX?BZA?N==B\A@V?ATBTANAFNATCCXCRCACBBB\EFDFFGGHGJFZF\I:FBGDRBBVCVCD>>=;P;788N8X4X75Z7564426^2/R310d412P1N02\/V013.Z0X0P2T0/0.b/Z/-`/d2N321V.-Z/V0^4N0P1P1b03325P40//h.11^3/X233V30`2X3T/2X14P1X1V2/R31Z1N322T3b0.N00N-\-0L/^/P/X/X.X.,,.T,X**'T)P+N((X&^(X(P&&&d'^'^%$$#T"R$"$!V"R"n"V XX V8`N\HNZZVHNfNV T \ \ ^ J T T P^NbR^`T^PLJVZTnVX`NXVZT^NTTJXdXPPBVXXZJ\^hZ^b>`Zb\VXZRZPT\VlRVTb`\BbZRVXJNf^`bZVNR`X``T^NVTP^\^R^LVJX^NbVVXNT`FVbnTNVXNVT`VfTLVj\^HfPTV`P^\X`XpR^TN\J^^X*`\^\^HJ\`\JRLZXVn^RXNZb^ZNZRVT6\bN\R^`bR^ZVTZhbBXVL\\^P``VPRP`^H`TRXb\RLZTB^NPH^ZPZ^`XVRTRdbR\XXVXdR^`ZRdXb`^\B\PRbX\PVbJR\NJTX^VT^JVPPdVTL\NPL T Z X L L XX f VVHTZXLPTJVX XRX "J"#%^##&Z%'Z'V()*T)P(R-+R.X00-/T0437X7446L8J6\::R9T;T:\9T:=?@X@RDBAPBJB@B?NA>?TAAN>R>R>;;?X=<\:Z=T==R=>R>b;L==;;R>=X?V>=<\<=X@>>>?@BCNABECEdEFGPFTII`KKRJJLNJZIMLKVLLM^MXL`LRPFPMILZJJJhJJZJJJKJH`IbHFFXETFGEEEfG`GGEHFJZNXNQOPPXLJNLMLBPPONTPZSRTOVKLNJNLXMLLLXONLMdLVKLKNORNKTLNRJXNR^NTKNDOK^LQKJJVJHFINIGDETELDDDE^EAPDDhC?A\B>?ADC\ABBCX@^CCENETGTEEHFBX@ABZDFBDLDZAADPDFLFITJPFRGD\EFDCHBENDGFZGXFHRHFFGREXHLKPONHOTRLSLQPQSVRQTMPML`RZSLPNKRJJJMIFHFTHbK\KMLM`NLMVMJKQLONPLNNNNLQKKZJVL\KRGFHEDZE?DXBFBNCbC\BBVCLEPEREF@RABXCL@b@`CEZBT@?@@>N;NA=T=><`@>@XB@`?fAN@V^>;?PB?:>T=R<`=?b@N@A>;;P<;X;P:>\<;^<;^??=>TA>\=j>AL@NBA\DA@CCPCDEBCXCEFFECVDHIVJERI^JJDGJEFIVJXGDGbHTFTFDDA@>AfDJD\E`FEGNIfEACACA`B@PClFPFDVDBDCDPGIPEFBjBADC\EBXDdDCCBD^DNBfCA`DREFIIJJJLXGG^G\IfIdFbGRIFFLDAfCLDdBR@BBPA`DTBTAREA@dCHAXBTABJA?H@?R>RARDPC^@^DA\>d>?=RAV?B=>?T@AhAV@dEJDABF@P?APFBTBBhCBCdAVDFXGDBECEHZJPGZDFJ`IHB@JAB`C@V@<^;\98b99\7847T855Z434V24N2.T202X110\1.11`021.T//^.L.^/F.2R0Z0b.R3R0^5J//.V.T/-P//2b2225L3T203/D0.\221H3`11Z3T2\01/.-Z11f22T0Z26442Z4L2P00d//2-^/P.H12Z.,-T-,,+*`)\)V(T)*+Z)^)''(&&P'Z%^%#$$L$"h$H%#!^$H X!P VR^ZNJTTdNNZ^X`H`` Pd ^` X ` H ZRX^ J\bbTXlhZ`V^bRbT\Tb`bZV`VVVZFX\T\JZ@ZTRJL\XNVRD^ZZNRRbd^\^^T\TTPZL^Rd`RNbTZ`VXZP\PXZZ^V`VbdVfTRLX`bRVbRPPFVZNPRT`PVRZNV\N\\VLPZ^f`d\ZbbdPb\Vbb^VRf\\jbRfVV`\ZZ`HXR\TTHZVXZXXTbbL^VVLRXDZfPhPVVZ`tDTRZjXH`\d<``VPJL`Z\^bL`RbJVZVXXV\@h\RXN^L^TRnT\V`VTZ\^TZ^dZZRNXFH^X^V`\X\^^hd\bXbRJN^@X^N`b^Z^ZZX`VZTTZXZ^ T Z R f b V P ` T f  jf^N^TPRhJRPTVPLRZddZ#"R#!#N"f"#&(N&((''\+,J,L-.X-.X/V1.237^6355b856f=8h;:L:`99R:7^877T65R56Z3X354Z6Z2P0V5V4`3R53023T0X3V12P01Z4Z/V-*\.,-++R/++Z0P,+f,+-\.+R,d.V/f/V.R.^/T00b0\1X31\5Z4R5`8`88T;75Z7:X99V@H@ANBDFC@fA>V>ZAA@<;Z@`=j==\=<@^<=<@T>>\=?=RR;V87H7`886X79:T98P<>P>^=VCN@AV=V<`B`@@V>\@Z>@\A`>>==>XBVDEDDbECCFXFLKIdIKLJKL`KJJLJJRIMLKXMN^MFLNJbMPIXLTIORH@FZJTLXK`IGEDFPDFLFEPFTHEXFGLFTFF\FRHZJTLMNLbPO\NM`QNRPTROSNOPPOPNXLTLROLNIbLXMM`KKZKKZLKLHNJJNIMONKMKVLZPHNOPI\GI`FEVHVJNHFPEPFD`ANBZCbDVATFBC^DJBTA>>@PABCCjBVCVDZDPDGDDTEZENCD@VEABTCXDDJC`ETFIVJG\KHHDGEEEDTCVF`GPHEEXHHKPGZIdJHIKVKZLMORfQRPVOXQjMHKLXNN`OM`LGIRKENGGTFNHHIKLbQMbQNNLNXOLNO\PLL`HIIJJGREDD^EDD@@TB?A@DNFAhC^ECRERB\E^F?HCPCBNB^><=b?P<:R@T=\<@:V>\>=>=A<=N<;^:N?=^>XCAT@`?>B<=<\9`9N;N;9:\<<=R?H>V?BdB>?>@=^=P<>f>N;^C@^BRFDCJBCbFCD`BCjGBE\DRFGLLGJTHKPFVFHFEEFF\EXELDNC^DHBVBABLFCZGVEXEDEBC@CXBLBXAJAbCCRDdCFBCFRE`FXH:BPDTCDFERDBbEDALFZCZDCCPDCGDFfGJdIMKVKMXJVLHTJVHFERGIF`DCEEDCCZC^CZCBhA@b?R@?A`@A?@X@V?AdB>^AV>@>XB\A?`>A@RBJ?X=>V;<@AX@TCAbBB?\BXCA@\ADANCXDCPBEFB`DJ^EHTFPHJFFGFGDCCLBAD@?R>?\<+Z,.X,P--N0013P4745`58V88T877X:V><=l:=P;;;PFA^CBVBDPABB@>@FB`ADB>bA>>R=?;J<::R;:F;Z:=@P==:H<<=B>@>>V>>>V?B>RH=RCR<;>?NCFDZFATCTBBJBDDH`JTGJFIILL^LLLKZJLMIPMJPRPdMbO\S@LJVOMVJMJ`IFTHTHVHFZKPHHdGFEFVEHFPEFFdFPGPFREHGLNLDN\O\LPOVROPSTTXRROQRPlLNJLLKZMITKfIVOTKPhLKKKRJJILHTMNVRNNJQDK\PNOTMXL`LHELFHNIXFLHFHGCBEBDbAABEjCLA`D\DCAB??d@b@NEFA^AABFGTFGHECC^DDCBXBEE8CXC`EHCPHPFIFGHFFG`DHDTBGNDBfDDdEEVEIPIHGJVKHVLXPOROSRVSPRPNTSOKMRNLPH^IEEXDRHFZFHXLHVLTMMPNOXL`O\PO^M`MM`JPJJIVKTHfJFFHRETCBBDTDA@B>R@Z??H@BD\EdCLE\FCBCVDLCDNB\A>V?J=V@=>Z=^=>R=::D=X>>\=?D>>^=>d>^;:=^>@\>=?XJ@>?Z?`;P<:T=T:J9V>LV>R==VAE>BHF`DNCPC@DCBGXFDCXDJEdHHIINHE\GLGfHJFGHVDCPC?\@RBCDHbFRGFEZF\CDBVDNB\AZACAAVDDBGZCBEDHGD^EPDVDXC`BFPBCANEXEXCDRCDTDCdHREGJI\JJMbMNZN\KHLGJZFPEZIF`HEGND`GDXDPENG^DCVCXBVC\D@@@?V?T=;?XD>@`Ab@@@ANDd@BV?>P=^?>V?\@R?VDDEEbCVFEFIFGHHDBDNEBBB\@=;>^>P9V88P78N985V6Z47N64Z8460P3/\00/R31R24./T2R020N/.-.R/0P2/d/R/X3P1Z2/T//1.R2L1b3/1Z524\3T34J4^1X2L3\1`110L6Z3151Z33^51V21X3Z52b1d43R3P1..,/,/.210T3X1V-N0-V/`0R+L+F)V,V*))^)'*'%(X(&&%d'%T%d&&V%%%$$"X P"R P TbTVXfTFV\^^^NN\X R T ^ H ^ b N J ^ Z^RLTfTHHX\^RNTN\hP\6PVVZ^TLX^TRXTh``NfbPV\\b^fdXDfZZV`TD`RXPlPT^fRVHZ`PTRNbbTR^dVbNP`FbPNXZRRNd`^VRVHXNZRVHVTPZfXTXTZRLZZ^rV^RVV^`^bRXVXh`ZbZP^d^f^`Z\bT^^V^J`XVTTb@dXTZXXVTTTTZZR\RP\\bZ\TP^VPNdDbbZXXZ^PbNRH`NPb`\V^lRRVVVZN\TXhX\XNdlV`PP`VT\PZ^Z^H^ZLPPZXHTZ`L^JPTDPV^`h\LR\Z^ L J ^ X \ T X V V N X \L Zb^XPb\fPRVZP\ZV  `"!Z#"!"#%R'&'b&V)'N(F-,-L-/T102/23655P3X6J5Z7b7\8b;V^:\:V==X<\<89`::9T9d>7T^>D@ACNB\ATDFA\?XAAH??TA^DXA?Z:;=R9<<>D>@<>^>X?=^>9Z;76L5R6b5X55T884\7:<9:b=<<><;@=>A^>PC^@@N@XC>X=T?V;N?\=N?`BbCXCDZCDBCPFCXGFLPIJfJZLMOIFLOMRKMLPMMLOdOMZKIGMMJHKdHGGJF\FE^HFdFBERDECdEBXGHGILGGITELJHJJMXQRL`ONZQPNPPQSSRPBSPOVQTKVMMLZIXLI>IXJMNMLKRIRKLVKO^J^OTLIJM^QNJMJNKVNVN\JGZHFDE`G\EEXGTDAHPBCPBPEXBPATDZBAATC?RCF?b@DXDLA^BCEFbIDEEHVGLB^IATB\CTDJDBC`CCRFFFDEPECEPC\FXDRDdCCECC\F\GIHTKJTKRKNJRKHLK^OPPONONROP`PXPJN\ONNRQLKdL^H\F\GILFDLIFXKIKPKXMOMJN`NPVQRMHRJMTHITF`HGHFVEHEDZDEZCCEABZECB?BBP?`BBCTDRGVD^CNEXFBCANC@@l=>F=\>;<\===?==N?=HA=<=A?Z@N@;L>R=JAT<??A@>X><<=;9`R=>j>DAVA@BEC^CZ@ZDBBTBD^FDZEDDPHbGJZIILKHGH`FEBXFJCEHRBBCA\BPDPEF\GGfEADDBZC@@`DRERBCBBTDREBBPG^DVCVFXEEPBAVDNEBDVDBPEJCTJJCDFE^HVJLZNJKLTMGDKFGLJKNJJI`GZJNEDXEBCJETCCZG@^CZBBV@?V=T<^?P>>@`CBTBVAV@NA>`ABX?ATB@>@V?T@><8J:R8:H=:NTC@Al?<::P:P<;V?H?T>@d<=<>;988X76P85P3^7F66889X;8D><=;`=\?=<>T?V@DB@AL@`@?XBT>?>;`@V>@TBDDBVCTCZEBFERHZGVI`HKTMFKONQRKNLLRMNZIKZM\KLNTLXMJJVKRMIIEHJF@EFDGCTG\GCFTEHFGdFH^HHHGIVHNOZMVNPSROONMMBQOSNPQXQRNZLLZKPJJ\KHHIbJHHJJLJJVKXMLLNMKLVLTIJZJHKbJIZLFGD\EPFANGDPGEPDPITFHCAPACbAC^BANEB@@C@CdCLGELCEFG^EVHRGLEDFBTDRBBbDDDZC`CCACBEZDFCXDXFVDPDVBDRDCHRHRJVJTNHK\JbKKMLMbPJVKMQOXOVQLLXKQMFNTNM\MHH\GFC^FFGXELJGIJHFLNLOPNLZPPSZOZJIIZHTLHEDCRELD^EZEFTCZEB^DTABJC`DACBB@V@CLEHVCDXCJDC@B>>ATA?\?P??f==`@R<\@A>PA@?\>>Z@?T>FAV@=>X=Z?;=NCAAA\?@;=R:<^;V<;V=P<;;X:?;<;X>N>XABEANBDJEBDD`CFHHNEdIHJHGTHLFHIGGXJILGB`ECDXC@F>ZAVDA@TDFHDClC@@XDB@`@>D\A?PCPBDZDbHLDZGACdD@@NDFF^EDEJFINDNEBDXD^ITFHMLLKKRLLKNhLRJG`GFLHIHMFIZEhFFTGZFFDF\DEARCVAR@VAH@VA=^>=L@ZDL?TBRH@BHCJ?B==F<@>AB@>?h@@@?DACEDFCHB`CBCP@XAAJHF@`DDETDCEXFGEGHGNGNHAGGVGDXCLDV@A@Bh@>?::8L86^=F7^66R953T3H3^21^6V20V3Z4331P5Z40/X./P.T0X0X/L-^,0-Z0/0N.0.0/X30V0T01V2P23P503Z32\31^0J//2Z2\32N1^03L6\48^303L5`621Z2V3R6V33R421/,\--Z2X0/100^0/V/X,Z,X*,*'Z)^()L+)X))(`)Z)X'\'&%X)%''($'R%\'$$T#Z"^!J"b"X"TX!^PN^N^H`PbTZTXNFJVR XJ T N \ R X Z P ` VVdVX^NNdRZVVXVRTF\\fhTN\VRHVT`RBbPV\VZJTR^f\T\JHZdf\ZV^b^XZT\TRhDZZThNZXR^XZVlX^\V^XXXZ\RVN``jPHVLXZ^dTPbPJVTT`P\ZNLhRPfXj^TXfdZX\\ZNRZd^NPVd^PlRVVVNffP\VR\NZZbZ^XZZ\h`TVZVJf^Rb`PVX^RXbZR`JZVZPZ^XXRh`TX\PdfPbLXdPJRNX^RXVTRZ\Rdd\TfHXRZRVPVVXXZFRNV\fLZZRP^JZ`ZL^VT\NTfVRX\TTXXZN`Zd`Z@RX\V \ d d jXLNXVNZ\VPRNdbL  R !#T$T"%#R(&#%\)H''*`++,T,.^1T20X2466X:^6685X89T689b=d9R=;:\><^<;J=Z8;9N<`:87J9b99^9X8N68R7d6V3`643b35V3^3T6X32^403\01B0d./J5h3Z..-X-R+P-d),N/+R/X0)V+*,T/+H,`-^.0R/++b,L1.V11/0T65P6L76T77;8^>@:X:N<<9=V;>=RA?F=b=\=b>Z<\=Z@\?B?@XC?XA@?Z@VA?V@@>F>N>;b?@CCCEDHDEEVH\JK\K`HXOLMKOM^MhMRJNFJILKMTHTKHIKfHHHGNGDhEEXEPFRF\CGG^DCDCGDH`JTHBEGG\HKXN\MPNLbOZOPOMNOOVNNN\LRLTKMVKHNKHGLHI`KKJPJMTNL\MOdOMfMLLNJ`JITJRHFELG`EHCCPEdDETECDLEEFPGdGNERFEAB@NB`=A@DBBGGDfEEEH^KHJINHDEBRCACZDAPBCCVDDBERCDLDCbBB^FJHTERDBNDG\DJI`HJHKRJHMIJ`MINPMPN`MJTObNLLQMP`MMPMLIFG^FHXKFLVGJ`HdHJHKLTLLVKPMKLNKIIHGJNHELCXEHC@nE@BRAZ?T@PDRDCFDCFB@`>V?PDATBACBT@T@@b@>X>?PBXAT;\=<>L?R=X=\>AX@?A?RB>L===H?><@J;Z>R==V;T>R=P>;d?V;V?\>>>Z@N?ZA\DT@A<\?;;9`:<;:<9:;dCACBRBDDXED^HFGHL`ITHGRGXMFFXJXGTHITJF`FJFD`BZDVAXA>@A\ANDDCHTDTGB^CA@@@\@@VAXBRBXA^BAB^DDF@BNAXBRC\CFCRFXFVIPCHDZEFCE\GGKQTMOHPLXJIfJGGfKJJXKJNIEFGTAXGXFXFZEPECCCL>F@X??>?R>X=<@?=DRBTBCX@?P?=??>H>R=@fBEPEVGBCCCBE@PDLFCEVFTDbFRCZFbEEXEGGH^GVHGDGPFdDHBBhCRCC?>>Z=X>V;9;899875T3T853N5T/X0R51H612N314H20,...T/.0--,b.J/-/,`-*,\/T0V1211V1J41R4Z2211J2T3\2L0111\1R22T0l21Z322P452P42T27V3\2452X6h23.V-R/b.Z/00V20/X1J-+,+@.,R-*L*,)+T*+`*(^*(('(\&%^'''N)&\%($%X$T%T#P"T"b$\#^\V!LbV<XNP\Z\P\ X Z P l V V X TXXZhLlPT\RX\RVVPZNVZPV^XjXb`\NZRZ\^bNP^bX>NRVR^ZNbLT^J^TPTVPVVVbLVR^NZVPLV`ZdPXFbjfPRN\`LRVPXb`ZP\X`VbR`XT^^ZTT`^\X`^Pb^R`lXjd^ZTVTTTV`PTfTZZ\hVjdL\FZTZ^``XTHfXTVLXTR^\ZLZ^^VV`^ZZThZ`\NTLZ\N^PN^P^``lTT\TPTRbPR`PX`T`bV\RTXVJXRXPRjRLVXPPZZLZXdJZP\RVFN\^B^VJTLPdJdZRXDRPNXNT^LRfT T R V ^ R B RT R LBRZV\`DHX\Z`^fTdZX\R P P!#!!R!\""T$%R&%'V&&^(J()L*++//-f3R034d7D8d8T66T:b798X;J8h<9Z;<=<9V;:T>N:\;<:97L98P/X0010-^0/N-X0b++*+++V.V*'L*^*+-R0R--^,,-R-L.--`/\10R//X2V4H6T7b87:78:9R;ZNBT@fFBA\BADR@TA`CBR?d@?>F<:X8`:T;Z9T:7\9L:7L9X888\6N689`8X:<;P=:>JT@@PBABTAVA>R@?XCNB@P<<=AANCVCFDDGEXGHHLKJJKRJdLPOMVM\I\KKdJLGIFVGJHGZIKHKIHINDFFCPC^FPBF\G`IE^DBCLECZGJFHXFGZHKJLXNJMMOMZNLN^NQJPQNOPLNLJTMTJ\IJDGRJHXJNJNTMMNXMLLQTNP\JILHhFGHJFXGGCTDdCBTDEEDTCNDVDRGCEF`D\DTDVDZB@A`AXCC@BJEPBVDRFD`FFGIVGGDdE`FJDPDDDED^GJDVDCTBXETCCTDZDPFPEDdCEBHbDDHHEGHPFTJGNKXLZNJMMLMMHMMLLXNNVMZOOKNTNZIbNGjHFFPIHVKZIHHJHfHH`JRMRMI^LNO`LVOHTJ^KIEIEDTBbCXCLB`ALBC`A?BRBRCBBZAACXCHB??CTBE?X@CZ?P???@`>@V>d<==D>T=R>?<\>N?X<@R=>@V?AX@L>>N=V=X=T>;>:=<9F9;:T;=;Z;;;h>NBTC^@DBPCA\CBGFFVGTENLRLHJGHKIVG`EKRKfGGFDVF\B\C@XD@?ZCAA>XAVBfFdEPDDCV>^CRALBVANAXAT@^AZ@ZDTEGC^DNDC@ARACbAVDZFHPHVJHDEZGDVIFXJI\KMPMZQLbKKGhJIZJ\GPHdONTNHGZHGGZF\EBF^E\FVDEXC@@>?CR>@F@H@AH@PAX@TBEC`?>=^<^<9?F>>TAFA?BT@AC`DTBCAVE@CFA^BBBCFDPADHKGRIGH^F`GPHILE\DRDFLDE@B@@?X><:<;PR?89<98:`88T:T8F9;645\7R85P5L4R72129\440d13V2X2.6X.V1-,-+V.N,`+X+*L+*Z,Z),^()T.L/-X-\+*,/..-Z//R2T0N0d2516888b7:6;V89;L;=99J::99<>=>9l=:R>d=>>f@ZBDf@AF@A@LBZE?@Ad@>=X>J=XA<>b<><\N@???ZBTD>D=\A^ARBR?AJ>>\=N>=??^ETAFCXB`@B\?>V@A\ABBAP@?R;?>F==X?`>>R<;T;;V=@@>V;L>H>>??L=d>=VH?\;::V=R<=XAbBLA`?ACB`BVD\ADHH\H\EPIEVFFZL@JI\GTGJHKIFIHFDPDEBTDARA>?>?XCVB\CDCPD^AVCC@P?VACXATDXDTBD^GB`EEC`ETFARBJA\DE`FPFFG`KHFIIbI2IFI\JMQNKIZHXIXKZIZHZJZKMZLLI`HHGEHFDGGXGCBRC\B?>NA@XAXA@Z@>?d>?V>>P=\;>\<=BBA>V@@LHVDGVDDXDB@ZAT>TBADCB\GCALDHfFRHJVGHEFTIjIDVBRGE\GL@\@B@@T;;T9L7V:P85H76T:R777`:R66H74^5Z3J7V34P3J5^6T422243P4^0/R0T1X.X0R.T.V/Z,X)L)+b*(V*`*+N,\-.j,V-*-V.V1.N01-`2311R52b3R7V8\7V6N:V56:N;;<<\:9;:^9J;<:=PX?V=Z?DX?A@==T;X=fAR>J>b;8V=:=Z;:=:\=R?>X@BX@BBbC>L>Z@N?J@RAPC@X=>`>L=^B?VGVFJRGNHVIbLKKhKL`KjJIPIVJZJGJPKJIHfHXIGPHHJPJGFKJfHPJ^IKNE@ZCGDDXD^EDhENFVDVF\DNDXIEPETHbHGGVMRKNKJOSKDOVQPO@QQPPNNNM^LKMNLOJZLJLKdIGFFPNJKHIJJLTKJXLVJLPOLKIKHFFFLFHXIDERIbCXCVCLEENFLGXERDDPCEGJ\FECTA\BB@f@T?ZBVAX@PCA^DDHCDEJEXDETDD\ERINGdCZGCBBFEIIIIBF\EFTCLFDDDTEPDFDXEFJGLFFIEbHHK\MMKKLKTIXJHKKjOLLbM`OJJXKNKIPJGLHF^GHMHG`HIG\GHNGGGGXEIEXFGPGPG\GJFHTCTDBBPFRDXE?\?PAVAN@ATCbARB@J=H>PE`@>V@XA@XEN@?=>ZA>?>>P?D>?:V;==VBVAZANB>bBJ@?L@@N>>D@>Z=NA@LA\@T?N@\@\@@B>?=b?>J><==NJ;:h=>X>@ZADJDRB?hBNEEF^IGVGFEZGJKJTI`KKIFGHHHbEGRGF\BZDVCRB^B\B>@A?@@VEGFBFEA\B@ZAVBRDZAP@bDTCDXFTCCA@ADTAABB^CGHFdHLGKXJ\KDGXGKTHPIIK`KNbKNIMNGJ\IJFXLKDNXMZHJJH\IbH^EJGFFVDCF@TAbBBAAX>>XARAf?^=R=L=T<<:;=X<>A?LDP@@^ARA`@RBRBDCTA@ZDXBXDBCXEDCNHE^GFXHK>HFGIGEF^FHHBCVCBBV???;^;=N;8V99X<:8R:8Z6332\7L24L1F30H00T0N//\0^-N.*N0V/0T/X//V-\0\/B-`0Z-Z+,+103Z0L236\2`410`0b0X1P2T2Z21\0/^00R12412X22X14154X46321\3V52J5L3V0//2V0.-Z../P--R/,-L-P-,.N.*R-,f-Z,Z+,)(X)N*`(X)+(\*')&(Z(&Z&V%##T#\"V! Z d!\Z\^PPbXPP\^VX^ZLZT`RXb ZV Z N R T ^ Zb TbbXbZ\FP`NbJ^V\RJ\BXN``TRLJPVXPZN\^RTbZ`NZX^T`VVNjbV`BX^\LZPXZdZZZTPb^`NXJbjVVhVZ^l\RR`XZRLjRbVHF^JRT\\^TZZJ^d\\TZHV^Vd`jV\lT\`VbVH`Z\bTVdP\bP^TTlXR\Lj\XdXRf@X^`ZTLfV^dFfXbXXZZ\\FbRb^nNX^^T`LXTXPTRR^b`RPPPRVNdX`^^T\VbPVNd`XPZPdTPfLV\\ZP`hV^\XXXTV^DZBV\FR`VRLNbdP^ZV\LL\\RPHNXZTZTLPRTR  X D b R P T J P P Z ZTZT`XRbRXR`XR`VRRLT!!!` !"!#H%"^'X'&\))()f+,*,P-`40P2L175569`77V:8J;Z:8:\<8@:979T<:J9^:9H;X9X<^:6V:746J8V68846N74P65X5546V34R45\3L51L21//R10.Z*,X*P-,P,d**R((h+**)N,+-,V.Z-,H.R.N0-\/P11X4112b2V4T7V:R;P6:X7j:R7T;8N7\=:;=T=V>L;=?H<;T>R<9P=:T<<>?T?@LA@PBLCBZETAAVA>L>`=Z@D?A`@=>??X<:Z::89LP=X9:Z8766768L977:f6<;<\@b>b=@??V@@>f?NAA^ATBT@dBP@\=V?`B@N@CLANA??J?@>X>=>?V>?=`A>AAA?VAABV=d?d?R>^<R:==\>b>=\=>@\@AT@@TBDXB?JB`DbCJ=<>P>=T?X:L97N:;V>@=A=JA\>B?DbCZBB@dB@bDAPCDLFhDGC\DABC^ARH@BEXDAPFXBZ@A\B?Ab=^CBB\DGLRGEJKHJINHXG^IGZHIRKNK MKJ^KMDJGVLJJKK^JITHHTKI^IJHRFTDGPFCZDAJBTBRB>RA@A;h?>H??>RACBPC^D^DPFGIVGVFVFHJ`ILIFE^JPIPGRGIAEVB??P??R?`VX`PVTHTVV^\ZZb\XZ^XNJVVPZ`ZhNfb`JTN^P\hTRdZZHfRVNNL\Xd`b`\h>`\\RZX^ZXFP`b\VbN^L\\bZ\dVn``dJh\LNZ\V^PTTPHdRR\n`VT`RPdJXb\^ZZTJ\T``BdR^TTb`dTh`^PP^^^TdT`V\ZfZV@NT^\8XTdLdXPZ^XTVdN\LJ^RD\XXT\VVRbZh^XTTXXZV\TF^RbRVT^LL`ZVTTXP\T^`VbRJTNFV\b^^XVNbFTP\DVdDT\Z  N X b J X \ \ \ Lf`HXLZX:RJT"X !^"\$$!#P#%($'J','R*+,R../X1N0V234T5H8T77\87\:7677R8:X;6P6Z9f9b9N99p8<;;H:85N;T;X65P8L6P8X55b7648V9R435Z44V7T53L4H516V3J01031L/-+V,Z.X+J+`()(T+^*P--H+J-H,+T,X.B-X2-.X2X1103R3L2273T6L6V6R78N?F=\LDZA@`@T?>F?>d?=P<`<8:9B<;;\=P:;9;<=>XAX@b>Z?^A=^AV?F@\==^=@J@B@\AXALAB@D`GRGHNGLXKMPI\JXJKRIIHFTFVKJVKIKZLJNJTGGHEVEDHLVIPEbIJ^HTEDBDCCHCD\CZDbFD\HRG\GZH^G`FZJJTKIPI^INNNVOLQZPT`TPXOVPLNMLMLJTLVMM`NPOIXILIHK\JQMLMM`MFMhNVNFNJNI^GNKDFFBEJDBbCRIXETDJBATABCBTFTCCFENHGHICDD@B\FCNALE^CCFG^FHXE\ECZEGDDGDVE\ERDXBA\BP@DPD^DEDDPDTGGKGF^EDEJITGNGZILHGKGJ6HZFZIHLIGVHRFVHPFVIGZJRNMXMIZKHVMTKITGIETDHHREGNIDXE^BDXCVCFETFDdEf@BTDB^CJZDNCV@@`AJBCABHDLATAR>ATATAP@?H?T=\BAT@?XD@@b?f>L>X>L>T=L>LANBBA?^?@A@@=T??>L=P><=^>;R;^B>>?N@\?=V=@@j@VARA\@P@B\B@T?R?>=>A\=;T;\;H=V<;;F@=@H?L?^?F=X@P>@V:b=\<>B>BCCJHNG\DEVIJLMIHTG`GFIG`HTHVGTFXGDRFEEXDRCCECBXCTA@h?NAHDTC`CENCCZEFbD@Ah@ZACA\@VFDXF\CREBFB@@LC\>DTAPCFBbHZIEbFENHXLKdKJLVLMMTLTORLLNLRKJXILHVJRJITK\JH`F`FJPGHTG\DXDDfGE\CRCA??>VB?R@V=N=b?D@ZA?V>;G^HFTEHE`JGXITHD\FZIHRHNJEA@f@Z?@`C?=<:;V>:^<<;d568444R6P31/\-N0.00R0T1J1-`+-**^+J,\+-P0/\-Z0V0L0.-\.^0,d2021/^20Z4\23R10H1j111V4^2b2\1L26N423T4T0N2J27L455T64P4T5V3\2b2X0R1`0J25V1V.h1/-V,N,d1,f,-T-`/T,^,`,N/b.V/\..T.+0+T,+V+(Z)X**H)L+)Z)()\'%^%b$$b&$!#D T" V! ZT\RNRDRZLZ`RLR<JXXT X \ X T ^ @ n \ b N \ ` \X`J\DhXTVJZTXRV\bVFdHP`ZVfVJPjFTbNdNNZXhPFbZVL\`XNZhXd`VZXR^`T\VV\RXVFHPfLNV^XZ^^LV^DT\RXbJR`V\\L`PPV\V^TJXLN`RJT^JZVXXVdjb^fPf`TLTbbX^d^Zbj`\hL^bbPhXHb\`bFdXXbVlX\ZZJ`d`TPd`^ZZT`Z`Z\FV`fFXXR^RbdbV^RjR\fPXZVVN\b^N^b\bLXRJ`dTTVVXXZNXRb\hRVT`PXVRPNT`NVZVZJRLJ\TZT\XNXXNdVX\^LXVPZRZLV\XZ\`VV\VdT^P^T b V T Z V \P ^RZb\\D`RVTXL `"#d!R! T$$$'&)T)T(N)*,-\+X.T/0`2^2675N:\998f87VVV?d@XBDR@VCXD`DJDC^C^BjA@VAB^?V@@??L<\AZ@Z?=b>X=Z:7J;:^>;`=:9T;V:8\8d9\8V5h9X97T77X89b?B@P>B=J>=XAT>D>@BZBVAD@XBPD^@BTCHENJIZLHNHTJVGJIbIGfKIHFJKKKXKMKNIbJVE`EDPEFGENGFNFHRIC`FZD`BRBC^DEFAFEFXGZFHGGLJXJIHKKNMPRN>TPRR`OVQMKJORLLZPKKKRKTNGfJZIGKMMM\LPNRbOLOTMZLN\H`GLEZITEFXHAFXBAC\C\DVFLDBBNCVDJGDEENGEFHEDF\GDRBDCC\EPHF\DJH^DREZEETGPFDAdDCCXBCGXEG@BA\EAZGEFZFXH^IZIJIGZJIGXFPIFHIFHKZFHRINEVGXFZGRKIVIJHDXDDGVHHJH`IK`KhMTNGPHGHXJFjFFEEDBEEXCE\BBBHABVDCNF\DETG`DD^BDAACXAN@APC\@E\CDbA@A@X>^AN;LA\B?^?>=N=d>>T?=;N?Z=;N>X;Z=>RZ>X=A?@BZ?>\?>R=J>?=>9P>\<>Z==Z?`=CT?dBVAR@`BAABA@X??T@=@\?;L:h:9V:;V?J@?AZDVCVDbEDDHHXKIfIHHVJRHILKVMKRJMNKMPNMHKKH\JNJXGNI\IJJHIGXF\EdDDVCRCFFZATC@f@@N?T@BX=R=;Z9T==>R>>l@\CA?HCdAFBADCCHPGFXHHF\GH`HDLdGHFRHKJTJDLXGJFLXG@CB@?;::H7R;>T?<`AD>V<;;V;HJ>;b>R=PAT?b>X?==A>X=f=AV@>RAZ?AZ>X@T?@REC@bA@@H\HJFLLPHGIRHEEPEFXIRFXGPFHNJNLRIJTKFGLEZDDBDFDXG^FPCDTECZDERDBXC^DTDRC^GTEVDDCTJRGETHFJI?PD?BPCBCDFREEBBFVB@XC??d>?>JC??ABXC\BH>@=V<`:Z<;L>AH>T>=\@H?>?CALB>=`?D?R>X;b;@==;X;:=Z>>:;V<;X;=\?N=?=`;<;>^CVAR=@\CFFCEVECGXENLhMHKMM\JNIMILLMKK^JJ\HII^JXKdIJIZLHGFGTEFPHBCDPB@>NC\BA@P>V>dZ=>b0Z/T1/./L3^//Z22.0H022T4R0l011T00Z33P3H62V46J22R49V72Z4N43H201/`11152R/T3R.T..f--/Z--`.+-.f/0T20,-,b,-*(T(),R,*N,V()*%&%&%$%#\"$Z$f"X#J "X!bPlNXL`^JPTL\bXT VZ R \ V P V f\NZVNTT\VZ^X\ZR`TX\\JZLLZXV\dZPXV^TbNP`ZJNX\^^V\Z`TR\P^T^RPVd^`FZFLJ^^NZ`V`\VFTRXRX\&L^PT\PL\RdPdRR^RPTXDTZXbfLVV`XNLZVJD^\Z^X\bbZL`X`\lLZV^X`bTbb\R\X^^F`pXVf\V`Ph^ZPTJ`bdNZNLjZDL`^T`T\ZVJhZT^VdVRRdj\TX^LdV^XR\b\TD^NP^`^TbRPhZ`VTdXN\\PNJ\^lTVZL^VTfRTVN`^\\ZP^V\Z^ZV`PTJZXTf^VPRNXZ\d`TZLRTNV \ P T X H P ^ X L ` B`fPVb`^`jNHbLTRXRVTT  b!T!!"V"#T$^$%'\(l&b(X(H*),,-1/20P4d33X5H5V;b9;77P78T4^8\7:R<6^7j7V9Z6884J;8H::\678f:786N68Z867X8V656Z75T5\66V7R6Z5N23R6/2P01/T/b3P--*,\,-\+))-+*))b/H-0L//\./X0T0V00X12`31`33H6^4T4P56X8879T<`99^;X;8`<=\;?;B<==Z=D=`>;dECTCGD^FDZCDLCD@A@C>^<=<;?AZ@?9=9`7:T8L867P;8797^8L8R9\>\;8:f:P;L?<>>=^=?>TAbCP>>X??L?TA>J@\AA`ATAANBDBC^FFIHPKI`KTI\FHIHTHFXFGVHJJLbIVGHJF`HHVGTD`EHLECREEEREZF\GhCRDHBGE\BbECNCbFXHVHHFXGXGGFJVMJKNKH`LbOMQPQTR^OXKJTLNL^LKLLIILELGVGJIdMNLJPLXLLPPKJTKHEEEBCCZB@@ALCCDTDhDLBEjBGbFXGIJGG\IGEFEVFZGTFZHXCXEVDFJDGXGETDEGDTGFECCFVEGVCCPD^BPEEFFXEFIPEITJLLHJGEGGFJFTG\GGbFHVHJGXIIH`KTGGVIDZBEZGFHHGIGVFZHG\FIHZFGXGI^CRETCBBdDTAN@>@??B^DATCDBZEJCDBAVBB^AJ@?A^AP?T@@@^CAJAT?X<=;=<:T:X;N?>`>\=>P;H9F<>^==P><X>?BDL?PA@^?=X=;<;P<<<<@<=?T@T>^DTDVFDVA^CXAB=Z>V:9Z>R<<=R;`<=<<^=D<>J;`:L<:9?^@@BDXHRFVHLPHJDHHJRHLKVHXGTGRFJJTFJFHDGRHJFEDPEEF^DCPFDPCEBVEXBZAb@@@?d?`CT@^B@BR@ZC\B>V>===R@?@DBhCVENFbEFJRI^KbI`JZKKfMDNXN^LKZKIJTNLJGHJ\ILLJbHNKIJF\GPGbF`EREB^ERAB\A@V?E??=@H?===H=h=:h:=98P>N;;=J:8;:>Z^>X=bTZPZRX\\\NV\ZXJ^bXXXRPTZ@`TXNTJN\VLT\TX\TVRL\^ b l ^ T R \ N JR\\NZNLNjRJVFZ^XJXXNRXPZ RR!V"V"Z"V"R&!$V(&&&V(`)R)L+P0N-0T.R0X/T0X366R7X:98H8V7^97:J6T97Z7;6V7J89N79B98V7\9R8B77P:V:T9H4\8V66P6T8R95P76\5545R58^6P74V5V3R200X011T.//V-R,+*-**T/H+)+/,,*/01L0\1P00.P1\/N0d000246`5475@8b:8:V;<:R;V=ZA::Z=;Z@@?@BAXDRDHHG\DFZERAEEREVA>>X@V<\><=R?\=X=^>?P>X@@X?\@?dCX?`=?N?@VBXAB?F\ALDXCB\EZFHJNJOVJRJHKZDGEVGJFZE^IGJGPHGVJHFLDDRFJVCH^GBGXFbD^F^FCGVEDBCArDB\DEE^FIGPFGEPHFZHJXHKTHLG`N\OTOS`QSHNMZIXHM\KZJNLVNNIKVGJHGRKITNHLXMXNZLNVIFLLZLIZEFDDCBZCHBBN@CDXEDDHRDFC`GLHFDIPGHEEVEEDFEFVD\ECTCADDFDZE\EEEZCJEfECLDDBZGXDHEFPGEFdFGEGGIIHI`NVJHHEFHKINITFRJGFGGIHIEHRGTEGHGIHEIPFDEDINFEZEFCND^FbDVCAXDC@>==\AL=P?@>BdAAVCCALDZD`CAZBLBD@X@ZCf@V?R?>F>b>>>>NV=>R?=;:J;Z>;T;B=?T=;>;V@ABR@X?<`?L=>9\=:T;97L9X9::=b=N=Z<;;<<=f@?AJ@bCBDBCAPA>HAR==VV=>=@>T<>:<;<\:;;N:=V;=\@@?ZCV@JCDGZGI^IbKJGG\GKHVJGPHGFNFNDD^DENDLGHINFCTGDZDDFCBETDbDCFDR>\DB>^?H@`DA\FA@BX@=?X@>CH;V>P?BP@>TB@FCFTGIXIFGHNIJOJKM^MVMIJXNdJK^JDHHhJXK^IZKHVK`FG\DDDPFPDBC\CBZBRBA@?b?;J=V>?H?\@VLfC>>FddXtfn`R\VX\hfThZpJJ^bfHZR\TRP`P^RTVLRZZD^D^X^`NVPTZXT`NRXTf\^hf\`V^V`bX`f`bP^P^Jf`\\dNRfPNdZJ\ZXXb\^TX^XZVVL^bbTnb\P\ZlR`X`Vhb\Z\N`TVL\Tb\^XTTZfPb\`T\\ZX`\^^ZhXVXbJJ`T^^TT^^V8dZRbXV`\PT^JTRNB^PVPVZNL\Z^\HfRbRX\LPZRXTRP`^NfRT b J V H X V B J V V V  bPZV\XXJXNR Z#V ^"!^"#X%&&T%'P(&**N+`+)b.X-T/1N1045L5f6776R8:5P86767P57b8567b:X9V5T687X9b:8\886N7Z879F;\8Z68j88L8574T3^5444202H13V1J0X.2-.`-/V--b++,**+*T)+N,,0T0J/T21/Z23\03N6P5P3X2T255^94R6X9^;88<f@J>PA?X?\@@ECREGTHXEHERGFJEDDAb?B@=A^=D=;>>R=>b=>:8989\9N8V8T99N89<9::7`:8J8:=;=>;@?>RC?A?BBTDDZF^ERB\DHIOZNTK\JXLHZKHHIE^F\HFPGPGXHXEPFFZGHFG`GBDDZBCDDDDDDXGCCDXDA@bCDRFbGDGGHGTGJGlHG`MITIFLJdMMPOZOQQPQXJfHJJZKNLMMJNK\GGHTHJIKHNPLPNPNNKJJJXGGGTHPFEGJCBPCEPCDVJJFTETFHHVEGDC^JI\JI`GGXIXGVGDbECCCEF\B^CXCZETDBdEFbGJILFDTED\GHErCPDDXEGZETHFJFXGbGDGGLGROLZOIKI\II`G\IHKfGNHFIGDTFXCNH`EVIZJDENGFNGNFEDTHE\DZGXDVF\ETHE`EZBBX@RBDVBZCAAZ??=d>BV@V@T@XA?B?VA@AAAdFdBbCXBBL?f@=T=`===b=Z=\<`>`9V::<9:L<;:D<>@TA\BRAJ;X=<@:R;:P:X88?J>HC`B?ECA@AAAZA=>^;N==N=<9<::PA;`A?BEADB\CbD\GGIIG^IDIIVJIIVJEFNFEZDPGGVFNETFNFFXD^DfDEC`CLBB^C@VCB?ATAA^?AVADBCTBTCLBAbB==N>@>?N@d@PBCAFC\HEPGERE`IVHJhHIMKOHKLMbNTKJLRKMZKPHXKNKH^MTIHdHZHE`DC@NFREhDE^D\D`C@>RAT?<^?<^@Z>R?R?<=NP;8:=:`7X6374Z301P...--`+X+Z-+/*b,V-R/H/,.P,\,*T+*,D+,+P,R,V,0X,\/>-,/N0-0V.-1b-.R02T//\20R13P2X1T1T23\5R4473^424P622J22541L/112V1..0V+-T13/./X/3./.1P/\.F,-\-F,,..,+*,'('f&X'P&%%'%T$$ ###\"V"Z`PN\H^Z^LRTL`LhLdTZ D D \ ` b ^ h dPZ`RhPVZJTT\R`NRjh`TTNXTRTRX^NdR\ZPfRZLZdTVJ\\`NZdZTPVRb\^\h`ZVZ`PNXT^ZV^RRXjbXXTjbR^ZHH^\LLdR^^\^X\`RRDLPTLNX`VPVPVZT`^N`ZXRTfR`XjjRVZV^f\Jl`d`bV``XN`P^PbZ`T^\^HX\\^Z^VT`RTDZZRTXL^bX\hV^XXZ^^\VVXP`XVRX\RhV`ZPPbPRNVVTRVV\\NLJhTLTXXRVLFVTPfdRZX`L@\X^VRV`XL`RbbVRdB\^ZNNXNVPJPHH^VVl\ P V T ^ L P \T R L ZH PL^TRTRbX\Rd`ZR\HbDX\RX\ T!" ""V!X"#$%&R'),N)(*X,N-X.B/1V4V116P6\6b6B6T9Z;V57X77P7b8;L:67X8^6\64:X85F78X5f96P6`7L6T6\5X98^9:R9R6d8644T9R57T745H42H5n4N123-P/\/,..-.*^/-D.^.R/X++Z,+0B,-X-T1\1V>N><^>B@>@XAL>\?TACE^CPEXGXFEXHTGHDHC@ND@RA?V<^?\>@><<=T;<::;\9R^>`>R?^?=@^APB@=NA>N?J=>?hAL@HAAXD\DHFB?PAPAXCXA?Z>P>;A`??@X@Z==`A^@NB@@HA@ABAEFA=?^>P>V==>T=P>P>H<9<97<9:V<:=L>^=VAVAF>>X>J<999`<=AbB?d?\BA?BATBC`A\>VD?d@@V@^>=><;Z9b;P@>??CCVCHDCPFLGJCjELGIK`HILHKH^MOMLNTLMRIJM\JIJJRJ`IKVJGL\FRHVEJGCVFED`EACVALAfAA@?@?@V?:d@?d?\ABV@@@PBCDFE\IHGGXLHKJKPLJXK\LLLfJTJL\HJHDZEDPAhDCRCR@?<@V?A=XF=X<:P9779b9X<:V;7d8F:`89Z:D9Z9P=N@<>

d>L>N=r??@DCDEXG\IVFdBEH^JRKIHHVJHGVGIHZLJH\H\FRGJTGXJJJGHEVFHCGFbFFA\CV@BXDAJDFHXENE\BFDAfDZENDfDFHGERGHJG:L`KLIILLJXKJMMVPMbLVKLPOLNLNMKKMTKNVHXIdMFOVNOMOLLIFGPFHNFEGCTBTDARBDCXFVGTJGlIG\HEHFJVFVH\LHERHTIEdITGGZHVDTDLCRCTBdCDLD^CZFTDDDCbDC^CJBZDBB`CLCBDNF=Z=B`@H>@X>\>;J;@XAVB@C?@GDACfBX@>V>L@R<9N;V<;\;T;V:Z;96J<89:7:=R8\87B9V9j:Z9;J=Z;X<<<<>?@XB\>T=\;<;;;`;;>?>RA@NB@\DDAR@?>`ABXA`?V?>A?V@99<@::P<;;>X=Z<;b@N?XABRCBHCLDZFBPFDFFbGHKIbK\JIXJJVM^OLLIKJJXNbJLJKIJKHRIEbDTEFREZDRAPA@@=V@A?@@@>Z?L@Z<Z<:;Z8897^8d7P=Z;Z>>L=Z@^@`B?\ABEZD`GNGGFHTH\JZKLVMOLfMKIIHJI^GGfFDCRBEGXBB\@>N@j=AZ^?9:7L8333F3\5Z20//-\.,,T,,d,V-X,+b-X+(*X,V.^++j,F+X+T+R.Z*b,//0.-b0\1,^/Z.\/P/Z1b1P01b/\0/f0L02V/`30V03355R655^5Z14^2H1X31\1X222N2412X0f//f1/T.2443N100N0`020*,^.-V.-N/\0^-+-^*(*(N'&%b(%%$X&P$L&N$`'"" ^"X TZ\T`^D^J^\ZNZbhHdNXZ h ^ J X V ` N J \ B f VVdPR\VJXXTLTV\ZX\LTZTVZhJF^RbjXVdZV`LTNXLZZP\TVZN^HdX\\b`V`RPX\\`NT`V^RP^`^P^^RPZZTR\\P\`P\\\VNXTbXLXZP\ZRLXhLJJTZ^F`h^RTTXNLVP>NVdLbXRbLZ\XTLPV`b^dfXX`ThfVf`d\jTVdNLTR@Z\ZXlRd`ZX^N`RZRDP\bVVZPVTVJFZR`fFbJVVT^`LX^XRTTZfd\b^@`RXVbT\\D\JLTPZ\VPVbPX\bXbRfRHNZLb^H\LLVPVZVLVR^FVHHlV\^FLTPLNXTTPLbJbR X ` Z P \ > Ld bN ZJ>XZFRTTXVPTP^ ! L"N$!$T$"#%P'&'&V),)R,\,N0/T.X0R0R3P3X7Z58P676P8V8L8:8;;N:6@386Z664V76V6R96N7V7H7b7647T6T56V98X7R9T6V6T6^7:6\756L64\3262J0N0N/1X,0/`0Z.Z-\-*\/N,d/J,*N,.N0H,X,-2^30/000483T23L4\649;74Z9Z:P=9\9;<:9=<=>V@VB@>TC?>ZA=TAE@?AXFCGZGEPHCXBVAAAVB?R@>=Z;;X;=8V;X:X:Z9;Z;X<:^=V;P;;86T8Z;R899^;:9\<9N=Z;=;P==?<P\>TBAPBD>@R??@@ZABBZDRCPCbDB@A@R><=<<<=N>R;\;<:;L:J;NC@PA;F@R@?AVAAALC>A@AV@=@Z?X>>>J:X<;?F;V;;9;X;PB>BR=:XBbBL??RCTBCEHXGGHHXJIHTIE`DPHJIJHHLKM`GJFdFFGHbGLGFFGHELBB\ACARBZB^@^@J@JAE?ABP@@?P@A?>?A^ADGEBGJECBEANFBDFFGKJKNJIKXLMXLRKPJHZJKhJ^OJ\JJPEEZFFDDLCGCZBTD^C@AR@B\@LCAB>R>;:f=<=9b;N<^;9L=@=:P:P:9H:T8;b=\>d>?\BVBLEF^INLGGFKL`MRJhLXLKNM^JOPK\GNK^FGXEIVCDVDNDJCVBV?@FA>R>N<;>Z>R;^=T7^96\664110T13L/V.V,^.b.d.\,+,Z,-,,*N,,N,.+B-N.R*^-P-,J-R,-V/V,.Z1Z.X00R1b1P200L.T/X0V1././102`2V4N56V5P330\3\3 2R23X2d1X4V322P20J11H2P//121N11V01/X2\3N.-.^----Z.0.,/*R*)V('&%T'R(N)T&$&V$%&$#$L$V#\#!ZZ XHPTbR\PV`\J^VTRVLfVbJ l X l V H ^HJdN^JbTTZ`RRRf\^PZdXVDNdPRTT`^N^\Z`PZV\TVTZ\V^bNTXhb^N`N`XdTTV^D`Z\RVLZ\dNTdXRDb\TXddbNTN\bXVPPRZ\XZPV\fLV`H`RXRRdRTVXXNZ^ln^ZhTlf^dVVXPVXPVZ\HhVZhPRPXRTbV\Rf:ZdXbPR\b`RJZZl`TN^LNV`RbZVVVVJfNP^dZ\Z\\Z`V`TP`TZZJdTXRNbP^dPXZRdTV\V^ZXN`T^FHZbXZV`R^XNfVTTVV\^ZbLJT\VTXXZXXb V ` L P \  P NXJR\NP\XZLNXXLT`ZRJb! X!R$$$d%#d"$$')'\(^-+T+P/^-R/0Z24V4^5X6H3\7P8V77N97^BN@TA>T>@DJBd@Z?AADFVDGZIVEF^CXCCAEdALCZ@><^?;;`>:9:8`9H:V>9;V:H9^<^:8:V777:;;:9N:;>9<N=Z>d;=;R?=?ZA=>B>ZCdBDDVFPFTE^GG^EXDPGDdGVHHGGFNFGjHILIHHIZGE^EEVG\EETGBNEVDG\EDJA@ABZBG\CXGEEbFVGGFDETFDZGGPJ\GNGJLGZMMJFHTHRFLIXKKXMOZOZNIKJ\LKMPLKLXLO`KJKJNJXMLMMJFfIDDDHDRFhCBb@bDXCNA@NDREH\LTHIKJJLHJKVMKF\HTKIZL\JHXIPHF`FFE^BdFECEJJIVGTHNIFHTDCDZDCZBBRBBDE^GTEZGFVHH`JFTHVHIdITJTJ\JRKTMJJhINJ^M\IVGGFHC\DVD^BXEPC^EZGE\C`D`B\EPGEXEE`FXEDEBD\E\DAf?D>?JA@X?<\:L:P>=RAP=@@b>=\=J=n>dBD?VB?An@F?V@\@HA@AN>P=\<>8N9^>8`::R9856N8Z9Z7R96B96\5V85N7^78P898:X?X?=L?A?T<:V9N999X9R7T9d9<9::;`><=fA><=?T>R@?R@BCA?B>^?^@B;f?F=?P>`?BAX==:T

?j?=>V<;R=X?VBX?`BBNAACVABVCXGVGJNHbMIIGIHIHGXHTHHPJXIFZG`FHXIPKGbIFVGVFGFPFBEB\EAA?@TAD@@?ZA>@VBVBJCFZHRIZDVCDCBCXCBdHHNJVLNJIIGTK`MLdMVNJLLNJOdJ\NINHZGbGDNFZBVC^FZDTEdECDPBZBB@Z@^?N@@T@==X\<;P;V;N9:;9<:9`:^;R:T89Z=>;\@=VB>CREEXEJJTJPGXKLHJ`KXNLJQ\JZK^IFXG^IHHVFFFCLHFAJBTB\>V><=@=P>4>=?=<;988^5d5D3T1Z321-P.,V/^-,00N-,R(Z)Z+,\.\+-,d-N+\-,,\-R/,^-V+*,/..T..N//P0P/R1/N-1Z.-^1R0X/2T1V3X76X3T42L3\7V4310b32X21453X2N5T232R0V12V0T234H10X20P3Z1P/T/\-,...-R//*X*(F)Z*^)'T'^*%&R''Z'\&%$P%\%V#T#$#" R"Z VPL`PJVVXH\RPJZT\ R ^\ P T F P TTTR`VXHHLTX^LX\VTZRRV`dNV^Z\TZVPRTZVZVXVTVRXZdnLJbHVZdZbl\VNfVdZXL`bTPLFNd^TRPhdV\dXRbVZLX\NZ\VVZPbR`TRPdXXNbXH^XTbLNX`TLJT`b:XNZh\j^bNZdNZDXd`PPZh6RN\TVZT`NbXbdZbLZT\`P`VT\T\dZdTjTjT\FZTTXb\RZZ\XNbXR:bZLZPZ\NTP^\`XVNZ^^VR@ZVTZTVNJPTbN\ZRXLZ^N`XZZX\VLVDX\XPDV\L`bHVTPN`dTbRPR\VbPR\X X ` R  Z Z X P d RVHV^\VHJNZLZT^VRT\ !\#Z#J$##T#"T$V$&&P&(`+X,J-.b./b0R204f7X5Z4P68N7R8X788T9P8<9:R8787T7P495^4\6T765P7Z674`7H;Z75T57F574775d5^6T74T6P33232120P3/1/1L0,L/0T--+F,`/X/+.X-J,,H0///031N3232565X474T4`7:<9b=Z;;:P?V>\;=L;\D?AR@RDVATC>AXCRAANBZBA\@@DF\IFFFTCEACDDTCXCN@AB?<>V:Df99^>;8V;V;;;V;;=@V=>\>R=?@TBC^FCCbAFNHEFEHLBVEFZGD\DHIXIG\HGRGZKRMNLGJJVIEFVEFZEHLFXDCBRFENFGAXCAZC^CDD^EEDGVEGFFENGZFVGBHHXI\HVLXKKTINMNJK\IVGEIjLLVLOhMNJBKFKNVJLGLL^PNPNLHZKRIJHJVLLTLIJ\HXGDDRFJC^ELC\CVB^AA`EBCTGJJXMRIHIZJLIKTIRMJFRGGJBKLdHHEbHNCEFEPBHH`JHEHGTJHFREXEEGFFEEFVFII^KVGKII`KJKLZHbKJLLJHMTKKTHHfHFFFEE^FJGEVACXDTEbHXCERDRBB\CCTCVETCDTFXC\EERA`?^C@ND^@>^?P?R=>`AP>=N<@D=LA>TA;=HB=dBRAABdAAVAA?L@P>?X<;:R;==AJ@>=;88TP>VAN;d<\9b<^=Z;Z:L@^@?:@\=Z=Z@===\>=T<>?V??AAC@ZDHEFCLGIGHNMVJXGHZFHHZJRKJ\HLK@HKNHGPHJI\J^HGETH\HFGjFEE\DDPCLCXE?\?VBBT@f>@?DBCCC?T>Bf@P@>DDEVCLDC\CTEAZDfBCFVHHKNLJLXKPMOVLOILRLTMKMNJdKLIHVEJFEEDVDBCXDCBVB^B@\>?b?N=P?<=?^=V>>?@R?Z?Z;;J=Z7:6421^1N2b/-/,1^,@/`-+,*,L+*+Z+X*\)+.b+H*.,L.L+P,^,,,.f-4-,Z.Z/-/T02.V1T0^-d.-11/.14275Z54b42V323P420Z22R4\2X464`83Z2101/\441022T00H//^3Z0J.T/11P/Z/T.)N-*R*Z(X+L&('\)%'&(%X&L'h$F&R"""X%#R"! !P Z`TPTN^XPb^R^N XV \ `d Z\ `Z`VhXbbfhPXDTXZN\fNTPTPTTJNTXbVZXVfT^XT\PVZR^T\V`T\X`RbNL\NRXNRVRZTVbV^XXHXXRhXN^VZHh\bVRL^JFVLTTh`V\XBXFZZn\^ZZn^^^hdNd`\^^jX`dRj^tXXVfH\XZ`XPXV\Tj^N`XfN`^RZRRTX^T`DV^VJX^RVXTZ\dT`H^ZVPXXb^PZDfNT^TXRVjJV`VXRL^NhVbR^ZRL`JZT\\VTZb\^LhfL`dZ`JT\RTNPXVTLPDFZ^\`TV\Lj>hZN \  @ J P f V H T F T ` X`XT\^Lj`TP`> #\$"\#$$J&`%%)X))V*^,\.V.1X0N01^5J3L3P57N65`75\<8:X9:9X69X653Z54R4536b44^9546Z74L575H83\5P67V68\78734l4V3T1\121Z2001^/02V/^..1//L+.-d-j/*+,.\/P-,f0V.3T2R3P524\3X41N74477R8N9:89P;\=X;R;R=;X>=;?>AA^>?TAA@R?@AJBBZBZ@R@?bCDTFPE^DZD`BCJDVFXFVEbA>J@?=T:X;9:N8`=b@\?X>R?>J>@T>Z=C@@bC@BBBJFCNFRE`C\CZCTEbFEEFdH^JTH\IREPB^GHZKTHILFTFFZDVDVGTHFXGEBCEEEVGXFALDCCDFECbF`E\KGHPIRDNGVDXGVGEDFFGVJI`JPMKDLLGTHVFXIJNNF@?XA<=J=?d?@@?X?ABC^CB@CLAbA@dAA?`^;B=\;T:<:;=Z:P<9R8;L?>V>>V?T=?R<=X=?AAB@LA^@\C\>X=;@;;Z<\;?T>AJ>==;\@T=@?CACBNBBPDDRF\DRAEZAHGG^HJM\KRH^JIKL:LVLNJdNKVPKLVIHZHHVGDXEZGHVJJDTECCAAC`@>F???=>L=8;:\:=;f:H\;=f=>?=TBTFHFXEDTEDCDLF\?HAAT>>=f<\<:X>;f>?;=9T>P;::T=><;d=:;H?P?@X?>>R>=V@AB@jAbAFBLGCDCDCEVGCCZFVFNHVEEFTGZHHIF\FGE`IHXJJIEECJE`E^FFDXDDfDF\F\GZECP?T@d@@hBBDTCNDJEZCZHTDXICCNGPFJEJZLVMPKFJNIPINJTJFH\JRLXPNOTNOKLMHMMTPMKPMMNTMLjKFRHHNGMJKXFIXIED\F`BZAGRFEXDLEDDTCFEZHJKG\NINLKZMPMLXJHVGfHILIFRL\JF^EA^>PAXCDFVHXH^I`KVGGIGEFFPGFFXGNG\HKbKRKIL^LKbKNFLMNJJdG^IH\JJJGHIZHFBRBDZGHCCTD@FBnCD^BZDDHFNDXEGVFXFDFhETBLDCFJBCBAPEANBA@TA?P<^><@@V?ABZAPDECZEAPDAADd@V?L==\<\<\9:;>;79V8`9>9=9H8d<789X8T777d98d6`8B78\:8=P<==T<=L>Z=N;;N;P9Z8:9`89R:X:T8`:Z9Z:=R;J;b=b>F=X<=P>?==>`?X<T?P>X;V;9\;89V:==T;^A=>>b@J<`>T?A=@LC@AADCGH\HTHFJ\JNGIVJJVKPLLGIPMRKLLG\J^IPLIZKIHKIGVDZDbBL@TFA?F@?TD@`ABT@ZCLAB@>h@L?\EA@B`EBXAT@A@AABVBF\GRJTMfHTKIJPLJbMK`OVJORLLLNMKHGGTHGDDIFFZDDf@@XA@`@^C?N<\=^?V<:J=D;Z;9:<;P=6H9`8L7V98R8D>R>AdALAADXCBZDZHHTIFGIfGITKFHHbJGEGHFDPCFFC\E@b?X??T@X?V>VVJPPLP@VVT N d X P \ R Z^hfZTbTTNR^V`fbTXTB\`VJh`ZRZ^RZ^XP`\d`Td\VXZV\ZTZZ^R\PdTdLXRL^TZTN^BZZfRF^VfRZTF`TfTRfXTjPXPVVPdRPVVX`BLTFXRNVZPRPRjXV^\l^NbVbT`\VZjVXT`fdNhhVZ\`XV`PTRVN\NdhVJ^TddZTN\lV\`XdTHZZPdVbRNfZbTXPP`LhdN\V^P^`XHdTZf^VRTTL^XNVVVZTLhLJ@hN`RZ`VPL``DXNP\N\LZ`NVPRRX^TV`Lf`^VX` Z T T Jb : `TXLLb`LD\f^fXNdbPL\^ZXX!X$^#"#$J(\&Z'^&\'&'P*).-0.N/1V31b3Z7X5V6D76V85L6Z9:T<:L8R:d7V:867`666P7443^34443\5\52T7`7886d7B8X73h73X4X5Z7T423`2`211^/200R0//-N-`../T0R/.^0J.\-V.^--/Z.-^.-2^3Z3^55^26R465N64T8\9=Xd?Z>?XA?AXA>^DBBABVCVFBZHVC?DbFDXCEbGCNC^BTDBLC\@d>R?T?\===:;T<<<;\<::69X8T8\8::T79J:;=T>V=\?T=;<98=N=;:\:P>;<@^?VA@^@HA?^AR?RC@RA\BBTDDPFfDEGEC^DPFTGPEEFDRIXKhJXGXFFDdDRCXD\GZFXGFbFCCEDZG\FGFDFDREHXKDFA@ZAVBAFTENDdERFFDdFDFHVCNFVFlFVGFKXJJMJKIRGJJjHHKLVNHONVNZKLQK`MXKJL>MLROVLLVMTHHTGJXIGFGDHELDVE\EFEJGTHJGEDERIGPHZK`HVK\MPJZLRMNbLMXJVHVHTHEGGITIKHFLEBCCBEFEF`D\KLHJfGFELGLFDTJFREVHZHHHKLVLZNJJZKdMQMJJJIIIRIPITKJKLGNFHCBdELEPD\CC@ED`FFBIENEEXDTIBFTBDEZATDA@A?^BN>B`@@X?AZ@?CH>>>AR@>NAb>?\@R@@CAVERA`EBDVDA@L>Z>><<=J<=H<=;b9N=;<\>ALABXBCDPDDI^GPFTKPGHHXIRGIRN^NXMVN^MMTQPJLJI^HHIDLI^IGGPHNFFBD@A?X??ATATBLD@AATAAAR?BbA^?BADXACAR@VAVC?PBXADLCEJIKL\JMPK\K`LTLKXJL`LVOLFKKIPEIITJETGEFLGVAD\?A>^DV@>@>^?\><\<;XH99Z887V8Z;=d;T9f;;^=;Z?V>>V===B@CPBBHXCZEXKVIGZFFIGIJGJTGXKGHGFDTEF\HVERBVE@VCXDT>T@p?R?:;N8X9N8P78444T2`4Z1/h1T0/^.Z0V/-F,,+,-J+V-J,.*Z-/,,*.+,-+b**T++-V2`/X-.R-.V.1H0P/H/31F4T4h20d5354R31P0T5f64N124R4`5Z346^364L6X5T66X33X222^1231V05D/-/0.H1.Z.,Z*)R*d*T*D)^'\*P((^(**'V)N+'`%@(%'P%X$$Z"$#$X$" !ZVX`FVbXZ^\ZXNH`\N d Z Z R ` Z Z ^ \ZJRbdRJTVR\P^X\TVTfZ\h\ZbZV`ZX^RTR`FVT^TPRXVFZXX^X\fZVdbh^^NZ`Rfh\`F`P^VNV\V\\\RZXN^`N`bVVbPXV`PXb\NZXV\ZVL\TRLJZ`NN\P\X\PRfFNTZ\f`ZhZfdRldjN^^d^Zb^fN^HXX\RZL\bH^\Z^ZhVPZVPR\dLRX^^T`\`RNZVJ`VZ`fR`bTfZZ^\^RZNR`RVRZVXRfNTLXNXZLfXbTd`^TVZ`NN`VVRH\P\P`fRXRTXR^RZRT^^XNj\PR\RX`V\RVXPNLT``J`d \ \ Z P X > P NXZPZHTZ\fPJP^VNPZ@XXLX! R!#V%X%R%Z&X'(&'Z('T*)+X..0T2X43X5R3H8Z6b66L5J8887V:V6^88N9T9686R7V6b6475Z4b356452H6`37L6V565V7565\443R6f4\4F6P43T12T22V200X1/0\3F-R.0Z.N0b/L/-.../-/+T-P,L/Z1X3b30^2>333346R7P966d9:`>Z;9Z=Z?=R;<><@AP>AHA^??XBVCLCVCB^F@BXCCECCNDVHEJDGDEZDACBAZ?P@d=V;P=X<==;X>>L=TA^APB^C>VAR?JBTCXDHEZBDRCVFFXJTFGRJ`KGEHHFNH\GF^IHVEFZEH\DDEFTE\GCbEC\DZDNERFEVGEVETHGXEEPDDCA\E^CLBADFTDGC`DBFTGDdGXHPF\GGGJJ^OZKHLVJLXJIZG`JMLMNNMMKNKHIXIMTMSRN^QNKTKFG\FIHI^IdG\HJGHECXDERFEVFH4GRHEFGFKZIINNJJTPNMXLORLMNJTJKGFIPKGFKbFG^GNFDC^CBFHD^EXH>KGG\HEEZGhEXGFEHbFFXKVLLMXNhLJKKKJKXLXNKHRMJVLH\JRLZH^JGELGEGCHTEXDXAAFFBFDELFZIfFIRHEGTFVDNEhCXCZCB@b@=R>@JBVB>@ZA@PABL@TAL>@ZBLD@JEAC^C@ZAZBDCJA@VA?>R<;<:;N985N;`8H56J8678R=9Z<<\;F=Z;=;^?^>;\=R<=L>=<^9^;b;R=;:^>=J=<^>D<:P:^9=>V>X?RA\@DBCA??\B^?AALC\@LDCFCVBBBb@?fAAHGCPFZGVHdHVIVLLNHK`LKXLPQRMXMXLIJI\KHDFFFZHXECPA@`?P@?J@Z=A^>XTAH>=L?PBDBAPCGFBREIFHNHZFKRGVIIXHFIIHTFEPHnG\D\DFGZC^B@HA\C@A\@=;R;L9:T<=d>D@\>=R@X=d<\>>P??>LDXBLCFB\BBAEAFBCDZGGEG\DDP@CDV@@P@><>^@LP>:=:b97;b;;b=9=<

J=LDBB?^APB\D`BRDDDhDERG^IK^I^JVH^LGRFFXEJG^FPEDEGIZHTIBBCDEBVEGCCPEA`CFZDVEVEGFDFFEDCCNCArDHB`ABTDLD\EZDDEVEPFEHEFFPHRIGZJVKTLMKJbJIHIRKNPMQMZJNZKbL^L@ONLNLXPPQMKINJJGVGEIFHCD`DPDEFVGEJGGHGIRIPIbJTIJNM\NKRO`MXMNOJbI\IGbIJTHRNJHNDEETDDVHEVDFVHPFbH^GDXGEDHZIZFZGVEFRJNLLMLXMMJJJTNLHKGE\CJFGKJFKF\DLDEFBZDTFNBJDBDZEDEHHPIbGPHHEGFPDDPCDHTBAZBCV?J>\>?>??>LBC?B@BZG@BDTD@ABA^EZ@@@TC?^AR==::V9899:J978b99:N97\98B77V:9X78^9R9L8^;T=88^8Z9X;:=>=N=P<;=:87;88X7`:N:7\8Z8^>P;;9<<<;X:P;b;R<>N==L??;\:T;T>:<@?Vb>?T@ZBAHCBRDERDGPIHVGJLF`JGNI\HLLTMZNdRZPNPNONXKIHVII`KJH\LENHTD`AZC@X>^BbC?DA=dC`AAARD\FVB?V?Z?@T>@AAT@T?DB@B\A?Z@TCbADTFGFDnFG^ILNLLIMlONNLdOVMLLPNdITINHIE`D^KDGD\A>?Z?<=XP?>T?@AVBBDDEEEETIXEZFfHFEIKLZIhIFMIGGJG^HEdCPGbCERC^@NAECAJ;X:T:;V9R:96V641V1`0124b/0d3V/P//@-N0.^,+J.-V,L**^+\*.J,(-T-,*+Z+++,X.\-\/,0N./P/-V/T01\226T64d5N545d3H333Z66^5X3X25Z2`86Z4434P36557d5R4X63d22/1R1.P11J1/..T0b0V-V*,L,b,N+`*+)*T++)(b)\*J(\*&%H%'P&V%b&#f%&'$!! T NbXNRRTPP^HnRXZ^ b Z T f T T ^ Z ^ P^TNDZ`PJ^R\XNR`PZRZXP`PZJfZPNXRNXfXDHZX^fRV^Z^ZZbJ\ZVVP^RXNZ^TVXPT\`PLPT\ZX^N^R^HVTRXTH`\PJTXXVd\VRZFZPbLB\VXb\ZbT\bLdJ`^ZVRVX\RP^ZNPTlNTdTf\bd^F\\R>bX^^ZVbTbL^Rb\TTVVdP^XN^bRPfTZP^^PfH\Td`^`\TVN^BdVd\N\VbJbL\b\R^DZLbdRPRJXLLZVTZR^LN\L`\PPTJFRRPXVVVH`\T`\TZPTXZTZZ\^XX"^J ^ Z Z Z P X Z N P NRTXVTHP\`TTTNVJXN\`HX V!!T$$%R$(Z'&''),P,...\/V/Z22P4N6L565Z6666N477^879N:X8Z8T66d8T:T:5X756\5Z69426H5D45b66;66j74:V5d536V5X43H2X2201d343L1N1V/0L.P--X,0-0>/\-T,/-/N-+R00X.N/0/00J3R4\63X7X8D9T::99B=V;N;@;@T:R:TA?=Z@;X88:T:;V;V;R?\@@V@@^DP@^C?bCA\D^DGRGG`LVIbKTJLDKIPKHPGPIRGHIdFHHXHdIGDDCDDLADZEbDPCEHD\CF^ENEGXEbDE\GEPERDBDEXIJIHDLCNCJCBZCCTDHFXCbCJEGTFF\EGbH0J\KVMLHJJXIHIIKVJZOITKKLOZM`LTMNM`O\NPPVMXQTNJ\IGGGFVIPHBB\AbCDJEBDHTJGJGJZJZM`KbPTKJ^MPKRNXM\MMKNRK\IJPIIbIJdLPLXKTL\I^HGRHDFJLHPDEGTJVJHH`H\HIHJFJlKGVJPKPIMJLZI^LPKIbKG\IZHVGVINFFJHHFJ\FFFEFFVETIGREVBZECDCGEbHF^IGdJE`GIETGRGXFCDPAC>d>R>NATAB`?D@RBJ>@RDBCEDChGCD`GZDPCTDDfABV@@B?>f>T==:D<9;P<9;P9\8H:9L;8:98h<9\::R=V:;99T;R::R:<9Z;V;=X<`;=;=:V??V>=A==^==Z=>;>N=b?@??VA^B?VCDIDdGVKHJJGHMKLNRPMLObS`QZOPZOKKIXIGIIF\EDAB@?@ATB@T?>BBB@XDDAP>C@@@Z>^?@ABNAVCAZ@ACT>A^AFBTBBD^FGHKXHDfLHK`OXKLVMXNPTMVP@MNLRL^JJIVKLTHHFEBZCC=@L>>=;L;R==V;V:F;Z:=8R<8879Z65\4D856V7\:;89<=N<^=XV?V>TCZAD`BAXERCBVEDEFZGFDFEFJIRMbKLGKZINIPFGJGHHIEHBC@ZBB?R?=T=8Z9F=X=A@AA@BALBADXBHC@JDZEAZEFNDBDLBZDb@?B^?ZA<@?<>P<\<>V;=<=;X;:<Z;PAAVC?T@ZAdCNCZDE`EGPGVIGJXMROMdJRK^HF^GdGJFGTFTDD`IH^FVEBABARCNCVCCCDJGZEBGJCDDPGZIJENHDERGDZETGEVCZBL@ZDRFJDDVEGEGTGHFHPH\HIIKPPKNZMJJJKHLKHOJMMbNNNbOVNRL`RTPdO^MNPPMfN\OJGXEJFCZGGCXDRCTA\BTDVEDFJGNHJPILZOJLMTLZLMNJNNMTK^MMBJRMhKGTLKIMTJMH^H^HZFHdGGFGTHHGRGTHRFbLHHNI\ITLLJJLMLMJ\ITHGJF`HEED\ECDE\FIIRG^CbBPDbCCdHFEdAZCACCDDZGTHHGEJbDFRGGHPFFGBNGBJEAPB\AJB>?`BAFFVDDDEXHHFFVJIHH\FREBPHDDF@V@>\AN;h>\?`>T<7^9;b>9:`;:L9N:9=X;d=9Z:;^:P<9=^<=;?>N;9b@@>@RBL==^T=?>=;Pb?V@XB>PABRDVA?>?AF??RCGFLGLRHNKfLbLXOPLNNNMOHMRNKVNJJZKIMHLGETERDEbB@`B>V;h>=<<;?::8T9h<8H;9V76T4\5d4N;67:b:7J:b>X=;;N>f>L?Z@\>?\AZAJA@TD\FTEPA`GRGEGNHFbIXG^HH\HHIFJG>HPJPERMLGVHdCTECBXDZ@J@B`?X<=X;^;:Z87442T1T/46451L1/--.0P.h0/\,P-J-,T.+T)X++(,R+`.+*L)+,P,T0T//`/00.R1R.N3.10R145X57P34`5R622\5Z3X446X8T7V556V6245P54Z45\5\5R56344V1X2\1J.T10.-.0`20^-N/R,),X.N+*T+,R*)R*L+(*(P*^(\&$N'%L&%%V&^%d&X%# d R!VP VV ZRPNTVZJHRZNN\RXTJ Z Z R J V ` V ZR b PdVbRZ`TP^TRTVRT^\ZT^ZTHjVNNfZR\XTPZPTddDbbbb\FbRNZVXfNTbPrV\PRPXVRHZPJXRNPX^^LNZ`ZNHR^VNhN^XNbjNR\FdV\L\V^`TRVN@PNV`PbX^`VX\VhjbT``^RBn`RlbbTH^NfZfPPT`ZXLdN\`XV^`ZNf\\Rh`V>`PdRV`LbPjLRZZJTRF\hV^H\JT\`RbXTJVTbVRVp`P^VNLVZ\N^Xf^ZPjJ^VRhZR\dZ`TLRZNbPTRZZLTJNPV  \ R : N l T> Z DTP^RTbT`NVFPZNRPP \`!H!!P&&X(J'&Z(P(J)'L-h,/\-0/`00f12`5>5T777b7j8b588N37V99:;9\88f8\8^6V:^646R568V7P68565576V7b345\64V8\44`123R213V2X2P01h21P/+/0.N.N/X0-b//f-0N00R.0R/Z10L/J2^0T331R4f4243T5Z7R8;8L:R8:\=<@^=T;F>TA<=>?@=?CT@>DPACRF^AZCALCXCACHDCPEBFDABCC>V??\AR?X?@N>Z=>>\j>^BT@\DAX@ZA@NBTFFHVKJJKIOJXLIGIFPK`ITI\GRIVIGNFCHNC^FTBCAVDCPHTAXF^EHFEFRFDHFDFDBCVHCHZECCBD@BDZEfECdCXG`FFZIHNKHJG`KKJN^JPOdK^LMLXPLK\NIKLVMPMNXPPP\MHQOQVQNNPKFHHJFCDVFAEbELDPBTBDFDXCEHGEGFTLHOOTNKNLONLVMMJFM`JTJ^L^KIVKKLJLbMJTKHKIKMIFJFJFHJBIIJTMPIXJZJIJRJJTKdKLJL`NIIGGdHEHPFECZGNDGdHJEFDCABVDHE`DFVFEFCDRDDIIKRHFVEXHPEDVEGNGJFJHZFE\DEDVAAVCZC`>B?ZABE\FDXEFRDEXHJFZIXHHENGTDZCCZDX@H@?=Z=<>R;L;@<:9\;RAPBP?AAAAXBLEFTIKLGJHFKJKRN\NNPSQP\SOBP^MKPHJKZLIGGG^EVETDVF\CAPFFBDTGTGXDDCXCAJBD\?^@?C=^@XAX?AXBTD@?BBA\B=?>jAHAVCEHHPHJILGfMKKPNOKhRJNhNTNbKRKKHJHHF`ITFEJCfDBT?D@T?^?X=Z=T;NA>R@>RB\=@AAD@TECCFERHZFEbH^GFHPE\GFGHJVIKCDNGXGZHFDDPCPBTA@@?>b=<;99X?=H>N>>;Z@?l>=??A?ZBAL@BPB\C@AZ>TA@CRCAACBEXDCPBD@Z>V@\BfD=;R>`A=\>:?\:X=;V>=T=:R@@>=^=TA\@@LB@\BBEZCVFFJHNIHVIIMMKNILLKRHZGH`H`GRHbELHGF\G\GCZDbAAACCXDEhEGHZD\JZFXEZD^E\DEDEAXC`DXD^GCL?JBZACNB\KGCXCTHDEDIK^HFKZNL`HLLOfMNOMTLXLZOOKNLJbLLLMOPPPPMMfQ`ONNLRN\HPGVFlCN?NEBXCXBHAFEDXGJGDFFIPF^H^HpKKMMLKNMhLZLTLPMM\K\KPMLVJKG^MXKRI\IIJJPM`KKKLPGJJVJ\JGFJNGJGJLZMKRIGKLL\LKJPKINHVJJRFBFPHJED^AVCDD`EDETCRCENCNDFID^EADCGRIZFGNHFTIRHXGD\CG`EGFhFVHTFEGDBNERDXE^DBFBCBBXDDRFFREEIGHTFGRFXDHCE@??@<;Z?T<=R@<;8T9b:8f8T8789:9V:8XT=::N;:d9T=XP=R??X@@V>TAhD@`?\C>R>?b>==P=:b?X<@>J@@AbDLDZC\CBGfH\JFGZJGHjJHJLPPPOXTO\OMJBMHLZLJIHGETKZFAZHC\D^FFCZDED@?\AdC?B@>A?C=@P>XA>X?V@BA@>?f??@^ABLFHHBKIVJ\KLMLJN^N`NNMLXKMJZLJGVKPIHXHFZDNF@TAR@TBV>>=;<\>b;V8Z;8^;9T8Z;X878R74N9X=D;9T;<88\?9b>=L>>=>NADBD@>D\BFFGRCDJ^GGFH\GVHPFPJTMPGDHNIRGJEHVGXIXFEIRCTCXCCBL@=T?T;P<<<8R9J853T733852R3Z133V1X/R1T10N,\,V,N.\+^,*P+`*X-)*X++\-,T,P0R.,.P140Z.L/1P/0`011L3T2X6Z7\543X1447\787V6V745d6J76h4T634P3R655V6N78Z7B31\421P3X/T.N/0H4.0R0.b,b.N/,Z,X./8.R,X,,*,L**`)X*+**&'(\&P'b&X%H%\%$X#P# J H b h!L^ XX\PZPZZ^VH^^J^HXT V b R R N \ Z \ N ` ` V d N`LbRRT^VVPVBTXP`\Z`PbXNVX\RXVVV`P\VP`RL^ZNb\RZTf^^P^HRNTP^NThZLPXXPbd^V\FVlVZRZZRbVHPXZZJZbPNVR\VLTVfdPVZhVRRbP^VZXPPX^ZPTXJ\JdZ\\\nljdh^dZX^bbbV^PVZX^ZbRZfZbR\\ZHXPXbT^TlJdXN^\JVhL\NZfZT^\ZHFbVZdPRdVHPJXJf^XNPXbbNTLVNRX<R\<dLNLnP\\TbdT\ZR\JX@dNTZV^XPTPXPRJ\V^J>bTJ\TD\LVXJR\\^PJ VTT Z X \ X P T P\TT`FVXNXbRPZJLV"P X"!j$$^$&'$N*)+(^.X.-R1-b/L2N2d22R4P1N5d56`5664d9b7Z858;9J8N:^868F85f7Z:L75Z66X8N9J75X6^5^67N:6955\8T5b2454R411`12.X2.21.b/R/\...L,\-,-.X/`-D/0X.3.d102P200D13X2/17D6X547648:;=V=X@@AT@A>\@CL@PBTAD?AJC^CAb@TCTETCAAX@B@NCRB^CXA?R?AAA=N<=V?R><<`?T>X;`=\>V@>ZB>>\A>`?T@b?BJ@R@BRF\EPCJDDEHFFG`IXH>IJI\IVLXJLTHJC\B\ENFDZEVG^JFTH^IGZHEG^FRDCCCEHH`E@^AFPADCZDFDDHJEZGJJZIPJbJHJXL`MLXOLOTKZOOOMJMOPMQQjPN\MORMLQFPXNKTL@JHGDBV@DATBdBNEEEFEJBHDDPE^FDEVF2JPKK`MVMKTNLVNJNVLJFITLKLLIJMhJRMXMJJXHFbJVJVKZNJLXKNLXJ^NdIZHKHHFPJbKVLJIGJJXIVNIILIHJJMNJLNHVGIFRDCB@@\B@PCDPBTCB\ABDVCCDFVDTHXHTJVKTLXJPMIGPG^DFBREJEPEHD\D\FFGGRDDNGCGPDEEV;:P9b;:;R9T9:9P;Z<=;;B;^;Hb:N\>;;P?=<<`J=R@@?A>DZAH@^@?P?V>P>V@<<=?X;^>N<=>?Z?XCADVCGDFVJ^K^JJ`IHTLBI`MLPVNOM^RPM`RNKNJIH`FXFDDGHDFbGHEGEZFF`CEANC@dA@Z@^AA>R@TBZ@>B?JD=D@L?@A=TAAX?PAX@RELEVGdHIKJIIJRMONNRMN`KJZIHTKHNIHJJ\EF`BAl?@L=RAXBAN>V;T<\;H9;77R;b:889P77X86P<8RZ;;>Z=@?@P>T?TCBCDAdCEDFGTFJGHJFNIEXJGTJVLLLE^DDGGPFFF\CZBD?CTCCD>=XAR=9X@b1T1L0X1J10\1.++H.0j0P/T-T2/Z1.V/f1-T/312Z2Z200213T50V24R3Z4T4`5X;L:Z9>L;^;R>`>;B?ZAC@AVDCC`G\CTB^AT@A@LBhCB^A\EGBVBB?BH@B?>8J=<8:b;Z976T678\8d;:P:R;X>Z@L=V>>X>Z?@@lBB?@`D`FGLE\DDECB`CEIJNJdH\IHKXMNKPL`NPLRJ^IRKnHFFBFTFDfCXEBAAXCZDbCREGFHIHXHXIVGXJXFRFDZINDEXBXBTGEFGBTCBRCDTDFJDGHFIHKJJJTH^OJJQTPMPVLNTMQNR^MNNZOTM^OOdSLOPPRKfNOPNRKOXJFIFANBT?CVBNC`DCRFLHGEFVFEFdI`HGXLFQO@QQLNJPMNMKXNMNNLKdMTMZNNPLJIRLTJKJMZN`KNMVLdKLRIZMIGGRIFKTKJVJTGVIZJKMG`HTHRIGGFDEFNDDNERAZB\APCd@ND`CCBVD\BBBCDNEF`E\F\L\NJJTJG`HXHdHLG>F\FREEPG\HVHFJGEGfEEFETHfGKEFXJIFGnGHIIL`KJGNJ\GJhGIFbEFBA\Al>T?:VT<`=FN<;:j=:X8Z8J9;R<:\<;Z9\<9<`\;;<>=:H>Z=>`???@V@V?BR>A>\CAXDVD`BG\NPHTMJ^KJL`MNbOM`OVKKXLKLbHJJHRK\JLJH`FXBB`E@>@L>>??;:9T:;;679\9R9J7R85Z9d;<8V9P:88:^:9AR?J@X>PA@^?JBBZARBXCLDVCDLHDRGHGPGIKFZFPGJRKRKFVHDXG^GLEFECZB\CLCPAH@B<>?<dVZVJJNh^VPZVNXRZ>\d\PJ^`RLVLLZTVRPPZP\TZbJNJV^XL\N\P`XLXL ` J P ` J f P ^  bVTfRJV\FR`PX`T^XXP! X#Z!&R&'(d'((`,*d+V,R/b/2//1d342\4^6V65^4^88V78R88L:7H8V=^898R979N4N:9:8\8`8^7`;69V768Z67J447664T2d5P3232233\1T43010T,.\-/`0/X/-V-/F1R/03^.V3\00V04X2F3h3V32`3N34P446X6F75N79N9D:7`=9?<>>V?>T>><><@@=Z>;=X@;;>??;?>XCXB@@LBCNE`GEPF`DF\C^CCHfHVIGLJGHKNLOKIJJZKE^HFVEFF\DABNDDB@DCZ@\ETCIEVIF>KH`JHIHHPFDDJD^DC^FLHFIIEEAFDBNEPDTHdEEXHFNHGGFINJPOLLNOLdKVMNN^PVNTRQ^QMO^NQRPSdPVQ^NHNNVLNLHNKLHPICDA?@BZDDHECHIHTGhHZGbHBJINMIbLRMZONhRX@A@^DE\DCRBRFbDJDjENDFEVHJ`JPKVJTNTK`MIMLGZLHE`I\FXG>JRIXJGHXGED^FVIVJH^GPITLJRHZLDbKLILGKJKbHLFE\GEREGfGEPD^A@?V==:X;\;99;;9\=\;>N<979;\>9T=>>Z=F<=7Z988H7T::H=:P;`;Z>=h;P<<68P8X:;P>T<=;><=PF?>@@R?A@AAHC@ZFBD?\@==`?\D>P@dCLCECBFdF\FIHELFKLMMMTObQPORNQO\PPNKH^KVIHKIKJJPHFKXJTFH\FGJFHDADVFREGVCLB@R?`D?B>b;=R>Z?L@=V?@==jR=XZ<`>^@?XATB??LBTERDDCHGREDNGZEG^FGNLhIZIZIXGVGGHDHEE\HNHZEEBDFCEA?N<\;\?\<<99f;F9;\4V9d9J4X12^1X4\2102T1.,.Z--T,J/L*\-,,,N++V-+T,T-//X//^11d..0H0X2\2002/4.N423112N4b765\4N555\772`3T4f24X634N77R9F96F;L3P4/\0R3`2Z1T.\0^11X00Z00R0.,.Z,,L.0.-,\,+D-+*T*))'^*Z)()(^(&V%R%#V$R#!V!Z"#Z# "R \TR^TXZZdHb\bJNT H `T R V H V \ X BZVR^V\PVXF\FjVZ\bH\ZdTXVVZ`^TV^RX^^`\V`XX`fVTbVNPX^TTXZNHFfdLRXZZ``VZ\H^bZPZTXVXbLZVRPPV^NPZV`J^RTRNXF``\h``dVZXblbbPV\jTXNLbP\XVR\jbbVTThZT\`bf\\V^Xb^hZb\\bZddXT\^\X`^XZXPP\XRZZL\NhNXH`^Z`NRTX\\R\X`ZX`\XVVfVZTbPZXVVVZj^`XV`NJ\^bHV``RVL`XXd`6TVRJ\RHVZ>`\`ZRb T h @ h TFd VPfP`R\^VZPRZ\bHXLXPZ`N!!T#P$^&J&Z&V+X)+*.f-.-V-P-f0V/\343f3V546X7455X78R79F:N;T::9P;P;X7T9R:V;N9jL=P@?VAA@XACZ?\D`CTAbCVCABACDPED`FVCVBDEZDTFCEBAPCHBB??N>`?^?^AZ>=>>R@J@==N=>>:8P9;;R:9`<`9886X6b888V999L;f:R<:J;`<=C?@PA?BVFGEEECDCC|BC\FTLPIZHTJNMPPMRMKKRKJMZJJJGPDDECbF\BBHBAXF@BhDBGFNIKE^FFGGGJINFFTDVC\EZHVHDIHXED\DXDTBXCbGVGKG^GDHXGLEhKVMTLVLTNRLL\MOPLjN@LJ\MP`RRQNHNOQONPP`MNPOVMMPIIZLKNH\EJECZ@A?BBC^AJDZELGGG`FPHI^HPLPIXJPNXONZNJPXQTZPPTMPNbNXNPOP^NNSNOMPLLJNMKOOONLLZMJHFPHZH^HXLPJXJLHGVGTFXILHIZIGAEFNE`CVAZCCBNC@ZA@VBDBCFXFX@RE`FE\GCDZCpFIIZL`NJLfLFONKMLHMRNIZG`GIXKZJJVIJEEXHETIIINHMKJJEXKTG\KF`GIGdGEG\FXFEGCXERB@VBN=\:Z:R?\<;:l;L;`:X9X7^99;<>>;>T>N<=J@>=X>>?`@;D<T?V??J@BXB@AARD\AZBZ>T;=`=R<^>V<b=b@L@N>X=?>>T>d=J==X?@Z>\??V>Z?CZCCDbD\BFGE^IRJFGGLINLROLNfLPPJVOLIXLMJFTHVINElEBT@bDRAX@X>fB>RAT@CEACDBFTDfDF^FKH\J`GHHGbGZFEDHHJTEXFTECC@dB@?PB`@;;L>BN<?BTCACNC`AANBNBE@DdDCRFTBREBTCBZDLEdDDFGDjDFXG^GCIHBA=V?\=X@F>=H>=X??B\C=N=>:8N97R;N;P877b67R9687`8R76R7:<:;Z;T=>AACD`ECPDfEXBDFdECPGBbCPDDZHHRITJJTL\N^NNRNRDOMOJMKGFEEDBCBBCVCBRAFZD\GEEHJTJHVGKHEHNGZFDZDChGVEEHH\IDVGDFFDNEIXHTKKIFNJLRLNJTOQXQITLLOMJfMLNKXKMMMLNXOHPZPO`LVNZNLLNJJNLJRHHJEfINB\CN?\B>AECVJIPGJVJNJJZJRJRJJMOUQRTQRRQTP@QJQLMTNMLNXONMMJPLNMMNPRP^MMMO^N^LKZJIJHLGJITKK\KEPFhIFPJZI`JNHHBE^A??@\B>L>>Z>C^B^APAXFCPCXCG\BBTFDJGEEJKXJHMJNLPK^NZLKLOHFKGZKHJLHLJJ\GVDGEVHHIGIKTMMLZJVHNJHTHNKTJbKKI`GFEFFDdClEABVBP?>b;<^>V8TJ>\><=<;9\:P:\78T8:P:=JAj??>=@R=>V=T>==\>J=V?\L<===b=Z@d>P@\>?F@ARFDFDGTH\GJIbIVKKVKJHKNNfRQ^UZPNJQLI^JPIHJFIIZLJPNIMRIFDF`ITH\FTEfDAVEAAPFR@>@@8<>=`=@`;:=TAH=V@Z>h?=\@TC^CDXABPC\DRFFJhJIHJXLNNKJNMMPPNdMMRKbIHdKJH^FJH^GZDBXDBZBXA=A::`89Z9:;8J9L=V99J7h686^685N888;D9P<>^;=?=B@AA>V@?R@FTFLEDENGHGdKHJIIPFIREFVIVFXIH`HbENBBTECALCD?T?P>>;X><^>X@PBB?PDBAB?RCXCRCFRGHFPCRAVHRDTCjEECbD^BCEZETDXDG`DAN@`A;Z>>J?V?<\<=<><:`<8;8N7\9H797R7J7\9T9h9X9V:9`9^99^>^>>L>??@DB@B\CARHEFPCZDDC`BTGGIJTLDMNNNMPO\PN\LTJJZKPFHD@BVCB@BC@DGEFRGFZGXF\GGGXILGFVF^HVEVENCVFHFFXHJFNFCBCDDLJRJ>LLKZL\MMNRONfPLKLKTLVLK^OPJNKO\O^OZOPOOQNLDMKKZJKHTM\HTETGFPC@RC@@BNEFGRFFJJJLN`LMJPMPMLMMZQDUQTP^SQVSVRFSS^ONbPNRQLMONPMXMOOP^QLN`SQXRQXPTLIVJFGbIK\KRKINGTHVGHGHFTJRGRDCBR?BP>Z??^??P@H@FA\BCBbEBDDPCBDRFCHFFITKVLMPJMIJLZKIFKLJIbJGbHHbKKJTFGHdJJLLON`LQTKLMKKTLbKHHHHIbIHRHbFHEDGFBCX?AV>>P=<;=`<:X=X<><:X=;R<9V\@?Z@V=;R<^8<==<=T=T?N?;ATA\ACNEBFDBABB\A>J=\@=X==Z>N=B`ARBL@\>X<;V:X>A=VCN?^B@n@TBNDXBZDC^EFZG^EVKHJFZPJXMNOPZLPZMJPLLXLZGGJEFE^FFPHBFB>V@=<:P9:\99b:V8\;\<779^5666V664L7`49:97><\@fAH@J@r@C@ZATBCCVFDHXEbFGdJPJpIIXHJRFHNEHVKFOBGGHVECIEB?\@L?^?TB\=X<;^@>Z;X:9<`66;N66T312`353R30.R*+,b.P+,,)++b,V+,X-L-,^-.0L.-F+P-j-Z/0X120N41R02^/R014P2T20b3d3R2335^3b315X4L6b2L6^4V5`5X6T5b574b:76222Z232Z4Z2222b1X0/^0/Z/0X--.\---0F0J/P-X/,**))Z,X)(N'(J'V%&`$""#&J$b$P"!T V"Z\XVFbZVZjT\DTXVTTNZT\Z^ d P T V Z N ` J   jXPPXL^d\^NRZVbL\^\`j^TZ^F\VVJJXT`NZ\VXfZjP`\VXXZZZ\jVPXRPXTZVZVTRRTfbPVRbPXXXVRRfTVh\\dPV\XdX\VfNPV\Z\N^ZNT\R\Z`\V^b^b\dd^d\\N^VbXXjVdVP`RPLTP`N^\VPJ^^NVbZZ*^^\\XZ\`jP^^dd^TLLP`bpXfDXL^V^RfTTfPd`HVV`VTZ^XNf^Z^Z\ZPN^PR^TVP^TTXTV\^V^PZdX\V`V^nVZR`NNRPZJRRbNHZVVLVXdVPVdTXTHTFLbZ`T ` X Z F ` P X T fXTJNfNNZNZNTZRRXVNbLT!Z "!V""R'B&B(%&)P)X)*Z.j1V0.V2T2T0V0\4X243Z13V4\47V;T5`997R=Z98P:;^9>T;<:T:J89X:HN:<><^;X>P;Z?P@BXBCVB\BB`@DTDG\G^CDCDF^CTCTB^CAVC`DVGDEDdG\EHCENDBVCCBb=H?>?=Z@=`@RA@nAXC\BABBCbFJEIFEE`EDFVG^I\N`MVMN`NOhRNQQbRLZOJH^JGBTA^AB@A@\CBNBEZJDFEZEVHhKIRITGTHEGDEbEBHEXGH`HGEVG^EF`DFbIfIJNLKnNKNXLTP\MVOKMOTNNNKLHVM`KILLO\QO^PVPNhRQMKNLNJ\JfMGXHXHNHC\DB@ENBJD\GHHGPLTHPOLPMPMK\JRMVPQUQP`RRRULQXPPVOPNMKLVOTK^SPMMVPbPRR`NNQDNQP\QRLQLPMVNXLHJ`JTJNFFIHIJXHJHRH`HZK^GVHVHXDbA@AF?Z>=\AV>==A>PEX@CBTCRGEDNHTGTHZEHHPK^NMXSRN\LJZOZMVLMMIOJTJHRK^KHK\LJFHdJLIHLMOOTN\MJ^JFJLIKKNJJLLNFJFIVHHLPFhEVDCXBAVA`@DA\?X?=>R<9P>:\:Z<;=:T99Z:H99J9X?>X=?=?AX?=>;=F=R;T==\<9V;P=H=@B@TBXAL>>`BANDNFFJFDCDBhB@?X@Z?=@H@=J;R>@L<^??T?\@>B@NDAPE^HVCGF^IZJPJRNJZHVHRIIKDN\MVNO`MLMTMNIKNINGlKGXJLK`N`KG^HXFPFFXG\IFHFRELGPAfBDZ@A?J@><<`><\@Z=b:;h=J@@\?N@bB@CB\BXBE\DJVIbIPKG^IHRK\PNQNZNbLRONNLbLJIPKPJCFXETGDCF?@b?@?\@;;^;;R:`9V<\8\8V94:H6V85Z7F68Z6X769T:9:b;=P>AL?==V?<<<<<<=d:V=d=8:753L6N61d1J13/`--,N*h-X-Z,+L-**+:)*V+V+J0,*D.V+*+b,b-X1X3\20P10.T30J/121210P4P4^3V3F64124T3T42d54X4368\8V7;4T7T68V6V2234N4T0J2246L2N02X//h1/0N-P.V3P2Z...T-L.*Z,Z-*P**\+V(d,*'\(`&P&#b#"##\%##^#\"J Z^\ X\hLTXRZdLZ\XT^ R Z b D Z V ^ N V LVbVbTZTZZXhVZVPRVfRN^dRPV^^FNZRX^XLVLXXR``d^`LbJVZbVf``FfZd^^^\X\\^bPX`bRfXVjLNh^`bZN`ZZXVXRPR^RVTdRZJbNN\^R^p\jbdf\Zdld^`^X\`TT``LX\Z\ZX\\ZhdP^Zh`ln>PhXZTZ\NX\\`ZZVTfZZXVTVRR`RT\ZR^RThb^^V\N`RVPNPT`X`VTX\bR`^LhVRPVh\ZVDXFVV`XVPVVNTJZ`\NXVLV^RPRX`V`@XXZLjT X b X \ V R XTPPVJbVXLVTT\hB!"V$!!R"Z#%'&(+&)+*,+/.J/\/H4.V0^442d4L4b384V6X6T7N8976:T>9b=\:l;L;:BRCF@Z?FCADDXEXCCPD`BERCERFJDEVDT@\CDLELVJVD`CTH`FEBA^BEERC@?J==P>^A<;;<\;V>b>?=X?=:=;:V5\47X6\9876T9R95V97;X<<@?@>NB\CACAtAFB@CD\FZF^FDJFAND@FHJPGLNJJLNKPQJWQOLZLJIGNEVDADCT@B?`FCGGbFDD\DRGEIGHRDGDHhFTEDDTFIVGPG^G^FVFGITH\HHfLNMZOZMVMNMDLN^MKXMNPdRNXNZP^LTKMRKRKTK\MKKHNNPMRMZOO\NLXMRKJVKJFPIHPHTCfECDDXEPDPDHTGFPJ\NNPPHMKIJOM^POTTTP`RFRTOQPRPQMDNL\MNVNKLRJXKNFOMO`ORQMSRQHUbRZONKHdHVL`II`DVFVHF^HZJFRLJJH\JZKFfDTE?L>H?T@==R>N>Z=X>B?TB`A`CdDNDIPFEGIHJJFI\JMN\SXPRPMJLLMOIZJZKDGJNIRMMLNTHLJXLZJKMMNNPMZNbOLKILJLKLRNXK^LZJbJKIXJZGEFRFBTADAJDX@BNA??\>N<^??P>T>\=;T<L==>h=LBd=<=:H^Z:T;`;=b?>=@@CTCZEDBECRIDTCTANCEdD@Z>>=>=N>@J?<>?@>CZ?@==>>DHFDHGZKZHJJGKJ^HHTHTIZK^NXNJLbK\MTMKOJIIHNL^JPKKdL\HIGIfGRIGKXHFNEXAfCDTAb?VA\B>P@?;Z:T=L;`;N=;::V>>R>\>T??C^DHDZEEFKHbIPHDHHNE^HHKRLNHTLLVJbETDNEZDNDXD\CZB\@V>=h?==^==:<:V:V<9\9H7^5V8X453`3d1V0..^-X-N,,V+^,R+/P*,Z-`+\-+X+N,Z*+P++^*-P+,\.`1L2/X20h001X00`1V32T22T422T131H5Z3d3X4X13\4P444468X56`7:63633632^4N2\2Z21`0R2V30\1J/Z/T1`2,X,X/V1\/T/-L.*Z1\,)T**+)H,\)Z'Z%N'T%#H&'V#$#X%\$J"` X ZbFRR^VP\LHTTXfNXRNN ` Z Z X V T d X V NTPRjRZV`bJL\`VPXZV`XVTV`XZT`\VTZR^DVLd^XbZVN``TXRf\`Lb^XVXdb^\^VfbHZTZ^FLTb^N^ZT^PZZZZZPJZZ^VLT\bL\V^RP^RR^TRXXTdZBff`X\dj\N^bfddXRZVjH\X\ZfH`^dbVXLPbTZP^dR^TZVTRLbN\P\RJXNJZJjDZbP^dV`LhVVdXHZ\ZX\PRZ`PXHTRPVZ^Z`\P^HR\PVbZZ`fXRXXXX^TN\^RFXTZT\^Zd^^XZHXTPfFF`LRPLN\NVRP P J b F Z ` b Z P TRZTVZJfRhZRTFP^!`!"V"d##V#V$%'L&'X*(,P,++,`/.1b/0/2b5^322`62b69J8j7T98N9Z8Z9;8^:J<;L;=X<=Z;;L;;T7H:Z79:X655R83Z3H/^41b2\/1.103T223110L1\2V0`-02X1--f0X.f/N.Z-X-\,+^/b/.2J245^33@4X4b3B850355X7\78d:X?X;>;R=TAB@XCAB^CFCE^EVDFBDDCXDZBFZFbGDVDBGEEPEF^DFV@XDC^DRBbBRBPCVA=;ZBV;;V:V8:^;55N864d89387L87ZGPFEFHRFVF^HTGHRHEEDFKZGGHEPFLJPNMML`NTMbKZJZNTPMPTQPVNNMXLVQhMKPNPMLORPQOONTLJN\M`HNIJLHHGZFTIDB^BBCXDEZCLHGLRMMSOK\LNPNO\M^QLNQONQNNRONOVONNPN\KPNLKNXKJXLMVMXPONZNQS8RPbQLMHF\GEbDLEAbHdILH^HHHZHITIKGERDA>?d:Z>P>V?N?@AABFDRGDGLJLNFLJILLVMJPJPUXRbRNONZLLMNIXJK\GKNJ\MJJKRJMZNMO\LNLQLOZNHIXJXKdHKGXJJHLI`LJPKHXHbEDE\A@DdABXFDATB`@?=A\=X@LB>Z?>A\A>V=b;N:Z=X>;<\<9P;;;\=;<d=D<\=L=>P?AR>?dCAP@bA?F>?>BTE`EGXEEFJHIGIGXGJK\KJJ@IRH^LJLIJJ^M`KJ\MLKKKbIBKHGdGIHbGHZF^IRENCJDBLCBZ@BV>>>h>VC@^BCZDEGEEFbJJJTMNLNPLPNOTORPJVJKVKGITHIHFC`EJCETCZ@=P>=^>>PB?X>L?PAdB@DDlGXDF^HLK`JHGPH`MHIVK^HJNLJJ\FVE\DBBCR@?<>X>?f>><:=h;:PLXNT`PTZTPX^NX\Jf`TRXhZRfRZdVPXfV\F^X\HlNTDL`RJNXTJZX\XZVXdTTVVZZPNXV^\RBPLRPNNJ ` b N R X ^ ^LN \`VZRZTPNPXFXVVZ`^X\ "$"b#%Z&b&&^&L)L-(*+`-R,,^/-\0/b/2T3P4203424h4V7N:85`989^>;H;V;Z;6565L5Z77L7R54/1R33L/d/^2f5X02X4325020T03P0Z0//.\-R/0-.\,P--h.-T//10T3L31b5X45T153^4V6^::^7\8:^;X<=P>@\A\@?XCXCHBTAHDFdDLEIACFBRAhDZ@DBXHXFE^CFJKdIE^HGDETBEAHBJCNCZ>L@;R?f@\>^>

<:>RBZ>:Z;977P9^8b856J8V;T5\:9<`9R;R::\>=>V>@\A^?A\A\ABNFPD`CDF^DVCVF^EEXJTFERAEENKZLJKXLKNVPLOTOTNJFGG\DDEdBB\DFFXCGXJ\FGKNITDD`HLFdGNECFRHF`EFJZJJHETF^IRFEGPFXHFdGHZGXKTJTMXMMNZKdNNVKVHVMTSMZSOMKMKNbMNOLNN\OLQ`OOVQLPRNQP\SSOZOMPMK6NMQOTMVKKVNPXQdNPPPXPSRRdRNNM`MHEEZD\FDA^DJDfENGHIGGIE\CXB@BbBD@P?b=P;;;@@d?BCTDdCVF\DLGZFGJJPMZLTLXO`QSRJVRWP^TOTOZPKKHKI`KIIHIIfKLILMRJ^LTMMK\MNK\KJ^JIXHLJbJKZMRNLL^JPJbIJJHECA\BBVCNC\@VBC@@XBTN>L=8b:H:89F;>X><\=J=>^><Z=\@R;=d=`@A>@?P>BZ@?XCLAT?`?@R@ZC^ANCTENDENDFE\GGGXJHIH`HHMGVH`IHXGJTJIfKNPJJN^JZJIdJdIGIRG\IJFHDFVGFBDBZ@A\=N<=^<;P>R=`>H>=?Z<;9`8P9Z8T6Z8>795R57564657b:^:N;T:9D;\:^;<>R?@>L>PAC`DFCRCbFF\GHRIZJHXJHIVKMdJIJMTKIRGJHPDFB\CD?=dA?\>`>@R==D=?9T;:J:V9f75X7V345`31T-J,^-J,P,+*X)N)Z))+.P/,-R+*+*b.*(T)D+-,d0H1R00H0.\0b20V0H1d0Z00X1543T44Z1X2j52b2b3346676h8P6T87H766b5V9P8`4h3Z5Z564`6201\4J1X20X4\24/1b1L1X///-V,Z+.--.***D'b((Z%%&'$P%\##`$R#F$f"T" P!N!VZ \P\RdXX`dLPXRXTP^ R b R T B T P \Z HR`^RdX\\RL`ZPZhZXVZLV\BZbfLd\`Z^NZV^^^TPdPXbj`\h^V^HNbbbTPRZV`VN\N`RNbbbXZ`TZT^T`\XTTVJ^XfLX`VZ>FRRPPXbDNd`^^^hZ`V^VfL\`R^^VTVjVf^HT\TTTN\XJHLTNZbZ^J\L`RZVVdH^\TTT\DbZ\\\f>`hTdFPFZVLX^ZXf@TPV`ZNb\L`HZPVZRRZZRVRXXTh`VV\\XfPVVZVVbHJTNV^hZLV`LNX\RTTRPdTPZ VR ^ F Z ` Z D d XXJd^XZHTVhNRTVTPVPPPLZPVPX ^ !b"%R#$\&%Z)&N(\)X)V*-^.F,,/\+-.R4^0T3R3T3V2R43Z37R4P86\76R<8:V:9:>R=RbPA@>\?J=;7V98R9Z87R65T669>;;;@;;L:\>JV?N?\@TB\ANDCE\DB^EZF`BVFEXGG:FDEXGDFXGGPNKNbMNPQTOMMNN\KPDLHREDDRERAC`DGFFF^HFXGBEHFGDDEFPFH@IDGZIIHRHFTGH\JTH\ITI`LIHKKNObLNN`MMNdMXLTSbSPOQ`PNPOZM^OMNNPVLVONPRRNdMPLNMVJVJJNII\JRCDA@ZCBGE`DXFDLHIZKNNTOVPPSTPNRPOLOQLOXOQLPPQSRHP`QPM`MLNNNNONNZRMNPPZLFMJONPTQPQXOOXLKHHCE`ABABVBDNH^FPGXHFERE\DXBZ?PAdCV?T>BT@CBXBBBP?DN@^BC>B>>=H=<\>;T?V9=J=J?P>R<;TTA=dDB`>P=T=PBd?>DB@BXAbCCXFEZEVFJG^JHPIVHRJLLNHTJFfG\IGF`HPJHJKVM^OMKfITLJI^LXJFGZFTKETG^CFLCHE`DPFZ@=?R?;V<:R>`>?;Z=?X??Z?@>>?DHGKEPHIGdLJIJZK\LZMTLKMJOLNKTJ\LIMHKIXIK^ERFV@`DCV??<`>V@?X?:99:66d886R:9L5N8T9Z86X67B8P38j:;9V><^;H<\;V=P@?XCTD\BDVCEB^ELEVFLGbLK\JTLLKNLIHK`JTJVIJVIDXEBEAZ@@P@>=A>^:=<\<\?J=T:;\9Z7862h00J-,X+\,.X+J.*)(*Z(()Z*Z..*)R+)+Z-)++V+R,//+-b.T0N.T1T/\/J000d22542P5632334534P75X6R85R693V3X63X4V6Z7:P7Z3^4443`310Z41`24L5X2230T0V0.-/H2-`--R.L.+V+X,T+(L&(%$%V%%&#$"#\"$ T! "T \!R!b`TXPVbTZZRXVTP^ZVd^ ` X \ Z \ T X Z VZThPRTFJ`@dR`VX`\N\dZX\VJXZTR`bJZ\RXNVXT``^`d\\XRRn\^X`N\VVZVXV`\^dZ``VLJbTZ^T^jX\`\d`VbZXZTZTbF\`RRTTL\dRNPDLXN\XXH:PbRVXNLXZf`h\hbb\XdPLNZPR^\ZZLZHV\dZ\XdZdb`ZfVRR`^`hR\Fd^V^dV`bPXDbXZ\ZVbTVJXN\JT^b@VbTR^^X\`TRP\T`VTXXJbVF^LZZZdXVHZH\b^\ZZTZDdTdJLZJXRVRVhT^XTN\l\L^VNPVZV V f R T `ZN hPZVR^bZVhNXLPRD^h TN!R!!T#V$T$%%\(&*(^+,(+,b-,/.V-N1`3V2Z4Z43N4456\6587f797Z:^>J?;L=<=`>L;`;\:X98:j78X7634`854^4\11R202`30F11202Z33F3N/02L01L/^.01.N-/,+^-2.d.Z0/1\02T3X63425R7b649\47X8:=@T>@`>?V@X>V@=VAF=`:9696\8566P;R899:=R=bV:F=T=P?@RB?Z@B@CFDPCNFNAZHZBTGFXJ^GIRGFEXHKJVLJ\KKMNXMOOZLJHG^IVBCPDXGbFDVD^GGGVDZFFZDbHLFEVGEGEnHREPF`HIHXIJZHJHZIVGZHGGKRKL^KMNbMVMXMLLHMFK^MKMXQQVOPXNRPVOLPHKLZOMNRVNMPQPPZNTNXMRKJIbGXHHCJFEbDTCB`DVETCVEFLHfJLKNZNXPM\RbNJMNTNN`P^STQNQRTOdPNQZOVOVJPPRXUUTbRTMXOMOXRJRRTTVVQOPKIG^EDJBPBV@\AAPD^BVCTFEIGF`DTCPAPCRAA>>X>XT<=N>R=h=R>bZ?=L==>f?>?V@=V<<>:87L9979V;@:=^;>>\@bCVFFFDCGZDGELGRBLDCEEGbFRDLED@AVCR?P>?TA@XCVB?=;;=?=Z=T>>=T?P?Z?N>V@<>\?JA`CPA^>AA\BPDTG`GJKIPHGXKXKHbLfJKKLLKRNFMPKLIZJ\IRMIGZIFFCRBVCFZBC@f=L@=h?^>?^;X999H76V9;N9Z:7d745V9`7b79X8V;f:<=;Z:J:;VN:`NC=Z=P>JBREFXKNGFFPGJKVFFTGXGFVFVCEZEHHEHBGEFLIFFXGJEPF@EdEC?LFBTB@==T>\=`:;=6V6L7^6667T@T?V<;=VA:Z=>=AZACDBDCVF^DD^EZCCVDD\H\JVLFGF`LJJRLLKKNKbQMMRLTMVHIF\GDbEEFBTFJEZE\IDZG^GVFFZGVDLJHGGXGFdDLHRKPK\G\IFGFVHNIGI^K\JbJMMJPMZLBOJMMQONMZOHMNNZQThPPDOTP^NLNdLPbQPPNFTPOHQHOXPNLRKJJJIVJGRFZECDCDFCBC\FERGHLLJNNNKQ\PVO^ORROR`PXR\SXVVSdQTQ^NVPNOPOZN^NNPMRVQVNVPTNONONSTTPSSOMNK`JFCBJDANBLC\ARAEBVEDFIHC^CCVAR>B@X=\>@BAhD\EDCXABA^CTCX?NDCRHFFIHKOPROPVSbYXSRQPTNPNOVNLMHJXJIKIGKbG^NKKMNJVPXNNVMIVJRGZJI^JH:LZNKJHHGKPFILKRK`DEZHEHHCCFBBE\EFlDXABD@L>Z@?X==Z<;;;>R=@BBA^DDPEVFTH\FdGERHbCDF`EVDETHTGFAC@Al>>VC?\BT@?DVCN>\=<;L===?@AZ?VAVCCA\DFGDGFJVGEGI`IHXLIZJ`MJRMILLXKDNLMZKIXLJMMTILfKMG\EJGGZFAAA`BBPAGNBX=FAR?><\=?CR@BB^?BN>`=?\?BT?RACZCPI>GVGFZHVHIIRJG^KMMRODORLNXMZOLTILIPIXIZIRJhIBFTDCV@ALAXA>Z@ZBL> >@;R:b:Z;988T;;:77V978f8X97`9Z6:9=Z=R:@CDFFXC`DDFFFGnJKK\G`JLJ^KI;;>;97868V62V/..-X/-,Z,R+)V)**)P**^+\+L.*H)T*Z*,,-)\/`-/T//P.N-T,H,/.0..0T/00V4V225R2P34\4363Z556T653534b96365F:79X823^5^7P23\2B2V32N/53V2^4X5T6/J1`.^.-.-L-,/N-,J/\*(+Z&`(X($b$X%&Z$T%#\"f!N##P""X!T#R"j"N!!TJT^RVVNVP\LXV`ZTP Z \ R X ^ T T V PP^ FdJPNX\TZ\VVX^XVJ`VZPPVVZXbRP^P^ZTD`JDPVXfbd\^PVHTLXjVZZNRnNZP\X\^P`RR^RJH`\RLPJ^ZJb`^HFfNRZlZXLTbZXRJPBRZLZXLTX`TRHhPX\`VRbXf`^`\f\^\RZNRTPLffZbhRZVhR\jXN\XR\h^V^\X\lXVF~P\X^TR\JhTZN\T`RbPZXdPbN\\VlNdZHdRNZVlT^JT\dRrVbVP\TPLfRLR\N`TRTVZjVRXhbRHXT\L\V^L^Rbh^J^bDJVJ\`P^XTRR`\X^\^X Z R T V  ^\ZTFZ^P`ZTNdT\\N`dRhN X"T#R##^$R%T'&&'b*`,R)N+b,,/.0-.L/1-X2^334Z5N876P5f8;:L;9N=>==N>Z>N>\>BfAf==\<:\9^;N8^9\97V:R5X424X1L472R33//1.L12N/1T2b2X41\2H1/^/^1P10R2-/^//F.h..-L/X./^1.V0234433^5L63T77N66P79R;\;>P@\AN@L@^AA`DRCG`HHZDJJKFJFLGGICXEGZEDEJDDDGNFETGNHTFFZIREbDTEBLIDB@V=L=<>?BR@XA^@?^??ACTBBNCTCNF`EPFXDdC^GCXHGHDHbIXIVI`KIPMLhJIZJJONPPJVLZJHZHEFIGHVHRERGVGXD`FTJHELGGEFXFGFXDbEDGGHLGTGFFLHJGZGHXJF`HJTKXMbMK^NJMFMfNQ`QNXORPN\LOXQXMXNObNfNKNNPOPROOXPZPQMDNJPJZJMIHI\FVG\EBPFDPDVDXDHE\FTGHHJXKKNLITLZNTRRONPTNNOVQTONQPRQQOJOLMbQRNPRTTVTRPFQO\QNVSRQRSTRONFKXJ^HFZFEPAVCA`BAB\BCVIGRD\HGNEDHBAZ?TBA?@?AZCRDCCECEFCD`HD`FG^JXKLXLPHNTMDQ\RPRNU`PHQNNVPXOKJL\LHHHFIIZKGHG\IHGFRNMPXKKXMHILnJX><`:<=T=;;X=h<<=^>?V>d>N@<=<<>^=ZR>`<;=;=Z<@R?^AA@ZCVC@ECADVEHGHH`GXHRKGJNIJGbLZJ\JbLINMKLK`KPJfLI^JJPKfJ`LHKXHGGVF\GNATBGZChDXA@f?L?P<>V>=AL@`@V?f@<>AN=R>@?bBNEDNGbJGPLE^GHZHI^GhKGLORMZNNLMO`JFFHZIKPJVHB`C@PA?@@BVA^??@\>F@TAZC^AZCTGJDH^ITFGIRJKbIK\HHTKLJKGPG^INNGHDEVERDELCBC@@\A?=V=<<=T=9J9^65T2^10R0R--,.*+J.,(`,V*-Z*\+,B,R)^+)+X+,J+,\*f.X-*0+.N-/-0180-R-0d1N0/5\42X3^445Z4P2N6767Z8R7485d75T47@8F5667:7\3T43`56L42P5P33`3F115263h4T0-X.,N-,P/T.-+P,\+f*,X++')V&Z&$%\&&^%Z$"$^!%#X! "X#N X\dPV^N>RVXVVJhTZ ^ X X Z ` R ^ VPZZV^RPVVRdVR^X\`HdV^HTdR@RZ\TX\`fXTZP^TXVPZdTTZZVNZDZ\XTJZ`XZdZdJXZ`^fbVZdPP\XZN`RNZXZ`XZbRbTTZh`dT\>^PdZP`TLHZ^RVRP^@PVZVd^bdZRX^XXj`VfXRVRPP`ZbRdbV\Xd\ZTZ\Z\ZPXdTRbTX\V\TT`\^ZVPXP\NVTT^\LJ\fd^RZXJVfbbdPVZ8bPTXZ`@JbPNJhPVV\T`T\VL^TPNZLT^PPRVZbTf\`TTTP^ZPZ`R\^L^LLVZPddHVV F R N T V X ZRTBXHXb\\FHNVZVdRLXP V!H"%!R%"#&N(&'*)P***+//T-X-H/0/24N1J4\47N768^9V:L77=V:P::P>><<;T=H?>>X>=P>?N?Z?A\A\FJJFTJCXHFIPHJKPH`DNG>IGBPD`DFFVGCED>Bj@BA>V:@NP>R>X=X?f@>PBBAdBXALDTC??R<;==>>X?=XAR@DRHXDCTGFENHVGFHVHEFTIHRL^JNLVJ\IJMILNMJNL`KbNLJZKKINJ6IHJGVFZEBXBLDVBBBJETA@R@?@>Z?T@V>RAF>`=<AAXDCbEdIJJpHJGFGXGPJ\H^JJNMONJONKMKKZKpLTJPIHKFXDE?NA@A>?ZB?X@X@R?<R@BABZEFTFJFELGFHXLHIKGLJIIVKZG@HHIRIIJXFEE^G`AVDbE\CD\EA@<;=X@^TZVZPH\XdTXZ`VRTPRZL^ZVff\PVZTlb^XLTXZTZfV^TP\XZP^T^LX``Z^\bZVZZTFVX\fR`ZbTZT^VL\ h RZZ`XZVTbbbhPX!b T"R"!\#L"#&b)R'N''^,++*X+Z--d--Z/J3010Z4H4^43N79d8;^9P;N:99X;;Z;b>?@>V<==<;T==X=XATCLCXBR@RDVCDCZGFVIVHEHC`FVIXILNOZJTIfI@JKIKPHRJL>MKK\MVMINJJGH:LKXJZGbIbGEC`HEEFHGNHHIXIGfEXHFFGHHFXIbIHVHIMXLTONKbMZKVOPVPhPLLLJdLNZLNOPSPLTMLLLJMbQOMVLMJLMHNRJPXKMKLJFIXHGFGI\FRGHXEbEVEbHCRGHJTJJILKPKZLRMQQRPRMKNOJPJVNRONZNjPTRPNRNVRNM8PJLPLRMNOSQOTOLPP`S@PQZNbQP^O\KJLJFBVEA\B@^?T?@AFXGHHJGJEDF\B?DTARBTA?AZG`EECTD\G\EFNGFFTJL`JLfOMTONbOXQPQPVRNOORN\MVM`JVNHHGTGFGIHGRFGE^D`GPIVGPHJZIHbJJVHPH\ITFKHNTMLKRLVGRFREPEFPDPGXDPABGFEdCJBVCCCPFBVCCDRC\EB\BNDXDB@ZD@<=b=^>D??N?=>;N<@<\8;V;9:P;V9^:9P;869R6998T:D7\9;:=>N=<=B`AEE`GDZDbEBDDNBBVBHFJFNHTD\H\EXETBZEAXBEAAD@P?BAXBBZ@A?>?<@JBZ@A\@PCPAFCFFXFCPHFDPHdHLKIdGHTKRMGVLIITKPKJMKJJRJfJHLIZLKNVHZHXIXGFNEbDTETBBHBCRABA>RA?\?J?^B>R?;X>>;;;?=@DDDZEGFHLGTFFPIFHLLN\NJMPMVLM\MTJFdL^LL\IGhFHATC`C\A`BNFXETAB^?T@\?^;;;::R;J<^9V67b8@5L6V999F8\8Z7*89V:R:f;X<;R@T>\?PAB\DXBRGfDFDNGGPIIKHVKlIVHGhHH\JIZHGTHfJXJFLXEHEGRFPFTD^DCPBTCX@A^@=\@XVTRJPL\j^NVLJXRRV\d@Rd\ X X N b N bL ^ PLZVJTNZh\LbV^NNJTRN!!"\%%#$&X''J&(')))^,X-/H)010H0^41112V386678Z:V>b9=R>:L=^>=:`;:^=:P;R?\BPCXGCEPETFGPDF^HDG`KFIJG^GFAC@HFA^DTDVEVDVDNFNG`DEDETEC\DPCTBTB^APC@>R@^=\===AX=L=:9J:^<=^8N9Z7P6`5V7D:99V899L;J::=V=F@@BBAPC@DZGAEG`IGFVFF`GFHILOHLTMXJbLJRKZFMG^JKLJJVKJZLZNMPKGPIGGGGNE\IDCDHVIVHVHJXGDJG^G^FGPGTHFJPH^IXHXGJGTHIbHZNXLHMKZO^OXPJM\MZKMbLPPXOPOPPZOKORLLRSQMNNKbOXNLONLRPDLPMKTM\IGEfJFHPIGVGGFREbHVIVHXGJGJVIJJKLJRKVJKNNNOOVKZNJHMLXNNVORMPOQQMNPORP\MVOLPOQSRRQfRdOMPNNNPVMVRNNHTGLCLDZBXCX@??A@`?VDGEKNKJGPFTECbADZBAA?b@NBDICGECD`JGHHPLNN^L^NNOONNPPQZPORLN@M`MHJLHZHFFVEEGNGDNDGREGNFGZEDKPEFjDVFLIIKG^KJNKXLPKHdIGNELEGbB@ZCbCBHCEDD^DLFJEFFDL@\DjCHBBF@AXA@P?>=ZA=?XDR@VAA?H>=C@AF@Z<^9R8X<8F8Z<8887L:P6Z6588R77X8H9X:Z9;;R?>AbACdCCDDGNF\FGTAETFHBFVJJHEbFDPGERDTBDTFAAB?>ABA@R=\?@J>Z?B@>\B\EXBXCLBPECNGLDEDbETKFKFDTFEHJJbJ^KITIIRJMRJIFJIIIJTLI\LXE\JfGVGXJGNGCDXD@@JAT@X?`ABXA^?`>=f>?;X?ZDVFABBREFFGHLGGHNK\LJXIGNIVHTHENIVHJEZGRILEHNHDRCDDFLBRCBCdCR;<@:8>5Z4L5Z62V1.,+X,^+,`,<-+-R,`+b.X,+X,^.`*V+**+T/L)X,*++Z,^-^-,-N0-\/0/H01N5P244V44J5\74P7X5\7T9P77T7^66Z56L4V57Z;V77L735Z54T4X5J6^84337577553F2R44/0/.h/V/b0R2/d..+,Z+*\*J+`*V((&&&d'&T%%^&&\%"""!"!!!!R \dJVP^ZRTdPJPbVRXXffXH h V T V ^ X X \^L\TpFRPZLRNdZ\ZbVZ^XP\dTfbV\P`TZZbPVZRNbV`PXRXXVVT^Z`VPZPVZJXVR`fbTX`^^TTVdPN\\ZR\VjX^\hLVL`\^ZJVXXbVZFZVd^PRj\BFPRNLRVTR`^^bdVd`XfT\bdR^VJNXhTPVjdP\f`fXbVjXT^b`V`^^X^bbP^ZNZ`L`DhPZ`RZ\XVd\\dN^`Ld`\TX\TLR\\fdR`ZTL`T`RXVZT^VP^Tj>ZdhZfZDfRDhRP\RVVV`RRhbThPL``VFXH^PZZT`NLXbNZZR^R\VVXZ\d L ^ T R F ^^P TZVbPVRTXbVVLZ\P!T""!`#P%&L%`%Z&%L)'(L**X*\,-/N/\0^1d121N23P3X76V65T:T:9;;\<\<;;;=;V=<;<:\?V<>R?ZAV=<`><?P@@NBN=?@b@X??XAT=X?>@Z?RB@b?Z>^>=>F;V:8;9X6J9T;:;R8R9P87Z7R7P6\79^:9R98:X;FZ=??==V>>Z=Z:X;J;V<;J:?AdA\DTFHXGLFPFGXEfHFRFTLHLLLP^KTLVJVK\K\MXKL>KDIIJGTIG^CZC\FD\DPEbBTC?R

=:T:L<:H;8\5Z64P9b9V7X6654P5\9L5j87Z8N9Z8X9=T>?>ALA^CGZE\FVFZG\JHVHZHEZLRIJJDKHIIFHFVEJTHZHXGVHFEFJHFHE^B@@BXBV=;;:65T54^00--V.-/-\0L/X.+,N+,/\,T.+,,Z,*R.*)++L/`-/B-N-J-d--.R0/1^1P2`4^7R354^8^5Z7T9d686^:V8:T94P;4667f936`73^556^4T57X754X47^578654436T3N0T0-0R0/T0X/T..++*b,((\+''N'd'T')P&&&b*#$T%b#""^#! N!Z X"NV\L`X(XLbVJVhRZ Z \ X N J R X B ^ ^PlRXNVd^`bVRB^f^LTZZ\J`XZZ^VPL`XTT\NfXZZV^ZPVTZTXP`Z\PVL\Z\^bVf^PXNbjThZXJF`b>bVV\dNZX^FL\HfRT`\\JdRZPXXb\RVfT^dTVZZ^RXbVl\\jX\^TZZTR`\XT^PVVZRX\TZ^bf\dXb^Tb^\TZXTTT\\XZRZXNNhZZXZXTP\VJbTFVdPTXZXVXTTZLXfZP\Hf^RZ^PZ`XVXZP^RjNH\b^fV\VXRlVVVHZV^ZdRT^NNTJZPTVRfZ\TN ^ b X Z X Z \fPRDXL`TTf\^V^VRb^PR##d#!%'&#^'L'&*D&Z)+,^*Z,.b2L1\-R/0R1234Z8P5J96X76T9X9P;9^??>T?^;:l=T=T==>Z>ZV>;R>V=\==>J>9L:T<=VCA`CDVEKILbLPLVNRQRSJTQPZPRNBNPJPJRF`HVHFIXFFZE^G\ENETCFPDPEVFTCZFRDBCVEVGHFFRIEFHJGXHIPGbGNELELGFDCZ?@>RADCLF\GCZCECCBXATAN@@?BFA>@V?J?@R?Z>H=AABXCA@RAV@?@CA\A>X?X=\:<9V8Z6F7`8:8b7>78R:N789^87:\:Z9P::H<^>?X?D>XAAVB?FCE^FNEEDFTFNFRFF`GHFE`D`DCFB`E@CG\E\DLDDBXEPBA\@BXBAT>@H?`@@@?RC\CEJDBPAVBCPEF`HHJKDIPGIHIJKOIKKN^KHGHINII^KfMZPMZNJKIHGTGRGEEECTD@T@=?\?HA=F=p;H<^>>>`=@@JBCDGEXEDXDCDGJ^N\NXMTOKXPLMKKTKMM\M`KLNRIIRGFXE^FNELDBBB`??\;<;=R?798L7b89L:\8L3d1221N000R01//.40N440\4^3H60R42Z3T00-/R.+R/0Z0,`/R.4215/R3333>876J669FABEARAFTCCIENI`JVHbGTFZDLC`FCCHTCVFNFEREbC\CZDBCFIB^DFCLBBF@JFVAVBB`>==:`>B=;=V>:;9?h8;h79R8X:?N??ZAL=JAV?X?FFXCbGPCAGZETEJTJLI\LbGVLKFXKIZLHIJL\JIhHHRHGXHLlIXGLIMPLMdLLKIJKLJLKJKFEDFBPHVGJJXJ\JIKHCCEFJI\MZLTHGJJJFNZLhMMZMZPLnKZLN\MMPPPPKKOXNPTQP^NNZNTLHMOONSNQTNL`M\PNZOPQMPKHJ\IIXHElGZF\F:KGZGHJ^H@GHMJ^LbPNJM^K^PXQQPRVQVORPQSTQROL^Q^ORPPPRQSPTQTVSR^RPZOPNVOQPPTQZN\LDJIHXIHBGJEC^GHCPA\@DCPCETBGVGGI\HIJMM`LNIVGHGGVENGCEDZEFETBCZATBVCGDIFI\LTNVHKTLVOQRQTPJNVMVLXJI\JFJVGLZGRKVGDND^CBNADDHE`EBAZCDE\GDFEC^EFG^FFFEHJbE\EDTDDCb@Z?XB@XBCGDCX@D\C@TE@PBbAVD@\@=@>h?VB>?J?<@XCD^@CbAVAEDBC^D@p>J=^@>P?HA^C@`?@ACE^CRDHABBHAZDDVEEEJFVKZGXJMLLXMbPOKVMKNMLLJMRKPKLNOTLMILLGIE\GEGZGD@T?^?L@=?=;Z===V;V<8\@;=L<>ABRBDEFZFDTFFG\F\ILJL^OOMTM^LN`LZKKLNPKLHbHVHRGXIPFFXI\DXGTCA><=<=;X==R><8J7<55F86T68P7745d8987Z:9V9::::F=VACVF^DGLDDEIKPHJERJMNK\KHKHXKbKZIHHGIII^HHFDRHbGELCb?CX@d@DA<;^98V7d6R3X2\140r0-d/Z/^1,.H-,-D+P,-,/,X.Z/,J,\))Z+*L-N+,`.L./-00L1X2T13X3\325T547\786b8:9N9Z75X66T7N7887d8:`5666^6636L4L9X8R7\8T8L8X7H8X8T5X5`4\0L41V1T0`0.h/2n/-\-.+,+))'Z,()'B)f',H'(^&'N$Z$`&R#V#b#P!!\"L"^ XXZ\\V\HNZPVbL ` V ^ J \ N R X V P TZXLfZPV^ZVRRfZVVX\h\RX\R`^ZTFTRPXN`TXZZTDfd`Z\TfNX^``Z\ZZRZ^\T^dbPTdLbXRTVXZ\Z^VXdNZRPVR\\^b\bTL\DZfLnHZXbT\Nd\\JT\^j\Z`N`PXXTVRLdbld^Ldh^dTh\b^NbZh:`bbZddDLLZRJVjTTV^NZP^LRBVb\PVVRdNfTP`PPdVPVRN\^b\V`X\TTRV`XRVPXLbJbP\@P\JRVT\XRj\PbZRZNZb^TPXZ`TFXT^NR\TZPhJP\FTP^L\FZZFNfVVRDTZRZ\`b T P T Z h T R LTT^PXVNVRTTPHV N#Z" "T'J&%b&%&&'h('+J*X-\--.-Z10R32\33R6D77l:99h:;d=<\=j?R;:\95V886T87X211d3J420R0V3P/Z/.//R01X2`4121/F.0/P--/,+*N4/N0-P.L1514P0T2R05P35N6\5X7R8698>;Z;=R>?Z>V;^=F<9?AJ^KKJ^KM:JM^L`JGXI^DPGHVNKKXIRLRILVMMMMHXIEI\MJKFFFdDRFRFFFFEXEDXBPDfEEZFJTJbHLIZJTKI^MZLLLLKNXO^O\LLLNTN\NIJKK@NOPLPNNOMLZKLMFNNNRPRhNLLNMJMHJJKMXKKGGEPFZETFFBIXGEZHIPMJORJ^PBLJPNK\MQZR@RRJQQNPQNQROSPTNQLMQBPOHOQPPRFRTXRQOROfRNLOMKVIKFVGXHGXIVIDTCAPDA?DTBA\BCC\H`FTK^K\MXJN\NLbPLZKKXGFBFFIFTCECTED`CBRGVJHbLLHLXIVMXKRO\NZJNLTN`MMPRJRL^IIHTIGENCEVEBVBBTDACALBZAECZETDDFZFNHZFCDCRC^JfGGCDBC\A=BZANA`DAVCPHFCNBDPAFCTC?XDZCB`>AbAA?\=T>`AP@RA=Cb>ZD@lALACB`CDDRDV?==J?L<::9<9R:9989R:\;9J;9999;T:R9X;=V>>XA^AF@RAJCACTEZCXC>@:BBBTDBCbHCRFPJ\KJJH`LMMOdL>RROPKXMKXMPJ^MTPLPM\LLLTMHOKH^HVDJILKZFDDAB>>=L@=^>V;=X;V::T:`<?VA?EZEVBPEDCCEXEHZGVLK`KRLRLPKXOLDKLMVMKMKJTJ`MVJ@KFTHPCHFVEFB`C^CA@`?>::>T<^73T5f2X31H0^1L200J.,b.X-R--.,Z/,//0P0D-R-d*H,^,J-V0^-./P-R21111H1Z44X5T3L4T85V9L7N<`:;b7P<;89:^6@6b9T8:`<7h7P63X53H56X37R55`85d78V9l989553R4R2/T102011V-X1^--+N+.d*\)\*(P-'('Z(P*j'T&(Z&(`&#X$N#\#\#T" !`"bNXTPRZPLRRZV^TZ^VT^ T Z T X Z L V \ `LZVVHNVZHfNb^L>RTL`\XRTBNR^X^`ZXbTTPfN^dFZ\^Z^XbZ^TVhXJf\Z^RNbZNV\RTXFdV\NPXbNPZV^NTXfRb`\ZJ@ZXdTT\PTR`VbZd@NPPZ\T\TLLJPlfNbh^n`\^^RLdhRPNVd^^VX\XTh^JZZb`fVdXPdjbbL`bZZRjZ\JbV\\ZLXd^`PPZP^^XT\RJZNZ\"XZ`Z`Tb\ZRVfV`bXbZ`VXZ\ZZRX^`jTbTd^XD\XX^TTV`XTXXbXX\VZPXTRHNTJXX`fRVJXR`V^\RZLJXlXN\T T R P ` T f P d H PNbTPJPXd^PZV^VVT"b F"R%^#"#T$&%$%&)Z'V)T)))J-,T//^/.03T2T:4N8d6P:^:9Z:Z:=T>X>?R;=Z@DXBBPFTCH\HHFHZFFZEFRHVD\ERDEGFFRG^JBE@ACDD`EBbDbDLG\DF^CAlC??\>Z>X>A>?V>>Lf;R:Zb?P@P@X=>N?^CDTEDTETGXEHJRLTJPKHH`LPIITKIdOJJIJNKHHFGZIJKTKIHXKH\MJNZK\KRKHZJIVIHGVIFCbEFNDGEEXHDDFD\GDJFTLLHIbKKXMRO\MKMJLNTNVRMOKRRVNKK\LLDLMMTOLMPLZMLLQTKLNVRdNLHMJJJ^L\HLK`LNRNJK\IEBCCfDZGZGZE\G\IHGRJGHMZLTOLhMILMKLLPNPNPMQNOTONPNTbPPR\RQP\PPOZSS`NOQR?B?BB@BNGCBC@ARAECTBDTGG^IGH^J`I\LNPNPTRbOQ\PLKfLRKLZLPMRMM^KNKKTNNMMZIG\FdIDGDE@VAAAP>b?>N<^>b=;;9=`=>^=H>>PBTCBNEFCXDCXAGFKNJHILKJBLN^QbMJQTP^KZJbOI\JGHFDGdGdEPFERGXBdCAP@Z@R?Z;?R>=9;X:95Z5P4X5Z6232V3/0b,/0V..R-`/P/0-R./Z.,+L,b,P--\.-V./-V0P2T1X0N31N3L55^3Z5T667^:976^778b75^7486^9876j9R635`848V726R5678579b;4d9432L22J03H2\1T20\0.d-^-,X,*Z)X*\)\))N+Z,N(')(b)'&\)$$X#"Z"L$#$!b!V bN^ZRZRRVJTZL\bLV\Z LdX V Z H T X ^ b \ X HVP^XBbPTPNV^T\dTd\XVdVXNZRXP\VVN\hXZ^RRVfd`J\X^XVb^\`PTN``ZX\TNTZNLV\NPNP`V^bfRZTV`bbNRlZ`Z`fZhZ\^TbJZTlN\b\\VZTV^T\ZXVb\LTR`RL\dZ^b\f^\L`TdXVjFRXV^^j^^VX`fhP`XZT\dPVd\PN`\PNRNdhRZ^^\`^RPfXVZV\`VJZTfNjN\\X`T`XNZLN\`PRZ^T\PXX^TDVTZf\^LNdV\RN\PPVLNfLXRPZPN`^dHNZRR`V\RXLRVL^^jPhNXFjRXT^bD Z X > \ X N R ^VVXZR\XXZ\"""T&"%X$$%&X&^''(*b,Z,.,T/`2/005X6Z3458f8X;R:`\?L=>V><@;=J;\=;78V8V9<9R>>FR?@`DPBGD\GGKhJZMIbLZJFIJ\IHGMPKRKNNZMJPLKLIPHFGKKLMJPG\HTKMVJLKIHHDVKGdIIEDDLDBEEFGF>FDE\BFTI\GGGNI\KRKfM`LO^KMKRLTL\N\NM\OFPPKhLLLZNIIVJIJ\KLPQNbK^KMMNJZJILNHRHfLZNHNJOIJJEGZFCHFJZJHXIG\F^JREHPNJLJLKLM^ILNVNLbPLM^OTOObOPPHOVPNP`OXPZOQRPNTOOMVRTO^LKLVKPKZGPDEVCB\IDTEFVGVBTFTBfFADGRFbGEZFFZKKVPMNQNPXO^NXPVPOLNKJJhHNIbHHFCF`IGdJPJJPKJKIXGK\IHDVJXJI`K\LNKFVGZEJIdGLDVBECJCLCZBDC????XAR?HAAB^CLF\BZEZEA`DEDXCCNCDXD\AB@X?P>C@=ACDABAAbARAAdB=dB>P@A?LB^BAFD\CCP@ZA`B@PCBE`DBCDCVC@@P=Z=X=\;=T;^;7<9\7R9T97\7X:;:J9R9P:8:V9\;;N=R>?><>V@FBATCPATDCZEPGFFVJGGIDFGTEIJIFEGEG^G\GdFZEFVH^HXHVHLGZEPBA>@BP@?R?\B?@AV?XAV@XAAACTDNDB\BZCZIHbFILKLbRNOPQPNQNMNMKZNNbK\LNLNXLKTNZKHJGJGFVDFBGA^?TAb<\;TA?;V;h;9:<=J>\?lBXC@T?@V@FXD^DE\JNJKHL`LNVPNbQNOZNKNN\OM`KTJJIIbERHFRChEJEpERDE`EJD@?@=Z<@ChDZEDGCGVGZKNFLNHbKFGKPJJ\ILVLLXLHFVJIHHIH^HPGXIRH^DZHBDCb>>P;^=`9T6X5R5354R53X30Z0V1`//Z2L.X31T1h.0-Z--/+^.+0..P/b-/1\1P32X1T2J23X23H8h5596X9::\<>96Z9\6T6V7\978Z;7778\7Z66Z5b765P569J797N58883h4^6N542\1T0f522R1B.+^-^-B-L-\.X+**)X*(+Z+*)Z,d''(%\%N&P$$#`"V$@%X!Z!!VfT\JX``N^XZTd T\X L T T J \ \ b @ B^Lf`LPVP^RZh^PVZLZbTXZNLf\`NTb^\^XR^V\T\^XVV\Jn\jZhNTFZNZTPlZXVT`ZTN`X\RfNdLZNXZ\^NRbRVT^ZVRVVZXPVZfNR\\XLVbHXbXhdNl`TbZhd`blZrPbZZVb\XZ\\ZPjTPj`jpJZbPhnNRZRL`TXdHZhVdP\TTZ`>:h``ZXX^VPjTBZRVVdbV^PTV\XbbT\n\`RNbX\V^RbPXb\VHdTX\N`\DT<ZHZ`RLXdRR`\`\VTTdRb`F`^^RLZ\NRXhNXZT\D`RLZb\Z V ` X d @ X V JfPd^XTRdd\TR^ZP"$f$"R#%Z#T#R$'$'D%(B)(R)+L/*/Z2F/22333`8^6Z8L78b>R:<=P;V:F:\;Z<\<^@<>\<^;\=^1j11/V.V0/01`//0d0F.l2X0/.)*-^.f//-.R.0N/P14V0033d4\46\74^9:P:V<9::N?>=^=ATB\BZBDC^@DHIBB`ERCEFhJRHLXGERGHJCRFDbFACPEDZCEFCFD`CBAdB^DAA@\@?\===:b<99J96\7<HKKTMTF\KbJFK\I^HFK`LG`HDEEDG^B^FRDXFB^HHCGDdHPEFPKHPKBMNLLfLKMKJZK^NM`QKMLZNbNKKKXJNOVO\ONLXOJMKTORLP`LNKIjKHIGPJPLKLLbLNHPEC\CXFITEFG^HFIZKBGPJRFILHJFIKJLGZMTMPJPMNLNDPJLH\MXP`PQTQPNXPPMZNTMMPMVO^QNTRPOP`NNSZKTLJKGDF\CDERE?ECGDFPD^CLE^FEGEFHPFGJZNPMNORPQfQPRXQJSRSPTOKJVMXGVJFVHbFdEHIEIJPGNKJTKKLHXIVJEZFDGHHI\HFFFDBFEXEAAF^BCBB>=@?HCBB`ARABEARDCZBXC`FCE^FGBdBNB@X@XA@Z?XB?P?TD@@B@ZANBRBRAZ?=<==H?R>@^ACDCCBCX@@B?@DRCNDVBLDCRGTBAJ?`??<\?V;;9:V;N:88 7R;6X;\;8<`;;P>9X;R<<>X==^:J;T?Z>BL@A>ZCbACGEEHIPJJG^KIZFNIVKMPGRKRIGGXJZIG\LVGJFEVGBPDAA?VAV@@XBDXDXE@ADB@AZERBFNCHZGDCII^IK\J^LfMZOOPO\RNNVKLILKLLOdNLKKZLLLIZOFJHIFHDFTECZDHCV@=P>;T;X@^=TP?Ab@H>V@`@@BLEHFGbJKRLMJROQLMK^NPPLPDLIOFK^HFHFDLCI\HPFNDCDDRAR@@B@>`@:\:8667V6\76J:7;9F:\:Z99;;X;R;9=:=J45h5403/0d0^.,P./*^-+.R+)^*P+X*(P)\,)R&P'''`%X$#T%N%""Z !B R ^V^L\ZDXDHR`TTRPLDXjZbVL \ \ j P Z Z ` b^V^f`f^bfNXXRX^XVbV`TR`HbVFVl^TTZ`LZ\fdZ\PR^VR\bXPTV^TZRfTZbd`ZT^fRXVRX^ZV^VT\fNNVXdZR`NTF^XJJNX\TdVR\\b\^\RLBZN\X\\^fPfhTXbbdbTT\Pd\PPXNVJV\dPjNNTXTbN`RRRZ^ZVRXZXR\^ZT^`LXVV\ZZZTT\R^\RRfPLRH\VNhVdLpVHb\RTTXRdPVZ^XXZZVTVZ\HfZN\JVP`ZLXVNPbLTH`HVTTbZVRbRPFV\RZ`ZhV\TZRP XX N L R P : Z V XTVXXNfThP\TbTHTNVJ\`TX!V"\#R"%"R#&$N&`(P('V*+R*L/P.`./3\301P4V56R789`;P8:;^V?^<:J<\;=\>?<>9X:r9>;TZB^BBAAAZADBXCRDJAFEEJKJHdGVFFFIFRGFTJ`FRCbIHEfHCFEVIE\FCC^BC^DCbB\AP@\@J?Z;<;:X:^;8T:99V::Z:T978R:;:V<<<=;=@@FZCZFC`EJHXMPJ^J\IVKGJIDLHIKFPMPM^LKFL^MNMNRK`JG\J\ITKKZKKL`GI`LKKTMJ`ILHLZIJNIHJ\GDVCZCE`A\C\GGHGFXEFXGITHKPIKKXKLLKOOMTPKJINN^KKPJLJIXKILJJVLTMLMNKPKZKbNKLJRKNRPIILHJKNJ\MVH\HGRFHGEJNGF\HIHHPFbHLFVGbJLI^INJGLKMK^LPPMPLMRJNKNNPNPQMTKZJXKQOPPQPTFPRUVRNTNbOVKKHVDNFXFPDZDECCFPEVCEXFCbG^GFGFFLGHIRJJLKdNONQQXPVSRQXVQZMRNZL@KLLFVHVGZDEEHJXJMLVITJ^L^IPIMNHGHEEhFNFZIVHFCDZDBVDZERCCZCTERABAC`CVBA@@@>?AR?NDJCbATCDCDBGATACT@>??>F=F@?V?>?B@X?>R>P=j<=;F?@X@XAZCEDEdCRB`B^EZADCJBG\CXCZDXA??`@=;N=:F;9Z;9P:9X:8X:X9Z:P9;<979V8X<>R?P?R=Z=AP?N?Z@@CHAh@B`GPE`GPF\HfIGTJGIJKPJFKGGHI\MHIXJ^GbIG`FLCTHVECDLBdB>JAN=?@=TB^ARDBT@PD@XCFFDEFXGFFJLIIMXMMLTPPPNNJKVMNK\KPMMLMIPOMKMRPLTJ\HXHIHRLDKTFEFJC@BXA\;NCb>;T:P87Z777989P97V=99;T9R;;L?V?@RBB@BHEDFG^HCFRFENGKXJXHFLPORKLJJ\MFKfJLIJNII`J\HHHIFfEA>R?T>hH`NJV B Z R L Z PX H\NZTVPTPbZ\TPP\V`TXRRTT\VTVf`TXJ`Zb^HPR^dTJRbXbX\PXdJX^XX^b\^\JVPbh^bDZPHj^PTLZ`^\Z\ZNXLL\L`TTVZXV\VdT^bRZX\rXRVfXRJhL`P\XhLjTPXb`Rd`T`djdXhb`PPV\d^jVT\ZRfhBNZd\PZVVVZ`^^^\PfV^\`Td^\ZX^XXV^XZXThPRX^f\NZ6fTZ^\ZT`b\bjRTj^NVPVLPNhdZLTRTNTJRXVZ^ZRbNT\VPbPNXT\RbPHVdRVV^dVNRPXLTXT f V V T F ` ` PXT^NN^X`JZ^BVLL^dL\TNX R"!Z"`#"\&%$&T'(T(`)X'X,,j/N//2D2f4V1X32V7\5\8F89T>>:TVT>\=>;d?::9`:::67V5^45\7Z7L36/1220X/1^3N54/.2/b1N/2\/T-P1/P1H0X0L/^-d-*X.X/,,0,F/L1R005^3Z6R5X59=Z5::T@@:P??V=C@AdFCTETF^DRDDEDXE`DRDXHIRHXFD\G^HRJPHHHHVHJD\DVHGBIbC&HTEVCPDZ@VDPECVBBVBR?>=N=\>>AZCfEEDTKHIJPLZLHKJ\MIK^LIKLKbK\JILOJPMXKMfMbK^H\IFLKJKXKJRKIHIbLMRJLMRJGIZIHbH`GG\E^DXE`DCZCAETCTE^FVFCDFFILHJIZOJKRJVMNVLNJKTJNNLM\LNKHM^KLJJLJbNNNMNMTKLLRNXKLPMLLLTLLKJIJHFVGRIDIVJPHVHZGGLH\HIG^GLHHILGDEGGH4JRKfPDIJK`JdINJKLKK:KMNZRXQRTPZLTKfLOOPVQOPTOJLPRQRKbKJHIEBCFBNCZBCGGGNF\FdEFTHFIEFIZIHGVLRNQVSRVVQSTQVRZPQNMTOJHGFREDTHGHJJZJJJNVKZNPIKDJJbGEFGbFHGRGZHGCT@BD@BFDBPChDB`AAP?^BB?HBZA>>V?V?R@BXDDFEdDREEhCT@\?@?;;P<=X>?L>>X=L=N?^@`>T@Z>>\P?VAJ>\>@?B^>X==dBHAdBdCbDD\HTFF^HI^JHJKVIKVMOINVJNJhF^IEHTEEDAAA@dC@?>B@\AC??NBPDdDAGDXG>EREJVGbIZKKJbPLXJLZNONL`OJLLNMMKNMNNVLQPVN\KTHNJIHGTERGZGVDRCAR?`<=;\::N?9:\8Z;<=R?X>b?=hEDNDZFHZHZJJVJKLKNVMMTK`NRMZMIKJIKTIG^FFEHRHGFDFC@D`A>A@AbAR>X=77P88P<7J:R9V;9Z;9J;V:;^<=V<9:R::P;L?>XBFBDDACDdINGCBDXD\GJFPGZJTJNJRMLVJJHLXMfMTJZKXKIJXKG^FVF^HRH\H^FCh@?V===9:87^5<753l2J3^2N.003F1V10P1N00-/,T-/P,-6--^.,/,T0V1X2P0/X0b.1133P45R:\8P:7^7:`578^79;6V67N:R78;N8;7;9V9Z8T8V6875V9R7V66N47B63243F1V5R5T1303\/X//T0F.R/-^,/,R,^-+`-R-N,(V+^&b'$(h$F'%%%V%R$$Z N BT TPXL^\RN^\\PRL b d f L b Z \ V ^ X Z j N V T\V>V`\NRF`Z`\^Nj\\T\^RZ`P\L\b\jVRdbN^^bNRXZTV\^FNnPZhX\^ZbXRZ`ZV\PTR\TNVNZP^@XXh^NTVVZXTlZNVVTVT`HN^`b^\XX\NVVX`RZXXNVVj\TJTb\RPXfbfTVbZdbdZ`JJZ\V`RdVh`bXXdV\^^^dP`^nTXPZVXRp\bTbT^JLb`NXPP^`PLdTZj`N\nbX^NRjDhR^Z\T`RXVZZT\RNbT^LVNN``XXZ``HRb\`X^V^ZBbXhPTXZdTPLRHXL\NFXR\ZXVfZ@RRZ`LVF L Z b VPPV^TTVTbZNN^!P!R!"^!R%R$X&'$P(%T%))(,^-J,0P00`4\343N3556T78:9;R>=d?Z=<;=\<;:;J;<:N==>T=P=R:X8X;\8^7R9R76R4V843T3X142N2^221131/0T/-X.0.,.d1N0-j-Z.`.-^,,-+Z.Z,j.`/\0V0T225Z74b7X7T66X8;L>N?T@>`>T?\=>A?VA`EZFC\EDEZEXCRFFDIZETIGGFXJIRHdKGPGXGI^JIDZFPHEDDFRDDCCAXF@DCA^BAL@<>;8797:95`898869ARAXCDDB@`BF@AN@JECN@HC?HBb??\>ZA\DXCBCNEZDABABZ?T?=b>Z\=D<=\;=L>d@F=;?X>?X@bDA?T>R?ADFADFJINGJJJJPNLLXK\MMMK^OLHEEDHETEC\AACRA@C@AP@?n?AA@F?XBDBBC\GEJVKJIKNHVJMTOKHJRLNKJNLLZKZQPRN^MPZMLXLZLdJJHZF^H^GXIHFBXD\BAA==;T>;XN=R>:V:9Z7\88;V<>X<9V99\;7>N:=J@DNCXA@?ARCDRDBTE\DRFFEG^ILRKKKRKJLVKBLKKZKJ\KK^JRLTKIG^IZFCNAAX==T=`>9J8V9R9577R4h4\1/`3B6X4^3L1/^10V-,X.0/./-,.,-,+R0X2L1/.Z/^/\33P2^6Z4653:P9P:8V:697T9V9J:V7777R:^:P6Z7R8:X8:X7:H87;R68V9^7L78H4P345V546T6N523Z3P12F1.-1/d00L./,^+,^/`*D)+\)X)T%&%(n&%Z'N&&$V$ PN jXN ZN^\XTLXBV^^LX P Z R T T N R ` d H \Pd\RZXJTN\^LZR`B\PfRV``ZZ\fbhjb\^VX`X`\Z^X\ZZNX@PVhVb\VZP\N\P\d^`HV`BZ`^XX\^Hh\dT\Z`X^PbPPL\\h\PfLZTRZNRR`H`JRR\F\\ZdbbfZXZZ^V^Z\X^XRXhVPdNd^^f^d`^`L``fX`bd^RZL\lbTN`\dJfdf`TNNXdZfNZ^XVjT^`PXd\HhPVV^ThNX\nZXV\T^ZTT^fRbT\ZdXRNdTRd^X^L`dbNNXTXdXZd`Z\`V\Xb^RVXJNdXXHbHXFdHZ^TP`^X\VNLZbP L^X T ^ V Z f R Z Z \ b\X lR^dHbPRVN\FTb^XDLF fR`"!!T%\&X$Z%\&\%\$T)Z()^-*T-.n225L2P145h556b69P;n:=^==R>:V<;9;;P;=?\<=;9;^9d7X5:8X76L6Z63T5\04421T3b030b/V1/-T/0//--d-\2F0\/R.>,X1/X+J+X,V+--/P/^/.5R35V6Z3@46X;;9F;=X?`=?=V@>?R=\EAhBTDNCJGEETHNFEFPEFPJ^GFDTGJVIZGJGEHVGTHPEGTKPERKJEPFVGXFCREHBANDRDAT@VB`@@B=dR>T:H8R76N9J96^877h899::<=>=X?ABVAEVCDHFGHFZGXGIJHILHLTJLLXNhQXLKXLXJXMLKKIKKPHbGVJKTHXHIXNZFbIdKPEfJVIJGHMFEPGRFXFFNFHCZEB\DE^CDVC\GF`HXJ`LHPMVLRNVPLKTLKPOMTLM^R\NKdLNLVM^IXIJNKKPKKHKdLLNM\JTKNJKXN^KMNTNNNTM`JGHIHGKZKBKGZI\HNIVEIbFPGILdLK^GVLHJTNLNJ\HGLLLQZOOONMXQTPQPVSOQRQNQORQdNVNVRZOQJVLHKJ\JHNFDZF^@EN@BAFEXD@GTHFNHPFVGFGHIbHRIJXJZON\RZVUTYWLWRRSVXRbOOFPKDJIFDHFGHGNHEFIJOZN\LZLdKLLNHNJLVGHDXFLGG\FEDAB?R?VBBBZBCXAdA@RC^?ZAVC\DZBL>AADCJBRD`DTCEBPA\CA;b>^>;L;>L?`>P?<;T;:<;9F=>=<<^@A??`A>VBXBCbD^DLIHJGLVPJDLJKJKVLJKKTKJGVGZFHGHH^ENDXCAA\BT@TB@A@V?X>=X@ZD?^?XB^DVADETHTGPHGTGJLITLHVHMJKJLZMTNNN^MMM`OMO\RNROKLJ\JPIXKXHNJIXIPHFhGLD@\B>^@@X?d;V=;>P><^=T=>N@dARDVGEGXIMM\MKLRMPLZLJ`OM`JMTKKJFGJPJZHGERFHHhFNGDEZCD\EBN?P=H;;=T;B:Z:;79^::Z=AZ>^9^8;<`>P;@DCP?AV?A?TAVCDFGPFEZGRHHLGdLNJL\LJJOXOMdI^L\LI\LNRLIIRILJELFDAA==X<\VL\ZVfTPVRNfV^V^ZTbVVTXRVT^RZBHTPT^`XRNXZXRbVTV\VRLHL^B d f V R ^ J N J  T T^NZ\FTPRRbTJh  Zb^ V#!"Z%^&)&&(X+V)L*V-,.@//2/4P1747P4N97F9R;;V=<>N=\A:;:;b<<\=:T@R>X;V;;;=8J:X9X8\:6X67X9R944R3H2V3D3V0R531V1J0//-N/V13-.R/L,1/0X--X,-N-P.,X1-\.N..2R4R32b44J457f9XFACT?^?R??R@,GXCdBEVCCBHBRDCRFAPHLG`GFDI\EXHJKXGGZH`MHKKMIXKCG^EXDDDXDdDACA@L>VAPA=bA9J:\>T<;`98::@Z=L<=<;:;V=P9L9:Z;TDAZBDVCD\DPBZCBE^ECND?@T@>D@===R^=P:J>X;>PA?N?B?ADFECEFGPHGKJZMMKMFNK^IMVKK^JGLHGZIF\HDXFBXBBVAD?@>AX?@T?@LARDC^AAFBXDEGfFZJEHGHLILXLLJPfQPMPNNSRTN^ONXMLFMJTHIIII`LJFXHVFDT@L@=^=?L=V<9N?DP??h@AGBDVC\FKHIKJVN`JLJMI^KLVKRMLZLXPLZMPKI`LNHHZDVBJB??AT?;N?4T2/.3f1,\-0,-^/T,V/V,`/-.--.-.Z3-/T/Z0b11T52Z44T5P7V7P97Z8V6d6:8T;8R:8:86X:@8Z:Z<`8;`<:9Z;9;`;V;866`747L6^6R74R654Z32421X2H22T022T00\/X0L00+V-V.R(J*)T*X*B'^)%f&$&V'X%V$`$X"V N"!!L" T TZFdV\^\LLZVZZPZ V ^ X ` T ^ Z L X ` N TbL ddX\XTPLR\fR`XJT^V`HXX^\N\PZ\RVVP\V\XdX^bbVjdbfNXZVNRZ`bn\ZfX^b`JVXTJPVd`bXHP\XNXFVb^JT^Z\P\`dX^\LZT^NXTRXP^fRRTP`\V>VTRXTfjblbbj`Zbb\j`RXbP\TZbf^D`^`HXTZVVdRTX\^^^LZ\TRNTTPrF\`Nf^ZZT\PfNJ``J\`ZXJXZZZNTN`bH`ZXZ^T\NNlR`TZXNNT`N`TZjVTjPX\Tf\RbXhRhP\j^\RXDXZVXdRRTZT\\\R`XLXfXNRjJLL\  Z T F T \ b Z X V ^ ^ bRXFbXTRTV\bb`TbJ>h\^T\\ J"!!$%^$%'Z'Z&**-Z,-X.R/R2h02Z0R25b4:6X;9X<<<9;d=A@V?R?H;b=?@V@>Z==Z9\<9B:9T=BBCB\DbEB\DCXFPFNCBZA@X@A=`>>==X:L;:79\::R:\>==Z@X??X=N=V;<\A^A@V>?A`AEFPHXHXGHLK^ILO\KHLPMVKKbLJ`IGIKBIFFGdDXDLCDVALBPC@B>`?N??T>^?\@CBDBAZBD^GFZDEGRI`INKHLIDKTIZLVKLMPQXOOTOOVPLPNMTQPKJ^JK^LIPLdLIHKFnEAR?`=V>r@T=;;`=9b<=;`@Cb==`C@bDNEKGfHNJILLnOLbOLNPOHQJLZMhMRJNKKJZJbJdKGHLFGTDEJCJCB@dA^A>X<=X9L:TA=@>=?`AN>=>?dCBdCDDEE\JILLIIH`JLJTLTKLLKIRMXKNNLNKKVORFHEVHCHDB@X?;P8:N<:P7f6R5T63f7R4T32/12.Z2Z1^.Z0,-\/Z/*R,),V-,-L-T.-R/P2X301X112b7P83349P6L5^75L4T69:8\;88Z<^98l=Z999f98877V4H6P5T6P344T4^1V3Z3`1T1Z32P3L/P3N1`.R.*.)+P+*j&h*H)&&'T'T$$Z#!P!Z!X#Z&$\ dVPPPXRNZXVZ^bTRVFhR Z Z L ^ R R f F j L T J P `PTV\TRZ\Zb\PVVP\ZXhTPR\hL\NT^lPdfV^ZV\RXT`ZVZl\V^`VPX\`\Nbb\ZbVX`LR^RPNXV^^Z\PN^RZX\h``LT\HdVVXLXRZXVRPhRR^XVd\\J\NdXJbRTFN``TPRTVRpd`b\BT`P`dV\XXhZPN\fXJXXTTdTTdTRb\`HXTlT`\`TVnZ\^ZNN^f`X\\fR\`\R\V\VPjXVjPXJPfN\F`NZ\LfNbZbT\`^LNfbTLF\PHf^R^PdRX`X`Z\HTZZ\XVPTPHbRVRXX^T\^RJ^RZRPTLXTPNVRTZT ` \ T d J h J L Z V\L ZLXXZ\R`RTZ^LV \R X!^ #X L"\"R$L$%T'&('\*R,-X,-/.0X1L2\3Z64d5N7`3X59<:d<\;=JA=;;^;R=R=R=?>T?N:97N9^8\;T:L;b::J9:==T>>>@DC^DCERFfINDGFVIFHTHGhEZGTIVJJIPLKK\NVR^RPNJMNNNNMNDOKPOVKIXJKRIFPHG^IHJIZKJJVFHTGJHHLGZGECCZDDPDCLCXE\CCNDD`GVIMIHHXMBNJQO`ORNVO`NhO\PQPO\OXMJJ\FGTI\HBG\MVMKORLMPNVLOH^KJMNITL`J^OLJNPTNKK\LKJTGbJKJMXMJLJLJRJHINIVJNLHIIdLMHM^KMITKJOLPXNPQNNKNOMNPPNMZQ\NBMLNLLMVKJGI\IHFIIEXEXECBP@ZAFF\ETFEDJ^JMLMHKOM\LIZKJTMJOOXMJVRUPT^US\UPUSLQ^NP\MHNNOM^MNPMOPLLXNXNLJ>JRKKZJFTKGFNFJIE^EERHEEDNDLCZDDVBTDRATAA@B@ALBPCEGVILFHEE^HTGVDbED\A@^@Z?>V??=>?L;=:7\:R;9^89777;^;9L:<?d@N=@R@X=>J?R;PA9>9>;\;;X:==N;\<\\>P?Z=@L>;`=`<><>HAb?>^DJBBZGZFFHZGTI^IMLdK^LLKZL^JIFIKLHIVDTFXDJPGBTBB@BA@^@>X?R=;>VEATDAAPGBfDEPGDHFEGRFXKLZH`KNIKLKOPVQQRZPVMNRMMONOKLKTLNJZMNKLINFTKEPDZAA@;X@T?>L;\<>^;=b>;=T:9X;V;^:\=\=9\8^<=9;8:9L=V;=:9\<<;V97V8P<<;R;Z;hZ=T>\==::8\::9R9Z:876354L3413210\1\2-Z0V.X-Z,,`,+0h,,-R-\,-+-D.0X.^,P-d-0/X1\2R2445Z6T89X9\@B?`@X@H?`N?<=V=@AAXERGDREDLGEFRGPIFGXDGRHEHdMNbKIFLNbOPPXSRZPMVOQQJSROMM^MNJNKK\IKPGZJGGbJJKJIVJKGJGTHRFVFHGFBDTBCCDRBNDCDJINIKNIHHNKMZMZMNS^NZOPQXONPRKXMGHG`IZHHdKMLKLNPKLZMJINKLJ^L\KLHKTMhLLQTN\PTMOJJMTMKFMRMKN^L`L\KZKRKKNHHHXJZJLKJPOJZKM^NJONO`OQKMOMM^OMMPOTNO\MNLNM`NHIIHXJZLVFXIVF`FGHGRDDVFRFB\CDHEIbJ\GIKM^LbPJOOLTLPKJJTOKOO^PTPRRXR\TPRU`PNhPLN\MP\RPNMXQVQVRMRNIO`K\KM\IDbGEFRCEVDTGE\KbEEDCA\APCh>AAPBC\DBCZABLEHGFFbEHGJ\GF\FCA><=V?J<=>===V@=J==H?>Z=>f:9<9R;X;:F=::?<;H=V><>P9T;ZR?A@`C^CCPFDDEGEDGRFG^GTGGNGJMTLNXOXNZOPNLMVLLMPXKRNMIdLLbMJZHVHLIE`CDZBZA?@?N=P;=;:?;`>L>=H=b=`?R@BHBDDFJbLKJKKTK^NPZPSQ`QZSNK^NILLbLMJ\HJ^GEFDGNG`KA@B;`=8^=?<8B9V@T:99Z8B:V:R:=<\=;P<::=NAj>^=F=RB?AZDLCDDHHVFNGNGdGRJLIMXJPKNMJOOXGOVMVLbMOTNJ\KVNPJHFNGVD`GDDD?VBZ?X>V<;9H8;\6X6X5^8P64X3/V//..V/Z,-T/P,^++,,,-X-.-N--00\0./2T3346^6L414T34^3V436d78:J:X9H;^9N<^<=;7X668::8X;;=f<:V=89:^8X87V:8P7FRZRVZ\ZF^fR\hbhbbbVb^b`df`R`^NdZZZ^\RRXbNVNRfP\^^TdJVZZP^V\Pb`X^ZdX\ZV`T\\VRTZ\Z^Xb\^`dZRV\^VZRbVLPfLd\P\Zb\NbTjXZTJP\XX`RX\N`RXDT\RLRJ`^NRR\^VNlT\ZZ\\T@PNT\JRTRB^FZbNf R d R X d N P Z`VNVPNFX\R^\J`VT Rn!! \&^#"&$%b''V)V,p,,V/1/D/1P4R3V4N6P375R6X76\9:XZAT@;V@X@ZA>@AT??P>=F>?J@;P=j;6X9X9J<:;\97d=N;V?T@RA>T>B^DBRERFVFERGGTINHHPGTIKFPJKKXKHNPOPPOPPSfPZPHQQRR`RPPVQNOLPMHdHZIDXJGJTHKIKZIKGIGFGCFRDPCCdDAJFVBDCNFdHNKHILK`IJLJbKOQRPRTMVQ^M^MKMJ`FHJJIIVMGXJMNODO\OKRKNKFM`KZKJNLJQZNJONXQVSXMXPP`KXMLhNRLZNJLJJJXJJJJ^HIPJ`NRH`JJJJNNJLIMLLZKLNOONZQOZN^NLNNXPMPRNRNFMKIZKPKZJVITHFFHZEFNGEEPEDCTC^GGNFVHVH^HPHVOXMPNRZQTPZNPTPMZLKNNMTN\NZORM\PNMLOZLRM^LKNMROTQ`O^POQZQRRNRNQMLVK^IGGGHGDZE^DLJ\FJGPGLEEF^DD`GVCBBJD`CB\DXDdEBATEEETDFGJEfHFTIhDTE@^BV@R=^>>D:\>L>BX@VBAbBXBXDLDGEHE\KF\ECTEC^CAJ?T@b@?@@^=V@VB^=A>L>\>N>X;Z<=9R=:J=>P>?Z=?T>\;hAR>=P=TAPAT@XC^ECBTDF^GBTHDCVEHLH\GFHJI`JMKHNXNLPdPbO^MTNVNTONPZMQMNOKPM\N`NKGJLIEB@>JC\@>@?N>R?;<;;=F<;P?d<d;V=>A=>L?\CABREELDCLIXGL\FVJZLNLK@L`MILORMNOPPORMMMKNJhNGRGE\FJC\DFHBXE@@P=>T<;^P9>Z?9;:b6N99;X;N8f87V9P888L6X56T56\53R6T6411Z0V/2P.`-P--**R)X+*\)*(&T'H&'f$H$`$P%"X"b#""b!P N \FbNXJPJJZ^`NV`RZJX> DT f V V V N ^ R RN` R\NT^N^TDPR^PPRRRZZXTVN*HV\LXPXXL\b\^bVbPTdbJ^VV\NLPXHPZX\^^VZZXdbX\RPZZ`LT\h\RRVbTPZ^X\T\NX\VXX`VHb`\R\VZ\bRVXbTdZZDP^Bb\V`XVNbPdZV\dV^jXd\dfZRf`^V\HN`Xbd`R^R`^FdZZ^`VfXZR\NZ`V`NdRXHdX^NX^\bZ\T`TZdTH\^ZhdVN`RblTVPTXbVX\NXNdXR:jj^^TZZHTRRbJfXfVN^VVX^XTblT^LXb^R`VR^XTX\bT^XDXlTXPbVBZVRNRb\PPRTRP \ ` T P X Z X V`R`FJ^VXXL^VN\JZHZ^ LN!"^!P#X"%N$Z'$&^,^++Z-,L..Z23T334\43V6R4V8^8N8V;8;X;d==V>b?X>X=VP?`CA?>R?XBABX@`BNC\=T@^=R<;X;8:\;P;R;9:N==d@ANA`AVADDDLIGFLGNHHIXKHKHBIVHRLMJVLNOMOQXShRbTNUPTbT\RQPSQPPXK^IPHGVEJIDKXJLLPOLIIFJ`GDTGDFREBAA@XDCDfDGIXHJN^LONOLKIRKXNPMPTPXPVOTLKOOXKTJKVJRKLRJIL^MLVM\OHONHJKXJI^KHNPL`NLMfLJNMOTNPORNOVSdNZML`JbJMRNKLMJTLHIRMJJILTJ\NMMJNbKJMZNVRXQPFPNZLLHMNLXNMMMKLMTLVLJKHJJVFDH^FPHIZGGTFZEDITEZEDGIJRJPK`OTNPRPVPTPSPROJRPRPVR`NKMbMZLJOOMXIbKNK`KTIKKOONNRRRPO^PKLLIJLbGHRH\I\K`GdFEXFHdFKRFGZGC@EEZB\EREZCCGHFBECA@DbDFZEZFIILGFZIHPELDAL?\AB=>?:Z;T8h:^:9X89V9:N9989Z;X::::H=:N<:=TA@TA`CAV@P>>\H;;N<;:`ARBPCREDTDdGFGL`MHKITIHFPLKNMJKJTIZGTHGGLEJJEEZCEXDVEB^?NB>Z?LAAXBfEhBBbFFG\DVJDEXFEFDZCRGJZHRHJDJIILP\NVON^MPhNTNfMZNRNN^RLMbPJKHGFFGDB@AAV>BdB^><<`=V?V?=`>L=>P?AAA\C^GGVHhHRHKVNXQRL^ONPXNNONSPlO^NNMLKMJJOZLRJR=\<>:P:T::9=Z<9:?b<=^;N=N:b8X:L823310H00N.0,0L-^-/F,f..+0/R/.X,.,`30F2`3N2T24B;73`3R3d353J3X5L34578;999:<^=:;R:\?<;hL=N\;=Z<=P=>CX@fDTCTH^@CEGZKEGHGFDGED\GFHIPKKZINMKKJVHIFBIDFDEdFDVFAC\=>Z@?N?@?TB>RBL@N@RA:=L?T=L>T;V=VP9?dAL?@@DPECTGGXJbGELIIIIKIKZLIJQNbPNOQVQVVWVSThRTRRXPR^QPQOJ^IJHGbFPJRKILVMKINNKFZKLFGETE^DTDZCG^BRDDGD\IFFJJKHN^PDLTJJOZMOVPO\RRPMKZLNKLKLJTGTHnOXKMOMRO\O`OZLJJ`KLKRMXMTLLLMLTQOPPP^RRdRLRMNOVPMLRNTNNTN^ONLJVKKJKKVMMNLMXMKKVPKLTROQjPOII^LZOVNTQQdOZNMLMNJ`KI\LRGXF\FHbHXGdFVDGLEGbENH^FDbEGFVITLXKNMMOVPT^RWUQQSRPPN`MPNLKJKZK^ILHF^HEJH^JJFKfNFOjP`NQMNTQKbJPIINKZNGZJLG\IPLRIJ\IKGZFREVE@DZFLFZCGC^GFDHFXECRGED\DGILLZJZHGTF^G\GFRBVCT?A@P?:Z?=;P<>>==\=:^:<:R:P:><@=X@=ABCDJHGTFEHJRITMGGZJIKIJK\KRHZJ`HKGHHE\FGVHCBD^AB`?L?J@BCbC^B\DCJECBECNGDCCD`FXE\EVHGJTLKJIHfMKJJMONMRO\ORQOO\ONJNNVJHGCDPBXCB@F>ZAX>;=;Z=P=A^BR?=Z>?@XABGZCHTIPH^IJhMKZPXLOLNPUXQO\ONRNXUVNPMTLVLJVLJHNIGbEF\GPFKF\CR@@?=>L=N<>V=L>R;;;\?b;\;P;:b;b:R:;P9;N>>ZBDTEND\FTDXJLTKTJRJMKNVKIRMQDPJVLOdOKNLbJIdHHNGJhHNEVJG\DXACVAT?@D?V:9R8R;^9Z95Z64R2D112/0^.Z0V1.^/2.X1T-..-.`.N-,02L1`1P1146<632T324T3V58L5456T:^99Z;<:R:J?9d:b;R:<<<>bTTZf^TVN DT!"#! "Z%P&%R()'+Z+b/Z/N00R3Z455T457\:\7T896f88;V==T<>@b>=>@H;\;T=\@<^>VL>P>Z??VACDBGFCF`GTGXCFbHCZFG^JVHITJHHHINKdLNKHGGLJXHZFFBZEABAV@>PAX?D?VCBBBLBP@>>?>?\BV@VEDVEXFLIIIH^JJJLfKNLH^J^LNKKNNP\NPTWXUbUNZQSTPRTJPNQVVRjOKGGE\GXIIIZM\KFMNLfK\JJMLZFC`GLCDdDNDXCA\CDHEJHVJIJLPTMPLNVQOVS\TOPQVQN\LLTM\N^LVIZM^JLMPL^K`KMMTPbN\OM`MKVKdKJKNPK\KLTQONOORZPSZRQPNPPNPL^PNMVPPM`NNJVIJTMVI^LMKZLRPhPM^ONNJQZQRXPfPMOTNTKRLMNQOJRJNL`PbKJGFLGI^ERFFVDDIJIEVH^HFGXE`DD^HNGJLJJ^PPOXOZRTRXdUSVWJS\SRXPPNQNVKTLI^GZHbHNFDGPFIDNGjIRKMJNNLKOMfMHJXMIXGKI\JJJM^I^JGZMXJXHHTHZGVDJDDDLIELFVGRFFXHGG\FLIRFDFGLTIK`JFILJjEBBC?VA=X?<<;T=;R=V:\<<=:b=V;R:99P9;X9\<=b>B@?TABBXFCbHTENHGFHI0JVHCGITJLLMNLJTHDRI\HGJHbIGFPHRFFCL?XA?\?@^BCVFZEC\EZGnDB^CCFCB^D`DRFDIE\I\KPMJPLJIJMKN^NRN`RbPPLQJUROOPMO`SPSRQTNMM^N\PPONMNLVKVJJRKVI^LXEIERHEBCVCXB=@P?=>=<:;=CCPBLECCPFJXHNKLVKM\KLMLXQPQQNPMZM\MRNJNLNH\GGFHXJJjIIIHDGRCN@Z@\>J;:V9;X4T4X4Z6F;9Z868=R:;;\:8:`;J=J<=`>;<;\9:`XXTNXZ^`TV`XZ\V\NRRP`^DZbLFbT\RNRVZdbZNVTVPnZL^XRRVLXXPVLNdZXRhJ^J^PVdPZT\V^T\^ZXlXXZLVXVV^^``d\PldH^RN`Z^`X`XT`ZX`ZNNjRVNT\\Z<TbbZ\T^RTV`VXjVH`NbV`^bTZRPPR\LbJPZXpTTZVP\Zd^^`Zb^ZNZTXT^PJJXZZdTTVfPDVd\\^LLTfDR^VX^NbZPd<\ZX`VHTXJbZ^XVVPV \ X d P T V \ \ V VNbXFRVJnTXVV\`^ZV! b X""#%&%P(Z'+T,`,P-1T1T1`6435853X6`7P:8`67`999?;T=j;X9;X<>Z9\:8d:>V:\76T8674L3R32B21\2V41`12V.-J,\-,+*)'(T+**,,+.Z,Z.,-/1X4Z2P4J4n9N56h36`989L;T?=V?`?Z>@BZBREGTEREFXGD\GTGGVGXJGGTIJ\JVHLII\FGPJNLPMG^HVIFHXGGTHHVEZGPFLBPEBRA@VAX@?TAHA@dBZB?RC=T?^>P<<>P>Z=;fX?@VD@NC^BVFKKZHGH^I^LJROXK`LFJIRMM^OO\PPVUPXWZV`VVSPWQTJTQRTQ^QNKMRGEVIKLIMKKdLLILGNKTFGEGXFJCVEDTDHF^EVC\FFF\EIKLO^NPRNNRPPSPRNQFQTdOXNXJGJTJ`MFIVLLJKXMQNNVSZMKITM^JbMLZMhMRMQNNJSRUQOQOPRpOOOOFQOQNSNQTOXPXKJKXM^HMKJMZRVSQRQZOZNROLRRRTQRTPOKMnMNTQTVPQLNNMKINO\JhKF\FHGGPDEPEbIGGJ\DFbDFEF`IIJTGJIRKXNbOS`VJTbTQQ`RNU\SRORQRVLVKE\HXDEZE\DFGEGIGbJJ`KM\KTKOLMRKHII^JhKH\KLPJZJRJFIJZOTIXH`DFBCTCFVCVEXF^ENGIJHZINJHCJIINJVKVKLJ^IHJFEHdGTD\@J?NBX><=@T;`;:R9J:9^:>8<:V9Z;:L97X:P9L:b9Z9:d:9JCBJERJEZEBEABTBZAA:B\GXBCBPCBD?A@D>C?AT=R@Z==F=>?:;P=T>@@=;`;7;X5P9T;Z=<@@AA^CH@NDFPFGTJIXG\IjHHVGPJRJJRKNJJXKJKHTIG^JEREGTIDDDNCNC?BR?Z@BZECD\DTFZDECXFFDTCXCRBHXDDVEECXJXIHI\MXHKJTJLNXSQRRP^RSUPRNNbLVM\HXEGFFVC^AP?B?@`BLBZ>@ATCVB\A\@dBZBBBhIFJXMJJJJILPMNMXNMbLNHPOFQTQ^NXRPQRONOL^OVOTNLKBJMPIXIZH`EEF\DVCL@d@R?HAJ@X>V=V=R=;L<:;\;9X<:R;>98;T<;;f====B\@L>?P?XEFDCVHDEPKXKLRKITMOKO@NHMORRQPJNL\MRNXOJJHJLVJJZJIHDfFTEZE`D\Ad?=X;`<=:Z<84@5V3X10N30J1.`.`1X/P1/X0/N0b101T0Z0R30b0`00Z1V4343R54:5N75H2X76545857^7Z6L6X68X<:b9Z<><@?^<`?;L9:>>V=R>J=j=;:T:\=N>:X=:P98b9L:7b:6X8R50\11T62311000P.P-R-+*(X(T,X+)\**))V,+.\0Z-\-X0X1R12d24564T76^;L:;`=L;\?@^@?B=V>@<@=<:V=^A>==R@?^>AJGBXBEXEDTGRGVJLKbLdJHRHHJMGPKXMOPVSRNSTU^Z:SUVVWWPSTRTSbRQZOfNK`KdI^L\KJJhJRI^I^JbJPHIZNTFHFXFEFRDXDDCTEXHNF\EPEZHHPJINMK\PZSNT`PFPSdMRSVTbRLSPQXVRLKdKLOXM\KNJ`KILJMRNLVMbQVNNMLJPNMPLOO\S\NPLXQPPRHSQQTQVVQ\QPRPFROLRTOPTdPOXPLVQJVKTIXKKKNMPZSODRPPS\MOBOPQZKRPVNPOONNVLMTLNNRKPHHITF^GRHZJRFXGFEFHjHfIVGNFDFHGPKbJTHhKK^LNVOPRQRSTVVVPR\TVSROMRPPFFFE^DZDACG\EDZGRG^HFIVIRKHbJI\GRJXLGII\JI\JIJVHFRKPIKDILKFDVDFDBHEEJEbJDHfGFFGPKIFGINKHZLMFKHLVHIXHTDbCA@>Db@N=d<<<;=Z=:=TT=`fP@J:X:R;<;L<`<;P:d<;968BZ?V?^AN?f@AGPGEGTGFHZN\PJLMLMfLRM\OMP^NTMJSP`OXLMXJNNLRMVKNKfK^LbLIVIJJ\FNHEPEZEC>>X=;=Z:X9Z7^6V6T4P2^0`25Z0j/-^/T312X1/V/R0d2Z/Z0-\02Z0V4B5T3\1d3P53^8R457V4`6P5R554456:J8577:769;P=X=AR?Z>?;=:=d::89>H>9X;9R=Z;V8P87R::888b775V4X5T6`3`2V3T0V2//T-X.@0+/T+*b*\)(\&Z)&&&'T'#$Z$"V%$V NFn PVTNNNJRTPbTPTNTRPLZ H L b X H \ R P X H ZVVbZZ^LRNVbZXVZ^N^VRTNbVdPXVfP^^^NFbPZNfVXTdP^XljTNNdfTRZ\RPbXh\XZVZhXX\RHVRRJ`JZfT`TN^VVD\VjjR\TNRHPHZR^RT^XXXTF`JXV^NbVbRH\ZPH\PZRdrRfZbf^`Tf^\^PVPTH`ZVZhV\\\XRZZdf\jN^^P`Xd^Zb\V^jVXV\PJTPlZR\XLVRZZVVbV^TXVNPXVPZ`VTnTXVX^XX`PbVPbLXXdfTZRd`bXZ@THbX`^NVlHZRXXVDZPZZXJ\R^\PPX`HZTJ^LTFV` H Z Z Z V R \ ^ N^D\HVbXRXR\PVRVZRF  P!R##$&T&\(P(**^-R/\.X5013X365V7585X:V66T6d88V::::N=T>:?==>@:8:<9Z:?T=R>V=P>ANC>VBCCDXE?BRDHHJINHJXKNIRJJIGHPIZLRSRBQXR^TTXYXYX^FXfS@RRSBPRNQdTTMMVLRIKHPJVMJNPIMIRGTFPGG\FRDZDFDEBRFdCEEDFFGKLLXLKOZOTVTRSXRRRRSPU^SRQPLJ^I^LKNLPK`MLMBOZN^NNQMJNKNLNNPLNbLP>ONTZQhV^TQPRTULSRSTPNTP\QTPPOLPL\L>MLXJJRLORNQPOSBORO>RRTSXPPTNPMVMFOPNFMKITLJMNKVKITITK\H^IGHEEDFIZLLMZJGJHPIKZLPL^KIJKJKRNMNTTSS\RRPZQRPQDQVNPRLRHIPFDDVFE^EVG@C\BHD\FPJHRI\IIPJGGIHJHHHG`HGLHJKKXIXJHXIPHCJACDFEJGGFHXFFHZIJL\LJJIK^LTJRMIIFZHDRA>A@?b?T=NBZ>=P>^;9:9:;8;T8;8`97V8Z7\99:=<^>TA?BRCXBCTCBTABRAR@NC?CPFBCRCRCPDC\CPBBA@RBB`AT>V?PA>Z=>?AN>TAP>\AA>?;:T8b;;::^Z>XC@^B@LAXADBZERGLFHFVGIKZNM^OKIK\JKKKKIKHHIHD^CDXFFTDH@B\ANC@V@^B@DDDAVCCADCZDEZEZHZHTEJHbFHDKML^JRLTLLMOPRSTZRQZUSOPRLNJKHHNHDVEDEPFVCH?CdAA??PARCTDLAB\DEfCFJKILLdJXIVKZNJbOJ\NVMPNZO^NJRNVRKOPMZPPNQVMROXKTJIfLLVGDIGRFFPCAXAP?^?P@LAT@A<9\;::N=d:88T:;>N>V?^AZECCZEVEDIhFBKKNMK`K^OKMO^QN`NLO`MLLRLT^OLNIHJ^LZMLZMVIHI^CZDCB?AP>T=^=;;T:D95\2J12T2^1T0.00F04R0R32\10X1Z01X1T2T2T2F3f3525233R583b4X49Z75P64Z5T6Z:P8X78T66X6>R8DT9:T7X;;7Z<53^845543L2X1P3T0Z31^2./f1d+L-b)f-*X('^)T)X(%%T%X(#Z!%T!N"NV!R N<TXJTTVXTXXT\XNTT \ H T V V \ \ B ` T T P PV N\fR\fFbZV`^NXLRPZPf`dTXVbf^Rd^Z@T`RLHJXX\\TPdX\RPTXR^\VX\dNXRJXFZdN`Rb\N^^^\VdZZNXXR\R^\RXfVZTZXT\\ZP\R`PVR`hRJNTbPhPTZbZ^RBZVXVZflTbVXbR`^^h^Rf\^nZ\ThhVHVZ\b`R>ddNNP^hZT`Z^d\b\TL^PdNXZZXX`ZV\\BNVP`ZldXXbPTFXR\VX\\TZX^RTR\V\Zd^TZX`\^Td^Z\bfV\fZLbPXL^T^RlbTPVJVNR^XTT\R^V`bVLbRD`ZRX R RP R X T h T J XZZFV^T^`L`RXLZVTXX\PRX\JL TH V !h$#&$N&(\*N**L,0L0N21Z0Z43d665V5^6^6F6b79\9T:b9:9<>T<\==?>>>=;@X=NRA=AAE`HDEJTIRKJ\OLFJJJM`LVJHLhKVIFHKVQKHdHJHTJJNM^KGFGG\IJDTGVDA`CPAB@?@@>P?XDBT>R=@<@BV@Z?^@>bA@XBdBNEGGHIBHFIKJXJHK`LMKVLVNXKbLPMLRRQVJRUVTUVX[YTTRUQRNUXTNOQON^OVMTKTIKLJJXLJGNVIHEFGGHFDEZCE^ENFHJFDhIHHKJJLPRNfOLR^UNT^SRVRYRZSVQRRVR`OLO\LK`KLLKXNXMKjJNLMRQOPLTMVMXLVNMTNNMPVOTRQQSbVSBSUfSTVUU\WTQVSDTZTSPQPVQPKMNNJ`NJJPQNdRTOO\NM>POMnPNdKSMNQQO`JJM\KLdJJGLJdJJHNKJZHGXJGHI^KM`LZJJLL\OdMJ^NOMfKKZKMNPR^QRN\QbPPXNFOTOZOPMXHIEF\B\HACHBVDTCPGbEHPKGPHPIHFZI^KNJJOdMVK^HIbKJIGI`HXHZHGIVHTDJCETE^GEPK`GH\HFGRHK^IJPJdJXM\HRJJNHJPJHHFCAhC=>B>P@?>X?A==X?V>V>>\@;P<8D9\9\;9V;\:V6:779:::H=R=@T@NBlCLBVCP@VA>?N@b??Z@NAXCPFVDD\CGEEEB`DCANA@N??@>@D@?^>?=>@@V@X;T=J=ZDC`E\JJ^IVG`HG\IHJJNOJPLdMMfPMNTMPM\RbONR`RRMBSXLPONNJHJ`MXLIJJG\DDVDTF\ACTAX?TB^?^?@>=<9d;;`?:<99X7777R9:\<=^@ZAD`CLCPFFHHHILNMN\OJPMbMM\NMLOOSOM^OKP`MLMJNMFNLXOJVHHEFCXFDNFBD@@TDV@\=^<86852<1H0X1\/\20X1N12T43b12000d3`16R533R3b331Z315X47R5N7J557646T7\77R8^7\587j;;9R;<;A>>Z:<>H88J9f9N8d;<\>ZC?J=:::R9=<:=>^:AB?bHRD@FDLE\HXHTNL\ITJNZM`LTMXMPMbJPKMLI^JVKRKNPJXGFGPJKRHJJ:HDFGXGTD^D??@TF`AA@X@X@>VB?@L@d@L?T???@d<>>@NCBLC\DDE`EFPFPDTJVLTKZJTKZN\KK^MPMMdMPMNPORWNPSRTT\UWR[XXWUTQTUQTRRSQRPM\KHKHHIHLVKRKRILGEZHEJDFETHPE\IVFZDFNELEGXFdGIJMJLNJMRSXS\VZQUV^VHTPRFTPQNMKIIJLNLN\LQMTMPLTQPNNNXL`PLdNLZJMbOPNNZQRQXQRTFRbSRNSNUVVZXTSRNTPO^QTQRNPRQPMNOMbJZLKRQTONMMNTSOPLSXOPROMLKNRNDNDLMKRLDJHRJHPHPI8IRIMJPKXGEPFTFTKMXK`LTLVLRPP\NJTHQOQPNZQNORQVNPPNNNMbPPJNM`OJE^CXEPEVDF\EDELCGGHKLPJK`LHJL`LPQRPI^NTPLLLTKG\IEXJGHFZFCBIHGTIIRLJ^LTIKI\JPJPLRLJJHLGNLIJXK^IG?bC=d?@N?DJBXANBBTB`A?b@>><^<=:;V;:99888V9:67Z77;`;<=\>T>@?B?RC?N@?>RBN?BA@ZEZBCZDDEFDdG@N?AAAZ?BRCB\CRE??P?`CLAB^A@T?V<=V;:<>;@>ZC@VBVCACR@BBN@RCCXEGVJKJHLVKKJXKZIJVLRLhMOPIHTKFGfFXDCNFXDEXDBHECATD@@A\CRDRC?@RAPCCRDAHHGRMjI^ILIKlMdNNLKRKTRXQPQTRUHWLVZQTQTOOQKVLJKVLKNHFHEFRGLECPDDZFBFECN@`ARAD`DH^KHHNGdG\GJNXMTL^MPMVOhPOLLNObPONVOMLTQMMfNMLMdIZHHKNNdHEDEdEXCBRC\A@N=@P?T:;F;677889:<<>?bAT@FbCFEGGI?:86Z7X626730R1R44N2V3253X0N10b2016Z54Z4P45\84^33X645X44N44;T<6N7J65Z;Z6T87\7P7N9Z7V:Z

X>=?X=;j<^\?>=>V;L;9P:^9J:988;:T8V8L78d6`7\5V5\23n2V3^51`2R3F02/R,j,+R,)`,)(((L(N&'$`%#R#\"d!"T##"VP\NRVTRbTZTPRdPL N R L R Z J \RHZPbRdPLPb^V^\PP^`TLRX^VNfPT\VX^N\RXfTPVXfZb^X\XbH\XNNT^RZdTV`P\^T`^XNDTdTTZZTTZX^TbPNPVPfXRf\LRT\T\Rd\VJZRHTXj\FLRXVNJ^NVPNRLPdbdj\f\^VTZN\\VdbZN`^jTR\VZf^Zf`RZ^\ZPblVNT`VVX\ZXVZVdNb^`fJXN\LRX^ZZZN^Z^^X`HTZJZVR^VPX\@XTbbX\\VX`bTNTNHXZ^VVPTL`j\RXPRPX^RXbFJ`d^PXd@PTTNlV`JDZZdRNVRT Z  V T X V P X Z \RVbNZPdbNdTbT`VTVXZ T"!#T"""d%Z%&^*V*,\+-`-R/R40323Z34^7786<:<;b;^A===`=TB?<>>P:VCj<`;8Z7V:H7P974Z5364b7\4^2D5X5X0/.b./--X,),,-V.^+\*L+*N++-2b00D.b1^3X0X0f2T6T8b98N:X:f9:\99>^:>T=J>?VABTHBVH^DRCFZJXLJLbKXJNQLXJ\JZKPOJXMMNOFZNMJFXJGNJJZKI^JGJHGVFDZGDD@ETDREXANBZAB\ANDXB`BZ><\BP?C??RBAPAAVBCDXFHHGbJVGPJ\KROLLTJ^LNKJFMORZNLOMXRVUTSZTZUXUXZWUTWQTRNURTUWRONVPJVLNLGXLKK`KZLLLXFG`EVJDVGDFENDXELHFEPEIH\KH^JL\I^LhOJNTPTJTRVRZZWULQbPQXQNZMLLOVJHbJJJNPbONZNNO`MRNZO\LNZOVQLKROQRZRNWTPTUTVSLVXX\SSVRSXTP\PSZSPTSNNTPVLN^L`NNPKQJTMOVMPPXRP^TVRbO\PKKTQVKNMXPRONNNLLHMXIHKKVIL^JZLJIZJLLKMXQbKZINPNQVZXUVQROOQ\RORP\MO^MNNZNPOjRFSJMNPKJHK\ETIfCNGFJEDREKVIM^MNONILXNMJLRONOVPTSNTNLPXMRNPLKJFHVEFGFEEHFNKJMNLRN^M^LKLO^MPOKPMRKJIHHIJTGfFERB@>bAL>@@NBANBX@?^?@X?V=V>\;JAP>L>T?>>?V>HB@@@?RCBCNCBTDD`FDEG`FND4A?XB??BANDBCGDDDPDN@>^AVAB@?Z;D<=P;?;\>A\APDJAV?XB^ABVAC\DEEbH\HKJIKLKGITJJKVLZNRMVLHKTLdJ^KG\GPJFDCETE\GDENDCBVEA\@ACVB\AA?A@EI`GLIKLNL\JVL8K\OJLMJJXNNPRbRXVRUVUNSS\PXSPM`OHPPLTMMHH\IJHHXEdB@BLAPBT?Z@Z?\ETAIfFHXHHZHIIK^NL\OKMJJQdSKZMML\MdR^OZSMPNJPKVQLPPJMZGJKjJRMJEERCVFCDA`A\C?DZCTAA;;=<:>N;89R;:8;89N:L:?=?V=ZA^@BNHCDLDRFdGHJJZNJHL^JNMKXOPMFNhQZN4RVMMPXNPMN\NOMXMXMLROLPFJEFDZFF^F`DAE=\>h=\=8R9444T2`4J2X1/1X2R3V4b1^00b12b123f4364P754X553`32Z3773Z4475f8h7H8974X8^6ZV9d>;;Z=N<<>T=>V??<=P>X@;V?Z=D=R<`;8;<9>J=V>;86R77\:\6547P594L3T6X1\4R02\/00..F+-R,X.,-P+Z-+P.,,.-J1-X0V0Z1Z0Z4T34b7R;X8:H8P:R;:P;;V=;P>V?V@BCjCFBXE@HCFJGJ^N^MXM^JFLN\ILNHLKTLRNNMLMG^MKLLNITKIZLMLNJGNHEXGPIFTEDPDLDENDZCbBLBXA??BFCf@:T@=\BV?A?NDTA^DCHLG\FLFGhGHFETGJ\NfOLITMOOLPSPRPZQRRTWVTXhVRVV\]TNVTXSVQ\UPXQ^MXOTNJGII\IXJHIKGRHJEHGGJIVDDCPEFLEXFDRHbFIJGJKHPDMPRPdVRTZUVPSPPOXOTNJQRRZNPNNN^LTKZNVQOPHRNPPQSXNO^O\MNMLVPOTPOTPNSFXVSVUZTVWTRURVXUXSSRQ\RPNODMNQTNNNPOMhKKPNL^MJZQQNPFPOPSSVNOXNVMKKhPDOPPMPKKZQZLGGbGDJHXJHXMXLLKKIVGMRKZLJPOZQPNQTHT`UNSNTPSlUdQZOQLXR\KPOFLNNNMOOTP^NQMRLZJTJGZG\IKHILJMFOLbMOMPKKMMOQOOXSOLONLNLRJZHIERG^FZGFFVFLEbIIJQbNLXORNKPKOKJPMKMLLM@ITLTIHJNIJFC`BZAPABV?@JC\ATDPBCDAV?bAB?N>P<<dB?\>R;==>AXALA@ABNAHDBCBD^C8FIFG\JHJIJbIfIRJKMDMQVMMTMMHPKHGTEI\DNINFDELGTHF`DECCZA?AER@ZAAAERHFTIOIZJdKMMNNXKPKLJQIVRPHPJQUTPVWXNQbQPRZR`NLQNVP\KKHLJNGZFCDDPBVD?B@VCDDGHFXJZIHILIJVLONbNdMdLMZMMJNVMM\LRNSOPQMRONTO\RNXOKRKLHVJRGKKPIFZFRIXDTCBDA^AR@@@?Z>J?^<\:L989777Z:R7J<9==<<877Z6464X43R0^341Z3214P2b4P1P3235N4\785R62>322P5945Z7R75T967:8R8767Z;T9:VAh>X;=<:T99N9T899:X;:J9^8V6X9762336T5f3X3N414-.R**b)X,(*l(V+)Z'X(&T%^$"#$#L "h"`!^!Z NZBVR`h^hZVPLV VTV L Z  h X Z X V R L RXbTVbVVT\TNXN`\Z^fXLVNZ\\RHb`RXRPHV\hTNLTNVZ`L^R\T`X\VVZRlPZV^ffLT^`D^fVfVR`dJZRTjLX\XN^\LRXR`\^ZVhZ\ZPjPJ^TXFR\VJXHJXf\NRbfXTjX\d\XdbRdVTZT\TXPZ\TP^LXb\f\`ZRZHVnZPZPP`jVFT`RVX\fNNbdRPP``ZnbZ^\VT^^h`XX^ZV\ZXZRXd\bbN\V`dNbVHX`T\ZJVZ`bZZ^ZDdRRTRRZJfTblZHV^dXL`VLjVRNFJX^TLTR\fZ ZZdZ P N V V R ^ X ` \ J ^Z^F`ZRXZ`\V`\JV^X\ X" R#b!d"!T%\$$(`(R+*V*Z.`/N//P.1X/V313T6P77d;R8`8\8888h8X:V9:V:9b<=Z?@?T@<`;b;V;;TT>7P6Z86T66355d4L3H30^1V10^0P2`2T0P.00V0R-H-,V/R-`*)+R02+,/V.\/..X046L636757b9T<9`;T<=Z@`BH?WXTTPUPUUdS\SlPOVQONHPMJL\LVKTNMNPPTLTOQSXUPQQNPLNMVKTMP\MJHLMJTJIZFGFIJ\OhOLMRJILH\LKRQLPPNQS^SRUWJSXTP^RZPSLNRONMRRPVPPLPTRONOMPMVNLZMTMLI^KM\NNNQQP`PdNLOJBObMMNOZSRbQTNMM\NKHEPED`DZFXGTIFEHGHJbMNLLLZLLNRMLMPNIjLJNL\IJhI\I^JLHNIVDZCAAA@VDCA@BNCECAA>@V@<>^?>>\ABAPBRE\FPDVF>F`HVJHHPHRLGdHLJLlLRP`PbML`JJIVLJIFFXFFJIDHIREZEEFDRChD@AZE\BBBDVDZERFZIIXLLXMLOOKL\MXONL`MTOQDSURZVXNZLTTQ`R^QPNNNHNLTRXKMJGEI\GCZAABCVGbFRD\GIGDEIGJFFbLNNJIOMNTLMbMQNPPVQhLOKO`O`POPNdK\P^KNLGJJZLKJIDPHGBZEZDBXC`DXDB@?@V?=b<=<\=;V99|888Z9V;R8P;XACBE\E^BF\FHH\JTLZJLLJ^JMXNLMTMdPOLQLbPbOTRLNR^QLFL\KPVOXK\JXKLJPFXHL\JbGHHC@@RDP>^Z?R==R==V8T7R98V;9>8:H7V7R7\7P52f5V44V7T2Z626V55/-,R*)\+(`*D)*Z(`)L&%^%"R$X"X#"h!V#p hHD`P`N^ T Z b Z f RbXdP^RVZ\`Z\NHRbPZbdPHTVZH^P\RXTVVbR`J`^\^RTP^TZ^PdfbPN\XfLVRV\b`f^ZVZZ^VL\XXZF`^`XX`PNRJbZZLfXNfFRZTRLZbhH`RZdnJPXfXDXLHRRbT^hVZXZVZ^XXb`bX`PVZfhbT\XV`bXPZR`ZVVR`VP^VTB\NVT`bRXZZPZH^ZP^PbRV\^V\TP`LfL`NXR`RNRN``R^NZbRbRZ^VVVJ^H^N`VVN^fJZTZdVR\`NRfDThJNX^`TLdRbVN`ZdT^\JNZLbVT \ V T T P N   \RPZ\XVLNH`VTN^PZ!\ !\ !""N&"%(V))N+*+d.>/,^2Z3\4Z2V/2\4J9\7X7`6977T9V97b9`=V=V===>?>>T>V=>:=>?N><\<=Z>H;\;:H8;6966`6F32Z4^10040P2\3P-b2V.L-Z.P-Z-,X0H-.P-^.J.+/P1R./.J3Z3V0f24H7456T8T:T8b:8L;R?R>>?Z?==T?BC\EnDNGITIhHXHJKXLOMKNNMKVKL\ON`MFMNNJLOZLEJVHI\JXI^OdKFPIHDHTHJPE^EZEDBjFED?RA?HC^AJ>bAAT=\ARA?@VBBVFChKHdJFIIdHZLJTKNKXJNL\OKHTLSQOZUhTJSXSSZTWVX^UTUXVVTWRRPZQOZPLLTKIPHFFIGJGLE`LTIGZFXFGRGGEFhEDGXGGIVHJRH\KORRSZRPWRT`TSSSSRVSNRQQOLPPTN`SMOMORMR6TRRNOPRPOPRVNNRROZQZOZTPRVUZV^WXLZFZTXXZPZ[W`VXXVfVXSNNML^NJMRPMOPNLORPP^ONNQ\SdRVQNQQPSSOONHJIM^NOMbMHXJZJJGRIHRNMNN\MLVKTOKMLNKKNRSOPdRTTSRUPTRVSOZO\PFMONOXMQOPPR`PSLOMOLOMZOZQTQPPVLVQNXUQ^TQTUVQPZPPKKLNNZLTMFNRPNQNOTKXJZIHFZDRGBH^HREXF^IGJIQbPKZOLMTQOTNQMZNXLHJ\KZLZKZKLNGJF\GFDDPALCXC^DEBRCDDCBCBB@??R>9:d;:98`;VR;T@\>>?XA@?`B>@>RCDTACVEBHZJNJdLNJIF\JGGRIJMNMPM^KZLXLNMTLQK\LTIHKZHXFFHHVGPFfFEZHDAAAD`APFBRD`EEGPIZK\LQLNbQDOXOPOZOZMKK\NVQZPPUTTXTNUZWXURRORVRPXNNRNNLIHFH^GHFLB@CTFRFHEFGXIVHFGITKTILMMbKMN^NMVNDOMNHSTRTQVRPZSRSRZPTNZPbORNXNMNdGXJIJKFFHDXGDVDXCVCAACA@\AL>>@AABGEFBGXJLhJF6LJRIITKPOXORMOKZMdKHLPNNFQNLNOMNLMLhK`L@N^LXGNKXHHEBC=L@dB=<7:P9L6`83Z7V45^4`35342`1H02R62R53N35R34`6F757453575H637Z6R4`8N58878:;R=>?>VB

T<;8:\:P;X=Z>T?B@>T>P==^=Z><\;;T<;`9\9b7R:P<b>^<>R>>;Z>R\=?@^>;J/2.P331D/.X0P1P1./.T0\0Z/.,X0^/\1^1.^.T/P1111155T3X5b7b9T;9;X;N:d??P@B=\>R>ZCFCGHG^MKLJPNNRKbMM`LM`N>OPXPJTMTL\OKfK@JbLHXIETEJHTLHJXGIETGJHHIDdE@BfCdJFC^@fCPCVC@CR?d?B`BbCPDABBhECDCFFXFGKK^HJ^JdLNLJL^NPLVNLO\SPNTPPRZQTYVXVRZVP\LWUTDSQNXOMK\MOROZLINJRHHlIIRHXLHRGFD^FDFFRGdHGLGEZIKINIK^L8LNNVRQ,QPURTbU\WXRVS\UJShPNXOPRQNONZQNLXOQSRVRbS^RDR^RdPNMZPRVOZRPVQVUbXUPVZd[W[Y\[ZX[TVVXUTOUOXPROMPNOPPOQSRSNJNNPTPQUNT\TSPRJNNNPMJJNKLLZJKKGIJMDMVQVMPOLNNdPbPZNTNRNMMMS^PZSPJRT`TSPPTPMN`NZPPZKVMJMZMXPMNS\QMZRRbPLNVOPSN\TZTVUSQNSNROVMDOL\MQbN\ORMNNOJMHKINFPI^I`EHFVJVIXHZIJ\M^MJPNLMSLQVOM^MVONJLMJJMRJKPKPJHGbICBLDbH^DDCGPETILHBEHCPGEVAA^ARA?T<^;T:V9@:98J97447V7R9R<9f:H:;T>;P=d>L?BARCTADBEDNJFD^HHJK^MGGJF\DBDPDEFGGEZHGTEPD`CXCNGDCDA??X==@TBdDZA@N?>N@LA\ATDBBRECEE\HHKfFGIJFFGIJZQP^QQPQLMXNRNMZNJKI\IKHGRINHGVGFENF\ER?hAAAhE\DDZDPFHFHIKLXMLJP^VN^P\PZQPVRPVPPTUTTUUV^TPOOTPP`NPdNfK^OLGIPIXHZHEDXEGE\GPJVFTHEEHKTHZKbJKLMNRNMLOVMOfLhOMXOTQ\R`RVRRR`STROPUNdN\NOfOLbLJHdLLLHTITKGXCFbDBdE\@@RAT@\?L=Z>>P=V==;j;X@=>PBA\ANDXFRD\GFNJdGJLKJKHZNLO`QNTQTPMLKTNMOPPPQLIJQO\Q\K^ITLIRJRNM\MdHDCRBVFR@=?R>V:b8V765V3V566T34\114^4b1P15L6`5J424^6P237N7\463T6V2336R73R8T886L6`9V;V9:N<:<<<<=V?=^;T;T=R=X<=L??N?bAP>?=?\>>=J=;<9;b;;<:b>P:8R7N6T53V45`4V5Z7N6\4V3b31R/R,*+T-).T(*(T(`(J(&V%V#`$V!"#"!#"J^TZXbTX\^PZbNZT P V T \ X R h \ ` Z h \VRLVXVVZHX\Z^N\VR\RXHLXdR\XdXPPT^`PLXd\`LV^TV^VTdJLZ`\VVbXTVZ\NTZ\TT\b^TZXf^PVRRRH\P\XZ^VLRZZTddNZVPhX\\R`P`ZXV\PTPTP`\FTH^XL\NbVXJF^LXZN`^TTZTRdZP`^j`^XXdTJjVJ`Ld^bL\fVLZXVXfTdTPV``dXb`VTTZ^`PZbXVV^^XZfJ^\VLRVT^L`XLZLBV`RHbTRX\XRTZL`dFbbPXF\\`dP\dTVPZV`PV^PLXVLDXR`VTXZRZPLdTXX`TZ\>VXNNLLPVbXTZT\bR\^RTP^DZ\fFN Z R Z R h Z X ^jP^PPZVTBdVXJ\bRJfZ!"R#"X""#$#%%X*(\,.+,,.01X142V6R5N4R5;P99N96X:V;::d:P:V=>>>==@>???<=\=>BV=;;=Z;:7R<78644V2\1.X5b/01////X0/\+l+`-N.R/1-.D-+,d--/p003043`5X67R7^8P8\:<^;<;V=\>J>=`?XA\ACVDBFCHKIHTKTJNNKOFQPQOQLVNLKLMIIIbHHGGTHRI`G`IFVGEPFJ^JfJJF\GXDBHLCdEIVB?V@@PB@?>L@>>CLBFRGNFXEPENGXGHHZKI^LJVLM\QVOKXNJNLbMPOSSTRPPTdUURXRZVTbZJUPW^VjSVRPQNKPZNHMdPJJIGRHILHIJHG^FJTIPKFVGXGFBFTHE\ETHJDHZK^KNVOMPORRUPRUPRTVSTRRSdSJPONROBQTPONJQN\NNbNNbQQNQOOhQZOOJQfNMTOOTQRUVUZRY[\WZZY[XYZURVWdYRTQPRM\NVN^NDN\MVNS`QVVPNOPSNPVQPTQ\TVUQVSP\MIK`LRKLTNVJKLJIL`LJLFORPNQNKMhO^ORQNSfNXQPNQQNOPXRVRRUNTTjUVPZOOZOVMBRXNHNPLMFOJLOOPO^NRLNRTLOLOSLSVT\UfUPVPW\UUPQDTSNPZL\KIPNKK\OVPTP`JDIRHPGJTFZFBKZJIFHHLlLTKZI>KILLLNPZLNNOLVN`LROQMPJTJKPITFLLFGHF`FDTDGHHGG\GDEXIGLFG^HVHRHCB\@A>H>;X;85f977J6L7R57b9J8V:::P;>>X<>>Z@^BRBBEXBBEBRDBJHGLGHLNGVFNEGDA^DXAGTEFFPGBCTGRFREFDZCB@f@>P@BZ=A^BDAZ@CT?@@T@@NA?BXCJEHXDHXJTJ\HJGRKTHNIRLTMPNQTPRPXN\OTMLdJLJXIEZGJIbIGIKGZI^EdFVFZDLEBGEECFXLZIIbLNLKX;:`V?:=^=<>==B\BBTDTDEGFHILXJMLKGHMPJMQLM\NXNXNPNNKN`RNZPMMVPLdKPKjLPIVKNLM^KHKVGTAAC@^@P;>R99T8775P6`465846X0N4V0\5T32;4Z6`3354P4^5T9N2X5R55f5V354\5^66::7\7X69Z;R:Z;X>;X<^DVA>>>?R;X;>L=H<\>>Z?N@V=VDLBd@?>R;`<H>=CV?`ADHD^GJFHEMTJNLKMMLTOhPZRJQ\PZOOLNPZNLfIKIbGLJHEGXKGKLGGdHbHHKfKFBI`BFDDPHPE^CADDDA@XAJG?>TARCEDD`EPHFCRIIHMZLLbMLPDOKK^LNO`LTQMRONOhV^WTTQUTfVWXYZU^[W\VQZSQOQTOOPVKTMQRMKPLNXHbHILKHFJFVGGJG\HNI@HVKGGHTGTHPNFJ\NNNRFMPPXSHPXSV\SVVbTTWSS\PbQPXMLPOPZRQjQNQ^NLOHTOZT^RLURXRLRONNNP^QTQVRPRUXXJYV[V\^XHY`VYVX[B\PVHYXXbTQROfQDNZMKNNQNQTS`RSPTSNQQdTRTPVSSRRPOKKHJKZLLRIPJLZNNMLPVQ\ONNNQPZTP\PQ\SNPXRfNLS\QTSXRULUU`SXShQPN^NMM\ONMLXPJMLNRMKTOR^MTR`QO^RQDUJUbWUWJY\WTRlQRPXMNKRIKVJ\IFKLRMIFFCTGTIRFNLIPJHJXJbHKIMKJZNbPPJKDKPPJITMfJMLFLZMJdKZHfGGJEFPF\FIG^GLHdGPGfGXMPH^LKPLGIFVDA@Ah>f=@<<;76^55X4Z5V5X7^9;<:=:T;>X>>=ZA`DVEVEABLDJJLRIHTMNO\MMXNZMLPZMNPMMbMdOdNOVRSRX^SLN^LPOJQVO^MLP\JNLRK^LVEIhF?X@^>=>V:<^<:V7P7^9`6J7R55425T43V21Z43X5d4`5L32\34\2J56T4T7567V75676`78Z997\<8V88T<>`>\<\<\?P:;J;;FV><`>X@P@D<<^AZ>N?;L>Z==R<\?=:T:R9V:X:X98P3h5`5J7X84b4^551R0X-+d+,n+T+L-X++P*)R&D'V&L%\&R%T#X&V"T" !V!V NFRVPNTVT\VPRZV ZP b ` ^` d \ b > T Z \N ZRX^fhJPT\^NfVVV>T^L`TfXZZLhTX\X\T^V`fVTTRXhb\TNRfFXZ^X`\X`fV`bZ`Z^^TJV^\^bNNP^^PTdJTVXXTTH\VT`TTXXPNd^PJRZ\JV\PdVVXPTXZXbZJ`VR\`Vf\fffD\bXrX`VRZbTHTfdPPXVbV^XR^^\TTV^VTZlTLXV^VV^V\`VZTV^^`ZbV@^\\ZTHNNblPXV^RNTJbXVbT\^^\^PTZTPXV^`RZN\ZRHRPT`Xh`XjTbVh`HZ`\Z\RX^^TVVZVNFVRT\`LTHh\ZR`VbVRFNX\PbX\bJV\HXT D b R V P V bTTZjN`TZRTNdRP\dJLN^\"N!##!%D&%$%T(+L*X(+L,//b-0.R3J2P5h47h76R6V757X<;8T<=9X=J<=d=>=CdBT>CX>A6A>Z@BL=@:9Z<6:<^;L::5T75b5T8V955L5L4/^1f0F10\0R/P20V0-Z.^1L/Z01X.N-\*,,X-F/X-1542J4677X6`:9J:Z>::;>>??b@^?ZADVDfFNFVJTHHNPMLMPQ`MPJPOSQVONPRLTNL^LKNbJJKHEFVFJEINGVHRJIHKbIZJKDGDRFVED@AADA@?ZCN>R@?VCAFRDDVILEHVHdLLI>KbMTJNMLLMPMZQLNQNNXRPR^WQLVT^UUjUXVVZVZVSbVZQfPRSOO^MIPJMOdNN\GHJJFRLPK\KRJJHGGGRGHdKLfJJL`ENHH^KHJDKTMLNM^QPQ^SXSRUVRUVDRTTTQRSQQNMM`PVL^RSTP^RVSLRNfPQRURR`RRQZR^ON^ONQQR\SRUUXTTVVVXXdZZH\FWRX\YZWLKJTLLTKIRKJHHVOVJJJN^IIHHHHZIPIHHZGdEGFFJG^GPGILK\OKJKNZKFD@T@>Z?b>V?\<==>J?@?ZBLCPECCG`FFFVFFFRDBAACNDDDEbD?LDFVHFIXGCC@@?>@?JAR@L@BRABXCX@RABANCDADBB^DCFKPJHIIHBKIZMTOOXRTPRTR`STOMJLKJTI`J`JIJMGbKHGITIEFC^FFHZHXILHVKNM^MFLbJLKMOQQRQTRN`QTQYURWJY`WWVQ^THOPZOObQXNRJOXOOXRGFHRITMIbKMLVMZKPIILGK^JTKRJIKZK`KOKSLL^MSZSRRTVSRTWFXX`VPVSZR^UTPTQTNLOPNPKVJKHGIERGFHEDGCZACZCV@ZAX>\@`=:P@;:N<;<;R>\@Z=X?T@BZDGBI\JKXJ\JTKPNNLHNPMLJOMLfNFNZNLNRMZPPPONJQfKLbOMVLOLKFOJPMZKIHPFBFX@R?VB@<\=;^88j8468545Z8N446^463V3^455T6432Z22X4F68`5L5455T68T487R4P787\7R7=8X;f:R:N=f>D<:Z=Z:=:@@>@?j=`:P>===RVA@\>=??L@>J><;9;Z:77L7X7Z634357b10R0X/./--T/V,J.,N+\**(`(P'$\$\$V" !#P"$b#! RZ`PZZXXNFV`\ZXF b \ J P H P ` T X T X h ` \T@VLVfTZT`XfR\Lb\db\LVJZZ`RVL\`LRLjBVXHLbJXbZZF^NZNddZZbV`PVNTZZT\`T\P`VVX^TRZR^\dXLf`fZTXTX`XDZZN\VbXXhXX`dd^LZZ^jTRRbVXVn`b^^hNfTVPXbHVPdTfPNVRNFhf^X`dZdXd`dbfLbXf`dZXT\\hlZ^\R\b^XPbP\^b`NbdV\ZPbXLPLN`\RZ\^ZHbXL`f`PVTZ`XXXV^V^\bVVTT^LhVXbLXTZVPV^R`^\@dL^RRRLZX\`ZZLRXH`PZRZfZLdj`XZPTN`TZRRFVdJVR^\FXJNV^fN^^XTV L F Z P Z h N \^RVTTZNbX\bnP^NLZXXT"!!N"`$h$P&T'X&%\('N,P+^+),V-P1\0.N3b32R354T41`56J>>V@A>>J?R?P<<;Z6T;T>=\BZBXCCFEZDGFIMMQ^NMPKNOORP\NMdODMNNXOXOVN^TJ^IVHDFG`H^GGTKbILHPJ`MKHJHPGEDGJGhIDDRC^FA@XFZ@@>ACEHIXGGNJKQMNNMMPNNL\O`NLPdPJSHShUVV@SWTVWXTVZY\YLVUUSPRNPROMLPJ`HHKjKNOKVLTH^KVHIJLHVLbJVGJIZIPKI`HTFHH`KTJJ^JOORPLS\PZS^RdWSUUQRRNT^TVUTSVTZPNXNNPBRS\T\TQO^UPSdWFTRZSRNPPbPXOMRPPX^TRXUJVVUXVZWZTWZWX[`VWWWJUJW`VPS\QRXOVLPONNM\SUPTQSRQP`T\TVTP\SXO^TVQQO\OROMJJMLKIKLJNLMP^SPTTZNDUDQdSVXUTRT`R@TWRWRTURSQNSSSV`QRdTSPOPNFNMQPP`NFMORPPMhNFOSRRRPPRTPZTVTPTdSJTQ\RNONPMMJTKHJ^FHNDVGNDPDXCF^CDPFVHVKbKXJRKRJMNIJRKHZLJXIdJKJbHEFHIIJIVGXKLIVGHMPKbLRHVHEEG^FELGGEIJ^MPOKVLXGFZCFAb>>=V=:PR>=L?@?`A?A\G?CPGDZDVGGGFVDERDCCECVD\F^CbEHPEXFJFGVEBC@TB`A^DZAfCVA^AT@XCNB@\CRDdF>XARBXBHCXBCHGFJI\LTJTKRLTNNMRQWNSRUSQTO\PKMJJMNNKI^HHFXJFbD^GHHGNLIVJIINIIJJ^OOTLOVSRQPXQLOXPTUVSXUXS\`UXVPUTSNOOQMPPDPNUZP^MQ^LXNKFJHHJnLVMTL\MJLHRKRFTFXJHGJVIKZIhLLL`NOMLOZPWSUSUTSZVWWUNTTUUTWZUWRZT`TMMLMhMNLJXGBF\KRFEFEABHE@DFAABb??^=b==:R=N>:?VAPDCLDPIHGLLJZKVLROMNLfMOPMKNMZPLPORPPLSNPODMPMRNNJLLLM\KKLJVNNMXJNCLENC?V??=>897T9Z;9X:X6D967R8J2`5V5X5V3R6T34X4`74f5231244R4T7V58Z974f64\5676:^;9V8`7:;;9`:;9Z8T;;;?=T?>?J@V=R>R<^>?>=?RAD>:H9^9J7X77j6H;574V4N512\21.---`1`-R---+*T))d(J'\)$T&#"N$$^$V"b"T !TfN`X<d\b\ZJT\R``` P X ` P ` ` L P V V XN ZLdN\FTP6VTRT\`^N\dTX\jZ\V\\PhZTBb\ZX`dZXPX\VZf`XXbLZZNPTRVfJ^XXXRNTXbZZ`HVbN\XP^`^R\VP\hN^V^\^Vd\TXZZVXZ\b`dXRX^P\TT\LZ`^`V^ZZVDTR^LTdTd``fZRXhffjVVF\\dl\V<\^TJPh\^^\NJVT`<Z\H`RV^dNRZRVNRdVNXdTXRXRVZPVfJFRZRTNZbZdV`HX\XXbTZLVNZlRTT\VNNZXRRT^^ZfbZPV\^\\fV^\JJPX2\XJRLRRDXb^N`NXLRHVVTbTTLZL`d TdJ ` Z P R XV BN <TTTHX\`\\PNH^J"P!d#H"!#N$$X&&')X*R)L(+*-,\..\0/1\4Z23J3T45V7P3N6T:V9;L:<=\<::^?P;;T:P:88^9:V8:75^:R5R2d66V34^3410B2/Z5^0/0/1-0N-\2D.3/-j,F-`--/\0033F5`56P4778879<=`;R<<<><@P>VA^CFEFRJJHGKXNNNZKMKHR`MM`PRKTNPLLMOMdP@NRLLNNJTIPGGNIXG`MPIZIHHFHTGPIJRKJLFHVIGXE`HFCEZCNBFAb@P?D@CPCRCDHGGhJBNLMOdOVJMTLXKNNMFLPR^TQTZTSXfULVVTZF\YVSURWNXTTUPRQVOXMPLLIKJLNMTNOfLJK`LJPLHHGTKGHHGI\I`ILVM\KMKNZNLQHRNPPLSQNUVVSURQdNQZSPRSRP^M\OVPLTRQSSTU>SRXVRHTPVQNSRXSVQN\NPNJPNUSR\WRSUYVX^VYWTUY`UXXXX@X`VVWPRQZQXRUNVN\TSSZTNTRSRSQSPTPNOORROPUQPOMbLNIJIJL\IMPNONPRRRUUHSRNTSbSTTXNW>VWQfVJSRShWRSZUPSRQSTHSVRVUNQMXOM`OTPOVQPRQOZWZWUVS`VNQOR\TPRQOSPQPVPOQHNPMNKXIGGF@FPEGZCVDF@ECDVFH^LLHXKNLHNMdKKLXL\JVIHTGIGGKTFHNFPJFTJGdHTHKTJ\JIPLTIGCGEDVHVGGKVKLM@LZLLHRHXBT@R=R==V?:7R9R76X467^6b899<>:9`>L=\@N?`>NAR>?@ECDFXEGJEEJE\DbHXH^DE^DDBRECLEPFGdGEZGVF`HdFTGDDNCPCNDAA@VBA@ABZB^A@A?T>RBBRCPDfGVFdHGFZJXLFKINOOdOOPNXQR^V`UVWSTSPdLLOLZJ\HGTL^KZGFTF^FHFTJbIIXF\IJMPJTJJLI\JK\OK`MbNN\QZSRQ\QPSRZRXVSXhY^UV`QVUPXQ\Q\RZSUVUQPMZK^LLLJ`KMLPN`LJIGNIHIKPKKJKKOQNNPfRWXXWLTSVTPTYXVJWUU^UPWYUW\THRbQRMK\MDKH2FJEFRFPFPD\DZDBTBBA?^?HA=N?Z>?;H<<>?N@\C^FIF\EVKKMLMPL`KNLONTOVLZQKPRMOP`NZOVR\NMLOHNOM`NTMNHRITKKRJ`INDDDA@@AnD=<<<<:7736Z9F5L76Z5P4343f7T6442H0V2N24R624L77N4Z4865J6R67834V8\7L9:R:H9`;9R8R988Z:;^:Z;XL>XD>V=d=;D=R@AX;R@P=X@XC@@T@bA^A>@=P6:J79P7X87L95^34Z420`1D0\.//N..b-`,X,T+X+*V*N(X(%&#Z%F&`##$" "ZPb`R`PVNZTVVT^TbRfZ <Pf H ^ R ^ d Z Z ZN hTVHVVbXVdP\VPTfD^^b`TZP\X^PZTbP^dZ\NZ`PPZZR^`NZVXXZRRZHZ^HZXZHLXTRXRf^\^\ZRTZJVJVVNbTTRVbR\XVL^HRJZX\PXD`NX^\^PjVTZXXL\Z^DL`\BVJZHVbhd\bbfjTTbZb^nbZVV\\fPfVZfPbZXPRVZVfZXbb\^V`bRXbZZ^T\h6PL^VVR\fJVZhbXRXVRbNR^\X`ZVVTPPf`VfZXbZ^`VRTVDnHLZd\bTZTTbZ\XN`\P`FXVXXTVPXJd\VNJRF`T^RN\`NNbhX\`ZXX4^`^ R ` N R P Nd R P Z V Z\^\T\PRbXNdZJVZ^\T"T!V!Z"T$#$P&R('d%%)B*+)-*V/1T.V/X1f342T50Z35b77R7T;79Z8>d=\R:h>>?TBL?`?<=PD?P>`ABCB>f=T=@b=8;D;\9V6X866V875R45J7754T4d1`24R1N/520P1X1`0j40\2X20.,b.-,b.-/R1^0b5d7X3d4599:V9;;X9=\>=:b@>B@dAR>fDEXGRIXEF\GGHZI^JNJRIFPF\FD^FZJHRKJRM^PRQBMM^HJEZBA?Z?=J=Z=H:X;86R6`8Z8F7:h88b;=:R;Z=>?^?f>V>==P>@\@BBFXCREJDXECChGEFVFCGEVBF`DFXGFbCHIVFF\GRH^F\EDBTD^DD\DAZABH@PAVCZBZDAETCRA@DTD\H\FDKTFGPJJPJRNMPXQJQP`TPWTTWTVbWNU`SOVMMPOKKLNHRHJLHGNJ`FRKXHJJXKMLILMLKPLXHMLJVNHMRMOQZVRP\QQZUVTSUTUXbUTPRbUQ\Q\TRP\PRNRROMOMXLZLLN`OLMLXMZNHHCTGKPMNJ\NZLOVMQRQP^SNXRXVHVUURQ^TRVTXZZYTW\UXRWUWVTWTPRLVKKJJJRIDGHEDDCPDBVBVAFPFL@@T>=>=T>F?V>=Z>V@d<\=;9N88b873T6^5T8756\5T43T5244V7R146^33T7`5556995V5R7564Z5T9R8\9d;8^9R;:R:N<;=N=\?@?\=L?AA>LB=>BPDVA`DVCJ>\?^@j=T=8V:^99:78\7T87R6f4R6N22-T.R1f.-T,`.T/T.*X.H+R+)\'J&&%`%`& R%F#R$!P!X"!TZLH`VTHLZ`XRLfXDPT\`\`jR b X ` V J Z D `\RPJRHX\VXZdPPXZLfLFPfTTTTfRZTbXTVX>XN^ZPdLhN\bTRbZX\TVbH^bPTJTP^XbP`ZdVXPVXVZPdVPVfbVFZRNZTN\dZ^XPlRV^PRbNPPTXZ`\dXLR\ZP\R\R^JVJX\dRfPbdXXdb\d^VRf`ZdX`VbVdVTXRT^T`LVPV`L^XZP\hTb\NbZRZPXTT\X\NT\PJVL``ZXT\ZTPP^RbV\LTXXdZJbXXPZR^PLXXP\V^RHVJP`N^\ZFbbLT\XT`XZ^PPTFVJPb^^XNVVHZTZNJF\VRXP\PVZVVLF`NRHPVLLbVR\NX LH Z N ^ L d NR XZ^dZ\XFV\PXJ\PTPPBL H!!X#X!#$$T$V&P%(\'%**T+Z++.1/.Z10P13Z1V3L5f5458R797L8;9\<<`@=N?RA@AR>=HAP>A`<=V=^>=P;`:T:H9V7Z77Z86L5J7266T2Z432V22b3N6T5Z1/2Z32V20R3T2/04,/`,/00/2T33X45B9f5N78:N99X9\ATB??EDBFDFHLJVPMRMKNXKLKJOOPNNNROPRMJJJjGJLBHPLINHPGZHJNLEVLLGIIbJKFGbJ\JGLA`DCR?RABEC?A@GRGJPIbHHHEIKKNLPN^KLNRRVRFQSUHS\V^ZXTXVVXZYWZXX]WUTNSUSPPOJOMNOXKLJKNKMZJXM\OMNMJMPIIbJHjJG`IPH`HEHFI\MNHNMLMRLNOPQRRdQPRRQZQQRQNPNRZTOZR\RZOPRQPTOTPT^UTWTVVZTSbSPS^URSRPOPNVMQ\OfRZTUV^XVXZVW[W\UWZXWXfVZXSRUbURU^WbU\VPLRSSTVUTYU\VPVbUSTS`Q^QVPXSPZQVRHOMLNJH^FLKXIRJRMMQRPRRRHQSVUZS=J>b=\P=@T?@AhDDLEdENFETEXDCXGPGFPDD\IFZFEF\F^FVIFFHJGEVERDDjHEDFDC\ECBDBBVARDB>@N>DPBVEGVHJ^LJIXK\MZOTOQRSRVTVUTZTVVTWUZQPLQOLVOJNJbIKING^INHhINFJJIMMbQJPNHJKLXM^LVLPPNXOTPVSQQ^TbSbUSbRTVW^UVWRYRTTVhTVR\WOQNTRN`MMILQPXMZLXLQ`KXMHTINJHJIL\KXOXLNO\LMVMONPQXSTPZVSTRXU\XVPWXWV[P[PWTLWZXVXTZOROLLRJZKHIRF@NGRDCBCRE@PBNBT@?L=X?=<>H?;R==@L=L=;:>T=@V?DCTDJDXEdFDIFJHXMTLNLMNZOTNSXPPPRPS@Q\QVPTOPXMRQXOTOPOJROZPPLXMZQLKNHJHNIG`GRENFFBNC`?>>=;=?\?\CPBC`>RADRAp>F?V@P@R=>^=V;T=\6R8T;P:Z88Z5P5503T303`00P1T-2\.\,+*Z*+L'(&^$R%N#$F$h&J#^$!!NTVd@TXLT\dHFX\bRT` R Z Z V T R T b Z T \ J`XTVd`RbZ\^^TXXTTJ4\Vb\PFhP^`NV`L^TVRTZ`N^XRRJLV\hXTVLTZNb\XV\fZNlZZP`b`d^PX^XZZb^^Z\RZVZVVRTDPHJNVLXXdP`LZZ`^TR\V^P^TZ^DXZJbR^LVN`NbPZRTBVLPZPVTX^`d\dVTRZX\^V^jbb^dJV^V\RNRb`XR^XXdRP``XNbJd`RPX\\\`\hXX^`R`\d`ZZVXdTNV`Z\XlZ``VfHXRJVT^TbVR\TZZVB\XTN^`VPVd\^V`\FbDffRN^TT\VVbXHP^Pbf^LZFX\^\fZ\`ZLb^ZVXVR^^`TRTj Z ` ^ L HZdbT\HT^VXLP\LR!J!"!#R##T&^'%&&J&'R)\)-\,^.\,+V0/.T2V3\2111545X6L9R8P87Z9b9=b@T>d>=TB>A>?BCfBP?RA@?@>X>>=R?P?<\9V9P7Z76d8J8V8V:X55X742T2122b2X3X61Z2`1542X1R1R/N.1P.L1l.L-./Z.^.`4357^6V7P4V7T78d;V9<<@>ZBVAPAAV@`@FHDG^FIJHPNROPRMILKZOdPXObNORZQTQVRLDPZLHKTLJLVJXKKHVKPK`IHRKIM`LXLZKHTJHH\FTHEJDA@@\BAZ@ABAAZAELXKHMI\MJPLTOKMLPJTMMRTRSQRRXV]YXYTXZX\\`\FYHZYW^VRJRPMFLXNTNfNN:J\MJ\M\OQHOQNNNJVJNLRGGHHXIG`FTGIKIIM^LMPLMZNXSSJQ`QdQHRVPLTVXSNQjNNOPTPRPTQXQPT`O\TXSRdYWVYRVTVhSSQOPQNQNPOTQPfWZVLYZZVWdXNWTXUNXHZ[WVHWTTVTVbVXXWYVTLU`SS`SVRUXYPXZWWXXUNXSRRPQPZTZONMVMLJVKKXKNIJKMVLRNP\TbYZSTHTSSJTSUXTR\R[TQQ`QhSRTSZSLRPONQR\R^RFXVfSbVSVPUPLRTNTT`ZZWNXZTXXWVWTVZRbUBTRSRPNQVQZMXORPZK\MNNLIPGKIfHNCE@BBTBZEVDRFFRGGTJJ`IL\MK^KKLOHbFVH\GGIIFC`BCNCDRETDFCDJdKIKTIFIHZFF\FZHZJFKXONK\OJRJGNIDELBRD?V>=9\:9\7X5Z75X7L98`9;;P=<^=X=;>X<`@;>>C\B@JB@EGCJCCPD^HRGDNE^EHEREFdKHGG^HHEH\ITHFEDNGEVGVDEEFNBTEBBACLFTCDE?DC@ZDRGEKJXJJVKM>JNOS\RSPRVTUPUWW\VNTRQXQPOZONLfO@LTIXH^HDXKGbHVGHKNKKKNMJ^NfJK`MOPQnOTNQZU^T@QRTSSTUSXVTWTY\XTVdYZSdSSSOSPPMKJKPLNMVN\PJ^LLMJHXHMVMRKKRIL^INJLJNQPSPSUSQZTRSnWUjVYXZj\dYYTVHXRSRRL\N`LJ`JTJ\HZFEAEZEXCB^CCAPBRBb?=R>>^:=<@>?@V?P@>Z>>hB@B\CCCTDPKZIJJH\JJLJ\NDOPNPTRO\OVS>QRQZTLMQTRXR^QZMPLdN^MLPOFQOMdLZOMZJJNZIHNGCAfF@A@TV@=;:T877T6657Z674652P84L5\4R5Z2V14P2b3V23`4T6\795X744B8H9;T<6P<;;<=^<>@V>TC=>Z@C@N>?RAXCV>>@\>\BR<:N<\9Z>8b7`;V85L45333R22L1V12`0.d0..\+d,R+T**&`%%b$$h&`'f%X"!d!\ P`RZR\HZXV\T`R^ZZVZ` ` V T V Z ` P T \ X X^JVNX\bT\HHfZTLZdTR\bj\PVbf^H\jX`LNZ`\`^hP^XP\fVd^XZTVXb^jNb^Z\Z^`\VV\PdR^Vff`fVhPXT\d^dR`VfVb`XTLj@\\R`XRZfP^b\`PXT\d\TNT^\fZZT^Z\Nb\VRdRdXR\\f``ZfbV\PXTL\PfTRPNbHPXXJPXHZVlVN\NfTXVD\VR`DTRL`\VdZ\R\`FR`NZdV`V^fRTVN\F\TJXLZ\JPXVb`VVPXdX^HRFVd\TZLPhV\JjVPPLLhPTXXZNHZj\ZVXXdRfdNJZRPJN^X^RZNPX ^ PR ` P @ Z T V\XbNXVJJZR ^TN "R###D$%$\&'d&'&f(^(L+L.V,d/Z-R-`/F1R0^2Z34V14N4336V7T:^9:H:<:`9:>TA>\?b@N@V>AJ@dATC@VA;J=b=b9`99T865X7N66^6J84P5J4V403283X3R1H2`22T1j4P1510.101\2/X20/V10Z01T4f7N7T5Z5X7`8H8\9:X:N::@@=?V@\DEAAZDZCXCF^HHFTIE^KKKLLJIKMLOLPPOMPRPOfSNPMVMLFHZLGGE\KGKG^KLJMbKKXKRITH^KFLI`IRN\GGDdCX@@AR@\EVBBT?PCLA^JGXGE^KXIQIRKPNbMKMLL\RXR\PXQRTUZR\Y]FWXYHY\\Z_VXLZ\V`UZT`SOMNMNMMOOKI`KNMMVQOMPNhKI\GFRG\JJRKNGEI^INTOPNL`NNQZOPMOTPTRSNQXQQVRdSQRQPOTQ^TSPRRTVPVRSVZVRUXPWNU\UTPZMNVSOTQLRMPQOQbQSXXZXWYVX^\NXZLXHZYVWXSSQUUZUTdTNUTUUXPVWFYWTZ[@VUXRVTTQOQXPNZPKPOXMPOIKLLdLMPTOQVTQQXVR\TVSR\WRU`V\WTTJT^N\NPN^OTSPNPOPOTRXXTSSRRRQSPPVWVURWVVYd[P^YRYRWTYUVTURPPPbNSNPNMILNNJRJZKLECENDTCBV@CDVEHVHHH\LX>\;\;8:b78889;;\;;b<`>T@VAj>=@>>V?J?B>?P>;L=\?N@VDDGDZEXCF\ILVLLJLRKKXPNNKNTSXQXP\OQ\PZRQSOROROKTMKVPZOXRdUPPMTKNNKJjHHZIE^EFCCbCH>;D=L=T=J<9;9R75Z6R5H7L8^7Z8T9H73Z84T5J4\653J41^2L5253X4^6^8T555^5R5`6L5:R9T8;<J>b?@CA?>RADPD?XCHB?VD@N>^=Z?JA9T7V96P66;:d@X<<=L>=@<@BZET@@`DAVE^>D?ZD`@J<`<<^@\:^778R8l9V8\597>8544V3P2n1R4556V5b6Z21`1Z1\23h//\1\1L0410>/1/4L0/454\7Z67`6=T;9:J<\=N;T?>ZDVA\AX>R??\A`ACVDGEFIFNGKPJ\KVLLNLXOZNOONNQNULQRQNJQPLTMVDLKHH`H^HGGHZLbH@JJXHH^NLLINGGEFCCDTC>C\@@BJAXDLB?@E\DIVH\HTJF`HPMbPLKMRLXL^KNRPVNQRVVV^X\ZZL^\Z]^\Z]TVXQXVdTOOPLZOPLO`KRPNMTMJjMRZSNOPfMX7^=;;:T<>L<9<<<>R<`=?A\BRDD^BCCJHXEED\DXDNDGDEXBHLHFFGHXERHEDH`EZD^JEDHKZEHVHFBA`CRBFNFDPD@TBBAIRF\H^I\HhJFJRMXI\LMNNPQZUTXXVWXVWVURQOSPLP`ONDM`H\KIKK^IPLHZLVILKXMNNQNOPNVQJNQPSbWXOU^WdRS\QR>OTNTSVY^YZVVbVXVUZWRSWjRHRfPTOZNN`MObMMMMROVOFOJMKLKJPJ\MNMMdKXNQPVO`R\PQXRS^RNVPZPWZXZRU\\ZY[XX[bSTfRQ`OMM\OPNfLNKTGNHDTETFEF^BA^@AANA?Z>ZABT??V?>`:RBP?@N@@@X>VF@B\C@T>>^?X>Z>P=LAZ>A>APBT@B@ANA@?^;>?^D@\ECDADVGIPF\HPJNPPVQPQVM\ONRTPbPNQ^TPNWN]h[b\VXYZYD[\ZXU`VTRbPLJMZLVPQXM`MNJRVP^NRO\QJUPbPNZMJbH\JTHMJXM^JTMJ`IPMMObRSPQKTR^UTPPSROXQPSPSVTRRSVRRQPRQNRLSOTRRSHQRVYYXTTFTTUQRQMVOKfOObQTOVPdPPTPST^TU`VWY[TYX[^\NXZVZZ\XZYYSWWWUUPVNUJXXXUNXbWXXW\YXVRVRWUSLQN\NNMPQZNOOPRQMTPLP`QRSTQUWZXFURVWZ\VUXUVTXTVhQUNPONNO\NPNVKMXN\OVT;T=RDAAVDTGDXFXGNCVDJCZCRDPDDDC\EHIHHPI\JPGGFFFEVGE`IEHGBGZINIPIEPHE@BVEPEEHED@^CDJDCDJVKVLRMKLNMLXO`NQVSLSZT\ZTVXUUNSPPdPPPNbMNPLMbKHHKVJPHJJKXG`ILLZJNbINNMPXPROTQQVRQfQ\RRVZWUUQPOPXPZRdTWWYZXRWPVXXU`WSTbUZTRPOQMMLLbMKMMdLXLJKVKIKIOOMPLQLZOdONS\OSSRNUZV^\[ZYTXXXW]DY\ZWT^SXRPPNMNVQOdOLXJ`IGXFVEDHBDA^AJ>XBNAP?C?=XEAR>R>R?`=J?X?JANBABL@BDFGJDTGHBKTJK\MVKVOVNMLPTROPQVRPfP0UZTMORUVO^RQP>SRPFNNM^QPKJOKLIPHDDCRDFF?X??><=L;VALA>@@PDh?J@RDBVF?=N@?V=Z;=R;R9b7L45T6T77853R63F303/X.b/-+-J*^+N*`*^'P&R+'%J&\#"D!ZTRR`ZZ^L^ZLXP T X Z ` P T X N fdVV`X\^JTZ\PPRdT\R\ZZdXTfRRRLbX\TZXPRXVbRdXZ\hRFXNLTD\`PVRRbZP\XXZ:Rfb^dNP\dZLNbLZPLN\\XTNP\TXVN`TLlV\^P\TP\\ZRHb\PDbRVZThRXf^^ZZdPZfdPZb\bTXdTX`rd^Pb`XRnJfVb\VXX\LFZbXdbR\V`\bZZ\b`RbVRNXdT^dRfTf`RP^RRdJTF\\ZZLjTRbfNZLVXNPRf^Tb@NlLXRX^`DT^^NbPZTbJNZV`^ZXRVV\PbTNJTdVFPd P R T P R L P T ^TT\XNNV^NL`X f^"$X###N%'&'L()((d*)P*-T-.f0-\5F/0V35N3^4P4b4X6X7T7T8=\:;;<=NA^AJ?V@@=ANb?Z=;R=98P9X989P76P655l4R5\564523F3d334T60`21Z3T21/1X628V1/V//N1.X4X4L34X7f65\86^9;=>B^AAbAZ@XF0@BEXBABILDFRLGGJIITNKPRRbUHTORRU\NNT`SOQM\JJRFVGGVDTGHXIEfKHKKXKTGXMHTMLIRNGJGI\FDDD?NAR@BA`ACVBbAZCCGGXJRJNNP\PZQR\RXRPN^Q^PS^RZQLRSZUTTXYX]T\[ZXXZXXY`RSRSTPOPKZPMOOQTVNQ`QFRPLRXPFPRXKLLKIJPK^LJJJJIJOPTORRQTNNVPVQWVQQQRPRXRVTQTPSVQXSOQQdRTRRS`UVU`WU^T\TVSVTRQR`NVMQXPjTJQRQVQPSWVWLUVTYZR\]X[[`ZLWVYZXXUZYFTVTXTBTTRTZUHYUZVVZUXV^XbZFVYXHWLSUXQ`RjPQMTMdORNM\TOZSO^PBQjTTRUVVLXZ\Z\NZPZPTX^WQURRQDQMLZPhNLROMZNN\MMM`SZWUVWTSXWUJYVNTWZYY^XHWNVVXTSR\URNTSSTUVRSXN\KLdIZIPFD\EZF^G8ETDJHEVEHNCXFFZIGFIbIJdHJM^KGTHIIGI\HJJMRHG\FJEBFCDC@bDANIEFCBDZEVC^GGLJIKIGXJHRJJLFIILFE`DC@CT?=F>>RA>??T=`>;;N==\=R>`@TA?b=>?DdBAb@@DNFDFNI^JPJRJTKbLOTJL`OHN^SbPNL\SONNXVQVPPQVQPU^NXPPXOVPPPTRLPLQLNMXIGHVEJCBXCTD^@R>;Z=b=:8:97::P9P=V;;>d^A`@?BB@ZCN?Cb=L?`=N><\;J==;^?^@ZA@\>T?H@@d=A?X?RBJA>V?BA=>YXV\XZWWVXVRSSPTNZPVROTMbN^LHK`QLMXMPPTPJUUVXSXUUSWUXWVVHTPS`TTHRSVWNPORRP^TROSNQfTOZNNN@LXJJGFfFFlFEFdFXEGFG\IIZHKFHZKXJLNIIIILINDJVNHRFFVH\HHIRFXFVDERBHE`AACTETHbCC\ECDZFFGGFJ`ITGJ>HGPIXLGGJINIXEGXCEZCPA`D?@@ZB^A?\AZ=X?=?R@=<>V<=T?L>R=L@\==>;@BT?@BABTD`GIJHPGXHLKPNIK\K^MRL\PZOHPZQLOXTQ`TQOXRbQ\U`SRRROVQRUSTPP`MHMMTM^LJFEPEDDFEH@BXB==L>d;678T;9T;9P98V6\5T6Z6P9f74X54d33345P5X324P57P6564^8J8f:8f:D<^;:f;@=8V9X8V::\;<^=<=^=T=\@>@Z@>LAB?>\AX>RAABRAZ?=NDd=Z=N<=Z=?==R?>@^:J;:69P4P9\5\9V6T5Z8Z61^010V1T0b0-^-X+-b)T,*j+b)T&T&N&$T$!"!d V!V!^Zd`H\TfZVR`^ X T P H V \ P b R R Z  TJ\LRPbdXZN:lR^fVXXX`TTPVVVdRRbPh\d\ZJ^Z`XXbZ\XZJVXf^b\^\b\^^P^R^ZbL`Z^NTP^VR``fN`VZ^`ZZZbbPNVXX`R\XbhbfXRX`R`XXbbZXJ`ZJVHXZXBRJNN^bRZdF^XTNdfV^dTZJfZXX`f^\`LXT^VdVhNh\\dRbFZ`^bhZX\N\\\F^^TZVZP\L\FVX^P\Lh^PPbNT^TP\RbbTXVLdPVTTdTFdTXdZbJ^`VRf`b^VP\RPRLNlN\bVRNVTRXP^NP`VLVPLP^`\DVbNLdZfV`ZZV^NP^hfTXVbZHZ`T\ J V ^ T V L V \ L\NVbVdJ\PRXTfHbP"!b"F$%##D&P'X''Z(&`.-)>**d..X/-\3^1T/P2`34Z443d8V77\89N<9;9>`@=PVBbCB>>\?H?<@LC^@XDRCBjH?C\GJDTEZCFCTCDTHPGF\L\GZHXJJ^LXNLMZO^RPROPPXP^P^MZPMNTIZHGZJKFJF`H^NZNKXLKKHGI8HK^H\KH`GEEhB@BZC@?AXCD`AJBVFTGJMOPpRPOJPZQQQXPVQhQSZQUWNSS^UVVXZ^_YbXU^XXVTVVWUPSXQL^KbPNMdMOQTLTfUTQQbT^QPMLOI`KJMMNOhKKJPRUVTZWNTVSWXVjXNWZYRWZVZURSRQPFQZRORRQdS\VSRRTbYJV^[YRXUTfUTT`QOPQRNU^SSQ\RFUjSVPUUUZTZZZT\]h_J^YJ\PYR[[X\XVY\XYV^VVZWUVWVVZYUFVXVXUVZXdVVTU\WPPXQQML\QPNTUUPPQTUUSYYTZZWXXV`[VVNYPTNYVRjRQJORLOORK^MNMVNNZMNXOQQRUZSLUUlSTSTU`UWTYPXXFV`RPWSTSRTLP`PDNPPOMQLQQPQVRRNJMLIJJ\JLFGDVGH^DXFVFNKBJIXLVKLI`NLIZKTMJ`LIJRM\LRLM^JHJ\FNIZL^DEVDB@TCB@JDBAPEAZDPENDCNEEPHFFNJVKfHPGRHIHEFFKNHbFDVGJIENGCBRBCC^BC\@R@?R=@=A??@=VAN>T>PB?FBTDdD^DRDVFHJFRJNJLLRKRLLMOOTQdORN\STTVSTJV^RSPKN^PWQVS\TTSMJKOPLRQKVJ\IHXJCDDF@`?>^B^==;:;V;b9R9L:8b:8:9^7V364N664R32Z7T44V54X4`367Z65R7Z5b67;9:9::b;=Z;976V<<:<;P

@?<=?b@Z?PCV>@=?AT>\Eh?@T?VAX?;>`<\?===8p:5755X::57T45`30/N0-P0..,*(V+V,,J)(P'%N$^#R "R!"!P h! `XPR`B`JXV\fLTd\ Tl ^ N N X L b Z T ZJT\XNR^T\^\\TRXFVXJdTXX`TVRTZLb^\`N`^dTJdT^TVfLh\J^Vnd^VfV\bfV\ZRdf\TZXb`\Z^ZVtZZV`TV\ZbTXf\XPX\l^fb\b^XJNZZX^XXfb\PRhZ\ZXZT`\R@\XVTP\L\ZZVJ^Z`dTLnd\T^h`L`TZdNdZVp\\VXXZbddTLV\VN\hTVZ\fTPThd^TTPZ^PXHZ\`Z`TXZV\bNXD^ZL\NXLTPV\>VX^V`bTfbV\RNPXPXVTbN\ZHhHTVT,\LPD`RbbVdVJVXXXZVT\^F\\dNZ\TXXb\JZZTX^N\^BRZ JB T XN L Z ` b X T Z ` >\V^jHTVT\FR`TR^bV!XZ!\"$P%Z$($J%L%'T)),R,h))R*++\-0/421X44Z536R4R7f8N<;9;=B=\ARA?VCA>?C=DV@@=>VC=@X>@>\;\9X7Z99H968P8\6Z642N63436D3X1213L3Z10H3V2001N21130/^2/213^4P25`9H:T78VCA@DDXCXCE^ED\CACVGCXD\FDXHVHDJLKVJLILLLBRQUQOQPQDPNLJLBMIJbLIPKhJPKTJVLKLLITKG@HXJXHGEF\GFRGRFATCXBA@RDfBATC\DVCdGHGTIKNRTRNPPRURNQZPLQTSLTQVRVNXd[T[Z[\YZR[8Z^Y^VTUS\QRORPMNNNPONMTPZLFPZSPRSPBQ\SQTONOBQNNJLLNPLPLJNQZQ\RJVTSNVWXWV\ZbW\VV[PZVUVTTSP\TTVQTVW^T\SQbX^UTWVYVYVXRWbTUHTR`SOPfNOfOOVT\SPVWXLVXWTYZ]_\[P^[\\`W^YZ[\VYWZTYUF[TWRWVWXW\UUNZ`SZWlWFXWVXVNSLP^QNPLPLXN`PMRUJ[XTYh=?R?l@L@>d=?T?PAXA@AC@VCDDZC^F\EEbFPIXFVIbHXIHFPHFPFVGdIVGPIH\HIdNPKGIH^GIFGEbB\D\DFFPMIL^LMZIXM>PQQdQDSdVRSTbTVZXVXXYPYVTJRRZQOQONMTQPNJNRLZLJJZM`LFKLOMPJLXMZMZMJTOPTSW`TWVTT`TNURVUVV^XZD[\V[[[]\JZJYh[YNZTVVPUXO^RQPNVLdNNN\QJXLJNLJTLVKZOLOMKLRM`MQ`PbTFR^SRZXZVY[]]T\XRYZ`^YNWYVYXVNXZWdVVUNSQXNPLJXKJHdIPGZDDDXHCCVAbBADARA\>=^@H=N>H@^>B=@=b?V>^>R;L9:8L;@;^;b9P5P6H4P4j4R56532N4V45Z787R3Z6@64^487d7F4T:;9X<:Z;X<:R<9`6T88\=?@R<^?HAAB\@=?TD@f?CZ@?AN@ACT=\@P?LB^>>X?=J>?B;^?Z@F>f>:T9f9:689`;545Z4P305T2^.Z0/L/-,l.V++V)+X)'%X$#`$#N"#R!`R P ^N \ZXJX\JNJ^JJXb\Tdh  X^ P d J L d D ^ \ L`XZZPZNRVLRJRT\^LRJT`bVFX^ZZJdRXZXdJ`T0n`XJ^ZVXRX`FPJXZ\bP`NTNTbXTZl>XRDNZjJPTbZXX\FRRbVJLVZNLDZPZ\P\RhZ\TTFXTV\TVXV\Z>XTTXH\VTNL`h`\`b^XR^^RTPR\VPZXPXRdT\\\ZhN\\J^f\T`ZXNXZ^V^^V^Tb^^LX^bZTNJfPVbZVRZVZ^FdVJ^ZRX`HbHNRPPRVZdTLZVbZXLTNdPT\^ZbN`FbR`H\VJfTRNd^RZZV^HLVT^LZX\PFXjZV`RPfRd H `  Z h \ H R Vf X `bdPbVLJVN`fFZ\ `!X!X"#b&#d$$\(P'\)R()'*)V+,\,Z,0X1-L0f1X37Z5L7V5^4Z6:T9R99;;H<>X;>?b>=;>XC^?A?J?\?n@V>C`?>=T=X<>T@@J@?T@VBPCHAV?CNABZDDACDEB\FEVFFVFGII^FGHFPEGGTILVHDJJPJIJTHGTJHKHF^GVEBEVEGJMLFMHLXLNOTRQbTZWT\UXUhXVXYTUW^WRS`QRVPR^PLPXNMP^JRK\JKPI^LRN\LPPMfKNdNLQQJTTPTSTRU`VWRdTSWdYX`T^Y]P[]]ZY^LZ^Y\YZUXVPSXOJRRNdMMXKRNdMZL^LK^ITLKJTOZN`OMVM\NHPMTPOQS\VPVWZ\Y\Y[ZY^YN\Z^YT\YXYJY`XXPYRQPZTVR^RMZKOHXM^GJHNJdJFF\GAHF\BV@ACZBD@=>>\>@?L?@J@AFDBPEPFENGZFDNFbGHI^IKM\PNVLNTQSHTQ\RRRRR\UUVNV^RPRZSPSMLMQ\MJNdPbLFZF\EEFGZDTFTHdF@BHEd@?NA=X>Z<;<;9:6X8Z9P;9;;@;;V>?^>T=`??VA@V?^BCAZ@CVB=><@R<==?J=>T=f?:7^9T;7Z=:J:753R74Z2`11102-/-f-R*X.^+)T)$b%X%\$$R#!T"!L X!!XVpXJX@VZf\PhNVdV^ZVVDRPb \ V V P R N ` H d L jR@`RPV`TN^XL^Z`TNdVVb\^^X`ZbTRLZjZ\JVX```VR`ZjZd`VTLL`JZT`ZP`JVR`BVdZTZV`XRXP\TPhPZR^PXZdVXZ^dT`T^VZXLT^V``<`\VVTRX^T`HNV`LZ\b`hVRPhRb\nfVXP\^Z^PVZ\ZN^\b`RV^RXB\VZX\VPPfPZXH\ThZVZPPdXBZN\JXT\bVXRXX\RN`ZL`VT\RVXbX`F`XXX^`NRNZVPdX^d^`b\XX\TPfdLPV`VTV^f\\ZXPX`J\DZ\T^\Jb^F^`D Z L P Z V D^XPNX\VXZV\X\`TXR \^"L" R#b"H$##Z&V%%T)')`(R*+Z*+++R-N-/T0L133J7\67<554`7N;J:X;;>`?^=ZAAXC`B==ZB@A@C?VBA\>>;?L>V;N:d8\6=h8Z;86`945722L5V3T40^3T0Z2\31X4213\/Z/X11N0H42\2.X1Z14N52757Z8RP@\@C?ZBBCXDCEFABAEDFCD@CZDHHIZF`HLZGKFLZPQPPTPTdSVONPMNK^KLGZKKIMJKKZLPIJTKRERDNJGFI\GFDGFVCRERDDP@BCCCCNIGRIZJKNJPPNRXQSOQPVSHVQNRR`WWWUVb][Y`[`[YN[TYVXTYU\PVPdOTNKLJMZMJKJ\RPWSNRQQjTPQVRbPVKNLHIKJRN\RJORjPLQNUTY^WYV^T]P_VXdXNXXXWHUQfQLSRXTLTVVVRSLTPY\VHVZYYTYXW[VRVXYZPWPTSQRQVPRVQONRRPVTWYTYXWVWZPWT[V^V`P]__X_\\^J[YW^XRXVTW^WdZY\T[YXXTVRVVXWSWTUUbTZQWSTXUVQNOLOPQVRHWW\YTXX^\YNZXYZRY\ZUNTJTbR`R^O\ONPRLIXL`JKMKVNVPN^QZWQZTRVUWTXJTXWVY\VYXWYbUPRQRTLLVMROK\MIjMP^OLMMVMTNLXIMfKKXKK\KLdNMKXLLMFMKXN\NXMTPVMjLPZPQQhPBNVLZMKKLLXIGDPGNGCREVGHCCGECDJC^C>bACDDBEC\F`GEFCGCEETDFF`JGELGEFDJGHJTJXLPI^FFCXA@NA@R?A=>T?J?Z=AX>?RDZBFBXAX@?XCBRACCBCEC`FXHFNGHVGVIFXJJ\JEVKZJHHHGNHTIHNKIJJHbIXIFJFG\ECCIINK\IJMM^NZQHPQRVRZUXXXWX@V[WWWSNVQZRQSRjSPHSONLLMNMbLMVKRMTLKXQZLPKJ^LOOXUXRbURSbYUTdTUPUUXXN][\T]RY`\]\ZH[V[Y\_PYXW@YVZUQNPPO^NNZLK`IXHHPIHTIIJJJJKJNLMRQNPSXNUWL[Z`XTYXV]T]Z[`[P]X\b\PZHZXVVWSTUTJPRMZOORKIMJHJGJGDbEFBE@XAADB=\?X?@R>TBAD@TBTADAC`BNFDGF\HDVJHLGbLPPMMNZQVRQRRPPZPFR\QbV^S`RTSSSPPLO\TL`NZNZNdMLPPKZMMHZERGRHfGZJVDFBNBBRD==f@J>=b<<<;X9Z:X7845`5^44`54T2j55`9h:R46H54T63^64H5L7:N:T;87\6R<9V;^:<^99D:=\;<^>Z;`;>\A\=?J=\?L?=`>B>X@B>V??P?T>=H=N<;V?;>;=;?b;H;^;F;J;`9P;T97\6X4\6`41D1/^20\2.-+-V,*\,d*T'L'Z&V%N$#L#X!$T"!\VHdDVLNZTP\VTRBJXHH V LN T X L \ T H D^ZXT`VXRPZT^`ZbLTFZTXVX`ZZLZT`NdbTVJdf^P\PVTNT^dTbVjdR^Z^XZN^``ZdbX`N`X\Z\P^\ZVV`VdH\`JV`T\V^bL^PRXVPRT`P`V^RRRRP\^X\XZ\HfZ^RTV^dXR\FZ\hPZpfpTdb\f\b\\bXV^XdVZ\^f^dZT\V^^Z\`VnXdPN\lTRNTVnRVbNpP\^^bVP\V`V^V^hT^PVfL`L`JP^TRNVVTTbNR^ZVZVPF`XXNf\fVZVRVJfTTV\PT^T^PVP`D`V^T\ZL^XT^^\ZPTbVRVRXNZTbNbDRJ^T  T P Z R ZVjTXNPJbh\\VXR^!R !P!R!Z##^%$b%V%P'V)'++,+,++.`-/\0V3h5Z372Z8859R88X:=R=`>=X?R?X>h@>D>VE?Z?R=T@ZDTBXEZFXBBBFCDNE`BFBGVHNFGHEEJNNZNPPOZN>RPSJRURR\PHO\IH^JGKL\MK^KMTJTJJN\MH^HHTJHGEHbHII\DRC^ADDAEDZ@RHEbFKHM`M\KLNQRZQNRPZTVP\WPSUTWVRTY\YXRYVY^X_j[]Z]Z`\YVUHRRPJMNKKVJRKLLJXMOOVQRS\TRSR\ULO`ROKKKXKTLKRPRS\SRNT^TXVX\\^a_TZT]XUYVXZVRRR^RR`UXS`WTVHYZXTXZ[YVXZUUWPUZVQLP^QRNORNNP^SXWYZZYY[PXZ[\J\]T_^T^^[\J\`TRYVXWTXN[XXYV\]RYXZPZ[Y`ZFX\TRUSNSPV`SLUPRWVWJU^SLRROPPTTdRDXb[X\b]\`V][[Y[WWLURRXOPQP`ONVQKJKhJKPKdPPTOPDTRPVTTHTWFVT[XYXVXXVU@VRWXRQRNdKKZNKJIGLNORPLQLLNLDLTMNPLTObNOOVPM\LLOMPZMQMVPMNPNRPROQOZOPRKJKZPIJHGTFDHVG`EFLBEEdDCTDbBXA^A@DRBPCLFZENA@XCHDA`CfCBDCEGZDXHEHFEdFRGEHFLJHbHZIIFCA>A\BAT@AV?b>V?LAP@XAR=^B@NCA@XDBCZBCPCTCEXFFHNGIHTIZIZGPG^DGLKbIPKPGFTEbJTHLKHVHTLPKIIZJK^KNJbJHD\FHEHVGJG\LZMLRVRRdRXST\RRUH[X`ZTZX\X^WVTSVS\SRQRHPNR\RTQMK`IfKO8LRNLPLVL\LNLLVKROPTMPPRVQRVVYZW^VXYZTVXZVV]X[TZ^^P\P[\RXZR[\Z[^^RXZlVUlVNSVNQPQRLJIJbKJJITMKHRIPJJNLOPLTNXQS^SVYXVXVXd[ZY\Z]Va]X^^T\ZY`\XLVZTRN^PRTNP`LLNMRIK\K^IGGFTCGZDFA^A@@L@`?@B=\>=AhBbABRATAbBRBDFPHGHGJIKJXKTLPMVPSORPUP^SUVRTFRQTQdPPRPN`QFMjMXPROMOITNfMZKHZEbHIE^ITBBBLCEV@?A8?RA^=XJ?;?A>h=V=<=^==BR>>Z>A=BT>F@`?Bd@>j@>`?Ad>^>R<`=T?T;P=:988:<\:X:5\8X8Z8V41^5010/^.Z./V-X,*)L(L)'V##"$V"d"$T!TTXR ZHXZJ`N\X^XdPVVl ` ^ Z T R X ` Z ZT\`TTVdTP:\^FbZT`VXdZZZlXh\TZ\RhRRVXL\T`\V`PbL^hXLfZR`XRTb^Z\TNRXl\XT\X\RbbT\H`Rd\^Fd^N\bDnRZTjRT\P`\HRFl`R^VHLdHHRN^ZZTXJV^VNZ\PVPPR\dXV`llTj^jPff\`jhhdn\h\`fXZb`ZbVV`ZN`T^RFDJPVNLZh`JfTfNNVfX^XHdZX\@N^XN^XZTTHdNX^NTTfRTZRRT<bRbZdXbJbNHVX\\^N^PRRXTfTHhH^bPXTV^NPbXVXVf\bZN\Hn`VTVXZX\V^XT`XL`X Z X P Z X ZRP RbXRZNTN`B\X\dN\L b! !X% `#"#T$X%'&'T)^))Z*P+H+R+0/b0P0/X22R4`8N5V9V7J6`888P9^;Z=`@?h>L@N@?ZDX?X?H@>P@=Z>F>=7?9`6;::;97P857N9X<\6:^9453434b31Z/04V050T1`1P4/21>/^/\.00R13/0N6V15597`:@:=?AP@AD@XF?VCCBADEbEDPDFLA\EPJHVNPIGRJ^HPIKLMVNRSRRVUSPQTSM@JOI^HINITJTKZKH\HXJDJHRKHHGL`GHVIVGGXJVJCDDEC@CAAbDXGdKLHXJNLOMTTQQTP\STX\WPSTSUU\ZVPWLZY\[L\J\N[^^\]XWV\WVVdNPJVNKHKI^JLLLbMPQVVXQTPQRO`NNJVLLLRMPRSUPSXTb]\\PaXb_F_Z\^VVVVXU`TUTRTVSWSXT@UUTXTVVYR\^NXVZXbTVUZVQTXQSNPNRQ^TROP^SRXV`YX\\L\N[X]X\Y^]_P_aP\^`\ZVZUUXNWTYYXTXV\PZ^\ZZZYRZJWTTSUV`XPV`VVTPPVWhVTUQJSTShV[fW\`^_^`Pb`_]LUXXWSXPPPRPMLKKLZJLNNLLjQFRRWSXTTUPYFVPWUDWZSPULQXSUWRPPTPORLVMMPKONOMXOTP\NKMOKNOMZRTQOVOPQBSNP`NOZQPVNVSPbTPVPSVSXVPFNZLNNnLTKIXHGDHGdHD^EZFXEFDjCTEV@A>B@??>@N?X@REBA@C@AV@?T@PCECDGHXEPFXEXGZGXGFDIXIKPIING^KGCCCZDGRBJ@P?AZ?@VB?BVB`C\AbAAAB\DBTG\DGPGHRJ>I^HTIRHGNFHIPJPLVKH\HHKJIJ^JI^H`INIJI`HJJPJKHHFJIdGHJTHHXKXLLRNQ\RLQT`QZZ^U^UfYf\ZbXPYW\TJWRSSTSSXSQ^SOXNMNNOZMZORPLMVIPJKNHLNNKLLVO\P\QTWTRSUTPYXVX\RZb^Z^^Z`\Z][]\ZY^ZWVYUDWSRQSJSQTZRTLJIZKFNKMKH\JEJZKJVMJOPPVTTVBTYXYXX`]HYZ[^[]Z]N\V[V][WZNVZYRVVUQPNLPKKOMXMGJ\FGEZERECZD^CXB`?@V?ZD@\?\>@A`DHABD@RGBXFIbHGJHHJPJHKLJOROQV^SZSRHSQSRR^QTLTRSQRNRO^PMOLA@;?T;b;;^<66884T5d6P7423X585675887675b8P9`;T;:b87;R98:X;=\88X;;>V?=T<;X<;\><<;;Z>XAVEA;>Z?>XCX@TAX?A^@\=BT@Z^>X9^7T7L:5Z88F2R3H113.T0P0d,f+-*)(&%L'b$#$L$ X"!P !B XXXV` \TNXRf^ZLR^fPbZV^^R LL P ` \ : H   Xf\T^T`TLb\^ZdTJdRfXdJfVVXd^bfRLbLX^TZbXj\X^TVPbRD`bXZL\LLTX^^NVRRhNbRZ^j^X^^V\^`dVbhZ\`NH\PLdbZNNjPVfRZZ^^hXTLTXFbXRhLZJfXVdVLRTRZH\X\Vb`ZjZh^TRZ^bjVT`^N^RPRT`bDbf`X^ZNnbd`\\XRX`XbTPX\``XZV\XhVb^PTj^`NJXX^h^H\VRFh`JlR\^TPTXNbHVZnZVD\XbT`PTVdRJP`dXTXhNJVPX`VhDR^`TVTTZbVVLdTTV`TZBXZ\bZZVJTf>\NJ Z F T b h N N \ V^^N`VN\\JXR\\^DZTXT" ! N"#X$J#\$^&(')^)^)N+^,J+d,-L.X/d/0d34Z4d5Z45J9`:X8P>N@@>AfAV@?>;P=;:d><=:L>\>`9;;::R<9V6b8L698R:`8T8f5H5b53d5\5^30B51L1/1Z7.Z1/V223/2/31200`0T3\3184P88X=b<^=T>>CBTB^GVBPC\GNEGFFBCDTGbGCFJELFKHfK@EJHjMZLSMPPNSVZXTVPTQNSNRIMRKVJMHJLZLJGJKNMZHJ8IHHJMH\JTHJLHFHGPERCEPCHbCDE^HJJ^GLITKNPXSQFOVRSNPRXSRVTRTVNTZSTSS^UTYTZ\YTZ]T][NZR^XVYXY`RSN`MKRIVGdIbL^J^KRLTQfSTQbQUTNRZSTSPTLRPRPLVOKLVQPZTVR^YUTX^^_`a`Z[]XYZ^VTTTRTTLUXUXHURTRXVVWZ`YXTXPUWRQTRQQQPUNQQVR^QXPTQPRTWZY^T`V`^[XVYN_X\]T`\bJe`Z_\^^[YWbVYXYN[ZZ[^X]ZZ]L_P]\^ZZ[XVTPXRVbSObUPZZXL\JV\UXUPUWXXVX[T__R__N]b^NaLZXTWTVTSNQJMJILKRLZNMNLJOOWQZRSVLVU\WYX\LS^RbQ\QPOOLSPQPZOZPHLVMfL\OOhNbKZO^MPNQO^OJOP^QLN\RVSTSXPVRTJQXQRQNQLP>SPTTSNO^RNNKPOMKVJKIVIJEFHCLBBFCZ?BB>AZB<>NCLCV?`ANAAXAC?^?V?=>J??LCAPCE\ITE^HHDDXFDHXJLJLG`KGG^JDECGXFXCCBTB@B^@^CLDZDJB?ZEETCA@BVDNFDFHEKKLKKKJRIGIVKLGIPJVHGL\IJJZL\JLFTHJZKKVHIIRIEILTJJKJHKNM`NNZPQQOXSVWb[XZ`ZYVYTLXTbUSWZSSRQbPOPNPN`NN^PRONLLMJMKVILVP^MRPROHOZQSSBYNVTVV\V`UVY\PYZ^F_^_]JaJZ[Z]]YU\Y\VfUVVJSXVONOINMMRKJIXJHJTGFPHPLPHVLTRMTOZX`V`ZWd]TZTX\XYYNZ]^^^`^ZX][F`]\YlWVSNSQONXNXOXMOLjNKI^JED`EBHRBBNAB`>>VBN@\@hC^AAN@?E\C\CVEDECGFIHHhGKVMJPVQObQROTQVTDOLRTRQRQSYVUbPP^RZRPQZNJ\NRO`NVNJZKXJNHFFHHNGZFRD>@NFZBZB\A>>75Z6567V87432^6737T5X56l57T:87H::\;F;76J6T967^:7d:V=T=Z<^>;H;h::=R@d?@X>>>@?d@N?>d<=H>V;;X=>9b>:T<9\7\9P96444R30V/.0/-h.N*Z)Z''P&H%\&&n#\"$" R!Z``L^X@dp^PRb^T`PNJP^VVbPH Z P T X p \ R ` V ` T PhNX^TLPZZPfdXZPdbZVPZTf\`NZTb^TVXbdT\\PTZVZP^ZdXX\VJ`ZPZd^RZh\NX\XNfbLXXT`VPb`N`RPLXRZjTdX\XXN\l\RXTVTXZPP`lbXV\TNTX`JPfX`TRR\RZdLZRdbRLVXPZX\b\VTXPZ\ThV^XVPRpbVf^RRX^`R^L`RN^ZV`NN`TTVdVNXP^LLdZ\\PZbhJdZZP^ZVRTNXNRZZZPNZRd^ZVVXT^T`ZZVXbTfdV\\\Fb\`ZdNZPPdZX^TH\^X8FLZ`NVZbTVjdV^\LTPZd>L`R`N^LRLTNRT\ZTH\VVPV\NP\bZPb^ZLRX>RXl R N`N b ` T X d ^ N XX\ T\Xb\>J@`\HfJRTPN^R!"!X"X!`"L"##^&'`'(')L(*P-f-b/`,1Z/X34^164X6899:9:N9T<:d=N>b>@\?X>b??V>R;;H>P?:<;:N:h?V9::8=:\8756H76556X3P2H30Z2^0V1b3./T3^1N02P1T0^03f5^10P1X4L1V369X9\9T9N=d=V;^==^BVF>DBD^KEVIJEDVBCNE`GHPFhJEZHTHZLIG\FGIVMLNNPTTTUbSVTOVPPTKLNMbKM^KRLXNjPPHNJ^KKJ^FJKPKJHHZIIFGEDA?^DZCTCRBDH\GPHJMNNMOOQURQPVRRSWTNYZUVUTXTWULXTUZNXN`[N][TY^\TYXWUNUNMbOMjK^JNJKGXNVNLOhPNSUPWVT\YRSXSTPMPZQ^O\QONMKVP`QbUZVVXRXX\aTbV_N_deXdT_Z\LWP[ZWNVVURTUFSRVVSPTDWU^YXfTTVRW^SHWRXSUNQ\SXRQNSZQTPPRXUZZ\N\d\aT_V`T_Z[[\__N_\`\a^^^J\YVFYVVZJXVZ[WPYVZT\ZZ^^[WWRTSVTTUSTXXNXRWNWSXSVW\[^^XbNdP_`X`b_\ZZTRVNWOZOVNLLIJXKONM\MLQL^OLQXUVJU^VXYZDYHWNWXULSVOPMJPhLMOOPMNZOPNOONLPONNRPNO\QOPPOOQUPUXZTfRSfTQ\PPOdTTVROT\QPRQSdP\RMLPNJNZLIXELFEPBVCB@T@ACLB@V@>P<`A>?`??`>R@T?L@^@==R>;=AVBLGECDXH^EBEVFEjHZHVKKNIJIJTI`GHHEIdHDZFRE^EPBCBRB\HBEZFAB@DTFE\CNEHHHLIBK\LhM>KNIIJ`JXHHLIIPJRJHKXKILVLKZKJRIXLKIVITJFGHLIJLKBK^KNKJJ\RNdQRTXRXSQSVYXXX]R\^YXHUWUVWXVWWUQBQOONNPVQfMLLVKKXKLJ\PMNROQOXSPQSRT^UTZ\UVW[XZX]ZZ\\Z_XcR\X]R^\N_[W\X_P[YVZUVTQPJUVOOFMIIKXKJZLI`KLGNFZIKMBLQbPLRbVYWVWW`ZZZYT\Z^_\N`Z`b]\YR[[\ZX[HXZ`YFWVVLV^PNNONOKdM\J`INIRHLHANCCXCAF@A?X@fBH@?f>TDB@RC@VAE^BZBDGTGEI^IJK`MGKROPMK@PVQPQjSPJPSTP\SNSNR`TTTRSbPTPPVSLNN^PNN`OPLRNKKLNNKIXCIJIJJDDAARC@ZAN@NB=f?P<=;87V9D56j7\78J54235R85436T:R68979:R97;Z<^:^7^7769^;9T>R=;<<::@:V=`@9Z<`?V=??Z?@A@B<^?R@==:R=>d=\>>=X<=:9\Z`VR`H^VPT<\PZ^\LbNNNXPR^RLPTXJRVP P ^ T L R X bRP\RNTLXJT^\ZVPVVPVXTRP  X#T" $X#"""$^%%'J(X*`+-R,Z,T,.L-V2P433`457h9N87Z;<;N<>V9:V=JDD`@>=<<>><==X:ZA?>T?X??PB>T?T=>b===ATBCT@XBELGTJbLPJZI2ITOPLJZNI^LIJIGIHLGNKGHHDD^CELDGREFEXFDdEPDDE^DbHGHdGLLKMN\JJK\PJ^JIIFJIIVMTM`KMPLNK\MMTLXK\NMNQPMIZHGILZL`MNJJKJJjSMPPPSRTS\UBWTWVHV\YX\XY\R^L[WUXTZVTSRNSORMLPNbOTOLNL^LTLhNTLTMXJN^NRQNPPQ`WTRTZYRUX\[^\L]]l^\^N[P`R^][\^Zn]_\V\P[XYVSQR`PMOJPILLKJJ\KETIITIJJVOSVXTUVWLVXWYTY^^YP]b_]V]T`V\f\ZXYY^^[ZY\ZXXRYTYVRSROSS^PXNMVKHKGDLDPDDVB\D\DhBAl<>?T@ZA@TBRAdADEBNEDFGCZFDHFFRKKMLQOOdTXNRTSSTRSZOQSVPW\TFSQQ\TRVQVNLNMVO^M\LRLRLVMTNVHfKTJHVLXFVF@fB`DPDTD@XAXA<=989Z;P7b9L936F;X6Z4X6V4566R7\4X5V577R;R8^9T8T8X=>X@:\?R>b?`?T@JBA?\@V?\>R?^?C>HDZCD@>BV>>><;?X=T>X=X;^b^RTHPb\h^VZVZ\Z^bJ\XZ`T\^`dV^LHRRRjRTR^XRH\VT\TXZFTLXP^PT`fXPV`HPRZPPjf`X\RN>\ZTPPFP\ J P V V X Z  `XN^XR\RNZV^bb` T ! !P#$##^%$'*&R,*X+J0*/V.Z/Z010X3X4\2P46J8J79^8^;9N;=B^@D=LKL\NdMOTQNRRdSZSNWRTTXPSTZQ\SdPTOPQONHSPRXXWZf^a^X_VcdePfhiba]f[XVJXVUTVVXUdRON^UfSRTUPXXSTSSPTSLRPOORMQPVT`QSNUZV\]^a`\`ba]_P`[H^`[X^\aXYY\WXWWXRWXYYTV^VURUVVX[LXbXVWUURRPSLUU\ZNWWPXYLZ\[Z]^_PaaTcDeVc_T][P]TX\WPUVTTPLDJVIPLJMJKXJJQHNRTSTYZXN\ZPYX\X`YXPTVRTNXOZJXOIRGTGZGGJKI\MMO^SNPN`PNVPXQRRQQZRPRRfTUbU^WXWbXTTTUPUQ^NSTRbS\RRTZO^R^TdQQLTFP\SPLQZPMM^JVJHHFNDDECBBBCXCPA@P@V?Z@T@=@f@@P?=L>=;V?P<=>X?FCAEZBELIRHIZJPKMMMOJLNLZLKJTJFVHITLIRHRILGJF`HERIGbHTE^EVGZGZC\GELFHGGILVMKLLKLLRNONLIIJKRJ\KHM`JJHJVLPPMQLKXMMNVNZJIJJKTMQROJNMHPKTMfPOHQPUVUVVUUVXVUVW\Xd\F\^ZZ`[R\V\WRTURROR\RNZQMNTMLL\MMKINTOZNP^NVQZNPPZRZRUZS^VYWL[P]T\b][\_`_`a^N]N_^]^]P\X[TYXZYZX^TQ^PXPRLJGRLHI`JKTMLZHJGH^JLNTLZOS\RfQ^TXZXWVW\Z\ZZYd]V\]f]\]`]H]T\La]\^]YWTW^QZSUPZRVRRQNLZNJLG`EFRDjDECCd@?=>TC>`>NBLA@@@JFDTGEVFCXHIXI`JTJTKPITMMMNPVQPVTTQVPQPTfQPVTWUPS^PQdQTOVMM\LNOKNTJVKVJ`JJVIGIHVGDFCTGJEdBF^@>\?V=V;`8^67\9796854Z3420h445Z3^7f66\;Z;<<;d=X>R=j;@ACT@A?ZBT>\>=^=?h>8;P><\T<9;8L8X7^94\423X5\5J/2.X0R++d+Z()X(R(L($P$d$'&#R#T%#bP P PTNVRVZXdbXT`hJVlXbb R N P \ L V VTPPjNHTRb\jNPXV^^TJZ\T`VPRXZ\XjT`\Z^TXTZJPZXb`\R`\dXXRZN\^LVRfXXXXHTfddd\\T\V`jbbVLPlJ\VPTZlXXRV^bZNXF\LjVLVVZ\V`^RPZ\LTTXN`N\NR`NjRNPV`\VLZ^^dRTZpVdf``fdZn^^VNV^bVd`bbh\h^fXZXh`l^`VX`Ld`\TN\NV\hN\VXP`H\PRXdTPT^N`^`LTb`Tl\ZZV\NDXLfL`H^X@hR\X`LRV\dPbRXRLVZdhTV^^^z\`R^RZNZ\^NbbR@fVZXVVnXXZF\ZZ\JJZNRBLZ^Xl  R L FT J f X RPZZ\JnZRV\XRh\TJN` Z P^ "#f"&##X&#V%X&T*X*,N+.\,.X0J/L4H225R65R567;b;\9^;;>\>XB=>\>=Z?Z=X:N:9=7;`7^;P<9Z97:R5J9^77P75V4`432Z1V/1.J1^02.H0-.\2^2T/2/\110P32R4H3\5J865^8Z79>Z=@?V?@ZC`FJZIIRJ^FKVFGJ^LK^J\IVFbJ\KLZOQOMJPQT\VRDTbWdVV^\TSQRVNNNNLLFOfLRMOJ\LLLINMMFIE`EG\EEPFTHVANDBVCACPAbCDIHdFKTMZPQPTNPTTRLSSSVNWLTFZZUbXXUXTX^DZ[^ZX\Z\ZZVUT[VXSdQONfLdNOHLVKBLNPL\RJRTWVUWTZXYSZWHSPRTRSPPPPQQfT`XZZ^^\bafcNdPdieVc`b\P[VX^XXVVVWXVSRQQ\QPQJPS`U^TTTTTUVUJS`RPVNLPLOS`PPQ`RSTUVX`Z]]`aNa`a^dVaaV_V]_]V[][WPVYWW`XZWTZVZVZVXbXWZVUVUHXdXSZUNTZShPSQNVPVFVUVXWWT[p]__bdPbZ`aRa`]ZYU^UTbSXPOMILHKNNTOMP^VWRVPVWLWYH]LY[[YRXV\PLJJ^JTI`HDFEGIGKJPKbOP\QOHPOSTQU^TUTXVVNWXZXPYPXJYTbVT\RNPXMQOPQ\RRPbPOfQ`RXPPZQ^NRPRfPZMbJLBJI\HDFNDLBXDTDAAAAARD?NA?\AV>@h?>>P=@V=V@^=?H>CEREZFTFVHGJHOXOOPNOLKLJbK^M\NJIKIZIJPLI^FGPFGH`ENEVFTDF^E\CDF\F\KIHOTMXM^N\PJOOdLLMIdL\IJVJ\KPIRKNLITKIVJLNP:b:b7R6^7N7X4H6b6583R42`214^865568Z8L789<\9^8V54Z6d7T877N9T::@@?@X;^>?^DEXBL>R>@X@^=X>=@@^CDAXBB>X@JAfA9=Lb;;X=>X<\;<::6\;Z63N4R7P42R41-/T-*(,(T*T)`(N'&T%j&L%&#X"^"N#V!d!\F !HXP\TF^ZL\RT`R ^ T X F ^ b T R Z^LX Z ZX\XZbRjTTHTbZZbLV\JVVZbDNRL^fN`TTjhZ`ZV^FZT`NJd`ZPd`P^Rb\VV`PR^V`ZTT`RfR\ZR^RXDfRTZ`XXTlX^ZPR`ZZd`XbV\DnXX`bVZZXZP`dTRV\N\d`TVRf<b^^^VVLZbNXDZLJ^`^Pl^d`XT\`bb`Z`X^h`hVXZZdDLTZ\R^Z^XRbVTB`TVdXVVXNb\HRXTL^PTL\VZLdPbjZ`VVhZbR`dZbTX\P``JTXPhTLjPVT^^VDhTZR^RBdXZXZT^Z`XNT^L\XZ\FZ`T^\Z^NTNVVPP@`XZ^VdBNNNZXJZ^V\XVXX \ V F ` X X b H X Z fP RZNT\NLXXTb`` L" \! \$P$$&#$$T'*Z)J(X+F/N--.V0/T2\143Z5H4V8f7T8N98L9X=`>@=L\<^B`GXHILGKJRH\HLKJJ^KTPLJMPMKONPZRTQ^OUWUXTSVXUTTLWRQRSRQ\KHMOVLPNKLKJLTJGZHRJJRJKKNDNDHH\FRHE@CAAAX@ZD@ERGPHGpHZH@GPJVNR`R`QZOPPSTZXTZWPYVLUPYXUWUWV\YZf]]H[X_^\^XVdYR[N\PZSJQNVLOMNZNJOXNNXQRRVHVVDYNX\TWXUZTRMQNOQRQhRPSTTSVXZT[]`P`cXceTbXfbLhdX_^_X[[VdZXVWHWUXTXSJTVQSZTTVVUUJZILIMMTPNU\RVURURVWZ[YW\W]X[NZXWULTNMTJIFFXF:GbFVFGVHHPXQfNNQZP`PXPBTV`WXXbVPWXZX^YR^V^fVPY`USSTPTNNPODROPRJTQNQTPQPLZOXONQdNNZMRLNMHIFFEZH@BHCCLCR@C>T?R?>`AT?AN?V>=X>\=B<\=;>:?N>A=ANEEDEGGVHKFPXPNQZLPVQLILFLMLRKJLGTIHVGNJFVHF`IFIdEGFRHCXGH^IXJJOXMQPVOZRKPOROLKMHIVJZI^KZLVJKIVMjMRNLMbMRMJ^NOPMNLKNRNMJMLRNRKK^LILXNdTZSHVXW\W[VTf[XVV]]^_\]YZXWDVT`QLSNRTQNRKdOVLNL`KLdKJJLLXKLZNPO\Q\OLRZUTNUJXY^]\]Z`\bRcaNa_]X__TaV]H\]X_Z[YRYZV\UNQNONMOLJVJLIJJJ\HKTJVKXOMRVTPXZVXXWSbTWhYYLXJZ^^]Z_Lbh^N`\Z]^b\^\^\XWVWJS^SPXRQQZTbQM`LVKLZJLGdFGA`EFdERDA@?X?^ARA@VA@b?LBdCCTEEBEFRHH`JPLLPLIRNXO^NOQ\QPSPSR@TVTQJWVTVfSSVSRPUNfRVMXMKTNKMM\KRKVJKLhHEFDbEBFI`EdF@B<^>N==R:78b?N=;@`=VAP>=V@CZAXACT??@=JA^=R@BCB@LB>^@=d>>>V@P>j>T==\>V>>?R=T@b=`;V<;`>R=Z=d;>N9f<;V8X;;>9h6J:b7979d4348V2N100/d.01-\0.P-T/2X/2T0100L/0T320Z7V:Z7b6V68P8\:>XACdABRAZDF\HHHLIXMPKKJONLQVPLOMVN^SZRSS`RPRTZW\XZ\RWTVV^SPbMTMPOONKPP^J\LKMPIKTKIjKJLHCPDDNDDDFAEA\Bf@`C@TE^EG^IHKHPNZRRSXVTSXUZR\W^VUXT^VVVTVZ[[WV\Z]\\[XZXZX\WXZVRTRQXNOPURVOVOMTPRPRSYVWWXZ\NXV[NY^TSNPQMLNjQVP\R^SFUU\VPZT[Zdb_LgfZeXd\eRhLbda][YTXNU\WVQ@UPQNRVUWXWLXTRWS^VRVSQTMNTO`OZPQbR`RbVXVBW`WT[b[`cPadcTb^fTd`db`T\ZVYY]ZZX[FWTTTTdSRTSPTSVSVSUbRVNRTUVLTSSTTTPUUXYNWWYY]VaP^\``abXda`Nbad]XTY\WUQSNDOjMIGdHRL\MRNVOMDRRP\ZFUXFW`XZ\N\\_\]F\`[^URXQ\MJJI`HH`EEDVGHGJXJMHNPNO`SQVUVTX\PVxWYPXN\[XZXZRWFVWWSPONMNjNbR^PNN^MVOVNLONT^LTMMTMZN`NLPLMKGXHFFZCBT@f@\A@A`CBA?A`>`@>H<;Z;J<>T>?>>XAVDVBVDBILEJLLdORQ`NHRQZP^ORNdRQ^PJSQLVJJJGXHRJfHGFDHbF\DE`FEFFJHZFGZLNNVPPVRdQQDPVUPRLVHHHPIXI:MKXKJLTPK@MO^PMNNR\MLOQZMZMNNNXMXNVPLMLNLKNJLKMXNQSZVZXWRWWPWXYR\Z^R_^N`ZXY`[bXRZYVTP`S^PSTPKXRLNP`M\LKLKVNMTNKTNNOPLPSPRPXPTSVX\[[^^X`\`^\Ha`\e^XcV]^_\ZXZ\Z\bVJURTPPPNPKLPONLLJ^IH`IHJHRMIMVMbQHS^XVWSUPTTXPWVZH[[]\X`]XV^[T[T]b_]^Z\VVbVURbTRXQPXSSXNOPO>KXNKVIIIXLC`ECCB^@AfBH@TCZFBREbBXCbALFPDC`EG\IXF\HLJHLVIKLOMMPQdOOPPQSRVRSZUTHTZVSTTTS\UQPVRNLLLRJKHKRMVQXJ^KHNKLKKEFGE^GDDEPICE^DRA>d>X;:P:6X66F6V534N5N73`5V5N3^14`254T8688H89X89`:7^877V8^8::h8N;V<:P;=@?R?AV@b@@V^?<X=X?=?:;^9:;>Z=X;=b=V?N;>>@V>V@\=?:X?BV><=<>:>V99Z9:::^<8^=9J75Z7\8d64\463N623V14V00V../2F2V/R1.2P/.Z.J1Z22/2^334R7Z<6`7d6P:\:`<=?ZCF@`CXBXLNLfI`KJJKNPN^NLNNOOZPOPTbVNUXWTUUXWYVWVWbUZ\SZUQHOQOJPTMN\KIIHKLMIKGJJVHGVEHRBNIXEETIEPDZDbBDfCVDZDXGJE^JPIXLPKKKSQVDTQLVNWW^URVWWFUZVV`[]b^YXZh\\^^\^XY\JZZZXV^UPQRPS^OP^NPORT^YUWYVWURVTPRRZNP\TQOXUZRRSSTZXLZP[`aViPcZdThhca`c^h[ZRWhUDU^UTWXT^TWRRRUSPWSSUYTVTRPLRNdRRQN\LRPQVQULTTUVZXY[^ZbVd\fZeeaHb^N^]^Z[TYVVRW`XfTSRNRZVSRPVVPUVU^VVXRUZR`RPSXQ^UUUVW^YXY`[[VaadeTfVhVaZbVd]`V[\YX\VQTRLKKJPJJJPKRN@MMOTTSVZWdZYXZZ[V]NYP\ZYT\YOQTPGVMXHZHICLDDTDDGKLNSOU`SU^ZJXZWZZb^PYZ^\D]\[V`XW^XSZSP\PRPPVRMQZLbM`LPLJOPOTMMO\MbLNOONK`JLJHFI\BFANA?RD\FANCNBB\AAT?;N:P=H<@BjBPDdABPDDIVEJIZKTJMPZRRP`P`QLRVQRPRhNMKMZHIZIKHXGHFJPFELGNFLGEHJJRLJJ`MZL@QQVP`PPRPROKXM^LRKKJMbLVQMQHNZNVPTQPJONMPTMbQOMPN\SPBM`KKKZK@KLLhKLLNNNZPSSZTRXZPX\P[]LbFaZa^\[ZNV[H^WRQ^VZPRXPNXRM`QPNKNNFLHKTIZNLK\MZMVPXNRPPOPNXVVY\VRZNZ[P]T^a]Nc^]H]]ZaX_H`]]XXV\UVNUTPMNLVKMZOMNKNLHRGJHbGKHMLPMOTVVT^R`TPWjRTbTVYP\bZYXY[X\VYNZ`\_`]]V\^T][UXJV^SNV\TNQT`QQ\NRMOJMKHPJL\HHRD?ZENCbBLBXC?BCDVEXFZCEPFLDPDRFGHNGJLKHM^PXLONOZNXOZQbQVXSSSdUTUZVTTURS\SXTQdOFQNON`LLLZMLLOMXMTMKL`HFFHDPEGVGDEBNC`E^A?T?==;9886J6V6T772T3455T22X548598Z76X5X<@>T>=;h>RCA>ZAT?Z>=V@P>>=@AP@dBLA^C`=PBb?R@>AT;>=N?=R>B=X;^=Z=B=8L=X57`96^4L54L47\30+Z-.-f,)b)*+@,(R'&R'P%$$^#Z"L!X!T$Nd ZfH\TfLXdXHPPHL ^ T T ` V P N T X ` NZR`bZVTNVRhJTZdRfXXbVRX\bb`b`T\^b\RVJ\dZbP`XN`RRJT\PTPRX\RXHdR``\X^b^VXXfXfNT`X`XPlNVXRR\jRP\Hd^L^V`^L^NVVVP\bVT\^VPRPRTNTZTTP\RDNVJbh^\TZnT`jfR^^XdT`XhP`LXNTLXPXdVPfR^RXV`RF\ZJb^VNT``bXVX\XNbd`XTVXV^Z^\TbTHZ^fT`^RZNN\Rj^\\P^PXfTV`LfbPZd\fTPV^^d`XV`^jdT\ZRdFR`\XTXT\V`rXTV\\bRlNTZPP^L\T^N\P`bRfVX  @ T X L Z Z J J H R XNTTXNhTNV\^R\XV`N\T V#^%N#""Z"#J$$R+&^'Z*T*+Z.-X-Z1\/0`75^2\5^8T66P;`7V:=\998N;D?;T>>AZd@LB:;<;?N?V=f<@X=T;=9\<>:T99P:\:8H5L85f8Z4^54N3437Z2Z20f2T1T/^/X.X.Z,,Z0L.0.R0/T.V11L4V350^6Z6596Z9R97T>R>BEAFDTDFLVJ^JINLXORQOQVTUTQR`SXTNYUTZUHS^WWZ]VYWXUT^TUNTHTbONMMNTOQLVOFLM`K^JI\FXHIFPFZETILFCCfBbGEBT@TAXDTCDTEVDFIbJKINM\OPSVSU^TWTXdVPXPW\UZVbWFYV^[H\^ZLYb^T_]]\Z\^[W`WTYVZTXbTTRRN\P\PXQPLPNQVWRSTR^TX\W\VYL\\UR`SRTLPXRQQVWXVQTVTjY\\^`R^c\cdadXda``RaH[`[YFWXTdQTURWRT\QTNR\UTVUSHSSMM`O^MNTPMjQQUSFU\YZZZ^Z[R_PaPaTcaPfJhd`Pb_[PZXZZXYbZZVWWRZURTRjSTSR\YLTW\T`WPYVVRRRbUVVSBRHWUFVZPVVW\X[P]`HaXadJbVddX_X`H]ZB[URPTPLKBNZKLJROKTKLLJOOVPRTZWV^\XY_hYTWTXZXVVZYU;Z=<>:P<;???AFAZDCCFCFF`KZK\LLKbNVORNRT^@R>V?B@R?@>j@?Z?`AXD=VB?J@`@>?X>==VBh>X=A\@RAAX=T=:98B797^;5B6^41f300b..,d+*\/R-*f,*)V)Z&\'V(#`!Z"X"R#!ZJXT\XH\RbZXZVVTTd T X ` R ` b PXVHRZb`X`LRHPThV\P^X^\hX^XbVV`NTTHbNXbbT\\TVZT`X^b^NZfLLXB\\X\XP^\Fb`\VT`NXZZZ\PXbPZ\XT`Xj\LZNVZZTXR\dVZV^NXXd^HbNbfVTRdVh```PVLXX`^T\\ZDZR\\\V`RdB^^XZT\n`fh`\dL^^bd`RZFbJ^XT\Z^TZ\Ld\\R`bZXPDZXZV````b\TZdbBZTZT`Z\b\`VVb`TTTFjRV\\VXT\ZbXFPX`TVT\^`TdRH^`P\VPZTXThbbNXPXXZX`VRTZX`\PXfPXPN\Rd`PXJTPJVNNLXN\PVRJBZV ^ J  N F Z T ^ J T J T P \T FRJX^R\NNVNTTR`b\!R!R""\%$!"\$&N'Z)(T+L+)`.V/T/\.P1Z1N344\8T9V9^8T9R8T<`=J:`>;8\>Z=<=h=>>=Z;`>AV<>>V<>=d>@F?B@>B^@?R@ABJ?;V=P@X?>VAP>?V>XC@@=@>R?V;\9R98\76b9`58\4X5N34X/.-.+R+)V--V+Z+Z*'Z*'X)&"$R"$F" VR! !JRXTVXJ^T^ZX^\bR \ D N \ b X P L Z PX V l ^NVNZVLb`XLX`TVV`lLVX^ZVVbVXXNhVRH^ZXfjJN\X\jZRPRRbTHb^bXLRXTVljZXbT\X`dZVXj^^XPhV\P`XRVPZfXZPNT\Tb^`Z^ZD`ZV^VVZ`RNVbJ^PT^PZTTRZXV^ZR^<T`XZXVd\Tn^hf^\d`dRR\ZdT^frFjRXTdfT`XRXXj\V^Z^PbXN\XDVd`ZXZPZLPX\V\bPVX\RbXTVZ\XRVTZRRj^R^VZZbXTXRhXVfVXZNR\T^PJ`XR`NVRR^bhZJFZJR\^P\ZN\PVNTZNXdV``PRZJRTT` h X N X P V R J TR P ZRRNJ\^ZN`XRVfTP ^!^ #!V$R#T#V%T$b(%^((^(^*+,V...P2P35Z5j646\:6Zb>L=T=<`=R=<8=b?>R>6Z8T8V9R7=677\4b325X4533\2X2\1-^/T-d10/-J.-T-J-.R0Z.T/P575426d8V5<\TAB\ABFbHKH^JVLRIJQbOHSTPVRRWSWURVP\WT^VXUSVXYJZ^WPMP`OPJNPJMLXOXKJKJPKHNFFXFADdCEZHTJFXHPGZGNIIEfFPG@@GXLEHXJLMMLTPTPhPVVWTU\XVWU^VXY^UZ_`\T]Xa^\f^\]TZaXa_X^Z[Y\]XZ^UJSTPdPNNOXOTORfPSRXWTUZXb[W^VPWYTWRW`SRZTSQFTVRTUZVWUdZ[\__bbVfRcbdV_^L[ZX[XTXQSTUZUVUUJTSXU^SZRHRS^ONONNVMJFMMLPSVVYZ]N\_Re\aRhbhNdecXdPgJ`J`R`[LYXWWTXJZVWHX`TLVdR^URUhSUZVTTTYXTLVUPTUS\VSVX\ZWXV^]T\`_^d`gf^ga\edHd_`\XTQO\P\NJHXMJONOLXLNNLVOZQTVUVYZT\[^\NY]^VTXUPQSOKJTJJHHHEEGJHHJK\MPBSJUTYZZ\P^N\XVZZXYTYZ]dZVNVUUPPRN^NXONOPKLJPGGJGGKPJVIJPLVJIHIVOMZLNIMNOM\KKVKLFNFEEhGZGXG^G^GEZERCDB=X?@b@R=AZ@R>>^CPCD@@BE\HH`G\KRIMI`LTNFOQRRPS^RTRT\ThQSMMTLJKdIJ^GDZDGEFDRE^HEJJLLJM\OZLM^QONOOMNLNL`MNdPIPMMOOVOLPVP`NRPK\MJNONVPQQPPONTKLJGJfL`JHIZMLMLJJRPOPXQFQXTTWP\befaXc\`Rda]^P]D`]RXRVTTTSSTRPjONRLPLZMJTLKJMJKIPLJJL\LFJKNOSSSZNWXWY\YN]]\^Z_V_aJc`N`dR\YVX^XjVUBURTQQQPTPTMLKKKGGITKHbFDJVJPMNR\R^UNTTJVX[X^TRZ[XV]P[YXX[\]^\R_`\P[\_Z[Yd[ZYXZZVUZUTQFOJ^LLXJIK\JKXMDHDNBE`DD\DCH@REXCCTECPIfCNHIGGfKXKKNXMTNZLPVQSRQTULWXXRX`TTU^V`YVYZUVSdTTQV^RQS^UQ`RTRN`M\MJNLJHGZKIJHHBFdFPKECFZAA>P=:V988\:V:977b54742^5X56N8:8X4j6d67P6N6R677R7P78Z::P>>^=<\>=@J>?X>V=^==`@^AZ??L?P=jAH?Z@XE?\=@@X@?L=^A?d?\>?b?<^B<<:Z678Z;N:5X77R53T4P/>...`/X-+/^0h+Z+Z+T)N)Z'(X&f%#N$d!#H!X"!` PZb`LZPBZfL`Z \ J P N J h ^ TR  XTXHZNPJ`LXNXVP^^fbV\VPZ^^`VZhNPTVV^RNVdbXXT^XX`VN`XJX`f\TbRZPZ^P^^`TZ^^ZXTVRVXPTX^X^JNVZdVRTPTP\NR^R\NJV`\PhDhDjDhbTZdjRZP^RXTRRTPPZR`RXHRRn`d`VXT^Z`bV``JNZ\V\bhTjHbdZ\bjZXZfVXbXRXfPb\\\ZfXZhVRRTfPXXRR^`^\`PRbJb\J^VRRTNZZX`PZ\Z`PNRT\dX^ZdVZT`^fZDX\`HP\TXhXXRTZXVPdb\XVX>X`XXZPXX^ZRX^B^JH\Nd>^FVDlXJfX`JbNb\\VfNPb f L X P Z B ^ b \ X P\XXPPNTLFbl\Z!d!V!!%R$J%$Z%\'&&V)V+,Z1R..X/b13898N7^6T9T:T=9^8R::::R=`@?V<:;;R=?A=R>>N?@><^6\6J4L5N5h5V2T243L3\6N10X5Z2f/V-/`,H.,X,.F-,X0\/0`20X02L2L44H989:T:;d=N;@X=@NBbBAEbHGKNJXNZKPbPTZTSSUZVWXVYWW[W\UbVZUXUTZSQROONOhPVRQVLPKTMHLNJHVFRNREENHFJDDEHH\IfGTHRFRKGFDFGE\JRJXJKZMXOVPRP\UV^QZSTWXTUYXRRWUXWYY\[bX[\[[\Pe]^_NaV^``WYWbWVTSRPRSOORP\QfTRUU\RXVNWNYRVXNVZVTWUSHQRFRRTbTfVFSZY[\``aPeePfZ?T>^?X?R=@>>\@?VBCD\GHKGHfLPOO`PSSR^RTVUfTZVTTQ\QPONJHIEPFEFCNDBTERH^MJVLDOJONVMPFP`PNQRQZNMVP@MVNTN^OPNLRNQOVPS^PQVNRPOZOLOPTPTXRPKLHdHZGTKIKTK^KOMTKQhUS^TRUbYfX^]P]jaXbcPbTdj^`]P[[PYXVU^UhUZQTQNRQTOMH`K`KJFILHbK@MZKZMK`LMQRbRRTTTVWXU\T`\ZXR_]`c^^dT\^ZZZWXFXRTfU\VSUNPbPXRPOJ`NRMKI`GIHGI`JJZJ`PMTSSRST^UNVWX[X[Y\ZX]dZZHYH[[Z_T`_^YX]YZ]P]ZZZZXYVNWRVQMNNKKMLNNKGXEPG`F`CCE@HfCBLB\BATDETFGfFZGFGI^KRLZOMKQNPTPTRV^UdT`UWVWTTUTSRVW`URVRRTVVXUPSQSPRP`PNLMLJNMNJPHLP`MHFGFEXGDCND?T@>X<9T;:7ZR;T>?<=X>>b=>@?@V;N=?X=?X=X<@Z@@\?L@=XANBd@?;Z??<>XCVAP>B\@PCP?B>=X>L>`?::N7V:NXJdNLFf^RXTVbNdXZ``fRP\^\RVR``NPTHZTJTdXXVDHRhfd\pVjRX^\`XdTrXVLTdRb`VhVb\ZN^jL^``\ZZ^Z`D\fV\X`dN^^lb^V\bRXXVRb^XV``RVXj`TfTTR^VVTZ`hdd\TNbdHV^\`^bTdN^XTTjZdN\NX\P`VZTZZTXbT^Xb`VXZLXP\TRZXXTLXd^Zd`^TN`Z^VJ P Z F T ` ` V X V^PVTN^TT^H`RF^VZV T"P"!!X$R#\#V&%(('*,P-l/N/\//j1L12557\7\7;b;89;N9R;9L:;P=;R;Z=?=:^==L?ZC^=B>>R<>;N=N`??R@CVBCdGGE\LVKPMNMPNZRdRTV^TURRVTVVUNQNNbOIIXJGHPDZCC`DCRFRIJIZMTLKXMMMLMLZPPOMNNMNONRQdQ`RbSPNQPMVRdRfRRPPRSZSQ\TSTPNPKJLFHdMGXJNPLPNKLOQTVPTZXXP^Z^VcVbTcaRbfV`_P^]XZXU^WZYQS`T^PXNMZLKIVJTKPKHHVLPMKMNMfKO^OOPRQdT\YVSNXXRZ\[PZ```PaV]P`\\^^]N[YYNUWUTNTVVUTQVRTRSNKVKIJMdLHILMbLQVM^PPQPXQVWUdWWVUYV[PZ`[\ZYT\Y[RbL_]_\[X^^_Z[[H\YSTTRRQ\OPP`OHLbN^QXKJGZGGHFZDPCACCB@j>B\DCXHGVG\EHNJbGVHJKMMXNOXQTMZPNZSHR^WVT\UTTWTVHUXXUURUZVUVTX\WPFT^PfRPThONJKXOMH`NLOK^IPDhGGVIGFGBA\?B@X=V;b:;>9545957`8b7N87b;T::V:J7X<645^7b4\9T7^97V;^>:B=:R<;f>V=^L>j=?>?X=><\?N?<;V>>\BbA\=<^=Z@X@^>RX^TdTXX\`p`b^bTXV^N\Z`db`^^XfXPJ^XXNJRVXXXf^Z`^`dV\JV`Z`ZdXZ^ZbPXXLXTTNhXTLhDVXX^VZD^P^\\fRPVZ^BX`L^T^ZVZXRTZNPZ`T^^NVTVZTVdNNdPZbRHbV^N\R\R\PZPR\NDTZTZRZVJNZTfN`LT^d^XV` H ^ V X R X L P bL\TRLTVVZX\VV Z D! b %%#$P%$R)%b&*V,,R-/1V22\2L64X787T8687T<9>;<^<;?:`?T<=?=?^>dB>A?b>Z=N;=9`><@T?Z@?VCBACEDD`MFHMMLQRQRPSVTXYYX]dZ\YXbZWWPSRWSTXUPOZOjQWXWLPPZNP\JKJNGHDdHXIJZGGZFFXKIRGPGRGRKXJGF`G`NFIPIN`NQPZQOTTSSZUPQFXXS^Y\TU`VWXRYX[XZYYR?@?P@@pCRGGFbFJ`LNNPTPZRPWXWJVRWXTBRXVSSTUP\OOLZKHB`GIF\DXEEZGRGHKZMMRLfPLNTRbMPLJPLNLZP`NDUZVjSFV`TUXPQQTdVRVVRS`VLQTVSbVQRROROJJZLHFHfHXGGGHLDQNPJSZRSHXhT[R^]`ZbP`dcdXaT`R`]JWNXVSRVSQ\QO^MOZLGdKbJHGG\KZKTMQZPLfMPQQbRT^URRX\VVJYYf\_[V]h`[Pa^ZYPYRYUVVWVUTRTDOMMfQPR^KTGEFKVJVJKNO^QLQXTSZSRRWVUTW`XVUVPWZ^\[\h^H\\[`````[LZP\^_]ZXZWXHVdShTPRPRXRPNOLH\HHTGTD`ECTA`DC@DNBX?@FBHdFF^H^FXG`HIIVLNXKM@NhOJPbTTRVSUZWZ`V^UV`TZVZXRWSXUbSXXV^XRUSWTRbPNM\MRMKMXLdJP\MJXIHE^GERARAB@R@A>P=P=79T;H9X75R8P76V6j77d7@8L76P76R8R566N6\58799?Jd@=R>X@Z@X@\==>Z@X;=b?@=>BZ@V?XA?X?@RC@f;h;D>fX\RZDVh\NXJ^X\HRR^NN\P^XNNV`NdNPjdZFXZ^PNZPbZTbjZbn`f\\V^nZfZLfjbbf^lVfPfbfb\jNdXZVJ^^PdZR\T\`RRV`\XdVbNZ^^\^`TNX`J`^RddLZb^XN\^VNXVXb`T\X\VRP\hZZZbFXVN\N`NfJTVbVNPhRVXRTZbHTZT\RXXb`N\bXRVTP\V^Zb\^V^PPX\N ^ B L X h X RTLRPNR^\ZLP\PR\XX !Z` !T"^#$Z''(H&f')Z(^-/^-N,`12V3153^66;`7A?=LA\?Z=9h7T88:V78T9:4211f5b4L..X2201L3\012`/^1Z/),,N1V/`/.N20V1Z1J2R65L6X:X:;`;=^?R9`=<87`46P77V85T76P96V:`9979b:6Z984d3f5L<=bAN=P=>T=X==<@@^=^@?==^>>@X?>>?`@BDV??=T>R>P==>;=h?X=@=JB^CDB>X=\>Ad=P?R9H:\;P7\6Z:78T5\6^55T3\2P0T1/H10.30/Z3H43T..+f/J./4L21./T2T12\2N4Z5ZX>^=>?R?=<;?P?RCN>;@n>N=AV?<=P><=b>?`?T>R?T???>??JE@XA<=XAR@9N?Z;P;V;<;@@?b>LAP@P?=TA>T=^:<:R=V:9^8Z8856^52P5\33Z23`3^1/+/2P1T00V3b2X0P21N..0/2V2-L1.L01X2Z5^9b7X99;::<=?@XABVAZG@B?DGEXGG\LIN`NL\SSSSRUZU\[[ZZVWlVTjRS`SVT\TXTSdSPTVUQRPKZKPLbK^JLMLE`GH`IJdIHDI\EDdCJZHF^FHLIJ\JHRJ\MNLXMRPRU^SZQdXW\YVUXVXW`\ZPXXJ\^Za^[b__\Vacb``T]V]j^_^Y^[TVUZT\QSXT`SQBP`RVURVYX[b]]V^N[[h]YLZUXWUWV\WY[RY\YXZn]]P]^`^X`Z`bhcZeXdRc`]L\[U\XVNTZ\YPT^T\T\R^OQZT`WTTQRVPSRVVS`UNUbSSRRQS`SPVZb[X[`\ZR]bbbZdaa\aP`Tba\^\XZZNY`U\VUUZU\fVTX[U\XTTTXVSWZWYVX`X^XZZZRZL[X\]__b`d``ccP`VfbP`N[]NZYTRJR^OMJI^JFIIIbJNNQThSWYY[\[ZR[\][[WVhVWVZSJSQOVMHIITE\G\KJNOTNVPPbRXTNWRWV[Z^Z^Z[Z]b[fZXXQVRQTFMKXKbLIGDIfDXGXBLBAHBfBEC@nHFEbBEIJMIVOOQKHOMNKDLZNdMKLOfNXQMNOOMLZOLMXPPQVK^HIH^I`HEFRE\DREXDAAN@^EEZCFINIINRSZUfW\U^\Y\YRYUXSPUTQLPJRIG^F\GBhHEVF^E\GE\GKLIKJMKnKNM^NHN\PZNSZPSW[WPWPXZVSUVUSUTXPXWLUYZURXNW`TLQ^NMZMLKJNHbHRIVFFKJKVMQdRXTTTHYR[^]Z``^^PbbFdXa_]]P^LXPYWSSSSNQOM\NTHMRJM`GbIVKZJIKJOZOQVMNTSTNVSNUbRTdSRUWVb_VZ[V]]XYVZVZXYRXVXZXd][VXXRPTNPXNKNXNRJdLXKRJMPMNMTORPROObQRSP\WXR_X\\WYZY^]T\P^X_\`X`bJaZ\[X[R^]Z\X\\XWU\URURZQNQPVK\MHKKGJIHbDFdDZBZD?@@N@BFBZB^DFFEVJHHM^JVNXKPMVLMNQ\TNQZSWHXV\URV^U[`XVTTLWXWYZW`VWV`VPSWVRRRSPLTKPLbLRKRLGFZDFHJJBGEBA\BB>`@<=86L7N794`767Z68X:`:Z97669V;f5H799785:879X::;R=V>X;\>@@`?R<^<:><;`<^<=f?N?dAR@X>N@T<>CT@`?^>A>DX@T=`A>R=X>=;<>^=>=>d@@>ZA>BXAPDNEXC\?T>@X>X@=d:\>T<;h;9X7X75X496X853Z2X2400-/`02-/Z82V21b00Z0/J1V2.-./R.R211`:T8:T8R9:><@@CAVCCVDBBN?LCGG^GFLGM`KKPOPSQJWXYTR[\YXNZZSVWTWTPNSUXNV`RVSUSUZSRQKLKMXLJ^GNGGNNIVJVJRDJERDEFZEFVKFVGRGNLbIXOMLFNNMRUSXVOLZVVYXWURWUTYTZVXLYZX[L`V_bbJca`caVa``Jb^^L\]ZL]HZZSRpPPXS\UPTRDPbWNVR\T[ZX`^\\Y\ZXXZTYZUVTWYWZ]TX]V_[R^_X`Vaa`FfNdXfPcTdc^]YTUUYSNVbWhRX^WSQUbSZUXTSRRQQLVPTU`QLXQQQTTTVDXWZP^]\^aV_bbbcbe_`b_`^a_V[YXLWUVVYDVLXZZPVJ[`WWY\ZXXdZVYJVbW^VPXWVYZVZ[\^`XbR_Xd\bbLeRgZdd`V`\XYXV^UFO`QLLbIHdIFKTJI^QMQQVVX^ZXXR[NWZ^Z_^[[XLVRWhT`QTQNhN`MZNIKJZJKOK`N\SSTVXRYR[\\\L]\f[\YRZRT^SU\TSS^QZNNL\KM`LG`FLFFACZFTDREDDEZDTCXG^HEFI^HP^NRNL\NLIXJ\JdKFIJ`KLXL^QSQTSQSNQZPFNXQDN^PLOIJXITIIdFGZAFEFD@F@NGG^IH^IORRSVS^XWfZYLYYX^ZTWXZSPSQLJTFCDVDdEEEDDXCNGFdHLHK@KPIZLXI\MVNLOOS\RVLVXUWLYR[`TVVVWX^XVXWPVPTXOVO`KIGVH\DEXGnGGIKOLOPUJU^WWZ`\`_]_`e\_T`Zb\V]V\P^XYWTTZURQRRSdORKJL@JLKHLKJOHKOPQQQPQDTRVTLTPVZRTRX^Y]][[TYZYVLXJ]XZ\\YT\XZX[YXQPRP\QZRXMdM\NLO`MLfLPOfMbOO^RVRRRQZQ\SUTURW`X]Z`[ZZXYVX][T_P^X[T^\^R_`L`N_Z^^]]YVWTVRVSSSPNROHMbMKVI`H\GIDTHNFEB?R@CABDAZDPEI^FNFFlJJIMZIJ\LQbNRPVQTUNTSTVSXSVVW\URVV`YUJTFXTWhUNY\URRPTQVObPL\PMJJKGG\H\E\IDGBDNB@PAR=Z>:896^8d86\>Z<:69J7Z9T8d866T:9f7b9R56X8J8V<97`99H<^:<<=Tb?R>T<9X?^;;N?A>>@TAT?>R>`@N>L@T?@V?@=X@TB=P@RA=X?V>=B=R??=`>L;\7T98646b4V3R2d51`0d/.T-*Z,((`(R)R&J'Z(J'X%T$`"`#" b\VZFRNZ`T`ZFZ`J\bHLRJP RX X ^ D T \ DdT\PbZh\ZbRNR\fT\TVVH`\\`X\PRfRX^RF^\fVdPTb8fbb\XT`PfbRZX`fZ`PXZX^ZZV^\TRNVdP\JVdP\TXXZLXH^RBVJ\XZTfZdJLT^\ZdVXRNhXHTZH^bZPN\TF`VPTXTRX^Xh^\ \f^PV\`\\bhXnRRd^NnR^TZf\XjbTTLXZXVbRXX^XfT`N`\^X\XVlZ\Z`NV^\XbZ\ZXVdPVNPdZ`VZT^bRfVZ^\RPNRdT\^^\VZTTZRVTJbRbXHTX\LXNX^N^fX\PdfVbfXXF`dTHLXZT^VRV^JL`^RdV F T ^ ^ V ^ X R N Z `\\VXbB\VZRXX\d\Z jBR""\!T$&#$%X''(++^0.h1J3R//15T6R6V68^;Z8J:h9\:R8X:?RA@T>X>=?R@@VCXA@?^B?N@=Z=N9>9b;:\556X73T3`4X0R4/.T-\.`/2P/4/X/0V14/Z001F3\,^2/R1.V0V15N6`5L7597>f@@B`BR@dAF`DE@B^FH`GFHGHXJVM\PJOR^XTUYLVZZZ`WZTXSWPTXRP8TVUVRTQTJVNXMJLLII^LPJXGEXIZGHD`E^G`CGFVJHEF^FXFJJJ\OZK^K`PQY\XZYRZTUV[DXXXZTX^XXbZXZX\^ac`La\_b>edTaR`N]\[[\\Y^WXVPUfQORSXXbSWFWRUUWY\Z\T\ZX[[LYXWVZXZWU\Y@XZZ[][\\_]R_^babfP`bcZa\ZZZ\VVPVTWXU[XUNUUTSRTSWVTbVSXTdSbSXWXTTR^TRUU^VU[VZ]_\^T\b]^a^aff`bRdJ_]^`a^^J^ZWXPXRW\ZP[]Y\PXWXNYdZ\ZZZZXVXNXVWTXVZZZYV\T]H_N_^^cTab`_dggeZbcZ`P_XNWURTSJQdMRLXJJLGXMVKGTNXRSSLWTYZJYYYV[V]\T]ZWUPUT\SZRVNNTQRL`PJRIVMVJINMTPORUFZZ\^\Z_aV^\V[PZ\WPSJSTNON^NdLBOI^KZLKGD^DGXBCbFdDLGFDXEnGJIPFHPFJIIBLVIJOVLfMLHI`IRIHTIJ\JLTQOMPPBRdTTTSSRPOMVNIMVGIVGXECRGBBNDJBBAFXDfDXFXGJMVNSJTSVPXTX\\^YZP\^WTRQXNIGDBVCEZCRDB\CCCJDhFFFF\JIVHdJHKJJQOPhU>STVPXPXWbV\UWVWPWRVVNUZURXXXZUJTXXUUTRPONNKZLIJGZGITGEGMMVPRPQRQTUNY\][^da`aa_\]P[`[\[>ZVXVZUSROK`IRLTLbQXLPNKJLZNLNXOO\SfQZRQQbQNQO^TN`TVRXXXZZZHXZZX`ZfZZ\[^R\^^]Z\\bY\[RVPVSVORQRN^PNKNOK\LRMNLPLdLNQfPTPPQTRSW\TYRXV_YVXYTWNYh[\\_\`T^^_^b`aN_T`\ZYYXYVPTRQQ\PRNKK\JJJXJ`JPJ^GGVGCXBATA^@ADBECFDFfFGGPHXJJJVNJKMSZSPSQVTTURQTUNVZUWXPVbSV`WRYXNXnWfUVbTTUURSPOXNLOJMMZNIFGXGHHHbEB^BZBVDFA?X<:;69T8566V8V9R8F865P5Z7V9T555;8:d76:R8^6L67\;88;;==X;=\>;@JAN?^>=>P?H>>>=d>?>>VC>A;@>PB\>J>@VC=>X=>T@D^>@Z@`=9Z:T<`64T5437R2Z1N24.T-.Z-h*-,^*)(T('L&\'%'"# N"V" Vb`PTTbZZfN^LZZ\HFP  Z ^ Z d ` J L H b ` XT\bXHLR`RXNLPXPJ`fV\NZXPbdN^p`Pf\ZV`Lj^NLbTX^`^VZZNTZ\T^R^NXfTTfVT`XTbNNdN^^ZXBPd^VbPbR\NZ`X`^XTXFXT`^NbXLZT^NV:Z``ZXZZbLPVb`VPdV\RT\J^TTTRTZPJLZ^TLVXbT^Z\ddXh`dTNhVPbbfL^XhX`\^FdT^ZZLR\NJPLRjPbPX\TRXL\R@VXVL^\PRX`Nb\V>n`f^Td\Z^nLVTPX`\FdjJ\XPRVVPF`\TJHT`LRLZRLVTXX`TjT`XR`XNTRNRZfTZTTTZ`ZZVV``ZX`dXX8 d ` \ R P \ PbRVTVN\`XRV \ !"%%X'&N%b)P))R)\*Z,F0N001/D4165V6Z87;:H;8X:8`N>=@?>@ADZB?ZC>T?==;J>9>;:8V8\667N7P9`:5T52Z2<1R10Z-01T/-.T.X/P016`0`0D4F2^1R1T/.0X2221Z6V7V7T9X:\9;>P@A=ZAV@?CNCACEEGEDFMJXKNPMTRTTVRSZ[TTRTVUYWNULZTP\VFW\RdWTR`RUdPZRZOKMJJNLIXHIXGKJHXFGHFVEBHJDVFHG\JNHXG`KJMDLbLNXSQVV`XWXVhULY\Z[XV[WXW][X^`_R`b^\aba\eZcPa]\L\[YRZVZTP^QZRSTRXTWTYYWVXYX[Z\VWVWRVV[WYNXSYXY][T]bN_b]^\L^V]Vc^dcbTaa__XYPWZVV^XWS`XZTUbW`UVW`VNTUXTPVNSUZSW\RQUQTUhRUdSRXVY\XVXd\^Tb^_bbccgcVbXbL`X__f^H\\XXWY\\\Y]WL]^YTZTZP]^]]ZY[Z^YLXPXZ\L]]\b`]_bcccZd^ffghRcga\\VLXPVTTRQ\LHLIZKZK\NHNVRQTTWRZV\VP[Z`ZN^`]PVWPSQPPNOZQVMRQMLNObJKRKKORMLKPZTYVWZT^``V]XaT^\Z[XVXPYSOTKNTNNJLNLKNHD`EXEVDNBLFVIXGNKFDGHH\H\IJFrKPLMXOZJKZINKDFHJIPFbEGIIKLPZSQQ^XNTNUZTSTMNLMIHH^ERHEBJA@RA@@@fECNGXFTIMOPTVUXUYJ\L]]^^_XYWVR\RMTNFNEBCDA`AdA\@A\BNATE^DE^IETJIXIGNKJS`RUX[\XVXWXVTXfZXLZZVUVVUURVU^SR^QVOXOJJGVHTHZGHPIFI^L>POZPNQTRPQ`UX`\]]habcfb_B\\R^Z_XZ\XNVVURRdUZQOONNLTJ\KTLFJJVL^IMJJ\NMJONP\PRPJQRRZTRSNTRXUX\WWZZ\[ZY`[Z[P]`P\\[YXVSTTQPQMPNXL\OLLOLLVNTLOOZR\OVQ^QTXVVhXVVY[ZJ\ZT[V^\P\b]f_X_]Z`dbZcbR\[X\X]VZWTVT`OXRRLKNIJTLNKVKTGDZDZBBAZCRDPAE^BTDDAHCZEEEFJLNKO`JKKMOMRNPR\PQPQPRTUPPTfSVVWXWW`VLV`XXUTRUTTUT`UJSZPBN^NRZKJMXL\LBGFZINIDDA>LB@><\A:\78778^76b9Z8\:769T9b54X656V689X9Z585\6`76Z8T;P;Z7\=Z=V9<@X<=>N=@X@>V@>b?HA`??>?L@TAAL@???@?=AT@>TB?^AR?R?Z>;;:X8Z8645N5h3630N0\.`,X-,+^,V)T&(T(`''&b)J'$"\"" ZdVT ^P`HRXFTNT\LRXhZbTNPL \ Z ^ > T VZbPVXRX`H\^XJXVPPdVPV\ZdRXVV\XTZT\RVT`ZTb\NNVV^ZFX\^NNR^XVNXb`Z^hXZX^\ZXZ\T^Z^^bTTLXRXZN^^XXVLX`VPXLL``VNVR`bfZTVb`XbVT\XZV\^Z\h`\^hTfdF`FPTZVP`^TXTPXhJh\d`\\\bd`TZhbb>`PfhflfTZZXZ^XfZbR^LbTbfh`\RTbXZ^dVXf`XTRZ\RfZJjbXPNT\LdNVbdZJ\j\XV^V^ZXVR\TDfT^VNVZ\PbJbh`ZZLR\X^XnLdNbV\PLNbX`JNZVXRXRX\H`N\N\VNbXZTTXN`XRV ^ T R T f V X P N ^\ bV`NPb>bTJ^^^X\NfV!!^!#$$&L%%%(+*+R+f/j.^00`34l2T4\5R5d897:X9Z8:T99;>J=?>X?V??Z=b=V@P>ATCA?`?d?X==X:=;;R=\:8X7^764527\8V220210./00P//\/2V3.321V3\1\1^3.0R3\123V24d6Z68\99=b>XAVA`=T@D@PBTEBPHTENHG\GVFDG\HJDNMPRPZRPVUTWSV[TXXfVNVVXYNWXVZUbWJYVVRTOPBNNPXR`PHNNMIKGIIHGPGFF\GEETGXE\ERJPEZGNFFVJLJZLMTNZRSX^WZ\^VVXWP[WWVURUZWJ^@\Z\^^^JbT_acceFaTebb\^[X\dU^WTSNXNQXPVTVWSRSPWVRY[P]`VWYT`WTPXV\T[JXPZXZR`_NaN]P^_V\Z_L_a^cJa`Xad^^@\[ULVPXWWhUTVUXUdWVXLWTTXUURPVVZSTSbXVRJWVQSLVZTTVLZTVYZ]_^_XaXd\_cccHfda`Z_R^R`T]\Z^[XZLYa\ZV`XZ[\V[T]\\^]\`ZXZY^[]_\`d^H_PadacHg`gDe^hXfJdbge]][YUUZQOFMKKTN`PLVSPJSPWUXdYYX[RWR[ZZR_[\\\XTSMRZKJONZKMHNfLNOXN\MLUQU[fZX\aP[^^Z\\T]^ZRZUPUZRVPZMKJGGbHGKKKVGEZFVFZHRGIRKIJN^NIH`KXHLVIJIhLJKNbLLHRIILGGTF`GK\MQRLPMRR`VYZXUSXVNRQOXNXKIfHFGR@CPCJ@ALA@DDCVDFHLNTQSXXY@]X`H\T\Z[\RZYSOHNfJLHDCTBA@@ALBTE^BD@D`FRIXHHIVJHJLKNLUUVZ[XXjWVXWYV[[LXJWVZXT\PX[XYTVO\SROLVOZFXG\JGLGPMLNXM`P`OLQMRQPRTZYL\Z]^cbdPaVaa_\T[ZY\XWbWUhWTV\UOJOOVPNKTK\JLHKK^KjKLZKKP`O\RVPTRZTRXP`M^QXUbSSZTYR[\[[VZZ[XXVZ\Y`V^X\`_^[ZVZXZSTRSTUTPRQNTNFKKJXJNVNLZORNPNOTHQTPWUUYZXJYZYZh[^`a]`\Rd^`_a``TeNb`^@][\BYVVNWTUPPPMLXMZM\LLKTLLFIZDDBVBCA\BVAZDXHCVDCBDZH\IJFIXIJMdKKI\L^QQTP`SOLULRPJTRPZTTPUTXVU\UWY`VRXTTZUNXTVRX\UTVQVOSMKNPJVLPJDFRHIVE@\DE\AZDPAT@\:T<9X8<8`889:7^7H67V8V8b4557N566R97d4f;X87T76V9;R:8;^=?\>Z>X>R=fA>>ZA<;<=^@\?X>=d?>\<\?R=A@R@Z@=P>X@D>C?ZADBd@?TBTC^@VBA=Z?T=?\?T?`BCD::V:\634D5`7`63141/d0V,`--*P-T*(R*Z(P(R'%($J"V#T#$!HXX\L `TPVZXVZRTPN\T Zf Z N X b T H V V ^RTdjNVXZL`\NfZRlfVPZZ`f\V^N\L`TRXhT\T^V.^R\XX^^TZXZTbfdVZLVh^bTNfXVTRfLTTZV^ZVZ`fP^NVhNbZdDPXZLZ`\T^LNPZPRNXbZRVTLZ`TdTTfZHZ^HJXf\\VTPRNVhJ\X`ZVdV\T^TLJbLLR\d\\jZj`XX\ZbTN^ZBLR`T`b`NhZR^XP^Rj^RbbZd^FbXRZdhd`L>ZLdTXZZPN\NXJ`hFfPTZXLVVTX\ZV^Z^PZJLP^8^^NL`XVbN\jTTZX\ZLPTTXX\LB\XTVJVNRNPNR\hTR^\XZXZRXTbLbPXbPT\NXBR\TdVH`NVX ^ T P V N f R XZZZPTVLbX^^Z`dP !`"N#X"#&T&X&N(()N,Z)`,-J/b-Z3^1V043835^6`669X98R;X?\>>R<>@ZB@VC?<;X>B=:R9:R7:8X6;<\6P956P43042N3R3/..L/^0V...22421J2V-R01T2\1Z00R3V3f3N3X6;`::8;P<`9X==T>Z=X?=>\=\=@RC4?`BRAND??B@^CPAAb@A>X=AF?N=BH>R>>>=95V6Z64L24334R0T1T1.,V.-Z,,(`)N)'P(V(&%Z%Z&Z&R"#l!Z\VZRTVXbVTLdTX ^ L ` ^ d b L P ` ^VbZXX<ff\LTXPRNZPT^`L`\dZdZd`RNTLVLRRLXLZ`JVZPb`XV\^lXJXXZRRZL\XDXTRVLZ^^bh^TdPPVZN^bXJTJdRPXPVRRr``JRV\dXj`RbFdVbfL^XdRP\`JZVNXPZPPV\NVbRPdf`Tjjd\NfdT`fVVZDPZ\jbdVT^jLFPX\Z\RZTZTPh\\TH`NZ`\PXZNLTT^ZTZVXXXbJXJh\TZ\\PbFVZ\dRRNf^dNV^RdVVZ<^Z\VbT^bZDPZ\LPV\T`NVZZbRbZbTZN\ZXXP\PVbLf`HbZVX`\JhNLV\^P XV H V V T HNPLXT\PT^Vd^ZVX!Z "^!#N$%$&')'J*^**T*,*P/0V21`2^453b87d8985N69:9`:==VZR>=X?TBV@C@>dCT?XA@<<9b7765`79664X335Z2222V1T20`00...J1N.1230\44j1P31N62\0V3P5V4232P98V8:8b;?Z<<:@^>d=T<`=ZB==@LV=b=R=@L>NBR?JAATB@?TDDB`BNDDHBhBb=AA>X@?V<6AT@ZA\>:8^74`82337112V1//--*T***(\()&`(T&R&J$#X"J" \ fX`nZLTR^`\ZFPXH T N X L T H ^ R Z B ^ VH  NTLZT\^V\bVLTh@dT^pPTPXfLTXh\\^XRV`dNN\NV`R`^ZTXPb\NPXfXVXZlZRRRZV`^XP\TdTRTTRZTVNVZX^VXVVXRX\VDfXT`bX^`bXZh`VLT\NNLZ\XZZbDXRLPJPXZZ\J\Z\VRF\T^ZTTR^JNRX`\L^TX^dL`X\\df`b`TZ`VfXXT^hRdTZRbhb`^b`h\\ZfZF`b\JZR^d\ZX\XZTdX^\LPbVTZ`Xl^X`NXVP\XZXB`RbL`bVbRRVPTLVVR\Z\bRVBFT^HdNVTLLXRd`L\N\V\VZ^N^RRR`ZVTRTT\RZNPZVXNXfV`ZJT``NTh V N H \ \ \ B P RRXNXFbNdZRJ`\^RRN!X"X!R!#b%T$#(H',V+N(V+-P-*F..3D/0R2R7346R5R8\5P689=T9T?@f=:V9Z9696N8b;j56d5P531d72j413F0T52R.R.\/02/0R03L4\4L425P23R3f4R21T353h226N;;N:P:\<>L>=\>>fB`DBZG`CGFHXMTJZN\Q\PQOPRPVDUSUPXWdWNVWX]FW[RWWLUUTSUbVRJONMKLNNbMTJZI^JNGEGNGbJNHDGRKLbIHKbHTFJfLH^HIGOFNQP\PRPU^V`WVXZ[F\`XXT\X[Y[XY_\[^`^_cbgZgeecLeXfcN``^T^\ZPTXSW^UZQTQROXSRfSVYTQ\TjYVVNZnVNYRZRWVXNYZ[R]V\F]Z^[\R`F]8bPc_a^bNaJda_X`cbT_]\VWVJTTUHUNWXTSTU^UZRLRPXSPXQTRU`VXXTZVRRQPTVTV@XT^Z\Z\X[H[`_RedePcfLibchRcbPdRacc`_\\b\R]VaR`j_^_V\`]HaP]]]Pbba`^ad_``]d@_R^cNafTgRgNfjRhg\eTbcHhgZdLdc@`Va\LYUPV\VNQRXTPQTQNORPTSNRTWRUYRW\Y^V]VaR_a^J`Z^V[bYTSVQ\OMhPdM`QLZP`KTMVLNPPR`SSY[^^\```J^YXYVTPVOINGRHACBDEVGHXGKPI^LMLNQUUBX^WSTV^RSLSLRQROKZONIJIIGPFETJXGbIVLMROQbUSPXd_V^Za]T^[`ZTTLTTSQTPBIGDZBE^B@Z@BF?@>>XAXC\FINTFTW^^[dc``Tcb]Z\JWVPLLJH\FFAJ@>N@D==VC@fBALEFRETFJJHXKTJKOZQUVZWNV^YXY\XZYXX`_WVPYf[V[ZRZJWHYVRRZOLMJBGZGHJJIINKHPKJMKOROPVSXU@U]N^X`T`_bHbd`Pa]T`V[ZZXFZTUVZT\QNjNVOM\MONNQdPVQRKNLVL`LNZNbRXNRRTPXNXR\QPHU^SJVXVNUh[YW^YP]H\X[ZT^YP]\aZ^Z[]]XVXWUVW^RPRTQNOPNMQ^OXKRML^NML\MXPdNOPTWTU\TTVXTX[^LacbF_cN_a\``abaBc`Pb]f^@XYWUWVWJUPOPQLOXM`ObOLLHVEF^GDZEDHXFJGDVGN@XBDBFDDDZGPH\K^GMZLJTMVMJLMQTSNQXPLSSSbZW\TXYYWV`YXXXWNUVT[XXPVTWVSTXOPUVPONTJFZKJDHPIGJEXDHD\CD>R>R;\:<98X8R8P9J9X:\;5Z5N5j4P33Z4L2N4546Z8R79V79^8Z8^988:P:=N;V;V<=<X>>>V@^?>ZAABBBCC\DEdBAVCR=@TC>V===?`AbARCX>B^>RA<^=:^76^4`4R6Z67Z69\5T3P13\2P01N2X1R1X0-13V/^3161/N3T3`43`4T64Z425R52b42V54V8;P<78;Z=X?AX>@LCDVEDCRHBFINNJLKOLT\PPTTSVUUX\XZWUVXYR[Z`VNTbQPTSRR^SQMDMXOONLZJTKLRGZJHVKFVKVJHHGZGILXLNKHFPIKJFMJTORNMOBOPQS^VLWZXWV[\YY[\]Y[T[_d\X]_`LdbNfi\iePeaaRb\aR]YVVTXTVTPUXPXQ^QNVNSNUVVVZTWNTTZVP\T\XfVWUXDYbZT[X\ZZ\]_TaNb^cN`XaFdbdicbdPaR_\V]XbYUNWWVUVYJVSUSLTW`R^UTRQRFRRUUXYXVTXWUWVW\PYXYf[[]`\`\bdddefBgDg\e\c_XbecaZcf`T^bac`^^a_d`^J`^V_abX``aR`Zab\d`ab^\ebLdgXeffiaXhdiff\beac__YFZZRTTSHPQOO\RZORRRTSVWL]X]__aVcZab`_\]U`TSNPLPOTLLPMHMXQZO^QUUWXV[]__h^b[R]bXVRRSLLMLJFAEbFXIGFlFFTIXN\MQQRTYZ[RY[YWPZHVUdUTXSPONOL\KTHXFEHE\GJH`JKMLPPRRXWZYP[T^^N]R^YXRVZYTXS RKENACP@L@^=^@=V?Z>b>X>?BEGJRHR\XWVZD^Vb`dXbe\cZ]XJYTQNXJHVFEhB?V?TX=>X?B@DLF`JGPI^LKDODPTRRUVW`YhYVYfZZ`ZYYYN^VZR^N`ZB[\WX^RQOMMVIHHRKFK\INJI^KZLJ^PPPNVTUTV^^bRgHdZbe]\`da[R\WVZVTV\UTTZQRNNPPPFQZNPNL`NPLbLRMJLKXL\NLLTNX>P;;<9;^;8J9P:\745\8T3\5V4R3^657735\6F5f7X;7F89:Z;=:>CX=Z=V>>@`?\=^>T?@R@^==V:;R=@>>NAbDCl@JB\A@ZEXDEJA?PA@N?XBVAZ=>N?<>f=L?^:V:6X6X74351H220V3P1.b0Z2P-X,,('X+R'(Z%'R%P#"P X""b"R V T^RPTTb\PXPZTTV^T ^ ^ Z d Z T R Xd FXJXPVPXZLdTRPX^`ZJPRRHT^L\RJRXL^bT\b`fTZHJ`VDZVd^JhPZNb\^Z\Tb^L\P\R`\TbTTVZTJR^Z\V\bVXLRVZZNbJbVT``hXZ`X`\NPT\`b`VZ^TXNbR`XbVhhXZLZbXjXdXZX`RTZTX^RTPTTZVTXL^TL\\f`f`^V^ZbX`^dZ``fdVfV^^^`b^\FVR`V\dVJhPbVVh``V^RZ`B\\^PVVRZDVhRNbTdXVPRXddR`ZR\dTZXZXddbZ^\bXR^VPbLHXdVPRZB\\RXX\RZX\`PXHPV`^\RZ`VVb\`P``PNTV^ZdTRVFR^PX``ZPPPbXNPdX\\RN^XZ^V V T N F Z F ` T T PN\T^^\dbLPJ^^J\RZNRNVVn^ N "$#$%X&%'^*L*)R,..--^,,20T4f3L4X4435J6V797d;`;N:89r:X=X==;;8<<@?TBT@A?A@T>\@@?NAZ>=T987P9\7Z5X8^87V6335Z24Z40T3R//N5/^0/Z.053<0`2X22X2J4Z6J6V2271d1b3N3:7868:8H9P;b;=>^A@A`AbAE\GFMH`JLMKRMfPQRTUZTUXV^\XdW[WhXLX`ZSJYNUSPQ^RQXTHON\OKZM^PLLMKHfJPGGZHHMJTKJIHGNLHMXKIZJJ\LNHHLHIRTQPOSSR^XYPY^ZX]\WV\`\HZZV]`[T^P^][a_Nc`lfejLkkbhJg\_Xc^`X_YXURXSPMPZQQULU^XVFYTXLUfXH[ZJ[YV\WXZWX^\\ZZ^]X]b\d]`febddcZe\dZgHc`_Nbb\\\`Y`WSPRURSTRSVRZVXSZSXSTNOQZRUNYbW^XNTVbXXVWV[[\ZR]]^ZccPcbXdehgfRee\dTadaZd_V]V^`_`_b]\dJbL__\]`aaN`NabXaaLe\cdbebaaacdc\dgfeejfXgdbTbaRbP`RZRW@ZHWTURTTQSSQ`RURV\VTZLZX_YN]Z`R`Ha^`\bbT`\]T]`YNYRTQhONP\NLLMNRPPSXDWZWZ[ZR\[``V^]XYYEBB\CNFZFFGXOMPNQQPTZ\[R]f`b`Z\V\YYTXFV`ZXT`VTUPSRO\MNM\IRGdGDITFXHLVMXPVSPYHZ]]Ta`Xd`\N\WhVW`S\QZOHHXCBA>T><<\=`>X=NBNGEVIMR`XX^aVcJabcVeTc_T\UTRjPN`MGDbEPDA>?L>>F>VA?@PARDTEGdJNMLMRPSPSRLWTYHXYT]\\YTYX^\WZ]J[X[P[XVXUVVRVKNKHXIZK`IHHKNJKTJTNHPPPNXPXWXR_\bhaNbPbPcTdcPaXbX_Z]ZYXWVbSFUTR\ROOVR^RPPN^PRLNVLNJRL`ONMLNPXNhS`SPPNOSQVUfZWf\DZZZf_Z`Y\`^P`V\^_^b\XZZTXXV^XWSTUSfTQZQNHN`KRLJPQN`KRNOMXNMbNPTRU\VVWbVZW^X^X\a^`_^XbX___`b_\^_Z`J][XYXZXXSNNXObOL`PLL^IEEHF`FNGNGFEHVEFZDBH@BRECEFGLHK\JXHXMRMLMNNPNM^LL`NZQSQTTUTXb[YRW`VZTWWbVXZUXRXHUTZWP^UTRRTROPTNKTLLJHJKFRFFEC^EDd@Cb=V<>=:^Z<\@T@?AbAR?^?;=Z=^>TC?jBX@^@P?dA@^;99V>X;=;Xd?XBb@TAT?XE@@BCF?P?X>987T87V5R34^673Z41^423\1j22h23T2V1V20P2342/1`3b46T9R46V563J8T2\3X53N799R79=::=<@?R??^@?LCVHLJLIJHJlNLOPQSUTTVVWbX[WjXXZVVNSVSWTPVQRQRQbVROMKNJIMJMIILKZMKXIOH`FfLFMTIIF\FVFTH`LVJGTJRJMXLJPVQRQPVTSXW`\ZNZdXXZ\[J`Zb]V^f[`Hb^ab\gPkilRki\cXfdf`c`\WWUUONUO\RTVX[XYXYRVUHV^YWVYY[XVUZX[VZTZ\[^`bfViHhVkXihheddRbaaZWWWNSTWSLWNVXQ`RNVbYNTUTRNPP`XNUH\TRUTX\ZWUTVZR[]R\L_R^`__NdbHgk\eTk`eVebc`aZ_Pc^_Z_^^^\^daPd`Vd^a^P`d`aNbaHcddhgZa\`J`abdbc^cbRigJkNi`jhf`fVeddh`\\]R_PVVTRRQPXPNRVRbTZTZT\WR\VXY\]``aLcXbRcfX``^P][YWVZTURN\OMKL^TRQRUPRLVXV^\[[[\P[\[XR\PWTPVTVHPXLVLHVFFPB\FVCGIJTMLQTQNSTXWP_]Ta`cZ`_Rb^`\VYVTUPTQXSJQOJKLGRE^DFDBZGJMZN\TNVU^][_^`dfa^]\[\[TYWjPPPPIXGCB;PVE`BFG^LZNS\V\Y^]_ReacXhZdaZb[`XXVQXKXJFE\HBB@Z==P;??X>?ACXE^GH\PbOTOOONVUURVWWb^[H^ZZZ\ZX^N[T`[R[LYN[V[TTXTVMMKTMLMIXJHJHbHGRLJKLKdLHO^Q`TVURY\X_VbcZbPg\f^dT_^TZ\^R]\YX\WVTTSNNQRQQPLPbPVMKVHVKKL8KXKJMMJRXONPNZO`RTTZT`SVX\V]ZZR]^_d`^\\R]`_Pa[\bZVYPZXZVWXWVURPPPMOrMNMdOLON\NLRLfOQLNMRQVSPPRVZXVUY[fXV^^^Zb]]V]_cZbXc_V_P^`N_]]L[HXVXUVdTQOPORM\LPLKNHdIEPFEVEXJFJGXFTEICDT@VAVCVJRINHDKFMPGJJKKZMVMHKLJNR\VfUTdVZSPSQ^WVVRZWRTTPUTVZRXV[TZSWVPTLQ^S>QPR^ONKXKKKLMLFG`DCB^>Af>T@\?`;9;Z;T==;`;9T=X;H>X>?NBj@>T?LC@@^?@;>P<><=V@BCECXCDRBBJDVAZBAL@APA?AA>^BN=X>@;Z;9999d86X5441V5T4T2V0//.\,*+(***`&&##"#!Z! J"r"R!NJB`\d\JZPVXJX^Tj`fbV TT ` R ^ ` j V P N Z LT P\TXZfNXXT\VX^X^f\bPdZXD\^N`Z^bXbRbL\JZZNR\dZXL\PZbjP^PV`Ndd``TXLfZ\`T\\jRNVXZ\TVRT\\dZ\\Z^`T\^fTXbX`TVHdZbZ\RZZ\HVVbPZ`jZbTVb\J\ZHd`dbP`NfZJRR^XLVVbHX`J^dXNdRZdVb`b\`dRVbZfd\bb^ZdXD^ZV\N``Rd^V\bPTX``\X`RVJbVP\XZ\`TPnX^\VfbNZN^XVT^XXLNNLXR\NdVRRXTHXP`PjTZLZTNBHZXVNTZnRZdRXXX\^T^VJ^VHBTRLZbNXTFPZ^T\LRd^RJ\RJLTPT X J Z V ^ R P X ^ L `NLTJRZdbPVHZRPRZ PZ!!T#R%R%''^&'R)R*N+V)R-B/../^//30Z33X53T6h577N77VV>Z??RA\A\?^?^??ZFC@>P==8<\876T7`6V88\75X3^3T13V121Z2T0R/\0b2/P00P222\.b22458\7254R42V6T668d:J:\8V;;XAX<\<;`@ZCZBPE?CGHG\LIKMVQLXNPQRTbTRXTX\XWWWXUXVJTPUTRTXPPfOQFQVRTPVNMIZLRSNMRKXJHVIMHVK\LRKHIFJPHHNFETJGPMZJHPGKZLKMMWSTSRYJW][h[T]T\ZT_\X_T^_^`a_RcdihlkPhfThfHgTe_]`YHWZUU^QVQRO^QVFTVUt^VYZXTSThZ\[XZXRYWFUYYX[V][b``PbXeZgjgVigjRmVdcd`^aP[TZXTTQSSXRZSRS\RVUUdYTUUfTPO\QTTFUTZV\VTNVSZVNXX`Z]Z^NaZa^c_Pb`deRf^kg@h`daRibZbX_]T^\a\Ta`DabchbcbbacJddddbXfcfXbe\cNada^dcdfhf\kXiXk^lmhPf\ceaT_Z\YJ]ZWTRbTNRLRQPP\TU^VLUdW\X]\X_R`cPadTc`c^Na`T`[V[H^XWUSQR`N^PNNPRNUVZXXRVN[Z]\XX]^WV[VUXTPSbTTPXLPHDEPE^FVDFD`GRHJLS^VU`XX[bNb\ac^fPfb\aPaR[\^R[UVRUXPSLON^GXD\G@CC^G\KNPWYL]`ehfXfLac_X^L\`Y[RRFNHXHVCFB@XAT;XN=L<^;X?A@Z?T?\<B@`CPB@?>=ZBZ=R@V=?XB@TA?=:\8V9\7<987`8F5J744P4224Z20^1T2L1Z3P221L2T0R0250R1\22N6L42^546X34L5`56L6b<99L_T__`aeZhbi\dgVfVbZaR_R`\bdc^F[YJ\^FbeFf^dVfbee`cbcjhfgNgefNcTcf`hRdPfdijTkNjn@ll>iieVcZ_]J\X`\[ZXRWRTRHQdPOQhRVBVVVXZ\L`accVfcccVb^V^\[\XNYNWVWQXSPTQJPZQVRUWZZX^]Z\\JXTW\YYZTRXLRROLPIZJNDbDFdE\FHXHZLNOTTXR_@^ZabPfdehZfVeZeb]V\WZYTNWQVMNJJCAJAA\CFZITMP\WWbbJbg^fRfXhfXfa_\LZ^XPVUVLIBHbFAR>=`;;?J>\?^?BDNENRMMXSXTVRbVRX[VZ\P^Z[Z[T]Y[[N^[[@Zd[YVHXSJONN^PJRK^MI^LLKZLfHJJNP\WSTWRW^^R`^aHbcZbddaNb^T^d]N[VY^YTT`WQRQVPSTQOZOTPMHMMFMILbKVLNOPhQRUJRTRSPXU^OSUZZ[\V`]T^b\N]__X_\T]XaZ`_XXZRYVUVWPTRRXTNZRNRPLN\LK\MZK\LNXMMPRHQ`RTSRRSWZ[PYVZ[Ra``\[\]P`cZdP_`V_`[\YZR\T\X\[WTW6SVRQNNRMMVM\LZJ^H\IdFJFFIFDNDDTDEX@EENJbGHFXIZKKKRIJJ\KJJGZLLPQRQQUUTV`VW\YZXZU`XV\UPZUSR[fUUS\RNRPZMZOMFNPLNIMdIEZGVEBN@=<;=N?V>Z<=^<;d?=X:9;f>;=Z>X?V>Z>>CAX?\>==>\;Z<=bD^C\ATABTBBXCHCZD\@BR??P@RDRAT?V?VAV@:^>;>T7L<;;\fX\PbNNNT\d\VRTdJZZX^Z^DJ\^NhNR\LPV^VXPRTX^XZZRZN`TXNTNX^VLVVV^VPVbN^X\JXTVX F T ` VXPRTBXN\PLXJX\RLHFRXP R#%`$%L''P)(N++R,N.,Z1X.\..T//T2f0P14P5T7H7577N98;9;;=^=F=?TX@VAZA`?@J>BTAV<>>?A\?R?KERBT===\:R>;N==<<:T98^856154H67\4454X45B35P7N7\:99:9>\??=;T?:V>^;;CTAZ@@BNCAZC=RCl<<>T?;88:L<88855`45020/T2-N-b,P.T+)X)N'N)P$$J#T%R N!P"T!\ "PHNZRVbf\\\ZVPNV\ V H \ P L Z `  P @h`D\\@L^JTX^X\RV\XRj`NRXNXb\D`\L\bfZP\N^XRPnHjX`\ZZ^``fb\XPRVP\V\HX\Nb\X\`V`TVT^`fX\\JPJ^dRPJ\RTVZ\Xb`bPR\V^ZTd:HbNRbLZNThFL\TTT\dN`^\R\NNX\V^BNZLdbNX^\tHfX^ddfddlhVTTNVZZ\bRbZ\XR`\TPjHPP`VflXN\V^h\LdLHZZ\^V\VXhZV`X\P`VXTb\`\X\T\TR\XLhR^lPZ\TV`l`XR^brbD\`Pd`VXZ`X^h`ZRVT^^PNTN`VNT^T\Z\\LR\T`dTD R N ` X d T V R l TZT\XXHL^ZPX\RhZ\\L!V%$%&%&N)(,,J,P.X,.X1X/01/L1`23R544`5V7V96h8;R::J<`;9X;X<\<==P?>Z@`A>D==@>9R>>X?>=b=@;J=\V=T?ADHOORVY[Rb\ac^h\hhhc`LbZXYXS\OIJEB?LD@^C^=N>X@?CZBC@DTFFJLLXOV^VU\UTWVWZVZ`^__F^V^T^P^Z]T]_[]UFWVLWRSbPLTO\ODP^KMJLJHLNKIKVOXRSTZJ[\P]T^P`_bVabcLb\dPaZ`P_[YWdTRTOTSQdQRTOMPZO`L`OPLLNM:LNNOS^QTRXQTSSPOUVXTVV[Z`^\X`R_b]^]b`L[Xa\_b^^]\[X\NYb^ZbUVP^VSPTTS`VNORZPPdKbNjMMTMdLOTQ^SPRURTUVVUDUR\Z]^_\P`\`_J]R[d]]\^_ZYRYNY]RYZLYZ\YPUVZU\QPOSONOMMbILHJ`HEHTLEE`GXCBDZCEFNHZIFEIHJJJLLKTGRIRL\PLKPPNTZRTPWPY<[YZXTYWJY`YVVTVRTSXUWXRTSJOOPN\LKZNVKNVK\JHGXFCZBNCC@R??LBV@=Z?X@?T@\AR@XCA?AA@T?V?C?@\AA@AVA\D=f=F=9Z9<:`;V<\XF`NP^ZFZXb^VFLJTHTH B T Z T Pb` Z 6^RZ\NP^HPVTTZ\\TXH^VR^^T!!N&`%P$'L'Z)(L**N.+,0,-0L/11d23b83X947:H;Z7;<;=R;>f=?X?>ZA?@^>f=T>\@@R@^R??TA@@bBEDD\EF`MKXLI`LKKTOOXPJORNR^TDTVWYRURVQVRRMTLXOLPNQOOQdTFTNMMFNPLNRMHMKFJVHJLZNIJJEK`GHEVJFGHIRINJHKMNbPVSXTSWVVYFZ<\_F[]\H\Z\N_^LbRa_PegeNjhkRnVjii\ddR^P\\]YhVXTUXTSUVSJUVUTVTYXVZUVfXTXY\[`W[Zb^\P\_f__VeXcRfTcPgileff`]a\PZRYVTZUXPDVRTJRTPRZS`T`SLUXUUTXTVVQTQSRTTYSQYXWVW@W^b^^``bcbdad_PdecgfZbd^d\Z[b[`YP[Z]f]Xa_Za^ecXf\gaddegXgXdfhgf\iXlLopniXmgjnliVknjo\kHoRigbRadd\ZZVXWTS\TPOP`PPSVTUXTZH[PbdVedNgNl^fiLdc_c^XZXXRY^ZWP[LZNUVQSUTRVWZPZL_^YXPY@Y\XYYXZYSVVTPN\KJIJJJGIHNMJQJSVXZ[P`PgeReiXhh\no`olThZkcTdc\UVSPKJFREZBhEH?BVCTIMVQbXPXb^ZfPh\lXnTo`olhjb^R\XX\RMbJLHC@>;;Z;Z:L;X9T>:^CCHLZQTVV\\\aTcPejehR_LaH^^[WWBPMLEVELCVCTAAV?RA=@T@jBRCJGTFbCHVKTRZQbTRT[VVVVXP\`[TZ[T[6\RZH_\\YR[YWHXSUSRXQN`PRONNNNVJJJVHVKJKNJLbOBRRQUYTY`X\B\X]`Nb]`aLddbaR]f^[ZXTbUPRSRRPNONTLlLTMNNKdMPPLLNPbQfRFROOZRPQRURVZ[H]f^Z\`^^^Z^]T`_\_^Fd]T_YPZZZ]NYfVRRhRPVP>OP\R\PN\PPNQRPLPOXOLJLQNTSWWU\ZVX__\^H\P\_Z^^Xb]Z\B][Y\TZTZZL][j[^Z\XWPNTRVTTQNUdOPKM^HLM\KFHJVGHZIBFDZGGTGVHGE\IEJ^HIXHHXKJHRIHTKNHdPKNRLMNPPRS`TVTPZLWVXYTYWVVVXY:TRZ`SRUS\XUPPQVQTLLHN^NO^LNFERFBB@f>X>P=?N=<=Z8V:P;9Z645T8P6Z54N5^2X5X7N53047P5R79V=:R;Z?==BR?R@Z??R@??Z;V>^@b@RAA=?>@DZ@\AT?^@d?P@VB?AJBCRA\BN??ZA<`=T;:b;<=X;;f8R7\8`8N5\543.J.-0R.d-,`.X,R(`)^('##R$P$"!"b!X H! FdVddN\VdR V \ R V T V ^ V PR T RNZVf\LL\RRDf`JT`HZT\hVZ\VXV`NbZVPb\N\T\RZ^^bX^dR\hdjhRZb\TRdZZ\XfFHbPj`PTTZbXNTPPX\X^VVVP`\ThR`\T`TZ\`LTNR^bZLNJT^J``h\XXVXVdT^\d^XTbT`XVR`ZZVf\f\RZV`^h^\RZdJ>PRbT^`Z\bPVXVZ^PnZ``X^\Th\VfX^ZTNVv^Z^T`LXTRNVXZ`RZ`PjT^V^X^dh^f^Rb^fZ`Rf^^\NNdP^FbNZZTbb^XVVTNPXXXXPJXTV^PR^`tn\XVVXXVN^TFVZZJJTZLJVPVZbLT\XT^T@\`V\NN\  Z X T N : R R V Vj V ^ NVXTNVTRHNPTRXbNPV\XXfPZ!^"#P%`&d'X))J)l,)V+-R,+.R0N/T0X.20R5X4\47\5\8F7:J::=8;;P;h;@=L@l?@?ZV;;R::T99\8Z584N41b53L1Z24V4B33R3d4P4X1\101H22J3X240V2//161X32524^54P5d49d8PR=?>Z>LBEdDFFBbGPJLHhLXNFIL\NPPT^TRWRWX\WT\VPTSQUPWRQbQNbQLN`PNTZRhRSRObQNPPJPSTLTMVKHMHMZKIGIFFVJGVJHFfENJXJVK\JRPNRRRSJVF[YFXYT[_Z]Z`[__^P`X]ReePbTggbmlXkn^kbgLgeLfj`PZT]>YWYXWNUX\RZUSNUPWVSZSJXfXNXZZXYWYZ`\X]^ZZb\\\]PcR`XddNbZcRfdVnVgTiPf`__R]^[XTZTRTSJSQQQRPOOQSSLU^TTSPVdSJTZTQRPRRNVSUSZVWWXh[T^aa^cdVei^fTb^fTdLdd`LaVbhYZJ^X\ZZJ]^Hb`^NaP]gVc^gdRg^dVhhViRggRiFhkNoRlmkRhTkomZilmiRoqXpLliidbfbJ[Z\YZW\SSOPPPNWZW\XVY^V``gjlJleXgBdNaR]La][WZPVWVTVVUVZSVbVZVVR`XXXV]PYbZ[D\\\XXXNYWQ^P\NMILTINKZGHKHKLUNX[`c`^hd`mRhi`i\mNoknbkFgRd`]XYVUQNPNI\JG\HCHDJFCGVJ\RTZ\]R`ejdjjVniXjbeRc^YZVONIEBCT?Z=9>@JBKJHORRVXZ]\dJcgf^fdbaPbP]JXXPQ\NEDTD@B\>?>X?`@VB^CBTGB\IGIOPTUbXU\WYYZYd_[Z[X^T\Z_V\]\ZNYXZVW`SNVQHQO`PMZOQNLJJJKMRLLP`PVRUbWZ[[\\a^f_^FceecZb`Pe`N__P\fXSXUSTS^TNLNTLRZNNJMMMMPhNRPSOSXQPQUPPTZWXYb[d^`]TbV_Zb`X`X^X^_DdbRa]YNZV]T[ZV\WSLUTQP`Q\QQP\ONfPdOO`RMONXONP`ThVUWXZ[WVY]\\]_R]H\`J`R_^_F[][\[[XZX\\TZ]W\]@VSRTFTQPSRRONPLLJZGK\IITH\HRIETEDFHVHNFDPFFEIXIFIIRIIPIHLbEF\JMNZQJOfN`QPRTQUYYdYXFVVTZ`\PYXXb^UQUWWTSSPONPLMTMZKHKFE\DA?@C=@T?LL>A^@R@=A@fBARA@bB==N?T>>\@Z@N@ACRB??@=:\;=^>`<>^>9\99Z:8Z85\6\4`21./T-X0`.V--Z,(N(V(`&'^#%F'V#Z"T!! "JHJdNdTRZR\ZZPXJNZT Z D > f R V Z R R L DP\LT^TZd^RDRFRZ\XdR`\h`jL``hLVZ`Nl`XV\d\^Z\XZf^TZN\\LdXhLR\R^TVbfFLVPTfNPhZ`XZPHTZhP^V`\\b^VTb`VXPNTdTDbrZ^^V^`VbZRJ^^ZfFZT\Vd`PRRLR`LLX^P^FPX^T\Hb^b^TNRfVNNV`\bXhffZ^\\^XZZTV^^\^\bLXJPXTZTLXTL>R\XTZjNPrT4PDTZTTR`P\X\XTfVP`TVXVXZ\RXVN\PbNZPPTX^\bbfRFZ^XjRRb`\\VRPPTP^XZHVVT^ZZTN^Zb0\TTZ^\X\^`X`NT^\h\V^VRVb^JRdP^FX`JlLLNT^b  P T b ^ X R P Z R\^ThVZVbHbfZL^R` #X'B)'V)D(R-,N-,>*+,.`-.Z213N222X4P57X87P8R;L:8;:b=T;;N;=J>;P@V>Z>b>P=<>Z@R=8X:`>`<:9T<8`:\:67`5P4f697X3V3T531Z6R2743^2P10N02P3R15Z2X4F201033L52P624b3d83\4V:L86f9X<=B?=X;>PCLBFEETC`IFFPHKJ\GRJXKTT\ORQUPX\YXXVUYUXTTT^TLSTbRNOSNQOhMNRVRNMRWMXQMOJKL\F^IRGHIF\I\J>IHGGFNHEHH\OLI\PlOLdQRQP`SXWVSWZ^YX]ZT^Z[ZZZTcb_bTbDc\fkkom\kibjbVgc[ZRZXX\UVTHWQPZSSTSTZTTX`XYVWRTXVZ][]F[TXD`V[Z`\[^N``Td^`Ri^fPlXjjhVgPhL`b_^L^YXFVP`STSRPQNHNHOTPHRQSR\PRRVSUVWVSFULWPNUUUTXTZZ[^`bh`jhgfedRbbNbTb_^`\X[\ZYX]VZ^R_X`\b^b\bccZe^`\dVigghgfXmZnjTlVnRlbnkmlTnlVjiPilXl`plJiXeePaVa_T\\WVNWRLRQRTUVRY\`Va^cRgPfiPmkiLe^dL``\^bXdZXWVZ`VXZTTTUBVbUTWZZYWZYY\D[_[L\XWhSQNPIJVIVKG^HGIIRLLPRUY]aNfjfkhPkonZnmRnRhVecVc\^XRQObKGBCCDLDHDTJPGRNPRQ^_cNih^gjVjT?N?X=;<;X>\AB?X>C=?V=>@PB`C@>LAD??P=bB>AP@T@`?TE@@>Z=\;T<\>@P;>T=<<\:L:P9\;X834Z2R2/V1b2T1--\0,+(J*Z+X*B(b%$#f%X%P!l!" "\V\ ZLRLLVhN\XVd^dNRT \ N \ T X V V d  XH XTXPR`RVT`XTXRZX`TbDb\X\T`^NRXDZLh^NdZ^XRbbP^N`Tb\TXJT\\^P^`^ddRP\R\\`^TbRnNbXdPfdT^VX^^Rd\ZX\^TfPh^T\Z`bTRJFZTd\PfXVf^^ZXZfLTZTVTTVd`ZVTV\XFT^D\FTfVTpXVbJRffXbjbfb\nbZVV`XffZ``Z\XX\TXXX`RT^dX`TVZLTd`T\PhX\ZRZTT`PLNTR\Ld`XbX\^TfTfZZTbRZLb`Z^ZVTZXVTX\XPjTLfRR``^\X^`PfTVZR\XVZVhbVhLZ\Pl\XRTZ^`JT\Tb@ZhPFT R R d l T V TV NPJZbTD`\TbJV`fHPNZ Zf!R#L#R$$(L)N+b*L+b-*^+\+-\,2`01X7P4222T3N66^9;X8H9d;:V>::<>V=>>`=ZA@;^=<\=J?=^==AN@@:X>>?;;R<^:8X97^6X6d55^316X547^48R6Z42V61Z0X3J23F13P44n302T14Z4`4X62J41^514R67;P79V:<<==@V?CEdCDF`@VDKbLhIjIZJRLNMLLPRRQR^SYXXj\WU^S^ZRRHQZQZP^PXQLRPKNNNNNPRSTPVMJZJ\IhILVLHJMG\LGFdGGdHHI`JGXIJLTNVOPSTR^T`TUTZ`YUVYYV\^HZ^Y[\]ba_V_T`XdTcPefhVlhhNlZmTjePeZ`L\d^H[\YVVRbQ\RRTRVUlVTJZXf_V]X^X\[WNVdYTV[YT\\]ZR]ZV`VaaZff^ceXeNg^f^fXf6b\aT`^`YbW\V`TSSRQ^PMPLZWQFOQ\RSXSPSXSPTSPTTU^SNUZVXVUXZLXZP\cbeXh`hhgiLfTbTg^b^^_b^[fY[bZXY[Z[Z_b]b_a\dLcNcTehVahdNieeTlJillXjXnqoNqlNnm^lVnPnlnXmPhj\fhc`h]`YPW[USXSPXZU\YV\J\^\\P^aVdh`imDlZjXlfTd\a^^^D[YVZV\XV[ZZXY`VRURYWLXNWYZ^RX[XXT^X[XWNVVSLRLP@LI`KVLFIZG>J^MPPSLX\Z_XbPc`hkTkhjqpo`q^uqnk^hdT`ZYSPPMPJGZHLCZCNCTEBGHNINZSVV^]cLgbfkjiXlRifheXeX^TXSQKZK^GD?N>L=<^R>XCZAEIN\QRWZY^\^`VeddfbPa^[^^JV\WNQhKHIF\FXB?>`>>Z>>DDDGZHPdMXRMTU\ZVYZ[^VV\RYZTX^XRXZTYdY[\NYLWTJXRSNPNNXPMPNPXOKLLHI^LTOVN\RV\SWZYZ_[J`V```PbXcZcbLffaHc^\_]Y\ZXUWTQP\SOJMMKdJ\ONOJOTM`OHPOXPSS\OPUWTUfVUXZXZT\D]_^aF^^F_Tb`^_X_d^]_`V]^XZZhVTXRTTVOPQPdPPM^OHMOLOQPbPQLSQTS^U`XPWZXZP[ZT^_T_]bbD[`^aN_]\]^T\]PZZb]L[XU\UWTVTZSJQZULURSRXNJMJMFNN\LJVHXIGTGDEXEJFENH`I^EGVJ\IJLJHGHIXLIKHKLMNMXPSRSVPWRXVYWZZ]VVbZJX\YTVVVSQbQRVXTRRPZRRPNZO\QPJMIH`GHXEJCCC^B??RCH??@Z<=R83P8\77`8`37T8654Z4T55:2^7Z265Z8\8:j:`:X@<<8P;^==:\9;P>=L=jB^?@??T@>>>N@XARCV=?@>@VDT@A`EV@RA>@P>=@R??=\`dVZbZZPRR\L`fd\NTTdb\b^ZN^bNT\bP^`ZfPlXVZdV\P`\b`f^\fVVXThZjfXXfV`\`^hbF\^X\f\PPfXVX\fBVFjXLfZNZRd\VR^Z`TTRV@RXP\Z^XZ:RVJ\`R`ZTPV^RT\Z^hX\b`R^h^`T`d\^Zf`NZLd\X\^\^p\PRXb^\^VNTL>LdTbRbX^ZZbfPZJVXVHXXZR\JZXT\T^VVVNdLfVTRdTZZfVVPfZTZVR@\ZNFXJbVTb\bRZ^^PX^T\XLVXVZ\TTTLVTR\ZJhjVbN\VdTNhbZJRPP`TPXd^PL P b T V R Z X n JV^H^X\bPRZV\LLPXfT !!"$X$V%''^+@,-),N.V.R0T.B/1T4-4\444Z33366>6b8N:=X>;<;;?L>==>=>`A:9;\;97T89L=j;66`6L5R7L647443^5b5P34Z7344V3d3D41T2T68b242303344L96X4V5J52L36:89X<=h>N=X>BNDDFDEJ@@DAbD\K>LZKPKGJdK\QVRRFRPNRYLTNXV^VWUUQTS^PNQFPPNLITPZOXPOFSLNJLRKLLXIMBJLREZGLJTKKZK^GdF@JGGPINGbJbKGKMPMOSRSNSPTVUR\XTWVXWZV]ZN]^_R\d^P_\dR_f_cbRihhhllTejeL`\^T]ZZNXhTHVUQZQPTSTXZYUYDYhY]b\ZXXZ[JXXVZRYL\[YVXYZN]]V`gXjd\f\ijegXfXhPe^`T\L[^V^UWTSRZSQVNNTPOHSLPNXOOPSQRWVS\S\ZPUWTVVWRXYW[]T\acNe^iRgillLi\eNc^e^VcR_]\8[^XX^ZYLVT[XVV[X]^]bbXdRcbcbdZfffkfijklTj\llnZpRsmZn^nmi`iZnklRefgaVc^[\L[TTNVTVRZ[RYWXZ`_\Xbe>ihJj\l\i^ifDdRb`_R]\]YJXPUX\YYXPXPYJTWXWXVYYPZZ_\[XYZYZ[TSVPPKF`HbJPIINJVOfMNQWX\bPdhbjTorwTutVqsRnVniZiTc]]dWVT^OMEDDCBZBCECREPHMLRRS]`gDjhdiVjXjPh\gb]V\UMLFIZCRC>>:Z;RX=J?\@F@X=;>\@\A?=R<@LB?RBCL?AEZDHCBR@dDLC=CVB^>>X>?>@>T=<@;>>=R=X<:;>X=X?=>=R?<;=R?9T99:X<@>LCVCXHHKVPXWVY_`Pf`fVcXefNg`bb^TYXY\UQ^PNZGFCCPCZAbA^A@ETEZF\K\KVMPNNHQPWSYXZXZ`WVXXYVYYVTWRVVWYUbZTWRTJSTPTQPROP\NNMZKMLJZKTMPNMXOMRU\UYnaZL_aed^ecTb`edfffV`]^][RYXTSQQTZPPMFOMROJM^IJ\MVNMLRjQRPTNSZT\SVWZX\YR\b]_``F^f]\]_Tbd`ab`a`\[^[`\X[P[WWTTTJQPUOPPPVPN^KIZJNSPR^TRRhUSVPWZYZXZ[P\Z`b^L_\\^TaF]dTcN^\]L^T[XZVVVTUSTZULSTULV^S\SQTNHO^NN\LKKXHZHFfIJGDZFEGH\HG\FDCPDVG>KII\KJJVKKZOP^MNQNNbQWNTUUXVTU]j[XW\YXUVFYLUXRUUNSQPRPNTPjQ\MPVMMdNIZKZJEXFEFZA\AZ=>A`?:T<`:\>N;\84X9Z8X7H8P5\43Z8X55264V467R89N9869\>V;;T999b=R;Z>F<=^=T?;;T:^BLAZ@H?^BbBRD^@B@f?PDC`BJC\?TC^DXATDAHABA=^@X;T?;`;8`;:4l7:6P22^1Z2131d0J-,-*)%f'''R'%$$&" Z!f\V^PH\fT\`TZ R X R X V Z X RhZPjR\hT``V`dPZRVPdVRZ\bnZ`VT`TTnVPZPTb`NVX`fd\`Rb^bXbJ`TBLbZZXTfN`P^DXRfhVT^HfTTTLTXXNVT\P^FVX`J`^VZvVTHnLJ`XTRZPHdTX\hXZNZZ^^LXT`XZDZHZP\NV^LZN^bZPJ^ZXZ^T`T\XbZZX^^XZ`d\FZJRX\@^V^R\\VVdZRXR\VV`VThXL^TVZ`T^\`\dXJ\fZTLZbPdZNdXXb`RRNlRZRTZVPbRXR``^L`XNRbRXZdZTLX^VXJXXTZ^V\PfFV^fNR`ZN`TLVJXJVf^\ZFVXTZHT\LNTZ^dPP N ^ V L N L \ ` P VNF^NRTBP@\fPVNVX!!#""V%%H&Z&b)++,R*\.B+-/-V.0//414319\88:;;H=XV>=V>>V@L;:D@;\>Z;b=X;P:V>JA?@CD\HJPNQWbYZPaaciPgfd`cH]\]WZTQNZNTNG`ETFCXCBCBfFJEFKNPNOdRPST\XV\ZT[^YZh[\[XbYfX@UdW\TXVZXRYXVZWSTOONTPQVOLRLfLJRKJKZPRRVPTSVYV`^`\gc\eRegJefNddTc_Tc\X[X`XNTFRlSVVQNPbNJZJXMTLMRMQNRRNT^UTQDUVURUX^W[N__a^Na``^a^_]cXd\b_Va`_`[`^\[W[S\TTTVRTSQORbRMOOZMOLMMLObPQRQRRZSU\U[ZZL`P\[^Z^]^``^]^d^b]\~\`^[\]YVUWVRWSjWTT\QZP\OLOVNOJPIXFDH`H\DHGXFGLJTGTG^HTJHZHGGIHIIJRJHK^MROTTRNNPRRRZVVXRZ\\Y@\YXY[ZNZTZPY\YZ]VQROPNNQVSOROP^OR^LLVLI^IVIHFEAXABRA=

L:T:V:N796`75T775R7T56`662P334b666:99R;989T9J9Z9R98?d;\?T=@h<;X;;d@b?d?V@BAPC@T@CF@B^BEPDFXBC??PAAT?=@^A>R>X?;X=<7J:9b765\6T4R5R33`/T/d1-\/d.+Z,\*L(Z)&'\((&&%#P#V ^ " ` X^Vf`NP\XHVTXPLXV X N X \ f H ` J \ b d ^\Ld ^\LVdXfL^^L^TZXXXZL\^d\XVXVNBXXVXP`RVThdT\ZV\JTVVRRR`TVLXLZLLXHfVbj^Tf`PLXVVTbbdP^ZVRPLRdD\PXP\LZNPTlTdbZ\PT^R^T^h^jTXPfN^VPPTVVX@NZTP^XPF^RPVL`TRVPPP^VVPPLZXZLVXVfXZRPh\fZXfjZtXd`\nXfbbVb`VbNLdNRZVV>Z^LbR\T^P\VbR`l^\F\F\V^^TZX`ZD^XRbPZ\bZNVZP\bbTVZVPLbPT`ZX^^LHDJPP\V\N\lZTH\`VZ^ZRH\ZTXLJPRbVVlXZ\VbTdVPXX^hRRL d d V T R ^ ^ ^TPBfPXfNXZ^`ZRh`P\\bb!N #$X&h%%&)*X)*\-++,-/Z/./V00R14b4R5^4T5H5R99`\?V=;<:;;=T;><^:>;V>\:<:V<\9T<<7N9`7V5h77Z65T53V6^3V44R5j4^5T4\41620B3R10@3H1P515R743T2X5L5Z6b864V5T7V8b676X::N>=Z=>PELBCCVDGEDCPG`KDJbIOXNJJNTNRSUTZTSNXVX\SURQPVRPOXR`QTQPQbPQQQ\OZSJQIMIIKRGXP\M^KXLL\LIZHGTHHGFJZJGVKL^L^NNPNZOVRbQXSXVUZZVPZX[X[YV^F^Va\h_T]_R^`cc`fecjijgnegcd^P]^NVVR^V8N\O\PLP^SZSRQUSUhWYZZVZ\[]WD[[T[]WXXYVZ[`[\]`a`Xb^fjnkXiXlbgLjXheFeaZ][U\XT\XZXUTRZRQFQRSQTRPSfRRQVUTSRTTRWVRWVPZZdX\^^f`aadgVkPjji\ighR`fd_[[D]Zd[YN^XVVJX]d]\bac`VbHadfgdhLhef^gkhij>poVpHnqosjkRpphdj^eTfec\_RZ\\\YUJVTXU\YV\Z]Z]haBaVc^hbNiTdfNike\iRhbdH`\YT[Z[WWTTXRYTV\TUUZRZ[La^aT\R`_XeaP`Z]ZY^XSRMRMLGTGE\NKMLMQXPXSVV]`ffbiVlLrpnqlollcNcV\[RRMJDC;=d9:T:;X?V@PEVENJMVRY[P_VdTef\keZfdN`YN[RXTPPKGRFB@;<=9V;X>>@\AHAE\GIPLVRTHY[_ac\i\gifaa\YXLSRRLTIVKXHD^EE*ECIBZGVM^K^MLQTfULUTHU^XWYTZ]^]RXYdXYV]SHX\WdWUYfYXYTXTNXNVUPPTVQNMLLbOP\JLLZIKMMNNUNVVVWZZ^`FgegieRfXiRbe`La>__RYYHWTUR\QR^ROZONZNL`HRMLPVNUQUU^WZUUDW`]R\T^L^^BbL_`c^cXdR``eZdVdRe`X]\\ZhYWTXUhVTVURFRTTSNPTObNVRLVPTM^LOMRRTNQSSPShVTN\XXZ[X\]faRa`d`T_VaH`_`^N`VZ^\XYW^WZXHWS@UTRU\VTSVR`RXOPMLJKKH\HBVGE^AGVGGILHGTJTG^IVHGFHIHNIJJJ`LN\TVNTSLRTRUUY^YLZf[X\R\Y\[X_X^^YJYTZUNURTTQRRPPXONNQNVNVMHMJXFTHHCFHAN?\DA?=:\=Z>8;67H65734R4X79V7L5X6X35P4X5b8768^=L;\><@XN@j>Al=R@XBH?`@BABX@^AL?@A`AB^FLDDNBT@@T@PCZC>Z@?L?XBJZT:R<>@9NREAAPEEFHTGHINIIXLJNNLNKXORLQfTUWFYXRWdUVSRSRVRXRTWPNZSZNOFQZP\OLQVP^LON`M^ONZLTJ^IPLLJORLFZJlKPHHGZGPCXJIHTIJJJNKjINL^NTS`RUdWVXLXXX[\_b]T]V_d^X``acbacbfTlXfXhhJji`ejbZ\[URTNRPMPS`OSVXYUWj[W\XJ[[RZ`[^ZZVNUNWVWX[Z]\^_]Ra\hgVmTpfnVlieZhfRig`V^PaZRXYUVUW`SXRJPQTVURT^V^T\V^SfUVUQPWWRTVTVHZVbU\X_nbVfLgNfelXhbj\jHfZhhXebR]ZP^YNYVYXXY`WN\VXWhY^Y^[P]^bL`NcTacZfFgf^cePeLffjLkdhNkjTmTmm^pjilnTokg`jXd`R^]\`WRY[TUUVXWTdW]\R]aVbdd^cdgfhThdjhcXcVdVa__^XWbVUZSPSRT\UVRTRXdY\XZ]X``\[R_d`^N^[W\VRN\MJLIXJHLIZKJMRdPSX`ZL`Zaem`nmomXqFqoikTc^TYNSQNLHLEdBD<99f9R::ZF:\=R<>T:b<=VV=VBVATC`@NFZ?TAND\F@DCPDBNDDALBB@@@X@X?>Z>V@VA>X@;=:;^53b599X53N2J2001.X/\0`-.)'^*b+(T)^'$T(L%P#"^# !N #V! ZT NZfPZPPLN<XbVPV ` b R Z ^ \ X Z H X ^ H ZV^bLZ\HRJR`PXbXVRJlVZRPHX^HVXNRZZ`Xbb^fVNTZTRTTJXb\fT\`\VPLd^^`f^^B\VZVXRf`^^FfZH^XfXbb^XVR\Zb^RV^NdL\VJbfTT`^VT@XT\ZXV`\FJ`^XLH\R^XZR`\`T^ZN^XNVRhXhfN\^Xfdd`d\ZZh`bVdbXfTZdRbjZZPTbt`NdbXZbXbVJbXh\RdNbXZ^T\PLdffZddTXNZ\RP^RZ^VZ\Z\RZ\V\ZX\RdVVRXTVh`XhN^TVXlNRPZPTPV`T\``dfXX`P^L\XRdXXX^XVRVJRRZV\T\LXZf^:`VRNTNP`  T Z Z V ^ N b V `  ^XNPbP`PP\`ZPZT\bD^^!T \"#^$()`&N*+),-B+,\/-.\4\0T0N2R2T2P7R7V6T679B;7\;?\>\>`?R?C@=T===P?\9@A\>R>V<:P9=P8R=;Z<=dC??RD@HDRDTFIH\LRHJIXL\LPhN^PKRPUSURVQRXUPXPURRVSOQOTNZNXNPQPLNMNORRRTNOLLNJMTOMMGXJMJ^HXJFE`IFELKHEGKIbEFMIVOOSSJRHSTXUPWYP[\*\T]bZ\[ZaV_^Zb^b_]RcdfeXedeejlh`geTbd]]R\Z\R^OXObRPRPZUWVVYNXTZXL[VWVWXYZdYDZWYXYXXXXZV_^_a\bNc\goZpnhmlNiXiVggPddga^\ZRX\VUUTXTSVXVTYV\SXVVHTQTSSPTdST^SQLUUVVWW_R]P_VceheijfDihhiXe`efhdHaP\T]XbW\XVW`YZ[[WWVXTWZ\]P__aTb^fjRghNjglhThiLg`kjRkTkjlLmkPonPkk>leea_[ZX[TUZUZWRSTRD[XXX]J`P_V`Fcb`d`fZfXheffRdPccVbc^J]J\VVTXSdSQRTZTSUlTRVWL_]_^fNdbZeFf`[YYdYTSQDMTNKVJZHII\JMKRZP^VWZRbXc`ghNkn\kPidjiegd]RWfVPfMFpB>hA:8V:F9`:;=PAlDBFFJQPVUX[`beVdfZdeLaNa_V\[UQLMZKHRAJ@b?PWlWR\]ZP[V\ZTVVbYUjTT^URPSPVQNSPOQ\LPNlLVMNJLJPLLECXFZA?^<>;V>R8;P79>?X^=?T@A@^BAR@A`C^@TC@DACZGJ@\AVBZECA^@ZC@A<@?>b<;=8;T9P:8Z67V7N5^3b2H4P6Z30.-X-+<+*(`,(L++d)%$#^$!T!N$$f#X R PVZ R XV\\XZZX^ZL hV ^ V \ d d V Z L b Vb`hTPP`hL^^ZDfXjVbBNPTjN^T^TZDVPnZNZPfTRRZLRj\X^FRbPPXXd\ZPT``NLX`Z\\^`dZ^^^NN\dLVFbfTZfbTTVNNXZh\XhVdXbN\\TP^XbP`VjJV^`^fZVR^ZP^V`RXhTHPXJVJZ\LPLVZR^hRRhPpZXPVX\V\J\`dR`LhNZ^VbR`bTXF`NZR`fLXdP^`VjTfJ`Z`h\\RXZ^ZTZNdVX^V\bbVZRfbT\bZPfB\ZJ\RLZT^RdT`^NZTRZXRZPZXRNTNRXNJ\P`fLXXH\\^dXZTLV^Z`dNZffTXZZbFXPd\TRTV\V`JRPTT\^PFdD^XdH`\  \ J ` R T N b J` b VZ^\^VPTTZTTXTLNVVL\ \!$\"N%^%'&^)(b+L,*,`+P-1\-V.L-X2020445N7`5b7X8fh?@X?X?=P@X?b=l@<;V997T8X97==P=`::<8R:6R74T9V4N68457P96H7768b5T6230/\2/V0P/F/./^2Z04b4N22@2V4^4J667R57\665Z9:>>=?\DTIVKfMLRTY]bbhNePf`dH_[ZXU\PLNFE@P?=Z;@=?;RBV@@dCbEGIJLNbQNSbWXa__Xb^fhfebP_^YRR`ONLKJfEJHEFEGEGLGGHIXLLXPjRORPUXR`TUW^VZX\[N\YJXZUVWDWVPXFVSTbUVVTVSNTUVQPHNNJBNVLZOPIGJKHLNOR\WZV_L_dRfdXfjiifJbcLgbcb]LZY`XUTTTXUPPVOMLKbKHLLOMNPXSZWTT^WV\XWJ]R[`^^R^N\^aN``gLaV`bddTdZa`b\X]VhZFVTPUTZUSWPQQTQDPPJKVOKMRMhQPOVUHPYBVSWVPSRVU^SRTRSPM\OPNMOTKHLN^NRGFXFBPA^@@:h<<:=<>Z;T=<;H?=P>LAd@ABBV@A\BVC^??XC@RAAEEZBV?DXAB@^BXA?`=N;??>P?=j@L>=T=\N?A@NDVBHKGDDRJZHJIJNPJRhNM`QZPRTTPdSX^SZTSWTWRUZSROTTHSNTXPXQPRZQPPPNRbOLPM^LTNHII`MIGPK^K^JXJPHVJJ\H@LHRJRHFGFjFJ\ELPJVNJMNOOSSNWVXYZ\X\^^^]J]_`_aa\`b\c``jeRdidgReNjihLke__d]ZXVYXUXXBX^XQQbUNTNWXfXXXVRXUXXWVU`UW\_\[X[XV`[\cdb`fXcTcdhdj\lonXknbRdPc`bh`P^b\XVSNXXSXT^VVVVYTVUJVVXXTURSRThULVU\X]bWXT[ZP^`XfihgThLkghiiNh`gVgfae_\\YRYV\Y^[ZZYYHYWf[VXXT]^_`\`ccZhjdghh\kZj2m\nThibh`mVfeXjDoRjjhJfcTb]\Z^XTWVLTVT^UPVJUTSWP]P^T_ZacXgHegeehVgdRadeRa`_[ZJYXTXUQQOPPQZRQNVUVZWR[^Rd^_fbcRfaVdb`\^[ZVVRXQLZLKKREINITKXKHLVOOVS^TW\WN_^fhbfdbiZgbJ`^^]XOL\IPEbBR><;P9T;9:7V=T=P?DEKN\SYT]_Pc8dVebbaj^aN^\TVXTdQJDH^A@b>@@b?>\??XCDEPEZGhHXJK\O`TJX^Z\VbbbTfegb[\XTUFR^MJTJETFDFEEGFJHJJINJNP`RVVZTXTTXTPWXUVUX[UTV\WXXLXYWUX^WWTNU^TOQMTMJMTIRKRHXIIFHHKNRRdUW`\e\_cehdlRfVkhdRgbP`RaaZYXVUNUUSOOOMKXKK\KVLML`PPTUS`TTVPYZXZ_^bb^R^`aa`ReefXafPaZ]^\]Z_ZT[WJWPVRNTUQNP@POVRLMIJPILMPNOLNPSPTU`TPSZUTXTV\WN^]\f]\^Z]N`XbV^[[R]^`^RYPXTXWX[ZX`UU`QJQS\RO\POLR`NdMFFVGEPKVE`JGbCXDHD^GDDfFTEJHLGVGLIITJTI^NNPMPVQXT^QSWVFWbYPVNTWX\YV\[bZL[VVDUUR^TVXTTTQJPRVPLQONHOQNNLLOJnIFF^DAXCL>Z>N::::Z984P75h7^3P3f573^346V434h5P8V7L;Z;97558`66\=^98X987\>;8<\;<=V?f=T>?TA?>@TERALBPAATAb>Z@P@@`@V@===@V??J>>X>Z;<7T6X767J5Z62R3T2R400T0-\,Z,.,X*^'V)*'T*V%%'$^"T!^%V#X"@#V!XFDZV\VTdTVJLhRPXXV b \ X L F H  Z P\ZhRVd\`lLDTXhVJZ\XT\ZVVVfT`TZHFXth`^PN^RXRT\l`\^XR`\H`VTZX^bVdRXZR`ZNHbTRbZ`Zb^R\JR`^T``FThHZBdTZfNRXPT\FZNVbfRVRTZ6Z`JZXXPHbPLdTJ`VZZPZ\fVRRTZZZDVTXV^VX\`VX`f\Z`FRZXVXb\`\J\bV\`ZdXX^PbhTL\hZfZXV`XLZ`XPdVN^TR^XdZXdfZ^`^VVb`XdZPTfdZNHZX`ZV`VjT\RdPVNHR^dh^XVZXZRbXPXDJVZn^\R<^^b`H\XlPZPVTZZP\VdXZ\`\PRPVTTXVbJZZP^ZNP^ R \ P R H T \ R \ P ^VRRXJF\LNTXXfTZPVRX"##$T%X((+N*R(,*L/,N-Z/Z//d0L42P4\5L55T76V6\7b99f7;N:Z@?XA@T=?=f<:;<8\9<6f<=:Z9`9:N6V6X5X546T58V:J8T8Z:X85f9Z6`93^3L0`430T1T32H.T.0`/T03b6\1Z1V3R65l6574f5V7R4:=V;>H>RD?VA?@@ERERIfG`GETIXHIHMKDMPRORPQZSSVSWTW^VUQFVPJM`OPRRRLbPW^PHQMMHP^NNZMHbHRPIM^JZE\HHZHVGJTK`KLKPHHLEFdFHJFJXLPLbOKLOPPQTSSSX]T_P^^]\P_]^^_d^X^^\a^bVeg^hRkidZkgfTef^]X[WYYNYTWUNTPSTVXTUSSWPVPVX[bZN[RXVYP\_ZY\[ZYNXb\XbXaaXbRcdeZhlToiTk>kNhiNidTcZa``XZ[jVRY^VLXVVUXVTWdVXUXVXTUHTRNT`VRYV\VVRYWFYh]jZHgLcZbViifkdhVmNkiikXij\hfN^J]]YPWWLZTWWX[HXXWYY\]D_R]\aX`VciieVkXjFkk^kjjiXk^gll^hhkVhNhLnNjTe@fdZ`b\H\HYXTRYVVRXPDQHVBUFR^XWZZ\\`XeXac^ejTfg`hgLfRd`a`haZVVRXV:WSZOXRNP\RTSR`Z`VRWZ\`TdZ_dcc\iVbVbb_^[dZPUXVRSMLNKHXJXFKZKhMVONQ\RT\VYX]`R]PcbaaR^^ZD[bWbQHKZLCB>V;:>N::L9T:f>X>@hCG`KMTRXT[LY]cffVd`aPa`]H]\WJSKJVFA^BAT@A?^CL@NFZDNDGFL\NOQZVYYRZP_`Tea^\b_[RWVSMfOKFE`HXECG\GHMLHI\JXOHPPXQU\XVXVV\TUXNT`WTX[NXXYSfVZ[^W\XWVVTWVTWXTXWVRXT^O\RDKJTIIRHHG\GKHHJLXMfRQJSZ[RadLdddbjkJlTgddPeRadFb[TZL[^]XXVYXRXNQPMLVIPKVLLLTNZNXN\OO\PVUUVVZUU]bZX]\X_JacV^XcJjdadehcVa]^_\\_XZV[ZHU^\UXTVVP`UNNOLRMNNLJMXJVN\P^NPOSZRQRRbRPWSRTYXPX^\WZZ[X]\[^T]T_P\Z\YX]ZbYXYXXTUV\WTTSTPTSJO\P^STPONMRIGFDHDLJZHXJCDDGF^EGEIJXI`JRIdIRLKZOQLVOLOP\RVTYVWZYLWSVX[WWXnVVVSRYVVSUZVQVVQ`SOSSPNOVON^LPLPXJVIGTGFGVB@R:Z::77`7P7V56X5X4h42`33^82d5b54J767V75R878J76T69Z6`:V8T:T9:;:R=9=L=`>;=^@VAX>>V>BR@Z?\AZA??fCb@R>ZB^?@LCLBBBB=TAAZ@?FDL@Z@=X=V?V>X;@?;9L;R:7H85X7R55\5L12T7`01`1L+/.*T*R-'Z(T(F(d&$#%#Z"!Z#"T" Z XT\L^NRRZd`XZXX\Z\bDXFJ N Z \ ` N V ` T Z X Z V V^PRVHPXf`RXLRRTFJVN\NTf\NbPX\VNbJPPRZd\T^dVNhXVXDdP^PX^X^\TRVZNPRVbZ^XT^XRHdhZddT^RfPV^XZ`PZZPZRPR``N`^\VdHTR^`JP\V\RfNZZTbR^jNX\V`LfXP`PbZTNPbTHZVZTXTXFZZVTZJZRd^\\Z\h\bXbdZdRXnVX`RfTZ`^N`X\`hZ\T\nT`\dhXZ`\TfJNFZ^`R\R^RP\NVNT\XV`b^fTXXZ^PX^XRfTN\L`VFPbLT^VZ^TXbfRRRTVRT^hN\`XdbXVThdRZbNXN\bXZN\NRhFVL\RVhZ`RdX^dP^^ZXL`TRVX  T b V L Z V ^ X Z f `VRRbD`XTLdT\!!$#T%`&$P*H*+Z+b.,.Z-/0R1/02T40H6T6P97;48:;=P=>R:f=?b=N<<=X>;8::;T79Z;:X:b9P:N9;:R6X8`89X85\1^66L3\5J8D<8Z6V6456^3T34H3b1V301/H/\00d/*.d/225T556f447l7^67b7\:X8:f@N@LAhCZ@JA`CDEVGXCJF^HDKJJJPJJ`MfOONdRTXTUWXXWTPT^SLQPN`PPO`OZPSSOLMLPZKLVLTIFRITGGPKFKHJG\MFJlIDVKGJJXIHIZGVNJJdMLLdMRTMbQNQZTYZ`[\XZ^_Z_LdJab`\^_aVdZ^\``bfbTgPhhfHkij\e^c\`\``Xb^YXV\VWXPRXQZSU`XTYSZTTWTVVXPXRYV^T[[[]YXZXZ^``^^abidJgfhgBmVmkljigfTd`Rbb^X[TTR[VDT\X^W[XVXXU^WVLSTfOSRRUWRZXPYX[f^PYaacc^gekRhjXljiZjhgHc`bV```[VWXXYVRWYWTVH[Z^YP[\bd]_^cbhffehJilhNmj`oXlkbkkXjZnjhkPf^eRcVf`T_^[P_`VUQPXRRbUQTXW[Z\R_\^^b`hRcXd\gjhVdbc`]Va]ZVXRXbUhPS\P\NRXOXOVSWXWZZY`[^]`aFc\fee`cTcR]`XXPYJVXSP^NZML^IHdIGIKLLQNNSVVU`\VZ`a]\`X]\[XZVOXLjIF@>X><=N:V@XC`ETITIbPUTY^`aX_f^adeVf\dTcN_\^YRXQLJENAA^A?B?BCBEEH^IQ\NO\VXXfY^N\dbXa^PdZaN^V\UPPXNL^LLGI\DGVFI^DFHH\KRJ`LVMRMROXRVUVTZUSUUZXVV^Y`VZVUVUZX[UVVXVY`VUZTWVTMDLRHGDjGGHGJVKJZMXPPPR\UTYf_bfccfe`fLfh\jTieXga`V[`N\]T[VTVTQOVL`IKJHRKMHLMMOVRTRTUTYXWP_^PbV_`b`X`aPchVcXdVgXdfbcZ`V\h]J]d\XRXTRVURRSdSVSXTdOLLZNHNLO^KKJLQ^KS\OOOQSTPfTJWYVXWP]ZZYT]LX\Y\]X]P]]X]TZR\[[V\NV^XLXRTUSTR\RROVSROdNMKGPGFDTGZHFTHLFLFRFbEXGVIF^HGbGK^HNHJGNHNMLTJPTNN`LQSFZ`VVVVUPT\XYLXUZWW[[FT\YWWJQJTPQTQTRRSUPSTQZR`NObNRRGKRJJGdEDNBH?X=;N:d>P@?AZ@@?TB>=>>;\?\ZAZAPX@?@=V=X>=998^:\8X4N42V3L3b81L1^0h.L-0+*X,T)`+L-b*(P)$%P$%!!%# RP!!XdnfRPXTN^\\X R ` ^ V R F d Z h J ` \ \FVhL\PTTRXJDPN`PXR^JZRT^TdJZXHbbffFT`ZZdZRbTNVZVbXZPdTL\^XJd`TTVVVTZVTZV\P`hB^V\TT`L\d\PjPVXTVZ^XTZR`ZRd^ZNPNb\dX\XbTbJh\hb\T\R```X^HdXNLZTLNVRNZRXRPPXP`\NXXT^VNBFRbHP\ZJ`\Xhf\jdfbhXj^pLfj`b`dbhf^\bbVfTZZbd^PPfNVb\XV^^TZP\X^VTf\jBVHRPZRZVf\TTJZJ\LN\VXXV^NP^NVVj\ZXJPZPNTNT\\TdV^XbTRHZb\\J\FL\TVNRRZbVdP^TNTNNbZZJZTXNRZZPLjZlbV\:PP`R T f  l \ V RL Z TTbXb`PR`LNVRVRT\X<LXZN TX" $\%#^)Z(L'+*+,+b/.D./P1\03P31^54R6^8Z;75N7R9>P8V;=?>N==N>>;;h8d9::L;L:R:<:9^6V98=\98V8P;9P8\8`4V5558L56^6Z8P75X45P2X51122..J.b/P/-^,./N0N1d0Z02Z4V54R6f74X5V7\XCBDJdMDFRFDJ^JZHPLKNOXJTQ\MRTQ^S`TUSVLVU\VRUTQQMKSOONPQJO^PNMLZLZLMPJVI\IKFPIDFGFHIGGHJPKRJHII`ILH^EIVJR^Q`LNDLZP`RTRVYV[[V]a^`_Xa_`acVbhZdfaXa`LcNccXl^lPj^kjk\jdidd`_F]]VZV\VJSZUVRPRXU^UXWTWZUHVZUUWNYXZYWN\_X[Z[[P\H[]]`adjVgiiBjkPikRgDhgLj\e_b]_[\WWRWUH[NUWVDWYXRY\Z\TWTXRUWRVWNWYfYD]`Z\^cbdjhPiZhjl\ldmPmieTfPgXeb`[YWVZXWWYV\^\[_Z]Lb_J_bcXaZe`iVffjkgfkLknVmTpoolohNkhffjPdc0`^N]`^[XW@RR^MNPXNSTSXXRZH[\X\^^NdNbdRefhLfjkhBhbbR__B]\UNUURPVRO`NTPJR\RZUPVYX]R]^_\aZeVbTig^eeJe_`\[WXVRRPMNKKVJRJGL`JDKJNTN>RSRT^WJ[W]a[[RZXWPWTPKBXBB\<:D>X??Z=X;=;?`?APC=ZAV@>XAP?=R?@^@b@>@?\AV?ZC?\>=>L@@>ZAA?^=P=Z>T?>X?XX;\9:7T7:7^63N7Z2D6R12\3/d.`/,*Z+))+(+'$d(N##$$N##V#X#!NVZJZFhjDXT`bTV\lTXT\Vd @ T b Z ^ h b V T ^ `XN`ZVXRXVX^VZ^RHZLbX\XZRZXfdFZJVZ^J^XXZ\HbRT^RfN`VnXXTZVdRV\NjdLTVXfVT^dNZL^XZ\\fP^LbZT^\dbV`P^^XN`JNRbdNRZVRTPHZ^N^d\ZL^`XJZTP\PX\X:\dXR^N^RTJ^TNb\PP^2\V`VhRd`p\\Z^^TX\dBT`ZfVZfbZV\NTlTXXTX\``d\P`fTJN^VZ\X\JdPfX\Tb^RZd^TbZ^TZXTJTXXZdT`RZZfXVX\XfTJhD^\N`dXLRLd^\X`PbVZf<X\PLbTXXbV`HXPjXXV`BTVF^dVJZXP`XXVFZ^\b^^ZZlVjX P P R d T d d R VFXVl\Bh`ZPPV^XNd"V!V!"#X&^%%Z*)>*^+*R.d/J/.\1.12V33P35H56f9V8P9T;=X:j:;^9Z=?T@>>@H=;9:8`:8:^=9T899F;Z:V7X:R:976`5P485^6R7Z7X753X7L7101R1/1d3/V1--X1Z0.X+/Z3Z1V2Z3`4Z5R3T3667X76j;V>=;;`?P?BN@CZGHEXF\EVEfGTGKJ`LO^KROZPLRQXUXTXWYWXUQ\TRQMXM\NSNPTOMNMLPLTMFLTH`HHJFJDVFDGHHXJJ\LjINHdKJHdG^E\HIHJKTMLLNXQTZWTn[\W[\[Yb[XeZbNga`cVaXedcaah_FdeHfghHjgXgLddJiN^daF_Z\\XWHWTUNTWTTUTjZJZUSTX^YWVY[ZR\lYZW[Y\`]N`aaViTiLiRihNiZgZiTgdhRj^h\aVaf][[ZJZXYYUbWVUVTVWfYNWZWURRTRQZWSNWYRY\ZN[\TZ[V```cdiJiVjlnLnlihFjbcdb`d_[V_Yh\`YVRQhTPUXVZ\X`\a\`_aPddabXcNfgiZhHpjdkmRpHnTmfpNnVmnlTlg\jgZgbbR_R[T^ZBYXXWLPXQdPPJPRS^RBUVWWXV\L[`NdXe\fhDm`kgRl\hdNb^\]\`YXSNSUTTRQVPVRXQTRFWWV[]aV^`cdbfgidfXfb`P`V[ZWRSfP\RK\LHHFILHXHJPKJKOHQTQ\ULUTZ[HY[V]^\]LYhWRTXRnLIBPCJ=T?9P=<8h<=A@LGXETLMP\SWXRZ__J``\fZgjNfXfbf\TZdWWPPhNBKTHGABT?ZB@@`DJDEEHPKTKXNRVTWXV[[L]]V]`ZZZ]TPTOKLXL\JDFECDDXGHIZKKLXLRROQ\T\UPVXNWV\WXWVVdUFTVVSVYYWW^XVX\UWZUDSXQSJdK\GGREEBFRFZGVHPNZNLDNS^WTTWX^X_Pfe@cXbhXgJgLi`kRg^gccb]Z\\NYUTRZPRNMMINKNIMLIRQVOQbPQRST^X`XZ^V_d^\\^^a`db^b_bhTcZcZcXc``^\[Z]RZYWPWLUUU^RQXRTSPNLKdNKLTKVLI`JNNNPLLVPOTSVT`R`VZXR\VJYXZVW`a\R\_^^bL`_][[XZYRZ^YYXYRWZVVSSPVPRQFQRdMOXJ\NPKHGdI\HGVIRGdCCZCRECF\GJRFBGdHFGIIKTJ^KVL^L^NOPRTNZQUXYYTUT`XNUPXnTXUXVXVV^TSRT`USVlTXPbW^QNTRPTPTSQ\POHOhQLZL\LGRHJIVFF@R>=8R=9b:;N7R77N7\7h4L7T2^2244R4d72;^:66V46578^79N;X797V7<;:Z@?\>=V?==>?ZA=AT?NB=R>=Z=;>R@VAT?^>@XAZ>Z>X?BV?X>Z;;b>:3N2`41//d.-^,Z.+V+V,*+^''d&R&%$%#!d""`"V"^ \NV`T^XhRhTTjVPNRZb d b d R T b T  b JX^\NVbVTbZTTP^HN`VZ^VZXVd`P`VX\P^^PZ`X\LfdXX\`X@VV^hX\PTX^^\X\\dX``\f`\XP`XbR^VZXXXXd^TV\ZVd`R^R\\dZVXpdXdTdT\bdT``^FNXVRjTHbTBZRBTJNPB\fHX\LN`\DbXRZbVNFXP`XlZJlZ^``^\XZj\XVdjVf^`^P\j`NfRTT^TpVfVNVXNRZ^`NXPV@LZZHZPNbP`XjNdDfTbF\B^hNXZZTZfTBF\Z\DTT^ZR\``fPNRZPPTPVTXZL\Rl\ZjVFHLPPB`hVZ\J^LP\djR^NRNTd``\ZZfPVZ d D Z L ` \ J LZHRTZTNPNJB  ^# &^%X%X(F(V()D)*X+*/P/b/1200R1^17456V97N888\;V;T=X@N;V>;\;:T:Z;R:`<\7::`9888H:<68V;T>b9L9T9<9X9P<544V4^9T454Z5J554h2`3d2P31^/Z011-/f,Z.,..0X0/R3R4T66T5X5h7N6788\;R:\>X==\AFBjE^EBH^EJDHFG\HVI\J^HJOLZNN\KRPTSTTHUPVVYXW\WPTXV\RBTOSPDNKZOLLKVM:MZSFNMXOVM\NRNITEDIDJEGZEPJZHPJIVJMXHJJKHHHLJXHTHM`JIPOMRRVRWZDZPZV[L^]J^abc\_Pcbdffha^`iTbHhPegRhhgePeXbXa^\ZZUdUZVQUhTSQSLXXXPWXPY\URXNYZXNY\\^]TY^XbZV[ZZ\X]Z[bJ`ehZjgdmgZlXflmljgTeT_T]ZX\[WVXJVUbT\UVVVWYTYRWTURRTbRThXZSZYT^\\ZZYZ]^__Zc`egPjhRimnnVihBfccV^V]B^YZVXZZUT^XUXY[\RcPc`_\ahcdaffi;=?=DBJ\L`PWTVY_V^aTcgeiPjfgdi`c_\SP\OKLJbHNE`AR@?^?>ACEXIGJLL^RNV\YZX\ZZTZZ[YVZWSPRLK\HDDXFCGNDVGVFPFHGXLKVMMPO\PdVLVTVVYWUNTXW`WNURXRTYVZbWPXWBXURTTLONVLJTJGRDDGCFGLLK^NMPQbPNQXTNVTZTbPaaff`ihhhh`fZiPfd``^X^\[dWUlPPZNLMJKVLKXMMDM\LDMXNROUVXTRZ\YP^f\Z^aR__TcZcabXaefLdcde^\Y[[YfYUXUTQN`P`M^OSLFJJfLLKVM\LONVLdMMOTRSXWTZTXXWWJ[V_[]a\`^L^V\^N^JZ]LZ\[V\[PYVVWTNTZSNTTRPVRRMLPJTKKBGHGNKH^FEEVHVDCRGDGZGHFFBIRHJLKNLPLTN^PNZOV^VTVZWUPU>XVVW`XZWVTSTVRXU\UFTT\SfUXRPSRTdTRUPRWNMNOQNJ`PZK\IGIFXGD@L=<=\:\9V:X9865J854X42h2Z3\5V42Z8^4^5P5T3\4P5613;;F9T68f;6R6V6F7N<8\:9\>V@X=J=@^>TBV@P@J>ZB^A?@=\@J>@@XAA@>>X@@>R?R@?PV;X9X<=`=R9T9L<:9X9?TBTFA\E^DVDETFGHRMXGbJHLDMNVP^NMSTOFSXUVVRUXTPT`SRUfRRTMZPJNTMTKLLK\QRPT`RdQMIHGGLHXEERIBLBGGGJ\KPHGFVGGKI\K@GIGPJVJNKOOQTJTZ[UYd^\ZZ`a]\`d_VfTb``ddVdab`cg^c^dZgmhhdbeaL^aV\YRTXSQTZVTR^UQVWW[VWVXXVVV\UY\WLWX[W@[`WRZRZ]Y\ahafkmjhPiHgihRhXed`ba\ZR\XZ\XZWV\VVYS\TU\VNUTV^YXPVSVRQUVDXVV^XZZYT\]Z`eNddgFiTiVlNgiPl\kPhglfb\`[\]^WbW^XXWYT^V^XVXR]___^``baVigPjdi\ifjJiThXlTjjl`rPknXliiLhgTjfaL^T^LYDaHYXXTSFT`V\ROPRRXRPVUU^W^Y[Rb\dZhdFihgNlfeFec`P\TXYVSTTQFOMQNZORQVZY]^dTbfefBh^fbcTccTabZP\\ZLVQON\OJIGFHJEEIDHHKdONJTVTVHV^YX[Xa\V\\URN^LHDB?;>:f=J@`>>VDVGdJLTP\YW\HZhZaaTbfeZi`iVjTokXgRcP_\VWVUPQ\PJNIDFZ@JCCVAAXCD`EENFbIONRZWXYWZ\T[\ZVTTSSPM\QHL^KEGEZFXFENELFEGXLTJTMP^NZNP^QSWWZZXhY\XVRTSRRZSPRSUJVHX`YXfU\URONXMXLVHHDEHDDF`HFPJMPL^MPRSSVTWV^^aLcRbTggThiXkVjeZfVdNcbN_V[XYTUJTZQPMLVQMLHMZK\LVLbPOVQTQZQQVjVDXNZ]]L\\NaT`ab`\bdTbXgcbNb_Pab@`R_P_`W^XWdXRR^QPOXO^OZMbNGJIRJdKJVJhK\JJbLTMPVVRRTLUXHZZ`ZWL\_\^Z]d]^V`]`Y``_T[Z][lWhY^YbW`VUTQRQP^QQPLMKNJJ^ILVIK^ITECRCCED`BDFGTGGHGDHVN`MKbKKLZNNRdPPUSTLT\SThWPVUWPUWXWVUTYTSLWfWTPUQQ^V\WYFTPLUQLVQOQNM\LLN\GTINFDCT@N=X;P<;\B=A===Z>=fC>ZCJ@BZB@V>R<\=X<>>V>B@AP?VC?^BXBV>X=J=PBJBVCPCfCLCXDCZFHLJH^KLLIN^QTNHNPQSZTRUTHW\WPX\]TTTNPMRNPJ\LVNRPLXKNRQVNLMLIXHFPEEHDFEHZGERF^F`FTI^JVGVGRJLIFFJJJMVJKZMKTSTSbXSTTRYP`Z]`^^Vddbcaad\cZgNa`aVdb`fJmhXgiTgVe`__]N\]YXS\TPPXUdTWYLVRRVVVXYUVDT\VNUVUXZZ\WXXYY]D^[`aggfnDgnij\eiVhfgdc\NZYNWVVXTTUVQ\RYYLYXXbXWNVPWSPXXNYUZXXY[V[`N_bZfggVfkTlVoijkgThdba_[]X]W\^XPVVURTXXUZF^`c_`\d_PdhTeZi:gTiVjg^kjmqRmVnJkXp\mNlVgiNhcab^V]X[VLYQTRLSQSOQRQTQfUTU^WXW`ZZj_Fad^dVifjVg`igabR``^R[TZVSXRNOlMRPZQRPQUTSTVVYHY^X_R`elZdjff\cLfce`P\DXTUXQObK`GHFG^FC^CCGFJNFNPPLTTQXU]R[ZRY\WZWROVNZGVDVC\?=P<;@\>;N?X>L??V?=`Ah@\@AAD=`AZ@\>R=:\;;8N76N:86:6\86\2`402T00^1./L3d,b-,R-h+**T(&'%'&P#\#"V"`""R !ZRRZXVX\VPNdRZT`^`J\ R R P T Z ^ Z ^ VX VXTVPLXbRNVZZNXN^VPP\RZPXTTR\^fhbbh\NVTZRTTT\NhPhVhRTVXXR\RfTZ`XX^RRX\ZVVfbRfbVTbPNVRL``Z\ZV\ZZX^b^hRhZbN\bZ`V`TdX\\V`TRfPVL^FVRV\ZLRZLhVRZP\Rb\TLV^^RXXTFfJXTRHRLNVRPRTh\lXf`R`bV\bZVbd`h\RVjb\ZVFX\XPXd`\ZfNPdZbZZhVXPZ\`J\VrHbX`NnD\fX`ZfVfLVXbdJZ\bL\XbhXVJRTj\\`XZLb\NZZ@ZTTb\\^ZR\VTXV^dXfXFdXPh\ZdZ`JZ\RTZFR`V\X`PXL^TXh^bNVP X  P L T Z ^ T VFRXlXd`VPN\XdNTRFd ^ P"T!#P$P%R$'B(+N..-.-.b0X002T2J200V5T65\7X9j;:9P9R=d;9T;;R;;<^<;J>;<<78Z:76355767\70f3@/01.N4R/..P,^,,^+V-.-^/N244H2V3R23N65V77698?>?bBBCAX@HBERGEHH^HTIE\IJMjOhMVLZPTPUTYSLXPWZ[VTWZWTVRSQNPQ`OfNNNOL\PXN^PTRRRONKXIGRKIIEACbEFHKdHLGFHIHHZGHEPGFRGNHXKJPJRLXQVQRRUWX]\]^aR`e`ebLheaNedXbLavbJc^`Vbb\b\efgjRffVd_]\XYLXZYOLTQXVWYT@VXTVWNWZXUWXWVVUVVX[JYJ]PWZ[XZ\HX\^aPcglhloRmlhfjFhJeeRd^cZa[V_hXVHUdXdYZXNTXVTUUXdZZ`ZV\VXVXTU\XUZVWUPZJYZR\X\`_dZhXhkhVgdmVlfRjgTkPiLiVa^HZYYXWUTPULY^VNWWX\[]\`aZedfZhhdiTkhFiihlnRkkmlXnVkZgheiicZd\ZZTXTUSUPJQQOQTDQNTQXQSTZ]XHZ\]bTeeedeXfbTefb`ZL\ZZVPYQHPPhLVOMTROQR\TUBWXZ_DdVhJfffNh@mhVdcZh`Pa]\XTPZMONKhL^JRIDHDXERELJ\OQPSSW^\Zh]_R\TZ^[pX\WQZPTJGAhB>=RBNEBBETFKLTXPfV^UYZ_\ZbbffiRpToJk\lhdJc]V[TPnLHTK^DXA@=T@BCFDNHDG\JP^RRXUYW^[YUVUVPNNP^KLLKTIDVENGZEVGEXEXHGdKKLRPTP\PFR^TbShXVXV\UW^VPWPUNQTOPS^RVJVWVXWTLTSPVTNZKLIH^FJFXDE^EEG@GLROLZQRPVVL\H\bbbfPee`gVm`nXihbgcZb_^]R[WVV^OZOhRTKNKHM^LJJZJZOPMNXNNOOMFUObWVWRUWPXZXX\ac^`R`b^ffbaabfZ`bbJaX`]`WURUPMMLRLVMML`MLIfIHJTLPNVJNKNKLfNSOSPPSJQPVQXXY[J]\`[\_R^ZRZ[X`L]cZ\^VW\UZTUVPSQTRNJP^PZNOJPNIJG^ILGFVERFBR@AZBPFNCZGADEJFGDG^IM^KJTNKLLR\S`UTSTSQVPZSRWRVXT\TXQRXRSFVTVV>U^UTU\TpTVWbU^SRRPPPdQSPOOVNhLJ^ILdGHGZDCZ?@>AX:V<86T66L8X52f324L31B4R6^641P/d03535`55V655X75V77X8`9;798b::X>\>h=X>=<>R@X?JCH@>V<`;:b;@\@D@CV>>XB\@NB>XAX;;;d8P9P:L;:;R8X9X7Z7\510/1X2`2b32V/,V0++,\,'N+P&%$Z&%%%$"!L!\!  T^VP`VXNjV^HLV`\F` Z bV R T \ R \ V N\NN^\fTJXVT^TZZZ`RTZ`Nf^`\TP`Bf\dhL\bRRZPd^`FVZ`NNbRPb^R^PVXbPZdPPZZ\\dXL^XbVNZZ&^Lh^N\XXdTjH^^VZXT^\ZZRPX^`TF^\^ZXN\NRXVPPV^TRXPT^XdXR\XVPJZ\ZdLNJ`X\TX^VJHX^TdZT```XHRZVXVZ^ZXZ`\hZlXRZhV\PL^T\NXHNj\\\ZZVp^ZZ`f\R`ZZTTbTVVX\ZVTVXT\ZfXFP\\T^TR\JPJ^\^TP\RXR`PJXVHfPXVBTVN^dXZVLbTRRHJH\FPVXR`XXZXZPPLTRZVTJN^L^T N \ l T N L b Z Z X \ f`@PNXR`TVfXTVTbbXPR\`b T"$j$$X$''T*F,,-1^0j/H2X31T23R2\4L2V37V95j8L<9T;`>Z;:R<:T:X;TCDZFGLLMORSXVHXR\a]b^hiXjjj^kmXkVefV_V[UTSLPXLVHdE@>?BCTCZEEdDPJZGNI\MORQNWWVR\XWVTUXT\TXUPPHNKbKHZGCDVICLFVGG\HRGH^KNRJPOPURSPZRZZVXbTSXVTUPRRTRQRWRWWZRWRSXSPQNFNMKHRGGVFGFHZILJILJQQXZWX]^RacgHgfTigkZj^da^bbX\H`]PYXXQNXOLJ\HMbKNZKVMLbLMLXM`LRNNP`USYWPYXV[ZWZ\ZbcBf\beTccVdNd^T_^VcXa`VYVVYTXUVP`MOhKLVPVQLMMbILJIJZKdJJMLNQdSFTXRPSPVVn[N\L\\_b[P\B\Z[R^\TcJ[]Xa]^ZXUPVTUVTVSNSSPMJM`KVPXKhLLKTEEPGGLFECATBBHCE`CJCXCTEEPHE\FJEHVJHMTLPKNLNRR`RSQUSPUPTbRWQNU\SLSVSUTTSNVPULVURSWTTJVSOHO^QNQZPP\MLVKIGRIEFFVAF??>=>9L8P8N66\6\5T51`344`2T20412/3233385N86\7Z<>697V7`;7777:L=T;b@X@D>Z>R>?b>^=>?J>=N?@^E>`A>RA>AX?F?RABPAA@=AN><=F<9\7NN@CDRHZHPHLXJJJMLKLRNQTFP`MTRS\WS`WRdUTWNS@NR^PQRUIPN`NDQMFNXPRNLPN^LGpFNGFITIECIEFVGZIhFHKGdHdHLJG^IXIIRLOJMXQHRNSVTV\^T[^Re_^_VfccV^NdVb``Rb>bbJcbd^ddVddRfHc_]ZXW\WVbW\WPSRSZZHVUZRXXWTZZVRZZVXVXZ]^VLX]X]^Z^\^\[n]bchlh\lPp\ofkiiBdVbJbX`a`^PYXYNX^VVRYVTZWV\QUVJWXWYXWVVVXYUUX^XWVLY`X[[P\Z__RbefejZlhZoggfZe\d^\^\YV\WbWXXVNTPT^VRXZ]\[\``X`VcddRjkmjlhk\kl^qNmnPqmXlLkigjl`efb`^^][V`VRPZR\TOPSLNOPRTVWZJY^YR\^l]]XdPfZiXhPhbcfTfZedHcbcT^YRWfSOLPbMNKPIZNTM@OMDRRUSWP^^_`aHg`jdj>lkFk\jfThcT_TZYPYRNRPIKRHXHLDFIdEEIJXMZQORTWXY^[R]XZV^N]XbPaNZYVXRNPJH`GDB@D^ERFGGPLN\OQ\RVZV]D`^afghViLlplnhd\eVcV[WQNOKLHfFB@VALAVCDXEEJHRG^HJTOQUTLXTVWWTVXRTR`SROLIJHRFBHC\DDPDEDfH\JPN^NhRSVQ\W`YXZZTWSUXWTSTRRTTUXRRThWdYS\RRDPMTMKVNKHLEVIGEZE^F\HHHZLMTPRTHWZZV[_bfLfXmVjjdhRibdeZ`^\\X\T\RLPQXLdLJNJJHXKJLZJK^MZLKLLDRP\PJR`W\V\VTXdWNYL^_Hagdde`^aXaV_`J_H]haVa^YXVRNOOOLLZONNKZLJTEHIJLKRK`MLKRQTQXQTW\TVW^RWZXXD[\Z_]^^ZRZT[\[_R_Zb\[VNUTVTXRSRQQPVLTLJ^J^KLVKIJHDPFZDDEEXFCAPBCCGEGbCDJRK`GGI`JILMNJOXMdQPO\TLSO\RQSVS\RVRQVTU\RWRVTTSRYTXRTbYTbSX\TZPPXRPQPPPPNJZNLIFHEZGCXBT>P?V>^B>h<^8N6767V6h321T3R321^140V6R2X433`2327J84626J668X;`649:b9R;T=P?R>>@XDX@hBP??LAVC\@\;V;:=P7X9<\;6;R;X87533X311V0./0.\/Z0-Z+H,L*,Z))%`%n(%X'X%"X$X&X!#n#NV^`^TZVTZTRVRXT ` T ^ ` X Z T T dVN \LNZRbTTRRT^DVXhRZPP`H\^T\ZLdJTbbTV\`TVRdT`ZPVRfRXZRX`^\d^fZXX\\bFZbb^TJT\\dZZXb`N\d\^RbVN\fV\`PNPbVPd\X`ZZPRfNXHP\XLPX\TL`T`TZVbXRbVL\\TZbPbVZZbVZF\NVZTRPVZTbZXhd\X`XXjVfRdbX`TlZ^PF\VRVZ^bHdR^XVTLbdhX^VXbXXRZNhVPXVZRbhTHbTR\\jPR\TVT\BZpVNRbVbbLPPXX\fVdR^TLbTdT^ZDR^fbNXXbPZ`Vd^ZVTRNZV^RX^VXX``HTF\FVHRVR f X N V L ` \ V \X J J^PNJ`P\RPbX`\hHL\f !\"!\#$%&'R*,R+R+)-.0f/P24131X113136f9^7d9H:^8d=X:?N:;R<\:>b:^;V;R<@B??ABDNGFJKdI\JKLfKLLVOPXQQdNFPTPVSSZTR^SRXTRQRQXMBPhPQTN\MPNNNQVSUTMMLLDKJGVFRFEFGDCCXICVEFLXHF\GHXHNJbIIITHXLRIJHLTM^MRRNVRVXX]b`]d_\eH`aB^`Zd`V^Fb`_Td\jbNcRbfZdbbd^a`W^VZXWbWWTRbTBSTSSTLUWRWVU\WX^[VYTZXZZWT^ZZ\T\_]\[`__ZeRefglTlVjnkkThFfXhTacZ\daY[W`TUXTVYU\LWVXXX[XX`ZUWNYd\NY`\HZ\Z`[P^Z[`^`ZcbcdVgglkNjj`fd_T_]\\XWbWUTUTfY\U\XYZ[]J\bjiLjhPklmlpXtLnkRrofonkZigHhNieNhfVdNaX_Z_XYVVXTWPPOOORPSXQNSVZ\\^_[T^[^]@dPaZdZejZgRgdcVeRa_V_N[JZPVXRMXKZIKRHTK`JTNdNPQRSZSXWR]^Pcf\hkRnRlPl^lZjePdJ`J]TXS\RSMdOKVKPGIZIJF^INFhLPLO\MXS\RTV[R`^[aTcb`R`^b]ZWURRSFNXJGXGVDCDIVINJXOSWWV[[^\`^bTelcglkhNkhXigeX`aWhTXOXKVFEfEBA>DTAEDTEIXK`HfMLOZP`RTZLWX^VVXVU^ONO\MMLJPHRDHVBDXCLD\EZA^@ZEJIPNOTRSU`W\TZNXUXSVTRVLTLTdTSUSXQTTPWUUVPSRZOPMZNVKIHXINGVGXEHDGGZGZH\HMRQLW\V[TaZceVfXiPhDg\iNfd\fafN\_L[^VUZSJONMQM^NJMIbIIRHJMJKKPOVR`S`X^YW\UXV\Z`_\aaZbaXaR`Xb^^H[P`V]`X]\^ZJVVSZQLTPOOLQP`MNMPKIJHGVIHRMKLJVNHNNP^SbQXRU\TW[P[hXYX[R[YYhZZZL\Na[P[jURXYTVXTSJTRXOPPNKJPNNK\L\JIFHVDTBCCAVAZBZBJDBPFVDZAXG^GJFDHTEGPIIZLVLNMMQQQRQPSPOUdSQRRUUTSZUXU`TbRNTTXZSVWXVUSQUZUZTNTNRRQNOXJ\IVKGFHGH^CRBN>`??T?b>>V=P>@\A@APZ`^>^`^P`f^VPdXfZZNXR\bNLbP`N``XVXdX\\\P\ZfVXRbVP\XRXP`L\P\PXX(^PZRVdZZ^X^TVXZVT^^dT^Vl@bjd^ZPb\fXh\ XH T R ^ N Z H ` P b\ `JRNNVLXNZNFNNT\``!!"N$d')(N,''),V.d/R41L323/L525`66L5d68T7X::J:L8V;f;T<:\:X>;79b9f57H:6X;;76Z34Z4Z3`37V4T402^/,,0f.R-R,0-1.T.P+X.254d5^844^4X48L;:9<>=<=@^@DNGGJETHTILGTMKLL^NMN^OPQ\US[RXUUU^TJQTPVNVNJNTOPPNDNPJO^Q`LNOVMMLLJIXEREGEGFhAX@T=P:X=>\?@X=XAAL@\C>\>V?^@T@@==V>?lA>TFXB?@=^@:;_[YYTWNXT^TSXUVRVZ^P\J]e`P`cXjikHk^q>sTnptlNoRpomLqkfffFg^edLcde`cZ\LZ`V`YSSSPPOQUPXWZR``_V`X`D^bafZc\cgDeXjJigjdfBaV_]VTRPLKLNHNKGKVNVOVShTLUXL]\aaFki\nPooLlijiRdc]ZNWRUQMRLKTJRK`GGHFLTOHKLTQ^OUWT\Z_f^\__R`RcPb`\T\X`[ZWLVTPPP\QJDIMVN`PJNQXTZZW^N]`dccdXiPhXiPiNhkkNdLg\b\b]\XZQMLHXGJEZFXD@?AXDfEGITMNVNRTSUTVbX@X\TXVSROOXLIHZIDDNEB@AAV@ACPGDGNKZMU^WX\XYZZVTFU`TXQVWUURSFSTU\UQ^SPPNMLZLGIZJEVFLFHRGDHDETEHMSRRWTU[`Vb`^fdVfbbecVbafRa`ZPVSZP`TNNZMLVNTLNJHNGZHFETJGTMVMNNPRQVUSVWQXZZ[R\\X[T]P_d]R^B^`J__dT^N^``NaRZZX\TTRPPORfQOMXK^MJLZKFCHLFdII@O\JPMLNJLOPTPTSVST\W^W\XXLUdYFZYY\[]]Z\VYVhZ\VVXVVTVOONKKIPJfKHIGHJFVI\KEDFHVELGTE\AD@AB\FPDZDDB`GFFbKKPKJVLjOMOSOVOPQ\QXRQVRTSXVSXPTTRR\TTZUSjUQUZTVXTTURTPPMJVJKTFEbEDZCTC=P@?X?=8X8`9D7T8J55Z8V30R3441T2b0/\4\1d1`326/N1\1R3V31Z44V3R34Z88f876\;>X;R>RAZ??@>?R=?@f>H?T=B@\?XATBd@\BZA>>`@jN;P>T;;;9:b8;:X=Z;<Z7^8P:8Z888T7V84\76d6678511X31f5L3X1F5l21R,T0/h.*L-F-/Z/X/-`3..\535Z244\5H:P88Z:T;<9:\=\=>Z?dGEXFTG\GIHGHMVLPMTLMFNPOFS\RSVVJV`XRRWQRQS`NMVKdNRMbMTJKLHLMPILKKPGGHGbGJD^DVDGEFETG`I^GHIFdKH^KHRH^HZGJINN`LFQ\RVUTZZ]R`[ZL\J[]^^]R^P\`^^b_`_d^Xbede`ec`XbaX^V`[RYPWT`UhVZT:SjTNQRVURWUZWZZT[X\VPZJY\X\[RVXY^ZZP]\b_\df`hf\eRnbih`jLhjZkfdgNa^aF]\^XWWbVTSPRUbQSZFVSUUUTZYTXTZX\_Z^JZZ^[[R__^P\daZeZbTdbbfeVkjfgdh\dTgRca^Y]RYWbW\VPXXV`SZZXVbW^\^T]b]D`ZcXdhJmTon\rZtrVlqmlZnl\j\pVhZjJfXgcRhheNdhc]]X_TXWLTTUQdTRJQV^TW[f`fbba^]T`c`ZefRkVkPgiVeTeDcJg`R]\[RTNQ^RPOLPJK`KIJVKKXQZUJYN[Y\]d^kZgkNokPmfl\igfhZa_^pYTOXOMPIbKKJHVHJ\JZNMPO@SXTNYj\F]X`XbZgaVcbc_\]_[Y^\PYNZRPVMNQORLZSQLUVTZN\`VbfgehVeXhRi\gVgTeLeabb[RXZSRSZMXKKB\DLBH>TAZDACZDHNML^T\RXVUVUXNWT\VPULRQXMHLJHPH`DbF^AAV>AXATACCCDFETJjMORSTXXdWYRUPWVTRQOQPRVRTUXXRRUPQRJKdNKMJRHGbDJENE\EDFFBGIRGFHI^QRPXJZ\]ddddfLfb@bNdbR`XfL]`^YXTSTPPPMTLLNXKNNKJ\IfGLHZFPHRIdKHNRNPObORRRPWVW^^YY`]^aNa\V]]_TaT`bf_^Z\]TX^WZSZSRVPQQBOHMLLNK\KHIJRLTKHKKOZPPRK\PQTHTRWVRTVWVVWHXJZXX[YVWYYZL[TY^YXXVVZRSTVPUTXTVPXLJKXNRJLXJ^IGNHF^EEdIHGFPGNDEACDJFDJG`EXEJIRGRIJKMLJORJLNMLPNPVN\O`SR\SLSTQZRVfWR\SRU`TTRRYTRTYW^WYTZTUTVQRO@NVMPHbFDTDDXDJAN?T>@R?=??>@b@N@N@T==>f??@>??CVA=J><\A=<=N:X;=T>;V99F7;N==;;>b=?P;?=X<;;<:8R9R6R5779545F85T3V2631^42T2\0/R/H1-L,+,,/0-T1Z220X4N7643h78Z;:V8Z9:=R=T:=:=VALD^BH\EDHDKJJHXFbNfHNBOOVTVVX[TVTSVSfP\SPMN\O^KPXMNNOFKVKKRNJPKIbHLJMRIGGGECRFGRHLFIFF^HZJGE\ILMIVFFRHVJJOSOTRXZVZZ[^DZba^X]\]Lbc^]L^V]`dbVbdj`cbZcZbfc_P\HXTXYSbTTSSTQZQQbS^U\WZWXLX\ZLXUXXWV[N]X\[__]`abPcTdNePiggXligd`jea^^YSN[FXZUSRRPPXO`SlWJXVVW\W\YbZTYR]NY\]\p[[L[`ZZR^\]]]`LbXecbdbegPgiZheTdLdec^[XZ\\LXXVHUURVUZNY`Z\]a^TcVdegkhroqvPrmnTlLqlkkmifZhbc\beVc`b]^^_JZT\VW^WTUTSURVSRTVXjX^X\]Zb^aa\had^eLhg`k^g^iJkjdbb`TX[S`PMNMKIdJRLGKMLMdPTRYf[^\]\dbfeNil^min^jhdfZbdb\YRLUVNOZMHLI`HPKVLKMMMOPZW\YTX^dPfJcVhhi\dX`bheRc`Pb\^NZ[XVTUR^QNOXQMSQPV[\YY`aXdVgJcigefjHhfb``][L[ZSLVM\LDHDTGZDXGDBADGGJ\ONPUTjXURYZWVZZZYXWSSTNQ>MHFEA?HB@??>@VAR@VBDEHG^KKJSVTVYYXNVZZVTPVPPXUNSdSNXRLSRSRQHRZMPMLJNJJKFIFLFFEBbIJDRFGIHKXLNUTY^^`a_dLce`daRg`edde_L`TaTbJXTjTXRZNfLNORMVLXIGHVENGZGZDLHHZGHKJJL^RRQPSRQLWWY[R`da]V^_R][X`pcXdXb^\]dYR^[USROQFOO^OrLJjFHNFXFGJIXKMPL^KZLXMMOHQVOP\U`URUURW\RNVJV`WXYVXVX_[J\YFZYWTTXTXQ^VVV`VONLJJKJNF`FGZGRHEPHEEEGHBRDCBP@C\ECEZGCPGXHJJNLdLNMLbJMXMMTOQNTQZRnTV^S\T\PRZUUT^SZTUDU^YTTXNSZRUU\UPSTPOMVLIZJHbHZG`FBDZBR@RA^?>F?d:L=R756d9R9^646T5\2h413Z03R.^3\2\13\1T//V1V11R3d3d5X6L465N689d8D9;D=:\Z;@d>\BRA=VB==b@@B>@>@??AA>VA?Z<==X<==9Z:V;6795b7P4H6524`240T01b1R0/Z0\--j,T'^(d**V(F(&%'%%&X%^#L!fdPd^\bPTbTP\bZZV ^ R P V ^ ^ R \ ` \HNVZFRbfRPb^P\VVjNb^lVJHR^RBX`PZ^F`RVNVJZZZ^TZZ@`b\ZVbTfbP^XThZ\RVJT^FVTTXLXP^HZZdLdbLL^ZJNZ`\`hZVLVbXPVXXPdbh\VTb^jdZfN^XTVd`\R\ZFPRPTRVXZX`T^T\TXPV`L``dJZXHT^\0NjZbVdZT\\^b^dR`ZZdXJhNZXFPZP^dPhT^VLNXTXXfR`ZR^XPdZbX^^XDhb`R\^XNVdbB\``VN^Rd\Zh`ZTTTXXVjP^HJRRJZXbdTThXTXbXZfRf^^`TLbThP^VLPbJnVXRN`N`NX`^XX\RZ^Phd\ Z V H T R \ ^ ` R ^ X jV^`h>bfZ`XXRbV\^N^X\ "#"$V$^'&H,(X+L+/R-R,R/X.X011T2R5j32H332b6Z469b7Z9R:^9:=V=T:?\;;;Z9X8d;<`=T:=`;L;:96b6R767Z56V33T5421X4R2Z52Z5R32^3/.Z0-`/Z1-0j0,.2131^33X5237P5:b8T;:9=X=XBBNEEDZIEFGZG`HHLJMOZMVUZTTfSTTPYWXRTRPPZO\OMOVJOJJ^JRHTJKMJNJJJIXGLJXIPIDFJGGZDPDDEXKNKJGINHGVHLIZGKZJJHLXKMJPbRLVVNWXPZYX[[X\X^_[_^^\gXdab^J_`^hXecPbZbaP`ba`XX^]W^TZUUbT`PPS^RS`TU^SPUVXVYXTV\XY\T\[\ZF]T`[X^^ZaX_bTeXe\gg`kfTkZfkZjf^jc_L`aWbYSUWT\QXRXTQSXRX\W`WN[ZXVWXXVdYX\^T`b`]\R_aXabTeNib^bbbhhfdLfVe\c\`abcYPYJY[LURTV^QQTTSV\LV`R]Z``fFlj>k`pZppsrpps?R?HBVBG^FXGGMOJWVbXNYXZURWU\RRTRQUTTV\TTRPPXObNXNZOLPJJLKIJJEDGD\E\F`G8JIFLbLPXTWJ\TZ]V_bTifbPcZbZdRb`\`R]J]_TXWSTSMRJdLdJKRIVG^HHPFNGPELbJRLZNfMXNVNDP`OVQPWX\ZZ``^_V[V`\R\]Dab_Z^Vb`\[WZPUQQdRRRQfROMTIPLVHKIJMJTKJJJK^OTLOfOLTMQ`NRQUUS@VUZVd]YRYZ\RX\X[^P]hYN]XY^XVQSbUQQN@ObNPJfMMMLJH\GCBEGTINEHGBEbDBBEZCAEGVG\GLG`EVHFVGXKTLLHXKKMBLKLKVMN`PNOPXQZSHQNPbQVWRTSNRQbVTRdUUUYNVJ][>VR^RRRQZQLKZJKGLCDTELDCZB?=>>^@L?^>b>R=>?T?AA??A\?R@@:X==8V<8`7X9P:8T85N44T5V3\54P3b31X0//Z1V.^0R.-,*(b+*(V'V('Z'$L&b#f#!  \bJfVZZRLZb`NZJ fP V ^ Z ` ` Z j Z  X \ V\RX^PNThNN`V`JdJ\VFT^DTX`^bbRLTZX\ZLXN^NVPZ\LfTVdhZZZ\``\^X\d`ZX\\lVT\PV`^h\NZRPXhX\`X\VX^bXX\NJZ\^^X\ZVXfPXZL\HbTXZXTVTZT^VfR``JPRZfTdTVZXZR\PX^VPT^P\T`XPZfTTXRPRdRhZV\b^dlTXZRTNRfP`dfR^X`Z^`fbRZfbT\R\PV\LZ\bbRPNdZ^Zb^ZV`XNV`Zj\X`NbfDJ\Rf^XPVPtDT^bNXTjP\@dXXLfHNRZP^VTZlRdXT\JXXPTfZT\FTRbVXTXbdHZVR^R^hLXZ\HfV^ X P T Z L X ` N P Z Z T L`RVTLVZFL\BH`T \  \"%$&`(d(+T*P)X.T..L-P1.h0/X0V34^50Z4V5553L7Z8T9;L:Z<^<;\=`;T=V;`<`>;7V;=P;;=<^;R9:;N;P:9b977Z65Z7V4V5V64^2421122b131/.`10-,,-/.,V0.d03L/.^2H4L43b3H2T47X:96N>99?>;Z@DADEEbEECVJXHNGVGdIHVMZLHMOFRRXWUZRLVWNV\VVPQVNNQXN`OZLNPLbLG\H`ITLJNKIPJVJPKHJVHHFNFLHRGFZDEJILNHNMNGVIIINJKLIXLNJIMQUSXURW^[W\b\_b\`aZb^X_L_`[cRd\_]b`ZeehZdVaaVaed`^ZZWfSRORXPQRbVNNRLR^TPVXdZX\WdVZTWXYZ]L]Y`[X]RaR^P__RcbPbacVchhVfigRhPgHdXgVba[bVZVVUQXRTQPXQVQRVUW^XW[XZTXWLYXY\]^H_^T\\`[J^XaeeXcBedeTedg`h\bPcdXec`\[WWTUTRPZTQU`UWLY^\Z\^a\bdih`mXkdkqTv^sRpRrLmTljhTfikTbXiefaabT_Z_^\Ld`a]X`YTUWTTVLUUPNWZVUNY\_XdPf`iel\gjPlZghThNbcP_^V]VXVQVOKJKHJRHZHIGTHMPOPRTWRZ[]_RcgLgmRoFp^pkiDkRhdJcV[[XfZ`SOPLLJKjM\MORONQVWPW\_T`bhRhjiXg\fRjZgeNgZc^^h^P\T`^Y[^VTQRU^RU^UVV]_^ja`H`b_c^_`T`]\VUTNDL`KJFVGZIGEZDBZGT;H:Z<:=>BbCJHXGVIKLVSTTX\ZZDVWZ\R\XVU^URSbTRVTVURRPNPXRKTPMOPNTG\JbHEELGDNCdBTD`HILIXNLPRYXT_J[ZP_bNbRdbbd_Z_bV_X\V[XZVJSPPNLOMKTLI^KHFEFJXIIOML^QRMNdQ`ONSNVJV[]^ZZ_B`Z^[aTa_ZL]`F\ZYZXVVXVUQNNRNHQL@JGF^IGHfKXIKNTJH`KFMK\NTNHO\OOR`OS`TXT^QTJ[\WVVZ^\ZRY`V^N][b[WUWNZXUXVR\TQMPJLdKHHLKLJEFAFDNGFGhCXERC\BZDBdDPCBC@C\DEBbHIGXHJJdKJTJVMNA?T?A=>b?RA>L=?@?R>R@:<;;:\fLJZV`PRR^PZ^` J b J R Z X R V \ ^ R Z D VX^HTJZPXZLNZL`P!ZX ##P$$\&\())*,-:+^/B111d00b321\1V4V4V4`44Z9P8R9T9X9P<:9R;;N;\>TP<:Z<;L:f=P<9P<8L:\9\8T665845R3R/*26b43X23\1^10R.Z.0f0P,/.b/Z/b-N0L00.J..\24R3565l348867Z7f8V<;V9T@@<=PCADGBfHPHKFGIIfIPR\OP\TQhQR\SUVSPOOPQRXNJPLIQIXJHJHMXMdRORIJTIFdJHG\ELHFLICFFHTJVJMHGHKFKI\IL\JTGIXOPRTUZU[b\[V\]d\^P_``daPba`]``aN^adfee`gPc^bVa]]b]_^WR`V\SNQNZRXPSORSQQWTVU\WVUVHZVRXYZW[`L_^]f\\Xa_``HbTdi^iRhZghbbXebba]VZZXU\STNTRS^QT*T`RVTSTZZRXZ[TX\ZH]XYV^[\]_ba_cL_^LbbVgfcaHeRbceiTiXhi`g__X]^XRYWU@URVbRNPPOJRSUXZZYV]^cLedXeilmLpTlJonnRmnRlTiVfPdffPc`LbJ_V_\]_]^[Z]^]^\Y`][W@STVTWRT^TTXP\_aTaTbLfPhdgfXkNoiiHg`\`\XPWTOMZM@LIdJNHKRLJPIN@NRQ^VUV_`]^P_ZcXghnjRmnHhkjVhTdZcRa[VZVXPVVdNJLTKLLNOQZNPQNRNTWb[c^TffNjh\iLhk^kZhTjZiHfbXbba_L[VYWVSVRTUTW^ZX\X`f]]P\ZNbX]__\PTVTRNMLdJJEHGbDNHECTDHCHZIHKKNTNQPXWRW[HWUZVYV^TTQJQRJGCC@@R>V:98:R==AZBRERJXJNKTLdRHSXZ^W^Wb[N^[XZVUTVPTfVRRRTSPNPLO\MNXLJMMTNTLXKhHNHVITHHGZDXC\AVENGLPMTLbLVSSY`\\Z\\T_\_Z_hb`Rdb\aLcV_^ZXZZYVVU^U`QZOILIXLHGERIIVFKZIRJLM^NJPSLO^N^QMVPPTT`XX[X]_\]N]Z]b]Z\``^Z\^[PZZ\YYPXNUSPOMNXIHJHGPECHKITKL\L`OVJRH^J\HbQ^NSXPOQNONP`UXVVUTYX^Y]YZbZX[L]h\ZWN\WZ\VVQRQLQLTKLHH^GITFVEITDLFVBEHFDDBBAZDD\EXDXCCZBbEEGFJfGNF\KRHVIXKVLKfNDOHN^QRQO\PfORZSPfRQUQTUVSRTSTRQ^UDVYNVXVRUVZTXQRVRZQXL^HH\HHVIEZCd@\C@@DA>X;:d9T6: 998X5R7`3L4`4010X321T4120X/04f2^3V5V213T446Z7X848X6f:T7Z7d;8V9X;R<89P=P;>^AZ><:ZD?>V@fBV@d??X>NCAd^>Z;T<:R@:^87`:9843\53\14X3`03B3R51P0b/N/\,X/-\.,p)&Z(\)Z'&%R%'N%" !Z!T\ P!bPP\\^^Nf``ZVX Z b H ` ^ ` V R Z X>ZVNPbRZ^PXh\RD\\TXZJXPbhd^`ZLZ\^PfbZVZ^Z\bP^HdbRZ\F`JX^R^bRVBbZXZ\XhdVdZVZ\\LdbZfZZRj\hR^^\jJbV\L`L^PR^ZN\N^PXFZZHTRPNRZTTPbJVR`\JfZXJbTZb:jPPXLTTPT^^F\L\VVT`\RXJbVVN^T\XX\XdX`j`\\ZZvTXX\RTjNbPbX`VF`NX\dZdZPZF^`bPj^``^\Rb^NbRNbXZVVZ^JR\VV^X^PVVPV^ZZZL`P\bXXXb`VT^PVFX\XVN`ZhXfdPX^Z`\Ph\bLPZVN`XTT`ZVLVPXRThRNLNPVLZT\FXPTVP^T^TZRRZVRVTZRNX  d L T ` d T R j T \Tf\\BRT8`JVRPZb Zd ^ R&#N&%(Z)\(*`-L-T,.L1H11F212V4513V57b47V9b9D;j9N8H:;b?;\=<\><9;=\=79:X>X<;H;;=P>`;8P;J98H:T89;975P54V5V44V6X5552T3Z34V02R.1.^--^--,..Z10V2.`122X456561N7X;6T66^:7>J<>X@B?TATEJ^GAFHRHRHKXNQOhNV^PRRQVUVUVPUZSQRLPDLLNIGZLLNKJHIHKTLMFJGGJJI`FZE`EEXEbECFbILJPIIJ`IGTNRIJZLRJHHZLNQXVjTXVY`_T\^_F_^bePbba`L_X_c^a_RaaNb`cgbe`bb^^aZXP[YTRHQ\ROVVXRNWQ\U\QTHRSZUWUYdUUWX\X\]__]Ja\`\T_]a`fVhe^eXlNgLce`b``a]TYNWhWSVXTVJSbVSXPNU\TVS`TUXVLY]f^`V`\cRgebgj\kNln^ll^kggLgfVg\edcVfb`aL`T^`^_[aT^NYXXbTVTZ^WNS\XZTJVWDW^Y^]_^eXgZ_NiVflghhTfJ^NaYZYSP`OQFJPLKVGVHGIHIRMTNQZWWDWR[_`RbJfgjknnVhXkeJhd\bZ_T]YXZX`TRQNOJR`MJLLOXPP\T^RVXXT]X]`^fedhhmkkjlmLjNgdhaPb]\Z`[P[ULUT`STUZRZH]PV][T]`Z\^LZ`WXTQ@OfN>JJI\GFFXDTGFEEDDTFGGIIKP^ORQUY^VPXXJYUZZSPLMIFVCB=N?ROBRRBTLQ`YN[^XZ\`Z^R[ZXZR[TX\ZWYHUYTbWXTPPXSPLPLIHFXFTJGFENDRHDHDCFLEETFZ?TBDCLFDBCDXEXEVBXEEZGJ\GVGJGPMTQVOQfQSbNROUSNTSPPQTPU^RTRHU\TZRRXZFURURRNSXPVPJKXNVIHEZIDC\?ZCX=PC@RA9R9;Z767VfB>Z@\Bd==R==8Z776F2X2\3064^2T02b43L12F1R-,.-+))(\('%V%&%^$"^!!! R V!RLL`VTVTTL^b`d^ZH^ V V V n P ZH RZNZLRdF\VNVXXP`^FdXTRJVV^\TR^TbTPPTVZ\Z\NNRDT\bX\RV^bT\^`\Vd\DPd^XLR\`\\d\XZNXZbRTfZ^bFTNVR^ZL^^b^TJ^`RRPLXJdP`\bN`\VPTbPV`TbZ\TLXf\LRV`TV`\RNZF`VZVdB`P\LbR`^N\`\\L^`jbdXfVdTZdbRTf^^\V^^ZNPd\XbJXZbb^^^Rf^PVZ^dV\^LR^bRRXTbZ`XZXZl`ZjHXRXZVb^JXPZFdTbV^\dZbXN^b\`\ZNZRL^NJTRdZ\^RPNZfXT^B\XTT`dRRZ\Td\V`ZTb R \ ^ P V T b T X T V \ XNTTRP`NZFThLPZ N!\"T$Z#&L*T(b,P+b*>./\0\1P/T0X330N5T3R3V536T66\997Z6:P;8:R;@V@<=<=@BGJDCHHJI\EOOQXVNRRP^SRUSTVXRMDOTMZKbLMLGIJRKMTKIGJHOPNTL\KHGTK`KE`DDPE`FHCRFFGTHPLJ^L^H`I>JhILKZGZJLKdKLRNNSUXRYPXdYZ]\_b`caXbaJdX]_\da`b__c^bbVdcV_Nc]\R\XZVUSRQNLTTQSHTU^QPQTVXXXUTYPXXZ\XP_H[Z\Z]d^\\^Z\]]T^d`eRecggjLibdf_c^`YZZTSTNRZRPRVVXVPW^UYPUVVPY`XN]^]N\WVYZZ^H\aLaTaRbd_dbLc`X`X``bPd\a_aVgVfh\dNfVdH^\\\P]WVdUTPNMONTZONQVVVW`\@^aaXdZdkhXgRhLiifiTikfggXhhPdb\^ZdZ^^Zc`T^^^XZbYJWRWTYXWUVZWZWUWWWV\h^_R`acdeNgejZiPePd^][ZURPOOIGKKdFIHDIZINNRNJRdQZWVX^^_ejRfn`nPkk\lNjjRgdd_\YXXYPURPQTOMLN^PRRQSVYZN__b^bcigRjjdokJkXmNiieZg`edLc>^]ZXVRVSYPSTZTRTUdZVV\WVYVNZJTSPTQLKLHFXGFCEC\ILETETGHIKPOVMRLPMONSV^WV[\ZXYVNXVVPSRMIbEFEXAD==9Z8:7V7P>?bBdINTKNORORT\UTWX@[ZVYTTNR`QOOhMLKLXJHHJ\IPKPRKPMVKPIF^IdILFdI\GdFPLJLVL\N\OTLTTS^UVWU]`\\aL^PcZcaaV`X^_ZZUYQ\OZPQRVMIONLVHZLJMPJHLZK\LPN`PPOTLMXKOPbRZRPP`T\WUfYWR_\^X]^ZX_N[Z_^X]YVZLWT\TWJXNRbQRMXOXJI`HFGGGHFJJZIJIHKKNLNPRQPOOSXR\UWW[P[\X[P[LY[^\NXXLXXPXTVVYTS`UTM^PL\IHFJEGE@FF`FBTCEDIE\FDE@?ZCVCR@BjCADBGZFVEHXGbHXIGVGbHJLPQNMXO`MNLS\SOJRQRQQLVPRSTVLQTRPVXQZRTUSUNUJTRQQMOTPPMZP`H^FdE`FNCANAV@Bb>\=R8b8\8N7::H8\99R8251^3222\/d022h3Z/R2`01P0h04R3T2022b64H798V879:57R6Z<:\;L;V99;:;\=AH??AC:\>;;X:X:8J6X;P9:8X::b7836212T6`2R013H2R1T0^0,P-+*,P)(P)X+&($%&\"!Z! HRXPZFRP\TVXZN T X X \ ^ Z  R bdXRNLZ\NRNJXZbbVXPP\\d^VLdbXRVd\TLTL`RfDZPZPRRXfl\dVXX`ZVN\RVXbXV^N^RVXZV^RV^TV^fXRZXf\R\bRbb`^XPVTT^RhX\P^`TNXRRb\J\^Vd`\H^XR`VX\bVTZ\f^TVTZ\TRPRNX`J^VPV\VZXVR\ZRL\^TdXXbX`^b^\jFbZVd\b`L^\ZR\bXHbZ\dPXXXRd^VNXZJrh2VX^VPPXTVVf\ZNXPL\ZZNV^VfbPXPXTbZT^RP\V`TV^X^RXZZj`\VJVZ^X\VZZbTXd\Pn@Nd\jZPX\`^XJHRNbN^XVRhXfZL`F`V \ Z h V h T T ^ L Tb ZTX\P\PZbXhd^TZZR6!#V%$#+\*(,+X///,-02:3b3N53R3X26Z76J5Z59\;88f:R9R>?N>L?=<:V:<\<=D<=T9:R;H<;8898l7`67L7R7T532^7b64\1374743h3Z120^.0T,1-\-V+-R/X/1X//0N116V2234R3T8V5V567666Z79=N>?\=>@ECVBPCCZIGJHKOLPQNQPfORQROdQ^RPSXNNMR\MMHTIXJI`LXKNIXKTG`IXIOVMFRKGIFHCPBTF`JEFEGPIGGXHJFJLVKdFHMPLJLPTOVTWU\XZV\_H`beXbV``P_X\]V`Vadc`L_PdeVfedL`^N\f\RXPXXTUTNVXRQQURS`SXQPNSSTTNYZVRY[H]XX^[`[Y\^_T^bZ[JaZ^eRi^difRgZbVdPbaa^]_J\WTUWSSVPS\SRVVSVQVSWVY`]SNZdW\XWXR]Z`]``b`\]^^_`^`eViVdhccdLfgLe``X]T^T\\TUOLRPQ^MTRXUSVX\XY^cT_Pd\f^fcTdhJjiRdmPgifVk`eTcXbbad]P`^aL^Z]NYXH[WYRUXNYPVHYYYVVW[R\TZdZ\\b\>_aLeZej\gggfPb`^bW0TVQJMLIHbIJTJFDE@KHHL\LLPPRZURV[][`HeTjkkRm^jhRmXhgfd\aV]N\^fW^\NZXVUPOOPU\S>R^VVdZJZ\B___bgLliBkZmkkRlRjPkZhPePbbLa^`N^J`YZXVSQTS`SHPSZRTPWdUTWDUPVRNOMVIDLRKNIJE^ADTB`DZFBE^FTFXKGLMTLVNMORbUVZ[PZX\WUXR`S\NNGGFV?P@TAX::F889?H`<>878Z9H:8^996V53V3P1^1.L/0T0P02b10.V0P12/`3J0T1\047N43`63Z7P9^89L:f78V79L;J:;P<^=X:b<<:N:;TV@BbAn@`@Z@^@AZ<;N@<:;;;\7Z8:^?^8V798b7^4h4X4b34H4232J20`2110b.^0^.X+^)+^)(R))b'X)L'B%`$!! ^!d T b^ ^^XXV`VfF^VTT N N NR ^ \ T N ` NT VNVTXTTVR\V^VhNX`\b`NLZZ^ZnV`RRZZ\jP^T\TTXT^HdZbP`^`fTT`P\\VNbbVX`b\R^ZjVVX^P`Z`\\X^PRTVVVVNZP^DXPpTVT\VdXXjLLTR\bRN`NLZRV`XhfXRXd\`^RX\bTNPX^VPRTZbRVVXRV^bF`jT\j`jh`bXlZZnhNd`PR`hVV\XZZ\Z^Rb``df`bbZdNTHdPj\VZ^TdX^\bZ`XJ^TXRNVRbVJX\h\fNRP^\LZ6Pd\TX`dTZLVX^FfRVXTJdJ\Xf\hN^RJXVVXPR`Tb`^RZ^Xb`Nnb`PdZd^NRTV`ZFbbVXR`Xd@ ^ ` N V P ^ N d @f VV\`\XXPdFdZVP^JZRR H!##"#$Z'd)P)+R)+T-V+0P/1T0-L3X2T12V67Z6V4R7H39V78P88^;`=;T;X@b=>TAH?\?B;=Z<<;=\=>9<:98V7j884;P97935415V95^5T655252b4X/^1/.J3.0P-^-Z-/0230X111f20R545`:b244X67^8588;=X>>XAR@^GE^GGVDZEPFJKTPNSVL`OPP`RPPQ\RO`OZRRQ\N^QVLMPKXPPLVJMVK`KKVHNHIVKfKFNIXI\K^HF^ALF\GXEGGF`JIFXJPGVHIOKKGXGZJbLIMVKRPLQ\UYb[\\N\La^b^e_bcTc_F_^^\_VaVb`\bb`dea_ab\X[YRYWPVVRRUPRZUXOVS\SRXOXRTXXW`WZXZY]\]TYVZZ]P]N^Y[a]Xc\dHb\geje\ceZbacaXc[hXZfUPVTTPLUMSPPTQSSbQTU^XTURTXbYWRYfYZZ^]``^X_Va`X^aR^]a`Vc_aPbebNbdZa^[L\VZVPUVPVPL\ONQ`PdVTWXWX\]T^`^_dRcLgehfTejgiVhigZgTdXdTdd\c^X_Zb]^[YR[XTWPXUJWXU\XLV`U\WUTZ]`_NZT[ZZN`faJdh^g\fgTjPeb_]b\Y^RM\KHFDFEETFDGPGXIHPROPPZPVUWZ\L`Fd^fcNl`kPodjFimkfhfVaJ]YH\T\YZUSSTQSU^VTRTVXYVZ\Y_cca\dh^nlljTilm\ijebLfV_Z`b_T[RYUTT^OVQRNTXPP^QVTLQNTM`NZOXMDLIGhGJG\GNCF^DCCZCGPDIKRILOOTNRNVSLSRUYZ\XZTVRTZVPMMTOZFXF?P?AP=V:X<8Z=:X=PBGRMHPK\RNRVPPUVSTSZVLXWUVUTPR\QbSZPQXN^JOLdJMRKZJRLZGVLH`MLXJZGGZDHGCXDERHKTMPQNXRR\VURT\ZPZP[X[\ZP]_TdadeX`J\[@YRXVRRPOPRMTPPPLMLMVMJ\OlLIZOVNNIJM`KLVLROQ`SZUXYX\\ZXZYL[[J[^^ZZX^[]VYRZWbV\SOPOMIPGIZHGJG^IF^GGTGjJHTIL\KNJ^JTKNOZS\RONZPZPNRdXVUPWXVZXXX[VXYZVW^YVPXdVdWTV^T^UPFSMPLZNHFfLbFNCBDDC.J\FTIJF`EJGDE\EBC?`BL?XB@TAdELFGLEFHFEFRJJJL\KKONPM^NVNPOMPR QLRPSPTSTUP^RRPWVXRRTRT\NNQhLTJXLKVI\HFZE`CALEZ>=`>>b<65;789:584R53\4.2X31/P/4T1R/0J.V/`1/0Z1-322X45V5164T7n8R87V4\678;Z;J<:V;L:d;`?;V=?>@?@H@R@>=?J;9V8B78243T54V2Z2^1423N1V33<11B.d+X,(`)(`*T(X&b'`&'$$`#T!"R!  \^ZZhXbNdNZ\\ bZL h b X R J R b XZ XTL`NTDTR\\PZV`^RX`F^R`^``\XZJXTV\Xbf\TJndTd\fbl^ZZlP\\P^dNVjPffVX`ZbZhPVVd\LT\TJbXN^PV\`^`J`R^FdP`^Vf^XP^HXfJ^PPfX`LThd\Td^bZdbPbVfbVXZFR^HZ`VTdHVXVRZbJRXLT\ZN\XVRRXZXHP\bfZ^ZVTXZ`XXdXT`R^t`\db\d\\ZlX\ZfXfhX`bNVZX\TNVXVVLb``ZbZJTXVVdFPT^XV`N`^JXV`DXP^PN\VTZRXXRP\^NJ^PXT^\hdP\X\^FbLRT^HVT^FPVZTZTTVfLdRb\LZHZ\>L\^R^TPjdfDPP^NRbhFXVZ^ \ X N ` Z N `Z^\`PNbRJRPX`TZ\PTXd "!^"X%P#d$%`'()X-+Z-Z.,V/0H0P/2P3X6Z224<747B8X=JL?L@AP?:>=@P?R;<9R>;b99J8V:65^5`7:4f4R57h51V154T36T5J4321b010/X0\/r/L..Z--V1T0V212/d3P212^35`5465\56X957>8N8=^>?B@ACJLNFVGERIJ@OKNXNPQVSLPfPBPXVOLPOQOMSPORNNMJKMHMNIJRIM^JGPHKJNOXKVJJJK\HEHHRKVJNIdFGZEXHPILKJJLHGPLGRE^IIXKLJJIPWS[NUTX^[X__ab`a^c_^ca_XabJadLdNdgbce^d\`aaP^^ZXZWZWUS\ULTHQMOhPPQRSTTZTTVVYWXXN[H^R]ZZR[ZP\Z[]^`FbZced^dgHd`gae`aT^b\`[XYNTJUVZPTRRQPZPTMQST`STHVU^WU\UXXVV^Y\]ZX_Z\`aV\X[ZV]`\\cV_XhVceBfcdPcRbX`\PWZXVWQPORO\NZOT`TS`TUUT[ZRaN^`VbXghhg`kRiePehTdfcbecVcNd`abP_^X\`_^]N\\WJWXWXUbWT\VUTVTXWTTLX\^X[]\bcccHj\ifbgfac_TZPTXLKKGFGVGFLEJEPGHE\JVLTNTQZSTVPVdY[^_VaVgNjmVmRjNjLljRihTd^]Z\_X\PVWXUSSSRTWTVURX\ZX[[Z^]L`efVg\kZiPij\jTgJheT`b`\XbH^f[J^XURURPFRPRQRQNPTJHMHKFVEBNF`CBE@APBFDDZDEEJGXHNLPOQXSZPPOQTS[X_TZZNXVQSMKGAC?^>R?CAJFIVLZMRSRRRRQRUVXURSUZSTTJTPOUVMMLGdILNMM^MZKJRN^LHJL\KIIVEXGTGXH\EFLINKbRZSTVVX\XYZZZZb[XZYZ^_Ta`PbZ_X]R\RVTWVhSTRPPLRNJNOL^LIIXLHHPNJJLIZLJKMNOSTU[VYXX^XZX[T[[\T^ZZ_V]V]]ZXW\VZSUVUTPOJIHNIIVHI^JTKTG^FRJFPDGZIdNPLZKIVL^OPXOTSSPZS[WPVbZ\VY`X^[WWjZWbYNWWFTdVTVVVSXRLSRNXNJNXH^KEJETCD`CPCEGC^?CTEGBFGT>N?ZADGEBBLD^BFDFVGdHTI^HGjIHKLKRNLOQ\O^QS^Q^QQ^UN^PVNXSVR^WXVS\UXRRXVTR^PNMLNPJKL\KHHZEFB>=<`>@=^;\:^8L8;d7:Z7P642V5503P/\/`.Z3/X0X1T2..304.//d3X12645Z5757X7P57T;6R8;Z:T9R;;^::D97:T:P?<=T>Z>>>@@LA?;;>X;^=96;ZZ^XT\\VVZNZZVRVP`b`X^hLVZfX@R`\VJTRXP^FRL^L^fVdZ\VjTZL``^TJdZ^ZXZVVbZJ^XTVZF`JXV`VXJZNZRN``LJ\VNbRZXXJd\Nb`ZV\^ZZXXZ^THR^bXVPHLP\PLX^RVLNdTZZVXV\^\RNHTLNNNX\``^TV`^RLTVP\TVVL^Zr\`VZVZf^h^NTP^f`ZVXZPZ\VfTVZdb\TTV`dXXT``hbHh^TVXR`Z`TJ`RHH^dd^Z\8`VHbRZ\VV\^V^TLVVXTZ`^jf\ZZNPZ`NJdZTRNfVXRN\bZVL\FRLV\VPLTTR`XbT\TPZ\XZXJ`HVT T R j R X L V V X l B f H J^R`fVF^NRZ`fPXdRZTN` b X!"!b!!$Z'&)F)\,T*^+`-R/\1d/h1V033d23R3d7345`689T;d?@@V?\>J@X<>;ZC@f;BZC@NEETFEDPI^GLLfL^MSQZQSPOR^PNPVPMZONORQ\KKLRINMRGMJJNVKJbHVL^IJXIZKI\PPKGRF^ERIGFIDXIFXLFRGGFKMKNJJFJMRITPLMIRPTVZYYZ\Nc`T_Vb^VaZaV^J`VaTcdVbJ`NcVfebeXba`bbPb^^]Z^ZXPUXUTbTXS\MNTMfO\RU`RQPXTUUWd[^Z]Z^YYbZ[[`bZ`^aZ^cT_bRdRfdbVdgX_^\_V`Z\YVXJU^XTNT`QXRRRQVTPPYYRRVQZO\PXSRVYUZYWT\H\L`]_^F\_P^XYc^L`baZcddcabPfTd`^^aYSbVTS`TVOOOXQNPSVWRT\WX[\f]a^^Tfifi`gjhFfeTdVd`RaN`ZeZePhfaaV_][\]]NZXRWVUSUTWTUVXTVX^V\PY\]R]\aN`Rg^b`heJdac^iLcTd`_WPTMbHRG\GETE\FCRBTDPDbFLGKOZSOdWPYZ\\baddBjk^iLkVmkZidfdb```V^[DY^YXShTSPUSWSSFSXU^UPX\`]bXYf\V__LdgfhfbihfdhTb]`L^^`TaT\bb]YdWJUhT`O`OOTOPNFM\LIIFFDVDAAJE@?CBCLCBAVCNE\EPG\KLZPLRP^QOS>RTY[V]b\`YWXYQdPLIGTCCV@;:^<:^<>XBBFI`NROQNSXSTSZUVUZUTRRQRPSROSTPOJNJGGIKNRObK^I>M^JLITJJFHFEG^EFTJRLZLLOOQSVTPUZYXZV[`[`b^T^\]\[]Z[`\SUVUSRRPPVORR`MMNLXNJVJRIKMPL`LNOK\LKO^PSRTTVPW\`ZX[`X`ZRY`__X^ZZ[[\[PUTVUTXVP^PNLLIZGFEDECGNFRGJ^H\GXFDJIRLKZMNJKRPXQXSPWSJVSUfTX]`XVYZXD\WZZbWYRV\[QXVTV\WTNTPRJKjLKNNGPGLLFFZFNEC`DVDXERCZCVDRCTB@EZA^BBBBEFEDAD\DEDEVFPKVKTKLVLHJMPQRhRSQ\RPTOVQXQORPHSUTSZTFRfRdTQQTVSNPPNNILJXMFE^CPD@A@R<::8L;:d:99J7;T4^82R5R45//V232101l..X0T.N/1Z0X/12T4X3T7b4^5X4T6D4Z74D8V5`5\8R:R9V9:X89V:;\;:F9=\>=Z:^;=B;;:b<9=:;P:;J:\956^5h34N4d7N31V1X130N1Z1P1^-+,Z+)*\**R+(R$X(d&$&R"""^"R ddX!bNR``VX\^bVVX^b b ` Z f T ` T XZ\PXVbhTPVdZRLZZPVdVPN\dZ`dLV\^b`RPL^Z\ZH\R``VX^VZ`^ZTXX\RXTl\bd^`XJV^\VZV^ZRPNnZVZTVT\^`Z\R\TZXbbTRPnZVRTXXVXBbX`^Z\^d^RZ@fN`JTddN^TLbLTZ\X\X``L\N`Djd\XR\b\PPjPLX`VZ\XhX`P\P\J`V\fddV^PbhdjT\`bLLhZdl`bR`T\^RfFbbZZ\^fRbP^db`N\`VL\V`X^NNhfX8nbLLXHdPXZVNVZhXbXTT^NLHR`L$TbXRNb\Vb`^^ZTXVHVhXfHH`^XFPTZTLXPZ^DXZXP\hNf`VX`TVXXVV\VPZVXZ V^P Z F ^ T R d H \ R^Z\<JX`XNNTFDT`V ^ ! j!$$$'&Z)-X,*P,-,^./V2N1f45j4L3\44R56\67V9`9`9^>P><>jB`BD^?@6B>@\A>N?b?H<;\<;<9X;H;6T9J7J6R6556T4b5b3\4X673N65\5\63R21\0N/`/--V-f-P-/,.0V21\13R141b54321L4466Z5956T8X;^9:V>VCCACCdIKPHLNNOZRNZNPPP^PMNXKOQLfTO`QNdRSLMRLMHTNVHhMHHKJLJMZLJKPPFHGHGH`JJJFDFZFFDJJIHH^MJIGIEGMKMNLMORZWHYZ]`D`Pa_\ba`_blcTadXaXdcejiaVd`_`RcV\]VZXTXTXVSTMNHKPQRTXXWSTVYXUR[[_R\UJYPY]`^`Y\\_T`^V`^X`TcJcg`gZhVhBce`@b^^]WXSRQVX`TXTPRRQMTQPRVZT`YTQNUZVP\RVRSVSVZWV`VXbYWbZ^[V`DZ`^TbTacafeZbhfiXiefP_`V]\NZXWT`TZTPONFRFURQTTX[\Z]`VefJhTjPhgRggNmg`g\bBce\cPacf`c]aa^[^X^N\^YWTTSQPWTRPRTWVXWP[P]X^`[V_Pa`a^ggXfbeXaac_]RU^UM`L^K^GVFE\FPCRAPFFDEHZILKR^XZZ\``NaZdfPiRjklNpNkfkgPdf_TbN^J``[PZZUSUULTTQNTVT\UNXXYTWXWX\\bReNdeXgTgXgTicdc\a_Z]^J`^P[[BWW\UZRFQNOXLNLNVMRHNIFC\DER@@BAdABABRBNEV@CNE\EFGTHMMTNNQTRTQRVSLXZ[V_X\[STUSNPbJXJVFA^@T=b=>\@Z=P=NADA^?BNCIKRQQLRXSVSYRRFWZUFSQOVNPNOLMKbIHNKKKFMMLRMDM^MPNVMJILHEXFNFfGGRLXIVKNXPPZRLSbUTWSU^[[\_``^T^\YVXVURRPPUXQPQfPNQXQON\LMlOJFHIDIlHJMdMNL`ONRMPZSUV`XWRZVRXZZWT[J]T^[Z]J\\[X\Y[LVX[VRSRTPMLJJfLPJXIRGPFF`IGTENFFDJKXGIJMJJMHXJbOXQXQdVPXTNVTTlW`YTW[VX\`jY\YVYVHWRQTS\UTPLVHINHlL`DZFPEVDRCEG\CVDPABPEA>TB`E@`?ZAVCjBJCA`GDFBREfDCDNEZDNFjFKIKMLMMOZRTVQQZN^R\PVTNPXSTVRUNVRNVROMVQOXOO\OQJI\HPEGTFDPA@f>@><\8<9\96P9647X5V345V6P21P2V33R-b1Z00H/-.V-P3X1^.N/.N14P33L7V3h5V7X56V55`6h5X79\;R:J6\:7b9:;?R==Z`=l@P<^=T;Z;N;=T<:^9=<=P:V9:T9b:Z94L5\6P664l474P31\3V03^0^/0+/+D-n,L-f(X**H)V&&V)Z$%##\%P$`"RT`"^NTJZBXFXT`P f P b Z ^ X b V V L P \P`L^PZNPRZ\TRRTPR`R``Z\PZJ\VVZRPVbR^bbHX^^^`NXN\bZXJhZTP`VV\f\\LX\RT`PT`TPdNZdP`RXX^`L^XfNdJHbXXP^ZTbXVLXP^\TZPZVPh\ZTdTNZXfZXV`TRP@TBZ^XZXf`PX`\T^VVZZRZDXbH^\`djLd`bZTf^\`d``XV^dXLZ\VZ^Rbj`\X^bPj``ZLfNXdN^RXXFXNJbTV\PRTRbFdfTdNd`hb^fRb^RDffPVTJVP`\VX^L\Z^XZf``\`V\`^jT\ZRXRXTLdRZ\dT\^dPR^NZPZDh^X\PRVZbVTdRZN L Z \ V T R b RXP  Zf\XRTV`hJVNXRT^XNJ NZ#\ P"\#Z&%&\'(^*)\+\,b.R/Z01Z00Z323^7P69425 :8L=:R;R??X>P>fCDR@=AZ@==@@><\:Z=X<:<;V99R45P68L4Z54j2R2T1R033T2P3P4^21`3^12R4F2V,L..1+L-/0.X/1-J1P/R1P1\10T24214b46J543B97\;9D9R>;PAEBXCHDDHGKKNLNN\PQMQTRMLLNfTPNbVRZNSRNPP^PKXKMVHVNIHZJKKGTK`L`LHPTNPKZHG\KHTIDZJVH^JEFVF`FTHGfKF^GHPGD^LJIG\LVKBLLNNTSfYXX]T_R__VaV_^_XaXagLba^bef`XdVeNiZgebc^_D`^R`[\ZVUQNPSS`TLNON^SDUTSVTSVTTP\\^R]V\Z[\ZXTZ\_Da^Xbb`bT^TbeXhcXjTjZebe_a]\]VYTVV\RR\UQVRLOXNLVPHPRUXWLOSXSTPVRXHXZX`XZNXLWW^Z__Xb]ZdfbcbTgHeRbVfPh`^:_d^ZWXWRRPFTSTMSPRWVUZVPZ_^`^`cdNbfVgLejf\kXjcLePc_Z__bd``gR`^b_^]P`\R]N\TUTRSLRQRVT`OQPURUYYY\\\_PfL`cbbcb_aJ`Ja`]ZUPRXOZLFH\FVFCFJBADH\FRJXK\LN^SHTZY`\X`_baeh\hkhmTmied^^V\l[[HTZTBUVT^QQVQQHVTUTTUWVZ^T`R`V^`bdVdfZgfdd`fZc^\b[L^^VYZZ^XVSOMOLJLMZKXI^EEB^EZA???T@RAJAZ?BDDXBJDA`FDND`GHXNNPP\NZP^SR`[ZWF\R_`YXB[`VTYT\RdKVGGEAPA=d>>N>=J>bB?BDfDHZKJLOZNZUXUXTSbWXXSTRSbRQHMLOMJKTKKRILJhNNQbNPTMXMRMIJ\KhMVHPI^EE\HPIHLHXIVLNLMjOPNQRQSXWLVfWb^[V`N^]\^\YZYLUSSZPQRVSZNOOZQQZLPLbKI`FL^HJJL\LJNRJTM^NPP^RTUYVWRYlZRWX[\X\\R\^TZTXWYjWTFTQVSVSRPLLMKXHIIVIRGF\DXCTDZEGIHdLXKJJM`KNMRORQZUQN[JYXW`VV\XY^YRYTYXVYYXLXUUTTTQUQZOKHZKFHVGDHCVGC`D`BCEVBA@?RBRDT@NANA?ZC@C>AFTF`EC`BZDPIBH\HHI`MMMNXPNOQQXOPN>XNVTQSLTRTSTVSXTTR^QXSXKP^NOOTLKKD\HLGETD@VB>=Z>9X<8X:d7P46\;T44R4N6V4342T2R2//N0X/V.2/Z/N.0/0H4R316V6R33F5j3253`5364\5\78`7J848F9:R=;C<@T@AA??PB\>LA?Z?f>Z=?Z@JA@LCZCXJTGLMTLKMNQSHPVNLP^QPBNQRPNRRMNZNNPKLLVKQHJIXIdHNKHIHKPJIZHK^IKRG^GRIE\GZL^GGGFEFGLGF@HCHXGEE@HfJOdNLNTT\VZZVa]VcH^jaJacbdcc`VfZfdfHejhehNcgeba^_]N`T\LZTZTUVRWVRSRPTMMRZRPTXRWULZSNWH\TZL\^ZZWY^]bY^aTc\cb]T`_d_Tcf\fkgVheX_ReP`_[[RYHUUSbSXPTRbRLMMNXQNVOLOOPQ\QOPTV\RXS`UUDWPUFUHUY^X\X\_`adPaeVdVabTedifZgZaReZ`_\YZUXUSRPSdRTSUVZ\_^T```aNdPacbeljXdJeXheebZcaZbc`fNd`db\]P^V]X`XLXU`USSSLOQVS`QOPSWRUNZY^Y\]J[Z\Z`bJa^`cZbNacHdV`_\ZN^VjXDP`OLRGGXFDCVFJC@VFLF^GNN\MP^OVVV]]TaR`b^ePjZjNkRijXiTgcc\^\>ZWZTTbSBTZOQPRXQUT\TULOQNMVM\LNLGJJI`IVFZDZFFPH\K`LTJ^KIXLOXOXQQRbSRXWSU\YZWVY[D[ZR\XXZ\TFVHTXXZVVUXSQP`NIRJVFELHVF\FEF@CBA?ZC^@EL@^?A=VAP@A\ABNAPCXCRFAVDXDCEDHLGNHXJVLZNTQSOFQVRRSUSLPJPQJRQU>TTVRfSZPJRTPVP\NDN`RZQNMJJVJfJHZEDHTGB@R>\?ZB@?::`98V677B5H5P7Z574F4V3Z5N2\22X11X33X4/2.X1R-.P02113V4T423H215Z46X4\5L56\6X:9f7V6<:<<9::VAN@Z>P=X>?^@P>X>\;P;;\P^XZRb`ZnZdb\dRVTTbXJ^\V`X`XTVR\TXbNd\fjjZV`^VbLVlVhVJ`XRdPVb^\\NdXRXb\Zhd`V`\`NVPTVZ^Rh>bPX`TNLLhbRX`RR^`Z^Pd^`Zd^LTRd\XL^^db`\F^hZ`RZPRfjRXLZjHR\^`\PZ\PVLjZ^RVb^ T j J \ ` d T \ T X VTTZR`R`TTLVT`RZ d"!#$H$L%&&B&V'R)**,X./00N1Z1V3P4\5J55N85\66\:9:;?A?=X@@`??b?AC@Z?f@V>X><;X8`9D<89\7b8T64`8\2d73V20P52L1P21P31R62h30f22F0N/b0V.^1P.//,.-^1,R/0Z3^110V3L2\32P5\2J4V736P2Z8:lD?CECVFIVJ`KKP^NFMORPfQObPTQXO^RSRS^TOXPPRPRMNPnNOMMMOJLKFfHFDITHKZLJVNJTJXIIHfGTINFHHZGGFENJFDCTBLIEVIEVH^HENGZIILNSTSU[]D]^\P^F`J_bcecb^c`bbZfgmgVfedddNeRcfdeb]L_VV`V`UPSTTZS\PNO@SVQPWU^WTVVYdX^WVYLXZ[^\\\bbhdHaVcc`J`cZkdd^a\hHc^c`b`T[fY[XW^VQO^P^RXUHNPXPO\LNJRSbQVQRXM`QP^RTUW[NYLXYWZL[b^Xb^eXb`acXdd_Teegbd[]T[YXZTbWVTNSLP`RP`TZX]X_^T^^_LefeNa^cJc\cf\gh`geddbdc`^`bRa]_V^`Z^R\WVVVXUTOSRSPTXTV\VZYTXPW^[fXZ[bZN`X^a____T``dZ_^_V[WVNUSLJGVIXEXDPCBDLEVIIKZM^PS\WPX[\]\`dc`f^hRikNj\jd`Te_\RYH[^TVRSVQbPQNNQZSLVFX`TTJVWZ[J]b`aPbVcRdPg^bh^fdabaHXX\XJYUV\TTOR[QZLXPNLHJJLGDD@@R>ZCR?A?AC`BXAZBBV@NFDG\GN`KKXMM\Q\NQVWZXZ[[R\VVRWbX\R^NLJVIJBVC=>f>KDMMMQPSRhTU\SRU\WXP\V[`[`X`]\bWBZSV\WNUZVTXbWRPRZO^NNPKKVKFGXF\IXFGJXIbG^GJFFIXLLMLKQPSPTQRUZWVSWYSP\ZPY\W\ZWYTZZSW\RLU\QdPQPMMIXH`G\DREDCDT@T@bBVB\BT@@??>X?BZ>h@A`@bDPBA`C^FVEZD\EBDDjDKXJNLVGRIMLNPRPNSSVWLRZQJUTRUXTSQPZRZTVS`SOSLZNRMOP`PNKNHJHTH\IHEBV?b?PAfLT>Z?9Z:N;V?\@T?FC>T>T?P=N??T@bAZC?T;;<P??AFbE^G^H`LMMHO`OLMQPOMVNXQNMLPSPNQMNVMLNTMbMIJOLOKHJFHHEIZJbMXHPJ\LGXKHJJ`ETHNFLIEEFFFHZGRHEVEPEZGfDNEHXFVJVJTLOPTUX^Zb^]T`Vc`aaaV`d\gbbdVgiVlLki\dPf\de\iLfdd__^TYTUSNT\TVTVRZR^PPTOPV\ZYVVjYRUTVWZH_R\^[[ZPZX`cZ^`\`X]Xa\_RdXdeff`edHeTfXbP]YXYVZRQXPNOOPLXLHON`RN\ORXRRRQT`RVZPSFUVNVPUYf\XXT[aHcJbcaXbcRgjffiedN`a\ZV[XVRPUdUQfQBSRTT\Y[]>_a__RcacaTef^dRfZfHlXhiTfffN`Z^b\c_^Xc^\[YJVlUUVQQQ\Q6UJPfRFUXXNT^WVSTVPXRZZ\L_aa_b_@bRcXaV_N^\]P]LXPYZVVPLJhHXELFDBfC\IDZHPIIMTUSLW\L]\b^ZafehLkTchVcb_Xa\]`U\TQXTHSVORO\MQOdRLTXRRRJURWZX]Y^X`N]J_N_X^bZfZd^df_`YLWVUUTTPUVQMbPTMHLJNLPIEG`ECPB?AA^BHERCBCTCBRBBJA^DHEPFJRLVLIL\O^QRUVX`[ZPYZTXVdWTTNKLFE:EBV>?V>Z@=>TBBCBHBEFHJOPMPVLVUVTNXURTbXZQNROG`IIXLZM^NKLNLLVNNLHGRJDRHIGEVEHPFTKLIIMILM\ORPTPPQSY^TXZZP^TZT]H[\\VPXVRJQPSVRJOZN\PNLKHIFILKHbIZHTHPINIKH\KXLROdQfRTQYSLVWRZYYN]cH`J`^ZNZXVUTTUVYVVPTSTPPVOILOXKPJFIGPGHFRLVMH\JFIGPILPPRJLKPNOQQ\RTWdVXSZ\X[R[[fXYXLYUUVW`V\TQPPPLMNGJLITEbJZCDZBB@@VAAATB?>X=>P?=RA>AABADDElBHB\DCENEfG@KTILKRKLOQRPXRPSSTOR\VUWRLSNQ`VRZTRSZON^OXNMLVOVORRKINFENGD@?B^=>:=L=P=Z:9V56F77561L51J1T341/`3//P000T1-^/P12Z4144`1P5423f26d4^546Z66J7757N8h7:R;^>=D<`?=L>P<@B@>>V?;V;T>`>b>^;7P<\

9R:R756L79R4\8j653Z1/P3X////.T//^2\0.+T-\,P+)*&'b&%X&V$$T##`#"!R ^LRZLH`^\lXd\XV^\T P V T Z T`Td^Z`Z@^bZFJXPRVLZTdT^XXTVTTfZ^`R^J^DTbdXZb^\\T<ZbTVZbJPL`N``PfR\ZHh^XZbnL\^NThPZVVZZXLJdVVVdTXXb`PVZVXRZTNHdVZ^P`^bRVPZ^`T\^\ZVRTT\hZ@R`\V@\NR`TR`NZL`VXX\LR\ZTRV^RfRbd``VVhT`RhXjZ^VXfX^nXbVTRj`\bbT\bTfV`XbV^\P\\`fXV`XV`fZRXZV^RbZZh\VXZZ`XhVbT`RVJfZ\lP\T`NbPN`XP^dRTZfVPJPXRXZJjR`RXVNXXNbVbRpfXV`\\P\RX\`PZXTT\` \ R X P RJ X VZP\^LZNPTFPZ`RTZP RZV"""N!#$P'X'J('(^,T)R..-/P11P1^4`3P344Z7868Z9L;=::h>@X>Z=\@?d=;>@bDP?VAC<`=^?CRCRBE\HHHVFJKZK\NP\KTQPNVPObJM\OOHOXQRLRXPdOQNNMKTJ^ITN^RHMMGJI\HIIRMHOGFNKPILRMHGTHDGHEFDFDXGFC^GHTFKTEIHTNPMNQRTWb\XZYY\L]_L`RadbbP`Nbf\cdcbZeReBdeecfJg`iXjb`bZ_d]Y^WVVVTQSTS^QRRJSQVTXWVdZVWWYZ[]PZd^HZ\[h][Xbbb[cXbPcX^\b`dVdd^hfNgPfVd]ZXWWTXFR^UPQNVRPNMfNNTNOTKMJURPRMZPPPHQP`UVUjVZ]XYJ]bWT]X^Z]_fe`iddefmTfhcZa]^][RXV^TSbTQNTZQVWXXYZV^T]_b^caNddeZcehTkXlkHhFiRc`R__]PcbR_^`T_\\^P[\]WXV^USPRRPQRNNP^RSXTLXXTXY\\X\]a^ebbrgNe`afb`^X\TYYTSOfKJTFDVDCRD^DBIRJNK^QPSV`WW^WFZ_Rc`^ahRgjJbcab\]V\XXYYZSUTRQPNMJNQZPQQQXRSXVXUY[[N^\^X^V]VbZa`cFd\`]YVRTTRQRVSOPVKbHKbIHTFB`CX@?^@\?L?ADBDD@DT@ACFDCXE\KJ`INJFTKJLSUZV\_LYP\UPWRURHQNLKFFEZCR@RBHD?V?`C\>d@DXC^GXETHTJTJTK^NDPZTRlXXV^XSXVSRUMZKIbJG`JLJbKKZLNJFKJRJZJLIVGHXFFNDFTCbFGFRLIHILXL8LPZPLRWUXLUPV]P_]\ZHZVV\XQLRZTVQQPLNLRMMKGRJKGJG\HPJKNKI^FI^HMZNVQOVSQ^TSRPT\ZW\[[\^^]\_]BZWRTXWV^ZPVVRQPQLJXLJMKJPKdHPH\GZHGXK^ITNM\GFGNbKKPH`PPPPROQRQfP4Z>@?>@ZBNBfDTBC?bBXETKJI^IPJKbJRNfPPO^VLXTQ\SZQRTUFU\TZSSdRZQPRRROQRUL@KfLZNKIHEPIHC@\Ab>L><\=;>J>D@T@=b<;A\=X;9;`97968b8695X3434L21X0V0121//,01.R---L0T,($R%T%X'f%X#$#%"Z! ^%Z RVPNZHbNXXDPXPT^J\ Z X \ X j \ T Z J d^bFTR^HTNRR@ZVbT\^RbTZbR\PVlTXXRVXNHd^XPRVfXbTL\Zd\`XRL^PbVL\JPXTVXbdPZVXhR^PZ\HT^RLlPt\\\L\ZdJPLNTZZbThRH^XVff`F`T\LFVLZRXVTRR^NV^N\NZ\NTJ<\FTZLZVP^NPRPT>TRlJ\dfb\Lb\VPXVRfPjVRhFLZfX`P^Vb^Zd`RLbPVV\RP\TZDRTdZ:XPP@<^X^bTZZTd^RPbR\P^BJb^^^\d^P\ZPZTPHRJZZbXPTXV\\ZPRhVNXR`V\RDXZPRTXjRVdtPVLRTXLh^Z\\XXLRXXZVZXZZJ h D R f Z \\FfRPT\LJN^@PXPZ R\"#"!X#\%%&%+')J*V+T+P-/13X3T4T3d3J4Z4J46`9V8:NJ:P>T??<=F=@@?N>N@d=?T>R?\>R<p@DTHHDH^IJJbINMLPODMKNMXN\PXOZONP^RZTLQOTOKPPML^LZMGNLTHTIPJbNdILI\KJRKIHPFHPKhHNIKbDD`EXGhFFGCJEHHXGJHGNIEBLHIZIMZNOO^TXZY@X`\W\ZZXaceRabaZdehVfedVb\f\fiVb@dJegife`fVa_\T\RWVRRTRQ\PTSTXTPSSTSVVWWS\ZW^ZV]P\WWZP^R[[VbV_R`V_Xa_\dfbbbgBePgLh`\aT`]XXWVQTQTSBQMNNLVKMXNPMVObOPOQ^LSPPTVQRVFX\VVXWVY`YZ[Z^]]^afTbFdahVhihfZebhh`c_>\ZVRSbP^TTRQPJQPXS\WPY^WV[V]Z\_^bbceXjhhhjgjbgdf_bZaT^^```V^^^YR]ZVBVRWFTXOPQLPQPQQQRUPWXVVVWVZT^R\bBid\ddecX_^\H[D^Z`YWVRQZMH\LPIFEANCLEPGGMJNLOPQ^TT^T^WW^`^]NadihbcPf_]]P`WXUZPShRVNMNLXLRMRPFRPXQTQNPPSRLUWTY`YR]L[RZZX\_XbLa`^\`\FXTQTRRNLONMVNPLFFRITGdFTFPATCBABNBT>Z@CAA@EABGEXED@HbHHIFILMMVRRQWZYXjXZVPS^SRQMKJGCZGC?@RA?A?A@?ZCFFBGJLOPSVQVRLXTXVSJVWNPOL^M`EPGTEHJVJXNH`KIGH\JIXGHEGTHVDE^HGFVGKI^GJJJ^LLPP^OQPS^TUNUVTYXX\VWRVVTTZULTZRRSPTVRPOFNKBLJGZLZG\HTKFNZMGFGNMILIKNhRJRS^TQQZT^UVT^ZX]N[\RZ\][\\LZhVPTSbUUSVPTPVQLDJbMLhMIMNXKIJHVHF\K`MJITINHKLN^KMbTTPPZRfSPURUSVX]Z\NZ^[LWPV`X^VTUT\VRTdQLMTMZOVKIHL\K^KNKGE`CZD@>??BZBd@N?>`@@Z?@J?P@`?R?>NB\C@BTABXFRGGIJKJTRTRZSPP`QS`UUT\OTRUHURXVXROSZVXPVPbONVNVNILPPMKGIFFHRE^FBT?>>\?V;b;X=^8V88\2V5V4V44\6X51Z2Z30`4013`0T0Z1Z.1P40^1`2N3Z325X47F2X5d3F1Z/T622^3`9Z9T8485`7X:X>N<@>=>V?===\=b>>=P;=F@P>T?X=f@VZ>>bCFCHXJLDHXLJXONM\N^L^NZNVOQNFPNBT\OPXMONI\QPNOJRJIKZIXHVIJ^JJFH^HKdIGNI\I@HHTG\FPIXF\ECFEZIRIHHHFJVHIFXJ\K\INNJPMLPRPSTW[L^Y[ZDb^^`Tb\caZbba`bVaXcf^idPjVgXiVh6g^cgenbdP[h\XX^SRTQNNZSSXS\VPS\T^XWJZW^W\\Z[\[P`R[WdZXZ\][_P`hbVabXcVf`feViVgbdT^H^^\PXVVWPSSQQM\NlRILNXOHMMJMNKUOZUPORTSLS\hYH[XXZYZf[X]aXjhfPi\gnojTg\fbcb]d]PYZWWNTLOXUSPOTPSPRXTSYNW]Z[N^Rajd`PghgVgVkXhfghZh\jac``Pa^Pf_Z^NaT]\\Y\ZYYVVS\WO`SXQMRTXRTT\XTYX^^``_c\eTjfdkfdgX__\\[ZSV^OPPRJIGEDDXGTIEFPI^JLLMPPSTTTX]Yd_VefbVccL^T\\ZXYVUVRPZOPOL\LL^MNJLLNNPLPNZPDQ`TUNXTXV\XFZT\Y]H_cR^YNULT@RONXOJOJIGJZDDCTDE`?PB>?\?=XBP?A?C>AZBZHDH\HHGJVIJ^HIhMMHSVSBX\JX\VZVZR\QNNRKIELCBAB?>RB>Aj@ZA^?EGFVFTHZKVPZM\NJUbSXURPRNTVRQPMZJKG`GG\EFTIJGFXH^FIGXKRILHTGDFEEPGEZEHFJRIGIdKJJHOMPPSXQRUVYTWJYWXWTV@TT^TNSUNNOLVOVIF`JHFRFNEVH\IHJ\KPKZJ\LKH^KMfPXSXO^VHUdSVSQYYZP_`^NYV]PZbVHVR[YTVTRPPPONRLTLRLRM\OMTMTMLJJIVHDH^HGKPKVJHNHVJ\LKPVNQXQPROTSRVXY[P^Z@]VU\X[T`TZXTTROLMIIXLJHLE`GCCT>>PA>\BZB?R=9X=bA>?^=?N@>\B?>@LC^AVBZCJBXEBDJJHIMhLJLTRbQPRTPRVRZQTNPSXRZRPTU\URQ\RTO^O`LFNLXNXLKLRIF^HRHTEFRGDZC?Z?@Z>N=N9^7\6L6L5X8R6J65\741T30101\.0^30/.V1b11H11231P5\04V3262V4N7`4\62368T5V4L:\9`987N86XXRhZTZVhXLXL T L V T N R J XVRNT\DR^VTD\N  `"#X""$R%$$J)%'b)H+b,/.1X44X3Z4554^559:9\;V>l>\>>;R?=d><=?XP<9V:l;R9N9T7Z64^6j542b61Z20J110H322^5J11\221T0P0`0P.`./N-N0.0-2X3L0J3\11V11T32R95448P587===bA]ZdJaHb\adb`P`][\Y^SPONQOPN^JLNXODLJLNM\PMQPHSRVSQXVZThVWRWh\XfY[XXdTW\POJKJJHJRDEVDAdD?b@@??=?J?=?AA@CABEFFFIZIJIIPKKZOPQRVWTVZYUXPFPXO^LJMZIVDTDLERATBH@B^AV@L@CVAAE`BNIGOPNZRRPHVSUTSdTXRQMNNHHEEFFFDZGEXFFEHGGINITHF^HRDZHFFH^JG\JVHHHKJXJZMTNNfQ^ROJUfXUVW^URTUPVXQHPSXQ`TNSRdNNLNQHHZITIHhFNEFhFXHJdOLMNKNJbLKFLNO^NVXPRLTQbTRVTLYNYTZ`^^W[XXWJWY`[WU^UVPRPONOVQMKNLXNKTJMKXKGPIFPGHJRIXK\MLLMTMNP\VTPZVhTUTTZY`Wh\XZ]XUXXSdVTTQRZSZMJjHIZLIPHRGFEX@DN@A@^A\@T?>@:;:VAP;;=\?ACZA`CCbCXGIKKJJXOZRNNVORhS\TNPPQTSU^STRNRNNIK^LMM^NNLHHIGFEVGE\EHD^A??L><<\95795N42b5P38`2V511V50\/\400X0j//3333R24f3334N3d3N42N343T45^15`66T655B7f88L98^8;J<<>J><=L<;P>F9:V@>V<8<:7b55679P7:P7b96^525V563D4P30T0--L/Z3-^/,/,f*P(&^'Z$$\$Z&%%Z$&d#^!P!X" \VLRP^T^RhZPP F ` b V V X Z ZJ b RLT`ZT\NL\\P`DNL`NZZXVV^TZNV^^ZHLRP`Z`f\``^^X`\j`XfbZTfXVZX`fP`JJZVff`dZRVbTPV\RbRl`^\bNNVVbZX^bX^nL^fZ`Vf`N@XfXRPZPVZdVJ^^PXRhP\XTdPNdd^NTNXPZbVZ^VVLVR\RT`LVRJNRTT^PXZXdj\`\V`VXhVVbJZ\Z^\V\VNZVbb`d\XjPXVTndZNPXZPXRlPT\ZnVVHZT\PRd\XX`^ZdH\bHfXfbVXjXLPfL^T`VbXPbZZN^jV\TRX`^VdVb`R`ZLHZh\R\VZX`Jd^bPbZ^ZL^TDJRP^^ZTT`\ZVfRRRXXX bh R V J V ` \ V Z l N Z H P JXVXXh\\L`RRXf\Zbhd\"\"X"P##X'$%R&'Z+R*b-*^/`/13L14V58V64X5\4Z7`;\9:R=R;N><;@P>V;f=T:9;T;:d<=J==;P=d<;MPO^MLPPRXSRTJSXSZRSTVHTbSTYYW\ZWRTOKPKJ\LVLHFDNCVABLB`>@`?>T>RA?=?L@`??BB@AVDZFTFHHHKJGbMFNVP^PPSZT`WXXNXFX^VR\PONJIIVDLB@b?DT@\?\BVA^B\AVECTB`DPDjFRHXNPPVSSQUUUW^UTSPLLIFHGDTFGFGVHPHLFEGJ\IVFFNFCFBXFZDdHDHXDVKGGTN`HXJLLVITMbMDO\QQXTLXTT`TVWTWSZRbNQ\RROPMJZKHKFGIZGDFEE`IHJJJVMLJJKTKKLLOPTRbRTVNR^RRVTHVXU`W\ZTYRXS\Y\UUVPW\XWHZTURVTRPTbORM\MILKRMJIdJITK\EJGFGXGHHGLJJJLRMKQNRRQbRFTUUYWT\\[\bVVVS\VXR^SRTQRbQbOVLNOHTKMI\JbDDVFPB`?J@Cb???Z?X@V>=X9XV?F>@>^=?b;`@@DEPBLCjDZHGRIJML`MMTMMOOPQONQXPPVQPZUfTONK\QJMLPKJNMXJIJLbGFGRDXBVA`AHB\ATBV@RBV;JA>^?\;@<@Z:P9V<^988\675L:6D5956H65T41X5Z3b11V-+1V0.P,/\,+V)'&d%$&R'd&^%J)P%#$!N"R"RXRVT\\XZddTXbR`^XjR V b ^ R ^ NRf^TTXZNRfT`NXZfbdD\R\\BRhX^ZV`f\TV`LRFb\TVXTZ`\PV^VPXR`VbXVXZR^TFRXHP`VPbVX\\LZ^`^ZPVVF\TT`^VJhL`Z\PVZN\ZPn\dNbLTL`Zb^XhXVV\ZdJPVfXRTP`b^`ZZTRFXZVVVXVX\PLTd`^HbPpZd^bfh\VZX`\bl`\Zf^\lTVTPdbXF`P\ZJZbXZVNV^\bXJ\T``bZ\PV^RdRR\PP`XTPJd@\\P^`HTb^PVR^R\ZVV`PNPX^X\\\lVZXZXTHXNNT\XVjLVRDbVTZLX\ZVZRXXZXh\dR^jFP\\`TJh@\ \ ^ ` P \ f Z ^ J X RRZXV`RVHHfLNLRNdZPL N #"F"$f$$J&%'P)T,*X-,T-X/0435766P3P7P589P::<9:^=;J66T9\8643743R3.0L3T354J3R40V03F/0Z3L/R.P2//J2-P/J/`1/V1D3H1Z1N142366T8R66h;V=T=j=Z;R=AABFCRHNLVOLKdKZKNJOPbPXNbNPSRFPRNQVLN^NLTLNPNRMTNVLKKNNLL\JM`MNKLVM`KHHFEFJXJHIXGJHJHKKHdH\JIGJdHRNLMNVSTZPPRSRVW]][WR[X\]^Zb]R^`_^^^af_T_``^`bbRd`b``[_aR\ZZR\WS\TXWRW\SR\PPWVbZZYURVVWYR\\ZT[Z\WXXWYXYVX\][[L^R`Z__a`fceh^fac\bLaZ^Z\XYZVUNQTPMPM\PXN\QMLMHNJMOMSbP`RQSbW^V@WVTVS^WVXZX\ZR`bcfd\gVk`gj\hce\fdbP`R]L^WU\TPPJONLPQ^RVW\S`WPV^]>YX\aeTffhkXmPmJl8lToVmjiRjmfJccXfbRaaX^aNb]LZR[TYYRWTTFTLR\SRTV`TV\VW]D]V]P]P``eJfLkJgihjPlTfcd`N]XQRNPKLZLJPHFFEETGEGGMIMLNPDQRFUZ[\P\_\bc__^V^Z^W@P\Q^NPJNIZJLMLJMRP\PNXLOPXMQRXQOPTORTTRHTWHWUPUNWTRQ`RHNKhNRKHG^IVEVE\DPCA\A^ALAX@F?@`@A?H@?A>L@ZDTBCCCHHTKNLLNFRRPPQNRdWTXFZ^WUVQPNPJFGFBLC\B\?Z@`AHDEFBTCVDF\DHJK\QZNURPTZTNY\[^YXVdTDQRKLGE\EPGDFEG^HGVGEFHXMKIGEVFRGEhEG\HKJbHPHJKHKVHI^JTMNPUWTVWUZTVUSTRLSQSQRRNPONNLbIGLFRGE`ETGGbJXJ\KIHVITML\MPPTMKQOQTTRT`SFTWTVX]Vd\RWNT\V[V[YXTSRTTHPPTXNLMfJFJbIIVK\LJGGIVHFRHPHTLJMRMhLNHM^NNXOQVQOUVUT\YYVUW^WUXTVUTTWFTZQM`RNNL`LJbJGTJDAVDAHBBPDZA?@^?Z>=;J;d=\<;b;:;?9T=?P@NA^C\DXBEZEHbJLRLMLQPMTMdPRQbQVSVQTTOP\UOXSVQQVPNLZMOTN^HLK\LHJXJFPHJNHD^AVC@AP@=>R;T@8<8F:Z9:T79T76J:99h65R9J84F4Z4R4541d3/.X.X2T/0,\-V+^,N((`%&&Z&&b'%N&X%^#X"R#!V%b ZRX`\dPhRXVXhbPVRR^Hd^ P d R X X X X T X XZ ZXPRRXPTN^VXZ`L^dJdX`VVDdNbhXPh`\pXTX\ZHR\T^VNR\`R\TX@b`T\bZTJfbdVPf\H\\XV^`VVhnPTVfJTbL^\RVdHRR`hPZPPP^^TbLR\Z\TZVVVT^ZZ`HP\`PXZJZdVDXRRRN`RfD^RRF\XLLLVVTTNBNPdR\ZR\fZXXTdT^b`d`jlLbdnT^dRP`NZdZ\bJZ`\bTlTNbL`\bTRJVHXbbLT\JPZVp^Z`\fhbRvX`\RZhTr`nZ`hFj^bZH^ZhZbHNJPRV^dff^\VRd\ZRXRRZZPPTXZNdN^^hVV\`TJX^T`\`LN\V\VpVTPL`VXXdTVXT Z V > P P ^ F^PDZ\bN^V^ZTTd\!L"""!$""R%\#^&\&f,R)+X+R/,T0R23T33J74h7R65Z89:;R9;P=`:N=;L>T=h<9X7`:=b?:P;;=P>?^DTB\AdCDGEXKdN\MJTQRMN`SR`QJNORS^UZSNQR^PPNOMfNOKM^NMIJVKELINJ\GFHCFBC@f??^>d;?98H85b6`5H4X34X53`2V200N0F0X0`1N13R4X1/R302Z5T2344T5Z2\130d5L445Z5845\7V78d:X;76^79:9X:7:V<7d;N=l>;=@L=;=8;;;X;;\9;R9T77V8F9d76h7\944V3\312f1Z30-\+//-.L,)+b(f)b&R&*X'd&N'$'T$#R"R^"X!" X\d^ZNZ\\PRTDDR`N R ^X R X \ h X `XT`Pf`NJHXV^Z`RRV\XNRZb``LZTRFdVLLj^Xd^RZ\ZZf\T^hNTPb^ZZVRbNV\ZZPV`bJX\^^ZP^FRH`N8ZRThZX^lVTj`\VTThVPb^ZZTXlZXbbZ\T`RT\X^\P^dLP`VPXVLXZTTV\`T^TZ\^^Z\JjRZL\P\LbHTZVP`RZ^jbVbb\^Thb^T^`f^\b^`\L^b`PRn`N\XT^JT\VffLRR^hZLZVf^L^LXd^PdZT\\PZX^`VTh<XfRV^XZZ<fFJVXPT`LbR\^ZBTVRZbJPPTRdd\Zj\PRjVRTZXPVRZZJXZ\FTNXRhRT\NZXfRNVRTH\TZXNTNRVT Z X \ X \ ^ R T P NbZJXRVPP\\NLbT\\TN \Z!R h""!"Z%%H$%'X))-+`-N.,/V412578V5Z6Z7N898X//N1B/`..0d1^13.^.1X0^2.1N5X1344543:9`<9j;V<X>X>`^;X=`9L:;X;h:<;:P?L@VC?ADfBANDGVJLJ\PRRLJLMPNQRUNPPOJS^ROQQ\QNMQNbMQMNTMTKJPIJFFGETD@GXDRFZF`BAX>AR>:N=N97R74X3\733h3T34V2T2R1.F/V24/2L21\21Z4N32T11\53R41Z4D0V1f3`3^002X6\4V8^5P4\8L8T79\9f9V;J:=L:=d;^>P=7;8Z9`7\;;R87N8759577N5\3T04T5^3L2020d0-,N-`--V)(V(D(('''\&'&R$X$"X!^NN!!b\NjJVJb<V\d`TV R ^ \ d JT JbHlXb^ZLHZTd<TVRTNbPPT\VXXZJXTDTbTJ\NVJLHTbLHbVTVRdPZJ\XbXP\VXX`^V^ZRVR\T\Z\V\LbfdVXNRZTXVf\TJTdjVRT^XNTbdfRT\XRD\XPNfT\JhLFfR`L\X\T^RPZNb\LXN^\X\XLRZ\ZVjPhTLXbXfRZ\`\`fhT`ZbbbPLfZRbHZdRNZZZTd\^Vh\Z^\bPfdVRdRNXR^VZ`VV\Rp^V^Zd^bdTZX^`\\ZbXbTJV^dF^RT^VVbJ`dXVXbTVbVXZ`fZlXb^TRHXLRZ\TNdXT`VbVZNVXDNfdH\^PVTXdVb`R ^ X B d Z X P Z T PT ^ `NFX^N^\ZHd\^V\`! X!$!N#R"P#L%$\&Z*)P(^,,^,Z-b0L1/220D23Z5R9\67R;9^99T9;:;;9Z9;X:7V;J77=f9\:d9:V;D:P:8^67P7X554631422\4\51Z1\1T4\3R0R/1\-P/0.J1\3Z00J1h1X0N1H3/N1132Z4T4V66T7b88=<ROZKNKGRKTIIGTIEHTKGK\JEdFDPFEIKHK@OZLZQNNTNQTTSZV\V[VWTVTRWW^YR[PXXXZXUST\SORQLMK`MKMXKRKNIGTIfEhEGHJGJHdHFFCZGLFPKdLIJNLMVMNUPTWZRWRYXWPZUXVVUVNWTWZT`RTMMTNfLLLEHFVDTDNBD>@A>?@\@@T=H><;;;:V::R;J=?DR@T>=?@CRETI\HILMONMKJZMQOPMMfQFQMZTQT`OZQ^R`QPMRQL^KTKHINJRJZFXLE\IBCTAA??=N;Z:;9Z:Z68V5R641V40V31V/T2T0R/b3T4142J2\23513L4V4^33X3J2Z2V1132P4d4F36385P668T77R9Z999L:6d:\;J;9T;b:\X\T^bP\ZbhXT\``N\nZZVFX^hJVlXNN`jhR^dXXNdTRVXVb\T``ZJVX\`P\dRd^^F\\ZZj\ZX`VVXXZZTXZ^RP`XRHX\XZVTLR^NZdTT\BJZJXdV\bVZPRVP^T\dVPVFPPN`PLRdJDPFPVZX`JTLFXZPT`VX X` P \ Z B d T N Z R P^dVLFZDRVNV\VH`PLbZ^ X" J#L"#\$Z&&'('*,,-,\.0L42V6T7545X8\8N99;X::H:b:>:^@L<68V68P8L8Z99T=77V:B9T7`887\:V6Z5Z55V7\36333H2f6X5322212T0T0V/./X1//L2d-J-^02N/V1F.J26^1T5473456:;N;R@TCARCRAGJZIbEHHKIMJRKIHJTMPPVPLPMRP`MNVOMZOXROLPPNMOUZLNRONKXLJLfHFTHFFFRCREFFBDEGZGERDAVEVDFHFTEIHTHdKXONLRQJR\RWbTWXYb[[^^_\_^dXa]_V]N_Td^P_^^]a]^__\Pa^aR]V^_^X^`\[ZYXXTTUTS^RTWQNUPPSNTVTW[XVZX^XWV]PXT]VZZ]^XXTZRYZ\^Z[P\bZY\bbfe`lcTfbVeabH]T[LUXROQMJPNN^IPMJIRMLOKLdLLPTNORXONTYJYW_jWdXXTUY][V_^X`PgbcifheVhTaZ_^P\L[LSTTPOURVPORRUNT^SUXVFX\]^ahaVcaVfeZidkVorTsuPp`rjkiReh^ijFdXd`]\WVYT[RVPWYU\TSUVW`X\WZ^[][\]`_[]bRgjinXhfcVfTffhb^_N\\\WWZRZVBL`OIF\GLBEXEFEHVIRJLPbPQhQSLT^XBW^]Z\^\b_^\b[V]VWUWRQTTN\MTKVL\HILbLZLHMM`MPONPQNfOOPQ\RXQ^R\NPMK`JKPLQROPMRK^G\H\HZL`HHGTEJHCEGhGVGEDGEFbEFDDGFHXJVNDNbMNUTURZXVXh[WUPWURSbPjMTRN`LRIDXDA@NCHB@@RCdAR@CCfCJLGhINTLRMM>PQQUR^MRPDPOPMI\JNGXGZGFFPIZD`GJHJPKGRF:G\HNKGFFEVGG>BECFGBGFGFVK\NTQJMPPMNSPRRSTS\SNNMLXMNOJIRIFITIIZGIRIKRIKDVHEGJHXILGGZKPJ\LNJZPZQR\QZUSTXTd[XUUULVW`[YWVZWFVRXPQPNQRQTOXLO\KJMZJKVGHTFNFJPIJIRKFJFEENEGGGJPMJLPM\OfSVRUVUXUVV]VTTUTTTUTHWQONLL\NJKbKEEEFBAJE`CBA`BfBH=@>AJ;3/L2J4N5V639R7Z7D7Z:888;T8P;VZ R^d\JJH^^PX\^VL`VVLTTPVTTbfdJVbTVPZb|TZTF`Z^@bT\Nh`TP^h\RZhRZVRTb\L\XPV\^TfRRXP^`h\ddTLVRTRVZPhNT\dV\bXPPhN`TbH`HZd\hLdJZTdJRZ^N`PXRX\T^L^\VRNVRhVVHFXXfZNX^TJLRH^PdH`R`NbVZVNf`V>`hb\ZdPbZZd^bX\RbZVffR^f^`bTbZ`T^d\^Tj`Tj^\pVZZVVXV\X`Vd^P^ZV\VX\VX^XRTRbVZbd`RTPVRbVVFb^XNPX\\PbRPVJD\TP\XZRRRR\^RVPZVV`dNhXXVR^TZR\\ZN`XZ\ZPDNfN ` ^ L V \ d L \ Z Z D P VZNbRR`bTZ\RdTTT^ H!!#B""^"T"b%&&`((*\++,X-/0N223413585`8V<9:V8T;d;=N=@bDFABVFIEbH^GFIFG\HHVH^LJPMTPLXKNRN^OKPMXOMN^ONPPPM\PMZKLJLIKNIIHXFLGFHEDCdF\I^FXGZHFCZCXCGELEFIEGbMZIXJ^JO`ONSTdXXT\XXZ^]]Pe`c^eXb\\a^T^b:_^b^__^^_`]b^VaY:`R][V\\L\XWRXVRNRNOfSONQQRPPVUFVVZ\`YTVbX\TWZZ^\aYPW[PYP\Z]]^Z\\_^Tbfd^fbhcgd`^aVY[UUTQNRZMLNNjLXJlNNKJPINKVOPMXSPQSV`W\fYT\L]X\`ZVY\^NZZ[\efeVebdeDiga_^]TXWNVSZQTVQLRQM8OQULP`TTTS\TY\]N[^^fdhTkZkNmTolpqLnng\ndFjdZcDe`b`]\YNY`W`YXHULUSTTT`VTWYR[XZZHXZT]Z\```^ahgfHgXgLegeff``T]F\\X`YTZQVMMTLFLHDFEEDDEHPGJZONNNQZZRTRRJSNTRW\XZN\a\ZVWYTFQPNOVP^L\IJGHIIJMRQMNNLN\QTPOTQMSQ^NMML^LVNZLXNO^ORNKRN^MIJRKITHIRFGZGJGEHIIFC\IFGHDZHGJGPKKK^NOPNQVWXW`XW^YVRRXZTPPOOXNKHBFEECVAT@TCZBZ@@V@VB\BC\FDTJdGPJ\NZPMLSZSJSZTONNPZM\JGPFIZENHGZIjFHFTF\FIPEVJD`DDFDFVEFDDXDCTENACFNKXJG\KNM^OXOOPMRfRSNVRPQMZM@MKTIJZHXJXJ\IGFVLIFTHJFGAEETH`IDHJVJXMXPRQTPPTQSQX`WJVNZVZZ\WXVUUJYXYU\V^WPVNPORQTPRPPMKZKZJFKJJGFVHF\DDFHHHJGEFbID^GPHKIPKMVNXONTQRQVWVT\VSTTSTTQXVSLRdQSMLOTJVLIGEEBRAB@BV>X>T<:<`;Z=:9R;P9V:T;;T??EA>B=LBEXIRPNRJ\JKVOLPKOOUVPRZNbO^RZOPXSVRRPOJORPTSTR>NdLKIVIZKZLJMKFFDHPD`EBCN>b??A=;T<`R><:;9^=Z9R9=P8X7X;66:7\544b3b5`15J23/V2R13V0,.,Z-**<()*Z)\'\')d&R' """V"!V#Z"RT HfXZTTNThRT\\TLdVRZ^R ^ b R  PZ\NTV^N^TP\BLRRd`TRZVT\X\TVF^RbVfPX^`NPXXbdV^`ZZf\XRXZP^LZX\\dNZTD\\TVdfX^NXZ\TTd\JdHZVRRXV^bHJRbVL^PTZJfZPffV^X``ZZVf`B`^hRT\\PLfZd`V^b\^TTZLbP`N\JXXVNPZR^N\T\PVLNXNPVJ\bNLPRZ\\`\\ZX\\`Rd\bjd\lDRfVbd`TXTTZ^^\fXZ``R^P^DV0N`Nh\^^P^ZXdLbP\ZbXNP`ZRZ\XZXPPb^RVVRNXVbbP^bRJ`P^NLZVPZ^\`ZTVbXN`bTZRB`TbRZX^dfNLNJDVRRVbJ\^dLXZPbJ^`T^F^BXV J \ J T f P B JRXb^JT\XTFVhPXTf^\P!!X! \"Z#"h!T%&N&V)'*T+,*F00/X0Z0T1J6P32X6576R8N:89;;F?JB@HECbFTFHLNORONZQMdNVNPKNJVKZKZGTEFPKLHFGEDFCVHdHDAJFDFCCBECEFbCRDCEZD^FTDFdILHNHKOZPPJQNTPQQVSRPYQbPTOMRKLjHVFRGFHZGDKTIKJXJ`G`FZFEXDERD`EVHLFHJ\LVNMNTQOZSRXWU`VXDTTXZY`Z[WS^XTQSJSZPTFQNTMTMKBL^M^JHRJEZGFGPIFG\FJLJEVHTHFCfFMHRJJLNXNZJ\QS\UTRUVS`U\Y^SVW>QSSROTTRXUVP\PLNdLTKMPJXH`HDDXDDBLBdA?Z??f;TX?N=:\?@?=T>HAbKJ^J^IPKRKVKLlLZJKNXPO^ONL^QdPJONL^QQbON^RXQ\LOPO\JJXJGlIXNIHFDDCDRG@Z?@b>>^>;N>P;T8h5X7T1R1R4X21J2n11203R3R/N11R212N2^5451`21T0R1R0T02355102X0V5f7Z4\5T858b8R9X9^:Z:F:9:999XRX` X!R T#"X&#X"V#^%%N(*(`*V+,R..L-\0X2X22Z42547f7698\99::X=V>X>9:>R@>=RDDjGIHKXGXEZF^HKHGEbHJQ\MNMVKXPMNROPQTRPNMM\M\KMPOKMIL\OKGFHTCXDCD^FCFZBBIZJIXHF^EXELDEfFGHJIKLO^JOXQLPXSNSJZYZWd]`H_^^`b^Lc\][_h`b``V^aX^]e^^^bf`_fbaR]V`[f_TaXWUOdQQQ\RXROXOMNJNVSTFY^WXW\]^hW[\ZZ`^V^X]LWX\YYZT\fcR^Vd`Vdbk^kjih^iZfhX`^]\XPVXPMMOTL\KKJK\K`JRHJJOJVNLNJPQSSbR\WW[^UbTTXVHWV_X]`\dPgmdgcZdJ`g`H`V_P_X[VRRRTQVNXOQOPQTSTPTTRTV\[Y`Ra\^b`NdZfjkToZpVnmdljk^nffhbc``V_`^`]Z`]]YdYTPVTUZSTVVhXX\X[Y[V\[Z`__[VbVcdgfhmjkFgVeZfT]X]X[\XLVdPDOXPZMVJIBIGDFFFGJXLVKPRTNSJSVSRXV\W]TWZ\^\WXWSZT\Q^Q\QOKGXJKLVKNOMMHOOXTQRQNPNXMPJMPRMbMTMLKKROdK\OJ`NTJLZMHXJGIGGJGFRHGTJHbHPJ`GRJLI`HJJNJNLMQFSVRTTZX\WVUVXSP^QbQNPNZM\M^LVIGZJVE\ABV?@XC?N>@@ABZBTIZHBJG^KDLRbSVPZSTORRfJMXKTMTGGERFDLHHGFJ`FPEPEDZCZAEDVCCZE`ENDNF\FDRFVFDZDG\FGHVJMfMRPMTOXRNPRLSTRLSPSXQPQML^KXFGG\GXHLGKGGTFXGZEBVCVACEDhDJHJINROXOLOVSpRV\S`TbTTdVXUXU^\XZWXWZWTVS\TQPZMVPFQOTOJQNPZMPLKTLZH`JGJFDFGLEEfCPHF`EDDBAXEFILNJKMJVJFNTU`RT\UQWQ\SLTQQVTTBRPRNNRQ^NIVJIEHCCDG`H@PGDTA@>\A??AX?N=d=b;T=^:`>>J@AT>>NAN?`;:874T5X7P5Z3Z33T21Z131\0.H211b4P6^1T/\5^4Z15X32241.^1V0V2P2^246V55X4746b75::\99R;<7P8`<9X9=N>f:R;?9;;8999Z:9:8N:96R96875P57j433/L36X200.L.d-F,+b(N,X,P+X)V-V)J&&(b&$$#Z#$L"\%"b!H!VRRFbN`ZR\NTZF\ T VP b B X n J  b^R Z NHbXD^bZZTb`NnRLVjX@PRNHXZnZ`R^R`VZRLLVb`V^N^N^^PbTVPPbXV^\HZ\bTffX`VRTZRV^D\`R^f`^ZPTlVXfJXXZZ^LPPhZPZbTXV\\XVTXXZZPZX`Z^`P^TV`dRdFfR\VZTRZP\^Lb\ZdXXRVLXbHZXPbH^FRNPJTJRTdT^R^LV\N\XPbV\PTTdZV\dXdNd\p`d`^bb```bZJjRVVHJ`bXfX`Xd^`\`R\Nn`R\^`fJNVVV`dXfRVNZL\Rb`^Xf^XXVPTRTVXhV^LZjlR^JZ\NdNPbF`jPd`X`\TVRT^LX\ZZT\^XNVTRPN`D`f`RjLT\N@RN\`^ PP P N R P ^ Z R \ \ Vf`bXTd\TXNJ\XXdL\^RL`HbRX^ "##V%#J%$('R*L*,*-/10Z0L345T43R66X:\99X7X;9P>;9:b=;^9<V>@ADDCGZLHIGGNFRGVG\LTHJ^IFKMLOjRLQRRDRONORLQO^MFKfMOP\LHLM`LLbPGF\GZCCTE^CTCGC^AGTFERIVGdELGJBDG^HPJJVGJ^HRLZKXKNZPPULS^UUPV\\X\LZ_D_c_]L]^^^H_^`cNf`T^_ZR\R`d_ba`aP`]V_XYXbWVUZSTVNO`O^ONRQOQUPQRSV\VZ\XY`ZZ]RX]D^R_b\f[^\W>^]bNd`dNbli`lf^eghRh`_h\VYWYQOZSZLTMMTLIFHKVKZHdJ\LZQM^OVQRVTWRXWZ[VYVUTVP\`ahchZeRe^fgbd^^ae`cLaR]^WRROOSLO`RJLdRPHQ`VdOSHTLX_`^^`R`ehiiimNnXlZkFhPjfPnhTdaT^`_N_\]_[Z[V[DZTUPNTZRWSbVV\\[^[\Z^Z`ZZZ[L`beRdgVohRgljNgHgbg`NZPXUQVQLJMZJVF@F\GERJPF\GVIXLNLXPPNPTPRVTPXRXPX^`P[YRYRWRWT`QRTOO`NMfKMMKVPTNNXLVNOVOPdR^OVONO\QLNONNLbJLLfNDOKbLIMZHK^IBIVLKITHHIPGJHXIJ^JHLbIKKZHIJMKN\PXRSHSSUTVVUXZRLWMMMNVP\LTLLK`HZGE^DXAXA?:@AAJ@bA=dBFbCKTJLZPJOXPOXO@ONTM\LbMHKRJIZJEZKEHPJ\FF\FCEBBLCVAAdBXDVIbEDDXELGPINDGZECGRHbHVIKPKLVMQSP^MPPQO^RVTRPQUQQMKFHHGH\FXH\HRGHEGDCB?CX@DPGPFZDXIHLJ`OLNMXQRP`VLRJSTVWVVVJ]ZTXWRVhVRBTZTOONNQQZSNTKJDLMIZIGZIPEGLDFBZE\DD\DFGTHDGHXFHTMJJOLNNLK\RPSOVTTQSQ^UbQZSVQXRUZQVPMMKVLKRHGGFHFZCRDBBCA\>BLARA>V@?T@;N>=\;;P9T97N::=?>d>>@=XAB`BAVEXGHZJTHFHKLLJNPQJMP^ORNQPRLXPNRPNMO\NLLBNLhMTQXMVK\IFJZKBKIVE^GLFEJC^?CN?P?X@`>=99556\3V3^5\323f2P1`3X4N2-N11\5520L3N2V2`0B2d23^44214X10J1\234\6V63N5d4^8X:768:`87:;9J98d::99d>/J42T1V5\5d6T6b865X8\:R=V:L=R<^<;:>X=P=@P?V@H?>;b=T:8R:6V7T45V43V11F512155f2T30R20/11Z2V.-0N/T-f.0d1V4\4Z34F6V6^576P79h;L:H8P=;;P<\AbDBHEDGbHNI^KFVFZFKK^NXNIIXLMNMMOMPQQRZPPQMNQPOLMNNdMNMTNXOL`NMbNJFKLGCIChELFXCbCEPERF^GD\KIGFTFD:GHIIVKXMMQHQST^RXT4YNXY\\^R]\]`R^\J^^[Zb``PacLa`B[F`_XbHbaXbbab_J^X[X\ZVWTSFSOLPPPObPNLQ\STSfVTVV\VXXb]YX[b[RZW^XX\\n_YZZ^]N_Z`b^cRgZdJfhTjhPmigfdL_N][V\HTUVTQNTLXNFIMRKXJHLMXLVQPPRRSPdUPUdTT@WVDUWlYZXa`ae_fhgJeTeTf`hXh_`_b_YZYUXSXQKTKMRKMTMbLTMOQRTV[[N]\a\]aVjRfPiVnHoHlmjkjfgXd^b]^aT\X\X\\V`XP[XWVXVTTRZRNQfTH[^U`[`WJXLYV][\YYVY^[^acaZe^eTe\heg\g@hNdPd]L^YTZ^SPQLPQNPLLHJFTHVH^KGIHLKLSPPXPSSUdUVY`XWNYRYRWTTWTOOROTQNHLLLZKKZKOhMTMMMTMMXMNPPOTOORONbNHNONVNRQPLMXLNNPKXKRJNXOL\KZIZMHJTGKFNI^HHILGLJH^JLJPNZLOVMLQPRQPFQS\PXTXULSVSZR^NKK^LL^JRKJVFGZBCVA===>T??T>RBARHGJLQJOOP>OXQRQORNbOfNJVKGXKFF`FPDHXEEBRCTA@LD?BRBDJFBFIGXDVFVBZE^DDE`H@GJVNN^LNOSLQbPOQfSNSVXU^RfR^POJLGFGRCCEDXHFI^DD?DVCBNA\A@BDGPHXPRKNOFMLONQNXTXYR]VVY\YWHWRZRLYO^PPRTPPOHLnO\SNNLHJIH^FIGXEXDTFDRFXE\FTEAb?EZEJ`IHGFLHBJJH\MMLRLOTMOWUTRR^QQJOMdQP\OPPMOObJHGEFHDXETG`EB?@AH@\AV>V@=V@

T=<;P=f:N

X@P=:;?N>X??dB`AZBPEZD\IFHIbKGJLNSJOIJKLNXQMdKbPRNbLRKKTQVKhMM>HPPVMMZJbJVJJFHLGXHFVECDDRD>D@=^>V>\=9:\9Z;56T33P4632T2X2R60R3120\45X2Z431300L1P231Z1P34`6V4044P54Z5R45R6L:T9888V;^;N889Z9T6V9;=PdXTVTJ^ZdXVX`XXVNXPVbRNXTNZTTDHLRLPTdNHPR`d`XVb\RVN` V J  ^ V Z d T L b\^VZdNZbb`NhHRDNH^X R"`T!F X"!P$$'V&(\&&)+,<+X/f-/T0132Z44547N45^74V5788T9R:;\;\8R<:X<:Z<8\9f:8\:R=9996:J889:\9P877\7`55Z35P3X61L23X2R6T3n34V3R155/R1/X/+\./X///23Z2P4T4N6b64^6P887T;`9;T=?I^INL`PPVQQRS^SNRTURVU`XWZ^VaadbaVbhkRi\jeXkd^b\`Z\\WTXRXRQTP^NRO`ITKLJLXNPTVTTVZXX\baV^bTd^gkjjkVh\g^jheXaV`^`\RcD]]N`L_Y\X`ZY\UV\UXWSJTUT\UJWTVWT\XRXWdYN]T[H]R___RbZdhlec^fVdZbTa]aY<]RVVQVPZNLOPPTNN`NZKLIJ`HJJOMQDOPTTTTDVWdUZVPW`YUUTURUZTSTSPSNJXMVKMIJVMTM^MLXMRMNLNOZPNVRMPVORNVNK`MZL^KTLdNNMLONLXObLTO`LRKIJHTJVGTFLHGH`FTIVHRJJLJKfMJNNQZPNPNOPRQOVVXVQT\LLXJVJJXKJ\GLFVD\A\B=?P?N>?@T=R?b?CDTI\KPKP`QNZQQNOT`PNPJNRO^LZHLJHEDHCXBPC\BATBCVBADDdGDJCRFFGTCTEEVED\FPDDRGNIVMJ^LK^NRXQPOQ\R`SLPTdSTQKPPOLMZIFCbHEH\HPGBGFFADC@@Z@\AFTFLPJ`OJITKO`NfTMSRZXYX\WZZTYSRRRRO\QR^RPM`MOTPMTJLXIJIZFPGDEEHCDREdEFECABCGEBEIH`J`JGZLLN`PQVRPRPbRObUXMROMMPR^QRMOZL^KKI^FH^FZC`FFTDEXANB?PE@A>R?>@L>=Z=@=F=X;T=N<=L?L?^@@?`CTBTA^ABhEVFNHGNIJKRL\LNPT\KJNTMVJNDMVJ\ON`MNJIK\KKIFK`MMPXLJDH`G^FHBbCXC^AA>`>?L>\@>f<9X6Z8\876`213T8^48`5Z4H2^3Z/1B424`310322X101/J421N3V33R2X1Z33b7\65\645:P8:88789\9;\;9\:X8X;;P:::V8Z:;:T:Z6^8P:^;`97Z7::R7N465X6582H342310Z..//J,,Z*J,Z+X**N*(X(&&Z%$#$""d#"P"\ T" Z TJTTbHLTLDTHJXNX ^  PT ` V V T N b NLRVZVZVVVhZPNL\NV\RV\ZTD^ZbXT\VZV^RL\J\JVb^\VN`XRZL`RRb\bfdXZPHX\nRPfJVZXL`XX`ZVHXF`T^NP`b^NRbZVZ\RVTjXZP^ZZj`^b\Xb\JT^ZVPVZTVZhZPh\ZZ^Z\>fTD`bXZ\nNT^dbDfPfFRThLXZ\^T^PTRbTTXJXLdZZ`jZZbdVZZ`ZbRdXbXZVZdXf^RXZVZZ^\T\ZVVdRd\bbNfXXTb`XXRV`bNdHTNZP\ZPJZP`TP\VbNJDXHVTbZhLN`ZNLVZf\`XT`hRP`Xb^T^PPFPHPRV`TT\TLfLdZN^RZZb`bXX\XfPTjNXHXdFZZ\T\DTZLT` XZ b H L Z : V ` `B ^J`>\^DbX`LLNPR@\VRHXZTJ!ZV!N###&\((*V*H,+-,X/3R0024X485D4\33V6445^988;R9<=:J9;Z;^>J;9V8:X9Z97N7j7;777T9:9:67T:b;X3f3`253P30\42Z22L44J213V42P3022--V-R00H1\025V42V69845`98<97TXBCEANEJGNFPJ^HGGTHdPMLKLKLQRPdOOSLRVRS\RbQZNLPLZPHKIZMZMOMZMNQ^MMJLIXHJGPGERBEHDREdBCFPDGJXDD\FGHIHVHXLVKKXLORNUfTUVTVT\]]]^\a`BcR`d_^ddX\`aP^_X]N``T`L^b`L^PcZ_]\R[YVNY\TSPTQS\TMNQXTQRVTX\VZ\XVZ]_P`][R]V__L^f[N\^ccJg^cXgedkPeid`hbfReXf_[d^XYdSNLMI^IKbHKVH^IKVKKXOLOZM\T\MFQQPOTRWPXBUU`UULXV[J]RcjgbVjmilefPf``\\YRXfXTFRZU`OQRJOVMTKJTNZSTVTTWZ_V\\aH`\eZdXjk`hfkjRohHi\fd\dXaJbT^b\NaZa]\[P[\WX`WW\SJWZWRSFRTNVTNWXVWZ@[ZVW`X`WNWX[^T^L\]bbTegNcbLfad^_a`]]TZSTTNU\SRPQTNMNTLLZL\KNPVOJOQVRVUWUWZUUW\XXbVP\T[ZXSPRTRXLQVNVOLPJKKXPROhLPOFNOPXNBOVQJSQMRQTMNQONLZMOLLRONVNVNPNO\N^LZPRMbOKMNIIF\DGPGF^HJJKKfMbMTMR^RTROXORXUORRTRdRQRORNXMMKbLGLEFVE^D?^@V<>J==@?>>DDEZI\NOPNPXQZOPPdRNML^KLIFPGFVEBRCZBATA?\D=T?RAJB`CTCFVFXHZIdFEVEHDRGRBRC\EPHJXI\JZMNMRK^MVOQSRSTP^TFTPZQLLKJ\JZJXGEFHGIGEXE\DNFXBD@\BBBEXFEZKdJMN\PKNNPPRRUXRLVJWT\WRPZRSUdOJQTORNXQPQPTMIMHFE\D\AVCCCXChDVC^ChDRDZEDDPFDZFTFZHHHGJKLLTQNSNVQjRUVPSRNTOMLMJOTLZOLVMJFBHFRHEVFVDDAN@VB?@?T@F?=>L>`?<^:?`?=^=b;=<@`=A?>A@CRDTCjECLMIKJXMKNNDMXNOOfLJMRNFMKTKKLRLKMLTQMJJRI\LNNRJ^KVHGG`CDIF`CBZACP@9?Z:V?V=76V:F8N6d7Z35336F5N1L44302Z10B3`4Z2N2Z63X4Z5T2P1X0542262^2R5L22Z64\5955L847R9V<98V9H?Z@\CDDD\DGZEVHZJTNKINZJbKMXK`LPLVNSRSUTRZR`URROOMdKXMMNLTNVMOM\R`MNJHNTLLIKTHEPF^HRGTHNDDVDCNGEFFNFEGHDGdIPFXIKIJMRNNLFN^SPTRW`ZL]X[_V]\T^X_JbL^d`T_``RaV``\_N`Nd\b^^_^R_^adPcd[\ZWT\RWROLPOVU`RTPQXSdQQQQTYTVWVZWT\]Z`\L^]^`_N__N[[][ZcaXbPdafReViehgReXjXaR`V]VYRWUNP^QPRJ\G\MJbLJVJOTKPXQLNKdKLPZSRUV^YYZbXRYWRYW\]LabRjfJbdifiJfdjc^\Y\XVWZPTOVNVKXOKMMJNORRU`VN[\[]`_`jgdj^ilkVjPeg\i\dR_X`bZ`^aV^]HZ[`YRZYZZWSPTQURPPHVSbTUVVTTV_VZW`ZYXX[L_]J_ZbcZcZbbLb`ad]D^\P_YWYTRTQTOTXbQRRM\OMLQRKMdPNNOJTTUVT\WUUZSWTWTVZUVTRSUNOLRMZKMHbLBMOTOMKQXOKVQNSNTQHPPZN^NFOLXNOLNNMKhK`MNPbOOfPPRQ^N\LKJRJIDEZGFhFFFJ\HIHJLJVMNLVNTPbOTNPTTRRRPTXPO^PXNRNKZMIZECD@?@T><^BAT@`CL>?>=>@XDPBVCCVFGjGDTDCPAVBA\BFVKKZOLLJZLbLZOLSRRNSRPNRdRROMXKHFGGGXEFZEGXHFNEXEBACTBBHXCXBIETJJTQTMLPM`RPOXRNTQTZTFWTTbT^SPRT\PPT\URQPROhOPTNNNMN\QTKNLGXGZEDCEADHCCCBZ@BCE\G`FHFGLIRGRFDHC`IMIZOHNZON^PdNRTMXQVOVP\QPNOMKVK^I`L\JRLNFF`F`HDNBZCDAP?bB^A@N@>VBN=f<@Z@:;B=Z<=;>V@@bAL@^@@F^ALD`EFCHLJXL\JNJNMJKIITL`LMKIHLLZN^NRLXMNPKPKJLJIIJNTHIXIPHbIJVDXBZA>?J@h\:<<>=76J9:R647P8\6F5T7b4103H2212P1j13P1T2b12d1R3b043X5P41X1d5566V534f57l6L6767Z575596^:R89N:b9T9V86V7V99J8F9`:N8`:L7Z=<6V9F96`8`>;X>T@?X@NB@APCTHRIZJXLJMR\NMZP\N\LOLLIXLGGGXFDClA\??@R?====\@RAXBAbBXEJECBTAPADZEBVGBGTGZJKHLLRNXNNNOORTQRWQPQVSTNLINKEPFZGPGFFIHXM`GFDECBVCBLACG\D^GFNIHZJJMdMNRQ`RPSbUJUUVUXVFQRXRUTTLQTTUTNMVPZTVPVIMlLM\KJEED@C\@VAXANA@NC^EBAC^FDDdDXFVFEFNIFVLRMTM`PLPPNNROOVPROXRMON^NO\OM`Q`JLKRIKHEEHTFFBF@^ANChCN?=?^?X:H:RDV@d@P=^<9;T<89P96Z72L53P4`433Z2035T403/N31V2d2R2L51T0H/4\2\4d31^112\2R3Z63T7L5\36X74l557X77T8:6Z:Z9L78;9J;9D7\;6P:<99899Z;P:f:7^88X8758H474432N3Z1./.Z/V-,-+*),*&&&()`&Z%##"V$ R "H!bV^^^bX`LbxXTT d \ V \ J P \ Z L B`@lPf\^RR`VXXNVR\\XjHTTTXVjVPPHPbPbR^VTVJhbjVfV`\Tf\ddXRVdZf`XJTRbR\ZPV^H`ZTZZVTl\bNdTbVRZV^RTXZHdhX`bXhN^VdTbbPTNbVPbd^L\XJ<NLfZZVN^^\ZVLXZTTT\^RZfRX`\\NVlX^T\X`PZV^XdbX\`ZbZ`h^R^^\bfVX`fdTR\^nXZpb^dN\^bL``PnVT`FfTZ`T\Hlj\\NZZXNZVZVT\P`TZ`TpbVV\VbPlP`\V^VbT^fTZ`L^XXTdf^TZ^RXb`VTfhfXVZVXVhDX\JVVZ\V`Pb^NNJTNVRRVRb^^df`Hf^dR B Z ^ R b X N Z V F ^n^LRRFZ^\XT\XRZ\ X Z !X%"%$V%('X*T)/,`-0`0R-H/02^401153Z02Z3546R8^7T9P8:7;d=Z<:9P=:L9`89:R98J898887F777d8646R86X22111D1R2j5P2d3d3T/4L3R5T23b2R3T0V/N2P5d2N3316\135Z6b7^3666R^=>=R?XBDDRDGFHGLGHXJPHLfINKRMhKfNPZTQDURUWXWfVbS`QTTZM\KVPRMLNMJNOO\KOLTJbJbHLHFfACBFTG\EZCRDGbFHTHRIZFHPIRHVFVH\MHLLOLO\RPS`RWZW[VZ]f]]\`N^bVaaVe^V`]]a`cbchb`\__`R^``XeZ\VPTRWRJUXRTPO\MMXQPOSOTNR\USVYW`ZXZ[`^Tab@`\aH\TXb_VZ[eZ[\fR]bZ`dbTgTcaa``]X_TZP[XTQLNIG`IKJDGTJKIFdJKdMVNPT`SNTLPXUTT\XZU[XWX^VXV^RaPdfjZiabe`efbbNhNaZL^WUUQPSTPPPNKKTPXNRUXY\ZLcRdf\iLgkVmHjijghdbdc^Z`]^^cd`PcZFYTYbYVWZWVRTXWRRQURPFUNTXQTUPhUU\VVVVXRZJVbXXRYbZT^fbV]d`R`P]Xb_^db^P]\cXa]\T\RUV\ZPVQ\QPRSZOdNQLORTORRQ\UUNTXS\TfPRTT\WZUUVVT\UJURZPOPJKLNROLOONQNPMRMM`ONP`S^TQROMbNXPVOSOZNJPTMTO\OR\PHP^QP^QPLPLMXJ\KPE\EREDEDEHFLdLIMNNRL^KL\NO^SPXRFRZRRTOMLLGTLJNGBl@AA>Z=bA@P??CENEEGDLKLNNZPfOLQ`LTNRLLZKKXIFERDCAD@R?^?==;C>P>@B@@C@BNA^CRBA\ADXBXCVHRGZKJRMMKOTLObQORQTROLSPZKXJKFXFFdFLEFHdKIEPEBXEBCLACDTDD\EFEIG`IPJJL^OSPSSVRZXWQXUJSXUWVYSTRST`MKNMKLPONZLNVI\G^FFCAbB@VCACBCZDBVCfEBADVGbINE\FRFLILTLNOMVMLfO@QNRNNSNNNJPQZJfMMTIXHFIFD\EVFHGB@XAA@BT?:;=9;N<=?==V>f=<=^@>@X=RAA>AEREGjFF`GHRLXJJTJMRJJVKLKK^LTK\HHIKVMTQXMLKHVKXKdNLHGRKXIfJNJ^CEDCD\B@?>AH@>::<:98`:V7X8X325Z4Z331410N312//P15f0V2P52^213X4N4V315P52T43b10`542564b43b54^6X78V8Z7h8;V:7\78;9\89\<:989V:N5X9Z8P:V7576413210X2/./d-T+.R*T,+V,T)b(T%&T'L'Z%N$##R#!\"\ V#V JXTPNPVLT@VV^dR Z f V ` V X V Z nH RRZbLXTVZNPHZXT^bF\TjbT`fPT\dh^ZHTPHTl^VT^Z^TTTTb^ZZTRlfR`\\^`NV`^JXRdNZT^^pPRXP`^^bLbNJX\^LXZ\`VTZb`VNVRVNXL\^`d\NZ^PPXTZhXJTTXdbVjJ\jfTLPTVVDdL`VXV`\DTbTbXVJJ^RRZJNV`\^XVXHF^XbZ\bT^\P^^VZ^L^`d\`l``P`bTnP^bVZT\p`RVRZ^XL`JRV\HXdb`ZXPXTh`dhXVDVXR`X`PT\`NRVX^RPPPRJVZblVT^fZZXVbPf^RNRXT^RRTVXPdhN\PFZPVRVdVRf`VTfPbHRr`DRTT`lTJFZ X R Z X ^ \ P Z V V LRR^Z^RPVZ`fLPVP`^Rb Z !J"b$\#Z%%R&)V%P+*P)*-^/,j//3/2`1012T1R4N2337L5V97T88^9<>Z;^9<8:9b;:9L99`68988V9`9L6N68L984T5j9N62>4\0N021R321320N213Z2R310F1^1Z1R13d34V4N314V73T2X678V;:N:;Z9T:>BA?ZCCGHVFIHHKIK^LJJbNZMMVPRQJTVUWU^UVXRRO`OpNN^LOQPPLNPPDLZQNMIHIHIPDLCBEDDPDFEXFITF`IZGFHPHRII`KHFKIVLNQPOJOPJWPVZb[VYJ\a_R_Z_Z_bXac`FaXb`bcXaV_bcidb`dNc`^]V^\_]T]\ZRYPYZQ`RXRSPNZMMTN\RRPPPPPVS^TVT`SJXTW\X^[P_`caT_b`^f^Y[^]Fab`N]f`^aebbh\eTd]^^X\RYPWVXQQTOHLGJIFHJMHJLIRIG^ONPTPPPPHTQVTNUT^SZX[^\]]]_c`f\bXdfbbcfeNcac`^R]`[`TTRXR^PFPPPQTXOQPWQXY^\X^ddhiFmnNijPjlmVhigbb_Vc\]^X\R^[]ZYL]DW^WRTUVSRUTXSJSQVRVTSRXTVXWTXZYfYRVWT[WZVLZT\P\_[P]N\^_P`^[L_`]`TXYXUSSTU\LONHP^PNRP\PUNUQSRRPTSLSULU`RXQS`SRZUVUUSVVJQVUVOXMKO`KRKVMQQPP\PQONPPLN^RTPPZSZOLMNbQNORQLT\MTSORT\RNNRSNPbOOOKJ\MLGGXGPDREdEEFGFHHLRKRNMJXLNONQPZSX@@V?N@ZEPFITE^KVJTKJM\M\OOPRZOVKTNKJbGKPJNHZGFBAT@A>>>=RBd@@@^@AA@XFVDVCTB\ACRA^CPDCEFGGIVHM\NTMHPVPQSJORPXMNXPLG^HEVEEFGJJXJZHHXFCXE\DP@CXBNANECZEEFHEPGKFIKFRMJRU\RQVWPVS^XQJSbXRXYXUTVTZN\KRKNLXNKHJ^JKHIZFEjBDTDCA@B\CCXFNFVEZCdBZDGbHDHHRH\GGKHLJM`LLO\MTNROTVT@QVRQP\MZKXKVNK\HZHE`FNDPFVDFEDE@TD@CZBP?T=`B^>A^AXD`CAIFfGFDTJTJK`HLbM\KJLTLNKLRL\NTLHJ^JnMXM`LK^MXKL`LJDRGRHGXGDGCbDBFA@Z>LAH>V:F:;b=RZ>V><>?\BXBZD@T@Z@AVCBAT@VEAB^GDTEDGFZFLPLLPNHRLMPRS`QRQVNPTKIVJHFDZEEJCHFPJdIVDDFXE@VA^>@FDDCBHIdIZGJKHXI^OQLPZRQXTYXTRZVTHXTRURVBZZXRRQORMLGHIVIbJIJZIRFTG^GCLFDD`CTDBZBC@ZENBDE\FCEFDBJILG\HJLKK`KTORO^QRNQNWQQVQOOPMZM\M\JIGbGHZCFXDXDGNC@C@TAAX>>>:X9<7;:>N=<`=^:9N>bCB\CHFGdGFJHJIKIO`MPLK`KXFZJVLMLTMXJNLNVMbJKTJLNJNIRGEJVFRHTEXDbCCTBZB\>?P?T^5\6`76H89X9;Z<^;=@C?=X@^BC`C\DJLLfMJRKPN`PVQQXQPPOXLLPMbKGRFGdFPGPETAAA>@=PAAbCAbC\>CZC>>@TCVCBBDDGVF^IGGII`N`NTO^NNPTQZPROfLXNLLNLGPHFFEGGCHVFhIHHCDCZCAXA@^APANCEIIJI\HXHHZK\KO`NPSNQ\TXTPUWTSRNVRRZ[^WTSPVRUPRSVONLJZIGNGVIIZH\KFEKGGDDBEPCCPAhA@CACBCDCDLFEVIbKPGHPKXNbIJTOQMRnRQTPVMZPXPOTQOJNKdJXLGPFDB\BRC\BXCT??@RA^?T<;P=8:X:9:;h===;d;\;=P>AX@\@T?A@PAX@?bCXI^GGJGKIXK^JMLL\OXIKKGILN`LLZLJJjKIZJIJLJLFHPC\GHECRB\BNABAd@=`>P9X;<9:Z9:7255l35R8f2`522T30Z0d1/1X2R/17441R542243`4H3435133P43443h5H78T7Z7^37`7L7R9`898766^8:7V78V9787X98Z=RF?JB@NGETEXGFHLJXKIjFRJJIJJJPQRNOdQSRTfV^VVURXUPOPPOK^OXO`Q`O\P\PMPQLLVMIJKH\FDETBPE`GBGZDDFXGJPIJGJJHIhPGXHITKLPRMVSUVRTVVZ`\[]_beTgbb`bch^fdfTdFcX`edfXbX^Ra^F\ZZZYXPUTlPLROTLMQLML`QMNP\PROVShWP[^][[`bca^T^P`JYZR`Z^^^aTbXf`NbTccbbc\bPYXX`SR\WdSI^JKGXHLLIXHHJMNhPM^OLQR^QSS\TZWYHXfY[f]^[\ZT]X`^\h_T`jbdRe`hi`ZcXdX^D^ZP\ZW^ZPJP^POfNPXQNRRRXSW\TU`Z\\bP`i\i\gPlkkdg\i^iZhlga\\]^X\ZZ\Y[VXWYNWXYTPVRTRXUNQXOVQMPOZRQPXW`RRTRNRUXWTRSZYZS\XbWHXNYWYV]T^Z]N^bZ]V`_`]^Z\YR[VYRRVRFRVRSXQQS`OTQVRVPSPQ\TRTVXXTNThTUXSRQXSFUSR^WQPLSPXT`NPPNQ^ONSOP`NJQLPOLQZTXPZNbPMLOQPOhRTOP\RLQRSSTRPVQTO^JLMLPMVKLE\H^ChEB@NGRGIIH\FZHNKPNKK`LXIGIMJRJXJFTKENELDCL@@>B\CP?AN=@ZCBJFELEEH>A?@X?>@>f?A>VB`BJ@hAVC^FGJPGNHTGTKKRJjKHLLQOOOJTMIZHRJDI\HXDVGCFJBDVFFFFXHCBXCVA?ATCNDVI\IIKHRNZKIRKOXNOSZUZSdWTUXSVRXVFVVW\YRZYVROJNM\LJJJHJbK`IGDEVHXDA`DPEDADLBh?^A?^DV@CRETGE\AC`DBIMHI\KKdMRJMROJPNRTVRSXQP\QQTQP\KNOIJPGILH\E@DBVCBt@B>>=A^Z<,:`:h=N?d:P9=h@L=XL?V@XAVA@BXF`HTFGTG`FFIVJJJK\K`IHXGTJL`L`NXIVKKLLN\JLKbJNIJHHbHE\GFGXB\ETC@bAA=<9;=:P?;7H;76R584F42R4^3Z11Z1101N0/P22^42b233X444V3355V3775Z45h5T4X7466N4`5Z55T8P7T7`7^6T36V5747:b889:78R9X:X:N=@>\@JVObQQQVQlSSPST\UYXQbQSXPNORLNRNFSRQLKRJ\L^OXKXGGFFFE\GDFBTHGCZFVHRDPHMbKHNJJHbKTILLTNNMTMRRSTVSRYUNX\^XL[P`Vc_Rd_gbbgTfNeRgfVgaaRb_`VdbJa^c]P[_ZXTJUTPXRJPMnJJILJK\LMNPTOTQULTjUXYX[^^]``RbZ_]`\]_aVaPebZe\eedTfRcVaRc\ZPXUTVNWHPOL\HXGJIJIZJTMQMPPOKXMPZQUbORVNTSJXX][NW`WLY]L^\]\P^NbbfcadgeNea`^^^c[PYZSNRQXNPT\OVQ`RVTVRX\WW\X_T_VcdeZn^fiXhkfPi`oRfLfRia^ ZaZYRYYX\WV\LWPVZVnUXVURNOOTPQhQNNRPTVQdVWTUTUTZXURSfSXX\XRX[[^`P^T^aP\\[]^\PYZ]F\V]V^UZSBXTUTS\URSURSVPXRNNRON\UZQTPUZSTUXTPWZVTTSZSSjUVNVRQPPPOMXQLPPQZMTPdNMP\QNQZUZSPObSQRK\ONDOPPLRbQQTNVRNQVQOLPHZKVJLPJJEJF^F\@@fBFCEEFZE^HZGNEGRHHIbHHK\IHHLFfEEDCZB@Z?A`=>R>ARADEb@?PENBXBREFLLTMLONOSQTQNRLKJ\KGXFVHCbE@B>>@>LBPBAA>AV?>@Z;?HB@^@PFEZFI`IJRIF\LJLKKJRMRKLMNJL^IRHXF\DFEJNGVDHE`DDEADNACbCCNAZEERGPI^KLHKJ^HLKZMOXPVSPQdUSZUXSTTVYHWZ[SXT^RSOROVKKNTKGPKTLIHTDPCH\CTEDRACALAP?VAV@?VDTATBHEGDPDCRGFJIfHJFQVKHKOMNLRRP\TSNRPN\PJOOMNLKMGEDLHD`ERDRE?RBZ?X?T?<;<=:98^;``>>>?>@XAB^A8ADjEDJHGDEFLHMKI`KJNP`KJGHHIK`PM^NKQN^PNKLVIGJJPQJHVGHDH\CRD?NC`@BCP?;P==T=T>\JTJX\VLZ^VR\VfVRVFfXLTbXRX^XRhXbXP\LPN\PDfRXVR`\HRNVVbZX\VdXXJ^TVP^L`VP8\FRPVLZX\TRX\^PNbndfhd^ZX`b`\`Rj`TffVZ`ZffXZhVf\``VhN`ZXXHXdJP^bZ\X^8RPPb\NhNZX^T`XVdhTNZPR\NZ`Z\ZVVTTfdlTPZV^bVZ^T`ZXdRfTVbdV\fbZ\VXX\\l\NXVZVRVXVdbJRbV^\nXP\ZRRR\JT^V\dLPVX f  l ^ V ` P L T \ L X X`ZXXXNV^RT^NZ^"!b "#T#L#j#L(T('N)+N*+++-.D,Z1/R0Z11Z40R23131N4355V7^8T8b@\?:9<<:V?BBBTCDFbIIXIXJdIZLbKVPIKHNjKM^PSPRQRVJTTVRQ\SNTPQNMMMbTOL^QHNQJPNTHIFXDGECC\BC@bHCH^HPGVGXHHNLhJLLdJNNLXJ^KPOZOdTZQ^VXVXUV\X]R\`_eaRgjaXbcRePfcchZdc\`bechdJ`_`da^P[\XYXbSPdQMVMMKJFIXKHLJNOSLNNPPQUXZL\__`^^_Z]`^H`[T_\]lc`aJcRf`ge^cb`acd\V`ZT@W^RM^SKJVG`HVGZIXE`KJNNZOKO\MOO\RTTTX^TYTVWWVYT[\\ZZV]`[_aL`hcdffa`bH_d]\_WRX[^RVPPPQXOMNPTPRdWZXZ[Z\aRbfdecefd\jl\higXfDefba[b\VYYVXXfWYUWVVVVLZW\\TTQPR\QMN\QdMPQTTPXSXWWRTTWVSYZUUVRRWPX[YLZ\ZaZX^]^aa\ZZX`[W[XVTZY\VZbWUTQQPPPVOROQhS\STSYUSTWURUZWTSPWXWDUbTRVS^TRRNVPPRMPMOMXNQRPNMQLOLNPOQMfPOPP`QPUUTRVRLQNM\JKTILPH\FDPDA`C@BZBbGXFDFDLGGRJfJINGGPGRHICPEEBBREbBB^AZ@>b@EV@@=BBX@\AADDFFIHKdLMVNSQZRRTSTROdQMIIIEJDXCA`BT?Z=?>AB?X@R?\@@L@^@@BfAFG^IPKPL^LXKLKKVKOTPOdMKLNKdKHIRIDGHLHDCFFDEPCB@^BBTBA@ZFFGFGLHKJFL\J^KKbPPSPPTfTSS^QVJTV[TTYXTVNQVQZOMNMN^LDI\JVJHHLDHBVHA\AT?XBlA=AZA>V?Z?\CBRDDFDFGGPH^JTJLRLXKHMVPTOOSTQTR\RSPR\TJRPOJXINHNFNHCZENCbAZCF@C>=;=P=V;:\:`9;8J<^>;=8;^9V;?Z>=H@=R@Z?D^HGFJEZGPHFLKLILLXLKJfMHJLZL\KJOMNOOXNNKRH\JFLRILFbJ`EPGLC`AXCP@?@^@@Z@=V?P.+Z++('&&P&%R)&$#V$d%""" !PFZ^V`Xt\RPbTXNZd`XV Z X ^ b R d P TV ^Z`NT\TJLPPVhV`^TXP\XdTFZH\j^RdV\DlXNPh\`R`^`^XRRV^`ZVRZdLRJ^^RZjPXbXZVXXd^VV`\bVh\\\\ZVVn\HbT`dVdZXR^jTXJdfZ^ZRhXRXj^X\\\VZRX^f\VTPRfT`^h\ZZDRPXZPbPd\XLXT\Z^TX<Vj\LT`bdRdTfJXX^nL^jhTfP\\HX^dZdXTf\N\`F^f^XPLfhRbZPRbVXdf`ZDVLXJTVFPJ^fFHZXTF^VFP`TZ`XT\NbRRJXX\VRRVXVPVPZZVd`NjD`NLXP`H`fX^LXT`VNXPTRR^Z`NV\PZVXTFHZXXVP\PbV\`FXRH\XR^`LZV X \ \ B L b V b H ^ dRPPRR\\RTfTXLR Z $X&X#L&%&(P(B**H,,L)Z-1/L0/P21\2L2Z1P1T33b2D4232\677R9;:R;R;l9:>:Z:f9:^:^ABCDNDZHJGZKKNVIRM^KKMdMKZLNTRbQSjPQUTVTbRRTL\SOUNS\MNV\P`OQLMLXINZJ\GLFEJFCNCBCB@DGE`HEKNIVNXJL\LFIKKM\MPTPSV\U]Z`N_^`c^PaJeNf`gbbghhgVd`]`dNdFcLd`bcfP[ZWUTXTZTTPLNTP\MOMPNNHbNVMPN^QO`QQQlSV^\XZZb^Ja]T\T\]N[\_TcZaTcXbeTe^hcf_Ved`_YYJWRMNTMTJHbMZJhKJINLXOTLZPXMTLMPZORURTR]U[YH^YXXXYRYP[ZP\V_X]^bVbbcdj``_ZcZZ[XVNWR`RZQUhNPNZT`RXV[TX^[]\cF^ae`ba`fhhJk`bTeXgNcdbd_gV[RX]WWSUWJTTUVURY`YWbVTPZTVSP^OORPMTP^SQRPTTVSVVSYLWLWXVUH\B[VZ^_Z^Z^__X_^]D_j_ZV\WYUdUXTVUVWYTSV\OQPOZQQ^S[LRXUQUXUNVTPYbXJY^[UWXSXV\RZT`TZNPN^NN8OOMXQOPPZMQN\QXQVN\QOOVOPZQNQTRRR`XVTJTOZPM^JGEZHFNEEXB`ALAX>b?B?BC\EZE^DJDZFFJF^HTFVGRDZEDCRDTDPEDX@P??==>\BXABDCPAjDBPBFFZI\KTLMNTPLORPQLTSRNMTQIZHZJLDXEAAAT>\?=d?R?Z=A>?RAA\ACZCN>?ZBAB^DRETI^JHL`JRMJTNKPJdLJJKK`NNKTLKJGFDEPG`FTDFHZE^BLEbA@A=BCCGVEPFFKRMXJIJRLTLLKZNM\PBPNRSZRUXSSRZVZZWUWVP\PLMVLPNRPPLKIEAFfDXCBRA\D?@?\ACLA?XBDEAFPDB\CEGKJ`KTG\KPHITJTNRMVNVQP^PQTRXRSQPVN\QKKFFLDZFBVDELALB?=\>Ad=>^>H>Z;J<;;:;:`@T>d9F;V:Z<?Z>@PBV@TCBRCVFXEFfDEIGTJTIIIJML\JJJdOTLfIG\KJKOKPRZNNdJJHFEEXJZENGADBPCCXAAA;;R<:6d7:6^9Z884Z62L4340Z300N1H042\412P2V252T32^6h4J54P5`855Z36T578Z6565N5f766Z7^7L6V78544P5H;d78^65:V7^87Z9X9^;8:8d9<8^79X;9H8Z6\:6Z514f5L30X1^///T,X+,,(H+*'Z(f(`%&Z'%$$&#L$`"X"VTJbRRNVFTPfP^T^T V ^ \ ` ^L \H N VXNTJTXVTbdXVPRNHVRPT`TPfH>^TP^TVJNTPTdVZXZ^NZVXd^V\bZT\Rb^XZh^RZXZdZZVR^^NX^\fTVj\J^`^RZZVZHZ^R`RT^R`b^N^HTNbP^XXZVZ\V`h`b\RbN\\VVZf\Zb^dRRfR\P\bLbRZ^ThXXXNJPRRVJb`NbHZPVd2^VXhbdP^^\dVd^\hd@VbTf`ZZfXXdbfTRdhdFdbdVP`V\f\Pj\ZX\PfNTdZ`PRjLVT`TTZLfPV``TVZZdVfLX^jV\\TZ^N\VjXXP\PVPDV\\ZbRXhXXPTPXjXXT\ZXXPhR\JVNb\\\JZbV^V^`fdTb^X\TZRXZN\XPVZVV ^  ^ ` ^ P Z N TN bfRFVVbJV`P`\Z@XN:b T#f"T$\$P%$d(`(')(**T,Z-/-.N210L1d4N12Z4P435258X66V9:`==:\;;T?<:d:9XB`B@dCXFFGMLKdNJ`KOLbOOTMJMQQRQZMRbOQWZTXOVMRPQNQPONLDP^SPQPXPNNVOZPJdIVEG`ILFK\GXB\CCEVJJEHFRIIPKIL\KIOHIJTJJKJRNNTXVFTWYVW\\BbJ\`ge_Ragea\fdPdeXifZcZdZcTgZgcPclbX^`\ZXYJVWSRZPM^MJH\JIfQN\K^OVRRRMHO`TZRbUNVRYR[X\Z^D\^a]Xc]eTaa`g^fddecXeaePd`]V[VXVYXVRHNMILLVNFQG`J\KPLMdL`OMM\QPLQQZTYVT[XYNYY^]V`\W`Y[]\\T[``eTg`diF`dfa\c_`^P\TTYUXQQOO^PBLKQORTVUfZR\Z`[P`Z]X^Vb`JahVfibhlhdecbcb_^X_V[ZTYUXY\ZTVWTSVWYWPXRUPXQdPLVL`QLNLT^PQPUHQXTUSR\UWLVXWTWHWYY[_`\bPa_^]TZV@[YNWYLUVVZZXWV\ZY\YPURTT^SQRTTSPUbVZRSSbVZTVYSUUU[VVVbVSRSJSVOPPNORROOMRONO\PXMBQVOLNNbNNTN`RMRVTVTbP2UNSVPTXSRVRRMNIGIZEHCCTEX@N@V=P@`@AXCZCPD^CBC\FGEVFFbFB`B\BXF?=@NAXARB?L@VAPC=@TEC@\DRDCLGFTHHXLVLLOXO\RRhSTLUZPOQ^MFKfGHXCC@^=>R;>=RR=;>^>TB@`@^BfBHFVJHIXIGbIGLRLK^OLOMFTbQ\S`WZTPTSXVXZYTV\VLU`OKfL^PLNLJOMVJ\DbBNAR@@\ABbCDCXBARCA@AAC@VENA@FRIDIHVJKLNKTJMVMVNPQKfTROSOTP^RTTXROMZJRIZIVD\FjBTCVDEBP@?T>>=;J==b;9Z8f;^>h<879;==b?^?P>V@?J@X@AVE^HEEJETCDRFHIKIIINLML^NKZH`JJbLVQLMOM`PKKXIFPIVJIZJERGVCDDPFAAFC@A\?N=;:R:6577T8N99Z9J5b53Z64P2102\0b1113V1T3113`3V51243`55Z354\6V4d44R7P7`86\6J5H74d5V64T45Z6V79J5b76H6;9\;679X7:8N9998;D;9Z;=R;R:76P5\7N4V31411-`-R0Z./,0J,)+()d(b(Z%Z)%`'^%j%R&R##T T TV TXNdBbVXRNhNXRZVD\T^^ R T \ ^ \ X Z LN \ N ^ ^\Zh^VXFbj`XdLTTTXRRXPHXXNR`fVjZ`\JX`ZNJX^XTb`h\TbZX`TdbJ\VNP`ZTbVZVVV\JbTZHXZZdTXVbTJTRX^RfdZ`ZjX`^Tb^^NX\\``RVXT`NRbZHf\ZLb\VPPdX\RRXV`N\\TPbTfFX\VNXR\6TZTTZbJ^`Z\PJV\Vbbjb^VbRd^XVXVfPXT\dDXblT^TVT^bVNXhVTTdR\X^`\bVV\RV^^XV`PP\`TZbXdbbN^TLZNVTPXXL^T\JVbLLXdZP`^dX`TP^NXVTV^HP^PV`VTbRVXBdVTJZVVZPLPZRZVNX`FX\ZRXRVL^Xb\`\ZTZNT`V\`RbV^T T V Z P d X T R L PT`d`VTPV`RTF<b\L`Z ` b!$'N$&&'L*R)&\),Z*`*+.P2.0V2J5Z0Z01/\610T5d7T53b75^;68L8l3b531P5222325^4d3R1125N3N62X3b3Z2R4T78545Z6Z5;P:T7X:9T8V:^;;ZF?^BT???^?=P@XC?CBAPARFXEbEFFGZKVMLOMJRRSORJPbQJOPNKZHHFRB\CZ@>>V?\;L=>B?Z<>@`@^?Z@TBTCARA`ETB\FREGFTHPIINMJKO\LNHJKPLNMNKJJERGEC`EDPGHEGGREDHFZC>Z?B?bBDBEJXHGIGLRGZMLITJ^LNONXTNUOWQXTUXUWXYYRSbSSNXLTN^OO`KFKH\GCVEB^@=@AB@CDAB^DADZ@p@BVACDPEHJEHbGHKLJ^IRKRJTLOTLXRNOLRP`RRPNRQSHONPKL\GGNGGBPEFAfALR>;Z@>;Z;;N:<`:X;;=>N?ZB>><\?\BNCBLDDTE\ENF^FF\JJKLHZI@HIJJMPLPJKLTMTKZKNRNTR@PLRJTKI`E\HHJJFbEDDbFENDC>DAV?X@`=>::995D6X<<:6P6L4433Z2^6101511b3Z1\3236P1X33N1N24F366R536`7^6R445\6^443453R345V6Z4P35T44556677Z8`8N88R7R88877V<7798;R;:N:8\84H323Z3<4j30/0Z00.+,R+d*))b'X)H%%H)d&V%%r$#l%\!RVHXNZ\Vn@VZJRZTTBp`T`RXdH\ R X ` ^ L X ` V L \ P b T\ZHb^LXLdTFZ\dVVVhXXTTZTRZZVTXXP\VPLdb`^`ZX`VRTVh`^^VTLZ^hT`d^D\RNbLJRfNHV`^XbNXX\VRjP`TjXZNZbdXN^^LT^ZT\T\\VZXdP\XTRRVhXfRZ^fVL^PXV^`^dXNLXZXZHVV`X\bRb`^TTNT^NR^fH\Rd\XbXZbh\f\L\ZRjZbh^\Tfdhb\d^^^d\lb`NlbdZPhfXbR\^`bdL^XZ`ZP\^XlFXd\VRd^\VX\JPZ^dRbZJNXX\NV`XTd\ZXhTd^Z\^b^TXXJ^\N^HXX`bVRXbTZNTT^PVP\TTVP^Vf\XTR\N\TXPRV\VXFTdPbXR T ^ L Z Z b Z P X ^ T^ XTPdFP^hPhHP\ZTTRZLZNZ$X!!T"#$\$#\(''(*P*)+V,.//2/\222P1`3`2h2\53R4Z6V7X6`697\;<:P=:>X;T\>CCEHHDIKRLNLJTNZPPOM\OZOPMOOURdVSQSUTXQPTPPHPLQRNMQPOjQ>PMVPRL^LRNRMSTMXKGHDjFB@N@BZHNIZIKbJHPHGNJKVMVKJMMVNNNZNNPZSXXXX^V\aLa_Nc\e`bRhPddbLcd`bdfeccXdaFabFcXga\]Z[VTY^TZRXMMPTLLPRKNO`OMRQdRTRXRRXUV`W^YNV[Z[]\b\_F`ccVa_\_XbaTebehVecfe`^Za\]P\]RVRXQfPRMO^P\NTJTH\JKZKLIPQNQ\VTNTU^Y\fWWhWZJZW`ZV^X^`PYVY\\b`b^R_TebaVdbd__YVUVdPSNTPONNLTLOPMWPBTTLX]WZ_R]^Rc"`X_cfceke`geeb]Ra__T\VZW]ZXVXZb[WTYDXhXTXVHVTRdUVO\QLLQ^OLOfPTQPSVTXWPTTXYVU8RlWVY\ZbYD^R^\aXX\VX^WYSdTXUShSNTTVRXUbVRVLUZ[XZXV^SUFYX`WWRWVUXWW[TYhXWXZXRZ[PXUZQMTPfMTM^QLKNPTMMKJMVJJLL\P`NO`PVPROTQXPTXQXSLRXRTSPNOLGLETFVCCBA@@@TAVDRBXCCVGDTFTDREFEEREVEDChCRA`?@>TA@=?P@P@P?Z@`BRCFNCFLEGF^HbHdOPOLZRSQZVTQVUVR`QO`KLMHKhENGAR?`?>?>@A?@?>=>P@VDCBVC^EHBGDFTFbGDHIKLNK`JJPKZLMLPVKTPKVKXKFPGHTCFNDHZECHNEEVHbCC?D@VAEFFG\KJZJGHHGGJ^KRNPOPfQQDPSDTlX^UZTXVTVY[UUVURNOVN^NHQNRROGDCFbBTC>AVA^AB@?V??RANABL@@FBABRGVDLHCXGHHJMXJJKRNLNNUPVUP`SVQPTPQVNQTLXJHFJIZIPE`AVEXH\CC>`=PBd@\=<>P>T>AFCEDFEGCGHJKJJLKGNJK^MZJJHOTOPLLRPKXIXLdGNLDJGXK\FE^EDZEDGBd@P@:JB:F:f66455H5H98N65R57`5N44P5122N3b4002N3^042@6H74V81^65436T426j46H76J8R96V56\88X8V769H<8Z9R>=AB^AAVDhFHEXHLIRJHNNVNRS^QFOHMXNPRSHRJU`VSPPSU^TSPURPRRVRNMbLRSP^PQPVNM\LPOVJRNJINGGEF\BBbBbCZF\FHRL`IXIHHK^JVMXJMNKMNTO\TOVTPWWH]Z_[B^Va^fdNecTfXfLgfTdPbdNafPdgfga`cad`^L^Z]d\WXdVRWSSLOQXNM\JMJPPNMODORVRRVWUVTUXRXXN\\aNb\aVa`a_^]bacefe\ffcVd^Z_`]Y^Y^TRQVKL^KLORKIXIHKKJZONZQVTRZXdVVVVURVULWXP^X[L^V[]\Zd\VWXZXbRc^]_beZ^La`Z^^P`VXSP\RTP^UJLLJKSPTTTTRZXZ`\Z_Jb_`dgfDjTecfbdbbb\N]`]f\V]VTYXYSX^ZPXbWRYWYJTUQVQ\QNTMJVQPROMRPPQ`QVTSPUTUUXUPVZJXTXXWWYXWYYVU^SSSLVShU^UUT[YNXWD\]XZZ]TXLXUWYYXRXN[^\\dYXZBZ\LXN[WUSRROTNZLHIXMKNTPO\LXJGNMLLNTNPLHPMOOPRXPQXPZPRQObQNPLIFXEVAAA?A@PC`EBVFBVFFEEFTFEHC`GDC\F`BHCJ@X>\@Z?H>RA`BBV?H?VBABVDPD^FdEHEKLPILVNQROPSQRdQPOPRMOPNJIDGDA@V@V?==X?@bAC??BC?A\FTGXFELEVHXKTHIRIPHJVFJJMI\ONJbLXJMZM\Q`LMTIPMdEHEEHE`GZCCVD^GFNAACRBATA@DTFB^FFGZHXJZHGVJRFVIPK\KOS`S`OSZRURUVRUVZ\WVVVZQRR^PSTTLMMOMIGFCHCVBVAB@E@TC=?@RB@\?C`BR@ARCGHbGFXGLJRKZKZL\N\OTNKQTRMTOVSNBQXP\TT^ONMPLZKHHGDHVFLGXB?CP<>>T==>\=T>^\=R?=XDfBNCZDXHCXEJGFHJFRFPJIZI^LKRKJ^LXO^I\LTPhMNPVMTJH\IRFEZIFFIETCFHPGAAEDT??=Z>T=9X879H;48L9H6442T4R4V22X/1321T201\/50P21N2435`3T4P3T63Z43T544^5\4Z43X556\5\3f323144H57d5L8N96R6b:Z9T7`:7V9R7`67Z9:R889:T8X:R8`:Z::6R42X433^20\1`0Z0j//.T+T-V+P)V,)**'N)&R&'$^$$T" "f\ `\T\^dR\R\d`Z\ZT h L Z Z X  T ^ \P X^^LdVVXZ\L\\`B`bbf^PLbPP`VX\bRbTJXhhXZZfV\VPVZ\Nd^fPZDPTdd^ZZlPf`VThL^`XRJbX\@HNb\J^jRZVNX^`\ZT^ZTX`^XNVP\lRPP`@XP^bbX`ZRXNRNXZhbP^\VfjXTR\PdNXR``T^R\T`\T`VfZXZJRZNbVXHfhN`VdV`bX`\d`X\j\XZ^fbTVZ\TlRf^^fhT`VTX^dX^XNV\RdXHXRVJPN\ZbbZ^`Nt\XN\\JV^NnV`PXTZXR^^dJXJRfb`\NlVXVZRT\^VZbZNPRZdR^^^bXFbVPXZX^H\TLVZ^jRTV V V T P P \   TPZ TTLd^bNRTXPh\\DND`RJP!X ! $R!%%&\'('L'N)\*`*+V0+./R-.1P0L223P2X3`835\54\89R89;J=V:<\::\8^975N4V53`45X5X67R5\6\4V674T5X3d4V3T2X5X2P35P3V41N24D56^4R712d2Z3F3T3V6R2j1B23335:f96X6X69R;b<8b8:=;;^>^ARGDTDDVFVHJLMMXSNNJ\OZNRST\PhPTPQVX^S^UTSZTWVFVTSQOQROMIMJJNKNMNRL^PN^OK^J\FE^HPFPIEAG\DTITGXJI\FXLKDHKIJVJLZLZLbLPM`TVYYY\]T]`cjffXeRicfcVbTbc_bdTeN^Zb^```_^aNcl__r_[V^YVXUUQTPNRMJ\LOLO^NQONUTVTV\[UVL]b\V]PcXcaRdX^N`\]^b_L_^X`\ab`cifc\d^a`Z^^YTS^T^NVJdKMdIHIRKXNL^MdPMbPQSU`XTUWUX[ZLYf\V[\b^^[ZRYR]^c`^Pbdb_Xd`\\Zn]\YV`UTPQPTPLNMJLKXM\LPSPV\W\]Y__aVbTgNb^eh\dJecVe``dc\d^_^T\J^]bY[V^VT^UXUVdUQVUWPUURS^NTNNLNOLRPOOTXRJPnS\QS`RVUSQSRTRVWWVXZWVdUTTVRQ^XPSRZRLTSVXXYZTYX]lZZ`X\VYVXW]\[V[P\LZ^Z]_Z\ZUPVZ^XQRUPRHQLJVIIH\JII^JJfHGNI^NNJFN`NTLVMMM\OTOhOLOQRN\PKI\HNFE`C@L@\DBTCDZECFfDTEDGE`GFDDCEEBRCVC@@^@>XP;T9=>>X>@f?RBV@\BVD\EPD^CDGZHZIPJJ\J^MHNIVGIPMNVKfLLjOVLPMJJGZFHGEDDFbERFDPCBFLB\EBP<>=Z@=:T9V8Z:V:873784P44N3/R5H2d0>4X216F4T00/Z1T21b2V13J46b6T3d6B3^7V5j3L5326L85f85T4\7\430T4334\13T45P56878\96R9F;V;`8:T67X97d9T989:8978^476T4^551401/,H1,..,\*b,d*(P(h%*d'T&%$#^$L"\!^!\!ZTL`bXRlbZbX\dVZPV@`NbR V V X X  T ` PZ LR\N\V\X^VV\LZ`PPbdTVP>^R``NRRbhV^NXfbLP\lV`X^\lfPRJ^PJ^L\LVX\>fb^dX^ZLZZR@Lb\hXbL\PTdP\LTb`T^RZPd`^XZ`DXV\^VbX\RVb`XRT^hFVTX^^XHXbPZT^PVPP^LNV``P\`^XTVNTPhFV\^BZT\^dXTfdjp^jVbhb^TV`ZfbHdVRRjPZ^ThXd^LZb^ZPR\PRTJJf`\\PZPd^fdTd`hfVTVb^VR^dXTXN`^X\bbVV\R`R`^ZJZdfd\X\^XN\\V`XTRXZTZ^T^ZV\XR`^`LV`V\T>F\NVLbPRbln^L<XJl`N\DPTP^NL ` ^ T J X ` ` R R V \ R l VP`TLTbdRVNRVTZh#X!"X"%^%&''V*X((H)X+X+0X-.X..F02Z31R6N3d2^1X42565N:57:7:V?>AAVET@EGHRLON`KN\OQNO\O\TQXPJQhRFUZSVRRZXUVSRPPRZSP^OXMOdO^MVJJKLNNMJJNMVNPLDKVFEDbEEFXC^DFIH`JHEGMF\OHK^KZJMP^QTSPJRHSPWLZ[D\YZ`T`\ffRfXa^jNcNjdfTdXcHbVcZebcc\aRb_Z_^Va`\YZWUT`VPPLNQTL`JLKMHLVMbOS\PHVX\XNTUTWPUP]`^J\RbbbNfF_\cN^_]cP_Z``cbhbb\eeT]c`[^YXTTVURLIZIOXLXJIVILPLNZOKQQSZRRJSVVZVXYY]VXWPW[\bf[DZWXdN\J]R_T`Rd^`L^J``dXZ^bbR\X[NVUXQVNTNLJRTJ^N\KLRObRRTZ[XVX\[[P]VaTdbXciPgJi^ee^cHfa`Tba^[\WXTVVZVVYHUTTTTUVWTSbUW\TTWNLSRQRPVNOLTOOdKSOLTdNRRSQUOQTSQPWR\ZNTHUNWSBURUP?VBX?@T@VATCA\CRE\CHEGRHXKKRLQdPRLNTTROZP>NTPTLMH\FVEBXA?N?`BACB@B`B@FA\DFXBVDXCGNHFIJZM\JFHGH^INLTONdONLQLN\OPKTRNOL\G^JXE\EEBB\HETCVC^CBPBCVCDCDAPBEJDFEGGJFNHLIJNP\OVSRUNPURUXRbWXZZXTXZTTQZOXQNdMVRNDLTJ\HEFDDDVDfCCDA@>A\?ZCXB@DC`D`CB\FVH^IXGF\GJMQMXMMPPOOPSP\L`OQ\T\QLS^OZLL\HHZFJJH\HXGVDB>=T>>?=N;P=Z;V<=\?LA?@L@T@DDCVCC^DHHRIJHK\JPNbNXOZL@KZM^LZKONXPZMNO`JI`HG\GPKNGKFGXEPFCbHBBAL@f>D;PB;T=:<7X9:73Z44343V1^33N10N1^30/J0J1/b1\4h4X2Z00X142434R64L36N66323R5\66d532N6V4j5L34`33d3^5Z585567d7N87V7R7`984L9\999V7<99Z9775j6@43534h1./0P/0--,X*d+*P--Z+T)`(*'R&%T$\"R!!T"\"P ` PXTb^Z`VRV\R^\P \ ` Z Z ` P V Z R ` Lb PdZ^dXBPRfNd^HLV^TLVVPRTVV^^\XXX`PVLbZPT`XZfjVP`VZV\bZbJZ^^RVJ^RZZZVVNTZTV`TZJ`^ZXdN^VbjZXZdJhZJXPbZRRL^VbZRRPTXZJZ`VbD`V\R\P^DbPXVbVPZTZZLZRRX\`TPhX\`NbN^HN\\R\NZNTLBbF\H\B\\`TXJTV^XJR`Zd^j^LdTTTTjf^X\L\`VZL^fZTNV`VL`T^bT^h^`NjX`^`HP\V\NlJjT`Zd\XVbNfL^VXHV^ZX^`R^LbXRXVZT^XPbJN\\PV\^TH`^bVV\^f@NdR`\^bdbRPRZJNRf```ZTLPX^TRTLZJRZfZNHRNb\X Z \ f \ T f T R Z ^FP >`V```ZPR\\LbT\TZPZ!L!^"#R$X$Z(%)*)'('\*-T-X...X//11`1X4R3Z42V65Z8\68956D:d::\<=V?Z>J;;::=:7752452D5d4J5d4X6N57T786`4V7<70d2R4\3X2Z3R40^44N5`5V6\3T4j54P4`42V6313^44T4P4`56::Z:7^;V7V9R89V;;b<=<\?TA<:^A=\@@AXBXAhC`?@XBVGLF^GGKKPRUZSJTbRRbQLP\MNXOLJHGXFNCA?XDPBD`DAR@CTERAhENCBFFEFPGIdJ\LPM2KbKJ^LJVIJ^LfNOOPQMLXOZIXKKVHIDGGGEFDRB\B\BBDXCDCDZFPCDNCVD\FHFCbGXF\FG^NNMXPLbQQZWRPS[TVh\[\Z\WW\VJQXSPTRXO^PHMJKHZFXDXDGJFBGTAC@A?A=CACCRBBCdBND^IEPHXHPGK\MLKLQJR\MQ\QQLHURPQUNXRVPQOLJKKHGPCFNB@C>@\?d?@`=>>;^<;T;;?ZAJ@AREAGBEXAFDDRGHLJKIdJMVLXOJJTLJKJL\MLOZLJIG`HJXGXJPGDCDDDTCPB?EhCR@>^?>Z=n;^757\9X68^5T562Z8343N12.\1L11V2240/b0/b33/5R4Z6Z43X5L4Z3T3D3^4F3V65X3N6f6682X3X614^4R66f3T5J3X8P55P3797P6864X96`6L9B8R;78X=`;R87h6L67T37J644T41^/0F0\1L/0N.b.R,d+,+R-`((j)T*^(%X%^$`&#V!  XVN^\VHdDLNTRfZdRn ^\ \ \ J \ N bZ`ZN JVbVXP\`FdRlNXbZhPTNTbX^^VbRVl\X^\JVfXZVPT`j`Vh`^Rj`Z`T^\dT`ZbVRZ`\TLZXd`VT\^^Pb`VN`RRRX\VdZ`VV^VTR^\ZbbTVVbNhl\Z`fNVd^Rb\Vf`^\^b`ZXXXhj\XZV\VXbbVbTX^TjPJV`F^NJVj`fThTVX`XTH`ZPbt\Z^^^j`fX\ZX^RJXVbfRXf`Vlb\ZXXZ\j\bL`Tdd^fTXVHZTXVR\b\l\f\RVZ^^N\fbRfRNXR`V\RZR\RZ^VR<TJhXbP\LLXD\`X^RTJZX\rdL\hZbR\PPVdHVRH^\^Vb`fVJLNXX\NZ\RfZ`RZbD\LdTZFV L ` X N d h T b R `NNTZP\NNTZfX`Xh ZZ! R%#"H#$R)X&N&R'))\+,.,\0P110^/0X12R3^53P25X4P777b7@7\88N>9\>R;f?<>>ACPCVDBDE\MKNPJVOPJjL`NN\PPHTSPSXTPVDXUbS^TQ`TRUOOLKOMNMKJINONTM\QRMJHIHRKVJIGPGXFDGHILXHHPLZKIMPLMTPVLRONPFRQRRTN\Y]ZX_^_baFcTi\efacTabNjhbaeccVaNc_d^^fXbX`T`\`aH]R[L[ULWSPN\UDNMLFGKTJHNLLVQR`WtTLVRWVZX^[dZX]\_[Y^f`<\c[Ta\d^beeTcdhVh^ec``V`[]LYWXXSSNJJQI`IGM^MN\LNNPNXMNQZSRTVV`XWTWPXUL[ZaXZX[V\Y[\^Xa\Jcb\cFdXbNe`N]]\^]\jXSZPXPMRKKOPN\OPNORPWJRQ`TVTXZYZ[J_Y^aaPcTgbegeHdaVa^T^[`ZWJTXYXYXTLWWSUSTUPXUTS^SZSXRROPXVXQVRVSQXNPMNVSQOPMPVPNXOPNOQRSZPTSPVfUTDVPPRZRRO`RSPSSWXXb^VZZ[X^]B^`]\_P][YTZ\P[R_b[\^]^[YYPWUJRTSXQXQRNPJXHNKRJG`MZJVJ\KNLKMLNLMNMZNH\JTJJhHRJFXFGEFTH\FJFXKITGPERDBBDGPGDDZFGRGFGH\EXDDACBDJBZ@X>RA`@NB==<<<==T?T?b?=A^ABZBREfEGKRJLROVVUPXRQNZNM\LRJL\FDfCEJCBATHBfBVCVBGNFBdE^CDFGEJPGONLdKJJMbHFJTKK^KPHQbQOZRNNTOMNGPK`JGEH`GTFEFNDNC`DPCPCAXF`BVGXDVELFTGZFD^HJEBDEVHH`I^HJLJK`LO^PTPTU\SVVVFZXNZZZVUTSUVVNXQQjLNH^JXHFGTDEbEEKDAAAVBH@?AAAXDbEFXFTDTDJDE^GHJJLLJKNM^NVPFTPPONRSbOTURQORPJJjJGCDDXFZB=T??R?ZCF>^A?H?P;?X;R=T=b@\>>b?=ABNBhCNBE^DGH\GHLJXIbLJLJdPfLFLKLNRRVNNMVOPPNNKhLIHZJ\JZKHFEDZHDZF?@^?A@<<>^>?Z8V:7L;Z54L5`64X43X52`3T/.X//T.Z0P221/0R2X213Z5R2R3V5Z4T5`334P454243T4H34T7X54X3R63^3P3R3V33H3Z6N7b76T5V65^87P74f7P8h7N5:\987V8P8P:662^54P5T65T2D4h1`32Z0T1//\/X0b+*X+T*Z,L,N(\((T)\'&N$$#"P"!Z! ` N!^XXfN\FXJRP^PZ\F\V f` R \ L X R X L V b`XZTTPNRbLTNXDXHZRPHTJ`N`VZXT\VNVdZfNdVT\XVTPRfLTVXTXV\`j`BZRh\\T`P`\hV^hJZPX\hN^RZXVZV`RRTT\RNd\DfPH\Zb^T`nH^RTV^X`P^TZR^Xd^ZRVV`Z^TbRTZ\ZjXhbZLVbPRPVH\V\TV<`^RRZXHPZ6TPDjZhPZbdVfbldX^^^VfZdXZbfT^ff\ZfTdPbfZbVV`\P\TRR^bX\NR^\Nh`X^JTZZ^N\bRXVPXRXZXPRbXRH^XZ\`PV^R^R^P\`X`TXdVP\^NN`^bF`LbX^d\hXLbR\`TTXbP`^p^XbJ^JPVLjZJ HT Z ` P f Z \ ^ ^ Z T^XZ b^X TRVXVX^PZ``LV^H\ ` \$#N!#\&`$T&&P*(J(,X*\,\-/-/X1032L2V6V5X385Z5X8P6R967\879V;b;V:N:<=<>Z:@<7^:6^9V5\73\953T5L625346^5P5V4843025443b378N4`555b7752R7V7Z56\636R8J4X35Z6R8:\:V;V9H9;<@;;V:T:=L@?b@BZ@NBVEdFIHHPITGZJZIbKIVKL^LQORPSVSZW\TjSBPZTTLRQPO`RQHKZLKFK`OVGKRNK\T`LJpKOJJDJdHFZHDTHE^EIVIJIIKJXJKPKXNPLPOhNOROQQPRVWRWX`F^`b\@bd`PfeaRcbZbhdVbdc`Ta_Laf\^FaZbHc`_]_\N\bYWTU`PVPDRQbLLJJKMbPPbQVTNTTUPVWV\Z[PXb\XZV[Z`^L\aL[_\J_VdZeTdi^gLgdfe`^R`\X^[PXSYUXP`MLOKMRKZNPPOUVTTRN^PSWUXWT[\ZZLY\Y[XXV]Y`[NZ^^V_\\a`V`XdJjeJb_Te\[d[XVYNUSPVNRNMMVPQXSVPXRRR\U`XSXUTW[N[\b^\b`bgXbfd^fbcVeZ`HaR_Z\ZWHUZVTULTVU\UXRTXYYdXSbVTTNLU\P\SQHTPRXSSQObQRNNSP^PQROKMHNPOXNPUJO^TTVOVP\SJSNPQLSDQ`UPSTWZR[[^J^[^_[Ya[_ZZX\]X]R``[]VVTZ`UULTRUPMTMJKVKRKH^LXKbMJNOLLONQQM>OML\JHFFDDHVGEZDZFPFElGHIXETH`E\CD^FFFHFZGXJ\HEZFNGFDTB`CBA\?@>T@L?d?V>=V=R<>`?VAA@EPDVFPCGLEFTFVIXJNLINJK\IMJKLPODQPRPONRKXJIVG\IGREGTHFGHFJIE\DPDETCCDbFZCRDI^IZEHCDDLFZEVGGERK\LILXKNMNdTR\YSWTVXVZRY`[PZTXWR`W^QNMMMJHbFFF\EEdFDJDERB@hCXBA@RBECPEETETDEHE^EPIVHNI\KIFLXL^KXNPOVQPZSOJPdPQXWRTRZURZOQZLLXKFFEZDhETC@ADC?X=d=@@=<>d;==@X=Z:R>?T==Z?T=N=>PA\BAVDETIJD`FdIHHfIGLLHRJLJZMDMMPN`OdNbNKMTM\RZONXPLLJNLHLJVHfGEDVDBEC^Eb>J?PA@Z@T@X>:J@;98X87774Z623^3T421b2/2V10Z03Z0V2/2f53`0H43615\4\7b414h333H74:R4Z3R8Z5d534h4323N1X33Z5527564\56P7`97T6Z;P967P8Z9:L7Z8:653Z3643L2301Z//.-/T0-J.+V-P+T,j,+P*)f('&&%$^%T&X#H"j" \!\^ VVVhX^RRZVTV^RZHN`^T N d ` b \ V X \ ^d Z ^ZR^FZV\^n\Z\jVRZ\J``^ZPZd^\JRZh\TZ\X\Z`Rfh\^`^`\hR^dXVLXR^bXR\\^h\T`\X\^`dNj\V\R`^LhV^TXT\VjHZ``H^ZbPRfZbT^^XX\VPTfPVf\`HZhVhXP^XT\TT`NLVVfn\\bZbLPVV`^XNPPTbRdZZfZNRP`R^XRP:LV`hb^dhV\^\V\rZd^\Z`dZBVVVZJ^PT^\T`^dTTT^X`XZT``\TLZTV\RbTDRDT\PVFLT`fTZLHXZXJXHPPTLHLRZV>Z`ZR\PXNXT`RZbZ`NRJZTTRJb`RjbHZJTNPTPLZ^NRV`TPZRP`VP`PN`^XZ\ThPdXVRXNPPb Z T P T T Z R ^ J RPJRXNBVZJPNPD\N!"` \#!P#"`%>)^&P')T&'P+++-,0200P2b0J0L32P5R645`568R8\588V99:9P:\=N@9<>V?VBBH`EXCHLHIJKPG^G^K\LONMMOOLPQRXRTZT\VR`PPRJR\SHK\LLKXJ`PPL`MONTLHNHKPNVHXLRKIGHGPGNHRGKFFHGIZK^MVIFIJVO`LTPVPVPMTPOQUZWRWN[Y^\JZ\[baNaf\hTcRaZbfcFdaFefb]N`T__`^`_Nc^^_R^^V`WUZSRZOOVOHLZNVKTLNXMM^OQTVTVQVNWVVZ`_V^VTZ]WZ``P^`\Z\R_X^`acPfhcXbiVbda`cR^abYU\XTY^PQMUM^KIXKOVOQRbQLRS`PVPN\RWYUPZ\]_]J[[Z\a_`\\F\]NbaNhicb_`\`\[WHV\RUBPdPNQMTOZNRRJN`TMdUWRTNPWXYdX\d\`b_gDeafZfea]]^\\Z@WXNX`WNXSUURTTTSRWTbQPQTTTTOTQLQPQQUSNQZSRPjTNSNPTPKNMZOVNNLTSSRSRPRTRTQPUPUPPSRVVWXV\L\]]TZ[\P\\^]J][Z\R\ZYP^\V\^`FYTVbURUTXRPP`SJQ^NVMXOJMILKMdNdRPQhRRPOTQ`PPOVNJVMGFDDXF\D^DCDDGGEFJFbIF\GDFJGfGPJRIdERHGJGXCDVFDZCRBTACA>V>?>T?==F><<;;R@T@\AAfATCBEJH`JRIdMMHQP^RRbSPT\URPNR^NJLPIPHFIFVFECTCDCTD@RAAh=LB\?B@ZChFCTEPFFFHKOJKIIKhK\L`OLQJOTOLZPM\JHKLHFVGGZEEHH^HCTGFJFEFCFEACTCfC HTEDC\CDNDFHGMKJMI\LLPZORUTVTXfXXWVfY\XNWXXZVVSXSbVPN\MNI^MHFG\GVEBNIVDCRAD?>?RCE`DbFZGH^EXD\EJGZHRJNIH`ILLVQJQP\T\NOOSRLU\UVQJPQQVROTNNVNbLdJK`EVHLFB^A@>CC>L=>R<:L<=L9Z@J=>=<=C`BTBdBCEF`GERGZJdMJOKNKLNQZWS`OOBKPPLJNMTLLXLTLVIFGZHFPC\DPD\DNDAN>>ZAPA\?<^=;X=T:J;Z89`98V86H8R55J33021J2j1Z2/Z3P30`0R1V343X354L4224V1R2R14X34F44^4Z2\534b5L6T33R3T4T42`4Z2566`5T7\45J4:R65Z7`857:8799569563\4V533T3N3T1X221-N/--,-+L1-P+R*)*('%V%&"Z#X#$!L# PX ddJXRrVN^JLPNbZRFZ V P \ T P b F R ^ VLVhRTXPPV\P\Db^lVVXJPdTPLT`^Z`T^HPTNVLP^^^ZdZXXLTPZXf`ZL`\XXVR\XVPb^bN^Z^^fPdbVXXZ^T^VXbP\TZ`VlR^RV\^L^X\RdLX`bT^X^P`\VXLL\T^`HRN`XZV\XPVXVV^^VZ`P^TZVNXbXZNXXT^ZLJXT^`FXTjX^HNfZXVdT^ffrV\bXfnbh`RfTfZd^h^\^b`bZThjT\XhXdJZZ\T^b`dJfrJbDJVZ^T\`TbHPVZVVPjP\^`VLXX^TTZFVZVLX^^f\Pb\\TZdDTXTTX^XFXV^TX`jZT^ZTXRX4bXVRJRTd\\ZbXTXZTNbbP^\R\JZbXN\LZZ h Tf  ` h ZV Z^\h^XVVRXJVZbLXP^ R "F$L$T$R%^!&&T(&(*(`+,-0L10T3`3l373Z463R55X666\389Z99\<<;R9:X=V;=9T:8987X7J554X7L35`3d3T6d6F6X76662653563\2X42R2X59f7\4\63T8\4Z5^42^6T6N6X5\45\5X855P:T9V:X9X99T=\;;;=:;T>@VHBRBdDTDTDHGJJTJ\KXJHJJK\MNNUQRMTVRbQVUPRVRPSPJOMNLMVKVKVI^KhOOQ\NOZMOMJLIIRJdHHFTLLJXGFTIXJTGIXIXLMJ^KJHINNVPRjM\LVSZSV[^]YZ[[VYT^N_\d^g^`daRdcNm^c_\c^][^^_^R^^c^baN]`\ZV]bTTQSVP\RPLP^MMBO`ORPNTPSJRRHSTVXXTUPXWTWPV`YZYP\^[YR^\T^[`\Z`dXfXeRjbbTcfLcbfdc^]XYUUTRRTPOONNNVGZKPKXTJSNQZSSXOP\USWZZXY[Z]\[HZ\R[^Y]^\_\cR`bTacfdhe_d]``_]\^R]dWXVNRMNOLOLMOROMZSTQSZSHXZURNX^XLYY\^Hd`h^deRfNcaccf_aR\_[WULVVWU\XHTZTTVSPURV^RTVUTPPNTPSOWRWTVTSHRRVSHPbOVOIZNTOLQKNMONRQSSOPQXQRWVQ@UTUSJVYX[DVR^\\]^]\[^VZZZ`\^\T[ZWYXLXZZLULUTT\TZRjRXQS\SRQPNKKHRNNNO`QQ\TTVPUSRQOhPLRRL\IVIEDNGdDFEDB`GFDPGbGZGGGGZJPFEFGNJHKFD^HDLE\EFACA>?RADAZ=`?V>=P<\;;D>>T;V>ANCPBTACCHJLPPOOQ\RVTNTTQRRNTLMTJHZFLHTF`B8BELA^DDN@@b>>d>@?CRAADXABGLIKLGXHH6L`JTKKKRHM\OObSTRRPMVNROKJLLHKF`ELHJJJH`GZGIZEPGEdGTEJIE\CFCNDENKZH\BC@TF`DZLHIVK\KMdLRMRNRLXORSRUZT`[XXZbY\ZXTWUT^Q`TTQMOLbIRJXITK^DXEVFREFEBED@D>@@BBPEfGDGEhGIJ^LJVMhIKKXMKbNPPLJOTQPPLSQ^TRRTQVRPMKKZK\KJJ^KHKJEFDEBBZDB;\=<@;@>>Z==d?@XBC^E\DFGZG\JdJGLIKLNROMfONR^QOPQ^ObNO^PORNOONKJHHZGTHTGEDBBVA^>=>R@T;?;`>T;;;`9895:7V69V5R432b2R5V65426X69R45B8V55^323513P2R3V56453V228H2Z5`484125\664Z7d7X:9Z8H99V>`=PR^?ZDEGJbIDD`KH\IJVLfIIfKNLRM`MRSM\QP^QNSSSfRQLNPPVPJJKXKXOXIKJPMNJLKHKVLGJM^HPKJNJRGVEFIFKZHFFGPJhMQJJJNZI`LRP\OKXPQRO`QU[D[X[\H[`cZ^^_\acihdeggdc]^N^Vab][[R^ccX^_^R[d^[\\XTMdQLRLL`MLKOKNRM^QTPS\QRS\XPURPUXVWRWXWZZYF[NYb^Zd^ZZR]a^Nfh^eZghd^fJd\cb^`^V^USXTOORPOZQNLJLXMLRPQ`QVTPQTVFWPZVWP\N\Y\V]_YbZ^`PZ]]PbX_aVefcafefdPa_ZaN_P^^WVVTQPXSbOQKVLPLONfQUSPP\TbTTXZZZP\\abdPcNc^ac`]H_^a_XYRZWXXWU`UTXUT\OPRURTXVPWPTXSPDPZSTTUbYWbURZRRXS\MPNLMLQQQRPQQLNQQNOSNPR^VTVPVWYNTj^`Y\TYU]YR]Z[J]\YYYTW\VJVWSTTTTWUPRQbULVXTVPRNNML^PR^PRQRXNUTPVLRPPOPLMKHXGZCBTDVFRDNEICbDXJGXIIHZFEbFIJJ^J\MRJHDBCEHEXEDTCVCHA@>>>V=Z>=:N<<>=AjAVBVDXDCGJJMJLP^QXR\PORQMOMbL`LKH`HAANBDAD`BNA@?@V=X?@?NBZADB^CPC\GXIJZIXNMVMLJZILTLJ^NOQPOMRM^MNKLLHFFNGGHLHFBGCGChEDCD^DGBZD`CXGRDDCHBXHNGHRIMKVMK^LKPNdPVQNSXW\V\YZ[T\X\VYVTVXS\XZXJQbOZNQHNbNH^HTGHGFXFF\CBHEAbDEZBjADCREDREECbFPHJIIKjKKPNJHKLXNFSNPXRFQVRhTbRRQPQXRbPPXOHP`RJPbMRLKZHZHPHfHDZ@BBN?\C=\>T=F<::b=VAH>^=X=F;V>V=>X?P;V=^f^TR\DLNZVTZf^\Tf^VNL V V L V ^ d V XbJ\Z^Z\ZJTRTJ`@^LR!N"!%V#R$V$'$&N*V,)X)L++T-0537J5`63Z5\4T6X674R5858V77N8D=f>:b89<=<8V977Z8T77663n2X4X43258V73R4P58J5Z4b6b4\53X33\3V3X3H4T656^5\4X46P4b4V2H32J7R1V37d7656788Z;N>=^;9;A@=N>@@^DLD^EPF\EFFF\HIRIXGbJHG\HFMKOfORSQS`RUOXOPPRTXMHNONNKPOLH^QROObJHLJLdOJLFHVGGTHIfGFFFRG^HGIFGHILMIZOZKJZOLNdONTO^RTZRRYLXW\]P]\]T^_R_Zbe^iLdhRb\cN]Xa\L_[`\[`]V_\\^eB`N`R^b]\RZ:XJSROXRXROdKRKZPPL\ORKXMMVUNQLQRWRURS\SNULUTRVXR\WTZH[WZY\Z[X]cPcdZbeNbjc`aPcbLdb_L]^_ZLSRUTPXUZNM`MNTLXKNJNTSVPPZQPSbUXWU[V[^ZZ]]NZRYZ^b]V\\_gb^aZgVeZh\cXbL`^PdjfT^N^YRYV\RPQRfOOKJHJMPMRPPNLPROXSPUXX\Y`]J^\bXdaa_^^bc`^cRZ^DVjXXWXRXSVTNRBTTSSXYdVPWRSTRSBTTUWTVVXVVPSPSR^ZQQOPVQMKL^LINMPTOPPP^NdNLOFM`PSVTTTUTYZ`YY\]V]XL\XZPY^Y^XLWTZTRPfY\WSR`UHPVQOTVJRQJRQlOPPPURNWTRQVPUTQRQPNTOJIRFDV?C`CAGDJAbFXCJHHJHG\GNHHbGIKJGIHGECVF\FXE\C`GCBA?TB>T>NBP>=Z@>@pALABFNJKTLPMXNTRQQ`MPVRLLXLXKTM\MNHPG^EEBTBdCCVDTFVCA\?@@==XD>TCCRCETF\FHKVHZLRNKdPMJJXNRNVPXRXNTbRNQRXOVQKLbMVKITMLI^G`HGHGEDXCE\CCdBDBfBLDBDLGZH@\CDFVIJVHZKHOHLK`OQRTXU^YVW[XZXXUXXU`TVVT\PQNNVN`MK^JNFEGDC^GVGDRFTCC@CBXEJCVCPEXC@`DEfGKRLOQVIXJJLdKbOPR^RV\QPSRTU^PPVQ\UbQ^RRPNPdKZNOXLVKMVGED\BAXBBN??>\>@f@=>>T=A=>:V<^=L?b?@:><\?N@CfDTFBFCFILIJJbLKRQTL\PPZPPUPVNXONO\NPXO^LLTPI^LJKHIHHHEbBLECXBTB@\>d?RBL=<bRRT V \\ V T T X T ^ Z\ X^RL^RHPPVTDVN\bPHd^Z!X! \"X$L"%&^$$V%&R(T+X(\+*N+T+N/N2R225R6T436X6\976P3Z6B876P8898^<8Z>;=;=79`9?XDBGEF^G\GJLE\GVI^FTGEJPJbL\MBLNQJP`OOO^RRQRSR\O`PMORMZMTOMLZMLPPLGZNL`NGPGK`G\G^IIZFRHF^IIFF\IJJIXGH\KJJIHJJTNVPNPZTVUJO^UYTXY][T]V]^`c^cZe\dgc`R_R[X[X]Z^[R]\[R`^fd`a\^aN\]\XTTPPQLONON^PLLLZOVKMZP@SQRHRTUVQRWSTWbWUXV^X@[XajZN\T^^`bVageh`aRggabNbV\hXRXTVTPTRhRNJLN^LLJZOJMKVQQTXVQTTJWXZN\dX[VXY^XR^\^L^\]cVigfbdRcl^jBef_ZiafJ^TZRWSTO\OOVOMLIKFHLNS^RJN^OFURWPXTTdYZT\XbZaV_`PaJ]b`V^aVc`\]Y]`[LXZ[ZRVTQQHUZSDSOVZLYJUWB]U`XZUJWXTNTVLTXZWSSSJWPRDQSRNLNMNNMRMPPQPXTDPVOPVPFSSZRBSNW\UVTTZYXUWbZYXVYXVWWNVWTRZSXQXRXQS^SUZRRUOPP\WbTPTPSVRXRSVSTRPRQPRR^VRTPORLPNMZKNF`DB\AR@^@TC`FVEEHDHXJPJRIKTKfIKZJHGKTJFXGFD^DEFVEFEEA^DFBX???>==Z>R@@?<:\=>;<;==L=J??^ARFNBZBCCCFHDH^JHHJXNMPNRPONQTRRPQNMNNOXRMNNHJLPMLJKJDZFBHRBR@`CRBPCA?V?;B?^;^;>Z7N97R77865d85Z4R4Z200`0X10R/X022421\2313^31N0^20J435`2T4P1^443T4P5f2R6b86R:X5^514T4V5848\63\55X9R7774Z68Z6Z7\96Z8^8R7N7B537765T2V424T14/000.V.0b,-R,P,-*L(b,T(&R*&T#Z&"`# T"L!"X ^ X\\`RTNRbNXRNHNRR^PP\T \ l J d X PPPPT\NR\FNJX^VF^V^PP^fTXXXX<XP`^ZL`T\PhHTb\hRZZXJVp^bTZXVPXTHZHVP^VXXNTRJPVLXZR\P\JZRRPTX@`Tb^^dbR`VD^jHTNbPhVZ\`RdPJVb^Vb\f\PVXVVfD\J^T^XH^jP\PdXdZNTXJT\VZZbTT`XXNZhX\\RXP`RHb`PT`VPfhNV\Tl`f^dh`V\h`Nfh^b\ZVh^Xd`ffXJX`\V^PdP\`Tj``dXT`bZX^bTf^HVVVVLZR\PVXRV\^NVXP^XZP^XZJXZ\L\LTT`TFRLjdHZ^P\PbNd^`TDP\Z\NV`TVRTXVd\^dpZ\T`ZLdZXRJ\X`NFbZZ^TT TR R > V ^ X P ` \ dT  frZNN^JXX`^\XJVJb N#^#R!N$`$$$#%&^(T&(F*T,R*F+T00Z41f55X5^5569R84b5Z65X584799^9Z8=X;?f9b9P8J<99Z8T99X54566`79b9T74T4586T7N85X5V4^01364F4`31V2V63Z6X34P4`5Z5\1X5V633J5X8X8\996P7Z9`:N9V;88R<=?=`=?R>TGDGGREXJGK\GdFTF\ILGIZHZI^KKjLNMKJLORQOOQFRMSQP\OROSRSVQMLOMTMVQM\NIRIdMOKZKRJ\JGFFFHXFVCNG\KHFGH`HbJM`JTII^JNIHPPQORPSOLVTRHZY`X_Ra\de^gVkif`fNbJaZ_bY[]]N\[\][\^`a`Z_^ZNZTQVPfPPSPMXNLMO\NKXRRRUSRRTTLXTZT\dZWT[N[XW^ZW]\[d\H`a\cRe`f_Zeb\c]\X^X\\TXP\RQMNNMRLONO`MLRKMKPZMLQROVURXWYTXXLZ^X\f[^L[p]Y\aP`ecNaRcT`RaZa\h`fg\h`cRaV\VZ=T>=L<:=P>^BVADCVIH`KLJL\NPOLLIF`GHTGVHGCFVH\CVDBBPCVCLBBC`DB\@RA?AAPBBREAXEVJ\JTLNPL^KLJLPONZLN^MPNP^MXQNRMRQ`PROLPGZMLMK^KIGFNETEE^D`BRB\AHE@@C@TBbDCVCZDNED\ETLGGIINLL^THOhSTTZRXTYXZb]Z[b[XTXWPWS`XSNPNPQTM\JZKHMXGF@K^JF`HCNCXAA\CZCbFCCTDDHZBFGHZKPKJJPL`LJRMMTSVR`SUTVSZUXVLSbT`VJUZWSQQM\PLZONHTJPHIVGFNHJI^EAZCA@TA??B>V??=;R;9=>J=>H=?^?@NCDBPBDRE`BCHVIJLRLTMLMVPPNOdNZN^QPPXNONPOXNXLPM`JNJ\KJ^KZGKGHEEZADCBFA@>>=>?;=;7P8V8T65N85\3320\21N1V40N223X2Z5P310P2b5311L712V1233V43P21X13N3644V5^7526P3T5V539Z4Z3553566^635653P8\65X7Z55V4^863L76N3R00j5P1/0^//N2d/P/T.L0J.Z-V/,.\,-X*`*'H%R$$%$"X#^$`"!! ^RRRR^VPZR`VXT^\RdH bf V \ V b J N  f Z^ ^fL^^NhV^`L\XLNVPX^XH^ZTdL<TPVVTZLTPVbVX\bVVXPbT\`b^^R^\dZXJVhNLhVXVjX^RR\\NVdRPVVd\LfTL\JPRZPXZTX\lHTZZLTVPfZZJXVHZjbVZXV`^XXL\\^`ZV^hZVbZ^VZ\RTXT^XPR\jPRVR```VVTJ\NRVTb^LVNP6VXRNZZ`V^ZVXVXNX`ZPfJ`b`XlV^X\XPPRb\h`L\Zh^dpVVZX\XVZVfdF\`bZVRJZ^\XVT\ZR\^PVVdRLLVV^bRj`L\R`fJVVNZZ^RRZF`TNL`JPVRJ\Xb\LNlR\XVZ\RdPPNb`b^^\H\DRZ`\RVT^XRVX^fTTRf^LXVVNX  ` ^ \ X P \^ pN\PZN`LVVZLHTP^VP`XF RL P R"P R"B#X$T%T%$&)R(*j'H(,++R.0L3323P435T6X855Z63L5b58Z6F88F9Z9;<:X==V:N:R:9X99<9673445T6P57V8P9T6697`8^4N5L72H4353N2X44N2T234X513Z44d5L226V3P5\6V5L8R7V;6R:Z79<8V8ZbYNXd[WXFZR[\ZhWZV_aF^NdabbdaaReLa^c\]JYVSXTTOPQNJ\GHXKKRKPfMKI\LKQSVQPOTRVV]RYWZZLbTa^YZ]ZaZaeHd``cg]cHgXfRedhf\e_`J_VTYQVPTRLOVKKJMRL\LbMLN^MOSVVUXXYXZW\`_V_\Z]\`[P[]ZbZ_X[[R[YVXZZTVUSVUDUYTTRVVVUTUVN\ZWZ[J[[LWZTTTNSbUR`XNTXTTRDUSZUQZRTQQLMOLNVOVOVORQOVOQRQNSUPTZTHQXRUSTTRdQSLRQ^RPTdRSXTZQS^STQ`QUTRRSTRQPPQTPQPQPRNRUJTSR\SbRXPS`P`SPPTORMQQDKJ^IG^CHDDJBXABBZBG\EbEHHEVKILHZKHIG^JdINMITG\JPJEGVHGXJGTGEVFTCjAV@>X=P=N==>L@>@CACDF\JXKILJTLJIVFDD^DXEPGTDGECVB\CBVBDXDFZA@VDZ?>?AAAPC@BICKXJTJMXITPJZOdJ`KTNLLNhPKFM`NNMNMRNN`MIJbLMM`L\HRJGEEXDdDLDBECBFRCbCCFEEGDHEJdHBGPLTJ^KKbNNO^RJULPJYVZZ`\\[`VZW\VZVWXWTPVRPPKPLZKPJJFXILHFDEECTGECNCDD\EBVCA0CCEFVGXHHJJK^JKbKONZLRLPPRjRRRSRUUTSTXUSTPOMVLJIVHVIHE`G^EBXEL@CX@?\@>@=>@>=<;^;9V=R@dZRVfJRTP`TdH\J\ZTRTLbLdHdB^P\bh^db^dT^ddXX^lVTb`\RTbNZdX`fTZXhXbXnXH\N`lZXZ^LVdfVj^X\XZRZR`d^VZXfRR`P`VVP`RbVX``dTfXJX`ZXT\`ZTfNTTbVT`TNP^fPdTX`Lf`ZX\ZRfPZTVVJ`^NRHb^Z\ZVL\TffTTRRDD\^Pb P L R T R H F \ H X L \ `NbPdJ@LdRT`ZbVR\T\ P !$"Z#%"#$L%%T(\)&J)*,V,Z.`.15Z4255654`:34D6f7X5Z576T78V:;:>=^8N:8V:7P7X4R867T:^76d3j41X3V3L44P4473428X477b6:R9V999Z7::V9Z:T@9V=n@>=\CTDEHGHCEGZIdEVHDHXHFHbKHJNOJTRNQ`LRONbPOPNONbONOQQVL^LKZK\KJTKGTLXKIMGLXCCEH\FFTA@FGNFF<`>;d;T::`;=<=X?b=<@N;>bBFAA@N?VEPCA`H`ENHK\LTKKNLJLXLVNT^ORVPOPQjPLRPQOMMfPLKJF^JGTIIZGHRFPFE^ENFXCTBVAV@?d?<=@;9:N78^666H8V32161`1X51P5:40L3R5L11@0X1412N441L4Z22X3Z2342N43T412X34X51255`254N7H244X3326X6X367V637Z667V9V5h6\9T:24R2654^74X352:421b312300-T,Z-,.*V+^*)'%&$P&\$\$$!!X$\!!\^V\PdVVLNZVX^\TF b ` ` R T XbVTjV^DDPXXL`VPb\\\Z^H^PN`\ZZ\XPTDX\bBNTVVb\R`^ZZTXXX^TRLVZ`bRXZV\NN`Tb\\\bTb^PZJhJ``TNVZ^`LfVVfZbZ\\PTVRRd^VVjFL`P\BJf\b^ZX\RbLX^\ZLZZZN^XdVX\`P\DXLb^ZXhbdRbZX\XRjTFTV^PbRlJT^`XJXVXZdjhbh^dZb`d`lZbR\DPf4TPXjbdf\\Db^hdfX^L\XRhfhZd^\fVfPb\^Rb@ZV`VTfVh\bPP^TNVXF^RXXF^\^^NXZZPTNJP\^^Z\bTR\PXZrfZHPX\TTRTVNj`NNXVff^XTHf\R^RTVLdNDLXZVTZVXTh\RdP^VX V Z P R Rj R^T B`DHdRRhHPTnLVVXVT"^R!`"T$L"#"R%R&<%^'H*N(X(P)-Z-0L.V0X/2R2\14L6V75^96\544\7H5h475N98:;;`;<9`:>;hCDTEEBHE\DFGKPGLNIK^JJTPKKNMRQNZO\NMNlRLSROOLRNZRTPLLKORNNLjKKKVKRVLMLZPHMILLDHFZDGVMFDNGGDEGJPL\IHTJJTJIL^KHTMJOOMNPRUXSUWRY\T\cBcfXkfddXcTeH_L_`^Jb[[^Tb]Pc[d\X_H^D\\]YXPVXUPQPSXU^ThSTNNQThRXQPOPQ\PXSVTVTUYRbU[ZV\YR]ZT]T[VZZ]VZ][bPdLb\bT`aTaR\L]YFVNRnSRZPRNJPJLGjERFE^IRK`OXQTK`LZNPMO^SSPT\UZ`X[d[[ZT[N\``cPcV`\Z_aP_V[afabTjbbLabZ_WXZPZUOOLKPNKXN^LXKMZPObMNNVNSTTUXTZX[_]]]TZ\WPXRXV[WR\YX^WVU\XZVWdW\W\SRTTbWZXPXV[V\TYV]R]XW`WVTRfSRRBQOdQBPPXNZP\PPONNOPPTNOJPSVTDNMQXOPPOBNVM^RTOLQ^QTOVOMMHSLTPLLZMNPPQJQbPPRSNNRVQZSNPVS\O^QN\OXPPFXULTTQMXO@OPPNMVPLOMOJMFXEVEVDZGbBZ?LBPE\EDZGPFPEfE\DIZFG^HPIF`IKFHFGHGHVJXIIJGGD`BR@=X@AjBTGHIHVIMDIPJVGNFDCG^DVCbDAD@TETB^BZDB\AZBhBHA=<@>\CXCEZAZDXAJBfEFFGMIIK\LFMKZKXLRNORNKJKOK`LNMMhMJMJJJ@IHPHHFDTEFECLBRFVGTFJECDPBHDZHFXEGLGZHbI\EHZHZKIRJ^JJKRPSSSVUULWV^NWW^YXWdWTZVU\SUVPRZQNLILJJHEH`EEBZFEDHFPBCJCFRCFDNFLEPCCFIKTI\GKJFbGZLRNROdTTQ\NRRbQhRhVWWX\USZXQRbORNFKMJLJ^IXIZFDXDG^CD@N:L=R?X>`?<:<;@=dABBRBRBEEEEXGHXJIJTMNP^OPSTQURPQS\PNTORRPMOTTVPOHGPHIGEJGTIPFZFTEGZBT@ZC@XA@><>d@\<6T7`86\7V6V352R320^.T1X32/J24d142\230f32V51212\6N2V2^22N6V2\3d4862H7B12`4371226^3d34323X636V4T75X6V656f5Z88X5j:J3V64^4V5N74P8^844X720X2X302V0`.0P-+-X,+V+',(*&#%%#$#H#T#^$B"`!RVXRbZNXh^ddXTRTdZ V f P \ P j X f ` dZ\LLJNZFTRRR^TZ`\LZ`TXTT^VZP^JVTV\^RX\\\RTZNNdB^T\\l`^PV`HfPZVR`VX^ZPX\X\fP^jHdXNXbXPLZXZ\TfVXP\RVTTTT\PdVd\TVl^VPXJlLXd`>R`VZXT\`\Tj\NZ^X\NT^T`RhNRRXXb^\VbZV\bNbNN^PbZ^BRFXFNZVXVR`XPRZbZZh^Zf\bdbd^tPXZbP\ZRLR`^f`bTX^TbRlbTfVdbLRFjVP\RRVdThN\J`TNTffRjXPTRh^TZpLb\\b``ZNRZ`d^\LTVVbTVX\\NPZPVVVXdPPXNZR`^ZXZXN^b`VPZ^\XLXZd^R^ZJJL^RVZVdTLb T b PV X ` \ ^ ^ j VPPb\ZL\\NdNXZL^^VT!$!Z#$`#"%$^%&R((Z('*T-,Z0\-0^320R777968544Z3V45T:3F66;X=X9:9><9:d>;b?==\>?TAbAfCVBFbFDE^HVIIKIHTJ`JI`JK\MJHKLfKRLXJJMJLJZMNhLI>KPKPI\HG^HdGNHGXEXGEEEDDFTFEGGECTGFVDEZIJXJHXLHLJJON^QRZVVVVhVRYVXZV`[PUTXXZVTbTBUdRPPNZMLJHHHVFG\EREA\BFXE=T>N=j>R=f99==?V=\>>Z=<>@\CJA^CbEVGXGfKXJJdMO^MXMLPSXSRPTTWbRTFVTPSNMQNONMKLNJfHZKHZJKRHNMJKDZFVB?TDPAZAT@X>`<<=`:6T5^8h6N6`41X3b6T1L3L20R12d2P52N6\33134V1N12V3\2P2.H3b12b5121^5X5345d52V2X1b345113V533b4j003724X1L6468686Z875865Z65^69N5N6V27^42T12R302021/X.D,^,,T*R)+**V&'%#\&"T#b$d"T"bf"^HJbb\XXVZ`\X``TTX`LbT d L j b R X L TV ZXJZbjLT`ZXLVZZXDVbbTNX^TX\Rb\RRVP``\X`\`f\dP\L^ddPT\XhdT\^Vb^`dPbbPf\PZV^H`^ZXH\\\^XXbP^Tdb`PXN^\^\TdbdR\^R`HT`\RhdZ`b^j\TjNJ^^F\b`TZTTRVZPd^b\``b\XdZbVTTjX^T\VRLZNR^NLbZVVRLbP\ZNXTZVR\ZjZddXlR\b^RZX\XXRVV\TTX`LTfV^jVZTRdZXX`b\^L`PJ^ZHPb`HTTNXbVbH`JNN^XZNTRT`ZB\NhRfJJ^ZZPLPNZHPPXPHV\dR^PXX\T`LT@\X`^NXRR`b\RX\RRVXXPN\XTd@NNRVRN`Z^XPX`NX^^FLR`PPL b P P ` T Z P X PLhNZ^XT\ZVNZXTRTBPZ^ZJPPHR"!8%#$&Z%V&N'L('L)B)Z)X-.T-P0/N0^1R4666R9d6D5T4776443V78:9`:\89L888<:Z7H;\:9\2`4X633N644012X4\4X43P56N513F52d7X78L87:V9N=P949X<\:Z===`@PC^D@^BBCNDjAPFEHJdMJVNLN`MRTN\ROPRfT`TOZSRVQOSLVQNM\RRbQNMN^OPLMVKbJMLONPKGHJKRG`KIGIVIJGFZGECETLZGVLGNK^JRHNJZINXKJJNMMVQOSQZSTTU[a_TcddflhFefPaXc\d_bP`]T]]^X_N`d__f\Pc\[^\YJ\\WTTNVQR^UNNRNfPMTOXOTfPPPUPUVVXVVYT]Y\\\D[]WZWVR[Y\[aN\]T`\^H_a_cR^Z[TPZMK\NfFFRERCVI`KGHGIXFKHXKLKMPTfTbVWV\WZT``R]]^`RaTdbP^_b^N]\b`^_P_R[\_\ZYVWY\ORNNQHFJ\HFMTK\JdLLLPO^OQVSTOX`UTVZ\WWXXNWZWXSUNQ^UWLWVLVXVZTZNTSV[UDXTDYJW\UXWNWBVJXTZVZ[WZX[JWUTRRSTQRVXVQNRZSRPPOQNPRNLZOO^RMdQJNMLMTNHOLMLjNLL@L^OJMRILJTNKPMJNJKJNOMJM\NLPZP`PRQRNRQSbUVUT[XRRPPQPSVUNOVNTOLOLQRUO\OOXLROK\HTKNGHbGFPGEJDECfCCNDEDDFEJFHLIVHBKHHKZLMLJTNNRNTMJJTIJF@NB^>PB>Z>bBHCAb@ABHD^CFF^LLRNNZJJ\IFpIVDBDCBA?TAb@LACP@RACD>V?\??=`;=?NCC?PBZBA`CDXGJGJIHJ`NZMKMKOKINJHH\HKKKOROVKhOL\JKRLETGEGTJDXGXFFGXEXFTF`FRCTDD\D\EVEEGZGXITIDIG`M\MLM`QbO`TVTSXUVXHY`[VRV^WZhYL[\WTbTPPOZMTN\KKGXHHRFNDDRC`CPBCCLCTECDXFjBEPC`EbGTFTITFVLJPKPLJdMJ@R<==J?X;V?>X>L<^@b<=>V?BA?RAXBAXCGEbGJVJLMFPOSQZPPTXRXVNSOPTPQTPbPKPNVNOZQTOLJTN\IXLbGIhGGIHDNFAJDAR@>Z@L<`>X9N8B7794B4f14553N23H1R/2152N1V3J30R1N3X2R02/N1^224N341b34254^4`51\41R2L4T5Z34V3X3\4P4264F1X375\563Z2T75T9844b7J9\7`65^658R577^3N344J40X00X0P01V.,`-.-R-.*(*(T(V&&&`'$T$"Z#! X! V!R^^^VXdRRhZZX^jZ \ hL h F X \ ^ L Z T b VH^XX^^\bR^RPjN`VXXbTVVVZ\JVNTTXLRbN\VRHR`RVbNNRTZXP\^^XhVZTdX\P\^\XL\`RX^bB\LLPbV`FXTVZR^N^\RDbHNT^ZLHN\TP\XVVZXZT\XVZ\V\bbNdLTVJZ^\PfJ\^hXTVTdbLZX`^PX\PbP\`LVV\PR`TVPRP`P:TJPhVRTFZ`VV\ZV\VTF\VfL\\V`RbRZbbl\^fTbV^XZZ`^f\Zd^PbVZ`bfZV^R\dNfb`Rjb`ffTT\VNXhPfPbX^fPh^\NVVbVhVbhNR\dTVR`TXbPV^ZLTl`fXXTfVPVZX\ZbZR^\`bLNZXh\RFhfRTPVZZJZjTdN^b\\HTR\VV^bf ^ \ X T L ^XRLN\\V^^XTXR "^#V"L##"X#%%Z(^''V((+V+`--/\..01Z3V4786X436R5d5X834^8d6Z7`9\::X>;Z:P<8H856V9:b8X9J:^9:l<:;:^:87P40\52^242N323/43T5\2\1\3`3T2Z4V54\5N513375^;:b:V>b88\;P;X>\=V?<=XC>XB@B\@A@`?^??T=@=N??>\>R<>>X>R>R@HCBCZDbGGRGJIdHZL^KVOSRO^SPRNPfUTTVQQTNRQOTOMjO^PfRLPKKHHIIGFXGRIIETA^DCTCCTB`;N=:9`77N8D78532R3P335X2X1/^0T.2N2204.1X2120P2b1Z0V13Z32\57f325Z33@4^2133X43R32V6V321R22`5236R7L5566^4895V67d5:\5646V744F75d53T76F333R1B30\1R-Z-,X.H..R+()^*('(R'#T%Z##`"T! # R ^ ZThZ^^\TJ`XbXTXVdR^  X X V V b R \R\TZRNRRbXVXZXXXbXTHR^^bTXV\^\T\h\`XXT^bXZ\\^RTfRn\X\TPVdZ\\^\RfXLZTPP\^^R`VZXZZ\PdZXXXdHdbZV^bZdXbZbRT`BV^ZXVfVhPXPP^RR^fd`Z^XZTNZLfRTVdZRZZR^fXTNTVTVTVNLb\P\NRXF\TDRVVRT^RZNXR`TZV@RXhPffF\dZbL^Zd^^\XFHZ`VbbPR`ld`bXBVbTT^h^VHjZ\`VZRdRHjb`VbX\B^h`V`TZ^h^HfXL\dZX\ZHj^\NbB\V\ZZNRX`JXVLR^RbdT`b^TRRbN`ZTZVXZBPLTNVR\`ZBVZRRPV\\VXX\TNTfFRXZL`V ` < f d ^ XZBZX\bV`LXLN^bTbRTZ`H^^`\ !D"!!\"R%%V(^%P'''T)V)*@-T1b/X..^.P1P0J63X68V6L56V5Z3T4`5N6X5B579:;;>L=V;<\@h@TAAAbAf?RD>CZCHDREEPIKTN\LLOPRPZOONOLPWXWZ\TfSROPMMMNPMLRNMLO^KRLbKXMVLNLNNTLMG\GVHZK\IH^KHH\GIXHbI`EFVEGRGG^HFHLJHMKPJNMPPVLVKPPMZURTVXY^YZZN`_Xa^^Tg_\fTgVceV_Vadda]R]_L\_XW]N\^`\[_`]^]bYRV\WZT^UFRROFLhKJRMO^QMTNPbQS\XPTYZ\WZYf\Z\Xj[\YT\`^W\YLXVZZR\X\Tca]XbLbX]a]FUSQLOMTLbK`LIFDCdGHKJPMLROKZNKNL\RU\VY^]\W[bW^X[V\``Rea_XeJba_[ZZL]^Z\]V\^^_]VYfZUbQXPMNNTHII\KJJNM\LQNVONQPZPUfUQbSSHXUXUVYVXdTLTTSVWTWSVXUXSbVSUTTW\UWPRVVTVXW^VYJXYXJW\YRWT\RbQ^Q^QROPLNRQLSTNXLLJNMNNPMZSNPJLMRK\GJXJMLLVMDOLLJJLIKLMVMLOBM`MRMPL\LGL^LLKMTNTOPPOQTRTS`UT^VTQSSXVST\QTPROJQFRSVUNPVQZOMLMVOJ\HhJXGKGFHfCAXADTEBNEDFEZHLHIZHTG\JIXMNJHPJKJHL`KHIEBXD?XC@BRDXEXDDbGGEbHJJKZNXKJbIRHEfFTFPCXCNDBXC?^A=b?A@XB>X?>>>X?T;\=L@j>?@P?`BChCNEXEDIIFJXJLL^NNVKIKVJNJHRJHJJHITHXJKM^OMNQNJCEBE\GFTFFLGFHHLDFBPAJDCBNDCFbEGhLRH\KVJKKN^NOOQ^SVZRXbWVY`UXWZXW[WVYXRQ`NZNLKIVK`JIXIFPFHC^CLF`DCXDDEDCREIFRFELIbFITD\HNI^IKMZMMRNNVQRbSNPSVXT\TYUVVQ`Q\RNPQOPN\KNJ\HGCD`GHPITFEZARA\@=>P>@?=?R>=\?HBNBCPED^FGVLHfGXJdJLMJPNPSXSPRPTV\QQdTVQTPNQVNHM\OMPNLJ^JKKJRHGIXDHVFPDFbFAC@<:9V;P9\6V655F5X3Z1X453b65T4T10/3T2\2Z3R6J33Z1R1X/0F510R243P535L3T2V253T410R24R6P63R14`4R421F4V345b5R7X5X4X5P666b9P75T5F96R83V5^6J73`556324X5N1N00b02F1L/Z0R.J/\-T0+`+N+H(j)()&$%&\%%!d#!!T!d f\!R^Xd`RTL\^\VVbLR`^dX \ N ` R ^ L R ^T^ZTLZ^PZXR\XbXN\P`N\X``\PfNZF\XL^TPXR^\\V^RTX\TP^`\XRZV^VhRVJXXXTTZL`VZdXZJNbdNTBpf^Pb^F\PXRVXbZDX\DTHZ^bfJ`L`^l^RTd`^^ZXRd^TTPV\XV`^ZPb^HZd\JV\`LRPZh^VXTXZ>fVPZ\XbVb`XPZTbVRXVdNXlH\VX^\Zd`PbfXdb\^XTbfZhZNb\PdZV\VV\b`NZXP\R^`PV^VVhpRdX\X`^V`ZZXZTL`PjPXXTJXXbXfTN`VVPP\Nf\XNb^dX\Z^^VdPRT`H^X`LPTfV\\V`ZLXR^\T^^FVXVVZ\R``XZ^VXZTTJX`ZBdTR X Z Z Z Z\XR XbT^h^\LPXNTJJP\X:Z V !!P"L%Z(Z&Z%&P'(\)\'^&T+F,*Z-\..,^00\04h33j6Z6P3N16X55b84\6987b;h7>;T;X;>X>N@=9N=N:N<8`9R8X8;F6V97::\8=`:8X8\66771`3V531`10T61\16\21X1b523413V453b3R8^67V:7V;:<:9:P:F<\@N@=\=P=A^A>`@ZB^AFDDdEEE^KLPM\LNNNXTMNNPSRZTONS\QRNPKLRMZOXLLTMTKGPRLKNPMLLLKLMPHZN`MFZOIRJFGTKVHJ^EJHF\K`IKHIC^HKFNVS^NRMKJLRMdRWRUWRXXW`X_X]X_^L`^NcN_aRb>e_Rc`b^Z_\D]Z\R`\V\[d\]^^]VY^URUNSZRQOPNMKJOMMONVPVQThZZY]WZXZL]]V]YX^h[WZZ\YZ_T\a`]Tc^ZZV[^VHRRRHOLXJLKILKGXGEVF`FINOOPMMNOJQTbUVZVbWWVTY[^aT^^R^`af_TZZ^PYX[P\`[\Z]]V\XZX\\YVW\VRT\TRMXLLLZNXJI\LM\QTROMLVRVPRNTQPPSVVTUNUVWRVTVT\WTTdUVQVfSSJVRWTS`RPTVPRLTXUNVSRSSV^SXUVWTZXYYTZPWP[LQTQDVhSNTOXSPOPMLPMNNBMOMbKKHJHIJJZJJVNMLOXRPKfMKPHK\KLPM`LJQQJLLLMJTMIKKPLMROJNXOXTTQTQSZQNSRQXUNQRTNLRPP`SSJSUPOSXMKXMZHXGTGHbINJG\EVB`EVBPCCdECXETEBFHJIHI`HGKRI`MZKHGHHGPHXIPEEBVCZA@ZFCLD\GBGZFGGMLKZJJNI\JIJVETETB`B@\BCBBA?<>>?><<;\>>`?V==@>=J>T>^`=\?@NA@ABDDFTJVGITNJXLFL`NdN@ORSQLQTTVTS`SQSRPPSTOTOTNXNNMH`IFKXKPJH\ITIGTFDTHJDDLG?@R?;:`8X8Z7^6T5T95732P4\22V4R4X0\2.V./>333L1240b04\1R13^11253^3663565\3R431V32^33`2L5`6Z63f542Z33j6`4426V47L6544L74T765R58V566V656L2p31N10L3/20H/0Z,/X0-\+)T*)d*h(h'')d&)%!^#X!P RR^!LRXX^\PVd\RV^FXPV\  ` T J X R V ^ B Xb\XZVLXbRVDX`XhdbR\XPNRLRZdHTXNZV`VNTVPLfP^^XflPVb\RVZ``^VLRNN^LXB\fVXbXVZ^`NbX\\PRX`LV^\`LVVXVbPhVjXb`VLZ`^``P`HVX^\V`RVhR`\hj\\Hd\Ld\T^PbVPdXVNVNLZbR`jjf^jRV`@LF@JTZZ\PLbVRZXTNP\HZHXTNZ`HV^VlPblhLjdj\fTNXVX\^LRXdj^\PVZLbNXf^Xj``dZ\N\HN`VbZVVVT^`\XhPV^N`PXXlVbTRbDNnNPRNZT`VZVXZTTT\^ZdX^\XRF`ZL^^B|JR`ZRdR`XZTZZXTF\ZZd`\VdTP`hXHbJ\JTRP^LLZT L V X V R P Pd^dTV\N\`VRVZRL\VL`T!T#!V!T%J%&&()'N((X*Z,X*,R+,V.\0<2`4L5223H4Z7N4T6R5^6f68P5T66\7T9L87:T=::?L?J>J:9X<88N6:7L;8X89Z=T9^:Z:\=98\J:V9>X@TAZAjDLDTDEECNFTEHXHJKPLMLKJHRIFZGXGXGPJTKHGjJHZIRK`MTOVMKHIHZFG^EFJHXGBDdGVFRGF\?AAPARCACXFEG`DRGJLLKLVMKPQXORVVTYFYVVTXSV\f\ZV^QVTQQPOXNKRNMPKVEI^IXEEPDZEVGPEXANCCDFCRDFbEHTJ^GHFRITGFJPIRLO^OTOTOMSOVTRXSRVQQZST\SLUWNPRNS`PPOJSLJI`IRGJTKIENEdGRHNFXE@HA\>TBCd>N>^@A=R>:<^D@@DXGED^GNGKMRJLNTQXS`SLPQNNQ\TQXUNjQPNOZQQdNXKINIHIJXHI^EGGFJ^FDCfCB?==::P8\7P757X836131412Z4V1R0Z13/4220R/L-.\00.\/X0/b4R364F55752L51123X9534^3T34N334b5455344h78d77V5^8Z6f73Z7V542T8Z8V64P6323:33H4V///T1L3\1P00P0.P1/.('(*X)(F'&&^&%P%`!\!R$L! \XVVPZTdPT\TXTRXVXT ZV b P L R ^XTZT fXNdVTV\Rb`PXP`TbFP^fZRRjRXZR^Z^\PPdbdZRNRLRfh\J`jbTTZfT^`VN^Z\Z`ZX\fTNTZjbRrRhXhH^TT\lXdXXVF`RZPPV`JLdXNVX`Vd^RVbV\V\T^T\TV\VZ^bT\`\ZX\TNTNRVLT\bH\D\T`XfRNTXLl\X`\VXNTZRNZNXT\^dbNN\DdRTRHZZVpb^b`Pdh`ZZrPlbXdbXdTlfZ\flbbXfPX`P`X^bbdZVXddhdRfbRV^d\^fZ^bT\nVfdbTZX`D\`\^dTRXRTfVVZTV`JP\^^dVN`XVJ^VTb\VFhTJXXXVfXXLVf\JbZDZ`ZfXVPfVTXNd\L\XPVRVbVPR`jdZTjRZ H \ N ` b N V\TPVfT\bbZR\`T #Z!"##%)&R((T*\('*-V,R,*J/.\.V12Z511h5>72b54T4R8P668`899:J;L:8=<;==N=\<`:8VV<;^=P@=>bBT?HF\G^DFPHKLPLN^LPRKQPPQUS^ThTPUXSQRONQNRJXIIbIMJLLXPN\ORN\LHJRKTNdJMKXIJ^LPKFdIXLREVEDHRFPH\FbDPFHHFXIEGdHHOGVKXPLXOXLZPNTSXTW^ZY[XYV^R[_Z_`a>b_Vd`\^R]`a`]_ZT_P^XP[Z^\\X_V^V_WbZ\RWTTR\OPPRRRPS\QMVL^TNSQQUSDS`URWLZXXVRWWZ\YZW]^[WZHW[W\^X^T^X[Xcd\ZYRZdXRZLVPMXNJ\H\GJTF^GNIbG^JLRIPPZKKK\QNMPTVVX\\ZYV\VWZV\T]^Z^]d\Z^\Z]P\]TZ\]_X[Z\Z\Y\W[Z[YVVVRSSTO\RLdNHdPJH`M\MZOHOJKQbOTONRLTPSTJWShUTZTVNWZUNSRRZPOJRbM\OMXQPSOSXUQTVTRDWURVTTT[XVJW\QTZVT^PTQRPOORONVJSQXSDSN\QVKLXOjLLMbKZJGXHIIPLbIRIORJ`N\LXKH\MPLZLLLPTLJMTNLMZLRLJLVLNKlNVMVONNfOQfNQM\NZKM`MMTORPPRdONP\QPVQ^SPQPdOLOPLNLJKGIJ\JXIHGdFGAZE`DFCXFXEELFBIZJJZHPIINHTGHXIGH\FJEFFPGC\IFGIGILJRI^KVJHK`KIbI\GHTHRDBBB\@^B@HAD@@XB?\>b><\;R:\:\::T?P@XARADdBAA^EBRDbCfE\DCDEbIMXKLPJZKbLGZHPHEGFERIKHXKXFGJXKXMNM^NTHGF`HPFHZFF\GFXF\HXDBXEA@ZBDHDFZGINHHZKNHJKLKNFQQRPYUhZFUTbUTXVY`VRWFUQNUbNP6NTLPPLJPIHdHXEZFHCTDRCAACLGNFHF^DEVGTFRHIFFGTH`HGKILXPOlROPTRQOONQXOUXT^U@PjPQPRTUOXONNNXQRNKZMHFGIRHJGIIXEbBXDAV?NBV@??T=@HA\>XB?V<<>>=?f@=;N?b?VFJCVE\GEJGfF^GTIKXKfONNZSbMPMRPXSXTTO^QZM^OQSPNOTLMH\IIG^JRIGHKJJHGDbC@^A>=d>=:Z9V<\846X4N4362^4V3P1V30/2V1N4H21V10f41--.R/b2/b12B253\3J3L7436^54V42126\5R4\0Z55\6X5h5V7N33X4463J5666V8Z4X5T6`578Z56L6Z445435T2`74V3T2/0R3//Z0J3T./X0\,Z,J,b+L)Z+^()Z&T(P&`%'\#!#X"P"!V Zh F RRNdbZVJZ`P`fXHL^V \\ XN` N Z T L V \P `XX`P\ZZdZZR\N\R`L^\ZJNXVZTRbPTR`VPTP`ZRXZ\TR`T\TdP`XXNT\VV\RXLdZfZLbZTbX\J^RdV`d\dR^ZRZNVdT^bN`PX\^NTVNf\PbV`P`bbFVZR^JP\dVhZbXbPT^TVbRTRdH`XZdnR^\P\P\P``VRdVVJRZVPdTLbR\TVXX\N`X`BLRZV\hVTTRhXVX`bZTXb`^VZR^\Pf^bdPjJ\\XXXXZdfTXhPZZ^ZVbX@\T`bX\\N\\PX\^\LNR^\J^TVN^fNX^T\RR\F^J\RXPVNffHX\ZJJNXN`\bTJRP`P^^bTPnR^`hRDV^TT^\\\XZVPLR N  P N X T R ` PZXTT\XLVZTVZVVR^RJ`Z^\JH`!#!b&P#T%'&''X)'N(('+`-*V+V,Z-V2R0N2T422J41b5526X7B4^79N7Z66F9>L=;\>?N:88L<`9976Z<;T8:T;9:R7R88R7\6:45N2^3V4b31T11112N2R3X3Z3X5\362214X5N535569:WPUUUTTWURVNSTPPRLQL`PdNPOP^OQQPTSQTSPSJTS^VXUSS`VZVLWTURXWXRPTOOXQTPLRS\VSUbSPORQVRLVLLKLJEHIZJHHXJNLK\RMMTOJKXLLXLKLPjQMTOTNPLZLMKMTQfLQNMSNN\NVKRKKHLXK^LLNQRLNHOPXPVVPOORQRLOLIKIHKJ`GTIZGDNEFPCCRDTFGXIVGLGbJ`KIHIEfGGEDADB\E^EJ\GFKJLKJHKNLLLZJLIJIHTGVI^CRFZAZCB@TBfAL?TAV>\@A=L=>Z;J>X9N87<;D>f?J@XAB@@CCZCCVBEEFVGHXJGTJJKIHGFTCBG\FPDXGZIKXJFGNLVLIJGTIXH\GdHDFDTCNFTGF`FCADBFGCPE^GKKIIILI^LK^LLOTPPSBSRWWTUZWSUTUUY\V`VUVS@PQOM`P\O`INJ\FF\FbGBAdBCXCCFXFVGEJD\FdDEG^JRIKHTGHXKTMXNOVPQO`SO^QTRTTPRUZSTP\QVROS\PNXQPP\RFROXMIVGNJPJ\HGHZIRFVCA@AdA@@=>Z>?V=R>j=>\==>=^>V=d=T?T=j;=Z@>@@X?EEHJXNHNfMNVN^PXQVOPPOS`OTQT^TUUTSVRTNZQbPNPKJJO\NNPM`ONLLKPRMNMK LZKKJPNHfHGFPFfFJ\IVK\DVEDF^IELFPG\JIZK^KLVKL^MPSO\TTVYW^LYJ\TgRa^cdaPdLa_[Y^YPZ\dZTZYXXWPYX\Z^[]bZXZYS`\XRONMLJZNSVSVON>NORfVW\WVUZX[WWXVYZXVXRW^VXYV^RXUZVZd^fZfZ\]X\\Nbb]^R\`VSWRXQJ\KKJITGIFFRFLRJLVLOOKNPXOPZS^NPTSWJVX[^ZNVPXVNZUJVUZXXXN__dZb]X\\NZ[`Y^bXNYVWUZSPSNLNZKPLN^LN^JdPOVH`KbOFOVR^PRVVSUR`SSWRXUSPJSQNPRNNNPQPRSTPfRZP\VVXS^USbPPU`TbPTRfTXVSUbQNPTPdQPXUWPSTV`XTUSXSTQRO>PTO\MXMHIJH\IFKHN^JN^LVJXKOMXIPLNIMPJMLZPLJO\JK\KKJ`MRNNTPOJZJ^ILLMLPLN`NNHNRQNM\PDOPPQbMLLJJVMJIRI\HFbCE^GEHGDVINHHPG\H^HJI`JTITHPGDFCD^BBLBDEHGRJMJJHJLLNTNfKLLI^JF`GJHCB?bB?B\>?P@@\?R@J?b>dDDRACDABTBCJERFCJDVBHHMMKLZGELGEZFFDCEFRIJKFTLPHGXJPJGTGBF`DCFADCLF^CTDbBRFDDFXDCZDFEVIHIHTLIIH\IPJN^OQRS@STLULYPXLTVWTUPUYWNSPT`RQONbNMbKK\JbGTCFBFCNABCBEVEZHEZFTFECFHIHGHVJ`KXM\LFKPML`OPROPQFUOUTQ`PPS\RPdPR^RQTLQLbNPVKIPIRLJ\HLG`HGCTDAXBHEB^AbBR?>>?R=T>Z=\=>>=HR@?V>==R@ZBXEDG\FJJHKLIM^MLLMLZNQOTPfPFObLNNL\MKMXJJM\MdLIRHXJZJININIHD^CBEX=N<:V769V6d4535R5X221P/Z20/1b7X2J20F30P./-N.P1d.00H21334d54T56P5V3\6`45X6Z6Z7N46^5544475X3/R2b5\82313P7Z56X4V35859N535f5R4542T314T4\1P01\1^2221X/\11R..X*+`,)*X'X(J&V'\(%R#\"^"P"H ^ V V^jLjP`n.\\PXVDb\ TX Z Z J T ` ` Z FZZ`PbHZTZXfTZTXRXRPXXPTXfPXVdXTfZT`LTXZ^b\V`\^XZRb`TZTTb`T\n\XR``XjN^`LR\\XXPVPb\`^NV^TZVP^bZdhXRbdZdJfZ\dZjZXVP`fbPFb`Z\NhTT`VNddNVPh`VLLXVd`NJLZ`NHTHbV^\Z`FfZb\TTZP`R\^J^VPZdN\^dXPZX^ZHNNPRhbVp\Tb`^Z`VX\LNZPX`l\T\bJPXLdfdZfX`VFNbbRbZNLXVVZVX\X`LNTZ`HZRLXPTZZNNZXPJPXZHXdfZVd\HNR^VX\VX^\\RV`T\^^TVZDjVHbPN`HV`XfLZFbfXZ\dZT^VbTP\\bVVZVlTJdJ\NXZLZb^TXVP\TR Z \ V b V \ L^PZRZRRJXNHZRb\PT\RZ X"$"b##&)N(V)))+)+Z++d+F-V+L,P,T40021P52L32Z4\8Z46668T::6:N8X:\ZC@`BTEZFJ`LLNMPMLLKVMXRXPNfPRQ\STURSS^PNTOBQ`PNVLNLZORQNPNPLMXNTKLN\MLO^LTMMINKHMHLHXDTFGGRGXITFRGRGGRHEXEI\HZLVIbKXNMKP^PJTL[TVU\X\[_a^a^^_[N^J[F]^T\[L][`[`WTXZZX[ZZYVNTXOVPRMJKZLXN^NOVQNOZNPN^PQdTX\VNX^QU^YT[VUUUXNV^YTUXVZRZ\TU[[][YHb^]^Zbb\\ZVNR\RPSPQZJGNGVHMTJPLHG\FIHKKKLO^NRTS\RWTTLUSUB[D[\RZ^WZZXWXPZF^][L\^YRYYbXXYT]Z\XVY]`V^UXRP\NXKLVLRKNPKKKLJKVNRVRVSTSUZSTSLSdSTSRRUOXRPZOMHOZSTON\NKPQLP\OOXSQR\SLNTRORSRRfQ@QRXSVNX\XPVZYTRSTXWVWWVXRPVROPRRM^LMLK^PVIPLMIIFNJRKdMJLIMZITMKNMPNJKM\NLMXLMVKXKMRKJNRTMfPJJJLKZKL^MN^NTNNPNORPLOVLDOdOPPLKJKJLITITHKLGNGD\DFC`ERG\KDGRHXHVGVJIJHG`G\E`CCCT@FF\JVKKLINNNPLL`JPJI\GJGLBAVD??\>^A;T>H@V@X@`BV?\>X<=R@J>j>:CZACVEDCLCC`BVGIXH`IRLJ`HGRGGEBVDEIH`JIJVLHVFEVHFPFVG^EVGGVDEdECZEJEZFVE\CDGGFEbINGdHKITHGHLKK^KLSQRRbVVUWSTdXWUVTXVZHVTVVWPLSM`NOJVH\LVKGB`CCBXBCZCRGBVEPFDBC`CPEG^FH`LTJRKZI`LJLNNObNPQMTQHQTVXS\TUSQR^OOP`TSRZQOZP`Q`NbKLZKIJZITGIDDdH@ND^ABRFZBBBP?=@N=N>f=>?V>f@\<X@^EIFK\GHHLIRJVNMXJXLP^L`MLOPOSLPPNVM^PNOZNPMNLJLRMO\JXLGC^GGTGGETETATABZ@TX^\\VfVZ^ZdL\JhXh`PZT^ZZPLfNVXR\Tb\XHT\ZJP^L\<fVXXVRZTbXbRbZTX``TZhN^dTlf`PVpZR\dZ|bR\Zn`^jZbf\\\\\dR`hT\ZZbZZVdVVXZ`ZZN\VVVP`XVTZXb^ZT\`Ln^Xb``X`\dPZXpPPZb^TdLRXZ^T`XVVV\LJR\LNbPLbbPPZZXRZTNnXPRR`RVR^^(`XPB\XH^bVlbddHZdPTZR \ R @ V N P f `LTNVJTXPZ^XRPD`V\X!X"##"P%&'Z)T%&T*Z*^,b+Z*T+,+,-.X1106b5X4P3V3Z66476`:X7P;Z66R8D:\:l9;\;h=\<;N;\=;R<<79X7R=\77h6>97X7\:X9T;:X96V58T6j40\10T24R1h31/X02L45J7P33X566^0^547d48X5\8P8V98;^:8^;:;NR^KPLMPKfIRJ\HLIXLI`LKLIdKJXIXIMON2PQPNNTJ`IJPKfJLKLMPMDGdNXNKKKZLdMNKNPOZNXNVQZP`OQQNPOfQHMNOKKdLNKTHHTJGHVF^GdIEDJ.IGVIIJRJFKZGHEEFDCZDVCCElG:FVH\HLN\JKZNZM>NJdNHNKZJFCFBDAB@>;R=B=T?==Ad?V>b@Z@Z>^?>=N>KHKFED^C\A\AAA^BB>@@P?>X>R@=ZADZDVCFPFGGKFXJL`MTJK\NI\NPRVQOPbOLK^IJXLNLJJ\LIJNbSHVHDFNFTHdGC`ARAFXB@=<:8\;63R7643p2B2\341Z3Z20b0/042330:/T01d-\0V+/Z.R01X4V3573V52P4^46443N4433V566430313145543R2211333383R65`984D6h8Z561b4V3V11^2b2230`0X/H.`,.\.+X-f-)^+)X*'`)P'R&'`#T#!T#  \ VTT\TR\dJP``\^XR`J d n RR b \ X ` ^ ^ V T : ` RfR VZXZb`V^`V\T`Vb\Xbb^Z`TLbbNZRVRTVd^N\L^hZ`XR^hRX^VP^VVZX`XR^jVb\TZVXd\X\N^TNhfNXX^fXR``fV`^TVVjdLNHDPPX`T^`LZbZ^dPh\RfbZHXd`VpRbfZ`b`dbVX^bZ\X\fZX\bZ\X^RbT\^XVLPdTHhLb\NbZ\bLVXN`bf\ZZTTb^P^^ZTRjX^VX`J\f`f^Vh`XX`\XTVRTn^Z\bFXJbXP`\PXLJhZ\^`\^j`VHXRZ\`LZZ^TZ`NXXLTXLVVXTf^^TTPZZ`PNNTVNRb`^Z\X^\TXZVZHLZXHbThZ^DR^ZJNXT`^TP\\^RVP`\`FPRZPT\NR R N N \ d V ^ XFR XN^TRV^HXVPfT^Z^b b"V"J%d$R$%(R(B)T(V)L(,X+R+)++,P-,^1T1Z0115h5V4Z54N57\868L;b87N678H9<;<@T?Z;>P:Z=H<;X88Z:V:;6X64T8666X<<974T9N551/^3330X2N002354N36d543T6V64^4F55`5T4^456T5V8:9Z8T7N;9:7>;;N=<;>BTBXFVELCILVIfLKBJJQNRPTPOPQURSQVTWXS\PZQdNPVODLLMNMfPM^P\SNQXMOOTMNKLIJI^IM\JLGVGAF`DdEEH^DEdERECJGI^DRJLIFMO@LJMJMOTY`YY\XXZF^c`^_ba`_^]^\_V`NaP]^Z]f[d]bZZVYZd^\XVFYTRfSHQKRNZMbQ`PLMNTQQTQJSjSSVTjRZURVTVNWVUdXVTUTXVTSTURYUTYpZY\L\YT_^^ZZFX`RPXQNLZNVLVNGTHEhFPCFDGFJKTJLNKXMXPZPXRVRVTTTUUTXR\WNTjYP\XZ]LYdYT[X]Z\Z\`a\f\VX^BX\XTVTHSPPR\QLRLKRNNVKJLORMPN\TLSNPP\RTRSJOTQOSDWVRNNPNNORPPDSO^PRQ\PQPXNOPNbRRRHLXMZQNSJV\PTRVXJXbZY\\WUUY[[Y^YXWTWTVRQTPTTOPP^PNQTQZLMJJ^IVM^HXMZKZKLTJLLLKMMNVOOXPQMNXPXJbK^IILKNLOPNXM\MLNKRNJ\KVJRKZIVKMLKNNRQMZOdNLXPRMKTMVKPJ^IZJIbK^IHGHXGAXHJLFFHH\JNJRH^JJJGFF`GEDDGVJGLJLLKTKdKLTMXKKKKVGXGPDTCXARCBC>?:;P<<>;R@AR?^=BA>B?`=RA`===\?PBBn@>Bd@@ADbCCJDdDTHTEHTILKIJ`FGENHTEVHFHFXELKHZIKHJHbFTEDdHbDCIPHRDbHBF\DDBZEHDZERCGFFNGdFJIFbJ\KHTLIJZLNPQXT^SU^TSTRRTPSNRXXYfURRSRSRORRM`MLKFfGEH^CDDFXGXCZEXGRCZDG^FC`C`DDF^IHIIPFF^KHXGNJLNMLVMVMZLPJOZOQLRTVUNS`S\PQXSP\SRQRVRNRMLILPLLMMJZLZI^JbEDBZBNA^CA@VD>Z<@^>?=RC\ATAN@AACBDJEEIZLJINMLKLONQOMVNTMNORNbNMKNMVMKHLZKXLNI`F@EENJEEDdE^B^@>f=T?>J7^;f7T6P483306L304H13311/R2104X0B/\/.V/0V.V//.3R.3\6T34V6Z522\6T3211X647543b5\6Z51V2Z11\142^3V5210R226P8T35\5T4\4^5`5X4P7`6R6Z363J64T4T1X/00.Z/2\/b0V-,H,+T-*V)f))*&R&'X'%R$#F"d"T#!R!\bZbXRZ`\ZV`TRRZbV TX ^ b d T V J ` ` P J\hZP^\b^`PJFXV\HV\V\RbTdF\JPbZLBRTVXbRT^dbXVH\RTLLX^dZR`^`XVdTd\\^R^fHZPH\LJX^XJP^ZP\XXPdTNZ`XTXX^JdjNdJPZ\X\R\\PZnT^R`PZVR\^\TNV\XVLTZZ`ZdbXR`LbdV\VT\bVXfP^H`RX:ZZLX\TPVZFdTFNPTTVVdF^\NH`PZfdtfXbh^`VbhP^NdZ`\f\\T`h\f\bbf\XlX^bdl^Z\`bbL\jdbTV\TXf\\bbV`^bb\HT`XV^JXhZX^ZXL^XXTXpVJ^Z\N\N\R^N`P\b^ZVRRHTpZ`ZT\VJ\fTb^pVTXV^PZ\Z^TRRb>\ZPbLd`RJXVTZX\ b Z R ` ` V J X < R b N \ \ZLB^\VZXHVXTbZ`ZdHXZ !V"R$\&#'((\'(`*(J,T*,T,X0,L.-`.^1,24\46Z6Z5X55Z4V79f778h76T:7\:<:P=Z::;=>R?<>:N=\A^??h@?R@L>TCHAh?BRBE^EFFHGTGGPFEDLHHJDDZHEHEH^IJGXHbFE\HCGXHGVDG^DNF^E`CHEBA^D^FHFHRHNEVKZKHZIJHjILLNNUQ^P@URVRRRPSUTUX^WXZWdWQVRZR\PNLNTN^KXJ^FDG^FEDFGGLGTFZEdDJEjCCVCPC`BH^KLfMGI^HRGXHHVNXNOM^R\OZQPRLRQR^SPTSTUSQPMOfPTPOTOLMfKMNQQNQ\NK^IHF^FCD@LCAAZ=AP=N>@`@>T=>Z<^?A?XAP=@?DACTBZA^ETILGINITHJMILTKJLdRTQ>P`OMRRNXOLPOXJKLJIGK\KKIDDFFZFFCXFTA>?dXfZbPVbXbj^bHR^d^Z\f^bVPRhPbTb\NhN<XLRbDHTNPJ\TTbVBVPP`nPVP^\Z\jbh^\bhTNfZ`fhZXZZPVfbRd^PPX`VX^VPT\b`\T`\V^PVXV^R\^^h`ZVPZTZZffTRJVPR`RZN`ZXR`^d`Z\LXZZRRZX^ZVLPTTZH`VVbdZZPRN`ZNbXPXNXH\LbRR^V<^\PVPZT\RTRb^RPB\TTbVRPd`PN`R^N N X ^ T L \ B V P d`T\ZRTlZ^RXJR^TV^V"R N"$$&%f&V'F')++X*J/R.X,R,-/V0X.L-^2T333675X9T5V65l858X<76N688R<;=H;X=Z<:N9T:R;T<:87L8b7V6L637`857R99:Z7435J4T452\5X32306R4X4\35P45545L8:4`3044X6\5X64`8T9J85J7:f:P9X67X48R8f;fR<>Z@<><>l;==?@@^DNCABRBbDCfFLIIIRIMOKLPKRM\PRPJOZOM^MNPQPQXOZLPJJJ^JIJJ`HDHTEZH`HFHXGZAP@==;;;:;9T5L64^447442P23\32L3Z2T311H2d2P40Z./X1.V0d.X.N.V1B32`232J314T53T735L5Z255b7N13F5X4T5Z3N22X5T4\5J36V44123\7N5X5`5N4`5F4j5369\4^6b4b3`2\4J1\22`2/V31R61/P/--X,b++P)+P)L,*('^'R$(P&X#Z#!J!LX\\PNLdTF\Z^VXLbbLV^VX N \ J V H Z V X``NbfJP`H\^d\DVTPX\XZdPZRTbZJPTNVX^T\^VXP^Lb`TTX\V\blZ^:HXTXVTdZZFXNX\ZTTT\^T^VLbPTT^bPVbDL`^T\\VXTbbR`\P\f^^VP\^T``VdZ\VV^`XRVThXdZT\V^ZNLP^\XZ\VL^T^TXN`^\ZZ\^X\`RN`D\ZFT\XZ\JN`HTbLXVZZP\VVX^D^P\Xl^l`^f\Z^``jV^^N`^b`lVdZ^R^`b\hX``lXX^\XbZX`dZZPfZVD^LVdZ^P^Ln^ZZP^RR^dXd\PZlfPRLXVXbZXPV^TNbb^jTbXTTV`TX\\lRbVZP`dV\n\LZL\TR^LXZV\TNNT^RNPfPfZZbLVRX\XZ\PRDJ^XZZXZT:Z b P L V b T T N R N XH ZTdLVN\\RRbb^XZRX\`R^"Z#$V$R$&&)P))),)Z,L++^,T,-/b0/0R3Z253Z6Z5^4P5f7T8Z7V87^8T69V6;<<\;d;===^;d=R<:^<8d976\7b6Z5P6N59D78L9;8d856\6\6N72\4R443R25V3\1D7V56V564\756J23N2^5d33P57L6\75J6h78Z5Z9J66T87X7Z8Z=>;;<<:=Z=R<:`>ZBDD@REBT@@NBARCB?X@@`@ADHVGZIH\EfGFGGVGDG\HEGPERH`HDF`IGIfINJ\HIdGAC\DRDNEDFRCBEBTB@XCGHTI^GFF^JG^GIITJRMLPQZUNSRVQOQP\RPRTTUdQVRSPUPPPQOfNZOXQKZMPIFZDRG`DGZGFHDRGERDHACACPEVEIIGHH^HJG^HH@IMR\RUbQ\NRK\OZSHSVP^Q`Q^SQRRXT`PXSNZQQPQO`MfOXMRZM^PRKKJJKdFHATBXC@R>X@X@=<>@=N>^AN=?<@??T>=X?@bBLDfEBREdCERILLRIHKTKMKJJJNPZVXMLPMLMMObMKJJL^JKJFIGLGXE^GdFdFXHGFZEA>;f>\=T>9T:97R8N73P6Z413b4V2V0N6f0V110L11N3V1^1/\1>2J.Z./^..X0.124D2/0L2P3f3V44b4452X43T555236^33Z3\374`3J44T31^2`3J3Z2T33R3643V882V3\5T4331b1V441T21V4T1T2./.P.T/0*+)P++V)R,H*'R''%$Z"$f%V"T JT^\P\RHdP^JZXZ^NVRV b b P ` V ` d X P  fFXRJVbZ^V\X^X`bRR`RD^PZPPPP`ZRTPXPhNZNNfP^@dXXVPPXnN^FRb^\X^VZVfXNZ^PZP`XZTbRTjVVR\dPPTNXTVVXFdLbZZVPZdNbPZbRZNd\dFZN^\XVfNbPVX`\^\j\b`PPT\bbVTXNd^TTfHZ\ZR`\V\hVZZNXTNPHfVTTVZXbRJXVNZNNZRTV^V^bXbl`^\Xb\ZZZd`R^^Xb`VXNbT`FZDLVXZ\bf^XT^TL^NhXRVfdLhJP\JT^ZZRPZPRdfHfXj@p\TDfhXbVT\bZbZZ`^Z`\^PVT\V\R`TXNT\TlZFZXd`TV\HDP^Zb^VH\VNVZ\N^ZPTF`\dHRPP`Xf F T X R P d L R J JZXVHbVFdZLLbRTR"T X!!#$Z%%#L('V+R)T)V,,+H+*+\.T0-V//1X5135F56\8B6R6;5X55P;77f::R;<9`8:=H=^=:Z:^:T8Z8V7L8R6^65V7T59:8R876b>976d7X7X41h1^5T23F30X3Z2N3556F7R5P65R4R63N/4T315L2T7\43X778Z7R6\6X586b99^8\7Z;XRTPLNOPLMLTNJPJLNQNONO\ORTT`WSOMVPPQZOPPNNNQLXPTNMOLLL^POdQDNNXORfUVYZZYT]\[YTX`][^[T_@Z\_N\N[X^\N\]LXYVLVUR`PNPOODIJEKHTLIFLIKLLOZPMOONRXVVXSUZUZSXRMNdQVOLVLZOKHLJKHGGTHJHJLLTMFNJNPO\PNPN^NJNMLPNNMO\MMMPXIIOJXM^LITIKGTGKTIjJGXJKbKJPMM`NJMLLOKJ^LLLKH^HHFCAZHXAC`BTBCRAJ@TCNCX>J=;`<:^88J;Z;N=AZA=@>^=?=>\?>=@`?DBABbCLHJFXETHIdLVHVLTKVLJXN\NTQPPOQMNLLXPPHSORLIIIKTJRGFEO`HhGXJdEFGAP?=:;R;f;R;R;:88Z56P6R22V10V3\242b3.2^4F1b1321`6Z/N0H02/P+-J1.R22H200Z015d4X44L3V3\3R44Z5p655V434^455\33J5J53J6`46P5X5H4T542d556h686d635L5T4301T3N5V6220000.\//T.^.H,)++)V(\((&\'P%$^#$&!F!^"!V PbT^V\TbXN`d`\TNZTP`FVR\ dP Z R d h Z ^ V R T X X VZ RbVVRRVTZRVTTXLdPRRNZRZZhV`TTXZd^JXRZVXb`RXV\Zh^P`P^XPXRPhR^HZZVR^RX\R^LVPTb>LZRTX\V^pX`lLdNbNRPPZjJZFXXbZVPbTP\JLb`\^RTPnZV\ZZbVJZDJdRTNXfRP`LL`LXrXN^B`\LRPbRLlfHH\\TRRVfbFVPXj``T^pTXP``dVh\bj`\\\h^ZZ\JT\`Jbd`V`\^d\\`j`P^PZZZjXbff^T^L\P`N^XTNZXZRR`\nNPTbH\X<ZZ\T^XTJ^\TZ\R`NPTXZZV`\TZdfVVddN^XRT^Vhb^bNdZ^P\\FJh\^XXV\X\RJ^2V\\Z\R^dLb T \ T T R ^ T N F ^P^RRJ^ZLTXX\^TTNVP`TVVXRZf P"X%#$Z'''N'V+*F,(*T+*..--\1X/R/00N3\25T4`3L4D:T963J8T84F8\8J<:`;:b;8:\:n@@EZIJ@DHFTH^MXHVKPKJJQNNTU`POZW^TVSSTRZSQ^POVQTOJZRPQTRRXTRBRTSTZPNLZLJIXKGKFGVNHHRHFdFBHCXEE^DDBEJZHXHGbM\LMLTLOLQOPTPTdQWTW]`X[N\X^T]V\_^bTb__e^]__V][N\^^L]h\ZV[HZWT[NXXWV[VPSRSQRQQPZRRXQbRN\QQPQRLT^SSUVVZUbPPVNVJR^VTTTRX`VTV\Y\T\XXXVFYXdUYXbXVVPQQTNJKTGNH\FFJZFRIREJHLIJ\HQOOSPYXZZUWWbWZXUVTRVSLTTZTQ\TQVV^T\YVWLZ[XLYVdYVZNVbTNUVJSZTQTOLVKLLKKTPXOMMPQ\LROPIRRRSRSHUTPNPQVOTPVPOJVLNMbPJVONFPPNZPNNZOMR`RXRXXYTXZPX[^_XX]`^H\R^^`Z\_B\]XWUTT\XPORXNMMHKHKRJJ\NBNK`LMSXQRQRPRSdUVHVVbVZQ^UQPNMbLQRNLKTP`NTL`JHNH^FH\IHPK^LMZQVTHONPMdOMPNOPOXNNM@L\NKNLbJJJOTMIJ^IHIHHIPGJINJZJKJLM^PNNLKXK^KfK^HHJHGFECETDAbCB^A^DA?\@\B^;T@^=P<`;h;X;>;JTCPA>=A@H<;>V>^>@R?XB@ACDdBED^FFRGJHGXHfHMLMPTLKJP^NN\OPKMMNM\L\HGRNKRIIIFFG`EJHECAANA=X \V P L X   FZTdV\J@H^TZPXj`NXXRNVZXRZRJlXPZ`^jPPbXTVP^ZNJPXdXR^dXT^`TbfR^XXfLdXTTXTdLTTHH`PbXZBX^Tb^`\V^`PJ`Fh\L^ZZTbHTZVZ\VbZXTTZ`PZ\XbbdZRTJV`VRVHLX^hDdPR\fJ`PXRd\`^`\ZXXTjRXZNZVHZRb\PT\HP^ZZbX``TXddZdXZ^fdR`V`\j^f`F\\^TXX`dbbZZP^Z``^dbfPhTTbXRV^d\XZLfNPZRXJVV\LZdDZVRVhNXXb`XPZhf^TfbRNZXhffXPRR\JXNVDVRZJ\XbZ^TTVdNJ\\4`LL\lXNT^VPTX^RLVDNVZVRfPH`\N \ \ j \ D ` l T Z B Z  RXX^^PPLN^PP\ND^\Z""P$"B)&&(T)+F*`,++,,\+T-^/.H11Z2T2P235N868^5N55T5756L9J78T8<::8\8<;N<`:\9V7;T8d742J5H;R6J68V687X9V8d:T:V77b5`5Z5R4V4Z34R32P4\5^1X35X4934\5Z5J42/14`2P1N343\4R4V4166853677V9T@R;;@>BXFPINIPGFVGJ`J`MKfLILXMN\PdSSQRTRWQ>THRPNPZOLHMOZMPPQ\TQ\SRSRZOXOO^KLMRMHZKH^HJZJGXG^IXDFB\ALFDTCbEVCTGFREdJIbHBKdQDMKPZQXSOPPQXSThYJS^YH\Z[YZ\_J\]N]]ab`L^]N_\PZ^V[Y[VBXV`]Z\XVXP[\UUbXTSHQXPPPLSVL^NXOLTSPVTXTNUSRJSRVWPRRPfRSNUTVfT^VUWfXZN[WTWdWW`WJZ\ZTVSVUZSPOJZJXMfLLKPNXIdNRKZHGFXJfOM\NVMTTQQPST\WRU^TXTV^XPUUVNTURQLQ`OJSPSTVU`WXUL[ZTZ\RXYULVWSUdU^PNM^PXMMXLTOKNNbNZOIMRLNRQZRLPRhQOXQMUVTRZVZNPVLVPFJLJO`ONXOOSRNSOQSQFXV\XZL\TXRX^ZZ[^ZT\`[bY`_V\[TZVX\XZWV[WUVZSNVPROPOPLRKXNJTKPJZFMLIPNUXRRVSTXRPTNU`Y\WP[@VWTVSVUVZPROXNFORON^QQPOOJTKJFRHELI`LMTKPOJQdSRZQMQNLMDNPM\MOTJTOVLKDIXKKOL\MLTIbLFINJZGJTHXH^IJTKRJLNNXNPVLL^NIKVLH`HGGE\DEbEVBfBH@ZATA>AR????Z>T=>=D:?TT=\>=?=TAPALBAZBBLCVBCBNDfDLDZAZBFF\F\EHHFVFNFXFERGDIfFDG\F\HITIPJVHRI\CPIRFJFVIPFZEPEE`C`BBXB\ABVDE^CACVGREGHNVOIGNKfIXJJLNbR`ORROPJQNOOPHUSJURSSTTVTUXQNONQ`RRQQKLNIHZGHZFVF\GVGDFHPGCEETEIJGIJPKGlGFIFPN^NLLLONNMRfLRPNSNY`VXRSbSTTVTVTBSV^TJQXTM\QOLPMFO^MMMKMRGE\HE\FC@?@T@>@R>L=?;>@=V==>?@RBN@LB?BN@PCDDERENEFI`HJJ^JNPOPPLOTMJMfNhRKKLJNOKJ^LbK\KhLPL\KGLHZGdLHHHVGXBDPF@T@N=F<>X>=@R=^ALCBDAACCCFRFVEDD\FAVBDRBAFDEFFPHNJ^HGHVGBHXI`GJRIVG^JCRFXEEHCRETEXDTBZET=?PB\@PB>BfCDBfFPFEJGHK^HHXJTJJIBMRMTOObNTNSRMMVLRQJUWNUSRV\URQVOPNVMOZOPJOKZJJHFEZFE^FFHEFFPD`EGHPJLG^E^ICNERJNGILbLTMN^OMTJMZOPTUWTXUVSTUV^UUbTT`UVRbPPPQ^QVMPMZMMLTJJ`GbHFTFG`EHB@^?V>ZAX@T@>>X?;H>A>=^>Aj@ZCC?CB?ABZEABNDFIdIZFIJ\IVMLNN^J@N`MLP\QKRQXLMLJMJNI\I\HJIPHVFbGHTFEBR@Z>?>;L;PZ7Z9R756N5345R6L57f76H898X:V=9875Z44P4j5314L5`3D32D1J4b9`4X64b1P1R/N0R//b/N/N0V/T/1d12\54L9Z4P6^8V9999:Z;R@@fCXEZDETHDTEGHTIXHJJJJZMMQSQJQNS\PZVTPRS^P^QQLNNPLOPNXOP^QNPRSORPPOOLbMJJJFHBECDFEPEREfFEKPFFJJFIHHMHHKRKJZNNN\NONNOR^USRVUX[R`R\]J[\[\^]P]N]]XYXTXRYfWWTVRXXWV[LY^VYUbUTRTSQRTROMKMSONPPRS`RPZQVPRRQVRTTPTRTPPXVXV\T[VV^Y`UHUUWWYTLWVdY^ZPSJUTDTQ^NNLKK`OHHF\FXE>GMLHRMVLLN`QNNPNON`RPSZTSUXSHUXVLQQTRZXNRSRQPfRSRWT\TTRUNW\UUZNXYV]VZVUNPMbKLMXNLLPNZLOHILLKXObOOLSOOZRSPORRSTNTRZNTONLPORPL`NPTXPQPQOHONTPTSVTZQSNTVWV[\Yb_Y[H[D`RZR[WXWXVUR\NWWWLXXBTSVZRJRPPPFNJLPKJKMKINNLVMOJPVSVVVVTXRV^[V[VZYVhTUXTVSPRBQPfPPLNPOTN^LHJHTHIVIFGMNPPRSNUQ`SVRQRQLK`QHMKRN`O^KXKMNMTJHKLTKJTJJH^JMH\FVKXFGEJHHRMRPTLZMKKHK\IXI^DCDfCTA\CE@AV?ZA??T;^<=?dAB\@@AR@BBBLDXHF\CDLDEFEERJHbCBPEPE\DBbEEFNEGNIHK\JKLbIJRKXJGEDNB\H^GDXEAFDA\A\@VAjCX>BLATEFGDGJJZGJJJhObOPRNNTRTNPMPOVRXNbSMQPVJXXW`YPQQUSXOLPdP\ObOOMKNKHJJTIKHGRHGGEF\FRDDCZEFPHKIFdGBC^EFPGLZNMLPLLPNMONPXURV^ZbVXUTPSNRQS^TbYLWHSP@PORTNVPLLMNJJGHFFDR@>>j@RAT??TA@?XCH??T>@PA>?D`AABDECBED^JJE^F\I\ONORMKKKDOO^QNML`NTNOMXPRHNLHRIEHJFPHETEdF@@AV>V@\ABBDXEGGFHGdHVGDM\OVLZMNRMbOTQjQNPhRPXPSRTP`LQLOQ\PNMNHNQNPMOVSPRP`ORNLfJ`LLGIHEEBIZDC`AEFHRHfEXIGEMLLN`OPRZMOPbPXLM`PXRRRSbZbWPUZY]b\^]^]\T]\XbTa\_F_YP[\[\^\[`WX\VHWVXWL[WZYDYWbWZSFV`SRN\PNRMNLSJOTMPNNhVTTQORP^QTPTSWPNSS^WVFWWZSTTdSTRPSLRTVVVUVTWLTPRnVTOROZQJRK\IGVGXFREFLFGLLXNZKXNRMXNLOQPVSZQPPRTRSNRTZQJVUSXTTNPQWSNSSZX^SXWXT`WZSSZ\WTVLUNUVUPN`SPNLPNbOjPXMTQZMIZJJ^JKTKPNbPTPPRPQTSBSQTbUVOVO^PLOOMQRRMM^PKNVPPPONVTHSVWX[R]Z]aZ\a^XPXJZWW\WRW[V^YDUURTPSTPTQ\PPVMTJHMRLLJLVNVNMPVRUPUXP\ZZh\bXWYTVVRYUbUZRWQPNLONROPOdMNXMKVHLLINJJINLPdSOTPRQQ\LJONKNL`OTMZJGIGZH`KHNTLbJLK8K^KHJKfHFGVHRJGDIILKLM^LIJJRLRGPJELERCVDDC@b@>Z>@H>>X?TAB>\=HA==V?T?L@BD@N@@@FBXAV?XEXDP@\B`BfCHCdHFRHTIHZHI`LLVMTLKO\OLXONQPPO^OMTLTJMKdJ\HLFGH\HJGVFHDTA\?=X@Z<:=d88b7^56747^3T3^23X2X20N32V023.222X.Z01/000J/./d3Z0\2./012004L22R31N31J1\01L215R54P6^5X3Z3b2R4L5`22R23b541X343P683N343d411X21R4`65\2V4F0P2R/P/X/j-.T.*B-\.*)T-R*('X(\((Z%^&%%L$V#d%! V VRTZTRT^`XdV\ZPZXV\\ R d ^ X T ^ X Z T h J ^ P X XVLVVVFZ`d\n^RVNTV\VPdHdHZ\VP`^dR^L^PXfT^RbHV^Rb\\XRXbZj^X\`\ZTJZRfNVVNVF`N`bV^`ZTfLbPVhT`jTZVdRFRRVThVVLbZ^fRXRVNZTTdHZbXR`TR^hTZRXX^^X`\ZVVZX\``R\R\Z`VZRbLPVHTVZL^RFNTZV^LNZPPXf`Zdfhdh`PVf`ZfbXXRV`Z\X\V^Z^jRbZTbV`dNThXbhVb^VTL\bTZLNVb^dT^XNX`JdZT^DNPVFVV^HHXPTXP\VTRNXZTRN^Rf`XXV^\NTdTV`TT^XZTFbJPLbZZTdZXTLXVbZRZTHXlLRVXRLX\VRR`^Z>PNFH`ZT\PZVT Z f P X R d T \ Z N \ D L V H\d`FZZj^NZR^Z^L"R"!!Z$L&&^(L+)J*P)(T+,@,,/R.-V/R/X/L201X23T56\79974X6P65X:48:658:J8L989N9N:V86V655463H46\65P78J9X?ZB@EBAVFRGHGLNHFHVJJJKKTIOQQZPNPN\QVQbQPPQNHN\PJKN^LPTOXQbQLP`NO\QNQONKNFI^GbI`G`ETDDD`HFCVGHHF`KLGHjJIBO^MIXNIHMMMfNTNMNTRQVUpUNY]VZ_``^X]J]FaR^PaR^Z\`ZXnZ\ZJZXZPXWWUXXYPWWWVSU\WDVfUW\PPNXQMVOPMO`LPNPHNZOPPNRPTPRQURRPROPQP^VNVRQVTSRR^SQR`SS`VTTUTXUVPRTPLMZNNTKDFFGZFTG^GDlNNMK^NPQXMT^SZQQPTTRhRQSRWQhSZUTRQPPRTRXSZSSZSVRZSQURUdXUVTXVUWXWPWPMNQNRTNMPNPQKNOLVKfJITNVRMR`QROQ\TOUQWP^SPUbMXPQPXSQNO^LVNMHNBJLPRNMSTRRSPUTW\WWZ_T\R^YV]TYRWWZVTWTXVWZQQPSNX`XHVJQ\QTPLQPNMVLXLfKLQNLXRURSVYZPVRX\ZV[^XRZURXNPHVJSLPQPKOdNMLMJZJ\LZJJTONNZQPRT`TQSZPMVTMNJTMXK\NGINHLGHGKJNIHHKPKJlLH`IHIILK\IZGITJKVJKTMLKJGC`EVF\HAD\FC?P>P;T>XBBLDD>C`CNCCTD\D\FTENFbEVFDFE\G`I\GFFDGNDCRC`DFNDDDZK\JKTLRNKRNL^INPN\FPHXF`EDCCDVC^BCZBC@\B^A^CA\EPDFGDINFFGJFP\MQOTQRXURS\OQONNRPLNPMTQRVXWTTVQ^R^RBSVRPPfM\QLK\HHIJHXKPIHDFIHVEI`EFG`HFTEVGJ\EFVDFZH^HJNLNNKTO^O^MIMKZRPbU\VXTTVTVU^VNXZUWVN[UXVTURNQTS^TPNL^JMGJJHZEPEDZCLAD>@VAR?@R>>Z?=P>@AXBbBJB??@NBVCDN@ZE>BDDBLDPDJEJIHLIH^EHXJLO~NIM^MMLMhPVRMOMVNVOLK`L`IEH`GEGFD^C`CbE?`ARAL;R<8\9657L54R63N124P33b3332L2Z3H00/4@0T/.//0T0/T-B/0-V/2T011J2B/2J000J3d4223421^22V43\562p53T241225V60212234d74V465d4322Z2^3^32^51Z1R00/R0./X/.`.H-,P*+T)T,))'(T(Z'&T%$N$X#$!Z^^V\ZVT`XZVXDZd`NNX TD T n Z b X V T P Z R^\Z^^bD^^\bZVP`P`TRFP^LbZ\R`HZP`ZRXXTPT\XRXTT\bR^RfRVJZ`FRLnZbP\TJVVX`^dX`VVjTJ``^VJZdZhhRRR^^TVRLTVRXdXVX^PL`TZ>PVRZX \TfR`BbXTdb\lHRZ`X\@jNR\VVR\ZBbPXXN`NTR\RTXTB\hh`b^X^b`bBjPV^RPh\`RP`RN^PbVVd`V`^jX``\NT`RZZ\`RhZfdBdZVT\`\bPPV^X^^dTXLH`XXLX^VVXXZ^XXRLTPRV\NNXXR^d\bhX^^T\XblXXRR^ZV\\TVVVT^\XXVR`R\RTLZJ\X N l J ` T j R P d T Z T b \ T^FfF^`^XRVRNL`^DZJbR!#!$J''&&P)\)^+D)X)X+X*\+T/++D/b/L0\12Z32X3\3T4X3\95L8\5V6Z7956^9J7J:74b9>:8N87998b7\736T3V4`50T8475X9R<9H=:L;Z:`9:V98L5X9L6212F4X4P4j53R2X624T3^1b4.R2^30j00/Z1./V3`127H6T48NRBZDDRD\@^BACD^KHIXLGbIHVJHZLJ`MOVQ^NXRQNOVQUURRQMRQN`NNN^OMHROVRNNMPdRHPNLRLdLTMKHDVHTDHBZGVBGZGFDXJGGHGHRKXJLVLNVJLIPNLPNNPOPOVRSUS\NZP\c`_c\V^L^\`V[\`^[bXPVPZF[\X[VUFYTdXX[WVJWUPUfUS`XRTPRPXPbMNLZQ\MKXPTLVOPQPTPQPPZSSVX\SVXTTRRTVTSRXTPTPQJTZWFTSTXRV`XPVPTbNLOVPXR\NKlI^INGhFEFIJPKJLJPOPKjLhOJKNPTRPNfQPRURTNYZRRV^RVVRTWOPST`TU\RPQPUSRWRSRVVJVXSXSSNXdVWVVHULSXQ^KRPPPMPQNPO\LLK^KLLNNOZQbQRVSZPNOTNOQRP`SPSNQNfOVLQZJHIMLMOXMXSRPUTTUTU`UX\XJ_X[]]_\VXSTVUUXVVPVVZRQTVSFRQRRMMMTLOMNNHNNSVQQNW^ZPVXX\WXVVWV>pA@CbCD^AJCBBDFPEDCC^HLFEXHEDJG^GEBBVDGZDIEHXIMLfKLM^KXMNTJIRIdFEBBBC\BRAAXAA@LA`B\ACC`HXGdGDRFTIXGRHfJTL^MHQMMRP^SQTQVPMXOQQXNRORVTW\VUTTbTJQ`PbPTQPXNMLXJfGRIIG^KFFNFFEEGF`FDG\E^EIZIHEFG`IFIFJJHJ^LONRO\J\KfMSSUU\TTJT\UXTTXUPUVfW[ZZUUPSXTQNNNNKIXIHRIjIRFC\DATA`@V@=Z>Z?>P?ZA?A<@VBB@VBTA@?Z?BPA`CCRBNE@ECXGG^EVCIVFGbFKVJZLNXMLHNNLZMNZOdObNZMdPJXL^LJLJdGNJBICIREECZGAX>?@^<\?V:H8j9766b57V4J3d352T4V1L.\22T3X1Z0Z/-101^0Z3Z1T-`0..X/l../d/R1X42^0\3Z1f0`20/.X113503X324X2P324T5Z37V23`4f2`4b3P2305`347675X64b55R222`3H3213d2`1d4N.///b/`0T-V,R/+h*'))V''L'P'h'T&d$%$V#b!LX^RPVfZfXPXZVfd`ZTN H VPPZ V P \ V ^ P T f fXTZRL^bLL\R`^f^ZN^ZNZVRZVZR`XTVlTbN\XVjXVL`^NRLVRVVfXRZb\T\RLZXbVVdV^`^hT^ZVPZPdXXZbTVXN``^RbfR\T^X`^dPbfXdhdV^Nb`NLRP^TX`Z\d^N\Z^^^VbNNX^V`NdVV`V^FdTX^VPR\TXTL`F\PNRP\RXDb@fXZPT\RP`N`f`\X`X`f`RLfP\TZF\X\ZfZXTZXT`B^XVf\^hVX\Bh^VVXVZjTL^b\XVBjNZVdPXXLB^TfVJX>V``\XVT\TdVZTRX^bdVdXNbJRZNbNfbVDdZZ``ZVXTXHT^RTfVZ^ZPdVVLPRPRLTRPfNZ`PRR^\R ^ R R V Z P ` R \ b T X XPH\ZbJXLdRXP`T\^RTRV !Z$%P('T*R,)')R,V+-+--Z,+/3T111423527R79R5j97b8X:`88\57\;b97:7^9Z9310N6R253X1T42\721P/R/1X4`1>00^1/.P4/1T2\365j7?F?dD\A?^EPABFDTHZFEHHFGNNK\KRJXMNOO\QOTPXSXQbUQTdRHRbPLQPMNXUTRONbPOSTRSfLONJGDbEGDFCRECTGDH\KPJXKZIIKRMIMK\JLLNOLMNNVP\PRRVYT\]R\\^b^a]H_X\X\[][X]TVXVRWXVXVLWV[bWWPWXVVUZVROQZMRLPKXMJKNJ^LLZLNMORPMPOQP`TSXTRQZQXTQPPZTSTOSRQPSU\PSTXSV\VVWUXVPOTONMhLVIJ\HDITITGTHPHHbKKMbOOhQTOOSTSS`PRTUBU\TTVXV\UXSSPJSNZUSVHUTR`TNRQRRWURXVUVFVSPQ\Q`SQ^RTRRTLPL^NNNKPKOFPMP^TNNLRPONFQNNMJOQVPXPPINQKdLLJVMKPNLFU^UVPSXSNUfX\VX[^\WYXVXUSVZVUf[VVSbPQJUWSSSRPLPKMNMTQQ`STRTXOSTWFW\U\VRVJXVPW`TQQZTRRSTHRRNQ`RPPL\NXLNL^MZRHPVQRORURU\UPTSRSRbTRP\QMMOZK`HETHGGIJZLLJ^NKDNNJDMM`PPKZLTLJH^JNKK^JNKHTHRGFZGbFGRFXCdFA=V>=?\>RA@FXEFCBFGTD\EDGXFTDREDHEPFG`EHETIFVE`IVFGFLDFI`HFKVMMJ\JbJFIHTKRLLJFE`EC\CDXDCB^DCDCXAPANFEZGLLZH`GGEFGIIVKO\OTSdTSR\QHPjPVSQQRQNDT^UT`QTSLPPSONOMPRLKJHdGFFVI\FXHFGVEdFC^FLEDG\ERGFKFEXFFTFfJVIRJLJLXIJJNOLQRRRTUVSTULPRJSTZUUXYJZ[UTQQZNMZMKVN^JdJIHERHZBGNEPCPA^@>?\A@>>^?;T=>^=R>V>A@?VAALB@FVFTDVDDCRBXCTD`FXDTHLJI\HGJ\LVKPPPXLNTLNLNQVPONOKKKNJIRFL\EXGDCbCAf@B@NB?h''X%$J#\$!X>^PRbNHbF^V\PJTXR\TRbXZLD V N T F b N V H H  X V\HVT^R\RZVPTRBjLT`\FT^ZPdXZbZXT^X^ZJVbTb`ZJ^JV\T\TbdPPNXbNR`hR`^NlVdLddTTZ`RddPZVfTVXZ`VJVV`X`RVRdbbRVX\\R^TVRd\^NT^fTZ\TdNfbX`RJ\dZTVF\hbRX\\\\RVR`^P^TNNRb\^`VNVTPF`\RR^\VVRb`LVPPTVbZdRZXZbllZ^jZ`nfFdbjjF^Z\VP^TbXXd\Z\`d`^^`Nh^\\X\Xb`V^V^Vd`NVZf\PRVT\`JVb`XLLjZVFTXTNdPbn`PP\XNdV`PZ^rjb^`^\`TZ`VbbX^^`X\`bVP\VXVVNV^\VVR^^\Nd\TRNTVX^Zd N X` ^ ^ V L J T dP X J ^ VLVJh^fT`VRNXNNZN"!##&N&T)L*(()V+-,^+D,/V0N,P,N124T223H6b65X5X79L7T7^85^8X9T7Z76L8T79Z67f8H;V78P:793Z4V74V7N8^6775V7;6T::X9\;\;\9<^:=^9N543`010T5234Z4H4222X3/2N4/T32/V0V04442R44V648T9R@BbBA@AEZGBF`FHKITJNGXFKGNHNHQNM`MdKDTZOQR`RVORPRTQONNPRPTSPPNOPPTRNPROQKTQHNTJZH\GJLZHjEJG`BBXC\GVDDREIHHGRJTJJKPIM\OLKLXKPLJMP^RRORTQZVYbYY>]Y\]^Pb`Xb\]]Y[]X^YPW\dYXVV]TXWXV[X\VPUU\WVVTU@RjMDMfMII^IMIMVN\KNRNPNNdO^SU^T\P`Y`WFT^ONUBSfPFSQ^PZWPVRRVQRRUBRZJ[TY^VNTQSONVOfKTIIJNHIG\INEJK`IbJIHMKVKOPQQNQUZTRbSUWSUXTQZQQTNVTRQ`QQSZOHRjPXRJQTWZVUPV\SRTVTXRVWOQRdPTT^SMMTNJMNMTNORSRZO^QLMXOTMZO>MfOL\N\MNXMLTNIVNLLTLLXNLOLVNORNQQPJQN\SUPWY\XUWXVT^UXVXSLXVV@QTTQRXRFRNRbQJSZLNOXOMSOPRNSTZVRRWWTXS\TQPVVRFQTSRQTRP\SRPTPXSZQODPVNPfSXOXQRPTURUVTY\WRVUNUSRZQSTRPOTMZNGJGFDJFMIMILMNNLKLRKMMZLMROKTK^NXKNOJLPKHHGGEFETEF\GbFZC=?<<;X;Z;9::8\9=V?XAX?TDDCBD^EBTEZFHG`FFFTH`EEZFXGJG\KGFbE`FFTGXFGKHIfNHRINKTMHGGGbKHIJJIHEGXEFJEDDFCCCNCEEHHZGTHGGITIJJJZMMXONRZPOPVdQUhPOZSQPZS`PZSTPLTVRRTJSPXMMORQQN`L^LPGJG`HFEFIXHIPEGEDDT@EPJfHZGFFXI`FTGFHfKJJTHLPJ^PKZN\QQNUZVRRHWRT^TRSVTSWdX`XPWVTTRURP^RPPPMJXMLDHEE^HXEVDVANDdB?A`A@H??JAAX?>b>=`?`C??T>?CGB@TEDPCBDAhFC\JTGZFHVJ`IIRJVJKHN^OMHOOXNOZPM^MMZKXNHFFGEFFB\DGEBDC=X?R:Z<`dV\bTdTTZ^b^VbTNfff`fb^TZ^`LbZDZh^TZ\\Zh^\``Z``XX\RX^L\j\RTTFTZLJZL\JN^@VJNRTdVVXBX>bZ\fbVbjTXVL\H`VVVXdBRNbJZRNHRZfX\b``\dJbHbL\X@bRTRZT`VNLR\LXb\XR^ T T X X @ b X ^ X b T X TZV`ZJLTNXTPZV^TTNZ Xf#Z#\%^%\'V('`((`(T+Z*)*+-,^+V/Z1T2/22b434J3X4755X7\8X47D666T5\7l87^6Z9J6:D8T6P775\87`4R7\64L46X:78777Z=N;:d;CABDdEFF\FEJGHIPIHKJJ^HVM^JZLNSbP\QbPNRXURMPJRSP\MTNQXONVR`OP\T^VVRTVQfQ\Q@NMMLIFGDVETDTBB\D^EXEEVFJGOVOHKGFJ^OPON^MLXO^PMRRPPRPQRZP\ZZVZN^ZT^T^^\Z`[YWW\dYWZD\HZZY[Z^Y`ZYRYXU^\RTXSRURVQPQLMTLZIZINLI`JI\IbKXPLMZORTSXSQSJRSRRR`RT\QO^VRVOVVXNUTRSRSTS^TTV\\XTPQXNMN`JIJPJGIRFJH\GJLKNLZKKJKJNR\UbQQSULWTRUPVLW\SXWQXQTOLQRPbRMOQ^RQUThVVRZTTRWNRVWUSVXLUTQ\QUXRXRRPVOZPLQXPMPROORMNVUNPNPZNNLZLNLM^NXMRNPPLVMjN\OOdMJLKFIROPhQPPPQSXR^YTVT`UVRXRRV\UVDYVQPPVZWNTQVUP^NS^MNPTOTPTMQMRHPJTXTUUZURVVTVNQRQ^PLRTORXRSTRPRRUFRJPRQQSdSSTRQVUXLZ[Y[XLUTURSRQNKL`LHIFHKGKKPMJZJ@MdKNIMMVL^M^N^L\NLTNPMJNKMJKPGVGECjFEXE>ANDAPA=;:Z;\=\:?@@HBVC`AEHVDZD\GJEEHGXHGPIEbDDdDFfH^HVHEbGHJTJG^HZLbIKN\HHFGVEHLGHJKKZKNIVITGVFF@ICVIBFEPDXCTCHFTCHGJLK^MHPI\MHLXMZQ^RRRVJPSQ^RRJRUSSSZQVTTPRLUQQ\PLTQ`QNPTNRQO^KJJFGNIHHVMHHZFENHELDPBEDTF^GGLFGF^EHKGJIVJbIZHdLJNOMZQXPPQTSRPbTRR^URTXUW^UPRRT`QQOPQZKOONKPKLbGNGFFCBAA@P<>P@ZAh?@@A@BZ>P>n?V>?@>AbCAd@RCFLCC>DXFBTDCDJH>JEIHZKPIZOTMPMNFPZOTPKNLTNVPPRSK`M>LXKIGZKFF^DRBBXCR?B@@>@9;b2`43P0^31T-.-,1T1^//-V0..00.R.P/^1H11N1/200Z1R1X1/01^3\4N22/4Z011X3X14F4b53X7Z4T33112^2V8474b4J6662P4L6Z36350V1/V1`0/Z2/0/.\0-+,*V--Z*'F(('`'(d&$Z$$P#\"  TfPTXXX^JTbTN^JVTLXR ` Z V N b R b L L Z^Pb\TPDZXVNbTZT^R\PXHX\ZbVXVXVTTZ^T^J\^fJVP\\TLV`Tb`V`VVd^Z^\lR\XdXVTLT`Td^`XTVdXZfVP`fHTTVZZfVH`T\dR`dbLZTXRhTRXZVZ`TjZhfT`fHFdP`TV^V\^LbLZ\VNbZTbT\ZZ^dR\PZhTX`PT\ZT`L^LJfTZT\NTLNRPd`Vhbp``XdNZ\bRd\bZ^b`bXdbZnP``R^RdH\^XLPbVVZV@f^TT`X`VJPdZVT\PV`HdVXXLf^dZ`PZXXXX\^PZTLZ^F^fP\\J`RRbhVd\`PZVXXXVZb^\HT\\NHLZZVnL`VPPTXXZT`\ T T  T f R X X V N ` P X \bXH`N^NT\\VXJZXR`ZRX ^#P#N&&J&L'T)^((),+,*V/,X-H.V-V10324Z66b7P84V7R567d;5\67T54388Z:P79b8^8j759T6X64d4796T7765L766^:89>=V:P7:^;R75\1R22\5051N2T4/2b1L2h23P2N203\2R1^42Z342\42\66Z7P87:J::=@>dCAA^C`HXGEFVIGdJLGGJLGdJHJTLJONIKPONDSSRVPQNVQHRZQFRNNjNPXRNhNTQQWNRZVNQ\QZPNKZPVJ^HD`EJFRB?CDG\CTHEERIGMLMRNJIONVOL>PVPONVTMTPLO\TTVdZ[[\\^^RZXZ[XZZ[\YXd[J^Y[V[\FXV^\Y]\Z[YNVNW\UZWhWSTOTPXNPON^I\MbMFKfMZLVKJJRMXOLONRdSXS^VZUXR`RTOXQhROhRdQTXQNTSORUVU^WVNS[RVTVTRVNKIXJHZG\KTJJJLHHHGdJKKKKOZNN^QPULTTSRSfRSZRRSVVQQQ^RP`NS\SONTPOQR^PTVlQJTSRR\W^VUUTYVUNURUVTdSSTZSPNO\PNPPZNMMOZOXMNQ\NZNTNIJKTMLNHRKKMNLNOOLZNZOOVQ\P\STRPPQ`SVRSPT^TSUTXTYNUTUVTTUZTTWRRZTdPRPTNfMNZQOPVSTTTPNRPPTTRQOXSDYTZTUR\R\QXURUXRZUZRTSLTS\UTSUXRVUTYVV\VVUTYTJZX\YVXVXLXT^VOVNMHORNNJKbHGHFGKIJKLINXNbKLKJTMIdPINRNZKNLZOXIPXJRIDZDLCNFDCAAT?>X;^:R:H9R;Z;9\=\>fRAR@Z?@N>L>?b=RBC>@L=N>^=@T?Z>?HDZ@AB`BANF\DTCFHVFHKDLZON^KXHVI^KLJLJOMLLPLNQTPNJ\NZRMJFbIF`FRED`CB@JED>?Z<`0N0.P.^.@/b-,T0/1Z110V1.L0`2T3/.1/-/-1H21<3R314N23R35d2J724n5205V3`4T2Z64542L6V45T2X242222X2L01R122f0b-H2.Z/\.Z,\,*+),+&&H(d'&`&%$""P$ T Z^Z`JV`dRZ^hXDR` LJPX X NN d ` \ L V \ b L P ^ \^ VFZL`dV\\`ZRB\XV^\fdTbZTN^R^dlVZLbRVJ^DTV^hRbZJ^Rf^VP^VdjZLd\bVPbdbH`hbTXPb^VXZ^`ZV^``^PDTX\^VRThJV\VRXRX^ZPXZd``^dV^XfV^\fXRb\ZXbL^V``PXTT`^^LLP\djR\bPVZXTN^Pd\b`ZRdHV\TXN^RR`HjRZP@JR^RX^V`TL\XlbZXZ\``X`ZdbTR^^^^lXV^j`ZbbDX\ZXZTN`^T\XLZ`L`ZfXZRR^DT`\^VLVZNP^XTNL^\RPT`XV\HjhTZRXZVT`VVZ`V\TVdbJT`VRTZVXdPXTXbR\RPTVhRL\RfJ\TVDPXZL\\PVRRNR\>^R ` D R \ b T \ Z B F d LFXF\HLbbJPZVN"`#$^$%b'X%%*R*X'X*+,Z+T+\-\1F1T-N.2L/0R36`78T643X3\6775\9<75T77X4j:6R68Z8;P7766>:V7R687X76\687`:P95*7;P?X<<<:9b:776l1Z2V21`20T0V201^0R02h21P2`13T4Z31/V543>62T876\8\9T8f9N98V=P@L@>RA^ABBFEPHHFH\GGIIPH`MTMINMRMVJPN^NbRUQOS\SPRTPVNR`OMSKRN\QP`PBQRP^QXSZP\PbOBOKNIH\HEXB`K@FAbDAXEETFZJHJJLJM`JTKbMPPKRNDMPNMLTTXPTSPQWJ\N\NXZ^\ZVYYPZYJ[`Z`XV[YV\VZX]]T\\ZPZV\B`ZXYRXRWVYVT`SNPLLPXNONhIRNMJLKJ\MIPMZMMLPXSOVUR^UFSUPTRVTPRUPUQXRRTQSVTVUVNYUPTZRYTXJUSPLOLPXLTN^MIVMLKXJJIJ`MEHHIITLKLJJJbMXRRZPR^SJYRSZTRUTSSNTTZUXTVRNRP`NLMJNOVSOXFV\YSNR^WXQTZWPWTV\WWUXRTTVXXUUVRPQbQXN^NNZNNNOZNP^MZQMNFJZLLLVKPLJININLPMONOMPGJJL6LN\QOP@QQQ^PQXSV`RNTLTTTRTVJVTTQSXVTWZRQSLSVSTQLPFSOJTUM`SMfSRHOROLQQRNS`RDTNSPTTUQSdRT^UZRFV`UdUUU\WZWYZ^XLZWXVYY^P^\\XYRLWUTV^S^SONZRVMZOKdJKVIJHINHlLNIJJVNDMLPZMPJTMRLMNVLKRJLhLXNL^KGVEBBNBD\@?P?X;;N;:;Z;:;;@b@T?V=@XB??`>PA?L?D^@ZAV===tA`?@bBTARBFBRDXDXANE>PE^H^IJJ^GD^GHKLJRIHIIM\PTPQPPOTQPLLJOTOKJDCLGHTFHBnE\ADZA@>>X>:X=Z:Z9H6\:V8^:V:`8V747h53P3412000^../V.X/h2N0--.*-V,,b1/N0R43^/Z0P02/00/H2V00.R10T1R2X4P2/N0023V344j63X2T3H2^2V5Z4P55X552^4N535R51V3b243b2V4`3.R./\/f/N12Z0/.T,,h-h+*+V)*'^)'V($%$Z$b##! Z \d^T`RZXZZ^hRZ\Vd^ VH V N ` ^ T X V ^ hDfXVNbdVbTX\^bb\TlRJXVTP^XXdZTV`bN\NL^h^TXh^bXPZb\VV`^TRVVNVT\bVLHfXVLZZVVLdVXVXjVRPL^`\VVXTRdRXd^TT`XRPXX`X`VX`ZXNfXd^b^ZTX\^RXVZR^VTZPXFbNbNTLRX`H`^TJTLZPR\VZRJZTLdRNV\VVRVN\d`Vbh^hTXVLTVVVbLRXZTb\VdZVT`X^^XfNVXPX^ZX\ZV`bjXfPbZVLVh\ZVXbN^N`TdbTTVRTRRh\\^ZVVbVPXVPHVRX\bRbZVdbfXR`J\PNb\^fTR\RdTfNdbPXZ^NbTd\VXZ\lZP`TTTXNFVTZJXZPZVTZTf T Z R ^ R T X D ZX Z T VLbVTPn^bdZ^PLNZR\`Rf ^NV!"#^#P$'R('^)+^*Z*J,)+^-`/L/.Z0X0Z/4N13T64P5`5536Z8B7^6h8>68^4775X66H67X87X6L86X779^9R966R7V8X86:\8\87\:;<`=;:V>8\8^31V4j3b222^1./0/R024/3X2224d10N4\34b32485b3R:Z8V:<:T<T\SSSUP\TQOXTTQPOQORTNROTRNQPMUTRTVTPVTTURVVRTSVRHTTQFTTWRNU]UVUVN[BZZYY^XVUdXY`\PZYXYLZVP[WURTXTXQXO\QMMZLLJKLfKPNHPI\MHXIJNIJVIJJMdKJZKLPJKLMOKVMLFGF`ETD^EC>^>Z?\=^=Z:V=d9\::=Z>X?B?^CP>>??=XAbACA\DCVHfEFGTJI`L\L\JLLM^KNKBGF\FEZE\ENGG^J\LKGRGbMMK>KJLIPK\G\JJIHTFPGJIbFIJKGLIDGZFDPCREXFFPDDLGXDLFGKdNRQPQPPTSPNPTS^PZLXMK\KTORVQSTWUY^SLUTXURHRTQRSXNNLLKJI^KJHbFFERHFCBHLDVCdHHLGF`FGEDGFHGXHH\H^HVJRNRKVLNLRNNOThROLUVW`WVVWjXHYYdVVdRdPQZQSRRRTNNVML`KIVGDbGGDXCZB@XBC@=\@X@AX>T?A?=T>`<\=R>J>VAB\FCDTDLHFDHCHFVJRJJHIMRMNPXPP`RVM\LLNJ`JPMbMMG^GNIXFDACLD`A?^@\>n>4=^<<:T778N7V9Z6V6P6h4T611Z1P2R3\3P0N0`/T/D/0^.R.-j1R/-/^,+*,\.00^32./`01100/Z3\2d/03P1R245X1D2R3Z2N2/X12R1V2X42T5Z4444247314X33N7\7R630V1//031/\0T3^/P1T/-/,V,T,N.,+,(X(*(&`))%\$F&h#R"#^!Z\RTP\J^XVPZVVPbTd` \ V` T ^ h T L h X X\PLZXRJX`bVJRdLfVNTXN`fRd^^LVdL^fJVNbP\LLV\BRV``XbLZPV^fbbTfJ^Z^\jXXTXHRRL\R`PZRVRX^bXX^`^X\bRZVX\\Z\`T`TdZTX^hdH\PddDZTfbbdV\\TL^T`P\\XRV^XVXT`R^V^bT\D`^TZVVVhPZR`R\`Z`^ZH^RZNXNHjX^hhlbbRXLfTbZV\ZbTRnfRd`jXVZT`ZbZ\RXZLTVX\J\`Z^V^PX^^^\Jd^f^^\`X^L^VF`bT^hHN\XPdbJ`ZfTTVPZbJXBVhVNNb^\XPL\`V^\JRZN^LN\ZZRRXNXT^\N\`^^JbpbVTJTdXVXRT\ P J N F J L R T h X LTD^LL`NNR^TN`XTF\\\ V!!N#$L'$('((Z)P*T,F,+0,H0./1T2J357N76596R8N7X85J5^66L6P67544\8588999X8\;T:J87Z677\:T787N78T8V;:89<;X;`8N98\512D1X4/\10d3V401N-R20^44311434^6N35d6544^7^7X679T;=J;^;;T=C^?@DRDFGFPGNHHVILVIKTMRGPHZFLKNNLXOPTUSRQQZONNRMOM^M`JNKMPONXNNPS^PLRLOMbKZMKPLK`A\DCCBDRFRFZGXDFDRIHXIJGZKJLRMXJ\MMVMR4MfLSTRTRTYWWR^R__JZ^XYZWXXVXXTXUVXTYLWWVXZXYJYPYZXWYX]XVXVPYWLTSSOQPLOLNZRMdNK^NLKXNIHLTLXPNMPPTQNVdRRWUQTTSZO^RRPTZOfRXPQSU`VbVTSPTNJOR`RVRLLTONTKTIKH\I@JETIFJECHVKGPIH`ORLbJZNJOZSROPVTPSLOSRQTPRRMLLPLJPZMXNTOTTT\SZUSUUDT\YTXX_PXPZJVVRYTXZYZUURXDTbXQP^POLPDNhMTNNNM`LZKIJKM\J\KRLH`JVIPJ`KLNNMZL\LdMDLPQP^RPTZRPXQVSPPSPXSZRU`UUS\RXQPdMNbQRSTPUbRXSRPVMS`SZSOQMPVSTQR^RQTPV6UfUZYVVTUTWXVWXTdVYXVXZWX[W\XR[R]Z]ZPWZWJYTZX]PZ\RWRXVLVPXSTQPOZPXNROVSNNNMKXNGHHIZJRIVLDGGKVIIMMMbNVK^LKZMMMZKJK\FDBXAb?>=N=>=P=;;?:L??>`?CCV@@@NAATDZCHGFZHXDLGHfIHKLNZLRLIJIDHVCDbDFTGPJZH\ITKLIJPJKVKTK\KXHJXJ^HE`CbFBERIEVEDGXHGVGGNEZEVEDCEZKHHFDVF`EFMLOZROXSVTXPPTU\ROXNOOLMdNVORZ\USDWYTLT^TVTRSVSZROLQ^NLJHIILHKTLFLbHPFLC^GCDXECVDD^FNGHHKZIPG`GNELCbDZFIKIHZGJJHKHMKKZLRKOLQQVXTZT\UTSUVXbW`XNW`TRULRP6S`NRbOQKLMVLITIXHE`CFTEEXB\CPDfB^C?\?AXBL>@>TANA\A?J@Z?V@TA>@ZA@BEFXIFXGRKF^EVEFHDIMPKKTLLJJXLNOTKRVPNN\MJjKKPLKI^HDGNEEZDERCP?>>`<@@n<^:X9:J8:7N7764J844X46`644V00/1P/D.P0-Z0.0`0V-V-X0^+,T0T./1J20/Z01Z3T///\20N2,2/T1R2R4L532T52V13J46b2V4^042256N7X5Z5R42Z33^123^3R21..0/1f/L10`.^/N1V0V/\-L/.`,P-X,-*'+D*^*()T(%$N""" ` TZZVNTVdVRPfJVTP P R T Z ^ Z X V \  T TTd`\XV^`TXRJ^`PH\XZdLbV^TXTbX`TLPXTN\`NRJNP^TZX^ZZJ^^T\`Z\RR`V^^nTZVdPJ`Z\R^TRPNRX^HT^`RdZXZ^T\H^VbnVfT`VZPVb\ZbH^bNRdTVHVV^ZZJf\P^`NbLDbZTXNlVRbHTXN\T\bPPTdZVNXPRXZVR`PNP\NP^P``VZdbbX^jXbffhXZd^R`\b^nb\Vb`HR\dXXTrf`hP^XVdNLTZd\dTVVh`H\RdZpPVZLXd^^ZZ\`dLLhT^Rb`TjRRdX`XRVFZpVRdZZdJVVN\VVVhXN\TdPNfXVRNTbhTfPTH`\F`LhVfZTZ^XL X b T R V L \ V X ` XfV^ ^XXRH`VfP^dZ!L !!R#$&'&\&)D)+Z*P.,/,.T0r/H1002f4b4V668V53N7^76P68\7455`755`8V7876H;h9X979d8d99X8L76T85R757897\8D8T8J<;R;:5b4h5V513P04L13L./22-021R6Z1R02^3^52X3V4D5^42@6`5L6X789^:;R;\:X:V?R=?CVCBCHBEGHEHK\HTLGFJGHJ`HNNXMMVL\OZOXRRRXRXRRPPLMLFZMPXUjONQOQ\QTUOXMMNMPLK`L\KbGCEEJGCIJHZHRD`FZCXFNI\JVHNNKNKMbKKLJKMVOLOPUSV^UVZ`Z[_]`ZZV\XX^YV\T[\WRW\VVZVLWUWWVVVPXWW:UTRUJZQNRTONZPNNKOMMPKNLbM`KTLMLMbNPROOUSXSZSPU\T@TOSQJQRPRbQ@R\Q\QHSTSJTTVQ\OXQTQ`QOJQZNfNZSPhQKXMVJRIXFKGDTFFZHFRHGNJLM`KZLNVMTNPPSPVVbTPRPQPXP`RLQOPRKPLMMNPNNQPROTVZXXNVU\XXYWX\YWRZVZTWVZXWLS^MTORNLHQNVNVOMTK^IPPMNN@INMLLVJTNTI^FbFVILNILMZKZMKOZOMNTRPPPONUVMRdQXRRRVdQ\NVQXOJPXN`LMLQVSS^R\ONOQXSZPVQRRORPXNNXTZQRHQPNRTRPLSTNTNWWU\W\TRLT`XHXNVRYTXTZZ`[YZ[PZPYX]RXYRVXZV\VTZVVSPN\QMZQNRP^NLBLMbLILJLINJHXEEGRH`IJLN^KHLLRLVLQZLTMKZIGD@DT@V?\?==ZZC\A=X??=N?X?b?P=R>^;T@>@BXAPAFBFEGHXGH\HEXIZIPJKTGIIKNLHJ`KROTMdK^JKTMMVIXITGDXG\DEbDBBL>A>=JA>LAX<>:T:\:\968N64Z5B4532Z2H122.R.^0X-.R01N0T1T0Z/^.\0,P-V/+L.V.h1Z1Z00`1b10V1X0\00L0/L11420101^0111P2j32152:4464X3T5P4354\3\44d2^3X4/`3/0X0/N1.V/b/.T//R0^/D1V.-.,-**(((\''L'%:&^&$!! !Z!lR\`VRNVbVTXdFZZ`d\V V Z V ` d X NdT\XXZVLdbHbX\\\TT^\^j^hZVb\^TP^`\L^NDd`LZRbP`^fPZbHNdNThZVfZX^fTVJb`Xh\bZV^\``T^\^VXRhTX`dXX\F`NP6\\ZPZRXPh^VXXJ^Z^PVZNZ\VRXZXVpVjZ`bJbLPZXb\`TVV^VVRZ`N\X`NR\Zb^\XPRV^^TdXVbXdT`VXT^ZZ`X^^TnXh`^ZlXdhZRZR\^fNZ@VP^T\jJRRRXPf\bX`dZVVJf^V\X`R^^VXDR`Z\VHbfRVfJTPVNXN^L^\PVPTTTD`ZXPTV\N\`VfR`ZZPRZ`RZ^^XHbVZLNZRXVXT^D`V\\TZHRZXFXddX l ` ^ X X J Z V X TP` RTLRNNfLP````H PbP #\"J%#$&Z'P''T,-N,T-,j..H//X0R2J/1f33J49N557P5,7R7R767f6364H4\6:7N67L867:V9799f8;V:587`598T7788Z:L:7P8Z>9:X547R53\3\21/T1\0111J1Z1216X34Z0R765312`6245487P87:6:R9XXA@P@@ZAP>FAJBbBBJFCBZDAXEHBbCBHCNEbGILHIVHFGHLJXNJLGHbJHHFGEPETFKZHIGHLfLIIHFZJIGG\HGL`ILNLZMVKVO\NnLONOVSVRVURSTHUPYXXRWlVdVVWTbSNQVRNNMKZIGHF\GZFLC\DDbC\CAAdBN>=>D>@=P>=T>=?=\>=T=V>DC?APATCAHCPCRERFTIFH^HKbG\JdLVMLRLJJFKXJJQPMJPO\LXQIHN^OKHIVGFfCEPABbDVCP@Fd?Z?T;:;J::\;8P96^785V4P3Z4\5R04V/2.X.00.-.R-,-P/V/-R/Z+-R.30N3P1`0Z0./20X3V0/T/00P1Z0N2/3L4R3314T54R641J33\1V1X3Z3^220Z4V640P3\3/1X3X4R3Z1/Z3V2N0/Z/21`0V11L//R.R.--Z-L-L+Z,R(+((L)V(%$J%#T" X! R!XTXZP\X^P\LXLbV\dZdH^ N ` ` T R L l N ` Z R \ H x V TTPXhDJP^`JNDdXNZXXP^DTV^JR:`VR\THV\T^PVNTXZVPnPZNZRb`dPXbZT\XPTRN\\XZXNRXV^XTV^ZfnF`NZV\ZVDJT\RX\b^V^XZTb\VT\^@\Z\\XPbVZbRPVVHN\PPX^RZ\VfRT`LbLPXZ^HZR\N>PJ^FR`PXTTTX\PPdj`ZL^dnTHR`jVfVVTdd^^^XhXnlZPfNZbTPZbbXZ^T`dZT\\Z\bXXfbPHTPZPPZTbf\fFXF^VfN^VNZ`\RRZ^b\NjV`J`XXRDpFXbJL^\RfXZLRN\\bPR^ZR^N^\bZTZ^fR\R\\VT\\LdVZZ`XZ\ZTVd\bDX  N \ R Z T Z N X T TZ ^Xd^\XXZ`bLLXR fT!d$T"$$%\('()b+\,X,P++--01310R02V65b6\:696T;6P99L6\4445L8d7X7d7`;7R887Z99Z:9F:7^<\9X6^5\8\6D8:V9;79L:R7f:9^;^666f5^5130302\1\0/L/1b0/L0Z5V33038b32643Z4\44^4`6V7\77T88:9<=L?f?ZBACfFRFEZEXFHHHTH\GG`HLKGHN^PONMNO^SPPOSVSNPPKRLXGKOXOZPXOQJORPLJJIdMGRHVHHFFEC`DCDFFECJFTFbFXIbHHG^JXJZNfJHN\KLPMM\PLPLRTMLNhRJUYZVTW^XLX_\YVNWTWZ^UWWTUVWZXUXZYHZ\YXUXYXUPULObSLOdQTOUOXOTO`JXLLIRJOMMVOPOPZQPOOTRTRTSPVVTVRRP`TSSJTVQTTNPQQTVTPO\PSMQXNZNbJTOKMMVOXKVNDGGJRGJH`IFbKNKKLMNSVLZOOXSNWPP`ULRVPTQRTNXO^ORFPPP`MdLXRLLLK\JHMQpQNSRQXVTUVZXZYXWXYRVZVWVTXUSQSPNMLPORPZPNLjLVLKKKVJM\KKJKIH\JLNL\KTMZMKZMMPbNXLROVNNXPRRROPMNLMRLVNLTROSXQ\NZPXL\PVTSTFPPXNLPZORRPbQMOVNRZMRNdRFPXRSROTdWNTOZRhS`QNQQVSVTXYV^ZW[YTX`WTWWXYTUPTSVRZbUT`ZTZUUUSXRPPR^SQZPJTKJJLVI^NHKJG`?T?`@R>T=>@^>>>?<>A@@@VAEZGGGDHDdGF^INHXKJLJKIKJL:NXMKDMNKIPK^NVONNLGFTJbFECHDBX@AC?RA`<>988786F7V6X5R320/L1V4X2J0.3V412H0N2d3243\447/25X4H2d44d4V869J8`:R7R:P;;VVNFRSPUTNW\WJUMOVSRP^PNMXNQ\RbRNNQhMLdNPOfMRMXKIRIVIHE\LGJ\IZPKfGL\MMXKQSSSJRNRhTSRTRNTRSZQSR\ONMVNNKTNfM`OLNN\LJQRRPRTTWT[WXVYTWYTU[SDVVTPRXRPP^PXNM`N\NJKLL^KNbNTMKMLNIIILFOLPbMLHIVKfNLXNTKPJJJTOLMNM\PZN\QRMNIKGRMbKTOZQOVQXSPT\TZRZU\ZUPHS^UMbLVPRNQVO\JOMPbNFTROR^RNPJPfRNJQNRLQSVTTZ[^UPUW\UhVUZWVUZXUSTTVPRSZTSLVQJRRR\VPNRVMNMPM`OTKPM\KJJFbFNHZKFEPEF^GE\GILNMMNMNOXJTKJKTJFZJbDEXDA`D@@XB^BT?DLBAD^HEFE^FDNFLFE^FDHbFDCEHMEJTLZJRGHHK^HJ^IJI^KXKI`H\IJLIDLJMINIKTFRIZI\GHJKRJZJGECB>NCRB\BBVCGPIIHGTJJJJKKNKLODNPORMVQNPPVNQXRROR^OFTPSRTTTJQNHRTRQS`TTRU^O`QdPPVRXNOOITMZK`GFF^JJFGCB\GDDPDZGNE\EEDVFRD^DZFJJHFJ\IJJRKOVJ^KPNNZPQHSjRFQRTRV\SPV^XXXU^WRXUSSTURS\PNNVPN`LbHHVJEB>DBRCZBVA@`?R?^>NAf=\>?;>@?T>N@X>>@JAP@D\C`A`BBTADPFZEG\GCIILLMGRHJ\JdJMGK>LbMJ\KKhJLKLOXI\HXHFdFTDbC\D^DD@C>@??T>f;:=99^?R65884476J4T4L2^30T.N..h1N0\/X1-L+\-R/d+\01T/b0b-,/Z,-B-.0X1/T0N0V001T1`0`0F/0T/01/X//1V1J13V022224N44R4R4L343b2443X22V4123003`/P2V2-J1V01L0-X.^10^0T0N-,X,,\.R-,P('d)D)'`'&^#$"N$^` !d^\HXhZbP``T^HPbZ T VV T H d L ^ f X P ` TdP^fXjZJHTZb`TPTP^VF^TVhffX\^Vb\f^bPR^\\`hPXfZZV`RP\VT\^^VdPXPbZ`\R\^N\XZ`V^V`ZRZd`Z`TdbPXXTTfdXRPb\fP^`dTX`\VPbTbLNZHX^hX^^ZhpT^ZXZhLXZRTVZTdX`hPT^ZdVNZDLZVX\PTfJfZ\\VRd^^dL`^^``nhZVR^Rbdbb^\h\^VXRVZ\^T`bZVZRdjbXZ^PXXjFV^TdX^Nl`^dTVd``PfFhPRrR^`V\LfTXPf^VjRHXZXLlbZfR^\JTdNRR`\PXVBPddbZVVd`bDVPd^V^bTfRRVPRXX\\\ZfDTPbVXd T V d T X Z \ P T ^ FX^djfLZ\BHTJRPV<XZVR !#$#&$(b*,)`,--.-,-0110X355N4L33T6:@9;N58P3\5534L479j67\7F9h8^799X9:9h9V;Z:5d9674T87\7`9@6;;X;8\8Z7T7^5Z6\76V5N43D02110T21f1^4R1102433R4J31/2N33D3X244435b66Z9X;8;^>L=Cb@VAXBEDBRBF\GH^HNGEJZJII^JMLLLNPdNOTP^P^S^RPNPNKZGLGXLMVOQPTMXKdOPKMLMKKPKKRJRIFXGBJEZFVETCCTDLG`D\G\HfDNFKKKIJIZNPMIDHLPTQRPNOOPQQRUbT^TjXWPZDY[`YUFVZWZYY^WPVRVUHW\UVL^NV`TTUTQQ`PZKRNPPMQNQMT\OPN`L^LJQ\KJLKVQMRPNUbPSRQdS\UHSTTV\X`UTXV^ROhUbTZS`VNWXR^>=>T?HA<`??;b?T>@>RA?V@DZBJCDCNCDGFDGFFIHI`ELHLHLKXJDJ`NP`NTLbOIKQJJHKRFHVGGEFEFEEDCPAA=A;;N:N;6V9PV9T:;T::7R8R8<^7V6455X65@:b8D;Z;;976T65T9N6^6J56\52062Z3R11X61V1D41\3133\75X1P3V45V5P1\1X3V53326d8N5L99\A?R=`AF@LA@^ED\GFVCbFID\I^FGBJKRII`L\LTPPNMNNO^M`QNNM\LTMJJFHLVHhJHTL PPRFKLKOVKTJLbLRKLXNTFHIHJFFbE\DEDRGFGEGFNIKDKKJKTMZK\LXLMQXOMJNMM\TPVRW`XZjY]V\]YYJ[WX^W^ZVRVZJVWX^Z^X\QSQ\PLTQNNNMPPNLQNZSTQZQMZMXIJLMXQXRFO\ONQVTTSSSRSWWWYYRSfTLTRSSbVXRQPTPVQNTRSNMZQZLPLOZMNLNZQSLhO\KZLIGbFPMfIJNMbOXPOM`OZPRTTLUXOQQBRVRRTdTRS\PPNFOL\LJKLNHIJTJROROPMPXOTSVNQfQPRRTXV^UXWURZUJRQPPNRSPRBMQOMMQMML\KL`LRMVN`LMTMMPNPLVOMVLIMNNNMBKTKTMRJMTMOMROLNJMKKLNOLPOHP^RXRTDPXPSTRVYPPNTOHMONO:MOLLMMMPRNOTPdM@KLFLQNZOTNVOVQQFT`TdSTQbQHPXP\PLS`PQfPVROLTRTOPNOSdQPPNOOTP\RVNLLNMMJLMXIKHJLGIJGIHDDG\KLEfFNRKKILMNLXKVITFPHDHFC\BNDCBNEFEELF:HDDXLFDBFHLIIRGTJKZLHGETH`IVJIfNJMJFFGHFXKILNMKJXKHJIHLfKKVKZJZMJHKPIZGIDLFLGTGLDC\BVAD?APFDEJRIZIVGHHEHGVGH\KNNLXNPRONSS`NNOOTQN^NVPRXUUNTPT\TRTRSUTZURQZUSLRXRTNMIINJLIDbGRDEXF^GND`DB^FLG\DFFlCEDXCHXG\HJVJXJRHIHdIXKDKMJRLN\MVOOP`OOSTPV\XFWVWX\VXUSTST\ROMXPRPLJ`LH^IRIEFZBZBZ@LAHCF>?>=VC==>?BV?Z;;@P:<==T>@>BCdIB\FREJGFVIHEFFGLIF^HG^HIINMJJLNN\KMJJLXJNJFjHZHEPGNF\EB^EDLBRA@A@=d;X;;Z9;:b;T87`7R76J5b62\5V501/.J-/H/.b1X-.^,H,R+`-Z1^2R..X.L/-,.+X.V-Z/\0-P/d//T3b21`1..J/\--T/..0R02`4V3N1j34R25\3X23\4R234L4421\215^1X3Z42/X1^0-X0/N0-/0.0/,P/V,R.,)-*d(V**N((^'P'L&$#T&"^!d!V ZRVXTPdPPtTfJP\T\N`XX`XX j B b L J X \ l ` dTTdb\PVNVVfNJXNdPdjV\VHhRRXXPZXRXbbZVJXVT\`P`VdPVXVVXT^Lpd^ZZ\ZTT`XX^^JddNTPRPPLRbfXZTZT\PRTPZ^PbTN`XZVV\Xb\R`fVT\R\XhTNZb^b\\`XV@T\`ZX\jbHZZHXX^XNVZ\VZ`RX\`PXHVP`PVTV^jhjZl^hV^hff\LdX^bZ^\X^PZZZVn^\h^P^JPXZ`d``jlLZ\PXb^^jJXbhP\bd\\lfTfV`LV\NLRPTbf>^RZX$V\XXbTTLVTRNPVRNlTXVNdVLXdPV``Z``PRP`PJ^XLXdZ^^Nd^VRVVR\`Z\VbXNPfTbN^ddPRVL^ZJ@ZZ X Z f J V b L b r P T b HbXb\b\X`TN`XTZd^! $#$$T'*(,R*+,^.Z0,^.P-.2Z3/\0\0N346R5\57X5J7R7L5V75X52`835J54678\:\88\>798T:6\7b;H9T6N5b6R75F587V9X;f<88547:6P7`4574Z00T23F22b3^35Z5H3Z4041R2X1043N2T2d32X2N4P34T1T38486;>^>@?dDdCDC`DETCTCDZFHEGLIFHILOPNPLdPNRONFOMPKMMJ\JLfKXHZNKJMLDKJKL^NQPPJNJZKIIPFHHID\EfBCGTHEI`EFTENHZFHJXITKMPIJKKLLONORMVP\NPDRTU\RXXFW[[T\[JYbUY^[LT]^W^WTVWVVZTRRSXQPPZM\N\OTQ^OPHMPKPPXLJNbPRNOLIPJMTMXOQNOTP^PO`UhSSnTFTTVXYUVXVTWPTRYSSUXTdQSTTTSRQQNOO\PPNLNPNPKNNbMMLVJ^KbLFGJKOLNLLM`MhMPMNPQPVNVOPPRPPMOXNMJTdNLMZMHNLKZKXMRORPLNMLQQZRPSJUSNYZZVXW\dY\XURUQO\QSbSSQRPNMTObMMJOTINLZL^QNdMTOLZMVMOTLXKKJKKJJ^MLIJMOOXQRM^JNRMMPMPXKPLVJDLIPMPVRNWQTTOSNOHQUNRBRXVnSPPPBOVMMJH^MZMKKdQMRMRMKKLZKKLOVOPNMRQNRT`PNRXOZPR^NOQPPRRMNPMTN\RVPRPVQOMZQLXMbIJJKIKPKRJIKGHXHH^IFLHPIHGZGIZHILILJJE^EFGPFGRDDVDACDBEGHKZHHFIdGlFGNGDJJFIILPMH>>`>d>T>ATBJ==;P<==@DA>R=:7\:7P;6X4R5Z9Z7032\3X0Z0^/.N/0X-`/R.-H-,,L..-P0.0..T,V-R-N,.-/,X1X./T0X1X3d/b0..P-V0T0Z110L212d2`4X5443Z6P253^3X1R6631314\6P4R2F3Z0X/T10.Z//1R5.0P1.0/.f.P,H-T**V,+Z*V*'&h*H'Z&^'$N$P%X#!^ "R RXVbJP@XVZ\h^\VVPH\^^^\ ` N R \ \ L \ > dbVTVZ`ZTd`XR\^^^T`ZTN\d\F\bV^XXXNTVXZJ\^NNPVJX\RHXhX^@ZLJbVXZTXh\Jj``T^PXfLdZTJR`VVZRVVVjNbZfVdXXNV\fVTXL``X^\^V^dRH^\R`fdJVX`VTL`fRXL^V^JPfRZXRbZLTTfpdJrJpZHTRX\\bXbPX^`Thf^Z^`bH`VVhf^XTbNTVVh\`ZbR\^TPNfdZ``bLVD\X\XXbTP*PhfXZ^T``ZZ^dVbXhFfVZPZVJLZDlVp`T`NTJTPn^dL`ZPf^T\XVj\bXXPTXZJX`RbZPTVbVhXZ^\PNZTTXNVJVRNFRZVFNXXX\NVPZbNTT X Z V V \ X \V T T \R`X^^RVHb^RPZLR LVXb!Z!"`$&P&Z**^-L+d-R.X./d/,0V/,42^2L2X222D53R6R8V889\5`761P33N6534897T9Z9R8V9::L8T8T9Z8X9N8565\479N8R6N;:b9Z9589D7:d:5N422331B4^3X23b2\2L72X2Z30V5`3F243R5X434R4432T6^3L54H7X7J>Z;;;>=BdAARDCI@FdEGPEGVFPHNJZJK\KLXLROPPRLTRZLVML\LKZLIPLHINJNLLZKKMMKRMJQO`NKKGHVL\GhFLGdFZBLENADDFTEB\GEREJHJVIDKHRKJINPPOPNPLMNOQPORTUVR[\YWBYVNWZXTZZWY\XZWRUYQVOMPPPRPVRZSOPRNPP`SQRMRM^MHJKOMdMMSRP^QSQRUMbL\LIIIITKNLMLIJFVHFFDRDXCRGDNCRCb?@L?@`BEFTFJTJI`JEZHHEJ`JTPNPLRQPRURU`SRObOSQdQTQRRS^TRRVRQUdUNUPSTUVUZUSQPPR^LJHJKJJTHDFFC^DENFCB`DDBPCRC`DPEVE\DfFJGJXGFFDHPILGGNK`JTLTKPLMMfORNPPUTTJV\TUSXT`UPZXhVR>RRSQOOKROILHLTEDG\CCRDCRCBAhCZ?V?T>L>N?<<=fA@?`>=?Z@V=LA^?CBVCGEDGHRE^B`D`D`GPJI^E\IjGLMLLL^IKLMKXJXKVI^GGVFNEZELIhEbFJC\AZA@L>`@P?@X>=;R`LPTN`\VVXZ``\L^  \ \ Z ^ b V ^ T d N R `X\ZTPZh\XNZPNnTT\Tj@Xb`VVX^RN`^PXRTVZXdZ^jLZbdTZhT`\XX`XZdRXLZ`RdVRZLVZL\f`T^`XlRNTPPXV``XXfLX`bZ`HbRZXNlbP\\^ZDZHZXVTfNhTnT^`XbVTnHhZ^PTVZPXdVZ\Xd\RXT^Z^LTb`bBZ`^JVXL>XfTL>P<ZJ\NXnPZVPNH`NbV\`^TZVTf\^X`PT``NpZb^`fT\``\ZRV`T\b^ZZbPNX^^\T`LdV`ZXXRZ`^N\PVZdTXVXTZRb\dff^XLbVRVbf\\bRXb^JPRTdTNZdRXVZZ\\PNNbVR\R^RZX\XL`JHbPV`HJZ<D\XPXZD\V\\`NP\Z^`ZbLb\Vb P X T N T H Z X L f hb *X^VF\`PVT`N^\XH^^! ""T#V&\%`&F)T,,+Z-N/\-d.X-^1./Z00X3/2^4R337P6\757646\3^4^344^3Z43R7679J9T=b;\:R:V<88T78^852L6d6R5l6^:R7X787Z7b6\76N898j7X4312X4`43X6V3T445`224P2044320\633Z7V23\432T4L52H86L8\:Z^=@<\@;=@?>T=Z<^=L:>898@8P7\82^66L5V33201^3J/-L00--Z,J/b,*V0,..002f0--P2.//\-.,T.X..\4h/H0X43R0J022Z-0-V01\2132J22V5X4V823X323\511/F4T34J42`2`1-/0V1-./J0b1J/..Z21Z-X+Z,)V,^+R++'J)(N+T'V'f'''X%%""b"!`V"ZVTfL\^DVVFV\RV ZTXZP b ` F P V N d fX Z  ^\PXdZ\XhTPL\ZZd`bVZ\VVZ\FXbbVfDXlVb^`>`^TPdjddVTX`\`XhhP`TZfVHddd^HZ^d`V\X^dPbV^`bd\NZZ\\TRb`jRZL`^XXbX^N\\XX^^V\XD`VPbZXbVRXVXb^bXV``PVZPbTNpHXV^V\RFlZNXb`VZ\N\BTNJ`X^ZR^`\LB\R\RNRTVXTbTZJRRDZPXZXXd\`Tb\`V`^hR^^ZTP\R`fT`TXbZVXbTd^XN`XXjZX^f^bVd^XThNV`dLVB`^V\hX\^L\XXZZfPV`L\V\^T^Z\P^\L`R`ZPnRbT\Z\RfFXXLZ`HJHZ\LVZPRXNXTXLT>b^^\:RVTNZ^^JR^VNRN\RXZZHbZFNDXZ^PfTXdXFbV^ H  F l T ^ R V \ X @  ZNPVd^2PZHFbPbb\TJNNLLNZP R!!^!T#$&\*)J)V+Z,,-.H.-X/P/,L0`212X3X2N35N55V4X8X67447X5Z4R545P635d55^9Z57V9^9:R98R6L666R7V4153T77F8b6Z6L9b:f:d6T9T4P;V8\:4T5^4T6L7X42Z4X33032N65\331T464\34`522`4N52f3J3V6V323R87N88=b;=>NAB`CRCCZCVEZCXHTEGVHHJKJKNIJJI^M`QRXQXVN\JPMP^PLLJRKZMMDIMMKZKNKVMJLZOXMdOKN^QHGFXFXDDDFA^BBZCFDDVB^C?DEFHGJHKZOHMI^KLMTLbN\NLVORPQRRTZSVbWTVNZVUXWPT\VRTTVTWZJTVQNPNTRONRS^RRTTPOR:RSNTNPLNNZKIKIMMML^OTPS\UTV^RUTVWWWXRXX[UBT`UNZRNUSZPRVRRRbONMXTMMONMHPXMKMDO>MRLLOVOVLKdPOKMOKZMLMHKVLHMHSPPUVSRRR`OOOXNSOMfKRKdHVM\NNfNK\LGKJLRJNbQHO\MTQZQRPNTRPUPYZUPWXTTVZT\YY`XVVTUUXRUHQTVSQdPNSRTPXRZRRZTTRZPJOQMRNMKLVIKJ\H\LVKMM\MMGXLLDJVJL^KLBLLLMMNLMOVNQTUOdQZPLPPRP\M^TXQMONNKJGXIZHGNKVJDJZHGJRJRJKHPXHJKZKMMZNXNOVPMLNNNdNN^OOLL^PHVIVLPIVJPJTHKZKXINGRGIHF^KLLILM\ONJHJJIJ\KLMKLMLJ\LJGTJL`GLLGZKGFZFF^FHHRGhEbEGIPIOFMXOPPMJZOKZJ\JLMNLXOLJLMLJ`MFNRQNPJGFOVJGbGIG\M`JRNMLOK^QJHRJGJGIHVMLKLKRIJNFFDVCDENFNBATAPE>XEC@GFFJG\JhJ`KJXKbKIObPO`QNTVZPWRTRRVUZUSQVS`PM>Q\P\PQRhTSDPRVSLRZRSVSPRQOMJZJHbKRKIFVFPCHECDVFNFLBXBRBC>@CGXDDhDZEJZENFhGDHIFJZNIbLTHRNZMLN\QQQQ\WXRZRVSRVSXXRUR\UP`QK\MJ\J@?R=\<@\<>R>>=<>T=<=R=B?b?V??BCV@BBFhEDFEFGTIH\HNKGHE^GJPJK^JVHLJbHJLLIJGVHKETGDFCVETAPB>@L?A??<\;;;6Z=R:F\` X ^ \ d Z h `  T NXdJRRVV^ZZXZZZ\ZTDVRVVHZZXFX^L^^`dT`TT\bXL\^L\Td^V\V^TXRVRbTRXbhBTTZRXTT^\`bZP`^JZ\`b\\\bh^LZ^^X^^^VZfdRXbL\X`bVF\VdNNbVZ^JXZTfVP\^ZNVLn\^VX`bbDTX^ZVHZZT\PF^Z@^d^X@bVJdV\N\VTTbLXNTNP^jX\hd\Z^h^^^LhRb\^Z^Xbd\0bZh^dX\ZZfXZZ\dZbXtTZ^d^\dXZP`\rZRRldZNXXRP`LR`N^dVRT\LTTX\PVP^^XT^\bRXbR`Tj>p^N`Ffb^db\P^VlZTT`XdXbTXT`^V\PLPVZV\^bLZHb\hN`VN^d^TP\Vd`XVTTZZ J T X  R N Z ^ X X ZR `^JhHXX\\TH^V`^f^#!`&L&`''((\++V+R/Z.-P.L-,/H-`10\1Z1P4T34N34375J5P:44652^7Z4V0P3L334\75:\7;P9P<98b7V9T;6d66^5484L8T766T578;9687V8V4N53R8d2R3X43H2`3X12Z46N4T6^35T421^1\3Z6V45V5P341\3V6V5X5N9868::>>@bFVECEDNG`CJD^CPIdGHGTEVITMhINhL\R\TRPRN`QPPLLXK\NJHPIjLJJGTKVIVOZRTMbKXNVKNTMKN^KLGTG\DFEdFTALBDP>\BRHD^DVFEFDG^EFfJPLLJI\JLKGPGVKORNOMVSNUTQUSVX\UT[XJVZXWS^UVTXW\XTRSZNXLOLR\OOSdZTQSPTPX\QZMMLKRTKNKjJNMJZQNMPPOMN^V^UXSZXPWNTXXXVX`UVVFVRTNTPZQXQQRMTPNRL\NLVKMVMNNP^I^LjNNNPQMKMPOPPLS^MPdQTMLLTNNMVKR\PRQRN`KORPPVPK\NBMTNdMKNO`MVKHLJLMMP`QVOPZQMZO`RXTVRTRWXXVYZWVZXNTTbVPT^YFVRdSWTSTJVSTRhT^TSQZRRUPPVV`QQOZMOKGJRIKdJTNMPTNRPNLMMMZKNKLfMLMMVKRJIVQLWSPTPVRVQPMJOLKQMZNRNKOLVKZGHPFHBIGJKZGHXJLLIKdJMITI^LOVMKMNdONDNZJXL\LLRMTLFGHG^HGHbKdJHHNGXFEdHNFFZH`HVKJVNK\KdJBIZHXJRLRJLbOL\M@KJ`HZG\IXHXJTIHFEZKXHHIZGPIVITJ\FZJPH^N^NLNQJOhPNLRGVMM\LNTMXMRKLOLJMRMNNLMLXHHKJRJII.KPJJLM`JMOdIZNJHINLMXJbKIKVLRIdHEGCGbCTBDABNBRBANFFLGHNrJJNLM`POOLTHWTQPTSPT^TfSPVQNHONNROOOJNPVQPOSS\STRPP\RPOVTRPbQRNVMMJI^MJEXGFHFGPC`EACXANDAZB?bCTDBRBF^EFTIIXIFPGEIJFGRLTKILZO`MZN`LNNRRTZU^TFQOPTRTQNU^QVRSNNZOMKLIZK\GXFBGTCbBBCDVELBA?d=?=L?=b==X==Z?=HPAXAj?N?AZBRCCXC\FREZF\IGJGZJVHFIVGVLEG\GLHPJKIJINK^IILDHHFCDVCVEACfA?b P X ^ d \ \ ZJ P RXV^b\R^HZ`XZ^RZZbRhb@^PXjN^XlJdRXTV^XVXZVXjX\RXZHp`NV\TdHPbpl\NN^`\\NRVbXLVNF^NVP`ZZnXfT\\^dFf>H\jPNjZ`h`\>b^TXNXV\VPbX\`\bLl^VhZ^dhV^`PZZXh`TNffVRVX^VT^Z>bVNHVXRZPLRF<DLbZbXJbRXNVVHb`Z`TddbbLVn`bV\bZX^Z\L\`\BhbXZR^bXNHRV\\f^JXPRN\XNXXZJXJNR^ZfVdPVZ\\J\ZXDTTN^^JRPPRXbDVP^^LXJ`<\ZTbHbJD@TNXNVFZ`TVJdN^TX\T^\XZRNVXVTZVXTRPXNJ\TTN`ZT N ` \ J ^ ZT X` XN\^NXZbXLdRjRLjRV!! !$P#&^%%\-L)B*.T/-P0,J-V..,T0N.L--T1R116P4N6R656T44Z5P4V5T2f5L4`5J36X34P85h7R99L978Z968764T2X25Z3P7^4J66R88:Z:8<:887X8V7X6b5N6532Z8d301P26553354422`2X53L2@51R44J3T4\146X86L88R>R?VCLAHCVBDREJIfDGALGDZEbJXHIJJXKNPQXPXRMVOfIMJQMKHZIKhHIVKPGTHK^KOPMIVLXKLJMZM^JJNFH\FCbHCXDDEFVDDDAbC@ZC\DHITKTFHHFKNIKJNKTMZNLSOZUTXTTUWPZLZXRXTXLZ\VVWLU`TJSRTON\MNNQZQdPRVTPRRLMFOPNMPNRQKNRJJTKRKRIJLLLRXPTFVVQRHYYVYXTZXVUTVWFQ`XdUPTS`MOPPPMhNTMLLNNXKJ\JRROMRNSQNPVSORPNVNP`JNPXOKPRXLMXOPQRMNLMKPRLPRORPKIKKQKOXLI^NJ\JPMPKNO^RdRRNNLRSSVVVZVU`V[[T\ZVZWHYURZVZ\VV`YNXTULWXV^VLVRTTPTSQ^TRTNVSZSPR\RDQOZJNRNZMZI\LLIJXNN`SPLOKNLZOM\LPRLOTLNMNTNQPRJQ^OPdRNRSO`PZOZLNKILNINdKINGGRCZHHLVMHIXJJINL^IJHJKHXLTKNMVMLTLLINLNLKPKRKHXGTHGCVGFCGDF^FXGTD`CFNEDGETIGbLJfIJfKZHXKKLXK@MTLJMK\LIPIPIHJHI^GLI@GHKbKZJRIILOlKMLTLMOLQP\N`PHPMNLLNBPTP^PNMMN`MNJVMNKL\KHVKTIDHXNITM^JMJJJMVOROMONL`JIIfIJ\JNNKdORJVNRHRKEDRGBCFPFRECPDHD^C^DCVEE^HLILOLLO^P`STR`USRXQ`TQ\SVPNMNQPRSXVPOOZRPORRRXS`TZRVQTbRNSZOBPQPNOLM\HdHGfGEVBDCVEDDZDEB`A>AR@BVCJCBTGVF`LVGXFXEEFFDGHIVM`KLLMFKK^KVMVTXOJSR`RS^QOLSRPOTQPHPZOhP`NMLbKNJGRF`F\GDD@CEb@@`@=T=Z=R?>>X>`>P==X=`:nJ@>A=@?`??R?ACZGVFfDEDHGKdHGFLFRGEE^I^LDNRJFFVKLPINIETGEIZELBE^FRB@?@RA\?T@T@=V<=;9:6536\21b000T/b-\//\+T//T/+-\0V.-L.h.P-H.J-f.-V.R-J+,V-P/.,X,B1R2/P/L004R1V31/5^3T0N31`2J25Z63344V5b7Z3^4F53X2^2R21`0V2X22N1f13Z2V./V//\/.R.V+/Z/../)*-`*V-,+R*V)V)(\)J(R)&b&%#^# N"&d Vj^ZhBTXJTRJ`TVf`bRP ^ R ^ V V \ V ZL ^ZRZZbT\V\HZTX\hNXHPPVB`P^bb`>ZRXdpTXPJTRNHlNB`XTNXLb^\VF^dXZ`^ZXZJlZX\f\Z`\XZP`b\RPRfRbLXdRZXbTfTV^XZhZf`fRP^LZXbXVPnd\jF^`VVVVV`\^\`dPVV\^ZXZHRXPZ`TBRbbZf\X^lDZ\@NLXhRZ\XXV^ZTXN\d\LZb\jV``T`\bZ\lbfPf\\d`lTVhbNT\TfNTTTVTZXX\XVZ^bZbZR^VV^fXZ^Nld\RjV\bX\V\f\`ZZVZV\bPRZ\Nd^NHbXTbh^^VdJJ\XZ`PZbX\\^dJ`^bRbdLNb^TPXHb`bNV\RJZ\`XX^PZZPR`V P R d Z P H N R \XdR^\T^B@XV^T\JVP\NhP`!P! !V%H#f'&R,T,-T,/`-+-\,^/+\,V,--.L0N1V315h45365\5Z6^2^64^5^3X4X6T5V45f67f5\9N99788J69\85h4R04\3765Z96Z42:^<:;67`767\<7Z8L7^54X3D4252f565R4443R3R3N4^3Z3P305V4\11^554T48\74^8b9;><=BA@^?VBCG@DBVFVDXFLDGJIMPfQRUVOPLDP`MXPL`NNKGVLH`JVFNTILhNLNVIVOLMML\NL\MKIJZJHdFTCDRG\ECAbCRC^ECVFVF\EDFBZELJ\GKRI\GTGEGGRF^LPLbJLOTNNRQSVWRXFZJ[TXZf]\XYXNWdTVUNSVN^O2VPQ^SQLRROOTNRpRPQFMLJJLRLK`KPJII^JJXMLOQRPdTUPQTTURWYTXYdQVTPT^RTXORKNQ^OPPO\NJIIQjJNUZOTTWUZTSUZM\NXLNKOOLW\PNNJMPPZNbPXJbMVLNMKKXPOJLKXLJLfMZMJLXIHRK^NONLNNMTORPTSNWJUUDWTV\UBY^XVfWWZV^XJZWP]WHYRXZYXUXUVSJUU^WLURR^USZQTRVQhN\QNLZMZO^NJNKVKVKbRJKZLONLXMJLM`PjLMRP^QNSTYNRdUSLTXPPQKLNJZPXJHKGZHEFDIE@FVHKJ`LJNZJTLLPJJHLKLOZOLKVJIGH^IGPKITJ^JFVJDICZDFDBNCXFBDjHEDZGGGXIKMZMKTIJII`MLN`KNPMMHJRFJdJZKILH\JLIXHHN\KK`MKJZMM\MZMN\NNQO`OTMXONPXMLL\OQJPOZPMPLKM^JIHHJPHNIXLZJKVNTPJN`MVNM^MLRNIHNJTJ^MRJTJVLLRNLHGFDXGDDRDLCPDDLFEJB\BDCXChEFI\LHP\PNPPZSRSPTR\SSRQNOTNjRXSOBVQ^T`POLRZURTSU\PSQS`QZRPPOLPODOLMVNHZFDCCJBB>CAZDDDJCEGBAXBPDDDF`HFFHNGFTEPD\FGGKXKVKLMdLRNVKNMMN\R\OVShPLPTUQ^RRTXTRdOMOKFNKIXIIEJDFVCNBVCEdA@T=>=V@Z@>><=f?V>9N;X;Z=R<9Z:X2023243Z5Z333V4^0`6 3V4^8R5L4574b6Z53R4T1\211R10f3V.\0R1\./X/^-/-^.H/R/,.V.V,--P-b*f*(N*R,+*()^'Z&&X&$Z%T#X"!`!D# RXPRTdR`PNRdVRfVNX`R d FP N ` V ^ R V N X PH VP`TVVZXRV`^bTXXRbXdXhTTXVPH\Z^VRJVRZZ^X\H`dTZ\RN\`VbLZhPjf^`\T\VdXVZTL`bJfPRZXFdZb\LV`f`R\`^X^R^\b`R\NN\^RbJVVXZ`VZ^H``Z\JdVZPbVXbVZNN^Fh^\PLXVZb^VXdT^JTLFX\PTP`\^RTLTZVXDXVHJTLRHd`V^\T``dVZ^\TXXbTT^TTX^^bTdb8\PZX`fN\XVfTdR^V`V`bXV^XZR\VVRN^T`V`HXZ\PZJX`NVR`XV^VNT`TZD^^LTfdXVZTTT`dPVVX\ZPTVXFXRZVbffPNhVXRfHd\NRRN^@^R^J\TXN\\ZZ \ X Z T T H L H X N T V T ^ R PN@NHR`NLXP\\ZD`^ZV!!T"T"V$X#\&)P%&+P+\+.,+-`-.^.,/f.+P/00V1f3`6Z45d3X7X64L5L1`6\43\4\321R6h47\57;8898`::675R44X46N63648X4^97<`>\9>779f8N78T857R5Z126d55X35J5336`42X51V4541h1J0^3L1P00T1R5556N;:d<;A^CN?F\CBRCCTGFEVGG`DINNLOVOdODO\LLLQLJMJdLTJJCGVFXK\KIN\PVLPVMRKZIZL\JM`MJE^F^DbDCFHCA@D\BhCEXDCjDDEdGFHFFHGXFXHZIDZGKNLMORMTbORPNUfTVZVZYY^XXaZXYPSOZRQRQPJONZQNPNSO^PJS`TXOLN^M^ORO^M\MRLKOMLZKZLMNVKXJPPZODM`USbUUVS\ULXUTTUS`RFTZSTSPNPTRSOZPVPTOFPMOZNZNNM`M@NPQRQPQLQUJWFWSNR\SNdLNN^QNPNOMM`LLN`NMMVJNNTNMNN\MIPONJ\I^JTLKKLMKMMRNONQNNXQPQ\WTSdUULTYP\UXXlX[PYR[LZZVZVZNYX[VZd[L[[WRYPXbWTUUXUTXUUXTT`OZTPPTPMPJNRJOXMIK^LTJPLXJJIMNNLTQONZPZRXO^URZVUQVTNQPS\PRMZPJK^JJ`IFH^GLIECVGdFGLHVJLKLVKKXNIKINMKLLJRO`KNINJIENHGVILHGGDfDVFRH>E@F@VBEBJCCNCF^DVDhENJGHIRKJJZHJZILHRMFPMOLZNTIPM\IGFLN\JKNIRHDIKI\JLL^K^MQXNRPPN\PQ:PdP\PLQ`OPOZNNNMNLLObLLIbJKGGZGLdKNXNLVLJJTMZLOHONRLPMKKVK^LKIBMLNKBIjFFHEZGVEXDGFDTFFDdGD@TD^FRFGNLMPRjTLRdSTSZQRPRRPQ^PRPZSV@TSTSSQTPQPPZP@QTSSTTT\N^NBKKNL\ONOPI^JDCCZBbDB`CDF@EGFHBdDABA\DbDDG^FNDZFEZEDZETFDH^F^JRHKIJJMMJNNNTMP^QFOPPMJQZNOPQONXN^PLKHGHfGFFDRDCCTFE@>L@=B>>@H?\>;;LN@?\ENAJDDXDEhCJFjFHGZJIFG\GXEGGHLRHZJMJFGK\HDGVELFTFTDEEVBDBFBL?>@^=H:>;;T=8R:8975T66R75Z01X212/Z.N-+--P,V+T,b0,F-..//--++.+d.-,+++/R-`,+H.+21\06302\4R426T31^4T434^464b64X6T2Z7T3422`121b4\3V0Z/T11b/N-V/N.1/T-Z/-..2H1N/.^-+H*`,,'*)*)&&&T&%P%R#!X%X!^" j HTNfPPbLR^Z^T\\bV X P X L N d P R P XjRZVBd\NVV\`Z`dLHb:Z`^\dZ`HZT\VX`f^VV\`TVVZT^ZX\lXTJVPN`\LZfdb\\ZZ`fPZXZVjPZ\\VRZhLRV\NR`X^RX`L`Z^bXjb\VTV^^VN\^ZZL\XRXVTV\HTVRhXTTT\`ZRVRN^\NZT\\J\Z^bVVd`j\V\ZZXbD\TZ^TV`RX`HV`P^HL`RL\@bH^XZ^\RXV`ZbdHh\\bhFT`f\T`ZjX^b`TT\N`VX`Lb\fd`Pl^XZ^\l^\^hP^\V\`TZ`T`dFXVdRZVVR\^Zb`\^fR\VnVP\V\TfXdRb```^JlLZXVXV\T\ZXPRTbNTfLHBXTlTXR^TVZVVP`PTNZRXLJ^TZbXR ZV V F T h f T X ^ N T R X\ TbbZXRRZ^P`pVRRTZ\h^VNPVT R D \!N"&T&%T'V(R*(^,V,>/T-X.d,,,--\.P-L//V0/Z2V1R7J5L6V5R643H43474X33R4V2\4377N967f9R7R:88D:6V8^65V6X46Z4447R77J7=8;:T;89;78X34^4X3L5182\73L5`2P5N32`21V23^4Z5^2`3`4\2124341R4T4448;dAP;R=N?<@Z@XA^BNBZCBCTFbCGGCHO^L\PVSROJK`LMOJNMTINJ^N\M\JHbKJHRHIJKNLQ`LTOP^MOO`LI\OJKZJGTHFB\EJGAjABA?@DFGfIEDJKIIKFTHHXEbGG`EI^JIdNL^MNSNRXOTUWNZN^TYZ\VXUSVQPQPQVUPZQPTSPQbNOTQSRNOPOTK^RVJVLLJONNTMJdINPQRNNNXMdLbNTOfOSOQZRTRVQZSQRTPVVQTPRLQPNPKKLDOfOLfLMRPRMTMZPOPRTTRHUJSRbTPRNPbJOMKZRVP`RVNTN^RKVMbNJVKPMJKJVMIFLXO\LMVMbHIPILJJTIFMXLONQROPUMLOXQSRdP\UTVWVRWXYDXZ\YVZVZR[\[`[_RZX_R[\\Z`X[YWVXUWW\V[UdUbUPUTPVQ`POXUSRNfNOKZMJPP`NJKNMdOHNhLMPVQRVVOXPVRPVRSTWQRRXPXOPMGIRHRMGXHVFCDRFEDTGXEJLIXMKKRMJJJ^LJOLROLOLKGFFKTDZFlDFFGDBhFECBRACVBB`DdBCDLZMLLNKZLKMJI\OJNO\KPZIVIVIL^MHKJL`JOZNVO^ORMNOTQZRRjQPQSOXONXMTLOXMKBLKTI^KLERIIXM^KRLPZRQM\Q^IPLTMKLNTL^QLVNLKPMTKdJM\LIHGE\FFPDPHEFFPFDCCFhCXCbCCJDGbKXMPPSRQVUVWRQRXTPQOPO\ROUQTTQZTQ^SS`PLQPRNSQVT\RPSTS\ShKHLITJKL>JHJJIVGCRCXCLDVBA`DNGTGKEPFJE^D@\ECZCAVCDB^DEDGECEGTEH\FNKXKJI^NKN\NNVPMbMQOO\PN`O^PXOZKNM\LRLTMhNKRGEEFEG`AJHXCCXEVAV?=<=Z?<>@<^=V:\:L=\?>>X?V>??R>BX@\AJDXBZBDDBRD\HVERGHVI\FXDPEIGG^G\HJ\JIbFHXGEGGXDVC\CLCFlEHB^DVALCX@V>b>V=N@J;Z=N;X:d,R.--+\.X+*\.0-P0^00^10`23L7262T44\2R2H3 5\63Z5V4V4X4T3Z7T5T6^2P11^13Z0102X2/\.V1V0Z1V02P/b0.0.V/^-Z.X,Z,F,**(l+**)%^%'&%%j"Z"P"^"Z#X!Z Z P^bV`dR^Z^`PdXX\NbNd^ d ^ ^ h d b bLVRN hX XVZZRVT^\Tbf`FXV`XT\ZZR^RTRLLTVVXZ`T`PPNVbPf\XZNRX^NhbX`VRdRZZRRZ\Xf^PPLd\^P\`VhT^NZlR`TVb^lVh\\ZdXR`\\b^V\fVTXP``ZdTVTXZRLXN`XRf\L`XRZZTXD\Z\RL``RVbRZZVX\fVRTTT>bLVV`XPPbZRRP\`Xfb`N^\\^`^rV\XP^pZ`XZdVT`bP^PBX\L^dFhXR^R^fbXV\HH^RZh\XPXfV\R\JZ^R`P^VTX\ZZTLd^\N^^^RVdFT^bXBhVZTTd\PPXNjJVZNPTTHTRbLPXXTJ\VX^XZR`\hP\^DLPRH\\NZFRBXPNZLTN \ H J P ^ P N ^ F Z XZTPVfR\TRXVZJJX\JV P"X##Z#P%$T'V)+,J.L,*`.+X+J,\+Z/V.T-,+V1`0/0P4X55X365422R3Z53415R7P4T6H66:6f98T99=9`5R6b5X9`644V8V63T8V8=86:=<^9X88V9h99\88^5T75P5L2V4J21N35^531213L1`3`5Z4T6J6R33V65d33N62\557J7T7R9P?=AZ>^?\ABBd>EB@VDDEE^DCXHbGLLLKLNJJfNNMON`PNNKTKJIIJHILNMMM\NKXQVLLOR\QVMbN\IKLINHIH`FCHDBTBT@XBVCPB@XBDXGGLJFVGGJNHG\EHGCHHKHZMNLMHNZPRTXTXVTZT]^ZZV]PTWURW`VOHQSNPPRTTQVPQ\SQNPRQfPZOZMLTNLOXLLMLLTNPPZMZN\LMTOLTMKXNROTNPTFRTRO`RSdSPJRTSTXQOLSORPPHQ`SdKMZN\OZOOL`NOQXQPP^PT^STVTVVVNPRMFMKQJSNM>MXLhPKXIMTOZKJLPLHfK`JLIDPZLIZJJObKdKMLHOL:OPTPPTRN\O^M`RPSdUVDWXWWXVYDZV^P^\\HY\XX\F\ZXh[\_[YYXHZLXVZUW\YNXLUVXUNXdSPRSXNLJLN^NJQLKNLRKMVOPLLOLNMMRRQQUFSXRHTPWLUW^OTVPRTPJMIHHHIHGTGVENGDDFPFGGJbHPMLMLMRKRKKPQOLLK^NHXLHNGEFEGFTDCZETDDEBb@PFRC@dCCJDJEGHETHFZEIPIRJJ`JMHKJNRMOLKLLKN`JTIMKLXPMVLKNMIHKJVMXLZKHObPNO\PHNOPSfRTPPQ^PMODSMdLLM^JMNHRIRH\HVI\JTKOMLVPbOXMXNLLJIMNONPMRO\NKNKJXKNIRGJEPHEEPBXEB\FLHEpDTHDZDCJDhD`DDIXKXPLO`RVSZOO\RSJRTRRSVTPTQ\RWHVSQVPO\ODPR\SRORQ:TRPQMNM`IIRJILMMIFIE\FNDVBLB\DBEEIGMDEARAXBDCCPEELECPDD\GGTG\FTFFVFFVFIKNLFKLPK\OVQJXMHK^MNVLVNPRZMN^QVNLKLJKXLRKHGE\DVHE^F`DEDBFZ@A?B?T=N=^TX@REbBBCBXBXDBdEXJGHIECNHRHFjKPIH`IRGRHGFEDHEbBJCBJBdBBTB?LB?LB@@>T>VC;X=d<><8\:N9995R56\6B71Z4X03/Z..F/T.,--+-b+,\/L.,./-T-,X-+++R-L-+Z/V0V-T/,.\-,R.X0,/10/H3155Z43P63R45^3546124Z3P5421V4V4R011X1T21\2@10.P0f0b0X0.//-H0Z/H1X,f,+-V,,)L*T))T**J(&&'%%!"Z#"""X!RZJTRdNdNZJJJPZX\N\\\R` J V \ L d X \ V \f L^T XVXLTT\T^TNTHNZPVh`hXZPdXZHZ`dRZZP\NHPbTTXRRRdNV`Z\Tl\`^dVVRf\^dZbV\`VPP`RZLXZV^RX\VVXZVXXZD\^^LfbTXZbV\H\V`bZfP\R`\XJT\^VV^L\^TXP\TJP\`XZV^\TTbZZXdVH^dTTT`NRZ\J^d\bVTT\PH`L^HVV^XZZXbhZhfPThXbhlhj^\bj^J``bdZ\^d\ZfZXVX\fTLdRbVnTV`T`P\TXNhTNbj`R\^HV^XvVT`JVbX`XVdXX^^Jd`T^^XXXXZ^XXXXP`bTTZT^ZVbVLPN`DPfTh`\XbHPVjbXX`bXT^XXRT`fX\\^bRZ`Z`NLjZRVV P X j \ R d Z J T N ` V R ZjLdf``R^`Z^PT`d\F J!"n X P!Z!%$%%)'Z)<*Z, --T,.*,f-V*L--.N1P.0P/J31R2X3T53\3T5Z34J22^45H2P4V4Z4P6Z5T5X96:7;8;95V6:6X5X8`477d25`7\99Z=X>;:86Z889;9X6^65X7\64`347P4T2041R1^3\437R5D4X6\245754J5X355V8:6b>;=TT=P@AX@R>F???:X=A?VCXBCb@\BbDVEFGHNJIbCTFXEE`JKGGFPGZGNHFKVETFRGVFBCDCdCBE\CXAN?X@XBA=V@=f<;b9P965V6X8V;\7T55`5R7^54X343N32f1V20P1\12T412f2`30^3\4482f4V42V56V6`;8:A@ZBZA>^@APCPB@@TA`CBEPFHRG\IfINH\HKP@SRQXJQMP`JIIFRKZHXIRKMZLNKOJLLJONMMlPLdKI^LXJITMFdIVGBAXB`BDBX>dAVDbCHIXGFEEIVHNGHIHJHRJTGIRGJIJ^OOO\PVTTWXT^V\Z^XTVVUVWUSQUXNJS^TRdQLQOPPQSbPPONNHNPOVPXOSDQbTLNXLJQNMFLNVQMbLNM\MOHObTTNURNLRPQPNPXNLVOTNPRQPPQLPVORVPXPNMNQPVRRVRQHSVPTPVRNOZKNN`KNM^KKMbMMKHILRMJ^KPHTJPHVMZKIL\K\LIXKMbKRLLPfKJ`NNTNO^N\OLXOPQOPVTWXUWVV\XXHYH\XZN\Y\T_Zb[RX\^`\]\`\TWLZWLXVZb]]X`ZXVTVV`RTQNPPNMRL\MNLOKXK^MHRdOHMNQP`QRSRSNSSTVTVRPROJNVQOM^PBNTNNTLGJF>HZKGJNDHLIRKTKKHHPGXMPMKKOXPMZOZNFLIMVJHVJVHIGHTJXHXGEfCLCDDBECRECJFGPGGEIGXFFHRJFGGGKOKRPJK`PMDPONOOdMOM^SR^PRVQOPNMKMVKMRMNOMORRLTTTU\WWVT^NMVK\O^NKJPLM\N^LNJ^LPJKJKZJLTNTMMMLVKKfKRLJKbLN\KQNLTKZMJHTITHRC`FFXEHH\GDHED`GE^HTFRCTEEVDhG@HGVJLNZPTRQZP@OO`PQQ^TSNTTZTbQTVRQNRNPNP^S`SLRRSJQNZRXZTVNPLHLL^LdJZINJGEXI\F\GDDZCTDZEENEHDVDVA@ABTDDLFbH\JLF^GENDFHFbGIJI^HJHfHRKJJLKROPJNRKVM\KNNN^UPTNRMXJHKLVKMK\J^JFXJCPEHHEEGPF`ETDDXDA@>=;V?=;=>d@?TAZBRDfAA@XC\DHGJEZFEXFFZG\GXIRJTGFjDH`GXIFHXGEPDFBZFC?AB>DA>V?PA=H@^:X@R=T=:H8X68Z7Z983>64520`00`/L.^/.0+/^-.,N+b,.-.N-`--f.V-B,),,X//H+.-R//.J/^,,P,P110.3Z123346f43Z3L54V4T22^524554412P2/02R2T4J4V0H0/L/0\.L/2-b.-Z.X/H1,-d-T.X*T-^+h**`)(V)'N'*^'b&L&$&$"P! \f"Z L\TNNX\RNRb\TJRhXZZVXN TX b Z L R L N d R XjX`VZhfbX\FZPR\VTZ^JVJ`\\TVVR^`HZTTNX\VPVXh`RFZbZ\^T`TVfdXTXXX`R^\Z`Xbd\ZX^L`\R`bXbRPd\L^PTR\b\\VPRXF`NLb\d^jXPZTRL\TZL`PTXdXXZ^VXPX\PNbXVdX^TTTTPDTTZ`JLRZZdTXRRN\bTHhXfJVf^bdfVn^R`lh\NZbXfhPRVTZfXZZ\TdZRVXZ\b^d\NXZ\^\NV`RXX^LdJjd`ndZ`L^XdZ^JfBTZXZ\HX^HhJT^T\^bbP\hN^R\dV`hTV\XPbbVHRZN`R`F`XRFfZbR`ZRPTTLTXR`^NTb`V^\dZ\V^\X^^ZT VRR ` T b J V \ R ^ T X V b NNDb^XV\VRXbXP^V ^"Fd #T "!#$d&H'^(V*F)`,X*\.-R-V,*-,0J/`+-\/\003T3L5X5675<58J9T5\43V6Z5b45765R677:88^979F6T758679684V6`<9;Z:l;P;:;:P=98P99`6R6T64F8\6L55V2\3P3Z4V1H43L2X22d253P2`3\41d64X2P6N2N55\8b6\6^;N9=X><@?@VDTB?DZ?X@`@@CLETC\GPDPG\G^JLKXNOOMN`NL`LNKKFPHIZJGI`IOIPL\MLK^MPL`KLXJXHZJZIXOTIHHZCAXC\FBVBBNDBEPCDEVEDGTKLFlGLIGPGGNHRHKJMKPRR`QSTT\SVTWdY\\WTXb[RWURYTTXVO\SbRXRRSWVQlONMPR\OPPMMVOVRHRK\OTQVKhMI^LVMIPJMLOKXObSOVPLSNPZNVONPVNdONK\MKPPhOJONPbORPOPRR^N^N^MXN\QZOOOP\OJRVSTRUROQ\SNTMPJVKMRK^PfJMLNVMVKZJJRLXJ\I\KLHNKKJPJL\K`JZM\KQNLlMNKFNOPNMXNMVPZPORPQ`ROMR^SUVTYV`YLX`Y\X[RY[Z[Z]J^Z[_UV[\\Z`\[V]X\\YVXVUVURPLNLJKROLTMMJQPOOQQ\PhO`TbPORTXSjTS\QSPRLTOPHPXRPPJQNMOMJbHZJRJJJZIJHlIJHGJLROJKZOHPMMLLKLRJHIHdIfIIJZIPFZGTGLCDLGDHdHGXIGGLHZIHIXMIFbKLJILXMMRMKVLRSHPHPLOMOQfPRSTSPQ^NTPFLOMJKROPTPP^PSTbYDXYXUSfPP\PLLNNDLbNTKPNKRNMKKKRN\LMTKLRJIJNKJ^IIJVJTLXNZOLLLVLJI\GfHHFVFG\G`FfHG\F^FFNG^GF`FXGPFNIVGGFLM^NTURPQRXPNTNTPM`TRJWXUPVSNS8URLTOPLbRZOPOTQP\TTRXPRMKTObKFJHIdGFJIZFTFTDDRDFDCFCBDGRA@AA\B\GNH\JXJTGFECGEHjHIHIHJVHJH\JHLRJM`NJZK^KLMXPTQMORQdPTMJNTHLOGGXIHbEbEDRHdF\FREVEZFBNCTCB??=>L>==?R>^<^?J?=>Z<=;b>=L>BPBA@\BTBXBFDERDDVDEKbKKH`IHXIZHZGKEXHFHG\D@CC\AAP@??V@Z;?`@`A\@^@J@=>=@>AAZ@BP?>H@C>HAVAPEIHEDCVHI`JJNLbNTNTOKZOPNOHFTKHINLKTMZNITOML>P`JO^LLZKLLLIIXIHIGHEAE^CBZATB^BDAEPAETFE\EJFXFGFDIHJILHMXHHKKKPRPPVRRWNTUUW\\XXXXWNSUVSTZVPSJWWRRPPUSXOP`OBQOPQMXPQ`PHRP^QSNVMPVPMLKMIZKRLNLVQKNXORNHP^NPNPObNRPKTMTMPOSDSPXQPSXOONQJNPfRJRTPTPS^NXOXOVNOO\QMbKOKM`P\M^GHJKMKMXKJVIKFKJJHIJJ\OHVJLNFLRM\Q^PMXM^NLMMLK\NNPLO^PXPMTQbQXOPXSOUTXSZVXXXXYN[Zb\]b_X^8^J^`X\[ZXN^YVXYVVYNTRTSNSPO\M`NN`PNPPORNLDP^MOSZORPTMOP\STUUZRR`PPXR\PPORNRSRT^VLQNTO\TTKMPSOMLJPLDIZHTK`NJ\K^KVLKHPKLVKORQVPMLXNTLJfMI\HITKJI^KGHXHTENIHEILKJKHVLJNbKTKMTJLJKJJJTMBNNFM\ONNNTPRRJSfTUSOPHTOVVR^TZOR>OLPVRSRORRQQQRSZVTWYYZXTTZROMML`MMLOPLJdJRNO^NLNNJODJJHZKHJ^KIJ\MHZKKVKLhNLVMNJJKFNH`GXGGNGXIPGGGNIZGVFGCRFGELGDITJXLKKXOPPXQPOOMNQOZTU^X^UTP^RS\MLMJNOXPPRVSTPRPQPPP^MFKTJZLJHZIENEREFD\FG\EXDDDADDVCA^AVBTADCVJGLJXIHJPFDC^FXCTGPH\IFIGXGPEPGGHPKKXJRJTPLVKbOZNRSNXNON^NJKJTKKJVH\IZKZFCFF`CXGCPENFCBBNACTDbCBR?=R?P=?b@A\@??@@Z>\BDEVEC\CERCXED`GHGbIHJ`FPDbHGbGPGGXFXDELDE@Z@AbBNCZ@@@R?@?@>^?==d;n9::d9Z8865X4b3T4P3P1X00/X/0\0b/T/L0P,-P-R,V,^+.+^.-X.V-R,Z1-*R,N,+,+-,0/T0.d0`.-P.^/`/1/1P1N14043Z0F1b3H3X3V2T5\37V33T470J12L50P2//P2P2f2Z0T/P/F1l11p.,-Z,\//N-Z./b.V/h.J/*Z*\),(T)(\)F*&f'$$V$V$$#f"T!R!X!d\Z\^VX\^fP`TV`\D V V L V T H TT F\NTbN`bXP^R`\ZR^R^XNN`\RJ^\\ZRXZZ``VHVbZdH\ZL`XPbLNVL`H^RX^`ZJ\NLf^^`f\bJd^bZN`^NTd^LRXD`LZNRZZXT^ZXTTXR`V\Z\V^`XbR\\R^NTV^NTb`XZR^bdVTRfXXXXFZZdTVZ\ffh\\bR\RbX^R\ZX\^NT\VfNRZZRVX^ZLFNFXZ\N\Lb^\XZbhpdRfJ\bb`lX\\Zb\hXfNb\h`RP\XhlZZh^LXZ`h^T^VR`P^R`Tf\TVN\RL`PZV\d^V^J\^ZdXX\fJZd\ZL^RdZ^TVZfXPhZT^T^TXXZ^ZX~`bVZ\^Z\^ZTXFVRVVNZ^VXVVHR``RdNbXZ^NVbZ^dTR\F ^VZ ^ H Z T P ^ T d V f@ XjXNDTbV^NfTVTZ XV N R!!Z#"!V$%('(L(+\-+D-Z-Z/`.R.R-/b.-0^-X00Z533^6V85Z5X:8H8522^565T66;`75887X:8:8L;687X756668\579=T=;R:Z<;\;:^;L8Z9R79P8b657V51T2J35P1P3H131Z6X42\30T1263334`6R3R56343X:`8b9X:R<>VA@BfDXB@ZBB>>@HB\@AbCFbAjBFJTKPM^KXOPNLONOXLMPPbJRJNI@KOJ\HXL^M^PHOLJ^MOXLJMjNONNLdHTJF\GVF^DA^CA`BDdBCTFCJDPBG^DDTD`FRDPGJIFNLZKJVJLLVMNPU\SbWVWNVTVX\UPW`T\TJVXTVXTUTSXRPSRT`V\UPShUQVP\RRPXPPPXTTPPVNPRZL\QZMO`MJHJK\KI^PMTOKVOVMRNIKNP^JPLTNVOMRVL^NVSJNdOSOOPRdTOPOQ`QJPdQbMQQdN^M^OTNdPVNZOXNRTPOM\Q^MVLKTJKKZLTHXJJIGHZLRJVKKhMMJM`JO\NNKVOIVKPMlPNjJMZMLRVOTPHNNNODRRPbRSWTWUT^]\YT]_ZZ_]abT`\P_\L[Z\ZVYWPXVU\WRWTZUVQRSMBPXNNZPTOP\PVRNPNPZPRLWPFTVPQ\SXRQVRTUVRQQZVXUQN\PVPRPPNQ^QLOOPLNM\NQHNHLMMhKVMXLfPL`NMLJNZNPNRLJ^MMXIVHPI\JMMLRMTMRJHIG\JLJMVQLLKZKVNKDLJKPOJ\KKKNXLOZPLPOPOVOQRTLRRR^RhRZOURTVTRPTRSQONPOTTXRS^VRSXVZVTVbP\POOMZMJNKJXNKLKO`OJMJLJHGHbGXHIJLHJXKGJJKKKM^MLHHEDTHHNHEVHJfKZLZJG`HEF\IXGRJRJ\FMPK^KMLN\POPPSQSVOPQ`PTWTX`XTPS\PMZRVNNPRRRXQRPRMbONOTR^KZIIZHRMJVHZHHFXEVGNDHDDAZDCDEE@\DRAdC\CDDFXH^HRGRHHHDDXCDGIH^JIHIFFGTIVKJXKJMKKNBLPPPL^NHKPPTKIJPJZMNOKZJIPEE^EC\EVGDGnFCZB@B@\?XCL@P@Z=`?;b==X>`=@`?P@@^>ZADBb>d?DB?A@LE`DVEFEDPEGRHXJZIBHVIFHGBE^HZDTDZDDB@BFj@DA?d?V@b?`>TCT>=;>9d::T87d:86V7R9210110/.^.V--,,.`/1d/-.,10-X-R/..d,L,+T),T*,+h-./.^0N.-.T//R0X01103400L2\2326^33312\4P21P2f2\1Z1V1N2\1\02l0.`/V0.1T2/^/-^.,T-d-,.d..d0X/V-/)P(\**(((V'(X*L'^%F&#%"$n#!Z"J!dPV`PXR\NTV`XT\XRZXPXb R \ R ^ f 8X ` N HT\X\\nZNN^b\\NTdZHnRNTVVb\VRVb\VX`RZ\V`NNhNV\P^V^TVV`dlVhV\N\VTTbb`ZX^bT`bfT^^TVZPTpF``fZdRTPNV\<Tf\bf\PRLd^Z\D`T^`V\Z\^V\PfRdbVRNbNb\Z\`b^RZZ\^X\`hT``ZbT\PZ^HLj>d\^\NTZZTN^XZTZXhf`X`hfVZVbb^\XHRjPdX^L`TTbZRXNbX^^XXXbT\X\TP^\Xb`dhH`\^^fTZ^ZR^X\HVjR^R`VJ^ZNRZZN^TRVN\dTbFbJT^P8^H\\FZT^ZhNX\PHH^TfZPbXdJRNX:J@ZV`VX`VRP^ZJXXP\ZP\J\RVZ^^bNT^Tb` T T T V d R f ^X P N X RVRPVDLXX`NVZXNT LR"R"T V#! Z"#V%#X(^(&*(,\+-*X,L,/T.X,-L/--.^02\11P66J8H446X:V:N5R54V8T55R3558@7X7`8L:X9L:b:;::X9`:999:V9X637T24222V5Z1X/0/Z2L35R626T233Z3T43\2L36`6X5L5R45^6R6\8\;ZRAVAVA`C@L@ZD?V?X?ATBRAAATCZCdEETJJHLNLHPNPORRO^PIVKGIIKLLKKLK\MPMZNfLMRMOFOJKLKKVJHMJE^CECNBRBGbIXC\EDBCGVGNEDPFTEG\EHNGhLPHHbHIMOfRVRUQWNUUTQJTRT`VUHXWfXRUZZVUTWRWVTVRTSURJQ`PTRNT\RTRhPJRSQJQLN^PPTJ\NZLJMZMbOVKPIFOPP\NZHXMXPTMKMJPZNL\PJNPNNM^NLP`PPRNPNVPVRS^SPhRXNRTMOPPMOZRO\LdLXLO\NPMTOQNO^NRQVMMMLMLTMMTNGI\ILLONMPIVJHTIN\KMK\MJRRNMZQJL`LKbKMMM^KQNNVRTSVPOTTQbSPSXYR]R\X^]La]baT_Na_h^_Z[T[L^T[VXTY^VRRSXTRWbTLPNQNHUXR\QPPVOMMZORPS^SVQXQRRZUOS\TNRbU\RTPVQPORQbQOTVQNSQROR`SOTQ`RQNKNTOPMMLFKXMZNLMZLNMPVPMNQMFLKNJ^PGHNO\MOTLJKOXMLL\HMNZL^NOFLHLXLTKKMH\L^LLJ^KKXNMPbSNPQPRXTTXSdVOVQOQO`VXSPSQT\UTTBRZOSQRR\SXXJVUTbVUROM\LLRJ^LKKLKMJ\MHQNLJFHG^HNIIbJRITMXINGbLbHZJVKZLbIPKXMXJZIHHG^FEHFKNGZJLTKLDMVJTFVGHGHPGJL`PL\ORQNPPORSQPLPPPVRWXWXSP\PVOVNNPOMVUObQRTPNKLPNVMdJPKKHPLRIXIXFCA^FFBEBRFCEDJEEBPBJCHPGTHHGEJjL^H`IVE`FFGEDFVGKKJKCEHHbLJNJ\KfKM`PNRHRKdOPdLINMTIJPMXHZKjLKJIXHJfH^EHREFIPD\CAA@B@TAXCB`AV=d>R=^:=V>?===LAF=^ABd@?BAbA@NABLBVGTERHHFERLJIHPITGGfGbJF^FCBdBVBVC@?b@@@?dAL?X>=@VBN>@;;`=f8T9V94R754\4f311H32j0P3P/0`,-R0R--P-`-L-../-H0,-R,+P/.T-J+Z,+N-\.D0N.X,B/P-/.11N1P/P1X/X0124V31`2^1D0^30L23N0`0N542^60`020X/-.P32J3f3V0Z/1X/0T/P-T.-,\-\-/\,R-R.h/-.X/V+P('*,(((&*V'Z&%R%^$ "V$^"#V!X N PN R`TRTVVVjXPV\R@NXdRV T Z J ` ` X \ ^V P>\ZRdTh`bThVLX^`ZPT\R\XTJ\ZdV\T^fbdbLh\P\B\hRT\VPfZbdZZPPZPF^F`R\VX\R\HZ^NVVhPX^T\Nndb\XXFN^\ZVTZVX^Z^NZd`X^\^VlRXZV\\\^V`bP`Xf\XH^LTVRJ^THZZRXV^PPRFhZ\TXZRVXZ^XXV\\\RTNRVRTdPbZ\bRnXhZf\\`^bLXTb`^bXPNZThZ``\X\^XXN\^V\bdZVZVPXX\^\\ZLX`RH`\RX^^T^`jXPhPZR^L^\TZ^RZ^XXNXbNXTRZ`d`\TbXR\VbjVb\NVb`V\BJP^ZnXV\\\DRZZbZdZZLX\PVT\^\Vf`NNHVZT\P^^\N\\ H ^ P Z T V L \ H ` RP\VNTfTNVJ`ZVb`Tfb`LL X !! V% d"$%F'$&f(V)L*+-Z,,.-00+N/0/\/P0l2`2^32^4^75X7N86865\6^3f4655^6X66d6R:b:V9\:::;Z?87^7656N6X5X57;;;\==nAFAVC=A\BdA=>?LAd@L=>`A>TCBDC\JLTLHOORXM^NVOMQMLGZL`LIKJKXJTNJKZNNKM\JM^NMbLJOdIRKFVGPFXEEBD\CBD\FRFCCHC`FEFDPJZGFXFLIKGNJXHVJXLNMP\QXUXSDUVQVTTUZX`ZYZTUWZVZXRURURTXQRRUTT^WUHVVNJRhRPRSXTUPR^PSOT`Q\MdNXMXI`IjJ\O\OVNBLLK^JLObJKOKZL^MZLMPXQTPdRbORRBRVTSVQP`NO`ONNNN^RVR`PM`QPOZMMfPNNPONKSPOZMbNM^KKKXLLOJIIJKMNNJVLKK\MjL\MVKXJKPNL\NZJLXMLLXLKONJMVKQLPNP^QQZUTWXYL\T`X^a^`\a`cdd^^X_T]\`]ZYJUZVWRFT^UTUjSFRPO\ORQRQTQPSRQOTORRRSOVTVRPT^URPTXHP`R`SRTWRRQQNTNQMP`RTRZTPS^MQ`OMTOROONLXMK^OTKNKTOQTTNMRHObNMHKIbI`N`LdRLMMMMZMPNNPJVMJPXMRM`OMNKJOhL@R\MKOL\NP`QjNORRPPSXSZUSRQ^RPROLRTRTRTTR`TVfSVPjVPSVTRTSSSSSRURROOLN@L^LKKHVKK\JMLVKRJbKI^IJXIHHJJZKXLK\JZJVIHIVKJbHTHXIEFFTE\EHFhHTIHJ`MZNKNKVKFFJKRKIbL^KLNJPMOKZO^NPSbQQ`PQbQVSSTWUXUPRQNfMPQRPNPZTRTPXONKfMNKLKGMM\GHREDC`DAZGZCBbDNDDZFCDVDDEEZINJHHTFRJ\EEH^IJGGGZGHFINJfIGJHGNKJMVLFdNNVM`LKfK\LLLKNIGILJXLNJJI^JHKXGTIEEDF^HVDC?`BVA\@ADAA@VA>=^:AL=\=2>^?;R;<@@AAjA?TCBA\DXDFBLFEbJGXHbHJIGXIVIIFRCDXECDATAHAZCRB>B@Z>`?=>>V>X=>^<;FH\GXFFFTDPFFI`JIbHMIMZNOdORZQNP\RQXT^RZZWXVZWRXVTZZTWTY^VdR\RRSTSZSZTURSRTXTPRSPTXSTHQVRVQPXQPLZL`KLRNKdHIbKKbOJKZKPXMM\MPM6NNPNNHNNPPRPdOZROTQVPSVSR^TMMTPJOMNNOQMVKZP^OLLMQ\RRPRNKTNLZLKKRNKM^NLOPK^LILNJGZMMJZOfLKHLLIN@Q^KKXMIPMLLHN`MROLNfMPXQJPOTS\UWVZWX[XN^`J^`PdgR`^_\Z_\_Z_L^]\TWXXWTXVjTUXVPTHQLOTSRSFTQTRUfSQTPTQ>BAT@APC?A@T?Z=f?`<=>R@L=^ZA>D?V>AX?>@VA^@>J?^<>X>86L765L65f8`5L47R3L21N0.-/T-X-D,f.+\,./R/0-V-*\.-T+(,,-P/,--V/,,*,,,--11T2/N3b0f/552J240F0.J///30L3b02N102T/X1b-`20//Z2///3--/T.T.-X.V./-R/-/X/0+N,,*^()'X)(Z&%&((&X&&^$T!#!b#"X!J"\PR^\d^ZFXR`nXbPRXL\ B ` X L L X  X T^ZRXXZNDTLfVRVFRJ`VLd^RRdPVLJVZ\`ZRT\\TXf\XRTN@l^dVZ^hXXT\Z\<^FXTT^RVbfZXTf`fLf\\X^ZVRZRX`RfL^\XTbXVXTh^NXZN^ZdVVd`JLLVb\f``XbZ\N\d\DX\X^`XH^T\Zd\Z`PZZV\DZ\RN\ZPLTXPVL``^dTR8PdV\THZV`TlVRBbRN\^ZVf\L\V^bTPdVj`lH^Xh\V`@\^^PR`LjZZd\TZ\VXjZ\fbXf^XV^TXbTV^XRbdPbTZ^bV\>RbR`R\RTZ\bVbJRT`\VhXRTRNZf`VRRZZbT^N`P^fhLTZVVX^\\V^lTDNjHTZZTLT\V`ZhVTPVdVR\ P B X ^ Z L X \ L N b ZXLLbVZLHDNP`Bh^\ !^"6"Z""V#$#N%N%'Z'Z'*V++,/\0D-V+T/L12.Z00L30X2V434P5X4784P5d7478T7\6Z9L8V64`3X7`6T:B97<9V9R8R;9:R:7R6R58T957V89d;V;:=L8N:>^;>N=:X9789Z5j533V5^530V32L5h7L5R55P556^636^5N2P42Z22\3V56R54P79;@:Z?\@A>bBb@@^B^?=X>?Z=<>X?>@@\@PH^IIfMLSR\ObN\MINOXMVMJLIKLNKKGVGLMhOTPNLJMVPZKKII\JGFBFCFFXEBVCEVFF^GDXERG`E`IZGdIHREJG^G`JGbJLM\JMXM^RMKXMPTWVWRZJYYF\VXFWUV^TXUN`RTRRTRSU^YRdTPTRXTTRTOfQNQPOMHLINNKNMKIIVHNTKM\KLK\K`MJKJLMNdQO\RXRSXQP^VPWNNNQZON`SJNNZM\R\LOdPPOfPNdLLLZPOPON^PRMPJT`PNXLKLOTOPPVMbLOhLKLJZHJKJVLJRM^HKRMFLZMMMTKNIZJZO^KLLNKVMVPKZPNZMQPSOXUVNXZ\[Z_N[T^`a^`aZXL[NZL^f_Z\[XYTXRUTVTX\VUZUWFT^SXVTVQVQVQQ\UR`TJRXWSSLVFXU^UPXXOVXRNTXVPTRRWOfS`STTWPR\XVUSRSVQTVRPPNOLXPPOMjM\MRNXMZNXOXPXPUVRMXNfMMO^O`P\NQJQOVONNQXMROMRRQMQRRPQMNPRPRKONPNNRQNLTP\ONOZS`RTRSRObQVOPNOPR\S^UUXWRUTTTTWTVW\ZlVRPR^RPSPSPRRTRLhKPMP\KJ@JbK\MKDKXJLNIHLLZKLMJLbL\JfNJVHNIFERFGEDBZDE^EFENE`DHHMI^LNMKMJRMbKLXMNLLLKRKK^PNPQOPLQZOLRZRTVQU^WUTQ`O`TQ\OROOfROMjIXLXJILM^LZJRINGRETEABCDDGEEZFHVETEGLEVFKG^IIHGRFD`HIZIHNKJJKJ^ILZIGhHLRKjPKOKZLKJK\MKLMHJNLJHNHRJbLbJHKJRLXHGbCE`IXGGXIG\GJBAAN?BHDfACdC@A=fB@Z<=PCN<<=V>=^>d@X@\ETDAVA^CADCRChDDTEZEFFRGGRL\IHXEJHIGGHEVDHEdA?AZBDAbA@d>=^=ZAP>>T=Z=:>==`:X6Z8\6L9b45\65Z35X20^00P0/,+V-/.^.1R/h,X/V//\-..Z-R--Z-+,R-+P+L/Z,,.,L+*+-\-N1d1P/Z/0^31\0Z203T1^51N/.10f1T1b1/0T1F20../V/T0-b0/0/31.^1`.0.Z+-,//V/.-/V/++)Z**V+(*+&&X(d&&%^)R'L($$#!X#!R!R!JVV^PX`ZJZ^^XfDTRd^ d L Z \ L f Z R Z` ZX R ^ `VhNZ\^Z\\VTVX\Zl^\\Z`VX^^HPXdLR^LRbVf\Vb`X`bR`VnZXVTFRR`\X`\TVXV,\`\ZPZD^dR^R`VfXT`Z^J\RVjJVHRfLP`^VPZTRZXNVJVRZ`RXP^XPZXXT^ZVP^LZZZPT`bNNV\TXXHX\\`RJXVh^\^\RZfXXR`NPVRZ\fHX^TX\ZdF`R`dVPdhP`ZTZVZZfh\X`\ZR^Zfj^\^dZTfNbZhX\h^^^fVlNRhfXfXhhp`P`JPHX`TZZFPPX\^PX\R\NXP\PPbZ^V^PLXXVNjV^ZPV^FLLV\bX^V\\VNRNVbH\`FNZXJRPHZ`\PbTXXRPZ^TVR^^XPX`VPT>hTX\`VR`H^``dXFRNB P X T V R Z d P L X J d Z V` XHVTP\RPZfRP  X!#!!"!"%Z&\&%\'T)(X)+d,+R.,V,N+\0.Z/,0L1/R//N1b3544X:\765^7975R6X5f64\95`56Z6658V:<<;:;X;T>=8;N;\98Z7X:95X4J845f5Z3^3R343535L5V84^85T33\3H434`15H445f3R679f;:N=H>V?>AH>NCB@\AB\BZ@>=J>`>?ACDJD^HKbOTNNSXPM^MP8MOMOPIbIHKXILIK`JVM`NLRL^LPQQOTNlLJFZHEXEGTITHVEAXFAEPEKFHDGhDHHTHHVJHIRGXLRKI\JJKIO`LTQLLPNNMZOTTTVWP[^WWZU\YTWVUNYRNRSSSbTPTZY\WVVVQSSXWWSXRZUSQM`PLJNdLMKHXMGGPINFIGPHKIZKLK`LJLXMMROPPXPPPPQPOdNMDObQNPZOPOVMPhJLPJRNMK`NNdSQ^QLVMRNNO\OXMXK^LNK^NLLLMJPHMMVSRNLJXJVINL`NXNITLIJH\LLJIPLLPHXHKLL\ORNJLXM^LVPP`NBO\PSTVUNX`WX[Y]b\\Z]^V^]R]Z[ZZV]_X_^b^]F\PWbVU^VVYJYTWSWTTRUXUbURVVZTXUXPTBRSWTRRQPSRQNPTRNSXS\WLV^VQRSNUVUPUPUTWXUW^TUVXRVWTPRRFTTSPOO`OQJQXONP^NXLMJPPfOMPRfSZQTT\MUVOO^OMNRSPRdPHQT\O^NPZQQTSjPRSQV^TUSNQZUOQPOSVMOSTPNOONOOXOQNQTQPPHPQRDV\WYSZ^WVWJVNV\U`RLSPPXPOOVOOXRPQ^L>KRJ\J^PJNIDNdKbKK\IXIIHRJLJTJPGJKLXINPJMTIF^CCbCCAVCHFEEFFGHXENDEFK`KLKHJLPMLNJ\MRPMTKM\MTLVJTJLXPQhRZSVSTRdRXQTPORTS`TZTXSSTNHMPRPPONQ^NTIJbIFDDFGIILJGHTFRDF`EKLKNNIGVIPJHKPJJbLNNJMMNNLNKTKK\LXM\KVKXIFPLKLLIZH@KXGHICJH\HTJRGJGdDTGA@^C@XFDNFDB@?B>V??b@N?\>?d=;=Z??P=>?T>X=X;N;V<=;P8`<9V6X44R0\64\31/`1/J0d0.-V--.-Z.0\.d+^-L-/X-\/,-P,Z++.*Z.X,V-,b.^,L*^,\)\*/b-^,-10.0^1.1P04T0X3b/N1Z101102012001200N22J1101L/`/201X0X-.1-V-T./--0/J.*L+R)++'L(( *H(b(Z)L'\(&R)V%$$\!L!!\ R"nF ZdJV^XVVTJ\R\\^VZZ \ j N B P \ \ T N Z VRZT`X\lRX\XZ\VVVX\NdbH\ZLRdD`XNH\R^`^hV^ZVBdXhbP`TX\VR^XX`^RdRJ`hTL\HZZRDTVXZX`T`TRVPXfPT^n^\ZVZ^NXXN\Z^XXdX`TXVZRFN`BXjR`PhRRX^h`N^V`^X`J^XX`RZXd\\PTP`^Rb\P\hVRXXXRZRXV\TfnRbZ`NbTbZV^`Z\fT^R\bb^Rh`ZXT`Z^lfR`b^dXXh^R\bdl^BTZ`dRfR`TTV\^bJdTXXhhdZX\XXZbVVV>R`Pb\\fPZRTTPH`\T\Zd`b\^LhTRR`R\PRXLPBX\^^P``Z\ZP^VPVXdT^NfH\nFPRXZTbVRVTV\TTlXRZP`\^PLZfRXZLNP d l ` R h T V \ L Z X ^\RX\TNR\h\\XV6 #T ^"H!Z!"T%%\%$&$'R*Z+d*J-T.d.V/,Z-0J/.\/0V1N1X0.3V245b;P7V86P465V;H8b;N5H57V52R5589V6R:9\:T::\8^:^:\85X8J97^9L9`77;9:>RBX?P?V??=\AL?BCV@b?=<^99P??@AZDCFLLHNTONPNOTIK`LLZMRINLGHKGPKVOTOPLdNLNPROXMRZO^NfMF^EbFFXFZE^BBNAABDGRDVH`GVFEFPI^EIJHXHKK\KdK6J\OKOLPNZLPROOLSRHTRVhZV\X[YXXdYNWV[URUQP\WZVVSSRTSTRUTTNWUVUNNRRTTROLLMO\OFTHJKdJFVE^FIVIZFRJJ\JhIKLLTOXSMRZPVPQTPXQ^NTNLPLMNdNXROVMLLKMLPKVNLXLLM^RPRRTUNPPPMNdPMP^PZMLMVK^KPbNLKML^NKTNNKZLNMJKLFdKJNMLJNHXIMKVKITMKVO^LMOOdNJNZSURVYULU^VVLZXYRX\[Z]\`^YZ]]]^^N[P[`[WVXXZVW@VWPWbTUWDWSfULVXWXWULSXVDUS\RTWR>URTXRRJSQbRPQJQRWXQUPXVVVY^UWNXXYXUTVXWTNTU\VUVRHQZPOPONhNXNOVPRNPTQZROLSPSbRKMOOQRQ^R\UTO^QShTRTQfWWUJV^USQOTRSUPORRVNXLRNNMO\M^PQPQTSQbRZPRZRPUUTZVHWbWXUTRSRP\P`PTOQZNXN`QbO\OOTMLKINOKOZLITI\KHHILLfKLZKJJKRJMVJVJFFPED^B`BF>ZCDNFLFHNFLEFFGJRGJTLTKNNMTNVLLTMNNVNRMTN^JhJJ^JZJM\QO`RRQUQS\PMXPNPPXSfTSPTPOLN`QQbPPON\L\JJJVI\QJ^JG^GF\DCTFhENFNEDZFbGGRF\ELH^EVHGFGHZLVIJJFJJNHNHPLKNKI^GLHJVKPMbNXNMTLPfMVPLLJMMfNJOIVILH`GTKdL\MJIG^FXDB\EREJHLEDXB?RBDPGDXCBVC>R>\B>??@XA>H>?X=Z?;>Z:V<:P:N77\3X6T972^423V1d3b/.//.L.+0R1Z-\0-^*T,X/.X/-T0-+`,L+,+,N.R.,Z/,X-*,H-H-.-B/-N./10Z120L1T0V230\2h0V0131X1^31`1T210/.X/d/R22/10T/X4P3^.Z.X--T,b-:/-.-,R/-,+X*N+(^+'P)(X(R'B*P(&'((N%%#V#!\!X"H P`!BRVFHPVZfR\RX\d\bXDZNpVTRRRPL \ \ J ^ T b  V `  LXTV^\bTbXT`TTjR^PZR\JXTNTLXdNV`TZTR`JZZTL\PZ`XJTZLXPjT`ZZdbXbZX\\R`ZP^\PPbLbZ\X^THNNfP`fX\ZRX^T\hN`\VfP\VbRVX`f\Zf\Vd^^\XTVPZ\ZZZV^`^`Z`^XXXbV`P\Td^NV\XddNdTL\TRb^ZfT^dVbXjPZ`TTVTXTZbT\T`LTbRXTHNd`ZXVXd^f\^R\`NRZRNfRXnVjX\TZdXXdXJJTXVV^TZZFbLZXRXb\^\JVTR^PR`TbRV^X`XVPR\PNXRZVNPVZZZVTNZJLLf^\HXbVbR^VP`TVJRNRZRTZXN\T^^BLZ`^fTZpTJTLB^RNbXbNdNNJfjTFLXP T P \ Z X X X \ P<JTXPVX^d ! F R ^"!B!\%""Z&Z$H&&L(P)(V*,,.-N/Z-/.f/.\-0/00336666b6N6f6X94`95434355f8@7\7\8::9;T9?:V8H7X:X66P7:9T>;87^:B;;R>>d:=<:7V<7Z:d765b66\336433255253V76h4h313`551J4d24364R4X5T6:=><>=A>\@XATABb=T:>Z;b>PBR=V=>@@ZBC^DXBABDREJEH^GGTDG>IFJVHFNGGIEZGRGdECE^F\A`FFBBC@XBAZ?\?V>X>^>\=<:\;<:D99F:8`675\442`19`4N67T653R7V5\643^3X4555J420^4f25N5^53R7X;9\?Z?>X;@>^?JCBX?X?V=>V:;P=>?^FL8ETKhILNMXLZRMNOZO@K`L^QVTSVUUNTZUP\P`QR`NOVQ^VNQKITKRLGJRJJGFFbI^FRGZFIPHIIXKPNNXPN^MTKNOMTM\O\O^R^LTN`OMTN`QRMLJMKKMTONbNMTSSPfQMPNORFQNQXSUOQQNKZNMKTNN\NHLMO\NZOLQRNHPMIfI>\A<<>A?V@AB@?HCPBFHG`HXJHGGVIFIF`KGFfGZGXIdIRCZDAXEEC`AC>@TCZ@=X>V<^;VN<9X;P<;J9V7f5Z7V6433T/b2P22Z11/1X3.X0-/+`0-\-,L-R-./.\1-d.+/N+X(J+*N,R/,P,d+*+L-b.//T.-`3.l30/0^/T2112313D.0R5001b02J2/.T52R/X0X2X2^/F/^00J//\2`/-,^.0D/,.\+-X++H,T+V-*`*R(*&V'((('`&%R#X'\$R#%L#R"R"T\RRV^\^ZJRVTX^\RdV`VjPh X T ^ \ T ` X f \ R\^\NPNhZf\nLZ`NRR^PP^^XNXTd^LJ^`dZ`VPZ^bLZXTV^VVXfPTZjLVLZTVD`VRbVd\JZZRPP^f\VhZV\`fL\fV^\TVXTdP`dJ`Xd\XTfJTVN`^VR\jRX`bNPZX\fNX\\ZZTdTTPTFddZ`VRXZZRRXJVXZTPT\RDV`L^\V\RjPHRZ^fV\XVRVVRX\bdXd^DZP^hR\VV\\TX\\NPRN^bVXbdb\XJZbRTXTbDffTdZR`DN`ZTd\\nb\^Zh^LPfdR^NPXV`P\\R^PTfbZV^VXZd``R`dRbFXVPF`J`b^Z\\LbZHJP`XZPPXJ^^PdN^Vd\PTRH\V\l`Z\PXRZTVTRNRR\ V X \ T V ^ V X ` \ T PPNFfTJ\^\d\VVZL !!X!!D  L!T%R$"%X(#(&',X,R,0/-T/.-.1X/@2`/12/2b4H75F74475\67R9T57643237`77\789X;9;<<CF@b@TSQPXRPPZPVPPKLNOPPLQhTQQ`N`Q\MQO^PPPbPZRBSWRWV^YNWZ]]L[\RYZT[fYXVPWVVNSR\QXOPHNQPQNOPSQPQQS\TXP\UTU^RRXXZYSUPQSRTRdNTOZNOLMVLNNVKHKFZHFHIPHGGED\GVITGKTJ^IKVJI^JHGFRINHPGRFHlGVGLEVCDbBX@JBb?@BBTDBZERF\I^FRGJHJ`HMZOKMOZLM^NLOGVIIKLZQNPMOOV`PN^ONPNNJVNVRPMS\PTUXQVPOOXPLPO\MNLJZIHLHHH\EDZEHVCBEXGVHGdHFTFZDPGDHJIHH\JVJHLJXLOIVIJTJXJPKXLKPMNL\MObPLPMMKTLVJHL\MVMOPQZNQ\PK\NLJPJXKH`K\HHFRFIFJFFVJREFjCADBNEFGACC?\ATA@`BB^CVBV?H>;X:R;P<<<8`:`66638X3d4J31X050T1L3^///..^.-J+---`---.+-,-.P.+))X,V.-,++*-R/0-000^/1J1P1T/T0V2T3P11R3P3T40/P412P222L1\2T2X12/X/11L.P1d//111.V0`0J0,X.V-T.V,-X,*Z+d+*P+P**B)Z)T'T(%b(V&%%\&%d%V$Z"X$"V"! PV!d`RNZZ^b\RXbTjPdN\BZ \ V ` T `  b NVLZT`\fTZNN`\`TfdZ`RVV\VRh\T\^JVRZTTNVLPPXbRZ^bP\^\Z`R\VPbbVV^VXZZ\T^ZdXJTVXTfZ\blRV`P`HRZbJ`bbTX^N\RdZLbR\XT^V^d`\RbZVXL`N^\Z\LVVH\^XRVdZZJVdfL`TF`N\`LfddXXN`XNXhTV\^NRNJJTbZL\dNTVV>TVZJ^J^Z\\ZfdbT^Z\`^\dj\ZPbZ\`RffLh^`Vbb`bZ`T`Z^ZdjR^V`^^\X\``T\`d\hTh^`\RTf`T`^VBVNRVPTZ^fRVXNZ^d`TVT\TTXZTfXb\^NTb^ZHbTZ`X\DTXb`dd\XRRRZ^X\ZJLb\X\VpNZZ^TbR\\HX^HXX^XhLTRlTV\^VRRXPb R  \ J R V \ R H Z \ V VbTRd^NdP\PPJ`V `" R^ !X$P#"X"T'^(%V&)))X+F+L-\.0f..X.N-P///2-0303`7d5^9T55T66`5L5Z4d7f33T3^3X2363P7d79L9\>:T;\=\;<^86V99V68H:9:7H;T<>R?>>R:AV;;\:P87939P63`25X33X44`434d774Z3364`5X62X5R5R3R61X1253N764V;7;Z8;n==^@ZCXA>\D=F?N<^=:Z=fSUSUUZSOQMLNMM^LKLMPLPOOFONPTV\WFXVVUVXRZBVWV^WURWYPTUVSR\TbRPPRQJORNPRNMPOPVRSV`RVQZPQZOTSdNVRROUSLV^UUUSDUfX_\L\HZXY[TZUZV^VZQBPTNMFLOPQOR\TZRS\ST\SbRPNTdQPRQOdVTNUTHQP^OQRPNZNNZKLLHJHI\HIEbEEGXEEGLJ^IJLIXMbKK^KNIVIMVFGJFF2GENDPFXEBA?AXBB@TBDFE@THHFJG^GGjIJXLMNQRNNPMXNMJXIXJ^MKTQOVOPLOTPfNN`OMNMMMTNZONNSZVRRQQLLILNMXMILJHF^D^BTGbEZFEHEbGXFPJDF^E`EERGXGTHbI^HXKM\LILFK^LI`IIDINJLJBMJKLNHNKRMbLLHLMLKVKL^MO^NRNSNTL\KLK^JRLKNERIVHGJPHPEbHHVIDEFdEJE`EFENBCBCTD^ABXCV?>AVC@T@N>@?V=\?\C>>ABRB\BDC^EFPHFFGHTGEFH\EFJGGRFH^GLIEbGFGBC`CREEDEZAL?@BdB>X=T=V>bZTTV\ZZ\hTnZX\R\XVX^\`bZZHjPfV\@^\R`\Tf\XTHV^V`^VdTT^TdnXVV^\NRhdTbZ``\\ZVVhbRhZT^ZVRNXXbZF\Z\^P\ZF`Xdf`P\bd\THf^^f`ZXVPZlXX^T`\bNnRV\PfX``ZX`Vb\HhZ`XNb^`PTV\P^^TVZB\VLZ`\bPXTV\XHfD`VZT^XTJVbRZ\ZVTNRXRJ^NbP\TFNT\XXXN^NXZT^NF\h^LZZfRT\RTNLJ`V^ZX\`N^dZRVVXT\XbXTZXP ` H  L < X L R T R T NT RZZ@d>ZPDVXNXNRR R!d!XL" R!N%^%&$T''(*)+P--\--Z//P/L.V0/.B.//0^1P4545R755\:L5P:4D3^4N5X413J6V:Z67T9:d;V=<;?<:8b:b9V9V:R9T7d8\;97F:V8;Z>J>V<;`;9:P7;X7N7H7B4T2357P4P5X63555444P1L5`6J74^6d333414V7\7X87V8B8N88\8X>:>@`>@RAV>;=?>\;Z:P?9T@ZDVDHCJKH`LIMPRQVLLNVHZK\INPI^FITDZHVGRDDK`JJMTKOOMMRGGPGJ\GIERGGCETJbFPD`BZDIDHLhKTHlIGXHZIJMJNMIJGRG`LIMfLTOKNZPOSTPRLVTdXZZXXTTXWU^USRTVXT^UTVTU`SRXR`RSWTQPPTQPVOMOJKNJPLIGMIKXHRFZIPGFHRLOVLBNdLHXKMNNMTNOdNNOPNOZRNLZMZL`O\RHOMOTRTQTPNZNRRZQNRORPT\TfWVSMTRSXUUXRPSVPPZSPfPKVN^KKLKM^QVMPN^LJKKTKZJRLLNILKJLOMOQZONNMNKMRNPQPOORPJQRU\WTP`[\XdVXV^TLTXRSZVVTXX`ZY^Z\[RZ^[YYWXZHX\hXXXXVVYTfUXPRVR`LMTLRKJNPIMbLMdMLLTNQOQPS\U`UBVTY[[Y\XYYYUXXVPZJUSZSUVQZObNQQMPSPSRVO^UNTRVPWQNTPSBBARANAF>>AL>VDBJBD?bAT@@BC^F^HCBH\HXHRJDHDH\ERKGTJHZHJTJ\FCD^FETDCBAZGXBZ@@PCCJA?V<:d;8N;V8;79Z<98V566^::;9d9;=;X=?>?>==R=>V>@Z@AVDERJhGFLVLbOPQbNNJLI\O^INJFI`DPHGVGZIdLPKMfMLMZNN^NKLIZLIbIHLEZEF`IVHFH`EEB^CHHHIK^JKJLI\KJ`NPMPNKJKJVMNNLLLXQPOQVUTQSRTNTW`VTWZYRUNWSSTPVXRSVLZV\XVS\UQSVPRQTNNSPP\TRRQNNdONZKPLKOXJLHITK`LFHIGGTIZJPITNbLJKIJNMLVMPLRMXQOXUQUQRQRN\O\PPRPO\ONXQNN^MO\MMZQRRXR`SYWZZTTY`VRYSTUWXRO^MRNRLNMbPLTNMMPOOOMKBLlKKZSXIJfLHPO`LOPTMQPRQTPdNLJLQMNP\QLPN\RZSUQTSNP^TSdRTQpRT^XVWJVZZZZ[Y[X\VZ`W[`ZF\[VZX[^WUYWUbUQ\NLTLdLKJJNOVPOJMMZRNMJO`QLQRTUWX[XXWZXXJ\XTVWbXWdYNRUOZMJRLNMLPOPTQQTXRFSbSVQbP^TTUSRXVVNXWWThVYXZTYVXVVXZ]RbTQQbSZRXTNXLNMVPPbOZOSRXRSUZP^TJ>h`9V;R85V6J3^8233b323X3N34P1/0^0T.Z1R/d2Z-b0.R/,V-X1T/,./++d*R-V,*X*H+N+-F,X++P-L,`.Z.N,L/0P/12\1\/2-J2T23X2Z01.P/`/0.//Z2T1`1X2Z3`4X0^/3T/V2N2d1^01Z01.,.T/J.V/Z/-,-`*+J,*,h**V*Z*,L*X)`)T(`(^&L&P&&`'N$&`&%"\#L$$^"XX `NfTVZRZZLZTLX^XV ^B`Z V R ^ ` b d Z Z\Ldfbbj`NH`fPbL^LZ`VXXJ\\`dXVZjNnTXTb^\\PXR`^PddhX`VdJ\J\^PXPbfXdXXV`b`VJFdZVTb`Lf^`LRlbdPdPThTVP^^RHhd`L`bPVbfXL^XNNdRV`JfZX``J^dH\XVRbZVZ^LVR^VbVPXb`NNP^ZJ\RZXTR`NJZVPFRP`L\tf^^XdX ZVVVV^nXLT^^b``XPRVZNZRTPRRLTjVVN\XfPZR`dTRV`\TXVbZXFTRhJlZdXZLb8`J^hV\fTTFPhLZR\VXXZXX^V\`\TXNRL\`VTDjLbZXPP`ZTd`H^^bZVTbNTFXVZfbZVHXLRR\dVT\XXPJXbVTPV^ F d ` V \ P H N L b R X ^ X R f ZVXLBVhRjVV "Z!P"T" #!T%Z"#&$X+D'(N)\+J-,\/,.N101V0\//-./J23/`426N768d6b6j86X756`4V75`033776R;V<P<:;8::TH?P>?BCXHXKJILdMVQHNSMRHLJL`I`F^GEdG^JPGJL`LMMMHTOXKIVNMKJNGHEbHVJHFDGTFXEFCNIXFTLGIVJJMKRJVMJJMJLKMfIIHJLJbNNMObSZRSTSbQR`RSJWVDWUPV`ZXUVQJVXTRLVUJVTZQUXWLPLNONRQSVOVVLOLNLPVPOP^PZOHXKIdIKHIKLVIHIIHNPLTLJ\KLQbLKKKVMRK:NN`ORNVRQNOTPPNZM^ObPM\ORT\R`ON\PQP`V\TXRUdVVWPVdQ@SjVR\V^[OTPRQQONFONOQPROOXMKVNPO`LO`NNNNObMXQPQ^LMPbSTNTfPNMVMPPNON:LTQXSPS^PDUjRPfUXRTOPRTSXUUWZ[XJ[X_Z\\P[SXZdXWXZXZXZdUJV\W[N[UUSLMLTJVKNLOXMPKMTLNTKXQPZRJQOTLTUV`]Y[^[VYdXYLVXWSXZS\VUUNSPOVLZNZOLVPjSO^Q`SVRQV\SLVdTfST^WVWWbYZWUNY^X^WX^VTVWSDVfUTTURTNQPRPXPPQLQ`QQPTNRPR`SUXSNMNLQZM^JRL\L^NZK\L`OQ^P`SPNQLLLPJRIILHNF^GGITFCB@DdEPETMLXJVMHJJHXJbIIDDDDDBCDbBNCXDfETB`CTBCXBBVEDLFGHZHMLLKXNL^NOPMPZNN^OLMNNJLXOLLNNMMdOLVQPQXPRP^QRTOOOORRN\QNKLOKIRKEZFFRCEEFCbGGGDXINFH\GGIJJLXMKNKKMJLPIJJZHXKJRNhMN\JHLKMLPNNZOL`M6ONO\O`PP\PMRK\ONTKdIFKTJbI^LLbIPH^JLGfHIFJdFPFVICECCBIGTFGZDVDXCLDlCC@R@TAPAXAR@>L>=@\@@F?C@@FFEJH\GGZIGCdHFZF^KLZKJ\JGMTKbHRHEFD^EXECBXFRIZCEVABpBFA@T>?V=X>=P>=^?>b>ZBTB>R=?CBGbGGIRMHK\ObPKMKVJI^GJJbHEbIENH^I^HTNRKNLPLVKLHMTMTLJKKITGNFGHFFFFXD`GGXITFGZHIjH^LZMLXN^LlOIGLLdMKHXH\K`ILKdOPPQOZUOVSR\RTbTV\XNVXVRXRUNU\USPXZSVRSNRQQQMJXKSPPVTOZMRLRNlOfN^NQTOJKdIHGF`H\J^MJ^IKRJJZMZM`MbKRI`KJXIJVMNTNMNNPTPQVOPOSLORNHPLNQLRPVQFT^QVQXQSQRWPVWUYY\WWFWU`TUTVUTM^SXNRM`RTQXTXSLQVQZPP`ORPRPOhTVNXQOVPSRZROMVNfQJNPNOOOORLQOPPPRPZNfUbS`P^OROTVPVQRWS`XXTSZVZ[ZPXbZYVS\XP][]T\\_XUX[Y`VRZVRDO\MbLTJXMIPKO^MXMQPLNOQMVQTRXYRVXVWX]\VYRVWVTTRU`URpQXPXPPXQVLPTOXNZURPPUdVTQSVVUXWZXNXZYTYZVWTSRWVLSLVVSRSTSP^RUONRQDOSMNPRUPR>TRTP`VNVTTSfM\RMNM^OKLKTKLVM\NXM`NNXON^OLLKHPJNHNIIZIHFEFCjDEHGGVLH\JfHZHPITJLJFIbEABC\D\HDPEBDBDEhG\DPC`ACDGFKJJ`KJLIORbNMLMKNPMKKXL\LLLVLTNOMZLMMLXMQPQLSROSSTSR\QXOZONQRM\PHNRKfLKMI^I^EZDGFF\JFDG@GGFEHPGXJXI\NJ`LZKXJO`L\KZKZHGXIK\LDMOSXOZLIMLK`RMM\ORNXNNSTQZP\OPLPNVO\MTIGHILGNJTJHVGIGZGG^KPIXG\KFHCCCFJEfCbHFCDTFFdATAXEXARDPAB@CXAVAA?V?AA^DBLAfCCDVEZFGJZHRLHVEDNHKHfLNKXJFNIJXJRJFFHF`F^GBCREF\CB\DN@b???Z>@Z==X;V=779L57L4\253621\4`310b1\1P4T/T0H.`1d.-L-.`-,-^-..\.X0+V-\-P-+V+^*,X-`/*\+--R+T0/.P.\/02^03X42.0f1`/,\//L0Z,X./X1Z0.X0N2^1Z30^1P31//X3X111.0\0V.J2j-b/R.,-H+-d+h**+V,-b)`')+*(V((P('H'&%T)D&d%%R%#V$$" NbVTR`ZV\^XVNZ\V\N^\ Lb `N X Z ^ ` V R ^ T P h Z ^ \RXdLL\R^\Ph^ZTbPn^JRPf`HXJR\R^ZNdRXRXRVFLTT\X^PN^RZRRVZZTZZXZ`X@Z`ZDXVVdVTdP\Z^VRfV^rL^bV^JV`VhNRZj\\PZd\HLVf^^JZZP`\ZbVX^XZ^`R\VVRdTP^nXZbZ\X\X^nTjbjhVRJFh\Pd^b^\TXZNH^X`bZXNRXRhbVJPDJ\nHZdb^Z\d^RN^XdfTh^\TTXR`^^T^LPbbTPFfZThTbd`^VPfd^^^V`RdRfR`Zd^RbPXZbRTZLV\LP^^VXJNXhTTJXT^F`PZfVVTXTHV^\ZX\RZbPJ`JT\bPRXTPj\H\^XbTTXXNXXR\R`PfJ`HPdRTdXdT^PV`Z`H\TL  ^ b N P \ T J T \ ` V T bdXFJVNTPHRTN VP R "P!"L$T%"%$'%X)P)`'N/+,+J/L021`-/Z,L/Z,1.1`2\1T3\36\4N677Z7`66X4R4262^104R5V7d9d:T;HJB@FABBBCVEVDTHXH`MXFVJDPHHJIXMTIVLdKL@I\GF\JHTGRINIbHGFGlHEbFNDADh@>Z?N=L>@DA=d8X9T797\6P6\8315\5N2T35J2\4d3.21///R1V/d0b1,-T.H,.\-V.`/^-P-*X*Z.)(-,L-,L,+`*)T+Z+T-b0l0R.0^/T3X4V1T4Z0R1\..2f0H.X12N1/d//1R0`2/T20Z01J/1/21/1/Z2\///Z-,-R/+L+d)+))T+*F,h)(T(P*N)'Z)&F)N)'R'%%$j&'%"# V VNZTPN ZXJb\PLTb^bZ\JPZdVRTT ` P V ^ R ^ Z X Z Z ^ RR\TdVTXZXThPfPXVRRPZXVTNf^VTZ`N\\P`VXVZX^XDRXLVZZTRdZTdRbb^^ZbT^ZTVV^H^T^^XHXdVfTdRTNTV\^\^J\J\\\TVZV`ThR^X`VZJbNTr`\XRThJX^PZ\LZfXVH^dVVZPXXhNhV\VTL\`T^Z\RZ`THR\X\FbfV^TPN`DDTPhV\F``bVj^Z`bZVb\bV^R^bVdPb^dZR^hRVPdT`\jh\VP`ZVVX\VF^^TVZNbf`bXP\\`b:dPZ`R\RP^XRZ`TdVR^Z\RNR\RXTXVPV`hZXdX^LT\XVRZP^Z`\fH\NPT\XNVV\NVNP`TXTXLVXV`FV`ZP^dVTVFTNXJT `b X ` L P ^ ^ T j bX ` NV\ZJXdX^JXX^ V NT J"#b!!b$T%%R&'`((`)\(,-X,`,/R10L/,+,//\0-23206664V9\9X64T46T5L54`24/8N;<9F<<:L@>PA=@b>X@??F=P;;\@TBBTCZEDEIIMNJNLVQQPN`KJLJG^IZJ\GEJHhJJMJK^NL\MdMbIXLMNKfJHHJVGGNED\BCAVFJFVFGHRHJLQ\RZK\LfKHLHMhJLIZK`JLINNM`PMONVMNNZNQVSNTTZXUW`UTVXVUlWVVSZTP\PSNVNKMMOZS\QNNLKMKLXONIVHTHVGHRGZGHKJNGGIGJ\JZLIMNJL^MMVKVILTMLdLMXNNNVO^NXQNMZOXOLONZQOO^UURWPQNOhVHWWVdY\ZTWXVXXVJZS\TXWNUJPTPjVQbTUPRTPNQ^RRYSTQJTPFRSXTXSRR\VUNSVMPXNPMRN\QLMbLLPNROPJM^NdMDM\MPPOZVU`VRQSS\XWpX\ZY[XU^UVWWXZW^\RYXL]YPYYXVZTP`SOTMNOPLPLMXPN`NPPNNPPRVPSTRRXW\XUJXbVPTHQ^QPTLRNTSRPROPVQOZPbQLT\SdVSDRTTJWTYZUJVbY`XXYT\XX\TUXTVS`QTUTTPTOQOSVPZRQPHOPTM`OMTVRVNbTQRQXQP\PNNXP^OMLKXJKLKLJK\OVLBQMM^KNPHZHRHCXFD^GDJVHXFGHLILE^GFRDbCEFDFRFFDDFGDEVEVERHNEEGDCBDCEPHFRGbIZMdJLKMXJTNHJPK^IZIPKXN\KdLNLPZOHPOJPOZObMKLRPNQRTQURPJQRNQZTPVOPROORQMfOMVOLMH`H^GMTHGKFNFbENHDCDGIF`JDMbNRKRLJGHFJXJXJGKPXOLRZPMNTLKL^NMLMNdQNPPJOQRSQONPdOVO`MVMHHKGKI^HFEJEZFFNGHFFXII\JPGDAPBPDEDVFDPEADCBVB\EEFCTCXAAPCVEDB@@RDbAE@EPEbHF`ITLNJTJGH\GHVHRGIZIXHZLVFGPJTF\HVGZHGJF^HFFbECVFE^C@N@@?CX>T=>d:H9^:89V8V85P43P2b3R2n4N230Z11\2/0`.//0b/R-.T,R---h,,-Z-,^-\*X,Z***J+**X,/Z*L*+.Z-Z1./.2d12^3R1V1X2/N1.//X0J,/X60Z21\10/F30Z00R.123V0.1/V.N/b0Z,--/,P/-++)V*R,V+l-`)'T+b*N(X('(R)(%B%%V%X%&b#"R!R$ T `!T`VL`bbbJ`J\V^h^R\^^JZRZ VX V X b T h T X l d Vd `f T^PZVbR^`X@Zl\NXXV\\RPZddXX\RJXX`\\ZVZZd\Z^PX^PPPl\^LVVZT\XHd\PfbbXX^JH^V`bf`TR\NFdhN^V`XTJdVX^\BbffVTLR\\LdT^^hT\^Z^T\TTXXRZdV\RZ\X\X\XhN^RZZRXXTZdN\HJRNNT`^ZfJVPb^RP\BX\Xb`VXZZRPdRLRXZLb\ff^\R\^bTPjR\V^\bRTXd`J^\h\TNNV\NRbVTbZXRVPVLPXXV\NRTPb\fPXZPlR\h\Z`RVTXbNHZNPPRX\X^PVLNVXRTXTXXp\HVN\V<LPZdTZPJJf`bTTf@VNXZNf\V^bZBVHVV\bT\b^L\\TVVVZZbdTJd`RR fR \R T X f J ^ T \ ^ P X JRH`bZZjNXZbXhJh L! "^!b#"T$T#P%Z%%&%X()D*),d,+//1/Z0-/d-Z,3/10.043N5^9R856J86T461\7X6Z91X4b7Z9:T8fR886P9P7Z54V65Z6B96Z9\6697T6d678J8\8V64Z1T5R25/V2X1X1^04\466\88:>L>>@V@l?EAXBVB=AZ@d>A@@VELE^ILEIbJZLKOPZNRMLILIXIDEHRKHKKJKIZK\M^JNLKMLTLLdLZKJHXG`FVFDEENHXFCEFGTNPN^NOL\O`OJNMdIM\JNPTL`JKPMZMIMLXLPMOPLNQQHPRTTVWNSSXTSXTLRZUQHTJSPXQSPOXTMJONNPTOMPOLQO`NKHMXKHXKZGRIIJZII`LHIKJRIGNJfHGIVKGXGfOGIRMKJ\MVL`NdKNQ^OPNMNTShSNSbQQM^NMTRQVR\RRTLW\SSVSP`SQ`PTRTVPWT`XZWTTVTTXSTVRRXU`PLUNUjTRRU`SSSNSSVSRQULUUSRSJUV\TP\QMQNL`KMVK^JVMZKMZKNNRLZRNVMJNHNLMOPZQ`TPWVYVSZVTXHUSPVWTbUUY\TTVNZWR]W]XJZ\TVYU\WRTOPRQOBPTONSOPPXRRPQQPMRRPRLST^XRVWXRVQSXRURSWTPUUTRZTPZNO^OXORYVSTWU^TS\R`SVWTSUYXX\W\UPYTVUQTSOQQROORQXPRQQRPOQRQRVPSLUQZNQOBNR^O\KdOLZJJMKbK\LPJPNXPLKXJROXL`KRM\MHKPLLHBIDGPGGHGGZJGTGRFRFGRFCRGEFC\CDPFPJFEGbGRFFDFZEDTECDXB\ECRDPEEILKVKN\QNNJKJMVGHLjJPIJ^IMPTMKHMPONPOTNLML^NLNfNQ`PPRR^PROPNZSRPVOfONdNNOM^LKNIFKbIEGEEJRGTGEEPGPFCTFHL\JILIMI\JIPHG@IVMNZIJKPNPPVRJLXMMDLZOMLPZRNXONROTORQ`RQPHPKKMTKdKPOKZGRGHDTHJ\HLFFHHIITH\EDCVFE\ERCBRETBEAXBVDBGDFRGCXC\CREEEXGBTDNBCbGfEVFFFXIVIHIIGIHFENJHIHFdKZGRHHZJNGhI\GHEHGGVFEBXEDLBA^@>;T>>JN^Z\TXVbXTPddJ\>^H\TZPZLZ\LDVB`NVT\^FdF``Xj`V^`fPhXb`X\V\Z^jbRbdZ^^hbX`fL\jZXNb`bRTTVV\bZ\d`bXbPXPZZZ`XX^jP`VPZZFbZf^jZ`\^VPdZ^^\^hPZN^XT\\XVTZZXZXT\`ZFTV>PbdZbhP`ddR`TfRZVLZVRPPXJ@PZdTX\V^PhNZZP^R^ b\ Z R ^ \ ^ P ^ Z ZT\J^\fVZZ^jXZ^NhZNTZVZ X"!T!X!##"$%`%X'V('\*,*Z+-00-T/.^.T1-X-10//^00N2P4d366^754^;R6J7h9535`5451\67:^9:<;T>V=@RH>;R99:R9Z9<56L6`6d6\94R5Z6P7R7T7T;T7:^6X8X5X6253^32/^.1\10T03h55T6X7<^<>??d@V@A=?VA@A:Z@ZA\BTCECI^MKNdObRdNNjK\IEERHGTHHGGJ\IIHKXIHMN`JQRMNLbNKfKIJVGFTEDDFCHDTHZJXILLKpKRNJ`MJIRHXHQ`L^OKJN\N\LPKI`KITNNKOXORPQnRRXTWTXXVVPSQNQPPf@@A>`>;9R<9N:6X3^8\75Z:71P23\430T/X2/N./Z1Z.X,N0+X0*,,+P-L+0+,^-+^*+*H+X-/+f*N+Z*+-L+.+-.Z,d/220Z1T4p31V00V/X2R3.D0b1R12R0`2`0N0V2\2T10/0X2V5L11/3.V1Z.\--.X+\-X-)X+*X*X**+^+(d*)'Z(''`'T$&&H%Z(F%%X%%V#!L!!R"\ZPR`\VXT^Z\B`ZRPlPZT Z f N R V J X X RL ZV`RTZ\\NPJVR^PbPZfPX\RZ\V`^XXVVbZZZXZT\RfX`^X\bPX^fZ`\RVRN^VdV\RbNNV\fV^T@bXZHRb^THd^\TLTfX^bXZX^JX\T\`f`bjTNPbP\RdZj^^L`^NZbZRZZT`RLV\^^TXVfZ\\`LZ@ZXXLP\dT\VVXXRZRZJX`\X^<FVXb^fdF`\d^fTVd^\TV`RPb\XfjHV\L`LPTZ`Pb^\RZfP^Z\bL`PXZbJVfXNZZZZd^PR\TVVHTZ``^XNdZNZPRR^^\hTVbTPX`X`RZZRNh\RX^ZVZZ:VZXNlZZbZT`VT^ZXV\PT`Zb^XbR`^:Rd\ZR@TTZ  NT T \ X X T ` JhL` RJRT^ZZP^TNfTX L TL!" H##X%$Z%N%$L(')Z**H**V.,-R0/`/P.Z,T-L.Z-/J-X0D2Z3Z1j5N568999:V94J8344R7N677N98N:L9=:H@F>=>T=8V7L8N7\99V9`7X6V6898:Z?@N=\@V<9D99`<6Z3R77V96\64R5^9R6^68X64^6P8L4N47^4B43/T2\0T0Z1h1X13V439N69\BRBVBPABD?TB^@BC@?>X>?P?@BDTGEFGfJLLP^MNSKKVLFGF^GHRHH`KTF\GPGVKJMJKLTMJMKO\PM`KTJGFCGZEFNCFEZGRGdIINJL`KZNNPJLJKLBJJONLO`OTPMbJIHJNRLVOVPZOTRRYRUPUSRV:XfUUTSZSPNQQNQZQZPOOPXMMfJMJRNZPHONPPNTONMKZK^NJNHJRKLLBKNJGGGNGJdJLKIIJPKIXJNJfJNTLKNMOOPURR\OOXOZNTOfTOZZRVRRPRhSNSXTVTWTUTJT`ZVXV[ZZWURVV^SUTUTVTbW`YV\YXTYTWZPZRYTXVSURTRVTLV^URNSTLKNMKMLRNDLLKLKdLONMTJLMJNTQTRJPbRVMLPTSQdRSUXRSPRdYVV\ZWRU]^T\SV^YTWVXSXZUSNUO\RTQLSLTTRXRXPRTNTRjPRPOMPLGIGIJNKKJVMLRQNZPDOMPONHNNPPLfONNNNZNOPJO^SQRRRO^PPO\ORPNMNM`GIHHHZHVE^CFVFDTIETGGFVGTIZGHJLKIKG^IPIIIZKMKJTMJRKKKVJPIL^P\POOTQOHQPQZPLRQPPRSQOQOKL`OLLJ\LZITHNHNGLJHHGTKHHXHLHVFETFZGHF\EBC^DFA?TCBBAECFVEdHPC^CBRGXFFEVCPGClHNGdG^JKTHVJH\K^IIHPIPGTIXLXFGTLHXIIFGhGCXGGFFHDEZEADNADZBZDH>Z>=<;N@P::^5T:964D5N6V6Z37L22Z21Z4V3Z16Z1T0T..+./-V.`.`.+0+T-,+\,+P,)D+V.Z,,d,+Z,-.V/\,H-V,/3.02T3P003V4^5^11V0P/.V//R2^/11P2`12Z21T203`1\1b0X0/^//2.0Z-0@-V,V++L-R+)d)()())T(^'N)T(V'd''J(\&'$D((P&b)Z%$#!P! !ZR`NXRRZfPZXfXRXXPTXVhVZ V R \ R ^ V ^ V ^ZXP^TbZRdXT`\XTRZVXRDRX\^PVV`bVVT\NfJVLZbP\bTVZTVZb`TRHLT^ZV\jBRZD\HRP^N\V``R\NNf^ZV^````NNhj^LLb`H^Z`FTbLXbTRRTffRd\PbDV\`X`RPVVPXZ`PTb\XVV^J\VlXZZTVNf^^ZVZRbFhNR\ZTNVRZbHZJRR^`Zb\ZLVV\VL^P^bPV^Zh^ZVT^fd`XfRXXXddNTT^vX\X\N^X^NRbHZZZ\TJ^bbTLd\\`PlD^X^PbXfRRN^LJPNZX\VdFLVZVN\LhLNRZZZTZfVVPXZ`ZLZRRP\ZRZTbXRT^d`\TNR`N`fVdfRbTRdTZ`dbldfTT^d\`HRZZVXTTjX Z T N N P ` X X \ T P P Z^RdP`dXTd`PPZ !"%"P"N%%%Z(^'R(L(L*+P*,Z..X3^//..0-R/f...J40^2Z4^3Z6N7`:7:7H768N635T444876X8X98<>Z>\BBTB@d>X@N?BBTDZD=>XBR>Z@PCETGHIfKPKIPKOTNZJGbKRHTFRJGIEVHG^GIJI\MLbK^KLMOMLRKRKKIFEHbF\HVDLFE^GXGLG^KfLTKZIRIJIKJGLRK`KZL\KNMOZLVKROGVJfIFKVMRIOMPQjNRRUbWRTUSVTRSPSSSMZNKMTOO\PRQLbMbJZMOTPNNZRNRONJPMbLbKPKLOJZLMXKJMJ\IJJQJIH\INJHIdKFRHGLKKKZKTLOMQNTNS\ONQJTUSYTbV\WRPPVRUJUBVNVfT^SQYVWZVTNUTUXVXYNXZbUULVXYV\ZZY`ZRW`WXPURWd\dTSXTRTRRbTNWR^SSXQ^TTMZNNXL`J`MKJKJLKLJNOLJHLLLKVN`KTNXOJTQQ\OSRSP`TTTY[Q^WRTTNUV\YWVJUTXZULXS^QS`QTTWUUSRPQNLQORORQPOdRPRUXT[ZWWRQRQVQTTXTVZVXHSTTQXVTUVU\U^TVSTJT`R\QVRNV\TP`R\TTRRNPOQNLMObRNLQVPRRRNVOPRONPHOZPN`POMNSMOJMNNOVKTOPKXNO^OMHPbK\KKZJ`MJXJL^JJKJKPKIXINJTJZLNTKG`JHIHCVDD\BTACAVCXFGJJHDZERCXBRDC\DXEEEbE^FEHdGJKNN^RS`PNZOTMJXLbJXMMONOrNLTQ`MLlOJNKZMLMOR`ONDPZORNMNR^OdNTMNPNQVPbPZPNLPKTM\GIG\HPHE\CbGPFG\H\JFF^JVHFXIIINLLJHRJG`KIJFLLJJKN\N\KLJNJJKNQVQDPQRHPRVSHSQQP\RRRRNNLbMVOXMM\JKH^D\FXGTHHGJHIZH`GVHJHEDFTJbHFPD\BEA@X@BRBETBDENCDDXEDZGJD^FEICELFDFK\KGG`JHbIRLHXIJfJGGFHIRIIJFF\FDLGK`DTFGTERGTECBB^BRA=>@^8@;=P7T6V6699b8:V;999@?<=;9N;X;68\7P68Z85L53d65^:6d8L7d7F44X635P34P4J41\0/d10N22R74\5;=VD@B?@A@f?AF?L?L???\CI^EIHLGEbOLMNPMNJHXHGIVLF`IFJE^GLJIHHTMRMJNQPOOI\RZLKJTHZFXH\GTEPFFEHPG\ITGHLRLRKIHfLHRKJLLMK`HMMLbNKNIIHFhILKJKJ`MLOXNRZSUY@XWZUXVURTJRPMOLVNPLZMNJTJHKKhKLLQNL^R^QO`OOZRJMJMMLNTNTQTKLKLMLJ\I\HKPJJGPJVHHVH^HJGVGTMRGIdPKKONRPMZPKM^VMPNSRSUXTbRZSQTZSTTSUS`SVSPWZVXT\VWRUVYWWVZRVVXU_R[Z\UfZNWWLYYVLW>UVXVZUTNSTRPNRTVTOMKZLJXMKJPKLIIKVLOPNNPN`IPMI\PTONTOJNOPRQRUfUDU^SSbWZULTFShS`RV`STVFYRXTXW^UTTFTQVUXU=^A^=H=9\9Z876b99T87::j:8^:;:=F?><^@\<9D=@X>?XBfBV?`??XAPDBVFPITFZGZJKXNTN\MJRIXLJZLPKIGHG^I^FRFVI^IbFIIbLLHLOQMLNIKVLOHH`GGNFJG\GFDGPIfJhMJZGRJIHBHIKbKKKDLZKKKJ\HVJKHLHXMNQQDOOQPOXU:TbTNTRRWRfSPRRQhOPNNPVO^KPKJIRITKLRPRQNVQZPN^QXRNTQLjMVLNKNNM^KLLLHKEJTJHHGTJGfFH`FGILKIKIVLKXKFLOLXMXRP^SO^SPSSRQSRRTVUXVhU^WRSVUPRQRXWTVS`W\^[ZX\XZUT`WUZV^[N[XXWVYTZ@\WTUVWZWJWUUURHRZTSXRRNM\KNLJLLVHZLXLbHLLJbMKXNPNDPRLXMNMLPMORQPPRPSRRWFUbPSRTPZQPNRDURSVSPUNTWPWVUUVR^VQFSSV`VUWTUPRRP\PRTSXNNRTSFTPZUVFU^VRRQRPRLSVP^USWTXXWVYJWhSVVXRTTVVRRPVS`SSPRSbPXPUORMNQMPN\QZNNfQbP\ORVORQQPPQPPR`SHP`ORPNTMZN\OZRLODOSPP^RJOPTZUXPZPMMMLjLPKVLLH^ILKVKNNZLMRSKVM\MJJGXFFXCB^D?NCDbGAFjGHINEPEHAZEbCfCAZEAPERAFRE\FFE^F\J@H^IFEZJJXNIVIIGbI`IRKKJLMKIPMHGLEVDEXFEfIRJFCLGGZIDFVENEdFFBA\BR?=`="h!T"`"\BNXf\`XTZ\PbLZdZVR^\ZFv T d X V \ ` J ` N l TV`NV^VZb`PbV\L\ZVP\V^bBj^PfVXdh`fRRhXNVZZLb^\fbbH\X`\hNZXR^R\JXN\Vf`XlX`TZV^hXVhZbjZVTZ`\HbZ^HdPdRPVdfTVnVfZbP^ZVZ\XrF<`XVPh`\RldldZXJbV^^FHh`TZXVV^\NVZPd\bVRH\JX^ZbV\BXXZXT^Xb\VTh\VdZ^hbZj^NTZVbLV\VTVPZ^``VR\XXTR^^XfTd\ZZdXXX\VLhRLfLd^J^`TZH\T`L^`VZZbfdVHZ`P\Tj\VhRZf^NZZLNV\FZXZTbT\PbPD\PTTNVR^FTVZbZVPZfVdJ\HZLVZXHB^P\TdJd>T ZZ D ` V ^ b T Z R P J ^ d J \L^TPTVRZTXZ\VVJT !#$%X%"#F&V'T''^('L)*J+,L.b-V./1-^,X.Z4X1P,-,V1.\0V342V477T7\87Z;96l79R4d3P9777b98X:=:h>77^:b55V4V9776\::8N;X>;f<><`DV@=D?AbAP@Z?b?AAVB\DHDEGFLLRLNJNTKMXJXFIIELJIIIGF\JLTIKKMMMRMNfITIJJVHKRJ\D^H^DE\JII^H^H\M\KIH\ERFJVMKNOK`JKXNLMXMHJN^LKVNMVMOLN^RNSR^TLVUSjSTPRZSPXNOOPNXMLJMGhJXKXKNNOOTQLRNPQROXPVROQRLXMRLL\JHLLILZNZGVETHZJDGTIGRIHFGGVFTGZIKRITJH`H\PPLVLK^OJOQPOXQVTTS\QRSPVZPTTSWUXUVU^RPZVSVDTVPWXZZP[bWV\TZXWZWWX\h[XWdX\XbZYZXUUS`RVRHTTRRPR\MJKLKZKLJJRIHJNKITNZNHNMP^QLMPNPOLN`MPNL\OVQXOXOPRP\NOON\NVP\NJOOTR^P^RRW\VTSRUQVQXVVZWTVTYSSTXTSRTVPRNTQSUSNUSTVUVVPPNXRODR^S\TUTVTUSJSSVWSTXUDWQZRNTXSRPQOOROPQTNOXP`RR\QRPdNP`RQNdQ^RQTSL\QVQTKPOOdNPNLVOQNPXNQQTOSbQRQVROPPPONOOXLZOJVMZKPMLLN\OdKMLJKLJXIOGFECNC^@LAA\BAFEHTFTEFC\AXDXBFAEJbF^IfF^JJPLXQPVL`NMNJPM\NVNLLONNJMZNLKdOKKK<<^<:d:X\;;b9:7f8768L:`8X;P8>X7N<=R<

^>j;Z?>JA\C>\??V?=^@ZY^YXZW]NY^VWT\TfVVQ^QZPpPQOTNMRMbJPJHdMM`K>KL\MKLVQMPDRO`N\QbRPROfPQOM`KNMVNLLNZNLQNPMVJOXLRPHOS^QVPjQVTJWRU`VVVVXV\VVYLST\YTZUXVQXRRXRfWR`WVRPRTRQNMZPJPPRQNVVSdRZTRVTfUZVTW`UNUTDTZSQZTPMXPOXPTRjTQORNQXOVOXOPVPMbQOXRbRPQTP\SN^QPO\MQNNSQbOTOP\NTON`NNNMMPQ^OLLZLNIhN^KJN\MJN\MXKXJKN^H\JJGHJXFbD\GCACRE`AbBVFFZFFEHDZBEVGEFVKGJVI^JTJNNNLRLPOONFQPfQN`NKLMZNTIMLLVL^LbJJZMJMMLZMPPXRTOPFRPTJNMQLPNXMVNPL`KMGFHGFGIL`J`IHDPBDDBC`GJHLTLbMJPI^JMKDNIORMPOP\SON^PNLZLJL^PPLXNZOMKTMZNZONU SSXQ\PN\MKLfNNXM\LOJLL\KTMfKJZJPIGIpIVDBXB\EGVELFRF^HZC^DJF^E@RBCBHCZDFFBPCXAX@RDGREEPG\IEECHHHLHNHFLJFPKKHHdL\KKKMN\N^L`K^HFETI\FXGHKGGIGNFVCDEGCEZBZ>>?P=:8V:H95L:7632V5Z4T53F443d3\20P0L0^13b4P0/P2/1T,`+X.,\+^*P+T-*+)T*+*Z).R.+f-+,-+X/l-0V/R5X1N31l20T.-h1J11/\2-^,.F//X.2J1T11N12Z10/`2>3T0\3/H.\1R.0.-d,`,l.++)L+)V*b''V+,P('h)D'b+%L'&X('%%'d%#Z$J"T$!P T! PPZb`NNPJ`dVZjfRZbP ^ N ^ ` N \ Z \ Z X h Z V  `XBNRZVPRPfXVJR^X`RXbNdPT\Pb\JZNXTfNVPZRFnNhXj\h\LbX^^ZjTh\\XZXTP\fZTh\`V`^XVdTbVJXLhXlZbZXZ\\Z^TLRZZ\PT`NZTnXJBLNb^\XR^`bZRl^PLNXRZ\\XZTRBD\TZXXZTT\JZFVBZXVZRTZDXLbH^^RRVRbJ\PT`\^lXf`PT\hR^V`VX^f\XfbX\RVZNbB`\XRZZPfVXN^ZNP^^\RV^^VJNZTVNR`NHX`NR>Rbd\PXd\VRbPTZV^\PTZPZL\ZfZZ`^JZZZ\^hNFdJ@`dVddP^VR`dRZVZVD`^Zb`bV\NRXJjb\T^LZX`TRNRFVX\V ZP` R H P X ^ ` R  PTRNTRX^VJ`XTZR""$#$d&!#%Z&''''.*,8/,V/R/2`/T0V1Z1/V0V0\/.^-\1L014V35V6N6\<6T8;N:^9V8\8V636R76\9X669;9;>=Z=9N98:6V5^54X6f35F743V22P4^63X5X46V86\312P0`62^2P13X3T7R:\9V9N95;>@PB==>Z>d?PBRBJ?`DCGF\GTFGZJKIKbKVMZMPHINI^JFGLKHFG`GEIRQL\MTMRVPZL;@T

^<9:79X8J9;R=:V88V;d>\=;T;^?\>=T?>=X=X::88577Z44425126574Z7H3B6644h5022`2b12h1P4J7:88Z<9Z<\=R>V>P=?EH>V>;P=X==L;b>R>=b>bBAGHXFRGHFKZLZJJMJNVKIJLLXHGKNIDFJdLLLVOO\NLLJK^ONHTFFjEDRHGRFFBFCTEZEFFEXJJJIJNdOJhO\NXML\JXJIKRG^K`GGXJH^HI\KNKPNdQPT`RRHTRUV\RbRQNROMKLOZMZJKMLNO^OXMM`NXSRR`QVPOPOPNZMLOLIJKFMI\E\GDDERCDHHGFEXGLCF^GIMMJJNN\MbMO\NbRPST\VTXVWVUVSZVTU\VYNYRWSUTTXYRWX[WVW[h\RZ\YT\V[ZP\_YYVZRZPWS^VRVBRXUVTPVQLNPVOOMbN^NXKL^JPGBKL\MJKNONMXM\OZMNORPPRPMNNMQMNMOZMMTKLKbJXJKLKZKMKM\ONRPNNUWTQSPRdUJVVUUVWNWYZXLWNWLXFU^TS`Q@VQPQTQS^S`SOQPhPObOP^ONTOVT^QBSQ`VVNSRLU\Y\YQTP^WQPVSWSZRQXQVTOMBNMXLPRRRRZRXQPPSXPQbPOPMZM\OVQTRPORQPTPPZMXPMLOROMXNVKJITLJPJbKdNPLVMNNJMK^IKXFGVGFfHVJJ\HGLFEDCfEXFVGRGbCD\JTIfJJIZJHHIGGRI`KJRLNjLLQN`PXMMXQMRMQPRNfQRLNHbJfMJMKLMQVPbMOXSbP^NPRPVSMNLLNP\QZMNNPObN\ONMPVK\KHFIFjJZHFJHTDEHLI\GbGFTDRDlEFIILL\KL^JHIM\KNTNPTM`QO^QdNLMNMPMPNPOMO\MZNVM`SOPPUVTQRQPLVLKLdOjRfOKJXJMGRITGGXJRGbHIDDDBPEEA^CDCBCDBBCdERCVDCFCBXEEDHJHDFCE^FRLK^M\GHdJTILLHTJKJLLHDIbN^KRO`LJHXGEJRIXH^ETGVJG\GIHFJIbJEbE@CBV>D\BP;>P;9R9\:`89T774Z48`2N8536f52\1V4`4112`4J/.-0.V00+^,*f+*Z-Z+)+)X,f,+d-X-^0+V+,-^.00X11/1L/10R0P0.V0X0H3^1.-Z,Z,/X00//Z2\0020V20.2V-^/3Z/T,^,.V,L.\.++H,Z)',.**)*X(`'T()&(&%%&%`%%%$$D"Z! h !hXVZ\\X^Z^\VNVTTX\LL^TXTR ` \ V ` X b  b P P X Zl`RTdZNTTXNVbVZXXH`fZRZVJXRdRZ\LZXlXZ`TT\XVXTVbf``^Z^VRhX\`P`L^\nHPZRVT^VVX\^\PZRbX`Z``^^\@bHX`T^^^jX^bbPV\TRT`L\Pf\fZXZJR\bHXZPjTbR^X`b\NZXTZ\^b^XR^^njNVbJ^XT\VPVRXJdZ`bLdLPhNVPZ`NZTdVbP^TPbP^bZ^hXRZ\Z `b`PlT^P`XfPJVV^\VLRP`jZV^ZTT^^RnLXbVXXhN`\^PbTVhPfXP`P^\\ZdZTXPbPLPZ^^PpXZNTZ\VPZNN^^RT\\TH`Z^F^P`ZRFHT\JRrTX^LZTTV^bVXR\fXVVZ^VXPbZRTP\Z\P ^ZPJX b Z P T d V ` V X RV^TNZZ^PVTNPR`XVX ! Z!#"V%$"&T(R&L&)P'+*--T/R/.`2N0/1X2/R1\.X-.D-0V012^554l5:X5:;7P85N6d6b35X5N7427`;X9Z>`9<\?T^D<>X<\BVABN@\C@DJGXGTDEGLL`JMJHILHLXMXNLHRK`HVLEIKdLOZJHPN^OKZJKKINIZI^HIBREEEECC\DEZEIGGJRINKJLKXLKJKLVJVHIJRLNGHJLDHEIIhKIJPQNMXPPT`TRHSTSSXSJTRVNSTQ`ONMNNNLVMZMMPPMOLNPPSWUJUTOOLXSRONNLLK^HXKFPHPJLDCLLFHDZH\F`JFTGTDXHXJIXJJDJVLJRKLTRTVRONVRPbTVUZUT^UVRYUPWPSWRU\UTURULZXW^W\`\VWXWZb[^R`\]X\^_F_^XPYWXWURSPQXPPPNHOLOPQMNNFOILJTMOXLZQOTMOS`OHNZMRMOMLMPVP^MXSLDNlNPNLNLNFPLOKVMTIIXJHJZPMJKMM\NLROQPNVOXWTVUOjVUTT^X\WUUbWXVVZSZMPXPPROTPPRNOTP\OLOXLFMRHSXQQHQPRQRNRRPSQPSVWTVTXWVZUTdSZRRTRSTQOPPXQLPTOPNMPRRQQQSOPNPQPOOQNVPRRRbQM\OQ\PTNJNM\LNI\N\MMJLVLVM^LKLNMTKJLZO\ONIG`F^IXJHNHTIdHHPEFHGEVFXIDHVEGjHG\HHLTJTMHK^JRMLVJJIZM\NNQKPJNNQZNQQPUSJOZOLfJNZJNKHMZN@LTQZRR`RSRQPNKNNTNXMMKNQVMTObLNTMNKDKGGHHNGXHNEfELFCFRIXHfDEEEG\HHdMLKXHXNG\KJVIKMSOPQ\NMKMNLQNPfQPNVNVNVOfONOONSTJSRPfSRQNLLJLOMPRK\HZHJI^KPGLJZHZGLIZJCJELDlC`^\NR`XXdZlNXVXhX^XldVTXV\Zb`LT^ZhV^Zh^j^\^ZHV\TZ\RRRb``^T^bF`VbPRlb^jTRbP^H\RTV\RD`NXXXXVXjT\PTRXRTRRZ\NV^b \ ^ ` T b X P X b j V f \ d HJRfVXVTF\`Pf ^"F"\##$T#f"$$%&(&X)D*,\/0P0\0^-4`0L2X00b1-.^.R///02356686T:8P9L:n965V<4Z4`44\7578H:d=:V;>?X<^<<=T9=8Z8:R8Z:T;;;\>BV>^?L>@>\>:<;9`95T6T56N6274233X4h448\8`677X99552N545L30375V59;R=9A=AREDVBEFdEIdNMMfKZMNZJ\M^LhIZMpIRJF\JTDE\IITKIIKLMJILTMN`IZH\H\IG\EZDIBFTEVCVFCBE^FNGFGXG\GbHPGGGIbMbJIHH^GIHRHTHVHETHGVLRJIJKRNPMSQLTUYbSR^VQTXNbMZMXMNOLMMNNKSN`OMM^RRXLTPQXSPTOVRPMKXRRNZOKITJITI^LIEIPGHVHjKIZFGZHRFKKZGJZGVMPNJI^NZRVRLPTVPUT^VWZT\USZTXVPU^UbTVVVDTXTXSVZYTXXYXUXYXXTYZYTYZN\^[_^_YY[LYXWTUbSPRDP\QTQVPZSfOO`NPMMTKZKbLLNMNLVN\MJNMZLOVOS\P^MOXLOJPNPQNN^LVKROfSLVLONRHIGKRKXJMM^MXIMNLZOXPVMLMOPTTPZRPSRRRTVVRVXSXURTRPNXP`PJMbOXRPRMJ`MfPNOLVMMMQPRdSNTRdNQQVPQ^URVTTNTYW`YUWVSDSSJVPSUXST`QSPRPR`PQZPTRJQXUQ\SPTVORSMbR^PSQPXP^NMNPRNM,M`NXMbKHLIXIMGVJLZKhMM`OZLNTLXK^KJZHLKZIGKKHG\II`HbITGJVJFDEGEZG\GEXJJPIjHXIIIKKLL\NMLOMQXM\NKPPQR`RbRSdTPMMOIRJKLPJRbRbQUQUTZPNMROHOMXML`NTMMLOLLZLKTIdKHTGLFFFEZGdECVFE`GFFGZKKVJ\PJ\KXLIIVHLIMRNNRQ^OMMPLXLOMOPBRTQ^QNTRJOXOXQPPQOPRRVOPZOPO^MMvOLOVOJNIMJKJ^JZJKHHDZDTFRGLFRCDBX@E\C^?PCRAXB`DJCXAVADXBPCCVCCBGhFEFLI`HXHGZJNIKVJbMJEGNJNJJZJJNLHTKJ^K\KZKRMHNHZFIGPIZFTGXHVCG^HXGFPIfEDNCBACE?VA\;T;9J98X:5Z7P65f43d5T43P5h4\3210T2X7Z6X0T..01-`.2Z//,\-))*,T,R+)*b-V*V+++++/,.V00V0V00R2.-2-N0^.X/T.L//X0/J.\-X,V/Z10/V1^1X31/3/T0d2V0/2N/.,`.L-B.,F,*.N*H+d)V,*Z*V(*)b*'R(j'X&%&P#&&T&%#"b"T"T#"Z\TR^VJNj^\XXTZfVXL ```l L X T N ^ ` F T P h Z T Z\bXNbXJXX^\^T^`bLZNTRRHV^Tf^\RRV`@`NTRXFXTXNX`V^bVd^PVhRd\\`NX^`PnZX\Z\`\NVLT`NbV^XZ`\b\^VZHbLbNXXn\Z^JX`X`RX^^TTZZRTXdZ^V`XX\`ZJVT^TZVbV`^`XJ`V^dX``XPVP^J^^PZb`FHdVTTXXZhZ^XPdR\V\X`\ddP^fV^TZhbd\bPf^bZ^XRdRbbRfd^T^VVfRXRdTbRV^ZH`\r`RT`VXdTnLZVZX^T^lXXbJZZ\RVV^HVjPVdVV^^\^P^X\jRJLXT^dX`^dHXD^XV\j\TN^TV^ZHbbP^`ZL\ZZT^RdLHVNZfZPbZ`LZXdRVFdd``TVZNT^\XbJVVZ\TL b d H R X \ ` J H P ` `R R P NfV^XZTTLXRNb"!$J""X"$P$&X&%%X%*^+T,,.D,d1L.02B0Z011.R2@.2//122F4V4R:578766X63D7X7V56N346Z79R9D:V<^;Z>^@L;`>;X;R::8`88L;@BA?L=V=L:8\6X8X6b6L45^4Z66X3T6N846J6X86V5T9:\6N65Z3X452X354d3P84V76Z::9T>=dAV@F??P?>f=@>V>>P=;FIJIKMNMPPObQQjMLbNLdPMbOPRPRQPQ\SLQQPTQQfQPTMVObNNPPQOMLOTMJNRKJXKTJJKVKVJVKNHTGIEPFnDPE^EHDbCCCVB?AB`CNFfFEBN@X@TB^BCPGAFCFHIZHHHK^JbJVGIPIJLVHJLI^KTJbLJHVNTIMJOKVKKZKI^KHRKdFHJFPHTINF\IE`GE@JBV@\B@@Z@N<;N<86b9b99Z85575N4\87721b0d12\4V..0,.h0.L.//,^*,).f+*+Z*+,-+J++,J,.V.Z//T--H011V100`-,P-\1V/.P2N/00T2.X.Z/2`0f.N1/1P2..R02^0..Z0b1V/F/-,++,+d+V*V,(b(()X*j()('b'%&%&L&Z%T$T$$L"d#N"%j!"^ d!RTbRXbZPVPZTRR\ZdRTL ^ h P X ^ P ^ > L TXdlXVLXNVNbZ^RZTVbT^ZZTfTZZHXL`PVZVVVNZTZ`dTRPJTbPRLDNZRNZFPhXTV`J\VbV``fZXTb\X^TL^TT^^\VVTVXX\^HbJj^JZ^^PfV`PPd\TVZbZVdRVXRV\R^TZXNbb\TXZ\`dZ\PfP^ZXVX`PdVl\TPbPRJ`ZdXZX^VFH^\X\TLXFV\T`jXZT^VZTjZdX`\fhTbZ``l^flfd\Vp^ZNhZj\Vb`\`Z\ZXbD^ZRd^d`^ZZJNT\XT`\\Zb\^^^bTPhTTTTL^RNfTbRZN`JXbT\Z`R\TX^V\RbNX`VdVVNN`R^ZNVXZ\VFPJTf`XNV^T\JZX^FT^^\R`\NBf>`PdVTTfL\HZZ`X T \ X X ^ R Z H V X X T ` \ ZR`TXLbNTV`NbfVTRZX  Z "!\###V"'&`&`%$V*'N)X*X-`0R.-1F2X1`0P1P0^2/R/-l1/1/\1^24355F;9V6d978Z7623\53T2N6T6779<9B=V?V>=>@;^>H;;8L:`9R>BZ?=??R;d?:;<H;^;V>>=h?;>`H>V?N@P?^;\5R57224b2(4Z455P6b68569T65X67^7H6944H5R2b253V5^:3f5D:\8R87V7X;X=Z=X>T?=B>d@>R=<ZBF?@>P;::T9J:H77Z755V65V67N24V4112.0Z0R/Z,`.V*+-,X-.-R-P-,`-+V.b/+X*L-(,-J,)V*\+^/H.X..`0/D-0H/J//-L-+,./T0/0V/^.N-V2-./`2111f0F0/T/-P2`3/T-...N,->.V,+*)*-D))(()j(&X*(`(Z'&^$R&&"\$H$`%P$#"f!!$ V"XL fB`ZP\`R\Xd\NhXR` X`PVXb J b ` J j F V \ V`TZL`X\^VTX^TP`TZRb^R^X`T^NXTVP\NjLTLV`RRdZJV\dRTNnJRPVZdbRTl\RPZVXbX\\fXPZbD\^dR\dbTX\hVXN^Vj^XP\\^PRbZVH\\HRVLHZZLZL\bVVP\V\LRVTRTN\VTXdTdLXPJXTVVVN\\^LVRZ\bV\V^PRZPRPX\RT^T^RVjVXj^ZTd\\h\Zb`bVVbZ`PVdfZ\h\hVddZbXTX^Td^b^ZT^`VhRXdhVXRbhV^`\ZnXR^b^dVTPV`2`T\Z\\hTNbHZhVTT^V\XTdZ\N^\XJNj``X\X\TRRZb\`Dbb^V\RRN^\\T^L@b\X\T\X8XZVHf TVR\ Z V N ^ R T f L h \ V X DbXTFXXd\T\RTTJX^V"!!!Z"f#$l%N%P##$%&)',++,.0V10V/20N02-T0.0\/T//3f2V4h55^5^67R567T87N4Z63h2X33\3b86H8:;L?@=V@Z?X>PA\>=@VA@b?==P<7f4Z7b4^2^353524T65R68P667V9X64Z74\5H4\4V426N63f34\45T7Z5:7H:X;V:H><>TAXC>T?b=L::T<;\9Z:=@>?Z>`AECFHK`LNQMKHZLJHLI\F\IGGFE^GZGRHKNQRGH\IZKTMMOhJJ\GNI\CJGDVBZ@CBJEbCPBEFCZFLGPGJRHHEENGC@FdEI^GXIZHEFBHRG`FNKJJLOQZMXSPQVTQVPRPTXURSTXTFRRTRXQZRQSVZVSRUXRHQTRUQfSTRPNR`PMXPLLLTJdHTHfHHZIEVHC`D`JGKHfIVEbJHMFKNVLKMPLPPP^TNRWT`UPVQV^URZURTSbXPZYY^ZZYX\\W\XW\WY]XXY`[]RZ]\VTYZV^UYdZNWbWUPTZRRTQRRMZMNZJMHVMVMLOLOdPPOQTQPTNPHPNTPSZQSPOP`QOLdMJJ\KTLJLLLJMTNLQLlN^LVNL`LVMMQZMNKbKHGGJXLLJMZJKTI\IPKPIJN`MTMVKIRKK\KfJ`NMOM\KNLM`PLOZQQNPXPHQPPPROPPQQPfQZSZTQPTOZPPOPORXQRRSSPUPSZRTPS\QTQXSTRTTWRUSSPQRTOPMPPNJMJ\LZKN\MLOZMMLIVKNLPXQRNVORNNhJTLLJNKTKOdKZIIIIVNILJEPGHGXG\HTGH^HGEZII^JXOJN`QRP\PNTOMMMbSP^PQT^TUQ\SZUR^QP\PVWXQOTMNJPOMXJXO`P\QPPXQXTRQObUT`O`NZOTNMPXLKI^I^FTHEHE\F^HZIIHJVHHH\H^GI^G^LRIdL\LTLKLILKKTNK\NOP`RNQPOQ^POXMVPPXRVRTPRRPQN^QRQbQSSRPdRLTMMLNPQRVPXR\MKVLfJGPJdKVGLNKK\IFTDbFFEXETGZGGDBCBfEBBDZGCEAB^GAJGFEFdB^DDEEE\HJJZHLHIFH`JFLEHGIFJ\JXLXKZKMKXKNHVL\IJLJdIIIGFXFPIEHEE`DDBBV@R@^C?=R>9f:\=<>hA=P@<>;988P=R==H=@T;>@R?^=?X88T41J321Z6P4575b87X78d:78`8^;J7X5H755L7h83V5V7454N45258V;H89Z>T>;;X\=X<:9;;V=h?ABFFNHHN\OMXL`TMJKNLNKKIHXHFhG\I\DRF\GPJJRLPONJLGPMNKJXIGDGVEGCCNAJDBVGZCDHEFFEdJHH^GbJJG^EXGXFGXGRIFBC`GEG\FEHGMLJZKLZLJTLLMbM\PdNRPXRTSWbTVQQTVUQNWVTYXXJX\dWVVZWZYXT\ZPWJ[lYTBWVWVVXVTVRXYZW\ZTSNQQXRR\RLVOVNJPNZOMLLL\O^KNPURQRQ^TXTROXQFPQVNUQRPO\QSN^N`LK\K^JbMTNRRKMXOMMPJ@J\NRLTPZLDMPLfKRJ\JGFTHGPKbIG\IGTKIHI^JVIL\LRINJJIXMMJK\OOLLRPbOTQRRQRJSR`TTURQXPNOQPPRPP\ONNPMZQNO\RRTSTTUWRZUQTUJTR\WTSXUPUPTVRSXQPVQNNPKJOVNVLTOHNIKKLOMMPMNZONXONMXNbMTOONMONOMVK^KGGJRJKRNJFJXHGfGPFNHCPIJNFGGIMZPMRPPPMRTONNXKTPPPQPVRWUSVQJVZUQ^SNR\RVR`OZPTQ`O`OQLS^QPRRMPdRLZRRO`QZRQVOTPXQZKMRKLXJVFFVGI^HF^JFJFIZG^GXHVIFLGJLKVK^NHM`NKMKOPZNNTNLR\QJR`QJPPPPRSTNRPSZTQPQPBSPQTQRQSWPRVVRM`MNL@OJONROVN^OVNNI^KTJIL^KTJHTJRHHJB^D^FGEGXFDDCZBZ@AVA\CPFXFBCDjBDRFFEGFPDEBA\EEZEFFGTEXFRI`HH`KTK\JJKJHLIIJHNVLMPIEPIFFdHIMVHZHGKGXIHFFXEPDDEETA\CL?b>:9::;88^:T;6T46Z668b42L5Z4T01003V1V/,,++T+)^,,+`-,,.L-Z-d*,+,-L,-`)V*,V+P,N.X/\0B0+.--H0/-./P2X/.\-P0b0V./..d..j./.03^.0B/T/d2T0Z2.--P.R.X-Z-j-X,R,V+T,R+X+V+R+)*b-('&%)'V&$#"^$%#\$"#Z"!R!ZZBV Z\ X fPRT`LbFTJZVPTXVZ`Z R D ` N X \ X `  N T ^XH\bLVZXZHVN`NXR^dZNhNZ\TVV``\^V\`^JLTflZXfbdRZVRZT^`P`ZTNZNNNbVZZBVl^V\RhLb\ZXRN\LdVdT\ZZ`P\P`XT^`L^RNXNXhZ\`bb`XT\^bTd`LZVV`ZRXX>VT\NNXRZRV`PXbV\H\b^RP\PZR\V`RNfTHhZ^dVTl^^T^X`\^VNJ@`\RZ`^J^b^bHZN`TZdPj\XNZTZ\^nf`Z^VR\TX\\\XXZb\TVZ`h^\\XH``JZZ\h^l\bTVX^bRZJRX\VVXTNX`V^`V\dNPbVVRNTXVjP@`@^NNjbXXN^TVX`^\V\dRRTVZ PX  R \ ` \ X N N V H Z L Z^RJXT`dbV PV" ""X#"B$#$$L$J%'()\*\+^,d.`2N.P.130/.H-\/R/V2J/Z/V/V30P5X245R4R6`5Z3X6645L73R5T3Z2P43j69X=b:D

R>T=@d?AhCLA>^;:;N:9N<:L>d>=:`>j;>BXCAB>^D@=J>=;R;X:8N8b9X::\==;Z=T=<@<8;T9d7R84R6\5L413\4P4P57V78997`7687\6645l3T6874\65X742T648:^;P==:Z:?^AAL==R;B?VBJ;?BTDIbGLGIXKTINPNObN`JRIOKJ`JJECXH`EHEI`GGXGhJOMPMMVPLL\OPIGXGTGFXFbBVDA\CAPBZDFZHFCXFHGILLPH\JHZGFVEXGXHIFGjFHG^JBLKMNKMN^PVNNPXPVWSTVHTZTd[UXTY\VTVXZZUJWhYUPSWSRXVT^WLVR\R^STPPOMZQ^NLLKMPVOVHEHHJVF\FEDXEbFGZHIbLZOJJVL\KLJXMJLOPPPQRRR^PTQRNVUXUQNVLTVWULVWTTVHYZ[NXXYYZXY^VVhVZVYWWUJZ\XU^UXTTbVFVPOVQRPM`LJOhR^OLdOKJOXOM`QFSTOVQlQMVSVRVQNQfSRZVQSSOLO\NLKLMMNVPRO\QLJP`P\OPMLNRMILPJKTHIFI^IDEGEXGFNIFIRHEJOVGZGG=X?T;P;9`R==AR=A?N@@P;X@R;J=:5;T:N<;`<<AZ>?B;F;?Z=`<=Z;;XC@EZC^CRCDE\IfHGHHHNI^HHEbJHHNHETHH`GHFGXJNIJIKPMdPTPTRQZQUVVUTXZYXW\ZJWLZSZS\WVXHYZVVV`VTTZUBTTRZWUPVQQRVQ\VSZSTOXSO`NL`K^KGXHGXIEVECBEGXJHHRHVIVHVLIHVJTLNONPTROZOQQP^PXP`TS^UPTWTQNUdUWLVX`XTZWVRYWXbXYVZ`VVXWZXY^UXYXXRd[WPVSUXQPTRQTOONfPORMPROfLORQOQRVTQXO^Q`OLVJTQQPPPPPMMRMTLLLMbQMNXONNQQNP`QHNNMTORKVMMPKKTIGZKIGLEHDFBGEVEXIVHETHFHIVF^H@KVJNVQXLTQLQQ\TTQQTPZPMZOZNPQOMQ^QN>UPVRPTONOdMMZNOM`MLPTOOZQR`VNTVVSRTTT`UXS`TVXX^USUORQZMNROMVNRNJLNNLILNIIMZJKVLMNKXO\PPO`PXRPNPFTVQlNRZRO\QbJKJGGKIVHHRFVJ^KKVKJRLXJXNK\MQ`NOhTDOZPNNUfQPQQTObPQ`PJQVQbOPPLPJLNRPVRVRNWhULSVP^QPTQSXPPOPFPZQHO`SOMNOJ^JRKTJHHJFVGI\HKJKDKJHVGTFFDEjEFHFH`JGRJKM^N^RPMQ`NXQRPTOTTQTRRVRHQNBPZPTSVTTT`R\TVDQbRQSLSJUTQdPXTSRQ`R\QZQPN\PMdOLLMhK`HITIIKJKdIGGHXHFFPF`EVEFXFPF^CBC@DPBVCPGDTEfEXHDEbE\H`CERGFHZFLFVFdGLERC^GEF`HIJGHJJFILIHGHIVJVMNJ\HFXGGFJHIbEHHHEGPE^FC\C@ZD@C`@TC^?^<<\;^;R:898;454V5Z757T353D4R4N2V01Z0d,V.`+\0Z-d+**\*V+X,,L-X.Z,Z,*`+))V,+N+\*Z-+.,.*h.*X/..-R-f-L-X/N,0/.^-++,R20.X01.X.3.10H/Z.1P0X1j00.-,^/1.,-b,,,N+)**X,V,`*P)N(T))^'R''R(b&X$V#R%$"P" \#! J `X bN ^ZbTZRfRbVnHfbV\R^N H X T X Z T R X ` X d\ VTN`JJfXX^Tf^VN\`XJTZ`ZRdT\X\^PL\^\VJ\L\R`T\NVRPNRZRZRN\R\ZffVfdTTHTdbN\^dTZlR\``PbZVjR^Z`RT^jX^^fNP^^VdZ`P\^XZXPhZRXVX`T^`ZB^VJRN\X^`XZTRR^RTXRXdVdV^\VZ\^Ld\bTXjTHXXZ\ZHVXXZVXXRNRLZ`bZdT^ZfZZVZHnX^VdXnZ^N\RRbTP`ZRZZT\RXJVXRZRNb\^R4XTZ\`XVTR\fNZZZVh\X\N`\\Z`P\TZLfJZLTLfZ`\V^`^\X^VTZV`PZVXXXVNZVXPjPdRV^V``f^XTXNbH^fZT\TTHVRR`^X^`db`ZVddZVf^`LXFd\R TTT P h L H X H R T PN`Td*VFVhRPRhTZbZ RR#" !!T%%#$ X$H#Z#&X'V(&)N+.0Z2X0T213R1.0X.f1J/Z--X1f1/L2P3N3Z5R523P4^6V5P8533b6J3232T3Z76P<9h:;Z>`@P?A>=<<;p::`<98Z9P;J:;J;;H@=F9=T;R>X;7L;Z7663376D5Z35454876d9765P8Z5D8^4Z58f6X44H4334"6V65^7`:9X9@>:>R==R\<99Z98<8775462V5^551253\0/`0.X-P,X--N++^*N+-*)P)X-.-,,R-d)f,P+,\+,N*R+d*++Z,X-V.X,Z+---+,b-/f-0-D-d.-+V/J00R-0X./11.`1j//\/30T1P/..-b/,-*+,,R.Z,X)*Z-Z,\+*Z*R*(Z+*&V$X%b$Z%##%J""X D"V P"Z F!fB !ZXZVLNT`^`^Tj`JNTNd^L b BZH Z T L \ X b X \ T P P RPNT PRjRXN`bVj>\^TVP`X^NVbh^TNXNdZZ\T`TTXTL`ZNZXX\dd^HXVfVPJP`\bNPlP\Rb^VPJhf`dZRLffR\T\ZT`fPbP`VJ`ZV^ZXXLRX`BZNbb\TT`\ZV\bVV\Zb^XX\HVX\\^XX\L\RLX\XN\PLbTPTXVLZDF\\`ZVVLXTRfTP``XP\P\LPVTXZ`XPX^NJdXLnPRddd^PVV^N^JXZXRlVThV`H\`D^Zj^jPTb^XRh\fR`V\fd\bPL\VX`^`^jRfTZbh^F\fLTVLfR^\```TX^`PZlLXRRPX^PDLbZXdfPT^dfRZRRlXb`Z\TLjNffX\RdVR`HLd`VPVR^<^\\``\^N\VXPT^^R^ZRJXZXfZbdfX\R\^^bb\\^NZ JZb \B \ V X b X LTF\XZTTT^TJ `R "#"`#X#""#X$R&\)X%\(%^*-*V/.d/l.b2P3d1X0b2^2.^/L.T.T0V0-j21N3V3Z2425R47Z7\6P6b5R53215T4V3V97;;V;>A=X=?P@<^@<<8897`<8T9:=Z:^>:^CR>\><;R:7Z7T6744V7Z8\4\43P4666P79556^5\7V44f4`6Z3f67530\2Z2Z3\44787^<>\>\@\=H><;J>CVC^EFHNK\LJMSVQNZOXN\KKM\IJGHHhGFDRHEFITLKNMZNO\ORKLZKLJJ^HjG6BAV>?PB@BhC@XGZEPHFGXGNJHGFdKHGFEZHHIXHHJNIVKJKIMVJZQNK^LXLLP^RJQHUNQVjVdWRWUYVlZNYUTSTTVWSHTVdUHVJX^VNRUVUPSXSPUXWTXTQSVQOZLjM^LJL\LHFIVIERHDXHH^HTHZGFfM^HKIJKTHTNZPOhR^PSPJPPLQRQSQVLWVZTRVRUZXU[`UR^U^UXVb\XZVPVLXTWVXWU`VT`\UXUlUSROROQTTQPXRFQdWOPSPQQRJR^PQ\MMbMTPO\OXOXQTQZRLO\O^UPN^UQR^QRNUR^TXQPRLRPPPOLQRONBNNQJPONKIGPGJFXI\DZKXGDREGGFbHGLKIJbNMMVRPQSLSTZQMLMVK\NHN`NNRSbNJNLMZNQ\MPbLKNPSFKNNNMROFMQTSQRTZRRRSVPWTRQUTfUWZWbVTTdRTPOLFPLNOO\ORRdP^ORNMPKXK\M^HLLLHMKPRPRURURSRWT^P`PLPPNONTKZJXJ\DHHRLJMJM`MOPMORO\PO^KPPTRTOQXSdROWXUQRPOTPOfQQOXSTPPPRNZMOVR\SXZS^TRQTLRTRTQTRRULRLTXPRPRNNLRLTMJKdHTHIG`FLGMLHIKHE`FLCXGZI`MZKRJ\IJLJQLPNROPORPNTfQRPQTRQ`RRUR\OQXPPLSTUUZSZOTQ\TQZRPTRPXUJNbNOVNMXPON`QOMJJ^KXHILNHINMLG^HdGJECDjGXGFDF`FTEHCA^BAVC\FPERGREDDED\EZF`CPDNCC\FGJDJNGFGTHTJ\HLIJI`HIXHHjHKTHXHHbKNKJVN^KbIHKJVKG^GFHCdG\E`BCHDFCAHBV@XAA>^P^`XN^` N^ZZR R P Z N b Ld`^^dNN`^Z^ZVTZPVh^ !X !\#R#P#V#X%R"T##&V%%'T*V),V+,.T2101d0H/^/./l0-Z.00H0\032`44X2\7b76745F23T2V13T355^5Z7X;:R;J??dAbBZ>V?;H>RZ=9^7X5`5^57555R60J5344^4N577R6557F5567P9T6543N1R4\2L5V245Z5X:^=8;B@^<<:`>V>@:BF;;CD@PDEDXI^I\ILJOHMOOQTNJONL`KZIHJRLFFHZEERJL`OMOONXNJ^MHIIGPH`CA`@P@AAPBCCBDEJVIH^FJFIVILGE`G\ETHDVGXEPK`HTHGHG^GXITMPLLMNPNHR\PQTRVUJU`XV:UVTWTTSTUVZUX`UVSTWORSRR\RSSZUZVbUUVTYURjVJPLOMIOHL^JNFIDLE\IHMfHRD`GPDHPFFIZLHJRhOTP`P^SMXMNTPPRRJPRVTSTVUSNPZVdUW`TSTQHRTNXTYYVDYWLURWWXWZXZWVLWXVNUSTPTTTQPRVRRNOOXPXTRPFROPVOPNUTQMKPMNRZSRMP>>=R<<:;9F;9<:76P5T66\4T2b3T5V5\5V3303^/N/+\+L)`-,++Z))+Z),,,d+,V-R,*Z*++.+*,B-+X-,*+f/R+\.H-T.^-/P,,+V.+,^,P-b.-`/Z1\-d0/02j1T0`/-012.Z.1/X.X-2H+^,T-X**\,`-\+*\,()**d)B*'V)+h)Z(V&T'Z$V$`#"!T!"L!"^ ZV!Z \ZVfRPPVT`ZLVVXLVT V V R d N Z N b X ` ` V TN^`J`ZPVXP^VTJZZbNbTd`\ZPV^^NTbRbRNRT<X\XXPPZZ^R\XND\RXXbNXRHbbZDTV^bPfRNZTLZH\VfXdN`^NV`\XT^D\^XZRddLjbNZb^`hTPZVXJ^bNXNfR`TXXZbT`dJbR\X`\N^JRZ`\XbfZdPPVPXZ^XNZdR`Zb^dXVZTdXTXVT`TfTVVN\Xd^`PdZpZ`\V`^Zp`VV^Z^`VdXP`X`fVTfXbRX^T\hXNTT`\RZP\VTZZVrVbTbXdJ\NVZbV`RTVXVNL\dZ\Rd`RdP^LnV^pV`TJ`fLXbTdfTfJTZd`jfXZL^fR`PbZJXPZZ\\L`XPHXPV\ZVTRVPXV^NHbZTVT`N\^P\`TRZVXN\dP d^` b X f ^  XTTVZTXNZPRfb^TdP^^fLdXPT V"d!#B$#!\%$R$`%'$N)b'(*F+,L0j0\0.b1F/0^-0X-h...0b/20\1/V2462X4`5P8H756d4J4>43Z3h4b8`4P779;>b;;^BP?B\ARCd>`=\=<\=9\:J99;V=<=@<>^=\<`97489T73`5V435P3216b48X877V73j7`85d5N8L7`;555J24L2P436;7\:9L>@\BAX>>?d>N?\9\USJPQXRQZTQOOQ`NOPQONL^NKTLZRTONNQTRRVT`VVTNWXRbRRQPRTNQPOFSRK\JIIZJJKMNNBQZRZQTTPPRTOPRROZPfTTTQXTZSQQNSSZP`MOOXO^NOVKNMNOPNTQTQRSRZPQSPAN>j?;<;9F<7b;:7X9855V648V2T02^2b1R2D5/1V00,,\-T,T+*(b+)-*N,^-)\-,X-,,\*d+-)^-V.X,R+^,),Z,N,L.+,H+,,,X/V/,T,.-R..T+Z.P.-P,/b1^10b0.L/f0V/X1..H1T-.\.N--,T-`++P,L-^-\,+V.*`)P)b'J&*(Z)P**(%%d%%#!! j!T#\V R TT\HTXPd\LRX\jNZdf^PdZ^^Z^ Vd ` R T N Z V R Z  \^\VhTfJhRV\TVV^^n\\d^dXZZVT`^VP`X^RXfN^TRb`XZNhfVZ^Rb\F`XZV^J^TZNRfNV\ZTPZRVfPL\XV`VZX^PffN\`^nPVTZXRZXPbZT`RZ\^\VRT\P\f\VVVTH`X`nZF\\ZNZdZHPNfTTbRVNfTV^^TZTRNNVT\RhPZLVRZP^XbTRd``X``bJnhNd\RXVNf^Z`RRX\VhTbPNhbVNBjR`^LV^PZP`XLTTTZH`NX^FPR\DbRX^Hf\TX\JZXVR\\VZB\VZZ\dRDfHXVVJR\b`TPH\ZTV\^JR@fXLZT^bXNZJJPXPVJZZNd`NNT\\Z\VV`XpL\TVRfbRR^JXN R^\ ` V F J P V T hRVZ@bNRTRTX\ $"T!$Z&J##$%%b&V(&V'J(),*V.0L0/.\0V/.^//2F.+--b-F1L/V0V33X764L78D7V7f45R34\0^2\5645V9^9R<\>R;RZ>T===T=J?@@=>=<;=\=^<@?CBVHGRKZHJJ^KNVPNTNXPPTNJFPJXLHI\HFZFGMKOPSRTQOJJMILGGbFLDZEDLCZB?ABCFEVDPDVFZEEDJbIJFVIGGTJHTJKIJRIIIZEEHpILJZMRLLNQRRXQS\QUVTdT`UTRYWLXZXTXV@TTYTVSNUJRQ\S\QVSRdSSPRVWRUhWVV\TZ\T@TTTROQKKNJI\HRIJ^IGGTIRFVLHDKNI\IFVKbJRPJLMVOMNLLMOMOdR`ORTPRRQSVSXRNTULZR\T>VRTQQ^TWTX\bXVTWXUXNVHVTWRYUYVTPWYZLYXVWXWZSRRPPQRV\SXQRSNPP\LMZPNPVORMQXM`MNPQM\QSLSOJR`RRQVU\TVXXWVURTS\TUPTOPPPPQHNKTMVNXKNTK`JJHFI`FFHGFLJGIINfKMXPPNXORRObOQVNZQIbNRIJL\KXNNXKTO\PNPR\PRNVQhQOONNLQ^OPNNPO\PLOVPZO^OPPTPSThRRSNR`PPLRQRSQPVOFPPSDRTRVNNOROOZTRSNNQO\OON\LLOSZN`U^WTTVVVRRQ^UTTOVQdRPOPRZRPNMLNKVJNVMPObMPRRRQORTZURUXRPPUZQLTURXTJPURROMNMPRN^RZOPXMMZPRVRQRTQXRdOPUVQLPOZOORPT^S\QKJNfL\JJNJTKJZDRDXIEFXJRERFIJGFZJ\LNPK\LMRSZSNLONMXPPPPSUXTTbW^TLV`TVUQLPZRQdRZQJRRZSSP^QP^TSdVRPMQLQJ`OKMLKXN`KLFIZKIVJVIJTJJF^ENDTEFDZGDBF`IZG`EED@E`CTCDF`KLLCHTDTEhGGbF\HETE\H^KDFGFPHIPGG\JHG`JHJIJVLIhJIVKVIbIJJHHHHEIFEFND\FZEFDDXEFA@XCPAZA`=>=^><`<<7R<96B6;X4X9`364R53T3V42f10V/.T,-N-,-^**)T*b)L*)**-.+N++,T-+L+^+T*Z,)L*Z,V+.*+R+T.0Z/\,-V-+V*b+++T-P/R/-X.T01.0P0+1\02P0^..2J2d1X/,/-.X-P0,`.X+L-L)\+\-b*F)H((^+^+(T(\'N)^(T+&)'(P%R'##V#$""" !Zb XLX `JN\NdVZNZRPVZPJ R X J X N ` V bJVH JX^RZDV^JRX\@TdbX\VRZ`ZVXXV^VVZ\`RN\:R`VnZTb`TVJLnXXFnLXXVT^b^Z`hFXXdX\Tb\^bdR\FbPdRT\XTRjLhV`TVTR\`NNZJZVN`Z``R\dXXT\VP\RXNLfVZZ^ZbVbPjV^N^X\`bZZXl^XR^PRL\Rb\T\TLP`PJnZNPTX`T\`TNZ\ZZ\N`db\^XRbhn^^ZT\bX`\ddZbV\`bb\D\TPjPb^pZZ^\ZbXfZ`Nf^X^`ZfJ`PZ^X^NX:f`\X^^TVfVTn\^^ZbLhhVVR^Z\LRjNl`TZ`^NbfTZVZX\XNPhLZVJT^dXZ\RVZVT\\JVZ^^bLV\VT^`bRbJTTXL`TBZ\RfX^VdT`N`f` j T f T ^ \ ZV^dL PTDRX^PPT\PX !V"R"d###\##$'`%d&$b%'(,^,T./R,X0-/Z2/N//\10-V,.-N102/j14^5N6d977d8X8Z552X3X3X3Z4V4b84698V<P=`=P:J=<;;;\:F69\=9J6f6N44210\3`62`4V43T244T857V88^86627R57637P9Z7J9V99=>>=;<@XB@C^?=R>`=A;b<`=BJ>A?^CFVG`GJLKKRPOZPLPdRJPXUPJbK\JHGH\KVFRHFJRNNPfSOPRXNVPLNLPJEZGRHBERED?\FLEFBCD^GCXE`H\FTDFIGVEHRIVJPKIHJKJIHXEHVK\JJJVKKNOOOVORRTWSZUNYV\RYLZ\V@TbVVdUNTRUZTfURR`QLRUVRRSURRU`WVXWLXWXRTRRQ^PLL^KINIXNZKJKI\IVHFJIHLJGHVJ`GXKbIVITKDN\MOLNVQPPPRNPNMXR^RQSRXUTULTVLTVTZRRRRUPTTXVNWNUU\Y`TVTTVV\`VURXVfWNXdVTZWLYY^VWT`SRVTR^RRZSSTSRTPPRLPRLMTOL\PMNLIPQORPTTVQRRTRVURXW\VUTVVSQQORPQQRVLVM^PMNQNMVLJXKJG`IJGKKI^KNZPRNRRVNNPbOTOPOSMNXPNJLNMLNTRVOPQNFPNRXON^QQNPVRPVPRPPONPTPXROBShPXQZTTRPURPQORSXQSPVSRLTZRRNNTQP\PPRVOQbO`PNROTPZTJURURT`WTU@ZQPRUXSRbQVPbNRROVTZO^MbOROPT^SRNTZPQZRS`VHURDUXTSRPSLTT`VVRTRVQRSTNKMLQP^ROONNjMZLTOPhOPON`QRSPOSOVNPRRRZPXONNZKIGZH`J^ITKNFFTFGVE\FZEDCTJIKJTMbLZKFNNOZPZNLIMNTZURTTFSSXRVUZTRT^TXUSRTRXP^QQTHOTRRRRZSTSVR\RPVLTLLZNMLI^JMPLVLJdLZIKJbLbJJHH`IZIBFBCVETCACDGRC@BJAPBTDNChFTFRGFTE\CHXEGFRDHFHDNFETGD^IHVLGNHI^JVMXJXKIVJPMITL\IJHbI^I^HFZF\FFTFZEGZEEGGE^HERIT@T@P@^A?;\<=9=P>8R7:88;;T8P7Z75V445X4P610R2.-+Z,X,T,+(Z,X+**X)')b*(+J0-V+Z-X++-+P,*^,)R))+\**h+,,`,F,*+*\))^,^-.X,,/-0.\/V2/1-0/0X.`.`2V1Z1\./j/\,P.`.R,\.,0-+N.)+`-(+))+N))(*X*f'V('V'f&L'\%%\%T$P"\ f J"X" d^ ^^XNL^dXF^XTd\^`V^RfTPXX ^ X Z X Z V R R\ bRX NTJLPX^L^T`bP^JhVPXLV\RTPVX`^\ZHVT`NXX^`\`Jl^VF\\dVNbZFbX\^^bdVRP`JX`XhPZVd\TXT^TLX^^RXhN\R^TXXNbX`VV^`bTNZ`Nh\TbRPR^L\ZbNdVTNXd^bVLVVVdFLZXPRXXVRR\P^ZV^\\\RL\LZ\JRTXXPR\dhPbPPfdVZX^`X`XZ`TZV\Xd\RXL`VZPlP\dJZ\RTd^LVT\TdRPdNXZXTPnPjLRLVZRlbLdb\bLdJbVTR`^hJ^XnT^P`R\D`P`J\NTLbZdVRXbTP@XLXVRXNPVV^bbVjPXNZXP^\RJVXT^RN\JXXJbLPJ\P^\LPPL \ T V R P T VDV\\N\XZRP L###"X#D%\%V#N''&&L)(T)\++./Z.N.T0Z1.X0../\-R-/P.f/2P.22V4X48Z:N89842342^53784J6P88X;T=d=^A=?P>\?=?@R<=;^<9V98R<:;P>\:V>@^?@LE\ADd?XAXAZ?R>H@V=>`C CN?BDEXJTJbJIL`QPRPdQJPOVOXOJKKTIJNHITERA`DTDXAVCAADCVDDZCXHDZFDKRIHXGENG^G`KFNCEGEXIVKFG^JVFTKKZIJJJKRKKFVIZJDIHFIHFVKTGHFVFbENHjDJDTGXFVEVBPE?AV>?P>R<V;J>:^98;:L;T?P=>;T?=N<=h=>R:`7;X85b67V5b33R2b362J7T343T4Z4F774^744f7`866h8867^6\5^6X6Z:8:6H;V<<ZABd@?C>\?N@;??A?fDZH^HIdKVKJIXMXNSQRUPOlNMIJMGFNGdJ`JNLRQNPQQNSXQXPRMO`OHNJNG\FXGNGC@hBZA@RBTA\BNEXCETEDGJdJTIHGRG\MN`IJLIGRHbHFVFXE\GTGEVH^INJZLOPNXOQQOPRUVT^SQUVTWTVXV`WZYSUPUJQLRVTRSSWWU\WT[XYPWUTTU\PRRLQLMVNIKNPNlMNLK\JGHTK`IIdFHH^KdMJTJ\KbKZNLONO^PTPZR^PQHOXQZRNPRSO^PP^QTR^=V`@;=V:V<;T;:X=T8d;6`8547Z53L5h121/0R.Z-X0+f,)))V+j*\*'R(R+)f()*^+b.X*(V,,b,P++H-*b*b+*)^,\(X*,*R+*T)X*+h*Z+^+,R-f,0P-.Z-./\/Z/0/d0R--X-P/b//Z0/L0T-,H.0-T--`-,,X+L++)*)*)R*^*V*H*Z'`'X%b%(^')'$R""\#$V# !#!d!^ZZ` VZ`^\Xd>VV`J^\Tb``` \ \ T T ^ d b T T \X^XDZPdVL\DZRT^bXNbZTTXXXZX\\bZFbF`ZZTTDZ`\`ZFfPR\RRffbZ\TfRJLXXjZ`RRX\^RVfP`Z^\<ZT`TVbXfPf^R^RTh^XX\`PXZTT`V^ZfDlF^`^b^XVTpdTT^^l^R^bfXbj\LXXNNVhF^\ZZXN^NVPTb\\TTdTTLPVTPX\^d\ZV`Rbb^RhZnRVZd`ZNTbb`LhbR`Nf`d^Rh`VXZ`bVXVPZb^PTV`b`T\R`NbT`JdZTPBXZ\^ZPTZjR^J^XRT\ZV^^X\HbJ\NVZR`RTdTbTdV^Zf^`L^ZbTXVRN`PVVTVX`TXVLb\nRXZPdX^FLjRddZT^TbBRT\Nf\XTf^^R^JLLZNddh H f n P X Z ^ X H V^bFVP^^R !V R"Z$"X$$T$V$$$J&$Z%Z%&B%^(`()Z,R.6-.Z.V0.P.X.H,P,Z--h--D.T-/L.^/P247H8d6P988J564464Z56H8\6689??\;@==^==;=<9V;V:b<<8T<:84^4X21N5T5R7`3L14332N7L5H88L99N9Z66N5T45d5^55Z98R87;988:J9^:V>X>NBAAH?>?^AN?=N;B>A@ZBFABXDETKPKZKJPQVOTT^SNSXRNNONSNKLKIFMKLMROTRHSHQQVPRSOORNKTKGF`IXFXDbECBBVBB?ADDhIEE^CIJFbHE^HHdHLJ^LKVIIHITJIJDJNE`GVFTJbHKVJMPOLOTNPR^TbUVbTLUYWXYTVNUTQQJUZRpRQbSLRdTSVTWLZbZVXUVUZWTUOXOPRPNMKQMJNMNPLHIIJZNJIHLIKLXNKKRLUPVLPQNORPVRRMP^PNNNQbPQZRURTT^RSTPTTPSJQZSXTTTXXZZ[U^W\T^[Y`XWXWPURVX^VLS`TYXYT\SVPRRZVS\PDNQL^L\OKObLMMP\TPQZP^PQPTRLXTUUNUVWVVLW`ZbZJXXhUSVRUQSPTNbPPLJPLJPL^LNDOPNZJRNFNNRPNNORNP^OR\WORONQOdRPRQFMNPM6QQPMNMKXKOHMPV\QOHPNQR\MRNMO@PMTMVROSPTbTVTUPSPOSVP^RVSVNWOQDM`N;V@P>X:X?Z;8:L;8T8\9f864P8`73Z223P0X3R1d-Z,-++X*T)+)+V)X+b+Z+f)+V+*Z***P,L*R0*^-,)))Z*'h*P*.D+V-d+`+)b-X+^,-*\)T,R.L.R.,/P0/V/.F//1P2N.\1/R4.R/^/,1.1Z-\/0/-.--,P(Z*+V)R+*T,J'(\))(X)'(R&N&&b'&V'!!%#!\"T""J V P^ ^VP^RXLR\RVbZP\VRX^\XJ`J\T  j N T b b ^ V XB` X XRX^fTR`TRH`ZNV^PNXZ`NRT\`Z`P\fJ`Z\Rf^^T`XhRPd`VNV\PFLV`bV\LVTRXVfP`V^f\^dPbR^fVP^XbV^Z^TjTdTPdTJZXV\XZhh`R^X\ZR`^VJZ\^T\`P^X`d\Z^ZVRXVTTZNRF\XTTVd^NZFRdTRR\^VXXTZXR`TTNXLT^V\J`LJ`JjdV^bXfT\Xdh\\jTL`bThL^dZXXZdbZX\XZTP`VZX`XbbN\VTN^^dZ^^^J^PX\hRD\b^`dPbPXfPVV^^XXdPXT`VV^j^LNVPNfTT\ZVXXJdRZdN`P^PTR\j`VXZ`hHb^^fZ`RZRTbRTf`P\`X`RbT^RX^JZJXVZ N  V V j< ^  ^XTN\\ZbRX`Lb`\V^ZN"!"%`$f'&b'$\%$$X&&V(^%R(*+L-+*<,/.P0X0`,X-X.R-*/f.`,/.R2N1T668J7l6R9^63T8L565R8`3546Z7N@b@Z?Z@Z>^BdBf=T;N;:=`;;9<<`=>=\=?V?`9;N;446R6`42V32T2X11233V33L9:R:T76V7:\8^43N226R55T6X:Z77V877R@\>\B`>ZA`>T<>ARDBZDGFEKXKVO^OZPFSRTNVR`PPPVQZLKHJFFHVJHJNOROPRfSVRVTZQdKIGI^JD^GVBDPCTGPCB`ARBEERDZDEEFETIFHjKVH\MZLVMJIEEGfFGGHHEHbKGLOXPPQXQR`TUUZUVVTYYVVUUSURUVTTPPQRdQTZSUPUTW^XZV\WVWXlYNUYSZTSQOhQZNKNLMZLTLXKHZJLJLZHHHIZIXJZLKLK^LP\LZMPMZMORMNSNNRZNLNNfMLObSQT\WXU^OSUPXRLRZUVVQS\VTWYRUW`WRWTZWXYXY`WbUhTPU^VSXTYWTNUSNRdPRXPTOPNVMK\NMLMLOfPPS`RVUZRSTS@WV\UUXX\VVVTYTVSJVXRLRFQ`USHQROQMdLFPJNZN\KLMOLP^RZSRTNQZNP\QDRPU`PBSTNXNNOPN`K`NZNMPLHNRjNNdLTSMNMbPQVRTQFRXVdPTONVO`MMOTVRQT\PRQRQOOORQXSQPdQPZO\P\N^QOLPRPTLW^WSZVBXWXWZYXZVTVRXWVWXUJSVTLVTfRSNSTURV^U\ZZUTXVNVVZROPNQNPTPVWTUVUVXU\SUPRRSRRT\RROXPNQNR\ROLQROVO`PNQXO`OdNPXOFNbRRVUQ`VPORMMTKOZRONfNXL\N\MjJJTKJLZNTJdJPKGIRLNMMLSRKNZNMLNRZPUdRSZRPQRNPLPQUJSLRQPSURWZTZVZUZVXURX^UTVWVQ\T^S`USOXQdNOObOMPNZKJLIGDFF\GEIFFFEJC^AFACD@BXCVALCB@BCZAFCPC^CRCAAdDE^CZEEDDGFGRHJJHPKFKLFEFXF\GFHXJJbINKXKTJGZHG^J`J@IHJI\LEFEZDCC\DbECDDXBZAB>\>V:^=Z<>;;P<9:`>N;R>9R:\8f;\6V42P3434N40P3X424\34N498d8T7H76843T3^5366X77X7P56X89>:F>=TD@P@DRBI\HIKrRLOfSdSTR^UTSVRLRQQHLKLJdGFHHXKKNMPORSZPQPVQQKLIIVJXJDTFBNAATB?D@^ABCALDdCCPJNEGPHHHII^M\LIFFETFTH\HFLIGZGJfIHPKLNNNPRLZSXSTWNUTUXZUTULRVXUXQTQTSTWRR\RLWVQZThSPTULX@VJXhWXXX`VXYLThOTTSXLRHMFMQNZMXLKNM^JZHTKFKHK^HLTLGMNNL\NQTOMNNKTLMOQPXNXNNHQPQORPPQTTZRQPQTPZYTQRQQVRbXTVVYZXXXXZXVYVNZHURWVYTVYUTT`TTQLS^ONLPNZRVPMXML^NJPPPP^RRTLZVXUTWXR\UTVUW\XTZZXVVVPUXWTVPV`UVQ`NONNNhNNLRO\ODPQVSTPRONO^QPVQQfURM\OM`P^RPPLLNbLKI^KOMLVML\ILdLPMRRRPTPR\RNTVDQSXSPRZOZPTJUQTPW^NVPLPbNRTSOfPNTNPPRLRMRRQSSUVRWZVXYXDXRYWW^YV\\[W`ZZRXVZW`STQVUWTVRVRZWXV`WLY`YVVXRTQXRNDQPRTU@U^WXURPUYZSTSPXSVQTP`STfRRVSQO\NVOZNNMZPPQMfPVLRPN\PNOZPQRhSTRMJLXLNLRNPLLDMINJNIKRHJJKJJHIJKXN@QTPZQPAJ@jBCRE@NC^EBAXDRCF^GHFHHZGKGZFFVHZGJEPDIRHJIGHbI^LGJFFKrHLJVEGVHbJRHdGEGDEEZGBJEBDXC`@@T@l?N?Z=T>=>`A?T=?^C@FCGCL`GMbOOQPZWQhSVQQNJOfMH`LIHTITNZMLSZPNPvRfTTR`OOTJLTJGEPFCVIpCVBZA@DBVC`EVC\C^DCFIMJIJIRKJHHLGdF`DEXGhKREVDVHPHFHNL\JO\OJONPVSPSbUSfSTXUW^RTTbUQTWUU`SQNQTQdSQRRPSUTUVZ[W`WTUT^WURSURTPPKLbJKVPJKMIVKXHTG\GHbI^H\IM\OOZOdQZNdJKLMPPHLN\NO\NMLPLPROQbUPROP?CBEB\ANCCC^F\EDDBbFJFEVITGIF\JbKFGXGRIHJJHVIJJILJTFGNHKfLIH=9F=`AZ>?@RA>?V=PEZAB^AL>@HAXECEDG\JNQRQSNQfWSRPSdRSMPN^P^KLVLL\LVNVNNMMQBMRONXPNQPLOMMGJXHIPDETDPC@CA@DECNE\DZGFNGGZIRHJVIHGXHILHEI@I`FPEJECDPFF`F\EMObGMLNPQPXTTRWRQSPWbUVTLVRQTQNVYZSTTbWVTSXSTTLSNV^TT`YZWZWXVSVZZWZRTQS`JMNFO`QN@NLORITIRHNEVGLIJOVMXQbOPRMPQBOJQMMMLPMLQTNPPSPRXVU^SSYRRWZUVRVdWWVTS\VWVHXVZV^XRV\XVFXdX^XUF]YPYWVVV`RSRbS\QPMTNLLN\MTTPPRTRVPVQRRSdTWXY^VXY[VWVXYWSHVNU`VSTTUdSPOVQ^PFPPRTXROONFOTRSPUURTXVU\RRTfU\SSTTbWUdRZNQNJMjLRNXNLIIMTLbKOMVPZKVMOXNRNQQRPSYDWRRRNQPSbUS\WTVSNUdWR`NPbNROFOTO`RTPRPdSTVRPFNRTFVWVXXV^X]\[\ZXXV\\ZZZL[T[Z\[W[L\YYXUXJ]XYPWVWVXUU`SZTVT\RPXRVUXTV\VNYHX\\TTVbSXRQ\STRUTUT^SWV^RRPQMILMLLTOLMLQNNOFOSZPTQZSNPPLMLONNTQM\LLXILJLTIILJJOBLNLNPQFPRROJTP`SONPVTUXWU[T\TRTRONQRQVQSTUTTWSUVTUSTVPURTTUWTTNSJRSLQZPZQQZOJMLKIVLTKILHHHKHJhHCEGDVF`CBfDBA`ENAXBP?>Z?VAA^@VBXAVDCTBBCFG^DVHDREGJIZFGFHGhJHDHFHG^KPIVJNIFG^JIIVGGIJ\GFZE^HbG\KHHDEFEE\ABEZDREhA=B\?<<;;H::V8n;;8\6:8Z785232V4b2T0/0/P0N/+,f.,*T)N*`*R)N*,)H)`)),`*Z,(+)^+'(+(*^*)*T,*++T++0T+H())()D(Z*X*+-.,-/\./`0-11T1\32N4^20-/2R-1/-,^+-.`-+J.R+Z+,)(P,,`,('(&''(%X'X&T&$b'V##L"b#!"!"!V PHjHdXTXLTP\VPTdNTb` R  h ^ P T P h N  V f 8RRR\fFPhR`T\Z`bJfRR^P\bVXfD\`ZVZVZZZ\^^PRTT^LTZP\bRX^DPXPP^TTXZX^n`^ZJbJPPXR@VfVfTLRdTX^HPX`j\RZL^RVZfhbTf^JZ\VPVbRXd`VTXd^fXZpRNbfJZTfVTXL`\VbP`XdjZ`Z^TbRVZ^PdZThXRPJTTfJTPd`Z^LVfJN\dbZ`dXN\P^fhbbXhb\TXZ^h^TX\dbP\j^^TdT^N\VJf^b^\dTXPj`VRd\\LhPh^j^`Vb`LdVRXPb^`Z\jTTRV^\PVdPVRXTHfTZZJh\LdF^HZ^LdfVJR`\`d^PX\^RV`^TZHRVZ`TZXTZP\TdRVdRbZVZJXbZB@VVXX T ZT \ V P L H X L ` V X N`PZ`Tbh`fXPR^PL\Ld#"Z P"%&P'Z$'%$%J$f'%d)&V'+\*Z*V-X-0B,D/f0V,--\.X,T--\+.b1Z0D0448V6796X\;<9\@P=\;>@=>Z>9;P:^8848X73b2P3Z3X22X5`4958N:9Z4R696^65J8`5H4^64V5Z32F4L6679J8=V>V<@^A`CXA?X@=>`@PAXALAAfAR@NB\E\EDXMfJKMROQOSVRVURTdPQVP^NPPMRNdLZONMOdPPMPNPNXPVPPPP^OLXKKRIFHJHHXI\ERD^DCHCBB^BTCBCXEDGHHTNZING`HTHVFHKRIZEFBEDdECDXFGGbHHIMZLTNJPQPRSTLUS^SbVVTJUTSRPTbVV`SZTfRSPVSNWVPQbUTTUZZX^X[YZVVVDVSXTPPXRLSNZRNPN\NLJIGVKTIGLNJPMLVNMfPNOTQVRTPRQhTNNPRPNN\P\R>S`TSUXWRTTSPV^RVWbYVP[TSVTVVYZSPVTVLV^ZV[XZBXJZN\YYb]X[ZZ\]VXYNYPWZTTTXRNOOTSNMbPRVSURRP\RQRTVRUXXYVXHYZZVY[YTVfWVWTXZV^TTPPPLQRObNN@OQ^Q^QRVRRTNTWNVTWWFZTTNUUVTVU^XUTTQ\RPPM^NRKKTKJJXMKLLOXPFPRXTQUUVVVSTV\bUXUVJSVXThRVTQUUUZSVSXQPVLOVRXQ\SdRTR^STWRWfTUXXWTZ\h[\XY\\YRX[nYYXVZTW\]DZTZZZXXXXZYPYYZVTVXW`YVR\S\RZSXQRSUVUWRUZVRXTVWUPOQNQR\S`V\VVRTQQROO\MLNNJRKRKRObMXOXOZONNXQQ\TNZQXSVSVPLPKVKPNNRNOVOZLLIGKbIGKMZNMRNP\OQPLT\PPQR\PPVPQHULUXUZTZXTTRUR>PQRXSJUTRXVQ\TUUTVVX[UXU\YRWTUUTUPfPT\SXO^OZPJLGGDGHHLI\GZI>GDXIZDDZGPEC^BBCX>?\=H@P>V@A@B\ECpFVDAXDXBbFRDXEJFEGEEGEGTFGbHDFVFHdEFFbGdGHJNIVKbGIHNLJdJH`LHKFGhGEVEEHG`GPERCRBDPB?H<=>PA=:V=X:X;V<`;9^;^7d8Z9T77^53N302`3N1-L2l2/P,,h+h,\,*T)(T)T-V)V(T*L+)*((b*`)'*^)\+d,R)P*b,T*X*L))V.*^*V++T-J+N*f+))V)'T-P(J*,^,Z.,`.^,R.V0X//2.N-.3^//0X/4\1/J0T0L-V.V+^,Z-+Z,+F+^-d*^++)f*)++@*'&*\%$R&X&V'$"N$$`#V"!R!N !P""\\V^^RZ\JT`JXb``\VZ^N` V ` h V\  XhhRJTV``ZZZZfJ\N^Z`Z`TTZZdfT^`VXLbX`b\^LZhVVf`VXdZXLN`^ZbbVXZV``TZV\`Xbb^dL^^ZVR`R`\Z^\L^`bnPVZdHT^Z^bPZhRddVZXbX\PbHX\FR^RV\`PfX`VfVJ`\^V^^VJ^X^TZHZTVJfR^RfdJ`TT^bZTRf`\ZPX\LjbXb`VD\LVrHX^dRX\\j`TVbbPfPX\`\`Rp`\T\Xd@^b\Z^P\XTfRNRZJbTf`TVZ^JVZ^VbdhZ\hVhZ^Zf\RZ\TTPjTNhVHTFPRXVXPTbN^TJZTXbDThVVVJPTVTJXXHJbJRLN^@X`RPVZ`RP^TNTR\^T`VXPRTXZ\^Pd^ZTVRTT`N^hHHdXZbbNV\PX \\ ^ R Z J Z ^ j P R T ^Z RVNV`NZb`ZRPTT R#"$&d%T%^%%%F&&T#R%$&&^*`**Z,\,V-`-/-\-R.,..-X.-+//R1/46R7R87L89`:T88H:V:6P6f5666R7\9Z;:V:8^:>^?=>?=V=99^;J8D8R9<<;;;<=RAP>>f?>?R;T:B9P;6766V41P521f2P2Z125J6d668j66Z7D6^74V5244p53217455b7Z:R<>L?>@?R@>=??DRDCBf@@b@AVCVFHfHJKPNPQQbOQXVTSRS\TTPRTNXOKMLQXPVOMZMRON\LORRPONQXOfNLMKJJ\KTNZGHPFFbBEXC`FAAFF`BRFBRGNKHGIF^JRIFVLHKGRJFCTFDVCDTB^BC^EZF\EKVJNLTP`PZMRTSSS\UVTYRVRSTVTWhUHX`TVVS\VTWRWVWXTRXUTVYTVV[JZ]YWLZSJXTJSPPNXSXNPJUNSLNZJIPFRFFZHbJJKPMMMQLNNONR^RSQNO\Q^NMNSXQ\SRRQQDQSXTUVVUTTRXSVTWUUJUVTXYnZVTXZf]H[VZdYP\YX_XZR]\X[\[LXT^SSNTZTLP`PVQXQQTRUSVTXQRUbWPW\YV\WZPYYZW[ZfWYVYTWX\WYQLSTSTQ`QOOPNRQFRVVRVUSVVTPWZJVWZTXWWXR^YT[X`URXT`QZOZOXOLNLKRMTOILJPLQSQRVRPQVUQNQXV`VfZ^\RXN]VTSVVTTVUSUT`WSZRQRXQ^Q^V^T\SXVZ[l[FX^YRXPY^XVTXZ`Zf]FX[X\P[LXVZVXXYVZF]`]ZX^ZY`YXN[Z[YYYXNUXU`VRUNW>VUVTYRNURXUSSZSLRFSPWSVTR^QPTPRQXQSSSNSdRHRTRMO\LPNRNNONN\P>NdNOOOTjOOTPVPJQNM\ONMJSNONLMJLLGHHRKMJOXQZOTOPZOXOXMZPRRTRSQHQRVSXTWSWSR^UJROR`PRbTRQZV^VVZYYdVTVZVVTTWUSTPVRQPNfOJ`JIZIGJGIGbKHGXEZDPEDZD@BDFTDA`AHAND>Z>V>A^@?DNEAAEJBAREA^GDEDF^H\HZGFGfFXE`IJFFRGFNJZGbG\HGGFfJXFH^KJfOJF^FPHPKHK`IHFFFFCNCVAZBAD>d;`;>RXA>>;T;Z<@CAAP@@\AXDXAPABACZAXBXGDHHLNIOVPS^OQBTR\S`TMOOZMQNZP\Q\NVMTONMVMZOPNTPPTQXSNOZOTNLMXJLG\EEXIHDCNEC@ABBEXGGRHXJTJJfJZKJ`HJ^ITJGGBCA^C\EGTED\GHGINIKPNZMXNPQZW^R^QXSXSXRWVjU>SRQVTTUTZZUBYPXUWRWUPTZXPWTX[XTYYS^WSZSQKSXQQPPVO`OJKLLPKTJHRMJJVLVLM`MZNTPRRVVNWVWVRRPK\OO`OONS`S`RNRTRXRSFSNSdXSXTXXTUXVVTSSTTUVXXUZXXZYdWWVWZ[YXYT^P[`Z\Z\d[B\TRTVS`TRTQRRRRTZUUXU`TRSUfYY`_TZ`ZYZ_\[[\]V^XWYZY\XZZUUWZVSHTR`RQNQDPTUQRQNRRTTXUUXJUZVZRVYZYZY]\^[XRWZVPT^PRQOXONVMPTPNJSPQRTR^P\TNJS\VPTVSUFXNX^YTVTX`[VJWWYJVXTXXW^URVLSQ^VVSXUNYWfVZZTWZX\>XVZ\[V^Z[TYZZY[ZZY^ZXY`]^]_]\[P\YT^R\T^NXZZXWX`XNSVVVTW\YVXXZYNZbWLUZTTRURRUTbURTQOROnOTRNVSPSV^RfOOTORLMhN\NN\QQQRRQ`NVQONONNMVOVOPPTQMMMRP^ONL\MM\KNJHJ\JPIJM\MOZNZRQdMNQNPhRTPRRZU\URUTRWVVVVXWTVRR\URUTSdRVNTSWbWTWVWX[XVfX`WRX`WLW\TVVRPUXR`QXO\M`J\JVJEHJVGGIHGdEHbCDDDLB`EbETFVFB\B????X?b?NC@XCXD\C@BCD^BbHDG^FZFVITD`KXJHEEjGBVDHVIFCHEVE^FTGF\EPIPLJK\IRHVDI\HEZLGGAVFEB@DLBC@`C^@>d=?`>B=<`:8:79:X;9655R75`43F3H12X1R.0.^.j-*P*T))(D+N-`)R)h'^,'X.'\*)^*X)*P)+T-b),*N*)\(+V)X+-V,(J*+)*),T),L()F*d')P*(+N1-)*T.L1X1-Z--X0V/1.V/Z2.Z-V+--+P+b+*-\-+.T+P*)(*P)*R('V'`)$+''V%N'\$%%!#"^" f!H!! \RZVTZZdXXPVLZ^ZZRT^ZZV P f T T Z X b  nR^dXf^b\j`XXPRXT^XZZR^V\XXVbR^\^L^PD\ffdfPVPd^NNTTRT\VXXZfNPZVV\RVTZNNNLRb^VdP\``bTlNhTVj\PNZTfPPRJRZX\\TjVPhXZXZVXd`\b\bT`VbbTPZT^N^\bFNXVTdT`\LZJZfRtVdR`\fXZ^VhV\NJXFXVR`VZRRLZ^N^TJPLZL^\VddXZZ^VfbTb\RVXdJ`\ZP^ZVbXPVbZVZJ^\`bbbRbZlVfdZPPlTX\RT^FjTV^Z\V`P^L<JT^TX^TZfPNbNZ^dX^b^\PZ`PRFb\TV`dVbNbX\^DV\\TVVVV^LDN`PdZZFXPdTfNRNVd\^f\VbVVNTXPRJPXVfRVR`TLdT^XbNJPVTRR\R\ZbLPV Fb X N H b V Z \ ^ T X T \ HX^`VNPHX\!l"##X#$V&$Z&%$'F'$^&'%)V,`,,1+N-`-/.0///-,d/Z.j.0/3654T:78:7l76T8796V946587H98T;;`=D>=X=L>Z>f;Z?Z=V<<89V976X4^43P1V2`0V2566N69Z75:R654Z796636X65Z5Z24R5\6R87:T>N>=\>@>Bb>\@fAV?\CX@F@?NDBARBJ@`BAETBPIJKOQXMOPJSTRRVOTMNMVNLMXLLNRMPO\KNTMNLPO\ORfOOZPVOXOKLIVIFNK\EGEDCZC`C@\ABCFHETEIhIKJOHZJLTJPIZJPIIBID`EBRFVENDEVGVBE^GGRKPKMVJZL`PZPPROPORPQfTTUJYTUWUXNW`THTZUN[XYXXWJXUV\TTX^VPY`[\]VWJTWRTSRZO\OZOPOO\QRNMTKOLJJFMOJNKMMTLTLQ`OPRS\PNRU^WDSQN\PTOXROQNRQXPjQR`QUXSTHUTZVYTRSRWjUDWWWWUnWJXZZZXXP[Z_T[T]X[WRYWVRVUSSOPPRJUTTUPUWOZLKJFZFTF`GETFEZEFD^DCDVF\DVDEFB@V>@>A>HCAC\DCFC?PA?=DBhFEZCEPFZGGZKZGGFEVDRDDHF\F\FEIEIFFGFVHJXNMTK`IEDNG\G\HEVGAC\FCBTDDC\BdAAA?;=Z?V^^JRZ\`^`VTPVZ^V^X\VZZbb\T^ZRRZNTb^^XZbVb\X\Z^N^HR\Z^\dZV^PTZ\PXdXfV\`HZXXbXRP\\XXJ`dVPPXfXVNX`R^dNX`NZTRZTVT`N``ZX^HVdZZJZ\RPXlhfj\Z\^Vb`jf\f^XffTd^V\^`d`X^VZ`jXb`bJh^XNXRVXZ\FbR`bLNT`Td\\`b^`\`V\VdLdVXX^`ZLTPLT^NNVZFb\PT`RVZVL`HfVZ`^bR^PZ`XdVTXJ\\NlZd^LZTZfTdf\@VTXV\\T^`^TL^^RZV`T`VXfZXPVBVNV h XT \ ` T V D P XTNVP `X`^\TRJdTT\Z`NX  !"V%R#Z&$R'$$N%V)&^((h'((J*)L/+V//Z//0P..^.B2R-0V/,.02X2Z4536N7:N8X9T67T9P7544R4`544T6\6`6\:V:Z;H@f>@\AV?d=>T:;V;R:V<:X;=X;d;:;=:L?T=bA<^>V;L9=8:97R64T3Z3T3N52b3`4Z9^6:576h65Z7N7446^75X32R5N4T535X9V:Z:;T?P?fB?=Z=J?Z@N?CJ@L@dBAH@ANB\>BZAREFCXGMNXLO^OSOPRNNTUPZNN`NNXKPN^PMLLLKPNO\QROZKTOOPXNfKNOVJITIHJINGDPCA@VDPEDBXFFGJPHTKJJIbJbHJIHPJbFDZECCCACDPERDfHM^KRORJXKJJ\KLQ^PbSRPPhUWZXZNVVV^YUZXTNXXVXSRTUXZRTSYXZTP[TYRLTSTUOOQ\QNRSVPOXNM^PK`KNPLMONRPVMSRVOQZSbVRTWRXRTQPOFPXONP^QRlPLNPZO`TQXRRURTXXVLXUbUNUfULRNVWWVZW[VVXWVYVXYX\NXbW^[\^[RVX\SPVPWWTTTVSXWL[BUdVYVU^VZXZ[Z\ZZTX[RaV\Z]YbZRURWXW\VWXULTPTTT\UPSPRNWUX\UURS\TVVVZUPWVTYUYHY\YVZVWZDSTRVbSjS\NNPRXPVbUWPbVNTZU\VVTVR\SRXUTFUQZXRVRYbXYNYJ[VYV[FUUVYWX[NVY\^WRXXWYH[XXWZW[^_[\_^^Z\X[Y`X`[]X[^\Z[XZ[]_]\]^X\N[XWVZPY`XFYYRVSTUTPW^XWX\\ZXT[ZVdRVWShMOOXMP\QPTODNNRMLSTQSTT\SJUjPPVMbOTPRRZRVRRQNOVLOMMfKLdLNLRPNHN\NdRNPdPPNTMDJITIJZJNNL\ONP>NXSRNPZPZOVTW`VVWPURTUTRVPVXUUWVYhXVWUUV\TUBWNWRZZX\PWTVdVZSVURVT^TWXUTTRULUPHRNTNILGHEEI^JHDVEXDEXDRCFB\CRCBC@T@>:>X@CV@XAADPCdCA>>\A@BEECbDGEJVHHHPKEVEECTI\DE\IGFXFIbDIRGLKTLMJXIETEVHH`FVHEC^ETCNBNBPDCC\@\@`?N?V>P;;>X\::V<7755`7L4^5\30^110T3\0,-,++.h,`'+*)b))`)R)('*)(T)b**`-,-L-+P,j+b,,V*+b**P)^+*)N(H)X-+X*)\+F+Z-N,T-,,R0`.X-,\,,0P/...^.0/N--/0N.\,+,N*,d,,++))**)))(d((&L'd&(\%&&P$Z'$H#\"#V"!^#X" !VRr^\^dNP`ZbVVTRb`L\X\\b T J f \ Z b h T P L ^PX \ PZRPjPZNRb^NbV\JP\\XjP`NX\T`T`\\^XVd\L\V^VLHbRVVDfXRbF`RRXVvPVZ^^RZhRXTbT^LXXRTZRTRZjLXXVTdb\jN`^X^dZhV\d^RZ`RJP\`ZBXV\RbTRVZ^RbZPNZZ^ZZ\`VNdZR`R\P<TX^R`TRNDPRN\\hj\^^bVXf`jVN\h`4n\hTV\ZRZRb^8TVTP\T\N^XT^XVL`TT^HdLT^T`X`V^b`VVbXfNZ\Tb^VT\`R\TTVTXbVNXT^ZHP^PTDLRRbT^`FNZ`\ZV\\b\RVXTLHVddVHPbTTTNR^N^dV`\TVV^Zb^XL\PX\X\\\XTT^R`^X^XLZ\XTTVZX` NX\X \ f T ^ R H T  N VR^^TPbVRZRTXJXTJR!T!L""%L$Z$'d%L'P#&T'&V'%Z''Z'^)\+R,-D.^-,R.P/0X0T/.-^-.T+-.T1`4R6T8547P?P@\<<;LD@XDVBCJBNCV@XE\CXBA\AZA@DCZEXGRLNKNPOOTRPNXOONPPPLLMKONN`NOLI\NMTNTORQfPdPNLdPbNL\LLJIVPHHJHJE`BLDBAD\BDFXG\KKKKTIHbJILJNJGXHNFEGRFZDDXIZD\E@LEIhJMHHVITK^KOJVOZOSRSSU^WNWWbTUJYdT`YPUWVUPSVTUZVV^W\VXX\VZW]\WVbVPX\XTTTTZWTS`QQ^RNQPMJPMnPNMO^ONQNNMPNdPQTZRNTSVTUQTNXQXTPLOLXNbOPTPPTPW^WRVVXXZZLYRVVXXUNTYXVLUjUbT^XWZ\\WYXYN\W^XZVXR\USPSTSTVX`VSWV^XfXYPVZRUVZNY\[R^RY^\]`N_^YZ[TZXUXWZTYTRXUSXTTJXPWVUXZRRSNTJRSQRVSHZNYVZX[XZX^`[\[USTTJRPXSXTUJW^ULUXT\LZFXPUVVSTTPSY^XTTXWUXbYZ[X>YDXZY[JW\YR\[\YZRYZZZZXZY[YNYJWNX\UVZVXbY[[[[RZWYWPWTY^\XXWXY\[FZ^`Z\`T[[YUYHVWZXVXXV\\dZ\[YYLZWVXSQP\O^ObPPRRXSONQ^OM^OVTQ\UVVWLTOPPOTRVRjSTPfNONMPLPNLLKM`JN\NNRQ`MMVMNMRPNMMfMKILbJKN^JMPPOORTOPNPSTYYVSUbUUXUVTV\VPUXTRV\WV:WWVXTU\W:VVWJ[\YJ\HYVNWXUZTlSTYTWUPVJSTVOL^LPOKZJG\HFNHVHNFDFATFEZCBTFB>BAH@?R?@AZAXB`CXB>@BA@?XAXAE`CLCDCREGZGNCBHNHGGCdE@EFVFVGXGRJRFRHHHHGPHbFINJHXIZECJI^HDCE`CZBA^E@\CLD?^?b@X><@T;V>R<\;=9Z<\97P888T9T5X7F625V4R1^0V22/V1/.b-\-L++''X&X**)`+**T)^(()))*b)H+P,)`*+R,-*)+*)*R))R*(*'^-j*-R,*+V+`+,.+X/X,,*--N.N000L-/-b0V.+-./-\.,+Z)*,V+`-)`,T,**+'&\('b&T'V)J(d+N&'#Z&#\%R#T$`#$#N!Z!f JXZ RV VTXPHnNVNXVXVXPX^Z L V Z \ X Z V N \  ZP `TJL^\VVZT\NVTRRhZZXLZV^bT^fXh\d`RNVXjRNV^jTZNXVZbb\XXXXpRPbZ\\T\j^XHRX^\N\TRPh^PXTJVjPVX^^\N\VX`\D^RVbLZTdVNb>hV`RP^L^L>X^Z\d`HP^bJ`f`^T^J`TZZ`VRbXZ^bLLTHh^RRfTNbJVbZRZTPddZ```d^X\TVhHLNbtnTb\ZZ^`\RZNhRdZfPJb`Xj\\R`RZZ^^VPXZRF`b^DZ`P`^V`XbJ\TP`XP^V\XXXTdXbJ\bVZB\R^Z\XRNXhH`\TVBZ\\JTRVZRZLVX`R^XZPPH^RTX\XZPNTbN^\HZLVdLRR`b\X`^\hbRjd`HTR\V^VR^T^b f`^ R \ T d P \JT\L\\VXj`J\\T\V!X$!!P#d#%P&h%V)%%V&''P*&&b'+)J-/T/R-01/Z/d/10-Z.^-,-J0514Z5T65F6d69V:;X;9b9V8^6P5362456669==X@X@V>ZAP=:T@V?9:V:;Z8>=\;;:^9^;Z;<=X;R6H69Z4355P55J587P97L775P75^6537L3V85h43425Z2^8T8:<>P@;\@Z??\>?VB\ADZA@B@Z?RCV@BDZHFTJK^MNQXQP\OQPQRRT`PMM`MM\MMdLPLLJVLO\NRMTONLNVQLLMJLN@JbMGVD`D`BBBBDB^GEIJ^F\KfIJPIRKHHG^IFZDNFREEDhDVDTD^DEPDTEIIMZLPHLJ`JOS`QUUQ^USHVRSZWTU`WWWTTVBVNUWUUZWRXYUfXTWVVVVUUUTWRTR^WSRRPQVOTP\PNNO`MLTPOQMPMVPTQQQPUVWRRJTRTPRRXPP`SJOO\NbQ`MPPS\RRURLVWVXVZ^VVUTTV\WRVX`XRUlTRWVLW`V\X]V\RVTUY[\j]WVV[XWWfUW\TVUVXYbUUV^XZWXYWVYW]P_`[\]\X^VYXXWP[YUVWFWWVLVVVWVYYVXPUSQPS\RTVXXR[VY^W[ZZVX\N]\X^UWPVXRTTWSX\WWYUVXWLXdVRYUXWX\YV\UVV\VNVbWZf]V\Z[VZV]T[VZZ`[[`]ZY[YP^[ZYZXX\XJYRWVd[ZX\T[^J[[\\][`YUZ[PXb\YY[b[V[Z]ZLYLTVRYHVXJWL\U[JVVXYYNXYfWZSSZTSPRQPNRQPNQZRRMVMPQ`NXQQVRRVZNSZTQQXQTOdRTVSOPSVPNHNRKPZPL\MMTNMOXMPLOMVM`NRRNKLOLONLKNONN`LNN`POVSPRRRVXRYPWRXVSRUUPYRVjU^URSUVVXYUU^TTX^TTV^VdYLYXZRZXWN\XXRWVYUUXUZSVRZOZOPVMJKJVHIEHH^FFB^EVDZCNDRCCNBL@?R=>?HAb>BF>\AT@b@^@@@J?CNA@CCABDBZ?CDXJEZFNEEVCRETGJFRFXGGPFEERINFZEFH`IGZHJ^GGFVH\KEXDCV@B@NBBARAV@@A>N>=R?b=;P=d=R:8d>L?L?J;<<<?P:LXA?@>`=P@@AZC:BAENDLFNJJPOXRN\NOQLRNQRRHPQXQQ\LOM\O\NK`NK\JJKRMNPPOQJQVONRPPJN`MVMVNJVHK\EANCbDJBBEXF`C`FF\GHJJHHXHIdJDZIRGZFD\FHVDPEGPHPEhJJC`FG\GbIVIIdIRLJONQS8PVTZXNXFXWWJXTVSXWTTWVSDU^UNUZUSfVNVUTSSXUVUXLXZU[XfSQTPPZTRVP\PdPQZOXOOPPdRVNZNXLPQS^QR^VQXRPPjSTORROXMbQNSVOQPVUTVRVRTU`QRBTYXWLVYTRSUXTSdT\R`TVXTUUS\XVZY]Z[Y[YZXZJWRXUTZUNVZVWWXX`XWUTWXUfYZUUZ][T]\`Z^^X[[^]ZYR\XXZZLXPXZWPWYJ[UPXTVTZZUSSdUNV[]LX]\VYYUd]Xb]d\^XYXZHWXWZXVZ`[UX`XNZYWR[XVTY[RZX^XWT`SHWTXYb[RXHXZ\Z[`\\[\T\^[VZZ[ZX`]\Z\\W]]ZXYXRVVZ\PVZZ[\b\^ZXVYNYXXWX[W\XZLY^Z^[ZHX^YWVNYb\PYXVUWTJY^\\XYTWYU^UFWRBVQPLSjQQZSVP^TQP^NVNPTQRSTTTVZTSFURSPQSOJMLO^NMTNRQOLRLTMQJNLVMDMZPKfPMQZOXJ\MNN^PHMMRNPNONROPhQR@VXV]VLZWXRLVZSSZV`T^SVW\UWVVVT^UWWZVYXPX[TW`XUXTWLW^UZZ]PYVPXQRRNXMNNM^LTIVKVLTIVFGFD`BADVGEXEJCZDN@<=?T>TBLBP??==@\?B@AR@DRDh@@ZBC?BdEDGRIJTGEhH\GGFHNIfGZEXG^GFXHFZJGFF`HLJGHJJZIXFHB`BDABBDCD>=N?X=b>?V=?=Z;:\:P:d676Z755T6533.^0/0T0-.-.`,)X*D)d)P'V(^'F)+)Z)8)^(Z)X)R*+)\+Z(\)+,-(*^.(T*)P)V'\'F**(\*(R-R)R,X**L+*b+-J-,-V,X2L/2\/`.\/X.`.^1/+,,.Z.H1*,d.N+,++,b--)P+*++)F)'&X(L)'Z'*''f&T%Z$&N$%#"#"R#!X!^ VRL\HZTZP^ZZ`LTJJd`T P ` P V T ^ T V ^ Z R ^^ XV`ZRR^^\PX\ZZ\\ddRd^ZXZ\T\VNVZ\LT^P\L`\Pd\pffhZJL\RXRNVXT\R^bRXP`TH`H\LfVTX`RPbRZZH^bVHVbZRZXbJdDbVbfP`VTT^\R^T^TZXhNlRXP^^\TbTTj`^d\^^^`\hNTZbVd\bdLlJLVXJZXh\VbZ\hHbLVVDZVL\dPXXR^RXVZZRVh^^T^T\\T\xL`X``XXPdVLhb`DLdZR^\^TZNh^^TZV^\\Z`jR^fVT\^\PXTf`HV`db`T^Z\HTTX^ZVRbTRdTVP\TXNZL\XPZ\XXjR^`TJfhPP`ZbP`\VJNXX^bXXZTVXV`\`dRRhZVZVVZjN^ZRfX\ZRX\VP^ZZR\^HP`f^b\`\^L`ZbNVd \ R P R N VPV L LTZT^`V^dV V!\!T#"T$%X%^%%'#`$%D%(\'(R())-X-Z-d///V/`1n21.\.-,-R/0j/2D4252V8X8V8\<9;Z88R5b;X6V6Z4V55\57;\8??=P?^?\>`?V?P>==V;X=X<=T;9:X:9\=Z;R?d;X?=L@b>==P?R>d?X@XAb?X?CLC>AAZFFbG\GEPLXLTO\ORMNP\PNST\RXR\QZMPPJN`LNLJJRKIH\OKTMNNVP^SPPdNXNPNTRL\OLOHEXFDCVB\ACLBEDZFTGHHG`LFXHEVELDG\FEEJZDBXHfECLHGFZFbEFXE\GdKFGIMJLN^LQbSPPXVVYSTVWbShXLVTUXTT\SVXST[T\XUU`TVVRQVVRVUTVVXVVYW\WRVQQNS`ORVOPQORMPROOORPZQS\RROT^PMLSQdSRN@MPJPO\QVSVQRU\RLW\UZR`QSSRPR\UlWXXbS`VJURVV`S\QXSQSNXYVZVZUHVjWXX\`\\^^YV^bZXTY\VTS`VYYV[YZZYVVWZUVXXTXhZ][VYZhX[j^^\LYTXJ\XX\[ZZZHXXXZY^XYbWR\ZVNTUfWZWVXVXVX^]T_RWRYPWXX\[RXVYYXY[ZYY^X\X\Y[TZT]R[Z]XX\[\P\\YY^YXZZ\dWfW^[RX[RWYVZ\]h]XJ\h_\\P\R]]YXZ^VYZV\ZYW`YRWV\W[L\R^\]]L^^[ZX[>]XZY[LWVXYT]N^H[^ZY[N[\\]NW:YZbWXLXW[YX]TXXSdUdVQQQZSRS\TTRP`RRQROTMMMjNPQRR\TVURUQZRRNbQP\PM^M\PVQL^QMQ^PKPNVK`J\GbHIDMLZODNlPXNPPXMNN\N^MNTNPPRQDQUTTRVW:W\XH]YV]WZUTVVZT^UbW^UUVW\WTUZWWVXRVYTXZXWYPYXXdVRXZTXXXVVW`RRPMTM\MHKVMLG\LNEVHEDRDPBZE\FGE\FBNCZBR?TATA?TCBB>=`B?\AZ>=@XFXBCABPDA`D@8@hADGFTHVH^HD`FF^H^IRGFPF^FXFRIZJNLHJ^HEDJIZIKMPLPIEDBBLFCE@E@>@?<@@?B=D?V>PBA?<:Z:X:8V?<<=;:^<5Z4J6h6V783B4V48H7666R688J7878T7Z5T23@5468P576`8T:V;:\;J?@^CJ@@@=XADRDZBBNECEEILKDOKVNJSVO^WTNSNRShSXOOTL^MJTKMJIJJO@LLNNQPPZPNORQPVOTPMZKJJZE`EBDBC@AFRFHEHTFPJdHDCECA\EDGDG@GVECCFHJFGGTDREFERGGLIPLJ^JLO^QZQPSUFWTXLZVUVVFWU`WWVWXLTVVVZUdVRWRRXTUU\VVZTUSVUYWVUNYTUTTXVVW`URPQQZROTL\PNNLRXSP`QVSXTLRVQNTSOTQNdQPVRNXRZPJVSQPS`TSTS`RNSPdRZSVVTTTLVRURTVUfSVPZVPU\SVUTWVWTVVNYZZZZ^\H[T[R\YVYWVV^WVWXWXXTYXX[WVRZZX^WXYZXTTZ]JYW^[V[RZZ`\\\YdYZD[[P[Z[WR[ZP\YV\YX[YVYUVWWX]jYP[TZ]BZUTYfZZZYP]V\V^[:Y\P\YZ[PVX[P[ZYZ[[L[YXZXTTVLWFUUXYW^YHYYWJZ[\Y^]ZRXd\`_]`_Ta_b][N\P_][YZNYPYXVFWWW]X[D^ZZ[R[^[ZdZ\^bYWL_YLYWPW\TaZ\^\V\VWPYZJYRYHYZXZXZVWTZhUPTU^R\QRSRPUQ`ORO`PZPQdNJONjRPOhSLUSVQLTQQXPLMdONQTONNONOBNPOVMMTLXJ\LGIMTKKFQMZSQNHMPQNdQ^RTS\RVSTYVLV[XXYXYNZR\ZWTJXVVWUTVLYWVVVUZTSXXLXVYXZRVTVW[W^UVYXXVXWTVVOOXOVNPOLVKXMPNHGXGVDHFGXBC@FEPFFDCBCT@BNBbBTADC@=^@LBXDT@=V>;:^;7:55R74\6b4b242.2/d-P,,-^,h,Z*(^,Z)+)D*(^())V(&^)P(d((+)V*N+*(T,X+d*((R)(P((@**b+*V)`+d-L+\,,^*R*b))X*^+-`1,Z/J0T.--,P/\--^/,--^/-T,V,T,R,R+*+.+\-V,)+V)N+)+')f('\')(H%&V'%P%%$#R#"#"T!V! " "F N\LhdRLXN^bXdZXZXTJ\T \ \ X f V P R HR TZLLZN^TVRLT`bLXHVRPZPZJZRDXVR``NTRPZXVfZV^PZXZRdX^NVTPDJhTP\NfNZZZRX^HTb^\\P\^^\\\VZhPRZTXZRXT^`FJ\^^^RT^^fH`R`^LP^Z`bVZP\`LXT\XXZ\NXN\JlZbPNV^PVXR`R^^^XTRBRLLfLXH^RXDPXV\bp^fP\Xf^\Ln^XjNNPXdf\\pTXbT`bV\J^H\PZT^R\^dXb`TZFdXTVd^NPXXRbV^LZhbX^fb`^Z^PDZ``TTfTZlNZZZdXb\JDbX\\D\XV^JhlXPPBRXX\^XZZXT\`bNHXZbR`L\\NXTLZ\VBVV\L^VbX`D^TVPLNLZTR^dBV\^ V B  V T X b V T ` Td LbL`XVZXhVd\XT@  Z""V$"X%$J%%&X'@''R%'^#%Z%N'f+Z)X+P,`-,-/R0L2^---0V-J,---Z0Z02T24L5R6X8L:T=T8V8`8b;P9P87:97469;:;@?R==<`@A@BN?>>=^>\@:9:>R:>:b<^>>X?V<:R<>?;V>N>R:TP\==L@=T>XXVTWRVLU^TRTSZSVSTRTTOfQOXSQN`OLNVKdPVMPOXRNURRVVROJRLOQOPRJNOPVPLOPLKVKLJPIZK^MRHIKJJOdRPT\SQPVS^UPQPSRRVHVZWZUP^JXFXdWfYTULWPXWPXYX\YNVVX^VXUUWUW[TZ`Y[\UPSSWRZU^TNWVfVTYZSZTPXOMMPNNLQXL`LHFbFGDDFGFRDND^CGZDZFFDVECA^DV@bBZB?L?@P=<@?@PBRA^DRABCTBVCCVEHCVCADCCDRIGFFHPHGFHFHKXKMKJIJREFHIDFGJDbCNB\?LB@JAVAV@?=>>B>TA^>\@>??;:d=N>=\:V86T6552P3Z5H201L.,L/T-.,X-+J.\*,)**^(H)^+\'*Z(b)(^(\((P))*^**T'*L+((J((\+(),\+-)P)X++b,Z+N,)R+*,`*+X,-Z.,-b0.b--`-.-,/,V-X+--.`.H+)*-Z-V.^++-H+-*p)J)')d**\'%%%X$P$J(\'b&d$"'$X$X#!f!J"l!ZfPZPZ\Xh4XX`bXfXb`ZP\b^TLd`T Zh J ^ P H D L Z X N N \VRV^L`jNZXZ\^Z`fRJhRXXXdVJdZJRfZ`PdXBRXVJ^l\bVLXZZT^fXTT\lLXNLR`LZP`P^ZXXT`NfX`T^PT\`\``bbPRbZfd\LnN`fbN^`JFdVfNVVdXbZNf^TR^VbRV`d\^fZRL^R^TPTXj`R\\RTV^PbPXLXTTVXdZTb^dX\hb^hRPTZVJ^NT^FB\P^^`PV`^b\^X\XTbZZbfRTT^b\``VbJ^^LbVTXLR\XjRR`N\\`TVZRXjTfLVV\`H^BXZXRLNTN^NV`\^ZNTThPJPZXb\P\@XRNJP<ZXV\ZTRF`FJTXTR\VLRVVJhFRZ`LXFXVfZ^VXNVd@NR`XJZPX^RVRLJ`^T`RbV^PZPZN``^Z`VZPV b \ Z F X V R XF ZRPTTV\ZH>dPXPdTHTH`\#V R"N#H$%\%$J%$#`%$&X%)&&(*X-\-H-R.Z.Z1.H0V0-N/T,N/>-F/\/R.205L2`4d67b9T;J;N;9J::N86R7R7V5^7V7R7:8V?V>H<<9;::=;P=;<:N<:b;Z9\9D8;R6866F857\6ZL>^:;b@V@J?T??\@BPBdC\FELGEHVLKKZLLOMNfOQBOVRZSRDSVNKZKGJKIZMDK\KNJMOOLXRVSRQP\OTNLTMTINIZFGCECDDDDHHFFHCAZ@CLCBBFXEGRGbGXE\GGGGETGTFEECG`GZGXIPE^KMM^QO\SVRRYQR^VRYUV^WLXZV^VXVZW[WXVW^R^S^UZVVN[PVUXVV^^YZVSVWXSTVTUXTUVVUXVLURXPRQLbQbNLZMMSRQNSRSRXQ\TNRPhQTPXQLNZMTNRSRLPPQXTJRQQPHTPOPbPbRRSURQ\S`SNTU`TVXWYXXXWWV[\XZRWVNVLZY\VZTWXWVVLZNZJWT[TZ]P^ZULVVXfZBV^ZY`[^[Yj[P[[N[\]\]\\^_\Z^V`H\\bN]b]X_]]ZZNU\UTS`WWUVZVXXT`[WD\N]\^\L][YX^TZ[[J^l]DZ`_]^[^\_XX[[VXHZ^[LY\^V\YZYXWPZWXVYTYRX[[[R^B``V\J]ad_][]`Z\ZY[ZYPX[XYW[\VBY\\\RYYXUZZZYTWTXXhY[\^T\T]Y[V\VZPYWTUTTPTbTBVPSTPVZSVdVPS^TSP\PPSTfQ^QPTPjNNKMMNOQRQ`QTJRSJQRRORNOVTVRRTO\MNJPNPQjPdMBITJ`JHLKKZIJPOXSSZTdTNPRTOORRTSZTbUXZXWT[dWZV[VWY[ZVJUXDXUXVX\ZX`YPUTNVNUJWZY\WXYTXR[WWVVWXDYPVV\WSPSOQbLXQONMMKFDVD^@BVCZCXE^CBJFEdDHB?@CVBLCA@?@\@?=RBVB`AXDNDCDA\EBDFTCpCBZC@TA\CJEC\EHGPMEFPKhGI\EPKNLTIMKIEI^FXA<=@?>LAT??ZCB??`?X?;Z=h>>\=<:R:99Z=R:9D??C`>^>TAXDTB\BCbHBDTFGLPIIJJZJJMZKhNQQP`S`PJLOLMdIJLKNKIZKVLOVMJLbLNOWUVQVOPO`L\LTMJIZJRHE\DNDFLHDFDXDRCHPBVEf@BVBBXF\FXDD`GVHJJTHD^MVFELIH`GJFVHdHG\H>HLKNjNN\QXO\RQVUVUT^Y^V[VXWUUbVdXURXNXWVX\WXWYTYPWYXYWVZ[X[X[TW\UBX`V`SUVLVTPfQnPRONLPLOL`PXP`TQQ\PQHPQPTS\RQLMXNMN^U`RFQQSNQZPPRZT\NOLQPQPRSRLTBSZUXTNUVU\UUbVP]Z[[XWV[WWVVYZYX\RYZ^WWULWRVYlYT^[NY\\XT`UXVN\V]P[d]V^JZ\Zd[ZT[L]V[\T^\R_^]\D^P_``_`_[P^[]ZVSPVRUXYXXVfVJUS[XYXX\ZX`ZZ^[^R\_T_J[\]\XYT[\]La]Zb]T_ZYZ[\YVZZZWX\YZXVWV\XHXj`X\]][\]P`f^N\\Z[\X[d\ZXZY`W\[PYXZVRXTWY^ZX[ZWZZ[X\R`Z<^B_R`T^[l\TX^ZVFWPSXP`PUXSdWWdVZXUVRTVVRSXQRQLQRNQRO`O\LNPT\RR\TQZQShQJRP`MRRORNPPVQLQTNRNVNXLdLM\JKMTMHP^QVdVRQQXSVPQQPNTLSUT[Z\PXWJ]RZU[]^][ZYXHXT^\RW\WUXVXVVYW[^[ZZZZFUUTZWYX^WU\UPUdW\VRbUPRROPPROXONJGEBC`EEECAD@AbB@@A\BXBACBED\BZ@A`=AChD^ARDAPBNCCJEG\FBDERA\BRC\AXDEEdKHVKNG^IPHGFTHXHRKK^JTMJGEEJNHETCEZBZBA^C?@XBBBB??F@V>^>T?=Z>d<:@VAVD?XACRA@`>><>B?J=H>L9`7X9^<\>N<\=;;T;>T@V@b?>?@=\>T:\=Z;`;J;9F:h;T78`:X7Z59N9=R=:V87:7:8Z6d4X66R7P44L633H8`7Z999X9^@@@ABD@@AGPGGLGnFHTMXML^OMXLOTLMTRPLQFROTLVKLMIHXJ`MNJK`MKNPLMOPHSTJTLMLOLI^K\K\I`CDTGDE`EBNBPEXDBAZBABRDDZCVIhEIHGGHGVFDHF\GLIIIZFZHIHPJ^KNH\MQXPZODSPPZUUVTWW\FWbU[TVVVUNWYXWWTUTYWWZYPYVNUVP[X^VXYURWRWY\YWWPZVPYVUQZQN\QMSOZSdRQPUPSZU^PVPPUhOOSQRPXRO\ROTdPVQ^QSbQVQFPTQNQQSQPSRQ\WQS\QVTPYUWRVd[WXVZZP[XXZYXPXXYT[YZZT]XYUUVXU^VVZPXVbXRU`VSTWUPYZ[[[^ZN[^_Z\X^Z\^]WZ[]R^]Vab`L\T][a\^]T^TZ\YHVVV`YLXXYTBVVU@UNW\[Y`XP\PYT]\[^_R^_]\]L[\X[[J]V]T\^\T[ZZZYVXUXXVYTUTUYVVPTYYWJWLYHYYYZ_ZXaP_^\]Za\\@]TZYb^YZZYNWXLYZXHWXTWVTdTXXRZZ\W]FX^YNVYYa_X[[RZZXU\ZV`[NVRZU\USTRhXPVVLYYWUVRSJTRTVRShTR^UPROSNXQONQNPUSHPNORdPNXNXPJOQPNONNPXONXPMPLMRLIjOZJLNLORPRXUOdPVTNOOOTQ`R^TXQT\WZ\T[XjXLYZVVZXYZ`T[YW[W^YVTWVW\V>YXWVZZ\]T\Y[W^UPZW\VUZWVUWUW^SRRSNOZPXN\MRTNXMLLEFVGVDfDXICFCBZCZ@H>=?T@CFJVCLCND\EC@>XAAXBETCFBXAZDPCAXCEDFB@@^APDJEFEVHLGGbIGGZIJFGII\KIIJMIGZKRLXGDZBDR>XBBHCXAEh@V@A?^A>R>=?:;^?=;Z=LBT<>P:8V76R665341R00X..b0/,*,+R*P,*,)R*()T(Z)f&b(\'P(%d'V'(`(V'\'((&)(H+V+\()*^*+))l*,X.,)X,*\-P,+f*+R++*Z.\-+T-Z.,V+.Z0,---+T,V-..N**-b-L*+^,,`,P)-*b*,`)J+^)R(d(J(V'Z($$^$P$!f%<$Z%#R"R#"H#R$#D!LX XdZTPZRRVHP\NbRh\ThTRb V H ` Z` b Z R^ L^JdZ\T`\\L\JXZTL`P`PPNRVV^\V^ZHTRLRH\\^\T^XZZVDdZZdXTZfXZPdbXF\\ZFVZVX^LXhN\Tb^\\X^ZPdPZbf`TbTHXVRRV`PPdTZf\\ZXbVdbVRZ`RTPRXT^X\^PPX^RVP\XDXPXVl`LXF\TZNTLZZR^RT\ZNP`N>^f^VZZZL`H\ZXf^`T\bdX\bfhRfhZVl2Thf`hhbNhHjZ`^Z`VVZ\bhXXfR\ZZ\^^PdV\d^`\ZhL\^PTTXTf`ZZTP\\fXRfXXR`NN\ZXV^fVNX`L`F\T^dbZRZP^XfJLVfZX^XTHPN^^^bR\`VXVbXVN`R`VTPVR\J`\bV\NVXXXVZVXT^RVbVH\ZFRLNZFV\PXX\b J P V N Z P \ P Z f XVVVd^dRT`RXTLZX\#T!V#P$V$^$#P%&T#Z$%%$Z&L'f(,*-/P,N/J4/Z12.-R/J...--.P100R3N6Z;88V9;\9=N989N;N9X9968^8T98;@??X??Z@?PB@P?X>=`@@\>:9`:\::`<P@=VCZ=A>;=V@>J@P?\ABA?VA??LABPCC^DBIHHTJGJRJJKRKOLONN\QNKL`KNKINIVIZIJNKKNMXPLRRNQVRSTR^QTNORN`MdJPKXHLI^HTECNDVD`DB@b@XA@^DND?CFEDHEGTHKBIIGFH^G\FPFKFJXJINTJN\M$JVNXNRSNNNTSFRSTVTWZJYY^YV^W\WTS[TXVZWUVVVU^YVXX^WUPV`XZWVWWVYVVVZWX`WZW^TSTQSVRXTZTQQ\QPRWHST`PXQSXQRSZSTU\VTSPQdRZST`QVTQZQSUTRRVUR^QRNRSSQTVUQZSHQQ\TSbUNYWZXNYYZYNZXR\VXXZVXZHXfYRVFXZTZUXBX\WVWPVYXSRXPV^Z]j\\Z^T^]\]^[Y[]\^`d`Z_L``X]\a`P`d]aX\P\RZT]`[R]R[JWZWHWVYR\XPVVUPVUVZYN]XXVZ]^ZH`_Vb_`H\da\YT[^L^\l[H[WPYUbXVTXbUVV`RT\U>U`WVXVWVXV[\_[P^VaT`Z^b\\T^\XWXWXVXXVYWPYUdV\TbWTbVTW\WVUZNYR_[f[`[XYZXZV]VXVTV\UVSSVTfSVJVZWXURVU^XVXQTUXSURSTTONOQMZOFS^PPPVO\NHSNJN^M`OZNMPNRFQPNNPP`QTQMXOMXLZKKMNMPPRfQRVRQbQNPVP^ODQRRUWX[[XYVHVW[[Z[Z^YX\Yb\ZWTDYZWPWPWVV\dZ]X[\ZY`VXHZVT\WVYWTdWTSdSRQSNQTQbPOPPVMLHZEBEETEDHDC^CET@Z==fAT@XBCBAXDClCA@CLAD^DPADCXABHZBCBnCJDCPBPBADFLEGGBEG\FPHI\HPGJGFZJIHHJRKHXHG^C@@B^@?>@>>T?>Z>`AB=J><\h>\@@A`B`AA@?PAB:P<`<\;@;:<:<@AT@B>^?`AX<=<=d;`>9P9N98N86`76b6R7;R9d:`9L8X8H9Z77P=6^7Z3L646Z4R1f24R6^457^89XZCPARBND^A?@@>ZB>ACGDEDEPG\G@KGIILML\RfNO`NXKNXPOLOKIKTIRKLKKKHILQ^M^QORQKTQJJL\M\HLIRGZHHFRIDAFCACT?@AECFFDdBXDRGGGHFIRITI@JDHHTGdJ`EGIVIOLLHNLLTNRdSdUTSWTWZXVVXL\UVVWUSUVWW\YTVVWTYYXUWb[`ZZZ[YW^ZN][VXUNX^WVVWTVTVRVSRRJPRRXSSPQQUQQ`QVTSRSTVXRU\R^TVQSXXWURXUSRTWTTRbYXVPQOObNPNRTXWPZfZWWj[[Z[YVWUX\JY\VNXWZJVV`WZNXLYZTUTXYX[TZLYZ]\[ZR^X]V\YZDYR[]Fa_P`ba[_\_b^]`^^f^YX[\]`ZP^V\X@ZYV^WTYXZXNWWZ\Z[V_^`J\V[]^P]P^\Z^\\YTYT\L[]P[WLXUVPVUNSPTRNUTRUXTLW^ZYVW^YYR^N\^dc_Z^d]T^X]Z[YXVYY\^X`ZLW`YVS@WRXYWXXVXRXYZLYZFYZ]R[[Y]\TYXYBVZWTSVTS^UVQ^STXVTWSSRRUR^SUdTbWTVTRbTPRVfS`NOSMZOVROQXMZNLLVOVNbQPROZSPMQVOONTOMFMPMMNMMMXOOPXPSPVQSLQQZQSS^V[Y[RYXWUWZ[YP\ZL[P\[bXR\PZVZT`TZXZ[TXX\YZNXYZZR[WU\WTY\UUWRURQQPQSNQS^RjRP\LJJIHHIZEFTFLIFERACRF^EZABREDbFFEDDVF^HPFHHLHdIHJPGJITKH^JVKFCB^@NA@FBXBLA`@Z@`A<=>?BR??=>=`;T=`;T<:<:6X8X5463V4V3/0/-b/1P-/+,\+R+L.+b*H-\.b)Z))`(R(R**X(P**`*Z(X((`,'(X(''Z*R(T))*,N*^-+,+T-`-*)/*+\,P,,,T,,+P-P/\.f-`-Z-\+^,Z-Z..+`++.R+,\,)*\,-+L/\,-*)J+T+R((f*d*X((N(%Z$T('%V&T$L#V"^&&D#X#! $h"F d !ZR X`RX`L^X^bLR^PLVDRbXh ` ^ X L T R N \ \  TXL VdLZ`Z\ZJJRVV\`XVTXXZ`^XD`Pb\\`XbPRZFZVRPPfR\\R^V`PbZb`L^TbfVVVHZPTVXVZV^Z^ZZ`Z^`ZP^XPfT\XfbbXRPjRN\NTV\\\\^`XHPXZbVfNRTXJXVjThHb`^ZVV^^VZd``NTJJ^T^XXFjVXVb^RNXL^`jNVVVZDVhTL^XRLXZNZL`TVdfVnJ^jhZ^N\n`hR\XdX\Z^^Zb`P^TlNZX\NVVZd^fXVVfVbdbXXVd^PjR^JZXfZV^^^b`X^P```\RTXRjX`^PRJZRTRXTR\V\T^VTVFNVPdNdNdN^ZXRRHXfX`RXb^ZTXZ^PZ^`XPVddNhnLZ`VVbVNJH\XPLj\JLbRb^N`dNNhRLPZV``X NZ`^b \ P R N ^ X V Z `VLJR\`PT\\L\Z !\$$%T$^$F&b%$$$j%&(T%T'P)d(^,-*V/^/Z01P3P2/`.0//-V/.V/001T24b56X7:9<?>R?=^A^A?@A?X?<<;Z>P;D<`=:P:D:R>8\>P<<9V;8;V668@856T896:T9P7T7V8T87554L44Z12123R24\857V::=>Z>TBBTCX>AATBP@\A?AVACNCD\GFEVEVCLAB@VBCTIEDDFCVE^IHGECGCdHHLZOHI\GHPJ\GIIZKVH`EFbCd?XA@?^@ZCVBAdAd?X??AVAN>;l;P=;D;::9:V764H7R42L421\0.l0..f.V,X*T+J)P*P+L,,*)P+'V)')(Z(^)P(`*T(L+L))d*N('d((,&P+`*)R,d)V-**.N,V+\.+X+^.+T,0/-*-,.f-,H2--V1^-,^.X-.b,J,`,+J0Z,*L,)V+-,J-,L-*,Z++)B,P(V+(&\'%&V%`%R'H%^'V'^$$^$$"$# V"Z!L"\"X ZZPX\ThTXPRVP`^ZZ`Z  P V ^ Z L V ^ h `X ^ R NXdTNRbdZRZ`ZZj`PPNXZVVPbNbVV`Z`Z\PZPNV\TJZNTP^Df`Z^hLPT`hf\PVh\XVVTPPZZdTXfPZZZ\TTddTd\HRbbf`R`NXZ`Nb`XTXXb\^VTVXdXTZVLh^PTX\^RNTVXTTV`^R\dXNZ^TLndVVdVbfXbVXX\^^jRdjNXZhPVdZ@\^X`VTNN`TPTPRVJ^FPRV\`jb^NZ\``hPX^^bZ`ZdPLXj`R^V^XL^XfbJ^T^^fN^\ZVZZ@\RRTZ^XNZTXJT``PTPTRVf\`hZV0TZZ^PL\ZVbNNTdLT^L^Hf`TL`JLT`PZ`NLdTLTPPdNbN`T\XVPXX\^HTTVV`TZTVb\XZNXPfV\NXVXjh^X^L^NTRZNXV^P V X V ^ \ TL ^^VPT\fX\TLNV\ZN\N" %L#R&$#'X%$%R&%J(\&X))()f)Z,-..V0.V0b0Z1P..1\.1-.N0b42Z24747`67F8N=b9N:X?=`@APC\BT?P?ZE>R=?;\@:R?N;\=F;d:9;d<<^@>AVD@VBd>PA;N;T;H@Z?\;;T875X7f5ZAA`B=><`=H=;N:h;8V;86P5V5b54h2R3`01^1.R--/,,)*b+*`*\(f)*V')^(@'&R((((R()X+`(\((('Z)Z**`((+T)Z+*'*R-^,\.,V,,-,-/-Z-/*Z-J,-.b0/T/J-/`-R0-j-/J.,+f+^.Z,T*J-*)J-++T-/V-f+N+)H*,)+V+T,%'&&T$&R&%T'^##d"$"!"# Z" \ LTPVRTXTdNb`XLTHhTTXPTVX\\T PN R T \ T \ f \ \ZVdfTXL^Pb`\\PLTTVFXXPPRZF\VZRNTdTTZH\N^P\XTPRbV\jR`PPjXVLLZFfbR^LVZZV^`H^^`\^T^PF^X\VLV^^RfXR`\JPRR\XV\hZVZTT^\VfNbZ`L^Tj`XX^JVTZV^fPP^b\ZVPTVHVJdZRXVTRlZdVdXN\P`TBZRT^RPXRXd\fNd^RVP^fbZXTd\^VBX\X^dPfVXJ^Zd^VPhXTTX^bV`TT^ZZd\\XXZ^dfLPP^ZZZR\FfT`JXfNbN`TT\X\^`Z`b`LjZf^h|dXnJZbdZRdXdfTRVfbHThJbX^b^jLVJTd^bXdXXZZ\^XRXTTXZ^fhVTTjbXbZLTPVXZRXd\NJ`TXbX\XXTXZXXZ\b^R^PXVPJZV^`Hd TTT`\N L d b p N T b ^ \ ^T ^ZP^XTTZVZZH\^LVX`^\P"!!X%$#b'$%(V&%&X&)&((,-J+,,1\/21V1P0T....X2X.V-.N1/X1X214566X9T?Z>^<99P;98`8^7^9:8N=8`;??AZ@AjA@^:=V>f=`>X;Z:L:;R<9=J;==?A@BjC>`;;=><><8V75\96T5P6\746R55;7837P8T6763^5D3\2d2X14122486L89N<>T<;b=@>CVA`BdDA^BABAbAChE`FBVFNCIVJFTITHLLJbMXMhOBRjPXMLO\NhLRKFHJIdJIHNKVKMLMNONNVK\QNXNXQJTI\KGDA`BXE@BBECBGETE^G`DZGGG\GGEZFZEnI^HI^HHINIIIMRLDNKPMNOZL\LRRFPPTRVQS`YVdUXVWPVW`ZTY]ZWXJZ`YXYUZWZT[`Y\YWYYXPX[TZ[TXY\XXXTUXVWYRPQVTVZUTWZUWSWTR\Ud[\ZTWNWTUUVURURVVSSRSSVYX`UPWWQ`V\RPQ\PVPdTRSVPTQXSdVRX[FWRXVW]ZZZYZYVRYR[WhYXWbXZVY`USTW`UVVXVNWUZTUX[WYVXWXW\\RZYZX`[Z[X\^__R_\`_]P`V[_YL]_N^[V[ZBZVRWRZY^SXXYXTWUWTXR][]\[VZ\_[N_X\T^V]L[[^][[\V^TUUWRXZXVWXPVRWXWUbRQNWXVlWZbZYj]ZV^[Z\\_Y[Y^[\Z>WVTJVTPUURR\RRPPVQP`RSDTONRPPTMNURdSTdZVY`YYZZ\TURVTUHURfTRSP`RVQPRQS^RTQU@UbVVWDVWTR^VQ`NNM`NNPN\RHQPLNZPfRZP^MRO`MXOROXNLXMJVMNRNSOOVP^MBPN^RNTT\Q>QWV`VTTZVPXTRTSVYZURWVURZWXWXWVY`Y][VWXZUXWWWXXT`TVLTWV\VLYWbUTTTWQNPSTQRTR\Q\PO\OPKIJ\KLXLLKXHETHTGTEERCRCEBATBNB=\>`@d>N@b>J?CETEVHVGRDE`D`BBPCb@XDCLDbFNFVEEPCEDfHRF`FHHHLJ^M\NL\LJXHLHJVI\GNE^GDdDBTA?BTACT@PA?ZAZ=D=\?BA<^9N?;H=VV\BRTZ^bJVR\dNVTVXPPTVVPVTZ^X`VRPT\NRL\VX^\^LZ^bFZZ^dn\PZ`\HhbRjTdRJ V X X X N V P ^ B hfR ZNZLV\XXDhbPV`\b\NR!@ "T&"T%P#R&\'V'%%H(&`((@(T&&+).V0V-.H/D03X0D/L1\2P01T0R/0,/L3V31`55\8T:7;^:;b:9H:8h87P69B9::;;=Z?>XAPCAR?@@R?;=;\><9;:=99:;X>N@R@Z?`@?PCPA?@^>F?T>J<;V9V89:^7V766V85J8`9Z8\:77T57`8`865^50Z411V1^3^0524456N8b;V=<<=A@Ad@D?`ADC>AC>ZC^BBNFBLEZHFGK\MTNNNSSRSKKKTNMPILJTGNMKO\LLIKMNPP^OONPRPNMVJPIRH\IITF^EXBJATCH@fBCC`C`C`DTEDFGFHPGPEEXFJIPFJKTJXKKKMBKXM@JLJJJ\OOQOZTPPTPQLTVTZWUUXWVVZVYYWURVV[XZRLVZV[`\bXZWZ`WYY^XUZZ`UVHXNVNVNUdVUSQRQQVTXTSrTVXUWYYWXV[YXWZYTTXXXNZXTWWdVTlVJU\S`WTVVVTPVTQPTPVQ`TLSSZVXTfWYWl[dZ[VVW\YT\T]^Z`ZVUYXZWVYUTWZVXYVTXTPT^W\VTZURTUWYYYLWZVRX[fXZR\XT^\\a^]P``a]\Z[\YJ[T]N[^\]][VX[WYVRUXSXHZVWRVY`YV\ZPZ\\X^[]^[T]ZZ[\^ZXX[VTTRXVVXWVWXPX\ULVZRVRS`X[RY`ZZ[R]YYY`TZR[FWZ\RXYUUnUFUbUT^RTPRPZPRQOOfPQQ^P^QVOXOQ\MZSVXUPVVYZZX\XZX[TUfYPVSZSNSFT SJQROVRQS^PPSVUV\YSWTQRTSLTVONNPLdOVQ`NTNJMPRMVPNQMJO\N^MLMLMVM`MLNOPFQZQZPMOMRJRTTUXV\W>YVXVXXTVSVZVUYYXVWTUNXZ`ZFYZXYWdXWUZWVYVZTXjTRUTZVRXYY\XdUPX^STVSfVRTQPVRP`QVPbNPPZM^JRN^HVMTJVKPKKLfIFVE^EDNBFTCFZFABCAR@>hA@NANBPC8FFC\ED^EBCbCZFDBCELCVETDTDDJDFFbJXGLXITJHLMDNKPNXJ\G\JIKJ^FDAdETF^DB^D@RB@?@>:b==<@@?=R?=<:97b776R55P421^/Z10,-/T-X+P,)V+)R+H*b+N'+T&f'\'(&(b*Z*X(J&^+T+(*V+'()P'X+(*&*^*(*T+*-V,N,,T,,V/-//-.-//,Z+P.1-X-.J,d///^+L.V/^-T,N,X-J*-N.+\+L.d-+L.+\0T+R*+\))p*Z*H(`(&N'&V''%P&F&P"$d%J"!!#"Z"""N!# VPLDTLbJZbJ\VV2fRT^ P V L ^ ^ ` X ` bT TLf ZTNdNVf\ZRRVbT\^XRXT\V\jbZX\XRXZb`^PXNXVfTJTJ\PNfJPfBTTLVTNZNR^^X^HVZVX>bBZZV\TLbfZdPXVZVV\T\>\^^ZVNTTD^RfPVR^NVRfNTLV\ZTZ\NNjHNR\RT\XV^^ZTXXZRHZ`J\HbZLdXfVTZZX\ZZLNZZX\\J^R\\RXNRD^VDh^^\j^\VZfd`b`V^VbZl`\hZhTXbhb\J\\\bT`Z^RRjPL\X^XJP\Z`\ZZ^bLVbRVZZ^^^Z^VHR^dhbRVZb^LXLLNNdZRVTPX^^`jD`ZXR`X\\hX^^dTVVVV\@dVTXT`jbVHThXLfLT^hTBTXRVbPR^FZRbZPZhPV^bbLbR`Rf\X`\`^NXd@VX\ d  R \ P ^ b T N hX \Z\`^TbZX^ZVV^\^`^T`!X#!#T#$T'%\%$$$%&)^)')'P%^*X,\-n.`/P.,\0T/R0./L0.T.,b/.X10\22378T899;@LA?D@XBA@bCCBN@BT@`B>V=J>V<9P:\8757\64j9R7h6X86f;\=Z9b6X663P695`4435P34^2Z5N5X52\44N96P:=>;T=J?bBZ?P=BV@^A=@BA?AABE?`CDCGKbMVMRPJPNN^PMNNPOKKH`HPK^IJIPOHKRKMNRNRO\M\S`MPQQbPKdLFLHEREFZD@NDA\ELCEDBTCbF`EE`FEREGDXEDFETNI^KLKLVHZJ\KJIIFjJ\KJINLLOVNPP^RVSVSSVRUTXTYTTXfWRYPX^UVWW^VWX[]XYfWU\XVPX>\jYVZVZYfXYPVT\YUV^SRS`SZSRTVZYHY`XTXUUTRXVZXZR[WVVSWNYNYTWXXUT]XUYXhU\VPUVTVR^UVVTVVVTZVYUX\ZWTPVXXWVYXXVWWZZTXbVLXVVXXVHQTU`RRRUU`UZUUYVWPXXXZTB_VR[[^[[R]\[P]TZ]P\[\\XZJ\\ZYXX]Y\ZX\N]R]WV[TWXbXNXVY^YWWWVUDYTY[Y^YZ]X\XVYZ\[YLZNZWdWXTXUTVNT`XXYVW^ZVXXVUJUSZUNWWPXR^LYXPYV\XXXTWdYVXV`U`WSRUXTSTRVPO\PNPRPRQQ\Q\NQOSRTRSWW[ZVYZXZVZRYWTT`TS@RWbQVQRM\QXTNRVTJTPX\TVRWRVTPTZR^YU\S^RRRQJOZObPMLRZONPPNQPTOfPZOJPNKPLFN\L`K\MTR`RV\Q^STR^SSTSSVYZVTXWVVWb[TSXTXXVXXTYWVT^XVDZ\X\XXdVVXLUVYXTYT\bXVZ\TUUNV\UWXL\[WXVSRRTVTPUJNPQNNlNXMKNKVNLJJPMXJRLHIIRILCEDG`DGTELCHPBAAV@J@>PBAdGDFEDEBECJFHG^DDEbEBDFRD\FfFTFDGKbHDITN`KTMdLVKPXNLG^LHHIRHIZGNDBD`FEVE`@@??T@=P<=X?R>ZBV>?f=:9P9\896N6`5J3T6^7T22/0.Z1-X-N1f,J)`)^)))X**)(V(''d'(R('\+)(*X+(*&')J'(`+X)X)^*N*\)D+V-+,'P*T-h+P1.,.-L,-V/T/-,--Z,b/`0R.N.R,d.X.\-Z,-R+T,V+,+^+P,+X1T-R/+X+\+X**)^,L+*)*&J*T(^)Z((Z'&Z("L%$%X$$b"!$""B"^#"Z !PT XZ\`RZVFZHf`Zb^fb\PRNPJ\  Z ^ TR Z J X X Z T V V ` X JR^Xb^V^N\^^ZTXTZbVbZ`\RX^ZT^TbRRRZDZR`ZX`^RhTdV`XXVVhX\`^XVTTjLXR\T^J\JXPR`^`V\`hXT^PL^`NZl:b^\ZZZ`\^fH^PR`XT^\`f^f\PZ`Z^T\`^ZPfddZb\\b\ZbnXL\J\ZTP\^dZRZX^DNjXZTXPZ\XPXdR\PXTXTbL^`VVbbdV\Z`N`hXR\pbf\dT\V^TdVTfFZ`RV^bT^^bXbfXPbT^XfJfZNbb^T^XVfT^\ZXX\fXVbPRFj^\R\PVPdP\DXZb\LX\XV`Xb4\VTXNTH\RbJVTZBb`PZN\>\X\RZ`XXZJJT^XZLNRL^P\dXZTRT`XhTR>``HTPjTP T Td F  R P \ `JVNX\T^N\J^`N`XRF\HV ^! N!#%V$J&`&&%Z%V%$%f''X&`&V((X*T*,-B.X.\/b3V/.^/.//N//--\/T0Z2b2V24Z65\7;:==986\785CZ?@T@@=V>>L=X@>;;=R;X<>X>?^@>NAB\AA<@P>==R?A^?>AA<@J=R?X?`>C^@P@@A^FHHJKJNOMNXMODQVPPLPKIRHHNJVJMJ`OJ^MPKLOXLbPMNNPNMMOJ^KTKITHVFJEBdBTAXALC`ACEE^ED^BF^G\HJJEXD^EJFKjKILKKdLLITLILPXJMRM\JLTQOfSPNOTOPTTZTVUUVVNVWTVXXWV\YPSVVVRXUVWXU\X\X^WVTY^W`ZVY\\UY\YVNV`VJROS>VZSUdWXWVSTVUTUVVXPW[FXUHVXZXZRXYUNYWXfX[JVXZ\TZWTTURVLVXTPWRVVPYYWP\YTWTVXXVWWfWVVBZVXZZ[[UTdUZVUZSPTQXRVTjUXXRWYXWVYlZWYJYX]T[Z_^[L[ZN[J^\H]N^N[YZXX\P\XZ[R\\\^^Z^\WPW\XB[XXWRXV^UVWYWUX`V]\[VbVUTWYVLU^UTZVVPZ`YF[^[XYV`SWTZRTVYNX^WLU\UJSQR\T`RLNMPMVM\NTLObLMIJGKI^FKK\JRJ\KLFCCXCZIbDGFDE@PC@XCAN?XANDNDETGRGF\ECCF^EbETFXCDXECDCFDFHEGRL\HINMKTKTLLLLPQROMI`LdLHKFCBCEABBTABT=<\>RAT>@?\?Z==@\;Z;><;<88R6\65X7P45\5Z61\/b/.\..`0T,-,)X)*N,H,))+R''T+`,(,'&F&^(&f'V+&$J'd'Z'()L(R(*N**+X,R*b,+^,P+T-\0/^/.,,--T.P,X/P,^,R./T-0,T,R-0T0.+R-+T/Z-*+^---.*X,@-*+-f)B,)^*P))P)`())'&R'%%#T$X%\#N"#"P#""""! ^!P f H\PDJNVjRZLVXV^`NXLT`^XV\ Z f P X \ V Z.TZNV`ZXbXZbNdjLLVXjLjVV`bT`PNH`XbZPRXZTT\ZRhP`TPTHbR\TRJ\Z^T^PPRVP^fbTPNVBRFPR^Jh\NRNTP^TdNN\N^bVXF\R^`HVb\ZXV\XdNNRZLhR\d^VdRVXVfVX^\NJX`R^HbLX\ZXNbPfZ`RVXPVZZ^ZRZTXX\bLX@bVZP^L^VZTTVXdVBd`jbZZnZX\b`bb^NpR^^pTpVj`\\\`Z`\FN`Z\ZZZTb`^VbT\\\Rphbbd`Xd`RjT^ZNJZ\RZ`\VnXNbPVHdThPJ^^dTb\^NNp\`ZZ^hJ^HXNfN^\^^LP^VTJN`XZXN^TlT^DlRR\DXL`XFdXXRRXhZ`XXdTNRZ^`Z`TZPh`dVPPZXdDlJ^^J XR d V  Z N Z  hbXd`PhVfLR^\JdTZN`TNXD"`"Z$\!$#$^%&'%f%#&T(&V''P'b&T*\+-,T/R-.0/b3/h0V41\/b--T-/^23X34T477J8`9;Z;Z;<897V867V;7\:`:9j<>>`@V@\AN=RATA@?T<<;;Z;>;=Z;^8N5^4Z7614X5Z56^857T97J8h76P77X4Z4533212F4046P4Z49H5`8<=V?D??P>==>=d@AR@?=R@@?@@\?A`FCVHJHJZJLdMNNLJN\LXOJNJJI\I^LPLNJHVI^HJZHIL^KHKKZKPNHNfQ`PVK`HTJXJ^IXGCAEDABDBBGCEENEdEVEACFFLJ^KJNJRHHZKZJ`JXLHLNLVLLJHZKHNKZMOONNQQ`RTTSZWZTXZUVXXXRUbXZWXVbUHT^[UTdXTFWXWVXWZSWTUdZ^YPYXXY\V[YXURYU\TXTT>URX`WUDTdXXUbUT\SdUXTWVYVTXWbZ`XZZbZJVXZRYVYW^XW^WTV^URWUbYZ\XYRYX\NXYYbVVX[RWZHTXXZWPWYWW\X^SPSOOZRZRZSSRTQVRVTXY\\Zd]ZYZ[TW]TY`YHZZP\XNZ\Z[ZZZ\[P\TYXZV\ZZP[[[TYZ]]\YLVVYbWVRY`YTU\YPWXXT]X\YVWWRYR\WPVH\`WWdXUZdWSTUTVVRUU0UXYSXUSTUVWTT\VVXXXLXVYX[VRWXZWYLWUURSVUVRXRR^RQVRRNPTOUJMbSfTJOSRUWTQZVZWUYPZdYWWbYRWVVY^THWJVZUPPSPUSbSQJUSbRTTMRMVOXROQ^PfQNSP^Q`PQOPQPQKPNNPVMR`PZR`QOJRbPZQUQXTUjQVQTPTUPT\TPTVVTHUVXYX_b[YZRUXW\XPUVZ[TJXfXTUUNVTVWTWY[^XUVWZWLYTZV[PW\VVWUUSLWX`ZNXWVTROPOVMVN^ONTMXN^LVLMfNKKdJLGjKVN\I\KGZFVD`BXDEZIDBHXGCAZ@BA>RAXABAZEDGEREDVDCGBHD`FDZEdBACCRIF`F\FPGNFJHHVIHNLMFMZRNTMNKIZGHDZECdENBBXDVDDC@<=>`8\7Z5852D3Z73\20^2h-\/---b0,+T-,+*T-+*'^)((')(`+)V(P(((L(Z'^)J&d'@&V)`'()Z*b+)V+\,.T-+-P.R-`-X..b.X+...R,Z1\,N/./R./b0`/F0R.-/.R2N+T,,.P.^-b.H,J+X-V/`+^-+^0*V*L,)V.V*(Z'F))R+)%&'&l&T&X$X$X%%d#`#d& V#"%\! ^ XN XVTPVV^ZjRJdTlPZVX\N ZRL V P ^ \ Z T ^ VVZTP P` PXPXRfZ\X\P\`PRRVJNZT\\J^NZVL`H`Rf\ZXHT`H\\RL^^\n^R^ZJ\VL^^bhZFdbNb^\PXR\XVbLRX^N^VbZ^XPdh\NJ^TJXRPZL`XX\^^d@dTRRT\`PjZXX`RZVb^T\TnL^V`TRbLHX^^T`bhD\`XLXXHRRVPXR`RPP\lbD^fd^hl``bR^`NN`\TX`b\\RRlRXTTZ\TjbbN^ZFT\^^fRTZdV\\^ZZVPZ\`P`VVJ^LZ\ZZ^ZRVJ^ZFV`XP\fH^RZXT\VRbNTJ`XPRRJN`XZ@Z^^XZT\XTPbTTVVN``ZJ\RRXRPVFdRNHV`XbXXPZN\ZRPN\^HPXTPFZZRZZ<XNXZLjRTTP\PPPRVRB^X`JXTTRXHjJb\ ` \ \ X T P T \ Z \ \dHTPV`bL\VbV\ Z H "&X%\$P&R%T&^$V$%R$%%'P%&^+J(L+H+Z,.T-L/X//\/h3`/Z2-.Z,X-0/L1b61\3^77899:T:^:`;b;J78V;89d7:V;;X;N;VA^BA>^?V=V@@X=V>d?:>;;=P99?D>>?XC??F>P@?V?@b>=<=:78`3T9345d86\848\7v8P5897R;N46`6X35H40^3T442P2Z1T63898?;j=`>Z>>T>h=HD?=@X?`?\DHGGJPHDNKOQNNXObRJLVMJ^OJNIJJdLdNNKKLLLJ`HRMLRJZJ4KKXNbNRNMIIRJ\GH\G\GHEETBB^CBXCC`DJF^DZFGECJHZI^HLHINK\JIZHHLLHKZJJdLHMNRJKKPLXNR`OZLdONM^NORSUULVWHUYTV`YhTDAVDbAP?L??@BABBBFDEGTEADGCXDDZCXEZEAAGIHGVFF>HGGRJL\KNPM^JOMbOJNHKL\IDRG\DFBPERABBVBN>?^>=N;<><9J?=^;=>Z:T8`98R5662N53\5P3P3`0H/,`/R-X,.V-B/,F.*++R*,+*+N'&R(X(P(T(X)X*R&'V*'d(>'Z,H*'T)'(&)**+.N,1,X--.X/.,\---,R,T./,P-R0//\.f/.Z/J+R0\-^,-++`+/,j-@0X/-Z-T,,,J+*\*d)-d+,-)(V''R)'$%'$Z&d#h#!%#"T#!Z!P#!^!" \LLbJJTV`RR^dXFNNZ XZ ` X V L @ R Z T b \^ T L `V XPZZJP\b^VZLhZHZ`TP^`T\TdRXbZVJXXTTdRTVLXVV@PTTXVZXT^XZLNRR^Nh^^ZTdHVXZ^Rb\N\Jb\\Z\JRRXZfNRNfN\\dXNVXPPZZbTLXXhXNHjb\XTdd^ZVTN``ZJLb`>hfDZ\`PX^ZPXZJJRXZZZV^DlTl`^PX`Z`\\Z\VJJ^ZZZVTbbX6V\Rd\h`^`\bVT\jZbhXXdR^h\\flTVldZZ`\^hT\ffZVZVZ`\`ddX0\bB`h^TVTZV^\bPPb\Z`V`JT`\HFh:dT`bZdB^fP\N\`X^TRl^^RBVZ^b`ZbNZ^ZVLNLdJV^b\^VVR\RXXT^TJVRV^lTR\XZLdV`ZFTR^RX\XThTL^TZ V ^ T T ^ T ^LXJdTTZLZ`ZN^ N T!V#P%b$T&$&#'$V$R'%%&V'()*T,,,F+\--,/Z.J/b.-,`--b/-/Z1256T6N66R:8;d9;9888^779^8R7;R>@bAA=?R?XAPA>\;?;<;;;B@?PBT>VA\?d><:76P6574Z766V6X8777R7J6T6N6Z4X6Z48Z2V5V30R0\1D0/236`66X9j9X=:V>?=C^?P=?A\=ZAT>>:P?f?CCLEHHJ\I\OMLNO`OTOJNM`CGEbDDC^DZABCfFCZFEB`ETFVHTHXHGTJGPHJPJTJVIKOdLNNM\MKXKI\KfFREDCCB@XCCCZAR==?>R?>@:::>X::V9789N56Z24N245\123.P.-V.0h-T,,T../.*+^-N)T+X+f(J)J*&)X*`+(^'X)^)%R'd((X*L)'R(T)+R,d-*V--*,/.f/R0+.@..P./T--/./X.f1V/d/,X0V001N2-0T/-\+N,X-H.d,P-H-X..P/,Z+d.D.)V,T+*+'R*,P*V)b*(T+Z&%\'\&$$"d"T#$"##!P!!X X!^ ^`ZXFLP`R^TdbVZXpVnZFf`  ^R ` ^ X V T X  b R`bZ^JhVV`XfbN`XZZXT^TRTJN^\LX`^\\XdhVZ\RbRXRNZ\RVNTTXP\V^PRTRN\X\X^RX\TXdXV^bdLJbVdZZfPXbbXhLZTJP`\Z\Td`\b`XPRnXjZN`ZXdTJV`PPh\\VTJXT`hXbbNJVVVXTXbJV`^^V^R`PXJRXZ\RTfVPRVTJ^VLX`FnX`p`n^TbTfXZ\^^RTfP\TZd^Zd^VTPL^fX^ZZ`XRdH^\\RV^j^\TV\TX`XL\NN^`Z`PbT\bVPdP\DLjbN\TV\ZNNTHVZXV^TPP\^BdHTRR@VF`VXLZbRH\NPDJVZb<TVPTZZ\LXLBHNdRVNLZRPVRPPLlV^^XRPZPdNX^RNHT^X\ZT X Z J V \ X J  `VbV`NR\JTZPN^RXTLf ! "T$h&$T'Z%%%&$"l%J'X&^')*+V+-,/0/b/f2X2.Z/,-^1-.T/0J3Z1L6^6P9T7N::=:;:8N9R9T;96R;j98;L9:^<^?@F=XD?@?Z@>f?H=>;==J:R;^<`?=b=L><@B^@X=Z<@@XAV>Z??;\<:R7P6\86N6`7N3R346^8X57:69Z8T7455X4553P101`2j22P447^57`:V==>>B^>R>^@?BDHGZJ^KZPVMTQNRMN^LhMMMNMHRHKGRLMTJH`KMHRJMNKKNI\KMXMZON^JLMbHXHILGGECVBbEA@CZAD^EX@CEEGEHJGXGGHGVGJHRHKJNKRKNIZK`JRIJRLLLfQJNM\RSXUUUJZXVW^UPYRVSRWXVDYNVXJVZTVXUWLUTWV\V:WVZXYXVXXVVYdVPTS`VU\XVYZXUUXTU\WYHSZVPRZVUTWNUPX_VYYXXZ`[XPYYWZVT]Z\;<^?B?A?R?N??T@f?d>?<Z32Z20T0.2d2J3V46P6Z;X;:=R;>\>\:<>XA?X@V@T@X?\>V?XDDXDTHPFIfKKRJ^P\NdOXNON\MONN\KVLIVH\ILZJFFHGEGIZNTMTLPZNfM\LJLDNKK^IXHKEEDDZCD^FBDFBdDTBXDDZGFREKNH`JXG\KHKRGII`IZIZILHIVJJNHHKHfHIbIJ`P>MRPQfRTZRXVVVJWUU\X\YXVUfVPXTTUWZVSXWTZWDXX^YVZX[^YTZVXTVTVVXN[VVV`ZVTSRQdW`UDVWUUTVTJTXZUPYUXXVVXVURVjYLWYWWN[Z^\^ZXRXXXdZVZ\]\Y_\dZURVTTYTV\WXRTQ^UQQSFPOOTRRRXR\QDWZRfR`STRPTVTXX^]XZdZNa\YYRZZTZXLWXXZ\`VWTVJRWUTPVSVZLVVXTYVWVZR[VXJWZRZYZX]a[R\ZTYZ^N]YXWUJST`VXXXZXYUZU\VTUJXXVZVYULSQJRTQRUUVUVVSPUYB[RX\Z[ZYUURYVX`XTVVSVTRRQTPPXQ\SXUXTUbVRSLQRTURTVRPRfV\TSQNSVQTTPTQRRRZRLURRbQQSSVSTSPPQRUZQJLMfNPPZRQQbWRRVTXSW@RLRRRQSTWQPROPhNRO^MTPM^QSSbUTXURWZWfSWVVWTZfX[T_X^`[YWDXVVRUWZ[ZVVT[NZVZULYYZZVPVNYUVTUXRUfYUWZX\WTUTWRV^WXHVZWRWZURW^UXUVW`YPTNV^RXSdOPPROTONK\P\LXKKNTLNONIKGFCRG\F\HRHHHRGbGDE\EBBXAX>@?ERCRDCRD>B?HZEA@^D^DBDRHVE^ETDGGXGFGPNIFIZG`LKO^KNMZKRKMPJ\KTMHZIFXHFVFRDD^@ARB@ZA\AR?=R<=;P<==>F:J9;;J:V87345134^4\0X.0P/d//b.*P/,,+P+0T.,,*V)X+T*)(+V(Z(&(T(''X(\)\(b(Z'&''P'L)N)V((+P,^/V.,,,^/Z2R...V-,0N-^.X.\,.`/X-3`/.P---0-X1,T,-,V.,X-`,.R,h.,\-R+L,..,L.*R)V**)N)(P*N(&X*(Z'&F&%d'P$>"! $"J$"!N!b!NjL \B\DXNXRPX^Zb^jX\TVP TV d P \ P P P \ X b R `bZ\Hjf\lXfLb\dRTXTXZNh\ZVRZ\XR\ZVPTh\\JZV`LDL`TN`Z^TV\^H^JfDZdNX`^XNF\N^RJTX^JTZTVX\N`NV^LdRXJ\Z`RR^XZd`RZXfPR^XfZTRZNZRZZL`L`TTL^TRL\Tfbb\Jh^`ZHZV\X^ZRRdPTZZXZ:dZPXP^D`TXP\`^dPLNbRbFZ`ZfV^DbRH\\fJdX`^lP^jHTPD`nVTXRbXd\hVdXVbZVbVPhd\^hX\XXddJRhJdZF\J`f`dN`^X\ZXRJVJ`VV`^RdPVdVVZTVXVZfRRH`V^TVVZ^VVL`VfZP^^XdVdZ^\LVP^TVJ^XZbL^NRlV\N`\X`dhfPFZVVbVPFRPTJN^XfRTPNNXFVD\LTZ V` L ^ f R ^ L\hRLjPHB>JV\ZLRF!"\$X$P&b'T%H#L&$$@$^#N$#T$b%H''&(P)+,P+P-J//.^/.-/,-.R/Z0T./^0247T8`=;:R:b<:T;<98h9^>9`88;79R:?L?T@dDX@BRCA?X@\?b=@V==;^@bALAPAb>^=V;N>N;98Z6B6`3R72<2V3T4f75N84575^674\4P53X533\/0b30Z0P5Z2\3R65L78P;d;9;;;R;<\AX?ZB>^>@>=TBFDZ@\DEKdLNNRMRNRNNMTLFL\MKPMMRMJbLGJG^JFGNGZGPFI\NVLLLVPNPMNOXKLL^OFJNKGRGTGDCEXDRDCVGBBTBDFDG6JJJNJPEbEMGFGIfGJFKTJIIILHPIIHG\KIP`PTNXOPVUSURU`UUVWWVRWWdZXXLVLUTUSUVUXVWVZVXV[_\ZZYZ^D[WPVTU\WbXX`WWYTVTSRSPSUTV`RSnUbWVYPVPY`W^WSVRWWVZWL[DWPZ[P[^XNZXZ[YPY`[ ZR[[\^YT\ZZZXX`WbT\ULV`WSSHRSP>RNPQOVSQNOdQSRRSVQSUZVU\XVXZP[\^ZV\ZjX[[YVXWWXVTXHUSjPRUQRZQRVdWXWYVX>YNWhZ`WZJU[\N]NZP[ZW\`^XLZb]hYFWLXYRSZUT^XYUWXTTTTSNQRSVWVVYXVV^TSUUVTUVYUVX[NZ\\ZZ^ZZUWPVRSVTbTTRRORRTRRZUVS^WSQVT\VSVS^UZR`ROOPOQPXQRTSS\UTPTRTVLRRSZRUTRPVWRP`RMZOMFNTMVQOQHTRSRPP`UPROFRPTO^QQ\QN^SQO`RRTQfURTTWZVdTTUSQWZNYJ[]\[V\\\ZZXRYRU^WXWU`U`VVWZW\XXWYWVVZYDYXVNYXU\XXYHYX`USTXUUT\WZW[VVHWUVbTUSQVQ\PQLPMNQ^NXLTMMMITLPLLZNLMXIVHDE\DNFE`HfHGFRGJFECbA^CABCCGETDCLDfCDRGXFPED^BEEXHETGTHFVIZFNH^IJZLHRITKTKbJKbJLRILIHLLLKJLKPGEDEDhAXAN?V>?>Z?T=;<;=<^:V=;h9R;L:887X6J5h8D43V4\12d01N1300-\/,P..,-^-,J-V-*R)N)d*J+V,L+^)Z&)('Z(*&D(d&V%^)P&X&+T'X*(,,*/+++R-T1Z-X/-/-H.P-Z./\/Z.\+/-Z0`/.T.,--N/\.H/,-J+N-+\..-R/-X+-R*\,`.,T,X*V,d+J+'((*))'(&&&d&T&R%#P%T#X"^""#"`!Z!!^\d J V\PVXjNTRVPTXT^ZbRNN\TZZTTZ Z L X d X X ^ Rd \ h V LbPR\fXb\V^JTPRPb\`V^Vl^\X\XTdZ`LZ^VLZ^bL`ZLN\b\V\bXfXZfRZ^ThRTL<NRdLXNVP^FdV`VR@VVRVVT\hP`bhXVP^f`L`b^LdRV\TTTPbVRbZTdPZNd\NT^bdfPjZ\\TVbPX`dTXNZPRTX\\NBX\ZZXTT^LLPP`\ZVHL^PRVZPl^Vh\`\Ph`Z\jXdLn`fbXXZX`T^PT`^XX\jTdV`\djTZV^V`^VVZVX>fhXd^bR^^NPJRHbdRLHNVdTd`\T^^X\ZXb`RN^Rf\ZVP^ZTXbRX\XZPTbRL\RTLZPddPZVbZXLPd`VVLRd`\`NZXLPNXXZV\PRT\ZZPZZFHl^XbRdLXXbP^`ZZTJTD\^N J \  Z R L `\VZJXJ\T\NVVfZb\XF@\ V""#$X&R%j$$#&$&T#R#$'&`(Z&V(X,*`*,V-V,..T1X/X/X-L-\.,P.P010/1R3Z978V:B::T:f7:98^8T688X:H:79<:8T:J@?f@CBZD@?;>?=R;^;N?X@H>>>X?b@@^?>>T=H>X?P8:6Z55^62X5N4^2^6554R57j8T66V624d5`22Z431.X1/T.`2d045436V5X>^?9R:>;9R?Z=X>T<=>>X@@N?^DVDPIXHZHKH`LNMQdQPNRMlMZMZMLLJIHKLIZKHGHTINZMVMNNbNLNLRKP\KJIVHLI^FGFbCDCAD^CAXCD\FPEBFTF\IGEFEHKTKRILGbJFJ`JHXKOPKH^GIGZEbKTMRMMLVORLTWVNT\TVU`SJTUVZTTTVSdYXSXTRTVUTZR\XTVZYYbYZ^V[\Y^WWZbVX\UYTWY[ZXPTTXXTSbVRWRTBTU\VVYFYVWVVVVVPWTY[V[\Y[^Zb\T][a[Z[_YV\ZZ\RXVZYL[\ZZXdXUVTbRXSfUTVQZOKZSO\P\NOPTVQPOSRRSWSTSXXZU\V]\\f\[V]YXYVXUVXZWTbR`TPQZQRSVQ^RTTRT`TV\ZZbYTW^WPYb[WV[TYXZ]V\ZL_]YVY`YTW\UZVRXSSRVZRVLTNVVbRU`QVTTWTUdYQUWUW\SUXJ\ZV^T]WXbYUPU\UPZRSRUHPZSTPQPQVTUTURSQHUPRUhVTQRhSdRPQ^QQVSFOTQUQVTLTRJTjTVSPT^VNQQVQPDQTPdPPObR^O\MNORVQTP\RTSN`QTONOP`OLONfTQUDSVSS`VVSJT^VVVXD[WUVUUV\YLXT\]P^FZL[Z^HZ]UZRYRXZXVUVW[jYLWURXfZ\XRYX[LUVZUZWVVVYVU\UR^RUdU]`[VYWWXUUPUZTFSRRRRRLNbONP\PTQNVNMNOL`KVNfPHNVN\LL\NHZFEEHHGHFfGDJFCBCBHERDBXBPDVH^FCCCPENJNFJDGEPCNEBREPFVGPHVHbGNEJFdIVKJJ\JPLHKVMKPJ\NIPL`M\LdJHPEGXFdERGEAVC?@^?=N?>N<^<##"$L$&%&L%X%Z$&b&#f%$b&&%P)b+P*))`)/`././.\-/J0-,V.-^0V1245^7:X9;\AR>R>A@>@CXET@X?A=dV?L?`BVAA@R@<R>T;R@=R<=<>^ABJ?ZBVHRJHH`IXLOIMMPVOP\NNLPKVN^JILHXGIJZINJK\ILMLJOHLROOO\QNTKbJJK`IVHGFGJGG^FGCA`C\B^BZBCEFGIGGLFFKNGHIGPLFXHHGTMHTIINKTIHKZJLMMNQLPTT\TXSTUVWTVQVUVSVUTSSS^VUZRUUTWSXZY^ZZTa^[R^RYZVY`WJZRWWWVUPZLVZSXTTT[XTJY\UVVVLWUXXVXVVWNW`WPXYZ\Y[\\^LZ``aJ]h\Y[ZXYd\Z^Z_V]\X\DVWVT\S\VRUSPTTOLNO\NLNZOXNVR\PVTSZQP`VTPTWR\VRWRWYZXXX[dX[JZ[WRUTTWTUJTUVVQSHRRPdRQPNVVRUNVVSPZVPYW^ZZPW^[TZNZYJ]Z[YPXWVULUDTTTUOPRRR^TRSXT^TSXYBTTU`USJVTTVXUUV\UXPYU\XUVTYVY^TVTZRVRQLMMjUNMMTQZSPUXUSVTRTTQHRPR`RPJVPXP\QNXONQNQJRRS^QVRU`PVRUXZV`PNUVRRNPSRR\TPLNOTMKVOPXRSPPFSRNNLOOMHNTO`SWSUVNV\SWSTZdYRYjVST^UXTWXVV^YJZVXZYZ\ZXV[Yl[TYT[\X\XYWXUPUTPW`YYYRYXZ`[SXXVY`UdWVTRQNUQUWYZZZXWbVVURQRRdSNQOQPLSQTNNQLXMMOLTNTK\NNTMOJIIZH^HVJRHLHHGFbFPEXCATBBHCXBnCEBB@CFE\GXEbGGJFNKGRDZEDCFPELEJTHHZG^EG\IPJNK`LVI\MKVMK`LILJJ>MKFJXI\G^E\GGCZCPAT?TC>?>X;P^?X?>=@>=?J>ATDA?=?=N@;X;<\::L5R72R1244`5`3X28f5^5Z7564R5Z4J6332B00N111L.V.03d2b3R5365797X<8;V?V>XB\?^?C^EfGPHVIITJ^HRM8NPMLRP^LLJMVLIJJVJKLKHIHZM\KHOLI`ObNPPMXMIfKLIRIVIhIGXFERDDEZB\BXF`DBLBHDBVEEXGGFHLJGHEFTHXHII\KdHK^JH`IHJGH\NKKRPTS`QVSTTTS`QVV^RdRVV^Q`RS`SSUVUSSUXSSTVbTDXVZX[\`N_R]Z^[\`^YYVYXTVNVXRWTbV^ZTYV\PVRVWVVYRTPUTYWUPZXX^`[_`[TZ`\_b\^]`\\[]Z^ZR\ZWXYZ^XUTRQTTUNSVSNJPONDOVPVSP^PPP\RXQRRRQ\WSTUVT\UZV[ZWVYVZTYZWXVY^YTRVTSXUSTUSPSNQShVPTLRdVSRSYTRT^SRTVWXR\W\L[VYUYTZUXSPWTQPQHPPQORHQVSRTTTS`SNOPP@UU^VNXTWfTBUXf\VbWS^URS\PRPPONRMQ`PFQZO\QJSSbT^VFTRTTTRNQPQbUUZT\SPHNdNPO\OVPPPN^U\QPPQVTVdXNXbW\RORRUP^U^TQRNQRTNVOLNPTXRdRR\RJPVTOTOQNfNZOSTTTUbYQT^TRVXYHVXVbWVPUPXZT^V`Y\XZXXXY`V[XP\ZX^YXTWYXR[WbTXSSRVVXYXVWV[WZXYYhXUSTVPZURVXVWVYRVVVhU\SSTNRQ^PQNPM\MVOLLLNLTLPMKMLKMKLfI^HdKK\KXJTJVHBF\CRDCGERCEECDVCEHPFEEFHFFFFVH\DJDGTIZJ^GIFJTKLQLLIIIKLJXMXMHINGGTEEDCdEDJDTEXAP?V@P>?\=`:=X;;;Z:99;\97^;;V;P?>V@RARD\BBNEE\BjA?^D\@>A>V?=d>Z?R;<==>R>R?Z?>X>>:>=686V6P3Z3B222X3V72564X5366Z63H4R6T43\4F/000f1T3V2X255V46859V7Z=99b?=J;d>:P;7H=9\>ADF\D`IPFGKJMJLKM^MVOMJKXMVLPKIKIXHTIK`HPIfKKIZM\PROMMNOO\LKZKLLXJIKHZHNDGBBX@`BBCPFGF^DFGTFLGF`FXFPFEZGFG`JXILI\FZHXI`HbJJfHXHTIdJJLLMXNMbQSXW^U\UQPPSRSQ\RbU^QRZQTQQSVT\XXUVW`UUWZnYXZ\^^_^Z[\ZR^VV]XYLV[VWU`XTW\YYRTZUTUdUPSZXQVUUUXYYZPYZR[VZ\]R]b_b^[T]`[\[P^[Y]N[XYZZX`QVQZTRPTOPPSRRPZNNOPNROPXMPP`OQjNZPNQPPXRPPVTVXfXVVXLYbYXYJTXUV`VVVSPVRQVPQVQQQJQ\PRVTSNWTJUVFWHTUXFWfWXXT^WVVVR^SZTTPRQdQNR`OPOOXNXPMPS\QhOfTSXTNVPSJT`TVTZTTWUdYTXSTVTWVBQSRP`ONPRM`MNTRJQOOTONTPZR^UUfVXS^RLRRVTZQQUQQS\QRSXP\OXPOVO`PNRXQSVPRNSSRPRRRR`P^SSZQRPS\URURhQMNMVOP`UbRZRXTZSVPZOO`N\TTVTTZZWVUWWbVS^UUTYTYTVWZ[WNWRWZfVVWX[NXYNZRVZZjXTXWVW^VXYTXJTTTUTSRNV\UYV^^WYYXYXRXYXRZW\UTTURRVVZWXULT`TROSTfS^UVRZRTNMM\LMLDM\M\NPLPMdNJ^MLLXKTO\NKINKHLIF\ETCDCEFDdFDNC^G^ALFVD^FEFFFLGKHXJH^IVFZEFGXJTJZK\IXFXHFLLNKGIIbJNLLJI^IGFJHbEFDXCDF^DCDZD@V?>T=>>\Z\`ZTTdTbT\dPbXV`VN^ZRZNZ`RTR\\\R`ZVLR\\PPXjXlNH`X^D^Z`ZRVb\b\ZR^^ZX^^RZRV`T^XT^RVTbbRTRZL^PHR^RP^Lb`d`RhLVdH`V Z h V N \ X V V ^ RLVXRfXZR^TRNJ`R #!"$b#h%X%%R%b%R&`#d%X$R"N$#%*T&(f'n+*)/,T//0.\/P+R-*`-J.N-,^0/1V3X34L869\8;9>9:7R:^:9X9J5^9Z:9:b;T>TAHB@A@BCCB\AA?BR?>>N=h<<=?N;45Z34J2^3N/0b321P3\123244354P87b=J;:<;VL=?X@DDD^HEXGPHNRKXIKJMJNJNM`LJK`LZNNMKTMJJHMVNZNNbORQbMORRMMMMTKXKbL`IFGTH\EDJBRACPBHA\B@A\EBERG^GPHELGGDJF\GVFVHFJGNGTFNHGJTGIbHTITKNIKNLOVLMOXPORQXRMPM`O\UQTPPPTRNTRPbU\VSYRWvSTSUZVZ\\[R[^\P]^V^R]\]X\XWL[dWWhURWWRW\XT\\VWWYVSSSZUJTSXY\VZWZYZXP[]T_Z\N_^Zba\_^^V]_]`X\[[Z^ZXNXVjP@ObQTRR\O\OOnPZPVPNZMLMVNQP\NVORdSQPORbT^P^SbVUZ^XURRZULQ^USR^SXS^QQXMZRTSJP\QSTTP\QP`RXQJUTSVUXU\RURTUZUJSNUVTRPQRNXT\QSVSXRPNNOQNMZPM\OMORNTbS\TRRS`SPTRRWSVYFY`VFSRVSRSXPZQNMK`NfMJNQTOdPORQVN\PKOSSOTQLRZTXQTTQQSPRSPQQ\RZOPNQLQPSTNPQSVQRSVVPdWTVUURSRSTRUUJRSQQBO\SP\PSNONR^TRTXR^VW\VSRUTSJSNZPSTVTWbVUYVRXVZTXlW\YPY\YXRZYZZXX`WR[TVRWVSNSTRXTT\UUUVWTYbYRWZZYZLZZVXfZZSUUSP\T^SZV^STPOOPPPTVQDNOfLKHVJ`LLXNVNN`PVMJG\GINRKP^MLRKRNhLGFXFVDEVFLFED\HEPEBXCEfJEGVHDTHF\HRGF\GEZH\GTEHJ^HE\HfMRLVLIMZKZKhIIJXLLH^HNHTHRFG`DCXCFEEECA@>Ah=<>=?^9\:R;;;f=:75h5^5620`1h0/h1/T11R20/-V0/1Z1Z0-X/Z-+V+H,+h*)'R(Z%`&\('^+'&Z'%$V%"%X*`'^%f#'\(R+)^*^-**L+,d-P.H,J--Z+R//\/-b/R/J/b0+`/P./-P-V..X--.^--L+/V-f.\/+)d/V-J/-\/*,,b,X*\+,*\(X(T(f)R(%H)$d&%$N)'%"#"\#"V! ` !h" \ TL VXVZLT``PFVV^ZNFfVVhffNPd Z T ^ \ ^ \ \ R R Z X PPZ^L^ZX^VVDRRX^HhRZdP^ZVhVP\ddTT\XLVfRdZ`ZVXbNZ\P`TX`JVP^V`P^XZ\b\\RRJ`d\Z^ZnVjZ\ZdT`JZZ\^Z^^\\JV^^NPPVZRVXV`XdTn^RTLXhL`X`X^NXd^`VX^P\NXb`b^\dVPTb^bhRP\TP^X^LPZZhVPPVXXTTN^N^dVTdXPb\P`JPTZX\d`^ZZZVVjPh^^R^\hdV`^RV^^Z\hVdDZ`b`\`\^`T^FbXXXVR`XNdTR^X\TT`VZ\R^L`R\TRXTVX^fXT\ZLVL^\T^\VT\VR^`TV\hT\XTT\RTTZX^\VjXJRZ^LZdPXZNJTRLTBNVLNRV:^HZXFZVXPXT<\\bVT\TjXRHT\PX d J X F T TRTNTlNNVbTVZ\NbLV^ ^R%!""X$J&%$(>##R%#P"b$%&&%%^)V(P+P,`,X,V/0.-X.X-V-j.T*b.-^10P121254:\:=^9=\>n<78;X9J79d7L7b99Z:;\>@R>PBZEZEBGFTC^B?C>\?\@Z=T>?9;;:L;P=?=@?PBb=>P>J\<=LB@XBBZCDFEGHLLVLKPNLMMLKTJNLNK`LjQMPRKIXP\NLKLJJKRMNLZKKLKKMKPJ^JTGFHDC\B\BACA@ZBCEEPGdGGXEPEbEZEGEGIHGdHH\GDPFGGHJIZITLLOLRNHMNMN\QP\O`PbMVOPVOHPONOdL^POOXPUhMLURNWHTTJWX\bY[[Y[X\^\`ZV\\\V]Z[^\[WYNWLW\XWV^UWHTXVVSPWUJUZWJSRTWUTWYXZDY^ZNYZ^``XafdNb^^X_JaT^\\ZTYVUVTURXQMMLOM^OOUQ^ONL\NPLXO^RTO^QdORP\S^SbOPQhPUUPRNTbRJTPTbTPRQQdSLS\MHRPVORZNPXOTOZNSTPXPPNZQRPR\RVQ\SQZSZSN^NZTJQNONOOQROTPRMMOMKNLObLOOOPPRRQRS\T^UNSNRVWNVUTSRVTLQQhPNML\NMNRN^SOLOPNPXPTOLQKORQPQ\STPSP\Q`PZQQRRURZSFQUXQTO^QPRTQSRO\UOPTTPQQTSUUUVVWfTTUZSPZQPPSLPMQPR^PbPMVQ^OVNPTSdRUUUUXVWTTZTXRXRUSYJXYXYPWTUVYPWXV^WW^[PZ\WVWXZUZXLVVZYbV@XRT^QTSSPUXZYYTYR[XY\V\Wf[VVVYdUNRQPUPTTZS\TTR\SRMNORPPZMHJHVLTIdKVLZOO\ODJIdKK`J\JKTNZMFPPMN\KGBH^HGlJDG\FXHVIDTGDTCGPFJFEPHAXDdEKDKbG`G^GDRDI^DDHDHFHRIVJJVLZIIKHZLII`KHGJFB\CDRCJGHdCAA@PE>@@^;HN\\TTV^^TX\VLR @ X Z b L P \ f h T b L \\^` PZ\\ZTdddTZXRVTjH`\TJHlRJ^TZX>RZXbPbNNPPT^`^^D^TFP^\X`ZR`PV^TTfZPZVPHTR^Td\^Td`Z\^\RV`fXR^T\\`PdTT`TZTVZVd\b\X\R\F^^`^^JdT`nTV`RZVf\hL^ZX\RXdRbHRV`JNd^^``TdXRd\VZZZR^ZXZdVXTRTd`^VPZfpb`\ZXbh^ZdPhdRfbXjR\fhVb`^^VdbdPT`X^`TXTRd\P^Lhd\`L^l^bVPVfZJTfN@ZjJ\XJj\^\dHVR\bT\fPP^T\XRT\\\RfZVNZXVZXP`dTPfZLV\Thf^^X^^R\VZLTBZ^VXT\X\ZXH^dT\dbTfXRh\XZ@\TJ`V^TTJfJ`ZZ`TZR^R V P  \ X Z \ J V  ^Z\L\F\JX\hJTPRX^VP\ N L!$#P"V##X$##Z&#R$%$&`'R&$X&J&'Z*N+h.R/-//00,V-,N+T,Z,L-T/R/\46V43Z5X7J6L8;9;P;:T8:8X9f9V7\;7`87:Z=V@@N@DFG`EEEPA\AP@?=V@>@>=@b?:b;R:N;^=L:>>\>=JARDZABdEbGTIIKPLJJdL`NLQMLKLLIVNKHLK\KRLJMMTLPLLMLIJMKhMLTLJK`ILKFJHGIZFCCdCAAE@DCEZEHIXFCPG`EPGNF\ETEZFHG^F\FLGCNGEFXIGPG`HZIZNTNMLTLLMXL`NON\LPRKJNfKJXLZNLNjONLNQZSQVTSUXTVB[XZV`\j^\\[Zb[][N_RZV[^\WWYHYPYNXZTVUWTTXXXVW^VTWVWXZVX\Y\\P^X^\^\a]Z`ab^\]j]X]\ZUZWTRS^TPQ`LLLJOOOOQZQ\MO`MORLNOPNMZRXQOQZQZORRO`PdQPQQTPXNPZSVOOZRNQZOPNMNMPPOLTPNTP`ONQXP`QXMQTRT\SS^RUTSXM\SbNRPQTNNRMbRVOVPO`T^PPLNPMLKPKKMMOLNP`PLRfTbRNQVTUU^ThSXVOTVJTPSNPOVKOMQZPXQPQQRPSQXPMPdPXOPO^MTRRSVRO>O\UQTQSPQSZQPPTPQXQT\TRUOXPKTPQhULUTVUTJYXYYZU\VXURhROMQTPLXLXNZMFQORR^RZRQ\RTRUUTUXVUT^TT^TLZdZZR\YJYXZWXWTYTNX`[ZWVWVXWUYBV`UUSXTR\QXTPTNTU^TTSNWPWbXZhW`XUUbWVZZVfYTXVdRTSSdUTSJTSPOQSQK^MJMLPSOPOM\POONRJJKZJLMVLJNONTJHPJGI\IVITDGDVGFI\JEGHADFETJHdFHDZALDRDDIZGHTEH`HHHKPJIXHXJ\JZM^GZHFZMHVII\LGHNJGNH\DVHFPED^FBA?T@J=LA>`?\=>@V:X:H99`9X:8X;V;\84^7N34Z2P30L22./P/4X1/N/--V0/F././L--+*d-+V*''V)%'N&'R&'N$`%%%Z'%'R('&X&%\(N'*(P-f*H,Z-^/^,/`.*b-,f,b....*^,-1h,T0L/P-,X0V-L3\.R-`+V.N-.-V,P---F.+B00+**Z,+*Z*)b(Z+'V)'N&&b&&\'\'f&$"#&d#Z#!V#b!"^ dT!P Z\PXVbfRTVXJbH``bZVNZRV ` Z T P N Z ^ X ` Z \ ^ P `L\Z TZRFT``h\Z^fJbPfbN^b^V\\b`BjV`HXPX<\\XX\VT`JT^Z\X^VRZLNXNZ\bVPT\VR\X^XXNd`N^VNV`ZZZTbXZRfDTNRNTd`T\NPZNN\^\^jVV\RX\XRPR\^HHN`VVZZZbZXfFVXV\\XR\VbHTXVPPN`Xb^HTX\^Z\lNXbF`NJXP^dbN^jPXZ\j`ZhTZ\BdZ^dj\T^bXTb^j^FXJ`\`\ZfV\^XpR\XZXRV`\RHZJBLN`TNR`ZRb^`ZTVPR\XHFZDZbZ^\N\TDVLVZ:F\VLXVV^N`JZRLPb\ZVVdVVXXJJ`jLP`^dV^TTVP\PbPVRh`TbXXhL`PJV`XZ`FZ\VT^PbdXZR^J   X V X V X  J`R\hXZXVP>X`N^b^HX\VHRNZPT !!^"#"V$b#T$#$J%Z$H#"d&&H&V$'&X)-N.-`.-^0V0-+,N/,T.--/Z/B033T54P79d5F9:<998:P:`89R89b8889;N=T<^:R<;;\:P7V652N2@1P2R2V1T2f42J03P3R7Z5V4N5J4`661R1\41Z01\3V0113L44X4Z23N68;9=9V`AZBB@P@`GREFZHLTIHLZJZLXLLLPQZNFRTMMLK`MMKNNNDNNPLTIRLOMOJQIKMJKNIJ\F`KNEFC\C?@VCAXDPBHCEJDPGPChDVECRDXBTDEDIFJ`EEFDG\IVEIXE`HITMKMKKLTNJMMVO^MPMJOlMJVNJTNJXMQNTSRRRSUWVNZ\XXRZ`ZYD[TZ\Y[Z]h\T_[X^RZT\XZ\\YXZTZSURUW^QRTRTXUZWTDVY[fYb[XZF]H^[^[^[``N]^La`_`^VcZ_[`ZPXNYNSSRSVSXRPOS@MP\PQOVOPNXMbMbNdPPRPON`RPM`PMOPNNLVP\OLVO`MONPXPZRP`NONPM@LMPMZKIOONM\POFOVMJO`VPNP`OPROTPOQOJPLbJTKHOLLPTOORLJPPMMLNRNNbQTMMZMOHSbQPQVSORSPRRXUJVPQZNM^Q^INOSXNOhQQYSQVSZP`PVP^ONLQNWZOTSQPXPXRSQVRZPRQSQTPZPjSQZTOPjL^STPP`TLSWUPWUVT\UTU^UR^SLPZPMLTNOUQTQSRONO\TNRLP\TROUZWXVbYJVUTYVUbX\\TYX[NX[UVdVWVVXXbY@UTWUUXVPUURRQVUWTSTRVXVWVTTZUBSURUfWU@Z`VTPX\XDSSSSVR\QSTRQNLMVM^KJMTKMVKHNlNOLROMfRPNJKMJRNINLfLMjIJRJ\JKdHNNLVHZJHFIGRJRGELCVANDVIJE\HCAREVDDIGFBFbGNERHKI\HJLRJTLLPM`MJIXIMKRJJGHIFFXFEBCTDBA@?A=RB>?\@b=T;9V;;68Z=9b7543Z42302/.1N111/-\1f1N/X/T0-./,b,Z,N..-)*+d)(R&b&f&R%b%$`$T'T%P%V%)T(L($Z&\$*)))()T',+R+,+.T/Z-^,+^.X1/,+Z+,-T.Z/,*/Z.-T-\0T/+,-T-/..T+V/N+P+---\+\,+Z++*Z)(),((%Z$X'''^$R'J&T$$#$"\$#X$T! #V \ hXbf\VLTZVfT^f\^\J  > H ^H Z ` Z ` P H T J ^ \ X \ b H^T`RX`T`NPX\RdXR^ZVPdZ^Xb`LTNTbLVdZT\ZLXXXX^RJ`VPNbNXN^\VZNXTRZL`TPXRXVXPRVd^^NRTXRP\RZ\ZN\VjXZZV`h\NN^VPbT\P\X\dDFDRhPVjV\ZLXX^ZbhbRRT^dV^`Z\VhXJTJ`RRXTdJVX`NV^LfPJN\PNX^^h\hbb^jfPfJZd^d^L^P^dZ\J`XdVV\ZZ`XXRjZdf`VZZbbbj\bZFZTXV\V^b^b^PT\X^b`TV\lVR`NXfTVXbVNZXDJ\VZ\PPV`ZDJ`VNPRRLVTNX`LPRZVRT`Z^XRVNL^JTZRVXT`^^FN^RXRJT\`TXPZ`VXRRTbXF R X J \ < d R b \ X j ^` VXd^\b^ZT\VR^TR!"%b"P#%b#"$R"$##!#L%X$%%(+*P,,P.V/F1V/,J-.,X0,\-.-2\22634X5J99:X7<88X9X97Z;J9V698=89;B=X@^ADVFRDPEG\DVBXD=^DT?@b<;>9X?T@T=@F=:75:D7T62V12P222222V444R8P5X4332`31`1T30J00N2V.22R2112V29b9\8b<;;P:J<<=Z@=?==:L>@T?>R>=L@=R=R=9\9T9\9678765b4523V21\2V2`1.,/0f2V./f/Z00-P-J,.\-\,*Z,^,^-H))T(V(&'V&\$\%&$$#\&R'V%V$`)'$X&Z+'(*)(H,F+J.+L+X,b*+,+-J,+V.-,.T+,/X-,R/^-Z.^/V..L,,\.,-,X+.T,.,+f/-d-)*T*J+*Z(+Z)Z+'f)''%b%f&X&R&$P$\#b$b%b$"H"b#!f!T!ZZ THJR\RPj`PZVV^TRVXRPRRb\ZLL b  R ^ R X Z Z ` b TN\TZZ^`^`VbTZTTZ^RP`\FNP\jVTXd`Nf\bbRh``LBZX^`dX^V^^X^f\VR^^R`^RP`T`Z^VTP\V^LPLVP\PVTRHZbpJbZPbL^XXjVbHR\Nd\PRNXHb`XT^Rbf^dX^VT^ZlRZTdZZ\ZV\ffP\Zb\LZXJZfP^Rdb\VX`R\XJVRZ^V\XZRRfTPTR`VNd``f\LT^TjRdT^\\V^TVbhVNTlVXD`j^ZXLL`RbZ\dhXJZT^VbZLVR`N`PZ^\ZVb^\VfJ\XV^fdbZ^TZ\\\RVdR<XZbTjNRHV\d`X\^^L\PhZZXRXV\^^^`NTTXRZFbVPNh^^V`TNTXTRL^ZJ`\N^VV\XH\NPXRRNRLBTdT\ZPX`:\TbdRb ` V R ^ ` ` H \ h JNX`jR`RRTTXX^N@\PHLPV"""P#N"""#"!N"#$"P##$($^(Z)\(+R-N-..L0X/R0^-N-Z/T,V/*,0Z1243J5b6T6V7P9;R;H:<<9V:88;8V97\99J:\>R?=TFBPFDEHE\@@@^@X>^?JAP;N9=V9;F:T;LANAV@P?<<:R;:V;P422112P2V32L222J2`549\7P4R1f011f1R2\/L0N3Z..220\3\1L2546L79=;=;<`T[R_Z_\a\][Xd\Y\WdXhXUdVSJTS`R\QOZPPPNXQOP`MXMLMONXPRMNbNPO`OTQLdLK\LPROLPLMNLKZMNMNRNMJNKJTKjKXJZILLVNXMRPNPZRPJZLMNRN\K@M\O^MNLdKMKGHJJRLNNLNONOKMMRORNPRMPMVOPRXQFQPQPPTPNNLTLRO\MLLHPPXPOXOFSPLPNOPOVQZRXOMOQMdOOMN^RSRT\SbS\TZRHQTPRLMNPMNNXQZMNNVPBSJTXRbPZVLURVRVTPUXWVTTDR^TXQbSNR`SRSRSVTSSXMRTTQTBRPQZPUFQdUUTXXUTBUV\WP[^[YXWWV\SWUPUVU^VVXWUVHYRPUSUTSWZSVSRTTLT^RTLUXQRS\QDPQTTTVVVUVSQSVQXVNRQSTUTML\LLKI\NI`M\MXQL^LVM^LFLNJZK\I`JHPKNK\ONPMMTLIJKHHJ`LVMTMVJ^HEXGCNEERGZDFJIFHEbECbHCZFZIZIPKXGNJH\KZKXGJLDPKHLJJNLNZLKBNHJHJPHdFTEDTE\DBJECXA<>n>V?R@@?==VlXdjJNhTbHR^R`ZTN^Xbbb\TR^X\TH``P\NbTV^Zd`XX\VXFbRPZdVPhp^`Z\V\Z\TXbZlN\^X^TbTVTT^^\bNRXbPTlXRVlZJh`VDZTRTN\PP\Xf^T`^ZRV`VZLXN\bVfBNZjVV^jPZRVTTTZJ^XZRP`PRb^VZTZR^ddNZV\VbTRP`TPVR^PfZHZ^dRRFJ\ZT\V@bf^nX.hT^hdN\XZ`ZVbN^T\T\\d`\fZVV^^ZdZbj`^Tf`Z^XZnXbVTVdVRTRfdZb^`ZXXXhd`\\X`RhNZnTRTld`XFX\XlV\XV\dR^^j\``^R`j``JFXTP^\f^V^Xb^^PfLbRRHTTdLLbbTb^NPdbZZVD^\`X\RTVVTRFZRTXdd^ZJNVXbdbVbZVRPPTZ`DTPTTXTbd^X^PX^P bXN L ` \ P d PX`ZDbH@VPN^\\FTRV^"^"b%X#$R%%N#h%`$T#X#`#F##%X%(&V*b(X*R0-/L-.>-.R./,X/*`,N.,0Z/`3H13467697L;:Z:7X8R8X:<`:96R:\;d@?ZBR>>V9`;R88P5434Z21^43325433`567X6^3Z022d2X4N01./j/R.303/3\55Z9`8^9@:V;=V9b?>NAA@HAPD^ADELHG^L`JbMIJO^LPTNXJhJZGJJKPNKJNNKVNbLMZJVLJLILKfMLLNTJHGRIZJETEDD`BBBbCf@HA@`CbAXAB^ABA^DA@ZDEFGLEbJXETHVGH\FNpFGHPNILJMLZMNO`MNMTJ^KPITLI\KFNVMLNMRMNQN\NNOjPLRXR`SVULT`TRQZTWUXVUbX^VPZY\[YbYTZR]ZZ\[X^[\f[VXZ\YP\WWZXXLZXT[^YlYWZW]X[YX\\\D^]P[bb\^c\^[bYZVVXbZVUTXXURVTRS\SVPXQVSPVRSVRRWTQMNMZQMPZNOORbNRQRQPNfOLMMPL\NMPLLTNJLFMKNMVJJVML\HKNLRNROVRNXPNMXNXLMVI\JPKJbMJKDL^JH^IJJHKGVNJdKVM^NNTNOORQOPPNOMOOMVPbQZR`P\PVOPPVMXOXNMLKJJTMVP`OSQbSVQQRMRPOPTRPQLMOORQ`NPbQTQRZORVSTXPMXOLPLMMdMNRNQRTdR\RQQFUQTR^STRTShVPUdV`VRP\QPQQQQQRURVQN\OR\TZPZQJSPQPXVSYXUXPWWUXXU^W\XRY\XXTVZTRVTJRSSNUhTLVRQSQSVSVZVZWSHRTTSRPSQVP^SNQ\QTPXUNXTUVW^VUSUSSNTRSV>QJR^QRNKPLLVPPRQNMNNJXLIJTIVJ`JNHL`MMLKTKHHhHJI`GJ\KBNVJIFVGHIVDXEFbJTETJPFHZGGFE\DGREGXII`GVHHGfIMHPNJLJN`L^NVLbJRKIIIEGXEFIbFTCC`B??>9X=>V@X@f=V;::9<7X=:R9Z9X6B434221F1^0Z.//-0\1.^2V3/N./P1^-,0Z-*.b*)R-*((P+&&F)X''T$$"$#N%$%$V&)N&\*(Z(+(T)'^()*+\**(T+b*+P,^-R-+++/^,,`-+^,--.T/--R+,.L-/------/X-,+*,`+V,,^*(T*b(D)`'%(X(\%^%$&&$"Z#L%#`"^#X"H""`$d!" RVZVTTR\PBT^R`TdVVTT`X T T\ L Z Z \ \ Z J V  d\ T Vh\ZXPV`HZdP^RRVR\^`\LZdPXjN\bX\X^\dV\N^fRNVd^D\N^V`ZfZPVfXj^H^Z`^^^\VPXfT`TXjVP^`ZfdNT`XdTV\VnXPVbVV>`Td^`rTV^TRbVX`X^Zh\\V``^^>XVVhRRlTPLX\VV\^TbPbBXXVLP\VVV`VXdHZ`ZPXRfZR`VT`RXdVhP``Vblf`\VXVtZ\\VL^d\PpX^X\\\`JVdZV`RVZZJTb^P\Z`RRZdR``ZN\XfTTX\`bVhB^PbD`\VT\fdZ^T^bVPZXHRbfRXTTNVZRXRZRJL<DTN\BRRbHVRH\RRHX\PVJPLJVTL\`dVJbZP`TLX\JT^VlVTXJVX``\JV D V T X ^ P T R F ` `PZH`HNDPH^LVZVZbJRVXH !H "X#\#!!"N$\#L"Z$B#"N!P#$R&P%%))++X,+1R.L/R+*R.+F,,-L/\111045@8d6;7b<<<:<\=RN=^>:98V5H6V54Z34V2b/Z0P2X1T/5X156`5532J4/T1/2R0V0\0\22^00Z3T2R2T457f7H;`9\<:H;X?>=R@dBA`CNDNF\CGJIZMlJRJL`KTKhJbILIHRJRJLHObKTMMXNJLHPKLZJJZNNPVMKZMJNIRIGLHPGHfDD`D@VDNCAAB@D\A`CZ@R@ABPCDPC^EVDXE^FZEGJETEH\LHNLRHXIKI`INXJBHJKJMKNMVNL`LJPIbG4MhLMbQLRLTLPPZN\R\OQSUfRS`SXWJQTVTZXWPWVXVZHYTWYP\JZZYV[WUBWZNZ`]X\^[YZYZ^^YT\Z\l]]YN]\\X`\YZ^_Pa`XZ\\[TXZWRUWNXRYXVVVSZUdRDV`PQVNSDQ^PRLSR\PHO\OOTOfMMMKILbMTPPZPXPMJNKNLVOnPMMMLVLLXNJ^MJLNJPTNNKKKdLL\PNOHOPOZPTLMLPJbKLJHJKZKFKPLIPIITJDFTKI\LTMXNMFL\KRMQ`PXOXOZQOOM\P^ODQZPNPJPPQOZP\NMLK`KRLKJLJ\ONNQMXSZMHLMM\NNPRRQPPNQTORQNRTMbOPPRPSVQQPQPNMVNM^MOPLVTThVTUQNRRSLVTVWURZVWVTSSQRZUDUQRPQRRSPSNRQPROVQSSRTUPWUVWVZVSXVVVX\XW@STVQUVTTSM`QLRRjRRTfS\UVSNSbS^URVQPTPPTPVQRNUTSRTUHWTS\SUXRTR`R^RJVPRRSRQNMNKZNVRXNTPRNMKKXHVIMXJZNNLRKJfNJJKMXJGEJHRKJIG\IIJHETEXDGGGJFHHJGZF`HDTF`FRGIZKILETHXJJI^KPKLdNZK\OOMLJJGFPFZGZD`FEZDBFbAT?=b;\:>RA><\<\;;9^<9<:9Z876Z32V21X1P/.1^,-0P0-.T-.1V,b--P-Z-F.T-+X-*^)X*\*)*)L&Z'J*J(V(#^$##$&P'Z(&\%$b*H)&f'&\*$'V(*^(V)R(+Z)P*b+)\*^+X+d*+V,`,1\0N-/N--0./0V.X-V-,h-Z0.+,h,N-1+H,T-,Z,-`+,H*>)T(*(f*'`(X('$')f%'$#V%`&#""#L" \ !!R"Xf!VP^\VfZb^ZNd\XZXVNRRXZXXVVR b V\ b R ` V L N T  LXRP`JhP^\\X\dLV`LbLdTRLThNfXZ0TTPNhXRN^BXdR\ZP\TV\PjHRbZRLRP\\RLbX^RfZPTL\XJ\^R`H^^LHTZHNLZXXRRRPVRR^T^P^ZXR^RZZdR`ZZPVVbLR^L^bJXT`^Xb\dRTH^TZ^`V\ddXTL\``@\HLdFff`V`R\RRZbZZXXJTZZb`ZjTXhZR`dbbdZjbZ\bZ^b`\XT\RXP\TJ^^hdNZ\ZdZlPbZ`VRTVdV``Nfb\NTLVNV\dbZVPNb^`bNT\^^RZVTTX^\XNRdNbRRTVJZXhXbRXTNVPdTZ\L^^`V\T\\hXXbXNVbXhVZ^TZbdR^\TPX`LRXXRZJ^TZP`Z^T`VXTHPfZ\ZZ\X\` P T Z Z T \ \ V^ ^VPL`HRX\NJbXdN\dHdTPb\!"R#!#Z$b"V$!P#"#h#%""F"P"P&%((.R*+,+@/-T-0P/`-T-V-\,f--.3V4d3n12T6Z:V6b9@=^<:68H:\999V8;Z;T9Z>Z=L>>XDCXCDC>CCPCDPB>?Z@T=f;9f<8:>^:<89L8`8^5T1H14L2b0L1^1T3^14P3333D43\3001L2Z0N0J/.X//R0X1N54P4Z6`79X:P99;ZV?T?X@^@Z?@ZBAB`GVHVILZKMZJ`M`JRKXHGJZHNMMbORNPL\OZKZMTIXM@LVKRLGMZJdINPNMNJNGGEGEEJD^DNE\GDPCC^CXB@DjBXAXFZC^BXFbFNDTFCFGFFKKVFRENJHH^IXK\KHHIILKZOMNMdJG^OLHlIVOVMNPXKJ^PMXMOPPPSbQURUTbUW`VYVVYXYLYhXZYWUV[W[\`YYUXX[[XY^\]Y\b]b]YbXbZ^[Z[[a__J^^``L]T^\[]\YZF[RWWRXXXSPTTPNS`RTSVXTXSXTRSbPPbQ^OLR\RbRP^NPM^PJOP\QROOOLVKLNZR\LHMLKI`LJLLLJKML`NKTPLd<<=VAV>`>+P-N+X-F-X.T-/.V1Z0-d,F+N/./002X43V989Z:8R>;L;8899J::b:988=P<^=BCCAXANDEZD^DVDTABAR\:\;77N3V0\2\011N53F13V2X5R3L44T261b21T5`001b/V-^.j.Z1R1V2R53`427^:<\<=Z<@dACFCDAAhBdCZEENDCHdH\IZKFJLH\HPHFdHGEEFZIHKbM^JIJHRH`HTJLJJLLTMJMOQNP`OLOPOWTQQSTTXZWhWWRVV\YJVYVXXXYVTYTVYWVXWW]ZZV\YV[L[Z]V\WZ[_^^\Z_TdV_d``P`_[]Y\ZXYWXWUXXNSSRXTZJWUTRSfUSRTT^QJQPOPTPPXP\ROLdOPOORNPPNbMJNLMJKNZKKHNKRKVIILRLLPdONOROZLNVKL\KLMJJJRL\LTJROJLJLNLKXM`JG`IJGTJRLILJHXMbNLKHL^KNNPVQLP`RVPNXNNTMTLLMbKMPJVKLHJKIMKVLRLMVLQHNPPQQZRZQQ`TNP^PPJPPQLMXQOPQhPO\NR\ObQVP`PLRRhRXQRSOPONUPQX\STRURTDVZXYTWRT\UWVTWSXWUT:TZSRVSTUTSTRTNR`PRSJTXVTURZVZTTVQTWfTLULZZWPWWVTXUTTXVZQTJOLQOMQRQNTXQNVW\SXNVRUTRdTSZQLQQVVVSOjPQQPQ`SWTSZRUDRR\SPRP\QRJ^KRNVKOO\QXMLXLLKLJ`JJTIJ^LPM^KKHLPHHDHPFDGHPEINIVOJJI`GERETGFFG\ERDPEEEJFIDDVGbDRHTHJLLIJ^NXMhLVMTML^NNLPLROONNVLVJ\JFTGDDZBCCFAH>T@?J=L;>`>>>X9b;::N<^<=8h:5\3P1d4H3f421\0/,0-b-X-`,H/Z.\---,N-+,,N-R*^,*,V-X**Z*V*R)&)&R(R(&\&H'T%^'V'V&%L&&N$(T)&&'&&'T'*f)+R*)+*\*P*b+Z,()+`+X0/.Z.P,--.,^.X/.Z.J+V-P,-.,*-X./,b,+b+R,b,V++*N()^(R*V)f'((H('V&N'X$P%$V#j%$X!Z%#X#V" !! VJZLXbN\\BLL\VTTTN^RZXN\` dRR \ Z L X P b R l T V b V  P NR RR^ZRLZPZFPDTh^PVZJdLVLZR`PnbTTJ^XR\R^ZPRP\^ZVTddb\f\XVTXPRfZVH^@NT\X\hT\LJT\RTLRbNXJZhPdXbdJX\^PJZVL\`NXX^ZfTXVXb\TX^\ddTVV`ZndZZ\d^^\ZVTZ\\VLZR\LbP`RP\^^P\VV\\LXZXZ\RFRR\^RTfXXd`\bdTX`NR\XdT`Vfd\\TVfXXVXdd\Xj\bXNDVZZ\ZXXT`Vb\hdRbbbZ^bVB\bXb\\XfRRh\^`\fLLZ\dV\ZNJT\hNpVV^XDZNZTT^R\VN\LdJRRhNVXXVbVVZT\XNf`Tb^bRLVPZRbHTVVRNZ\Xjb`\\XRZT^^V`^B^VF`XTTJ^ZPn\ RZ \  P ^ Z ` ` PXZR^VbbVHXL`bDHVH  $! V#^ !Z"T#!r%"^"!T%R#$^$%V'b(d+R*X-*2.L.++/-+N/,R-/.002469<:T9V>::>;J=8:J8:\=b9:V;V>;BR@T??P>Z?=Z>T?ZAfDRBDETFTJJLMGTJJdKZLMLMPXQ^OJLMXM`MHTMFH\JPIKITJLJI^NKKJPHHFXGDZDVGPENGFGEDNCNCCXDAVAVCB`A\?@PAXAJ?@\ACPERGJF^IGILGGINGHFI\GGVFEVHIhKJPH^IIVHXHZIZJLZIVNDON\LQZSTOSOPbRTSbVZUhYTWNVfYXXYVW\XZ[WTY\XZX`YST[XXZXaZ\^\]X]Z]`\TZ]ZZ^Z\\P]`N_Z```R^ZT_b\YLZYWXWVXTWTWVWUTUUZVUUVTfTU^TR\OLRORNNVOPP\ROP\RZPROOTPNhP^NNQbMLMTO^M`NM`MMN^QNTINNdONNZN`KPL\K^NLKTLPO`LXLTLHRKHLMLMMdITGZJPKKJVOVJJNMKLMKZKLLVNLJNRMPPTRXQQPQTPNMHKfLILJRNKM\KHM`JJVMLdQOO\ONNONQVOZRVTPSPSNMSLVNPRNTOOPNPONQLSZRQ^OPQXPO`UOZSXVUHUQSSXVX\[XZVXTYZXU\XHV^RUTSQSQUSPXTRJUQRPUVTXNVTdSWUSLSTTRTWSfXXXVXTS\VURNURRPXQMOR`PQ^RXRNSWU\WRXQLQ\SRRZSWWRSTOPQVPVOLPSVSRQONQOVPNMQTMMNMNMIROOKKLZOLMMGNIJJ`JZMbKNK^INJG`HVHF^IFVHTGHGVKHPLGGF`HTJ^GEFCF\CVDNEIIZGXCEHREGXIIJ^MfKKTNLMOOJMXOMXNPNN\LFNEFDfFXFZDE^DEZB>F?^>b@@J??X?=R>R ^`ZbTFb^ZZTRXRPTZRZT\fL^ RNT V Z \ X ^ ` d f R  Z PVRZRPXd\P^X^bV`R`HfX^fNPDbZ\XRR^XV`VRP\TZfNfZ^VPLT`\ZTPPZTZVZ`J^LLVV^PfXbdXjVVTh`dVX^LjFRbVVRhThHh\^TRfZP\HVTZdZbbXTV\\h\bhRlRZT`VZX`Pb`XZb^Pd\dXPPRL`ZR\`VNb\ZPRZZT`RZX\bFTRbRbdJLddP\XZVPN^T^JPPT`ZdZNhD`bRH^PfX\VP\^HhNZN\lXX`PXVT\VZHV\HXJZVXZVRF\\VXXLXV\^\Bd^TZVXX\FR^^VbVbZ`\P^NNdRXbTPNXTX\XPP\FRXR^HNR\FXLLHLPZVTTLR`V\PLTZN^NXfLPV`^TdTNT`  \ D R Z X ` X T Z \ ` J HHVR`dVZ\RVZL\TZZPTT\`L !X!#$F!R!!#b%X#b#!!L%#"H'F'N'J*+,Z*\-B/.+N.N..\,,J/`.T,/R/B0T4N2N4`67:\9L::V;P=L=V;:;:;5Z;R7b=:`?ATAXCATCZCDZEZECZCRA@N>^==;T;:99P:799@T==`=R:<=<;V?;?89<>?P@A@DBjHVEIJRKHIZLKIZL\NLLTbNNQXK\J^KMKRJ\HGLIEfLIHbGJIJVJJHXFFE\HFRH`FGHRFFFBVEAZA@BLAVBCAV@@@BbA`CAXFEFIbJHXHFXFRCDGEJHI@LFKXGFTGIlKXMNIbIL\HJ`NFKRMXNPRVNTRPQ^QTQOVXRSRSZSVURXXUZVVVWXSbWTVdXUXX\VTNUVWTY[Z`][[Y[Xd\ZZZ\\[@^``]`\D``_N`TbP_R`_T_T[YL\`XV\XWVVRUHVTWWXhVFWUVURSTRTXRSZRRVPNPPOPdSUZPTOMXRZP@OOVLbNQXOP@NZLKXNXPMPNTMMXQJMMTMLZOjMPVKNPLPMRQOJKKKOKNKLJHI^LJL>JKI^OTLLMOVN^LMMZMTOONNPTOPP^SFPLQZUTQZPMLIJXKZJKK MLJHVKZObKJdKPMLOLMJN\ORPNNQTOVSPORTPPNPQLLRK\LTQRPFQSVQ\QQOP`VJRST^PXO\QPQPbUTRSbRbTTVXTW^XZPU^WTUPWTWTQVSRfRXTRQUR\RTQQTRRWUTVY\XVTU^SQNSTX^SRXXNUhWPU`UPSRQ\TTR^RPPRPTRQVPPZRNVSbTPUHP^RWdTDS`TTRTRZQROOXOHOROPRTUOTOSHOORMNPQJOLQKNJ\MKdKTKKHfIJLVLdKKRMLPJIHGTDFFXFHFHFHhGKFIVHGBJFVJPHTIPGVFGDD\BDGFE\IXGG^DFbEJHHIPLH\JLJMK\NLVMK\MHLNLKNIFRI\D`G`G^EEZDVB@>V??==;T<^=;X?;X;9h:89f78T643^31R6`3H2\0V0L/`.P/.Z0-`,-H(,P+^-V+,,,L*,`)N-d*)*L)T+(`(X(V)T%X()&%\%X'^'H&V%$F$%&Z'X%'&j(b)V(P)b**)('h*))()*^-^+)l*,+,b,--,P/,b..-h-/\/R//+,L1.+,`-L.X1*V+P+\+*Z*(P+<()T)(*'(&('T)$h'&V#%#P#!"!!Z$`" ^bXT\^LXRV^>FRZVLXZJJ P R ` \ h L V P R^^ L`PbPXlX`dPb\RN^^\PNZVbXHb\\X`H\\LVTZXdT\R\`RJL^XVP^`XXZ^XVhlRfjRLXRZdTXTXZ\R`RFfP^dfVZb^RTdVXdN`XR`b^RR\bT^^PRXTN`PRRZTXRXN^TbV\XbJZZLPPLdZ\PRVXZ\Zh\XdXT\RXNZXXV$RlVLJXRHXLPHP^PTPNl\P`Z^ZfLjhb`^h\Xdj\ZjPnZfPZb\RhX`TZ^fJdZRZVfbR`PX\V\`Z`b^d\TZ\fX`d^ZjT`Z\^RjH^bZTTRZdhP\J^RTbd\PV\`X\^TfT`RZP\VbfPVXNXNbX^XTZJRPTZ\lRXLZ^d`TXZXLXbLTjVXVVPX`bZVJ\TVNVd\TTZh\<VLZVbDXZHZ \ T \ P \ X P L T X VPdXVRPRDdXb^PNX`XP\ZR ^X!^"f!J #!\#!"\$"h"L!"Z#h$H&%\)X()T*.J.0---R.,+R+V-T,P,\-/X1P52`7^8J;89P:8;L>9V<977Z>D7R9\;X=VN@P<:R;P5789P<:\:Z<@>N=^@?@\:R=::ANCBRDVFFJGGHHdMKLML\ORKMMMKbJZJIdKHHG`GTGF`GGHRKZHGHJHFdGNFXHDZD^FdEGE^FDTDdEBBDABdEA>A@ZBARAAEFRDZGHHE\FDRCREEFRHJLIIH^GTJDMHPJPJNJZIXHHKLRNdN>PQVUNQTSNZSPSPVTSORQbWPRVNTZTUZ\SSXUWVYXNVYW^X\d[^]\^Y[[_Z[YR_L]\\]dX_]^X`b[V[ZLXXYdXWXYWVWWYWZZZ^WUTVRdW^WXPRSTPPVPNRVQSSQRQVPSNTNNONNhLOXMVPNRMRKTLXNXJNJNM\LJJbKNfPLOOO`ObNNRJLMXKRM^LPOL^LL`K^KMPK`LOFP\IM^KIL^MKXOXPbQLKM^QNNQOQTUOHNPNKJHJMKRLXNJPKIHrKNKbLVMbJVRPVP^RQNOMMRZQOPZMZPPNNL`LKNBTLRbROPPZPPNWZSRUQHO^SRQQXU`TXTFVYXTVTUN\XWVZfUdWVUNRVXUbRU`SPSSQTTRQXQdVTV`STTPY^T^XSVPUUSU^SZU\TZTb[VWUSJSRO`TNTTRVWRTZSThRDQVNObQQPQSdQRZQZSTUVTdVPXTjRZT\OXNdM`NRHPOORXRZPNOMNObNONLZMPJKZIHZKLfJXMKI^MMKLJJEGdHRKIXI\HHF`GGFZFXGEVHTFHFZHFJZGJGZHbDAVF\GFKVHGFREdFFEJXK\JZL\NJLRKKL^PLI\LJbIZJbKHEFFHE\GXEC@J@B\>>N>=<`=;=VCL?V=L>?:\:N=T;^500T11P20L3P3V3f12^0./3N0X03P1032\11T0Z120R11L32R3^5Z3586Z867F;:^:99b9;=Z;9::^:<9==T>@>\AABHFEGEFD\ILXLKMPNVNP\K^KZJHKJNLKPFHFDIHRIXIRGRFGFbEPDEDGEjGhFVFGGEE^FVF\CZCLGTDBfB\CEXCCCFfDVFbFPBXFDZEDEXEbHEFEVCNDF\HHHEHNKPMXITIKXI`KJPJ`MM^KLLM\NXMS^QdQPOLSS^RQJSbQRLQVVRRSVTPTRSQTQVSVUTTUVXU[XT^[^`\Z\NZN^V[T\[X\^^T^_LaR]_^J^Rc`]X_RZZ^hZZP\[^[XZ`\dYHYPWXXVZVVVWZSVWhQQRSTRRSTPVRZTLTXSVZTVQVNPPPNPNNOVNNXMQJSRT\PQHKNKMXLN\MNbMDKLNKN^RMVOLJNfOM\MOLNNXQdNQOHTKTOJRLPJKLKVLLNKRLFOTMONLMVLPMVOOPSPOXO>JTPIJKNQLKKMLHMXHKKNNLTNORPNZQZPRNNLVP\NTOLR\QNOPTPRPQPLRJOXQORSTRTNVRPSRRTWVTSXWUdWTXYTRWWTTVdWTRSPV`VWDWUSLTSNSTZTPXNRVTVSXZVTXTT^UTJY\TVVUPWTUUZYXLSVRWJR\VPUdVUPVPVRTS^QNVPRdSPUTZSLUTQPNQRPOR\QZRQRXS\VXVXVV\USHQPSNOTNZMPLNMNZNPZOPJRLXMKXQ`PVNZPPKINJMKHIVKH\JHVKORL\LJLGHD`DDIHPHVJFbFTK`FNGPF`EZH\EGHI@KDMG`DNEHFTII\FHVLRIPIGZGHHGVNXJK\JHKTLJTMKTKLEGPKZI\HRJFdHFHHRJNEC?@X?>\AA>=;T<`=89P7779:R9=X>\A\AZCEZCHDFD`CXF`DABNA>\=\;:5\89:<=9X:\=`<<>@=X=>V<`V>;=>L@V>\ABfG^DJEVHFhLONObMfJJLIIKVLGLI`ILFTF`IGDGGVGXHGFEE\DDFNFEEdGGCF\DEZDGEDNDD\BBA@A^AE\ETGXC`DnEVFfGEBZE`FVEpECBTDbFnHRHF^ID^KHHLKVNPK`MfJjMTLRO`OVKTMOOMTPNXPRbUTXSTQOPQURTSWLYbTNUTPZPRXUSTLYVRZZWWX[V]ZL_X]d[T[T[]\_N]_`_^^^X```]d_]\][^[ZV\ZT_ZZRWXZ\UUXU^VT`VYTOPTQPTR\ORPTQPS`VPfRRRNPMJKMNQ^P^NUPQTQNNZN^L:MLM\NPNTNTRPNfMPQPNRMMOTQNVLOOZPPPO^OQOZNBMNTMLLMK\MLMJNPP\ONONLLLMVNNLSNLObMMRVN^O`NMMMZO`MLLLMXIVJObLZLOQTOXPVQRMNO^O\QZP^PPPVOPXOZM`OPMdLQLM^RQTR^SRPQLTZSTSTTZQTUWXYX[bUVTVVU[WNWZTYYXWZWXWSSRUWRSRQ\TTSdTV^VjTTdSSWV^UXUVUUZUR^TVUpV^X^YZT[dVURQXUQ`QT^SRRPZTSXSXRT^RdSPPSXRXTbQTU^U`WPTRVjSPUNWbPNPLLVMOPMJNPMZONMLPMOVQTPTLIFPLFXHIdHMDHdJfM`LLMJGEDCDEPHGIPHEFGDTECG\CXDXGRE\GVGG\HVHCVDPFPHJ`JhJZJbOZKPGFFHG^HMIHXILKJdKNL^JHZHZIPGXGRHFRLHHGNEZCB?^A>P@@^A>TZ@H><9d6^8T6V55X1L3.V44001-`/02T11L2T/1^10./b./X./2V./11/P2\5P4R8Z8J95^989V:9T9Z;9V9:d9;T9b:9H;Z<\===?fDB\CDRFbCPFNEIXJLhNXL`QKKII^LZILKFXHFIFF`GF`HEGFHHLGFD\HREFDIDJDENHXEEFEJEGJIFBCBCDLBRDDBDFCREBEDVGXCRHDJEED^DGRG`EPE\EEIFJLKNKLXIMRKPRLTNTJ^PLPML`QN`QQPQTSPOZPPLRRRV^V^VRRLSFS`SHQRRUTRXb[LUUSZVbVFY\XT][[YX[^\]T`_R`dba`X`\^^_R`[^`aXZXXX[V_^ZZP\`ZXUTbT`STLRRRS^UZODROUQ^SZQPSPRLTXTRRPML`MLRP^PZNQXPTQXRNRLSRROLNOMMLONQMTMDOPbNZPNQLZQMMOMNN`ORPQZR\UUPMdNHMZQSOOQ\NBMLPLM\OOPXNXJLdONZQXSO^ORKJhPMMNbML`NXMHLMXLLLKNLNVNNPNPRPVRO^NOQPRQTOOVNXOMKNSTNSZRNRTSRRTRQXTWT`TXTVPXVWSX\XYPZY\\`YBYLWVVUVHVTTT\VVhRHQYVVTSPYVZVSPTXWNWXTX`XTVVTXVTdYJY`XYVUHVPYJVU\SQ@QTVWVTXTZSRQP`RT\Q\QbTR^SPWUV^TVTURVRPZQRMMLRLJNLNVOVJ\LdJTOK^LK\NMM\NJKGG\FFF\HXL^I^J\MFJLRIMIHERGXGPJTJTF\MFFHVDEEJFDFdGbHbEHXFFTHHGAF\EGH^H`GIJFETEGTHGIPK^MVKTKLPLJZKKZGZGFZFZEEHTGdFZFDVGDXAVA?XBANCC<^;:9=<:^97632P2\3Z1Z5T20^2---*V+.H+J+J,.R+)J*\*\*Z,)`)*())X,L(r(>))R'b*`*\))(`'J&f%&b'&V'&V%)$X,&)(X'Z'H)h'T**^)N(Z*'^)T))`)+'((T*b(*X-++*X+P-d.R+X,.R/T/\-Z-\,/Z,`,P,0+.^-+**b,+)Z*)X*%')Z&+(`((V(&$%'%b%P%#F#$"%#f!b$R"b!!j"JX\ZT^^ZNR\V^bXXdT` ZP^   Z d V `  V ^ \H bL`NHP\NP\LVJ@N`\`VVXJLh\VRbRLZLbZVT^VTXZ^\B\TbPNRVV^R``b\T\XTN\V`ZRVbFhbXT\VnN^\@\Ld\^XHZ^TPbTVN^X^Z`XZTXZT4LXRTXX`RTZ\VPX`Z\F`Z\XT^`\PVRbXX^Z^\R\VPbZf^NLbd\\bR^NRjZV`\RZRRHJX^V\RTVZZPbdHX^ZdVTVZ`fHV^V\PhRVTlZbTTH\fdJ\TfX^TTPVfRdXTV^\`Jh\^^TTLZVVdTXZjTN`ZdXXThZbhVb`Vbd\hVZXXRVTVVX\ZVX\ZLNfbLZRZb\JZVfF\ZRbPfNR^TXZfXRVT\\XVfPNV\ZTNhRTXZ^XXP^ZV^VFNL`TRZZPRbNdZ`ZN@X`N\XTlXJ  X d L ` b b P L X \DZVRjXVbdRXnXf\ V"^ !!b#Z#T&^"^!T"\ `# b#!$V$#%@'b'X*++l,//-+R+++/-+T.+j-V0P204477R99R;V>;:R8Z;8b85V:::`>>C@?T?fGZEBAVENBVD\A`@B<=9b;7f:N;9=R>?N<::5b6X6Z32P1b..T1T30X2-/b2V/N2Z/0J/1210/-X./T.-0.0..V1d/^2346^4V87:T8:;:9d;9j9:Z^T\R^PThN\XL\bVfJ\PZfRVTVPbZTdfVFHHbZ^bLlTjP`\\XVTL^\\\hVNX\\XXbRJR^`fVTXjbTVNX`\V0\VTRV`XV@\XZd\NXb\dXRN`V`ZVLXPf`d\bRVJZ`\\ZR`dTTF^ZZhXPTZZNP^XXTPZR\JT^\dH\V^VZ\`Vf`f^VNPfZXTbZZNN`VNV\hhbbh`ZZVZVT^XRdfTLbZPLZT`P\ZR`PbP\ZT^^HL^T^Z^T`XbTXNJZZ^ZJf\ZRT`XRVZbN\FDVHL^TXN\lX\VD^ZVfR^^b\VTBXdNfF`LNPR^ZNTj\XVjT^Z^TXR^ZZRRRVTZ\X\`bbV`ZZJVRJZVXP\RbVVVV^`\PRVRbRVfPRVRRVXPVFT V T b X N N ` P X  ^Z:PV\`VRZR^H\\\^TXRX V!F!!P Z#H#!"J R !R#!""D#X$L%\&B(*,,,+T-N*L-.N+R+N,,^,,,,0d0`2655R:T:H:T=Z>X=R>\<89X9Z8569b::Z;L?X@DCBVHCBZBTB?<;;8X9V78P6^:\99;=9:J>RL?<:H7T7333V20/Z0T/0T2V/^2H02Z0P20X0\1/N11V../Z,V..-R+P...T1X.X1X31^255h89P8X9X:87f89Z9V;8J8V99;8\;<>P>ADDXGJEFVDITF^HJ\JNKLZJJJTLPKLOTNJRHGFbFNHZHDDRFG^EGTEdJF`GGZIFZLGFH^H^EGVFVGZHERHZECBTDBBEdEEDDTDBBLEFEGPGIDZFIADZFTCbFEGLITIIITKLL\N\JbJLVNPLMMVLVOZMLRPVQVN^RTQOJUVSOPbRPQPHSSUJU\TZOPTQZPS`URUVUVYVULTLT^SYTWXN^PZZPZ\X\Z[P[\^]V`f^bb]^[\`ZZ^_\[_TZXT[T]P]N^]WTZX^WVWTXSUUTSPhNVMVMXPNMPZMMKLZKKMNZOPMOPXPRRSTLRPRFRS`SQSQHODLLO\RNNNLQJNNNQORSLSZSdTT\ZfUNTTTQHQdSSPTLSSRP`OO\PVURV`UNOL\QVMNPTOQLM\MNXNN^RTQ\ONN^NNJT`NN^NOLZLLTOPNPVOdSHT\SVRVNVPThUdPQP\QNZLXLPKJO^OLNHQ\QSJQTV^XT\TZVVUVYVT\[LX`ZHV\UXWXXTVZXTV^VSZQTWSPWSRTSUURSUZRVTUVXVVVWUVSZSXVTVYTUVXUbT^VVVXTLVVZUZTQSWLRVPOPNPLQTUPVTRPU^ZNSPTVQZQPPPQZURZMXMRORJO@MKLMJLKJIZJHMZNKNJVKXKZJJTDXJNGFIHMMMFKMdMLKRKdL^MJTJGPIPIHHEGC`FETFXF>ERDTEEDNCZFJHFGXH^JHIHK^GXHRHhIXJENH\LJI^NJ`MPNKJLH^IBDLEDEEPEXGREFPAAAbBNBT?jBP>^<^>Z<<^;9\:;\;7V8645\3N22V2H1//\-+,+)(N+)+)V+V+)L**D**N+))(P*V*(*()\'V'b&T%'H(&`)F&&Z&%R(X%F&&&`(T'P('Z)Z'J)'P'*,:)+))T)Z+L'\+)p(R,+Z*)*L(,N*),X-P,*.-f.L/,..,-X-*--L-`*\-Z*T*@)-)-T'(P+`+)X(''%^((&&V%`%Z&^%L%$#"Z"$!!\"N#!b Z!T\RXTbbR`ZNdX`V\P\ZRF T Z R P ` J R ^ Z X J \ J Z \V XRXVPRXNFHPP^XV`bNLP\VPZXfN\RZT^TLZPRVZPZLJZ^LFpT^PJXZ^\THVRPPDRXRTVTHRRR\XJRRT`\fBL\NV`XLT`ZVX\RZZ\N^`TJlXRfPVTdLfJjNdXf^ZP6Z@`Z\RXV^J^Zd\``T`b`XTNbVTV^X`V\XLRT`d^\NTZZZZTTV`XfVb\^dP^dTbfhV\PhbVlXZ`TVd\X`ZdX\VVhVdZ^``VpRdfV^\NZ`f`JR\bLf\\\fX\LX`V`dD^b`bXRfdNbT^^^\ZH^ZVlVNTDd^ZPZHXTd^LRRHNJZbTX`hV\\`TbPHXZR>LdZfPT\\VbRBTZZRXVdTL^\hRTN\^bRHJh ^ F b P L ` d b VZXNTPRN``^hJV\NTLRZh R"!^ T N!!R!Z!X!\!^"N&##^%X(^*-V*N+-/+b*-,X-/,X,V-P--Z-/33L479::P>d<99f:AV@@A@CTBLGAT@^A@`@Z<8X9=<7:N:78f9\<;><?=^=^N<=:L;J7Z777T748\:Z;\7\>P==9<787^:98Z5Z8V:N>=>Z=>Z\BN?@bC@EDhGFRGHEPJLJVKFHNLJ\IZLXJKIILJ\IGFPFTDEC\FE\CEDHLLI`MJPMXJIRJIJIFPHIDLGjFEPCEAP@^DDGJCbDCDFE`FGFDJXKGGDfFERHEVLK`EEXIKI^MKVM^O\OHLZPVLNjMRTQROdNNJNOXPORNNQTQQRNPQOFPNPP\PRZSTSVXR`TR[TPQUVRT^VXUZYT[`Xd\PU`]TX@[Z[\d\ZV[XYXZ`]F\[^^Ta[V][^^ZLZYN^]B^hXZVWTSURWRS\QOONM^M^NVLKPLM^LHNRLVLdMPOPPQN`RQPTTVXVPS`SDUVU\WPRPSVRRJQlOURbQRRSPTOP^UTRPVZUPSHPRQXSRPVT`RRSXSUXPVP^OROS\R^UJQRPONOdRTVSXTPTbRPQ\OQXNRQ`OORQNLQPPZK>NNNHLNfPZPRSRPUXTQQBRJT\PQORRMVSbLLLMMJOJPNQZQSUUXXD[`[TZ\[\VH]XY[XXXW^WVYJ\b[XYWSXWRPUPTTXUPVSZSQ^TPSPPRQZSPYbSRVHTVVTRdYVWUVUUXTTVVUUSSVVTVXUZTTVVQUZST@TRZTZSSVWR^QPPNOOSPSXTMZPO^OJTMNLXKJKJHMTIIMNKHIIbKXKbJHXMHXKM`KNMNJJTHZIJZJNMNJ\JJZIZNH^HGGRIRFHHHFJbHFTGjINGHTMLTKMJKbJRJfGFFbJ^MKRJRHVJPGNLLPHhKNIZHVKfLbLJIIXFVKD\EbDVEA@B?@@BA\>T<=??X=:H8<;==9V966X7846f8T;;`;9;bB=CVBAXDB@XEBA=L?:9Z9X79R<6N776Z88R8j=`><<<;:4X5b2T2Z2d2//N.Z0,X1T/\/V,/.30Z0`2-X/Z20\/^0J.`-J/.T-X,--V/V/L1/X0V221`857T65T9X8\8:<^??B\AEdGGF`HXFKFLKZKIKGXJGdLJbI`GGFG>ECCNCACFCJXIGTGHMLLDLGJLM\JJdHRGJILEHTDEBDVFCVDDCENEFFH\GVHGGGVJDF\HVIRJHHITEHbIIhL\KXLXMZKMZNLLLbMZNTRMOLO^OVRTRQPQPfQbPRS\QZRTO^NPQNSZRSV\R\U0USRSZV\SRUX\R^UTLXWZRXFZ[ZBYY^YWXY\YYZXYXZ^N]V__]`N]YPZTVYJXZZ\YY\VZUZSZTbYZSXS\LVNbMPLMMVLKKXNTIbM`JTMLLNNPbQTSRRXUbTjWX^U@TVTVVLUTRSPTR^U^RbRRTRRbTVQNONOJQNOVS\SRR\STUV`TXTXTLTRLRWMRRT`PRPQjRTVPbR\POVNZNVRVSOTPSZPPRRTPQOZONNN\LOVO^MTQNPQTZSQQVPJTQTPPUNPNNMNN^MRQjNPK`M`LNNPSNTShU^VXY\W[WbXVXXXXTZYVWZXVX[Y\ZNWVSHTTUQ\VRPVRTUZRXTRQQTOPLRS`STZfYWXV^RTSS^WUZVLWTURWUXSU`RLSNSRQZRPVUT\R`UVTT`QRTUSUbT\OQLdOVQO^QR^S`OMXJLMVNZLjMJLI\L`IMZJRJLGHTJFKIJJLKPILJLMJdGFLGKHMMONJKJTJIJXH`JVJIIKGPCJXDREE^GHIXNKbLRJ\IIJVGPGInKlLVL\IJLRK^H`NKXK`IZGLHhKfIKH^GVFZFfFDFbB@ZAX@bA?T==^=;Z>9V:77413^42Z220.\--T+++R(T)Z*T((P)`(X(),Z*\,)-^)J**)X)X(N*&V)'X)(F'j&%%&`'''P'Z%F&d&&&f'((&(T%((N+*(R*V))'X*'P**R)l+)L,j()**\+X,b++*P.,-N-`.-\-X-0.b/+/N-,Z,-^*(V*+^)T*P)H*`+V*)V)*P)V(&&'('N(`(P'^&'&^$%#$##%D#\!X !^PRZhVF^XRfZ`b`N^PV\\J\Pdf\ XV ^ J P R ` ^ j N \\^NNJDJVZVPHTNX`d^N`R^\PXbT\XfPVZNTTVTTVZVTb^Z`bj`b`Rd`T\ZZLT^VZd\RVVZlRTf`RX^XXb`^T\`VHJ`^R\TXh`d^PZT`PZVXLjNTRXTPB\\TVPXPRNVV`NTX^f\fhTT`bX`^^bLZVRNjZXNV`VbD\\fbfPZ`PX\dRdZ\Z\\VRRVZdR`ZRd`fT^d\`XXX`^\^``RTdVTFVNZJXZf\TZFbL^TZZdXhNJ\PbT`RHVTX^HR^HNVTP`RJVVTX\^LX`RVTNd`T``NZTRLNRfRZbZZdXTZP^PZ`fNZXP\TRF^VZV`XX\ZNZTPX\dRJBZV^^^PbZP^X^NPVX\XVHbP^V`T\>`fPNd XVLL^ d T T Z ` L L l8XVb^RHNVZJPXXPZPVXP!l ##Z" X!\P>!X\!N!$"d&V%^&R)\*f,H*Z,N/-^.R-.,,d+R,++/.V343666N9@V=Z;X9X89R6V86J7T:X:88\;=`>?NAbBAVBVAB@>>?@Z;897^7`:5866\699TNQ^UQ\VSVUbSRUVTTRUNST\UY`XVVXWWSUVTTWSVRXRTVX[SJXWZWRPSXSQdTfSXRPNLPR\L\PMQdQPPTNP^OJKKKJ`MjI>HXLPLNMfJXIVJGNHbFIIJTLJHJKIbKIJIGGXJH^HdMTMJXNIM\KMJZKRLZIKJHILVFVGFZFFPHXHIKJKJHGFHKJKMRJVLLZLZJHIRJ`HIHVHRITIVHTJRHGFLGGERFRCdB@T@\B>>A?R?=9@?V;T9Z;7^9Z5^33334T22/V.`/Z.*+*b*J+)H-^*+()(T+(`+*d*V(d(R(L+H)V((X(&L()Z''%X$%$h%&)'&X&&V(&V((Z(')'&R(')'(b(T('*)^+F*Z+'(b)B*(**J+P,*B+*+-\.Z-V*Z-.V/--X-.Z.V+,V-,))+T**V**H*T)(''R('()''&(')X%T&'Z$&T$^"%%V!b#Z"`"X!P T R !\\VbdbXRd^TX\X^FRP`NdbVRN V T Z N Z ` ` T T P ^` RNXLbN\RZXV\^RX^`Z`T^dNX\XfbXRXRPbTLLjZZ\X`RLRd^`PjVT\ZXXVTdV^TTJdXVP\RnX`Z^Rd\bXXT`RPXVVLf\XT^RF^\ZXPfZ\RJ\bHZRVj^ZRZhLZVV^LdTbbZV`NNV`HZRX^NbXTJR\RPbPTHL^RZR\JVT`X`LVPf`^Jp^jXpd\RhtbTPV\jR`XnZbNHZ\Z^PVXZZ`XXnVZ\TfPhZfXJZNTXbT\^XnVX\VFNfPn<d\PbXbTZbV^ZfdZZRTZZdTVNdN\Zb^hPhN`\^\TVL^b^Z`PXPdXTNNRXZb``XRVbRbN\NNTb`B^`^XR^fVTPX``RJR\XNhRRZTP\PXh N` b X N ^ d V ``L`Z^XJT`hPTR^VRR`PfZPT;\@ZBATBCZDBCZ?`A`<@b=9T9h<\7@;V6R5Z57988:9:\?;R:TAZAVCRCEEIFHBGJHGXIINGXFGEVIEDF^IDGDXCBDZGATDCEPE\IVHIJEXMZLITJTJNJEHJbHIH\HGdC@AREA\EZECDXIVJGEEXFRFFHHDZGVGRHHMKHIVKTIKdJPKTNMRMNZL\LNMMbMhLMJLJPNL\P\PXObTNPORL^OTMXNMRSNUZQfT^S^QTQUOTXSTWVSTTSTTPU`WRTSWUPXVXVXWZV\bVF[ZDZYP]P[Z_P^W]ZUX[TYVX[\VVTXZSbS`SVTZS\WSRSTUjPP\MMXJTIKLJ>IPJRNXMZO^MNQQPJRUnVYUZTRUUURdT\SSQSTODTQZSZVlRLSJQXRSPQVPPfUPTW`VQJUdU\T`SXTTXWXYWLYURQRUZT\UZTRZQRQ\UQSdUSTOPRSTVRPZUPTSOOXOPOTPSPONRO^RROVROTQdQQP\QXTROPNKTOTPNRXSTRXQSFQ^QSVQFSUjVNZXPZZX[Z`Z^[RZfY[YVXXLXUV^ZHVXWRTTSQ\ROTjTQPQ`TRTVRTVPTPOQRRVR`U\U`RXSVUTPUTZUfS^UJUVUPX`TRQ^PP\VVTPTWTUVSNORBROPVNbNNJLZLLPLbMTMMVLKMKTIKLHNKTIINLJHTLHFVHZL^NVJVLhJJNKJLKPJGLGXHLFbINGJVKJVKTL^ON\KVJRKRKMfNJKHXKIMFTKGHXG\GbJNH\JKXLIMdGXJHTKZJObKJL`KdJJLJHbHF^GLGHNGTFZF^FBBDXBZEC?CATA`?>N@=;9<^<<=b:f9N:f7b4^5P2\253/0.,+*,d)*))*T+Z(\*Z)Z()()J(X***N)T*Z)(P(V*N*%''N)&%T#L&%&X%R'&P%V)Z'))X(V'R(^*)V(N&(*Z)`)))V(()`+\)V,J(T*)`)V)\*+V*+)Z+l()+,R.*p+-,/,T/-d/,T+*N-*d))H-R+)\*+)(`+*f)N('((*Z)N*'''$%^%X%&D$`%`"#L#D!b#$ F\"T`^b`X^TNTRlbJXXX`RXRXRL`Xf Z T J X J ^ Z J R L \ PV\X^VZLTXZZ`ZfRTfTTZXZVXXR`TN`X`VbVf``\XFhJf^VXfTTXVNTR`L^lXN``ZZN^TP\T^`JXd`XX^XXFP\XRL^NT^\VPR\T^\\L^P`^TXlZl\\T^\T\VTbX`bV`VZ\`^dX\N^BXbXRT\d\f^RTf\ZT\ZZZTXLZT\`\VP^XTT\fJLVV\bNZZZ\FZPTNLRTXbVbXbJlhdd``^FNfT`PVP`ZbXRRPbbX^d^Z`Z\`^^bbbZ^`bDh^bPjdVTJVTRZRl<\N^^bZZb`XThT^TRfLTVRdZV^ZPZTRNPFXVVZTTXTXVFXP^J\XNhXJfPLhZRJRdB^jJNBPXFbP^ZTPdVLV^TT`TbZ^ZbN\VTNZZR\TRbJJPZNZT\TLP X Z N X b N X R ` ^PPVVPXTHd^TVbZN`Z^\VLV^XV^ H#b!X F"R!V"\!F"`"!F!`D!V!"#R%P&)R)*`,Z+N/^,--,T-,\,`+V.Z,..0.1`587;>=f;N;;978587R7`7Z8N89=;>N9:?N=:7:d76X63d4R4X2L0`0Z.,,X+\-)*Z,\**\(*Z)T+N)')X))J+(R(*))(^)\('&L)V&P'Z#R&'"\&d%L%)R((N'^&N'R(J('H&R'(H*F&)H*)))'N)\**)T+R'Z(*V(*-D)(X*V)Z)`*(-T**--X,J-H,,//b/R-*J,(*+*+P)^*F+**P*^((L*'L*V+('h)(Z&'+P%)%J(\%%X&V$n##R$#!Z"V!J" `XZ^V`TZfbXVTRPPVTX\F^RV  ^ X V \ \ b ^ ` X X T \VhXf`ZRPZ^XVTXNZRZJTVV^Vdd^ZT`PP``^RTPPRXV\VR\\^ZRZ\XRbVdTXL\HXfHXT`HbXLRbTrXlhNR^LlRTZP`J^XN^TRX\bT\^N`\XhbVTJdZ^PNbbHF\^RVXRRVRTT\ZVNbV^RZ^`\dTZ\bZ`JbT^TTRFFVJbTPT^JNbZ\^Xp^P^Zdd`^d\Zh```j^\d`^f\hZVXV`^\PhXhZXPd^`TTZ\bdT\^dPbZN@VZT`dN^VN`h^^TLfZT`ZTdXXV`^JdRP\^TXN`\R\TNXRdXTHTVdVZTNXTVNXJZPfThTfZPT\`VbVB\TJ^TZT\ZPbT^PfZZ^\bVZV\^VN^TZTXPLR`HbTV\fTLP  N h b R V Z VTT\TRNVVVRbHRRVJZ^  L X"X `!!J Z"TN!!"$P"T&&N)+Z+\*+.//P---D,b+^+T,,+F/V233\5B9`=9N;d;`<;>R:87767N6f6\589X::9`>^>^@>VECRDPC@?Z?=X;79:R9b664`66d5`;P57b97X7:98765R5^44\10L/0/.-/0X-0X-X..\10R./T11d2/1-0,J-*++-X-\-./Z-04/23`3`6L765J:R9;:R;d;:F;=<<^<\:bDBZCBbDZGF\GTHlHGRHTLLHFFGTHFFNGXEPFPGRGZBDVDBZ@VEbEPDIEPKGHMKVIGKIVMIIHKFKVMDHILJdGXDZCXEETENDXCREXFZI`FGTLHBIHTGHFIGGTHHhHHbHNMKJK\MRKLXOVLNLKdL`NKKMKVNbKJI`KNPRdPPdNPPPPRPHQUPVRhQPS\Q\QVQQPRFRTZTSSUZO^WTRRWV\VSbVVTSUPTV`VUXPXN[RXZUVWWbUTJURTTTVTXDW\UTTTR^VSPXbQTSbQRXOXL^KKJVIPJXNJMfLPbNLTRQdPSORVRS\TSRTRXTQRZXQSLSdRXSTXQV^SQRSTRZSVTTRTR^Vh\VNZVXdUVZVWXfZUTbSS\TBS`TSQSUVUUQNWRSOVULWSTTSPTTUUSZRRSTQNQdTSHPROPLQQPQXPOQZQLS\RVTMdPXQPORRT\VIIHKVKMMVHIGJZNIJJ\GXFIHFhFRI\H`GNGECfE\DECBCBTABh?>RA?==:9b?=AP@^BAT@h?>=<@;X98P6J373956L7H778789`8N8Z8d644V3R2/X1R0H.N,R0b/J0,-0..b1`012P13Z-.X/P/.*-X*)V*d,+.b//X..P1l343P3^24R78V9T8P9T;H;<9L;N9:T;9R;:`<;ZB?jAABbDXGLDGLGKRGFE@HFNFFIFPD\GDAHC`DZDB4EbBEPEDED@HZIG`IJIKJRLXKTHFLH\IIPHRJVK^KHGBD`EVEHTHCFEGHJLEHTHGFGREZEdIEGTETIJVFNH\KKVLIJKLKTKlKKVHMJJ\LXNMLIIKM^PQVQTQNPQNPfPQQVTVQPOZRNTQOZRPOOXSRTRVSVQZRPURS\UPTTbQ^RPTZTPUFVVJWZY^YpZTVRWRUP^RZWWV`UTTSTXVZUZXUYXSJUS\TXRRSRVQZOJQXOMXKJKL^MZOPNRONrN\SLNVTPUXPR\RSPVPTfUFP`QPPSQTRXQP\OPbRPQR`TLVVXSWBVVSZUTNWVVWYYPUW`USNUBUUTRTbUQQZUSTLU^UV^VSPRXR^VVTTSNWVVNVVRW\TSRRQQOPRSSVPPRhQPPRPRPNXSP\QRQ`SPPLRTR^P\QRRRRRPVQOSRURWZUUS^VTWVVSWdWWRXXWT>VXUVTZTQQPPSfSTQ\UVPRbUSSNUXSZY^WPQNNQ\PPVNRS^UQNR2TOOMVOPTRPXS^WUQRJUSP\QPRDTZP^RVRU^NMLLLjNKMXPPOPQNPIKNKTJhJJHHGJHTHKK^GXJZKVJHLIXFXHLEI\HNLJ`HFJFTH\HPIJLK`JHLIZJF`KZLXIJHIZKXJNMKTPPPJ`IIIdGZIGJRIHPHGPIZIGLIIF\MHPHJJHGbHKJTJLM\ILEGGLFXH\FCFXECTGEACdCDTBBVBP?\?P?>`:P;9L;;`:97R8X7X5H412V0..R,*V+*))'X(*X((&\(*)(h'V)N'V%X(*N&T('`&&R''^(^&%$R%X%Z%&%N$`&V%^%#X&`(('''''(')H)R+'`'&)*V))T*b('+X*'*+(d*(()Z)+b++-Z+Z-+b0d0V.\-,-.f--H+T,f)**X*(Z**(Z+\)b*)V(b*)`')V*)X(('\&^&(&&b#^#P$#!#d"#Z" R#\`VZN`VZV\^^ZLZhRXPTT`NTX^\ V P P P Z T T Z P X `f \ \VT ZNbVTTXXZ:PRR`@TVJNPXRX^Z^HdVPb`bVP^ZXXR`hR`TdZXn^NVZXRXR^PPVXPP^RZZ^RLTVRXd^XJl^P`ZdZb\RRJJ`RZVXP`hTbZLVJVPXbTP`d`X`\Z^ZR`fXVbZXTXZb`ZVZ\bdd^RT^VZTPXNNDNd\ZZJdH\R^`\h\\Vfjh`^T\\`J^`^THTXZb\TTXRTZXf\RV\`ZT^VR^TZZ`XZPThXHNTV\PZZL`XZ^bXdbPX^NXZ\`RX`XX^T\^fZXNL^XFb`bZf\ZZPRPRRT\^fVPZbXRZVh\^\TTRTZhRd\JZTPXZZPJ\TJZTdFdd\`bXZf^P\PJXjRRPJ`XfRXNPVd@ V X jX \ V T P Z T X T ^ d J \TZd`NhXRTZhXdVXF^XZb`>R\`VN " #Z#!^"#N ! J!\"f!^#`&X$''(X-*,\-,-0+H/,L+-`+V--/.T22Z56N8N::R9T8;\6P8N76:\8T<9L98=@@lBVAD@^BBh?>`A;;;7R83X3X4556b568R7R:9\77T7R8^6464^4`0X1R-.R,N--.-L.V1/-`0X1.R/V30l0N1\/-`--`.)b+X-T-,`++\-/0H03T0T2\3Z6V569^56N8\:999;>\=;:7X;::=<>?B`CAV?`FPHZEbE\FF^IHFbGHXJ^HPIJEFTFDdIVEC^BBBfBTF\CEFbFTFVKHTJRKLK\IHFJHJ^FTOJIJIFF\GCXGZEBbHDIGFLGJRKXHJFIXKHEEFXJHB\FXHPHJPdLRMJLNIfJJHGTIbNXLLPKZQRLKJKNLNTPPbOOPVSROQO\OQOXTHSZPTOMNXOTPPSRMXPPOZPVQRRlRURXNRTTSRR`VJVYXXUXSRSQOTUDTVSURSRSVNTTVSTbRRRUPLSRSTQQMNNOPOMLNPRNRTPNTRXPZT`QbPRRNUTSZRQ^PNPONRNOXSfUTXPTRRPROJSPQZSZRTZSU^SNXXVXWXWY^WX^STUJWVRTTUVPTRLOQQRQVUXRRVUUPTVS\VVRVUXVX\VNULX^SVV^VNURRTVVTO\UZPRVPQXQPQN`RZPVO\ObRRRO^SlQhPO`RHQdRZQPPZSSNSURTW^T\XJWRTSRWXWURXVTTXUVTLWTSJTUQVTTSQSdRPTTSZSJRSVTSRSBQ\QHPXOOOOTXR\RSOQQOQOQ\RQ\S\RTRUWRTQP^TXSROPRQP^Q^LKXLRLL`NKMPfPLNLZJFJXMVKHJdIF^H\IXHGIfJMIILFZM`HTHTHIH^JfHGFPHdGJZJPEdJIKdKZGH^HHKRLHH`LJJG@I\JLNJGFIZKKKLZJPLfIJbHIKIHLII^JHHVIDHVH^IIGJLIKIGIRJIhJNHFEZIVFRHFZDEPBVCNBXDZA?B@>BA@^<<:<;T;\7b76V5R44T41P//\-X.-\.Z+-L-)X*V(Z)(&(*''&V-'$V((d)P(&$`%$'&''b'P%&&N&R$\%^$#$$b%R'')*d'R'('')R)(T((H'^'(*)n)+(((\(\(d+-*))V))X)+`+Z+Z+V++++b.R/Z+P.f-+-+L,L)N(')++'(Z)*f+X)J)'((X(`'`')X'b'V'f&J&%`&`%%$V#T%Z!!!#! !!VX\b^`ZbX`\RhNNPZZP\J^`RHVRVTb R ^ h J X P ^ V d Z V\ZPZjL VfRXVhPVZPZRVRRRV^ZVLZX@NX^VRVLNbfJNRXLdTfJfPV^X`ZL`Z`dhZXZXbXH`ZV`fR^LjdVjJZRjXVfTVR``PbV\PfP`ZR^ZT^dbRJ\RV``Z\\JNJRV`ZTVj^^XdXP^X^^XNh^XVZ`Vd\h^bnR`\^^\Pb\b`ZRZLbX\PZX^\bTRR`ZVZTX`NLLTZXZb`Tff`Z`\d^b\``bnnL^XZbVbR`\@jZRVfZnRnP^^dVXj`RTZ^\TTXHXLZ^FRd^^PLR`V^Z\LPR\TTJZhTLZdfRdPdTXfTPX^NbL^^XPLZV\X\R^VFZRP^XZJLN^XZV\^`^`FZTZ^P`VLVZR`NbRTRPR`PRXdTTLRf`T^^XbTfTZRR`NVVRZZb T` ^  \ d N ` R T X R \X R`LXLfb^\PbTFVbXPZ R !V"H!# X N!P^""D \"H$\%\$&V(V)*H,,--P/X,+d-.+\,++`.-0R3\3688V>`<;V;;?V98:8f83667V6`67P8;:L;>@?R?JAV>>bb?;T;Z;:54V0V535N6R7Z9V5P7R8778L76P:6\3/X0X3T01.+-T.X0V.-X--V.-L01./R13^-/Z,,P-\+L-X*+B--,/R1.^.1V0N2344Z5T8L676L9R79\:<;:T996>:b=?JA`?BB=BBNDCbFVGdFTLF\GHRNLNGGFDDN@DXDFVAD`CBATCDD`GXEXFZJNIGIJRMNI^IXIGF\JFIJHFDVEEPGVILHZGIG\GFXJGI^HGFEHBEDDH`JNH\IJKRL`JNMTLH\G\GGMJZMNONdOJ`MVLPOLQTQZNPOPORdRRTRNNMPXQbPOLLPNTTLQ^QQdNQPPOXQORST>UWSLTQUVXVJX^VXTQUOPSTQ^S>XXVTPZQRV^SRVNU^WSTWLVVQPSLVPQQNQPPVRMRON^PNPPT\S^UNQRRZQQTRSVQPNNRJPRMRNRTMSQ`QQTSS`RVR@RRRNTUUSTFVVVUTVjXTTTU\QTTQSjTWXUSVTTRQRSVR^UUNSXSdTLTSSRTNW`WLUQTR@R\TS^X\SRSZQPPXPQQZSRSRQQPDONO`NXQN`SZTNNZPNPQROONHPQPRTQTVVUUTRVTDQjQPSXVNTXUVR`SNQRRQ\QRRRSXUPURTTQSRHVZRTQXQRTOTRQNPQTLLNHQVQXTQPRRRTONNNXOPOMMNORdQZQZUPPR^Q>P\QXX^OQMVMXMNIJJLbHTZ;8:\867p66548:9;A^?`=T=>BXAdDCBRDFLJbFdF\IJVKHGKEFZFVCbGHDDTDdCLAVDTBZGDE\EDCHZHFHGJEHIhGRGNGFGFRGTGGGEFD\FFHIXH\I`HLIJKFHHFFFDHTFXEERD\FVHIHFK\HITIRGTM^HJGIVJZLJbLK`OILKKMXNJTPRO^NNNRPQZRZOZPQO^PJM^OJXQVP\PfPPNQdNNQLMQTORN`TUWS^W\TTVTWT^UWVRR@QTPZPQP^UZWRRSTNOFRPQTSTVRXhSVSRW`QTRQQlQFPRRRSXSTdRQRTfULPVURVSTR\SOVZSP\UXQbUVRQNSOQOXT@QUSQQ`OTQQW\XRNShUNTZTUXWJSTRWZULUTWFTbVVSTQN`RPZU^QNRLSRTURPRVNURV\TVWPUWPTWTDRQTTSRPZQTQRQRQlPRQNPXONVNVPPQNLT\OZTLNXSMMONRTQTQUSPRRQPHQFQJX\WZWRRPrSOPRbOZPPUSSdQTTUTfRZSPTQPRRPOMbMLPZMVL\NMXOORXRXQWQTPVMQPNMXMOQNNUXTTTRS^TQVPjSTQLOhNTQMN^KVKPMJ^JFLIMTPlNXJRGNJRJFGHEIH^IF\GVDRHGFGZHTLPLINMMXLJK^IJHGHGLFdJRLKIJZHVIGVHDXIHPIRJJILM`ELRIKJ^HHINILMNM^JM\LLJXGGJLNGIVIbKRHTFXHVITIXMJHGGGGGJFfGZGDFGDHDXCZ?\ABEVFP@VCXA@N@AZ?@@VAT?Ab@JAV>P?X?b=d;9b8f8X53V8\6T97R5d:675:65Z8N9\6F3Z31`13Z,--Z*-X,,R10.T/`.R.^/P///N1X0/.X/-,\,0`.T-X-`,^,N.T0P.P.-.R.P10Z3X5R6R4f6\48979X9P9:6N=<9N;N<\:;P=T?`=Z><`AH?R>D@PCFFIHIVH`HTFGXIRIFEEE^DZD`CPCdABCTDDTEEHFEHGVHXHZFXIPGHGTEFFFRJEGGCTDFXDCPGHGZJRI\IHGNKIdGDFNDGRFNDDGFFGGRFHJJ\GXKfJTFHIILKJLHJVKJK\IOIKLMLTKMRM^OKTOXNMKOKLLKVLlLN\ON`QRQNNPQZMMONORRPPNSSSSJVSOMNSTQXVOXOOPNFNOQQRUOZRRSPUUS`UUTLTNQVRRPQTSZTNSQbT^S\RRS?N@>?@N?:R7D7h63000P30,Z,,R,J+R+*T*R)V)(\((Z('&V&d''(R+(R&'(P'$$#&N%$X%%$%R$T%"#%&&$$V%&'&&P($X'P'&&'X*&X''()*B))Z*\(\*b*T))**h*P(X**,\,*L*b+`*T+n++R,X,++-R,,Z+,('Z*H*Z+H,*++)\*N*`-V*)\)*'(^((l'%#L$X%$$&$%V$#"""!Jh ^!R^VVHZLXTRPPTTT\XZXV\ZLB VV ` \ b L J X X b T  NXRRbZXXnRZdXVZZ\T\T`RRTZTZV@Z^LXRVb^XRTPVVNV^`TRPRR^d\\Z`VZTZJhTV\XP\ZPPdZZdTZR^Lbh^^LdR\NXT`X\^\XV^TXVjN\Z`XLXdP\LTZ`NXXXV\ZdLVZZN^VP^f^VXVHV`bd^f`VRVZ^\ZVXd`N\VNbd\ZdVjTRddVZ^PXNXB^NVRVN`PPV^PJ\hjVh`db\n`lZ`dTbTZ\TVZbLPBf\bP^TbZPT`RV^\Pb`hZlNd`TXNfbHb^V\bF\bVVXXnX6JX^LV\^^`V\X\`Z`ZNV^V`VVVbZbRXbLZPVR^\^fR\X`\LV`XP^NT\dPZXb^^^\TXfDXZ@PVRLTRhbTPf^db^ZXP^^^ZZXbZTV PR J ^ ` Z  H ^ ^ TX ` X`VZbPTbLTRPhRVZL\! `"$ ZT!dT!f"T#b$^&`&L(P(b*^-T/`,`+.+P,.,,X--+V-L//4^33:78:8996^68L5\6R2P166^<:Z;BP>=X@@@@Z?P>V@=P`?TFBbIE^H\EVDH`EIIVIFEbFDDDNDJDHF\FdBTDFEEEEVDbEFZIHTGGfGXJZIZHHI\GFDEGVC^GEFIHJJNGJXHXGRKJGIHTEGFHTIPGHHJEHFHTFLHDZKZGnGEHXIGZKJJ^HKVHZLILTKXLQLMVPKXMXLVLJXMMKPLVNRLVOMZONNXOP`ONKbKBJPMPLLXOZNXQNRQPbU^SVSdTRXORTTR`RNOQL\LVP\NVM\LM^QQRMQ@TRQNUWQQVPZOJS\RTQfSQRTRRR\R`R^QTRU\UQS^US\R^PNP^TLLPQXPTQ`QjTRTURSTZR\UTYbTR^UQSS^PbUVQRPUTVVVRVTTPTRVVNPPQOQXObRPZSS\V`PJRRSTRTSSRW\TRXXQ\TVSRP\SRLRbUQHPPMNO\OLVNMQO^OPNK^PINNRMVO\NMZMOQR\P^STROTS8PVOTQRORO\PfNLOdNPNZMOdT`PLPSRRNZRZQTSPTMXOPNHPPMLNbKLLN`O^PPPMOL^MJHKRM^MXKPLONOTPbUTOP`QLPJLPKlKK\LNNPKIKZLKJHKdKRGbIFERIE\I\KVFHGHHJIGE^GTIdHLVMGJTKKfPLLKRIJKIFFH\JJIKFIlIhFD\GDEHXITKJI`JXHGdHPHKO`LVLKbNTMTNTIKRJTJRGIPKIKIZM^IH`IIHHdJ\NJFFEbEFDGEHTDCCh@XD@?CHEbD\CJCR@>d?\A>@@>=;7\97P6V6^23X20`-R0+/d)V*X+)N()P(&('&'H%V%()('&&%\%^&%%V##R$b$H&%&%T%#%%l(&$%^%%R(%&h)*V'&b&T('f)\*\)T'&Z*(L+P)'(`)+d(R+Z(`'f(Z)*X*(+\*)L)`+d+X+*d)P.-P+))+T-+V,)H)^*(P))()*\)L)(+R+)Z*X)V'&%'V%j%&#V%$$$^$##^""\"D"^ H ` PfTZdP\``d\dLVbT^ Zd dP V T Z L L T Z N X  bXNVdT\hTTVTRjVb\N\\^XJ\Nh^\Rd`RJ^\@\JZjRNf^V^hX`PT\XPZZ^dPXP\XPPdXh^`N^VZ^`VjNjRFNXfVXRdfVTX^`dbbNdTT^R`\\`RZ\Z`b^^bTbR^FV`T^fVHbXV`^RHf^ldXd`bdJThVtJNXX\Z\v\^``HXfL^ZX\`ZNVZR\XfZ\\\ZR\Z\VPNRn`\XRTZRb`bddL^^nbTZTL^`NRT``\ZhT\VR\PdJXZ^VXTP\lTJTNJ\L```VR`RVZXVZVd`bRVRdbV`Rh`Rhb`^RRXV\^`^RTVVpRXVVJ^`NTddZ^VXP^`ZV\HVLP\RX^NZTLPHRHHT^\RJPTHNHR\`PVRZZFTZLTX^PRXLP`RRNZ<VLXFN XRX ^ P \ P Z l ^ P ZL`DR`VRXLHXZ\HDH^TRHPZ#R!N!\! X `#V"T%P$N%\(R(V(P.V0X.P*-\/X-/+,`.Z,+--1R04X46^6F87F92;;;T:<9^;6P6V5R55324b66Z;=X=>\B?ZBVC\C^AR>A`>@^TA<=>?^>>X;T9H9:9R7J5H200J2j0.,V+P-P)\+J)`'(V'(Z'^*X&P&%&'X*Z()$&>&$%f$$$%$V$&V%^$#V""D'%d'R%h&X'P%&*T&Z'%X)T&`&('`*+'(((\)*R,V)B(&Z'(Z,('V**N'Z&L+++X*+`,,`,)T+,>),,))Z.*X*\*))Z)V(^),(R(f)R)*)Z(+'''&'$"$#V%X$%##%X$"#N#^# \ `!!T V! ZXTXJRT\NXJ\TNZVJXJJF^Vb R ` P ` R bZVTJ\TRFPVZ^^TVV^\ZdN`dPX^`VZTdTNXbbX\jXTPd^`\P^XJNRXZRJ`P`RN^L^RTX\TNNVZP^XdbZ^bL\ZTZD`DnVZPRhB^NTZbNRXVZLN^RZ`Z^ZZV\RLPZZXPJXRXRHV`\Z^V`XLN\ZXVhjNZjfPX^VPbP`bFDT`RPTZF\TJX\`dX^h^`\fXhbld`X^XbX\XZddFj`PTR^V^^DN^ZZZdZXtdbP\V^hXXbXVXbVTPfRb^`PZ^`Pd`X\fZZT\RfPXRlZXVXPRZ^VZVVV`Z\dVfTbVV^X\jLlhX\P`fX`PRX`^\TPXNVb\h\VF`D``\`bX^bLXTTRfdZTfVZTR`VV`R\ Z T X ` F d ^ NVH P ZPHbL^\B^R^ZRPP`ZXbJN^bHPZT` ^ V!T T!F V""T#X$F'R'J(P)+L-Z.X.\-/T--X-,f,+T---X/P12X4^8\7N89:9<;b=<8:8V8V64X5R56R8:\?d@>>J@`BB>=\:T99T988L6Z41V2Z5N76^79T6T7d:65672^500R-\,X.R,L-,R+X+Z*T+-P+-V.1.00/X/-\0R.`-,R-T00T/0.P++-^,\.0L-/`0.26Z3666;9:5^6\7X7;b899b7`6^67::::<^9<==>AN@TDF\GPG`EDfEGJHGXEE\GFD`FbDDCjCCF`EGTEDXBD\EEVJF\HGXIIHF\FPFbDJFTGFEGPH`HJIKPLGKITIGHLVHDFXIFHTGTFJIGbHNDFPCGIFdHNCGEGF`FEfGHXIDVHPDHHI`GXIIXMMLQTPfKIVINIKMFI\IFKPIJJLNIJK^MLLJXJ^JXKKXNTPQZONPPXQSRRZSXQRPMLQMNVRPN\MbJMLVMNNNPQQMRSOPRUXTPLV\Q^Q\NPSUOT`SSHSdTVRRRYVUHUWSJSQTQLO^QNLZPM\NPVPVPVOTVRZORQTSSUWYXSSUUXULUVX^SSUTTSPTSRRPHOQ^PjUVOPNLPNNXNLMSRTQVQR`RXQRVQRRdU\VRVRTRbQJRQPQHSTNQVPQSdPHOPPMNMJOQ^MOMZOL\KKONO^ORZPbOPPQRTNNNK\N^MdPNPN\PRMLFMfILNLRJTMOVQNN^N`NOJP`MLXNMLQVMRQHP`MXONKMZMVMMDKLNHLXKZNFPLIJEZI^IIKBJRNLHJJIIH\MXPMKKVOIHJI`FFEGHGGFFGEHFZGLGKZIVJPGPEF^EH\FDJZKGXFXHPILMHH`FZGRMXKXJLJRKHTJJHFNJJFFPIZJTFLKVJHJZJGI\JVK\IdMRMJDJLIILGdITKJVHIK`JKNLBMNPL^OVIHGKLJhI\J`H`FNCHXGPEjAAV>TAC@BAZBVAAb?>AV?@=>@B>>;Z:P8b8Z9P8R7X3`30\/\-,+++*)))V)(^*Z(^'V+X'V&f%&Z'''R&l%%&'V&$$%T$Z$\%#P#d$"N#X%`$&%$R&V'L(&''(*f'*V*Z'+*'X*`'b)(F))(^**'>)&X)N+b(f'&'*(*V,/P+R+)V-/**\*+^*+R,*R*`*((P*T)V,T+N(P'((*(*N))T&L(^%X(f($"%#`&V$%$"$N$!!!  bXZN\XbZ^^R\NVVVNb@b`VZ X H \ ` d V  V^\NdTZTJ^`Zb\\d`fT\`R\XN\^`LVVPVd^Vh\\X^TZbPR\X^XR`^fPZ\`XJfb\VRPhNL`V\f\XTRZbPVbVZ^T`XXbZ^\ZDR\h`XPVbXR^XZ^^TV\`\TT\HXVX\dXPNLj`dR^ZLfXdV^\VT\Z\\`Nd\ZTJZXPZTRfZP\L^RF<ZXJRVZT^RTZX`hhP^VdZ`BdX\RVb^Rl`d`\^flRf\Z\^fX^ZRRTXbZZXFT`^TPXV^TZPVRZZ\LNPVXRRTZXL^XXbNRX\TVPZ\P\VH^ZVVPVVXPTDJfHTZ`TdRRPPhLJPTTLZZLfTZNXLJ`XNPbR\TX^XPZ`bTXPJ`PbLdRTZ\NRJZdTXTL T`d f X X Z Z L V \ d R ZVRP\VVVP^^`nVXVL^hXbbdX\\ `P"X"!Z   T""T"X!$&\))d/Z-\--Z,\.N-.Z-P,>+F.+,*0R/Z2X36X6R9:>\@>^DHCX??<9\9659\844j365N4^5L6:6^665L84b7Z43Z1.V/,**R++P,X+`,L*-f.-^..L/V0F00R1b0./-^--V.X01-+.N/0Z.0^.\2Z/\.d01`2J64N7777558X8f676J;76b7>948Z8<:\:T?b<>=@RC`DCJH\FTEGNJC^JE^GIHJdDBdEDDGB\BECdGGbAZCDGGGFVIHFlFXHbHZMGXDEFG\FZEFIZIKKLLIHXFHZFKVH\ELGHE^MFXKGZHDGVE\IFH^EZEIDEFCVGjFFJFXGHGIILIFLFI^IXMNHL\SNLJJXHFVGEZINK\IHTHdIZKNJIXI`KIVM`KXMKJLJJ^LPLJRdQQNQTQRQTSONbQLMNRMXMTLIMMKLTNNZOOTMRPRNNNRQRO^PXQQPRT^VS^UV^UPVTUZTdUVRSVTdU\RRQVNZOQHPVOQTRRNDRSfSSPNQ\PbUV`V\V`VTVTTWZUT\WURRNTQJRSSZTR`QONSPZOPNNOJMOOOO\PQJSJPXTZWUZTSVFSTSQVUPRSQONOXPNOONPHN^NLXOVNFR^MLJTPKPNNPM\OVPN\OMHNOVSNOLZPZNKXLLdNLNTLJMRNKJMKNMNOJNOPNdONPJLJNMXNNbKMLROXMK^KFLHbJRIHPLKHZJJFNHVGGHJjNJ^IRLLZLHNIHIJbLIMMJ@L`HNGHJFXFZDEFPGIGFFEVFGGNFKKFHHHbGIEERFDVIEIXJTJFIKILJOLIHFHHHI`FJGTHJII^JIKHNLFGGHKKPRJMLLLJIHI\MJJVJVMZIZKTKJTJLKZH^KKHL^JMPIHJFGGFENFFG^CdBT@BPDAC?VA`??`>HA\>TAT?N>X>>T>X::V776R7X65R4/f1L/R..V-X+*V++R(V')`)'''X&^'$2'&&'h''f%%P&R'(%\%Z%"$%fT%#N$#\&X%%'^'&V&&('&('\&(D'V)'()(V(*+X*+R'(*R((`(`)T,L*\('`)b,*+,N,+T,\*.b**)+)(+)+V(&(T)`'))R)(())**X(X'`)'T&P'N'&H##Z$$%Z&#" N"" " b! !fZZ XfR\NfZZhNXXPXf`VTXPRfNTT^ ^ TNV` R Z d X ^ f T XZ `\``VXXPdVXTV\^d^NXjXZX`jX^ZZbbddTVNRTHR`\ZRZTPZ`\T^bTbP\VZ^NbZb\ZRVN^^Rl`^bVVP\VVR\N`bbPhNLj^V^j`dN`X\fNTTV^`XV`jZXTZbf\^^bZ\VX^^PR`Z\L^XZP\Zb\BFJXZVbJ\NR^^VTPlXZZT^ZNTZRLfX\bZjfl^VXV^bbfdl^\b^j\V^PdfThNf\fZVbRX`jT^``RV\jbXV\X^\X`Z\LdPfXTX\\XXZL`lTlXjPPX`PPZT^^^fZ`bV\`VVbX^X`XRT`^XPPdVXP\Ph`ZFV\PT`Z^P`Z^Z`dTZN`bXRb`@`\VZXX^b\\ZRNJbNd\RZVVZZ^^XdNJP`XZ T` X V V V j ^ Z ^ P F b^RVZ^ZhZdN\`V`RXVXRJ!P RT b  f b!$b#L'''),-,V,X-,B,+R.*`+H-d+b,V.,\1X123f:`<9X;:T:J@@\Ab?54N24T4`:7h5495X8637945d01.N,+X-\-+Z*(+*,T.Z,R0/Z0^0b0^/d.V.-,,.X,+`/J./`/+>/X-,\-..0Z1/.T12^8T67N6J85:T7R76P6f7`9P:656J5569P8T;T<;H^D\DLABRH^GXFGF^EGTGDRHD`KVGLHXKRGZENGHEFDCGbDXIGKJIJRMZOHLGVJPGIDHTKNGHZHhHJRIH^JPJ`IIIHLHJLM\MLLRKKJZKIRGKNJJ`K`HHNLIKOKZKGIZK^HIIXFbDFXDVFDERC\@P@?XCD@A=b@=b=?^=X>=P>X?;:9D8N6P765Z63B3T0X1..R,./+R+^+P(Z*R(T)\(L(X('T'X(V%N#%%'b'H&%L%b%P%%d&##"D!F"\&P$V$Z"`"P$$%&Z%d'&Z'&'Z'Z%'&(h'(H*Z+\))J*X*d*D)*^(H(\)&b*`))`(('*b)*++X+N,`**+-Z,X))T,X)`)X+)*(*(^(+Z((+'`(()V)'&Z'T''N)\+X&Z'$\%%$##""\#V"b%R"F !R Z!hV!ZFX\LNXHRTT^VJ^HPRLV V H V T J L V \ ^ Z ^ R \RRZ\TnV^\``V```PVPJ\FL`\\`RVLVNfVXbV\XXd`^b`ZbT`ZZ\PTHRTTZdH\V^X\PPZXZZ\PXZX\`Tbb\T`N^^h\^`bRdfdP\@T^bX\`X`ZpTXXLXbX\\TXdN\R\Z`ZXbVZ`TNXP^\XLdVX^`nP``RZ\bV`bf\LbZXNTXZ``JbbRZLZ\TVd^TZZXdPPVPNVbndh`^XV\`V`\^JjZLZVRVl^NXfb`^RNbZ\VRZhZXVbfT``DhNNZJP^`XNfL\dV^VXTF^@jL^T`Vj`TLhXPfP\RRZVThZXVbbPThRj`\TTZ\^VZ`D\VVRTTXZH\HTZPTdNXZNZ`XX^LJ\RXTT`NRhT^\Z\`RjLRTV\VNV`\V^PXZZ\ L \^ j ` R J H X T `JHZ\LFPPTVPRbLjLhRPVfPVNVR"\!!!!N!f  X !"\""$&T)\)**-+T.,V0.-^+*T,+-N,,./f/1V5\77V;H;\;:8^;;;9763h5`655T5V5d6b6V9V;`??>l>R?Z@>\@@d>&?r=9\9P6Z72^454`2H7d46L5R8<7J36P6V5X5V401Z/d110*T*(,)Z+-j-Z,.R-X/---,V-\-b-N-/R,-X/0h.`,/,++.T.\1P/00\2N25Z6Z8456V7R965f5656H44Z7P87h8P789X8=T=h=P=^@PEhEXB\DC^DGXHXFRFXEhFVITDfGRFB`GFDTBBDNBNCECC`FEDEPENG\ETDZGZEDRHH\FTE\EZGHFTGEIMNIVGCHFfIGIJNIZIFTFERD\FFRFdFZFLHGLDG`FXHHDFCHTIHXGRKIHGIbGIHbIKGVJZH@J\GFHIGEDFKIGEPFHFFH\FGTLHZJTJbHZINIVKdNNRP\OFPMRMNXPhO`PLN`MLIfIJHXLGMLVLMTN^PLMDMJLLHObPPMLRTOPfQSfRUWdVTTXV\XRSJWRUTRUBT^QZPSVPOUO\PPTTPZUORbWPRPQ\PSSXTRTTVWZYWUTVURPSVQRQQFPRZPfSQPXMMdOFONQRQjQNVQOXPbPPQZTSSRV`SVNQSRUPQTSPOTS`QJQLNOPMLLJON\KPLM^MbKZNXNKMXNLMNHPXMLFMVPMTLPMKVNKJGKTJTLTJ\LRKKMXKKJGJLTKLILLJMJKJ^MJJKZI:QLJJ^NITLRIHKZIEFFIJZITL\II\HTEPFEHFjHFZHHRIHTHHJXGIIIXIHFFEBX@AADFCVFTLEEZGECTFDGXIZGH`JVHG\GGRE\FRHBE\HRHGIIOJKVJIFFVE`HHNGNMIRIRGGJHIHKJ^JfKJTLL^MdLVLN^JXMPIIHXGJJKFIZJZIVFbHJOMLKVJILGFVFXHPENFD\ECLIDBH?\?Z@bB\BZAC\?@?=XV==>V@<::86X8\673V6\513b-X/f.-^--d.X,)X(`'X'R(((\)T((P'&H$&d''(&T&Z$N%$P&\&N%!P!$"$%#R"!^$\$$N#(Z'j'P&('&V&L(P)(Z+*X))*R(\*Z)V)X*b'H&^''T,b+(V)D('T+))+-*T)^+\+,+P*X)L)Z)*(+(')Z''b*X*X(((`)J+N)X)P(d('%&'V'`'V(%V&$$X$Z$J$J%Z#V"\!\!!V"T!X ^ H b!L! dVRDTX^X`Z`\R\P@XV\TV ` V ` b T T d TX`XZZTf\PVVRXRPX\\bNZP`NbLVlT\PLJ`Z\TXdPNbRVPPZNZTbLPR\VPX^XZT`VZJNTd^bT^Zd\T^XbbTXXb\XRVLT^X^hZj^TRR^R^Tf^^RhRdVb`\\TJdL\Z^\\`XRh``T`\H\ZTH`X^^^b\NZ`VZVRL\RR^bX\L^XV`ZPT\hR`hPfPfhTPTLLXB`TfX^XdZhP`\\b^NVT\`ZV^b\hPX`TZhP\^hXXVpR^\^\`P^b^bZZL^Td\jbXX^^NTZVPTZ^RdRVPd^X\\hNbRVVb^\bbNZfVfTZb\Pb\`\XlN\`NfRPP\>NHb`ZTX^\RTZZbVXZRN\ZT\bZJZZTZN`TNX\X^RbX\PP^XbRLLh`L^\@Rf\^\DbV\h\VT^PR^FPbXfTRX V^ P T \ ^ Z ` Z h L \ T Z LX\^VdXN\\XXT^RT^dZ^JXRVRL!`D Z JN!T!R! j!" h'X&&*D)^),^,,--,,.n+-.J-V+-V-01P4\3`5X7:<9V;:`=P>;^>T>=>A>f=8P9V76J9P72`3T7V4Z3N5b7X7544V4V5d68L6421^1P..^0/.N-)**h+,--./.1---,+^/.X-,X-+T-,^-L.-P+-`-N/H-P.f//15Z433Z47b57N8N:6465444X665^79H98T;`<=<@XBZC@AfDLI`GRGKfD`DFFZFDEJHC`EXFEZBlC^GVDTCEVGBECP@FCD^ECCCJGGEPFDEPIFELIVGGGNHFFJDXEXGH^JFPELDXDCF\C\GXFTEJEEbHZDNIDDCHVFHKRIJHFRLLJ^KPHIHPGEXGGGH`GDVIDJHZFfIVGXFTHRDbENDD\G^K`LILONLNMJK^LJ^MbKFMO\MQQXPMKM^LVHI^J^HXHLJdMNKZM\LZR\KLXNMXNMfNKXLQRXTPNUZSRVdWZU^T^TSTSSJPQPSQfQRQSPBQVOZORO^QNRNXPhRQZPT^RTQUZUTSYVUQ`S\SQbP`R`OTTQRQTRRNLVLXNfQZQQRLRQZRRVTQRSTRQTSZU`SSPS^PROPQQZS^TZQQ\N^OPbQNK`LNXJ\KLVJI`MKVO\M^PKPKNXKNKM\LFMdMTM^J^JZKHIXJ\MLIIJJJ\KRHJJ^KHGIJXJJJDL\JLJMMKKLLPNNLMLKH^FE\ETHVEBE^HdGRGIPHGHGJDXDNEHDCKDEJGE`IRJVJNHXHNJ`JFdHPHGED@VDABFE`IFfBHCVE`FVFHdIJJ\JZJ^HHF\IFEDZCIdHFGKLKLNJLEVGXHFbHHMZK\NPIIKHG\I\KJJ`NbMZLVLLbPJNMdKIRIJZLIGZFVHNHVGTFLFINJFKN\JHMNJHFPHH\KIFPCCNBXEND`=P@?R?@A@TA=X@=\=<\=V=bB=?;:`7598T5d71N3N3`2V,X..L,X/,T+)++N((L*d()`(L*X%&'P'N'#Z'X$'%'$J'^$V%T$d#"#"#"%#J$Z$`&d#$^'&*&(R&)&F(*N)f-L''b%'R'&)L((R&Z()%N)),*((((N)V*R,)+P(),.*`,b+&^*H)V)&Z)R)*&))V(V(N+^(L(R'V()\*Z)V'T&'`)d'%^($V%^&$T#d"#V##P d"F!#h!d \ \!T `TVNPPTXZNfZPVN^FRTV^TR`V bX V ^ f \ P ^ T X db\ b\bPXVZRNbdVT`bZbVP\`XXZX^^\h^X`PdVX`\NZRNXZ\VTX\dh`Vd\\T`\\Nd\ZP^ZT``bTdRddTZL`VbRbbjT\bZT`NZdF\RX`VTPTfVbLXV\bFdVTZXZXVZPb^TdZT\ZV\NVPZX\XXbR^Z^^fV^V^`RVTTVdRZTRTVb\ZPVbTVTRZ\bjZjbXdVZ^^ZNdbZZTX\^\Zbdf`ZPZPXfZX\bVVNXZXVbLl\\Z^RN\^ZNL\PXZ^^L^`^LVZJT\ZZVP`T`hTPXH``Z^dXVXXZNdVVXL\^TV\HnTZTNPlTRdZ`\dRdTZVPJ`ZDNRdP\\VNZ`TVHRNPRbLfVZRR`\X^hZPNPZ^T\^^  H f H X V N X f P V X P L h RVjRR^RRZPJBTVXRP\HPRXJH! >` T TT!J!#P#l'R'(T)(N*V,Z,T,-X.-D1^..,-/,R/.L2/T03689X9:9:9=X:\97^675R3X4374T36X;<;<=PBRAP?>?P>:89:8N7976443Z4V6T6\53`4R6F46^2f524X1X2X.d-P0..N+R-h,+^+\*-^,P.+-J/`,--\.^,\/b./,0*-,X,^+X+j-^(V.++Z/L./1T1^1R40R4`2`3B6N65F86^3^6^58H8^9Z5^94T8`6N7:\9R;;b??@`?>b>;?;;f;P<`>9T887N6T69V3333F2..T,T-.))L*`,^*T)\)*R+'Z(R'L%V'l&%H&F#^%\%V%N%^$j"V&V%J$f#b&`%$B#Z"Z"V%R$^#! H"T%#T%'%%R(d'&&,())^)V(T&T)l)%^&)T)'X$&Z(X))((^'`)))N()R-*P+'++V,,%)X(V(Z(T*(h&V('L&+'Z)R*'T)(&\))\&)R&&Z(&N&%$#Z#$%f$R"`#P"#R#"R!h!b\`: h!"f`JXbfN\RTPRPPddX^XZZRTRJRN^J V ^ V h X P Z  LT`LR`bXbP`N`T^RBdV`XLb^VZR`ZZVPfTRNbZ`V\TFdjVfdVZbZTZR\H`NXdVbTXX\X\VbfZZd\\\\LXd\\\`nLH`bPTVbTPbZRhVT``LVP:ZTTbJPP\T`JV\\TT^PXf>XX\RTJbV`^RNFZ\L^X^dVZ\`^dXN\FlX\^PxJhN\`ZdR`HTb`RVPXXNrhXdX\T^bfh\\jdN`bP`ZjVjJfRhV``TPTd`hb^\PdZN`Zb^VVXXd\ZNf`L\NZ`dZH^T\`^ZPRRXJdPhTVV\\hZVP^T`XRZRHfVZXVRfJ`ZJlFbVlP^XbdNZXLTj`JTf`ZlL\TPPV\Z`V^bb^\^P`^R`\VV^RVZR`d\PXH`fR\\dVTfXZL\PX X Z ^ X d l ^ ` fT PT^hRRXX\Vd^NTV\\\LR`X R! PV!J" Zbf!Z %^$(&T)()V+-/V-b1.-,-,--Z-/L/\3J3T5R547R77;Z;:=^;b;8:P<5453R5N4567T99>T>X??b>>L<>>T>DR??P>X?L>`>F@\AVA=C=@9;88^9f56L5Z424N64F5558556X546\5X3X14^/X0--X+Z,P+++++-,b,+H,V,.1R,0V2V/J.P,.,^.-+-L,V)\,*d-^0P..Z/0R.0V2F1T1R/V3V3f7T4656979884777Z5b9f8d:PA@XBVA\AL@`?^;=F<;`?<^=>;;`:^7V6d57R8X7`2N1d3b.3Z1/--j,,*>,*T*V*()b+*'(^)H(&)\'P&N%T%N'`&V"b#X#X#X#$b$$#%`""#"Z#N'%&d%N$$R'(T&L&'&X'^&)(T(T&T&X&V&&'H&(Z'\)X)R*')(X(Z('N(()*)`+)V(*.V*,*T)X*P)\&^()'`'^'(N(X(L(&Z&(X'R'`(**(\(N)h(('&^%`%%b$R&%H%X##"D#!b \!f R!!X P!\H !T ^bTV^\NX\THRXT^D\R\ H `P X b X ^  d N ` f`^dPVPbZbVbVXRXLVXTZTXZPZFVZ\ZXZ\TV^^b\TTZdRfb`ddfZbbRPN`hZRdR\fb^\XbZPXhVTP@PZXXjZZb^TX\VTfZN\d\VVJjTL`P^Z`NXbXV^FZV\P^R\bT`ThRXb\bP\dZTLPZR\bTR\Tb^R\`^VL`^\\LVX`RR^dZJPXXZVN\F^hb\dfZ`F^XX`P\PlX^XPX^^jd``bT\`VdbZTZZZZ`^N\nV`ZTVnf^FT^XP\^dPXZVZX`NTVXZPTR\RVR`HVPjf\\PjXd@`LRhTV`\XX^fT`R\^NZRV`jRT\fV`PT^\X`F@\T\^X^dF^XfLTZ`X\`R\J\Z`Vd`NVRN>ZFXbT\\RX^H^RRX \ b \  \ B ^ b L \fLfVbTZjdV^ZVbLhVVZj!B#T"\" R"R^ V !! T"^%('Z*f**`+/L/J-\1P1Z,V.-X-X.X,+-V/V0L03T3548b99;j?Z:b;N=9R9Z5\8P873T75X7P67b9R9;H<>PAd?V@XATD=b;9;6R85\6X645Z5T1N3h4Z:5:5Z44L5b43220Z-V/0,d,2*h+\*h+T*b*`,b0*+R+++..//1/X-V-J-L,Z,\+*,+)N++h/.d/Z/0\-V./X22Z/X34h6T5d64\78P9\9T89R78J9796V8T8;=P<>X;R@f?b@@@B`FADFEBZDCVCFDCTE`CBTFVHBDCBEfCFGCFXGENECPE>DNGHCLBRCLCREGVCDJBJCPERFZDdCDHDFDDVFE`DHXFTCCZE^EVBVDD`GKGEVEEJHFDGETEGFHIILfLXMIHFTKGdJI^EC^EE^FEFJbEBVBZCPCCXFERD`DECEZETIGPIXHIZK^JH\NJKXLZKTKXLZMTJIVIIZJVKRMIPJ`IFHRKfL##$"!\$""\#^&X$b$T$$$%&P&N'$T%%T'(^(*('%&'R(V'P&&&Z&b'$N&X)Z'T(Z)&)))\+,*X+)**L+)(X*P)'L')R')^)Z)'(&R'*Z*^&R&d&''J(T,)X('b'((X'F$$L'n%H*$N&^"""$ N"!^H VT`\\ZVfFPZ^JjVRbJNLFRTV\^RX L R d V T d R L XZR``X^^X^XXTZRbTPVXXTVXXVVbbJZRl\XHZRjXRXTfFRZ^Nf\^RnTn^\hP^T\P\ZfRdZV`N\^TV^^PPhX^N^^XX^fX^VZXL\bVPZbTT^\\db\VbTXbVd\L\bRdPZNbXT^\dRbVVXPPL^FXZV^^TP\VZPZV`^PRhb^jXPLXV^fRZnXPZZT`Pb\T`TPXLdV`ZLT`^d`l^bT`ZbZ``Rb`TLNRNVDdJ^V^XdLVd\XPR^NVLRTXVlXdXX^^XVNJjHfVZNfT^PVZRVXVJHlRVPf``XlLZZ^VVdNT^ZXb\`RD`H\\L^RVXPTPL:bJR^VLP`RdV^PXjbXNZ\T^XV\ZTX\ZjVPTRbT b` ^V T V T B Z ^ V h HX\\^RTZ^VNZTLVRPb^^P^TbHZVH `!V"J" RVN^H%"N#b&$(d'&+Z/\,-b/T-./-Z/-X-L+^+,.-P1f16T33X4b77:Z;<\88R:7\;P9^5N54Z55P8T5V58L89P;JT=^??CR@JB>?:R76`765R3V5Z21\222566T4J553V4R6`220D--.,+P+)+*X,+).,V+\.N-R,,R.`---Z/N/P.,-,*++\,Z+Z+.V-V/T,R+-/T/0-.235L6V5Z44\6Z7789J5d8J7p;R:8978H;;:=>V>\B^BRAA^@AXDCARAXEBDBVDTDEG@LECZF?DZCTCBD`ECE`ETDBDEGDXDhEADBJGACHBPF@NFNBNBBVEEbCATERDPBBFFEABPCZFbFGEFDGGD^ETITFXGIVIIJfJJdMHLJhEZFNEHDGEFLAD\EbIGPDbAHD@XABDhIJFVJ^DGFGVJH\HJJHTL^JXJNJIKNXNVLHNZOKFKRGbJTJF\JVIXKfKZKKFJJ\J^IHKGJ\KIRL`MHTJRLLKfOXPNbNPLVM^K\LNNINMZMNN`RVLL\NONJOLOQZOQFSTNL\LLbNZOROSTVO\URVXTWTTVVhTdQPDMPLM\NLXLNNQVPNTOMNVQNVVU^VULUZW^TNU`STONOTQPQQfPQNTQNOPOhOLOTRMZPLTQMRKJKXLVKHHJTIVNJINJLHNGhMFDJXJIHLBGPIIIGHHZKIHHFGKGdIFtI\IIZJVFZHDVEG\HHLHHHLHGHPEHDPECBCDF@\DBA\B@TBABZB\FNGGCPFfDECB`CVBDjC\CCHFGAbEBCBGFBHXGFBDVE\CBXFGVDVDBV?REDLBBVDCECEENFCECTFFDGZGHGG^I\MKLNKRO\LMIGHLIFM\JLLLXLVHZJHIHIZMdKNKHhHNH\NTJPOZJJKRFEH^EATFZFNDBEJDEDFERCNETAX@`??JCB?@?;=X=X?N?V;^;Z?N>;`:655F4^5445J30T//-N.P/j/H-T+Z)X))J(((+T.+)b(%%'N%Z&'$P%"Z#X#!"R##Z#"V#V"#"L#!V"T$X$N$%R!##L'%&$&\'&'(()&Z(%H(V'X&X'*%T)L'(()*R((&*\)*(,*`)'X(+V*P+X+*')Z(*T($Z)D&X&%+'P(j(%\&J')H&*&\'\&d(X&P)\&T&T(P%X%$Z%$Z$Z"#!R!R!! L!RVX  ^H^^^d^NDTR\TTPXXVTRRb X\ Z RX Z P J \ F T ^ L \ R RfPXdX`ZLJ\bJ^HV^PV\R\T^\\VXRVd\hH^^b^R`TbXR\^\ZVRbb^Pbj^VL`TNh\TVR\PNZ\^JPh`VLjX\fVTX^TT`P\\^TVZdbdbV^^NTXbbZPP`h<\NRZVZ>`\VPZf`j`d\HVZRPhVTZJj\f\^dXZRfN`P^XZPVV\L^TZVXX^\^PbNRZVbbXFXT^Z^Z^TdbhZHdfdZVjfb\fT`\^XZb^T`\V\bffXPZ^`JZXZT`nR\X\NVTb\`VP\PbZ`ZTnN^VdJ^TXTdV`X\V^\\VhJ`dZRRPTZ`\d\\fR\^\f\dTX\XhJR^TTXZlPbVVXJXf`fVjXPZX\bb^\hTZT\TPXT^bHRZThV\RVfZdX\P`N^^J^^T`TdLZdNP\dnb N P  N f T N \ N V \XTVXHRNT^RZPbN`L^PV`\XL ! ^!V ! !X!^!P$\'V&'Z(T)J*--R/.X/.b/.,-d-/,P+\--Z11T225T48<:h:98<\::878P8T5f5V4\4L6Z48T9<:b@`=R>b@XBCAB?=98V9N9\6577L61b3P34L2V5\5N54T55X4P5L3b31/,R--Z,`*d*))**R,d,X,*+`,+X-P/P-`.-r/-\-\.T+T*T*\*T*)P)L+R+`,+Z,T.f-Z/,`.\/0/Z24N5\5`3V58X6798h6X7L7b6H8R9R;9d::P=`:V;;CDTCRACARCRFCDC`EGB\BBNBTBCG@EDAPE^EBBACDXGCXDEZDCCJB\BEVCBTBBTBBCBCERGFZEELIF\EC^EEDFFNHH`K\H\HVLZKMdMIHJ^KZKMKbMZKPKI^JVFJHPJRK^KRKHdKJJRFI\H\GPKHEENERDEHEZGDF`HVEGCHDfDLDVB?@VC?B>P?>;n;Z855R6`7T6V7N6231./n-R-\,V-,,f*))*)*V*,\)\)H)T'V(%^&''&&R$X#V$$#P$""""#$P""^'J#$%%#X%\$&^'X%`$P%%%%(&(\'`()((P&Z&Z%&\%&(&*T&^'R(&'(Z(&T''l'`('^)\)-+))P'Z'*\'J)'&'X(*\'V)X(T'^'Z*&V&`&Z)&'T'('(%%%%^$$j&#T$%\#V"X!"n#L`d BPZXRB^RPRX^h^\XNdd\VbRVVXLR R ` H d V V f \ Z J R JNT dR\ZJ\T\R\PV\X`RVXNZ@bTPVL`THFXRZP\\VRJVN^Pf`V^X`bZR``ZNX^bVXfZ`VX^\Pd^Zh\Z^VVfbl\ZVV^Z\LRNdVR\bTXT`Z\VXbPTPd`TZ`Z\X\jPPf`RVXX@bZZVV\\^\\bbXXdZ`R^XZ`PZ`N\ZRZZVVbT^\\Xb\\\PT\TPVRLHb``TN^TJ`fXdbVfjd^db^TbnZVd`dZ`X`\\N`ZRZZP^\\bXVNRhXX\RXXf\RXZL^TZ^fT\fjnVVFZhPR\ZdPVVbV^VVJD^TL^T`ZJ^RXXXTnVPVRZXX`LfTNZXZRZN`F:\VVNPXZlTVZXXZVL^TVVXPfTVRbPNTL`HLX\TVTXXNZZXZTHV`Rl`dPf\RRLZ^VTVTTDfV^ V \ P ^ \ L X T X NT V TZRRVJbV`XV`X^bV`j^XZ`P! T ! !L !V!!$T$$&)&X(V+*---^00/D0B-,+L.,Z-/N+\3P//121\5T9L:\<\;:;V;8R:8N;765P5Z64V9`79R98^=N>TBVC@?AD@`>^@=86b4^5453510251T4H773\5\65L7332^//N2,R-.-R+V*\*V++H-T+*,V,R.+j,0X,N-,V-Z/,*V)*R+V+\**\++V,*`-P,V.N0^/`/.P0Z11P2L4Z3V548\5T76R887`:86b5T8V9T9Z:<::H<<=X?@T@CBCZCAA@dCZCDbEBNECbCBLAdBCZDjFBEVGRCbEVDXERC\ADZCTBCH@dDCDAVCTCBAAhAJAbC\@XClDTFD?@ZC^CCBVC\B\DDCDLFPGD^DdCGHhDEG^GTD`FRIF`GIII^JPDDCXCZEEB^ALE^CXD`ENDBBBAADZFZGHTG`GREXHGTHG`I\GHTHLJJHbGEF\GTKIKKZHXH\GFKZKHZK^IIPMHJI\LKJIXKGTHHGTKKXKRIJIZJIJ^MJ\JRHdIHMZMKHXKRLZK\ONNVQZOKRIFKLLLMOPOPLZNLONPTNdRPTPTXVUTTUWTS\LVSSRPSSBONRHOOMN`PVQVUPQQVRZUJVTS\VXNV>VVU`S^TTSTNPNOMOMOOP^ONLKJPM`MTNKVML^LJDOLMNMIJZNHLKFFdIHLE^GGPE\EPHE^FVFPEFILHG\ITE^EDdEbKHZFBERGTH\FRGGHGVHGIZHJJTIRHJRIFHDZCADEDBBRDpCEBAAD^B@ETE\D`CLDGRAVBTAPB@CD^DJHLFFD?CTBBJCA\CbEADFDTCRDDdCD@D`DLEEDANFZGECDDXI`FHEFfEIXHVGZKXH`GJHIJZKVJJLMPKRNKKNKLI\ITH^JHIKXJTJMXGXHXFHGHRIILKZFTDTCVECCNDEdFXEXD`GDbFED@N?@`@NBT@T@R=N<^>;h==<6P73\9363100J/+P-J-J-Z-D,)P)\*())Z+N,R*R)T)(V)J'T(%$'Z%Z%##V#%Z%Z#T"##"H!!R"$L##b$P%P&\$$$%#V$'&N&\&&V')J'%$&R'X(h''N)&&(\'Z*'%'d'Z&h')^+))Z*+h&((N-\,P)R(V))((*J(\+'(N'\*`)N+&&&')'()d(L''()'&&#P$X$#$t$N$Z"d"P#Z"V!N \`! ^Z^^^`PbP\`TVZ`^ZPR`XZTb\` \N ZR V F N ` V h V Z^H PlZRfZZjRVRXhNV^LZP\^RRdHV\hR^NdTR^dNffbVfVZZVFTPXR^L^TP\X^RH\TVbVdVXNZR\PPRZ\dJ\`\NjXZXbV`d``RfZ`HXdf`\R`n`T^\DTVZ`X^^f\bXXbdVVbHXLhTVXLRNVZ`RdFjZLfZRlZ^Nb^hJ\\VZ\F`Z\X^RXTTd``RNPXT\DRX\fLTV\R\`PV^T`PjRZZTZfRllX\\f``fThZhZb^V\`ZbRXZ^PddT`^TbbZRVVNP\ZNjZbTP\T\fRXV`LRdZR\VhdTj`TV`L\^RJ\^\RbZVLZ\HNHR\PRnRL\dXdTd\RHLRXLX\\TfZ^N^XLbPZLVX\JZdV\b^^T`\PT`^lNdbTV`XNd`XX`dVL X\ F ^ Z F X ^ T X J V VTRLjDT`X`LZT\b\VbV^dNX"Z P ` V" `f"\#!V"f#P!!P"$V%&X())b*N,Z./L.X.R1V10-X,^+B0b,,.b,B/V/.1R6T6598:><:V<9f79Z:V76V347549R6J9==?X?X@\@BZB@?P?V;\7\9P76T40`2V311X4J1T2L234^3Z66\3L5\535L0X1.N.,+^-h-.b*N,`+X.^**,X,++P*V-V.X./-/*P,**(T*)+*(+J**++X--T/`/-P0.\01>2455\5b567P97h76767R86799\9P:\@@B@C@F?ATBEBPFLDEFCEPE^CC^GACA\CECZFDVAAhDXBPE`CND\BXCRBRABX>?V@fC@DBJD?AJADXCZDPFDdC`ATED`BTCHERCjGZDTHDXEFTGGGTIFDTHJJfJGDhFGRDfETDDVBBABCDFDADDE^IXHIXGIFNHFDXFERGTFXFJCNHHEETGNJXHIHGZJVI\DJHVIHVHMJPIdJMhONPLVHLIHH^JRJGbIbNGDLbKGJPGVD\GbJPJTJbID\KIPIMXOTLMPMKLKLKRJjLNMRMHPRLNMLXOTPPQ\RQSSXUNYPRQUBRTQFSdRJQLORPQQQQPQTTZTbVXWTVV^T\XbVRZPNPPLRM\RXMVOZQPVTXLFNTOQMKN\PKJTKLZKJKIMXMNKVHNKXJHIXGZEVI\FDCDBFEEHEhFIFKHTHFEF\GfEGNGLDHFFNGfGFIERKJZGGHKRHIGXEILDD\DE`CB@X@`ARFBTBBAB\?NDPACND^HjFDPCPDDADRACF^GHVFdBVCD?PABEBBDbCXFPCVBBBEBRD\BZBD`HRDBDDFDDHFIXFDRFdEEbIIJRIlKLFHHTGHfKLM^OLIVKNKbJGRH^JIRHIIIJKHJLG`EHGHGJTJKTLF^GDAfEEDTDGBBBLAdALDdCb@RDdBABjC?=<=X;<;\>P<=8;^:9T9T6b53d45b43T3V1F/\.-L,-Z-.+X*P))+)(V-`*)b)))\'R)%T&`(%`#%`#$$l%R%&H!j ^#\""T#^$$P&%T$T(R%&R'Z(%d&%$&('^'\'V&&T$&P&'%J%J&L)\&%T)l)J*`'Z&%(\&&R(((T*T(P)T+++(V,`(B(d+((+'`&R')P)(+(N('&T$\'%'T(T(&`'()R&d(N&$%#b&&L#Z%"#! " "TH"PR DJV\NXdTbX\^\RTRJbPP^RPdNV\PTTJd``XZZ Z N R V Z TXPXJX`ZNdXTXfVZVX^PVTVfZTb\JLVXJPR\TXThXVZ^`dX\XlJbJTbTPXVPTRD``RXT`PRbHbPXjZ^jZ``TDV\XV^VXLZjJdT\^VP`TVb\TRX^XXRP``bPXR`Td\bb`Xb^ZXPZZPLVfbP^ZTJR^XVV^HVN`TNN\V`R^RbV^X^BZdXXfVZTbVJ J\N`Z`\JZV^`hR\\dbXTd`LDRf`\\^J\XdV\Z^VTHDZ^`TZ`TPjdVLT`^`T\VdnVZVVR`b\bH`HPRV\PdVZNPRVV`LVdL\LPTLRb`V^Rf`P\\LXbX\RRdPf`T\ZVX`VTRPJ`^dLbT\Z^ZbT\\^PTdJJ`PZ`b`ZbPNVZPVJVZNZRRfXTPTT^NF`PJLVLRTXXT\Pd V V J Tr R P ` V Z ^ N \RHNRXdRV`ZTX\NbVFTXTPd!X!`!VT "T! "^#L$&\'&T*+-R-R0.Z0V-J/,,V,*,\,---P1R/Z2Z1f3L56;=B;<\=:;9:P8n9P;65T54T74P4Z7V9P>?X?\@E@V@PA>R@<<:786X5J1X0P21b1N11N52`4X6344h3644103`/-H-/H,-Z,)*)+++l--V,P++,-b+V.Z--)^)V**^)T))**^*V+))+,X+..,/.10R35d5X458D98;;787L7L8R7`:56P8X8R9^9X;T=<=P>>>`BT?d?TC?NBRBEPFDNBGEPAD\HTIXGVEHD@C@AZABRCBTB@@\CCDXDCB?BAPA^BA\ACDD@AR@dAX@ZCZD^ECdDEEB^ECFI`HTFNDRFFDIFXJTJRLjI\FLEPFTEFEGVFVF^DDCGELDAANAVCACPANEDnCDCFHPHDHVJJHEDTFNEDVF`HRGFHHEBRFVEFIKVHVGXFVIHXLPG`KLZGXJKG\LJ\KXKJKIIJHpMIJIJHGH^HJH^DEEdHMK\ITKZJBHVHZHTKNONL\LLVMVOHPLVPLMXNVM\LTLMLNPShQ^TRZQQRUPPU`RPN`PHPLPQXOFMHQXRTPOTQTSSWUXNWTTUUfSdXUTSjORPQORQZRNPXN^PQLPPDM`LNP\LOJLKI\KGJVNKLZ??=;;\=`=9:T9Z9;:N7X74\7L3T4^4X3211N3-^0/..b-Z,+V+R,X)+N,T)\))D'(&\&&T('@$\%\%$V#!L#V%"!T""Z!P !$%V&b$V$##'\'\($\&P&J%^%%$X%F%(d$$N$`#P&\&V%Z'(N(Z'T&&+\''H%d%$R((\&X)d(D'''^'V*J(*`(\(Z)&T)`(V)R'^)d&%%P(^'(d)'''''&'V'&(&T'(Z&#L$b$$$h%#% #\#P!j J  Z!V!X! PVT^R^d\`RXHRX^HX`LZ\` Z  \ d P N L b L XJ ` fZ^^PLjdBRdRdb\TZ^XZLdXTX\TfTT\ZJh`TXVTTTZX\NLPR\\HH`bVXLRRXP^VZ\X^dRTX^bVhXjbP\ZT^^VRH`X^^XPXd^`PZ\V`L`\L\^^dZV\fZTZRlJX`PZ\Z\bd^X\TR\TPXNdLP^nb:TZ\`X^VNVZ^PX^FX\T`TTZV^X^XHZVbJTJJZVTZhXhZ^ZfP^^f^ZVZ\ZZZjZfVhfTb^j`Xf^HRZl^`VRX`h`Xb\TZRf`V`X`V\`XPbV\fdf\JXb\\VjVT^TfTXT`b^`jRTX`HbL`b^lXRb\T\^Rb`bZR`ZbLjLdhbLXPLZT`\`fN\^\NNZbT`XZDVPN\Z\ZLLXVVL^L\PRZHVZP\RTfZhJLXLVjXZ\TbVZTPNR^TVRP^`d \ Zh  P X X D ^ Z ZNd`ZXVVRN\VNNJ\ZTVTXZJj` TN#X!!Z J  N "P$R$X&&%R+P)+,.-/b.h--R,/,X,H-V+^,*d..\0X03Z4`5^:V8:R:899P;b7775563`5545f9X9?N;>T?=X=F@?Z@\@X?T:87`856^5Z00L30B2d10^2L354J6V65T44541.0//d-f,H,\,.+,*+V+*l,X,+^,^/--/f,+b-L)T-^+(*P*)R*\*F-V+,N,*)X.).N/T-J,1N14T2486X:88X=<<=T=N?@B?LAA?TC\DZ@\FAZEBBEEFDZBA`E@?@D@ZE`ACdDA?RB^AN?CZ?dDA@\ATCC?DCBCAAD\B^FbENFVED\FDdGGGEFGJ`FJVITH^KXFRDDVCGFPDGF\BRDD\DE^H`DD^BXFABZBATF^EDBDVFdCFFTFVGNECGALGXERHRDHRFDCRF\C^EEGVGG\FFIGGXIPIXJXNVIILGdHGLKK^KLJZH^GHRH`IJTKHGEEDDHFdEHFKRJHFZJLJRLKLKJ\LPKVKKLL\JJVKI^KKKFNLfOVKPKNPOQU^O^MdPPZN^NNFNXPVNNR^SPURJR^VVSVT^SULUSUSTVRSQQPOLNJNTPOPNQLbNLQnMVSbNLKJ^IZLTML^LJGnHLERFECDECCDBBCD<<:=B;;:9N966\5T6d57L424N521/1/01.`/+,\,+-*Z*X(n))'&f%'Z'&b(L%'P%%T$#P'$T"#!#!##X#$\&V%#$$\$('`''Z%$T%f%'&\'X&%\%#%V%L%T&&%%%X$`'&'&Z(&N'%(f(R()((V(('b&()X(*\'+'\+Z(J)'(%''))R*'^(d))T(R)%(V'('d''L%$#L'h'T#!Z!L%d"R!`!l X!T X \!f!RX\\VVHTXVVJ\X\^Xb\`dXV XbZ L \ b P R TV P\XbVZdffbR\XPX\NZ\V\^ZVh\h`VHRPNfVJXd`XX`VZ^^RXdX^b\\\\fZZVVdlXfX\ZX^fVbddP^`\bXbXXfJZXV\H`ZfbZfTd\T\^TR\ZbdV^\bRP`XJLbXFXnXdXVR\hfVV\\Jh^RZTffNXZVXbZVN\\ZZVb^TVV\fhRJNZZZX`VTPVTbdXV^bXZlbXf^^RPXb\Z^JTVZ\\bZ^N^TZ^Xb^^\N^ZHbfP`\P^d\LbfRZRX^\^NZNFZ\Zh\DjTR`XR`\ZTVbX`VTNTXRpXTPLPR^PbTRX^HVPXfPRNZXZPZXTV``DPVTP`XHPFbRZFZVZX`XZ^V^XJ`VRR~RXR^HNVbXNbXVdR`RFP^VXXPZ\^ P ^ ^ R V N : R L f N b \V`LB\PXP`Z8Z`T\PVTXB\JB!d!Xd!V"JP"R^N!T !`%L'%&*T*)X)+L1.,T1D0V-+-+,+,T0\,Z-X.0L4\3T57V::<=J=:;R;:6N7N6`652X33V45J88::N>?R>^C??N>>P>V<;T8Z5R3X22N302F/2P112b54V5V354Z35P7\31/2^-,++*P)*)()^)*Z-----T.^--\,.L,*V+X+-`+*`)N))+-L,,*J+)V-P-^-,Z-/13X3\4T676T:78b9V8N76N77X9;F88Z<9:J:\;9N;j>

AD@@hBA^ABJBAB>dDZBCZD@\HZG\CXCPAV>R?CX@=VATATCVBXAV>B?PA@@?TACDFFXBLCRECBCB\CBE^ACCZENETCETETEFDF^GGDGTGXITFXJHETCECRFTCZJPFG^CBE`BXDDETBVBTABB?CRCAGPFVF^DTDD^HDDGJCHPFENDLF\ETERCC\HXGdDCCFHRFLHLFIEVKRGHLITF^MTLRIVHBKbJTJIXIHILIJRHETIJIGGELICDjCLJFHZFHK^IHZILJRJMK^KLLKRLRLXLIJNZJMTM\MLZMNMTLLLOHNLTPbQN^OZMOKTLNPbMHTOVMbQPURTRUPSQRTR^QSRSTRRTQdORMOLTMJ\OVPMRMQLMNLTNMTMLJPL\MNIGRFGJNJGZGFXDAC\AfDbA`DB\CBV@BB@HB^CBhFCCFfBRGGEbEhFLGCNIZEVIXHHFC@CDGVEJFRHVGDPECEXDGBCBCAC`GVCLEE\BJDDR@XDTEFTDRIG\FBZCFETCbEXEDCTEAT?DZB`BXCFTD^FF^HTF\EBCFXDB`EZDFRFZBVDREECLADEJCREREfHFHIGI\FVHTGGGTJIKJLKNK\MJ`JJPMJMIK^GG\ILKHRHJGXHJHG\GTHGK\J^HEDGCDDGCF\ETDBXA@AAD??XBP@V>>>@R>Z>V>R>;^:<^84L777X5357D2\21\1X3321V/`1^/\,\0N*+.^*H+*,L)('V)P((&'B''$N#$$#Z#Z%!!^!!""T#"#D&T%#$`%X%`&'\'P&$$%%%%V&P'R%#Z%&%%(P&%%\%Z&R(()J&^'\&$^('P')j'b((N))$'(V'b(('X+&T)`)'%(&T'R(`')X(X+^'V(T(H(V(&'V*'@%V(J%f$N'X&$&$#H$""#"^ "X!Z"`b ZZZVRNP`bRPJZlT\d<ZPRVX ^PT L F V R T ^ T d bNF V\P hJ^\dHbbRLXbTP\VJXT\PRZf^VVV`JL\XVTZTTVNf\ZPNZXR^R\LV`PNR^\ZVPTfbTR\XRP`dRLTZTVXXRVVZHVNbJX^PZV^VVPT`XV\\L`RVNDXXXZPTLbXZRd\VPV\`VrJRdV\\XN``T`@\\XHdHT\Z`VZRX^XXNRfRVRVXN^PNbPPVJRVTZZNbfNN>RHRVTjTXf^^^bZTHdb\^Xp^V\\Xb^f^TR\R``RX`RZlfVTXX\TVVPdJTXT^RT\dT^\VX\VR\Jj`F^VT^hdVZPfTZRN`bVdZbJ\VXdJXbJVhbZ^TN\PTPVb\XXpXVZXV\TV\LV^P^dbbLPJNTb\bT\LRVfTZZLdTRXT\\ddRd\`VJfZPNVRf\`N`bR`NRX^ X L N L ^ b V ^ T FL l^`HT^T\VF`ZZVNfHfZJb! V bV J!XJ \!\#d R$'P'(\(*V,-,T-X1\0.-,Z+L-+,V,-T,V10b1\5T35Z6b7T9;`>Z@V=,,X-R.++**H,h*\,)f+V,*\.,,-`,,,,,,-V0b11P4V8Z7969^86@78b9T6`9:P8Z89R:99:T;N<<=L=d>CLC@?ZEbCPD^DdCTCR@^CFDBBB\?bCD\CbF\GFEBEDGEITGXIEHGTHVGCHGVCNE^X:8J9L8T566N9L5V54`7P1\01X3P4d4/2`0.,+,V,N/T+P+L+*R*X)h+(+N)\((^&T&\%N%%L&$N%h#&J""#T#X"#""^%\&V%Z"L$X&R$'%L&V$Z%T'P&%^'T%'X%^&'F%&F%&`&'X$P%Z''&\'(\(R&#T&'Z(''''('N+'J''`(N)J'J(')X()'*'&\'Z')b'*Z'X)\()(J((&J&^'J''%%Z#%##N##"!!N!Z#V!\!!PJ!V!XR`RR\^PP`V`TVXTbTPZTZbF\LVZ T Z N b T L X ` P ` Z V ` P XTP\^bZHh\^^\RZ\N\f`XLXN^L^^^^RV\TPR\bNVRTZ\ZV`\\Z\XTTlJdb^VPNX`VTPVf`bTVZT`^\H^`^XFNV^ZdVXbV\hT^NZX\PT^XFJhL\\p\VZTrRXXZXR\LThbbZTN\P^PH`VJdVPZ`ZN^^T\X^V\LZbLP\RXPnZVF`\VVXVVd`l`^d<^^RRT\XlVjXb\\^f\XVbdTdRRRV^^^h^@`^bPZNZZR^HX``bX\lNRTNT\dPZXT\2`NVNVH^V\FPZVJ\PfPNjR\XdV\PVRLf^X\TZ^P\FTF`ZVZJj^FNR\H`fB^RPF`HTDbTZ\VND\TTRVRVfVVLVVXR\dNPP`VTN\ZZ^VbRZXbTPRZJXZ>\bVZVfV^RXZTR^ X  V R H T L H X LXh dfLNZJV`LZVV\<ZTZV N!!!F"H` R"J"\#$'&R)*-,L0V//P..0V,.*,R.Z-Z..-\/03X5\:h6L7;:=V@?<>>:h7L855L412N0^.D211Z24R55794T6F721T2T2.0,*.()H*')N,^,'*\,()\-,Z-H/+^+N/*)Z+-D*P,)L+N,X*N,*V-,+V/+J.,H0.T121V4Z588656Z465\87R88d:R9X<<7X8X:8^:T8?j?C@CR@ZC\BJFXDFZFAPAVBVB>@AJ@@NCT@V?@^BA>989857J5V5342203010D/Z1R/-,N-\0T-,@-d++++)Z(X)'`'V'L('$\%\%h$H'\%R$%"#Z$#L!"\"Z#"#$b$V%<$Z&Z%Z%L$$J%N&L&^%B(T%X'$`'R%&`&%%#P'f$%R%D(T(b)Z'%f(&V&&^'%\&Z&J'b')(X)f(Z('\(''L&&X))V))))(P&\&b()R'^'f((b)'((%Z'&'%$T%J"#D$`$"#""X"L#"^ T Z! ^`LXNbhRfVXTXTPhND``XLbPT`^XXZHfN ZTP ` R ^ V D T N T ZX X dTfX\XNf`D\hbXV^`PR\R^PbLX^ZXdXZ`Rd\FXd^fT^P^VZ^`LFfZL`fVfPdLdjfNTPV\ZR`ZT`TXT\P^\JZ^R\Z`P^bh\NXR^XdP^hPTTRXThVPhRXZXTTRZNXZ\ZXLP\P`XbbNPX\bJNTTH`TRTXPVdVT`R`\XPbV^PVTN^Lbf^TZR>db\V^^j`hb`\`b\`bXf\hhRd`^\``ZXZ^T\N`b\f\RZ^VJfTZRZbZ^`Xnf\b`ZbFZ`V^dXh^\TT\NfZj^^R\TT`XZdhZTZRJNjVT\VZbZPjTfV^^Rj\XLPVNdhl^^Z^ddXNdX`T`bhfbLbR^XVXVTbT`fVPTPTNbXd\V\^X\PZb``\ \V \ ` \ f X d X T P H X ` : `ZZVLVJZNV^VXPT\L\\Tb VV "N!Z V NT Z""!"^%\$$^)T*+B,X--\/--Z/b,,T.+*.^-\--`,-/015Z5^8V8;8\:^<9b>Z9<`758h545Z52676;X;R=Rd>FA>d>Z>J:d8483r5T3//J.d0\/2R3P14L63`34b3330T3J20..`-R+h*)X)L)+V*f**((F*`+-j+*`,X,+R,^)'Z*N++^*H+.+N/)^-B+---.--X0T0b/`14d3F64`87b7B5N78V:79`:^89;P:989P:<;\:8:R;;T>N<FCdA@LDAA@@BDRA@ZBNBh@@hBT@XAD`AJC?A?ZCRBBRDXCEDTFHGKDFFJFNG`FZEFGA`CD`HDRG^GVGGDEDFEDBCDVDNEEbFNECXDCEhGDDHEPCFCVC\CFTENFNHbF\GDD^DAJEFCVFDdCB\DTE^DDGPGGPIIXHLH^GPIHJ`GIGJHJGJRHLRHVJHLIFZHEGXHE^JBGRHERB^APGFFDEFG\HFRHK\GH\HLIZGTJVI^HGPFXJHbGVFK\KZKKTJLJKIINROKLZLNLNNMZLPbN`NZNNR`PMOOM^LLMONPbO\MPK^KXKKLL`NbPM^LHNJbOKHRJHJNKGLGIPIGJLE\GDRFVEEEVC@VE^BDRADEXHC@^BZFDXEDFFHCfEBJEFG^GHTFTFTEbFTCRBBDXGDBGCDCPEBDTEVC^DRDANC`CA`EHCBGXEHETCDLCCLDCAB\CbCRCDZCBRCAdCDF\HEE`HTFCBDB\B@CTFEEDbD`CDEhFGTFHTICbGGDFTFXDJGGPEEGDGGZH\HPIIKTHGLI`HbJLMVLIlMJ^GLLZNKKOjHJJGFCFFFRLHG\GFFJJGFHEDDVDZFfDTCPCbB@J@PA?@BV@A==Z;:@>H;P=;;<^9:V647F6\4^434D4\104V0.T020L1N/--L/R1-\,J-*P+d+((T*'^('>*&&R%\&R$Z'X'%X#J##T#V#`#Z#X!!X"#"&"##$R%d$d$$%L'D&b'`&%Z($X&X&`'V$`&'T&V&'%Z(^'b('Z(&R'&^'('X(Z'N+V(&++&N+&T%X(&R'%)\'\(L(T*(V*&T*X)('&\&`(\*`)*T)`&H&N(`#N&T&V#%X&'T&^#B$n!V"#L"b"^"V!b ^!^ dHdJhT^Rf\HbJTZZVXNTX^^F^N\ VV b R R P R l P V H\PHZRVbbfJZh`jdZ^^NTVNdN\RRfL\RJTVRf^PTbR`bVVZNTHTX`ZT^\V`ZVdN`VVRThRNJPV`ZhdXVV`^`V^VdRTjJfPVb>jXTbN\`dL`d`LZfjFZPb^ZbX\bT\N^ZVXDLZ``Zbf^pXTdV\Vp\Xfj\\R``R`bfXPXdRL`XZD\`ZZbVZZZ^ZVRZJ\bP^TRTPnVTj`VbbTRXVXbZ^TZZjbHPTVTLXR\dXXR\Z\TTTZPXRVX\`\\PZf^Vh`\j`XH<bRVZ`VZ`\Lfl@\^dVhX`\VT\\hLlHPLRVRHbTPbL\Fd`dNZfLVTXLRNbfV\hXRX`RDTfLbNPNPRP^PXRhPRRZZZXLZN\RVVTHR\HR`LXR\THZJX\TXLRPNVTD Z H N X \ \ b b P PP bVRTbTL`JZ\@TZX\LbXNNbZZ" \"#X R P`"\! X V# !`$b%&+T*)b+.-0-,*.R,X-^-Z,*-Z,J/N1\/P1V26L6L7N7F9N6;:9T>@ZBPGhAfBJDZC`@LDE`AC?NACAACNCC>>B?@?ZDdC^@>>CV>N>^BAHAP?PATBTDNBBDZBZFFHFEHFXHEJELHIFRDDLEEGRKTF\GRELF^GGTDZDXDXHfEPECPDCTCG\FCEJFE\HbG\DFJEBAE`F^F\E\EGbEZDC\EEBDRFDTHFGDbGFEZENEZKJHJGGTHJZHRJEMJVKEHHTKGITGFIH^G^FTFGNGbDEfENDTDEBRFTGGJEGIRHEXEGIVK^HLJLNJRJFE\KFFHXKIJLRMLTJRJJ`JLHKZIXLKJNKTNLNPDKVN`PPPLPKLLKRMXOMRM^LVK\KLODITM^MN^K^NMbNTLIHJHHGTIJIXHVJVENFE\DEHDXC^EDDRCBARCBAAZCBBDNEGJIGXFJDVBDFTHECEGTGCCfBJD\DEFCBCAVBDTBDVDFZ@AAPCAC\AC`C\BCFTE@D^DZF@BTBDXDXF`ETDPA?V@BDD\HVH^G^GRFXDJDGHDCB?TDXFPA\E\EEFGGLD^EJDGEVEETGZFE`DZFEG\FCFZCEEIXJJHVENGLHTGITMJZMFLVLL^JXIFOKNTMIJHFH`DPEHFTIHHIGCRGIVFZGPEEFPCRDRDDVBRB>XB@\AF?TA=AXBR=XA9=9N:`76L656X23\52d22/V20/0\1L1L1T./D/R.X2^.J+,-*f*R)X)*((R(''%N#&&h'&&N##T""#V#N&R&\"L$%N$R$&%h$"h%T'T$P'$\&&%^'%`&%^'(T()'F&&Z%J&Z&&N*R))R'$J$&'X*V(\'T)R'l*'\((Z*&&%^((d('b')(^*(\*\))P&(&&X'X*F(R('(\'&b'%N%'$%$#T$P&R#b#"b R"!V"V R!Z V!T^ZVXXdVbbVJ`ZRX`XRbRX` T N H  H  JX^PVHHNjT^NV^XZ`XZXh^Z^PXh^b^\bVVXfdVRfP^`XX`RTPVNZhJ^VPTVRVhJRlRdZR\LP\R^ZZZXZXXHHNFb`XT^V\Z\XPN\T\ZRZXXTZTXXLd`\^\TV\bVRfbN^ZVLXVPXVTXJLPZVZ`NZP\fTL`VJVVZLdV^HdDZjVVTLd`\PX`bP\ZNhjdTf\Zh^Vb\XZdVdVLdVV^RZ^b`X\^XXTddhZTX\\ffLhZ\RV\R`Z\X\TX^Nb`XXJXNTVXV^VRd^LZLZV\J^JX^fVXTZXLd\ZXlfT^P^^XHNT\PhPbBfVZdTZRb\PZTTPX^LZPFNT^`VZXN\HFPVZZVR^^T^VZJJbTLXTfZLV`^\TRR`R`^HXXb^  \ J R T Z R V X F b P R \LRXZLRX^RPZRZXNRLZ^JVJZHBX Z#!\ V!\ ^R dL !!"`"T$^'&X(*,\/-D.-.F-+,R-+L.L-P,\.V,//^00b2b5P5V6\87F:;L6\8;R877Z7Z:Z574\666b6V:`:J<=>=>d@V<=:7Z6X7R5H3b1Z0J..`0b3P2F2X255V5R6N5X44N3b412R4`2^+*,\+X,,`+^)))**Z,*L*Z+N-/T+\))P)P,h*))Z(**.+-R.Z0-/b/V.V/T.-Z.-/\./P25P1667:Z98X<89999889T9P9:P7L99;V::`8^;d:;>ZC\>Z>T>AB>CX>NDX@E^FB`CFXE`B@BAACCTCATDA??CTA`BJA@HAR??DLBZA@R@BNE`FB^ED\HRIFG\HVG\ILGbK^HXI`JTGVFZITFFE\GDZEG`E`HHGEPHFIZHhHI\IHVDBZBC`EDGEG`EDDDCEHC^CBCDBBZDPDD`CEDTDCEXHFEEdIJE^DDGEJTING^FTFIPGbEIFVIG\GVHIJGJGFHJHGVKHFIE`IDZGFNE`DTEDFDECFGNHLIdGFHTIEZJIHI\K\KIRGFGHjJJTJVKIJJKXITIIZJIINXKMXKLMXJLKO`ONVOOVKHJ^LJOKZKJ\KLIHKLMLLZHHHJRHGEIHDJ\HZGGdGHEEJF^DbFVCBLDNBFRC@?@@\B??BVAZACNIDGFGDHXBTGI\FCFFEXGDV@^DJBABNCA@bCVDABBCbDEDBRDA\BAT@PCAPBZF\F^GZEXDNEEBBTCLDEEEBVBN>TDfACZEbCZGXHGTFFCC\DCdBAVD`DLFGE\H^E^HZCARDGIZENEFDTHVGEVIFbJHGZCVEDCXFVLJXLPI`HEGHIIPLJMPNZN\KJKINJM\KNJhIIIGEZGbITITGGIZIRHHFE\FBGFbENDBfE@??AN@@R@^?ZB=A>;;;<7N:P53Z1R2F1-0L1^22J41X3Z44b73`3^32D2X2b0P/T/Z..H.\-H-P+P,)F(*\**)(h,X*T*)V-)`,T*^*f+,b)T,\++B,-++`.`/P--B.*^.,0..F/d1T2h3P55H69T8F;;`;b::V9;`<98;:6X9\9L87:B9P7\899<<<<<=>@RCANAZBAREAABdBXDBDHBP@AXBZ@A?XAR=b?^@^BVDT@\A@>f>@@ANB@dBTD\EFDFHXJJDJCEFRGGFH`LHF^FZGFXGfF\DHGHJG\KFXGHF\GGXHGTGGGDGEEEEZDfCJDBXFPDDDbFF^EVFNDC\EEF\D^DB?BjEFEE^FHNHNEFPFEFRG^GfDJHHDFEXFFHRGFFHLDXGREPMGPHGFGHEXGJFTIENF^EGDEDEDZDBPFHGJKG\GPGHhGIJ\IKIETIGDENGPIGGPLIIKIPHHJIHbLZJNfKNPNLLJKJKPJHMILPHFPJLKXLrMJTIIKGDLHNFJGLLVHJJrDDNH=@DBCDVDGDJENFRGDEPADbBERGXDGZFGHEVEPERD^G`EhHLERFII`GFHHKFNGEFFXHNGFVJFGFPFXHXLRGTJIKMHOJHDGdIIIMKMJKZE\FIPITJHIPLJJEfHGFIGPELEJCTBATC@C@@J>L=<><;X;999P96n76^4323Z1R10./.V0\1N0/L.L-L--/Z/J/+P)+X,T*^+))J)(\))B('V'R%\(%#N$#X#"\#V$\$$"`%H$#J%J&d&%$%%Z%N%&&P(&%$T'&D&(X(\(*Z&\%V'X''L))'(N''X'&L(b%^(P)&&d*(\+`))(T&R(d'(Z&L'N(^'T(%(\)X*R)`'f'L&`&&Z&*J'&d'^&&N''Z%^$Z%N$R$R$"$%V#F"" T"\!V!" l#H"T!XV^R^HfBLdDLLDfZ`0ZBTTN^  V T ` L Z ^ V d d b ^VL^RVh\ZH`dRPVF`F\HVHZZX\ZP`^ZNRLZ`Nd\\XfZXL\BX\\hTb\fTb\b^ZTXf\bN`^RXPXZbbZPXR`TVV^^hZR\XRZTRF^R`VXZR`T`\`fV^`\\XZVpJT`Zd`L\P\b^RTZ\VZX`RbLZVPZ\JZj^BP^fXV\VXRh`XPXTZbTRdZV\X^VJTfR`bVZX`\bdfVhZ^V`Z\VjhZT^flVdVR^\VZVT\VTPN^Xb\X`^fbXbZPZ^\`VdTZ^ThRbTJ\R^VZRZRbZb^`B`^J^XX\T\ZXRHV\XRR`TH\T\fdP`T\bVX^V\FX^^dF`X\^VN\bV^VXTPR\^h\LHRVX\\PVNJRb\^TVZJVbN^fRR\^VPNP^V ^ J T V T J d `^PXLhRRPNP`TjTRZP^XZbTT  T#!\#b!TP! `"!!T!V$"`%L%(*N-\-/X-,+-/-.D-+,N+l+T*+.-014P6Z8^889J>V;b8^853/b20N2R/L/^0.0T20`4D3Z52T2241Z2Z11R1L/-P.Z+\+*')('P+`++J((*R)\+*R,T),\*P*()**T,,,N..`-*-T,,d,R+`,-.-.01X2R3L37^5D67799Z<8Z8X:F;8J<\9::679P9987:=P:;V=T:V;V<=?X@C@C@TB\A@ATAZCBVD^BXAAdCABTA`BXB@P@AVGTHXDFHHIGREGbGD\IGJVGHXFTEG\HIZIZFHFE\HFF`HTJJFXHHJIHFRMLG^JZDEEVEXG`F^GNDTG\CVB^BhCABVDDNCBVBCLEBTEbHXCfFERCXDDFH^GFEEE^ITGXHGBG^GTHZJFBZF^GD^FJFXFFBETF\CbF\GERE^GJF\F^EVDHTERFRFIGDBECDEE^EfHIG\EFFEGGI\IFIIGZGRGID^FHFVFEE\FERGbHVJZILLI`OdLKOLJKPKZMJH\INFGJJIdLGZGbGIXJ\KJZKRJHJ^GNHHHRFEFEE`CB\CC\CZDJEBBdCBbCNEC`@@?>@\@V???DBBCDEbF^HFNHCCLGCCRF`GFZBCBVBAD\ABNA^B?\@CA`ETABATDXCVB>^BAd?TEECD@DFECBXEbECXCDdBAATABbABCChHPD\FE^ETCCREETBFJETFFTJTFFEXGBCD^FBJF^DPFVGENE^LHNZKHPFTGJGXGPHVIdHH\GZGVJRGFRHHXJfOLMKKI\KHK`IRHIXJID^F`HFGTHI\GdJ\OXIVHE^EERHNEFNFTCAXBVAZDA>@X<`;;b:=<=<:P:<<9b:V6R6X535^62d111X/.0.\./V.\/\-/\.Z.d1T0+.J,X,X)T)L)*)X)''P(V(%%B%X""$""V##d%"P#`%"\%##X%%&Z&%^&$d&`%&Z)\&&$b&N%X&%X''&"'&T(''&R)''&&&'&Z'&&j(Z)*`())Z('Z'\'V&)&'&'&'H'&'(%))R(%J'$%^&V&'N&h&&Z&T&L&"V#Z%$V#L#%`!T Tj d Z!!^TT XL\ NRdVdZ^^hb`V\XZRP\^`TTRb V R R P L P R T V X Z  LTZ\J`dfL^PZRL^TdfZTNPX^`X``XNBNZ`^^\ZVLXRPffV\X\TPh^P^dfP^`Hb^jdTT`\L`dXR^dZ\V^b\PVbJ^VZXTb`\DXX\VZ\VRZ\V`\^VjRVV^\T`NdX^XVhTZPXTZNX\RHD\ZTNL^JRVVbRN^VRTfNZ\VbbXb`d`fNhdLbZdZ^NpB\NXZVXXP`VPfN\l^^b`^R`Z`bf`dtXV`XjPV^f\XhVZX`bhXTl`dV\XXhVVVdX^`RbFT\P\T`NVXTT\NbLZVZ\`TdnP(XZVb\Lh\bVtXZVJZ^TV`TVN^NPVZ^ZRbVXNVV\RdRddTZL^NV\T`RX\bTXXT`bdV^HTLPRN\RP^RLBRPXN\`L^bPLH`JTnV^NTDb`PZV X L R ^ b J L LZbX`H^JbPTX^\X`RN\ZPXPXVZFZTR  ` R!Z T# L "!T$X#R "d#!#\%&+`+T*T/-Z,,V.,.X-/V/`.\*^,+R-//1.35N9:X:^9V=`:=>Z?>\:T=T8N845113X2`1/1.T0V0X52`354244H33X10-,,.L+Z+X)P,)@()L,^+)(V(D((T+X*@**Z)l+*X*X,X+R.V,,-.-V.-l,,H,F-*V.`0,Z/1V3V23^366`95:8R:7;`;:;@P>@f?C@XDZB@?P?HAAACE\C@ARAT@P@ZAA@APBN@@`DABBBTCdBBZCNGDBDH\ITG^JfFLGDTJ^EZIG^DEDVBEG^IZHGFFEG`FFNGHHGXHGJTJRILJGIXGXHZI\FbFHXEBGB^@PEAFTDEAdCEVEDBDDHBFVDG\E^G`EZCHHVHEE`GD\GIbIXF^FIBDCCDXEdGLGPDXE^CREXDE^ERFXJHHFCVFHEGDG\HHLDDEdFPD^GRCHDEXHH^HJEEXEPCFZGRGTJKVG\ECNGCCCXCBTFVJDHVFZG\FTIIIjJMVJIHHPJJIGRKJ^EEEGXCAXGFGJHHRH`HXFVF`IEVDXCD`HFEZELFTEPERBGCVDTECdCADCRB@NA@F@DZ>?@?Z@DCXDEEbKVIGXHXDTEFXGBHZBPDALEDX@TCBAP?T@@DC?BB@TB@VAB??@DXCZBDFfHlDAAF\DFTDdBXFD`C@A@EJF\D\ENCPFDDEXID\EPE`DF@ZGVJFZFTD\KEZGjF^HGIVHEERIGHHJ^FHIKJRIFVHFJNIZJMZJJHGNEfJG\KbJLJNKJXJIXLLHVKXNHIVGFdGJHJTGH`JJXKJfGGJLRIEVFdDCCBPBVDXB\?;8;9;<<XX`dLb`VRZNV\fVb\TVX\LL`XFbPb^VhHTXPh\^Zf`ZhXd\fVZTdPXhNd`^LT\fnTflXXZZ\VL^ZdHVPVbZTZP^jRb^b\R`bNVV^^f\TfVbZVX\j^`XbZT^^`^fR`j^^P^hTZNd`dJhP`V`dl\ZjNbXdTXb\\fNdjL\\`^\^V^\\`\Z\RZR@^Z^RXj\fNhZf``d`T6`T\ZZX\\bP^XZZJ^T\`TdXRTfL`hPbfbH^V\\F^ZVRL`PLPZZZVVVP^XZJZfVRT^X^N\TTV\RPVPfZPNlXbNPTPThLdJ Z`J R Z P ^ ` X ` V Z X\ZV\NdRZZT\dTR\RX\` Z "Z! b"J ^"T! V"#V$`&P%^)**,F*^/,T,\+/V+,J/\-P/+X+T-X,h/T-\02\5377@5b=T;H;6R9n51^43R0H/Z2P01X2/R1V04`1b23\44\5f3L1`1//,.V,H*+)'d,'V)N(*N+R)X''X+*T**b,(h+.h+T+X,Z,-,@-j/+`-.`,\.H-`+T-/\/R-N//12H735P58677T9P8\7F7X89P:f:9`99b:f9J8Z79L8Z:^;L:7^;87;?=@A?>?@VB>ZCBTBVCEbBBEC^@b@X?>X?X@\AA^ABV?CCAAFDABRC^CCVDXGLE^H`IPHdFEC\EFF^ECZBEbDRHFPIGXIXIHGEFZFXGI\JbM^LGJXLPKbMXHPIfKIVJjKVIFTEbCVDJEADJCPC@RDDAADBFCJG^BDVGTEZDDDFGRHTHBEXGHFDGH\FFFRFPD^EBEDVCdHfEDDC`FRDENF\EEHNFZFGPIEHHHFHPFXHJ\ECZFDED\FDNFGFI^HPDFRHFHIbJGECbCVDJBCTB`AX@BLB^HlGDCTE\EFHJbLHXJDHLFFXKTIdDfICHdBbEERH\FVFTCTDEG^EDDFCCCBDRDE^HBPE\CX>@^ACAV>bGV?J@`@B\C@Z?ARAAbC@dD?XACC^EdFXHGFXI\HCZGHDFDVHCCTBICLAVC?>?V=Z@V@?XCX>?N@J?T@>@DBVBJBTA\GCDFDXEDCZCC^BJERBLCTEDBbDCVF\FTCDZCFECEhHPDDCDEFKGIGJCdFRKHTJ^KGTGHFG^JDHHLIXMJLNJJZHIJ\KJVHHFHJRGXHVG^JMdNLK>GdI^JZGbKJVK`JXIRHGJJLHFI^GIRHdGXIFFZJTFbGFJXGERBBDX?>::R99Z=NZ:<<;=R:d9d9L:V6^9V976Z33b3R410X/T.Z--H.1-/0-.H0J.P,^,`+V-,*X,(F)b)T*Z)T''\''#&P$%^####"X$\$P%$$$$&$$V&)'%X'd'l'T&&\%&T'h'%T'\&&&'&Z(''+J(&`&&b(X''&X&V)R(&R('T()T))V()^(T(*(*Z'`&$&&&&&\&%`'&b''%&(%$`&&N%'$F%#\'%"#"P#""\" d"R b VZV#bR\TT\^NXFVVXTPZNVPZRV\ZXZd \ N h V P V T F  bNNf^LXfZTPRJlTV^X^TJXbb^XPR^\T^ZH`V^ZVXLTXZdDZXTZ^ZPRZT^XXRZXd\THdRZ^ZpR`P``VXP\RZ\LddZTdX`PF`nRXdJL:\dTf^hZ2\Hfb^`bX^bXXlD^`f\LHd^\`^^^\bbj^LX\ZTZ^NX``ThTb\bXV^ZRZ\hbL\jdRbh^`JZVZZTXZdVNXN^\T`Hf\NTZhJJd\X\P\XRTf`R^Z`LbV^\ZZfPRXZfDF\ZTXVXb^\FNhZ\\XRZTJjLPdZVTLZdLN\NF\TRVNXTTVP`L^\D^VTbVbVd^T^fX`NPbNHFBdX^^NJ\^bRhZXTb`R^NT@VPd^\NZVd`\VdZdZRPfX^P^Z\PLR`ZTbf V X \ N Z P ^ ^ NbbXT\\JdTT\NVXPVHVZRdVVZT F T"" \ !" T!T !T"$%T)*P*V--,,J+L--:.b-^-/^+P,\-H,V-.^0X31L4T6R4T7;9b99=;X;^:H9Z885H54526\77d58N8L:;;Z<<<FA>\@@XBATAAVAD\B?`BLBCLDFDADDHDXCPC\GFFEJGEDDGVGEEGZDBD\GZFVFERJRGJGGFH^KLPKJMIJGHHIMJJTHVHHFJFEBFCAVARAZBBZC`DJCCRAAXBLEEZH^FFRGRJEVFGIGJVHHGFFGF^EHEBDCE@TEdCHRDIZDVDdB@BBFGXFEGGJF@FVGJbHTGFGF\HDCJC\CARDDFHHDVHVFJHZIIJGRDTCBCZ@^AVAAABBdDVDdFHEZEDCRELG`HJGPLXEFdFFXHGFXFTDDFDRCARBDCTBXE^DREZDbEDDXEAZBZ@\@>T?N??CBA`A@`BFEDFFI\DXCFPEHZDD@N?EDCHXHED\GCBDVFDDDPED\ECE\FG^IGJFFXH^G^JVG`GdIJVIIZEFHITGHPGJI`NIIHbMVKNK\JFDITGPHEFlJHHXHMDMLKIIXJEGLIHKIXNRJTIHJHIKNG\DHFIGbGFHBG^IENECDXDA^?>>b>;;N;b=Z:V=X8b;9X:^<:856\56P:64b3P1`422N/11-N0/J0-.V/T1N.++-*X+*Z-^*D,*)V)*Z('(X&()'$#R$"$T#%f"R%&N$X%#%V$#&N'(R&$H$'R&$#%$%$^%%&N(\(b'R%&\'D'\(d'D(\'&^%J'V'+&\+j&@'h'R&X'(*l&)X((L(&\(\(&)^'&(f)&%f(T&'$^'`+'*L%$`%&F(((&J&$L%^$d%T$#!f! J"P V!^!F! V NX L !VZZ Vb\T\`\VN\ZPf`JX\TRXDN T X ` ` T bR`XbN`LX`HjZ\T\Z`^dZVd^HZNf`TNdZJL\VRb\XTZPTXdVTd`VR\RbXXNXXfZ`X\RNfNRdRT^L\XRBZ`dXZT\Xb^L\ZTbP^ZLVLVX^XT`TNPXZJ\X@nZTfT`\bJ`VbVTX`P^Vlf\Tb`\HZhXTVRX\ZThPL\\bPV\PJVTVVbDVVPTDZPNRRVdPl^\\dXZRXfRhn``fNRXTfddJZXb`d^``Xb`HV\\\Z\TVTX\b`\Z\`V`R`XVVTXbdZ`XPfZTZR`\ZVZXXbRRVJh\VVPZ\ZTTbFLRRTVR^XR`\RTdZ\X\ThZf^ZNdVTjXRTXZZ\JTRXL\LR`V^VR`\Xd\VTTVVZ\TRT\NRLV^JVR^dbLVZ  J D X ^ ` R ` XZX XB\Nh`XPTRPZFZZDj\`H ^Z N! X!R!"Rb ^ #L#^%j%)*)+T.-d,P.,*/X/^,P-+Z,Z,/R./130485?<;N;?BACVB\@\AZ@@bBRA@LEf@AV@=^?==B?E>f?R@@A?TDACBCEfDHE\GXDDNDbEbG`IVDDZDCZE`HEJEFPXL`\\\VPP\XJ\LnVFT^JZZNfbJXNLTXXZTPNVFJ,T^RVbFRRTRLZJJ^FXTHXTZXZhXRTbJXX^VPRfVLRTRZZPTV^JP\jL ^ P T P B R V B R NR\\ ^JHVP\HTTPb^\TV!V ZP"F"X " Z"V$"P%%Z(d*>*V.J,,-,X/P,-,T/-,-Z-.`-0Z33T443^788Z;Z;b;P@dA\??>lCT>N>>X?T@>A\=Z>?Z@T?bBEABBND^G\FF\GCVDDEFGD`DVFZDdFHDTHGPECCRGGHJXJIHK\IHPJLZJKLLJLMRIPKPJJLPHGLEDNCDGEECZCDdCABBEREZEVEDGEREGVHVJdGfGRGEbIGTGFRHLHEEDJEFDCDCD@@PDA`FZDRDRCBC^@FEFGTFF^FHHFVHZDFERF\CZCPEEHECAC^BdCETGCXCDGREHTIdDDG`F\EEDBbB@=bBL?TB?C^@BA`DPAEVEPERINHVDC^DEFRDZD\CTDhA`??@^@D\D@EDDVBRBIALCLDbB@DAX?fA^C>@J?BBCdCDABA?\BP@?P?XB>^BAZARCRFGZFXFBDBA@AVBXC@AABT@TAARBBRGR@DVBL@>ZBA>?>?bBVD@HA@@A^BC@EGDXHPFZHCbBCGNBHTGGZFVDEHBTCCTEVDZCETEFERIC\HRDJJH^I^JITGGTHfGIFHHJXHGHFRF`HLH^JLJKLLZNIJKDLhJPM`LJJ\LHIbIIHMLI@HIFLEJVHJVJLLPNLlKbIHH`H\HG\MXGVHGTIXIPFHdFHDRECTBRBAf>P>=>d<=:Z:P<8f:77^7J;X98^;`7`66X5J2//23T4/N0X00/^/Z...-Z01.V/+,T,,-,P*^)(X*&H*Z'R'(b(T&'$$V##T$%#&R##d$$V&%P%Z%Z%\%V&%$'&%b&(&%$J'f'd&X&$(d'%X'X')&X'P&P'Z'H%&&')((%%$Z((\'J)&(%'^(`)'Z)X')N&\%<'\'Z'$R%%$d&'%\'&R&(%%`'L(`'X$^%L*`&%R"""#Z!" b R Xf H TXhLPPTJPjXXbZ\TdJTPLJdXTNRZR \ L P H < T P @ N V Z F ^bNLT^JB\ZZJLRXbT^JTdNbV^fNZ\`RVb\`V^ZT`^ZTR`\ZhV\hTRbFlZVT\VRVLb`bVbR\VTNVXZLR\V`Z`H`P^dXV\PP\F\dbXZ\ZZ`\VZ``VLR\VLD^VfbbR`b^PbT\L^dJXZXV`^TZVXR`RdT\^\XT^HTdD`\TbVP^VTTP```V`PNX\\H^F^RXXTZVZj`^VbX^VL\L\TdR^^V^bZdXNXV^Z\VbZP^bPXhTPZZjJZXZTLNV^NZLHfVTb^^\RbZdXZT^JRPVFfTVfL\bhXZDdXVdRTfVX`RTZ^P^dnNZL`\XXPZdVVR`ZT\PfXXDdR`fRXTf`Vb^VPjXbTbZ^T`FdB`\Pj`dVT^`f\R`PbZ^fVDXJ\bZV\RX^X|b^TT J \ X Z J J \ N ^ j XPV`PhP\L\JTfRbR^VVX!XhL ^ f!!\ #V^" X#$F%R&j(L)*\+n-,-V.Z/-d.`/F-.,T0`-/T2T/T3V4`3X6V4b6T979N:;:99\7V75V4V5P3T437X56Z59R68T;<^>Z98^:H:T@TA>L@?X@=@P?@?@D>L=P@BBBAB@\AA@VAEDNE^BFGXFbHRFGDDZCBBD`CA\A@>TB@FD\B?@Z@ZAX?P?d@?dA?ALA?\BR@A`?A>@X@??RC`ETDDPDPCCCVC^E\DEEDZIDCDECDbICRFDD^ITFZKNJRH^EXJXHJ^JLGJFLGVFHZGXJIGGH^IIVI`FIJJMJTLZJFIIKKIXKHL`LKZLLJLMLLJ^INIGIPGJ^LLQMRJKIF\IVJFJTIHZHXIRGG^HbGPF^DCCANA?`@ZDR@JA@=H=<>T8X:<8Z:V8^:88686432H3`1242J1Z1`/3/J.0d-N0/0\/J-.R.h.P,,T0,)X*X+P('(P('V$`&X'R%'R'$^%N#^$%N&#T&V&P$`&X%&T&$R'Z'X%%$&%R'\&H&%&%%\&%'`'X)%''*%T'd(&%R&&(\'X*N)P)`&&^&h'(&T(^))%&'*%((%^'Z&'X&%%&N$V%N'^%%%'&V%&&'\''$X$$b$\%%"N P V"^ h"X! PH ^! XL ZX\^TX`Pl`bVLRRVRP`^Z\ZX b X n X \ f ` ZfLVF^RX\ZdTXN^Z\VTdLTnbTdP\VFT``\^^Z\`XVXdfVLVZXTTZRRdRLdPXZdXXPVb\^R^d~`\^^ZVTZP\fP`T\Z\fVZV\b\`\`^\J`PTR^Pr\ffV\dVbHRZV^`^XXZVX^JXBbbP^^P^\\PbVhNVTZN^\\PXZjTXZPT^f^L^V^`XLXNP^RPXLZX`^X\bbL\ZZ^XZV`R`N\PNf^XVVNZVhRd\PRRbRXZRPHRRPbXR\J^^^\\`Z^`VV^PXZXVbPX\VTTfN`N``RXPTVfLl\RZ\PVJZbP`TVbZXZXXZPdNXVXjNP^`@ZdTZXFJLHdD\^ZXRdRJXhNRZT^Z^VZR\LXJX`PV\VRTTR`LVHTVLRhNPbPdJT`RZX\FRVTLd\FdLX d X T L V T Z T T X N R b^T T`VRT^PV\TZTDZTN`Z`Rd Z"!  \!##"P%&^*)Z*.\,0,R-,.0.,\.f.^.-/10V3Z14V55@599^<=9V=<;f7V:\7J54b6333N6546d587H:T;<;Z:;:T75R7\4`41`1V/Z/0P2N-`/./h02L1J2b3X23411h5P0.X-Z**T)R)f*N()T''X(>''(T'))(^)+*+Z,\*b+X+T,+\///P0`+\,.\,V/L.,L+,-h.X/T.-T/R0X/b0T1\3b1V62b423R6X6564X66X889T:5N:V<^88P69R9P;<9FNB;@>ATA?B^>?\@=Z>X@D@?RCV@?=@@@@VBV@\A?N@\@\CFRG\GdEBCDD\D\EHF^FCFLCCPEBF\GJKXKGHIH\JPJhIVIRJIMXLRPfPK^MHRLZLJXKRLFbGJG\FDEXFDVDRCCDDCCB`DPDZFDDPGZHVKTMVGEZG`FbF`IXI`GXGGTIFJFCNCNEXCDRBCXEF\GLBXCFZCDB^DLCEBVD^CFFRGFVGNEVGVDPENBADEFGHDBPBVDA^E^C\BXDCBGDEFC^EChFB@TEAH@ZHACXDbDCNDFCACdDBFGVAECbBTBEJCbACXABAV@?RB\EFTEDVEZBRBACNCREC\CBCCAB@\AZBAZBTARB^DBAATC>@\ARBBJEdDFDLCZE`ELDEDPDL@@DBVDPEPA@?PA^D\BAAX?J?\A>=<;?dBL@PAbBA@JA@DB>BBCLCVHVDRCDBRDbDXDBTEbEH^ENDDC^EPFVFG`IRIPHXKHNEbFIGJPN\KKIRH^GVIXEGXJdKVG\HIHEGE\KFLLRJZJIIHJTKEhNLI^LJXKLKVNFONNPI\KMRKMK`KK`KHKJJJJHXFHFVG^HXIJIFJGRFZCGRHhEbEZB@BXC^AT@`?V??X?;d=::;V8N:^9T7V89:8J94d342Z2V20b11J0.X/-.T-,`/R-R2.0V./,-^-P-T+\,N*X)T**)X)&L&%'Z'Z'&`&"V%$#X%b$#$&X%%P%Z%%T#%`$$%d'^%Z$(h&P&%&X'J'V'%>(L'\'Z&&'d*')'R'&T%%&&X(''$%&''&\(P%&V)'b((h(%&'$D$&%Z&X$$X'L$\&L'T'%%X%(V'X*$'Z'X%%$&P%%R"  "\! V" L!! R VdHH VV`\TXNFTLZ\V`PZZJJXVVZV\ \`PR b N N Z ` R P P R N L N d \ `RTLVbZVJTPbPVbLN^RVJbZT\\pLRL\bR\`X^FNPXRdNRb<^NfXP\NZ^XhR\`^\bV`hLZNZ^^J`^ZVbZZ^Jhd`\^NRNZ\`Lf`TdfTRVVRhZXj`bLrH``jTf`VHP`NVR`\RX`NFVXL`\^ZPRVX\^`bdTXNf\\VdXJZbZ^^T\PVX\TVfZ^XJ\X^ZVffJdh`\ZbX\fhbVNX\Zhb`j\XXl^Td\PXFZ^^dXdTR`BZXVNhX\TPLL^XHRTJR^\^XfRdfZ``\`NN^jV^PZ\bTXT\`\VTRhbX^b\ZTd\VRPZXVZJ^\HVTRT`T^TV`TT^XbRZZR\\XZfVNZdVZfXbR`\bX^HbVT`XPl\ZVVRZT`P`\RZV^\XHR\\dblNRbVZZbXh\N^^NPH ZTj ^ T V Z X F bPXZZRNFZX^ZLD`RJVVbZ P\#R Z \ R """P$\$&Z(b)*J,P,^,.0X/^./-b..Z-/T...003N32388P9b:f;<9H<:Z8T8Z7R57655`3Z4P5344^4-N-R/R.---X/\-.-h-,P/^+-.`0P/Z-d-R/Z/L2\0-00Z3^2`54P5b6562V57T67J76^8N98f6P6X988N:V8V89b:P>;\;>X>>X==@V@>>=@b=<\?DB>?DA@ZBA=>T>A^C@NBCTCCJDENERDCdDdFCFVCEBC\EXDVDPED`IEG\G\ITIZIFVIGPINKNTJXMTK\LJlKKVKJPJTI\KGNGEHbGX??VA@@XC^B@@P?A^?R?T?Z?NDDTBNFAZBBDRE^F\DBlFRFDHC^DBZGXDFGHFLLdHVI`KKDlKLHHFIHJLLHKTI`LPHFlIHTIG^IZKHK\KHTMMFJ^LKZHPLGGJbJLI?^=;R77T::6J5R551V1131\120^0..V0`.V0-/V.0/10N0V/V/V/.-,)+T*('(X')&`'R'%'%V'F'\'&#$$N%%&h%%&f%R$%&$&X'L('b&$%$&T)&&'%&&L)*)'Z*('&(&(L&'^)'V(%&&J&`(&&X)J'&T'`(&d(P'V%&&%p&&V)&$d'T%&V$%$\$V$V&%V%'^&b%%V$^&T$X#\" #Z#L#\#d!Z!R!X Z `ZN "^L Zh^F`VVR`TbRbL^`VPfRT T `X Z R T N \ T b N h H Xl XV^XdZX`DbV`XZTdPXPRVZd\^fbVfRPZPVbVLZXN\ZR`LVZXRb\^VR`PT\\\d`XX\R`\^r^\fV^ZT`fVN\JDRXBZVX`NTp`THRPXV^DV`PJVX\PZTf\P^ZdbNZTZjNVTb\P^P`NdTVTdPTZbfRX^XV^XPVT`^\FZZPX@ZR^fVZF\bb^X^T`DZR^ffV\\XPTVZ`R^HbT^ZPRP^\VPHTbJ\VdF\PRPV^X^RTZTJ^dHV\\JTTbh`dbRVdRbXVJXXZVPVTTXDbHVbbVPZZNVJLR^ZZdZRZRVVHVP\fV\fbVbP^LN@PTBjR^LXP`\XB`R^JHXXVLLLdT^Z^bZLNTTXdX`JTNPXJbTLX \ F T b TddZ^PNZR`VfVTV^ZXT`\ZTRVL^TR RX! L T ^ TP "!^"#^&Z')J(P)+.l2-\21X.-/^,J,T+,-L.T0Z/34R2P33R678V:J=;7;79T9V63445\321P333\5Z4\9R<;V;b:X::99X75X5f3Z30^/N.3P1`0X/00/P.^03\31L4X4^302X2f0/\,+++X)V')&&(&V&R&&'))V'*(X+H+J,X.R.L-X.,V--0R0V/X0b,N//P--+*,X*+`-X-X..P/X--d0J.h0T4R24d2V35b6V5V4N66697L8L7\665V7f67=d?=^>>>X?Z??L?Z@?RD@Z@>?@?XA@@J@BFDBBA\DATDTBRDVBIZAAD`ECBhDZEVFJIKJfKKRJ^JIJLJLKJKTMfLVMfPNJJVK\KFK`L\FGDEG^FEXFRFBVEFCRHEjDTHNEfFG^GFG^EVETEXFEfE`ERF\IITE\DLGCFED@^@PBTBNABPFDEFCNHAALDPC@PDZE\GBFFZECEBNDPGCB\BRABBRDRAABT@NEDCdEVECJDEE\GERGBCCA^EECZEHD^GDNCPACFBDGTCEZDELEDCAFE^DA\EBELFEBCFTFAHCDDPEVKPEDRCFFRE^AHBADJACL?@NDTABJ@C@A\?ANCAVDHERCEBBDETCXCCTEDDTCF\FLCDZBABfBTA@BAVAZ@^C@Z@=TAPAXB=HAAABA?RA^@@BTCdB\BJC@VC?CXABLAAXDCA^CBCPCCLEHCHCFZELFRJIVINJKRLJIZJHHFGJIVJKTKNILMNRLGHHTLTHLTJfKKNG\IJKM^KJ\KHGfGLZMVKLOdNMJIKLLILN`PVNLHKVLMHITJLKGGHJGIGGIGZGGHGREGEDEBAV@=T@=P>`>?^>X?:R9f=:L::;96J8X753N53X1N1X3Z241R1N0F/X.0P/V-1Z/V/2\/1/N-Z--,+V.*+H*J-Z)J*+L)\(Z'R&&'X&%%%`(%'f#T%#'%Z%\'%&^'%&J&'T%V&&F&%^%$%^'R(j*%'^*L'Z)P)L&(&V'(V'T(h')*'f*')\('(V('Z((T'&%\(N&'T'&b%&T(P%%%&b('&h&R#V'J'%P'\%&V'Z&&T'%%^%P%^'$P#R""L"X#F$ #`!Z"J!`!Z!Pf ZTR^RRXJbPLZ<TXV\@f6VdXXdTZP R \ X \ ` T  P bbZ`0RbTXTPd^V\VJ\\RVT\`XF^fT^Z8d^VPVdH`<PTPXN\\`^PVVT`ZbZ\Pb\dVX^bdXRXR^PPVXhd\`f^RX`P\TfTPnXdLLPZbTZRZ^X^b^\LTXN^b`\R\N\BT`L\RVRnZbhTdb^\JbX\hbN`TRRVHRT\XPPf^VZV`PVZ`VRVZXbR\TZ\T\Z`Z\X\``dpTNRLfJ\TRPlVNT\TZfJf^X^^bdV@VbZN`PZ`Vf^dPZ^Z^dPdvXVN^\hRLfZ`d^LT^^L^R^XNdZZRXX`X\TDZNdVPbRVRZT\Z\`XZ\8RN`dTX\JhLZ^`bZ\LXLTTN`NnNf^TZRZVTVRFVZNfZX`hb\LVBfVTLPX\T`HB^\X\T^FXRZT`ZRRRRXRTVVVZR^VXTZ T D Z h L N P X ZDH `PHT b\ZNVdhJhTRVTdVZPjZTZP^ZVR"X#"!^ Z ^P !^""T$Z(L&&+X)N.-.\/0V/R0-X0Z,*X..-Z.0/h032d6T9Z6R6\:7<:V;999X5J6\23Z514T2T324`26Z5:\:b9<=T>;:9T7`55J31031V.1T.`0/Z-- ./003V3^3\01D0`0T-,.-J,('Z(b&L%H&&X'X(Z&\&'R)(R)X*^+`+R++D-V0Z,.V./J0Z./\-+L,h/,V--Z,*`**`,,-^,L..N..R.-02N4L124R4253X37\6V68P5445L6f:F6^9T9\7\89`77h:<:;<9::V?>>Z?X@N>>>=`A>?BRAjA^@@AX?TAVBnBXATClB@RAARB\AVACVD\DVD^BDAEACEEIXIIKKLXKKLMNLKTO`LNJMZONKKZMXJZMbI^HZGVGHEJD`GJFPGHFFGFXGH@HGXHEZD\I^JLHFFHF^E^CDD\EDD\D`HBlEfDACEBEC@@AfDbGTEBBBZANAV@ZA?VAPGFBD\BBLB@AZAA\CCBAALCPCCTCVAAXA\B@BFBDTB@CHEE\EE>EC`DZEHTFBTD^DFPAdDFFZCNCDRD\H`CDDVECN?BABVC`FCCCAZB`FALCDEC`E\HTHF\EFNBdCHCAX@AA^C@LDbDjC@NA@ZCBXABXATBXEAXDC?dCAZCDEXIRGF\BDZAAZDJB@`A??\C@?d@dAAR@?b?BVA>ACBVEA@@?XBA`@J@pABAXCTBATCB@d@NETC@fB@EE`FRFTGFNFVGJFEZJMNMIfJJHfIJIJNPMML\HK\INLJfIHTIbIHHGIHHVH^HZLNIL`KLFIHKXK^MKRPKJKJHLHXLLfM\LNO^JXLZJKXJ`GHbMKHbKTJVIXIGdGXFCGEXFEVBDC\B\CCF@VAV<=?H>^@>?8Z;P<\;X:\98V946X65X622021313J0^/F2,`0X00`.b/.T/,Z/P/-T/X-,-X.Z-^+*+(R(P*)(X'J&\%V&\%%'X'V%&N&&X'^&%d%%N&$P$d$$N%&'Z'$&&##$P&&&`'J%P&`%N'\'&((*b'Z(&b((*'P('X(R&`%J'T(+'%T&D'Z&'d(&&&`&&(T'f&'L&h'$`&'T%T'R&&(%h&\%%Z'R%Z(P$H&Z$L$#$\$D$!#!P Z!X!@"P PTR!VXX^JRV^PLXPXV\\Z^d\T P P T N P V  V FZRJJ`TZXfNdJfZTRnJfVNTb\\T^R\VZ^\J^bPPP>XVZVT\LfdHVNnL\^TPZZT\NRdPVZTNL^NT\PHT`V`R\dJfZX^T`XdRFZPLZRZVf^^VV\DZRX`Nh\\^RTjXRNZNlZbPVTZ\R\fZVRbffdbJ^\PZVJN^^^bX^TRdP\VN^bPb`V\V\`fNLHhTVrPR\XbV`nZJVXP^^Pf\NNXXNjTPVXRdXTdZF^ZfPb\P`PfF\\VdJTVT@``X\J^VVZZTZ`TTd`hZRfRHfR\X^RXLRR\\NZFRX`XP^X\`VN^LXNPLhTRV^R`VP^XNXj\XHXNPVbPbZ^^NT`TZRNRNPVLZZDHX\NTFZ\R\NHRZfP^T\JV\R\XXTXRZJ\LRTbN T P R P V Z N ^ T  X Z XX\NNTRVVTNRHBRdZZVRL\d J P b\L!Z P "T#b!#^%&B),\)-R/\/-1Z-Z--T/.@.b./`---b0343447BZ>R<:967L83X62P403H1^3X233X45P96X:\::98865V84T1311R/V0/0`,j0T,,.1\0L3N2013P1/\0/+,b)T+X)'\)'%R&P'Z'V&T'&*(n)`**))*,+.R/P..-T-,\.\+R*,,J,,+-*\*+@++`/.-,f0.1f1X213X1223^3L44V66N98H445V53T44T5N7R6557P7`888888L;P8B9:d@X?@T=<=P?>@AJ@=R?@AV@@C>R@>^@@FCZAD?AXAfARADTBCAEERI^FPHKJPLVIO^MMRKLONZLJNTLHJL\JTKLPFBHPHHCHDTHRHfHNH\G@GXIVHGHIIHTIIKJPHTEZGhE8FLGXETDCZIE\FPHCPFDERBRB`CTDC?@dCJC`CCAFA@dA`C@`ENCBBLBA?^CPAR@H@CNBCDF?B@VBA@^ARC@AXBVDbCDDBZAEDCdFHECVDCCXGNEDXE^GFPATENECCDDGF\EJHERB\FCD\CCFPERCVCDBRA`EXFLECEAZBZDDCCJDJD^DEBTADAC`CD@ACB?=?>BXBNBZC^DRBCdCL@AEEZGCRB@XECJCN@VAZ@AF@@VBHB^?>`C@@AA?@RAbE?B`AR?X>?RBFAR>??N?>TAXA@X?>ATA@PB@bAAfCABCGDHFZGHIJ<<=\9R:9\97L8Z7775735P2T113R20X/T-b.,0T,/N0F/-R0J,-.H0-,-V-P0,P-*L)Z(*X(('R'\(&R%b%X(%&%'%P'%V%N)'X(\'N'T%%V%%`&&'&F$T$$`#\%R('(%F(P&L&b&&'(`&F'('(P)(`)(^*^+Z()`)J'*)\'Z'(Z'('P)Z)N%((%&'^&'R&('H%b(V$P&(T$f'P%$T'&%$%$$d&%L%$\#"`!h!!\"Z !f X" Z R!Z^`T@HZLH`VRbLddTTVVL^fRX V`Z N X ^ V ^ \ N  R XfTZRRX^^ZJ\ZXf\hVTb`bLNXXJVPPRb^`RH^P\PhXVb`\bRZTPZZPd`RNX\XVVbTLPb\^^TZPX^VX`^X\VXhNPVbd`8TZX`Xbf^NfXXN\dLR^RpdfTV\TZj`^^ZXXX^\RNdJD^X^XVPHR\VTHZdPZZ`XbTb^JZRdXZZFRRXZVNX^`VV\T\`\\TnXTRRX`Xh^PZRbj^VX^Tf`VjP^\F`\Z`P`TP^XXPZN^`HL`@R\R^ZhXV`^lRhDRb`PVL`bTdBdZVRPd`RR^^R\\T^RZTPRLX^NTZVZb\RfTZZVPd^R^ZZTJb\VVRR^ZNbXTLZZhTTL^bfV^ZT`XXRh\P^N@RBP`P`JZXZPbNdT\`H\X`TF^^JZ\HbZ`NRVV^JjRRRRVjVZNR \  V \ \ X b \ H Z d Z R V`RV\ J\XRXRZTT\\VX`XPR\@R\X f!!!#@"  P !V"$#'T)(T+*d+P+/b/..0J0.,//F.,.-Z113L1Z354;V9:\>P>A=d=d>=AJ@@@@V<<=AN?R@P?AXC?RBRBATAZC^C@ZB?V=BZERCPHFTGIIRJILMPN^LTOPJJ`NRLJHFZHG\HGRIVGNEEDJjFZGE^FdGGNGPKFJ\IJVF`IIFHH^GIFDRD\EEVGCEZER@DZDXCECAPEBPECBXB^EZC\EBVHTDPDTChEXBX?V@T@R>\@@ABVABZ>\?Z@B`AAVDVBC`B@G`@LEbB@CNBbCNCA?ABRBACZCANDDGFGIbCC\D`EBBFVFECFREGVCDDBCPFdDfBDZDB\ETD^EVBEZBTE^CBBRC@RABPCfCDDXCNDCVBC\EXCXFC@TChC@@`=X@@\>Z>bCNA@EFATAVARDHZDVBEA@AVA^@ZD@ZBZ@\@?h>b@VAXDVEPA@C@CAVABB^BV@Z@?>B@F@`@^@LA?Z??j@V?BATBA^BH@\DBNCCRBPEZFFTIDVHHDG^GXITFXJXGPJJJXKILJdMTM\KTIKRKVJFIJIHGXFIGHLGIHIGVKVIZJdJJKFJTKhKKLJXKZLVIIHVEIJPKZM\MZLTNJTIJJIjLKLHHJJHGEXFDANGVGRBDXC@D@A@>X==V>=Z>>;:<<;7L988N:;b6X75332L1331\-T-V/0-,-..X.-++R.,T.P/-..,,,))N+)*\+^'F''d'##X%T&'%\'`)T))V(Z(^(J'`&&&&#V$%L&%$%%F%V$Z'&Z%Z(%'&&^((\(>(X)*(R)(X**(+P))d)F*Z(f+'Z(+Z)b&N)&()N(P("X&D%V&&%Z'V'&%Z&(L%&Z&T&D%V'T%N$R&J%&d&"L$j%L#"X#"!!\#!f!Z !X T""\ V NV^`^VZVZTZZb``NPVVXX\J`ffL` T f Z R R ` P Z T X Z J ` X ` VPL\VTN\VLHb^Rh\\TNR^XT^LP`ZPRRLXX^T`PNRTbLZ\^XdZTTbF^ZdTV`NVZfZ^`RbPNZ`V`lVZ\JZRZZbX^dPbXX\^XTZTZP^^VhJ^RX^RbRBdZT^RXP`\^dPZ\RTfXdZ\^^V^N\VXXZJZV\TXV`^NVb\PV`TXP\@dVZVNTbTXVZ\VZTT\NXb^bZ\T^\ZX``TjXbZVJX^TTfLfVZTXRTLXXVPTNl\V^`FdNZ^T^^fVf^LT\N\\ZhdV`J\`ZbNbVXdZ`ZLVh`b^NRX\\T\dZ^fXHV^V^`Vd\PV\\\J^NbXX`TfVTTXXRR^TRZ`^VfRdTP:XVJXV\TTR\XZL^ZJJ`ZXRZZX\RPT\NXZXV`XZhVTPXVLV^T\VLTX ZR^R\ P N h L N FTdJT`  ^VTZXRTNb^L^@NXRP\ZJRTJJ T ! !N!h Z \"R!V R!#&R&((\+L/+N2-..\-.f0.V-Z-./V/X0//1T2\6T6`5J7889\:Z=Z7V68\5\4P422L2V/3\/1d1V2R4356795X8Z8\7865V7V3V2T3Z2.2-V/T.-,,-.^04Z3J3X1V2L0X0R0/T.,*R,Z*(Z)P((Z(T&&V&%Z&(%&F'+F*-+^,+-,X/,^,+R+V+-^0:,`,`,-V++)-L*-N,*\,+/`/-..R/R/^21341V36d4L6b53^32Z6f5L42X35P3V45b3X5`5\;R9d667X675N7^::\<\=V<:\?BV?=?L>RH>Z=?=R;:X?=?LCZ@NA@L@@@XBB>J?ATBXA@:CEVCXEPGRDZGEIZILKLL`HXJTMLbK`KPKLXGTHEHGZIJHFGJFRGVGDEFIIG`JMXGZNfM`IHTK\I^KJTLfO^HFHXF`FECBCbDVBDDBDCX@BCAAZCBVBEZEPGBDDCBAZDTD???BBAZATAR>R?=>`>^=@N@R@C?@RAPBBB@?PCCR@V@DdCEVAbBCCDFTDIJFZHTHXF^IGPBVETCFNE^DDDTCRDTBALDDVEJBCZD`GEFD`DNGZDCCCDNBNBNB?V@EA^CECBCANEADXHTBZGXC^ATE@BCA>=V@V=@BVBCBDCCBDVBXBVC@Ab@>?>??L>?V@b???T?AV@N>?B??@RAAdCRCCCNGXEEF`FGFfEFnHVHGTJFIIJIGNLKMKKPK^HbHIZJRGIJZKLJIXGhIJHHGHLL>LbLXM^KZNNJIPIKXLITIJLTJNH`GFIJKI\KbIPIJNK`JJIbKHXKHbJVFZFGXCD`CDA`EbCAA@L@TB\?\?=^>TNTNTTX^PZ^`^\^X`^jL`JbTZL^NPRZV`\ZPb\Nf\^VNNZZb`bP`ZXZ\bRJXTVRVT^\B`\RXRP^tNZP\Ld`RZ\\RR`bX`^XVT\Z`^VLNPLnT^hPbXZL^P\ZNhLPXVL`HP`dVPHPDRXn`^bjRX^d\RbbV^bLVXXVXJXXTdhTLZh\bJZN\XRRXbRXRRVbRXV^TVlLVbZRXRbX`RTbR`dVrBTlVVh^LVXXRXX^ZXbZ^NNRRZZZB^RdTZJXJNXb`TXFdRLRXL\LrP\J^XP^\^dPFj\RXX^R^RR`ZVTRZXT`VJ``^ZVX^dlXZ\XFd\b^VV\BRlVLf`RT`PXRJ d  ^ R ` N V Z X L N b F^\ lPZ `F\bVXVTPbh\ZVPZX\Tb`TRX V!!T!^ "\L d"bR"T!f!d!!p#V'(\*X)^+`//1L2b/X3/R0Z2`/./.-F-b.X/020d36b8b79Z::<885b:b736Z30V0d/V2V2224b2X7R58J6R:7:66T8V67`6`35V11L/\3b0\.\,^,/\0-0P00^0V140d//`0\0X-R,V)**R,Z,(&d'$%h'%&R(''^')^+,*L+)`-P/`-Z-.Z++,-P+\-`.`+\,R,(,V*+R*d,X,+T*.,V,N///R00Z2Z3b64655412`23Z5\1Z4X40X2T4^445353d646N75F7P9h8T=Z;>=?==X?\=b@@<\;?<>L>?Z?ZA@`CB@B?ZCdEETACVAEZG^DFHK\LPKKPNLKK^JKJGVJfJLGFbEHFHEF\BRGDTJGIVLdJGLLXJFJ^JHPHZGMLGJGGJfFVFGE`FVGABDCXCAbC^BAN@@BZ?fFNCbARCCB`CA^CDAATAAJ@`>^@\?X>PBf>X?=V;^?L>?LB>XACXD^BTB?ZA\?XAZ=B?CDRHCFFECXEChDHD\CVEXGVCHTETDRDDCZF\EGXERFbG\BTCDHBXEDEDCFBZG^EDPE`DFEPCNDVCTAAbDR?NC\FBNA\E?BNB?\ADNBTBALCfCRCh@AX?AAL>X@b@ANABdCJCEC^EBCRABd@V@@N?>@L?P?bAb?>BV?`ACdCf>>>R>Z?PA?@XB>XAP@^@?T?=V=A>R?XA>??\@VAL@Z?\BA^ELBTDbDRFTGGF\JF\FIGfFTKXHZIITKIIHRLXKMTNOXNbKJJJHHH^J\HTMbJ^MdLGID^FTEEGRLTM\KM`KVJLKJRJI^KGJHGdFTILHbHZLIZMNIHGIPHH^LM^JJHGF^ERCZEFG^C^HBZCEXBR?fC@L?ZA\?>BAV9RJ`f\Z\n\\h^bT\^Z`L`P\b`dX\L\\\R\\fV^^XVV^NXV\fVldVXfXZ^XVbZ^ThX^X`bZ^^RlR\TXXV\jXRRVTP^Z`ZRRP\TV\\X6jXRX\ZV^ZZTZ`ZTTLR\`JNTTTNf^^\VVZHhRXTRTb\f`bPVXdVPj\N\L`Z\ZVf^T\b`XRXNjhVL^NhD\JZRXRVR>Z`\ZXTPNLTdL`N^Z\RPPPNZRXddXP`RfXZ`TZb\XZPRPJZ^^LfJLfRdNb^RLZ^DfHRT^`FPLZ^bbXXVTZJ\JTHF^fRLXRZZVR PVLXb^hTHV`JFVB^NTNRR\VDXRVdff\TbP^RLh`\VJbRN^f\ bT V F \ b ` Z \  Z  R `JDX\TVfb`V\HFHPN^\`\dZP^T!Z!V" !"R" P"H"#%'J,X-L,,D.-.d10X2T.Z//.`-/j..1Z.R00^35J978Z=X:;956736P455.1Z1P/b2T34V2R656R55J8V977L6b76`6V3`84P2^1P/J.b-N,\,Z+-P/../1Z00220.//-X.T+X)>+J,(X((&('N('R&&f&()P),-V,*R+X,Z.P-V,Z+P/,-,/b--+*V*(L-,`/Z-R+,V.N,,V,Z-P-.^.1/N00N222`41X2N3h1T31R3231^1/2243h33V246`87P669D:b;VR;\A=?^>?`=;V<@=H<@J;>\AN?P??N@^?@RCC@D?REJC\AB@Z?X@R=>>?Z?X@=V>^==@?RATAF>6>R>f>RBZ??X@@@A`@X@@H?X@?V?>V=b=Z?=T?T@NA\@T?VA?XANAPE`C\DEEEDbHRHGLLI^LNJJK^H`HLIMKPLLVM^MKNKKNGMG\HHNOHJGRGDG\GFbFbHPJJLLKJL\LIIJ^HRGIRKbKGbJJZEJFHKTK\HbHBKRGI`LKHGVHVE\ADBD`CC^CZCLEhDDTCX@X?R@C>R?AH>`??V;;\:9TX<;b<89P;T>V=;:;;X@Z>\BfBBA?ADVFVERIPHZKHVKfJ\JZNLPMMKGTKGKMHZHHGHED\FZD\ETDEClDJH\JJJFGDF`JRF>JbHnJXKHRKXIRFPFdJJdECDDPD?XA^@?@hBDA=?^BB@BBZGPDD^B>RA\BClALA\DVBR@@B@TBb?L>T?V@`;>>A\=L>@>`A?X@@@@dBERGDDA\BBVDBVCZABBDZEXCREBDCDBDH`GEBFFfFETDE\HFNIGLJ\EDGDCTGNDTCbDJAFDBAHFBTBXCB`BRCVB^BABRCNDNC@@@X@TAH??P??=VBAABTDA?AC?D@@X>=b?=?>Z?`>L>R?N>Z<>?PA?`=EARBb@LA>N?`?V?\ABX=@J@JAXCPB@T?PA=X@@?VAAbCCDG^DFDTFFGEETIJ^JTNTJKRJNLPLK^JVMXNKTJHVHJZHVIHIJKG^IVDE`FEFEGJJIKKGHHGHLILGLNG\GFGGEKFVIFJGF`JXJI`HRHNFRE\F@EACCBBD@CAPBXAR?T>?J?>H>Z>d=<<;N<;H=9Z99d:876`4Z4T22X45Z2.0`0/,\./-/\--+R.-F-+R--f.X-\-\+*+X+R+X*.*N*)Z)(P('*T(()''`&)&$X&P&&%V'b%X'$$$P$H'J&%V&$^%&&&H'R&'N'&(R()@)(''X(T&(L*V(`*(^)+*+d(*L,D)')%H&X(&(%J%T&'L&(`'`$%X&b&%V%'Z(V)'Z)'&`&&^(%^&!"#D$^#P#L"!\ "\#""X"R XT`ZZXbX^X`jZVT^PdXRXFNTX^R`D h Z`ZX L X P T Z ^ V R hP F`\N`XXL^R\V`^bL`ZRT^`RPVfL\Z@f\dD`Xb@ZJ`^RZNfTRPTXbLdXJ\dTZRbVTLhTb^XN\Zdhd^`HZR^VhL`ZpbPVfj^VXN\XlPZdRT^fZjNfZ^`ZXXT\XNV`VTZX^VVZPZN`ZD\V`ZjJ\JTX\\VZ^VTPVR``ZRPbdXZdX^fPVXhVNZX`TZZPVT^XHVTX`N^XXZjRTVHXLT\\lbZP^PZ\^^V\VbVh\TVf\TbNXNjLLjf\Zd^V`\^`ZZZZX`VPlNFT^Z`R`P^\PdVVVZT^XNH`PPdPPHNdTPZPV\RdVPXN^RVZJXfZPjRTXTTjV`ZR\VTFT\VTV`RT^D`XXRPRNDNLNXDP`NZXP\XH\`^\P`TV\TZXb^^lTTLbJT^Vd`VVLP`VX\ZLZ V X J T P V N d XBjPX^NHbNL@T`XDXRNPX Z H !\ ! J" \%P''*X)V,+N-P-V/R/0/V0/\.\0/J0V.P/N,T0.P04H2X3L8L7798X98855N6R85Z5P10Z0P-1/d01N22Z5476F6\8V9V5V6\4Z64R4`3`2\1Z1.V.N.,P+,+.Z.0J-L103`21.1/X.-,Z0,P+N*\'X('Z(\'V)b(\'(%)'(T+*V**R--,X+d.0.+Z+,+Z/P-L-R/V.d-,N/\-^-.,.*,`,+T-,V-.X+-j10X2B20.\0^0d1^10/\20P000.\2\1f21N2/T45655T6R5X:N7b;V9R;X;N>>>?;;d<8X9\:R;8:=9V;>N;=>b>VB@XA>XA@BBACCZGXIZJHVGJHHTJKPKVNI^IXJKjLK^JHERFXECBZDDPBFDbCZHGRKF^F`GXDfFGG^HI\GGHHLHFFTEDFDETEPB?Z?AV?T@BF=?NAXCCD@TAC\AANBVB@HAAbETECCAETADBXBDHCFBXCEFVEdH\FPFFTGjIFPJ^GCDG^DBFCXGDCBFC@>A@@PA@HC@\BCC`B@A?AHBV?VBDAbC?DBVD>BPB`AA>@\@?AR>;R<<`=?=R?Z?>?=f>>AT>>@Z?Z=@A?NCAAX@hB\=`ABZ??X>V@<^@P@JB@^@T>>D`?A\BDXDCZC\FDTDEGFIZJfIXLIJJIJTHHJVKJRKL\IG^JdKIG\IFRH`GFFTEFXHEVDHGHKZKJGMGGHJVJMKZJJJEHFGFHTHGHZKGNGI2GVBECEHBX?TBAbAVCHDbA\B\AA@`?A@@jA??>P==9R;9\=`968R7P9J86H65^22211V/X0-d0,.P/B/n-.0R/-/X-X/X--,,/)**+T,*Z+)V))\)(L*J((*>(X'T'N)\(&(b'b&&(^'&Z%%%$(V(&X%%T%R&^'^('&)P'Z'N$V'^')R)-T('X&'R,L(j)*f-*V*Z*V+())^)('\)T'X(&V)(%Z%$(T&('V'V'L$j)&'(\''&$%P$&X'($P$T$X$X##$$"R"L!!#"V!$X!T!X\ZXTZZR\PXNX^DLRXXTNVXZRN`Z ` T V \ X X V T Z Z VhNDPHZZVZf@Z^TdZRPl`Rh`RdPZNR^XZNRTXTXLdNPXN^PP`\DLhf\`XRbXLTX\\HRZ^VRZd\LbdRb^Z^ZZX\V`Xd\R^`XV^XPTfVT`V\T\TZRJjNJ\\XVV```TVTV^d\RJlD\\\T^hVZVZN``LlTP``\PX\^F^NTZR^VX^d4X\V^TX`fVRb`TZX`Xb^<JZZZPh\^XRTf^^d\V\VdVZPVbhR`PVhVVTfR\TXL`V\^PR^Z\`XV`fZRbhXXb@^bJ<dZZV^XhTXTVX``\^VVZ`\NTPRVd\`^B\fLbR`TXVVRBNfZX\PHZZb\dXnbV^^Zd^^P`\\`TTNTVZXDX\\\R`dR`Vn^Z^RbLTJXNTlXT^TXfZ`VXfJHHR`dV\VZNNZ T b j V Z \ b T `N \jdbTZ\VbX^d\NR^P^NNZR` R N P "R f Z T!T"$#V&X)d)H-f-.N0/.j00N01.1/1`-^.,R/R/X.X/X3b27H9`9997f8T:XT=b;X999V:RP:X89:J::l=V>@?ZBAZ@CEBHDZIfGGFVFKHPJ^KIPIZLI`JZJHXLPHLKOXJbHTEC`GRENENGBFTEbEVHTHLKHHHJEFGFXIIZIIHERC^CNA\EEVFVHED@T@>XAJBXAJA\DBXBAABVA`EC^BCTAA@AdDANCAP@A@L@AT@?<\?AXC>?`;T=;=;^>\@T>>N@?>V?J?Z?F@??VA@ZATD@VCEVBBCCJCEV?HC?DEFdCXC\GCBEHdEZFG`EEERFE^DCNC^GFBTC^DZBRBdB@B?`AR>AV@XAT@B@X@hCRA`AC>V@^AACA?VAPB\C>\?NAfA@@N?@T??d==;X;=@@`@\=V?H>?=?<=><=<>^@@AN@d@><>b<,=V>=X>L?A`@A?@\@T>>=?R?@\?==NVVj^\X|ZZJ\X\RL\dhTX<HTVhTbH`JfPL \ D T Z ` R P R\ ZZZ^TRLfH\\b^J^\bXV\ZX\^LJ!JL !L Z!R"\ !P h"!!%\&&L(^,P0Z/,V.d21/N00-/T0P.b,P/X.L-,+./L245j9T;X98\::N;976N640^52^2//N./01N2434Z7\5878V9\7R7V44Z7Z43R2-/d--L-X+,b-X,..1Z20/2.J/.V0R0--X++N*-R*()'R&R'd&^'&F'X'^+(R)R*V.**,R-+f-+,-J.J..\-`+V.-/Z0^0/,`/-.X-,V,R.-,X-.-,.Z.L-0.T//,.P/^0J/Z/N10N201`24V41R20L/23676R98979`:V;:;P989V<;:R9Z;T9T:7P9:P:9V;R==?J==>X@>XARABCECC\GPGZHTMVMTI\JGGIJZGJGINKJTIRIFEGEPDLFFEZIdJTKI^GJKJIZGG`FTGDFXINIEfGDDZF`GCEDCDVE\F\EVClAZCB>f@TCX@XB@@A@^@CBABA@B\@L?ADTABCB?L@R@X?>Z>@Ab?T?>=@=;J<;Z?V?@H?Z?>??@AA=>Z>?DHA\AET?\CAVB@BJBCFAVCECZBACEDBPFZIFZGFbHEFEFDGBTEVEDNEVDZ>A@r>V>V>T?R=>TT@V@ABDCPBTAP?dB>ZA?>TAAX>R=@R>L?P=?=NB<>V>\=b?V>BN?N=XAJ=X@>Z?@A>T>bBZ@@=VBH>T>T@AC@@=T?A>?CRADVBREHFCGGFTIMILHZMJTKIJH\KL\IGRKHRKLMIDEHXKJXI^KFK`INGFGFJEZKE^JXE^ENGEGHLKMdKdHFMFE^EBBRFLG^DEHRGnELDFJD`E^GCbA@XBCVDRC@XBVAAR>?Z?\@B==:Z>ld?\>ZB@N@`AVCFECXDXCbELEHIKI^HD`EHEDJGIJRK^GXG^IIRIKEDFGVFXGVHNHITJHVJXF^GFDCHFDHHENFNFDHTF`EVDF^EETFBJGTGND@\AADDAXBC^DXC?ABAZBC@AB\BNBCAAHA?^ALB@@@f>??\@>LC??d?T?=<>@AL@?>P@TAA^AA@?^?T?AVBJBA@B?^C?N>TBX@LA\A`ABDDDRDTFdI\FPGETE\FdHXEEDDTCDJBAR?XDJAAT@???;=?===V<=>J?B=@?CV?=R?^?AT?bC@?`BP?C\AP?`?d;?<;<;J;=D=>>R>RC@fA>j?;R?=b;RC@>V>>>\@>=R;=`=N<@@>CfDA\@?XBB`ADVA\BBCDDDVGGXGNITGNH\GKVIVHHLHJKH\GJ^KRLVL^JbKRHHBGLHXGVGKZGIIGFdJHF\HHGZGGGDGPGHFIEbJNDFDLDZEDGHD^HDDDAVCXALBCAAbEA`BAT@PA@`@?;^<f@<:\=6Z4H9d4P55L3V3V20b.Z0-T/.P0\/T/Z/.-T/R--R,V/,-+R++*+h+\,*N)Z)T-(\'`(')('`()Z)X)\*'^'(\)'\('T(%'^&V('V'(&&(Z%%&b&'&V%Z'%V%&(R((T(P))\(('*N(`*N+)(+X++P)T)R((R)L))&'V(T&($Z(Z)&F)%'(d%^*T&R%'h''%f&R%$L(R%\$X%R&V&^$#\##!"j"T$"Z Z&! RTVR`\`VVTR^\LT`ZXNhXbRXXPRT\TX\ ` ^L J ^ V Z \ H P ^ N b V Z  ^\TRNHTXVHXVP^Xb\TPXPZLPRVXfdJ\\JR`VZZVP^bXVJVRHj\Ph`HTXJfVV^XX`d`ZLdRbXbN^X^bfTh^T^J\RdXX`\^bR`dL`^ZXdRfZV^Pb\VTVbV`XZZHZTfTPPDhXRV^fVb^bLVXhVXRVZPdVZ^`Fj^ffLX^PV`PTTVdV^dPVfVRNZHZX^@N\XXX^``N`XfVRjVPNZVVXf^fPLPLXZTZ^NXTHTTRLjX^TP`TnZ\X@^X^V^\XTR\d\XVfXRdPZZTTZ^bX\TTLZXZN^JnFZ^ZTZZb\PRD`hTXV`\XXHRPV^ZbRXbP\dVP\\NRRVLZVbdF\^ZHTNPbJZZ\TZTZ\`ZTRZ`bFRZ\f\HLXP\XJ^TLTHX\PVJ\V\bL^Z ^Z  Z h L X R D ^ hX \P N `XdbdDV\bXTZN^ZTdH\ L" !N#V"V Z""R"X$^ !#&\$))),/J00b/h/-/N/./.R,-`,,R.,f-R23F36486V:\::;:J:855X4V2210..b.R.\3^1T02h44j354b4L4Z6N4V5`2b44h30-//\.,+L*T+L-Z--,T0^1R1/0/0L0^00/H-R-P/\-++''R')&P''V&))()*d*+R))*X+.,,+..R/1V0+B-Z1f0\0V,-,-,V,,-\--+,*V-H-^,+P/--/R0X.`.0..\.-P0/1P3X363P2J33\3\3V25B4\6T7V9^9N7T8T7X896H8^:8:R::9V;78d7J9P8=<>ZL=;=?>`A?P?`AXDHGHCTDFVFC^GGGFCXGJZIPHHJHFI\GXGGZJHJTEFTFXHJLH^IEKGVIEZGEPERGbGfJPFEFFPDdKDF\HENGXFFEDDFVDHDbEPEFCBBDTBbD\CC@C@A\>Z@AZFTDFAARCPEXCTATD\BPB@NA<>?h>Z>AR@=DN>?@\CBXDBX@=PBX@Z@P@\@ARA@VBFBC^DXHEFGTGGXGG^F^DDFbEELCCPA^AAZ@?RA?T?X?:`?R=@F@;>J?Z?=@^>?TAT>>@L>>@=B<@VCNA@\B>>RA>L>Z<;;=:<=@VAT?NAN@P@=R?>?T>?<`?XX?R@@XCD\C?VCPDbCRDZCNDRBDTADBTDVGZHTIGHGRKHFMIHHXIINKIZKRJFIHHEPJHFLGNFHPFPHLHZOJHRHhHRJJFRM\H^GLGEEFRGEITGdGGDGDVDZEDZGCDEB@BRAB@VABPCD`B?@Z@LAZA?T@\>>X@<><>?V=H;;>=9:^:9Z69T9X57J5R7^7J7D3J4022V/T/1X0V0H1\1/^01-.-.//P,N.X+^+^,)*X)\,,X+)X)^)R)(')(X(X)*(((*)))')X')\)*'*))R(N&P(%&&'%'L%b%&`(%)Z)P(Z,(b+V'H*''(\)N*Z***`,P)((+'P''^(R'f)T'Z'&L%T'T&'b'Z))T''$N'R(%T''$'\&&$\&`$#%D%#$!P#"X"X"#^"& ^ Z!TPLPT`ZRf\JXbRZVX\RXT`bdHfTRVX  Z J N J T^ Z \HRZ`VXRL\ZRTj^ZbTbT`XPf\`TX\T^NXVVXR\VRZ^`dfXR\^XbR^V\V^^\T^V\\^PVX\\\HTd\LJ^TVT^XBVFTVXXTZVn\`^PTVX`VFXdZjDZR\ZTbX^4bVV\XZHNRfNThLh^hVbZVN\VfZHdT^PRXV\VV\^Tb^P^T\bVTLXX`ZT^R^JdVVdbRLZRX^L\bR\R`\P`Z\P^ZZRVJXTXV4RVTdZbZRd\Z`\bRP^L^Vb\HVL\VFXZ\XTF`RhRdnNThLbVRbZh\ZXL\RZHTZZX\\Nh^PRN\ZbJj^dR\ZZZZV\PZZXX\NZVVJPbPT^ZXXRTdF^VZTXb^RJL^VRVVPZPVXZN\ZThfPXPXXVXLdX^XXP^NT\`hZfVXTVHXHbbVZ\^ZR\\  Z V T R L N l R Z ^ Z V X V N X Ffjdh\XH`TdFd\bZZ "d! !"`" P f# l!V$R!!N#h$%X(+*T+H0h0-J,,/0\/X///-,++Z-+/T1024\5b97\9T8X:8P7b9h85X6L302h0/.//L2T1`00101T314X3R3\2R5J5433P1^0N3P2`/+,.L*+++-T..Z11/X4-h/1/.b.-*-,P,L,+V*''&V'Z*^&^**B+Z,)((`,P*^,+,V/+.Z,,^-0/.V.b/\--Z/X0,+X*n+R)\-V,*X,d,+X,,H.,)\,-,+,,`,Z0---X,T.\1R2V1`4^4\3102P242\54T8T6`55R5Z587`98V78V8:X5b<7:966=T:<=d>=@@>P@@BjCBZDVDGjGVGfFPDCXIFZGD`EFFEZEIGGGGHXG\KNG\FHG^JRFE?`?@TA`BZBX?b?A@B?TG\C?B@AV?X?P>==LBT@^CXDARE`A@V@XB>\@HB?@BTCV@JDD\HXJG^JGPFEEEDNECPCdCP@LB=P?ZAXAX>>V@<=X<>V?`==`BBNCL@XARB>AlAL?^>RB?AZARCLBVBC^?PA=?==<;`>>`ADAXC@?@=T>T;X@L@@RAVA@X?NAV@?@=?>>V>Z>>R@?@AENCVACJBECRA^@T@CHDRE\EFDELJXJIHI\I\I`IJKdIIZJPJVKTFPK\JFXFLGZFbIHGHGNG^HFJ`IZG^GJNMfJXHHHGFdHGJG>GVFCGXD^DRDE?EAERCBXDC>`>@AP@ADAZ@A^?^@=P?=>VB;>@?>^;;=^;`;Z654465^862Z6T44X100Z/Z-0X01./.V-R,D-.V.X.,+**J+**X-((^*()N((R(%())`)*\*^+)*f*)T(F((X)'*+()V*T(X('d*'T'\'T(R'''\%T&&V)))L&(R(b((b)J'*)*),''*R)f(T)^+(J'%&&R(V)*'&Z)`)^)Z&\'X')Z&R&^(T'b)f%%d&%Z($%%V$^$R%V#"X""!#X"T"b!N"b!\!N Z!`Z"V XHVXLZPV`BZTdLVD\N\\ZTVPRRX X f R V Z ` T Z ` H T f X \ R TR^ RP\`L\bPT\R\PR\Z^TdXV\RTXd\\`Zh`XX`VVL\f^\XZXL\\TPN`XHbX`RRXZbbVbZdfPZdXTbT^`VP^ddTR^j\\ZXTX`b`XbX`VVhRl`P``P^VV^Tj\HZbVfNdPV\V\V`b\XhZT<bh`b`dNdZZPVRhRPR\TN`^NRPV`F&LLTTb.tHfb`XXjVVRld`Tf`.VRf^P`VZZXXL`NNXLR\RZ\X\RbVTbZXTbTdZfbnX\NVXX`XL\^RZVXRdVJjbB`R`RjRHPVPb^Z\TbZVZV^V^XP\V\TbRXNTRTVRfV\\PRVXN^TTZVBN\hT\PVdb\`TVZH^RTZP^XVXZl^TLTTbZZVBD`VFZVPZTTTJP^X^dXRZZRNd X H H ` R h d \ D ^ R X Z XVNXTTTVLL\RRVRHVRVX`"V R!TP""N#VN! B! #T!P"H$$'P(V),+.H.0.2//N2P/X/.1,*X-\.//`1D132\48H69V:D7;:\9^6F8V4\1d30.V.-F0Z..V11L1f1114R114\5F35`2T33^2^20N2/Z.-d-P,X-,,b/N0Z.0T/.d/T1Z/0//V/R./^0.*^*P)^)N(T(Z'&f*`'X(T*+X+**)Z*D***--+,-R,0b/.0T.L.-0,L.Z/,^)L**V,Z*T+X+X,*,))X+,+,,+D/`...^./R..X.L002F2b1^201`433J3^4V4567\66675:67X3758J:Rj?V@NC?L@BAPACBXAB@@^?@=>PABVCCCXAB??A^?AV@@AJ@B^DVBCZGTHGdHXGEVFPGBZEF\DHDTA?ZC@ATBJ@=`?<=T<@V>T@?>@XABTB?\A\?\@P>DPATALAAD`D@6AbBA==>\AZ@?RA\DTBV=X;P@N?BP@bT?<@LA?ZBANAAV@BVEDCJGCAVECHDE4CXDFDHFHXJZM`LIK\IGGGGJHHI\GIGTGGGVGRJLIJXGETGHI^GJJFPJTKJJH\FZLHDXGEGNGCFB`D@VE`BCfBBBAVAbC?A`CT@Z?`>XBV@b=X=BR>>=>@X?^@X=V@X>>X>^<;`=R;:<998J95X6\83V6224532Z3F3\31\3...b0f/T/J10X0//-.X-*P+)(L++V+P(*h+(`*)V)'Z*^**)V,))^*+*)`)^)N)`)((((+&('P)'''Z)V'%)%V&$X'V&^%h(T)&X)&P*V)'^,^)L*P+V)))(J,d*^+P+()^(&'Z(T'T%'\&'''(T(^(''V&&\&(b&d(`%H%&&$'%$#R##&#`%#\!"$V"b"^!"H"N "VRPXbPT\\^L`XPFD`jZTHdZZNR NdnT \ X X J L V ` Z T ` TdZ PDTb\X\^RZJRN\hZ\NXNbTRTN\XT\NdL`L\\V^`NT\ZPNFTZLL^RZVD\HRZZVV\`VJ\Xb\XZPPRZb\V`XLRV^f^fFZL\\D\R\Zb`L\\NVDV\Xf`@RbVT\XXN\XhVbTTTdPbLNZVLbN``TN^dd`XHTbZRJNj\^RPXfLTbRTRTN`PR:TDXZPPfVlhZ`\``\rZbZj\VVT`XXd\`lTRVV`df``XjX`^`\X^XVf^VBJXbPX\V\XR^hrXbZXV\T`VZVVZVZTV^ZLRPdV^XX\^V\R\^TN\LZTTPV\hD^RfZZFNHP^RR\Tb\PR`T\dXHHVDhbhXVRTPZf\PDTT\b^^XVVJZfZXP`Xbbf^NLd`VVd^\^^ZL^LXN\H^XRLRZTV^bVZZVT`XR \J P P b \ T N ^ R X V bh  T \ VV `NLV\PJ\RhLXXHV^V! H" `" H!NV b "#Z%J'%'^+V,N-0T/V//Z/0X/\/J0,1/,/+,P/2^0V/0j1378R88888J7T5N6T322T0T1J.V.L/J10P0Z/3Z32\43V433L3R5Z44^5V2`1-/2T.f0b--**-.X0-h-\/,R//\./R0X.X1///-X.J-Z-`+%&J&&T'`(&P)Z*)T+f*Z+)L*\+)h+X.L-T+H,P-R-b-j,Z.V..^---.-J-J,+(b)N,(+Z*Z*+P)\+*J+,X++-N-..`/\0H2R/b/J//f0/^122H3H2B45`3R2X5T4v443J5T8X7^666d6T7V6Z77T8V:R9\::X;\:V9R89:98;;Z=?;b?N=?J=T==D@T>V@fA\@^BJFGPC\DVEFZH^HHDHFFFLGFDREVGH\GJHJGbGXIGFNEDZCNC^C^CC\CCBZBZBZBdBXBCEXHDNFCREbDEDF\EEXDXHFELC`DLCDdFNGED^GBJA^CXBCDCRBBDARDVCT@BXCREPAjAV>P>=J>?@V>BT@V@@@@@@B@HARBA@B@P?@V>CP@RBABVBZ>?L?`?N?@ACCVECVDFJGHI\EFFNGEVETDBEAEVBBF@?@R>=L?>J<:;`=V?>BBA@Z@`?R?A@JCRB?LCB>@?NAAA@?J@T@`>>><=?RA??RBXC?L?d?@>?>Z@X?b?H?Z?R@`?P?>X@T@@=L?b=@B@XAN?TBZBZ@PBXCV?CXDAEBRDDXEBF`HEF\FXJ^JJZLJNVIVJHFKPHJXJRGLHRHFFEETGLIfKPHLbGIVGPGhFGJ^KRKMIIFDGD:FEEZCCRCBCXCAA@JATBT?=b@>?@??Z>`@??>R>T?`@?T?>T@\?\@>T<:;=T;;9\;9:X:H88X9V5\9X5R6T42b3H4^1V3T2T6Z41`/X/X0b-/X/..,b,P,^-,-^,,^+R)L,-)X*Z*+*f(X*X),V)R*X+))**N*+)V*V(+++)n(&*)('*N)\(((V)L)P'&&%#&N$&\'()('N(Z)b))J*X+)\,(<)(V)F)X)('(\'P'N)(f)*p(#(''`'(%`&%T%%%T()b(R&T&#J%&%R%$^$T$V#^#`%#"Z#!P""!X! V" dX LVLhTbTTLLX`PN`Tb^XR^`XVj\N@T T T ^ Z @ V Z T ^ \ T ^ fXZ `fNLVX`^Vb^LhT`TPXbndPfRZ^\Rb^bXB\\TfZZVbZLVHZZLV8VVX`P\ZThbT^VR^^ZZX^^b^RbTXLXbXXdNZXbNbNV`XZ^dbhZVhVb^FLTnX`^bRbX\hXPZTRbTNThJRdTfR^bd^\\bZ^^JXVR\VXP`^\XbbTTLH^\\ZTDd\VTTTT^\L\`R^j^Z\X\NTdZ\^jJ^P^.\ZTVTXXHjbXX\PdJPLDbV^LZVZTVZZX^LXV\NP\P^HbN`TTPXZ`^XRRJ\^PR^\fJXPVL`XBd`dHP^XPhHR\T`X`XX^^PX\\^NLD^TRHZPV`ZVTXNTX\XDRZXTRHPXbP^LZXTLPh`NXJP\XhdVRTNdTZJTRNR^DdVTd^TNVR\PL^ZLNLPJX^NPPLVPN RPHV Z ^ R ` \ N L F J T JFLRRTJJ`RXVNTR ^ ! \"^#"V!T" NV R !#H'%%*V)Z,+`-@0`121/./...T+,\**Z/,D0R1122^6P67R8^89`:T9P9`555L4X0`2P0,.<0b00R/0^122H5\5N12P4V4N64P6P33R40/0-T,++',T-Z-/L-,N/.0\1R0B102N2V2/..+d+)T((P'Z)T('H('')(^+*((*H)B+^*P)X*4*`.D+,-L,+R/,T.\,+,P-+J((P')(*T*,*L*X*))+b+.P,*-R/X.T0\/0J02L12^2R2`1T3T4R4Z2P6Z3P2`4L355f5P6V777P676X7R6Z98F7T9X;V9T;^:8:Z:;V9\<>T9<=:=Z=V>?RAA@ARCGbGDDDHFHGXGXGHGIEEEXINJIINL\KHG`HHFFD`FDFVFDNABRF`DCNCL?d>VC^CCHCC^DBB\CEFJBVHCEELHRDVDENHCCDVAPCRE\AC?VB???BNC`ECE\CJAAXDDRBNAfB?A>A>ZC@TEB@TALCAXDAB?ZC?R@AANE`Cf?=AP>N=H<;LL=d?AX?T?>\?R@@TAA@@VAAAB>bC?XB\BJ>T?J?L@R?;T<?d@>=?`?@@@V@T?Z@@b>N??bAhA`B=V>X?N?BBBbFZB@TCDABREDCVCCD\EEE@ZEbDXFZHGNKZHJVGGGRKLGHGHVHIFZFETFEPHVFIJHVGGZJHNGhINCEFGH^JKVHHK\ETGCbDDE\FBdHZCAXEN@>JAZ??\=XA`@<;=TB\@@@X@>?>B>@^=>??X?>^?N>>P=^?=\;\:;P97R:797557L277J20b201R1^33Z5F310X0\.L.X.-D.\0.X.,d,+++V*X*X+\*^+\-V+*\(N(V*`'()`+*)'*^*H*+R)V)+)T,V*b+(^(b)b))\(Z')J*^('@''b*X'%Z%X&T&X&P(Z)l(`&&R(T)*^++T+h(Z++'),Z.+)P*(Z(T('X'(N%'T&T$%'Z(T+N'`'&&f%J%$&')f%T&'L%&R'%$#^"Z$"R#"V! P ^$ ## Xf!Nh`XZ\`h\ZXTTNVdPZVPVFhBLRRZT` P V L N \ P B L  RXVRdRBXVTZXJRHH>ZV`VdVLZX^\`^TVLdNXdT`ZZXR\F\hXPb`X@`V\RR\dX\TbVZJ\TX\^RTdNVXLRXNXVbdZRV\DLd\^Z\dPRZZX^VZfZJZJ\hLZ\`dXb\`NP\XNZbT`bjZZdP\V^^XLjVNV^VR^\RNZb\dTT^\\TnPVZLVTZld\\Zb\^t^^hd`fZVL``PbXbplTXRTbfZVZ^ZT^b^f`\VJ^TfTbR`R\ZJf\d^XJXZjLb`\b`T`RVZPJPXd`bRHNPPlR\PdZVPZZVXTT^T^L``V\ZPP`ZRdZfVTXdVVVNX^^XZ\ZZXXVXlZZZ`ZRbRJbVhX`\ZR`TV\d``Z`NPHXNPVTH\d\\dhNR`Xb`j\RTZRTX^bV\^R\ R^Z Z Z P Z V Z T d B \ d \H ZR j X^LdTP`TZNXXXN!V"!#j"Z!! V!T T" \"$D%*)++*-`/T00.1J0.--0P,*.j+-X/^.d//3^1J6665D:b778P64N4^1R4\0N.d1\,P/P,.0B1-\/P1V1b022\45P455T43\40/.^/-\,+R.X.`+`,^..Z.R/^0N/2//^/V00X22/2`-X-,()'()('X)&R*\)(*\+(H((L+h)V+'),,,T-^-)T/,8.*J.+V+\*+)(**`((@*R,X*)),F+^,b,\.@,,0T1.f12J/X.P/`0V03V/1V23Z22H22b2P2Z42245685^67F98P7^9Z69Z7\::X:999P::L;:\:;;\;T<9R9`<9<<:R>Z?P=VB8?\>dATC@DANFfF`EE^LFGZHHTIHFXIPIbJXF`HVI^KdJIKHDRFREXDEDB?b?ATCZABRB?C>@VBATBBFCTG^FNFVHdGDGRHHCEDCPB@^CLBAA@R?AX@T@`@BEDVCFDdETCDPDC\CCCBTAXDRABbCLAB\BEVCJCNBAJBJAR>JDTBFDbBX@@R>X?R?@?BD@BBVAHADCCCXCbFBTHD^F^F\EVDbGNFCZFRCLCXEPACAT@BR?@>?X?<>=@\@L?BA@@D?b?L???Z?N@?HAV@?TBAN>ZB<?>A>X@XCP@\@A?@Z@B@b@?Z@?T>Z?dBAV>?L?=P=@?Z@=?@\EjC\BCAAZBRABXGEGJC`A`DTBDJDGX@>BV>d<X>=V@T>>?>>f@>=d>T=Z9988H7L865Z754h656\6P4`4X21P1302P32/1/T.,--H-J.J..+.H.Z--,V*+*+d.,+)&(((Z+V*'**(((N*)T)D+Z*N*T*('(N)d))'`&)J(R)J(R'J(*'T(R&'V''T'()P(%'^+(J)+)+*&)Z)*+V+`++T((R(*)'*)%&T&R'f)b''&D'`'%`'$&(X%P$^($$`($$R&Z$V#Z#^$b"!""!R"X \!P"d!"\#X! ZZRV\NJZJJPRXZbfd^NHVbRJ`XNV X ^ NTZ T V d b P d X X R X Z J \ D^ZRPfZHXVZZXTZd^\JNNNT`PVXTXd`RP\`TdZZ`TZ^R`bfdT^fZDV\XT\N`fXRZP^\b\^>dN^T^PdP```V\ZVf^JfVTZ\VZV`VjZPPT\VXP`T`TLPJZZXd<^TXL`\Pj`Xh`bnXL\PR^^^dX`b\V^P\LTZXhT`TPT\X`TR`TZVZL\h\ZdXFZ`d``RNXbbVX`P^XX\\``f^LTPdVRdZXNPPZVZ\h`\^\bPRZ\`hT^>\RVL\X\N^PTRPXXRbTRZlVHZV^\bTb\NRLPVR^PXLdRPfNPL`^`PXZJ^V\X\PZHLJXbPBP`\VHPH`TDV^XN`\VP>^`X\RXbT\VVNXP^Z`HbZ\TlVR\RTXHTZ`PbbHLXVTVHd\RdVZPTZNTDLNTZL\\\V^^JTJXZX\V^Vh\^VX^<ZHb\ Z ^  J V b J \ X R B\ ZL ZL \ `LLXVXTNZZPTNHb !J!\!$"J#"R#V#V#R! "$*R)T()T+*+P-0-00//Z2V,X+X+P,-*P.b0D-V0-N0104\5\8H99T7N77\5P4X6N1R/N1.,-.,--1L/.N/R//.0^5T35\3N3422P/Z/0,T,R++-\,V...f.R.--P00.^/b.0N02R0P/-R,`..`+X((+R)J*Z((*))R())^*T)(P+(+V)*+d+*V+-,,+)^,**Z,b,^+*)(+'''(N+N*X*,*-P1+`-/Z.`/.R0^0X2Z/031Z2X43V4X41Z3^24R46L2J343V7T46`544P7P7:\98X6;=8J;;>ZBXBATDTCZADdGDHZEXF\DCREHDTCBBBZDXEVC^CEJCANEZFGCERA\A?A`BZEAAJCbANAA@@@?`AAXAVADACDBRE^B\GFXCZFXEEBCBBBXDBRE@@RBN>X@JA=@\>F?N>@==>Z>=?N@^CAP?FA?BAB?bCABbAX@ZB`A@@T@>d?=L>>ZV@=TBG\B`BTEBBA?bDCDCHVDB^F\GdCPDRBZFFZGEEDHGKJEGRHGbHJRIXGDGFdEEZFBREbC^CPGZGXGGRFHXEXEEDfGJFCTCGBGRCHCRFVFEFRGA`A\><`>??H=>=:X<<`??`?B>N?N><=P>?;=?\?T;J;b;J8X76\64X5T4473T644R4Z2010F20/3^1D00.@.-,N,.X/+\/-V,,-+-**d*,-)V)b*R+)((*N)'P*d*V)*F)`+P)+V*)*'T)*>*P)T*T)'\)T))+)V((V&&\(Z&X)D((T'(N('&N('&\)l*R+(D)**R++R+)P++\*`*V*(V+P'N'&P'`(V)''L)'V(P&&N&&X%d$N'V$%\&Z%%X&J'%#""`#<$P!"X%!V!" """D"jfHZfTLXLTN`^X\hTZfXZP`TRdXRhLTV R L \ P @ \ V h \ X h L ^Z N^TPXVNZXRRThd\VN^XXZZVXR\HVTjbXXT\NZ^NTV\\XR\`NTfPZZTVZhZhTRHdTZX`fNT^XV`H^LP`T^RjZTNTZP^^X`Pd\^RJVT^b\PNPX^\T\VVR NZZ`RVRbXddJ\``^XVL\^\PdJRb\\TTNbNZbRVdZPTb\^dTH^X`P^bVZJ^TPTFVV\RJ`V\V\Z\jT\`NV^VdPjj^BjVlXbNjVbRVb`T\X`XXZ^PPVbT\\d^\Rb\P\^\Zdb``R\bTTZZbdLTZTZT\PZbDXPNXRRdbPT``^T\Z\d`ZL`XLXdVdbXR`ZR^ZZl\Z^THVX\BJj`ZZ>bbP^fRdTV\XTXXdP\T^JZ`b\dHVTDNPXZTTVTZ`XZR^\ZXR^\RZd\\NJLP ZfNT T R Z ^ N P ^ N V ^ X N R jL ^ N` ddZTR^TXJZX\FZJnN^d^VT !^"V#"d"N#X#f#!# TP"X"!T$#%X'''^+P+X,-`--^4V3/V-\2,`-Z,+F.++Z-.21T3T3T3b6H9\6F6R86P7d7h5N443^0^/1,/T/^0T0.//V0D//.V11P2X5221Z2F41.-N-V.^,L,T+,`,Z-h-F.,b0X.\/X../.R./\/010-+b/`-N-^*X**L*(`)T**+L(Z*P*)(*R)P)T'N(:,L)b(,R,**D+-T*P)V+N)`))`)(X)P)N(Z(&(*(P,L*-,p,X-V.^+,P-+-.H.J1Z001V./X2b2H401Z5`3T42j43d21B5N4V8V54J444^98X7X7`8N97Z;:=N;^:R:P9H;:<<^87F8T=TA\=R?@DA@@@BXDDCRDE`DECTJH\ODHHGFIGIZIMVGHRDEJGZEDRENDNFC`?TBVB?CA@ADRD@LBDNDdAZEFGPDbIFBJLF\GPJ^FFXANDA<@NAJATCBB?bACBRDDNE`CGCZEDLC^DHCGbDBLDTDABZFCXBBbFDFZE^BBX@A^D^DVCNFFBB@C>H?>b?VAACBE\BVFXFATBI^EXDfBDPGCFVC@RAARC^C^BHARCB\AX=>BZ?d@?B?T?`=>VA@@@T?A?XC\?@@AZA@JAPAXC`BBLCB@\AbB@@Z@NA?X?X@@@bBARD`BB\CBBVBB@TANCZEB@bA:APANA\?>>`>A=^==V@>@XC^DJFC`DVB?ACBBCFbCDCTCdFFDJIIFGVFFXHFEGIGFBGDPHITGbE^DC\CDDEDVIbGNHGZI^EXFXCXFFGdEGBCJDBDFNFFFEPC?XAj>`??>R>=>C^=T=PA==<=^;>T@T>V=?:<:`;87X5^7J4l4564L7J4V4`31T0\.\2N2l01L2^3N0T1L/.+h..Z.,-Z0^./\,,,T.T-b,V-+N+*b+(((b(T)''V(('P)^))*\*F)*)X+b+)H*))X(N)^*(`''`'T(+X'V)H&'&'&N(\'N)Z'P)'V)'J((X*+L+))+)<*)N/)^(()b*Z))b')R('T)J(*L((Z)b&X(L%`''Z&#X'V&#Z$V('f'%$b$$X$Z$"""!\$R!!\$!! ^! T TZ\BH\TH\ZX\^PbDTbVV\PBFN^  R h L ` N P R Z hFV TZRdbFJb\JjLPbTTXVbLZV`RdRX`bPbZVJJbNTTVXd\ZfdXXJRVJX`V`\FNZdfRLRX\\X\`bXZlN^ZTTTPLV\``J\\hbb`b`\VL\^d^^T^Z^TXR`^ZLVTPXRX`^j\hdXbfbNVXZbNZVNXXP^ZZVL^``ZRXTdV^ZVnVJLT>V^LZVPHbRJ\hX`R^\ZlZXVXZXXfXXnLV`f`XV\vL`\JVb`XVV\RlXV^Z^PZD`XVT^JJbdVdNbZTT\TV@XlVNRVTX\\`VXPRNL^\TVXZR^VLb`JTXbF\XJLL>PTTNbVNZVV<L\`VdLVLXPVXLRTdVNX\J`\TXR\^XFLHVTNVfNPNPb\N^NTPfRTRVNR`TP`T`^RXhbXdDZ`Pf^TTZLVVHRZh\V XN \ X V \ X \ X \ F Z b T  T\^Z X  NT\XLLRJT\LVVLZV!$!$$#Z"J V!!#X!H"b!V$`$&(d*),/b,H.V210J3P1.,-\.+,*.V-..1/L2Z3\3R9V657P9b87\4\2R10L0Z1/,-,`-,.R/--3F/L/T01V2F1@1\132L42`1..Z+j-+V-.+^-\,T+Z,.Z,H2,/-0^-X//H21B/b--L,`-*),+@*^)R*P*R)P*V(L'H(&d)*('V(b)b)V(T)^*+L+^+*Z*)^*((N)X*'T*)D'X&P((H+h)J)b)T0,+/L---+^.H,Z..0/.001N2d123V2\1b33R73\322321J34P5b758L78N;<8;9Z7:8;H:V;<;V>::^:8V8::=;Z;Z=Z;\<;XBZAAT?@>d@AXDXFTBXCFNEEADFREXJVEIGJZINIH^GdG`HETHVGEVDF^GEFBBTBCZ@B^AdA^@CTABCCTA\BFEDE\BBbDPBTDDVFCC@B?\@HB`AAARBD^@@C`ABBEFRDfDBFFbFPC\DREABZDFBCBDAVCFCCGGBZDRCdFDD^FCbCBVBC?>>TAABETDTC`DXCbCNCFBRCCDPCRDCB\@ARBPA?BCLD???ZBR@@A?@@Z?\B@V@@>R>^?@RA@AAABAALBZ@@VD@DJ@@TD??L>\?AVB`@LB\GNBFPHEPFFZBPEGRCCCNCVBRB>CTATAA?B??T@?L?T??FCCZBCRAREAXBNCJBDCTBBXA\EdDfHPFVDEIDGHFPJVFEjFGXG`JGTIDDD^BZEhDG\CJCPDZENGZGdEPEHXGZDXBBDZGE\DPBEA`ANDNGdFCRBRD?@>BP=>=P@>\<<=9X<\;P>9:\?;V>V;;X><;;<:b:T=^> V X T `P \Z f  PR^V\ZH`^ZVVLP`PL N X!N!4#!`$ !\#X""T !N%P"D%h$&J'^'V)X,d,L,001P01`0/X-+6-N0Z.\+-,.`/P./`342Z6V7V5b6T786R5X212.Z2Z,R,X+Z+T/0R-V..-^-R.0P11J32d42X43V11d/--P.^1\+R,+-J-j*J.*,--+.`..R//F1/0V/-.N..*)d,R,d,*^+'b)(Z*Z(D+(V*(R*R)&Z(*N''))*^+N+(((Z(b(Z)J(()')(()d+T*(\*,Z+-,`-R-,l-,f+H/^./H.00.`11L6^2H22J3X33`3\32/1\50R0J223X5V85T6797N8Z;7:X8T:Z=>^:`><\Z@A?BBC\CVCTGCD^EZFRGEHGRI^HJHRDPG^EC`IXDIDFEJVGEZCC>ARCBRB^B@XCDDBdAXBHCEEXCAA^D@PC^FDCDBA?X@@\>EXBFBHBPC^A`DTA?CBHCCCAXDENFXD^@EEbDDEEXG@CVCCHBGGF^FBADCDH^GTCDTE?CB@@CBVDAB\DRBRF\FXGECBdAEAXDdB@XAB\BBAABAZEZBXEZB@AX@BXAZC?V?>bB>bAh@X=BX?TA^A`CdEVBNEV@@?T>A@ZA?XCA@C^CPA@B@CfFVDB\EEBAfEZAEEGXGALFVDB=V?V?^=T?A@R??R@BTCAZC@\AAL@A\?\A\@BAVDDXEJDDEEJCDVFHF^GLG`CG`EJGNDZD\FBGJG`GPIFEEXDDLECEFDNEDEdDZFZFCTEDAVEXFCdATD\CTB\CBE\FXGTCAAT@bA<>=<;>;:RJF^JL^bPP^\XfVRXT`LT`b\PTTXPdPLVNdJbNRZN\^TbP`XPTbPXNVPR`B\P^VP dX V N Z Nd Z X H ` R X V Z `  ^ R` V T^ Lb\ZbHXRFVJ\Z\`H\ P \!!"\"L$\"Z!`!\"#T"X `#V" Z#$%((+,^+,X0/11V00T,-.--\+N+,*\,,H.V/061N24P37d5T4X5V4L3N42/.P0N.`,,-,^/P,Z,-V.^./R32342T321\12-f+,f-.,,+V.`+X.*-**+Z,.X./b/\/T11.001/V1^+P-P,d+b,R++-P*^*Z+V)(^&X)(Z)'(\)T'P)T')^+`+`)`,Z*(X(Z'P+^)(+X)`),X***+((+`,,-,N-,--J/P,/^-Z-1J.R-L//1^3X32V31Z2P6Z2327T0@/X2432F7234N689X67P:L:99786:J9T:::Z:7X8T999V:`<=R=`=ZH>>Z?RABTCEbA@XDAJF`ECZDEJCTC^EJF^HGEEF\FEBFHZHTG^FNGVF\FDGXJC\ETDDV@BP@?TAdAdCPAJALCC`@EDBDEBAB@ABJFTEb@Z?R?BF>R@\@?AA^A^BV@VA>AC^BDDDDGTDECDABPDDBDCFEDBVA8ATCZC\FDBFbBDXEdEDEAB\GPCjCTBCRBPBB^BZBG`FDbEEC`DRFFTBfC@A@BEX@CBCBENC@PCAbBEAVBXEJBAB?VB?R>D>=AXAADBNBN@@HC\C@P@\@X@`B@T=VBANBJAR>ACBTCZCDGEDNDBDbEECTAZCVDZDXDA\@P@T=\A=f\=V:X;T;Z;<:b?:7L:9^;89)Z(R(J((R'%b$T&V'####T%'$!##$#%\#\$Z"$"Z" R! T!VXb Z"^!ZZ^!XBPR^:TN\\XTVTRjNNPZn TX D d R ZV V Z X T Z ` b R b \ XVR^VP^N`\\RZdV^L`V^ZHZTdTV\Tb`^TbZNbP^TL^TfLXdX\T\ZP\RXZX^ZL@TVXVbV^f^F`ZLbfb^RZfX^ZZ`VJP^LfVbZ`bPdbVbVXV^XXRPbRbP\\P`Z^\\P`T\^bXbX\`^bXPVbN^NT^bXJXTXHV\RJXPRV`PFHZNXZ^hZd^Nh`\ZTRX\P`^TN\Hb\P\LJ`\Z^HTdb\`d`jjZT\Z\VRPBhR`fV`XV``VXTR\JVJdT`L\PPNRZ^`Ph\XZNPLfXPTZbV\LNJ\XjLX`\VRZ`R^XV`Jj\DHdR\FD^\V\PTdX^NZVJdXPVZjZdRVbPZXNPPZ`X^R^`d\RTT^jZbfd^H`^^\ZTRZTVZVNlbP\T\X`DXJfNX\b^HXRZJPZnXXNVhPjVHhNjRZ@^N\Nf\XP^ R ^ X lL T X Z R R T H Z \ X Z LRXZV \V J FVbhd`fTXTTVZT`T^^!X"N##N#%R"#^"X! ` T"X!V%T$&Z&X))T,T+)Z-.111/Z0-P,R+d-V+)+-+(`+-N/X326Z24R623842T02\2Z2\,H-,./-++Z/-`,X0/.0`0^3X4R3H7T2b2T0.Z.H0+-0b-P--V.H,-Z,L+X+N*+-/R-0/X0/T0/.X.-X/R,-,*X+^,*R*X,\*&*P)X)V)H*)*'^&(V)(+*)R,)'D)+(()`+R)V(^)V'Z(*b))+`**h-d,R,/0L,+-0X-+.N0P/^0-./2X2T32b1R-H302V4232101V3b5232^5f636688\9T9R8`;Z9J;78d88:Z9Z9b<8R:Z9V<:j>L=`?ADVCTADE^ABTDEELGZDDXC`DCVFEF`GZDCFJXF^HRGGGFG\EdGGJJHDXG\EC^EBRAR>?BL?@d?@AZBJCBZC@B@@?TB@DA@?>CAX?\=P=AZBCPBbCAZBXBPCCTFdEGDD^FPDCPA@@AHE`DDE\F@CND@^CLD^DXFLBADXICDF\EDVCXCNFDhEjBE^DTEFVGLCdDECHDLFDEVE\DB^@PDHBbEXAZBdDABDZDALACAPDXCdENCD\DFDXDBV>Z@CN?XDJFARDLD^AZAZA@\@\AT@VCfA?CX@A>B@D\BDBFFAFHZEfCZIEFCEVBDVGBBAA=TB^BVAR?BXC?Z@>PA@@AA`BRA^BB?\BNCZCLBTD^ECRC@@BNDXCA\D\@NDDDCXDNCXD\ED^EHGFFBCXEPD\CIGZCEVETBEBCTDDLBCDXCTGDA@RCV?V@DBCN@GBZ@\BNA?R@HA@b<=h:Z;9b<9L99^89P877L898:b7d6V5b6R474P72T342`10X242/P21/\///0^0J//V-0Z.N.*+****R-V.J,,\++L+(N(`)*(P),X)Z)L)(()))b+N-)P+Z)'*)T*V)b*('^(N'%X'\(%&H(P((^)'V(L'T(*()')`(L))))Z)()(*+J(Z*)X+V))T+)*\*)\*Z*P*\+))))(''L&&T'V&'$$#J$$$&j$""P#$T%#%%X"D$# "L Z XR \!PN V bFZN\RP^XFRZZVXZ^P\XRXZ\\Z\^XPf Z V Z ` P \ T V V P Z R TT` ^NPNT\ZZ`XPfFTPd`L^P\bPRbZJX^hZTVZj\\X^bZVVFZZRdXX^PbXZZXZVZjVX`R\BZJBbh\Bfd^PX`VXXXL^\hTP^\^XPbVnL\d^jb`>^\PjJL`fLNF^TXZJP`^V`Z^VfFVJfJTZH\ZfRZhZNb^hTV\Nbb\dR\f`\TRT\VRbZX\TVXHTTV\TTNN\^VXfVZTFbP`lZbVVTXThXXX^^TR\fZfRZ\hXPLT^XFZXXRlZ`X`TPb^`H`ZLPRZTXXTJ`N\LVVXRZJfHJPLRFV\NHXLdZRbZ>RbZjTRbVZZdPZJlPZ`ZT`bbR>LX`\VTJ`XdZPVH\TfH^Pf^N`TJLRLh^\XT\NVZRVP\VZHVL^RV^dVV^bTJR^^NVXZV^P`TN\`ZLNT\PZ@\ldZNtNJTX Z^ l P h V J  d Z Z V H l \ R D V  H\ R  NHVRPZ^`VZ>H !b"$^#J#!T!b! P" L!#N"Z#$`(&)(\-Z+1Z.1V0`2/X,-V,^++^+)V)\-+P,V--.P1/V021T35P6`7R123./1\/,V/P-T,J-,N.J,V/0P0..Z04J38Z5T3\11/-./-/.Z-P--V,+*P.+b+:-b.-/Z//P2L001X0X/21T/Z..L-,P--\*+V++`*-h+X))R(D,T)X'*Z(V((`(')L**R,^**'`)Z)()T)'((J*`,*)+)N+,,,,,P-Z-b.X0X-T.f.0b.21`.Z/`//`0\1/P01P11/4`1T0Z1d1V33Z66\44X476X6R8T8Z887V:^:B<97X7:R::8<<;9;J;>=@?@@@>\A?RA?dCEECNFDDCAABCXCCDGCrBCD`E^DGFTHJJIPIGXJ`EGF`HJD\D^CPA?>T@C^BA?ZAbBDFEVEAR?T@=b>fBBNC`>?@X@f>HA^?A@AATA@A@BBCDCRC\BBV@JFDTE?jBA@JB`BVDALCNAPAN@LCBCCBCPBDDEFXFVCREABFXGXGNDCETFTEbEHERDEEDGEbBBC@RBAE\DCABD@TCD\FCGCD\DBCGC\CTA^?PCXCARD^FZADB^CDBBACTATDZ@CR??AALDCRE\DEB`DTEXGFBH\F`EVCAFBNB\EBDVBRD@RA@@V>@ZA?Z?X?\??BP?BA>P>R@=B`>X@A@PCCRBV@C@^@@AbBDCHBDbDPDECbEDCFCZENDAECXElGBCA=EPAEDG`EXCBCCCEXClCNDBRAT@d@T>`@?BBFFEXB?\?Z@T=\=R=X<*'R((R()(T('B'X'T)&'b(N)b('\+(X'\(D)^(F(*`,Z*Z**,+T)P+V)++V*P)&L'((R+*N*F(*T)'&%)&'&X$"&d'X$%`$V##V"R$#"Z"!f""P"!X"N^"^ ! bP\PX^HR`FdP@Tf\J@\PNPV\TZZT l b X X D X Z Z V Z \ J  Jd^THfN`Z\R`\bRXjJPVFTLPXTX\VhFXZRPTZZZXL^NZ\VFTVX\^hHZXVZL^RTXLfRRbT\\XJ\`T^\PVTXhTNRXZR`NTTVXbTZX\VNRdRZ`RD\P^`PfL`PTRTVHNJPLPZP\^\F``PVVdJPZ^\VdVRZlZRT``Z^RVZfV^ZJZTNNJRT`PXRXT`X\Z`Z^bXV\\^bXVb`Xbb`^fFf`TJhTNXTXVTbJfXRf^Vd\XZdXNRTZVBV\f\T^`PLL\ZPZRR^TXR^R^DPTVRnVZPRd\`RpRZrhLF\RNXPdDZ^XL^ZRXZdPXXHZbZ`HZfPNJ`V\PTPdF`^RT\^T`V\PTPVRT\TVRT^b^PTZ\NX`jXTVZ^PL8T\fVHlN\VTTN`^bZ`TRR`^RPNTPRZVTRRNXD\ R b ^ F H R VZ F LX^^ZRfJV^FFPRdXdZZTVH$!"N$V#L%"T!X!#d Vh!L#!#$%Z%)+*V.-X//0`2`.^0P/.,,J-)J*`()T)*+P-Z/0f.031T35Z5d53T1b1^0P//,-\1V.Z-+J+-,/0L1.02X14F2d4X00.0/0,X.,.,:.^,,V++R*V+)++...Z..V111V0X/N0/R/L.,^/^/-T-X.X-,L-*-T+(V)()b(`*V''''J%(*)*'P*,((\&b)*R+N)Z'()(*f,*,-+,,-`..R.^+.,R+1X.d1-0-X0/N1f///L21V3`00\/L/D4X11d415354D46d659R7R78\:R:N9`77:b898d;J<=:\=R=::Z@=XB>??=?=@BPBDTC`ALDBBNEA@DEZAPDEPENB^EZBBDBTDHHbGTIHPINGFJXHPFTFVEEEBL@?dABNA>ZAB@`ANBA@TATBA=V=b?PAR=D?R>@>X@A^A??B\AC@@LBBZ@BPBbDPAB,DCFCJBBBA?LBDECCA?\BV@`BJDdEEJHED`D^DFZFBXEDEBRDRFFREGbHVFRGDGVIZIXC^BPBT@ERA\BRCHAV@ZAPDBTAV@ZBBBPF`DVFVERFTDECBCDPA@?bA`BZFZBfDFC@\ARCRAJ@@@DA^@?>R?`@BZ@^ADVDFCCDHFDXBERHXEVDVFL@Ah@?CCCCVARE?>T@C^AX?==>B@@A@@@F@@@`A@X@C?@@fB^BDEDPCPDZACRCA`CPANCC@ZDVC`BEAB`CDVBVCBDVCCTDXC^EECdATAR@^AL@>X>@@=@@TBNB^AT>R>?=T=ZF`^HRdX\bTLXHRZHjTRZXZVZP^TNRL\\PLRZZ`NTfHJXZ^PVPZVXT\^^ZdL\bRXP`T\bPTZVbVdTbddXZJb\T`\^R\Dh\PbTdVXNLTX\V``VRFdTTbTPXbfTXXVdhPRVX^ZJ\ddRXZFbb^LfRHdR`LRV^<dNFTNjZ`^XR\n^fPRdV\dPd\XVHJ\FHTbbXhLbT`lXPRRZ^TBR\bZVJfVXZbdN`^J\\PVN^ZLVh^bTdb^^lXPTZX\VZ\\XPP`FZLB\X^`P\DXLVVZTV^bV^^FZRLRV\RPPXJHbVX`T\TVdRXVRXNnN\N\fVlLJP^NFHZ^hT\\XRR\P\^NTlV`F\RRJLRVTR^RXJ\NJhVJZZ P XR X T P ^ X \ N T Z b \ N R Lj PT H f\\ TT\FZX\XRTZ\HR^^R"X!T H"#P##!X$!"\! X" T"T$Z&N&&%V*(R.-.f0J1./0b/,N,X+*J-+),+*Z):--\/Z.N/3P13V2V4J26100R30.L-0^--b.D++,,.V.P.0d1N321V331J11.R0-0.X0,R-X/T+N/++P+X-)Z.d-,-`.L0d0L/1^1R/.L00\//-,-,L/Z.,,+X+,)+*(X&&T'''&(\(N(((*J*+V(N*^**X(\(h()\*)X)L,-J)b--+L+^-V+T)*)`,`,-,X0-2.-.V//R/`0T/-Z/1/L0.Z0X/R122T3V1P1d1Z63P4b55\5N8\77:b6F7^88X:5`868d7Z9:N998;;;;:?>?AT?P?@AZCAA@CETDEX@PAAV@DBXBZBDAZBF?LA?EBEDG\GVH\FGFXFXFJGZEFDDPDC^BRBDA@TC?@hDTB\@A@\?P?f>^AR@H?AT@Z@bA@=\C\AT@hDT@@B?\>ACCETBF@@BZ@^A@VANBXCHBZCX@TBCC`DPCTFPD\EAEPEAAdCXFECGRDXIHLGTGGbEIdH\ECJFCAR@B`DTBATARC`CAB\@CJEJFDDCGEE\EDNBBPB@A?X>L@fA`AAJCRFLDVBTD\@AAA???R?@^CJBGAXA`EXDDZDVDEFFC\HLECBCXCAZELA\A`DRBRB\B@PBR?^D@>Z=?F?@NB^>P??VA>>>V@NCZBVBT>?h>`>RBL?\?@ECXDR@BRCBCCD?@@`CCXAC^@XAEAA@BbBLBbABBB^B@A@TCXEDbBJBAXBP>V>?T>@^??VA?D@?PB??>@@@dVZ^DXNb^X^dbdX^dfXXdhP`VJRXRJ`\FRL\^H^P^\jdJf^dTbZd^TVfVl`LVTZ`Z^bXV\VldTP^XXVL\XRJRPTVX\bLh\RfXZV`bdNXNVXVVV^RPVR`\ThRTFTZZVdVV\dHRZZ`\bdZXRVTdB\fTZTNZTPbNVVbLTdfVTVJFfVZ`^fZfP^NNLZVTNXXVT`VPTRVl`NP\V`LZPTRb`RXV@^VR^^d`XTh\Vb`ZbXNNXfbLXPTVLV` Vj \ V V Z X j T \ N  Z  ` T Z ^ \XVNdVZTR^TPP! P###\#\"P#R"!\!!b!^"#$#%&()T+-R0-Z/L/T0`.P.-X-*b*Z+**Z*)*-,,H.\.T/0Z4f12\0X1X2\0P/.P.P/,`/.`-X.+-Z-+++P-F//f110X11V30Z100230R0V0-0-,X,V-T+^,*\*\+,-+-.X3P21100//..Z/./X..,J,,P.))T*()'&P&R(''L'R'f)^&\)'T(X*b*R+*,(*H,+,)),R.)V-*+,*L+*()P-,^*-N,,X0--D..0/^..1-/2N0J/Z2.R02Z1Z1X0X2132V474565X6R8T:X87VTZC@CAAARBABH?^AAEATAZA\BCbD\GJGNIHbHETIDETFPDE^ELE\BXEBXBAJBCCV@ATAdB??^BV>>X@=T<9T;R;F=l=@^?\?<=\?>T>H@`A^AVE\D\DTAfACbBBAD`ICNBACXANBP@CdF\E`C@@C>CDCTEDNGTD\BC`CVCDZCPBTEZFGZIDHH`GI^DGVHGFF`CBDX@`BRC^ECRDACEBELGDRDDBVFVEPIPCEDB`DCA?RA?\>L>?AZBXBRAA@\>h@T@RAZ>=ZBFA\AdBRBCCDDBFXEAADAAVCRABTAVCABPCATA^ACX?@?XBAP@\?XB?P?AT?B?JCP@N??@??\A`@B\@@X?dA^@?ABRBbCA`?AAC@?V?b@=VA`DBCCEAVD>dCBT@RABADVC@XBZ?HC@CECBA@\CP?PA^AZA>`?T?>H?X=T@L>>@AZ@Z@L>T;;8;;:96T6R8N;6:53\46T5535T86473H41X3J120f0/0102/`1H/Z00111.`0/Z0R.0X-*\-,,d-N*b-V)*X*)b)^*R)(Z)*R+*Z+P*+-J,,R-\),+V(b*)*^*+*V*)V*)`)+()\)*)N(X'(T('N)+(V)*d))^(''*P((Z+))')l+B+\.((L*(H+R,X*X)Z)'()))V)X)T)(R(^)R(X)V*L((%X'&%$P&$d%#X##!#R#!B""N#N$T"!^"P !V!!!H `P ^ n\NNRTPZff^ZXN`V^XXV`FZTTbXXVP ^L L T J \ X L V \ `ZNXNNZ^d\ZtVXb`dRdbPXTXdP\NJ\XRR^\\TVZ\N^NfZVZ\bZf\V\\VddTh`ZTlhRHTXfhTNH\PNf^RVdLNXfJ\XZ^bbTdbZbRLTZT^\T\\T\\NXR\\ThN`V^`dJ`j`\`fX`bbNFbRfldD\^tNPfXXP`ZVTV^V^\bVPdZ^LZP\ZJVZNZVTRRXNbHVXNX\P^XZ\DdhTZZbJhRTLXZTP\\P\LVRZNNXZTNb^^^Z``RZdPXBd^\RRV\BXXPfj^JdNPRVfVVN^RZN^V^VV\^bVZXPTVbXN>dd\V@h@^`V\T^LX^ZTLRP`dPTP\VXZ^XTJJ\V^ZX`R`XLRRXXXTTRNPV^ZZLPPTFDJdZlXVh^XHR`PZfVN^^VZ`Db^^NPPRVXVRVRZ\ZT\ZPZ@N` R Z P R Z d X V H V L X ^T ` V ^ ^LTZR\NXZXTX`PN!##^$"^# V P"!"T!!!#"L#&%P'**R--.f3P./V.0V-,X,+-\*)(*(V*T*.,,-\/0H011210D./J-T,0L..0-P,+**)Z.*N+d02.1\2113T2@1001h0/1.L..T,-d,P+f+V*T,^+*,,T.J-L/0R21-X/Z/0L.2///+X,-.\,R+V/*R*^)T+X(&%''b''J((T%T)':)`)Z(Z+X)V(*b(P,V*R))N**,V+.*+D*)++X)T+R*F*^+T+T+N-H+P./b-/,V.,P/Z0T2.X1./-1//1T2N11/T1312`4`6X5R6b6V78H77^77b6J7h9N88N8\;Z:`8:`:^9n9:L;d>\:>N==P>\??P@ZAADTBV?ARDBVBTCBVALC>VA@BA@CRABfEXCRFLDEFHdDFDTFTC^DVFXGFGLDT@@DDZBZCRF\DT?\@?^@?@V@F?b><=F=Z:=<;>@=LLC?VAfAZDCEVEPDLECFXC^BPDPFAVATEJECA@\>EAAVC\AT@AXA=B@AD@`?=@j?>?T@@X@lBXAN?@BAJC@V@B?VBFAX@@TA@`D=V>>AAPAA@TB?ZARCR@Z@A^A@X?TC@TEV>??@@>LBAZA=@;Z=P=>??A^AH=;X@=<N?L@=>P@8F8Z7:^854^5^64444V433H5N855422120J0.^/0.Z/.1/0/1X1D0`0X0X2L/N.V,V0T.F/R/Z.\.Z++,)L**(F()+))L*)L)Z,(+J-+T),+T+Z**^,+*X+*L+*^+R*)P))N*\*P,N(d(T'')(X)N)((T((''`)N)(T*')`*T+X,X*,N*)(L()(T+)^*R*'+*Z(()).**('&&)X(%V''P%'@%R'$X$"P"R$b"V#R%\!!"R!!!R!""`"\ Z!!!# N"\PVVVR\d^V^T\bVLZ`TR\bVR\N Z ` V Z \ Z T P P N \ F  p \VhJP^RTV^JfFl^TZLZbLTX^lTTRRX`^bXNdXVjRFTRXbLVZ\V^ZRVTFRTbDLZdN^`@bVPVTLRV@rPZdTJ\^HTTHZP\Z^VRV^fJT\VX`dT``VhNV^HN\\jfLXTLZVhXTTN\PNZ^XhTXJhV\RPVXJPL\\RXZ`bJTb\\`b^^`\fV`XlL\LRTF^ZbX`bZ^V`XNXPFV^bRblldX\dRfTbZVNn`^\bXTblR\TR^VhXRVTbX\P`\`hVd\fJ\^dXfXd\P^TnXVhL`RTVdbVT`\dB\XZ^f^VT^NLPTbTX\ZRdJ^XRTTdRTZTZN^`NX\TFZXZXXJN`^RN\VP\RTb\VjVXZfZXZ`^XVX\Tf^`\Z^PJLTP`dP^J^RXNT^NhRXX^J\XXT^\VhXFlLZZP\NXJXbTdRPXV\VP\XRRR X\  X R T V N L ^ X ^ b TbXZRVZ ^f TTTRVVXDXRTR>PNd"#N#"f#%#V!"Z"" %"!"V"\#R$&&J)T*T,L/l.-b.J.^/b.V,,Z.***J+b'*(`+(*+V0-.j.10/V1^/T0-.Z/0,L..X-N,T.+T-X*X,R,+\//0T45P12X4X114\1T1T12R2/Z.-R-,+^,*T*V+F++P,+Z+-P/\0P00.T.T3J,X./0/\1-1^.L/,P,X,-+*'(&d'+*V'*L'&b$J(`'''(*b*'P((\*R*+^(*H+\)-*)*)l(+P+V+*`,R-,R-b,*J+P,.+,b.,`-.Z1^0X0/X.P1.0--//N/Z0R01T3R2T324V22X3T3R5X4566X7795R7J8X57Z:\;R:V:8:H:T9d@ABBN?X@@?b@?>A>XA@R>d?b?>`BTADZEC?BRFDAdGVF^FEZEDFDRI^HCELCALBHNBVBCTAPB?RB=PBLAd>ZA?=Z?T@NAhAPBB@\BP?AX@@ATDJFVDBDCB`?V@L@@@BDBLAA@BJC`DV@AZBXCB`CENFVDXDDJGdDPCbFCEFVGGTFTFRL^MPHRHLHGF\JDZGEbIINDTE`CFFCBCAEE^BFVGEHZEXGRDDBDB@fB@ZB`@JCDVDLABl@PC\BNBDDB?XB>d?\?@D?@VCbDDDEFCBDBLC\BVARA@^CB@bAAT?NA@A@A`@??P@@CXBA@P?N?^>T>V>L?^A?\>=f>XABP?>^@??>VBA>\?`?>Z>?\?@@T@BARCCXCbC?ATAR@>\@@CAD@B??V?b@>TAX@P?X>Z==?^=n<;b>V=Z?=:9=N??==V?N?F\??JA=^==<>X@P@TA@@VC@?BZBXHJBDPDZHPDE^FVE^EFIDCCBARA^BCXA@T??BV<>R?<==><=^?^B>H@AT?D?RBA`=AdA^?D>BXBBAA>A?TABEBABBfE\BB^A?DBBG\EERDRHdHCPDXDCEEfEF`DPHE^JTJZLIIDFFPHbEHZEbIC^GTDTATDCDEZF^BPBNGCPIEIXFXERGVAZBRBRB\@@@XBC^ADAZAT@bACTARCVA=>@ZAb>?Z=>>N@?ZAHFBCDP>DXCBRCNB>>`C@H@X@Z?AAZ=?T@A>T@@@@BV@?d>@@R?RA`A=\@\@NB@AR@A^?>`?T?PA?DCV@?\@N>?=>X>=L=>P@FACVA^@B@NA=d=R=L=\=V?RBAB=?@<<^>=N??R>R=V>==Z8;d88F;P86:964V4`5662X2h33f44L5N7b2`40011P301X0--,R/Z0D0^10b.0N/\/d/-/j0Z/010-,N-X-\/-Z,,d**T+Z**(\*()P,-.*,,V++T-P,,,,V-j.,T*^,\)H,^-h**X)*()X()(&T(T*))J)&'Z))V)b)T(*)R*++X,*N*+R*)\)P(T'R'X&V+)V+'^++)R*X*('X)(Z(&()P(\'`'$X(\&%L&d%T#T"X#$F"N%"`!J# "F F L R X! !N!!!!Z d`J^Z\Z>RXVTNXV`ZVbDZZNXXNbV T^Z F R b H P V N N \ ^ ^ T XXTX`VXXLZZfNfLXpX`^Vf`PdXXPTZRF^N^VTdJ^ZTZZVP^XN^N`lRb`RhZXZPZZX^\VVPlZXd^PZT^\`JZTdd\ZNJ^P^^\^R^NdR\JP\Z^^hNVlRVR`\XRT`\DhXJ\Z`J^^d`bfTjLB^ZdRVP`h`XR```TVTT\ZLHXTXBVP`ZPN\TT^TZNbrZ^bN\ZfXVPLPNZ\XPTZX`XX\R^bHdb\XTT^VRPPNf`T\VVZTT^VXZXfXdfVRRfVXdVbXTZ\VL@TXZF`PV^`RNZbTXR^hVXLX``PJLPjVdTbXLbT^fVL\`RX\NT\^\ThTH\TTL\PBXT\\b^ZLdVXTXbRXZRV\Z^FZVNV^LRHX\Jj\^RXX`TdNZPNVR`hN\jHXdTTlVZ`RBVDT`T\bLRZRXJZNV^\ZhNV^`L`HVVV`\^HX  T  J b R ^ R  X\^ PRX VTZ`XXVXfRZJ^N^T`BN Z!R"Z#b#"R!R%#Z" "!N#!"#f#L&$'^*),+P/X.b/P0X/N/.,*h,Z,d(V)P'X*`*(^*)Z)*R),.-V/-P/X/X-`.L//.0^1N-Z--,+T)N++.b,--2T2J11R1^1@5Z242L1\4R1J31V//T,Z+N+++\,-*\*+V,,h/N-L.D0`-b/T0L-R../J/F/X0X0/@.h-j.N,-*++X*,(P(L,('&\(P(P)'Z)f(N(^*'\*b*))F*)),)^+*J+,+^+N+T(*(Z))'Z+`+)N*++P*,+)N,-Z-.,.-`.Z1R,P/R-.T1/R00T//Z11V12R3N41.V1N33b25635X46J776V:^5`;9Z8^898Z:V:F:=;L@>P<=`>>?<@P=;\?=^?@@P@@P>\@f>>=>B=V??CZ?BL>VAVAC\ECNDhBDRCAFEDTFBDVDCAATABVB>>;<`;=>==Bb@>?PAXAZ>BC?>X<=Z<`<@>VAAAZ>b@@??A@LAXD@T@?@ZA?BAD^BVA`CCDNCRGEEPDCCDDPGhDGCLELHHPINHPI^ELFVGRFFEGhEVED\DXC\C`DNBBdBCTEdHHVGGHXCB@RBTCAB?F@T@TENAXB@AH>CXCjCABfA?@>?^AAVB\C^A^BCA@HCTDRABZ@Z?`?F@Z?jAR?^CNBC>lAT>@D@AV@L@?@?AAd?P?F??=ZB@L@@^@ZDbCH>B>NAL?@^=T@`@D@>==Z?V=d?L>X==ZDR@AA^BANAX?>@V;V>?@BAPB>T?XBd@\>T>?R=:;>^;JP^RRX\\TR^ZVTXRPbVVR\lRTRVdTLVRRnVRNRVP`VR\TTV^L\VTNX`lR`LZ^VVP^VRZTd^XRPZTNNZZNPH`R^dZPVhdbdVR\PXdb`ddV^R``\XX`Vd\T\^L^TJR`RXXP@fPXLRRX\RP`^V`\Tb^RTTHTNJXTXPXZd\PbLdZ^RTT`V\ZFZTJb^P^R\TFVN\XVZFVXN`R\bhLRXPH\PPTHb^LRVL`XZJRXN\fJTTJLLVNTNZLHRHXVTfZBTVJ^RR`V^BPPbdVTZ^JXZZ\P\VVPRNVLH\ZH^PJZTN\L N X \ b PV ` V L T H X L Z^ P  ^ V X TVV\Pf\PV^HbP ^"""V#V"`"D"V"L!!Z!X#J#^!X"#V"^#(Z((+\,Z,L./\0.T..d.+,^)X+(H)P*')&)T)l)X)b-N+.,//J.P.X///./Z0T00,*0P*-,f,N--T-/0/201N1N23^1j0N2223j2.L/t+,,+L+N*R+,+8..-H,/X-N-.V/D1,X-,.0.-V0.N.^-,++**\*()`(((''(N(T*'(*P((X*d)'V+Z)*P*R+T*X*X*+*+X+R))^+L*'&)(+((R**L)N,+V*,Z)H)P+T/+X..N.R.\.@-^1H.`40Z21.N001X2V10l3V22\2F03X2P222P4V7D4X45B7^7X77\:V9\79V;::T:\:L=;R>T>\CV=@RAZ@=?XA@JC>^>X>P=@B>N?@?JA>Z>RA?DLEZDLARDLBBLCDGRGFFDFXBA?\?JA;P?9Z;Z:\>X?Ad?\A>L@@P?CRC@ZBHB?ZB>??XA@@BAPCZBAN@P@NCADPAAPC?A?C@AAXBVCE^DFCE\FHFTEDXFFTGRDNDDFCDLGGTE\EEPDCHEEHDXGFETCTDCFCCEEJIDFFG\EEDDDA\AA^B`@T@Z?B`A?A?@ALBRB>AA>D?^@;P>^>?Z=N@=?A?TARABTBJABNBJB?h?JAB>>?d?A\A>?PCT@VA@NAVBR@R@A?E@?N>\@T?^?PA\@Ad@B`A@>\>?@^?\?T>Z?RA^?P@?>?V<=Z<`?T=A@>A@??CT?@V>?>@?B@dBB;@<=<;=\A==>N<:=:;b<;P:<\=V<f:P?:N;X8X9P6X997L676d5Z7f56Z53f6\43Z0X0Z31R3H0\11Z1Z/d423d/R0N0V/N/0H.\//T/R0-/P//N/\/-T1R-X12b/,,-R-.Z,T,T,,,*P.J*Z+V+)+B,j++-^-L.`-\,,^*Z,^,T.P+T,/\*\+d+)\*R+X+P+f*))H+Z*Z*Z(P)'T(Z)`((%()`)X)*V)\(V)X*b,N,T*))L('N&*('Z(Z&*(V(,`,V()+^'X(V)&(b(*B)V*T)L*V(F'T'R&&%J$P%#L"! !! ^!f ` R\!T  ^ RTZZLZV`bNhPPRTfNRNfZP`bNNRPLlTJ`lTV j H ` h b H n  X V XR P VRZPRZTZ`Z`HRZHLZ`ZZRX^JZVZTPTRXNJV`NPVT\X\P`TRjT\P^bZRP\TXVV^NPVdJ^BP^HbLdVbPZZ`^XZL\`TX^XdJLdZZ\jVRN^N\RRTf\^ZVVVVfZ^`d^n\XVbf\ZN^HbdZV^XPh\ZXPTZFdXd\RZX^PNdf\T\h`VT`^RXRdP\^FVbFXX\^JX\RXj`V\PZdR`Z\dVPZVPfflH`TJ^RZ\fh^VfZ`VfZTXX\XV\`LX``RJb\hfhVh``RRZ\Nb\\ZNVXZZTZ\\VNFVZXXR@TZVdTTPX^XT`XVT`TVV\PXZVV`N\<\ZTNTPNZZT^J^Z^V`JTR^XNT\\N^RRXXJd^T^VbVV\PR^\`^XZXZTHRZJZPPPVVRZ\JTLbVZTVTXX`VL^XNJZH\TTbZNRfV ^ T V ^ d Z T V ` X T Z L R `Z T   LTXT\LVXPXT^FXLLXP^^!h!$@#`"X#! "!" X!!V#T R!##N%%X(X)^)D,B-`,^.0P.-h-,P-+X-)X+B(''^')R))N+*X,.-.V.d/`/-1X1\1Z.-/T2./V,b-d+J,Z,+/^.--^2.R0B00Z3T3b1`1J2\02T0f1P0h1Z/,`.,*R+*V++*P,,J--P-T.V-Z.-.T.-^.0T-.X0R.-d/P,-T+\+\)`*X)'P''X'&X(^'J&*R*T)X+(*'(b))F+^+Z)`)+V**P)+f'(\)(T)d++T('N()R(L*+T)V(N+X**Z+X,Z,+X,/,`.,R/,R/.1V.00^.`/h10`2000003T00R12h2T0R123Z5T33Z6R4X643b8\9N9V89R:8899<==<@V?@P>=R?Z?A@Z?P?>`>d?d?AV??PC>Z>f=L@?VA=V=bAR>?BAZECbA@LACXCCVEVF^F`AAB`?\B>T@VATB=V=b@T@=>\BZ?\@BJADT???>\AX?<=Z>^ACBfCRA`@?Z?>`B@ZA\BBA?NC@@CC?B@DJDEZBFDDATFRFAEBXEAPCVFHCCCTEVEVEDEBRFDCLEXEFZJHERCGJHHINGGDCREEBFCDATA^BZ@@P@PA@A@@N@??N?d?J?\?P>=\??>=X=T>??bA?@ZB??X@BjDADR@H@><\?AR?<>^@^=?XA@\A^@BN@LB?AR?=T>;@=@`A\B?JA@AVA\BJ@b=Z@B?\=>^B>Z@N@H>TAD`B>?@^BX?ATA>ATA=P>V>d=;Z=>`jV^LNTZXRL^RXfNZ^XPXV`^^VZP`RZNNXfDZ`T`\`ZRXRX\^TPf\PXZNR^LbbLZ^bfNLRdR^TZZbVVNZNhRZb`VPb`N\^bPfVZRVd^XdJZ^Rb^^NVT^^XXLR^TX`hZV^bbXhXNdPZb\`R^d`FXH\NJbZ\`NhfTZHFZ`HXf^\ZbNdRTTdX^HVdPZdVNXR2TTjP^XJFZ\^\RR^VdR`LRVVVbXTXRTTdZXNJXZXL\\H\HX\XTbTT`XFRTPZ^T^XT\NHN\df\JJ`4^P\\b6TZ`bTVR\>V^XfRVVVHVRTT^^LP^NPN\VbZ\Z^^NN^ZLTLVT\LdhR@bZd V P ^ P L X V^ X ` > X D Z H ZhPL VZR LRFP`T4RRFH^RRZ\!##"R!%"X!!L!#"dP#"D#j$L%V&'T),.-V-Z.-/H/f+J,N)f,**P(()(N)`(`)T)(,/J.,,b---R1.d/X11N.N/+P+,R(L+-\+V+.+-b.R.T///3V0N13J312X101R0F0f..H0,T+*Z)\*)V+T,*D+\-b--Z+V.,V-b+.*.Z.-j0-N0-V,,-T,*))V(')Z)F&&'((R)('T)Z(()'Z(\)R+X)+T)R*R,T)L)'H)'V)')d(F(Z(d)\)P+*T*T+)D*\)**,,X,,-`-L,-`-..R0`///^//B0J/R00V1-P/T20H20\0L23X2F31V3T32115P5b64L655V66T79^8P;T96T====:=?=ZB?@T>?TN;?>?>@R@^;<;P>N=jA>@JB`B\BXBTD\DARDJEREC@^@LANA=>?d?=<=`>R?@@T@=>@V@?@?b@BLATCBD`APA>X>CBA@AT@A@C@D@B`DB@CBPCBZCA`@@DEVFXGRCdH\DDDDHCE`DHDpCDBJCZEDTAAECDALBfCTDXELGFNCDHCTGTFDGGDAEF@TFh@XA@V@Z@AF@?^>L@@@?PA><=J=Z>>X=<>\AL?^BZ@T@NAHDRAT@C\CX?@?V@V?NA>??=T?L>B=T=X?J?VA?H@TA?T?=?>=>>?CJAXC@JAdAP>T=\<D?R?=:=T<?P@`>F?PB>CZ@XN>X<;d;f99R88:`9X9>;Z=;\<=R=?@F?Z?PA\>T@=?;;X>T<;;=?FBP=;=N=V=?^A^@\@VDbBAPCdFTCREBVAdDZCh?>?Z>AV@b>>P?J@R@Z>>A@AV@>??j=`??L@`BTBAT@>>?@\A?B@VD>ARB@ED\CF^BHCCFXCBCABABEEZDZFDFRHPCBfDAfC@XBCEJDbBRDdE\@?BJCANAFTDCTDfFEC^FDFLDVIDXE@FCT@@B>XC>>??HA@?HA?H@`?>>R@=;P=@B?>>?R@Z>>V??=R>?=R=<=`@X>^>R>??Z>A`=X<=@J=X>>;6==V;^=>XA@>`?BV=R>b==;Z<?>R==<>;<V?>X?TCXC\?>V?>J>T::VZXVNZf^V\RPPPVPLPTXPVf $H""T#@"""L""^!N"` Z!""$&(L'**Z+*X*,Z,,V.).*T-V+)\'H(P(%&&*,^+L-T,,*+L+,,R.-R.-d.-P,Z,N,\+R,X)T+H*D-`,P0d.\/H-1/.010\404371R2\2T100.X--*J*L-V+`***)+)X,,b,^+,Z,L,-J-.X.Z.X-^,+X,^+,R-H*+J*\(X)(L(Z&'%(J)*)h),(+**()+`)-H*J*\)&Z)$V'T''(D(N(\'(**+*X*+\+Z,*)-P.b//-+T-.P00..T/-^+-12Z/F1X.^0-V0^/V-/\1X3/Z31//L2P114F55d633`42d63Z55X556T9P8f77;Z;Z;V;T`>R<:R;J;T;<;==\?=XB^C@B\BAD@@C??X?@>===>P?V?TC\B>;=>B=RD\CPA@J?^@RCR@N@PB@AV?D><>^>>jAR@C@CBDJB\DABNCXDXCVBDNDVDC\CBXBRCEZDZGLJDVEAZEJAAZC@TAAfBABRCRBABD^AZCDBDB\CCbBDCVGFCDCTAV>>>A?LAZEABCTD\?N@>Ad@?Z>=>=N=`@X=V

==;>J>A@ALDT?AT??<>@;PL@N>=J=R>>A?VB=L>>=>R=<=>>@A<>=N=Z>b=V;Z;j;<:V0X0/1Z30P110///R0./R.*`.Z--.V,\,P-\-b,J.--,X-R--,,T.T//R.X-,J-,++++*)f+T)J*+d(L*b**)T(('X&H''P'T(b'R&((((+))R++(*d)X,n+)')R(Z(()V)%%Z&&(V'h'%(&@'X(d&$D%\'V'\&D%%!#$J#"#!Z!P!L!!X!"f!L""f!"VPbVRZTVb\`TPZbX\TNfPTX\VZ hd d f ^ d N H L F V d F b RZ R H TT\ZTZ\VVTXZRZXjD^NXXXdTBV`NfZFPZPRX^VRP`Vhfd\JZNNRPR``T^V\bThPX`PXZJXRZfRhZHV\XNVbNXdVXV^D`V``VTVXTLVX`fPVZbRVTf^ZdbXXfl\bFPXZ^jXXT\JXDfVTVV\FZZN\TfRXVRb\XXRV\ZhRbT^ZbVBVRBfd^LPbdVTZJXb^\`ZVfd\PXfZRLZl\Td^XL``XPfZf\^Zfb\`TTP^RZT^V^`J^V\fZTTfJ`JnVjR`TZ\Z`^l\bR\JRV^Z^hZZPThXTdXVb`bZdVVZdZ`L`dd\fFhX\HfZPZLXPXhRV`Z`N\\TH\TXZRnPV`VVDV\PPfLZZnNbdX@PTZ^PVZP\XHb^ZXPNhfXPP\b^`PX^bXDh\VJPHRJXTPRRRd^ZVHjT^RV\d`V bLZ \ Z `Z ` B b V J Z F`\ b RBZNfVZT^TdZVVVV`!"R#Z"!""$Z"d!X P!F!"`&"`%L(L)(`-+\,-P+,,P)*,+L+(b)R((T)')X))(R,,V-\-Z.,,\.T//0X0.N-^0D.-*).,d,,R,`/X1./Z0.\1`.2^0Z2R20R3f3352T3`2^1X.b,J.-H,*T)T+(D,T)*T)X,b*<,Z)d+T-*)-T.-0-,/+N*^*Z+^*T)`)`)P(()'Z'f(X)J(^*V*(V(d)((N+)X))T))(,R)\)P)'d('\'&(^('\'F'X(*\**X)+*+*.,,0/.V0\1P.-/.-0.P-0.^1..,.^0.X0T.L/.-L.`-X10\1N511422<62P342X3X64j56657V77T88X:99:>;RZ=^?=>>;@>>?BR>h?R>^Af@FA?=?Zh?X??\@?N>>>>`ARBBABNDN@A?A^@@T?T??>\=f>?<>T?@BCAD\GEG@VE`=BNDCbGIDDBAHC\DE`DXGVECBENCCZ?\ABZAPCVDA^D\DNBNDREBTBB:CXCCCCECNEPFFRECFB^C?\??b>?T@@BZEBTAX@Z@D?`@ZA>=L=R>T<:9:X<9;>?VDXA=?B>>J?=>;?R;T?f>N?=>f=\>=P?<=N@=>\=<@;B`?N>f?6?\?LBX?<F@>N<=<<^^THTnRXdLX^TP\XL\JXLN\ZfR^TJTZ^TdLhV`X\NZRlR`\`NTZPjLZZRPRbTL^RZTTXXLbVPXjXd\XVbLX@ZRX\VVj`T\RNNLPfZN\X@T\JZ`XTfV^fJXVZNZFf^d\VFVb^`VNZZbTLVH^ZV\XPBLVJJX`NZNH\ZT`TH`<\T`PZdTZXTR^NZP`PXfRTbN\LZXTDPNVbJ\VNNVRZ b L R X d N ^b R T ^ T X Z f \ZZL RX VNH\V\`BV`RNZVHJ``L!P! "!\"L""># ^!L!d X"d$%X&')X)X+P)f+-T,N.,X)Z,+T-`-)V)+b(R(\)R**R+V)N)Z+*b*,R-.F,R./V0L,..d-,Z,+R)R,,`.T,-X-.`--T,V.01X02^..J5V3\4F3R6V7L2/d2L0H-/d,+P-,P+,^(+++L-T)D+*X**),++Z.R,)-T-+P,*b+*+)**Z'')Z+V(()R(V)`*N)*'))R(*((`)(F**N*''&L*'X&X)(`('T(H)(X*N*^*)H-,+R+T0.X-.-b,V/./X-B..-../R/.//X/---/V/b,-`--R./100b02V0N0^2J3R2X4P1\754L145P65`7Z5X7:7R;^9`9J8R:9<<^;L;:=X?N<9;^<\:\;:=<<8`996X9T;:;9L:`=XN@`?X@V@B\@@=?X?@@@Z>@N>:>P>Z?>R@@>AETEFDCAJC?`C\?Z>\<\=XAX>=>J=>=<:;^?`?==?=N=L>X;V>===?Z=d@?J@d<><`A<==R<=V9P=R::T:9P=^=X;@;b:V<`?X>@P><=<<^>:;^@=T?LC^?P>`>>>A?<\?@@?T@?V>;>P>=T?P=>X@>NAJBFVDZDREEhA>LDXAD\GPHNFDED@XBfCJFbCBD@TB`?X?V?@?H>A@@ZBXBLBBLBXEBBDDTDDXDDCCFVDBLCXAA>AH@AZB??P>ZB^CJDA@@AN?>^>R=:<^:N<A?^AT=L>V=><<^::;=;?=X@=?@^AP=>V;T@=`8\;J<;>V>N<\=>?\>^Z;X;;;9999h9:T6;R:`9Z:8b8\<=<;T;Z>;^:;f8:\=X::P:^8\97\89R:Z;\:98564\7N8Z646X5R545L5^45Z74V5V4455\5j53`41b1X0T4b34P50P11f2J0/10V01L1302V//1P/1/Z00T01b4F12b0/0/T-Z04d1R50X/.b.T/.2F2V/.b/R2.R-T-D-`.-,`/.X-V0--+P+/,f..V-Z/,Z-Z-.T-N/,P,+d*,R,T,+,*P)*)T)Z)b)X)h,Z*J,(F)N(X()Z*T(h*^))*)'))&(()&(Z(N(T)X'('(f&^(R)d'\'&^&$&V&%T(%^%#V$$"X!L$L$\'R%X" !^#X#!`"Z V!V Z!XVZPJXXVTXFVP\NbTVjTZHbh`TRDj P X \ Z b ^ X ^ X Z F R P ^ TT`V^^RZXT`Z^XVV`\Td\Zb`Z`R^\^RNVNTRbZ^`nTNVV^^Z@`^^\``PbPdhR\VVPZ^FdXf`TlTTH`R^VVVVZd^VffTR^\dXT\V\TZd`bVNZ\TJbfVF\hbPXNRnRTd^PVbJJXTXTfPTlTZVP`T\\XTRVZTXRZdR\TZR`XJVPdfDX`TTL\^JB`VTTX`j^bfVRf^\T^TBPjZ`Zd\fd\TZVdT`XRVdRbh^JLPb\X\R\^TRPVPVV\\VNPN^XNT^XRRHXjVdTTRXbTRT^PdD`^VXZTbXLb6\`^\PZN\PHZf`b\NVN`RXRDRNLbTbP\X\ZTRPHV\ZP\XZVTZZLPbXPVRRfNVZbTfV>XLNNNTHd`NdfRHR\FbX^VVhT`bZDhXR\X^VDPV\NRbTNPRT^R\THZ X  T N d T b\ V R H n^`\NZ` hDZLT^`XXTHTVPJ^ZF!h "#!"b"!h!J!T \Z!^"!#\%J$%L&(R(T),Z*\*`**-*+T)d)R*\)h)*N(')P())T+T+,D+X+N,+P,n+,\,b-P/1f.++,V,+H-^.Z--b-/+,\,T--,V+-.V0Z2/43V2\20T20/R0T..`/D.*\+X*+T+T**(L()+,T-N-b*+N.+P+B-V0B,`-++X,R+(+b)X(N+)&B*(P((\)L((^))Z&V)V'T(T,()&(Z))F(*()N)V+V(\()Z(X+'P)V,P,,-*-+++)b*R+,R--...^-F+/-P-+T,+P,,-,j..^/R,-,^..,H..^1H210032f450^5>5473X75N4566R7T95T6R656V7\:8666:<\<:d9V::J=P<<=;:\;X=V=H?>\@>?T>\?\=>=^==?@P=>Z>??L@f@?>@DTEED@DBpDNCECB^DCCXAB?PAEZBZ?T?Z?Z>@Z@X=V=b@R@JAB^D@BF@CBVCDFBFCCFECDBCVC\CVB@@J?=<^@`@fARBTC`DL?AF>d@;=L<9@=h;T<:=PAX=L>b=P@^?N?V>V=b=?V>8==>B=`>R;=^:D9d=;`=h>P>>X?X<=P=;@;T:Z<TBJCJCB^DHCZB@DXADTAVA>CB?B==X=X<^C@A@>X?B\@bCACT@LA?@fD@D@@^CV>dDRAV>LA?>^@<\>BPABJ@fAA`>>J=<>n?:?<=<\:;::X=9F<<7X=;<`<<\;Z;;:V=9:V:^;:;Z;7Z;8:;R8:R8Z98b;T;899L:J>T=8`9T:8:`:V97546;69H9b:X888`6Z7X5Z734X:L5T4P5^556P26334\3132T4b5323325Z40Z000/`0`01/d00^1/b0/0X0-\.X0`00R20f201T0V..+.1j/f0/F0\00.P.J01R2R2X0R..^/T1N,X1h/X//-X/./1/\0+`-T-V-,..R.+,R/P+-+,,+T-,,J.H.h**N*,+^*D-`*)X,P*(\(Z)'N)X+X*`))V**Z(P*X*(+X+('&)*^(\'()Z''\'$%b&&((^'X(%%Z+V%%h%T&$"H#P$f#L#P#$!F"T d!! Z$V "XXX ^\hLX^NPTXZ\dJ\\PXXJbJNf RZXbX ^ ^ V ^  T ` P TTd R VZ J\VhX\PTXbFPPRXV`\VXXDNJZZPXHb^hd^NdTRdH^XT`R\TXZj^XTb^\N\VbRPTNNH^\V\VRdXZdXP\X^JFVVVX\d`^LTT^VZ^dRR\Z`Z^^JXT\VVdTZTT\ZhTnP^RX^TF\NVHbVTP^XP\PbfX^VT\XT\P`RLfN\bTTJLVdZZXV`bJZRfdd`\lLZ`VX`^Z^RXNjPfdb\bXT^l``^H\V\^\L\bRFZVT`R`ZbZDT`XRZ\ZZV\JNXZ\TPhJ^V``N\VPX^PZFVRVXX^`VLbTR`T^PbTVZZ`N^XHfbdTN^R\VbNZ\PLTP^RbL^JTJZbFPX^VX\>PBRPHh^f^TRPRdZ\H:N\N\LdZTVXPPPTVHXzX^ZXZHRZL\ZP\bT`TXT`VTVZTTRLL^\NTNPN\dTHPJ Z P ` ^ P T ` X X V V T R L X T VfTX XP`RVPTR\ZZNPL\ZPRHRRT "!J""!"^#$"#"\!R Nd"P #""$Z*'R*)('),b+N*)V)*)^'H'(P&V)F((')P*X)+,X+,+,,--V-,T//-X--,-+/\-\,T+X,*V-+,^-h+>--.13d1R321^111\2/b/L.X0/^,)Z*)V+L)Z*`*(\)(R))-**b+V,.^.X+^-+*,f+*R+)^)*(F**Z)'`)))T(()L(R)F'T&\*Z(\(T)(b'T)*\(Z(T)*)*R*^+V+))J**+V+R+^,+-,+*V-+T,,*T+`,V,-.)H+-,R-H.V,*X-V-N/Z.*J,R)+J+`.-T.+/X./01N.^3D22/X23\7V123351b144J7337^6N6f96b9J9X9X5\8Z:X:;X:R;:X;P=::;Z:8P;R:Z;9V9867`887`8R74T79;V;`>R:B;V<\;R<;V=?:N;R=R?<\<:X>>:V;\;@;Z>F>AJBFDbA\>N?>\A\DNADXAA>CA\BB@PEVCCRE\DbDAB?A>Z?Z=X@LP=X>>T>?>XBBABCCXBGXA@@\BBADR@CX@@P@A^>>R>@=\?@TAAVC@A?Z?=?Z;;T:\>N:T?=Z;;\<>:H;L>X=;=9H>:J;f>?b?<>P>P=??B^C>Z?V?>ALDTADACPCP?XFZ@^FADDD^A`CBNCj=@XAN@V@<=h;;NR@A?TB<>h@@dBAACF@CXCVA`B`E>X@N@bBf@V?>V@@?V???>>N@AN?^@>>V>=P;;V>=;=;H=P<=f9:<<=;R;P@ZX=X<=;;R>=:;Z::;9:=^;?N;:V^\R`NPfZ\^VV`VFZ\VPhZ\^VNffdR`bPXNbfZHXZVN\VLZX`TXXVRX`TNhVN`hdldVXTJV`\TTb\\\VRThVN^b^XX^Z^HdXb^Z\^ThVbXLXXVV\`^^N\VdVT\TT`Rl\\\PTTlVZ\RNVV`Z\`bNX:^PnPNfP^ZPX`XXP\fDbV\T^\R`fVb\V^X^X^PZNTL^VPNZ^bFbVH\T^NRVL\\ZV^VV\TXRV\FVZ^`ZVPZRXNf\PTd\H^LRVVLZTZTVXNL\\\TPbZRVVXRLPLZ\RdRFXTHZTbTTNPX^LNP\^V\XZPZXVVTVd^NPRX\F\bH^LNVZZZ^RLXVXFdN ` T b ` V ^  Z N ` TVb FV`P PVXP\BZXPFXZTTZVT!! T#T#$R"""^!N"Z!"\ b` !l#!%'^+X'X'()**,*T+`(\)*Z(R((Z()T*\)b)&'`'R)P)V)R)b()T+.0//,,V.Z+,N,X/,^-/P,,,^-***)B+,,V-T/J2P013\//R00/1f..T.N/-X-+,+B+\,(*R+V,F,R*+X+)-J*+-L,T.P.*X-,F0,+b-R)-'++**N*(,'f)R)'Z*)R(T*d)Z)b-Z*()b(&&`)L)^))V,+-+D++`,,X+`.V+++,)-+P+-B+^*)N+F,*`*(Z+(R+L)T(L*X+^*,V,N-*,*+J-.R0^,/,B-X..101Z2Z3Z011L3R23202^41T5J4X5R6332L55b57T7`67Z6V599Z:`8;J9:b=N;h:=89:R:8;V:P:AB^ARA@T@DCRBD>EZ?N=d==J?^A?AdB\@HDVDbCJD@C@B?@\AA`>B??R?J?A?^@@C?d?>@\@\@X?P;<<<;;=J==>^=>b:;T<;>T:=9:8V;J=N?b?ANA^?A^A@`B\B@D?P@?B^@@XDTC>ZA=@X?<;J?T@??=PAAh>CBNB>V@?DAZDEANE?Z@<`=F>R?X@N@^@@Z>L=^=\=V@@\@?@XB`>R=:>V>=:V;Z;X<<=`T=P<<\;;;T9^:R=;R:<=;V9;7888\=P:^879R977L5\7N87555\9F96557b43L44T4R4P3T456H5354b3J3^3^4V8Z4b836V79T75R5`84X7Z5R736`44J676X3h5X4Z43435Z46R4P30121Z5Z3R3\0T24R22X3V3111^1X230301R2d.0..-/2N0N3/1`2T0L./L-`0.1/T0Z20V/Z/.R-V1V./P1/H.T3.\.-.\.-..V02012H./X.0b-012T00-Z1.-....---,,J*+*-/-,,\-)X)Z,)X(^+-T+L**V-/*J+h*+*P*(*)))T&X''R'\(&(&Z)Z'P'&&X&Z)(X&&T(b(&(h'`%X*&`%Z%%&D&$$\$^"V$" N!h$^ X!L!FX FXRVZ`TTZdXv\RRFJ\\ffLZV\ZZTbR ZfHhRVZ `\ Z ^ V X h X X` V XNdPVTXdR^VRXDTf\`jZZjZZT`X\LZV\NXb\d`fXT\XdX``RVT`b^Z^VZNb^P^\TN`NTPXVVRPXZVf`T^N^JVfbFd\NVHlZZXXLZjThR`NXXfdJ`VjjXZV^VJXfdT`fXPP^lVLR^fXN\\hH``b^V\TdLVd`RbP^\RX^X\VVTNbXNH`PZNLP\T`LdLNZTVZZfTXNj\JF`^P\V\hXPRNTdTLXfV\XfZdZDTZXZbJ^Z^NTP`ddjV`XXRVR`JPb`VP^^\XZZZXTF^XRPTVXHbZNVhTbHfTV`TJZXT\RZbXVTZRfLXXl`^NJRX\J`XPh^`Pd`dNVNVRZVfV\\VP^NPRPRPZVb^dV\TZVLPdV^JZPffV@TRTLPTNZXLRZRXdJLTV\\P\^BVd`F\RVNXJVZXN^ZVbJRZ P \ ^ N V R V T ^ PXP  ZJ^VVVJbR^X\BXH !#`"D$"H!\!R! TN !#\%$&X&X&V'('X*T)N)`)^))N(P)'('^','P)%(p'N'T''P(V*b)^,X,-X+b-L+..T-R-.L-.--,\-V+J+N*-R,+()L*`+-Z,.,/-^1,.V/0N2/^/F./H.-++P-X+P-*P-X.X/H--,\)*,+)b.\,T,R-T,-V+X*X,+Z+V-,V+*Z,+X*+N*P)'X(^*R)'***X),b+*Z,Z+)V(X*`)(X+\+,\*V.)X.\,f-X.d-R*+-V*V,-P+T-T,H*'()*N+*('*V)V(h,V*)(N,X-,X.^.++*d-Z,X-+,*Z,,^/-2N10021V13141b26L10T2X0P33Z3R321F22^4N5d6F7Z65L67V9X8\898:6767V87X986R55V654566Z7L6Z75F86H6`6P8\7b799Z8:89V:P7987Z:N68X87J8869\;T;Z88R8D;T:`;Z=:;^:;<<>R>\@Z>RBRBBATC@\A@?AB?@ZB`BjA?R=?J=Z<=T?@>V>=>>>>RBBP>J>RAF>;T;=Z=X;^><;PfZRD^LHV`R^``Tb\ZVZJ^P^RLZXZ`\XZ\X@TT`bZVN`XRT`PNb^TXVXT`XVR\VHRPZ`TTXXbVTX^^`\N\TT\T\VTXRTdVJb\R\\JL8RhZVbVXZVLb^ZZVX R H F  V X V d T j R f VP` V XZ bRfX`^\bRZXdTbNdX#d#"T%V$Z#b!`!Z"N$  T! "D$Z$P&$J'%'''N*\*Z)b+X*Z)Z'^('*X('d(')X&'P''b)f&R'b(\()L),,L,+h.-+f.R-.+,.,,*H+V*+)*)(+)+\,B-*-,,b/f0/-00-/V.,0F0Z-\,d,X-Z,Z0+`,0`-R,,+*)*T*\,h.**Z,J*J*^,,-`,(X+F,++*`)d+*T)T*(f(()+V)+R,,,`))T+L*d-J++V*+\-*,)+.*F*.+T+V.H+P**H**P((+)\,(+*(('*,+)*R,*.R/..`+H+Z.,+,+,d,L-,R..^//1T11X/13^4J3X12h3N4230V2L41f3212T65b844N8`6`9X6X87R8R99B876J4P67P75X66\:^5\64^69R7X;7756T9767N78\8b7N9R677H:79d95L65L96886\7f7T79`>b>;=;?>Z<;T>\?VBZA^CD>X>Z?<<<:b<=d<>T@@>V?@>A`A@\CCdCXA>LCRDEP@AVA\>?`=N?<\<>L=N@?b@=PAL=^A^=V=V;T;T>Z?:`?<\?L=Nf9889N<\=P\<:T:L:T:R:D>X;;:Z;^87`9:88\:;N7Z96977H853R77`84T6V53N4R5\44V4R4`36H63722\2Z1^1Z12P1T454P34X2R3R6\40V1R11R3X6d5364F5`4R34J4P4247V4T74V8L3634221T6\4B42X1B4D24214532X34Z0X/2201X1T1T1X/X1T3\212h1N1\1V10d.J021^02L12N.Z/N1\1/1L0X/./\0P/J0/R1///d-/--V.-\/R/^0V/`21Z//.d.R1/`/d1T0R1N.--X.\../,Z.Z,X,T,+*N*++*V,+T.+V+H-V++d,-++*,+,N+R+)))P))P**D*Z)Z'&d&H%&&N)(&)$%T%Z'\*Z)L(&&\'R(V''%X'#$X%$L#X$%!!T"$d" P"T"V!#!RJXT N NVVXZZRRX^JRd`LZL`lVVLPR`TRVNV`TZ Tf J\ B h Z b R N ^ L j Z b ^ R \  T\ZbLdTN\X\RJ\T\dFJN\ZTX\Nd`PbJdXZ`XPN<TPPVHR\\VdT`Z\ZJV`V`\LTVBb^HVTRXpJLlLVV`VbfH`jd`hRHTRTPNNVRXTNbVhd\\VhTT\Zb^dbXXVVh`XRZJ`RRJfVZ\HRdbFPdZ^\XTTVZR`JbTLZZ^\ZHXVPZhT`^NTZf^b\djPXTVVdLV^XFT`LR\\L\LTfTZX\bNJJfXXL\VRf`H^^bX`NNdb\jP`fJXZRPbVRZfVXPL\RNT`LhNPNZV^XPV\LX`DRNb`VHfXXRP`RPRbHTTlVXLB`ZTF`JdT`RV\bV6h\ZPTPVVRNVZhRV^ZZX\TP\XPZdD^TZ\`PRZJNTT`LN\\R\dLRRT\\VR^jJV^\ZVXR4RNX^^ZP\RbZ\XXXV^\b^dXVXXNTT`bTTVLZ^`RRRXJLZBLbVJ\TTZPJLVT^XbRHR\\L^\PRV^X`XNfX ` Z V D b  R P V ` J L T ^ f  Z^ HZLRTPX^RHV\T\\J`FVb J b"L#!!N$ N \!P$"Z%%V#%%#%X(&`('**'j(''&'R((^'&'&*J%%J%&'N+)(,+P+,X++V...,.-V--.`,R+,+R*)^((b*^*T+V*\*L+.V++-Z//T.Z..0-//1Z,,*N/+L,,,,X.--+T++)T.d-+N,R,D+\+,T+`,H+F,-,N+Z+-P-+d-,)()`*()V**\*f))(X-b*)(V+T**.,Z*)X,L,+))++`-Z+Z-*))L)H*+P)))+X-\+T+V()(\)+V*P+X--Z+\,N.--P--X,+)+L*b..X,)X+V+R+P-f..X01-T.1001^2/J111L1\1R3X325V3T6Z9X5P6d3343V5J9b76R7d8X7::V53^4R5^75T6`;P7P7:9R8X69J76X67655J6b66758<66468F7L;6L6\6X7D66567^6679Z8X89X;;T<=;N;>^BJ@X?Z?H?V?=?=\;T@X<`>X=V:?<=P>>R=@V>P?bBXB>BJ?@@PCPBHCZC^?@^=Z=b=>`@<`=^<>T?@@>XBd=F=^==d>R@<;d;;P:N<9:;=J=>\Z`HLZXLZXbZNLZLPR^LXL V T` Z ^ dP^  l J b R X n N\  T4 \TPX XVF\TJ\\@@XPFPPR`JZ V"`"J"\"b"R" Z "\!V#$R%R$"&%N(`&'b(^)T)X)'&\))''X(%(&X'V(V&R(X&&H)&'\(R*R*)T.`*,),-\,`/+,+/,,-)++()T()X,,)R*,Z+,R-P-/V,\.\//-T//T10V-,X.X.T.T+R,+-.V--+*X,)J+f+R*^)R++,V**V*^+P0\,,L-.D/+F.V,R,+X+N*L(,*-^)J)T+)+)))+*\+*d),**X+b+N(*,\,.Z.*)X)H(R*N(`(\)N)b*T)*)L)*)*)*,*P--R,,J,.,.,)+N+*--T+P-\*,J+*J+P+X--R/./R/V//T-/0/T0Z/01N2T0V3R4423R344P33B2365Z5H3Z75^6N8\5Z5\3646P87\8b6L97J67X:6X564T673\5V5P44\58876V7;6Z9`5R782^552d56Z7^7;P68T98J9:X8:<P=X<\;Z;;;X=f:\:N>Z=:?R@>>`>R?N?@=^?^@>R@\?TAX@PACN?^>Ah@==?^>@\>:T<9<<=Z;:\:<98^9P8P:P9<8;796T76T75`7R872`6b5P4P6X5b3V4433T3P333/`1/22302J/R/22j3Z1`5T13L4P2`41d4Z93N6d7T4b4^1^0X102R3V1L1220344f3L63\47V4342V35\2R2101`4N101R22Z41V4X2V01L301X0/002253/X0V2V0P1R40-N.P/\.Z1311X311P2^/..P03..X.\10Z/.0-2`02R.P/0T/--.V01/3N0R/X10N3P10@/.0-0b/0L0.-/Z/V1d.P//X,V.X,.-./F,N,Z+,X.-+-d,-Z-+,X*X+T,N-()*)**^,R)T)X)(L'N'(V')&'L(%J'&$^(^(&'((&&T&'')%X&L%X%`'#L#Z$"^#"#!!T!!R "`"Z !V\ Z!Z! TdVX@dfLhdRTVX\XTZPZJ`TNbRfJfT N T\H N b T Z X Z V X \ V V \ T V T^Z^PRPLT\XL^RjfVR\ZXP^TTVXX^^T`V\N\R`^R^^bV^bVZ\TXVPZh`XX`f`J\V^Pb`R^PfP\PdVTJVRFZJhVNdRbZV\hbLV`JZjL^\R\jV`V`TLXL`XNNXbbZ\R^TH\JJPNNbT\RRRVPVXRZZbh^ZTTVfPh\RdpTZVL``LZ\HZR\\\Ph`bZRTRP^LNPVBFfV``N\Z^TTNTZbhTNZRT^JZjRBZN\LB`XZXX`TXRNZVTZDT^L``^VTT``\`Z^ZPTX^dLbDZJ\RVPRXT^d`^RN^ffTdZ\^XVX\\`VRZNPRLTX\T\^NN^h@`6RZZVRNPF`F\VZT\`ddPPfJ^ZH\^NLHRRPRXPb^VZJ^\ZZXVRVdPBbP\ZXPZNP\J^PRX`H``RVf^PV`XRRV\TH\R``JJXFVbbZ\d J ^ ` V R V R H X L \ P F RZ \  XX VbT \f\LZ`NNRT`N^Nh V!""#!P"h X! !\ X!!R#"$J##%h$%b%\&Z('Z*L'J*&:))(()%R(&N'P%%T%$J'F(F*P(L)+L*+X*)^+\--^,P-.,.`/H,b-(+\+\,T'(T()**())R*)X+*++X+-N.N0L/.T0P2R.T./X-`.+,D,,`,X,,-+X.R,+d+L,+T-P.)`***+,--X.X-T.\/X-X+V++*\+V))-,R++N)\*()V++Z)R*X-R*(),L+Z+P.+Z+T**R++(()''))R))P)'+*Z+'b*))X*--*\,*R-P+R--B*.+,\,\*)**T,+\+**-\-*-R0P.p.-\/.//X02V40`12Z10X34j63Z4b5H4L3L5X7H62L8X4^5Z5P31`356L66R75P7`544R:V9T::\66b:R53P7Z867P4R6R66f8577\85\76V75331\4T42234X56F8:76Z8P7Z9:;<99:\;:;;;P;P:;:^;<;\=R:9L=:`;X;9;Z>\=L;A`@A@?\=R?>`>T?N?;=X=V=9^=`;=J;:9:V=>;>==L?P<=V=L=R:P>b;7R<<<:D9989P9L:<;X878H<7P9\9:7<8:P::Z8:8686b66\94P5R694445b466144531111/Z0V0^4.H/b0/2R2/\01241\211/0b4P5R5V4b2b5620b3.h1R2P12Z0T11^2X2X5J53R8Z6\44V4X5T441R51R1R2X210R403d2221l32T/0Z0213H1/2N5^44V1J0X0.T2/X0/R/\/R0f0Z1P001P1Z1P2T0b-T.\.X/`2d-,P///\-/0V0L/01/0R0^./.T0`//22N2^131J013.0/N1\0/V/Z/J/b.L0//--\--P/+-`-Z-,T-+,L-X.-,H-.+N,-.-+)T**R,^))X))()V*('(L(Z''')&V&`%%'\%&%V&&Z'T%H&V$$&N''%R&X%#b##P! D"N"""!Z"!L! ! R!H ^ \ LdR`\L\RLLTLN^PVRZbFPJZ\PPTXVPVXd T d R \T \ X \ ^ P J V N V X VZ\TbX^TNRLX`hT\LTX\XR^RXVT`JR^R\ZXVRX`XX`PZZNT^VV^TV\NfdTPVVDH^PVJZTPNX``H\\``\VN\`XbVRjT^PVTZ\RRL`X`R\T`V^X^R^^FZ\VL^XLZ\dFZVXZbb`fZHXVZj^\PV\RfDTRLZbXRP`BXD`ZJZXVfJZ^J\H^`ZRZ``T\P`T^`NN^DTP\^X\XdX^P^XP^\\f`ZZ`fTR`N\`TV\^VXdNTHJRT``NVb^^ZJZ`PfXdZ\Vb^NZ`RZTPl^ZTFFZ`X^XVhNTZ`ZJhbH`\PPRTbD\\PPXXZN^PbX`R\ZnNh`RVTJ\PlP`DbXXTb<L^NPV\dRL\T^VZXXdTTVZZ\PRZNRZV\N\XT^JVdXTNDPHVfFZZX`X\TPbRRTT^T\ZXTXPbf\@N^RX`ZTT R T\ ^  VP D V Z T Z T P   NZ`LT bN^NPRNNTRLNTNVR\R!R N PL"!F" "!f!# T$N" "T%D$$(&+*`&'T'(+((%%&V&Z(&$#&T&'Z))'(h'X*^)P**+-X.T,,+f--V.X/-*)T+R))+F(''X'('^(Z***++^.-0..V001N/-d.`.X.*+..,^,`-`,+.+`+N*R-X-T,--,*++P--.-V0Z-R-.-Z,Z**P+,+-V/0+`*)\)H)X*`*)T*P*R)*+J-*Z-^.,X+Z*X-V-),L)T)V('Z(f)L*(*R*(&'T*X)Z+T+P,)V+`+,^,*.+^-,,,/X-b+*N+*+++b+,F/T-d.N+,`/0.V+2.2R.\/.^0T21`/00^134T53X3\22F2V34Z421120\3b5`37F66`8666585P6R674384\5424R4V5Z4P45V5l7R76N6P8N5P450Z1334214R3V48`4P96X6L7^8Z9F:N:R88;9f>L;N?;Z<:9;:`;:j::h;N=`@>`>P?=;:P;Z;;L<=>P<89H:9;8;95Z9Z:7b;^999V9H:^6Z8T6P7L9`7X5F9`9T8R9;R99\6L85`4`66Z9f5J64^4\4>6b2N5N40\343b5Z4^53V0T/0R0-`0T/..T-P2N0^0R00X0L1X4h2J43P10N4R31V1b1J1L3:2/642N2X3J030V/X//23L4P33b32Z52445X1\011X23X223R1\120b2/F1n2D0L0`411J14^1^111P4`3V2T0P0\/V0Z.P1^0`.T/-\013\3N30-0Z1,/R0/^/.R-..0.X0d.-/P0X/R//\,-1/N10V/R/F002Z47d200\0N110T////R//--/-V.,-H/T-`-^.,+J.V,^./\/X...L..-^,d,T,T.\,,`+\+,)((,Z)P'T('(N)'&&X'$`'&&b'b%d&$$%V(P'b''X*Z('&V%$D#V"$X#b""!b"Z"R!""Z"X!R#B! ^V R@RR^RNhX^L^VThVRTZLbF \` X NP V H X ` X d ^ Z ^ d \ XR V bVTZ^\JPTNh`XVbXLTbLT^jPPZZXXPVJbPTTLDXTNT`PLXTdTTbbNdh^\^X\dPVdVR`VZ^RR\\`JZVb^\^ZV\\ZN\ZbZXR\RRVR^RPdbfFN`\\\RPT^Jb^NH^^VR>VRZXhR^^T^JRXTZZ^D`\V\`JV\ZbD\XNbffRRTTXhNbP\XPhf^N`^RbJLVDZBDfH\VZLdLR\fVX^V^PjNRP\`bXbZXb^XPV\^^NXN^^R`\RPV`TPR\N`VRZbj^XTjh\PTRZTZhZbR\XTNZ\T\`N<ZJ^RN^HPRBT^X\ZTRR^hV^NRDHB`TXbXHJ\ZH^Xf\F`DX\NXVZ^FP\ZXRXF`PTVTR\ZXZjN\\RV`bR^RZZP^X^```\XR\\XPFJdLN\RNfd`\^XNHVPXLL\VjRZR4DVVR bZ  2 d R X ^ j P P V Z b   T XXXVNRVVjXVXPZRb\TX^ "Z!" R!d #`!H!!R"!\"""$$$$&X'N((()()()*'&\'%Z&V%X$\&Z%\'&P&''X&''F+)-N+\/,.,.X,-^-,^,N+Z*(V))H(N*\)((P'H(**F*)R+*--.V/N0b0X01X/^/V.T-,,-X./@/\,+R,V,V-^.N,R+X+P,R-,-+-+V,X/^.//^-X-+J,\,,,Z(N*R)`-+`-V/Z--P,X*V**(P+P)*V+)*\)++,^)*Z*T,R+\*)*X*T*'*\)V)P)P(T('')X++)R+R+,+H/,-V,V-^-\,,P/\,X-.,F)d**+*^.P,Z-D,+\,+,+/,-L,^-1P11X3.^1h1X112d3R3Z74Z33X332f3Z22//R1T02F116@35L5R5Z4N7L6T6L65^65X644h4N6Z6543F55P436664R4T5P64100`452V2X3013265d65`776Z:9978F<:Z::L<8NN>>>TB@?>=9H;^:R; F N X  FFXPLTRTVb^VZPb\bdP\fXXNTNbVLJ^\\XXZf\VZTTTP^\P^ZL`^N`XR`d`JZRRZZ`TXd^HPT^HZ`XNPR\\RPFV`VZXZPf`^VXXbVRbXdPXTZRXV\dTLVh^j^XTNTh^TdJ`ThXN^XRTVTPVXV^bV\V`\bZHNL`VPZTZZZ^\TVh^`bRXPXXhZ^^P^dLdFH`PfXdbZ`nPfV^\XRZJX^RVVVd^ZD`PVZ\ZX\RbhZ\^LPX\N\^XRPfLT`XXNVXpRXZTX`R\RdTbh\dT`\XNTXZP`^T\HZVT^L^ZZZRhRbdLJdnP`Xb\ZX^RZXTLRfZVR\ZHZ\N@PHXZLJXbjV\bbPRNPh\NXTH`\bT^LR\XTXbbPTZ^TVNNX^P`^XJPXVZ\RP\TZdLPPVZZTL\\XVRVPRb^RXP\\T`RJ j hN \R ^ Z \ Nb V T T f ^ P Z \ ^ Z PJTZVPN^X\TVZR^dV^NV$V!!^! ^!P! d X" !F$!d#$V$"$&Z'R'&Z'^''J'`(Z*)\&R(L&`&J'\%H&%T'X'%J*)&Z')d)j**,),+^-,.T-X-R.,++L(\,*X()\+R+b('b)^)h))P*+*V./V./X.L//0.\0/-0--/1-J.+N+V0-.X+T,..+.-T-l+.P-T-J/T..,X0R-X-V+,+T.)`+*+D-T+Z+X-X+T+L+T*T,b*^')Z*T*V)(X),V)\++P*T*T+X,X*)j(R(+H*X()\)*^)(J)b)))T,,,J+L+*P./.J.,/)*V-\/T-^++(Z,+Z*R,+Z+*)P.^+,+V+N--,V0.,,H.P00L3P223N1b2^22132R2//T02H0/P.\-Z1N2364T46`3J6Z64X6J7P5\5473L5n4L4Z52^3Z331X2J4X64J9b3R84V4T4^22Z5\3R30121`21\4X1`4P75h64b:T:896H::N;T;9J:89`9868`::;b<\<>P=;=b9<:X:Z;V>R;:;^9Z<^5P;`8`7P6586V776R96V75T756P7`7L7T7V9Z99N88T75X53R3`6L2X7b50V5V3110312Z50X5T31b/R.V0^0011.Z/-/D13/P./.0d105T31/0N0110R1//.231T200.11P/F0\01L0P20T/b3V23X1`32V2^211d23Z1222114N//L.0Z0100/4L1R10D2\2J1R4231V1`23T31/D1d0101\01060`0T11b0-`/\/,-.00/V0-.V./\31f/V20-.0011^2H1Z/4b342\2L21130b11^131--0--V11T1,B.1R--,P1Z.\.N0b.X.N.+B+N,/L-D+*-X*N,+R*)(*X+T)'T*(`&'b(P''$%T&%T&'h&^%f$V#X%X%($%X&Z%%%$$$N$$%`$T#!X"""#"!! N! !!X^\^bZP\JNXJTTNT`BdTZXTZZ\VNP X Z  P P ^ V \ d h N X TL R ZXDh JbVPRDdRV^N\T^bNHVfZHVPXXPZZJX^ZVRXVRP\Zf:b\RbJZVd\ZbbZXP\VZVRXTNFnXX\VT`\ZTLX^XPR\LR^^F^R`Zd^ZdXP`Pj`bdXT\dNVZR\ZDV\^TJZ\r`ZXLZZZ\XVdZ^^bXZ`Z\\XXRZLRRfbVRTl`\``\R^f^bh\R`\VPN^NPP^Z`Z\d``PDVd\`PbTRZHHXX\N`bbV\`\Z^fVh^JTTZLVdTT<^XFZ\`NN\^\JbTVPfLPZ\ZVR^JH\ZR`fddNfVp\VZDZJbLTrL^XfVbTZXZL`XBdXVNTVNVJ`DPRR`PXbN^TXZ`\bFXDhLTTXVPPdPP`LTXVj^TbZL\LPHT`T`J`N\\ZRHZVRN`NjTTZZRTNNR`VXX\X\jXXH\XT`VZVZNVZ\PNPZbV\bNHX^L`VT^^`R PX\^` f TJT Z \ d P Z N TXb\ V: T TTFBTTPXXV^RdLRT@ !# @#T `Z!"HT d!R# #L#&%N'%L&L*%R&`&'(N'X(&'X'b&P%&\%F&&d&%#R%T(`'R)(N(*)V+\+/,`/f-J2-./V,F+**Z+*T,)^)N)T&R'X+)((V-*h,X.`1b/\.N/T.-/N0\2/Z.X,X/-T-0:2^.N/*.-X.`-V+)*+\*J+f+@.T-,@.-X0f0,H.H.X.+,Z.R,T,++*+**N,J+*b+`+,+)+,N**L+)V(*P)\,(\)*)R+'N)((Z)(d+Z*V*N+*(()X+R,,Z*^+*X,-N+*,-T+,N,b,-++*,H())d*d+\,N-,+N+(R+,+,,-P0-0L0J/4X1N2L52/P43X12V2N1N10R.-0H0b0./--T41`43R45R4Z47X635^64422f220r40F2^1^3b46\5P4X4T6\5T5b4X4N2210X/115^3L22J44N3V56J8X7V9R7F87X87V6R8\98<9:5Z9V88Z98;9X:765R674869J8P;Z;::;L;;:`;>:9J^TR^DPB^XXdZ\VPbVR\NZ\fV\F\^bNTP`JNPjZVZ`NLX^ZVhX^`TVTdb^^TT`XXD\\\\bP\V\DZVRPXNXZ\ZLXRnXZLbXDXV^VFP\XXVTP`FV\ZNTD V ` V J ^ X \ L X ^ V Z T P ZR `XnbVPXVT^VVfJT^fJ`RTZV ^ !R `!R!\ T F Z T !T " `"!L$Z%$'%%Z&V(R$X&X'd&Z*'(X)\'&%&b%T'@(%%J&'L(&N'P(h('d+(N)L,R.P.Z0N-N,,P.,+Z+-R+b*(X)((f((P)\'(,T*T++,/L--X.Z//0/2...T+-X0D0T.,.Z.-/N-f+^++R.0,,,,J-H/^/R0`-N.Z-,H.X,N,*,.+/-,F-(P,,)X+F,R,P+*+b)b+P,j*\(N(**R)+)T)(`+Z')T(`)H)`,\*J*)R)Z)'*Z*)R+V)+,J+*++j++/,*N++T+***+)l,N+X-V,J+*),J+*X++./j.D.d+J.-Z11\4N2L222b22P3/`1020/V.\/V.\-./-/^./.2N1X1N2\54R43`5V6V4P524321^21014X234^3\221b21V1X14d/0f1H/5\5223f320345b3L48Z75Z9697d67Z8Z88Z69Z7f7P7R87V6n576P9X9^4F4L45N5P6^<:9\9d8X8R<:8:^<::8P::;8:89P99858677X7\89T7:89Z:9^886567L85T748J7T5\7T1X24357D5X3F665454F5495N4N75F5d434Z35B4b5J3T421Z0R2P432^20P.+./,/1-,,/.R0-V002.R00.P/T.b0d0V111V43P4/1L./0\0`2/T0-^.P31L11^-V/L/P0V1/11V2R222X204X2F1\1V02T1/50R1031`1D0/Z2R4\1\2V2b1H200^1d20f40H211//-J.//Z//001T/`3.b/--//0102T2R1R0.L/R1100P0000/0V0P11b22Z34P4R12L2J/\2b01^34J1f/^.H0/b0X.N/Z/.T-/R/./Z-R/.-`/F./++N,L-V.,+,+J+T,-^*`,*T+N(\&&&((P'&P'V%N%`&J&&$'V&$N$R%#'$L$^&H%$$Z$$%V&J$$J%$#L#!!J!`#$N  !F!Pj!P V\@<`LV\ZP\XXV`^BLVbZf^DD^ZV L`P ` X Z j N V d T J T j P f\N`JPZ^TbXVX\TZ\VXL\R`bVXf`VZ\HR^NfP`\XZ\V^Z\Zd\PRTPLVRTVXLXP^\XHZ\d\NV^VPdVXV\`^fJZ\TR^f\PP^b\PTTR\^`^VdVZH^bR^d\X^bfTN\XXT\VXhP`NXV\dRTRV^X^\`XbXLNXLbTV`XV^\TVdTFVLJZjdL^TT^bTXb`\ZHPZRRJ`FR\RTV\d\^`TZN\^j`bV^VV`hXNdV\Rf\`R^\H`bT^ZTVbVZRVbJLbVRhTfJXL`JRPD^bTTfZ`XVR\\RTZVRXZ`RZZZPZZXXPX\^TTTZJP\VLV`^TjZNFVZVX^XRLXTRh`VNVVPZ@R\PRXNTD\ZDHT\ZTV`Z\J`PLV^LVL4XTZZFTXZ^\PXXRZZNXTRZRF^PV^RXTVJ\NN^PLBXd\bFJ>JP\VTVLVXVHNPNR^\Pb`VHVP``DZV \ \T Z ` b V R F JB  R N ` T V N RFPf V^RRJHXJLZXNPRRXPT\"b#Z!R!""P!R"^#J!^"H !%J#%#$%J%#T&%(V'(`)(&\)F'd('b%L%%%&$R%V'X&d((P*\**X*+*,P-/,,,-\-+V,+)T+((P)'X*R-R(P'+*+P*-X,.---,0//.X0`/0N.-/\-\.N0+Z,\,,,.R+-.P/,,,,^-Z1-,`1R2-,\,X-N,-T.`--**j+X*J*X)V,+*+)*X))`+')V*)(J*(X,R)*X'Z)F+'L*Z)+Z)P++B++T*V)p,+J.X),,-+,X,R-V.+f.D,+**\)b+**,L*+N,^)+*++R,,V+Z*Z*+d0./P.V.-V--R1T21F/10R101^0X/L/-0-\,.T1N-.,0.`1b1@/1-\124\3N5P3V2b126424V11Z1Z2V0F43R1B2020N01T120h2T120\22X36X4\5542531P4Z4`4b6R5576Z86V5`6N7\7\68T5h655444754V44P6T644d7V7J97T87:7`86\;P:Z689^9:^8N9767678V865^8P97N7`:6P89X76^7J6P5^74L5N5\34H5^2P1P3342X0`212433X34J3Z52X34\36L42Z2V34f4L4j56L3T1H5223V24H44X3V0b210X./,J1.-J-D.+-X,..03,//\/L1\210/2J452V445020.P0/-`1N0Z/d/Z2T1`.D0./X10L3Z2/V401310/1X0201X/V1J0R524110R/0b2^/1.1F/0T1T/Z3`10/0Z21./Z-,^.0H1V01///.0.T1T.22V13R20/0/F0h.L02V3V5Z1b/0.-0d01p222V5d3L1\33R0001Z1Z1X0//`0R2T/T/1R/0X.P.T0/V0-.P.H.T-2V0-X.X/H/V+X-X)++@*+^-Z*),P*X*(^)&&Z%&%'Z(d(Z%V(^&R%\%P'%%%%N&j&R&`'N%$J&P'%$`#"!V#X$V#" T"!!!# R" !L X XRP^NV^ZX\bRjT\PRbVXV\XP\\JVL^NZhXfb X b \ @ Z P V X L Z ^ T V `J` J\V`jPNP^JFZJbRRRVTPVVXPZ`FHP\VT\FdLVNfXRXXNT\ZFNRX^RXZXZZN`LRZpJXb\TXbZ\NbFH\N\^TT^L^VPLL\^ZT\^XPR`NfJ`f^dZVf`HNR\hZZLZbPB\JHLLRX^T`\VZP`XT\XHXXb^\^Z`fZRbV^XRXXXZTZVVRdPXXP\ZX^VZ\bV`V\PFVnVfVXXZZhBTVVdZd\\X`Xf\j\^RJdrbP\^DZ``fXbhf\ZJZ^\T`X\bbDH\XV^TXRXVZZX`R`XRVLRTRZLV^\fNRLjPV\Xl\XTV^N`V\RVh\`ZbJ^L^DLd^LTRfPbhZT`\`PZVXTdXZbHNX\Rj^PTP^T^X^TPXTLNbbL\dPVbVPV\bf^N\X^^XbfPdHZ`ZF`N^^F^RTVTb^P^TbZNb^`Td`XP`PJNPVXLdNd\^VZPZZF\LHZ Z L Z\ Z ^ X b T T Z R VR X\\L``PR\\b^ZVPPPF\VPHV^X N Z"T !\ V!R R!V!T !d  X!#\#"$$V$$%&''f*(^'%P(T&^&#V%`%%H'%N&\$X$N%R&'*((Z*b+*)+,d,P,,*\,*,,f)\-^,)&*)(*&X(P*d)++^-+\,X.+T-N...V2..Z1/-`0.`.-,T-N..L,f.R,.X-*X.,,,J-0\.0+-`.P-^-V+X*-d,N,.V+.^+F-*N))V(*L*++R+()+)h)T)(J)h+R'+R''R()(H(^*,),,+N*'))Z+V(P**\)+T.,*+T**P*Z++T*`*V+\*N*+-J-b+P,J,+-T.+-Z+J-T+-H-h.P.1-/^.X.T.-R,-.N-b0h,^/^1R.T..J0J.X20R.P-R0-^.T1n0H/1./\/N1`24L21000N2^1T5T32V1R2/401340`01-V30Z2V0/b/X3N0V02Z3X222R0V135P32b64X534T5T5T8D667633B3P55875Z55b75Z557454^84R86566Z8866P66457H:785P74T6678\5V86P7X98R966898R7f6P76\5V5R263b4R42h21\3X2202X3D41R1R1T3522@24H5T55R41Z2N4V21X31J3L44422T32R520V3-H0-2B..Z1V,N00R-`,H0.Z-V--.\1T.-P/X0X02//10V2N51^21R1N2.2Z0R0Z.-X--P1/2b-+-/.-`//0/T02301R4.2/\/J0\/N.//0\321X5R1L41R1P1`1./T11/103L2/1X1Z10\2N01^0/.P//V/P.Z0.Z/T.X.-,R/P/R20Z0\//P3R/01J3V3R1L53L3/V11031h2f2J23X3Z22N41V13V110X20^/0L/N/V//f-\20/00.`0-/.`1.V.\.-R-Z/.D,J+X+/+.+R*,,L*)(&P&P'R%&%%%'%X('^%%Z%&H%\%H%#$T"V%#^%#$"$X%#V#"$^#L"$#\!H!R"h$X#T \ X# XV FTTX^PP^XJZT^\RXNfL<d`D\`d ^ ^V^ P  N ^ H Z T \ P b H VTR VNXTf\XXXNbdZ\^^\XZVZ\\LNTVdbTdZNH\JZZT^RZfTV\PN`XPXPL`R`VXdTdJb\ZLZZNnNRXVJhRZR\\P^XTL^RbTXl`\dNt\P^`NR^lXF`fV\RVjZTRZ`df^dVPZ<L`XXJ\dVTZHJTVVZL^NPZHb^PVbbLPJP\H^VZhZ^ZZV^L^ZXJXXZ\LbVNbRPhTVRTdZ^XFLJN^bVPRZRXNh^RVPNdRRTPVHT^bNTZRHV\T\ZPRJdXVNPXb^PLXZRPXVJZVRZ\RR\XZPZdZ^T`V\R`ZT\VJdbLX`ZJZ^XVZXNVZ:^lTTBLPFNR^JZRlXVRTT4bbTR^\\T^lPV`PPTpPNZVR\TLTPRT`T\Z^T\V^XTBVVZXTFVV^RDXNPZJTRT\`LXbX^PRFZZXTZR\^\JL^`^^ZRVX\TRPXXLZ`f^XVbN`PNPf N R H R PV L ^ X^  F X  R NRXRVPTLLTb^ZB^XJHHbB!! Z"b" V!!X bNX HV!\ P"$"#T&T$H%&&%V'Z)(X()%%&V&L&%f%J%%#$V%'&&&R((X*(d+-\,*D+*+\*-\.-R-N+*V+**(*),(T+P)`)*d+N,Z-,T,,--`/P0/^1L2d0X.N0N1N//.+/-L-/,+\/,-J-V.-.N-R./+.Z/+X+R,-.,T,-+,\)^-T+`-R*+T**X*b*N)b),(('R*(*P*)Z*P(X*)\(Z,*\*@*T,(*++((+N+'^,V)X**`,,J,Z+V))T+T+Z)\*Z*X**,*T)d+(h-P,.,L,\)L++L-T**b-D,,-L/^..,H,T-,T,-J,.\++V,R.*R-B0^0,V+./L2^0-,-T/n..N+V/T//./P1H./.J/P.3R22\0^00/P.0H210/P2^0N-.V2/X1T/11R32f.0P/3.b31f0V113R46X46F4N5J6P5N65423H4V4N5\4X335T7R7\35V7P5R65495L64658P8`7N46\7`6T6l2>7565\6L7^8D5^5836`6T6P74^6Z6L74V87H95N443\72`433\3Z3V133d2P02011d3R2P2Z221V4`1F3V35j3^4b2P2321h3N4L0X22L43V2421P34j3.00,.Z.H/,X-L-/R,-J,--/\1h-V,J1^-01R//@0`1R0R1X/001`0/^0-^./1P/.-/-P./-0,---,V0H/f/0`01T2\001T.P3T.01d./X0H13N123P1J30.X/Z//0T3/.J/0./^1.L0X/-X1.X/T1..b/1^./.V//0`,P/b.0J00X2Z1J0V2/1P0V1D0113^2/2Z1P2231T323V1123X2X4T011T0\/11/R2J.^1L02P//^0R/.^/P/d/.N1F/T,Z/J.1Z-/-N.*-P.,8+-,,*()b)H('R'&^'&N&b(&F&%%\&J&%F%R&d$\%$$T$R$#V%R%N%p$N$$#\$Z"$ J#Z""! V"R"X P"T bL jRHL\\PNX^T`ZLZVXL\RRTXZXVRVNX^JVX^  R < J H T Z T ` V X P V  T  fb\RVX\RNNRfP`XZRVR`NFRXLBVZT^PRnJL^\VNN\dRXf\T`2RPNZRJ^ZVfNTT^R^NRTT`LTXXPRR`^`ZdlZXPbV^JXTZ\TpRdTjR\RTTZ\`nZVLFXVR`\\XVZVbD\dPXXjRTVVTdN`JfZbPZ\LjZlL\bX`XVHV\Z^`ZPZVZZN\Z^Z\RNjPRN\b\Zf^``^\TdNb`VhVh^hVbV`dbTdTTh^lJbZTXNBbVXNbJj^lRHTT`\bT`RVX\lRRN^XfVVbZbZZXXNfPVdJN^XXZdLXTRXjVVRT`jPbP`bh`b`\VXR^X\VZ^bX\BTdbNH`RRTTJZVZJ^V\\ZLNZb`^\`ZT\TPbXHXXTR^Z^ZLXXHR\VZ\TZZL^T\VPZ`PZVfTZ`PbTZ\TdPJLHTXN^f`ZVN`P^\\\\L^PZZRd b T V \N  RV V Z Z Z X 8 R  \ L dL dd\^LHTZRTT\X^Pb^VH! VfL \^!R!d \LX T Z! !"h$^"%H$^%N&)P*(R(d((J*)'V'`%h$Z$$b#l$J%$L'H&'%&R')^,T))\*V,Z+*T,+,\.V,*.V.V.F+(^)\)L)(((V*+-L*V)Z+D,*T0d-Z--.f.-/,R/-./T,\-,,.--j-H,.*X,V.,`..0/X-P./J.V/+-,-R-P.+\.*++,*N++'*`))^)`(V'\'^)\()\(\(X(+'**d)h((*V+f*+*,P(*B(T(P+)+\*+R)*`)*F)*))\()D*\*+()d*(P**`,Z+,))\)*V+L+-+*@*-Z.Z-R.P/,N,-^+,T--,<,,+V-+X+R-,.-,.`-,P/,V0\-\/^,R/.b-N-X/\-.j0.X0V0V/..T1h1.\1/\..\/0R0-X/T0P///`/.R/\/3T2`00/.-.N0X.R0T.V31R333N33d2T2X56V4R5L2J421Z4V7V77V7^65X85J748X56457656T79R6R5X6R63T647T644P5V5733R12V4X6^7357Z3\7V5\56R76P6V8N65X64\2Z4322R53T20R34100321011V31Z0b23010\32X1222R5445T32R3Z4/L41^/\11P1,X/*P,-/,,+V..,-/.Z,\/1.-.Z/h/P0Z/0d/P0F20d./P/-.T.1^-\/Z0^.+j+\-,+d*-R-.,f/V3V/T0X021L1`2\4f3F1`31^1/V/2.\42Z30`2P3X11T.Z02P/^///\./1-b0^0-b11Z./^..00N/-^.n../^0\/b/@.h11X/1X./^0R2N4V2\23P3Z1L32`5V211Z4P22211`202\425X210\3X0f01V020.^0\1.\0R/0T0/T1R0T.-.R/.V./Z/V0.f0T,X,.-\,Z*H*)*T*'P)Z)F')('&T%X%T%$%P(Z(V%''&T$J#V%#d$$X%%J#"R!#V#Z#R#!T R X!"V!!>!X V!"NN T @L^ZTH^ZXRPT\LNBV^JfV<TVZ T^TN ` X T Z f P X d N ^ VZXLdJTLbTX`\`LVTR>TVbR`VdVV`RRXRTTVXbV`\\X``H`FdRRHZXZNVJbXLP\ZV\Z`^^RN^^``Z\XNb`X`X\\T`\L`JPZ\Z`^ZXR\L^\VZRXNZ\bZX\Z^PXRX\dJLZ^^^JPTP@^XHX\ZVN`dHVJJVZdV`XXbT`Rh\TJZRfXdZNbNFBX`^ZVfXDPVfPNLTZdZ`^L\fV^^T^pFXR^RfV``P\TXT`fXL^PVPXT\LXRPZRZZ\ZbNVVXZbRhFRPHhVX^NXfbZVZNV`^VPZTTL`VN^FZNX`N^HZ\VHjXF`RRRRLXVTN\^^NTZR`XR\TRTH\\^TL\XBVPhNLXL`XHX`bVdTPZXRZP\XFhRHP^L`P^VdRVb^VLV\RdD`ZNPRb\PTPRJ\NTTDF^VLV`bVR\XZVVZbT T R V X Z L df X ^ J P \ F \T ^ ^  ZZ ^RZVTZdddVR\TJLVT\HX  X Z X"J  X!NJTVP!!X#X"\"$Z$X%%&('(Z(&&\&T&P&L%$\%R$\$$$%#L'$%`&R&b'Z)\)P)N+)+*R+)+*P-+P*`+P,b,),**')+R*X)N+^*P*)R,T+-P.F*d.T.X.,+--.X--`-X/..,-T-R--+V/+,*./B,B/X.R2-.V-^-.h.F,R/-,,P+V,X)X+^))N*')T*R))X+((&Z)'P((^*'+(''L,^)))*)\*^*F*J)()`)L)d(()X)(L'''N'')f*X)T*R)N)L(f+*(*R+++\+T,T-,,P.-.*R-`,,V.`.,\.+.+,+,*R+Z,b*X+b,(+--,P-P/P-.P.+H/X.1/X/-.,-V-P,^-\.L/.T-+,-P0b/-R.Z/0\0T.P1f/1-\...\/0/`00^10,0/Z1/^00001X411^2H31V1J12R20^4T12^5&2V3Z4L5d5J64P65R66R45V64H5V757566\6T6555`67R4T24P544L5Z45025T56566^43L34H547555R5321T45Z522T320020J10L122`0B1H1`0L1Z2Z422^10D0R1P10/3R20\1L31.1N/T2V.0h.//.b.d/0J.,.T-*@..N,B,T.b0*\,T/T.-N.,X0V-L0/b00./X1.P...^0//L.Z//R0T/^,X-J+-R-b.^)R,\1./0-`/2V/2,3Z0d2T0b2L010Z-2/010R3h1X3103^0V011P1b101T.d0V0`/V00..H.Z/N.^..R1\0N//.H/L1h1H1\1N100V0b.1P212410/2L5V321d4F1^4T2L4Z2X324N22P4132d2R2H20/0F001T1b/..+.V/-\/11/X.d/^0/.\1/R/1.\/b,,-R.^,^+,Z+)+(''(+()`%%&%T$%'P($d&&#N$%X%&%$R$\%R&!`$##F%J#P#^"^! ^" "ZTd VZ dTZdD\ZVXXZZRT\R\VP`VPJfNDRT`^VB\ ^ TT LR ^ R ^ V N H N H ` XP \XN^P`R`PXRD>bVTf^`NZ^VLRHdHjZZXL>hPbTTdLLXVJX\LTZZTPNX`V`TdXPHTLZZhXddRPXHhLZfPdBTZLPdZJ^ZXFRbXXZLXRXJPX`\VfTbX`VP`PddbXTbPXdTdXLXR`\hX\TbPTX`RbR``fRT\`VbZNXXXPPbJfZJdP\jHP\R`XTBV^XbXVZZJRTPXX`bh\NjRZbVhV\RjZR^P\RhhbXTZhLbdddDLT\\^P\HRd^PPXFLHbTTT\^`RJPX\T^R^X`jXRP^XT^XX^\\\`\V\ZbdXfN`bjZbPN\ZdV`\V^RRVNXZ`TVNXPlVRXhXL\RVTNf^TdP\^RZHXZ`PV^LNV\^XZVXV^`XTJ`T^T\VXRZ`LRJb\RJdRbVZ\ZZRZ^TVHJ\F`TfTT\R\pXXLF\X^^hZLX`JZ\TT^RL^ZTXHF X N  Z ` V ^ H P P bX R\ XVTXZJNZZTJNHTPPXR"TZ!N j H!^!PV!ZRXV ! V$"$X&P#d&'('(''(''Z(&V#R&T%$$`#%f%h$$$\%J%T'L+(')')*R,f+**N+J+(+-X,))+)J))`+V*(L***)V,V*^++N.,X-.\0/R,,T,-L.-+,,,-L0-,.^.-,*-+^.V,-V.f0..^.X.,Z,,,L/++L,(()^()(T(\(R*'b)'(\*''&H(*b'('L+b+R++)d)d)''^'^(`)((d'd(Z((Z)'b)'&V(l(&(V'&T(X(V(')V()V)+*X++,J+*R+X,X./R/-/,J-p,+X.*V,Z+)\)*R+^,+,R*\)P,-*b+T-+,N+*T,+.^,X.h.V,d,.`-V-.\-.T/P/\/.,-X.-.V/V.^-+F-\+Z--N1./L0b02^0\/\032Z//0/Z021-.2/\2/01/00V3V/0V0.X3J32113^3X4P8`65^5@3F77R46H5\6X7N6N6`7N6\7H6Z6V35T53P5T5\4J4b5d73P5J634^1343b5J6`856T7534R8P65N3b433V2/1V2\1V3X1^00032.T01000H0J1/////T11.2.Z.T1T/.1N3V515^3102X-Z./1b.0/\.0.-T-,*-R+/\-0P-,N-.T/.-,-X,0.1T.R0/0L/N0-R.d0Z.,J/`.P/X,/,.*`-R+J-N+*D3Z/N0.0X.V01/33\10/0N320J/.N2b13`1P1223^/\21Z4b.0\0Z/X1P1-`.L01Z/-01T0.V1./^0,.H0T3V00///V-\/.P/03V1\1X23X0J1T431^6J1625\4T23B533X243`4T44^3V1F1T.0/312X/J/00/Z.Z2-2V2T/X0F/0Z.+^0R1/Z3Z0X-.,P/++,+\)V'B&X(+\)(X*\)X)H'&\&^%N''\&V()b&^&P$n#^$N&$$##X$P"T#"$N%\%P$"R!"^!R"Z# Z Xh XTXJH^\R`^VN\VZ`^VNTRRVfNX`FN Z^JdPR` ^ b Z \ Z V X `  ` J f^bPZTTXJ\RVbZZVN\JTRX@@VBXJdX^XR`\RRh\VRd\PJfH^\LL\`Zb^T^R`^VVVjJfVXPV\PRX`V`LZF\`bP^d^\bNTRPVXf`\L\TLVJVZfTX^^PRZV^dVTRTZP`XbZPZ^PTZT^\ZbVXVRNNRJLRTT`TP\RPRT^bbX``RNVXdZXXZ`T\fFT8DPXVZ\VfT`LTJbZPRR\V\TXZDN`XjJbZ`VbJbfJVPP\LV^PZ`^T^R^VRPZ^NdZVTbJ`T`ZXLZNXLZTXTRVXZ\D^XZ^XJfNh^`RR`b\`ZVdVZ\V^PVXJPRZVNVf^VVTZ^^^TbXZZPJ^R`RT\TVN^TVbRJ^Xn\ZZRZ\RL`X\VPXNRPDNJVf\NRXfFLjVVRL`B`RXRV\PXZ^VT`\RLTVXBLd^\F`>PhZ@VZ\L^ TZ HT  R  \` N T H ` V N P P ZV  RZ N \ XN^R^LPbVVRPZdVTPTNV\V! !"T\RZN`TZ"! !"N#T%$&*L''R'V('&b%b'L&\%N%`#%\$$T$H%P'\%Z$T%$d$b&&')''(Z***Z+**V++.-F)\+V*V,T+V,(T*),N+\-).R,.`,++,+,/--,^0.X.\-R/^0/P/X-R-,-,Z/T,,V.^+,,R-V.-.D-^,+h+,b.J*Z--^,V))`+J*^)R)`+))((X)'((R))'R*)N'N)P)(Z+*,)B('^)'R+X(R*`'P)L(,*P)J(X*((N(('&X(''))R*N'*(F++)^*,T,,/---,.J0,L-/.++)**X*)F*V)R))Z))+V+),++X,N.N.<.H./J.\+h-R-,^,,V.Z-,,J,,+R.-N--./-\-,^.+-,,-P,V-F,^..V.T1\/V0Z0/0Z0-b/-0L1\0/0/N12R03241V2L1/^01`3P30F2N1P33Z54X64V5N4^5T5^3664R566Z534R55H343D53226N4N65T4f5T2R2445h38N67454b4474L3V4Z33Z3\2N12`1R20^0T0R014T/N0T2\30\1R/R/0-/21/N0N0/f0-0..P1b1T12Z343N02-P.-N/T/1,-L0Z,0-/b/V,Z-J.-.X-Z1Z-\/+-@-+`.--/-V.0-P..\0>/.Z0-.N.-,^.Z-P--\/,,V+(N-T+\-,Z3/N,Z/^/f0/N/1/Z.10H/P20\311^02\//20^4P32H4F3J221/T0/1F.b./h32V/2/.L0\1\1/T//\./02T0/`0J/^/\2.3^30Z41`1\2^2435335232N3\3R44X83P3X631101/1V1J30F20\0-.`-Z.N/Z//.0R22J02N.V0/0/0/J/---X,,-`++L+`)T*(*Z()X*(T((P'b&Z'&&V(%&$T&R%%N&V(X%R"!f$#"N"#$#X"" ^! V X!d ZTZZ`JZbTHb\bTPH\XRPXVTXXJZPLVJTfTVJ`XFF V P J b X Z R R ` f ` ^P X LZ`ZbXTPVRXNHT\LP^J`^ZV\VXVR^^TXZTNjP^XTTdPZXZHVXJV^VTPD`R\`V\PVVVZ^f\L\JL\^\\Z^jL^X\\`PhbTNZhVTZV\`NbdZVXZ`XPbPP\nBVLZ`X\NZ`LVTF^h^`LVR`XR\LBPZT\VXffN^`^RZ\LbZdT`Z^JZZ`T\bDlVTVhVX^^LVFVN^Z\TTfLXXZN^XZbRZTP`Z\NbPZV`XTRZhJ`P^bhNJVX\PbVRfZdTZV^XLhbVZfRF^T\PV`X\V^\VVVTfRP\`RL^`TXX\ZRXVTXPVFPJfNNTVRLfVdTZR\\NdbZdbX6f\XRNVXPFZ\VP\DZd^dbRTXZ^```RRPVPdJbbPVRN^TJVTVZN\DXVbFB\VV``V^V\RNPRJZTdN^Zbf^V\dRZbLNL`XVNfX<fL\XdRJ^ZHRRZ V ^XP \ Z P N \ FTRHdR^LXTH\bRNNN` T^ ^!db \ ` RTTF \! \!T"X"X&'$R&&Z&%&F'L%^&N&%$$R$%$^$\&$%$%&b&$d(&^&('V*T+('+T*<**-^,d+J,-X,)^.d,Z+X*,d*\))Z*+V)H,V,P.*`+R+J,,^,N/.\0f-N2j-.X/R,R/X-Z////,.H-`-,`--Z.-+^-X-R-T.+,P-R*,Z**+X)h)^*N*)`)P*+)(T)^(H*&l'T)\*P',P)\)\)V)d(X*@*R+X+(^*^)^(R***V+'d*(T*b*`)*T**((^)'b'&R)R&()R(*J,^*))V++F+Z-++\,Z*-R/--.J-+,**T*\*T)((%X'f(Z(Z)(+^,)+`-@-f-0b-0,^-,L---+P,L.T,,^.*+P+`.\+-+,J.L.D*),d,b+P,-\.Z+Z,b-^,Z,,T,./-J,L/V-.X..--R/.0Z/V/f.N0/0122`00`31T1P0V1\1R42354^755V5V8Z5n576^536X53V4N7V232^2V1213121b3J2N42\22R5334453X34133V53X62^42Z4T50T11H0P02l00V1/0\131F/^0/T/N0./b/X20X/N1f0T1D/.//0@00X6D223j2Z.D/.X/.//b../Z/>,L/.H,-X.,^-^--L.X,-b-D..+Z+^0-V,,b.b,-/.-b-L/-R--,`/V/Z-d+T*+N*,+\)b++P,X.-H/2V-/N2P./X1.V0/R2b2R3b3R3V0V00F2/Z4`12036X330B1.-Z/N/,/0T2V1\443.L..P.P0^//V/1X-^./0N/-\-R0\/223V411b21X2`23T4`33H3\32`3T2Z2L24X52R347T4R6N6d3j1^0`1J2R2d122\0V0V,N1X/T-0.0V1T31N0J.0/R0//1V0<.`/V-b-,R0\+P+T,()\,*L'F+*Z(('b('&%'T'`&\('T'`%(N&(`&%\$V#V$$"V##!#X!"!!!V"" X P X X`V\HN`VVZTPZT`PZZ`\\dd^VRZVJ^`NRdR\T ^ < P V X N Z ^ V \ ^ \ R^^JTXXdHVD\`NPXPRbbjT\VRPZbPTZ^^\TPZXXLV\dNT\F^jP`TTjbP^R\XVVPTRR\XTPZZ^VjFTPhNVX^P\RTP\XT\RRZ^VRVPdXH`TLbVNb`VZV^VRRb^TR`LdPNRjX`LV^T^R^ZRf\X^ZNLdRH^VdLXX@N<RPZX@jPVVPVJb\dVf`TXb\N\RZXXVNT`VLPdV^RRT`^dZX`\XVXhh\b\HZ^TXJ^\NbT`PJTZ\d^P`\XV`XbZ`ZVVLdZTT\``RTZ\`ZZJJ\Ndf\bXVPTLbHNPRVTZRbZPVVZXPR\Z>NPhThVN\dZXXHXVVZN^XNPXVNLJ\^bTLfRXPP\PZ\F^PJ`ZZZZTZ^`Z^\H`XHVdXVRZZNXXRLL`RPRHVZH^RPXP\LPF\Lj@\\TRR\`VTFXTNL\DdT^PXXX^L``HPPZHDV^ h H\ Z V  T V J ^ ` N P VVXXTZJ`DTTbZ\LFT^RV!R!X TPfb\V<VV !"T$P$'Z&^%R)b%P*f(L&V$&%Z$T$%P#%T#"#$$$$"%H%$%X&T&f(:*V+^))`,))+-H-,P.f,+N,P,J,X,Z,\+,\*+*P*)++^+F)b+T+-/^-./f.0V12..P./-.1^.N0,//l-.-/V,,,P,,+++\/*)+)N,+N*+T*T)T+')R+('h*D()X**\((*L+X,\*('\*V*,f)N,T*+T*'V)Z)J*'('(^)()*P(((J(T'P()R'V((T)*T(*^*+T,R)F+,F*R+N++)+,P.\+-V+*L*())V(\'Z)P((&X'')D*P,*f+V+X/.+//+,)+N,J+Z+V,d,^++^++)+L,,)V+Z++T,T,**,R-`+Z,d--.J+P*R+`,N-,T-,V,X,-D.d1R/V1,-.R.0..V1Z0J0X0V0/P2/H2`2N1b316R54L5b553^4X777F5R6\624P4T5J55P5^412H3V6P4\3L41L2T012040`443433d303J22233R234d15`4Z2V00T01R1/01/2X/d2\02X01/N/-\2-.P-0H/b/0///2V1Z0f11P/X3J1\301Z03/R3.X0J-P/R0.0V+.+X,+P,+-^/X/,+H/N-T++f.b-V-N-L,V.*-N,,T,,N.Z-/,+-X1X-,Z,+P++N,,+J+f-V-,X,T.P/`/V.`//1V0-Z/d/3X21401\2b0T1P23013V243V41X/.Z.X/1//0\51P0V1N/V.0X3/X1J1/^01V/-0/T0X01020R2123b1T2`10X45R4R443T4V4V631N3Z311T333V43P20X/b1303X2J220T2@0/^00h00/P10X020d0N11h/1/L.-^-.X,P,***+Z(X))()\)X(L((N(X(&''`%N'V&`&R%&'^)&%^&$L###P"X%!!T! R!!!T"T T! V\ RR`BZ^@XLV^XPP`\HV\VTVNT N\ZR>TT  ^d R D f J X d b V ^ X X ^ X R ^ PjDTLf`^TbJ^ZVRRb`XL`ZXL\V\BVZVTpbRRPNRZ\Nbb\VNXTXPhNbJXRPbR\JRbFdZ\ZRLRhhL\^JXH^X\LPPXXXZNPVTHNRXN^d^XVPVX^^Rj@\H^HfP`fPT^LTP`ZRVbTPbRdX`RLVV@`JTNJ^b`VH^RdXJ\nHLLXrZ\XDZPVRfPXZ^PPX\TXJVV^^LNNXR\Z\`n\VXThfV`^RlHfXZ\dLPD```XVZJ`RTTNlbJ`VDFZP`TJd^ZbhX\PTbNPV\NZfF\\P\NPj^\N\`LT^\XZPZdRLbTPHXLZVjNdXTTd^RZLVFbHV`HVX\bVV\^LTRPZ`ZbVbP`VVZVVVNZHTZXZZPR^^dZJNRHL\FT\PR\^V\dTbF\X`ZTfdhNV6`NRN^PJThZdVJ`b\ZbTZRb^PTZ^ZVd>VZV\jPZZ`VP j b  ` X T  f \ XN  \ RL JX^VRXPb^df^J^X\ \^!LT P N^bdP `"H$%Z$R(\&'\(^&%%V&Z$%#"&L#$%#Z#F##"b%##F$P&L&f%P'V)()X'(^+b),X-T.X-X-/+^,,f-L,b/Z,Z*X,b)+*T*@+R+*,+f-b+b+,R..`.R/J1N/Z0/V/.--\+T./Z0^2/R//1-,\--^+*H-P+X+,+V+V+N(,*T***V-P*\+N*\*b(+h)(X(T,`(X,L)(((+())X)V)L()b)Z**J)+((Z(P(^(^)Z***Z)'&R')P'*X'X'X&'R*Z*&b*'))+`'*`*F*Z++,)R+b-d+-J-L*d*V+(Z(H+))R)V(&'R'^))R)T,),X)H,,,,\0,T--R-+\*f),**+\)***()*))+*X,h*V*))+V)+T-,+V,T+-.+,-T.^)R+H-\,)+V/H.//,F/Z-V-Z//V..R-0/J1X11>121\03V2`6Z54b5558P5^8L57T45Z746`7B43N23Z63P231\1\2X00T24Z2P34242\2^20/0Z1Z355@2T24h1R3V22V3Z1X4/J201^0L1T0P00/1L0X31T//0X2./J0--H,/0/Z1T02T11/X2/10N0b2N1/H3`1,-.V-T.+,V0V+Z*..b,P-^++*T,N,+X,N,^,+-.d-+.`.-T-Z++V*+X,Z*-*.*\,X+*\,P,P.d.L-X+V+V.0V..0\/-\.P00d3/L0^2R13\30/212N123P4P2\2132J50P0.0-R/\/N0`/02V0022X12`22/@5X4V2R202Z0N2T11h4V31X3b4/2013X2`231465130^1X113b1\423\5N34T5\0034T23235\0/1/1`11\/\/V/0f21V2/`2/.`1//^0X0,h.P.+)R))***)`+(T'^(*('T))&'N((T&N%^&X)'B*%T%V#$#!#!#V"X"d"> !" !H!d!Xf VLf^DT\L\@L^XRZTVRnP>^P^H^PXZ X X ` L J X h X X f T ^ X V ^ P R X T L fVb^PXNTXTVLN\XR\\FXZ\\`RPd\VdT`Z`^XVPP\lfVNNXbT\bbfDXhN^fVDdRTRZ^XP^`PP`JXZV\bbT`XbZZX`bpTbPZbR`dZZHNbX\RT\ZR^ZVTD\ZXZVVT`RJDVb^^^TVLTXTR\F\hN`XbXhPXJZ^\VLbNXbfXHZRTXdNVVH\:N\fZVbXJ\jZ^^XLbb`^TZR^dfZV^`J\L^T^LTXJVV`JL`XPXlVP\bZNPR\XHbF^``\NZVV\XVR\\LdZZXT^JHVRLVPRPVb\Pb\ZFTJP\J`V^XX`ZPZR^RR\RX^TPZZbZXjRX\PRLTXdLRbDPZ\NX<`NVPZZLZVR\PTDB`\TBLNTTRRXBPZNL^ZXVP`TVNV\RZZ`8VT\N\HhTTZTT^ZTb8JZV\LRPPF^RXNVfBN^VTPPXJVJZN  P Z RL X \ X R T Z L d^NX R^ V XDLNZVT\TNFZP\hXRbN NRT`PHdL^TRH!P $b#T&$f'F'\$H)X(&$##X%T#V$B%\$H%`#^#"\"L#T$R$X#D%N%%%&'(T)V*)P**+N,,0-V.X,,-T-+T,,V,X+X+N+T,(,J*^*R*,*H--+f0T/+1h/V/-X/J1X/V/,V.b../1\/J1.,P1V/++P,R,+-T+V.+\-N+V)+)h)R+-*+\,V*D)V*H*Z**'\)*^+)(P)Z+*(')T++*X)R(^)N&('(T)%'T'((*`(N&(&^('\'T)'N((b(V'*P*',Z*J)\+(b)+N+**T+T+++*()N**N+*(&(\*R,'(f*(*V)H*(+P)J(*+b+)Z+V.T+L-J,+X,,*+P*^)R+++*P'+)f)d(,*V-('')V*+V+b+T*P+++,F+,d***V+*(++V),,.,d-`/J*Z-Z--L--L/\0H010T4T3J3L6V2P2Z01Z4R5V4H54R4R4`5R64N632^4P654142223.3/`/R203V2R224`25N2b31103P433j61N200T4T2H23`2000\0//Z.0\/T/2X1`2.R/0/\00-F2b-L/X,\/./T022l0\/.--/.\0N1.Z.T/J-1,,X,\-d.,^/N+`+H-\+,N,**)^.Z.,*J+f-V,**J,+**X++R**)-,T,T*+-**(T+,^-,R-\--L-T0H.^/T.^/X0J/T2V2^.1/T0Z3Z211X1f10V13^22V2V3T2V210L1T410.N/^/^0R.J-,0`1\0T203413V2212X11200N031\2f4X11300V0.X1X22F6^413T4\12R213^1R1T4R511421`11P0211P33N/\1210/0L1`0/V212^30-Z.,T0b./,`0,X.R-.T,*)H+*X*`)'(&()(`*((%R&T&f'%N$%&d&%h&b$$"R#V !X"L# ^ T !^"d! Z!V fd NT`NTFZZV\bbl\ZRRVZ`ZJ`hNJV`TVT^@ Z X VL V ^ h V Z R R X J \ H \Z R ZP\\^ ^^TJ``XL\RLNX^N^ZTNV\VXNTVVHVhR`RTVTXXbDfRVRTVPPZd\ZR`V^XXZRR^XXZVN\f\J`\VLZNZ`TTRZTTXJZd\\`Xd^f`JT^`NJ\T`RflJdZ\\XR\DXJdX^^lXXFdZN^TVXPZPLN^bf^^XJ\PdNZZLfZRVXRZXLVHVNV^PPVRXT`TZ\L\ZZPX^RRbX`\XZZhRXjH`RV\ZNJVZJbXX,`XPDd\TT`ZfPRfVXVdTZZ\f^hJfRXR\V\dd\P^\dVdVfXbhXLR^ZVZXXfZ^TJbXPVhTZZd`XLbXdX\HVZNLfZTL`N`\\R\X\TNZZ`X`VVLVbZV\R^\`Vd\ZdPZTZ`PXZVZ^d\T\HV\T^XTVb`LXZRXhXT\bTFTRV\F^ZTJ^ZBXb\\\TbFJ\JRRdNHfNfT\V^PTN\^JZVT\X\XdNZRZjJ^FV VT` R ` X ` \ N V VT ` R Z H`^TTP`^PV^\L`^XdT`RNP\Z^\` dH\PR X #^"N%V#$%%$#'%Z&L$d$$"%%"V##T%F#"!H#T#\$$%V$V&&b'R+P)b()**d,*.Z/0*+F,R.`,N,)))+*))P+)+P++,,\,N.-^.+X+P/-T10-/R0T//-/V--R.0V0X.T-`,*X*T.R.P,^+Z+V+V+*,T***^-H)h+,$++Z*X+`)`,T))X+`)X)V(*(N+J)(*+)L)P)Z)*)V*^(>*T*F(^*'T)T*'(\('(\((X+(',(P)N*\(*(*'(),`-R*J*L)+N+,)+(++\)*Z*T*(*R+T(N+&`(*(V*)*('H'b)X()H*)V,b-(+,*,*d+*)'R+*(V*X+P())'%'V+R*(X*N+(P((Z)J)T*N,(+T*V+X,-T,'*(X+\*(^*,+***,\-+:-R,X.Z0.0..J025T2V020H04Z035`75\34H223b4N1T422R3X2J2233/.V/0V//20.3J21b121`01^1D4^3314226V2X.b1T/\1T1Z11V1111`/01P/X0//Z1X-0R.d0L0V10X0R0/,N/\-/--`/J20J.\20R+P0-T-,^-/-@/-/-V/,T.-N+,b-T(*))P+V*`)*^*T*T(J+)T,+(Z-^.X,**++T+J,**++-,)+V-,`+R-T*/N0L.f,-X/T2N1--1./X/.12\4L30001`11V2V13F212^023R0V10Z11T1^0X1.0./`..2\0115342b52^1f2f523R1<3P0X2211R1L2\1/-B00T2N2650R2V31\2T4\314\2422\33`4X2021T4T13P3X1J2\21V3X10V0T00N/00^/T1.+0`.-X./\/^/F-,,N-\+V**N*X*,f)(*%%)`'T&%&V%%%$%Z$V&N(($`%$V#!#"b"b# h L$ D!R!> @JVRNJ``R^bHHb`RZ`P`R^^ZPHLb`PXZZ^NT  P ` N V X T P P N V P X X X Z Z TZ RXbTJZXVZbZJR\X\\NTZZfb`NZbVbNTZ\ZZNXVLXX^VZh`dPbbZL`NH\L^TNjXdb\HlT\LXPZ^LXdTXTXTXVT^fXXbXNJZVdRbTXLZ\jZ`T`\`XL`VXVXZ^NZ\`X\f\ZV^ZPP`dPXdVVHd\LL`Z``VRXTVXXdRPbZ\DdX^NVZbT\V^\T\RPb\BlVZb\LVfRbNT^NVXRVVPf`\TJRbZ`^^RV^NV^^\V^PV^Z\XZ\TVPRXdHT^X`ZfT^ZXVTVXPPRRHHF>dJZRTPVXT`DTJjZVRPZRZTp^P\PLTVP`P\H`LZNZ`^ZVLNLbNBNRLLVZLPZPdPX\JXPJjPJR^ZR`R^RJRNZH\XTZ^RLRXjX^dVVDVX\L`\TV\TLPFTJHb^TdRN`NPVXHVVXR^`fX^\THLRRVVJXX\XdbFPfLXXJH\bZ\TbZFVLXRRTRXRV^ZZVVdjV N PT^ Z d P ` @ b N X ^ T d P R LNHVVVZ@^X\XVZNfZT`bDbZ^bT XT ^Zd^T Z!H!#`$%%$T$T($^$$$R##$$"$#V#$##L#T%$d%%$%N'R(d(N*d+V)*T*,^.b.\0V,.N+Z,+N-,)L**+\,H--P,)T+L*`++^*-\.,Z+,/N1X.-00^0/R1V.R0^0/2X--V-,-*T+D+\+P+++X,++,V+T-L*P+N+T+^+,*V,\)Z),X(+()P'N)`)L*Z),V,+^-L*\+Z+^-N**)(L*P))()P)j)X*(L()''^)R))(N)B*X)'X+V))V(R*D*+^,+b)()Z*X*Z*T)`*V)V)^*`+P,+V*X,'-*))R+T,b**()(('X,N('P**-)+b)V+N+*+,B+**Z+N+h*(T+X*'&(&'X(()<*))N*'H+R()V(D(b+`)^)+X*)*(L)f**^)+Z+)-F--*,R+\,+,-B1Z/1X/N1V0L0P1B201\/11R41N4215^34P5X43V3302X2N01P1P3/N0H.0P2\/D0f2V1J/300^1/H2Z2P1d11T3/L011F4L4V.N0V0N1b02/b/0/X00,^/N000Z3T/V-b0V/Z.B0Z/1b1//0/Z,T.+-V-D/X/P./+T-^,-,+-L.`-R,T,X,R+@.J+/*`,@*V*P,d.N)(^.)()*P,^)))L*)J*'T(*+^*P()\**+\,T))-L)*T.,P-\--+T,^-.T./R.L/X0P0V00-0H3.1R3V/L3N1.X/N/h0V0/Z322/\2000\0V2R1B1101f1--T/X//-L130V3V2T21Z315J3f5312\32L2X2/1V2X4B201032R1L421N3T1V3R624532H3V51\413V012P22/\3L1R20T1J101D20L2///.2.V/.-Z/,.-\.///d+L-V+N*N*^*T+@+*b)D&%'X'Z*'P(%T%%%B%\&b'N&'&V%$%X$L""R#R"X#Z"V#N  V NR!P  Z Z ^LTTFDbPTZVRXPFXjZ\RfVP\ H ^`VX H H Z X ^ N P P V R V  X \ J^XZZdD^H\T^LVNRPX^XJZXXZXNPZLTTPfPLPRVTT^VP\T^^X^VHb``N\\\NTXLV`^R`b\XTX^``VXLRPPVbNXLV\JhPT\XN\R\d\VP\RNb`VXjf`XPTVNb`Zhd^\R^FXXXV`TZXR\DRXT`TZZVdjX`ZFbNbdV^^\H\LN^RV`R`dZLhVV^f^VV^ZPrfXXT\`VFTHPPXHXFTNddLd^T`RXRL\`^\TZfT\VZX^Fd`FdTdXXLddL\TZJZ\XZRVf^RXR\TP\bN`bPXdLXX\LZLPX\^\XfNXfZfJfVVRNX^`ZRVZT\PX^LZjHPLbF\DXXT\B^hNTRNbT`PV^^Z^XXVb`PjTV`TTZRd<\\NJjXXXTRP\ZNZTZ\RL\dVTNRVVJT`TN\^^PRXNNTPRVTDTNTLBrTTP\`XVN`HfXRHJZPT\D lb ^L`J R Z J \ RT  L TVTT\LN\RFJXTVFfR^PLVPNTPLLXTXZ P fNZPRT"R"`#$T#J#R%%'T#N#"$"&X%T%\%%B%"#F#L##$&%X)%'T&'R)(^**R*X*P+V--R-N-,-,H-,+-`*+X.*T.*+^)*F*,-,Z-,,/,V/113L001H0J2f..\1-,h-b.T/-X-b+Z,*,*-F*--,++V-Z,X)R.J*),++D,,)*)*R+))))P++D-`-,*T)`)*+\+))X*l+)Z+b+\()(D*\)R&P(R*(P)*J()'N+L**f((^()T)R*J*X(R(`*P)))(+)N)\)*(H(`*)R)*+R*),R-*R,,((()V()(-^*R,(,+T)`+,*T*))Z(J*R)**P'*)X(N(X(R&J&&R(X+'Z)+'Z(X'(X)J)+\((+R)(Z*(N)\()V,R+*d*+Z+)*'*\*^*H.,-0-\2/X//L0-H//0f1R31`21V0212321P210L11R2//D0/02/-.X3.2J30Z20.R/,D.-V/T/X11/P21/--R0Z//-d/b0X/.d-`.V.-..0V1V/2-N,T,-,01^./.Z-\.P.X-,V.P++Z/,Z,0-Z+T.\),,),\.+++N,d,,R))*\)*)*T*^*,*`+\++V***\,T**T)\,^+X)(j)Z))),J,),X,+N,+X-,V0+P,*+b,-d.---1./3/Z/..T0/R/R1j/T32/V1L3\1/Z2/.`1L2`1R02R1.P11/-T2.b0V//b01Z01`23^6N5^31`1215f3V4V11V0V0/Z21Z21Z1N0/0F/X01\43R2N375T4R4V4X5P3T5V6R5X2P2X4`5H520/Z0\/R2J3N110/1X0R1V1/R1T.R.0N0.^/,V/J.,`-T.T/L0.T+R,Z-d-*^,**d*N')X)L&P(`(V(d)R&P'%^$%f%$b(L(T%&$Z#^$P%"V#V"V!" `!Z PX !FV  RPTXfbVTTVFjLXZPXhR`FdTRV`FRTTLZhVP` T X J h ` P T V V Z \ Z P ^ X`\\^TXL`RPXTXXZV^F\NXXXRTVVZJZ`Vb^d`fRJPV^JdNXP`PVPR\\XNXbZHZZTd j`L\T`TVZ^X\H`ZTVPVNPNTVf\Z`XXP`ZJXRRRVZX\ZRb8HXVTXV^X^bTb^b^ZRNhZZPf^b^Z`Rb^PNNZT^HZVPPb`\FdbN\XN`XZTXT\LZVVPZNVV\TRJPRXHbhbX`PVj\P\\Nfj\VPLjjZDVdXVDT`RP\Z`h@P\ZZ\bdPZXR^Fd`ZHXRfNbR^TN^Vd`h\\@ZPXVXV`FXdRLTRTTTP^RRRVVRZ\NTbhPZXRVR\VDDLLT\XT\VV`X^ZPZbNRTPfT\H^^^^XZfPXXZVPVR\^^R^PbTVZXbRZdPTBZVV^ZPVXVXVRZ`\V`P\R\LR^RZFZ`P\`H\hRPJ^PVXR^XDfHX VV`H \  V \ X ^ P LZ ` XL VRXPPXPNTVL`XXbdVR TTRVBXVPXX !"Z"N"T#H#V$$b#"X$$#X$R$#"d"B$"%Z%:$Z'R&P%%$'b&&'(*)R*P*^+*)+J+J/h,N/T,X.d/H+R+`+,Z*Z+\+@*b-*)*+`-+X,,...B..V/V.X-.R0T2.0.0,X+*,V,Z*Z*)*T*T**Z))P***B,X-+R,d,+,P,*X.(,h+Z,X+))H,T)+L**X-+,)+))**P,)-R)*'V*&'')(((*)P(^+Z*+R+N-^)(R)*)(*)(b**n(()b*b(*+h+J)))+X+(*L)+Z,T,J.++-T**V,)Z+X*V(+\,\+T,`+H*\*X-++,N+**+`*\+`++'V*(H(**()(^(d'))b)J+b)P+`)D()')V'(Z(L((Z'''b('^)T&*))'L()\*(L,B*V../X-.P0/F/V01//L1j1R00/Z3/10^1P40X0L3Z1V/13L012R0/T.0/00b1/`2Z0/X120/J,-.P-..\//P2`0-X/d-X/X-T/-X..X.,H,,L,R/X/3R/N0N/-P/+,..J...X..T,R0/,\,V-/+-N-,N.N.,\+h*T+)X*b*,)L+X+Z,T+*)(\+-(,*F-)*`)^)P*))V*(*V*N()J*R(Z(&'+)N*(*(P)+,,`+,++-+V)P,*,0X.-,/Z.0Z0/P00//X2/2^0P0`1/0L/\0V.T/`/-.2T202R0V0/20^/0V10/P0R11d11N41V22R20L2X0^313`322L2N0\0T10.1V1V0L21100P2L1P1T5N4P5Z343524b423b4565f620//R2V/P1`32V11T1//^/Z/L.`//T//:1`//b./V.-f1-Z-J/.,X-Z,*,b-P*('F)('R(N'(^)P'V&N%$%&$$%##"!%X#T#P"d"" P! VVVbD!`\NX>RVRV\TZ^XJdX`TP`T`LZPTT PP ^T P b ^ V X V h R V Z R T \ V X Z \ ` PbR^ZNT^V`ZRX^nRV\DbZRZZVNJLZbTb`LT^P^\RN^FRJVbX^PNP\VXZNZXV\^ZTZ^Z\Z\hTX\NbTVV^XRZH`ZRTXhNbb\TZZPH^XX\jb\``ZVTNTb`\LXL`^fV\N`TXXX\X`^`X^RZbbfbP^bNVZdV\`\^bJF`\PRdXXVZV^T`VdThRZZff\bbPJZR`F``PFT^bZRTXRRRd`L`T`^bdPl`PZLfdfd^LV\VZVbHTVT`\nbVZfJRTZ\^PRR\bNfX`ThTPZF^Z\VN`Rb^\X^^ZRPfPZR`R\Z^`PdTb^X\ThbXRV`TZ`Z^fXXXLXPXZTN^R\X``hZNZVbLX\R`VDTdPLTjBZXPZ`^L\VXTLT`TZXRh\P`R\P\HZZXNfVXJZ^R^fPVNFNbZVXL^NX`XZT\XXTTP`ZLLVfRRX\RVZVJTT\XH\\NTPbPXZTZN ^ XVT\ ` Z h d ` P bR^ R B NVNXPRXZX`bV\JdJVTTT\V V"RHRR^@VP\XXJ"X$T$#T%#R$R#Z##R"!#b&V#"$!Z#"!#$X$Z$P%f%%X'V&%N&'V(\)J')*+++,V.,V.-+.d+Z-d+)Z+*R)*R*^+^+*X**,+J-.//X/X-Z,-b-T-T0R0.X/\/,0`++f++V,,,*Z*L-b++,X+Z+X,+f-+,.^.+d-X+d+'P*R,V***)L,P*R-*+N-+,H*-)\*)(*^)N)\()\(%N(T)&R'T'(\)*)R())+^,*\*N-X,T.d.,^)+0+V()R'*,J*Z+\))N)*)N)V,d)''^*++`*\*)V,*++f+T++)*)\++V+*Z.*^*V-+R,*\+Z+X,T*`*'8*b())D+(*+*T(*(V(X+H)^*d*P))(%(N&&V+'^(T(X'(X'b)^*(h)'R)&b(T*()`,N-+R,+-J---/---.b0X1.\2V2T.N/R/,-0R411/.1L/X0T/b2H.T/d00R-//X/00`00V1L.R0-/,^.D.X1n-B//N21Z/R--R,/^-^--,T/-,/n.,.L/F/X.+P.N/N.\0R.P,+b,,+@-+*+V-d*Z+X+L*-X.+,N+(X-),(Z+`'')*P(b)N*')V'V()V++-*T**b(^'Z)R,))f)b))'()b(*d&N')P'P+(Z*b*V+*R,,d+,P-V+,V-,*Z+,b/P--N,L2-/1\2/d2^/.Z0V.X4P.00.^-.`11X/Z/0\1R00/J2J1.V00N1.0\243T2f2N22Z2P21P5330`1Z331J512-b0-h10d0d2T2X00Z0V0X111R2\4X63t232b33545V4T5P57>4T3R22X0`02X4l1\312R00///P0N11P0/0-//b-b.X.-T..1Z.\-V,h.-Z*Z+*)())L*(()(T'b)(h&'%$#R%X&R&$%V#$#!!!Z! N !L ZX^LZXVXd\PJ^ZRLX@d^bhZ^J\BPZ HX\ XL J ^ \ J \ X \ V N  R J T FnP VLTJbVV^ZNdJXV\^R@\`VTX^XbZTP\NZ^@VN\HBXZTP\Z`ZTTPRVT^N``NNTbZ^ZRHdL`F^lVRZZLNVLVZXN`R\``XJPjH\XbVdDpPJhNTRXPdZXX\P^VfT\XHZP^PVZNVhPbRR`^`fTL`P\V`RXbXdZ\`TR`bf^VV\T\Z^RPbfL`VnbXPNR\XZV^`PjPPPXTJ\bZNd`TdZFdVXfTjVR`VVbXNhXd`\P\jXJP@`HZ\fX^HRLTpZ\Bd^XHd`T`L\^NRTNXVD`f<Xh`N^^d^XLXL^V\R^LdRTRTV^RVRNfNTPTJNRPX`NRb\J`^`ZLF\dRVP^XbTbFPb\VTRXLZ\TJLV``TJhHX^PHZPF`XZ\lZ\Z^RN\XT\RP`PXFZVF\FNdPBdX^TdV^VfRX^VZV`V\VVBJ``RVHbXVVZZV`VVTTJRVLZJXJhZ`F \f XV L dhVN R V Z Z b T TR`XV\PRD^TfdTR`^RDVT^XTfRP\T\RhB^N`b!!T"#!Z"P$J$J$$$##b#!"L"^"Z$#X%$#$P$&V%$(T&$%%&b*Z((\(X)+T+*X++Z-+V-\-,,P,**^*\)^*@+h+X+),P)+V*V+P-T-R-,+T...V-X-J,-f1J,P.,X,+^+P,H))*\-,X*Z)\+,*T+*L*,^,L-b/P.R.-\,-Z-,d),),T+P--H)P+*X+^+*)T+V,N*,Z)h)@(N''b*j((X)J'&N)R)(V()***\-*)+N+@++*V-R,-*V,,.J-T**)T*,)X)H'R''(T(>*(T(V)*j*R)'L++T*L,**`*,V,>*P**T+Z)-),,Z++-X.V)(X))P+)Z*T'N&)'J*(V*()%&L*)Z+b)('D(^(T)('R'&&b''L''T(H(R((R&P&'%P'J'''X+()X,.T-..L,.R/T-,D/0P/.d1-,0T,X--V.0L.T0F0Z0..J0V-Z-X,j-Z,.,-L/./1V22/.`.P/b-R,B+-.V,T0J0R.P.+^,.*-,\-V-F-X,R.-P-,0\.F1-V-+V++T,P,/0P.+d+*,*H+R,+b,8+R++L-,)R+,Z,++)h)''\*',\)+((*X(+*T*D+Z-P)'+L(L(*)((d''T)'')\(''X))J'(*R*R)X+R*)T*X+\-*-X+P.Z+X)).0N.b-P-V1R.-/R2.P/Z//b1Z/^1H0/-H,P0F10/Z1V1J2V0./0.Z0.0-0V/0R001X4Z2P2R1L2X43222L33H3J21T4Z10/0V0.-20L0P/H2P/Z1144T3F2N3V53d55`544T47X6P7h46J4b1/B00P22211J3\3H1P2l1V0//1/1N00.\0R0.f.P..N,T/b.,+-,`,+)+Z*'\+'(T*Z((\))X((L'V%&&b%%T$\%"`%"T%b"`!!^!!d!N `!NV^\TVTXZZTJTVbLTTVR^^XZNZjNXV\FPPXb J F H N ^ X X V \ J dD DZPRbX^`NZXRXbP\\\bLHdPRXXX\fXZ^LfdVXT`XTZ^VPfV\TZXLZNPTZ^XZZD\bdTD\Rb@\R\JJNXV\^P`PdP\VL`PbVZjPfX:b`Rh^TdTXRdVXTTTHdTT\HlhXhZ`R\N^\R\dTVVNJb\\HRZTR^L\dRNJV\ZTVFP^bPPfVZhVL^Zdj\dVRd^ZLVdD\ZRVPV`VHX^DPZXXT`f\TRXd^f^XVTVV``HbVZHLhV\^ZRpXdVZjXVRj4\`VfXHXL\VXbZTRZZNRZNRT^P`T^P\JVN\PL^RPF\N\NLnRVN`b^XRb>^`PPVZXT`TVXNVVNb^\NZ^PN`\dTXXXFPBXTVRf^TTP\\`^Z^RVN^VH^V^ZZ\HHTHZXTPZ^ZVdbPLV^fP\^Z\JJ`TDLbRZZP\nPDXP\\X^L\^VPRRP\JXPLVXXd\XPR N T f X V L V T X Z V R b V ^NLF \ XT``\\NRXBbX\^XZTPZLV`NX\TR`TjNTZN R$R#^#H"\""!"V"X#d$$##"j##Z###!\#\$V#R$#%%N$`%%'%&V(P)`(J+P*T,*)+X-+L-/,H.V+,d+V+'D*)-*\)+*X*Z*V,-T,^,-,+/,-Z.l+.,,+.T-\**+.-+V+T)d-*V)*)P+\+N--D++,T*,Z.*^+)Z.`**`-Z+H+^*,V-+,,\+*P,H*T,\)J++'''&&T(T'V,V(N(`)Z)V*Z(((P-+T+P,R,N-.-*^+N++*L-T,R+*+F**X)+b+((X&X%%b)(\+)'X)'\*H))*T*-V+X+)-X,^**X**Z((V*V,)\,V-l,`,T,J(T*P+D*V()\)^(\(P')b)^)&(&'(L((^'(2('T&\)^)D'f'%P'b(&)\)V&'%\'n&&^%%&Z&&T)\(Z()*L,d,Z--X.R,T.,N/\0/0.^-X,*+.b.+D+V/N-//0V0.R-L-,T,,R.H-..1T0V2-^.-..P,Z2+P*f.-+^,.-\.+T+,)V+J++.*T.,^,\-*-0T.X..-T-,)*Z+P,,.X*T*L-P++)+*J-.\,T**R*'f)d*V)R+X*+P(V*X(''V(N((T+)**X(+V)))`'(\)T''H)'(%N'''T'X(H'%J(`(L((P&d*F*\*)\)J*(Z)H(+f,..h-,*,\.J/,-L-.R/+/2J000^.b2/0./.b0-X//V1T/0/P2N0.J.X/-/X./b0R2/H0X01T12X11P4T35553V4X3Z323/./X1./X0V/Z1X0b/P3Z10P0d2Z125344N151L4N5754b63V3V422/10X124X2d1P11P0/T/R/L2h31/T0b/R.0.J0.V0,--,,J-,L,+)V)L*X))P,J(()V')R''(&&R'&V&%R%T%"!!##d#F#"R! !`#`$X!h H ^\``bNP`RRb^ZRX^VbPXXPPHZfPR\R TX \ V R ^ PP ^ X H Z B V P V L N ZL ZVVThRV\bZVZXXT\f\VNXPTNd^VJPVRLPVF\P`VNTTbN\`\b^Z^TPZHZb`BZZV^^bHdR`b^`LbX`dXbbVTRFNd^H\Xb\F^LVXXTZ`\VNPdZV`j^``h^bNfTRPTXVN`\```ZL^^V\J\`dZLXNX\fXV\XRPVZZP\N^PRHVHhHNdTZX\^N\`fPVNZbbLTZNX\hZ\B\bZRdHVLPJRZDL^PdTpP\RPX`@XPbR\\d^NR\TLb6TTdVb@\^TBXZR\\N\NDZVXX\XF\PN`Z@P`\VTXRd>`H\LRZVHZTRXB^NVXXRXN\VPPFR<^T\j^LPPLRZZL\\NRVZP^^PjZbTR^d^NH^^VTbRPZT^XZ``F\FdXZ`VdT^HVPbVb^`hV^Xh^LJPNTXHTX`NPX\J^^RXVZVTP\bT\ZJVPbBP^RPP\T`TTHZLRXdRpZZX`XV  N ` X Z Z N X Z X L P X D bP^TVFL`JVVJ\b^PbHXP^P NZZT X\\D`N@!T !`"^ #R!F$!#X#^"%T$#X#"^$Z#Z""X$%$###$J(\%$&'\)'%f''+X'R)+~*\+,T,V..R-X/N-f+*P*)F)P*X+*V)(R*)F,Z,)+,-,X/,,\-L-,N.+J.L,+\+P+*V*)*)L)))\,*+(V+V*P++\*R-R+\+R/+,\,,X,Z,-+*R),+-(++++T++*+)('^'N)&R')T,&>)V()&\*d(X'*P)R+T-L/b+L0+&R+,,X+X+*`.X+)+*+V+T*R)()&R'X''((X(V)*(*V-\*+-X*-*V+T+R-Z,d+*)L)+b)+X)^,R,,*V((N&V(V()'J*H%R+\(N(X')`'X*`(J(&)X'%'L'&P+((\(\&&%L)L&X'^%'X'2&'&^&'&b*'(`((j('*X,V+Z,Z.+V,,L-V.L-T,T--Z)J./.+F)X+-V--,Z0/P/X/),,+b,T+,V//d/N1N..X.-R.,Z.,,-`,+-,X-V+X+*)^*+)+Z+*L+V*,*Z1V,-T-B-Z+,T**.N)X+Z.N+)b*X)+^+)),*)+*)((P*X*L(**()(V)$L(X'd+(J+V)^*N+X(R'J*(`'R)+)*''R*(N'P'&%)&)'&'V'X'R'V*^(*)+)*V)L)+X-.H-/X,\-,+V.//+X-Z+X,.Z0R0^0100/\.1P.\/-..D/X3\.T/0/J.0-b++-.10.X/0V1Z1Z233X12R4L2\16H3174^3`3J1/1N/F0N/.H/J0Z0V0.1\1010Z333P42T54R3L333\55^3X5f632V2212R2^231/1/1P0Z0/X1//^//\0X/1T/N-Z0.-^,,V.,R,-,,*,)V*'L))\()'&'N*`**R(X(d&'`&($#"Z&#R$$#""L!#`""T"` ```TXDRXTZ\TJ^LPf\bT`bHdFNPLZVb\DNZT  ZTT N f X V V T T V V RP J X X P V ZZXhTV8^TZlPVVN\JVN>bLZR`LhRVPTTdPTTXVZPJPNTNTTJVPV`BXD^b\^dFP^TfPPZHfN\`Zf`L^ZVTTXRR^RhXLPRZ\RbPbRXXTRX\\TbRVDVLPTVH`TfNXRNPV`RVP`bZXZBb\ThNXT^NTfTHPP\XRT`TVVZNL^Th^`^bN\DFRT\PbTN^NFTTbT^VZJVj\NVRZZN^\`TTZX^ZVRTPVdTLbFVTBZP^XPT`TZ^\lddN^`T^^bJ\XTZ\R`^ZZVPFXZNV`^bLbRXVVVdVfLP\RTNXTbbVTR\Z`X^VZ\RT\\V^PX\VfVZPTZF^\\VP^P\XVfTTPdRV`bXPNXTRZVRPR@PJXbfJ\\XTV`J\bLL\RZZ^NRBX``XXRZZHb`\VZVJdPZTVVZ^RTNRZZFT\HVTPP^^Z\RZR`PPVP\Z V^L\J V J V V d X X V ThXXXXXJJ\VZLNXNZJVJRNPVZHVRT \PVNV\^RR  f#N"!!^"H"V"#$#"D$"$Z#X$b##&^#$$F%#b&#J'&^%Z&Z&&(T)^'(,`,))B.+V-X-,-F-*J+**P+*\)P)R,X**V*+*\,,.^+,X*,N+`/V,*+R*T.N*+X-*(f*P**&)*N,,L+)R)J+*Z+*^+V,P*+*R,T-b+--,+**J*+++V-)^,^+Z*+^*++*)'T'b'Z(&L('(f(H&&&\(^)\))T)Z)*+-Z+P*Z,Z+^*V--^,T*N)T+'T)Z,R)D,()(&'\(P'X(F*R)*P+^**)X**N,X+*d*P,*R)H*,*^))*X)P)V*,R*V-\'\*`&&'($\)L((b')X*P()&X'('P'r'&'&''(^'^)(Z'&V&\$'R&(T'Z*%d(&&Z'&'\())b**N)*F*Z+`+R,\/B-^.+,^.b.R-X**))L+)+V+L+\,,V-,T-`-*X+))*+B-+.X.-/,Z+*,+/+N.,P,T,\*T*X,X-\+*P)Z(X)Z)P,Z+))N-**Z,\-,T/T++,d+`*P+F,T+,-)*N+)*J+\))J*T*D,\*Z(T**)R'L'L)'b*L,'R(&&&N)T&))R)+)R)((R*)T))F*^'%&''\)'%'%^&%(&$`%V(\(V(R*((V'X,N+)R*Z+*,V-R,-,X..0-,T/.-N1T/V.N//..Z.\00-T,X0,H./.,-N0/-X/b/.T.R0//f/1N0V2F10P4`3\1\302\3Z33\42Z53430T/F//,Z0X0H1N0/R0P0/L01Z23`12^355T3P72X4456P2Z411N5\3P35402/V02X10L/d0R/V0V12V.0h-//b/J012T-..,V,-+P-,+)b()Z)*)X,N(\(F)V'&')'(N(T(F&'%`&L&&$L&"V$\#R#%^ ! V" "RNNBZRRZDTP`dTRNb^d\JTjV b T R N H J \ ` T d d P L L RZ ^ h V RRhbZVTFFXdL`JZZ\XVNNbNbP^ZLTPV\D\RT`XX`TPR^P ZX\Tp^X\VJR^ZRPLTXZbXNbLf\bXTVXVV^HV`\Tf`\JL\N^VJZh`VZZF\ZZ\^^Z^JhN\TV`TRTR6\^NVX^\XRX`bPhXN^XTR^Z`TlXTTbPVRVNX`T`NbdJ\P\PX\LRNZ\V`\V`VXPfJL`P^^db\T\hZPXflXTX\\n`^XZXX^XXZTN`^ZPX`\\dR\`TLT^THNl\RJ^Z^dRf^\\LNTd\`dTdZTDX\N\NPJdXTNVNRZT\jX`Z^PFXXV\\VRV``LVPLXXXR\dNVd\PdPVP`RLdTP\VBXZHVHVNVXVTVN`PbHRPJZTRXV\JTP^\VX`ZPf^NLZ\XTddZbFZV\P6NHPdFPRNXLZ\Pf\TZ^\LLJVRVV^d`TB^ZVRPTNXLRdj`NN \ T h N Z b V ^ ^ ^\d HTNJVJbNTFTZdTLhRFVRb`RFZR VFb^TPPPDD` !\ `"\!"X!"!#H#!Z#""T$$T#&##V$$%%T%$#L&\$L%T&^%\&N&&Z(X(^*+R)N)-*+.-P++T,**X+)(L))T))*))*()V,`-T,*J,++,,*T,*+D)+*b)()*^*(**f*,R-V(**Z+J+Z*,,R,F,T,+,J,-T-+V+\+(N,L,,*.\+L*+(Z+*D*L*(&''L'd'D(d'&%&V'L(V()H())d(H,(X*)R)`*F,+T0,,*+(T,(+)*((')L)P(((&*f((+`+,J,))P-T)R))T+Z)T),^,V((b)P(\**V)Z*)^(('('N&^))V')(()D(*'b'T)'&''V'Z'`(`'Z(`)'R)L'N(@(&'&&b)'B*b'^'(X'(T''((P'+X()()@++R-T-Z*+R,+T,B-D+V*P,'F))')**\,N+V,+)*V,J*X*V)(Z/J*-/6/,Z,V,h+L**T**,T.j,D-*>+,X-)R.^+T+,+)+Z,)*X*\+-Z,R,*Z,**\*b,d***L+H)((Z)H+P*\)*X)*)Z(R*(`')^&'&'V''V(X'&%T'&)Z(((T(`)`)V)`+&+N,X*%L*X'&&(''Z'F$'V&'L&P(X&'%&')(R(L*`+\,)R)X*D)X*Z+V--+-+-+R/,,^/,Z/P0.,\0X/Z.X0Z-0N0,R,R-0X/.T//-,..N/.V/T/`0/00X21J1Z1l120b0/Z2Z4Z33L04P2T3T401J1-.-V1/V3L11/V10/T1h4X23^1b65h45l4b6222321\44\3h4452Z20221H2X2T3011^/0.L.\/X/R010V1X0X.P/-T+T+*-V-N.P,b,f(X*)H)+(P(X*&)%&((^(%L&Z%$\(b%D%&#R%X#N#V""Z!P!X !!VZT X^RRP^TZ\R`dZLVVBVXNXVPdf^L^\Rh  T ^ ` Z Z V Z P X X L P T N L  P R RN^T^\NT\RN`RdPVZTZVR\XXTTTb^TXTVPJR^`LLTLR^NRZRP`TZZ^J`DPZ^NJ^RVV^V^^LVZfZZT6ZVV`j>f\\TPfVXR\XjTbLTL^TN\hdPTPZXh>TNdfX>PR\XX^\`XRZJZbPXL^ZXTRXLVVX\8VRT`^\XddftVXNZXZ^^\`\\TJrVJRVThXh\\\TVLXJTPVXRTVVXTXVNTVbX^XTTNf\h`^`PXR^NbdlVTPfbfbbfVX\LdlVbXZd`ZLN``^`XXLVjVTTX\JbRNdT<VNRdNbZR\R^^ZZ`HLPZXF`HF\^\RZfRX\Hb\JPV\TVRXXfTHNdNXZ\RTVVT\^X^^NVdZJRVJX^>T\`X\R`VRVZV\f^bbVbLbf^\Z^NXJTTX^TJZLTDbXXRb^^\dDT8RXPT^ZbZbdTd`:RVZT^ZTPV^TXXXN\X\\VdH`^XLXb`Nb\VTNLZVXbD\XR V f J N ` \ J N X Z ^ R Z N`JVLR P`\PfRTV\RV\PPT`TN\PdPRXJZb\ZVZXVbZJL\"V V!P V"!!#Z$Z$X$#\"""\"P$%&T$T&#P$R$b#&#$Z&N#Z$Z$%(T'h(F))()-Z+b,,++`.,*L-+H*(j*(\*\)P*X)\*\*(*^**4)*`*\+Z+T.+,^))X*),J)(*\)V*J+j*T*\*P,,@-+**X+,,H,-T-B,,*T,d.*R,T++),`)\*d****+)-*Z+)P**T-d(V(*()V(P&&`')((Z)\)R(V()(^)V*B),*++*++,L,X*+*T+\)(J+*`*(\(')*`)P'P+R'X((d)\+B**-)J,)F)*)))'+B)'d)(b(N'N+(N(''%('\)R*(T)Z')h'T'*N(&(F(\')T(N''&'&X))Z(N&'V&P''V(X'F'%L&b'P(`(*H(''H(*()X))*P+N-++,*T+J,-)^,V**N,**`*X))^)Z,)Z+X)+b)`))`)()D,`.+P)+Z+F)*P+*b+*T*N+d)+**Z)P+*R-+P-h-*\,+*Z*P+),j,-X.N+b+^*))X*D-T+*V+V**R)&`*\&*L')(*^(P(^'X')&J'(&T&(Z&+'b(*P)(Z('(Z)T()`)*'P(F)()J*+V'N&)T')%%V%(&&(L*T%'T'X)'()'+'L)X*V*)+X)V*)*+)P+.-R,^,T..^++P2V/N/0,R2X.-T0V-P/`-.,,,0Z-\0-2.1/V1Z0P/Z10b0./2L0\/X/N0`2R15\2V42R22X224X310-.1V.`/X01\0/X/110115J12P4R672R54\2F3^12\2d42\33Z1X4R0V2n0T./.X2/b0h11V11b.H1.L0Z2\1R20/.N0\,V.`,+**+R,*)(j)))L)Z*V(''P(X&&&$&T$\%$$%%X%P%"T$^"F#!R"!fPZ \XTXbTV^`DT^PNPZdVhXVRLVXNX^^bZZ@X`NR  L R Z P X V N X D b L h f V \ NXD J ` V RVXP^XVV^VVVRFX\VLPRVN\`P`NhZ^RbP^TL\TTX^VT`TZR`dPVVbTXXPRZXJF\VX\LXNZ\ZPXbR^VVT`\^XVRNb`dZXNb\TXRXPVRXNXVbXL`XZTZVPT`\XPbZdbZB\lN`hhJ^^NZZTVbPPlfRRPHTX`RV\P\`Vd\Xf\JfNVZRJTdfTXHZZTXbZVRXV\`TN\\JHVRTN\\^\^TRNV\TTVRTb^ZLN\PTNBZhLVV^ZRVJ^FJH\N^bNNRXZNNZXRPJRHXTPVZVbdRT`XHDZ^\JV\fPXTfdVVZZFTLHXNVZR\^RRbPPX^\`d\XV\P\TB``LbTL``FR^Z\V\NbVTT^^NVbXZLZXT\HHDHTNNZZbJ8P\\`^N\`PVRXNN\JV^F`PXRZLHZR^XRRb``\PhRLZFZNZTLTNXZT\XVDVLZL`bVLZVb`R\`DhJ`TJf\`XT RB  X R D j \ N P H N  R^\ L^^bTZXXT\HXN^VT\V^FRHVVNTRR^HLhTJTD Ld!Z !\"` `# $$\#T%X!N#d$`#\%V"j#\$D%"""R#V#T##$d"Z$%&'(X)*X)V*P++,X,*R+b,R+*F)`*X*`)*X((\+)R+^+)X(T()J*V)Z-+P++P,*^*+`'8+Z)R(\*f)+*Z,R*+))J+,++Z+T,R,+*P.b,J.\,-+N,++R+*R)H*^)-)R+)^,J**,**Z+*P))(f)b*J)`+&'*'Z(^)((*)*P)\)V((*+)*+)L**Z*V.++\+V+T*X)'(L)@(Z('^)'`&&P''Z((T*'P((R+f(+*(\((^()(\*J**X)(X()())V)'(Z()^*)X*()Z('&&\(&&J)(F)N)'''T*L(T)'(L(('(&(*H'X)L'R(P''T'V'`''('*()(V)+)J.`,X+X,V+)`-J*X*\*'((L)+^+P,)F*j,V+N)*V+L+L+P*)P-P()++)T+*V,T*P*X)R*P*b)H-T**))T+)P)T+**N-R+V))X*`*\+--*`+*)T)R)d)(d+*N+R-)V'&%&Z)&L(`')R*T**'\(>(b('*T*P*(`'d)'(J(()V*)J'N)(((()()&T*^&&(&J'Z'P)%R"Z%R&)R'(''`''T)'V))P+\)()*)(T(+L)+**+.R+T+R*,R/V,,.-,R1/T0X.V0L0j-Z,.P.R0\20\0L0D1.X/T1X0N/N2001P/b00P1/1/.V310R0\21@2^6100Z30T1N/,\1/Z0P01T0/0b0R0T03P2X4R14T24T2P34L3L3R621\1P3D43D4^10.0L100B010D1^101T3Z0\2F02/f0L/.-V/L.T/.Z.N-R-X-R-*X,-L+\*(b*F)P*('H)Z'&P(%V)&%&`$J&N#%#%\#$P!#L#L$ P L N LNX T V\` VTTV`\^PTVDVJ\XRZTZ\jRT\LV Z` V LN Z V X d T N P V R ` d Z ZbRZRJ`NL^XHd`NP`^XTLXPX\XX\NXJ^@bN^XXV`\LVZXLfXNZTTTVX@ZVNbNd>VZX^VTXjXLXNP`XbRRbXbP^ZPZLLhVbTZTZdV`FRTVTT\LTLVPVNbJR^LZNZTXXDXd\XdZJ\bVNV\Z^XL^VXVTX^bPbD\fX^bd`Z``XDVb\`RRNRHNVJNfX`PXZZNTZZ^`ZdXVF`TbNJN\XTNJXXPFfPXb\XRh^V\XdDZnZ`lN^X`dfZ^d\`ZbVT^RLD\`VJ\\XbVRTbVhLPVdR`T\LJXV\VNlTVHZlN`NfRP`\@\j^T`bLPVJHH^^JjNZZ`RTTNX^^^\Z\@^P\jNZT`bNFjbLdRhPN``XhZ\T^H`LX^`\ZTTVfZHb\JLHTd`b\\\Lb^VHPbX`VV\X\^`PZ\XVL\dXZ\RRFP\N^LRT^VVRZT`VPHXVXPNP^ZR@`NXVVNbTZ^dZ^\\ R ^ Z d P F V V XNTVF`VLPPJJJP\\H^RZRJZTVVT\bRVXV T``^Rf`PRDRV\P!X f!"\""Z#"X!V#T$`#T$##\"!T#$V##$$#R"#T#V#$N%`(X%X(&X(N(T+\(h+L+V+)V,,,++\*^)-*+V'(V,)d)L***(\)D()Z)R+V,Z/V+\,-d))P*V))Z*(J**R,R**L*)V**N-+V-Z+X,-T,V*`+*T++,*N+*@,*N-(H)()*()d)*+*V-L+\*+V,))((T(*(d)*'&'(***\(X**(R(\*\)Z*T*^*)V))\*)P+R*Z*P)(T'&)')\()P'X(b'Z)''()'H)(**R)Z,V*,,*L)N)R('P((((^&R()&F''(N&''X(\(F'p'J(\'X''%V(>&^'d'&Z)J)`'*'(d(P(T')%&)&P&&`%Z&&V(J'&(V'')L*\((P*)V(V*b+^++X,\,T+-F+*)X)X**P)*V-**++P.\*)*P+X-)\+*X),+V)V))Z)N)'T)Z**(+H*)J))\*d)R*)Z))(+^+*P)L*`**(+^+V-+-Z,*T)T*'((+*X*+(&&'R''&(V''&R'(()'b)+('&R'((L('P*(N'X*'T(`('V*`((()(()%F(T)P(&R'^%V(&T'L'))X()J('X)*R(,*Z'N,Z((Z+**('Z*^)b)X*,\*X+`+`,.*+--L.V00-1\/-\0-b.00./1/T00/V1T0P01121`/0\2R000^010100^1^1V2P21P2R3R1^3V3P0`04P01V3f2101L4T/\21V11N444^5d4N5X44T2d6N3`511Z1F23X20b1\0/00/0L2X/\2Z2\2T0/V/0/R2N//0/R,-./T-X,*R+\.*X*P,T((''((Z'&'($6&'Z(%%&'j%R%P$%\"!V !Z!V!!`!J TZN!T dT\L\\NTPVZXV^T\L\\fBXV\dRhXXdXbPf R ` f ^ j R \ d X V F RTVR Z\V\VZ\^D^bN\V^XTT\J`TP\dPX^NHZVJNNb\NRZPVBT\P\\TV\8R`RXVbTfXXXRT`\\`ZZfbXV^ZfNHVT\\H`P`\XfVZdXRHZTbZPNb\bL\TRPZ`ZNTbLXZRPLdTXT^VTVR`VZXP^bDJhV`PV^Zd`TP`^NT\TPRZRfXZZN^ZThPHn\^PfVXbVVb\NZfVX`HZfTLRL\RVRdZZ^dJTJ\ZRPdbTJ^PTfjTRRJ\P>\\XXPH\jLbLbd\N^ZVZZXH`Z\LVN`HbNJXNXVTVLPHRT^^^dN^J\PfdZ\HRVTZ\HRVZ@RT\bPXJVXVLLbPP^RZhVb`RBNfNZ`RJ`bRZ`JXRZ\VZT^^RTZZRNZHZBNXNVRTTNb\`X^V^>R\NFPZbNVFZVZL\R`^PTTb`RLFXRNT\TFLNNRR`TLVVNN^NFPXZLd`^ZTXVT`THJTDP`TPRN ZF R NT V R R^ \ d P ^ \ V ZTNNH`NXD^V^ZRhP\V^VNVbDR` FPVbZX!P!!V$P"H$V%#P"%""Z"P$#$"#\$\%N"\$!H""#H$&%(&\)L(X+Z,+\.T**>,+V-R)D+(V)**))L((X+(Z+N)V*J+V()Z,b.,F+R/N,),T+-++*Z-\+Z--D.+,L+\)N+,P,N)+R.V-+*,R,J-*Z,T+^,))+X(^*P)*,*)+P*\*J+R*)H+T+Z+R*V*d)+***)P)(T(V(X)'*`*L'(X'))**((P*\+')((*X.,R))Z(N'**('X*V))R((%&R)^(J((\&R)*`*)P**+X)T*L(P'V)^**R)('&(X'&&)&Z&'N')Z)&'^'T&`('d&`)'&''''*\('&'V'\&V'R('''&Z'&'F*b'X&V''''Z(T'('J*V)X.)),,^*V)Z,+d*X,R+^*)X+((V**X*l)V)()`,\+T**))T,P,)l)H(\+*L)()P)(X()`)H+f(*),P((^+L+d)H,T+,**P+X*)^,+P+R.T+)*(&*J*)H)Z(&'P'X%>*X(\'&&'R'F('&&'^+)+V*L))\(&(P)&R*()'*'B)B'D*F)((Z((V(T)H&'P''F'&)X'&&d'(>((('(V*H(\,P)V)Z*L')(,^*`)P-Z*H*))d-,N+*N,b*+N-*d,./,`/2.Z/L./N//0P.P/T02/X1.1H2/X0-J1/00\0V32L2V2X2T10b0J1V12R1T20X1N3R130L/0.^22N10.00V13Z00T3253X94T7R6V4\543T3T33^405V201L210T/01H0/Z1/T000//R11.V/.././-.---Z+N*V*P*R+X*+^*6(P((`('\'V'&b&D&'T&'&%$\$%Z$R&#\"R"!R L D"R!"\ >`Z!R\PRPNVV\N\XNZ\\N\JTRXZN^DVXRZbX`P \XN V ` V T N X L N Z H X  N  TD\bNZRL\Z^TVdX`^\RXT^hV`TTRTTVTRZTXPRXZZ\`Rb`^XbVXLZT\F\NhL`F^ZRT^TV^X^^^^PX\`jRh`NZLHJ`^V^NdVZRXRXd\NRHNZ\RJP^X`ZPBh\ZZTJLd^LfRJdTT\VfhN\\ZRdLnRT\`ZbTRZdZ`VXT\`VTNNL^Xd\F`\`bL`\PNTbJTZ`VP`H^^RVZ`VPN\RXRXJTVXZZPdhPZZFNFLZRdnd`b\bRdVZ`ZRTb^ZXnF\^PVbTTR\X\d`XZD^\LbbXjJbRTTb^VRP`h\^`PNXXPZ\Z^RTPpZdP^\ZlZRHTL`LVVTNLRJL\J^^RVVZTdVZPP\\\L^PJNbHLXP^f^B^PP^RR\b\fV8P^\fVVb^dP^LNPZRP`NNT\LPTXTbVT^TVVVb`FPX^^fRV^\V`V`DTb`XZ\bR`T\JZRdJZDRNPV\RRRRFT\XT^LVTXZPXRXT\XTd\TXdP\XRZNTZVPbLT\ P N \ b R V R Z P ` T R \ T P TXX\VJVPBTPZ^L`XVLZPVJ\f\T\\NPdTTLfV^P@ N ^" Z"J!$T$\#$##`%N""#"#Z%Z!Z"Z##"N!#\$"##L$\%X('`()*X)F*b**++L)`,X(Z)(X(')((Z(^)-*+*\)X(Z)*,,L+V))H*J+X**)L+,P++-*R-,V,R.T++,^+Z-+*\-Z),-R-,N***,*L*Z)(P+X)X,P,R+N+\+Z+),\,X**+-,,R,\++:.)H(+(^'(\*''P)\&(f*'X((*^+()d)L)^,*)\+0+*F*N,**`+^)+*X-*'N)&R'X'V)'(&R%b&'X)**Z)j)(T)(`(*+(F'(%L&L'(J'H&'Z&%&%'%X)&T'\)P*''&\&H%B')L(T'&\(&X'\%'h&R)`(D+)*R&`)d(*b&\''V)H'&Z&&'T*V+X+)X*)\*)P)V***T+*()T***T.*X*\+X)T+J+*)*^+))+Z(X(\)+Z)f)(^)^)((Z)L(*R)T*)R(N)N+H+Z+b**X*))*)**+++H,\++*T+\+Z+L**'*('R(N((J)(&&L'(T&D&()*X'&N('T'V)((T+(^)*T(('P(b(V(V('X+)'(+(')%'P'Z)X&F')L)()V'&N'P('(Z+)R)(^)^'T(V)^())^-Z,Z)`)*b*T+X++,)))`.X++,.Z.P/P/d/-/21/1V01H0.12V2V2/..L.-Z0L00/2.211T02P10`0T10N0T01H1X120\0\0T20Z0`00T10\001110\4333T4P4N63`444T32b3Z23\410T210`40J1\0X11T0//V1X/B/1f.f1X/P1/T0N1R0^.^0-P/V.,+)+(*X+,,X()&&''(&'%Z%J&'X&^%$X$"N$#`"\ R R T"!^#b ^"`T^X^ZPbLZXLb\XLVRZXZT\JNd^NjFdZZVRBbJ ^ V J J h T ` T \ V R T F V b T ^Z\^dP@HXL`P\XT^ZTPTPRZVPPfVTNHXRZV\HdX^VNNVNPZHTf^Rb\\`JHLXRNNPL`Jf^PbPPRVV\TbRbXZJ`h`TNVbZR\PLLTTTZ`VXF^TXFP\Tb^Z\`b``jD`HVVTXRFN\TdTTPRTXhH^fLV\b`b\TZVXPTRhVZbTFTH`VNTPFTVXZXZTT^VdTT<^\\PXRTT\Vl\^\TRZTR^ZJZdXHZV``PVNd`ZXJbX\^RfT^XTZNXdZTRdXTJTZ^RRXV``\PJ>bTV`\`XHbTZVVX\\PZZZ`VH^T@`XXLZZ\ZRbPRbPLTPX\XXZLV^LRXZNZd^PTbTRZVTLXNXRRVJL\^XP\TNbVHhP\F`JVNX`bHP\NH\bhbRdTJfNNPPN\@ZZNTTPZVbZ\B\RPRfXH\RVJPHTR\\\^VTRhZXP\XLJ`LNXXTHVPdVZ\PRDLNZFX\VPJVZZPX^TNdFT\NR\PZJZNZPbRfR H TZX \ f H V \ T D Z XNZXZP`J`VVRlNjT^XFZVXb^\\N`TfFZP!!V!#b!#\$Z$J#!X$J"!D%#\"Z#!$X"""N!R"R#h!Z"$%$b%X'`'*^,,+P*)*+V-<()V)P(l()P'<('())))+(@*),`+*^(`)X)R*P),.+P+N+T**++*n1++^,+-,,+,Z+D*+l+-T++,T++*L,))J*+*P*P**Z+,D+\+R+**+P,\-,^-R/,-+R*\+(D+(D))')(('H'(&Z(**)++,V)P+*V,X-*++*,B)+L+\++L+T)J(X(&R&%P'T''P'%\'L)R)'d)`)T&Z'(')H('\)')V$R#%X&F($&J%^$%%T%R'\&L%f((R'R'&L($&\(V')(&'V&V'%f&Z)T)&(T+(b(*T*(&('(F'b(%T)@(R*L*X*)X)Z+T,T)**L-.Z*^+)**R+X)\*X+)+))R,`*(T*)''R(^(R)(P))'&X(+'(*N**)N*L)*)L+L*)P*b+T(T+()--+^,T*R)X)*)*R,+V***<)X('P%'<&j)b'N(&R&^(L(J(^)&'T)T&'(((H(T(R**T*X+N,)('(V*(*(()P(*)R)L+^'R(V((P)'')(V'&'P(X))X)*P+*'(X*f)\+++V+*\*++*J,\)+***\*+,*P+V/V.X.-.\-/20D2V0`121110\0V2F2d..H/21R02V0/V21/>4V02P100J2H1X11\1X100X.f4H00Z2/R24021451`23^1X3^34R32\4b3X3V2Z13D332d42\2L1P1V2X0T2V2d3P210b2.,,V/N/0X100Z/B/b/-/R+-N+L-Z.*Z,R*`+^)*V*D*\**)X'N(d(X'V('L&R&\%%%f%&T$$#^#$""!P!P L"Z#b"!F !\ `^ ZZX XZbPVP\XVRLZVVXNbVJb`R\RR^NRf` N` X T T ` F Z\ R ^ J X N X V R Z H R Z N \ V P TZRZZT``ZJ\LP^^XJLZL^LXX^VZZF`VTZTRXT6dXXL\VVBVXTV\L^^^NfVPTZVRXD^^JX`X^\NbbXXXd`b\\ZNd\ZTHZ``NVJ^X`Rb\RVTVL``RPX`ZPVXd\Hb`VLVTVLXb\P^JZZb`PZfNTXhRXZbX\\L^^Z`T`VR\NZ^^VR^`HbZ\ddT^R^hTTTd\RVTHhZVJLXZVbNVLj^VVNRNbXV`HH\ZRZFPT`ZLZLLR\RZrbd`fdXhPPVPT^^\VXN\b\N\^ZVH\Ld^Z^R^\RLbRZXJTV\`HRRfZ``L^FV`JXH^VV`Jb^RFlN\VRV`Tb\V^`RTZV\`TFZT`PX`\`XL^^TdZ^TlXZZVZHX``T\X^^R^V\XZX\VPRV\Z`RV^ZZ\TVRRJTVXZLZBZRPVZ^TVZTNXXHJ\VJXPhXL^PTX^FDXJVhXRfVT@b^BTZV^`XVL<dVbT^\\VN@PZb`VR\XbNHP^HXPRbb ` R \ V  b ` P R L Z ^Z `dXP\FZVXZ^H\R\ZX\PRLRLRNRPLZXTNFXbbTVXdPb L L" R""\"V"$V"! V!Z# !P"L#X"!#!R"Z""!"^$$X%&&&V()++*L*)*R+T+^('T(Z)L(V(''V))P**B)X+(&^)R)N-'()P+)*@*+),P-d-R,*+Z,P,-f-+,,-R.-,Z,T,j-V,P,.R,\,*+T+T'+X)D+b)V**+N*V,Z,*++,,-R/V,`-,,<-Z.F+++V-*N+)Z(*L'%P()V(b((^)\)'*T(**\)J)+-^*H+P/N.\*+,R,*`(*R)*Z)'\&')L%\%''%H('V+)')T'H'N&Z'(V*L)T)'L&%X&P&N&'(Z&(%&^''&%P%&L&b&`%V&%X&&^(b&&'&%B'X%'f'R)'\*)`+V*(\)Z(L)R)()*)(Z(P(+N)F*(\+X*V+(^'')*V*T,Z,*P+V*X,(P)j*)))L*V+T)*P(V((P('Z*'F(('\&X**()X*(*&N(J)+*L*^))(P)'')L,*+X,-Z*)T(&Z))b*+d*P*T)N*(b&P&'(R'(%`'T'%&(''L)&*V'$&N(P'()J*d)\**N*(H*\)P)R)H*T(Z+)P(*(X)X'((&\(R)b((T('(R)X()Z'B((X(X)Z(d*X(*)*f,J,`,L+X*)*,J,,/F*V++P*,*d,T--L-+/b-^.111T/\1\204Z1`0P2Z2N2`522V1\2X3`1Z4V001b00L020J0N2Z0000J4P1/2./J/V//0Z021R11101V33V502R3P6X3X2T1\4142V45J34T3R10X0/H02J211/L1h23R/T2/\.\10P0\1P.X/././L.@/V-,-,\,L*)L)T)()Z*&&''H)'V('%Z'V&%%$Z(R%\$"#V""H"!V!RR!J!$ `TZ^ V^ZXVLPNPZPBbNfHTTTTX`XlH^VZRP RNHX X ^R^ R T ^ P V L R X Z R \ Z T V N N \ \l VP`bbLRXPX\VNVVZ\`NNZ`ZfNLR`VL\ZX\VnTTNVTV^fPTTR`Zd`TLNVXRZZLRfNNPZPVXXLTZ:jVX\PHXT^dXZbFNRH^^`F^R\PV^XdRNZnTRdRXVfXfN`RZR>TZZR`\RV`JXPZXVjLP^fRTJZdZXXZVRZ^HPPT^`R^T\`XTRb\VRRJR\`TXXP\LdPXRTR\jX\XZLZXPJB\TRTZNbT`hXZ\X`XdZV\VfNdPVZ^L`XJPV\P^\RbJZTVZPZ^fVXTTJ^THRbTXZTLV^XXXZ\lfN\TVRbXV\TRX\`VT^\ZPRNPb^\^\RZhFLJVbXZNV^ZPRPL^XRTTN`TJXlL^`R^PT\ZZN\V^VbJNPV\\^^PbVHfPXXXFdPBN`VfH^VV\HX@Tl\P\DXJ\TRPT`\RF^bfVVTVTFbR\JPbTjPFNBVPN^bLZJPNRRJ\\LTXNZJ<RZ^P T Z  TJ J D L VR L > R N 0RTLF ZRFTLLNZR\b\XP`JJFZL^ZNRJT\TZTR "` #j"!Z!T"!V!!Z!"!V X"" ^ X"R L! #V"`#J(&R(&Z&T(f*R**)\)+\,*&\))H*^(T'('()T'X'(R))Z+()T((,)**+^)\-+Z-+-D++X++,N,,,^+V-,*1X+X,*\+,V,+H-+L+*\**))N*J-*X,+*,V,\*\.-+/,N.`-J0V,L,,Z,\,V/,`,L,T*+)>+H*T()X)&()+V)*Z('T*(\'N,d,0V+.R.\.,\+,*+*,+*)(&%R&%Z&&R('&h(V(H(Z)R*V(d(T)(F(''&&\'V(&R'%&%&Z'&(J(&&&T$P&%&`(&V&F$%$\&T&%Z%%%X&&%b&P(\)Z'P&V'))'P'P(*R-R+)(N)(X*h)j(V)J*(Z*(T(((D*P*V*T,)Z*b*(P*V)('Z()J*)*T*(('Z(d)&'V*^'T*V(>(P*D*)V*B()*V)N*X)T*T*)*N*X(X(Z'*+*)V+Z*J(\)f*Z)J(J)^*R*+*j)(\'H%$X%R'(R'&@(&(b(%&(T(T)V)T&%#%V&*(D(@(()`+()`)*(\*'((H)\(J(''%($^&&P&Z&N(()P(`)H+X'T&')Z))X)V*T*R**\*P*H)P+&*+,H+X/)`/R+,Z/T.\-X,-+R,V2`/B0.000^/2Z220.^2.0f1T2\01T14X4Z330/b10d0V2^2R0031\2f2B/V52/Z1J0P3`0\0B/302N34Z3b1V2011f411Z25T43113J2F0d32220-F2`1V42^0V21T2V3^1`1X2000f1V2`10N/0-L0`0f-8.l--,-Z,N-))))*))(P(Z'&'('(X(X&#X&%\%&V$R%^%#X##" H!! !V"\\@\VPNZHXNNHL^R\\TVVZTP`hX \ZNJR\`P N\R V L Z F P ^ R T P P L R T \ b N V X N T V TVfNVLXLV\R\PVZTF`LV\NTZNH\LXXLXXXjRZZV\Z\HZXdLNVRRTh\`NNR^\^VVL^ZVVHV`^`\\NZRXZ``PNJTd^hT\VTlBXLRJ\LRb`VX^FVVVVP\`RNZVTVV\VPVXXbZX`bVl`^`XZTZd^NfR\P^RHV\X\HT^TNRXXXfPZ^ZVPRj`^PRX\\bTXZXNDdXVPLX^HT><\TT\PZbTPl\^TR`\hhJdPXNhVRhTTVVT^PPbR^p\XV\Ld^^TXRZRPZRX^`\NPRD\fHb``\ZZZnVZRdXV`X\`V^XN^\VXdVT`TJZdRZXT`T\\\TXXVRL\VB\NPRjTVZVT^lTPV^bVNPbNNLPb`TdXZ`RVLX^NVP`FXDTHPR\DXNVbLTb\^VbZNLXZ``\b^^V`RVRVLZ@\RFbVP\`VTfF\JLRJVDZRPPP^N\V\RbXNVPNP^R``\\T\ V V b R ^ X P \ @ F H V NXTXJXT ZfZVTdNTZXVVP`HVZdRNN\ZVdP^ZZX RVN "P#j!$V"$ b"Z#J T! V!N# f P"P #T#`#R!\!V$L#X%''`&%P+)J)^*N(`*T)V*R(N('H(V(^)\&'Z''N'''R(J,^*P((h)++)+*+Z-L,.d-,V/P,,P,L-+N,+\,T.,,`,.^,,b++)B,R,\-N,R(N+)),`)P+d))B**)T+X(+*+-X-P,+-1,\.N.,--*N-*+P,+Z,)\+V((()b)X))^++F(L***()Z)*P,X*,.h,.Z-R+b)***N*`*($%%%J&^&Z&'\)`)L(*)*X,(T*R)`)%V'%$X'%Z&&R&$%H)$R'%D((`'R&V'L&'^&%(R&Z%P'$$V$Z%Z$T%Z&%^%%(*')((N&\('V)()V.N(Z*X)*))))T'V('*((j'+P*T,))^,`)L)(X)(^*X)T+N)T*\)(()(''N''L&&'((V)Z(L)Z)(L)X()X)*X)N*R+'((V('*P))*R,f)()^(J)Z)(*()N)R'H'H'R&'T'F'X*Z'('(%'((T)(H)Z*^(P&`)J&X)(Z))^(((J**f)))V*^()$@))L'^)*'^(P)'%\('T(&&V'*X)V('&)(*+T**P+L)*,+V,*\(),-J.-Z-J,T/b-.X+N.V-V/+/1`/.T1/Z30\121N3Z.000b4Z34324X42P4d21X/0f00`.H01/f0T0^3b/V01.1133D02j0/@0`2b2H1T22b3L32430022113V122Z20P403Z0T./0R10.^3/0/P20Z1\30V3V20/,@.X-/../.T--.H+,+T*+'')L+''F((L%X(&V&)&%V%'%\''V&%Z$#R#"!!XZ"!Z VVXRNNVRPPZTXRN`X\FJXTTVd^\PP`LPPb X \ Z \ ^ T b \ \ V N > d < Z P f f b X R J LZRXPX\dP`^VZ^\RVXTNR^TV^ZVh`^JJjPXX^^RL\P`XVVPRZ`PTfTRPVTb`XZhTB\ZNJZTTF\`XZd\R`Z^fH\\`VHR\bDp:XRZZ\ZZVVd\ZHXTXZHZZZ\N`V^`^^bTNJ^X\N^TPVRTXH\^R\PXP``VdV\NbJb\\\bT^R^JLRZXXVZbTZ^\TZZVZ`\lN^\\\TVV\P`TX^^TXfTbFZNTNLZXVfR\R`\Rd`hRZXj`VVld^\Z``VbXPb^ZXZZXRRHVD\T\NPTVJffPZ\FNRZbZZTXPJTbLRVPdPTVRJ^\\VNX\FfDfT`R\DTZZRXbVZVZPP\^VV\\NVJVPZHPZHTRLZXJPPVPTLRLP`RT`LXTRR\FXJPNRRHV>hR@P\bVVRLP`XfX`JP>RhNB^FTXJVd^4^ZZTNT\VLXb\R^hXVLXDNP\\Pb^LXTXRXVVLXVVNX\XN@VPZbBhT\  TR \ X P V T XLNVV\PZVL``RLLP\XZVX\\LPVJ:PV``\\ZTfXX@NVZNTRPX!""#X"\!!TT P"X!P L!!\"N "Z d""!Z#%P%'&N&&\)'N*))\('(('(R(&Z)(P'\(T''L'P()H&'b)+L+\(Z*T*(+,-f,**l+,^/J,-T+\,T,.H-\+`,-J**l+@+\+(T+,*N*+Z**(,)V*)+J,.)L,T-*P,*L-N,.^++R.,V,,\-T,,X+N-+,+R+^+-+^))')()('V()*++*f)+R,H*\+B+f.P+-T,-++@()(J)T(&^'%'N'L&'J)R'L'R)')N*,^***(b&%%L%%$%T%%P$N&(L&Z'V%`&T%H$%R%N%%%F(\'V$T$N$P&$$$X&$%H(\''''%$(%&*&&L)Z'J('*'Z'P''X''(P'P))(N((')J,*P)*V-)R++)N)V*,*P**((H)N((V('X(Z('&'(V('(X*)V)Z)F*)'V*T*T*)\*(+Z+)'J)''^)Z(&J)V*(N)d*T)\'''(&(T'N)L('X(P'L(V'''b&R&)b**P*'X((L'l(T()V(H*^*P*(+)N*Z'R+'H'%T'V+'Z)')(N)*'''&L'(((^)X()((*))`)(&)T+X*'L)^)(*T)L.+,^--L1/\0-\,X-+T,./0d,-\/\.T0V00V1J2Z30J01T4P2V1P2315X35/.N1-/2Z0.\10./R.0/0X/f362b1\3V14Z0X220P15T5N2143Z2V2X52R212X0P32V1Z0//H0/P//^0P1\/V//1T3J/T1F/1X0.^1`00J2P0P.-b,^.T.R.T.J.+@,X.*R,)(H)(')&&Z'V&(\'$%&&'`'`%N'V&R%H&#`"\$#V !V#! !ZHLVTNVV\DJZfRP\P`^b^Vd^LbTRDVXRV\P DP  P h J Z L ^ P N b X P ` \ N L ` D ^  Z Z ZPTVR\PR^J^\N\V`ZHXTTXVNXZRV\LTPTTbRR\JbXfXVHRRLdb^TLLTBX`TRL^dTfX^TVZ\R\RXTXLVR`TJ^Nb^T^XXXdLX@TZNdTNVZVZXZX`\^PPXJ^ZXR`J^PZXVXb`R\VVDFdRR\VRVdN^VDRR`bXV\VVZD^Z^NRXLZVNPLRFRBbDbPbTZXVTdTXLTJdN\\bTTjZL^PbZb\R`R^VZ`\Vf^XVThT`ZRTT\XNXd`PdV^XZZDb^X\dVlfX\V\X`Tb^X\TR\NTZF`PfVnNTPT\bXZh\PLXVVhlnP\ZZLX`RVTTZT\dFHfVb^dRTNRTLPRVZZTZRbVfXnZhZZRTVJVPZVJbVTXZ\T^VV\VTZVbRNVb^j`NX^L^hRX\XNTL^TFTRTZRZN\VPZTT\dVZJNRP\ZLX`TRH`J\^BP\XT^TXFZ^JbXXNRVXXTTXPfVZJVbX\X``PZ\^XTZ ` T N`^ L R ^ J V R\ `T\Z `P bZN^T\NbL\XRRLTRfLLTVdVXZ\LN`dJfZ! X! \"X#`!T!N"!X z#! Z!P!! !X"R!Z!#^#%Z&`&(B%Z&''&R'T'f&'(\&'X(R&Z(&\((T'(&L(('\*)*`)(()(X()P)*T*)Z+X,.F/,J.N-/,,<.,+*V,b,L)`,V,))h**X,*R(T(,*X*B,Z,*T)J-+D-R+P,*-B,T,N*b+B,R..,H0--N,X/V,>.T,V+H,,^*+J-))++,J*T*J-\++\+>,D+)++.P*J,\,N,\.+Z.,X,P,)V)Z+'D(`&R%R&Z&)@'%b'X))X)Z))Z)(P'R)h)R&(T&%`'P$$L%N$V%%%Z&X&%J%&%X&%B&f$"#V'$#$T##%#%%(N$#$V&`&>%N$#%%R%'J'))T'L)''&&'$'T(N''X('N*X+)N*,*V*L)\)Z+\*Z,*b,J,\*+)R)((V)(('&Z&)H*f(V+J'T'Z)*))Z,(N+T)')R&'T)P*T*\*\*)\))&'l'J)F))N**)^('')L&V'L(&'`(\(P,B*f(T)^)'P'\(P'V'))(+)(P,J()J(R(@(Z)f()Z(R*)\&'(V*&))J'V'X((R)T*P*`(T(P(Z(P)(L'T'P)\)P)\+R*(P+X)*R('*X+*)R*)/d))Z,.\*.--X/+d/F,R0N/,T./..J2`0/P3\0/001\1T1T0`/634T5220^0P210R/0P1/V/0N-L/-V.\/X/0H3233010N2.21141f23\410200^/0Z00R2P0V1/V1.b1-/N//T1.T0\1T0V/.//-/^0.J.V0,H0P-/+P,\-T+,++)*B)V+)^(N)'Z'^'&%'%^&#H%Z&j%X&R&#$&P&`##$"" X"\ D!BXPb\FX`^RZTH\XZZTTZP\VZdVPfZ^LLJN^LTN RX Z R V d h P L b b ` V Z T ` X  T JV\ZPdP\`^NffbRjJPRVVTRd`TRJ`PbXbVf^T\XZFbHPZFR`PLXFbLbDTXXVXdNX^hRHXVjNFVNZLZJbT\\J^XRL^RHRTPT`X`TR\X\V\^TbTX@fJZ^^ZRbXf^XNfT^XhhXZLZT^XRhRbR`J^^hPTbTdVTZNVN\RdJZZRPZLfj^NbR\bLLXbZLZTVXVX\PV\NP\TVXRVPJLRVVZTdZNR\\P`Z\XPbV^ZVFV^FVfDT^\^@RTTVfTZTR^X\Pb\LX^DbRPVPPNRVR`ZJL\LRJV^TJXZ`dR\^H\X^XHXVRdNRTTdPZF\\NX`RTXVTX\LT`VZJd`\RN`RRRPVX^DX`XPN\\^PbVHR^\fbVZT\RTF\ZdZPT\ZXRLVV^^HTV\JVZRZZVdPJPNZNJJR\TbPD`V\NJNbPXVHJR^JX^X^^^RTVZdJ^VHP\bhVFPHVVXRb \ bJ X  ^ V N R P R X \LLZL^L TTZPHPZ^RdPPTTbXXNRbJb\R\T`\^Z\T\FZP N"\ f X!X!V! "P!TB!"#H"V!#%&R%'J$$%''F(V'&'V(&%X&&T%'%d(P(H(V(X'&^)N'N+b)V)H*'&)()(**T+,X-V.-R-,,V,,-b.,)T*X**Z+**)X**P*+R,)\+)Z+**N,+X+j,+T*Z-X++Z,B,X+*\-^-..@.-N.N-V-T/\-V.V,,,N,)\)L*+,*L,,V+,V*d/-,),-)+*++,X-Z,J+**),*P+X)V('T'V(f(L&&V('P)f&P)*R')(T)^)\(^'&&`&&Z%V%V%$&$$###%$b%R&T$"V%J%Z$#"$L$##X#N#L#$$X$%\$F#Z$$L&Z$&($%%V&&&)X('Z&f%F%'&^%&%(\&Z&'\)((R)Z+(((V'Z+))+\*)(H((H+(N)'&F''&&P''V)&N+b+N'*^+X*L+R)V&N)'',B*T)L-+*((P%L%%*)')'&'(X'`'''\%('L(X'`+(N)'Z)''&%Z&'&T(Z)V+\+,`*^(N)))P)((X(b*'R(L'J(*'R'('R'P((f&J*V)*&T(*N,b(d(F(D'R((*b+d*`')),+)\,*+-++*)b*Z-,+,V,b.,-..20.V//R0Z2\1j0P2P0/21211`1\12L2L52X1P/X412112V/T21P/0^/b/d0//10\0V1X3h1\2P3X/V2/`02/T3J1R/P22^200b0/^/d3J.12/./.2-V1V10V/L0/2Z0./J/-1@.V/.b01.\.\-Z+L.^/,*L+**X,^,)N*Z)(R(\()X'P(X(P'%N&%L&R%%N%J%#R&V%T#L#""Z!!"D"\ P HNTR@J>XXNZPb^TNPdXd\HZZXL ZfNNPVTV\ T Z L ^ T X P T P P R R N \ T\R L\VXTXXVBXX`^RXRVVdJNT\TXTLTLPRPfVPRdVFH`ZNdVX^RNLLVZDZRPNPLbbRLPXX`^ZPRPTRdhXdTNLTXLTX\R\LT\\PVT`ZNJRRbJVBVNXh^Z^ZlTLPbZ^TJNPNRZ^^VZ\ZJTN\LPZ\PNVHfRLdPXZNbHNZP^XTTLPTbNVJ^RbP`J^\VT\XdZRTZ^X\LTPVXJ\`FP\\L`BZNTV`ZP\RHNTT`fDNdZPRNfR\\dX^XNZRPR`\RRTR``Lb\\`bRT^Z^d`VPRJZXPLHP\XVJV`PJPT`P\^RDbZpJXbVZPJV`\X@VPZF`P^ZJZRNZpJ^ZFbRTff^Z\fJV^N\^TPNPRTH\bHVPTj^`VP^bP`\TZJ^\`XXVR\bf^VZTNJ\fJRHZJ\NJLPbPXTJTlf^PBXLVRPPdhLVXHXZZFNXVPNPVF\^XdfT\TP^fZV^RZT^  \L H R F Z T FXF TZDZ\L \ XPPLZPVdVRJFXdbTP`T\RXVVXbf\XZPNZbNN\VRXH^^ D V X ! V"L " N" d!R !X!D"X$T$J&$X#$R%$(%X'P%%%d'&&Z#'X%T&F'T&F'V&%T''J(&R'P*'((X('*d**d,+R,+,+*+,b.H++**P+*)J)*R*)\*+*\+X*^,'L)*J**,P+++`+T*T*V*,)X,T-.+Z-,++*-++J+J.+\,-,L-+R)+)N+d+d-P+T,D.T,@+*,*+*\+X.+P+V,X.N+)L+)*J-,,V-,V-R*\((B'^)'P)F)(X'T((T+N((R-T**N(*%(^(X&\%N($%$N'&%P&\$V&R$,&l%#P$^#J!V#^$"$!#T"$""P#H##V$##%L%$%\&%^&&P&$N%&Z(&'#d%%V%&$(^&'&*(((b,+)(N(`*R*`)('D)(P)V*'T(''V((R(`'Z''&b&&Z'R(N*&'b*P,b**j-R(*('^(\*Z*b,P(V)(V*'&&')L&''(N(d'H)'N)X*&&)R(Z)''*`')(&X&\&b&P%&N(T(j'R(Z**b(F*\'`)(P)Z'(B)(R''R((V*R&%N)X('P'((R)^*T))**d*f+'V(''%N'V&)()-*(*Z*)d+,\*N,,-T-X+\,/L+J.L00P//^1d/H0T1/d3^000V0/X0\.0Z31Z1V2b02P1X3/\20/d2f1V001Z.0T0P1.R../0R0/Z2N110/L/d1T2V0T2T1R1R212.^2R1V1t2//X1N0.R/.J/l-\..//R10N1//V1X0011.@2X/.-R/V.,^/-,\/H-N,,+J-^**N*)`*^*+(&&R'^'%R'V$`&%Z%B%b$%N#$$#%$X#X#$!"Z! RbVJRVRRLXVPX`XXRVNbNf`\TLNNfJVLT^Z\JNBZNPP ZN \H^  N Z N j H ` T T  VH J T^ \`PR\bZ`HR^VPV\PZV`H\PPRdZRd\XT^XhR`PXNPLV`JXXVX\\VXThDZJXR^X`XPPV^f^RTPPV`Z^J`NNXR`\`NP^^LJRhT^H\\N\ZfDPXZ\dTRX^LVJTRNXRXRPdTVXPPZddTNV^dfbb`T^hXZVPXV^RbP`Z^`VZ^V^T\^\PRXV^ZPV^ZXHZ^D^VD`FZZ`XdZR^`TXPTXVZXZNRVR^RPZ\\RVV^b\XRRZ\V\^bRZJ`\XfVVf\PPfNRT^DLNVLZJRR^JVZXJ`XRdHbPVTXP`X\PNLlRDfXRR`J\\^VTXXRZXZNZHNL\NJPXPR`JTNj@<Zb\`NHRLXHJDTLfJLFFZTLNNPLdH`hN\\LP^VNH^R^`^^\JZ\VRPV\JJTJVLbH\XNb\N`PL^`XVX^bFPX^TVZPRNRN^TXXTX^dTPTPZDTb^ZRPZNV\`LXNV^L T RJ N F H N ZddRf\H\ X ^RRTXLVT\VZXFR^V\`XVXJHTZTTXXLXZRZR@ B!`!L !!"!N"R"!"N! V R \"%R#%#$%R'%%#&$'$T%N%`&V%P%'%''R'&^&&Z*V(l'^)J)')J,V**)H*(V(,`,+*,Z*+)+T-**\+Z*F))N+(X(T,T*)T+J))))D-,-+*^+T+`-'(V+'^,.*H.J-(+,Z+*+(L))+/H,L0Z,H,L,,R+)R+*^/P.0L,N+.^,P,^,,\,X+.Z.X-)T,^,H,X,P*+D*,H+h+N0R++(N)*T'N*'()()\+^-)Z,\,b)R)V&N(%b($H&%%T'%%'&&N&&J&d$$%N&"P#$#L##$!<#T&V#"N$$$"N%&#\$$$\%R')%(%V$&%&X$F&d'$H%^%J%$&&H'%(^+(&)P(h(R(V)*`)J'&X('F((V)'''()'X'&&V$%^)\&(T((Z('R*)J+),(&T((L(P((b(\)P*\()P%^&(&((Z)J&R%(&$'((J&&R(N)V'))&V'*N)%%%F%T$%&*'*(V)b*N&N*B(*R(\+('N)T(()&(((T('T)(R)'')')%)L()(()&J''Z(\+)L,,()*T+X++P-+/P,,*V,+-X-b,`./0.X1P2/\/\2T20/211104f2J10b2L2N2Z1//1012`2T.1X.-X0.01J./////`12/3F01L1J0L/X4`0.0/p/N2P1.^.T.X//.X1--,.,...0.@/--0/1/N/R301\.X.N-V-L-\0-,\,-,R-*\*)(%N(T*)V('L&&R&&'N&\&&V$L$'%'%T$#"##%R" !!X !Z! bJP T 6XXL\VHZVTbHdTZVLNZXDVP\XVT^ V TXT f L N N b ^ \ N N R P R P ` J \ B h Z ZX\XZNTXT`ZRZ\PPZVXTZXbXVNRTZZZP\ThVFLX^T`PbXRZLVNLhPVTXZBXPXRRRRNVVTJNNXRPbVLRL\bTRRVXV^TXRZ`TZPTTHPRVTXTTT\ZVX\ZTJbRjX\R^VVLLdJXR^XbnbVLRZfZV^bR`f^^RJVZLfN^b`Nh^`RXVVZNXh\^LTX`XZ\ZVZ^\\VVTRVhZbVP\P^VRZVBF^PNN^DLbZXD^VZTPfN^^X\XVTf^P`P\\NZTf`TT`\\^TbXHTPnf\\XT\X\`TbRNRPVTRfL^L\ZLRhXNL\ZN^R^B`JNP`LNJTX^ZbXXZXVTZdVLbNPFXTZVN\NXVPTTTNZXJ\ZRRVPXRZ\LX^d`NT^lDZHXRdZT\JRPPV^TZdZHZ\VLHPLTNP\LRN^XFZnPZRBP`T\ZPFPHVZRPN^X\^ZRPV`\TLNZZ^ZL\bXP`fRTPV^N^X:ZJ``TPZRLPTL ^ T J F N L LT X T d D X R N X  bbN ^  bLZ N TRRXBXXP\NN\ZdZdL\VR`RfVP\PV\PXdLN^P`BV"R!H P$!R$F#Z"#^$!\%#$"##d$`%F%\&'%%D%$#$%%V&%%%D&D&^()((&%N&R('F'&^(P()R))+Z(')+T,*L+*,T*\,T.-\+**4*\*d+)T)+N*))\*)Z,X-J-X,R.X,,T*N,X,**)++*h,)+-)+(()V,\,***P,+,H,V+P./*V,Z0-V/N.V,b/-D-`+`)P+J+L++J*,)+J)**,\+)N*)+N+*,*N,*)T)P+V**(^+L+F)f,*)\))(%&&Z'%d%%%^%L&'N(R'\&##"J$%R%%L#$X"N$T$d%\$X%f%#$Z!"J#X#b#F"R$X%\$\&%$L$$^$@'T%$N&T$R$$$f&&%$d(D&')V(N('(*X+F-`+T,)Z+'&(R'+F+V(&('\(*X(%(^&P&%)$)^*X''d'L()''V'%('(F)N((b&V'r%T%^&'%&T(%&V&%$\%#$%N(&Z'b'Z(\'('B&R'f'`)b'h&(Z(T%V'Z(V)Z''\(Z&*`'Z(b(N*f*H)J)+((\'X)X*T(((%\*)^')+(P&T'(T'(b'(X''))*X))(Z)Z*(N)')f*+,Z.,.Z-P,-*-+,R,-T0R.N0N/.X/b-.L0J0T01Z/0X/3R111d200^1>1^010/03`0N0-/0d001X1.T0T///2Z/1P1P,0/N1P2..X00Z/-N/j/..Z.V/f-L/X.P.--T,\.-0/.P//Z.Z./^1-/005X0T-N,V0-,X--Z-+,`,+X-)('(R'\&`+)X(b(&\&Z&%%L'b&&$#$$&%f%"T#V#R%""!P""\ T\PZVXJR\HXTf\fXJF\XfJ^PN^ZTRT ^ b\ N b \ > ` V X N ` b R R J R ^ fd T P `JXVZNLXFTVfTPPNLNhL\PhPRZZ`VZ\VZRPNH@hFVXR`VTPXVXJR^Z\ZN\XhPZHVXJVf^ZP`TLVVN\jbb`LbTZ^DZVTZHXTZVHXd\NbVPZNRbVV`ZX\^`PXb`PX\LPL^TVZ`V^PJVTZP^JX^XD\RV^RPNVTZ\R`\dTVPfRX`FTPfZLZRPbXPXRfTR\\\^fLZJbV\`ZXbfZb^`PRJ\ZBTPPX\NXZP`Vn^XbXXVf^bXTdP`RV`PTRVN^Fb`bXNPpRjZZ\ZPZRXZTPNbVT`RVTX^RX\bXVLBBhPVR\fRTVL\NdZdVP``ZLXRRfLNnL`XZ`BXVXPXNPZX\LP^`ZV`Z`ZZLZPVR`fXNZZRT\PVbJRRTTbVPhXNJRX^XVXZPXR\X\dJBVRNZPPRHPRL`LNb`R^NPVRLT\VL^XPL^V^`\ZT`XX\\ZNRRXb``JTXX Z  V L P R P Z R N \ ^ X X Z J V` \T V R `  XXVVZTNdPXP\HTZL\VV^XbLPbF^\ZZV`\TVZFTN  !Z!!R#V#J#P% Z$Z$V"L$\$`"R$R%R#V#d"R&&L'V%$"F$$&V'b'X&R*@%(N(L&\(\(&(P(T)H(d)X*&(^))T*Z((^(()T*+T+*\*H*Z-Z*j*+V*+N*+**\(f+F+T,X,h+P-`+T,^-X/,V,N-+X*++*F,Z**J*T*X,*R*)++(*(*-+-j+@),*^-V-J0T.,N,H,Z-1L/-T+-N,^+**)***))N)R*N*P.*+T+*+X+X*)H+*)''*P,))'+**V*)P*R(D)V(&V)&@'X)b%V%X%'(\('R&R&#V($#"R#"R#d$%Z&N$b%&#\#" ^#!""V"$$"N%\#Z$&"#$Z$$R$$V$%#^&%\&$F%T'&''^'%%('N+*T))')'X)b')R(T)J(R()'^)R(X*'&\(B&b(P'&L'V('(&Z'L'Z(('R'L''%&b&N%R&@&V%Z&&&%&d'%P$$Z#\'$R&Z&'H($&P'T&P'X'd&&^)L'L'*V%')%&L)&`&')T*')T*V)(((Z(X*)*N(()%'''T)(R(P()Z)X'R&(R))^(()*,J+F)(+)`))L+\))X,N,.`+P+R-,L-^--T-N,\.*\0d/-.L.P.,N/Z0-D4R010X101X0X/0Z1T0.1H2L3h2R1V/P2X/-P00N0V/^2/D100//112N0R2//0-\1F/\/0B2V/b./R0-F-+,X-J/,+V.\.+R-/`0P/T//R-X0X.,-\/Z//`.\0^20.,+-,X,.,J,^))'T))))V)`('^(%'$\%T%X&V$#%V%#R%#&$P%R&N%`"#!\"!V! R ! T ZZTLVD^R``<XXZTVZZRVTRdPZTNTJd T ^ R X X \ D` X T f H ^ N T \ H L  V V RP`f ` NbNPNX`RFRdLdZHbVL\ZR\jRT^N\RDb`jf`H`R\PVVX`\VRVLP\XJNN@T\^^PZh>VbHVPTDJ^LRV\NXX`V`bdLPRP`NPXNLb^VTNZLbFVNb`P\\\^RPXRPh^Vf`V\ZN^^V^TZfdb\VV^LV^\H^PNZLZ`TTH`JZ^RTXXRZf`BZXTbRTZ\ZNT`jX^VhRRX^T^ZHfVRZVPXT^P^lNRfXZRX\f`NL\XHVXZ^ZTfTN`TH\VVNPZbZ^^\bL\ZDVBTPXPhdHXZ\X<^``T^d\PTf^bL^bRTJTbXZTVXHVZTR`H`RbX^ZT^DlT:\ZZ\LZ^TV`dRVTP^LTFR<^L\^\XZRlVRZX^V\FRZ\RX\ZhV^HXT^ZX^RJXTV@T`LVdN`VTFJ\VNVRTXN\^`VRPfRTR\PFfjVPfLNRVTdVT\^RZJD`RX^\XZXDXN`ZZT^^^V\NZZ\bVlRXZVR`PXLVN R \ X LZ R \ Z X Z TX ^@`T  X TPX`\ZTX\XHPVT`XT`TbD`PNNZVLLNRVZT^b^TT\JZZR!!V#J! R"!V!!#Z%V#n#$#$!#T"`$!^"$#\"Z$%%%P%X$%&D&'B%%&'`+P(T)P(R)V(V(H(R)V('j'F()'R*L()T(\)F()X(,`++(+b*F***\)P+')P,+,+,+-V..T/,T,+P++N+-++N-X+)T+\)Z+\+J+V+L+V**)N*+*++-*)T,`.--,+,Z.,.`/P.-+)N(b+T-*d**d+H)(T(,f*),,Z+T**L*T+*^*`+H'^*X()(Z)L'Z)b),*+*^))f'P)\'`('(`&\&%%&'(&$#"$T$#&###^%$N%%"!B""J$!T!!""V$!X$H$#X%N%P"j" %V"d#h###L$##P&`$Z%#%Z&(b&R&^)T'H''V*H+`)'X(*H'Z''('N)\(`(R)(V'Z(Z'%T%`'N&Z(T%&T'(f(&&((T(X''Z(R'X(R&Z&'&'Z&&\'\'V''F%$T&R#`$T%$#J&d%X%''&&%%L$Z&V&$R(X(%H'(Z%`)&&'R(T(b&&R'^)P('T&'^')`(H&*h))T(V((&'))&V&''(N&&&)('N(%\'%*Z)(-)R+X(V**,Z-*,J,V-\,V/X0\.T/T,b0R-X-f.T3,N-X/1.`/R1Z32.Z.\0/d1V1V/X/./1N/N0Z1T1V3/T0-R0/J3^/,/./Z0^/L0R0Z0/-/0T.^0--X-j1.0d0-L+,..-P/,+b-R+*P,b.R//\0..,/-P/,+Z+-../,-,\,V,P.--,H+Z-)X*b(\*^'X(&''\)H(V&&^%L%X%P$$T$%%$"X$F%P$%T#\""F#V b" N#LN P"RNV\\PTRNZ\XRVHR`TT^RVNRJ T`VVR^XFXbH^J  V ` T ` ^ N ` V L P \ N N h f R V  D ^VP FXRTV`J>JNZZRNT^`^TVVZRLdX\N^N``RXVXRNNdRDRdXR\R`PLT@PNZVNHF\ZZTLVP`RTVTZLZ\\^X^RXhHTfJXJ^\V\RHLXZTNN^VdX``N\ZP\JNTNZ^^VL`ZVTV\PZXTLX\\TXXPbVZVP^LV^`\XVdZd^fX^b`\bZVf>>\RNT\XFPZZ^VdRbNX`d\XTPN\NXP^XRV^jXX\\V`dVXFLdTZ\dZf`ZRRZP\Z^ZTHTTVVZ^\^JHZZRf^P^\PN\V^J`LB\H\XdLVNN\TPTJT^VHPHTVZP\ZVDXFFfXXbRNZ^LX\HTbHLLVbTLbdT`RPb^LZ\dTTZThDdLdR>VXRNJd<^dPNHPVZ^XZT^^VNRN^VL\JR^ZVVXbRLN\XFV^LNJ\JXfXJRfLJFZXTVRZZPRX\NJ\PZTJZdD`XJZHP`HXRLN\JTNP`@\NRRXX8V  L J R TX \ Z J\ND ZZ TH \R PVZRdZ^XP\RTVdDVFJNFDPLXNVPVJ<XdTXfZVF N!`R! L !^"" F!b#D#R####P#""$Z#h##N"h$N"%"`$R$#%$P&&Z'$'`''V()'()Z'V)T)T(d('(P)V)')L)(+X*(:)(X*(P)*\,+*Z)H,\*Z+H+L,,b.P.+^,T,L,/R.P,.)J,D**,\,H.^+H*^+V)()X(d)**V*`+T+R)^+.*H),R,-,-N-V/b,+R,R/.-/,-+**)f+*R()Z*(X)V*L)L+V)\,Z*+N*N*)Z)P&V*H(P'J(X)))',Z+P*R)*,('&L)H)(((&(%'%Z%f'>'"#$$X#P$$$N%R%Z&%\#$T%T#X#X##T#"%#!#Z#L&$#L$Z#"H"V$F"!#P"^$###%^$F##H#"'%&L&$\'J)H(Z+V(T*V*('X)'(R)V)R)R)T&h'&'X(P((F)Z(L'%L%$&%&&N'&%R''**H('&%Z'P&R()**B('^$T&#%##T&X$#%b'%J&'$%b&&T(&\&\'&&&''&B&d&)\'P*'Z%X'T)'((V&T'P(V(T'L(('N&*'T')&R)(T(P'N(\)V((&^'(%&(T%(T'&X'V())(^)^*N'*)Z*^*,T.-,V/-P0-V/d-J-h/-+R/.P/.0V/`0/d1P//T0..Z-R.0J0/R/J3`/T1X..-X12,0L.X.\/..X.N0V.b1/10R2-T/d..`0R-.0V-,T.-B-,*)+,+,F))+**/-,.R,,N-,P--.//-R/-+,J-N+/V,f+V,*^)V))X)%\'`(V%j''d(Z&&d&P%`$#V%$$L##P#Z$"J#^%T$`#R"" " T N L\ PFF`^R`XR\Z`\NLRZLRPVTZ ^ R X R h V Z H P L V F \ P P Z ` PTb^XXb@\PJTPXJVVJ`\VLV\VZ`RPTXZJX^NNP\XZNTVTXlPLV`TNLVNRNZlTZdLXJbXZ^ZRXRbRb^`HZbRfT\hTTV^fPXRXbXV^XN^&P^`N\`\VVRF`XZNXXZZVZJV``JD\^P^^bXZZPP\ZNdbNRZXf\ZLLbbVRXXTV\XZXT`JPTNH`VZPPVJNTRPZ^^bR$\RVN`bPJVXZj\TPRHTVRLXTR\XfZdbVT\bhbRZJPZP\`TbLDZX``P8`XjTdTRZPTVZVNXLZb^N^`N\L^ZXVPdTZTNdZNZd\ZT`fRdXHdXPR^^FTRTX^RhXb`VNXXLdRTFZ\LVVPR`^XRT^PRZXP`DZ@ZLRZ`ZN`ZXZFXRJFhV`N`^TVTXZNTdVLX^XLR\VVjVPP^RTNdVXZRXR\hJ\DN`LJRTFZPbZ`RPZLVN\PNV`JPhV:T^RBX\Rd^ZbZRV`RVRL ^  Z R H ^Z Z Z X ` T T L L TT  Z NF b\\dbRJNX\ZJVZ\@X\``dL^R^LXjXbNdNXlJ\R :!  N #d!T!J"b N"!H"f$"f!^! b!T"" >#""!$$f#"R#$$&b%&H(b''(F(`'&N(N'Z('P'X()((f((Z(+'(R)Z))F)(*P)T*`,*)-b,)V+*+X+\--@.*d++-*N.^-N/,+-Z,*^,,\,Z+-V+*T,)*(`+*))V+*X*)V,J+d,,*X+,T.,b,\,B.Z.R-.Z,,,X+R+\+Z++)T+`*(R*'*))X+V**R*Z)R+P)^+(`'('Z*)V))(R(^*J))F*`(T+(N&'F%P*\&R%R''R&L(Z%%R%%`'$#&^%H'$V'V&R'R$$X$H$Z#\##$X!J%#$#$F&#N%$##R$R&\$$$"#$%$%$'V%N#"#$&(&&'T(()V&'('T('X'P(V'&X'\)(&N)d'L&\'R%&$Z%%$R&\$f)Z'T(%T&%X&`)'''V'($`'\(%\(&N'%\$X%N%R$`%Z$&f$$N%\&V&&Z%$V%<'^(P'\&P&V&%V%N%\%X&%'F'('B'T'()&\)P()'X*P()(^('&T)V'^))(*+P(*(*\('J(\()P&V)%L((*))&d(()*h+N)\+V,T+X*+,)R+V*+,`-,^-/P.N-X,-V--R/`,.\.0R,.2T2R2\0N.0-P/./N0/N/-,,+.0T0N--.V.,.X-F-X0/V0.X0`0R2.N//./-P/^..-*f+,,+R+*^*+)V)*)+*R+,d,.+V-V-D0L0/L,V-.,.^+T*R**\,+V*+T+)J(R'V'X)'R%#%&T(J&X''J&`$T$%b%R'$#Z"$N"##$V$`#\!H" !!P `ZRVHPPXVRVXRVNXLVLTJBRZbTNHHZTVP``^XTPbHT T \ X V ^ T V J \ B X N ^  > b ^P V XZZPXjLjZX\TTVXfXLZFXbd^X`^V\^\PTXLRXTHTVJ^R^XX`RPR`TJTJPX^ZbVT\hPLZHdZZXXXZRVNXPZXNVNpLT\VXjXXbF`dTbRbVXTZX\XZTbZ^`ZTZZZRLXTVZNdXTTX`TV^jT\TZVZPdT^JL\T\RdZ`XN^V^dZJNXTPl\^BVdRVT\bVXdX`fVXXVVbRXFX`J\LTTNTZ\T^ZVhZR^Z\RRJ`^^LRj\PZZ\X\fTRT^H\JRXZbRJZX\VFNZL\fT^JPbVNNXTJZ^TZN^JJ^ZVXNXTLNTP^TV`X^\L^\Z\PPdNZ\TJPXVXXPNVRVP`HVTVXPXTX`TPd`^PTTXZ^VXfD\ZX`d:LZXVTHTLZTXPVNLTR^RbNZZD\NPT\TXFVZLNLZ\TT\T\RhHVRPLdZZJVXZLTVNT`LTP\V\NLTdFNTLTZR^VPNRJR F \ TT ZX R L Z ^ J \ Z LR ZV XVN^XTNXPR\\XPVJNfN\ZXZ`VTPTbJR`jDV ! !V X V H T"` d"J P"\"R"B"^!""%##"!"V$`$$&$%&Z(X&('(L(`''J(Z()N)'^*N(*'H)'b'd)(P')T+(V,&*)T+>)F)-*,X-X-+P,X,V-.R,.++P-X+.-,N.-H-+*\.V-`)*L,`+Z,(P*Z)*\)^*T*)`*^*T)H*Z+`--R*Z,+X,*,L-.T/.0L,/R.H-.Z+,N**N*d*-b)*(V),)P)V*)*Z+N+V+(((J(R*f)V((V)V(P&J'))X))V(T)N'J''&%^(&R'&V&&%V&$&#$H$N#$L'^&T%d$T$b'"%%X#V%T%%&'%$"J"#!b#%$Z$$\$#R#J$@%%$%%&f%H%%%V%$L%'V'(B'L*V()'^*'V('&J((((T(J(R(P&X&&Z&'%H&N(Z%%V'X$d&@(&&\'b&'R*%T(^)&)X(&`((Z(T(V(b&L&#^#V#F%$$j$$X$%$"V$J%%&&J'%T&T$V%&L%#V''&N''&()\(*X*(N(''N(Z)X*R())V(&Z(P)B(T'J'(H)'X&)(&)&X)V(('T'^'R('T)(+X))N*T+*+,,,T,X+N*d)Z),\+R+-++,,*+N-,R/-+-/J-R0^.R.,-`/V-L,+Z/V./L-T-,,-*-..0-++-D-*N,,T-P.`//L/0./^00D,L.X-^,T-R,Z+L,L*V+^,*)N*+X)V,L+,)(,(-\,R----f,-d+^,N+))X,P*)T,H+*b,Z+''X'V''b'T'(Z&&%X&$\&\%T$&X'R'N$R$Z%V#$X$!L%`%f!#  N ^Th TZPZZZNXN\^T`hNVl^NNXXTVXPVXXPhRTLZLdbZRZ ` J ^ R P h N ` \ V  P T b T X RbNXX^ZHXdVVZF`TZZV\\JPRPZZRVRdJLZfNTXNHZdLTPbN`\^R@jR^\\TZRXRVJ\TXXRZT\RdL`NLVTPV\V\bVlZ\jXLZVHVN\PX^VZB`PXZLPPNVX`fP`ZZ^LRPNZd\fbjZfVVVXlVPTZH\\NNBZHV`T\^Z\\hZdX\VT^XZVF\ZTLhV\^\`\b`\X`\`\LLZVR`RJ\\T^fX`ZlDNJj^d`TLVVTf\fR\RZNVXRj^ZHhTPRTLXT`\RFbZX^dZPD`^VPdT^dRRbVZVXXNZ:bL^^T`ZZ`VNT\J^VTRT^fbVNPTPR^ZT^\VZLVVb\RPRT`TXbRXLZTFZZT NZ^`dH^ZXFb`\^H\XPZ`VTL\\ZbNV`TjV`\bVXVbXVXBNVTXJLNR^VTDRRVNNVTLhP^LLR\bVTPT`\^^Xb`^J^`PVHbRB\\NhLVZ ^ ^ XT Z P X b R d ^ ` bL b PR L  VV ^ RTHRhXN`LZR\NX`FRXZT<bNXT`XNX X !N!T!T b P"Z!!!\"R" !Z"^#F"Z$!!"D"b"d###"$f&R%'%&V((f*N,\()T&'*'+V*\(*'&)&V*'8'X+b+&,N*T+H)R*)(+,,`,J.V.---,,,+^,X+,Z,,N.P-,+)*X,+^+V*,,L+L,,,T-R*J)+)+V,)+*Z-+',+L++-R.,^0P,0/^1P.\.H.,b/R*`+,V++V))\*'X+)+d+P,*()(,P*T+T('(L*d('(T*X+R*)(L*T(V(&F')'()+b'd'X(&N'T&Z'$Z%%V%&T%%%H%d#%%H$$L%&X&^&$Z&$R'Z&%%`%#!\##b%&P%%N%%$&F%'T%$P$$\$R#$L&%%V(T'&N'V&T&%L'))'^*V'V&X'*)))V'V&V&%&'%P&P&&V'%R&%%%)'''H)J&P'H)\)''L''N&L&b&J%`%^&^$R%X$Z#%@$T%#B$"R$$N%T%^&#\&H%%L%^&P&'('V*&^&T'j'R%V('T'(J(*(J)(\*)R))'P(<('J)X'T')\)T(X)V'\&H&V&$&(T(&)'R'T(P)Z&V((T)))l+Z)*L*,*N-))V*V,*T)^-X*Z+*R.P-T-d-+V.F-,-X.J++`.\,+-,b,b0H,++X+R.V-j.,>/V--,-/H/,--),R-F*,,-0R1,.L0J,,\-R,V,+*,*+Z,*N*+N*\)),b*)J*P-)L,T,-P/N,++*,V,-H+V*\+N,*D)(X))^,'N((d)X'V''((&%&X%T&V%'T&\"%$%R$#L$"V#\#"X#N#\"N!N"d!V!RNJ!TPXZZN jLNNNRVB`PZ@DFZZVPZRLZTNLX^PX TXJ R V Z R ` \ V b R N V R N L L L p F \ X P XbbPZPPVNfH^RbTRVTXL`T^NJTX\\^XRTZ\bjXRb``J`\DXXXJ^VHR^R`LXjRXRTVPNBVXVZL\`fBNhVTV\\VTJTZRZR^ZZVbJVLPP\\L2bf\NRLVb\BZZ\RfL<TX\L`RHXLZjVRXZ\PbfPbXNXdPXb`^\ZXPXd^`h\PNNT^TVV`ZZVT\ZXXXTTV`^TLZ`ZX`RVTLTXZhP\dfB`VTTXT^\XX\`N\RLX^`dT\\VhXRf^d^LP`ZRVhJTNNbJ\jXTD\NNRZXTXTNVZLPLbP\LHP^ZXXVVHPb^R^\ZFl^^PdXZf\VPTTVPX\^PlPXZTXR\VR`LRbVbVVRV^ZL\TDVJVTHPN\V\X^LPVR\XXX`ZdJRVLXfVfbP`X^\`LVPbZbNTFD\TVTJTP\8dXHHF`ZNTLZRRV^PXPHXT``ZXL`PHZHVJ\PZ\RTNVNRPNXjNTXVZdLRZVPPJ`ZXT\VPVN^NLRZLPPF Z R L  X N V Z ^   F R N ZR DJXTLPV^bZJTZV\NHVRN^PX\NV`TTX`V`FLZ\L"P D \X!D!b# b ! d! `" T"d"N!##$#Z%%&R$\'V&&P&&V&(L)d(\*'(P((\*^)(\(J''N('`'R)'+J(T)X(T))(*++R(R*`*+.L0,*+J-.-d.T,,/,,,,P++X+V+X+T*)P+*P+^+V+X)T+P+,+*^+\+,+N+Z+,*X,,*,V,-^-V.N/B0H0`-\--,*V+T-^-L*H*b*X+R)R(L(+d**)*+V++N)^+(R*^(L(T'V()+)*X(R*N()L*(V)N(b&'T(R('^(*\&d)T'Z'N*V)&$b&V%J'R#&&`(V&N&#%N$$^%%d$$"$#b%'$$N#R##L#`'$^'&$V'V&R$&%X%%&&X%%V'%&%N&Z'%Z&&$&$`'%('(R&&&&(%&Z&&%`'P(%X&d&&%%b%H%&&V)+J'V(&&^((Z(&V)('''Z'd((&R%$#$\%L&$$6%V#V$#X#$X$$N&&^$$##b)X'%R*D''(P'Z))&T'R(b(&&\)J()^,*R*\)(*X'h'*V(`+P)F'`&(('%N&b('B(T''&')()J)(P('()+Z-X-d)P+*\**))Z*(),*+-V-\/*\,,.\+P.P.X-,^-T+,R*L)Z+P++,X+J-R*^,`-^-,b,H---V,J+X-/-X,R+-*V.R+F0.//,*+-^-+,N+))*+*H*p*X+'T*Z+\**J*)L*f*T,*)P,V+-***)b),p(H))'((^'X)j)B('%N&d&X&L'J'&V&%%X%$T'$$&"Z$\%$T#V$b" \!#\$T"^!X V!^HLPHDT\VhTLNRXRPVTZP\Z`P^^^X\ZZVTXVRNN` T P Z R ` X R ` V N Z T Z F P L  R b V dZPLZNbPN^V^D\TZN\Z`ZX@`Z\ZLRTPFVR^`HhL\V^d^`R>\NJ`L^^THXXR^RHV>`LXRRP\N^B\NRP^`VTJRTXXV^V\Z\^b`TV\T`bRRVbLbPNXV\VTXfLD\\P\^VFNTB^JLX`\X^TJXP^XTVT`\`VT`Tb`ZXdV\V\^XRVnd\bZ`LfVdVfTZd^VVLJ^h`^pLXLR`\`R^Jh`\P\PDJPdV`f^bThj\dXV\N^`RRBnVRnRJd`V`NVR^XVH^H`RP\\dbbPfLVHZb\\\TVPJZ`RLdVTXLNXTL`VTLLXfTZZPBXVb\XTRTNRVNX\^TZBF`^X^jTTbJbZXLP`NXL^LLP\TXVb`bRd`TTJVNlVL^\RlRb\T\lZNR`fT@bTRVRTbNPTJR^T^FZJN\RV^JRhXV,`f^Z^RPZHXBNNbJXZNPbXRXTT\\`P`LVLPV`TJJ^N\L`TF^^^R`^XXT``^bPT\PR XR TN P \ L L ` P F V L H P b Vd Z `T R TXP^P`RRRdF`dZbXZXXB\L`JXV\Th`PjNNPFP\`bB^`! X ZJ \"L! !Z!""$#$^&F%$'$(&'T&P'L)(\+&*'&X*D(J&^)R)P)&&(d'T''+&)*()X**R,N+)+L,J.-+-P/V,V..-L+,+^++D+,^+,+R,+,,H,V,*,V*R+),^+*V,*+Z-^,V,,+V*P+()X++R+N+,,-L-L+V+)F--,*^+++L*P)P*H)()X-`*N*(T()b+()'V&P''(`)('V+)N*))()^)('&%X'&$Z)F(`)'&b'd%f&\%B%$>(H)$'$%D$\'f$#&R#R&h&$%$$"H%V%`&$R$#%&F$$$&^%'&%$&$P&$F%\%`'&\&'\'&`(&H&&T)&H(X)*X(R&`('`&`&(\%N'R(V'R'&&%X&%V$%$$X%T&L'J)X'T&T&&%%*L&'\)P*J)N*l'^*(%N&$%\$%<&$$H&f%#Z#J%#b%R%P$P$P%`'V%%&L'\&R'&\&b(B()(X()^(P)V(&h(Z)N(J)P*+H+X+R'(+((^(*(P((%V'('F%$'X+T)Z''''(J(P'(),,B++N-R-X,)`)P,Z)Z)H)l*-B,)++.,**-`*R.L.*b.`*X-X)`-++((^*X,+*+*X+R+F,V,.X,+++-V,T++P+Z-T++X-,/,-,,++P,,+,,V)H+)*^-R,V-N**R***+T)\(X))-J-+*\+J**T*R)*)*V*f)V*)P)Z)V'b)b)'&'h$%'''X&%P$\##Z$`%$#^#T#T#$L"!P##\#!"L!!"V$!` fLJVR\NVRNbZX^Z@`FHVNHZ`LP`NZNT^V Z V Z N R ` R Z Z \ ^ Z N P P ^ H^\N\ZJRP\TVbJXNLPbLRTTbbTTR\8VPPNXTbPP`^JX\`VJPVLJRPPVPbRjVFV^PhdR\RZPTHXRPL\ZFTV^VZRP\VTPZR\^V\XPV\TX`X\V^HHZPNVXXdH\PdTX^\pHNV^Z`bdtd\JXTbP`\VLRVd\hRR^dTXJXhdfP>\bHDP`XjDBVPXXTZPdL^XNZJ\R\T`j\^ZTdT``TN\RH`PVXPTXTTZRXJFRZBbP^\\^X\VT^TZfPb^RVV`L`^T^^H\VJbN\\XZbVVP\\X\RX`\TJHZTPJTRLXTTNbVXZ\XTZPDbTVZRXRVRT\l^V\LJPZX`bRFXNR`ZPPdP\TXN^`NN\ZR^`bXDRTRNNJ`XbHXRPPZLTRTZXTP`hRXTPNZ^PZPXfbL\BR\XRFVXRZfN^ZPLZT\TH`ZZZPHZjZ>\`hHRbPTJN\fPbfRNR^NJX^\VVRlTJ\^bPNHPZRRJLRNbPTF Z ^ V J N N ^ ^ X R T P V\ TJ ZZN FbR  NX\f\VPBVPVbLX\RRD\`^PRHZRVZJd XN!L!T!h\NN J d PP !J!"T"#R%d"V%J'h%h&%Z''V')(()(X+('l('X(T*''R'X'J(P'%\'N(&)F()B*N)h,R-X,F-R+Z+L,,,+\-F+X+h-\.*N+^+*\++++**+*`)H-)P*V*+**)P**F,)`++.+++*b)R+++L+*+L,Z+X+.X1.,L*-P-/^,Z,N+(d*N++*,(+++*X*R)N)(N)T,*('`+(V)***N)())T(H*((T)X&V&&'&>(%V&$'%$Z'(V'&T$%%^&(P'R$#L&#$$`%X$T&#%P$$%J%R%l$R$%R%#$H&N&F&$'(R)d('T)'Z%V(d&&&%Z&V'J'V&X'T'%(&`&&''X'(V'(R''((F'&%&$$X'f$\%L)%X(V&'^(&%&'$%$P'Z)&&V+P)&&&*L&%&\'^&%F%$%V#\$D#^$N$J$'R%$'P%F'%D(L&F'(')V)'P'(R(()B)\(&&%F(T)j))))'^)Z(L('(P(N)Z((P'H&&L&H)Z)N)&%X'T&B*Z(X)X('(Z)X)'(X))(*`*)`)\*T*.*++)(`.>-T,\+,V+b*R-/,.-T*Z+P+@+P**+`++*+Z-)(+,*N-,-.R-+b,V-T+t.+V-X+0J-,X,T.,X.R+,+T,,f+'(V))))*((-(J++))T+P)X,,^*,T,T*F+V*(((L+X*^+^,)<*(&(&Z'N(\$&N%$$h%%R$\$^"Z#Z$&V$X%J#!"Z$F""L$!"! P" Z"V " HVJRPZXP`J^ZPXJF^hXZX^VNRPPdVZXT^HRT \<ZRR X L N \ L N b ^ V b X ` VLVJ TNdFJ^LVNJ^NXTT`T^ZX\NXNVZD^\fNXVLP^PHNVDHRJ^RXTTVRVRTXbVZXRTbVhTTRbZRLVbLNJTTR`d\pNHTP\V\XVRXHVJTRNZZFTNX``\ZZd^^X^hNbf`TX\RlVX^VTjX\^Z^XZ^XBL^VHPPLVN\^X^\NPTXTT\R`ZLZT\TRTTRZ`Z^L\ZL\TXL`\XTXTdTXT^R\dXZNfZ\R`PRNVXR\\TZZVjT^ThjZb\\dXNZBd^XRPZ`^XZd^VZZ\\RZfXVVVX^dfRX^PVn`P`VX`\Lb\VX\\ZRZ`VNJJb\ZPVXfZRTbVVZ^XVJjXR\HT\D\VZJVL^R^DhVRVTXL\RV\Nl\N`DZ\\V`\ZXXPXXP`TTXf^ZJRTTjLfP\XX\NPRDDJ^bTZTbT\R`ZZNZ\RTLj\XR\F``ZV^VRLPLZRFXJZNLRXPN6FX\\XTdXR\TVVZZTV\R\NPTXNL^b^HN\LTZ^b\VPdNXZT V ^ B b^  N H R T F T P ^J RRN^R\JL R TT^HLZTV@J`d^b`THVZLZVDTZNZZZH^b^NX^N!P^`Z ` V P!!b!R Z ^ \ l H X$N#N%##$`%(&&&*(X*>)N''''P'X(&'&Z*N)(&N'`'\'d(L()&X)X)L),(,T-+Z*X-,^-+,+L,^-T*-(,d+**)**+N*)f+P,)(*d+H,N+^**V+N*+.X.Z/,d+*,-,)-J+`++-+J/-P//\,H./,-p+X**R(,Z+L,,\+,N,F+L*f*)()N+^,X**)(N*')))*R*('(L((V(L'^&'#J'%\&N(&R'&T&%@&`&Z'V$X&X$`%b&'&\#J%%#%&&Z#R&`$b$#%P$$b%V$$#&^(H&\&V&&&`(R'V)P''&P(\'(\%T'&''N'D'&''N%%%&'Z*^&T*'F(&X((''N'(%%X'&''N(%&)%%&(J(&&^&'^&H''V(T)V)'R(D(%Z%b%P%%%&V&\'L&&#%X%`%R%X($%&&H((((*&T'X(`'^&)^&\))V()\((\&P)`')'''`)(^++H(*)*(R)&Z&T(&)%Z%)N(R'T(P(R*T(T(&,Z)\*f*,()T,),))+(H**+N*++^,*X+,^+,^+P*J*+.R++T+`+P+Z++*V-++*-*f,J+`,.R*^-+,H,.,-,d++..,,L-R,-J-h,(X+*V-^+*X)R(R(T+Z&V*^*((P*X+P*h*(T)(N(**X+)X)R,*P*)R,V***'+T+>)'&T'&&X%Z%R&L'R$$$R'!T$'V$X##"T$T%$#"V"Z$T$#X#X$X#b!T" JF"!ZRVbdRfLDRTRJZ^FZHPNX`RXB`\FTHd6NVNVbFVL \ R\ P Z H J P L ^ P V L P Z  HJV b X VTXNP\bZZfVZNXL^bNX\LZNBTZRZVLRTbTVLb^L`TNVDZ`ZRNT`JfVRXNRXXTTXP^RTTV^N^\LVN\P\PX^ZJbLZVTTH\FZNf>X`Nf\VPZRVXN`f`PDZNdN\VH\L`R\`ZJHPH^ZTLXNT\`L^RhNhVT`ZXpPb\jP\PPZRVf`RXdP`\XV\VTPdVXPVfFPT\^\RbTDZ`bPTl`V\bZZPNZ\TXVZRTV\VLXTZ^\R^TVVVTXbV^ffb\ZH\X^ZTb\ZZV\NfZ\XVbZX^ZfNTTbFVPLjXJV^TRR\VTXXRbTRTTLXbDhZTX^TTd^\\XNNXXX\VP^VVVNTJFV\XDbVXXXTRRTjJ\RLTXZP\NNTJ\TZ\`^ZTTN\`ZXFP\\TR`JN^VVPZXXXVXZHNVdH^JL^TVTP\XZbHL8TNfNZVNTJTV^HXhVZVRNTVXL^XXN^dLV\RVZ2XT^RVbFVNT^RTL`HRZTRNVX T X X ` Z PT T X Z L \ ` <F  < P Z` N VP`NDLNLL@ZFXZPLZDTH^PT\X\JZVVXXRRfJX^`b^bVPNV!X ^!X!jR!X"X!\ D V!R!Z !" V$!b$\'#&T%Z'N&&R&V&T(f('Z*X'((%h'''R(''b*)&\((V)(V)L)(^)P,V)-*V+,P+P,*+,*R*-+(b*(T)*X**X,R)T+*L,+)+F(H)(N)b)J+V+V.V..^--X.,+V,P+,+L**Z+-,N-\.\/-D+-F-+-+Z-)N*V**),T*d-+Z/,T.,+)`-*Z+:,)>())))\(`+L*+'\&T)<'(B(%Z'$T)V$P'T&$R'h%L%X$Z'%%$P$T#\$V$V$%`'P'J%%%P'R&T%^%$\%%$d$#N$Z%P&Z%%&(&)&&\'P'('&(N&T'&$f'F'$'&%^&d&X&N(%&%T(((Z'Z(R&N'((`*R)^((%T%^&%^)'(T'(R%%P&%N&N(T'R''\'%8&R'(P')\*V(X)&J%&$P&^%&%%^$b&R(#\%H'%$(%\*'J'),L(\'Z)\*\)H'^'(\''T(H()b+)(b*P)X)V)J*V(L(*+V)*B,L*X)(T(('&$`(R*)R&P'&V'&('R)&&('((*Z,+X-N)*(V))X+R,\.*(**L+\+F**,,X+P-,-V-^+,-.+*T*J**d,T-+Z,X,*Z,P,+T-**+Z-Z,R,*)V,+L+d,V,R-+T.J*j)L*P*X,V+T+)+`,T*&')d*(()T)T+N)`)X(T)()N))*^)\-P+)(T*P)V(('h)J)R%b%&b&(V''`&Z'$P&$%###V$L&#$"#$X#"!T"V$N#P%""!P `RH Z VZ`VhZDXTXR^R\Z^P\ZZHdXPVLV`PV^X\HfBZR T N B P V V V T N X ` H  \P hD Nb \X\\bJbT LPXFZLdNJXZXTZRLV`Nb^X\\RdJNNVbXbPLbPRXRTPXhjXPXV`JL\Z\TRb\NZXTVTh^TXT\Z^J^PTT^jX>blVXVPNZXTNNNnH^^ZVZdRbHZ^BfdNTVLd^XPj\bR^VXjP`VJJb^T\X\\\LNXRj^VVTV\RdZTJfTZR`Tl^RPZPX\XbbH^ZjPVRXb\^TNRZZT`ffTPdX^\ZVZDdPVZjVTPTdPVVLZTLRjV`bX^fTnRl^VfXBfDT\XR\VbVRR`JLLZDVV\ZHbHVP^RTbLZd\dZVPdXRj\dZZbZRdRPRPb\VDZ\DTTZNfPR`Nbh\`bNTF\XBbVb^\V^R\`PZLRPR\JLTP^VbL`L\bTVZXXP\LR\TRNV`VVL\HZ^LDRRdVHZ^TbJLVPZNJZ>FTTNZPZVNH^RfPbX\NXVVP^H\PH`NPPTVPVbRXXZPZT`ZVJXJPB^T`VRX\XVNNXT\TNZ XT J L T L `X T L Z B F T^ P VV  PTVRTfZ<PVNV\LdZ\NZF^PVT^`NZRjb!X!! "N\fP! L#!!R#T! "Z #"T##X$j$P%N&V$h'&Z%$''X'V'`('&J%(j')&j(b&J''(''R('''*H+T*.,)+*)*+J+*+^)+.+P+Z+j*+R+(H,b,\-`+*J+)T**-R,R,,-T,,\-X-/T,+--+J,*L+.V+^-,V--++-.N+Z-,,`,^,+T+R,Z+X,**\,T.H,,**f*)*-d+,+R)Z+V)*)'V((\(Z)V('&&N(P&%(Z'R%T%V$H%&%$%%$R&R$$%$X&H%R'V%%\&L(V'%T&X&P$L##$%N%$%T%%'X)\))(^%&'&\&)('&&(V&&Z(Z%V&R'&%P&T(N'('\&R'$P&'\'H&'X&P&'''^'%'^'%N(('&^'^&&L$%'''`(D'N(&$T&&Z'(T+V((H'b'J'\%Z%J&&%%L%%%%N(L&&L&&T(&J(&((Z*)(L&V)L&V&(J&'(%''*(*X+^(R*)*T(d*H*`,)+(L)(d(Z(N(&'Z&&T'&(\'%R'&'N)P('`(X)$R)'(*R+R*)(*))))(R,P+,\-D,P,**V,^-X-,(,T-,,*X+R+T)>**X,++P,*-P,/P,,+),*R.N*,Z)F*^*^+*+f-F+J++Z-@0\+H)Z*)+j+('T&Z'Z*`(R(b+()X()'*(`)+)H+*V*)^)(V+D))&X)'P'$J'^&J(b*R&''%L%Z$b#H%H%T#$H#`'$f%Z!^&X%T#!"%T##$P$#" Z#ZRXZLPTXVNVZ^\TJPXHRLTJT^\L^BTPVTR`JfhVT\J\XVX \X  N D Nb \ \ T T T b H Z d \ PD\\X`TP^XfbP`\VPTLPTTXT`R`XHXN`fJXVZRXFZdH^XVVP^\bh\F^^LFTPTJb`LXRJ`RTVLVV`TZXH^^\T\b`XL`\V^NVPP^bVJ^\TXZZ>ZZ`VT`P^ZZPRZRZR^VTRTP\Z\fVPZVZRb`bRTXbPVd\\ZZ\rJDdh^\`N`b^PTXTX^V\NJNRRT^R^lR`ZRbf^\LXdXX^^ZNVRJX\TPZ^ZNF^ZbbNXVFZ\RdVXhbXV^PLVP\`XXTX^`JPLP`PRXTZdXPJ^PZJFFVTZZZ^LTX^RTbXRPbnZL\dD`NRPRXZPbdXZ\XR^^bLN^VV\h\ZJ\R\RLZbVJDR`PDdJ^V`\TZJVVTL^XNfVPR^ZbLhPn\NPZ\V`Z`^FTPJPZ`Z\LTRVb`VJZTZNZZN>RNXVVVLD^fPVP\<RRTVTVNPTLXTZ`BRTJLTZVFTXRJbJ^fTTRVZNLZX\TRPDP`Xh^b\LXXP X ^ jL H ^  X P H J ^ H ^ T R R  V\L NLZR ZR T ^ RVZVRdRLZZD^TPdVVLP\RXRNNDPJTF\NL\XXRNZ"b d! F \!H X V P d N!R!$\$"R#`#T%$V%T$X&J&V(X'(P&\'T&^&%'&d&^%$&b'P''P)Z'(H(`'&*(H*+^***N))N)X+j-Z)**^-)*+**L)*',,*`,+^+*)+^+*+J,,,L,--V0d0\-.h.L+R+*)V,**V**,L+++J,\+-L-,-,V--V+P,+-P,\/\+,R,+J-V-R.+++,*R**)R)+X'*))()V'X'H&V&R('V&X%%b'%X'`"X&V#'R%#L&N''&\$&N&L&$$&#%V%$#P%$#$%T$&N''V)^(&T))Z)'F%%R'Z'F'&'Z+V((X(%N('V(&'X&%'&V(R'(d(N''R('Z($L&L&\&&Z%L&(T&$$%`)&P'')&(%&R'V'R)(`''`&%''h&'&'f*(&$'%L'V%N''#P'#V&V('((N'T'R)R('X*`()X)`(N)R('X('`)N'\*Z)X(,P*b*)*R(d+N)(R+),H+X*(*Z*b(J)(P'\((%R&$T$&((%N'Z'P+J(L'(+*N*V*(b*X*J))+)L*+\*V,V*X***X+Z+\,-+X/+Z,*+Z+-X+)X)+`+T)))V**N,N*+T+V,P,J-^+,,)F+j*),^*+N**J+*T++\*)^,N,\)+b+T)`)'()T'R('X))*)'\(d((')J)')*)''('&H&'^'J(&^'V&Z'&$Z&$%%L"#$R%#j"$$#Z#"#Z$T"#^$"T#f""!Z#! Z! VXVHZdRJ\BVP`TdNVDP>RTV@T^VRR\RTLdZVP^ N \ T \ ^ \ b \ X F R Z P T X P ^RX Z\LRD`TFV^TZ^RLZfNP^X`H\hdRN`N\ZDBZVR\dDT\\RTbHP^R^HZXZRRXXPbZRPHZX\V\^RVZ\THZLdRTbLV\PXTJ\TNV^Zd\XZR\VLdXB\\T`X\fDf>Z^TX\dNbdN\ZT\H^N\X\PVZVZXjTNZFXLX^dZTP\nPVV^VRZRNbVNN\^XTHPVVRXf^NRPX\X\T\\\V^XV\`^ZVfXVZTd^RJ\Fb\LVXZTR\TR`bd^FfTRRTFVXf^\VZLTdZ^^THZb^XhfXX\VP^^T`LZZ^\TXX\XV\R\^bRH\\T^VTTfVPZZVVTVTZJR\VbP\VXZZZX^VZVVFLPXbVXXR\\6V`PZ,bPN`XP@^PTXX\VZLZFP\JXL`PJRdBTVdNRVV\\VjfPhRTZfbVl\fZRdJJRJdZ\TXXNPLNVTNJXRd\TX\XLP\`RJV^^TNlVNRVVXVb^ZN^VPZLZVXd`\RXZ4RRJTHZd`X\XXZbLJPX XL ` H P H d T J X \ b T h ^ d V Z\V^J\ R T L `N^PLTZV\T\^NVLXbZZLhdXLZ^dB`LbRdVRZTRVd\^  L T!T!`X"Z ^!R" d L#!!#H#f$X#V$%#%'&L'`&X)H&R%%T(V(''(b%)Z&`(f('D')T(Z('(\*))b(N))X-J')V*V,*))`*T++(*Z)^)(b+*L+)*Z+*H,*-V+f*V,j+-R/--P/.\/.J.P+,\+Z*-R+Z)R)*^*,R+N,R-Z+.+Z,+Z.-.N/h0.Z+-+P.Z,-^,,\,\,V,^,^-\,*V++,*)L(+J+)^+)\'('(`&'\&B%\%&%$%$X&^%^$R#^'b&N&%T&&%j%\$%T$X$R$`#%"X##\#&b#`&R'&%X%T%$^&''R(N(X&')X'V(B*)H'f(R(\'''((J&)N&F*R(V(R+&V&(&J'^''*&'L%^'''Z''^%D'^&%^'(T)Z'b'\&Z(T&%V&R&)&P'Z'J'L'%%&T('%L*X(X'N(%T&R(V&^%&T%%Z$'Z**'''`(L(R,((^*N('T(X)(Z*(T)(*T,X))V+(*\*X')&2*T))()'&''X(&%J(R%P'\$Z%(T%V&d''(F*b()\')%P(Z'&V(j(&&T(f*X)*V(*X)(d)N()B*V*))F,+\++V*L+Z+X***j,T*b-*+\,-+^*++V*H-X+*Z*+-**<*R+P*)`)X)Z+)+H,()d+)R+(*+((P&)L&'*V'Z((N()b(b')('\*(*)**Z)\)f(N(`(&V((&T&\&R%$%F%%`&X$V$T"V$^#X$#N#"#F#@"\#"$$N#V$b""!%!!` H N RV PVF^RVRbVRPXXZPZ`NVPRH\T\\LLRHTNL`hHJ XR ^ Z ^ R ZV L R N F Z X Z Z ` V \J`\XNZ\V^X>`NTZ^fhT`^ZRRdF\`X^LZXXT`fRfVXZZVNXX^NZVXLjP^B\b\ZZT^d\X`RbXVNRV\Z\XVbXVL\`\NPTVNVVhXXZdVXD^D^VRVb^\^PVVP`bP^RZ>LXRTTb^VV^^VhHDJNN\b`^@ZZL^TXVXVX\NRPbV^bJRbZZ^Tb\XZTP\PL\P`VRHRVTdV\VVTXTPPf`Jb\XR^`L^h`TRJZlX`XX^Z\bV`PXbLVNXZ^`RbLLP`.`TR\^``Zh`^Z\\N^TZZfZNL`T\PXRRP\ZT`\N^VNN^XXbVPXPXTVRX`RR\`\PfXZXDlTVTDNbNZBV<\TVVLVLPZPT\\ZZZVPRZDV`fT\^\\JhTZV^H^XhNbNLZDTZXVNdNHNTZXJbR\R>^BR`Pj^TVTXZTFRPRPPXZF\\X^TXRZVbPbJLJN`JZXVZVdFXXRTFTV\RRV^XPXXZR`\\bPXLZLlHdFZPTR P  V X ^ X \ \ \ VN Z T X V N P `\RN P^J f ` J\TXLNVPTVJ`JZRTT@d`JXN\Xdb\R^TJ^VZNfZN VTnX VV LX F !! X Z \!^##\!V!$$!$$X%^#^'#f'&(^&'%&F')&'&*f)'d)'V'&\%(X')L))@+((b(+*T-(*'b)'(++P)\)*T*)*L**+*)+X+H+T,\/^1X0+N.J/Z/,,--L,\,*,T+-Z,J+*^,+,V--*+.R,,.-V-/-^0-.\,^+X0Z+Z,+,V-Z-++L,`+N/,,^+)f+V)+('*('\'Z(%\&&$%X'V'H%%$X&`&#R%%$b%%%f%#R&%X$L$P"T%$b%""!##$P%&N'^'&L%\&&&V'%''T)*R*\)`''V'P'V()'X'&T()'F(((X()(V)&))R'R&%%P%'&&T%%&V%&T&T'&\)h''(\)%%d&%&V'(Z)'V'%V&%`&J(V'((f''%V'(%V'V'X(R&X('P(V)J'&)*))&\)N*V)P)()J*)'F*')R)d(F'T)^+`(Z+X'()J))''\(N'*^)f&'Z(V'''&d(&X%&>'&%&R&&'N*&)\)\(('&'(((R)X,T+(T()N*d+N)(Z))V*V++*)V+P-Z***)(+)^,)P+*)X+Z,L+N,)**T+J+\+*T)R))H*V,T*d-X)+'L('R((X+X)L(P+'*f(%^'P)f'V*&'\)('P'(X')J)\)('R(V+D))*(R&J'$X&&X&&D'$$^#"#\##$""$`#X$"d$T$T"!b"R""T!"R!V d!\!N T!TVLV\NV\ZPLNbXTNH`LNPbNXTPTDTdVVVN\PXDXLLX V F \ R D b ^ V Z > N ^ P ^T^>`^N^P`DZVNFNVb`TPPTLhTNjXZTVLJ^VVRdLVXN\RZTR^NRR>PZLRZhH\FZRhX^NLXVT^VJ^\Xb\b^bTdNZNT\fP^d\\NP`RVFNR^\T^^J\T\PhRHTTP\PZRXFL^R^XHZb^DZNX\NRPVH^LJTZRZ`P`N\RJdVXdPLb`Vj`\jNRBhF``TdNVTRPRVNJZfJZNPRP^\<RVRfTVZhb\ZD^\RTRPPTVNXPNT@^\RHLhlZhZ^VHRZ\PXJRPPX\\VRbT^HPLh`T^TRRjd`LZTXbP\VP\VTVbZNP^PZDJNLTVHNRVZVT^TfL\RLPTb`VbTJVN^dZRTVdb\ZVT`LN`V@dJZX^^^ZZHNTZ>TdZ\TVPf\XPL^XRXZP`ZVXZVfP\TNX\JVZZNV^P`XNZPR`RLhZX^HTXfX`P^ZZVVV\LjP\LVLRVZXPLVXPd^ZTJVRPZNX^HZbDTdT\XdZNF \ R X Z @  T P V X X \  R V  \ V P ` FXN^JHNXZXXJFX^^LJZVNBb`^RZ\JZ`j T"P J! b X!F" X!PXVX !`!#T"`!P"J"L!R#"Z%Z$T%D(Z%&&X&L$^'H''V(b'R')R'&(R''&L&`'^'Z(V)-L*)Z)R)R+T*+*V,(&H+T+R+,/x++*V+-,-b,++P,T-\+P-,,V/..,-F.,/V.,-+T*+++V*)),F*P-+*X--*L.R.-b0b-Z.X0/b1,-++V-T++**P+.V+X.F,\,-V-\,)P))L)*Z+) )&&(L%X%J$R%$L%T'$$P$&$%%N'P'$"#F#b$%$d$$Z$###$T&#$X$#X(%&V'&%V&&'V&,X'L*R(Z&&T'&L&T(Z'J))+'X(()'('*X'X'%(J&Z&b&V'\)&%R''R&(^'')(Z(%(&R&&V$'%l&N&N)R&T((V(&'P&X('(j&`'R'&N&Z'*X'J'(H&('b'('%'Z'B)H))N,(L+H))H(b('\)T),N((^)V)J+*T)J)+Z('D(\((b,)*L*N)Z+\'N'&`(J')'(X(&V''b(&%&%d(R&'Z%Z&&%'&N''&P(&^'X)'\*V)+T*(^(''Z(\*)++Z+X****b+N)**`-)`*B-N,)+*))**(,Z)H+*^)J,R+d**)(T)H'J'^('&(%J+R(^(''V&R'%'('%%''V(V&\(&Z'&&'V(&T&'T&(%&'$'`%%&$%V$T$T$$#"P"V!V" R"T%""Z"T!J \#R"P$h"! R ^" DT VTT``\LPTTPPZVRdTTT\\TXbRRR^XTRXJ^TRVNTZNfVNRRXXJ XH B ` b V T P V L T > N Z ^ R ^ R P\XTX VhLZ\N`\PJZHbPZ`VbXPNbPT\\`PdRF`TTNPZbZRRRRXTJNL`hbZNVX^VL^hN\LHdRZ\RVXPXhR`Z^TH^ZRLRX\NP\\VPNZTdJT^T^^^RT`^^TTdTPHjfFfZddRhJR^bVbb^ZVXHTVfZZ^^hH^ZNRLd\XT\Z`TZPVVP`\TRT\`jRjHJZbdB\NhLf`FP^hXRLVP\bLZVVlb^\P`XPPZZRXTNRZZJHXRThRPZRZNP`RNXNHP\^`RNbVfTTXXTbB\V`RT>PZRP^BVN\NXD\\NPVXZVfPZNL`J^V\^TTTbTHd^TNRVPZ^\TPT@RLB^H>XNZd\\\NbXPP`P`D^TVZXRb\TTTHZLN^dLZFRHRV^JPNFbPPXNZXTXX@\<\JJbPXXPZX`TfNLJR\L^XF6TV^TNVN\XTLRV^XXZPP\PZRPJRNX`TNRTfX\RRVZRTTVRR\dZ^ZVXBZZD  H \ \ b X P V X bP d R ` P T ZTN R`  ^ T Z R Z RTHNTT\bTRVH\V^XVZL`NPZ`T^FT`JPTXX  T!ZR!!V!"!HR "!X"#\"#^!^%R#X#$"P%$(%''%$b%X&&&'^*R(''\(&X(L&^)\)T(P)N*^**Z+)^))^*P**`*h+N+H*,+`,V,`+,++\,+.\,,`.,V*-+`++,N/X.+P.Z.-d-`/P-,d,*++R+*P,d,*X++P,h,,X,-./,V1b.V.d1R0/-Z,--,H*-,X,T-B+/-+^+T-F+)X,+)F)+(>((\'P'V%%&\(%Z%%^%T'$#%Z$^#$"%L%V$`%^$T$V%P#^$##P##T"P$N#`$T$X%'$&&&$V'%P'T'V()')(f)Z(&&^'))*V**(h*R+X&L)X(F,\()*^(%&'X&(H'($N'T(R'L(^(^'&(%'\'R(^('\(%%Z(`(&P%&'&%d)()'&L)&'&Z%X')B&)V)(T))'\(''>'(h'L)')'R(\+)&((D''V')^)b)(+*H(&Z))L))*F()f+)J**b+F'%L)R&P&X''N''%&'L&Z%&T&%^'H%\$$T&'R((H(V(^*N')L)R+'V((X))^)Z*T)N(((V+*++)d+Z*)V)*P)`*f*D*+)+)))b)Z*,)J)`+R,D),)L)^*'(N(Z)'V)'V'Z&H)''Z+)&(%V%f%%"d$Z'#'T'N'(b%$F(&&&b*N&`&'R'&&'d&L%P'%T(P&L$f$#L#$`#"X$`#!X"\$$"f"V!"R!Z!!!!X!"Z!!\`!F DXVZ `VR\lZPJPRVRRFZRNPP^VVLXDZZR`XTRbVJR`\Z L \ N ^ R N X V V X FZ T n ` V V\X V \PJNHRV\XLZXNVHXTXNZXRVPVP^FZLTXLB`R@JZ^DDT`NLRXNVV^V`^LPVLXVTV`NVNP\RXPTHV\fVbbdXXP^LLThV^VVJ^XNPTfhL`NV\JNHHP`HV\PZNb^VRVf^HX\J\fb\N\H`V`NZRfJP`ZbbV\P\f^N^fPXd`XTVbdjVdFbTZLRT`^RXRb^\VZVZZ`NhPhX^X`RNXTZ\XXVb\b^hf\h`bXZNbbXPVVd^TPV`PDVTXT^XPbRLPXXdZHhN^fPZJ\ZR`NR\TZ^X\dJLRRTNVdXT^XZV\RRNXZJHT`J\PPLZRL\DLJNHPTVTV^ZTdVR^hZT\P^XZTZPXXTLbTXT\^V^\Vh`PL^`PV^bVXLZbTT^^ffTJRZbpTR`Z^^XRDLLNdVjVPXX^JbNXdTDZ\L`L\\TPZ\\`XXf^F`dNRV\VXbdDbZ\NPTbNZVfFbRZfXJ`\\XXVX\RJT`T0TFPT N Z f \ D ^ N V N T b J Z N \ V N X <\ X b ` T X JT^\LTPPRb``ZJRRZLR`fPLPJ^RVXTRd"" Z! N!T! LRL !!V!"P&"N#X#P"#""F%#$$%T&X&&%P%%\(f&%^)(\&)\)''''X)()D)(Z+\.(R++X+)+\**Z*F,-+*,-T.,P-L,-Z-++B*H+)J+++.-J.h++\+`,R--/,+V-+\+**`+F*+++,*,b,,*`,H,\+H--f.T--V0.,P,+,R,V.)Z,,b,*b+++X+P*+**)*)N)@(P&Z(L*J(R(`&%&%&#%L'P&^#V#"J%f##%#P%R##"T#Z$d#$%Z$###R$X$$$R&X(&T%'&(J'\''%&V&\'X)&(V)d('R(X(R*L)L)J(T(`'B(b(('V''J)X)P'R)''&%&)^(R(V)&V&T(V&&\(Z&%'&T'*T&R'%V&X&T&\'($')^&R'Z&(b(R)%Z'N'(''&Z'(>)\()N'@(&''b)V'X'X)%L'R(&'*%N)X()))R)P&&\'*L)X)`+*V(X)T)\))L)'V'`(P%&('%(&&&J%%%&N$`%H$%%'T%(Z&'(&(L(^*L'`*N*^(J*X)H'X&V(T)&)'(*()r+)V*N(Z*)())`+T)X+*((V(\)\)R*b*H*T,Z+`++)T''F*J(T')b'`(J*(L('b)'d')L&N&X%V$&$#T&$V%&&&T&R&%$&&%b&%%R'V&'&J&X&X&P%#$$#\$#T#J#d%!""N#T!Z"R"#Z! T "h$!!R H"!d ` bZP XjZXTRR^RZhPXV^RdXL^N`fJP\RR`N>THZbNXVhNXRXJ  f Z L Z d Z V P d Z Z j V X j RZZ\ P`\X\NV^H^ZF\b^NNXZP\NbVVTd^n\VZbNfNVD^\`dT\FVRV\b\bVVT\TVXP\ZRRVZZVVTHP\JTNN`Z`\^TV^TN\ZJXL\TTPX^N\Tdbb\ZNRXh\LXTlVTTRZXlBDXXZfLXRVTTTRHb^PRZZb^RbPTjT^TNXhXR`PhhT`hLJZXTLJTPPTZV\PN\VVLNNNN`dP^`LXRZ\X\bXh\`TZ\Hb\L^PLPZR`PtNPJTh`PTNX`VbZXZf\`TTXVfZfjfZZTR`\XZfNVRBbZ^Nl\^NRbRVNZbVNPbTdXPTdHV^PZPV`NZPdH^`fP^LJX^TZ`X\X^NVJVZJ^N`HVLZZ^fTL^RRVH\TJ`R\L\^\bL\PTR^fH>FXRHZXX`VZJ`DTRbXV\Z^`FX^^PZPTfFLNRJ`X\^\P``^VRL^J^V^JfXT^ZZ^LX`^JPL`PLXBXV^V\VZbP`V^LV`jFRV\TNLB^`HP:XVVJT`LXj TR X Z Z ^ P J R X \ Z n T J ` ` X R  Z V J R F R XXT^XV^BVXR\ddV\\HZN^PDL\RTXZTRJRVf`V^`TTlPRvR! VVP !Z!Z!f " #R"!f Z!#""#X"##^%&N&&j(X&h'R&&&'^&@)T(X&'P(''P('L&R(\)\()V(\*D*))+T)T*)N*^,^+T-V)H+b/B/X-P-X,,+F.+V+L+**-F,-P.R+^,,X+L,,H/j-<-^-,^/X,+)N-`+D-),j,X,++^-*-+*\,*,Z-T-X--,f*++++f,^,H-+T,)):,+b)+X,(),D)':('&>+b(V(J(f(X(&%)Z&L%J%d$B"N%`$R$#R%#D#%#V#X"#R###$b##$R&P%R$%'V%F&L&T'R''R'd'&L&(Z'X'')(^''J*X&`(`*+T'R'''Z(R)\(<)''()'X((h'L&&&'H&(H'Z')L'Z*R''\''b'X*R'%%T%%$'&&X&'%X((`'P&N'X&\(&P'N'L&(L&\*R'P)('(R*'&P&N((%%%)+V)(L&R)H&Z)R'F(*'V(&^(N)'*T(H))X*H)`''$&$&`(\%&%T'&P'P&'%R%$X#D$$#$L''J&D%Z&&P'&&P+)P*Z'J)V*^&P%R')'N'\)V(()V)L((R'(`+(((*()V((((X(&)()P)*,T*T,,((%'&')R))T''&'R'('R(B'(%%&$\(d&T&N(^''`&&&%P'$'&T'%%Z&$'$%\&`%L$Z'##\#P$"\"^#"V"#`!#"^ !X!!T!"L b  P!\ ^`PRR TRTZXZZ^`^HR^JHL`ZJRVbFPTHV<^^NVPZL\PT\ ^TPZ ` @ X N Z \ V ` N J H J X P N  RHb@`JV\`V\TfRdPVXTXHV^N^^XPVR\VXTVdVT`VPf^`XT\TZR`\R`N^^^Z`TXZXTZ^L^R`ZdP^bdRV\^dPVJLZPFRRJJ^^PXHPXZbf``VTLLTZ`bZX\bTNZ`ZT\Xd^\H^Z^`TX^^VfRLZFdZTTf^ZZR\^`ZVRX\^bZjHHZL\VJ`^f`PXTXbVVZRXZJPd\Z>VT@TXPb^V`,dP:Zb^bTHVLZVF\^VT^VTThHNVZf\RVR^X^ZTZT`fZX\dXRbXPZfZVNN\^VHNZRTRbTJX`bPNZ^\`ZjVL^XXlbXVNbdHXPXZ^Z\PLbF\PZPJ`X\XZVjNXBjbR\TF^`ThbVLXbZL`lZPLTd^PXVVdJZfJXV`dPZH\PXRVZL\PZNTRTXbRVF\JTXV\TV`ZT\TPR^TPRNVbNNLVTdJX\\T\ZTP^TRXJVTZ^NN\fLVXVNd`LNHDT`Rb@`Z\RLVTVPPVXVTTRXP\RZ\T\ZV>>ZJ^L  T T\ \ N ^ V \ ` D R F R \ P X T T R f NnZTPTZZb`HHD\LJJTV`PRXVhF^XR PT V!^ V b"f !b "N" !!#b#$^$\"Z%$$T%&P%'$%V&&&L(Z''d)P('%)'B('T''*(H**(b)L*L(h*))J)^)Z*+V+d.Z+R,P.L/R,d--,d+L-N*R+`++N,b/,,V-d/+*-R..,->-,/+*\*V)V+X+H+++-+++Z+*X,,*Z+N,N,++Z*(D*V,*+)*+L*Z*V*(N)((+*N*))+H()Z(Z(P)^&(T'R'P%$j&$V%$X%%R"`$$"#V$$%T$#Z%b$%%X%N###V"^$ ##$$$$(&'&*''%%X%V'(T)'^(V($(B('V*R))T)'^''*P(P(X'X'd%)&d&N'T*&L'V&'V('&\'$)Z'b(T%'V&^&'T)P$P(L'\%&L&T'(&)'$Z&$)T&%`&V&R&^(N&&(N'('J)&Z)T'R*V'V&%$%^&^&D(T(J&\&N((&B(^)`'Z*R()V))(()(^&&V(%$'&&J(%&P'&%Z%d'$&F'$^$%&X&&l$&b&%H&%&%P&$&V%L'&%\(&('d'&&\'V)X*V(T)'R(f)')'\'N-*L'X*\*V)Z**h*)(((+X)N*)N()Z(P(R(^)N'P'd)(T'')&L(&('$&J%$T%$%(X$$X'N'V'%$'^%d'"#\$j%#N&Z'R$$%L%&J&$$%#l#R##"V "%D$# L! !^! j X  \" ^PV\NVfVh\ZV^\RJ^`P^\ZPRJZ`V\^\\LTBVJZN`\FPTF L V ^ N T Z V P ^ N X \   RVVXXbfN`VRNRVbLX^^R^JXXH`VhRNRTVZZN^@Vj^\F\J`RXNbXPVV\FPVRFZJ\^PVTXNL^`PX^PVLX`bZ^L^bPX`ZnLXRX`PPXHT\RXXD```^XbfNN^R^RT\RNRZXZRR`NTZHVPPZjLbPV`Jd^TJbJVZd\N`TXNN^R`TZNX\XBdVLJ\`TTZR`\hN^^PbFJhBVP\`^X`ZVL^2T\VZPRXRX`V`b`NNbVNFZXd^RP<PZVZXJJVb\LJNHTbN\Bh^TNX@\X^Rh\LbZPbT\NTZ^LXHNb`ZRL`T\XTfTLVXTFVTFZTN\ZXjd^ZPTVT^VJPH`NTN``ZXP\VDX\PdXPJJ^XLLX\XTNP`V^J^LX^RV\NRHT@bPZLTdTVb^NZfZThdD\TZR`VLb`V\LJ`LR^NX\bXTTNJZV\ZRVHZRXTbNXTPTRHVHZ\F\`TBVVNJ@TZTTZ`XNRZXVVZR`PVhZ\RT RJZ\NXVbXTTxL\HTTV\DBZTNJZ P  XZ T b  \ P R ` ` F T J  H R R L J R \R X`TNJdPTZJ`VXNTTTFNPV^`^^N\RBdXT\XVbNXdRVTD"\d L!X"V"!^N \ l"R !l!Z J!$^"Z#\$V%T$N&Z$Z&T$Z(&P$J%&V&T''P'&&P(T&>%f)X(((X'&('(Z**\)P+V,Z.)'*)(\+Z,T,/Z-F/T/,R,`.\+^-+Z--T-H+^,N+,,R.,-T-.X-Z,L.D,R,L,*,,+,T+*N),*)\*)L,Z-,+H+T*R++,J,X)V('@+X)*))X**++\++L+))Z,*F+**((N(N(()&)&T&J$"$D%`$'T$$R'\$$%$H%$T&N$\$H$N$N&$N#V#\#T%"&P#^%N#F#\$Z%%J&&$%%N&J&`$$$P%'&('(&X&(R((X*Z)^**'(J'*P*V()X''H(V&h*L(R'\)'R*((R(T'%'&(&&X)T%&%%Z&'')P&)''T(('&'&b&J'&J&^&J&()@'X&')*(J(\&D&'H&N'%)%T&^*%^&J''&\)'V+'J'T(&L'b('%'%&L('N'%H)&'^'(T%P'P&&#$P&$F&$"#"%X%$V%V%&P(^%N%X($T&%&T'(&(R)N))J)L))T,)'L(X(T'N'((P))D(X'Z*\(b)(P'J(%(Z))(N*V(V(()'&P%&L&^&'&J((N'&d(&^&&\)N'X%''H&&%V&$%$$J$$V%#T&T"#T#$Z#F$N%$"$X#\$&%P##J"b$F#T$"P!!T#"V " L h!"P ! !J! N TJVVZZbTXXZNXXPT^TPXP`V^R\dXB\VZPVbPRBZDJZNZf`FZXPN\  X\ D @ h T V Z N ` L B V N X ^ RTZVLVTXXZV\JZR`V`\d`6nZPVdT\R^bPTd`V\R^XTHTJ`RV^L^^`L\jVNRZVN`VR\PFhNTR\>XDRbR^X\X`\ZJNVH\`\b\JXV\RLXV\XP\dVXLdJ\XBVNdV\HXRZX`TTfT\L\NX^H^NTNT\\PjTPTXTJLTZPZTP``N\dV^TNXT`JJZTHPTLTdXZZ^H\VNR^L`ZRN\XRX`Rd\h\b^Z`Z^XNZbRXZ^P\@\Z\VR\ZVfRLbb\T\V`bPPR^^RTVjVXT\\RPlH`ZL^TTRX^PZ\`XXXJ`TTZT\^p\LNhTZV^\X\VJXdbRZP\J\\PXbRbPTFR`LZVB`PZBfdbPZRRVXNbZJ\X`XR\ZfPRRTJNHXb`VTTFJZTTTPXXNTTb\VNJHVJ^VZX^Z`NVDRjR^^N`PRPbRRT\@PTfPVZXRXTXd^NXPVPNN^VLLHVXRTRXT^DV\ZT`ZXX`P\b^`ZZ6VPV^ZR\h`XXFbVRVZ`NfDZ^\X  P Z VR T   P P Z B Z f F b Z Tb L Z TN  VZNNZdTRNPfJVPZbXTZ`TFRTZRF`PRN\R> \ VP"NhX !!\#R V !N#Z"T$`%Z%P#$X%$%%`&\%\%P&&*j((J(T'^&(`&^&^&')T'`'(d''X(L((*Z)*F)`'N)T***f+N-,--/Z-H-`1X.+,-Z,*X+,\,++,V-R/.X.L-.D-+-/,+R.`+N)V+V))((X)*\*T*,T+P*T,P))\+P*R,\)L*R,((P)b)*N*+*)H,n-+V,H,-),^.V+**H)N'(%P&&&'%R'b%#&^&$$$$^&T%f$$V&^%%#$##$X%b$R"%$"%#$\$P'6&J'&%#%%'$$J&T%%''&R(N'^''X'^'N*'V)*'(R)*(H*'&&(&L())^(&'b&T'Z'''(&R)B*&'R&''T(P&%%'%V&L(d)((Z(V(T'Z'T)%&'T'V('T)P'Z('R'')'(&&%^&'X%T%%&%T'\'b%X'('R(R'&X(&R(R)J&&X'(\&N&%N&^&&&(^*V&X'Z&&'d%X'X$J%R#P$`#R%b%%$L$H&"R#$J&Z$F(%%Z%%&(R%(H(V&'*d&'J)Z*('(&&&%X&%&(T'((J+'N'N'`&%Z&\)%\*,f'\''&X'J&'H%J)('H%^(V'&%'&`)R(''^'Z"%b&$V%R##X"##d%$V#V"R"#!!""Z#!#V%`"#<#P%V"N#d"!^"#""B!!"J"`fX \V L ZRRPPTXRRXPTJX\TjNVTFLZZLXPLLRJTdX^P`^PL\NXPBJ\TZZX JV T PP NXP P T b h P \ P T V V R T \ P X  Z V F``RF\bVP^RDRNTZPd^^TP\X^NVZZR^VLLV\VR^NL`JRV^X`P\TRhXJfD\\\N@RV^`TTVVTBTX`^L\TN`XfX^H^`\B`RZTZL^L`PVdNXX\\Zb`TZTPNT\XLZ`VJfTFXRP\T\^ZdNRfPP^VV\Z\ZRXPXfR\RVLZhVdVRZV`RZXPNbVVZDX\\Zd^XTZRXPTXV`PT`HRVTX`\XdJJ`\hXTXT\DX^\JXRNRV^L\PN^FTRTZRdNhNjVPV^VN\LNXTNZVXRVXZPNLj\TZDVV<ZT^ZPXJP`bZ^Pb\`nRL^\X`\^V`TVZRbV`H^XVXZ`ZTZhX\X^ZLLX^TXRRVPNTVLRFVVbV`lZV^ZTTLV`XLPZJVZXX`bPN`^XXV`XXbX\XXXPP^LRTDLd\L^TNR\R\PTPTHZ\ZPPL\^VHXZVRX`XLRTVLfTJXHbR``VhZRX\VX`^DX^bZJRb\XTR^JDVPTT^PRRRJNNB`HPZT R P ^ J X L\N V L V Z R R P Z R T  L ` H R Z T X N R  b^F\PNN`VVN`TR`LLPPLbThNJLX^XVdHXZN`LR PZZ T!R `!` ` "!^$X T!"V"T$R%R$#$$N&%J'(P%T&`&'(B&b&&V'J&R%&H&'R'Z&&b)D((L(R*R)'F'N))@*V+*`,*(P+)+L,N,L/b-H,Z),V,h-^)++d+X,+N,h-+++J--X-J.,.\.X--P,V-h+Z*+V-+R)V*N(,(L+P+T+*\,L*X+\*()()V(Z('R)R()(V,*^+*V*^**b,*R+**+N))Z'D&%'&f&d&P%^!L$$T&V%"D$#"$%b$$X&#N$%V$#P$##F'P$$$J%#`%&%\$&&$T'%`&P%$R%H%^%%%&Z%%(N'%%L'(N(N('J*Z*''(T)&N()'P*T('((V'V(&^&Z&T'V'V*\'N+'b(&'`&%%V&b&P'('\((&X&(P%V''%&'%&(b('P*()(''R(T&&R&V'%#L$$%V$&L$J(N&%P%'(T'V(&&'&*Z)T&%V'%''R&P)R''^(N)^(((%R%'"$F$f%X%V%R$#$$#R)%j$R)%%&&\%)H('&R&&((V'V(T((%P('^'&&X&$&$`'\&V'&R&''R'&R(\(&'%T(R(R'Z&V&'T'%)(P(T'H%'&&X&^%P&'Z'X(^&$&$L%j&N"#\$V&H$X&$"H"H#!V#!"X"T""!"h"\"#"j"""V"!\ T!^"X \!b!B" ^!PL!N d` b!LT pZH\PZ^F\HPXLTJLVZP\PZNPVXJPVR\ZV\T`XRhd  P^\ V Z L ^ X X V V P  ` V VD`LT ZVNdFRXVRNJZZ^RH`^h:>\XNTP^dNRVLLVZdRJ\Z@VT\R`RNbXbTPHBLRXPTPd\FRVhFVdbVT\RNZVXZ\XZLbXTbfVb^`Fd`PX^ZZPXVJ\TVLPN`ZRTV^X\RVV^XN@LbdT`LVZP`\^P\P^`ZZTZ^RT\^NVTXdh\\^HfPZlVRTPjRRb\N``R`XV`TXXTLL^H\N\LZ^X`LThTJ`\FVVVXZXLZ`XRPVX`VV^TJ\N\RNRFPT^>VnX\b`HJdXPZ`\RRfX^d^^fNN`PV^J\\bbTJNJ`dX\\RPZPTLLPbPT\^dVX^VFLTRXJfRTVLV`^JRX`ZVjXZ\`Z\FZFTdXTZTXXJVRV^J`T\^Z``FbVRJdRbN^^Z\TbhRb^^NJPP^VXR^NPL\PL^LV<JZ^T\VXhZ@VTRdVPdZ\dLT^\F\LVRRR\^V\\TPXTRF^`T\TX\P\\NRLNXDRbTRX`b<ZVRL>bT^Z^RbZPN^P`JPfP\\\XVZZ`XXP\bTT Z Z ZR R X N V \ N ` V V P P X D  ZV X R \ V F X H bB\LhRRVjHFL^BTf6N^dR^\\JXTPXNfRRZLLZTP ZT\X!\ T\!dL!F!P!T# !L##B#$#%Z%'$%$d&'`)T&F'`%T')T&&&P)J(f'V'\''N'T)*&`)F(&V&''&`*)T*'(++,`/J.-+--X*R.Z+,,d, 0\,,,,+-+L-.-N.`-T/+-R,R,+V.(+*\*'&)L+N)X*L.^+)`-\*L)\*)T)''L*))''X*X)T+P)+\++^*T,\-*V)X+`*()'^''F&%%R&T%R'$$&X$Z"Z'R%R$L#$%\%$N$P&X$%H$$X%$$$$"$#%R%Z&R%T&%##N"$%R%Z%$&%"%#X&$V#$Z%R&\'(&j'J&L%&(Z&d'V(X'*(`(N)'V('D&&'`%()f)P(()'X*&R'%'L%''L)T((X($Z'&'%b%&%&L)Z'D'T''T(R*B)X(H(Z&%T%V%\%Z%&$P$#Z%%%P'P%L%R%R&%&J%R&H&&'`+(P)(R'&'N($'V))''R'L)T('T($($#P'R$#%\&H$^$V$%#T#P%&`$%'&&`((b)L')(%%Z&'V'd(&'L(%P&&P&&R&H%#&%Z%$&Z('&D&Z&T&N()'&'))&)'%f'V'&\)X&F'T&Z%'$P$'N&&%^$L##"P#f#$!L#Z$\$##!J" #! !R!!b"V"V#""b Z"L!T! Z!T!Z!PB"^" ! N^N^^PR^VDFVPf\HdFPRDdXRHLTL`^bbVN`XZ:DR@TXTf<Fd\LP ^  T X \ T b ` J X \ X L \ X ^ ^ ^ H LV R X VVRRbTVX^LTRNHfN\ZR^RT^ZN`XNJT^HbZZRTPRNZPNLZdR^TXN``PPPZTVJ^`^P\VbDHTTVTFXZ`XddP\TN`\`X`ZfLHN\PVTPVVZZ^T`T`^^TXZXL\VJNV\XXN`\^X`VJVT`^lTHT\VbRHf^L\bhX\bXdZbdNZZR\TZRhTLNJbRPjPXRZLVPFLX\XPXTZPT\TRPZTTRDfXXZ^fPP\HP^bT^Z\NVTVVbb^`@TfTPPfP^`Zh\`b`TXb\\XJ`\VZ^VXLdXZVVXTThVLR^\THXZXZd\TTN`TT\<XJRTXXdD\lP`HVRRfN^NPVRX^FZL\ZXRT\X`\T\TXLTVVJVd`ZN`TPlRPPTZPfTbNZZNf>V\VhPTNPLNdPZ\ZT\TL^dbLZVNXR<`NTXVX`J\hDXTXXVXDNV`TVRRh\XR^RbXPbRVNLNDXTZX^XV\\LRRJXFVVVd`LVXRV\VJPbP\HVfVfFPBPXPRRLPXRTVXTTLPVTHVJNN V F V< L F \ Z X N T T Z R N d d P V ^ h X ^ N T N ZXVHDLLXXN^TXRZXR\\PJ^TVZbNVNVLVFPTF^T`Z^P6 `lFX j ZVF N!P#!X#H$ $!V&$N%%$$F&`'P&L(R'&&%J&&J'&'T''\'&&'R&)'^&&V&X(&J(\)))*R+,F,b-+,,.L/R-L-,T.,X.P,^+,+*,P*T+N/-+*,H.X-N.Z,\+*`,*^*)Z(T((+X,,+*J*++d**(X&*^(J((&'H'(^'L))*X*Z-J+X)(N))*d+L*X*P+\)&T%P%$T%%R%"&#%F%$%$X%"%$%&^%'##$$F$$J#$$&'P($V%$J$$%$&^#%L%Z$'R'$%H$R#"&J$&&R%T'''&'Z&%X(&X(N(V(P(V(X'(d'N'J)''V((''V'(Z&'Z(('`(T''&\'''&'T%N'P$&&Z&%&&P'H'\&F%&X(P(+F')J&'N%$\$%R%R%%$Z$X'%''X&T&&H&'\'J'Z&('&J)T)Z'(R'B&X')R'Z((P(^*R)'('((T&$P%d$V%#$\$$V%D&`$\"#%$`'T($'X'&''X'(J'%$*&(<)&&'&X%&^'Z'V%N&#X%#R&%\##J%&`%%N&Z''&'%V%'\%L'(&$X%^'H%#'J%$Z#R%X'$V&$\%h$##T"!Z""#^"%""Z!J#P "T!!Z!Z" \#V!"!!!"" \!!X X"!T @!H bTJRZZ\TPV^NbZXVV^TTXNH`XX\J^XVTdRTF\RPTJRFNRXZZ X P P V ` l P X N T X N P R N D  V P X TVPTNbR^RPTJTFN`b\\NTXZ\HP\X^FT\HV^`\^XTP0XNPfTNTVPRTVXRRPhPlXXNTXXZ^F\PLZZ^X`ZH^RB^PjPTVPNXbRd^LTT\VLVVbXhX\^NVRP^VFjV\VXN\R\H`\4T\TVRX`XhJTV^ZTTbZLXRfTXfVRhPb\r\TLRf^VZHZVVV^ldV`P^\RPP^RTZXRbdbT^VXXbXLfXRXZZRRVXVXXbdHT6ZPdH^P\PRNN\\fZ^b\X^^\`bb^T`<TdX^\Z\fFVTL^`PX^VRTTNZRD`RZ\RHRD\P`LZ`\PZXVFVXPZX\V`FTjVX\ZV\^TT``ZV@dXVXPV\\TRV\PF`V^RNZVPN^6\PVH\\VL^J^bJ\T\VV`^NVFT\RbZFd^dLXPZZ^V8FnX\T`J^RLZfT^bF^Rf\bP^R^Tf^b`\VNNR^LZP^RFVZhNRDVT\PJ`^XRFVZJ^\ZdX\`LXTHNZTVP^VX\XJ^TfTRf\TRZ< d R  ^ `Lb h > D T b \ L V d N J V Z R Z d V XdLfPXRNZZXZNPRVZbR`\`\HVVb`PPLXNNbRX^XPX^X ^ P! X ! V# `#H$T##%%$T&%%(V'&%'&&'(H'V&P'X'P'^'Z'd'`'&(T'X)T&%Z'H)P)+)R,+`-Z/+-T//-.-0Z+**R+-,)\(**-Z-P-,V-N+*,R+T,/X-V*Z+(N+Z*V*(\*Z**d-))T+*P(('R(N'(T)X')''`'T)'X)+)*)f+*T+)(\)(X'`(R)f'N'%N$`%L$R'&`&P%$D%R(%`&##$$^%H'\'R&$###P%%T'$N&#&T%$Z%$%P%J&#$#b$N%$%\'V%&&$%P#%T%\'Z&'&(X'&R')V&%&P'&\''\(&^'L'P'(^(^(V)(('&T&P'&T'&\*'(&&H&$Z'Z&$Z%$&%'X'P(N(T&F%'T''&%&X&&L('(($P%''Z&'V'P(Z&P'Z%%X'`&&T&^'X&J&&&'&&X&L(f(&P)'&%X)T(X'X(J(%X'&&%%$&T%'B#T$Z&#N%N%R&J$##T&X$X%R%D(%(T&%R'`'X(N&%Z&'(J&X&%T'%%B%d%Z%$$"$$\&%&#\%H$N%$&(P&X%$V%%\%L&R'`%%%%%Z$%$N#P%#"%#$%R&\$T#J"T"!"V"^"\"$V" " R"!"N!X"X d" JT Rd!X N LV < N"!\ P!\NN VPXJRXbXJHZRX`LLbb\XPTZHXXFXJ<XZX^\\ZV\VL`PJP\TfVHP V V Z J ^ V T X L R N R Z V ` ^ Z X N R X^TXPTLTVPDZ^^F\LVV^ZVTJ\TdZZVZLPNZL^ZbX^^\N`ZXPRTVHT\H\^Z`NVPTVX\ZVfTZ`NXVLZT\JFVZXVbXRPbVZZVLRZRVXZ`J\dbT\b``bLTP\R^RR^ZV\RNRbV^\`PZ`ZbZXlX^V>NN^TXXV^TV^XTZTZRRPX`VfV`VZ\Rd\Lb^^VX\R\P\TV^FJ`HRJ\TbT\J\Z^VZP^P^PdRL`T`ZLRJ^hV^VR\XbTJb\X\Z\FVRPhNdV^ZXXhbNHNRV\\X^XXXdbPbN`RZVXZ\VhXTJLH^PZbTRZLXV^\TZ\PRXZVLXLHRRJ`JDjR\`RfBVTPRXZVXLLZRHTFXXXXRZT`Rd\P`TRZRZVRdjT`ZVL\T\TJdJT^PjX^PFHXXV\ZXZZPFPTZJ^VNdXZH^\TPTdNXXHRZRRRJHPTTPZV\TTDPZLTLPZ^d\TbTVRR`TVNN`RVRPjPXXV^TTLHdHF^VTPLR^\NP\ZRZV`^HbHTZVBXFNRPTPV NZ HVR FR \  T f B L X R ^ T ` L R \ \ T Z d R V N Z\`NdL`NJbNJX`LPXfb@^VHXBNNPX`\^\NVR\N^FV`RXX ZN Z b  ! Z!!!R#"P"!D$D#$X#\&T&H%^'X'R'V'P)\&\*&)'&R%X(&)(%P&'Z(%&%&)L(L)f)N++\,R,-/N.+Z-,V..,**^*))(,L**N*)\,T+*)V+^+J+P,),)P**X*\**^*)V)*)***F)*J&'&&(P(J'd)b*X&&(*')+*++)^)d'V((@*'$T$N(V'&%\&%$$%%R&\%%h'Z$#%B&X%$H%T&#Z#P$L%T%&b%$V%%^%%%$X%T$H%Z%X$%Z#X$$$^#T%&$%H$P&$L'^%N&R&Z'\(`'%V%(V(Z)'X*N)R(Z*V*T(\(Z)%'^+)P(N)V))b'N+(&&&Z'R'&'R(d($V('%($R$%&N(\)%X)R'&((D((J&(&T&%\''Z%P%X&^&T&Z'%^)N&J&%f'R&X('&d)%Z&B'$%L&N&Z&'%&&(T(Z)R'$`&(&F&P&%&%$$%%&%#\($$%$#T%$R%^&P%$T(L&$'$$%(&'''Z(&T&P%T&`&#'#$B##^$%$Z%$d$'$&$Z&&L'Z$%T&X%L%%V$Z&T&\%"&X$D$Z#"#N%$#R%#$D#H#"Z!V R#d#R# T#J"\"!b!`"X P "d L! b!f"^ X!! !"Z Z"N J!d N ^N!X RR XhTXRP\L^VRDBRT^THPTXP\\ZVPTJRJ`HPRJNb R T H V\ R R J X X H J ^ h T J @  RH ^ B\^ZLVZPX@`>ZRVD^RNLX^\`VLXZVhR^\XXV^RPZHfRZRVXT^ZTXd\8BVR\NVXRLTHRHZVRPZ^XjVTfP\Zb\^ZPVDl\RZ^^V^hZTTX\FXNZ\d\HXV\NTN\d\NPVJ\\XhNP\PT`VNZTNX\TPXP^\PLfP``dXR^VTZb\fdLZXZbZ^`VV\n`ZVT\RXRV\\dVPZ^h\ZHVNZ^NdT^VRPZ\ZZ^LP^RXPVFXRZ`ZPRfXXlV^`H^^dhXhT\`VZd\VbVjhLXVJ\ZZfPP\NPVXbZZ\VVR^XRfVTZZZVPL^PfZXTT\VV`F`^R`ZPP\XXbPbTX^`b`T`RN^TT\N\^NLb\DTXZRP\\dRJVf@hZlVVVXNRLbbB^dTRZVH\b`VR^ZVXR`PZXhVZRdNhV`bdbRRbZT\JT\^T`^LVJ\XHRTLLRRL\Z`TRTbVDRLZVLVTLRNTZZTZ^RZZJbTP`T\NhZLXXT\V^TNJP\ TPP X R`V X > ` V R T \ Z b R P Z 2 R  \\JN`dL`^HLXZZ\P`R^RTPfP`XVbb`FRHVXd\XXbT\ZPRXN^T!N !P  \! V!b""R"J$#V#%$#"\%^)P'&'T'^'V)\&&X&&'R'P''%%R&f*%`%'%`(&`(N))**Z+h+,,X-P+b,+N**V(\)N+T+F+H)'f*B)T+*-B,+^,)X*-,V,l-*)'^*J)*Z(V,N+b*,L*T*J(^''V)&X(`'&*P&%&Z()+V()&((((*)&X&%'`'(&Z%%\&R$^'F$$R$`$#$L&$N#N$$R%>&&P)T(X'`'N'(%\%6'Z'%V$%H%$H$b%#$L%&&&X%Z%`%$$$%X%%T(#R%%L%V'%N'%%$&P'T)(('\*)*X)Z*+X&j&&%X(X+L)N(\(%J'&H)R&&R'))R)P'P%\''R&$T%#%(%Z%J'd&T(&(V*&&&&T%$N(V'&J)(+&X'\(Z'&T%&%%V$&'N%'(d&%%$V&'^&f)T(R%Z)Z*(f'P'\+'V'N&&`&P&D)Z%$'h'D&%F&F&&L&$#%X$L%#%T%%%H&)$$X&%`&V'$R&%%%P&&#`"T$N"P!!!"T""`$$%#^"^"$#L$##"X#V#D%`$$$%P"b#$h#P%"b#\$F#Z&"D$R$Z&T#V##b%""\ "P""V!> N!!P Z!h"! !!b"!\!\ ^ !^ "V! !^ !N"^ ! Z b ^RTL\FZVT`L\R\JPZTLbF`RLlZBVPT\XR VH L\d ` R Z X T B ` T Z \ ` L b ^ ^ L X T V^ N ^NZb\TRVVNJjVP\`TZRNNRPRZLR`ddRLRVR\XLXbPHLRd\VVLL\VVPRTT^ZXZV`ZTJbVPTPVVlXXhJ`Pb^bN^\hXP``\`XXXR^XXNRXfNZTXN^\VXldTXV<ZN^Z^`NXhZN^NbVb^bhlNbNfjFfLbFLZRPFNbT^NRNTJZ\JZ`TZT^PL^lL\VT^VNLZN^VRVJLLZZPRV\VTbNZZ`\\RbXTT\LZTb\hTTXJ^TPZR^^XH`ZT`^P^^ThPPTf`\RXT\VVHd\>fJT`TVXRTH\D\Fb^^N`T^TNXPRLTJVPjZ`PfVR`LVZRb^VXRV^X^8l^^JX\LZJ(RPRX\dNVXZZRbNVdXLXJPPZLRX^\XVZdLR`\VXR^N^VLZVRNTdLDZ\\`bN\N`XPTZPZJDhPVNXNXP\V`TNjTT\TZJTF`LTNR@`TRJ^P^BH^NZbR\PZZPfdXZ@RLVDbV^TXRXVH\T`^^>XRPNTZLZLXZ`HT`RRNVRTP\LRV^DT^NTVNHLTN Z N T X P N f R V X R H R R \ R T R ^ TBZ^\R^PF`fVPHFX`NXVVN^RddXTPhTJZ^Z^PXVTPN\^VT\PHJ  NZ R! f T"T!V!!T$"^&R&#L$T%`&b&(Z'Z&f%(N&R)&P*b)F(f''(R&X('T)X&%&%&X'P'(N)\,`,*,V+T,h+J+X+-N+.-+b+X(P)R*H()T(+*+\,+T,\+^+T-h,N,P,N*)+R**D(^)f*)V*`*Z**T)(`'V'^*>'f)R&%%(\&Z*(P)Z&&&D''L(J'&&l$V&\%`%&$'&X&$Z'N'%\%%D%#$#$R$P#$P%Z&%J'&L'\)'%\&L'\'^&P&$\'B%#R$T$T#V$%$V(X%X%L$##$%$X$$T%$'X)&'%R%%%`%`'L''''P*(P)&(X(P)&N'^&''(V(F(F(P)X'))(F)T*)P)'('\&J&''%d'Z'%Z'b&%Z$&V'&(&P&V%('@'&&L*&\%'P&&'&P$d&$'#V'$$V&Z%%'&&b&N&%&L(&'Z)'H(H)''T'T'%&$X&#&P%#T'''$Z&\$#$D$&"T#Z#$%^%V$'"%Z''^#$#R$$'%B$V#%%"\ "H!J"##""$"T#d"P#$$Z""!$L$T&V"#D#&T%!X#"H%H#R#P#!d"X"N%$#$"%!D""R"!"J":"" "P!R!R P!!!bZF!Z!Zj Z!X H j ! hP R !X^LRJZ\`X\ZXXfJd\RBZ@VXTVRTR\XX^DJPPT^ ``V D b \ T Z P L T P b X V R d F^ \ZRZTZLLhJRZ^BVVP`THVT\JP\RVVX`^^RPbRdPNXXNfXRP`^RRJXTTPTTTRX\^NfJL^^JLRNP`ZfXZFZXXZN`XZT`H\bXPJF\XfNVDj^hPZLXNVZJH\^\VHbJTX\dNNLXbXNXZ^Xh\T``JVZbNVVZXZ\VRT^XfVVT^PZ^XP\T^PhTRV\VZZ\\\RVX^XJX^L`P`ZXXZLRPTR\`dZ^PVP^R\\HZX\\H\NRJHTVLH^ZPPRZTZ`TX`ddZT`b^\^LLdPb\dHRTLVFdX^N\X`TTddVPN`^PVRTVTbLbRPZRXZdXVT\LZ`PRZ\X^X^XZfPRZ`FTLbfF^P`\ZR\XRPRLXXRbV`RX\^^^DjD\TdTd`V\N`ZLL\V`bH^`RVT^ZL\RFbTJVRT\bJDVLJ`ZFRbJ^\\\^DDVNdZXNX^TLPdXTVTZPXb^^ZTRXVNRfXFTVZZJPVH^NZ`^T\T^LLbXVTTTXrN\PTLTJPLXZZ\TNJf\RNdfHNfB<RL `   \ F V J V f N Z Z V X H P b R Z ^ T X N \ J RTbPRXPV\FTVTNFVTjT`Z`^VPbbP^`RdX^RRVNZ^\ Z\Z ! ` !T$^%L&%N$%\#%%X$&X'&R)N'')R*`*('&R&N)V'`'`(R'&%V&V)Z'T)'T***+^)X+L+++,+N+,)*(R(N*^)'(J()X**)D,*,H-`++,\,P*h+6)X)^*P*P,Z+L+P+,)X+F*`)H)b)&'R)&N%^'X'(Z&'F'R(P&%'%Z''Z&V$Z$^%%Z%d'%T''%R%L'$'^$F#T$$$P$R&X%&$X%H)d&b'(R'V*&Z'&T&'\%T%V%$X&$^$'%&&&&'#R#Z%%X%&V%d%L&%H(&(%&(P''&P'd&H')X(Z)'V'(R&N'H'')X)(V'\+&V)V)R('b)*P)&'L)L+D*^'T%@$'\&\)F%@*&T%b''%&&$^&&(&Z'J%P$P&d&%$X(%%^%(R&%T%Z&$Z%&$''('&(%%&&V'Z&H'%X(((''(^&'`&X'N$P$P$%R'^#$&#^&#Z$"X&R###D$$T$Z#''T$%(^$$R###Z$V%$P$X$#^$`#"T !"!T$#!D""B$T#$"P#^""N$#"#N"Z$Z#J!$P$"d$\""J$!V"V! R#!"#^"!`#!^!!!T"Z#N"P#L!"! V"F @!X\J !VP\ j JLJ d H ^PT\VR\`LP`XPP\`VT\TjX`VLXPPTJPVPdFHZ^bJTRdXRNXhJbNZZ\ T \ f T R N V P T X D J d N Z P  Z `PT X F\RdJX\\^`P^b^VD\`XRXdXNLXXDh\`ZhZZZHVlRZT^RV`DPTTPbZbPXLXT`JNZLVLV\JPJfVXLPJVPDXJVZNb\bV\jPh\`TP^T`N\fRXLXTTZNTbVZ`PR\PPPLTVTV\d`RdZ`ZRnP^PXRbVXRZPZNPXTXXVXVTRTbbXXX`N^RRT^RRbHPbJT^TXNT\NXRVXBTHXRZXb`\N\FRZdF`PNT`X^LTJ`NXdZPfhRX^\`RVVTZTHZ\\Z`TV^T^PV\dXRZVV^VdJ`R^JZ`LjNVXZXPT\VnTVZVpZhXhb^RdVZJNV\\fT`^VT^DLNNVb\NPLR\VhVP^NPdJTP\PTV\LfNHJR^\JZZ\bZ\JLTPV@b`VbTNXhRPHXTNN@DXPV\T^XZNNZR^\\JD\P\RNhX\FLXT\\NVFdRNV^`L\^XPH^TZNTX\JP^VXRLPLLLRHXRVfPRfTPXbbPX^NTjLZVTbXNLdV^XVP R^NZTJZ ZPLZ J b P \ H J ^ ^ N  H ZNTVL\XfZPRJN`VZbRfT^PTRX\^`X\LFXLNVPLZP\ ZNR R X T P!R"##%$^$$J%X'L$))%&'P'))X)))R)Z'R*b(V&d&B$)H&L%\'N'((*R****V+P,-.V-+L,N+Z+H*T+P*((L())'V)*))Z+**+-***(^)X+H(*)N*V,*^)**)H)\(((L('('&N&\'^'J&F&(d%R&%^'%'R$%%$'R%Z$^%$P&\%^&%Z%$H&$#$%$P'\&&&\(L&`&'&T(&(J''%$$$%N'F&$&P%\'V&&T%$Z%%%&Z%$%'\'%R(Z(P&X&%Z&P'*%''\((X)&%(''T,Z'R)(V)(%\'''Z)(H*R(`(&)(Z(('(&'\%(b%P$'&V('^'J'J&%N%L'D&b''$&&V%^%T$%%%%$$\'%#P#%&P%#V'&\((\'L&%F&%'P%X$P%V&)H'X*`)J((4(&&B%$%#F#"Z%\#V%Z#%#V#"H$&$b"N$R#T#V%T$$%D%`%H$!"`"X$##n$\$$d#" J"L !"!Z!#N `!!\!"V$^###"#"#J""!#"T$F" P"V#L"! R T" !Z!D!J !b!"^!T!!X##V#!\!P!"T!\ L J Z XV!^ F R\LTPTX ^!@`XjDXHVbTDVfTNXJTb^TFRNXfRbLdH@RTTLbTdH Z\ ^ \ H NV \ Z T Z P V R N P N  T R T VP\VjXTXP^XPNNJPJbXX^XVNN^\dNL`PZXV\XHXVZJX\NVRX`XFVl^\fXR\NRT\VRTJJXVPR\LT\ZX`\XRV\`P^X\XTZ\NZV\LVh\\XVF\XXN\RV\ZXD\LZLVTZP`LhLf\ThHRTXH\L^V\\RbZLnhZ`LZRLZXnTTXRVXJH`dd\NZ^PdZVNT^ZX\RZZ^R\TbVXX`ZHP\RVNNXhhPNVZdT``V^RTVDdN``NRB^`HTRNbXP``^X^RNLTN``ZRVVDZLP@N`JV^\`\TVXRR`^Z^R\\^X\RfRT`XRFVT`XXVJP`PB\VHPZHXXVT\`\VXRbNJXHB`bRdZVN`TPDhRbZL\`N\XHV\RRZRTBZbTL^PfVbXNVH``VPbHZdL^\VVVVZN`N\^RRVXPffVj^TTPX\N`VXRZTXVJTXZTTHbLRHZJXdbRZ^dXRTNXR^N^T\PX\\XV^JTR`ZRLNZdPf\TVLfD\ZfPJf\>V^NRZV V ^^X J\ Z ^ Z T ^ \ X J ` T Z \ X J P N B d RZ PZPPXP\PT`>`XT^V\L`ZX``XPZHNNhV^LTbX V!PT! V!\""X#^#"R$V$$#J'N&%T'N'&&&())(((&(h&D%Z%%P&D)&'T(('(*()'^**,f*b+N*\)*`*)*V*+)`)X'Z)(P)*T.*R-V*\+V++P+**h+J)'X('(*(\**\))()Z(*R'd(N)`'&L$&d&$%T(\%@&^&d#T%h'N'L'%X&^&H$#&$&f&V&\$d(%&%#J&L%:$f%&$^&F&p%%X'X&X%$&$Z$$\%%&X&&R$b%F%`'V$N$R#j%R'%^%$Z&$$T*T'J(&'&'T'd&&(&H''T)*T(N)b((R&X)'b)&R(()&'^*Z(X&)T)`)(^(J&&V&X''(X(%N%%&F'\'\(R'd)X)J'H(P&V&@&%%T$R%T%$\%&V$V%Z&$%V'$%$#%Z'#&V'&%&%%(%%R&%'(%\&b(d)L(d)($P'(%#$%T#^%\#P$!#`#D#"P#V#^##P#d#&#$^###D$@%#""#Z#$T#$P$N&"!"V !"!N#V! "T L!!Z!L"!P!"#N V"V#R!N$T#\!T!"!!N!" d"T R" ZV !Z !L^!! \"\ !b"\ T NP `ZL fTDdb L XhNZLZJVTRRZXPT\\TbRLZVZXLXNdNTLNJXVL^HbRBLXT NF N LH TL X V L ` Z \ > X Z b V P \X Z\L^TZ\ZZbfZTNXX\LTZ@RRb^^RL`VVLfPTTTJPHbV`ZNN^NLHH\VXhXdBRd^TFZLH^PjX^VR^HFVd`ZBPNRXXZRV^X>Z\PVNF^Z\X^FXbf`Nb``PZLXd\`b^JZPXXRDbb^^\NTXPPRPLRb\TX`\VfN\NLPL\JRJbX\\b\bXbXRTXbV^``LVJZ`ZPZRh`N`ZZ\Zl\\\`^^PZZ`Z`T\VN`hPd^\XNdZRXNZbHLPNZB`T\^NR`dL@RJVhfVJPT`HVLZNT^NNPbRX\L^^BdD`NRXN\RH\V`RTZN`RNdLJfRLTVZ^RTV\XT`TVVTXTZBbZVPPNJLH`RLX\bXT^NNV^VPR`NdLBXHLZ^TPV^^^\P``TLbPXF`LPPZZB`ZXRXLX@PFVbT`X^\NPV\T\Vh\ZHZ`N\RddR\NTZL\T^XNNZZZXPX`ZZZL\ThVNNXL`TVTJJT`V\PdXV\VVJJXXFXZDVRPVVNJNdTV8P^PVD`NVN\Z D  ^ F H NRP N N J V T B ` L T T T \ P T P T T  ^LN\PR^DRVXZD^PRVZNfXZTNVRZNJXRZZLXRZPJTTdX HNV `\` R!X "!"N"P#R$&b#J&F%V&V%V&T(\'V(^(&V(''&'L'&b&'&'&%Z&`(&Z))N*X)((H)))V*++^)T+V,P*))(()Z))(J(R*V,)\)X,T(N*@)++V+V)(B*b(+P)(*()+P(N**\)(Z)'&^'R'^'\(%T($N&b$J&#\$#V'$P%%$Z&`$%N&%#R%"R&D&\%N$$%`%X&^%N%%L&\(%Z)%F%$R%X($&B%X%%&&#$J$`%%$:%T&%&(X)'V%$Z%%F&Z&(L)('(R''Z(&((''B''(V*((B'L(*T*V(R'b&N''\'N(R*)V)&X'b'&N&&'&T&J'%P''%&&X&F'&(%&'X%%%V'%R'%'H%V$&F%%J&&^&'b$T'N%$X%P%\&&%%(Z&%'d(N'%%#%d&%('(T'%\%T%Z$#T%J#%N$P$Z !"V$%F#"T$#T%R"! P#X#R#"V#N"##\ X"D"!#"$"D"@!V Z RNb# !T"\! !!V!Z#\ T"!b!!!! !P#V!P!!\ !N `\ !X NRX ^h VX PX X TT!bJlNPXLDXTRR TZZL\XNXLbF\LVRX`L\VXLV\V^fNLR`FRJbLPVLPXHTPb\`VT \Vj J b\ V Z : R P V^ N B R Z V ^ ^  `  TP\NJbZRJVPX`ZN\LZXF`XL`B^\^JTRNX\bNVXRP`TNNFXR^h@\N\^VR\`TbXZR\NfTVTTTVXH`XDXZNfT\Th\XLVZP`^J\TTL\P`NT`bLbV^VZ^PNLdX^T\ZDVXNdLRbDL`VJZL\`XRVDTTR^ZZPbT`XXdXTZXVRXdJVRXNbNbPRdTfR\LdP`TZZPb`nfNB\X^LVXPL`\HZRZ\\PLZbT\^XPT^H^\bRR`TTNbJ^fbTVTV^NTfVR`RTFLTXL^HdXj\TZbJHPLjH\XZ\^j\NJdRZZdP^ZZTbRdT ^^ZZLFPPRPhZX\fRZ\`R\\V\^`bTPXT^ZN\`^TX\T`NVVLVRXT\VVN^bXPJRVVLV\`bZV\N^^N`Z`JdNRb\RD\RXXRbTTF^HPTJRPTR\VTTTXR^L`TbTXXRL^JJHRLN^ZLFV`VPFTRHP\XRVLZ\FbR^NRV^TXHbPJPPJRTLR```PTVN\VVNVjRZ\Z`LVZVRJf^TLVXVZH\RRHPRNdfb \^VTF^ L^Z d TT \ T h R Z \ V V N V ^ L B X V R L N \ d dV R ZNRR^X`TRLNRFZV\NT`\VhPVTVZdTXDfThTT\^VPFVPXTPTR\`Z^ R X!j!Z"#$P#X$$`$%%P&%T''V'N()T)T(H*'l*J(\'\(%f'J&R'F%&T(F%L((T'N+Z*H)(*R((*+,P)L-)'(P)@)(Z*T*J*L))*+X+T*)))P)R)^+*)\)\(R))'*')')V(V))T''V)'T'&%&<&%P$$\(#$T$##`&$f#%$%d##"F#Z"%\#D$%^%V%^"#$&X%V%&F%`#V%$$$V%R&$#`%#&T$$R$N&T%L&`'$$$%V&$&'^&%&%%X('R)'H)X(''\'R)&(T%P'l'&X&&\)(X)\'L'&Z'%'X'()V)N(*&'^%T%P'Z%V&&(V((N((&&X&%%:%''T'L(%\$'X&'b&\%$$&&\''%X&$P&L%$%&$'R'%&'%V'%%&'b#J&Z&#T&&&&\)L$#X%%N%T%$F""#J"!"8%T##^"N"!T!!P !H#!\!P#\#"!P"!T%`#R X"H#  !R P !V !X" T Z! N"Z!T#T L d! V##!\ T R"!P!#R! VfTRD ^T^b\NJ  T!\N L hTVX^ZT`T^\`NTfPZTRb`dXZPR<R\VVNZN`VLNT\NHf\ZZV X J XN X V Z X P\ H Z ^ J T T X P h T P V V^Z LfP XPTVX^bdN\TRVVVHHZ@Z\TTVPJZRJX^ZT\RRV`VfZVl^`f@TRPZ\bXTP\V^JZ\^N\XXDfLTZBTVZPRb\^RXXVXXZZTbP\f`RRNTT\BT^VfPZPZ^LZTPXXTddN^^RdPfDZP\TTZXRVT\^\JN^N^XX`LXFNhRXXVZV\XZR^^RFTNVZX^Zj`dNb\ZVXZV`XNJVN\\PVZVZVJF\TJTVh`^VR`X`XZXX^XTbV\P^\XXVfLPRXDLTVn^JXVTX`XZV\RLh\^bNP`T`RNTdZZ`NdBXd\ZJPR^TNTT\jPPXDb\`VJhPX\X^FdV`L`VPXJ^bRVZTPVLPZVTZHTbHT^b`BVN^^J`TZPVNP^ZFTXbdXRTZX`NTXL^LVdT\HV^NbN^RTL^ZNNXLbV@XTTTNPPX\NXBTRfDNTR^XVZRh^bZdVDVTR\RPVTT`JJZ`Z^TB^2LX^T`h^fTHTFLP^HTJZTP`ZV`ZTZPRVVZNJJHJNNNRLXVVVNZbVTVNXVNVRV NZL` b X R \ L Z f R R Z N X \ X T \ ` N L X P lX^ZPNbRPJ\NNTNRTP^ZNFZVXFF\LVLBZLnTZ`Z:ZXfDbHV\ V \! !##"#$V#$H%'R&X%#&%&P()'F'&&Z%&Z&X&%X'$V&\)X'V(()N((^)'\)++,H+^,T)\*+*^*&(P)^'P'^()V)V)*V+*X)P,(H)''\'d)'P)R)V+*X*J+)@+,X)T*\)'N*\(V'&%&&$P%$#$^#%\$$$Z##$`"$R#"#J#"$b$##$^%^(%#N%%&b&$%B$^&\&R&$N$Z%N%N#P%%T%X$L$%N'N&X&^%F&b%%&\%%&&'N'T*(P(H*^('T*b('(&P(X)P'&(J((\''R'()'L'J'(T''(&()(r(H*%V)R'V((P'%&X)F&R)%(&'P&%f%T$`&''X(Z&j%$^'$L&J%'&%%$$H&d&F##P&&$^&L#%%#X%N#&R&d&%#%"@$\'&%N%L'Z$#%#^$"""##V$R#F$"T#N"Z##"" ! P# !! R!! N"#"H" \!T D!TP ^ XR T"T" R T" L \ R"`!!!!V!N  J H `Z Z ! L TRZDdJRV LTZ`VVP`VFPR^^\PVLZRV\LXd>Nd`f\NVL^HXXTLHTJbN\dTZZd^ \  N Z 4 b R X Z Z H R \ X P J J N P ZLJLX\ZT\PT^ZNNLVVdRRTRTT\NZRPT^XPZHN\P^ZVRDRVXV^hD`RR^ZjDVR`NbTJRfRRTVbLZ`NTNVRT^NbRZP`bP\NRR\^^`XFXT^fX\bRPfNZVR\RN\`PTL\TbbB\RVRNXVTT^R\VbPTZ\TRP`BZ^T\TZTZPVVH^`XZTRZZRbd^TLV\RTX\dZTHZZ\FTZJ\Z`PLXZRNLd\`LL^ZVJZN`PVTRLXfNFdJPTJLbR\JFLjF\XZTBTLbRZJPNRXbNTTBdZ\VZ`TXRV^dVf^JhVZPZ`L\XDPZZPd\^NLdd^X\XbXNLVfNP\^ZT^TR^TbRR`dXTVTd\J\ZZPXR\dPVVbPV^L\VZNTVTR\X\\V^Z\PXZXVVbNXZXRRd^P`N`VZT^bTVRN\\NRTP`\ZT`^XbNRZ\X`NLXXZZVXXJ`\NhPZ`VPFTbXP^TPVXhP\T`RZ`LRZNThVRdPJRdT^^\LZ^T^NZdPR`RL``R<RPdTJDPdRPPdZLPV^LTZT^Xd\`TV`RfZPfRPZ T L V N D X ^ R V H T \ T R R P ^ Z T P V P `R  VJF XVP ` fbRXXbNHTVX\XNLPZZRJZRVRZJJTDhRXPRZ@TXJ "!!V#Z$V!L#H"X#$L!##d&&%V())@)T*L(n+J'H(&&\'&P&`(&&(J'L'Z&X'`((V)*)+**\*N+T))(+((X*)(B*\(Z)&P((N+'((V&(N&L(\(d*(^))*Z)\**T*\()L))'(&(J'&%%$\)R'$$%V$^$$`&%^#V##T"Z!"%\#d%#$T#R%T&\&^&#%Z$$#R$\%$R%L%#$X$%$R&\&$$d$$%%%Z'%`'%P%%^&L&F&P&R'&%%`&X)F*'&T*&Z''H(J(`'B('(&'R(^*)+))'('Z&X'(&X((L'Z&V(b'%%R%V&%%'P(&&T()'T&'\%%&R%H&V&%T%T&^'&R&'^&b&\(`%%L%N$@##$\$%T%%%V%V#R#N$"X$#`%%R%%#"$N&Z$&#""\"%$"D"! R$#"R$%\# !L `!! !B"P#P!H  #P!R"!T!V"b P!VZ!\ !RbVV !\ F D !J"X T P!\!RVfT!f!^NXTP PRVFT^DdVRV XRR^VXb!pT!PTfNX XTRdPFX^\VNJRXXhTPbhRTPZRNT^RV^TPbXXTR\HlZhhBX\p N V Z X Z X b L T P P H h L N N T Z N V f ^ X V^ XRXVXdPNXRJRVJ\\b`PZZV\J`PZTNXVdJNZLTLHZPHPH^VDP\^L\T\`bJnFPVXZ^RPJf^PVNTT\PPHVZTRTXZ^FX`P^\TXdP`fRHZTPDRlZZVfPL`\`XH`ZRDNRP\VNXZ^T\T\NVRN^Z^P^V\b^J`PhRLRRTVTRT\TH\PZVZVV@V\^ZT^`HbL^PZ\R`VZ^^bZPXVVXRdZX\Xj`HbPRH\RZN\PV\^RXVV^FbZZZVdXPT\H`N^JJXZN`FLLVRTJX\TXVTLhZPbL^Rd`RXX^xTJN\P:LVVHfXXZZTlXTh\RZ4`RRZX^PjVP8XLFP>PP6\V\R^\RNTbT^jLfVZR^^b\lL^`X\^\FVRNFNZT\R\^bLRlH`\JTL^HT`VdZX\^BXPTDVT^PXNF`ZNPXXN`XT\b^R`PPPR\P^RDPT\\VPX\TNJNVRPX`FPDbVZ\<NVZZ`ZBZ^\PPVN\VbRdPZ`VNVL^^HVTHJ\@P^RVZRT^^TLddTP`^ZFTPPJNhL^R`F X X Z R H Z T R V L b R X P T P H R X \ R  X^  T \ TJXLZNLTnZ>VLNHd`^LRTbX\JPV^ZD^HBTVTTVR!\!V!N#Z"!$!H"P"T"$#F&Z%L%)%&J*)+(L('T'L($(&&')X&P$&L(&+'N***(*^*\(*P)N)X+V(d)()&D*R'V('((^''X+'T(Z&R(%X,((('\+)N)*))L*(\)'(P&'((T%&Z%X%L%$J(P%%$#T$N##%"%R#X"##T#$h%#Z"R$^&%#$%`$""$d"R""T#$$#%`$^$">&V"L$%%F$&^&^(%V$Z$V$#&b&%%'Z((d)(P(&('&%'X(&''&T'&X(T)H,V(R'''&((J('(^'&$R'Z&X&b&f%P&&J&`&%%'&&''P&X($%%V%$R%$R%Z%V'j'%%V&^&&%$%&Z%%D%\$P$#$#T$"P#""#b%$$%R##T$Z%X$$R$^&J$!b&Z!L!^"P"""!!L!N"R"V Z J d Z"T#!Z ZR!!JZ ^X! X!R$T `V\JRZDT !J ! ! "R! F `\b bZ`XVTL\NJTJdTJZZ`\ZNJP!R^NdZ RLDLV`VLV\RN>NTZVNVLVXJdTNbXRR\NXJVNRVPN\ZH hJ X@ R P N Z N H R R b Z R Z H ^ X N ^ R N V T  FL`VX^bXNTP^^N\Z`TZVb^R\ZPLVTbVVVhVdXJVdV\JTJNPVThVT^PRPdHXPR^LH^bV^@X\XXZNTR\ZTN^H\N`XJXNb\ZRP`RH@PNb\XVXNfLNPVNTVbb`^LXhLb^LP^V^@\TVZT`RRZ\V\VRZZ^RZVXHVJ>bJbPXHbTVJ^\JLRXP^PdTRRd\J\^BRZdXZPXZX\\\^RLdTZN^NhZZVTVVf\N`P\RfZVd`bTVTZNXLTV^dN`XRdZLVT^Zb\ZZdJTZZXVVX^^VJ`\^bJLVbbT^T`XXZX`PR\V\VbTbJNRVLdXXPTZX^PRTN^^XVXPhXJRV\ZbRP\XVL^\fTXRZ\\R\LZ^\XNZX^ZT^PdXTTV`bb\VVXLBNbRRNRXLLDLLVNZRbNVVP^VX\JhRXVPP\NR^RDN^X\RX\bFhdXdVP^XVFXJXDL^HFNTd^ZP^FL\VbBJLPFLN``V^BLNL\TJXdZLP^XRbZnRX\@XLbTXNPLZR^<VDD T\ TTRNTR > NJ @R R\ \ V Z V V T D T R X ^ V n JXVl\XT X V\ PbVN^\HlP^^VNlVLPTV^NFN\TXZVLP^ZRRdT^\\TZPR!V!#Z!""!! \!X#$$^$N%P%^%&b))\)'(')&Z)X'L&(T(&J&X&&'d&)'&()*P(f'X()&V(&&H(''P'`(T'*T(R(R()Z(R*N)'&'R'd'&P''b&*)'F*J)V)R*P'V(('''&Z''L&T%&&T%$%#$^#&"\$#$$B##R$%P%F#V#N"!"T%#"\!!J"""P!P"V"V##"#J#$%X"X"$R#L%##J$P%N%#^&$%%`&N%%Z''&b*'V)P(`''T'b&@(\&'%^&V)''&Z)Z)&N'&N&\'J'^(&%%\(&X&V'\%%J(%%\'b'J&('J'$&`%b&V%V%\&%V($V%V%#%&&%$%T%P&('^'N&Z$%$$F#R%"$^#%#h$$"$^$P$T%N#d&##@%#X$\!L%!\"!^ "X!P"!"Z#"V#H!"Z X! b H T!JZ"\" l"T RXRfTX R!P!TR!PPZ!P!D `! !N \L\VX RZP\X VP\Z^H\NPXVVTZPFVbTV`ZVN`H\RJT\PXDbhRRPPTBLZ\N^VT`R^N\\LPRN \XX V ` V N V N b h V Z \ T T J V H J J X Z HR^PXX@PFdf\LVLR`V^PVTN^>d^JVVVZT^fX^VJX`TZZPZ\XLJRLZHNZFTXTVPTPJVXVZZP`R^R`TLfNXN^`VX^TTVPbPbVNZZVVf\PNlPTPXVRRZTVLZR^^T`TVZX^TZ^^fXZR^TXL^VZ\XZfT`NJT^VX`^FZ\^R`hRVVJT`XPPbLX^\J\N`ZVLRfXRJ`X^XZ^bJXPHZ\Xd@ZTXXTP\RXTZL\PXXPLR`RJRVXNd\X\VbV^Rb\TXZbPfXpJ^PPbLPbFZVjVXP`\dL\`BFRNNVZN^\dP`\RTbRVZLXZXjXZZZRXRfVV^XFN^L\VJ`ZbHZV`X\J`XTdJR^T^d\RdDVNZZPZPR\FJJZVZTVX^JHPNZVPLZT^TVPZPFBPRVTLZ\N^\HVPX\ZPN`^PVjFTL^ZTP^\NTTZVTXP^\N`LPPT^DfXXVXZPZNNLRZVbJX\VJXLLTVJPZZ\X^LRVVJRFVRPdDPN^\fdZbTXVXTZJfT^\XVXTPNV\PbPVJNPLXBZXP JZ Xb X f Z ` N P R H X P ^ R ^ P N H T \ V  Z XV ` XRPPVFNXT`LXH^N^RRXHNHVTLV\FVHTXTTLNJVT"R! ^ Z!!!T ###V#F$&X&&^*R*)*)'V*T'((&%'((Z(('&V(\'')^(*d*(+H))d'''V(V(')N'X+V((P()&&\('(T+&&P'\(L&(P)V'F&X)P(^*`((^'(P((('&&T')&V(%Z&$Z$V$###V$#L$P!N##"#$$^&P#$T"h###"X#P"V$#!f' #H##"R#"!T#"L#Z""$"$$J$Z$%%$$$$d%%%T&(&P&P(J'd)P(\(N)\&X'T&%B)'J((D'*^(T&'X&&(R'R%%P''%P(T('%^&%J$L$(b'L&%%$$J#^"%#\#%'$R%%T%Z$$&N''%V&L%%N%$%$T%%V#F#L&Z#"#P#X$L&\$$T"$D#P"#"Z""T"#$!"!!>!J!"R H"!T!d""V"N"F`N :!NH!!\ ! PRP!NX ZZR!RZ Z!#j ! !!T!J !b RHXPh P`RVRJT N BF\N^PZRj8@fPNJZNJXd`H\LTNN\NbT^ZPTXRVTPNTNZR:RTZRTL`ZXPZRX\L` L N J J Z Z T X R T h T V P T J P \ B N N T ^ TNPXJ^`bLbX^VVTJ`dV^^ZRVXV`^^Z\JLRRTBTNZ`XZRZZL\\RTX`XLPJZ^R\PPNNNR`PBHZTTNVNTXbXZZTLfD^DRPVVNRp\XLVbdTJd\`Bd^P\`TRHLRnTZRZ\\VdPR\ZXZVVJdP^NRXbR`PZLR^`\TLTN\T^RJTVJdZVZT`LZ^`ZLjH^P\ZX\\`Vl\V`X\Z`f^ZH>ZJN`\NNVb`\P`\XZ^\ZVJdTT`Xd`NXZ^^LNVPVNV\NTPV^NTNPZLjbdXXhHX^^V^Z`ZTjZfZ^NP`X^dVRR`Rd<\N\T^bVRP`RR^JXjVbPNTTVff`RTRXVdV\PZ^>^JRdNRLNR`dXVZJTPRRT^ZTdTPH\NPPLbNX\ZZHVTbLbNb`XX\^ThPXbV\ZTD`LhTNFVLLJFV``JPXZjHnZNVTNHFlTXPTTZZPF`Z\\ZPZ^VZZNPJdJZNZHb^PX`BbNT\VZd\H\bVP``PdVRR\^TVJXTPP\LD`ZZRXRZPNTRZVZX`RXZHPhZ^LXTP LX RXRF` Tb X P ` N V Z d d J Z d P ` R X r b V N V hZ RZ T \ F \TZZVV^XPbTNZVTBTTTVNXZL^VPR^HZ^LVLZF^HZdRZXNRRR!! J N" X R ! ! !!Z#$$%%`&T'P'X&X(&)*Z'd'X(&N(d'P(L'^(T'`%%$Z'Z'^)P)F(()L*''X(()(Z(()&Z())('Z'T(&&&&\&'(Z&R(d(J(%&T((&N)'N+J(T+J(X(*T(\)L&''F&X&n&&X%`$$"Z"N%%`$##""$V#Z#^$"$^%Z"Z$`%N"f"Z"#!V!"\!R#N#b !#P!#b!N#Z$P#f$J$$$R%$%"V#T"D%#$R%L&^%T%(f'`'^+\((Z*&('\(X'*N'*''X&^'R(('N'Z'&X%T&%%'&%&V'%%Z&L#&J'Z%N'X$Z$Z&$X$V$R%X$#J"#R&%$T%h%N%X%X%($R%V$$^$V(&%^$V$Z%T$T#V#T$"!V"T$Z"%`#P#`"H !!!^ "!T!P!V!!F Z"T ! Z#b!"V N ! B \ : X!\V!" !Z L " X "H^! T!!ZL ^V\HdTX \`VTFT\XRTHRTZLZR\\XTTbZ:FJPTZXNTVHNNZPN\XTZ\R^ZHXVXZPJZ\`RRZPXZVZPT R\ R PT V ^ T \ X T Z D ^ T T X V X R \ F VXLVVLT\T^L>NZjLR<^X\TTJbVThFVVhFLRLP\TR`NbLZT\^ZDbRFJNRNbN`\VNVT\R@^\X`F^JVFRX\>XHT\XTTP`bPXddXRXRfbLXZb`\`PPZHV\LbVVdBbT`TPPN\`^\JhNTXT\H`VXTRNXVTRZLVZVXXTPf\X\X\ZZXZVTV\X\Z\XfVT\ThV^`X`L\`VdNPTVZVXV^TXdRV\VX\T\TVn`ZRXZFXVNRJRXPV\XXVVHDT^LTLJbRhXPZ`Lb\`\\\X`XdXRR\TVJ^XZX`bNV@`jRPTT\XZN\NH^PZ\RTJXLRZXd^.bZX@ZZTLNZbPZBZTZJdF`V`ZP^VRP\VVPLP`PXV`T^RZRT`RV^Rd^TX\bNLXTLZJHT\D>Rb^P\XbLL^FPdPBX``V\VjDRR\TL`XPdVJdNV^ZJ\^RTfRVVdP\XPjHLTZLbdRfTXXJRVXLVTVP\V\Rn`NDdHb\jTfTT\b\TV^L\PPH\FRXVZfNJ`TVBb^\DTFhTTNRP^F`^bTX^P\XTNPTJ\JRXP\bTRNJ `\X ZVZ R P P^ N \ P b P Z L T P J F B L R P T Z H Z f V R X  NT Z^ PVPDNPLPbZH\RZVTT`ZTlT^fPVNdbPNTRR P L X! J"d \!T \!L#J##%#$`%$T%Z'V&%((%R%%&(b'H(Z&P'%%L%Z'P('*)((H((X(*X)F)X(*((&(\&&&%N&%N''`&'V%&%%'N%&&F&R&L&('(Z*X)*T*''T'>''Z(&%%X(J%'N%f&##X&"P#J%#N"X"!`%<$f##'%"T$Z"Z""!"!#!!V#R!F!!b"P#R!B"^!"!R$T#%$\$N$^%"X#$#R$##$L$&'(T'&Z('(&`((&N(R&Z'N'R)R'(&&$&()'V&%%&T%V'%\&(V(P%(X%&%X'L'R&#%%P&$#Z$V$Z'#b"%P%$&%R($%&P&X%$\$\'%P%%R$"#$""T"!T#V"!!R!! !H!\!^ T L ^!!P LL !X !P!X !Z ! "X ^!NbT ZN!Z R \\Z!ZZZTRR VN P !X!^VVRTRRXJNHR\ZPVRfNL^X\TPfZ^NR\VX\J`bN^fVFZNV^JTJRVZTTVR\ZR\TLTJX\RTPVXDVRRZRTN^LRT\b  R b ` Z \ T Z L Z X ` X L H V T L \ \ N\\\\TXFTf\RVT`VJTVP^ZPbJV^HZN\RXVPVTTX\J\VXfTVVT\HbbZbVLV^\R\HPR`^VN\dPNHNFRJdXTZVN^ZVT\dRXTXVJXLTZFTFfXHJnTH\`TLNZPZb\@\^ZJXZR\VT`XdNDZTP^jXP\J^hbRbZT\XVJbPP^VRhVbFPPLRZ@Z^\^NZXf\VFRPVNRVTTZbR`LRZfHNNPTZXV^\bXZNR\RXRdJLVb\TX`XN`NVNb\\TbXZT`bNbXXP`R`bJJbNbLRVXPLZPFTLXPTV^XX`NTVRHT^fRZ\dZ`FVP`J`VL\HJVVVPRdTR^bRTPTVTNbN`NXPFN\NX\TVZPTTTFTTTZXfPTXVdBVXnLRddPh^ZPXb\^JfZRXp\`LTVR\`P\V^XPRFN\TXD^ZXNJTTT`THZZPTVVHVb^Z`L\ZTJbRTbXFXVVPRLRZTNpPZdB^VVXXXPVLVhTVVbPTdRLVRVZ\\PRPbdNdL^\R\LZFXHVNXVBLX PV d f P V J B V b N ` J R T V F h Z V X\P\VTN\LXFVVH^\\Vj`ZV\ZddR^PHXXNXTR\<VNPRPbd\\! "H!Z `"V$` X! !#$^$X"T$^$T$$$$%''%L%$Z%&p('V&X&Z(#T&l&P%L)''P(\(N(&T(\(X)J''(Z(X(&X&H&b''%P(&%&T'$(%R(R&`&N%''Z&'\(()%'N''V'''J(%R&R&$Z&$$V'&&J&X#X%N$%#$h#H$ ""^$#P#`$#h#!V!"^#!"\$f !#"$X#X">$!Z###$""b#$#`#$#$#%b$L%#T'%X%T'&'&%'&%^%&b)H*((&R(%(Z'&)&'h&%Z$Z$'$%V'b%T&%\'>'&%%N&$j%`$R$$"T&'V#V$"#"N&\%$%$R%&$Z#X%&\%%&X$T##$%P&F#"J"X"!\ !Z D"!Z!b! P Z!^ `\!l!!!N ZX!RH  P NXBLL\TZVPVRF N `"!R R XVRbJXVTP:^dJFTPTVLTL\\LJT\R^RT\V^P^JVV\ZTL^J^TRZ^TbN\\XDHdVTJVJdXVb`VVNJ\LXV V L T Z R T > V ` D L d P V d Z L P V JZP\\PL`VbFZLZLJXXNj@XTBfDNNNFTJZFNRhNdRJjXHXR`TV^V\`TXNP\VJ^TTXVPVBRT\ZXN\ZR`VTLFTVZNZV\`RJ^NTZV\LX\XX^XR`P\\LZJ^bNhLTNf`V^NJ`HbVXTXdVdPX^PJPJB@`\T`XLX\fR`F^`RRbZZX`XV\R^ZNZPdVZV^PVJDTV^PN`XRfZVPbXXVHP\^b^D^ZVL\TVTZRfZN\Xd`RXLXZPVVTRVLVJPRTVHZ^H^`NF\LXPRZd`Xp^V^XRr8dRVZ^RbHZ^TPTfXF\`VLVT^BNjZNP\^PbPPBRJZXZ@RLXRPZ>VZ^T^V^NXRN^\VLTVPV^^\\XXJRT`ZNTRT`PRHPRbZRVVJRX\TLLXT`RRTNd^ZTVRT`JV^JbbPXPRXB\d>TDX`LXPTRdZVTTZVVP^LfTN^dJXlHVVZTRL^LTPRPV4Pjd\\V^`JLNLVLJVVNV<L4XdTZRH\R`TV\PPJ\N^R^XbZJ\VZRHT\ZLZP\ZRLXPJJPPDZZRLJXRPT@VJdZXT\ N  X P P F R V Z T V F Z R F \\ R V  T V bLXbTdNVbXZXT\PbHJNbVDVL\ZRfF>\VZTNTXNLL`RN!NZ ##R Z"L!Z!L !N! "!J$##L#""#L$#P&&&J'%^('d&^&&^&%&&V'&J'd(b&Z(X''''R(P'%L(^&&R*&D'N&#$X%^$Z(&:'P(X(%''T&P&Z(R%'(`&''(\((&&J(&R%b%%$%&N&V%V&$R'%\'P&X#Z$T$V#V$##D$\$#`"N#"!N!`!#X"#"L"b!!#"f!V$T!Z$R!!#^#$%##T#d$#P#D&$"V#^"#N$$$X$$$P%&%%&%$X'$X&X&(V''''J'%T'N%b&%$%%&$d&J&$Z$N&H$$Z&\%J%R&$V(d'&Z$#Z"L#$P"Z#J$"""#&$N%$%&\"R%H""""@%Z%$"#d"P"Z!N$\!!!"  L!N!X! ! \!`!H !RR \ N !"X"J P L NT!Z X B!B RN` XPL dZZP VX V h!!X!Z >ZRR^FbRRT\TDb^VVVTfLPT`RJ\ZT\N`bPVZNdVRRZT`T^JXXNXVL`P`PNfXZLVTZLP b Z R N T b T H P J ` d H F P \ R X H  Z ^ V< L R `X L H X`RTVRV^NXTRRZRXRP^RLP`Z\^N\j\NjR\bRJTNXH\X^\Z\V`ZNXPH\VJ\TJTdJNbbNBRTHXRJ^TTTN`V^NX\L\XV\XNbTdXZHPPXZLZbVZ\\D^THfJZf\VRZX^`RLPP\T\dNVZT^TJZ\d`^LZbDPHdRZX\>fNPT^FZTbXLVTdHVZFZXTNZhVXXThRV`F\VTLXP`\T\NF\BLNNPNTTRPRJTV<VTZVDXHT`^PJHZ^\PRX\\LRTNPXZFPX\RbVZLhd@ZLTN^\XX\V\X^Z^^^@VRXZPNf^fVPXTXZTlffR\X\RTTZVJTRXXJN\JdX`b\LdfPZJ`NLZLRVVT\VXVVVZDRVXPX\VHZZVVbdThTX\dPJJPVNZ\N\VXT^\R^^`TZZ^FZVR\JJZPR\JhTZ\RZJRBT^Zb^DVH\dJ^X^L\`dJRR`DP`D^RLJ`VZJNRR^^^RFH^XZfJPZRZTNPNZ\^X`Rd@XT^`R^PPZRdLfZPNdHdTNXbRVLJTXP\XZF\RPVF`XZT`RP`F VRPTVXP TXF PVRV b b ZV ^ \ T d Z T V Z P H X \ \ BP Z P LFV`FdJfRXZZLJPb^`TZXRTPPTLbLT\LX<VTTJbFZ!ZN"\ V!P" ^T"J!LF N !Z!V"V"!!%Z"T$X$V$&&Z%''%$F'&)''\'F(R&%P&%&d&L'P&&'^%$&%'V&h'J'$#%d(R&#&Z%%L&$b%N$#$$$##d%P'&&&J&L&X&X%%L%%%#$V%$\%V%X%&$$#"\$""%#"V""L%#"V"#H#\"N"#"#!"!#^"L!!#"""#X"Z""%"b#N$R#f##\#"J$f#N$#P#L%"R$V$%X&'(P&V(&\)&T'&&P%&%'X$$#%$$$R%&b&N'(%\(#P%P%#N$P&X&$N$$$#R$!"T X$N$"X'$%"d"##Z%\#P"$b#R$N#!d#F%$R#"R#!T"P"X ! ` !T"!"> P!R N !PZ `BbT"^^ JZ! X !F FR R J P\ZVL\PnR  VNN d LTLXPRPVXN`fX^PX`bJXPNVXFHVJH\LPTP\NPVX^LVFDZ^RRZDVLT`TV`PHVN`T\fTPPJNLTF@^  XZ H b Z @ R X T T Z T b R T N ^ R V X V P  H V JX T Z Z T D\RLXXNV`HRTRXRdTVLN\VJN@^@`RZd`^PN^N\T\RT`XNP`RT^b\NbR\HPl`TRT^fJXX\ZNZ\PLPPX\XbXXRLNLN\NP`LTTb^VXZTdZ^dXbd`NZPVVP^`LZDbVRfLfRX^@JRl^\XT\NNXNR``\fVT\\NTTf^bHbVXVPZ`ZZPPT\PVRP^TTPTN\XLXXVR^\X\ZLT\TRP`R\L\^`Jb\T`TJf`NRPXVT\RXRf\LZF^\\XRVLX^NJXNZXR`TVRTRTJVPTX`\j^RbZZb^^L^JNJ\`JN\LZ\bXJRZPZFLN``\RFL<D`NNJR`NZTDPffLLVVhLXF`RZHRRbXP`TZd`NXNbTXZ\T\RRTVfFPdXbPPRPNVRTFX`dVNHZ`^RNN\RjXLB\XbfJZVPZb\RRRVX^XZZPVbjNTZD\Z\\DZPJ^PJLXVNTJL\FTNNTP^HXZ^NRZLXPTRLXJdLZT^PRdHb|ZHNTVZ`NXXZ^PJT\bXLVVNJRXT\HlHNRTV^V\LNVXTNTPVZ@X`X`d`RNDNbL^LVBV\LNTBL`V P^ZTdXR X N P \ H ` H V L ` P X V N X P D N V N T ^ ` ZvV@`XbLZ^DZLHP^HJPTXTZP6^@TPVLF\\P^LZZNZ R!!!\!"R!! RV P XV!^ "\"""$$$V%%X$X$#L$$#&R&%&$R%H$\&P(Z'''V'$'P$J%j%F%V&%Z$\'X#"%$R&$#\$D$%$$$b#^$"P%$&$X%@&%N&T(%#H&%P#V&#$V#P$#P%\#%$B%$"Z""b#\#T"T#P$L#"!$$P"%$P"b#"#"\$H#Z%$N!d"!"N$" "`"!H #"""$b#R%b$#f"#!`#$#V##%L'`%D&`&((J''(b'%%$V$#$$X#Z%f$#$V&#$%$\$^%b&&N$$#^#N%$$#D#"\"""!V!"P# P#$Z$""$$X#""^$L#$"$\#T#R$Z%%R$" P!`!R Z" TV"Nb V!^F!\V\\PF!L ^` T PL!\#R!P!\"d"dZZRV\F`R fP!FPTTZ\DZJNXBPPNTThV\FVV`\TPJ\T^VZ`ZbLRVN\dhXRHNVZPXP^PNPBTXZXXbPN\LHTbN ^ Z* V P X \ \ ^ ^ F Z P X V L X Z X V J X Z  \ ZV XT  R PbVZdX\XNTZXVX\JfPTT`PfRDZ>`XNd^R\Z^R`NbTVXTfXR^TTXP^RRPXXNTT^NXTLZR^dRB>XLVVVDbhTZXZNLT^`^HRZTdX\JZZXXZ^NZdVJ\XXZP`^VPPZZVN\J^V\\\TVRH\N`\^^fPhTV\`XPRZZbP^\^ZVBV^TP\V\hPTRX\VLXZ\`ZV`XRZXdZZL^RN^VPTJLTTdZjb^^TPLZXVbVVTNV^JX^JLTZVPZZHZf^\HTVXXTJbLRL^TLdZ`TX`XZb^T\RXTFbXhPZ^b^`NVP`j\`\\X\T^PbV`VP`NLTPXJbZ\ZJ^VdLRPXdZVbHV\FF\VNfZ\DXfTT\^^F^TNPJLPXLbbLN`HRfXbX^bVZPdHXZN^X`Ph:XJX\\VTXP`HLR\dP^VVV^`X^V\`PTL^V^XZTVN^ZbVTHRbPXZ\N^VLLL@ZRZTb`TPJdRRZ^R`\d\NPPb`NXVPVXXP\VXPVZLZ\VJPVXJXZ^PZXXXdHdN`JRTjT\ZP`PbZ bJZRT^lN ZT R h V V  L \ \ T V ` L R R X PN X VTJ Ph^R`Z^VJ\LV\TZVPXP^XVZRdZNP!X" \ \XX!bT `! "!!\$!T"##%T$H$^%`&d$J%R&&L#^$P$T%Z$&P%(J'\$L$$T#H$`#"#H'$T$F%b$R"$P$`&#%F##\&$%$#T&H$$&R$F$N$"$V&#P$#D&D$$^%J#N$%X%^#"$"%T"#\$"!d#h"X V#$!R$P$#^$"$#R#""!"#d""b"!h"R"Z#P"X"R!`! # \"!"R!%%$J$N$$N"###$\##P'R'%V'b%&X')P'V(b&T&$P#B$$$N#$j$P%X$Z"$#%$L%''D''j%^#$#T%$P#`$L"H#^%8#:! P!#""X$#"!"d#H#J#"#T%L%Z%"L"!$"D!\"H!^!J  J Z b BR Z"^L ^R Jd! L JJ!\ ^ R!`N RR>\RVXVV\R^PV!^V`PXJZTbVZJPRT\PX\PXVXLX\^PfXH^N\Zf^FN`\Z\TbP`ZFfR^VN\TXPX\VX^PTVBTZPTJV\\LRDNTXb hP  N Z R V P d L ^ T Z V X T ^ T NX Z Z^R\``f`HX`\XNP6TLPfVVX\XZPVNhDb\FVNXJZ`ddZZ`PT\BRbLRV\JVXTPTZRRRTXNh^^Z\PPXPbZRT``dXTT\ZTXTTV^bTT\TVXRVPR`TNRRbN`^LX`T\ZR`RTNPR`XZdXd`\H``:TRR\XVZBPZXX\V`dVX`F>JNhVNT`XLTXV`TfVN\VVTVZXnVTZ^RVTbZRbP\fZZN\N^PjTN\XbJJX`F@bX^XfRFTNTTTVLV^NRXRTRTTZHFdLPRV\X`ZRFX^\\TLZl^bXNPTlVT\^`VbVLVVN\VPTX\PRXd@BR\TPT\^XFVPTHR\^\ZV\hT6L^XJTJ`ZRHZJ\TJNHV\X^bRFRfXZfTPJ\NpVVVRN\JLRRNdNTT^ZT^`ZTZRN^P\PPbTZRVVJVPHNhbT`LXFTNXNX`XRb\FXH^TV<^HZRVT^P@`VTN\V`PTVTPHHNRZVLPX^XV\R^TVJXV`NZ^NVHfJZVPV`ZHXXdVD^VLL`V>`V^VZb\PTBVXNT\XhHZRXZTL\LTVNTX`\TbLdNHZNR`XXR\PX Z`XTXXJZ P T f P N R P ` V X ^ R V T d Z N P N\ZZRdNRVPLZTXXLPZNVXZfdLHP`VJ\X^\b\PNbDTXV^!L T dFX JN`N X R! P!!V"!X"##$V%$$%&^%$"%J$%%V$L%T&Z$&%%%$Z##%$b$^#P%"%%P"V$%%$L&%%`$$P%H#`#V#\#$^"$#h# $"#N##B%X##%^$P%Z#V"#T$d%H$V!#  P"#V"$#L#Z#""#"\#!T"f#!#"$N"@""b#""! F R$P!f!""P$d%#T$X#X$#J"V$&#%#%%%&\$&^&$P&$N%V%P$T$V%#"X"N$V#"V"$#&F$$T$F&X%%L$$$#$Z#&H%%N$T$\%D! R"d F#T#$L$##"!N!`$#"X"F$#X$"#$! J"R!RT!"TJ !P "Z"N !R ^ `NXX`\LX " V \ XZ"T!T V \TXRJFNbbFPVX^HN^ VRPFb`DVP\`X\BNV\JVHVVdRNNdV\PR^VRPVZBVPVVRXR\^XPbTbNVRX^VZXPVVRhJPFVVN \LT  RT N T ^ Z D X j J D T X D d P \ V B R d J H VN @ \ NLd\`NVN\LZ\VHRX^hPD^PRVN\BZVLTZXL^JZ\V^RVXXRHXD\ZRRRNRT`P`P`ZX^RLZJJV\^PVLbXPfJL`ZNLPbTP^\RV^H\RNHR^XT\bPXXNNN\P`T`ZT`XfdPLfJVZRRPPXb\`HR^^^LJ^PRTZbNPNVZR^LZXZbDLZV\^dDJdTF\VZdXXXLR\TFZNR^LVLX`P\VVVRL`LTR^RZNbnTZ`NlNTR^VXZZXNNhFNXT`TPR`RRT^L\NbdP`PZ^N^hfV^dTZ^jV\TP\NNPVPZXTNb\P\R\XNXZZ^PD^XbZZP\TbZT\XT^Nf VZVT^FbHNXXPpZVP^RLfRTV^ZNXdVVX\PNZJ^`TV`VVhT\d^FV^LdVFX`HN`LZbZ\`TTPXNNRVTf>b<P^JjXVPXFZX`XRVT\VNVPRN`PV\dRN\HTN\bRVb\XLTXNNTLPRR`\XNbT`P`^>\ZZXNPd^>NXFPXbZXZHV`HZZ^VNVVVJVRDN\T^`P\HLVfbNTLH X ^XT^ZjbTP h L P \ Z ^ ^ J P Z T T T b F L ` V \ PR R PNfRJZ\RfTTj`NZ\dT`XNNRFTPd^^h! R bP\ >" `"J!$"##$X%^$$$T$%V$%%J$f"V&"$%$#X$##f$"#\##H#V"P$`#N#%#$#%$#L#&Z$&%$Z$%X%$"#L## #\##"`%Z#"H#R##L$$N$N" d !\!! J! J"#$Z#!R$#X#%^"!R R#^!N V"H!b! !N!#V$"J#!"^!R$P"#J#$R%"X%P#Z%#N$$P%D%"#R$`$$%N%%$&%T$###"Z$#V"#$H"T#^#"R$T#V'%$$$#X$#H$X$T%$N##J$$$d#!"T N"Z"#N%\#!Z"X!^$!Z #L!$#"!X#J"\ " T!X  !Z !PV !Zb `LF!R` F XRX FZ H`PPPNVV\RPL^TZRLB JXVX`NLRRNZbN^VRTX\RDFL^TZVbTR\FXJ``XZTFLVfVRZR^XRTZJVN^^FHV^VZZ^bRRRHTL T T Z V d X N \ T T L @  ^ FN RZ`NT NTHL\FRTZNP^XT\\ZTPTZP^Rd^\TdLdDdRHZTbJVRXZ^FVJZ^PVT\`HTLRZPZDH\^fLPRRX^VTVR^VXNTXTZP`XV\NZ`HZV^TVlPf\ZX^TPP\^VXTP`VZL\LLZbPTTVX^L`TlRbX\VFBV\^RT\^\TXXdLVVTVXT^bT^VVdVdPf\\L\XRN^`b`H`XLZbXLj\PVR`P\HXVPLTbLRZ`VXDhPR8FXXJ\JVb\NRNVPXbVXX<bNZ^\XJPVRNZVVZbFLVPTNXb\^TF`ZRVPT\XHX\PbZPT`^@Xf`ZjNVZZV>\TNXR^X^nZP\\TRb^Rb^XPPZR`FNHRXXPPLXNbJX@J^TNPVTV,JLLR`VbNZTXTdTVJTJ\DLNVRPN`R>ZJXL:LP^TRPPX^JV@VbP^P\RVPJDNbPbfPVVbPVTZTX@LVT@XXTT^TJ\`ZP`VLB\LXXfbZbXNTRhLV`FTRRZNfPRXVPPVPZXPRZZNRRVHT`XR`TVVHPNV^Nh@`T\VTPJXP`bLZ^`ZV^V`HT^P^PLP\V`JVX`^b^P \ \ \ N ` P f P X Z X ^ N ` ` H \ @ X J ^ R TV NXN^`FRbT`V\BpXZRdHVZVZXXVb\TZH^<XFVR h!JL` TN! "N"T R !V"#!b!#T%`#%Z$#\&T$H"""P"b!"T$#$R$#P#$<#N&"V%^#F#R#L""T&#X'$#V$!!b$V#$"$`$$##R#H""H""R"!H! X!\"\#T#!"#T#V"b!P#X"P"V "Z#L" T#T"Z# N!Z# T! "H#Z!""T!" # T!F"!F!"!"P"##!"R%X$V%%%j#%^$""b%$%R##%$T$X##$"@$N$T$V"L$#\#>#V#" \$"\##%%$$\%R#$##h#T$R#$J##!"^ P$B! $Z"\$X!!\!T!"N"$H""T""!N!!!!R! X \ \R RT X V! RP N TZ XLP@HJ\ TJ !TZL^@ NVLdRXNDRRR^ZT\PTXXZF\RPbTTT\ZXRFT`JRR@LLTJPLP\HPTPPJVV^XTL^PNXRf\\bJb\L\V>V\LZVTRXFP L P T N X R T T T T N T T F b ^ X V ^ T F T T N V X  RB ^\H\RR\Tb\Td\X\VLZXT\RVRXVXP\P\P\P^^RXDP\VTNPZJRLZNLXHTTTPVPVLL`V`RZPPVXP^LRXP^ZRXLZN^bPb\ZVdZTRJd\TJ^FZPJpTT@VTb\dFdLjRZTb\VZdZ^Z\XV`\^VVVNVR`^ZLPTPZXd```bZJNTRT\ZX\^dX``VHXRVJTTRdLPXTHVd>LPRXPJXN^RZRN^`nLNRdT\F\XXVhhVVdFZHRb`JRXPR^ZPZ<PZXTD^V^Z`VDVN`\lpnRNdZ`Rf^X\NXh`^`^`\ZhNXL\VV\V\\R`R`LR^`PdVTXLPPdJPZXZ``TZVf\VXdZTRXTXdX`ZR\LRR\J`^J\ZVXXPNX^XZF\T\VVNLXZVTjThZXPP\RPl^X\JbXVT\VJP\JXN`TLXTNVPR^XJVF\XNTF\^bJP`PJZ`VFVXlT\ZXXNHZVVXN`P\DF^Vf`NLjl`TPVPZPTHPZV^VXJTRHTXdL^^PR``XPTV^dbTZNPJ`TLXZPLZN\VfX\^JHTXTP`ZVHXHbRRHN V \ N N R ^ D P Z P X ^ ^ @ L ` R Z b ^ b`Z R`RXNNH^JZZVZPTV>`^XPPVT\>VXN^JZFV N\P^!  ZTX!!"!L R"P!!!"!"`!Z" \$"\"X#`" `"#!"X""#""T#X"Z"B#V$\"!V!V"d#T#\#"P!!!" ""\#! ^#"#!!!"^# !""^"^!V!N! \!P!X N R"\!h%#f!X `!J!! T H\#b!!X"B!L ! !#V#N#!T N!R" T"! L$\""\$\#Z%$Z$N#$!#f#\%`#\$P#\#%"^#"$ `!"!X##""X"!$%V#P%X##%%V&&$##&#b#"N!""b"P!N!P"Z!#B$R"""!V#^$!\!N"!T!V T!"\"nV Z"\"R!`"$` T\Rd N h 6! HXVR^H!RbN R bT\LRhN\P\dXPPX^XVHNVXVVPXLXLX@R\JVN\PV`TnDXVdXfVFTP\NTJbN`ZJZ`\P^DZXRXN h \ P X b X P `J j X L P R T` ^VRN TZZN^T\DfZTfXXNbVLP`bX\T\Xh^XLRXLVTJ^V`FNZ\H`VBZbPNVR`^\TN\^^DLPVVVP^bJdbFFR\>NTHJX\^ZHTVJPRVXJTTPV^dRVHTTbT\HRVV`XbZdh\\RVTdHRZ\f\VPVR\^Z`jVV\RXVX\N^ZXRXXZJfT`bZZV`J`Zf^TVVTZVf^PRPhX\^`RN`ZbV^fZRF`DRTNbPRF\VN\VP\bLJRVV^ZVZZZT\RZRZZZNVXXbNXLPf\TR\ZRVTXLVRfRDfRLf\HXZV^XdNTVTVhZbFRPjRT\^jZ>XBbVTVRTXFPfjb\V^RXhJLTP`\R\XR``VVZPRTZbXdV\DJ`LJVfHT`BT^VPNfNLVPV\NNX\D\ZZL^ZVZdHXJTnZX\dTRFJLRZ\TXXdRV^LZJbXhPXZZJ\J\JLb`ThL\^^`\LXN\ZLLRPTXbTbTHXZVRN`XRTNRR\RNdXZ\LNh^X`JZZ\NRVPRN``T`VdTTNPT\ddP^ZXVbPHJP`PRNZZPTVbVRZfNVNNdhXZ\ZRPRLNVTVZ F D R \ \ F T R N X Z Z ^ X b Z Vh XL ^ \ f VbVXTVVZbT`bbTZZNXTR`XZRZPTZD\\ZhXPJVXPV P ^T XJ R!X^H! !X"P!F" !P"^#P!#"V!V!T!V !!L#H$F#X$N'^!\$#\##!^&R"P"J"P#H#!!T" #F$^#d###R#^!!J!b !! T! \ P THb V X"^!  N ! P RZ !!R F$ b Z#D N LF VZ !F"X!""$T"V#$ ###\#J#$"N$P#T"P#V%N"##`!" P"X!!!h"P""T$b%R$"P$#"%#\"n%Z#L#T$#!T%V"""!J#L"^"!`!"T"R##T$b$"#!R""V"H!#R!b"Z!J"VP!\ J^!Z!\! \T b! Xb`ZB"! R\XV NHLPJX^VPVNRVFL\RTPPTZJRLZ`TPXhP^PLN\FZNZPN^R\ZXbZ^HZRRZPX\hTJDJZTdDJhTbPZZDVV^VNRX fXDP JR J N Z ` V ^ V ^ H X X PX V ZP H ` \dF f ZTL`PPdZJNZV^^P\ZZfRDfPTbNVXVFh`RN`HLXRXN^dZTTXhX`NdX^R\Z\VT\ZZ\RNPNZVRb\TR\LT`PJTV`VVTPL^d@JVZZ`T\hHb\ZT^b^JZ`VVFVVbffNTRNVRbNVVP`TPbD^L`^ZZRbT\THZPXZ`hR^PXTHR\TfZJfbbbd^XfdXVbXT`hf^Z\TZVfPVd^\VLfN^TNZ\\LdV`N`XPTVZZXTTLXPXXNZb^`^\`N\N\ZZ\DPV^^RXXb^XNNLpd\\TjN:b^fT^T\TZJN\bP`X\ZRTP\ZRPR\XbZ\Lf\BhN\V\FTZLJ`\VXRfRVfXdXTFR^VddXJJVXHVXDL\RZ\ZZRVV\\VXP`J\Z`VPZT^XVbbX`XNXPZ`^TjfbZJXL\PTXhRXNJfZXVb^RVdLLZHNVZZLVLJPfJTTRXVRVTLZVX\\ZTPTbXTZRTVJ^PLNBPX\ZTNXXZRN`PRR\RLX\TZVPfPTX\b\RTD`RXZV`\`dJPhJVHRFjBXJFZ\XDfNZZVNRJb^ZRR|XRNZ ^ ` P Z ` f X X d L ` X N N N V V L R T & f V \ Z R \ \ \ TNf L \  V NXVZNP\bP`JFHXPRRbP\^TXV\^Z<PbP^\TTV FRT:!VDR RR  " #"#R#R"!V X ` T"J$"!"N$L#""#P"!"`#! Z"P!!^#"!"V$!#V!!"`"D!Z`T N!R J\ R!!P"N L" ^X \PV`XRRT N X X\NVV `!F!J^ P" $`#T#"##!^"!T$"%\#L%"""!"V#!! "! !X!V#!#\!P$"`$!"#"$`$V$T"#!"%R##^!!$ \ b$!X "V!!X#X##V""!J!R^" V""T!\!!` T^  L ! Z ZLZXL  ZVVNX^RHVLXbZZTPZZNVTVfZZPFXXPT^P\^>bN\\DJ`XFbjT^P^RVHBNJdXHNZRTT^NXZTLTXbHXVTRXVRNNZ\XTZ\\L \N  L P d ` N T V N L V P \ P V Z d X P ZN X HNZN\ZNXZ@NVJL\DLLT\\TX^P\F^NZZTRLLfLNV^ZXVV\RV\h`XVXXP^RdVR^PVVZXb^JdVTZRX\^^B`H\^XZHZZ\dVHRNTLZZVX^ZXRN^^XP^LVNVJPVN`TVTLZ\LZTbFbXVVbPVPZZXVHZFZ\NTZbVJP\TH\VT@ZLXXXZZbXPZVh^RVVX\NL^XX^\RR\lXV^ZTT^X`^`^fT\hdF`J\R`NTV\`R^\PPXXNRTR\R`Zh\NVZJRZZLdHLN`PT`Zbhb`ZV^ZV`X^R^X^bVVBbdd^\LBVXRPZVVTZNVZTdT\V^ZTHThHXF\LX\Z\FVJ\Z\ZRPPPdP\BTXRb`T```JVXjT\PVXXVTPZ^LhPRpZRJXVXfZR^^XRNT\FVXLTNNL\VZbV`\^TfVPZ\LXRRPRZZ^^bHL`RR^XN`^VNPDV@T`NPNL\`ZhFP\VR\ZR^HTZRX`RZ`8XRVRRNb`ZTP\JRPX^XbNZVHTTbDPVRRVVN\Nl^JPVTFTr\HPVXTRHHL\VZND^>PXJ:\LV FZHjLH\XXD^VT H d d D Z b ` N N T H T J L T L D \ Z T \ V X Z Z T Z NZ JTZbN \X^JV`JRLVX\L\NNXH\X^TZJTZRHTZZRdXNR P\" Z!!R !"X"Z!V#"D#L""!"#"X"! N!N#X!!!^ "N$\#!#T""X"""\! R!T F  L ! V\ PHX^H VZNL VXR\!f TB\V"ZZ"LTT X"F" 6"P#!P#N"#L##T#"L#\"Z"! !XZL!""""T#V#"!#"N$\"#J `#L#""T"X#!! T"X! H"!"R P R"L \!N!X#! R!T L#  V!Z" ^ :" X!!V!N!"bV!T!b!R`>HfZjVXVBLRNLFLdV^^\dTHVXRXV\VX\ZTZT`P^\T`Zb^NTX^TVXbVXTP`Jb\TRTLNVbdZXTXfPTLRNVXVTPVV V R N J Z ` P X X N ^ D T d T V V T\\XPNTXZXNddT\^VRP\^`VZ`jFfVHLX^VVPPPR>bDbbXNj\T`XTTPTZDRVRT^\JhTT`JXNRRNZ@\TXLBZX\ZXfTLRLVPZVZNZVfV\bXTXJHXZRZT\XdJRTbfjRdXL^P^ZdJNZP`JZXZ>f`^VdLN\\Nb`ZZPXRVJVbXPRdZXTZPNF^X\T\HRRT`T`^\TXh^`H\^XRbXdPZZTN^RXXPXR`Z\\FT\ZDXlNRN\dTX\^hR``\ZP`bTZ^nTRV\XrXNP\XHPNXHV^`VH^bdVVXdXT^VXV\XVF^<TRTRTHPVVTJ`NF^V\hR`ZPHhTTfX\NR^ZN\VHLB^^NPVHVX@F`RRRPN\R^ZFT^bZTdJRVbbZVVZZVX^^\JZ\X\bbh\ZPT\XTbXLLVXXX\J`TRVZXZJRRTPRZTVFXZPV\\X^^XZTNZDXX^ZLZTdPb^`NLdXfTJh\TXJVNTVJ\JRNXNNNXX^LVVRLT^bPZ``\ZRZVRZVPFT\L\VTNH^bTb\RNPbZNTVPHHRTVLVRdNPRT^JVPJRRRXT\XPTJRXFRLXVXX L  : V P b L L b b ` D T \ X T V T Z Z \ F J Z j XTRb\^VHL@^XNXT^T^dHNdZFPZV\LRVFF`dj \V! RN^!V!\!"N!b"!""#\$"P#Z!X"\#! f#^! " ` R!\!T!R#X"Z&###F""H b!L!^RH f !Z"Z X NRNZX\fTPPX\ ^bHb!V V!V `! T"!h `#!J X!!R !b"!""^ F!X!#V P#X!!\##!"L$L#!^!V#N$H#V"L##R#"b" #"H P P!"V"$N##b P!X" !" T!L!Z" "\ V \!@ ^!P!XTP NR^`@XXPPPVV\XHR^hJNH^XXPT\HVJB`TZZJNTFTZX\N`VbZHJTX`LVTRTV@fHbVX^fTT^J`FTRLF^lVJ^VTPVZ^XZX\JZ`dHVdN\ bN B X V R X N ^ b J X \ b V V L H Z T ^T P P  NVRZTPf^D\N`VTZVF`HZVX^XjbRLRJVN\XZN`P`\H`RNVHdTJVZV^VX^HZ\ZPZBb^HLVRfV\X\b^NVRTVTbVP`\LHX\TJ^TbRHXXPTTVNJ\fPVTPfTZ^TZbRXfZDhRNXRLZZVVZ\T`VTdbPTdRP`^`HHZZ`Hf\THHPP@VbXR`RpHfLRRZRZ\dFbX^N^T^^XRV^TbLD`NN\VJ\\XlZPRTF`bd`ZPX\VLPTRX^V`LX`X`bZZVXNR\RJXXZL^TLPRPFXX^`\XVTPVFX`Z`ZfX\^hT^XdZ^`T\Z`RTXZPb\\^RXZXXhZf`LVRb\\\hbPd\ZZZNdZ`^TZRTZJLXbT\NFXRTZJXZ\bJ`RLH^HbR<^NTVXZXTJfT`Lf^XV^VNFRD\T\V\bNVVHbXVZX\H\TLZHNVZZLVVLVJfNZ\`VLTTNP^NPZRbZLRPJXDfFXXZJTVbL\TPVRZDVTZ\V`RNXPTZNVTLPZRT`NF\PN`XVNT^\PJfXR^FTVRL`TXZ^NPVNTfXVXVXNZNNNZPVPXZP\@RFPPTLFVVPhTNXPJJ`LXPZHT`P^ d R L\ J ` L L X X R R L ` \ V N P H V J V ` P XP X D R ^TZR\RZPN\XPNZ^TRRN\FRRRPXVfLbP^PfZNPNN\^\RXZPF RVbX RTZR\R` H" "T! ! `"F h h!"P  ! #%"! V#Z TX VlFTP V!Xb \ P!VLX\PXLbNLTRPV J L^ ! Z!B#f!P!X!V!^!^""B! J!Z!Z! "!X#Z#!"#!R"V#"J T!\ V $V"T#! N!R!N!R"N!L#ZX"X" `R!B J" D! X X"V ! ^ NXVd^L`>P\L\PfV`LNNLZV^@NZPNR^LFZdRXXVHT\RXT@`RFL^TT\\`TfVXRRTTTXZZ\ZJ^NHRXVHTNZbPPVLXX\VTP\ZdRXTLLbTHT \ J R \ T J Z P \ ` Z N J L \ R N Zp `  X ^ ` P R\ZNVZPfVVJRPZVHV\N\T<J`L^LPF`NL`R\JVHVV``ZZVP^TJFZZXR`XZTX\\HRPRbRRLTN^PZ^JVLLNNVXX\\V\`NPXJVHVRdRLRJXXNRPRD^RLZ\PTRLVRT\VTP`^HXPP\XPN`Z^^R\NP\TTZZXVT\\VX\\ZNVVP^ZTdDdZX\RNfDXXRVVTL\^Z`dNbNNfJXR^BdZfPXZ^`JXZPhTT`^XPXV\bZ^LTVbT^XBZV`ZTRXV^\F^\TJVZP^VJTZlj\XRXPPNR^TXZD\JZVRDPVRVVVZRf`ZTRXZ^bVNN\dFRVZ^XHBJjT`dRT\\^JZXTR^\PNNNZTXP`D`XTR\XZXPRVXTV\\N\TLbTXH\VPZ^NdbPNh^BRXNZR^ZNZJXVX^JVNbZTLLTTZX\T^^TVXV\^``Zdb\\PVPdbNXTXVHXL`\TXXZLRTJXXP^^`hT`J^J4XV^PNXJLPPL\TbPXV\VTZTVT\Db`\VT^ZTZR`HNXR^VXRRNHNPPXFXNTZT\VHZJ\TbDXb\PTb^\hBNTVFVVZN`RTX^ZJHJXXZVTVDRPNV^X@^FXPbX\PLTR^ZVXTX^H V^ X D P X \ X Z V T Z N Z P N T H` J X ^ X N NVPX^PNTRdRbX`RZV^TZfXXVVX^XLVL^TV\NHTPV^L ZBXL!VZZ! ! V" Z !FT \N N L V T V"V" T"X#!"X ! R!F T"TJLhZ\N R!\P^`J@PLJdN^PZPRLTbP # L!V !^ ! !" d"Z!\#V X!V!T###b$!X" R"!X!Z! V" H""R T Z!! VL!PT J!PZJL^! V^ ZRPZP!TFXNTT J \^VNL^dXHHhZPZRXZZ<LRFNbZ^:NPPZRT^\XLVDbTTLT\RZ\R\dTTN@RTHHVV`XTLFZNTNV`F`RP`TPTbjVLRZHhXVPZZNNLX \ R N ^ \X R J T \ H ^ H Z N b D h T X R X R Z P VJ Z XRLT\ZRV`VZXFHRZ^\Z`H\hZ\NTJZZFVFNVRVZRXFZRRVRVXPPb\RTVXRTXHZNTTRPNHdR`VZXT`TVbdXXXVX\JRRTLT^b\`ZbRPdPNNPR\\`NJRVV\dZLTP\XRTfR^LV\`VP^XnLZV\ZT`XH`bTbVTnXRX``R^@ZH^^NbRXRZBVX^TRf\\^RTJJ\Z\VPR^fVbfL`^VZZTPN:XXXT`V\ZbdXbVXP\VX^L^XZP2Z\TZVVRZRZV`>XTZZfVTZTVX`VbdHFZTZTVPZZ`dVTZ^XTTFNHZT\ZTJbdTT`FV`V^@Z`ZdVZ^TNTTTLRZTP^H`J:TZRV`PVTJVPJZNPXLPbRLT\bTTXRHXfRLTfJRJbNJLXLXFRT\bJT\X\Vb`V^\LLVZfDRTbXJJZZRRJZR\NNN\HZTd6X\`^T\dTdXdTVVbRTfPVJhPRTP^Z^P\XZT`RLLR\\TN^ZlVXXHbXZZXNXX\RPT\RLXVTFTT^^^RLTd\JX^TTP^LVRdRRLTXVPHRZJbHNXLDLXH\F^RdPTBZBH^XZVXNVPbJH@`T\\\NLXVJXVXXVZZTPVVP\T\RJ\LR^^TRBPRRVRRH\RTNV JR T V Z P RP X P ^ `P ZV J R D T P V R X X  PV R R^ TV LZ XN\\P`XXHPZXVdN^LRXJRVPPXXXVNTF>PJ\XT\ `!TTVZR N!L"N!N X:Z P@ !L L!^N! T!> `!H X bR NPV\VTbZ^ZPZ\LVZZNJ`XTNTR\JL#T \ T!N!T"! !bJ !" !T!"!!b"`"!X!R$ b!N!V!F!`  Z ZZLD PL  L\!V bH"H R\ T VXRPPZbHR`ZLNNTVNZTRNZ\N\^TJLXTH`XZNVLR\bP^`dZTRTlTNDjLRNJb\LZTTTT^F\NZTPhRLR`ZJfN\BZRhTNZb\P H T H J X b ^ F H T \ H D X L TV fJ RV TDD^ XbZhTB^DR\TNBNXRVRXRXXZTN`ZPZVFVXZXZX`T\JNPdZP^VRRTHLXd\bFZXP`FTXNNVLRDVVXNXNXZVDDTNRZV`T`LXPZXPVJLLRL@ZX\PXVXP\NXDHLJVVXd\NZ^^VFRVVbL\\bLZJT\P`PfL`\R\VNPPZRXR`b0bJLPfVbHX^\\LVJX\ZV\LfRXXJZRN\T\Xd^\TbPbTL\J^\^VLXfR`\LZPNNXR`TTZR\TXXbXZNTbLRT\RbP^JHTVRTTRTVfhddRZdnZZ\XNZZ\TdTV`RVTj\NRVVVZPXRVT@TXdR\\NRNT^`RfXHXXLRVdRPRVhX`bHR`\TJX\N`PdBnN`d\NXVPTTHVb^NVfJTZNZ^LT^VXHdT\P`TXLLXR^VZbnT``XXTH`F^^^JVThRHZVT\Z\PTRJ\NXVP\\^\PTPVbPZP`V^dTjVRVXVN\PZDPX\dNXTLZNNTXXZ^XXPfP`XRTXRNZLdLFZTNJ^@bJTVZJN^TZFPVV``JfXRHX\`H@VRRPXPHJVPXVTRV^\TB`LFZPZZTTJRVL\LNPR\  T X  \ R \ R \ X P V d \ T Z V X f ^ \ ^ HbR X\ FV^hT^X\VTXbfh\T`RVH\VTNXN\\VXV\\X^TZRXBbT\ZRVTHRdXJPTP\" LR L  PH!J J! PNT XXPJTPVT`J^D RVTT6Z`HH\R`NZN`\\VP!T ZJP T ` T! P V" `!N!!J!!"!`"!" N!X" J!X bB P"VL H!P F`XT PT RL! ^ J ^VPRXfJZbLXVVPVRZTZVTNLV\RRLFNP`PVLDbDLRZdLN^PXH`XDTbLZRTXTP\XJ^PZJVPXXTTVJ`\HVVTN^PB\ZXNX^ZXR^\TNPRPJZXTNL\RhbLP f \ R P V P V \ J T ` \ N ^ J P Z ` P Z X R  dJ \ RXVTVZdLP^VTX\b`LR`XbFXd>dXJHTZT`ZXZfdd`\J\RH\XLVNHNbXBZPdVZ^RNTNJNbXXNP\PVJXRT\BTV^`TPZ`RZTXRbZXT`PZPN^Z^T`T\VZdRZf^P\\VXVZ`bNPRP^NRN\XZRTdZXbNZ`JTPTXHbFZZfpT\ZPXbFNbXPXdT\XX\NT\`b`dP\^JVR\ZXPTTZHZ`TXNRXFBPHRLZR^Lf\V\LV\JRN`^\ZTZTPRVR\PRJRXRLNZ^TT`HdbdTHXHNXR\8XFXX``P^`HfR^VhJZNNRNVR`RVPVRPLXXbZ\PRZ\VP\V`TXVLVNVLFTZPRNPTTRPRNZTNHFVHVTVRJTNXZ@bFZLRXVLdD\TZNRTRNT`^T\Z\TPP`PXLXZJTNJLLTVVFVPFVTNVV@HVHXXV`XNRVRPPXXTTRPNVFXPTD`dR^\dX^RPPZTLT\TLRZZZTTHHZZVLRRXJd^T\Hh^FT>h\PVN^T\Z<\RPBRRbNXVLHL\TZ`bLbXZZfNL`ZZNRDNPX`ZPLTT`TLLVLXPTP\VVV^`Z\PTLPVbLLNT\R@ZD^ZVR^LV`LP T ` T N R f ^ Z  L J H Z b R b V R V P L R Z R P V P T\L ` V ^J R PPP`XX^TPZ\LPTLhR`XdRV`>JRBJVHZBZZP ZV\R^VV PVV ^ \RL VDPdRNRD\XTXHZVXLTZXJTF^Z\J LXX  R!HV"X V!P"!! L"d Z R"R!T"X !\JX V VbTR\ VRV\X`NTZLT TVHJPJNTJRHZPHHNNXVXVNFFHNRPZJhRPdVXVdf\R^F\N`VbTRNTZFZNXXZXXNNVBJDRRPZL^^XT^PVPXXLRPb`TRPBTRZXPRNPZXX X\ZXJ R ` L N T Z N L Z h Z Z N J f T H R R V Z ` T`ZPXHXL\ZJXZFRJRJLRNRJVJX^VNXNTXZ\BHV`ZDXL`XTRLVL`bTZ>F^NZ\VJ\LL\TLTXRJNV\V\PXZ\Z`FXJZTJL^LP\RRTRb\H^V`P^ZDdTXXFT^N\H\H\bhXXHdTTZJNdbbL^dPXPTJXdZL`ZZZZTRJXXX\XPVPPbXhLdVZ^V>X`VPN^dVNX\\^^fZBPHNXT^\dPjP\\RJZXZTVZbXJRfDLT@PXVZNNTJ\\HVd\ZTT\NbFRVPN`\^dTZL`fXT`Rh\T^TF\TNXf`^\NRTRZh\R^X`^\V^NhNjXTXJf`XPXX\ZVJZZ`h\dLb\Zb^XVF\RXbTX^l>NB\TTXXb^Z`LnXL^TNPV`P^ZRLbTLRXR^T^LRLb\VPb`VLZNRZXVTP^\TPZ^LXffP^fbNPPHLdNdX^HTZDTRZPLRdZZXTTP\NVVTRNN6ThRNL\\RLP`dXR``RTNR^d^VP\ZFdRZTLJRLVRXPV`ZdFhRd^^VZVVVZ^JVPXRRdLVRXTRXPHZ`VBRVNX^TZPPRFRNXN^VRP\bLTD VT P Z Z`T V \R RD b  X T J ` Z V N\ N N J \ ^ F  T^J TJZR^VZ^B^TTD^`XNNTP\JbJ\Nb\VVbf`RZRZPZH^FHRT@Z\X\N\TDPTT X! ^P!T!" \VZTbNJVT\`\VZLXNP^T\R ZJZ T V V R"R\\ V L!\ N!V ! f"NJ^ b ^\\RJ\P`RPRZXXlHRZTVTVRTT\HRRbP\PXPLTTVPXPPdVL^bXXPRVDTRbLTjHRXbPVHL`T\LZRPTTTXTR\\JZHXFXVNP\RDV`Tj\Vb\LDNTX\TZ\ TLZ X V V H R ^ R J X Z P ^ \ \ V P R ^ d J T b X L ZJ V NN\XRXJZVPPLLZN\JPVLTZ\`\NJVXPX^\XRfRZfNRT\b`JbT`JR\LTV^TbZ\\XZRN`PT^XVVVV^NlVLTVNVNDX``VbZ^`XRXX\X`R^^XRXTPPTV\LhFNTVPRbZV`FZ\RRPJ\^ZTPT\RV\TP^`^TXPXbVXPRRVNV^V\`pR\PNR\TVXTZ`PHVJTPVNVNXdT^TV^VVRZZXbZ\\^^TNdP\LZbFTLNXFPT\^NbZTfN\NLZTPdTXRRVR^^X^\TPN^ZZXPRVVNLRH\BhFR^PTX^fNbRTHdZPJTVXdVHVPTXZRDhNhXFJPT^bX\TXLR`RRV\^XXT`^RPLXRf\XVVBRD\D\\RRRVbTXL`TZNJNZNLXXV^LNZPNVL`VL(`XLPXTLbDT`ZJ^DRXdXV\\R^^XRTZ\TfXVTLlJdRNVZXTXNZHlVXTPPZXVRV^X`XTX^ZVRX`\ZNNZP^JJRXTPLd\PXZRVTLPHTNP\b^P^\TNFV`XTPX\P`XNRP@HR`^VNDbV^XRPXNPT`FZbXd\VHTPJZTJf\PLDXTNRXV\P`P`XJ\XXTRRZDfPhRTTRTbVVNT\PZV DJ VL X R J P V T H Z H Z Z P Z d ^ T ^ D^ X P XZ NXJT^TTRNTHTdJXXT\TRFXDTXVdPZFXHRNZXLXTfDTHPV^PTPLT@T\VRZ RPR  ! L V\DZRTLFX `PPRTX\\^\ZLP>PZ\H`HRZ b!\ NR!` T!NfNR B RJ bFLf TJ^P\Z\RhFJRVT^bXZRTV@RT\\ZZVR`FLX\TXTNTJ\PR\TRbZ\`VF\P\NRZHL\XZZPVFLRTZT\XL\RJT\ZL^XbPPVNZ\VZRLVRT^NHZZXX<PRZbN>V^VXJNZ^`b\ZHLhZ @ Z ` V X Lb d F P V X N h p Z > R L N ` ZF H @RJJ\Xj`^fRRR:`TT`R`TRRVZbLTZTF\HLTN`N^L>PPPRTP\`RTbRPNbRN^ZT`RZV`X@^`^RJXNjHV\RRTXHTZZL`RZXXZX@PTRdXLTPPZbLTVPnLRNPfZJbXdVPBfXRXjVRXbTN^VPXTZZN^XRPN^Xd^BVd^HVTXT`JbTTbX\RXHR^\ZLX\VZ`XVP\4\XR^NX^\XJVRXdLVP^RVZVZHLX^VZXLTRdhd^dXRPVXbHVVVVNJ\VdRRTRXT\bRfFXFVZN>\\d`ZXRNV\TPNhfX^L^VX\`NTVLZZZR^^LZV\VRVRP``BhTRdRVVJ^LRhVRRPJZXPbNP^NX``Z^HTNV\ZbTNZZJV\LNJVVVXXTbPJRFRfFPV^\PRfZLXH^\ZXRL`ZRTRXbRPPTV\8XRTTXXTTNXXTN`RXdV^P`PN\b\X\VdR\FNTX`L`Xh>\LVHTR\RbNRRNN<LXVJT\`TVdBZ\\ZXXXRNXZZZ\XV`XV\ZXZX^LVTPXHPTZVP^@ZVPV`JRZXJV^XXRB`dTPN`\LV`\XXFPH^LdbTT\TdLPVV`dZXPPbRXLX PH XJPD \ V b TF` P J b D   N V T b V f N X V R \ V ` P NXPNLTNVLJ\\PF^X`lPTHTT`Z>\LVZRTJ\LHVPV\FNLbHJVVBbPN`XPJ^RTRZRRT^T^bT"!X!P! ^hDLfPZNXVP\PRPR`\TTZNHTXF\TP`R`!PD"` L \!NVXRT X P\VTNfRTbRb\LLFbNJFXVRXTdPZTPZPbRZ><^JD\TZZHRZNZ^XZfVTVLPZVVNNV\`TRbRXVVVPXNHX\bTPJTXLRJHbTX\VZ`Xd@V\V`RdNXZ^dL^PLdLVP\R XT P ^ XH ^ @ ^ Z T V T L V ` b B f d ^ T ` > RB P HX VRRTJHHLPH^XVVZ`P\LR^RbNVLlPRVT\NLZXNH`T`RDVLdRLXF^`RNXTNNT`ZTRbTTVRLZVNNNdLNLJPXZVZXV\^XPRNTVV\RHf^LXLTT`Z\TTZVVL`TVPbPNXV\RHX\ZN@TZXNhXZd^ZRT\^BX^DXVZLZVXLLdZZ`PNLV`H^ZN\XbX\VV^dXZZdP^N\ZTdVdRXRLV\JFhV^^TLN\lJXdXZNf^XJZ`\V@NFVT`^VXXZ^RZXLRZ\ZRf\NVZX^^TdZ\TXbdDZ`^PZ<dh\V`\bT^VbTTZ@RdXLPfbFZTBX`XHJNJ\^VVPT`NZVdR`XXTZ\LPTP\TJJJP^T\dH^R^\TR`HNZRPHbHXDRdVR`XPNLnX\TdBb^Xd\V\\XR^^@`XHTXhLNdJVJRNVLTP\XRZ\VPVPXZ\ZXV`Z``L`TJHV\HRVbVTRPPLhNdTNZZhH^VXZHPNLP`R`D\bTLZTNZNVVTXbXVX\NZPVJTTV`LZP`PLF\HXXXD^^JHHX\V^JbVDVVbXfLDZ^TXJNHRXZFZLRHPJVT\PNXPXNLBDZ^LLXPNHPHf`ZbXZXZJTDbd T ^ L P XZ `F V V \  ` ` P V P \ D h f ^ D T ZP`TPXBVLNRRZPV^FZPP\XTRbRPJT\Z\Jd\RLZVTHNX`NRZVTRVVPPTVNL^NFfP DT\ XTR`TdLVX\RV\T\Z`XFNNNNdXPPZPH V V JRX P` `VZXNVDRb!NDhXLNPNZDF^HXPh\PdPPRTR`NPXVbFTTVXRX^XTLJ`TNXPPV6VNLThVLTT^J`fZTR>VD^VVBTP^XX^LJTVXVPZVZbDV`X\@^Xb\LRJ^`TPNZZXNL`LRTTXTRXF Rb \ L T R X N X H ^ R N X d P L ^ \ X V L ^ Z P XTPRVVHF^V\TV\T\N^TX\FZb`JVVF`LVX\NRPXPVTVHPPfLVhLTRNTVb`N`VN\ZR^PdRXbV\XRdPRTXPR^PZPRNV`TVJTTV\\THZP`XJ^ZT^HbXP\RNPNlRhZ\TjXZHZbPZ`N\PNdN^XJTjLTDZDf@ZJ^`RHX^\V`N\ZdRVZTZ\VFLRVbX^RTHR^PVDRP^R\RZL^RjNZLbPZXR`RX^R^^DLTdDT\N^\FXbBHZPLJTLFZRdXT\NVRPZNXJXTR\LLLXF^TT`LNRd\NZ`bZRLZXJ\XV`^TZ\`X\R\RVT^RTN\\bhTNbV`\XTNP\hTZNLZbZZRP`^LZbXHTJRPT`Z\JVZdP\XNRfPRZ^\XT^D`NZ\ZNZNJTTRXTVTNPTHd\^LhXX\ZL\RZVfFPdX@VTPR\VDF^LR`XZ^`\PZTR`\RVPTVXPhPPVVXXNb^ZVXNZVZNPRV\`FXTRHZX\TbXf\`J\Z`\FdRZ^^XNVZLTPTXLZTNjfRTXPLRP``TXNPdP^Z\bLTXTHDr`PZ@^FP`ZZPNVZ`X^XNZPPLX`\TdVRF^D^LPPXT\RFTVVVLVPRP b\JD  \ L L Z  R V L Z V V b F N ` R Z \ Z V J Z L NVLZ^JXd\^DZNNJ^`TTRDRJVdbVHDVD\ZRJX`R^VXXhVHRTZhRR\^`^dJP\VZRTZLRZT^NVVFTZXTHPTZTTRXRX \\NZ^6!bFNXfPRXPNZRNVXVB`NVX^ZLRRdZVVP`L\:\VT^XFJLNLZRNPPPVTJ^PBZDbH\XXPRDL^VPL\FHLZRTTPLJXHbX`P\P^RVN\HTXZZ\RL\PdTHH\TTPZNNTTHR Z \ l J h X P V ` ^ V V R ` d \ V J V T T d T \ V Z P^ T\VRBTZZZN\^JXPVBTLRP\T\XFJRNXf\V^^VX\bTLT\R\b\\TVXXV^Z`^DbNNBTZdd\LdZXXRXXXVNV\PVX`VXPVNZVVVTbNbTVdZN\NdRZZPbLR^\\RdbXHVP^ZTHXbPVLVD`^P`lLNX`bZ`^R`R\^\@rbZTT\ZB`HXbfXNXT\\XVZjNT@PXphZP^PXLdNNX^d\RVJ\8`XPXD`RV^dR\J^RPbbP\XV\LVTZPP\nT\VbVTZbNNRfdRNRPXRR\HLbXZTPRJBX^jZ\TLNHRTTPZR`Fb\VR\PTdVfZJXNbZLbd\PVPZRb^XLLbL\PZRVbXP`Z`NN\dNNRd\T^Z^\H\V`LLZRZ^TNHTPXVRZZVXXRVdH`RRJ\H\T\R\Z\RNPB\dTTLTVVHV^VLlTJPVTLRdXbDZN^XT\RZ\LVH^RLXXTXRV^JTTRRRXVLVRZNNXT^NZTVR\XVXLPVVT^NfZNZZTdXXTdDRXZ\PbVRJ`bVRdZFNXNF\hFZJRX^\TXPX`dT`\TTNLT\NZVHXRPLLP`\T\JTPbbHLNXJR Z T R \ `P ` N ` R N X d L ^ J N X Z D N Z P T VXRR \ NPVVT\PX\\PdTXDZLZH`Pf^RPNNPVbPXPVZX\PBVLJVHNBRZTZh\\PZXR^THL^N\P^V\HL`VZ^PTPZRVXTZVP`HVR\LV^`N\NX^R\HF^LXPZbXPLPLZNXZX\X^LVb`NTJZTJ`DRFJZXBHNXR^RVJPJP^N\VLVPdbfXXHVHPL^TXTXVLZZRTVPTRNRVJNXTNZHdP`TLVbTPNNT<F TTP^VbVV Z Z N f N T L\ ` \ J ^ V Z ^ V R V X L T f J T VJ^ZPF^RJdVNRN^XFXTbZVNPTRPDdR\LRTNTJVVTNPdZLXXRX`NXTRd`^THN<PTZLZXTTLXVhNRJfL^RN`R^LTPN`FT^PF^XNVLTLNVNTNdJHRVRHTPJXT`TLT`LPNDP^H^NP``ZXRV\\Z\NNdTbRJ\NXVPVZPP^dPPRNRJ\^^X^RXV^^LJJFbD\JbTRPRPdTRXjXX^RRJXbVPVVNJVTRbLPX\TVV`bV^h^R:JZVRVVJPZRFNVP^bZXVN^PV\PTZLTZ^H^VZHZf^b`\ZN`ZRHXXdNVVbLRXTTXV`NT\d^\``XTH\^XTTThVT`XL^VRRXVRNd^N^V^XdX`^\`V\PdVNXZJ:V\T`ZRLPTLF^ThL^\XddTZ@^ZbXNRPbNh`TVXXJ\`VT\^TRXRVXV\:8\`T\`ZbT\RXZXTTTVX^ZXPfX\bJ`VP^fT^J\TX`^`\V\>NZXTNTZXPVPP``PTHTf^\JjNXRNXTXVRVHVJdZLPR^X\bTVPVTZRb^^RFH`TVXXZZZD`bRTT\TX\RNZNLNVPFXNZFRX ZZ  RR `V N L BL R ^ R X R \ ` N h H R B \ X R X N R h V d XP P XVTVNHPb^PVRTXVR\RVRRJLDPBHPLTTTPRRXP^VTT^\JPZXV^NV`XNX\bJDZLNTPfNTbX\RLH^NPDLJTJPT^DJ\ZLRXL`ZJVXZJRX`X@ZL^PL^\TR`P\VHT^LN\\NZV`\RR\T@^XRbXXHZ<\LZFZLNVPLNbPHXZPVTTV\N^>ZJdZ^XZ\\XP\FHZP`VFZXXTX\XV\NHR hP\RZ PXNLVNZ  NV V ` T Z R T X X ^ F X T V ^ P T J P j N V ^ R ^ XNN RTjXbPZd`\VRJZPVZ\TZ`RRXVNXHfR^FXLB`R>`<\VZZPTJ\ZXR\RHLbXP^V`RR\`XVN\RhPXFXZHVZ\VZNNZF^XNNNTNbXP`^NXZN^^bTPdRRbL\LPRLdPR`JXVbdJDVTVR^\ZTVV^TTTbHPb<XbP`^RVVLVTNdVdVPJDRTbdL^ZVVNLXP^8hXR\V\^HTRPVXVTVXZLPVZTNV^TRVX`NVdXHdXZ^ZHbLTLRjd^`Z\`\\\ZXNRTPXNh`bLRXPPf^ZX`\LXbLbNN\RHLHT>^^XT^d\TN\P`TZhbZZLRXRJZPPBHh^BN^TTLLXBNNVVTTR`THTVTHTZPPL`^bZZTZTZNR\XZ^PZ^\JbTZZLRHRR^J^NTPRXhZFJTdLLdHVdXXXT\RN\PTXLTTTVLP`T\XLV^dZN\LH\HNTThXTPXT\L`RZZJTVL\PZbPbH^^NNJXPTVL@`PVFVN\HHTNRRNDTPZV\V^XVXNLJTR`VZPRdNXFNfLXTVNZTRRRX`ZZPXRZXX`HRN^V`N^ZRNbTRXJ^ZbRVR\PDBXbLTRNJ^\T8L^TTXZ`VZPTZZR\VXN^RNXB^HdRVdRHXRV^\LTR TZJ Z^ Vb^ T J ^ b` H R R f ^ ` > L P F X ` X  `\ L DVJNXPF\Z``\F$TRPB\PhTJRXPL`\RTdVP`VdRTFTZ^L^\RRRbNR\VbZTJPXTXZjNb^XXZRZZXV`LRRLXJbVbV\LZ:b\Z\VVXVJVT\PRTJXZLJZ8NZPZPVRRT^JLT^\NFXTTNTXJTHTj`HXLN\PTLHTZTZLT^PdV\bZR^LTJPZVX\RRVZHJRL\Z\\X ZRTFXZ X  \^PX^ \T T VLF T P T T L h R N T V V P Z d D N L ^ X Z H Z T X ` dDXPJRP PbVVJPHTZ<JLJRPNTRTJLT\RRVRXTVV\H^HF`PHNVFRRRZ^JZRZ\VL`PX@XXTNP^LZX\ZPPVZDRbRNVZFJPDPPN\FRPVRZX\HL^TNTVV\VNXRTVPJV^XR\J\HRVRTPZL`NT<VZJRTbXhTJ^fZVX`XNf^D\XbZF^`NNTVTXLVTbN`JXFP^P`TX`ZNbXPPXZNRXH^\\\b`X\X\T^VPNN\VHVFZL\bPN^LXbNVTTTPRLTVFNXRZFZV`b^PXZHRXZ^^PXVNVNNbRZP\L`R^\b^PdX`TD\`NXXN^P`PLLdVR\TbLVfPZT\hPTJ`bPhfXH`^`VXDbDR\XDXRVZV^NLZNLTbZXdRTV`R`^`PVRZBbHX\bZP\^bPbbZT^ZbZfHZPRTXZ^R^TTZVVDVPTXdXRR\TZTRLf`ZbbNN^LbRTZ\N\F`RRNTV`RZXXPHNFL^ZX^HHVJ`FJXNPRbHZ^R^V^TVRbTP\NhJXfZXVXPTb`RbXJPPXR^XL\VHV^``^VZNFTHHRLTL@\XPRbNVPNPVNRLPTRVVXJVXLNV\VXTPLTJXVR\RfN\LdVX\ \Td Bb V\T N \ T \ ^ Z b P Z X N X JZ TZ X Z P \ N P ZV b ^NZBZVfN^^dJ\PRVJTXXV^^DZ^VXXTBLPXXbLTPZNbDZ\PdTNFJ\DZX`J`RFRZRbB\XV\TfPFXXZNP`NPPTVNJVVTJ^VV\XRVXVbHNL^NXPVP>TPXVXd>HPVRH\RTdJ^HRLXbVPH^VPLVDX@ZPNd`LZXRVNVPTVVRVXVRHRRNZP`NbdRVZP^DhPbZPTVX\\RX^^NHJRXVVRNNN\`R ZDVL NJ ZV ZH` R X B \  N  V R X Z R T J \ R f ` X R X f T V L L R N \ H X NN ZLX@ ZV^VVNJbR`PRRLL^`RZVPPRZ^PRPRPfXT`L^JN\XX`ZTPPFPPT>VbTXXZ^LNHLbjZT\\JT\<^HVFZ\ZdF^VXV\T`Z\bVRRLRPdXZPZV\LTDPXL\ZVV^RbPTV^NRPHVLT`X\Z^`VlPdJZTdjT\ZLh`NTVV\PZfZVX`\\\^VP^F`Z`V\V`dVXXdfZ\`\FRdXdXZfXX^jZbVVLZ^`dPZ^fNVZLPNZRZLV`\X`P`RVV`b\TX^^RZHXNL\VX\\$bXXbbTVXTLZVNb@RVXPLPRRVb`NTVPTXNN\ZTTH\TRVBZNFVRRVTPXZVbTJLfTZTRBTPRXRTXVDPLFVX\\DbDbP^RTP^VFV\V^XLNbDN`PXXLPXHXXH^VZ^^LPNfHT\LPXT>TRF\LR`RD^ZPXDJVT\FXbLTPZR^LZ^^RZPRTT\VHjXFVRRh\XXZfPbL\LXV\V`VRP\TVRXP\RDZ@`HV`RVJ@ZNXXbTbN\DVVTZLRRTTVN`XVXX\X`TF^T^NNVdXRRDXXXTNLJVRVPJRVNPbJN`XZVZL``VD`R`bHNb\>PZXXPXNT`JH<RbLXX\V X V ^ N J V L V F Z T J L b V J Z V R  \TRPTDT\RLRHbVXZ\TRVPZX\XN\N\XHVLRNH\R`PZV\L^NXTTTX^PXTZVXNJVZNPVFL^PZPJTLHVP^LNZLN\RNZd`R`VNTVVbJRV`HVRTLTR\NRTVf\JVJLRP^NRP\RZPNZXV`LTPLRRTLZVJVFTXNXP^BNd`XTXfRPJXBXbRTPLRJNbVZTLTZR`HJVV ZDZbF\ X\F B  ^Z \ b P N L ^ T R h B V P V P T T R H b X ^ ^ D N D \ \VHNBZZBN\RNRRTX^V\LVNJJDZTd@XdN^PRTTHjZP`X\RT^ZVVPFV\ZXXFN^X>NZZLZP\XT`XV^TZRTJPVZTX^\PbfVV`LXPP\TTRPNXV\`TP^NXVPVV`VT^P`TFZ\TPTVP^TbVdXdffbT^XTXTVZTDN`VVJ\XTPVb^P`VlZPd`hL^j`fP\XVRZbVN^`TZdjP^d`ZfXZ^XN^X\XNJfZddX\RZbX\L`ZZTNRLZNRLPj^X\bLTR^`\`NJpT^nPHVNLNbNPLZNZbXVf\fZRdb^^X\^^VV\\^X^N^VdRX`ZbPTXVT^P`jTRNLNTTTXPbPTXXXLT`X`\\JRZVNhPRL^TNZX^:bLbZ\B\\F`T\LVV^VRPZXLNVHZZHZbLN\\^\ZBRVTTVTZZH\XHbZZLRTX\THRNRNDXZTBVH\RXXVZNRTHZRJNTPR@FbFR^\DVRXXFTLZR\`P\\N`V^VRL`\JXXTb`RRbZRXHZXRVZP^R\\ZVRXZLX^VPLZVHRJZX^PPNhN^HTd\TFPVVh\^NXjX`ZP^NV`PZX\ZP^NJfTVPL\\dJTPPNTdZRNNR X`ZZ\^ ^ P  H  P Z T R J T X N X X\^\\PNZTFTbXNRT\ZRRVTZfTT\bHLZHNRbNZV^RVb\\b`HRNJLXZPbXRVLLZVZNTVV@`ZRJT\N@RdVZP`TTVnZTV\NdLPJZdL^\HZ`hVD\XXPJZJ^N^fRZL^X`\`B`PVN\HDFVRT`J<bNTLT`PbND^`^TLZXT`VT^LVF>NXTP^XNVbXLR XVP XTJ  X Z \ Z P V R RT ^ V V ` N T ^V  L \ ` Z V R \ T L Z V L ` \ Z Z N H T TR P\^V`\^LV^RV`VTZ^NV^``HVRT^`N`LTH\^LFVRRTNZTVRPThVPRLXfPJN\^TRR\PVTVJT\N^LhVZXPRXXTNVZJZRVRXNVX^TFZXZRZP`BPLDZHX^<XLTDZZT\RZDHFHXL\PTJPP\NbZF\HdTVXXX`TJTVRfRBPFLR\TnNVVXXbT`LTZ^bfRLZRRPRPVXZ^VRjTJD\VNXR`TVT^RLfXVJRV\dF^RbP\PTTRVRLdN^RT^\`VVb\ZXb^`TPPV\PHNTHRLLJLLZZTRDP\LL`TZ^Hd^FP`D`fXZdXVJNX^^<V`X^XXNVJZPNhVZLRVPLnX\\b\NVZVJHDXVZLLVV`RNVPVFZ`R`HTHZ^DZRZVZ`JV`LR\RDN\T\P^PVZ\ZVXfJVbbX^`jJbVXHjPX^NZZP\NJbRZTNF^VTZZP`bT\RFVVTXT`XJNNddPPd\RTZfVdXXZ`bNXRXbTPZLlVPbJPLVVXZ\ZRbPRJZVH>Z^VXR^RRZPZ`TNJBL\RJ^XH^LZ\`JLf8VbNXXZ`JPPVXP^LD^NPHbV`PXZ@HbVJLRVTbJZTP`XLXVLZ\L^NJ^\ZVJVTN\XTbBJNZTPJ^`ZV ZR d ^ H X f N ^ L Z \ f Z Z V P ` H T N V P h R\HNhTNT\N^VX`VRVLPNLZ\LNVTVTZZRRT\TLT^HTHVPbVVbRbFRR\HRP>`ZVbJBNXV@ZVNRV\TPPVPDTRbXdbVRJjZLbXF`T^8LH^RXPRNRVNTX^VPPTL\RNP\ZLVNRJ`VVT`RZL\N:PX\RP`fJX\PNbHT^^TP\N\d``Z^P<bbNR R N LdX N ^ P  X \ V X\ R H b NZ ` L T b ^ N \ X P T R V N T X L P T P J ` L Z X R ^ \ N X RX `VVPP\LPLTVPPDFd\PRXdbXHFhNHPXLVLTZ\PPDZZ`NPTTb\bP^RVPN`ZXjLbXNLNPVRXNZZLVZZTXXXRLTTVHNRXRDNPNRXZdVHbTX\RFZXRRFPXDZPP^HTRXV\LZ\RR^FV\TTZBV^TXRXbTXTZRVTTXP^T\XTVNbVT`L\ZJZ^LXH\Z^ZXZ\XTT`\T\djT`^XNX^RXVl\RPHJfR\RXN\H^Vb^NNRThPR^NRPPLPVVZ\V^VZLZPN\^ZVR^^ZVVPV\VTF^RLZRVL^ZTTTB^TfTX\TJdV\\\VbZV\bVRTTL`RRhR``X`\bTFTZF^N`b\T\ZJVTT`ZVV^RbFZddZlTLZHVXRR\XJ^\VLTV`dXRDdZTLTZT^^PV\TZRPb^H`jLb^^bRJ\R\ZVTPPRhdRH<\XN\DT\JR^LLJdNRVXZbPZ\LXH\^RN\VP`RZPHRNZDZRBPPNXTJTTZ^XRbHZbVPVNNDZ\dR`TZVZ`TjL`RHXTF^^TZhTXN`VRRbX^BVRZV<NHRRLFXJNHVRH^L\fPVZTRB`TVPNX^V\VXJVTXTRZ\TVdPVbRP`JXXVPRPLRZRR^LZHR RJT^D XTH nX ^ ` d d \ N d V P > T ` P \ \ Z B Z P R NXXN^JLPPH\XJPPZJlB\`bXNVVbX\ZHZZRV\bVXbXF`L^XXPT^T\^NZN<^NPTFXNXNbXXRVN\TdRRFVN\PNXRP^`PBTXTP^FZXX^HZJJNJLX\XH`XZVZT\^LT\XVXHLZVNVTNZVXXRVL`RHFXRZXXBLVRT``RRbNVTPF`RRTTZTJfVXP\\VLRTRX^f  V ZZR V P T P R b L R ^ P R b l Z V N N b R Z J V \ H h P V J V b X P N @ L V Z ` P `  ^HP RfZTLTXRDTDT`VPFLVTZNVTP`TVJTRNVRZbXZXZZVHTLVNPTVPh\ZZR`LLXBX^RFR^TH`PbdNHXXZN^P^VLZZTRPVHLfRZPVRPTVFbJZTTXNRT\TBXNNTJ`ZdHRRbhPRZR\ZJVPRN`XRF^>DXJRRPVTHV^VP\R\T^TPLXJ^LR`TZHJZDPdTVHTRTNXZHRPhP^VP`b\PVTT`ZLZRL>LZ\XhhRPXDd`XP\JfXJXL`XPXfL^`LT^^FVT\P^^TTdXhTbJTPZXVRHbPZTbTP\\PbX^ZhTdDZVTPVHR\Xj^Th`V\XTXbTHRTbT\RbNV>R"^\RbXTfF\J^VVZRZP\\Ff\VNL\ZPRX^XF^LbbNZZ\TZ@\df\RZ\^JZjHdVXRX^P\NX`PNZTdLBRPVJN\TZZVbFdZJ\VTjPdPhZT^`P^jLNVTRNZTJR^HR^V\VXTZ`^ZRTXP`ZNNRRZLR\XVZTRV``\`J^RT`dHZLXbXJXXHR^^V\hR`ZRFDR\XPPXDHJ^PL^PRRfP`H`Z\TPfRXhPRLN^RXX\^TVB\HXRPFRV`\8\ZF\VRPN^\R^ZJNT`@VR  HbTP Z N L ` X V R H ` R D X V J V X b R XVJ VTLXVbR^^d^LJV\NVNT\Vb`XZNVTPNX\\TR\\RNPVVJR`F\RRFXFJVhXNR`NZRV^L\^JZRb\XPlR\@V\JPTdNTTTP\\TZRXRLZXRZRZXhFNPLhVVDb^^NbLPThNbTRVPV\XBPNbVXZHRJVNHjBNHTRTR^PHJ^^FVJXJXXZBbPdFRVT\b^TFPfH@THXN`\  Z \ VP `  ^ ^ F  \ Z ` Z T X F ^ T L R P N ^ B B P N R T H N X V V Z T P P X N X \ R T  X\ N N R XRXHRPP\NXVNB^^^V^^RVd\XVLTfTPT\PX\RT`ZTVVZPXZB^VRT<\^XVXTdJR`VZJRXXbNL^LZ^PRTJT`ZVVX`^PXX^dNN`T\bJLX^^B`\XPbT`XHNXX`RRVRdLZBT@XhV^FTVPH\PXThV`fTNV`\VX>bTPV`N\ZZPVbPDTXZTNZFH\bVLNDJ`TXL\R`V`bTXXR^VZjX`bZPTX^LVTF`PZbPH@^Z\RTVLVTFVTTN`TPX^\d\`TRbNHNT`TNb`NZVd>J`PLJTVBZTRR@^TN`XRPLVTR`NX^VXZVJPTRZZZbVTRZT\JR\T^T`RXPLXR`X^dZVRT^\XTVThZZHTPP`PfRPNXbPdZXFXTXJ\LbV\RDZ\DPVdXRPLTRJVbRTfHF^\JNXH^RD:XNT\XLTLZHVX\ZT`PF`PL`PPJR`NX`TLPZ^NdT`bRVPVVPX^`ZXJTbJXLPbPNTPXTTbVTfTfRPF^JRRRdLJVTdPbTZNVZRVXfTRTXXHNV\RTJX^T^ZV@V^T`fRXVVRPfLP^PT\NN^<R`R\FdTNV\Zd^PJTLV``JFZ\TP^VRX`JDZTPTB\bfPZL X `f Nl ^ T d V N J d X J N V D R R \ P P V L`bXTR`^PFLXZbF\HZVF^RDZNb:ZV@NZPTNbTJXPXXhRT^jTTJ@bXXV^P\XTJZTP\ZTZRVN\HZf\T\R\ZfVTRNHPVdRVR^V\ZVbPbNdRTDLXbRTR\VVNZL\Z`ZFV^LTNNdXHPP`PTL\BbVBL\N`NLdRVZNTRTHVHVTTfHRTN`J PH`\  XRN N b B ` N ^ \ N^ T H \ \ N \ J ^ d X \ l N ^ P Z P X ^ \ L ` L ` N T Z Z ^ V R V  J  JXTRVNT^ TLZVXLPVRTDL`PZPVTN`bL>R\VXJNRRV^XRV`NPFPJNRDDbT^XRZZRNZbd``NXRR\\^XHLRVPRRFXNZ`NVVXTZTRLPZP\NNTR\R\VZ^NLPN``\TPT\RXFXXLT`T^^JX`RdT\b\X\Xb\^\P@d\hTJZT^ZVJJVTXZJXVfNP\P^V^VTV`N`Jd\\XZZNbJ^^TXFPTZRH^PX\V^fVJRR^TR\TZZbT\ZVHbHddV`fNR\dNZJPV\XLTXVVTTdTRZZZ\^hJbP`TZVP`TVT@\PVl`\T^NXVV`ZF\``P`RZR\\FTNZ\JT`ZTR\ZVZVRTFb`bd`ZR\PTVVX\TPXPl^PFVXJVV\RPRXTZbfZRLZT`RFPZV\dVV`TTXPZLXbXXNbNZTb\R^\NZTZZPZHPPfTJ\LhRbNTXPVNXRJ\LZJ>TXXXVVVZV@hTL^HX\TFZRZHZH\XNZFTNJFRRJzZVNT`PVXXRV`VV^TbVTVPLXDPLRZPTVL\Z@\T>NX\V^@bL\RhLRbJTf\Z`HdFVfFT^`NZ^HNVRHL^P`TXP`X^^NNJZ\RV\T`V\RDRRJdTHdX`HdNXL^XVZTZJBTXh\X  bV\ ^ N b T R P L ` L P V \ V V H X \ bVXXZXRbJN\VTTN\`LHR^TfVXL`PLXZLX`PRdTRTHLVL^ZTTdJRZVNPbPNRJRTZPZVLTTZJdXLVVRV^X\LZVRLBPTVFRF^VRdVV\X@\RbPXJFRZNXbPPV^PZNNTLZRPRJXNXTXRXZZRTLdFXNZNNPVVHRXDXTNVbPLTRTPP P F L R X R \ \ N R X H Z N R J ZT V P X X Z j R \ J Z J X J L ^ \ P  Z F   J T b T >HNXRZZV`P\h\@XPXDdXRLdNdTZV\TR\VRH^HjdRPLTR`^`TJ`dDPHTPdNT\TZHZdHT\RXT^FTL^RX\PJj^N^BRTP`VJZX`XRZTXVVTRXPN\XTVPLT@LZRLXTJZ\TLZXNTN^RZFPRTLPRVRZRfRPZTLLVVRVXPXR^PjTLNX^TXbXXRTZXZTVXZPZLHVXHXVZTXL^bZXTJfZT^b``^ZdT^XXRT^LV`NZZT\RZhRPV`^TRRRT^HFNNP`V`TbJBV\TT$PVLVbRXN\TT\XZb^TpP`bF^TT\VRZ``NPV`ZXVNZZR`XZXbT^^RX^XNRhZfXVb^J\\^TRTRVX`V`NbZN\R\X\XL@XNN\V`ZPVHLT\NT\HVXbJXXR^TL^^dTZZVV\X\\ZVd`ZTZX^NZ\XJRTbNZXTLXVPTTZTTPRb\RHPZXdVZ^^FJVXX^PXT\b`^\`RZXT\TZPT`X\ZZN\NPbdXZ\VPRT\ZHPXZVTTVz`VLR^X^`PRXHFVRVhN^PJTN`XPDNTPdV^LLRRNh\Z^^JNFTRbZHBRPT`JVXPN\NT`P^RHN>d\XFXZdV`^^`RdPVZ`TPT^HXRnTF Z P \ N T  N ` V T V \ P T X H Z ^ X \ J X \ PZVNVRP`RdPZbVNX`\V^HVT\XZTPRVXR>\X^BVJZFTJ\T\ZPZR\ZXN\@RZ>RPZXPVZVJVNPPDZ`RF\`TVbXR^\ZX\^^TZLX>ZPPNRXLTbTVXPPVRZXVJXRX\XBbXJ`TV^R`ZVXBTV`VLdHVXNbXLLLRVL\P^PXRHLf`LXVJNJHT\h P \ V^ VRN N X D X J `\ X T X b L T P T V T Z J L ^ Z V R Z R X P b P T P V V R f V X L X  X P TLVL `P ZNPjPNRVVV\JRFT`PZhRHHTXRNNRD^VNRRNXP^^TRZNNT^NTTRNVXF\RHRTdLjfRRNZJXZN`Z\FTPV`TR\PTVN^RZ\PVT^Lh`\XPRNb^TLlL`XXNNR\PR^RZZRNRR\ZVZNVV\F\B^ZVNXRZ^Ldb>VjVRZTF`ZdB`XHdTHZX\ZRLZHVXNdPNR`JHXZXRdXT^^\ZRPNNHVffNVLVNNV`PRb^fZVPbfV\VfXNXTZbXXBLVTTXV`H\HV\VZT\PPNPHVTTTNRV^d^XRVP\ZPVbXNVXbPR\^f`ZhN\R^^RRd`PLTbTXPZ>d`HLXFVRLRbd\RPPFPPZPZXLHh\ddFZVZ`RZJ``XVTbHPTFXVPXVTP`TV`:LFJZP\^XVVZV\\RPPXPNb^V^RRRV\LTTZZRNRbZ\XVbV`FPbRRNT\NLVV^\`NJ`^LPPVDXVTNNXJHXBRVN:^VTZHRR\LZZ@P`^XX^PZPNXTJLdXXVZL\dXJDVV$N`ZVN\FTLXXRlVNNTDZPLZZJVNTPR`RVTV^XTLXZPXRRdbT\FRVRXRNXXXNR^VRPVR\THVLfLfJRVH^J<\ZPV XT ^H Nd L ^ d J T D N ` R ` H ` d N P P RRTTRRJZLVTN`X`TLRLPV@HZ^NTPRZ\XV\XXVTPPRZTTRRRXTNVXRXZXVBV\RXVPBR\LLZVL`ZVZZVJJH`P\ZdTRHV\\NTDX\Z\DRZZDT`JLNTVTXJXPV`^ZRVZPXP\RdLRbhVbXVTlfXT\V^bPNN  \  LN N P XZ Z \ N  R T ` X J X V V Z \ N P P T b \ \ P T P b L N P n H l X d P R X L B R Z X R R V T Z L P L ^ R ` TT \VTVVX^XXHRBJVdLd`PN\HPR`PNZPNVTRJVJ\THVRNdZVTTVHZZRR\HZRVZVVR\R\LZ`^RT\Pbb`bRXRP\NVTZP`TVR\^\XNX`bVT\N\PF\^XRnNT^^\FVXPX@bRbXRX\VJbPRT\T\LVVNRbXTZRFNV`TLhR^JTRPTXPXV\XTP`VbH:\X^L`\DLXfVb^\NVVZNTTLP^T^XPd\VT^jL\XH\``^LPbJTVXd`XVFPVTF\H\TZVRRdFX^DPRX\\\RVl^X XXdTTLRfXNPRLZXTdPJPZVbTXNRTZ`VJBZTJ`Jh^hXZR\hX\VP\^d\dPP\VX\VT>TZ\bV`Z\V\dL^R\\ZPN^bJXHVLHXZ@PR`PVJZH\TL^N`R^VJVlJVXVR`VHXTNTb`ZTTX@ZPF`VX`J^ZZXZDlDVLZ\TJVTZV@ZP`ZLTRP`PXXR^XLZPV\FZFNTRZF\V\TZPRP`JX^LXB\N`XTRHT^TPfTHLRbNRJTFPPPdLRb`LFVV`dXJTZPXN^LJJRVVXNXb\H^JFL^^NZNLLX`PXLVRPbPRVVR\XTLHT\ZDXHXHT`RV\DZ^RHFR\Z\Z@P\PZR^HJL`NNZLJ\XJ`PVTXXbR\\VZ H\VL\DX R Z LP  ` H P V T L ` J F f V R F T V T Z T R fXR PNL`@VZJjV\ZNHJP^`ZXLVP\JTRXbP\BVRZRVXR^XNJLTHX\HHTJXTXX@bTXPTZbHXNLfPXTXZNdZJVdZHPDVVZTXNP^@NbVH\XZP\P\P^TRNDfbPVPJb`FZ`b^RRPVLX\LZ^PTB\HNdNV\LNTRTZNJ\ RTD \ P `T ^ Zh T N \ \ T X \ T L X ` N L H Z P ` V j ^ H \ V T J V Z X P Z T H R R  P ^ P L N X H T d Z Z\PPVLV^ZT\P^TJZV\Jn\^PPXVN`XVb^ZN\^L@PJV\JTPJDV^PLj^`TdXRLNRPhZRR^TRRT^XR\XJD^P`^FRRTTVTXTVT`HjVRXTTRbLdVDR`Z^XRDjFJNXRH`Rf`HLT`RNZbLZH^^BXVXRdVXXfR^^\FTNFfJfRL\XJ^\\^TXZ^PLVR^JZTZXTZFZPXXT^P8N^J^^XVX`ZNTbR\`LFNRXXZ``T^``T\NbV^^HNHZNPL\ZT\TTVZT`ZLVHPhLVXHPVJRVVRHJPZZTFNZ^VZZ\`TFVPTXVjZdTbXPXL^dTXT`RT^T^@VXZ\NXRRNR\PZ^XVdNFbRL\X\TTPV\^VVR^PXZBV\TVpB`V\VPLDVTBJTPPLTPT^^XVVhLVPbZ\NZNRRRLTV\X\XLHTJVRT\L\P^VX`fJVVXDb>TNPTb^BZ\H:VV\XRZ^jPLXXVFNLZVHZLLZHVXTZ@ZNV\\JTZJVTPZbL\PXTPZZJjHDDRN`VBZR^P^dLNZPVJVJ^RHLbDRJL\Ld>TZRbVLXTVXZXPVf\TVPHVRFVXPRVNXTJZ\RVXXNTdVXVX\ZZP\ZVRLLTX BR^TPPNTRZ N V L T \ N L V b J L V ^ X R Z \ T J P PR J\VXTHLX\JbZZ\LP\V^XZR>TXNV`f``HNXRP`VZT\TPZ\\@XZ\PfJZXXXbPTVVTZbTVNVLXRNVXVHjPVN@VfT\XZPLHLRVH\VbVXTP\XHNB`^bPH`TVdBHZZNJRZT^ZR`\NZdHNXPVTL PN^XN  B V P X T T b H H P X L R^ ^ d F Z V X R P T R L h P X P T T X V R l R Z T R X T T P F h T T H T b N V L b X L ^ LV  JZhNRZTPXXbFZLZXP^\fZLDNRdFRXVHPLRZ\XLRPTRhZhT\d\^R\ZZZV^XNZN\PX`ZZNPPLRV`LNJN`BbRTdZX`\NL@DXZ^NV^FR@^^<VdTX@bFPFXVTTTTZZ\`DhZPVVX`J`XXTbPRNT\Vd^VV^RRTVV\PNPX^TRRFT\X^RZ\TZZTHZPPhPTRXZZFXnPXTL\bLF\VF`H`RHVTVXN^XV`B`PRP\PVZ^XX^RZZRJ\TRVLVN`VZ`NP`PTX^N\V`RbB^Z^N\VTZR`NPRRP^hRZdHhTZ\\JXfRRJ^R\ZN\bXVZ^TlXXTXZT\\RX\\LZ^LZ\TZPP\NXfZ`TPN^X\JTX\TbL\T\fR^`XTPR^XHZPXXXV\^^ZX`^NPTNZVL\TfNZZ``RT\H`TVN`^TT`\TVNZZJRV>DNdLZPZHLbRZTXT\HPDZPHTRLVN^RT`VV``R^RNVRJ:^JXTV`XDJR\PPbbXZXVXJJTTTP\RJ^TJPZdbH\J`LJHV^XRZZZP`TRP\N^\R`L^^^P\^TJ`RT^\VFJVX^\PLDTVJTLNTVFZXNXXLV^ZHZPXNPNZPNTTPVJTNHTRfV\XPXR J P d ^ d L X Z P T J P R X N ^ R L P\ JTL^ `ZJZRH^RTP`ZRbHXXV\XRT\Zb^TJPbP\R`TRVXNTXXX\VVTRXbVZ`XVRZ^ZHZVXL^X\TJPVL\^P@X`PZfNDV:PLVR^H^PJ^PTbP\PJ6T^HFTLLJXNLZXd^\XXNLTTZ\ ZRT^\XTL F P  Z\J \  T \ ^ T d X F L d ` L R X \ Z L X V V P D T X N ^ \ D T X b R X b T R R J ^ X \ \  X Z  X T  P R D ^\ V ZV  dZPZ^^b\NTXFJ\\FPR`HRZRTZNLdF\JdTRT^\ZdZRZLRPXRLVVNfR@^bTJXVXLPT^TR`\PVVZ^TVTRNNL`^NhXJRTX\Z^`VZTRPTHTXPRHVZVRNbLfh`hJ^VTXPRNTZNXLTDPVRZXV`PTL`PHZZXZbJRXLRNRb^\VTNRVVVTR\RXPRVPZVdXTZZZhVVbZTLjRFZX^X`RR\^JDVZV^FXFHVP^TTXVXb`\VLbXTTZfZlhRZP\ZRdfTT^bJTPPXTTdPPXTZf``\`ZTRPRLTNZ`XFfPTRPP@bVj\PF\PRh\VdPbTRTZRZVfTjb<LdZRRLXd^L^b^bRVZ>H^RDZP\XXTT`T^HZ\NXBZBh`RTRH\^TR`VVN\N`VJHd^fZVNT\XTVLf^XH\T^X>NBfZ\T@ZTTX\PdTZRNFd`\XZLTZTTPR\\TdTZRVZ^HRdNNN\NPNH`VXTJ`XTNZZPTNX\R\HTPNdJJR`P`TFTd^DHRZZh`N^PHJdVXT`PVRZHhLNPZPFNZRT`PNNHZTP^b\PPNZL8FRPJ`V`J:^XLP\^VNHbV>TFVNT\`XZR\T`J``FVVTj\RbXJZRTPb<JZNVX\`LV^LBTTLNLNPFX`VVXT R\ZXP N `RbJ V X V P D N F V J T R N V N V V \ \ N ` X T  TV JLP^bFXVPDTRZJ\>T\TPDHFTD\TTPPZVf<\Thd`LX^JLbRJbJPLDZTPXLL`^ZTPTTP`ZVVJZPNLVP\LRXBZVN^VVV^ZFPTLN\X\LF\VFlV\XPXP\`ZVF`ZXLVNVTRR\V^ T LPR X \V \ Z N N P V N \ R f J ` H L T b Z ^ P X X L Z P V H X T F P ^ Z b P X R 8 ^ V \ @ b  N R R VL R JRV XZ  X ^ \ ^VPLR`J\^L^RVP\dP\PLP`ZN\TPbTJPZjZd\\RPZ\RXVHRdPb\NPZPTZXVN\fXR`R`HR^ZTTZV\J^PZ`NJNN`\VRRPV\^JVX^L\VTNZ\:`\RXH\`\TVLdF\RP`\V<`bTJPlThTFV`LVRhLZN@ThHXHZVJ`^b`\NdJVRHTFX\RNd`TPPZ`XRN^NT\LbZX\^^TRX`TbXNXXV^j^VVR\^N\ZLXXZZbXZVRddXdX\VZZPXNbXXD`>^^XbT`LbTTNPTZXVVFNTXL`HNRNFRX^TbVZZjX`bVfhTV^RTTVbLjJ`JPLZL`^f^TRZXLfVHRXPNPPbXdRZ\P\dRTTbbRZV^`TP^RZVV\VPTZ^NfRTTPPb^f\^VZ`V`\TNNXZTVN^bVFZL<P^\VVLZfJbP\^bVNZJXVVNhbF^XfN\\PdVTRH^RVZDHTfHTVTRTRTNVPXJ\JXZN^J`RLV\>PVNRVXJZ\L@NFZVVZLTNZPb@\NTL@TZR\bLT\RLVDTfR`VNNXLVNXLR\NbRXHV^XVNX^HhTDfVVBT>T:VRZ`R\TDT^^XTRR\VRX^ZPR\^XPHdXRXTf\ZTTHTT bZLL L NPZ Z V \ V X L f T P N ^ \ ` ` L H\ X N V N^ZXL^\TFhXPXXLN^`NVRXHZZbZPLLRbJRZTN\JZ^FTXRTN`JRPZDTL\PDZVRRXXXNNTTPVVTNRRTJFNLXT8`XTPHX@VRT`ZPNVZDL2PXNFVZNTV`VPPFZ`NX^R\LF`R^^TRVTVdbN V R  V P R ` X T f P X Z P \ ^ P R B ` V ^ P T P f d V T ` X \ Z N b T P X J T \ Z l D L N V Z L T LX T P  V X PV f^PTPZhVDZT`TFZRRNZXP\JRXHRNXL@VHVPPPNZTNTFZZ^PVVPV^RJfHN^BVXJ^fLLXDRfX\bXXVVRZXdbNLV`NPZPXT\RhZPPRH\bhTTRZNbTTTfVH`ZLf\XPNXT`XT^XP`Z^Z\XJZNFTTVV``^\XHVXNHNjp>\fN`RHRP^VT\\ZJXPZ\\TFV`T^NPXVZXVRXXVRXXbbV`NLFX^jFRHV`X`^VbJN\`TXVb`FdfR\VbP`bN\TXbT`RXPXTR^XVXTXLNPXbVVPLTPbTdJZTV`NfXTNhdJVJ^2R`JT\bZTJJT^TH\JVRZJT\fVVZNJVbXZTbT\PZTZXZRZXL^`RT`^VTTXdVPHZdVRXZZTJD^RTRHV\ZNP`VXT^TdNdNdNXRXZLX`PZVdP\TPXTN^XbV6NLNTXVV\T\RXNVbVFVZ^TVb`LTdHR^XXNVX^^XRRDPT\ZZVfPLPNdXXVXP\PTLP`d`X\Jj\ZbVbV2TNVFJPDVR`PhRNTJP\XVTNTLPR^dRPNJdPZZNV\PjPRRXXHPR`J\LTVRNF\P`PRRPZHDNZNZP^JLJD>RXNDDTX`ZbJbTTJ\RH`HT^Lb`PLPVPRZTVLVZ>ZZVVbHZ^`X\PR R P ` V P f V T Z L N T V  ZBLXZV^LZ\\ZXRLTN`XPNXXRTfTXJH\PLVV6XRJ`LZFDNRJFT\LVLBT`\NJLNPP\RXHRNPZRPPBVVJFXVVNVJ^^JN^ZRZTRd HVVXXFfVFXXTN^ZXTVPRRXPTPZR\TJ^`RPXHLjZ \ L ^ T P > V P L X X P \ R V B 4 T d L J N H R T R b ^ X X b ^ Z P V Z Z V L T  X X P P  PN V d N Hb L R RNTTV RNVZNRVVZPVbJJV\NFPX^PVJ@DPD\TVT:RTJPTR^XLPTXPTNZ:bFPfLZP`XVNNVdPRVRTTPRL^THThDTPZXXdDF`P\TXdTTVRZHPR^fNTJRXf^dNVZTJ^PVZVbHXRXdTNXPR\NHVhHRnLRP\R\PVHR\XRZZFZRLZ^JXXDjXJVR\R\BZ^NRTPPFTZNL`^`VXZFb^RPFJ^X`ZRX`TLJ\`TVXV`LRXZ\RZX\hV^ZTZTXZNXVVLNfV\^BP\X^\TFfDbTHTXVXRXRL\XTX\D^XT\N@P\ZV8XV`R\PPLTP@R^V`dHRVXf^JPN\^XTTJVZ\LV`Rb^fTNJP\FV:JXRVZ\LTZ`LX^N^VVLN\VPRPTN\NZTV\RXPdb^\LbTRT``PPR\RRTdZ\ZVPTH^RZXBZ\TXRTJZRZPXVP^XRPPPV^HLLVLVT\XXTPPVRT\RV^RXP`^XT^RTXT^`RHfLXRJZFZ`TdVfNL^RXPNXVLVZTLXbbfJRPjTPJX\fZVTZPRP\XZLTdFTDhLTXXZLb>bVXNXdHXRDXfPT^T`NPXbJbXPF`V\ZbZ>PLVVRRVZXXbVZTPLZ\NJPPXbZbbDT^FTR ^T >\ Z ` \ X L T T ^ Z T J ^ ` d X F Z N V d    T ^^<NXL``RZZVLHP\RVTXJ`ZZXdRFN\`JLPZ\ZV\JNRPdJL`PL^JLZLRV^R\XNFHV\PVFFNPFJHPTTPTRNNRLHVXX\\ZRFNPT\VVZLNLNDPPL`PTZT TZVLX  XN R NP J X F P \ LR V ^ P ` X R H V J L h N L T F Z H V Z R T \ J V J Z Z ` N Z J b b P P T L T T b V  T Z^ LbTFP XXZ^ZFLZJXVJR`NLRH\RZN\X\^^bVP\RPP`XL`Z`RPJlX^TZVT\PXVJXLP\\XD`V^Bd`ZZd@^\RDTJV^hP\RXPNT^bjNRPTVN`TZZR\^TTZH\N`PRZbXTLVNZVZJXRZTRTVLN^\LX\T`RT`jZZX\FTL`Z8^dZZTNZdXP\TV`\XZ\^Z`T\VV`RV\P\LRFJV`\ZlTV`JXdXVbVZN\`dL`\LRXh^XVNVddTZhV\VZRRPP^PJ`F\bjLRXrZ`Lfh`TTXPB\fX\LXVfXNZJTjRLVVH^`^d`TdZ\R``\jRbRN\VLRNLVd\TVVV\V\b^PH`VXP^RVPXT`RZHP`XPZ`XVXVXRX`\TH\`PPVR`NLRXNV`J`LXRJRNT^XN`DFX^RXPX\NH>bJPdRdbLXj>X`\NdLXPB^RbRZJ\\^RPNLNZPP^RTZZNLJTLRPZRX^ZP@ZXFLPRTPfRLNRTTT^FDHZXTPP`T\VTZXTVRLTT\\P`P\JPZNZX\P^XRPPT\^TTRJP\VRLPPTZZJNXVLPTHLT\XDTXNVXNNXTHXN`\ZdXX`V^LPPTDXRP`TV>ZRR\\\PTNfL^X^V\XXXRR@VbRLP\\VNbT\ZVZVLZ L Z N N h Z R Z ` N N f R H ` R PP `T R H T\VVHTRZTV`DdNRXDLLTTPDPZ>\^XZ^ZbH^\X^LXXN\RfDNJ`FPfL\\N`VVXNTX<TT\LTXR^XVRFXPZVHNVPZdRPJJZXTZbP`.ZL\\^dTjRT^dDLTVJdVPPLVT^RNRTLX\\L nT  L Z ` P P N Z R R H X L Z V X L \ ^ L X Z ^ T Z X L X R F H Z Z P T ` J R  ^  R V X ` T \ TN J N TV fPRLJVNXX Jb\^LPHPN`VL\\TdZ^LPLVNPXH\VTVTXH^N\TVV``XVPXNPBP\PZLXZ\\TX>FXHTL\NTVXJNP\`X\\Z\VP`RF`XRTJ`T`THV\\NXF`dNZHV\:fTV^ZJjZN\^JbPNPVdPP^TZRJNPTTPPPFZPZHPL\H`V\DR\XPNVR`Nh\RLFX\VZ\RXbXVPT\VRJVVJT^d\^XZT:VJR>ZVdJb`VP\TFPdRf^\V^XVRL^RV^NfTXNVbPP\`VPfPZX`^F\ZlZTH\VXfTTN`ZTP`J\TTbVH^B\d`LTTTV^@bX`^RVJ`B\`PVTRHVV`b\X\NXjJLlhRPbT^PhTL^^XXVHD^P^XZ\^dZR^RRHZX\PXbP`^@^^N`\V\PVZL\ZdVRVR^^ZXTRLZ@L`@\dLFZTT`DLX^fZTd^RPX\dLZPZ^\VZ^BLVVL^\V^NRZLRPXFbFR^^LNVVZZ^P^lTRRVhRJTXd`\PTNZRNLN^RTRT`VRZJVZFZVZLPVPT^\PZXTXT\VDLNXNX^PHVb^NXZPT\XXZ\PN\\ZBZFB\ZZFTZZNN\RTRDZH^JBFbZPLLRXN\NRPdLNXNFF`DHVZHF`TPRVdXTZPVRHTb^Z^XXNVP^TJ`PdRR`LVRJXTRTNZRZTBVVZLTVRT^L b L X R H ^ b f T N T Z L P \ T \ N \N^\PP`TNTXFD\H`NVFD@TTBFV\RJJ^TRPBbRHPXXbPPRJLZbPNTDZTVRRbZRPV^VPVJL\JTXPNRjbVV\PP>LTP@\HPVJ^LLZ`lF^X\XNR RFH`XN N T  \ \ N L HL X V L b N P H H T V h Z T H H \ \ X D \ T h f X N ` P b L H P Z N P T P  b N X P L P \N X T B J N \XNR V^LRTTRTbJL^VVTdTZTNXP^TTVTRHTZXVX\XThP\PR\\^ZPVPPPRPNPVZdZJNL\RNNXXVLV^dNV\XZXPXZNXZ\PXRV<TZ\L\dVDDZRTHVf^PPRfPV^R\V\RhJ`JVRRZLRN`^VZZHDdF`T^bT\XTZ`TNZbV^XXb\RPTT\NXX\TZZVXVJXdTXL\XN@V`TPVPTPRT`VbfJ@^TTH\dl`R^R^X^XTTnJX\\NT^XXRPF`\VXXRZJTbRT^\PZZRdXZX\XXbRjTVFXZHjXXPN`l`PV\VDNJZfX\X\VdbNVPPXRX\\dRJRJbVLXDFPb^XJTRRPRPXFZT`NHR^NRXXJTVXjT`XdbVd\\T`RTT^FZVbPXbNXHXPLPVdTNJJPVNPTLVPb^VTZVHT^V\\^\TZTT`VP^X`H\H\ZPR\`NRRXN`VVJ^TTNTDPVTDNXbT^DNFTHJPHLDVDLPZP>TVRdPL`DRZ\hRP\\ZVXTVNTPjJ`lD^TRZDhTXN^NLTXTVT\\`RNXRNN>XTJZPFXP:LXVX^^RTVNZVZ`PXdHZ^\V\RZHHRXZVP^TVTPXRNZVRZJTP^XZ`TfZRPHRTdTNL^VLHXX^RbTVTRRJ^XVNdXTT\ZDL^NL> Z H f N X X @ H R \ T X X \ T J Z L T  R \ bRTR`^VRdXdPL\LZXJbTXRJZ^^NX`bRT^TVRN\`LTdTLJZR\J`RTZFTJRhJdVPNP^VD`Z`^T\PXPXVPH`FdH^NX^P\NZLZXP^T^HL^\DPLT . XZ \ VBPT XF R T  Z X P P N : R V J ` \ V T Z F T R D \ P X L P R \ \ ` \ T V ` F X N R V L Z \ d ^P \P\ NfN V DD J`\RPZXXXNNNXJ`\^PVLHXNLXPJL^JTRdNTRTZ<^RJVXNLJHTVVLVZZHP\TJN^TLbJ\^XNb\PTJ\FPd>R`TLZdZR^>d^TXTLTZZ`X`ZVXdNZR\THH`JRbL\NRVXX\RHZTPFRLZTZVRXZPZPVXTXB`NJPTPXLRR\PJZV\NNX\LX``X`Z\bVRT``VPd^N\DFRD^NjL\RDV@bZNZTFNJ`V`RX`PVT`HVZRV`\Z`ZXJjVb\bPL\ZP^ZZV`^VZNV`XRLTZ^VbPf`^VVZVXdXf`T\JXRVPR\\HTRXR`jRPRf\RbZfDVZbf\\\ZVZZZJPfZZRbT^RT\`^ZNPhTZb\\NTTTPhZbL`\^L^<XLPNVPRLbRRDdRTT\LX\VXHdDPJJXZjT\V^NbPR`P^ZbRdNbZ\^bF\TNlRfF\VTLFLV^`^^T`X`RRJTTPdRRNf^\dZV^XXNZBhJbNVDVLRZHhHNVLb\R\VdLdX\TZ`HRLPRVVH\JRbNJNZ^dNNLN^J\ZRT`THXJfL\dZDbX\BV\TdB@TVdZ\NRZV`RTJTFJfN^NL``VVLFb^PHZHRJTXNb^TZTXPT\`N^JTdVNPXPXFVN^VZLNPZNXVdZXVRbZRLb^Pb\R^PRJR`X X X T ` P B F X P R T ` V R Z V Z ^P  P f\XN\ZRV\\`RXNZHT\LXPPTLTZL\XXLTLJN\JV\JLN`\lPZ\HVjPR`ZHRVRRRLNZ\JLX^XHPXVJ`R`RRD6bRPTP^ZNXXP`DNZ\ZR\PTP\N`  LRLX X VPR Z T NR R TV J X H X P X R R R H \ P P R H V N D Z L \ X V T R X b ^ L ^ ^ R P V P \ d Z \ \ Z L ^ bV\NVZ NRZRPLNRFXFZJVPPVT@HR^ZR\^JZXNRN^TVhFRLVJVTLXJfX`HPRXPPVNL@^TLNTTVFTPPR\JJZZPXZH\N^VTPZR\FPRZ^\\RTZT^PX`T\ZPZRNPRN@XL^bZfRZPDJP\^VRRPRXJ^XTVJVLTXDZ^\XRN^bJPZT`ZlRLHNXLP^\Td^\PVNPPhdVTN^PRTdX\P\PdZLVV^J\NRR`X<^XVZZ^`^P\L^\PTVZ`NV\lLZXD\^`@PRP^bVJXP\TH\\XXN^\ZHZ\XXRDbP^LD\JDZXPPXZ`LZTdVXJjJf\P\XL^L\H`N\VB`^J^XZHRV\NNVFdTJbJNVTR\`TRbVR^VVR\ZJ^T\ZZPFNPL`FPRXbFVPRPRZ`XXLV8XNJPLVR^L`XVPJXN\JNXLVPNL`RRLBLTZDN\RTJNZ\JVTTXPVHRRJ\RP^DVLJ`ZTPN^<`hDRXRJVZTbBRbTZZLH^TZDTJ\JTZFZXLTHP^VXJRTZRRTZT^ZVHTXZRPVLVRXZXXP^TXb^LP^LXNLNTVPLT`FHRTTNT`ZX\^FP^HTPR\^RPNZX\HRLbVRVb^RHN^^TLPVVTLVdXXVRbRH\TfPX\R`PVRT`VZRXP^LTVRPTPh^XZL\DFPVdP`d`^J^JdZ`PfXTPRH`RX`LDbPN D H B h ` D X V b @ J \ f T V Z \ PT` H RP fVVP PTLRNXPT^T\\BbTRT\NX>P^ZTVNLTXTLH^dV\NHZJ\PLRLFRX\XZPJVLVPNLVPNVNTfVRT^\PNRP^NDTRJVXTN`TVNXLXRX\TbPZT^TZZVVdN`TT<\ F ZTNZ T T F N Z N P R H b \ \ X V ^ J T R X \ R ^ X L T Z L Z | V P \ ` R ` L F R    X \ X R P X N \ L H R^RTJJNNPBNZL@dNPHFbJVd\HNPNLLZRBJ^RHPT\^L`PT^`THZV`DVTZJRZLPRBZ\\XTZbVVVVLVZNbRTPR\ZP^>PPVR\f^LLbNNPL\\J^^VZTFdLP\JV^<XV`PR\\TVV^ZRLPPV^H`P^FXTjRdfZZVPbVTR^\RZX\`FRHVRBT`Z^TJT^`RXRZDTX`L^TXXXX\RDPbTRTH\VFZL^ZXXZXNTLT\XZTLXFBTT`^R`fP^NTLFPLP\J^RXPFRdRZb^\XZ`VT\TdZ\R^PXLTLX\XVD\ZhZ\bRhPLbVTLVPPNNRRVDX^XJbZlZ^bJfZVd\ZVP\RX\`XVNRjbB^LZVZ\FZ\XNZ^N^TVTRRRdH\`bPVLX`NLZhPXRV\bXT\XX`N`VT^\ZRV\\VVVX^\b@P`XXRZXJR^d`LTVT`NNXdZPHT^ F`XTX^^^`NLPJFZPPRR^XNJVHRHTXXRXZHLJZVTRPNZ`N\HP^F`\HPTRbZVZLT\JfTJXTdZLZbX\\LNZ`NXZVVZN``LfR\VdHPJXXDJNbTPNZFhX^ZTRVTH\XZRVHTRPJFNJPNfJNRRVZTVZd\NTTVHTPF`X\PXXTlLV\XVHNN^`NVLdJJZVdVTTTRV`ZRRPJ^`VRR`VRXXLXPTRbPFV^TTVZ`VTZ Z X Z R V F L R V D L b b ^ V ^ h F V V Z @ JV ^VPRZVRFRTbJ T\NRT RV RLVNRfPRT VZTN HJbX^RZ@`JR\\JRT\L^VXXJTbTVRNRTNPPLVBTT\XT\LTVXZ\TR^VJ^<Z<XJ^R J` ` Z V RJ VVL` ` V d V Z T R T T T V P X N J R R T d J R V V X J N j  T J X ^ V Z \ R X VV X L`N VZVRdLTnZPXTL`\PTZTXLNfBFNJVVRVXZXTFZ\bHZLVNbVZZ\ZjFZPPTXFV\P^VJZVbRNLZXR\^RFhV`VPTJH^ZPDHRXbPN^RRZ^XR^LbP\PZT^PRXT`V`RPVLNL`XRZdPVL^X^RHZFTRNTdR<VVRHNJ\XXPLHPZVPPJRXXRR>^`NTRRTX\DX^\PdTV\TJ\R`VVJ\`JZ\bVDfXP`PTHR2ZPTNR^VXL`TXZ^PPPXNVN\LV^PZbZP^NTVNVXTXZH`HJP^bPR^VRT\XZVZTnF\VZVBHJ^^XHPXPXZP>P\TZdJb<XdFLXXLRFhTd\ZDRPR`\\RLRZPLP\^XLXHZVRV^VTDPRZd`NP`XXX`\`FXNXDZJ`TZPPR`NFH^f:\`RbNN\\`VNfLPRNR\^NR\T^b\FLL^H`LXXdHRTVFVVLP^PX`RL`V\`VT\RZhVDNXZXXVXR^LRT`XbPPT\RX\XVZRVZ^VV``ZH`JVPNLDZR`ZT`TXRTZ\\^RV`\ZBNHRVVbZ@^RR\HVXZ^BPRTRTZRFJ\bZ^VdZRRXVVV`LJXVPHLXBRR\`\hXTRJZZdPHRX^LVTNTTZHNTJ^BXZLXXRVPPX\RXTNXnH\R^XN\L\\NLZTZVVN\\TXRP N   B \ ^ h L Z < T F ^ X \ X Z Z D V J N  NV ZL`NRRR VHTLDLVHR \ V`VXJTX P TXZT ZXB X`NXN P \NR  XLTTTH^RV`PJRVb\\T`bVX\NLLHNJLVZXPVR\DdPNfZ^PX`HJDZRNRTPTJV^PLVJ XT P Z ` \ R T J V RV V T \ \ P L ` N l B V N V J \ L P \ J H \ P T ` R J \ b\ T Z bB V \  Z V ZZ V X\J \`B^VT^JVT\T^Z^bTJFXT\TRXBdT\XBNTPTL8fRRVRJRVPTPLZBTBRTL\`X^^RZ\PXVX^XZPTFZXFPXN\dXdZFVbHZbTTVZNXPXLZR^LXX`FVLFR`^NfTZ^X\XNTVR`ZJ\Lf@Z^HRJPZNRN\LXLZXZHR`XTNN\PVVTN\TVR`TNLXThLXbLPRLBLXZL\VLNVPTh^`RTRTVPVV\T`TR\RRXj\VZjZ\HX^VRZVV^NV`JVX\Z\Rd^dbbLRNR\TZTV`hXZTNb`PRZVXZ`VH`ZTTRL<XZFN\TfNb^TNZ`VRL^XJb>VL``LNZRTJVNR`T@Z`NPVf^HRVP\Zd\BZVTl\\VZ^TZRPXHVVRVPZZ\fRRVTXLLRVNTXTZTTXRFNf\RDTXfPNVXP`Z^ZNRbPNVZFXfDZVRZP`P^FLJ\Z`XXNXbB\TFNLRZ\VZV^HV\@VPVTZ\VXbNTVV^`X`DFVTVT`N`RTNJ`XRVVLJ\ZZPPZfTXDZPZTVF@ZDL`L<TLVJ`VXRL`N`VL^TFPPXNVJXb\NV\\V8PXZN\HR\`PZXPTBBRRTXXFTLTRNLRPN\NVLJ`^bX`RVN^bJLPPT\V\\XJfJN`TTZTT\RP\`VLPF\dVX`V\RTD\RFPZXhX\XZPXHXL^P\P\TdP LXV J L f ` L Z R f H B d N b R Z V T Bj V TT V D^\ H \L  NNF R   XTT n L ^ XNV^  `  T X R  P \ JVV bVVZ JZ d ZR TVbTbP^PNVZNVPh^DFbFNLLP^ZPTPJTZb`VTX VJR FV`TP J NX X V R R N Z T ^ V T R P R X X L X h @ b J P V V L R P L ^ J ^ X X \ T  X Z ` J V P R R L V H PR LZ d f   VXJL fR<ZX\^\@l`NZhZZFXNTHXVH\XPTRZNJVXPPRJ^H`NJTRlT\RRZ^@P`VNZTZFLdDNNJL@TPPPR4LZVN^J^FLTZ^FPJ>XNJXPT\TT\\XjX\BXTNTPbV``^XZfV`XVX^XNZR\RPPVZJNZT>hTTVVnRZD`PX`NFdP^T8XHX^NLXJdF^PRRPZFXVLbPTV\RJ\^PVNJfXRLTZNNPZXRZ^TTdV\VTVRVT\`^XVNXb`VVXZXLVVf`VXf`VZhbTVT\RbNVfJ\PJd^\VBdP\`ZZfPV\^TZVPF^`VTRV`JRdRL`dJfZZXNVVLN^VHTR^LTV^RdVXPNV^jbdRf`^^b\`PNTVTLRPb`X@RTP\RVRZTTVbP`D\L\^RRNVhR`TT^`TXZTbNXZZXN\NVHbHNlXJPVZXZb\R^VZRRNPTVRTPVP@ZZTH`JHLVXH@VNh\J\>Z``PN^\RLLZ^hVTRTV\b`TP\JTT\TLVRbNXRLZ``XL`N\N\P\R`P\F\HPRbP^FXhLZHdJ@VH@FXXTZZN@TNfRJRXV`PNT^XL\TVRXNTZJRZZZRRNXPNNPRXXV^\LdNH@VPfX\XZXPPTVDPLZXHdTH\LRVZ\RNLJLPL`JJTTNN`NTRJXRXZPfRJ\TLL`RhFdTPTXNJLT\VT^PTXNNhX^PXdVZR^@JT R ^ H Z Z T R T R P R V T V \ N V P T H  ^VXTNT \ L^ D X L P\ XTB  JP JFN> T N X T X \ B R T R^ T   bN `J \XTV`TP VX^DVT\JNZTLNF\VNHZFdVX^RRLXBTP\ZLNL^^ `FJX RLNV F X` R  X ` R ^B  T R P R T J > P X R F @ T N H N X X \ J H J V ^ P N h R H T f D ^  V \ H Z R X J XP Xd  V `ZFX^ JRNZLLdLT`TT`fR`RP\XTTR`NPXbL`bLPNVJXXRJRZPXNLJ\RLRXXXTNT\\ZbXPVTPHXZVNPHXZJF^VPH\Zbb\TbZHLX`XLFT^VfL\^`\dBX\ZHRRZZJPZXVN^NXH^^JR`fTJ`R^^VV^JZZPZVRZZX^Z`NVTRTV\ZFf^\ZXRVVfZP`VR\`>TP`FZVTR@TfTTbPdP`Rf\JXTTRNX`VB\R`R\fdP\TDRDPdRL^\LdLRTVTXZ^VXXdTXZBPJVV^P\HJXdJLTXDVT\VDZDRTfL^F\`^FVX\^^LRZX\\RbZVHHXP^FLXRZR^T\NZ\PHLXVJ`^ZPX^J^N^ZTLVTh^^TPZb^HL^:RRXPZP\b\Hd^\V\\dPLDVRVJZVNNTLL`L\V\PV`XLTT^XNRJLR^RZXNLfVLfV\JTZRbBZNT^jRLVPBJTdlTTL\XTJVRdN\B\`DPdDd\\\XLN`RXZVRNhLLN`\XXRVPVbLZL^RNZlZTVRhPTPZVNR^dTV\`XZ\b^XXL\X\FXVbXPfTNPZVRJd<bRNLN`jLTVN^\TV``LZXNLRdVTTVR^RXPDNNVJN\XHTJ^XX`V`RTRLVLZRRTZP\\^`LX\\RJXJTXR^NXV^VJLTHZLJVXTNF\XVXTd\DV`X:PHfD\JNXN^HPdT H V N Z X R d b V b R P N b J V \ X Z F P \ TV Z \ FL N ` \ J R T H XR  D\ D Z P DL Z P V V X b V ZRN N T R ^  V XR X D ` JXN X RXLXHdTJ\JTTR \P\\N\X:TNDR^ZPXPPfVb\X R FfZT R L  PJ V^ B P X T R V R ` Z T \ R Z P T \ L ^ N X T P T \ T ^ R \ X \ X X R n X F H \  Z\ \ XV RV LX\PJV\\ ZXZTLJTTLLRZVZV`HFXXJXrTFLJXNNXbHPZRbLXZ^LNLPNNRFDX\P^P\J`J\fLX\LZ\TPRPPTXJdPVFbRTXL\Z\TRVRNPNXX\NVTN\^NLLXPFXL^FbRVTRZNDhT\^>PPDb`VTbNV^\PdVPTRb`T`V@XTZP^VTRTTNNV^VNTDLFRVNZN^RdXXTVdbTZZ\P\TXHRDjbPZ`RDLTNNTXN\ZDZRTbTPVZR^^PVTFTXdDLNXXLN\R`VN\N^ZBXb\PZX\FV\^HDZRZ`N\TVZ`\T@\VhRVFHTZ``^bL^LtJX\NVXRZXV\XTRRXVX\`d^\VV\TJ^LT^^V\RRhB\X^TbVHTZXddP\d`XVhZTHXb^bNfPdJ\VLb\RRPd`bj\TJXVVHFNTVZPXTLJLfR\XPDVRNJB:`XTJJNRZ^RNPNVRPRHP^F\R>VF`PPLTNfFVVNPRPTTPJ`JPXPRL^TPfT\NR\R\XHT^V`\RRZLb@ZJLNBZTP8RTXdRRB\FX`PPN^TVLdF2V^P|ZDDD\Fbb:XRVVLVb@NN\LbZTVDTRbTZLTRNRTZHbLTJ`R@NJ\^V\PLbLVJTTD\R`RZLTZLRRTNXF^LRRPPNBZTHJBRXTPVPFVVZJZ\VPXXTVP\NFZVZbfBLRBTVX\LZLZJXV^NXZJJPZVTPJ`XLXL^VNZVT`XXRbJ \ Z X \ H ` F V L > N V J ^ T L N `  D XJT T J ZL X J N T F X LXLV JV\L VV 6 DN L^ R ZJHXH P V J V  X HXX P R ^ N T H N>L P b N L R L X L TLVf J`NFX`XPr ^NTJR^RXVP DBPNVTX NTZN LN `@ L `R \ b D Z J  ZX P Z Z Z R f Z P R D X \ J T P P X ` R V P F V ^ J N T Z \ @ ^ F P T ^JL Z V R`RT RPTNPJHLHBZZZJ`LbNPXP\^\NTZVJJVP\NZLLNZ<VZLRVVT`NVFRJPTFbNRLLVdPTRP^NRVRTbNRLT^\VXbRJZPXPZNLXdPXJJXXf`HTR\RNRLT^TJZP^DNbTDHRPRJfTLLN^\XXLPTX`\XVTXXVZVHPT^JTPJ^P^LHPXNNPNVRDRZTNLXDLbPPPRP^XFJPX\VTV\XV\PXPVDRNbFX`ZXNNRHTX^DTTTbXFVTdVTXZZP\\TfHLRPVX\^TJ\RRP^R@bLT^ZNVPTHRfZ@LXZPT^V`\ZZ^NVZJZN`PNN^dZVXdTXN\NJRXJPhZRJPXTXVPXR\^jb^^RZPVTZTVR`T\\RXZVjNPRZ`ZhXVT\fLX\TZR`PZ^Hb^P^^RZH\`R`TLLX^JLL\XP`P\dPLPVP^Lb\N^VZZZdJJRTD\TPVZXZ^VfbNPVTZVXXRVJJNNhHRTPL\R^FfVZP^PbV\P^PRXNVNVFTbVL\Z^TV^HTLNZZ\Z\XZnPVVH\L^RRTNVH^XXTPJTNFBZLXJbPTXN\N\VLFXT^TRPZHR^HPb`b:\VVRZZLDHZPNTPdX^HFZPTZTdX<V(\dT^TVNR\LVhTTT`RP^TPXRTLZTRJL^^nRTDR`TVLlNHTXT\LLVPNBTT\FZV`VXLfTJXNRRX h P T V J < f R \ ` P ` H P X N R R N D T P N V ` V J \ JP < N  N X V F > T`H D PN \ `VT H `P L T VX R b R TJ D X^ R Z V B H P \ H P B ^XZ  JhHTRP^H VT\ NPb J V TVZJVXT\V LbR\ZFRTJZR  8 V d T X B R V F T \ \ V N X Z L T @ \ T J Z ` ` F R R N X X L @ P V \ V R X X L L N \ Z P Z F Z T fR Jd J LHFNH\NZVTJXZFTTHZVTdHbXdL`ZPhFTZNJVTRVXPVTH^V^PJ\ZJZ<RHZH\b\TLTFVXZNPLLFFVFLXTT\VRRVT\VLNRdXRNlVJX\JXJPRZHbZZPJNLNTPPNXZNXBfLXTNNVZ8V\XT\`\PDZN^PB\TRVHV\NXF`DV`^XVVPXRd`F``ZP\NZPT^TLTdLTVVTVTJhJTPRJ^\V`JRHRXTPFF^TZPFVNPHJRV`VTTTRTFLDLPTPXJZXNb`V\JXb>^^XPL\TVRXTbF\PZPVHXTTPXFZ`FVTPX`Zb^`ZVN\PF:^NZB`VRfZX`T^R`LbP^\`\\LTVTZJL\dRX`VJbRVLXbJRHVZP^``T^\`\RZTVT:VL\V^TTPXRT`ZLNLRZ\TVHVVZVRXXV`JFXNZ\X\ZJJZP`ZRZJTJTH^`P^NZRVVTZL`X<R`BXRRHTXX^bTVVXVTPPZX^NJTTLXZ\TV\N^TXBLVRTTbXVFTDRH^RJdLXB\LLVdTj`^DbTZNb\JR@VHNNVVVTHTJVR\N`\NR\LB\TPRPPVZLPPJfRJbRHbXRVRJVN`NZ^J^TRNN\VRZ`VLLV\ZZTDPH^HVTX`HRdTZZ@RTRT\TTRZNZJZVXHVVTJ`VRZZTZVVJXL^^JVTTXPP^L^ZLbZPTLRRVRPRRbVXPVVXNLTT^Fh^\DNPbHRVXPd@`ZR\T` XT^DT PP P R N V P X F P R b P L X R J ^ H T b H T D b X L ` N d TB N NZ LL Z ^  Z V Z Z \ RD T V P @ X N d N X Z L R h N R P P J \ P H PP XVZ XV T^T\P ^\f Phb X N P P JZZX Z N D   RDR T H b P b X R T L P N P f ^ Z D R D X L T R V X N b B T R T P J N b N V R N @ X H Z N b J T  ZTZRXVPHVTZ\J`H<N`DLPVJjTR^T`JT\\RL\N^L^RVNBXTRJ^\XNJFj^JZRHRXTVJ\HNdJPTNNHJPVFVJ`T`DF^`P@VNTDDZ`HZTXNPVLV\`TZX^XR^RZRBNLT^JdXfXLJ`HbPJH`TT\T`RXPJR@nBXLZP\`\JLN^H^`T\^XRV^TNXNTPLXR`>`ZNPPXhZTl^ZTVVVLJLXP@RVDVLXRV\TDBHV`PNNTdP^RB\ZNR\RNP`@VV^RZZPTTJZTT`ZV^XNPRXXfR\Z^ZTVZZd`ZZbZddXh^RVPPPjJH\FVL^PXTTZ`Vh\NbdHPHF`JZHZJNNP\ZHZX\PX\^RJNL^NVXLZVZ`bdZL\^dT^^\ZbX\T\PZbZXVbPB\RXZLZXRV^HTV\\TTTVZZZb`NX\VFf\RL^JRXbT\PRV\JZNVZN\LVHTVR\X`VRJ\H`RbZZR`XF\NXVN^VTRTRXPhP\f`fZf`ZVTXZ\XV\^XbTHZJNZb^PPPT<fJZVXLZVRR\T`RX\R\VXZR@HTh\ZHPNNTJ\VZZLZ^VVVTRXX\pTbN^JNdHfVXZPRdB\TPVV\XH\LT\HJV\JJf@ZRRP\TTVXRVD\NDTPNTR:JV`TPb^JR DjFbFRL^T^bTPXTPP\JPJ`RRRTPXLTH\ZZNHHbT\ZRTFJXXTVRTBPNPJNTXXHZP`VXV`NV\fPbP\RPRTLZNLXNFNPNRd ` H X N ^ P H T T X V L R \ b N T \ J  L RJ\ T P NX Z b J b R N Z R \ b V T F T Nf b H P L R Z H T T N N f @N F bN \ X  JbJ^ F H @ \  ^ \ VX N R T\NZT R \ ` L L X J ^  V ` Z ^ H X T T V R V \ ^ R T N L ` L N Z P \ \ X T V T V V P L T b ^ R N d T X T Z TTfZNRF P8N^FV8bNZR>b\N`PNR`ZLZ`RZTdNT`PXLZR^PZPPVRVR``JTT`XT\ZZVPRNVNPLNVRJTX`\DTVXTTL\\TTRdPfZ\VPLJTZPH\L\LPTZNPTX`ZJPRdTN`TVPTTZ`VZTLNRD\bXZRZXRR\hTPRbL\`HVNLVVTRR\VRNTRP\fNbXRXHVN^HPZFXXX^TXJRFFHPdTNRLVTLVZ\ZXRVTTThXNZZRTZPTRJZTlXPVXNXVVRTNV^\V^\Z^VPb`LLbZNFjPZNPVVXP^VVD\^Z^dZXVLXTXR\XVRX\RLVHLF\H\JThTZ^PVT<\ZHRHTZdR2ZVZTX\LPT\NPXTJTbV^`LjXVZFZNXT`^PJJNLXN\TN`L`LD^HPT^L\JVHRbT@NFFVJX^VZNLN\F^L`R\PRLdNXFR^TPZPRHXLTLZVPVRFHRRBNlNVJ^VZRPDhPTNZJN\T\>VXHFnRNL`JL\HLRND`ZLNZDTTbXNFbRZVRNRXVFJTLZN^PZ^HjPPZXPVXTTJTNZJJRRLTP4L\T^\`PX`LLDLXJ\TJPVRPHZ^VL^RR^VXLTNPXRXPFVLRXPZX^NRTXRHTRVNVP\TJRZXRRNVRVH`RP@^BLXVT^HZ`NZVTPZXPPZJXPLJRTP@`LL^JNZVJVTNPZZ^LNZdLPPVRVXVPZXVTZVVPJHNRTRJXZNZ TN P X T H P \ R b R X ^ T d P > T J N V N Z H V N J \ X LR R R R X X h ^ \ P R L ^ R H V ` L L D \ ^ J L Z \ \ V \ ` Z ` H N D P R T ^ LH T R X X N PX VV VT ` R Z N N P ^ T N LVT N Z \F ` \ X JT T J L ` L V Z \ b f : T ^ V B N ^ ^ 8 X J R : T R R H \ X ^ P N T R R N L J V T N N X FT ND X TT NZZTPL >RJLLVN`NLJN`TRHZJVDdFR\XRh^VVZT\FVJJR\XHTVJTX^XTL^^^LXFJVZVZNTHXZ\FFbRNXVXV\b\TPVX\^XTZRNXTLPXNNZLTH\LRXRN^RL`\Lb\V@V\ZNNVF`V^\VNPNLVN`\VBXNVTBJ^R^bJTVTLbVRTdL`^`\V`RTN@bVVPLFXRNNTRPPFT<RJNN`RRb^HTLRNT`XJRPXdXNDj`bT^\ZVTP\TZTRNNXL^X\X`ZVT\\VPV^PRNNVN\\^L\NV``FRRVVXX^XXXXd`TTdPZ^VJXFfZFXJRVLXRVXRZR`XR\ZX^JLVZb\Thb\TL^^RLVX^VZDRXTJJT>TFVRVbBjX\jPHZT\VV`^\R^ZZRVbZF^X^NXXPP\VR\ZTnNVXJZ^b`RZF\Z\VL\HVPPVN\d\PBZ`TPLNJ^Z`NTRZRNjP^RT\JPTjZdTVZVDRX`^VN\`NJdPHVZXd`NVLfNNXVXPPD^RTB\PZL^NLJRPLLXXTL\\XRTJ\XPPXZbRTJ@T\RRDfZbPJRX4HTJ\JTNdLPZBR^X\LZPHRN>H`RRNZ^PTFZTVZ`b\T\RVNTVXVX\D\TXVPRT\PVZPLNVRXFXJ\ZZbJb\\TLTN8ZbZD\LZZPVNZ*ZPVZZL@RNRXLXHLTX\T^RZVNRRTX^\HLJTTZRRVNXPL\XPTTRTRJHTL`ZZJJN\^ZZXT`X`V\` JPT J J N L ` VN ^ X Z X ^ X D ^ ` X d Z P J T Z D V \ T V \ \ L \ X X N Z Z \ T V P R j F R H J P L d D Z N \ F N Z L J Z ^ P V H J J L Rd T X V Z N J T R N NN B X T H R d \ D R T V N  L N ` Z X L T Z ZV P J X J L X T T T T R H ^ V ^ \ R N N J D T P N F N Z P \ H \ Z F V N N b V  X R Z VZNV NP\LJTFbLNDPX`\NPTFZX^NJfP\PVPNdTZJVRX\XhLTXNTXTXTNXVPJ@XVPJ`d^`Z`R\P^TVNVXBTXXNPXbTlZHHdTZ`VLNJ`TNDPL^LTXZZV@TjTRN`fRVZXbbR^ZPPPXTNPT\V\^ZNLT\X\T\bVB\VRJPPb\HVPXJZPPRR\`bFPLZTTPRXNTRNT\X`dRTFP^dLR\LLN`VRRPJPVPP@XLTNLbV`THHTR\TVTbTT^4LVTTZHTZ\T\HZXNRVTP^V^R\TN`VPdb^V`FHXJ`ZTVLTZP^HJdN^`R^HbLZRHL\VNVNZNb^RpXNLTZLVRRX^X^PX^VJXZX^\TVVHNPPXJbfNjRbPd\PbN^@bXN^TdJ^NXX\b\PZVVPZLXbR^^LNPFXdT@XV\BR@HF\\VRVV^RNNLJT`NZXRXTPPTZZZF\LNPPXpXXNTXNXLPLjPLTVXTHJXV^JdLN^JVX^hRRZLT@VPPXHPPfH@`LP\PXVTPL\ZV^T\J`\\HRjNVTHVZ`PZTPR\P@VFNTTTFZN\\F\:VVLN`NXXPN\TTVb^^\RHXRXVHJTVb``LZTXJPJXTZVZNNHXR\N<LPXRlPLN`^N`VLB\V8RbTDZRTD`Z<^N`ZPNZPNPRZTXRBVPPTXbFVNZL8FlRRRNPTNTP\^LTVTVhfLb\dNRVPLXVLTXTPHRTLVZ\`VDZJNV^T TXHjXRBR N j  bR P L V V X \ ^ F V R R V V L L X V P T Z N R X H J F L F L L d D R Z T H f L Z \ Z X D F R H V ` T H X R F ^ R T \b T X d \ \ T J Z H R P ` b T \ N T \ F XJ R T T N T P T ^ R H ` L R Z T > ^ N P < T P N  ^ : N R V D R Z L J T N N Z X T ^ f XV R X V P @ R V X R RV H R`ZJVNL`R\TV^\NVJZXNJLBV^XRVT``V\ZbZBTXRP`VPVXTL`X\\J^DbJ\HXV^VPPHVN`FPNN`\T\HNHVHXJZLXVVP\V^ZXZZ\RHR\PZXHH^bTJPVZZNRJ\b`RPTNRHNXXPLfRVP`XRfT\D^^^HRb^HT\JPPRVNVVVVbPVT^TTPRTLVXZDXLT@TVZPbVdNl>\\NXV`V\ZXNXNLfZ\PRZTRNNPZZJJZTZP`RXTLTdJPZRLXVTVNZTRTT\`\\JPPX`RP^PVZNRNNT`ZLRVZTXNXRZ\X\PbVV^`HRHZVZ`X^H\PTRRLd^PbRVXR`VP\^TbXR\VH^>ZZVNbPLRZXDL^TXVLTTndbN^`VVV`ZRNR\X\\TLNVDXPNJPZLXF\JXNJZHZHRTTPV\PNZdVZXXXJ^FLPT\H\PXZTH\HRXVPXTP`LHRZTLLRXZX^RPdRT`T^TPVL\HFPJZHfTDTP`XXZT\DF`N^PLHHX^FTLLZRRHDLNdNPdJTZfJN^8\HJJNXTfN>`PNPPHB`NRZXZPJPDJdXJPV\VV\RVRZLJd>VXXV\`LPRVRPLXVNXX\R\PZRRPHRXTPPHLDDf`bV\XVP\J\HT\X`RTTXRNFV\HbRZZRPPR:Z\XXbHH`RdR`^\FZRX`ZRTbNdZRLXXXXXXPZ^RNJTL\NR\RRZTL\JP`4d\DZRRZLR\LZZTTTRXLV`NN V T X dP X T d X P T T J \ N X H L D H T ^ X L R R L P D R X T N V N \ T T V X T d N d V J R b N Z X J ` X L R X R R V P R \ V R X N R J Z \ X T h P T ^ D P T \ Z V R B T R h N ^ \ X Z Z L T b T d V Z T T P R H F Z P R T P P R  T Z N H N ZDRP \ X`LPL HN `P\Z\XV\NH^PLJZHTJXVbPXJTJ^VbRXRLP^L\PNZ^DPNZ^`XZLJZZRZ\HdJNTXb\NfP`Fb`VR^ZXJb^XL\RLXTVP^@\RJVFR\HZ\NXVBPDZVJ<P`PXbXR`@R^H^T^`JTXZfZV\ZTV`ZVNTXbPHLZXLZTPBNVTLXXPP^P<J`V\bDXHXXNDLD\HRbNLZJRXRD`TRZT\jPJT^P\JTV<VT>`J^\`XVXZNlJXD\hD^`J\`HVP\JJPPNX\\NFVRXZT\VPVZLPHbZh\VVRZVV^XZbLZXPPXLj^PN\LN^^X`TZTZLVN^@^^F\PXVZ`\ZbXXdVHfZZfN^HFT<bVHf`VTX\\RVfHVTbJbZ`b^X^`VFZZRV`PRLJT\RRNDVN^NRb^\RXDV\PT`Xb^VZJBRH\ZNVPZZXNN\NTVZT^LLHZ\bXTTHXF^TFZZJTJ`RTRRdPTZhHVLrRJR>RRdJPRRbJXRDdJJVBPXTTRP^L`RXXLRbdZFZRL\L^R\TbNLXTN^NR>^TNV^XNfPXNRVNTZTVPTTHBLTVNX\JZb`J^bXR`@`VH\Z`RJPRdR\PHJPbTLR\FV`XHLNVV^JXTVZXPZZVXVVZTV\`RR@ZLTXFJdRHLZFRfRRPJRXHXVJPJTR^XL^LT\LZP^RVh\PZ^ZPZRJRX`DXF^@RbTbL`\R`TPZZTVV\V J R Z J X X Z R @ V T R R X R B H Z J V P R V H N L L N f F R P L P X X T \ L T T T V b T L R V \ F P ` D H f Z N Z X ` P X B T H T ^ \ \ ` L Z ^ Z Z V J \ V Z ^ N Z R N B ` V ^ H P P T d < P X b X V \ L \ ^ ` V \ b T V F D P V \ R ` T T Z Z L \ J T P J T RL N R X ^R NP:X T\ P Tj\VVFZHRNP\DR^\`VLRXRPBZTRPTTT`X^TTP`FL^dRXVVNXRJRbNNVPJXZV@TPbZHZ`JPZV\TJXZ`RPHNNVLXH^NVNT\LLNPTPRTDVLRRT\^D>LPd@dJBT^bXXLJTZPRbJRFdRZVTZHJPXX^RJVVJJNRVLJLVTXbX\BTLTLLX`L`X\PXTV^bTPZdTXPjNLNVbBNXZfPLb@fVPbZZZVRF\LZ\LZ^ZRXHNJL^ZPVXXXVPV`XPVXRfXR`ZZBPPDHPXNffRZTN`XRTTbL\XTX^NX\THXPdXfPLZh`NDHR`V^fRfvZZPVlXRPTX`RPFFPD\FV\@BbVXTPVV\^VVTVT\T^^ZXP^F`BZPTVPTJ`fJ\bFTR\PTZZ`RTXPTRdTVTDRRdZN\f`^T^ZdZZJRTVZT^NTH`XPLVNHV\bJXdTXPVLLPH^^ZZRZNRLX`XBRd^XVR`VRVZHNXRXRTNDXfPVXfR`RJTNXVBX>TTX^FbDfNPTXLVNjdLP^JXbT^X`\NHTJTNVTRPLT^LRTXPXNdNPRX`PR`NZJPVhNJLZNVTRPJ\XPFD`BB`RZVRVV\V^R`bRVNJN\@V\^PRTZXV\PRNZJRV`JLZBV\N\NTZLXR`DRfdJ\dfBPHRX^TZVLXRfRTNTZNXP^L`HX^TZPZdVV`^^TPN\dJVVZD^RVFT`XXJPT\TRXR^T^^JR`DVFVPJTNP` ^Z T Z L T R ^ X P V X V X P T T P R V \ L X P V N Z P ^ R T J X ` P Z T Z T T Z T V Z X \ X F ` P \ P Z V H Z ` L T P L X < b T B N N D \ ` H P T L \ R ^ \ T L l ` N L X V X N T D V P \ ^ X ` N ^ V ^ T B Z ` X P R R X V ` B h V R \ X R H V V P P T Z V ZNZ^J\\T\FTV TLbL^HTVJ VnDbRTZb@^HLLHTTRVPRZFZZV^TFTNXR^VX^`TLJTHF`P`XNHXRPFHRLVPXTTNV\TTTNTFHN^RPVLH^^JfXLNP\R^RPXNZJ`F`RRR^T`XTB^HRFTHFXRPX\VJ^Nb^NNVZ\X`b^XPLRHdPPTRHJ^RXTXZ\BFXXT`RZXRVV\Z^J`J^@PNVXZNR^j\PNZZP\Z`NN@`T`PZ^PTJfXPTZldbDLX`\VRLbRlPNPHV`VRbV^N^RPN^HX\\XVZTZZXVZBVV^`RLVZFTdZ^TTTVb`\RhV^ZRX`\XTjfZVV`V`XTNXF^`\\R\^b^PXV^`N\TLPT\PP^FVLDFLFVNZHTTLZ^@ZPPL^NN^`\T\ZT^\fZRFRTRZ\LR`VPfTJPH>\VVPZ`V@^NVPTPVBZVTNd\V\FLXTJVXT\\TX\^>TPXLTXbPXHVZFbVTX\^ZLRBP\RXNTjP@TLPPL`XVTVVV\\\NHZJVZV^J\ZdLXR^XHTRZP^HXN\F\BLTT``LXRR2XNF>RXXNHRTNZVR^J^ZRPH^X\JLX\Z\\X\JPL`F`VJXZT^`VZBLRPV6\TRbXXXJXLRPZZJVLX@VLXJJN^XRJR^PFHXZDfZZP`RXRRbZN^<PTbDV\RRFJbVTNLTNX`PhXZLVHT\LHPVVbPFd\PRNPT`VN^FXRfJJTVhVL`J@VV`T\\BLPJXVPTVV`d\ `PTF\ VBP d ^ T R \ T h L b ` H H \ P X X X \ L V J  N T R N @ H T L Z T \ ^ ^  d J Z ` T F D Z H D f V P R L X V D ^ J \ ^ Z J V V P X V Z X \ T P ^ V H N P V N V X Z F H B T N T V X V P B Z T R T V R J P \ Z J L Z N b P ^ N TV Z H J T V B P D V R V d V Z J T P XXd^XRRZJ^NTNTLLZbJP\PTNLVD^PLVR\J`P\N\VTB`F^RXFXR\HZZXZHVZZDRbRPNJ\PZPXVXNN^NVVVXHNNVTV\H\\LPXN\V^ZVPN`VP\R^lRdRHb@NXfT\\PLPZ\BX\RNRRZTHPH`VFV`VNNZHNRR^TJRPZTDN`PFRPLVZVNN`X`fJZ^RBZ@TV^T\ZZPRXbbTNBR\L\^JTZL6TZFbLNTV`DRTVPDVNJZD^RPL^NRD^FZP`JVVLZL`PbBXZbTTNZNV^TTbPXVPbX\F^PTNPjZJPVTZd<ZTVPXNZVXJVTR\Z\LTNLT\Db^nVDVXRPb\hbFZXXTFR\ZLTZLRNNRXNTDVTVNT<XPP\`^R<h\d\NX`fjRdTTXRRZXLf\XTFHN^`PBdRT^P\^dZLfRXVZVF\ZXPRTTNX\\DXVN@ZXJ\TT\@jJRHbTP`HPdLPPbP\XV`NTTLPRVXRRZVVddJR^FPbRZRX\RTPZVVRTPNT`NNhZJZR@NXVLRd`\R`^ZDXXTT>R`ZTdD\R`VJJnHPVXf\PNfN`VFRJ\TV^RJZ\VXPPTPPR@X\HRRVN\T^VfZRhTNVRRHR\NPLT@ND\NRRNTfJLLbXdhXZ:RXLJXX@ZTLP@PNJ^XRNdVX^TX\ZZ\\`JVVR\V4ZbVTL^@ZJ\V^XHJZPVVZ`Z@\ZTfhRbLTHZLLRZHd^\L`PNTRd@VRP`XRbLL\Zh `XR L N  Z J Z R L H  N V P N D  Z V J > Z \ J T T @ R Z b h D V L h > R < Z Z X V R P H T P ` H T b J Z P Z T H T L B R R P T X X Z R f J Z X P f ^ J J R d V N @ f T X V J L R ` T P N R V P X ^ V X V J F \ X X P Z D f D R  V R X X X V V @ R X`VbP T X  X R L\ZVNVVDHTLL4\NXNVZNVbZZJbZVTV\bR<RTZ\L^TZbHXTNZZP@N\XfTT^>XTRZJRXVRjVXN\JZN\VNJ^d\L`\\LNHPNTXRNZN\RJRBLXLXVd^LR^N\X^ZNfN\PXTRZH\VHHfbLT\X`\P^Tb^XL\^RN\XTN\`XLTV`V^RX\VPbX\D`RTZVVPPjLNTTVVPbNdTdTRPPXZVH`VbXVXLV>RJXVXR^\V^PN\PVPXLbNdR`NTP\bJ^\PbTLJRJ`THV\XXR^bR`VTLP`jHXL^Pb\\PbNPVRh\^\ZPb\TH\^VTXLP^VZZTRXLdDNL`^PZZNPJVNPL\NT>J`FhRV^hVR^dZ^RRLT`JDXJV\LRVTbR\PTV@RRPZLPJdd\HJV\``^ZF\ZVX`PZTNNHR\VVlRhVNZbVLPVN\^JP\\\\ZLNZB^XPDPNL\fb\RVTTXR\PNTZPR@XVN@ZLRPTZVTFXT`LNVJJPVbbDL\RJLPJXNNddD\BJP\XP^HZBVTLPVXV^\DRL\`\XJVP`RNdHLNXBDXTLVVRRXB^THhRVJPNfRR@bTJ`PRTPfJRXBHRPHZZP`RHXTXPPXTJPVTNdPVX\PBVTZX\\VXLDLT0HXRB^X`T`RPNLNZRVJD:XR\VZRNRTJTNJRRLLNBVNb\TXLPJVNVX^LZPbR^f\VNDFTPVZ`\XRLR\LNLPFLJR`\VLTRVPVLXZRZNVTN\PVXLTTVXTPfRDVVTN TNTT ^ J  N h P P  J V P \ D  b H ^ F P X N P P @ ` X > ^ J X T D R Z V T H N V N ` L T T ^ R V V T F Z H ` P T R P V D Z N b X T d b T N V V F N H T J L T ^ F N Z P T Z B \ V \ Z V T J \ Z T 8 : ` J P R X Z Z J R R  VLXLd\DD^DFVPNXV\TJNV\ZPFZHJJXVVfLTVZRD\VRL`TX^dRDRdNXTNLXRTJRZdV^HJbFNF^^VfHPN\TNVZXRJHJR\XTRJ\V^RJPTPTPLR`HRRTFXdXT^RXZRPLRBLX^TfR`L^PbTLFXP^RXN^XNP\LTHVLVD\NZJXPX\VZNVZZJTN@R\V`\VNP`NPXfdb`VZX^PXTRV^fNTLNTXZVTN``RXJTNPZLTRXRZ^F^RFZdTPN\LPLZFdVTTVXRDZTj\T\LP\X\TJRRRR`VZNZVLVPTTJZTHJ<XRVVVL\R\HRZPPTVPJX`LP@TThR>R\BLZ`X<VXZTZDNPTV^fTNVNTZ\TRTLZXLZPVXXfPPLP^ZDVdNXb`VNNV^XNTHdR\RRbHJPZTTJVV\TXVXRJLVZVH^XXP\J^XRZVhTnVRBR\LXV`V\JXTZR`V\^>XT\\TJ\T\HV`XRPfNfDZ\NX^TTN`TNVfT^TTXPN\JRbdF^TVTRFjDdZR`T\VXPT@HVXRRR^XVZZRXbPJ`^TBPNXb\d\\ZP^LP^ZPNd\NZ\TNJHbPVNNRLTTJTNJLPRXZPRbHV``\ZXZbhZVJ\VHP`VTPZNJJ^HTRTXTZHRFVNHNR\JL`JRPZNVHNTZbNZVVVVLXTRFdNXVTZTR\ZXXTXDZRVNNVTP\^JP`<XPRL:XTXP `Z:V D R b P f R Z V  R T d J R VX B  \ J Z TR DL \ N V X J P  ^ X N  < J P ^ F Z X N R L Z L T J P Z Z X Z Z N P J N T R H N Z L B @ \ X ` R T X Z R ^ ^ R R F b J V R ^ F P P T b L R N ` R J T N ` H H V  L R X T J ` \   Z X X PR\dDRR`^\ZN\VDJXNV\L\\NNT\V^DRNV^XXXZLXFVNNNLXFTTPP\\PR`RZ\P\ZJNJZFB\ThHZV\\DLFTXLZNL\VlTPPL^X\H`LPRTJT`ZXPZVTTFTRX^BRPP\RV6TZNLPPDPNTJNRZRXX<^PXP^LRZZVJL`^T`NXNFVP\RXRTHRNb\ZNNZVPVb`\PVRVNTTLXXTNHRR`VPNTVLDXTddNXTV\XRH\VFdL\PXPTZ^Ph\V^^ZPNVTZRRfX^FXXZPZNHf\XZNJFNNVPXbLTTNZL^VFL`XNdZZRFhPLFVV`NJ\HbTVNR\PX^NNHFX^PLPNXLJLFT@NVBT`Z\hRPD`P^JXB\TTVRPXVJRTTNFVTNRZLNJRN^^^PRRV`bDPRLZTPPTXd^bbXXR^>ZL\XL^T`PdN\ZLXJRJPLTNVRfXHNVJPVPPNLVJXJ>V`XVRVNRNHPhRVV\`X@`P`NbLVbRVJTRVJVVNR\NZF\XNP^PF\XPJZP^RJT`VTdbBXPRP^RLXRLNB\\VRTHNZ\ZR\NVJPRZVV\PZLZNPZPDXHTZJXT\J\ZRR^BVXXPPVXXNR^TPX\XVZN^XL\JRHNZbbPJPP^F`JZLVZVPNPF\ZLVfV\NJTZPZPNRRLXZLTVV@LTVJTLJRXV^H\ZZ^NHLZ^XdX\\RHVV>L\\ZLPP\hPjPRZPVNVNT`NPdHXP\RVPXRFXXXXD PN^ ^ N X J V  H  J V   N  DT J R T N  H B bH T Zf < R  T ^ J ZN D `  R B ` N X X N J Z T T N Z N P P Z T \ ^ H ` R R R ` V \ H b T D L J ^ T R Z ` R H R b L b Z P T P L V N T R X R X H V V N N  J L \ ZN Z H Z TT PLNLXNNP\JLPbTN`\HVJPZRTT^PRP`JL\RBLNPT<TNLL^V^NT\J\\XPTXJZh\RRZHV^^ZbVL^LPZF\TRJ^P\NVTTR`>NR^VXRLDLj\T`PVV>R>TZTTTR\TFVPJDB>fLZJVBVT^LZZFTZZRRTZRJV^FZL^`ZVJJRZBRTdPZNPLVRVbPRX\TTTFbF\FJffNXPTVVJ^HTRFbJ\JXNdDXNRXPf^ZLNR\nL\^TZPLL:VRZPLRR^^^JV^RJZN^VdRXNXR\\PVVVXPXR\XXXVXJZJPJTTP\XTXZLRT^TT\R\RPHNdRZX^fRZ^ZHdJRbRLZVVVNZR^ZbfRNPTFdZTZZTRLLLVVNTRX\VTXHVXRXTP^F\D\BVPVV^JPNZ^``TJbXFf\ZX\VT`TRZHJbNZXJNVV^^PVJNHBXPNZJdZNPT\PLVPPJbXRT\HRbLLHX\TTZP@^NR\ZPPNT\RZZHXT\R\NXJTTXRZZZLVJZLVbTRNTVPJ`PHF`NVNV@NbXPRRZ\N^VZTLFJVPVNVPN^NVTVFVNFV\RVJRXJL\D@ZHVX^H`RN\DNXXXNVbL^N`ZTXZ`RRVTTPNVN`dJfDRZTRNLTZTPJbVRB\\JdN^LFVPNVXVLVT^TXTN`NRLPRV8XXX\FVV>RHDXVRFLZVdLFL`XV\<``V\Tl^ZZHZBPXPHLPLPX@PXVZNXLRHPNX:RZdV^FHTLNHRNbVPLTVLJLLFZXLFb\> N\ VL X Z R V P T RB^V  P@ Z N V PP TdH>VH R `V H Z X H PX N T ^ N X ` ^ V R L R V Z T d ^  ^ ` b Z T R T P \ ` P T \ P N X d Z J V X X N P T D V Z X R b ^ ^ L N V Z X V XR  R  JX\JN RLV JPPR\XRVZTPVP^TH^^VVFVRT^JTXL\NXRRJTRbP\LN^\V^XTTLbPVVXHNNTNN`PjJLT\PRF\JXLXTThfbJBTHT^`JLNXLdNVXTTTLZHbTPHXVJRNZZPjRRTH^TVfRR`VT^PJV\NTRNVPb\jTPJT^RXTRZX>\XZPFT^TfRVTV\ZBZ^TLNbdN`\VXRPBJ^L^\RPPZRFTL^@^DRR>P\JLPLV^PZN>JTXZRRJHZPV\ZXP^LVPPT^TTdL^RPTTXNV\VbjXN\R\XRbVDPVbZTPJFNTVRVXZ\hVHFRTP`Z^TZVVZPZVTdPT\PXLLT^TN\\RLTRXZXVHRdPXRPVF^T@^LFTbZ``dZVRZJh^\ZXXTdVTVX\NN<^JZRTPJRXTZRTT^@PJR`LPRXTDXRbNZXN^NRlRPN\^TXJVLTXRRV^fBdXTTHTJNdN^XTNTbZ^JbdJ\VJX\VP`TNTZRXJ\NXPZPTPHVJTNR^LTLHL^VNRDPDXPbXP\LhVJTRR\`Z`TVHVTXR`VPT2FXRNPNVNBTRdR`TLTJLRLPNRZJ^\RZXNJHRLBJXXJVbPHLPP8^VXRHRP``XZNFNdZPTZRBTRVJ^LXHTRNBTJXTJLZ`JRZXTXRVXHHLZNld:TJHZV0L\JRTVPR`RXLfZXRZ^^JXHPTRFXLNVXDVRbdNTRT\RPVNLXPVTFFLP\TLP R\N PX  TR Z DN D N Z H   LV HJVPXNR `V HJN R JP> \TR LX X N LRR J bN J H L P L N \  P L X ^ T ` d V R N ^ F N h H V  V H X f H R L H H V L \ \ P T F b \ T V J Z J` ZJVL X V HX `TJV NRbVRHVPFPNLPbNRRN\VP^TJJNPNTVLRXPZ>R@TX^6TRNLH`JX\\RLPPJdPX^LZXJRP\T\\XT\^VTZPX`X`dDHJTXVRN`JDTLJ\bJZPXJR^XH`TFPbF\TNR\DZHNTZZZ^dNTXHZXV^`^HTNPdF^RVbXTRRTbDZbNbFTJ\bRXVbTXD\L`P\^\LbHR^NdTT^bPhPZNRXTJVL^JjX\JVJV^HTZLXN\XPRV\NPZNZPfZXbVRXVTTN^TL\RN^VTX^HXJRTRX^P`LJLR^\FbJXVJL`LhRRJRf^`^P\VNN`PHRX<^HX`VVV\NNX^bTNVVP^T^RJ\\PHPNhXZL\\XTHRFJ^HRZTVXFZ`\\XZFTTXT\FXVH^ZPV^fXRPPPRR\^^XNVLNXZTVX`LTPb`RTVFXNJ\VPZRTVLPPTPF`^X``RRXdF\VZbN^JFVTVfLTb\XX\JVP^\\LXfZLfXNRZVHbPRTXRTbPNNHVV\NVZVDVVX^JXVJR`TPXZ\LNPD^NNbZRLTb`F\FVJFdXTbdRZH>VXBZTXJJJRTPLZ<RJT^PXLJXZ^\LNHZPdPZhVJ\FHXX^HP`PNXdJTTRL\dbRPTV\XPRXPNNVLJPPXRTVRDRPX^RH@VJ\Nb>JNRDVdbHBfLXTNF\\L\VRRHL8JTX^T\DLN`LH\VXNNPXHTTTP\XjZRTLV>PFZTDTJ^NPPP@ZXRR^^\ZHXX<V\JZLTVZZRN^NJXRNTNTZ^LNXPRVNNVJPPVdLTbN\ XP  NhV` JJPF^ J^R FPJh\X\NRb `F ^V D \ DX NRRL PRR PB^DLD Z dXZ P T V ^ R T Z  R P P \ B Z V X ^ d J P  B T P X X P V B ` VT F V J H X \f BL ` B b ZJJ V ZVL\ Z NH`BX LBX\D V BZXRXbDVPRPRJNRVV\ZPLZNRZFZDhHRPVTJTHXLPHRN`NVVZXNRFRTRXVVLbRTXJVPN`RbHZVZTNf\TZbFPbNNLZDZFNR<ZTL^TbVZNTLRbJTXX^NX^ZP\XPZHPNLVb^HXTNJL\TVTTNXDLX^TVL\FVJPXJdZVfVN\LN<RRTTHTThNZXLXPZVVdNP`ZZX`RTNRXTZNHTXBZ@VJXX`TX^\NPHV^VXZXRRRZdXXLJVTLXTVZ\@L`L^^XJb`fLJPX\JfVTZRRHNX\J`XL0XJZTL8XLNZP`XRNhZTF\HPhZXXHJ`dNN\P^XbZNZ`P^XFZV\NTXhR\\HdRVJ`RJVNbR^bJL^nTZVfV\\LXNb^PHPZP^JTbLLNVLNVPVP@PZTNTRVRV\TZdfTbTPPR^N\R\TFZZD`PRRNVRLJV^PNV\HVfTRTd<bXHTdFTfTbHPZPXL\NFVRJb\ZDTTTbRZPXPTPZ^HZZ\T^HRZRTPRRLXT\PLVVTfHRX\dNVZTVdX\^N`J^d`^LZRhN^HTJPVFhP`LXbBRTPBR\PNZNVDVRZVNHNP\VXNLXdDL\`Z\DTV\NVRR`XFPbZX^T^PTT\XXdRVDLDNVPPTZRH^f:RNHVJNNXP\T^hLHTTLZVRH^PFJZVFVVdXZXLNLPLTPPNTJ\V`NFT\XTV\H\VL\TFZN\V\J\^BR^ NNTTBV\ ^RLZ XHZXJ RZDT\bV NhXNFT TDZH DJVL^`NdR NZFVZT@\ bPR ZT^ > R N N \ F L: ^ N  \ R   P R Z H L N R ` Nb> @ X  VbJBF H^ ` V>XNP^X XXZVPPd\JZVLTRJDRZ`TTZRFXNPFRZFNZDBPHVJ^dVPH\NRTXNNVPT^XFR>^@NP^FFDT\\PPTRJ^NJVJJFVdRR^L\H^ZP\XBJD^THPZRVDZVTLLDFLVXZNDLNZT\JTRXJZN4ZXdRXPTXZRd`\HPHNLTPPJT^XLHN`HZZJ`^RbZLXPbH^XTXTXPNNHT>^PPZT\RXhV\RDd@JXTF`Z\RV\L\T^TPXV\\VZXR\HTLN^DHDVXLNNRXPVRZTZ^VNXXf@`BN\\\VVTT^NPBhTbLPHFV`bXXXX\NJZZRHV^P\JP`LXRRVdZ\Xb^bV`P^DbNZZ@>XDX^LXTJPbFTHVRT^F^b\\ZdTZ:Z@L^TLJNb@RHbPLLLV^TRXTf\BTHRFRRXVZPP`HZTRXVDNNFJdR\dXRNNXdN\J^XbVV\VRZR^ZHBB\VVZRPX>VVdXN^P^TZN`BXRFRLLXVVNV`:RZVHXX\TNPfHNNRXVBTNXNTJNPFP\HRTNPTFTVZP>RNTR\TTLTLXTLT^\^TRJLTXJNZ\H\DXTfPXRjXJLXXXNHTTPXVX^XRLZH\ZXJV\\XTVZXV`RZ\PZVF`TTNTTV>VH^LRV\^\L\TN`RLLN^`BfPRXXTHPfNXVXVHVNNHXXDZNTTd^bH^(R^`VPVV\DVRFPVV\TJ\J^bLHPNTNdXDT^VNX`DXRJXRJZX^^dPTVRNTZNVHLJXDbPNZLPPVTPJNXTVDPTTPVRTXF`PTdF^TJBZ^T`RP^V\\RRR`HZLJFJRR N B N \RNXR@TP  L X^ P bX D X\ N   T  T H X Z XDX LN X T NLHPZ <V NLPFRTNT@dVFNZTTRFPTJNDZJRPZFXfjRHJ`BRTPdRNTFLPP`BZZTLZZTP`VVLTVVZNRNVD\NJb`PTZHHVN^^NdJRbH^RPNRXJXBXXFPNPdXVLTJ`T`RF\FPJVNTNZNPFXLX^R\HRPDNRLNPLPPHHPZDRXTZHd<RVZ\X\HVNTZLNV^`XNVZXlDZNLV`HXHdRHTJTJZf^RXbZ\R\RXZ\LT`hLJ^DVZRhNBdPVRTJ\RVNTXZPR`V`XTLLR\ZV^TNZH`VVR\TR^NPbTFX\`RR\RTVDV^L8RJLR^VXPFPXXVP\XTRRVTVPNZDfPNTXT^bXTRLZ``JZZTbT`XNdNLVZHZVLd`XfXP^HZNT\bLLZZJVRP\Pn^Xb`D\`ZVVL\ZRLdLV<LXTHPRPX\ZHPFJ\d`JP^ZXVZ\RNLZRZTPTHN\dLXL^`RTTR\RbbZNTNNRdXL^D^^\JV\\PRR`T^LXR`XZD`LZTR^bZV@T^XLJfJNTL\NXRRNTTVRNNTNNTZNHBHL\@TVNNXTF\L^LZT:V^LTVDVbX:XFPNPVVH\RD\TRThLRLXTVVVRNdP^ZB\ZRD\XLXRHLTNHXVRZVT8dX<bPRPZJPNVRVNZXDTZJ^L>hVPDLbRPPF|`8NdHNHbRXZVNHZL`>ZNLT`XTDJP`Jp\ZbXF\PJF`HLXXZPRR\LPN\PNNV`VHT\PJ^\ZTTXTdPX`Z`PNPT\FZ\RVR^HTRRT\FZLNLN`\NNPLNJNZTTP\VNXRPRVPPR^V\TNLRPV\ \^ZLFZJH RTRHN @ P`` J TXXV L X^ HNFTH^^XTVZJNR VJP VP\NX@RFPFTJPBFVJRTFZJTPT>RHTZ>@JdVJTNVZZJHL:H^VXNRL@TJ^TZXVVX^LL`VHXVLZT^NdVHTHRPRVVbNLPXVRdTD^ZT\PJT\VJ^FXZJJR\TPVXJV`HR\VPVN\XF`^NTT\JTLJPVJ\NN\HTXTZL`R^V`PJV`hVDXDTXRTLHNJLJPHdhVdX`FVBZV\fP\Pb\NNVZXZLVB\PbTTPZFTNRXXL\\<dV^RPFRRV`XZRPZVTbRN`BZbNTjNTL^NVXRbTPZXPF\P\^T^TX\^P^PLR^`TdV@RNZ\T^VXd^bZL^NdLRL\ZPL\TLJFTVJ^R\`RRFVRNfVZXPLZPZHHXHVNLV`XVdLLdN\VT\HZZ`LDVBZNVFVPDh\ZDX`^BZ^JZ\`\TT\RXfNf^\VHVP^XLBZLR`V@\T^F\XVP^`HFTTZVDdP`VV\VR`RZVRVRXRJTPXTZTR`Vh@\VV`L^b\b`R>P`TXfRT\t\dNdTb\\f^X\bVPn@`\XJP\ZhR\RVJlFTVPR\FZNRPVZ\HN^FVV`L@HVNVVXV\VV@XNPNTL\PTNb`T\TDTVhNL`XZPJVXZJZ`NbRZHTTRPLXZTXNZLVHP`bRXR^PLZZTTZLRbPJ^\HRdXZR\HXHXRXLRbLZ^TVFTjbJ\HN`TRB^NLbX\TLVT@VT^ZZLT\dFVRP\HTXR^NHZL\JRP`PTVD^^XPV\LZPVH^PT:RHRTVRFVVJPPRD\HFRH \PLNTFJJ^PVVN^JTTJRTTTR^RFZbTJL fPV ^H ` NTdbVP TV> NTP f\PJ^N ^LZFNVP^VdRX^Hf\JbDZ`JXTVXZX^^JPHLRX^HNXPHTNRXL^NP@XRZPlJTR\Z^b`\N^Z^ZPNVP^PVVTNHZTTXRZT`V@XV>VZVhdVT`ZFRDHPXXZZHVZV\LVXTXNVRRP\PVXVPTRTVZ`ZTTVTRLZVPXJ\ZVTZZTP^JL\XP^J^^RXHbNT^XTJ`ZdL`V@^B8VLPPJdNFd\bR^LRfDZ@NZTZTNZNVZHRXXDN\NFVV^PXR``VP^TTBVLXPHbXH`PVTLV\Z^NZRX`RV\P^P`h^PNhRbN`XXdT\VFRLTLZB\XV\XJNZJV\\PPTTVPVN^bVLTPZLVXXJ\^Zb`\ZVVRdbNVTRV\RVVZZHXPTbNNLPPLPLT^RLNRZNTdTP>\V\bLZ^`\J\b^XPZB\\`PJZPhJTTNPPVJXXN`L@VLNXZ^PRHVZX\VZJPHL8PNPVZRTZN^RXVTHRHPVTTbZLXRXTJVZZRRJbHV`J\\JLb\HL`RTXfLLVLL\j8TR^HZRJXHZH<XL\TF@Z^HPHbN\JVRNTNVTZTVPZF\P@BVTP\DPXXV^PXX\PXVPFHJZRj$HZX`F^TjHB\XPP\\HZ^PVRLBFZXVHPPH^Zb<D\V`R`VLP\ZNZP`TVHRDJXXbTRZTZLbFJZXLVVXFXLT`THXhP\LTFZLVTLRZLLV^VNNTNPTLX`VTNLVXFX8V^ZPPNR^TV@bVJ^\PVRD^XXFNRXJ\XPTNR^RZPTVDDbLLZZDZFRZTL HP`TZZVJDZXH>VHRPX`ZVbFXTR VVBNX^Z VTTT`Pb\V XHTVNHJhL@V\h`RXZHbNFfNTVZFbXRZLPZJVLTHXZTTLXLHVZN\RRXVLTJLTVZbHT\XfNHVfTJRPNJDVTPN`RNVLR^XRJ`T`LdRZRLPNXXVTVNVVR^`LXHFV`L\TZZLL^X\VV\VLJ^XRRLTRBZJTrXTTbP\NTVTLJXPL^JJjJTbFJT^L\ZfDRLZ\XNNRT\RNRXRZPX`TZV\NVBHRVFRTL^:DPZVB^@NXJ\N\^PXHPX`\ZXLV\VRTTdVVRR\LZHRdJVVRRL`RbRR`TTRXBVRNRJXFRRRZJhZX^XfVNXN`TR^T`TV`VDFPX`XJHZRTbRXhRRV`d\^L`RXHZT^bP\\\V\XRXPRbNR`HNN\VVVX`VVZPRLNP\HDRVH\B^<TTbN\`ZX`VX^P^`V^HXRZ\bTdXT^V`RZXHDNZRPXXR`\VR\Pb\RJdXPPfbXLN\\LXVLTRJTTPXPVTNRFPTZZ\BVVBZXX^L^N\TbTTVNVZVPHNZJTTTXZVB`JVTRVT^T`X`ZTPVfL^NZFPTZVHDBZ^RVZDTZT\TB^\XPXZ\NXVVL^VVPP\DPRPbTX\XVL`TZFjVXRV`TF^NT^PRLJZTP^VP^VRXVLfLXTVXTN\^rLV^TdNVVX\T^BPTVTXLBRRRVNXTbTF`X^JRDTNXHVHZT\RX\HRX`HVPJTL`HLDfNPV^NZRLR\HJJ\VR\F\TVFbLNDN^VRR\JRbPPPRV`XPLFRTZ^\PNBNPZbVDN\VNH\VLbPBZLZPZHZVNPTJFJJJPH<FDJJXPN`N\h:VRHTNNdNTJVDNXVNJP\LDX`RNPPPTZTbHVDRF NLXLX6JZHVZP HZ^`LRZTBXBPVJbLZJ\LDPX^LPZ^ZDZbZXXZRTNZ^TXTP\PdTLJ\RNXX^NXTNDXT\\PHRZLPTTTLHZTHVFb\F`RJNDT\\X<^TTVZfZ^LTRbbVLR\TTP`P`LJb\RN`P^PPTRH\XVXFNNPRTPbRXVNZXV^N\PVJP\X\ZVNBPRRHTZhVXRTLb`ZXZZTRNdVJTdZBJ^PL\HXTVVHT^VLJZJJHF^\VHL``NVXXNTNT`PXLXLPX:TRLPRLXJPX`PTXLTNX\PX\PPNXNPHNVdVP^XLZVNf``VTPJT`NPLPJP`R\^^\TNZ^fV`ThRPN^^VRZPJZV\HRRTL^HnX\T`NJJbXT\VPX^TPZXRLjVV^Xl`RVTZRRFXXPhRRP`J\FVP^F@RTLfV^PN`bNZnZVZRdPP^JXXRRZR\TZbTJ4PnXXFJ`\\V\XRPLZHZRLV^L^PXTTVRNX\\VTZLVXL\`hDRT\ZPXbF^VDJRFFTTTd^NRfV^ZJ`ffPDNVRVZRbZfNT@ZPNV^JX\TRXZTLHZTTZZTRPHJLXLJJJRZNXXLVRPRV^VFZNLJJTR\X^TTTNVPPRVNZJ\dXNZNJB`fJ\N`BD\HNXTfRHdR\XTPRRPPHVF\R^R^ZRHZTJX`VJLPPJL\VRHNN`R^RJVPLJPJJVZLVPVTZ`PRRVLLZZRdZVZTJTBRRTP\R:PLLHTH``P`T^dVZRTXNVH`PHNJLVFZHN\HXTRRZXV^XDBRF^\XTNNPPVRR`VJNRVTNhNPVZXXRZHPTTRZPVZVRTDZd>VT\VH\ZZRTVVX^``XVZVLV`T\RNTF^LXRbDRZDRH\LRRTPZZX\TdTBH`VRdJTXXJ^\dRVTVVXVL^PV6<`\ZZL\XVPTXVTXLR\TZPJV^VFVVRNBLNVHRJTDVNTT@TLRNNXJDJHTNR``TR\ZLFHRT`PZNRLXVZ\ZNdR\PLZd`ZPVRNFH`ZRPL^NHXJPBT`JF0NTNNNHN^dHV^BVVbX^DVfVVR@VH\HHTPR^LVTVT\XRRRV\\ZRTPfBVXPRL^ZZ<LVZNH\PZZXLPPX\`LRVXN\RLNdDX\RRdTTbT^HXVVFPJRZZRTfbVT\b@ZZRXVPTXbXPTXZH\FdNRXPdTdTXV<\N\XfZTNZXPJ^^LLLRPRJVfXRVNPZ\RXPT`VZPdV^RfhRXVXTf\^VXVZTVTVZTF``fTLLXZNV`ZZZDZPdRbVRTFVbPJ^f`\Z^RVLV\\PDZRL^2HPPDNZZVfdd^BTPZNVN\\LNVXXJNPX^R\HRZRVhBJVJZ\d\NRRT\THRRbVTTdXPHTHTJVFJTNVP`VRDRPLZNXZR^JZJ\^TXZT^HZZNLJNF\JDLPRZHNV^L^NLFN\RX^R\PNND^FdHZFTDNZ^HLZLJDDH^RJRZF^T\J`ZTP\bLPP2XLPdPP^JJPXTVVZ`FRLRRVTH\JX\RXXNFVXXXRXRLV\RRZVLVPNRLRFBZTRPLRXDZR^R\PTNVTFP^VFXPPT`@RFPHPPPXFX\XXV\T^XPTXPVRVXH`PRNVXFPXPRPT`NhLTPH\PDdLHbXVLJXFPPZZ\NBRXFNLFJRL^^NTFRH\VRTTVNLXNZJRN^HP\XLNZHPH\RDXJ^\PTJRPDPJXR^VLT@RJ>XRZTHZ\XFbT@P^RZJTV\PLRXVZJVJLVZJRDPZXDbJVbHVVH\V\TXHZNFTPXXTJRR\ZVT<L\XZLNbP\\VZ^^^\HRZZH\ZNLP`PRPLPTTLTPXRdJZbPPLZJJ^RNVZJRXHNLTVXPDPfPXRNHhP\XRVNZXVLHRRZV^R^RfPNZ:RTJVRTRNXJZ`JRLNZX^RNHZL\PZ`N\PD<FbTVRXTF\dVTLFVL^TJHTPF^PRbZXJT\H^NdJXVdZjJdV^\PPfJJJPdJbVRH\VPHH`LR`P\\P`PVbXRZXNDLRHNTP\VVVP`HXBTFVPTTLDXZ^RLXVXLLfPL^FbFdDZTHP\@N\HVNRR@bRL\DZTXFfHVLXPTNNVZJFNH<HZ\LL^@VVXLZ\LZPPTTVTLR\^dPhXbLVXTPPbRhdXRJR\T@fTJ^PR\NZdX<VPZRRVRNfRHJLHTTLTFN^\NJZ\L`^`XR\hLZLTbTLXVXTTLJPPbDTZ\LXV\JJVZXZZRRHL\\\XTNdZTPT^Z\NjTbTNfZPV^Z\Z`PLXTTPXXLVPN\lVZPB\LRfZbX^XVRZRb\N^TNHLBRXRVPTNXXTRJZTXZ`XXRbLVHZN\XVLRLTLZLTNJV\@J^VNPbFRX\VDX^TR8NP`DDXPLPRTVJ\<VZNPVXBLJF^\RPbHNNbdVHHTNN^RJTJ`\NBTRRN^RXVLNR\XLZRjR@fPNN\TJ^`LPLdZdH\ZBRHR\RTX\VTVVThVLTR\PXRNfFTNVNb^X^TVNZNZ^\XfBTXNXL\XFV\XDbRRXNZ\T^L>XPZNJZRFNRHXXXZLD>\RTPHTPN\NN6XJPLPVXbX\XRTRFRVJTF`NXRNDbTJRPZJDRZTbXFTRDNV^VHRFXNTPNNX\D^L@\VRFXTNRNHXPPLV8NJ`FNRNVV0T^DNHJHHPV\JPFH`ZHFP^VNLTbdXPLHDP`T@VLD\JXBJJPNNV`ZXNNXLP`V^V\VZRJ^`THJZDb^VRJPHZ\NRH^VRTLX\XT2XHTF`NR\`VLbR>R\H^XJNX>\XP`RZFVFDNHFHVNRN<PTLb\VJ\JZ\^PXP`bP\V`LFDZb`NRT^^fPZTNZVJPTTZRXJ\VZXXNVPXHNNTNXN^PLZZL\JL^X`D\NRT^X>L^TTXTZ`HXhVVXVV`PPVPXVLXF^BbfbTNd\NZ`X\bVR^NXF\RPPJ@d\^RVTZHVV\\VHHTRTDNLJVFHVT^^LXTZLNB`4L\RV`TFhNTV\R`XXXRVLbVLRJ^XTF`FL\fZRZXLZVRHRVd\Tf\bR^TL>TbZLbXRNBV\BTRNJ\DTRZ`VLF^JJRZF^PNXZRPPVN\XHR`\TN\JLR\^ZRbVb\NV^ZRNVTJfRPTZXXZXNbR\^VVbJLLTPBH\XJXL^BBNVVZRXB`hR^FXbV`HPJZfTX^RPNDVPRVPNXRPHRJTXTRPLNTPXBRTR\^XVHZNVD^^^XPN`XNVXbTNNFN^VLXXl\PXNNbPhZVZXLPT\TV^HRLRJRbXVDfdDjV^RZRLZPXTP`^NZZNR@RZRLZPJTTRP\VVb:VXHJ^\JLPPJ\L\NPVDXJdR\8\T^RVFRXbV\VNTdNRVZNZHTD^XHT\NTTTNRXNPF^JNRBH^NH^N^VRVJDVXPRJdTfVLTXZFJRXPX\^^PVRTRT`VJ`RP^4RFVN\JVD>TPPNXjF\VVZPLFTHP^TNHPNLPLTV>Zf`XJVH\L`BLFT\L\@hNBBbRNPbJHZHZTTZ`VNH\NNVXNDRHVXH^PHZVPNhPPdDR`DPXl>RT\JRDRLFHLZLJJZTXLFPN\TVHVTTN^PX\TZLJXPZNXHRVZ\JPXLZ\PNXPPFPPTPbFbXbNJZVZPPLbBLTRVLXTT\VJP@V>^`^`P`XVT\HDL\NXHX^RTPL\NNNPP\NXJDPTbNZP@ZLTHZ^XDHVPdTZVXPVD\JLVX\RDNVLJ`NTZHLN\VVR`PTXXRPL\N\ZVPZHbLLZ^P`P\FPXR\NL\XPJZRbbZP\TTbFL`T^NV>^HX\B\TN^ZDTZJPX`PLZ^R\LXTFLN^TFRJbR^H\L`LNj^TXV\`N^LTXVXPFDTZPZ^ZNNXZVT`NDLXNPZ\LPH^LVZ`NVZ`^X^PhP\PdTPVV\HZPJ\\`DXFZHXLVTDRNPPRRT\`XF\\JPPT`XXPLBLNNNBX@\<\PNXPT\HVLXTHLdN`PbNXVRbF\VRVTFXZRRFZFX\`HbL\ZDNVLVXLJNVV^>VRTTPJP\XZRNHVVRVNR\ZJXP`DVHVPLTPXV\ZRZF`R\TZ\NTH^RDVRZNVJVBV\TZT`\JNXRDTRNRR^NJ\NBPTZRNVR^JHZJ\\XNbH`^LXPDDPZVXBHTVLLRB NBTPbT\LTPNZ`RLPLLJV<XXTRVRVFJJLVTRRLLHP^HPNPRTXNFVLRPPLDXJTPZRN\RRRFN`L\B`HVHLJZRZLVJ^NTVbPdTTPR@\\NVTPbLN\ZbZ^RBJNHRPNLXPPNRZPRNPXDVPbTHLN`TRbTNVV\P\LBRXRNNVRXJPTLdRXXL@THFNXJ^VLTTdTHPVLD:ZRNT^ZXLTbRV^^PJPZh^bJ\XTTP\`RL\LVFNTdJPR^j\RRRRHR\PNXH`FV\bZNNVRLNNVVXLTZ\PRT`FPHXPVV^PNJXXT^JVFVXLNNT\JPXP\LTHPVPZHRTV\ZRTXV\LNRDRRd`L`L\`VZPRXFVZP`ZRNFHRPVPV`RNFXTX\RF^TPT\V\XZZT^HJNJNXVTRPTTXRPVHNRdRT\b`RLbb^BHTdVNDXdH<PTRB\JN\JR\PhHZTPPRF^\TVTD\T<TXVZ`bLRPfXRNL\hHL`THPPZXdPVDLXP`TVT\P^PVHZVVN\XZXR`8^dJVVVTTBLVV\PNVVbH^fXRRJDJTNV^TVXNZT\VHZZTTTVZRX\^^`ZT^bTPVZ^NRXVZHHVTTbJZbTXJFdX`RNRZXHVR\`P\T\JVfZ`TPD:NTFH^NJ\BT@RPVFVLhNLRP\`^ZNLVJbVRV@VJTR\b^^VXR\PHZTZX`PPNRLLJZ\\FXPRVX\X\jJJHfXN^NTVZVdLLT^XN\VR>P\\PTZ\RVVNVNTLNTLVPP^\Z^JZVDPJXJTTRRNV\DZTNL\JP`TZVPL\LL`XbTNNPTRLZTNJTFV\^JNVTbJ\JXRLRP\N^RPRXJbNVRP\XLLNbV<HBTNR`XNRPJTPV^RRRNJ\XNX^\TTNLPHXZXTTNXVJF^H`N\VP^RTX`VTLN`^T\VPXVP``NZPHNPFTLPVVLJLZXLZXTVPRZ^bTTXRVFHXZFZZfPL^\NVXPJTTNNX\`JV8FXJN`VXB\RZXHPPNXV^bNV^ZLV^VRH\Xb\X`H\RTNHV>X^RXJXNTNZVPbZXZXP`VPLJ\PPfH^JZLLJVPdRPZR`FRN\\RBXbVBZNB\Z\LFPJPJBNTV\RN`HJ\HdDTL`R\NJLNbNZNVZX\RJbVTbRZZVPVZN\TRTRNZDNVVdLJ\TRVLPBZPNZLVbVJ@TRXPTLLJ\TV\TNLRVPRZXNPZ`LN^`FHLZT\\^V:X`HP\LbF`RXZTJ^>FRV^PHP\BdP\RfPLPRTV`\N^LZVZRNhTVdVPNL`RDbLRHRTT\XZP`RRV^FPTZZTL`ZP\RVTLNVZLPLLVTfFPdfRXXTTRTbHVVT\TbJR\T`XR\\\TP\LXdZ\`VR`TZD^dTP`XPPDRTTZ`FLRN^TVVRZDB`R^@TN^dRZT^LZX\\\HTbZNXR\JTZVXXLZPZVXXTPRT\ZZZLbHXdHJX^VPJZRNZVLN`NVTNZRV\`ZVfX@``VZd>TPZ\P`dPXbF\^\N^TNZN^J\`DXPL\VLXVR\HTRPZ^JV\bPVPbZPXJTBd^PT^NRVV>NZ``HPXTXFP`\PZ\TPP\XPR^DNTXZLR`dRT^F\N^BBPTRZDLZPXNRPRLRVT>VVV<\RTJ^FXNZ^LZXFNXXRZLZXJNV`TXPVPbT^VXNRLdPNP@VLLLBJBVZNV\^^VJL^LNZJVVVPL`L\`VVNZVXLLTZRTVTXPVNTXNVLFLNfLRX^LDP\VNVbVDRFRPLPTPV\RJTNTPfXPNLBbRFTRbPZNPHL^JRVDVRLPTZ\VNHTVZDP@HXNTZPHPPPLZPPPF^J\\LVLRRZDDVLbVN^NXXTPNT\R\RZJN^VXFXDN^VL^TTT\\VVhHXj^LV\^HLTNP\FbNNHPPHRPNXZPXLPbRPTh^FXFTXJXTXJHTR^\\XPTdLXNTPfTfNTPHJ`^NXNNX\JVXTT^F^B\`VHVVD\VRZNVN@R`PVZ\JTLTVRRTV^RXT`ZRVbL\VLJDTRTTT`VVTXFH\P>L^TNXVL^THRPTXV^ZLP^\TZRRLBR\\NJRRXXblXNXT@VRN\LRN\RbLN^NVNX^NVPPV`TXNTTTPTN^^\R>ZZJXVbZVXPTRTRFLZHPHTL`FX\VRHVJ\PVNJNVVLV`TJRHXXL8\\dT\JNRXRPfNZVZB\`PJXD`VLTF`\`JTXRP\J^V\Ld^TVRJLPDNTHTLXTTDH^NVVX\TDLTZVb`\N\RZXLJPFTVDPFP\NTFXPhjPRdP\HTR^LPfPPVX`bVVV\^N\TLPJP^\PRF\ZN\DV\TLHXBZNBTR\T<`VBPVRJ^HPPFZZLV\LZTTLZVNVTLVd`2Z\NFRh\TPJTVLTXR^\^T^VZfd\THNPZRZNZZN^XVLJTJTP^DVZHfJPZNRXBPVbBTXXR\RXVbXXD\PHB`RTZZdLXPP^RXXVZDZPRLPTLTNPRLRZLVPRNTFVXVJZDJVRLXTVLHLVJVT@RN^PXHRBTJ\bRXZTNJ@TPXJLNVT^TXXFLPTLNTd`RNNZVPPTJ^RLNTVVZP\\TXT`JRHV@ZVDXRVRRXXDRRVRVBT\VXZJXTXRLVZVbN.XFB\RVHP\THRZVFVFbPFFPTXXXBbRVXR:X@ZR^XHZJTHRNfRJ`NRdNVXPLXFL`PTZ`NPHJRPTTBNXX\DRX@PJVLRHR:VR^HRP^TP>LRDJV^P^RVTXFV\L^TLHJRJhJ&LNTF\hRXPPHNTJRRLXP`ZLTbNRVTTPRXHRPXLJbVHVRVJPRRJPZXb\FLBRVZ>R^TVTVPVTJVZXTNZVPVZHb^NVNFBZX\XTVTRH\LN>TNJL\8RPVPVTRNTJJBXRFNPbJPBVVJZHHdNJNP>NPXXVP^JTRD`HV\RPVV\RNPVTP\\P^LH`RLRNLNfLVPTVbT^BPTH^hPHbHJJTT\dHZNlLTZHT^R\VT\NTRNRLZP^XbTVPVVDVV\VPP^TZL^ND^TLZNRRNJVdLT^`JZRR\NXXXH\VVNXTRD\dFV\JR\VN`LFZXFbJ\RNL\ZRZLV^bPXPVXPRTZXRXZ^PXR\Rb>^RRNTXdNVP\bTRZ`JR`LRP^PRP^JTV^T\ZRPZNNTPVPN^TVZTFZ`ZT\L\\JVb\\^dX^^PdTV`PZZ\6PZHXXb\VL\NRRPVXVR>HXZPLLNZPNRDV^JPXTP XXb\T`T@X@LH`DTVJTHPXHT@^NRRB\XVbTR>RNbRRXP\N`Df\^RLTVbLVNNX0ZJRFDVRhZFHRJJBPN^LVXRLLNB`PJRVPVRLJZJTTPPb@^NVZPNTPRD^DLJ^XJFXP`BVJRXNNX\DRP\`LBVXNT\RNBBXNRXTPNZbNVRRX\NTfNZ8NNXZbT\LRPTNNTRPPXRLTT^H>VNJ\\:BT:VXXP\XTLJVLTZTJRPBLRHX\RLfTZ@LVNdVPRRTNTTRNL`VBVVHJLRTJbRPHP\@^TPZVPVfZHZRLVZD^\XVRVRJ`LTJ@XTZNR\LDRDTfB6@fJDX\PTXdPPPVDTZL`NVHPT\PfT\LJJF^\LT\VJTRTNTFVNHV^RPdZRZR^PXPTfR\TRN@Z\T^PXPT^PDVDVV^X@PZJXFTXLRZ\FPZNLJNZ\N^HRR\PTH^RbThPNLXRRNLVNXRTTZbVVVZPTP<RVZVNJTXHP>T^NVFbJNNLP\HRBBXB\\NbdFRTTVVVDTZLTVLbJVVPJTNPNT^NL\NHXLD`PTNJVLXRLX\TNTZVTPDdJXJJPRT@\RVRTRbLRPFVLVVJ\bDZVRRFTZXH^FVZLN\PZX`P^RXH\ZFXXTZHVLPZZZLNlRPXZZHFRJLXP^LZDZJHZVFRRVPTVVV`ZLNTdRPJLXRRNRTRVTFX\Z8NPP\D`VTVVZZT`RTTRRVJVd\P\VXJT`^`ZZ\F^TbZPTP\P^hT\XTZNV\RRXV^VTR^^T\RTTTfPH`NR`TRXFZ^`RLRDbVdL`XVR\^RNVFRPTZRZVVTTNV\XRTXNHV`VJPPRNRbRVT\RJFXBZTZNRPVT\JPVLZZP\V`R`LXTVXbNfN^NfVfV\R\LPPNHXFZZTXLVVdDNRLNfZTNTRV^P^F\bLbNdHRLdb@hZ^RbXNVBhFXTXVXHFT@^TPXRFT^BRNZ\PZVXTNNVNZJTRLVPTfRbD@NNHRX>R`^TbP\VB`NFVXLNRRRPXTDFNPVZV^RRbPZNTDXN^bdNNHVVFNHTVFVLX:XDTNVVTH FLZPRLN\LZ~H`RdV^RPPP`RRFD`bTP\PPVbTDTRJVP@TRVTZNNNPP\`TVRNJV^`NPJXZTPNXJb0TL^^dTNPXVXN\JVVXXFRFXXNTZVN\TVZND^PHDRXRVZRTLJJZXPX@\TZ>ZTHRXP\@XLbZXHN\JHPLNTLdVRJ\XXT\RZVJXVJR^bD\\LTTPNXRTRbZLVFRXPPVBVVDTTXLLRLVRLRZXXRX:XJPT`^FVNPLPLLTBLJZXXVXR\bJTTXNXN\\TJDfLRXRVdZVRDJPNPZ\LPfNZhBZTL`NX\\RVZBZRJ\TR\NTZbVNJR^ZNZBLNZL^RfVNHD^Nb@ZZd\RJHZJNNXTLJZ^B\^RZb\VJNNV\LV\VPFTXTZNX\L\`XRPVJ8Z`JNVL^DN`TFTVLZDRR\TXNZDPVZ\JP`HZ\\hHJH`XXRR\\RRZNTLRP^TR^ZXFbH\JJL\VR\ZB\PZXfXTV:THH^PLdXJTP\TDXVZNLZVR^XVXT`ZZJRZTXZ\XRP`X^NPT`XZZJJNXZVZhN\VXNb^VbRbPF^V^TbPJRDRR:X\^LThRRP`\L\TPLZXVL^P\\FDN`VVNPRTV^VDT``J\d`VL@RJZZPBZTZLXPTPLVbPLJHJ`Jbd\VL\NT`\PbRH^DPVVPXR\XVFTbPD^Z\TVXfBHR8\VTN\XZRRNT>\RJVTRVHLTTVXNZ^RXLPTLTPd>TRJdRbNTFPTbTLRXPNRZ\Z>HXP`DJRR`@ZDPPLTRP^TTJJ^\PRJXNRP\FRX`NZBNZHPJPNVXDLXd\LV^VXRL^XPP`VLdZTPDHT\RJ\bHTT\^V^VLXNHHRXb`F@PT\X\\VHZ^V`PNRLNRXR\XNRRVZTX@`XNXR^ZLRHDHTTVXPDdN^XJ8DJRLXVTPTZVLRZPJRTNT`VRTPNXbZRFVT`PNNVXZXDR`\LZXNbXbH^TX^ZLDRPLZZHNRJ\VT\`Z\Z^NLRTfXPJRN8HXT^RV@NZVRZBHHLTLPTD\P`PFLNPXJZNRZXTPPZ^dPXXVVTTB\$dNPVRXDRVTB\T\LJFZJPTZPNRT\HPXPPJPPb`NJfTNTR\>HPTRZHNV>RRTHLVXhLV^P\RFRNbPHJRPVNTJ`\LVRRVJTZRVRRVTLRPJTRJbTLLJPHPRJ\JRRP\RHXXLJTDNZ@VZPVTTDZ\NZ^HBZ@DVNZJTNTPLlZb^VXZV<ZP`RLbFXR\ZPVXNVX\V`H@ZT`\T\6NHHBZBVT\XN`\TVH^PTL^ZPF\^ZNRRVFJTRZTHVfXTBXPbVLd^NXZJRLHDXJ^VX\VdNLFPZ\ZLZHRPPVb^NdZXXLXL^`RPTN^PVVLfP`TXdRdZRbLLNT^TTNRl\XPRTTLXXVR^HTFXLVZ^XVXZ`TRV\XLZHXN\JRhLNV\VXJNZVR^\Vf^PX^VdVRb\ZNbVF\`V\^LZXZPVPPTV^RXLZRZVLN^HVPPX4VRHR:\VF\VX\ZNXXfP\RV\VNRNdRLPVXHjPVTVZLRL^`ZNTfZXZ@JTVFTDP^^TN`FTF`bXXBZDTT^JPVLNPN\^VNNXNLLZHVPXZ>\BPX\JDRJTZ@PXPbFHPTVNPPTHJbXLVRR^H8TNHNT`FPXLThDPNZXFRVZJXXBPbDRP`F^H\TRTRF`DNFRPVT\LPTNZRBbHXZV\VX@RXFRNR\RHDNPRTPHJ\TNPZTbJTJPZTPZLRPJRXZ\ZFV2FH^PZPNRZNTTNH`PR\TZXTXTHLTXhL\PTL`PTH`TD^dTLZJHVDTVHd\^n\DJL\NBhHRTbNVVT\^\RLd^NXPVNTTLNTDRPLXPNVF^NXV^JVV`HHLVR\PNZ\XLFN^JX\RTBR>XNVLV<LZ^JL`@ZNVTNZTNRZV@LJ\NTF\X\HZRfNPLPPTJXBNRNP\THL\FX>LTZDNbV>LH\bRRNVFVHPXVVLXTLTFPPN\DPHPTVLZPTXN\VRFRXVZVNRL^\Z\XLnXTX`HRFZ`^ZNXVZV^VH^NTTD^VX\N^\\VRLPNZTVJR\L>LTJ\VJDLFRNNXXVJDTRRJJbNbXPZH>T`LF`RTdJDDXVPLhTZTRLNRRHPTX^VPZZFTFLN^VJDTVX^V@ZVN`NTPH`RdPZRVNLPdPb^DR`Z`LZFNXTP\LTP`N\NVHVBVNVXJ`ZNXPN\PRDNJ\JRNTLXXXZL\PRRRNP8XXFNJ\NJ\XRR`V^^JV^RTNRLZP\\LHfPXPPRNdVVN\`VXTTXXVXT\LTPXRbJFjRVZV`PVTZT>R^LJTPZXHVDBJVNX`V\VVRPNXVHD^LLXFVVJLN`ZV^XZV^PbLTV\\TRJLFJTZBH\NRVJ@dNTNNRRNJZXRTJTNVFDXRPPNTdFLDXVPLLNRZJJhP^@\BD`NdT^PRPR`VVPNVJTT@HRXPFXNVLRdH\RFV^V`ZLTXVPZV\XLR^T^B^NBTRXTbHTfZ^NZVTHNPHbRNLZXTdBV\TJTV^D^XDNLZP\b\ZPTVV4ZLXdPNPVLFbVDVHLZP`PNVZF\BPdTRThDXRTHPRFZL^HbNZPJ``DTRHNXP\LBdDPZPLbP^TNNPNZRRNVTR^XRLZHRXVTbHLNPXLNXLT<VHRFX^bF^`DX@VTJdRFJVTJRV\FRLT^LTD`^XRBVRVF^JnFFVZXRRDjVLDV@DX^DZTVPVDVPLPZhR\P\VLNTZZDDXNZLHFJRX`PXJZDNJR8JNNVP^NNBTZRPXNBRZLTLVFBZTPVJRZLTXBLVT\ZTJZPHX\HTPHR@^PNRZ>^`VR\NXXVPZX^FRF^DNJLLRNXZVXXPTXTLZTRb>\HPJP>ZRPRLZ`VNH`FRHTTZHZdLXV^ZDNbVRRTVR\HRHZRH\RZTV@PVJT>VNNLTJTJXDNJLTNVTRVR^ZBN\PXN\RTNRDRDF\JZTRNL\\PLXLZTFR^XNLRL\\T@RNXVT`VXRHPbFHVNJZTRTPR>NVNL^\L^JTdJPJN^HRR^BP\PXbFPLX^P>@JZTDR^ZLT<bRPZLN\TV\TDNHJXLfNZdTRTNPLVXPVXdJTJb\N\RPTL\LVRJNbRN\NhVTfL\TVX^VXTJPRPVXZdRPP^XNTV^\XR\ZXTPRT`V^RZVXZ`HN^bFZRVRX\V^bLVPHRhFVNT\VXTN`V^XR^dXNZZXb\HZJRTf^hXd`XL\PT^TP@LH\`ZLNRbJRfBLN@L@hXVP\JTPXFLT^TLRXTVRZZTRVN\BR^VTHJTJV<T\TBJ^PPTLZ`ZXRVVFFhJTVJfDVLV^PJR^J^T^V`^Z^ZPXbRTPX:RVT`VHHXRNFXJNHNRRLL\TPV^ZTVNRTJXTbTLXRTZLZDVPPXBNZTTVVTJVVPHRRPP^BVXVTRXNV`F^PXRTRVHNPR`XXRTV^ZXHVJJXJVTRPBXL`R\L^NdVFP^PZTPZZXXNJTVX^H\VNVNN`ZVVXRRTLRdJVV^V@P^\RX\TNX`VN\\N\JJX6VRHVVZLFNTNRdXJX^V^VV^VLTTNLLP\PLHHNXNHPZPPNPLPTL\ZTXPXJb`\ZVNZXVPFJL\P\T^^NRLT`LXPFXhDXLTJRDXNR\RF\VRTFRLNJFXLH>^BRNTPNDJJXTBJZN^NTPRJ\PZPVNTL8NRTVVZDDRHbR\\FRNTVTPPJLH^VJVPRPRZ`XZLVRH\>RR\PVHNL@RBRXNVZ\LNXNXHPTRTJ`VNX@PD\`PRXFNPR^NZRXJTTNVbZJNPNPLXT\VNPRLR\^TPJXNXPNFTPX^ZdPNTRTT\^ZVRLb`RFR\VZTTTNJPP^RRVZ^TTP^FVVPRVRTdPPR\`PTXPd@b>@LZPNbJR@RZDTTRRPNP@ZXbXTFVTVNVVZR`TJNBJ:JNXX`NXBLXPRJ\XNfbTJLJX^NT^TZPJTNFdTRRNXJRFNPNRdZZTRTPVJZJTP\X\RJLR\P`VZTT\DL\ZfVRPNVLZ`PJ\^T^Pb`Rf\bTXVZRbFL PVTNTVV\LTJ^\HTJZRZ`Z\PXNXTHZXZVN^\LVJZLTHPRTH\XV`ZBd^\RPLXNPVZTTVX\XPV`Z^HXVXZXR\JRNZXF\RXPN\TJVZNXXXPLHXNV`LDLVT4ZZV`TPPZLbVTZVLV^PLNZJNNNNTRTR`NVLP\HZZRLPVXZVLRRPVTH\LJXLPPBbXRPBPTHPV\N@\TXBTTLNXTZNBLT^LVRLVRXFDVV^^NTNTTTTNFF`BRV\JZTN\RBVPHF^JXLVN^NPXNRNVLbRPDZLXXTN\RRRF^b>XRPPNF\`^TdXRZZDLRZD\NLXJTLHJLTLRPVNR\<ZHPVFZRPHRJ`^VXVJXTPHRV\^TVTJTTHTN`ZTPPTXHLJJJR^TV\HPZTPHNPBZLXLPJTPbNJ@V\\RR^`\PZFTPXRRVNRTNJTPXLPNN`LPbPNL^PZLH@RLRRTPNFJ`PPPTVZR^JVX\NRR\ZhLRPRTXLFL\^XRHXVTHX8PVZ`VZLRZJ`JRRP\J\NVJNLNX\VTVHZVTZXLFPPRNHHBNVTTXVJVTDN\T\\LTV\RF^TLPJZNhXVLbJHZPHRF`\RVPfHVTLNTVFH^PZTPbZPB``NXJTPN\hZZLLXRRDHTXVFPPPdF\^HRNJXJ`TLJNTRJNVXPZ`JBJTPZP^ZH^VZRJZZPZFNNNXZFX`LXRTRRR\XPZ6^RZP\VTJTTFZVBdTXPXXPdTDJBVHJfLf\T\Xd:JXL`NN\JTL^X^XZVNNPN@LdVRX`LTZXHXNNPNL<XXDVV`X^FPVZVJVTNZ>DVVVXLZN^NjJ^RFNNLNNTTXX\f\`RVJZXHVP`N\PVZPTNVX\\X^PLHHL\BXZVJ^XHTdNXTVJJLZPRFNTVVXJNVVVRFTbVdZVRTXL\VXZN\PJVTBNHH`\^LXRHHXVXJd\XdLRTlZRPNF^FDTPJNZZZRTTNLZ\XRVLXTNXTTNRRLPHJLVJTPBTBV\`Z\R\ZPVN>V`RZTLTHJR<XJJVNZH^`N\LXJ\JNTLHXZXTZJRTTRPFXPhRJ\TD`XVLNPXTPTLZ\NDTXZ\^THRVHPPNLbV\^NLXHDNZRLNN@RTZNfVBXZT`TbZZRHdVX`HHPRRNPbLNbRJ>ZZXTTPTBZNPXTTBTVJLXVXHJX^RPTX^\HHNPbTZRLjJ\JVPRRfZT<ZJZNRX`TRV^ZX\HR^RZX>BXT\\ZLH@\`\P^^TNVRLLVV\XNTZPZLFXXXPNXPPdJRRXHLRNRHJRTVRdZXT^NDXXVHXNFPPZbBJBVLRFXbLFJfPLZPRNTJJVP^RJVLPXF\XLNTJBVZNV^TXPPNXJRVLNTFRRNVJPTLXLZ\PF^PbZJVP\RXJNVVPdVFZTFXLTZDdTZXVP\XbDd`@RHVVJ`XL^\LXRNT^\XZPV`>^ZJRPVRLXPN`^RJVLTTRbZNJVJ\XPPXXZLNN\JP^XRBTXL\VT^V\HLBFVPRZ\FJL<NXTHPJ^HBHLJ^^RLTX`J\h`ZNRNXLVR@ZXdH^R\\TZNLV^VTRJbVV\FRLLRHVZT\N\BZ\ZX\RZNJLVPXRXXTZVNZNTbHBZVfNXTXZTPJT^XT\XVJdT`LPJHL^`ZJhZT^bT^T`NPRN^`bTTR:TRX\ZZF^TLTVXHPZHPPPPPP^R^^PLHbHZP\NVTR\VTNV\RNPNXVXTNZbPZVPRX\b\NbRLP^XPXZXNRZR\J`RfPPV@X^^JfNZJX:PXRTLdPbVN^LVRBTbVNTV\XV^RZPT\XZdZ\RPTRdHNLPNHL\PHTPNJZLJHPTB`TTNTTRDZNP^RVTHV`N\NNPV\P\LXRPNV^JLZXP`DXXZV\RJZLJV^XLLDXZfZ^LLXRZJdJ^D`RHVVXV\XPBVLVNPTZXRF^D^N\LRRXPFLVLHPVXVVNNTTPB@@@TRXPLRJRLHZLRRPNP\R8R`T\JZTZN^ZZXTNNVPJTNJLPXPP\RLXDRHTD\N`LRNTlNLR\LJJN`ZVD\RXZJb^HbdJ^PVT@TPX^NTPXTTXRTPLPZLRTTRVDXVVPPbLRPHbL:PL@^`FDPTVJVNJL^PNHLXXBVF\NDTJPZLV>LLVXLHZ\JN`R^FNXX@`PTDHJR^TFDRT^JZDRNPJVXX\RLVdRZFJXPLT^T^XRdHNVN:^DRVVRRXJJT<ZJHNNV\fZXPX\\ZZLZbRX^PDRPR@TP`NXVLJdVJ@HNHXJVXRRVZPVXVPXLPRDZNHL`NNJPJFZHRHX<RNFNVLLbTVD^NRLJZRNTTJHRNFRT`P^NTXPJZRX\HRTPR\PNP\PL@R`DPLfH\LJHXH^LZ^F`JLJLHZPLTZLLR\ZHZR\\PJHRJN\RHTL`N>fFL`T\LLTRRFPRTPZFXRTTXPHbXJPPZd^\@LFf@TPJT@VDTV@VNTTHXPZVRVZLH^\VTPVVL\VJLXTXNZZbdLbNVBZZT\RRF^FXDTRVPZXL\VTP^TRLPVhJHZL@XXTZ^RRHLHFP\PJTPLVPRLTRV8LPPRVPHNFRFDZPVRPVVRPRfRFPJNTRhZTTJTbPRTJV^`TRJRZhR^ZTjPR\ZV\TVZXVXZTR^VH\\h:XXfHTFdXXVTNTVZRRRf>PTVXZZXLNZJTNDJXRXFZXPXT\\`HbbX`LRTVP\J\NVF@ZXRTRVZbDNXRRZJNZRRH^XbV^LRXLZ`JDHVPNLRVVXN\TVRVXJ^XL`PNR`^ZJZD@d`NPTbVVZVZLZNNPVXRPXTZHXRBNJTTNNZZTPX`jPXLJVJ`XHDVZV^BdRPFL^\NJXDZR`HRPP\N\`VHDJ@NL\VXLXTDRTNBVXLXT\H^ZNXPNVT`BTRRHP:\PXPTPNXTXbV<RJHPXN@RXPb`ZJ\jZRXZNDPJJRZNRRTPLNT^L`FJRRXXLXTNPRBP^TXPPNP\F\RVR`NHPJLVDRVXJP\X^ZVFJPbDRJXZXJLDNRTVLZTRVXFDbTT\RDXV^FHPVTZ`JNHRPL\HP\JVRFLLVRZJDR\ZX^LH\RXPB^ZFNTDLRVXRXXFLLFVVRTJHDVRVHPFTFXNX`NVHLRZXN^\FVTHVXVZJTL^JVTZTTPFTNVBTLNHT\TLLNJZRP^DPXTRPRRRL\LTXXJNXPVJHPNVDZTZB^PJPNPNHNTLVXXNVJTXN^N:PF^TTXXPVVLdPPTNHVVVVNXPLN^R\HZVRZJTZTNVXR^PPXZTBZHJXJXHTLXRNT\PT\TFPRRDVBJZXLPL@ZLD`\RFV`FTR^LLTJTPRRFJ^<NHLjDZPTL>VV\VTTN^XPZLZPPTLPX^HNTLVRJRPRF\TZV\NVXfHRRFFdTHDNXRHXVLTPTN\LVNTPN\FLT^VLTFTXNRHRVTP`PJZRNZVTNVNH\\D\LNJ\ZZBlDbL\TRR^@^TVTTNH\PPT`PLXTPFVZHHPF^XTVZRV^HZZVFdHBZZNXJFTRZHPXXVRVNJPLX\RRXb`L\^\dVTRJFZZTRRZTVPJJdN`NVHNb^X^FJV\VZ`Z\^^VZ`V^Pb\NXN^TJZ`PNTRDVXJ\B^JH`ZLJ@XDFXRTVF<RXLPRTRLPbTHNTVVJXfBRVNNLFZBLP>L\PN^PTVTRJZNXdXXT@XTRJNPVTJdPVNL`F\HVJZJTTjNdZR@NdFTR\TP:^RPRFPN@^VTJVRZNFVJ\h^R`BFPZFJFVJBbRJXPZNL^P>FLLPPZLNJZLDJdZPPH\TXFFZ^`XPPRXBZFPTJXHV`PPPNRRTXPRLPF`JZ@XX0bLVTV^XL<`JPLZBJXPP@@NLPNVZPT^XVX PJZTXZ\RTLHVZP`RZTTZHLXNPVPPVTNTNTRLTP^HXXLLXNPVHL<8NBBRN`VVPn@NTdLJH@TR\PB\Z@P`NLRPXRBBZLNLNLbLLPVNHVNTVTPVTNXXVZ`ZXPZZFd>TJXPVT^LPNVJF^PXPVJPT\LNHJRPPZFJFBFbTRNTXHRNPVPXLZTHZHNXNFHHR\DhHXb@DXR:TRNPVVX`H\L^PHT\HVVRLDRRTJJR<TPFNPHTRRRPHJPJNXPLXTPXZbL^PHXHHNDVVXT\LNPNZTTVXZX<FTTPL\bLTL^LTTN\Z^FX\TNR^hZDVLZV\PZXR@P\R`RJLRPNJBJTVNTPRRXNbRLVHJVRJTNRVX`JZTTVPRFNTRJZVF^`VRRDP<RPTXdVPRVjFHTLRVJTDRLTJPJRJRRNPT8LNVXVXNLNXJ\LHLHVT@N\J\RTJXZLFP`LPZHZNPNZVPRFTLR^ZHFR\VFRVDPZJXXL^\TZHNZZV`ZRbPRLXLHVTFdLTZTFdD`PPHhPXV^ZXXPVJbJXPf``JFbTLHV\b`HNJ^RLNLFZZZPRL\VTFRZ>X^RPNLDLLf^^XZ\N`^^T`DJZ`b`R`ZRZD`ZPVHNXDFZFDTN^JRLNdHH`dJR\DHZPRT<VVTR\NNHXPFBZJLNHZNNTJFF`l\TXJXhBXZVTPHTTHLRJFJLX@HVR^H\PLXLTDFLZNRPRVTPXdLNTLPXNBT:\TPNRFTTHFTPLZdJLPVNXVFRNPTTDTRTZPTP<ZP\RJXPFVLZXJ^^ZXVVP^ZLTH`FZVV0LXBRPJPT@BZXLPZVbN\RP\PHRB^XP\TB^XVbVR^TPP\>NRHHTfLPRDXJNBHZT\NHVFVL\FdBbPBPV`RRLRNZ`NTR\VVRX\TVPPL\R\ZNX^fRH<TNXJVXRVPR@^RLLBRRXJ\L`B`F\DNPNN^ZPH\BDRR^ZJTPR^T\RPHVVR`H`ZLT`LRJRTJLXVFFDJPJ^XTL^\X>^\JNTTHVRT^TDJ`R^VJTRNRRZ6RJRNZB<`THDNPLbHJNRRRVFNJ`RRLN^XLPLNT\LRXNRJRJVPPbP`NRBLVRNZLNJHPJVJXZNLVNR\RXVNXB^PN@NR\TH`JXNVXZRLbJHHJVLNPRTRVNVNH<PNTTRTPZLXTJ^`PNXTLZ`ZTVVNNLP@RRTZZPXZD`NLVNVNNRZXZVBXVZRLH>ZLN@LX^@RTBVLLbPN\P\FTVFT``VHNDTFPLVJ\TNHb@XZ@2`^PLVfHXLPXLXTlTF^VZJ^^J`RTJLJDNJXTHR^VVDNZH\LZHPVJZTTRNB`R>P^RVLRJTP\LPVTNTbRJTbTP`^VPVRD`TZJNTRVPH`b`J`TP^P>`J\VRbRFP`L\>PbZRhVNRDfdRPHZZLXV^ZJLJBTNVLRPPV^`>TP\BPTLRNRZD\H\H`TTRNLTNNNXVZVNPNZLTJJXHXVPRLVVNLNVPJJPVZ^ZLDbTDVFNRJL^LJZ`R\\V\XZXHP^fNXZVTTTJJXdZNJFFPXN\RLf\VJ^VdVN\PNJHPNT`PFbHR@PPPN\BVT>RZTVLJLLVTJ\NPNP\HNTJ>NNPVXXFRNFJB\JTPTfPLb`FVVJTVZZRVJXJZTdLJTLH`DHXTLRNZTPTTZTPJ\DBPVfPTRLJPVPJJTXPX`RPJVXFJJJPL\\NPXNPPdRZVLH>^XTDFHNVDNX\<PDNRVNVbJ`NfPXNHB\HTP^BHNL\LNJZPNLNNNPPJLLPDTRH`LXHRbPZLRV^ZLRVXFLXLbPVVRRNZRRZL`JH\\VLDTZ`R\DVbVVLT^PRPN\NVHJDJbVTLTLXHTJTZLLRPDVVFXXJXPFRRFHRPXFXTVRdLT^HNVNVNP>FPPNHVLNJLF\RVNJNRJJ`<X\TPXPBBRTTHLRLFDTRPL\PTJ@LRDJXBJJFRNTJPT^D`4XTJ>H@VDHdJNRBTNBF\RXXbX^fLZNZBRPJJZJP^`R`JHVXRPTJNPZFFPFVTTBHLJLHZDN^VPVRNJL\XP@PHPZV^FVLZJT\LNRN>TRNR\JX\@LLXPNFFXJTZTPTFFRJRN^VF^Z^LZFTTPRLF`\LVnRJNRPRR\T\RPbVLDLbP`LL^VH\NFXRZJ`\NHZTHLTLNZZL`JTXdPPVV\XTN`^ZTRX\NXPXDZRBFPZRVXfR\VTTRVTTJZF\TZ\NNR\LP\XFLLVTRLXJLbFVPV^^R\JJ`JVR\X\RRNPV`\d\JZPR\T\`RfZZdVXXVPNXj^NJFRNTXPbXLbTHHZXLVDZJ@LV\\\LVTDdJNZRHT\PZ^fP^HXfV\VNRRVRTPXXXDLTXLR`RN`jPVRF>XZTFZT\XPLFNPNZjJTN\`PV@LRFNVbNXRNXJ@TLTPR^VNT^RNZVN`NNFPF>^HVT\dPdVLLL\VR\@RXTDRZB@RTXVR^ZNBNHDNFTPTLLN@PZ>HVZPTTVHFTVZXLR\PTVBBPHLTRXFZRTdT\JNJJHRTTLTVbNPDVlZZNL\N@\Bb\^bVVPRVRNZVLZVLPT`RZTFPN\VPPZRPhPNP^TfXN^PPDZPRPJ^^RXRNZRRRNJFXZTVDV^LLNXXhbJFZPPTZTXNJ>ZLXPZRVVDDZNNT^@PLPPHZHTRXJNHZRP\ZLZZbLZ\XHFXJNTLFP@XHZR^VJPJNPXFP\L:NRRT\RNJP\^@\VXLFJNfLJZXJV`RXTNRBXVVZP\ZP^DL`NHNV@N:T`TVTHFRJ^^\VPLTZPBXXR<XRRNPDXZTZFVRXJHLTbLVPLNFJFF\TVVN\:\PN:JNVLXTLHRRLBP^VRZVFPJRZXPTLNFN\ZL`dTFVVTPDHLVT^FXXNLVTb@TDRXR\\NL`TNZL@RXPPXb\RZD<LJPNXNP@PhTZLPJVJLXVNdJ^PP^VXLZFLbLTRFZVLR\ZZTVTZPLTHJRDZT\:J\ZVP\\NTXZNVN\XFPVHR^fPH\RBXTLX`\R\R^NbXTZB^Z\RNDbLXVNJZ`Z\^Z\XVVTNLNdXHRZNHHRF\XRT>PRRVXVVFRZXLX:NX^JX^NN^XB\bXLV^>VXHZR^PXZV^jL`RNR`THLTDZR\N^NZLTJTNPTPXL\TNTPRVbLJZJ`Z\BRV^bdDDZZNTVTNPJ^PNVPRNHVNRTPJRPFDHRPHXLX\TVRLjDTXVVRZPH\XHDRfTVDNDLF`FRJT`Z`TJ^RJNTR^TVNVTXZHFLFZR\B^NXX@NHPT^ZRRHlV^^ZTRTLLJTPXNNZTPPd`XTZZXTTPVThZLXVX^RTTZVTPXP@TVJRVRXHRfRJ\PD\TTVRPRVZRVJ^RVR@Z\JPX\HLPX`RHRPFJRXFJFZNVVRbJZDFH\VNRFVTLRXVXLNZD\TVXNLRPFTbV^TNP\Vd^LXVPXVVNPRPNVNRTHXLPHRJXPFRVF^PXd\FRRFJNPJ@F\LVB`\LL\VBZXV\`dV^PLPJbJTVPD\\\N\XT\\TZVTB^TBPVHRXdTZZFbDPV\bXPXHJJ`\ZbVFZ<XZTPBPPVVXR^XLVFVHN\N>B^H\TVT\L<\NRDdTFBXTH\NTPPT^>PH^JFZLZTPBJZFPTbHHTPJPN\NTXRXJZT^\@LPVNVPZXJLZZNRVL`4HPHFJPbHLTVTZJPTFRXZRNRPRNJTPZLRFVRJ@JBPTF`RDTJLNZNbR\TRT^L\\\ZVNTLJJLNV@NPJL\JR^Z\HXLP`VTH\NRN\\ZJ<b\`ND\DVRTPDdNJFTHPVPVZD\\@ZPRZ:RVNTZTLVZZ`TVPLHTVFPNZTPJZP:PJV^JZBNPRNZRNNJRTDXBZTLRJXLPRTXNFPPFBZHRTVVRLVRJ\DdZdVJ\P@RTPV\TZLfZHVVFV\JNfNVVZZ`PTVRTNRN`HPXPN\b`V`PZNPZJL\\PRXD\TXFbP\J`RVNbbVPXVJ^HPP\T\RN\HbRF\HVVZVRVV<JBJNJZZTDZZTVTPXPVVZ`RXZ^bBZVVPPTXXNXNZPPRRRX`P@X>^LXNT\bVPXXNR\JNd<R^VRLNRN\\ZdFRbHTP\^P>ZPXDfDPZ:NTBTNLPRXNTHPTRTX^ZNJ^ZHJPPH\H`BZ\FNRRVJHNPJXJTZTXPP\\RBPN\\\TTBZNLLZVTFVNHHR<`bBPRHLVRXdV>HL`NDLNZPNJTZ:LhZRLTRHVHJHFdLLRB\JJh\R@HD\`FXRJZRRVNJ^LHF\VNRTVX`NNVPZLRLL\`HDRVTVRPVRZX\VJFZRN^ZRNVRLRV^\JP\PBJXXDJZHVRXTHXVLPTVZPH`XZPNLXN^fPLFH^HVXRfRVJBVPJHPL\HLNPP\HPbVPLZ`DLRVRFXDHJF\L`VXLRHLVf>RR\PDHJTNR\ZF^LPNR\TN\bNJRNFRXPZZ`R^B>ZVZHPN>JF^DVXFPNHLN\PNVVBNXRR\VZV2HXNPXVJ\VVNVHFXNRdPPJLHDLLRPTZ\@PXPJbXRRZXXHLRRT^PX\HPDZFVVXH\J`NHRJJTNDfXPX^JPLJ^DPPLV<JNNHNPNX\HNRP8BZXZJRLV\RJPPTHNJ\JXPVJ^NZXPNFXTPXXTTD2RTJVVXLZPLXVNXFVPPVPLRPHN\PPLbJFPbFPDVLZPTXTF<DPHFN@RLPNTLJVNXLZ^NNXTP`PJZJXLLXL^JTRRRPdLPLVJTXTJ`F^TX>\dPZXXRVTHPVHJ:J\RZT@TNZVVXPXHNDTVJ\JXVHPPHRTNRFPFdLXRTVRVHXT\TZPN^RXJ^NVXHPNLP`NFTHXPNRJRHTRF^P8TNPJf^THd\\bdfT^VP\TXTTVJDPTL`T^XH^JXTH\TVN\NFdT`DTNNXRXd^ZRP\NRJNNRRJ^RXZPVNRVVN\RZHL\HVPZVXZJT^RJTDRNP`ZHT^ZTXN\dHXPTJ`XJbLHZN^R\TPJRXNV\XDP\XPPdTZPdXXNZVXXJT\LTPF8RbHVPXNlRLN^PRPJV@\BRXFTT\BFTZ\F^HR\RVZFVZXNdRZ\NTTFXZ^RJNZVLLTVHRLVXPXTLVLL^XRRV`"PTbRRf`LXXXHRZDXDNRHRJNJVN^XJTP\@NHbRRTLLXNDVNRZJL`TFDPTXVNXNNRL\PLPVTRTPNLZNXTHJ`XVLXRZLTL^PNFZZZRXRPPbPVLDJHNJHHVVVPRDNLHJTHLRZD\NRLRNDRPTVD`HXRPRJDTNDRNTZbZ\>RRNLTRFPNZNLXRVVTJXNPVN^LLN<NX`DPT\JPHD\Rd`TJXX^D\\VNH^^JXTT>N\d`RNNHLP@TBJTVZFdNTb\T\TN:VNLPZVRNZPLXhJF^H:ZJ`JZVJTDn`>dXRRJL\Nb^XT\bPN8T4dRJTR:PVZLTLNV`RPbVH2@^JNBRJVd\VJVPLVH\THNH`H\J`XRJHPTDX<hXXRZPPRR^LZR>HTJN\NRFRLNP:HHXPFNbRXTBNVLNT^P\JPJ^XLX`NRXRbPRB`FTTTVJNTXJRVR^NbN\PHFP\ZXHPH\TLJXNDTVTRZVVNFPZLJTFJNHXX\XRLZPZPXHVVVPTVFdTdPNPLPRbNPNNd`HVN\>XHR\N>RTPFTJVVLTXRHLHVDTTLLN\V\NJRPRT\XVJTLRZ^LXV`PXZN2BPZ`FTVZTPPRFHJXFPRLZV\L\JTVVP`^DNTRNT\NVJLRZRhXNbVZZdF^HXRVXX@XZHbVVZPbZLXZPZ<NPTR\bDPbX^VTP^`RNTJDFFTDdNTRHP\Z^LbPH\P`NZP^J`V\NdbJVXXXX\XJ^TJVVPT^P^PBXL\PFZHPbFPJP^JJX^^XP^TPVbJ\PdLT^PRTFf^R\ZLL`XN`DNFZP\TT^ZPT\XFX`TPV^^\T\HXN`DR\N@NJ@H^^NV<TVXJdJFfPJT>bXPRbPNhLLP`NXRbDJVRHFVVTB\@>ZVPLNHbbJB^PdNP`PVTZVJ^BF\RPRLLJPXXJTLPPRT:VRNNVX^`FRJJXP\^JTDTZNNL`JVBZPHXfTX^BN^`RLZNTXXVZHZ\JTXPLTZT\\HRP^:PXL@JVjDXbPRLX\b^ZZBLPFPXPXZLHXXRJXRJVPJ<TNXLFFTT\L`LVHN\ZPRTLTLLLNPPLX^PRN<VnXNPL\PJR`VJLLPRRHNNTVPJN^DRTRBDLbJRTVH\HLVNZTJNPLHHRDP@JbPPNVdZJTRPJLVJFPf`Nf^^VTN>LDBRZZTH\X\XJLRPHTNRXLPRVN^TJP<^fN\NDPRXH<JHFXBXbJPVLTNLVX`XHXNRR^JPNTJVXR\XT^PZTXRRNR^NLFTXD@TZJZVLXPNTHRV`RVNT``JHBPVVZVPVJXRTPTF@fHBPH\RVR\TTDZHHN<VVXP^`P\NJNZX\F^NJPPX\NPXRDRbFRPDTbP^VNJPZHXX^JLTLFNPZPV`LZZ^PDZRPZL8VBVPRVZVVPZRTTNLR`ZVFV>TLNPhDFZL`FZBRTbDT>PRTHPRX\FNVXPTZ^BRX\fVT^XJ>LRRXP>VZZTTRfXTRJZHXPHPB\N@R\X`RTXZ`VZTHTbX``JVX\`R^^\FXJPJPR`PVXJRTRHXL^DD`PPPZR>TXZXZZJ^V@f:XTXRT`XVTTRRZFPPXBXTNLTRVLVTTLNXPLTR\JD\^\TFZTXVP^R^T\VJTVZNZVZXR\\XHJTJ\VHJRVLTl`ZPLJRRZPPFZPNHFPRFPPXT`PBdVTDHZVBVTZJ^TXLHH\RLNHXHTD^P\^N\RLNRXPJNVBNTH`NBTPVJRLTJVT@VXTNFLVbR>NHHRFXBRTDZTLJBfNPVNRXFPJVDTFL:HLNL8\PPJH`\PXXNJTTNXJJLHRNHX^TRDNHFFJ\VDRVXFHZTP:DRJLVTR<HZ^TRNRP^LR^VJPJP^R`HLDJXNXNRLJHVZDTFVTLbJ\HJHB>Z^bFJNPPP8XV@b6>TLBNTLPN@TPHTV^Nb^XHFNPNVFPhRLX@PNVXJ@HVZPP\BTVNT^PTF`RBTNR^PTTdZZHbFLPX>NVJlFRVTLVTJH\^:FN\NNN\LHNZDXPRZNJfNRPTHZBHV`TPVbR^XPPJZ\N\FRbXRTVTD^TR^JHRTPZTJ\TPVJJZLRT\PNLTTXPN@PLRJ`6TFD\`H\6VFH\BPZTNRJH@TLVBJJRVZPRRTPTDJNRTTXZRPHTRRHP@LNRHJJ\LHZVJbNX^JPNRPPHXlHVH\NTLPZFLTR^X`NP^FdJFF\PJLZPV>TLRVRDBRbZRNFNPlLRJPNJFX^NFRLbXHLLVVPVbL^@LTLPTFX@NH@VLLVDJX`XHTNXJFVNbVL\JBZNTNFNZPDZL\LHLXTNZVPRV^ZHZbNdPRD^T^XLPTVRNV\ZbHXTX^^JTX\RNHJJJRPVVH@BZRTPXJL@XLXNLRPNLPXNPVP`VJXP^RLTXR@NTTJ@RZJPPF\^VdRX^NP\`XZZNBXJFPHVT`\HTRTZVXRTNXFVD\R`PJLPTRVNTHXVHNP`F\R\THJJVVPJbXfRjTbR\Jb\LjZFXVRTT`dR\Z:P^N^hL`HXN^VXHV^XJ`BPHT>TNRVLX^ZVTFRR^VVJd`RNTZHRPX\XNJN\DDX8@BP^XNPXRVTHNbJJRNXNZJ:NNL`HXN\RVP^PRVFP`TVTTL^RRRLRZV^FT`NZDXXZJVRXTLLDJ4ZdVXNFVJPVJN\V\ZHZZXHJB<NZ\PPVRJLL^ZJVZNFVLXVR\JRJRBTHTNNTT\RT^ND>XVZJV^NPNVRRRLFbV\NJXTVBHDNJR\DV<JV^ZTXRLbJXJRXPTJLVZVN`XBZJJVRRT\PVXP`RRLLVRPV^V>VZVZRTbXHFPXXTPNPPRFhVPFNZLX`NNN`NNH>DLV^\TFXT<PZDZRdPZPBbNRTDNFVHNRRVRXTBNRVPd@JV^B^@VN\HFZLPPT^XZTHFLTHJR`LLRF^P`XPNJTVVJRTZPJ\RTPXDNZLHXJPLXNJ\PPRLXRTLTPNDV^PL`H\ZFXXPFZVDH^XFFNVFPLR<`@LDLJVTTX^:VTTHP8ZJ^dXJXRNT>`T^FTdP<PNXRXPRLVZRLTNLJX2LV^TRVXLXLJ>TJ`TRTPP:PR\VPD\TVXHLFJPHTVVNLJZLFDTJXRJZNXDXRZJLLLJLPPTRVPZLVNDVRRT\XPTVNTNJPVTJRLPRPVZJ\>`RFRJLPTVXLNTDLR\J\LH\NZB^NFNJHVbTPXRNVJ\dHZNNPjRPVDHJFRPXXND\PN\PVLHPXPHXP\XZ@ThXLRZL`PJ^bXPJV\FbLH`RVPV^L>RPTNHXVVRRPFRZVJJNV`XLTPVZTNLT^`NT`V\NVR>NR^`TXN\PVZRL\jNBR^TTRXJTPLLVPDXPTZLZPP^ZVZR^VLVLZXXRXRJfBPXZZZ\VBRZRJZTPLRPFNTVRb>LPLNXJR^^HTP\RVLLZTJZVVBXRLXXLLLLNZNH^NNTRN\PRNVXDVTJPRZ^N^VNRPLLRN\\^LXVPNZ\XRDR8LXR`F^NRHbPRRVZH6ZRPPDX`H\BN\F@DXRHVJbT^BRX\<T^\RRBNNXRFTJZFL`RNdDHVFHR\THH^TLR\N>PTVTXPD^PTLX\J\VPDVN^VLVPVNbNVXR\TXZHRVV`J:XLTHVV^RHVNLLZPZT^XHPV\PJPZVZJZHTXPBV\R\NLRF\BNFlRNHFLVbDT\bVP\RDZPHRP\NTNLV@RLNLRNTRZNLFH`PNPJLZZXRJVHHTZTVVLPX\RXDHPVJ^NBL\HLDT\@ZZPR@HVLBXXTFZHVXLZVV^JRFZVRJJFZJTXPRHNNLFZTLV\HVLZTTVPJHXZXLRJJRdPPHP\ZRPNZPLVNVVH\LPBHPPLH>Z^JPRV>P>\NNVRRNThH:P`ZFNPPVP`NTFRLHTLHVXHR^J@RV\LR`LVXTHLJPJ^T^XFJXX@XTLDJLRJ:XPXJTZR`RN@RLRPNLFRJRPLJB@PXTN>FBFTTZRRXHTNRLJTHJXPLXPDTRNXLJVNRXRLTXVPVRXN^TLJRRTXF^X:fNLDBNZNDFPL\NXF^RJHLHNN\NXJRXNHRTNTNPPTNR@\LPLBRV\R`JT8NJZVJR\ZTNBVD^RLLRL^L`JPN@X\DTZDVPd\XZVDR`F^H^DNFHRZL^PTXND`>HVLXJ^NTZ\TVTPfRBTT^HFPP\XRBJ`^XJTXPVVJZDNZDDP\JHNZLRLP`XPhXNbLbXdPPLN\NT\\@TP\XPLT`NbTHbRNDTJ@Pd^JPTVLZR\RTLVZVHV4TVNRRVRPHJHVDFLJ\LZN`RDNTLJNRHX^VZRNH^TFNVNNPLZJR>P^JZbRJ`TTJPbJZJNN^TPdHVdN`HTJ`ZV`VZZRPXRXPH\ZXHPVXTXbPBTNRRRHXTR`TZVVJPbTJXdXLT^^PNhVXPJ>TLNXVHbTfPJTNJ^N\VL\VPVJTVR`ZHVX^JXVPN@JN`NLRNLJNTRVHBNTN`P^N\FRJ\R^PPVPLV\RHT\RJRRRPJNBP\LTTVFJFFLNLN\R@RRTTPFTV`RRX^RT.THTPRLVHHVVPPLPPlRPLN\FTPNRFXFZRJVNHHPJXLN\XZVNJDTTTBLRPHVFVXRPZRDJ>PF<LTNRLRVNX,HPZTFJJF\HZT\bHVJVTLBdRXZTVVNN`JLLVNZ^PR`:XTHLJLP@TZBHBdHVXVDN\^NPNVNXZRNHTJLX^JJBZZ`PTRLBTRXNN`PTXNLX`ZXVDbPD`<\L\HPNZXZNNXRV>^VN\XVRTHNXRT^L8^^\XPXZ\LHVPTPH>\dJV\RNH^FFJ\NVX`LXPR\ZTNNXRLVJFTPZZ8PXFTZDFXdLJF^<T@T^RPH^RXL`JPX@Z^LXB\NX`LNBZXRTLPNHNXP\@XFVJR\TP>LDJdVJT\ZHFLRZHVDTXPNRXTPVHL\LZNHTFPLTRVNVNVHN\XXNHBVN\LL^RVJVPL\LR\bZ^TRRPNLN^HPNdPTFZZX\JPZPR\RL` NLRLZRLXHXXJLNT\XXPTTVNdJXdTLT\PVZRTTLR>TR^@PRZpLb`F\J^@`PTRJXZTPHVZ`VZNRbJZNHHDZLRVPZPDLLBHLPLNDHPRB@XTZTN>RLPN8PXPVT\^LRRZJNR\HX@NRFVTZ4LPF\VlVZDVTHT\TDXRXRLNXPTXHN`TLJFRTPNR\>ZP`PVTLLL8^ZR^NFT`XNT8V^^JN^ZVNLD\RTLRLNXPLHDNPNN^N\VPD`XFL`RBZRHLZNPLRXPTZB\HJZLTLNHVXLVRRZRZFJbXL^VNNVDRRRZRXZHPXDFJRNNTDL^N\L^NLZJRHZLJZPPPVTRLN\NRP\JXLX:P^LZNXPLHN\@VL^BJRXdPL>TJF`T\LX\LLRTdJTVNLVVTNXRJZPTPXPTLPXJBLZPXPZN\PDTPPXZ>\VVJN^PX@ZDLN\RJ@\Z^\R^JRLJPLVPJRHHTNbRPT^TNRRLH6ZTLRV^LPLXJXLNBXJFZDBPXLFXTRVTTHPRPRXRNV^PLNPT\JXPLPLRZPJNVDV`\JLVR\bNJXNJRZRRLX\HJZ.N\@PXTLXJFNFVDRPBRVP\JBVXRVLLZVLNZVPLVHTPV`XVBLHJPNVTZP`TJPNHXZ\RLZVBVVXF6T\PL^^LPDTTT\XNXJXP\TLVH`XLN\JVLbd`TPVLXR^`RPVJHRRTRZFLXRH\TZFBVXBLTX^R\ZVLNNJNXJVXPXVNRVFZJV`HHB\\D^JZRRRVVHZXLTJRP\ZTHHHRRRLPXXbLLVTZV^XFXTTN\`PT\VV`VTHZJZ^\NXV`JVVVLN\TJbHJT`BPXP\bLPTZVXNXVTTVLJXZNZBFPJL`PR8`Vf`\`bX^V`\TPR^J\>DRX<JlXXHP8XXZPLXNZ^JRV\T`XJZTNFZN`DP\LVRTfLVHPRXTTbZT\LbHZHNL\RNLTZZXP^NZRF\L`HPRJNZHb>BLJT`\bRJTTZVVXBXPRHNTDNLNLXLPPVPRNTNTRZRPV^d<JTVTXNLLZTbRRVTJVRRF\ZHFPRXRRFPTLRZN\LLZ\\NRPXXTPJHJT\JLVNHNRTFXBP^N\HVPXVBV`HLPPXHHRLJJTT^HTDNHRbLPNPV^JHVTBRHLF\BR8ZVR\6ZTFZV\JDNLRLTNL`LNPZ\PJFZHPBPNPLNPLBTNPXRNJZVVPVZXFN^JbVTPNNJNZRZRLTPFbXFL^XZFbXDNJLJTNZJTPDJZLNVPLTZ<\VLLXHNHV\VPRPLTV@TNLJNPTTRD\BJVRfRHNL`JNJXVJVP>JPVHVZX@VR<XRZRP`PV4VZT^VPTTZTVJJTPDVRLPTNNNRLXNNLRDTTPL@TRLZXNRHNRDLXFFTFHfFNJ`ZX\RRLPVVLXNHZXVTdNHZNRPNT\JZFT^@XP`VTRV^LN`RdPZLDPPZbFNVVVR`NT^DPLXXNRJRNRPLLRPHHJTHNLZXTZDFRHXFXPFPZfPJR>DdTNFPTRXVDLJ\bPJLHVR>VdJJPNXXVP`VJJV\RVZPRZTR\PJNTJX<JZXPXXZPFNRHXZNB\^PXRHP\JXRNNRBNHVPJ\DVTRRJ^PLNLHJVNNJPRVJ\HbVR\PVNJN`NJdXVZRVVVNTN`J^VVNVjNLXZTTZJT\BbRTNbPHVTRFVNRPVVRB^PVLJNLTPXXDZPRTRRJPXX^FVV\LZHVNZP\LBJXPRNPRJBbLHbPXHR\RP>^TFR\^RZNbFPLLJFNRRPRNVTJ^XHFN`LFX\ZRT8TBTZRFZ^PLD^bPLTfN@TB\\VVPVN<PPLLRLZXXTTXbV\RT@bDPL`XRDPRFHf\BHHRZFLLP\LLFXRZRR^R`TXNFTZPHNZVBVNPLDZVVXTPL`JLHHTJNN@bHPRJTFPTJNNP\FZRBZX@JJRN<HTP^LPRJRRZL`VPVPHVTPNJJ@NJ`JN^^T|F\P`NJX<PT\PRRFJVLRRTR\PNHTPXF^LVNJRRN:TFV\P\RTHPL`TVX\VJhXTN\\H@<\RPXPXdVBRVFX>XDNJHFLNRdPTVNRR@NFJTXPV:\JDJPNBP`Z\@DRNRPNTN^XXZHBNJjN^FHX^R\FF^F`JDFJZTNPRRRZHXLHhFTNLPRZR<ZTTDHLXDRHJPVT^^bHJZPX>RLRRD8V\RV:PRZRHRLRXVBDbN<HZNXHNDVPXXVPDNVPTHP\TTXJRLLPPPF`LRDR\LZJVZVVBZTLRPXZVHRTNNNBRLLP^PXNNTRNTTLP^VZTBFJ`JHXZHTHVN@RNbLXRZ:TFPJ\Zb^RRX\NZRBFV`XRRdRZRP`PRPBTVJ^HRRTXTPXHXNPVXLXNLN`TPNHRPLNRFRH8bNNPLJhPLPLPRXLVPVVNBHNBJXZNRXV\XXRVXNZTXNZLL`RJTDPTXVTT\NFNJPXHLTTTRP`TZRZ\LPRX\TXLPTddF\VR\LLDB^NJPB\HZT@ZLZX`TNRRR\ZLB^LBRXJZTNB^P`Th^XFRXfNP^ZPRPZRXPRPLXPZfLNFJJ`FD\PPV\RZFPJFDZRRHPTZPRPZPTTNVXV>LhZJ:PDZTTRJZTb`TRVRV^VNPPXDZJF\:TBXPPNVLD^TJFRbLR<TdVPTRFJFDTL<V`BRXLRVTFL>TRLPXN^b6FXP@\JT\DZ8jHXHRJFVF^VfFTTHFTB@\8XNLX^ZZVTNRVXVLPNFXRPVFHZT\X>^PZXRPLd\VZTLX`NRRVHJ^^LBVVJRVJXZXR:H<RVDP\DRXLP^`B\JTJZNRNNR^XLP^FHZVLLdPV^FX`TLHNXHHP@`bHJFBHZXRTHL\Z\VTRRBLHLNNLLPTV\ZXL\NRRRJPRFXJLP^T\T`L^ZPVVRX>LXVXTBLVJ`bVPZRNTV`\J@R^RPHLV@RPNDPFNTPRPTJNRTJT\NHPRT>NBVRRHDVLFZFVPHNJDXNPRTbTZ\8XVTHNTLBHJBPRRR`XBXPFNRVJ^\R>JRTXXNPH`RN\NJBRLXVJN\FTTVRZLNNPR:NXXT@\LLX\LPLB^ZR<LPXXNF@NZTZNTD4\RXH^TPPT^FP>F^NDNL8NRHZHRTLNXX>XNN`NN^LNVHVNNPN>RVdRBNPJJLPNRTd\\NDJHTPJXLPHXFZNJJPV`JHHLHVLZPV|dDR\TLVRTVV\VFTPVDLVVDXTXJ^ZXR`NZVV\<V@\`JPRJX\VPPLJRJbVPDZNBPZJHXDZVXJ`LZVNTVXPNNXZVRTR\^XTHXTTRVTVRNJJ^LLNXVPRNZPLBPZXXRRJNNTRNXPHTHP^HTHRX@LNVTDRPXHDPVNFNXNTLZ`DVNXRNTbXFV`ZXVPHJVLTLVFV\PJHXDdRNFNVRB\FT\ZJfNPdNPNPJL\NPRb>X\RRPPFHJNbJNXBRPL`\ZLHZH\XLTJRRXTJZRdXFZN\JZHPRFRV^ZTNXD\<HHRLVPVXHPPVFNPNBNZRTPHVV\LXRFNXdVDNL:RLJLLLPPJRNPVV@XLVZRFX^ZJVRRTBVJNVF\RHXPdXTHXRTTVVFLVNTLNB`bJDXJBLPPB`NRTRLVXNVPTVPZ\RVLf8ZN^FPX\PTZbPTFNTX@BLN^F^THTXBPN^RPZJ\BF`HbRTTPTTVZNTTRT`TLTNJT^VVPPZPXLNNRRB\RZHNPT^VNPPJV\\THRBbZRTPDTZZfJVFJVT>V@PZ8^RPTTN^B@^\\NVXT<FLLRXTNHZ`NJ\LRFJZHPXXVRN`LZFPNPRLNTLTVNPRJVXNXRRN@ZNZPXP^LZFVHVVLRRFVZPJ\LTPT`TDVZNH\RJRLVRJbXRFNTTHXPPVRTRNXTTFFN`F`\XHRRJTNLLVBFTLNZFLRR\PNZNJH`NZVTRR\PR`RZTLVTZRXRZNX\B^XVZTV\DF<XRNZXFPZZ^VVf\X\VTFPJJNDTZXJbPNXTTTX`PRXPZTTLLPNHVVJ\H^ZVXH<fTRdLPZTX`TTZRXPFJ^VZTJPBZTL^TJNL`\XHTXR@BNLRZ8JLVJbRXPTNTXHJRXLZHRRRRNFXXLPRXH^V`HPVbXVPVZXRJXZT8RNR^XJLTV^LXHZRLNVTNHZ@JVPTLJ\PJX\TVPR>PPLLJTNLHLHT`L^XXhPfVTPdPRXXL\VTH\Pb`BTTNPf@\NVF>bTLHFDTXNVVRT\JXRThZZHRNDVJZXTLDXPR^^`JDLRXRLZV`BJ<`PRFVPhPTTZPDT\LRLZRBP^TJPJFPRX4LXZDVPFBHH\\RH`VFHNZLJVNPRRLPVLFL@HLL`V\JTLZL@NNLFXXNVXLNzZDRR\PXRRVb6`TJTJ`RPHVNV>\PN\JDTNPNRbBVDLNLXVTDNFJJLPHTFVNXXRhJPRHZDHHVRLPNVPZTRTRPRV\NHVNNRDFXLPLTTNZDLTXXTFJTNJ\RJLFXXPL\PZXLN`VXJHHVVLNXZRRTPJ4`TZLTXR\ZPXJ:PPVBNPfN>ZLV`JJTLVXNTL`XR\NP^BRJRVXBR^N\VN\HTVJX:NLVZ@ZFJRVNJTPRT\NLJN0RNXHVN^VJj@PPLVVRVH\RTXP>bTPVDTRJRNNPT@DH\F^NRJVLJJTLHTLTPNTDDRXJLLVPVPBDVRJ4Fd>PZ<V@TJXRPJPTLT\PJXRRFHT\VXbJbXPFJNLTVDNPP\RPNT@DNR:LBPR\LX\\HVFHVVVDRBNHHVPFTVFP^XRTNZHFP^DBJP\TX>TXPXP`VHVNDPX\JZFTTZTJJDJTZJXLZPRLXXLRRJXXLBRVXLJVVRTPRLTLVNbZZPT`\PZPH\NHFXPPbX\\JNBT`V`ZHJZNZFVFHB\RFNXLnP\`^PNJVJ\HLXZPPLNXLR`LVVR`P\FVVRXFZTXTDVFVPJZVRZRR\V`PZVL\`RPRNVTL^FFXXPVDLdLZRFPPJXVXLVTNF\LNRNFVNLVVHVRHZbVd^NL^bV`JbPJV:NZPVVdPXDRXFXZVNX\TJNL^LVXLVNPFLTT@PNXXLXVX>XVVD^ZDXT\>XFDXjNNZV<jZTTN\N\PTRTLD`XVPPNHNNNXNPT@TJLLTTVHTZXNLZNL@N^RNN`RZLHXNXRHTFNRDRFRdTL<X:T^`^<VX>TZPTVJbLJTNPLHXRbTLRR\LJRXNJVTJXRRJNTBFRNTH\\HPHTNTVZ^DJ\FPRD\RX\NRXNDDPP\PPZRVJXRPL^X8TF>DDBXPNZFPLHNPXDPJJNZPTPNZVPBNJFPX@JdDRNZN>VBZVNV`VTNTLTNJTbFDFZFTT\NVbLHJLXRTb\P8XZNVZ@PTPLLPH:\>NNXBR`D^RbLRPHDTZXZV^LPNVNPVVVZ\VVJTL8RP\PXPRTXLDRVHLZVTZLNX`RHJJL@PJRV``NTLHZXBZTTRHNJ^NXVFR@ZTFJTJRNNBLPNVRNHJN^bT@\RFPHNb^RF`RD^VXLTPPNZ@XZ\DbLRZRRJHJNLDTFRLdRH^JTPHJTJHN\VXTNXPL@XRXRTR^FDNXRPDJRFJTLHPBVFbXLP@PLfD^BTFJJJ`NPFfXV>VHVNPXF\XTNRNHL`PP\DLZFJPNHTHTXTXR\VFV\RXTDVR\JJTRLRZXZVTLH\T^RLVdBJRTXT`RHRZLNJNHN\N\X\FXVPTV\BDPXNNTZFV\BXV^:VFBVRZJFPZ`LH^TRJdR^PJ^RVNVPT>RPTRPJXR\Z\RhBVRXT^THLDLZNZZXBV\dVRN`JRNPLTVRLJRRPTZHNZNZXXNdVFX^\^JHHV^PPRPN>@dNb`R\THPTTXVTXHPbBVPN`LV^T^HXRTRLTTZP^NTJPXRNTXXXXDTPbPJLRHVZ@NFH^PVNZLTJPTLRJVVXJLNFNP^@@ZR\VJPLPdRbZDPHLRHZXXVPbd\NVHVF^\PJRHR^^JLdNXJVTZ>^RNNRTNVR\LPXLN^dTDVVF\LLNF^L\>FTPLNRZ\NVNJH^ZbDNRXVXTVH\HNVRDLFHX^NNXHbZBPbXXLZ@XJJPRFLPFPNLNLLZN\PN`HHTR`P`VLTLJVHXL\TH^^VJPL^RDRFXZNJLD^\FXPRFRHT`VPRPXNXZDJFZBPZDFRZ\D<LJX^PLV\RNXFZTJRT`LTLNLDR^XHPF>VPJDJTRRF`HLTJFLLH>`T@`HJRRR<LRPXLNTTNR\<RNPVVFTDRHbPNTRVBT^NPLHPFVTHNHVFJV`D\D^F\PVTRHRTVHNdJRTPP@VBP\RTLT>2RLT<^LP^NNJHRJPPFLNXNLTJNXTRPVFLP@THZXLLZVPNNXTTHNVVNTPNRJJ^BVNTVPBTLTRXRHZL`B^JJDRPX6NXhLJJbPHV^F\J^JPNPDNTNNRLRLXPPJNHTFVLRTT\PTV^FZ\ZVP`ZXLL>N^^JNJZPRNPNLhRJTTJRBTZR`\NT\NXT^HVNRHX\RHNTTRTRZRLdbVVLR`JLZLNZRjHRVBZXRFRDHbJ^TPNTVXPRDZVRB\NNTVXPZBPTPLDXJPPR`P`VTZPNRVL\JVDDPPRVfNHVVLRZTTT\H^P\PT\\XN^NHVZP8PVRDNZPFPLTVFZTTHP^ZPNVdTJJX:RF0JNRXXXZRdXTZLTZ\LPZVF^VPNPFFXVXPXFJ\>\NLP@\TLTRFRJJR^D>VLPNN^TLTJdfN>P^XRPV`PXPVTTDPPVJPTbXPDNRRBRVRPVZVVDXPF\LVXX\RH`VT@d^THVZR\L`TLR<NRZHHV\\\FL\PNJRJN<\B>@HZLFDNPLFFTR\RF<TXTPV`>VPLXJZRN<NNTRXNHRTRPVHTVNJZJRFFHRHPVFFTVPJPNXZPT`FXPNXH`RVTJBHJX@lTF\VFTVTTVNZJV^@NXPXZVXHXVLZVJRPVTJ^PPRZBVRFLVZRJZTPPZRRVXHTNRNX\JRHPJXXTHfNZVDRVTRPPHNbDDRJ\RZNRPNPZHZ@FX>TLPV.HF\PXJT`TJHFLPRXTTJRLP^\@NNPLRXPTHJXLVLJJTRJ\LXRNRL@NLTRF>\LJdVFJFZVTHD\`VBL<NNFLN^DXLPLR@ZVTLXZLTLFZFPLRZJTZP\PVPVFTHHVTXN^ZFB\DFJVLHDHPZV\XJPR^LV`NJNRLF`PR\HPLBPZTLNJBTPXXHXPbXVDLXJTPZJRTRLBNNV\F^NTR<JJHTTJRN@RZ\DLVB^TP^NLNBPP\PXDHNLXTLPXTRFVJFH<TFJPDT`LZNLbRLZRT\FXXVXNRXFZJZRVPVPBV@RNJFZJVJPBZP\NJRLZZLZR`bVXPbHPbLBNRDLDNVTL^RXPXXRZVRbJNTRZ@\RZXb@bN\RfFLTVPRZVFFRZHL^LTZVVXXXRN^T\ZDT^LR`PVbR\DFV\XXPXTPHLPR\R^PXPN^VLRVZVVBNRJTXTFfNRRTFJPXRZPjdTZNbjNVJNVXNJXVbVPJ\NXPTRV^Nb^ZLHJVJXHZV``HVLRP\<XPJRb^R^NLJHbPbR`TFTRVBXTZVLJVHRXNNVFJfVLNHPV\>@bP@>XNfXLNR4NDLZRRVdRTDPXTRTVJP PNRLJVPRHL\FbZ^DRHPRJBVTVJJTRV\^RTRP\XLXVHXRLTR@\LTTZVVTHVPHV\\VTVHHTHHXXXbHJFLZNDD`\TVHTJNRTTVN\bNZNNHPLJPXRJ`TNPR^N^RVDdH\JXPRRNXXRJ>X<JbVJ`VNPPNTVVPN@VZBVLHVBNHNVDJRLZNFV>FPRNX`LHLHL8LLTPVLLXN@PPXPXTVFNR@RF>PT\NFNPLNNTNTPJLTZ8NVVRJPPDT^NRFLTHNFTRT@RPFHFXHTRJXTPLV>`:DDDFPPFVVHPLNTX>^RHLZLX8\RBFLPJ^TNDZ.VPV<JPLXTNHX:JJTHF\N\RNXNRHHFJTPFNRLP^THNVZXH`DF\VLPTHFV`L^NHT\ZPJNNFJPZHRZFZVLPPHPVTFH^T^HLFLLRNPR^^TDRTHT<NV<X\HRTNTNZL`JXRPJ\NHTFVH^JXNbTJJLHLLZRNTN\XJPDdRbNXNJVZfVVHVRXVJVVTBVHPTDZJN\F`D@XXNPNTTXR`LJPN<LXPJ\LLXRXL`FJJRXTRJ\V`Z`FTTHLHPRRX\B`TPVNTXR>R\LJJTZLRXXLPTNVRVNVFXVVTPbVRVFX`RDZLLVNL\LLL\^BRVNRLHPV^@^FNRPJNTV8TTNRPTJJLNRRZLTTRTVXJRTXRPVVFXTTPdVJDPFVPRNDVV\\HVHPNZ^XFJdJZR\P^hJVV`RFRVJ^\FBXT<TZTLTBVZX>VTNNLXXPJR:RTDTPLJTX<NNPNJXJVNLLHNVHVTXZXP\PZRDVPBPFZLRHP@PPRL^R`DVTNZFP<HPNdJJJN^TTTXLHZFVJPPPT^NDXVRR<JPDBNFBTLXTTRVP`XJTXRP>H\TJD\RZPPRhFbNPRXNNTFLNN@^@\PHZT>dJT@ZNNJ\HF`PXRVN>LRHTZNXX\>\JZVBVRNV\XNZRH^<TVDL<JNNP\JLHNZHNRJLVTVJZRFZ^TJVHRRF^TNBTHLFBHVRFNTLXZHHRVNF\TXPTVVTRHTZhVP\>N^b^VJT`^JRDRP\RZXNZNRPDFTJNZJPLZJTN\HPHTZX^JVPRJT:LRT^HT\X<P\RPPHF\N^PVTTBLRJD`LDNP^HX^\VBdPJN^XHVTV`RFN:VZ<bZNPB^RbVNLXBDV^R>PJFNPbRRRZJFNZPPJVZZPVHPXLLN@XHTPJJXJ\PJLH\ZPRTFVN\PFFRLVPHN^TRR\\XHfNLZVT\LJRRTZX^PLLPJRPbVTTDHJXJR@JJ\>\PXPLLL:PRZVPRXNZZRHNNHRNRLXF@<LPPLHXXJ\FLTJF>PLTVNJFXR\>@^TLTPNVRNLZJJNXJVHRTRTXXTV@RL>>T^RFNJVDNTRFH\PPTJFNhNL^RLHVPLRPDF@`>ZLHPXHNHVHNTRL@NFXFLHVLLZPP^H`XTVDhDTVXN\HVDNPNTZVRTPN\NBNR^XDTJJZLPNT\JFRVNVLRLVZ\VVXTX\XRPN@DNXVZHRVTPRRLNXDPRN^VXJZHXX^RVN^^\VTNBZT`F\RRZNFFbNXPT^FXPZN:VX^JXNZZXFFRh\T\PNDX`ZP\JNTFV>PN^bFPJRLV^NTZVLLTRRRRJFRFXHVPRZNRP`NRNLVDVNRX^ZVPX`JlJT\XLXRTXRXVPLLPTHPRTPBHFHJLTL^JRJTRXVPPZTPTHTR^TPVVFDNTLbH>RDR@BBFZBNVXBBFPRLJ`TNTZTDPNXNXLVdTZRRVXLHRPZPXJZPNTNTVXRNPZZ<ZLR>ZRXR^HV\HJNJLJb@HRFdLZTNPXZNVXZNLPNNJTBH8RPRVNFRHP\LDZ`@FXXV^HNDdPPNTDP^LX\>H@XTRXJHJPLL\DXZbZJP<DLNHHTDJZZV`:NHRHLB\FZDRX>PTRVJTHH`RHFPPZNPXPRFNXPVTHTN\L\RT^PPRXRJTVV@LPRNJLXR\LLTFRJ\JJTNFXN^D\RTF`TXJHdRLVVNXRDPRJBXPVXZR^DTRXZ>\LLVNbHXTRHVVRVRN>PJNBRNRTXXZFXb\RLLR\ZVH^ZHFPLNT\\PZJXXNHP`HPDNF\TRF\NJRRTJDZ>PTTJJNXHNTHHF^NTVLHXRJPRXBRNNJJZBPFD@X`NT\TRNL<^RXRPNPLDPdB@RHPLZVdH\RZRPLH`RTZDPDNPZPL^HV>VVNHNXRXFNTJ`PZZTFZNRLTNRXVF^DFNN\bBPLTJHNHHRRV:JVR^JTNFXNRHFJTXVHXLVTLRNHJNJ\`XRRVNLLRNLJ`ZH@XTRLVTZHFTL^RNRPX\BZNXVRRPJ^FJLFXVR@LFVHDJ^NPPR\RXHJPXLVNZPTLXPFXLNTZNTPHPTFXRN>TJPTFVTRDRRRD@\R<NPXJPHXRNLZH\XXPDR:TTTbPTRP\`RdPJXFLXJLZ\ZRZPN\ZPL^PRRLRTLFHLRVRDJPHV@N\NFLRZFFP^LJRVX8LZRHPLPRPh\XZFhJ^`^\V:TZLPJNLHHDXV^X^ZDZPN\JPLLBVPVTTTJJfZFV\NNTXNTVFFNV\NVJX<DJJR\@TJNZHF`PVXLJTBTRHTNZFPRLVPRVRJJVNZNDVTLVRVRFHNTFNVXVRRDLRNRVTZPLXTPTPDPZNXDDVPTJVRVHRZPRPJRRTJPVB4ZJXFbZFVT`LT>VXF@RHTZPR`L:NT^LTRdPTZPFJN\TTP`\RPZFR\L\PfBJTTZHPRP:@X>HJRT`ZXVbXLVFRJTdTJXD\ZNPDNVPNVNVHVBHVLHVXTPNTTFPZPXNZTNZTLHRRR>VXLbHRPVDZPLPPRXJ>HT\Z\ZNN<BPPRLRPDVpJTJHNDZ^NTVLVTRHTTFLXNPNF@PB\NVHRRNLNXRPFRPBJVTVHD@NTRHLNHT@PTb\RPRPVJRLDZ^L8JTPPTNPFLbJf@RB\LVJJJDJXP@TNBTZ>XH\VHTVNJN^\V^NLLDLJTXJPRHFJVPLL:bPRNR:@^JZNLH2PVNTXVVFRZHXFRNVJRLHLPTHHVLDXXHNDFPTTTZXfNVFTP@NNPF@RRR>LVVJVFVJZbTNRTLPHFXZXXNXDVNXTJP^JF`LZFV^VR``NPLNVZVXJXVJLLJRFFTXRXZPLFZHVTPVNPVPXNXRRTPTHJRJTZTZPTZHF\XPBRDZVBRLDfPNPNTJTVNTL\RZRXNDRFTL\VPX@`NHPRV\VXZTZXTZD\TXfJXTVLPXJRVLLTP^RPJTVR^TBJFL^`^XLF`LP`VBVTFTJNRVZVTTN\\BZDNLRV\NNXT`NJVH\TZVLZbFfPJNRZPVTJPLTLVZ`^fDLPRVNP^DXF8VVVP\hXRVZXXVVPTZZLbRVRPNHBRJHPNTDNTB`JTJZJTPXVLLJ\DN>HTHPXNZRFZNbNDRD\LPVJNNNNHVLXRHL^PLJPRX^TXJPRVZHPFXVPPVPPVVF\R`XTTN^LHNFVLVRJR6HXFFXNRPbPL`HPLbNXRTT@VDX<^@FFT^:TFH\RLPJZNR@RDNRXNXPZNXBRJPNV:^PNFR@P\8PTTNLHXRVB\BHXNXNLNRZN^RLXRVFTNV^LVDVLJND\DNLR:XJRRPZLVbDZNTNXFVNLNTXRLHZPZXL\RX^PHbFPXHLRRHFTXRRZVHXPZFJNVJRNXJT\FLXTZNPRPPLJLRHFFVRTPPJTDd^RLV\VLZ`FJD\HZX@ZbLHJHRNTTPTZNT:JVPPRN@DTHR\^HXPLXHR@Z`VTZXN^LPVFHPN^RFLL\LV\TJLLPPHRLRNTNVVBXV\RXDRVRRVNVPLP\FNR\PX\LJVBRVFF`PPFX>ZNLDPNLH^DRPXTVRXVNTPN`XP@TL@TVhTT\JZTZVPJVF^PNJP:NTLLJZV\FVVV4^\LZJT\JHVVP^LVXJN\PXXJVFPPTP>ZBPNFTVF^6JXXNZLLLJN^BF^JRLVLHHVNNDHLHPLTJLR\>`DPHFXZZBVJTLLTPXLRLH>NR\PXXRNRVV\JXNXJZH^@ZRZNF>ZPHZZPRNZTNPVJPPRVJBPRdPL@NPVVVPJPR^JPRF\HRRXVHXJF`VPPLNVXPT`XVNVJLPXHRTPZNNRZPXVPTRDJ@RTXTTN<^PPRLRLNPTVBRXJPXJ\HX^HL^T`XF`PVZRX@ZXRP\NTNTL\^NLHTNRX<R\PTTRZRZ^JLLJRTV\PLTTX>LRLJTZPRRLdR^JPhXh`XTVP`LPVRXLTb\LNFXP\BLPPHTJZNJVHXHL`LTJ^bRZRNJLR^JLTJhHLZVHN@^VJNPLF\T\RLXXLRJRFZ\VLTFVF>LJHRPVZRTTLJP^P^LRR^HPdT>\T`FLZRDN@PZR`VRL\RP0XDDT@T:XVVXRXDTP@LP\VNVVLFXX>ZTHNBRFVHVV^NVFXVBXLJPHVT^VTZLLTTXBLTXTNJVXD^DZ@P\NPPPR\ZFR`DRR@NTT\RXPFLFH^VBNRRXNNNNHFXRHVRP6RNDZ^RH\:N`\TP\<J\XNLPLJ^LPPRdRPLPTVBPHXLRR\ZHL\ZJTF>H`VPPZL^DFJLL:ZVRPV^RTTXJdJRTZTLVb8PRTB@VLX>ZTTFJL>X\PVRJP@THV\RNHJZLJHLZPZNXNZHRHPPTHPHRRRNPNVPNJVTZLHRPZLXHLPLP>F\TRRZZVPXZ`TDRHZZHXNRVZBRTJLLRJHHJNVFPNVRXTD>PJRL\LRJ^JNLJBLHNRTTNHHTL^XPLTP^DZJHPPNPVbZRHJ`PL`ZRL\bLRVTPH\LLVRXVZLRFVLZLPBPP@DTV\LLTZ0TVNTBHTJ\RN^N@LT\BVHRP`RRNRT^V\RZ>XNH\RNZJhPZZNVXLN^J`bNHFPXdR\RXLPVRFVRV^RN\\FX>TT84BHXdJfP^N@XFVTHdTXdBRTRPR>DXPF\@PJPdXFNLZZTR\XBTLLVLFPNZ\<XH\^JT>PJfVZZRFDN`ZR^PNPVJLTTNXP`JHXNVVRLX`\TbPNZN`HLT^\RXZXNPNRVbFNdLVFRJVDT^RJ:@TZPDJZ\P\TJBTJ`JTRFLVPL^b^\^hPRVTJ:LH`N@RL^RPTJVVZXZFJRPZRPXTVJ\F`HPP8JTbRN^JPH\TPZJVLN\THHZFNRNJ`R@TJVPJTNJ>VL\TXPPXJPL^BZJPR>HVVXZP>RTHRH`HJZVHT\NDXXLPV<PfDFTRHZdHVTT`@JLZNHLN\NBJTFVLTNXFXRHX`PFJRJTZBTLVPZBVVV>VTPTFLdPTNHPPRH<L\PXL\<HDRVJdFPLRPJPd6RZHL^VXRNLVZNDNNPRFdbLJXHZVZHHFVVHHNRNNXTR\RXLR^VRPLRDZTPLPJPNJZXNHXL>R@JFVPXDdjDPXNNVVV\PR@PRPVNV^HL2PP^^Lb>H@PLNPTbXJJPZDL^JNXZJZNRH:NRNXDVP\NXPZPbHTTRNBNVLVJNNP^`NPNDTFTTFD\JXRZZLNFJ@JPXPX^@RNNRL:XFN<VXTNNLTNHLZBNV\>XTRJPBDZPPNR^HNXND\NRXLBHNJVJRVNVb^RRLRBJDRJHNJFPXNJJPNXJZHL>RJVPd^NLLLXXLTLHJLTNPfLT`P\HPNJRHTVRJJ<FHHPJNLRbDRTLPRZVNFJZPTHFTLRHL\NLXVFHBVdNNHRZFPTNTVLPTRTXZ@HNZLPBNN^`^LFNX^TRLNVDVR\JVN^ZLBPPFTZRJXXLNZHPPP\RLVXLPPVV\X\\VVT^@JRJNZ^RHHR0V`:VPLFHX<XNZPD:NHPZX\TPXNLBTRJPNLDRZTVHHTDV`TXbLN\PVP\PFXZHBLBRBJHNJP>\DD>N\<XTR\BNRPNPFVRXVPJNRX>VRJPRVT\RNJP^XZVRBXPbPXXXZPTPVTT\V^TTHP^RLFNLNXDJXLRVNPVLF^ZLRPVTTRXRVPLHVVN^HPFTJ@J\RTVZRDP8PPFFXPJTLjNVHV`dRPPVJRVbXH\\FZNT^JRJLTRXD^PJJ:fLL\^:`VXJVX^R^JRDLRVNJXT^JRX`JNPTTbDNRXFVVPJTDNPJFXVPRFJ@NTVHXH4PH^TNPPN\V6\NL\PXVVVNDDNbDPXTN^VJZV`JRDVLLXRNZHZVXD\ZLJ\FJNTR\PXVDFXFXVVJTJBZPLLLNRdVZPZN`LJ@DVVLZLVP>R\LV\TTZTZVHVTJ@VLPNTRJLJRVDXTNLHJHRFPHHXLFXLNDLLRHLXLLVVBXJL^^JNRX>N^RLJLLNFFFNRPXLV\LTXFTVFNTHPVJZXJJhTVBTHJdJH@VRPH`RJTT<JVNPBRRVXLTFPPRXB^V@HP\PPLPVRNV`X8NXJX>TTT\HVRD\:PRLLJH`NJVTPFTLTBLRVPHDTRT\NPJPF^LRZ>NhPPHFNND`ZXNF`VHPVNTZ^\FJ^RDTBNTTRPDLLHPPH\ZPJRVPVVPZNXRZPNRRNXLTFFFTDPRXRLJRHDNPV@PZLVXPHLR\fNHHFDPPNVNH^PNPPPHRNLJVHZDLJ\L^NF>RHfLHLXZJLHdLLRRLLZNFLVNPJX\JLHRTRPXRNZTTDPRXLLFB\PLRLXVJRPP<RHLXZLNRRNDLdHHR\D^VLT<LLR\DDNZLNRFZJJ`VHRPPD`ZLPbPRP\HZFTRNXTN`JLVRH^RZR\XHN`RR\PbDVVZFTVPf^XNRF`JLNXZXRLPRJVLZFXP<\PPNVZRTJTHJRLXNXTDV\XXdTbJVLRNTZP\hPVXHDVHLNBXXRHPPXFPPLTVXPXZRX`JXTPRLdTZPRXNJTVTPR`NVRTRb:LXFFJVR<PRVFRLPPJL^LJJPVL>VLVVRNNNBFVRTLVLV>TXLRRXjHXDTN^BLdN\ZZVPTRVPTT^6JNJFD^PZR@JTL\6LZ<FL@LXDNB\TVDNPL\LTLJPXLBXV@B^RPPRDXLRFJ^LDLFJRFR\Z@VLXHVRJNTVZTTFRHJHPJXJRHDRVZ\TTRNH\`HLHVPXLNPDLPPBTVPLNPNHRFJN<LJNLFHFXZH\\FJ\TbRHLLHNNHNXTTJbNb^DVTPFVZFTD@JZPRRJH@DNRNJTLNFN>8RPRRXJTXJPPPJdL<<bVPPT\PHVRVNT\NLbBTHRPTL^LTLT\^JD\RP:P^DXRRHNPP`NZPJ^NNPNHXHXFVbNTRPX@LBJTBFHZJPJRPBVNJRVFVNZVLB\XRHRZTNLdFNVHTHXLBHVRLNDVT^BJPHZ<TPVRJXR`LJVRNTXN^PT<X:PHX\VVRLR\@VZN\N@ZVP^ZPPRXLXPN>PdTN`P>LPPHZJZ@LNPHT`ZJR`*PFXNVRHTTT\L>RHLNVD^H:ZPZNTRFDZJNVZZHF^THZ^RJFHNVTLNNTLLVTNTNZ^VVFTPZ>FNXXRFJTDLPL^ZPJRXXVHT@NZRRVZbX^TNXV^R\LZNHVNLRJ`FZVDPXZRTRJRLJLJZTPd\VVRXTXJPZRLN\R@^RXJ^T<NR>TLZDH>NZXDXRTLXVJPjRVZ>\ZXVF2H:L:LNVFJlZLRTVTVFPTH^RNLJH4NLTbXHLR^TPXLDVHPHVDJNPHZjJNTNZRHH\R4LJNTNB<`R>JTDTVLZZXbNRPRXXPNBVbJBN:R\FT>LLZRTNbVT`>XRFNJRVNXT^JLVJJNLLPPNFJT0HBNPN^PNXZZTH\N`TJHFVRRJZDP\FLJTVFVNVRVR@X\JHBBRDNPVTDFXRHRVPV\X\XLNbFL\LZJV^LNT\N^RTXRVFTfVPVLBVVNZ\JRPLDNLJPJPNNHRVRL^PLHTNR^XRXNLFXJPZNJRFJVVLJVVHNFPLBXRTT:DRPJVX\HZPPRXLXRHPPNV>RTXPVTJVZR\RTZTLBPTZ\RZXJTNJFJVV<NJVT8RVH\LHB@TJNNFJVTRZLNJbHNVPJP\PBPRZ\F^RTHJPRL^TNT@NfFRXVbFPRN>DPXJPVTLRFPZFJNPNJPNPTTJRNNPHZVZJNVFFJZDVJZNXVNHVJLNV\ZRV>X`8HNDV^PNpDL\RRJP@N\RNPDVLJPJXbRRJRFPRLXlTTHDZJJV\PXDHRHNRLFTNTFP^@BLX@TBTBXLHNZFFV^FPVH@LLZVVFRNV`JNLHVL\PRNFXVTTdLJ\^R`RNTVXHZVTRHVdPP`NHVLNLLJJN\XNTTPTBZ\FRXNJTVDZ\NRLF\HVTFh\\ZVZVRVHDR^F^TRX@TXTNBHNNJHLDRHXJNJNVVHLPHP8LH`TJHT<HNLVRNNTRTVZVPLJBFTPVTPJRR@XXFXZXXZ>dFPhJZPBLRL^JPVTR@N\DNLJZ@^T^@XHXTLXTNPL\FXXVLZZPZTNBVJZ\VXfLXNX<LNTP\LVZRPN<PZJ^Z\TTTVPT\\XRLTJVHVHJVZ\DRP8TRVJLDRNB^ZHNXTR<\X`PZJBPRFVTPZTJ`H`H\RN\bVZJ\RbT\ZDPNRHDVLVV\RD^R>ZFZVVVX`DXJNRF@PFL\PVN`TLT\FPZX:RPZXPDR>DTPVZZ`V:FHN\\FN^NV^PZPDTL@VLNRNZFTXXHLBTJVFV`LNZNPZTDLN^JTJLNTLHHVPFT^HHPJRHDPPHNTDLTVLbH`JH^DV\PLT>\dHZRNHDDXNRLL>PLLJDJNFPRVVJ>LVXPPXD>NJVFNJLNRNBN>ZTPVTVTLXJ^LZN\BTZDFTPLVNBTLXRHLTVJXL@PZVNDNXDPPFLTJ<>FTX@ZBJHRLJNJ>BZ@^PZNJNTFDP\N4D^ZRN\PXLLXXLVBVH^HLJ>LZL^FLLbDXT:RXDLRNPZNZHNXPJPXLLLRNDPJdHbDVXRHNXRhJJVXNTLTLV\NNPJRX>TXLLVNL\JNV:XTRR^RbBNJVfNRNXZRZR^NZRDDRPTZVNNLXBBZHPHVTPTP@ZP@PLRP\F.NNTJX\J`8NLN\\DNNHJPHRHL@LJRPRLR^JRRZTTFPHVBBHTLZHNRLDNV\RTFTP@XRHLFd@TVRJZVFNDNDPDXRXPTPPXDHRTNNBTJTHLDZRDHZRHXL^B`ZPZP^RRXRPZRPTPRVNDHFNNRPNVBPPXR^bTTXDNPJN\FXJXRRPNVJPPTVZ\TRRXVNZ\V^LJZdLdNbXbRRNVXPT^J`LP>B\ZHVXhT`NZH`RPDZT^hNXRTLR\L`FLHXV\TFNHNNLL:ZTVJNFTVNRPHDPB@HPTRVZLXFB8NHJDPZDRR^LLPZNJD@\XD\PLTZ@JPP^`LP\TFVZBNFDJNTPTHfDNHX`NPPNHPLJLT\RXb\NLBTJVLRLTRTDPFDX>ZJTXBXFHLNPXLX\JHLTNNZPLLLZ^HXNNX>LP<LPFZVPFRRLNNfPZ<BNJHLDbVLPVNPDF.H@\RLTXVN6XRPXXRRLV`ZBV\R\TRJNPXJXF\TDVDVHVPPLbJRVTNFLVPJVRLVHJVJPJXRDH^ZNJXNHVV\FPJV^NPNJ`FJXP\RHHRFZTNXV>VHJNLPTXPR\<H\>BZRP4PBZNN^FPVVJ@NT\2FR@VRTJTTZJZ^JFNPJHJV`P>NZFHRNTTDT\FTPTNR^P@TDRZRNPZ<ZP>TTPHHXRZbLXTTVTZbVT@ZBXNZPXHLLLTNN^TNRRHRPHDXTNXTNBNJNRFND@DRbVFXFZJ&PNT\LRTTLLHNL^FZ@RPLLTHXJTL@NPJZ@bHLTR\<TXRVLL`\DTP`VDLJPBNHNXLDRRNVNPVHFLPBFVRB@DbLL``RNVTDHZJBD^ZVTZTV@DBNRTZDPFDR^PXTLL`VN^LLBLPRLL`NXNHXZD\Z`\HZVDPXXNHRV@LHNDJPVT^XRV^JHFV^>\JHTPRPJNFlZFXV\RTJND\DTXTLRNXPPPRPfHJVVZLPBNXT\BRPTHNJJDFFHJZLXXRBJR\VT`XR\P\J\FTTVJ\VVTXPZVVZTNVRPTVPXLXLZVPJFRTLHZPX^^XRPR^FNL\H@XRD^NLVRLV\TbXXZP^TJLVJDXRRZR\RPZLLPPPVTDTRHHLTNP\XP^Z`ZJRPX\NT<JPZPRRJVPZL:PNVFZ>LV^RT\VRPFPZVTJRXJTbRZNZXNLJTRTJR\JRN\JJFLPT^\TjVPPXRDVd`VNPNDNTRNT@VR^TLRRFbVPLXLZVL\HJNNRTNBDPPJHR\VLLLHTNVFTLFHLNV<^BRDPTTJ\4HLFZDVHPXZTJLLDJ^PXDZLN\NPTNXPFTRNFDPHLXZXLVF<F\BLFZRVVBTR^XTVRRRPDXND\VRPPNXL6NZLTJRV\FRTTVF\LP\>XRTVJ\XHLRVHDNLZPPNPDVPBTNRTdRR@RX4XPP^NVX8`XTJDVHfZPZRTXRV\8>JVTLJVJVZTFZLTP^HTFRTTNTPRRXLNLVPJ>HPZ^TTHJTTJTHNXTXPHXPLLJ\VRHPdLTJLH`XFF^TXJPRBFLPX\PL^PDTJVFPPZLFNRJ@\NHTN:BTRLVLVHLXLHL@\RRJBZPLZZBZLLJ2LZB\RJVPBb@F>HTFV@VZP\H<RPDVJXNH@XDXHRPLN`VTTDXVRNXVLDBLRTRPJNd\BLFDVHLTNXDRBLZLTLFHZNVJTJRN^PXPBNHJ>XJdLPPXTLLNVRZPTRXRPRHN`ZXjNJL>NVND>PZRDT<Z:\JR\PNNBLN@`DPXLTXLT`V`LLLT>XHPXRLFLbPLRL<PJPZJRPZ`VPHXPJF^NPTBVJVJPP\PN\XJJ`LJZDZPZXRVR`HLFNR\FVLNJVFJRNTFTLRTPLJVB^PHTPNJT>TJRPLdZbNLVZLPN@LFVNTL\RPH`DPDXBTP8TXPZRXVTHRL<\RNDXNLDJLXPZBVBDfTJP\ZFXXZVD`TZ`^PDRTZBZ@R\HRJXXdPN^TfRXVDXTVZTL\NJNR@RBTHLJJRPTT:TLRR^DRFJRBLRXPNNLVNVJ`fR<LLHBPBfNDNTNFRXVLZTPBRTPF^RLX\\PNPBNdTPZZNP`VPVTNFZJVJVTRNHTfRTNZLTTjVNRTTRJFVPXJRNNJPJVPPRHTJLRZDTX@RNHX>\JXPR>NP\XFFLHDTTVNN4^PJ\RRPXNX>DVLJBJLXH`PNHJZB\NHNTVDNLTJT\VJNJB^XTTPTVD0PPTZPNVFTPPLNF\PRZT`HTLZVLNZVXRVNfLLFFDTPJN\VPTJXNRRRBJTNLPTXZZBVHLTRBLPBVZ\VLNP>^TRXJ8PbNDPBR\TFLBJDZPJ>XRXZNPNJRVFFLN>j`H`NPPLVDRP<NJFPZJLTL@\VRNLFVTJZ<DXPLVPVBbPPVLB\PFJP\LHPXPPZ\NFTZJVL\JXRPVL>VVHLJHD<DP>RVPTXVNLT`T@FNLNBFXJTNVLFFP0RTJTLBZPLLNFBPN<FDRRRXDFXLJFBLFNZXBLXV:VFBVLBT>FPFT`NPZ\NVVdVNDRLPTZZLVTVH\NPTVPRPLPZFVJTNTTJPPRZNPLZRPTJRVP>ZLFRNRLRV@DX>TJdVZTLN`DNPDdRZL`RHb\FZHZ\\JRLNPPJRPRJNDTJVRZN`RFL@XHXVNLLPV\TFZF^NLXZ^PNXVVTRPZFBRJN\@XRTTHRVLPNTVTV\VRDTLNR`TV^LPHTZH>TNhDTLPXNPRHZZ\BPFdBFR^TRNFJ^V`NHD^@RLVBbVV<XVTLHPJNZFZ<BFDfHXNhJLTBLXVR^ZH\ZXHPRTXNXVTNV@\LZXLDNNPPXJL^TLJZ`PVVN\VFPTHPNLTNXl^PXXRVhFXVRV^dTN^VXLVVHJ^NRXHVX`^`JBDZRTJJHHTZJJ\XTR>JPbDVXPHRZLHLPLNR^N\PPNL<VPh@NPNTR`RPPVFRXLNLNLLNVNB@`V@PXX<LPPZNBXTNJZJJRVLFTRXTZVBZLPFRXFPJFHTXNNNLFLVL\TNRVV\NH4XNBNJFNT@\J\VVJHDPJHZ`PNP^R^L@FVDZVHXB`JRHNL@ZLRFXVTNDZ@PRRHNZJPLNRTPRRN>`RL\^NXXVZFJJTVDNNPXDLH^JLRJRVTJLLPPPFZT^HRPTTVZXDPTV\HNNP\JTPh@LR<JPXVdXDLPLPdXFTH>ZZLRL\`@RJPP4RPZD\RRTTTNDPRFJHNHXVLZP`:PbLZVbRXFBTJ^NNNTNFFJP<^NFRXTPHJFPDPPH@N\<VNDVVXLTZZXHL\NDVXHBVHPF\TVXFPRJ\@NLJHHZNT>JT8L8\H\V<T@ZFRXVPRR\bJRHFNXDPNR@\PFPbJPZPJZDPZJL`DVJNXPPTLX\BFRNNLJR@XHT<B`HRRBHXJDPJ@PZTDVXLLZPRTBVLNPDLLXZZLN\LHVHJPDDLPRRVZJ8LTRPN`LJF>VJFHXHPDZZZR\BFTL^JX^PTPFNDN>PNZDRTHVT^ZZFJ\RNPTF^TTFbZLJTRRNPTPRZFPR\NNFTHJXHTRPLRJNLDLZTRNXR<NDRPNRTPPLTZJBLPLTT^TJJLPTJVLPN@DNTPFVRRHJZNLLJNLLRRL\TNTNV^RXPbLXNPX^NP\NNPVFNXZPLD^TRXJZXDRZ@\TNZXJVbR`JDPPXDJPT\RPfX^Z\N\LbL^NJTXR\RPBTHPDLPZ`VLRVLZZLTLTdXVHHRXNRVTHR>fP^T\H@PZXZZFXVTLPTJ`VVFZVHJRTZRPXRRNTLTBbRNRXJRRRRLRVbJ^JXNPPXHPfNNV\NP\NT@NF^RF^\^VPZPNHXNNLHX`NPXDNTJJD\HLVJLNTX<RVDJL`HJNZ@LT>V*P^JZLNNVN@HZVJH\BZFJDPDFHPJHX\ThNNRNT`PRBRNXRNFLPZNNPHXRHN>VVdTHHTTXRHPR\:XNR^RPJVLLV<NFNPNLDPVXN^JRNNPLTTNDPJVFF>bNLFHFTBL\RHJPJJNXZHVX<BTTH`THXPZJTRZXXLNX:VZT@@TXLZPJFRTRJF^F\N^X^,NF<JZNLJBFN<X>ZRN<^JPNPPTBTLV\VNXJNRLVBLNJLZRLBRbHVBBJFRRDP>RTLRJXT:RTTJNN^NLLZZ\NVXJVNPNJFLXTDP^JPBRBVXDPHPJHNJVRPTLRR`VNRHR<dLHFH\\NT^VLHNZH>Z<XJDbTNXTLNLPbNNVJXXL@PXXVPNLN`DVLRNLRNRLPFDFPZLJP@\JRNTFHDR>XPVZJLV\NXNZNPHRH`DJLXDNZTHVRTVXNPPHLJFRPJRPPPPdHHRNNNVLDN<\XPRVF\TLLLHTNXDBR\FF`FJRFHJLT<PTLLfDZFXPPFVPTV@HXPRB\RZ@BLTT\TJRLXHVTZXPPPNDJ^HZXXXX\P@^LTNR`PPXFRRHFJZHNJXPHTPL\NHNPPRPFLVRfTZRNHPRHTLL>ZPN`\JPDPDP`DVNbPJXNF^LXZJH^NXJPVNXT`PVBNR`ZRJZPBVJZPDJL@PJL^NLLLLTVdLTZ(JR\Z`@RJJHRN^XZJZD@PLXDZJDH@^RL@^\TVTNLNLVLNRFRXTNHHJLHPNJbPLNTFVRPXXJJHNRRLDRFBZPLN@PVJT^RVDJPDPFPTLLXPN@BJBLTLZLNTT>NTLXPJXRRNNVHLVXTJXZVX^VHLXN@PJJNJ>BZNHPBLHJVJH\NHFLTNXFLRTLDZRXXN\RNNJLRPbXP<VXLNVJXNNN>PPZZTNBPNVFTHLTTR:>LVLHFb@\`HTNXH\NRXJHDXDPNPTNZ:@VZJN>TXdBPNPLTBLRPBLPHZRJTR^BZRFRBVRPPNXPRBLFDXLXPNDJPRTZFVRJPXRTJDV\TFRJNR\JFNXT^JJPXBTJVBPF`HPPTN<NRT@T@LDTFNLFFHFNRLLVFLDRHFZJJDPNNXNFXN\NRXPRFTLTFZ^\RVP^J`LZNTNL^DTZVbNR>T`@XR`LXVTPHNNRRNXJTBJFXLNTZJZL@RJXPHFTRBPFDNRPRJNJRFVN:PLDRTLZTLBNVNLR^DTLVDRBTZNP`NX(`ZHJNZZP@RDR\@LPVXNLXLVDPZHXJZNLDVJT<TZFNLLNNRHLJ`JPRRd>@X<BPBZJ`JNBRN^NFVHRF`FPNFNNHRHTPDRZTJV6RZhJZTLFXDD\JVJH\JfTZT^:JTPNRTPHV6VPPH^BN:PVNPPVNL\XV\FV@L^FVRNPVbLTHRTP\LTP4LXFZNZJNJ@LVLRXNPPPHP^NXXTPR^RNJP^\VHPJLJVB`JPVPNNLRTBPJVX`ZRZR@VTTVPRRLZRBPNRNTPXJHVTPR\HXHPV8VN\TFNZPLTHVbRZ\DdFVJFTXJVD\JRTNV:NNZFHZXXPXTlXF\\PVRbZJRXJHZPPD^^VBV^ZVD\NJXJ\JDXLJNbHLLLL^V`TVBJTD@TNTFFFLNP>HBXDT\NPT\ZTRLJR^XNFPJPNPNP^XBXNRXFPTVDNTTZBJXPRFNTVXJTTJVX\JHNPJNVBH@XRPTPRZJNXL\VDLLN@NPJVFR\T\>TLRNXPJP\ZJJVHFTNJDRXbDNNF@VPZBTVVZXJXVZNPRTdHPPh<RJXD@`PHRNRNfXLHLXBPFTTJPH^PDTRPFPR<F`VP\NNTVVR`XRTFRVNTDB`RTPRH@RLNRFH^VDVLLTRTVNVVTTJNNPTNJ\RXRR<@JPL`PFVXDRPHPT^NT@RHTLVXVNPHP`ZJNTNZJRTLFNTJh>FPV`BTFT`JJTLLPP0DbVFXPX4ZTJLTX^@PBTVZDV<TTLFH>VLVLNPDHTHLVRRVHV<<LDRLNZ@\HTFXPXZR^ZV^NPB\JRNJTNNJFFTHF<NVRPPNVJZTZHL\TNHNTRBTVVBRXTLPXNDXZZJLJXRJZH<XPNTHPVJR\`HTLZPL\LHLLFXRRLDN\F:\TPHNTTZLZNRPFTJTRHXPLRNVRRVZNBHJZ^VRFTJVNJLLNPL^J@XDNJVJJFHNZHJBLD^N^HNLXJZJRXPFZVhFRPTZJ^RbH\HPRHRH\NV`PRXNL\XPR>hRPNNJVRFZJ:^NHVRRPZVLLRDZ^FfTHLPHLFL\VZDRV\TXVL^XJZJRPHPFLXPVXLBVPLTHXDF^RRLNV`DP^RXNNFRRF`PTLT@XTJPJBHPb`VXRRT>HNNRLVRXRNN6HJVZLVLXPRVPdRT\lZVBNRD\L^LLPVPPVDH^LNbN<DRFLRLZVVVXTVRJRL\DTP^TDPL:PXTRTDXTJJX\BTJZPR<LZJLRPJRPPFV>JP\TT`DF\PPDN\T@HDLBZTF\JP\LN^FLRXR\:\TJPXDDTJJV>`NNLVHTHRJLTRLR\BTHNNV\JNPNTFJNJTTTXNRFRX>^NPTFTXHXPLN@D@XXjBNFNNLRPF\DVNH@@RHfTLN\RHVBRJBVHJHVTRLTVLNTZPPTLX^HJTN>PRTHLVTTLRLX<XLNRBTNVHRBX^RPRNJPB^NZ>RRNJVLRL\ZT<NTLLLTLXTJNLH^VPPFFHBVHFPJFHNRLXLDDHTRVRVPVXHLRLDPL`VND\FXHVRPXRRVP\LTPTRZNZVNLXF\N@HHXJVRNVTLTXNPVFDPPHZRRXBFJFHZJPFTR`NPFXTNLLNZHNRHPXDJJVRJZHVRTJRDHNHRBLRTbNVJNV8FFNRLPLbXBBLTH<X@T>BPNZZJVJRLNPVTJNLVNFDL<PXRVZVXTNVLJZLLNBBVN>PHNZJVPTRLNVRZZVPHDXHTFVLPRNXNLLLHHJRPVTRPRTPZXRPNLVPPNRPPJVLRZ6TP^NL<FFLVN@PHH\LJRLHXLXDZNPXNPRHJXJDJRTLPRHdJZBHJFNLXNTRXTBF<VPTLNVRFNPDbLLPR@HRLNPFJ@DZRJVPTNPJJFP<RH>>VTJDHPDFHFZFNVB>b\JFNDLJPNZXJTRN\ZV>TNRXTXFLJXFVPTNLRVPN\JNNTB\TJXZBZFD@TbPHLT@FNZLV^HJPVN^XXHL\<NV:BFTVPHZJVLPNVZPRXPFBH@bDHPL\T\V`PFDVZPVB\\^LXBTZXNPPNLJTRFTbFTVRZNXXDXHRNBNZVJhVNVN^Lh^`NXJP^J\TZVPJVXX\ZNTFPNRFPNNPNFJTPD<^LXPJJ@NRNTXNJRJ6LVFXLD\BBb@FTRNHZZFD\XNPHPJ\BLVHNLR^NNLL^NRBTZFP@HFTHFJ^ZZHNNV@NRTVNXLRLB\PFPRTFFPNHJ@@PVTNLTHD\FLTRF@NNLJHDRVDNL<BRLTXJVLJ>NNHPLNRbNJ^ZNTLJRJRL6NNFLLNTRZVHTXVXXPJJLdLDNRNJ8PZHNTPVPPRV>`JJNPL\P\>VVHLLLRD@XTBFNNJLRNZNDN@F>NTPDVPZDT@hVNNPLPBJ@XNVZLVTRFR`JNRRPLTLVJHNLPHNFFTFTN@NTBRL\PJPXPHNFXNF\BDTRJLLJV8VXFLTDFH@NPPXJLTV>4NJ>PRNL^>VTBLNNFFFVLP6PND\PXPPND^TLJH@XFRH\FPJHVLNJ`NXNH\LXRJPB^FPL\ZTJR\B\LH`HPNFTFZPDBRFRXJFNPP\P\HVXP@NPTLT^JHBPR@ZNhb^JXHR@XLLT8@dLVZNX\TRPRRTVXRFZ^PPZZRDFXL@NfHbHTRJRZNDN\dfTTXRzX`JVBRNPPZBNNDV4TJD^LRVTZFN>LLNRHHJ>H@@RZNJVRR<\XNHTFNVNVBZTJTN\LRPZLNP@JVPP\VVBNNVPTZ>JVLPdVLVNTFPLRDFPTPLFHZFXV@JZRPTPVZNR\VRPLNV<ZRNLFH@PVLPX4JP@THLd:JNNlPNR^`DNBBR^NDbbH\^^VXLNRJTVL\NVVVNRDPRRXHNXLRNbRNJVTHFRTLXP>NTVLJNFNRN\Z\JDXNPFRVTLVNdPLPNRbf>>ZNXD\^FJTBRNRNPRVB`VDLTRZB\JZVRT\^T`PNZHBP`THLXDXJVRRR^PPR`P\DHNPRXLHLdDZTZDPFVHRR:P\XNNLVHTT@TT\FdVJVNRHDBZRLPBPHPLZFH`JPXXZRPNNLhR^\>@XZPJVVTXLPX^PFBLRRBL<N\ZZLVNJNVJRL\NXHPNDNTZJNRRVVVPJFLfRZP@RLF\@JhRVPPNN@LLLRLfFJPR\VJHX>LV\TLNJZXXDVNJVPRRBNH\DLJLLRZJZLDj`XTZRNFLVHJT@dPZ`TBRFLBPNBPHVNHfLTXNNHZXF\XHPNZXPDRZTNRVRNRFT^\RRJRF@`TLJFRFNfLFFXTTLP\FLLLP\HNNDRNJNBLPLNPZNFXDNZL^LJPFLLXXTRTTNTNN:RR<T>FLVPL^JPRXTXTRVLNNTPJBJHJTPPFVVT\L\XRFPHPJV<LPLLFHVLVJPN\FBTJDBXTFZLPHDVRTLZTHRFPJbDPPXBXXLRD^JfRZPHJTLBJ\XVLTVPLNDHTPPNFPRPNRFFVJNPP`LJPN\PHPLLT\BVXRRRLNLVBTFDXFLHLD\ZNRVJBLP\Z>NPTZPR@PJFTFRHFfLZFLBPBPXJL\:NV`TZZLJJRJdBFLbHHJBNPFPHZNJPXLJLT^VVXDhVNL\LJLTNBNLT`TDR@TNLXT\J`LZJVRNRPXLZ`HXFTHRHXXT@RJR8NFFTZLRVTRNPVHbDV@THbTNVDJLHX>LZLPNNV>DbLXXLXJLN@X`JFVFXPLTTNRFTL@RPBRR`NNNVXTPRVHD\TRXPRNFPTFNTNFPNLL\ZT\R\R^BT^RPPDZHXFNRHVFLPTZVPZNVTVFVXBP@XL<LTNXFHTbRNTXXLPVZPTHX<TBJ\LTTF<<F@NJBNLX:TTBZ8NTLFX^`VX>PLNH>HHHLLT@FJRFfTLXBL`VNRRLNPTJ\FFPDH\TLVJV\DT<JJTJDPRRJb:\JV\LP:\HTNPZP^DVFFPTJXRRNNJXVDVPTPLN^NT:JXRTXRRHDLT^`RJTJTfFT^LFJ`JJNBJNLZHVDNJJPPNLPVPJH\R@VPHBRDZPH^JHDNTL\RXNJRPRRPTVHXNPBXRPVBNZ\RLXJRPV>NTTD@LTFXV:PNHfPV8VDNBPBFXRFFR@HNHBVFRJLVHVNPPLPHLRLTNHPPLTLJBLF4RPXTDJHJNF8\BRZJNNPNP^RR`V^LLLTNRNFPTNZbX@RRNFPPPPPNJHXRVPJNFNDZNVBNVXZNJPLFLLBHDJJPZVNRLXZR@JTLZDTHdXL<J:RPJVFR@T\JVFHXHFLPHRRVdT`F^HJTNFJFNXTLVJ`N\RTXHRVJXJJ^NDZZNBRDNFF8TNZ:TNJRXNZJPVHHP<LXZV@NHBVVJVNNRRVFRRXPFPRNR^BJFFFfLDBNP`BJZT\TVLRZNVHLFVNPLBRTRVBLJVZHPHXVLJNHFdPPX^BLTJ\ZNZNXNH:FNPPDTHNRDLP\HJNVNFNTHFJVRRPZXLNJLHNNRJ^TDTRP^J\XHDPRHXNPBRRPBZ^RNFRVRPBbNR@NPTLJJTTTXDJFV\^>JNJZ^NN\4`R\6VZL\VLPTPJNNPNJXJHNN\:NNZTHFP>RP6V\TDLLZXDFTXPZLLZHXHZJFZVJZHDZ>@VJFPNPBXP^JRJRLFFHPLVPXNLLPVVHZJN^TPJPLTTRDRVVNNRTTZPNLJPF>RRPN\R`<NVHLVNPbRJ\PdXPF^FZFJJHNTLHZRZZXPLZLXZLPRPVLRXLPNNH`PVTZJTJNZDPJF@\HPLXJXPL`LP@DH`P\Z>\NN@HDPJ<XPNLFFJXZLTLXPHNTNZLVHTTT>PTRLVZLVJNRZ^RDRPTH^FRNX\LVZJTNNXHVFT\VHHBD>FTRLJ^D>TBB,DHPNNRBPP@NZFP>VRPHVT\LT\HR`DNTXFLPHJRXJ@DHNHNVRJV\`FPLXPTFP^:LNLN\FJH>`BXHPRF<ZF\BPF`RFRZLXVTFTbJVTPJNVRRXRTHHVLJLBJPDDTFPTF^dHD`DDf>JDDVZ@ZBNBZHDZ@bLdFDPXPDVLHRPNDFLXNDTXLXT^RHDVN\BRVxJHDNBH@NJVJPHLZPbNLRRHZP@L^^VRP@PNNPRPDNJH\\JXV`LDPNR<`HDP@THTR<PHNNR\HLHDTNLJPV\RVTTXLRHRNRLZNZLT\HTH<T4L\VJNPTRTR@HZRLDTV`XJ<RJJRJPLRTLR>PBRF>B@^RJTTVP@HFRHJLBBRLDbHZHNJ@R@RJBBTNLNHXHXF\VTTPFNLPLDBN\LZXRZXXVZPVZRTJFZV8@PDPHRNDDHD@ZTBTJTFPRNPRRNRRXLJNFHHRPLJ8VPNTJPTXLV@XDHVVVRTPRJ\L@V^TJLL\LLNNJZHZ^TTVL\\ZRXJJ<VZBLDXLPLXHRTJXZRN4BVJPRP\\XHRNHDZTPTB^PDRRJRBR@F`PPPV:TFNH:fDX>NTLND`LHLPDPBJTfVFVXJPJL\RDL^H`DFHVZTN@bDFL\R(TTFNVHPPLRJRLNVHLHFB^^RVFRZP\RHf\`RHRPRPV^LZBRNRBRHTXLVNRNDBHLJJVNPZJRFPTX`ZLP`^TJTFXXRNH^RBLPVXXRJRHRLFHJ@\P^HNFNPVXHVXLPTNLD\PT<`XJP@HJTNLPXPZLH\NLTVJPPF`XL`LLNH^<PJ\X>LJH>N8LHRJ`PXT^L^^PRNBV^XNNXXHZ\XJHNNRXNNTHFN^LLR\NZP8`2RNHBRZLPLbLLFFZ<XNJLTF>NJL@NJ\TLN@PRPRPFTLNVLVNPJDVH\RJXP^J\JRJR^VZLNLDDJRPL:B`JNRZJTLP8ZNZPBRL\DVLFNRT`RH`BHNTLV<`JNL@X>PbLTTX6JJLBHRRJJHXFVHV<TLRPZVFF^>8L`JJ\NFNN\<BTVBHLJVLPNRVLXVLRTRVVBRFTXHVNHX:LHFJTNbLTTHPBVJJVDFZL\X`NNVP^JBL6VVFDBFDFNF6>NFTXR>@P@TVRZJRLLBHDL\LFXLLPVLDHZ8ZFJDTFHJPTRHTRP\NXXBNDHVDT\RDVBNFJHXN>VTFLNDHL>RV@DZLDJPRTRTHXHZTJJPH>PNHHPPTPNNRTRTBNJDFTNJPLDTVBRPNRNZ@DNTNRFJHNZ\RNHXBXXH^XVBLRJZLRN^NXJHDVBVTPT4DPDTFDJJVVP\RNZFdTT\@XTPNVTPNV\HbLF\TNNV`TLZR^LVLFZN@RLVZ\LX@bBPLVZXPJJPJHTH\TNLRNLPPV`DJXJP\JJ@JFPNJVNTHVPPNPRPNJZPRFHHRNRTXFRLJNLNHLPZT\PbNHT`T^FLTDfDLTRPXDFNXJ^ND:VJNRR\PPXRTTTH\X`LFJPTHPFXBTVJDXHL\LHZVTLZ^TRRVP`HVH`J\VNNLNRXV>\FRLRLJZVLJDHRDLVX\T@R\HTlXTFZ^LN\@RPTT\@dNVNVLPJN@R\TLFZHJ`LXXJRLRTTV:PR^NZJTP^HVZNbLPPRFTTPLTJDBF`NNVXJZPdHNRBNfHRVFDTFTPPNPJNbX@\FLDZNPLJLDHNDdJTB\J@\HRRZTJ^LZNbXXJPTHRHRZ\FL\VT\ZJNHd@FBDFR<TTZH8P@FDXFN@\RPJTTNFfLPF<TFH\RLXRFXTTNFX^TPdHPV\XHTbP^@TFVVDTLVLP^\JRRTNZFVHDdVTZ`\J^LTHPNRXHF\:RdRRZ\PDBFHL@LZ@FTPP\VVTXNJNHPBFPHNRRJHFVXRF\HNZRVXVZPTdN^P<\H>@P`PZTZTJRH@NNP>`RJBJPPDT`NVTLPRTBVVH@NNDVNRXJ::VL<TDPNZRNXPLNHbPZ\JZ@VPVTJTNRNVVF>\RTJF^4\BD^\BhFL<XRPPZDVTFDN>\\RRJDLZBBNLVVZLTNXBHRPT>VRHZRLDLPZH\VJRDJFZ>dPJDVF>FHLHNZPJ>HJNZFN\PRTHNPNLLJRLF^@L>>RLRTNRTXTJJ@LLTL<D>NXRT`TZJLNVD^FRVLDJJZVLJFDJH<JXPFJ>VRHHNLRL<NbNLJB@NFNHJBPF\@RZPHTRF\HFTLNFZXT>d@LXJFPPNXBLVNTNPRTLRFTRBNTPJVJ@X@BNVRLbHLXP\LJ^VZPRJTVBTDND^^TVR@XTLFFVFNLR@TBJ\LFJDPPNTHB@RNVFHHRJXFFVZLDRRV`LJRN@P\@\TNf@P`ZFRRFFTNZZTT`TRPV`ZNXZPJZVRLP>L^P^P^VNBHZHF\`ZHF>F\LNLXNP\HPVZBVHLLRJVX^VDNFVHRJRH@RLNZTVFPL\NPPbXR\\JRLT\VR`NTLNL\>^JTJVVFVXLPXR@<dPDLT6PP^PLDJPVR\LJJ@HNJBNHLVXLPPNRJXDTDD<VJVPJNRD>D\<HZPRHZLDPVTNRHXPVPPTNXPLNRVFRFLNVJXHZTDNB@^PPNLTJ`DRTDbVLPJDPNRHRHPXJX@^TXR\LNVVF>RPBHNHRJDBN@JR>NTNP@RJFNJ<ZRFHDPPNLPZNLT>RHPRPBPTHX>DDHTBPF:RLLL`NN@RTJXBNFBRJLXRPPRLN\HTDX\NNDFJD@LL@PLTTZRHTBVXLBXXJVTLV<LXNZVJHPXXNFNZJHRVTHXPNTFPLLLDX@XPRPNLJNLLPHHNHHP<NVHPJJLRNTD>VHRJFVLPP\VJHTPJHP`@JLLTPVLPHTPJRRbTPL@FLDRNNXHRTRXVRLH<L^FLHNRL@^DDRJRNTXLJFV>PJJNLNPNRPXN<PNNFPPNTVVPLZ@BNLPVPNJFNNDTVNXFVNTLHVLTDFPPVJPJPLVNPPPHVLNFRNRBJZBNH>BNNRZLRJNPTN\RV8FLPNX@R>JF>DVNJHZ@TTFB\^XD`PHJRH\NRBPNJTRNDPTTLLPLFZLZZRNVNP\6FJJTJLHZFTPDTZRLPRJbLPPXXbN6JDZLDDPf@<>bXNPPLXPB\VRRVPHHNT\JRR`JV\RN@VFZ@PDTHRZR`HPNTJDVVPP@PPRLPJ^XVTVNNTDRPJV^PFFNPVVXHZLZVBL`RDRRHLDRXPZLVF`JP@VRVFXRNRL@FBFJVTRRTTRhJ^J\HXZH^HRFTPZXLN^PTPPZL^RNHRHPZHF@`V\LFTNRN\PTX`J\V\\TRPdPXRBLVLJNLPHR8BNZNJ@XNDRHLPXXBNTTR`PLVJZDHPhN`ZNLJL@TNJHf>PF8XNNPRLB\ZLZBBZLFRNNPJVLLHTHT8RHPRBFPLXhT8FH\BRBVPDFRP\`FPLVBXRTJPFHBR^F@VRVDNHTRJ^NNPFFXFR@J<PJL\JRJ^\^DXLT^TDDNRX^BHTDTFVJHNNRXDF^LVLNdFLVBPHRHZNHJ^RT@F\ND`L^PPHJ>P>XRXFXRHLX>PLRTHVNLRDZ,TPDVFRLPZLP\RHDRNH@HBH@XVZXHVPHTBTTJVNNFXRX`LP^BRZPNFNHT\JHDVJZPNRZ@TJ\HDHJPDHLNJXLZPTBRJV:XJ>TVR\``PPJbRD>PBH:PBT\NT<TL^LJ\LZZNLRLLNPJPRRNTNZRNLHTZNLD:LHVTNRNHRJNJHNXHRJP`FLV<BNXHLFTRR>NJVRNJ\RPJVJLHRPPZFL@J<PPNNRTPP>ZLFTLF^R>RBRDRDXRXJXLJV<FDTLPRFRBFPBTPFBVRJ>DHXXHHVVHD\^@dNLbF^RJR>H@PJ`<HXB@dFPBRFV\FBPHXFHRHLXXT\XXTJJjJNLP<LXJ@LTHVXDTHFTPFFF@FRZXPLXRLVZJZTNVXLPPLFXBRLXL^TRN\VFR>J@NLN^LZRLDVVPLVPH\PLJDPVHV@XTRHNFJHTTXZNTVJVB\HLLPXHJ<TJPJBTPRHHZD^N\DLJBPHJVTP@NLLHPdZRJJ\JLPZFP>TBR\DL^RJNHT\BfLJPR\TBTRNdVDX<dXHJLFNJFHR^VBJVZJJNNRHdNRFTBV^<JHJPNFLD>PHZXP\6RZNRPBT\RLTRHXTXF`TNF`JHTBHZRRPNVTVVLPNDVZXHH<DHFLBJF\bPPZNHHTBXZNVNRPBLN\@<VH@NPZ:TPRDLZVLZNNV^NH:F@JRRVPHNBVTZFNVXXbfHRHPRNVPHJTHLbLVFBHRFLZXHPHPNTTHZHTR^PJ\ZTX^T(TNFT<XRNRJLRBTRPLLDLTRJXNTLLRVZLFJLJP\THVJNFT@\TFPFXXVR\8P>FTLTVNNRNHLTPLDH6LJZZ^Z@JXTXJXRRFDPTJLRDFPJPTD<\RDTRZPHNHLR>^`NFPTbJVNP@^NNTRLXBJ@BTTDTDTJBHXZVBNDXLTPN8XPR\PXHTFPBNNRNNPPPRBPN^F\X>JV@\PB>Pf@@VPBPPHR\`JPHJTDFBNBRJHXRJ\VXLNP<FFRTJLTXPBLHDPT@XLNXJPBRPVXRDJNLRBP8`DHJXRF\RLZdRNTJVVHPR@JJ\JH^JPDVVNFLDXLLNDHJJN<^R@>HXTDXPJJH@JZ\JHJHBJRTHDNLRDTPJVFRRPLLTRRTNFT@XDVDHTVP\JLHTX>ZVZFJRF<LF@TPJDBVNBP>PbPN6NRNPLPVPPHXRFTR@HVTXHVDLHJZNDFVLRNPNXN\LHV6PDFZNTbXbNT:\R@R\LLL`TLPPBVJ`XXPN:dH6dXNRFBd@LNBT@RPFJdN`TJRFNRJT@NNHV<fHH>NNHHXXTBHXTXFJDVT\LPHZFVJBhHPHNHBNLdLBPZN\JNJJRJRTNLDNLNHNB^LPZNH@N@PDXNLJVXTVJF^F^\VNNRTLNHXNJRTPNLTJNH^PFJLVBPV`PBHVRDfLRVRDBXRP^RPTPTZ^RPPNBVN<L^TRTVDL\^LFLRH^VVPPRPTNJVH\ZL\^N\LX`XRDPX>PJNRVNZHPPRLXNHVPPFDN>NXTN:BNHXFVZ^PVTVXXHF^TFVJ<JRTLRB:PXFBRVHJTBNVXNRHRXRTLRTZFHVN2LZLVXNJDRP^Z>XD>HRXHPPLTNJZNVVN`LL@J@\L>\LPRfZNJFZFNDZNdZHPNRXPPFRVVPHRPRV@VNPD>ZVRHDT^FRHJNXJBV8RNT@RJXPXHHHNNXTRLJZHTTLDPHV>PVLRNN>DPT\B^V8RN^J@BNBLNXL^BV@RL^FPHPLPRJJPLbP\DHFRLZ@RDRRNPHXJHVDJZJHRBRFDJVLLLXLXVRNHNPXL^FVFPJ\LFRNLZTP`8NLBR@JHNV`LT\NJ`LHbHBFX@LLXPRL\PTVNPZDd\LVLRZRBPDLZJHFHNFR8R^\LD><`TJVLLJN\BR^LLHZDRPNVPLBH@FNBTPB@HNPH4FHRHH\RHZBDT2LVHXL4HDRFNVJLBVJFFNPPFLRVVRFHNRRHHPRZBLJ@VXFLLRNRNXLXH\JBJL8>LBVPH>FRTVHDFLXDPN<FPVL8DNLFVJTZNTLRNHF^NXPTLDLPFHRXHFLFJN`PTRN^RNFV\NTJJNXHLLJFLTNLFDXNLPNRFT4DTFB`H\8LJHBPTTBX^@V>VTN<ZP>JRFP`BNfPTFRNZFRND`LNJT\TRLFBXVLTNPXP\NV\RJLT^HHLXPBZPPRBPJLVPHHLTBVLBlPBNPJLDbHBVV\R\JRFXRLJNDNLLN\@\TLNFPN>PLNXPTJP\LDXPJDZZPHLLXN>X@XTDRBNPTXRRXRXJTVXVL\PJ\<RRNP\VBHXVP\ZHNVVRBTTRFF@LRdPVLHLNHP`R\HJJPHVXbHF^JLZZZD\\JTN\N\RZVVLRbR:ZNVZPRVLJLJJXNLLVDHVTFHX>V@FVLZPJLXVXHd\@TPHVHFNZHLPZDRTDbPJ@RNRPVNNJVDRFN@Z>\P<V`J<NRVP\TDRRNHR`FNVBRFPPHRRFVNNJRLVFJ<PXjFD^(PRPRTPRJT@DTPVHLjJV@TFRRBTFRNDLFRFFJHLPHP6H\HFJNF\JDXDTLJVL:N@HDJNXFXVNDPVBXTHXZBXFP^BR\DRPPFNTJJHJTNDVF>FHhFNNLJbFLDL<DPNTDLXNHDVHJT@<FLR>XNVX4HVF`RLNNF:NRHLTBR*FTJHTRHLPVPLJXJZLPJLPJ\8JLB`PJ>NXTX\JTRFTRPRFLBFPVNVJZFNHTN@JFBJJTFPTFPPXDRPNXRTN^RVHPRXNXVVFR>VBRDT\N@VPPNPT^NZJFHVPPPL>^NFJLFNHTP:LJ>V@@TJXTDH`JBNRLRZHFJLDNZDLDPPFHVH:NRLFVN>BFHVJRVNNH^0NLHDRDhRLT84NJJDTXHXZXRFTPJLN<NL@NJFZJRDVDBRJLPDHRDN@RPVVNVNTD`J@P>VTVPZLHLRNPNXTTHRNTJTPPHTPTR\R`FNNHL:VPFN:JBF\R@^HFR@NXPVVNFTPZ@XXN"BNZ>LPPDNHFFJ\VPHZJXHTXRL\NF>D`VNNVFPRJZ`JTVZJFR^T`@THZXPXNJH>fLTLLF\NPDLRHZHRHXTFLR>VXLLFLNHLNDR\RZ^RNHX`TRL@F8Z:T@PJLZRRT\JTNLTRJTVT@TTTR<PJTZPNZH`TVNRTBV>NV^LFF^FbF\NZJRTHfDDHTFXBFPTHVP\X>XN^BNFHNJLLFVFPVBRVV^TJHjNBTJZZJLNXNXV^FTFH\LPPb@RRR:HVFX\@V@TPLJ<ZTTBTJNP:FLRHRJRRJ@@\NRRJHPRR<PLTFPd8NTNT<L\>DTHN>PDZPPT<HRDFX\NN@NJJHTTPF\RHFLDN\LDRPL.:NFPD@LDHBNPLVDTJPLNPPRRLTRP`DJHNZHNJTB\>DXZ<>F\P^TJBHH>VRHZVPNDRBRPNFLTDBNDDXDJBRHXL@PLNNTNBP\NTRDTLNTRB`F@VRPd\V@LDNNVDHBT\LJD\L6P4HBFVLPTTVRNLTH@X`PLLL>L>J>THLTNBHPHNLXHZTHFVHPZT\HZLRRR8L^T@T\NJNVHBRJFZHDTLRBXTHPFTL^R\D^<THXFHPRXLTHTLZLDFRHVNDBVDTP\PFPJ8RPHTVJRNBV`NR4JFRNJXJD<RDLBPBHBNRJLFFXFJTHRPXLJPLFHPRZHTDJ@HR<HP@PFZNXLPJRFHZRTHPF\HJFVHTLHHJVXXTJPL\>V`FRVLXHHVHJ<NDFRD\NHPNHDJRR@VHRHHDPDPTNL8PNRHHDJNFF^>ZD\HR>NJ@PH@TTPP\HFDDLTPDV0\PXbBVPDLDLFPPRNRJFXFNNXBZXXLTTBTDFDTJB^TBPDT^NHFZDFBDDPZFXPLHR>H:NHHRXNHTTLDVTPDNHNHLTJTPVBXVDZNJRFLXJPXHTP8LVHJNLTNP::HTD`DN@FJTDX@\`JL@FVBXFRJ\PLRDLdP`HF>XHTNLFPNBTHLPP>JNL>PRPDPJHFVLTD>T<^TZTRD^XDPNLRR^NXbTT<FF`dJXLXNBTXRJDLDVZdDZbB\PFJLXTXTRHHN4PTN@ZVVFJDR\THRD`NHJJVVXVTNN\XVbJVLTRP:DRNVFTX`ZRH\Vb@XJZFTRPRNNZPVDLN\LHTNJFNLZ@^JZJRNLPHJJPTFLHRNB>LJdT^NNTNPPFLNBPJXPNJRFTRJPLTRFTRHP^XDJJTdR@LLXF^VPXRTTHJJDR\VRJN\XNPBJJRNFLVX`F^RJFVTVVXFLLPNJPJVR@LTLLNLHXRTTFP\RLHHZPTHTVRL^RVJ@ZTDXHFTRRNHRXDPPT@>bZVTPNRPPHTVLRJRHHV\PRZ^BLPTDXTLZJN\BRTFRZLH\VRT>VRJ@PNPPDRV@^BPX@DPR\PN<NPLHNPBJFPJNJ\D:JF@FJLJXPPP:FFLPR>TR@TVJPPZJ`JZJPJTNFTLHPJLZNTHTX<LH8DVJNJZHRB>>JB^HRNPJLLTXT@\@T:ND`V^VVB>NBD@DXVP8DJBVZRZVRXVNBZTJLJRRLRLVFFHLPHbZTNHRRJ>THFRFRXPDPLVVPPHJZBLPPNDNDLLFTPVR<PVLJTRVTHNFJ<L\JFDV^XRFHJJNLPJJNPFHFHXNL\THDNHPLFNNXVJJPFH^\JNNNHHJPR^TT<@LP@VLRTVD@LJVBJNBX2XLTNRLTTJZ@NJRHJRNDZPRJFRNPPB\RZPP@TN^TNJb8HRLX@PLLHLLN8DRRBXJZPD`NFVLRJHF\ZPXLRDTNVZBLP@VPJ>FZ\JXJVVLX6XRNTTFTNVR8`\LBPLPFPLZH`ZZPR`LVLHVPLXDFTNTTJHDTHB8PJHPBBJLTFXVPN^V>TXT8dR<PHdPJNJ\HhVVPDNLXR^JHRBJTNRV6LRHPLRNHNTRDNZ\RBR\P^HNZRNVRdDX@PVHLZDFPXFXT@JTHVTJ\HH`TLTNR<X\N@PF\VVFZRT:XHXJN:FRHDHTFTPPTJJHNRPNRZXLB@P8ZRJPPPZPPJJ<6HT^RPNDTTR<RF2XV:LNJPFNDPPXZFX>H8P<R<BLLDRJHXNPLFHNLL^P@NNVXNJ8FFTVNBT^TVVFHHDRRPNP^FLLFT>TPLNDJ\LTLLNJRHRLTNJ@\TZTJLLPNJL6VVPTPRRVB^NVRDXPTVFNHPFPRT<TPNNRVTPX@LJTLHXLNL@BJZXDJDHXTJVXLLJ8JXLJPVFJTFPHRRTBRRBLLXTDJDHRRRJLNPVH@LTFTV^XPJLPRRLVRF@JNH@N^NV`VFTD\NVFJJHHPJRH4LJTTXNVP@FTPFD>LLN@LFBX\RHP^VN:TP^NVJJHZBNLJJZN8PVRVJ:LHRTRRHTPRJZNNTHXFNNBPBPPHHBDTX\TTBJPHD8PVRXRNNLPTNJRLJbFHPR6dVPDPHHT@JVTXNLNHRJVJHHHH@VR@RP@PHTZJHLHZND>P\TLFVFNNDRN6HLD\TNTRTJH>\@NPL`NVPJ\>B@LRFXLJZ\HLTNFLL@LJT>P6RRLLXTPRTJPPL<PBHFFHRPJ8ZPLF@TPT>>`DVFB<PN>\FJRHN@Z@JP>N*<HDDLL8RDHV^FRBR@N\PVFPNZHLNN^NFFNLHLXR\PT8NX^V>NHLHVR\NDRPDTJHPXD\ZFPP>V@HXLLTXJPPJVVB:JNFHLF.NLVRJRTZZHBNNLNZRXNFNb:VLZ\DTFZL>FJ<NN@NPR>dTNFX\TXLRJL\NXT:PHHPVVLJLRF>@<TXBR>NVDJPRRFXXNFL^P^:NXRTJ`RHLRLBXPNFPRNJPRLNPBNNRDXHZV^VXFJZJRJFNLTRPR\T>bNLTX\RVRJJFXB@JLDLNVTXRNHJTTTNJP^PPR@F0B\LTLRVR`RJNF6VVVVLBF@RB6XR>NP\DHZPXTPRLNVBHVHH`TTLPPR<TJVFH>FXHTZVP\J<NNX@HXRTXHLPJPVNX@RLXPNFJFV@PLTPLDFVHH<^XLFL\PHLRJDXXDNTPPV\ZN@VXJHVJPRT<VPTHTRVV>>NHRRR\DLPT@PXHFVVNFP@P^LV^PNJH`JVLXR4JDDHRRDJJNBPJ\THVF^FXBLBLLN\\LTNHLLJTVHR<^VJPNbJRHPTXNF@XTNJNRL@DXVVHNVBZD>NDDN4JJJTLFJVTNLLPXHRXRLRBVX@PJBPR@LTBPJL>JJ\:VVRHBNPHNHJDPFXRNNLJJBZNJLNXNBZ\NXNPDJZLNLPXJLD:NNXPPJTLTVD^XFLDZNL8B>8XPZPJNPJBPN<LThRVDD^XJL^XVFDHHJNJBHTLL<NfPNHXJLZRPFHR>HTLJPTRRLPZPTV<XJHZBP@FJRNHLbFLRJNTHVDLLPLJNJT>VFVDJNRFX<PBTDBPN@ZT>L@FTJ:XXD`F`>TVNFHBDPJRNPFND@HPRPN\XJHRLZPPV^N^RP`RTPZND@ZLFTHXVVLJFPRPPTFPT>^J^FHPRX:TXNPPDPJZVP^VTPPPRLJTVT^FP`TLPJ\JP^VTJLPNP>BLRFJNNVVLR\ZRNDTRRN\@VTZNFPR>XDFTRPPNPZ@@RBFDR\4PNN^NLR\hNVRBDNRFJTLNXVJJNDHHHfNJNDTNLRLBZNPRNDDJXJHFFNNHZF:HLLLFLXZL@PVTVHX<VH\RF^TVJHXP@R6FRZPPRPRBRJXFHDXFRLFPVT@LFZ`RTN<^HHLXZRDNVPNHLZHRZVVVFDHJJRPFRJHNFd\JdLJRPNTHRRNRL8HLRDNLZTXLNPJNFHBT`H\FHPBHNXLBZXVLHVNJJLX:TJLVJ8TRPFVVLLPNBLL@JDXXPN^TFBNPDDNHLJHTJHFPNT`R8JLJP\HDPLLHTXFNRTRNBZBPZLFPBHNJJDXFL>VVTNDHVHLZXDHXJTPPbTPNNFRJPJPDLFJNRVLPJJNXJRPZXPJDP\>VRNNN@ZJ\TNJHFPNNPJBHR@L\NRHNH@JPHZDV:HLBFTLHNPTT>XDRTFXHJBFDNHLJVRFRVDRFXJTV>B\LBTJVTXHVJJTRH`HBNTF\NT@VHRTVL6DFHD>D^bBJLLHFDPN\@TTHPVHHTZN@TH@L>RVNNJX@XPR^HB>RRBTD@VZPJJJPNPRTJXJLFLZJPHFFPNFD@NJXTHFPJXHRPF\FPHRTX``PNFNFJHLRDTDLJ<D>NPXPTNNDHRJPBRLNLRNTVTNFRVN^8DRfPXNTTX<ZVHRHJT<.LHFNNNX@B>HJX@ZF\LNLNPJRR>PP^VJNJ^PVVVZBZLNV^@d>NPJNJ>PBRNPR>RBNLJ>LRDN:@B\D\TRTDRPRVBLDPRHR\TXHR6H^@VRJJ\DZZJZD`TVV<RRLVNZBLTRTT>^TNN^NL\X^PNLPZ`HVPLR>PTXPXHPLZRX<hVZXVXbXTZLPFTTJVJR\NZNV^HVVXVZHDVbXN>BHVZPHJB^X\P^X@LLHXLJFFJ`^Rj>LN>RXT<HLV\JJNRT<NHBJ^PTFHTJTJRRLNNNBTP>XZRFNHPFPJHZHRNFJZN4BNRXTbNRHVJXLFTV@NPLVNXNNXDPNZP<NTJTRTNZLHDbHLLTPXPDF\RHHJXPPVLHPJLNJH\RXdFTXP^HRN>LHDND\PX@LPXXFVPVNFP\BXDP<RHXH>NZFLHPRRTHJNNVHR\PHV@@FTRdRPRNNDTNHRVNRFLZLLFN>N`FBLP>FVLNJ:D:RNFPRRH>TJJXRN>D^FR<XLDR`PPLRJLDDVJRRHNPJ>T>FVFX@LPLLTPXNXZ\BTHRTLNRDFN@\@PBTLDX@PHHNLPRXHXPFXTJBRPLBNJNH\DRLVJNFBPFJBPVP<DPPN@F@VXNFVLT@VHLNP@HFLVH\RBLNP\DB@LLFLTLRDLLJDLPPJJRLRLRFLB@JNDF8DVJVHJFTNRPZXLJBD^RHTFLPVNPJJDPT<VRRJ6PNFJPFJFVRZLDNBLHPJLZJL@BPJNN\TVJTdZJTVP@XZBZNRRRLLXLDJLLP\`XHRXVDRHNLFTPJTRHPHTVNDRLRV6RDHZFLJ\DZ\FDHL`ZRPRVRVPDPNT^\JN\FLBDTTBTPPTLTFJTRFZR@FZTP<RJLVLPRFJTVTJBXTJPJHNDXZLLTRHPTBZNVJFVXVTTNVJRLRVNDPBLBbF>XTLTLTJJZP:PVJN\bRJNH\ZNV^VTPVVLRNTLJNLBNPNJN:^L\L:NHDNBLNJL>NRNRZDPDHRLPVTHHJZFNNH\@NPLNH<FTJ`BJXXdD<\>V@H\ZJJBPTXJVfV8RJJNHRTPJ<<TL>NFPBLP\@@DLPJPTLJL\>L`\JPbLHJXHPJXHP@RRLFNL@BPLTNNFLVTVLFX^RLLJTLRNPNJPPRDFHTPHHFLPJBPHJZRNZ@LX@HJHTJJJVJRLDJVBBNZTXNP<V<TDLZJ<V>JRLNTBP:R@ZDPJLTJJ@TXTBJXTLDNFNFVFNTX\BRDDNTJ\BBTJZPHLNHXBDTLVLJRLVRR\DXDHFVTRVPNZTTPDTP@^JLRBTH8DZRPJJVV\NPLXTP>>PTN@^NHL@PTJJZJLPDHFXJ>H@HPLJ^<PXTNPN\HTJRXX\BFDJJH@\V><D>V:NBRVPVXLDTPFNNLVJDLRV@LX\P\@XTPNLL@NLNLLHDN>8NRJTPJFN^DNB^PNJNTJTXX@TVLHJR:LNN@`@JRPPPNNXPNPFLDV^RXF8PTRZ\HBJVTLDTX`F:L<RRHHHD@TFRTRTBJFPJRZLVRL>HJL@PR6LLJDHFTXJLLLTJFBPX^DBRPNBRXNH6D@ZPHLRV@FFJLX>>JDPFHT>P@VVVR>TLDJXHHZF<ZV8:HJPDNT@JJZ@JFNHNBN>F\LJDLN\TZJNXXNJLR\HJRRHJNL\HTHNTRR><^FFX@PDPND@P\VDHT@XXJN\P@RNLT@LVXLLPFTFPT@LHJL<BV>JZ\JNZNZLJHZVLV`XRJTFXFBRJTPLHTHJNRNNNR\TLXFVRFNT@RJLXLR@JPLRTRJT`HZRD^N\N>JLVHRTL\@@Z^fVNTP4`XVXPVTbLTNPBPDTLVHTTVT<LLJJRF^LTTbPb^XLN`ZLVNNLLdPNJTZ>`ZTFNZXRVNPHZLXJ`TbTPJ@XJNRNHTRNPVNDX>HPFJDFXRVJJZTLZjLNLjJJRJHNXVT:D4JJXLVJFJJTV@THN\JRRZDNJTPNJXFBLRLVVBNVJTLNFNTRTRJNJNDHJRPDJ8H^BJTVFZJPN@ZRHBL\RFJHNNJLTJLRRNBLPLJP\DPXN0JPN>RHR@VT:T\DHXLTJDXLLZHJHVNNFLJDJHR^TXTLHH0N@8LJLXNFFTRDRJXJPVZNT>HLHHPD\\P@HFFPFLTTPJVVNJNHDXNR\RTHNVRJFPBDDFX@B\HX<ZDLLZFT\lHLHBLZ:`XLP`FFJPHZDPRDD^T\LHLRLVZH>TTPRN8NDJFPRVPDR@JRJJ:TNJV@DFZDTFNb^NNHDLDDN`VTVfPHPLJFV8\LVRFRL\RJLZLNV^R^@`JN^HRJN@@DL\^JVBRXPHLJTVPH<TPNFPJN\VJRHFHVNRF>H^RP:RVNPFNPXZPNZLVXPT@JHHVRRTTFTHTTJNL>LFZZ@V<FVR<XJPPRN8VZL@JTNFDNPRJPNJDXRDXRNBJRD@JXNV8BXRR4NXNLRHBBbL@NF\8RNVLBJN^HL@XHJBP8RPRLRXJLPN>VLVF^LXHTZHLNFLPRPPJJF\JHL<HNHLNH`LP@ThLN`N@XB`LLBRZRZVLJ^XRDFJJbPNZTJZXVJN<HHRTHN@JTNHXPRRNPBDDFTP@PT^RLJTP^:ZPZDTLPBLJVJPLB\NPXJHPLVNVFTRPTPFVJFTRTLT>HJ`NPJR^XHZLNDRTBX8J:LNV@NJNPN^:@VNVNhLDDVL@\NRTZDRLVBNVL@H@JN\6LPHRXTRDRTFDXT`LJD>PJ\LHPBLXPP>P>PZLPHFDFRFTRJFZJT>R.JVLXNJ<HLF`DR@TRLN<TRB`<PNJ<RNRPFNT@NDPVFJBNVX@FFZR:NNLPLJPNJHZXLJZNXLPXBN\P4TPR@HTPFLPLTPJHFT6J>BZFHFZPVRNTJ^XTRZFDRLJBbR@JLZJLPJTFLDHTFTLHPXJZZFVBVR@NNFPZ>RHRHTPHNTRNNZJPDTL<LRX\JbLRT^DF>FJLLDNRHHTB@\LHLP^JR:J8DH0DHHHH4FRN>L^RF^FTXXLFRJJLFXTJP>HJDNPN\HBPJH<PPVHTNVRBJFXRZ<V<VDRBZRFBPPFFFTDXHRTLL8N0NNRJBRNBF@RNFL@LFHJHZHFDJZ`BRP\XXL<VBDLRRPPZRND<NLJPJRHHJTPHPJDPRL>F<PNTBVJRPLHJ:PHDT<VNL4:NPBDJJVFVNN8BPRHPPPDPBVNXBJNLVRHdHV>NFDRJNP<VXHRBT\LJ<LRHTT4T:@\HHVV>DLLLRR@XB\<TTJTLD\N`RTFRLXFTXLNJHPBJLHZ@BJPNFF@ZJFNFDVTJLPLXP@VLTJJJXHXVVTJ@BLRLNN\PD@ZXPNXB>BDRN`FTNJFLNT\D^LZH<RDJNLL^R@\<NFPJTBPFVPJRPPBZFTXNXJNVLDVTLV<ZPZHNDVL\LHRJPF@NNJT>JJ\NXT\DJR\TH^LBRLNTXdLVRZN@ZBDNLPFPTPXLJFZRNP\PPNFTDNBLBLNTLJRNZRZX8HNTNTFHHLH2J\ZZdZNVZPLTTTFHTZJNFRFNNDRVV@`PNJZTND@RJTJ\PJN:BPTNJTJVJTJ`H6H\ZVTLZNLFH>HRBRPH@bRLJNHVNL@ZFVTFJT`^<HNHZPHDPNDLPPNLDLTHLJDPJHN:NFR>>LTHNNTFNDP:NPLZ8NJHLV@@F@JNDTTH8Z>HDDDPXRDLB@RRN>HLLFT<LFJNLDFRDTNNN@PRFJRVPLNPPRTRJ6D<RV:T<RTJ<TDLFLJRLNR2J`XHTPDPPNFTFLHRTHRJJHH\<NNHPBRHLNVTFNF<Rh@R\\DZVFFDVRVJL<RP>JV^LFHL\PZTZRPP<XNVVHNJZJPTP@VPPFJVLR\LNLLPNH<ZVBLFPLFVTBD>\2BNPPP4HLB@JhHXP@TXHVNNHHFRDJPHRHHX,LRVX@HNJXFDDFNJRHZRTHLTNNDXRFRP>DPLFJJBTBNFRP^RJRRDTVRF:LfR^F\ZH>P@DDBNBNZ<TJVXLR@TP@JT@LXTXN@V\RLTPFJDDRJLNTFDPNTBJPD\HXRHL@VNTRVBBZLJ@L^DJPJLPVP`FFTXT\FTHLLTJLTPLD8DNDJFVHNHH@LHBHDPJPHJNJ8DDLTDFJLLNDTT:LRRHPNDN<JRRDXDJFVDZNXHFPTZRHTPHV<LT\LJP@@PNLNTXVTV>XNJR>HNPTRJRZPJ@J>JN`NFNJBRDL\LJLDVP4VL<ZVJF@HHF@<ZNJJV@PZNZJP@JTVVFXLRJPRLHXJFPJVRDLXP@RB@T>JPZPBRHBVNZNPFV`L\PPLPPHRNDLH>THVTNVPFTPFbX\XVJHX:NPRZNT`HRDRNTXTTRNFNZXJ:HTHVPFJLNPLNRNNRLNPP<\TVLN<TLNZNXRHJFFBP:BDVJLLJVLV,RPRLTF`HPJHBZL:R`BXRZ\BDVNPXR@JVRXJBTFFP>LJRVLFXHDRNBDFL^PJ\JTRTJJPTRV<PPLTRXFF\DDNRHRFBTHNZZNLNBZRX:RJ8LHPPB`PPNNLNFLN^LVJPLJR@VTJNPNXJH\J\TLTHNTFJRHLFLTNPTTPL>\NRFFZDPLNNJDJ>FNVH<NLFVNVXPJFTHPJT\VFR@T^:HR@NR\JJ@LLFN@RVZ\H^NJDB>NTRFRJRLZTZTLFTDNJDXPR@NLdDR8NFVJBNRPNJT>RBTDPHDVLDXH@HVZ<VTP>VHLN`PJRFHPNBTRTBXDJ>BLNRL>@BDNDF`0N>NVLTJ@@XFPBDDDL8LHXNBNPLDLPVRLR<DFLBFVNFTFPRNJTJBHDN4HP\FDP@JP>JDFXPNXT@XPDLTVTJF4TNPRVHBXFNHFFHVPPJ:ZDzPHLPBHH\F@JVLTTRTXFXRJLVPZLDPNPLJJ>@DPFJBBNH6:RBNTNPL>LJNJVZHHNVHH<DJN>LPNPF@DN@X@VT@^DPFP@HRRFTRF@VFLHB>^HHLJHPL\DNPRPNFB>NLDJNXFT>BFRHNFLNR>TJJPTBV>@FP@NJZH\ZJ`HFD\H<J\\NDPFDLHRNRJJPFHPPPPJVHNDVRNVR@PJNJTRJ>TJFVBLPTFZX@NH`@VLNJD\XLRJ^JTVHZVPBP`P\HZLP<RVPP^JV>DB`VBZP@FTLTPLJFDNFR8TP>DV:VNPNFF`NLXZPNTPTLX@FbLJ\JVRV@LRNZ@P<DPN@P8FJTTHHN^JHFZBVFTNRTVVR`ZJBJJLXF@P@NTD`JNPR>TDHRHJRVFTJLV^@DVDbLXJR<VJNTBNPLVHJ\JNX:NRRTdLLfL^VHZR>LZJVPHFPVZFNFPVR<XHPJR@NRNHNRFHTDHHHRH@D\JPRX@NZRRRRFFLPRPFLLR^HTLJDLDNTJJZLTJVPHFPR^PLX<N@RNH:LJX8DVRTbRNZHVDRDD\DHPZPDPTFTLZFHBLNDBF@DPHPLB@DHNHHD\H<NXTJZ@^JbPTVPPTR`\BTZZLJTLHNHL:N"XNFV\TPB\TT<LVLN^P@LFHFJTRF<RPFJNLXRDTFTLJRVN<NVFVVR0D^LFDN\N>VTJLL\NVZL^TRBPD\XNJNJDJ`RFFVBRLLTDFTBHbNX>RNHZ\J<@HFR>L\TBNZJ>LDRV@VDNDP\PJRX0DPLNPFRR:>LDHRXRR>:D@P@LTP@FHPJDHN@BJ@<FJJ8V^NLLLLVT@<JZLJNHLJTDNFHNZTFDHFJLRDP:@HT*HHHHRTLBDJP@VLL\JFNTXHfPPLRDDHNHDRD\N@NBHXDBZNRHT:LL^XBFNFHJXFL@2HP\LJ@ZFJPJJDVVNVDZNZ^JDDHVVTNTNDdNFPJHPPZLPVLLNHLLPTLRVHRHBRFJHfJLTRT`PT\JNNBXHPRHTJFL@NF\FPL^\TTXVXLL6ZLJ<PRTTBJRZPBDPRVJHPTNNXHZFBLHLRTTNXJR<V^>N@NJLLJJFJDTLJTXJJXNXHVJXLNRLPTT\LZLRLBbPHLPHN\RPRL^F@PLLJPLVNJXNLRNNL\\^R>DbXNP<TJTHVDNBF\RT\DLR<`LRFJPFBH8VHN>LPRVHPDVXVH>ZZZPJNPRHT^LHDLPHTTDRJRDRJ\PD>LPBP<DTLHT:JJNHP@LHPTLN\LNBRR>PXLV8JD>NJFPBVRJNL\N:HF^PZFNTBV\FDRNN:RLJVJHNX:VDVN\JPZNRRD\HRBRBLHRJ@LNP@FPR8V@RL@JJJ>LHBN@LJNXBXB\TBNHJP>NHHRNLFBVVJHHNBJ^DJHFVXXTDVJ6XJRJD\VF\:VBNDZHT@DPJ<DNNDJNNBJTNFVLXDRPT@LJBPXRPNL@PT>TDJLRTPDLJP:PRJJN<VJHHLNB`JPN@NR<@NHLNDFHPJRTDDVFLJHJFDTNFRXJ>6\RVP:HRHRHH\NXLRFJNZPHNXTPJP2PLLD^ZFRNNJVLFT@VHNZRDRBN>:DN8NXPDVR\NPLNHZJVNLNLNHLTP@FNNNNVTRFVJFPBLB@BX>LH>JR^JJ\LHJTPHLTRTFPTJT@RP:NLJHBDVPXJXPDRF>ZFPHFDPZ<FP>JV@8<^JJRFXPJTFRNHLD>H6HL<P>RHHNJDJ\LNHLNX@RN@PVVTDT@DPJ>JDTTLP*JH<DXPLJP\NTBVNPLXZJNFLJPJLRDRX\HJNPJPX@^LPLRHJL:TJHTDRDDJXNVH6TBRP\FJNPNPJTTRFRLPRHBH@PLNRNLRPRJ@JTTRT>LPNNLJJNRLDRPFLZ>RLZFJRNRLFFjTPLNN\VTBJX6\RH`HP:bNPNH>TRXFDXVBLJDVHLDFPLJRLRJXLTND\JVXRL\XTFHTDXHPV^R@F\N\PHDXPPDNLXP\>TPLXVDHHVJPZB\FLHJHXF`FD8NNRLNJNPdDJ<\:JTLXV`FHHDNP8b^:DH^TB<V:XHFDXVBBLJXD4PVPTRPRLPDDRJBDRPJJ@P@@P:PLJJPDRJNZH<PJFBBNDRDRXL@TPVFFBDNZX@HVRRF^@FdRBHHRFVDLLF8VR@NFRHPF:LTDNJNHXTL@PHJVPZ<PT@VNL@<BFHHLBRJ^HP@VHHNDFDNH>NXDTBZVL4PXP4TPPJX6TXRZPBPLF:@DLHLNPB>LPHRJVT>PPX`FH@HXJ@HLLbF\RLDTPHHZJVF\NPNN:^RPR:VP>@PPBV@PJNF@PNDL@FPPHTBBVTJHPFVFBNPTH<FLJDHDHN>RFN@HLNBLPDLNJLJBBRPFTLVLD4NNP@PVFFP\RLHPPJLDTBHJ>VFZRHDLLRPRNF\FNRTF^HPHXDT^8NH@PPHDFLPBNFFLNJ>PPNPVPHLHDXVHDHJR@BRHLL@ZLLTJHBHVBBF@J>@@FNDRFNR@JNHNDHTJNXFHHNDPDNHPNR\HHPRPLFLRL>^dLR\TFZTNZDPVNHLFJH@DJ&BDFLVFJD`D^HDVLNZTLDX@DBRHPDNHNBB@FHHXBDLJNZXJRXFPLNDFJR4BXHTB^J<PJJNFPLH\ZBPTRZPbP@R>DNFRJ\FHPT`6^JHPFXPXV@RZHZTRBBPTPTbRb@PZXFBVTVTPTTXLNRP@NXJZHLL8HPRPNPNFTBNLLFVRNLVXLLLJRPTVNBVLPRTBPVLPNVJXZFXRZHHFF@dPJJHFPLHFVJLFVLRH>TJPZN<NNHBVPHHPXJJTL^:@>PTR@J@RNH6N\LHRDbVLTTBL:JLDPLNNTJJTDJPJJDHLTHPNJTDRJZJNZFVFNTDFLHFXJ4NRTLDPRDNNLF`XPD6HNH`PHNTLTTHFRXJDJ@NRXFTF\RTT\PRLLNHHPXNJNTD@PDZP@P@DP@HT6X>NZHJDHNPHDRBRNJH:RXJZXF@HT\6THH@FPLBFDRFXFHJF8@L:d>RDNNLBVN\PRXJTLNXHRVVBNRBPVHLLRR<P:ZPVRVJHH@ZJRJLTLPPTXNFHLB\BVDXLF:RNNTTPJFHVFJJNPVH@B>>DPRZTNPDNTPNHHTJHP>PNBN^T@RV@JHBFVLLBJPNFVRV>V@PJHR8FXLVHVLPHT@TDBPTFNTFRJ4DTDTNPHXNRDFRN4N<XN6>LHdXLR<XJBJLVPN^6RLFNJBNLJJ@RHRPRD\JJ6`JJD(:XDBRLJVVNVN<L@PP>@HTP>JTDNVHJNRJTDJLJTPFLRJFPHHJLBDDLNPJNX FR@LPDNJLHVJ>NJZNJZZFN>L^PHTJBHPB\FHFJLJ\BPFZPRFRVFBPPRHZT4DXFPP>DTHFRFD&LRHJRXZRZ\V\JTB@DTLL@JVV\FRBFR<BJBN<HFRRH<PDXH\LPNPNDLBPPNPZXVRFNXJTPNHPNLTNT0TNHFLR<b@N\FL@R\LBLdFP`:JX:LDL@NBDTFZ2JRJDNH\L<^JLVRXRLPDBFVXLTRZLBBRVHPFJ@TLRRRFFL>JJJLXBPXRPJ>LPLHVXPD@HRNNXXTVLNFJJJZBJTTHJPRL>T^J<RDTLLLFTHJRNTZPLHTFFPDHZFFZNJFJFT6TJJDRPHRVHJRBTFTBHB^HFPPNTLLTTPJNNZJDRRJPLVFJPJVHRDFL<XFTHHRHDBTXLNFVHXPFPDPNHX:TRB@RLRZFLBVJHDPPFNJNPXPLNPJJLPTBTLLFP:PV^HPPTNZDLNFFHLHHNPRBFTTLZ<PBHTXFF<PPBLL~HPDRRXFLD@DNPJN>B>PJN@RJ\TJ\FBHLDNJHP>J\JLJJFFR^NJ4TBDJHXLPHLTJPD>NF>JJB>DNPXVVVNH\FPRL\PHJVNJX:HHHVBXVRDTHDRPRJNFDPBBXBVTNDJVTNLHBJ^ZLLPNLP@DZLB@TJPTRVJJRN@>NVNHPNDVNRPNRBXTHPJXHJHTTNVPNTHNVHNNP^@DRPLR\HHLVD>RN^0LRPHLLRLXPLHRL<FRRJB@@XP:HPPXDTLNNVFNHJ@JRDVPNHFN@NZXNJNZJPJVDRJTbBRXRHPDRLZJHJZLH^FXTLNNLX^@LVbNPFRVPXVNFBZPJXVNTPPZLFPFPRFTFHFBRRNDZNFLPTNNfPPBNNRLJJPFXFJRJT>RBR\HJDPVHPPPDJHXZHFRNRJPHT:@HNBZ@RNNPPLRVFNN@FNT\J>>F@NNLFPVVJ>JT@T8>>XLFFRLHHDRNLTJFT`XLHPFV8LVHP^JPLH<VF@RFJTNJPRDF<LDLNBJXRHNFFPTPVJ>N@LRBBLR>V<NPNRDLFLPNTJNFPFHPHPNT>FLDLJZNNV<P<TRDL`@L:ZV@NDPRJVXJL\BPTZHHNJVF@FFLHTHLHLRTPLHFLF\LPHJLNFRHRJPFVVDBJHJDX@LH<VHX8DdZ>TFJRHT^@TPZDJVBBLPL@NPTZ@BBPLBFNBRP@HJ<NRHVXDHZFPT@DDRHJb^JNZLJX:LNP@JB8BFXLJJDPJRBTRJDHPTD:F<XBJRR`LFH^LZ@HLDVFZHPZF@:HXBP\>LT>HXTHF>VLDR6R@>HPLHDBDLFHP6fFJRZRD2>TTLF^HPJFPLJJLXPHLDPLHXFVL<X^FZNNRJ@PV@HPRN<NFPNL8LPBXRJJRFT<NHF:LRJFJJDBLVNJHPDTJ\B:JFPRJNRTRTDNNRFHRNFZHPRN<VVDJP:>f>FJXNHPDJFHPPN.PN@TJ8NJJVJPBPNHLHBNHT:L@R>L<RVBLBHBLPDN>XHJJP:NZN@LTZB@h>JPTLHHR.bVR<L@PX@HFDXBHPNPJ<Z@V>\HBRHVJDJBFVNNR@NHNHPF`LFPFD<RNNJNPPNJLNTPFDN@JL@LJDNZPDHJPHJNRHJNLFX@BV@FbZVLPDR<^>V@FZFTN<DR\LPLPTFXZ@LTVDPHRNVHDPTNHP>VLDTBXLXHT@NZJ\^RRVRFBPHDNFRLTBNTLF>HNNJHTJ@LJPPNHRFL@TFTNTTRTZRFNNXXVLHVRV>BHFNNNLJHVVPTRHJ>:DPRRDLTHRBNDPTPFLJZ<LJH>P:\NFTXPHNN @JFHJLXJPPNXVFNBHVJ^NF2F<FFLZLF`RDT@NBFXRJLLLNZLJDLNBNHPLHZPPHPBV`DHNNRJ\DXB:JXPDR\T>\JBFJRVTJLLNB^DFLHPZRBRRDZLDJ>RFFLNPF<TZNNHXFJRZFFJLLVHZL>LZJPBPTDPTRVFTHNPRNFTL8HZHZLBLV@LDLFVN@V8RHTPPP^<BFVLHRRRPHNLHVPPPBNPRVLPJNP>PBLXHNHJP@>FTLNTNT>@N>LJPBLFLJNNDH@>LHHNPRTPBDXBPJNJ^DDFFLJRDVLLRNJ@VPPJTJ\JDXH8HNJJBHJLZTFPRNR:VPL>HFHPRHPHDVDXLJRTPDNPP:NVNDJJBTXJPN@ZLTHNN\JPBLFHNRPL\HH>LJLJ\DJNRFTZNRHN@@BLTPPJN^PJZH`DRVH@>J>dPPTBTLPZTZBJVHFLH@XVXRPLNR@LRPRHFLLFFNFPPHJJBZJH^PPHJ\NXDRRV@RLRPLRDBBNBLPJRTVL@PFJJPH2TXHRJBRVDLVHTDTJJNZ@dRFLHH^@HPRDHDPZH:DTVPHRNFTVHPJRJV@HR>>NFPBNRRBVTP@PHLTRT\DRNNLHN8NDL>HXBLJHH:ZLPLPHJF<PFJLNL@DDTN<RRRB@LFRBH@JBTPNHRJZJB<\PV^N\TTXTXJPH@FXDNTLLRT\HHRNT>HT^D`PV>HFPXJFLTLVPZN@8HB8ZB>NNHPNVTT\f^^Z8VTR\LPLP\LTPJFDH`:VJ>FRRNDHVZ>\LZH^6LTJTTJFPHJDFVB8DJZH\>HBNLVRPFJ>RF2NXH`RVNHLZJRVBZRDBVFFTNDJJNBL\PXRHLLR@LFHLLBZJDHJPJPPPPTLFJ\:HHRFJP@BPVVFRHXD8XPLP\NHHRPPdD@JHX@PRBDVPVDZBDDXLZJNHJ8RNRLRNRFRRJHLNbHTPPLVJPHL\\@FVBZBD>FDXJNPH^H>DJ\LPPVJHVP<JNPTHHLVHPNNDLHfT>DDL@LJ<VFJDVJV:FFPLJ@DLJH0FDPLDF0\P@FBPDRJRXH@DNJ<\>TTRVPLLXLDF<HFPJJDJ@PX6bLLF2RHHH2TVDVJRDHRFLHN>DDFRBLFH@Z>HFVDV:J@JFLXLL:6L8NDRLJHDV<@P4<TNJFJHPNNDFRTHLHHJVPHPNRJLHBHBRZRLRTFJXLPFHHDFHRH:BDD@>NHJDNPDJJTFJ@@ZD><FNVPTJRDJDFH2:JDT<RL^NLNVFL>D`TLLHLBVFPTXNFH>HBRJNLBLH@R\PX\JR@HHVXFJLLLTBF:XP6BXDLFNFZHVXHJHTLDRTJPPNBH:NNJFJJZ>PbXLFRBFPHPXPNFJDDJ<`LPDDPP@XP>X^JPNNLJLR:VHJHR:PVLLTVZ>PDVTD\NNNRDDXVVLNJDXFTNBJLHPLPNNV:PJ@HHRLXPRF<PH\LRVJPNJJRXLRBF^FNTRLFX6RR:XNRHBJTLBHLBPLDDH`NJR@NNPFJVJTLFRPXVTLVRLJV6FPJHXPTL\V@JPJLRF\FJF\JJPRRLRXHPVXLHLDJJ8HNRXV`JXNTRNR6XNRNVFHVVLRH<LLNZJNNZTRP@ZPFDNVLB<HDHHBPVRTR>PL:HPTFNDTNNJ>ZB:VHPRHHT<HTHJNLRPNLTX\X<JVFNFD@XPVNHBLRXPPTNNHP>THXXTNLR^JR8D<`BPJH@J@PBHPTL>0V^XVD6^FHXPBF`0JFBJJ>X\LTTHFX@`X6XD\N\6Z0LPFFDNJ:JBVBBR\HTDTD@JLHV8BZDJ<V@JLBR`TFFH\BJXDBNDN\HDRRBRPLRL`>RJRTBTDPZLNDTVJ`LJNLVFRJ\HF:D@JJDJNNNRPVTFLLFLPZ>ZTVFJ<JDLPRPVJVJ>PV@XBP^JXJTHPPRV^TNR:PXFLZPRBD`<XT\HJPFjD@\>8NHN\8RDDJ@RJ:NPHLRNFF>NBVTHFPVHHNTDHJPJ>JBPPNX6NB<XNXLPVLRFTDH:HJR@\@FFB\@\@TL<DRFT@T^HR>RXNHTLHRRNNF^HZPXF^LFTFVVRDLXNDLVVJ6NBJBBLRVPVZFHRZNHP\JDHPHPXFD<XJP@VNRPV>BFBRJJHPHLP@TBVF<RHL<NJFR>HLTT6HBRDFJ@JN>BRNHFR@TPLPXZXTLNFNDH`HRHLNJRNNBNJXNVBNRVHRLR`P@VP`^BJFLVJN@DZNLRHDJJN@F^F:V@@JTXJLVD@HNZPTXBNBDLTXNNHNHBP\P^FPRJHN@DJBP@HPRZDLLTTNHPJTN6XTP>TPRZFX^LF\ZRP>\<NTJXBLFFX>LHL^^XRRXXT`\HL<H4BPTTXL@LNTL6NXNNDPLJFPTJPTLJRVXTRJVRRDZRJLHNL\JJVN^JVR>RHTXRPPDN>^T8NPBN@H\<PRHJVD@6HPXHLXBHXFLFFVVTNDZ:@XPdNDDPDbHVRBTXBVTNBHDXJDPR^LNLVJ\>NPF\NJLJRD@HPRX@LT@DHPX@RJHFNNDXTXDBHLNFRNZVNPDLHBPNHP2X\NPDRP.N\JHTHHLVLRNJXLTVLHXLLJLN@NL\VR@N>RFN`D@^DRNJHJR@JJLBLRDP>T>:vDZJJLHNPJFDZJPJN^J\2HPN:RbLXH>RDNFT.BFVRDHH>RNTPZFH>PHTFN6RD@L<VTJJJPRN<@BHDL<<BFHDH:TTD\RRFRRDFHVLFPRRJNVZ84N@DBTL<>^\PJ>@RB@T8V>>P<NNPDDB@FNPZ@2<PBDBHFX>X>\JDJX<`DNRRD@NR@PLLFJPFFRP\<BJDF<FFJRD^VP<RRFPZ<HHNBFR6BDVLBN\PNHV4>NJDHNLP>6NLTFFL@FNJLRDJJFRPTH8RDZDFT<BNXHLVHDTJP8H8RRPNBHDLP\HTFHLDP@LJ4FP<L:NDJHRHNNRL\XNTJNJB@NJJBTDLPP:JHLLHJPRJNFD8:T>8PNHL:NVP@ZL<B>J@JFX8TPHLJBHNP4HZR@@THTLPLRXNJLTDHRFD>RPJ@FRLNN>FF4DVLFLDH\JTPNB@LV<F@FZPN\PNRLFTZLVTBHLFTZRNFFVRPJRRJTDDHB^JF@FLJTTNRLFR>LRRHTZRFVJJBBHVDFJPPRLLV:J>J:R<DLZRVDNX>N>NNFBNJX6JPNVP@NFXL\PFPVVJNR@RHDH@^JFNPNHHP0R>H\\LH@RNVTF@VFNVBHDBF<LNHVBTP>L@LDPPLR>NRLHHXNHTLNLDLRNPBBJVL^`@NRHLLTBJNJFVNPJBRRLNFDTRPJTFRLRZ@RP@BRTRRDXPNTLFLNNXRFTLFJ>PXRNPX@VDB\FJJ0R:b>:TFNN@LFRJRFDRRPN>NNHBXHLLjHTDPLJR>\LDJLZ48HR:NJB<PHHHR8LNNTNDL^J\NTHNNL@HTNRN>LRNP^><@RHDZPR^PPLJJLDJPRVNL4RJVDXJJNRPPN@JHTTRPXNFBDJFHD>@P`BX:@PRXXJRDJXDDLD>>TPRB`P^LLDNPJHFLPDLJHD@H8PHRLJDZPDVFNBH\JRJTFVJLHLLHF@BRPJPBNTV<JDBTJF>LLTDVDPBBT>JJPPHNRFJRTVJLDRJTRNJXNNVVBPHPLHVRNRPD\RLXPRFVD<RR:LDXPR>BP@X<F@RZL@NFNPVHXLFRR^D@B>LZPLVFBHJJDBJRN@:`N@VTDPFTH@JHVDJRDPfDV@JND8H<JFBF>TNTHLDLNBbDNBDFBVHBRJ`BNVNF@JB@RNNJJNFFRJBJJHJ\XLVFTNPRHNLJXRRDBPFXNT:LRB6FRBPF>DTDFFTP\LPPPBPJXXNNLN@JDTPNDZ@TB>VHPNT@RXRDDP@LV@TVBL>HLV:LXFRPNVZFHZRPXFFPNPRX@RRNZDRZRV\P@TL\HL\TFZRLFBFDHRDJX^XFLPXTFZJXD@RNPNPLPJJPXPPHTRJDP\6NFJ\RHRHJDNHPNPRHZNNLFRVNRPNJDPF^RVLPP>NLNNP\HJH^PH`H@XDN(@@Z6>6PHVNH8BL<L@DJR4F@LL2FPDJFFJHL:TN6DFRHLL:XBHLFPN8JV:DNPTTTPBBBLTZRBNHVHLFJHTTJNPT>THZLXHfRXRDJXJ@HRB@JR4PNNDVFBNPP\P@PXH:JFLBJ@P\JV@LPFNRZHF8<R:J@F2P>JHR:DHLJHF:HLHRBLPFVFT@LDP8XTNXDBFTJJ>JLLJJNBRJ>TFLJJLN@P0JRRFVPTNTLP<TNVFRJJJPHNFLH@NT2JL@TTLLDHHRHPJVNRJHFZRPBFHNLDFRFNBFPXBVNNLRTNDNVFB6XNRd@FDLTJHJFJRVDXHJ@VNVHN@PFRP8FFBTNRRPJL^DRTLRH<LNJFPPT@HNTF@NPHDRLFJ2<<BFH@FNHPVLNBDLL\TB@LRN@JHLHPTHLPNNDLRLJRFLVRDJDDNRLD@@NFFP@FHNHJJNFRLX@HPHPHHBJXJHJ:H@>NRNXBNXXHFFNFVTHHXBFBVHXRNHJNJLDJHNFR.JJLLLBJP>LJDB8XJLJLFHPV:XXDRFPHRF>^LBTBJVB<NNDHJD@HF>>@TRLJLDRFHXJJNDXPP<VBHHBFPXHb2R@TLNPRDZP@H@LJXNFN>JFFJHFLBZFNHJLLDD@LXFZ<RFXV>HJLDZRBHBPFJLNFHHHPNHJV@XLNHPVJTNNXRDV<PVN<NLVFPHJRFLJRFH@T\TJNHJRP>LHTPDDHR`NXTRDFL8NBL@LPZD\HFFJXTR2HHLT\H>NNLNPHNJJZJNXRNP>DLDZDDZ:DBRNPTD8@THXJ\>Z6FVHXBPJHHFNTJ@R\LDLZFZNFV@JPBXJJ:JXTF@NVH<@XRZX`2RVNHBJ<NNPHFNFTTPBNJ8LRLPbNJPJFJRDVRVDFXHZLL:Z>NJFNB^LXXJH@TJJPPPRBT:LDTFRVF@JNF>LF>HJVVRFRLJJTPJ6JHP@VBJBT>JF>DDRJZHF\LPPJF8TPPDF@HRRTPXHLVLTFHTFBRNJNNRPJFXNL@LN8BB@L@P8ZHZFNNPFNN@FLHRTHBV:FNDXJ6JFNFJBVVNRZFHVHFBVDBDPPJRJJJFN@NRTNPFLJFHHRHPJLRBJNRLRJH@@N:FJNR8DT\LTFJLPDXPHXH@VNXXD.RHHLTDD6DPV@HHTRDJRLJ@PLLXHFNJFH:PLPJJF4X@THNRVHHJV>DRJJRRJJ<NLLHJP6HHBLXDZBZ8Z:HLPPPPFNTPN\FFLHBPHTNHXNNNHJLBBNVHT@R4NJNVLZDTHNVJTLRBDBL<PPJNLJJPRNNHNBD>XTPP>@J@HTPBJVLVDTXT<NTHLHLZXFFPNTJBRB@VXL@HR\LL<FDPLTT\ZHJTNTDBNPFNXRFJVJ@LPPXPFVJDDTFFH`RLJNNDRVP>DR`LNTDFNDLJDJJHPFLPRd6ZZJLDNTRJX>RP@T8RTF>JNJ8RBN@<RPXNJXJNVRPLJXRJLBJLHHJVJLVLJ@VLXTJRFNNLHJNHL8RVNLPPJXNRbDNZ@HXFTFLBN:FV<PHRNTZ`JJZJNPPP>TBTHP>RTRTXXRbH<PHVPPNBVFDPLXJJTLTJHRFNVRHNZ>>V@FVHDLHJ<PTDT^@ZVLNTVRFNDH2XR:NTRNPL^XNDFN`NBHH^<T<N8PVDNJXN@8:LTLFLFPRHHTH^TF<HPRLNTPNPLTLLFFLLDTDLBFHLHVFNRDP2TDRFRNHLHDH<RRTJJJN>XPHPFFF4XJVHPTXJDF>48J@LDP<DFBHHDN>L2DPDLHLTLZ:NNNLLHFXHRHVJ@LLFRNNTLXJBLH@JRXNFLLLLXJNDFLPFHJNXRb>H>H:NTDBLJVJHBV>>NDVJLLTPJJN0VZXL>J`8:FRNDLFZXHN>JJJ:JPLP@PNFDRPJNFLLFNDFLBHHTTL:VBNFFJBJRRHPVJDTJHJ@XLXNXBXBLZN8NLD>JLFT@JXfTHHR<NLJB6RJDZZFXFH@HND6:6HLHVP>NVTTJBHHT@HHJJBHNBB6DJVHFVDDF\PBVLP@@FFDJFL\@:BX>F^RFFXNBR@D6BHNJ>N:TPDP@LTLVRDTPNLL@XFRLJF<LJPFTDDPJJFXRNP@RDNDRN>8LF@PRFHH@TVTBB@JHBHPPPLL<\HHP@TLVHPFBDR@VF8RFH@XJRRLLFR>BJHLBHLRJZ6PNLN<LNFNDRFLJRLLZXDVF<bFFLL@P>JFLXBTXNNHJTTHLTLXPBJ<FN4RHXFXLLJVLR:HR@RFP>HHFHNRHXLZ\NPNNVZ@FDNBRLRBFJ2NFPJRFRHDDLJLVPLVJBDHHVJT6DPJDJFPNLDPPHLPFNLLJHJJNB8>DHNZ^HLPRFLHPNPV\HVD@RJ<NJ48TNXHDPNPBTBV>P>PRNLBFF\NLZFPRBNH:P@PFLBLRHVLSigima-1.1.1/sigima/data/tests/image_formats/binary_image.npy000066400000000000000000000236201514013333200242400ustar00rootroot00000000000000NUMPYv{'descr': '|b1', 'fortran_order': False, 'shape': (100, 100), } Sigima-1.1.1/sigima/data/tests/image_formats/binary_image.png000066400000000000000000000333541514013333200242230ustar00rootroot00000000000000PNG  IHDR&6IDATx]ٶ*^Ɂa~>(Ed0&QRJ)?O3}(O3`O8~'?G? | @4>+ 7QG͉D>LܗkRAgp iӺq'D 0ΆVlwRJ)$iŇ=]vK~Z_}7>Oo2^Nc&`z:qcG6/筚>,]@x7rժxB>LeZ~@ ȝ|ZI_p98hnV<"~p_lh9Pw'tAyjׯNZXGӅ:ucO1%!`,? LVM:K'$ǿ !9z X.}kfOh|ܺ-̜]ev(|s*pA`qr.cpˡm>>sG~h+Q5| #bz}ĕJ:j|1B;h\Bn&zoşR DJXZA2xUr xe,%?['c:{cqR߫KBןӒݻL9bںQl vC)5F=G_R"^6[K#=z7`$^G7/ Wk31ۭY*rS.-Rfgn'K1\sb]fdhS! K ;@j!%oӟw,Q6-g/ Ûhk[Al|۱sNPwC6C7Ml y 8r F{0GJL=j) 2|3uRam 3P hq4S@M r0 ,NE'j΋w[<-8dFSQ$%)q&挛!8;s6?!l W\*&|k* 3c] >^ #p'!Pi㡵JW̞}Y鯖%TΖix6LdSGFz 䗴 L]|j7йb≚Uzcx ^zp׺Qb[۲CR_DP-Dz:p LCQzl$ZLo7RG[p5zx"sSvLbIj [;SԿY>t`lD2qbՙH7Ql ͌έӠ;K ?V0gXY!nޥ7DW% ^>r܄#(ҳI YZ9鉔] ՞#D}B,0 e ɯJ' 32>oIlv mI1Dٗ@))%%+ %''Υ5 :kܓZ_U;G>- L 5M$0>%BVacY-!fs%u/F (܆]w( (ݔ3n9oٜRfӱ=e*KIy S(ɯc]X[A~n*<'r X=.bbՖa&d qb @0> Nx -GTY,j̫reto&ыyWfr$9 +ejՅZbrxTD^.'1wTh@q$[z]G}{0@uDU\mx0)o?Ԝwz9tca0ёT rH- \U1Й3ÂmFP6[]`5[ҫXau͞zuT0sCiM1KRZ=#7t-=yc}m~g` F;9sfBQ$!lIW7@ʰMk$ 1{^vM !']j[RGYrО 6d荲ڵH9ohsC L'׃_(f93i6q㬯hoT ghH`t~޶s"8n $0t([@-˂y6\Jrfu@U0t.V?UB)mp3d=oOd4fHO?f\(,_חY|p7gF lW_S>vkvD?"ՒKABG JLёE} Xe}F)1Uw1Ts R!2+Z7ZQ4y.hc*T*>TJx)A}2@f~$`})%BPPW>iN9m/9 7gllzpmg"(Qpx8KkDO|C\>%y3(CkY,4Biq DL֥rJ]%.$i4kOUx7x b=22j 4Jᙜ4`k_P1#x3%x fvuhQDV*0*6j]^UF@VZ\H!?1e"?1na$VVYxpºmhT) P(%]E-?X1G$ؘcLz^9FU;PmƘ!L&5ɒ3UW6j`CcO$nioE)H3LS HJ7a#z5nχVDحVUS%\âAcpwzTB'YSB XӰtiy )L:Oǰ&a#qNqPya0Ug !u୤d4FBRJW#.G0'ƿJqJ( IIv $Y=-(VB;`.:ڥx&F?:\p4WjC.l ڦaGP2ϐT-VkFs$!FCSr؏5-&R3s;o˚RFdɍ~95&nsǙN</\7/141(_[BjkFU*N'pj!$J4e8Rx^S+JY}ݲʃo[V;V6SƳ%'hԩsAX!c X%Ga_Y o@Stt~m(g_p(Fa95)QuiP'3ʇka/<^-dl݆%9F"YfXqZ%9>btBs֐ӜZ>p dbSA~c9">;A,@J'–%oO)NT>46 _>'}ex_cQ-A1DBq Sy>:E=`_||an_pi<8sj s=VugOFHEaqb@%$qQPSsDQU@($n˳jqv ۜPVc,C4dahsv+gDzN46pf"Jy|5{+^ۖǶK5,+QI@'(7ɯJDئ4,SpI!U_\{YJPƉ.zՐ/X!Md&(w+hkF}sDU!4Th5bhX<˅IoX#v1MU?7۵_8] z0mEl\:%~α/v QJ0E;fi_-[r`3CCxcc(=Tt*' k\Zg2guK:*h)5lbD p"ɌuL(&,J +ZS;.hG? &?=2-sdS [yJڲs,I)$kb?~4]i`n ^.3Wa0(O 9 h<|FʼnprXC Kj=nf&=Q֨ο=,X4udU/=I^\ڠZ!y>@PzÿӀm_Y9 Pu`|l$]gqSev<Қw)z{e7-@S~v\S:u/]NW&m#=i,X֍L*A ;|ƗCaC1^N"c7rm.K[H#w@O,>1EX%oUc -0M50ǹـ{qDɉe0n ܹ \%Ԑl55[(TY1#֛:rNJE6'_v,o`֪"Y e 5@?EF. W9}Xu_t5:(`c+,a!u1|f'u6_J|Ϟih1ItZ4Mbmu<'R U/HqW| ^ = Py<:`;BklBEdHIBA_v`KgwaO"}tV>XqU.@) n`>-9isM_4 N,܇(+:QQ(Y6_t `oѼU'V蒰-U|sD+0CrB[}QGQKМ Lh#ěrdmuPk͓\ą8& K UQtN3"X}fswG9y%]:fn:I&D k@bZ֔F/_<@xӵE )RE3 >u_B@0>`2*fs7,P yj~AH!"pty ֋4u#c)-gcNjSgVkf 쫅G(''҇w87n2¼ Б5F +mBiq2lm9/2a Ft瀙XlfZHxW }Om"P|-~51 [A8\B=*G@(BB7ӛyW KMx C–@!h|[cC%9Vt VӊX^S\ Q؃#bEЃ_t]>v` Dwcw;tB;}l 1 &+Hs4o6466,HXA_ҥ54q6fd?0q0E,v΃\0 #bGJ!4=6h'Owxb(y2:N? uvs^[Ͽim=l ~c(x7cg@V<*XM* 9 p.'}Qh] V CA~)Y8hXfP.4Lt6Zr=o`m:c$7\X̚Fuct ,`u=cnWvRO1@~ʪsK BmIxn ) e|̊ym%6{]Kc]Yl/i?[#3F塞(wK oys̤˹q畺4Y<1Xf(YuRz=CǗym#5LKp XA~ު&32TIAblV=ec/Op*lP>)X09ݐz|ơ#T}8HsOH e.bD)\R$e].}{yְA=& jS]w:F=g:/U֖ =j䈺yCz9eEKSEG,AߛFKs du=hJIj9.;ʼHz%3qoTz^žx,sAG׮s%˄d 4609gr?BٍA^_i,%IjBJ덻&4~Mɂ'1C |*8\s.GyZןM;/>r/M7VT9GPanVӊ{Ɣsl-D%xȮ0 yO zf&oJsepu*uq/x2 Pn lp,`Q @cOƣk+-d2&m;{,(G;7v@YWDA;3d4l4h㖯XkB8H 4IXdn7/kڒVēڸ_* >˧4(U.՞p_MDl=:*gk [K@>z!l]CNJ{ v?̈"*Z $:Ql d)a{`u4[?vz#h!EsN-ſtlxYV dRK@sDL؜FRA@7`ՌM=LzŤA %`P\@ߒ;j0yھOu5(HX%D hqO/[r!oF(xO_oOH[D"# M]4?%IC1hH/ N\`!YRl%30.m(yܐ-pIO%~w~H,*qH&whJ_nR|8vz^QG1 nPݡ'CY  ꤵ ~Gsf?fe__oXQ1q:cՕdmZi̐k^Xa cϋXt&F&֥}Y!‡۹s/Xh, Dc[ɭPcGޡ &6T'i3''a<-CE1s {GcL#ӭp۱(+EO*c?Xߌ3ts%dN2mxA!j JZs ފ^ x=r%ܻ _udQ:@_&Xw M>P xXt]AD1|[^ѝ#0v[`RCntsT 7E?A+%v'%TД*X%.MĶeeƇ!ɷ c,µԂlJR$XYw+ggGVe\Ƚޮu-J ;^Z0?5Rh/D|F=v =а+{]Ľ;kQ Dj~ہ~vZ%V T:#@؁ @M>&*6ZxfS`ɋTmoYq7,oA~zI >6]3g vJ$'>CfA6De^eu ߛ%.)E=U/Ū(>Z^^o?}˼ 0/I'`5#P}%` BM^d @ETCox<CA6eC9v|0(t&ApJ -KzmeJ}oOfGG pzJPUib RbdXѷ/ Z;H9T~xp7$_&]^+"_&7&h/ }Aj+M`߽C]MCjQ`bٓ(.`oTQP^"u6 Ե'Bx4C>mꄬn*)}upW҇ ɑ:+^ZM"TF>[\o;PS^4`X<~24FzukQK@O 8oȎޯBq~8K~j$%~8AAk#* 8xQNȻQ%X^%M??o?vx@z~DfuDz_&K0/[9ySOlxhQ7͵xS62vӾ11 lÜ_u06%M¥JH)so"I窩 N%xͷ xn砕b|G ٟjZ/fm&g.&&f% %c>5$7{4@Z#ֺ/r Bwp ߳ wO ѽ+Po!$u;~,gm$=K@޻Åo J?opVF~WO8V _+?`{TRIENDB`Sigima-1.1.1/sigima/data/tests/image_formats/centroid_test.npy000066400000000000000000004706001514013333200244640ustar00rootroot00000000000000NUMPYv{'descr': '^D7DDDD}DTDuDPDD$DD_D DDDhD/DDD-\DȶDDhDtD>DDDD¡DoDDԃD;DˍDADDDDlDD@DzD~DDDDDDWDd DDPDMD{DDD9DDbD4D>Dr DD%3DRNDD.DDDRDDDRDDD= DDDuDVDn D]}Dj<DXDXD} D D[D6* DDDD DEDBPDDDlB D\ DD= DTj DD>X D* D] D=DD Dڲ D`D!D D D>TDD Du`D4DTDD DSDDDDoD DUDAZD DA DD2D DK $DٯDD} D8 DDDIDDgcDD3 D8 D1 D$DuD* DZDfDDDD Di D= D DDDDDQ DG DDRQDu D D[DDVDMD| DD4 DDDxDDkD} DB DS DK' D.DpDT DDZDD*u DDMD1D& DV DCDD v D)DYZ D DODD/ DDu D D-DD DDDXD DD)DDttDID(5D{kD)DV2D=DDD^D{DDDDaDaDοDcDPDD$DDDD D6+DM2Dv8D,D /D^DBDDpDDҾDDDDiDDDDDDQDy\Dk,D$6DDD1D\DTDADʿDNDDͽDDDDDDDD[DDWD`DwD&]DD]DIDXDDD'ODAD=DD!oD ]DDDJ~DYDDDJD^DED@FDnDDkPD9D@Dh[D$DDRDD/DmmD9D;DhDD9D%DD9D~@DDbDDDDDDDDyDb5DMDD=WDiD.D?DD@DDD'DDDBDDD D7QDW'DnDD,EDc6DD4lDODoDRDz,DfNDYVDDDKDDEDLD9~DDDXDLDZDu_DAD"DQDjD^D DD*Dh*D9%DfDSDDDWDD[DYDGDDADFDDufDD>DpDCD'~D\DBYDDzDD DD&D'\DD(D D)DKDDDDЀDDFDP5DD=DGD xDDDDDgD4<DCD!AD GDD5D{DDqMD1DrDD eDuDiDDӯDKDDD$DDcDDDxD?D]mDD DD?D .D2D`@DHDEDDDB D DDDDZ DsDD DuDxD\D&D6 DlDc DD^ DBDD)DD DDDD̦D[DfD DcD#\D۽D8 DHDGD D DY Dݶ D<&D D' DhDЂDD8 DDD DDDD$ D DuZ D Ddž DD] DD˭DZ DED DLDDF D'D< DDiMDDDD DH D DF{ D%D DsDK D)DDZ D7DD_D$DUtDDxD DbDDD" D D9D= D<DDbDׁD% DADDD% D/2D Dm DDj D+D?G Dv D0 D D DK! DD D D D4D D7D D?{D?@D DWDžDDeDD DӊDgDSD;D/DsD@`DUSD3D 'DZDaDJDDyDDvDD3+DaD-DDoDADDDD~DDDTDDDD DZDwDD'DLzDMaDeDXDZDDq DNQDuDD[D'yD?UDDD7,DDD(DDDQ}D"D"D=DD2D`DjDD^DۼD]D %D1DaDyDzmDDhnDq(DПDDZDD4DSDDd0DmD D*D DqDHD3DDDD_DD $DDDQD,D/DMYDDDD D DjD=DRDDdDD%D"D=DۭDD*DDD6DaD{DD4DeDQsD)D!D'DDrDDDD :DDQD6D,2D5DϽDbyDh#DD&<DnD,DؠDDVDTDDoD DdDΕD;DSDZCDi-DKqDDD.DΦD,DˆDDDxYDoDDbDDOD!DDXDrDIDXDDܦDDpDDZDDD{DDDgD.pDEADVDD̟DDMDDoDDDѷDDDDVDWaDHkD. DmDVqDD'DDDDaDVDDDAB D\;D D+D?DD% DD]D DDD# D zD DD D7 D=:DDDDDHD D BDvDDDDD0D D%I Dt&DDND^ D;D*w D DaS DBDiD DVD&D6DRDDN( D) D6 DC DHDQ D7 Du D Dh&D8 DAD%D,DoDÈ D=DIDOD| D+wDDvDXDV D8(D DDj D4 D DGD6D{4 DD DDDBDD4iD D DD(DD D Dk? Dh D% D! DDZDDDD^ DDDDDD͔DDD DАD|D\D(DoD9DDD68D<DDc]DDaDD[DPDoD6?D{D[DD\TDhD5yDDjaDFDODD-DnDj@DDeD<D)DDDWDBD~DDaUDnD:YD7DDmiDDDDyD-wDzDDeD\D0DDeDD)DDtD9D DD iDDgD&D0DZDDDbDDBDDDl^D,DDD/DDD4DpDDDODJDD/D|UDDYDDD2DbDDD0D-"D!IDDDoDDEDٺD DٜDٖDAD&DDQD_ DFDx DcD[ Dy D91 D?D7/D_D` DD DU2 D9m DD Dd Dl DS3 DDSD7D D%)D_DD D7hDXH D DD D DDF DDKd D D% D DQhD DDD D,! Da Di` Dy DJk D%bD>DD D*Do DDwD9D^Y DD]D3PDwRDVDD~D? DUs DDsD DDDcDDq^D D_D9CDDDM' D =D"DW DDvDK8D]w D D+DmDF D6d Di DDwDtDcD D?DkDyl D DDE D D:& DD D DvD5 DDDCo DkDSDADT D!eDԃ D D~ D D8 DvDcDz D D> DD. Dg5DXD" D DDjDD D^DDaDDD<DD{DJDUDKKDD3DD@DD)DDjjD+DDD0D4DX0DDADDMDlD7BD;DXYDuDqD DDzcDDrDsDD_D5DDDjDV)DD@DD|D DDvDڼD1DDlD^D+dDDɳD?D_DD$DDDDDBDD DfDDB0DRDSDDDDDKD<DDDjDDDDoDDDD>IDDDDDD}qD&DtDqDyDDDPDDDDDy^DDuD2tD5DED+<DZqDDmD^D6aDx:D^DQDcDD^DDD8#D0DD<DoDVDsDDDdDdDPDDOD4DDD(pDpDDuDDD[D@DkD<D*DDD6DΑDPDvAD<DDGKDDԙDD3DFD"NDNDD\!DpDlDzDD?DDDPDD\D'D1DDD:DDDDDDDD@DIlDmD3DDDLD D _DCDDYDDDqDj/DDDED{DͺD6DTJD*NDD+D,DDADDDRDͫ DND DWD+DDR D'a D!D DgDG^D D%DD D#DdDNvD@D DwD̅ DDv DDDd D OD DUDDD DDDՋḌ DDDZ D~ DD8yD~D³ DDB" D DD DDDAgDlDJ D#DYDDHD;D4D} DϛD6 DD D3wD\ D DdND DDvD"D DD|DTDD DDD Du DDD= DdDߞ D!DDDZ DDgD D_D;! DD@ D) D)DED8 DMD DDv D,=D W D DDe: DZV D1 DB DDD D Dh D«DGD D$/ DD3 D D DR D7 DDh DNDEsDJDw| D DYD+)D<DDlDDD'DIxDDDDDL}D DDCD4[DCDDDDfD8UD`DD6vD DDDsDFDmDDDDDDkDDDD ?DEDLD=D_D1DDD9D[DDD$TDVDDahDq?DDXD6DD)DDLD0DaDYyDYiD<DQDPD҂D;~DgD%=DuDDDrDmDlDDԳD7PD+{DDDDDZDaDhD}DD=D#D Dz DRDDDDuDC]DPDD%DvLD^DDDDDnDYD DDD; DDD^rD94D|D*DDD{DD>DWDDD DvDDjD`1D}4Di_DNDDDDD:DDDPD@DDADGDwDFDSDnDe+DGDBD D D D:D6? DND7 DA D-ID0 DqDDX, DD4DQ DDDI8 Ds D}D D-- D?D Dy D= D&$D DO DQ Df+DQD9 D8D!Dͣ D Du DD#>DD_ DDF DDXxDDDm DJDo D( D DDDDDY*DA DwLD Dp D D3{ D*B D>DDƊ D' DDD\DDYG Dd D D#D, D DdZ DMDDDDD4N DDT:D_ D DDU DY D#DX+ Dz!D.D0 D D DD D D D> D DDfDS7Dh D7 DͿDD_ DDDj!D DD Dn DUb DE'D.] DXDD[D D DD(DyDODDbFDdNDDD)DkLD]DC=DD+DADjD)#DvcDD_D>DGDDVDRD$D#DDBDU@DDD|D)DD-DDDsPD6DDpDDD@DzDZDDD0OD2DrDDDUeD?DDTDDSDhD DfDfDFmDcDDDDqDDKD_D DtbDDD7DD1DDADDHDVD\CDDMDHpDDD1/DDD DKDyDeD>DD jDoDhDD*DYD9DwDmLDD?Dy{D0D$D>D@DPyD)DDFDDdDDLDD5D;_DDQD!_DDD6 DiDDgD Dg%DID D"D(DD 6DSDDDODdD D mDDD{D!D^DQDtDuDDD"DSDDDV-DDD|DTDDUDeDUDD% DDDEDD@DDDKD(DDDrDqD*DED*D+DDDDlDDzD DYD^D"D3DDDD;D$DgDLDwD DDDD-DDtDAD#DI;DDZD%tDADDDlDLD3DZwDZKDDD6DD>D D3DD MDrDܵDLD D\DDyFD`JDD?UD DQDDDDDuDD1D,$DhDsD:DDD$DD}DlDDD?D5DJ%DDy=DD,mDDlDeDtDq4DmD''DDHD DHDD=D4DD"DDncDKDR8DUDDDDDBDrDDDVD[D DDDxD,gDDCD=D DDT|DU0DDDTD`DeD]D3D(D>-D:D;DkD&qDyDDӋD"DD(DDێDDDJDDDNDDMmD^JDYD $DZDD;DDnDDDjDJDDD(DMD1[D_D(DDDD DRD۩DDD5DuDDADD]DDQDsD-.DDDDD_DÑDJDDinDbJDD=DkDDbDD2DDDDHDDDm!DD{D0DDD&DD60Dx}D%DjDjD00DdD3D?D{aD~D{=D{DDokD'DBDD=D0DEDDwnD̴DgDD&DuD5D2DD DtDDIsD!DDkDmDD|D4DDwDjsDD DD`DD+D>DfDDDwDdDQ-DDEDD5D0DllDqDVD`DDDRD9DDXD^D>DDN3D DD|DPD#DzDU DDs D4 D9 DP-DD} D D D>DEDk9DDKD MDdDtDD@DDRD&` D„ D+ D D& DJ D1DD>DaDߵD D!D| D` Dk DDjDmD DD D D DH D)D DQDdDʙD3D->Dk Dm DD D D-DzDDDDw~DD DwD0 DJD Dx7 DL DD2%DD;Dn DD#D?D D DYD6DE?D D DPDB` D DB1DD DL<DDD DP DD DV DzBD8D{Din D DG<DDfQ D+ D8 DL D DS D,D[ Dݰ D DWDz DXD$W D@ DD1~ D Dx DkDCE DJDD#DeDށDr D-Dh1D|{DrVDDDwDtJD/qDDYD|DiDtxDDqDBDDsD^?DD DDBDSDDWDHD/DqDDtDUDcEDQ}D"Dn5DDӯDNDhDUD 6DDD=D3D=DDD-DqDD$"DzD|D)DDDxDGDlD߹DwhDS D8DDD؜DDDpD;DJ{D{<DD>DDDD!DDD DDPDDDSDDwDyDPDlDDD*DDD6KD(ADDDkDDDD؛DD>DlDokD2DDtmDD_DDDDD,DD:DDVDLDDD\D/!DbDeDBLD)D)DDdDDDDD?DoD֡DWDzDsD5nD9ZDDDIDWDe1D!D=D DDxDDDDMDQDvDDDrD DDV'DDDZD6DjDDDiDDLDrDD?DPDӿDDDV)D{D)DDED]DD4DVD?gDHDjD:DDPDDDDV}D/D77DMDD/D+D:]DPDfaDFDpDϮDDQDjDDTDaD;DVDbDD5DcD{DD;DdD׈DD!DD&D|@D-2 DD:3DC7Dj:D] DDK DG DSmDDDD]ID-DDDXDDD*DRD+ D: D O DDFmD`$D `D_ D DNDXDDU!D8 De!DHDCD_ D_!DDhLD0D¸ DQDQ D+DaDDl DLD_aD D DDGD DD D3 D[ DeD0 DD Dk DaD1DDkmDDD8DwDDZD )D&D˴D,D>DDDdjD|D/?DN=D DD8DTD&DCDRDDDhD#DDD+DDdDzDDZgDDDDDDYDwD|DDD DVDDD}DRDDDED}D DDDD8`DD(wDD؆D$uD8DDDfDpDTDDoDVDćD)DODDDVDDDDiD#DDcDbODdDH&DfnDD DDDEUD(@DbJDDD,DcDKD$D)DW,DNqDDDD8DڷD}_DDmDQDnDKD DD,D\DrDDM.DD,QD"2DDDDDD}5D'D]D?DD:D+kD6TD&RD&DDl_D.DV$DVD6DDD8D]D͗DD#DbD]DD/DDjD|DDnDDǁDDDDDDAD4D4DXD&D DDDDtDjPDr6DaDBD?D(lDDLlDbDQDYaDD_D:D"DDDD^DfTDDD&D(D| DDOD-DDD DLD\DUDHHDD Dn+D"D_DaD DDDxD: D֝DAD Dj& D'D0DQDDD DDwD D9 DBD= D/3DDDDDתDA D!D@yDYDVTDZDmD$D-Dk DDN DGDr D`rD0 DhDtDD PDD)?DI DLD$S D)DD[D]D>DV DkD? DYD:DDD:DO9DD3xDD=L D D+%D2TD v DD`Db DDDʅD_#D D tDLD Dm$DD D$ DD D DSD$WDD~ DvD DPDY\DD, DDR Dz\ D?DDhXDi Dl DRS D}` DcODiDID}DD 3DADVDD)DsG DI DP D DK D D D" DFDD D D<D DUD DoD DDD DHD D5 Do D^DD<7 DJDރDD?DD@DCeD cDSDDD+D5DyD^D D-DD DEDDD)D(D`DKD3DD`QDDXDDDg$DEDBkD&DD@GDg]DDD,D^9D'DCD D7D>DDDcDvDDiDxDeDD[D/SDDD-DD.D<DDDD<D DDDD.Dz DFDE_DsWD\DnDHDiD DD^&DDDgDCDDD]D@DD`DwD DT0DDJDwDFD;>DTD D̞DYD D3DMDtDDg:DDHMD\;DaDDSD/gDʔD DzODD=DDD=UDDDQD&DDiD{DHDDn,DDDDwDmDD DD2uDDD@ DdDdD;Da,D"DD=DD;DDDDDDDD0;D~DDnDpDJ_DD6EDD9DDNDDpDMDKD}DFDɲDTDD1DDD)DDDtwD4DD7DDDl D]DDD?D2DQDD3DD4DPD5DDKD5DDDVDiDLDDDr\D3>D/DDPDG+D&DHDہDDODmD&DDD[DDDߌDXZD'D0(DWD DeDvDTDfD̐D;DDrDDD(DުDD>DaD DtDpDDjDDD^D*DD`D:DbCDX'DDMD DeD_DDDuEDWDDEDDýDTiD`DbjDnDD/_DpDHDgyDvD2D+DRFD+D8DDDn D|D D$D+Dn DgDzD D'D< DD$ D D8DDR= DN DlD DiD0 Dt D Dx D D!DDDG DDT] DD DDDM: DDVDDD@/DX DZD!{ D+ D$D0 D`D Z D D D" DD D֤D DDBD* DK D/DSD5DDID*DHD DCDMDpbD\D DoDD8-D D D. DiD D]Dj D\OD1DDNDD%g D΢D DfX DXDm DDDJD DoDKD DD)DyMDLDpDDBDDD! DS DDDJ D D0 D= D]D DRm D DOcDk7DD* D\ D D9D$D DYDD"D\bDD&Du D D/uDk Do DtDDeD5D DD$DD5DD&DiDkkDDD DDDDsD(DDmD?DDDDD#D'DDX8D1D;;DDDUD kD"]DD@D(DIDmDݲDD D3"DDeCDMDDND+DUDDD&&D2DDDDNDlD{DDdDDjD^Dr)DiD;}DYDZD6DxD$D[7DhD$NDDvDDDDv6DA^D?DDHD71D=DD DDfDDD6DoDDZDD+D@DDmDD)D8DDwDDuIDDDFDrDDCdDWDD->D5D'D]DDM3D3D2DDDDcDD"D)D3DDYDaDD^D DD\DD!D~DDLDD-DXDƈD_DD>!DVDoDHDDAD;DDNDDQ D*D D D}DDD!DI D l DtG Dת D wD D'DD<D-D DDD DRDܳD2DRD:D>l Dp1D DH6DA D_2DV D+L D DMED"jD,D@ DNDDAh Dy D4DǮDD\ D+D?D D3 DD De^ DJD^RDK@DhDGDW D% DD.!D?~ DDDD1 DwDD׊ DAD DjD]&D/DDD{D/ DD>DR D^= D D D;"DxD DDDdDE DDDsF D D DhDc D' D D DƎ DӲDD D'D| DD D)DxD6k DD DWDD8D(D|2 D@HDeD|D& DbDD DgDDThDB D\ D DjD،DpD D;D D6?D DEDzDw D D D. D_DDD DIl D}DD.FDD;DGDND$uD3DD^5DaDDDƐD5DZDDXlD]DDۑDNDDD]DDSDD&D(D.Dg,DhDrD`5DD;DD|DoDD2DqDDDBD(}DDAxDDYDDyD|D\DDD DFDD-sDVDD]DADKD- D7}DDD9"D-DHDDVDDDsDDDbDa,DDDzfDDD?DsD8XDDI>D>DfDfD?[DD D8D%D&D9wD>DD]&DuIDDbDDM D DDD~+DcDD[&DuDuoDD&DJDD DxDP5D=DDwD7 DD9DDDODDD%DDKD`D8DW<D `DάDYDoDD)D:[DgD;*D|DWDjDDyD[DD"DvDDDDD1D4KDD]DDBDgDDIhDdDDDJDDD;D1DDq!D DDD!DwDDߵDDDíDDX=DҕDSD>Df\DϰDDD-DRD]4DwDi DODDxDDWDq+DQDDvDDjDDDpDMD DlDDmDcDzD:GDDKhDDyDDD9 DED@DDD3Di DD"DDU DO DDmDyDc D | Df DJ DR DDD4D D"DөDfD D&D Dk D D_f DD3 D DDrD-sDݨ D+D D6 DD4q D^D͗DHDǂD$zD+D D[%Do DS D4 D D,DDw DD* D(+ D D7D3DDo DYDDW6 DMDD D3D D D2 DAD*"D- D DDp DDeDD DKD~ D( D3xDnJ D DD SDh DDDr#Di D| D D D D`D DDjL DGDD.D D DVDDD#!DD/!DX Dr DDmDDDPDYDDJD DD4D D{u DD D D1DVDDDK DD]D?DtD eD Dk DqDolDy D'. DD D] Dm DD%DD} DDD D(- DxD*?D8DBDD%DDDDD!DGDHDDRSDhaD_D]JD6 DDEDqDdDDDDDDGDDa}DD_D`DDDD+=DD7DDpDsD%DDDDWDZLDYDydDD D¿DDguDCDvDDDWD @DDߥDDpD}tDDjDDDD%DZ*DODDDfKDMDDDHDDDNDXDD9D{DD**D%}DD'DgDhyDD dDfD]vD:(Db"DDzD+ZDɂDBD DFDDwD DDDD1D[DyDD}DtD1D D)D>D1DpDj DrVD[DIDڊD2DD_DDLD[Dw,DtPDDѥDzD`D4D+!D%D'_DZD*D'DD!DDy;DDpCDD,qDDD0D.DDR;DT+D9DID]D$DDqDZDDZD DtDCDDDՍD1DDeDDDDDDDsDHD<D&D<DxDDD(NDD{oD,DDDbQD˲DOD0DjDDYDDgDD)DDIdDD[DDd2DlBDDWgDDDD2DDDHDDzD/DfD DDDx DDD'D"<DD#kDöDp2D`D iD DADC$D,D D܅ Dz D Dv DDW D DיDftDCVDD@ D2 D_$Du DD Da{DUDDvD|D D(fDс DB D5hDbD0o DhD D DDID DDDRDgxDD D/ Da DK< DDD߅ D9 D D@DJD' DY D&DXDD DD>D#DD DDh Dv DCD< DuD|DADDD:DDd"DDD/:D$ DDΰDD=mDD!D+DDѕDDrDDD.1DwD( DIDD6SDpD DJ DvDDDDpDC?DӆD+DDJ*DWDDDڝDXD{DDZDdD =DTpD!DgDZ$DrnDrDDDrDD}DbD>oDu6D.DD D6D~DDThDEIDDD+DWDfVDuDgDrhDDvDZqD)+D@Dl=D5D DDD0DDDDN5D~DMDYDDD DLDrDDD_DD"^DDDDDl)D*D.DdDD D6AD!DTDDDLqDD7DD;DtDVD+DD D+DDpDyDDDDD(]DDJD%DD^D ,DKD8D8DD4DEDDDDD0_DDD.DlDvD-DD8DD@DjDDDpDD|DDDDL DBtD Dk D DMUD5DDDDjD[XDDOfDM\DDSDdD1DoDDDrDOD)D*D'D2?DD0DYDHDdDDDDQDDNDDDUDaDDWDDsDD-DdDjDD:DQDHD4D DYDQIDHnDDJDDDDhDFDyDFDfDDeYDDBa D " D] D]D+ D! D0D2 D2 DeH DRD D/DG D]v D?DLD7Dk D>_DDADBD D( DDVDDnD7CD_ D|DqDSD! DDHD+/ DDQ$D% DhlDvD(q D_ D DDT\DE DR D6 D Dji D9 D/DDDJ D DDcDHDHDq D DDDw@ D2D Dh D+ DM DDDvD^DnD7DpD DW DGGD DiK D DD( D_ DDSDDgD%DD@ DD6D D D DDx DD DЦD[DDtDg DÕDD> DSD  DDDh DD D' D DI Dm DD^NDڱDKDDt~D/n D0 DF DFD0D6Dw^DDDD4DD\"D_DDDSDDD[NDȨDD*]DDۼDDDuD@DD)D&DDDqDD!DD`DqD5DDtDDD>DdDAPDDDςDD[D/DD DD6DyD#D^SDD?~DDD-D0DDDCDnD:DtD!D4D%DʰDDHDMHD8DE"DT6D2JDD?DyDDDDJZD qD^aD}D/DD <DD DAD9DHoDDUDiDDD} DDVDUDDmDDD-DDaD֢DDEDBDs,D4nDDID4D|DDDdDsD*DqD0DmD%D&:DDSPDD #DDDD;D;nDDfDDD8DDDDӈD D?DDTiDDCDbD0yDYDzD)DDfDD 9D]ZDD/DDyDvD D2D}De+DDDD?DN{D^D,DWDD`DfD(DD3DwD DD;D1D>DDzD.DfMD,DPD{ZD>D}DNDtDDDcDDGDDDDDDZDLZD5DDKDD1DoD%*DDӵDDA_D<DwOD}DWD`D;D\D#DDpDD>DwD1Dj\ DD D8 D Dq Du#DL D D5DY Ds@ D? D̝ DrD DfD@ DG D8 DC D[D DC Dk DD D DS DDY* DkD- D D=" Dc D" D&~ Do Dj DQDDDD DD8fD Dt DDbDD D`D:: DD DDh D D DUDi D$i DBDDy D*@DD}DDn<DnDR]D_ DDDD[DD DUD D D Doi D`DM!DDF D:D D DqaDDD$D DD7D~3DD;E D D Db D 'D!F D{DDD D D D DD D® DnDjDP D4 Dv_DZDD"D0D9~ DMDp DT D8f DDU DDpDD DHD@Dw5D+ D D D; DIDM D D5vD,>DfH D17D\DPD_DADyD6zD8D*DDKDDcDDKDnQDDDDD]D׼D ;DD5DoD'D=D^DwD&DBDsDlDفDxDID5DMDD4DDjD$ DCUD uD pDD.DDdD xDv4DƲD,DΜDDDiD DDD)DnDiDDJDQD'DwDnD DXDD$DDDYDDDDDrD^D+DiDDEDԖDADDԶDFcD,D5DD\DDDyD/fDDD D`DD{DD DBZD6DD{DDDnD DD DaDY}DD8DDDD}DD$DjDeDDPsDGDշDD'<DzDDcDIDIGD$YD$D"DD-DUD7DDDD|DD|DD4DDcD&DBDYDsDjDDD kDDDDBD<6D.:DRDDDQDۏDOD*DDDDDnDܪD\jDDdD`D1D(DD%DbDDD&DDjD͂DD.DPDDtDDDADD:DD{DKDnDYDD;DlD DδDD.D}fD DDDDEDD}DdDƙDlDDD5fD֛DDDADDADD6DX|DDa{DiD~Do DDDLDojDDBD D D Dc8 DDD#D%D߆ DN D'Dt` DDp^DDDBD*Dr=D\ DQ D%DBDDٚD D^DǺDbD~ DrDp DND DN Di D D DDD)e DD~.D*!D5DDE DjDD9D`D DK DDSDq D3OD+tD]"DPDED}D ,Dw` D(DpDD Dz DOqD DD?DlDޘD~DD D! D D:DDvDDDYc DD D& DEDU DzDlRD D D DODD D,BDD%'DDD,Da DIh&D D1DsDUD D?DH DsD]D%iD2D%Dq DK Di D DZDDgDDWDD$D DWD,rD': DDl Dq D DBlDqDD]DhD}DqDDH DzDD-vD tDl DpD?D DDDD3D1%DDDDDDDDDDV4D3DlD]DDE6D%DDK^DmDDwD*DDkDPD$DDWD:RDDRDODD'1DNDDD_WDD/DC`DyDzDDD/DD DzDuDǔDHDDDXD?DD DDhqDYDDD7DMDNDjDDU-Db;D}D6DD6DD_[DDjfDDpDfDGDHD DD%DDDxDƉDSDD D4D3D8DDLDDDDǬDƁDD:HDDDƏD#D DSDDUDW6DFDpDD}DDe>DDdXD DMDCDDDDDDbDDyD DX{DD)DQ DDDDODrD+RDDuD)D>DtD^0DD DD D/DؤDDDGDWDDKhDdDDD"DxD9D]yD-DbDD&}DcDmDD2DiDDDu"DDDtDmDDGDw>DmIDyDD~DxDDƉDD4D D DlD2DH8DiD D,DDD DDRD(]DFcDuD#DDbDCDgDlD+D\DmDDD DDGD'D% DD2DD D D^ D D-Dn0D* DʝDp D Dӏ DD4 Dv.D7DJA D DDPDS D D¸ DDDDDD D\ D D( D3Dq DDeD=DDD DD4Z D/DDstDD2 D D. D^UD&Dg D~ DDu DZ DDYDkD}DDDdDTD) Dw DO D DC DDM D?DDDA+DDDD DDc<D D D DqD? DVD=nDs DMD D DlDl$D) DGqD DA D DX D DeD_vD/- D7 Dg| D DXDDS DjD D?D]DK Do DDJDR D DD>0D D) DwaD 5 DKDiD DDD^D4Du D;jD+D[D&D D;D۶DXDDVDD0DTDnDDRDD9,DD<DD-D]DOdDDDDļD'DFDDӳD3DD)gDDDD:D5EDDA.DDkDD DD8iD"D)DZDDJD&DTD@DVDDkDG8DDQD6D DDwDkD~DMDDD:*DuDNDIDvDؓDڦDYDiD_DoDIDVDlDçDDDRDDDҎD%D-(DDD#D|DʩDXDMD0Dz^D&DrDDADEDDDDbD0DDyD(D:xDDD6D@ DDxDDD%DPD}8D DDDwNDʓD'!DD*DzDDADjWD)DDDDtDcD(D'?DtDDiD`D>]DtDLD\D%D,DD~DDV"DD|D0DDDxDiD[DD~D/D6DȩDv#DuDD|DDD5DaD0DD(DDBDCxDDD4 D%D/DDMDɻDDDDDDHNDODcDD1D/DDRD~DƚDDwDDXDTD DD%D DU-D?DuDDdDD́D9DD$DD%DD,D@DM5D4DnDD-D DDJ Dn DBBD:DiDR D D DDN D- D3D"DDx D DD: D DDG D DDe D<D|Dbc D D Dl Dh DwTD4,D DM D=E DD>Q D| DDD*uDnD) D dDfD/SDuDD8 D DԃDr6DTD1DޢDKD7 DiD%D| Da$DecD? DDa DB DqrD>D`DӲ D; DҗDWDxrDbDDDDG DW DgPDF\D+z DD0 DI D DDDyD-Dz De(D D D@D DsM D[ D# DD|DD?8D/Du DuD`vDYDD} DHDDHu DWD3 DcKD/ DD8 D(Dz D D[D DBwDH< DP D D} DZHD D DqrDЏ#D D0 DjDq D:{DiD Dw DD D_ D^DDJ DMD DE| D DV;DD?DUDXD8?D`NDFDLDDDX'DfDXDR"DDcaDDDD4DDqD!D%D1D0DDsDSDDD&DD|DEDDDuDtD DDzhDD<DlD/DD7DD}D&D}D/D7DLDMD2KD9D\DNDDDwDfDD(DDDDDDAD\DD`DDTD@D0D7DxDDnDy4DYDXDՌDDtDkDD/DWDlD#DDODkDDDۋDsDMD1sDDvD"D&DWD DD>D\D?DUDDDfD[DPD DDr"Ds+DsDDXD+DS@D7mD\DFD`DDDFhDDD?DzDDlD?DbDadD!D1DjD;DD2pDQDDDDnDDO?D D?D(D]D/D)DDDDD7D6DD+D%D6D{DHD$DvKDHD4D:D&DáDmDDeD2'D=D' DDDrDDDkDDDáDD^DD^DDπDDFD1DdD3Dv:DqDiD)=DDDPDDD 5DujD=D!D DD|D`D5DiDDZ DdD”D-D2D2D'D9=DDD{D DLDD_DtD= DDBV D DI]D5 DaD DDD3D?D* D-DtDņD[DDM D= D1 DDGD"' D\uDw?DDD9>DD D D9Dw D%HD+DƌDD[DӦD DuD?KD DDhD:D%[DDDyDsD~qDD+ DDvD DD*> DAAD~ DDD}DKDfuDwDE~ DD_ D=DEDDu DlD7 DDD& DuDZD*DD DIBDAv DM DeDJK DD&~ DG-DDLDDDDDςDVb Da D DW DDlDylDDxD/N DUDFs DcDED*rD= D9 D DeDEDDDDDi D(D D D D D D D@ DҽD7~DDY D/D?k D{D DE DD:DD D D[Du D D+ Dg DpD]x D1 D<D D!DDcDDDAD DgDqDPDD JDhDDzoDXzDD~D+D.DLDK`DuDD97DDjDDD!dDzDſDDDD@NDdD2D$DQDgDDBDDNDDΊDDD7D'DD<D>DD@DDmDDOIDlDD BD-DtDxxDڛDD#1D@DDO4DDD+D+DoDDDqD8[DDkDDJDD0D?DQ DDyDԾDDDfDDDD"0D,D~6DADb:DYDD:RDqzDDDDDD?DD@DD6jDzBD$D)DDbDDBD@DDwDp DjDgD͚D(DSDDD:cD}D DKDD D-1DaDDڈDXrDc.D@DyDJ0DϥD8eD;D DKuDDiDDD|D],DF@DhDCDDrDoDD 1DDDfD5DBDoDDDDDD#DDD~tDD4D)DDADDDD'"D'DZD^D0DDD@D0DδDuDqDDoD(DݹDDD pDȜDRDXDDD DBDDqSD^D iDODDTD DuD:D 1DcPDfoD%DseDDD_LDDD4De+DD DVD DzVD DDWKDSo DD! DwDD DuD DqDD8 Dn DDh DD ~ DDo D DED DS DDGDrD;DD? D DD$ED/DDS D'DDfID Dh DD DfD D DDDD-DDHHDD DND3 DD%D<DjKDPD;DDYD>D^D2Dt1 DD97DzDZ DD5Dh DDtDDDD# Dc D DϝD= D DDDX D5DD_DDD nDbg D0D# DQ DokD Dck DADUxD.DDQDD?DD D DDآD DDD D| DDY DD Dx@ DL D D DDD?DR DD0 DHD DDwD DD Dd4D[DXDP DED- DDDD&D?DD. D] D Dzv D3 D D^ DDi.DH{DDVcDDUD_DDDtDDDDUlDIDhDDDDDnkDTDRDDDDDyD D%DDSDwDNDDzDDRDujDDmDoDS/DR5DDDDD&D D<D9}DgDsDEDwD[DpD!DDDIDHDD-D5;DD^DDqDDMDXD DT,D/>DDGDÄDrzDDDDaD`DoD^D݇DD=DeD!7DwSDD#DhDt1DQDnDDD[D MD% DrD@D ,DbfDjD<Dn DD/uDA9DaD%DxED3<DDzuD> DD DȔD DSD DwDd DDXD- DDp DGDWDvDKDZI D]DC DDcDDD8D DD D'DD D6tDQDƎ DwD[ DhD2uD w D DD7 DE]D" DmDDe{ D D$D>DD7D DDxDQ D DD DD] D D5DD D DoDDx DW1DUq D DPDDD DD D1DD/7 DDrDTD D D9 DD@RDD De D5ADtD D4 D-D{DUDڅ DW DD0 D D DSDc DsDyDC Dޜ D@ D D\ Dɢ D!DwDF D[DmDDVD D D|UD*iDD~fDM Dݍ DDNDe D DDDj{Dr DDu DDuDw D D5DD1 D} DID{ DpD, DD D) DD+DXDD; DDqDRDPDDDD0%DD$DCD4D|DDDITD.DD)DDDDD]D^rDXDDdDnDkD1D&D2<DبD DDDD8DoeDDDD%DSDEDqDZDD=DD*DDDe%D(DZDDTD'DDD@DWD DDDhDaDUDڍDKDDDkDDɨDJiDZcD&DeD-DDDnDCDuD+dD? DXDADD'D9jDl D7D-sD~DDDH5DDD DDD4yDx)D@DD,DBDgDªDXDDLDHDk-D0DD8mD }D[DDD!D0DxD?DD[DpDVDٛDZ<D1D_D.2D!DCDȉDJ4D}DD=DD#DDwDD(DDDzD.ED7uD$DDD;DDxD*DoDMD=DGDED`DD0DYDDDDD'DdDiDD|DGDXlD"DDDD_DDDH.DDMDDDxDD.DrnD:DKDXDDVDuD1DFD{Dy~DPDLD(DDDaDٶDlDd^D\D֖D D3DBD~D^&DWDDzD$DnDDDDDDDRD2)DJCDDc D DMDD 2 D. DkD. D*CDND D D(DD D] DX_DED7D`VD D DD(D D>DT D7#DV#D D] D Dih DMDA D D D DDsDDn D3DDDD8\DD D DDrDDQD&DlDlD *DϒDdDXD D#f DED~ DCDDfDD DO DYDD-D6D D&DZDDHD D/D{"D{ D% D: D( D D D D]DceDgDV DD DuDio D, D1c D9D D DygDDD7 D5D D~lD1S Db"DV DD* D-Df D5 D DDDDRnDDyDސDKD^DǍ DnD D_ Du DDmJDD/D :D,D DtDDѷD̢DDz D D9IDD D#n DoD DQ[DC D D`Dl& DDDFD DD DyDD>kDM D,D+DqDyD(DD SDvD=DSDDD!&DD]DDDDLDD,DDMD(nDbD=DD(D4]DDA1DDJDDDyXDwD.DD/yDDזDD62DDDD DADD6D@D1D+DDDϔDׂDPD;9D DDDID D4ED!D=DXDD5DuD%DD D5yDD DPDDťDrDqDmODwcD>DlDOD=DuDD}D$RDCD"DDDDنD[Dy6DDDDPD`D!D:DrDtbDnBDD|DODcDnDD(DDDlTDD!D+DODDDVD-DDeDDn D])DDDuDD D;D,DLD#DDvDQDxDD@fDDrDrDDv Dq!DDaDEVDD4ZD'DQD!DbD2DƌDwDD}DDXDxDD~Dc DZDD D5D'DoD8D DDND=DfDD{DD D)gDRmDCDyD`D@DեDADSDPDwDDD6gDDDD2DODDǹDDD)DDDSDPRDlDKDDD{DDYD];D?DHDrD5DUDDNDD DRV D2Df D9 DD%D D& DvD~DBD DXD!4 Dx D;h D#DD D DRD D DDv D D)D Dd3 D DAt D DIDl5 D?DD$mD9"DoDe DkDDY DeDա D;DzCD4` D.DtUD DgdDDjdDD* DmD D/D?pD D D DD|DƐ D$ D#DD DDDkDpD/{ DDڹD D D DDYD%W D D$/ D{ D D D D| DADDtDvH DDDG D~1&DD~|D D&D| DDL'D#D| DhD?DDD Ds D?[D DD D* DDAD DsDm DyHD D1D$DD( D7X DD rD@D DD_5D`DrDDvD D^ D) D= D Dtm D(.D D[D- D? D D DwJ DoDlD DmD DD:Y DDDDD|D DD;DBDD-DD^DBDD47DƢDPD)D@DDD\wD D^DDKDDDBD 1D|vD{D#DDDDaD9DDDo%DoDD{DSDDRDnDXDjDnDS3DfDDND{nDCDmvD-DbD~?DHD.)DDSDD;DZDDDlDD D<D:DJDDP1D$DDFD>SDuDDf)DVDjD|D DdDDeDDDDDDDD<DDc6DDD-D}RDDM-D DDDWDBDZDn/DcD3DDD<DDKbD1DDgDhDDFwDNDaDDƭDwDDLDDDuND|D$DvDzFDEDDVDCLDDDwD`D} DD6DDSDgDaD0DpDDD5D{D DwDD1DDDDXDdD^DRD DړDpOD?DD6D_|D@DUQDDԄD}DDD{DrDiDvDDMDɜDUD"D(DD DDLpDDDrDMD%D!DD DD&)DuD[DuDDDiDDDDDmDg>DqDqOD~DD0DDdDDMgDDjDXNDM DDDjD~IDDW6 DD8R D Dw D DJDx D D DMD{DD@* DD0DHgDH D<8D! DD DEDL D-D"@Dp DWDqDDDh_ D DpD DWDSFD DD:D=DWDtDIDZ D~DTD DDDDD~Da DC DD DD1G DY,DDDnD D Dܛ DzDՙ D DD\ D8 DXD1D DQDDDۯD Dx D0DuD DJdDw DF D%D'e DDD>D,_DDCDsRD D&JDCD DDΎD D[D]D D DODD7Dɮ DZDGDD>DX DDDZD DDDzDKDDDCDDqcD DV DC D?D5Dv DD/DQD7UD\` D DD D3 DBDD/ DD" DL D DH@ DO[Dx DK DDDz9DAs DJDbDǨD1D7}D4DDDuDDtDPSDgvDCD7wDADvDD|D=D#DhDdDLPDaDfDDDuDD-DfD|D2DhDbD}PDmDW DD/DbDDrIDID_Dd7DDDD DDkRD&6D D#D{lD2D3qD.DD8DDFDD'DaD D}D2D=2DDODH-D;0DѡDLDxDDsDODDDD DDBDyD~DDxD<D:D<DEDDlDDdDXDSDD#DzD>FD D;D˷D2DDUDUDDvGDhDsD1=D#DDD TDD!DD0DDDD+DTDDJD DfDͿD$dD D^DODLDDY6D8DDDD%DyD8D}DDDFDuDbDDdD_DDDWD}6DCDDJDDxDdDDDDDD0DDDpDtD_DDDbDDNDDrDODD*DDZDnDDDOSDDH_DDDjDD\D:DDkDpDbDD#DW_DDWDg$DYDBxDDDɻDSDD9DD۬D2D%DD{DD,DD}D;DDzDmYDjeDD DS_D1Du D DOD7DDo DcDx(D{DN| D/D D+D~ DDDDD! DG| DVWDD΂D;5D DD DT0 D%b D DbDwD=DD DDQD`rDD DDD D9SDmXDf DwDEsD D;E DhDDQ D2 DDD+D D%D{ DQ DY DA DD8D3DD9TDDoDD D,DDDD DDɞ Dup DDH DxDDRDDh_DD73DDڨ DPD, DDD DhD D~D)D DD9D) Dj D;V DDDD3 De DK DDDsD:TD D+ DZ D D7 Db DDD{ DSDx DKv D΍ DG!D DmDd& DMYDWD| D^%Dl D DtD\cD D ^ DY DpD;DDD- DD$DĽD Dy D D11 DD DfDDGDDv D4D6 D DՀDķDDDd:DGDDxDlDӻD~DDDq DkVDDD7D*DDDID)D~\DBDDg=DDOmDD4D6DTDDD+DDDoDDDD^DDDOZDDDDtDkDDDS D۵DxD#D D\D`DeDfSDODIDS!DDDLDMDD~D#uDDD7<DDBD1D)Df(DD=DSDDD-XDDpD DADˏD^DZDWDޙDGDD2D8DMDiDUoDDD1D;DJDDPDqD`DDDvTDD5D%D6D0D+DlDD D5DDD#D[DD)DͅD DDGD9DtD,(DS>DDD MDDXDDPDD3DDaDMD/DD=lD9DuD.DϼD1D4DCDِD9D2DmDD-DADCDjDDJDD5DD'D8KD?DDD~DDQD D5DEDD1DkD }D#D# D]:D_lDD+D,DID*DD(DĎDGDFD&DDD=D1D6D}DD DpDDDGDxD$D<DQzDDSD'RD%DDD3DDSD7D[DDaD DDwAD D-xD DDth DDDQ D~Du_D DD D DF DS D" DDD D14D DT Dj}D D?5D»D D D DDD DtDD D=0DM- D D<D DDBD DH D$RDD=DDDD*; DJ DD8D4o Dq{ DD'vDyD6DTD [DVDYD2DyD^PDmDDDDDeD/DD,D׫DdXD'DVD DI=DDkDDDD;D˸DODDrDDDGDvD-DDD>D| DMDJD+D1DxD!DqDHDoHDDiGD]DDDD DDج D DDFDD D3D3 DD) D- DEU DqD DDwDfDrq D DLD& DLD{ DqD}DDIC DFDDI DeID DQD3D<D/ DhD DD' DD x D D9/DwDU DoDD%D%D8DFAD1v DDD1 DD@D<DԘ DDDDS D D6D D DqDDD,D D)l D: D,D DDz D7 D2 DD D/Dv D^ DA+DUA Ds DD> DZ D_DgDxD DDNDD8DdDD)ODDODBD!:DZDDtfD%DD<DD@DD`DDD`D|DrD|HD:DD DDDDp"DmD4D6DD`DnD'D6DDUD)Df!DWDFDI^D\[D=DDDplDq4DVD:D0<DF D$DaDzD67D2DD+DNXDD DP]D<DpDqDDcDDvD:D_DD DDWDDD@DDD\D1D#DD%DkDFD+DDED4DDA*D5|DjpDD!DgDuDsaDwDDK?D>D?DDDXDآDSDFcDdDfDD4DD3DDF Ds5DqD DDPWDDo<DDIDbD.D=DيD+D̪D/D6DRD DuD<DD;D%DۇDDwDDIDlrD=DD\DDYDqDND+DdDDDDDDD)D D=D./DyD*DRDDD#6D,DbDDvDDyDGDDD#D>D="D D:zDDDDDD<DwD-EDDdHD~D)5DDdDLDDD+DDDmDGDdDuDTD{DjD8DD#DYD['Di}DiDxDpDDbND˓DHUDDvDDEkDiDD$D͆DDF D" D D DhD)DVDDD DiD4 DDV Dp D%d DT D-$D DRD D%D. DD!D/ Dp D Db DHD D]U D DMD] DDGDDDuD D DD D DD3 D DjD+g!D54DZ@ DADj~ D Dm D>D D$ D7DDD D` DDl D D D DR}D<DDADb DNDD DDLDuDZ DDA DD,DD̫ DDe DuDDKD DCqDD% DW D7 D D7DD DrJDUDD D9 DDDE DX D8DiD< DZLDDD DJDY! Dr DVDND-DI D^QDc=D DLDD"DQxDDID1kD7D D XD\o Do D D De DfD D< D DD+ DM DjD1 D[DDD'* Ds D DODb DD?, D[ D~e D DDBDo#DSD>D%D9gDťD5D*DDDȋDhAD*DH"DaHDCDRDDIDUD]kDDD=DADDDDڞDDDWDKDYD$DDiDnDDoDBD&DDy/DD^D+DDD>D\DԴD&DD9lDeDDQDD=DMD DlDDeD~D>VDDD/D܎DDjD5-DsDDD]DDQD~jDDDDDDDDïDDDD2DDDxDZDD,DnD—DUDc&DzDDuTDcDD MDDRVDcDpDD*DgD?D%CDD@D*DD UDDD7DSDD^DxDDDD=>D=DDDDaDDEDWD6DD?TDDDDDD[DJDDDDD`/DADDzDD3DDDDADDD|D6DJDY@DDZD!D|DSDDD.DYDd8D/DgDDDDDD4DDmD0DMDMDCeDDxDeDDDDD-DhD$WD<DDDDvADܒD8JD>EDVDDDWD+CDD:DDlrD0DD}D8D6DsDDDxDDQDpDn D%DDDn' D DDDҋD DhDNDO D&D D8 DO DD%9DUD9 D X D DDDDID DmDgfD:DDi D D] D ~D DOLDDY DE D Dm DbDDZD D D('D+ D[D'v Dm-DCDtD'Dld DڰD DK D DUkD D &DqsDO DDkDfN DDs D*D:DDDӆ D'DF\D7D\ DhD=D Dk&DDD?Dq D$9DDD^DDi D-D*DAy D*D{D D6 DD+ZDDD2 DDD@ DiD<DPDvy D DpDD 5D DjRD{D DD߫D8DdD%D> Dk DDbD D4DV6D DDjDfDD6.DPD%D1DD]DfcDnKDrD0DD:^DDjDXDDDD+D!>Df&DV&DuD=D&DHDQDADDDh0D2DDѿDD DFDD/DDDnoD(DDDO\DCDxDnyDDCDFD"D DD<DND!D%DDD DEDDsDRFDKDDUD@lDQD&D>D%zDDDID7DDWiD,D;D D9BD DRDw DܚD=D D"eD\D?D}DJDxODDDO:DkDDODmDWDD6DDUD'6DQDADHDD wD1D]uDDaDaDGD*DM~D$DxDqD DDDnDYDDDDDnDDD]DDbuDѸDD D DPDDD9;D'DDqDYDDDD>D#DyDDDDD DXYDpDD`DFJD9DDcDD(DD2DDGD"DfDrDzfDJDDDDD%DDKD DqDpD"!DB9DDD{D)D>D?DYDD%%DDfDb\DDDqDTDFD5GDD$ D2g DDg D DDTDoDߙD D3DADD.D5D.!D} DtDnD!R DuDR DwDZDD D DD D'D^ D:H D=DDD]D DODDE D=D?DL Dw9D DDi"D0qDD DxDƣDy D0D,P DՃD!D>DgDDnDD D(D+ D~$Ds DtDrD}!DwoDDDD D~Z DDED D DHDW D DXDP Dq DD$d D%7D^2D D D D&<D D DiDDD D SD# DD8 D DD{ DD5 DDDD͇DD DgD2# DDD D.D D DFDD D. D D:D D[D Dz0 D D D: D] DL D8 D'{D Dڄ DTDDll De DxDW DDRgD D DDDe Da:DhD( DS D% DDE DV D D=D_DLD D+DkD66DqDñDDDD>tDLDD*DDhDDDDDDwND&DIDDg(D RDD+,DķD,DDADD-DDDgD|DpDCDdDnDD׵DD-8DK*DQUDD>zDBDDRDD\2DBDDDqD7DD< DyDDDDYD]DCDDDY^D+DDgDDfD]DODD+DDDDD-eD'DTD: DXDDDGDzDvDmDCDDvPD9DODsD DCDGDDdDD(DDfDDADD%DDDzDDu$DQqD4~DD*Do{DDD!DrDGTDzD DD2D8D DD\DDtD<DzD$DDnDD[DHDgDҏD2D:DDfDD D DDD=DyD*DɓDnDKDTD&DkoDDD+D?DXcD-D,QD.DEDhD[DDDV`DXDFDIDDDDDsDxDDDDRkD_BDDSD@mDDSDsDdDD~DRPD` D,DDMD(DGDoDDvDDDbDID=DD;DTDD@DD 7DDDwD#DD#D DD$rDk DkD5 D\DD5D> D2' DsDHL DLD D_0 DƏDw?D&D D* D*DD; D^D DDD DVD 2DUD0 D21DPD<D DٔD֠ D Dd DflDDD DP D_ DDDQ D DD?DT DhD% Dݾ DhDDDhHD. DvDxD$DDD.`DlDDD\ DDmDSGDNDղDf8D DfDRD[DDD, D'DD D_ D D DVD> DWD DjD@D*IDIpD DŇD/ D֜DW D D DD#D)DitD D D D@ DmDSDDXD,DeDDD i DJ6 D CD{DDDO DJD4DJD:D DDD$W DO D DDND9 DfDD!DDlDD3DDL Dc DacDZ Dp D D D8DD* D DD.G DP DDY Dq D7XDDu DSD99D)DDDJD ]DDCD'DD3D3DED.DmnD-D{DNDD{Da/D6DD)rDJDDڿDl,DuVDAiD$ D*D.D|DMaD|cDFD2bDD.ID+D2ZDD^D:DsDj<DD DDnDVD:D"DHDlDmDʓD`D DD DDDT8DvDID D3D*DDȽD{D0DDvDZDcDV,Dk(DrD 0DDDDsoDD%D4D%DiDDDIDD_VDL-DQDiD_DD,D(DDD<DXD%DVD(DDʝD)DEDDeD2DrDZ4D)DKD?DDDDDsDDlDWDDAmDtPDr"DDDDDr&D DD$DfDDDMDD DkDMDљDDxD۞DDU*DDDبD.4DބDDJD!DmuDYDNiDxD+DDaDpDD/hDDٕD3D3DqDDyFDCDrJD5D>VDDD-NDsDḒDrD;FD0EDE!DDDDGD-?D_D_D-DDNDhD{D~D]DDYDJDpDZcDDnD9DDDDmD=DHDpDD-D\DӎD"D}[DDD DBD7 DjDk D D D1l D DD7 D DD6D DW D D D Dy8D0/DD$ D D DDL D Dw*D_? DcwD DDED>DvD^D D9 D Dw DTD, D= D0 DDD D$ DF5DD D7 DDHIDS] DN/DR. DD Dw DDwDD D7xD!D# DYADD̘DdDh D,Dud DD 7D D D DM#DfAD DR] DG DPD D5D`2D(D DD DDD/!DjFDhD%D6DDfD D D DD D DD DDDjSD4D#DD D]: DiDmD8D D,DaDD_ D! D x DyD7D< D4DUd D[CD{;D D( D΅ DDЎ DG\ DDY>D DK D D DGw Dl DqDDm D DǕ D2 D9 D. DjlD4 D0D| DD' DtDD. Du. D\D D D*DUDDeDIDzDDXGD:DD` DOeDXaDDhDDD!DRDDDiDWDID7DD DSCDDnjDD6nD-Dy`D<DB}D'DIDcD)DD8DoD*DD$DCDSD%[D]KDDZDDD8D_DPDDDVDڏDRD pDWDenDHD^nD:D4$DD.DD_DLDvD1DD D"DDKDD,DpDD&DD{eDyDDDkD%vDDDDD0DDDݔDk DDVDuDD{D DTD%DwDvDDD-D~D rDDƊDiDDjoDD)D.D1D%DlDXDPDR?D8D1DD5^D$DqSDPDKDT/D D{DDDB&D@DoD D D DvdD-LDD^DsD}D9DD'DEDDD}AD$>DHDDPDDDDDND~DҐDADnDIDQD$DD]DDDD&D7D4D{DfDDDD DD5DJD#D[DDdDDLFDDDD(DrDD<DADD>/D?D)DbDDDD6SDDmD)Db$DAD^DDDbDCDD|DVDwDHD DD-7DD<DkD DMDDDrD<D9DgDDoDDD^]D=D.D#DwDDDND`DDՏD D6DpD?DD@D('DD2 DD( DDD0DD2D6DED)D pD^D DDD@D5D|]D.VD6DDD\DDDDD DBKDDYzDDD=D,DSD}DPDMD$DDMD DD|DkYDD~D,vDhDDa D.DrD~DMD3Q D.D D DZ DtDN DDzD0DG+'DFe DD D/ DF DD( D$D>DDDn D:b DWDԓ DDD1_D2W DuUD D?DDl D4D[XD h DHD+ DVtDaD#&Dlt D, D DXDDמ DDDs DR D DODD D¹D DˬDߵ DD3I DtD D/DEpDwD Dw D#+DDDgNDD DODpD6D%D0!DD1 DDaDXD(DDDfD DD1D DODD(7DgDD"DE DD]D~ D DϐDD(D?D DxDܹDD D$S D3 DID( D,QDrD DsD6U DDDcD[DD D}Dk D3ZDD D DKD) Dϟ D?D÷ DDȥ D' D#DD DDG D# DDDl DDDD4D%DDDDD;uDDbDB D D' D D DADlD~D%DxDFD7DGXD2DUDpDatDcDfDD3DBDDuPDDD DRDlDOD ,DD%D8DDNDD D8DIDD%DPDDD~5D`DhD 5DHD9|DDDmLDDIDTDlDDD/DD D&D|DDeADM?DD[DޱDXD?DDMDDDo/DDDDbD3DD9DިDDy DDgDqDD:jD=DD@D\D}DK'DFDߛDDHDbDDD2DDD4DbDmDfD{DeDmDDDQDDZDKKD{-DD2DDy5DDD\EDMDDBD\MDJD DcDdzDDVD5D7DDI8DD5DaD`DEDDTDDIDWD.D3 DRD7D>DDDD8DD<Dc`DD9DͬDtDZDBDGAD&DVDDKDDzDFSD6DMDDD;D.DWD*fDDDoDiDD<D5DKD[DRDƩD DDD 3DlDD:DTDQDDDcDDDDD D uD'DDDDb{DKyDDDD/DBDD+DDLD DDD9mD-oDHD\DD DaD5D$DD:DD{KDD> DUDDD( DGDy$DD DsW Df.D+ D#%DӄDQDCD`D,CD DDDc^DjD33DDo D-DQDc DiD+ODM DpDR D D[H D- D?D DDEV D@ D DD= DD-DIU D D[ DXDX DPDHDY.DDD2DDDlD$D<D>DMDDDDWDtDSDEDrD,DҮDDD)EDqdDDrDND"D@D%D^DkD"D|DlDZD:>D|DGD6KDBDD>DiDHSDшDf/D6DDDD4D@Ds4D9Do+D{DDBDD:DPD hD}fDDyDBDdDD D DLDZD9DlDDDDDQDuDD DGDD*D+D;DD|DDzyD=DkDD,DDnDDD(DDBDDD$DDQDDwD5DDcZD9DDyDDDq_DzDƅDDWDL7DD|D\DnD7OD6ED DmDD.BD#DDDeD>DÚDhDD3DLLD5#D/~DmDyDID?DʨD.}D"DDdDDDDD'DwDfLD D DGDD*D~DD~DD]D̽DDDMXD DSDDDDD DlDDDDnDD#cDDD,DXCD05DDDDDSDDLDD3D>DCDauD~D}DD@DEDΛD-DSDDSDfDRDq(Da DƧDDD\DDDpDfhD DD D>, D64D,Dk D12D D$ D D2Z D- DDD D DDETD DDDȝDDD DхDDDD)D]DK Dy.D{ D DDe DY D[D\Do D.D DЗD D Dy DDDDDDxDIoDDDD:D6Dj3 D DY D8D D DvD DD+D^DDk DhDqDDDu@ D/DI' DDTDB DP DYZD_ DY D8Dm8 DDDD}DD'D D0D6(D-D | De D DD D DmDSZ D*DfO D'D*DP DD D.DD D}D D DeD| DaDWDDVD DS D DDD'D-Dc D@s Dr D(D{ DDDQ?Dm]D@ DM D D"DDuDDbDDUDrD)DDgD:D<D.DDpDD2DsD3DD"Dc\DzD~MDDDjDDD DܚD?wDlD/D:CDDLDDDD)rDUD*D]DDiD-DfDWDDfDD}1DQD*hDD{DKDUDDQD;~DLDED"DDȑDƈD!DGD*DDD !DD*DDD;D/DUDEDtD"8DKD/D]DD_DDED}DO9DlDD[D3JDG'DޓDDD^RDKDDscD9DD]DDY*DD DͫD,DotDQDdhDDDsD_DGD 3DDHDnDuDDBDHDxDDDDDDLDQrDDmDʭDD1DDD%DD.D!D8?DtDDq;D=UD0D2jDD=DDaD6MDs DDDD5DD?DDYDɅDbDDi DcDvD>DlDDmfD0DDD~DKD!DD5DԡD6*DCPDUDTDDZDDc=DDnFD(DDWDQDrD7DB D Dd%DA DDSAD D DH; DE DBDw DD"rD; DSDjs DQvDIDF Dr DODD# DsD^D D<Do D Do$ DDH, DIDID|D DD_ D;_DoD0 DDEW DCDD@DDTSDm DDjDDaDD~ D2D;D֘D*Dg DlD% DgDDDcK DUDę D DyDDf D"@DdDm DDD{DۥDEDnB D{DDDDpD Dv$D DE1D4 D 5 Dv D|DDT-D4VD1DDw DDD D:D[R D  DDj D<DDD-DgD` D^D D D DJD D DDDDM DDxDQDQ* DDGD Do D Dŝ DDwDDDcDD D>DeD D Dl D~DDK D D$D%Di DDcDf DDvDq DDs DI~ DMD D@Dx)DDrD DDiDDDD|DDeDD0D5XDّDY9DNDaDUDfDDD.MDDWD^DV^DDזDD|DDgID)D$DDaDޚDDDvZD#DD͈DgtD;DY-DID/DuD[D\DDuDYD DnDPDuDoD4D*xDD-DD{cDDDhD D80D%'DDDѨDD D:DoDCDDDD5DDo3DDLD,D DRDDD D~DUDeD,DeDQD\D/DDDD DcDD%D5DDbDDXDcD"DDh"DD!DD#DBDdD?DD:DhDIDDjDDMDDDD7D9DD%D%DTDDrDyDO,DD%DDDODԇD.)DDmZDDtDxDҐDD1DDD3DeWDYDDD DD9DdD1cDD D'D#AD9DD-DJD^D^D0CDDJpDuDgDDZDDJDEDDCXDDʟD8aDDyDDXD\D$DNDD݃DdpDǣDD1DNDNDDID 0DdDƅD'Dm9D,DzDQDFDD Do/DYD'DDODADD D+4D D{DH D]i D2D"" D D, DDpD4 Dc D r D] D? D*DD+DD D" Dv D= D> DyDZMD/!D Ds DD2D-D{ZDx DDڨD DD=D/ D)Q DD2 Db D DRDD D Dj]D9D(D DD D D>DD DKHDD1 DD!Do|DRDDD}D} DD_ DQDDL4DDO DDF D DղD;D NDDr D7DO D& D&Dِ DD Dg'D+'D` DD D D D6DKqDӨDDwD D(DD]DU D D DQD D D5 Db DDD D͇Dԍ D2F DDxDAyD D DD D+D{D DË D|DbD.DDF DDDׁ DYDDL D DrD D E DDڻD( D1T Dt DmDRDDD92DUDBDY D5DeDS Dd D\jDPD*DB DUDDEDD4D4DYD_DDdD2DDpDWDmD4D.D!DDDv*DTD,DPD{DoDDXDfDD\ D/DD DD=DQDD!DmD;DDmD[D+>DDUDDW Dv\DDD &DMD)DcDD=D:DjlDXDPDDUDDfDXDD/DHDD/DtDD"DD4!DD*D_D}DD,DD*<DDrDED]D D-DD7kDHvDDMDNDDZ DDDDo#D>DlDDpFDDDADǂD2DeDnD7{DD*9D D@DMDDxDXBDfDzDDwKDDDBD|ADˣDlDDDD D^DDD!DDޒD+rDDn*DDDD'TD2DDvDgDDDpoDuDFDnD_D#|DD>DDzDDD \DDEDMfDQDD\DqDDDͤDDDDDxDtDeD~D5HDDDfD\DwDGDc D2D(D4sDD"DeDiDzDgD$DD4DPzDJ0D4JDz}DDւDZoD9kDx?D4D^DsD>D/DDDTIDxDDkaDz)DLDHDiDDwDAD D?D D_/DXDaJDD[sDҞ D< D*D7CDn DT D DD` DJ DEDDDp2D DDJDo D)D D0DJ DocDz DV] D DzpD^: DDBC D4DM DJ D D, Df+DFDD~ D/D! D D Du%DD D|DDoD1 D( DD D_D DRD< DDqRD# DDD#Y DDD DǃD DDDLD, DDknDW D D5D Dg D D^BDxD^ DD DD/D D]DD0D DDa D DPD!D[D4D D0D3 D9DDHFDD~D}DD[D9DD4DD Dz DQ D@t DD\DD#@DD/D]DjDoOD DDvzDA D@t DPDr D4D*DO DhXDuD?D DDJ1 D1f Dԉ DDY DPDD D,wD_+DdD DDDY D^DM DEDDػD!DjDDDDyD+D4D"DD&D+DND`UDCD8DsD(D}DkDsDSDDD #D-D DD"DDDޫD[DDz>DlD>DDDDDaDDtDD'DZDD8DŒDDDDD0D$GDJ~D6Dq+DqD,D}DcXDUDNjDFDDND D DDJDD1DCD9DLXDDlDD[DDD>DDէDDEDTD1oD&DJD!DD DۿDKDtDDUDDiDD%D%Dy|D DDD DjDDSDfDDD.DDAD}DADRODD$D5dDD"DDxDDD8D/DODDxADqDND2D4DDYDDLODnD<)D%D>D$\DPD9DD^-DaDDyDDh~DTDBxDyDDDϑDrDVD՗DpDvDD]fDD9DkDNDhDDbDA]DmDtD##DqD?DDDDCDDćD]D_DDDEDDԗD5mDDDDDIDQmDD:sD-mDSDDBDƅ Dw D D DD5DӎD[O Db D D DBDDV D DD7|D D6`D4 D DODDN DDD D8D:D}q DOC DE D6~D4D| D 3DD%D D Du D D{Dd DH8D DDDXDr D<DUDJ~ D DQ+D.D'DY D DP D D\ Da D#D^DD2oDpDT D D^D1 D D8Dc DDzDzDj D>DODڕDD D} DD Doz D4 DI DDlDybDDDqDޫDDLDU DCD) DF9D3) DDz)DDTD` D%DyDf DJl D D$ D@D^q D D DYo DxsDDqaD,DR DUDD{ DD#j DF D D)DiQ D D6DDD+ D Dt D8{ D]DMDpDz<D nD D D" D DuEDDADDGDDDD<DDU(DDevDADoDrDqDs]DQDDiDJDDXDDND D D@DD-DDDDmDUD8DNDD'DSD-DaD/DDDDcDDΖDDtDD)`DD DD{D~ĎDDDDDDDDDCDDD޺DъDyD֩Db>DDJDiDADD,Do%DEXDDDD3ADDgDR4D)DDoDٵDDD+DDX>DpDz?DD0DDDZDD DfDD'DDDDDpDE_D3DD7D:DDDHrD{D[DxDDQD6DDDCDDDDD#DDeDoDDD\DSDDwDeDX-DDDDD~DeDxDƤDDdD;DEDuDDDD;DDDDADD~DGDmpDD>DD^D rDD] DHDkvD^D D+Di`D$D;uDMD@RD$@D"DD<4DDQ=DD@DDtDmD4DdMDDGmDD*]DoDDMDqHDUDuGDD&DXDD<DDpDoDtxDxDD6DDDDƐDDjDӖD-LDYD0D DkDDߏDu D Dyo D DDxD(DDD<D0 DۈD} DDDD D& DD D@eD DHyD#2 D+ DD D8}DD Ds Dc&D, Dm Dd.D D!D9 DADD DstDQD Dq D DHMDQD.3 DD(DD6sD6DsDPD#D` DD} D- DSDDROD|D eDњ DDND-Dg Du DUDDDU Dp D D.^ D? DmD7 D DB` DT DGD}Z D.JD& D7|DuDD DD ( D D4D%DdDD3DSD D D= DDM D[Dr% DDDR DbD1DfD D~DDǒ D' DAD9D DD3D^DSDyc D DD DqDDD D D\ DD+DXD'D Dl DtD DĬDD DJD<DJ DD] DDDeDX Dk DA DSD DYDUDϜD< DÚ D8HD`DD<DDDeD"DUDkDD,DDOD8D,SDfDBD2DDDDeDD+DDYoDID[;DD7DDҠDWDDDD;D$DDMJDFDDqGDuDADDDzDqDD\DDD`DMDi-DD DDDtDsDD D8rD^D$DaDZD<DaDD/DD{ND,DPDiCD0QD~DUDDD;DDDiDSD wDLDfDgD HD'DDPD3D6JDsDD~D!=DDSDDDlDHD>D8 DLcDiDhDeDȐDXDADzDD:DDD DDD5UD?*DcDDD&DrD۬D8DDcD DDD9&DXDvDDwDODgZDDDylDDDDDQDDeDgDl"DD0DDxDDDD@oD|DBD4DyDiDDDzDDiD$:DD9Df D(D¦DEVDtmD DDDrDD~DNsDo*DiD'D[DDDDSDDD6DxWDcD>0D|DD=DWDDDuDDgD.D_DtDDV|D'D_[DDWDEDD /D}DDrD{DYDD=4DzDxD=wD^D|D  DPD Dq DDvo D Dϙ D DDD5 D DD&@ D'ID/DD[DYnDDԯDD ,D5 D: D D[Dc D{LD2DuDj D6 D_ D Dn DeD$DD #Dw DDDDR; DD DD3D1DDfDD DyD D / D D Dt D`D0DC,Dx D'D, DĐDUD˳D$eDg{DD8DU DDm DD ] DDqV D4 D D0B D D)i DDDtDD: DDDD DړDe DDFDy@D2 DG/D,Dj#D2,D6D~DUDlD YDUD DDD DR DkDL D DzzD> D( DDD D+DDQ D` D-DaD&DV #D) D D3D D{Dn D| DDDD΢DoDD^DDWDInDmDvD͒DWDDDkDLD"D0DDDDD`DDVDD\D`D DD>D|DD(DDK(DD9DDzD[DʭD^(DaDDQD DDGDdD^DM%D1D<6DD9DhDDeDDD D DD4DaDrD D\DDJ DD1 DpDy DVD UDDVD D$DDqDpH D; D|DusD nDyDmDDDhDDD DSfDmDۅ DGDNDA D\DTDKDUDDH DD D'DV DDOD{D D( DS D>D DUD DDfFDD=rDi DT D D1D DJD- DDi D! DDjsDUDD}DVDT?DSDE?DD'DD>D*[DNDFD[D {DNDDdD/ D{5DOD)DDDDDD2D7fDDDEDyADXDDaDDF"DDDCDNDWD=D?WDs$DDDgDDCcD`RDDMD+DDlDA_DD4D ]D;DDDD,ODDdDDDgJDD;DD/DD{2D5D2DDDDD1D#DDD3D#DaDD3DD!DgDODgCD/DG*DT*DDuDTDD>D DDjDTDDDeDDDDD +DԂDoDyD=D-DjDPDD7DoxD>DoDv DDDDDDD6%DjgDD'8DxD;DjDȮDDmDѮDiDBRDDD!nDDyDDDHDuDD-DDD!D;DKDxDLwDzD`DDMD'D‚DxDoDDDMD D/0D _D\DDDPDoDD?D?D$DSXD DW<DLDb D}DD.NDXvDDDDWDDHDD?DsDDDID~_DDBDODGD 7DyD DVDDDCDD JDCD D= D D D D DEDDDj DWD١ Dh+ D$4 D DL DRK DfDDWD!HDN. D DӽDRDeDIf D<DD- DDlDODDD5zDfDl DD' D0DD D?/ D&DDDDwDӎDD Dg DD Dc DDDDDJDDD'=D,P DG DAi DD'DDM!DD# D!\ DC DUD2lDeD#DSDH DcD2 DDDͬ D Dm DLDD DhDj D_DI D!D8 DDzD9DgDDJ DDF: D D_ D2Dۃ DDc D DDĠ DDND D=BD!D&D8 Dׂ DU D3DF*D D D}DzD$}D D? D1 D DkD DD@sD6DV9DFDP DD- D^ D҆D D DY$D D,` DD D DDDo D DD D DDPDp DDmD;D^ DnDGC D D<DpP D^-D<DDDD DCD D_DD/DJDDًDDwDD.EDDfD7D DϫDDDD}DDTD(DhD{HDDADxYD`DDpD fDV=DDDZDD/D<DDVDD-D`DDBDD=DDD^D+DJDmDDD0DDrDDDD>D7D/DD$D8DDD DXDNDBWD>DJDD.yDDD*DCDJD,DsDD۵DSDD"D{DMuDD}D`DD,DFD DD)DRIDDF[D ,DzDmD+D!D[DD,DEDDD8D@^D;DRDD5DUDxyDPDhD+D(DS DpDX,D2DEDPDDb"DytDD۪D2D)DDD/5DD̛D(#DއD}DDDD>zDK-D;\D DvD-DDDׇDۑDD_DtDp0DV DIDDyDfDD8DaDDD+3DD^DDWlDD DIDDHD3EDED&zDDD(DDy6D DD? DDe DyDh Db8 DҮ DkDgPDD Dg D DS D DDDH_ D DD1 DC D DD&DBD)!DDzDUDVDDR Dv(De D6E DD3D|DeD D D-D* DqD D" DC D'- DXDzDD+D,DD}DiSD D=>DDXG D DQW DFD ~ D#D*Dt!DƧ D,DCDD} DD"DsDDDDDe D3DtlDaD6 D D6D1D DQD^DY DcDkDtUD> D D"D_,DHD/ DD DH D}DDi DgD$DX D D D1 D8DDt DD/5DPD^ DDsDH DXD$D D0 Dy DD#R D1DDDSI D܄D#NDDpiDPv D%DE DS- D=D DB D/ D[D D_DDDh Dj D2D DiDKD_D DY D DxD" DږD@DaDvDqD|D^DŒD0DDID8DDsIDͅDDƄD 0DQDe{DVDzCD)DPbDNDD7DdD\uD;D$DVD_D DBNDDDDNDnDzfDDD*DqD1#DwtD~1DUD|>Dt DM*D5DxD?QD5DuD_DDMD.DODD38DrDٜDmDcDD7hDDPDD cDYDDYDDD޵DDBD+DDiD_DDwD)DO_DDdD{DDxDn D6D6D}DGDzDQD-^DJODDd9DDDsaDD8QDr~D&DڍD'DDuDDGD#D:DDnD:D yDDD_D(D.4DKDDSDUDZFDTD&D<DiD6D0DeDWDgDDnD DD#DDADDDDSDלD tDDDD DDydDwD$DfDe!DD)DDKDD dDDbD]DcDDZDmDCDD1DDjDDDDlUDD-DOD>D,DD D DEDP*D7DޮD2DPDD*DhsDDtDh7D*HDD\Dv/D)DYD@DH D4DDDȮDlmDD@DZwDD@D,eDDDCDDZD7-DDD D)DLD D' DYDH DDk D D DDa)Dl$ Dw DDD DY D& D^D}DPDx D D DD D+D2jDD DDDϑD DD&'D4DD}- D DL DE!D, D D DD"D D@DfDDD-DoDED>CDDD D DtD}P D)DD!DjD$WD DBDֲD$ D;DD <DD& D:D DDDDZgDD&DHDD{ DADD8D DqDvD DQD D" DDUD DY D 9D DD DiDDDFDmDKDmD+DzD0Du D D D%DtDW D^D DDDڭD]D D2 Ds D~ D D/ Dg D9DDD(-DX~ D0 DD DD DDDDi DjDD0 Dм D1; Dd DD{DD}5DDy{D/#D DDiD(] D! DBt DJDh`DDDD(DӏDD}DDGDDDrDˡDmD]DedD{D#DtDD.^D6!DADwDDDDTDD5uDD}DDDD8YDrDRD0[DJGDJDsDDŌD8D+D7Dr7DDDoD\;DZD0DuDDýDD&tD qDNDTDDGDDٯDMWD.DxDDD,D=ND D!D DDDEDDD^D)?DђD D DDDDDADDdD%\D|DcD(DODDDD[D$DVD~DpDDDDvD /DD3RDr?DDfDXDFDDUbDDWDkD^DD0wD DwDkDGnDD3JD!DDDBD~D5DDDSD/D*DD,DDDDDODDDD{DiD3D1D5DD~IDDgDHRDEDDD IDDQDDŎDDCDuDDKD<"DgD_DJDDuDDDDDDȜD<DGDtD)pDDzDj0DeDeDQD/D߶DDDVDD8jDBMDFDPDwD)0DlOD DyDJDD D@rD^DbDDDDDDDDjD}DǣD5D-DD D DyDAD DmUDDD5DFQDD#D^ D D{ DWDDDD D1'D DV-D*DHDLDDTDoD{+DD(%D8DtD DHDDxDŖD DDz DP D3 DW D^ Dt D92Dz DD D DsD}DwDr DD? D DD@ D D$F DD DbDD D7 DDD DGDsDC DD D\ D Dv Da Dn DkDDD8D $DDB D D D Dp D5?DGx D DیDLDDl D! DPnDDDWD|D D DCDK D D DD9xDlD_D DK DR D7 Dr D D4DXDDD_ DD D(\DDa1Dm4DDD5DiD3D!D D"D,DaDgDޣD)}DmDDDDFDrD+~D$DD*TDJD1DۄDDDDHD.D=gDDĿDwD_D2DHD\bDxDXDDD@D>DJDDkDDJDDDDX=DDDJD nD+sDDDDΟDfD DS D# D7 Dx D] Drg DMD DM DKD DZD_ DDKD$D D6 D%DRDh D D[?D! DDrD^D˖D5D= DD2D. D7$DE_ D-DD֡ D.F DF D DD DMD.DDa'Dn DB D#DD DlDQD DU Dw DHDOD6 D2Dr D DD DaD;6 D DD DD.#D5@ D D 4 D D=d DD;DE DC D DD DD7 DV DgDCDZ D**DD(& D@D\DJD\DmD D DzD}DmDC DHDDq DD|D8DiDZeD=DY` DɑD;D DNcD% Dl/ D4 DDD˞DhD2DBDY$DD D(DТD D D#D^ D! D!D mD Da"D"7DD|%D?D 'DiD)D$ D DF D;D+DX D DD D1 D3 DG> D*nDDDwDDDDhD)DPDVDnDlDdDDD -DLDD3CD%DD5DD,DDtDsD?`DqDDDDD;DwZDSDKDJDpDyD'XDDDDzD'DD3D|cDD}lDDDD-D#'Dp"DrDD:D`D[DD(*D.DDDgDAD?DuDdDDBDbDbD$vDDDPD0DD/DDKD26D5DU]DzDV*DЊDDDqhDD DPDywDD D5DDKDZaDdDDD_D DfKDqDsDD[DD^ODDDԳDDD*D D2DWDDDD{JDDD.MDD{DRDD1DŌD DߎD8`DGD DXYDDg(DDD[DGDlD/DH~DLDDoD"DDa1DoDNyD]DDD=DIDDD|DD'DTDDXDDdDVD~IDXDh\DDDwDsDDDaDێDDDTD^aD/iD^DDԕDDDbuDjDD0DnhD\DDw1DDg6Dl=DDDQDJD6DQD^DDpDKDfDDD Di-DODD'JDLDVDrD!DDV%DkWDDkDDID D DJ D%DDy Dw D DbDtD3DHD,kDDD2rD( DD{D]nD DD DDD DzD@DDxDl DD D'DDPDCDBQD[D D̚ D|#DDcDk D D]D2 DRD? DW D` DaD DD ADPl DD|<DmDq D D= Dm D D.DGWD2 DO DwDD DlD DJD, DDD˳D( D>D"Dl]DQ D. DD D? D, D4D DDy DD'D:4 DoD(D#D4 D DDD D0DDwDě DcDDDS D DD! DPDR3D D DD DvgD D^D=D#DDȥDzD~D,D D_DC D De DK_ DS D.D DrDc Do{DV D; DgDxD>DD D_ D[ D@v DDYDD\ D D5D6DD7 D DD DDDќDD>DD~DlDDp$DDEDakDD(DDXD1D9DYDDD)D(DrDDDDD%D-DrDKGD3?D7DDDVDDYDD5DD~"D DHDO Dm^DDD;BDEEDlaD_ZDN1D Db DD4DD:D D[ DDXD9D D DSD͝!DDM DrvD |DDDiDvDh DDqDuDw D,&DQ D D_> D4 D*jDD DةDDDDo D+ D D@D+ D=DJ*D' DC DiD D<D Db DҩD DXD' DDԝ DDDIDID DW Ds D!DWDDZ D.DS Dj D D6D_ DYr D D^DĊD!cDS1DHDDmDDdlDzDԝDeDDDD3DDDKDךDYD\1DDDЉDDD?DDDDD }D0D{DUD0D|DUD.GDD_DuD=D/DmDDLDcDvDD +D.D`CDDaD\.DDJDsD0DCDBD/Dw4D@PDWDD=D{DD"0DYD\DaDbDVD]D2DlD֜DD1DDjD3DD4BDHDDaRD<DzSDxDD@JDDzD$DDDv DDDDDD0DHDSDDID8DDDjDD1uD1]DD3DDrDDFD%DKQDjD DDxD DDhD1D~D6DDD0DNDXuDoDDDjDDD DKDfDYeDgcDVDDkUDnDDxD/DXD8DzbDDDDDMDDD#/D~DD&DDED3D- DWeD_DOfDKD0/DD+ D$DDTDDDmDj~D~DDZDDu;D(-DwD1D*@D~DDDdDDUDH"D|ZDqEDODlDD|D"DTDaDeKDcDDDDQD9}D8D DDDJDAD{eDD-D D DDGD8 DDVlD DDmDD[ DB Dq_Dp D`D#D D9 D) D@:D'D D5 D)DDYDeDA@ DDD2 Dr]Dc0 D DdDDV& DDE D9 DI D!D@= DDDr\ D6DD0Dm D DaD DD[$ DD%DqDD0DD-DsDSDxI D D"DzDۯ DDr}DD D7Dў DDD/Dv D D’DaDD{ D D( DƘDDDD=sDDx DlkD=z D DhDD Dk D D^DNDD:DDD#DoAD3 D DdX DD)DDD3lDzDD#DD D DBDwDP*DD8 DħD`2DD D@Di D=D D\ DRD D6De D] DRDD~ D7 Dt DmDDcDZD`Dg DD DܳD D΂D[ D*<D D D(D D\ D Dq D^D/s D\ DDDDE D[DDHDD +DDޭDDZDwD'D(DMDiDDDDDIDdDD9Dk&DΕDDjD DDJ0DTD?DD>$D9DlDĕDNUDD DDD^DDD'.DDDaDAD)DDDjDjDDtDegD Da(DDD:D?gD{DQDDQDD.DDDMDDEDDCDDD\D=DnDDDF&DEDD+oDtDDKDnDZDDD}DDDDYDkDD;iDSwD6DiDKDDDHDUDGD~D%DLDѼDQ>D7DYDDDDvDD%DFDDDD`D=DDDD֬DYDD:VD<D DD6DD~DD"wD7D2DDDDZD6DD=4DiDPDxlDYDD-D'DDNDSDNDw^DDhD5DcDD(DqD+D=DDHDŐDD@DDvDcDbDfmD;D@2D9DD[DyD"CDE9DvDDܖD D¾DqDqDDD=,DLD6DDDDDCaDeDDWD,DDDQDIFDmDD+D9DD DŰD&DTDmDVBDDWjDSDؑDDsDDnWD$ Dn D7 D7k DRDK D D D D D D7x D DD` DDDa[ DDvD~ND8oD De D)DD߃ D4-DLDA D DDDN[DD D D2 D DD5D=D7{DD D'DL DOD D DD_bD DDADDS D)D D D|c Dj DD+ DDsDD4D0DD5 DT D\V D4DE D> D DCD DDD2DkDODX Dt DD~D4D( D{DPD5 Dl D DtZDk D(DD D DD% DD<` D,Dޛ D{m D D DD D D F DJDDRD *D@D6h D DDU D DKDD^ DDU DoD DD>D֝DP`D7Dxn DF8DvQD7DD D Dy D D> D D- DR D`%D D W DDu(DD=DPD9 D}DDqg DDR D D DD}DD#DD&DDeDiDDYDDBDlD>DD*D_D!DDXDDwDDDDDGlDDADDPDsDDwD%DaD?DDODmD7DqDWDkDlDDD'DtDSDDݤD~DDDD D_DTDrD'DqDDD,DD6D"DlSDInDMDDDDDIDDYD8@D}hDD!D:TD9DDDD_DNDDD<DWD*DDD DUDtQDD05D{kD DaDDCD"DDDDDsDD.+DzDSDDE D{DmD#QDDDD+D{ DĕDxFD`3DD|DqDjDwDDEDDDgDpDDDjDD DV(DOADD[D_DDgDDD4hD DgDD؍Dm DXDZDDD1DiDGD^D DD=DDX1DeqDD-DDoD(`DDߺD DyDDcDDvD;D9PDD(JDDDfDȥD]D,DDDtD?DD DϴDx DD DDb Dٷ D99D DD"D DD Dx Dף D DԐ Du D?m D D4%D9DDD4 D"D(:DtDDDg;Dp D$DZODGDG DX DzD D[DDSDDH D3D DͲD D DbD. D[1D D D16 DhDD%DDD: D D#D Dv D DCDD DS DFDDBDN DG DDDDD7DxDюDD DRxD: D # D1 DHD D D^FDf3D` DDDDDSDDD D1DlD.DC DDD DU D* DDmDP DT D0 DDf D D- D[D&DDDl DVDDDND DFD Dw D&1DS" D]d DDqD D D D>DQ DZ DY6 D[D1 D D"dD& D DS DCDFDv D? D T DGDPDv D[ Dpl D! DO DSD0DD DDnD8DuDlDDDADDsD6)D{DՏDxDdDD' DDTwDcDcD:DڬDDDDDYDzDiDD Dp0D=DmDDD5DDDDP'DDDD>8DUDVDjeDDmDDXDuDVDpDDNDYD͝DD/,DDD`D2D/DaDlDL?DRDDDkDDx9DyDιD~DLD YDruDMDwD<D2DDtDBDD9.D|\DRD=D:DD}BD%D DmDD)aDD`D$D°D 7DڒDDDDDvDŭDDܮDRD#3DDDDDD9CDTDsDLDGDDD8D$DgDDH1D_^DDu-DYDDD3DƗDWD.DDDWDSDrD[D D@DՇDDkDDqDbDZOD,FD D^D9DDDND& DxDDr D;cDCDDD>DDD)D[DiD`DHIDlDxDDWQD5DKDDaDPDD/-D|DHD<&DLDDpDD D[D;DaDDvDzD%DdDqD@D%DDC!DDDVDD@DlDuDDD+DȭDXDDDDDD|DhDqfD DW Dt D D@SDDDVDd DYSD!JDw DN Dr Df D DDAD* DDSD9 D DsD DmdDs D3DDCD$D D3 DDX DVDͼDHD8D Du D[D DD | D| DV Di!DyD!oDD Dh DODD DDϜDDG DD7 DD D1DO D Dp DvD^D DaD D/ D_D=DDDeD( Dn DZ7DƟD^DɟD.D2 D D,DD3{DDBDD9 D DD D@ Dx D$@D)D3DDr DDD D D̹ Dq8DqED D} DDgDID y D?DoDHD- DMDym D DWGDl DDҼDDDK D DDZ DWDZD/ D?- D DD8 DdDGx DDDD= DpD;D% D[ D D D\DB DDj DDDس Dj}D D Dj~Dq DvODDM Dm D'DDdiD!D(DDDD1DDDDvDbD=D-xDsD DBDnD DV4DDGD:D#DDpDHDzD\DRD_1D DD=tDoBD5Dk;DDDu+DD=DYDi/DDFDDuDMD+^DuDuDiDȣDCDDsDD<DDD*xDȟDDDDDDDODDMDDED DDJDDD]RDLDD:D´DD%pDZTDKDDYDDDpLDDwDDND@DDGD%[DnD:D DjD4DsDݼD!D DED6DDzDD_DDmD#LDTDD4DmD͇D1DeDg~D/D7DD<DDDuDD(6DD#Dz DDD~D;D)DBDVDkDDȦDDDpDIDD,DpD5D D]7DDMD DDDtDFDbD*8DDIDoD DDD/$D?DdDD:pDDO;D'DTDWD6ODD"DDD DRDDD3nDD=D=DmDYgDDDۭDQD0D[D4DIDDD&D DD'Dc:D#D,D9DSD&DDDDRDDDDlDkDL Dl9DDL DOwD+D sDVe DdDtDфD D$eD DU DA DDtDDpDD- D7Dd DDDDcD]5 D3 D6D@(D3D) DE D9 D| D8DDDDD" DD#DDb DDSD&DDI D$D{D DλDED)z D D# D D7|D DVD_D\DDV DD+DDذ D eD[D D*DI*D#Dc DDDD'DOD/< DO DD z D DSDKD DlqD| DD DsD:rD D'DvDO- D DDD DDAD; D DD DP D|PDD" D2DDDL D#DD( DnD> D0 D?D+ Dƒ D DpDDDD D1 D@ DqDn D, DD8`DDāDD7 D`{D]D( D\`D D DTD» DrDpD DdQD5 D# DJiDVD D§D, DٟD1DK&DDbzDDlD.DkDID3DDsDDWDD 6DZDzDDDCjD.3DvD}D%D@DDBDD8DDoDDPD=D 5D9DtDsD1nDDӮD0DID}DBD#^DDD?YDDXDLD"D=DDD DԨD}DADHD҄DD D{DDD5DD>DDTNDZD1DڲDlDD6 DDDbDZfD: DRDɫDDD+DͤDSDJDmDD`D.rD WDDKDHDvSDFDDED;)DrDTDfD`DD@DD@.D?D\IDM+DDǂDV!D$DDD DD>DDDtmDD{DD_)D_DFDDwDճDD/D3DmzDDD!ODDDD DFDD,D ID DDXDDLD~?DD~D>lDDDDDҮD:D*DkDTDDDD sD4DӉD԰DDDDD]CDD3DDyDJ{D]DD~DhD6DpDD^D4D:DD5DDDGIDDDD6DHDQ D"DxpDDDYDmD̹DkDDDFDpD6D!DDޘDDIDDaD DiDVD7DD#DDnDDD>DUD' DDV D* D Dp[ DDD܆ Di DU D!Dy;DtD# DDD} DD&Da D=D D. D7D$D9 DdDddDPDw D3D D$D/D+D ]D!DKDD DUDǚDD DD Di DDU DU DDHDg D DKD/Dh D@DqDNDD DsDDP DD D˟Dz DV D D D7DaD#Dy DBDD2Dl D(DD DD5Dk(D DA DDtJDQp Dy DDb D~bDSJ DDl Ds D DDDDqR DɞDD8D8 Du D_DDY D"Dw D DFL D# DDDa\ D} D| D7S D>X DD1D>DD DDDD:- DD D DEJDD D DTDP Di D܆ DZ D\ D5 D DAD+D8 Do8 DV DD#DDhD D-X D"T D=D D}.D< DܸD/DDDDG_D7D!DVDxDD,nDicDh[DD@VDDsDDGD+DcDtXDD7DޱDLD,D- D@D3DD6hD:=DjD%D1DpDDTDp(D$DD?D"DDADD]D?DDsDuDDeDtDFD=D4De)DDDhD(ZD޶DDDD*DDDDD DRDD5LDD)DїD^DDDBDDDDD(D.pDD#kDE!D`D#DD(DgDלDUPDGDiD DŇDDD DVDDDt DDLDDDDdDDD De DVDDDDDDDhDDeDHDNDD>D)4DDDǰD#DuDDKDDhDD DD8DGwD0 DIDD"DDD1[DDQUDDJD&DDD_DfADDDf DK0DDDD~uDZDD=;DtD[DDD{DDDVFDDwDDFDiD(D,DKKDqDDDZD DD@D(sDFDIDDDD=Di}DD=WDDADDDDfD=DpDFDtD D\DDzmD|}DD"Do D6D DDDDwD@MDX D DG/DDD}D8 D DW D%bDDD D-p+D^ Dv DD3DDZD^D{D Dl DDD3HD-l D DnDwDPDD&A DmQD(D} DRDD%D#D`D DP0DyDD_DDDDD%nD D6DQDc0DDDD0s D D D DDCDz D DDMD< DDiO D D Dz Dċ DF DDұ D-D DD D+ D D DFDt DDD D(D5DQ D DqDw D D"D D D ZD#D?DD} D[ DDD8 D' D D D DMM DD DD D DI D DDt DvDEaDDDD D}& DL0DQADvD+DDMDy D DDY DڝDqDit D|/DD D* DVAD DaDD D, DLVDoD DQ}D:DDD[ D:DpDVDgD|D!DS,DADtD4DBDKDGDBD'DDDDDDD(DalDDZDxDDdDHDDDiDuD DjDD|3D8D DDaDDeDKD4DDDDeDXDkDXD'DLDDDh3DaD DװDDDEDD&D+HDD#D6D(aDqD=D1DzD4DiD^WDвD\DoD*D]`DDDDEDFD^DD DDBD/sDdZDDD6D=DLDRDDD DmDDDD\DDDDD?DD,D DTDPDDHD'D"GDmD/DiDD{DD5DHD|DkDDD`BDD gDFDkZD;DDDl+D1[DDDDDbD.DKD=DJDD,DDګDNDuaDSDDDID&PDCD~D*D[DDtDD2DSDDQ{DDDYD D?mDIDOD(DD!DDD_DDDD DID2hDDDD[DDLDY"D̈DTDRD5DDDhDk6D0D¡DDZD&D"$DDDDD/D!D-DDD,DnD;ZD΋DD0D/DΟD%DDn D=_DcDi DDw DB@ DDW D Dh( DDDD-D1DfD dDPDDd D% D3QDy DqD6 DD DDDjD4!DDD7+D] DDHDX D Dǹ DXDӊ DtpDlD D) D 8D Dl D[| DDDDD-RD DD"D%D\DDxD~(DfHDwDDv DDJ DhE DV DpD DDD DDFDD DWND DXDDE DRv D D DfDDI D D DY+ D?D DE. D? DDnD8D?D+DFDDDXDfRDDyDDD;DBDBDyDC<DMDGDeD"DVDTDGeDD!DD,_D ODLGDDDJDCDD<[D[DD=DDDDaDDD9D%DGDDgDIDSDD5:DdDnDH1DDDp3D;5DcDD<DԔDkD0DmADvDD+D-D D DDXDQDDDNDbDD nDǝDWDD:DDDYD8DP=DݸD:]D3qDzD˩D/qD_DM4D7DD=D DnD/DDqaDDJDtDtDD%D5DKcDM#D&pDN)D DD<D0zD(D!D%\D4DD~DD?DZDaDD9DmD^DHDD~DDDgDDגDxDDeDL{D?DD_DDhID;YD4DDjD3DDDD<D1DtDzD=D9DXD=DFDD8WDSDDDDqD~dDD\DrD-DODZDDlD0D;DDjDDDpeDD_DCDlDsDDTDDD*DDvD=2Dw[DD@DDiDDuDKDDjDD2DDDD<DDSDfrDD,Df1D:DD; DDpD D?:DO]D:D DD&D"D2 DD{qD$D+ D LD D DDO2 DiDD} D;DoD D-xDsDO D, DDD7w DID D$Dm DD DDn DDTDE D8D, DdDD DQ DSD3DDWDD1 DG DyD0 DD DwDDtD1. DRDD*%DD"!DDXD-DMD'D Dj DDDSDPD7D,jD DѲDDEDCD%DUDSZ DA DD DDDDU DW D` DD|D Dg DXD[D-D(HD~ D DXjDDϨD gDD D DIDCD9D[^ Dd Dz Df)DDDRDYDDC D. DԈDDD"D!D% DDDDn4 D| Dd D D D DDDթ DD# D DtDDD^D?3 DDL DtDEDhF D DxDD% D DwD$DPDo Db D8DDDDDDLDϰD /DijD6DmD}Dz6DrDNDDDDdDjD6DDwD DBD'tD]DDJADDDFDDDpDJDmDHDDoDDDfCD~D!D D$DDgDDMDEDD91DfDfD D3D`DvD%DAQDeDkxDDDYJDyDDDD%?D~DxD`D;DDeDDY0DeD0+DD`D5D D&D DuDDtD-DiDD0.DDd?D]DDDarDDDdD,D]DF(DmDDDwD=DqDD9YDD6DwDJDPDBDթD^DDD&DDjDDZfDDDO=DE9DbfDgDWDnDDD DDFDDtDDaDD8-DDDbDgDDDA;D<DD TDDQDfDyiD˸Du~DTDDDF5DYDDwDzDbXD]D D=DDDV|DKXDDD?mD0DD `DDpDWLDDrD2DD2SDD:D.DDD>TDLDPDDKDDD)4DDiDD}DDD6JDnD=DiDDuDa DDDdD\DaDDHDD`fDx+D(DvDm=D.D DDdp DDDB D DDܜDT De De]DDgD DrDiDD(kD{D'D D\D9D8D D,D62Dh'DV0D D! D@k D D D D^#D)D D DdDD! Dq D'D D DDgDDXD@D Df DY D DD^GDDw DxbDe D D D$D5 DOD~DDr DDN D& D-D Da D> D D D DxDDf7 D DD D\( DD DdD DD%D DbDsDD0DDaYDD_ D D&D D D DDD7 DϝDVD D/ DPDFD] D9D.DvmDD? DDqK DES D>AD D DDZDE D6D D DD sDCDKc DHD> DٴDDDp DM DɭDSDɒD DV D1D D D6 D<:D D!FDt DB DaA DFD/ DLDD!D@DDrDDDDHDzDH/DwDODJDDfDD DFDpDkCDSDDDpD DaCDvdDDDNrDkDY\DD7rDDg=D DDUDkD~DZDD!fDDD DVDRDD!DDD,DXJDD^DuDS4D1 DbDD-D-D_D>D(DDDsDGDcD D(D<DDDDD`DkD7DwDvD-DҨD:DDGDD_DDDDHD D>DFDDDD|DDCyDD.DD3DTDKDDDED#@DD3D^D"DL1DBD'DDG<DDfhDDDDDjfDlDDWD-rDzDD/DN=DDDD`DDRVDDD D.hDeDD'D4*D8+D{%DUiDD`DjDXD DD,D\DDDuDD0DD6_D DD1D mDDۗDED@D@DvD[WDTDDDDYDDFDDJD~DD`DND^zDDDDDs1DDQ.DDD9DDDZDDD>UDDDDSDDZYD%D<DDDDD"D3DDID)DDK=D DDeDDDD D_ D DD DQ7Ds D D@ Dx D?DiDDK DD4DDF! DHDp Db"DuB D/Ds D DD8 DoJDD D^ Dn D? D_: D@D D DpDD DEDPDiDD G D#D!D[I D)hD[Dul DR D?DpD0 D[ DD DZDjD"D D D D|D D DlD1DzQDDjDD< D DDDSXDDIm DD D~ D / DD D DDD D D' D[DA_DD,D DC%DDȈ DDfDvDDYDJDKDNu DːDDLD/oDwDlvDDjDX|DDDzDpqDOoD  DP<D#DDD]DDiDXDMD DDB)DQD D[{D[DY DDm D2QD^D D}D DDe DaD]DDͤ D D_ DD2D% D^%DdDJ Dh(DXDtDD D~DWDDS D D(zDXD)DG2DrDD <DϟD[`DFD~CDDDDD2EDZDDXhDȱD$DCDDҒDDdDD?DDD7DWDD{DlDXD{D ZDDŠD$XDD?%DQfD(;D)DzDDD U DiDDDDdDDDDjDDD|xD9bDDD7DDGD&DDcD6WDqD 3D)D?QDxDDAD+DkD~DXDDzD#D1;DDRDlDD#D8D)DODDcDD2Dz*D5D.DDhDqDʨDWDvDq+Dv,DD]DDYDwQD.D2DD`DDt^D2D<D`CDDDDDxDD&fD%DD%D+D$DDnDXDthDaDBDDDDLD1^D.DDnDzDuDDDDfxD4DDD; DDDݲDX]DcDDx6DسDG~DDDDqDD!DD3DWUDJDD[DDDDFDDDDϬD(DODDoDҒDdDAD?D!DZ!DnTDs1DBD\ DJ/ DDD D WD.D( DDy| DHDD S D DcsDlDc DLDDKDHDtDmDwD D* D9DL Dߡ DD DD׋DAD DDjDD DADnD D{D,*DgD^:Dq D7 D۟D+gD3D DēD DD(D< DN DDWD"DI<DRDu D DDGD Dz DDDnDyDD,k D[ D DD>g DwDDΝDx DІD0 DPD{D D=)DD#D D DD]Z DDn DU D!7DDDB DD^D?DvDśD5D(DDrD DD D.DsDDID5DDDDC DDWW D5DDN DQ DDwt D=Df/ DD( D DD? Dr DZ; D}D%eD D D^$ DDjD DDjDgDhD DeI DzDlDDx, Dz DV Dw D DZD:Di DDpDdDD#D*DDDDCDD,DDHD}D.D)DD5DD& D<DZD;D[DDND(DpD !DDOD3DD DbDsDDDD:DZD~DDnDHD(D9hDDTDTDDDD~DDeDdDYDDyDvD%D D D*BDDuD&DDDDDEDD #DD 3D\DDD(DDQ4DbmDDEDVDDjDDsDa DQID D DqDWiDRD]D2DD\DVNDDmD,ID%DID+DqDzD DDǶDDH/D8LDDPDtuDDuDT_DD=,DDYD UD,DVD!DhDDgD]D{DODD$D DDDvDD DjDDDDeDDDD=DDΊDXAD]Dr DD.DDsD}DcpDN=D\PDpDDDD3DXDKD~DDD'DA@D) D6DgD&<D}D+DDDuDDy3DƛD D5DDa%DDD}D.D7DDDD9DD50DpDDDNDDKDa9DDeDD,XDD{DD%DdD+DD|D3DDD+D%D4D]kDYDJDDD DY DDD DN DB DšD]D` DDY3Df DL D/ DqDB D4D&zDD1 DaD}D0cD] DD{Dn9DD\DMDD: D8D D DG*D0DnwD: D/=D D D{D D:^DDD;-DY DDw DDDk D@ DDʜDDD D\eD[ DH DoADDD6c D{D D= DyDП DDDIDշDDDDDD DD֗DsDD4DD Dk DD&DwiD DDD DDxDDT DDU D"D; DSD*D7DF DDD DDDtWDD22 DND,5 Dp`DUDH' D` DeDP D DB DDRD׷D DOlD9 DaDD1Dk DD DuDmDC7 D Dw DDa DuDM D>D Dl DD[D DsDr D- DDq D2D D&D DþD D DdDPDƋDoDeDD| DDXDD2DXD%DCDy^DDDCqD"D>DD DD܏D DIDvXDDDÅDD<DfLDa"D_D D2DBDDXDoDDDZDDSDDD2DDmiD~D(DDD=DwDDeD٤DeRDeD_D[ DjDyOD[D(DDx2DpVD7DADfDDsD7D:D#DS D9DlD5DDCDCD@ DR;DfcDiDb"D~DD:VD-DDD`DjDbFDfDS(DDdjD DpDR+D4XDDXDD3D%DDDDD D+DDcDDDjD*DDUDDDl"DDDD]D6{D~DUDDDyD;D(jDDsDDD,D-DZ.D~D/DD5DDDCDxDʉDHDDtD+DD DtDD~D.E D5DC D*8 D0 D8vD)DD D8 D D D( D#D: D! D9D DiDѲDVD+ D9DnD%6DDDMD DD D DtmDDD: D6DZD Dj D D_rD&qD D!~ DD$ D9 D0DWA D DaD DH<D,DD D D D%q#D DmD| D DD|Dv(DDBID DDDeD0 DD DDD D-DXD[ D4D DDR DDMDDDD} Dg^DD9.D D##D'D0,D6Df$DDDG Dj D?#*D- Dg5 DDQ DKDD{ DsD#Df8DBDDDǽDDfD+DDXDQDr DG D(DDD D-gD<DڍDH DDFD Dz Dh DJDD{SD_ D D( D! DD1dD|DDo D D&DD(DqmDD!DH+ DDD=DD7)D%Da;D&D1D-uD DHD=DWDDԥDUDYDD:D$D)jDqDDUDn6DDDD9zD#KDFDsD[DDDDPD-6DDDD.DD/D~DDD{DDrDNBDT#DMD5WDJ)DDDDU1DڠD|DDDDDԯD6DDD D7DiD<DվDDDDWODDUoDDcD=DXDCDDMD`Db DD1DDpDD.DDߘDD2DdDDD\DlDID=DMD;\DHpD'DD DDoD#D@DtNDDDjzDolDD8DhDUD9DD<DDD=DLDADvDDDuD D}DDD D2DDUDTD8DDK,DqGDriD"DwD2+DêDDrDsD0DտD)DDlD8DJ*DDID޲DID;DD,CDiDDcD &DDDDpD3DD.DFDsD'DDz(DblD^9DDDj\DD9kDDKD-]D˅D DDPDDD/DDIDz9DmD7DD+DA0D#+D`D@DNaD{DD^%DrgDdD DDDD3DpGDFD"D!DDAD"qDD DcDw&DD D DMuD D DCD} D Dp D&DDPCD[ D? DEDDt D D@D'DD>D DVDt DjD/D DQD>,DuD DABDD^; Dʮ DA_D7 DD?DmD@Dl DcD D D-D DD DMDD#D0 DFD+DD D D7D Dg DĒDZDD D_D DD_D D{DV D Do' D. D DDuDDGmD%-D> D"D D~DDD DDD D! D4D D'DɎD{^ DPsD D$ Dq DP D4FD D DoD6 D DDjD D D6p D >Dh DWD D$ D+Dxp D5DTD~DnDmD^ DBDPD DDDu D!: D D+Do D\Dx DDD,rD8DbD D*D]D DO DD_DW DޥDKD"D DdO D) Dw D+D\D| DGDF D`DDDDG^DD}DΙD DD8DDDDHD<DADpD<D5D;DD&gDDoDv6DD*DDoD DoDDND\D*DDDD,DDI{DxDIuD$RDXDNDCDD-D{DTDXDkJD.DSD5DDFDmDDqDjD%fD DDDvDID1D#-DDDȽDDDDj;DDDGODDDPD,DDDGD/LDDD"DxDȤDwD#D6DyDD3DD/D<D1DIDrxDeD\DKD{D[DDD0D)DzvDKDDs\DF5D 0DxDFDDaD D[DMDkDDDeDDD5DD{;DwDDD/wDDDDGDnDGSDcDDDNDD D-DD[iD~DDD*DcgD%DDDHD9DDDD^D,D}eDMDD"-DDDUDKDDDʱDXDDȮDND/BDfD DhDP DiD4DDDD0Ds DD<DD~yDDD DnDD\DDDDkDj1D@DDvDjDXKD D0DD]DJ'DDED{DD DDD͚DDDߊDD|D,DM&D2Dd D#DD>D:D DWD_DD+D<D D] Dt DD Dl Ds D D\ D D D?{ Df$D.yD<`D% D'D D DB D. D DR D cD D';D7D D[DD D DgDŇD/ D,DDݩ D| D+ DYU D3# DDDRDu DhD% Dj DoD~ D\ DgD-0D! D9DxDcD : D2D DUDeDWDDD.DD DxID9DD DFDhDϒ D D D DODfD Dc D DDml DDQD6Df(D DdDo DD=cDa D DDnD?DD D֠ DsDL D7 DvDDDHDJVDDD D1D-MDGrD D DDDDD' D D(D2DDDDI. D D6DDD6 DDD D D. D D| DGDfDD D D# D DV DfDD"DBDpD% DD"DRDDyD DDhDfDD,,D'_D?NDDDD ]DDD{ID&D-$DyD+DD3D DDDDDx1DD]DeD4Du$DD"DDDPDD+D7UD D+mDDKDDDYDJD*D}D&DDSDNwD"D+DD@'DD DkEDRDDDժD"D D]D2DdxDDDfDD2NDWDDuwDD{D#D2DD%D8*D]DFD5DDCD]%DDDVKDDeD-DD9DKoDDD%D5DDDzDCDDDQDDzDVDDnDr5DmD2D eD'DZD16DD7DnDFD-DDDƮDDDPDD^yD"/DuDfbDDDD DDlIDwDDlD9D2DFDD~lDuDjD=<DDwDD&jDuDzD~D,sDmiDDyD1D>UDDdDDÛDmBDoDlD}DuD?HDHDD]DD)DRD{DXDiD/DDuDD9DDNDDΟDDDD+D(D]D1JDÑD;DTD֢DDED;D^DDkD5D #D@DDDgDDD"D%DڀDDhDODb DDDD3 DD3D!DW DDr\ D DD0) DDDEDD&DDD.D-D DC DuDTDDD DD D D4 DADT Djm D D DoX DDWYD DjW D DKDD,D\ D NDb D? D+Dg: DF D+ DDV"D,D<DDD< D( D{ DD DĴD=B D< Dpi D)D D~ DD'DDWD[SD$D/DsDD D"DgDD*ODD dD6 D4D DDdDD DGDt{ DD5 D DL6 DtfD˹ D%Dhf D D Db=D?D DwD"<DD`D/0D: DD D D7 D9 D\ DHD D^D DtDyI D DO D( DD DdD D^DD:DDD D DDS DU DY D D DD@ D D D{Df DDZDuD DưD=;DDD&DSD1_ D D^D. D~DiADVDD@DD;DvD=DDW'DVDuDCDLDzDzDCDM:DDDy&Df9D$/DVDʭDyDDq9DaDQDzDDjPD|D)DQDD[DDYDhDDYDD "DD?D D DDIDD)DyD zDc-DDTD&D DuMD5DD8]DjDxDf+DڲDCD'DD+DvDtDDD D(D1DBD0DtDLDqDk!DAD DPDDJD D DwD DoD'DD-DDGkD(DD2D\DmpDQDBDúDDDDUrDD[CD-D=D*DADD DDEDD;DMDdDDD3DDeDD.D?DMDYD'DYDDDDxDYD DkDnDDxDxD8D*ADDjDDAD/D#DDD5D_D}DBD}DDhDDTDXDDU D}DDKDD$D7DDDD6DDiDVD,0DDDV+DDSDPD D DbDՐD/DkD|D{DDD@qDQDcWDNNDuDDjD.DƼD`DCCD%DD%DND,DD+uD dDDDjD~DhDDBDD*DaDDyDTD D D5 DhD D DTA DDC DsH DDD. D2 Da Df;DDk DѨ DD D] D D D DD' D D D DD5[ DnD.DH3DDTDND DwDD>+ D_ DNDODN D7qD+o D}D DGDD&DDܴDFW DD`DOD_ D"&DSDD!D_dDrD"DC D DD_ DID DE[ D DDD5DD DtDFDVD0DD?p)DD3D8pDDDZDiXDED.D D DDٓD DDDD>DOD DqDPD D; D*DDr}D!5DvD/D]De D@'DD D=DD1e Dr DPDl D Dj DDD D!D;D DX DoD@ DkD D\DDDD6D D wDzDDMD% DRD Dn D]D4 D8 D9D@ DWD90 DRuDfDD@DUDӿ DvD D D2DDV(DDED D$DDXDq$Dg^DDD}DD DڎDVDDDDDgDDuDJD[;DD[DDDqDDTDێD^_D!D2DDmD?DΤDiD̆DDDDDIhD'DODDiD6)DoD1DDDbDbD{DD]DuDDDa:D'|DD:D}DnDD)6D[DWD5DaDD6DDDsDnDU)DbD&D+DzD D-DDDD8DDcD-DyDѤDrD^@DD=Dn!DDBDjDDxDCDDm)DDGDDEDxDDQDDu?D~D DDh<DSgDDXDCDDDD D@DDODDDD(DFDDDD[DYD'DDzDDF.D5DDNDD!DADMED=DDKDDDDDUMDDcDbDODDDhDDDYDD%`Dk DGDʛD DDlDoDDDDDCDDmpDD/DDkDD_D DDDDWD4DiDFD!DDAuD DDDnDbDbFD DDD4DLDDݾD*D&DgDrDGDKD*DEDDSD4Dk/DJDmDDDD DaUDD]D D'Dy Dǡ DB D D" Di D DP DD? D'D>3 D DDpDhD DKD0Da Dd D0DX D DD DDD+D#D D o3D) DD+xDnDV DuD D#DDAXD(9D+DDaD4DwD2 DV D=o D DADњD8D D.D1D D$xD;DDkD rDnRDb DSD&D; D~ DXDCDDD^D5 Dr D$D!DDG D DDDF D!,DG D D DsD;D\ D75D D)D/b(DDLaDcDb D_ DQ Dٔ DCD D,#DDO Dc D(DD#5D DgH D, D3 DXDD3DM[D DrD2 DuDDiDD%[ DLDـD7DDR4 D~p D5D DA6D DFD} D DlDD. DD> D/ DJiD[DO D2 D D4 DDH DDD DD!^D|DDODDәDDKD[WDD$DDDDD)D)DD(D,DrDD'_D1DD<DDD%DDD|DcDLDHD3}D!DeDD5D|D1DD D(DDDDlGDX1DDDDDDgND4D[DDyZD'DDD!D DdDD DDDL+DJDDfD.DYDpD*D^DzDkeDkD#DD~DDDqDLDrD@5D D[D\EDuDEDDDBDpDwDבDDsRDrD2D?D.DDXDaDnDxDDCDD0DZxDdDnDD DDD^DpD'DvD2D&DD]DށD3DDDgDpD|DDDyDD8/DhDD]DDwJDIDDDWDDfD4DDvDwDDDZDXDDrDcdD}D4DέDcDQD;DD$D\D_DDDDDh_DϬDfLDDDcDEDpGDDD8kD*DDڸDDDڭD1DvD;ADgDD?DHD+DIDDCDD"DDDDDXD1.D~DDzDDE}DIDDsDϟDD`DwDD/DD\D7DDzD DD%SDgN DȟDMD D D DfC DN D D DkDrDD DDD^D_ D9D Dć DD D~DVDUD9D2^DD_DEDbD D DTDDDlDD.DZD9DDWrDDD2DDVDѿDDYD{HD6DDxD,hD!D2DMD:DMDgDǣD4DxDD9DHD]D7DLD:DD^D&*D~DDDD:ZDDDD,D DDPD7DJDD/DDBDDGDqDDDMDlDsDLDxDCDDKD8MDDDnDrDTYDD2DJDD%DDҠD;DDD1:DD?DDfDDwDDRD;D4D]ZDb DDD?D+bDDIDeDgDzD9D[DDyD*DDDCDGWD7D D[DxnD DDD\DQ]D D(Dt DRQDD6QDDXD-DDdDDD}DDDkDDID%DD5DDDT D nD`9DD oD2DDDRD2DDDyDtD"QDDȝD5{D' D]DjD DDE DDŜD5 Dt D4ED[ D D)D]D$ODVND]YDVDDVDE| DRD6D8!Dw D* D DDD6 Dx D*D DAD?DԔ D<D5!D DXDo DJ DD DPiDT DjgD%D% Db% DD5 DDF DC D@DDdDD DWlDODE D DӡDϡD/iD D{D DDDu DDkDD#D D`D D4D 5 D DT D*D " DD D D` DD~ DDDD#DDD D DD}D{Y Db2D/DtD<8 Dt DD[DBRDDDn D4DuDDG? DD_.D D\D1DW DUgDFDDD D DJ' D%DfD D2j D,2 D\ DC>DL D DαD Dm D`D D^ DD DD D;DDD D D1D D"\D?8 DwDDD?DʍDDfDDH$DDkD.D>`DkDDD DJDDD DîD/DDuDUDDsDDi*DD D D\D8DO+DDWDD-DgDzDBD3DyDDˍDsDDDDDDzDDFD3D#DDٷDdSDDDDT@D~{D~3DD-D=DDFDHDtD,tDDtDZWDDkDDDEsD=D=DDDDbDejD[jDoDмDDNwDDD0DcD̺DKDDczDDaDDD}0DDeBD,DPD)DwDD>D5D^D#DsDXDeyDS*D$FD DDGDovD3DD?DHDDBGDDDhDZDpkDoD"DD8<D!D:D؞Dd_D%DfDTD5D5D DDKDDDfDD&DbDeDFD%{DD\D8iD6DDDg/D>D D=DD.DUD DLxDDD͜DzDDDDDD\D8D D SDHDDxDDD[D,ZDS:D;oD~DaDMDDDHDED(DxD\D D4%DJDWD@D DEDnDaD*DDD DDKD3QDDDDDa*D&DeDDvDdDx2D7D D]D. D7DD* D DTG D{DDaDDX#D}D|9D>D;DƚD3 Dl6 DDFIDOD> DD%Dx D iDDhFDD D-fDDDe D D2Di D_ D DDFD2DDsDTDADD& DzDLDDyDnTDDDDh DaDN DD[D D` D$D@Dٴ D#!Dr D!DXDíDD?DD2jD-D66DD D;D1 DDDPm DCc D?wDJ DD|D-Dc DDDt D*D"(D D DDkDDy DD" D DsD0DD1] D D4 DDw^D D^Dh D]DiDtD7Df DKD)&D1 DC DD& Dt D$ Du Db5 D@DDr^D DW'Dr DDD D DfDrD D D D Dv D~ DDp D/ DDDD DD DDgD DPDDXDBDnD DyDfDLD'DvD6DDDDGDDDDDDDiD{QDD(D|D"D͎D(D]D DDDDDDmD8lDD~DDA/DmD76DaaD`tD, DD|DkDDHDDD DRD?DݡDDWD*DcDqD{9DrDJDY!DDDyDDDDD$hDDDID DMD>D\De DϱDDDaDFDDkDDvDhD>iDZDAcDD xDWDBD{DРDOD5DED]D/D,VDDsDD<D,DPD1DD#DDD'DJD }DD-~DTdDZ\D9D DMDDDIJDD!DD DUDmDDYD9D[D'DYD%DD[D_.D4D,WDfD5ID:RDDзDpDDD<D$DDvDD@DàDqDDe.DoDD\EDDD.D4DQD-D SDȜDgMD8DzDlD3DݎD#ND1D D DSDDpVDDhD.2DDy D|DDD_UDrD$D D#D?DDVD[zD,DaDDDBD DD' D}DD@DDDD0DMDD{DzDDuqDX DDDDfTDDG#DDjDSDD<#DRDԝDD% DDD=DDDUYDX DxDD  Dh~DKDn DD Dm D Dŝ DD/TD D-D# Deh DDlD\ D DDDdDxl DeF'D$DB D D-hDrD D D D'DDrX DjDD DgDbD D DLD DzDD)9DDD@ D%D5D$NDDaDѯDD?o DDAD" DfDpBD D DODD9 D?DDDID/DDX/D?D¨ DD )DWDZ D!DS DD Dt D DDDPDR DKDl DDx DG D DfDD D}DVoDuSDcE D_DF6 D` DgDw D Dd D<DgD D D DmD DzDlDFD DDE[ De+D DFDD D DqDOa D3 DF D DHMDI D# DDY DbDc DD.-Dx D DDWDDDNqDVDDHDFCD%DDj DXqD@_DXD|D,D@DyDD7DڷD DDFDDmDZD:DVD DD~D>DWDDD2DVDέDDDD.DD DDDDIDDD[DaDwDDWDDDD*7D DteDDDHDT(DDDDDwDEeDRD\]DDD:DD1D}DDgDD$DeD DD1D6DDfDDS8DD^D1DDdD`DD_Dj]DDRDD]DDWD5ZD+DYDDDBD'D DDD, DgDDDnDDD֩DDdD2D#DgDͤD(D̴DD>D6DDjDD D\DDD: DdcDrDSD8?DDDK}DDHD)DD]DpD DDVXD-DDDDxD,D`DDpD8DLDDkDKIDnD[7D5@DD{DOD3DDDDMD7D~ZDD]D DsDGDD~D_;D$eDl%DD$DDD6gD4D ZD.DrDDD"D>DhDwD2DpDnDVDDDcDpDnEDVPDtDDD DD DDDo^DDlD DDwDDtDUDMDhD DD|D D DDsD,oDSD DrND Dx D DbDD0! D&DE D DDLD [Dd D; D1 DQD"Df D!D[ DQ}Ds: D D|Dl D<D;o DO D D DD-DU D DZDr9 D D DDİDqD DDo-D DfDDi} DD" D Dx DD?D-3DFD#DtDD1DD DH D DD$ D D DD^D4D D DxDhD2 DJV Dk` DlD~D DDT DD D#D D._D D"DD)D`D<D> DDDa}D7Dr DD|EDy,DRD]Dg DD DV DPMDXDS D2 DDD$DQ D# Dd DDw D+DDDDw D} DH D D( DDwD D8 DD Dd D D DnDvaDϳD D D!Dq& DDDDID>DDCDDv'DUDDyD7kDƕD DD DD=D*DnD!(DPD DDDD_DDǃDxDHDD/DDDDDDD.$DVsDeDDDD/DzDчDQDDDpD DDXDq DD5DD<D D2DD%D+D#8DnDPeD;DDbsDDDD.DaD:DDD{DD53DyDrD DDiDJKDSD1D DDwDDDtD DeDDODyDb/D.DDDpD%DGDD8DDDsDDoD(DDxwDCD'DjD|?D8DQD#D?DpvDnDDD=DD@}DD]\DD/DDD:`DcyDDD/#D9D:DD;D`DD[DD\GDDDx[D\DD;DmDaDD\D"D?D,D/DDGD@D;FD9DDDZDD>DpDADDДDDiD2Ds1D$DwDdDD.DbD DNDD D@m Dyi D D DP6DD-DBDC Dק DDz DZ D| D>DTDvD< DlD DeDu D } Dw!D/cDI DDDBDpD DD D DDaDDD#x D D@GD DA DDDDv DtDc DξDD+DxDLDMD DDD_DoD$ D-L DDNJ DHD#b DuLDD+DYD DaDDtDDD DQ DaDkqD*QDD`DD5DDDpD6 DfDDD DDPD m DD(Du D D!DDn DD_ DD+DuyD Dv# D#WD DD' D5 D DhDE Dj DR D= DQDbD D> DDDZ7D]QD D Ds DDlDr D$DQDݗD2* DF< DDD}.Ds D: DD D D D<; D1D%pDr DD,DpDr DDSBDtD1?DR DD"@D;DD!GD)DDDD!DDDcD9D}DߑDDDDسD&DDd}DQDDDjDVD4D!DD D|DVVD DxD6D;D3DGDDD$D2{D\DWDafD+DKDDDD"D\DD D JDDDDDDVD0DDDD%D#DD|DDDDŽDDC8D,4DD|DnD"DDDDDVrDDXDDXDD D1DOXDuDD"DAD\DnD#D@D\DcD?DD8DD<DDRD?DD+DrDUzD9DwDDDzDD/D)DnDKDުDD9DGDPDD(DJDZDDwDDiDDDDhDFD DeD"DːDaDD׮DD@(DyD}lDcDVDhDDrDD[DDD\1D,D D:DzDDEoDf*D2D D!mDjDRD{D!]DDDVDDDDDӿD DàD1 DȿD D"DwDBD1DDnD޴DDDfDDD!aDGDWoDPD4DD D#DDȻDDDvDD`D1DlDD4}DDoDϳD}D~D DaDGD.DDRDD D- DD8DlDS D DDc D' D(bD\ D DOD~D D DD3 DD*DD=DpDsD\DqDnDfD٫D D D D*DPDp D7DD%Dk\DD%3 DD_ DCDtDD2 DDk DDA Dp DDD>(D D1D)LD DTqD3D{D>D D6DYD DX DD, DɒDED" DDMDnDDײDD DDaDjD D0 D7DD,2DKD^DI`D D? DN DxDD̊DD DDDDADx D_ D DImD, Dg D RDÞDD D? D D DHD9DID_D2DD D,D D Di DwwDbD*DB DH D Dh DPD~R DkDM%DYD>: D]\D ? DD{D7DD0 D D D9w D D{DBDDD D0D D6[D֯ DDDDDTDD!D/D3DD`DQDlDDDDQnD*DD2DDD8DmDD DDvDIDDDzDVDDu[DDED\DdD0DzD+D#DDsD8)DzvDE%DDZ?DDDoODyDPDDD\kD̯DIZDDDD3DDoD}DD DfDWD:DD$DDDPDzD.DpeDDDDDhDDD;DDD$GD`DADD"DD4DpDDD iDNDDzDGDDDODxDZxDD=DEJDJD@DmDYD١D˚DaDeDDqDDhDD-DD5DD/D DbDJDuDihDDDDDVgDۭDDQDXDcD.D ~DDD`DiDgDDIDDTDIDxhDDDDRD(D*D"3DADD^DDSfDԒD!DD!DeD DaD,DgDDGDPD4DD DoD\DuD9DtD`\DaDDDDվDDDDJUDfDrD0D&DWD}DpD$1DDD D" D` D DuD#D>DD D[ DUDTDDk?D DDDDD % D$ D˖D D1jD De!DMD! DD'D0KD. D DgD'K DDDr DPD$ D DUDSD"D- DuD DD+'Ds/ D :DPDM D DD\ Dz D9D DZDd{D=DD_D$ DGDu.D D]T DD DDD@ DDܾ D&DuDj2D DZDD4D!DDpDDJD?Ds= Dvb DM DK)DF$D. DD DD$D DD0D] DT D%DIDDpDCDlDQD D^y D Dg D D D, DZDǪDDcD DD D^ DUi D6 D۱D DY DDD DնD8 DٻD%CD"DITDDAD9D DY D3DDzDDDՅDWD @D-DPD5dDDDoD9DuD}DdDDDDDHDؑDDDCD DDDD)xDODD0lDD@DDDDDqDD|lDmDDc9D DeDʺDDaDD}D2DDD;D_{DnDeDhD$DDD D'<D;DԘD6DD)DHDJDyD3'D-DCDDqDDD*Dm{DBD`DD0DDDD6DD/DjwDD:D2DDOD@D| DkD :DvDDچDʍD>DDYDDDbD-9DMrDD1DD-SDDn:DcDIDD-D]DDĪDDND D8DDqDގDD]D:JDDODg DDjTDWD=DUD8hD|vDH<D#D~D}DBDD^D4DܞD{D4DMD>DDwD֎DDDDǀDgDDDDDy'D<D|D9DD^D=DDD$DPDMD^DD`DDDDDDDeDDDr(DDm[DD1DDjDZD~DDDDQDTDڣDjD\DۗDǪD4SDDkD\DDAbDD$DaDDoDDDDD|D]D-D+D8D0DD!^DDD(D.D5Dc]D[DVD3D D4DD{eDD^ D`D D D D D6DDIDWDft D D DM DsDjMDD>DD> D~DDKDDP DKD:DnD D D DWD> D; D< DDVmD- DZDrDDMDn DFG DDFDDDK DS DD@DDD+DoDCVDD' DA D DkDWDD8 D D DD<D4DdD DC D DD DU DD(y%D. DbD:DD{DD D D D]DD D D D=DDDD) DJ D|Ds D`x D_W DgDpD0 D DqD7 D5DT Dy,#D1 DDՋ D!DD$ D" D D D8D'@ D@iD?K DD< DTmD D D D D/DDqDQ DIK DDwD D D DDOD D! DA D D?Dm D~DUD}DDHDD>DDD7D3DgDDxrDDDΟD4D\DDTDD,NDDDUDD7D'!DDzDD+D1DDLAD4DDjDDtDqDDDDZDLDDQD4yD?D>DDoDuD6DTDuDRDDKD2 D&Dv'DD+DDDD½DED|D%D,D\DD/"DBDDkDD9DDDDD DoDD(DDDqD`DkDDkDD]DoDDD@Ds1DtDDDDD)WDDD5gDٰDPDxDDuaDץD?DDDUDDEDo(D-DADDND"DpD*DDD~DquDBDDDDD6D^DDv5D8DIDDͰDRXDDDxD~DD^!DDD1hDP@D5DDDDDaD6DDIfDDJxDDDDD>DD{D!DPQDD{DpD D|DtD׮D Da2DxDD3D@$D:D~DDDeDzDDѬDD%DDDD'5DO'DVD9tDDkDDDkDDDDDiD D5DPyDD!DDDmDDD8D DDMDDY2DʇDDD0D{DcDoDD; DDVD-D0DDDD DDQ D{D~s D D D DX Df Dk DqD D+DQD{D DDD}tD#DDkDjDDnD DiD Dm DpODnD DBD7xDB D-D[D=DR[D"DD1 DDcDXD'D#DD| DDR"DD DGDa{ DDs D4D< D} Dl D D DLD4D0D(D# DD"Do DR DEDD DD'{ DD|DcD D>DSDDݚDVD{>DyD DV D-DGDu2D!q DND DSDE`D^D) D D DQ D0D DZ D&De D1 D'~ DjP D[ D8D( D DDADUDDvDDD>DD+HDzD[DD_,D-DmDc0DDED(DD DD]DDeDDDQDDD/ DDfD.G D D: D# Dø DDPD| D{DA6 D[Dȉ DDDMD'5D D D3DD D? DlADW D{D2 DT DD DD D5DIDD/ D D DmDPDcDDڞDVDr D aDsD^DDDX DY'Djf DnDDk DBv DDD3DDSD DeD. D+ DɆ DtDD DsDD2DD D D7DDGQ D42DD0hDL DӬ D; DD DUD(9 D D DN DPDaD, DDv D D DD8D DK D7D D Dq Dj D?D@A D6 DDC`D DD`Df DDsD(\Dt DDyD D DּD DXD4D!w DRD&D!DM DDN DQg DDtDa Dz DwDTD4$ DCD?D] DD5DE D[wD2DiD'bD DDDDD&DDEDD D6DzDDD MDDD4D1"DFjDDD&DKD/5DD? D D^D6kD_DlD|oDDRGDUDMDtDD DD>pDDPDDpjDD]D]DȎDDyDDrD0D4DDdDD'DDM D*D Dz3DDD$<DDDmDD D_DDDMDDpGD Dk;DDD\D8DܟDqD4D DwDioDDqDDP%DDSD#DjD"DhD*DTDDED`DD3DDyDDDRDD4 DDJD dDfDDOhDDDkD0DCVDIDDDYD :D KDDD)D5yD8DDHDѩDDDDNRDeDDDDeDb DDmD;DDDPDDDDDND$D$DsDhD)DD1DD%DDjDzDdXDpDD7DDDDD DD/6DgDDDD D$zD@_DDD "DDLDDDDtD uDl D~D D4D̹ DeDDDDDDMD Dg Di DDz DeD Dg DdD|D D#DD DDXD D3! D DED-D6wD1GDD• DD} D Y DBD'2DADHDi( D+ DXD_D DրD DD`DDDRDYsDJ D D} DDx4DDD% DND?DDD0o D[ D:DDDD<DTDdD0D D}D D`DDp&D(SD Ds D D& DTD\j D D D! D` DDDlD%"Dv@DDR,DDpDDDwLD%D\ DG= D^DD` DmDm D{ D2 DD;D)ED D3 D D^DlPDG DD D DrDFkD4 DID D#YD D DDh Ds DDD`2DwDHD<DTD*,D> DD5DE D5 DDTDP D;DMDD]DlDD1D!D\DRDCDiDBD-DD6DD-DDeD[GD>(DDDDID,nDDDDFDDDoDDD~D-DD3DoKD"DwDDDADDDnDJDDVDjDDEDDDD7D:D yDKDH{DDDSDfDDU0DsDD`D-D DwDD+RDaD]D:jDDPDD4DDΞDuD/DWD DfDyDYDʧD0DDADDKDdD DD DϩDDZDvDDxD^DDFDDDÊDJGDTDnDjDVDj{DDDdDNDD[D%D D ^DeDDlDDJDlDD D3D}DDDzDc)D}DDqDBDDiD;DDjDDD/D]\D-DVWDD_<DDtDDDzDvDXFD1D D%D@Dʇ D{D DE D* DD DDIDL D D=GD D>[D"DD, D DDDu D,+ DDVaDhD>)D5 D D DĢD2XD DDU!D2DXDF DkDYD Db D,X DJ\ Df DW DT DnD: D D DD) D( DpDi D+DFD""Dq} D] D9 D' D'D8DDfDDD]DDD!D'7DނD3DD DWD8DD7D DD1DdDîDz/D@D+<DBDD7DPDlwDD[DkDDސDDهDy<D73DRD,DLDDj%D DyDtD[DD?D;DВD\D#DKDfDnDDD[ DyDjoDnDD2?D'_DDD6DDTD'DqDN DDlDiD_DUuDqDUWDDIDDDFD DhD/DDHDDTXDwDD$rD$.DPD2cD6DDDJDDG\DWDDʌDDDFD}DDD$DD(SDbD&D>DЅDDحD hDʞDmDD)DDO[DDDND DDDDlTD0gDDD/-DTD8DgDDDD3ZDDdDrDzbDDDDsD?KDD3bD ~D]D*DD!D6zD`<DJ\DDXD1lDDDD1DDKDDDDyDvDP{D/DEtD2|DDsDD D$DD{DDDDmDDDtDwDD|DD5DD~DYDDD%DDRDrcD4D<DDD nDfDD4DD6(DD6 DDjDDsDDDjDDDuGDDDmD*UDиDaDDEADTD̏DN DbD. D}DDC DRh DDR DD DcDֳDCD{ DvDM DDDDv DD D[( D DDK D D=DD DNDDZDaR DއDJDDDJD1D2 DD DEQD\XDW Di D;PDdDP DoD+ DDDTrD D DΕD0D({ DD>D6DqDDG DDϔ"D#Y DlwDDV DRDozDDDDv Dc D;CDiv D D2DDsD6 DZd DD D D D(D DOD D9D  D!^ D DPD6/Ds DdDqDDݫD:K D4UDNDZDDу Dm D@DS DD$]DZ D DЪDDd D6 DF D Df DbD8 D DeD DDoDuDD6 DD|D` DL DDZ DGDDձD DDD D܄ DTDqDM DCDZD1D1DDD@MDDDwDDDR[D|DQDWDDWDM D[D!?D>~D D`DDvDuD1D9D HD]DD#DDD(DjDΥDD62D۝DDC^DNrD5DFDnD)iDeDHDD:9DCrD<1D:DӹDDDDFD0D+JDDDCDD6D8DoDDDD=DDDDRDUDoDDqD?DfD;D4DSsDbDDDFD(DDDDDD!DmDmDn,D7DDFBD2DDDDXD[ DQ|DD)DDeDDDDVDnDD9QDD,DtDD5D>D]xDDD,DfD DDDDDDDq<DDD6DkDzD D#DxDUDS\D=>D~gD]DVDDDDDDvD8DDDE^D]D9D7DȱDsDDDDCDDD-DDVfD\DTDDőDMDtDDDD5&DDaDD`DiDv#DDZYDDDDlDMDD*DADDBDDjD BDDKDdDtDD~D{D\DDD:DD!DDaDD'xD%JDhDxDDD]DoD%D\DZD9nDFD!DD`DDJDDDDD#DDwDDDD D0&DD5 D%DX D DD^b D+D^_DcDoD DtI DDKM Dw DDOmDy( D DZL DDDY Df D,DR D D DJlD D Dg D D DL D` DY DkDADD DaDY D DuDDDD DD Dm DD'Dca DDrDG D DODD D$D DDΐ DD(D/Dk D+D.d DMD D. DDp DZ2DtWDuk D D>D* DåDDD5D|>DHDZD D DD9DӒ D; DJD* DGD;)DDnD D DJDDi DTD D DDDs!DΤDADDDgD)DD! D D DDDDDu D) D b DDIr D_ D!ZDD@YDD]DDf D DD5 DX DnDQ D- DzD Dw DDD-DذDDЕDUDDpDDDoDvNDDD:DDD6DDL:DzDD DBDDD1DD0DDDuD @DKD#DPlD+D=8DD"SDyDUD6DY}D$DWDYDdFDZ_DrDE1D<DWDD׾D9DR^D]DVDDZD<-DzD{uDzDDbDZDDgqD5DD5D}DgDDDYoDNLD7DD+nDDDo(DgDŃDDѕD|UDD?DOD`#DDD&DD2DpkDDED(DI!D:D2DMD<DςDrKDSD\DD4DDD)DDsDD,D9DLDDD^DDODEDDYD/`DD|lD/'D D&D,BDD;DDDDAjDDiDdDID)D{DDdD-DID`DұDFD@D1DGD֮DDDDvDKDDmD־D_DDDD6cD6DAD%D D D -DD5DDDD5.DD(D:DCDFDb D]DADԖ DcD6 DEDH D\,DtD?DADLDDDw DD'DDtD%DDF D D D` D` D^ DRD&DDFDXDDD-D Dw D\D1eDB=DmD D7 DDwD/D9m DL D:DDr D6D D֡DDVDjD7DDDԝDjBDD D. DU DD, DOD D1r DDD DD@ DT DVQD`f D^DT DnDDDX DFW D rDDVN DD DaDD* DDD DGD.D>SD DC D-e D˙DD=DkDDDm D D>DE|DDL$D DF DD D#DOD%Dy DDy D DsDl DD DmDf@DDD; DK D,ID& D sDDѯDD^ DPD-SDDM4DJD D+G DIDDDڐDgDÙD|D^ED7DD DD!NDDGDD#D.DD;DۖDD1D-DEDBD`DDCqDDvzD^DOD7D5D{DD6tDhDDD|DD8DcDBgDfD}D DD RD_TD<DDD6DɗDKDDDJIDDgDDD9D4yDDZDDדDDApDODGD DD`DJD̢D;DD(Dr!DDDiD/DӇDD1DDDיDDD1DzDDoZDBDsbDDcZDDD.DDD`YDDDD"DPDkD8PD @D_DD5DCDDͣDŔD6DDD>BDtDDDÄDDDX`D}DɏD!DDlD]gDkD&)D%zDDDĒD DD.DD"DkDTDaD6DDjD"D&D:DDL-DvkD,DsDDxDDsDD DDD߂DDrD}|DaDDDљDDDDԼDVDDyD9`DDVDD(D!D.D8DXDBDDDD'DDJ:DlnDѵDw:D#Dp:DD\DADD2DpD<DTD}EDDz&DYD~sDD1D?;DvDDfDDDfD|+DDɔDrD DN DD=D=D}DnDMDDD\DHD+DcND:D DDڝ D$5D DDDľ Do/ D[DD DBD DIJ D۾DDu D DDW D D DUDgr Dv D> D=DD%D DD D/ DD<DED/DqDDD DD.?Dn6 D(bD<D DD DHvDDDhDrDDt DYsDl+D D *DDt DDڣDMD2D@DD DDD; DD DDDJv D * DRDDD DDD5DDB DiDΟD4D D7D[ D"D"D DD DPDkDDDDmD D D*s DDv9DҚDmDHD`DD5wD] DlD D Db D Df6DV DD¬ D+D D[ D DDiDmD D/G DP D> DeDƴ DL D{< D D] DkDDN Dq Di DD Dt DDěDDN DC DwDDDDRDD fDDD DpD{DDoDDD6IDn>D6DNDD<DvYD&&D:DD`DDDukD $D#DDD=kDsDU|DiD}DMD_DjdDD4D$,DD2DD~DDjDm'DD+DD(D4D5DŽD,AD&D6DDDD+ DDܒD|0D= D=DD+ND D^D1DjDFjD.[Df"DDMD3(DmDpD D= DtDDGDbD D<D.DDODǕDDD>DDDDYDDD9DIDhDCD8D7DlDDw.DVDߞDWD'DDbDDDpDD/^DًDmDoDߏDDD"DEDxDDDLDODsD_DDD~)DtD!/DDDND_D?D"D"DDCDDDDDDDDD(DDdDSDTDDDDiD DDFD D&D"DwDGDxDWwDDGDD\D%DcDDUDpD`DDy:DD D"DDaADU_D)FDD9D_DDCD.@DP@D@DDDODND[fDDh)DE,D2DDDD[DD0D,DFDvD:>DD D_DFDbDTDDTUDwDDzLDDDD5DSBDDDDpDpDY?D'DWK D D=D0y D"D%~D= D D4 DVDD DWDD DM DSD,DD DD l DM DPDDDDv D]? D DtD DX DCDDxDUD D[Du Da Dd#DdD D D D D DG D|DR Dc<DD DQDD&Dg DvDDDD' DDDHDZD D DbD!DD DXDD Dg DDbDyDЄ D DDv DאD2 DDoB Dr D DD2D]DezD}D"DEr D]DDpDDeDCDGDfD D* D*DE DS DFD}p D D ~ D DD$DD DD{ DoD DYD܎D4DDhDI D DDxe DR6 D%DDD DI D D\D D D D3$DH DȦD DT=D9 D DPDD)_DTD&xD[D ,DkDDfDD@DDkDPDDtDDvDeD?DcD$_DDOlDFDD{DDDDc DDD&DՑD٣DdDCD&sDWD$D}D^D&D/DlDqWD|DYwD6kDDDtDB"DDED3D2D.DD8DDDJD{LDxD=CDBD(uD,DYrDYDUDRDDHDe?DDwD DDZDD*DBD}DIpD?DqD[DvDDVDJDfDZMDBDVDC}D^DDvDh`DQDD=D DD?DD'Dw.DR.DDD D=DDDxDD D<DDČDMD4DuxD DqD6DbDϓD߯DfD(DDCDwDDDeDȥDMDDX!D)DŽD"D mDD]D|D8DDPDPDlDED'WDD'DDwVDwjDQID!DDDWDfDļDdDnDDMDQDD1DDRD`DDDt9D DDDDDk;D}]DxuD DD2DoDlD}D5DD"DzDwD֦De)D"DZDcPDDD*DJDD DDDIDgDC D2D<DD+D&DD6DBDphD2D:aD+DDDDDJDDDpD=DWDDDRDDλDj+D D#"DDzDDyfDnDZ D D DC(Dj, D" DD.| DdXDJ# D D"PDnDDiD,<Du D D~E D\DuDaD D D Dt^DTDW D^D D[DDcD DDDqDz D]p D D1ED} D7lD# D{DADDB D.a DnD D3DD} DSDhDD:-DV D D~W Dl DB D6DQdDD D DD D RD<DD2 DX DU DeD` D DDX D#D DaD D7DDDٶ D/1 DD` Ds.D}DDDQ)"D&CD D.DU D^DtD% DLD\\ DD6% D" DcDYDz D Dq D! D D+zD8D2D D]D Dn DEr DrDD F Ds D~D~DD D?D D DvD DrD D{DDcb DDDD DbDDDDFDqDND(D"D0*D:D2dD<D{D DЫDsD_DD>DpDOJDBDDDvDDzD7DDD7DwDD1DxDD{wDGDBD_D;DDDDDwDfhDDDDXD:DsDDDED@>DDD-!DDQD6DDxDwDSDd.DtD+DLDijDLDDDxD=D~5DDD'{D DDUD+<DDD[CD-D%DD]DnD|D6Du DzDZDSnDDiDVDRDD@@D%DDDj@DD;ZDD*D5DubDDZDD9DyD DSD~DDDqD5[DwD-DDD+D'DDvDT)DDDTD[DD_DaDFDPDwDOJD#IDHD1D D&DD_pDDqDDD/ED)jD?D4D&D LD"D1rDD1DDD6IDD-DD-DNDP&DD$DGD/DDD8D5DDiAD D>D!DDYDDDiDD/D|D#D"<DDD/DkDDDcDI4D/$D@DNjDDD?D<D+DD0DbDfzDzD2bDD3D~DRDeDÆD۽DD8DDD.DDDD DDvD$DDKMD<D$D 9DvDDD(DxGDde DGDD? DDTb DDD DQ4Dl} D&@ D DB D:DfDDy4 DFD D,DE D6D6D< DDbBDDDydDa&D D[ D D^ D{DDD$D DVD D+ DD9D D\$ Dй D߀D9DoMDI DDD͒ DDDDlDPCD DmD5p DDh DjYD"D o Dd DuD De D-DOD9lDy DoDJD`DD4| D+ DxDIUDD DFD*DID D\D D D/r D(D`Db- D DD DإDG Da^ D D $ DoDT" Df DDDkDv D?]D) D& DDDͮD D D?D4D0 D/D Dc DDrD D(DDcD DO DZ DDu DSDD( Dh2DWDeN D DD DD?,DSD]D`D4DaDDđDDD+DD4DcoDSDDDzDSD1D DD[DD?DDDCzD0DD6)DjD DUDEDF DDbD7DTDD1DbD3D DD[DDDD|D DDDxDDȓDD]DDD3DDND4DAD•DDOD`D#DDDDNDD3D<DD/MDڽDD|DD]DGD &D8TDVdDYDRDJDDKDdDy"DDD2&DeDDDZD D%D; D`LD֨DDzD$DDDDBVDDGID'DnDxDGD;DDD'<DD D˕DʼnDx-DԖD[DDDDuND DB8D6iDxDDWD}DDlD{DeD2FDVDDH(Do1D-DFDyD:KD&Db7DwDZRD}DD8DDrDNDk Dy1D|DDEDDlTDuDzDaDD9D&oD'D2Dn D]DD\D'yDDDٝDDxD=qD%D dDۃDDDDYDwDgDDDDDDaDkD<D lDD=Du|DϭD/DDzDj~D:<DDVDFDDDtnDiDFDDޔDzDDABDDVDrDϵDD{WD DyDD;DDDMD8D%DD;D'CD8~D-DgRD1DsSD"D:DKDtDeD}Dh DDDD^ DD$ DD4 DZ D[ Du5 DׇDD DDgD^mDDD'DD DT{ D@ De% D D_ DMDӥDe DgD?JDJ D D: DD DD}DK DDi2 DHbD9_D[EDT}D٣ Dݖ D6Df DD D8DK D D=D DL Dr DZ DDDB D~ D1D^D7 DLDtDD D= D D D8D~D D|Dc DrHDfDvDD# D/DDD; DeDA D%D DT DDSDDLD,> DCq D DODU DLDhD,D;D:D D5 D*DE D?DD) DD`D,YD- Df# DR DD S DV DDD DR DrD D$ DL D!D&D D DI} DP D DDbNDX D DDzDhD DrDKDDD8FDD D *DDCDI^DDDDDSD,DDBkDPDDDҽDD=D2DRDDzvDDDDD;DDDDyDDsDDD7DDaGDjDDDDD7D/tDvDfD=D~DJDR3DQDDv3DvD2Dl!D~D9WDoDpD"DuD(DhDT|DMDeDSDv DDDVDgDYDRPDDzVDGDBDDWDD#DYRD7DDݥDDDND`D\D DDD;D=hD!DD)D$TDDyDDDsDDDjDDDyD^DyDe?D5'DDD6[DmDAD DDjPDL#D6DwDZDDnDBrD2*DD D3DDD^DDDYDDADyDDcDgDGD!DCHDDtDMDg,DDD6wD D$DD`DjqDVgD)DD "DDID9fDpD,DDYDvDD >D>DxDDȆDD.DJ[DDA D+DD*DD:PDZDXDBDDD|DDheDёDD]DDVDyDD~DDBUD=D EDSD#DtDD dDD DDDDDD8DDDDD|D;0DD*.DDDۡDUDD2D=hDDD8DtDkDrDDDqDID DYDU% DͯDDuDSD D6 D9D D DI DuD R DL D&WD Dd# DD Do&DDr DGLDbD D4D DIDD D$v DD DAD\ D DG-D Da$ D(^ D Da0D DD DM DzD1GD&_ D~ D`b DD3xDB D Dv Da DMDYDW Dϑ D D_DH8 D9 DDx+D DD DE5 DbD D=DeDaD'qDE3DoDDD-DD\D D% DD99D# Dj D#DRDj D8Dٳ DhD_D*DcD/zDj DD {DDfD3 D D= DbDɧ DD D3D D^5DD D D \ D|D*' Df D=jD DDfDrDDDC D]D D DN D?9DDD"DsDg;D-D+ D DVDDDDjD9DDDt+DDlODUDDTD[D'DD DoDzDDMDD D1DۚDaDiuDiDDDDLDytDD DvzDxDD%ND3DD#DyDuDfDD<DpDD;DTDEDfDDjND<DqD?DD+D@D$D/Da?D4D] DZMDRDmDrD8D#DDrDDHYDD\D}D/DDD DtDD(DDD4iD"DDJDDQD/DKDDD1DLDlPDuDDrEDDiD%DO?DwDKDDDDvD4:DaDDDhDDDDiDDDD\DDQDpDăDDDDDD_5D)DmBDEDDDD9DjIDDQDD!D|DWDhDVDDDuD 4DuDfDAuDDgIDW1DtDD D@DDiDPD&uDID/DuDdDwDmADDDoDfDD%DŲDtD׎Dt^D/D۪DύDSD/DrD DDQD7DkD@=DՂDDDYD>DsD,DDDD[DDDDDBD]}Dd D!DVDQDDDDsDIDmD#D.BDD?DDD'DfDD}DΆDtD"DHDDBDsDӈDD D*D D 5 Dc. Do DԬ D!D2D D;Di DDDD D`D'#DD?DۜDzD DDlD D$Dt D D DD D6DUDwD DD! D DDD( D\ D|D DcL DTD DD D'n D* D#R DJ Dv DY DqJDn D\ D7nDUD)DnW DoDFi DJ D? DjD D9 D0 D* DDDIJ DD:V D DD- DS$ D DXB D DnD-DďD=mDMDD}DDYDzDoDDDD3DcDd#DD{DuDDDD~DD%hDmDc%D[DDgDADDDوDDDFID9DKDDhD%D<D&DDp]D^@DiDaDDDƕDD,D+lD+DD'DDDDD_DDDXD1QDD,DGDD{iD$DDEDDDDDDՂD6DxDD MDl#D8DD8D+D0DDђDDDcDwDiDwD9DDQD]D|DSDDDXDPDDsD6DWDDD DmD3DD^DsDqD=DDDID" D8DR?DyDDbDDDDDD|DvD|DsDiD$D>DuDDHDDkD*cD@D+DD _D@DNDUDDDDD~DDD@D$DD@DD>xDD0D(DؼDDYD*DDD DcjDDYD[DDZDU0D)DO3D!DxDDDLDָDxDDMmD-D DD[D D%D|DD0DDaDDXD6D*DlDDIND DDD DfDDqDDmDtDi D,D^6D!DkDcD0DDGDDD%D:DDA_D*DD"DD6DDDPDڬDDD DfDDKDPBD"DwDp:D+XDx'D;DDuD;0DD+EDRgD{ DU DDf DlD DdDd DDjDD: D{ D;DqD Db, DiDnf DD_D9 Dߺ D\ Dq\DD Dq`D D D5DDeDB@ DDK$ Dx#DED8SDr D!' DDA3D= DD6 DDvDPQD D-DDDSD2 Djd D{ DKDaDDD(} Dkr DYDu DD"DDDSD D!DD D D D DHDxD D DiLD5D$D DL DD DDէDDDDr D D D D|DDE DWDD DaD! D$xDvD9 D. D  D{DDp D}* D D D Db D^ DD*S D&WD  D<DUD DP] DDD<D D Dm DD7eD DhDKgDYDD8DD`DnDoD{D^[DhDD3D(DLDtD(D DDJDDDDbDsDNYD D@DD%UDD^DD}D( D0D<D7DD]}DNDD!D5DDbD5DIDD"9D! DDMDqDHDDD1DTD!JD֎DD]D\DD>DdD*D5+DTDD2D=DDPoD2mD$pDoD DnDD7iDzDDNDD)D$DDgDDgDNDvrD/DhDDZDDDwD[DvjDxD\DDRD8sDD OD0DsDdzDTDPdDDDD)DqD=DhD"DkDoDbD5DTDD DSD,DxD1D}D.aDļDXD#DD(DKD.DDFDfD(D9DxtDsD"DCDpDDDBD6DMDDDDDDDlDDDCDDgD;?DMD|DDD7DDBDD2D3D<D%DD"dDplDq%DLDsDDiDD\DDD_DDDDpDD?DDD)DVDBDUDRDDDDa"DD!CDZDDDDDD.DZDDDnDDwQD.D =DDXYDDZD DGD QDDDSD D4DDͩDfDUD>DWDaD:NDDHDDvDgDDDDD%DcDD2D""D:XD"DXDDDx D:GD Dԟ D|G D]D|D D D%DD DA( DlDW$D@B Du D D1D Dz~ D$Dr DMDp Di DDD?DD&DtD3 D>D`+D DDD$D) D& DDDŷD DJ7D3VDPtDF DDD DT0Dj Dt D7D9 Dp` DXDDD6DN D DBb"D`DDގD DHXDGDkDD D" D Dm;D^ D@D%! DDOD D_ZDFD>Dz4D'DX D D:Dlb DlD D`D D1 Ds DD8dD DRVDuDID DX D@CD D- DD. DD.DDTDa De DƱ DPD#DD/{ DD: D5 DF D4Du D DDD DiDcDCLD4ND6DٍD4DDWDdD`D7DDDo=DDGDIQDVD͵DqDDBDַDDvDߘD&DvgDD&D+DUDXDRDDUGDDDDxDD>DID7D8DDbDzDkD\DDmDGD DDDnD}DjD]mDB&DD87DDDt*DDl DDDDDH@DJ0DSDDDD>D<DyD\rDTDDDDhDDDDD DDDD DDhDeD>DDmDD?DDDhDTDXDhD{Dy8DdDDDD[DcDaDD DD<(DD'DDD[D<D:DDHDDDD8DuDDZD^DUD NDP DQD\DD+<DDDQ5D DJD;DD7HD2DD݀DvD_ DD]D\DkD0DDDgDDDGDDaDBD-DmD-ADWDxDJD%D >DDDDz\DRDD!@DDD8MD@D.DDCD0CDDDDesDD88D>>DDXD#DD)DDDD^pDDND&D^GD DDnODHD{DD}DD8DTGDXEDDD:@DkDkDNDD>D:DHzDDoDQFDDD.iDEDD,MDzD/ADDDDDD>D:DhDAD)D3aD~DNDVDLDD߉DD6 Dg_ D>DDCDD}f DD DD@D Dm DlZ D D"D{ DݻDr<D@D DADD&^D[ D8V D)D@}D*DDD+D1 D DDB DtF D/ D¿ DUDDD D DA Da D > DxDn D* D DD D@2DMDi DJ}DKD$ DRq DE DD_DDB DDֻDDxDDz D DIDD Dh DVD( DD^ D[4D DD; DzDw D0* D D_ DDx D>[ DT D:D Drn D DD D D DE D DD Dm` D+D D DCD` D DD` D DO D>D DhDODxrDf[ DXDD0DNbDDӠD2DDJ Dp DDCDDDBDDEkDXiDLDDDMDoIDΈD]DyDyDQ?D6DDDODɦD8DWDڟDD!DWD>D DDDDD D~nDD-DD}4DDY@DMDDxXDD/DDI-DDDDE$D9@DDDXDD@DFD*D8D;DDyD!`D0DJzDSDDZDQDVDDEDD3D(DDDD[NDD{DDaVDKDqDQ[DɁDAD3DD!Di#DLDcpDqD_DD%PDAD!D"KDMDvDD/DDmDDD3D@DJD DDKDDE DDsD DDDD7D'DkDQDD6DDD`DDDSigima-1.1.1/sigima/data/tests/image_formats/coordinated_text/000077500000000000000000000000001514013333200244165ustar00rootroot00000000000000Sigima-1.1.1/sigima/data/tests/image_formats/coordinated_text/complex_image.txt000066400000000000000000030327651514013333200300100ustar00rootroot00000000000000# Created on 2020-12-03 09:35:32.835292 # By Username # Using matrislib 3.2.0 # nx : 100 # ny : 100 # X : xlabel (xunit) # Y : ylabel (yunit) # Zre : Real(zlabel) (zunit) # Zim : Imaginary(zlabel) (zunit) # Zre Error (zunit) # Zim Error (zunit) -5.000000e+00 -5.000000e+00 3.678795e-01 3.678795e-01 1.839397e-01 -3.678795e-01 -4.900000e+00 -5.000000e+00 3.752360e-01 3.752360e-01 1.876180e-01 -3.752360e-01 -4.800000e+00 -5.000000e+00 3.825867e-01 3.825867e-01 1.912933e-01 -3.825867e-01 -4.700000e+00 -5.000000e+00 3.899254e-01 3.899254e-01 1.949627e-01 -3.899254e-01 -4.600000e+00 -5.000000e+00 3.972458e-01 3.972458e-01 1.986229e-01 -3.972458e-01 -4.500000e+00 -5.000000e+00 4.045419e-01 4.045419e-01 2.022710e-01 -4.045419e-01 -4.400000e+00 -5.000000e+00 4.118072e-01 4.118072e-01 2.059036e-01 -4.118072e-01 -4.300000e+00 -5.000000e+00 4.190353e-01 4.190353e-01 2.095177e-01 -4.190353e-01 -4.200000e+00 -5.000000e+00 4.262199e-01 4.262199e-01 2.131099e-01 -4.262199e-01 -4.100000e+00 -5.000000e+00 4.333541e-01 4.333541e-01 2.166771e-01 -4.333541e-01 -4.000000e+00 -5.000000e+00 4.404316e-01 4.404316e-01 2.202158e-01 -4.404316e-01 -3.900000e+00 -5.000000e+00 4.474457e-01 4.474457e-01 2.237229e-01 -4.474457e-01 -3.800000e+00 -5.000000e+00 4.543897e-01 4.543897e-01 2.271949e-01 -4.543897e-01 -3.700000e+00 -5.000000e+00 4.612570e-01 4.612570e-01 2.306285e-01 -4.612570e-01 -3.600000e+00 -5.000000e+00 4.680407e-01 4.680407e-01 2.340204e-01 -4.680407e-01 -3.500000e+00 -5.000000e+00 4.747343e-01 4.747343e-01 2.373672e-01 -4.747343e-01 -3.400000e+00 -5.000000e+00 4.813311e-01 4.813311e-01 2.406655e-01 -4.813311e-01 -3.300000e+00 -5.000000e+00 4.878243e-01 4.878243e-01 2.439122e-01 -4.878243e-01 -3.200000e+00 -5.000000e+00 4.942074e-01 4.942074e-01 2.471037e-01 -4.942074e-01 -3.100000e+00 -5.000000e+00 5.004738e-01 5.004738e-01 2.502369e-01 -5.004738e-01 -3.000000e+00 -5.000000e+00 5.066170e-01 5.066170e-01 2.533085e-01 -5.066170e-01 -2.900000e+00 -5.000000e+00 5.126305e-01 5.126305e-01 2.563152e-01 -5.126305e-01 -2.800000e+00 -5.000000e+00 5.185079e-01 5.185079e-01 2.592539e-01 -5.185079e-01 -2.700000e+00 -5.000000e+00 5.242430e-01 5.242430e-01 2.621215e-01 -5.242430e-01 -2.600000e+00 -5.000000e+00 5.298295e-01 5.298295e-01 2.649148e-01 -5.298295e-01 -2.500000e+00 -5.000000e+00 5.352615e-01 5.352615e-01 2.676307e-01 -5.352615e-01 -2.400000e+00 -5.000000e+00 5.405328e-01 5.405328e-01 2.702664e-01 -5.405328e-01 -2.300000e+00 -5.000000e+00 5.456377e-01 5.456377e-01 2.728189e-01 -5.456377e-01 -2.200000e+00 -5.000000e+00 5.505707e-01 5.505707e-01 2.752853e-01 -5.505707e-01 -2.100000e+00 -5.000000e+00 5.553260e-01 5.553260e-01 2.776630e-01 -5.553260e-01 -2.000000e+00 -5.000000e+00 5.598984e-01 5.598984e-01 2.799492e-01 -5.598984e-01 -1.900000e+00 -5.000000e+00 5.642827e-01 5.642827e-01 2.821413e-01 -5.642827e-01 -1.800000e+00 -5.000000e+00 5.684738e-01 5.684738e-01 2.842369e-01 -5.684738e-01 -1.700000e+00 -5.000000e+00 5.724671e-01 5.724671e-01 2.862335e-01 -5.724671e-01 -1.600000e+00 -5.000000e+00 5.762579e-01 5.762579e-01 2.881289e-01 -5.762579e-01 -1.500000e+00 -5.000000e+00 5.798418e-01 5.798418e-01 2.899209e-01 -5.798418e-01 -1.400000e+00 -5.000000e+00 5.832146e-01 5.832146e-01 2.916073e-01 -5.832146e-01 -1.300000e+00 -5.000000e+00 5.863725e-01 5.863725e-01 2.931862e-01 -5.863725e-01 -1.200000e+00 -5.000000e+00 5.893117e-01 5.893117e-01 2.946559e-01 -5.893117e-01 -1.100000e+00 -5.000000e+00 5.920288e-01 5.920288e-01 2.960144e-01 -5.920288e-01 -1.000000e+00 -5.000000e+00 5.945206e-01 5.945206e-01 2.972603e-01 -5.945206e-01 -9.000000e-01 -5.000000e+00 5.967840e-01 5.967840e-01 2.983920e-01 -5.967840e-01 -8.000000e-01 -5.000000e+00 5.988166e-01 5.988166e-01 2.994083e-01 -5.988166e-01 -7.000000e-01 -5.000000e+00 6.006157e-01 6.006157e-01 3.003078e-01 -6.006157e-01 -6.000000e-01 -5.000000e+00 6.021793e-01 6.021793e-01 3.010897e-01 -6.021793e-01 -5.000000e-01 -5.000000e+00 6.035056e-01 6.035056e-01 3.017528e-01 -6.035056e-01 -4.000000e-01 -5.000000e+00 6.045929e-01 6.045929e-01 3.022964e-01 -6.045929e-01 -3.000000e-01 -5.000000e+00 6.054399e-01 6.054399e-01 3.027200e-01 -6.054399e-01 -2.000000e-01 -5.000000e+00 6.060456e-01 6.060456e-01 3.030228e-01 -6.060456e-01 -1.000000e-01 -5.000000e+00 6.064094e-01 6.064094e-01 3.032047e-01 -6.064094e-01 0.000000e+00 -5.000000e+00 6.065307e-01 6.065307e-01 3.032653e-01 -6.065307e-01 1.000000e-01 -5.000000e+00 6.064094e-01 6.064094e-01 3.032047e-01 -6.064094e-01 2.000000e-01 -5.000000e+00 6.060456e-01 6.060456e-01 3.030228e-01 -6.060456e-01 3.000000e-01 -5.000000e+00 6.054399e-01 6.054399e-01 3.027200e-01 -6.054399e-01 4.000000e-01 -5.000000e+00 6.045929e-01 6.045929e-01 3.022964e-01 -6.045929e-01 5.000000e-01 -5.000000e+00 6.035056e-01 6.035056e-01 3.017528e-01 -6.035056e-01 6.000000e-01 -5.000000e+00 6.021793e-01 6.021793e-01 3.010897e-01 -6.021793e-01 7.000000e-01 -5.000000e+00 6.006157e-01 6.006157e-01 3.003078e-01 -6.006157e-01 8.000000e-01 -5.000000e+00 5.988166e-01 5.988166e-01 2.994083e-01 -5.988166e-01 9.000000e-01 -5.000000e+00 5.967840e-01 5.967840e-01 2.983920e-01 -5.967840e-01 1.000000e+00 -5.000000e+00 5.945206e-01 5.945206e-01 2.972603e-01 -5.945206e-01 1.100000e+00 -5.000000e+00 5.920288e-01 5.920288e-01 2.960144e-01 -5.920288e-01 1.200000e+00 -5.000000e+00 5.893117e-01 5.893117e-01 2.946559e-01 -5.893117e-01 1.300000e+00 -5.000000e+00 5.863725e-01 5.863725e-01 2.931862e-01 -5.863725e-01 1.400000e+00 -5.000000e+00 5.832146e-01 5.832146e-01 2.916073e-01 -5.832146e-01 1.500000e+00 -5.000000e+00 5.798418e-01 5.798418e-01 2.899209e-01 -5.798418e-01 1.600000e+00 -5.000000e+00 5.762579e-01 5.762579e-01 2.881289e-01 -5.762579e-01 1.700000e+00 -5.000000e+00 5.724671e-01 5.724671e-01 2.862335e-01 -5.724671e-01 1.800000e+00 -5.000000e+00 5.684738e-01 5.684738e-01 2.842369e-01 -5.684738e-01 1.900000e+00 -5.000000e+00 5.642827e-01 5.642827e-01 2.821413e-01 -5.642827e-01 2.000000e+00 -5.000000e+00 5.598984e-01 5.598984e-01 2.799492e-01 -5.598984e-01 2.100000e+00 -5.000000e+00 5.553260e-01 5.553260e-01 2.776630e-01 -5.553260e-01 2.200000e+00 -5.000000e+00 5.505707e-01 5.505707e-01 2.752853e-01 -5.505707e-01 2.300000e+00 -5.000000e+00 5.456377e-01 5.456377e-01 2.728189e-01 -5.456377e-01 2.400000e+00 -5.000000e+00 5.405328e-01 5.405328e-01 2.702664e-01 -5.405328e-01 2.500000e+00 -5.000000e+00 5.352615e-01 5.352615e-01 2.676307e-01 -5.352615e-01 2.600000e+00 -5.000000e+00 5.298295e-01 5.298295e-01 2.649148e-01 -5.298295e-01 2.700000e+00 -5.000000e+00 5.242430e-01 5.242430e-01 2.621215e-01 -5.242430e-01 2.800000e+00 -5.000000e+00 5.185079e-01 5.185079e-01 2.592539e-01 -5.185079e-01 2.900000e+00 -5.000000e+00 5.126305e-01 5.126305e-01 2.563152e-01 -5.126305e-01 3.000000e+00 -5.000000e+00 5.066170e-01 5.066170e-01 2.533085e-01 -5.066170e-01 3.100000e+00 -5.000000e+00 5.004738e-01 5.004738e-01 2.502369e-01 -5.004738e-01 3.200000e+00 -5.000000e+00 4.942074e-01 4.942074e-01 2.471037e-01 -4.942074e-01 3.300000e+00 -5.000000e+00 4.878243e-01 4.878243e-01 2.439122e-01 -4.878243e-01 3.400000e+00 -5.000000e+00 4.813311e-01 4.813311e-01 2.406655e-01 -4.813311e-01 3.500000e+00 -5.000000e+00 4.747343e-01 4.747343e-01 2.373672e-01 -4.747343e-01 3.600000e+00 -5.000000e+00 4.680407e-01 4.680407e-01 2.340204e-01 -4.680407e-01 3.700000e+00 -5.000000e+00 4.612570e-01 4.612570e-01 2.306285e-01 -4.612570e-01 3.800000e+00 -5.000000e+00 4.543897e-01 4.543897e-01 2.271949e-01 -4.543897e-01 3.900000e+00 -5.000000e+00 4.474457e-01 4.474457e-01 2.237229e-01 -4.474457e-01 4.000000e+00 -5.000000e+00 4.404316e-01 4.404316e-01 2.202158e-01 -4.404316e-01 4.100000e+00 -5.000000e+00 4.333541e-01 4.333541e-01 2.166771e-01 -4.333541e-01 4.200000e+00 -5.000000e+00 4.262199e-01 4.262199e-01 2.131099e-01 -4.262199e-01 4.300000e+00 -5.000000e+00 4.190353e-01 4.190353e-01 2.095177e-01 -4.190353e-01 4.400000e+00 -5.000000e+00 4.118072e-01 4.118072e-01 2.059036e-01 -4.118072e-01 4.500000e+00 -5.000000e+00 4.045419e-01 4.045419e-01 2.022710e-01 -4.045419e-01 4.600000e+00 -5.000000e+00 3.972458e-01 3.972458e-01 1.986229e-01 -3.972458e-01 4.700000e+00 -5.000000e+00 3.899254e-01 3.899254e-01 1.949627e-01 -3.899254e-01 4.800000e+00 -5.000000e+00 3.825867e-01 3.825867e-01 1.912933e-01 -3.825867e-01 4.900000e+00 -5.000000e+00 3.752360e-01 3.752360e-01 1.876180e-01 -3.752360e-01 -5.000000e+00 -4.900000e+00 3.752360e-01 3.752360e-01 1.876180e-01 -3.752360e-01 -4.900000e+00 -4.900000e+00 3.827398e-01 3.827398e-01 1.913699e-01 -3.827398e-01 -4.800000e+00 -4.900000e+00 3.902374e-01 3.902374e-01 1.951187e-01 -3.902374e-01 -4.700000e+00 -4.900000e+00 3.977228e-01 3.977228e-01 1.988614e-01 -3.977228e-01 -4.600000e+00 -4.900000e+00 4.051897e-01 4.051897e-01 2.025948e-01 -4.051897e-01 -4.500000e+00 -4.900000e+00 4.126316e-01 4.126316e-01 2.063158e-01 -4.126316e-01 -4.400000e+00 -4.900000e+00 4.200422e-01 4.200422e-01 2.100211e-01 -4.200422e-01 -4.300000e+00 -4.900000e+00 4.274149e-01 4.274149e-01 2.137075e-01 -4.274149e-01 -4.200000e+00 -4.900000e+00 4.347431e-01 4.347431e-01 2.173716e-01 -4.347431e-01 -4.100000e+00 -4.900000e+00 4.420200e-01 4.420200e-01 2.210100e-01 -4.420200e-01 -4.000000e+00 -4.900000e+00 4.492391e-01 4.492391e-01 2.246195e-01 -4.492391e-01 -3.900000e+00 -4.900000e+00 4.563934e-01 4.563934e-01 2.281967e-01 -4.563934e-01 -3.800000e+00 -4.900000e+00 4.634763e-01 4.634763e-01 2.317382e-01 -4.634763e-01 -3.700000e+00 -4.900000e+00 4.704808e-01 4.704808e-01 2.352404e-01 -4.704808e-01 -3.600000e+00 -4.900000e+00 4.774002e-01 4.774002e-01 2.387001e-01 -4.774002e-01 -3.500000e+00 -4.900000e+00 4.842277e-01 4.842277e-01 2.421139e-01 -4.842277e-01 -3.400000e+00 -4.900000e+00 4.909564e-01 4.909564e-01 2.454782e-01 -4.909564e-01 -3.300000e+00 -4.900000e+00 4.975795e-01 4.975795e-01 2.487897e-01 -4.975795e-01 -3.200000e+00 -4.900000e+00 5.040902e-01 5.040902e-01 2.520451e-01 -5.040902e-01 -3.100000e+00 -4.900000e+00 5.104820e-01 5.104820e-01 2.552410e-01 -5.104820e-01 -3.000000e+00 -4.900000e+00 5.167480e-01 5.167480e-01 2.583740e-01 -5.167480e-01 -2.900000e+00 -4.900000e+00 5.228817e-01 5.228817e-01 2.614408e-01 -5.228817e-01 -2.800000e+00 -4.900000e+00 5.288767e-01 5.288767e-01 2.644383e-01 -5.288767e-01 -2.700000e+00 -4.900000e+00 5.347264e-01 5.347264e-01 2.673632e-01 -5.347264e-01 -2.600000e+00 -4.900000e+00 5.404246e-01 5.404246e-01 2.702123e-01 -5.404246e-01 -2.500000e+00 -4.900000e+00 5.459652e-01 5.459652e-01 2.729826e-01 -5.459652e-01 -2.400000e+00 -4.900000e+00 5.513420e-01 5.513420e-01 2.756710e-01 -5.513420e-01 -2.300000e+00 -4.900000e+00 5.565490e-01 5.565490e-01 2.782745e-01 -5.565490e-01 -2.200000e+00 -4.900000e+00 5.615806e-01 5.615806e-01 2.807903e-01 -5.615806e-01 -2.100000e+00 -4.900000e+00 5.664310e-01 5.664310e-01 2.832155e-01 -5.664310e-01 -2.000000e+00 -4.900000e+00 5.710948e-01 5.710948e-01 2.855474e-01 -5.710948e-01 -1.900000e+00 -4.900000e+00 5.755668e-01 5.755668e-01 2.877834e-01 -5.755668e-01 -1.800000e+00 -4.900000e+00 5.798418e-01 5.798418e-01 2.899209e-01 -5.798418e-01 -1.700000e+00 -4.900000e+00 5.839149e-01 5.839149e-01 2.919574e-01 -5.839149e-01 -1.600000e+00 -4.900000e+00 5.877815e-01 5.877815e-01 2.938907e-01 -5.877815e-01 -1.500000e+00 -4.900000e+00 5.914370e-01 5.914370e-01 2.957185e-01 -5.914370e-01 -1.400000e+00 -4.900000e+00 5.948774e-01 5.948774e-01 2.974387e-01 -5.948774e-01 -1.300000e+00 -4.900000e+00 5.980984e-01 5.980984e-01 2.990492e-01 -5.980984e-01 -1.200000e+00 -4.900000e+00 6.010964e-01 6.010964e-01 3.005482e-01 -6.010964e-01 -1.100000e+00 -4.900000e+00 6.038678e-01 6.038678e-01 3.019339e-01 -6.038678e-01 -1.000000e+00 -4.900000e+00 6.064094e-01 6.064094e-01 3.032047e-01 -6.064094e-01 -9.000000e-01 -4.900000e+00 6.087181e-01 6.087181e-01 3.043590e-01 -6.087181e-01 -8.000000e-01 -4.900000e+00 6.107913e-01 6.107913e-01 3.053956e-01 -6.107913e-01 -7.000000e-01 -4.900000e+00 6.126264e-01 6.126264e-01 3.063132e-01 -6.126264e-01 -6.000000e-01 -4.900000e+00 6.142213e-01 6.142213e-01 3.071106e-01 -6.142213e-01 -5.000000e-01 -4.900000e+00 6.155741e-01 6.155741e-01 3.077870e-01 -6.155741e-01 -4.000000e-01 -4.900000e+00 6.166831e-01 6.166831e-01 3.083415e-01 -6.166831e-01 -3.000000e-01 -4.900000e+00 6.175470e-01 6.175470e-01 3.087735e-01 -6.175470e-01 -2.000000e-01 -4.900000e+00 6.181649e-01 6.181649e-01 3.090824e-01 -6.181649e-01 -1.000000e-01 -4.900000e+00 6.185359e-01 6.185359e-01 3.092680e-01 -6.185359e-01 0.000000e+00 -4.900000e+00 6.186596e-01 6.186596e-01 3.093298e-01 -6.186596e-01 1.000000e-01 -4.900000e+00 6.185359e-01 6.185359e-01 3.092680e-01 -6.185359e-01 2.000000e-01 -4.900000e+00 6.181649e-01 6.181649e-01 3.090824e-01 -6.181649e-01 3.000000e-01 -4.900000e+00 6.175470e-01 6.175470e-01 3.087735e-01 -6.175470e-01 4.000000e-01 -4.900000e+00 6.166831e-01 6.166831e-01 3.083415e-01 -6.166831e-01 5.000000e-01 -4.900000e+00 6.155741e-01 6.155741e-01 3.077870e-01 -6.155741e-01 6.000000e-01 -4.900000e+00 6.142213e-01 6.142213e-01 3.071106e-01 -6.142213e-01 7.000000e-01 -4.900000e+00 6.126264e-01 6.126264e-01 3.063132e-01 -6.126264e-01 8.000000e-01 -4.900000e+00 6.107913e-01 6.107913e-01 3.053956e-01 -6.107913e-01 9.000000e-01 -4.900000e+00 6.087181e-01 6.087181e-01 3.043590e-01 -6.087181e-01 1.000000e+00 -4.900000e+00 6.064094e-01 6.064094e-01 3.032047e-01 -6.064094e-01 1.100000e+00 -4.900000e+00 6.038678e-01 6.038678e-01 3.019339e-01 -6.038678e-01 1.200000e+00 -4.900000e+00 6.010964e-01 6.010964e-01 3.005482e-01 -6.010964e-01 1.300000e+00 -4.900000e+00 5.980984e-01 5.980984e-01 2.990492e-01 -5.980984e-01 1.400000e+00 -4.900000e+00 5.948774e-01 5.948774e-01 2.974387e-01 -5.948774e-01 1.500000e+00 -4.900000e+00 5.914370e-01 5.914370e-01 2.957185e-01 -5.914370e-01 1.600000e+00 -4.900000e+00 5.877815e-01 5.877815e-01 2.938907e-01 -5.877815e-01 1.700000e+00 -4.900000e+00 5.839149e-01 5.839149e-01 2.919574e-01 -5.839149e-01 1.800000e+00 -4.900000e+00 5.798418e-01 5.798418e-01 2.899209e-01 -5.798418e-01 1.900000e+00 -4.900000e+00 5.755668e-01 5.755668e-01 2.877834e-01 -5.755668e-01 2.000000e+00 -4.900000e+00 5.710948e-01 5.710948e-01 2.855474e-01 -5.710948e-01 2.100000e+00 -4.900000e+00 5.664310e-01 5.664310e-01 2.832155e-01 -5.664310e-01 2.200000e+00 -4.900000e+00 5.615806e-01 5.615806e-01 2.807903e-01 -5.615806e-01 2.300000e+00 -4.900000e+00 5.565490e-01 5.565490e-01 2.782745e-01 -5.565490e-01 2.400000e+00 -4.900000e+00 5.513420e-01 5.513420e-01 2.756710e-01 -5.513420e-01 2.500000e+00 -4.900000e+00 5.459652e-01 5.459652e-01 2.729826e-01 -5.459652e-01 2.600000e+00 -4.900000e+00 5.404246e-01 5.404246e-01 2.702123e-01 -5.404246e-01 2.700000e+00 -4.900000e+00 5.347264e-01 5.347264e-01 2.673632e-01 -5.347264e-01 2.800000e+00 -4.900000e+00 5.288767e-01 5.288767e-01 2.644383e-01 -5.288767e-01 2.900000e+00 -4.900000e+00 5.228817e-01 5.228817e-01 2.614408e-01 -5.228817e-01 3.000000e+00 -4.900000e+00 5.167480e-01 5.167480e-01 2.583740e-01 -5.167480e-01 3.100000e+00 -4.900000e+00 5.104820e-01 5.104820e-01 2.552410e-01 -5.104820e-01 3.200000e+00 -4.900000e+00 5.040902e-01 5.040902e-01 2.520451e-01 -5.040902e-01 3.300000e+00 -4.900000e+00 4.975795e-01 4.975795e-01 2.487897e-01 -4.975795e-01 3.400000e+00 -4.900000e+00 4.909564e-01 4.909564e-01 2.454782e-01 -4.909564e-01 3.500000e+00 -4.900000e+00 4.842277e-01 4.842277e-01 2.421139e-01 -4.842277e-01 3.600000e+00 -4.900000e+00 4.774002e-01 4.774002e-01 2.387001e-01 -4.774002e-01 3.700000e+00 -4.900000e+00 4.704808e-01 4.704808e-01 2.352404e-01 -4.704808e-01 3.800000e+00 -4.900000e+00 4.634763e-01 4.634763e-01 2.317382e-01 -4.634763e-01 3.900000e+00 -4.900000e+00 4.563934e-01 4.563934e-01 2.281967e-01 -4.563934e-01 4.000000e+00 -4.900000e+00 4.492391e-01 4.492391e-01 2.246195e-01 -4.492391e-01 4.100000e+00 -4.900000e+00 4.420200e-01 4.420200e-01 2.210100e-01 -4.420200e-01 4.200000e+00 -4.900000e+00 4.347431e-01 4.347431e-01 2.173716e-01 -4.347431e-01 4.300000e+00 -4.900000e+00 4.274149e-01 4.274149e-01 2.137075e-01 -4.274149e-01 4.400000e+00 -4.900000e+00 4.200422e-01 4.200422e-01 2.100211e-01 -4.200422e-01 4.500000e+00 -4.900000e+00 4.126316e-01 4.126316e-01 2.063158e-01 -4.126316e-01 4.600000e+00 -4.900000e+00 4.051897e-01 4.051897e-01 2.025948e-01 -4.051897e-01 4.700000e+00 -4.900000e+00 3.977228e-01 3.977228e-01 1.988614e-01 -3.977228e-01 4.800000e+00 -4.900000e+00 3.902374e-01 3.902374e-01 1.951187e-01 -3.902374e-01 4.900000e+00 -4.900000e+00 3.827398e-01 3.827398e-01 1.913699e-01 -3.827398e-01 -5.000000e+00 -4.800000e+00 3.825867e-01 3.825867e-01 1.912933e-01 -3.825867e-01 -4.900000e+00 -4.800000e+00 3.902374e-01 3.902374e-01 1.951187e-01 -3.902374e-01 -4.800000e+00 -4.800000e+00 3.978819e-01 3.978819e-01 1.989409e-01 -3.978819e-01 -4.700000e+00 -4.800000e+00 4.055140e-01 4.055140e-01 2.027570e-01 -4.055140e-01 -4.600000e+00 -4.800000e+00 4.131271e-01 4.131271e-01 2.065636e-01 -4.131271e-01 -4.500000e+00 -4.800000e+00 4.207148e-01 4.207148e-01 2.103574e-01 -4.207148e-01 -4.400000e+00 -4.800000e+00 4.282706e-01 4.282706e-01 2.141353e-01 -4.282706e-01 -4.300000e+00 -4.800000e+00 4.357877e-01 4.357877e-01 2.178939e-01 -4.357877e-01 -4.200000e+00 -4.800000e+00 4.432594e-01 4.432594e-01 2.216297e-01 -4.432594e-01 -4.100000e+00 -4.800000e+00 4.506789e-01 4.506789e-01 2.253395e-01 -4.506789e-01 -4.000000e+00 -4.800000e+00 4.580394e-01 4.580394e-01 2.290197e-01 -4.580394e-01 -3.900000e+00 -4.800000e+00 4.653339e-01 4.653339e-01 2.326670e-01 -4.653339e-01 -3.800000e+00 -4.800000e+00 4.725555e-01 4.725555e-01 2.362778e-01 -4.725555e-01 -3.700000e+00 -4.800000e+00 4.796973e-01 4.796973e-01 2.398486e-01 -4.796973e-01 -3.600000e+00 -4.800000e+00 4.867522e-01 4.867522e-01 2.433761e-01 -4.867522e-01 -3.500000e+00 -4.800000e+00 4.937134e-01 4.937134e-01 2.468567e-01 -4.937134e-01 -3.400000e+00 -4.800000e+00 5.005739e-01 5.005739e-01 2.502870e-01 -5.005739e-01 -3.300000e+00 -4.800000e+00 5.073267e-01 5.073267e-01 2.536634e-01 -5.073267e-01 -3.200000e+00 -4.800000e+00 5.139651e-01 5.139651e-01 2.569825e-01 -5.139651e-01 -3.100000e+00 -4.800000e+00 5.204820e-01 5.204820e-01 2.602410e-01 -5.204820e-01 -3.000000e+00 -4.800000e+00 5.268708e-01 5.268708e-01 2.634354e-01 -5.268708e-01 -2.900000e+00 -4.800000e+00 5.331246e-01 5.331246e-01 2.665623e-01 -5.331246e-01 -2.800000e+00 -4.800000e+00 5.392370e-01 5.392370e-01 2.696185e-01 -5.392370e-01 -2.700000e+00 -4.800000e+00 5.452014e-01 5.452014e-01 2.726007e-01 -5.452014e-01 -2.600000e+00 -4.800000e+00 5.510113e-01 5.510113e-01 2.755056e-01 -5.510113e-01 -2.500000e+00 -4.800000e+00 5.566604e-01 5.566604e-01 2.783302e-01 -5.566604e-01 -2.400000e+00 -4.800000e+00 5.621424e-01 5.621424e-01 2.810712e-01 -5.621424e-01 -2.300000e+00 -4.800000e+00 5.674515e-01 5.674515e-01 2.837257e-01 -5.674515e-01 -2.200000e+00 -4.800000e+00 5.725816e-01 5.725816e-01 2.862908e-01 -5.725816e-01 -2.100000e+00 -4.800000e+00 5.775270e-01 5.775270e-01 2.887635e-01 -5.775270e-01 -2.000000e+00 -4.800000e+00 5.822822e-01 5.822822e-01 2.911411e-01 -5.822822e-01 -1.900000e+00 -4.800000e+00 5.868418e-01 5.868418e-01 2.934209e-01 -5.868418e-01 -1.800000e+00 -4.800000e+00 5.912005e-01 5.912005e-01 2.956003e-01 -5.912005e-01 -1.700000e+00 -4.800000e+00 5.953534e-01 5.953534e-01 2.976767e-01 -5.953534e-01 -1.600000e+00 -4.800000e+00 5.992958e-01 5.992958e-01 2.996479e-01 -5.992958e-01 -1.500000e+00 -4.800000e+00 6.030229e-01 6.030229e-01 3.015115e-01 -6.030229e-01 -1.400000e+00 -4.800000e+00 6.065307e-01 6.065307e-01 3.032653e-01 -6.065307e-01 -1.300000e+00 -4.800000e+00 6.098148e-01 6.098148e-01 3.049074e-01 -6.098148e-01 -1.200000e+00 -4.800000e+00 6.128715e-01 6.128715e-01 3.064357e-01 -6.128715e-01 -1.100000e+00 -4.800000e+00 6.156972e-01 6.156972e-01 3.078486e-01 -6.156972e-01 -1.000000e+00 -4.800000e+00 6.182885e-01 6.182885e-01 3.091443e-01 -6.182885e-01 -9.000000e-01 -4.800000e+00 6.206425e-01 6.206425e-01 3.103212e-01 -6.206425e-01 -8.000000e-01 -4.800000e+00 6.227563e-01 6.227563e-01 3.113782e-01 -6.227563e-01 -7.000000e-01 -4.800000e+00 6.246274e-01 6.246274e-01 3.123137e-01 -6.246274e-01 -6.000000e-01 -4.800000e+00 6.262535e-01 6.262535e-01 3.131267e-01 -6.262535e-01 -5.000000e-01 -4.800000e+00 6.276328e-01 6.276328e-01 3.138164e-01 -6.276328e-01 -4.000000e-01 -4.800000e+00 6.287636e-01 6.287636e-01 3.143818e-01 -6.287636e-01 -3.000000e-01 -4.800000e+00 6.296445e-01 6.296445e-01 3.148222e-01 -6.296445e-01 -2.000000e-01 -4.800000e+00 6.302744e-01 6.302744e-01 3.151372e-01 -6.302744e-01 -1.000000e-01 -4.800000e+00 6.306527e-01 6.306527e-01 3.153263e-01 -6.306527e-01 0.000000e+00 -4.800000e+00 6.307788e-01 6.307788e-01 3.153894e-01 -6.307788e-01 1.000000e-01 -4.800000e+00 6.306527e-01 6.306527e-01 3.153263e-01 -6.306527e-01 2.000000e-01 -4.800000e+00 6.302744e-01 6.302744e-01 3.151372e-01 -6.302744e-01 3.000000e-01 -4.800000e+00 6.296445e-01 6.296445e-01 3.148222e-01 -6.296445e-01 4.000000e-01 -4.800000e+00 6.287636e-01 6.287636e-01 3.143818e-01 -6.287636e-01 5.000000e-01 -4.800000e+00 6.276328e-01 6.276328e-01 3.138164e-01 -6.276328e-01 6.000000e-01 -4.800000e+00 6.262535e-01 6.262535e-01 3.131267e-01 -6.262535e-01 7.000000e-01 -4.800000e+00 6.246274e-01 6.246274e-01 3.123137e-01 -6.246274e-01 8.000000e-01 -4.800000e+00 6.227563e-01 6.227563e-01 3.113782e-01 -6.227563e-01 9.000000e-01 -4.800000e+00 6.206425e-01 6.206425e-01 3.103212e-01 -6.206425e-01 1.000000e+00 -4.800000e+00 6.182885e-01 6.182885e-01 3.091443e-01 -6.182885e-01 1.100000e+00 -4.800000e+00 6.156972e-01 6.156972e-01 3.078486e-01 -6.156972e-01 1.200000e+00 -4.800000e+00 6.128715e-01 6.128715e-01 3.064357e-01 -6.128715e-01 1.300000e+00 -4.800000e+00 6.098148e-01 6.098148e-01 3.049074e-01 -6.098148e-01 1.400000e+00 -4.800000e+00 6.065307e-01 6.065307e-01 3.032653e-01 -6.065307e-01 1.500000e+00 -4.800000e+00 6.030229e-01 6.030229e-01 3.015115e-01 -6.030229e-01 1.600000e+00 -4.800000e+00 5.992958e-01 5.992958e-01 2.996479e-01 -5.992958e-01 1.700000e+00 -4.800000e+00 5.953534e-01 5.953534e-01 2.976767e-01 -5.953534e-01 1.800000e+00 -4.800000e+00 5.912005e-01 5.912005e-01 2.956003e-01 -5.912005e-01 1.900000e+00 -4.800000e+00 5.868418e-01 5.868418e-01 2.934209e-01 -5.868418e-01 2.000000e+00 -4.800000e+00 5.822822e-01 5.822822e-01 2.911411e-01 -5.822822e-01 2.100000e+00 -4.800000e+00 5.775270e-01 5.775270e-01 2.887635e-01 -5.775270e-01 2.200000e+00 -4.800000e+00 5.725816e-01 5.725816e-01 2.862908e-01 -5.725816e-01 2.300000e+00 -4.800000e+00 5.674515e-01 5.674515e-01 2.837257e-01 -5.674515e-01 2.400000e+00 -4.800000e+00 5.621424e-01 5.621424e-01 2.810712e-01 -5.621424e-01 2.500000e+00 -4.800000e+00 5.566604e-01 5.566604e-01 2.783302e-01 -5.566604e-01 2.600000e+00 -4.800000e+00 5.510113e-01 5.510113e-01 2.755056e-01 -5.510113e-01 2.700000e+00 -4.800000e+00 5.452014e-01 5.452014e-01 2.726007e-01 -5.452014e-01 2.800000e+00 -4.800000e+00 5.392370e-01 5.392370e-01 2.696185e-01 -5.392370e-01 2.900000e+00 -4.800000e+00 5.331246e-01 5.331246e-01 2.665623e-01 -5.331246e-01 3.000000e+00 -4.800000e+00 5.268708e-01 5.268708e-01 2.634354e-01 -5.268708e-01 3.100000e+00 -4.800000e+00 5.204820e-01 5.204820e-01 2.602410e-01 -5.204820e-01 3.200000e+00 -4.800000e+00 5.139651e-01 5.139651e-01 2.569825e-01 -5.139651e-01 3.300000e+00 -4.800000e+00 5.073267e-01 5.073267e-01 2.536634e-01 -5.073267e-01 3.400000e+00 -4.800000e+00 5.005739e-01 5.005739e-01 2.502870e-01 -5.005739e-01 3.500000e+00 -4.800000e+00 4.937134e-01 4.937134e-01 2.468567e-01 -4.937134e-01 3.600000e+00 -4.800000e+00 4.867522e-01 4.867522e-01 2.433761e-01 -4.867522e-01 3.700000e+00 -4.800000e+00 4.796973e-01 4.796973e-01 2.398486e-01 -4.796973e-01 3.800000e+00 -4.800000e+00 4.725555e-01 4.725555e-01 2.362778e-01 -4.725555e-01 3.900000e+00 -4.800000e+00 4.653339e-01 4.653339e-01 2.326670e-01 -4.653339e-01 4.000000e+00 -4.800000e+00 4.580394e-01 4.580394e-01 2.290197e-01 -4.580394e-01 4.100000e+00 -4.800000e+00 4.506789e-01 4.506789e-01 2.253395e-01 -4.506789e-01 4.200000e+00 -4.800000e+00 4.432594e-01 4.432594e-01 2.216297e-01 -4.432594e-01 4.300000e+00 -4.800000e+00 4.357877e-01 4.357877e-01 2.178939e-01 -4.357877e-01 4.400000e+00 -4.800000e+00 4.282706e-01 4.282706e-01 2.141353e-01 -4.282706e-01 4.500000e+00 -4.800000e+00 4.207148e-01 4.207148e-01 2.103574e-01 -4.207148e-01 4.600000e+00 -4.800000e+00 4.131271e-01 4.131271e-01 2.065636e-01 -4.131271e-01 4.700000e+00 -4.800000e+00 4.055140e-01 4.055140e-01 2.027570e-01 -4.055140e-01 4.800000e+00 -4.800000e+00 3.978819e-01 3.978819e-01 1.989409e-01 -3.978819e-01 4.900000e+00 -4.800000e+00 3.902374e-01 3.902374e-01 1.951187e-01 -3.902374e-01 -5.000000e+00 -4.700000e+00 3.899254e-01 3.899254e-01 1.949627e-01 -3.899254e-01 -4.900000e+00 -4.700000e+00 3.977228e-01 3.977228e-01 1.988614e-01 -3.977228e-01 -4.800000e+00 -4.700000e+00 4.055140e-01 4.055140e-01 2.027570e-01 -4.055140e-01 -4.700000e+00 -4.700000e+00 4.132924e-01 4.132924e-01 2.066462e-01 -4.132924e-01 -4.600000e+00 -4.700000e+00 4.210516e-01 4.210516e-01 2.105258e-01 -4.210516e-01 -4.500000e+00 -4.700000e+00 4.287849e-01 4.287849e-01 2.143924e-01 -4.287849e-01 -4.400000e+00 -4.700000e+00 4.364856e-01 4.364856e-01 2.182428e-01 -4.364856e-01 -4.300000e+00 -4.700000e+00 4.441469e-01 4.441469e-01 2.220734e-01 -4.441469e-01 -4.200000e+00 -4.700000e+00 4.517620e-01 4.517620e-01 2.258810e-01 -4.517620e-01 -4.100000e+00 -4.700000e+00 4.593238e-01 4.593238e-01 2.296619e-01 -4.593238e-01 -4.000000e+00 -4.700000e+00 4.668254e-01 4.668254e-01 2.334127e-01 -4.668254e-01 -3.900000e+00 -4.700000e+00 4.742598e-01 4.742598e-01 2.371299e-01 -4.742598e-01 -3.800000e+00 -4.700000e+00 4.816200e-01 4.816200e-01 2.408100e-01 -4.816200e-01 -3.700000e+00 -4.700000e+00 4.888987e-01 4.888987e-01 2.444493e-01 -4.888987e-01 -3.600000e+00 -4.700000e+00 4.960890e-01 4.960890e-01 2.480445e-01 -4.960890e-01 -3.500000e+00 -4.700000e+00 5.031837e-01 5.031837e-01 2.515919e-01 -5.031837e-01 -3.400000e+00 -4.700000e+00 5.101758e-01 5.101758e-01 2.550879e-01 -5.101758e-01 -3.300000e+00 -4.700000e+00 5.170582e-01 5.170582e-01 2.585291e-01 -5.170582e-01 -3.200000e+00 -4.700000e+00 5.238238e-01 5.238238e-01 2.619119e-01 -5.238238e-01 -3.100000e+00 -4.700000e+00 5.304657e-01 5.304657e-01 2.652329e-01 -5.304657e-01 -3.000000e+00 -4.700000e+00 5.369771e-01 5.369771e-01 2.684885e-01 -5.369771e-01 -2.900000e+00 -4.700000e+00 5.433509e-01 5.433509e-01 2.716754e-01 -5.433509e-01 -2.800000e+00 -4.700000e+00 5.495806e-01 5.495806e-01 2.747903e-01 -5.495806e-01 -2.700000e+00 -4.700000e+00 5.556593e-01 5.556593e-01 2.778296e-01 -5.556593e-01 -2.600000e+00 -4.700000e+00 5.615807e-01 5.615807e-01 2.807903e-01 -5.615807e-01 -2.500000e+00 -4.700000e+00 5.673380e-01 5.673380e-01 2.836690e-01 -5.673380e-01 -2.400000e+00 -4.700000e+00 5.729253e-01 5.729253e-01 2.864627e-01 -5.729253e-01 -2.300000e+00 -4.700000e+00 5.783362e-01 5.783362e-01 2.891681e-01 -5.783362e-01 -2.200000e+00 -4.700000e+00 5.835647e-01 5.835647e-01 2.917823e-01 -5.835647e-01 -2.100000e+00 -4.700000e+00 5.886050e-01 5.886050e-01 2.943025e-01 -5.886050e-01 -2.000000e+00 -4.700000e+00 5.934514e-01 5.934514e-01 2.967257e-01 -5.934514e-01 -1.900000e+00 -4.700000e+00 5.980985e-01 5.980985e-01 2.990492e-01 -5.980985e-01 -1.800000e+00 -4.700000e+00 6.025408e-01 6.025408e-01 3.012704e-01 -6.025408e-01 -1.700000e+00 -4.700000e+00 6.067734e-01 6.067734e-01 3.033867e-01 -6.067734e-01 -1.600000e+00 -4.700000e+00 6.107913e-01 6.107913e-01 3.053957e-01 -6.107913e-01 -1.500000e+00 -4.700000e+00 6.145900e-01 6.145900e-01 3.072950e-01 -6.145900e-01 -1.400000e+00 -4.700000e+00 6.181650e-01 6.181650e-01 3.090825e-01 -6.181650e-01 -1.300000e+00 -4.700000e+00 6.215121e-01 6.215121e-01 3.107560e-01 -6.215121e-01 -1.200000e+00 -4.700000e+00 6.246274e-01 6.246274e-01 3.123137e-01 -6.246274e-01 -1.100000e+00 -4.700000e+00 6.275073e-01 6.275073e-01 3.137537e-01 -6.275073e-01 -1.000000e+00 -4.700000e+00 6.301484e-01 6.301484e-01 3.150742e-01 -6.301484e-01 -9.000000e-01 -4.700000e+00 6.325475e-01 6.325475e-01 3.162737e-01 -6.325475e-01 -8.000000e-01 -4.700000e+00 6.347018e-01 6.347018e-01 3.173509e-01 -6.347018e-01 -7.000000e-01 -4.700000e+00 6.366088e-01 6.366088e-01 3.183044e-01 -6.366088e-01 -6.000000e-01 -4.700000e+00 6.382661e-01 6.382661e-01 3.191331e-01 -6.382661e-01 -5.000000e-01 -4.700000e+00 6.396719e-01 6.396719e-01 3.198359e-01 -6.396719e-01 -4.000000e-01 -4.700000e+00 6.408243e-01 6.408243e-01 3.204122e-01 -6.408243e-01 -3.000000e-01 -4.700000e+00 6.417221e-01 6.417221e-01 3.208610e-01 -6.417221e-01 -2.000000e-01 -4.700000e+00 6.423641e-01 6.423641e-01 3.211821e-01 -6.423641e-01 -1.000000e-01 -4.700000e+00 6.427497e-01 6.427497e-01 3.213748e-01 -6.427497e-01 0.000000e+00 -4.700000e+00 6.428782e-01 6.428782e-01 3.214391e-01 -6.428782e-01 1.000000e-01 -4.700000e+00 6.427497e-01 6.427497e-01 3.213748e-01 -6.427497e-01 2.000000e-01 -4.700000e+00 6.423641e-01 6.423641e-01 3.211821e-01 -6.423641e-01 3.000000e-01 -4.700000e+00 6.417221e-01 6.417221e-01 3.208610e-01 -6.417221e-01 4.000000e-01 -4.700000e+00 6.408243e-01 6.408243e-01 3.204122e-01 -6.408243e-01 5.000000e-01 -4.700000e+00 6.396719e-01 6.396719e-01 3.198359e-01 -6.396719e-01 6.000000e-01 -4.700000e+00 6.382661e-01 6.382661e-01 3.191331e-01 -6.382661e-01 7.000000e-01 -4.700000e+00 6.366088e-01 6.366088e-01 3.183044e-01 -6.366088e-01 8.000000e-01 -4.700000e+00 6.347018e-01 6.347018e-01 3.173509e-01 -6.347018e-01 9.000000e-01 -4.700000e+00 6.325475e-01 6.325475e-01 3.162737e-01 -6.325475e-01 1.000000e+00 -4.700000e+00 6.301484e-01 6.301484e-01 3.150742e-01 -6.301484e-01 1.100000e+00 -4.700000e+00 6.275073e-01 6.275073e-01 3.137537e-01 -6.275073e-01 1.200000e+00 -4.700000e+00 6.246274e-01 6.246274e-01 3.123137e-01 -6.246274e-01 1.300000e+00 -4.700000e+00 6.215121e-01 6.215121e-01 3.107560e-01 -6.215121e-01 1.400000e+00 -4.700000e+00 6.181650e-01 6.181650e-01 3.090825e-01 -6.181650e-01 1.500000e+00 -4.700000e+00 6.145900e-01 6.145900e-01 3.072950e-01 -6.145900e-01 1.600000e+00 -4.700000e+00 6.107913e-01 6.107913e-01 3.053957e-01 -6.107913e-01 1.700000e+00 -4.700000e+00 6.067734e-01 6.067734e-01 3.033867e-01 -6.067734e-01 1.800000e+00 -4.700000e+00 6.025408e-01 6.025408e-01 3.012704e-01 -6.025408e-01 1.900000e+00 -4.700000e+00 5.980985e-01 5.980985e-01 2.990492e-01 -5.980985e-01 2.000000e+00 -4.700000e+00 5.934514e-01 5.934514e-01 2.967257e-01 -5.934514e-01 2.100000e+00 -4.700000e+00 5.886050e-01 5.886050e-01 2.943025e-01 -5.886050e-01 2.200000e+00 -4.700000e+00 5.835647e-01 5.835647e-01 2.917823e-01 -5.835647e-01 2.300000e+00 -4.700000e+00 5.783362e-01 5.783362e-01 2.891681e-01 -5.783362e-01 2.400000e+00 -4.700000e+00 5.729253e-01 5.729253e-01 2.864627e-01 -5.729253e-01 2.500000e+00 -4.700000e+00 5.673380e-01 5.673380e-01 2.836690e-01 -5.673380e-01 2.600000e+00 -4.700000e+00 5.615807e-01 5.615807e-01 2.807903e-01 -5.615807e-01 2.700000e+00 -4.700000e+00 5.556593e-01 5.556593e-01 2.778296e-01 -5.556593e-01 2.800000e+00 -4.700000e+00 5.495806e-01 5.495806e-01 2.747903e-01 -5.495806e-01 2.900000e+00 -4.700000e+00 5.433509e-01 5.433509e-01 2.716754e-01 -5.433509e-01 3.000000e+00 -4.700000e+00 5.369771e-01 5.369771e-01 2.684885e-01 -5.369771e-01 3.100000e+00 -4.700000e+00 5.304657e-01 5.304657e-01 2.652329e-01 -5.304657e-01 3.200000e+00 -4.700000e+00 5.238238e-01 5.238238e-01 2.619119e-01 -5.238238e-01 3.300000e+00 -4.700000e+00 5.170582e-01 5.170582e-01 2.585291e-01 -5.170582e-01 3.400000e+00 -4.700000e+00 5.101758e-01 5.101758e-01 2.550879e-01 -5.101758e-01 3.500000e+00 -4.700000e+00 5.031837e-01 5.031837e-01 2.515919e-01 -5.031837e-01 3.600000e+00 -4.700000e+00 4.960890e-01 4.960890e-01 2.480445e-01 -4.960890e-01 3.700000e+00 -4.700000e+00 4.888987e-01 4.888987e-01 2.444493e-01 -4.888987e-01 3.800000e+00 -4.700000e+00 4.816200e-01 4.816200e-01 2.408100e-01 -4.816200e-01 3.900000e+00 -4.700000e+00 4.742598e-01 4.742598e-01 2.371299e-01 -4.742598e-01 4.000000e+00 -4.700000e+00 4.668254e-01 4.668254e-01 2.334127e-01 -4.668254e-01 4.100000e+00 -4.700000e+00 4.593238e-01 4.593238e-01 2.296619e-01 -4.593238e-01 4.200000e+00 -4.700000e+00 4.517620e-01 4.517620e-01 2.258810e-01 -4.517620e-01 4.300000e+00 -4.700000e+00 4.441469e-01 4.441469e-01 2.220734e-01 -4.441469e-01 4.400000e+00 -4.700000e+00 4.364856e-01 4.364856e-01 2.182428e-01 -4.364856e-01 4.500000e+00 -4.700000e+00 4.287849e-01 4.287849e-01 2.143924e-01 -4.287849e-01 4.600000e+00 -4.700000e+00 4.210516e-01 4.210516e-01 2.105258e-01 -4.210516e-01 4.700000e+00 -4.700000e+00 4.132924e-01 4.132924e-01 2.066462e-01 -4.132924e-01 4.800000e+00 -4.700000e+00 4.055140e-01 4.055140e-01 2.027570e-01 -4.055140e-01 4.900000e+00 -4.700000e+00 3.977228e-01 3.977228e-01 1.988614e-01 -3.977228e-01 -5.000000e+00 -4.600000e+00 3.972458e-01 3.972458e-01 1.986229e-01 -3.972458e-01 -4.900000e+00 -4.600000e+00 4.051897e-01 4.051897e-01 2.025948e-01 -4.051897e-01 -4.800000e+00 -4.600000e+00 4.131271e-01 4.131271e-01 2.065636e-01 -4.131271e-01 -4.700000e+00 -4.600000e+00 4.210516e-01 4.210516e-01 2.105258e-01 -4.210516e-01 -4.600000e+00 -4.600000e+00 4.289564e-01 4.289564e-01 2.144782e-01 -4.289564e-01 -4.500000e+00 -4.600000e+00 4.368349e-01 4.368349e-01 2.184175e-01 -4.368349e-01 -4.400000e+00 -4.600000e+00 4.446802e-01 4.446802e-01 2.223401e-01 -4.446802e-01 -4.300000e+00 -4.600000e+00 4.524853e-01 4.524853e-01 2.262427e-01 -4.524853e-01 -4.200000e+00 -4.600000e+00 4.602433e-01 4.602433e-01 2.301217e-01 -4.602433e-01 -4.100000e+00 -4.600000e+00 4.679471e-01 4.679471e-01 2.339736e-01 -4.679471e-01 -4.000000e+00 -4.600000e+00 4.755896e-01 4.755896e-01 2.377948e-01 -4.755896e-01 -3.900000e+00 -4.600000e+00 4.831636e-01 4.831636e-01 2.415818e-01 -4.831636e-01 -3.800000e+00 -4.600000e+00 4.906619e-01 4.906619e-01 2.453310e-01 -4.906619e-01 -3.700000e+00 -4.600000e+00 4.980773e-01 4.980773e-01 2.490387e-01 -4.980773e-01 -3.600000e+00 -4.600000e+00 5.054026e-01 5.054026e-01 2.527013e-01 -5.054026e-01 -3.500000e+00 -4.600000e+00 5.126305e-01 5.126305e-01 2.563153e-01 -5.126305e-01 -3.400000e+00 -4.600000e+00 5.197538e-01 5.197538e-01 2.598769e-01 -5.197538e-01 -3.300000e+00 -4.600000e+00 5.267655e-01 5.267655e-01 2.633827e-01 -5.267655e-01 -3.200000e+00 -4.600000e+00 5.336581e-01 5.336581e-01 2.668290e-01 -5.336581e-01 -3.100000e+00 -4.600000e+00 5.404247e-01 5.404247e-01 2.702124e-01 -5.404247e-01 -3.000000e+00 -4.600000e+00 5.470583e-01 5.470583e-01 2.735291e-01 -5.470583e-01 -2.900000e+00 -4.600000e+00 5.535518e-01 5.535518e-01 2.767759e-01 -5.535518e-01 -2.800000e+00 -4.600000e+00 5.598984e-01 5.598984e-01 2.799492e-01 -5.598984e-01 -2.700000e+00 -4.600000e+00 5.660913e-01 5.660913e-01 2.830456e-01 -5.660913e-01 -2.600000e+00 -4.600000e+00 5.721238e-01 5.721238e-01 2.860619e-01 -5.721238e-01 -2.500000e+00 -4.600000e+00 5.779893e-01 5.779893e-01 2.889946e-01 -5.779893e-01 -2.400000e+00 -4.600000e+00 5.836814e-01 5.836814e-01 2.918407e-01 -5.836814e-01 -2.300000e+00 -4.600000e+00 5.891939e-01 5.891939e-01 2.945970e-01 -5.891939e-01 -2.200000e+00 -4.600000e+00 5.945206e-01 5.945206e-01 2.972603e-01 -5.945206e-01 -2.100000e+00 -4.600000e+00 5.996555e-01 5.996555e-01 2.998278e-01 -5.996555e-01 -2.000000e+00 -4.600000e+00 6.045929e-01 6.045929e-01 3.022965e-01 -6.045929e-01 -1.900000e+00 -4.600000e+00 6.093271e-01 6.093271e-01 3.046636e-01 -6.093271e-01 -1.800000e+00 -4.600000e+00 6.138529e-01 6.138529e-01 3.069265e-01 -6.138529e-01 -1.700000e+00 -4.600000e+00 6.181650e-01 6.181650e-01 3.090825e-01 -6.181650e-01 -1.600000e+00 -4.600000e+00 6.222583e-01 6.222583e-01 3.111292e-01 -6.222583e-01 -1.500000e+00 -4.600000e+00 6.261283e-01 6.261283e-01 3.130642e-01 -6.261283e-01 -1.400000e+00 -4.600000e+00 6.297704e-01 6.297704e-01 3.148852e-01 -6.297704e-01 -1.300000e+00 -4.600000e+00 6.331804e-01 6.331804e-01 3.165902e-01 -6.331804e-01 -1.200000e+00 -4.600000e+00 6.363542e-01 6.363542e-01 3.181771e-01 -6.363542e-01 -1.100000e+00 -4.600000e+00 6.392882e-01 6.392882e-01 3.196441e-01 -6.392882e-01 -1.000000e+00 -4.600000e+00 6.419788e-01 6.419788e-01 3.209894e-01 -6.419788e-01 -9.000000e-01 -4.600000e+00 6.444230e-01 6.444230e-01 3.222115e-01 -6.444230e-01 -8.000000e-01 -4.600000e+00 6.466178e-01 6.466178e-01 3.233089e-01 -6.466178e-01 -7.000000e-01 -4.600000e+00 6.485605e-01 6.485605e-01 3.242803e-01 -6.485605e-01 -6.000000e-01 -4.600000e+00 6.502489e-01 6.502489e-01 3.251245e-01 -6.502489e-01 -5.000000e-01 -4.600000e+00 6.516811e-01 6.516811e-01 3.258406e-01 -6.516811e-01 -4.000000e-01 -4.600000e+00 6.528552e-01 6.528552e-01 3.264276e-01 -6.528552e-01 -3.000000e-01 -4.600000e+00 6.537698e-01 6.537698e-01 3.268849e-01 -6.537698e-01 -2.000000e-01 -4.600000e+00 6.544239e-01 6.544239e-01 3.272119e-01 -6.544239e-01 -1.000000e-01 -4.600000e+00 6.548167e-01 6.548167e-01 3.274083e-01 -6.548167e-01 0.000000e+00 -4.600000e+00 6.549476e-01 6.549476e-01 3.274738e-01 -6.549476e-01 1.000000e-01 -4.600000e+00 6.548167e-01 6.548167e-01 3.274083e-01 -6.548167e-01 2.000000e-01 -4.600000e+00 6.544239e-01 6.544239e-01 3.272119e-01 -6.544239e-01 3.000000e-01 -4.600000e+00 6.537698e-01 6.537698e-01 3.268849e-01 -6.537698e-01 4.000000e-01 -4.600000e+00 6.528552e-01 6.528552e-01 3.264276e-01 -6.528552e-01 5.000000e-01 -4.600000e+00 6.516811e-01 6.516811e-01 3.258406e-01 -6.516811e-01 6.000000e-01 -4.600000e+00 6.502489e-01 6.502489e-01 3.251245e-01 -6.502489e-01 7.000000e-01 -4.600000e+00 6.485605e-01 6.485605e-01 3.242803e-01 -6.485605e-01 8.000000e-01 -4.600000e+00 6.466178e-01 6.466178e-01 3.233089e-01 -6.466178e-01 9.000000e-01 -4.600000e+00 6.444230e-01 6.444230e-01 3.222115e-01 -6.444230e-01 1.000000e+00 -4.600000e+00 6.419788e-01 6.419788e-01 3.209894e-01 -6.419788e-01 1.100000e+00 -4.600000e+00 6.392882e-01 6.392882e-01 3.196441e-01 -6.392882e-01 1.200000e+00 -4.600000e+00 6.363542e-01 6.363542e-01 3.181771e-01 -6.363542e-01 1.300000e+00 -4.600000e+00 6.331804e-01 6.331804e-01 3.165902e-01 -6.331804e-01 1.400000e+00 -4.600000e+00 6.297704e-01 6.297704e-01 3.148852e-01 -6.297704e-01 1.500000e+00 -4.600000e+00 6.261283e-01 6.261283e-01 3.130642e-01 -6.261283e-01 1.600000e+00 -4.600000e+00 6.222583e-01 6.222583e-01 3.111292e-01 -6.222583e-01 1.700000e+00 -4.600000e+00 6.181650e-01 6.181650e-01 3.090825e-01 -6.181650e-01 1.800000e+00 -4.600000e+00 6.138529e-01 6.138529e-01 3.069265e-01 -6.138529e-01 1.900000e+00 -4.600000e+00 6.093271e-01 6.093271e-01 3.046636e-01 -6.093271e-01 2.000000e+00 -4.600000e+00 6.045929e-01 6.045929e-01 3.022965e-01 -6.045929e-01 2.100000e+00 -4.600000e+00 5.996555e-01 5.996555e-01 2.998278e-01 -5.996555e-01 2.200000e+00 -4.600000e+00 5.945206e-01 5.945206e-01 2.972603e-01 -5.945206e-01 2.300000e+00 -4.600000e+00 5.891939e-01 5.891939e-01 2.945970e-01 -5.891939e-01 2.400000e+00 -4.600000e+00 5.836814e-01 5.836814e-01 2.918407e-01 -5.836814e-01 2.500000e+00 -4.600000e+00 5.779893e-01 5.779893e-01 2.889946e-01 -5.779893e-01 2.600000e+00 -4.600000e+00 5.721238e-01 5.721238e-01 2.860619e-01 -5.721238e-01 2.700000e+00 -4.600000e+00 5.660913e-01 5.660913e-01 2.830456e-01 -5.660913e-01 2.800000e+00 -4.600000e+00 5.598984e-01 5.598984e-01 2.799492e-01 -5.598984e-01 2.900000e+00 -4.600000e+00 5.535518e-01 5.535518e-01 2.767759e-01 -5.535518e-01 3.000000e+00 -4.600000e+00 5.470583e-01 5.470583e-01 2.735291e-01 -5.470583e-01 3.100000e+00 -4.600000e+00 5.404247e-01 5.404247e-01 2.702124e-01 -5.404247e-01 3.200000e+00 -4.600000e+00 5.336581e-01 5.336581e-01 2.668290e-01 -5.336581e-01 3.300000e+00 -4.600000e+00 5.267655e-01 5.267655e-01 2.633827e-01 -5.267655e-01 3.400000e+00 -4.600000e+00 5.197538e-01 5.197538e-01 2.598769e-01 -5.197538e-01 3.500000e+00 -4.600000e+00 5.126305e-01 5.126305e-01 2.563153e-01 -5.126305e-01 3.600000e+00 -4.600000e+00 5.054026e-01 5.054026e-01 2.527013e-01 -5.054026e-01 3.700000e+00 -4.600000e+00 4.980773e-01 4.980773e-01 2.490387e-01 -4.980773e-01 3.800000e+00 -4.600000e+00 4.906619e-01 4.906619e-01 2.453310e-01 -4.906619e-01 3.900000e+00 -4.600000e+00 4.831636e-01 4.831636e-01 2.415818e-01 -4.831636e-01 4.000000e+00 -4.600000e+00 4.755896e-01 4.755896e-01 2.377948e-01 -4.755896e-01 4.100000e+00 -4.600000e+00 4.679471e-01 4.679471e-01 2.339736e-01 -4.679471e-01 4.200000e+00 -4.600000e+00 4.602433e-01 4.602433e-01 2.301217e-01 -4.602433e-01 4.300000e+00 -4.600000e+00 4.524853e-01 4.524853e-01 2.262427e-01 -4.524853e-01 4.400000e+00 -4.600000e+00 4.446802e-01 4.446802e-01 2.223401e-01 -4.446802e-01 4.500000e+00 -4.600000e+00 4.368349e-01 4.368349e-01 2.184175e-01 -4.368349e-01 4.600000e+00 -4.600000e+00 4.289564e-01 4.289564e-01 2.144782e-01 -4.289564e-01 4.700000e+00 -4.600000e+00 4.210516e-01 4.210516e-01 2.105258e-01 -4.210516e-01 4.800000e+00 -4.600000e+00 4.131271e-01 4.131271e-01 2.065636e-01 -4.131271e-01 4.900000e+00 -4.600000e+00 4.051897e-01 4.051897e-01 2.025948e-01 -4.051897e-01 -5.000000e+00 -4.500000e+00 4.045419e-01 4.045419e-01 2.022710e-01 -4.045419e-01 -4.900000e+00 -4.500000e+00 4.126316e-01 4.126316e-01 2.063158e-01 -4.126316e-01 -4.800000e+00 -4.500000e+00 4.207148e-01 4.207148e-01 2.103574e-01 -4.207148e-01 -4.700000e+00 -4.500000e+00 4.287849e-01 4.287849e-01 2.143924e-01 -4.287849e-01 -4.600000e+00 -4.500000e+00 4.368349e-01 4.368349e-01 2.184175e-01 -4.368349e-01 -4.500000e+00 -4.500000e+00 4.448581e-01 4.448581e-01 2.224291e-01 -4.448581e-01 -4.400000e+00 -4.500000e+00 4.528475e-01 4.528475e-01 2.264237e-01 -4.528475e-01 -4.300000e+00 -4.500000e+00 4.607960e-01 4.607960e-01 2.303980e-01 -4.607960e-01 -4.200000e+00 -4.500000e+00 4.686964e-01 4.686964e-01 2.343482e-01 -4.686964e-01 -4.100000e+00 -4.500000e+00 4.765417e-01 4.765417e-01 2.382709e-01 -4.765417e-01 -4.000000e+00 -4.500000e+00 4.843245e-01 4.843245e-01 2.421623e-01 -4.843245e-01 -3.900000e+00 -4.500000e+00 4.920377e-01 4.920377e-01 2.460188e-01 -4.920377e-01 -3.800000e+00 -4.500000e+00 4.996737e-01 4.996737e-01 2.498369e-01 -4.996737e-01 -3.700000e+00 -4.500000e+00 5.072253e-01 5.072253e-01 2.536126e-01 -5.072253e-01 -3.600000e+00 -4.500000e+00 5.146852e-01 5.146852e-01 2.573426e-01 -5.146852e-01 -3.500000e+00 -4.500000e+00 5.220458e-01 5.220458e-01 2.610229e-01 -5.220458e-01 -3.400000e+00 -4.500000e+00 5.293000e-01 5.293000e-01 2.646500e-01 -5.293000e-01 -3.300000e+00 -4.500000e+00 5.364403e-01 5.364403e-01 2.682202e-01 -5.364403e-01 -3.200000e+00 -4.500000e+00 5.434595e-01 5.434595e-01 2.717298e-01 -5.434595e-01 -3.100000e+00 -4.500000e+00 5.503505e-01 5.503505e-01 2.751752e-01 -5.503505e-01 -3.000000e+00 -4.500000e+00 5.571059e-01 5.571059e-01 2.785529e-01 -5.571059e-01 -2.900000e+00 -4.500000e+00 5.637187e-01 5.637187e-01 2.818593e-01 -5.637187e-01 -2.800000e+00 -4.500000e+00 5.701818e-01 5.701818e-01 2.850909e-01 -5.701818e-01 -2.700000e+00 -4.500000e+00 5.764884e-01 5.764884e-01 2.882442e-01 -5.764884e-01 -2.600000e+00 -4.500000e+00 5.826317e-01 5.826317e-01 2.913159e-01 -5.826317e-01 -2.500000e+00 -4.500000e+00 5.886050e-01 5.886050e-01 2.943025e-01 -5.886050e-01 -2.400000e+00 -4.500000e+00 5.944017e-01 5.944017e-01 2.972008e-01 -5.944017e-01 -2.300000e+00 -4.500000e+00 6.000154e-01 6.000154e-01 3.000077e-01 -6.000154e-01 -2.200000e+00 -4.500000e+00 6.054399e-01 6.054399e-01 3.027200e-01 -6.054399e-01 -2.100000e+00 -4.500000e+00 6.106691e-01 6.106691e-01 3.053346e-01 -6.106691e-01 -2.000000e+00 -4.500000e+00 6.156972e-01 6.156972e-01 3.078486e-01 -6.156972e-01 -1.900000e+00 -4.500000e+00 6.205184e-01 6.205184e-01 3.102592e-01 -6.205184e-01 -1.800000e+00 -4.500000e+00 6.251273e-01 6.251273e-01 3.125637e-01 -6.251273e-01 -1.700000e+00 -4.500000e+00 6.295186e-01 6.295186e-01 3.147593e-01 -6.295186e-01 -1.600000e+00 -4.500000e+00 6.336871e-01 6.336871e-01 3.168435e-01 -6.336871e-01 -1.500000e+00 -4.500000e+00 6.376281e-01 6.376281e-01 3.188141e-01 -6.376281e-01 -1.400000e+00 -4.500000e+00 6.413372e-01 6.413372e-01 3.206686e-01 -6.413372e-01 -1.300000e+00 -4.500000e+00 6.448097e-01 6.448097e-01 3.224049e-01 -6.448097e-01 -1.200000e+00 -4.500000e+00 6.480418e-01 6.480418e-01 3.240209e-01 -6.480418e-01 -1.100000e+00 -4.500000e+00 6.510297e-01 6.510297e-01 3.255149e-01 -6.510297e-01 -1.000000e+00 -4.500000e+00 6.537698e-01 6.537698e-01 3.268849e-01 -6.537698e-01 -9.000000e-01 -4.500000e+00 6.562589e-01 6.562589e-01 3.281294e-01 -6.562589e-01 -8.000000e-01 -4.500000e+00 6.584939e-01 6.584939e-01 3.292470e-01 -6.584939e-01 -7.000000e-01 -4.500000e+00 6.604724e-01 6.604724e-01 3.302362e-01 -6.604724e-01 -6.000000e-01 -4.500000e+00 6.621919e-01 6.621919e-01 3.310959e-01 -6.621919e-01 -5.000000e-01 -4.500000e+00 6.636503e-01 6.636503e-01 3.318251e-01 -6.636503e-01 -4.000000e-01 -4.500000e+00 6.648459e-01 6.648459e-01 3.324230e-01 -6.648459e-01 -3.000000e-01 -4.500000e+00 6.657773e-01 6.657773e-01 3.328887e-01 -6.657773e-01 -2.000000e-01 -4.500000e+00 6.664435e-01 6.664435e-01 3.332217e-01 -6.664435e-01 -1.000000e-01 -4.500000e+00 6.668435e-01 6.668435e-01 3.334217e-01 -6.668435e-01 0.000000e+00 -4.500000e+00 6.669768e-01 6.669768e-01 3.334884e-01 -6.669768e-01 1.000000e-01 -4.500000e+00 6.668435e-01 6.668435e-01 3.334217e-01 -6.668435e-01 2.000000e-01 -4.500000e+00 6.664435e-01 6.664435e-01 3.332217e-01 -6.664435e-01 3.000000e-01 -4.500000e+00 6.657773e-01 6.657773e-01 3.328887e-01 -6.657773e-01 4.000000e-01 -4.500000e+00 6.648459e-01 6.648459e-01 3.324230e-01 -6.648459e-01 5.000000e-01 -4.500000e+00 6.636503e-01 6.636503e-01 3.318251e-01 -6.636503e-01 6.000000e-01 -4.500000e+00 6.621919e-01 6.621919e-01 3.310959e-01 -6.621919e-01 7.000000e-01 -4.500000e+00 6.604724e-01 6.604724e-01 3.302362e-01 -6.604724e-01 8.000000e-01 -4.500000e+00 6.584939e-01 6.584939e-01 3.292470e-01 -6.584939e-01 9.000000e-01 -4.500000e+00 6.562589e-01 6.562589e-01 3.281294e-01 -6.562589e-01 1.000000e+00 -4.500000e+00 6.537698e-01 6.537698e-01 3.268849e-01 -6.537698e-01 1.100000e+00 -4.500000e+00 6.510297e-01 6.510297e-01 3.255149e-01 -6.510297e-01 1.200000e+00 -4.500000e+00 6.480418e-01 6.480418e-01 3.240209e-01 -6.480418e-01 1.300000e+00 -4.500000e+00 6.448097e-01 6.448097e-01 3.224049e-01 -6.448097e-01 1.400000e+00 -4.500000e+00 6.413372e-01 6.413372e-01 3.206686e-01 -6.413372e-01 1.500000e+00 -4.500000e+00 6.376281e-01 6.376281e-01 3.188141e-01 -6.376281e-01 1.600000e+00 -4.500000e+00 6.336871e-01 6.336871e-01 3.168435e-01 -6.336871e-01 1.700000e+00 -4.500000e+00 6.295186e-01 6.295186e-01 3.147593e-01 -6.295186e-01 1.800000e+00 -4.500000e+00 6.251273e-01 6.251273e-01 3.125637e-01 -6.251273e-01 1.900000e+00 -4.500000e+00 6.205184e-01 6.205184e-01 3.102592e-01 -6.205184e-01 2.000000e+00 -4.500000e+00 6.156972e-01 6.156972e-01 3.078486e-01 -6.156972e-01 2.100000e+00 -4.500000e+00 6.106691e-01 6.106691e-01 3.053346e-01 -6.106691e-01 2.200000e+00 -4.500000e+00 6.054399e-01 6.054399e-01 3.027200e-01 -6.054399e-01 2.300000e+00 -4.500000e+00 6.000154e-01 6.000154e-01 3.000077e-01 -6.000154e-01 2.400000e+00 -4.500000e+00 5.944017e-01 5.944017e-01 2.972008e-01 -5.944017e-01 2.500000e+00 -4.500000e+00 5.886050e-01 5.886050e-01 2.943025e-01 -5.886050e-01 2.600000e+00 -4.500000e+00 5.826317e-01 5.826317e-01 2.913159e-01 -5.826317e-01 2.700000e+00 -4.500000e+00 5.764884e-01 5.764884e-01 2.882442e-01 -5.764884e-01 2.800000e+00 -4.500000e+00 5.701818e-01 5.701818e-01 2.850909e-01 -5.701818e-01 2.900000e+00 -4.500000e+00 5.637187e-01 5.637187e-01 2.818593e-01 -5.637187e-01 3.000000e+00 -4.500000e+00 5.571059e-01 5.571059e-01 2.785529e-01 -5.571059e-01 3.100000e+00 -4.500000e+00 5.503505e-01 5.503505e-01 2.751752e-01 -5.503505e-01 3.200000e+00 -4.500000e+00 5.434595e-01 5.434595e-01 2.717298e-01 -5.434595e-01 3.300000e+00 -4.500000e+00 5.364403e-01 5.364403e-01 2.682202e-01 -5.364403e-01 3.400000e+00 -4.500000e+00 5.293000e-01 5.293000e-01 2.646500e-01 -5.293000e-01 3.500000e+00 -4.500000e+00 5.220458e-01 5.220458e-01 2.610229e-01 -5.220458e-01 3.600000e+00 -4.500000e+00 5.146852e-01 5.146852e-01 2.573426e-01 -5.146852e-01 3.700000e+00 -4.500000e+00 5.072253e-01 5.072253e-01 2.536126e-01 -5.072253e-01 3.800000e+00 -4.500000e+00 4.996737e-01 4.996737e-01 2.498369e-01 -4.996737e-01 3.900000e+00 -4.500000e+00 4.920377e-01 4.920377e-01 2.460188e-01 -4.920377e-01 4.000000e+00 -4.500000e+00 4.843245e-01 4.843245e-01 2.421623e-01 -4.843245e-01 4.100000e+00 -4.500000e+00 4.765417e-01 4.765417e-01 2.382709e-01 -4.765417e-01 4.200000e+00 -4.500000e+00 4.686964e-01 4.686964e-01 2.343482e-01 -4.686964e-01 4.300000e+00 -4.500000e+00 4.607960e-01 4.607960e-01 2.303980e-01 -4.607960e-01 4.400000e+00 -4.500000e+00 4.528475e-01 4.528475e-01 2.264237e-01 -4.528475e-01 4.500000e+00 -4.500000e+00 4.448581e-01 4.448581e-01 2.224291e-01 -4.448581e-01 4.600000e+00 -4.500000e+00 4.368349e-01 4.368349e-01 2.184175e-01 -4.368349e-01 4.700000e+00 -4.500000e+00 4.287849e-01 4.287849e-01 2.143924e-01 -4.287849e-01 4.800000e+00 -4.500000e+00 4.207148e-01 4.207148e-01 2.103574e-01 -4.207148e-01 4.900000e+00 -4.500000e+00 4.126316e-01 4.126316e-01 2.063158e-01 -4.126316e-01 -5.000000e+00 -4.400000e+00 4.118072e-01 4.118072e-01 2.059036e-01 -4.118072e-01 -4.900000e+00 -4.400000e+00 4.200422e-01 4.200422e-01 2.100211e-01 -4.200422e-01 -4.800000e+00 -4.400000e+00 4.282706e-01 4.282706e-01 2.141353e-01 -4.282706e-01 -4.700000e+00 -4.400000e+00 4.364856e-01 4.364856e-01 2.182428e-01 -4.364856e-01 -4.600000e+00 -4.400000e+00 4.446802e-01 4.446802e-01 2.223401e-01 -4.446802e-01 -4.500000e+00 -4.400000e+00 4.528475e-01 4.528475e-01 2.264237e-01 -4.528475e-01 -4.400000e+00 -4.400000e+00 4.609803e-01 4.609803e-01 2.304901e-01 -4.609803e-01 -4.300000e+00 -4.400000e+00 4.690715e-01 4.690715e-01 2.345358e-01 -4.690715e-01 -4.200000e+00 -4.400000e+00 4.771139e-01 4.771139e-01 2.385570e-01 -4.771139e-01 -4.100000e+00 -4.400000e+00 4.851001e-01 4.851001e-01 2.425501e-01 -4.851001e-01 -4.000000e+00 -4.400000e+00 4.930227e-01 4.930227e-01 2.465114e-01 -4.930227e-01 -3.900000e+00 -4.400000e+00 5.008743e-01 5.008743e-01 2.504372e-01 -5.008743e-01 -3.800000e+00 -4.400000e+00 5.086475e-01 5.086475e-01 2.543238e-01 -5.086475e-01 -3.700000e+00 -4.400000e+00 5.163347e-01 5.163347e-01 2.581674e-01 -5.163347e-01 -3.600000e+00 -4.400000e+00 5.239285e-01 5.239285e-01 2.619643e-01 -5.239285e-01 -3.500000e+00 -4.400000e+00 5.314214e-01 5.314214e-01 2.657107e-01 -5.314214e-01 -3.400000e+00 -4.400000e+00 5.388058e-01 5.388058e-01 2.694029e-01 -5.388058e-01 -3.300000e+00 -4.400000e+00 5.460745e-01 5.460745e-01 2.730372e-01 -5.460745e-01 -3.200000e+00 -4.400000e+00 5.532197e-01 5.532197e-01 2.766099e-01 -5.532197e-01 -3.100000e+00 -4.400000e+00 5.602344e-01 5.602344e-01 2.801172e-01 -5.602344e-01 -3.000000e+00 -4.400000e+00 5.671111e-01 5.671111e-01 2.835556e-01 -5.671111e-01 -2.900000e+00 -4.400000e+00 5.738426e-01 5.738426e-01 2.869213e-01 -5.738426e-01 -2.800000e+00 -4.400000e+00 5.804219e-01 5.804219e-01 2.902110e-01 -5.804219e-01 -2.700000e+00 -4.400000e+00 5.868418e-01 5.868418e-01 2.934209e-01 -5.868418e-01 -2.600000e+00 -4.400000e+00 5.930954e-01 5.930954e-01 2.965477e-01 -5.930954e-01 -2.500000e+00 -4.400000e+00 5.991759e-01 5.991759e-01 2.995880e-01 -5.991759e-01 -2.400000e+00 -4.400000e+00 6.050767e-01 6.050767e-01 3.025384e-01 -6.050767e-01 -2.300000e+00 -4.400000e+00 6.107913e-01 6.107913e-01 3.053956e-01 -6.107913e-01 -2.200000e+00 -4.400000e+00 6.163132e-01 6.163132e-01 3.081566e-01 -6.163132e-01 -2.100000e+00 -4.400000e+00 6.216363e-01 6.216363e-01 3.108182e-01 -6.216363e-01 -2.000000e+00 -4.400000e+00 6.267547e-01 6.267547e-01 3.133774e-01 -6.267547e-01 -1.900000e+00 -4.400000e+00 6.316625e-01 6.316625e-01 3.158313e-01 -6.316625e-01 -1.800000e+00 -4.400000e+00 6.363541e-01 6.363541e-01 3.181771e-01 -6.363541e-01 -1.700000e+00 -4.400000e+00 6.408243e-01 6.408243e-01 3.204121e-01 -6.408243e-01 -1.600000e+00 -4.400000e+00 6.450677e-01 6.450677e-01 3.225338e-01 -6.450677e-01 -1.500000e+00 -4.400000e+00 6.490796e-01 6.490796e-01 3.245398e-01 -6.490796e-01 -1.400000e+00 -4.400000e+00 6.528552e-01 6.528552e-01 3.264276e-01 -6.528552e-01 -1.300000e+00 -4.400000e+00 6.563901e-01 6.563901e-01 3.281950e-01 -6.563901e-01 -1.200000e+00 -4.400000e+00 6.596802e-01 6.596802e-01 3.298401e-01 -6.596802e-01 -1.100000e+00 -4.400000e+00 6.627218e-01 6.627218e-01 3.313609e-01 -6.627218e-01 -1.000000e+00 -4.400000e+00 6.655111e-01 6.655111e-01 3.327555e-01 -6.655111e-01 -9.000000e-01 -4.400000e+00 6.680448e-01 6.680448e-01 3.340224e-01 -6.680448e-01 -8.000000e-01 -4.400000e+00 6.703200e-01 6.703200e-01 3.351600e-01 -6.703200e-01 -7.000000e-01 -4.400000e+00 6.723340e-01 6.723340e-01 3.361670e-01 -6.723340e-01 -6.000000e-01 -4.400000e+00 6.740844e-01 6.740844e-01 3.370422e-01 -6.740844e-01 -5.000000e-01 -4.400000e+00 6.755690e-01 6.755690e-01 3.377845e-01 -6.755690e-01 -4.000000e-01 -4.400000e+00 6.767861e-01 6.767861e-01 3.383931e-01 -6.767861e-01 -3.000000e-01 -4.400000e+00 6.777343e-01 6.777343e-01 3.388671e-01 -6.777343e-01 -2.000000e-01 -4.400000e+00 6.784123e-01 6.784123e-01 3.392062e-01 -6.784123e-01 -1.000000e-01 -4.400000e+00 6.788195e-01 6.788195e-01 3.394098e-01 -6.788195e-01 0.000000e+00 -4.400000e+00 6.789553e-01 6.789553e-01 3.394777e-01 -6.789553e-01 1.000000e-01 -4.400000e+00 6.788195e-01 6.788195e-01 3.394098e-01 -6.788195e-01 2.000000e-01 -4.400000e+00 6.784123e-01 6.784123e-01 3.392062e-01 -6.784123e-01 3.000000e-01 -4.400000e+00 6.777343e-01 6.777343e-01 3.388671e-01 -6.777343e-01 4.000000e-01 -4.400000e+00 6.767861e-01 6.767861e-01 3.383931e-01 -6.767861e-01 5.000000e-01 -4.400000e+00 6.755690e-01 6.755690e-01 3.377845e-01 -6.755690e-01 6.000000e-01 -4.400000e+00 6.740844e-01 6.740844e-01 3.370422e-01 -6.740844e-01 7.000000e-01 -4.400000e+00 6.723340e-01 6.723340e-01 3.361670e-01 -6.723340e-01 8.000000e-01 -4.400000e+00 6.703200e-01 6.703200e-01 3.351600e-01 -6.703200e-01 9.000000e-01 -4.400000e+00 6.680448e-01 6.680448e-01 3.340224e-01 -6.680448e-01 1.000000e+00 -4.400000e+00 6.655111e-01 6.655111e-01 3.327555e-01 -6.655111e-01 1.100000e+00 -4.400000e+00 6.627218e-01 6.627218e-01 3.313609e-01 -6.627218e-01 1.200000e+00 -4.400000e+00 6.596802e-01 6.596802e-01 3.298401e-01 -6.596802e-01 1.300000e+00 -4.400000e+00 6.563901e-01 6.563901e-01 3.281950e-01 -6.563901e-01 1.400000e+00 -4.400000e+00 6.528552e-01 6.528552e-01 3.264276e-01 -6.528552e-01 1.500000e+00 -4.400000e+00 6.490796e-01 6.490796e-01 3.245398e-01 -6.490796e-01 1.600000e+00 -4.400000e+00 6.450677e-01 6.450677e-01 3.225338e-01 -6.450677e-01 1.700000e+00 -4.400000e+00 6.408243e-01 6.408243e-01 3.204121e-01 -6.408243e-01 1.800000e+00 -4.400000e+00 6.363541e-01 6.363541e-01 3.181771e-01 -6.363541e-01 1.900000e+00 -4.400000e+00 6.316625e-01 6.316625e-01 3.158313e-01 -6.316625e-01 2.000000e+00 -4.400000e+00 6.267547e-01 6.267547e-01 3.133774e-01 -6.267547e-01 2.100000e+00 -4.400000e+00 6.216363e-01 6.216363e-01 3.108182e-01 -6.216363e-01 2.200000e+00 -4.400000e+00 6.163132e-01 6.163132e-01 3.081566e-01 -6.163132e-01 2.300000e+00 -4.400000e+00 6.107913e-01 6.107913e-01 3.053956e-01 -6.107913e-01 2.400000e+00 -4.400000e+00 6.050767e-01 6.050767e-01 3.025384e-01 -6.050767e-01 2.500000e+00 -4.400000e+00 5.991759e-01 5.991759e-01 2.995880e-01 -5.991759e-01 2.600000e+00 -4.400000e+00 5.930954e-01 5.930954e-01 2.965477e-01 -5.930954e-01 2.700000e+00 -4.400000e+00 5.868418e-01 5.868418e-01 2.934209e-01 -5.868418e-01 2.800000e+00 -4.400000e+00 5.804219e-01 5.804219e-01 2.902110e-01 -5.804219e-01 2.900000e+00 -4.400000e+00 5.738426e-01 5.738426e-01 2.869213e-01 -5.738426e-01 3.000000e+00 -4.400000e+00 5.671111e-01 5.671111e-01 2.835556e-01 -5.671111e-01 3.100000e+00 -4.400000e+00 5.602344e-01 5.602344e-01 2.801172e-01 -5.602344e-01 3.200000e+00 -4.400000e+00 5.532197e-01 5.532197e-01 2.766099e-01 -5.532197e-01 3.300000e+00 -4.400000e+00 5.460745e-01 5.460745e-01 2.730372e-01 -5.460745e-01 3.400000e+00 -4.400000e+00 5.388058e-01 5.388058e-01 2.694029e-01 -5.388058e-01 3.500000e+00 -4.400000e+00 5.314214e-01 5.314214e-01 2.657107e-01 -5.314214e-01 3.600000e+00 -4.400000e+00 5.239285e-01 5.239285e-01 2.619643e-01 -5.239285e-01 3.700000e+00 -4.400000e+00 5.163347e-01 5.163347e-01 2.581674e-01 -5.163347e-01 3.800000e+00 -4.400000e+00 5.086475e-01 5.086475e-01 2.543238e-01 -5.086475e-01 3.900000e+00 -4.400000e+00 5.008743e-01 5.008743e-01 2.504372e-01 -5.008743e-01 4.000000e+00 -4.400000e+00 4.930227e-01 4.930227e-01 2.465114e-01 -4.930227e-01 4.100000e+00 -4.400000e+00 4.851001e-01 4.851001e-01 2.425501e-01 -4.851001e-01 4.200000e+00 -4.400000e+00 4.771139e-01 4.771139e-01 2.385570e-01 -4.771139e-01 4.300000e+00 -4.400000e+00 4.690715e-01 4.690715e-01 2.345358e-01 -4.690715e-01 4.400000e+00 -4.400000e+00 4.609803e-01 4.609803e-01 2.304901e-01 -4.609803e-01 4.500000e+00 -4.400000e+00 4.528475e-01 4.528475e-01 2.264237e-01 -4.528475e-01 4.600000e+00 -4.400000e+00 4.446802e-01 4.446802e-01 2.223401e-01 -4.446802e-01 4.700000e+00 -4.400000e+00 4.364856e-01 4.364856e-01 2.182428e-01 -4.364856e-01 4.800000e+00 -4.400000e+00 4.282706e-01 4.282706e-01 2.141353e-01 -4.282706e-01 4.900000e+00 -4.400000e+00 4.200422e-01 4.200422e-01 2.100211e-01 -4.200422e-01 -5.000000e+00 -4.300000e+00 4.190353e-01 4.190353e-01 2.095177e-01 -4.190353e-01 -4.900000e+00 -4.300000e+00 4.274149e-01 4.274149e-01 2.137075e-01 -4.274149e-01 -4.800000e+00 -4.300000e+00 4.357877e-01 4.357877e-01 2.178939e-01 -4.357877e-01 -4.700000e+00 -4.300000e+00 4.441469e-01 4.441469e-01 2.220734e-01 -4.441469e-01 -4.600000e+00 -4.300000e+00 4.524853e-01 4.524853e-01 2.262427e-01 -4.524853e-01 -4.500000e+00 -4.300000e+00 4.607960e-01 4.607960e-01 2.303980e-01 -4.607960e-01 -4.400000e+00 -4.300000e+00 4.690715e-01 4.690715e-01 2.345358e-01 -4.690715e-01 -4.300000e+00 -4.300000e+00 4.773048e-01 4.773048e-01 2.386524e-01 -4.773048e-01 -4.200000e+00 -4.300000e+00 4.854884e-01 4.854884e-01 2.427442e-01 -4.854884e-01 -4.100000e+00 -4.300000e+00 4.936147e-01 4.936147e-01 2.468074e-01 -4.936147e-01 -4.000000e+00 -4.300000e+00 5.016764e-01 5.016764e-01 2.508382e-01 -5.016764e-01 -3.900000e+00 -4.300000e+00 5.096658e-01 5.096658e-01 2.548329e-01 -5.096658e-01 -3.800000e+00 -4.300000e+00 5.175754e-01 5.175754e-01 2.587877e-01 -5.175754e-01 -3.700000e+00 -4.300000e+00 5.253976e-01 5.253976e-01 2.626988e-01 -5.253976e-01 -3.600000e+00 -4.300000e+00 5.331247e-01 5.331247e-01 2.665623e-01 -5.331247e-01 -3.500000e+00 -4.300000e+00 5.407491e-01 5.407491e-01 2.703745e-01 -5.407491e-01 -3.400000e+00 -4.300000e+00 5.482631e-01 5.482631e-01 2.741315e-01 -5.482631e-01 -3.300000e+00 -4.300000e+00 5.556593e-01 5.556593e-01 2.778296e-01 -5.556593e-01 -3.200000e+00 -4.300000e+00 5.629300e-01 5.629300e-01 2.814650e-01 -5.629300e-01 -3.100000e+00 -4.300000e+00 5.700678e-01 5.700678e-01 2.850339e-01 -5.700678e-01 -3.000000e+00 -4.300000e+00 5.770652e-01 5.770652e-01 2.885326e-01 -5.770652e-01 -2.900000e+00 -4.300000e+00 5.839149e-01 5.839149e-01 2.919574e-01 -5.839149e-01 -2.800000e+00 -4.300000e+00 5.906096e-01 5.906096e-01 2.953048e-01 -5.906096e-01 -2.700000e+00 -4.300000e+00 5.971422e-01 5.971422e-01 2.985711e-01 -5.971422e-01 -2.600000e+00 -4.300000e+00 6.035056e-01 6.035056e-01 3.017528e-01 -6.035056e-01 -2.500000e+00 -4.300000e+00 6.096928e-01 6.096928e-01 3.048464e-01 -6.096928e-01 -2.400000e+00 -4.300000e+00 6.156972e-01 6.156972e-01 3.078486e-01 -6.156972e-01 -2.300000e+00 -4.300000e+00 6.215121e-01 6.215121e-01 3.107560e-01 -6.215121e-01 -2.200000e+00 -4.300000e+00 6.271309e-01 6.271309e-01 3.135654e-01 -6.271309e-01 -2.100000e+00 -4.300000e+00 6.325475e-01 6.325475e-01 3.162737e-01 -6.325475e-01 -2.000000e+00 -4.300000e+00 6.377557e-01 6.377557e-01 3.188778e-01 -6.377557e-01 -1.900000e+00 -4.300000e+00 6.427496e-01 6.427496e-01 3.213748e-01 -6.427496e-01 -1.800000e+00 -4.300000e+00 6.475236e-01 6.475236e-01 3.237618e-01 -6.475236e-01 -1.700000e+00 -4.300000e+00 6.520722e-01 6.520722e-01 3.260361e-01 -6.520722e-01 -1.600000e+00 -4.300000e+00 6.563901e-01 6.563901e-01 3.281950e-01 -6.563901e-01 -1.500000e+00 -4.300000e+00 6.604724e-01 6.604724e-01 3.302362e-01 -6.604724e-01 -1.400000e+00 -4.300000e+00 6.643142e-01 6.643142e-01 3.321571e-01 -6.643142e-01 -1.300000e+00 -4.300000e+00 6.679112e-01 6.679112e-01 3.339556e-01 -6.679112e-01 -1.200000e+00 -4.300000e+00 6.712592e-01 6.712592e-01 3.356296e-01 -6.712592e-01 -1.100000e+00 -4.300000e+00 6.743541e-01 6.743541e-01 3.371770e-01 -6.743541e-01 -1.000000e+00 -4.300000e+00 6.771923e-01 6.771923e-01 3.385961e-01 -6.771923e-01 -9.000000e-01 -4.300000e+00 6.797705e-01 6.797705e-01 3.398853e-01 -6.797705e-01 -8.000000e-01 -4.300000e+00 6.820857e-01 6.820857e-01 3.410428e-01 -6.820857e-01 -7.000000e-01 -4.300000e+00 6.841350e-01 6.841350e-01 3.420675e-01 -6.841350e-01 -6.000000e-01 -4.300000e+00 6.859161e-01 6.859161e-01 3.429580e-01 -6.859161e-01 -5.000000e-01 -4.300000e+00 6.874267e-01 6.874267e-01 3.437134e-01 -6.874267e-01 -4.000000e-01 -4.300000e+00 6.886652e-01 6.886652e-01 3.443326e-01 -6.886652e-01 -3.000000e-01 -4.300000e+00 6.896300e-01 6.896300e-01 3.448150e-01 -6.896300e-01 -2.000000e-01 -4.300000e+00 6.903200e-01 6.903200e-01 3.451600e-01 -6.903200e-01 -1.000000e-01 -4.300000e+00 6.907343e-01 6.907343e-01 3.453672e-01 -6.907343e-01 0.000000e+00 -4.300000e+00 6.908725e-01 6.908725e-01 3.454362e-01 -6.908725e-01 1.000000e-01 -4.300000e+00 6.907343e-01 6.907343e-01 3.453672e-01 -6.907343e-01 2.000000e-01 -4.300000e+00 6.903200e-01 6.903200e-01 3.451600e-01 -6.903200e-01 3.000000e-01 -4.300000e+00 6.896300e-01 6.896300e-01 3.448150e-01 -6.896300e-01 4.000000e-01 -4.300000e+00 6.886652e-01 6.886652e-01 3.443326e-01 -6.886652e-01 5.000000e-01 -4.300000e+00 6.874267e-01 6.874267e-01 3.437134e-01 -6.874267e-01 6.000000e-01 -4.300000e+00 6.859161e-01 6.859161e-01 3.429580e-01 -6.859161e-01 7.000000e-01 -4.300000e+00 6.841350e-01 6.841350e-01 3.420675e-01 -6.841350e-01 8.000000e-01 -4.300000e+00 6.820857e-01 6.820857e-01 3.410428e-01 -6.820857e-01 9.000000e-01 -4.300000e+00 6.797705e-01 6.797705e-01 3.398853e-01 -6.797705e-01 1.000000e+00 -4.300000e+00 6.771923e-01 6.771923e-01 3.385961e-01 -6.771923e-01 1.100000e+00 -4.300000e+00 6.743541e-01 6.743541e-01 3.371770e-01 -6.743541e-01 1.200000e+00 -4.300000e+00 6.712592e-01 6.712592e-01 3.356296e-01 -6.712592e-01 1.300000e+00 -4.300000e+00 6.679112e-01 6.679112e-01 3.339556e-01 -6.679112e-01 1.400000e+00 -4.300000e+00 6.643142e-01 6.643142e-01 3.321571e-01 -6.643142e-01 1.500000e+00 -4.300000e+00 6.604724e-01 6.604724e-01 3.302362e-01 -6.604724e-01 1.600000e+00 -4.300000e+00 6.563901e-01 6.563901e-01 3.281950e-01 -6.563901e-01 1.700000e+00 -4.300000e+00 6.520722e-01 6.520722e-01 3.260361e-01 -6.520722e-01 1.800000e+00 -4.300000e+00 6.475236e-01 6.475236e-01 3.237618e-01 -6.475236e-01 1.900000e+00 -4.300000e+00 6.427496e-01 6.427496e-01 3.213748e-01 -6.427496e-01 2.000000e+00 -4.300000e+00 6.377557e-01 6.377557e-01 3.188778e-01 -6.377557e-01 2.100000e+00 -4.300000e+00 6.325475e-01 6.325475e-01 3.162737e-01 -6.325475e-01 2.200000e+00 -4.300000e+00 6.271309e-01 6.271309e-01 3.135654e-01 -6.271309e-01 2.300000e+00 -4.300000e+00 6.215121e-01 6.215121e-01 3.107560e-01 -6.215121e-01 2.400000e+00 -4.300000e+00 6.156972e-01 6.156972e-01 3.078486e-01 -6.156972e-01 2.500000e+00 -4.300000e+00 6.096928e-01 6.096928e-01 3.048464e-01 -6.096928e-01 2.600000e+00 -4.300000e+00 6.035056e-01 6.035056e-01 3.017528e-01 -6.035056e-01 2.700000e+00 -4.300000e+00 5.971422e-01 5.971422e-01 2.985711e-01 -5.971422e-01 2.800000e+00 -4.300000e+00 5.906096e-01 5.906096e-01 2.953048e-01 -5.906096e-01 2.900000e+00 -4.300000e+00 5.839149e-01 5.839149e-01 2.919574e-01 -5.839149e-01 3.000000e+00 -4.300000e+00 5.770652e-01 5.770652e-01 2.885326e-01 -5.770652e-01 3.100000e+00 -4.300000e+00 5.700678e-01 5.700678e-01 2.850339e-01 -5.700678e-01 3.200000e+00 -4.300000e+00 5.629300e-01 5.629300e-01 2.814650e-01 -5.629300e-01 3.300000e+00 -4.300000e+00 5.556593e-01 5.556593e-01 2.778296e-01 -5.556593e-01 3.400000e+00 -4.300000e+00 5.482631e-01 5.482631e-01 2.741315e-01 -5.482631e-01 3.500000e+00 -4.300000e+00 5.407491e-01 5.407491e-01 2.703745e-01 -5.407491e-01 3.600000e+00 -4.300000e+00 5.331247e-01 5.331247e-01 2.665623e-01 -5.331247e-01 3.700000e+00 -4.300000e+00 5.253976e-01 5.253976e-01 2.626988e-01 -5.253976e-01 3.800000e+00 -4.300000e+00 5.175754e-01 5.175754e-01 2.587877e-01 -5.175754e-01 3.900000e+00 -4.300000e+00 5.096658e-01 5.096658e-01 2.548329e-01 -5.096658e-01 4.000000e+00 -4.300000e+00 5.016764e-01 5.016764e-01 2.508382e-01 -5.016764e-01 4.100000e+00 -4.300000e+00 4.936147e-01 4.936147e-01 2.468074e-01 -4.936147e-01 4.200000e+00 -4.300000e+00 4.854884e-01 4.854884e-01 2.427442e-01 -4.854884e-01 4.300000e+00 -4.300000e+00 4.773048e-01 4.773048e-01 2.386524e-01 -4.773048e-01 4.400000e+00 -4.300000e+00 4.690715e-01 4.690715e-01 2.345358e-01 -4.690715e-01 4.500000e+00 -4.300000e+00 4.607960e-01 4.607960e-01 2.303980e-01 -4.607960e-01 4.600000e+00 -4.300000e+00 4.524853e-01 4.524853e-01 2.262427e-01 -4.524853e-01 4.700000e+00 -4.300000e+00 4.441469e-01 4.441469e-01 2.220734e-01 -4.441469e-01 4.800000e+00 -4.300000e+00 4.357877e-01 4.357877e-01 2.178939e-01 -4.357877e-01 4.900000e+00 -4.300000e+00 4.274149e-01 4.274149e-01 2.137075e-01 -4.274149e-01 -5.000000e+00 -4.200000e+00 4.262199e-01 4.262199e-01 2.131099e-01 -4.262199e-01 -4.900000e+00 -4.200000e+00 4.347431e-01 4.347431e-01 2.173716e-01 -4.347431e-01 -4.800000e+00 -4.200000e+00 4.432594e-01 4.432594e-01 2.216297e-01 -4.432594e-01 -4.700000e+00 -4.200000e+00 4.517620e-01 4.517620e-01 2.258810e-01 -4.517620e-01 -4.600000e+00 -4.200000e+00 4.602433e-01 4.602433e-01 2.301217e-01 -4.602433e-01 -4.500000e+00 -4.200000e+00 4.686964e-01 4.686964e-01 2.343482e-01 -4.686964e-01 -4.400000e+00 -4.200000e+00 4.771139e-01 4.771139e-01 2.385570e-01 -4.771139e-01 -4.300000e+00 -4.200000e+00 4.854884e-01 4.854884e-01 2.427442e-01 -4.854884e-01 -4.200000e+00 -4.200000e+00 4.938122e-01 4.938122e-01 2.469061e-01 -4.938122e-01 -4.100000e+00 -4.200000e+00 5.020779e-01 5.020779e-01 2.510389e-01 -5.020779e-01 -4.000000e+00 -4.200000e+00 5.102778e-01 5.102778e-01 2.551389e-01 -5.102778e-01 -3.900000e+00 -4.200000e+00 5.184042e-01 5.184042e-01 2.592021e-01 -5.184042e-01 -3.800000e+00 -4.200000e+00 5.264494e-01 5.264494e-01 2.632247e-01 -5.264494e-01 -3.700000e+00 -4.200000e+00 5.344057e-01 5.344057e-01 2.672029e-01 -5.344057e-01 -3.600000e+00 -4.200000e+00 5.422652e-01 5.422652e-01 2.711326e-01 -5.422652e-01 -3.500000e+00 -4.200000e+00 5.500204e-01 5.500204e-01 2.750102e-01 -5.500204e-01 -3.400000e+00 -4.200000e+00 5.576633e-01 5.576633e-01 2.788316e-01 -5.576633e-01 -3.300000e+00 -4.200000e+00 5.651863e-01 5.651863e-01 2.825931e-01 -5.651863e-01 -3.200000e+00 -4.200000e+00 5.725816e-01 5.725816e-01 2.862908e-01 -5.725816e-01 -3.100000e+00 -4.200000e+00 5.798418e-01 5.798418e-01 2.899209e-01 -5.798418e-01 -3.000000e+00 -4.200000e+00 5.869592e-01 5.869592e-01 2.934796e-01 -5.869592e-01 -2.900000e+00 -4.200000e+00 5.939263e-01 5.939263e-01 2.969632e-01 -5.939263e-01 -2.800000e+00 -4.200000e+00 6.007358e-01 6.007358e-01 3.003679e-01 -6.007358e-01 -2.700000e+00 -4.200000e+00 6.073804e-01 6.073804e-01 3.036902e-01 -6.073804e-01 -2.600000e+00 -4.200000e+00 6.138529e-01 6.138529e-01 3.069264e-01 -6.138529e-01 -2.500000e+00 -4.200000e+00 6.201462e-01 6.201462e-01 3.100731e-01 -6.201462e-01 -2.400000e+00 -4.200000e+00 6.262535e-01 6.262535e-01 3.131268e-01 -6.262535e-01 -2.300000e+00 -4.200000e+00 6.321681e-01 6.321681e-01 3.160840e-01 -6.321681e-01 -2.200000e+00 -4.200000e+00 6.378832e-01 6.378832e-01 3.189416e-01 -6.378832e-01 -2.100000e+00 -4.200000e+00 6.433927e-01 6.433927e-01 3.216964e-01 -6.433927e-01 -2.000000e+00 -4.200000e+00 6.486902e-01 6.486902e-01 3.243451e-01 -6.486902e-01 -1.900000e+00 -4.200000e+00 6.537698e-01 6.537698e-01 3.268849e-01 -6.537698e-01 -1.800000e+00 -4.200000e+00 6.586257e-01 6.586257e-01 3.293128e-01 -6.586257e-01 -1.700000e+00 -4.200000e+00 6.632522e-01 6.632522e-01 3.316261e-01 -6.632522e-01 -1.600000e+00 -4.200000e+00 6.676441e-01 6.676441e-01 3.338221e-01 -6.676441e-01 -1.500000e+00 -4.200000e+00 6.717964e-01 6.717964e-01 3.358982e-01 -6.717964e-01 -1.400000e+00 -4.200000e+00 6.757041e-01 6.757041e-01 3.378521e-01 -6.757041e-01 -1.300000e+00 -4.200000e+00 6.793628e-01 6.793628e-01 3.396814e-01 -6.793628e-01 -1.200000e+00 -4.200000e+00 6.827681e-01 6.827681e-01 3.413841e-01 -6.827681e-01 -1.100000e+00 -4.200000e+00 6.859161e-01 6.859161e-01 3.429580e-01 -6.859161e-01 -1.000000e+00 -4.200000e+00 6.888030e-01 6.888030e-01 3.444015e-01 -6.888030e-01 -9.000000e-01 -4.200000e+00 6.914254e-01 6.914254e-01 3.457127e-01 -6.914254e-01 -8.000000e-01 -4.200000e+00 6.937802e-01 6.937802e-01 3.468901e-01 -6.937802e-01 -7.000000e-01 -4.200000e+00 6.958647e-01 6.958647e-01 3.479324e-01 -6.958647e-01 -6.000000e-01 -4.200000e+00 6.976764e-01 6.976764e-01 3.488382e-01 -6.976764e-01 -5.000000e-01 -4.200000e+00 6.992129e-01 6.992129e-01 3.496065e-01 -6.992129e-01 -4.000000e-01 -4.200000e+00 7.004727e-01 7.004727e-01 3.502363e-01 -7.004727e-01 -3.000000e-01 -4.200000e+00 7.014540e-01 7.014540e-01 3.507270e-01 -7.014540e-01 -2.000000e-01 -4.200000e+00 7.021558e-01 7.021558e-01 3.510779e-01 -7.021558e-01 -1.000000e-01 -4.200000e+00 7.025772e-01 7.025772e-01 3.512886e-01 -7.025772e-01 0.000000e+00 -4.200000e+00 7.027177e-01 7.027177e-01 3.513589e-01 -7.027177e-01 1.000000e-01 -4.200000e+00 7.025772e-01 7.025772e-01 3.512886e-01 -7.025772e-01 2.000000e-01 -4.200000e+00 7.021558e-01 7.021558e-01 3.510779e-01 -7.021558e-01 3.000000e-01 -4.200000e+00 7.014540e-01 7.014540e-01 3.507270e-01 -7.014540e-01 4.000000e-01 -4.200000e+00 7.004727e-01 7.004727e-01 3.502363e-01 -7.004727e-01 5.000000e-01 -4.200000e+00 6.992129e-01 6.992129e-01 3.496065e-01 -6.992129e-01 6.000000e-01 -4.200000e+00 6.976764e-01 6.976764e-01 3.488382e-01 -6.976764e-01 7.000000e-01 -4.200000e+00 6.958647e-01 6.958647e-01 3.479324e-01 -6.958647e-01 8.000000e-01 -4.200000e+00 6.937802e-01 6.937802e-01 3.468901e-01 -6.937802e-01 9.000000e-01 -4.200000e+00 6.914254e-01 6.914254e-01 3.457127e-01 -6.914254e-01 1.000000e+00 -4.200000e+00 6.888030e-01 6.888030e-01 3.444015e-01 -6.888030e-01 1.100000e+00 -4.200000e+00 6.859161e-01 6.859161e-01 3.429580e-01 -6.859161e-01 1.200000e+00 -4.200000e+00 6.827681e-01 6.827681e-01 3.413841e-01 -6.827681e-01 1.300000e+00 -4.200000e+00 6.793628e-01 6.793628e-01 3.396814e-01 -6.793628e-01 1.400000e+00 -4.200000e+00 6.757041e-01 6.757041e-01 3.378521e-01 -6.757041e-01 1.500000e+00 -4.200000e+00 6.717964e-01 6.717964e-01 3.358982e-01 -6.717964e-01 1.600000e+00 -4.200000e+00 6.676441e-01 6.676441e-01 3.338221e-01 -6.676441e-01 1.700000e+00 -4.200000e+00 6.632522e-01 6.632522e-01 3.316261e-01 -6.632522e-01 1.800000e+00 -4.200000e+00 6.586257e-01 6.586257e-01 3.293128e-01 -6.586257e-01 1.900000e+00 -4.200000e+00 6.537698e-01 6.537698e-01 3.268849e-01 -6.537698e-01 2.000000e+00 -4.200000e+00 6.486902e-01 6.486902e-01 3.243451e-01 -6.486902e-01 2.100000e+00 -4.200000e+00 6.433927e-01 6.433927e-01 3.216964e-01 -6.433927e-01 2.200000e+00 -4.200000e+00 6.378832e-01 6.378832e-01 3.189416e-01 -6.378832e-01 2.300000e+00 -4.200000e+00 6.321681e-01 6.321681e-01 3.160840e-01 -6.321681e-01 2.400000e+00 -4.200000e+00 6.262535e-01 6.262535e-01 3.131268e-01 -6.262535e-01 2.500000e+00 -4.200000e+00 6.201462e-01 6.201462e-01 3.100731e-01 -6.201462e-01 2.600000e+00 -4.200000e+00 6.138529e-01 6.138529e-01 3.069264e-01 -6.138529e-01 2.700000e+00 -4.200000e+00 6.073804e-01 6.073804e-01 3.036902e-01 -6.073804e-01 2.800000e+00 -4.200000e+00 6.007358e-01 6.007358e-01 3.003679e-01 -6.007358e-01 2.900000e+00 -4.200000e+00 5.939263e-01 5.939263e-01 2.969632e-01 -5.939263e-01 3.000000e+00 -4.200000e+00 5.869592e-01 5.869592e-01 2.934796e-01 -5.869592e-01 3.100000e+00 -4.200000e+00 5.798418e-01 5.798418e-01 2.899209e-01 -5.798418e-01 3.200000e+00 -4.200000e+00 5.725816e-01 5.725816e-01 2.862908e-01 -5.725816e-01 3.300000e+00 -4.200000e+00 5.651863e-01 5.651863e-01 2.825931e-01 -5.651863e-01 3.400000e+00 -4.200000e+00 5.576633e-01 5.576633e-01 2.788316e-01 -5.576633e-01 3.500000e+00 -4.200000e+00 5.500204e-01 5.500204e-01 2.750102e-01 -5.500204e-01 3.600000e+00 -4.200000e+00 5.422652e-01 5.422652e-01 2.711326e-01 -5.422652e-01 3.700000e+00 -4.200000e+00 5.344057e-01 5.344057e-01 2.672029e-01 -5.344057e-01 3.800000e+00 -4.200000e+00 5.264494e-01 5.264494e-01 2.632247e-01 -5.264494e-01 3.900000e+00 -4.200000e+00 5.184042e-01 5.184042e-01 2.592021e-01 -5.184042e-01 4.000000e+00 -4.200000e+00 5.102778e-01 5.102778e-01 2.551389e-01 -5.102778e-01 4.100000e+00 -4.200000e+00 5.020779e-01 5.020779e-01 2.510389e-01 -5.020779e-01 4.200000e+00 -4.200000e+00 4.938122e-01 4.938122e-01 2.469061e-01 -4.938122e-01 4.300000e+00 -4.200000e+00 4.854884e-01 4.854884e-01 2.427442e-01 -4.854884e-01 4.400000e+00 -4.200000e+00 4.771139e-01 4.771139e-01 2.385570e-01 -4.771139e-01 4.500000e+00 -4.200000e+00 4.686964e-01 4.686964e-01 2.343482e-01 -4.686964e-01 4.600000e+00 -4.200000e+00 4.602433e-01 4.602433e-01 2.301217e-01 -4.602433e-01 4.700000e+00 -4.200000e+00 4.517620e-01 4.517620e-01 2.258810e-01 -4.517620e-01 4.800000e+00 -4.200000e+00 4.432594e-01 4.432594e-01 2.216297e-01 -4.432594e-01 4.900000e+00 -4.200000e+00 4.347431e-01 4.347431e-01 2.173716e-01 -4.347431e-01 -5.000000e+00 -4.100000e+00 4.333541e-01 4.333541e-01 2.166771e-01 -4.333541e-01 -4.900000e+00 -4.100000e+00 4.420200e-01 4.420200e-01 2.210100e-01 -4.420200e-01 -4.800000e+00 -4.100000e+00 4.506789e-01 4.506789e-01 2.253395e-01 -4.506789e-01 -4.700000e+00 -4.100000e+00 4.593238e-01 4.593238e-01 2.296619e-01 -4.593238e-01 -4.600000e+00 -4.100000e+00 4.679471e-01 4.679471e-01 2.339736e-01 -4.679471e-01 -4.500000e+00 -4.100000e+00 4.765417e-01 4.765417e-01 2.382709e-01 -4.765417e-01 -4.400000e+00 -4.100000e+00 4.851001e-01 4.851001e-01 2.425501e-01 -4.851001e-01 -4.300000e+00 -4.100000e+00 4.936147e-01 4.936147e-01 2.468074e-01 -4.936147e-01 -4.200000e+00 -4.100000e+00 5.020779e-01 5.020779e-01 2.510389e-01 -5.020779e-01 -4.100000e+00 -4.100000e+00 5.104820e-01 5.104820e-01 2.552410e-01 -5.104820e-01 -4.000000e+00 -4.100000e+00 5.188191e-01 5.188191e-01 2.594095e-01 -5.188191e-01 -3.900000e+00 -4.100000e+00 5.270815e-01 5.270815e-01 2.635408e-01 -5.270815e-01 -3.800000e+00 -4.100000e+00 5.352615e-01 5.352615e-01 2.676307e-01 -5.352615e-01 -3.700000e+00 -4.100000e+00 5.433509e-01 5.433509e-01 2.716754e-01 -5.433509e-01 -3.600000e+00 -4.100000e+00 5.513420e-01 5.513420e-01 2.756710e-01 -5.513420e-01 -3.500000e+00 -4.100000e+00 5.592269e-01 5.592269e-01 2.796134e-01 -5.592269e-01 -3.400000e+00 -4.100000e+00 5.669977e-01 5.669977e-01 2.834989e-01 -5.669977e-01 -3.300000e+00 -4.100000e+00 5.746467e-01 5.746467e-01 2.873233e-01 -5.746467e-01 -3.200000e+00 -4.100000e+00 5.821658e-01 5.821658e-01 2.910829e-01 -5.821658e-01 -3.100000e+00 -4.100000e+00 5.895475e-01 5.895475e-01 2.947738e-01 -5.895475e-01 -3.000000e+00 -4.100000e+00 5.967840e-01 5.967840e-01 2.983920e-01 -5.967840e-01 -2.900000e+00 -4.100000e+00 6.038678e-01 6.038678e-01 3.019339e-01 -6.038678e-01 -2.800000e+00 -4.100000e+00 6.107913e-01 6.107913e-01 3.053956e-01 -6.107913e-01 -2.700000e+00 -4.100000e+00 6.175471e-01 6.175471e-01 3.087735e-01 -6.175471e-01 -2.600000e+00 -4.100000e+00 6.241279e-01 6.241279e-01 3.120639e-01 -6.241279e-01 -2.500000e+00 -4.100000e+00 6.305265e-01 6.305265e-01 3.152633e-01 -6.305265e-01 -2.400000e+00 -4.100000e+00 6.367361e-01 6.367361e-01 3.183680e-01 -6.367361e-01 -2.300000e+00 -4.100000e+00 6.427497e-01 6.427497e-01 3.213748e-01 -6.427497e-01 -2.200000e+00 -4.100000e+00 6.485605e-01 6.485605e-01 3.242802e-01 -6.485605e-01 -2.100000e+00 -4.100000e+00 6.541622e-01 6.541622e-01 3.270811e-01 -6.541622e-01 -2.000000e+00 -4.100000e+00 6.595483e-01 6.595483e-01 3.297742e-01 -6.595483e-01 -1.900000e+00 -4.100000e+00 6.647130e-01 6.647130e-01 3.323565e-01 -6.647130e-01 -1.800000e+00 -4.100000e+00 6.696501e-01 6.696501e-01 3.348250e-01 -6.696501e-01 -1.700000e+00 -4.100000e+00 6.743541e-01 6.743541e-01 3.371770e-01 -6.743541e-01 -1.600000e+00 -4.100000e+00 6.788195e-01 6.788195e-01 3.394098e-01 -6.788195e-01 -1.500000e+00 -4.100000e+00 6.830413e-01 6.830413e-01 3.415206e-01 -6.830413e-01 -1.400000e+00 -4.100000e+00 6.870144e-01 6.870144e-01 3.435072e-01 -6.870144e-01 -1.300000e+00 -4.100000e+00 6.907343e-01 6.907343e-01 3.453672e-01 -6.907343e-01 -1.200000e+00 -4.100000e+00 6.941966e-01 6.941966e-01 3.470983e-01 -6.941966e-01 -1.100000e+00 -4.100000e+00 6.973973e-01 6.973973e-01 3.486986e-01 -6.973973e-01 -1.000000e+00 -4.100000e+00 7.003325e-01 7.003325e-01 3.501663e-01 -7.003325e-01 -9.000000e-01 -4.100000e+00 7.029989e-01 7.029989e-01 3.514994e-01 -7.029989e-01 -8.000000e-01 -4.100000e+00 7.053931e-01 7.053931e-01 3.526966e-01 -7.053931e-01 -7.000000e-01 -4.100000e+00 7.075125e-01 7.075125e-01 3.537562e-01 -7.075125e-01 -6.000000e-01 -4.100000e+00 7.093544e-01 7.093544e-01 3.546772e-01 -7.093544e-01 -5.000000e-01 -4.100000e+00 7.109167e-01 7.109167e-01 3.554583e-01 -7.109167e-01 -4.000000e-01 -4.100000e+00 7.121975e-01 7.121975e-01 3.560988e-01 -7.121975e-01 -3.000000e-01 -4.100000e+00 7.131953e-01 7.131953e-01 3.565976e-01 -7.131953e-01 -2.000000e-01 -4.100000e+00 7.139089e-01 7.139089e-01 3.569544e-01 -7.139089e-01 -1.000000e-01 -4.100000e+00 7.143373e-01 7.143373e-01 3.571686e-01 -7.143373e-01 0.000000e+00 -4.100000e+00 7.144802e-01 7.144802e-01 3.572401e-01 -7.144802e-01 1.000000e-01 -4.100000e+00 7.143373e-01 7.143373e-01 3.571686e-01 -7.143373e-01 2.000000e-01 -4.100000e+00 7.139089e-01 7.139089e-01 3.569544e-01 -7.139089e-01 3.000000e-01 -4.100000e+00 7.131953e-01 7.131953e-01 3.565976e-01 -7.131953e-01 4.000000e-01 -4.100000e+00 7.121975e-01 7.121975e-01 3.560988e-01 -7.121975e-01 5.000000e-01 -4.100000e+00 7.109167e-01 7.109167e-01 3.554583e-01 -7.109167e-01 6.000000e-01 -4.100000e+00 7.093544e-01 7.093544e-01 3.546772e-01 -7.093544e-01 7.000000e-01 -4.100000e+00 7.075125e-01 7.075125e-01 3.537562e-01 -7.075125e-01 8.000000e-01 -4.100000e+00 7.053931e-01 7.053931e-01 3.526966e-01 -7.053931e-01 9.000000e-01 -4.100000e+00 7.029989e-01 7.029989e-01 3.514994e-01 -7.029989e-01 1.000000e+00 -4.100000e+00 7.003325e-01 7.003325e-01 3.501663e-01 -7.003325e-01 1.100000e+00 -4.100000e+00 6.973973e-01 6.973973e-01 3.486986e-01 -6.973973e-01 1.200000e+00 -4.100000e+00 6.941966e-01 6.941966e-01 3.470983e-01 -6.941966e-01 1.300000e+00 -4.100000e+00 6.907343e-01 6.907343e-01 3.453672e-01 -6.907343e-01 1.400000e+00 -4.100000e+00 6.870144e-01 6.870144e-01 3.435072e-01 -6.870144e-01 1.500000e+00 -4.100000e+00 6.830413e-01 6.830413e-01 3.415206e-01 -6.830413e-01 1.600000e+00 -4.100000e+00 6.788195e-01 6.788195e-01 3.394098e-01 -6.788195e-01 1.700000e+00 -4.100000e+00 6.743541e-01 6.743541e-01 3.371770e-01 -6.743541e-01 1.800000e+00 -4.100000e+00 6.696501e-01 6.696501e-01 3.348250e-01 -6.696501e-01 1.900000e+00 -4.100000e+00 6.647130e-01 6.647130e-01 3.323565e-01 -6.647130e-01 2.000000e+00 -4.100000e+00 6.595483e-01 6.595483e-01 3.297742e-01 -6.595483e-01 2.100000e+00 -4.100000e+00 6.541622e-01 6.541622e-01 3.270811e-01 -6.541622e-01 2.200000e+00 -4.100000e+00 6.485605e-01 6.485605e-01 3.242802e-01 -6.485605e-01 2.300000e+00 -4.100000e+00 6.427497e-01 6.427497e-01 3.213748e-01 -6.427497e-01 2.400000e+00 -4.100000e+00 6.367361e-01 6.367361e-01 3.183680e-01 -6.367361e-01 2.500000e+00 -4.100000e+00 6.305265e-01 6.305265e-01 3.152633e-01 -6.305265e-01 2.600000e+00 -4.100000e+00 6.241279e-01 6.241279e-01 3.120639e-01 -6.241279e-01 2.700000e+00 -4.100000e+00 6.175471e-01 6.175471e-01 3.087735e-01 -6.175471e-01 2.800000e+00 -4.100000e+00 6.107913e-01 6.107913e-01 3.053956e-01 -6.107913e-01 2.900000e+00 -4.100000e+00 6.038678e-01 6.038678e-01 3.019339e-01 -6.038678e-01 3.000000e+00 -4.100000e+00 5.967840e-01 5.967840e-01 2.983920e-01 -5.967840e-01 3.100000e+00 -4.100000e+00 5.895475e-01 5.895475e-01 2.947738e-01 -5.895475e-01 3.200000e+00 -4.100000e+00 5.821658e-01 5.821658e-01 2.910829e-01 -5.821658e-01 3.300000e+00 -4.100000e+00 5.746467e-01 5.746467e-01 2.873233e-01 -5.746467e-01 3.400000e+00 -4.100000e+00 5.669977e-01 5.669977e-01 2.834989e-01 -5.669977e-01 3.500000e+00 -4.100000e+00 5.592269e-01 5.592269e-01 2.796134e-01 -5.592269e-01 3.600000e+00 -4.100000e+00 5.513420e-01 5.513420e-01 2.756710e-01 -5.513420e-01 3.700000e+00 -4.100000e+00 5.433509e-01 5.433509e-01 2.716754e-01 -5.433509e-01 3.800000e+00 -4.100000e+00 5.352615e-01 5.352615e-01 2.676307e-01 -5.352615e-01 3.900000e+00 -4.100000e+00 5.270815e-01 5.270815e-01 2.635408e-01 -5.270815e-01 4.000000e+00 -4.100000e+00 5.188191e-01 5.188191e-01 2.594095e-01 -5.188191e-01 4.100000e+00 -4.100000e+00 5.104820e-01 5.104820e-01 2.552410e-01 -5.104820e-01 4.200000e+00 -4.100000e+00 5.020779e-01 5.020779e-01 2.510389e-01 -5.020779e-01 4.300000e+00 -4.100000e+00 4.936147e-01 4.936147e-01 2.468074e-01 -4.936147e-01 4.400000e+00 -4.100000e+00 4.851001e-01 4.851001e-01 2.425501e-01 -4.851001e-01 4.500000e+00 -4.100000e+00 4.765417e-01 4.765417e-01 2.382709e-01 -4.765417e-01 4.600000e+00 -4.100000e+00 4.679471e-01 4.679471e-01 2.339736e-01 -4.679471e-01 4.700000e+00 -4.100000e+00 4.593238e-01 4.593238e-01 2.296619e-01 -4.593238e-01 4.800000e+00 -4.100000e+00 4.506789e-01 4.506789e-01 2.253395e-01 -4.506789e-01 4.900000e+00 -4.100000e+00 4.420200e-01 4.420200e-01 2.210100e-01 -4.420200e-01 -5.000000e+00 -4.000000e+00 4.404316e-01 4.404316e-01 2.202158e-01 -4.404316e-01 -4.900000e+00 -4.000000e+00 4.492391e-01 4.492391e-01 2.246195e-01 -4.492391e-01 -4.800000e+00 -4.000000e+00 4.580394e-01 4.580394e-01 2.290197e-01 -4.580394e-01 -4.700000e+00 -4.000000e+00 4.668254e-01 4.668254e-01 2.334127e-01 -4.668254e-01 -4.600000e+00 -4.000000e+00 4.755896e-01 4.755896e-01 2.377948e-01 -4.755896e-01 -4.500000e+00 -4.000000e+00 4.843245e-01 4.843245e-01 2.421623e-01 -4.843245e-01 -4.400000e+00 -4.000000e+00 4.930227e-01 4.930227e-01 2.465114e-01 -4.930227e-01 -4.300000e+00 -4.000000e+00 5.016764e-01 5.016764e-01 2.508382e-01 -5.016764e-01 -4.200000e+00 -4.000000e+00 5.102778e-01 5.102778e-01 2.551389e-01 -5.102778e-01 -4.100000e+00 -4.000000e+00 5.188191e-01 5.188191e-01 2.594095e-01 -5.188191e-01 -4.000000e+00 -4.000000e+00 5.272924e-01 5.272924e-01 2.636462e-01 -5.272924e-01 -3.900000e+00 -4.000000e+00 5.356898e-01 5.356898e-01 2.678449e-01 -5.356898e-01 -3.800000e+00 -4.000000e+00 5.440032e-01 5.440032e-01 2.720016e-01 -5.440032e-01 -3.700000e+00 -4.000000e+00 5.522248e-01 5.522248e-01 2.761124e-01 -5.522248e-01 -3.600000e+00 -4.000000e+00 5.603464e-01 5.603464e-01 2.801732e-01 -5.603464e-01 -3.500000e+00 -4.000000e+00 5.683601e-01 5.683601e-01 2.841801e-01 -5.683601e-01 -3.400000e+00 -4.000000e+00 5.762579e-01 5.762579e-01 2.881289e-01 -5.762579e-01 -3.300000e+00 -4.000000e+00 5.840317e-01 5.840317e-01 2.920159e-01 -5.840317e-01 -3.200000e+00 -4.000000e+00 5.916737e-01 5.916737e-01 2.958368e-01 -5.916737e-01 -3.100000e+00 -4.000000e+00 5.991759e-01 5.991759e-01 2.995880e-01 -5.991759e-01 -3.000000e+00 -4.000000e+00 6.065307e-01 6.065307e-01 3.032653e-01 -6.065307e-01 -2.900000e+00 -4.000000e+00 6.137301e-01 6.137301e-01 3.068650e-01 -6.137301e-01 -2.800000e+00 -4.000000e+00 6.207666e-01 6.207666e-01 3.103833e-01 -6.207666e-01 -2.700000e+00 -4.000000e+00 6.276328e-01 6.276328e-01 3.138164e-01 -6.276328e-01 -2.600000e+00 -4.000000e+00 6.343211e-01 6.343211e-01 3.171605e-01 -6.343211e-01 -2.500000e+00 -4.000000e+00 6.408243e-01 6.408243e-01 3.204121e-01 -6.408243e-01 -2.400000e+00 -4.000000e+00 6.471352e-01 6.471352e-01 3.235676e-01 -6.471352e-01 -2.300000e+00 -4.000000e+00 6.532469e-01 6.532469e-01 3.266235e-01 -6.532469e-01 -2.200000e+00 -4.000000e+00 6.591527e-01 6.591527e-01 3.295764e-01 -6.591527e-01 -2.100000e+00 -4.000000e+00 6.648459e-01 6.648459e-01 3.324229e-01 -6.648459e-01 -2.000000e+00 -4.000000e+00 6.703200e-01 6.703200e-01 3.351600e-01 -6.703200e-01 -1.900000e+00 -4.000000e+00 6.755690e-01 6.755690e-01 3.377845e-01 -6.755690e-01 -1.800000e+00 -4.000000e+00 6.805868e-01 6.805868e-01 3.402934e-01 -6.805868e-01 -1.700000e+00 -4.000000e+00 6.853675e-01 6.853675e-01 3.426838e-01 -6.853675e-01 -1.600000e+00 -4.000000e+00 6.899059e-01 6.899059e-01 3.449530e-01 -6.899059e-01 -1.500000e+00 -4.000000e+00 6.941966e-01 6.941966e-01 3.470983e-01 -6.941966e-01 -1.400000e+00 -4.000000e+00 6.982347e-01 6.982347e-01 3.491173e-01 -6.982347e-01 -1.300000e+00 -4.000000e+00 7.020153e-01 7.020153e-01 3.510077e-01 -7.020153e-01 -1.200000e+00 -4.000000e+00 7.055342e-01 7.055342e-01 3.527671e-01 -7.055342e-01 -1.100000e+00 -4.000000e+00 7.087871e-01 7.087871e-01 3.543936e-01 -7.087871e-01 -1.000000e+00 -4.000000e+00 7.117703e-01 7.117703e-01 3.558851e-01 -7.117703e-01 -9.000000e-01 -4.000000e+00 7.144802e-01 7.144802e-01 3.572401e-01 -7.144802e-01 -8.000000e-01 -4.000000e+00 7.169135e-01 7.169135e-01 3.584568e-01 -7.169135e-01 -7.000000e-01 -4.000000e+00 7.190675e-01 7.190675e-01 3.595338e-01 -7.190675e-01 -6.000000e-01 -4.000000e+00 7.209395e-01 7.209395e-01 3.604698e-01 -7.209395e-01 -5.000000e-01 -4.000000e+00 7.225273e-01 7.225273e-01 3.612637e-01 -7.225273e-01 -4.000000e-01 -4.000000e+00 7.238291e-01 7.238291e-01 3.619145e-01 -7.238291e-01 -3.000000e-01 -4.000000e+00 7.248431e-01 7.248431e-01 3.624216e-01 -7.248431e-01 -2.000000e-01 -4.000000e+00 7.255683e-01 7.255683e-01 3.627841e-01 -7.255683e-01 -1.000000e-01 -4.000000e+00 7.260038e-01 7.260038e-01 3.630019e-01 -7.260038e-01 0.000000e+00 -4.000000e+00 7.261490e-01 7.261490e-01 3.630745e-01 -7.261490e-01 1.000000e-01 -4.000000e+00 7.260038e-01 7.260038e-01 3.630019e-01 -7.260038e-01 2.000000e-01 -4.000000e+00 7.255683e-01 7.255683e-01 3.627841e-01 -7.255683e-01 3.000000e-01 -4.000000e+00 7.248431e-01 7.248431e-01 3.624216e-01 -7.248431e-01 4.000000e-01 -4.000000e+00 7.238291e-01 7.238291e-01 3.619145e-01 -7.238291e-01 5.000000e-01 -4.000000e+00 7.225273e-01 7.225273e-01 3.612637e-01 -7.225273e-01 6.000000e-01 -4.000000e+00 7.209395e-01 7.209395e-01 3.604698e-01 -7.209395e-01 7.000000e-01 -4.000000e+00 7.190675e-01 7.190675e-01 3.595338e-01 -7.190675e-01 8.000000e-01 -4.000000e+00 7.169135e-01 7.169135e-01 3.584568e-01 -7.169135e-01 9.000000e-01 -4.000000e+00 7.144802e-01 7.144802e-01 3.572401e-01 -7.144802e-01 1.000000e+00 -4.000000e+00 7.117703e-01 7.117703e-01 3.558851e-01 -7.117703e-01 1.100000e+00 -4.000000e+00 7.087871e-01 7.087871e-01 3.543936e-01 -7.087871e-01 1.200000e+00 -4.000000e+00 7.055342e-01 7.055342e-01 3.527671e-01 -7.055342e-01 1.300000e+00 -4.000000e+00 7.020153e-01 7.020153e-01 3.510077e-01 -7.020153e-01 1.400000e+00 -4.000000e+00 6.982347e-01 6.982347e-01 3.491173e-01 -6.982347e-01 1.500000e+00 -4.000000e+00 6.941966e-01 6.941966e-01 3.470983e-01 -6.941966e-01 1.600000e+00 -4.000000e+00 6.899059e-01 6.899059e-01 3.449530e-01 -6.899059e-01 1.700000e+00 -4.000000e+00 6.853675e-01 6.853675e-01 3.426838e-01 -6.853675e-01 1.800000e+00 -4.000000e+00 6.805868e-01 6.805868e-01 3.402934e-01 -6.805868e-01 1.900000e+00 -4.000000e+00 6.755690e-01 6.755690e-01 3.377845e-01 -6.755690e-01 2.000000e+00 -4.000000e+00 6.703200e-01 6.703200e-01 3.351600e-01 -6.703200e-01 2.100000e+00 -4.000000e+00 6.648459e-01 6.648459e-01 3.324229e-01 -6.648459e-01 2.200000e+00 -4.000000e+00 6.591527e-01 6.591527e-01 3.295764e-01 -6.591527e-01 2.300000e+00 -4.000000e+00 6.532469e-01 6.532469e-01 3.266235e-01 -6.532469e-01 2.400000e+00 -4.000000e+00 6.471352e-01 6.471352e-01 3.235676e-01 -6.471352e-01 2.500000e+00 -4.000000e+00 6.408243e-01 6.408243e-01 3.204121e-01 -6.408243e-01 2.600000e+00 -4.000000e+00 6.343211e-01 6.343211e-01 3.171605e-01 -6.343211e-01 2.700000e+00 -4.000000e+00 6.276328e-01 6.276328e-01 3.138164e-01 -6.276328e-01 2.800000e+00 -4.000000e+00 6.207666e-01 6.207666e-01 3.103833e-01 -6.207666e-01 2.900000e+00 -4.000000e+00 6.137301e-01 6.137301e-01 3.068650e-01 -6.137301e-01 3.000000e+00 -4.000000e+00 6.065307e-01 6.065307e-01 3.032653e-01 -6.065307e-01 3.100000e+00 -4.000000e+00 5.991759e-01 5.991759e-01 2.995880e-01 -5.991759e-01 3.200000e+00 -4.000000e+00 5.916737e-01 5.916737e-01 2.958368e-01 -5.916737e-01 3.300000e+00 -4.000000e+00 5.840317e-01 5.840317e-01 2.920159e-01 -5.840317e-01 3.400000e+00 -4.000000e+00 5.762579e-01 5.762579e-01 2.881289e-01 -5.762579e-01 3.500000e+00 -4.000000e+00 5.683601e-01 5.683601e-01 2.841801e-01 -5.683601e-01 3.600000e+00 -4.000000e+00 5.603464e-01 5.603464e-01 2.801732e-01 -5.603464e-01 3.700000e+00 -4.000000e+00 5.522248e-01 5.522248e-01 2.761124e-01 -5.522248e-01 3.800000e+00 -4.000000e+00 5.440032e-01 5.440032e-01 2.720016e-01 -5.440032e-01 3.900000e+00 -4.000000e+00 5.356898e-01 5.356898e-01 2.678449e-01 -5.356898e-01 4.000000e+00 -4.000000e+00 5.272924e-01 5.272924e-01 2.636462e-01 -5.272924e-01 4.100000e+00 -4.000000e+00 5.188191e-01 5.188191e-01 2.594095e-01 -5.188191e-01 4.200000e+00 -4.000000e+00 5.102778e-01 5.102778e-01 2.551389e-01 -5.102778e-01 4.300000e+00 -4.000000e+00 5.016764e-01 5.016764e-01 2.508382e-01 -5.016764e-01 4.400000e+00 -4.000000e+00 4.930227e-01 4.930227e-01 2.465114e-01 -4.930227e-01 4.500000e+00 -4.000000e+00 4.843245e-01 4.843245e-01 2.421623e-01 -4.843245e-01 4.600000e+00 -4.000000e+00 4.755896e-01 4.755896e-01 2.377948e-01 -4.755896e-01 4.700000e+00 -4.000000e+00 4.668254e-01 4.668254e-01 2.334127e-01 -4.668254e-01 4.800000e+00 -4.000000e+00 4.580394e-01 4.580394e-01 2.290197e-01 -4.580394e-01 4.900000e+00 -4.000000e+00 4.492391e-01 4.492391e-01 2.246195e-01 -4.492391e-01 -5.000000e+00 -3.900000e+00 4.474457e-01 4.474457e-01 2.237229e-01 -4.474457e-01 -4.900000e+00 -3.900000e+00 4.563934e-01 4.563934e-01 2.281967e-01 -4.563934e-01 -4.800000e+00 -3.900000e+00 4.653339e-01 4.653339e-01 2.326670e-01 -4.653339e-01 -4.700000e+00 -3.900000e+00 4.742598e-01 4.742598e-01 2.371299e-01 -4.742598e-01 -4.600000e+00 -3.900000e+00 4.831636e-01 4.831636e-01 2.415818e-01 -4.831636e-01 -4.500000e+00 -3.900000e+00 4.920377e-01 4.920377e-01 2.460188e-01 -4.920377e-01 -4.400000e+00 -3.900000e+00 5.008743e-01 5.008743e-01 2.504372e-01 -5.008743e-01 -4.300000e+00 -3.900000e+00 5.096658e-01 5.096658e-01 2.548329e-01 -5.096658e-01 -4.200000e+00 -3.900000e+00 5.184042e-01 5.184042e-01 2.592021e-01 -5.184042e-01 -4.100000e+00 -3.900000e+00 5.270815e-01 5.270815e-01 2.635408e-01 -5.270815e-01 -4.000000e+00 -3.900000e+00 5.356898e-01 5.356898e-01 2.678449e-01 -5.356898e-01 -3.900000e+00 -3.900000e+00 5.442209e-01 5.442209e-01 2.721105e-01 -5.442209e-01 -3.800000e+00 -3.900000e+00 5.526668e-01 5.526668e-01 2.763334e-01 -5.526668e-01 -3.700000e+00 -3.900000e+00 5.610192e-01 5.610192e-01 2.805096e-01 -5.610192e-01 -3.600000e+00 -3.900000e+00 5.692703e-01 5.692703e-01 2.846351e-01 -5.692703e-01 -3.500000e+00 -3.900000e+00 5.774115e-01 5.774115e-01 2.887058e-01 -5.774115e-01 -3.400000e+00 -3.900000e+00 5.854350e-01 5.854350e-01 2.927175e-01 -5.854350e-01 -3.300000e+00 -3.900000e+00 5.933327e-01 5.933327e-01 2.966664e-01 -5.933327e-01 -3.200000e+00 -3.900000e+00 6.010964e-01 6.010964e-01 3.005482e-01 -6.010964e-01 -3.100000e+00 -3.900000e+00 6.087181e-01 6.087181e-01 3.043590e-01 -6.087181e-01 -3.000000e+00 -3.900000e+00 6.161900e-01 6.161900e-01 3.080950e-01 -6.161900e-01 -2.900000e+00 -3.900000e+00 6.235040e-01 6.235040e-01 3.117520e-01 -6.235040e-01 -2.800000e+00 -3.900000e+00 6.306527e-01 6.306527e-01 3.153263e-01 -6.306527e-01 -2.700000e+00 -3.900000e+00 6.376281e-01 6.376281e-01 3.188141e-01 -6.376281e-01 -2.600000e+00 -3.900000e+00 6.444229e-01 6.444229e-01 3.222115e-01 -6.444229e-01 -2.500000e+00 -3.900000e+00 6.510297e-01 6.510297e-01 3.255149e-01 -6.510297e-01 -2.400000e+00 -3.900000e+00 6.574411e-01 6.574411e-01 3.287206e-01 -6.574411e-01 -2.300000e+00 -3.900000e+00 6.636502e-01 6.636502e-01 3.318251e-01 -6.636502e-01 -2.200000e+00 -3.900000e+00 6.696500e-01 6.696500e-01 3.348250e-01 -6.696500e-01 -2.100000e+00 -3.900000e+00 6.754339e-01 6.754339e-01 3.377169e-01 -6.754339e-01 -2.000000e+00 -3.900000e+00 6.809952e-01 6.809952e-01 3.404976e-01 -6.809952e-01 -1.900000e+00 -3.900000e+00 6.863278e-01 6.863278e-01 3.431639e-01 -6.863278e-01 -1.800000e+00 -3.900000e+00 6.914254e-01 6.914254e-01 3.457127e-01 -6.914254e-01 -1.700000e+00 -3.900000e+00 6.962823e-01 6.962823e-01 3.481412e-01 -6.962823e-01 -1.600000e+00 -3.900000e+00 7.008930e-01 7.008930e-01 3.504465e-01 -7.008930e-01 -1.500000e+00 -3.900000e+00 7.052521e-01 7.052521e-01 3.526260e-01 -7.052521e-01 -1.400000e+00 -3.900000e+00 7.093544e-01 7.093544e-01 3.546772e-01 -7.093544e-01 -1.300000e+00 -3.900000e+00 7.131953e-01 7.131953e-01 3.565976e-01 -7.131953e-01 -1.200000e+00 -3.900000e+00 7.167702e-01 7.167702e-01 3.583851e-01 -7.167702e-01 -1.100000e+00 -3.900000e+00 7.200749e-01 7.200749e-01 3.600374e-01 -7.200749e-01 -1.000000e+00 -3.900000e+00 7.231056e-01 7.231056e-01 3.615528e-01 -7.231056e-01 -9.000000e-01 -3.900000e+00 7.258586e-01 7.258586e-01 3.629293e-01 -7.258586e-01 -8.000000e-01 -3.900000e+00 7.283307e-01 7.283307e-01 3.641654e-01 -7.283307e-01 -7.000000e-01 -3.900000e+00 7.305190e-01 7.305190e-01 3.652595e-01 -7.305190e-01 -6.000000e-01 -3.900000e+00 7.324208e-01 7.324208e-01 3.662104e-01 -7.324208e-01 -5.000000e-01 -3.900000e+00 7.340339e-01 7.340339e-01 3.670170e-01 -7.340339e-01 -4.000000e-01 -3.900000e+00 7.353564e-01 7.353564e-01 3.676782e-01 -7.353564e-01 -3.000000e-01 -3.900000e+00 7.363866e-01 7.363866e-01 3.681933e-01 -7.363866e-01 -2.000000e-01 -3.900000e+00 7.371234e-01 7.371234e-01 3.685617e-01 -7.371234e-01 -1.000000e-01 -3.900000e+00 7.375658e-01 7.375658e-01 3.687829e-01 -7.375658e-01 0.000000e+00 -3.900000e+00 7.377133e-01 7.377133e-01 3.688566e-01 -7.377133e-01 1.000000e-01 -3.900000e+00 7.375658e-01 7.375658e-01 3.687829e-01 -7.375658e-01 2.000000e-01 -3.900000e+00 7.371234e-01 7.371234e-01 3.685617e-01 -7.371234e-01 3.000000e-01 -3.900000e+00 7.363866e-01 7.363866e-01 3.681933e-01 -7.363866e-01 4.000000e-01 -3.900000e+00 7.353564e-01 7.353564e-01 3.676782e-01 -7.353564e-01 5.000000e-01 -3.900000e+00 7.340339e-01 7.340339e-01 3.670170e-01 -7.340339e-01 6.000000e-01 -3.900000e+00 7.324208e-01 7.324208e-01 3.662104e-01 -7.324208e-01 7.000000e-01 -3.900000e+00 7.305190e-01 7.305190e-01 3.652595e-01 -7.305190e-01 8.000000e-01 -3.900000e+00 7.283307e-01 7.283307e-01 3.641654e-01 -7.283307e-01 9.000000e-01 -3.900000e+00 7.258586e-01 7.258586e-01 3.629293e-01 -7.258586e-01 1.000000e+00 -3.900000e+00 7.231056e-01 7.231056e-01 3.615528e-01 -7.231056e-01 1.100000e+00 -3.900000e+00 7.200749e-01 7.200749e-01 3.600374e-01 -7.200749e-01 1.200000e+00 -3.900000e+00 7.167702e-01 7.167702e-01 3.583851e-01 -7.167702e-01 1.300000e+00 -3.900000e+00 7.131953e-01 7.131953e-01 3.565976e-01 -7.131953e-01 1.400000e+00 -3.900000e+00 7.093544e-01 7.093544e-01 3.546772e-01 -7.093544e-01 1.500000e+00 -3.900000e+00 7.052521e-01 7.052521e-01 3.526260e-01 -7.052521e-01 1.600000e+00 -3.900000e+00 7.008930e-01 7.008930e-01 3.504465e-01 -7.008930e-01 1.700000e+00 -3.900000e+00 6.962823e-01 6.962823e-01 3.481412e-01 -6.962823e-01 1.800000e+00 -3.900000e+00 6.914254e-01 6.914254e-01 3.457127e-01 -6.914254e-01 1.900000e+00 -3.900000e+00 6.863278e-01 6.863278e-01 3.431639e-01 -6.863278e-01 2.000000e+00 -3.900000e+00 6.809952e-01 6.809952e-01 3.404976e-01 -6.809952e-01 2.100000e+00 -3.900000e+00 6.754339e-01 6.754339e-01 3.377169e-01 -6.754339e-01 2.200000e+00 -3.900000e+00 6.696500e-01 6.696500e-01 3.348250e-01 -6.696500e-01 2.300000e+00 -3.900000e+00 6.636502e-01 6.636502e-01 3.318251e-01 -6.636502e-01 2.400000e+00 -3.900000e+00 6.574411e-01 6.574411e-01 3.287206e-01 -6.574411e-01 2.500000e+00 -3.900000e+00 6.510297e-01 6.510297e-01 3.255149e-01 -6.510297e-01 2.600000e+00 -3.900000e+00 6.444229e-01 6.444229e-01 3.222115e-01 -6.444229e-01 2.700000e+00 -3.900000e+00 6.376281e-01 6.376281e-01 3.188141e-01 -6.376281e-01 2.800000e+00 -3.900000e+00 6.306527e-01 6.306527e-01 3.153263e-01 -6.306527e-01 2.900000e+00 -3.900000e+00 6.235040e-01 6.235040e-01 3.117520e-01 -6.235040e-01 3.000000e+00 -3.900000e+00 6.161900e-01 6.161900e-01 3.080950e-01 -6.161900e-01 3.100000e+00 -3.900000e+00 6.087181e-01 6.087181e-01 3.043590e-01 -6.087181e-01 3.200000e+00 -3.900000e+00 6.010964e-01 6.010964e-01 3.005482e-01 -6.010964e-01 3.300000e+00 -3.900000e+00 5.933327e-01 5.933327e-01 2.966664e-01 -5.933327e-01 3.400000e+00 -3.900000e+00 5.854350e-01 5.854350e-01 2.927175e-01 -5.854350e-01 3.500000e+00 -3.900000e+00 5.774115e-01 5.774115e-01 2.887058e-01 -5.774115e-01 3.600000e+00 -3.900000e+00 5.692703e-01 5.692703e-01 2.846351e-01 -5.692703e-01 3.700000e+00 -3.900000e+00 5.610192e-01 5.610192e-01 2.805096e-01 -5.610192e-01 3.800000e+00 -3.900000e+00 5.526668e-01 5.526668e-01 2.763334e-01 -5.526668e-01 3.900000e+00 -3.900000e+00 5.442209e-01 5.442209e-01 2.721105e-01 -5.442209e-01 4.000000e+00 -3.900000e+00 5.356898e-01 5.356898e-01 2.678449e-01 -5.356898e-01 4.100000e+00 -3.900000e+00 5.270815e-01 5.270815e-01 2.635408e-01 -5.270815e-01 4.200000e+00 -3.900000e+00 5.184042e-01 5.184042e-01 2.592021e-01 -5.184042e-01 4.300000e+00 -3.900000e+00 5.096658e-01 5.096658e-01 2.548329e-01 -5.096658e-01 4.400000e+00 -3.900000e+00 5.008743e-01 5.008743e-01 2.504372e-01 -5.008743e-01 4.500000e+00 -3.900000e+00 4.920377e-01 4.920377e-01 2.460188e-01 -4.920377e-01 4.600000e+00 -3.900000e+00 4.831636e-01 4.831636e-01 2.415818e-01 -4.831636e-01 4.700000e+00 -3.900000e+00 4.742598e-01 4.742598e-01 2.371299e-01 -4.742598e-01 4.800000e+00 -3.900000e+00 4.653339e-01 4.653339e-01 2.326670e-01 -4.653339e-01 4.900000e+00 -3.900000e+00 4.563934e-01 4.563934e-01 2.281967e-01 -4.563934e-01 -5.000000e+00 -3.800000e+00 4.543897e-01 4.543897e-01 2.271949e-01 -4.543897e-01 -4.900000e+00 -3.800000e+00 4.634763e-01 4.634763e-01 2.317382e-01 -4.634763e-01 -4.800000e+00 -3.800000e+00 4.725555e-01 4.725555e-01 2.362778e-01 -4.725555e-01 -4.700000e+00 -3.800000e+00 4.816200e-01 4.816200e-01 2.408100e-01 -4.816200e-01 -4.600000e+00 -3.800000e+00 4.906619e-01 4.906619e-01 2.453310e-01 -4.906619e-01 -4.500000e+00 -3.800000e+00 4.996737e-01 4.996737e-01 2.498369e-01 -4.996737e-01 -4.400000e+00 -3.800000e+00 5.086475e-01 5.086475e-01 2.543238e-01 -5.086475e-01 -4.300000e+00 -3.800000e+00 5.175754e-01 5.175754e-01 2.587877e-01 -5.175754e-01 -4.200000e+00 -3.800000e+00 5.264494e-01 5.264494e-01 2.632247e-01 -5.264494e-01 -4.100000e+00 -3.800000e+00 5.352615e-01 5.352615e-01 2.676307e-01 -5.352615e-01 -4.000000e+00 -3.800000e+00 5.440032e-01 5.440032e-01 2.720016e-01 -5.440032e-01 -3.900000e+00 -3.800000e+00 5.526668e-01 5.526668e-01 2.763334e-01 -5.526668e-01 -3.800000e+00 -3.800000e+00 5.612437e-01 5.612437e-01 2.806219e-01 -5.612437e-01 -3.700000e+00 -3.800000e+00 5.697258e-01 5.697258e-01 2.848629e-01 -5.697258e-01 -3.600000e+00 -3.800000e+00 5.781049e-01 5.781049e-01 2.890524e-01 -5.781049e-01 -3.500000e+00 -3.800000e+00 5.863725e-01 5.863725e-01 2.931862e-01 -5.863725e-01 -3.400000e+00 -3.800000e+00 5.945206e-01 5.945206e-01 2.972603e-01 -5.945206e-01 -3.300000e+00 -3.800000e+00 6.025407e-01 6.025407e-01 3.012704e-01 -6.025407e-01 -3.200000e+00 -3.800000e+00 6.104249e-01 6.104249e-01 3.052124e-01 -6.104249e-01 -3.100000e+00 -3.800000e+00 6.181649e-01 6.181649e-01 3.090824e-01 -6.181649e-01 -3.000000e+00 -3.800000e+00 6.257527e-01 6.257527e-01 3.128763e-01 -6.257527e-01 -2.900000e+00 -3.800000e+00 6.331803e-01 6.331803e-01 3.165902e-01 -6.331803e-01 -2.800000e+00 -3.800000e+00 6.404399e-01 6.404399e-01 3.202199e-01 -6.404399e-01 -2.700000e+00 -3.800000e+00 6.475236e-01 6.475236e-01 3.237618e-01 -6.475236e-01 -2.600000e+00 -3.800000e+00 6.544239e-01 6.544239e-01 3.272119e-01 -6.544239e-01 -2.500000e+00 -3.800000e+00 6.611332e-01 6.611332e-01 3.305666e-01 -6.611332e-01 -2.400000e+00 -3.800000e+00 6.676441e-01 6.676441e-01 3.338220e-01 -6.676441e-01 -2.300000e+00 -3.800000e+00 6.739496e-01 6.739496e-01 3.369748e-01 -6.739496e-01 -2.200000e+00 -3.800000e+00 6.800425e-01 6.800425e-01 3.400213e-01 -6.800425e-01 -2.100000e+00 -3.800000e+00 6.859161e-01 6.859161e-01 3.429580e-01 -6.859161e-01 -2.000000e+00 -3.800000e+00 6.915637e-01 6.915637e-01 3.457819e-01 -6.915637e-01 -1.900000e+00 -3.800000e+00 6.969790e-01 6.969790e-01 3.484895e-01 -6.969790e-01 -1.800000e+00 -3.800000e+00 7.021558e-01 7.021558e-01 3.510779e-01 -7.021558e-01 -1.700000e+00 -3.800000e+00 7.070881e-01 7.070881e-01 3.535441e-01 -7.070881e-01 -1.600000e+00 -3.800000e+00 7.117703e-01 7.117703e-01 3.558851e-01 -7.117703e-01 -1.500000e+00 -3.800000e+00 7.161970e-01 7.161970e-01 3.580985e-01 -7.161970e-01 -1.400000e+00 -3.800000e+00 7.203630e-01 7.203630e-01 3.601815e-01 -7.203630e-01 -1.300000e+00 -3.800000e+00 7.242635e-01 7.242635e-01 3.621317e-01 -7.242635e-01 -1.200000e+00 -3.800000e+00 7.278939e-01 7.278939e-01 3.639469e-01 -7.278939e-01 -1.100000e+00 -3.800000e+00 7.312499e-01 7.312499e-01 3.656250e-01 -7.312499e-01 -1.000000e+00 -3.800000e+00 7.343276e-01 7.343276e-01 3.671638e-01 -7.343276e-01 -9.000000e-01 -3.800000e+00 7.371234e-01 7.371234e-01 3.685617e-01 -7.371234e-01 -8.000000e-01 -3.800000e+00 7.396339e-01 7.396339e-01 3.698169e-01 -7.396339e-01 -7.000000e-01 -3.800000e+00 7.418561e-01 7.418561e-01 3.709280e-01 -7.418561e-01 -6.000000e-01 -3.800000e+00 7.437874e-01 7.437874e-01 3.718937e-01 -7.437874e-01 -5.000000e-01 -3.800000e+00 7.454256e-01 7.454256e-01 3.727128e-01 -7.454256e-01 -4.000000e-01 -3.800000e+00 7.467685e-01 7.467685e-01 3.733843e-01 -7.467685e-01 -3.000000e-01 -3.800000e+00 7.478147e-01 7.478147e-01 3.739074e-01 -7.478147e-01 -2.000000e-01 -3.800000e+00 7.485629e-01 7.485629e-01 3.742815e-01 -7.485629e-01 -1.000000e-01 -3.800000e+00 7.490122e-01 7.490122e-01 3.745061e-01 -7.490122e-01 0.000000e+00 -3.800000e+00 7.491620e-01 7.491620e-01 3.745810e-01 -7.491620e-01 1.000000e-01 -3.800000e+00 7.490122e-01 7.490122e-01 3.745061e-01 -7.490122e-01 2.000000e-01 -3.800000e+00 7.485629e-01 7.485629e-01 3.742815e-01 -7.485629e-01 3.000000e-01 -3.800000e+00 7.478147e-01 7.478147e-01 3.739074e-01 -7.478147e-01 4.000000e-01 -3.800000e+00 7.467685e-01 7.467685e-01 3.733843e-01 -7.467685e-01 5.000000e-01 -3.800000e+00 7.454256e-01 7.454256e-01 3.727128e-01 -7.454256e-01 6.000000e-01 -3.800000e+00 7.437874e-01 7.437874e-01 3.718937e-01 -7.437874e-01 7.000000e-01 -3.800000e+00 7.418561e-01 7.418561e-01 3.709280e-01 -7.418561e-01 8.000000e-01 -3.800000e+00 7.396339e-01 7.396339e-01 3.698169e-01 -7.396339e-01 9.000000e-01 -3.800000e+00 7.371234e-01 7.371234e-01 3.685617e-01 -7.371234e-01 1.000000e+00 -3.800000e+00 7.343276e-01 7.343276e-01 3.671638e-01 -7.343276e-01 1.100000e+00 -3.800000e+00 7.312499e-01 7.312499e-01 3.656250e-01 -7.312499e-01 1.200000e+00 -3.800000e+00 7.278939e-01 7.278939e-01 3.639469e-01 -7.278939e-01 1.300000e+00 -3.800000e+00 7.242635e-01 7.242635e-01 3.621317e-01 -7.242635e-01 1.400000e+00 -3.800000e+00 7.203630e-01 7.203630e-01 3.601815e-01 -7.203630e-01 1.500000e+00 -3.800000e+00 7.161970e-01 7.161970e-01 3.580985e-01 -7.161970e-01 1.600000e+00 -3.800000e+00 7.117703e-01 7.117703e-01 3.558851e-01 -7.117703e-01 1.700000e+00 -3.800000e+00 7.070881e-01 7.070881e-01 3.535441e-01 -7.070881e-01 1.800000e+00 -3.800000e+00 7.021558e-01 7.021558e-01 3.510779e-01 -7.021558e-01 1.900000e+00 -3.800000e+00 6.969790e-01 6.969790e-01 3.484895e-01 -6.969790e-01 2.000000e+00 -3.800000e+00 6.915637e-01 6.915637e-01 3.457819e-01 -6.915637e-01 2.100000e+00 -3.800000e+00 6.859161e-01 6.859161e-01 3.429580e-01 -6.859161e-01 2.200000e+00 -3.800000e+00 6.800425e-01 6.800425e-01 3.400213e-01 -6.800425e-01 2.300000e+00 -3.800000e+00 6.739496e-01 6.739496e-01 3.369748e-01 -6.739496e-01 2.400000e+00 -3.800000e+00 6.676441e-01 6.676441e-01 3.338220e-01 -6.676441e-01 2.500000e+00 -3.800000e+00 6.611332e-01 6.611332e-01 3.305666e-01 -6.611332e-01 2.600000e+00 -3.800000e+00 6.544239e-01 6.544239e-01 3.272119e-01 -6.544239e-01 2.700000e+00 -3.800000e+00 6.475236e-01 6.475236e-01 3.237618e-01 -6.475236e-01 2.800000e+00 -3.800000e+00 6.404399e-01 6.404399e-01 3.202199e-01 -6.404399e-01 2.900000e+00 -3.800000e+00 6.331803e-01 6.331803e-01 3.165902e-01 -6.331803e-01 3.000000e+00 -3.800000e+00 6.257527e-01 6.257527e-01 3.128763e-01 -6.257527e-01 3.100000e+00 -3.800000e+00 6.181649e-01 6.181649e-01 3.090824e-01 -6.181649e-01 3.200000e+00 -3.800000e+00 6.104249e-01 6.104249e-01 3.052124e-01 -6.104249e-01 3.300000e+00 -3.800000e+00 6.025407e-01 6.025407e-01 3.012704e-01 -6.025407e-01 3.400000e+00 -3.800000e+00 5.945206e-01 5.945206e-01 2.972603e-01 -5.945206e-01 3.500000e+00 -3.800000e+00 5.863725e-01 5.863725e-01 2.931862e-01 -5.863725e-01 3.600000e+00 -3.800000e+00 5.781049e-01 5.781049e-01 2.890524e-01 -5.781049e-01 3.700000e+00 -3.800000e+00 5.697258e-01 5.697258e-01 2.848629e-01 -5.697258e-01 3.800000e+00 -3.800000e+00 5.612437e-01 5.612437e-01 2.806219e-01 -5.612437e-01 3.900000e+00 -3.800000e+00 5.526668e-01 5.526668e-01 2.763334e-01 -5.526668e-01 4.000000e+00 -3.800000e+00 5.440032e-01 5.440032e-01 2.720016e-01 -5.440032e-01 4.100000e+00 -3.800000e+00 5.352615e-01 5.352615e-01 2.676307e-01 -5.352615e-01 4.200000e+00 -3.800000e+00 5.264494e-01 5.264494e-01 2.632247e-01 -5.264494e-01 4.300000e+00 -3.800000e+00 5.175754e-01 5.175754e-01 2.587877e-01 -5.175754e-01 4.400000e+00 -3.800000e+00 5.086475e-01 5.086475e-01 2.543238e-01 -5.086475e-01 4.500000e+00 -3.800000e+00 4.996737e-01 4.996737e-01 2.498369e-01 -4.996737e-01 4.600000e+00 -3.800000e+00 4.906619e-01 4.906619e-01 2.453310e-01 -4.906619e-01 4.700000e+00 -3.800000e+00 4.816200e-01 4.816200e-01 2.408100e-01 -4.816200e-01 4.800000e+00 -3.800000e+00 4.725555e-01 4.725555e-01 2.362778e-01 -4.725555e-01 4.900000e+00 -3.800000e+00 4.634763e-01 4.634763e-01 2.317382e-01 -4.634763e-01 -5.000000e+00 -3.700000e+00 4.612570e-01 4.612570e-01 2.306285e-01 -4.612570e-01 -4.900000e+00 -3.700000e+00 4.704808e-01 4.704808e-01 2.352404e-01 -4.704808e-01 -4.800000e+00 -3.700000e+00 4.796973e-01 4.796973e-01 2.398486e-01 -4.796973e-01 -4.700000e+00 -3.700000e+00 4.888987e-01 4.888987e-01 2.444493e-01 -4.888987e-01 -4.600000e+00 -3.700000e+00 4.980773e-01 4.980773e-01 2.490387e-01 -4.980773e-01 -4.500000e+00 -3.700000e+00 5.072253e-01 5.072253e-01 2.536126e-01 -5.072253e-01 -4.400000e+00 -3.700000e+00 5.163347e-01 5.163347e-01 2.581674e-01 -5.163347e-01 -4.300000e+00 -3.700000e+00 5.253976e-01 5.253976e-01 2.626988e-01 -5.253976e-01 -4.200000e+00 -3.700000e+00 5.344057e-01 5.344057e-01 2.672029e-01 -5.344057e-01 -4.100000e+00 -3.700000e+00 5.433509e-01 5.433509e-01 2.716754e-01 -5.433509e-01 -4.000000e+00 -3.700000e+00 5.522248e-01 5.522248e-01 2.761124e-01 -5.522248e-01 -3.900000e+00 -3.700000e+00 5.610192e-01 5.610192e-01 2.805096e-01 -5.610192e-01 -3.800000e+00 -3.700000e+00 5.697258e-01 5.697258e-01 2.848629e-01 -5.697258e-01 -3.700000e+00 -3.700000e+00 5.783361e-01 5.783361e-01 2.891681e-01 -5.783361e-01 -3.600000e+00 -3.700000e+00 5.868418e-01 5.868418e-01 2.934209e-01 -5.868418e-01 -3.500000e+00 -3.700000e+00 5.952344e-01 5.952344e-01 2.976172e-01 -5.952344e-01 -3.400000e+00 -3.700000e+00 6.035056e-01 6.035056e-01 3.017528e-01 -6.035056e-01 -3.300000e+00 -3.700000e+00 6.116470e-01 6.116470e-01 3.058235e-01 -6.116470e-01 -3.200000e+00 -3.700000e+00 6.196503e-01 6.196503e-01 3.098252e-01 -6.196503e-01 -3.100000e+00 -3.700000e+00 6.275073e-01 6.275073e-01 3.137536e-01 -6.275073e-01 -3.000000e+00 -3.700000e+00 6.352097e-01 6.352097e-01 3.176049e-01 -6.352097e-01 -2.900000e+00 -3.700000e+00 6.427496e-01 6.427496e-01 3.213748e-01 -6.427496e-01 -2.800000e+00 -3.700000e+00 6.501189e-01 6.501189e-01 3.250594e-01 -6.501189e-01 -2.700000e+00 -3.700000e+00 6.573097e-01 6.573097e-01 3.286549e-01 -6.573097e-01 -2.600000e+00 -3.700000e+00 6.643142e-01 6.643142e-01 3.321571e-01 -6.643142e-01 -2.500000e+00 -3.700000e+00 6.711249e-01 6.711249e-01 3.355624e-01 -6.711249e-01 -2.400000e+00 -3.700000e+00 6.777343e-01 6.777343e-01 3.388671e-01 -6.777343e-01 -2.300000e+00 -3.700000e+00 6.841350e-01 6.841350e-01 3.420675e-01 -6.841350e-01 -2.200000e+00 -3.700000e+00 6.903200e-01 6.903200e-01 3.451600e-01 -6.903200e-01 -2.100000e+00 -3.700000e+00 6.962823e-01 6.962823e-01 3.481412e-01 -6.962823e-01 -2.000000e+00 -3.700000e+00 7.020153e-01 7.020153e-01 3.510077e-01 -7.020153e-01 -1.900000e+00 -3.700000e+00 7.075125e-01 7.075125e-01 3.537562e-01 -7.075125e-01 -1.800000e+00 -3.700000e+00 7.127675e-01 7.127675e-01 3.563837e-01 -7.127675e-01 -1.700000e+00 -3.700000e+00 7.177744e-01 7.177744e-01 3.588872e-01 -7.177744e-01 -1.600000e+00 -3.700000e+00 7.225273e-01 7.225273e-01 3.612637e-01 -7.225273e-01 -1.500000e+00 -3.700000e+00 7.270209e-01 7.270209e-01 3.635105e-01 -7.270209e-01 -1.400000e+00 -3.700000e+00 7.312499e-01 7.312499e-01 3.656249e-01 -7.312499e-01 -1.300000e+00 -3.700000e+00 7.352093e-01 7.352093e-01 3.676047e-01 -7.352093e-01 -1.200000e+00 -3.700000e+00 7.388946e-01 7.388946e-01 3.694473e-01 -7.388946e-01 -1.100000e+00 -3.700000e+00 7.423013e-01 7.423013e-01 3.711507e-01 -7.423013e-01 -1.000000e+00 -3.700000e+00 7.454255e-01 7.454255e-01 3.727128e-01 -7.454255e-01 -9.000000e-01 -3.700000e+00 7.482635e-01 7.482635e-01 3.741318e-01 -7.482635e-01 -8.000000e-01 -3.700000e+00 7.508120e-01 7.508120e-01 3.754060e-01 -7.508120e-01 -7.000000e-01 -3.700000e+00 7.530678e-01 7.530678e-01 3.765339e-01 -7.530678e-01 -6.000000e-01 -3.700000e+00 7.550283e-01 7.550283e-01 3.775142e-01 -7.550283e-01 -5.000000e-01 -3.700000e+00 7.566912e-01 7.566912e-01 3.783456e-01 -7.566912e-01 -4.000000e-01 -3.700000e+00 7.580545e-01 7.580545e-01 3.790272e-01 -7.580545e-01 -3.000000e-01 -3.700000e+00 7.591165e-01 7.591165e-01 3.795583e-01 -7.591165e-01 -2.000000e-01 -3.700000e+00 7.598760e-01 7.598760e-01 3.799380e-01 -7.598760e-01 -1.000000e-01 -3.700000e+00 7.603320e-01 7.603320e-01 3.801660e-01 -7.603320e-01 0.000000e+00 -3.700000e+00 7.604842e-01 7.604842e-01 3.802421e-01 -7.604842e-01 1.000000e-01 -3.700000e+00 7.603320e-01 7.603320e-01 3.801660e-01 -7.603320e-01 2.000000e-01 -3.700000e+00 7.598760e-01 7.598760e-01 3.799380e-01 -7.598760e-01 3.000000e-01 -3.700000e+00 7.591165e-01 7.591165e-01 3.795583e-01 -7.591165e-01 4.000000e-01 -3.700000e+00 7.580545e-01 7.580545e-01 3.790272e-01 -7.580545e-01 5.000000e-01 -3.700000e+00 7.566912e-01 7.566912e-01 3.783456e-01 -7.566912e-01 6.000000e-01 -3.700000e+00 7.550283e-01 7.550283e-01 3.775142e-01 -7.550283e-01 7.000000e-01 -3.700000e+00 7.530678e-01 7.530678e-01 3.765339e-01 -7.530678e-01 8.000000e-01 -3.700000e+00 7.508120e-01 7.508120e-01 3.754060e-01 -7.508120e-01 9.000000e-01 -3.700000e+00 7.482635e-01 7.482635e-01 3.741318e-01 -7.482635e-01 1.000000e+00 -3.700000e+00 7.454255e-01 7.454255e-01 3.727128e-01 -7.454255e-01 1.100000e+00 -3.700000e+00 7.423013e-01 7.423013e-01 3.711507e-01 -7.423013e-01 1.200000e+00 -3.700000e+00 7.388946e-01 7.388946e-01 3.694473e-01 -7.388946e-01 1.300000e+00 -3.700000e+00 7.352093e-01 7.352093e-01 3.676047e-01 -7.352093e-01 1.400000e+00 -3.700000e+00 7.312499e-01 7.312499e-01 3.656249e-01 -7.312499e-01 1.500000e+00 -3.700000e+00 7.270209e-01 7.270209e-01 3.635105e-01 -7.270209e-01 1.600000e+00 -3.700000e+00 7.225273e-01 7.225273e-01 3.612637e-01 -7.225273e-01 1.700000e+00 -3.700000e+00 7.177744e-01 7.177744e-01 3.588872e-01 -7.177744e-01 1.800000e+00 -3.700000e+00 7.127675e-01 7.127675e-01 3.563837e-01 -7.127675e-01 1.900000e+00 -3.700000e+00 7.075125e-01 7.075125e-01 3.537562e-01 -7.075125e-01 2.000000e+00 -3.700000e+00 7.020153e-01 7.020153e-01 3.510077e-01 -7.020153e-01 2.100000e+00 -3.700000e+00 6.962823e-01 6.962823e-01 3.481412e-01 -6.962823e-01 2.200000e+00 -3.700000e+00 6.903200e-01 6.903200e-01 3.451600e-01 -6.903200e-01 2.300000e+00 -3.700000e+00 6.841350e-01 6.841350e-01 3.420675e-01 -6.841350e-01 2.400000e+00 -3.700000e+00 6.777343e-01 6.777343e-01 3.388671e-01 -6.777343e-01 2.500000e+00 -3.700000e+00 6.711249e-01 6.711249e-01 3.355624e-01 -6.711249e-01 2.600000e+00 -3.700000e+00 6.643142e-01 6.643142e-01 3.321571e-01 -6.643142e-01 2.700000e+00 -3.700000e+00 6.573097e-01 6.573097e-01 3.286549e-01 -6.573097e-01 2.800000e+00 -3.700000e+00 6.501189e-01 6.501189e-01 3.250594e-01 -6.501189e-01 2.900000e+00 -3.700000e+00 6.427496e-01 6.427496e-01 3.213748e-01 -6.427496e-01 3.000000e+00 -3.700000e+00 6.352097e-01 6.352097e-01 3.176049e-01 -6.352097e-01 3.100000e+00 -3.700000e+00 6.275073e-01 6.275073e-01 3.137536e-01 -6.275073e-01 3.200000e+00 -3.700000e+00 6.196503e-01 6.196503e-01 3.098252e-01 -6.196503e-01 3.300000e+00 -3.700000e+00 6.116470e-01 6.116470e-01 3.058235e-01 -6.116470e-01 3.400000e+00 -3.700000e+00 6.035056e-01 6.035056e-01 3.017528e-01 -6.035056e-01 3.500000e+00 -3.700000e+00 5.952344e-01 5.952344e-01 2.976172e-01 -5.952344e-01 3.600000e+00 -3.700000e+00 5.868418e-01 5.868418e-01 2.934209e-01 -5.868418e-01 3.700000e+00 -3.700000e+00 5.783361e-01 5.783361e-01 2.891681e-01 -5.783361e-01 3.800000e+00 -3.700000e+00 5.697258e-01 5.697258e-01 2.848629e-01 -5.697258e-01 3.900000e+00 -3.700000e+00 5.610192e-01 5.610192e-01 2.805096e-01 -5.610192e-01 4.000000e+00 -3.700000e+00 5.522248e-01 5.522248e-01 2.761124e-01 -5.522248e-01 4.100000e+00 -3.700000e+00 5.433509e-01 5.433509e-01 2.716754e-01 -5.433509e-01 4.200000e+00 -3.700000e+00 5.344057e-01 5.344057e-01 2.672029e-01 -5.344057e-01 4.300000e+00 -3.700000e+00 5.253976e-01 5.253976e-01 2.626988e-01 -5.253976e-01 4.400000e+00 -3.700000e+00 5.163347e-01 5.163347e-01 2.581674e-01 -5.163347e-01 4.500000e+00 -3.700000e+00 5.072253e-01 5.072253e-01 2.536126e-01 -5.072253e-01 4.600000e+00 -3.700000e+00 4.980773e-01 4.980773e-01 2.490387e-01 -4.980773e-01 4.700000e+00 -3.700000e+00 4.888987e-01 4.888987e-01 2.444493e-01 -4.888987e-01 4.800000e+00 -3.700000e+00 4.796973e-01 4.796973e-01 2.398486e-01 -4.796973e-01 4.900000e+00 -3.700000e+00 4.704808e-01 4.704808e-01 2.352404e-01 -4.704808e-01 -5.000000e+00 -3.600000e+00 4.680407e-01 4.680407e-01 2.340204e-01 -4.680407e-01 -4.900000e+00 -3.600000e+00 4.774002e-01 4.774002e-01 2.387001e-01 -4.774002e-01 -4.800000e+00 -3.600000e+00 4.867522e-01 4.867522e-01 2.433761e-01 -4.867522e-01 -4.700000e+00 -3.600000e+00 4.960890e-01 4.960890e-01 2.480445e-01 -4.960890e-01 -4.600000e+00 -3.600000e+00 5.054026e-01 5.054026e-01 2.527013e-01 -5.054026e-01 -4.500000e+00 -3.600000e+00 5.146852e-01 5.146852e-01 2.573426e-01 -5.146852e-01 -4.400000e+00 -3.600000e+00 5.239285e-01 5.239285e-01 2.619643e-01 -5.239285e-01 -4.300000e+00 -3.600000e+00 5.331247e-01 5.331247e-01 2.665623e-01 -5.331247e-01 -4.200000e+00 -3.600000e+00 5.422652e-01 5.422652e-01 2.711326e-01 -5.422652e-01 -4.100000e+00 -3.600000e+00 5.513420e-01 5.513420e-01 2.756710e-01 -5.513420e-01 -4.000000e+00 -3.600000e+00 5.603464e-01 5.603464e-01 2.801732e-01 -5.603464e-01 -3.900000e+00 -3.600000e+00 5.692703e-01 5.692703e-01 2.846351e-01 -5.692703e-01 -3.800000e+00 -3.600000e+00 5.781049e-01 5.781049e-01 2.890524e-01 -5.781049e-01 -3.700000e+00 -3.600000e+00 5.868418e-01 5.868418e-01 2.934209e-01 -5.868418e-01 -3.600000e+00 -3.600000e+00 5.954726e-01 5.954726e-01 2.977363e-01 -5.954726e-01 -3.500000e+00 -3.600000e+00 6.039886e-01 6.039886e-01 3.019943e-01 -6.039886e-01 -3.400000e+00 -3.600000e+00 6.123814e-01 6.123814e-01 3.061907e-01 -6.123814e-01 -3.300000e+00 -3.600000e+00 6.206425e-01 6.206425e-01 3.103213e-01 -6.206425e-01 -3.200000e+00 -3.600000e+00 6.287636e-01 6.287636e-01 3.143818e-01 -6.287636e-01 -3.100000e+00 -3.600000e+00 6.367361e-01 6.367361e-01 3.183680e-01 -6.367361e-01 -3.000000e+00 -3.600000e+00 6.445519e-01 6.445519e-01 3.222759e-01 -6.445519e-01 -2.900000e+00 -3.600000e+00 6.522026e-01 6.522026e-01 3.261013e-01 -6.522026e-01 -2.800000e+00 -3.600000e+00 6.596803e-01 6.596803e-01 3.298402e-01 -6.596803e-01 -2.700000e+00 -3.600000e+00 6.669768e-01 6.669768e-01 3.334884e-01 -6.669768e-01 -2.600000e+00 -3.600000e+00 6.740844e-01 6.740844e-01 3.370422e-01 -6.740844e-01 -2.500000e+00 -3.600000e+00 6.809952e-01 6.809952e-01 3.404976e-01 -6.809952e-01 -2.400000e+00 -3.600000e+00 6.877018e-01 6.877018e-01 3.438509e-01 -6.877018e-01 -2.300000e+00 -3.600000e+00 6.941967e-01 6.941967e-01 3.470984e-01 -6.941967e-01 -2.200000e+00 -3.600000e+00 7.004727e-01 7.004727e-01 3.502363e-01 -7.004727e-01 -2.100000e+00 -3.600000e+00 7.065227e-01 7.065227e-01 3.532614e-01 -7.065227e-01 -2.000000e+00 -3.600000e+00 7.123400e-01 7.123400e-01 3.561700e-01 -7.123400e-01 -1.900000e+00 -3.600000e+00 7.179180e-01 7.179180e-01 3.589590e-01 -7.179180e-01 -1.800000e+00 -3.600000e+00 7.232503e-01 7.232503e-01 3.616251e-01 -7.232503e-01 -1.700000e+00 -3.600000e+00 7.283308e-01 7.283308e-01 3.641654e-01 -7.283308e-01 -1.600000e+00 -3.600000e+00 7.331536e-01 7.331536e-01 3.665768e-01 -7.331536e-01 -1.500000e+00 -3.600000e+00 7.377133e-01 7.377133e-01 3.688567e-01 -7.377133e-01 -1.400000e+00 -3.600000e+00 7.420045e-01 7.420045e-01 3.710023e-01 -7.420045e-01 -1.300000e+00 -3.600000e+00 7.460222e-01 7.460222e-01 3.730111e-01 -7.460222e-01 -1.200000e+00 -3.600000e+00 7.497616e-01 7.497616e-01 3.748808e-01 -7.497616e-01 -1.100000e+00 -3.600000e+00 7.532185e-01 7.532185e-01 3.766092e-01 -7.532185e-01 -1.000000e+00 -3.600000e+00 7.563886e-01 7.563886e-01 3.781943e-01 -7.563886e-01 -9.000000e-01 -3.600000e+00 7.592683e-01 7.592683e-01 3.796342e-01 -7.592683e-01 -8.000000e-01 -3.600000e+00 7.618543e-01 7.618543e-01 3.809271e-01 -7.618543e-01 -7.000000e-01 -3.600000e+00 7.641433e-01 7.641433e-01 3.820716e-01 -7.641433e-01 -6.000000e-01 -3.600000e+00 7.661327e-01 7.661327e-01 3.830663e-01 -7.661327e-01 -5.000000e-01 -3.600000e+00 7.678200e-01 7.678200e-01 3.839100e-01 -7.678200e-01 -4.000000e-01 -3.600000e+00 7.692033e-01 7.692033e-01 3.846017e-01 -7.692033e-01 -3.000000e-01 -3.600000e+00 7.702810e-01 7.702810e-01 3.851405e-01 -7.702810e-01 -2.000000e-01 -3.600000e+00 7.710516e-01 7.710516e-01 3.855258e-01 -7.710516e-01 -1.000000e-01 -3.600000e+00 7.715144e-01 7.715144e-01 3.857572e-01 -7.715144e-01 0.000000e+00 -3.600000e+00 7.716687e-01 7.716687e-01 3.858343e-01 -7.716687e-01 1.000000e-01 -3.600000e+00 7.715144e-01 7.715144e-01 3.857572e-01 -7.715144e-01 2.000000e-01 -3.600000e+00 7.710516e-01 7.710516e-01 3.855258e-01 -7.710516e-01 3.000000e-01 -3.600000e+00 7.702810e-01 7.702810e-01 3.851405e-01 -7.702810e-01 4.000000e-01 -3.600000e+00 7.692033e-01 7.692033e-01 3.846017e-01 -7.692033e-01 5.000000e-01 -3.600000e+00 7.678200e-01 7.678200e-01 3.839100e-01 -7.678200e-01 6.000000e-01 -3.600000e+00 7.661327e-01 7.661327e-01 3.830663e-01 -7.661327e-01 7.000000e-01 -3.600000e+00 7.641433e-01 7.641433e-01 3.820716e-01 -7.641433e-01 8.000000e-01 -3.600000e+00 7.618543e-01 7.618543e-01 3.809271e-01 -7.618543e-01 9.000000e-01 -3.600000e+00 7.592683e-01 7.592683e-01 3.796342e-01 -7.592683e-01 1.000000e+00 -3.600000e+00 7.563886e-01 7.563886e-01 3.781943e-01 -7.563886e-01 1.100000e+00 -3.600000e+00 7.532185e-01 7.532185e-01 3.766092e-01 -7.532185e-01 1.200000e+00 -3.600000e+00 7.497616e-01 7.497616e-01 3.748808e-01 -7.497616e-01 1.300000e+00 -3.600000e+00 7.460222e-01 7.460222e-01 3.730111e-01 -7.460222e-01 1.400000e+00 -3.600000e+00 7.420045e-01 7.420045e-01 3.710023e-01 -7.420045e-01 1.500000e+00 -3.600000e+00 7.377133e-01 7.377133e-01 3.688567e-01 -7.377133e-01 1.600000e+00 -3.600000e+00 7.331536e-01 7.331536e-01 3.665768e-01 -7.331536e-01 1.700000e+00 -3.600000e+00 7.283308e-01 7.283308e-01 3.641654e-01 -7.283308e-01 1.800000e+00 -3.600000e+00 7.232503e-01 7.232503e-01 3.616251e-01 -7.232503e-01 1.900000e+00 -3.600000e+00 7.179180e-01 7.179180e-01 3.589590e-01 -7.179180e-01 2.000000e+00 -3.600000e+00 7.123400e-01 7.123400e-01 3.561700e-01 -7.123400e-01 2.100000e+00 -3.600000e+00 7.065227e-01 7.065227e-01 3.532614e-01 -7.065227e-01 2.200000e+00 -3.600000e+00 7.004727e-01 7.004727e-01 3.502363e-01 -7.004727e-01 2.300000e+00 -3.600000e+00 6.941967e-01 6.941967e-01 3.470984e-01 -6.941967e-01 2.400000e+00 -3.600000e+00 6.877018e-01 6.877018e-01 3.438509e-01 -6.877018e-01 2.500000e+00 -3.600000e+00 6.809952e-01 6.809952e-01 3.404976e-01 -6.809952e-01 2.600000e+00 -3.600000e+00 6.740844e-01 6.740844e-01 3.370422e-01 -6.740844e-01 2.700000e+00 -3.600000e+00 6.669768e-01 6.669768e-01 3.334884e-01 -6.669768e-01 2.800000e+00 -3.600000e+00 6.596803e-01 6.596803e-01 3.298402e-01 -6.596803e-01 2.900000e+00 -3.600000e+00 6.522026e-01 6.522026e-01 3.261013e-01 -6.522026e-01 3.000000e+00 -3.600000e+00 6.445519e-01 6.445519e-01 3.222759e-01 -6.445519e-01 3.100000e+00 -3.600000e+00 6.367361e-01 6.367361e-01 3.183680e-01 -6.367361e-01 3.200000e+00 -3.600000e+00 6.287636e-01 6.287636e-01 3.143818e-01 -6.287636e-01 3.300000e+00 -3.600000e+00 6.206425e-01 6.206425e-01 3.103213e-01 -6.206425e-01 3.400000e+00 -3.600000e+00 6.123814e-01 6.123814e-01 3.061907e-01 -6.123814e-01 3.500000e+00 -3.600000e+00 6.039886e-01 6.039886e-01 3.019943e-01 -6.039886e-01 3.600000e+00 -3.600000e+00 5.954726e-01 5.954726e-01 2.977363e-01 -5.954726e-01 3.700000e+00 -3.600000e+00 5.868418e-01 5.868418e-01 2.934209e-01 -5.868418e-01 3.800000e+00 -3.600000e+00 5.781049e-01 5.781049e-01 2.890524e-01 -5.781049e-01 3.900000e+00 -3.600000e+00 5.692703e-01 5.692703e-01 2.846351e-01 -5.692703e-01 4.000000e+00 -3.600000e+00 5.603464e-01 5.603464e-01 2.801732e-01 -5.603464e-01 4.100000e+00 -3.600000e+00 5.513420e-01 5.513420e-01 2.756710e-01 -5.513420e-01 4.200000e+00 -3.600000e+00 5.422652e-01 5.422652e-01 2.711326e-01 -5.422652e-01 4.300000e+00 -3.600000e+00 5.331247e-01 5.331247e-01 2.665623e-01 -5.331247e-01 4.400000e+00 -3.600000e+00 5.239285e-01 5.239285e-01 2.619643e-01 -5.239285e-01 4.500000e+00 -3.600000e+00 5.146852e-01 5.146852e-01 2.573426e-01 -5.146852e-01 4.600000e+00 -3.600000e+00 5.054026e-01 5.054026e-01 2.527013e-01 -5.054026e-01 4.700000e+00 -3.600000e+00 4.960890e-01 4.960890e-01 2.480445e-01 -4.960890e-01 4.800000e+00 -3.600000e+00 4.867522e-01 4.867522e-01 2.433761e-01 -4.867522e-01 4.900000e+00 -3.600000e+00 4.774002e-01 4.774002e-01 2.387001e-01 -4.774002e-01 -5.000000e+00 -3.500000e+00 4.747343e-01 4.747343e-01 2.373672e-01 -4.747343e-01 -4.900000e+00 -3.500000e+00 4.842277e-01 4.842277e-01 2.421139e-01 -4.842277e-01 -4.800000e+00 -3.500000e+00 4.937134e-01 4.937134e-01 2.468567e-01 -4.937134e-01 -4.700000e+00 -3.500000e+00 5.031837e-01 5.031837e-01 2.515919e-01 -5.031837e-01 -4.600000e+00 -3.500000e+00 5.126305e-01 5.126305e-01 2.563153e-01 -5.126305e-01 -4.500000e+00 -3.500000e+00 5.220458e-01 5.220458e-01 2.610229e-01 -5.220458e-01 -4.400000e+00 -3.500000e+00 5.314214e-01 5.314214e-01 2.657107e-01 -5.314214e-01 -4.300000e+00 -3.500000e+00 5.407491e-01 5.407491e-01 2.703745e-01 -5.407491e-01 -4.200000e+00 -3.500000e+00 5.500204e-01 5.500204e-01 2.750102e-01 -5.500204e-01 -4.100000e+00 -3.500000e+00 5.592269e-01 5.592269e-01 2.796134e-01 -5.592269e-01 -4.000000e+00 -3.500000e+00 5.683601e-01 5.683601e-01 2.841801e-01 -5.683601e-01 -3.900000e+00 -3.500000e+00 5.774115e-01 5.774115e-01 2.887058e-01 -5.774115e-01 -3.800000e+00 -3.500000e+00 5.863725e-01 5.863725e-01 2.931862e-01 -5.863725e-01 -3.700000e+00 -3.500000e+00 5.952344e-01 5.952344e-01 2.976172e-01 -5.952344e-01 -3.600000e+00 -3.500000e+00 6.039886e-01 6.039886e-01 3.019943e-01 -6.039886e-01 -3.500000e+00 -3.500000e+00 6.126264e-01 6.126264e-01 3.063132e-01 -6.126264e-01 -3.400000e+00 -3.500000e+00 6.211392e-01 6.211392e-01 3.105696e-01 -6.211392e-01 -3.300000e+00 -3.500000e+00 6.295186e-01 6.295186e-01 3.147593e-01 -6.295186e-01 -3.200000e+00 -3.500000e+00 6.377557e-01 6.377557e-01 3.188778e-01 -6.377557e-01 -3.100000e+00 -3.500000e+00 6.458423e-01 6.458423e-01 3.229211e-01 -6.458423e-01 -3.000000e+00 -3.500000e+00 6.537698e-01 6.537698e-01 3.268849e-01 -6.537698e-01 -2.900000e+00 -3.500000e+00 6.615300e-01 6.615300e-01 3.307650e-01 -6.615300e-01 -2.800000e+00 -3.500000e+00 6.691146e-01 6.691146e-01 3.345573e-01 -6.691146e-01 -2.700000e+00 -3.500000e+00 6.765155e-01 6.765155e-01 3.382577e-01 -6.765155e-01 -2.600000e+00 -3.500000e+00 6.837247e-01 6.837247e-01 3.418624e-01 -6.837247e-01 -2.500000e+00 -3.500000e+00 6.907343e-01 6.907343e-01 3.453672e-01 -6.907343e-01 -2.400000e+00 -3.500000e+00 6.975368e-01 6.975368e-01 3.487684e-01 -6.975368e-01 -2.300000e+00 -3.500000e+00 7.041246e-01 7.041246e-01 3.520623e-01 -7.041246e-01 -2.200000e+00 -3.500000e+00 7.104903e-01 7.104903e-01 3.552451e-01 -7.104903e-01 -2.100000e+00 -3.500000e+00 7.166269e-01 7.166269e-01 3.583134e-01 -7.166269e-01 -2.000000e+00 -3.500000e+00 7.225274e-01 7.225274e-01 3.612637e-01 -7.225274e-01 -1.900000e+00 -3.500000e+00 7.281851e-01 7.281851e-01 3.640926e-01 -7.281851e-01 -1.800000e+00 -3.500000e+00 7.335937e-01 7.335937e-01 3.667969e-01 -7.335937e-01 -1.700000e+00 -3.500000e+00 7.387468e-01 7.387468e-01 3.693734e-01 -7.387468e-01 -1.600000e+00 -3.500000e+00 7.436387e-01 7.436387e-01 3.718193e-01 -7.436387e-01 -1.500000e+00 -3.500000e+00 7.482636e-01 7.482636e-01 3.741318e-01 -7.482636e-01 -1.400000e+00 -3.500000e+00 7.526161e-01 7.526161e-01 3.763081e-01 -7.526161e-01 -1.300000e+00 -3.500000e+00 7.566912e-01 7.566912e-01 3.783456e-01 -7.566912e-01 -1.200000e+00 -3.500000e+00 7.604842e-01 7.604842e-01 3.802421e-01 -7.604842e-01 -1.100000e+00 -3.500000e+00 7.639905e-01 7.639905e-01 3.819952e-01 -7.639905e-01 -1.000000e+00 -3.500000e+00 7.672060e-01 7.672060e-01 3.836030e-01 -7.672060e-01 -9.000000e-01 -3.500000e+00 7.701269e-01 7.701269e-01 3.850634e-01 -7.701269e-01 -8.000000e-01 -3.500000e+00 7.727498e-01 7.727498e-01 3.863749e-01 -7.727498e-01 -7.000000e-01 -3.500000e+00 7.750715e-01 7.750715e-01 3.875358e-01 -7.750715e-01 -6.000000e-01 -3.500000e+00 7.770893e-01 7.770893e-01 3.885446e-01 -7.770893e-01 -5.000000e-01 -3.500000e+00 7.788008e-01 7.788008e-01 3.894004e-01 -7.788008e-01 -4.000000e-01 -3.500000e+00 7.802039e-01 7.802039e-01 3.901019e-01 -7.802039e-01 -3.000000e-01 -3.500000e+00 7.812970e-01 7.812970e-01 3.906485e-01 -7.812970e-01 -2.000000e-01 -3.500000e+00 7.820786e-01 7.820786e-01 3.910393e-01 -7.820786e-01 -1.000000e-01 -3.500000e+00 7.825480e-01 7.825480e-01 3.912740e-01 -7.825480e-01 0.000000e+00 -3.500000e+00 7.827045e-01 7.827045e-01 3.913523e-01 -7.827045e-01 1.000000e-01 -3.500000e+00 7.825480e-01 7.825480e-01 3.912740e-01 -7.825480e-01 2.000000e-01 -3.500000e+00 7.820786e-01 7.820786e-01 3.910393e-01 -7.820786e-01 3.000000e-01 -3.500000e+00 7.812970e-01 7.812970e-01 3.906485e-01 -7.812970e-01 4.000000e-01 -3.500000e+00 7.802039e-01 7.802039e-01 3.901019e-01 -7.802039e-01 5.000000e-01 -3.500000e+00 7.788008e-01 7.788008e-01 3.894004e-01 -7.788008e-01 6.000000e-01 -3.500000e+00 7.770893e-01 7.770893e-01 3.885446e-01 -7.770893e-01 7.000000e-01 -3.500000e+00 7.750715e-01 7.750715e-01 3.875358e-01 -7.750715e-01 8.000000e-01 -3.500000e+00 7.727498e-01 7.727498e-01 3.863749e-01 -7.727498e-01 9.000000e-01 -3.500000e+00 7.701269e-01 7.701269e-01 3.850634e-01 -7.701269e-01 1.000000e+00 -3.500000e+00 7.672060e-01 7.672060e-01 3.836030e-01 -7.672060e-01 1.100000e+00 -3.500000e+00 7.639905e-01 7.639905e-01 3.819952e-01 -7.639905e-01 1.200000e+00 -3.500000e+00 7.604842e-01 7.604842e-01 3.802421e-01 -7.604842e-01 1.300000e+00 -3.500000e+00 7.566912e-01 7.566912e-01 3.783456e-01 -7.566912e-01 1.400000e+00 -3.500000e+00 7.526161e-01 7.526161e-01 3.763081e-01 -7.526161e-01 1.500000e+00 -3.500000e+00 7.482636e-01 7.482636e-01 3.741318e-01 -7.482636e-01 1.600000e+00 -3.500000e+00 7.436387e-01 7.436387e-01 3.718193e-01 -7.436387e-01 1.700000e+00 -3.500000e+00 7.387468e-01 7.387468e-01 3.693734e-01 -7.387468e-01 1.800000e+00 -3.500000e+00 7.335937e-01 7.335937e-01 3.667969e-01 -7.335937e-01 1.900000e+00 -3.500000e+00 7.281851e-01 7.281851e-01 3.640926e-01 -7.281851e-01 2.000000e+00 -3.500000e+00 7.225274e-01 7.225274e-01 3.612637e-01 -7.225274e-01 2.100000e+00 -3.500000e+00 7.166269e-01 7.166269e-01 3.583134e-01 -7.166269e-01 2.200000e+00 -3.500000e+00 7.104903e-01 7.104903e-01 3.552451e-01 -7.104903e-01 2.300000e+00 -3.500000e+00 7.041246e-01 7.041246e-01 3.520623e-01 -7.041246e-01 2.400000e+00 -3.500000e+00 6.975368e-01 6.975368e-01 3.487684e-01 -6.975368e-01 2.500000e+00 -3.500000e+00 6.907343e-01 6.907343e-01 3.453672e-01 -6.907343e-01 2.600000e+00 -3.500000e+00 6.837247e-01 6.837247e-01 3.418624e-01 -6.837247e-01 2.700000e+00 -3.500000e+00 6.765155e-01 6.765155e-01 3.382577e-01 -6.765155e-01 2.800000e+00 -3.500000e+00 6.691146e-01 6.691146e-01 3.345573e-01 -6.691146e-01 2.900000e+00 -3.500000e+00 6.615300e-01 6.615300e-01 3.307650e-01 -6.615300e-01 3.000000e+00 -3.500000e+00 6.537698e-01 6.537698e-01 3.268849e-01 -6.537698e-01 3.100000e+00 -3.500000e+00 6.458423e-01 6.458423e-01 3.229211e-01 -6.458423e-01 3.200000e+00 -3.500000e+00 6.377557e-01 6.377557e-01 3.188778e-01 -6.377557e-01 3.300000e+00 -3.500000e+00 6.295186e-01 6.295186e-01 3.147593e-01 -6.295186e-01 3.400000e+00 -3.500000e+00 6.211392e-01 6.211392e-01 3.105696e-01 -6.211392e-01 3.500000e+00 -3.500000e+00 6.126264e-01 6.126264e-01 3.063132e-01 -6.126264e-01 3.600000e+00 -3.500000e+00 6.039886e-01 6.039886e-01 3.019943e-01 -6.039886e-01 3.700000e+00 -3.500000e+00 5.952344e-01 5.952344e-01 2.976172e-01 -5.952344e-01 3.800000e+00 -3.500000e+00 5.863725e-01 5.863725e-01 2.931862e-01 -5.863725e-01 3.900000e+00 -3.500000e+00 5.774115e-01 5.774115e-01 2.887058e-01 -5.774115e-01 4.000000e+00 -3.500000e+00 5.683601e-01 5.683601e-01 2.841801e-01 -5.683601e-01 4.100000e+00 -3.500000e+00 5.592269e-01 5.592269e-01 2.796134e-01 -5.592269e-01 4.200000e+00 -3.500000e+00 5.500204e-01 5.500204e-01 2.750102e-01 -5.500204e-01 4.300000e+00 -3.500000e+00 5.407491e-01 5.407491e-01 2.703745e-01 -5.407491e-01 4.400000e+00 -3.500000e+00 5.314214e-01 5.314214e-01 2.657107e-01 -5.314214e-01 4.500000e+00 -3.500000e+00 5.220458e-01 5.220458e-01 2.610229e-01 -5.220458e-01 4.600000e+00 -3.500000e+00 5.126305e-01 5.126305e-01 2.563153e-01 -5.126305e-01 4.700000e+00 -3.500000e+00 5.031837e-01 5.031837e-01 2.515919e-01 -5.031837e-01 4.800000e+00 -3.500000e+00 4.937134e-01 4.937134e-01 2.468567e-01 -4.937134e-01 4.900000e+00 -3.500000e+00 4.842277e-01 4.842277e-01 2.421139e-01 -4.842277e-01 -5.000000e+00 -3.400000e+00 4.813311e-01 4.813311e-01 2.406655e-01 -4.813311e-01 -4.900000e+00 -3.400000e+00 4.909564e-01 4.909564e-01 2.454782e-01 -4.909564e-01 -4.800000e+00 -3.400000e+00 5.005739e-01 5.005739e-01 2.502870e-01 -5.005739e-01 -4.700000e+00 -3.400000e+00 5.101758e-01 5.101758e-01 2.550879e-01 -5.101758e-01 -4.600000e+00 -3.400000e+00 5.197538e-01 5.197538e-01 2.598769e-01 -5.197538e-01 -4.500000e+00 -3.400000e+00 5.293000e-01 5.293000e-01 2.646500e-01 -5.293000e-01 -4.400000e+00 -3.400000e+00 5.388058e-01 5.388058e-01 2.694029e-01 -5.388058e-01 -4.300000e+00 -3.400000e+00 5.482631e-01 5.482631e-01 2.741315e-01 -5.482631e-01 -4.200000e+00 -3.400000e+00 5.576633e-01 5.576633e-01 2.788316e-01 -5.576633e-01 -4.100000e+00 -3.400000e+00 5.669977e-01 5.669977e-01 2.834989e-01 -5.669977e-01 -4.000000e+00 -3.400000e+00 5.762579e-01 5.762579e-01 2.881289e-01 -5.762579e-01 -3.900000e+00 -3.400000e+00 5.854350e-01 5.854350e-01 2.927175e-01 -5.854350e-01 -3.800000e+00 -3.400000e+00 5.945206e-01 5.945206e-01 2.972603e-01 -5.945206e-01 -3.700000e+00 -3.400000e+00 6.035056e-01 6.035056e-01 3.017528e-01 -6.035056e-01 -3.600000e+00 -3.400000e+00 6.123814e-01 6.123814e-01 3.061907e-01 -6.123814e-01 -3.500000e+00 -3.400000e+00 6.211392e-01 6.211392e-01 3.105696e-01 -6.211392e-01 -3.400000e+00 -3.400000e+00 6.297704e-01 6.297704e-01 3.148852e-01 -6.297704e-01 -3.300000e+00 -3.400000e+00 6.382661e-01 6.382661e-01 3.191330e-01 -6.382661e-01 -3.200000e+00 -3.400000e+00 6.466177e-01 6.466177e-01 3.233089e-01 -6.466177e-01 -3.100000e+00 -3.400000e+00 6.548166e-01 6.548166e-01 3.274083e-01 -6.548166e-01 -3.000000e+00 -3.400000e+00 6.628543e-01 6.628543e-01 3.314272e-01 -6.628543e-01 -2.900000e+00 -3.400000e+00 6.707223e-01 6.707223e-01 3.353612e-01 -6.707223e-01 -2.800000e+00 -3.400000e+00 6.784123e-01 6.784123e-01 3.392062e-01 -6.784123e-01 -2.700000e+00 -3.400000e+00 6.859161e-01 6.859161e-01 3.429580e-01 -6.859161e-01 -2.600000e+00 -3.400000e+00 6.932254e-01 6.932254e-01 3.466127e-01 -6.932254e-01 -2.500000e+00 -3.400000e+00 7.003325e-01 7.003325e-01 3.501663e-01 -7.003325e-01 -2.400000e+00 -3.400000e+00 7.072295e-01 7.072295e-01 3.536147e-01 -7.072295e-01 -2.300000e+00 -3.400000e+00 7.139089e-01 7.139089e-01 3.569544e-01 -7.139089e-01 -2.200000e+00 -3.400000e+00 7.203630e-01 7.203630e-01 3.601815e-01 -7.203630e-01 -2.100000e+00 -3.400000e+00 7.265849e-01 7.265849e-01 3.632924e-01 -7.265849e-01 -2.000000e+00 -3.400000e+00 7.325673e-01 7.325673e-01 3.662837e-01 -7.325673e-01 -1.900000e+00 -3.400000e+00 7.383037e-01 7.383037e-01 3.691519e-01 -7.383037e-01 -1.800000e+00 -3.400000e+00 7.437874e-01 7.437874e-01 3.718937e-01 -7.437874e-01 -1.700000e+00 -3.400000e+00 7.490122e-01 7.490122e-01 3.745061e-01 -7.490122e-01 -1.600000e+00 -3.400000e+00 7.539721e-01 7.539721e-01 3.769860e-01 -7.539721e-01 -1.500000e+00 -3.400000e+00 7.586612e-01 7.586612e-01 3.793306e-01 -7.586612e-01 -1.400000e+00 -3.400000e+00 7.630742e-01 7.630742e-01 3.815371e-01 -7.630742e-01 -1.300000e+00 -3.400000e+00 7.672060e-01 7.672060e-01 3.836030e-01 -7.672060e-01 -1.200000e+00 -3.400000e+00 7.710516e-01 7.710516e-01 3.855258e-01 -7.710516e-01 -1.100000e+00 -3.400000e+00 7.746066e-01 7.746066e-01 3.873033e-01 -7.746066e-01 -1.000000e+00 -3.400000e+00 7.778668e-01 7.778668e-01 3.889334e-01 -7.778668e-01 -9.000000e-01 -3.400000e+00 7.808283e-01 7.808283e-01 3.904141e-01 -7.808283e-01 -8.000000e-01 -3.400000e+00 7.834876e-01 7.834876e-01 3.917438e-01 -7.834876e-01 -7.000000e-01 -3.400000e+00 7.858416e-01 7.858416e-01 3.929208e-01 -7.858416e-01 -6.000000e-01 -3.400000e+00 7.878875e-01 7.878875e-01 3.939437e-01 -7.878875e-01 -5.000000e-01 -3.400000e+00 7.896227e-01 7.896227e-01 3.948114e-01 -7.896227e-01 -4.000000e-01 -3.400000e+00 7.910453e-01 7.910453e-01 3.955227e-01 -7.910453e-01 -3.000000e-01 -3.400000e+00 7.921535e-01 7.921535e-01 3.960768e-01 -7.921535e-01 -2.000000e-01 -3.400000e+00 7.929461e-01 7.929461e-01 3.964731e-01 -7.929461e-01 -1.000000e-01 -3.400000e+00 7.934220e-01 7.934220e-01 3.967110e-01 -7.934220e-01 0.000000e+00 -3.400000e+00 7.935807e-01 7.935807e-01 3.967904e-01 -7.935807e-01 1.000000e-01 -3.400000e+00 7.934220e-01 7.934220e-01 3.967110e-01 -7.934220e-01 2.000000e-01 -3.400000e+00 7.929461e-01 7.929461e-01 3.964731e-01 -7.929461e-01 3.000000e-01 -3.400000e+00 7.921535e-01 7.921535e-01 3.960768e-01 -7.921535e-01 4.000000e-01 -3.400000e+00 7.910453e-01 7.910453e-01 3.955227e-01 -7.910453e-01 5.000000e-01 -3.400000e+00 7.896227e-01 7.896227e-01 3.948114e-01 -7.896227e-01 6.000000e-01 -3.400000e+00 7.878875e-01 7.878875e-01 3.939437e-01 -7.878875e-01 7.000000e-01 -3.400000e+00 7.858416e-01 7.858416e-01 3.929208e-01 -7.858416e-01 8.000000e-01 -3.400000e+00 7.834876e-01 7.834876e-01 3.917438e-01 -7.834876e-01 9.000000e-01 -3.400000e+00 7.808283e-01 7.808283e-01 3.904141e-01 -7.808283e-01 1.000000e+00 -3.400000e+00 7.778668e-01 7.778668e-01 3.889334e-01 -7.778668e-01 1.100000e+00 -3.400000e+00 7.746066e-01 7.746066e-01 3.873033e-01 -7.746066e-01 1.200000e+00 -3.400000e+00 7.710516e-01 7.710516e-01 3.855258e-01 -7.710516e-01 1.300000e+00 -3.400000e+00 7.672060e-01 7.672060e-01 3.836030e-01 -7.672060e-01 1.400000e+00 -3.400000e+00 7.630742e-01 7.630742e-01 3.815371e-01 -7.630742e-01 1.500000e+00 -3.400000e+00 7.586612e-01 7.586612e-01 3.793306e-01 -7.586612e-01 1.600000e+00 -3.400000e+00 7.539721e-01 7.539721e-01 3.769860e-01 -7.539721e-01 1.700000e+00 -3.400000e+00 7.490122e-01 7.490122e-01 3.745061e-01 -7.490122e-01 1.800000e+00 -3.400000e+00 7.437874e-01 7.437874e-01 3.718937e-01 -7.437874e-01 1.900000e+00 -3.400000e+00 7.383037e-01 7.383037e-01 3.691519e-01 -7.383037e-01 2.000000e+00 -3.400000e+00 7.325673e-01 7.325673e-01 3.662837e-01 -7.325673e-01 2.100000e+00 -3.400000e+00 7.265849e-01 7.265849e-01 3.632924e-01 -7.265849e-01 2.200000e+00 -3.400000e+00 7.203630e-01 7.203630e-01 3.601815e-01 -7.203630e-01 2.300000e+00 -3.400000e+00 7.139089e-01 7.139089e-01 3.569544e-01 -7.139089e-01 2.400000e+00 -3.400000e+00 7.072295e-01 7.072295e-01 3.536147e-01 -7.072295e-01 2.500000e+00 -3.400000e+00 7.003325e-01 7.003325e-01 3.501663e-01 -7.003325e-01 2.600000e+00 -3.400000e+00 6.932254e-01 6.932254e-01 3.466127e-01 -6.932254e-01 2.700000e+00 -3.400000e+00 6.859161e-01 6.859161e-01 3.429580e-01 -6.859161e-01 2.800000e+00 -3.400000e+00 6.784123e-01 6.784123e-01 3.392062e-01 -6.784123e-01 2.900000e+00 -3.400000e+00 6.707223e-01 6.707223e-01 3.353612e-01 -6.707223e-01 3.000000e+00 -3.400000e+00 6.628543e-01 6.628543e-01 3.314272e-01 -6.628543e-01 3.100000e+00 -3.400000e+00 6.548166e-01 6.548166e-01 3.274083e-01 -6.548166e-01 3.200000e+00 -3.400000e+00 6.466177e-01 6.466177e-01 3.233089e-01 -6.466177e-01 3.300000e+00 -3.400000e+00 6.382661e-01 6.382661e-01 3.191330e-01 -6.382661e-01 3.400000e+00 -3.400000e+00 6.297704e-01 6.297704e-01 3.148852e-01 -6.297704e-01 3.500000e+00 -3.400000e+00 6.211392e-01 6.211392e-01 3.105696e-01 -6.211392e-01 3.600000e+00 -3.400000e+00 6.123814e-01 6.123814e-01 3.061907e-01 -6.123814e-01 3.700000e+00 -3.400000e+00 6.035056e-01 6.035056e-01 3.017528e-01 -6.035056e-01 3.800000e+00 -3.400000e+00 5.945206e-01 5.945206e-01 2.972603e-01 -5.945206e-01 3.900000e+00 -3.400000e+00 5.854350e-01 5.854350e-01 2.927175e-01 -5.854350e-01 4.000000e+00 -3.400000e+00 5.762579e-01 5.762579e-01 2.881289e-01 -5.762579e-01 4.100000e+00 -3.400000e+00 5.669977e-01 5.669977e-01 2.834989e-01 -5.669977e-01 4.200000e+00 -3.400000e+00 5.576633e-01 5.576633e-01 2.788316e-01 -5.576633e-01 4.300000e+00 -3.400000e+00 5.482631e-01 5.482631e-01 2.741315e-01 -5.482631e-01 4.400000e+00 -3.400000e+00 5.388058e-01 5.388058e-01 2.694029e-01 -5.388058e-01 4.500000e+00 -3.400000e+00 5.293000e-01 5.293000e-01 2.646500e-01 -5.293000e-01 4.600000e+00 -3.400000e+00 5.197538e-01 5.197538e-01 2.598769e-01 -5.197538e-01 4.700000e+00 -3.400000e+00 5.101758e-01 5.101758e-01 2.550879e-01 -5.101758e-01 4.800000e+00 -3.400000e+00 5.005739e-01 5.005739e-01 2.502870e-01 -5.005739e-01 4.900000e+00 -3.400000e+00 4.909564e-01 4.909564e-01 2.454782e-01 -4.909564e-01 -5.000000e+00 -3.300000e+00 4.878243e-01 4.878243e-01 2.439122e-01 -4.878243e-01 -4.900000e+00 -3.300000e+00 4.975795e-01 4.975795e-01 2.487897e-01 -4.975795e-01 -4.800000e+00 -3.300000e+00 5.073267e-01 5.073267e-01 2.536634e-01 -5.073267e-01 -4.700000e+00 -3.300000e+00 5.170582e-01 5.170582e-01 2.585291e-01 -5.170582e-01 -4.600000e+00 -3.300000e+00 5.267655e-01 5.267655e-01 2.633827e-01 -5.267655e-01 -4.500000e+00 -3.300000e+00 5.364403e-01 5.364403e-01 2.682202e-01 -5.364403e-01 -4.400000e+00 -3.300000e+00 5.460745e-01 5.460745e-01 2.730372e-01 -5.460745e-01 -4.300000e+00 -3.300000e+00 5.556593e-01 5.556593e-01 2.778296e-01 -5.556593e-01 -4.200000e+00 -3.300000e+00 5.651863e-01 5.651863e-01 2.825931e-01 -5.651863e-01 -4.100000e+00 -3.300000e+00 5.746467e-01 5.746467e-01 2.873233e-01 -5.746467e-01 -4.000000e+00 -3.300000e+00 5.840317e-01 5.840317e-01 2.920159e-01 -5.840317e-01 -3.900000e+00 -3.300000e+00 5.933327e-01 5.933327e-01 2.966664e-01 -5.933327e-01 -3.800000e+00 -3.300000e+00 6.025407e-01 6.025407e-01 3.012704e-01 -6.025407e-01 -3.700000e+00 -3.300000e+00 6.116470e-01 6.116470e-01 3.058235e-01 -6.116470e-01 -3.600000e+00 -3.300000e+00 6.206425e-01 6.206425e-01 3.103213e-01 -6.206425e-01 -3.500000e+00 -3.300000e+00 6.295186e-01 6.295186e-01 3.147593e-01 -6.295186e-01 -3.400000e+00 -3.300000e+00 6.382661e-01 6.382661e-01 3.191330e-01 -6.382661e-01 -3.300000e+00 -3.300000e+00 6.468765e-01 6.468765e-01 3.234382e-01 -6.468765e-01 -3.200000e+00 -3.300000e+00 6.553407e-01 6.553407e-01 3.276704e-01 -6.553407e-01 -3.100000e+00 -3.300000e+00 6.636503e-01 6.636503e-01 3.318251e-01 -6.636503e-01 -3.000000e+00 -3.300000e+00 6.717964e-01 6.717964e-01 3.358982e-01 -6.717964e-01 -2.900000e+00 -3.300000e+00 6.797705e-01 6.797705e-01 3.398853e-01 -6.797705e-01 -2.800000e+00 -3.300000e+00 6.875643e-01 6.875643e-01 3.437821e-01 -6.875643e-01 -2.700000e+00 -3.300000e+00 6.951692e-01 6.951692e-01 3.475846e-01 -6.951692e-01 -2.600000e+00 -3.300000e+00 7.025772e-01 7.025772e-01 3.512886e-01 -7.025772e-01 -2.500000e+00 -3.300000e+00 7.097802e-01 7.097802e-01 3.548901e-01 -7.097802e-01 -2.400000e+00 -3.300000e+00 7.167702e-01 7.167702e-01 3.583851e-01 -7.167702e-01 -2.300000e+00 -3.300000e+00 7.235397e-01 7.235397e-01 3.617698e-01 -7.235397e-01 -2.200000e+00 -3.300000e+00 7.300808e-01 7.300808e-01 3.650404e-01 -7.300808e-01 -2.100000e+00 -3.300000e+00 7.363867e-01 7.363867e-01 3.681933e-01 -7.363867e-01 -2.000000e+00 -3.300000e+00 7.424498e-01 7.424498e-01 3.712249e-01 -7.424498e-01 -1.900000e+00 -3.300000e+00 7.482636e-01 7.482636e-01 3.741318e-01 -7.482636e-01 -1.800000e+00 -3.300000e+00 7.538213e-01 7.538213e-01 3.769106e-01 -7.538213e-01 -1.700000e+00 -3.300000e+00 7.591165e-01 7.591165e-01 3.795583e-01 -7.591165e-01 -1.600000e+00 -3.300000e+00 7.641433e-01 7.641433e-01 3.820716e-01 -7.641433e-01 -1.500000e+00 -3.300000e+00 7.688957e-01 7.688957e-01 3.844478e-01 -7.688957e-01 -1.400000e+00 -3.300000e+00 7.733682e-01 7.733682e-01 3.866841e-01 -7.733682e-01 -1.300000e+00 -3.300000e+00 7.775557e-01 7.775557e-01 3.887779e-01 -7.775557e-01 -1.200000e+00 -3.300000e+00 7.814533e-01 7.814533e-01 3.907266e-01 -7.814533e-01 -1.100000e+00 -3.300000e+00 7.850562e-01 7.850562e-01 3.925281e-01 -7.850562e-01 -1.000000e+00 -3.300000e+00 7.883604e-01 7.883604e-01 3.941802e-01 -7.883604e-01 -9.000000e-01 -3.300000e+00 7.913619e-01 7.913619e-01 3.956809e-01 -7.913619e-01 -8.000000e-01 -3.300000e+00 7.940571e-01 7.940571e-01 3.970285e-01 -7.940571e-01 -7.000000e-01 -3.300000e+00 7.964428e-01 7.964428e-01 3.982214e-01 -7.964428e-01 -6.000000e-01 -3.300000e+00 7.985162e-01 7.985162e-01 3.992581e-01 -7.985162e-01 -5.000000e-01 -3.300000e+00 8.002749e-01 8.002749e-01 4.001375e-01 -8.002749e-01 -4.000000e-01 -3.300000e+00 8.017167e-01 8.017167e-01 4.008583e-01 -8.017167e-01 -3.000000e-01 -3.300000e+00 8.028399e-01 8.028399e-01 4.014199e-01 -8.028399e-01 -2.000000e-01 -3.300000e+00 8.036431e-01 8.036431e-01 4.018216e-01 -8.036431e-01 -1.000000e-01 -3.300000e+00 8.041254e-01 8.041254e-01 4.020627e-01 -8.041254e-01 0.000000e+00 -3.300000e+00 8.042863e-01 8.042863e-01 4.021432e-01 -8.042863e-01 1.000000e-01 -3.300000e+00 8.041254e-01 8.041254e-01 4.020627e-01 -8.041254e-01 2.000000e-01 -3.300000e+00 8.036431e-01 8.036431e-01 4.018216e-01 -8.036431e-01 3.000000e-01 -3.300000e+00 8.028399e-01 8.028399e-01 4.014199e-01 -8.028399e-01 4.000000e-01 -3.300000e+00 8.017167e-01 8.017167e-01 4.008583e-01 -8.017167e-01 5.000000e-01 -3.300000e+00 8.002749e-01 8.002749e-01 4.001375e-01 -8.002749e-01 6.000000e-01 -3.300000e+00 7.985162e-01 7.985162e-01 3.992581e-01 -7.985162e-01 7.000000e-01 -3.300000e+00 7.964428e-01 7.964428e-01 3.982214e-01 -7.964428e-01 8.000000e-01 -3.300000e+00 7.940571e-01 7.940571e-01 3.970285e-01 -7.940571e-01 9.000000e-01 -3.300000e+00 7.913619e-01 7.913619e-01 3.956809e-01 -7.913619e-01 1.000000e+00 -3.300000e+00 7.883604e-01 7.883604e-01 3.941802e-01 -7.883604e-01 1.100000e+00 -3.300000e+00 7.850562e-01 7.850562e-01 3.925281e-01 -7.850562e-01 1.200000e+00 -3.300000e+00 7.814533e-01 7.814533e-01 3.907266e-01 -7.814533e-01 1.300000e+00 -3.300000e+00 7.775557e-01 7.775557e-01 3.887779e-01 -7.775557e-01 1.400000e+00 -3.300000e+00 7.733682e-01 7.733682e-01 3.866841e-01 -7.733682e-01 1.500000e+00 -3.300000e+00 7.688957e-01 7.688957e-01 3.844478e-01 -7.688957e-01 1.600000e+00 -3.300000e+00 7.641433e-01 7.641433e-01 3.820716e-01 -7.641433e-01 1.700000e+00 -3.300000e+00 7.591165e-01 7.591165e-01 3.795583e-01 -7.591165e-01 1.800000e+00 -3.300000e+00 7.538213e-01 7.538213e-01 3.769106e-01 -7.538213e-01 1.900000e+00 -3.300000e+00 7.482636e-01 7.482636e-01 3.741318e-01 -7.482636e-01 2.000000e+00 -3.300000e+00 7.424498e-01 7.424498e-01 3.712249e-01 -7.424498e-01 2.100000e+00 -3.300000e+00 7.363867e-01 7.363867e-01 3.681933e-01 -7.363867e-01 2.200000e+00 -3.300000e+00 7.300808e-01 7.300808e-01 3.650404e-01 -7.300808e-01 2.300000e+00 -3.300000e+00 7.235397e-01 7.235397e-01 3.617698e-01 -7.235397e-01 2.400000e+00 -3.300000e+00 7.167702e-01 7.167702e-01 3.583851e-01 -7.167702e-01 2.500000e+00 -3.300000e+00 7.097802e-01 7.097802e-01 3.548901e-01 -7.097802e-01 2.600000e+00 -3.300000e+00 7.025772e-01 7.025772e-01 3.512886e-01 -7.025772e-01 2.700000e+00 -3.300000e+00 6.951692e-01 6.951692e-01 3.475846e-01 -6.951692e-01 2.800000e+00 -3.300000e+00 6.875643e-01 6.875643e-01 3.437821e-01 -6.875643e-01 2.900000e+00 -3.300000e+00 6.797705e-01 6.797705e-01 3.398853e-01 -6.797705e-01 3.000000e+00 -3.300000e+00 6.717964e-01 6.717964e-01 3.358982e-01 -6.717964e-01 3.100000e+00 -3.300000e+00 6.636503e-01 6.636503e-01 3.318251e-01 -6.636503e-01 3.200000e+00 -3.300000e+00 6.553407e-01 6.553407e-01 3.276704e-01 -6.553407e-01 3.300000e+00 -3.300000e+00 6.468765e-01 6.468765e-01 3.234382e-01 -6.468765e-01 3.400000e+00 -3.300000e+00 6.382661e-01 6.382661e-01 3.191330e-01 -6.382661e-01 3.500000e+00 -3.300000e+00 6.295186e-01 6.295186e-01 3.147593e-01 -6.295186e-01 3.600000e+00 -3.300000e+00 6.206425e-01 6.206425e-01 3.103213e-01 -6.206425e-01 3.700000e+00 -3.300000e+00 6.116470e-01 6.116470e-01 3.058235e-01 -6.116470e-01 3.800000e+00 -3.300000e+00 6.025407e-01 6.025407e-01 3.012704e-01 -6.025407e-01 3.900000e+00 -3.300000e+00 5.933327e-01 5.933327e-01 2.966664e-01 -5.933327e-01 4.000000e+00 -3.300000e+00 5.840317e-01 5.840317e-01 2.920159e-01 -5.840317e-01 4.100000e+00 -3.300000e+00 5.746467e-01 5.746467e-01 2.873233e-01 -5.746467e-01 4.200000e+00 -3.300000e+00 5.651863e-01 5.651863e-01 2.825931e-01 -5.651863e-01 4.300000e+00 -3.300000e+00 5.556593e-01 5.556593e-01 2.778296e-01 -5.556593e-01 4.400000e+00 -3.300000e+00 5.460745e-01 5.460745e-01 2.730372e-01 -5.460745e-01 4.500000e+00 -3.300000e+00 5.364403e-01 5.364403e-01 2.682202e-01 -5.364403e-01 4.600000e+00 -3.300000e+00 5.267655e-01 5.267655e-01 2.633827e-01 -5.267655e-01 4.700000e+00 -3.300000e+00 5.170582e-01 5.170582e-01 2.585291e-01 -5.170582e-01 4.800000e+00 -3.300000e+00 5.073267e-01 5.073267e-01 2.536634e-01 -5.073267e-01 4.900000e+00 -3.300000e+00 4.975795e-01 4.975795e-01 2.487897e-01 -4.975795e-01 -5.000000e+00 -3.200000e+00 4.942074e-01 4.942074e-01 2.471037e-01 -4.942074e-01 -4.900000e+00 -3.200000e+00 5.040902e-01 5.040902e-01 2.520451e-01 -5.040902e-01 -4.800000e+00 -3.200000e+00 5.139651e-01 5.139651e-01 2.569825e-01 -5.139651e-01 -4.700000e+00 -3.200000e+00 5.238238e-01 5.238238e-01 2.619119e-01 -5.238238e-01 -4.600000e+00 -3.200000e+00 5.336581e-01 5.336581e-01 2.668290e-01 -5.336581e-01 -4.500000e+00 -3.200000e+00 5.434595e-01 5.434595e-01 2.717298e-01 -5.434595e-01 -4.400000e+00 -3.200000e+00 5.532197e-01 5.532197e-01 2.766099e-01 -5.532197e-01 -4.300000e+00 -3.200000e+00 5.629300e-01 5.629300e-01 2.814650e-01 -5.629300e-01 -4.200000e+00 -3.200000e+00 5.725816e-01 5.725816e-01 2.862908e-01 -5.725816e-01 -4.100000e+00 -3.200000e+00 5.821658e-01 5.821658e-01 2.910829e-01 -5.821658e-01 -4.000000e+00 -3.200000e+00 5.916737e-01 5.916737e-01 2.958368e-01 -5.916737e-01 -3.900000e+00 -3.200000e+00 6.010964e-01 6.010964e-01 3.005482e-01 -6.010964e-01 -3.800000e+00 -3.200000e+00 6.104249e-01 6.104249e-01 3.052124e-01 -6.104249e-01 -3.700000e+00 -3.200000e+00 6.196503e-01 6.196503e-01 3.098252e-01 -6.196503e-01 -3.600000e+00 -3.200000e+00 6.287636e-01 6.287636e-01 3.143818e-01 -6.287636e-01 -3.500000e+00 -3.200000e+00 6.377557e-01 6.377557e-01 3.188778e-01 -6.377557e-01 -3.400000e+00 -3.200000e+00 6.466177e-01 6.466177e-01 3.233089e-01 -6.466177e-01 -3.300000e+00 -3.200000e+00 6.553407e-01 6.553407e-01 3.276704e-01 -6.553407e-01 -3.200000e+00 -3.200000e+00 6.639158e-01 6.639158e-01 3.319579e-01 -6.639158e-01 -3.100000e+00 -3.200000e+00 6.723340e-01 6.723340e-01 3.361670e-01 -6.723340e-01 -3.000000e+00 -3.200000e+00 6.805868e-01 6.805868e-01 3.402934e-01 -6.805868e-01 -2.900000e+00 -3.200000e+00 6.886652e-01 6.886652e-01 3.443326e-01 -6.886652e-01 -2.800000e+00 -3.200000e+00 6.965610e-01 6.965610e-01 3.482805e-01 -6.965610e-01 -2.700000e+00 -3.200000e+00 7.042654e-01 7.042654e-01 3.521327e-01 -7.042654e-01 -2.600000e+00 -3.200000e+00 7.117704e-01 7.117704e-01 3.558852e-01 -7.117704e-01 -2.500000e+00 -3.200000e+00 7.190675e-01 7.190675e-01 3.595338e-01 -7.190675e-01 -2.400000e+00 -3.200000e+00 7.261490e-01 7.261490e-01 3.630745e-01 -7.261490e-01 -2.300000e+00 -3.200000e+00 7.330070e-01 7.330070e-01 3.665035e-01 -7.330070e-01 -2.200000e+00 -3.200000e+00 7.396339e-01 7.396339e-01 3.698169e-01 -7.396339e-01 -2.100000e+00 -3.200000e+00 7.460222e-01 7.460222e-01 3.730111e-01 -7.460222e-01 -2.000000e+00 -3.200000e+00 7.521647e-01 7.521647e-01 3.760823e-01 -7.521647e-01 -1.900000e+00 -3.200000e+00 7.580545e-01 7.580545e-01 3.790272e-01 -7.580545e-01 -1.800000e+00 -3.200000e+00 7.636849e-01 7.636849e-01 3.818425e-01 -7.636849e-01 -1.700000e+00 -3.200000e+00 7.690495e-01 7.690495e-01 3.845247e-01 -7.690495e-01 -1.600000e+00 -3.200000e+00 7.741420e-01 7.741420e-01 3.870710e-01 -7.741420e-01 -1.500000e+00 -3.200000e+00 7.789565e-01 7.789565e-01 3.894783e-01 -7.789565e-01 -1.400000e+00 -3.200000e+00 7.834876e-01 7.834876e-01 3.917438e-01 -7.834876e-01 -1.300000e+00 -3.200000e+00 7.877299e-01 7.877299e-01 3.938650e-01 -7.877299e-01 -1.200000e+00 -3.200000e+00 7.916784e-01 7.916784e-01 3.958392e-01 -7.916784e-01 -1.100000e+00 -3.200000e+00 7.953286e-01 7.953286e-01 3.976643e-01 -7.953286e-01 -1.000000e+00 -3.200000e+00 7.986760e-01 7.986760e-01 3.993380e-01 -7.986760e-01 -9.000000e-01 -3.200000e+00 8.017167e-01 8.017167e-01 4.008583e-01 -8.017167e-01 -8.000000e-01 -3.200000e+00 8.044472e-01 8.044472e-01 4.022236e-01 -8.044472e-01 -7.000000e-01 -3.200000e+00 8.068641e-01 8.068641e-01 4.034321e-01 -8.068641e-01 -6.000000e-01 -3.200000e+00 8.089647e-01 8.089647e-01 4.044824e-01 -8.089647e-01 -5.000000e-01 -3.200000e+00 8.107464e-01 8.107464e-01 4.053732e-01 -8.107464e-01 -4.000000e-01 -3.200000e+00 8.122070e-01 8.122070e-01 4.061035e-01 -8.122070e-01 -3.000000e-01 -3.200000e+00 8.133450e-01 8.133450e-01 4.066725e-01 -8.133450e-01 -2.000000e-01 -3.200000e+00 8.141587e-01 8.141587e-01 4.070793e-01 -8.141587e-01 -1.000000e-01 -3.200000e+00 8.146473e-01 8.146473e-01 4.073237e-01 -8.146473e-01 0.000000e+00 -3.200000e+00 8.148103e-01 8.148103e-01 4.074051e-01 -8.148103e-01 1.000000e-01 -3.200000e+00 8.146473e-01 8.146473e-01 4.073237e-01 -8.146473e-01 2.000000e-01 -3.200000e+00 8.141587e-01 8.141587e-01 4.070793e-01 -8.141587e-01 3.000000e-01 -3.200000e+00 8.133450e-01 8.133450e-01 4.066725e-01 -8.133450e-01 4.000000e-01 -3.200000e+00 8.122070e-01 8.122070e-01 4.061035e-01 -8.122070e-01 5.000000e-01 -3.200000e+00 8.107464e-01 8.107464e-01 4.053732e-01 -8.107464e-01 6.000000e-01 -3.200000e+00 8.089647e-01 8.089647e-01 4.044824e-01 -8.089647e-01 7.000000e-01 -3.200000e+00 8.068641e-01 8.068641e-01 4.034321e-01 -8.068641e-01 8.000000e-01 -3.200000e+00 8.044472e-01 8.044472e-01 4.022236e-01 -8.044472e-01 9.000000e-01 -3.200000e+00 8.017167e-01 8.017167e-01 4.008583e-01 -8.017167e-01 1.000000e+00 -3.200000e+00 7.986760e-01 7.986760e-01 3.993380e-01 -7.986760e-01 1.100000e+00 -3.200000e+00 7.953286e-01 7.953286e-01 3.976643e-01 -7.953286e-01 1.200000e+00 -3.200000e+00 7.916784e-01 7.916784e-01 3.958392e-01 -7.916784e-01 1.300000e+00 -3.200000e+00 7.877299e-01 7.877299e-01 3.938650e-01 -7.877299e-01 1.400000e+00 -3.200000e+00 7.834876e-01 7.834876e-01 3.917438e-01 -7.834876e-01 1.500000e+00 -3.200000e+00 7.789565e-01 7.789565e-01 3.894783e-01 -7.789565e-01 1.600000e+00 -3.200000e+00 7.741420e-01 7.741420e-01 3.870710e-01 -7.741420e-01 1.700000e+00 -3.200000e+00 7.690495e-01 7.690495e-01 3.845247e-01 -7.690495e-01 1.800000e+00 -3.200000e+00 7.636849e-01 7.636849e-01 3.818425e-01 -7.636849e-01 1.900000e+00 -3.200000e+00 7.580545e-01 7.580545e-01 3.790272e-01 -7.580545e-01 2.000000e+00 -3.200000e+00 7.521647e-01 7.521647e-01 3.760823e-01 -7.521647e-01 2.100000e+00 -3.200000e+00 7.460222e-01 7.460222e-01 3.730111e-01 -7.460222e-01 2.200000e+00 -3.200000e+00 7.396339e-01 7.396339e-01 3.698169e-01 -7.396339e-01 2.300000e+00 -3.200000e+00 7.330070e-01 7.330070e-01 3.665035e-01 -7.330070e-01 2.400000e+00 -3.200000e+00 7.261490e-01 7.261490e-01 3.630745e-01 -7.261490e-01 2.500000e+00 -3.200000e+00 7.190675e-01 7.190675e-01 3.595338e-01 -7.190675e-01 2.600000e+00 -3.200000e+00 7.117704e-01 7.117704e-01 3.558852e-01 -7.117704e-01 2.700000e+00 -3.200000e+00 7.042654e-01 7.042654e-01 3.521327e-01 -7.042654e-01 2.800000e+00 -3.200000e+00 6.965610e-01 6.965610e-01 3.482805e-01 -6.965610e-01 2.900000e+00 -3.200000e+00 6.886652e-01 6.886652e-01 3.443326e-01 -6.886652e-01 3.000000e+00 -3.200000e+00 6.805868e-01 6.805868e-01 3.402934e-01 -6.805868e-01 3.100000e+00 -3.200000e+00 6.723340e-01 6.723340e-01 3.361670e-01 -6.723340e-01 3.200000e+00 -3.200000e+00 6.639158e-01 6.639158e-01 3.319579e-01 -6.639158e-01 3.300000e+00 -3.200000e+00 6.553407e-01 6.553407e-01 3.276704e-01 -6.553407e-01 3.400000e+00 -3.200000e+00 6.466177e-01 6.466177e-01 3.233089e-01 -6.466177e-01 3.500000e+00 -3.200000e+00 6.377557e-01 6.377557e-01 3.188778e-01 -6.377557e-01 3.600000e+00 -3.200000e+00 6.287636e-01 6.287636e-01 3.143818e-01 -6.287636e-01 3.700000e+00 -3.200000e+00 6.196503e-01 6.196503e-01 3.098252e-01 -6.196503e-01 3.800000e+00 -3.200000e+00 6.104249e-01 6.104249e-01 3.052124e-01 -6.104249e-01 3.900000e+00 -3.200000e+00 6.010964e-01 6.010964e-01 3.005482e-01 -6.010964e-01 4.000000e+00 -3.200000e+00 5.916737e-01 5.916737e-01 2.958368e-01 -5.916737e-01 4.100000e+00 -3.200000e+00 5.821658e-01 5.821658e-01 2.910829e-01 -5.821658e-01 4.200000e+00 -3.200000e+00 5.725816e-01 5.725816e-01 2.862908e-01 -5.725816e-01 4.300000e+00 -3.200000e+00 5.629300e-01 5.629300e-01 2.814650e-01 -5.629300e-01 4.400000e+00 -3.200000e+00 5.532197e-01 5.532197e-01 2.766099e-01 -5.532197e-01 4.500000e+00 -3.200000e+00 5.434595e-01 5.434595e-01 2.717298e-01 -5.434595e-01 4.600000e+00 -3.200000e+00 5.336581e-01 5.336581e-01 2.668290e-01 -5.336581e-01 4.700000e+00 -3.200000e+00 5.238238e-01 5.238238e-01 2.619119e-01 -5.238238e-01 4.800000e+00 -3.200000e+00 5.139651e-01 5.139651e-01 2.569825e-01 -5.139651e-01 4.900000e+00 -3.200000e+00 5.040902e-01 5.040902e-01 2.520451e-01 -5.040902e-01 -5.000000e+00 -3.100000e+00 5.004738e-01 5.004738e-01 2.502369e-01 -5.004738e-01 -4.900000e+00 -3.100000e+00 5.104820e-01 5.104820e-01 2.552410e-01 -5.104820e-01 -4.800000e+00 -3.100000e+00 5.204820e-01 5.204820e-01 2.602410e-01 -5.204820e-01 -4.700000e+00 -3.100000e+00 5.304657e-01 5.304657e-01 2.652329e-01 -5.304657e-01 -4.600000e+00 -3.100000e+00 5.404247e-01 5.404247e-01 2.702124e-01 -5.404247e-01 -4.500000e+00 -3.100000e+00 5.503505e-01 5.503505e-01 2.751752e-01 -5.503505e-01 -4.400000e+00 -3.100000e+00 5.602344e-01 5.602344e-01 2.801172e-01 -5.602344e-01 -4.300000e+00 -3.100000e+00 5.700678e-01 5.700678e-01 2.850339e-01 -5.700678e-01 -4.200000e+00 -3.100000e+00 5.798418e-01 5.798418e-01 2.899209e-01 -5.798418e-01 -4.100000e+00 -3.100000e+00 5.895475e-01 5.895475e-01 2.947738e-01 -5.895475e-01 -4.000000e+00 -3.100000e+00 5.991759e-01 5.991759e-01 2.995880e-01 -5.991759e-01 -3.900000e+00 -3.100000e+00 6.087181e-01 6.087181e-01 3.043590e-01 -6.087181e-01 -3.800000e+00 -3.100000e+00 6.181649e-01 6.181649e-01 3.090824e-01 -6.181649e-01 -3.700000e+00 -3.100000e+00 6.275073e-01 6.275073e-01 3.137536e-01 -6.275073e-01 -3.600000e+00 -3.100000e+00 6.367361e-01 6.367361e-01 3.183680e-01 -6.367361e-01 -3.500000e+00 -3.100000e+00 6.458423e-01 6.458423e-01 3.229211e-01 -6.458423e-01 -3.400000e+00 -3.100000e+00 6.548166e-01 6.548166e-01 3.274083e-01 -6.548166e-01 -3.300000e+00 -3.100000e+00 6.636503e-01 6.636503e-01 3.318251e-01 -6.636503e-01 -3.200000e+00 -3.100000e+00 6.723340e-01 6.723340e-01 3.361670e-01 -6.723340e-01 -3.100000e+00 -3.100000e+00 6.808590e-01 6.808590e-01 3.404295e-01 -6.808590e-01 -3.000000e+00 -3.100000e+00 6.892164e-01 6.892164e-01 3.446082e-01 -6.892164e-01 -2.900000e+00 -3.100000e+00 6.973973e-01 6.973973e-01 3.486986e-01 -6.973973e-01 -2.800000e+00 -3.100000e+00 7.053931e-01 7.053931e-01 3.526966e-01 -7.053931e-01 -2.700000e+00 -3.100000e+00 7.131953e-01 7.131953e-01 3.565976e-01 -7.131953e-01 -2.600000e+00 -3.100000e+00 7.207954e-01 7.207954e-01 3.603977e-01 -7.207954e-01 -2.500000e+00 -3.100000e+00 7.281851e-01 7.281851e-01 3.640926e-01 -7.281851e-01 -2.400000e+00 -3.100000e+00 7.353564e-01 7.353564e-01 3.676782e-01 -7.353564e-01 -2.300000e+00 -3.100000e+00 7.423013e-01 7.423013e-01 3.711507e-01 -7.423013e-01 -2.200000e+00 -3.100000e+00 7.490122e-01 7.490122e-01 3.745061e-01 -7.490122e-01 -2.100000e+00 -3.100000e+00 7.554815e-01 7.554815e-01 3.777407e-01 -7.554815e-01 -2.000000e+00 -3.100000e+00 7.617019e-01 7.617019e-01 3.808509e-01 -7.617019e-01 -1.900000e+00 -3.100000e+00 7.676664e-01 7.676664e-01 3.838332e-01 -7.676664e-01 -1.800000e+00 -3.100000e+00 7.733682e-01 7.733682e-01 3.866841e-01 -7.733682e-01 -1.700000e+00 -3.100000e+00 7.788008e-01 7.788008e-01 3.894004e-01 -7.788008e-01 -1.600000e+00 -3.100000e+00 7.839578e-01 7.839578e-01 3.919789e-01 -7.839578e-01 -1.500000e+00 -3.100000e+00 7.888335e-01 7.888335e-01 3.944167e-01 -7.888335e-01 -1.400000e+00 -3.100000e+00 7.934220e-01 7.934220e-01 3.967110e-01 -7.934220e-01 -1.300000e+00 -3.100000e+00 7.977181e-01 7.977181e-01 3.988591e-01 -7.977181e-01 -1.200000e+00 -3.100000e+00 8.017167e-01 8.017167e-01 4.008583e-01 -8.017167e-01 -1.100000e+00 -3.100000e+00 8.054131e-01 8.054131e-01 4.027065e-01 -8.054131e-01 -1.000000e+00 -3.100000e+00 8.088029e-01 8.088029e-01 4.044015e-01 -8.088029e-01 -9.000000e-01 -3.100000e+00 8.118822e-01 8.118822e-01 4.059411e-01 -8.118822e-01 -8.000000e-01 -3.100000e+00 8.146473e-01 8.146473e-01 4.073237e-01 -8.146473e-01 -7.000000e-01 -3.100000e+00 8.170949e-01 8.170949e-01 4.085475e-01 -8.170949e-01 -6.000000e-01 -3.100000e+00 8.192222e-01 8.192222e-01 4.096111e-01 -8.192222e-01 -5.000000e-01 -3.100000e+00 8.210264e-01 8.210264e-01 4.105132e-01 -8.210264e-01 -4.000000e-01 -3.100000e+00 8.225056e-01 8.225056e-01 4.112528e-01 -8.225056e-01 -3.000000e-01 -3.100000e+00 8.236579e-01 8.236579e-01 4.118289e-01 -8.236579e-01 -2.000000e-01 -3.100000e+00 8.244820e-01 8.244820e-01 4.122410e-01 -8.244820e-01 -1.000000e-01 -3.100000e+00 8.249768e-01 8.249768e-01 4.124884e-01 -8.249768e-01 0.000000e+00 -3.100000e+00 8.251418e-01 8.251418e-01 4.125709e-01 -8.251418e-01 1.000000e-01 -3.100000e+00 8.249768e-01 8.249768e-01 4.124884e-01 -8.249768e-01 2.000000e-01 -3.100000e+00 8.244820e-01 8.244820e-01 4.122410e-01 -8.244820e-01 3.000000e-01 -3.100000e+00 8.236579e-01 8.236579e-01 4.118289e-01 -8.236579e-01 4.000000e-01 -3.100000e+00 8.225056e-01 8.225056e-01 4.112528e-01 -8.225056e-01 5.000000e-01 -3.100000e+00 8.210264e-01 8.210264e-01 4.105132e-01 -8.210264e-01 6.000000e-01 -3.100000e+00 8.192222e-01 8.192222e-01 4.096111e-01 -8.192222e-01 7.000000e-01 -3.100000e+00 8.170949e-01 8.170949e-01 4.085475e-01 -8.170949e-01 8.000000e-01 -3.100000e+00 8.146473e-01 8.146473e-01 4.073237e-01 -8.146473e-01 9.000000e-01 -3.100000e+00 8.118822e-01 8.118822e-01 4.059411e-01 -8.118822e-01 1.000000e+00 -3.100000e+00 8.088029e-01 8.088029e-01 4.044015e-01 -8.088029e-01 1.100000e+00 -3.100000e+00 8.054131e-01 8.054131e-01 4.027065e-01 -8.054131e-01 1.200000e+00 -3.100000e+00 8.017167e-01 8.017167e-01 4.008583e-01 -8.017167e-01 1.300000e+00 -3.100000e+00 7.977181e-01 7.977181e-01 3.988591e-01 -7.977181e-01 1.400000e+00 -3.100000e+00 7.934220e-01 7.934220e-01 3.967110e-01 -7.934220e-01 1.500000e+00 -3.100000e+00 7.888335e-01 7.888335e-01 3.944167e-01 -7.888335e-01 1.600000e+00 -3.100000e+00 7.839578e-01 7.839578e-01 3.919789e-01 -7.839578e-01 1.700000e+00 -3.100000e+00 7.788008e-01 7.788008e-01 3.894004e-01 -7.788008e-01 1.800000e+00 -3.100000e+00 7.733682e-01 7.733682e-01 3.866841e-01 -7.733682e-01 1.900000e+00 -3.100000e+00 7.676664e-01 7.676664e-01 3.838332e-01 -7.676664e-01 2.000000e+00 -3.100000e+00 7.617019e-01 7.617019e-01 3.808509e-01 -7.617019e-01 2.100000e+00 -3.100000e+00 7.554815e-01 7.554815e-01 3.777407e-01 -7.554815e-01 2.200000e+00 -3.100000e+00 7.490122e-01 7.490122e-01 3.745061e-01 -7.490122e-01 2.300000e+00 -3.100000e+00 7.423013e-01 7.423013e-01 3.711507e-01 -7.423013e-01 2.400000e+00 -3.100000e+00 7.353564e-01 7.353564e-01 3.676782e-01 -7.353564e-01 2.500000e+00 -3.100000e+00 7.281851e-01 7.281851e-01 3.640926e-01 -7.281851e-01 2.600000e+00 -3.100000e+00 7.207954e-01 7.207954e-01 3.603977e-01 -7.207954e-01 2.700000e+00 -3.100000e+00 7.131953e-01 7.131953e-01 3.565976e-01 -7.131953e-01 2.800000e+00 -3.100000e+00 7.053931e-01 7.053931e-01 3.526966e-01 -7.053931e-01 2.900000e+00 -3.100000e+00 6.973973e-01 6.973973e-01 3.486986e-01 -6.973973e-01 3.000000e+00 -3.100000e+00 6.892164e-01 6.892164e-01 3.446082e-01 -6.892164e-01 3.100000e+00 -3.100000e+00 6.808590e-01 6.808590e-01 3.404295e-01 -6.808590e-01 3.200000e+00 -3.100000e+00 6.723340e-01 6.723340e-01 3.361670e-01 -6.723340e-01 3.300000e+00 -3.100000e+00 6.636503e-01 6.636503e-01 3.318251e-01 -6.636503e-01 3.400000e+00 -3.100000e+00 6.548166e-01 6.548166e-01 3.274083e-01 -6.548166e-01 3.500000e+00 -3.100000e+00 6.458423e-01 6.458423e-01 3.229211e-01 -6.458423e-01 3.600000e+00 -3.100000e+00 6.367361e-01 6.367361e-01 3.183680e-01 -6.367361e-01 3.700000e+00 -3.100000e+00 6.275073e-01 6.275073e-01 3.137536e-01 -6.275073e-01 3.800000e+00 -3.100000e+00 6.181649e-01 6.181649e-01 3.090824e-01 -6.181649e-01 3.900000e+00 -3.100000e+00 6.087181e-01 6.087181e-01 3.043590e-01 -6.087181e-01 4.000000e+00 -3.100000e+00 5.991759e-01 5.991759e-01 2.995880e-01 -5.991759e-01 4.100000e+00 -3.100000e+00 5.895475e-01 5.895475e-01 2.947738e-01 -5.895475e-01 4.200000e+00 -3.100000e+00 5.798418e-01 5.798418e-01 2.899209e-01 -5.798418e-01 4.300000e+00 -3.100000e+00 5.700678e-01 5.700678e-01 2.850339e-01 -5.700678e-01 4.400000e+00 -3.100000e+00 5.602344e-01 5.602344e-01 2.801172e-01 -5.602344e-01 4.500000e+00 -3.100000e+00 5.503505e-01 5.503505e-01 2.751752e-01 -5.503505e-01 4.600000e+00 -3.100000e+00 5.404247e-01 5.404247e-01 2.702124e-01 -5.404247e-01 4.700000e+00 -3.100000e+00 5.304657e-01 5.304657e-01 2.652329e-01 -5.304657e-01 4.800000e+00 -3.100000e+00 5.204820e-01 5.204820e-01 2.602410e-01 -5.204820e-01 4.900000e+00 -3.100000e+00 5.104820e-01 5.104820e-01 2.552410e-01 -5.104820e-01 -5.000000e+00 -3.000000e+00 5.066170e-01 5.066170e-01 2.533085e-01 -5.066170e-01 -4.900000e+00 -3.000000e+00 5.167480e-01 5.167480e-01 2.583740e-01 -5.167480e-01 -4.800000e+00 -3.000000e+00 5.268708e-01 5.268708e-01 2.634354e-01 -5.268708e-01 -4.700000e+00 -3.000000e+00 5.369771e-01 5.369771e-01 2.684885e-01 -5.369771e-01 -4.600000e+00 -3.000000e+00 5.470583e-01 5.470583e-01 2.735291e-01 -5.470583e-01 -4.500000e+00 -3.000000e+00 5.571059e-01 5.571059e-01 2.785529e-01 -5.571059e-01 -4.400000e+00 -3.000000e+00 5.671111e-01 5.671111e-01 2.835556e-01 -5.671111e-01 -4.300000e+00 -3.000000e+00 5.770652e-01 5.770652e-01 2.885326e-01 -5.770652e-01 -4.200000e+00 -3.000000e+00 5.869592e-01 5.869592e-01 2.934796e-01 -5.869592e-01 -4.100000e+00 -3.000000e+00 5.967840e-01 5.967840e-01 2.983920e-01 -5.967840e-01 -4.000000e+00 -3.000000e+00 6.065307e-01 6.065307e-01 3.032653e-01 -6.065307e-01 -3.900000e+00 -3.000000e+00 6.161900e-01 6.161900e-01 3.080950e-01 -6.161900e-01 -3.800000e+00 -3.000000e+00 6.257527e-01 6.257527e-01 3.128763e-01 -6.257527e-01 -3.700000e+00 -3.000000e+00 6.352097e-01 6.352097e-01 3.176049e-01 -6.352097e-01 -3.600000e+00 -3.000000e+00 6.445519e-01 6.445519e-01 3.222759e-01 -6.445519e-01 -3.500000e+00 -3.000000e+00 6.537698e-01 6.537698e-01 3.268849e-01 -6.537698e-01 -3.400000e+00 -3.000000e+00 6.628543e-01 6.628543e-01 3.314272e-01 -6.628543e-01 -3.300000e+00 -3.000000e+00 6.717964e-01 6.717964e-01 3.358982e-01 -6.717964e-01 -3.200000e+00 -3.000000e+00 6.805868e-01 6.805868e-01 3.402934e-01 -6.805868e-01 -3.100000e+00 -3.000000e+00 6.892164e-01 6.892164e-01 3.446082e-01 -6.892164e-01 -3.000000e+00 -3.000000e+00 6.976763e-01 6.976763e-01 3.488382e-01 -6.976763e-01 -2.900000e+00 -3.000000e+00 7.059577e-01 7.059577e-01 3.529788e-01 -7.059577e-01 -2.800000e+00 -3.000000e+00 7.140516e-01 7.140516e-01 3.570258e-01 -7.140516e-01 -2.700000e+00 -3.000000e+00 7.219496e-01 7.219496e-01 3.609748e-01 -7.219496e-01 -2.600000e+00 -3.000000e+00 7.296429e-01 7.296429e-01 3.648215e-01 -7.296429e-01 -2.500000e+00 -3.000000e+00 7.371234e-01 7.371234e-01 3.685617e-01 -7.371234e-01 -2.400000e+00 -3.000000e+00 7.443827e-01 7.443827e-01 3.721913e-01 -7.443827e-01 -2.300000e+00 -3.000000e+00 7.514129e-01 7.514129e-01 3.757065e-01 -7.514129e-01 -2.200000e+00 -3.000000e+00 7.582061e-01 7.582061e-01 3.791031e-01 -7.582061e-01 -2.100000e+00 -3.000000e+00 7.647548e-01 7.647548e-01 3.823774e-01 -7.647548e-01 -2.000000e+00 -3.000000e+00 7.710516e-01 7.710516e-01 3.855258e-01 -7.710516e-01 -1.900000e+00 -3.000000e+00 7.770893e-01 7.770893e-01 3.885446e-01 -7.770893e-01 -1.800000e+00 -3.000000e+00 7.828611e-01 7.828611e-01 3.914306e-01 -7.828611e-01 -1.700000e+00 -3.000000e+00 7.883604e-01 7.883604e-01 3.941802e-01 -7.883604e-01 -1.600000e+00 -3.000000e+00 7.935807e-01 7.935807e-01 3.967904e-01 -7.935807e-01 -1.500000e+00 -3.000000e+00 7.985162e-01 7.985162e-01 3.992581e-01 -7.985162e-01 -1.400000e+00 -3.000000e+00 8.031611e-01 8.031611e-01 4.015805e-01 -8.031611e-01 -1.300000e+00 -3.000000e+00 8.075098e-01 8.075098e-01 4.037549e-01 -8.075098e-01 -1.200000e+00 -3.000000e+00 8.115575e-01 8.115575e-01 4.057788e-01 -8.115575e-01 -1.100000e+00 -3.000000e+00 8.152993e-01 8.152993e-01 4.076496e-01 -8.152993e-01 -1.000000e+00 -3.000000e+00 8.187308e-01 8.187308e-01 4.093654e-01 -8.187308e-01 -9.000000e-01 -3.000000e+00 8.218479e-01 8.218479e-01 4.109239e-01 -8.218479e-01 -8.000000e-01 -3.000000e+00 8.246469e-01 8.246469e-01 4.123234e-01 -8.246469e-01 -7.000000e-01 -3.000000e+00 8.271245e-01 8.271245e-01 4.135623e-01 -8.271245e-01 -6.000000e-01 -3.000000e+00 8.292779e-01 8.292779e-01 4.146389e-01 -8.292779e-01 -5.000000e-01 -3.000000e+00 8.311043e-01 8.311043e-01 4.155521e-01 -8.311043e-01 -4.000000e-01 -3.000000e+00 8.326016e-01 8.326016e-01 4.163008e-01 -8.326016e-01 -3.000000e-01 -3.000000e+00 8.337681e-01 8.337681e-01 4.168840e-01 -8.337681e-01 -2.000000e-01 -3.000000e+00 8.346022e-01 8.346022e-01 4.173011e-01 -8.346022e-01 -1.000000e-01 -3.000000e+00 8.351032e-01 8.351032e-01 4.175516e-01 -8.351032e-01 0.000000e+00 -3.000000e+00 8.352702e-01 8.352702e-01 4.176351e-01 -8.352702e-01 1.000000e-01 -3.000000e+00 8.351032e-01 8.351032e-01 4.175516e-01 -8.351032e-01 2.000000e-01 -3.000000e+00 8.346022e-01 8.346022e-01 4.173011e-01 -8.346022e-01 3.000000e-01 -3.000000e+00 8.337681e-01 8.337681e-01 4.168840e-01 -8.337681e-01 4.000000e-01 -3.000000e+00 8.326016e-01 8.326016e-01 4.163008e-01 -8.326016e-01 5.000000e-01 -3.000000e+00 8.311043e-01 8.311043e-01 4.155521e-01 -8.311043e-01 6.000000e-01 -3.000000e+00 8.292779e-01 8.292779e-01 4.146389e-01 -8.292779e-01 7.000000e-01 -3.000000e+00 8.271245e-01 8.271245e-01 4.135623e-01 -8.271245e-01 8.000000e-01 -3.000000e+00 8.246469e-01 8.246469e-01 4.123234e-01 -8.246469e-01 9.000000e-01 -3.000000e+00 8.218479e-01 8.218479e-01 4.109239e-01 -8.218479e-01 1.000000e+00 -3.000000e+00 8.187308e-01 8.187308e-01 4.093654e-01 -8.187308e-01 1.100000e+00 -3.000000e+00 8.152993e-01 8.152993e-01 4.076496e-01 -8.152993e-01 1.200000e+00 -3.000000e+00 8.115575e-01 8.115575e-01 4.057788e-01 -8.115575e-01 1.300000e+00 -3.000000e+00 8.075098e-01 8.075098e-01 4.037549e-01 -8.075098e-01 1.400000e+00 -3.000000e+00 8.031611e-01 8.031611e-01 4.015805e-01 -8.031611e-01 1.500000e+00 -3.000000e+00 7.985162e-01 7.985162e-01 3.992581e-01 -7.985162e-01 1.600000e+00 -3.000000e+00 7.935807e-01 7.935807e-01 3.967904e-01 -7.935807e-01 1.700000e+00 -3.000000e+00 7.883604e-01 7.883604e-01 3.941802e-01 -7.883604e-01 1.800000e+00 -3.000000e+00 7.828611e-01 7.828611e-01 3.914306e-01 -7.828611e-01 1.900000e+00 -3.000000e+00 7.770893e-01 7.770893e-01 3.885446e-01 -7.770893e-01 2.000000e+00 -3.000000e+00 7.710516e-01 7.710516e-01 3.855258e-01 -7.710516e-01 2.100000e+00 -3.000000e+00 7.647548e-01 7.647548e-01 3.823774e-01 -7.647548e-01 2.200000e+00 -3.000000e+00 7.582061e-01 7.582061e-01 3.791031e-01 -7.582061e-01 2.300000e+00 -3.000000e+00 7.514129e-01 7.514129e-01 3.757065e-01 -7.514129e-01 2.400000e+00 -3.000000e+00 7.443827e-01 7.443827e-01 3.721913e-01 -7.443827e-01 2.500000e+00 -3.000000e+00 7.371234e-01 7.371234e-01 3.685617e-01 -7.371234e-01 2.600000e+00 -3.000000e+00 7.296429e-01 7.296429e-01 3.648215e-01 -7.296429e-01 2.700000e+00 -3.000000e+00 7.219496e-01 7.219496e-01 3.609748e-01 -7.219496e-01 2.800000e+00 -3.000000e+00 7.140516e-01 7.140516e-01 3.570258e-01 -7.140516e-01 2.900000e+00 -3.000000e+00 7.059577e-01 7.059577e-01 3.529788e-01 -7.059577e-01 3.000000e+00 -3.000000e+00 6.976763e-01 6.976763e-01 3.488382e-01 -6.976763e-01 3.100000e+00 -3.000000e+00 6.892164e-01 6.892164e-01 3.446082e-01 -6.892164e-01 3.200000e+00 -3.000000e+00 6.805868e-01 6.805868e-01 3.402934e-01 -6.805868e-01 3.300000e+00 -3.000000e+00 6.717964e-01 6.717964e-01 3.358982e-01 -6.717964e-01 3.400000e+00 -3.000000e+00 6.628543e-01 6.628543e-01 3.314272e-01 -6.628543e-01 3.500000e+00 -3.000000e+00 6.537698e-01 6.537698e-01 3.268849e-01 -6.537698e-01 3.600000e+00 -3.000000e+00 6.445519e-01 6.445519e-01 3.222759e-01 -6.445519e-01 3.700000e+00 -3.000000e+00 6.352097e-01 6.352097e-01 3.176049e-01 -6.352097e-01 3.800000e+00 -3.000000e+00 6.257527e-01 6.257527e-01 3.128763e-01 -6.257527e-01 3.900000e+00 -3.000000e+00 6.161900e-01 6.161900e-01 3.080950e-01 -6.161900e-01 4.000000e+00 -3.000000e+00 6.065307e-01 6.065307e-01 3.032653e-01 -6.065307e-01 4.100000e+00 -3.000000e+00 5.967840e-01 5.967840e-01 2.983920e-01 -5.967840e-01 4.200000e+00 -3.000000e+00 5.869592e-01 5.869592e-01 2.934796e-01 -5.869592e-01 4.300000e+00 -3.000000e+00 5.770652e-01 5.770652e-01 2.885326e-01 -5.770652e-01 4.400000e+00 -3.000000e+00 5.671111e-01 5.671111e-01 2.835556e-01 -5.671111e-01 4.500000e+00 -3.000000e+00 5.571059e-01 5.571059e-01 2.785529e-01 -5.571059e-01 4.600000e+00 -3.000000e+00 5.470583e-01 5.470583e-01 2.735291e-01 -5.470583e-01 4.700000e+00 -3.000000e+00 5.369771e-01 5.369771e-01 2.684885e-01 -5.369771e-01 4.800000e+00 -3.000000e+00 5.268708e-01 5.268708e-01 2.634354e-01 -5.268708e-01 4.900000e+00 -3.000000e+00 5.167480e-01 5.167480e-01 2.583740e-01 -5.167480e-01 -5.000000e+00 -2.900000e+00 5.126305e-01 5.126305e-01 2.563152e-01 -5.126305e-01 -4.900000e+00 -2.900000e+00 5.228817e-01 5.228817e-01 2.614408e-01 -5.228817e-01 -4.800000e+00 -2.900000e+00 5.331246e-01 5.331246e-01 2.665623e-01 -5.331246e-01 -4.700000e+00 -2.900000e+00 5.433509e-01 5.433509e-01 2.716754e-01 -5.433509e-01 -4.600000e+00 -2.900000e+00 5.535518e-01 5.535518e-01 2.767759e-01 -5.535518e-01 -4.500000e+00 -2.900000e+00 5.637187e-01 5.637187e-01 2.818593e-01 -5.637187e-01 -4.400000e+00 -2.900000e+00 5.738426e-01 5.738426e-01 2.869213e-01 -5.738426e-01 -4.300000e+00 -2.900000e+00 5.839149e-01 5.839149e-01 2.919574e-01 -5.839149e-01 -4.200000e+00 -2.900000e+00 5.939263e-01 5.939263e-01 2.969632e-01 -5.939263e-01 -4.100000e+00 -2.900000e+00 6.038678e-01 6.038678e-01 3.019339e-01 -6.038678e-01 -4.000000e+00 -2.900000e+00 6.137301e-01 6.137301e-01 3.068650e-01 -6.137301e-01 -3.900000e+00 -2.900000e+00 6.235040e-01 6.235040e-01 3.117520e-01 -6.235040e-01 -3.800000e+00 -2.900000e+00 6.331803e-01 6.331803e-01 3.165902e-01 -6.331803e-01 -3.700000e+00 -2.900000e+00 6.427496e-01 6.427496e-01 3.213748e-01 -6.427496e-01 -3.600000e+00 -2.900000e+00 6.522026e-01 6.522026e-01 3.261013e-01 -6.522026e-01 -3.500000e+00 -2.900000e+00 6.615300e-01 6.615300e-01 3.307650e-01 -6.615300e-01 -3.400000e+00 -2.900000e+00 6.707223e-01 6.707223e-01 3.353612e-01 -6.707223e-01 -3.300000e+00 -2.900000e+00 6.797705e-01 6.797705e-01 3.398853e-01 -6.797705e-01 -3.200000e+00 -2.900000e+00 6.886652e-01 6.886652e-01 3.443326e-01 -6.886652e-01 -3.100000e+00 -2.900000e+00 6.973973e-01 6.973973e-01 3.486986e-01 -6.973973e-01 -3.000000e+00 -2.900000e+00 7.059577e-01 7.059577e-01 3.529788e-01 -7.059577e-01 -2.900000e+00 -2.900000e+00 7.143373e-01 7.143373e-01 3.571686e-01 -7.143373e-01 -2.800000e+00 -2.900000e+00 7.225273e-01 7.225273e-01 3.612637e-01 -7.225273e-01 -2.700000e+00 -2.900000e+00 7.305190e-01 7.305190e-01 3.652595e-01 -7.305190e-01 -2.600000e+00 -2.900000e+00 7.383037e-01 7.383037e-01 3.691518e-01 -7.383037e-01 -2.500000e+00 -2.900000e+00 7.458729e-01 7.458729e-01 3.729365e-01 -7.458729e-01 -2.400000e+00 -2.900000e+00 7.532184e-01 7.532184e-01 3.766092e-01 -7.532184e-01 -2.300000e+00 -2.900000e+00 7.603320e-01 7.603320e-01 3.801660e-01 -7.603320e-01 -2.200000e+00 -2.900000e+00 7.672059e-01 7.672059e-01 3.836029e-01 -7.672059e-01 -2.100000e+00 -2.900000e+00 7.738324e-01 7.738324e-01 3.869162e-01 -7.738324e-01 -2.000000e+00 -2.900000e+00 7.802039e-01 7.802039e-01 3.901019e-01 -7.802039e-01 -1.900000e+00 -2.900000e+00 7.863132e-01 7.863132e-01 3.931566e-01 -7.863132e-01 -1.800000e+00 -2.900000e+00 7.921535e-01 7.921535e-01 3.960768e-01 -7.921535e-01 -1.700000e+00 -2.900000e+00 7.977180e-01 7.977180e-01 3.988590e-01 -7.977180e-01 -1.600000e+00 -2.900000e+00 8.030005e-01 8.030005e-01 4.015002e-01 -8.030005e-01 -1.500000e+00 -2.900000e+00 8.079945e-01 8.079945e-01 4.039972e-01 -8.079945e-01 -1.400000e+00 -2.900000e+00 8.126945e-01 8.126945e-01 4.063472e-01 -8.126945e-01 -1.300000e+00 -2.900000e+00 8.170949e-01 8.170949e-01 4.085475e-01 -8.170949e-01 -1.200000e+00 -2.900000e+00 8.211906e-01 8.211906e-01 4.105953e-01 -8.211906e-01 -1.100000e+00 -2.900000e+00 8.249768e-01 8.249768e-01 4.124884e-01 -8.249768e-01 -1.000000e+00 -2.900000e+00 8.284490e-01 8.284490e-01 4.142245e-01 -8.284490e-01 -9.000000e-01 -2.900000e+00 8.316031e-01 8.316031e-01 4.158015e-01 -8.316031e-01 -8.000000e-01 -2.900000e+00 8.344353e-01 8.344353e-01 4.172177e-01 -8.344353e-01 -7.000000e-01 -2.900000e+00 8.369424e-01 8.369424e-01 4.184712e-01 -8.369424e-01 -6.000000e-01 -2.900000e+00 8.391213e-01 8.391213e-01 4.195606e-01 -8.391213e-01 -5.000000e-01 -2.900000e+00 8.409694e-01 8.409694e-01 4.204847e-01 -8.409694e-01 -4.000000e-01 -2.900000e+00 8.424845e-01 8.424845e-01 4.212422e-01 -8.424845e-01 -3.000000e-01 -2.900000e+00 8.436648e-01 8.436648e-01 4.218324e-01 -8.436648e-01 -2.000000e-01 -2.900000e+00 8.445089e-01 8.445089e-01 4.222544e-01 -8.445089e-01 -1.000000e-01 -2.900000e+00 8.450157e-01 8.450157e-01 4.225079e-01 -8.450157e-01 0.000000e+00 -2.900000e+00 8.451847e-01 8.451847e-01 4.225924e-01 -8.451847e-01 1.000000e-01 -2.900000e+00 8.450157e-01 8.450157e-01 4.225079e-01 -8.450157e-01 2.000000e-01 -2.900000e+00 8.445089e-01 8.445089e-01 4.222544e-01 -8.445089e-01 3.000000e-01 -2.900000e+00 8.436648e-01 8.436648e-01 4.218324e-01 -8.436648e-01 4.000000e-01 -2.900000e+00 8.424845e-01 8.424845e-01 4.212422e-01 -8.424845e-01 5.000000e-01 -2.900000e+00 8.409694e-01 8.409694e-01 4.204847e-01 -8.409694e-01 6.000000e-01 -2.900000e+00 8.391213e-01 8.391213e-01 4.195606e-01 -8.391213e-01 7.000000e-01 -2.900000e+00 8.369424e-01 8.369424e-01 4.184712e-01 -8.369424e-01 8.000000e-01 -2.900000e+00 8.344353e-01 8.344353e-01 4.172177e-01 -8.344353e-01 9.000000e-01 -2.900000e+00 8.316031e-01 8.316031e-01 4.158015e-01 -8.316031e-01 1.000000e+00 -2.900000e+00 8.284490e-01 8.284490e-01 4.142245e-01 -8.284490e-01 1.100000e+00 -2.900000e+00 8.249768e-01 8.249768e-01 4.124884e-01 -8.249768e-01 1.200000e+00 -2.900000e+00 8.211906e-01 8.211906e-01 4.105953e-01 -8.211906e-01 1.300000e+00 -2.900000e+00 8.170949e-01 8.170949e-01 4.085475e-01 -8.170949e-01 1.400000e+00 -2.900000e+00 8.126945e-01 8.126945e-01 4.063472e-01 -8.126945e-01 1.500000e+00 -2.900000e+00 8.079945e-01 8.079945e-01 4.039972e-01 -8.079945e-01 1.600000e+00 -2.900000e+00 8.030005e-01 8.030005e-01 4.015002e-01 -8.030005e-01 1.700000e+00 -2.900000e+00 7.977180e-01 7.977180e-01 3.988590e-01 -7.977180e-01 1.800000e+00 -2.900000e+00 7.921535e-01 7.921535e-01 3.960768e-01 -7.921535e-01 1.900000e+00 -2.900000e+00 7.863132e-01 7.863132e-01 3.931566e-01 -7.863132e-01 2.000000e+00 -2.900000e+00 7.802039e-01 7.802039e-01 3.901019e-01 -7.802039e-01 2.100000e+00 -2.900000e+00 7.738324e-01 7.738324e-01 3.869162e-01 -7.738324e-01 2.200000e+00 -2.900000e+00 7.672059e-01 7.672059e-01 3.836029e-01 -7.672059e-01 2.300000e+00 -2.900000e+00 7.603320e-01 7.603320e-01 3.801660e-01 -7.603320e-01 2.400000e+00 -2.900000e+00 7.532184e-01 7.532184e-01 3.766092e-01 -7.532184e-01 2.500000e+00 -2.900000e+00 7.458729e-01 7.458729e-01 3.729365e-01 -7.458729e-01 2.600000e+00 -2.900000e+00 7.383037e-01 7.383037e-01 3.691518e-01 -7.383037e-01 2.700000e+00 -2.900000e+00 7.305190e-01 7.305190e-01 3.652595e-01 -7.305190e-01 2.800000e+00 -2.900000e+00 7.225273e-01 7.225273e-01 3.612637e-01 -7.225273e-01 2.900000e+00 -2.900000e+00 7.143373e-01 7.143373e-01 3.571686e-01 -7.143373e-01 3.000000e+00 -2.900000e+00 7.059577e-01 7.059577e-01 3.529788e-01 -7.059577e-01 3.100000e+00 -2.900000e+00 6.973973e-01 6.973973e-01 3.486986e-01 -6.973973e-01 3.200000e+00 -2.900000e+00 6.886652e-01 6.886652e-01 3.443326e-01 -6.886652e-01 3.300000e+00 -2.900000e+00 6.797705e-01 6.797705e-01 3.398853e-01 -6.797705e-01 3.400000e+00 -2.900000e+00 6.707223e-01 6.707223e-01 3.353612e-01 -6.707223e-01 3.500000e+00 -2.900000e+00 6.615300e-01 6.615300e-01 3.307650e-01 -6.615300e-01 3.600000e+00 -2.900000e+00 6.522026e-01 6.522026e-01 3.261013e-01 -6.522026e-01 3.700000e+00 -2.900000e+00 6.427496e-01 6.427496e-01 3.213748e-01 -6.427496e-01 3.800000e+00 -2.900000e+00 6.331803e-01 6.331803e-01 3.165902e-01 -6.331803e-01 3.900000e+00 -2.900000e+00 6.235040e-01 6.235040e-01 3.117520e-01 -6.235040e-01 4.000000e+00 -2.900000e+00 6.137301e-01 6.137301e-01 3.068650e-01 -6.137301e-01 4.100000e+00 -2.900000e+00 6.038678e-01 6.038678e-01 3.019339e-01 -6.038678e-01 4.200000e+00 -2.900000e+00 5.939263e-01 5.939263e-01 2.969632e-01 -5.939263e-01 4.300000e+00 -2.900000e+00 5.839149e-01 5.839149e-01 2.919574e-01 -5.839149e-01 4.400000e+00 -2.900000e+00 5.738426e-01 5.738426e-01 2.869213e-01 -5.738426e-01 4.500000e+00 -2.900000e+00 5.637187e-01 5.637187e-01 2.818593e-01 -5.637187e-01 4.600000e+00 -2.900000e+00 5.535518e-01 5.535518e-01 2.767759e-01 -5.535518e-01 4.700000e+00 -2.900000e+00 5.433509e-01 5.433509e-01 2.716754e-01 -5.433509e-01 4.800000e+00 -2.900000e+00 5.331246e-01 5.331246e-01 2.665623e-01 -5.331246e-01 4.900000e+00 -2.900000e+00 5.228817e-01 5.228817e-01 2.614408e-01 -5.228817e-01 -5.000000e+00 -2.800000e+00 5.185079e-01 5.185079e-01 2.592539e-01 -5.185079e-01 -4.900000e+00 -2.800000e+00 5.288767e-01 5.288767e-01 2.644383e-01 -5.288767e-01 -4.800000e+00 -2.800000e+00 5.392370e-01 5.392370e-01 2.696185e-01 -5.392370e-01 -4.700000e+00 -2.800000e+00 5.495806e-01 5.495806e-01 2.747903e-01 -5.495806e-01 -4.600000e+00 -2.800000e+00 5.598984e-01 5.598984e-01 2.799492e-01 -5.598984e-01 -4.500000e+00 -2.800000e+00 5.701818e-01 5.701818e-01 2.850909e-01 -5.701818e-01 -4.400000e+00 -2.800000e+00 5.804219e-01 5.804219e-01 2.902110e-01 -5.804219e-01 -4.300000e+00 -2.800000e+00 5.906096e-01 5.906096e-01 2.953048e-01 -5.906096e-01 -4.200000e+00 -2.800000e+00 6.007358e-01 6.007358e-01 3.003679e-01 -6.007358e-01 -4.100000e+00 -2.800000e+00 6.107913e-01 6.107913e-01 3.053956e-01 -6.107913e-01 -4.000000e+00 -2.800000e+00 6.207666e-01 6.207666e-01 3.103833e-01 -6.207666e-01 -3.900000e+00 -2.800000e+00 6.306527e-01 6.306527e-01 3.153263e-01 -6.306527e-01 -3.800000e+00 -2.800000e+00 6.404399e-01 6.404399e-01 3.202199e-01 -6.404399e-01 -3.700000e+00 -2.800000e+00 6.501189e-01 6.501189e-01 3.250594e-01 -6.501189e-01 -3.600000e+00 -2.800000e+00 6.596803e-01 6.596803e-01 3.298402e-01 -6.596803e-01 -3.500000e+00 -2.800000e+00 6.691146e-01 6.691146e-01 3.345573e-01 -6.691146e-01 -3.400000e+00 -2.800000e+00 6.784123e-01 6.784123e-01 3.392062e-01 -6.784123e-01 -3.300000e+00 -2.800000e+00 6.875643e-01 6.875643e-01 3.437821e-01 -6.875643e-01 -3.200000e+00 -2.800000e+00 6.965610e-01 6.965610e-01 3.482805e-01 -6.965610e-01 -3.100000e+00 -2.800000e+00 7.053931e-01 7.053931e-01 3.526966e-01 -7.053931e-01 -3.000000e+00 -2.800000e+00 7.140516e-01 7.140516e-01 3.570258e-01 -7.140516e-01 -2.900000e+00 -2.800000e+00 7.225273e-01 7.225273e-01 3.612637e-01 -7.225273e-01 -2.800000e+00 -2.800000e+00 7.308113e-01 7.308113e-01 3.654056e-01 -7.308113e-01 -2.700000e+00 -2.800000e+00 7.388946e-01 7.388946e-01 3.694473e-01 -7.388946e-01 -2.600000e+00 -2.800000e+00 7.467685e-01 7.467685e-01 3.733843e-01 -7.467685e-01 -2.500000e+00 -2.800000e+00 7.544246e-01 7.544246e-01 3.772123e-01 -7.544246e-01 -2.400000e+00 -2.800000e+00 7.618542e-01 7.618542e-01 3.809271e-01 -7.618542e-01 -2.300000e+00 -2.800000e+00 7.690495e-01 7.690495e-01 3.845247e-01 -7.690495e-01 -2.200000e+00 -2.800000e+00 7.760022e-01 7.760022e-01 3.880011e-01 -7.760022e-01 -2.100000e+00 -2.800000e+00 7.827045e-01 7.827045e-01 3.913523e-01 -7.827045e-01 -2.000000e+00 -2.800000e+00 7.891491e-01 7.891491e-01 3.945746e-01 -7.891491e-01 -1.900000e+00 -2.800000e+00 7.953286e-01 7.953286e-01 3.976643e-01 -7.953286e-01 -1.800000e+00 -2.800000e+00 8.012358e-01 8.012358e-01 4.006179e-01 -8.012358e-01 -1.700000e+00 -2.800000e+00 8.068641e-01 8.068641e-01 4.034321e-01 -8.068641e-01 -1.600000e+00 -2.800000e+00 8.122070e-01 8.122070e-01 4.061035e-01 -8.122070e-01 -1.500000e+00 -2.800000e+00 8.172584e-01 8.172584e-01 4.086292e-01 -8.172584e-01 -1.400000e+00 -2.800000e+00 8.220122e-01 8.220122e-01 4.110061e-01 -8.220122e-01 -1.300000e+00 -2.800000e+00 8.264631e-01 8.264631e-01 4.132316e-01 -8.264631e-01 -1.200000e+00 -2.800000e+00 8.306057e-01 8.306057e-01 4.153029e-01 -8.306057e-01 -1.100000e+00 -2.800000e+00 8.344353e-01 8.344353e-01 4.172177e-01 -8.344353e-01 -1.000000e+00 -2.800000e+00 8.379474e-01 8.379474e-01 4.189737e-01 -8.379474e-01 -9.000000e-01 -2.800000e+00 8.411376e-01 8.411376e-01 4.205688e-01 -8.411376e-01 -8.000000e-01 -2.800000e+00 8.440024e-01 8.440024e-01 4.220012e-01 -8.440024e-01 -7.000000e-01 -2.800000e+00 8.465381e-01 8.465381e-01 4.232691e-01 -8.465381e-01 -6.000000e-01 -2.800000e+00 8.487420e-01 8.487420e-01 4.243710e-01 -8.487420e-01 -5.000000e-01 -2.800000e+00 8.506113e-01 8.506113e-01 4.253057e-01 -8.506113e-01 -4.000000e-01 -2.800000e+00 8.521438e-01 8.521438e-01 4.260719e-01 -8.521438e-01 -3.000000e-01 -2.800000e+00 8.533376e-01 8.533376e-01 4.266688e-01 -8.533376e-01 -2.000000e-01 -2.800000e+00 8.541914e-01 8.541914e-01 4.270957e-01 -8.541914e-01 -1.000000e-01 -2.800000e+00 8.547041e-01 8.547041e-01 4.273520e-01 -8.547041e-01 0.000000e+00 -2.800000e+00 8.548750e-01 8.548750e-01 4.274375e-01 -8.548750e-01 1.000000e-01 -2.800000e+00 8.547041e-01 8.547041e-01 4.273520e-01 -8.547041e-01 2.000000e-01 -2.800000e+00 8.541914e-01 8.541914e-01 4.270957e-01 -8.541914e-01 3.000000e-01 -2.800000e+00 8.533376e-01 8.533376e-01 4.266688e-01 -8.533376e-01 4.000000e-01 -2.800000e+00 8.521438e-01 8.521438e-01 4.260719e-01 -8.521438e-01 5.000000e-01 -2.800000e+00 8.506113e-01 8.506113e-01 4.253057e-01 -8.506113e-01 6.000000e-01 -2.800000e+00 8.487420e-01 8.487420e-01 4.243710e-01 -8.487420e-01 7.000000e-01 -2.800000e+00 8.465381e-01 8.465381e-01 4.232691e-01 -8.465381e-01 8.000000e-01 -2.800000e+00 8.440024e-01 8.440024e-01 4.220012e-01 -8.440024e-01 9.000000e-01 -2.800000e+00 8.411376e-01 8.411376e-01 4.205688e-01 -8.411376e-01 1.000000e+00 -2.800000e+00 8.379474e-01 8.379474e-01 4.189737e-01 -8.379474e-01 1.100000e+00 -2.800000e+00 8.344353e-01 8.344353e-01 4.172177e-01 -8.344353e-01 1.200000e+00 -2.800000e+00 8.306057e-01 8.306057e-01 4.153029e-01 -8.306057e-01 1.300000e+00 -2.800000e+00 8.264631e-01 8.264631e-01 4.132316e-01 -8.264631e-01 1.400000e+00 -2.800000e+00 8.220122e-01 8.220122e-01 4.110061e-01 -8.220122e-01 1.500000e+00 -2.800000e+00 8.172584e-01 8.172584e-01 4.086292e-01 -8.172584e-01 1.600000e+00 -2.800000e+00 8.122070e-01 8.122070e-01 4.061035e-01 -8.122070e-01 1.700000e+00 -2.800000e+00 8.068641e-01 8.068641e-01 4.034321e-01 -8.068641e-01 1.800000e+00 -2.800000e+00 8.012358e-01 8.012358e-01 4.006179e-01 -8.012358e-01 1.900000e+00 -2.800000e+00 7.953286e-01 7.953286e-01 3.976643e-01 -7.953286e-01 2.000000e+00 -2.800000e+00 7.891491e-01 7.891491e-01 3.945746e-01 -7.891491e-01 2.100000e+00 -2.800000e+00 7.827045e-01 7.827045e-01 3.913523e-01 -7.827045e-01 2.200000e+00 -2.800000e+00 7.760022e-01 7.760022e-01 3.880011e-01 -7.760022e-01 2.300000e+00 -2.800000e+00 7.690495e-01 7.690495e-01 3.845247e-01 -7.690495e-01 2.400000e+00 -2.800000e+00 7.618542e-01 7.618542e-01 3.809271e-01 -7.618542e-01 2.500000e+00 -2.800000e+00 7.544246e-01 7.544246e-01 3.772123e-01 -7.544246e-01 2.600000e+00 -2.800000e+00 7.467685e-01 7.467685e-01 3.733843e-01 -7.467685e-01 2.700000e+00 -2.800000e+00 7.388946e-01 7.388946e-01 3.694473e-01 -7.388946e-01 2.800000e+00 -2.800000e+00 7.308113e-01 7.308113e-01 3.654056e-01 -7.308113e-01 2.900000e+00 -2.800000e+00 7.225273e-01 7.225273e-01 3.612637e-01 -7.225273e-01 3.000000e+00 -2.800000e+00 7.140516e-01 7.140516e-01 3.570258e-01 -7.140516e-01 3.100000e+00 -2.800000e+00 7.053931e-01 7.053931e-01 3.526966e-01 -7.053931e-01 3.200000e+00 -2.800000e+00 6.965610e-01 6.965610e-01 3.482805e-01 -6.965610e-01 3.300000e+00 -2.800000e+00 6.875643e-01 6.875643e-01 3.437821e-01 -6.875643e-01 3.400000e+00 -2.800000e+00 6.784123e-01 6.784123e-01 3.392062e-01 -6.784123e-01 3.500000e+00 -2.800000e+00 6.691146e-01 6.691146e-01 3.345573e-01 -6.691146e-01 3.600000e+00 -2.800000e+00 6.596803e-01 6.596803e-01 3.298402e-01 -6.596803e-01 3.700000e+00 -2.800000e+00 6.501189e-01 6.501189e-01 3.250594e-01 -6.501189e-01 3.800000e+00 -2.800000e+00 6.404399e-01 6.404399e-01 3.202199e-01 -6.404399e-01 3.900000e+00 -2.800000e+00 6.306527e-01 6.306527e-01 3.153263e-01 -6.306527e-01 4.000000e+00 -2.800000e+00 6.207666e-01 6.207666e-01 3.103833e-01 -6.207666e-01 4.100000e+00 -2.800000e+00 6.107913e-01 6.107913e-01 3.053956e-01 -6.107913e-01 4.200000e+00 -2.800000e+00 6.007358e-01 6.007358e-01 3.003679e-01 -6.007358e-01 4.300000e+00 -2.800000e+00 5.906096e-01 5.906096e-01 2.953048e-01 -5.906096e-01 4.400000e+00 -2.800000e+00 5.804219e-01 5.804219e-01 2.902110e-01 -5.804219e-01 4.500000e+00 -2.800000e+00 5.701818e-01 5.701818e-01 2.850909e-01 -5.701818e-01 4.600000e+00 -2.800000e+00 5.598984e-01 5.598984e-01 2.799492e-01 -5.598984e-01 4.700000e+00 -2.800000e+00 5.495806e-01 5.495806e-01 2.747903e-01 -5.495806e-01 4.800000e+00 -2.800000e+00 5.392370e-01 5.392370e-01 2.696185e-01 -5.392370e-01 4.900000e+00 -2.800000e+00 5.288767e-01 5.288767e-01 2.644383e-01 -5.288767e-01 -5.000000e+00 -2.700000e+00 5.242430e-01 5.242430e-01 2.621215e-01 -5.242430e-01 -4.900000e+00 -2.700000e+00 5.347264e-01 5.347264e-01 2.673632e-01 -5.347264e-01 -4.800000e+00 -2.700000e+00 5.452014e-01 5.452014e-01 2.726007e-01 -5.452014e-01 -4.700000e+00 -2.700000e+00 5.556593e-01 5.556593e-01 2.778296e-01 -5.556593e-01 -4.600000e+00 -2.700000e+00 5.660913e-01 5.660913e-01 2.830456e-01 -5.660913e-01 -4.500000e+00 -2.700000e+00 5.764884e-01 5.764884e-01 2.882442e-01 -5.764884e-01 -4.400000e+00 -2.700000e+00 5.868418e-01 5.868418e-01 2.934209e-01 -5.868418e-01 -4.300000e+00 -2.700000e+00 5.971422e-01 5.971422e-01 2.985711e-01 -5.971422e-01 -4.200000e+00 -2.700000e+00 6.073804e-01 6.073804e-01 3.036902e-01 -6.073804e-01 -4.100000e+00 -2.700000e+00 6.175471e-01 6.175471e-01 3.087735e-01 -6.175471e-01 -4.000000e+00 -2.700000e+00 6.276328e-01 6.276328e-01 3.138164e-01 -6.276328e-01 -3.900000e+00 -2.700000e+00 6.376281e-01 6.376281e-01 3.188141e-01 -6.376281e-01 -3.800000e+00 -2.700000e+00 6.475236e-01 6.475236e-01 3.237618e-01 -6.475236e-01 -3.700000e+00 -2.700000e+00 6.573097e-01 6.573097e-01 3.286549e-01 -6.573097e-01 -3.600000e+00 -2.700000e+00 6.669768e-01 6.669768e-01 3.334884e-01 -6.669768e-01 -3.500000e+00 -2.700000e+00 6.765155e-01 6.765155e-01 3.382577e-01 -6.765155e-01 -3.400000e+00 -2.700000e+00 6.859161e-01 6.859161e-01 3.429580e-01 -6.859161e-01 -3.300000e+00 -2.700000e+00 6.951692e-01 6.951692e-01 3.475846e-01 -6.951692e-01 -3.200000e+00 -2.700000e+00 7.042654e-01 7.042654e-01 3.521327e-01 -7.042654e-01 -3.100000e+00 -2.700000e+00 7.131953e-01 7.131953e-01 3.565976e-01 -7.131953e-01 -3.000000e+00 -2.700000e+00 7.219496e-01 7.219496e-01 3.609748e-01 -7.219496e-01 -2.900000e+00 -2.700000e+00 7.305190e-01 7.305190e-01 3.652595e-01 -7.305190e-01 -2.800000e+00 -2.700000e+00 7.388946e-01 7.388946e-01 3.694473e-01 -7.388946e-01 -2.700000e+00 -2.700000e+00 7.470673e-01 7.470673e-01 3.735336e-01 -7.470673e-01 -2.600000e+00 -2.700000e+00 7.550283e-01 7.550283e-01 3.775142e-01 -7.550283e-01 -2.500000e+00 -2.700000e+00 7.627690e-01 7.627690e-01 3.813845e-01 -7.627690e-01 -2.400000e+00 -2.700000e+00 7.702809e-01 7.702809e-01 3.851404e-01 -7.702809e-01 -2.300000e+00 -2.700000e+00 7.775557e-01 7.775557e-01 3.887779e-01 -7.775557e-01 -2.200000e+00 -2.700000e+00 7.845853e-01 7.845853e-01 3.922926e-01 -7.845853e-01 -2.100000e+00 -2.700000e+00 7.913618e-01 7.913618e-01 3.956809e-01 -7.913618e-01 -2.000000e+00 -2.700000e+00 7.978777e-01 7.978777e-01 3.989388e-01 -7.978777e-01 -1.900000e+00 -2.700000e+00 8.041254e-01 8.041254e-01 4.020627e-01 -8.041254e-01 -1.800000e+00 -2.700000e+00 8.100981e-01 8.100981e-01 4.050490e-01 -8.100981e-01 -1.700000e+00 -2.700000e+00 8.157886e-01 8.157886e-01 4.078943e-01 -8.157886e-01 -1.600000e+00 -2.700000e+00 8.211906e-01 8.211906e-01 4.105953e-01 -8.211906e-01 -1.500000e+00 -2.700000e+00 8.262978e-01 8.262978e-01 4.131489e-01 -8.262978e-01 -1.400000e+00 -2.700000e+00 8.311043e-01 8.311043e-01 4.155521e-01 -8.311043e-01 -1.300000e+00 -2.700000e+00 8.356044e-01 8.356044e-01 4.178022e-01 -8.356044e-01 -1.200000e+00 -2.700000e+00 8.397928e-01 8.397928e-01 4.198964e-01 -8.397928e-01 -1.100000e+00 -2.700000e+00 8.436648e-01 8.436648e-01 4.218324e-01 -8.436648e-01 -1.000000e+00 -2.700000e+00 8.472157e-01 8.472157e-01 4.236078e-01 -8.472157e-01 -9.000000e-01 -2.700000e+00 8.504412e-01 8.504412e-01 4.252206e-01 -8.504412e-01 -8.000000e-01 -2.700000e+00 8.533376e-01 8.533376e-01 4.266688e-01 -8.533376e-01 -7.000000e-01 -2.700000e+00 8.559015e-01 8.559015e-01 4.279507e-01 -8.559015e-01 -6.000000e-01 -2.700000e+00 8.581297e-01 8.581297e-01 4.290649e-01 -8.581297e-01 -5.000000e-01 -2.700000e+00 8.600197e-01 8.600197e-01 4.300098e-01 -8.600197e-01 -4.000000e-01 -2.700000e+00 8.615691e-01 8.615691e-01 4.307846e-01 -8.615691e-01 -3.000000e-01 -2.700000e+00 8.627762e-01 8.627762e-01 4.313881e-01 -8.627762e-01 -2.000000e-01 -2.700000e+00 8.636394e-01 8.636394e-01 4.318197e-01 -8.636394e-01 -1.000000e-01 -2.700000e+00 8.641577e-01 8.641577e-01 4.320788e-01 -8.641577e-01 0.000000e+00 -2.700000e+00 8.643305e-01 8.643305e-01 4.321653e-01 -8.643305e-01 1.000000e-01 -2.700000e+00 8.641577e-01 8.641577e-01 4.320788e-01 -8.641577e-01 2.000000e-01 -2.700000e+00 8.636394e-01 8.636394e-01 4.318197e-01 -8.636394e-01 3.000000e-01 -2.700000e+00 8.627762e-01 8.627762e-01 4.313881e-01 -8.627762e-01 4.000000e-01 -2.700000e+00 8.615691e-01 8.615691e-01 4.307846e-01 -8.615691e-01 5.000000e-01 -2.700000e+00 8.600197e-01 8.600197e-01 4.300098e-01 -8.600197e-01 6.000000e-01 -2.700000e+00 8.581297e-01 8.581297e-01 4.290649e-01 -8.581297e-01 7.000000e-01 -2.700000e+00 8.559015e-01 8.559015e-01 4.279507e-01 -8.559015e-01 8.000000e-01 -2.700000e+00 8.533376e-01 8.533376e-01 4.266688e-01 -8.533376e-01 9.000000e-01 -2.700000e+00 8.504412e-01 8.504412e-01 4.252206e-01 -8.504412e-01 1.000000e+00 -2.700000e+00 8.472157e-01 8.472157e-01 4.236078e-01 -8.472157e-01 1.100000e+00 -2.700000e+00 8.436648e-01 8.436648e-01 4.218324e-01 -8.436648e-01 1.200000e+00 -2.700000e+00 8.397928e-01 8.397928e-01 4.198964e-01 -8.397928e-01 1.300000e+00 -2.700000e+00 8.356044e-01 8.356044e-01 4.178022e-01 -8.356044e-01 1.400000e+00 -2.700000e+00 8.311043e-01 8.311043e-01 4.155521e-01 -8.311043e-01 1.500000e+00 -2.700000e+00 8.262978e-01 8.262978e-01 4.131489e-01 -8.262978e-01 1.600000e+00 -2.700000e+00 8.211906e-01 8.211906e-01 4.105953e-01 -8.211906e-01 1.700000e+00 -2.700000e+00 8.157886e-01 8.157886e-01 4.078943e-01 -8.157886e-01 1.800000e+00 -2.700000e+00 8.100981e-01 8.100981e-01 4.050490e-01 -8.100981e-01 1.900000e+00 -2.700000e+00 8.041254e-01 8.041254e-01 4.020627e-01 -8.041254e-01 2.000000e+00 -2.700000e+00 7.978777e-01 7.978777e-01 3.989388e-01 -7.978777e-01 2.100000e+00 -2.700000e+00 7.913618e-01 7.913618e-01 3.956809e-01 -7.913618e-01 2.200000e+00 -2.700000e+00 7.845853e-01 7.845853e-01 3.922926e-01 -7.845853e-01 2.300000e+00 -2.700000e+00 7.775557e-01 7.775557e-01 3.887779e-01 -7.775557e-01 2.400000e+00 -2.700000e+00 7.702809e-01 7.702809e-01 3.851404e-01 -7.702809e-01 2.500000e+00 -2.700000e+00 7.627690e-01 7.627690e-01 3.813845e-01 -7.627690e-01 2.600000e+00 -2.700000e+00 7.550283e-01 7.550283e-01 3.775142e-01 -7.550283e-01 2.700000e+00 -2.700000e+00 7.470673e-01 7.470673e-01 3.735336e-01 -7.470673e-01 2.800000e+00 -2.700000e+00 7.388946e-01 7.388946e-01 3.694473e-01 -7.388946e-01 2.900000e+00 -2.700000e+00 7.305190e-01 7.305190e-01 3.652595e-01 -7.305190e-01 3.000000e+00 -2.700000e+00 7.219496e-01 7.219496e-01 3.609748e-01 -7.219496e-01 3.100000e+00 -2.700000e+00 7.131953e-01 7.131953e-01 3.565976e-01 -7.131953e-01 3.200000e+00 -2.700000e+00 7.042654e-01 7.042654e-01 3.521327e-01 -7.042654e-01 3.300000e+00 -2.700000e+00 6.951692e-01 6.951692e-01 3.475846e-01 -6.951692e-01 3.400000e+00 -2.700000e+00 6.859161e-01 6.859161e-01 3.429580e-01 -6.859161e-01 3.500000e+00 -2.700000e+00 6.765155e-01 6.765155e-01 3.382577e-01 -6.765155e-01 3.600000e+00 -2.700000e+00 6.669768e-01 6.669768e-01 3.334884e-01 -6.669768e-01 3.700000e+00 -2.700000e+00 6.573097e-01 6.573097e-01 3.286549e-01 -6.573097e-01 3.800000e+00 -2.700000e+00 6.475236e-01 6.475236e-01 3.237618e-01 -6.475236e-01 3.900000e+00 -2.700000e+00 6.376281e-01 6.376281e-01 3.188141e-01 -6.376281e-01 4.000000e+00 -2.700000e+00 6.276328e-01 6.276328e-01 3.138164e-01 -6.276328e-01 4.100000e+00 -2.700000e+00 6.175471e-01 6.175471e-01 3.087735e-01 -6.175471e-01 4.200000e+00 -2.700000e+00 6.073804e-01 6.073804e-01 3.036902e-01 -6.073804e-01 4.300000e+00 -2.700000e+00 5.971422e-01 5.971422e-01 2.985711e-01 -5.971422e-01 4.400000e+00 -2.700000e+00 5.868418e-01 5.868418e-01 2.934209e-01 -5.868418e-01 4.500000e+00 -2.700000e+00 5.764884e-01 5.764884e-01 2.882442e-01 -5.764884e-01 4.600000e+00 -2.700000e+00 5.660913e-01 5.660913e-01 2.830456e-01 -5.660913e-01 4.700000e+00 -2.700000e+00 5.556593e-01 5.556593e-01 2.778296e-01 -5.556593e-01 4.800000e+00 -2.700000e+00 5.452014e-01 5.452014e-01 2.726007e-01 -5.452014e-01 4.900000e+00 -2.700000e+00 5.347264e-01 5.347264e-01 2.673632e-01 -5.347264e-01 -5.000000e+00 -2.600000e+00 5.298295e-01 5.298295e-01 2.649148e-01 -5.298295e-01 -4.900000e+00 -2.600000e+00 5.404246e-01 5.404246e-01 2.702123e-01 -5.404246e-01 -4.800000e+00 -2.600000e+00 5.510113e-01 5.510113e-01 2.755056e-01 -5.510113e-01 -4.700000e+00 -2.600000e+00 5.615807e-01 5.615807e-01 2.807903e-01 -5.615807e-01 -4.600000e+00 -2.600000e+00 5.721238e-01 5.721238e-01 2.860619e-01 -5.721238e-01 -4.500000e+00 -2.600000e+00 5.826317e-01 5.826317e-01 2.913159e-01 -5.826317e-01 -4.400000e+00 -2.600000e+00 5.930954e-01 5.930954e-01 2.965477e-01 -5.930954e-01 -4.300000e+00 -2.600000e+00 6.035056e-01 6.035056e-01 3.017528e-01 -6.035056e-01 -4.200000e+00 -2.600000e+00 6.138529e-01 6.138529e-01 3.069264e-01 -6.138529e-01 -4.100000e+00 -2.600000e+00 6.241279e-01 6.241279e-01 3.120639e-01 -6.241279e-01 -4.000000e+00 -2.600000e+00 6.343211e-01 6.343211e-01 3.171605e-01 -6.343211e-01 -3.900000e+00 -2.600000e+00 6.444229e-01 6.444229e-01 3.222115e-01 -6.444229e-01 -3.800000e+00 -2.600000e+00 6.544239e-01 6.544239e-01 3.272119e-01 -6.544239e-01 -3.700000e+00 -2.600000e+00 6.643142e-01 6.643142e-01 3.321571e-01 -6.643142e-01 -3.600000e+00 -2.600000e+00 6.740844e-01 6.740844e-01 3.370422e-01 -6.740844e-01 -3.500000e+00 -2.600000e+00 6.837247e-01 6.837247e-01 3.418624e-01 -6.837247e-01 -3.400000e+00 -2.600000e+00 6.932254e-01 6.932254e-01 3.466127e-01 -6.932254e-01 -3.300000e+00 -2.600000e+00 7.025772e-01 7.025772e-01 3.512886e-01 -7.025772e-01 -3.200000e+00 -2.600000e+00 7.117704e-01 7.117704e-01 3.558852e-01 -7.117704e-01 -3.100000e+00 -2.600000e+00 7.207954e-01 7.207954e-01 3.603977e-01 -7.207954e-01 -3.000000e+00 -2.600000e+00 7.296429e-01 7.296429e-01 3.648215e-01 -7.296429e-01 -2.900000e+00 -2.600000e+00 7.383037e-01 7.383037e-01 3.691518e-01 -7.383037e-01 -2.800000e+00 -2.600000e+00 7.467685e-01 7.467685e-01 3.733843e-01 -7.467685e-01 -2.700000e+00 -2.600000e+00 7.550283e-01 7.550283e-01 3.775142e-01 -7.550283e-01 -2.600000e+00 -2.600000e+00 7.630742e-01 7.630742e-01 3.815371e-01 -7.630742e-01 -2.500000e+00 -2.600000e+00 7.708974e-01 7.708974e-01 3.854487e-01 -7.708974e-01 -2.400000e+00 -2.600000e+00 7.784893e-01 7.784893e-01 3.892446e-01 -7.784893e-01 -2.300000e+00 -2.600000e+00 7.858416e-01 7.858416e-01 3.929208e-01 -7.858416e-01 -2.200000e+00 -2.600000e+00 7.929461e-01 7.929461e-01 3.964731e-01 -7.929461e-01 -2.100000e+00 -2.600000e+00 7.997949e-01 7.997949e-01 3.998974e-01 -7.997949e-01 -2.000000e+00 -2.600000e+00 8.063802e-01 8.063802e-01 4.031901e-01 -8.063802e-01 -1.900000e+00 -2.600000e+00 8.126945e-01 8.126945e-01 4.063472e-01 -8.126945e-01 -1.800000e+00 -2.600000e+00 8.187308e-01 8.187308e-01 4.093654e-01 -8.187308e-01 -1.700000e+00 -2.600000e+00 8.244820e-01 8.244820e-01 4.122410e-01 -8.244820e-01 -1.600000e+00 -2.600000e+00 8.299416e-01 8.299416e-01 4.149708e-01 -8.299416e-01 -1.500000e+00 -2.600000e+00 8.351032e-01 8.351032e-01 4.175516e-01 -8.351032e-01 -1.400000e+00 -2.600000e+00 8.399609e-01 8.399609e-01 4.199804e-01 -8.399609e-01 -1.300000e+00 -2.600000e+00 8.445089e-01 8.445089e-01 4.222544e-01 -8.445089e-01 -1.200000e+00 -2.600000e+00 8.487420e-01 8.487420e-01 4.243710e-01 -8.487420e-01 -1.100000e+00 -2.600000e+00 8.526552e-01 8.526552e-01 4.263276e-01 -8.526552e-01 -1.000000e+00 -2.600000e+00 8.562439e-01 8.562439e-01 4.281220e-01 -8.562439e-01 -9.000000e-01 -2.600000e+00 8.595038e-01 8.595038e-01 4.297519e-01 -8.595038e-01 -8.000000e-01 -2.600000e+00 8.624311e-01 8.624311e-01 4.312156e-01 -8.624311e-01 -7.000000e-01 -2.600000e+00 8.650223e-01 8.650223e-01 4.325112e-01 -8.650223e-01 -6.000000e-01 -2.600000e+00 8.672743e-01 8.672743e-01 4.336371e-01 -8.672743e-01 -5.000000e-01 -2.600000e+00 8.691844e-01 8.691844e-01 4.345922e-01 -8.691844e-01 -4.000000e-01 -2.600000e+00 8.707503e-01 8.707503e-01 4.353752e-01 -8.707503e-01 -3.000000e-01 -2.600000e+00 8.719702e-01 8.719702e-01 4.359851e-01 -8.719702e-01 -2.000000e-01 -2.600000e+00 8.728426e-01 8.728426e-01 4.364213e-01 -8.728426e-01 -1.000000e-01 -2.600000e+00 8.733665e-01 8.733665e-01 4.366832e-01 -8.733665e-01 0.000000e+00 -2.600000e+00 8.735412e-01 8.735412e-01 4.367706e-01 -8.735412e-01 1.000000e-01 -2.600000e+00 8.733665e-01 8.733665e-01 4.366832e-01 -8.733665e-01 2.000000e-01 -2.600000e+00 8.728426e-01 8.728426e-01 4.364213e-01 -8.728426e-01 3.000000e-01 -2.600000e+00 8.719702e-01 8.719702e-01 4.359851e-01 -8.719702e-01 4.000000e-01 -2.600000e+00 8.707503e-01 8.707503e-01 4.353752e-01 -8.707503e-01 5.000000e-01 -2.600000e+00 8.691844e-01 8.691844e-01 4.345922e-01 -8.691844e-01 6.000000e-01 -2.600000e+00 8.672743e-01 8.672743e-01 4.336371e-01 -8.672743e-01 7.000000e-01 -2.600000e+00 8.650223e-01 8.650223e-01 4.325112e-01 -8.650223e-01 8.000000e-01 -2.600000e+00 8.624311e-01 8.624311e-01 4.312156e-01 -8.624311e-01 9.000000e-01 -2.600000e+00 8.595038e-01 8.595038e-01 4.297519e-01 -8.595038e-01 1.000000e+00 -2.600000e+00 8.562439e-01 8.562439e-01 4.281220e-01 -8.562439e-01 1.100000e+00 -2.600000e+00 8.526552e-01 8.526552e-01 4.263276e-01 -8.526552e-01 1.200000e+00 -2.600000e+00 8.487420e-01 8.487420e-01 4.243710e-01 -8.487420e-01 1.300000e+00 -2.600000e+00 8.445089e-01 8.445089e-01 4.222544e-01 -8.445089e-01 1.400000e+00 -2.600000e+00 8.399609e-01 8.399609e-01 4.199804e-01 -8.399609e-01 1.500000e+00 -2.600000e+00 8.351032e-01 8.351032e-01 4.175516e-01 -8.351032e-01 1.600000e+00 -2.600000e+00 8.299416e-01 8.299416e-01 4.149708e-01 -8.299416e-01 1.700000e+00 -2.600000e+00 8.244820e-01 8.244820e-01 4.122410e-01 -8.244820e-01 1.800000e+00 -2.600000e+00 8.187308e-01 8.187308e-01 4.093654e-01 -8.187308e-01 1.900000e+00 -2.600000e+00 8.126945e-01 8.126945e-01 4.063472e-01 -8.126945e-01 2.000000e+00 -2.600000e+00 8.063802e-01 8.063802e-01 4.031901e-01 -8.063802e-01 2.100000e+00 -2.600000e+00 7.997949e-01 7.997949e-01 3.998974e-01 -7.997949e-01 2.200000e+00 -2.600000e+00 7.929461e-01 7.929461e-01 3.964731e-01 -7.929461e-01 2.300000e+00 -2.600000e+00 7.858416e-01 7.858416e-01 3.929208e-01 -7.858416e-01 2.400000e+00 -2.600000e+00 7.784893e-01 7.784893e-01 3.892446e-01 -7.784893e-01 2.500000e+00 -2.600000e+00 7.708974e-01 7.708974e-01 3.854487e-01 -7.708974e-01 2.600000e+00 -2.600000e+00 7.630742e-01 7.630742e-01 3.815371e-01 -7.630742e-01 2.700000e+00 -2.600000e+00 7.550283e-01 7.550283e-01 3.775142e-01 -7.550283e-01 2.800000e+00 -2.600000e+00 7.467685e-01 7.467685e-01 3.733843e-01 -7.467685e-01 2.900000e+00 -2.600000e+00 7.383037e-01 7.383037e-01 3.691518e-01 -7.383037e-01 3.000000e+00 -2.600000e+00 7.296429e-01 7.296429e-01 3.648215e-01 -7.296429e-01 3.100000e+00 -2.600000e+00 7.207954e-01 7.207954e-01 3.603977e-01 -7.207954e-01 3.200000e+00 -2.600000e+00 7.117704e-01 7.117704e-01 3.558852e-01 -7.117704e-01 3.300000e+00 -2.600000e+00 7.025772e-01 7.025772e-01 3.512886e-01 -7.025772e-01 3.400000e+00 -2.600000e+00 6.932254e-01 6.932254e-01 3.466127e-01 -6.932254e-01 3.500000e+00 -2.600000e+00 6.837247e-01 6.837247e-01 3.418624e-01 -6.837247e-01 3.600000e+00 -2.600000e+00 6.740844e-01 6.740844e-01 3.370422e-01 -6.740844e-01 3.700000e+00 -2.600000e+00 6.643142e-01 6.643142e-01 3.321571e-01 -6.643142e-01 3.800000e+00 -2.600000e+00 6.544239e-01 6.544239e-01 3.272119e-01 -6.544239e-01 3.900000e+00 -2.600000e+00 6.444229e-01 6.444229e-01 3.222115e-01 -6.444229e-01 4.000000e+00 -2.600000e+00 6.343211e-01 6.343211e-01 3.171605e-01 -6.343211e-01 4.100000e+00 -2.600000e+00 6.241279e-01 6.241279e-01 3.120639e-01 -6.241279e-01 4.200000e+00 -2.600000e+00 6.138529e-01 6.138529e-01 3.069264e-01 -6.138529e-01 4.300000e+00 -2.600000e+00 6.035056e-01 6.035056e-01 3.017528e-01 -6.035056e-01 4.400000e+00 -2.600000e+00 5.930954e-01 5.930954e-01 2.965477e-01 -5.930954e-01 4.500000e+00 -2.600000e+00 5.826317e-01 5.826317e-01 2.913159e-01 -5.826317e-01 4.600000e+00 -2.600000e+00 5.721238e-01 5.721238e-01 2.860619e-01 -5.721238e-01 4.700000e+00 -2.600000e+00 5.615807e-01 5.615807e-01 2.807903e-01 -5.615807e-01 4.800000e+00 -2.600000e+00 5.510113e-01 5.510113e-01 2.755056e-01 -5.510113e-01 4.900000e+00 -2.600000e+00 5.404246e-01 5.404246e-01 2.702123e-01 -5.404246e-01 -5.000000e+00 -2.500000e+00 5.352615e-01 5.352615e-01 2.676307e-01 -5.352615e-01 -4.900000e+00 -2.500000e+00 5.459652e-01 5.459652e-01 2.729826e-01 -5.459652e-01 -4.800000e+00 -2.500000e+00 5.566604e-01 5.566604e-01 2.783302e-01 -5.566604e-01 -4.700000e+00 -2.500000e+00 5.673380e-01 5.673380e-01 2.836690e-01 -5.673380e-01 -4.600000e+00 -2.500000e+00 5.779893e-01 5.779893e-01 2.889946e-01 -5.779893e-01 -4.500000e+00 -2.500000e+00 5.886050e-01 5.886050e-01 2.943025e-01 -5.886050e-01 -4.400000e+00 -2.500000e+00 5.991759e-01 5.991759e-01 2.995880e-01 -5.991759e-01 -4.300000e+00 -2.500000e+00 6.096928e-01 6.096928e-01 3.048464e-01 -6.096928e-01 -4.200000e+00 -2.500000e+00 6.201462e-01 6.201462e-01 3.100731e-01 -6.201462e-01 -4.100000e+00 -2.500000e+00 6.305265e-01 6.305265e-01 3.152633e-01 -6.305265e-01 -4.000000e+00 -2.500000e+00 6.408243e-01 6.408243e-01 3.204121e-01 -6.408243e-01 -3.900000e+00 -2.500000e+00 6.510297e-01 6.510297e-01 3.255149e-01 -6.510297e-01 -3.800000e+00 -2.500000e+00 6.611332e-01 6.611332e-01 3.305666e-01 -6.611332e-01 -3.700000e+00 -2.500000e+00 6.711249e-01 6.711249e-01 3.355624e-01 -6.711249e-01 -3.600000e+00 -2.500000e+00 6.809952e-01 6.809952e-01 3.404976e-01 -6.809952e-01 -3.500000e+00 -2.500000e+00 6.907343e-01 6.907343e-01 3.453672e-01 -6.907343e-01 -3.400000e+00 -2.500000e+00 7.003325e-01 7.003325e-01 3.501663e-01 -7.003325e-01 -3.300000e+00 -2.500000e+00 7.097802e-01 7.097802e-01 3.548901e-01 -7.097802e-01 -3.200000e+00 -2.500000e+00 7.190675e-01 7.190675e-01 3.595338e-01 -7.190675e-01 -3.100000e+00 -2.500000e+00 7.281851e-01 7.281851e-01 3.640926e-01 -7.281851e-01 -3.000000e+00 -2.500000e+00 7.371234e-01 7.371234e-01 3.685617e-01 -7.371234e-01 -2.900000e+00 -2.500000e+00 7.458729e-01 7.458729e-01 3.729365e-01 -7.458729e-01 -2.800000e+00 -2.500000e+00 7.544246e-01 7.544246e-01 3.772123e-01 -7.544246e-01 -2.700000e+00 -2.500000e+00 7.627690e-01 7.627690e-01 3.813845e-01 -7.627690e-01 -2.600000e+00 -2.500000e+00 7.708974e-01 7.708974e-01 3.854487e-01 -7.708974e-01 -2.500000e+00 -2.500000e+00 7.788008e-01 7.788008e-01 3.894004e-01 -7.788008e-01 -2.400000e+00 -2.500000e+00 7.864705e-01 7.864705e-01 3.932353e-01 -7.864705e-01 -2.300000e+00 -2.500000e+00 7.938982e-01 7.938982e-01 3.969491e-01 -7.938982e-01 -2.200000e+00 -2.500000e+00 8.010756e-01 8.010756e-01 4.005378e-01 -8.010756e-01 -2.100000e+00 -2.500000e+00 8.079945e-01 8.079945e-01 4.039973e-01 -8.079945e-01 -2.000000e+00 -2.500000e+00 8.146473e-01 8.146473e-01 4.073237e-01 -8.146473e-01 -1.900000e+00 -2.500000e+00 8.210264e-01 8.210264e-01 4.105132e-01 -8.210264e-01 -1.800000e+00 -2.500000e+00 8.271245e-01 8.271245e-01 4.135623e-01 -8.271245e-01 -1.700000e+00 -2.500000e+00 8.329347e-01 8.329347e-01 4.164674e-01 -8.329347e-01 -1.600000e+00 -2.500000e+00 8.384503e-01 8.384503e-01 4.192251e-01 -8.384503e-01 -1.500000e+00 -2.500000e+00 8.436648e-01 8.436648e-01 4.218324e-01 -8.436648e-01 -1.400000e+00 -2.500000e+00 8.485723e-01 8.485723e-01 4.242861e-01 -8.485723e-01 -1.300000e+00 -2.500000e+00 8.531670e-01 8.531670e-01 4.265835e-01 -8.531670e-01 -1.200000e+00 -2.500000e+00 8.574435e-01 8.574435e-01 4.287218e-01 -8.574435e-01 -1.100000e+00 -2.500000e+00 8.613968e-01 8.613968e-01 4.306984e-01 -8.613968e-01 -1.000000e+00 -2.500000e+00 8.650223e-01 8.650223e-01 4.325112e-01 -8.650223e-01 -9.000000e-01 -2.500000e+00 8.683156e-01 8.683156e-01 4.341578e-01 -8.683156e-01 -8.000000e-01 -2.500000e+00 8.712729e-01 8.712729e-01 4.356365e-01 -8.712729e-01 -7.000000e-01 -2.500000e+00 8.738907e-01 8.738907e-01 4.369453e-01 -8.738907e-01 -6.000000e-01 -2.500000e+00 8.761657e-01 8.761657e-01 4.380829e-01 -8.761657e-01 -5.000000e-01 -2.500000e+00 8.780954e-01 8.780954e-01 4.390477e-01 -8.780954e-01 -4.000000e-01 -2.500000e+00 8.796774e-01 8.796774e-01 4.398387e-01 -8.796774e-01 -3.000000e-01 -2.500000e+00 8.809099e-01 8.809099e-01 4.404549e-01 -8.809099e-01 -2.000000e-01 -2.500000e+00 8.817912e-01 8.817912e-01 4.408956e-01 -8.817912e-01 -1.000000e-01 -2.500000e+00 8.823204e-01 8.823204e-01 4.411602e-01 -8.823204e-01 0.000000e+00 -2.500000e+00 8.824969e-01 8.824969e-01 4.412484e-01 -8.824969e-01 1.000000e-01 -2.500000e+00 8.823204e-01 8.823204e-01 4.411602e-01 -8.823204e-01 2.000000e-01 -2.500000e+00 8.817912e-01 8.817912e-01 4.408956e-01 -8.817912e-01 3.000000e-01 -2.500000e+00 8.809099e-01 8.809099e-01 4.404549e-01 -8.809099e-01 4.000000e-01 -2.500000e+00 8.796774e-01 8.796774e-01 4.398387e-01 -8.796774e-01 5.000000e-01 -2.500000e+00 8.780954e-01 8.780954e-01 4.390477e-01 -8.780954e-01 6.000000e-01 -2.500000e+00 8.761657e-01 8.761657e-01 4.380829e-01 -8.761657e-01 7.000000e-01 -2.500000e+00 8.738907e-01 8.738907e-01 4.369453e-01 -8.738907e-01 8.000000e-01 -2.500000e+00 8.712729e-01 8.712729e-01 4.356365e-01 -8.712729e-01 9.000000e-01 -2.500000e+00 8.683156e-01 8.683156e-01 4.341578e-01 -8.683156e-01 1.000000e+00 -2.500000e+00 8.650223e-01 8.650223e-01 4.325112e-01 -8.650223e-01 1.100000e+00 -2.500000e+00 8.613968e-01 8.613968e-01 4.306984e-01 -8.613968e-01 1.200000e+00 -2.500000e+00 8.574435e-01 8.574435e-01 4.287218e-01 -8.574435e-01 1.300000e+00 -2.500000e+00 8.531670e-01 8.531670e-01 4.265835e-01 -8.531670e-01 1.400000e+00 -2.500000e+00 8.485723e-01 8.485723e-01 4.242861e-01 -8.485723e-01 1.500000e+00 -2.500000e+00 8.436648e-01 8.436648e-01 4.218324e-01 -8.436648e-01 1.600000e+00 -2.500000e+00 8.384503e-01 8.384503e-01 4.192251e-01 -8.384503e-01 1.700000e+00 -2.500000e+00 8.329347e-01 8.329347e-01 4.164674e-01 -8.329347e-01 1.800000e+00 -2.500000e+00 8.271245e-01 8.271245e-01 4.135623e-01 -8.271245e-01 1.900000e+00 -2.500000e+00 8.210264e-01 8.210264e-01 4.105132e-01 -8.210264e-01 2.000000e+00 -2.500000e+00 8.146473e-01 8.146473e-01 4.073237e-01 -8.146473e-01 2.100000e+00 -2.500000e+00 8.079945e-01 8.079945e-01 4.039973e-01 -8.079945e-01 2.200000e+00 -2.500000e+00 8.010756e-01 8.010756e-01 4.005378e-01 -8.010756e-01 2.300000e+00 -2.500000e+00 7.938982e-01 7.938982e-01 3.969491e-01 -7.938982e-01 2.400000e+00 -2.500000e+00 7.864705e-01 7.864705e-01 3.932353e-01 -7.864705e-01 2.500000e+00 -2.500000e+00 7.788008e-01 7.788008e-01 3.894004e-01 -7.788008e-01 2.600000e+00 -2.500000e+00 7.708974e-01 7.708974e-01 3.854487e-01 -7.708974e-01 2.700000e+00 -2.500000e+00 7.627690e-01 7.627690e-01 3.813845e-01 -7.627690e-01 2.800000e+00 -2.500000e+00 7.544246e-01 7.544246e-01 3.772123e-01 -7.544246e-01 2.900000e+00 -2.500000e+00 7.458729e-01 7.458729e-01 3.729365e-01 -7.458729e-01 3.000000e+00 -2.500000e+00 7.371234e-01 7.371234e-01 3.685617e-01 -7.371234e-01 3.100000e+00 -2.500000e+00 7.281851e-01 7.281851e-01 3.640926e-01 -7.281851e-01 3.200000e+00 -2.500000e+00 7.190675e-01 7.190675e-01 3.595338e-01 -7.190675e-01 3.300000e+00 -2.500000e+00 7.097802e-01 7.097802e-01 3.548901e-01 -7.097802e-01 3.400000e+00 -2.500000e+00 7.003325e-01 7.003325e-01 3.501663e-01 -7.003325e-01 3.500000e+00 -2.500000e+00 6.907343e-01 6.907343e-01 3.453672e-01 -6.907343e-01 3.600000e+00 -2.500000e+00 6.809952e-01 6.809952e-01 3.404976e-01 -6.809952e-01 3.700000e+00 -2.500000e+00 6.711249e-01 6.711249e-01 3.355624e-01 -6.711249e-01 3.800000e+00 -2.500000e+00 6.611332e-01 6.611332e-01 3.305666e-01 -6.611332e-01 3.900000e+00 -2.500000e+00 6.510297e-01 6.510297e-01 3.255149e-01 -6.510297e-01 4.000000e+00 -2.500000e+00 6.408243e-01 6.408243e-01 3.204121e-01 -6.408243e-01 4.100000e+00 -2.500000e+00 6.305265e-01 6.305265e-01 3.152633e-01 -6.305265e-01 4.200000e+00 -2.500000e+00 6.201462e-01 6.201462e-01 3.100731e-01 -6.201462e-01 4.300000e+00 -2.500000e+00 6.096928e-01 6.096928e-01 3.048464e-01 -6.096928e-01 4.400000e+00 -2.500000e+00 5.991759e-01 5.991759e-01 2.995880e-01 -5.991759e-01 4.500000e+00 -2.500000e+00 5.886050e-01 5.886050e-01 2.943025e-01 -5.886050e-01 4.600000e+00 -2.500000e+00 5.779893e-01 5.779893e-01 2.889946e-01 -5.779893e-01 4.700000e+00 -2.500000e+00 5.673380e-01 5.673380e-01 2.836690e-01 -5.673380e-01 4.800000e+00 -2.500000e+00 5.566604e-01 5.566604e-01 2.783302e-01 -5.566604e-01 4.900000e+00 -2.500000e+00 5.459652e-01 5.459652e-01 2.729826e-01 -5.459652e-01 -5.000000e+00 -2.400000e+00 5.405328e-01 5.405328e-01 2.702664e-01 -5.405328e-01 -4.900000e+00 -2.400000e+00 5.513420e-01 5.513420e-01 2.756710e-01 -5.513420e-01 -4.800000e+00 -2.400000e+00 5.621424e-01 5.621424e-01 2.810712e-01 -5.621424e-01 -4.700000e+00 -2.400000e+00 5.729253e-01 5.729253e-01 2.864627e-01 -5.729253e-01 -4.600000e+00 -2.400000e+00 5.836814e-01 5.836814e-01 2.918407e-01 -5.836814e-01 -4.500000e+00 -2.400000e+00 5.944017e-01 5.944017e-01 2.972008e-01 -5.944017e-01 -4.400000e+00 -2.400000e+00 6.050767e-01 6.050767e-01 3.025384e-01 -6.050767e-01 -4.300000e+00 -2.400000e+00 6.156972e-01 6.156972e-01 3.078486e-01 -6.156972e-01 -4.200000e+00 -2.400000e+00 6.262535e-01 6.262535e-01 3.131268e-01 -6.262535e-01 -4.100000e+00 -2.400000e+00 6.367361e-01 6.367361e-01 3.183680e-01 -6.367361e-01 -4.000000e+00 -2.400000e+00 6.471352e-01 6.471352e-01 3.235676e-01 -6.471352e-01 -3.900000e+00 -2.400000e+00 6.574411e-01 6.574411e-01 3.287206e-01 -6.574411e-01 -3.800000e+00 -2.400000e+00 6.676441e-01 6.676441e-01 3.338220e-01 -6.676441e-01 -3.700000e+00 -2.400000e+00 6.777343e-01 6.777343e-01 3.388671e-01 -6.777343e-01 -3.600000e+00 -2.400000e+00 6.877018e-01 6.877018e-01 3.438509e-01 -6.877018e-01 -3.500000e+00 -2.400000e+00 6.975368e-01 6.975368e-01 3.487684e-01 -6.975368e-01 -3.400000e+00 -2.400000e+00 7.072295e-01 7.072295e-01 3.536147e-01 -7.072295e-01 -3.300000e+00 -2.400000e+00 7.167702e-01 7.167702e-01 3.583851e-01 -7.167702e-01 -3.200000e+00 -2.400000e+00 7.261490e-01 7.261490e-01 3.630745e-01 -7.261490e-01 -3.100000e+00 -2.400000e+00 7.353564e-01 7.353564e-01 3.676782e-01 -7.353564e-01 -3.000000e+00 -2.400000e+00 7.443827e-01 7.443827e-01 3.721913e-01 -7.443827e-01 -2.900000e+00 -2.400000e+00 7.532184e-01 7.532184e-01 3.766092e-01 -7.532184e-01 -2.800000e+00 -2.400000e+00 7.618542e-01 7.618542e-01 3.809271e-01 -7.618542e-01 -2.700000e+00 -2.400000e+00 7.702809e-01 7.702809e-01 3.851404e-01 -7.702809e-01 -2.600000e+00 -2.400000e+00 7.784893e-01 7.784893e-01 3.892446e-01 -7.784893e-01 -2.500000e+00 -2.400000e+00 7.864705e-01 7.864705e-01 3.932353e-01 -7.864705e-01 -2.400000e+00 -2.400000e+00 7.942159e-01 7.942159e-01 3.971079e-01 -7.942159e-01 -2.300000e+00 -2.400000e+00 8.017167e-01 8.017167e-01 4.008583e-01 -8.017167e-01 -2.200000e+00 -2.400000e+00 8.089647e-01 8.089647e-01 4.044823e-01 -8.089647e-01 -2.100000e+00 -2.400000e+00 8.159518e-01 8.159518e-01 4.079759e-01 -8.159518e-01 -2.000000e+00 -2.400000e+00 8.226701e-01 8.226701e-01 4.113351e-01 -8.226701e-01 -1.900000e+00 -2.400000e+00 8.291120e-01 8.291120e-01 4.145560e-01 -8.291120e-01 -1.800000e+00 -2.400000e+00 8.352702e-01 8.352702e-01 4.176351e-01 -8.352702e-01 -1.700000e+00 -2.400000e+00 8.411376e-01 8.411376e-01 4.205688e-01 -8.411376e-01 -1.600000e+00 -2.400000e+00 8.467075e-01 8.467075e-01 4.233537e-01 -8.467075e-01 -1.500000e+00 -2.400000e+00 8.519734e-01 8.519734e-01 4.259867e-01 -8.519734e-01 -1.400000e+00 -2.400000e+00 8.569292e-01 8.569292e-01 4.284646e-01 -8.569292e-01 -1.300000e+00 -2.400000e+00 8.615691e-01 8.615691e-01 4.307846e-01 -8.615691e-01 -1.200000e+00 -2.400000e+00 8.658878e-01 8.658878e-01 4.329439e-01 -8.658878e-01 -1.100000e+00 -2.400000e+00 8.698800e-01 8.698800e-01 4.349400e-01 -8.698800e-01 -1.000000e+00 -2.400000e+00 8.735412e-01 8.735412e-01 4.367706e-01 -8.735412e-01 -9.000000e-01 -2.400000e+00 8.768669e-01 8.768669e-01 4.384335e-01 -8.768669e-01 -8.000000e-01 -2.400000e+00 8.798534e-01 8.798534e-01 4.399267e-01 -8.798534e-01 -7.000000e-01 -2.400000e+00 8.824969e-01 8.824969e-01 4.412484e-01 -8.824969e-01 -6.000000e-01 -2.400000e+00 8.847944e-01 8.847944e-01 4.423972e-01 -8.847944e-01 -5.000000e-01 -2.400000e+00 8.867431e-01 8.867431e-01 4.433715e-01 -8.867431e-01 -4.000000e-01 -2.400000e+00 8.883407e-01 8.883407e-01 4.441703e-01 -8.883407e-01 -3.000000e-01 -2.400000e+00 8.895852e-01 8.895852e-01 4.447926e-01 -8.895852e-01 -2.000000e-01 -2.400000e+00 8.904752e-01 8.904752e-01 4.452376e-01 -8.904752e-01 -1.000000e-01 -2.400000e+00 8.910097e-01 8.910097e-01 4.455048e-01 -8.910097e-01 0.000000e+00 -2.400000e+00 8.911879e-01 8.911879e-01 4.455940e-01 -8.911879e-01 1.000000e-01 -2.400000e+00 8.910097e-01 8.910097e-01 4.455048e-01 -8.910097e-01 2.000000e-01 -2.400000e+00 8.904752e-01 8.904752e-01 4.452376e-01 -8.904752e-01 3.000000e-01 -2.400000e+00 8.895852e-01 8.895852e-01 4.447926e-01 -8.895852e-01 4.000000e-01 -2.400000e+00 8.883407e-01 8.883407e-01 4.441703e-01 -8.883407e-01 5.000000e-01 -2.400000e+00 8.867431e-01 8.867431e-01 4.433715e-01 -8.867431e-01 6.000000e-01 -2.400000e+00 8.847944e-01 8.847944e-01 4.423972e-01 -8.847944e-01 7.000000e-01 -2.400000e+00 8.824969e-01 8.824969e-01 4.412484e-01 -8.824969e-01 8.000000e-01 -2.400000e+00 8.798534e-01 8.798534e-01 4.399267e-01 -8.798534e-01 9.000000e-01 -2.400000e+00 8.768669e-01 8.768669e-01 4.384335e-01 -8.768669e-01 1.000000e+00 -2.400000e+00 8.735412e-01 8.735412e-01 4.367706e-01 -8.735412e-01 1.100000e+00 -2.400000e+00 8.698800e-01 8.698800e-01 4.349400e-01 -8.698800e-01 1.200000e+00 -2.400000e+00 8.658878e-01 8.658878e-01 4.329439e-01 -8.658878e-01 1.300000e+00 -2.400000e+00 8.615691e-01 8.615691e-01 4.307846e-01 -8.615691e-01 1.400000e+00 -2.400000e+00 8.569292e-01 8.569292e-01 4.284646e-01 -8.569292e-01 1.500000e+00 -2.400000e+00 8.519734e-01 8.519734e-01 4.259867e-01 -8.519734e-01 1.600000e+00 -2.400000e+00 8.467075e-01 8.467075e-01 4.233537e-01 -8.467075e-01 1.700000e+00 -2.400000e+00 8.411376e-01 8.411376e-01 4.205688e-01 -8.411376e-01 1.800000e+00 -2.400000e+00 8.352702e-01 8.352702e-01 4.176351e-01 -8.352702e-01 1.900000e+00 -2.400000e+00 8.291120e-01 8.291120e-01 4.145560e-01 -8.291120e-01 2.000000e+00 -2.400000e+00 8.226701e-01 8.226701e-01 4.113351e-01 -8.226701e-01 2.100000e+00 -2.400000e+00 8.159518e-01 8.159518e-01 4.079759e-01 -8.159518e-01 2.200000e+00 -2.400000e+00 8.089647e-01 8.089647e-01 4.044823e-01 -8.089647e-01 2.300000e+00 -2.400000e+00 8.017167e-01 8.017167e-01 4.008583e-01 -8.017167e-01 2.400000e+00 -2.400000e+00 7.942159e-01 7.942159e-01 3.971079e-01 -7.942159e-01 2.500000e+00 -2.400000e+00 7.864705e-01 7.864705e-01 3.932353e-01 -7.864705e-01 2.600000e+00 -2.400000e+00 7.784893e-01 7.784893e-01 3.892446e-01 -7.784893e-01 2.700000e+00 -2.400000e+00 7.702809e-01 7.702809e-01 3.851404e-01 -7.702809e-01 2.800000e+00 -2.400000e+00 7.618542e-01 7.618542e-01 3.809271e-01 -7.618542e-01 2.900000e+00 -2.400000e+00 7.532184e-01 7.532184e-01 3.766092e-01 -7.532184e-01 3.000000e+00 -2.400000e+00 7.443827e-01 7.443827e-01 3.721913e-01 -7.443827e-01 3.100000e+00 -2.400000e+00 7.353564e-01 7.353564e-01 3.676782e-01 -7.353564e-01 3.200000e+00 -2.400000e+00 7.261490e-01 7.261490e-01 3.630745e-01 -7.261490e-01 3.300000e+00 -2.400000e+00 7.167702e-01 7.167702e-01 3.583851e-01 -7.167702e-01 3.400000e+00 -2.400000e+00 7.072295e-01 7.072295e-01 3.536147e-01 -7.072295e-01 3.500000e+00 -2.400000e+00 6.975368e-01 6.975368e-01 3.487684e-01 -6.975368e-01 3.600000e+00 -2.400000e+00 6.877018e-01 6.877018e-01 3.438509e-01 -6.877018e-01 3.700000e+00 -2.400000e+00 6.777343e-01 6.777343e-01 3.388671e-01 -6.777343e-01 3.800000e+00 -2.400000e+00 6.676441e-01 6.676441e-01 3.338220e-01 -6.676441e-01 3.900000e+00 -2.400000e+00 6.574411e-01 6.574411e-01 3.287206e-01 -6.574411e-01 4.000000e+00 -2.400000e+00 6.471352e-01 6.471352e-01 3.235676e-01 -6.471352e-01 4.100000e+00 -2.400000e+00 6.367361e-01 6.367361e-01 3.183680e-01 -6.367361e-01 4.200000e+00 -2.400000e+00 6.262535e-01 6.262535e-01 3.131268e-01 -6.262535e-01 4.300000e+00 -2.400000e+00 6.156972e-01 6.156972e-01 3.078486e-01 -6.156972e-01 4.400000e+00 -2.400000e+00 6.050767e-01 6.050767e-01 3.025384e-01 -6.050767e-01 4.500000e+00 -2.400000e+00 5.944017e-01 5.944017e-01 2.972008e-01 -5.944017e-01 4.600000e+00 -2.400000e+00 5.836814e-01 5.836814e-01 2.918407e-01 -5.836814e-01 4.700000e+00 -2.400000e+00 5.729253e-01 5.729253e-01 2.864627e-01 -5.729253e-01 4.800000e+00 -2.400000e+00 5.621424e-01 5.621424e-01 2.810712e-01 -5.621424e-01 4.900000e+00 -2.400000e+00 5.513420e-01 5.513420e-01 2.756710e-01 -5.513420e-01 -5.000000e+00 -2.300000e+00 5.456377e-01 5.456377e-01 2.728189e-01 -5.456377e-01 -4.900000e+00 -2.300000e+00 5.565490e-01 5.565490e-01 2.782745e-01 -5.565490e-01 -4.800000e+00 -2.300000e+00 5.674515e-01 5.674515e-01 2.837257e-01 -5.674515e-01 -4.700000e+00 -2.300000e+00 5.783362e-01 5.783362e-01 2.891681e-01 -5.783362e-01 -4.600000e+00 -2.300000e+00 5.891939e-01 5.891939e-01 2.945970e-01 -5.891939e-01 -4.500000e+00 -2.300000e+00 6.000154e-01 6.000154e-01 3.000077e-01 -6.000154e-01 -4.400000e+00 -2.300000e+00 6.107913e-01 6.107913e-01 3.053956e-01 -6.107913e-01 -4.300000e+00 -2.300000e+00 6.215121e-01 6.215121e-01 3.107560e-01 -6.215121e-01 -4.200000e+00 -2.300000e+00 6.321681e-01 6.321681e-01 3.160840e-01 -6.321681e-01 -4.100000e+00 -2.300000e+00 6.427497e-01 6.427497e-01 3.213748e-01 -6.427497e-01 -4.000000e+00 -2.300000e+00 6.532469e-01 6.532469e-01 3.266235e-01 -6.532469e-01 -3.900000e+00 -2.300000e+00 6.636502e-01 6.636502e-01 3.318251e-01 -6.636502e-01 -3.800000e+00 -2.300000e+00 6.739496e-01 6.739496e-01 3.369748e-01 -6.739496e-01 -3.700000e+00 -2.300000e+00 6.841350e-01 6.841350e-01 3.420675e-01 -6.841350e-01 -3.600000e+00 -2.300000e+00 6.941967e-01 6.941967e-01 3.470984e-01 -6.941967e-01 -3.500000e+00 -2.300000e+00 7.041246e-01 7.041246e-01 3.520623e-01 -7.041246e-01 -3.400000e+00 -2.300000e+00 7.139089e-01 7.139089e-01 3.569544e-01 -7.139089e-01 -3.300000e+00 -2.300000e+00 7.235397e-01 7.235397e-01 3.617698e-01 -7.235397e-01 -3.200000e+00 -2.300000e+00 7.330070e-01 7.330070e-01 3.665035e-01 -7.330070e-01 -3.100000e+00 -2.300000e+00 7.423013e-01 7.423013e-01 3.711507e-01 -7.423013e-01 -3.000000e+00 -2.300000e+00 7.514129e-01 7.514129e-01 3.757065e-01 -7.514129e-01 -2.900000e+00 -2.300000e+00 7.603320e-01 7.603320e-01 3.801660e-01 -7.603320e-01 -2.800000e+00 -2.300000e+00 7.690495e-01 7.690495e-01 3.845247e-01 -7.690495e-01 -2.700000e+00 -2.300000e+00 7.775557e-01 7.775557e-01 3.887779e-01 -7.775557e-01 -2.600000e+00 -2.300000e+00 7.858416e-01 7.858416e-01 3.929208e-01 -7.858416e-01 -2.500000e+00 -2.300000e+00 7.938982e-01 7.938982e-01 3.969491e-01 -7.938982e-01 -2.400000e+00 -2.300000e+00 8.017167e-01 8.017167e-01 4.008583e-01 -8.017167e-01 -2.300000e+00 -2.300000e+00 8.092884e-01 8.092884e-01 4.046442e-01 -8.092884e-01 -2.200000e+00 -2.300000e+00 8.166049e-01 8.166049e-01 4.083024e-01 -8.166049e-01 -2.100000e+00 -2.300000e+00 8.236579e-01 8.236579e-01 4.118290e-01 -8.236579e-01 -2.000000e+00 -2.300000e+00 8.304397e-01 8.304397e-01 4.152198e-01 -8.304397e-01 -1.900000e+00 -2.300000e+00 8.369424e-01 8.369424e-01 4.184712e-01 -8.369424e-01 -1.800000e+00 -2.300000e+00 8.431588e-01 8.431588e-01 4.215794e-01 -8.431588e-01 -1.700000e+00 -2.300000e+00 8.490816e-01 8.490816e-01 4.245408e-01 -8.490816e-01 -1.600000e+00 -2.300000e+00 8.547041e-01 8.547041e-01 4.273520e-01 -8.547041e-01 -1.500000e+00 -2.300000e+00 8.600197e-01 8.600197e-01 4.300098e-01 -8.600197e-01 -1.400000e+00 -2.300000e+00 8.650223e-01 8.650223e-01 4.325112e-01 -8.650223e-01 -1.300000e+00 -2.300000e+00 8.697061e-01 8.697061e-01 4.348530e-01 -8.697061e-01 -1.200000e+00 -2.300000e+00 8.740655e-01 8.740655e-01 4.370327e-01 -8.740655e-01 -1.100000e+00 -2.300000e+00 8.780954e-01 8.780954e-01 4.390477e-01 -8.780954e-01 -1.000000e+00 -2.300000e+00 8.817912e-01 8.817912e-01 4.408956e-01 -8.817912e-01 -9.000000e-01 -2.300000e+00 8.851484e-01 8.851484e-01 4.425742e-01 -8.851484e-01 -8.000000e-01 -2.300000e+00 8.881630e-01 8.881630e-01 4.440815e-01 -8.881630e-01 -7.000000e-01 -2.300000e+00 8.908315e-01 8.908315e-01 4.454157e-01 -8.908315e-01 -6.000000e-01 -2.300000e+00 8.931507e-01 8.931507e-01 4.465753e-01 -8.931507e-01 -5.000000e-01 -2.300000e+00 8.951178e-01 8.951178e-01 4.475589e-01 -8.951178e-01 -4.000000e-01 -2.300000e+00 8.967304e-01 8.967304e-01 4.483652e-01 -8.967304e-01 -3.000000e-01 -2.300000e+00 8.979867e-01 8.979867e-01 4.489934e-01 -8.979867e-01 -2.000000e-01 -2.300000e+00 8.988852e-01 8.988852e-01 4.494426e-01 -8.988852e-01 -1.000000e-01 -2.300000e+00 8.994247e-01 8.994247e-01 4.497123e-01 -8.994247e-01 0.000000e+00 -2.300000e+00 8.996046e-01 8.996046e-01 4.498023e-01 -8.996046e-01 1.000000e-01 -2.300000e+00 8.994247e-01 8.994247e-01 4.497123e-01 -8.994247e-01 2.000000e-01 -2.300000e+00 8.988852e-01 8.988852e-01 4.494426e-01 -8.988852e-01 3.000000e-01 -2.300000e+00 8.979867e-01 8.979867e-01 4.489934e-01 -8.979867e-01 4.000000e-01 -2.300000e+00 8.967304e-01 8.967304e-01 4.483652e-01 -8.967304e-01 5.000000e-01 -2.300000e+00 8.951178e-01 8.951178e-01 4.475589e-01 -8.951178e-01 6.000000e-01 -2.300000e+00 8.931507e-01 8.931507e-01 4.465753e-01 -8.931507e-01 7.000000e-01 -2.300000e+00 8.908315e-01 8.908315e-01 4.454157e-01 -8.908315e-01 8.000000e-01 -2.300000e+00 8.881630e-01 8.881630e-01 4.440815e-01 -8.881630e-01 9.000000e-01 -2.300000e+00 8.851484e-01 8.851484e-01 4.425742e-01 -8.851484e-01 1.000000e+00 -2.300000e+00 8.817912e-01 8.817912e-01 4.408956e-01 -8.817912e-01 1.100000e+00 -2.300000e+00 8.780954e-01 8.780954e-01 4.390477e-01 -8.780954e-01 1.200000e+00 -2.300000e+00 8.740655e-01 8.740655e-01 4.370327e-01 -8.740655e-01 1.300000e+00 -2.300000e+00 8.697061e-01 8.697061e-01 4.348530e-01 -8.697061e-01 1.400000e+00 -2.300000e+00 8.650223e-01 8.650223e-01 4.325112e-01 -8.650223e-01 1.500000e+00 -2.300000e+00 8.600197e-01 8.600197e-01 4.300098e-01 -8.600197e-01 1.600000e+00 -2.300000e+00 8.547041e-01 8.547041e-01 4.273520e-01 -8.547041e-01 1.700000e+00 -2.300000e+00 8.490816e-01 8.490816e-01 4.245408e-01 -8.490816e-01 1.800000e+00 -2.300000e+00 8.431588e-01 8.431588e-01 4.215794e-01 -8.431588e-01 1.900000e+00 -2.300000e+00 8.369424e-01 8.369424e-01 4.184712e-01 -8.369424e-01 2.000000e+00 -2.300000e+00 8.304397e-01 8.304397e-01 4.152198e-01 -8.304397e-01 2.100000e+00 -2.300000e+00 8.236579e-01 8.236579e-01 4.118290e-01 -8.236579e-01 2.200000e+00 -2.300000e+00 8.166049e-01 8.166049e-01 4.083024e-01 -8.166049e-01 2.300000e+00 -2.300000e+00 8.092884e-01 8.092884e-01 4.046442e-01 -8.092884e-01 2.400000e+00 -2.300000e+00 8.017167e-01 8.017167e-01 4.008583e-01 -8.017167e-01 2.500000e+00 -2.300000e+00 7.938982e-01 7.938982e-01 3.969491e-01 -7.938982e-01 2.600000e+00 -2.300000e+00 7.858416e-01 7.858416e-01 3.929208e-01 -7.858416e-01 2.700000e+00 -2.300000e+00 7.775557e-01 7.775557e-01 3.887779e-01 -7.775557e-01 2.800000e+00 -2.300000e+00 7.690495e-01 7.690495e-01 3.845247e-01 -7.690495e-01 2.900000e+00 -2.300000e+00 7.603320e-01 7.603320e-01 3.801660e-01 -7.603320e-01 3.000000e+00 -2.300000e+00 7.514129e-01 7.514129e-01 3.757065e-01 -7.514129e-01 3.100000e+00 -2.300000e+00 7.423013e-01 7.423013e-01 3.711507e-01 -7.423013e-01 3.200000e+00 -2.300000e+00 7.330070e-01 7.330070e-01 3.665035e-01 -7.330070e-01 3.300000e+00 -2.300000e+00 7.235397e-01 7.235397e-01 3.617698e-01 -7.235397e-01 3.400000e+00 -2.300000e+00 7.139089e-01 7.139089e-01 3.569544e-01 -7.139089e-01 3.500000e+00 -2.300000e+00 7.041246e-01 7.041246e-01 3.520623e-01 -7.041246e-01 3.600000e+00 -2.300000e+00 6.941967e-01 6.941967e-01 3.470984e-01 -6.941967e-01 3.700000e+00 -2.300000e+00 6.841350e-01 6.841350e-01 3.420675e-01 -6.841350e-01 3.800000e+00 -2.300000e+00 6.739496e-01 6.739496e-01 3.369748e-01 -6.739496e-01 3.900000e+00 -2.300000e+00 6.636502e-01 6.636502e-01 3.318251e-01 -6.636502e-01 4.000000e+00 -2.300000e+00 6.532469e-01 6.532469e-01 3.266235e-01 -6.532469e-01 4.100000e+00 -2.300000e+00 6.427497e-01 6.427497e-01 3.213748e-01 -6.427497e-01 4.200000e+00 -2.300000e+00 6.321681e-01 6.321681e-01 3.160840e-01 -6.321681e-01 4.300000e+00 -2.300000e+00 6.215121e-01 6.215121e-01 3.107560e-01 -6.215121e-01 4.400000e+00 -2.300000e+00 6.107913e-01 6.107913e-01 3.053956e-01 -6.107913e-01 4.500000e+00 -2.300000e+00 6.000154e-01 6.000154e-01 3.000077e-01 -6.000154e-01 4.600000e+00 -2.300000e+00 5.891939e-01 5.891939e-01 2.945970e-01 -5.891939e-01 4.700000e+00 -2.300000e+00 5.783362e-01 5.783362e-01 2.891681e-01 -5.783362e-01 4.800000e+00 -2.300000e+00 5.674515e-01 5.674515e-01 2.837257e-01 -5.674515e-01 4.900000e+00 -2.300000e+00 5.565490e-01 5.565490e-01 2.782745e-01 -5.565490e-01 -5.000000e+00 -2.200000e+00 5.505707e-01 5.505707e-01 2.752853e-01 -5.505707e-01 -4.900000e+00 -2.200000e+00 5.615806e-01 5.615806e-01 2.807903e-01 -5.615806e-01 -4.800000e+00 -2.200000e+00 5.725816e-01 5.725816e-01 2.862908e-01 -5.725816e-01 -4.700000e+00 -2.200000e+00 5.835647e-01 5.835647e-01 2.917823e-01 -5.835647e-01 -4.600000e+00 -2.200000e+00 5.945206e-01 5.945206e-01 2.972603e-01 -5.945206e-01 -4.500000e+00 -2.200000e+00 6.054399e-01 6.054399e-01 3.027200e-01 -6.054399e-01 -4.400000e+00 -2.200000e+00 6.163132e-01 6.163132e-01 3.081566e-01 -6.163132e-01 -4.300000e+00 -2.200000e+00 6.271309e-01 6.271309e-01 3.135654e-01 -6.271309e-01 -4.200000e+00 -2.200000e+00 6.378832e-01 6.378832e-01 3.189416e-01 -6.378832e-01 -4.100000e+00 -2.200000e+00 6.485605e-01 6.485605e-01 3.242802e-01 -6.485605e-01 -4.000000e+00 -2.200000e+00 6.591527e-01 6.591527e-01 3.295764e-01 -6.591527e-01 -3.900000e+00 -2.200000e+00 6.696500e-01 6.696500e-01 3.348250e-01 -6.696500e-01 -3.800000e+00 -2.200000e+00 6.800425e-01 6.800425e-01 3.400213e-01 -6.800425e-01 -3.700000e+00 -2.200000e+00 6.903200e-01 6.903200e-01 3.451600e-01 -6.903200e-01 -3.600000e+00 -2.200000e+00 7.004727e-01 7.004727e-01 3.502363e-01 -7.004727e-01 -3.500000e+00 -2.200000e+00 7.104903e-01 7.104903e-01 3.552451e-01 -7.104903e-01 -3.400000e+00 -2.200000e+00 7.203630e-01 7.203630e-01 3.601815e-01 -7.203630e-01 -3.300000e+00 -2.200000e+00 7.300808e-01 7.300808e-01 3.650404e-01 -7.300808e-01 -3.200000e+00 -2.200000e+00 7.396339e-01 7.396339e-01 3.698169e-01 -7.396339e-01 -3.100000e+00 -2.200000e+00 7.490122e-01 7.490122e-01 3.745061e-01 -7.490122e-01 -3.000000e+00 -2.200000e+00 7.582061e-01 7.582061e-01 3.791031e-01 -7.582061e-01 -2.900000e+00 -2.200000e+00 7.672059e-01 7.672059e-01 3.836029e-01 -7.672059e-01 -2.800000e+00 -2.200000e+00 7.760022e-01 7.760022e-01 3.880011e-01 -7.760022e-01 -2.700000e+00 -2.200000e+00 7.845853e-01 7.845853e-01 3.922926e-01 -7.845853e-01 -2.600000e+00 -2.200000e+00 7.929461e-01 7.929461e-01 3.964731e-01 -7.929461e-01 -2.500000e+00 -2.200000e+00 8.010756e-01 8.010756e-01 4.005378e-01 -8.010756e-01 -2.400000e+00 -2.200000e+00 8.089647e-01 8.089647e-01 4.044823e-01 -8.089647e-01 -2.300000e+00 -2.200000e+00 8.166049e-01 8.166049e-01 4.083024e-01 -8.166049e-01 -2.200000e+00 -2.200000e+00 8.239874e-01 8.239874e-01 4.119937e-01 -8.239874e-01 -2.100000e+00 -2.200000e+00 8.311043e-01 8.311043e-01 4.155521e-01 -8.311043e-01 -2.000000e+00 -2.200000e+00 8.379474e-01 8.379474e-01 4.189737e-01 -8.379474e-01 -1.900000e+00 -2.200000e+00 8.445089e-01 8.445089e-01 4.222544e-01 -8.445089e-01 -1.800000e+00 -2.200000e+00 8.507814e-01 8.507814e-01 4.253907e-01 -8.507814e-01 -1.700000e+00 -2.200000e+00 8.567578e-01 8.567578e-01 4.283789e-01 -8.567578e-01 -1.600000e+00 -2.200000e+00 8.624311e-01 8.624311e-01 4.312156e-01 -8.624311e-01 -1.500000e+00 -2.200000e+00 8.677948e-01 8.677948e-01 4.338974e-01 -8.677948e-01 -1.400000e+00 -2.200000e+00 8.728426e-01 8.728426e-01 4.364213e-01 -8.728426e-01 -1.300000e+00 -2.200000e+00 8.775687e-01 8.775687e-01 4.387844e-01 -8.775687e-01 -1.200000e+00 -2.200000e+00 8.819675e-01 8.819675e-01 4.409838e-01 -8.819675e-01 -1.100000e+00 -2.200000e+00 8.860340e-01 8.860340e-01 4.430170e-01 -8.860340e-01 -1.000000e+00 -2.200000e+00 8.897631e-01 8.897631e-01 4.448816e-01 -8.897631e-01 -9.000000e-01 -2.200000e+00 8.931507e-01 8.931507e-01 4.465753e-01 -8.931507e-01 -8.000000e-01 -2.200000e+00 8.961926e-01 8.961926e-01 4.480963e-01 -8.961926e-01 -7.000000e-01 -2.200000e+00 8.988851e-01 8.988851e-01 4.494426e-01 -8.988851e-01 -6.000000e-01 -2.200000e+00 9.012253e-01 9.012253e-01 4.506126e-01 -9.012253e-01 -5.000000e-01 -2.200000e+00 9.032102e-01 9.032102e-01 4.516051e-01 -9.032102e-01 -4.000000e-01 -2.200000e+00 9.048374e-01 9.048374e-01 4.524187e-01 -9.048374e-01 -3.000000e-01 -2.200000e+00 9.061051e-01 9.061051e-01 4.530526e-01 -9.061051e-01 -2.000000e-01 -2.200000e+00 9.070116e-01 9.070116e-01 4.535058e-01 -9.070116e-01 -1.000000e-01 -2.200000e+00 9.075560e-01 9.075560e-01 4.537780e-01 -9.075560e-01 0.000000e+00 -2.200000e+00 9.077376e-01 9.077376e-01 4.538688e-01 -9.077376e-01 1.000000e-01 -2.200000e+00 9.075560e-01 9.075560e-01 4.537780e-01 -9.075560e-01 2.000000e-01 -2.200000e+00 9.070116e-01 9.070116e-01 4.535058e-01 -9.070116e-01 3.000000e-01 -2.200000e+00 9.061051e-01 9.061051e-01 4.530526e-01 -9.061051e-01 4.000000e-01 -2.200000e+00 9.048374e-01 9.048374e-01 4.524187e-01 -9.048374e-01 5.000000e-01 -2.200000e+00 9.032102e-01 9.032102e-01 4.516051e-01 -9.032102e-01 6.000000e-01 -2.200000e+00 9.012253e-01 9.012253e-01 4.506126e-01 -9.012253e-01 7.000000e-01 -2.200000e+00 8.988851e-01 8.988851e-01 4.494426e-01 -8.988851e-01 8.000000e-01 -2.200000e+00 8.961926e-01 8.961926e-01 4.480963e-01 -8.961926e-01 9.000000e-01 -2.200000e+00 8.931507e-01 8.931507e-01 4.465753e-01 -8.931507e-01 1.000000e+00 -2.200000e+00 8.897631e-01 8.897631e-01 4.448816e-01 -8.897631e-01 1.100000e+00 -2.200000e+00 8.860340e-01 8.860340e-01 4.430170e-01 -8.860340e-01 1.200000e+00 -2.200000e+00 8.819675e-01 8.819675e-01 4.409838e-01 -8.819675e-01 1.300000e+00 -2.200000e+00 8.775687e-01 8.775687e-01 4.387844e-01 -8.775687e-01 1.400000e+00 -2.200000e+00 8.728426e-01 8.728426e-01 4.364213e-01 -8.728426e-01 1.500000e+00 -2.200000e+00 8.677948e-01 8.677948e-01 4.338974e-01 -8.677948e-01 1.600000e+00 -2.200000e+00 8.624311e-01 8.624311e-01 4.312156e-01 -8.624311e-01 1.700000e+00 -2.200000e+00 8.567578e-01 8.567578e-01 4.283789e-01 -8.567578e-01 1.800000e+00 -2.200000e+00 8.507814e-01 8.507814e-01 4.253907e-01 -8.507814e-01 1.900000e+00 -2.200000e+00 8.445089e-01 8.445089e-01 4.222544e-01 -8.445089e-01 2.000000e+00 -2.200000e+00 8.379474e-01 8.379474e-01 4.189737e-01 -8.379474e-01 2.100000e+00 -2.200000e+00 8.311043e-01 8.311043e-01 4.155521e-01 -8.311043e-01 2.200000e+00 -2.200000e+00 8.239874e-01 8.239874e-01 4.119937e-01 -8.239874e-01 2.300000e+00 -2.200000e+00 8.166049e-01 8.166049e-01 4.083024e-01 -8.166049e-01 2.400000e+00 -2.200000e+00 8.089647e-01 8.089647e-01 4.044823e-01 -8.089647e-01 2.500000e+00 -2.200000e+00 8.010756e-01 8.010756e-01 4.005378e-01 -8.010756e-01 2.600000e+00 -2.200000e+00 7.929461e-01 7.929461e-01 3.964731e-01 -7.929461e-01 2.700000e+00 -2.200000e+00 7.845853e-01 7.845853e-01 3.922926e-01 -7.845853e-01 2.800000e+00 -2.200000e+00 7.760022e-01 7.760022e-01 3.880011e-01 -7.760022e-01 2.900000e+00 -2.200000e+00 7.672059e-01 7.672059e-01 3.836029e-01 -7.672059e-01 3.000000e+00 -2.200000e+00 7.582061e-01 7.582061e-01 3.791031e-01 -7.582061e-01 3.100000e+00 -2.200000e+00 7.490122e-01 7.490122e-01 3.745061e-01 -7.490122e-01 3.200000e+00 -2.200000e+00 7.396339e-01 7.396339e-01 3.698169e-01 -7.396339e-01 3.300000e+00 -2.200000e+00 7.300808e-01 7.300808e-01 3.650404e-01 -7.300808e-01 3.400000e+00 -2.200000e+00 7.203630e-01 7.203630e-01 3.601815e-01 -7.203630e-01 3.500000e+00 -2.200000e+00 7.104903e-01 7.104903e-01 3.552451e-01 -7.104903e-01 3.600000e+00 -2.200000e+00 7.004727e-01 7.004727e-01 3.502363e-01 -7.004727e-01 3.700000e+00 -2.200000e+00 6.903200e-01 6.903200e-01 3.451600e-01 -6.903200e-01 3.800000e+00 -2.200000e+00 6.800425e-01 6.800425e-01 3.400213e-01 -6.800425e-01 3.900000e+00 -2.200000e+00 6.696500e-01 6.696500e-01 3.348250e-01 -6.696500e-01 4.000000e+00 -2.200000e+00 6.591527e-01 6.591527e-01 3.295764e-01 -6.591527e-01 4.100000e+00 -2.200000e+00 6.485605e-01 6.485605e-01 3.242802e-01 -6.485605e-01 4.200000e+00 -2.200000e+00 6.378832e-01 6.378832e-01 3.189416e-01 -6.378832e-01 4.300000e+00 -2.200000e+00 6.271309e-01 6.271309e-01 3.135654e-01 -6.271309e-01 4.400000e+00 -2.200000e+00 6.163132e-01 6.163132e-01 3.081566e-01 -6.163132e-01 4.500000e+00 -2.200000e+00 6.054399e-01 6.054399e-01 3.027200e-01 -6.054399e-01 4.600000e+00 -2.200000e+00 5.945206e-01 5.945206e-01 2.972603e-01 -5.945206e-01 4.700000e+00 -2.200000e+00 5.835647e-01 5.835647e-01 2.917823e-01 -5.835647e-01 4.800000e+00 -2.200000e+00 5.725816e-01 5.725816e-01 2.862908e-01 -5.725816e-01 4.900000e+00 -2.200000e+00 5.615806e-01 5.615806e-01 2.807903e-01 -5.615806e-01 -5.000000e+00 -2.100000e+00 5.553260e-01 5.553260e-01 2.776630e-01 -5.553260e-01 -4.900000e+00 -2.100000e+00 5.664310e-01 5.664310e-01 2.832155e-01 -5.664310e-01 -4.800000e+00 -2.100000e+00 5.775270e-01 5.775270e-01 2.887635e-01 -5.775270e-01 -4.700000e+00 -2.100000e+00 5.886050e-01 5.886050e-01 2.943025e-01 -5.886050e-01 -4.600000e+00 -2.100000e+00 5.996555e-01 5.996555e-01 2.998278e-01 -5.996555e-01 -4.500000e+00 -2.100000e+00 6.106691e-01 6.106691e-01 3.053346e-01 -6.106691e-01 -4.400000e+00 -2.100000e+00 6.216363e-01 6.216363e-01 3.108182e-01 -6.216363e-01 -4.300000e+00 -2.100000e+00 6.325475e-01 6.325475e-01 3.162737e-01 -6.325475e-01 -4.200000e+00 -2.100000e+00 6.433927e-01 6.433927e-01 3.216964e-01 -6.433927e-01 -4.100000e+00 -2.100000e+00 6.541622e-01 6.541622e-01 3.270811e-01 -6.541622e-01 -4.000000e+00 -2.100000e+00 6.648459e-01 6.648459e-01 3.324229e-01 -6.648459e-01 -3.900000e+00 -2.100000e+00 6.754339e-01 6.754339e-01 3.377169e-01 -6.754339e-01 -3.800000e+00 -2.100000e+00 6.859161e-01 6.859161e-01 3.429580e-01 -6.859161e-01 -3.700000e+00 -2.100000e+00 6.962823e-01 6.962823e-01 3.481412e-01 -6.962823e-01 -3.600000e+00 -2.100000e+00 7.065227e-01 7.065227e-01 3.532614e-01 -7.065227e-01 -3.500000e+00 -2.100000e+00 7.166269e-01 7.166269e-01 3.583134e-01 -7.166269e-01 -3.400000e+00 -2.100000e+00 7.265849e-01 7.265849e-01 3.632924e-01 -7.265849e-01 -3.300000e+00 -2.100000e+00 7.363867e-01 7.363867e-01 3.681933e-01 -7.363867e-01 -3.200000e+00 -2.100000e+00 7.460222e-01 7.460222e-01 3.730111e-01 -7.460222e-01 -3.100000e+00 -2.100000e+00 7.554815e-01 7.554815e-01 3.777407e-01 -7.554815e-01 -3.000000e+00 -2.100000e+00 7.647548e-01 7.647548e-01 3.823774e-01 -7.647548e-01 -2.900000e+00 -2.100000e+00 7.738324e-01 7.738324e-01 3.869162e-01 -7.738324e-01 -2.800000e+00 -2.100000e+00 7.827045e-01 7.827045e-01 3.913523e-01 -7.827045e-01 -2.700000e+00 -2.100000e+00 7.913618e-01 7.913618e-01 3.956809e-01 -7.913618e-01 -2.600000e+00 -2.100000e+00 7.997949e-01 7.997949e-01 3.998974e-01 -7.997949e-01 -2.500000e+00 -2.100000e+00 8.079945e-01 8.079945e-01 4.039973e-01 -8.079945e-01 -2.400000e+00 -2.100000e+00 8.159518e-01 8.159518e-01 4.079759e-01 -8.159518e-01 -2.300000e+00 -2.100000e+00 8.236579e-01 8.236579e-01 4.118290e-01 -8.236579e-01 -2.200000e+00 -2.100000e+00 8.311043e-01 8.311043e-01 4.155521e-01 -8.311043e-01 -2.100000e+00 -2.100000e+00 8.382826e-01 8.382826e-01 4.191413e-01 -8.382826e-01 -2.000000e+00 -2.100000e+00 8.451848e-01 8.451848e-01 4.225924e-01 -8.451848e-01 -1.900000e+00 -2.100000e+00 8.518030e-01 8.518030e-01 4.259015e-01 -8.518030e-01 -1.800000e+00 -2.100000e+00 8.581297e-01 8.581297e-01 4.290649e-01 -8.581297e-01 -1.700000e+00 -2.100000e+00 8.641577e-01 8.641577e-01 4.320788e-01 -8.641577e-01 -1.600000e+00 -2.100000e+00 8.698800e-01 8.698800e-01 4.349400e-01 -8.698800e-01 -1.500000e+00 -2.100000e+00 8.752900e-01 8.752900e-01 4.376450e-01 -8.752900e-01 -1.400000e+00 -2.100000e+00 8.803815e-01 8.803815e-01 4.401907e-01 -8.803815e-01 -1.300000e+00 -2.100000e+00 8.851483e-01 8.851483e-01 4.425742e-01 -8.851483e-01 -1.200000e+00 -2.100000e+00 8.895852e-01 8.895852e-01 4.447926e-01 -8.895852e-01 -1.100000e+00 -2.100000e+00 8.936867e-01 8.936867e-01 4.468434e-01 -8.936867e-01 -1.000000e+00 -2.100000e+00 8.974481e-01 8.974481e-01 4.487240e-01 -8.974481e-01 -9.000000e-01 -2.100000e+00 9.008649e-01 9.008649e-01 4.504324e-01 -9.008649e-01 -8.000000e-01 -2.100000e+00 9.039330e-01 9.039330e-01 4.519665e-01 -9.039330e-01 -7.000000e-01 -2.100000e+00 9.066489e-01 9.066489e-01 4.533245e-01 -9.066489e-01 -6.000000e-01 -2.100000e+00 9.090093e-01 9.090093e-01 4.545046e-01 -9.090093e-01 -5.000000e-01 -2.100000e+00 9.110113e-01 9.110113e-01 4.555056e-01 -9.110113e-01 -4.000000e-01 -2.100000e+00 9.126526e-01 9.126526e-01 4.563263e-01 -9.126526e-01 -3.000000e-01 -2.100000e+00 9.139312e-01 9.139312e-01 4.569656e-01 -9.139312e-01 -2.000000e-01 -2.100000e+00 9.148456e-01 9.148456e-01 4.574228e-01 -9.148456e-01 -1.000000e-01 -2.100000e+00 9.153947e-01 9.153947e-01 4.576973e-01 -9.153947e-01 0.000000e+00 -2.100000e+00 9.155778e-01 9.155778e-01 4.577889e-01 -9.155778e-01 1.000000e-01 -2.100000e+00 9.153947e-01 9.153947e-01 4.576973e-01 -9.153947e-01 2.000000e-01 -2.100000e+00 9.148456e-01 9.148456e-01 4.574228e-01 -9.148456e-01 3.000000e-01 -2.100000e+00 9.139312e-01 9.139312e-01 4.569656e-01 -9.139312e-01 4.000000e-01 -2.100000e+00 9.126526e-01 9.126526e-01 4.563263e-01 -9.126526e-01 5.000000e-01 -2.100000e+00 9.110113e-01 9.110113e-01 4.555056e-01 -9.110113e-01 6.000000e-01 -2.100000e+00 9.090093e-01 9.090093e-01 4.545046e-01 -9.090093e-01 7.000000e-01 -2.100000e+00 9.066489e-01 9.066489e-01 4.533245e-01 -9.066489e-01 8.000000e-01 -2.100000e+00 9.039330e-01 9.039330e-01 4.519665e-01 -9.039330e-01 9.000000e-01 -2.100000e+00 9.008649e-01 9.008649e-01 4.504324e-01 -9.008649e-01 1.000000e+00 -2.100000e+00 8.974481e-01 8.974481e-01 4.487240e-01 -8.974481e-01 1.100000e+00 -2.100000e+00 8.936867e-01 8.936867e-01 4.468434e-01 -8.936867e-01 1.200000e+00 -2.100000e+00 8.895852e-01 8.895852e-01 4.447926e-01 -8.895852e-01 1.300000e+00 -2.100000e+00 8.851483e-01 8.851483e-01 4.425742e-01 -8.851483e-01 1.400000e+00 -2.100000e+00 8.803815e-01 8.803815e-01 4.401907e-01 -8.803815e-01 1.500000e+00 -2.100000e+00 8.752900e-01 8.752900e-01 4.376450e-01 -8.752900e-01 1.600000e+00 -2.100000e+00 8.698800e-01 8.698800e-01 4.349400e-01 -8.698800e-01 1.700000e+00 -2.100000e+00 8.641577e-01 8.641577e-01 4.320788e-01 -8.641577e-01 1.800000e+00 -2.100000e+00 8.581297e-01 8.581297e-01 4.290649e-01 -8.581297e-01 1.900000e+00 -2.100000e+00 8.518030e-01 8.518030e-01 4.259015e-01 -8.518030e-01 2.000000e+00 -2.100000e+00 8.451848e-01 8.451848e-01 4.225924e-01 -8.451848e-01 2.100000e+00 -2.100000e+00 8.382826e-01 8.382826e-01 4.191413e-01 -8.382826e-01 2.200000e+00 -2.100000e+00 8.311043e-01 8.311043e-01 4.155521e-01 -8.311043e-01 2.300000e+00 -2.100000e+00 8.236579e-01 8.236579e-01 4.118290e-01 -8.236579e-01 2.400000e+00 -2.100000e+00 8.159518e-01 8.159518e-01 4.079759e-01 -8.159518e-01 2.500000e+00 -2.100000e+00 8.079945e-01 8.079945e-01 4.039973e-01 -8.079945e-01 2.600000e+00 -2.100000e+00 7.997949e-01 7.997949e-01 3.998974e-01 -7.997949e-01 2.700000e+00 -2.100000e+00 7.913618e-01 7.913618e-01 3.956809e-01 -7.913618e-01 2.800000e+00 -2.100000e+00 7.827045e-01 7.827045e-01 3.913523e-01 -7.827045e-01 2.900000e+00 -2.100000e+00 7.738324e-01 7.738324e-01 3.869162e-01 -7.738324e-01 3.000000e+00 -2.100000e+00 7.647548e-01 7.647548e-01 3.823774e-01 -7.647548e-01 3.100000e+00 -2.100000e+00 7.554815e-01 7.554815e-01 3.777407e-01 -7.554815e-01 3.200000e+00 -2.100000e+00 7.460222e-01 7.460222e-01 3.730111e-01 -7.460222e-01 3.300000e+00 -2.100000e+00 7.363867e-01 7.363867e-01 3.681933e-01 -7.363867e-01 3.400000e+00 -2.100000e+00 7.265849e-01 7.265849e-01 3.632924e-01 -7.265849e-01 3.500000e+00 -2.100000e+00 7.166269e-01 7.166269e-01 3.583134e-01 -7.166269e-01 3.600000e+00 -2.100000e+00 7.065227e-01 7.065227e-01 3.532614e-01 -7.065227e-01 3.700000e+00 -2.100000e+00 6.962823e-01 6.962823e-01 3.481412e-01 -6.962823e-01 3.800000e+00 -2.100000e+00 6.859161e-01 6.859161e-01 3.429580e-01 -6.859161e-01 3.900000e+00 -2.100000e+00 6.754339e-01 6.754339e-01 3.377169e-01 -6.754339e-01 4.000000e+00 -2.100000e+00 6.648459e-01 6.648459e-01 3.324229e-01 -6.648459e-01 4.100000e+00 -2.100000e+00 6.541622e-01 6.541622e-01 3.270811e-01 -6.541622e-01 4.200000e+00 -2.100000e+00 6.433927e-01 6.433927e-01 3.216964e-01 -6.433927e-01 4.300000e+00 -2.100000e+00 6.325475e-01 6.325475e-01 3.162737e-01 -6.325475e-01 4.400000e+00 -2.100000e+00 6.216363e-01 6.216363e-01 3.108182e-01 -6.216363e-01 4.500000e+00 -2.100000e+00 6.106691e-01 6.106691e-01 3.053346e-01 -6.106691e-01 4.600000e+00 -2.100000e+00 5.996555e-01 5.996555e-01 2.998278e-01 -5.996555e-01 4.700000e+00 -2.100000e+00 5.886050e-01 5.886050e-01 2.943025e-01 -5.886050e-01 4.800000e+00 -2.100000e+00 5.775270e-01 5.775270e-01 2.887635e-01 -5.775270e-01 4.900000e+00 -2.100000e+00 5.664310e-01 5.664310e-01 2.832155e-01 -5.664310e-01 -5.000000e+00 -2.000000e+00 5.598984e-01 5.598984e-01 2.799492e-01 -5.598984e-01 -4.900000e+00 -2.000000e+00 5.710948e-01 5.710948e-01 2.855474e-01 -5.710948e-01 -4.800000e+00 -2.000000e+00 5.822822e-01 5.822822e-01 2.911411e-01 -5.822822e-01 -4.700000e+00 -2.000000e+00 5.934514e-01 5.934514e-01 2.967257e-01 -5.934514e-01 -4.600000e+00 -2.000000e+00 6.045929e-01 6.045929e-01 3.022965e-01 -6.045929e-01 -4.500000e+00 -2.000000e+00 6.156972e-01 6.156972e-01 3.078486e-01 -6.156972e-01 -4.400000e+00 -2.000000e+00 6.267547e-01 6.267547e-01 3.133774e-01 -6.267547e-01 -4.300000e+00 -2.000000e+00 6.377557e-01 6.377557e-01 3.188778e-01 -6.377557e-01 -4.200000e+00 -2.000000e+00 6.486902e-01 6.486902e-01 3.243451e-01 -6.486902e-01 -4.100000e+00 -2.000000e+00 6.595483e-01 6.595483e-01 3.297742e-01 -6.595483e-01 -4.000000e+00 -2.000000e+00 6.703200e-01 6.703200e-01 3.351600e-01 -6.703200e-01 -3.900000e+00 -2.000000e+00 6.809952e-01 6.809952e-01 3.404976e-01 -6.809952e-01 -3.800000e+00 -2.000000e+00 6.915637e-01 6.915637e-01 3.457819e-01 -6.915637e-01 -3.700000e+00 -2.000000e+00 7.020153e-01 7.020153e-01 3.510077e-01 -7.020153e-01 -3.600000e+00 -2.000000e+00 7.123400e-01 7.123400e-01 3.561700e-01 -7.123400e-01 -3.500000e+00 -2.000000e+00 7.225274e-01 7.225274e-01 3.612637e-01 -7.225274e-01 -3.400000e+00 -2.000000e+00 7.325673e-01 7.325673e-01 3.662837e-01 -7.325673e-01 -3.300000e+00 -2.000000e+00 7.424498e-01 7.424498e-01 3.712249e-01 -7.424498e-01 -3.200000e+00 -2.000000e+00 7.521647e-01 7.521647e-01 3.760823e-01 -7.521647e-01 -3.100000e+00 -2.000000e+00 7.617019e-01 7.617019e-01 3.808509e-01 -7.617019e-01 -3.000000e+00 -2.000000e+00 7.710516e-01 7.710516e-01 3.855258e-01 -7.710516e-01 -2.900000e+00 -2.000000e+00 7.802039e-01 7.802039e-01 3.901019e-01 -7.802039e-01 -2.800000e+00 -2.000000e+00 7.891491e-01 7.891491e-01 3.945746e-01 -7.891491e-01 -2.700000e+00 -2.000000e+00 7.978777e-01 7.978777e-01 3.989388e-01 -7.978777e-01 -2.600000e+00 -2.000000e+00 8.063802e-01 8.063802e-01 4.031901e-01 -8.063802e-01 -2.500000e+00 -2.000000e+00 8.146473e-01 8.146473e-01 4.073237e-01 -8.146473e-01 -2.400000e+00 -2.000000e+00 8.226701e-01 8.226701e-01 4.113351e-01 -8.226701e-01 -2.300000e+00 -2.000000e+00 8.304397e-01 8.304397e-01 4.152198e-01 -8.304397e-01 -2.200000e+00 -2.000000e+00 8.379474e-01 8.379474e-01 4.189737e-01 -8.379474e-01 -2.100000e+00 -2.000000e+00 8.451848e-01 8.451848e-01 4.225924e-01 -8.451848e-01 -2.000000e+00 -2.000000e+00 8.521438e-01 8.521438e-01 4.260719e-01 -8.521438e-01 -1.900000e+00 -2.000000e+00 8.588165e-01 8.588165e-01 4.294083e-01 -8.588165e-01 -1.800000e+00 -2.000000e+00 8.651953e-01 8.651953e-01 4.325977e-01 -8.651953e-01 -1.700000e+00 -2.000000e+00 8.712729e-01 8.712729e-01 4.356365e-01 -8.712729e-01 -1.600000e+00 -2.000000e+00 8.770424e-01 8.770424e-01 4.385212e-01 -8.770424e-01 -1.500000e+00 -2.000000e+00 8.824969e-01 8.824969e-01 4.412484e-01 -8.824969e-01 -1.400000e+00 -2.000000e+00 8.876302e-01 8.876302e-01 4.438151e-01 -8.876302e-01 -1.300000e+00 -2.000000e+00 8.924364e-01 8.924364e-01 4.462182e-01 -8.924364e-01 -1.200000e+00 -2.000000e+00 8.969098e-01 8.969098e-01 4.484549e-01 -8.969098e-01 -1.100000e+00 -2.000000e+00 9.010451e-01 9.010451e-01 4.505225e-01 -9.010451e-01 -1.000000e+00 -2.000000e+00 9.048374e-01 9.048374e-01 4.524187e-01 -9.048374e-01 -9.000000e-01 -2.000000e+00 9.082823e-01 9.082823e-01 4.541412e-01 -9.082823e-01 -8.000000e-01 -2.000000e+00 9.113758e-01 9.113758e-01 4.556879e-01 -9.113758e-01 -7.000000e-01 -2.000000e+00 9.141140e-01 9.141140e-01 4.570570e-01 -9.141140e-01 -6.000000e-01 -2.000000e+00 9.164938e-01 9.164938e-01 4.582469e-01 -9.164938e-01 -5.000000e-01 -2.000000e+00 9.185123e-01 9.185123e-01 4.592561e-01 -9.185123e-01 -4.000000e-01 -2.000000e+00 9.201671e-01 9.201671e-01 4.600835e-01 -9.201671e-01 -3.000000e-01 -2.000000e+00 9.214562e-01 9.214562e-01 4.607281e-01 -9.214562e-01 -2.000000e-01 -2.000000e+00 9.223781e-01 9.223781e-01 4.611891e-01 -9.223781e-01 -1.000000e-01 -2.000000e+00 9.229317e-01 9.229317e-01 4.614659e-01 -9.229317e-01 0.000000e+00 -2.000000e+00 9.231163e-01 9.231163e-01 4.615582e-01 -9.231163e-01 1.000000e-01 -2.000000e+00 9.229317e-01 9.229317e-01 4.614659e-01 -9.229317e-01 2.000000e-01 -2.000000e+00 9.223781e-01 9.223781e-01 4.611891e-01 -9.223781e-01 3.000000e-01 -2.000000e+00 9.214562e-01 9.214562e-01 4.607281e-01 -9.214562e-01 4.000000e-01 -2.000000e+00 9.201671e-01 9.201671e-01 4.600835e-01 -9.201671e-01 5.000000e-01 -2.000000e+00 9.185123e-01 9.185123e-01 4.592561e-01 -9.185123e-01 6.000000e-01 -2.000000e+00 9.164938e-01 9.164938e-01 4.582469e-01 -9.164938e-01 7.000000e-01 -2.000000e+00 9.141140e-01 9.141140e-01 4.570570e-01 -9.141140e-01 8.000000e-01 -2.000000e+00 9.113758e-01 9.113758e-01 4.556879e-01 -9.113758e-01 9.000000e-01 -2.000000e+00 9.082823e-01 9.082823e-01 4.541412e-01 -9.082823e-01 1.000000e+00 -2.000000e+00 9.048374e-01 9.048374e-01 4.524187e-01 -9.048374e-01 1.100000e+00 -2.000000e+00 9.010451e-01 9.010451e-01 4.505225e-01 -9.010451e-01 1.200000e+00 -2.000000e+00 8.969098e-01 8.969098e-01 4.484549e-01 -8.969098e-01 1.300000e+00 -2.000000e+00 8.924364e-01 8.924364e-01 4.462182e-01 -8.924364e-01 1.400000e+00 -2.000000e+00 8.876302e-01 8.876302e-01 4.438151e-01 -8.876302e-01 1.500000e+00 -2.000000e+00 8.824969e-01 8.824969e-01 4.412484e-01 -8.824969e-01 1.600000e+00 -2.000000e+00 8.770424e-01 8.770424e-01 4.385212e-01 -8.770424e-01 1.700000e+00 -2.000000e+00 8.712729e-01 8.712729e-01 4.356365e-01 -8.712729e-01 1.800000e+00 -2.000000e+00 8.651953e-01 8.651953e-01 4.325977e-01 -8.651953e-01 1.900000e+00 -2.000000e+00 8.588165e-01 8.588165e-01 4.294083e-01 -8.588165e-01 2.000000e+00 -2.000000e+00 8.521438e-01 8.521438e-01 4.260719e-01 -8.521438e-01 2.100000e+00 -2.000000e+00 8.451848e-01 8.451848e-01 4.225924e-01 -8.451848e-01 2.200000e+00 -2.000000e+00 8.379474e-01 8.379474e-01 4.189737e-01 -8.379474e-01 2.300000e+00 -2.000000e+00 8.304397e-01 8.304397e-01 4.152198e-01 -8.304397e-01 2.400000e+00 -2.000000e+00 8.226701e-01 8.226701e-01 4.113351e-01 -8.226701e-01 2.500000e+00 -2.000000e+00 8.146473e-01 8.146473e-01 4.073237e-01 -8.146473e-01 2.600000e+00 -2.000000e+00 8.063802e-01 8.063802e-01 4.031901e-01 -8.063802e-01 2.700000e+00 -2.000000e+00 7.978777e-01 7.978777e-01 3.989388e-01 -7.978777e-01 2.800000e+00 -2.000000e+00 7.891491e-01 7.891491e-01 3.945746e-01 -7.891491e-01 2.900000e+00 -2.000000e+00 7.802039e-01 7.802039e-01 3.901019e-01 -7.802039e-01 3.000000e+00 -2.000000e+00 7.710516e-01 7.710516e-01 3.855258e-01 -7.710516e-01 3.100000e+00 -2.000000e+00 7.617019e-01 7.617019e-01 3.808509e-01 -7.617019e-01 3.200000e+00 -2.000000e+00 7.521647e-01 7.521647e-01 3.760823e-01 -7.521647e-01 3.300000e+00 -2.000000e+00 7.424498e-01 7.424498e-01 3.712249e-01 -7.424498e-01 3.400000e+00 -2.000000e+00 7.325673e-01 7.325673e-01 3.662837e-01 -7.325673e-01 3.500000e+00 -2.000000e+00 7.225274e-01 7.225274e-01 3.612637e-01 -7.225274e-01 3.600000e+00 -2.000000e+00 7.123400e-01 7.123400e-01 3.561700e-01 -7.123400e-01 3.700000e+00 -2.000000e+00 7.020153e-01 7.020153e-01 3.510077e-01 -7.020153e-01 3.800000e+00 -2.000000e+00 6.915637e-01 6.915637e-01 3.457819e-01 -6.915637e-01 3.900000e+00 -2.000000e+00 6.809952e-01 6.809952e-01 3.404976e-01 -6.809952e-01 4.000000e+00 -2.000000e+00 6.703200e-01 6.703200e-01 3.351600e-01 -6.703200e-01 4.100000e+00 -2.000000e+00 6.595483e-01 6.595483e-01 3.297742e-01 -6.595483e-01 4.200000e+00 -2.000000e+00 6.486902e-01 6.486902e-01 3.243451e-01 -6.486902e-01 4.300000e+00 -2.000000e+00 6.377557e-01 6.377557e-01 3.188778e-01 -6.377557e-01 4.400000e+00 -2.000000e+00 6.267547e-01 6.267547e-01 3.133774e-01 -6.267547e-01 4.500000e+00 -2.000000e+00 6.156972e-01 6.156972e-01 3.078486e-01 -6.156972e-01 4.600000e+00 -2.000000e+00 6.045929e-01 6.045929e-01 3.022965e-01 -6.045929e-01 4.700000e+00 -2.000000e+00 5.934514e-01 5.934514e-01 2.967257e-01 -5.934514e-01 4.800000e+00 -2.000000e+00 5.822822e-01 5.822822e-01 2.911411e-01 -5.822822e-01 4.900000e+00 -2.000000e+00 5.710948e-01 5.710948e-01 2.855474e-01 -5.710948e-01 -5.000000e+00 -1.900000e+00 5.642827e-01 5.642827e-01 2.821413e-01 -5.642827e-01 -4.900000e+00 -1.900000e+00 5.755668e-01 5.755668e-01 2.877834e-01 -5.755668e-01 -4.800000e+00 -1.900000e+00 5.868418e-01 5.868418e-01 2.934209e-01 -5.868418e-01 -4.700000e+00 -1.900000e+00 5.980985e-01 5.980985e-01 2.990492e-01 -5.980985e-01 -4.600000e+00 -1.900000e+00 6.093271e-01 6.093271e-01 3.046636e-01 -6.093271e-01 -4.500000e+00 -1.900000e+00 6.205184e-01 6.205184e-01 3.102592e-01 -6.205184e-01 -4.400000e+00 -1.900000e+00 6.316625e-01 6.316625e-01 3.158313e-01 -6.316625e-01 -4.300000e+00 -1.900000e+00 6.427496e-01 6.427496e-01 3.213748e-01 -6.427496e-01 -4.200000e+00 -1.900000e+00 6.537698e-01 6.537698e-01 3.268849e-01 -6.537698e-01 -4.100000e+00 -1.900000e+00 6.647130e-01 6.647130e-01 3.323565e-01 -6.647130e-01 -4.000000e+00 -1.900000e+00 6.755690e-01 6.755690e-01 3.377845e-01 -6.755690e-01 -3.900000e+00 -1.900000e+00 6.863278e-01 6.863278e-01 3.431639e-01 -6.863278e-01 -3.800000e+00 -1.900000e+00 6.969790e-01 6.969790e-01 3.484895e-01 -6.969790e-01 -3.700000e+00 -1.900000e+00 7.075125e-01 7.075125e-01 3.537562e-01 -7.075125e-01 -3.600000e+00 -1.900000e+00 7.179180e-01 7.179180e-01 3.589590e-01 -7.179180e-01 -3.500000e+00 -1.900000e+00 7.281851e-01 7.281851e-01 3.640926e-01 -7.281851e-01 -3.400000e+00 -1.900000e+00 7.383037e-01 7.383037e-01 3.691519e-01 -7.383037e-01 -3.300000e+00 -1.900000e+00 7.482636e-01 7.482636e-01 3.741318e-01 -7.482636e-01 -3.200000e+00 -1.900000e+00 7.580545e-01 7.580545e-01 3.790272e-01 -7.580545e-01 -3.100000e+00 -1.900000e+00 7.676664e-01 7.676664e-01 3.838332e-01 -7.676664e-01 -3.000000e+00 -1.900000e+00 7.770893e-01 7.770893e-01 3.885446e-01 -7.770893e-01 -2.900000e+00 -1.900000e+00 7.863132e-01 7.863132e-01 3.931566e-01 -7.863132e-01 -2.800000e+00 -1.900000e+00 7.953286e-01 7.953286e-01 3.976643e-01 -7.953286e-01 -2.700000e+00 -1.900000e+00 8.041254e-01 8.041254e-01 4.020627e-01 -8.041254e-01 -2.600000e+00 -1.900000e+00 8.126945e-01 8.126945e-01 4.063472e-01 -8.126945e-01 -2.500000e+00 -1.900000e+00 8.210264e-01 8.210264e-01 4.105132e-01 -8.210264e-01 -2.400000e+00 -1.900000e+00 8.291120e-01 8.291120e-01 4.145560e-01 -8.291120e-01 -2.300000e+00 -1.900000e+00 8.369424e-01 8.369424e-01 4.184712e-01 -8.369424e-01 -2.200000e+00 -1.900000e+00 8.445089e-01 8.445089e-01 4.222544e-01 -8.445089e-01 -2.100000e+00 -1.900000e+00 8.518030e-01 8.518030e-01 4.259015e-01 -8.518030e-01 -2.000000e+00 -1.900000e+00 8.588165e-01 8.588165e-01 4.294083e-01 -8.588165e-01 -1.900000e+00 -1.900000e+00 8.655415e-01 8.655415e-01 4.327707e-01 -8.655415e-01 -1.800000e+00 -1.900000e+00 8.719702e-01 8.719702e-01 4.359851e-01 -8.719702e-01 -1.700000e+00 -1.900000e+00 8.780954e-01 8.780954e-01 4.390477e-01 -8.780954e-01 -1.600000e+00 -1.900000e+00 8.839100e-01 8.839100e-01 4.419550e-01 -8.839100e-01 -1.500000e+00 -1.900000e+00 8.894073e-01 8.894073e-01 4.447036e-01 -8.894073e-01 -1.400000e+00 -1.900000e+00 8.945808e-01 8.945808e-01 4.472904e-01 -8.945808e-01 -1.300000e+00 -1.900000e+00 8.994247e-01 8.994247e-01 4.497123e-01 -8.994247e-01 -1.200000e+00 -1.900000e+00 9.039330e-01 9.039330e-01 4.519665e-01 -9.039330e-01 -1.100000e+00 -1.900000e+00 9.081007e-01 9.081007e-01 4.540504e-01 -9.081007e-01 -1.000000e+00 -1.900000e+00 9.119228e-01 9.119228e-01 4.559614e-01 -9.119228e-01 -9.000000e-01 -1.900000e+00 9.153947e-01 9.153947e-01 4.576973e-01 -9.153947e-01 -8.000000e-01 -1.900000e+00 9.185123e-01 9.185123e-01 4.592561e-01 -9.185123e-01 -7.000000e-01 -1.900000e+00 9.212720e-01 9.212720e-01 4.606360e-01 -9.212720e-01 -6.000000e-01 -1.900000e+00 9.236704e-01 9.236704e-01 4.618352e-01 -9.236704e-01 -5.000000e-01 -1.900000e+00 9.257047e-01 9.257047e-01 4.628524e-01 -9.257047e-01 -4.000000e-01 -1.900000e+00 9.273725e-01 9.273725e-01 4.636862e-01 -9.273725e-01 -3.000000e-01 -1.900000e+00 9.286717e-01 9.286717e-01 4.643359e-01 -9.286717e-01 -2.000000e-01 -1.900000e+00 9.296008e-01 9.296008e-01 4.648004e-01 -9.296008e-01 -1.000000e-01 -1.900000e+00 9.301587e-01 9.301587e-01 4.650794e-01 -9.301587e-01 0.000000e+00 -1.900000e+00 9.303448e-01 9.303448e-01 4.651724e-01 -9.303448e-01 1.000000e-01 -1.900000e+00 9.301587e-01 9.301587e-01 4.650794e-01 -9.301587e-01 2.000000e-01 -1.900000e+00 9.296008e-01 9.296008e-01 4.648004e-01 -9.296008e-01 3.000000e-01 -1.900000e+00 9.286717e-01 9.286717e-01 4.643359e-01 -9.286717e-01 4.000000e-01 -1.900000e+00 9.273725e-01 9.273725e-01 4.636862e-01 -9.273725e-01 5.000000e-01 -1.900000e+00 9.257047e-01 9.257047e-01 4.628524e-01 -9.257047e-01 6.000000e-01 -1.900000e+00 9.236704e-01 9.236704e-01 4.618352e-01 -9.236704e-01 7.000000e-01 -1.900000e+00 9.212720e-01 9.212720e-01 4.606360e-01 -9.212720e-01 8.000000e-01 -1.900000e+00 9.185123e-01 9.185123e-01 4.592561e-01 -9.185123e-01 9.000000e-01 -1.900000e+00 9.153947e-01 9.153947e-01 4.576973e-01 -9.153947e-01 1.000000e+00 -1.900000e+00 9.119228e-01 9.119228e-01 4.559614e-01 -9.119228e-01 1.100000e+00 -1.900000e+00 9.081007e-01 9.081007e-01 4.540504e-01 -9.081007e-01 1.200000e+00 -1.900000e+00 9.039330e-01 9.039330e-01 4.519665e-01 -9.039330e-01 1.300000e+00 -1.900000e+00 8.994247e-01 8.994247e-01 4.497123e-01 -8.994247e-01 1.400000e+00 -1.900000e+00 8.945808e-01 8.945808e-01 4.472904e-01 -8.945808e-01 1.500000e+00 -1.900000e+00 8.894073e-01 8.894073e-01 4.447036e-01 -8.894073e-01 1.600000e+00 -1.900000e+00 8.839100e-01 8.839100e-01 4.419550e-01 -8.839100e-01 1.700000e+00 -1.900000e+00 8.780954e-01 8.780954e-01 4.390477e-01 -8.780954e-01 1.800000e+00 -1.900000e+00 8.719702e-01 8.719702e-01 4.359851e-01 -8.719702e-01 1.900000e+00 -1.900000e+00 8.655415e-01 8.655415e-01 4.327707e-01 -8.655415e-01 2.000000e+00 -1.900000e+00 8.588165e-01 8.588165e-01 4.294083e-01 -8.588165e-01 2.100000e+00 -1.900000e+00 8.518030e-01 8.518030e-01 4.259015e-01 -8.518030e-01 2.200000e+00 -1.900000e+00 8.445089e-01 8.445089e-01 4.222544e-01 -8.445089e-01 2.300000e+00 -1.900000e+00 8.369424e-01 8.369424e-01 4.184712e-01 -8.369424e-01 2.400000e+00 -1.900000e+00 8.291120e-01 8.291120e-01 4.145560e-01 -8.291120e-01 2.500000e+00 -1.900000e+00 8.210264e-01 8.210264e-01 4.105132e-01 -8.210264e-01 2.600000e+00 -1.900000e+00 8.126945e-01 8.126945e-01 4.063472e-01 -8.126945e-01 2.700000e+00 -1.900000e+00 8.041254e-01 8.041254e-01 4.020627e-01 -8.041254e-01 2.800000e+00 -1.900000e+00 7.953286e-01 7.953286e-01 3.976643e-01 -7.953286e-01 2.900000e+00 -1.900000e+00 7.863132e-01 7.863132e-01 3.931566e-01 -7.863132e-01 3.000000e+00 -1.900000e+00 7.770893e-01 7.770893e-01 3.885446e-01 -7.770893e-01 3.100000e+00 -1.900000e+00 7.676664e-01 7.676664e-01 3.838332e-01 -7.676664e-01 3.200000e+00 -1.900000e+00 7.580545e-01 7.580545e-01 3.790272e-01 -7.580545e-01 3.300000e+00 -1.900000e+00 7.482636e-01 7.482636e-01 3.741318e-01 -7.482636e-01 3.400000e+00 -1.900000e+00 7.383037e-01 7.383037e-01 3.691519e-01 -7.383037e-01 3.500000e+00 -1.900000e+00 7.281851e-01 7.281851e-01 3.640926e-01 -7.281851e-01 3.600000e+00 -1.900000e+00 7.179180e-01 7.179180e-01 3.589590e-01 -7.179180e-01 3.700000e+00 -1.900000e+00 7.075125e-01 7.075125e-01 3.537562e-01 -7.075125e-01 3.800000e+00 -1.900000e+00 6.969790e-01 6.969790e-01 3.484895e-01 -6.969790e-01 3.900000e+00 -1.900000e+00 6.863278e-01 6.863278e-01 3.431639e-01 -6.863278e-01 4.000000e+00 -1.900000e+00 6.755690e-01 6.755690e-01 3.377845e-01 -6.755690e-01 4.100000e+00 -1.900000e+00 6.647130e-01 6.647130e-01 3.323565e-01 -6.647130e-01 4.200000e+00 -1.900000e+00 6.537698e-01 6.537698e-01 3.268849e-01 -6.537698e-01 4.300000e+00 -1.900000e+00 6.427496e-01 6.427496e-01 3.213748e-01 -6.427496e-01 4.400000e+00 -1.900000e+00 6.316625e-01 6.316625e-01 3.158313e-01 -6.316625e-01 4.500000e+00 -1.900000e+00 6.205184e-01 6.205184e-01 3.102592e-01 -6.205184e-01 4.600000e+00 -1.900000e+00 6.093271e-01 6.093271e-01 3.046636e-01 -6.093271e-01 4.700000e+00 -1.900000e+00 5.980985e-01 5.980985e-01 2.990492e-01 -5.980985e-01 4.800000e+00 -1.900000e+00 5.868418e-01 5.868418e-01 2.934209e-01 -5.868418e-01 4.900000e+00 -1.900000e+00 5.755668e-01 5.755668e-01 2.877834e-01 -5.755668e-01 -5.000000e+00 -1.800000e+00 5.684738e-01 5.684738e-01 2.842369e-01 -5.684738e-01 -4.900000e+00 -1.800000e+00 5.798418e-01 5.798418e-01 2.899209e-01 -5.798418e-01 -4.800000e+00 -1.800000e+00 5.912005e-01 5.912005e-01 2.956003e-01 -5.912005e-01 -4.700000e+00 -1.800000e+00 6.025408e-01 6.025408e-01 3.012704e-01 -6.025408e-01 -4.600000e+00 -1.800000e+00 6.138529e-01 6.138529e-01 3.069265e-01 -6.138529e-01 -4.500000e+00 -1.800000e+00 6.251273e-01 6.251273e-01 3.125637e-01 -6.251273e-01 -4.400000e+00 -1.800000e+00 6.363541e-01 6.363541e-01 3.181771e-01 -6.363541e-01 -4.300000e+00 -1.800000e+00 6.475236e-01 6.475236e-01 3.237618e-01 -6.475236e-01 -4.200000e+00 -1.800000e+00 6.586257e-01 6.586257e-01 3.293128e-01 -6.586257e-01 -4.100000e+00 -1.800000e+00 6.696501e-01 6.696501e-01 3.348250e-01 -6.696501e-01 -4.000000e+00 -1.800000e+00 6.805868e-01 6.805868e-01 3.402934e-01 -6.805868e-01 -3.900000e+00 -1.800000e+00 6.914254e-01 6.914254e-01 3.457127e-01 -6.914254e-01 -3.800000e+00 -1.800000e+00 7.021558e-01 7.021558e-01 3.510779e-01 -7.021558e-01 -3.700000e+00 -1.800000e+00 7.127675e-01 7.127675e-01 3.563837e-01 -7.127675e-01 -3.600000e+00 -1.800000e+00 7.232503e-01 7.232503e-01 3.616251e-01 -7.232503e-01 -3.500000e+00 -1.800000e+00 7.335937e-01 7.335937e-01 3.667969e-01 -7.335937e-01 -3.400000e+00 -1.800000e+00 7.437874e-01 7.437874e-01 3.718937e-01 -7.437874e-01 -3.300000e+00 -1.800000e+00 7.538213e-01 7.538213e-01 3.769106e-01 -7.538213e-01 -3.200000e+00 -1.800000e+00 7.636849e-01 7.636849e-01 3.818425e-01 -7.636849e-01 -3.100000e+00 -1.800000e+00 7.733682e-01 7.733682e-01 3.866841e-01 -7.733682e-01 -3.000000e+00 -1.800000e+00 7.828611e-01 7.828611e-01 3.914306e-01 -7.828611e-01 -2.900000e+00 -1.800000e+00 7.921535e-01 7.921535e-01 3.960768e-01 -7.921535e-01 -2.800000e+00 -1.800000e+00 8.012358e-01 8.012358e-01 4.006179e-01 -8.012358e-01 -2.700000e+00 -1.800000e+00 8.100981e-01 8.100981e-01 4.050490e-01 -8.100981e-01 -2.600000e+00 -1.800000e+00 8.187308e-01 8.187308e-01 4.093654e-01 -8.187308e-01 -2.500000e+00 -1.800000e+00 8.271245e-01 8.271245e-01 4.135623e-01 -8.271245e-01 -2.400000e+00 -1.800000e+00 8.352702e-01 8.352702e-01 4.176351e-01 -8.352702e-01 -2.300000e+00 -1.800000e+00 8.431588e-01 8.431588e-01 4.215794e-01 -8.431588e-01 -2.200000e+00 -1.800000e+00 8.507814e-01 8.507814e-01 4.253907e-01 -8.507814e-01 -2.100000e+00 -1.800000e+00 8.581297e-01 8.581297e-01 4.290649e-01 -8.581297e-01 -2.000000e+00 -1.800000e+00 8.651953e-01 8.651953e-01 4.325977e-01 -8.651953e-01 -1.900000e+00 -1.800000e+00 8.719702e-01 8.719702e-01 4.359851e-01 -8.719702e-01 -1.800000e+00 -1.800000e+00 8.784468e-01 8.784468e-01 4.392234e-01 -8.784468e-01 -1.700000e+00 -1.800000e+00 8.846174e-01 8.846174e-01 4.423087e-01 -8.846174e-01 -1.600000e+00 -1.800000e+00 8.904752e-01 8.904752e-01 4.452376e-01 -8.904752e-01 -1.500000e+00 -1.800000e+00 8.960133e-01 8.960133e-01 4.480067e-01 -8.960133e-01 -1.400000e+00 -1.800000e+00 9.012253e-01 9.012253e-01 4.506127e-01 -9.012253e-01 -1.300000e+00 -1.800000e+00 9.061051e-01 9.061051e-01 4.530526e-01 -9.061051e-01 -1.200000e+00 -1.800000e+00 9.106470e-01 9.106470e-01 4.553235e-01 -9.106470e-01 -1.100000e+00 -1.800000e+00 9.148456e-01 9.148456e-01 4.574228e-01 -9.148456e-01 -1.000000e+00 -1.800000e+00 9.186960e-01 9.186960e-01 4.593480e-01 -9.186960e-01 -9.000000e-01 -1.800000e+00 9.221937e-01 9.221937e-01 4.610969e-01 -9.221937e-01 -8.000000e-01 -1.800000e+00 9.253345e-01 9.253345e-01 4.626673e-01 -9.253345e-01 -7.000000e-01 -1.800000e+00 9.281147e-01 9.281147e-01 4.640573e-01 -9.281147e-01 -6.000000e-01 -1.800000e+00 9.305309e-01 9.305309e-01 4.652655e-01 -9.305309e-01 -5.000000e-01 -1.800000e+00 9.325803e-01 9.325803e-01 4.662901e-01 -9.325803e-01 -4.000000e-01 -1.800000e+00 9.342605e-01 9.342605e-01 4.671302e-01 -9.342605e-01 -3.000000e-01 -1.800000e+00 9.355693e-01 9.355693e-01 4.677847e-01 -9.355693e-01 -2.000000e-01 -1.800000e+00 9.365054e-01 9.365054e-01 4.682527e-01 -9.365054e-01 -1.000000e-01 -1.800000e+00 9.370674e-01 9.370674e-01 4.685337e-01 -9.370674e-01 0.000000e+00 -1.800000e+00 9.372549e-01 9.372549e-01 4.686275e-01 -9.372549e-01 1.000000e-01 -1.800000e+00 9.370674e-01 9.370674e-01 4.685337e-01 -9.370674e-01 2.000000e-01 -1.800000e+00 9.365054e-01 9.365054e-01 4.682527e-01 -9.365054e-01 3.000000e-01 -1.800000e+00 9.355693e-01 9.355693e-01 4.677847e-01 -9.355693e-01 4.000000e-01 -1.800000e+00 9.342605e-01 9.342605e-01 4.671302e-01 -9.342605e-01 5.000000e-01 -1.800000e+00 9.325803e-01 9.325803e-01 4.662901e-01 -9.325803e-01 6.000000e-01 -1.800000e+00 9.305309e-01 9.305309e-01 4.652655e-01 -9.305309e-01 7.000000e-01 -1.800000e+00 9.281147e-01 9.281147e-01 4.640573e-01 -9.281147e-01 8.000000e-01 -1.800000e+00 9.253345e-01 9.253345e-01 4.626673e-01 -9.253345e-01 9.000000e-01 -1.800000e+00 9.221937e-01 9.221937e-01 4.610969e-01 -9.221937e-01 1.000000e+00 -1.800000e+00 9.186960e-01 9.186960e-01 4.593480e-01 -9.186960e-01 1.100000e+00 -1.800000e+00 9.148456e-01 9.148456e-01 4.574228e-01 -9.148456e-01 1.200000e+00 -1.800000e+00 9.106470e-01 9.106470e-01 4.553235e-01 -9.106470e-01 1.300000e+00 -1.800000e+00 9.061051e-01 9.061051e-01 4.530526e-01 -9.061051e-01 1.400000e+00 -1.800000e+00 9.012253e-01 9.012253e-01 4.506127e-01 -9.012253e-01 1.500000e+00 -1.800000e+00 8.960133e-01 8.960133e-01 4.480067e-01 -8.960133e-01 1.600000e+00 -1.800000e+00 8.904752e-01 8.904752e-01 4.452376e-01 -8.904752e-01 1.700000e+00 -1.800000e+00 8.846174e-01 8.846174e-01 4.423087e-01 -8.846174e-01 1.800000e+00 -1.800000e+00 8.784468e-01 8.784468e-01 4.392234e-01 -8.784468e-01 1.900000e+00 -1.800000e+00 8.719702e-01 8.719702e-01 4.359851e-01 -8.719702e-01 2.000000e+00 -1.800000e+00 8.651953e-01 8.651953e-01 4.325977e-01 -8.651953e-01 2.100000e+00 -1.800000e+00 8.581297e-01 8.581297e-01 4.290649e-01 -8.581297e-01 2.200000e+00 -1.800000e+00 8.507814e-01 8.507814e-01 4.253907e-01 -8.507814e-01 2.300000e+00 -1.800000e+00 8.431588e-01 8.431588e-01 4.215794e-01 -8.431588e-01 2.400000e+00 -1.800000e+00 8.352702e-01 8.352702e-01 4.176351e-01 -8.352702e-01 2.500000e+00 -1.800000e+00 8.271245e-01 8.271245e-01 4.135623e-01 -8.271245e-01 2.600000e+00 -1.800000e+00 8.187308e-01 8.187308e-01 4.093654e-01 -8.187308e-01 2.700000e+00 -1.800000e+00 8.100981e-01 8.100981e-01 4.050490e-01 -8.100981e-01 2.800000e+00 -1.800000e+00 8.012358e-01 8.012358e-01 4.006179e-01 -8.012358e-01 2.900000e+00 -1.800000e+00 7.921535e-01 7.921535e-01 3.960768e-01 -7.921535e-01 3.000000e+00 -1.800000e+00 7.828611e-01 7.828611e-01 3.914306e-01 -7.828611e-01 3.100000e+00 -1.800000e+00 7.733682e-01 7.733682e-01 3.866841e-01 -7.733682e-01 3.200000e+00 -1.800000e+00 7.636849e-01 7.636849e-01 3.818425e-01 -7.636849e-01 3.300000e+00 -1.800000e+00 7.538213e-01 7.538213e-01 3.769106e-01 -7.538213e-01 3.400000e+00 -1.800000e+00 7.437874e-01 7.437874e-01 3.718937e-01 -7.437874e-01 3.500000e+00 -1.800000e+00 7.335937e-01 7.335937e-01 3.667969e-01 -7.335937e-01 3.600000e+00 -1.800000e+00 7.232503e-01 7.232503e-01 3.616251e-01 -7.232503e-01 3.700000e+00 -1.800000e+00 7.127675e-01 7.127675e-01 3.563837e-01 -7.127675e-01 3.800000e+00 -1.800000e+00 7.021558e-01 7.021558e-01 3.510779e-01 -7.021558e-01 3.900000e+00 -1.800000e+00 6.914254e-01 6.914254e-01 3.457127e-01 -6.914254e-01 4.000000e+00 -1.800000e+00 6.805868e-01 6.805868e-01 3.402934e-01 -6.805868e-01 4.100000e+00 -1.800000e+00 6.696501e-01 6.696501e-01 3.348250e-01 -6.696501e-01 4.200000e+00 -1.800000e+00 6.586257e-01 6.586257e-01 3.293128e-01 -6.586257e-01 4.300000e+00 -1.800000e+00 6.475236e-01 6.475236e-01 3.237618e-01 -6.475236e-01 4.400000e+00 -1.800000e+00 6.363541e-01 6.363541e-01 3.181771e-01 -6.363541e-01 4.500000e+00 -1.800000e+00 6.251273e-01 6.251273e-01 3.125637e-01 -6.251273e-01 4.600000e+00 -1.800000e+00 6.138529e-01 6.138529e-01 3.069265e-01 -6.138529e-01 4.700000e+00 -1.800000e+00 6.025408e-01 6.025408e-01 3.012704e-01 -6.025408e-01 4.800000e+00 -1.800000e+00 5.912005e-01 5.912005e-01 2.956003e-01 -5.912005e-01 4.900000e+00 -1.800000e+00 5.798418e-01 5.798418e-01 2.899209e-01 -5.798418e-01 -5.000000e+00 -1.700000e+00 5.724671e-01 5.724671e-01 2.862335e-01 -5.724671e-01 -4.900000e+00 -1.700000e+00 5.839149e-01 5.839149e-01 2.919574e-01 -5.839149e-01 -4.800000e+00 -1.700000e+00 5.953534e-01 5.953534e-01 2.976767e-01 -5.953534e-01 -4.700000e+00 -1.700000e+00 6.067734e-01 6.067734e-01 3.033867e-01 -6.067734e-01 -4.600000e+00 -1.700000e+00 6.181650e-01 6.181650e-01 3.090825e-01 -6.181650e-01 -4.500000e+00 -1.700000e+00 6.295186e-01 6.295186e-01 3.147593e-01 -6.295186e-01 -4.400000e+00 -1.700000e+00 6.408243e-01 6.408243e-01 3.204121e-01 -6.408243e-01 -4.300000e+00 -1.700000e+00 6.520722e-01 6.520722e-01 3.260361e-01 -6.520722e-01 -4.200000e+00 -1.700000e+00 6.632522e-01 6.632522e-01 3.316261e-01 -6.632522e-01 -4.100000e+00 -1.700000e+00 6.743541e-01 6.743541e-01 3.371770e-01 -6.743541e-01 -4.000000e+00 -1.700000e+00 6.853675e-01 6.853675e-01 3.426838e-01 -6.853675e-01 -3.900000e+00 -1.700000e+00 6.962823e-01 6.962823e-01 3.481412e-01 -6.962823e-01 -3.800000e+00 -1.700000e+00 7.070881e-01 7.070881e-01 3.535441e-01 -7.070881e-01 -3.700000e+00 -1.700000e+00 7.177744e-01 7.177744e-01 3.588872e-01 -7.177744e-01 -3.600000e+00 -1.700000e+00 7.283308e-01 7.283308e-01 3.641654e-01 -7.283308e-01 -3.500000e+00 -1.700000e+00 7.387468e-01 7.387468e-01 3.693734e-01 -7.387468e-01 -3.400000e+00 -1.700000e+00 7.490122e-01 7.490122e-01 3.745061e-01 -7.490122e-01 -3.300000e+00 -1.700000e+00 7.591165e-01 7.591165e-01 3.795583e-01 -7.591165e-01 -3.200000e+00 -1.700000e+00 7.690495e-01 7.690495e-01 3.845247e-01 -7.690495e-01 -3.100000e+00 -1.700000e+00 7.788008e-01 7.788008e-01 3.894004e-01 -7.788008e-01 -3.000000e+00 -1.700000e+00 7.883604e-01 7.883604e-01 3.941802e-01 -7.883604e-01 -2.900000e+00 -1.700000e+00 7.977180e-01 7.977180e-01 3.988590e-01 -7.977180e-01 -2.800000e+00 -1.700000e+00 8.068641e-01 8.068641e-01 4.034321e-01 -8.068641e-01 -2.700000e+00 -1.700000e+00 8.157886e-01 8.157886e-01 4.078943e-01 -8.157886e-01 -2.600000e+00 -1.700000e+00 8.244820e-01 8.244820e-01 4.122410e-01 -8.244820e-01 -2.500000e+00 -1.700000e+00 8.329347e-01 8.329347e-01 4.164674e-01 -8.329347e-01 -2.400000e+00 -1.700000e+00 8.411376e-01 8.411376e-01 4.205688e-01 -8.411376e-01 -2.300000e+00 -1.700000e+00 8.490816e-01 8.490816e-01 4.245408e-01 -8.490816e-01 -2.200000e+00 -1.700000e+00 8.567578e-01 8.567578e-01 4.283789e-01 -8.567578e-01 -2.100000e+00 -1.700000e+00 8.641577e-01 8.641577e-01 4.320788e-01 -8.641577e-01 -2.000000e+00 -1.700000e+00 8.712729e-01 8.712729e-01 4.356365e-01 -8.712729e-01 -1.900000e+00 -1.700000e+00 8.780954e-01 8.780954e-01 4.390477e-01 -8.780954e-01 -1.800000e+00 -1.700000e+00 8.846174e-01 8.846174e-01 4.423087e-01 -8.846174e-01 -1.700000e+00 -1.700000e+00 8.908315e-01 8.908315e-01 4.454157e-01 -8.908315e-01 -1.600000e+00 -1.700000e+00 8.967304e-01 8.967304e-01 4.483652e-01 -8.967304e-01 -1.500000e+00 -1.700000e+00 9.023074e-01 9.023074e-01 4.511537e-01 -9.023074e-01 -1.400000e+00 -1.700000e+00 9.075560e-01 9.075560e-01 4.537780e-01 -9.075560e-01 -1.300000e+00 -1.700000e+00 9.124700e-01 9.124700e-01 4.562350e-01 -9.124700e-01 -1.200000e+00 -1.700000e+00 9.170438e-01 9.170438e-01 4.585219e-01 -9.170438e-01 -1.100000e+00 -1.700000e+00 9.212720e-01 9.212720e-01 4.606360e-01 -9.212720e-01 -1.000000e+00 -1.700000e+00 9.251494e-01 9.251494e-01 4.625747e-01 -9.251494e-01 -9.000000e-01 -1.700000e+00 9.286717e-01 9.286717e-01 4.643359e-01 -9.286717e-01 -8.000000e-01 -1.700000e+00 9.318345e-01 9.318345e-01 4.659173e-01 -9.318345e-01 -7.000000e-01 -1.700000e+00 9.346343e-01 9.346343e-01 4.673171e-01 -9.346343e-01 -6.000000e-01 -1.700000e+00 9.370674e-01 9.370674e-01 4.685337e-01 -9.370674e-01 -5.000000e-01 -1.700000e+00 9.391313e-01 9.391313e-01 4.695656e-01 -9.391313e-01 -4.000000e-01 -1.700000e+00 9.408233e-01 9.408233e-01 4.704116e-01 -9.408233e-01 -3.000000e-01 -1.700000e+00 9.421413e-01 9.421413e-01 4.710706e-01 -9.421413e-01 -2.000000e-01 -1.700000e+00 9.430839e-01 9.430839e-01 4.715420e-01 -9.430839e-01 -1.000000e-01 -1.700000e+00 9.436499e-01 9.436499e-01 4.718250e-01 -9.436499e-01 0.000000e+00 -1.700000e+00 9.438387e-01 9.438387e-01 4.719194e-01 -9.438387e-01 1.000000e-01 -1.700000e+00 9.436499e-01 9.436499e-01 4.718250e-01 -9.436499e-01 2.000000e-01 -1.700000e+00 9.430839e-01 9.430839e-01 4.715420e-01 -9.430839e-01 3.000000e-01 -1.700000e+00 9.421413e-01 9.421413e-01 4.710706e-01 -9.421413e-01 4.000000e-01 -1.700000e+00 9.408233e-01 9.408233e-01 4.704116e-01 -9.408233e-01 5.000000e-01 -1.700000e+00 9.391313e-01 9.391313e-01 4.695656e-01 -9.391313e-01 6.000000e-01 -1.700000e+00 9.370674e-01 9.370674e-01 4.685337e-01 -9.370674e-01 7.000000e-01 -1.700000e+00 9.346343e-01 9.346343e-01 4.673171e-01 -9.346343e-01 8.000000e-01 -1.700000e+00 9.318345e-01 9.318345e-01 4.659173e-01 -9.318345e-01 9.000000e-01 -1.700000e+00 9.286717e-01 9.286717e-01 4.643359e-01 -9.286717e-01 1.000000e+00 -1.700000e+00 9.251494e-01 9.251494e-01 4.625747e-01 -9.251494e-01 1.100000e+00 -1.700000e+00 9.212720e-01 9.212720e-01 4.606360e-01 -9.212720e-01 1.200000e+00 -1.700000e+00 9.170438e-01 9.170438e-01 4.585219e-01 -9.170438e-01 1.300000e+00 -1.700000e+00 9.124700e-01 9.124700e-01 4.562350e-01 -9.124700e-01 1.400000e+00 -1.700000e+00 9.075560e-01 9.075560e-01 4.537780e-01 -9.075560e-01 1.500000e+00 -1.700000e+00 9.023074e-01 9.023074e-01 4.511537e-01 -9.023074e-01 1.600000e+00 -1.700000e+00 8.967304e-01 8.967304e-01 4.483652e-01 -8.967304e-01 1.700000e+00 -1.700000e+00 8.908315e-01 8.908315e-01 4.454157e-01 -8.908315e-01 1.800000e+00 -1.700000e+00 8.846174e-01 8.846174e-01 4.423087e-01 -8.846174e-01 1.900000e+00 -1.700000e+00 8.780954e-01 8.780954e-01 4.390477e-01 -8.780954e-01 2.000000e+00 -1.700000e+00 8.712729e-01 8.712729e-01 4.356365e-01 -8.712729e-01 2.100000e+00 -1.700000e+00 8.641577e-01 8.641577e-01 4.320788e-01 -8.641577e-01 2.200000e+00 -1.700000e+00 8.567578e-01 8.567578e-01 4.283789e-01 -8.567578e-01 2.300000e+00 -1.700000e+00 8.490816e-01 8.490816e-01 4.245408e-01 -8.490816e-01 2.400000e+00 -1.700000e+00 8.411376e-01 8.411376e-01 4.205688e-01 -8.411376e-01 2.500000e+00 -1.700000e+00 8.329347e-01 8.329347e-01 4.164674e-01 -8.329347e-01 2.600000e+00 -1.700000e+00 8.244820e-01 8.244820e-01 4.122410e-01 -8.244820e-01 2.700000e+00 -1.700000e+00 8.157886e-01 8.157886e-01 4.078943e-01 -8.157886e-01 2.800000e+00 -1.700000e+00 8.068641e-01 8.068641e-01 4.034321e-01 -8.068641e-01 2.900000e+00 -1.700000e+00 7.977180e-01 7.977180e-01 3.988590e-01 -7.977180e-01 3.000000e+00 -1.700000e+00 7.883604e-01 7.883604e-01 3.941802e-01 -7.883604e-01 3.100000e+00 -1.700000e+00 7.788008e-01 7.788008e-01 3.894004e-01 -7.788008e-01 3.200000e+00 -1.700000e+00 7.690495e-01 7.690495e-01 3.845247e-01 -7.690495e-01 3.300000e+00 -1.700000e+00 7.591165e-01 7.591165e-01 3.795583e-01 -7.591165e-01 3.400000e+00 -1.700000e+00 7.490122e-01 7.490122e-01 3.745061e-01 -7.490122e-01 3.500000e+00 -1.700000e+00 7.387468e-01 7.387468e-01 3.693734e-01 -7.387468e-01 3.600000e+00 -1.700000e+00 7.283308e-01 7.283308e-01 3.641654e-01 -7.283308e-01 3.700000e+00 -1.700000e+00 7.177744e-01 7.177744e-01 3.588872e-01 -7.177744e-01 3.800000e+00 -1.700000e+00 7.070881e-01 7.070881e-01 3.535441e-01 -7.070881e-01 3.900000e+00 -1.700000e+00 6.962823e-01 6.962823e-01 3.481412e-01 -6.962823e-01 4.000000e+00 -1.700000e+00 6.853675e-01 6.853675e-01 3.426838e-01 -6.853675e-01 4.100000e+00 -1.700000e+00 6.743541e-01 6.743541e-01 3.371770e-01 -6.743541e-01 4.200000e+00 -1.700000e+00 6.632522e-01 6.632522e-01 3.316261e-01 -6.632522e-01 4.300000e+00 -1.700000e+00 6.520722e-01 6.520722e-01 3.260361e-01 -6.520722e-01 4.400000e+00 -1.700000e+00 6.408243e-01 6.408243e-01 3.204121e-01 -6.408243e-01 4.500000e+00 -1.700000e+00 6.295186e-01 6.295186e-01 3.147593e-01 -6.295186e-01 4.600000e+00 -1.700000e+00 6.181650e-01 6.181650e-01 3.090825e-01 -6.181650e-01 4.700000e+00 -1.700000e+00 6.067734e-01 6.067734e-01 3.033867e-01 -6.067734e-01 4.800000e+00 -1.700000e+00 5.953534e-01 5.953534e-01 2.976767e-01 -5.953534e-01 4.900000e+00 -1.700000e+00 5.839149e-01 5.839149e-01 2.919574e-01 -5.839149e-01 -5.000000e+00 -1.600000e+00 5.762579e-01 5.762579e-01 2.881289e-01 -5.762579e-01 -4.900000e+00 -1.600000e+00 5.877815e-01 5.877815e-01 2.938907e-01 -5.877815e-01 -4.800000e+00 -1.600000e+00 5.992958e-01 5.992958e-01 2.996479e-01 -5.992958e-01 -4.700000e+00 -1.600000e+00 6.107913e-01 6.107913e-01 3.053957e-01 -6.107913e-01 -4.600000e+00 -1.600000e+00 6.222583e-01 6.222583e-01 3.111292e-01 -6.222583e-01 -4.500000e+00 -1.600000e+00 6.336871e-01 6.336871e-01 3.168435e-01 -6.336871e-01 -4.400000e+00 -1.600000e+00 6.450677e-01 6.450677e-01 3.225338e-01 -6.450677e-01 -4.300000e+00 -1.600000e+00 6.563901e-01 6.563901e-01 3.281950e-01 -6.563901e-01 -4.200000e+00 -1.600000e+00 6.676441e-01 6.676441e-01 3.338221e-01 -6.676441e-01 -4.100000e+00 -1.600000e+00 6.788195e-01 6.788195e-01 3.394098e-01 -6.788195e-01 -4.000000e+00 -1.600000e+00 6.899059e-01 6.899059e-01 3.449530e-01 -6.899059e-01 -3.900000e+00 -1.600000e+00 7.008930e-01 7.008930e-01 3.504465e-01 -7.008930e-01 -3.800000e+00 -1.600000e+00 7.117703e-01 7.117703e-01 3.558851e-01 -7.117703e-01 -3.700000e+00 -1.600000e+00 7.225273e-01 7.225273e-01 3.612637e-01 -7.225273e-01 -3.600000e+00 -1.600000e+00 7.331536e-01 7.331536e-01 3.665768e-01 -7.331536e-01 -3.500000e+00 -1.600000e+00 7.436387e-01 7.436387e-01 3.718193e-01 -7.436387e-01 -3.400000e+00 -1.600000e+00 7.539721e-01 7.539721e-01 3.769860e-01 -7.539721e-01 -3.300000e+00 -1.600000e+00 7.641433e-01 7.641433e-01 3.820716e-01 -7.641433e-01 -3.200000e+00 -1.600000e+00 7.741420e-01 7.741420e-01 3.870710e-01 -7.741420e-01 -3.100000e+00 -1.600000e+00 7.839578e-01 7.839578e-01 3.919789e-01 -7.839578e-01 -3.000000e+00 -1.600000e+00 7.935807e-01 7.935807e-01 3.967904e-01 -7.935807e-01 -2.900000e+00 -1.600000e+00 8.030005e-01 8.030005e-01 4.015002e-01 -8.030005e-01 -2.800000e+00 -1.600000e+00 8.122070e-01 8.122070e-01 4.061035e-01 -8.122070e-01 -2.700000e+00 -1.600000e+00 8.211906e-01 8.211906e-01 4.105953e-01 -8.211906e-01 -2.600000e+00 -1.600000e+00 8.299416e-01 8.299416e-01 4.149708e-01 -8.299416e-01 -2.500000e+00 -1.600000e+00 8.384503e-01 8.384503e-01 4.192251e-01 -8.384503e-01 -2.400000e+00 -1.600000e+00 8.467075e-01 8.467075e-01 4.233537e-01 -8.467075e-01 -2.300000e+00 -1.600000e+00 8.547041e-01 8.547041e-01 4.273520e-01 -8.547041e-01 -2.200000e+00 -1.600000e+00 8.624311e-01 8.624311e-01 4.312156e-01 -8.624311e-01 -2.100000e+00 -1.600000e+00 8.698800e-01 8.698800e-01 4.349400e-01 -8.698800e-01 -2.000000e+00 -1.600000e+00 8.770424e-01 8.770424e-01 4.385212e-01 -8.770424e-01 -1.900000e+00 -1.600000e+00 8.839100e-01 8.839100e-01 4.419550e-01 -8.839100e-01 -1.800000e+00 -1.600000e+00 8.904752e-01 8.904752e-01 4.452376e-01 -8.904752e-01 -1.700000e+00 -1.600000e+00 8.967304e-01 8.967304e-01 4.483652e-01 -8.967304e-01 -1.600000e+00 -1.600000e+00 9.026684e-01 9.026684e-01 4.513342e-01 -9.026684e-01 -1.500000e+00 -1.600000e+00 9.082823e-01 9.082823e-01 4.541412e-01 -9.082823e-01 -1.400000e+00 -1.600000e+00 9.135657e-01 9.135657e-01 4.567828e-01 -9.135657e-01 -1.300000e+00 -1.600000e+00 9.185123e-01 9.185123e-01 4.592561e-01 -9.185123e-01 -1.200000e+00 -1.600000e+00 9.231163e-01 9.231163e-01 4.615582e-01 -9.231163e-01 -1.100000e+00 -1.600000e+00 9.273725e-01 9.273725e-01 4.636862e-01 -9.273725e-01 -1.000000e+00 -1.600000e+00 9.312756e-01 9.312756e-01 4.656378e-01 -9.312756e-01 -9.000000e-01 -1.600000e+00 9.348212e-01 9.348212e-01 4.674106e-01 -9.348212e-01 -8.000000e-01 -1.600000e+00 9.380050e-01 9.380050e-01 4.690025e-01 -9.380050e-01 -7.000000e-01 -1.600000e+00 9.408233e-01 9.408233e-01 4.704116e-01 -9.408233e-01 -6.000000e-01 -1.600000e+00 9.432726e-01 9.432726e-01 4.716363e-01 -9.432726e-01 -5.000000e-01 -1.600000e+00 9.453501e-01 9.453501e-01 4.726750e-01 -9.453501e-01 -4.000000e-01 -1.600000e+00 9.470532e-01 9.470532e-01 4.735266e-01 -9.470532e-01 -3.000000e-01 -1.600000e+00 9.483800e-01 9.483800e-01 4.741900e-01 -9.483800e-01 -2.000000e-01 -1.600000e+00 9.493288e-01 9.493288e-01 4.746644e-01 -9.493288e-01 -1.000000e-01 -1.600000e+00 9.498987e-01 9.498987e-01 4.749493e-01 -9.498987e-01 0.000000e+00 -1.600000e+00 9.500886e-01 9.500886e-01 4.750443e-01 -9.500886e-01 1.000000e-01 -1.600000e+00 9.498987e-01 9.498987e-01 4.749493e-01 -9.498987e-01 2.000000e-01 -1.600000e+00 9.493288e-01 9.493288e-01 4.746644e-01 -9.493288e-01 3.000000e-01 -1.600000e+00 9.483800e-01 9.483800e-01 4.741900e-01 -9.483800e-01 4.000000e-01 -1.600000e+00 9.470532e-01 9.470532e-01 4.735266e-01 -9.470532e-01 5.000000e-01 -1.600000e+00 9.453501e-01 9.453501e-01 4.726750e-01 -9.453501e-01 6.000000e-01 -1.600000e+00 9.432726e-01 9.432726e-01 4.716363e-01 -9.432726e-01 7.000000e-01 -1.600000e+00 9.408233e-01 9.408233e-01 4.704116e-01 -9.408233e-01 8.000000e-01 -1.600000e+00 9.380050e-01 9.380050e-01 4.690025e-01 -9.380050e-01 9.000000e-01 -1.600000e+00 9.348212e-01 9.348212e-01 4.674106e-01 -9.348212e-01 1.000000e+00 -1.600000e+00 9.312756e-01 9.312756e-01 4.656378e-01 -9.312756e-01 1.100000e+00 -1.600000e+00 9.273725e-01 9.273725e-01 4.636862e-01 -9.273725e-01 1.200000e+00 -1.600000e+00 9.231163e-01 9.231163e-01 4.615582e-01 -9.231163e-01 1.300000e+00 -1.600000e+00 9.185123e-01 9.185123e-01 4.592561e-01 -9.185123e-01 1.400000e+00 -1.600000e+00 9.135657e-01 9.135657e-01 4.567828e-01 -9.135657e-01 1.500000e+00 -1.600000e+00 9.082823e-01 9.082823e-01 4.541412e-01 -9.082823e-01 1.600000e+00 -1.600000e+00 9.026684e-01 9.026684e-01 4.513342e-01 -9.026684e-01 1.700000e+00 -1.600000e+00 8.967304e-01 8.967304e-01 4.483652e-01 -8.967304e-01 1.800000e+00 -1.600000e+00 8.904752e-01 8.904752e-01 4.452376e-01 -8.904752e-01 1.900000e+00 -1.600000e+00 8.839100e-01 8.839100e-01 4.419550e-01 -8.839100e-01 2.000000e+00 -1.600000e+00 8.770424e-01 8.770424e-01 4.385212e-01 -8.770424e-01 2.100000e+00 -1.600000e+00 8.698800e-01 8.698800e-01 4.349400e-01 -8.698800e-01 2.200000e+00 -1.600000e+00 8.624311e-01 8.624311e-01 4.312156e-01 -8.624311e-01 2.300000e+00 -1.600000e+00 8.547041e-01 8.547041e-01 4.273520e-01 -8.547041e-01 2.400000e+00 -1.600000e+00 8.467075e-01 8.467075e-01 4.233537e-01 -8.467075e-01 2.500000e+00 -1.600000e+00 8.384503e-01 8.384503e-01 4.192251e-01 -8.384503e-01 2.600000e+00 -1.600000e+00 8.299416e-01 8.299416e-01 4.149708e-01 -8.299416e-01 2.700000e+00 -1.600000e+00 8.211906e-01 8.211906e-01 4.105953e-01 -8.211906e-01 2.800000e+00 -1.600000e+00 8.122070e-01 8.122070e-01 4.061035e-01 -8.122070e-01 2.900000e+00 -1.600000e+00 8.030005e-01 8.030005e-01 4.015002e-01 -8.030005e-01 3.000000e+00 -1.600000e+00 7.935807e-01 7.935807e-01 3.967904e-01 -7.935807e-01 3.100000e+00 -1.600000e+00 7.839578e-01 7.839578e-01 3.919789e-01 -7.839578e-01 3.200000e+00 -1.600000e+00 7.741420e-01 7.741420e-01 3.870710e-01 -7.741420e-01 3.300000e+00 -1.600000e+00 7.641433e-01 7.641433e-01 3.820716e-01 -7.641433e-01 3.400000e+00 -1.600000e+00 7.539721e-01 7.539721e-01 3.769860e-01 -7.539721e-01 3.500000e+00 -1.600000e+00 7.436387e-01 7.436387e-01 3.718193e-01 -7.436387e-01 3.600000e+00 -1.600000e+00 7.331536e-01 7.331536e-01 3.665768e-01 -7.331536e-01 3.700000e+00 -1.600000e+00 7.225273e-01 7.225273e-01 3.612637e-01 -7.225273e-01 3.800000e+00 -1.600000e+00 7.117703e-01 7.117703e-01 3.558851e-01 -7.117703e-01 3.900000e+00 -1.600000e+00 7.008930e-01 7.008930e-01 3.504465e-01 -7.008930e-01 4.000000e+00 -1.600000e+00 6.899059e-01 6.899059e-01 3.449530e-01 -6.899059e-01 4.100000e+00 -1.600000e+00 6.788195e-01 6.788195e-01 3.394098e-01 -6.788195e-01 4.200000e+00 -1.600000e+00 6.676441e-01 6.676441e-01 3.338221e-01 -6.676441e-01 4.300000e+00 -1.600000e+00 6.563901e-01 6.563901e-01 3.281950e-01 -6.563901e-01 4.400000e+00 -1.600000e+00 6.450677e-01 6.450677e-01 3.225338e-01 -6.450677e-01 4.500000e+00 -1.600000e+00 6.336871e-01 6.336871e-01 3.168435e-01 -6.336871e-01 4.600000e+00 -1.600000e+00 6.222583e-01 6.222583e-01 3.111292e-01 -6.222583e-01 4.700000e+00 -1.600000e+00 6.107913e-01 6.107913e-01 3.053957e-01 -6.107913e-01 4.800000e+00 -1.600000e+00 5.992958e-01 5.992958e-01 2.996479e-01 -5.992958e-01 4.900000e+00 -1.600000e+00 5.877815e-01 5.877815e-01 2.938907e-01 -5.877815e-01 -5.000000e+00 -1.500000e+00 5.798418e-01 5.798418e-01 2.899209e-01 -5.798418e-01 -4.900000e+00 -1.500000e+00 5.914370e-01 5.914370e-01 2.957185e-01 -5.914370e-01 -4.800000e+00 -1.500000e+00 6.030229e-01 6.030229e-01 3.015115e-01 -6.030229e-01 -4.700000e+00 -1.500000e+00 6.145900e-01 6.145900e-01 3.072950e-01 -6.145900e-01 -4.600000e+00 -1.500000e+00 6.261283e-01 6.261283e-01 3.130642e-01 -6.261283e-01 -4.500000e+00 -1.500000e+00 6.376281e-01 6.376281e-01 3.188141e-01 -6.376281e-01 -4.400000e+00 -1.500000e+00 6.490796e-01 6.490796e-01 3.245398e-01 -6.490796e-01 -4.300000e+00 -1.500000e+00 6.604724e-01 6.604724e-01 3.302362e-01 -6.604724e-01 -4.200000e+00 -1.500000e+00 6.717964e-01 6.717964e-01 3.358982e-01 -6.717964e-01 -4.100000e+00 -1.500000e+00 6.830413e-01 6.830413e-01 3.415206e-01 -6.830413e-01 -4.000000e+00 -1.500000e+00 6.941966e-01 6.941966e-01 3.470983e-01 -6.941966e-01 -3.900000e+00 -1.500000e+00 7.052521e-01 7.052521e-01 3.526260e-01 -7.052521e-01 -3.800000e+00 -1.500000e+00 7.161970e-01 7.161970e-01 3.580985e-01 -7.161970e-01 -3.700000e+00 -1.500000e+00 7.270209e-01 7.270209e-01 3.635105e-01 -7.270209e-01 -3.600000e+00 -1.500000e+00 7.377133e-01 7.377133e-01 3.688567e-01 -7.377133e-01 -3.500000e+00 -1.500000e+00 7.482636e-01 7.482636e-01 3.741318e-01 -7.482636e-01 -3.400000e+00 -1.500000e+00 7.586612e-01 7.586612e-01 3.793306e-01 -7.586612e-01 -3.300000e+00 -1.500000e+00 7.688957e-01 7.688957e-01 3.844478e-01 -7.688957e-01 -3.200000e+00 -1.500000e+00 7.789565e-01 7.789565e-01 3.894783e-01 -7.789565e-01 -3.100000e+00 -1.500000e+00 7.888335e-01 7.888335e-01 3.944167e-01 -7.888335e-01 -3.000000e+00 -1.500000e+00 7.985162e-01 7.985162e-01 3.992581e-01 -7.985162e-01 -2.900000e+00 -1.500000e+00 8.079945e-01 8.079945e-01 4.039972e-01 -8.079945e-01 -2.800000e+00 -1.500000e+00 8.172584e-01 8.172584e-01 4.086292e-01 -8.172584e-01 -2.700000e+00 -1.500000e+00 8.262978e-01 8.262978e-01 4.131489e-01 -8.262978e-01 -2.600000e+00 -1.500000e+00 8.351032e-01 8.351032e-01 4.175516e-01 -8.351032e-01 -2.500000e+00 -1.500000e+00 8.436648e-01 8.436648e-01 4.218324e-01 -8.436648e-01 -2.400000e+00 -1.500000e+00 8.519734e-01 8.519734e-01 4.259867e-01 -8.519734e-01 -2.300000e+00 -1.500000e+00 8.600197e-01 8.600197e-01 4.300098e-01 -8.600197e-01 -2.200000e+00 -1.500000e+00 8.677948e-01 8.677948e-01 4.338974e-01 -8.677948e-01 -2.100000e+00 -1.500000e+00 8.752900e-01 8.752900e-01 4.376450e-01 -8.752900e-01 -2.000000e+00 -1.500000e+00 8.824969e-01 8.824969e-01 4.412484e-01 -8.824969e-01 -1.900000e+00 -1.500000e+00 8.894073e-01 8.894073e-01 4.447036e-01 -8.894073e-01 -1.800000e+00 -1.500000e+00 8.960133e-01 8.960133e-01 4.480067e-01 -8.960133e-01 -1.700000e+00 -1.500000e+00 9.023074e-01 9.023074e-01 4.511537e-01 -9.023074e-01 -1.600000e+00 -1.500000e+00 9.082823e-01 9.082823e-01 4.541412e-01 -9.082823e-01 -1.500000e+00 -1.500000e+00 9.139312e-01 9.139312e-01 4.569656e-01 -9.139312e-01 -1.400000e+00 -1.500000e+00 9.192474e-01 9.192474e-01 4.596237e-01 -9.192474e-01 -1.300000e+00 -1.500000e+00 9.242247e-01 9.242247e-01 4.621124e-01 -9.242247e-01 -1.200000e+00 -1.500000e+00 9.288574e-01 9.288574e-01 4.644287e-01 -9.288574e-01 -1.100000e+00 -1.500000e+00 9.331400e-01 9.331400e-01 4.665700e-01 -9.331400e-01 -1.000000e+00 -1.500000e+00 9.370674e-01 9.370674e-01 4.685337e-01 -9.370674e-01 -9.000000e-01 -1.500000e+00 9.406351e-01 9.406351e-01 4.703175e-01 -9.406351e-01 -8.000000e-01 -1.500000e+00 9.438387e-01 9.438387e-01 4.719194e-01 -9.438387e-01 -7.000000e-01 -1.500000e+00 9.466745e-01 9.466745e-01 4.733372e-01 -9.466745e-01 -6.000000e-01 -1.500000e+00 9.491390e-01 9.491390e-01 4.745695e-01 -9.491390e-01 -5.000000e-01 -1.500000e+00 9.512295e-01 9.512295e-01 4.756147e-01 -9.512295e-01 -4.000000e-01 -1.500000e+00 9.529432e-01 9.529432e-01 4.764716e-01 -9.529432e-01 -3.000000e-01 -1.500000e+00 9.542782e-01 9.542782e-01 4.771391e-01 -9.542782e-01 -2.000000e-01 -1.500000e+00 9.552330e-01 9.552330e-01 4.776165e-01 -9.552330e-01 -1.000000e-01 -1.500000e+00 9.558063e-01 9.558063e-01 4.779032e-01 -9.558063e-01 0.000000e+00 -1.500000e+00 9.559975e-01 9.559975e-01 4.779987e-01 -9.559975e-01 1.000000e-01 -1.500000e+00 9.558063e-01 9.558063e-01 4.779032e-01 -9.558063e-01 2.000000e-01 -1.500000e+00 9.552330e-01 9.552330e-01 4.776165e-01 -9.552330e-01 3.000000e-01 -1.500000e+00 9.542782e-01 9.542782e-01 4.771391e-01 -9.542782e-01 4.000000e-01 -1.500000e+00 9.529432e-01 9.529432e-01 4.764716e-01 -9.529432e-01 5.000000e-01 -1.500000e+00 9.512295e-01 9.512295e-01 4.756147e-01 -9.512295e-01 6.000000e-01 -1.500000e+00 9.491390e-01 9.491390e-01 4.745695e-01 -9.491390e-01 7.000000e-01 -1.500000e+00 9.466745e-01 9.466745e-01 4.733372e-01 -9.466745e-01 8.000000e-01 -1.500000e+00 9.438387e-01 9.438387e-01 4.719194e-01 -9.438387e-01 9.000000e-01 -1.500000e+00 9.406351e-01 9.406351e-01 4.703175e-01 -9.406351e-01 1.000000e+00 -1.500000e+00 9.370674e-01 9.370674e-01 4.685337e-01 -9.370674e-01 1.100000e+00 -1.500000e+00 9.331400e-01 9.331400e-01 4.665700e-01 -9.331400e-01 1.200000e+00 -1.500000e+00 9.288574e-01 9.288574e-01 4.644287e-01 -9.288574e-01 1.300000e+00 -1.500000e+00 9.242247e-01 9.242247e-01 4.621124e-01 -9.242247e-01 1.400000e+00 -1.500000e+00 9.192474e-01 9.192474e-01 4.596237e-01 -9.192474e-01 1.500000e+00 -1.500000e+00 9.139312e-01 9.139312e-01 4.569656e-01 -9.139312e-01 1.600000e+00 -1.500000e+00 9.082823e-01 9.082823e-01 4.541412e-01 -9.082823e-01 1.700000e+00 -1.500000e+00 9.023074e-01 9.023074e-01 4.511537e-01 -9.023074e-01 1.800000e+00 -1.500000e+00 8.960133e-01 8.960133e-01 4.480067e-01 -8.960133e-01 1.900000e+00 -1.500000e+00 8.894073e-01 8.894073e-01 4.447036e-01 -8.894073e-01 2.000000e+00 -1.500000e+00 8.824969e-01 8.824969e-01 4.412484e-01 -8.824969e-01 2.100000e+00 -1.500000e+00 8.752900e-01 8.752900e-01 4.376450e-01 -8.752900e-01 2.200000e+00 -1.500000e+00 8.677948e-01 8.677948e-01 4.338974e-01 -8.677948e-01 2.300000e+00 -1.500000e+00 8.600197e-01 8.600197e-01 4.300098e-01 -8.600197e-01 2.400000e+00 -1.500000e+00 8.519734e-01 8.519734e-01 4.259867e-01 -8.519734e-01 2.500000e+00 -1.500000e+00 8.436648e-01 8.436648e-01 4.218324e-01 -8.436648e-01 2.600000e+00 -1.500000e+00 8.351032e-01 8.351032e-01 4.175516e-01 -8.351032e-01 2.700000e+00 -1.500000e+00 8.262978e-01 8.262978e-01 4.131489e-01 -8.262978e-01 2.800000e+00 -1.500000e+00 8.172584e-01 8.172584e-01 4.086292e-01 -8.172584e-01 2.900000e+00 -1.500000e+00 8.079945e-01 8.079945e-01 4.039972e-01 -8.079945e-01 3.000000e+00 -1.500000e+00 7.985162e-01 7.985162e-01 3.992581e-01 -7.985162e-01 3.100000e+00 -1.500000e+00 7.888335e-01 7.888335e-01 3.944167e-01 -7.888335e-01 3.200000e+00 -1.500000e+00 7.789565e-01 7.789565e-01 3.894783e-01 -7.789565e-01 3.300000e+00 -1.500000e+00 7.688957e-01 7.688957e-01 3.844478e-01 -7.688957e-01 3.400000e+00 -1.500000e+00 7.586612e-01 7.586612e-01 3.793306e-01 -7.586612e-01 3.500000e+00 -1.500000e+00 7.482636e-01 7.482636e-01 3.741318e-01 -7.482636e-01 3.600000e+00 -1.500000e+00 7.377133e-01 7.377133e-01 3.688567e-01 -7.377133e-01 3.700000e+00 -1.500000e+00 7.270209e-01 7.270209e-01 3.635105e-01 -7.270209e-01 3.800000e+00 -1.500000e+00 7.161970e-01 7.161970e-01 3.580985e-01 -7.161970e-01 3.900000e+00 -1.500000e+00 7.052521e-01 7.052521e-01 3.526260e-01 -7.052521e-01 4.000000e+00 -1.500000e+00 6.941966e-01 6.941966e-01 3.470983e-01 -6.941966e-01 4.100000e+00 -1.500000e+00 6.830413e-01 6.830413e-01 3.415206e-01 -6.830413e-01 4.200000e+00 -1.500000e+00 6.717964e-01 6.717964e-01 3.358982e-01 -6.717964e-01 4.300000e+00 -1.500000e+00 6.604724e-01 6.604724e-01 3.302362e-01 -6.604724e-01 4.400000e+00 -1.500000e+00 6.490796e-01 6.490796e-01 3.245398e-01 -6.490796e-01 4.500000e+00 -1.500000e+00 6.376281e-01 6.376281e-01 3.188141e-01 -6.376281e-01 4.600000e+00 -1.500000e+00 6.261283e-01 6.261283e-01 3.130642e-01 -6.261283e-01 4.700000e+00 -1.500000e+00 6.145900e-01 6.145900e-01 3.072950e-01 -6.145900e-01 4.800000e+00 -1.500000e+00 6.030229e-01 6.030229e-01 3.015115e-01 -6.030229e-01 4.900000e+00 -1.500000e+00 5.914370e-01 5.914370e-01 2.957185e-01 -5.914370e-01 -5.000000e+00 -1.400000e+00 5.832146e-01 5.832146e-01 2.916073e-01 -5.832146e-01 -4.900000e+00 -1.400000e+00 5.948774e-01 5.948774e-01 2.974387e-01 -5.948774e-01 -4.800000e+00 -1.400000e+00 6.065307e-01 6.065307e-01 3.032653e-01 -6.065307e-01 -4.700000e+00 -1.400000e+00 6.181650e-01 6.181650e-01 3.090825e-01 -6.181650e-01 -4.600000e+00 -1.400000e+00 6.297704e-01 6.297704e-01 3.148852e-01 -6.297704e-01 -4.500000e+00 -1.400000e+00 6.413372e-01 6.413372e-01 3.206686e-01 -6.413372e-01 -4.400000e+00 -1.400000e+00 6.528552e-01 6.528552e-01 3.264276e-01 -6.528552e-01 -4.300000e+00 -1.400000e+00 6.643142e-01 6.643142e-01 3.321571e-01 -6.643142e-01 -4.200000e+00 -1.400000e+00 6.757041e-01 6.757041e-01 3.378521e-01 -6.757041e-01 -4.100000e+00 -1.400000e+00 6.870144e-01 6.870144e-01 3.435072e-01 -6.870144e-01 -4.000000e+00 -1.400000e+00 6.982347e-01 6.982347e-01 3.491173e-01 -6.982347e-01 -3.900000e+00 -1.400000e+00 7.093544e-01 7.093544e-01 3.546772e-01 -7.093544e-01 -3.800000e+00 -1.400000e+00 7.203630e-01 7.203630e-01 3.601815e-01 -7.203630e-01 -3.700000e+00 -1.400000e+00 7.312499e-01 7.312499e-01 3.656249e-01 -7.312499e-01 -3.600000e+00 -1.400000e+00 7.420045e-01 7.420045e-01 3.710023e-01 -7.420045e-01 -3.500000e+00 -1.400000e+00 7.526161e-01 7.526161e-01 3.763081e-01 -7.526161e-01 -3.400000e+00 -1.400000e+00 7.630742e-01 7.630742e-01 3.815371e-01 -7.630742e-01 -3.300000e+00 -1.400000e+00 7.733682e-01 7.733682e-01 3.866841e-01 -7.733682e-01 -3.200000e+00 -1.400000e+00 7.834876e-01 7.834876e-01 3.917438e-01 -7.834876e-01 -3.100000e+00 -1.400000e+00 7.934220e-01 7.934220e-01 3.967110e-01 -7.934220e-01 -3.000000e+00 -1.400000e+00 8.031611e-01 8.031611e-01 4.015805e-01 -8.031611e-01 -2.900000e+00 -1.400000e+00 8.126945e-01 8.126945e-01 4.063472e-01 -8.126945e-01 -2.800000e+00 -1.400000e+00 8.220122e-01 8.220122e-01 4.110061e-01 -8.220122e-01 -2.700000e+00 -1.400000e+00 8.311043e-01 8.311043e-01 4.155521e-01 -8.311043e-01 -2.600000e+00 -1.400000e+00 8.399609e-01 8.399609e-01 4.199804e-01 -8.399609e-01 -2.500000e+00 -1.400000e+00 8.485723e-01 8.485723e-01 4.242861e-01 -8.485723e-01 -2.400000e+00 -1.400000e+00 8.569292e-01 8.569292e-01 4.284646e-01 -8.569292e-01 -2.300000e+00 -1.400000e+00 8.650223e-01 8.650223e-01 4.325112e-01 -8.650223e-01 -2.200000e+00 -1.400000e+00 8.728426e-01 8.728426e-01 4.364213e-01 -8.728426e-01 -2.100000e+00 -1.400000e+00 8.803815e-01 8.803815e-01 4.401907e-01 -8.803815e-01 -2.000000e+00 -1.400000e+00 8.876302e-01 8.876302e-01 4.438151e-01 -8.876302e-01 -1.900000e+00 -1.400000e+00 8.945808e-01 8.945808e-01 4.472904e-01 -8.945808e-01 -1.800000e+00 -1.400000e+00 9.012253e-01 9.012253e-01 4.506127e-01 -9.012253e-01 -1.700000e+00 -1.400000e+00 9.075560e-01 9.075560e-01 4.537780e-01 -9.075560e-01 -1.600000e+00 -1.400000e+00 9.135657e-01 9.135657e-01 4.567828e-01 -9.135657e-01 -1.500000e+00 -1.400000e+00 9.192474e-01 9.192474e-01 4.596237e-01 -9.192474e-01 -1.400000e+00 -1.400000e+00 9.245945e-01 9.245945e-01 4.622973e-01 -9.245945e-01 -1.300000e+00 -1.400000e+00 9.296008e-01 9.296008e-01 4.648004e-01 -9.296008e-01 -1.200000e+00 -1.400000e+00 9.342605e-01 9.342605e-01 4.671302e-01 -9.342605e-01 -1.100000e+00 -1.400000e+00 9.385680e-01 9.385680e-01 4.692840e-01 -9.385680e-01 -1.000000e+00 -1.400000e+00 9.425182e-01 9.425182e-01 4.712591e-01 -9.425182e-01 -9.000000e-01 -1.400000e+00 9.461066e-01 9.461066e-01 4.730533e-01 -9.461066e-01 -8.000000e-01 -1.400000e+00 9.493288e-01 9.493288e-01 4.746644e-01 -9.493288e-01 -7.000000e-01 -1.400000e+00 9.521811e-01 9.521811e-01 4.760906e-01 -9.521811e-01 -6.000000e-01 -1.400000e+00 9.546600e-01 9.546600e-01 4.773300e-01 -9.546600e-01 -5.000000e-01 -1.400000e+00 9.567626e-01 9.567626e-01 4.783813e-01 -9.567626e-01 -4.000000e-01 -1.400000e+00 9.584863e-01 9.584863e-01 4.792432e-01 -9.584863e-01 -3.000000e-01 -1.400000e+00 9.598292e-01 9.598292e-01 4.799146e-01 -9.598292e-01 -2.000000e-01 -1.400000e+00 9.607894e-01 9.607894e-01 4.803947e-01 -9.607894e-01 -1.000000e-01 -1.400000e+00 9.613661e-01 9.613661e-01 4.806830e-01 -9.613661e-01 0.000000e+00 -1.400000e+00 9.615584e-01 9.615584e-01 4.807792e-01 -9.615584e-01 1.000000e-01 -1.400000e+00 9.613661e-01 9.613661e-01 4.806830e-01 -9.613661e-01 2.000000e-01 -1.400000e+00 9.607894e-01 9.607894e-01 4.803947e-01 -9.607894e-01 3.000000e-01 -1.400000e+00 9.598292e-01 9.598292e-01 4.799146e-01 -9.598292e-01 4.000000e-01 -1.400000e+00 9.584863e-01 9.584863e-01 4.792432e-01 -9.584863e-01 5.000000e-01 -1.400000e+00 9.567626e-01 9.567626e-01 4.783813e-01 -9.567626e-01 6.000000e-01 -1.400000e+00 9.546600e-01 9.546600e-01 4.773300e-01 -9.546600e-01 7.000000e-01 -1.400000e+00 9.521811e-01 9.521811e-01 4.760906e-01 -9.521811e-01 8.000000e-01 -1.400000e+00 9.493288e-01 9.493288e-01 4.746644e-01 -9.493288e-01 9.000000e-01 -1.400000e+00 9.461066e-01 9.461066e-01 4.730533e-01 -9.461066e-01 1.000000e+00 -1.400000e+00 9.425182e-01 9.425182e-01 4.712591e-01 -9.425182e-01 1.100000e+00 -1.400000e+00 9.385680e-01 9.385680e-01 4.692840e-01 -9.385680e-01 1.200000e+00 -1.400000e+00 9.342605e-01 9.342605e-01 4.671302e-01 -9.342605e-01 1.300000e+00 -1.400000e+00 9.296008e-01 9.296008e-01 4.648004e-01 -9.296008e-01 1.400000e+00 -1.400000e+00 9.245945e-01 9.245945e-01 4.622973e-01 -9.245945e-01 1.500000e+00 -1.400000e+00 9.192474e-01 9.192474e-01 4.596237e-01 -9.192474e-01 1.600000e+00 -1.400000e+00 9.135657e-01 9.135657e-01 4.567828e-01 -9.135657e-01 1.700000e+00 -1.400000e+00 9.075560e-01 9.075560e-01 4.537780e-01 -9.075560e-01 1.800000e+00 -1.400000e+00 9.012253e-01 9.012253e-01 4.506127e-01 -9.012253e-01 1.900000e+00 -1.400000e+00 8.945808e-01 8.945808e-01 4.472904e-01 -8.945808e-01 2.000000e+00 -1.400000e+00 8.876302e-01 8.876302e-01 4.438151e-01 -8.876302e-01 2.100000e+00 -1.400000e+00 8.803815e-01 8.803815e-01 4.401907e-01 -8.803815e-01 2.200000e+00 -1.400000e+00 8.728426e-01 8.728426e-01 4.364213e-01 -8.728426e-01 2.300000e+00 -1.400000e+00 8.650223e-01 8.650223e-01 4.325112e-01 -8.650223e-01 2.400000e+00 -1.400000e+00 8.569292e-01 8.569292e-01 4.284646e-01 -8.569292e-01 2.500000e+00 -1.400000e+00 8.485723e-01 8.485723e-01 4.242861e-01 -8.485723e-01 2.600000e+00 -1.400000e+00 8.399609e-01 8.399609e-01 4.199804e-01 -8.399609e-01 2.700000e+00 -1.400000e+00 8.311043e-01 8.311043e-01 4.155521e-01 -8.311043e-01 2.800000e+00 -1.400000e+00 8.220122e-01 8.220122e-01 4.110061e-01 -8.220122e-01 2.900000e+00 -1.400000e+00 8.126945e-01 8.126945e-01 4.063472e-01 -8.126945e-01 3.000000e+00 -1.400000e+00 8.031611e-01 8.031611e-01 4.015805e-01 -8.031611e-01 3.100000e+00 -1.400000e+00 7.934220e-01 7.934220e-01 3.967110e-01 -7.934220e-01 3.200000e+00 -1.400000e+00 7.834876e-01 7.834876e-01 3.917438e-01 -7.834876e-01 3.300000e+00 -1.400000e+00 7.733682e-01 7.733682e-01 3.866841e-01 -7.733682e-01 3.400000e+00 -1.400000e+00 7.630742e-01 7.630742e-01 3.815371e-01 -7.630742e-01 3.500000e+00 -1.400000e+00 7.526161e-01 7.526161e-01 3.763081e-01 -7.526161e-01 3.600000e+00 -1.400000e+00 7.420045e-01 7.420045e-01 3.710023e-01 -7.420045e-01 3.700000e+00 -1.400000e+00 7.312499e-01 7.312499e-01 3.656249e-01 -7.312499e-01 3.800000e+00 -1.400000e+00 7.203630e-01 7.203630e-01 3.601815e-01 -7.203630e-01 3.900000e+00 -1.400000e+00 7.093544e-01 7.093544e-01 3.546772e-01 -7.093544e-01 4.000000e+00 -1.400000e+00 6.982347e-01 6.982347e-01 3.491173e-01 -6.982347e-01 4.100000e+00 -1.400000e+00 6.870144e-01 6.870144e-01 3.435072e-01 -6.870144e-01 4.200000e+00 -1.400000e+00 6.757041e-01 6.757041e-01 3.378521e-01 -6.757041e-01 4.300000e+00 -1.400000e+00 6.643142e-01 6.643142e-01 3.321571e-01 -6.643142e-01 4.400000e+00 -1.400000e+00 6.528552e-01 6.528552e-01 3.264276e-01 -6.528552e-01 4.500000e+00 -1.400000e+00 6.413372e-01 6.413372e-01 3.206686e-01 -6.413372e-01 4.600000e+00 -1.400000e+00 6.297704e-01 6.297704e-01 3.148852e-01 -6.297704e-01 4.700000e+00 -1.400000e+00 6.181650e-01 6.181650e-01 3.090825e-01 -6.181650e-01 4.800000e+00 -1.400000e+00 6.065307e-01 6.065307e-01 3.032653e-01 -6.065307e-01 4.900000e+00 -1.400000e+00 5.948774e-01 5.948774e-01 2.974387e-01 -5.948774e-01 -5.000000e+00 -1.300000e+00 5.863725e-01 5.863725e-01 2.931862e-01 -5.863725e-01 -4.900000e+00 -1.300000e+00 5.980984e-01 5.980984e-01 2.990492e-01 -5.980984e-01 -4.800000e+00 -1.300000e+00 6.098148e-01 6.098148e-01 3.049074e-01 -6.098148e-01 -4.700000e+00 -1.300000e+00 6.215121e-01 6.215121e-01 3.107560e-01 -6.215121e-01 -4.600000e+00 -1.300000e+00 6.331804e-01 6.331804e-01 3.165902e-01 -6.331804e-01 -4.500000e+00 -1.300000e+00 6.448097e-01 6.448097e-01 3.224049e-01 -6.448097e-01 -4.400000e+00 -1.300000e+00 6.563901e-01 6.563901e-01 3.281950e-01 -6.563901e-01 -4.300000e+00 -1.300000e+00 6.679112e-01 6.679112e-01 3.339556e-01 -6.679112e-01 -4.200000e+00 -1.300000e+00 6.793628e-01 6.793628e-01 3.396814e-01 -6.793628e-01 -4.100000e+00 -1.300000e+00 6.907343e-01 6.907343e-01 3.453672e-01 -6.907343e-01 -4.000000e+00 -1.300000e+00 7.020153e-01 7.020153e-01 3.510077e-01 -7.020153e-01 -3.900000e+00 -1.300000e+00 7.131953e-01 7.131953e-01 3.565976e-01 -7.131953e-01 -3.800000e+00 -1.300000e+00 7.242635e-01 7.242635e-01 3.621317e-01 -7.242635e-01 -3.700000e+00 -1.300000e+00 7.352093e-01 7.352093e-01 3.676047e-01 -7.352093e-01 -3.600000e+00 -1.300000e+00 7.460222e-01 7.460222e-01 3.730111e-01 -7.460222e-01 -3.500000e+00 -1.300000e+00 7.566912e-01 7.566912e-01 3.783456e-01 -7.566912e-01 -3.400000e+00 -1.300000e+00 7.672060e-01 7.672060e-01 3.836030e-01 -7.672060e-01 -3.300000e+00 -1.300000e+00 7.775557e-01 7.775557e-01 3.887779e-01 -7.775557e-01 -3.200000e+00 -1.300000e+00 7.877299e-01 7.877299e-01 3.938650e-01 -7.877299e-01 -3.100000e+00 -1.300000e+00 7.977181e-01 7.977181e-01 3.988591e-01 -7.977181e-01 -3.000000e+00 -1.300000e+00 8.075098e-01 8.075098e-01 4.037549e-01 -8.075098e-01 -2.900000e+00 -1.300000e+00 8.170949e-01 8.170949e-01 4.085475e-01 -8.170949e-01 -2.800000e+00 -1.300000e+00 8.264631e-01 8.264631e-01 4.132316e-01 -8.264631e-01 -2.700000e+00 -1.300000e+00 8.356044e-01 8.356044e-01 4.178022e-01 -8.356044e-01 -2.600000e+00 -1.300000e+00 8.445089e-01 8.445089e-01 4.222544e-01 -8.445089e-01 -2.500000e+00 -1.300000e+00 8.531670e-01 8.531670e-01 4.265835e-01 -8.531670e-01 -2.400000e+00 -1.300000e+00 8.615691e-01 8.615691e-01 4.307846e-01 -8.615691e-01 -2.300000e+00 -1.300000e+00 8.697061e-01 8.697061e-01 4.348530e-01 -8.697061e-01 -2.200000e+00 -1.300000e+00 8.775687e-01 8.775687e-01 4.387844e-01 -8.775687e-01 -2.100000e+00 -1.300000e+00 8.851483e-01 8.851483e-01 4.425742e-01 -8.851483e-01 -2.000000e+00 -1.300000e+00 8.924364e-01 8.924364e-01 4.462182e-01 -8.924364e-01 -1.900000e+00 -1.300000e+00 8.994247e-01 8.994247e-01 4.497123e-01 -8.994247e-01 -1.800000e+00 -1.300000e+00 9.061051e-01 9.061051e-01 4.530526e-01 -9.061051e-01 -1.700000e+00 -1.300000e+00 9.124700e-01 9.124700e-01 4.562350e-01 -9.124700e-01 -1.600000e+00 -1.300000e+00 9.185123e-01 9.185123e-01 4.592561e-01 -9.185123e-01 -1.500000e+00 -1.300000e+00 9.242247e-01 9.242247e-01 4.621124e-01 -9.242247e-01 -1.400000e+00 -1.300000e+00 9.296008e-01 9.296008e-01 4.648004e-01 -9.296008e-01 -1.300000e+00 -1.300000e+00 9.346343e-01 9.346343e-01 4.673171e-01 -9.346343e-01 -1.200000e+00 -1.300000e+00 9.393191e-01 9.393191e-01 4.696596e-01 -9.393191e-01 -1.100000e+00 -1.300000e+00 9.436499e-01 9.436499e-01 4.718250e-01 -9.436499e-01 -1.000000e+00 -1.300000e+00 9.476216e-01 9.476216e-01 4.738108e-01 -9.476216e-01 -9.000000e-01 -1.300000e+00 9.512295e-01 9.512295e-01 4.756147e-01 -9.512295e-01 -8.000000e-01 -1.300000e+00 9.544691e-01 9.544691e-01 4.772345e-01 -9.544691e-01 -7.000000e-01 -1.300000e+00 9.573368e-01 9.573368e-01 4.786684e-01 -9.573368e-01 -6.000000e-01 -1.300000e+00 9.598292e-01 9.598292e-01 4.799146e-01 -9.598292e-01 -5.000000e-01 -1.300000e+00 9.619431e-01 9.619431e-01 4.809715e-01 -9.619431e-01 -4.000000e-01 -1.300000e+00 9.636762e-01 9.636762e-01 4.818381e-01 -9.636762e-01 -3.000000e-01 -1.300000e+00 9.650262e-01 9.650262e-01 4.825131e-01 -9.650262e-01 -2.000000e-01 -1.300000e+00 9.659917e-01 9.659917e-01 4.829959e-01 -9.659917e-01 -1.000000e-01 -1.300000e+00 9.665715e-01 9.665715e-01 4.832858e-01 -9.665715e-01 0.000000e+00 -1.300000e+00 9.667649e-01 9.667649e-01 4.833824e-01 -9.667649e-01 1.000000e-01 -1.300000e+00 9.665715e-01 9.665715e-01 4.832858e-01 -9.665715e-01 2.000000e-01 -1.300000e+00 9.659917e-01 9.659917e-01 4.829959e-01 -9.659917e-01 3.000000e-01 -1.300000e+00 9.650262e-01 9.650262e-01 4.825131e-01 -9.650262e-01 4.000000e-01 -1.300000e+00 9.636762e-01 9.636762e-01 4.818381e-01 -9.636762e-01 5.000000e-01 -1.300000e+00 9.619431e-01 9.619431e-01 4.809715e-01 -9.619431e-01 6.000000e-01 -1.300000e+00 9.598292e-01 9.598292e-01 4.799146e-01 -9.598292e-01 7.000000e-01 -1.300000e+00 9.573368e-01 9.573368e-01 4.786684e-01 -9.573368e-01 8.000000e-01 -1.300000e+00 9.544691e-01 9.544691e-01 4.772345e-01 -9.544691e-01 9.000000e-01 -1.300000e+00 9.512295e-01 9.512295e-01 4.756147e-01 -9.512295e-01 1.000000e+00 -1.300000e+00 9.476216e-01 9.476216e-01 4.738108e-01 -9.476216e-01 1.100000e+00 -1.300000e+00 9.436499e-01 9.436499e-01 4.718250e-01 -9.436499e-01 1.200000e+00 -1.300000e+00 9.393191e-01 9.393191e-01 4.696596e-01 -9.393191e-01 1.300000e+00 -1.300000e+00 9.346343e-01 9.346343e-01 4.673171e-01 -9.346343e-01 1.400000e+00 -1.300000e+00 9.296008e-01 9.296008e-01 4.648004e-01 -9.296008e-01 1.500000e+00 -1.300000e+00 9.242247e-01 9.242247e-01 4.621124e-01 -9.242247e-01 1.600000e+00 -1.300000e+00 9.185123e-01 9.185123e-01 4.592561e-01 -9.185123e-01 1.700000e+00 -1.300000e+00 9.124700e-01 9.124700e-01 4.562350e-01 -9.124700e-01 1.800000e+00 -1.300000e+00 9.061051e-01 9.061051e-01 4.530526e-01 -9.061051e-01 1.900000e+00 -1.300000e+00 8.994247e-01 8.994247e-01 4.497123e-01 -8.994247e-01 2.000000e+00 -1.300000e+00 8.924364e-01 8.924364e-01 4.462182e-01 -8.924364e-01 2.100000e+00 -1.300000e+00 8.851483e-01 8.851483e-01 4.425742e-01 -8.851483e-01 2.200000e+00 -1.300000e+00 8.775687e-01 8.775687e-01 4.387844e-01 -8.775687e-01 2.300000e+00 -1.300000e+00 8.697061e-01 8.697061e-01 4.348530e-01 -8.697061e-01 2.400000e+00 -1.300000e+00 8.615691e-01 8.615691e-01 4.307846e-01 -8.615691e-01 2.500000e+00 -1.300000e+00 8.531670e-01 8.531670e-01 4.265835e-01 -8.531670e-01 2.600000e+00 -1.300000e+00 8.445089e-01 8.445089e-01 4.222544e-01 -8.445089e-01 2.700000e+00 -1.300000e+00 8.356044e-01 8.356044e-01 4.178022e-01 -8.356044e-01 2.800000e+00 -1.300000e+00 8.264631e-01 8.264631e-01 4.132316e-01 -8.264631e-01 2.900000e+00 -1.300000e+00 8.170949e-01 8.170949e-01 4.085475e-01 -8.170949e-01 3.000000e+00 -1.300000e+00 8.075098e-01 8.075098e-01 4.037549e-01 -8.075098e-01 3.100000e+00 -1.300000e+00 7.977181e-01 7.977181e-01 3.988591e-01 -7.977181e-01 3.200000e+00 -1.300000e+00 7.877299e-01 7.877299e-01 3.938650e-01 -7.877299e-01 3.300000e+00 -1.300000e+00 7.775557e-01 7.775557e-01 3.887779e-01 -7.775557e-01 3.400000e+00 -1.300000e+00 7.672060e-01 7.672060e-01 3.836030e-01 -7.672060e-01 3.500000e+00 -1.300000e+00 7.566912e-01 7.566912e-01 3.783456e-01 -7.566912e-01 3.600000e+00 -1.300000e+00 7.460222e-01 7.460222e-01 3.730111e-01 -7.460222e-01 3.700000e+00 -1.300000e+00 7.352093e-01 7.352093e-01 3.676047e-01 -7.352093e-01 3.800000e+00 -1.300000e+00 7.242635e-01 7.242635e-01 3.621317e-01 -7.242635e-01 3.900000e+00 -1.300000e+00 7.131953e-01 7.131953e-01 3.565976e-01 -7.131953e-01 4.000000e+00 -1.300000e+00 7.020153e-01 7.020153e-01 3.510077e-01 -7.020153e-01 4.100000e+00 -1.300000e+00 6.907343e-01 6.907343e-01 3.453672e-01 -6.907343e-01 4.200000e+00 -1.300000e+00 6.793628e-01 6.793628e-01 3.396814e-01 -6.793628e-01 4.300000e+00 -1.300000e+00 6.679112e-01 6.679112e-01 3.339556e-01 -6.679112e-01 4.400000e+00 -1.300000e+00 6.563901e-01 6.563901e-01 3.281950e-01 -6.563901e-01 4.500000e+00 -1.300000e+00 6.448097e-01 6.448097e-01 3.224049e-01 -6.448097e-01 4.600000e+00 -1.300000e+00 6.331804e-01 6.331804e-01 3.165902e-01 -6.331804e-01 4.700000e+00 -1.300000e+00 6.215121e-01 6.215121e-01 3.107560e-01 -6.215121e-01 4.800000e+00 -1.300000e+00 6.098148e-01 6.098148e-01 3.049074e-01 -6.098148e-01 4.900000e+00 -1.300000e+00 5.980984e-01 5.980984e-01 2.990492e-01 -5.980984e-01 -5.000000e+00 -1.200000e+00 5.893117e-01 5.893117e-01 2.946559e-01 -5.893117e-01 -4.900000e+00 -1.200000e+00 6.010964e-01 6.010964e-01 3.005482e-01 -6.010964e-01 -4.800000e+00 -1.200000e+00 6.128715e-01 6.128715e-01 3.064357e-01 -6.128715e-01 -4.700000e+00 -1.200000e+00 6.246274e-01 6.246274e-01 3.123137e-01 -6.246274e-01 -4.600000e+00 -1.200000e+00 6.363542e-01 6.363542e-01 3.181771e-01 -6.363542e-01 -4.500000e+00 -1.200000e+00 6.480418e-01 6.480418e-01 3.240209e-01 -6.480418e-01 -4.400000e+00 -1.200000e+00 6.596802e-01 6.596802e-01 3.298401e-01 -6.596802e-01 -4.300000e+00 -1.200000e+00 6.712592e-01 6.712592e-01 3.356296e-01 -6.712592e-01 -4.200000e+00 -1.200000e+00 6.827681e-01 6.827681e-01 3.413841e-01 -6.827681e-01 -4.100000e+00 -1.200000e+00 6.941966e-01 6.941966e-01 3.470983e-01 -6.941966e-01 -4.000000e+00 -1.200000e+00 7.055342e-01 7.055342e-01 3.527671e-01 -7.055342e-01 -3.900000e+00 -1.200000e+00 7.167702e-01 7.167702e-01 3.583851e-01 -7.167702e-01 -3.800000e+00 -1.200000e+00 7.278939e-01 7.278939e-01 3.639469e-01 -7.278939e-01 -3.700000e+00 -1.200000e+00 7.388946e-01 7.388946e-01 3.694473e-01 -7.388946e-01 -3.600000e+00 -1.200000e+00 7.497616e-01 7.497616e-01 3.748808e-01 -7.497616e-01 -3.500000e+00 -1.200000e+00 7.604842e-01 7.604842e-01 3.802421e-01 -7.604842e-01 -3.400000e+00 -1.200000e+00 7.710516e-01 7.710516e-01 3.855258e-01 -7.710516e-01 -3.300000e+00 -1.200000e+00 7.814533e-01 7.814533e-01 3.907266e-01 -7.814533e-01 -3.200000e+00 -1.200000e+00 7.916784e-01 7.916784e-01 3.958392e-01 -7.916784e-01 -3.100000e+00 -1.200000e+00 8.017167e-01 8.017167e-01 4.008583e-01 -8.017167e-01 -3.000000e+00 -1.200000e+00 8.115575e-01 8.115575e-01 4.057788e-01 -8.115575e-01 -2.900000e+00 -1.200000e+00 8.211906e-01 8.211906e-01 4.105953e-01 -8.211906e-01 -2.800000e+00 -1.200000e+00 8.306057e-01 8.306057e-01 4.153029e-01 -8.306057e-01 -2.700000e+00 -1.200000e+00 8.397928e-01 8.397928e-01 4.198964e-01 -8.397928e-01 -2.600000e+00 -1.200000e+00 8.487420e-01 8.487420e-01 4.243710e-01 -8.487420e-01 -2.500000e+00 -1.200000e+00 8.574435e-01 8.574435e-01 4.287218e-01 -8.574435e-01 -2.400000e+00 -1.200000e+00 8.658878e-01 8.658878e-01 4.329439e-01 -8.658878e-01 -2.300000e+00 -1.200000e+00 8.740655e-01 8.740655e-01 4.370327e-01 -8.740655e-01 -2.200000e+00 -1.200000e+00 8.819675e-01 8.819675e-01 4.409838e-01 -8.819675e-01 -2.100000e+00 -1.200000e+00 8.895852e-01 8.895852e-01 4.447926e-01 -8.895852e-01 -2.000000e+00 -1.200000e+00 8.969098e-01 8.969098e-01 4.484549e-01 -8.969098e-01 -1.900000e+00 -1.200000e+00 9.039330e-01 9.039330e-01 4.519665e-01 -9.039330e-01 -1.800000e+00 -1.200000e+00 9.106470e-01 9.106470e-01 4.553235e-01 -9.106470e-01 -1.700000e+00 -1.200000e+00 9.170438e-01 9.170438e-01 4.585219e-01 -9.170438e-01 -1.600000e+00 -1.200000e+00 9.231163e-01 9.231163e-01 4.615582e-01 -9.231163e-01 -1.500000e+00 -1.200000e+00 9.288574e-01 9.288574e-01 4.644287e-01 -9.288574e-01 -1.400000e+00 -1.200000e+00 9.342605e-01 9.342605e-01 4.671302e-01 -9.342605e-01 -1.300000e+00 -1.200000e+00 9.393191e-01 9.393191e-01 4.696596e-01 -9.393191e-01 -1.200000e+00 -1.200000e+00 9.440275e-01 9.440275e-01 4.720137e-01 -9.440275e-01 -1.100000e+00 -1.200000e+00 9.483800e-01 9.483800e-01 4.741900e-01 -9.483800e-01 -1.000000e+00 -1.200000e+00 9.523716e-01 9.523716e-01 4.761858e-01 -9.523716e-01 -9.000000e-01 -1.200000e+00 9.559975e-01 9.559975e-01 4.779987e-01 -9.559975e-01 -8.000000e-01 -1.200000e+00 9.592534e-01 9.592534e-01 4.796267e-01 -9.592534e-01 -7.000000e-01 -1.200000e+00 9.621355e-01 9.621355e-01 4.810677e-01 -9.621355e-01 -6.000000e-01 -1.200000e+00 9.646403e-01 9.646403e-01 4.823202e-01 -9.646403e-01 -5.000000e-01 -1.200000e+00 9.667648e-01 9.667648e-01 4.833824e-01 -9.667648e-01 -4.000000e-01 -1.200000e+00 9.685066e-01 9.685066e-01 4.842533e-01 -9.685066e-01 -3.000000e-01 -1.200000e+00 9.698634e-01 9.698634e-01 4.849317e-01 -9.698634e-01 -2.000000e-01 -1.200000e+00 9.708338e-01 9.708338e-01 4.854169e-01 -9.708338e-01 -1.000000e-01 -1.200000e+00 9.714165e-01 9.714165e-01 4.857082e-01 -9.714165e-01 0.000000e+00 -1.200000e+00 9.716108e-01 9.716108e-01 4.858054e-01 -9.716108e-01 1.000000e-01 -1.200000e+00 9.714165e-01 9.714165e-01 4.857082e-01 -9.714165e-01 2.000000e-01 -1.200000e+00 9.708338e-01 9.708338e-01 4.854169e-01 -9.708338e-01 3.000000e-01 -1.200000e+00 9.698634e-01 9.698634e-01 4.849317e-01 -9.698634e-01 4.000000e-01 -1.200000e+00 9.685066e-01 9.685066e-01 4.842533e-01 -9.685066e-01 5.000000e-01 -1.200000e+00 9.667648e-01 9.667648e-01 4.833824e-01 -9.667648e-01 6.000000e-01 -1.200000e+00 9.646403e-01 9.646403e-01 4.823202e-01 -9.646403e-01 7.000000e-01 -1.200000e+00 9.621355e-01 9.621355e-01 4.810677e-01 -9.621355e-01 8.000000e-01 -1.200000e+00 9.592534e-01 9.592534e-01 4.796267e-01 -9.592534e-01 9.000000e-01 -1.200000e+00 9.559975e-01 9.559975e-01 4.779987e-01 -9.559975e-01 1.000000e+00 -1.200000e+00 9.523716e-01 9.523716e-01 4.761858e-01 -9.523716e-01 1.100000e+00 -1.200000e+00 9.483800e-01 9.483800e-01 4.741900e-01 -9.483800e-01 1.200000e+00 -1.200000e+00 9.440275e-01 9.440275e-01 4.720137e-01 -9.440275e-01 1.300000e+00 -1.200000e+00 9.393191e-01 9.393191e-01 4.696596e-01 -9.393191e-01 1.400000e+00 -1.200000e+00 9.342605e-01 9.342605e-01 4.671302e-01 -9.342605e-01 1.500000e+00 -1.200000e+00 9.288574e-01 9.288574e-01 4.644287e-01 -9.288574e-01 1.600000e+00 -1.200000e+00 9.231163e-01 9.231163e-01 4.615582e-01 -9.231163e-01 1.700000e+00 -1.200000e+00 9.170438e-01 9.170438e-01 4.585219e-01 -9.170438e-01 1.800000e+00 -1.200000e+00 9.106470e-01 9.106470e-01 4.553235e-01 -9.106470e-01 1.900000e+00 -1.200000e+00 9.039330e-01 9.039330e-01 4.519665e-01 -9.039330e-01 2.000000e+00 -1.200000e+00 8.969098e-01 8.969098e-01 4.484549e-01 -8.969098e-01 2.100000e+00 -1.200000e+00 8.895852e-01 8.895852e-01 4.447926e-01 -8.895852e-01 2.200000e+00 -1.200000e+00 8.819675e-01 8.819675e-01 4.409838e-01 -8.819675e-01 2.300000e+00 -1.200000e+00 8.740655e-01 8.740655e-01 4.370327e-01 -8.740655e-01 2.400000e+00 -1.200000e+00 8.658878e-01 8.658878e-01 4.329439e-01 -8.658878e-01 2.500000e+00 -1.200000e+00 8.574435e-01 8.574435e-01 4.287218e-01 -8.574435e-01 2.600000e+00 -1.200000e+00 8.487420e-01 8.487420e-01 4.243710e-01 -8.487420e-01 2.700000e+00 -1.200000e+00 8.397928e-01 8.397928e-01 4.198964e-01 -8.397928e-01 2.800000e+00 -1.200000e+00 8.306057e-01 8.306057e-01 4.153029e-01 -8.306057e-01 2.900000e+00 -1.200000e+00 8.211906e-01 8.211906e-01 4.105953e-01 -8.211906e-01 3.000000e+00 -1.200000e+00 8.115575e-01 8.115575e-01 4.057788e-01 -8.115575e-01 3.100000e+00 -1.200000e+00 8.017167e-01 8.017167e-01 4.008583e-01 -8.017167e-01 3.200000e+00 -1.200000e+00 7.916784e-01 7.916784e-01 3.958392e-01 -7.916784e-01 3.300000e+00 -1.200000e+00 7.814533e-01 7.814533e-01 3.907266e-01 -7.814533e-01 3.400000e+00 -1.200000e+00 7.710516e-01 7.710516e-01 3.855258e-01 -7.710516e-01 3.500000e+00 -1.200000e+00 7.604842e-01 7.604842e-01 3.802421e-01 -7.604842e-01 3.600000e+00 -1.200000e+00 7.497616e-01 7.497616e-01 3.748808e-01 -7.497616e-01 3.700000e+00 -1.200000e+00 7.388946e-01 7.388946e-01 3.694473e-01 -7.388946e-01 3.800000e+00 -1.200000e+00 7.278939e-01 7.278939e-01 3.639469e-01 -7.278939e-01 3.900000e+00 -1.200000e+00 7.167702e-01 7.167702e-01 3.583851e-01 -7.167702e-01 4.000000e+00 -1.200000e+00 7.055342e-01 7.055342e-01 3.527671e-01 -7.055342e-01 4.100000e+00 -1.200000e+00 6.941966e-01 6.941966e-01 3.470983e-01 -6.941966e-01 4.200000e+00 -1.200000e+00 6.827681e-01 6.827681e-01 3.413841e-01 -6.827681e-01 4.300000e+00 -1.200000e+00 6.712592e-01 6.712592e-01 3.356296e-01 -6.712592e-01 4.400000e+00 -1.200000e+00 6.596802e-01 6.596802e-01 3.298401e-01 -6.596802e-01 4.500000e+00 -1.200000e+00 6.480418e-01 6.480418e-01 3.240209e-01 -6.480418e-01 4.600000e+00 -1.200000e+00 6.363542e-01 6.363542e-01 3.181771e-01 -6.363542e-01 4.700000e+00 -1.200000e+00 6.246274e-01 6.246274e-01 3.123137e-01 -6.246274e-01 4.800000e+00 -1.200000e+00 6.128715e-01 6.128715e-01 3.064357e-01 -6.128715e-01 4.900000e+00 -1.200000e+00 6.010964e-01 6.010964e-01 3.005482e-01 -6.010964e-01 -5.000000e+00 -1.100000e+00 5.920288e-01 5.920288e-01 2.960144e-01 -5.920288e-01 -4.900000e+00 -1.100000e+00 6.038678e-01 6.038678e-01 3.019339e-01 -6.038678e-01 -4.800000e+00 -1.100000e+00 6.156972e-01 6.156972e-01 3.078486e-01 -6.156972e-01 -4.700000e+00 -1.100000e+00 6.275073e-01 6.275073e-01 3.137537e-01 -6.275073e-01 -4.600000e+00 -1.100000e+00 6.392882e-01 6.392882e-01 3.196441e-01 -6.392882e-01 -4.500000e+00 -1.100000e+00 6.510297e-01 6.510297e-01 3.255149e-01 -6.510297e-01 -4.400000e+00 -1.100000e+00 6.627218e-01 6.627218e-01 3.313609e-01 -6.627218e-01 -4.300000e+00 -1.100000e+00 6.743541e-01 6.743541e-01 3.371770e-01 -6.743541e-01 -4.200000e+00 -1.100000e+00 6.859161e-01 6.859161e-01 3.429580e-01 -6.859161e-01 -4.100000e+00 -1.100000e+00 6.973973e-01 6.973973e-01 3.486986e-01 -6.973973e-01 -4.000000e+00 -1.100000e+00 7.087871e-01 7.087871e-01 3.543936e-01 -7.087871e-01 -3.900000e+00 -1.100000e+00 7.200749e-01 7.200749e-01 3.600374e-01 -7.200749e-01 -3.800000e+00 -1.100000e+00 7.312499e-01 7.312499e-01 3.656250e-01 -7.312499e-01 -3.700000e+00 -1.100000e+00 7.423013e-01 7.423013e-01 3.711507e-01 -7.423013e-01 -3.600000e+00 -1.100000e+00 7.532185e-01 7.532185e-01 3.766092e-01 -7.532185e-01 -3.500000e+00 -1.100000e+00 7.639905e-01 7.639905e-01 3.819952e-01 -7.639905e-01 -3.400000e+00 -1.100000e+00 7.746066e-01 7.746066e-01 3.873033e-01 -7.746066e-01 -3.300000e+00 -1.100000e+00 7.850562e-01 7.850562e-01 3.925281e-01 -7.850562e-01 -3.200000e+00 -1.100000e+00 7.953286e-01 7.953286e-01 3.976643e-01 -7.953286e-01 -3.100000e+00 -1.100000e+00 8.054131e-01 8.054131e-01 4.027065e-01 -8.054131e-01 -3.000000e+00 -1.100000e+00 8.152993e-01 8.152993e-01 4.076496e-01 -8.152993e-01 -2.900000e+00 -1.100000e+00 8.249768e-01 8.249768e-01 4.124884e-01 -8.249768e-01 -2.800000e+00 -1.100000e+00 8.344353e-01 8.344353e-01 4.172177e-01 -8.344353e-01 -2.700000e+00 -1.100000e+00 8.436648e-01 8.436648e-01 4.218324e-01 -8.436648e-01 -2.600000e+00 -1.100000e+00 8.526552e-01 8.526552e-01 4.263276e-01 -8.526552e-01 -2.500000e+00 -1.100000e+00 8.613968e-01 8.613968e-01 4.306984e-01 -8.613968e-01 -2.400000e+00 -1.100000e+00 8.698800e-01 8.698800e-01 4.349400e-01 -8.698800e-01 -2.300000e+00 -1.100000e+00 8.780954e-01 8.780954e-01 4.390477e-01 -8.780954e-01 -2.200000e+00 -1.100000e+00 8.860340e-01 8.860340e-01 4.430170e-01 -8.860340e-01 -2.100000e+00 -1.100000e+00 8.936867e-01 8.936867e-01 4.468434e-01 -8.936867e-01 -2.000000e+00 -1.100000e+00 9.010451e-01 9.010451e-01 4.505225e-01 -9.010451e-01 -1.900000e+00 -1.100000e+00 9.081007e-01 9.081007e-01 4.540504e-01 -9.081007e-01 -1.800000e+00 -1.100000e+00 9.148456e-01 9.148456e-01 4.574228e-01 -9.148456e-01 -1.700000e+00 -1.100000e+00 9.212720e-01 9.212720e-01 4.606360e-01 -9.212720e-01 -1.600000e+00 -1.100000e+00 9.273725e-01 9.273725e-01 4.636862e-01 -9.273725e-01 -1.500000e+00 -1.100000e+00 9.331400e-01 9.331400e-01 4.665700e-01 -9.331400e-01 -1.400000e+00 -1.100000e+00 9.385680e-01 9.385680e-01 4.692840e-01 -9.385680e-01 -1.300000e+00 -1.100000e+00 9.436499e-01 9.436499e-01 4.718250e-01 -9.436499e-01 -1.200000e+00 -1.100000e+00 9.483800e-01 9.483800e-01 4.741900e-01 -9.483800e-01 -1.100000e+00 -1.100000e+00 9.527526e-01 9.527526e-01 4.763763e-01 -9.527526e-01 -1.000000e+00 -1.100000e+00 9.567626e-01 9.567626e-01 4.783813e-01 -9.567626e-01 -9.000000e-01 -1.100000e+00 9.604052e-01 9.604052e-01 4.802026e-01 -9.604052e-01 -8.000000e-01 -1.100000e+00 9.636762e-01 9.636762e-01 4.818381e-01 -9.636762e-01 -7.000000e-01 -1.100000e+00 9.665715e-01 9.665715e-01 4.832858e-01 -9.665715e-01 -6.000000e-01 -1.100000e+00 9.690878e-01 9.690878e-01 4.845439e-01 -9.690878e-01 -5.000000e-01 -1.100000e+00 9.712222e-01 9.712222e-01 4.856111e-01 -9.712222e-01 -4.000000e-01 -1.100000e+00 9.729720e-01 9.729720e-01 4.864860e-01 -9.729720e-01 -3.000000e-01 -1.100000e+00 9.743351e-01 9.743351e-01 4.871675e-01 -9.743351e-01 -2.000000e-01 -1.100000e+00 9.753099e-01 9.753099e-01 4.876550e-01 -9.753099e-01 -1.000000e-01 -1.100000e+00 9.758953e-01 9.758953e-01 4.879476e-01 -9.758953e-01 0.000000e+00 -1.100000e+00 9.760905e-01 9.760905e-01 4.880452e-01 -9.760905e-01 1.000000e-01 -1.100000e+00 9.758953e-01 9.758953e-01 4.879476e-01 -9.758953e-01 2.000000e-01 -1.100000e+00 9.753099e-01 9.753099e-01 4.876550e-01 -9.753099e-01 3.000000e-01 -1.100000e+00 9.743351e-01 9.743351e-01 4.871675e-01 -9.743351e-01 4.000000e-01 -1.100000e+00 9.729720e-01 9.729720e-01 4.864860e-01 -9.729720e-01 5.000000e-01 -1.100000e+00 9.712222e-01 9.712222e-01 4.856111e-01 -9.712222e-01 6.000000e-01 -1.100000e+00 9.690878e-01 9.690878e-01 4.845439e-01 -9.690878e-01 7.000000e-01 -1.100000e+00 9.665715e-01 9.665715e-01 4.832858e-01 -9.665715e-01 8.000000e-01 -1.100000e+00 9.636762e-01 9.636762e-01 4.818381e-01 -9.636762e-01 9.000000e-01 -1.100000e+00 9.604052e-01 9.604052e-01 4.802026e-01 -9.604052e-01 1.000000e+00 -1.100000e+00 9.567626e-01 9.567626e-01 4.783813e-01 -9.567626e-01 1.100000e+00 -1.100000e+00 9.527526e-01 9.527526e-01 4.763763e-01 -9.527526e-01 1.200000e+00 -1.100000e+00 9.483800e-01 9.483800e-01 4.741900e-01 -9.483800e-01 1.300000e+00 -1.100000e+00 9.436499e-01 9.436499e-01 4.718250e-01 -9.436499e-01 1.400000e+00 -1.100000e+00 9.385680e-01 9.385680e-01 4.692840e-01 -9.385680e-01 1.500000e+00 -1.100000e+00 9.331400e-01 9.331400e-01 4.665700e-01 -9.331400e-01 1.600000e+00 -1.100000e+00 9.273725e-01 9.273725e-01 4.636862e-01 -9.273725e-01 1.700000e+00 -1.100000e+00 9.212720e-01 9.212720e-01 4.606360e-01 -9.212720e-01 1.800000e+00 -1.100000e+00 9.148456e-01 9.148456e-01 4.574228e-01 -9.148456e-01 1.900000e+00 -1.100000e+00 9.081007e-01 9.081007e-01 4.540504e-01 -9.081007e-01 2.000000e+00 -1.100000e+00 9.010451e-01 9.010451e-01 4.505225e-01 -9.010451e-01 2.100000e+00 -1.100000e+00 8.936867e-01 8.936867e-01 4.468434e-01 -8.936867e-01 2.200000e+00 -1.100000e+00 8.860340e-01 8.860340e-01 4.430170e-01 -8.860340e-01 2.300000e+00 -1.100000e+00 8.780954e-01 8.780954e-01 4.390477e-01 -8.780954e-01 2.400000e+00 -1.100000e+00 8.698800e-01 8.698800e-01 4.349400e-01 -8.698800e-01 2.500000e+00 -1.100000e+00 8.613968e-01 8.613968e-01 4.306984e-01 -8.613968e-01 2.600000e+00 -1.100000e+00 8.526552e-01 8.526552e-01 4.263276e-01 -8.526552e-01 2.700000e+00 -1.100000e+00 8.436648e-01 8.436648e-01 4.218324e-01 -8.436648e-01 2.800000e+00 -1.100000e+00 8.344353e-01 8.344353e-01 4.172177e-01 -8.344353e-01 2.900000e+00 -1.100000e+00 8.249768e-01 8.249768e-01 4.124884e-01 -8.249768e-01 3.000000e+00 -1.100000e+00 8.152993e-01 8.152993e-01 4.076496e-01 -8.152993e-01 3.100000e+00 -1.100000e+00 8.054131e-01 8.054131e-01 4.027065e-01 -8.054131e-01 3.200000e+00 -1.100000e+00 7.953286e-01 7.953286e-01 3.976643e-01 -7.953286e-01 3.300000e+00 -1.100000e+00 7.850562e-01 7.850562e-01 3.925281e-01 -7.850562e-01 3.400000e+00 -1.100000e+00 7.746066e-01 7.746066e-01 3.873033e-01 -7.746066e-01 3.500000e+00 -1.100000e+00 7.639905e-01 7.639905e-01 3.819952e-01 -7.639905e-01 3.600000e+00 -1.100000e+00 7.532185e-01 7.532185e-01 3.766092e-01 -7.532185e-01 3.700000e+00 -1.100000e+00 7.423013e-01 7.423013e-01 3.711507e-01 -7.423013e-01 3.800000e+00 -1.100000e+00 7.312499e-01 7.312499e-01 3.656250e-01 -7.312499e-01 3.900000e+00 -1.100000e+00 7.200749e-01 7.200749e-01 3.600374e-01 -7.200749e-01 4.000000e+00 -1.100000e+00 7.087871e-01 7.087871e-01 3.543936e-01 -7.087871e-01 4.100000e+00 -1.100000e+00 6.973973e-01 6.973973e-01 3.486986e-01 -6.973973e-01 4.200000e+00 -1.100000e+00 6.859161e-01 6.859161e-01 3.429580e-01 -6.859161e-01 4.300000e+00 -1.100000e+00 6.743541e-01 6.743541e-01 3.371770e-01 -6.743541e-01 4.400000e+00 -1.100000e+00 6.627218e-01 6.627218e-01 3.313609e-01 -6.627218e-01 4.500000e+00 -1.100000e+00 6.510297e-01 6.510297e-01 3.255149e-01 -6.510297e-01 4.600000e+00 -1.100000e+00 6.392882e-01 6.392882e-01 3.196441e-01 -6.392882e-01 4.700000e+00 -1.100000e+00 6.275073e-01 6.275073e-01 3.137537e-01 -6.275073e-01 4.800000e+00 -1.100000e+00 6.156972e-01 6.156972e-01 3.078486e-01 -6.156972e-01 4.900000e+00 -1.100000e+00 6.038678e-01 6.038678e-01 3.019339e-01 -6.038678e-01 -5.000000e+00 -1.000000e+00 5.945206e-01 5.945206e-01 2.972603e-01 -5.945206e-01 -4.900000e+00 -1.000000e+00 6.064094e-01 6.064094e-01 3.032047e-01 -6.064094e-01 -4.800000e+00 -1.000000e+00 6.182885e-01 6.182885e-01 3.091443e-01 -6.182885e-01 -4.700000e+00 -1.000000e+00 6.301484e-01 6.301484e-01 3.150742e-01 -6.301484e-01 -4.600000e+00 -1.000000e+00 6.419788e-01 6.419788e-01 3.209894e-01 -6.419788e-01 -4.500000e+00 -1.000000e+00 6.537698e-01 6.537698e-01 3.268849e-01 -6.537698e-01 -4.400000e+00 -1.000000e+00 6.655111e-01 6.655111e-01 3.327555e-01 -6.655111e-01 -4.300000e+00 -1.000000e+00 6.771923e-01 6.771923e-01 3.385961e-01 -6.771923e-01 -4.200000e+00 -1.000000e+00 6.888030e-01 6.888030e-01 3.444015e-01 -6.888030e-01 -4.100000e+00 -1.000000e+00 7.003325e-01 7.003325e-01 3.501663e-01 -7.003325e-01 -4.000000e+00 -1.000000e+00 7.117703e-01 7.117703e-01 3.558851e-01 -7.117703e-01 -3.900000e+00 -1.000000e+00 7.231056e-01 7.231056e-01 3.615528e-01 -7.231056e-01 -3.800000e+00 -1.000000e+00 7.343276e-01 7.343276e-01 3.671638e-01 -7.343276e-01 -3.700000e+00 -1.000000e+00 7.454255e-01 7.454255e-01 3.727128e-01 -7.454255e-01 -3.600000e+00 -1.000000e+00 7.563886e-01 7.563886e-01 3.781943e-01 -7.563886e-01 -3.500000e+00 -1.000000e+00 7.672060e-01 7.672060e-01 3.836030e-01 -7.672060e-01 -3.400000e+00 -1.000000e+00 7.778668e-01 7.778668e-01 3.889334e-01 -7.778668e-01 -3.300000e+00 -1.000000e+00 7.883604e-01 7.883604e-01 3.941802e-01 -7.883604e-01 -3.200000e+00 -1.000000e+00 7.986760e-01 7.986760e-01 3.993380e-01 -7.986760e-01 -3.100000e+00 -1.000000e+00 8.088029e-01 8.088029e-01 4.044015e-01 -8.088029e-01 -3.000000e+00 -1.000000e+00 8.187308e-01 8.187308e-01 4.093654e-01 -8.187308e-01 -2.900000e+00 -1.000000e+00 8.284490e-01 8.284490e-01 4.142245e-01 -8.284490e-01 -2.800000e+00 -1.000000e+00 8.379474e-01 8.379474e-01 4.189737e-01 -8.379474e-01 -2.700000e+00 -1.000000e+00 8.472157e-01 8.472157e-01 4.236078e-01 -8.472157e-01 -2.600000e+00 -1.000000e+00 8.562439e-01 8.562439e-01 4.281220e-01 -8.562439e-01 -2.500000e+00 -1.000000e+00 8.650223e-01 8.650223e-01 4.325112e-01 -8.650223e-01 -2.400000e+00 -1.000000e+00 8.735412e-01 8.735412e-01 4.367706e-01 -8.735412e-01 -2.300000e+00 -1.000000e+00 8.817912e-01 8.817912e-01 4.408956e-01 -8.817912e-01 -2.200000e+00 -1.000000e+00 8.897631e-01 8.897631e-01 4.448816e-01 -8.897631e-01 -2.100000e+00 -1.000000e+00 8.974481e-01 8.974481e-01 4.487240e-01 -8.974481e-01 -2.000000e+00 -1.000000e+00 9.048374e-01 9.048374e-01 4.524187e-01 -9.048374e-01 -1.900000e+00 -1.000000e+00 9.119228e-01 9.119228e-01 4.559614e-01 -9.119228e-01 -1.800000e+00 -1.000000e+00 9.186960e-01 9.186960e-01 4.593480e-01 -9.186960e-01 -1.700000e+00 -1.000000e+00 9.251494e-01 9.251494e-01 4.625747e-01 -9.251494e-01 -1.600000e+00 -1.000000e+00 9.312756e-01 9.312756e-01 4.656378e-01 -9.312756e-01 -1.500000e+00 -1.000000e+00 9.370674e-01 9.370674e-01 4.685337e-01 -9.370674e-01 -1.400000e+00 -1.000000e+00 9.425182e-01 9.425182e-01 4.712591e-01 -9.425182e-01 -1.300000e+00 -1.000000e+00 9.476216e-01 9.476216e-01 4.738108e-01 -9.476216e-01 -1.200000e+00 -1.000000e+00 9.523716e-01 9.523716e-01 4.761858e-01 -9.523716e-01 -1.100000e+00 -1.000000e+00 9.567626e-01 9.567626e-01 4.783813e-01 -9.567626e-01 -1.000000e+00 -1.000000e+00 9.607894e-01 9.607894e-01 4.803947e-01 -9.607894e-01 -9.000000e-01 -1.000000e+00 9.644474e-01 9.644474e-01 4.822237e-01 -9.644474e-01 -8.000000e-01 -1.000000e+00 9.677321e-01 9.677321e-01 4.838660e-01 -9.677321e-01 -7.000000e-01 -1.000000e+00 9.706396e-01 9.706396e-01 4.853198e-01 -9.706396e-01 -6.000000e-01 -1.000000e+00 9.731666e-01 9.731666e-01 4.865833e-01 -9.731666e-01 -5.000000e-01 -1.000000e+00 9.753099e-01 9.753099e-01 4.876550e-01 -9.753099e-01 -4.000000e-01 -1.000000e+00 9.770671e-01 9.770671e-01 4.885335e-01 -9.770671e-01 -3.000000e-01 -1.000000e+00 9.784359e-01 9.784359e-01 4.892179e-01 -9.784359e-01 -2.000000e-01 -1.000000e+00 9.794148e-01 9.794148e-01 4.897074e-01 -9.794148e-01 -1.000000e-01 -1.000000e+00 9.800026e-01 9.800026e-01 4.900013e-01 -9.800026e-01 0.000000e+00 -1.000000e+00 9.801987e-01 9.801987e-01 4.900993e-01 -9.801987e-01 1.000000e-01 -1.000000e+00 9.800026e-01 9.800026e-01 4.900013e-01 -9.800026e-01 2.000000e-01 -1.000000e+00 9.794148e-01 9.794148e-01 4.897074e-01 -9.794148e-01 3.000000e-01 -1.000000e+00 9.784359e-01 9.784359e-01 4.892179e-01 -9.784359e-01 4.000000e-01 -1.000000e+00 9.770671e-01 9.770671e-01 4.885335e-01 -9.770671e-01 5.000000e-01 -1.000000e+00 9.753099e-01 9.753099e-01 4.876550e-01 -9.753099e-01 6.000000e-01 -1.000000e+00 9.731666e-01 9.731666e-01 4.865833e-01 -9.731666e-01 7.000000e-01 -1.000000e+00 9.706396e-01 9.706396e-01 4.853198e-01 -9.706396e-01 8.000000e-01 -1.000000e+00 9.677321e-01 9.677321e-01 4.838660e-01 -9.677321e-01 9.000000e-01 -1.000000e+00 9.644474e-01 9.644474e-01 4.822237e-01 -9.644474e-01 1.000000e+00 -1.000000e+00 9.607894e-01 9.607894e-01 4.803947e-01 -9.607894e-01 1.100000e+00 -1.000000e+00 9.567626e-01 9.567626e-01 4.783813e-01 -9.567626e-01 1.200000e+00 -1.000000e+00 9.523716e-01 9.523716e-01 4.761858e-01 -9.523716e-01 1.300000e+00 -1.000000e+00 9.476216e-01 9.476216e-01 4.738108e-01 -9.476216e-01 1.400000e+00 -1.000000e+00 9.425182e-01 9.425182e-01 4.712591e-01 -9.425182e-01 1.500000e+00 -1.000000e+00 9.370674e-01 9.370674e-01 4.685337e-01 -9.370674e-01 1.600000e+00 -1.000000e+00 9.312756e-01 9.312756e-01 4.656378e-01 -9.312756e-01 1.700000e+00 -1.000000e+00 9.251494e-01 9.251494e-01 4.625747e-01 -9.251494e-01 1.800000e+00 -1.000000e+00 9.186960e-01 9.186960e-01 4.593480e-01 -9.186960e-01 1.900000e+00 -1.000000e+00 9.119228e-01 9.119228e-01 4.559614e-01 -9.119228e-01 2.000000e+00 -1.000000e+00 9.048374e-01 9.048374e-01 4.524187e-01 -9.048374e-01 2.100000e+00 -1.000000e+00 8.974481e-01 8.974481e-01 4.487240e-01 -8.974481e-01 2.200000e+00 -1.000000e+00 8.897631e-01 8.897631e-01 4.448816e-01 -8.897631e-01 2.300000e+00 -1.000000e+00 8.817912e-01 8.817912e-01 4.408956e-01 -8.817912e-01 2.400000e+00 -1.000000e+00 8.735412e-01 8.735412e-01 4.367706e-01 -8.735412e-01 2.500000e+00 -1.000000e+00 8.650223e-01 8.650223e-01 4.325112e-01 -8.650223e-01 2.600000e+00 -1.000000e+00 8.562439e-01 8.562439e-01 4.281220e-01 -8.562439e-01 2.700000e+00 -1.000000e+00 8.472157e-01 8.472157e-01 4.236078e-01 -8.472157e-01 2.800000e+00 -1.000000e+00 8.379474e-01 8.379474e-01 4.189737e-01 -8.379474e-01 2.900000e+00 -1.000000e+00 8.284490e-01 8.284490e-01 4.142245e-01 -8.284490e-01 3.000000e+00 -1.000000e+00 8.187308e-01 8.187308e-01 4.093654e-01 -8.187308e-01 3.100000e+00 -1.000000e+00 8.088029e-01 8.088029e-01 4.044015e-01 -8.088029e-01 3.200000e+00 -1.000000e+00 7.986760e-01 7.986760e-01 3.993380e-01 -7.986760e-01 3.300000e+00 -1.000000e+00 7.883604e-01 7.883604e-01 3.941802e-01 -7.883604e-01 3.400000e+00 -1.000000e+00 7.778668e-01 7.778668e-01 3.889334e-01 -7.778668e-01 3.500000e+00 -1.000000e+00 7.672060e-01 7.672060e-01 3.836030e-01 -7.672060e-01 3.600000e+00 -1.000000e+00 7.563886e-01 7.563886e-01 3.781943e-01 -7.563886e-01 3.700000e+00 -1.000000e+00 7.454255e-01 7.454255e-01 3.727128e-01 -7.454255e-01 3.800000e+00 -1.000000e+00 7.343276e-01 7.343276e-01 3.671638e-01 -7.343276e-01 3.900000e+00 -1.000000e+00 7.231056e-01 7.231056e-01 3.615528e-01 -7.231056e-01 4.000000e+00 -1.000000e+00 7.117703e-01 7.117703e-01 3.558851e-01 -7.117703e-01 4.100000e+00 -1.000000e+00 7.003325e-01 7.003325e-01 3.501663e-01 -7.003325e-01 4.200000e+00 -1.000000e+00 6.888030e-01 6.888030e-01 3.444015e-01 -6.888030e-01 4.300000e+00 -1.000000e+00 6.771923e-01 6.771923e-01 3.385961e-01 -6.771923e-01 4.400000e+00 -1.000000e+00 6.655111e-01 6.655111e-01 3.327555e-01 -6.655111e-01 4.500000e+00 -1.000000e+00 6.537698e-01 6.537698e-01 3.268849e-01 -6.537698e-01 4.600000e+00 -1.000000e+00 6.419788e-01 6.419788e-01 3.209894e-01 -6.419788e-01 4.700000e+00 -1.000000e+00 6.301484e-01 6.301484e-01 3.150742e-01 -6.301484e-01 4.800000e+00 -1.000000e+00 6.182885e-01 6.182885e-01 3.091443e-01 -6.182885e-01 4.900000e+00 -1.000000e+00 6.064094e-01 6.064094e-01 3.032047e-01 -6.064094e-01 -5.000000e+00 -9.000000e-01 5.967840e-01 5.967840e-01 2.983920e-01 -5.967840e-01 -4.900000e+00 -9.000000e-01 6.087181e-01 6.087181e-01 3.043590e-01 -6.087181e-01 -4.800000e+00 -9.000000e-01 6.206425e-01 6.206425e-01 3.103212e-01 -6.206425e-01 -4.700000e+00 -9.000000e-01 6.325475e-01 6.325475e-01 3.162737e-01 -6.325475e-01 -4.600000e+00 -9.000000e-01 6.444230e-01 6.444230e-01 3.222115e-01 -6.444230e-01 -4.500000e+00 -9.000000e-01 6.562589e-01 6.562589e-01 3.281294e-01 -6.562589e-01 -4.400000e+00 -9.000000e-01 6.680448e-01 6.680448e-01 3.340224e-01 -6.680448e-01 -4.300000e+00 -9.000000e-01 6.797705e-01 6.797705e-01 3.398853e-01 -6.797705e-01 -4.200000e+00 -9.000000e-01 6.914254e-01 6.914254e-01 3.457127e-01 -6.914254e-01 -4.100000e+00 -9.000000e-01 7.029989e-01 7.029989e-01 3.514994e-01 -7.029989e-01 -4.000000e+00 -9.000000e-01 7.144802e-01 7.144802e-01 3.572401e-01 -7.144802e-01 -3.900000e+00 -9.000000e-01 7.258586e-01 7.258586e-01 3.629293e-01 -7.258586e-01 -3.800000e+00 -9.000000e-01 7.371234e-01 7.371234e-01 3.685617e-01 -7.371234e-01 -3.700000e+00 -9.000000e-01 7.482635e-01 7.482635e-01 3.741318e-01 -7.482635e-01 -3.600000e+00 -9.000000e-01 7.592683e-01 7.592683e-01 3.796342e-01 -7.592683e-01 -3.500000e+00 -9.000000e-01 7.701269e-01 7.701269e-01 3.850634e-01 -7.701269e-01 -3.400000e+00 -9.000000e-01 7.808283e-01 7.808283e-01 3.904141e-01 -7.808283e-01 -3.300000e+00 -9.000000e-01 7.913619e-01 7.913619e-01 3.956809e-01 -7.913619e-01 -3.200000e+00 -9.000000e-01 8.017167e-01 8.017167e-01 4.008583e-01 -8.017167e-01 -3.100000e+00 -9.000000e-01 8.118822e-01 8.118822e-01 4.059411e-01 -8.118822e-01 -3.000000e+00 -9.000000e-01 8.218479e-01 8.218479e-01 4.109239e-01 -8.218479e-01 -2.900000e+00 -9.000000e-01 8.316031e-01 8.316031e-01 4.158015e-01 -8.316031e-01 -2.800000e+00 -9.000000e-01 8.411376e-01 8.411376e-01 4.205688e-01 -8.411376e-01 -2.700000e+00 -9.000000e-01 8.504412e-01 8.504412e-01 4.252206e-01 -8.504412e-01 -2.600000e+00 -9.000000e-01 8.595038e-01 8.595038e-01 4.297519e-01 -8.595038e-01 -2.500000e+00 -9.000000e-01 8.683156e-01 8.683156e-01 4.341578e-01 -8.683156e-01 -2.400000e+00 -9.000000e-01 8.768669e-01 8.768669e-01 4.384335e-01 -8.768669e-01 -2.300000e+00 -9.000000e-01 8.851484e-01 8.851484e-01 4.425742e-01 -8.851484e-01 -2.200000e+00 -9.000000e-01 8.931507e-01 8.931507e-01 4.465753e-01 -8.931507e-01 -2.100000e+00 -9.000000e-01 9.008649e-01 9.008649e-01 4.504324e-01 -9.008649e-01 -2.000000e+00 -9.000000e-01 9.082823e-01 9.082823e-01 4.541412e-01 -9.082823e-01 -1.900000e+00 -9.000000e-01 9.153947e-01 9.153947e-01 4.576973e-01 -9.153947e-01 -1.800000e+00 -9.000000e-01 9.221937e-01 9.221937e-01 4.610969e-01 -9.221937e-01 -1.700000e+00 -9.000000e-01 9.286717e-01 9.286717e-01 4.643359e-01 -9.286717e-01 -1.600000e+00 -9.000000e-01 9.348212e-01 9.348212e-01 4.674106e-01 -9.348212e-01 -1.500000e+00 -9.000000e-01 9.406351e-01 9.406351e-01 4.703175e-01 -9.406351e-01 -1.400000e+00 -9.000000e-01 9.461066e-01 9.461066e-01 4.730533e-01 -9.461066e-01 -1.300000e+00 -9.000000e-01 9.512295e-01 9.512295e-01 4.756147e-01 -9.512295e-01 -1.200000e+00 -9.000000e-01 9.559975e-01 9.559975e-01 4.779987e-01 -9.559975e-01 -1.100000e+00 -9.000000e-01 9.604052e-01 9.604052e-01 4.802026e-01 -9.604052e-01 -1.000000e+00 -9.000000e-01 9.644474e-01 9.644474e-01 4.822237e-01 -9.644474e-01 -9.000000e-01 -9.000000e-01 9.681193e-01 9.681193e-01 4.840596e-01 -9.681193e-01 -8.000000e-01 -9.000000e-01 9.714165e-01 9.714165e-01 4.857082e-01 -9.714165e-01 -7.000000e-01 -9.000000e-01 9.743351e-01 9.743351e-01 4.871675e-01 -9.743351e-01 -6.000000e-01 -9.000000e-01 9.768717e-01 9.768717e-01 4.884358e-01 -9.768717e-01 -5.000000e-01 -9.000000e-01 9.790232e-01 9.790232e-01 4.895116e-01 -9.790232e-01 -4.000000e-01 -9.000000e-01 9.807870e-01 9.807870e-01 4.903935e-01 -9.807870e-01 -3.000000e-01 -9.000000e-01 9.821610e-01 9.821610e-01 4.910805e-01 -9.821610e-01 -2.000000e-01 -9.000000e-01 9.831437e-01 9.831437e-01 4.915718e-01 -9.831437e-01 -1.000000e-01 -9.000000e-01 9.837338e-01 9.837338e-01 4.918669e-01 -9.837338e-01 0.000000e+00 -9.000000e-01 9.839305e-01 9.839305e-01 4.919653e-01 -9.839305e-01 1.000000e-01 -9.000000e-01 9.837338e-01 9.837338e-01 4.918669e-01 -9.837338e-01 2.000000e-01 -9.000000e-01 9.831437e-01 9.831437e-01 4.915718e-01 -9.831437e-01 3.000000e-01 -9.000000e-01 9.821610e-01 9.821610e-01 4.910805e-01 -9.821610e-01 4.000000e-01 -9.000000e-01 9.807870e-01 9.807870e-01 4.903935e-01 -9.807870e-01 5.000000e-01 -9.000000e-01 9.790232e-01 9.790232e-01 4.895116e-01 -9.790232e-01 6.000000e-01 -9.000000e-01 9.768717e-01 9.768717e-01 4.884358e-01 -9.768717e-01 7.000000e-01 -9.000000e-01 9.743351e-01 9.743351e-01 4.871675e-01 -9.743351e-01 8.000000e-01 -9.000000e-01 9.714165e-01 9.714165e-01 4.857082e-01 -9.714165e-01 9.000000e-01 -9.000000e-01 9.681193e-01 9.681193e-01 4.840596e-01 -9.681193e-01 1.000000e+00 -9.000000e-01 9.644474e-01 9.644474e-01 4.822237e-01 -9.644474e-01 1.100000e+00 -9.000000e-01 9.604052e-01 9.604052e-01 4.802026e-01 -9.604052e-01 1.200000e+00 -9.000000e-01 9.559975e-01 9.559975e-01 4.779987e-01 -9.559975e-01 1.300000e+00 -9.000000e-01 9.512295e-01 9.512295e-01 4.756147e-01 -9.512295e-01 1.400000e+00 -9.000000e-01 9.461066e-01 9.461066e-01 4.730533e-01 -9.461066e-01 1.500000e+00 -9.000000e-01 9.406351e-01 9.406351e-01 4.703175e-01 -9.406351e-01 1.600000e+00 -9.000000e-01 9.348212e-01 9.348212e-01 4.674106e-01 -9.348212e-01 1.700000e+00 -9.000000e-01 9.286717e-01 9.286717e-01 4.643359e-01 -9.286717e-01 1.800000e+00 -9.000000e-01 9.221937e-01 9.221937e-01 4.610969e-01 -9.221937e-01 1.900000e+00 -9.000000e-01 9.153947e-01 9.153947e-01 4.576973e-01 -9.153947e-01 2.000000e+00 -9.000000e-01 9.082823e-01 9.082823e-01 4.541412e-01 -9.082823e-01 2.100000e+00 -9.000000e-01 9.008649e-01 9.008649e-01 4.504324e-01 -9.008649e-01 2.200000e+00 -9.000000e-01 8.931507e-01 8.931507e-01 4.465753e-01 -8.931507e-01 2.300000e+00 -9.000000e-01 8.851484e-01 8.851484e-01 4.425742e-01 -8.851484e-01 2.400000e+00 -9.000000e-01 8.768669e-01 8.768669e-01 4.384335e-01 -8.768669e-01 2.500000e+00 -9.000000e-01 8.683156e-01 8.683156e-01 4.341578e-01 -8.683156e-01 2.600000e+00 -9.000000e-01 8.595038e-01 8.595038e-01 4.297519e-01 -8.595038e-01 2.700000e+00 -9.000000e-01 8.504412e-01 8.504412e-01 4.252206e-01 -8.504412e-01 2.800000e+00 -9.000000e-01 8.411376e-01 8.411376e-01 4.205688e-01 -8.411376e-01 2.900000e+00 -9.000000e-01 8.316031e-01 8.316031e-01 4.158015e-01 -8.316031e-01 3.000000e+00 -9.000000e-01 8.218479e-01 8.218479e-01 4.109239e-01 -8.218479e-01 3.100000e+00 -9.000000e-01 8.118822e-01 8.118822e-01 4.059411e-01 -8.118822e-01 3.200000e+00 -9.000000e-01 8.017167e-01 8.017167e-01 4.008583e-01 -8.017167e-01 3.300000e+00 -9.000000e-01 7.913619e-01 7.913619e-01 3.956809e-01 -7.913619e-01 3.400000e+00 -9.000000e-01 7.808283e-01 7.808283e-01 3.904141e-01 -7.808283e-01 3.500000e+00 -9.000000e-01 7.701269e-01 7.701269e-01 3.850634e-01 -7.701269e-01 3.600000e+00 -9.000000e-01 7.592683e-01 7.592683e-01 3.796342e-01 -7.592683e-01 3.700000e+00 -9.000000e-01 7.482635e-01 7.482635e-01 3.741318e-01 -7.482635e-01 3.800000e+00 -9.000000e-01 7.371234e-01 7.371234e-01 3.685617e-01 -7.371234e-01 3.900000e+00 -9.000000e-01 7.258586e-01 7.258586e-01 3.629293e-01 -7.258586e-01 4.000000e+00 -9.000000e-01 7.144802e-01 7.144802e-01 3.572401e-01 -7.144802e-01 4.100000e+00 -9.000000e-01 7.029989e-01 7.029989e-01 3.514994e-01 -7.029989e-01 4.200000e+00 -9.000000e-01 6.914254e-01 6.914254e-01 3.457127e-01 -6.914254e-01 4.300000e+00 -9.000000e-01 6.797705e-01 6.797705e-01 3.398853e-01 -6.797705e-01 4.400000e+00 -9.000000e-01 6.680448e-01 6.680448e-01 3.340224e-01 -6.680448e-01 4.500000e+00 -9.000000e-01 6.562589e-01 6.562589e-01 3.281294e-01 -6.562589e-01 4.600000e+00 -9.000000e-01 6.444230e-01 6.444230e-01 3.222115e-01 -6.444230e-01 4.700000e+00 -9.000000e-01 6.325475e-01 6.325475e-01 3.162737e-01 -6.325475e-01 4.800000e+00 -9.000000e-01 6.206425e-01 6.206425e-01 3.103212e-01 -6.206425e-01 4.900000e+00 -9.000000e-01 6.087181e-01 6.087181e-01 3.043590e-01 -6.087181e-01 -5.000000e+00 -8.000000e-01 5.988166e-01 5.988166e-01 2.994083e-01 -5.988166e-01 -4.900000e+00 -8.000000e-01 6.107913e-01 6.107913e-01 3.053956e-01 -6.107913e-01 -4.800000e+00 -8.000000e-01 6.227563e-01 6.227563e-01 3.113782e-01 -6.227563e-01 -4.700000e+00 -8.000000e-01 6.347018e-01 6.347018e-01 3.173509e-01 -6.347018e-01 -4.600000e+00 -8.000000e-01 6.466178e-01 6.466178e-01 3.233089e-01 -6.466178e-01 -4.500000e+00 -8.000000e-01 6.584939e-01 6.584939e-01 3.292470e-01 -6.584939e-01 -4.400000e+00 -8.000000e-01 6.703200e-01 6.703200e-01 3.351600e-01 -6.703200e-01 -4.300000e+00 -8.000000e-01 6.820857e-01 6.820857e-01 3.410428e-01 -6.820857e-01 -4.200000e+00 -8.000000e-01 6.937802e-01 6.937802e-01 3.468901e-01 -6.937802e-01 -4.100000e+00 -8.000000e-01 7.053931e-01 7.053931e-01 3.526966e-01 -7.053931e-01 -4.000000e+00 -8.000000e-01 7.169135e-01 7.169135e-01 3.584568e-01 -7.169135e-01 -3.900000e+00 -8.000000e-01 7.283307e-01 7.283307e-01 3.641654e-01 -7.283307e-01 -3.800000e+00 -8.000000e-01 7.396339e-01 7.396339e-01 3.698169e-01 -7.396339e-01 -3.700000e+00 -8.000000e-01 7.508120e-01 7.508120e-01 3.754060e-01 -7.508120e-01 -3.600000e+00 -8.000000e-01 7.618543e-01 7.618543e-01 3.809271e-01 -7.618543e-01 -3.500000e+00 -8.000000e-01 7.727498e-01 7.727498e-01 3.863749e-01 -7.727498e-01 -3.400000e+00 -8.000000e-01 7.834876e-01 7.834876e-01 3.917438e-01 -7.834876e-01 -3.300000e+00 -8.000000e-01 7.940571e-01 7.940571e-01 3.970285e-01 -7.940571e-01 -3.200000e+00 -8.000000e-01 8.044472e-01 8.044472e-01 4.022236e-01 -8.044472e-01 -3.100000e+00 -8.000000e-01 8.146473e-01 8.146473e-01 4.073237e-01 -8.146473e-01 -3.000000e+00 -8.000000e-01 8.246469e-01 8.246469e-01 4.123234e-01 -8.246469e-01 -2.900000e+00 -8.000000e-01 8.344353e-01 8.344353e-01 4.172177e-01 -8.344353e-01 -2.800000e+00 -8.000000e-01 8.440024e-01 8.440024e-01 4.220012e-01 -8.440024e-01 -2.700000e+00 -8.000000e-01 8.533376e-01 8.533376e-01 4.266688e-01 -8.533376e-01 -2.600000e+00 -8.000000e-01 8.624311e-01 8.624311e-01 4.312156e-01 -8.624311e-01 -2.500000e+00 -8.000000e-01 8.712729e-01 8.712729e-01 4.356365e-01 -8.712729e-01 -2.400000e+00 -8.000000e-01 8.798534e-01 8.798534e-01 4.399267e-01 -8.798534e-01 -2.300000e+00 -8.000000e-01 8.881630e-01 8.881630e-01 4.440815e-01 -8.881630e-01 -2.200000e+00 -8.000000e-01 8.961926e-01 8.961926e-01 4.480963e-01 -8.961926e-01 -2.100000e+00 -8.000000e-01 9.039330e-01 9.039330e-01 4.519665e-01 -9.039330e-01 -2.000000e+00 -8.000000e-01 9.113758e-01 9.113758e-01 4.556879e-01 -9.113758e-01 -1.900000e+00 -8.000000e-01 9.185123e-01 9.185123e-01 4.592561e-01 -9.185123e-01 -1.800000e+00 -8.000000e-01 9.253345e-01 9.253345e-01 4.626673e-01 -9.253345e-01 -1.700000e+00 -8.000000e-01 9.318345e-01 9.318345e-01 4.659173e-01 -9.318345e-01 -1.600000e+00 -8.000000e-01 9.380050e-01 9.380050e-01 4.690025e-01 -9.380050e-01 -1.500000e+00 -8.000000e-01 9.438387e-01 9.438387e-01 4.719194e-01 -9.438387e-01 -1.400000e+00 -8.000000e-01 9.493288e-01 9.493288e-01 4.746644e-01 -9.493288e-01 -1.300000e+00 -8.000000e-01 9.544691e-01 9.544691e-01 4.772345e-01 -9.544691e-01 -1.200000e+00 -8.000000e-01 9.592534e-01 9.592534e-01 4.796267e-01 -9.592534e-01 -1.100000e+00 -8.000000e-01 9.636762e-01 9.636762e-01 4.818381e-01 -9.636762e-01 -1.000000e+00 -8.000000e-01 9.677321e-01 9.677321e-01 4.838660e-01 -9.677321e-01 -9.000000e-01 -8.000000e-01 9.714165e-01 9.714165e-01 4.857082e-01 -9.714165e-01 -8.000000e-01 -8.000000e-01 9.747249e-01 9.747249e-01 4.873624e-01 -9.747249e-01 -7.000000e-01 -8.000000e-01 9.776534e-01 9.776534e-01 4.888267e-01 -9.776534e-01 -6.000000e-01 -8.000000e-01 9.801987e-01 9.801987e-01 4.900993e-01 -9.801987e-01 -5.000000e-01 -8.000000e-01 9.823575e-01 9.823575e-01 4.911788e-01 -9.823575e-01 -4.000000e-01 -8.000000e-01 9.841273e-01 9.841273e-01 4.920637e-01 -9.841273e-01 -3.000000e-01 -8.000000e-01 9.855061e-01 9.855061e-01 4.927530e-01 -9.855061e-01 -2.000000e-01 -8.000000e-01 9.864920e-01 9.864920e-01 4.932460e-01 -9.864920e-01 -1.000000e-01 -8.000000e-01 9.870842e-01 9.870842e-01 4.935421e-01 -9.870842e-01 0.000000e+00 -8.000000e-01 9.872816e-01 9.872816e-01 4.936408e-01 -9.872816e-01 1.000000e-01 -8.000000e-01 9.870842e-01 9.870842e-01 4.935421e-01 -9.870842e-01 2.000000e-01 -8.000000e-01 9.864920e-01 9.864920e-01 4.932460e-01 -9.864920e-01 3.000000e-01 -8.000000e-01 9.855061e-01 9.855061e-01 4.927530e-01 -9.855061e-01 4.000000e-01 -8.000000e-01 9.841273e-01 9.841273e-01 4.920637e-01 -9.841273e-01 5.000000e-01 -8.000000e-01 9.823575e-01 9.823575e-01 4.911788e-01 -9.823575e-01 6.000000e-01 -8.000000e-01 9.801987e-01 9.801987e-01 4.900993e-01 -9.801987e-01 7.000000e-01 -8.000000e-01 9.776534e-01 9.776534e-01 4.888267e-01 -9.776534e-01 8.000000e-01 -8.000000e-01 9.747249e-01 9.747249e-01 4.873624e-01 -9.747249e-01 9.000000e-01 -8.000000e-01 9.714165e-01 9.714165e-01 4.857082e-01 -9.714165e-01 1.000000e+00 -8.000000e-01 9.677321e-01 9.677321e-01 4.838660e-01 -9.677321e-01 1.100000e+00 -8.000000e-01 9.636762e-01 9.636762e-01 4.818381e-01 -9.636762e-01 1.200000e+00 -8.000000e-01 9.592534e-01 9.592534e-01 4.796267e-01 -9.592534e-01 1.300000e+00 -8.000000e-01 9.544691e-01 9.544691e-01 4.772345e-01 -9.544691e-01 1.400000e+00 -8.000000e-01 9.493288e-01 9.493288e-01 4.746644e-01 -9.493288e-01 1.500000e+00 -8.000000e-01 9.438387e-01 9.438387e-01 4.719194e-01 -9.438387e-01 1.600000e+00 -8.000000e-01 9.380050e-01 9.380050e-01 4.690025e-01 -9.380050e-01 1.700000e+00 -8.000000e-01 9.318345e-01 9.318345e-01 4.659173e-01 -9.318345e-01 1.800000e+00 -8.000000e-01 9.253345e-01 9.253345e-01 4.626673e-01 -9.253345e-01 1.900000e+00 -8.000000e-01 9.185123e-01 9.185123e-01 4.592561e-01 -9.185123e-01 2.000000e+00 -8.000000e-01 9.113758e-01 9.113758e-01 4.556879e-01 -9.113758e-01 2.100000e+00 -8.000000e-01 9.039330e-01 9.039330e-01 4.519665e-01 -9.039330e-01 2.200000e+00 -8.000000e-01 8.961926e-01 8.961926e-01 4.480963e-01 -8.961926e-01 2.300000e+00 -8.000000e-01 8.881630e-01 8.881630e-01 4.440815e-01 -8.881630e-01 2.400000e+00 -8.000000e-01 8.798534e-01 8.798534e-01 4.399267e-01 -8.798534e-01 2.500000e+00 -8.000000e-01 8.712729e-01 8.712729e-01 4.356365e-01 -8.712729e-01 2.600000e+00 -8.000000e-01 8.624311e-01 8.624311e-01 4.312156e-01 -8.624311e-01 2.700000e+00 -8.000000e-01 8.533376e-01 8.533376e-01 4.266688e-01 -8.533376e-01 2.800000e+00 -8.000000e-01 8.440024e-01 8.440024e-01 4.220012e-01 -8.440024e-01 2.900000e+00 -8.000000e-01 8.344353e-01 8.344353e-01 4.172177e-01 -8.344353e-01 3.000000e+00 -8.000000e-01 8.246469e-01 8.246469e-01 4.123234e-01 -8.246469e-01 3.100000e+00 -8.000000e-01 8.146473e-01 8.146473e-01 4.073237e-01 -8.146473e-01 3.200000e+00 -8.000000e-01 8.044472e-01 8.044472e-01 4.022236e-01 -8.044472e-01 3.300000e+00 -8.000000e-01 7.940571e-01 7.940571e-01 3.970285e-01 -7.940571e-01 3.400000e+00 -8.000000e-01 7.834876e-01 7.834876e-01 3.917438e-01 -7.834876e-01 3.500000e+00 -8.000000e-01 7.727498e-01 7.727498e-01 3.863749e-01 -7.727498e-01 3.600000e+00 -8.000000e-01 7.618543e-01 7.618543e-01 3.809271e-01 -7.618543e-01 3.700000e+00 -8.000000e-01 7.508120e-01 7.508120e-01 3.754060e-01 -7.508120e-01 3.800000e+00 -8.000000e-01 7.396339e-01 7.396339e-01 3.698169e-01 -7.396339e-01 3.900000e+00 -8.000000e-01 7.283307e-01 7.283307e-01 3.641654e-01 -7.283307e-01 4.000000e+00 -8.000000e-01 7.169135e-01 7.169135e-01 3.584568e-01 -7.169135e-01 4.100000e+00 -8.000000e-01 7.053931e-01 7.053931e-01 3.526966e-01 -7.053931e-01 4.200000e+00 -8.000000e-01 6.937802e-01 6.937802e-01 3.468901e-01 -6.937802e-01 4.300000e+00 -8.000000e-01 6.820857e-01 6.820857e-01 3.410428e-01 -6.820857e-01 4.400000e+00 -8.000000e-01 6.703200e-01 6.703200e-01 3.351600e-01 -6.703200e-01 4.500000e+00 -8.000000e-01 6.584939e-01 6.584939e-01 3.292470e-01 -6.584939e-01 4.600000e+00 -8.000000e-01 6.466178e-01 6.466178e-01 3.233089e-01 -6.466178e-01 4.700000e+00 -8.000000e-01 6.347018e-01 6.347018e-01 3.173509e-01 -6.347018e-01 4.800000e+00 -8.000000e-01 6.227563e-01 6.227563e-01 3.113782e-01 -6.227563e-01 4.900000e+00 -8.000000e-01 6.107913e-01 6.107913e-01 3.053956e-01 -6.107913e-01 -5.000000e+00 -7.000000e-01 6.006157e-01 6.006157e-01 3.003078e-01 -6.006157e-01 -4.900000e+00 -7.000000e-01 6.126264e-01 6.126264e-01 3.063132e-01 -6.126264e-01 -4.800000e+00 -7.000000e-01 6.246274e-01 6.246274e-01 3.123137e-01 -6.246274e-01 -4.700000e+00 -7.000000e-01 6.366088e-01 6.366088e-01 3.183044e-01 -6.366088e-01 -4.600000e+00 -7.000000e-01 6.485605e-01 6.485605e-01 3.242803e-01 -6.485605e-01 -4.500000e+00 -7.000000e-01 6.604724e-01 6.604724e-01 3.302362e-01 -6.604724e-01 -4.400000e+00 -7.000000e-01 6.723340e-01 6.723340e-01 3.361670e-01 -6.723340e-01 -4.300000e+00 -7.000000e-01 6.841350e-01 6.841350e-01 3.420675e-01 -6.841350e-01 -4.200000e+00 -7.000000e-01 6.958647e-01 6.958647e-01 3.479324e-01 -6.958647e-01 -4.100000e+00 -7.000000e-01 7.075125e-01 7.075125e-01 3.537562e-01 -7.075125e-01 -4.000000e+00 -7.000000e-01 7.190675e-01 7.190675e-01 3.595338e-01 -7.190675e-01 -3.900000e+00 -7.000000e-01 7.305190e-01 7.305190e-01 3.652595e-01 -7.305190e-01 -3.800000e+00 -7.000000e-01 7.418561e-01 7.418561e-01 3.709280e-01 -7.418561e-01 -3.700000e+00 -7.000000e-01 7.530678e-01 7.530678e-01 3.765339e-01 -7.530678e-01 -3.600000e+00 -7.000000e-01 7.641433e-01 7.641433e-01 3.820716e-01 -7.641433e-01 -3.500000e+00 -7.000000e-01 7.750715e-01 7.750715e-01 3.875358e-01 -7.750715e-01 -3.400000e+00 -7.000000e-01 7.858416e-01 7.858416e-01 3.929208e-01 -7.858416e-01 -3.300000e+00 -7.000000e-01 7.964428e-01 7.964428e-01 3.982214e-01 -7.964428e-01 -3.200000e+00 -7.000000e-01 8.068641e-01 8.068641e-01 4.034321e-01 -8.068641e-01 -3.100000e+00 -7.000000e-01 8.170949e-01 8.170949e-01 4.085475e-01 -8.170949e-01 -3.000000e+00 -7.000000e-01 8.271245e-01 8.271245e-01 4.135623e-01 -8.271245e-01 -2.900000e+00 -7.000000e-01 8.369424e-01 8.369424e-01 4.184712e-01 -8.369424e-01 -2.800000e+00 -7.000000e-01 8.465381e-01 8.465381e-01 4.232691e-01 -8.465381e-01 -2.700000e+00 -7.000000e-01 8.559015e-01 8.559015e-01 4.279507e-01 -8.559015e-01 -2.600000e+00 -7.000000e-01 8.650223e-01 8.650223e-01 4.325112e-01 -8.650223e-01 -2.500000e+00 -7.000000e-01 8.738907e-01 8.738907e-01 4.369453e-01 -8.738907e-01 -2.400000e+00 -7.000000e-01 8.824969e-01 8.824969e-01 4.412484e-01 -8.824969e-01 -2.300000e+00 -7.000000e-01 8.908315e-01 8.908315e-01 4.454157e-01 -8.908315e-01 -2.200000e+00 -7.000000e-01 8.988851e-01 8.988851e-01 4.494426e-01 -8.988851e-01 -2.100000e+00 -7.000000e-01 9.066489e-01 9.066489e-01 4.533245e-01 -9.066489e-01 -2.000000e+00 -7.000000e-01 9.141140e-01 9.141140e-01 4.570570e-01 -9.141140e-01 -1.900000e+00 -7.000000e-01 9.212720e-01 9.212720e-01 4.606360e-01 -9.212720e-01 -1.800000e+00 -7.000000e-01 9.281147e-01 9.281147e-01 4.640573e-01 -9.281147e-01 -1.700000e+00 -7.000000e-01 9.346343e-01 9.346343e-01 4.673171e-01 -9.346343e-01 -1.600000e+00 -7.000000e-01 9.408233e-01 9.408233e-01 4.704116e-01 -9.408233e-01 -1.500000e+00 -7.000000e-01 9.466745e-01 9.466745e-01 4.733372e-01 -9.466745e-01 -1.400000e+00 -7.000000e-01 9.521811e-01 9.521811e-01 4.760906e-01 -9.521811e-01 -1.300000e+00 -7.000000e-01 9.573368e-01 9.573368e-01 4.786684e-01 -9.573368e-01 -1.200000e+00 -7.000000e-01 9.621355e-01 9.621355e-01 4.810677e-01 -9.621355e-01 -1.100000e+00 -7.000000e-01 9.665715e-01 9.665715e-01 4.832858e-01 -9.665715e-01 -1.000000e+00 -7.000000e-01 9.706396e-01 9.706396e-01 4.853198e-01 -9.706396e-01 -9.000000e-01 -7.000000e-01 9.743351e-01 9.743351e-01 4.871675e-01 -9.743351e-01 -8.000000e-01 -7.000000e-01 9.776534e-01 9.776534e-01 4.888267e-01 -9.776534e-01 -7.000000e-01 -7.000000e-01 9.805908e-01 9.805908e-01 4.902954e-01 -9.805908e-01 -6.000000e-01 -7.000000e-01 9.831437e-01 9.831437e-01 4.915718e-01 -9.831437e-01 -5.000000e-01 -7.000000e-01 9.853090e-01 9.853090e-01 4.926545e-01 -9.853090e-01 -4.000000e-01 -7.000000e-01 9.870842e-01 9.870842e-01 4.935421e-01 -9.870842e-01 -3.000000e-01 -7.000000e-01 9.884670e-01 9.884670e-01 4.942335e-01 -9.884670e-01 -2.000000e-01 -7.000000e-01 9.894560e-01 9.894560e-01 4.947280e-01 -9.894560e-01 -1.000000e-01 -7.000000e-01 9.900498e-01 9.900498e-01 4.950249e-01 -9.900498e-01 0.000000e+00 -7.000000e-01 9.902478e-01 9.902478e-01 4.951239e-01 -9.902478e-01 1.000000e-01 -7.000000e-01 9.900498e-01 9.900498e-01 4.950249e-01 -9.900498e-01 2.000000e-01 -7.000000e-01 9.894560e-01 9.894560e-01 4.947280e-01 -9.894560e-01 3.000000e-01 -7.000000e-01 9.884670e-01 9.884670e-01 4.942335e-01 -9.884670e-01 4.000000e-01 -7.000000e-01 9.870842e-01 9.870842e-01 4.935421e-01 -9.870842e-01 5.000000e-01 -7.000000e-01 9.853090e-01 9.853090e-01 4.926545e-01 -9.853090e-01 6.000000e-01 -7.000000e-01 9.831437e-01 9.831437e-01 4.915718e-01 -9.831437e-01 7.000000e-01 -7.000000e-01 9.805908e-01 9.805908e-01 4.902954e-01 -9.805908e-01 8.000000e-01 -7.000000e-01 9.776534e-01 9.776534e-01 4.888267e-01 -9.776534e-01 9.000000e-01 -7.000000e-01 9.743351e-01 9.743351e-01 4.871675e-01 -9.743351e-01 1.000000e+00 -7.000000e-01 9.706396e-01 9.706396e-01 4.853198e-01 -9.706396e-01 1.100000e+00 -7.000000e-01 9.665715e-01 9.665715e-01 4.832858e-01 -9.665715e-01 1.200000e+00 -7.000000e-01 9.621355e-01 9.621355e-01 4.810677e-01 -9.621355e-01 1.300000e+00 -7.000000e-01 9.573368e-01 9.573368e-01 4.786684e-01 -9.573368e-01 1.400000e+00 -7.000000e-01 9.521811e-01 9.521811e-01 4.760906e-01 -9.521811e-01 1.500000e+00 -7.000000e-01 9.466745e-01 9.466745e-01 4.733372e-01 -9.466745e-01 1.600000e+00 -7.000000e-01 9.408233e-01 9.408233e-01 4.704116e-01 -9.408233e-01 1.700000e+00 -7.000000e-01 9.346343e-01 9.346343e-01 4.673171e-01 -9.346343e-01 1.800000e+00 -7.000000e-01 9.281147e-01 9.281147e-01 4.640573e-01 -9.281147e-01 1.900000e+00 -7.000000e-01 9.212720e-01 9.212720e-01 4.606360e-01 -9.212720e-01 2.000000e+00 -7.000000e-01 9.141140e-01 9.141140e-01 4.570570e-01 -9.141140e-01 2.100000e+00 -7.000000e-01 9.066489e-01 9.066489e-01 4.533245e-01 -9.066489e-01 2.200000e+00 -7.000000e-01 8.988851e-01 8.988851e-01 4.494426e-01 -8.988851e-01 2.300000e+00 -7.000000e-01 8.908315e-01 8.908315e-01 4.454157e-01 -8.908315e-01 2.400000e+00 -7.000000e-01 8.824969e-01 8.824969e-01 4.412484e-01 -8.824969e-01 2.500000e+00 -7.000000e-01 8.738907e-01 8.738907e-01 4.369453e-01 -8.738907e-01 2.600000e+00 -7.000000e-01 8.650223e-01 8.650223e-01 4.325112e-01 -8.650223e-01 2.700000e+00 -7.000000e-01 8.559015e-01 8.559015e-01 4.279507e-01 -8.559015e-01 2.800000e+00 -7.000000e-01 8.465381e-01 8.465381e-01 4.232691e-01 -8.465381e-01 2.900000e+00 -7.000000e-01 8.369424e-01 8.369424e-01 4.184712e-01 -8.369424e-01 3.000000e+00 -7.000000e-01 8.271245e-01 8.271245e-01 4.135623e-01 -8.271245e-01 3.100000e+00 -7.000000e-01 8.170949e-01 8.170949e-01 4.085475e-01 -8.170949e-01 3.200000e+00 -7.000000e-01 8.068641e-01 8.068641e-01 4.034321e-01 -8.068641e-01 3.300000e+00 -7.000000e-01 7.964428e-01 7.964428e-01 3.982214e-01 -7.964428e-01 3.400000e+00 -7.000000e-01 7.858416e-01 7.858416e-01 3.929208e-01 -7.858416e-01 3.500000e+00 -7.000000e-01 7.750715e-01 7.750715e-01 3.875358e-01 -7.750715e-01 3.600000e+00 -7.000000e-01 7.641433e-01 7.641433e-01 3.820716e-01 -7.641433e-01 3.700000e+00 -7.000000e-01 7.530678e-01 7.530678e-01 3.765339e-01 -7.530678e-01 3.800000e+00 -7.000000e-01 7.418561e-01 7.418561e-01 3.709280e-01 -7.418561e-01 3.900000e+00 -7.000000e-01 7.305190e-01 7.305190e-01 3.652595e-01 -7.305190e-01 4.000000e+00 -7.000000e-01 7.190675e-01 7.190675e-01 3.595338e-01 -7.190675e-01 4.100000e+00 -7.000000e-01 7.075125e-01 7.075125e-01 3.537562e-01 -7.075125e-01 4.200000e+00 -7.000000e-01 6.958647e-01 6.958647e-01 3.479324e-01 -6.958647e-01 4.300000e+00 -7.000000e-01 6.841350e-01 6.841350e-01 3.420675e-01 -6.841350e-01 4.400000e+00 -7.000000e-01 6.723340e-01 6.723340e-01 3.361670e-01 -6.723340e-01 4.500000e+00 -7.000000e-01 6.604724e-01 6.604724e-01 3.302362e-01 -6.604724e-01 4.600000e+00 -7.000000e-01 6.485605e-01 6.485605e-01 3.242803e-01 -6.485605e-01 4.700000e+00 -7.000000e-01 6.366088e-01 6.366088e-01 3.183044e-01 -6.366088e-01 4.800000e+00 -7.000000e-01 6.246274e-01 6.246274e-01 3.123137e-01 -6.246274e-01 4.900000e+00 -7.000000e-01 6.126264e-01 6.126264e-01 3.063132e-01 -6.126264e-01 -5.000000e+00 -6.000000e-01 6.021793e-01 6.021793e-01 3.010897e-01 -6.021793e-01 -4.900000e+00 -6.000000e-01 6.142213e-01 6.142213e-01 3.071106e-01 -6.142213e-01 -4.800000e+00 -6.000000e-01 6.262535e-01 6.262535e-01 3.131267e-01 -6.262535e-01 -4.700000e+00 -6.000000e-01 6.382661e-01 6.382661e-01 3.191331e-01 -6.382661e-01 -4.600000e+00 -6.000000e-01 6.502489e-01 6.502489e-01 3.251245e-01 -6.502489e-01 -4.500000e+00 -6.000000e-01 6.621919e-01 6.621919e-01 3.310959e-01 -6.621919e-01 -4.400000e+00 -6.000000e-01 6.740844e-01 6.740844e-01 3.370422e-01 -6.740844e-01 -4.300000e+00 -6.000000e-01 6.859161e-01 6.859161e-01 3.429580e-01 -6.859161e-01 -4.200000e+00 -6.000000e-01 6.976764e-01 6.976764e-01 3.488382e-01 -6.976764e-01 -4.100000e+00 -6.000000e-01 7.093544e-01 7.093544e-01 3.546772e-01 -7.093544e-01 -4.000000e+00 -6.000000e-01 7.209395e-01 7.209395e-01 3.604698e-01 -7.209395e-01 -3.900000e+00 -6.000000e-01 7.324208e-01 7.324208e-01 3.662104e-01 -7.324208e-01 -3.800000e+00 -6.000000e-01 7.437874e-01 7.437874e-01 3.718937e-01 -7.437874e-01 -3.700000e+00 -6.000000e-01 7.550283e-01 7.550283e-01 3.775142e-01 -7.550283e-01 -3.600000e+00 -6.000000e-01 7.661327e-01 7.661327e-01 3.830663e-01 -7.661327e-01 -3.500000e+00 -6.000000e-01 7.770893e-01 7.770893e-01 3.885446e-01 -7.770893e-01 -3.400000e+00 -6.000000e-01 7.878875e-01 7.878875e-01 3.939437e-01 -7.878875e-01 -3.300000e+00 -6.000000e-01 7.985162e-01 7.985162e-01 3.992581e-01 -7.985162e-01 -3.200000e+00 -6.000000e-01 8.089647e-01 8.089647e-01 4.044824e-01 -8.089647e-01 -3.100000e+00 -6.000000e-01 8.192222e-01 8.192222e-01 4.096111e-01 -8.192222e-01 -3.000000e+00 -6.000000e-01 8.292779e-01 8.292779e-01 4.146389e-01 -8.292779e-01 -2.900000e+00 -6.000000e-01 8.391213e-01 8.391213e-01 4.195606e-01 -8.391213e-01 -2.800000e+00 -6.000000e-01 8.487420e-01 8.487420e-01 4.243710e-01 -8.487420e-01 -2.700000e+00 -6.000000e-01 8.581297e-01 8.581297e-01 4.290649e-01 -8.581297e-01 -2.600000e+00 -6.000000e-01 8.672743e-01 8.672743e-01 4.336371e-01 -8.672743e-01 -2.500000e+00 -6.000000e-01 8.761657e-01 8.761657e-01 4.380829e-01 -8.761657e-01 -2.400000e+00 -6.000000e-01 8.847944e-01 8.847944e-01 4.423972e-01 -8.847944e-01 -2.300000e+00 -6.000000e-01 8.931507e-01 8.931507e-01 4.465753e-01 -8.931507e-01 -2.200000e+00 -6.000000e-01 9.012253e-01 9.012253e-01 4.506126e-01 -9.012253e-01 -2.100000e+00 -6.000000e-01 9.090093e-01 9.090093e-01 4.545046e-01 -9.090093e-01 -2.000000e+00 -6.000000e-01 9.164938e-01 9.164938e-01 4.582469e-01 -9.164938e-01 -1.900000e+00 -6.000000e-01 9.236704e-01 9.236704e-01 4.618352e-01 -9.236704e-01 -1.800000e+00 -6.000000e-01 9.305309e-01 9.305309e-01 4.652655e-01 -9.305309e-01 -1.700000e+00 -6.000000e-01 9.370674e-01 9.370674e-01 4.685337e-01 -9.370674e-01 -1.600000e+00 -6.000000e-01 9.432726e-01 9.432726e-01 4.716363e-01 -9.432726e-01 -1.500000e+00 -6.000000e-01 9.491390e-01 9.491390e-01 4.745695e-01 -9.491390e-01 -1.400000e+00 -6.000000e-01 9.546600e-01 9.546600e-01 4.773300e-01 -9.546600e-01 -1.300000e+00 -6.000000e-01 9.598292e-01 9.598292e-01 4.799146e-01 -9.598292e-01 -1.200000e+00 -6.000000e-01 9.646403e-01 9.646403e-01 4.823202e-01 -9.646403e-01 -1.100000e+00 -6.000000e-01 9.690878e-01 9.690878e-01 4.845439e-01 -9.690878e-01 -1.000000e+00 -6.000000e-01 9.731666e-01 9.731666e-01 4.865833e-01 -9.731666e-01 -9.000000e-01 -6.000000e-01 9.768717e-01 9.768717e-01 4.884358e-01 -9.768717e-01 -8.000000e-01 -6.000000e-01 9.801987e-01 9.801987e-01 4.900993e-01 -9.801987e-01 -7.000000e-01 -6.000000e-01 9.831437e-01 9.831437e-01 4.915718e-01 -9.831437e-01 -6.000000e-01 -6.000000e-01 9.857032e-01 9.857032e-01 4.928516e-01 -9.857032e-01 -5.000000e-01 -6.000000e-01 9.878741e-01 9.878741e-01 4.939370e-01 -9.878741e-01 -4.000000e-01 -6.000000e-01 9.896539e-01 9.896539e-01 4.948269e-01 -9.896539e-01 -3.000000e-01 -6.000000e-01 9.910403e-01 9.910403e-01 4.955202e-01 -9.910403e-01 -2.000000e-01 -6.000000e-01 9.920319e-01 9.920319e-01 4.960160e-01 -9.920319e-01 -1.000000e-01 -6.000000e-01 9.926273e-01 9.926273e-01 4.963137e-01 -9.926273e-01 0.000000e+00 -6.000000e-01 9.928259e-01 9.928259e-01 4.964129e-01 -9.928259e-01 1.000000e-01 -6.000000e-01 9.926273e-01 9.926273e-01 4.963137e-01 -9.926273e-01 2.000000e-01 -6.000000e-01 9.920319e-01 9.920319e-01 4.960160e-01 -9.920319e-01 3.000000e-01 -6.000000e-01 9.910403e-01 9.910403e-01 4.955202e-01 -9.910403e-01 4.000000e-01 -6.000000e-01 9.896539e-01 9.896539e-01 4.948269e-01 -9.896539e-01 5.000000e-01 -6.000000e-01 9.878741e-01 9.878741e-01 4.939370e-01 -9.878741e-01 6.000000e-01 -6.000000e-01 9.857032e-01 9.857032e-01 4.928516e-01 -9.857032e-01 7.000000e-01 -6.000000e-01 9.831437e-01 9.831437e-01 4.915718e-01 -9.831437e-01 8.000000e-01 -6.000000e-01 9.801987e-01 9.801987e-01 4.900993e-01 -9.801987e-01 9.000000e-01 -6.000000e-01 9.768717e-01 9.768717e-01 4.884358e-01 -9.768717e-01 1.000000e+00 -6.000000e-01 9.731666e-01 9.731666e-01 4.865833e-01 -9.731666e-01 1.100000e+00 -6.000000e-01 9.690878e-01 9.690878e-01 4.845439e-01 -9.690878e-01 1.200000e+00 -6.000000e-01 9.646403e-01 9.646403e-01 4.823202e-01 -9.646403e-01 1.300000e+00 -6.000000e-01 9.598292e-01 9.598292e-01 4.799146e-01 -9.598292e-01 1.400000e+00 -6.000000e-01 9.546600e-01 9.546600e-01 4.773300e-01 -9.546600e-01 1.500000e+00 -6.000000e-01 9.491390e-01 9.491390e-01 4.745695e-01 -9.491390e-01 1.600000e+00 -6.000000e-01 9.432726e-01 9.432726e-01 4.716363e-01 -9.432726e-01 1.700000e+00 -6.000000e-01 9.370674e-01 9.370674e-01 4.685337e-01 -9.370674e-01 1.800000e+00 -6.000000e-01 9.305309e-01 9.305309e-01 4.652655e-01 -9.305309e-01 1.900000e+00 -6.000000e-01 9.236704e-01 9.236704e-01 4.618352e-01 -9.236704e-01 2.000000e+00 -6.000000e-01 9.164938e-01 9.164938e-01 4.582469e-01 -9.164938e-01 2.100000e+00 -6.000000e-01 9.090093e-01 9.090093e-01 4.545046e-01 -9.090093e-01 2.200000e+00 -6.000000e-01 9.012253e-01 9.012253e-01 4.506126e-01 -9.012253e-01 2.300000e+00 -6.000000e-01 8.931507e-01 8.931507e-01 4.465753e-01 -8.931507e-01 2.400000e+00 -6.000000e-01 8.847944e-01 8.847944e-01 4.423972e-01 -8.847944e-01 2.500000e+00 -6.000000e-01 8.761657e-01 8.761657e-01 4.380829e-01 -8.761657e-01 2.600000e+00 -6.000000e-01 8.672743e-01 8.672743e-01 4.336371e-01 -8.672743e-01 2.700000e+00 -6.000000e-01 8.581297e-01 8.581297e-01 4.290649e-01 -8.581297e-01 2.800000e+00 -6.000000e-01 8.487420e-01 8.487420e-01 4.243710e-01 -8.487420e-01 2.900000e+00 -6.000000e-01 8.391213e-01 8.391213e-01 4.195606e-01 -8.391213e-01 3.000000e+00 -6.000000e-01 8.292779e-01 8.292779e-01 4.146389e-01 -8.292779e-01 3.100000e+00 -6.000000e-01 8.192222e-01 8.192222e-01 4.096111e-01 -8.192222e-01 3.200000e+00 -6.000000e-01 8.089647e-01 8.089647e-01 4.044824e-01 -8.089647e-01 3.300000e+00 -6.000000e-01 7.985162e-01 7.985162e-01 3.992581e-01 -7.985162e-01 3.400000e+00 -6.000000e-01 7.878875e-01 7.878875e-01 3.939437e-01 -7.878875e-01 3.500000e+00 -6.000000e-01 7.770893e-01 7.770893e-01 3.885446e-01 -7.770893e-01 3.600000e+00 -6.000000e-01 7.661327e-01 7.661327e-01 3.830663e-01 -7.661327e-01 3.700000e+00 -6.000000e-01 7.550283e-01 7.550283e-01 3.775142e-01 -7.550283e-01 3.800000e+00 -6.000000e-01 7.437874e-01 7.437874e-01 3.718937e-01 -7.437874e-01 3.900000e+00 -6.000000e-01 7.324208e-01 7.324208e-01 3.662104e-01 -7.324208e-01 4.000000e+00 -6.000000e-01 7.209395e-01 7.209395e-01 3.604698e-01 -7.209395e-01 4.100000e+00 -6.000000e-01 7.093544e-01 7.093544e-01 3.546772e-01 -7.093544e-01 4.200000e+00 -6.000000e-01 6.976764e-01 6.976764e-01 3.488382e-01 -6.976764e-01 4.300000e+00 -6.000000e-01 6.859161e-01 6.859161e-01 3.429580e-01 -6.859161e-01 4.400000e+00 -6.000000e-01 6.740844e-01 6.740844e-01 3.370422e-01 -6.740844e-01 4.500000e+00 -6.000000e-01 6.621919e-01 6.621919e-01 3.310959e-01 -6.621919e-01 4.600000e+00 -6.000000e-01 6.502489e-01 6.502489e-01 3.251245e-01 -6.502489e-01 4.700000e+00 -6.000000e-01 6.382661e-01 6.382661e-01 3.191331e-01 -6.382661e-01 4.800000e+00 -6.000000e-01 6.262535e-01 6.262535e-01 3.131267e-01 -6.262535e-01 4.900000e+00 -6.000000e-01 6.142213e-01 6.142213e-01 3.071106e-01 -6.142213e-01 -5.000000e+00 -5.000000e-01 6.035056e-01 6.035056e-01 3.017528e-01 -6.035056e-01 -4.900000e+00 -5.000000e-01 6.155741e-01 6.155741e-01 3.077870e-01 -6.155741e-01 -4.800000e+00 -5.000000e-01 6.276328e-01 6.276328e-01 3.138164e-01 -6.276328e-01 -4.700000e+00 -5.000000e-01 6.396719e-01 6.396719e-01 3.198359e-01 -6.396719e-01 -4.600000e+00 -5.000000e-01 6.516811e-01 6.516811e-01 3.258406e-01 -6.516811e-01 -4.500000e+00 -5.000000e-01 6.636503e-01 6.636503e-01 3.318251e-01 -6.636503e-01 -4.400000e+00 -5.000000e-01 6.755690e-01 6.755690e-01 3.377845e-01 -6.755690e-01 -4.300000e+00 -5.000000e-01 6.874267e-01 6.874267e-01 3.437134e-01 -6.874267e-01 -4.200000e+00 -5.000000e-01 6.992129e-01 6.992129e-01 3.496065e-01 -6.992129e-01 -4.100000e+00 -5.000000e-01 7.109167e-01 7.109167e-01 3.554583e-01 -7.109167e-01 -4.000000e+00 -5.000000e-01 7.225273e-01 7.225273e-01 3.612637e-01 -7.225273e-01 -3.900000e+00 -5.000000e-01 7.340339e-01 7.340339e-01 3.670170e-01 -7.340339e-01 -3.800000e+00 -5.000000e-01 7.454256e-01 7.454256e-01 3.727128e-01 -7.454256e-01 -3.700000e+00 -5.000000e-01 7.566912e-01 7.566912e-01 3.783456e-01 -7.566912e-01 -3.600000e+00 -5.000000e-01 7.678200e-01 7.678200e-01 3.839100e-01 -7.678200e-01 -3.500000e+00 -5.000000e-01 7.788008e-01 7.788008e-01 3.894004e-01 -7.788008e-01 -3.400000e+00 -5.000000e-01 7.896227e-01 7.896227e-01 3.948114e-01 -7.896227e-01 -3.300000e+00 -5.000000e-01 8.002749e-01 8.002749e-01 4.001375e-01 -8.002749e-01 -3.200000e+00 -5.000000e-01 8.107464e-01 8.107464e-01 4.053732e-01 -8.107464e-01 -3.100000e+00 -5.000000e-01 8.210264e-01 8.210264e-01 4.105132e-01 -8.210264e-01 -3.000000e+00 -5.000000e-01 8.311043e-01 8.311043e-01 4.155521e-01 -8.311043e-01 -2.900000e+00 -5.000000e-01 8.409694e-01 8.409694e-01 4.204847e-01 -8.409694e-01 -2.800000e+00 -5.000000e-01 8.506113e-01 8.506113e-01 4.253057e-01 -8.506113e-01 -2.700000e+00 -5.000000e-01 8.600197e-01 8.600197e-01 4.300098e-01 -8.600197e-01 -2.600000e+00 -5.000000e-01 8.691844e-01 8.691844e-01 4.345922e-01 -8.691844e-01 -2.500000e+00 -5.000000e-01 8.780954e-01 8.780954e-01 4.390477e-01 -8.780954e-01 -2.400000e+00 -5.000000e-01 8.867431e-01 8.867431e-01 4.433715e-01 -8.867431e-01 -2.300000e+00 -5.000000e-01 8.951178e-01 8.951178e-01 4.475589e-01 -8.951178e-01 -2.200000e+00 -5.000000e-01 9.032102e-01 9.032102e-01 4.516051e-01 -9.032102e-01 -2.100000e+00 -5.000000e-01 9.110113e-01 9.110113e-01 4.555056e-01 -9.110113e-01 -2.000000e+00 -5.000000e-01 9.185123e-01 9.185123e-01 4.592561e-01 -9.185123e-01 -1.900000e+00 -5.000000e-01 9.257047e-01 9.257047e-01 4.628524e-01 -9.257047e-01 -1.800000e+00 -5.000000e-01 9.325803e-01 9.325803e-01 4.662901e-01 -9.325803e-01 -1.700000e+00 -5.000000e-01 9.391313e-01 9.391313e-01 4.695656e-01 -9.391313e-01 -1.600000e+00 -5.000000e-01 9.453501e-01 9.453501e-01 4.726750e-01 -9.453501e-01 -1.500000e+00 -5.000000e-01 9.512295e-01 9.512295e-01 4.756147e-01 -9.512295e-01 -1.400000e+00 -5.000000e-01 9.567626e-01 9.567626e-01 4.783813e-01 -9.567626e-01 -1.300000e+00 -5.000000e-01 9.619431e-01 9.619431e-01 4.809715e-01 -9.619431e-01 -1.200000e+00 -5.000000e-01 9.667648e-01 9.667648e-01 4.833824e-01 -9.667648e-01 -1.100000e+00 -5.000000e-01 9.712222e-01 9.712222e-01 4.856111e-01 -9.712222e-01 -1.000000e+00 -5.000000e-01 9.753099e-01 9.753099e-01 4.876550e-01 -9.753099e-01 -9.000000e-01 -5.000000e-01 9.790232e-01 9.790232e-01 4.895116e-01 -9.790232e-01 -8.000000e-01 -5.000000e-01 9.823575e-01 9.823575e-01 4.911788e-01 -9.823575e-01 -7.000000e-01 -5.000000e-01 9.853090e-01 9.853090e-01 4.926545e-01 -9.853090e-01 -6.000000e-01 -5.000000e-01 9.878741e-01 9.878741e-01 4.939370e-01 -9.878741e-01 -5.000000e-01 -5.000000e-01 9.900498e-01 9.900498e-01 4.950249e-01 -9.900498e-01 -4.000000e-01 -5.000000e-01 9.918335e-01 9.918335e-01 4.959168e-01 -9.918335e-01 -3.000000e-01 -5.000000e-01 9.932231e-01 9.932231e-01 4.966115e-01 -9.932231e-01 -2.000000e-01 -5.000000e-01 9.942168e-01 9.942168e-01 4.971084e-01 -9.942168e-01 -1.000000e-01 -5.000000e-01 9.948135e-01 9.948135e-01 4.974068e-01 -9.948135e-01 0.000000e+00 -5.000000e-01 9.950125e-01 9.950125e-01 4.975062e-01 -9.950125e-01 1.000000e-01 -5.000000e-01 9.948135e-01 9.948135e-01 4.974068e-01 -9.948135e-01 2.000000e-01 -5.000000e-01 9.942168e-01 9.942168e-01 4.971084e-01 -9.942168e-01 3.000000e-01 -5.000000e-01 9.932231e-01 9.932231e-01 4.966115e-01 -9.932231e-01 4.000000e-01 -5.000000e-01 9.918335e-01 9.918335e-01 4.959168e-01 -9.918335e-01 5.000000e-01 -5.000000e-01 9.900498e-01 9.900498e-01 4.950249e-01 -9.900498e-01 6.000000e-01 -5.000000e-01 9.878741e-01 9.878741e-01 4.939370e-01 -9.878741e-01 7.000000e-01 -5.000000e-01 9.853090e-01 9.853090e-01 4.926545e-01 -9.853090e-01 8.000000e-01 -5.000000e-01 9.823575e-01 9.823575e-01 4.911788e-01 -9.823575e-01 9.000000e-01 -5.000000e-01 9.790232e-01 9.790232e-01 4.895116e-01 -9.790232e-01 1.000000e+00 -5.000000e-01 9.753099e-01 9.753099e-01 4.876550e-01 -9.753099e-01 1.100000e+00 -5.000000e-01 9.712222e-01 9.712222e-01 4.856111e-01 -9.712222e-01 1.200000e+00 -5.000000e-01 9.667648e-01 9.667648e-01 4.833824e-01 -9.667648e-01 1.300000e+00 -5.000000e-01 9.619431e-01 9.619431e-01 4.809715e-01 -9.619431e-01 1.400000e+00 -5.000000e-01 9.567626e-01 9.567626e-01 4.783813e-01 -9.567626e-01 1.500000e+00 -5.000000e-01 9.512295e-01 9.512295e-01 4.756147e-01 -9.512295e-01 1.600000e+00 -5.000000e-01 9.453501e-01 9.453501e-01 4.726750e-01 -9.453501e-01 1.700000e+00 -5.000000e-01 9.391313e-01 9.391313e-01 4.695656e-01 -9.391313e-01 1.800000e+00 -5.000000e-01 9.325803e-01 9.325803e-01 4.662901e-01 -9.325803e-01 1.900000e+00 -5.000000e-01 9.257047e-01 9.257047e-01 4.628524e-01 -9.257047e-01 2.000000e+00 -5.000000e-01 9.185123e-01 9.185123e-01 4.592561e-01 -9.185123e-01 2.100000e+00 -5.000000e-01 9.110113e-01 9.110113e-01 4.555056e-01 -9.110113e-01 2.200000e+00 -5.000000e-01 9.032102e-01 9.032102e-01 4.516051e-01 -9.032102e-01 2.300000e+00 -5.000000e-01 8.951178e-01 8.951178e-01 4.475589e-01 -8.951178e-01 2.400000e+00 -5.000000e-01 8.867431e-01 8.867431e-01 4.433715e-01 -8.867431e-01 2.500000e+00 -5.000000e-01 8.780954e-01 8.780954e-01 4.390477e-01 -8.780954e-01 2.600000e+00 -5.000000e-01 8.691844e-01 8.691844e-01 4.345922e-01 -8.691844e-01 2.700000e+00 -5.000000e-01 8.600197e-01 8.600197e-01 4.300098e-01 -8.600197e-01 2.800000e+00 -5.000000e-01 8.506113e-01 8.506113e-01 4.253057e-01 -8.506113e-01 2.900000e+00 -5.000000e-01 8.409694e-01 8.409694e-01 4.204847e-01 -8.409694e-01 3.000000e+00 -5.000000e-01 8.311043e-01 8.311043e-01 4.155521e-01 -8.311043e-01 3.100000e+00 -5.000000e-01 8.210264e-01 8.210264e-01 4.105132e-01 -8.210264e-01 3.200000e+00 -5.000000e-01 8.107464e-01 8.107464e-01 4.053732e-01 -8.107464e-01 3.300000e+00 -5.000000e-01 8.002749e-01 8.002749e-01 4.001375e-01 -8.002749e-01 3.400000e+00 -5.000000e-01 7.896227e-01 7.896227e-01 3.948114e-01 -7.896227e-01 3.500000e+00 -5.000000e-01 7.788008e-01 7.788008e-01 3.894004e-01 -7.788008e-01 3.600000e+00 -5.000000e-01 7.678200e-01 7.678200e-01 3.839100e-01 -7.678200e-01 3.700000e+00 -5.000000e-01 7.566912e-01 7.566912e-01 3.783456e-01 -7.566912e-01 3.800000e+00 -5.000000e-01 7.454256e-01 7.454256e-01 3.727128e-01 -7.454256e-01 3.900000e+00 -5.000000e-01 7.340339e-01 7.340339e-01 3.670170e-01 -7.340339e-01 4.000000e+00 -5.000000e-01 7.225273e-01 7.225273e-01 3.612637e-01 -7.225273e-01 4.100000e+00 -5.000000e-01 7.109167e-01 7.109167e-01 3.554583e-01 -7.109167e-01 4.200000e+00 -5.000000e-01 6.992129e-01 6.992129e-01 3.496065e-01 -6.992129e-01 4.300000e+00 -5.000000e-01 6.874267e-01 6.874267e-01 3.437134e-01 -6.874267e-01 4.400000e+00 -5.000000e-01 6.755690e-01 6.755690e-01 3.377845e-01 -6.755690e-01 4.500000e+00 -5.000000e-01 6.636503e-01 6.636503e-01 3.318251e-01 -6.636503e-01 4.600000e+00 -5.000000e-01 6.516811e-01 6.516811e-01 3.258406e-01 -6.516811e-01 4.700000e+00 -5.000000e-01 6.396719e-01 6.396719e-01 3.198359e-01 -6.396719e-01 4.800000e+00 -5.000000e-01 6.276328e-01 6.276328e-01 3.138164e-01 -6.276328e-01 4.900000e+00 -5.000000e-01 6.155741e-01 6.155741e-01 3.077870e-01 -6.155741e-01 -5.000000e+00 -4.000000e-01 6.045929e-01 6.045929e-01 3.022964e-01 -6.045929e-01 -4.900000e+00 -4.000000e-01 6.166831e-01 6.166831e-01 3.083415e-01 -6.166831e-01 -4.800000e+00 -4.000000e-01 6.287636e-01 6.287636e-01 3.143818e-01 -6.287636e-01 -4.700000e+00 -4.000000e-01 6.408243e-01 6.408243e-01 3.204122e-01 -6.408243e-01 -4.600000e+00 -4.000000e-01 6.528552e-01 6.528552e-01 3.264276e-01 -6.528552e-01 -4.500000e+00 -4.000000e-01 6.648459e-01 6.648459e-01 3.324230e-01 -6.648459e-01 -4.400000e+00 -4.000000e-01 6.767861e-01 6.767861e-01 3.383931e-01 -6.767861e-01 -4.300000e+00 -4.000000e-01 6.886652e-01 6.886652e-01 3.443326e-01 -6.886652e-01 -4.200000e+00 -4.000000e-01 7.004727e-01 7.004727e-01 3.502363e-01 -7.004727e-01 -4.100000e+00 -4.000000e-01 7.121975e-01 7.121975e-01 3.560988e-01 -7.121975e-01 -4.000000e+00 -4.000000e-01 7.238291e-01 7.238291e-01 3.619145e-01 -7.238291e-01 -3.900000e+00 -4.000000e-01 7.353564e-01 7.353564e-01 3.676782e-01 -7.353564e-01 -3.800000e+00 -4.000000e-01 7.467685e-01 7.467685e-01 3.733843e-01 -7.467685e-01 -3.700000e+00 -4.000000e-01 7.580545e-01 7.580545e-01 3.790272e-01 -7.580545e-01 -3.600000e+00 -4.000000e-01 7.692033e-01 7.692033e-01 3.846017e-01 -7.692033e-01 -3.500000e+00 -4.000000e-01 7.802039e-01 7.802039e-01 3.901019e-01 -7.802039e-01 -3.400000e+00 -4.000000e-01 7.910453e-01 7.910453e-01 3.955227e-01 -7.910453e-01 -3.300000e+00 -4.000000e-01 8.017167e-01 8.017167e-01 4.008583e-01 -8.017167e-01 -3.200000e+00 -4.000000e-01 8.122070e-01 8.122070e-01 4.061035e-01 -8.122070e-01 -3.100000e+00 -4.000000e-01 8.225056e-01 8.225056e-01 4.112528e-01 -8.225056e-01 -3.000000e+00 -4.000000e-01 8.326016e-01 8.326016e-01 4.163008e-01 -8.326016e-01 -2.900000e+00 -4.000000e-01 8.424845e-01 8.424845e-01 4.212422e-01 -8.424845e-01 -2.800000e+00 -4.000000e-01 8.521438e-01 8.521438e-01 4.260719e-01 -8.521438e-01 -2.700000e+00 -4.000000e-01 8.615691e-01 8.615691e-01 4.307846e-01 -8.615691e-01 -2.600000e+00 -4.000000e-01 8.707503e-01 8.707503e-01 4.353752e-01 -8.707503e-01 -2.500000e+00 -4.000000e-01 8.796774e-01 8.796774e-01 4.398387e-01 -8.796774e-01 -2.400000e+00 -4.000000e-01 8.883407e-01 8.883407e-01 4.441703e-01 -8.883407e-01 -2.300000e+00 -4.000000e-01 8.967304e-01 8.967304e-01 4.483652e-01 -8.967304e-01 -2.200000e+00 -4.000000e-01 9.048374e-01 9.048374e-01 4.524187e-01 -9.048374e-01 -2.100000e+00 -4.000000e-01 9.126526e-01 9.126526e-01 4.563263e-01 -9.126526e-01 -2.000000e+00 -4.000000e-01 9.201671e-01 9.201671e-01 4.600835e-01 -9.201671e-01 -1.900000e+00 -4.000000e-01 9.273725e-01 9.273725e-01 4.636862e-01 -9.273725e-01 -1.800000e+00 -4.000000e-01 9.342605e-01 9.342605e-01 4.671302e-01 -9.342605e-01 -1.700000e+00 -4.000000e-01 9.408233e-01 9.408233e-01 4.704116e-01 -9.408233e-01 -1.600000e+00 -4.000000e-01 9.470532e-01 9.470532e-01 4.735266e-01 -9.470532e-01 -1.500000e+00 -4.000000e-01 9.529432e-01 9.529432e-01 4.764716e-01 -9.529432e-01 -1.400000e+00 -4.000000e-01 9.584863e-01 9.584863e-01 4.792432e-01 -9.584863e-01 -1.300000e+00 -4.000000e-01 9.636762e-01 9.636762e-01 4.818381e-01 -9.636762e-01 -1.200000e+00 -4.000000e-01 9.685066e-01 9.685066e-01 4.842533e-01 -9.685066e-01 -1.100000e+00 -4.000000e-01 9.729720e-01 9.729720e-01 4.864860e-01 -9.729720e-01 -1.000000e+00 -4.000000e-01 9.770671e-01 9.770671e-01 4.885335e-01 -9.770671e-01 -9.000000e-01 -4.000000e-01 9.807870e-01 9.807870e-01 4.903935e-01 -9.807870e-01 -8.000000e-01 -4.000000e-01 9.841273e-01 9.841273e-01 4.920637e-01 -9.841273e-01 -7.000000e-01 -4.000000e-01 9.870842e-01 9.870842e-01 4.935421e-01 -9.870842e-01 -6.000000e-01 -4.000000e-01 9.896539e-01 9.896539e-01 4.948269e-01 -9.896539e-01 -5.000000e-01 -4.000000e-01 9.918335e-01 9.918335e-01 4.959168e-01 -9.918335e-01 -4.000000e-01 -4.000000e-01 9.936205e-01 9.936205e-01 4.968102e-01 -9.936205e-01 -3.000000e-01 -4.000000e-01 9.950125e-01 9.950125e-01 4.975062e-01 -9.950125e-01 -2.000000e-01 -4.000000e-01 9.960080e-01 9.960080e-01 4.980040e-01 -9.960080e-01 -1.000000e-01 -4.000000e-01 9.966058e-01 9.966058e-01 4.983029e-01 -9.966058e-01 0.000000e+00 -4.000000e-01 9.968051e-01 9.968051e-01 4.984026e-01 -9.968051e-01 1.000000e-01 -4.000000e-01 9.966058e-01 9.966058e-01 4.983029e-01 -9.966058e-01 2.000000e-01 -4.000000e-01 9.960080e-01 9.960080e-01 4.980040e-01 -9.960080e-01 3.000000e-01 -4.000000e-01 9.950125e-01 9.950125e-01 4.975062e-01 -9.950125e-01 4.000000e-01 -4.000000e-01 9.936205e-01 9.936205e-01 4.968102e-01 -9.936205e-01 5.000000e-01 -4.000000e-01 9.918335e-01 9.918335e-01 4.959168e-01 -9.918335e-01 6.000000e-01 -4.000000e-01 9.896539e-01 9.896539e-01 4.948269e-01 -9.896539e-01 7.000000e-01 -4.000000e-01 9.870842e-01 9.870842e-01 4.935421e-01 -9.870842e-01 8.000000e-01 -4.000000e-01 9.841273e-01 9.841273e-01 4.920637e-01 -9.841273e-01 9.000000e-01 -4.000000e-01 9.807870e-01 9.807870e-01 4.903935e-01 -9.807870e-01 1.000000e+00 -4.000000e-01 9.770671e-01 9.770671e-01 4.885335e-01 -9.770671e-01 1.100000e+00 -4.000000e-01 9.729720e-01 9.729720e-01 4.864860e-01 -9.729720e-01 1.200000e+00 -4.000000e-01 9.685066e-01 9.685066e-01 4.842533e-01 -9.685066e-01 1.300000e+00 -4.000000e-01 9.636762e-01 9.636762e-01 4.818381e-01 -9.636762e-01 1.400000e+00 -4.000000e-01 9.584863e-01 9.584863e-01 4.792432e-01 -9.584863e-01 1.500000e+00 -4.000000e-01 9.529432e-01 9.529432e-01 4.764716e-01 -9.529432e-01 1.600000e+00 -4.000000e-01 9.470532e-01 9.470532e-01 4.735266e-01 -9.470532e-01 1.700000e+00 -4.000000e-01 9.408233e-01 9.408233e-01 4.704116e-01 -9.408233e-01 1.800000e+00 -4.000000e-01 9.342605e-01 9.342605e-01 4.671302e-01 -9.342605e-01 1.900000e+00 -4.000000e-01 9.273725e-01 9.273725e-01 4.636862e-01 -9.273725e-01 2.000000e+00 -4.000000e-01 9.201671e-01 9.201671e-01 4.600835e-01 -9.201671e-01 2.100000e+00 -4.000000e-01 9.126526e-01 9.126526e-01 4.563263e-01 -9.126526e-01 2.200000e+00 -4.000000e-01 9.048374e-01 9.048374e-01 4.524187e-01 -9.048374e-01 2.300000e+00 -4.000000e-01 8.967304e-01 8.967304e-01 4.483652e-01 -8.967304e-01 2.400000e+00 -4.000000e-01 8.883407e-01 8.883407e-01 4.441703e-01 -8.883407e-01 2.500000e+00 -4.000000e-01 8.796774e-01 8.796774e-01 4.398387e-01 -8.796774e-01 2.600000e+00 -4.000000e-01 8.707503e-01 8.707503e-01 4.353752e-01 -8.707503e-01 2.700000e+00 -4.000000e-01 8.615691e-01 8.615691e-01 4.307846e-01 -8.615691e-01 2.800000e+00 -4.000000e-01 8.521438e-01 8.521438e-01 4.260719e-01 -8.521438e-01 2.900000e+00 -4.000000e-01 8.424845e-01 8.424845e-01 4.212422e-01 -8.424845e-01 3.000000e+00 -4.000000e-01 8.326016e-01 8.326016e-01 4.163008e-01 -8.326016e-01 3.100000e+00 -4.000000e-01 8.225056e-01 8.225056e-01 4.112528e-01 -8.225056e-01 3.200000e+00 -4.000000e-01 8.122070e-01 8.122070e-01 4.061035e-01 -8.122070e-01 3.300000e+00 -4.000000e-01 8.017167e-01 8.017167e-01 4.008583e-01 -8.017167e-01 3.400000e+00 -4.000000e-01 7.910453e-01 7.910453e-01 3.955227e-01 -7.910453e-01 3.500000e+00 -4.000000e-01 7.802039e-01 7.802039e-01 3.901019e-01 -7.802039e-01 3.600000e+00 -4.000000e-01 7.692033e-01 7.692033e-01 3.846017e-01 -7.692033e-01 3.700000e+00 -4.000000e-01 7.580545e-01 7.580545e-01 3.790272e-01 -7.580545e-01 3.800000e+00 -4.000000e-01 7.467685e-01 7.467685e-01 3.733843e-01 -7.467685e-01 3.900000e+00 -4.000000e-01 7.353564e-01 7.353564e-01 3.676782e-01 -7.353564e-01 4.000000e+00 -4.000000e-01 7.238291e-01 7.238291e-01 3.619145e-01 -7.238291e-01 4.100000e+00 -4.000000e-01 7.121975e-01 7.121975e-01 3.560988e-01 -7.121975e-01 4.200000e+00 -4.000000e-01 7.004727e-01 7.004727e-01 3.502363e-01 -7.004727e-01 4.300000e+00 -4.000000e-01 6.886652e-01 6.886652e-01 3.443326e-01 -6.886652e-01 4.400000e+00 -4.000000e-01 6.767861e-01 6.767861e-01 3.383931e-01 -6.767861e-01 4.500000e+00 -4.000000e-01 6.648459e-01 6.648459e-01 3.324230e-01 -6.648459e-01 4.600000e+00 -4.000000e-01 6.528552e-01 6.528552e-01 3.264276e-01 -6.528552e-01 4.700000e+00 -4.000000e-01 6.408243e-01 6.408243e-01 3.204122e-01 -6.408243e-01 4.800000e+00 -4.000000e-01 6.287636e-01 6.287636e-01 3.143818e-01 -6.287636e-01 4.900000e+00 -4.000000e-01 6.166831e-01 6.166831e-01 3.083415e-01 -6.166831e-01 -5.000000e+00 -3.000000e-01 6.054399e-01 6.054399e-01 3.027200e-01 -6.054399e-01 -4.900000e+00 -3.000000e-01 6.175470e-01 6.175470e-01 3.087735e-01 -6.175470e-01 -4.800000e+00 -3.000000e-01 6.296445e-01 6.296445e-01 3.148222e-01 -6.296445e-01 -4.700000e+00 -3.000000e-01 6.417221e-01 6.417221e-01 3.208610e-01 -6.417221e-01 -4.600000e+00 -3.000000e-01 6.537698e-01 6.537698e-01 3.268849e-01 -6.537698e-01 -4.500000e+00 -3.000000e-01 6.657773e-01 6.657773e-01 3.328887e-01 -6.657773e-01 -4.400000e+00 -3.000000e-01 6.777343e-01 6.777343e-01 3.388671e-01 -6.777343e-01 -4.300000e+00 -3.000000e-01 6.896300e-01 6.896300e-01 3.448150e-01 -6.896300e-01 -4.200000e+00 -3.000000e-01 7.014540e-01 7.014540e-01 3.507270e-01 -7.014540e-01 -4.100000e+00 -3.000000e-01 7.131953e-01 7.131953e-01 3.565976e-01 -7.131953e-01 -4.000000e+00 -3.000000e-01 7.248431e-01 7.248431e-01 3.624216e-01 -7.248431e-01 -3.900000e+00 -3.000000e-01 7.363866e-01 7.363866e-01 3.681933e-01 -7.363866e-01 -3.800000e+00 -3.000000e-01 7.478147e-01 7.478147e-01 3.739074e-01 -7.478147e-01 -3.700000e+00 -3.000000e-01 7.591165e-01 7.591165e-01 3.795583e-01 -7.591165e-01 -3.600000e+00 -3.000000e-01 7.702810e-01 7.702810e-01 3.851405e-01 -7.702810e-01 -3.500000e+00 -3.000000e-01 7.812970e-01 7.812970e-01 3.906485e-01 -7.812970e-01 -3.400000e+00 -3.000000e-01 7.921535e-01 7.921535e-01 3.960768e-01 -7.921535e-01 -3.300000e+00 -3.000000e-01 8.028399e-01 8.028399e-01 4.014199e-01 -8.028399e-01 -3.200000e+00 -3.000000e-01 8.133450e-01 8.133450e-01 4.066725e-01 -8.133450e-01 -3.100000e+00 -3.000000e-01 8.236579e-01 8.236579e-01 4.118289e-01 -8.236579e-01 -3.000000e+00 -3.000000e-01 8.337681e-01 8.337681e-01 4.168840e-01 -8.337681e-01 -2.900000e+00 -3.000000e-01 8.436648e-01 8.436648e-01 4.218324e-01 -8.436648e-01 -2.800000e+00 -3.000000e-01 8.533376e-01 8.533376e-01 4.266688e-01 -8.533376e-01 -2.700000e+00 -3.000000e-01 8.627762e-01 8.627762e-01 4.313881e-01 -8.627762e-01 -2.600000e+00 -3.000000e-01 8.719702e-01 8.719702e-01 4.359851e-01 -8.719702e-01 -2.500000e+00 -3.000000e-01 8.809099e-01 8.809099e-01 4.404549e-01 -8.809099e-01 -2.400000e+00 -3.000000e-01 8.895852e-01 8.895852e-01 4.447926e-01 -8.895852e-01 -2.300000e+00 -3.000000e-01 8.979867e-01 8.979867e-01 4.489934e-01 -8.979867e-01 -2.200000e+00 -3.000000e-01 9.061051e-01 9.061051e-01 4.530526e-01 -9.061051e-01 -2.100000e+00 -3.000000e-01 9.139312e-01 9.139312e-01 4.569656e-01 -9.139312e-01 -2.000000e+00 -3.000000e-01 9.214562e-01 9.214562e-01 4.607281e-01 -9.214562e-01 -1.900000e+00 -3.000000e-01 9.286717e-01 9.286717e-01 4.643359e-01 -9.286717e-01 -1.800000e+00 -3.000000e-01 9.355693e-01 9.355693e-01 4.677847e-01 -9.355693e-01 -1.700000e+00 -3.000000e-01 9.421413e-01 9.421413e-01 4.710706e-01 -9.421413e-01 -1.600000e+00 -3.000000e-01 9.483800e-01 9.483800e-01 4.741900e-01 -9.483800e-01 -1.500000e+00 -3.000000e-01 9.542782e-01 9.542782e-01 4.771391e-01 -9.542782e-01 -1.400000e+00 -3.000000e-01 9.598292e-01 9.598292e-01 4.799146e-01 -9.598292e-01 -1.300000e+00 -3.000000e-01 9.650262e-01 9.650262e-01 4.825131e-01 -9.650262e-01 -1.200000e+00 -3.000000e-01 9.698634e-01 9.698634e-01 4.849317e-01 -9.698634e-01 -1.100000e+00 -3.000000e-01 9.743351e-01 9.743351e-01 4.871675e-01 -9.743351e-01 -1.000000e+00 -3.000000e-01 9.784359e-01 9.784359e-01 4.892179e-01 -9.784359e-01 -9.000000e-01 -3.000000e-01 9.821610e-01 9.821610e-01 4.910805e-01 -9.821610e-01 -8.000000e-01 -3.000000e-01 9.855061e-01 9.855061e-01 4.927530e-01 -9.855061e-01 -7.000000e-01 -3.000000e-01 9.884670e-01 9.884670e-01 4.942335e-01 -9.884670e-01 -6.000000e-01 -3.000000e-01 9.910403e-01 9.910403e-01 4.955202e-01 -9.910403e-01 -5.000000e-01 -3.000000e-01 9.932231e-01 9.932231e-01 4.966115e-01 -9.932231e-01 -4.000000e-01 -3.000000e-01 9.950125e-01 9.950125e-01 4.975062e-01 -9.950125e-01 -3.000000e-01 -3.000000e-01 9.964065e-01 9.964065e-01 4.982032e-01 -9.964065e-01 -2.000000e-01 -3.000000e-01 9.974034e-01 9.974034e-01 4.987017e-01 -9.974034e-01 -1.000000e-01 -3.000000e-01 9.980020e-01 9.980020e-01 4.990010e-01 -9.980020e-01 0.000000e+00 -3.000000e-01 9.982016e-01 9.982016e-01 4.991008e-01 -9.982016e-01 1.000000e-01 -3.000000e-01 9.980020e-01 9.980020e-01 4.990010e-01 -9.980020e-01 2.000000e-01 -3.000000e-01 9.974034e-01 9.974034e-01 4.987017e-01 -9.974034e-01 3.000000e-01 -3.000000e-01 9.964065e-01 9.964065e-01 4.982032e-01 -9.964065e-01 4.000000e-01 -3.000000e-01 9.950125e-01 9.950125e-01 4.975062e-01 -9.950125e-01 5.000000e-01 -3.000000e-01 9.932231e-01 9.932231e-01 4.966115e-01 -9.932231e-01 6.000000e-01 -3.000000e-01 9.910403e-01 9.910403e-01 4.955202e-01 -9.910403e-01 7.000000e-01 -3.000000e-01 9.884670e-01 9.884670e-01 4.942335e-01 -9.884670e-01 8.000000e-01 -3.000000e-01 9.855061e-01 9.855061e-01 4.927530e-01 -9.855061e-01 9.000000e-01 -3.000000e-01 9.821610e-01 9.821610e-01 4.910805e-01 -9.821610e-01 1.000000e+00 -3.000000e-01 9.784359e-01 9.784359e-01 4.892179e-01 -9.784359e-01 1.100000e+00 -3.000000e-01 9.743351e-01 9.743351e-01 4.871675e-01 -9.743351e-01 1.200000e+00 -3.000000e-01 9.698634e-01 9.698634e-01 4.849317e-01 -9.698634e-01 1.300000e+00 -3.000000e-01 9.650262e-01 9.650262e-01 4.825131e-01 -9.650262e-01 1.400000e+00 -3.000000e-01 9.598292e-01 9.598292e-01 4.799146e-01 -9.598292e-01 1.500000e+00 -3.000000e-01 9.542782e-01 9.542782e-01 4.771391e-01 -9.542782e-01 1.600000e+00 -3.000000e-01 9.483800e-01 9.483800e-01 4.741900e-01 -9.483800e-01 1.700000e+00 -3.000000e-01 9.421413e-01 9.421413e-01 4.710706e-01 -9.421413e-01 1.800000e+00 -3.000000e-01 9.355693e-01 9.355693e-01 4.677847e-01 -9.355693e-01 1.900000e+00 -3.000000e-01 9.286717e-01 9.286717e-01 4.643359e-01 -9.286717e-01 2.000000e+00 -3.000000e-01 9.214562e-01 9.214562e-01 4.607281e-01 -9.214562e-01 2.100000e+00 -3.000000e-01 9.139312e-01 9.139312e-01 4.569656e-01 -9.139312e-01 2.200000e+00 -3.000000e-01 9.061051e-01 9.061051e-01 4.530526e-01 -9.061051e-01 2.300000e+00 -3.000000e-01 8.979867e-01 8.979867e-01 4.489934e-01 -8.979867e-01 2.400000e+00 -3.000000e-01 8.895852e-01 8.895852e-01 4.447926e-01 -8.895852e-01 2.500000e+00 -3.000000e-01 8.809099e-01 8.809099e-01 4.404549e-01 -8.809099e-01 2.600000e+00 -3.000000e-01 8.719702e-01 8.719702e-01 4.359851e-01 -8.719702e-01 2.700000e+00 -3.000000e-01 8.627762e-01 8.627762e-01 4.313881e-01 -8.627762e-01 2.800000e+00 -3.000000e-01 8.533376e-01 8.533376e-01 4.266688e-01 -8.533376e-01 2.900000e+00 -3.000000e-01 8.436648e-01 8.436648e-01 4.218324e-01 -8.436648e-01 3.000000e+00 -3.000000e-01 8.337681e-01 8.337681e-01 4.168840e-01 -8.337681e-01 3.100000e+00 -3.000000e-01 8.236579e-01 8.236579e-01 4.118289e-01 -8.236579e-01 3.200000e+00 -3.000000e-01 8.133450e-01 8.133450e-01 4.066725e-01 -8.133450e-01 3.300000e+00 -3.000000e-01 8.028399e-01 8.028399e-01 4.014199e-01 -8.028399e-01 3.400000e+00 -3.000000e-01 7.921535e-01 7.921535e-01 3.960768e-01 -7.921535e-01 3.500000e+00 -3.000000e-01 7.812970e-01 7.812970e-01 3.906485e-01 -7.812970e-01 3.600000e+00 -3.000000e-01 7.702810e-01 7.702810e-01 3.851405e-01 -7.702810e-01 3.700000e+00 -3.000000e-01 7.591165e-01 7.591165e-01 3.795583e-01 -7.591165e-01 3.800000e+00 -3.000000e-01 7.478147e-01 7.478147e-01 3.739074e-01 -7.478147e-01 3.900000e+00 -3.000000e-01 7.363866e-01 7.363866e-01 3.681933e-01 -7.363866e-01 4.000000e+00 -3.000000e-01 7.248431e-01 7.248431e-01 3.624216e-01 -7.248431e-01 4.100000e+00 -3.000000e-01 7.131953e-01 7.131953e-01 3.565976e-01 -7.131953e-01 4.200000e+00 -3.000000e-01 7.014540e-01 7.014540e-01 3.507270e-01 -7.014540e-01 4.300000e+00 -3.000000e-01 6.896300e-01 6.896300e-01 3.448150e-01 -6.896300e-01 4.400000e+00 -3.000000e-01 6.777343e-01 6.777343e-01 3.388671e-01 -6.777343e-01 4.500000e+00 -3.000000e-01 6.657773e-01 6.657773e-01 3.328887e-01 -6.657773e-01 4.600000e+00 -3.000000e-01 6.537698e-01 6.537698e-01 3.268849e-01 -6.537698e-01 4.700000e+00 -3.000000e-01 6.417221e-01 6.417221e-01 3.208610e-01 -6.417221e-01 4.800000e+00 -3.000000e-01 6.296445e-01 6.296445e-01 3.148222e-01 -6.296445e-01 4.900000e+00 -3.000000e-01 6.175470e-01 6.175470e-01 3.087735e-01 -6.175470e-01 -5.000000e+00 -2.000000e-01 6.060456e-01 6.060456e-01 3.030228e-01 -6.060456e-01 -4.900000e+00 -2.000000e-01 6.181649e-01 6.181649e-01 3.090824e-01 -6.181649e-01 -4.800000e+00 -2.000000e-01 6.302744e-01 6.302744e-01 3.151372e-01 -6.302744e-01 -4.700000e+00 -2.000000e-01 6.423641e-01 6.423641e-01 3.211821e-01 -6.423641e-01 -4.600000e+00 -2.000000e-01 6.544239e-01 6.544239e-01 3.272119e-01 -6.544239e-01 -4.500000e+00 -2.000000e-01 6.664435e-01 6.664435e-01 3.332217e-01 -6.664435e-01 -4.400000e+00 -2.000000e-01 6.784123e-01 6.784123e-01 3.392062e-01 -6.784123e-01 -4.300000e+00 -2.000000e-01 6.903200e-01 6.903200e-01 3.451600e-01 -6.903200e-01 -4.200000e+00 -2.000000e-01 7.021558e-01 7.021558e-01 3.510779e-01 -7.021558e-01 -4.100000e+00 -2.000000e-01 7.139089e-01 7.139089e-01 3.569544e-01 -7.139089e-01 -4.000000e+00 -2.000000e-01 7.255683e-01 7.255683e-01 3.627841e-01 -7.255683e-01 -3.900000e+00 -2.000000e-01 7.371234e-01 7.371234e-01 3.685617e-01 -7.371234e-01 -3.800000e+00 -2.000000e-01 7.485629e-01 7.485629e-01 3.742815e-01 -7.485629e-01 -3.700000e+00 -2.000000e-01 7.598760e-01 7.598760e-01 3.799380e-01 -7.598760e-01 -3.600000e+00 -2.000000e-01 7.710516e-01 7.710516e-01 3.855258e-01 -7.710516e-01 -3.500000e+00 -2.000000e-01 7.820786e-01 7.820786e-01 3.910393e-01 -7.820786e-01 -3.400000e+00 -2.000000e-01 7.929461e-01 7.929461e-01 3.964731e-01 -7.929461e-01 -3.300000e+00 -2.000000e-01 8.036431e-01 8.036431e-01 4.018216e-01 -8.036431e-01 -3.200000e+00 -2.000000e-01 8.141587e-01 8.141587e-01 4.070793e-01 -8.141587e-01 -3.100000e+00 -2.000000e-01 8.244820e-01 8.244820e-01 4.122410e-01 -8.244820e-01 -3.000000e+00 -2.000000e-01 8.346022e-01 8.346022e-01 4.173011e-01 -8.346022e-01 -2.900000e+00 -2.000000e-01 8.445089e-01 8.445089e-01 4.222544e-01 -8.445089e-01 -2.800000e+00 -2.000000e-01 8.541914e-01 8.541914e-01 4.270957e-01 -8.541914e-01 -2.700000e+00 -2.000000e-01 8.636394e-01 8.636394e-01 4.318197e-01 -8.636394e-01 -2.600000e+00 -2.000000e-01 8.728426e-01 8.728426e-01 4.364213e-01 -8.728426e-01 -2.500000e+00 -2.000000e-01 8.817912e-01 8.817912e-01 4.408956e-01 -8.817912e-01 -2.400000e+00 -2.000000e-01 8.904752e-01 8.904752e-01 4.452376e-01 -8.904752e-01 -2.300000e+00 -2.000000e-01 8.988852e-01 8.988852e-01 4.494426e-01 -8.988852e-01 -2.200000e+00 -2.000000e-01 9.070116e-01 9.070116e-01 4.535058e-01 -9.070116e-01 -2.100000e+00 -2.000000e-01 9.148456e-01 9.148456e-01 4.574228e-01 -9.148456e-01 -2.000000e+00 -2.000000e-01 9.223781e-01 9.223781e-01 4.611891e-01 -9.223781e-01 -1.900000e+00 -2.000000e-01 9.296008e-01 9.296008e-01 4.648004e-01 -9.296008e-01 -1.800000e+00 -2.000000e-01 9.365054e-01 9.365054e-01 4.682527e-01 -9.365054e-01 -1.700000e+00 -2.000000e-01 9.430839e-01 9.430839e-01 4.715420e-01 -9.430839e-01 -1.600000e+00 -2.000000e-01 9.493288e-01 9.493288e-01 4.746644e-01 -9.493288e-01 -1.500000e+00 -2.000000e-01 9.552330e-01 9.552330e-01 4.776165e-01 -9.552330e-01 -1.400000e+00 -2.000000e-01 9.607894e-01 9.607894e-01 4.803947e-01 -9.607894e-01 -1.300000e+00 -2.000000e-01 9.659917e-01 9.659917e-01 4.829959e-01 -9.659917e-01 -1.200000e+00 -2.000000e-01 9.708338e-01 9.708338e-01 4.854169e-01 -9.708338e-01 -1.100000e+00 -2.000000e-01 9.753099e-01 9.753099e-01 4.876550e-01 -9.753099e-01 -1.000000e+00 -2.000000e-01 9.794148e-01 9.794148e-01 4.897074e-01 -9.794148e-01 -9.000000e-01 -2.000000e-01 9.831437e-01 9.831437e-01 4.915718e-01 -9.831437e-01 -8.000000e-01 -2.000000e-01 9.864920e-01 9.864920e-01 4.932460e-01 -9.864920e-01 -7.000000e-01 -2.000000e-01 9.894560e-01 9.894560e-01 4.947280e-01 -9.894560e-01 -6.000000e-01 -2.000000e-01 9.920319e-01 9.920319e-01 4.960160e-01 -9.920319e-01 -5.000000e-01 -2.000000e-01 9.942168e-01 9.942168e-01 4.971084e-01 -9.942168e-01 -4.000000e-01 -2.000000e-01 9.960080e-01 9.960080e-01 4.980040e-01 -9.960080e-01 -3.000000e-01 -2.000000e-01 9.974034e-01 9.974034e-01 4.987017e-01 -9.974034e-01 -2.000000e-01 -2.000000e-01 9.984013e-01 9.984013e-01 4.992006e-01 -9.984013e-01 -1.000000e-01 -2.000000e-01 9.990005e-01 9.990005e-01 4.995002e-01 -9.990005e-01 0.000000e+00 -2.000000e-01 9.992003e-01 9.992003e-01 4.996002e-01 -9.992003e-01 1.000000e-01 -2.000000e-01 9.990005e-01 9.990005e-01 4.995002e-01 -9.990005e-01 2.000000e-01 -2.000000e-01 9.984013e-01 9.984013e-01 4.992006e-01 -9.984013e-01 3.000000e-01 -2.000000e-01 9.974034e-01 9.974034e-01 4.987017e-01 -9.974034e-01 4.000000e-01 -2.000000e-01 9.960080e-01 9.960080e-01 4.980040e-01 -9.960080e-01 5.000000e-01 -2.000000e-01 9.942168e-01 9.942168e-01 4.971084e-01 -9.942168e-01 6.000000e-01 -2.000000e-01 9.920319e-01 9.920319e-01 4.960160e-01 -9.920319e-01 7.000000e-01 -2.000000e-01 9.894560e-01 9.894560e-01 4.947280e-01 -9.894560e-01 8.000000e-01 -2.000000e-01 9.864920e-01 9.864920e-01 4.932460e-01 -9.864920e-01 9.000000e-01 -2.000000e-01 9.831437e-01 9.831437e-01 4.915718e-01 -9.831437e-01 1.000000e+00 -2.000000e-01 9.794148e-01 9.794148e-01 4.897074e-01 -9.794148e-01 1.100000e+00 -2.000000e-01 9.753099e-01 9.753099e-01 4.876550e-01 -9.753099e-01 1.200000e+00 -2.000000e-01 9.708338e-01 9.708338e-01 4.854169e-01 -9.708338e-01 1.300000e+00 -2.000000e-01 9.659917e-01 9.659917e-01 4.829959e-01 -9.659917e-01 1.400000e+00 -2.000000e-01 9.607894e-01 9.607894e-01 4.803947e-01 -9.607894e-01 1.500000e+00 -2.000000e-01 9.552330e-01 9.552330e-01 4.776165e-01 -9.552330e-01 1.600000e+00 -2.000000e-01 9.493288e-01 9.493288e-01 4.746644e-01 -9.493288e-01 1.700000e+00 -2.000000e-01 9.430839e-01 9.430839e-01 4.715420e-01 -9.430839e-01 1.800000e+00 -2.000000e-01 9.365054e-01 9.365054e-01 4.682527e-01 -9.365054e-01 1.900000e+00 -2.000000e-01 9.296008e-01 9.296008e-01 4.648004e-01 -9.296008e-01 2.000000e+00 -2.000000e-01 9.223781e-01 9.223781e-01 4.611891e-01 -9.223781e-01 2.100000e+00 -2.000000e-01 9.148456e-01 9.148456e-01 4.574228e-01 -9.148456e-01 2.200000e+00 -2.000000e-01 9.070116e-01 9.070116e-01 4.535058e-01 -9.070116e-01 2.300000e+00 -2.000000e-01 8.988852e-01 8.988852e-01 4.494426e-01 -8.988852e-01 2.400000e+00 -2.000000e-01 8.904752e-01 8.904752e-01 4.452376e-01 -8.904752e-01 2.500000e+00 -2.000000e-01 8.817912e-01 8.817912e-01 4.408956e-01 -8.817912e-01 2.600000e+00 -2.000000e-01 8.728426e-01 8.728426e-01 4.364213e-01 -8.728426e-01 2.700000e+00 -2.000000e-01 8.636394e-01 8.636394e-01 4.318197e-01 -8.636394e-01 2.800000e+00 -2.000000e-01 8.541914e-01 8.541914e-01 4.270957e-01 -8.541914e-01 2.900000e+00 -2.000000e-01 8.445089e-01 8.445089e-01 4.222544e-01 -8.445089e-01 3.000000e+00 -2.000000e-01 8.346022e-01 8.346022e-01 4.173011e-01 -8.346022e-01 3.100000e+00 -2.000000e-01 8.244820e-01 8.244820e-01 4.122410e-01 -8.244820e-01 3.200000e+00 -2.000000e-01 8.141587e-01 8.141587e-01 4.070793e-01 -8.141587e-01 3.300000e+00 -2.000000e-01 8.036431e-01 8.036431e-01 4.018216e-01 -8.036431e-01 3.400000e+00 -2.000000e-01 7.929461e-01 7.929461e-01 3.964731e-01 -7.929461e-01 3.500000e+00 -2.000000e-01 7.820786e-01 7.820786e-01 3.910393e-01 -7.820786e-01 3.600000e+00 -2.000000e-01 7.710516e-01 7.710516e-01 3.855258e-01 -7.710516e-01 3.700000e+00 -2.000000e-01 7.598760e-01 7.598760e-01 3.799380e-01 -7.598760e-01 3.800000e+00 -2.000000e-01 7.485629e-01 7.485629e-01 3.742815e-01 -7.485629e-01 3.900000e+00 -2.000000e-01 7.371234e-01 7.371234e-01 3.685617e-01 -7.371234e-01 4.000000e+00 -2.000000e-01 7.255683e-01 7.255683e-01 3.627841e-01 -7.255683e-01 4.100000e+00 -2.000000e-01 7.139089e-01 7.139089e-01 3.569544e-01 -7.139089e-01 4.200000e+00 -2.000000e-01 7.021558e-01 7.021558e-01 3.510779e-01 -7.021558e-01 4.300000e+00 -2.000000e-01 6.903200e-01 6.903200e-01 3.451600e-01 -6.903200e-01 4.400000e+00 -2.000000e-01 6.784123e-01 6.784123e-01 3.392062e-01 -6.784123e-01 4.500000e+00 -2.000000e-01 6.664435e-01 6.664435e-01 3.332217e-01 -6.664435e-01 4.600000e+00 -2.000000e-01 6.544239e-01 6.544239e-01 3.272119e-01 -6.544239e-01 4.700000e+00 -2.000000e-01 6.423641e-01 6.423641e-01 3.211821e-01 -6.423641e-01 4.800000e+00 -2.000000e-01 6.302744e-01 6.302744e-01 3.151372e-01 -6.302744e-01 4.900000e+00 -2.000000e-01 6.181649e-01 6.181649e-01 3.090824e-01 -6.181649e-01 -5.000000e+00 -1.000000e-01 6.064094e-01 6.064094e-01 3.032047e-01 -6.064094e-01 -4.900000e+00 -1.000000e-01 6.185359e-01 6.185359e-01 3.092680e-01 -6.185359e-01 -4.800000e+00 -1.000000e-01 6.306527e-01 6.306527e-01 3.153263e-01 -6.306527e-01 -4.700000e+00 -1.000000e-01 6.427497e-01 6.427497e-01 3.213748e-01 -6.427497e-01 -4.600000e+00 -1.000000e-01 6.548167e-01 6.548167e-01 3.274083e-01 -6.548167e-01 -4.500000e+00 -1.000000e-01 6.668435e-01 6.668435e-01 3.334217e-01 -6.668435e-01 -4.400000e+00 -1.000000e-01 6.788195e-01 6.788195e-01 3.394098e-01 -6.788195e-01 -4.300000e+00 -1.000000e-01 6.907343e-01 6.907343e-01 3.453672e-01 -6.907343e-01 -4.200000e+00 -1.000000e-01 7.025772e-01 7.025772e-01 3.512886e-01 -7.025772e-01 -4.100000e+00 -1.000000e-01 7.143373e-01 7.143373e-01 3.571686e-01 -7.143373e-01 -4.000000e+00 -1.000000e-01 7.260038e-01 7.260038e-01 3.630019e-01 -7.260038e-01 -3.900000e+00 -1.000000e-01 7.375658e-01 7.375658e-01 3.687829e-01 -7.375658e-01 -3.800000e+00 -1.000000e-01 7.490122e-01 7.490122e-01 3.745061e-01 -7.490122e-01 -3.700000e+00 -1.000000e-01 7.603320e-01 7.603320e-01 3.801660e-01 -7.603320e-01 -3.600000e+00 -1.000000e-01 7.715144e-01 7.715144e-01 3.857572e-01 -7.715144e-01 -3.500000e+00 -1.000000e-01 7.825480e-01 7.825480e-01 3.912740e-01 -7.825480e-01 -3.400000e+00 -1.000000e-01 7.934220e-01 7.934220e-01 3.967110e-01 -7.934220e-01 -3.300000e+00 -1.000000e-01 8.041254e-01 8.041254e-01 4.020627e-01 -8.041254e-01 -3.200000e+00 -1.000000e-01 8.146473e-01 8.146473e-01 4.073237e-01 -8.146473e-01 -3.100000e+00 -1.000000e-01 8.249768e-01 8.249768e-01 4.124884e-01 -8.249768e-01 -3.000000e+00 -1.000000e-01 8.351032e-01 8.351032e-01 4.175516e-01 -8.351032e-01 -2.900000e+00 -1.000000e-01 8.450157e-01 8.450157e-01 4.225079e-01 -8.450157e-01 -2.800000e+00 -1.000000e-01 8.547041e-01 8.547041e-01 4.273520e-01 -8.547041e-01 -2.700000e+00 -1.000000e-01 8.641577e-01 8.641577e-01 4.320788e-01 -8.641577e-01 -2.600000e+00 -1.000000e-01 8.733665e-01 8.733665e-01 4.366832e-01 -8.733665e-01 -2.500000e+00 -1.000000e-01 8.823204e-01 8.823204e-01 4.411602e-01 -8.823204e-01 -2.400000e+00 -1.000000e-01 8.910097e-01 8.910097e-01 4.455048e-01 -8.910097e-01 -2.300000e+00 -1.000000e-01 8.994247e-01 8.994247e-01 4.497123e-01 -8.994247e-01 -2.200000e+00 -1.000000e-01 9.075560e-01 9.075560e-01 4.537780e-01 -9.075560e-01 -2.100000e+00 -1.000000e-01 9.153947e-01 9.153947e-01 4.576973e-01 -9.153947e-01 -2.000000e+00 -1.000000e-01 9.229317e-01 9.229317e-01 4.614659e-01 -9.229317e-01 -1.900000e+00 -1.000000e-01 9.301587e-01 9.301587e-01 4.650794e-01 -9.301587e-01 -1.800000e+00 -1.000000e-01 9.370674e-01 9.370674e-01 4.685337e-01 -9.370674e-01 -1.700000e+00 -1.000000e-01 9.436499e-01 9.436499e-01 4.718250e-01 -9.436499e-01 -1.600000e+00 -1.000000e-01 9.498987e-01 9.498987e-01 4.749493e-01 -9.498987e-01 -1.500000e+00 -1.000000e-01 9.558063e-01 9.558063e-01 4.779032e-01 -9.558063e-01 -1.400000e+00 -1.000000e-01 9.613661e-01 9.613661e-01 4.806830e-01 -9.613661e-01 -1.300000e+00 -1.000000e-01 9.665715e-01 9.665715e-01 4.832858e-01 -9.665715e-01 -1.200000e+00 -1.000000e-01 9.714165e-01 9.714165e-01 4.857082e-01 -9.714165e-01 -1.100000e+00 -1.000000e-01 9.758953e-01 9.758953e-01 4.879476e-01 -9.758953e-01 -1.000000e+00 -1.000000e-01 9.800026e-01 9.800026e-01 4.900013e-01 -9.800026e-01 -9.000000e-01 -1.000000e-01 9.837338e-01 9.837338e-01 4.918669e-01 -9.837338e-01 -8.000000e-01 -1.000000e-01 9.870842e-01 9.870842e-01 4.935421e-01 -9.870842e-01 -7.000000e-01 -1.000000e-01 9.900498e-01 9.900498e-01 4.950249e-01 -9.900498e-01 -6.000000e-01 -1.000000e-01 9.926273e-01 9.926273e-01 4.963137e-01 -9.926273e-01 -5.000000e-01 -1.000000e-01 9.948135e-01 9.948135e-01 4.974068e-01 -9.948135e-01 -4.000000e-01 -1.000000e-01 9.966058e-01 9.966058e-01 4.983029e-01 -9.966058e-01 -3.000000e-01 -1.000000e-01 9.980020e-01 9.980020e-01 4.990010e-01 -9.980020e-01 -2.000000e-01 -1.000000e-01 9.990005e-01 9.990005e-01 4.995002e-01 -9.990005e-01 -1.000000e-01 -1.000000e-01 9.996001e-01 9.996001e-01 4.998000e-01 -9.996001e-01 0.000000e+00 -1.000000e-01 9.998000e-01 9.998000e-01 4.999000e-01 -9.998000e-01 1.000000e-01 -1.000000e-01 9.996001e-01 9.996001e-01 4.998000e-01 -9.996001e-01 2.000000e-01 -1.000000e-01 9.990005e-01 9.990005e-01 4.995002e-01 -9.990005e-01 3.000000e-01 -1.000000e-01 9.980020e-01 9.980020e-01 4.990010e-01 -9.980020e-01 4.000000e-01 -1.000000e-01 9.966058e-01 9.966058e-01 4.983029e-01 -9.966058e-01 5.000000e-01 -1.000000e-01 9.948135e-01 9.948135e-01 4.974068e-01 -9.948135e-01 6.000000e-01 -1.000000e-01 9.926273e-01 9.926273e-01 4.963137e-01 -9.926273e-01 7.000000e-01 -1.000000e-01 9.900498e-01 9.900498e-01 4.950249e-01 -9.900498e-01 8.000000e-01 -1.000000e-01 9.870842e-01 9.870842e-01 4.935421e-01 -9.870842e-01 9.000000e-01 -1.000000e-01 9.837338e-01 9.837338e-01 4.918669e-01 -9.837338e-01 1.000000e+00 -1.000000e-01 9.800026e-01 9.800026e-01 4.900013e-01 -9.800026e-01 1.100000e+00 -1.000000e-01 9.758953e-01 9.758953e-01 4.879476e-01 -9.758953e-01 1.200000e+00 -1.000000e-01 9.714165e-01 9.714165e-01 4.857082e-01 -9.714165e-01 1.300000e+00 -1.000000e-01 9.665715e-01 9.665715e-01 4.832858e-01 -9.665715e-01 1.400000e+00 -1.000000e-01 9.613661e-01 9.613661e-01 4.806830e-01 -9.613661e-01 1.500000e+00 -1.000000e-01 9.558063e-01 9.558063e-01 4.779032e-01 -9.558063e-01 1.600000e+00 -1.000000e-01 9.498987e-01 9.498987e-01 4.749493e-01 -9.498987e-01 1.700000e+00 -1.000000e-01 9.436499e-01 9.436499e-01 4.718250e-01 -9.436499e-01 1.800000e+00 -1.000000e-01 9.370674e-01 9.370674e-01 4.685337e-01 -9.370674e-01 1.900000e+00 -1.000000e-01 9.301587e-01 9.301587e-01 4.650794e-01 -9.301587e-01 2.000000e+00 -1.000000e-01 9.229317e-01 9.229317e-01 4.614659e-01 -9.229317e-01 2.100000e+00 -1.000000e-01 9.153947e-01 9.153947e-01 4.576973e-01 -9.153947e-01 2.200000e+00 -1.000000e-01 9.075560e-01 9.075560e-01 4.537780e-01 -9.075560e-01 2.300000e+00 -1.000000e-01 8.994247e-01 8.994247e-01 4.497123e-01 -8.994247e-01 2.400000e+00 -1.000000e-01 8.910097e-01 8.910097e-01 4.455048e-01 -8.910097e-01 2.500000e+00 -1.000000e-01 8.823204e-01 8.823204e-01 4.411602e-01 -8.823204e-01 2.600000e+00 -1.000000e-01 8.733665e-01 8.733665e-01 4.366832e-01 -8.733665e-01 2.700000e+00 -1.000000e-01 8.641577e-01 8.641577e-01 4.320788e-01 -8.641577e-01 2.800000e+00 -1.000000e-01 8.547041e-01 8.547041e-01 4.273520e-01 -8.547041e-01 2.900000e+00 -1.000000e-01 8.450157e-01 8.450157e-01 4.225079e-01 -8.450157e-01 3.000000e+00 -1.000000e-01 8.351032e-01 8.351032e-01 4.175516e-01 -8.351032e-01 3.100000e+00 -1.000000e-01 8.249768e-01 8.249768e-01 4.124884e-01 -8.249768e-01 3.200000e+00 -1.000000e-01 8.146473e-01 8.146473e-01 4.073237e-01 -8.146473e-01 3.300000e+00 -1.000000e-01 8.041254e-01 8.041254e-01 4.020627e-01 -8.041254e-01 3.400000e+00 -1.000000e-01 7.934220e-01 7.934220e-01 3.967110e-01 -7.934220e-01 3.500000e+00 -1.000000e-01 7.825480e-01 7.825480e-01 3.912740e-01 -7.825480e-01 3.600000e+00 -1.000000e-01 7.715144e-01 7.715144e-01 3.857572e-01 -7.715144e-01 3.700000e+00 -1.000000e-01 7.603320e-01 7.603320e-01 3.801660e-01 -7.603320e-01 3.800000e+00 -1.000000e-01 7.490122e-01 7.490122e-01 3.745061e-01 -7.490122e-01 3.900000e+00 -1.000000e-01 7.375658e-01 7.375658e-01 3.687829e-01 -7.375658e-01 4.000000e+00 -1.000000e-01 7.260038e-01 7.260038e-01 3.630019e-01 -7.260038e-01 4.100000e+00 -1.000000e-01 7.143373e-01 7.143373e-01 3.571686e-01 -7.143373e-01 4.200000e+00 -1.000000e-01 7.025772e-01 7.025772e-01 3.512886e-01 -7.025772e-01 4.300000e+00 -1.000000e-01 6.907343e-01 6.907343e-01 3.453672e-01 -6.907343e-01 4.400000e+00 -1.000000e-01 6.788195e-01 6.788195e-01 3.394098e-01 -6.788195e-01 4.500000e+00 -1.000000e-01 6.668435e-01 6.668435e-01 3.334217e-01 -6.668435e-01 4.600000e+00 -1.000000e-01 6.548167e-01 6.548167e-01 3.274083e-01 -6.548167e-01 4.700000e+00 -1.000000e-01 6.427497e-01 6.427497e-01 3.213748e-01 -6.427497e-01 4.800000e+00 -1.000000e-01 6.306527e-01 6.306527e-01 3.153263e-01 -6.306527e-01 4.900000e+00 -1.000000e-01 6.185359e-01 6.185359e-01 3.092680e-01 -6.185359e-01 -5.000000e+00 0.000000e+00 6.065307e-01 6.065307e-01 3.032653e-01 -6.065307e-01 -4.900000e+00 0.000000e+00 6.186596e-01 6.186596e-01 3.093298e-01 -6.186596e-01 -4.800000e+00 0.000000e+00 6.307788e-01 6.307788e-01 3.153894e-01 -6.307788e-01 -4.700000e+00 0.000000e+00 6.428782e-01 6.428782e-01 3.214391e-01 -6.428782e-01 -4.600000e+00 0.000000e+00 6.549476e-01 6.549476e-01 3.274738e-01 -6.549476e-01 -4.500000e+00 0.000000e+00 6.669768e-01 6.669768e-01 3.334884e-01 -6.669768e-01 -4.400000e+00 0.000000e+00 6.789553e-01 6.789553e-01 3.394777e-01 -6.789553e-01 -4.300000e+00 0.000000e+00 6.908725e-01 6.908725e-01 3.454362e-01 -6.908725e-01 -4.200000e+00 0.000000e+00 7.027177e-01 7.027177e-01 3.513589e-01 -7.027177e-01 -4.100000e+00 0.000000e+00 7.144802e-01 7.144802e-01 3.572401e-01 -7.144802e-01 -4.000000e+00 0.000000e+00 7.261490e-01 7.261490e-01 3.630745e-01 -7.261490e-01 -3.900000e+00 0.000000e+00 7.377133e-01 7.377133e-01 3.688566e-01 -7.377133e-01 -3.800000e+00 0.000000e+00 7.491620e-01 7.491620e-01 3.745810e-01 -7.491620e-01 -3.700000e+00 0.000000e+00 7.604842e-01 7.604842e-01 3.802421e-01 -7.604842e-01 -3.600000e+00 0.000000e+00 7.716687e-01 7.716687e-01 3.858343e-01 -7.716687e-01 -3.500000e+00 0.000000e+00 7.827045e-01 7.827045e-01 3.913523e-01 -7.827045e-01 -3.400000e+00 0.000000e+00 7.935807e-01 7.935807e-01 3.967904e-01 -7.935807e-01 -3.300000e+00 0.000000e+00 8.042863e-01 8.042863e-01 4.021432e-01 -8.042863e-01 -3.200000e+00 0.000000e+00 8.148103e-01 8.148103e-01 4.074051e-01 -8.148103e-01 -3.100000e+00 0.000000e+00 8.251418e-01 8.251418e-01 4.125709e-01 -8.251418e-01 -3.000000e+00 0.000000e+00 8.352702e-01 8.352702e-01 4.176351e-01 -8.352702e-01 -2.900000e+00 0.000000e+00 8.451847e-01 8.451847e-01 4.225924e-01 -8.451847e-01 -2.800000e+00 0.000000e+00 8.548750e-01 8.548750e-01 4.274375e-01 -8.548750e-01 -2.700000e+00 0.000000e+00 8.643305e-01 8.643305e-01 4.321653e-01 -8.643305e-01 -2.600000e+00 0.000000e+00 8.735412e-01 8.735412e-01 4.367706e-01 -8.735412e-01 -2.500000e+00 0.000000e+00 8.824969e-01 8.824969e-01 4.412484e-01 -8.824969e-01 -2.400000e+00 0.000000e+00 8.911879e-01 8.911879e-01 4.455940e-01 -8.911879e-01 -2.300000e+00 0.000000e+00 8.996046e-01 8.996046e-01 4.498023e-01 -8.996046e-01 -2.200000e+00 0.000000e+00 9.077376e-01 9.077376e-01 4.538688e-01 -9.077376e-01 -2.100000e+00 0.000000e+00 9.155778e-01 9.155778e-01 4.577889e-01 -9.155778e-01 -2.000000e+00 0.000000e+00 9.231163e-01 9.231163e-01 4.615582e-01 -9.231163e-01 -1.900000e+00 0.000000e+00 9.303448e-01 9.303448e-01 4.651724e-01 -9.303448e-01 -1.800000e+00 0.000000e+00 9.372549e-01 9.372549e-01 4.686275e-01 -9.372549e-01 -1.700000e+00 0.000000e+00 9.438387e-01 9.438387e-01 4.719194e-01 -9.438387e-01 -1.600000e+00 0.000000e+00 9.500886e-01 9.500886e-01 4.750443e-01 -9.500886e-01 -1.500000e+00 0.000000e+00 9.559975e-01 9.559975e-01 4.779987e-01 -9.559975e-01 -1.400000e+00 0.000000e+00 9.615584e-01 9.615584e-01 4.807792e-01 -9.615584e-01 -1.300000e+00 0.000000e+00 9.667649e-01 9.667649e-01 4.833824e-01 -9.667649e-01 -1.200000e+00 0.000000e+00 9.716108e-01 9.716108e-01 4.858054e-01 -9.716108e-01 -1.100000e+00 0.000000e+00 9.760905e-01 9.760905e-01 4.880452e-01 -9.760905e-01 -1.000000e+00 0.000000e+00 9.801987e-01 9.801987e-01 4.900993e-01 -9.801987e-01 -9.000000e-01 0.000000e+00 9.839305e-01 9.839305e-01 4.919653e-01 -9.839305e-01 -8.000000e-01 0.000000e+00 9.872816e-01 9.872816e-01 4.936408e-01 -9.872816e-01 -7.000000e-01 0.000000e+00 9.902478e-01 9.902478e-01 4.951239e-01 -9.902478e-01 -6.000000e-01 0.000000e+00 9.928259e-01 9.928259e-01 4.964129e-01 -9.928259e-01 -5.000000e-01 0.000000e+00 9.950125e-01 9.950125e-01 4.975062e-01 -9.950125e-01 -4.000000e-01 0.000000e+00 9.968051e-01 9.968051e-01 4.984026e-01 -9.968051e-01 -3.000000e-01 0.000000e+00 9.982016e-01 9.982016e-01 4.991008e-01 -9.982016e-01 -2.000000e-01 0.000000e+00 9.992003e-01 9.992003e-01 4.996002e-01 -9.992003e-01 -1.000000e-01 0.000000e+00 9.998000e-01 9.998000e-01 4.999000e-01 -9.998000e-01 0.000000e+00 0.000000e+00 1.000000e+00 1.000000e+00 5.000000e-01 -1.000000e+00 1.000000e-01 0.000000e+00 9.998000e-01 9.998000e-01 4.999000e-01 -9.998000e-01 2.000000e-01 0.000000e+00 9.992003e-01 9.992003e-01 4.996002e-01 -9.992003e-01 3.000000e-01 0.000000e+00 9.982016e-01 9.982016e-01 4.991008e-01 -9.982016e-01 4.000000e-01 0.000000e+00 9.968051e-01 9.968051e-01 4.984026e-01 -9.968051e-01 5.000000e-01 0.000000e+00 9.950125e-01 9.950125e-01 4.975062e-01 -9.950125e-01 6.000000e-01 0.000000e+00 9.928259e-01 9.928259e-01 4.964129e-01 -9.928259e-01 7.000000e-01 0.000000e+00 9.902478e-01 9.902478e-01 4.951239e-01 -9.902478e-01 8.000000e-01 0.000000e+00 9.872816e-01 9.872816e-01 4.936408e-01 -9.872816e-01 9.000000e-01 0.000000e+00 9.839305e-01 9.839305e-01 4.919653e-01 -9.839305e-01 1.000000e+00 0.000000e+00 9.801987e-01 9.801987e-01 4.900993e-01 -9.801987e-01 1.100000e+00 0.000000e+00 9.760905e-01 9.760905e-01 4.880452e-01 -9.760905e-01 1.200000e+00 0.000000e+00 9.716108e-01 9.716108e-01 4.858054e-01 -9.716108e-01 1.300000e+00 0.000000e+00 9.667649e-01 9.667649e-01 4.833824e-01 -9.667649e-01 1.400000e+00 0.000000e+00 9.615584e-01 9.615584e-01 4.807792e-01 -9.615584e-01 1.500000e+00 0.000000e+00 9.559975e-01 9.559975e-01 4.779987e-01 -9.559975e-01 1.600000e+00 0.000000e+00 9.500886e-01 9.500886e-01 4.750443e-01 -9.500886e-01 1.700000e+00 0.000000e+00 9.438387e-01 9.438387e-01 4.719194e-01 -9.438387e-01 1.800000e+00 0.000000e+00 9.372549e-01 9.372549e-01 4.686275e-01 -9.372549e-01 1.900000e+00 0.000000e+00 9.303448e-01 9.303448e-01 4.651724e-01 -9.303448e-01 2.000000e+00 0.000000e+00 9.231163e-01 9.231163e-01 4.615582e-01 -9.231163e-01 2.100000e+00 0.000000e+00 9.155778e-01 9.155778e-01 4.577889e-01 -9.155778e-01 2.200000e+00 0.000000e+00 9.077376e-01 9.077376e-01 4.538688e-01 -9.077376e-01 2.300000e+00 0.000000e+00 8.996046e-01 8.996046e-01 4.498023e-01 -8.996046e-01 2.400000e+00 0.000000e+00 8.911879e-01 8.911879e-01 4.455940e-01 -8.911879e-01 2.500000e+00 0.000000e+00 8.824969e-01 8.824969e-01 4.412484e-01 -8.824969e-01 2.600000e+00 0.000000e+00 8.735412e-01 8.735412e-01 4.367706e-01 -8.735412e-01 2.700000e+00 0.000000e+00 8.643305e-01 8.643305e-01 4.321653e-01 -8.643305e-01 2.800000e+00 0.000000e+00 8.548750e-01 8.548750e-01 4.274375e-01 -8.548750e-01 2.900000e+00 0.000000e+00 8.451847e-01 8.451847e-01 4.225924e-01 -8.451847e-01 3.000000e+00 0.000000e+00 8.352702e-01 8.352702e-01 4.176351e-01 -8.352702e-01 3.100000e+00 0.000000e+00 8.251418e-01 8.251418e-01 4.125709e-01 -8.251418e-01 3.200000e+00 0.000000e+00 8.148103e-01 8.148103e-01 4.074051e-01 -8.148103e-01 3.300000e+00 0.000000e+00 8.042863e-01 8.042863e-01 4.021432e-01 -8.042863e-01 3.400000e+00 0.000000e+00 7.935807e-01 7.935807e-01 3.967904e-01 -7.935807e-01 3.500000e+00 0.000000e+00 7.827045e-01 7.827045e-01 3.913523e-01 -7.827045e-01 3.600000e+00 0.000000e+00 7.716687e-01 7.716687e-01 3.858343e-01 -7.716687e-01 3.700000e+00 0.000000e+00 7.604842e-01 7.604842e-01 3.802421e-01 -7.604842e-01 3.800000e+00 0.000000e+00 7.491620e-01 7.491620e-01 3.745810e-01 -7.491620e-01 3.900000e+00 0.000000e+00 7.377133e-01 7.377133e-01 3.688566e-01 -7.377133e-01 4.000000e+00 0.000000e+00 7.261490e-01 7.261490e-01 3.630745e-01 -7.261490e-01 4.100000e+00 0.000000e+00 7.144802e-01 7.144802e-01 3.572401e-01 -7.144802e-01 4.200000e+00 0.000000e+00 7.027177e-01 7.027177e-01 3.513589e-01 -7.027177e-01 4.300000e+00 0.000000e+00 6.908725e-01 6.908725e-01 3.454362e-01 -6.908725e-01 4.400000e+00 0.000000e+00 6.789553e-01 6.789553e-01 3.394777e-01 -6.789553e-01 4.500000e+00 0.000000e+00 6.669768e-01 6.669768e-01 3.334884e-01 -6.669768e-01 4.600000e+00 0.000000e+00 6.549476e-01 6.549476e-01 3.274738e-01 -6.549476e-01 4.700000e+00 0.000000e+00 6.428782e-01 6.428782e-01 3.214391e-01 -6.428782e-01 4.800000e+00 0.000000e+00 6.307788e-01 6.307788e-01 3.153894e-01 -6.307788e-01 4.900000e+00 0.000000e+00 6.186596e-01 6.186596e-01 3.093298e-01 -6.186596e-01 -5.000000e+00 1.000000e-01 6.064094e-01 6.064094e-01 3.032047e-01 -6.064094e-01 -4.900000e+00 1.000000e-01 6.185359e-01 6.185359e-01 3.092680e-01 -6.185359e-01 -4.800000e+00 1.000000e-01 6.306527e-01 6.306527e-01 3.153263e-01 -6.306527e-01 -4.700000e+00 1.000000e-01 6.427497e-01 6.427497e-01 3.213748e-01 -6.427497e-01 -4.600000e+00 1.000000e-01 6.548167e-01 6.548167e-01 3.274083e-01 -6.548167e-01 -4.500000e+00 1.000000e-01 6.668435e-01 6.668435e-01 3.334217e-01 -6.668435e-01 -4.400000e+00 1.000000e-01 6.788195e-01 6.788195e-01 3.394098e-01 -6.788195e-01 -4.300000e+00 1.000000e-01 6.907343e-01 6.907343e-01 3.453672e-01 -6.907343e-01 -4.200000e+00 1.000000e-01 7.025772e-01 7.025772e-01 3.512886e-01 -7.025772e-01 -4.100000e+00 1.000000e-01 7.143373e-01 7.143373e-01 3.571686e-01 -7.143373e-01 -4.000000e+00 1.000000e-01 7.260038e-01 7.260038e-01 3.630019e-01 -7.260038e-01 -3.900000e+00 1.000000e-01 7.375658e-01 7.375658e-01 3.687829e-01 -7.375658e-01 -3.800000e+00 1.000000e-01 7.490122e-01 7.490122e-01 3.745061e-01 -7.490122e-01 -3.700000e+00 1.000000e-01 7.603320e-01 7.603320e-01 3.801660e-01 -7.603320e-01 -3.600000e+00 1.000000e-01 7.715144e-01 7.715144e-01 3.857572e-01 -7.715144e-01 -3.500000e+00 1.000000e-01 7.825480e-01 7.825480e-01 3.912740e-01 -7.825480e-01 -3.400000e+00 1.000000e-01 7.934220e-01 7.934220e-01 3.967110e-01 -7.934220e-01 -3.300000e+00 1.000000e-01 8.041254e-01 8.041254e-01 4.020627e-01 -8.041254e-01 -3.200000e+00 1.000000e-01 8.146473e-01 8.146473e-01 4.073237e-01 -8.146473e-01 -3.100000e+00 1.000000e-01 8.249768e-01 8.249768e-01 4.124884e-01 -8.249768e-01 -3.000000e+00 1.000000e-01 8.351032e-01 8.351032e-01 4.175516e-01 -8.351032e-01 -2.900000e+00 1.000000e-01 8.450157e-01 8.450157e-01 4.225079e-01 -8.450157e-01 -2.800000e+00 1.000000e-01 8.547041e-01 8.547041e-01 4.273520e-01 -8.547041e-01 -2.700000e+00 1.000000e-01 8.641577e-01 8.641577e-01 4.320788e-01 -8.641577e-01 -2.600000e+00 1.000000e-01 8.733665e-01 8.733665e-01 4.366832e-01 -8.733665e-01 -2.500000e+00 1.000000e-01 8.823204e-01 8.823204e-01 4.411602e-01 -8.823204e-01 -2.400000e+00 1.000000e-01 8.910097e-01 8.910097e-01 4.455048e-01 -8.910097e-01 -2.300000e+00 1.000000e-01 8.994247e-01 8.994247e-01 4.497123e-01 -8.994247e-01 -2.200000e+00 1.000000e-01 9.075560e-01 9.075560e-01 4.537780e-01 -9.075560e-01 -2.100000e+00 1.000000e-01 9.153947e-01 9.153947e-01 4.576973e-01 -9.153947e-01 -2.000000e+00 1.000000e-01 9.229317e-01 9.229317e-01 4.614659e-01 -9.229317e-01 -1.900000e+00 1.000000e-01 9.301587e-01 9.301587e-01 4.650794e-01 -9.301587e-01 -1.800000e+00 1.000000e-01 9.370674e-01 9.370674e-01 4.685337e-01 -9.370674e-01 -1.700000e+00 1.000000e-01 9.436499e-01 9.436499e-01 4.718250e-01 -9.436499e-01 -1.600000e+00 1.000000e-01 9.498987e-01 9.498987e-01 4.749493e-01 -9.498987e-01 -1.500000e+00 1.000000e-01 9.558063e-01 9.558063e-01 4.779032e-01 -9.558063e-01 -1.400000e+00 1.000000e-01 9.613661e-01 9.613661e-01 4.806830e-01 -9.613661e-01 -1.300000e+00 1.000000e-01 9.665715e-01 9.665715e-01 4.832858e-01 -9.665715e-01 -1.200000e+00 1.000000e-01 9.714165e-01 9.714165e-01 4.857082e-01 -9.714165e-01 -1.100000e+00 1.000000e-01 9.758953e-01 9.758953e-01 4.879476e-01 -9.758953e-01 -1.000000e+00 1.000000e-01 9.800026e-01 9.800026e-01 4.900013e-01 -9.800026e-01 -9.000000e-01 1.000000e-01 9.837338e-01 9.837338e-01 4.918669e-01 -9.837338e-01 -8.000000e-01 1.000000e-01 9.870842e-01 9.870842e-01 4.935421e-01 -9.870842e-01 -7.000000e-01 1.000000e-01 9.900498e-01 9.900498e-01 4.950249e-01 -9.900498e-01 -6.000000e-01 1.000000e-01 9.926273e-01 9.926273e-01 4.963137e-01 -9.926273e-01 -5.000000e-01 1.000000e-01 9.948135e-01 9.948135e-01 4.974068e-01 -9.948135e-01 -4.000000e-01 1.000000e-01 9.966058e-01 9.966058e-01 4.983029e-01 -9.966058e-01 -3.000000e-01 1.000000e-01 9.980020e-01 9.980020e-01 4.990010e-01 -9.980020e-01 -2.000000e-01 1.000000e-01 9.990005e-01 9.990005e-01 4.995002e-01 -9.990005e-01 -1.000000e-01 1.000000e-01 9.996001e-01 9.996001e-01 4.998000e-01 -9.996001e-01 0.000000e+00 1.000000e-01 9.998000e-01 9.998000e-01 4.999000e-01 -9.998000e-01 1.000000e-01 1.000000e-01 9.996001e-01 9.996001e-01 4.998000e-01 -9.996001e-01 2.000000e-01 1.000000e-01 9.990005e-01 9.990005e-01 4.995002e-01 -9.990005e-01 3.000000e-01 1.000000e-01 9.980020e-01 9.980020e-01 4.990010e-01 -9.980020e-01 4.000000e-01 1.000000e-01 9.966058e-01 9.966058e-01 4.983029e-01 -9.966058e-01 5.000000e-01 1.000000e-01 9.948135e-01 9.948135e-01 4.974068e-01 -9.948135e-01 6.000000e-01 1.000000e-01 9.926273e-01 9.926273e-01 4.963137e-01 -9.926273e-01 7.000000e-01 1.000000e-01 9.900498e-01 9.900498e-01 4.950249e-01 -9.900498e-01 8.000000e-01 1.000000e-01 9.870842e-01 9.870842e-01 4.935421e-01 -9.870842e-01 9.000000e-01 1.000000e-01 9.837338e-01 9.837338e-01 4.918669e-01 -9.837338e-01 1.000000e+00 1.000000e-01 9.800026e-01 9.800026e-01 4.900013e-01 -9.800026e-01 1.100000e+00 1.000000e-01 9.758953e-01 9.758953e-01 4.879476e-01 -9.758953e-01 1.200000e+00 1.000000e-01 9.714165e-01 9.714165e-01 4.857082e-01 -9.714165e-01 1.300000e+00 1.000000e-01 9.665715e-01 9.665715e-01 4.832858e-01 -9.665715e-01 1.400000e+00 1.000000e-01 9.613661e-01 9.613661e-01 4.806830e-01 -9.613661e-01 1.500000e+00 1.000000e-01 9.558063e-01 9.558063e-01 4.779032e-01 -9.558063e-01 1.600000e+00 1.000000e-01 9.498987e-01 9.498987e-01 4.749493e-01 -9.498987e-01 1.700000e+00 1.000000e-01 9.436499e-01 9.436499e-01 4.718250e-01 -9.436499e-01 1.800000e+00 1.000000e-01 9.370674e-01 9.370674e-01 4.685337e-01 -9.370674e-01 1.900000e+00 1.000000e-01 9.301587e-01 9.301587e-01 4.650794e-01 -9.301587e-01 2.000000e+00 1.000000e-01 9.229317e-01 9.229317e-01 4.614659e-01 -9.229317e-01 2.100000e+00 1.000000e-01 9.153947e-01 9.153947e-01 4.576973e-01 -9.153947e-01 2.200000e+00 1.000000e-01 9.075560e-01 9.075560e-01 4.537780e-01 -9.075560e-01 2.300000e+00 1.000000e-01 8.994247e-01 8.994247e-01 4.497123e-01 -8.994247e-01 2.400000e+00 1.000000e-01 8.910097e-01 8.910097e-01 4.455048e-01 -8.910097e-01 2.500000e+00 1.000000e-01 8.823204e-01 8.823204e-01 4.411602e-01 -8.823204e-01 2.600000e+00 1.000000e-01 8.733665e-01 8.733665e-01 4.366832e-01 -8.733665e-01 2.700000e+00 1.000000e-01 8.641577e-01 8.641577e-01 4.320788e-01 -8.641577e-01 2.800000e+00 1.000000e-01 8.547041e-01 8.547041e-01 4.273520e-01 -8.547041e-01 2.900000e+00 1.000000e-01 8.450157e-01 8.450157e-01 4.225079e-01 -8.450157e-01 3.000000e+00 1.000000e-01 8.351032e-01 8.351032e-01 4.175516e-01 -8.351032e-01 3.100000e+00 1.000000e-01 8.249768e-01 8.249768e-01 4.124884e-01 -8.249768e-01 3.200000e+00 1.000000e-01 8.146473e-01 8.146473e-01 4.073237e-01 -8.146473e-01 3.300000e+00 1.000000e-01 8.041254e-01 8.041254e-01 4.020627e-01 -8.041254e-01 3.400000e+00 1.000000e-01 7.934220e-01 7.934220e-01 3.967110e-01 -7.934220e-01 3.500000e+00 1.000000e-01 7.825480e-01 7.825480e-01 3.912740e-01 -7.825480e-01 3.600000e+00 1.000000e-01 7.715144e-01 7.715144e-01 3.857572e-01 -7.715144e-01 3.700000e+00 1.000000e-01 7.603320e-01 7.603320e-01 3.801660e-01 -7.603320e-01 3.800000e+00 1.000000e-01 7.490122e-01 7.490122e-01 3.745061e-01 -7.490122e-01 3.900000e+00 1.000000e-01 7.375658e-01 7.375658e-01 3.687829e-01 -7.375658e-01 4.000000e+00 1.000000e-01 7.260038e-01 7.260038e-01 3.630019e-01 -7.260038e-01 4.100000e+00 1.000000e-01 7.143373e-01 7.143373e-01 3.571686e-01 -7.143373e-01 4.200000e+00 1.000000e-01 7.025772e-01 7.025772e-01 3.512886e-01 -7.025772e-01 4.300000e+00 1.000000e-01 6.907343e-01 6.907343e-01 3.453672e-01 -6.907343e-01 4.400000e+00 1.000000e-01 6.788195e-01 6.788195e-01 3.394098e-01 -6.788195e-01 4.500000e+00 1.000000e-01 6.668435e-01 6.668435e-01 3.334217e-01 -6.668435e-01 4.600000e+00 1.000000e-01 6.548167e-01 6.548167e-01 3.274083e-01 -6.548167e-01 4.700000e+00 1.000000e-01 6.427497e-01 6.427497e-01 3.213748e-01 -6.427497e-01 4.800000e+00 1.000000e-01 6.306527e-01 6.306527e-01 3.153263e-01 -6.306527e-01 4.900000e+00 1.000000e-01 6.185359e-01 6.185359e-01 3.092680e-01 -6.185359e-01 -5.000000e+00 2.000000e-01 6.060456e-01 6.060456e-01 3.030228e-01 -6.060456e-01 -4.900000e+00 2.000000e-01 6.181649e-01 6.181649e-01 3.090824e-01 -6.181649e-01 -4.800000e+00 2.000000e-01 6.302744e-01 6.302744e-01 3.151372e-01 -6.302744e-01 -4.700000e+00 2.000000e-01 6.423641e-01 6.423641e-01 3.211821e-01 -6.423641e-01 -4.600000e+00 2.000000e-01 6.544239e-01 6.544239e-01 3.272119e-01 -6.544239e-01 -4.500000e+00 2.000000e-01 6.664435e-01 6.664435e-01 3.332217e-01 -6.664435e-01 -4.400000e+00 2.000000e-01 6.784123e-01 6.784123e-01 3.392062e-01 -6.784123e-01 -4.300000e+00 2.000000e-01 6.903200e-01 6.903200e-01 3.451600e-01 -6.903200e-01 -4.200000e+00 2.000000e-01 7.021558e-01 7.021558e-01 3.510779e-01 -7.021558e-01 -4.100000e+00 2.000000e-01 7.139089e-01 7.139089e-01 3.569544e-01 -7.139089e-01 -4.000000e+00 2.000000e-01 7.255683e-01 7.255683e-01 3.627841e-01 -7.255683e-01 -3.900000e+00 2.000000e-01 7.371234e-01 7.371234e-01 3.685617e-01 -7.371234e-01 -3.800000e+00 2.000000e-01 7.485629e-01 7.485629e-01 3.742815e-01 -7.485629e-01 -3.700000e+00 2.000000e-01 7.598760e-01 7.598760e-01 3.799380e-01 -7.598760e-01 -3.600000e+00 2.000000e-01 7.710516e-01 7.710516e-01 3.855258e-01 -7.710516e-01 -3.500000e+00 2.000000e-01 7.820786e-01 7.820786e-01 3.910393e-01 -7.820786e-01 -3.400000e+00 2.000000e-01 7.929461e-01 7.929461e-01 3.964731e-01 -7.929461e-01 -3.300000e+00 2.000000e-01 8.036431e-01 8.036431e-01 4.018216e-01 -8.036431e-01 -3.200000e+00 2.000000e-01 8.141587e-01 8.141587e-01 4.070793e-01 -8.141587e-01 -3.100000e+00 2.000000e-01 8.244820e-01 8.244820e-01 4.122410e-01 -8.244820e-01 -3.000000e+00 2.000000e-01 8.346022e-01 8.346022e-01 4.173011e-01 -8.346022e-01 -2.900000e+00 2.000000e-01 8.445089e-01 8.445089e-01 4.222544e-01 -8.445089e-01 -2.800000e+00 2.000000e-01 8.541914e-01 8.541914e-01 4.270957e-01 -8.541914e-01 -2.700000e+00 2.000000e-01 8.636394e-01 8.636394e-01 4.318197e-01 -8.636394e-01 -2.600000e+00 2.000000e-01 8.728426e-01 8.728426e-01 4.364213e-01 -8.728426e-01 -2.500000e+00 2.000000e-01 8.817912e-01 8.817912e-01 4.408956e-01 -8.817912e-01 -2.400000e+00 2.000000e-01 8.904752e-01 8.904752e-01 4.452376e-01 -8.904752e-01 -2.300000e+00 2.000000e-01 8.988852e-01 8.988852e-01 4.494426e-01 -8.988852e-01 -2.200000e+00 2.000000e-01 9.070116e-01 9.070116e-01 4.535058e-01 -9.070116e-01 -2.100000e+00 2.000000e-01 9.148456e-01 9.148456e-01 4.574228e-01 -9.148456e-01 -2.000000e+00 2.000000e-01 9.223781e-01 9.223781e-01 4.611891e-01 -9.223781e-01 -1.900000e+00 2.000000e-01 9.296008e-01 9.296008e-01 4.648004e-01 -9.296008e-01 -1.800000e+00 2.000000e-01 9.365054e-01 9.365054e-01 4.682527e-01 -9.365054e-01 -1.700000e+00 2.000000e-01 9.430839e-01 9.430839e-01 4.715420e-01 -9.430839e-01 -1.600000e+00 2.000000e-01 9.493288e-01 9.493288e-01 4.746644e-01 -9.493288e-01 -1.500000e+00 2.000000e-01 9.552330e-01 9.552330e-01 4.776165e-01 -9.552330e-01 -1.400000e+00 2.000000e-01 9.607894e-01 9.607894e-01 4.803947e-01 -9.607894e-01 -1.300000e+00 2.000000e-01 9.659917e-01 9.659917e-01 4.829959e-01 -9.659917e-01 -1.200000e+00 2.000000e-01 9.708338e-01 9.708338e-01 4.854169e-01 -9.708338e-01 -1.100000e+00 2.000000e-01 9.753099e-01 9.753099e-01 4.876550e-01 -9.753099e-01 -1.000000e+00 2.000000e-01 9.794148e-01 9.794148e-01 4.897074e-01 -9.794148e-01 -9.000000e-01 2.000000e-01 9.831437e-01 9.831437e-01 4.915718e-01 -9.831437e-01 -8.000000e-01 2.000000e-01 9.864920e-01 9.864920e-01 4.932460e-01 -9.864920e-01 -7.000000e-01 2.000000e-01 9.894560e-01 9.894560e-01 4.947280e-01 -9.894560e-01 -6.000000e-01 2.000000e-01 9.920319e-01 9.920319e-01 4.960160e-01 -9.920319e-01 -5.000000e-01 2.000000e-01 9.942168e-01 9.942168e-01 4.971084e-01 -9.942168e-01 -4.000000e-01 2.000000e-01 9.960080e-01 9.960080e-01 4.980040e-01 -9.960080e-01 -3.000000e-01 2.000000e-01 9.974034e-01 9.974034e-01 4.987017e-01 -9.974034e-01 -2.000000e-01 2.000000e-01 9.984013e-01 9.984013e-01 4.992006e-01 -9.984013e-01 -1.000000e-01 2.000000e-01 9.990005e-01 9.990005e-01 4.995002e-01 -9.990005e-01 0.000000e+00 2.000000e-01 9.992003e-01 9.992003e-01 4.996002e-01 -9.992003e-01 1.000000e-01 2.000000e-01 9.990005e-01 9.990005e-01 4.995002e-01 -9.990005e-01 2.000000e-01 2.000000e-01 9.984013e-01 9.984013e-01 4.992006e-01 -9.984013e-01 3.000000e-01 2.000000e-01 9.974034e-01 9.974034e-01 4.987017e-01 -9.974034e-01 4.000000e-01 2.000000e-01 9.960080e-01 9.960080e-01 4.980040e-01 -9.960080e-01 5.000000e-01 2.000000e-01 9.942168e-01 9.942168e-01 4.971084e-01 -9.942168e-01 6.000000e-01 2.000000e-01 9.920319e-01 9.920319e-01 4.960160e-01 -9.920319e-01 7.000000e-01 2.000000e-01 9.894560e-01 9.894560e-01 4.947280e-01 -9.894560e-01 8.000000e-01 2.000000e-01 9.864920e-01 9.864920e-01 4.932460e-01 -9.864920e-01 9.000000e-01 2.000000e-01 9.831437e-01 9.831437e-01 4.915718e-01 -9.831437e-01 1.000000e+00 2.000000e-01 9.794148e-01 9.794148e-01 4.897074e-01 -9.794148e-01 1.100000e+00 2.000000e-01 9.753099e-01 9.753099e-01 4.876550e-01 -9.753099e-01 1.200000e+00 2.000000e-01 9.708338e-01 9.708338e-01 4.854169e-01 -9.708338e-01 1.300000e+00 2.000000e-01 9.659917e-01 9.659917e-01 4.829959e-01 -9.659917e-01 1.400000e+00 2.000000e-01 9.607894e-01 9.607894e-01 4.803947e-01 -9.607894e-01 1.500000e+00 2.000000e-01 9.552330e-01 9.552330e-01 4.776165e-01 -9.552330e-01 1.600000e+00 2.000000e-01 9.493288e-01 9.493288e-01 4.746644e-01 -9.493288e-01 1.700000e+00 2.000000e-01 9.430839e-01 9.430839e-01 4.715420e-01 -9.430839e-01 1.800000e+00 2.000000e-01 9.365054e-01 9.365054e-01 4.682527e-01 -9.365054e-01 1.900000e+00 2.000000e-01 9.296008e-01 9.296008e-01 4.648004e-01 -9.296008e-01 2.000000e+00 2.000000e-01 9.223781e-01 9.223781e-01 4.611891e-01 -9.223781e-01 2.100000e+00 2.000000e-01 9.148456e-01 9.148456e-01 4.574228e-01 -9.148456e-01 2.200000e+00 2.000000e-01 9.070116e-01 9.070116e-01 4.535058e-01 -9.070116e-01 2.300000e+00 2.000000e-01 8.988852e-01 8.988852e-01 4.494426e-01 -8.988852e-01 2.400000e+00 2.000000e-01 8.904752e-01 8.904752e-01 4.452376e-01 -8.904752e-01 2.500000e+00 2.000000e-01 8.817912e-01 8.817912e-01 4.408956e-01 -8.817912e-01 2.600000e+00 2.000000e-01 8.728426e-01 8.728426e-01 4.364213e-01 -8.728426e-01 2.700000e+00 2.000000e-01 8.636394e-01 8.636394e-01 4.318197e-01 -8.636394e-01 2.800000e+00 2.000000e-01 8.541914e-01 8.541914e-01 4.270957e-01 -8.541914e-01 2.900000e+00 2.000000e-01 8.445089e-01 8.445089e-01 4.222544e-01 -8.445089e-01 3.000000e+00 2.000000e-01 8.346022e-01 8.346022e-01 4.173011e-01 -8.346022e-01 3.100000e+00 2.000000e-01 8.244820e-01 8.244820e-01 4.122410e-01 -8.244820e-01 3.200000e+00 2.000000e-01 8.141587e-01 8.141587e-01 4.070793e-01 -8.141587e-01 3.300000e+00 2.000000e-01 8.036431e-01 8.036431e-01 4.018216e-01 -8.036431e-01 3.400000e+00 2.000000e-01 7.929461e-01 7.929461e-01 3.964731e-01 -7.929461e-01 3.500000e+00 2.000000e-01 7.820786e-01 7.820786e-01 3.910393e-01 -7.820786e-01 3.600000e+00 2.000000e-01 7.710516e-01 7.710516e-01 3.855258e-01 -7.710516e-01 3.700000e+00 2.000000e-01 7.598760e-01 7.598760e-01 3.799380e-01 -7.598760e-01 3.800000e+00 2.000000e-01 7.485629e-01 7.485629e-01 3.742815e-01 -7.485629e-01 3.900000e+00 2.000000e-01 7.371234e-01 7.371234e-01 3.685617e-01 -7.371234e-01 4.000000e+00 2.000000e-01 7.255683e-01 7.255683e-01 3.627841e-01 -7.255683e-01 4.100000e+00 2.000000e-01 7.139089e-01 7.139089e-01 3.569544e-01 -7.139089e-01 4.200000e+00 2.000000e-01 7.021558e-01 7.021558e-01 3.510779e-01 -7.021558e-01 4.300000e+00 2.000000e-01 6.903200e-01 6.903200e-01 3.451600e-01 -6.903200e-01 4.400000e+00 2.000000e-01 6.784123e-01 6.784123e-01 3.392062e-01 -6.784123e-01 4.500000e+00 2.000000e-01 6.664435e-01 6.664435e-01 3.332217e-01 -6.664435e-01 4.600000e+00 2.000000e-01 6.544239e-01 6.544239e-01 3.272119e-01 -6.544239e-01 4.700000e+00 2.000000e-01 6.423641e-01 6.423641e-01 3.211821e-01 -6.423641e-01 4.800000e+00 2.000000e-01 6.302744e-01 6.302744e-01 3.151372e-01 -6.302744e-01 4.900000e+00 2.000000e-01 6.181649e-01 6.181649e-01 3.090824e-01 -6.181649e-01 -5.000000e+00 3.000000e-01 6.054399e-01 6.054399e-01 3.027200e-01 -6.054399e-01 -4.900000e+00 3.000000e-01 6.175470e-01 6.175470e-01 3.087735e-01 -6.175470e-01 -4.800000e+00 3.000000e-01 6.296445e-01 6.296445e-01 3.148222e-01 -6.296445e-01 -4.700000e+00 3.000000e-01 6.417221e-01 6.417221e-01 3.208610e-01 -6.417221e-01 -4.600000e+00 3.000000e-01 6.537698e-01 6.537698e-01 3.268849e-01 -6.537698e-01 -4.500000e+00 3.000000e-01 6.657773e-01 6.657773e-01 3.328887e-01 -6.657773e-01 -4.400000e+00 3.000000e-01 6.777343e-01 6.777343e-01 3.388671e-01 -6.777343e-01 -4.300000e+00 3.000000e-01 6.896300e-01 6.896300e-01 3.448150e-01 -6.896300e-01 -4.200000e+00 3.000000e-01 7.014540e-01 7.014540e-01 3.507270e-01 -7.014540e-01 -4.100000e+00 3.000000e-01 7.131953e-01 7.131953e-01 3.565976e-01 -7.131953e-01 -4.000000e+00 3.000000e-01 7.248431e-01 7.248431e-01 3.624216e-01 -7.248431e-01 -3.900000e+00 3.000000e-01 7.363866e-01 7.363866e-01 3.681933e-01 -7.363866e-01 -3.800000e+00 3.000000e-01 7.478147e-01 7.478147e-01 3.739074e-01 -7.478147e-01 -3.700000e+00 3.000000e-01 7.591165e-01 7.591165e-01 3.795583e-01 -7.591165e-01 -3.600000e+00 3.000000e-01 7.702810e-01 7.702810e-01 3.851405e-01 -7.702810e-01 -3.500000e+00 3.000000e-01 7.812970e-01 7.812970e-01 3.906485e-01 -7.812970e-01 -3.400000e+00 3.000000e-01 7.921535e-01 7.921535e-01 3.960768e-01 -7.921535e-01 -3.300000e+00 3.000000e-01 8.028399e-01 8.028399e-01 4.014199e-01 -8.028399e-01 -3.200000e+00 3.000000e-01 8.133450e-01 8.133450e-01 4.066725e-01 -8.133450e-01 -3.100000e+00 3.000000e-01 8.236579e-01 8.236579e-01 4.118289e-01 -8.236579e-01 -3.000000e+00 3.000000e-01 8.337681e-01 8.337681e-01 4.168840e-01 -8.337681e-01 -2.900000e+00 3.000000e-01 8.436648e-01 8.436648e-01 4.218324e-01 -8.436648e-01 -2.800000e+00 3.000000e-01 8.533376e-01 8.533376e-01 4.266688e-01 -8.533376e-01 -2.700000e+00 3.000000e-01 8.627762e-01 8.627762e-01 4.313881e-01 -8.627762e-01 -2.600000e+00 3.000000e-01 8.719702e-01 8.719702e-01 4.359851e-01 -8.719702e-01 -2.500000e+00 3.000000e-01 8.809099e-01 8.809099e-01 4.404549e-01 -8.809099e-01 -2.400000e+00 3.000000e-01 8.895852e-01 8.895852e-01 4.447926e-01 -8.895852e-01 -2.300000e+00 3.000000e-01 8.979867e-01 8.979867e-01 4.489934e-01 -8.979867e-01 -2.200000e+00 3.000000e-01 9.061051e-01 9.061051e-01 4.530526e-01 -9.061051e-01 -2.100000e+00 3.000000e-01 9.139312e-01 9.139312e-01 4.569656e-01 -9.139312e-01 -2.000000e+00 3.000000e-01 9.214562e-01 9.214562e-01 4.607281e-01 -9.214562e-01 -1.900000e+00 3.000000e-01 9.286717e-01 9.286717e-01 4.643359e-01 -9.286717e-01 -1.800000e+00 3.000000e-01 9.355693e-01 9.355693e-01 4.677847e-01 -9.355693e-01 -1.700000e+00 3.000000e-01 9.421413e-01 9.421413e-01 4.710706e-01 -9.421413e-01 -1.600000e+00 3.000000e-01 9.483800e-01 9.483800e-01 4.741900e-01 -9.483800e-01 -1.500000e+00 3.000000e-01 9.542782e-01 9.542782e-01 4.771391e-01 -9.542782e-01 -1.400000e+00 3.000000e-01 9.598292e-01 9.598292e-01 4.799146e-01 -9.598292e-01 -1.300000e+00 3.000000e-01 9.650262e-01 9.650262e-01 4.825131e-01 -9.650262e-01 -1.200000e+00 3.000000e-01 9.698634e-01 9.698634e-01 4.849317e-01 -9.698634e-01 -1.100000e+00 3.000000e-01 9.743351e-01 9.743351e-01 4.871675e-01 -9.743351e-01 -1.000000e+00 3.000000e-01 9.784359e-01 9.784359e-01 4.892179e-01 -9.784359e-01 -9.000000e-01 3.000000e-01 9.821610e-01 9.821610e-01 4.910805e-01 -9.821610e-01 -8.000000e-01 3.000000e-01 9.855061e-01 9.855061e-01 4.927530e-01 -9.855061e-01 -7.000000e-01 3.000000e-01 9.884670e-01 9.884670e-01 4.942335e-01 -9.884670e-01 -6.000000e-01 3.000000e-01 9.910403e-01 9.910403e-01 4.955202e-01 -9.910403e-01 -5.000000e-01 3.000000e-01 9.932231e-01 9.932231e-01 4.966115e-01 -9.932231e-01 -4.000000e-01 3.000000e-01 9.950125e-01 9.950125e-01 4.975062e-01 -9.950125e-01 -3.000000e-01 3.000000e-01 9.964065e-01 9.964065e-01 4.982032e-01 -9.964065e-01 -2.000000e-01 3.000000e-01 9.974034e-01 9.974034e-01 4.987017e-01 -9.974034e-01 -1.000000e-01 3.000000e-01 9.980020e-01 9.980020e-01 4.990010e-01 -9.980020e-01 0.000000e+00 3.000000e-01 9.982016e-01 9.982016e-01 4.991008e-01 -9.982016e-01 1.000000e-01 3.000000e-01 9.980020e-01 9.980020e-01 4.990010e-01 -9.980020e-01 2.000000e-01 3.000000e-01 9.974034e-01 9.974034e-01 4.987017e-01 -9.974034e-01 3.000000e-01 3.000000e-01 9.964065e-01 9.964065e-01 4.982032e-01 -9.964065e-01 4.000000e-01 3.000000e-01 9.950125e-01 9.950125e-01 4.975062e-01 -9.950125e-01 5.000000e-01 3.000000e-01 9.932231e-01 9.932231e-01 4.966115e-01 -9.932231e-01 6.000000e-01 3.000000e-01 9.910403e-01 9.910403e-01 4.955202e-01 -9.910403e-01 7.000000e-01 3.000000e-01 9.884670e-01 9.884670e-01 4.942335e-01 -9.884670e-01 8.000000e-01 3.000000e-01 9.855061e-01 9.855061e-01 4.927530e-01 -9.855061e-01 9.000000e-01 3.000000e-01 9.821610e-01 9.821610e-01 4.910805e-01 -9.821610e-01 1.000000e+00 3.000000e-01 9.784359e-01 9.784359e-01 4.892179e-01 -9.784359e-01 1.100000e+00 3.000000e-01 9.743351e-01 9.743351e-01 4.871675e-01 -9.743351e-01 1.200000e+00 3.000000e-01 9.698634e-01 9.698634e-01 4.849317e-01 -9.698634e-01 1.300000e+00 3.000000e-01 9.650262e-01 9.650262e-01 4.825131e-01 -9.650262e-01 1.400000e+00 3.000000e-01 9.598292e-01 9.598292e-01 4.799146e-01 -9.598292e-01 1.500000e+00 3.000000e-01 9.542782e-01 9.542782e-01 4.771391e-01 -9.542782e-01 1.600000e+00 3.000000e-01 9.483800e-01 9.483800e-01 4.741900e-01 -9.483800e-01 1.700000e+00 3.000000e-01 9.421413e-01 9.421413e-01 4.710706e-01 -9.421413e-01 1.800000e+00 3.000000e-01 9.355693e-01 9.355693e-01 4.677847e-01 -9.355693e-01 1.900000e+00 3.000000e-01 9.286717e-01 9.286717e-01 4.643359e-01 -9.286717e-01 2.000000e+00 3.000000e-01 9.214562e-01 9.214562e-01 4.607281e-01 -9.214562e-01 2.100000e+00 3.000000e-01 9.139312e-01 9.139312e-01 4.569656e-01 -9.139312e-01 2.200000e+00 3.000000e-01 9.061051e-01 9.061051e-01 4.530526e-01 -9.061051e-01 2.300000e+00 3.000000e-01 8.979867e-01 8.979867e-01 4.489934e-01 -8.979867e-01 2.400000e+00 3.000000e-01 8.895852e-01 8.895852e-01 4.447926e-01 -8.895852e-01 2.500000e+00 3.000000e-01 8.809099e-01 8.809099e-01 4.404549e-01 -8.809099e-01 2.600000e+00 3.000000e-01 8.719702e-01 8.719702e-01 4.359851e-01 -8.719702e-01 2.700000e+00 3.000000e-01 8.627762e-01 8.627762e-01 4.313881e-01 -8.627762e-01 2.800000e+00 3.000000e-01 8.533376e-01 8.533376e-01 4.266688e-01 -8.533376e-01 2.900000e+00 3.000000e-01 8.436648e-01 8.436648e-01 4.218324e-01 -8.436648e-01 3.000000e+00 3.000000e-01 8.337681e-01 8.337681e-01 4.168840e-01 -8.337681e-01 3.100000e+00 3.000000e-01 8.236579e-01 8.236579e-01 4.118289e-01 -8.236579e-01 3.200000e+00 3.000000e-01 8.133450e-01 8.133450e-01 4.066725e-01 -8.133450e-01 3.300000e+00 3.000000e-01 8.028399e-01 8.028399e-01 4.014199e-01 -8.028399e-01 3.400000e+00 3.000000e-01 7.921535e-01 7.921535e-01 3.960768e-01 -7.921535e-01 3.500000e+00 3.000000e-01 7.812970e-01 7.812970e-01 3.906485e-01 -7.812970e-01 3.600000e+00 3.000000e-01 7.702810e-01 7.702810e-01 3.851405e-01 -7.702810e-01 3.700000e+00 3.000000e-01 7.591165e-01 7.591165e-01 3.795583e-01 -7.591165e-01 3.800000e+00 3.000000e-01 7.478147e-01 7.478147e-01 3.739074e-01 -7.478147e-01 3.900000e+00 3.000000e-01 7.363866e-01 7.363866e-01 3.681933e-01 -7.363866e-01 4.000000e+00 3.000000e-01 7.248431e-01 7.248431e-01 3.624216e-01 -7.248431e-01 4.100000e+00 3.000000e-01 7.131953e-01 7.131953e-01 3.565976e-01 -7.131953e-01 4.200000e+00 3.000000e-01 7.014540e-01 7.014540e-01 3.507270e-01 -7.014540e-01 4.300000e+00 3.000000e-01 6.896300e-01 6.896300e-01 3.448150e-01 -6.896300e-01 4.400000e+00 3.000000e-01 6.777343e-01 6.777343e-01 3.388671e-01 -6.777343e-01 4.500000e+00 3.000000e-01 6.657773e-01 6.657773e-01 3.328887e-01 -6.657773e-01 4.600000e+00 3.000000e-01 6.537698e-01 6.537698e-01 3.268849e-01 -6.537698e-01 4.700000e+00 3.000000e-01 6.417221e-01 6.417221e-01 3.208610e-01 -6.417221e-01 4.800000e+00 3.000000e-01 6.296445e-01 6.296445e-01 3.148222e-01 -6.296445e-01 4.900000e+00 3.000000e-01 6.175470e-01 6.175470e-01 3.087735e-01 -6.175470e-01 -5.000000e+00 4.000000e-01 6.045929e-01 6.045929e-01 3.022964e-01 -6.045929e-01 -4.900000e+00 4.000000e-01 6.166831e-01 6.166831e-01 3.083415e-01 -6.166831e-01 -4.800000e+00 4.000000e-01 6.287636e-01 6.287636e-01 3.143818e-01 -6.287636e-01 -4.700000e+00 4.000000e-01 6.408243e-01 6.408243e-01 3.204122e-01 -6.408243e-01 -4.600000e+00 4.000000e-01 6.528552e-01 6.528552e-01 3.264276e-01 -6.528552e-01 -4.500000e+00 4.000000e-01 6.648459e-01 6.648459e-01 3.324230e-01 -6.648459e-01 -4.400000e+00 4.000000e-01 6.767861e-01 6.767861e-01 3.383931e-01 -6.767861e-01 -4.300000e+00 4.000000e-01 6.886652e-01 6.886652e-01 3.443326e-01 -6.886652e-01 -4.200000e+00 4.000000e-01 7.004727e-01 7.004727e-01 3.502363e-01 -7.004727e-01 -4.100000e+00 4.000000e-01 7.121975e-01 7.121975e-01 3.560988e-01 -7.121975e-01 -4.000000e+00 4.000000e-01 7.238291e-01 7.238291e-01 3.619145e-01 -7.238291e-01 -3.900000e+00 4.000000e-01 7.353564e-01 7.353564e-01 3.676782e-01 -7.353564e-01 -3.800000e+00 4.000000e-01 7.467685e-01 7.467685e-01 3.733843e-01 -7.467685e-01 -3.700000e+00 4.000000e-01 7.580545e-01 7.580545e-01 3.790272e-01 -7.580545e-01 -3.600000e+00 4.000000e-01 7.692033e-01 7.692033e-01 3.846017e-01 -7.692033e-01 -3.500000e+00 4.000000e-01 7.802039e-01 7.802039e-01 3.901019e-01 -7.802039e-01 -3.400000e+00 4.000000e-01 7.910453e-01 7.910453e-01 3.955227e-01 -7.910453e-01 -3.300000e+00 4.000000e-01 8.017167e-01 8.017167e-01 4.008583e-01 -8.017167e-01 -3.200000e+00 4.000000e-01 8.122070e-01 8.122070e-01 4.061035e-01 -8.122070e-01 -3.100000e+00 4.000000e-01 8.225056e-01 8.225056e-01 4.112528e-01 -8.225056e-01 -3.000000e+00 4.000000e-01 8.326016e-01 8.326016e-01 4.163008e-01 -8.326016e-01 -2.900000e+00 4.000000e-01 8.424845e-01 8.424845e-01 4.212422e-01 -8.424845e-01 -2.800000e+00 4.000000e-01 8.521438e-01 8.521438e-01 4.260719e-01 -8.521438e-01 -2.700000e+00 4.000000e-01 8.615691e-01 8.615691e-01 4.307846e-01 -8.615691e-01 -2.600000e+00 4.000000e-01 8.707503e-01 8.707503e-01 4.353752e-01 -8.707503e-01 -2.500000e+00 4.000000e-01 8.796774e-01 8.796774e-01 4.398387e-01 -8.796774e-01 -2.400000e+00 4.000000e-01 8.883407e-01 8.883407e-01 4.441703e-01 -8.883407e-01 -2.300000e+00 4.000000e-01 8.967304e-01 8.967304e-01 4.483652e-01 -8.967304e-01 -2.200000e+00 4.000000e-01 9.048374e-01 9.048374e-01 4.524187e-01 -9.048374e-01 -2.100000e+00 4.000000e-01 9.126526e-01 9.126526e-01 4.563263e-01 -9.126526e-01 -2.000000e+00 4.000000e-01 9.201671e-01 9.201671e-01 4.600835e-01 -9.201671e-01 -1.900000e+00 4.000000e-01 9.273725e-01 9.273725e-01 4.636862e-01 -9.273725e-01 -1.800000e+00 4.000000e-01 9.342605e-01 9.342605e-01 4.671302e-01 -9.342605e-01 -1.700000e+00 4.000000e-01 9.408233e-01 9.408233e-01 4.704116e-01 -9.408233e-01 -1.600000e+00 4.000000e-01 9.470532e-01 9.470532e-01 4.735266e-01 -9.470532e-01 -1.500000e+00 4.000000e-01 9.529432e-01 9.529432e-01 4.764716e-01 -9.529432e-01 -1.400000e+00 4.000000e-01 9.584863e-01 9.584863e-01 4.792432e-01 -9.584863e-01 -1.300000e+00 4.000000e-01 9.636762e-01 9.636762e-01 4.818381e-01 -9.636762e-01 -1.200000e+00 4.000000e-01 9.685066e-01 9.685066e-01 4.842533e-01 -9.685066e-01 -1.100000e+00 4.000000e-01 9.729720e-01 9.729720e-01 4.864860e-01 -9.729720e-01 -1.000000e+00 4.000000e-01 9.770671e-01 9.770671e-01 4.885335e-01 -9.770671e-01 -9.000000e-01 4.000000e-01 9.807870e-01 9.807870e-01 4.903935e-01 -9.807870e-01 -8.000000e-01 4.000000e-01 9.841273e-01 9.841273e-01 4.920637e-01 -9.841273e-01 -7.000000e-01 4.000000e-01 9.870842e-01 9.870842e-01 4.935421e-01 -9.870842e-01 -6.000000e-01 4.000000e-01 9.896539e-01 9.896539e-01 4.948269e-01 -9.896539e-01 -5.000000e-01 4.000000e-01 9.918335e-01 9.918335e-01 4.959168e-01 -9.918335e-01 -4.000000e-01 4.000000e-01 9.936205e-01 9.936205e-01 4.968102e-01 -9.936205e-01 -3.000000e-01 4.000000e-01 9.950125e-01 9.950125e-01 4.975062e-01 -9.950125e-01 -2.000000e-01 4.000000e-01 9.960080e-01 9.960080e-01 4.980040e-01 -9.960080e-01 -1.000000e-01 4.000000e-01 9.966058e-01 9.966058e-01 4.983029e-01 -9.966058e-01 0.000000e+00 4.000000e-01 9.968051e-01 9.968051e-01 4.984026e-01 -9.968051e-01 1.000000e-01 4.000000e-01 9.966058e-01 9.966058e-01 4.983029e-01 -9.966058e-01 2.000000e-01 4.000000e-01 9.960080e-01 9.960080e-01 4.980040e-01 -9.960080e-01 3.000000e-01 4.000000e-01 9.950125e-01 9.950125e-01 4.975062e-01 -9.950125e-01 4.000000e-01 4.000000e-01 9.936205e-01 9.936205e-01 4.968102e-01 -9.936205e-01 5.000000e-01 4.000000e-01 9.918335e-01 9.918335e-01 4.959168e-01 -9.918335e-01 6.000000e-01 4.000000e-01 9.896539e-01 9.896539e-01 4.948269e-01 -9.896539e-01 7.000000e-01 4.000000e-01 9.870842e-01 9.870842e-01 4.935421e-01 -9.870842e-01 8.000000e-01 4.000000e-01 9.841273e-01 9.841273e-01 4.920637e-01 -9.841273e-01 9.000000e-01 4.000000e-01 9.807870e-01 9.807870e-01 4.903935e-01 -9.807870e-01 1.000000e+00 4.000000e-01 9.770671e-01 9.770671e-01 4.885335e-01 -9.770671e-01 1.100000e+00 4.000000e-01 9.729720e-01 9.729720e-01 4.864860e-01 -9.729720e-01 1.200000e+00 4.000000e-01 9.685066e-01 9.685066e-01 4.842533e-01 -9.685066e-01 1.300000e+00 4.000000e-01 9.636762e-01 9.636762e-01 4.818381e-01 -9.636762e-01 1.400000e+00 4.000000e-01 9.584863e-01 9.584863e-01 4.792432e-01 -9.584863e-01 1.500000e+00 4.000000e-01 9.529432e-01 9.529432e-01 4.764716e-01 -9.529432e-01 1.600000e+00 4.000000e-01 9.470532e-01 9.470532e-01 4.735266e-01 -9.470532e-01 1.700000e+00 4.000000e-01 9.408233e-01 9.408233e-01 4.704116e-01 -9.408233e-01 1.800000e+00 4.000000e-01 9.342605e-01 9.342605e-01 4.671302e-01 -9.342605e-01 1.900000e+00 4.000000e-01 9.273725e-01 9.273725e-01 4.636862e-01 -9.273725e-01 2.000000e+00 4.000000e-01 9.201671e-01 9.201671e-01 4.600835e-01 -9.201671e-01 2.100000e+00 4.000000e-01 9.126526e-01 9.126526e-01 4.563263e-01 -9.126526e-01 2.200000e+00 4.000000e-01 9.048374e-01 9.048374e-01 4.524187e-01 -9.048374e-01 2.300000e+00 4.000000e-01 8.967304e-01 8.967304e-01 4.483652e-01 -8.967304e-01 2.400000e+00 4.000000e-01 8.883407e-01 8.883407e-01 4.441703e-01 -8.883407e-01 2.500000e+00 4.000000e-01 8.796774e-01 8.796774e-01 4.398387e-01 -8.796774e-01 2.600000e+00 4.000000e-01 8.707503e-01 8.707503e-01 4.353752e-01 -8.707503e-01 2.700000e+00 4.000000e-01 8.615691e-01 8.615691e-01 4.307846e-01 -8.615691e-01 2.800000e+00 4.000000e-01 8.521438e-01 8.521438e-01 4.260719e-01 -8.521438e-01 2.900000e+00 4.000000e-01 8.424845e-01 8.424845e-01 4.212422e-01 -8.424845e-01 3.000000e+00 4.000000e-01 8.326016e-01 8.326016e-01 4.163008e-01 -8.326016e-01 3.100000e+00 4.000000e-01 8.225056e-01 8.225056e-01 4.112528e-01 -8.225056e-01 3.200000e+00 4.000000e-01 8.122070e-01 8.122070e-01 4.061035e-01 -8.122070e-01 3.300000e+00 4.000000e-01 8.017167e-01 8.017167e-01 4.008583e-01 -8.017167e-01 3.400000e+00 4.000000e-01 7.910453e-01 7.910453e-01 3.955227e-01 -7.910453e-01 3.500000e+00 4.000000e-01 7.802039e-01 7.802039e-01 3.901019e-01 -7.802039e-01 3.600000e+00 4.000000e-01 7.692033e-01 7.692033e-01 3.846017e-01 -7.692033e-01 3.700000e+00 4.000000e-01 7.580545e-01 7.580545e-01 3.790272e-01 -7.580545e-01 3.800000e+00 4.000000e-01 7.467685e-01 7.467685e-01 3.733843e-01 -7.467685e-01 3.900000e+00 4.000000e-01 7.353564e-01 7.353564e-01 3.676782e-01 -7.353564e-01 4.000000e+00 4.000000e-01 7.238291e-01 7.238291e-01 3.619145e-01 -7.238291e-01 4.100000e+00 4.000000e-01 7.121975e-01 7.121975e-01 3.560988e-01 -7.121975e-01 4.200000e+00 4.000000e-01 7.004727e-01 7.004727e-01 3.502363e-01 -7.004727e-01 4.300000e+00 4.000000e-01 6.886652e-01 6.886652e-01 3.443326e-01 -6.886652e-01 4.400000e+00 4.000000e-01 6.767861e-01 6.767861e-01 3.383931e-01 -6.767861e-01 4.500000e+00 4.000000e-01 6.648459e-01 6.648459e-01 3.324230e-01 -6.648459e-01 4.600000e+00 4.000000e-01 6.528552e-01 6.528552e-01 3.264276e-01 -6.528552e-01 4.700000e+00 4.000000e-01 6.408243e-01 6.408243e-01 3.204122e-01 -6.408243e-01 4.800000e+00 4.000000e-01 6.287636e-01 6.287636e-01 3.143818e-01 -6.287636e-01 4.900000e+00 4.000000e-01 6.166831e-01 6.166831e-01 3.083415e-01 -6.166831e-01 -5.000000e+00 5.000000e-01 6.035056e-01 6.035056e-01 3.017528e-01 -6.035056e-01 -4.900000e+00 5.000000e-01 6.155741e-01 6.155741e-01 3.077870e-01 -6.155741e-01 -4.800000e+00 5.000000e-01 6.276328e-01 6.276328e-01 3.138164e-01 -6.276328e-01 -4.700000e+00 5.000000e-01 6.396719e-01 6.396719e-01 3.198359e-01 -6.396719e-01 -4.600000e+00 5.000000e-01 6.516811e-01 6.516811e-01 3.258406e-01 -6.516811e-01 -4.500000e+00 5.000000e-01 6.636503e-01 6.636503e-01 3.318251e-01 -6.636503e-01 -4.400000e+00 5.000000e-01 6.755690e-01 6.755690e-01 3.377845e-01 -6.755690e-01 -4.300000e+00 5.000000e-01 6.874267e-01 6.874267e-01 3.437134e-01 -6.874267e-01 -4.200000e+00 5.000000e-01 6.992129e-01 6.992129e-01 3.496065e-01 -6.992129e-01 -4.100000e+00 5.000000e-01 7.109167e-01 7.109167e-01 3.554583e-01 -7.109167e-01 -4.000000e+00 5.000000e-01 7.225273e-01 7.225273e-01 3.612637e-01 -7.225273e-01 -3.900000e+00 5.000000e-01 7.340339e-01 7.340339e-01 3.670170e-01 -7.340339e-01 -3.800000e+00 5.000000e-01 7.454256e-01 7.454256e-01 3.727128e-01 -7.454256e-01 -3.700000e+00 5.000000e-01 7.566912e-01 7.566912e-01 3.783456e-01 -7.566912e-01 -3.600000e+00 5.000000e-01 7.678200e-01 7.678200e-01 3.839100e-01 -7.678200e-01 -3.500000e+00 5.000000e-01 7.788008e-01 7.788008e-01 3.894004e-01 -7.788008e-01 -3.400000e+00 5.000000e-01 7.896227e-01 7.896227e-01 3.948114e-01 -7.896227e-01 -3.300000e+00 5.000000e-01 8.002749e-01 8.002749e-01 4.001375e-01 -8.002749e-01 -3.200000e+00 5.000000e-01 8.107464e-01 8.107464e-01 4.053732e-01 -8.107464e-01 -3.100000e+00 5.000000e-01 8.210264e-01 8.210264e-01 4.105132e-01 -8.210264e-01 -3.000000e+00 5.000000e-01 8.311043e-01 8.311043e-01 4.155521e-01 -8.311043e-01 -2.900000e+00 5.000000e-01 8.409694e-01 8.409694e-01 4.204847e-01 -8.409694e-01 -2.800000e+00 5.000000e-01 8.506113e-01 8.506113e-01 4.253057e-01 -8.506113e-01 -2.700000e+00 5.000000e-01 8.600197e-01 8.600197e-01 4.300098e-01 -8.600197e-01 -2.600000e+00 5.000000e-01 8.691844e-01 8.691844e-01 4.345922e-01 -8.691844e-01 -2.500000e+00 5.000000e-01 8.780954e-01 8.780954e-01 4.390477e-01 -8.780954e-01 -2.400000e+00 5.000000e-01 8.867431e-01 8.867431e-01 4.433715e-01 -8.867431e-01 -2.300000e+00 5.000000e-01 8.951178e-01 8.951178e-01 4.475589e-01 -8.951178e-01 -2.200000e+00 5.000000e-01 9.032102e-01 9.032102e-01 4.516051e-01 -9.032102e-01 -2.100000e+00 5.000000e-01 9.110113e-01 9.110113e-01 4.555056e-01 -9.110113e-01 -2.000000e+00 5.000000e-01 9.185123e-01 9.185123e-01 4.592561e-01 -9.185123e-01 -1.900000e+00 5.000000e-01 9.257047e-01 9.257047e-01 4.628524e-01 -9.257047e-01 -1.800000e+00 5.000000e-01 9.325803e-01 9.325803e-01 4.662901e-01 -9.325803e-01 -1.700000e+00 5.000000e-01 9.391313e-01 9.391313e-01 4.695656e-01 -9.391313e-01 -1.600000e+00 5.000000e-01 9.453501e-01 9.453501e-01 4.726750e-01 -9.453501e-01 -1.500000e+00 5.000000e-01 9.512295e-01 9.512295e-01 4.756147e-01 -9.512295e-01 -1.400000e+00 5.000000e-01 9.567626e-01 9.567626e-01 4.783813e-01 -9.567626e-01 -1.300000e+00 5.000000e-01 9.619431e-01 9.619431e-01 4.809715e-01 -9.619431e-01 -1.200000e+00 5.000000e-01 9.667648e-01 9.667648e-01 4.833824e-01 -9.667648e-01 -1.100000e+00 5.000000e-01 9.712222e-01 9.712222e-01 4.856111e-01 -9.712222e-01 -1.000000e+00 5.000000e-01 9.753099e-01 9.753099e-01 4.876550e-01 -9.753099e-01 -9.000000e-01 5.000000e-01 9.790232e-01 9.790232e-01 4.895116e-01 -9.790232e-01 -8.000000e-01 5.000000e-01 9.823575e-01 9.823575e-01 4.911788e-01 -9.823575e-01 -7.000000e-01 5.000000e-01 9.853090e-01 9.853090e-01 4.926545e-01 -9.853090e-01 -6.000000e-01 5.000000e-01 9.878741e-01 9.878741e-01 4.939370e-01 -9.878741e-01 -5.000000e-01 5.000000e-01 9.900498e-01 9.900498e-01 4.950249e-01 -9.900498e-01 -4.000000e-01 5.000000e-01 9.918335e-01 9.918335e-01 4.959168e-01 -9.918335e-01 -3.000000e-01 5.000000e-01 9.932231e-01 9.932231e-01 4.966115e-01 -9.932231e-01 -2.000000e-01 5.000000e-01 9.942168e-01 9.942168e-01 4.971084e-01 -9.942168e-01 -1.000000e-01 5.000000e-01 9.948135e-01 9.948135e-01 4.974068e-01 -9.948135e-01 0.000000e+00 5.000000e-01 9.950125e-01 9.950125e-01 4.975062e-01 -9.950125e-01 1.000000e-01 5.000000e-01 9.948135e-01 9.948135e-01 4.974068e-01 -9.948135e-01 2.000000e-01 5.000000e-01 9.942168e-01 9.942168e-01 4.971084e-01 -9.942168e-01 3.000000e-01 5.000000e-01 9.932231e-01 9.932231e-01 4.966115e-01 -9.932231e-01 4.000000e-01 5.000000e-01 9.918335e-01 9.918335e-01 4.959168e-01 -9.918335e-01 5.000000e-01 5.000000e-01 9.900498e-01 9.900498e-01 4.950249e-01 -9.900498e-01 6.000000e-01 5.000000e-01 9.878741e-01 9.878741e-01 4.939370e-01 -9.878741e-01 7.000000e-01 5.000000e-01 9.853090e-01 9.853090e-01 4.926545e-01 -9.853090e-01 8.000000e-01 5.000000e-01 9.823575e-01 9.823575e-01 4.911788e-01 -9.823575e-01 9.000000e-01 5.000000e-01 9.790232e-01 9.790232e-01 4.895116e-01 -9.790232e-01 1.000000e+00 5.000000e-01 9.753099e-01 9.753099e-01 4.876550e-01 -9.753099e-01 1.100000e+00 5.000000e-01 9.712222e-01 9.712222e-01 4.856111e-01 -9.712222e-01 1.200000e+00 5.000000e-01 9.667648e-01 9.667648e-01 4.833824e-01 -9.667648e-01 1.300000e+00 5.000000e-01 9.619431e-01 9.619431e-01 4.809715e-01 -9.619431e-01 1.400000e+00 5.000000e-01 9.567626e-01 9.567626e-01 4.783813e-01 -9.567626e-01 1.500000e+00 5.000000e-01 9.512295e-01 9.512295e-01 4.756147e-01 -9.512295e-01 1.600000e+00 5.000000e-01 9.453501e-01 9.453501e-01 4.726750e-01 -9.453501e-01 1.700000e+00 5.000000e-01 9.391313e-01 9.391313e-01 4.695656e-01 -9.391313e-01 1.800000e+00 5.000000e-01 9.325803e-01 9.325803e-01 4.662901e-01 -9.325803e-01 1.900000e+00 5.000000e-01 9.257047e-01 9.257047e-01 4.628524e-01 -9.257047e-01 2.000000e+00 5.000000e-01 9.185123e-01 9.185123e-01 4.592561e-01 -9.185123e-01 2.100000e+00 5.000000e-01 9.110113e-01 9.110113e-01 4.555056e-01 -9.110113e-01 2.200000e+00 5.000000e-01 9.032102e-01 9.032102e-01 4.516051e-01 -9.032102e-01 2.300000e+00 5.000000e-01 8.951178e-01 8.951178e-01 4.475589e-01 -8.951178e-01 2.400000e+00 5.000000e-01 8.867431e-01 8.867431e-01 4.433715e-01 -8.867431e-01 2.500000e+00 5.000000e-01 8.780954e-01 8.780954e-01 4.390477e-01 -8.780954e-01 2.600000e+00 5.000000e-01 8.691844e-01 8.691844e-01 4.345922e-01 -8.691844e-01 2.700000e+00 5.000000e-01 8.600197e-01 8.600197e-01 4.300098e-01 -8.600197e-01 2.800000e+00 5.000000e-01 8.506113e-01 8.506113e-01 4.253057e-01 -8.506113e-01 2.900000e+00 5.000000e-01 8.409694e-01 8.409694e-01 4.204847e-01 -8.409694e-01 3.000000e+00 5.000000e-01 8.311043e-01 8.311043e-01 4.155521e-01 -8.311043e-01 3.100000e+00 5.000000e-01 8.210264e-01 8.210264e-01 4.105132e-01 -8.210264e-01 3.200000e+00 5.000000e-01 8.107464e-01 8.107464e-01 4.053732e-01 -8.107464e-01 3.300000e+00 5.000000e-01 8.002749e-01 8.002749e-01 4.001375e-01 -8.002749e-01 3.400000e+00 5.000000e-01 7.896227e-01 7.896227e-01 3.948114e-01 -7.896227e-01 3.500000e+00 5.000000e-01 7.788008e-01 7.788008e-01 3.894004e-01 -7.788008e-01 3.600000e+00 5.000000e-01 7.678200e-01 7.678200e-01 3.839100e-01 -7.678200e-01 3.700000e+00 5.000000e-01 7.566912e-01 7.566912e-01 3.783456e-01 -7.566912e-01 3.800000e+00 5.000000e-01 7.454256e-01 7.454256e-01 3.727128e-01 -7.454256e-01 3.900000e+00 5.000000e-01 7.340339e-01 7.340339e-01 3.670170e-01 -7.340339e-01 4.000000e+00 5.000000e-01 7.225273e-01 7.225273e-01 3.612637e-01 -7.225273e-01 4.100000e+00 5.000000e-01 7.109167e-01 7.109167e-01 3.554583e-01 -7.109167e-01 4.200000e+00 5.000000e-01 6.992129e-01 6.992129e-01 3.496065e-01 -6.992129e-01 4.300000e+00 5.000000e-01 6.874267e-01 6.874267e-01 3.437134e-01 -6.874267e-01 4.400000e+00 5.000000e-01 6.755690e-01 6.755690e-01 3.377845e-01 -6.755690e-01 4.500000e+00 5.000000e-01 6.636503e-01 6.636503e-01 3.318251e-01 -6.636503e-01 4.600000e+00 5.000000e-01 6.516811e-01 6.516811e-01 3.258406e-01 -6.516811e-01 4.700000e+00 5.000000e-01 6.396719e-01 6.396719e-01 3.198359e-01 -6.396719e-01 4.800000e+00 5.000000e-01 6.276328e-01 6.276328e-01 3.138164e-01 -6.276328e-01 4.900000e+00 5.000000e-01 6.155741e-01 6.155741e-01 3.077870e-01 -6.155741e-01 -5.000000e+00 6.000000e-01 6.021793e-01 6.021793e-01 3.010897e-01 -6.021793e-01 -4.900000e+00 6.000000e-01 6.142213e-01 6.142213e-01 3.071106e-01 -6.142213e-01 -4.800000e+00 6.000000e-01 6.262535e-01 6.262535e-01 3.131267e-01 -6.262535e-01 -4.700000e+00 6.000000e-01 6.382661e-01 6.382661e-01 3.191331e-01 -6.382661e-01 -4.600000e+00 6.000000e-01 6.502489e-01 6.502489e-01 3.251245e-01 -6.502489e-01 -4.500000e+00 6.000000e-01 6.621919e-01 6.621919e-01 3.310959e-01 -6.621919e-01 -4.400000e+00 6.000000e-01 6.740844e-01 6.740844e-01 3.370422e-01 -6.740844e-01 -4.300000e+00 6.000000e-01 6.859161e-01 6.859161e-01 3.429580e-01 -6.859161e-01 -4.200000e+00 6.000000e-01 6.976764e-01 6.976764e-01 3.488382e-01 -6.976764e-01 -4.100000e+00 6.000000e-01 7.093544e-01 7.093544e-01 3.546772e-01 -7.093544e-01 -4.000000e+00 6.000000e-01 7.209395e-01 7.209395e-01 3.604698e-01 -7.209395e-01 -3.900000e+00 6.000000e-01 7.324208e-01 7.324208e-01 3.662104e-01 -7.324208e-01 -3.800000e+00 6.000000e-01 7.437874e-01 7.437874e-01 3.718937e-01 -7.437874e-01 -3.700000e+00 6.000000e-01 7.550283e-01 7.550283e-01 3.775142e-01 -7.550283e-01 -3.600000e+00 6.000000e-01 7.661327e-01 7.661327e-01 3.830663e-01 -7.661327e-01 -3.500000e+00 6.000000e-01 7.770893e-01 7.770893e-01 3.885446e-01 -7.770893e-01 -3.400000e+00 6.000000e-01 7.878875e-01 7.878875e-01 3.939437e-01 -7.878875e-01 -3.300000e+00 6.000000e-01 7.985162e-01 7.985162e-01 3.992581e-01 -7.985162e-01 -3.200000e+00 6.000000e-01 8.089647e-01 8.089647e-01 4.044824e-01 -8.089647e-01 -3.100000e+00 6.000000e-01 8.192222e-01 8.192222e-01 4.096111e-01 -8.192222e-01 -3.000000e+00 6.000000e-01 8.292779e-01 8.292779e-01 4.146389e-01 -8.292779e-01 -2.900000e+00 6.000000e-01 8.391213e-01 8.391213e-01 4.195606e-01 -8.391213e-01 -2.800000e+00 6.000000e-01 8.487420e-01 8.487420e-01 4.243710e-01 -8.487420e-01 -2.700000e+00 6.000000e-01 8.581297e-01 8.581297e-01 4.290649e-01 -8.581297e-01 -2.600000e+00 6.000000e-01 8.672743e-01 8.672743e-01 4.336371e-01 -8.672743e-01 -2.500000e+00 6.000000e-01 8.761657e-01 8.761657e-01 4.380829e-01 -8.761657e-01 -2.400000e+00 6.000000e-01 8.847944e-01 8.847944e-01 4.423972e-01 -8.847944e-01 -2.300000e+00 6.000000e-01 8.931507e-01 8.931507e-01 4.465753e-01 -8.931507e-01 -2.200000e+00 6.000000e-01 9.012253e-01 9.012253e-01 4.506126e-01 -9.012253e-01 -2.100000e+00 6.000000e-01 9.090093e-01 9.090093e-01 4.545046e-01 -9.090093e-01 -2.000000e+00 6.000000e-01 9.164938e-01 9.164938e-01 4.582469e-01 -9.164938e-01 -1.900000e+00 6.000000e-01 9.236704e-01 9.236704e-01 4.618352e-01 -9.236704e-01 -1.800000e+00 6.000000e-01 9.305309e-01 9.305309e-01 4.652655e-01 -9.305309e-01 -1.700000e+00 6.000000e-01 9.370674e-01 9.370674e-01 4.685337e-01 -9.370674e-01 -1.600000e+00 6.000000e-01 9.432726e-01 9.432726e-01 4.716363e-01 -9.432726e-01 -1.500000e+00 6.000000e-01 9.491390e-01 9.491390e-01 4.745695e-01 -9.491390e-01 -1.400000e+00 6.000000e-01 9.546600e-01 9.546600e-01 4.773300e-01 -9.546600e-01 -1.300000e+00 6.000000e-01 9.598292e-01 9.598292e-01 4.799146e-01 -9.598292e-01 -1.200000e+00 6.000000e-01 9.646403e-01 9.646403e-01 4.823202e-01 -9.646403e-01 -1.100000e+00 6.000000e-01 9.690878e-01 9.690878e-01 4.845439e-01 -9.690878e-01 -1.000000e+00 6.000000e-01 9.731666e-01 9.731666e-01 4.865833e-01 -9.731666e-01 -9.000000e-01 6.000000e-01 9.768717e-01 9.768717e-01 4.884358e-01 -9.768717e-01 -8.000000e-01 6.000000e-01 9.801987e-01 9.801987e-01 4.900993e-01 -9.801987e-01 -7.000000e-01 6.000000e-01 9.831437e-01 9.831437e-01 4.915718e-01 -9.831437e-01 -6.000000e-01 6.000000e-01 9.857032e-01 9.857032e-01 4.928516e-01 -9.857032e-01 -5.000000e-01 6.000000e-01 9.878741e-01 9.878741e-01 4.939370e-01 -9.878741e-01 -4.000000e-01 6.000000e-01 9.896539e-01 9.896539e-01 4.948269e-01 -9.896539e-01 -3.000000e-01 6.000000e-01 9.910403e-01 9.910403e-01 4.955202e-01 -9.910403e-01 -2.000000e-01 6.000000e-01 9.920319e-01 9.920319e-01 4.960160e-01 -9.920319e-01 -1.000000e-01 6.000000e-01 9.926273e-01 9.926273e-01 4.963137e-01 -9.926273e-01 0.000000e+00 6.000000e-01 9.928259e-01 9.928259e-01 4.964129e-01 -9.928259e-01 1.000000e-01 6.000000e-01 9.926273e-01 9.926273e-01 4.963137e-01 -9.926273e-01 2.000000e-01 6.000000e-01 9.920319e-01 9.920319e-01 4.960160e-01 -9.920319e-01 3.000000e-01 6.000000e-01 9.910403e-01 9.910403e-01 4.955202e-01 -9.910403e-01 4.000000e-01 6.000000e-01 9.896539e-01 9.896539e-01 4.948269e-01 -9.896539e-01 5.000000e-01 6.000000e-01 9.878741e-01 9.878741e-01 4.939370e-01 -9.878741e-01 6.000000e-01 6.000000e-01 9.857032e-01 9.857032e-01 4.928516e-01 -9.857032e-01 7.000000e-01 6.000000e-01 9.831437e-01 9.831437e-01 4.915718e-01 -9.831437e-01 8.000000e-01 6.000000e-01 9.801987e-01 9.801987e-01 4.900993e-01 -9.801987e-01 9.000000e-01 6.000000e-01 9.768717e-01 9.768717e-01 4.884358e-01 -9.768717e-01 1.000000e+00 6.000000e-01 9.731666e-01 9.731666e-01 4.865833e-01 -9.731666e-01 1.100000e+00 6.000000e-01 9.690878e-01 9.690878e-01 4.845439e-01 -9.690878e-01 1.200000e+00 6.000000e-01 9.646403e-01 9.646403e-01 4.823202e-01 -9.646403e-01 1.300000e+00 6.000000e-01 9.598292e-01 9.598292e-01 4.799146e-01 -9.598292e-01 1.400000e+00 6.000000e-01 9.546600e-01 9.546600e-01 4.773300e-01 -9.546600e-01 1.500000e+00 6.000000e-01 9.491390e-01 9.491390e-01 4.745695e-01 -9.491390e-01 1.600000e+00 6.000000e-01 9.432726e-01 9.432726e-01 4.716363e-01 -9.432726e-01 1.700000e+00 6.000000e-01 9.370674e-01 9.370674e-01 4.685337e-01 -9.370674e-01 1.800000e+00 6.000000e-01 9.305309e-01 9.305309e-01 4.652655e-01 -9.305309e-01 1.900000e+00 6.000000e-01 9.236704e-01 9.236704e-01 4.618352e-01 -9.236704e-01 2.000000e+00 6.000000e-01 9.164938e-01 9.164938e-01 4.582469e-01 -9.164938e-01 2.100000e+00 6.000000e-01 9.090093e-01 9.090093e-01 4.545046e-01 -9.090093e-01 2.200000e+00 6.000000e-01 9.012253e-01 9.012253e-01 4.506126e-01 -9.012253e-01 2.300000e+00 6.000000e-01 8.931507e-01 8.931507e-01 4.465753e-01 -8.931507e-01 2.400000e+00 6.000000e-01 8.847944e-01 8.847944e-01 4.423972e-01 -8.847944e-01 2.500000e+00 6.000000e-01 8.761657e-01 8.761657e-01 4.380829e-01 -8.761657e-01 2.600000e+00 6.000000e-01 8.672743e-01 8.672743e-01 4.336371e-01 -8.672743e-01 2.700000e+00 6.000000e-01 8.581297e-01 8.581297e-01 4.290649e-01 -8.581297e-01 2.800000e+00 6.000000e-01 8.487420e-01 8.487420e-01 4.243710e-01 -8.487420e-01 2.900000e+00 6.000000e-01 8.391213e-01 8.391213e-01 4.195606e-01 -8.391213e-01 3.000000e+00 6.000000e-01 8.292779e-01 8.292779e-01 4.146389e-01 -8.292779e-01 3.100000e+00 6.000000e-01 8.192222e-01 8.192222e-01 4.096111e-01 -8.192222e-01 3.200000e+00 6.000000e-01 8.089647e-01 8.089647e-01 4.044824e-01 -8.089647e-01 3.300000e+00 6.000000e-01 7.985162e-01 7.985162e-01 3.992581e-01 -7.985162e-01 3.400000e+00 6.000000e-01 7.878875e-01 7.878875e-01 3.939437e-01 -7.878875e-01 3.500000e+00 6.000000e-01 7.770893e-01 7.770893e-01 3.885446e-01 -7.770893e-01 3.600000e+00 6.000000e-01 7.661327e-01 7.661327e-01 3.830663e-01 -7.661327e-01 3.700000e+00 6.000000e-01 7.550283e-01 7.550283e-01 3.775142e-01 -7.550283e-01 3.800000e+00 6.000000e-01 7.437874e-01 7.437874e-01 3.718937e-01 -7.437874e-01 3.900000e+00 6.000000e-01 7.324208e-01 7.324208e-01 3.662104e-01 -7.324208e-01 4.000000e+00 6.000000e-01 7.209395e-01 7.209395e-01 3.604698e-01 -7.209395e-01 4.100000e+00 6.000000e-01 7.093544e-01 7.093544e-01 3.546772e-01 -7.093544e-01 4.200000e+00 6.000000e-01 6.976764e-01 6.976764e-01 3.488382e-01 -6.976764e-01 4.300000e+00 6.000000e-01 6.859161e-01 6.859161e-01 3.429580e-01 -6.859161e-01 4.400000e+00 6.000000e-01 6.740844e-01 6.740844e-01 3.370422e-01 -6.740844e-01 4.500000e+00 6.000000e-01 6.621919e-01 6.621919e-01 3.310959e-01 -6.621919e-01 4.600000e+00 6.000000e-01 6.502489e-01 6.502489e-01 3.251245e-01 -6.502489e-01 4.700000e+00 6.000000e-01 6.382661e-01 6.382661e-01 3.191331e-01 -6.382661e-01 4.800000e+00 6.000000e-01 6.262535e-01 6.262535e-01 3.131267e-01 -6.262535e-01 4.900000e+00 6.000000e-01 6.142213e-01 6.142213e-01 3.071106e-01 -6.142213e-01 -5.000000e+00 7.000000e-01 6.006157e-01 6.006157e-01 3.003078e-01 -6.006157e-01 -4.900000e+00 7.000000e-01 6.126264e-01 6.126264e-01 3.063132e-01 -6.126264e-01 -4.800000e+00 7.000000e-01 6.246274e-01 6.246274e-01 3.123137e-01 -6.246274e-01 -4.700000e+00 7.000000e-01 6.366088e-01 6.366088e-01 3.183044e-01 -6.366088e-01 -4.600000e+00 7.000000e-01 6.485605e-01 6.485605e-01 3.242803e-01 -6.485605e-01 -4.500000e+00 7.000000e-01 6.604724e-01 6.604724e-01 3.302362e-01 -6.604724e-01 -4.400000e+00 7.000000e-01 6.723340e-01 6.723340e-01 3.361670e-01 -6.723340e-01 -4.300000e+00 7.000000e-01 6.841350e-01 6.841350e-01 3.420675e-01 -6.841350e-01 -4.200000e+00 7.000000e-01 6.958647e-01 6.958647e-01 3.479324e-01 -6.958647e-01 -4.100000e+00 7.000000e-01 7.075125e-01 7.075125e-01 3.537562e-01 -7.075125e-01 -4.000000e+00 7.000000e-01 7.190675e-01 7.190675e-01 3.595338e-01 -7.190675e-01 -3.900000e+00 7.000000e-01 7.305190e-01 7.305190e-01 3.652595e-01 -7.305190e-01 -3.800000e+00 7.000000e-01 7.418561e-01 7.418561e-01 3.709280e-01 -7.418561e-01 -3.700000e+00 7.000000e-01 7.530678e-01 7.530678e-01 3.765339e-01 -7.530678e-01 -3.600000e+00 7.000000e-01 7.641433e-01 7.641433e-01 3.820716e-01 -7.641433e-01 -3.500000e+00 7.000000e-01 7.750715e-01 7.750715e-01 3.875358e-01 -7.750715e-01 -3.400000e+00 7.000000e-01 7.858416e-01 7.858416e-01 3.929208e-01 -7.858416e-01 -3.300000e+00 7.000000e-01 7.964428e-01 7.964428e-01 3.982214e-01 -7.964428e-01 -3.200000e+00 7.000000e-01 8.068641e-01 8.068641e-01 4.034321e-01 -8.068641e-01 -3.100000e+00 7.000000e-01 8.170949e-01 8.170949e-01 4.085475e-01 -8.170949e-01 -3.000000e+00 7.000000e-01 8.271245e-01 8.271245e-01 4.135623e-01 -8.271245e-01 -2.900000e+00 7.000000e-01 8.369424e-01 8.369424e-01 4.184712e-01 -8.369424e-01 -2.800000e+00 7.000000e-01 8.465381e-01 8.465381e-01 4.232691e-01 -8.465381e-01 -2.700000e+00 7.000000e-01 8.559015e-01 8.559015e-01 4.279507e-01 -8.559015e-01 -2.600000e+00 7.000000e-01 8.650223e-01 8.650223e-01 4.325112e-01 -8.650223e-01 -2.500000e+00 7.000000e-01 8.738907e-01 8.738907e-01 4.369453e-01 -8.738907e-01 -2.400000e+00 7.000000e-01 8.824969e-01 8.824969e-01 4.412484e-01 -8.824969e-01 -2.300000e+00 7.000000e-01 8.908315e-01 8.908315e-01 4.454157e-01 -8.908315e-01 -2.200000e+00 7.000000e-01 8.988851e-01 8.988851e-01 4.494426e-01 -8.988851e-01 -2.100000e+00 7.000000e-01 9.066489e-01 9.066489e-01 4.533245e-01 -9.066489e-01 -2.000000e+00 7.000000e-01 9.141140e-01 9.141140e-01 4.570570e-01 -9.141140e-01 -1.900000e+00 7.000000e-01 9.212720e-01 9.212720e-01 4.606360e-01 -9.212720e-01 -1.800000e+00 7.000000e-01 9.281147e-01 9.281147e-01 4.640573e-01 -9.281147e-01 -1.700000e+00 7.000000e-01 9.346343e-01 9.346343e-01 4.673171e-01 -9.346343e-01 -1.600000e+00 7.000000e-01 9.408233e-01 9.408233e-01 4.704116e-01 -9.408233e-01 -1.500000e+00 7.000000e-01 9.466745e-01 9.466745e-01 4.733372e-01 -9.466745e-01 -1.400000e+00 7.000000e-01 9.521811e-01 9.521811e-01 4.760906e-01 -9.521811e-01 -1.300000e+00 7.000000e-01 9.573368e-01 9.573368e-01 4.786684e-01 -9.573368e-01 -1.200000e+00 7.000000e-01 9.621355e-01 9.621355e-01 4.810677e-01 -9.621355e-01 -1.100000e+00 7.000000e-01 9.665715e-01 9.665715e-01 4.832858e-01 -9.665715e-01 -1.000000e+00 7.000000e-01 9.706396e-01 9.706396e-01 4.853198e-01 -9.706396e-01 -9.000000e-01 7.000000e-01 9.743351e-01 9.743351e-01 4.871675e-01 -9.743351e-01 -8.000000e-01 7.000000e-01 9.776534e-01 9.776534e-01 4.888267e-01 -9.776534e-01 -7.000000e-01 7.000000e-01 9.805908e-01 9.805908e-01 4.902954e-01 -9.805908e-01 -6.000000e-01 7.000000e-01 9.831437e-01 9.831437e-01 4.915718e-01 -9.831437e-01 -5.000000e-01 7.000000e-01 9.853090e-01 9.853090e-01 4.926545e-01 -9.853090e-01 -4.000000e-01 7.000000e-01 9.870842e-01 9.870842e-01 4.935421e-01 -9.870842e-01 -3.000000e-01 7.000000e-01 9.884670e-01 9.884670e-01 4.942335e-01 -9.884670e-01 -2.000000e-01 7.000000e-01 9.894560e-01 9.894560e-01 4.947280e-01 -9.894560e-01 -1.000000e-01 7.000000e-01 9.900498e-01 9.900498e-01 4.950249e-01 -9.900498e-01 0.000000e+00 7.000000e-01 9.902478e-01 9.902478e-01 4.951239e-01 -9.902478e-01 1.000000e-01 7.000000e-01 9.900498e-01 9.900498e-01 4.950249e-01 -9.900498e-01 2.000000e-01 7.000000e-01 9.894560e-01 9.894560e-01 4.947280e-01 -9.894560e-01 3.000000e-01 7.000000e-01 9.884670e-01 9.884670e-01 4.942335e-01 -9.884670e-01 4.000000e-01 7.000000e-01 9.870842e-01 9.870842e-01 4.935421e-01 -9.870842e-01 5.000000e-01 7.000000e-01 9.853090e-01 9.853090e-01 4.926545e-01 -9.853090e-01 6.000000e-01 7.000000e-01 9.831437e-01 9.831437e-01 4.915718e-01 -9.831437e-01 7.000000e-01 7.000000e-01 9.805908e-01 9.805908e-01 4.902954e-01 -9.805908e-01 8.000000e-01 7.000000e-01 9.776534e-01 9.776534e-01 4.888267e-01 -9.776534e-01 9.000000e-01 7.000000e-01 9.743351e-01 9.743351e-01 4.871675e-01 -9.743351e-01 1.000000e+00 7.000000e-01 9.706396e-01 9.706396e-01 4.853198e-01 -9.706396e-01 1.100000e+00 7.000000e-01 9.665715e-01 9.665715e-01 4.832858e-01 -9.665715e-01 1.200000e+00 7.000000e-01 9.621355e-01 9.621355e-01 4.810677e-01 -9.621355e-01 1.300000e+00 7.000000e-01 9.573368e-01 9.573368e-01 4.786684e-01 -9.573368e-01 1.400000e+00 7.000000e-01 9.521811e-01 9.521811e-01 4.760906e-01 -9.521811e-01 1.500000e+00 7.000000e-01 9.466745e-01 9.466745e-01 4.733372e-01 -9.466745e-01 1.600000e+00 7.000000e-01 9.408233e-01 9.408233e-01 4.704116e-01 -9.408233e-01 1.700000e+00 7.000000e-01 9.346343e-01 9.346343e-01 4.673171e-01 -9.346343e-01 1.800000e+00 7.000000e-01 9.281147e-01 9.281147e-01 4.640573e-01 -9.281147e-01 1.900000e+00 7.000000e-01 9.212720e-01 9.212720e-01 4.606360e-01 -9.212720e-01 2.000000e+00 7.000000e-01 9.141140e-01 9.141140e-01 4.570570e-01 -9.141140e-01 2.100000e+00 7.000000e-01 9.066489e-01 9.066489e-01 4.533245e-01 -9.066489e-01 2.200000e+00 7.000000e-01 8.988851e-01 8.988851e-01 4.494426e-01 -8.988851e-01 2.300000e+00 7.000000e-01 8.908315e-01 8.908315e-01 4.454157e-01 -8.908315e-01 2.400000e+00 7.000000e-01 8.824969e-01 8.824969e-01 4.412484e-01 -8.824969e-01 2.500000e+00 7.000000e-01 8.738907e-01 8.738907e-01 4.369453e-01 -8.738907e-01 2.600000e+00 7.000000e-01 8.650223e-01 8.650223e-01 4.325112e-01 -8.650223e-01 2.700000e+00 7.000000e-01 8.559015e-01 8.559015e-01 4.279507e-01 -8.559015e-01 2.800000e+00 7.000000e-01 8.465381e-01 8.465381e-01 4.232691e-01 -8.465381e-01 2.900000e+00 7.000000e-01 8.369424e-01 8.369424e-01 4.184712e-01 -8.369424e-01 3.000000e+00 7.000000e-01 8.271245e-01 8.271245e-01 4.135623e-01 -8.271245e-01 3.100000e+00 7.000000e-01 8.170949e-01 8.170949e-01 4.085475e-01 -8.170949e-01 3.200000e+00 7.000000e-01 8.068641e-01 8.068641e-01 4.034321e-01 -8.068641e-01 3.300000e+00 7.000000e-01 7.964428e-01 7.964428e-01 3.982214e-01 -7.964428e-01 3.400000e+00 7.000000e-01 7.858416e-01 7.858416e-01 3.929208e-01 -7.858416e-01 3.500000e+00 7.000000e-01 7.750715e-01 7.750715e-01 3.875358e-01 -7.750715e-01 3.600000e+00 7.000000e-01 7.641433e-01 7.641433e-01 3.820716e-01 -7.641433e-01 3.700000e+00 7.000000e-01 7.530678e-01 7.530678e-01 3.765339e-01 -7.530678e-01 3.800000e+00 7.000000e-01 7.418561e-01 7.418561e-01 3.709280e-01 -7.418561e-01 3.900000e+00 7.000000e-01 7.305190e-01 7.305190e-01 3.652595e-01 -7.305190e-01 4.000000e+00 7.000000e-01 7.190675e-01 7.190675e-01 3.595338e-01 -7.190675e-01 4.100000e+00 7.000000e-01 7.075125e-01 7.075125e-01 3.537562e-01 -7.075125e-01 4.200000e+00 7.000000e-01 6.958647e-01 6.958647e-01 3.479324e-01 -6.958647e-01 4.300000e+00 7.000000e-01 6.841350e-01 6.841350e-01 3.420675e-01 -6.841350e-01 4.400000e+00 7.000000e-01 6.723340e-01 6.723340e-01 3.361670e-01 -6.723340e-01 4.500000e+00 7.000000e-01 6.604724e-01 6.604724e-01 3.302362e-01 -6.604724e-01 4.600000e+00 7.000000e-01 6.485605e-01 6.485605e-01 3.242803e-01 -6.485605e-01 4.700000e+00 7.000000e-01 6.366088e-01 6.366088e-01 3.183044e-01 -6.366088e-01 4.800000e+00 7.000000e-01 6.246274e-01 6.246274e-01 3.123137e-01 -6.246274e-01 4.900000e+00 7.000000e-01 6.126264e-01 6.126264e-01 3.063132e-01 -6.126264e-01 -5.000000e+00 8.000000e-01 5.988166e-01 5.988166e-01 2.994083e-01 -5.988166e-01 -4.900000e+00 8.000000e-01 6.107913e-01 6.107913e-01 3.053956e-01 -6.107913e-01 -4.800000e+00 8.000000e-01 6.227563e-01 6.227563e-01 3.113782e-01 -6.227563e-01 -4.700000e+00 8.000000e-01 6.347018e-01 6.347018e-01 3.173509e-01 -6.347018e-01 -4.600000e+00 8.000000e-01 6.466178e-01 6.466178e-01 3.233089e-01 -6.466178e-01 -4.500000e+00 8.000000e-01 6.584939e-01 6.584939e-01 3.292470e-01 -6.584939e-01 -4.400000e+00 8.000000e-01 6.703200e-01 6.703200e-01 3.351600e-01 -6.703200e-01 -4.300000e+00 8.000000e-01 6.820857e-01 6.820857e-01 3.410428e-01 -6.820857e-01 -4.200000e+00 8.000000e-01 6.937802e-01 6.937802e-01 3.468901e-01 -6.937802e-01 -4.100000e+00 8.000000e-01 7.053931e-01 7.053931e-01 3.526966e-01 -7.053931e-01 -4.000000e+00 8.000000e-01 7.169135e-01 7.169135e-01 3.584568e-01 -7.169135e-01 -3.900000e+00 8.000000e-01 7.283307e-01 7.283307e-01 3.641654e-01 -7.283307e-01 -3.800000e+00 8.000000e-01 7.396339e-01 7.396339e-01 3.698169e-01 -7.396339e-01 -3.700000e+00 8.000000e-01 7.508120e-01 7.508120e-01 3.754060e-01 -7.508120e-01 -3.600000e+00 8.000000e-01 7.618543e-01 7.618543e-01 3.809271e-01 -7.618543e-01 -3.500000e+00 8.000000e-01 7.727498e-01 7.727498e-01 3.863749e-01 -7.727498e-01 -3.400000e+00 8.000000e-01 7.834876e-01 7.834876e-01 3.917438e-01 -7.834876e-01 -3.300000e+00 8.000000e-01 7.940571e-01 7.940571e-01 3.970285e-01 -7.940571e-01 -3.200000e+00 8.000000e-01 8.044472e-01 8.044472e-01 4.022236e-01 -8.044472e-01 -3.100000e+00 8.000000e-01 8.146473e-01 8.146473e-01 4.073237e-01 -8.146473e-01 -3.000000e+00 8.000000e-01 8.246469e-01 8.246469e-01 4.123234e-01 -8.246469e-01 -2.900000e+00 8.000000e-01 8.344353e-01 8.344353e-01 4.172177e-01 -8.344353e-01 -2.800000e+00 8.000000e-01 8.440024e-01 8.440024e-01 4.220012e-01 -8.440024e-01 -2.700000e+00 8.000000e-01 8.533376e-01 8.533376e-01 4.266688e-01 -8.533376e-01 -2.600000e+00 8.000000e-01 8.624311e-01 8.624311e-01 4.312156e-01 -8.624311e-01 -2.500000e+00 8.000000e-01 8.712729e-01 8.712729e-01 4.356365e-01 -8.712729e-01 -2.400000e+00 8.000000e-01 8.798534e-01 8.798534e-01 4.399267e-01 -8.798534e-01 -2.300000e+00 8.000000e-01 8.881630e-01 8.881630e-01 4.440815e-01 -8.881630e-01 -2.200000e+00 8.000000e-01 8.961926e-01 8.961926e-01 4.480963e-01 -8.961926e-01 -2.100000e+00 8.000000e-01 9.039330e-01 9.039330e-01 4.519665e-01 -9.039330e-01 -2.000000e+00 8.000000e-01 9.113758e-01 9.113758e-01 4.556879e-01 -9.113758e-01 -1.900000e+00 8.000000e-01 9.185123e-01 9.185123e-01 4.592561e-01 -9.185123e-01 -1.800000e+00 8.000000e-01 9.253345e-01 9.253345e-01 4.626673e-01 -9.253345e-01 -1.700000e+00 8.000000e-01 9.318345e-01 9.318345e-01 4.659173e-01 -9.318345e-01 -1.600000e+00 8.000000e-01 9.380050e-01 9.380050e-01 4.690025e-01 -9.380050e-01 -1.500000e+00 8.000000e-01 9.438387e-01 9.438387e-01 4.719194e-01 -9.438387e-01 -1.400000e+00 8.000000e-01 9.493288e-01 9.493288e-01 4.746644e-01 -9.493288e-01 -1.300000e+00 8.000000e-01 9.544691e-01 9.544691e-01 4.772345e-01 -9.544691e-01 -1.200000e+00 8.000000e-01 9.592534e-01 9.592534e-01 4.796267e-01 -9.592534e-01 -1.100000e+00 8.000000e-01 9.636762e-01 9.636762e-01 4.818381e-01 -9.636762e-01 -1.000000e+00 8.000000e-01 9.677321e-01 9.677321e-01 4.838660e-01 -9.677321e-01 -9.000000e-01 8.000000e-01 9.714165e-01 9.714165e-01 4.857082e-01 -9.714165e-01 -8.000000e-01 8.000000e-01 9.747249e-01 9.747249e-01 4.873624e-01 -9.747249e-01 -7.000000e-01 8.000000e-01 9.776534e-01 9.776534e-01 4.888267e-01 -9.776534e-01 -6.000000e-01 8.000000e-01 9.801987e-01 9.801987e-01 4.900993e-01 -9.801987e-01 -5.000000e-01 8.000000e-01 9.823575e-01 9.823575e-01 4.911788e-01 -9.823575e-01 -4.000000e-01 8.000000e-01 9.841273e-01 9.841273e-01 4.920637e-01 -9.841273e-01 -3.000000e-01 8.000000e-01 9.855061e-01 9.855061e-01 4.927530e-01 -9.855061e-01 -2.000000e-01 8.000000e-01 9.864920e-01 9.864920e-01 4.932460e-01 -9.864920e-01 -1.000000e-01 8.000000e-01 9.870842e-01 9.870842e-01 4.935421e-01 -9.870842e-01 0.000000e+00 8.000000e-01 9.872816e-01 9.872816e-01 4.936408e-01 -9.872816e-01 1.000000e-01 8.000000e-01 9.870842e-01 9.870842e-01 4.935421e-01 -9.870842e-01 2.000000e-01 8.000000e-01 9.864920e-01 9.864920e-01 4.932460e-01 -9.864920e-01 3.000000e-01 8.000000e-01 9.855061e-01 9.855061e-01 4.927530e-01 -9.855061e-01 4.000000e-01 8.000000e-01 9.841273e-01 9.841273e-01 4.920637e-01 -9.841273e-01 5.000000e-01 8.000000e-01 9.823575e-01 9.823575e-01 4.911788e-01 -9.823575e-01 6.000000e-01 8.000000e-01 9.801987e-01 9.801987e-01 4.900993e-01 -9.801987e-01 7.000000e-01 8.000000e-01 9.776534e-01 9.776534e-01 4.888267e-01 -9.776534e-01 8.000000e-01 8.000000e-01 9.747249e-01 9.747249e-01 4.873624e-01 -9.747249e-01 9.000000e-01 8.000000e-01 9.714165e-01 9.714165e-01 4.857082e-01 -9.714165e-01 1.000000e+00 8.000000e-01 9.677321e-01 9.677321e-01 4.838660e-01 -9.677321e-01 1.100000e+00 8.000000e-01 9.636762e-01 9.636762e-01 4.818381e-01 -9.636762e-01 1.200000e+00 8.000000e-01 9.592534e-01 9.592534e-01 4.796267e-01 -9.592534e-01 1.300000e+00 8.000000e-01 9.544691e-01 9.544691e-01 4.772345e-01 -9.544691e-01 1.400000e+00 8.000000e-01 9.493288e-01 9.493288e-01 4.746644e-01 -9.493288e-01 1.500000e+00 8.000000e-01 9.438387e-01 9.438387e-01 4.719194e-01 -9.438387e-01 1.600000e+00 8.000000e-01 9.380050e-01 9.380050e-01 4.690025e-01 -9.380050e-01 1.700000e+00 8.000000e-01 9.318345e-01 9.318345e-01 4.659173e-01 -9.318345e-01 1.800000e+00 8.000000e-01 9.253345e-01 9.253345e-01 4.626673e-01 -9.253345e-01 1.900000e+00 8.000000e-01 9.185123e-01 9.185123e-01 4.592561e-01 -9.185123e-01 2.000000e+00 8.000000e-01 9.113758e-01 9.113758e-01 4.556879e-01 -9.113758e-01 2.100000e+00 8.000000e-01 9.039330e-01 9.039330e-01 4.519665e-01 -9.039330e-01 2.200000e+00 8.000000e-01 8.961926e-01 8.961926e-01 4.480963e-01 -8.961926e-01 2.300000e+00 8.000000e-01 8.881630e-01 8.881630e-01 4.440815e-01 -8.881630e-01 2.400000e+00 8.000000e-01 8.798534e-01 8.798534e-01 4.399267e-01 -8.798534e-01 2.500000e+00 8.000000e-01 8.712729e-01 8.712729e-01 4.356365e-01 -8.712729e-01 2.600000e+00 8.000000e-01 8.624311e-01 8.624311e-01 4.312156e-01 -8.624311e-01 2.700000e+00 8.000000e-01 8.533376e-01 8.533376e-01 4.266688e-01 -8.533376e-01 2.800000e+00 8.000000e-01 8.440024e-01 8.440024e-01 4.220012e-01 -8.440024e-01 2.900000e+00 8.000000e-01 8.344353e-01 8.344353e-01 4.172177e-01 -8.344353e-01 3.000000e+00 8.000000e-01 8.246469e-01 8.246469e-01 4.123234e-01 -8.246469e-01 3.100000e+00 8.000000e-01 8.146473e-01 8.146473e-01 4.073237e-01 -8.146473e-01 3.200000e+00 8.000000e-01 8.044472e-01 8.044472e-01 4.022236e-01 -8.044472e-01 3.300000e+00 8.000000e-01 7.940571e-01 7.940571e-01 3.970285e-01 -7.940571e-01 3.400000e+00 8.000000e-01 7.834876e-01 7.834876e-01 3.917438e-01 -7.834876e-01 3.500000e+00 8.000000e-01 7.727498e-01 7.727498e-01 3.863749e-01 -7.727498e-01 3.600000e+00 8.000000e-01 7.618543e-01 7.618543e-01 3.809271e-01 -7.618543e-01 3.700000e+00 8.000000e-01 7.508120e-01 7.508120e-01 3.754060e-01 -7.508120e-01 3.800000e+00 8.000000e-01 7.396339e-01 7.396339e-01 3.698169e-01 -7.396339e-01 3.900000e+00 8.000000e-01 7.283307e-01 7.283307e-01 3.641654e-01 -7.283307e-01 4.000000e+00 8.000000e-01 7.169135e-01 7.169135e-01 3.584568e-01 -7.169135e-01 4.100000e+00 8.000000e-01 7.053931e-01 7.053931e-01 3.526966e-01 -7.053931e-01 4.200000e+00 8.000000e-01 6.937802e-01 6.937802e-01 3.468901e-01 -6.937802e-01 4.300000e+00 8.000000e-01 6.820857e-01 6.820857e-01 3.410428e-01 -6.820857e-01 4.400000e+00 8.000000e-01 6.703200e-01 6.703200e-01 3.351600e-01 -6.703200e-01 4.500000e+00 8.000000e-01 6.584939e-01 6.584939e-01 3.292470e-01 -6.584939e-01 4.600000e+00 8.000000e-01 6.466178e-01 6.466178e-01 3.233089e-01 -6.466178e-01 4.700000e+00 8.000000e-01 6.347018e-01 6.347018e-01 3.173509e-01 -6.347018e-01 4.800000e+00 8.000000e-01 6.227563e-01 6.227563e-01 3.113782e-01 -6.227563e-01 4.900000e+00 8.000000e-01 6.107913e-01 6.107913e-01 3.053956e-01 -6.107913e-01 -5.000000e+00 9.000000e-01 5.967840e-01 5.967840e-01 2.983920e-01 -5.967840e-01 -4.900000e+00 9.000000e-01 6.087181e-01 6.087181e-01 3.043590e-01 -6.087181e-01 -4.800000e+00 9.000000e-01 6.206425e-01 6.206425e-01 3.103212e-01 -6.206425e-01 -4.700000e+00 9.000000e-01 6.325475e-01 6.325475e-01 3.162737e-01 -6.325475e-01 -4.600000e+00 9.000000e-01 6.444230e-01 6.444230e-01 3.222115e-01 -6.444230e-01 -4.500000e+00 9.000000e-01 6.562589e-01 6.562589e-01 3.281294e-01 -6.562589e-01 -4.400000e+00 9.000000e-01 6.680448e-01 6.680448e-01 3.340224e-01 -6.680448e-01 -4.300000e+00 9.000000e-01 6.797705e-01 6.797705e-01 3.398853e-01 -6.797705e-01 -4.200000e+00 9.000000e-01 6.914254e-01 6.914254e-01 3.457127e-01 -6.914254e-01 -4.100000e+00 9.000000e-01 7.029989e-01 7.029989e-01 3.514994e-01 -7.029989e-01 -4.000000e+00 9.000000e-01 7.144802e-01 7.144802e-01 3.572401e-01 -7.144802e-01 -3.900000e+00 9.000000e-01 7.258586e-01 7.258586e-01 3.629293e-01 -7.258586e-01 -3.800000e+00 9.000000e-01 7.371234e-01 7.371234e-01 3.685617e-01 -7.371234e-01 -3.700000e+00 9.000000e-01 7.482635e-01 7.482635e-01 3.741318e-01 -7.482635e-01 -3.600000e+00 9.000000e-01 7.592683e-01 7.592683e-01 3.796342e-01 -7.592683e-01 -3.500000e+00 9.000000e-01 7.701269e-01 7.701269e-01 3.850634e-01 -7.701269e-01 -3.400000e+00 9.000000e-01 7.808283e-01 7.808283e-01 3.904141e-01 -7.808283e-01 -3.300000e+00 9.000000e-01 7.913619e-01 7.913619e-01 3.956809e-01 -7.913619e-01 -3.200000e+00 9.000000e-01 8.017167e-01 8.017167e-01 4.008583e-01 -8.017167e-01 -3.100000e+00 9.000000e-01 8.118822e-01 8.118822e-01 4.059411e-01 -8.118822e-01 -3.000000e+00 9.000000e-01 8.218479e-01 8.218479e-01 4.109239e-01 -8.218479e-01 -2.900000e+00 9.000000e-01 8.316031e-01 8.316031e-01 4.158015e-01 -8.316031e-01 -2.800000e+00 9.000000e-01 8.411376e-01 8.411376e-01 4.205688e-01 -8.411376e-01 -2.700000e+00 9.000000e-01 8.504412e-01 8.504412e-01 4.252206e-01 -8.504412e-01 -2.600000e+00 9.000000e-01 8.595038e-01 8.595038e-01 4.297519e-01 -8.595038e-01 -2.500000e+00 9.000000e-01 8.683156e-01 8.683156e-01 4.341578e-01 -8.683156e-01 -2.400000e+00 9.000000e-01 8.768669e-01 8.768669e-01 4.384335e-01 -8.768669e-01 -2.300000e+00 9.000000e-01 8.851484e-01 8.851484e-01 4.425742e-01 -8.851484e-01 -2.200000e+00 9.000000e-01 8.931507e-01 8.931507e-01 4.465753e-01 -8.931507e-01 -2.100000e+00 9.000000e-01 9.008649e-01 9.008649e-01 4.504324e-01 -9.008649e-01 -2.000000e+00 9.000000e-01 9.082823e-01 9.082823e-01 4.541412e-01 -9.082823e-01 -1.900000e+00 9.000000e-01 9.153947e-01 9.153947e-01 4.576973e-01 -9.153947e-01 -1.800000e+00 9.000000e-01 9.221937e-01 9.221937e-01 4.610969e-01 -9.221937e-01 -1.700000e+00 9.000000e-01 9.286717e-01 9.286717e-01 4.643359e-01 -9.286717e-01 -1.600000e+00 9.000000e-01 9.348212e-01 9.348212e-01 4.674106e-01 -9.348212e-01 -1.500000e+00 9.000000e-01 9.406351e-01 9.406351e-01 4.703175e-01 -9.406351e-01 -1.400000e+00 9.000000e-01 9.461066e-01 9.461066e-01 4.730533e-01 -9.461066e-01 -1.300000e+00 9.000000e-01 9.512295e-01 9.512295e-01 4.756147e-01 -9.512295e-01 -1.200000e+00 9.000000e-01 9.559975e-01 9.559975e-01 4.779987e-01 -9.559975e-01 -1.100000e+00 9.000000e-01 9.604052e-01 9.604052e-01 4.802026e-01 -9.604052e-01 -1.000000e+00 9.000000e-01 9.644474e-01 9.644474e-01 4.822237e-01 -9.644474e-01 -9.000000e-01 9.000000e-01 9.681193e-01 9.681193e-01 4.840596e-01 -9.681193e-01 -8.000000e-01 9.000000e-01 9.714165e-01 9.714165e-01 4.857082e-01 -9.714165e-01 -7.000000e-01 9.000000e-01 9.743351e-01 9.743351e-01 4.871675e-01 -9.743351e-01 -6.000000e-01 9.000000e-01 9.768717e-01 9.768717e-01 4.884358e-01 -9.768717e-01 -5.000000e-01 9.000000e-01 9.790232e-01 9.790232e-01 4.895116e-01 -9.790232e-01 -4.000000e-01 9.000000e-01 9.807870e-01 9.807870e-01 4.903935e-01 -9.807870e-01 -3.000000e-01 9.000000e-01 9.821610e-01 9.821610e-01 4.910805e-01 -9.821610e-01 -2.000000e-01 9.000000e-01 9.831437e-01 9.831437e-01 4.915718e-01 -9.831437e-01 -1.000000e-01 9.000000e-01 9.837338e-01 9.837338e-01 4.918669e-01 -9.837338e-01 0.000000e+00 9.000000e-01 9.839305e-01 9.839305e-01 4.919653e-01 -9.839305e-01 1.000000e-01 9.000000e-01 9.837338e-01 9.837338e-01 4.918669e-01 -9.837338e-01 2.000000e-01 9.000000e-01 9.831437e-01 9.831437e-01 4.915718e-01 -9.831437e-01 3.000000e-01 9.000000e-01 9.821610e-01 9.821610e-01 4.910805e-01 -9.821610e-01 4.000000e-01 9.000000e-01 9.807870e-01 9.807870e-01 4.903935e-01 -9.807870e-01 5.000000e-01 9.000000e-01 9.790232e-01 9.790232e-01 4.895116e-01 -9.790232e-01 6.000000e-01 9.000000e-01 9.768717e-01 9.768717e-01 4.884358e-01 -9.768717e-01 7.000000e-01 9.000000e-01 9.743351e-01 9.743351e-01 4.871675e-01 -9.743351e-01 8.000000e-01 9.000000e-01 9.714165e-01 9.714165e-01 4.857082e-01 -9.714165e-01 9.000000e-01 9.000000e-01 9.681193e-01 9.681193e-01 4.840596e-01 -9.681193e-01 1.000000e+00 9.000000e-01 9.644474e-01 9.644474e-01 4.822237e-01 -9.644474e-01 1.100000e+00 9.000000e-01 9.604052e-01 9.604052e-01 4.802026e-01 -9.604052e-01 1.200000e+00 9.000000e-01 9.559975e-01 9.559975e-01 4.779987e-01 -9.559975e-01 1.300000e+00 9.000000e-01 9.512295e-01 9.512295e-01 4.756147e-01 -9.512295e-01 1.400000e+00 9.000000e-01 9.461066e-01 9.461066e-01 4.730533e-01 -9.461066e-01 1.500000e+00 9.000000e-01 9.406351e-01 9.406351e-01 4.703175e-01 -9.406351e-01 1.600000e+00 9.000000e-01 9.348212e-01 9.348212e-01 4.674106e-01 -9.348212e-01 1.700000e+00 9.000000e-01 9.286717e-01 9.286717e-01 4.643359e-01 -9.286717e-01 1.800000e+00 9.000000e-01 9.221937e-01 9.221937e-01 4.610969e-01 -9.221937e-01 1.900000e+00 9.000000e-01 9.153947e-01 9.153947e-01 4.576973e-01 -9.153947e-01 2.000000e+00 9.000000e-01 9.082823e-01 9.082823e-01 4.541412e-01 -9.082823e-01 2.100000e+00 9.000000e-01 9.008649e-01 9.008649e-01 4.504324e-01 -9.008649e-01 2.200000e+00 9.000000e-01 8.931507e-01 8.931507e-01 4.465753e-01 -8.931507e-01 2.300000e+00 9.000000e-01 8.851484e-01 8.851484e-01 4.425742e-01 -8.851484e-01 2.400000e+00 9.000000e-01 8.768669e-01 8.768669e-01 4.384335e-01 -8.768669e-01 2.500000e+00 9.000000e-01 8.683156e-01 8.683156e-01 4.341578e-01 -8.683156e-01 2.600000e+00 9.000000e-01 8.595038e-01 8.595038e-01 4.297519e-01 -8.595038e-01 2.700000e+00 9.000000e-01 8.504412e-01 8.504412e-01 4.252206e-01 -8.504412e-01 2.800000e+00 9.000000e-01 8.411376e-01 8.411376e-01 4.205688e-01 -8.411376e-01 2.900000e+00 9.000000e-01 8.316031e-01 8.316031e-01 4.158015e-01 -8.316031e-01 3.000000e+00 9.000000e-01 8.218479e-01 8.218479e-01 4.109239e-01 -8.218479e-01 3.100000e+00 9.000000e-01 8.118822e-01 8.118822e-01 4.059411e-01 -8.118822e-01 3.200000e+00 9.000000e-01 8.017167e-01 8.017167e-01 4.008583e-01 -8.017167e-01 3.300000e+00 9.000000e-01 7.913619e-01 7.913619e-01 3.956809e-01 -7.913619e-01 3.400000e+00 9.000000e-01 7.808283e-01 7.808283e-01 3.904141e-01 -7.808283e-01 3.500000e+00 9.000000e-01 7.701269e-01 7.701269e-01 3.850634e-01 -7.701269e-01 3.600000e+00 9.000000e-01 7.592683e-01 7.592683e-01 3.796342e-01 -7.592683e-01 3.700000e+00 9.000000e-01 7.482635e-01 7.482635e-01 3.741318e-01 -7.482635e-01 3.800000e+00 9.000000e-01 7.371234e-01 7.371234e-01 3.685617e-01 -7.371234e-01 3.900000e+00 9.000000e-01 7.258586e-01 7.258586e-01 3.629293e-01 -7.258586e-01 4.000000e+00 9.000000e-01 7.144802e-01 7.144802e-01 3.572401e-01 -7.144802e-01 4.100000e+00 9.000000e-01 7.029989e-01 7.029989e-01 3.514994e-01 -7.029989e-01 4.200000e+00 9.000000e-01 6.914254e-01 6.914254e-01 3.457127e-01 -6.914254e-01 4.300000e+00 9.000000e-01 6.797705e-01 6.797705e-01 3.398853e-01 -6.797705e-01 4.400000e+00 9.000000e-01 6.680448e-01 6.680448e-01 3.340224e-01 -6.680448e-01 4.500000e+00 9.000000e-01 6.562589e-01 6.562589e-01 3.281294e-01 -6.562589e-01 4.600000e+00 9.000000e-01 6.444230e-01 6.444230e-01 3.222115e-01 -6.444230e-01 4.700000e+00 9.000000e-01 6.325475e-01 6.325475e-01 3.162737e-01 -6.325475e-01 4.800000e+00 9.000000e-01 6.206425e-01 6.206425e-01 3.103212e-01 -6.206425e-01 4.900000e+00 9.000000e-01 6.087181e-01 6.087181e-01 3.043590e-01 -6.087181e-01 -5.000000e+00 1.000000e+00 5.945206e-01 5.945206e-01 2.972603e-01 -5.945206e-01 -4.900000e+00 1.000000e+00 6.064094e-01 6.064094e-01 3.032047e-01 -6.064094e-01 -4.800000e+00 1.000000e+00 6.182885e-01 6.182885e-01 3.091443e-01 -6.182885e-01 -4.700000e+00 1.000000e+00 6.301484e-01 6.301484e-01 3.150742e-01 -6.301484e-01 -4.600000e+00 1.000000e+00 6.419788e-01 6.419788e-01 3.209894e-01 -6.419788e-01 -4.500000e+00 1.000000e+00 6.537698e-01 6.537698e-01 3.268849e-01 -6.537698e-01 -4.400000e+00 1.000000e+00 6.655111e-01 6.655111e-01 3.327555e-01 -6.655111e-01 -4.300000e+00 1.000000e+00 6.771923e-01 6.771923e-01 3.385961e-01 -6.771923e-01 -4.200000e+00 1.000000e+00 6.888030e-01 6.888030e-01 3.444015e-01 -6.888030e-01 -4.100000e+00 1.000000e+00 7.003325e-01 7.003325e-01 3.501663e-01 -7.003325e-01 -4.000000e+00 1.000000e+00 7.117703e-01 7.117703e-01 3.558851e-01 -7.117703e-01 -3.900000e+00 1.000000e+00 7.231056e-01 7.231056e-01 3.615528e-01 -7.231056e-01 -3.800000e+00 1.000000e+00 7.343276e-01 7.343276e-01 3.671638e-01 -7.343276e-01 -3.700000e+00 1.000000e+00 7.454255e-01 7.454255e-01 3.727128e-01 -7.454255e-01 -3.600000e+00 1.000000e+00 7.563886e-01 7.563886e-01 3.781943e-01 -7.563886e-01 -3.500000e+00 1.000000e+00 7.672060e-01 7.672060e-01 3.836030e-01 -7.672060e-01 -3.400000e+00 1.000000e+00 7.778668e-01 7.778668e-01 3.889334e-01 -7.778668e-01 -3.300000e+00 1.000000e+00 7.883604e-01 7.883604e-01 3.941802e-01 -7.883604e-01 -3.200000e+00 1.000000e+00 7.986760e-01 7.986760e-01 3.993380e-01 -7.986760e-01 -3.100000e+00 1.000000e+00 8.088029e-01 8.088029e-01 4.044015e-01 -8.088029e-01 -3.000000e+00 1.000000e+00 8.187308e-01 8.187308e-01 4.093654e-01 -8.187308e-01 -2.900000e+00 1.000000e+00 8.284490e-01 8.284490e-01 4.142245e-01 -8.284490e-01 -2.800000e+00 1.000000e+00 8.379474e-01 8.379474e-01 4.189737e-01 -8.379474e-01 -2.700000e+00 1.000000e+00 8.472157e-01 8.472157e-01 4.236078e-01 -8.472157e-01 -2.600000e+00 1.000000e+00 8.562439e-01 8.562439e-01 4.281220e-01 -8.562439e-01 -2.500000e+00 1.000000e+00 8.650223e-01 8.650223e-01 4.325112e-01 -8.650223e-01 -2.400000e+00 1.000000e+00 8.735412e-01 8.735412e-01 4.367706e-01 -8.735412e-01 -2.300000e+00 1.000000e+00 8.817912e-01 8.817912e-01 4.408956e-01 -8.817912e-01 -2.200000e+00 1.000000e+00 8.897631e-01 8.897631e-01 4.448816e-01 -8.897631e-01 -2.100000e+00 1.000000e+00 8.974481e-01 8.974481e-01 4.487240e-01 -8.974481e-01 -2.000000e+00 1.000000e+00 9.048374e-01 9.048374e-01 4.524187e-01 -9.048374e-01 -1.900000e+00 1.000000e+00 9.119228e-01 9.119228e-01 4.559614e-01 -9.119228e-01 -1.800000e+00 1.000000e+00 9.186960e-01 9.186960e-01 4.593480e-01 -9.186960e-01 -1.700000e+00 1.000000e+00 9.251494e-01 9.251494e-01 4.625747e-01 -9.251494e-01 -1.600000e+00 1.000000e+00 9.312756e-01 9.312756e-01 4.656378e-01 -9.312756e-01 -1.500000e+00 1.000000e+00 9.370674e-01 9.370674e-01 4.685337e-01 -9.370674e-01 -1.400000e+00 1.000000e+00 9.425182e-01 9.425182e-01 4.712591e-01 -9.425182e-01 -1.300000e+00 1.000000e+00 9.476216e-01 9.476216e-01 4.738108e-01 -9.476216e-01 -1.200000e+00 1.000000e+00 9.523716e-01 9.523716e-01 4.761858e-01 -9.523716e-01 -1.100000e+00 1.000000e+00 9.567626e-01 9.567626e-01 4.783813e-01 -9.567626e-01 -1.000000e+00 1.000000e+00 9.607894e-01 9.607894e-01 4.803947e-01 -9.607894e-01 -9.000000e-01 1.000000e+00 9.644474e-01 9.644474e-01 4.822237e-01 -9.644474e-01 -8.000000e-01 1.000000e+00 9.677321e-01 9.677321e-01 4.838660e-01 -9.677321e-01 -7.000000e-01 1.000000e+00 9.706396e-01 9.706396e-01 4.853198e-01 -9.706396e-01 -6.000000e-01 1.000000e+00 9.731666e-01 9.731666e-01 4.865833e-01 -9.731666e-01 -5.000000e-01 1.000000e+00 9.753099e-01 9.753099e-01 4.876550e-01 -9.753099e-01 -4.000000e-01 1.000000e+00 9.770671e-01 9.770671e-01 4.885335e-01 -9.770671e-01 -3.000000e-01 1.000000e+00 9.784359e-01 9.784359e-01 4.892179e-01 -9.784359e-01 -2.000000e-01 1.000000e+00 9.794148e-01 9.794148e-01 4.897074e-01 -9.794148e-01 -1.000000e-01 1.000000e+00 9.800026e-01 9.800026e-01 4.900013e-01 -9.800026e-01 0.000000e+00 1.000000e+00 9.801987e-01 9.801987e-01 4.900993e-01 -9.801987e-01 1.000000e-01 1.000000e+00 9.800026e-01 9.800026e-01 4.900013e-01 -9.800026e-01 2.000000e-01 1.000000e+00 9.794148e-01 9.794148e-01 4.897074e-01 -9.794148e-01 3.000000e-01 1.000000e+00 9.784359e-01 9.784359e-01 4.892179e-01 -9.784359e-01 4.000000e-01 1.000000e+00 9.770671e-01 9.770671e-01 4.885335e-01 -9.770671e-01 5.000000e-01 1.000000e+00 9.753099e-01 9.753099e-01 4.876550e-01 -9.753099e-01 6.000000e-01 1.000000e+00 9.731666e-01 9.731666e-01 4.865833e-01 -9.731666e-01 7.000000e-01 1.000000e+00 9.706396e-01 9.706396e-01 4.853198e-01 -9.706396e-01 8.000000e-01 1.000000e+00 9.677321e-01 9.677321e-01 4.838660e-01 -9.677321e-01 9.000000e-01 1.000000e+00 9.644474e-01 9.644474e-01 4.822237e-01 -9.644474e-01 1.000000e+00 1.000000e+00 9.607894e-01 9.607894e-01 4.803947e-01 -9.607894e-01 1.100000e+00 1.000000e+00 9.567626e-01 9.567626e-01 4.783813e-01 -9.567626e-01 1.200000e+00 1.000000e+00 9.523716e-01 9.523716e-01 4.761858e-01 -9.523716e-01 1.300000e+00 1.000000e+00 9.476216e-01 9.476216e-01 4.738108e-01 -9.476216e-01 1.400000e+00 1.000000e+00 9.425182e-01 9.425182e-01 4.712591e-01 -9.425182e-01 1.500000e+00 1.000000e+00 9.370674e-01 9.370674e-01 4.685337e-01 -9.370674e-01 1.600000e+00 1.000000e+00 9.312756e-01 9.312756e-01 4.656378e-01 -9.312756e-01 1.700000e+00 1.000000e+00 9.251494e-01 9.251494e-01 4.625747e-01 -9.251494e-01 1.800000e+00 1.000000e+00 9.186960e-01 9.186960e-01 4.593480e-01 -9.186960e-01 1.900000e+00 1.000000e+00 9.119228e-01 9.119228e-01 4.559614e-01 -9.119228e-01 2.000000e+00 1.000000e+00 9.048374e-01 9.048374e-01 4.524187e-01 -9.048374e-01 2.100000e+00 1.000000e+00 8.974481e-01 8.974481e-01 4.487240e-01 -8.974481e-01 2.200000e+00 1.000000e+00 8.897631e-01 8.897631e-01 4.448816e-01 -8.897631e-01 2.300000e+00 1.000000e+00 8.817912e-01 8.817912e-01 4.408956e-01 -8.817912e-01 2.400000e+00 1.000000e+00 8.735412e-01 8.735412e-01 4.367706e-01 -8.735412e-01 2.500000e+00 1.000000e+00 8.650223e-01 8.650223e-01 4.325112e-01 -8.650223e-01 2.600000e+00 1.000000e+00 8.562439e-01 8.562439e-01 4.281220e-01 -8.562439e-01 2.700000e+00 1.000000e+00 8.472157e-01 8.472157e-01 4.236078e-01 -8.472157e-01 2.800000e+00 1.000000e+00 8.379474e-01 8.379474e-01 4.189737e-01 -8.379474e-01 2.900000e+00 1.000000e+00 8.284490e-01 8.284490e-01 4.142245e-01 -8.284490e-01 3.000000e+00 1.000000e+00 8.187308e-01 8.187308e-01 4.093654e-01 -8.187308e-01 3.100000e+00 1.000000e+00 8.088029e-01 8.088029e-01 4.044015e-01 -8.088029e-01 3.200000e+00 1.000000e+00 7.986760e-01 7.986760e-01 3.993380e-01 -7.986760e-01 3.300000e+00 1.000000e+00 7.883604e-01 7.883604e-01 3.941802e-01 -7.883604e-01 3.400000e+00 1.000000e+00 7.778668e-01 7.778668e-01 3.889334e-01 -7.778668e-01 3.500000e+00 1.000000e+00 7.672060e-01 7.672060e-01 3.836030e-01 -7.672060e-01 3.600000e+00 1.000000e+00 7.563886e-01 7.563886e-01 3.781943e-01 -7.563886e-01 3.700000e+00 1.000000e+00 7.454255e-01 7.454255e-01 3.727128e-01 -7.454255e-01 3.800000e+00 1.000000e+00 7.343276e-01 7.343276e-01 3.671638e-01 -7.343276e-01 3.900000e+00 1.000000e+00 7.231056e-01 7.231056e-01 3.615528e-01 -7.231056e-01 4.000000e+00 1.000000e+00 7.117703e-01 7.117703e-01 3.558851e-01 -7.117703e-01 4.100000e+00 1.000000e+00 7.003325e-01 7.003325e-01 3.501663e-01 -7.003325e-01 4.200000e+00 1.000000e+00 6.888030e-01 6.888030e-01 3.444015e-01 -6.888030e-01 4.300000e+00 1.000000e+00 6.771923e-01 6.771923e-01 3.385961e-01 -6.771923e-01 4.400000e+00 1.000000e+00 6.655111e-01 6.655111e-01 3.327555e-01 -6.655111e-01 4.500000e+00 1.000000e+00 6.537698e-01 6.537698e-01 3.268849e-01 -6.537698e-01 4.600000e+00 1.000000e+00 6.419788e-01 6.419788e-01 3.209894e-01 -6.419788e-01 4.700000e+00 1.000000e+00 6.301484e-01 6.301484e-01 3.150742e-01 -6.301484e-01 4.800000e+00 1.000000e+00 6.182885e-01 6.182885e-01 3.091443e-01 -6.182885e-01 4.900000e+00 1.000000e+00 6.064094e-01 6.064094e-01 3.032047e-01 -6.064094e-01 -5.000000e+00 1.100000e+00 5.920288e-01 5.920288e-01 2.960144e-01 -5.920288e-01 -4.900000e+00 1.100000e+00 6.038678e-01 6.038678e-01 3.019339e-01 -6.038678e-01 -4.800000e+00 1.100000e+00 6.156972e-01 6.156972e-01 3.078486e-01 -6.156972e-01 -4.700000e+00 1.100000e+00 6.275073e-01 6.275073e-01 3.137537e-01 -6.275073e-01 -4.600000e+00 1.100000e+00 6.392882e-01 6.392882e-01 3.196441e-01 -6.392882e-01 -4.500000e+00 1.100000e+00 6.510297e-01 6.510297e-01 3.255149e-01 -6.510297e-01 -4.400000e+00 1.100000e+00 6.627218e-01 6.627218e-01 3.313609e-01 -6.627218e-01 -4.300000e+00 1.100000e+00 6.743541e-01 6.743541e-01 3.371770e-01 -6.743541e-01 -4.200000e+00 1.100000e+00 6.859161e-01 6.859161e-01 3.429580e-01 -6.859161e-01 -4.100000e+00 1.100000e+00 6.973973e-01 6.973973e-01 3.486986e-01 -6.973973e-01 -4.000000e+00 1.100000e+00 7.087871e-01 7.087871e-01 3.543936e-01 -7.087871e-01 -3.900000e+00 1.100000e+00 7.200749e-01 7.200749e-01 3.600374e-01 -7.200749e-01 -3.800000e+00 1.100000e+00 7.312499e-01 7.312499e-01 3.656250e-01 -7.312499e-01 -3.700000e+00 1.100000e+00 7.423013e-01 7.423013e-01 3.711507e-01 -7.423013e-01 -3.600000e+00 1.100000e+00 7.532185e-01 7.532185e-01 3.766092e-01 -7.532185e-01 -3.500000e+00 1.100000e+00 7.639905e-01 7.639905e-01 3.819952e-01 -7.639905e-01 -3.400000e+00 1.100000e+00 7.746066e-01 7.746066e-01 3.873033e-01 -7.746066e-01 -3.300000e+00 1.100000e+00 7.850562e-01 7.850562e-01 3.925281e-01 -7.850562e-01 -3.200000e+00 1.100000e+00 7.953286e-01 7.953286e-01 3.976643e-01 -7.953286e-01 -3.100000e+00 1.100000e+00 8.054131e-01 8.054131e-01 4.027065e-01 -8.054131e-01 -3.000000e+00 1.100000e+00 8.152993e-01 8.152993e-01 4.076496e-01 -8.152993e-01 -2.900000e+00 1.100000e+00 8.249768e-01 8.249768e-01 4.124884e-01 -8.249768e-01 -2.800000e+00 1.100000e+00 8.344353e-01 8.344353e-01 4.172177e-01 -8.344353e-01 -2.700000e+00 1.100000e+00 8.436648e-01 8.436648e-01 4.218324e-01 -8.436648e-01 -2.600000e+00 1.100000e+00 8.526552e-01 8.526552e-01 4.263276e-01 -8.526552e-01 -2.500000e+00 1.100000e+00 8.613968e-01 8.613968e-01 4.306984e-01 -8.613968e-01 -2.400000e+00 1.100000e+00 8.698800e-01 8.698800e-01 4.349400e-01 -8.698800e-01 -2.300000e+00 1.100000e+00 8.780954e-01 8.780954e-01 4.390477e-01 -8.780954e-01 -2.200000e+00 1.100000e+00 8.860340e-01 8.860340e-01 4.430170e-01 -8.860340e-01 -2.100000e+00 1.100000e+00 8.936867e-01 8.936867e-01 4.468434e-01 -8.936867e-01 -2.000000e+00 1.100000e+00 9.010451e-01 9.010451e-01 4.505225e-01 -9.010451e-01 -1.900000e+00 1.100000e+00 9.081007e-01 9.081007e-01 4.540504e-01 -9.081007e-01 -1.800000e+00 1.100000e+00 9.148456e-01 9.148456e-01 4.574228e-01 -9.148456e-01 -1.700000e+00 1.100000e+00 9.212720e-01 9.212720e-01 4.606360e-01 -9.212720e-01 -1.600000e+00 1.100000e+00 9.273725e-01 9.273725e-01 4.636862e-01 -9.273725e-01 -1.500000e+00 1.100000e+00 9.331400e-01 9.331400e-01 4.665700e-01 -9.331400e-01 -1.400000e+00 1.100000e+00 9.385680e-01 9.385680e-01 4.692840e-01 -9.385680e-01 -1.300000e+00 1.100000e+00 9.436499e-01 9.436499e-01 4.718250e-01 -9.436499e-01 -1.200000e+00 1.100000e+00 9.483800e-01 9.483800e-01 4.741900e-01 -9.483800e-01 -1.100000e+00 1.100000e+00 9.527526e-01 9.527526e-01 4.763763e-01 -9.527526e-01 -1.000000e+00 1.100000e+00 9.567626e-01 9.567626e-01 4.783813e-01 -9.567626e-01 -9.000000e-01 1.100000e+00 9.604052e-01 9.604052e-01 4.802026e-01 -9.604052e-01 -8.000000e-01 1.100000e+00 9.636762e-01 9.636762e-01 4.818381e-01 -9.636762e-01 -7.000000e-01 1.100000e+00 9.665715e-01 9.665715e-01 4.832858e-01 -9.665715e-01 -6.000000e-01 1.100000e+00 9.690878e-01 9.690878e-01 4.845439e-01 -9.690878e-01 -5.000000e-01 1.100000e+00 9.712222e-01 9.712222e-01 4.856111e-01 -9.712222e-01 -4.000000e-01 1.100000e+00 9.729720e-01 9.729720e-01 4.864860e-01 -9.729720e-01 -3.000000e-01 1.100000e+00 9.743351e-01 9.743351e-01 4.871675e-01 -9.743351e-01 -2.000000e-01 1.100000e+00 9.753099e-01 9.753099e-01 4.876550e-01 -9.753099e-01 -1.000000e-01 1.100000e+00 9.758953e-01 9.758953e-01 4.879476e-01 -9.758953e-01 0.000000e+00 1.100000e+00 9.760905e-01 9.760905e-01 4.880452e-01 -9.760905e-01 1.000000e-01 1.100000e+00 9.758953e-01 9.758953e-01 4.879476e-01 -9.758953e-01 2.000000e-01 1.100000e+00 9.753099e-01 9.753099e-01 4.876550e-01 -9.753099e-01 3.000000e-01 1.100000e+00 9.743351e-01 9.743351e-01 4.871675e-01 -9.743351e-01 4.000000e-01 1.100000e+00 9.729720e-01 9.729720e-01 4.864860e-01 -9.729720e-01 5.000000e-01 1.100000e+00 9.712222e-01 9.712222e-01 4.856111e-01 -9.712222e-01 6.000000e-01 1.100000e+00 9.690878e-01 9.690878e-01 4.845439e-01 -9.690878e-01 7.000000e-01 1.100000e+00 9.665715e-01 9.665715e-01 4.832858e-01 -9.665715e-01 8.000000e-01 1.100000e+00 9.636762e-01 9.636762e-01 4.818381e-01 -9.636762e-01 9.000000e-01 1.100000e+00 9.604052e-01 9.604052e-01 4.802026e-01 -9.604052e-01 1.000000e+00 1.100000e+00 9.567626e-01 9.567626e-01 4.783813e-01 -9.567626e-01 1.100000e+00 1.100000e+00 9.527526e-01 9.527526e-01 4.763763e-01 -9.527526e-01 1.200000e+00 1.100000e+00 9.483800e-01 9.483800e-01 4.741900e-01 -9.483800e-01 1.300000e+00 1.100000e+00 9.436499e-01 9.436499e-01 4.718250e-01 -9.436499e-01 1.400000e+00 1.100000e+00 9.385680e-01 9.385680e-01 4.692840e-01 -9.385680e-01 1.500000e+00 1.100000e+00 9.331400e-01 9.331400e-01 4.665700e-01 -9.331400e-01 1.600000e+00 1.100000e+00 9.273725e-01 9.273725e-01 4.636862e-01 -9.273725e-01 1.700000e+00 1.100000e+00 9.212720e-01 9.212720e-01 4.606360e-01 -9.212720e-01 1.800000e+00 1.100000e+00 9.148456e-01 9.148456e-01 4.574228e-01 -9.148456e-01 1.900000e+00 1.100000e+00 9.081007e-01 9.081007e-01 4.540504e-01 -9.081007e-01 2.000000e+00 1.100000e+00 9.010451e-01 9.010451e-01 4.505225e-01 -9.010451e-01 2.100000e+00 1.100000e+00 8.936867e-01 8.936867e-01 4.468434e-01 -8.936867e-01 2.200000e+00 1.100000e+00 8.860340e-01 8.860340e-01 4.430170e-01 -8.860340e-01 2.300000e+00 1.100000e+00 8.780954e-01 8.780954e-01 4.390477e-01 -8.780954e-01 2.400000e+00 1.100000e+00 8.698800e-01 8.698800e-01 4.349400e-01 -8.698800e-01 2.500000e+00 1.100000e+00 8.613968e-01 8.613968e-01 4.306984e-01 -8.613968e-01 2.600000e+00 1.100000e+00 8.526552e-01 8.526552e-01 4.263276e-01 -8.526552e-01 2.700000e+00 1.100000e+00 8.436648e-01 8.436648e-01 4.218324e-01 -8.436648e-01 2.800000e+00 1.100000e+00 8.344353e-01 8.344353e-01 4.172177e-01 -8.344353e-01 2.900000e+00 1.100000e+00 8.249768e-01 8.249768e-01 4.124884e-01 -8.249768e-01 3.000000e+00 1.100000e+00 8.152993e-01 8.152993e-01 4.076496e-01 -8.152993e-01 3.100000e+00 1.100000e+00 8.054131e-01 8.054131e-01 4.027065e-01 -8.054131e-01 3.200000e+00 1.100000e+00 7.953286e-01 7.953286e-01 3.976643e-01 -7.953286e-01 3.300000e+00 1.100000e+00 7.850562e-01 7.850562e-01 3.925281e-01 -7.850562e-01 3.400000e+00 1.100000e+00 7.746066e-01 7.746066e-01 3.873033e-01 -7.746066e-01 3.500000e+00 1.100000e+00 7.639905e-01 7.639905e-01 3.819952e-01 -7.639905e-01 3.600000e+00 1.100000e+00 7.532185e-01 7.532185e-01 3.766092e-01 -7.532185e-01 3.700000e+00 1.100000e+00 7.423013e-01 7.423013e-01 3.711507e-01 -7.423013e-01 3.800000e+00 1.100000e+00 7.312499e-01 7.312499e-01 3.656250e-01 -7.312499e-01 3.900000e+00 1.100000e+00 7.200749e-01 7.200749e-01 3.600374e-01 -7.200749e-01 4.000000e+00 1.100000e+00 7.087871e-01 7.087871e-01 3.543936e-01 -7.087871e-01 4.100000e+00 1.100000e+00 6.973973e-01 6.973973e-01 3.486986e-01 -6.973973e-01 4.200000e+00 1.100000e+00 6.859161e-01 6.859161e-01 3.429580e-01 -6.859161e-01 4.300000e+00 1.100000e+00 6.743541e-01 6.743541e-01 3.371770e-01 -6.743541e-01 4.400000e+00 1.100000e+00 6.627218e-01 6.627218e-01 3.313609e-01 -6.627218e-01 4.500000e+00 1.100000e+00 6.510297e-01 6.510297e-01 3.255149e-01 -6.510297e-01 4.600000e+00 1.100000e+00 6.392882e-01 6.392882e-01 3.196441e-01 -6.392882e-01 4.700000e+00 1.100000e+00 6.275073e-01 6.275073e-01 3.137537e-01 -6.275073e-01 4.800000e+00 1.100000e+00 6.156972e-01 6.156972e-01 3.078486e-01 -6.156972e-01 4.900000e+00 1.100000e+00 6.038678e-01 6.038678e-01 3.019339e-01 -6.038678e-01 -5.000000e+00 1.200000e+00 5.893117e-01 5.893117e-01 2.946559e-01 -5.893117e-01 -4.900000e+00 1.200000e+00 6.010964e-01 6.010964e-01 3.005482e-01 -6.010964e-01 -4.800000e+00 1.200000e+00 6.128715e-01 6.128715e-01 3.064357e-01 -6.128715e-01 -4.700000e+00 1.200000e+00 6.246274e-01 6.246274e-01 3.123137e-01 -6.246274e-01 -4.600000e+00 1.200000e+00 6.363542e-01 6.363542e-01 3.181771e-01 -6.363542e-01 -4.500000e+00 1.200000e+00 6.480418e-01 6.480418e-01 3.240209e-01 -6.480418e-01 -4.400000e+00 1.200000e+00 6.596802e-01 6.596802e-01 3.298401e-01 -6.596802e-01 -4.300000e+00 1.200000e+00 6.712592e-01 6.712592e-01 3.356296e-01 -6.712592e-01 -4.200000e+00 1.200000e+00 6.827681e-01 6.827681e-01 3.413841e-01 -6.827681e-01 -4.100000e+00 1.200000e+00 6.941966e-01 6.941966e-01 3.470983e-01 -6.941966e-01 -4.000000e+00 1.200000e+00 7.055342e-01 7.055342e-01 3.527671e-01 -7.055342e-01 -3.900000e+00 1.200000e+00 7.167702e-01 7.167702e-01 3.583851e-01 -7.167702e-01 -3.800000e+00 1.200000e+00 7.278939e-01 7.278939e-01 3.639469e-01 -7.278939e-01 -3.700000e+00 1.200000e+00 7.388946e-01 7.388946e-01 3.694473e-01 -7.388946e-01 -3.600000e+00 1.200000e+00 7.497616e-01 7.497616e-01 3.748808e-01 -7.497616e-01 -3.500000e+00 1.200000e+00 7.604842e-01 7.604842e-01 3.802421e-01 -7.604842e-01 -3.400000e+00 1.200000e+00 7.710516e-01 7.710516e-01 3.855258e-01 -7.710516e-01 -3.300000e+00 1.200000e+00 7.814533e-01 7.814533e-01 3.907266e-01 -7.814533e-01 -3.200000e+00 1.200000e+00 7.916784e-01 7.916784e-01 3.958392e-01 -7.916784e-01 -3.100000e+00 1.200000e+00 8.017167e-01 8.017167e-01 4.008583e-01 -8.017167e-01 -3.000000e+00 1.200000e+00 8.115575e-01 8.115575e-01 4.057788e-01 -8.115575e-01 -2.900000e+00 1.200000e+00 8.211906e-01 8.211906e-01 4.105953e-01 -8.211906e-01 -2.800000e+00 1.200000e+00 8.306057e-01 8.306057e-01 4.153029e-01 -8.306057e-01 -2.700000e+00 1.200000e+00 8.397928e-01 8.397928e-01 4.198964e-01 -8.397928e-01 -2.600000e+00 1.200000e+00 8.487420e-01 8.487420e-01 4.243710e-01 -8.487420e-01 -2.500000e+00 1.200000e+00 8.574435e-01 8.574435e-01 4.287218e-01 -8.574435e-01 -2.400000e+00 1.200000e+00 8.658878e-01 8.658878e-01 4.329439e-01 -8.658878e-01 -2.300000e+00 1.200000e+00 8.740655e-01 8.740655e-01 4.370327e-01 -8.740655e-01 -2.200000e+00 1.200000e+00 8.819675e-01 8.819675e-01 4.409838e-01 -8.819675e-01 -2.100000e+00 1.200000e+00 8.895852e-01 8.895852e-01 4.447926e-01 -8.895852e-01 -2.000000e+00 1.200000e+00 8.969098e-01 8.969098e-01 4.484549e-01 -8.969098e-01 -1.900000e+00 1.200000e+00 9.039330e-01 9.039330e-01 4.519665e-01 -9.039330e-01 -1.800000e+00 1.200000e+00 9.106470e-01 9.106470e-01 4.553235e-01 -9.106470e-01 -1.700000e+00 1.200000e+00 9.170438e-01 9.170438e-01 4.585219e-01 -9.170438e-01 -1.600000e+00 1.200000e+00 9.231163e-01 9.231163e-01 4.615582e-01 -9.231163e-01 -1.500000e+00 1.200000e+00 9.288574e-01 9.288574e-01 4.644287e-01 -9.288574e-01 -1.400000e+00 1.200000e+00 9.342605e-01 9.342605e-01 4.671302e-01 -9.342605e-01 -1.300000e+00 1.200000e+00 9.393191e-01 9.393191e-01 4.696596e-01 -9.393191e-01 -1.200000e+00 1.200000e+00 9.440275e-01 9.440275e-01 4.720137e-01 -9.440275e-01 -1.100000e+00 1.200000e+00 9.483800e-01 9.483800e-01 4.741900e-01 -9.483800e-01 -1.000000e+00 1.200000e+00 9.523716e-01 9.523716e-01 4.761858e-01 -9.523716e-01 -9.000000e-01 1.200000e+00 9.559975e-01 9.559975e-01 4.779987e-01 -9.559975e-01 -8.000000e-01 1.200000e+00 9.592534e-01 9.592534e-01 4.796267e-01 -9.592534e-01 -7.000000e-01 1.200000e+00 9.621355e-01 9.621355e-01 4.810677e-01 -9.621355e-01 -6.000000e-01 1.200000e+00 9.646403e-01 9.646403e-01 4.823202e-01 -9.646403e-01 -5.000000e-01 1.200000e+00 9.667648e-01 9.667648e-01 4.833824e-01 -9.667648e-01 -4.000000e-01 1.200000e+00 9.685066e-01 9.685066e-01 4.842533e-01 -9.685066e-01 -3.000000e-01 1.200000e+00 9.698634e-01 9.698634e-01 4.849317e-01 -9.698634e-01 -2.000000e-01 1.200000e+00 9.708338e-01 9.708338e-01 4.854169e-01 -9.708338e-01 -1.000000e-01 1.200000e+00 9.714165e-01 9.714165e-01 4.857082e-01 -9.714165e-01 0.000000e+00 1.200000e+00 9.716108e-01 9.716108e-01 4.858054e-01 -9.716108e-01 1.000000e-01 1.200000e+00 9.714165e-01 9.714165e-01 4.857082e-01 -9.714165e-01 2.000000e-01 1.200000e+00 9.708338e-01 9.708338e-01 4.854169e-01 -9.708338e-01 3.000000e-01 1.200000e+00 9.698634e-01 9.698634e-01 4.849317e-01 -9.698634e-01 4.000000e-01 1.200000e+00 9.685066e-01 9.685066e-01 4.842533e-01 -9.685066e-01 5.000000e-01 1.200000e+00 9.667648e-01 9.667648e-01 4.833824e-01 -9.667648e-01 6.000000e-01 1.200000e+00 9.646403e-01 9.646403e-01 4.823202e-01 -9.646403e-01 7.000000e-01 1.200000e+00 9.621355e-01 9.621355e-01 4.810677e-01 -9.621355e-01 8.000000e-01 1.200000e+00 9.592534e-01 9.592534e-01 4.796267e-01 -9.592534e-01 9.000000e-01 1.200000e+00 9.559975e-01 9.559975e-01 4.779987e-01 -9.559975e-01 1.000000e+00 1.200000e+00 9.523716e-01 9.523716e-01 4.761858e-01 -9.523716e-01 1.100000e+00 1.200000e+00 9.483800e-01 9.483800e-01 4.741900e-01 -9.483800e-01 1.200000e+00 1.200000e+00 9.440275e-01 9.440275e-01 4.720137e-01 -9.440275e-01 1.300000e+00 1.200000e+00 9.393191e-01 9.393191e-01 4.696596e-01 -9.393191e-01 1.400000e+00 1.200000e+00 9.342605e-01 9.342605e-01 4.671302e-01 -9.342605e-01 1.500000e+00 1.200000e+00 9.288574e-01 9.288574e-01 4.644287e-01 -9.288574e-01 1.600000e+00 1.200000e+00 9.231163e-01 9.231163e-01 4.615582e-01 -9.231163e-01 1.700000e+00 1.200000e+00 9.170438e-01 9.170438e-01 4.585219e-01 -9.170438e-01 1.800000e+00 1.200000e+00 9.106470e-01 9.106470e-01 4.553235e-01 -9.106470e-01 1.900000e+00 1.200000e+00 9.039330e-01 9.039330e-01 4.519665e-01 -9.039330e-01 2.000000e+00 1.200000e+00 8.969098e-01 8.969098e-01 4.484549e-01 -8.969098e-01 2.100000e+00 1.200000e+00 8.895852e-01 8.895852e-01 4.447926e-01 -8.895852e-01 2.200000e+00 1.200000e+00 8.819675e-01 8.819675e-01 4.409838e-01 -8.819675e-01 2.300000e+00 1.200000e+00 8.740655e-01 8.740655e-01 4.370327e-01 -8.740655e-01 2.400000e+00 1.200000e+00 8.658878e-01 8.658878e-01 4.329439e-01 -8.658878e-01 2.500000e+00 1.200000e+00 8.574435e-01 8.574435e-01 4.287218e-01 -8.574435e-01 2.600000e+00 1.200000e+00 8.487420e-01 8.487420e-01 4.243710e-01 -8.487420e-01 2.700000e+00 1.200000e+00 8.397928e-01 8.397928e-01 4.198964e-01 -8.397928e-01 2.800000e+00 1.200000e+00 8.306057e-01 8.306057e-01 4.153029e-01 -8.306057e-01 2.900000e+00 1.200000e+00 8.211906e-01 8.211906e-01 4.105953e-01 -8.211906e-01 3.000000e+00 1.200000e+00 8.115575e-01 8.115575e-01 4.057788e-01 -8.115575e-01 3.100000e+00 1.200000e+00 8.017167e-01 8.017167e-01 4.008583e-01 -8.017167e-01 3.200000e+00 1.200000e+00 7.916784e-01 7.916784e-01 3.958392e-01 -7.916784e-01 3.300000e+00 1.200000e+00 7.814533e-01 7.814533e-01 3.907266e-01 -7.814533e-01 3.400000e+00 1.200000e+00 7.710516e-01 7.710516e-01 3.855258e-01 -7.710516e-01 3.500000e+00 1.200000e+00 7.604842e-01 7.604842e-01 3.802421e-01 -7.604842e-01 3.600000e+00 1.200000e+00 7.497616e-01 7.497616e-01 3.748808e-01 -7.497616e-01 3.700000e+00 1.200000e+00 7.388946e-01 7.388946e-01 3.694473e-01 -7.388946e-01 3.800000e+00 1.200000e+00 7.278939e-01 7.278939e-01 3.639469e-01 -7.278939e-01 3.900000e+00 1.200000e+00 7.167702e-01 7.167702e-01 3.583851e-01 -7.167702e-01 4.000000e+00 1.200000e+00 7.055342e-01 7.055342e-01 3.527671e-01 -7.055342e-01 4.100000e+00 1.200000e+00 6.941966e-01 6.941966e-01 3.470983e-01 -6.941966e-01 4.200000e+00 1.200000e+00 6.827681e-01 6.827681e-01 3.413841e-01 -6.827681e-01 4.300000e+00 1.200000e+00 6.712592e-01 6.712592e-01 3.356296e-01 -6.712592e-01 4.400000e+00 1.200000e+00 6.596802e-01 6.596802e-01 3.298401e-01 -6.596802e-01 4.500000e+00 1.200000e+00 6.480418e-01 6.480418e-01 3.240209e-01 -6.480418e-01 4.600000e+00 1.200000e+00 6.363542e-01 6.363542e-01 3.181771e-01 -6.363542e-01 4.700000e+00 1.200000e+00 6.246274e-01 6.246274e-01 3.123137e-01 -6.246274e-01 4.800000e+00 1.200000e+00 6.128715e-01 6.128715e-01 3.064357e-01 -6.128715e-01 4.900000e+00 1.200000e+00 6.010964e-01 6.010964e-01 3.005482e-01 -6.010964e-01 -5.000000e+00 1.300000e+00 5.863725e-01 5.863725e-01 2.931862e-01 -5.863725e-01 -4.900000e+00 1.300000e+00 5.980984e-01 5.980984e-01 2.990492e-01 -5.980984e-01 -4.800000e+00 1.300000e+00 6.098148e-01 6.098148e-01 3.049074e-01 -6.098148e-01 -4.700000e+00 1.300000e+00 6.215121e-01 6.215121e-01 3.107560e-01 -6.215121e-01 -4.600000e+00 1.300000e+00 6.331804e-01 6.331804e-01 3.165902e-01 -6.331804e-01 -4.500000e+00 1.300000e+00 6.448097e-01 6.448097e-01 3.224049e-01 -6.448097e-01 -4.400000e+00 1.300000e+00 6.563901e-01 6.563901e-01 3.281950e-01 -6.563901e-01 -4.300000e+00 1.300000e+00 6.679112e-01 6.679112e-01 3.339556e-01 -6.679112e-01 -4.200000e+00 1.300000e+00 6.793628e-01 6.793628e-01 3.396814e-01 -6.793628e-01 -4.100000e+00 1.300000e+00 6.907343e-01 6.907343e-01 3.453672e-01 -6.907343e-01 -4.000000e+00 1.300000e+00 7.020153e-01 7.020153e-01 3.510077e-01 -7.020153e-01 -3.900000e+00 1.300000e+00 7.131953e-01 7.131953e-01 3.565976e-01 -7.131953e-01 -3.800000e+00 1.300000e+00 7.242635e-01 7.242635e-01 3.621317e-01 -7.242635e-01 -3.700000e+00 1.300000e+00 7.352093e-01 7.352093e-01 3.676047e-01 -7.352093e-01 -3.600000e+00 1.300000e+00 7.460222e-01 7.460222e-01 3.730111e-01 -7.460222e-01 -3.500000e+00 1.300000e+00 7.566912e-01 7.566912e-01 3.783456e-01 -7.566912e-01 -3.400000e+00 1.300000e+00 7.672060e-01 7.672060e-01 3.836030e-01 -7.672060e-01 -3.300000e+00 1.300000e+00 7.775557e-01 7.775557e-01 3.887779e-01 -7.775557e-01 -3.200000e+00 1.300000e+00 7.877299e-01 7.877299e-01 3.938650e-01 -7.877299e-01 -3.100000e+00 1.300000e+00 7.977181e-01 7.977181e-01 3.988591e-01 -7.977181e-01 -3.000000e+00 1.300000e+00 8.075098e-01 8.075098e-01 4.037549e-01 -8.075098e-01 -2.900000e+00 1.300000e+00 8.170949e-01 8.170949e-01 4.085475e-01 -8.170949e-01 -2.800000e+00 1.300000e+00 8.264631e-01 8.264631e-01 4.132316e-01 -8.264631e-01 -2.700000e+00 1.300000e+00 8.356044e-01 8.356044e-01 4.178022e-01 -8.356044e-01 -2.600000e+00 1.300000e+00 8.445089e-01 8.445089e-01 4.222544e-01 -8.445089e-01 -2.500000e+00 1.300000e+00 8.531670e-01 8.531670e-01 4.265835e-01 -8.531670e-01 -2.400000e+00 1.300000e+00 8.615691e-01 8.615691e-01 4.307846e-01 -8.615691e-01 -2.300000e+00 1.300000e+00 8.697061e-01 8.697061e-01 4.348530e-01 -8.697061e-01 -2.200000e+00 1.300000e+00 8.775687e-01 8.775687e-01 4.387844e-01 -8.775687e-01 -2.100000e+00 1.300000e+00 8.851483e-01 8.851483e-01 4.425742e-01 -8.851483e-01 -2.000000e+00 1.300000e+00 8.924364e-01 8.924364e-01 4.462182e-01 -8.924364e-01 -1.900000e+00 1.300000e+00 8.994247e-01 8.994247e-01 4.497123e-01 -8.994247e-01 -1.800000e+00 1.300000e+00 9.061051e-01 9.061051e-01 4.530526e-01 -9.061051e-01 -1.700000e+00 1.300000e+00 9.124700e-01 9.124700e-01 4.562350e-01 -9.124700e-01 -1.600000e+00 1.300000e+00 9.185123e-01 9.185123e-01 4.592561e-01 -9.185123e-01 -1.500000e+00 1.300000e+00 9.242247e-01 9.242247e-01 4.621124e-01 -9.242247e-01 -1.400000e+00 1.300000e+00 9.296008e-01 9.296008e-01 4.648004e-01 -9.296008e-01 -1.300000e+00 1.300000e+00 9.346343e-01 9.346343e-01 4.673171e-01 -9.346343e-01 -1.200000e+00 1.300000e+00 9.393191e-01 9.393191e-01 4.696596e-01 -9.393191e-01 -1.100000e+00 1.300000e+00 9.436499e-01 9.436499e-01 4.718250e-01 -9.436499e-01 -1.000000e+00 1.300000e+00 9.476216e-01 9.476216e-01 4.738108e-01 -9.476216e-01 -9.000000e-01 1.300000e+00 9.512295e-01 9.512295e-01 4.756147e-01 -9.512295e-01 -8.000000e-01 1.300000e+00 9.544691e-01 9.544691e-01 4.772345e-01 -9.544691e-01 -7.000000e-01 1.300000e+00 9.573368e-01 9.573368e-01 4.786684e-01 -9.573368e-01 -6.000000e-01 1.300000e+00 9.598292e-01 9.598292e-01 4.799146e-01 -9.598292e-01 -5.000000e-01 1.300000e+00 9.619431e-01 9.619431e-01 4.809715e-01 -9.619431e-01 -4.000000e-01 1.300000e+00 9.636762e-01 9.636762e-01 4.818381e-01 -9.636762e-01 -3.000000e-01 1.300000e+00 9.650262e-01 9.650262e-01 4.825131e-01 -9.650262e-01 -2.000000e-01 1.300000e+00 9.659917e-01 9.659917e-01 4.829959e-01 -9.659917e-01 -1.000000e-01 1.300000e+00 9.665715e-01 9.665715e-01 4.832858e-01 -9.665715e-01 0.000000e+00 1.300000e+00 9.667649e-01 9.667649e-01 4.833824e-01 -9.667649e-01 1.000000e-01 1.300000e+00 9.665715e-01 9.665715e-01 4.832858e-01 -9.665715e-01 2.000000e-01 1.300000e+00 9.659917e-01 9.659917e-01 4.829959e-01 -9.659917e-01 3.000000e-01 1.300000e+00 9.650262e-01 9.650262e-01 4.825131e-01 -9.650262e-01 4.000000e-01 1.300000e+00 9.636762e-01 9.636762e-01 4.818381e-01 -9.636762e-01 5.000000e-01 1.300000e+00 9.619431e-01 9.619431e-01 4.809715e-01 -9.619431e-01 6.000000e-01 1.300000e+00 9.598292e-01 9.598292e-01 4.799146e-01 -9.598292e-01 7.000000e-01 1.300000e+00 9.573368e-01 9.573368e-01 4.786684e-01 -9.573368e-01 8.000000e-01 1.300000e+00 9.544691e-01 9.544691e-01 4.772345e-01 -9.544691e-01 9.000000e-01 1.300000e+00 9.512295e-01 9.512295e-01 4.756147e-01 -9.512295e-01 1.000000e+00 1.300000e+00 9.476216e-01 9.476216e-01 4.738108e-01 -9.476216e-01 1.100000e+00 1.300000e+00 9.436499e-01 9.436499e-01 4.718250e-01 -9.436499e-01 1.200000e+00 1.300000e+00 9.393191e-01 9.393191e-01 4.696596e-01 -9.393191e-01 1.300000e+00 1.300000e+00 9.346343e-01 9.346343e-01 4.673171e-01 -9.346343e-01 1.400000e+00 1.300000e+00 9.296008e-01 9.296008e-01 4.648004e-01 -9.296008e-01 1.500000e+00 1.300000e+00 9.242247e-01 9.242247e-01 4.621124e-01 -9.242247e-01 1.600000e+00 1.300000e+00 9.185123e-01 9.185123e-01 4.592561e-01 -9.185123e-01 1.700000e+00 1.300000e+00 9.124700e-01 9.124700e-01 4.562350e-01 -9.124700e-01 1.800000e+00 1.300000e+00 9.061051e-01 9.061051e-01 4.530526e-01 -9.061051e-01 1.900000e+00 1.300000e+00 8.994247e-01 8.994247e-01 4.497123e-01 -8.994247e-01 2.000000e+00 1.300000e+00 8.924364e-01 8.924364e-01 4.462182e-01 -8.924364e-01 2.100000e+00 1.300000e+00 8.851483e-01 8.851483e-01 4.425742e-01 -8.851483e-01 2.200000e+00 1.300000e+00 8.775687e-01 8.775687e-01 4.387844e-01 -8.775687e-01 2.300000e+00 1.300000e+00 8.697061e-01 8.697061e-01 4.348530e-01 -8.697061e-01 2.400000e+00 1.300000e+00 8.615691e-01 8.615691e-01 4.307846e-01 -8.615691e-01 2.500000e+00 1.300000e+00 8.531670e-01 8.531670e-01 4.265835e-01 -8.531670e-01 2.600000e+00 1.300000e+00 8.445089e-01 8.445089e-01 4.222544e-01 -8.445089e-01 2.700000e+00 1.300000e+00 8.356044e-01 8.356044e-01 4.178022e-01 -8.356044e-01 2.800000e+00 1.300000e+00 8.264631e-01 8.264631e-01 4.132316e-01 -8.264631e-01 2.900000e+00 1.300000e+00 8.170949e-01 8.170949e-01 4.085475e-01 -8.170949e-01 3.000000e+00 1.300000e+00 8.075098e-01 8.075098e-01 4.037549e-01 -8.075098e-01 3.100000e+00 1.300000e+00 7.977181e-01 7.977181e-01 3.988591e-01 -7.977181e-01 3.200000e+00 1.300000e+00 7.877299e-01 7.877299e-01 3.938650e-01 -7.877299e-01 3.300000e+00 1.300000e+00 7.775557e-01 7.775557e-01 3.887779e-01 -7.775557e-01 3.400000e+00 1.300000e+00 7.672060e-01 7.672060e-01 3.836030e-01 -7.672060e-01 3.500000e+00 1.300000e+00 7.566912e-01 7.566912e-01 3.783456e-01 -7.566912e-01 3.600000e+00 1.300000e+00 7.460222e-01 7.460222e-01 3.730111e-01 -7.460222e-01 3.700000e+00 1.300000e+00 7.352093e-01 7.352093e-01 3.676047e-01 -7.352093e-01 3.800000e+00 1.300000e+00 7.242635e-01 7.242635e-01 3.621317e-01 -7.242635e-01 3.900000e+00 1.300000e+00 7.131953e-01 7.131953e-01 3.565976e-01 -7.131953e-01 4.000000e+00 1.300000e+00 7.020153e-01 7.020153e-01 3.510077e-01 -7.020153e-01 4.100000e+00 1.300000e+00 6.907343e-01 6.907343e-01 3.453672e-01 -6.907343e-01 4.200000e+00 1.300000e+00 6.793628e-01 6.793628e-01 3.396814e-01 -6.793628e-01 4.300000e+00 1.300000e+00 6.679112e-01 6.679112e-01 3.339556e-01 -6.679112e-01 4.400000e+00 1.300000e+00 6.563901e-01 6.563901e-01 3.281950e-01 -6.563901e-01 4.500000e+00 1.300000e+00 6.448097e-01 6.448097e-01 3.224049e-01 -6.448097e-01 4.600000e+00 1.300000e+00 6.331804e-01 6.331804e-01 3.165902e-01 -6.331804e-01 4.700000e+00 1.300000e+00 6.215121e-01 6.215121e-01 3.107560e-01 -6.215121e-01 4.800000e+00 1.300000e+00 6.098148e-01 6.098148e-01 3.049074e-01 -6.098148e-01 4.900000e+00 1.300000e+00 5.980984e-01 5.980984e-01 2.990492e-01 -5.980984e-01 -5.000000e+00 1.400000e+00 5.832146e-01 5.832146e-01 2.916073e-01 -5.832146e-01 -4.900000e+00 1.400000e+00 5.948774e-01 5.948774e-01 2.974387e-01 -5.948774e-01 -4.800000e+00 1.400000e+00 6.065307e-01 6.065307e-01 3.032653e-01 -6.065307e-01 -4.700000e+00 1.400000e+00 6.181650e-01 6.181650e-01 3.090825e-01 -6.181650e-01 -4.600000e+00 1.400000e+00 6.297704e-01 6.297704e-01 3.148852e-01 -6.297704e-01 -4.500000e+00 1.400000e+00 6.413372e-01 6.413372e-01 3.206686e-01 -6.413372e-01 -4.400000e+00 1.400000e+00 6.528552e-01 6.528552e-01 3.264276e-01 -6.528552e-01 -4.300000e+00 1.400000e+00 6.643142e-01 6.643142e-01 3.321571e-01 -6.643142e-01 -4.200000e+00 1.400000e+00 6.757041e-01 6.757041e-01 3.378521e-01 -6.757041e-01 -4.100000e+00 1.400000e+00 6.870144e-01 6.870144e-01 3.435072e-01 -6.870144e-01 -4.000000e+00 1.400000e+00 6.982347e-01 6.982347e-01 3.491173e-01 -6.982347e-01 -3.900000e+00 1.400000e+00 7.093544e-01 7.093544e-01 3.546772e-01 -7.093544e-01 -3.800000e+00 1.400000e+00 7.203630e-01 7.203630e-01 3.601815e-01 -7.203630e-01 -3.700000e+00 1.400000e+00 7.312499e-01 7.312499e-01 3.656249e-01 -7.312499e-01 -3.600000e+00 1.400000e+00 7.420045e-01 7.420045e-01 3.710023e-01 -7.420045e-01 -3.500000e+00 1.400000e+00 7.526161e-01 7.526161e-01 3.763081e-01 -7.526161e-01 -3.400000e+00 1.400000e+00 7.630742e-01 7.630742e-01 3.815371e-01 -7.630742e-01 -3.300000e+00 1.400000e+00 7.733682e-01 7.733682e-01 3.866841e-01 -7.733682e-01 -3.200000e+00 1.400000e+00 7.834876e-01 7.834876e-01 3.917438e-01 -7.834876e-01 -3.100000e+00 1.400000e+00 7.934220e-01 7.934220e-01 3.967110e-01 -7.934220e-01 -3.000000e+00 1.400000e+00 8.031611e-01 8.031611e-01 4.015805e-01 -8.031611e-01 -2.900000e+00 1.400000e+00 8.126945e-01 8.126945e-01 4.063472e-01 -8.126945e-01 -2.800000e+00 1.400000e+00 8.220122e-01 8.220122e-01 4.110061e-01 -8.220122e-01 -2.700000e+00 1.400000e+00 8.311043e-01 8.311043e-01 4.155521e-01 -8.311043e-01 -2.600000e+00 1.400000e+00 8.399609e-01 8.399609e-01 4.199804e-01 -8.399609e-01 -2.500000e+00 1.400000e+00 8.485723e-01 8.485723e-01 4.242861e-01 -8.485723e-01 -2.400000e+00 1.400000e+00 8.569292e-01 8.569292e-01 4.284646e-01 -8.569292e-01 -2.300000e+00 1.400000e+00 8.650223e-01 8.650223e-01 4.325112e-01 -8.650223e-01 -2.200000e+00 1.400000e+00 8.728426e-01 8.728426e-01 4.364213e-01 -8.728426e-01 -2.100000e+00 1.400000e+00 8.803815e-01 8.803815e-01 4.401907e-01 -8.803815e-01 -2.000000e+00 1.400000e+00 8.876302e-01 8.876302e-01 4.438151e-01 -8.876302e-01 -1.900000e+00 1.400000e+00 8.945808e-01 8.945808e-01 4.472904e-01 -8.945808e-01 -1.800000e+00 1.400000e+00 9.012253e-01 9.012253e-01 4.506127e-01 -9.012253e-01 -1.700000e+00 1.400000e+00 9.075560e-01 9.075560e-01 4.537780e-01 -9.075560e-01 -1.600000e+00 1.400000e+00 9.135657e-01 9.135657e-01 4.567828e-01 -9.135657e-01 -1.500000e+00 1.400000e+00 9.192474e-01 9.192474e-01 4.596237e-01 -9.192474e-01 -1.400000e+00 1.400000e+00 9.245945e-01 9.245945e-01 4.622973e-01 -9.245945e-01 -1.300000e+00 1.400000e+00 9.296008e-01 9.296008e-01 4.648004e-01 -9.296008e-01 -1.200000e+00 1.400000e+00 9.342605e-01 9.342605e-01 4.671302e-01 -9.342605e-01 -1.100000e+00 1.400000e+00 9.385680e-01 9.385680e-01 4.692840e-01 -9.385680e-01 -1.000000e+00 1.400000e+00 9.425182e-01 9.425182e-01 4.712591e-01 -9.425182e-01 -9.000000e-01 1.400000e+00 9.461066e-01 9.461066e-01 4.730533e-01 -9.461066e-01 -8.000000e-01 1.400000e+00 9.493288e-01 9.493288e-01 4.746644e-01 -9.493288e-01 -7.000000e-01 1.400000e+00 9.521811e-01 9.521811e-01 4.760906e-01 -9.521811e-01 -6.000000e-01 1.400000e+00 9.546600e-01 9.546600e-01 4.773300e-01 -9.546600e-01 -5.000000e-01 1.400000e+00 9.567626e-01 9.567626e-01 4.783813e-01 -9.567626e-01 -4.000000e-01 1.400000e+00 9.584863e-01 9.584863e-01 4.792432e-01 -9.584863e-01 -3.000000e-01 1.400000e+00 9.598292e-01 9.598292e-01 4.799146e-01 -9.598292e-01 -2.000000e-01 1.400000e+00 9.607894e-01 9.607894e-01 4.803947e-01 -9.607894e-01 -1.000000e-01 1.400000e+00 9.613661e-01 9.613661e-01 4.806830e-01 -9.613661e-01 0.000000e+00 1.400000e+00 9.615584e-01 9.615584e-01 4.807792e-01 -9.615584e-01 1.000000e-01 1.400000e+00 9.613661e-01 9.613661e-01 4.806830e-01 -9.613661e-01 2.000000e-01 1.400000e+00 9.607894e-01 9.607894e-01 4.803947e-01 -9.607894e-01 3.000000e-01 1.400000e+00 9.598292e-01 9.598292e-01 4.799146e-01 -9.598292e-01 4.000000e-01 1.400000e+00 9.584863e-01 9.584863e-01 4.792432e-01 -9.584863e-01 5.000000e-01 1.400000e+00 9.567626e-01 9.567626e-01 4.783813e-01 -9.567626e-01 6.000000e-01 1.400000e+00 9.546600e-01 9.546600e-01 4.773300e-01 -9.546600e-01 7.000000e-01 1.400000e+00 9.521811e-01 9.521811e-01 4.760906e-01 -9.521811e-01 8.000000e-01 1.400000e+00 9.493288e-01 9.493288e-01 4.746644e-01 -9.493288e-01 9.000000e-01 1.400000e+00 9.461066e-01 9.461066e-01 4.730533e-01 -9.461066e-01 1.000000e+00 1.400000e+00 9.425182e-01 9.425182e-01 4.712591e-01 -9.425182e-01 1.100000e+00 1.400000e+00 9.385680e-01 9.385680e-01 4.692840e-01 -9.385680e-01 1.200000e+00 1.400000e+00 9.342605e-01 9.342605e-01 4.671302e-01 -9.342605e-01 1.300000e+00 1.400000e+00 9.296008e-01 9.296008e-01 4.648004e-01 -9.296008e-01 1.400000e+00 1.400000e+00 9.245945e-01 9.245945e-01 4.622973e-01 -9.245945e-01 1.500000e+00 1.400000e+00 9.192474e-01 9.192474e-01 4.596237e-01 -9.192474e-01 1.600000e+00 1.400000e+00 9.135657e-01 9.135657e-01 4.567828e-01 -9.135657e-01 1.700000e+00 1.400000e+00 9.075560e-01 9.075560e-01 4.537780e-01 -9.075560e-01 1.800000e+00 1.400000e+00 9.012253e-01 9.012253e-01 4.506127e-01 -9.012253e-01 1.900000e+00 1.400000e+00 8.945808e-01 8.945808e-01 4.472904e-01 -8.945808e-01 2.000000e+00 1.400000e+00 8.876302e-01 8.876302e-01 4.438151e-01 -8.876302e-01 2.100000e+00 1.400000e+00 8.803815e-01 8.803815e-01 4.401907e-01 -8.803815e-01 2.200000e+00 1.400000e+00 8.728426e-01 8.728426e-01 4.364213e-01 -8.728426e-01 2.300000e+00 1.400000e+00 8.650223e-01 8.650223e-01 4.325112e-01 -8.650223e-01 2.400000e+00 1.400000e+00 8.569292e-01 8.569292e-01 4.284646e-01 -8.569292e-01 2.500000e+00 1.400000e+00 8.485723e-01 8.485723e-01 4.242861e-01 -8.485723e-01 2.600000e+00 1.400000e+00 8.399609e-01 8.399609e-01 4.199804e-01 -8.399609e-01 2.700000e+00 1.400000e+00 8.311043e-01 8.311043e-01 4.155521e-01 -8.311043e-01 2.800000e+00 1.400000e+00 8.220122e-01 8.220122e-01 4.110061e-01 -8.220122e-01 2.900000e+00 1.400000e+00 8.126945e-01 8.126945e-01 4.063472e-01 -8.126945e-01 3.000000e+00 1.400000e+00 8.031611e-01 8.031611e-01 4.015805e-01 -8.031611e-01 3.100000e+00 1.400000e+00 7.934220e-01 7.934220e-01 3.967110e-01 -7.934220e-01 3.200000e+00 1.400000e+00 7.834876e-01 7.834876e-01 3.917438e-01 -7.834876e-01 3.300000e+00 1.400000e+00 7.733682e-01 7.733682e-01 3.866841e-01 -7.733682e-01 3.400000e+00 1.400000e+00 7.630742e-01 7.630742e-01 3.815371e-01 -7.630742e-01 3.500000e+00 1.400000e+00 7.526161e-01 7.526161e-01 3.763081e-01 -7.526161e-01 3.600000e+00 1.400000e+00 7.420045e-01 7.420045e-01 3.710023e-01 -7.420045e-01 3.700000e+00 1.400000e+00 7.312499e-01 7.312499e-01 3.656249e-01 -7.312499e-01 3.800000e+00 1.400000e+00 7.203630e-01 7.203630e-01 3.601815e-01 -7.203630e-01 3.900000e+00 1.400000e+00 7.093544e-01 7.093544e-01 3.546772e-01 -7.093544e-01 4.000000e+00 1.400000e+00 6.982347e-01 6.982347e-01 3.491173e-01 -6.982347e-01 4.100000e+00 1.400000e+00 6.870144e-01 6.870144e-01 3.435072e-01 -6.870144e-01 4.200000e+00 1.400000e+00 6.757041e-01 6.757041e-01 3.378521e-01 -6.757041e-01 4.300000e+00 1.400000e+00 6.643142e-01 6.643142e-01 3.321571e-01 -6.643142e-01 4.400000e+00 1.400000e+00 6.528552e-01 6.528552e-01 3.264276e-01 -6.528552e-01 4.500000e+00 1.400000e+00 6.413372e-01 6.413372e-01 3.206686e-01 -6.413372e-01 4.600000e+00 1.400000e+00 6.297704e-01 6.297704e-01 3.148852e-01 -6.297704e-01 4.700000e+00 1.400000e+00 6.181650e-01 6.181650e-01 3.090825e-01 -6.181650e-01 4.800000e+00 1.400000e+00 6.065307e-01 6.065307e-01 3.032653e-01 -6.065307e-01 4.900000e+00 1.400000e+00 5.948774e-01 5.948774e-01 2.974387e-01 -5.948774e-01 -5.000000e+00 1.500000e+00 5.798418e-01 5.798418e-01 2.899209e-01 -5.798418e-01 -4.900000e+00 1.500000e+00 5.914370e-01 5.914370e-01 2.957185e-01 -5.914370e-01 -4.800000e+00 1.500000e+00 6.030229e-01 6.030229e-01 3.015115e-01 -6.030229e-01 -4.700000e+00 1.500000e+00 6.145900e-01 6.145900e-01 3.072950e-01 -6.145900e-01 -4.600000e+00 1.500000e+00 6.261283e-01 6.261283e-01 3.130642e-01 -6.261283e-01 -4.500000e+00 1.500000e+00 6.376281e-01 6.376281e-01 3.188141e-01 -6.376281e-01 -4.400000e+00 1.500000e+00 6.490796e-01 6.490796e-01 3.245398e-01 -6.490796e-01 -4.300000e+00 1.500000e+00 6.604724e-01 6.604724e-01 3.302362e-01 -6.604724e-01 -4.200000e+00 1.500000e+00 6.717964e-01 6.717964e-01 3.358982e-01 -6.717964e-01 -4.100000e+00 1.500000e+00 6.830413e-01 6.830413e-01 3.415206e-01 -6.830413e-01 -4.000000e+00 1.500000e+00 6.941966e-01 6.941966e-01 3.470983e-01 -6.941966e-01 -3.900000e+00 1.500000e+00 7.052521e-01 7.052521e-01 3.526260e-01 -7.052521e-01 -3.800000e+00 1.500000e+00 7.161970e-01 7.161970e-01 3.580985e-01 -7.161970e-01 -3.700000e+00 1.500000e+00 7.270209e-01 7.270209e-01 3.635105e-01 -7.270209e-01 -3.600000e+00 1.500000e+00 7.377133e-01 7.377133e-01 3.688567e-01 -7.377133e-01 -3.500000e+00 1.500000e+00 7.482636e-01 7.482636e-01 3.741318e-01 -7.482636e-01 -3.400000e+00 1.500000e+00 7.586612e-01 7.586612e-01 3.793306e-01 -7.586612e-01 -3.300000e+00 1.500000e+00 7.688957e-01 7.688957e-01 3.844478e-01 -7.688957e-01 -3.200000e+00 1.500000e+00 7.789565e-01 7.789565e-01 3.894783e-01 -7.789565e-01 -3.100000e+00 1.500000e+00 7.888335e-01 7.888335e-01 3.944167e-01 -7.888335e-01 -3.000000e+00 1.500000e+00 7.985162e-01 7.985162e-01 3.992581e-01 -7.985162e-01 -2.900000e+00 1.500000e+00 8.079945e-01 8.079945e-01 4.039972e-01 -8.079945e-01 -2.800000e+00 1.500000e+00 8.172584e-01 8.172584e-01 4.086292e-01 -8.172584e-01 -2.700000e+00 1.500000e+00 8.262978e-01 8.262978e-01 4.131489e-01 -8.262978e-01 -2.600000e+00 1.500000e+00 8.351032e-01 8.351032e-01 4.175516e-01 -8.351032e-01 -2.500000e+00 1.500000e+00 8.436648e-01 8.436648e-01 4.218324e-01 -8.436648e-01 -2.400000e+00 1.500000e+00 8.519734e-01 8.519734e-01 4.259867e-01 -8.519734e-01 -2.300000e+00 1.500000e+00 8.600197e-01 8.600197e-01 4.300098e-01 -8.600197e-01 -2.200000e+00 1.500000e+00 8.677948e-01 8.677948e-01 4.338974e-01 -8.677948e-01 -2.100000e+00 1.500000e+00 8.752900e-01 8.752900e-01 4.376450e-01 -8.752900e-01 -2.000000e+00 1.500000e+00 8.824969e-01 8.824969e-01 4.412484e-01 -8.824969e-01 -1.900000e+00 1.500000e+00 8.894073e-01 8.894073e-01 4.447036e-01 -8.894073e-01 -1.800000e+00 1.500000e+00 8.960133e-01 8.960133e-01 4.480067e-01 -8.960133e-01 -1.700000e+00 1.500000e+00 9.023074e-01 9.023074e-01 4.511537e-01 -9.023074e-01 -1.600000e+00 1.500000e+00 9.082823e-01 9.082823e-01 4.541412e-01 -9.082823e-01 -1.500000e+00 1.500000e+00 9.139312e-01 9.139312e-01 4.569656e-01 -9.139312e-01 -1.400000e+00 1.500000e+00 9.192474e-01 9.192474e-01 4.596237e-01 -9.192474e-01 -1.300000e+00 1.500000e+00 9.242247e-01 9.242247e-01 4.621124e-01 -9.242247e-01 -1.200000e+00 1.500000e+00 9.288574e-01 9.288574e-01 4.644287e-01 -9.288574e-01 -1.100000e+00 1.500000e+00 9.331400e-01 9.331400e-01 4.665700e-01 -9.331400e-01 -1.000000e+00 1.500000e+00 9.370674e-01 9.370674e-01 4.685337e-01 -9.370674e-01 -9.000000e-01 1.500000e+00 9.406351e-01 9.406351e-01 4.703175e-01 -9.406351e-01 -8.000000e-01 1.500000e+00 9.438387e-01 9.438387e-01 4.719194e-01 -9.438387e-01 -7.000000e-01 1.500000e+00 9.466745e-01 9.466745e-01 4.733372e-01 -9.466745e-01 -6.000000e-01 1.500000e+00 9.491390e-01 9.491390e-01 4.745695e-01 -9.491390e-01 -5.000000e-01 1.500000e+00 9.512295e-01 9.512295e-01 4.756147e-01 -9.512295e-01 -4.000000e-01 1.500000e+00 9.529432e-01 9.529432e-01 4.764716e-01 -9.529432e-01 -3.000000e-01 1.500000e+00 9.542782e-01 9.542782e-01 4.771391e-01 -9.542782e-01 -2.000000e-01 1.500000e+00 9.552330e-01 9.552330e-01 4.776165e-01 -9.552330e-01 -1.000000e-01 1.500000e+00 9.558063e-01 9.558063e-01 4.779032e-01 -9.558063e-01 0.000000e+00 1.500000e+00 9.559975e-01 9.559975e-01 4.779987e-01 -9.559975e-01 1.000000e-01 1.500000e+00 9.558063e-01 9.558063e-01 4.779032e-01 -9.558063e-01 2.000000e-01 1.500000e+00 9.552330e-01 9.552330e-01 4.776165e-01 -9.552330e-01 3.000000e-01 1.500000e+00 9.542782e-01 9.542782e-01 4.771391e-01 -9.542782e-01 4.000000e-01 1.500000e+00 9.529432e-01 9.529432e-01 4.764716e-01 -9.529432e-01 5.000000e-01 1.500000e+00 9.512295e-01 9.512295e-01 4.756147e-01 -9.512295e-01 6.000000e-01 1.500000e+00 9.491390e-01 9.491390e-01 4.745695e-01 -9.491390e-01 7.000000e-01 1.500000e+00 9.466745e-01 9.466745e-01 4.733372e-01 -9.466745e-01 8.000000e-01 1.500000e+00 9.438387e-01 9.438387e-01 4.719194e-01 -9.438387e-01 9.000000e-01 1.500000e+00 9.406351e-01 9.406351e-01 4.703175e-01 -9.406351e-01 1.000000e+00 1.500000e+00 9.370674e-01 9.370674e-01 4.685337e-01 -9.370674e-01 1.100000e+00 1.500000e+00 9.331400e-01 9.331400e-01 4.665700e-01 -9.331400e-01 1.200000e+00 1.500000e+00 9.288574e-01 9.288574e-01 4.644287e-01 -9.288574e-01 1.300000e+00 1.500000e+00 9.242247e-01 9.242247e-01 4.621124e-01 -9.242247e-01 1.400000e+00 1.500000e+00 9.192474e-01 9.192474e-01 4.596237e-01 -9.192474e-01 1.500000e+00 1.500000e+00 9.139312e-01 9.139312e-01 4.569656e-01 -9.139312e-01 1.600000e+00 1.500000e+00 9.082823e-01 9.082823e-01 4.541412e-01 -9.082823e-01 1.700000e+00 1.500000e+00 9.023074e-01 9.023074e-01 4.511537e-01 -9.023074e-01 1.800000e+00 1.500000e+00 8.960133e-01 8.960133e-01 4.480067e-01 -8.960133e-01 1.900000e+00 1.500000e+00 8.894073e-01 8.894073e-01 4.447036e-01 -8.894073e-01 2.000000e+00 1.500000e+00 8.824969e-01 8.824969e-01 4.412484e-01 -8.824969e-01 2.100000e+00 1.500000e+00 8.752900e-01 8.752900e-01 4.376450e-01 -8.752900e-01 2.200000e+00 1.500000e+00 8.677948e-01 8.677948e-01 4.338974e-01 -8.677948e-01 2.300000e+00 1.500000e+00 8.600197e-01 8.600197e-01 4.300098e-01 -8.600197e-01 2.400000e+00 1.500000e+00 8.519734e-01 8.519734e-01 4.259867e-01 -8.519734e-01 2.500000e+00 1.500000e+00 8.436648e-01 8.436648e-01 4.218324e-01 -8.436648e-01 2.600000e+00 1.500000e+00 8.351032e-01 8.351032e-01 4.175516e-01 -8.351032e-01 2.700000e+00 1.500000e+00 8.262978e-01 8.262978e-01 4.131489e-01 -8.262978e-01 2.800000e+00 1.500000e+00 8.172584e-01 8.172584e-01 4.086292e-01 -8.172584e-01 2.900000e+00 1.500000e+00 8.079945e-01 8.079945e-01 4.039972e-01 -8.079945e-01 3.000000e+00 1.500000e+00 7.985162e-01 7.985162e-01 3.992581e-01 -7.985162e-01 3.100000e+00 1.500000e+00 7.888335e-01 7.888335e-01 3.944167e-01 -7.888335e-01 3.200000e+00 1.500000e+00 7.789565e-01 7.789565e-01 3.894783e-01 -7.789565e-01 3.300000e+00 1.500000e+00 7.688957e-01 7.688957e-01 3.844478e-01 -7.688957e-01 3.400000e+00 1.500000e+00 7.586612e-01 7.586612e-01 3.793306e-01 -7.586612e-01 3.500000e+00 1.500000e+00 7.482636e-01 7.482636e-01 3.741318e-01 -7.482636e-01 3.600000e+00 1.500000e+00 7.377133e-01 7.377133e-01 3.688567e-01 -7.377133e-01 3.700000e+00 1.500000e+00 7.270209e-01 7.270209e-01 3.635105e-01 -7.270209e-01 3.800000e+00 1.500000e+00 7.161970e-01 7.161970e-01 3.580985e-01 -7.161970e-01 3.900000e+00 1.500000e+00 7.052521e-01 7.052521e-01 3.526260e-01 -7.052521e-01 4.000000e+00 1.500000e+00 6.941966e-01 6.941966e-01 3.470983e-01 -6.941966e-01 4.100000e+00 1.500000e+00 6.830413e-01 6.830413e-01 3.415206e-01 -6.830413e-01 4.200000e+00 1.500000e+00 6.717964e-01 6.717964e-01 3.358982e-01 -6.717964e-01 4.300000e+00 1.500000e+00 6.604724e-01 6.604724e-01 3.302362e-01 -6.604724e-01 4.400000e+00 1.500000e+00 6.490796e-01 6.490796e-01 3.245398e-01 -6.490796e-01 4.500000e+00 1.500000e+00 6.376281e-01 6.376281e-01 3.188141e-01 -6.376281e-01 4.600000e+00 1.500000e+00 6.261283e-01 6.261283e-01 3.130642e-01 -6.261283e-01 4.700000e+00 1.500000e+00 6.145900e-01 6.145900e-01 3.072950e-01 -6.145900e-01 4.800000e+00 1.500000e+00 6.030229e-01 6.030229e-01 3.015115e-01 -6.030229e-01 4.900000e+00 1.500000e+00 5.914370e-01 5.914370e-01 2.957185e-01 -5.914370e-01 -5.000000e+00 1.600000e+00 5.762579e-01 5.762579e-01 2.881289e-01 -5.762579e-01 -4.900000e+00 1.600000e+00 5.877815e-01 5.877815e-01 2.938907e-01 -5.877815e-01 -4.800000e+00 1.600000e+00 5.992958e-01 5.992958e-01 2.996479e-01 -5.992958e-01 -4.700000e+00 1.600000e+00 6.107913e-01 6.107913e-01 3.053957e-01 -6.107913e-01 -4.600000e+00 1.600000e+00 6.222583e-01 6.222583e-01 3.111292e-01 -6.222583e-01 -4.500000e+00 1.600000e+00 6.336871e-01 6.336871e-01 3.168435e-01 -6.336871e-01 -4.400000e+00 1.600000e+00 6.450677e-01 6.450677e-01 3.225338e-01 -6.450677e-01 -4.300000e+00 1.600000e+00 6.563901e-01 6.563901e-01 3.281950e-01 -6.563901e-01 -4.200000e+00 1.600000e+00 6.676441e-01 6.676441e-01 3.338221e-01 -6.676441e-01 -4.100000e+00 1.600000e+00 6.788195e-01 6.788195e-01 3.394098e-01 -6.788195e-01 -4.000000e+00 1.600000e+00 6.899059e-01 6.899059e-01 3.449530e-01 -6.899059e-01 -3.900000e+00 1.600000e+00 7.008930e-01 7.008930e-01 3.504465e-01 -7.008930e-01 -3.800000e+00 1.600000e+00 7.117703e-01 7.117703e-01 3.558851e-01 -7.117703e-01 -3.700000e+00 1.600000e+00 7.225273e-01 7.225273e-01 3.612637e-01 -7.225273e-01 -3.600000e+00 1.600000e+00 7.331536e-01 7.331536e-01 3.665768e-01 -7.331536e-01 -3.500000e+00 1.600000e+00 7.436387e-01 7.436387e-01 3.718193e-01 -7.436387e-01 -3.400000e+00 1.600000e+00 7.539721e-01 7.539721e-01 3.769860e-01 -7.539721e-01 -3.300000e+00 1.600000e+00 7.641433e-01 7.641433e-01 3.820716e-01 -7.641433e-01 -3.200000e+00 1.600000e+00 7.741420e-01 7.741420e-01 3.870710e-01 -7.741420e-01 -3.100000e+00 1.600000e+00 7.839578e-01 7.839578e-01 3.919789e-01 -7.839578e-01 -3.000000e+00 1.600000e+00 7.935807e-01 7.935807e-01 3.967904e-01 -7.935807e-01 -2.900000e+00 1.600000e+00 8.030005e-01 8.030005e-01 4.015002e-01 -8.030005e-01 -2.800000e+00 1.600000e+00 8.122070e-01 8.122070e-01 4.061035e-01 -8.122070e-01 -2.700000e+00 1.600000e+00 8.211906e-01 8.211906e-01 4.105953e-01 -8.211906e-01 -2.600000e+00 1.600000e+00 8.299416e-01 8.299416e-01 4.149708e-01 -8.299416e-01 -2.500000e+00 1.600000e+00 8.384503e-01 8.384503e-01 4.192251e-01 -8.384503e-01 -2.400000e+00 1.600000e+00 8.467075e-01 8.467075e-01 4.233537e-01 -8.467075e-01 -2.300000e+00 1.600000e+00 8.547041e-01 8.547041e-01 4.273520e-01 -8.547041e-01 -2.200000e+00 1.600000e+00 8.624311e-01 8.624311e-01 4.312156e-01 -8.624311e-01 -2.100000e+00 1.600000e+00 8.698800e-01 8.698800e-01 4.349400e-01 -8.698800e-01 -2.000000e+00 1.600000e+00 8.770424e-01 8.770424e-01 4.385212e-01 -8.770424e-01 -1.900000e+00 1.600000e+00 8.839100e-01 8.839100e-01 4.419550e-01 -8.839100e-01 -1.800000e+00 1.600000e+00 8.904752e-01 8.904752e-01 4.452376e-01 -8.904752e-01 -1.700000e+00 1.600000e+00 8.967304e-01 8.967304e-01 4.483652e-01 -8.967304e-01 -1.600000e+00 1.600000e+00 9.026684e-01 9.026684e-01 4.513342e-01 -9.026684e-01 -1.500000e+00 1.600000e+00 9.082823e-01 9.082823e-01 4.541412e-01 -9.082823e-01 -1.400000e+00 1.600000e+00 9.135657e-01 9.135657e-01 4.567828e-01 -9.135657e-01 -1.300000e+00 1.600000e+00 9.185123e-01 9.185123e-01 4.592561e-01 -9.185123e-01 -1.200000e+00 1.600000e+00 9.231163e-01 9.231163e-01 4.615582e-01 -9.231163e-01 -1.100000e+00 1.600000e+00 9.273725e-01 9.273725e-01 4.636862e-01 -9.273725e-01 -1.000000e+00 1.600000e+00 9.312756e-01 9.312756e-01 4.656378e-01 -9.312756e-01 -9.000000e-01 1.600000e+00 9.348212e-01 9.348212e-01 4.674106e-01 -9.348212e-01 -8.000000e-01 1.600000e+00 9.380050e-01 9.380050e-01 4.690025e-01 -9.380050e-01 -7.000000e-01 1.600000e+00 9.408233e-01 9.408233e-01 4.704116e-01 -9.408233e-01 -6.000000e-01 1.600000e+00 9.432726e-01 9.432726e-01 4.716363e-01 -9.432726e-01 -5.000000e-01 1.600000e+00 9.453501e-01 9.453501e-01 4.726750e-01 -9.453501e-01 -4.000000e-01 1.600000e+00 9.470532e-01 9.470532e-01 4.735266e-01 -9.470532e-01 -3.000000e-01 1.600000e+00 9.483800e-01 9.483800e-01 4.741900e-01 -9.483800e-01 -2.000000e-01 1.600000e+00 9.493288e-01 9.493288e-01 4.746644e-01 -9.493288e-01 -1.000000e-01 1.600000e+00 9.498987e-01 9.498987e-01 4.749493e-01 -9.498987e-01 0.000000e+00 1.600000e+00 9.500886e-01 9.500886e-01 4.750443e-01 -9.500886e-01 1.000000e-01 1.600000e+00 9.498987e-01 9.498987e-01 4.749493e-01 -9.498987e-01 2.000000e-01 1.600000e+00 9.493288e-01 9.493288e-01 4.746644e-01 -9.493288e-01 3.000000e-01 1.600000e+00 9.483800e-01 9.483800e-01 4.741900e-01 -9.483800e-01 4.000000e-01 1.600000e+00 9.470532e-01 9.470532e-01 4.735266e-01 -9.470532e-01 5.000000e-01 1.600000e+00 9.453501e-01 9.453501e-01 4.726750e-01 -9.453501e-01 6.000000e-01 1.600000e+00 9.432726e-01 9.432726e-01 4.716363e-01 -9.432726e-01 7.000000e-01 1.600000e+00 9.408233e-01 9.408233e-01 4.704116e-01 -9.408233e-01 8.000000e-01 1.600000e+00 9.380050e-01 9.380050e-01 4.690025e-01 -9.380050e-01 9.000000e-01 1.600000e+00 9.348212e-01 9.348212e-01 4.674106e-01 -9.348212e-01 1.000000e+00 1.600000e+00 9.312756e-01 9.312756e-01 4.656378e-01 -9.312756e-01 1.100000e+00 1.600000e+00 9.273725e-01 9.273725e-01 4.636862e-01 -9.273725e-01 1.200000e+00 1.600000e+00 9.231163e-01 9.231163e-01 4.615582e-01 -9.231163e-01 1.300000e+00 1.600000e+00 9.185123e-01 9.185123e-01 4.592561e-01 -9.185123e-01 1.400000e+00 1.600000e+00 9.135657e-01 9.135657e-01 4.567828e-01 -9.135657e-01 1.500000e+00 1.600000e+00 9.082823e-01 9.082823e-01 4.541412e-01 -9.082823e-01 1.600000e+00 1.600000e+00 9.026684e-01 9.026684e-01 4.513342e-01 -9.026684e-01 1.700000e+00 1.600000e+00 8.967304e-01 8.967304e-01 4.483652e-01 -8.967304e-01 1.800000e+00 1.600000e+00 8.904752e-01 8.904752e-01 4.452376e-01 -8.904752e-01 1.900000e+00 1.600000e+00 8.839100e-01 8.839100e-01 4.419550e-01 -8.839100e-01 2.000000e+00 1.600000e+00 8.770424e-01 8.770424e-01 4.385212e-01 -8.770424e-01 2.100000e+00 1.600000e+00 8.698800e-01 8.698800e-01 4.349400e-01 -8.698800e-01 2.200000e+00 1.600000e+00 8.624311e-01 8.624311e-01 4.312156e-01 -8.624311e-01 2.300000e+00 1.600000e+00 8.547041e-01 8.547041e-01 4.273520e-01 -8.547041e-01 2.400000e+00 1.600000e+00 8.467075e-01 8.467075e-01 4.233537e-01 -8.467075e-01 2.500000e+00 1.600000e+00 8.384503e-01 8.384503e-01 4.192251e-01 -8.384503e-01 2.600000e+00 1.600000e+00 8.299416e-01 8.299416e-01 4.149708e-01 -8.299416e-01 2.700000e+00 1.600000e+00 8.211906e-01 8.211906e-01 4.105953e-01 -8.211906e-01 2.800000e+00 1.600000e+00 8.122070e-01 8.122070e-01 4.061035e-01 -8.122070e-01 2.900000e+00 1.600000e+00 8.030005e-01 8.030005e-01 4.015002e-01 -8.030005e-01 3.000000e+00 1.600000e+00 7.935807e-01 7.935807e-01 3.967904e-01 -7.935807e-01 3.100000e+00 1.600000e+00 7.839578e-01 7.839578e-01 3.919789e-01 -7.839578e-01 3.200000e+00 1.600000e+00 7.741420e-01 7.741420e-01 3.870710e-01 -7.741420e-01 3.300000e+00 1.600000e+00 7.641433e-01 7.641433e-01 3.820716e-01 -7.641433e-01 3.400000e+00 1.600000e+00 7.539721e-01 7.539721e-01 3.769860e-01 -7.539721e-01 3.500000e+00 1.600000e+00 7.436387e-01 7.436387e-01 3.718193e-01 -7.436387e-01 3.600000e+00 1.600000e+00 7.331536e-01 7.331536e-01 3.665768e-01 -7.331536e-01 3.700000e+00 1.600000e+00 7.225273e-01 7.225273e-01 3.612637e-01 -7.225273e-01 3.800000e+00 1.600000e+00 7.117703e-01 7.117703e-01 3.558851e-01 -7.117703e-01 3.900000e+00 1.600000e+00 7.008930e-01 7.008930e-01 3.504465e-01 -7.008930e-01 4.000000e+00 1.600000e+00 6.899059e-01 6.899059e-01 3.449530e-01 -6.899059e-01 4.100000e+00 1.600000e+00 6.788195e-01 6.788195e-01 3.394098e-01 -6.788195e-01 4.200000e+00 1.600000e+00 6.676441e-01 6.676441e-01 3.338221e-01 -6.676441e-01 4.300000e+00 1.600000e+00 6.563901e-01 6.563901e-01 3.281950e-01 -6.563901e-01 4.400000e+00 1.600000e+00 6.450677e-01 6.450677e-01 3.225338e-01 -6.450677e-01 4.500000e+00 1.600000e+00 6.336871e-01 6.336871e-01 3.168435e-01 -6.336871e-01 4.600000e+00 1.600000e+00 6.222583e-01 6.222583e-01 3.111292e-01 -6.222583e-01 4.700000e+00 1.600000e+00 6.107913e-01 6.107913e-01 3.053957e-01 -6.107913e-01 4.800000e+00 1.600000e+00 5.992958e-01 5.992958e-01 2.996479e-01 -5.992958e-01 4.900000e+00 1.600000e+00 5.877815e-01 5.877815e-01 2.938907e-01 -5.877815e-01 -5.000000e+00 1.700000e+00 5.724671e-01 5.724671e-01 2.862335e-01 -5.724671e-01 -4.900000e+00 1.700000e+00 5.839149e-01 5.839149e-01 2.919574e-01 -5.839149e-01 -4.800000e+00 1.700000e+00 5.953534e-01 5.953534e-01 2.976767e-01 -5.953534e-01 -4.700000e+00 1.700000e+00 6.067734e-01 6.067734e-01 3.033867e-01 -6.067734e-01 -4.600000e+00 1.700000e+00 6.181650e-01 6.181650e-01 3.090825e-01 -6.181650e-01 -4.500000e+00 1.700000e+00 6.295186e-01 6.295186e-01 3.147593e-01 -6.295186e-01 -4.400000e+00 1.700000e+00 6.408243e-01 6.408243e-01 3.204121e-01 -6.408243e-01 -4.300000e+00 1.700000e+00 6.520722e-01 6.520722e-01 3.260361e-01 -6.520722e-01 -4.200000e+00 1.700000e+00 6.632522e-01 6.632522e-01 3.316261e-01 -6.632522e-01 -4.100000e+00 1.700000e+00 6.743541e-01 6.743541e-01 3.371770e-01 -6.743541e-01 -4.000000e+00 1.700000e+00 6.853675e-01 6.853675e-01 3.426838e-01 -6.853675e-01 -3.900000e+00 1.700000e+00 6.962823e-01 6.962823e-01 3.481412e-01 -6.962823e-01 -3.800000e+00 1.700000e+00 7.070881e-01 7.070881e-01 3.535441e-01 -7.070881e-01 -3.700000e+00 1.700000e+00 7.177744e-01 7.177744e-01 3.588872e-01 -7.177744e-01 -3.600000e+00 1.700000e+00 7.283308e-01 7.283308e-01 3.641654e-01 -7.283308e-01 -3.500000e+00 1.700000e+00 7.387468e-01 7.387468e-01 3.693734e-01 -7.387468e-01 -3.400000e+00 1.700000e+00 7.490122e-01 7.490122e-01 3.745061e-01 -7.490122e-01 -3.300000e+00 1.700000e+00 7.591165e-01 7.591165e-01 3.795583e-01 -7.591165e-01 -3.200000e+00 1.700000e+00 7.690495e-01 7.690495e-01 3.845247e-01 -7.690495e-01 -3.100000e+00 1.700000e+00 7.788008e-01 7.788008e-01 3.894004e-01 -7.788008e-01 -3.000000e+00 1.700000e+00 7.883604e-01 7.883604e-01 3.941802e-01 -7.883604e-01 -2.900000e+00 1.700000e+00 7.977180e-01 7.977180e-01 3.988590e-01 -7.977180e-01 -2.800000e+00 1.700000e+00 8.068641e-01 8.068641e-01 4.034321e-01 -8.068641e-01 -2.700000e+00 1.700000e+00 8.157886e-01 8.157886e-01 4.078943e-01 -8.157886e-01 -2.600000e+00 1.700000e+00 8.244820e-01 8.244820e-01 4.122410e-01 -8.244820e-01 -2.500000e+00 1.700000e+00 8.329347e-01 8.329347e-01 4.164674e-01 -8.329347e-01 -2.400000e+00 1.700000e+00 8.411376e-01 8.411376e-01 4.205688e-01 -8.411376e-01 -2.300000e+00 1.700000e+00 8.490816e-01 8.490816e-01 4.245408e-01 -8.490816e-01 -2.200000e+00 1.700000e+00 8.567578e-01 8.567578e-01 4.283789e-01 -8.567578e-01 -2.100000e+00 1.700000e+00 8.641577e-01 8.641577e-01 4.320788e-01 -8.641577e-01 -2.000000e+00 1.700000e+00 8.712729e-01 8.712729e-01 4.356365e-01 -8.712729e-01 -1.900000e+00 1.700000e+00 8.780954e-01 8.780954e-01 4.390477e-01 -8.780954e-01 -1.800000e+00 1.700000e+00 8.846174e-01 8.846174e-01 4.423087e-01 -8.846174e-01 -1.700000e+00 1.700000e+00 8.908315e-01 8.908315e-01 4.454157e-01 -8.908315e-01 -1.600000e+00 1.700000e+00 8.967304e-01 8.967304e-01 4.483652e-01 -8.967304e-01 -1.500000e+00 1.700000e+00 9.023074e-01 9.023074e-01 4.511537e-01 -9.023074e-01 -1.400000e+00 1.700000e+00 9.075560e-01 9.075560e-01 4.537780e-01 -9.075560e-01 -1.300000e+00 1.700000e+00 9.124700e-01 9.124700e-01 4.562350e-01 -9.124700e-01 -1.200000e+00 1.700000e+00 9.170438e-01 9.170438e-01 4.585219e-01 -9.170438e-01 -1.100000e+00 1.700000e+00 9.212720e-01 9.212720e-01 4.606360e-01 -9.212720e-01 -1.000000e+00 1.700000e+00 9.251494e-01 9.251494e-01 4.625747e-01 -9.251494e-01 -9.000000e-01 1.700000e+00 9.286717e-01 9.286717e-01 4.643359e-01 -9.286717e-01 -8.000000e-01 1.700000e+00 9.318345e-01 9.318345e-01 4.659173e-01 -9.318345e-01 -7.000000e-01 1.700000e+00 9.346343e-01 9.346343e-01 4.673171e-01 -9.346343e-01 -6.000000e-01 1.700000e+00 9.370674e-01 9.370674e-01 4.685337e-01 -9.370674e-01 -5.000000e-01 1.700000e+00 9.391313e-01 9.391313e-01 4.695656e-01 -9.391313e-01 -4.000000e-01 1.700000e+00 9.408233e-01 9.408233e-01 4.704116e-01 -9.408233e-01 -3.000000e-01 1.700000e+00 9.421413e-01 9.421413e-01 4.710706e-01 -9.421413e-01 -2.000000e-01 1.700000e+00 9.430839e-01 9.430839e-01 4.715420e-01 -9.430839e-01 -1.000000e-01 1.700000e+00 9.436499e-01 9.436499e-01 4.718250e-01 -9.436499e-01 0.000000e+00 1.700000e+00 9.438387e-01 9.438387e-01 4.719194e-01 -9.438387e-01 1.000000e-01 1.700000e+00 9.436499e-01 9.436499e-01 4.718250e-01 -9.436499e-01 2.000000e-01 1.700000e+00 9.430839e-01 9.430839e-01 4.715420e-01 -9.430839e-01 3.000000e-01 1.700000e+00 9.421413e-01 9.421413e-01 4.710706e-01 -9.421413e-01 4.000000e-01 1.700000e+00 9.408233e-01 9.408233e-01 4.704116e-01 -9.408233e-01 5.000000e-01 1.700000e+00 9.391313e-01 9.391313e-01 4.695656e-01 -9.391313e-01 6.000000e-01 1.700000e+00 9.370674e-01 9.370674e-01 4.685337e-01 -9.370674e-01 7.000000e-01 1.700000e+00 9.346343e-01 9.346343e-01 4.673171e-01 -9.346343e-01 8.000000e-01 1.700000e+00 9.318345e-01 9.318345e-01 4.659173e-01 -9.318345e-01 9.000000e-01 1.700000e+00 9.286717e-01 9.286717e-01 4.643359e-01 -9.286717e-01 1.000000e+00 1.700000e+00 9.251494e-01 9.251494e-01 4.625747e-01 -9.251494e-01 1.100000e+00 1.700000e+00 9.212720e-01 9.212720e-01 4.606360e-01 -9.212720e-01 1.200000e+00 1.700000e+00 9.170438e-01 9.170438e-01 4.585219e-01 -9.170438e-01 1.300000e+00 1.700000e+00 9.124700e-01 9.124700e-01 4.562350e-01 -9.124700e-01 1.400000e+00 1.700000e+00 9.075560e-01 9.075560e-01 4.537780e-01 -9.075560e-01 1.500000e+00 1.700000e+00 9.023074e-01 9.023074e-01 4.511537e-01 -9.023074e-01 1.600000e+00 1.700000e+00 8.967304e-01 8.967304e-01 4.483652e-01 -8.967304e-01 1.700000e+00 1.700000e+00 8.908315e-01 8.908315e-01 4.454157e-01 -8.908315e-01 1.800000e+00 1.700000e+00 8.846174e-01 8.846174e-01 4.423087e-01 -8.846174e-01 1.900000e+00 1.700000e+00 8.780954e-01 8.780954e-01 4.390477e-01 -8.780954e-01 2.000000e+00 1.700000e+00 8.712729e-01 8.712729e-01 4.356365e-01 -8.712729e-01 2.100000e+00 1.700000e+00 8.641577e-01 8.641577e-01 4.320788e-01 -8.641577e-01 2.200000e+00 1.700000e+00 8.567578e-01 8.567578e-01 4.283789e-01 -8.567578e-01 2.300000e+00 1.700000e+00 8.490816e-01 8.490816e-01 4.245408e-01 -8.490816e-01 2.400000e+00 1.700000e+00 8.411376e-01 8.411376e-01 4.205688e-01 -8.411376e-01 2.500000e+00 1.700000e+00 8.329347e-01 8.329347e-01 4.164674e-01 -8.329347e-01 2.600000e+00 1.700000e+00 8.244820e-01 8.244820e-01 4.122410e-01 -8.244820e-01 2.700000e+00 1.700000e+00 8.157886e-01 8.157886e-01 4.078943e-01 -8.157886e-01 2.800000e+00 1.700000e+00 8.068641e-01 8.068641e-01 4.034321e-01 -8.068641e-01 2.900000e+00 1.700000e+00 7.977180e-01 7.977180e-01 3.988590e-01 -7.977180e-01 3.000000e+00 1.700000e+00 7.883604e-01 7.883604e-01 3.941802e-01 -7.883604e-01 3.100000e+00 1.700000e+00 7.788008e-01 7.788008e-01 3.894004e-01 -7.788008e-01 3.200000e+00 1.700000e+00 7.690495e-01 7.690495e-01 3.845247e-01 -7.690495e-01 3.300000e+00 1.700000e+00 7.591165e-01 7.591165e-01 3.795583e-01 -7.591165e-01 3.400000e+00 1.700000e+00 7.490122e-01 7.490122e-01 3.745061e-01 -7.490122e-01 3.500000e+00 1.700000e+00 7.387468e-01 7.387468e-01 3.693734e-01 -7.387468e-01 3.600000e+00 1.700000e+00 7.283308e-01 7.283308e-01 3.641654e-01 -7.283308e-01 3.700000e+00 1.700000e+00 7.177744e-01 7.177744e-01 3.588872e-01 -7.177744e-01 3.800000e+00 1.700000e+00 7.070881e-01 7.070881e-01 3.535441e-01 -7.070881e-01 3.900000e+00 1.700000e+00 6.962823e-01 6.962823e-01 3.481412e-01 -6.962823e-01 4.000000e+00 1.700000e+00 6.853675e-01 6.853675e-01 3.426838e-01 -6.853675e-01 4.100000e+00 1.700000e+00 6.743541e-01 6.743541e-01 3.371770e-01 -6.743541e-01 4.200000e+00 1.700000e+00 6.632522e-01 6.632522e-01 3.316261e-01 -6.632522e-01 4.300000e+00 1.700000e+00 6.520722e-01 6.520722e-01 3.260361e-01 -6.520722e-01 4.400000e+00 1.700000e+00 6.408243e-01 6.408243e-01 3.204121e-01 -6.408243e-01 4.500000e+00 1.700000e+00 6.295186e-01 6.295186e-01 3.147593e-01 -6.295186e-01 4.600000e+00 1.700000e+00 6.181650e-01 6.181650e-01 3.090825e-01 -6.181650e-01 4.700000e+00 1.700000e+00 6.067734e-01 6.067734e-01 3.033867e-01 -6.067734e-01 4.800000e+00 1.700000e+00 5.953534e-01 5.953534e-01 2.976767e-01 -5.953534e-01 4.900000e+00 1.700000e+00 5.839149e-01 5.839149e-01 2.919574e-01 -5.839149e-01 -5.000000e+00 1.800000e+00 5.684738e-01 5.684738e-01 2.842369e-01 -5.684738e-01 -4.900000e+00 1.800000e+00 5.798418e-01 5.798418e-01 2.899209e-01 -5.798418e-01 -4.800000e+00 1.800000e+00 5.912005e-01 5.912005e-01 2.956003e-01 -5.912005e-01 -4.700000e+00 1.800000e+00 6.025408e-01 6.025408e-01 3.012704e-01 -6.025408e-01 -4.600000e+00 1.800000e+00 6.138529e-01 6.138529e-01 3.069265e-01 -6.138529e-01 -4.500000e+00 1.800000e+00 6.251273e-01 6.251273e-01 3.125637e-01 -6.251273e-01 -4.400000e+00 1.800000e+00 6.363541e-01 6.363541e-01 3.181771e-01 -6.363541e-01 -4.300000e+00 1.800000e+00 6.475236e-01 6.475236e-01 3.237618e-01 -6.475236e-01 -4.200000e+00 1.800000e+00 6.586257e-01 6.586257e-01 3.293128e-01 -6.586257e-01 -4.100000e+00 1.800000e+00 6.696501e-01 6.696501e-01 3.348250e-01 -6.696501e-01 -4.000000e+00 1.800000e+00 6.805868e-01 6.805868e-01 3.402934e-01 -6.805868e-01 -3.900000e+00 1.800000e+00 6.914254e-01 6.914254e-01 3.457127e-01 -6.914254e-01 -3.800000e+00 1.800000e+00 7.021558e-01 7.021558e-01 3.510779e-01 -7.021558e-01 -3.700000e+00 1.800000e+00 7.127675e-01 7.127675e-01 3.563837e-01 -7.127675e-01 -3.600000e+00 1.800000e+00 7.232503e-01 7.232503e-01 3.616251e-01 -7.232503e-01 -3.500000e+00 1.800000e+00 7.335937e-01 7.335937e-01 3.667969e-01 -7.335937e-01 -3.400000e+00 1.800000e+00 7.437874e-01 7.437874e-01 3.718937e-01 -7.437874e-01 -3.300000e+00 1.800000e+00 7.538213e-01 7.538213e-01 3.769106e-01 -7.538213e-01 -3.200000e+00 1.800000e+00 7.636849e-01 7.636849e-01 3.818425e-01 -7.636849e-01 -3.100000e+00 1.800000e+00 7.733682e-01 7.733682e-01 3.866841e-01 -7.733682e-01 -3.000000e+00 1.800000e+00 7.828611e-01 7.828611e-01 3.914306e-01 -7.828611e-01 -2.900000e+00 1.800000e+00 7.921535e-01 7.921535e-01 3.960768e-01 -7.921535e-01 -2.800000e+00 1.800000e+00 8.012358e-01 8.012358e-01 4.006179e-01 -8.012358e-01 -2.700000e+00 1.800000e+00 8.100981e-01 8.100981e-01 4.050490e-01 -8.100981e-01 -2.600000e+00 1.800000e+00 8.187308e-01 8.187308e-01 4.093654e-01 -8.187308e-01 -2.500000e+00 1.800000e+00 8.271245e-01 8.271245e-01 4.135623e-01 -8.271245e-01 -2.400000e+00 1.800000e+00 8.352702e-01 8.352702e-01 4.176351e-01 -8.352702e-01 -2.300000e+00 1.800000e+00 8.431588e-01 8.431588e-01 4.215794e-01 -8.431588e-01 -2.200000e+00 1.800000e+00 8.507814e-01 8.507814e-01 4.253907e-01 -8.507814e-01 -2.100000e+00 1.800000e+00 8.581297e-01 8.581297e-01 4.290649e-01 -8.581297e-01 -2.000000e+00 1.800000e+00 8.651953e-01 8.651953e-01 4.325977e-01 -8.651953e-01 -1.900000e+00 1.800000e+00 8.719702e-01 8.719702e-01 4.359851e-01 -8.719702e-01 -1.800000e+00 1.800000e+00 8.784468e-01 8.784468e-01 4.392234e-01 -8.784468e-01 -1.700000e+00 1.800000e+00 8.846174e-01 8.846174e-01 4.423087e-01 -8.846174e-01 -1.600000e+00 1.800000e+00 8.904752e-01 8.904752e-01 4.452376e-01 -8.904752e-01 -1.500000e+00 1.800000e+00 8.960133e-01 8.960133e-01 4.480067e-01 -8.960133e-01 -1.400000e+00 1.800000e+00 9.012253e-01 9.012253e-01 4.506127e-01 -9.012253e-01 -1.300000e+00 1.800000e+00 9.061051e-01 9.061051e-01 4.530526e-01 -9.061051e-01 -1.200000e+00 1.800000e+00 9.106470e-01 9.106470e-01 4.553235e-01 -9.106470e-01 -1.100000e+00 1.800000e+00 9.148456e-01 9.148456e-01 4.574228e-01 -9.148456e-01 -1.000000e+00 1.800000e+00 9.186960e-01 9.186960e-01 4.593480e-01 -9.186960e-01 -9.000000e-01 1.800000e+00 9.221937e-01 9.221937e-01 4.610969e-01 -9.221937e-01 -8.000000e-01 1.800000e+00 9.253345e-01 9.253345e-01 4.626673e-01 -9.253345e-01 -7.000000e-01 1.800000e+00 9.281147e-01 9.281147e-01 4.640573e-01 -9.281147e-01 -6.000000e-01 1.800000e+00 9.305309e-01 9.305309e-01 4.652655e-01 -9.305309e-01 -5.000000e-01 1.800000e+00 9.325803e-01 9.325803e-01 4.662901e-01 -9.325803e-01 -4.000000e-01 1.800000e+00 9.342605e-01 9.342605e-01 4.671302e-01 -9.342605e-01 -3.000000e-01 1.800000e+00 9.355693e-01 9.355693e-01 4.677847e-01 -9.355693e-01 -2.000000e-01 1.800000e+00 9.365054e-01 9.365054e-01 4.682527e-01 -9.365054e-01 -1.000000e-01 1.800000e+00 9.370674e-01 9.370674e-01 4.685337e-01 -9.370674e-01 0.000000e+00 1.800000e+00 9.372549e-01 9.372549e-01 4.686275e-01 -9.372549e-01 1.000000e-01 1.800000e+00 9.370674e-01 9.370674e-01 4.685337e-01 -9.370674e-01 2.000000e-01 1.800000e+00 9.365054e-01 9.365054e-01 4.682527e-01 -9.365054e-01 3.000000e-01 1.800000e+00 9.355693e-01 9.355693e-01 4.677847e-01 -9.355693e-01 4.000000e-01 1.800000e+00 9.342605e-01 9.342605e-01 4.671302e-01 -9.342605e-01 5.000000e-01 1.800000e+00 9.325803e-01 9.325803e-01 4.662901e-01 -9.325803e-01 6.000000e-01 1.800000e+00 9.305309e-01 9.305309e-01 4.652655e-01 -9.305309e-01 7.000000e-01 1.800000e+00 9.281147e-01 9.281147e-01 4.640573e-01 -9.281147e-01 8.000000e-01 1.800000e+00 9.253345e-01 9.253345e-01 4.626673e-01 -9.253345e-01 9.000000e-01 1.800000e+00 9.221937e-01 9.221937e-01 4.610969e-01 -9.221937e-01 1.000000e+00 1.800000e+00 9.186960e-01 9.186960e-01 4.593480e-01 -9.186960e-01 1.100000e+00 1.800000e+00 9.148456e-01 9.148456e-01 4.574228e-01 -9.148456e-01 1.200000e+00 1.800000e+00 9.106470e-01 9.106470e-01 4.553235e-01 -9.106470e-01 1.300000e+00 1.800000e+00 9.061051e-01 9.061051e-01 4.530526e-01 -9.061051e-01 1.400000e+00 1.800000e+00 9.012253e-01 9.012253e-01 4.506127e-01 -9.012253e-01 1.500000e+00 1.800000e+00 8.960133e-01 8.960133e-01 4.480067e-01 -8.960133e-01 1.600000e+00 1.800000e+00 8.904752e-01 8.904752e-01 4.452376e-01 -8.904752e-01 1.700000e+00 1.800000e+00 8.846174e-01 8.846174e-01 4.423087e-01 -8.846174e-01 1.800000e+00 1.800000e+00 8.784468e-01 8.784468e-01 4.392234e-01 -8.784468e-01 1.900000e+00 1.800000e+00 8.719702e-01 8.719702e-01 4.359851e-01 -8.719702e-01 2.000000e+00 1.800000e+00 8.651953e-01 8.651953e-01 4.325977e-01 -8.651953e-01 2.100000e+00 1.800000e+00 8.581297e-01 8.581297e-01 4.290649e-01 -8.581297e-01 2.200000e+00 1.800000e+00 8.507814e-01 8.507814e-01 4.253907e-01 -8.507814e-01 2.300000e+00 1.800000e+00 8.431588e-01 8.431588e-01 4.215794e-01 -8.431588e-01 2.400000e+00 1.800000e+00 8.352702e-01 8.352702e-01 4.176351e-01 -8.352702e-01 2.500000e+00 1.800000e+00 8.271245e-01 8.271245e-01 4.135623e-01 -8.271245e-01 2.600000e+00 1.800000e+00 8.187308e-01 8.187308e-01 4.093654e-01 -8.187308e-01 2.700000e+00 1.800000e+00 8.100981e-01 8.100981e-01 4.050490e-01 -8.100981e-01 2.800000e+00 1.800000e+00 8.012358e-01 8.012358e-01 4.006179e-01 -8.012358e-01 2.900000e+00 1.800000e+00 7.921535e-01 7.921535e-01 3.960768e-01 -7.921535e-01 3.000000e+00 1.800000e+00 7.828611e-01 7.828611e-01 3.914306e-01 -7.828611e-01 3.100000e+00 1.800000e+00 7.733682e-01 7.733682e-01 3.866841e-01 -7.733682e-01 3.200000e+00 1.800000e+00 7.636849e-01 7.636849e-01 3.818425e-01 -7.636849e-01 3.300000e+00 1.800000e+00 7.538213e-01 7.538213e-01 3.769106e-01 -7.538213e-01 3.400000e+00 1.800000e+00 7.437874e-01 7.437874e-01 3.718937e-01 -7.437874e-01 3.500000e+00 1.800000e+00 7.335937e-01 7.335937e-01 3.667969e-01 -7.335937e-01 3.600000e+00 1.800000e+00 7.232503e-01 7.232503e-01 3.616251e-01 -7.232503e-01 3.700000e+00 1.800000e+00 7.127675e-01 7.127675e-01 3.563837e-01 -7.127675e-01 3.800000e+00 1.800000e+00 7.021558e-01 7.021558e-01 3.510779e-01 -7.021558e-01 3.900000e+00 1.800000e+00 6.914254e-01 6.914254e-01 3.457127e-01 -6.914254e-01 4.000000e+00 1.800000e+00 6.805868e-01 6.805868e-01 3.402934e-01 -6.805868e-01 4.100000e+00 1.800000e+00 6.696501e-01 6.696501e-01 3.348250e-01 -6.696501e-01 4.200000e+00 1.800000e+00 6.586257e-01 6.586257e-01 3.293128e-01 -6.586257e-01 4.300000e+00 1.800000e+00 6.475236e-01 6.475236e-01 3.237618e-01 -6.475236e-01 4.400000e+00 1.800000e+00 6.363541e-01 6.363541e-01 3.181771e-01 -6.363541e-01 4.500000e+00 1.800000e+00 6.251273e-01 6.251273e-01 3.125637e-01 -6.251273e-01 4.600000e+00 1.800000e+00 6.138529e-01 6.138529e-01 3.069265e-01 -6.138529e-01 4.700000e+00 1.800000e+00 6.025408e-01 6.025408e-01 3.012704e-01 -6.025408e-01 4.800000e+00 1.800000e+00 5.912005e-01 5.912005e-01 2.956003e-01 -5.912005e-01 4.900000e+00 1.800000e+00 5.798418e-01 5.798418e-01 2.899209e-01 -5.798418e-01 -5.000000e+00 1.900000e+00 5.642827e-01 5.642827e-01 2.821413e-01 -5.642827e-01 -4.900000e+00 1.900000e+00 5.755668e-01 5.755668e-01 2.877834e-01 -5.755668e-01 -4.800000e+00 1.900000e+00 5.868418e-01 5.868418e-01 2.934209e-01 -5.868418e-01 -4.700000e+00 1.900000e+00 5.980985e-01 5.980985e-01 2.990492e-01 -5.980985e-01 -4.600000e+00 1.900000e+00 6.093271e-01 6.093271e-01 3.046636e-01 -6.093271e-01 -4.500000e+00 1.900000e+00 6.205184e-01 6.205184e-01 3.102592e-01 -6.205184e-01 -4.400000e+00 1.900000e+00 6.316625e-01 6.316625e-01 3.158313e-01 -6.316625e-01 -4.300000e+00 1.900000e+00 6.427496e-01 6.427496e-01 3.213748e-01 -6.427496e-01 -4.200000e+00 1.900000e+00 6.537698e-01 6.537698e-01 3.268849e-01 -6.537698e-01 -4.100000e+00 1.900000e+00 6.647130e-01 6.647130e-01 3.323565e-01 -6.647130e-01 -4.000000e+00 1.900000e+00 6.755690e-01 6.755690e-01 3.377845e-01 -6.755690e-01 -3.900000e+00 1.900000e+00 6.863278e-01 6.863278e-01 3.431639e-01 -6.863278e-01 -3.800000e+00 1.900000e+00 6.969790e-01 6.969790e-01 3.484895e-01 -6.969790e-01 -3.700000e+00 1.900000e+00 7.075125e-01 7.075125e-01 3.537562e-01 -7.075125e-01 -3.600000e+00 1.900000e+00 7.179180e-01 7.179180e-01 3.589590e-01 -7.179180e-01 -3.500000e+00 1.900000e+00 7.281851e-01 7.281851e-01 3.640926e-01 -7.281851e-01 -3.400000e+00 1.900000e+00 7.383037e-01 7.383037e-01 3.691519e-01 -7.383037e-01 -3.300000e+00 1.900000e+00 7.482636e-01 7.482636e-01 3.741318e-01 -7.482636e-01 -3.200000e+00 1.900000e+00 7.580545e-01 7.580545e-01 3.790272e-01 -7.580545e-01 -3.100000e+00 1.900000e+00 7.676664e-01 7.676664e-01 3.838332e-01 -7.676664e-01 -3.000000e+00 1.900000e+00 7.770893e-01 7.770893e-01 3.885446e-01 -7.770893e-01 -2.900000e+00 1.900000e+00 7.863132e-01 7.863132e-01 3.931566e-01 -7.863132e-01 -2.800000e+00 1.900000e+00 7.953286e-01 7.953286e-01 3.976643e-01 -7.953286e-01 -2.700000e+00 1.900000e+00 8.041254e-01 8.041254e-01 4.020627e-01 -8.041254e-01 -2.600000e+00 1.900000e+00 8.126945e-01 8.126945e-01 4.063472e-01 -8.126945e-01 -2.500000e+00 1.900000e+00 8.210264e-01 8.210264e-01 4.105132e-01 -8.210264e-01 -2.400000e+00 1.900000e+00 8.291120e-01 8.291120e-01 4.145560e-01 -8.291120e-01 -2.300000e+00 1.900000e+00 8.369424e-01 8.369424e-01 4.184712e-01 -8.369424e-01 -2.200000e+00 1.900000e+00 8.445089e-01 8.445089e-01 4.222544e-01 -8.445089e-01 -2.100000e+00 1.900000e+00 8.518030e-01 8.518030e-01 4.259015e-01 -8.518030e-01 -2.000000e+00 1.900000e+00 8.588165e-01 8.588165e-01 4.294083e-01 -8.588165e-01 -1.900000e+00 1.900000e+00 8.655415e-01 8.655415e-01 4.327707e-01 -8.655415e-01 -1.800000e+00 1.900000e+00 8.719702e-01 8.719702e-01 4.359851e-01 -8.719702e-01 -1.700000e+00 1.900000e+00 8.780954e-01 8.780954e-01 4.390477e-01 -8.780954e-01 -1.600000e+00 1.900000e+00 8.839100e-01 8.839100e-01 4.419550e-01 -8.839100e-01 -1.500000e+00 1.900000e+00 8.894073e-01 8.894073e-01 4.447036e-01 -8.894073e-01 -1.400000e+00 1.900000e+00 8.945808e-01 8.945808e-01 4.472904e-01 -8.945808e-01 -1.300000e+00 1.900000e+00 8.994247e-01 8.994247e-01 4.497123e-01 -8.994247e-01 -1.200000e+00 1.900000e+00 9.039330e-01 9.039330e-01 4.519665e-01 -9.039330e-01 -1.100000e+00 1.900000e+00 9.081007e-01 9.081007e-01 4.540504e-01 -9.081007e-01 -1.000000e+00 1.900000e+00 9.119228e-01 9.119228e-01 4.559614e-01 -9.119228e-01 -9.000000e-01 1.900000e+00 9.153947e-01 9.153947e-01 4.576973e-01 -9.153947e-01 -8.000000e-01 1.900000e+00 9.185123e-01 9.185123e-01 4.592561e-01 -9.185123e-01 -7.000000e-01 1.900000e+00 9.212720e-01 9.212720e-01 4.606360e-01 -9.212720e-01 -6.000000e-01 1.900000e+00 9.236704e-01 9.236704e-01 4.618352e-01 -9.236704e-01 -5.000000e-01 1.900000e+00 9.257047e-01 9.257047e-01 4.628524e-01 -9.257047e-01 -4.000000e-01 1.900000e+00 9.273725e-01 9.273725e-01 4.636862e-01 -9.273725e-01 -3.000000e-01 1.900000e+00 9.286717e-01 9.286717e-01 4.643359e-01 -9.286717e-01 -2.000000e-01 1.900000e+00 9.296008e-01 9.296008e-01 4.648004e-01 -9.296008e-01 -1.000000e-01 1.900000e+00 9.301587e-01 9.301587e-01 4.650794e-01 -9.301587e-01 0.000000e+00 1.900000e+00 9.303448e-01 9.303448e-01 4.651724e-01 -9.303448e-01 1.000000e-01 1.900000e+00 9.301587e-01 9.301587e-01 4.650794e-01 -9.301587e-01 2.000000e-01 1.900000e+00 9.296008e-01 9.296008e-01 4.648004e-01 -9.296008e-01 3.000000e-01 1.900000e+00 9.286717e-01 9.286717e-01 4.643359e-01 -9.286717e-01 4.000000e-01 1.900000e+00 9.273725e-01 9.273725e-01 4.636862e-01 -9.273725e-01 5.000000e-01 1.900000e+00 9.257047e-01 9.257047e-01 4.628524e-01 -9.257047e-01 6.000000e-01 1.900000e+00 9.236704e-01 9.236704e-01 4.618352e-01 -9.236704e-01 7.000000e-01 1.900000e+00 9.212720e-01 9.212720e-01 4.606360e-01 -9.212720e-01 8.000000e-01 1.900000e+00 9.185123e-01 9.185123e-01 4.592561e-01 -9.185123e-01 9.000000e-01 1.900000e+00 9.153947e-01 9.153947e-01 4.576973e-01 -9.153947e-01 1.000000e+00 1.900000e+00 9.119228e-01 9.119228e-01 4.559614e-01 -9.119228e-01 1.100000e+00 1.900000e+00 9.081007e-01 9.081007e-01 4.540504e-01 -9.081007e-01 1.200000e+00 1.900000e+00 9.039330e-01 9.039330e-01 4.519665e-01 -9.039330e-01 1.300000e+00 1.900000e+00 8.994247e-01 8.994247e-01 4.497123e-01 -8.994247e-01 1.400000e+00 1.900000e+00 8.945808e-01 8.945808e-01 4.472904e-01 -8.945808e-01 1.500000e+00 1.900000e+00 8.894073e-01 8.894073e-01 4.447036e-01 -8.894073e-01 1.600000e+00 1.900000e+00 8.839100e-01 8.839100e-01 4.419550e-01 -8.839100e-01 1.700000e+00 1.900000e+00 8.780954e-01 8.780954e-01 4.390477e-01 -8.780954e-01 1.800000e+00 1.900000e+00 8.719702e-01 8.719702e-01 4.359851e-01 -8.719702e-01 1.900000e+00 1.900000e+00 8.655415e-01 8.655415e-01 4.327707e-01 -8.655415e-01 2.000000e+00 1.900000e+00 8.588165e-01 8.588165e-01 4.294083e-01 -8.588165e-01 2.100000e+00 1.900000e+00 8.518030e-01 8.518030e-01 4.259015e-01 -8.518030e-01 2.200000e+00 1.900000e+00 8.445089e-01 8.445089e-01 4.222544e-01 -8.445089e-01 2.300000e+00 1.900000e+00 8.369424e-01 8.369424e-01 4.184712e-01 -8.369424e-01 2.400000e+00 1.900000e+00 8.291120e-01 8.291120e-01 4.145560e-01 -8.291120e-01 2.500000e+00 1.900000e+00 8.210264e-01 8.210264e-01 4.105132e-01 -8.210264e-01 2.600000e+00 1.900000e+00 8.126945e-01 8.126945e-01 4.063472e-01 -8.126945e-01 2.700000e+00 1.900000e+00 8.041254e-01 8.041254e-01 4.020627e-01 -8.041254e-01 2.800000e+00 1.900000e+00 7.953286e-01 7.953286e-01 3.976643e-01 -7.953286e-01 2.900000e+00 1.900000e+00 7.863132e-01 7.863132e-01 3.931566e-01 -7.863132e-01 3.000000e+00 1.900000e+00 7.770893e-01 7.770893e-01 3.885446e-01 -7.770893e-01 3.100000e+00 1.900000e+00 7.676664e-01 7.676664e-01 3.838332e-01 -7.676664e-01 3.200000e+00 1.900000e+00 7.580545e-01 7.580545e-01 3.790272e-01 -7.580545e-01 3.300000e+00 1.900000e+00 7.482636e-01 7.482636e-01 3.741318e-01 -7.482636e-01 3.400000e+00 1.900000e+00 7.383037e-01 7.383037e-01 3.691519e-01 -7.383037e-01 3.500000e+00 1.900000e+00 7.281851e-01 7.281851e-01 3.640926e-01 -7.281851e-01 3.600000e+00 1.900000e+00 7.179180e-01 7.179180e-01 3.589590e-01 -7.179180e-01 3.700000e+00 1.900000e+00 7.075125e-01 7.075125e-01 3.537562e-01 -7.075125e-01 3.800000e+00 1.900000e+00 6.969790e-01 6.969790e-01 3.484895e-01 -6.969790e-01 3.900000e+00 1.900000e+00 6.863278e-01 6.863278e-01 3.431639e-01 -6.863278e-01 4.000000e+00 1.900000e+00 6.755690e-01 6.755690e-01 3.377845e-01 -6.755690e-01 4.100000e+00 1.900000e+00 6.647130e-01 6.647130e-01 3.323565e-01 -6.647130e-01 4.200000e+00 1.900000e+00 6.537698e-01 6.537698e-01 3.268849e-01 -6.537698e-01 4.300000e+00 1.900000e+00 6.427496e-01 6.427496e-01 3.213748e-01 -6.427496e-01 4.400000e+00 1.900000e+00 6.316625e-01 6.316625e-01 3.158313e-01 -6.316625e-01 4.500000e+00 1.900000e+00 6.205184e-01 6.205184e-01 3.102592e-01 -6.205184e-01 4.600000e+00 1.900000e+00 6.093271e-01 6.093271e-01 3.046636e-01 -6.093271e-01 4.700000e+00 1.900000e+00 5.980985e-01 5.980985e-01 2.990492e-01 -5.980985e-01 4.800000e+00 1.900000e+00 5.868418e-01 5.868418e-01 2.934209e-01 -5.868418e-01 4.900000e+00 1.900000e+00 5.755668e-01 5.755668e-01 2.877834e-01 -5.755668e-01 -5.000000e+00 2.000000e+00 5.598984e-01 5.598984e-01 2.799492e-01 -5.598984e-01 -4.900000e+00 2.000000e+00 5.710948e-01 5.710948e-01 2.855474e-01 -5.710948e-01 -4.800000e+00 2.000000e+00 5.822822e-01 5.822822e-01 2.911411e-01 -5.822822e-01 -4.700000e+00 2.000000e+00 5.934514e-01 5.934514e-01 2.967257e-01 -5.934514e-01 -4.600000e+00 2.000000e+00 6.045929e-01 6.045929e-01 3.022965e-01 -6.045929e-01 -4.500000e+00 2.000000e+00 6.156972e-01 6.156972e-01 3.078486e-01 -6.156972e-01 -4.400000e+00 2.000000e+00 6.267547e-01 6.267547e-01 3.133774e-01 -6.267547e-01 -4.300000e+00 2.000000e+00 6.377557e-01 6.377557e-01 3.188778e-01 -6.377557e-01 -4.200000e+00 2.000000e+00 6.486902e-01 6.486902e-01 3.243451e-01 -6.486902e-01 -4.100000e+00 2.000000e+00 6.595483e-01 6.595483e-01 3.297742e-01 -6.595483e-01 -4.000000e+00 2.000000e+00 6.703200e-01 6.703200e-01 3.351600e-01 -6.703200e-01 -3.900000e+00 2.000000e+00 6.809952e-01 6.809952e-01 3.404976e-01 -6.809952e-01 -3.800000e+00 2.000000e+00 6.915637e-01 6.915637e-01 3.457819e-01 -6.915637e-01 -3.700000e+00 2.000000e+00 7.020153e-01 7.020153e-01 3.510077e-01 -7.020153e-01 -3.600000e+00 2.000000e+00 7.123400e-01 7.123400e-01 3.561700e-01 -7.123400e-01 -3.500000e+00 2.000000e+00 7.225274e-01 7.225274e-01 3.612637e-01 -7.225274e-01 -3.400000e+00 2.000000e+00 7.325673e-01 7.325673e-01 3.662837e-01 -7.325673e-01 -3.300000e+00 2.000000e+00 7.424498e-01 7.424498e-01 3.712249e-01 -7.424498e-01 -3.200000e+00 2.000000e+00 7.521647e-01 7.521647e-01 3.760823e-01 -7.521647e-01 -3.100000e+00 2.000000e+00 7.617019e-01 7.617019e-01 3.808509e-01 -7.617019e-01 -3.000000e+00 2.000000e+00 7.710516e-01 7.710516e-01 3.855258e-01 -7.710516e-01 -2.900000e+00 2.000000e+00 7.802039e-01 7.802039e-01 3.901019e-01 -7.802039e-01 -2.800000e+00 2.000000e+00 7.891491e-01 7.891491e-01 3.945746e-01 -7.891491e-01 -2.700000e+00 2.000000e+00 7.978777e-01 7.978777e-01 3.989388e-01 -7.978777e-01 -2.600000e+00 2.000000e+00 8.063802e-01 8.063802e-01 4.031901e-01 -8.063802e-01 -2.500000e+00 2.000000e+00 8.146473e-01 8.146473e-01 4.073237e-01 -8.146473e-01 -2.400000e+00 2.000000e+00 8.226701e-01 8.226701e-01 4.113351e-01 -8.226701e-01 -2.300000e+00 2.000000e+00 8.304397e-01 8.304397e-01 4.152198e-01 -8.304397e-01 -2.200000e+00 2.000000e+00 8.379474e-01 8.379474e-01 4.189737e-01 -8.379474e-01 -2.100000e+00 2.000000e+00 8.451848e-01 8.451848e-01 4.225924e-01 -8.451848e-01 -2.000000e+00 2.000000e+00 8.521438e-01 8.521438e-01 4.260719e-01 -8.521438e-01 -1.900000e+00 2.000000e+00 8.588165e-01 8.588165e-01 4.294083e-01 -8.588165e-01 -1.800000e+00 2.000000e+00 8.651953e-01 8.651953e-01 4.325977e-01 -8.651953e-01 -1.700000e+00 2.000000e+00 8.712729e-01 8.712729e-01 4.356365e-01 -8.712729e-01 -1.600000e+00 2.000000e+00 8.770424e-01 8.770424e-01 4.385212e-01 -8.770424e-01 -1.500000e+00 2.000000e+00 8.824969e-01 8.824969e-01 4.412484e-01 -8.824969e-01 -1.400000e+00 2.000000e+00 8.876302e-01 8.876302e-01 4.438151e-01 -8.876302e-01 -1.300000e+00 2.000000e+00 8.924364e-01 8.924364e-01 4.462182e-01 -8.924364e-01 -1.200000e+00 2.000000e+00 8.969098e-01 8.969098e-01 4.484549e-01 -8.969098e-01 -1.100000e+00 2.000000e+00 9.010451e-01 9.010451e-01 4.505225e-01 -9.010451e-01 -1.000000e+00 2.000000e+00 9.048374e-01 9.048374e-01 4.524187e-01 -9.048374e-01 -9.000000e-01 2.000000e+00 9.082823e-01 9.082823e-01 4.541412e-01 -9.082823e-01 -8.000000e-01 2.000000e+00 9.113758e-01 9.113758e-01 4.556879e-01 -9.113758e-01 -7.000000e-01 2.000000e+00 9.141140e-01 9.141140e-01 4.570570e-01 -9.141140e-01 -6.000000e-01 2.000000e+00 9.164938e-01 9.164938e-01 4.582469e-01 -9.164938e-01 -5.000000e-01 2.000000e+00 9.185123e-01 9.185123e-01 4.592561e-01 -9.185123e-01 -4.000000e-01 2.000000e+00 9.201671e-01 9.201671e-01 4.600835e-01 -9.201671e-01 -3.000000e-01 2.000000e+00 9.214562e-01 9.214562e-01 4.607281e-01 -9.214562e-01 -2.000000e-01 2.000000e+00 9.223781e-01 9.223781e-01 4.611891e-01 -9.223781e-01 -1.000000e-01 2.000000e+00 9.229317e-01 9.229317e-01 4.614659e-01 -9.229317e-01 0.000000e+00 2.000000e+00 9.231163e-01 9.231163e-01 4.615582e-01 -9.231163e-01 1.000000e-01 2.000000e+00 9.229317e-01 9.229317e-01 4.614659e-01 -9.229317e-01 2.000000e-01 2.000000e+00 9.223781e-01 9.223781e-01 4.611891e-01 -9.223781e-01 3.000000e-01 2.000000e+00 9.214562e-01 9.214562e-01 4.607281e-01 -9.214562e-01 4.000000e-01 2.000000e+00 9.201671e-01 9.201671e-01 4.600835e-01 -9.201671e-01 5.000000e-01 2.000000e+00 9.185123e-01 9.185123e-01 4.592561e-01 -9.185123e-01 6.000000e-01 2.000000e+00 9.164938e-01 9.164938e-01 4.582469e-01 -9.164938e-01 7.000000e-01 2.000000e+00 9.141140e-01 9.141140e-01 4.570570e-01 -9.141140e-01 8.000000e-01 2.000000e+00 9.113758e-01 9.113758e-01 4.556879e-01 -9.113758e-01 9.000000e-01 2.000000e+00 9.082823e-01 9.082823e-01 4.541412e-01 -9.082823e-01 1.000000e+00 2.000000e+00 9.048374e-01 9.048374e-01 4.524187e-01 -9.048374e-01 1.100000e+00 2.000000e+00 9.010451e-01 9.010451e-01 4.505225e-01 -9.010451e-01 1.200000e+00 2.000000e+00 8.969098e-01 8.969098e-01 4.484549e-01 -8.969098e-01 1.300000e+00 2.000000e+00 8.924364e-01 8.924364e-01 4.462182e-01 -8.924364e-01 1.400000e+00 2.000000e+00 8.876302e-01 8.876302e-01 4.438151e-01 -8.876302e-01 1.500000e+00 2.000000e+00 8.824969e-01 8.824969e-01 4.412484e-01 -8.824969e-01 1.600000e+00 2.000000e+00 8.770424e-01 8.770424e-01 4.385212e-01 -8.770424e-01 1.700000e+00 2.000000e+00 8.712729e-01 8.712729e-01 4.356365e-01 -8.712729e-01 1.800000e+00 2.000000e+00 8.651953e-01 8.651953e-01 4.325977e-01 -8.651953e-01 1.900000e+00 2.000000e+00 8.588165e-01 8.588165e-01 4.294083e-01 -8.588165e-01 2.000000e+00 2.000000e+00 8.521438e-01 8.521438e-01 4.260719e-01 -8.521438e-01 2.100000e+00 2.000000e+00 8.451848e-01 8.451848e-01 4.225924e-01 -8.451848e-01 2.200000e+00 2.000000e+00 8.379474e-01 8.379474e-01 4.189737e-01 -8.379474e-01 2.300000e+00 2.000000e+00 8.304397e-01 8.304397e-01 4.152198e-01 -8.304397e-01 2.400000e+00 2.000000e+00 8.226701e-01 8.226701e-01 4.113351e-01 -8.226701e-01 2.500000e+00 2.000000e+00 8.146473e-01 8.146473e-01 4.073237e-01 -8.146473e-01 2.600000e+00 2.000000e+00 8.063802e-01 8.063802e-01 4.031901e-01 -8.063802e-01 2.700000e+00 2.000000e+00 7.978777e-01 7.978777e-01 3.989388e-01 -7.978777e-01 2.800000e+00 2.000000e+00 7.891491e-01 7.891491e-01 3.945746e-01 -7.891491e-01 2.900000e+00 2.000000e+00 7.802039e-01 7.802039e-01 3.901019e-01 -7.802039e-01 3.000000e+00 2.000000e+00 7.710516e-01 7.710516e-01 3.855258e-01 -7.710516e-01 3.100000e+00 2.000000e+00 7.617019e-01 7.617019e-01 3.808509e-01 -7.617019e-01 3.200000e+00 2.000000e+00 7.521647e-01 7.521647e-01 3.760823e-01 -7.521647e-01 3.300000e+00 2.000000e+00 7.424498e-01 7.424498e-01 3.712249e-01 -7.424498e-01 3.400000e+00 2.000000e+00 7.325673e-01 7.325673e-01 3.662837e-01 -7.325673e-01 3.500000e+00 2.000000e+00 7.225274e-01 7.225274e-01 3.612637e-01 -7.225274e-01 3.600000e+00 2.000000e+00 7.123400e-01 7.123400e-01 3.561700e-01 -7.123400e-01 3.700000e+00 2.000000e+00 7.020153e-01 7.020153e-01 3.510077e-01 -7.020153e-01 3.800000e+00 2.000000e+00 6.915637e-01 6.915637e-01 3.457819e-01 -6.915637e-01 3.900000e+00 2.000000e+00 6.809952e-01 6.809952e-01 3.404976e-01 -6.809952e-01 4.000000e+00 2.000000e+00 6.703200e-01 6.703200e-01 3.351600e-01 -6.703200e-01 4.100000e+00 2.000000e+00 6.595483e-01 6.595483e-01 3.297742e-01 -6.595483e-01 4.200000e+00 2.000000e+00 6.486902e-01 6.486902e-01 3.243451e-01 -6.486902e-01 4.300000e+00 2.000000e+00 6.377557e-01 6.377557e-01 3.188778e-01 -6.377557e-01 4.400000e+00 2.000000e+00 6.267547e-01 6.267547e-01 3.133774e-01 -6.267547e-01 4.500000e+00 2.000000e+00 6.156972e-01 6.156972e-01 3.078486e-01 -6.156972e-01 4.600000e+00 2.000000e+00 6.045929e-01 6.045929e-01 3.022965e-01 -6.045929e-01 4.700000e+00 2.000000e+00 5.934514e-01 5.934514e-01 2.967257e-01 -5.934514e-01 4.800000e+00 2.000000e+00 5.822822e-01 5.822822e-01 2.911411e-01 -5.822822e-01 4.900000e+00 2.000000e+00 5.710948e-01 5.710948e-01 2.855474e-01 -5.710948e-01 -5.000000e+00 2.100000e+00 5.553260e-01 5.553260e-01 2.776630e-01 -5.553260e-01 -4.900000e+00 2.100000e+00 5.664310e-01 5.664310e-01 2.832155e-01 -5.664310e-01 -4.800000e+00 2.100000e+00 5.775270e-01 5.775270e-01 2.887635e-01 -5.775270e-01 -4.700000e+00 2.100000e+00 5.886050e-01 5.886050e-01 2.943025e-01 -5.886050e-01 -4.600000e+00 2.100000e+00 5.996555e-01 5.996555e-01 2.998278e-01 -5.996555e-01 -4.500000e+00 2.100000e+00 6.106691e-01 6.106691e-01 3.053346e-01 -6.106691e-01 -4.400000e+00 2.100000e+00 6.216363e-01 6.216363e-01 3.108182e-01 -6.216363e-01 -4.300000e+00 2.100000e+00 6.325475e-01 6.325475e-01 3.162737e-01 -6.325475e-01 -4.200000e+00 2.100000e+00 6.433927e-01 6.433927e-01 3.216964e-01 -6.433927e-01 -4.100000e+00 2.100000e+00 6.541622e-01 6.541622e-01 3.270811e-01 -6.541622e-01 -4.000000e+00 2.100000e+00 6.648459e-01 6.648459e-01 3.324229e-01 -6.648459e-01 -3.900000e+00 2.100000e+00 6.754339e-01 6.754339e-01 3.377169e-01 -6.754339e-01 -3.800000e+00 2.100000e+00 6.859161e-01 6.859161e-01 3.429580e-01 -6.859161e-01 -3.700000e+00 2.100000e+00 6.962823e-01 6.962823e-01 3.481412e-01 -6.962823e-01 -3.600000e+00 2.100000e+00 7.065227e-01 7.065227e-01 3.532614e-01 -7.065227e-01 -3.500000e+00 2.100000e+00 7.166269e-01 7.166269e-01 3.583134e-01 -7.166269e-01 -3.400000e+00 2.100000e+00 7.265849e-01 7.265849e-01 3.632924e-01 -7.265849e-01 -3.300000e+00 2.100000e+00 7.363867e-01 7.363867e-01 3.681933e-01 -7.363867e-01 -3.200000e+00 2.100000e+00 7.460222e-01 7.460222e-01 3.730111e-01 -7.460222e-01 -3.100000e+00 2.100000e+00 7.554815e-01 7.554815e-01 3.777407e-01 -7.554815e-01 -3.000000e+00 2.100000e+00 7.647548e-01 7.647548e-01 3.823774e-01 -7.647548e-01 -2.900000e+00 2.100000e+00 7.738324e-01 7.738324e-01 3.869162e-01 -7.738324e-01 -2.800000e+00 2.100000e+00 7.827045e-01 7.827045e-01 3.913523e-01 -7.827045e-01 -2.700000e+00 2.100000e+00 7.913618e-01 7.913618e-01 3.956809e-01 -7.913618e-01 -2.600000e+00 2.100000e+00 7.997949e-01 7.997949e-01 3.998974e-01 -7.997949e-01 -2.500000e+00 2.100000e+00 8.079945e-01 8.079945e-01 4.039973e-01 -8.079945e-01 -2.400000e+00 2.100000e+00 8.159518e-01 8.159518e-01 4.079759e-01 -8.159518e-01 -2.300000e+00 2.100000e+00 8.236579e-01 8.236579e-01 4.118290e-01 -8.236579e-01 -2.200000e+00 2.100000e+00 8.311043e-01 8.311043e-01 4.155521e-01 -8.311043e-01 -2.100000e+00 2.100000e+00 8.382826e-01 8.382826e-01 4.191413e-01 -8.382826e-01 -2.000000e+00 2.100000e+00 8.451848e-01 8.451848e-01 4.225924e-01 -8.451848e-01 -1.900000e+00 2.100000e+00 8.518030e-01 8.518030e-01 4.259015e-01 -8.518030e-01 -1.800000e+00 2.100000e+00 8.581297e-01 8.581297e-01 4.290649e-01 -8.581297e-01 -1.700000e+00 2.100000e+00 8.641577e-01 8.641577e-01 4.320788e-01 -8.641577e-01 -1.600000e+00 2.100000e+00 8.698800e-01 8.698800e-01 4.349400e-01 -8.698800e-01 -1.500000e+00 2.100000e+00 8.752900e-01 8.752900e-01 4.376450e-01 -8.752900e-01 -1.400000e+00 2.100000e+00 8.803815e-01 8.803815e-01 4.401907e-01 -8.803815e-01 -1.300000e+00 2.100000e+00 8.851483e-01 8.851483e-01 4.425742e-01 -8.851483e-01 -1.200000e+00 2.100000e+00 8.895852e-01 8.895852e-01 4.447926e-01 -8.895852e-01 -1.100000e+00 2.100000e+00 8.936867e-01 8.936867e-01 4.468434e-01 -8.936867e-01 -1.000000e+00 2.100000e+00 8.974481e-01 8.974481e-01 4.487240e-01 -8.974481e-01 -9.000000e-01 2.100000e+00 9.008649e-01 9.008649e-01 4.504324e-01 -9.008649e-01 -8.000000e-01 2.100000e+00 9.039330e-01 9.039330e-01 4.519665e-01 -9.039330e-01 -7.000000e-01 2.100000e+00 9.066489e-01 9.066489e-01 4.533245e-01 -9.066489e-01 -6.000000e-01 2.100000e+00 9.090093e-01 9.090093e-01 4.545046e-01 -9.090093e-01 -5.000000e-01 2.100000e+00 9.110113e-01 9.110113e-01 4.555056e-01 -9.110113e-01 -4.000000e-01 2.100000e+00 9.126526e-01 9.126526e-01 4.563263e-01 -9.126526e-01 -3.000000e-01 2.100000e+00 9.139312e-01 9.139312e-01 4.569656e-01 -9.139312e-01 -2.000000e-01 2.100000e+00 9.148456e-01 9.148456e-01 4.574228e-01 -9.148456e-01 -1.000000e-01 2.100000e+00 9.153947e-01 9.153947e-01 4.576973e-01 -9.153947e-01 0.000000e+00 2.100000e+00 9.155778e-01 9.155778e-01 4.577889e-01 -9.155778e-01 1.000000e-01 2.100000e+00 9.153947e-01 9.153947e-01 4.576973e-01 -9.153947e-01 2.000000e-01 2.100000e+00 9.148456e-01 9.148456e-01 4.574228e-01 -9.148456e-01 3.000000e-01 2.100000e+00 9.139312e-01 9.139312e-01 4.569656e-01 -9.139312e-01 4.000000e-01 2.100000e+00 9.126526e-01 9.126526e-01 4.563263e-01 -9.126526e-01 5.000000e-01 2.100000e+00 9.110113e-01 9.110113e-01 4.555056e-01 -9.110113e-01 6.000000e-01 2.100000e+00 9.090093e-01 9.090093e-01 4.545046e-01 -9.090093e-01 7.000000e-01 2.100000e+00 9.066489e-01 9.066489e-01 4.533245e-01 -9.066489e-01 8.000000e-01 2.100000e+00 9.039330e-01 9.039330e-01 4.519665e-01 -9.039330e-01 9.000000e-01 2.100000e+00 9.008649e-01 9.008649e-01 4.504324e-01 -9.008649e-01 1.000000e+00 2.100000e+00 8.974481e-01 8.974481e-01 4.487240e-01 -8.974481e-01 1.100000e+00 2.100000e+00 8.936867e-01 8.936867e-01 4.468434e-01 -8.936867e-01 1.200000e+00 2.100000e+00 8.895852e-01 8.895852e-01 4.447926e-01 -8.895852e-01 1.300000e+00 2.100000e+00 8.851483e-01 8.851483e-01 4.425742e-01 -8.851483e-01 1.400000e+00 2.100000e+00 8.803815e-01 8.803815e-01 4.401907e-01 -8.803815e-01 1.500000e+00 2.100000e+00 8.752900e-01 8.752900e-01 4.376450e-01 -8.752900e-01 1.600000e+00 2.100000e+00 8.698800e-01 8.698800e-01 4.349400e-01 -8.698800e-01 1.700000e+00 2.100000e+00 8.641577e-01 8.641577e-01 4.320788e-01 -8.641577e-01 1.800000e+00 2.100000e+00 8.581297e-01 8.581297e-01 4.290649e-01 -8.581297e-01 1.900000e+00 2.100000e+00 8.518030e-01 8.518030e-01 4.259015e-01 -8.518030e-01 2.000000e+00 2.100000e+00 8.451848e-01 8.451848e-01 4.225924e-01 -8.451848e-01 2.100000e+00 2.100000e+00 8.382826e-01 8.382826e-01 4.191413e-01 -8.382826e-01 2.200000e+00 2.100000e+00 8.311043e-01 8.311043e-01 4.155521e-01 -8.311043e-01 2.300000e+00 2.100000e+00 8.236579e-01 8.236579e-01 4.118290e-01 -8.236579e-01 2.400000e+00 2.100000e+00 8.159518e-01 8.159518e-01 4.079759e-01 -8.159518e-01 2.500000e+00 2.100000e+00 8.079945e-01 8.079945e-01 4.039973e-01 -8.079945e-01 2.600000e+00 2.100000e+00 7.997949e-01 7.997949e-01 3.998974e-01 -7.997949e-01 2.700000e+00 2.100000e+00 7.913618e-01 7.913618e-01 3.956809e-01 -7.913618e-01 2.800000e+00 2.100000e+00 7.827045e-01 7.827045e-01 3.913523e-01 -7.827045e-01 2.900000e+00 2.100000e+00 7.738324e-01 7.738324e-01 3.869162e-01 -7.738324e-01 3.000000e+00 2.100000e+00 7.647548e-01 7.647548e-01 3.823774e-01 -7.647548e-01 3.100000e+00 2.100000e+00 7.554815e-01 7.554815e-01 3.777407e-01 -7.554815e-01 3.200000e+00 2.100000e+00 7.460222e-01 7.460222e-01 3.730111e-01 -7.460222e-01 3.300000e+00 2.100000e+00 7.363867e-01 7.363867e-01 3.681933e-01 -7.363867e-01 3.400000e+00 2.100000e+00 7.265849e-01 7.265849e-01 3.632924e-01 -7.265849e-01 3.500000e+00 2.100000e+00 7.166269e-01 7.166269e-01 3.583134e-01 -7.166269e-01 3.600000e+00 2.100000e+00 7.065227e-01 7.065227e-01 3.532614e-01 -7.065227e-01 3.700000e+00 2.100000e+00 6.962823e-01 6.962823e-01 3.481412e-01 -6.962823e-01 3.800000e+00 2.100000e+00 6.859161e-01 6.859161e-01 3.429580e-01 -6.859161e-01 3.900000e+00 2.100000e+00 6.754339e-01 6.754339e-01 3.377169e-01 -6.754339e-01 4.000000e+00 2.100000e+00 6.648459e-01 6.648459e-01 3.324229e-01 -6.648459e-01 4.100000e+00 2.100000e+00 6.541622e-01 6.541622e-01 3.270811e-01 -6.541622e-01 4.200000e+00 2.100000e+00 6.433927e-01 6.433927e-01 3.216964e-01 -6.433927e-01 4.300000e+00 2.100000e+00 6.325475e-01 6.325475e-01 3.162737e-01 -6.325475e-01 4.400000e+00 2.100000e+00 6.216363e-01 6.216363e-01 3.108182e-01 -6.216363e-01 4.500000e+00 2.100000e+00 6.106691e-01 6.106691e-01 3.053346e-01 -6.106691e-01 4.600000e+00 2.100000e+00 5.996555e-01 5.996555e-01 2.998278e-01 -5.996555e-01 4.700000e+00 2.100000e+00 5.886050e-01 5.886050e-01 2.943025e-01 -5.886050e-01 4.800000e+00 2.100000e+00 5.775270e-01 5.775270e-01 2.887635e-01 -5.775270e-01 4.900000e+00 2.100000e+00 5.664310e-01 5.664310e-01 2.832155e-01 -5.664310e-01 -5.000000e+00 2.200000e+00 5.505707e-01 5.505707e-01 2.752853e-01 -5.505707e-01 -4.900000e+00 2.200000e+00 5.615806e-01 5.615806e-01 2.807903e-01 -5.615806e-01 -4.800000e+00 2.200000e+00 5.725816e-01 5.725816e-01 2.862908e-01 -5.725816e-01 -4.700000e+00 2.200000e+00 5.835647e-01 5.835647e-01 2.917823e-01 -5.835647e-01 -4.600000e+00 2.200000e+00 5.945206e-01 5.945206e-01 2.972603e-01 -5.945206e-01 -4.500000e+00 2.200000e+00 6.054399e-01 6.054399e-01 3.027200e-01 -6.054399e-01 -4.400000e+00 2.200000e+00 6.163132e-01 6.163132e-01 3.081566e-01 -6.163132e-01 -4.300000e+00 2.200000e+00 6.271309e-01 6.271309e-01 3.135654e-01 -6.271309e-01 -4.200000e+00 2.200000e+00 6.378832e-01 6.378832e-01 3.189416e-01 -6.378832e-01 -4.100000e+00 2.200000e+00 6.485605e-01 6.485605e-01 3.242802e-01 -6.485605e-01 -4.000000e+00 2.200000e+00 6.591527e-01 6.591527e-01 3.295764e-01 -6.591527e-01 -3.900000e+00 2.200000e+00 6.696500e-01 6.696500e-01 3.348250e-01 -6.696500e-01 -3.800000e+00 2.200000e+00 6.800425e-01 6.800425e-01 3.400213e-01 -6.800425e-01 -3.700000e+00 2.200000e+00 6.903200e-01 6.903200e-01 3.451600e-01 -6.903200e-01 -3.600000e+00 2.200000e+00 7.004727e-01 7.004727e-01 3.502363e-01 -7.004727e-01 -3.500000e+00 2.200000e+00 7.104903e-01 7.104903e-01 3.552451e-01 -7.104903e-01 -3.400000e+00 2.200000e+00 7.203630e-01 7.203630e-01 3.601815e-01 -7.203630e-01 -3.300000e+00 2.200000e+00 7.300808e-01 7.300808e-01 3.650404e-01 -7.300808e-01 -3.200000e+00 2.200000e+00 7.396339e-01 7.396339e-01 3.698169e-01 -7.396339e-01 -3.100000e+00 2.200000e+00 7.490122e-01 7.490122e-01 3.745061e-01 -7.490122e-01 -3.000000e+00 2.200000e+00 7.582061e-01 7.582061e-01 3.791031e-01 -7.582061e-01 -2.900000e+00 2.200000e+00 7.672059e-01 7.672059e-01 3.836029e-01 -7.672059e-01 -2.800000e+00 2.200000e+00 7.760022e-01 7.760022e-01 3.880011e-01 -7.760022e-01 -2.700000e+00 2.200000e+00 7.845853e-01 7.845853e-01 3.922926e-01 -7.845853e-01 -2.600000e+00 2.200000e+00 7.929461e-01 7.929461e-01 3.964731e-01 -7.929461e-01 -2.500000e+00 2.200000e+00 8.010756e-01 8.010756e-01 4.005378e-01 -8.010756e-01 -2.400000e+00 2.200000e+00 8.089647e-01 8.089647e-01 4.044823e-01 -8.089647e-01 -2.300000e+00 2.200000e+00 8.166049e-01 8.166049e-01 4.083024e-01 -8.166049e-01 -2.200000e+00 2.200000e+00 8.239874e-01 8.239874e-01 4.119937e-01 -8.239874e-01 -2.100000e+00 2.200000e+00 8.311043e-01 8.311043e-01 4.155521e-01 -8.311043e-01 -2.000000e+00 2.200000e+00 8.379474e-01 8.379474e-01 4.189737e-01 -8.379474e-01 -1.900000e+00 2.200000e+00 8.445089e-01 8.445089e-01 4.222544e-01 -8.445089e-01 -1.800000e+00 2.200000e+00 8.507814e-01 8.507814e-01 4.253907e-01 -8.507814e-01 -1.700000e+00 2.200000e+00 8.567578e-01 8.567578e-01 4.283789e-01 -8.567578e-01 -1.600000e+00 2.200000e+00 8.624311e-01 8.624311e-01 4.312156e-01 -8.624311e-01 -1.500000e+00 2.200000e+00 8.677948e-01 8.677948e-01 4.338974e-01 -8.677948e-01 -1.400000e+00 2.200000e+00 8.728426e-01 8.728426e-01 4.364213e-01 -8.728426e-01 -1.300000e+00 2.200000e+00 8.775687e-01 8.775687e-01 4.387844e-01 -8.775687e-01 -1.200000e+00 2.200000e+00 8.819675e-01 8.819675e-01 4.409838e-01 -8.819675e-01 -1.100000e+00 2.200000e+00 8.860340e-01 8.860340e-01 4.430170e-01 -8.860340e-01 -1.000000e+00 2.200000e+00 8.897631e-01 8.897631e-01 4.448816e-01 -8.897631e-01 -9.000000e-01 2.200000e+00 8.931507e-01 8.931507e-01 4.465753e-01 -8.931507e-01 -8.000000e-01 2.200000e+00 8.961926e-01 8.961926e-01 4.480963e-01 -8.961926e-01 -7.000000e-01 2.200000e+00 8.988851e-01 8.988851e-01 4.494426e-01 -8.988851e-01 -6.000000e-01 2.200000e+00 9.012253e-01 9.012253e-01 4.506126e-01 -9.012253e-01 -5.000000e-01 2.200000e+00 9.032102e-01 9.032102e-01 4.516051e-01 -9.032102e-01 -4.000000e-01 2.200000e+00 9.048374e-01 9.048374e-01 4.524187e-01 -9.048374e-01 -3.000000e-01 2.200000e+00 9.061051e-01 9.061051e-01 4.530526e-01 -9.061051e-01 -2.000000e-01 2.200000e+00 9.070116e-01 9.070116e-01 4.535058e-01 -9.070116e-01 -1.000000e-01 2.200000e+00 9.075560e-01 9.075560e-01 4.537780e-01 -9.075560e-01 0.000000e+00 2.200000e+00 9.077376e-01 9.077376e-01 4.538688e-01 -9.077376e-01 1.000000e-01 2.200000e+00 9.075560e-01 9.075560e-01 4.537780e-01 -9.075560e-01 2.000000e-01 2.200000e+00 9.070116e-01 9.070116e-01 4.535058e-01 -9.070116e-01 3.000000e-01 2.200000e+00 9.061051e-01 9.061051e-01 4.530526e-01 -9.061051e-01 4.000000e-01 2.200000e+00 9.048374e-01 9.048374e-01 4.524187e-01 -9.048374e-01 5.000000e-01 2.200000e+00 9.032102e-01 9.032102e-01 4.516051e-01 -9.032102e-01 6.000000e-01 2.200000e+00 9.012253e-01 9.012253e-01 4.506126e-01 -9.012253e-01 7.000000e-01 2.200000e+00 8.988851e-01 8.988851e-01 4.494426e-01 -8.988851e-01 8.000000e-01 2.200000e+00 8.961926e-01 8.961926e-01 4.480963e-01 -8.961926e-01 9.000000e-01 2.200000e+00 8.931507e-01 8.931507e-01 4.465753e-01 -8.931507e-01 1.000000e+00 2.200000e+00 8.897631e-01 8.897631e-01 4.448816e-01 -8.897631e-01 1.100000e+00 2.200000e+00 8.860340e-01 8.860340e-01 4.430170e-01 -8.860340e-01 1.200000e+00 2.200000e+00 8.819675e-01 8.819675e-01 4.409838e-01 -8.819675e-01 1.300000e+00 2.200000e+00 8.775687e-01 8.775687e-01 4.387844e-01 -8.775687e-01 1.400000e+00 2.200000e+00 8.728426e-01 8.728426e-01 4.364213e-01 -8.728426e-01 1.500000e+00 2.200000e+00 8.677948e-01 8.677948e-01 4.338974e-01 -8.677948e-01 1.600000e+00 2.200000e+00 8.624311e-01 8.624311e-01 4.312156e-01 -8.624311e-01 1.700000e+00 2.200000e+00 8.567578e-01 8.567578e-01 4.283789e-01 -8.567578e-01 1.800000e+00 2.200000e+00 8.507814e-01 8.507814e-01 4.253907e-01 -8.507814e-01 1.900000e+00 2.200000e+00 8.445089e-01 8.445089e-01 4.222544e-01 -8.445089e-01 2.000000e+00 2.200000e+00 8.379474e-01 8.379474e-01 4.189737e-01 -8.379474e-01 2.100000e+00 2.200000e+00 8.311043e-01 8.311043e-01 4.155521e-01 -8.311043e-01 2.200000e+00 2.200000e+00 8.239874e-01 8.239874e-01 4.119937e-01 -8.239874e-01 2.300000e+00 2.200000e+00 8.166049e-01 8.166049e-01 4.083024e-01 -8.166049e-01 2.400000e+00 2.200000e+00 8.089647e-01 8.089647e-01 4.044823e-01 -8.089647e-01 2.500000e+00 2.200000e+00 8.010756e-01 8.010756e-01 4.005378e-01 -8.010756e-01 2.600000e+00 2.200000e+00 7.929461e-01 7.929461e-01 3.964731e-01 -7.929461e-01 2.700000e+00 2.200000e+00 7.845853e-01 7.845853e-01 3.922926e-01 -7.845853e-01 2.800000e+00 2.200000e+00 7.760022e-01 7.760022e-01 3.880011e-01 -7.760022e-01 2.900000e+00 2.200000e+00 7.672059e-01 7.672059e-01 3.836029e-01 -7.672059e-01 3.000000e+00 2.200000e+00 7.582061e-01 7.582061e-01 3.791031e-01 -7.582061e-01 3.100000e+00 2.200000e+00 7.490122e-01 7.490122e-01 3.745061e-01 -7.490122e-01 3.200000e+00 2.200000e+00 7.396339e-01 7.396339e-01 3.698169e-01 -7.396339e-01 3.300000e+00 2.200000e+00 7.300808e-01 7.300808e-01 3.650404e-01 -7.300808e-01 3.400000e+00 2.200000e+00 7.203630e-01 7.203630e-01 3.601815e-01 -7.203630e-01 3.500000e+00 2.200000e+00 7.104903e-01 7.104903e-01 3.552451e-01 -7.104903e-01 3.600000e+00 2.200000e+00 7.004727e-01 7.004727e-01 3.502363e-01 -7.004727e-01 3.700000e+00 2.200000e+00 6.903200e-01 6.903200e-01 3.451600e-01 -6.903200e-01 3.800000e+00 2.200000e+00 6.800425e-01 6.800425e-01 3.400213e-01 -6.800425e-01 3.900000e+00 2.200000e+00 6.696500e-01 6.696500e-01 3.348250e-01 -6.696500e-01 4.000000e+00 2.200000e+00 6.591527e-01 6.591527e-01 3.295764e-01 -6.591527e-01 4.100000e+00 2.200000e+00 6.485605e-01 6.485605e-01 3.242802e-01 -6.485605e-01 4.200000e+00 2.200000e+00 6.378832e-01 6.378832e-01 3.189416e-01 -6.378832e-01 4.300000e+00 2.200000e+00 6.271309e-01 6.271309e-01 3.135654e-01 -6.271309e-01 4.400000e+00 2.200000e+00 6.163132e-01 6.163132e-01 3.081566e-01 -6.163132e-01 4.500000e+00 2.200000e+00 6.054399e-01 6.054399e-01 3.027200e-01 -6.054399e-01 4.600000e+00 2.200000e+00 5.945206e-01 5.945206e-01 2.972603e-01 -5.945206e-01 4.700000e+00 2.200000e+00 5.835647e-01 5.835647e-01 2.917823e-01 -5.835647e-01 4.800000e+00 2.200000e+00 5.725816e-01 5.725816e-01 2.862908e-01 -5.725816e-01 4.900000e+00 2.200000e+00 5.615806e-01 5.615806e-01 2.807903e-01 -5.615806e-01 -5.000000e+00 2.300000e+00 5.456377e-01 5.456377e-01 2.728189e-01 -5.456377e-01 -4.900000e+00 2.300000e+00 5.565490e-01 5.565490e-01 2.782745e-01 -5.565490e-01 -4.800000e+00 2.300000e+00 5.674515e-01 5.674515e-01 2.837257e-01 -5.674515e-01 -4.700000e+00 2.300000e+00 5.783362e-01 5.783362e-01 2.891681e-01 -5.783362e-01 -4.600000e+00 2.300000e+00 5.891939e-01 5.891939e-01 2.945970e-01 -5.891939e-01 -4.500000e+00 2.300000e+00 6.000154e-01 6.000154e-01 3.000077e-01 -6.000154e-01 -4.400000e+00 2.300000e+00 6.107913e-01 6.107913e-01 3.053956e-01 -6.107913e-01 -4.300000e+00 2.300000e+00 6.215121e-01 6.215121e-01 3.107560e-01 -6.215121e-01 -4.200000e+00 2.300000e+00 6.321681e-01 6.321681e-01 3.160840e-01 -6.321681e-01 -4.100000e+00 2.300000e+00 6.427497e-01 6.427497e-01 3.213748e-01 -6.427497e-01 -4.000000e+00 2.300000e+00 6.532469e-01 6.532469e-01 3.266235e-01 -6.532469e-01 -3.900000e+00 2.300000e+00 6.636502e-01 6.636502e-01 3.318251e-01 -6.636502e-01 -3.800000e+00 2.300000e+00 6.739496e-01 6.739496e-01 3.369748e-01 -6.739496e-01 -3.700000e+00 2.300000e+00 6.841350e-01 6.841350e-01 3.420675e-01 -6.841350e-01 -3.600000e+00 2.300000e+00 6.941967e-01 6.941967e-01 3.470984e-01 -6.941967e-01 -3.500000e+00 2.300000e+00 7.041246e-01 7.041246e-01 3.520623e-01 -7.041246e-01 -3.400000e+00 2.300000e+00 7.139089e-01 7.139089e-01 3.569544e-01 -7.139089e-01 -3.300000e+00 2.300000e+00 7.235397e-01 7.235397e-01 3.617698e-01 -7.235397e-01 -3.200000e+00 2.300000e+00 7.330070e-01 7.330070e-01 3.665035e-01 -7.330070e-01 -3.100000e+00 2.300000e+00 7.423013e-01 7.423013e-01 3.711507e-01 -7.423013e-01 -3.000000e+00 2.300000e+00 7.514129e-01 7.514129e-01 3.757065e-01 -7.514129e-01 -2.900000e+00 2.300000e+00 7.603320e-01 7.603320e-01 3.801660e-01 -7.603320e-01 -2.800000e+00 2.300000e+00 7.690495e-01 7.690495e-01 3.845247e-01 -7.690495e-01 -2.700000e+00 2.300000e+00 7.775557e-01 7.775557e-01 3.887779e-01 -7.775557e-01 -2.600000e+00 2.300000e+00 7.858416e-01 7.858416e-01 3.929208e-01 -7.858416e-01 -2.500000e+00 2.300000e+00 7.938982e-01 7.938982e-01 3.969491e-01 -7.938982e-01 -2.400000e+00 2.300000e+00 8.017167e-01 8.017167e-01 4.008583e-01 -8.017167e-01 -2.300000e+00 2.300000e+00 8.092884e-01 8.092884e-01 4.046442e-01 -8.092884e-01 -2.200000e+00 2.300000e+00 8.166049e-01 8.166049e-01 4.083024e-01 -8.166049e-01 -2.100000e+00 2.300000e+00 8.236579e-01 8.236579e-01 4.118290e-01 -8.236579e-01 -2.000000e+00 2.300000e+00 8.304397e-01 8.304397e-01 4.152198e-01 -8.304397e-01 -1.900000e+00 2.300000e+00 8.369424e-01 8.369424e-01 4.184712e-01 -8.369424e-01 -1.800000e+00 2.300000e+00 8.431588e-01 8.431588e-01 4.215794e-01 -8.431588e-01 -1.700000e+00 2.300000e+00 8.490816e-01 8.490816e-01 4.245408e-01 -8.490816e-01 -1.600000e+00 2.300000e+00 8.547041e-01 8.547041e-01 4.273520e-01 -8.547041e-01 -1.500000e+00 2.300000e+00 8.600197e-01 8.600197e-01 4.300098e-01 -8.600197e-01 -1.400000e+00 2.300000e+00 8.650223e-01 8.650223e-01 4.325112e-01 -8.650223e-01 -1.300000e+00 2.300000e+00 8.697061e-01 8.697061e-01 4.348530e-01 -8.697061e-01 -1.200000e+00 2.300000e+00 8.740655e-01 8.740655e-01 4.370327e-01 -8.740655e-01 -1.100000e+00 2.300000e+00 8.780954e-01 8.780954e-01 4.390477e-01 -8.780954e-01 -1.000000e+00 2.300000e+00 8.817912e-01 8.817912e-01 4.408956e-01 -8.817912e-01 -9.000000e-01 2.300000e+00 8.851484e-01 8.851484e-01 4.425742e-01 -8.851484e-01 -8.000000e-01 2.300000e+00 8.881630e-01 8.881630e-01 4.440815e-01 -8.881630e-01 -7.000000e-01 2.300000e+00 8.908315e-01 8.908315e-01 4.454157e-01 -8.908315e-01 -6.000000e-01 2.300000e+00 8.931507e-01 8.931507e-01 4.465753e-01 -8.931507e-01 -5.000000e-01 2.300000e+00 8.951178e-01 8.951178e-01 4.475589e-01 -8.951178e-01 -4.000000e-01 2.300000e+00 8.967304e-01 8.967304e-01 4.483652e-01 -8.967304e-01 -3.000000e-01 2.300000e+00 8.979867e-01 8.979867e-01 4.489934e-01 -8.979867e-01 -2.000000e-01 2.300000e+00 8.988852e-01 8.988852e-01 4.494426e-01 -8.988852e-01 -1.000000e-01 2.300000e+00 8.994247e-01 8.994247e-01 4.497123e-01 -8.994247e-01 0.000000e+00 2.300000e+00 8.996046e-01 8.996046e-01 4.498023e-01 -8.996046e-01 1.000000e-01 2.300000e+00 8.994247e-01 8.994247e-01 4.497123e-01 -8.994247e-01 2.000000e-01 2.300000e+00 8.988852e-01 8.988852e-01 4.494426e-01 -8.988852e-01 3.000000e-01 2.300000e+00 8.979867e-01 8.979867e-01 4.489934e-01 -8.979867e-01 4.000000e-01 2.300000e+00 8.967304e-01 8.967304e-01 4.483652e-01 -8.967304e-01 5.000000e-01 2.300000e+00 8.951178e-01 8.951178e-01 4.475589e-01 -8.951178e-01 6.000000e-01 2.300000e+00 8.931507e-01 8.931507e-01 4.465753e-01 -8.931507e-01 7.000000e-01 2.300000e+00 8.908315e-01 8.908315e-01 4.454157e-01 -8.908315e-01 8.000000e-01 2.300000e+00 8.881630e-01 8.881630e-01 4.440815e-01 -8.881630e-01 9.000000e-01 2.300000e+00 8.851484e-01 8.851484e-01 4.425742e-01 -8.851484e-01 1.000000e+00 2.300000e+00 8.817912e-01 8.817912e-01 4.408956e-01 -8.817912e-01 1.100000e+00 2.300000e+00 8.780954e-01 8.780954e-01 4.390477e-01 -8.780954e-01 1.200000e+00 2.300000e+00 8.740655e-01 8.740655e-01 4.370327e-01 -8.740655e-01 1.300000e+00 2.300000e+00 8.697061e-01 8.697061e-01 4.348530e-01 -8.697061e-01 1.400000e+00 2.300000e+00 8.650223e-01 8.650223e-01 4.325112e-01 -8.650223e-01 1.500000e+00 2.300000e+00 8.600197e-01 8.600197e-01 4.300098e-01 -8.600197e-01 1.600000e+00 2.300000e+00 8.547041e-01 8.547041e-01 4.273520e-01 -8.547041e-01 1.700000e+00 2.300000e+00 8.490816e-01 8.490816e-01 4.245408e-01 -8.490816e-01 1.800000e+00 2.300000e+00 8.431588e-01 8.431588e-01 4.215794e-01 -8.431588e-01 1.900000e+00 2.300000e+00 8.369424e-01 8.369424e-01 4.184712e-01 -8.369424e-01 2.000000e+00 2.300000e+00 8.304397e-01 8.304397e-01 4.152198e-01 -8.304397e-01 2.100000e+00 2.300000e+00 8.236579e-01 8.236579e-01 4.118290e-01 -8.236579e-01 2.200000e+00 2.300000e+00 8.166049e-01 8.166049e-01 4.083024e-01 -8.166049e-01 2.300000e+00 2.300000e+00 8.092884e-01 8.092884e-01 4.046442e-01 -8.092884e-01 2.400000e+00 2.300000e+00 8.017167e-01 8.017167e-01 4.008583e-01 -8.017167e-01 2.500000e+00 2.300000e+00 7.938982e-01 7.938982e-01 3.969491e-01 -7.938982e-01 2.600000e+00 2.300000e+00 7.858416e-01 7.858416e-01 3.929208e-01 -7.858416e-01 2.700000e+00 2.300000e+00 7.775557e-01 7.775557e-01 3.887779e-01 -7.775557e-01 2.800000e+00 2.300000e+00 7.690495e-01 7.690495e-01 3.845247e-01 -7.690495e-01 2.900000e+00 2.300000e+00 7.603320e-01 7.603320e-01 3.801660e-01 -7.603320e-01 3.000000e+00 2.300000e+00 7.514129e-01 7.514129e-01 3.757065e-01 -7.514129e-01 3.100000e+00 2.300000e+00 7.423013e-01 7.423013e-01 3.711507e-01 -7.423013e-01 3.200000e+00 2.300000e+00 7.330070e-01 7.330070e-01 3.665035e-01 -7.330070e-01 3.300000e+00 2.300000e+00 7.235397e-01 7.235397e-01 3.617698e-01 -7.235397e-01 3.400000e+00 2.300000e+00 7.139089e-01 7.139089e-01 3.569544e-01 -7.139089e-01 3.500000e+00 2.300000e+00 7.041246e-01 7.041246e-01 3.520623e-01 -7.041246e-01 3.600000e+00 2.300000e+00 6.941967e-01 6.941967e-01 3.470984e-01 -6.941967e-01 3.700000e+00 2.300000e+00 6.841350e-01 6.841350e-01 3.420675e-01 -6.841350e-01 3.800000e+00 2.300000e+00 6.739496e-01 6.739496e-01 3.369748e-01 -6.739496e-01 3.900000e+00 2.300000e+00 6.636502e-01 6.636502e-01 3.318251e-01 -6.636502e-01 4.000000e+00 2.300000e+00 6.532469e-01 6.532469e-01 3.266235e-01 -6.532469e-01 4.100000e+00 2.300000e+00 6.427497e-01 6.427497e-01 3.213748e-01 -6.427497e-01 4.200000e+00 2.300000e+00 6.321681e-01 6.321681e-01 3.160840e-01 -6.321681e-01 4.300000e+00 2.300000e+00 6.215121e-01 6.215121e-01 3.107560e-01 -6.215121e-01 4.400000e+00 2.300000e+00 6.107913e-01 6.107913e-01 3.053956e-01 -6.107913e-01 4.500000e+00 2.300000e+00 6.000154e-01 6.000154e-01 3.000077e-01 -6.000154e-01 4.600000e+00 2.300000e+00 5.891939e-01 5.891939e-01 2.945970e-01 -5.891939e-01 4.700000e+00 2.300000e+00 5.783362e-01 5.783362e-01 2.891681e-01 -5.783362e-01 4.800000e+00 2.300000e+00 5.674515e-01 5.674515e-01 2.837257e-01 -5.674515e-01 4.900000e+00 2.300000e+00 5.565490e-01 5.565490e-01 2.782745e-01 -5.565490e-01 -5.000000e+00 2.400000e+00 5.405328e-01 5.405328e-01 2.702664e-01 -5.405328e-01 -4.900000e+00 2.400000e+00 5.513420e-01 5.513420e-01 2.756710e-01 -5.513420e-01 -4.800000e+00 2.400000e+00 5.621424e-01 5.621424e-01 2.810712e-01 -5.621424e-01 -4.700000e+00 2.400000e+00 5.729253e-01 5.729253e-01 2.864627e-01 -5.729253e-01 -4.600000e+00 2.400000e+00 5.836814e-01 5.836814e-01 2.918407e-01 -5.836814e-01 -4.500000e+00 2.400000e+00 5.944017e-01 5.944017e-01 2.972008e-01 -5.944017e-01 -4.400000e+00 2.400000e+00 6.050767e-01 6.050767e-01 3.025384e-01 -6.050767e-01 -4.300000e+00 2.400000e+00 6.156972e-01 6.156972e-01 3.078486e-01 -6.156972e-01 -4.200000e+00 2.400000e+00 6.262535e-01 6.262535e-01 3.131268e-01 -6.262535e-01 -4.100000e+00 2.400000e+00 6.367361e-01 6.367361e-01 3.183680e-01 -6.367361e-01 -4.000000e+00 2.400000e+00 6.471352e-01 6.471352e-01 3.235676e-01 -6.471352e-01 -3.900000e+00 2.400000e+00 6.574411e-01 6.574411e-01 3.287206e-01 -6.574411e-01 -3.800000e+00 2.400000e+00 6.676441e-01 6.676441e-01 3.338220e-01 -6.676441e-01 -3.700000e+00 2.400000e+00 6.777343e-01 6.777343e-01 3.388671e-01 -6.777343e-01 -3.600000e+00 2.400000e+00 6.877018e-01 6.877018e-01 3.438509e-01 -6.877018e-01 -3.500000e+00 2.400000e+00 6.975368e-01 6.975368e-01 3.487684e-01 -6.975368e-01 -3.400000e+00 2.400000e+00 7.072295e-01 7.072295e-01 3.536147e-01 -7.072295e-01 -3.300000e+00 2.400000e+00 7.167702e-01 7.167702e-01 3.583851e-01 -7.167702e-01 -3.200000e+00 2.400000e+00 7.261490e-01 7.261490e-01 3.630745e-01 -7.261490e-01 -3.100000e+00 2.400000e+00 7.353564e-01 7.353564e-01 3.676782e-01 -7.353564e-01 -3.000000e+00 2.400000e+00 7.443827e-01 7.443827e-01 3.721913e-01 -7.443827e-01 -2.900000e+00 2.400000e+00 7.532184e-01 7.532184e-01 3.766092e-01 -7.532184e-01 -2.800000e+00 2.400000e+00 7.618542e-01 7.618542e-01 3.809271e-01 -7.618542e-01 -2.700000e+00 2.400000e+00 7.702809e-01 7.702809e-01 3.851404e-01 -7.702809e-01 -2.600000e+00 2.400000e+00 7.784893e-01 7.784893e-01 3.892446e-01 -7.784893e-01 -2.500000e+00 2.400000e+00 7.864705e-01 7.864705e-01 3.932353e-01 -7.864705e-01 -2.400000e+00 2.400000e+00 7.942159e-01 7.942159e-01 3.971079e-01 -7.942159e-01 -2.300000e+00 2.400000e+00 8.017167e-01 8.017167e-01 4.008583e-01 -8.017167e-01 -2.200000e+00 2.400000e+00 8.089647e-01 8.089647e-01 4.044823e-01 -8.089647e-01 -2.100000e+00 2.400000e+00 8.159518e-01 8.159518e-01 4.079759e-01 -8.159518e-01 -2.000000e+00 2.400000e+00 8.226701e-01 8.226701e-01 4.113351e-01 -8.226701e-01 -1.900000e+00 2.400000e+00 8.291120e-01 8.291120e-01 4.145560e-01 -8.291120e-01 -1.800000e+00 2.400000e+00 8.352702e-01 8.352702e-01 4.176351e-01 -8.352702e-01 -1.700000e+00 2.400000e+00 8.411376e-01 8.411376e-01 4.205688e-01 -8.411376e-01 -1.600000e+00 2.400000e+00 8.467075e-01 8.467075e-01 4.233537e-01 -8.467075e-01 -1.500000e+00 2.400000e+00 8.519734e-01 8.519734e-01 4.259867e-01 -8.519734e-01 -1.400000e+00 2.400000e+00 8.569292e-01 8.569292e-01 4.284646e-01 -8.569292e-01 -1.300000e+00 2.400000e+00 8.615691e-01 8.615691e-01 4.307846e-01 -8.615691e-01 -1.200000e+00 2.400000e+00 8.658878e-01 8.658878e-01 4.329439e-01 -8.658878e-01 -1.100000e+00 2.400000e+00 8.698800e-01 8.698800e-01 4.349400e-01 -8.698800e-01 -1.000000e+00 2.400000e+00 8.735412e-01 8.735412e-01 4.367706e-01 -8.735412e-01 -9.000000e-01 2.400000e+00 8.768669e-01 8.768669e-01 4.384335e-01 -8.768669e-01 -8.000000e-01 2.400000e+00 8.798534e-01 8.798534e-01 4.399267e-01 -8.798534e-01 -7.000000e-01 2.400000e+00 8.824969e-01 8.824969e-01 4.412484e-01 -8.824969e-01 -6.000000e-01 2.400000e+00 8.847944e-01 8.847944e-01 4.423972e-01 -8.847944e-01 -5.000000e-01 2.400000e+00 8.867431e-01 8.867431e-01 4.433715e-01 -8.867431e-01 -4.000000e-01 2.400000e+00 8.883407e-01 8.883407e-01 4.441703e-01 -8.883407e-01 -3.000000e-01 2.400000e+00 8.895852e-01 8.895852e-01 4.447926e-01 -8.895852e-01 -2.000000e-01 2.400000e+00 8.904752e-01 8.904752e-01 4.452376e-01 -8.904752e-01 -1.000000e-01 2.400000e+00 8.910097e-01 8.910097e-01 4.455048e-01 -8.910097e-01 0.000000e+00 2.400000e+00 8.911879e-01 8.911879e-01 4.455940e-01 -8.911879e-01 1.000000e-01 2.400000e+00 8.910097e-01 8.910097e-01 4.455048e-01 -8.910097e-01 2.000000e-01 2.400000e+00 8.904752e-01 8.904752e-01 4.452376e-01 -8.904752e-01 3.000000e-01 2.400000e+00 8.895852e-01 8.895852e-01 4.447926e-01 -8.895852e-01 4.000000e-01 2.400000e+00 8.883407e-01 8.883407e-01 4.441703e-01 -8.883407e-01 5.000000e-01 2.400000e+00 8.867431e-01 8.867431e-01 4.433715e-01 -8.867431e-01 6.000000e-01 2.400000e+00 8.847944e-01 8.847944e-01 4.423972e-01 -8.847944e-01 7.000000e-01 2.400000e+00 8.824969e-01 8.824969e-01 4.412484e-01 -8.824969e-01 8.000000e-01 2.400000e+00 8.798534e-01 8.798534e-01 4.399267e-01 -8.798534e-01 9.000000e-01 2.400000e+00 8.768669e-01 8.768669e-01 4.384335e-01 -8.768669e-01 1.000000e+00 2.400000e+00 8.735412e-01 8.735412e-01 4.367706e-01 -8.735412e-01 1.100000e+00 2.400000e+00 8.698800e-01 8.698800e-01 4.349400e-01 -8.698800e-01 1.200000e+00 2.400000e+00 8.658878e-01 8.658878e-01 4.329439e-01 -8.658878e-01 1.300000e+00 2.400000e+00 8.615691e-01 8.615691e-01 4.307846e-01 -8.615691e-01 1.400000e+00 2.400000e+00 8.569292e-01 8.569292e-01 4.284646e-01 -8.569292e-01 1.500000e+00 2.400000e+00 8.519734e-01 8.519734e-01 4.259867e-01 -8.519734e-01 1.600000e+00 2.400000e+00 8.467075e-01 8.467075e-01 4.233537e-01 -8.467075e-01 1.700000e+00 2.400000e+00 8.411376e-01 8.411376e-01 4.205688e-01 -8.411376e-01 1.800000e+00 2.400000e+00 8.352702e-01 8.352702e-01 4.176351e-01 -8.352702e-01 1.900000e+00 2.400000e+00 8.291120e-01 8.291120e-01 4.145560e-01 -8.291120e-01 2.000000e+00 2.400000e+00 8.226701e-01 8.226701e-01 4.113351e-01 -8.226701e-01 2.100000e+00 2.400000e+00 8.159518e-01 8.159518e-01 4.079759e-01 -8.159518e-01 2.200000e+00 2.400000e+00 8.089647e-01 8.089647e-01 4.044823e-01 -8.089647e-01 2.300000e+00 2.400000e+00 8.017167e-01 8.017167e-01 4.008583e-01 -8.017167e-01 2.400000e+00 2.400000e+00 7.942159e-01 7.942159e-01 3.971079e-01 -7.942159e-01 2.500000e+00 2.400000e+00 7.864705e-01 7.864705e-01 3.932353e-01 -7.864705e-01 2.600000e+00 2.400000e+00 7.784893e-01 7.784893e-01 3.892446e-01 -7.784893e-01 2.700000e+00 2.400000e+00 7.702809e-01 7.702809e-01 3.851404e-01 -7.702809e-01 2.800000e+00 2.400000e+00 7.618542e-01 7.618542e-01 3.809271e-01 -7.618542e-01 2.900000e+00 2.400000e+00 7.532184e-01 7.532184e-01 3.766092e-01 -7.532184e-01 3.000000e+00 2.400000e+00 7.443827e-01 7.443827e-01 3.721913e-01 -7.443827e-01 3.100000e+00 2.400000e+00 7.353564e-01 7.353564e-01 3.676782e-01 -7.353564e-01 3.200000e+00 2.400000e+00 7.261490e-01 7.261490e-01 3.630745e-01 -7.261490e-01 3.300000e+00 2.400000e+00 7.167702e-01 7.167702e-01 3.583851e-01 -7.167702e-01 3.400000e+00 2.400000e+00 7.072295e-01 7.072295e-01 3.536147e-01 -7.072295e-01 3.500000e+00 2.400000e+00 6.975368e-01 6.975368e-01 3.487684e-01 -6.975368e-01 3.600000e+00 2.400000e+00 6.877018e-01 6.877018e-01 3.438509e-01 -6.877018e-01 3.700000e+00 2.400000e+00 6.777343e-01 6.777343e-01 3.388671e-01 -6.777343e-01 3.800000e+00 2.400000e+00 6.676441e-01 6.676441e-01 3.338220e-01 -6.676441e-01 3.900000e+00 2.400000e+00 6.574411e-01 6.574411e-01 3.287206e-01 -6.574411e-01 4.000000e+00 2.400000e+00 6.471352e-01 6.471352e-01 3.235676e-01 -6.471352e-01 4.100000e+00 2.400000e+00 6.367361e-01 6.367361e-01 3.183680e-01 -6.367361e-01 4.200000e+00 2.400000e+00 6.262535e-01 6.262535e-01 3.131268e-01 -6.262535e-01 4.300000e+00 2.400000e+00 6.156972e-01 6.156972e-01 3.078486e-01 -6.156972e-01 4.400000e+00 2.400000e+00 6.050767e-01 6.050767e-01 3.025384e-01 -6.050767e-01 4.500000e+00 2.400000e+00 5.944017e-01 5.944017e-01 2.972008e-01 -5.944017e-01 4.600000e+00 2.400000e+00 5.836814e-01 5.836814e-01 2.918407e-01 -5.836814e-01 4.700000e+00 2.400000e+00 5.729253e-01 5.729253e-01 2.864627e-01 -5.729253e-01 4.800000e+00 2.400000e+00 5.621424e-01 5.621424e-01 2.810712e-01 -5.621424e-01 4.900000e+00 2.400000e+00 5.513420e-01 5.513420e-01 2.756710e-01 -5.513420e-01 -5.000000e+00 2.500000e+00 5.352615e-01 5.352615e-01 2.676307e-01 -5.352615e-01 -4.900000e+00 2.500000e+00 5.459652e-01 5.459652e-01 2.729826e-01 -5.459652e-01 -4.800000e+00 2.500000e+00 5.566604e-01 5.566604e-01 2.783302e-01 -5.566604e-01 -4.700000e+00 2.500000e+00 5.673380e-01 5.673380e-01 2.836690e-01 -5.673380e-01 -4.600000e+00 2.500000e+00 5.779893e-01 5.779893e-01 2.889946e-01 -5.779893e-01 -4.500000e+00 2.500000e+00 5.886050e-01 5.886050e-01 2.943025e-01 -5.886050e-01 -4.400000e+00 2.500000e+00 5.991759e-01 5.991759e-01 2.995880e-01 -5.991759e-01 -4.300000e+00 2.500000e+00 6.096928e-01 6.096928e-01 3.048464e-01 -6.096928e-01 -4.200000e+00 2.500000e+00 6.201462e-01 6.201462e-01 3.100731e-01 -6.201462e-01 -4.100000e+00 2.500000e+00 6.305265e-01 6.305265e-01 3.152633e-01 -6.305265e-01 -4.000000e+00 2.500000e+00 6.408243e-01 6.408243e-01 3.204121e-01 -6.408243e-01 -3.900000e+00 2.500000e+00 6.510297e-01 6.510297e-01 3.255149e-01 -6.510297e-01 -3.800000e+00 2.500000e+00 6.611332e-01 6.611332e-01 3.305666e-01 -6.611332e-01 -3.700000e+00 2.500000e+00 6.711249e-01 6.711249e-01 3.355624e-01 -6.711249e-01 -3.600000e+00 2.500000e+00 6.809952e-01 6.809952e-01 3.404976e-01 -6.809952e-01 -3.500000e+00 2.500000e+00 6.907343e-01 6.907343e-01 3.453672e-01 -6.907343e-01 -3.400000e+00 2.500000e+00 7.003325e-01 7.003325e-01 3.501663e-01 -7.003325e-01 -3.300000e+00 2.500000e+00 7.097802e-01 7.097802e-01 3.548901e-01 -7.097802e-01 -3.200000e+00 2.500000e+00 7.190675e-01 7.190675e-01 3.595338e-01 -7.190675e-01 -3.100000e+00 2.500000e+00 7.281851e-01 7.281851e-01 3.640926e-01 -7.281851e-01 -3.000000e+00 2.500000e+00 7.371234e-01 7.371234e-01 3.685617e-01 -7.371234e-01 -2.900000e+00 2.500000e+00 7.458729e-01 7.458729e-01 3.729365e-01 -7.458729e-01 -2.800000e+00 2.500000e+00 7.544246e-01 7.544246e-01 3.772123e-01 -7.544246e-01 -2.700000e+00 2.500000e+00 7.627690e-01 7.627690e-01 3.813845e-01 -7.627690e-01 -2.600000e+00 2.500000e+00 7.708974e-01 7.708974e-01 3.854487e-01 -7.708974e-01 -2.500000e+00 2.500000e+00 7.788008e-01 7.788008e-01 3.894004e-01 -7.788008e-01 -2.400000e+00 2.500000e+00 7.864705e-01 7.864705e-01 3.932353e-01 -7.864705e-01 -2.300000e+00 2.500000e+00 7.938982e-01 7.938982e-01 3.969491e-01 -7.938982e-01 -2.200000e+00 2.500000e+00 8.010756e-01 8.010756e-01 4.005378e-01 -8.010756e-01 -2.100000e+00 2.500000e+00 8.079945e-01 8.079945e-01 4.039973e-01 -8.079945e-01 -2.000000e+00 2.500000e+00 8.146473e-01 8.146473e-01 4.073237e-01 -8.146473e-01 -1.900000e+00 2.500000e+00 8.210264e-01 8.210264e-01 4.105132e-01 -8.210264e-01 -1.800000e+00 2.500000e+00 8.271245e-01 8.271245e-01 4.135623e-01 -8.271245e-01 -1.700000e+00 2.500000e+00 8.329347e-01 8.329347e-01 4.164674e-01 -8.329347e-01 -1.600000e+00 2.500000e+00 8.384503e-01 8.384503e-01 4.192251e-01 -8.384503e-01 -1.500000e+00 2.500000e+00 8.436648e-01 8.436648e-01 4.218324e-01 -8.436648e-01 -1.400000e+00 2.500000e+00 8.485723e-01 8.485723e-01 4.242861e-01 -8.485723e-01 -1.300000e+00 2.500000e+00 8.531670e-01 8.531670e-01 4.265835e-01 -8.531670e-01 -1.200000e+00 2.500000e+00 8.574435e-01 8.574435e-01 4.287218e-01 -8.574435e-01 -1.100000e+00 2.500000e+00 8.613968e-01 8.613968e-01 4.306984e-01 -8.613968e-01 -1.000000e+00 2.500000e+00 8.650223e-01 8.650223e-01 4.325112e-01 -8.650223e-01 -9.000000e-01 2.500000e+00 8.683156e-01 8.683156e-01 4.341578e-01 -8.683156e-01 -8.000000e-01 2.500000e+00 8.712729e-01 8.712729e-01 4.356365e-01 -8.712729e-01 -7.000000e-01 2.500000e+00 8.738907e-01 8.738907e-01 4.369453e-01 -8.738907e-01 -6.000000e-01 2.500000e+00 8.761657e-01 8.761657e-01 4.380829e-01 -8.761657e-01 -5.000000e-01 2.500000e+00 8.780954e-01 8.780954e-01 4.390477e-01 -8.780954e-01 -4.000000e-01 2.500000e+00 8.796774e-01 8.796774e-01 4.398387e-01 -8.796774e-01 -3.000000e-01 2.500000e+00 8.809099e-01 8.809099e-01 4.404549e-01 -8.809099e-01 -2.000000e-01 2.500000e+00 8.817912e-01 8.817912e-01 4.408956e-01 -8.817912e-01 -1.000000e-01 2.500000e+00 8.823204e-01 8.823204e-01 4.411602e-01 -8.823204e-01 0.000000e+00 2.500000e+00 8.824969e-01 8.824969e-01 4.412484e-01 -8.824969e-01 1.000000e-01 2.500000e+00 8.823204e-01 8.823204e-01 4.411602e-01 -8.823204e-01 2.000000e-01 2.500000e+00 8.817912e-01 8.817912e-01 4.408956e-01 -8.817912e-01 3.000000e-01 2.500000e+00 8.809099e-01 8.809099e-01 4.404549e-01 -8.809099e-01 4.000000e-01 2.500000e+00 8.796774e-01 8.796774e-01 4.398387e-01 -8.796774e-01 5.000000e-01 2.500000e+00 8.780954e-01 8.780954e-01 4.390477e-01 -8.780954e-01 6.000000e-01 2.500000e+00 8.761657e-01 8.761657e-01 4.380829e-01 -8.761657e-01 7.000000e-01 2.500000e+00 8.738907e-01 8.738907e-01 4.369453e-01 -8.738907e-01 8.000000e-01 2.500000e+00 8.712729e-01 8.712729e-01 4.356365e-01 -8.712729e-01 9.000000e-01 2.500000e+00 8.683156e-01 8.683156e-01 4.341578e-01 -8.683156e-01 1.000000e+00 2.500000e+00 8.650223e-01 8.650223e-01 4.325112e-01 -8.650223e-01 1.100000e+00 2.500000e+00 8.613968e-01 8.613968e-01 4.306984e-01 -8.613968e-01 1.200000e+00 2.500000e+00 8.574435e-01 8.574435e-01 4.287218e-01 -8.574435e-01 1.300000e+00 2.500000e+00 8.531670e-01 8.531670e-01 4.265835e-01 -8.531670e-01 1.400000e+00 2.500000e+00 8.485723e-01 8.485723e-01 4.242861e-01 -8.485723e-01 1.500000e+00 2.500000e+00 8.436648e-01 8.436648e-01 4.218324e-01 -8.436648e-01 1.600000e+00 2.500000e+00 8.384503e-01 8.384503e-01 4.192251e-01 -8.384503e-01 1.700000e+00 2.500000e+00 8.329347e-01 8.329347e-01 4.164674e-01 -8.329347e-01 1.800000e+00 2.500000e+00 8.271245e-01 8.271245e-01 4.135623e-01 -8.271245e-01 1.900000e+00 2.500000e+00 8.210264e-01 8.210264e-01 4.105132e-01 -8.210264e-01 2.000000e+00 2.500000e+00 8.146473e-01 8.146473e-01 4.073237e-01 -8.146473e-01 2.100000e+00 2.500000e+00 8.079945e-01 8.079945e-01 4.039973e-01 -8.079945e-01 2.200000e+00 2.500000e+00 8.010756e-01 8.010756e-01 4.005378e-01 -8.010756e-01 2.300000e+00 2.500000e+00 7.938982e-01 7.938982e-01 3.969491e-01 -7.938982e-01 2.400000e+00 2.500000e+00 7.864705e-01 7.864705e-01 3.932353e-01 -7.864705e-01 2.500000e+00 2.500000e+00 7.788008e-01 7.788008e-01 3.894004e-01 -7.788008e-01 2.600000e+00 2.500000e+00 7.708974e-01 7.708974e-01 3.854487e-01 -7.708974e-01 2.700000e+00 2.500000e+00 7.627690e-01 7.627690e-01 3.813845e-01 -7.627690e-01 2.800000e+00 2.500000e+00 7.544246e-01 7.544246e-01 3.772123e-01 -7.544246e-01 2.900000e+00 2.500000e+00 7.458729e-01 7.458729e-01 3.729365e-01 -7.458729e-01 3.000000e+00 2.500000e+00 7.371234e-01 7.371234e-01 3.685617e-01 -7.371234e-01 3.100000e+00 2.500000e+00 7.281851e-01 7.281851e-01 3.640926e-01 -7.281851e-01 3.200000e+00 2.500000e+00 7.190675e-01 7.190675e-01 3.595338e-01 -7.190675e-01 3.300000e+00 2.500000e+00 7.097802e-01 7.097802e-01 3.548901e-01 -7.097802e-01 3.400000e+00 2.500000e+00 7.003325e-01 7.003325e-01 3.501663e-01 -7.003325e-01 3.500000e+00 2.500000e+00 6.907343e-01 6.907343e-01 3.453672e-01 -6.907343e-01 3.600000e+00 2.500000e+00 6.809952e-01 6.809952e-01 3.404976e-01 -6.809952e-01 3.700000e+00 2.500000e+00 6.711249e-01 6.711249e-01 3.355624e-01 -6.711249e-01 3.800000e+00 2.500000e+00 6.611332e-01 6.611332e-01 3.305666e-01 -6.611332e-01 3.900000e+00 2.500000e+00 6.510297e-01 6.510297e-01 3.255149e-01 -6.510297e-01 4.000000e+00 2.500000e+00 6.408243e-01 6.408243e-01 3.204121e-01 -6.408243e-01 4.100000e+00 2.500000e+00 6.305265e-01 6.305265e-01 3.152633e-01 -6.305265e-01 4.200000e+00 2.500000e+00 6.201462e-01 6.201462e-01 3.100731e-01 -6.201462e-01 4.300000e+00 2.500000e+00 6.096928e-01 6.096928e-01 3.048464e-01 -6.096928e-01 4.400000e+00 2.500000e+00 5.991759e-01 5.991759e-01 2.995880e-01 -5.991759e-01 4.500000e+00 2.500000e+00 5.886050e-01 5.886050e-01 2.943025e-01 -5.886050e-01 4.600000e+00 2.500000e+00 5.779893e-01 5.779893e-01 2.889946e-01 -5.779893e-01 4.700000e+00 2.500000e+00 5.673380e-01 5.673380e-01 2.836690e-01 -5.673380e-01 4.800000e+00 2.500000e+00 5.566604e-01 5.566604e-01 2.783302e-01 -5.566604e-01 4.900000e+00 2.500000e+00 5.459652e-01 5.459652e-01 2.729826e-01 -5.459652e-01 -5.000000e+00 2.600000e+00 5.298295e-01 5.298295e-01 2.649148e-01 -5.298295e-01 -4.900000e+00 2.600000e+00 5.404246e-01 5.404246e-01 2.702123e-01 -5.404246e-01 -4.800000e+00 2.600000e+00 5.510113e-01 5.510113e-01 2.755056e-01 -5.510113e-01 -4.700000e+00 2.600000e+00 5.615807e-01 5.615807e-01 2.807903e-01 -5.615807e-01 -4.600000e+00 2.600000e+00 5.721238e-01 5.721238e-01 2.860619e-01 -5.721238e-01 -4.500000e+00 2.600000e+00 5.826317e-01 5.826317e-01 2.913159e-01 -5.826317e-01 -4.400000e+00 2.600000e+00 5.930954e-01 5.930954e-01 2.965477e-01 -5.930954e-01 -4.300000e+00 2.600000e+00 6.035056e-01 6.035056e-01 3.017528e-01 -6.035056e-01 -4.200000e+00 2.600000e+00 6.138529e-01 6.138529e-01 3.069264e-01 -6.138529e-01 -4.100000e+00 2.600000e+00 6.241279e-01 6.241279e-01 3.120639e-01 -6.241279e-01 -4.000000e+00 2.600000e+00 6.343211e-01 6.343211e-01 3.171605e-01 -6.343211e-01 -3.900000e+00 2.600000e+00 6.444229e-01 6.444229e-01 3.222115e-01 -6.444229e-01 -3.800000e+00 2.600000e+00 6.544239e-01 6.544239e-01 3.272119e-01 -6.544239e-01 -3.700000e+00 2.600000e+00 6.643142e-01 6.643142e-01 3.321571e-01 -6.643142e-01 -3.600000e+00 2.600000e+00 6.740844e-01 6.740844e-01 3.370422e-01 -6.740844e-01 -3.500000e+00 2.600000e+00 6.837247e-01 6.837247e-01 3.418624e-01 -6.837247e-01 -3.400000e+00 2.600000e+00 6.932254e-01 6.932254e-01 3.466127e-01 -6.932254e-01 -3.300000e+00 2.600000e+00 7.025772e-01 7.025772e-01 3.512886e-01 -7.025772e-01 -3.200000e+00 2.600000e+00 7.117704e-01 7.117704e-01 3.558852e-01 -7.117704e-01 -3.100000e+00 2.600000e+00 7.207954e-01 7.207954e-01 3.603977e-01 -7.207954e-01 -3.000000e+00 2.600000e+00 7.296429e-01 7.296429e-01 3.648215e-01 -7.296429e-01 -2.900000e+00 2.600000e+00 7.383037e-01 7.383037e-01 3.691518e-01 -7.383037e-01 -2.800000e+00 2.600000e+00 7.467685e-01 7.467685e-01 3.733843e-01 -7.467685e-01 -2.700000e+00 2.600000e+00 7.550283e-01 7.550283e-01 3.775142e-01 -7.550283e-01 -2.600000e+00 2.600000e+00 7.630742e-01 7.630742e-01 3.815371e-01 -7.630742e-01 -2.500000e+00 2.600000e+00 7.708974e-01 7.708974e-01 3.854487e-01 -7.708974e-01 -2.400000e+00 2.600000e+00 7.784893e-01 7.784893e-01 3.892446e-01 -7.784893e-01 -2.300000e+00 2.600000e+00 7.858416e-01 7.858416e-01 3.929208e-01 -7.858416e-01 -2.200000e+00 2.600000e+00 7.929461e-01 7.929461e-01 3.964731e-01 -7.929461e-01 -2.100000e+00 2.600000e+00 7.997949e-01 7.997949e-01 3.998974e-01 -7.997949e-01 -2.000000e+00 2.600000e+00 8.063802e-01 8.063802e-01 4.031901e-01 -8.063802e-01 -1.900000e+00 2.600000e+00 8.126945e-01 8.126945e-01 4.063472e-01 -8.126945e-01 -1.800000e+00 2.600000e+00 8.187308e-01 8.187308e-01 4.093654e-01 -8.187308e-01 -1.700000e+00 2.600000e+00 8.244820e-01 8.244820e-01 4.122410e-01 -8.244820e-01 -1.600000e+00 2.600000e+00 8.299416e-01 8.299416e-01 4.149708e-01 -8.299416e-01 -1.500000e+00 2.600000e+00 8.351032e-01 8.351032e-01 4.175516e-01 -8.351032e-01 -1.400000e+00 2.600000e+00 8.399609e-01 8.399609e-01 4.199804e-01 -8.399609e-01 -1.300000e+00 2.600000e+00 8.445089e-01 8.445089e-01 4.222544e-01 -8.445089e-01 -1.200000e+00 2.600000e+00 8.487420e-01 8.487420e-01 4.243710e-01 -8.487420e-01 -1.100000e+00 2.600000e+00 8.526552e-01 8.526552e-01 4.263276e-01 -8.526552e-01 -1.000000e+00 2.600000e+00 8.562439e-01 8.562439e-01 4.281220e-01 -8.562439e-01 -9.000000e-01 2.600000e+00 8.595038e-01 8.595038e-01 4.297519e-01 -8.595038e-01 -8.000000e-01 2.600000e+00 8.624311e-01 8.624311e-01 4.312156e-01 -8.624311e-01 -7.000000e-01 2.600000e+00 8.650223e-01 8.650223e-01 4.325112e-01 -8.650223e-01 -6.000000e-01 2.600000e+00 8.672743e-01 8.672743e-01 4.336371e-01 -8.672743e-01 -5.000000e-01 2.600000e+00 8.691844e-01 8.691844e-01 4.345922e-01 -8.691844e-01 -4.000000e-01 2.600000e+00 8.707503e-01 8.707503e-01 4.353752e-01 -8.707503e-01 -3.000000e-01 2.600000e+00 8.719702e-01 8.719702e-01 4.359851e-01 -8.719702e-01 -2.000000e-01 2.600000e+00 8.728426e-01 8.728426e-01 4.364213e-01 -8.728426e-01 -1.000000e-01 2.600000e+00 8.733665e-01 8.733665e-01 4.366832e-01 -8.733665e-01 0.000000e+00 2.600000e+00 8.735412e-01 8.735412e-01 4.367706e-01 -8.735412e-01 1.000000e-01 2.600000e+00 8.733665e-01 8.733665e-01 4.366832e-01 -8.733665e-01 2.000000e-01 2.600000e+00 8.728426e-01 8.728426e-01 4.364213e-01 -8.728426e-01 3.000000e-01 2.600000e+00 8.719702e-01 8.719702e-01 4.359851e-01 -8.719702e-01 4.000000e-01 2.600000e+00 8.707503e-01 8.707503e-01 4.353752e-01 -8.707503e-01 5.000000e-01 2.600000e+00 8.691844e-01 8.691844e-01 4.345922e-01 -8.691844e-01 6.000000e-01 2.600000e+00 8.672743e-01 8.672743e-01 4.336371e-01 -8.672743e-01 7.000000e-01 2.600000e+00 8.650223e-01 8.650223e-01 4.325112e-01 -8.650223e-01 8.000000e-01 2.600000e+00 8.624311e-01 8.624311e-01 4.312156e-01 -8.624311e-01 9.000000e-01 2.600000e+00 8.595038e-01 8.595038e-01 4.297519e-01 -8.595038e-01 1.000000e+00 2.600000e+00 8.562439e-01 8.562439e-01 4.281220e-01 -8.562439e-01 1.100000e+00 2.600000e+00 8.526552e-01 8.526552e-01 4.263276e-01 -8.526552e-01 1.200000e+00 2.600000e+00 8.487420e-01 8.487420e-01 4.243710e-01 -8.487420e-01 1.300000e+00 2.600000e+00 8.445089e-01 8.445089e-01 4.222544e-01 -8.445089e-01 1.400000e+00 2.600000e+00 8.399609e-01 8.399609e-01 4.199804e-01 -8.399609e-01 1.500000e+00 2.600000e+00 8.351032e-01 8.351032e-01 4.175516e-01 -8.351032e-01 1.600000e+00 2.600000e+00 8.299416e-01 8.299416e-01 4.149708e-01 -8.299416e-01 1.700000e+00 2.600000e+00 8.244820e-01 8.244820e-01 4.122410e-01 -8.244820e-01 1.800000e+00 2.600000e+00 8.187308e-01 8.187308e-01 4.093654e-01 -8.187308e-01 1.900000e+00 2.600000e+00 8.126945e-01 8.126945e-01 4.063472e-01 -8.126945e-01 2.000000e+00 2.600000e+00 8.063802e-01 8.063802e-01 4.031901e-01 -8.063802e-01 2.100000e+00 2.600000e+00 7.997949e-01 7.997949e-01 3.998974e-01 -7.997949e-01 2.200000e+00 2.600000e+00 7.929461e-01 7.929461e-01 3.964731e-01 -7.929461e-01 2.300000e+00 2.600000e+00 7.858416e-01 7.858416e-01 3.929208e-01 -7.858416e-01 2.400000e+00 2.600000e+00 7.784893e-01 7.784893e-01 3.892446e-01 -7.784893e-01 2.500000e+00 2.600000e+00 7.708974e-01 7.708974e-01 3.854487e-01 -7.708974e-01 2.600000e+00 2.600000e+00 7.630742e-01 7.630742e-01 3.815371e-01 -7.630742e-01 2.700000e+00 2.600000e+00 7.550283e-01 7.550283e-01 3.775142e-01 -7.550283e-01 2.800000e+00 2.600000e+00 7.467685e-01 7.467685e-01 3.733843e-01 -7.467685e-01 2.900000e+00 2.600000e+00 7.383037e-01 7.383037e-01 3.691518e-01 -7.383037e-01 3.000000e+00 2.600000e+00 7.296429e-01 7.296429e-01 3.648215e-01 -7.296429e-01 3.100000e+00 2.600000e+00 7.207954e-01 7.207954e-01 3.603977e-01 -7.207954e-01 3.200000e+00 2.600000e+00 7.117704e-01 7.117704e-01 3.558852e-01 -7.117704e-01 3.300000e+00 2.600000e+00 7.025772e-01 7.025772e-01 3.512886e-01 -7.025772e-01 3.400000e+00 2.600000e+00 6.932254e-01 6.932254e-01 3.466127e-01 -6.932254e-01 3.500000e+00 2.600000e+00 6.837247e-01 6.837247e-01 3.418624e-01 -6.837247e-01 3.600000e+00 2.600000e+00 6.740844e-01 6.740844e-01 3.370422e-01 -6.740844e-01 3.700000e+00 2.600000e+00 6.643142e-01 6.643142e-01 3.321571e-01 -6.643142e-01 3.800000e+00 2.600000e+00 6.544239e-01 6.544239e-01 3.272119e-01 -6.544239e-01 3.900000e+00 2.600000e+00 6.444229e-01 6.444229e-01 3.222115e-01 -6.444229e-01 4.000000e+00 2.600000e+00 6.343211e-01 6.343211e-01 3.171605e-01 -6.343211e-01 4.100000e+00 2.600000e+00 6.241279e-01 6.241279e-01 3.120639e-01 -6.241279e-01 4.200000e+00 2.600000e+00 6.138529e-01 6.138529e-01 3.069264e-01 -6.138529e-01 4.300000e+00 2.600000e+00 6.035056e-01 6.035056e-01 3.017528e-01 -6.035056e-01 4.400000e+00 2.600000e+00 5.930954e-01 5.930954e-01 2.965477e-01 -5.930954e-01 4.500000e+00 2.600000e+00 5.826317e-01 5.826317e-01 2.913159e-01 -5.826317e-01 4.600000e+00 2.600000e+00 5.721238e-01 5.721238e-01 2.860619e-01 -5.721238e-01 4.700000e+00 2.600000e+00 5.615807e-01 5.615807e-01 2.807903e-01 -5.615807e-01 4.800000e+00 2.600000e+00 5.510113e-01 5.510113e-01 2.755056e-01 -5.510113e-01 4.900000e+00 2.600000e+00 5.404246e-01 5.404246e-01 2.702123e-01 -5.404246e-01 -5.000000e+00 2.700000e+00 5.242430e-01 5.242430e-01 2.621215e-01 -5.242430e-01 -4.900000e+00 2.700000e+00 5.347264e-01 5.347264e-01 2.673632e-01 -5.347264e-01 -4.800000e+00 2.700000e+00 5.452014e-01 5.452014e-01 2.726007e-01 -5.452014e-01 -4.700000e+00 2.700000e+00 5.556593e-01 5.556593e-01 2.778296e-01 -5.556593e-01 -4.600000e+00 2.700000e+00 5.660913e-01 5.660913e-01 2.830456e-01 -5.660913e-01 -4.500000e+00 2.700000e+00 5.764884e-01 5.764884e-01 2.882442e-01 -5.764884e-01 -4.400000e+00 2.700000e+00 5.868418e-01 5.868418e-01 2.934209e-01 -5.868418e-01 -4.300000e+00 2.700000e+00 5.971422e-01 5.971422e-01 2.985711e-01 -5.971422e-01 -4.200000e+00 2.700000e+00 6.073804e-01 6.073804e-01 3.036902e-01 -6.073804e-01 -4.100000e+00 2.700000e+00 6.175471e-01 6.175471e-01 3.087735e-01 -6.175471e-01 -4.000000e+00 2.700000e+00 6.276328e-01 6.276328e-01 3.138164e-01 -6.276328e-01 -3.900000e+00 2.700000e+00 6.376281e-01 6.376281e-01 3.188141e-01 -6.376281e-01 -3.800000e+00 2.700000e+00 6.475236e-01 6.475236e-01 3.237618e-01 -6.475236e-01 -3.700000e+00 2.700000e+00 6.573097e-01 6.573097e-01 3.286549e-01 -6.573097e-01 -3.600000e+00 2.700000e+00 6.669768e-01 6.669768e-01 3.334884e-01 -6.669768e-01 -3.500000e+00 2.700000e+00 6.765155e-01 6.765155e-01 3.382577e-01 -6.765155e-01 -3.400000e+00 2.700000e+00 6.859161e-01 6.859161e-01 3.429580e-01 -6.859161e-01 -3.300000e+00 2.700000e+00 6.951692e-01 6.951692e-01 3.475846e-01 -6.951692e-01 -3.200000e+00 2.700000e+00 7.042654e-01 7.042654e-01 3.521327e-01 -7.042654e-01 -3.100000e+00 2.700000e+00 7.131953e-01 7.131953e-01 3.565976e-01 -7.131953e-01 -3.000000e+00 2.700000e+00 7.219496e-01 7.219496e-01 3.609748e-01 -7.219496e-01 -2.900000e+00 2.700000e+00 7.305190e-01 7.305190e-01 3.652595e-01 -7.305190e-01 -2.800000e+00 2.700000e+00 7.388946e-01 7.388946e-01 3.694473e-01 -7.388946e-01 -2.700000e+00 2.700000e+00 7.470673e-01 7.470673e-01 3.735336e-01 -7.470673e-01 -2.600000e+00 2.700000e+00 7.550283e-01 7.550283e-01 3.775142e-01 -7.550283e-01 -2.500000e+00 2.700000e+00 7.627690e-01 7.627690e-01 3.813845e-01 -7.627690e-01 -2.400000e+00 2.700000e+00 7.702809e-01 7.702809e-01 3.851404e-01 -7.702809e-01 -2.300000e+00 2.700000e+00 7.775557e-01 7.775557e-01 3.887779e-01 -7.775557e-01 -2.200000e+00 2.700000e+00 7.845853e-01 7.845853e-01 3.922926e-01 -7.845853e-01 -2.100000e+00 2.700000e+00 7.913618e-01 7.913618e-01 3.956809e-01 -7.913618e-01 -2.000000e+00 2.700000e+00 7.978777e-01 7.978777e-01 3.989388e-01 -7.978777e-01 -1.900000e+00 2.700000e+00 8.041254e-01 8.041254e-01 4.020627e-01 -8.041254e-01 -1.800000e+00 2.700000e+00 8.100981e-01 8.100981e-01 4.050490e-01 -8.100981e-01 -1.700000e+00 2.700000e+00 8.157886e-01 8.157886e-01 4.078943e-01 -8.157886e-01 -1.600000e+00 2.700000e+00 8.211906e-01 8.211906e-01 4.105953e-01 -8.211906e-01 -1.500000e+00 2.700000e+00 8.262978e-01 8.262978e-01 4.131489e-01 -8.262978e-01 -1.400000e+00 2.700000e+00 8.311043e-01 8.311043e-01 4.155521e-01 -8.311043e-01 -1.300000e+00 2.700000e+00 8.356044e-01 8.356044e-01 4.178022e-01 -8.356044e-01 -1.200000e+00 2.700000e+00 8.397928e-01 8.397928e-01 4.198964e-01 -8.397928e-01 -1.100000e+00 2.700000e+00 8.436648e-01 8.436648e-01 4.218324e-01 -8.436648e-01 -1.000000e+00 2.700000e+00 8.472157e-01 8.472157e-01 4.236078e-01 -8.472157e-01 -9.000000e-01 2.700000e+00 8.504412e-01 8.504412e-01 4.252206e-01 -8.504412e-01 -8.000000e-01 2.700000e+00 8.533376e-01 8.533376e-01 4.266688e-01 -8.533376e-01 -7.000000e-01 2.700000e+00 8.559015e-01 8.559015e-01 4.279507e-01 -8.559015e-01 -6.000000e-01 2.700000e+00 8.581297e-01 8.581297e-01 4.290649e-01 -8.581297e-01 -5.000000e-01 2.700000e+00 8.600197e-01 8.600197e-01 4.300098e-01 -8.600197e-01 -4.000000e-01 2.700000e+00 8.615691e-01 8.615691e-01 4.307846e-01 -8.615691e-01 -3.000000e-01 2.700000e+00 8.627762e-01 8.627762e-01 4.313881e-01 -8.627762e-01 -2.000000e-01 2.700000e+00 8.636394e-01 8.636394e-01 4.318197e-01 -8.636394e-01 -1.000000e-01 2.700000e+00 8.641577e-01 8.641577e-01 4.320788e-01 -8.641577e-01 0.000000e+00 2.700000e+00 8.643305e-01 8.643305e-01 4.321653e-01 -8.643305e-01 1.000000e-01 2.700000e+00 8.641577e-01 8.641577e-01 4.320788e-01 -8.641577e-01 2.000000e-01 2.700000e+00 8.636394e-01 8.636394e-01 4.318197e-01 -8.636394e-01 3.000000e-01 2.700000e+00 8.627762e-01 8.627762e-01 4.313881e-01 -8.627762e-01 4.000000e-01 2.700000e+00 8.615691e-01 8.615691e-01 4.307846e-01 -8.615691e-01 5.000000e-01 2.700000e+00 8.600197e-01 8.600197e-01 4.300098e-01 -8.600197e-01 6.000000e-01 2.700000e+00 8.581297e-01 8.581297e-01 4.290649e-01 -8.581297e-01 7.000000e-01 2.700000e+00 8.559015e-01 8.559015e-01 4.279507e-01 -8.559015e-01 8.000000e-01 2.700000e+00 8.533376e-01 8.533376e-01 4.266688e-01 -8.533376e-01 9.000000e-01 2.700000e+00 8.504412e-01 8.504412e-01 4.252206e-01 -8.504412e-01 1.000000e+00 2.700000e+00 8.472157e-01 8.472157e-01 4.236078e-01 -8.472157e-01 1.100000e+00 2.700000e+00 8.436648e-01 8.436648e-01 4.218324e-01 -8.436648e-01 1.200000e+00 2.700000e+00 8.397928e-01 8.397928e-01 4.198964e-01 -8.397928e-01 1.300000e+00 2.700000e+00 8.356044e-01 8.356044e-01 4.178022e-01 -8.356044e-01 1.400000e+00 2.700000e+00 8.311043e-01 8.311043e-01 4.155521e-01 -8.311043e-01 1.500000e+00 2.700000e+00 8.262978e-01 8.262978e-01 4.131489e-01 -8.262978e-01 1.600000e+00 2.700000e+00 8.211906e-01 8.211906e-01 4.105953e-01 -8.211906e-01 1.700000e+00 2.700000e+00 8.157886e-01 8.157886e-01 4.078943e-01 -8.157886e-01 1.800000e+00 2.700000e+00 8.100981e-01 8.100981e-01 4.050490e-01 -8.100981e-01 1.900000e+00 2.700000e+00 8.041254e-01 8.041254e-01 4.020627e-01 -8.041254e-01 2.000000e+00 2.700000e+00 7.978777e-01 7.978777e-01 3.989388e-01 -7.978777e-01 2.100000e+00 2.700000e+00 7.913618e-01 7.913618e-01 3.956809e-01 -7.913618e-01 2.200000e+00 2.700000e+00 7.845853e-01 7.845853e-01 3.922926e-01 -7.845853e-01 2.300000e+00 2.700000e+00 7.775557e-01 7.775557e-01 3.887779e-01 -7.775557e-01 2.400000e+00 2.700000e+00 7.702809e-01 7.702809e-01 3.851404e-01 -7.702809e-01 2.500000e+00 2.700000e+00 7.627690e-01 7.627690e-01 3.813845e-01 -7.627690e-01 2.600000e+00 2.700000e+00 7.550283e-01 7.550283e-01 3.775142e-01 -7.550283e-01 2.700000e+00 2.700000e+00 7.470673e-01 7.470673e-01 3.735336e-01 -7.470673e-01 2.800000e+00 2.700000e+00 7.388946e-01 7.388946e-01 3.694473e-01 -7.388946e-01 2.900000e+00 2.700000e+00 7.305190e-01 7.305190e-01 3.652595e-01 -7.305190e-01 3.000000e+00 2.700000e+00 7.219496e-01 7.219496e-01 3.609748e-01 -7.219496e-01 3.100000e+00 2.700000e+00 7.131953e-01 7.131953e-01 3.565976e-01 -7.131953e-01 3.200000e+00 2.700000e+00 7.042654e-01 7.042654e-01 3.521327e-01 -7.042654e-01 3.300000e+00 2.700000e+00 6.951692e-01 6.951692e-01 3.475846e-01 -6.951692e-01 3.400000e+00 2.700000e+00 6.859161e-01 6.859161e-01 3.429580e-01 -6.859161e-01 3.500000e+00 2.700000e+00 6.765155e-01 6.765155e-01 3.382577e-01 -6.765155e-01 3.600000e+00 2.700000e+00 6.669768e-01 6.669768e-01 3.334884e-01 -6.669768e-01 3.700000e+00 2.700000e+00 6.573097e-01 6.573097e-01 3.286549e-01 -6.573097e-01 3.800000e+00 2.700000e+00 6.475236e-01 6.475236e-01 3.237618e-01 -6.475236e-01 3.900000e+00 2.700000e+00 6.376281e-01 6.376281e-01 3.188141e-01 -6.376281e-01 4.000000e+00 2.700000e+00 6.276328e-01 6.276328e-01 3.138164e-01 -6.276328e-01 4.100000e+00 2.700000e+00 6.175471e-01 6.175471e-01 3.087735e-01 -6.175471e-01 4.200000e+00 2.700000e+00 6.073804e-01 6.073804e-01 3.036902e-01 -6.073804e-01 4.300000e+00 2.700000e+00 5.971422e-01 5.971422e-01 2.985711e-01 -5.971422e-01 4.400000e+00 2.700000e+00 5.868418e-01 5.868418e-01 2.934209e-01 -5.868418e-01 4.500000e+00 2.700000e+00 5.764884e-01 5.764884e-01 2.882442e-01 -5.764884e-01 4.600000e+00 2.700000e+00 5.660913e-01 5.660913e-01 2.830456e-01 -5.660913e-01 4.700000e+00 2.700000e+00 5.556593e-01 5.556593e-01 2.778296e-01 -5.556593e-01 4.800000e+00 2.700000e+00 5.452014e-01 5.452014e-01 2.726007e-01 -5.452014e-01 4.900000e+00 2.700000e+00 5.347264e-01 5.347264e-01 2.673632e-01 -5.347264e-01 -5.000000e+00 2.800000e+00 5.185079e-01 5.185079e-01 2.592539e-01 -5.185079e-01 -4.900000e+00 2.800000e+00 5.288767e-01 5.288767e-01 2.644383e-01 -5.288767e-01 -4.800000e+00 2.800000e+00 5.392370e-01 5.392370e-01 2.696185e-01 -5.392370e-01 -4.700000e+00 2.800000e+00 5.495806e-01 5.495806e-01 2.747903e-01 -5.495806e-01 -4.600000e+00 2.800000e+00 5.598984e-01 5.598984e-01 2.799492e-01 -5.598984e-01 -4.500000e+00 2.800000e+00 5.701818e-01 5.701818e-01 2.850909e-01 -5.701818e-01 -4.400000e+00 2.800000e+00 5.804219e-01 5.804219e-01 2.902110e-01 -5.804219e-01 -4.300000e+00 2.800000e+00 5.906096e-01 5.906096e-01 2.953048e-01 -5.906096e-01 -4.200000e+00 2.800000e+00 6.007358e-01 6.007358e-01 3.003679e-01 -6.007358e-01 -4.100000e+00 2.800000e+00 6.107913e-01 6.107913e-01 3.053956e-01 -6.107913e-01 -4.000000e+00 2.800000e+00 6.207666e-01 6.207666e-01 3.103833e-01 -6.207666e-01 -3.900000e+00 2.800000e+00 6.306527e-01 6.306527e-01 3.153263e-01 -6.306527e-01 -3.800000e+00 2.800000e+00 6.404399e-01 6.404399e-01 3.202199e-01 -6.404399e-01 -3.700000e+00 2.800000e+00 6.501189e-01 6.501189e-01 3.250594e-01 -6.501189e-01 -3.600000e+00 2.800000e+00 6.596803e-01 6.596803e-01 3.298402e-01 -6.596803e-01 -3.500000e+00 2.800000e+00 6.691146e-01 6.691146e-01 3.345573e-01 -6.691146e-01 -3.400000e+00 2.800000e+00 6.784123e-01 6.784123e-01 3.392062e-01 -6.784123e-01 -3.300000e+00 2.800000e+00 6.875643e-01 6.875643e-01 3.437821e-01 -6.875643e-01 -3.200000e+00 2.800000e+00 6.965610e-01 6.965610e-01 3.482805e-01 -6.965610e-01 -3.100000e+00 2.800000e+00 7.053931e-01 7.053931e-01 3.526966e-01 -7.053931e-01 -3.000000e+00 2.800000e+00 7.140516e-01 7.140516e-01 3.570258e-01 -7.140516e-01 -2.900000e+00 2.800000e+00 7.225273e-01 7.225273e-01 3.612637e-01 -7.225273e-01 -2.800000e+00 2.800000e+00 7.308113e-01 7.308113e-01 3.654056e-01 -7.308113e-01 -2.700000e+00 2.800000e+00 7.388946e-01 7.388946e-01 3.694473e-01 -7.388946e-01 -2.600000e+00 2.800000e+00 7.467685e-01 7.467685e-01 3.733843e-01 -7.467685e-01 -2.500000e+00 2.800000e+00 7.544246e-01 7.544246e-01 3.772123e-01 -7.544246e-01 -2.400000e+00 2.800000e+00 7.618542e-01 7.618542e-01 3.809271e-01 -7.618542e-01 -2.300000e+00 2.800000e+00 7.690495e-01 7.690495e-01 3.845247e-01 -7.690495e-01 -2.200000e+00 2.800000e+00 7.760022e-01 7.760022e-01 3.880011e-01 -7.760022e-01 -2.100000e+00 2.800000e+00 7.827045e-01 7.827045e-01 3.913523e-01 -7.827045e-01 -2.000000e+00 2.800000e+00 7.891491e-01 7.891491e-01 3.945746e-01 -7.891491e-01 -1.900000e+00 2.800000e+00 7.953286e-01 7.953286e-01 3.976643e-01 -7.953286e-01 -1.800000e+00 2.800000e+00 8.012358e-01 8.012358e-01 4.006179e-01 -8.012358e-01 -1.700000e+00 2.800000e+00 8.068641e-01 8.068641e-01 4.034321e-01 -8.068641e-01 -1.600000e+00 2.800000e+00 8.122070e-01 8.122070e-01 4.061035e-01 -8.122070e-01 -1.500000e+00 2.800000e+00 8.172584e-01 8.172584e-01 4.086292e-01 -8.172584e-01 -1.400000e+00 2.800000e+00 8.220122e-01 8.220122e-01 4.110061e-01 -8.220122e-01 -1.300000e+00 2.800000e+00 8.264631e-01 8.264631e-01 4.132316e-01 -8.264631e-01 -1.200000e+00 2.800000e+00 8.306057e-01 8.306057e-01 4.153029e-01 -8.306057e-01 -1.100000e+00 2.800000e+00 8.344353e-01 8.344353e-01 4.172177e-01 -8.344353e-01 -1.000000e+00 2.800000e+00 8.379474e-01 8.379474e-01 4.189737e-01 -8.379474e-01 -9.000000e-01 2.800000e+00 8.411376e-01 8.411376e-01 4.205688e-01 -8.411376e-01 -8.000000e-01 2.800000e+00 8.440024e-01 8.440024e-01 4.220012e-01 -8.440024e-01 -7.000000e-01 2.800000e+00 8.465381e-01 8.465381e-01 4.232691e-01 -8.465381e-01 -6.000000e-01 2.800000e+00 8.487420e-01 8.487420e-01 4.243710e-01 -8.487420e-01 -5.000000e-01 2.800000e+00 8.506113e-01 8.506113e-01 4.253057e-01 -8.506113e-01 -4.000000e-01 2.800000e+00 8.521438e-01 8.521438e-01 4.260719e-01 -8.521438e-01 -3.000000e-01 2.800000e+00 8.533376e-01 8.533376e-01 4.266688e-01 -8.533376e-01 -2.000000e-01 2.800000e+00 8.541914e-01 8.541914e-01 4.270957e-01 -8.541914e-01 -1.000000e-01 2.800000e+00 8.547041e-01 8.547041e-01 4.273520e-01 -8.547041e-01 0.000000e+00 2.800000e+00 8.548750e-01 8.548750e-01 4.274375e-01 -8.548750e-01 1.000000e-01 2.800000e+00 8.547041e-01 8.547041e-01 4.273520e-01 -8.547041e-01 2.000000e-01 2.800000e+00 8.541914e-01 8.541914e-01 4.270957e-01 -8.541914e-01 3.000000e-01 2.800000e+00 8.533376e-01 8.533376e-01 4.266688e-01 -8.533376e-01 4.000000e-01 2.800000e+00 8.521438e-01 8.521438e-01 4.260719e-01 -8.521438e-01 5.000000e-01 2.800000e+00 8.506113e-01 8.506113e-01 4.253057e-01 -8.506113e-01 6.000000e-01 2.800000e+00 8.487420e-01 8.487420e-01 4.243710e-01 -8.487420e-01 7.000000e-01 2.800000e+00 8.465381e-01 8.465381e-01 4.232691e-01 -8.465381e-01 8.000000e-01 2.800000e+00 8.440024e-01 8.440024e-01 4.220012e-01 -8.440024e-01 9.000000e-01 2.800000e+00 8.411376e-01 8.411376e-01 4.205688e-01 -8.411376e-01 1.000000e+00 2.800000e+00 8.379474e-01 8.379474e-01 4.189737e-01 -8.379474e-01 1.100000e+00 2.800000e+00 8.344353e-01 8.344353e-01 4.172177e-01 -8.344353e-01 1.200000e+00 2.800000e+00 8.306057e-01 8.306057e-01 4.153029e-01 -8.306057e-01 1.300000e+00 2.800000e+00 8.264631e-01 8.264631e-01 4.132316e-01 -8.264631e-01 1.400000e+00 2.800000e+00 8.220122e-01 8.220122e-01 4.110061e-01 -8.220122e-01 1.500000e+00 2.800000e+00 8.172584e-01 8.172584e-01 4.086292e-01 -8.172584e-01 1.600000e+00 2.800000e+00 8.122070e-01 8.122070e-01 4.061035e-01 -8.122070e-01 1.700000e+00 2.800000e+00 8.068641e-01 8.068641e-01 4.034321e-01 -8.068641e-01 1.800000e+00 2.800000e+00 8.012358e-01 8.012358e-01 4.006179e-01 -8.012358e-01 1.900000e+00 2.800000e+00 7.953286e-01 7.953286e-01 3.976643e-01 -7.953286e-01 2.000000e+00 2.800000e+00 7.891491e-01 7.891491e-01 3.945746e-01 -7.891491e-01 2.100000e+00 2.800000e+00 7.827045e-01 7.827045e-01 3.913523e-01 -7.827045e-01 2.200000e+00 2.800000e+00 7.760022e-01 7.760022e-01 3.880011e-01 -7.760022e-01 2.300000e+00 2.800000e+00 7.690495e-01 7.690495e-01 3.845247e-01 -7.690495e-01 2.400000e+00 2.800000e+00 7.618542e-01 7.618542e-01 3.809271e-01 -7.618542e-01 2.500000e+00 2.800000e+00 7.544246e-01 7.544246e-01 3.772123e-01 -7.544246e-01 2.600000e+00 2.800000e+00 7.467685e-01 7.467685e-01 3.733843e-01 -7.467685e-01 2.700000e+00 2.800000e+00 7.388946e-01 7.388946e-01 3.694473e-01 -7.388946e-01 2.800000e+00 2.800000e+00 7.308113e-01 7.308113e-01 3.654056e-01 -7.308113e-01 2.900000e+00 2.800000e+00 7.225273e-01 7.225273e-01 3.612637e-01 -7.225273e-01 3.000000e+00 2.800000e+00 7.140516e-01 7.140516e-01 3.570258e-01 -7.140516e-01 3.100000e+00 2.800000e+00 7.053931e-01 7.053931e-01 3.526966e-01 -7.053931e-01 3.200000e+00 2.800000e+00 6.965610e-01 6.965610e-01 3.482805e-01 -6.965610e-01 3.300000e+00 2.800000e+00 6.875643e-01 6.875643e-01 3.437821e-01 -6.875643e-01 3.400000e+00 2.800000e+00 6.784123e-01 6.784123e-01 3.392062e-01 -6.784123e-01 3.500000e+00 2.800000e+00 6.691146e-01 6.691146e-01 3.345573e-01 -6.691146e-01 3.600000e+00 2.800000e+00 6.596803e-01 6.596803e-01 3.298402e-01 -6.596803e-01 3.700000e+00 2.800000e+00 6.501189e-01 6.501189e-01 3.250594e-01 -6.501189e-01 3.800000e+00 2.800000e+00 6.404399e-01 6.404399e-01 3.202199e-01 -6.404399e-01 3.900000e+00 2.800000e+00 6.306527e-01 6.306527e-01 3.153263e-01 -6.306527e-01 4.000000e+00 2.800000e+00 6.207666e-01 6.207666e-01 3.103833e-01 -6.207666e-01 4.100000e+00 2.800000e+00 6.107913e-01 6.107913e-01 3.053956e-01 -6.107913e-01 4.200000e+00 2.800000e+00 6.007358e-01 6.007358e-01 3.003679e-01 -6.007358e-01 4.300000e+00 2.800000e+00 5.906096e-01 5.906096e-01 2.953048e-01 -5.906096e-01 4.400000e+00 2.800000e+00 5.804219e-01 5.804219e-01 2.902110e-01 -5.804219e-01 4.500000e+00 2.800000e+00 5.701818e-01 5.701818e-01 2.850909e-01 -5.701818e-01 4.600000e+00 2.800000e+00 5.598984e-01 5.598984e-01 2.799492e-01 -5.598984e-01 4.700000e+00 2.800000e+00 5.495806e-01 5.495806e-01 2.747903e-01 -5.495806e-01 4.800000e+00 2.800000e+00 5.392370e-01 5.392370e-01 2.696185e-01 -5.392370e-01 4.900000e+00 2.800000e+00 5.288767e-01 5.288767e-01 2.644383e-01 -5.288767e-01 -5.000000e+00 2.900000e+00 5.126305e-01 5.126305e-01 2.563152e-01 -5.126305e-01 -4.900000e+00 2.900000e+00 5.228817e-01 5.228817e-01 2.614408e-01 -5.228817e-01 -4.800000e+00 2.900000e+00 5.331246e-01 5.331246e-01 2.665623e-01 -5.331246e-01 -4.700000e+00 2.900000e+00 5.433509e-01 5.433509e-01 2.716754e-01 -5.433509e-01 -4.600000e+00 2.900000e+00 5.535518e-01 5.535518e-01 2.767759e-01 -5.535518e-01 -4.500000e+00 2.900000e+00 5.637187e-01 5.637187e-01 2.818593e-01 -5.637187e-01 -4.400000e+00 2.900000e+00 5.738426e-01 5.738426e-01 2.869213e-01 -5.738426e-01 -4.300000e+00 2.900000e+00 5.839149e-01 5.839149e-01 2.919574e-01 -5.839149e-01 -4.200000e+00 2.900000e+00 5.939263e-01 5.939263e-01 2.969632e-01 -5.939263e-01 -4.100000e+00 2.900000e+00 6.038678e-01 6.038678e-01 3.019339e-01 -6.038678e-01 -4.000000e+00 2.900000e+00 6.137301e-01 6.137301e-01 3.068650e-01 -6.137301e-01 -3.900000e+00 2.900000e+00 6.235040e-01 6.235040e-01 3.117520e-01 -6.235040e-01 -3.800000e+00 2.900000e+00 6.331803e-01 6.331803e-01 3.165902e-01 -6.331803e-01 -3.700000e+00 2.900000e+00 6.427496e-01 6.427496e-01 3.213748e-01 -6.427496e-01 -3.600000e+00 2.900000e+00 6.522026e-01 6.522026e-01 3.261013e-01 -6.522026e-01 -3.500000e+00 2.900000e+00 6.615300e-01 6.615300e-01 3.307650e-01 -6.615300e-01 -3.400000e+00 2.900000e+00 6.707223e-01 6.707223e-01 3.353612e-01 -6.707223e-01 -3.300000e+00 2.900000e+00 6.797705e-01 6.797705e-01 3.398853e-01 -6.797705e-01 -3.200000e+00 2.900000e+00 6.886652e-01 6.886652e-01 3.443326e-01 -6.886652e-01 -3.100000e+00 2.900000e+00 6.973973e-01 6.973973e-01 3.486986e-01 -6.973973e-01 -3.000000e+00 2.900000e+00 7.059577e-01 7.059577e-01 3.529788e-01 -7.059577e-01 -2.900000e+00 2.900000e+00 7.143373e-01 7.143373e-01 3.571686e-01 -7.143373e-01 -2.800000e+00 2.900000e+00 7.225273e-01 7.225273e-01 3.612637e-01 -7.225273e-01 -2.700000e+00 2.900000e+00 7.305190e-01 7.305190e-01 3.652595e-01 -7.305190e-01 -2.600000e+00 2.900000e+00 7.383037e-01 7.383037e-01 3.691518e-01 -7.383037e-01 -2.500000e+00 2.900000e+00 7.458729e-01 7.458729e-01 3.729365e-01 -7.458729e-01 -2.400000e+00 2.900000e+00 7.532184e-01 7.532184e-01 3.766092e-01 -7.532184e-01 -2.300000e+00 2.900000e+00 7.603320e-01 7.603320e-01 3.801660e-01 -7.603320e-01 -2.200000e+00 2.900000e+00 7.672059e-01 7.672059e-01 3.836029e-01 -7.672059e-01 -2.100000e+00 2.900000e+00 7.738324e-01 7.738324e-01 3.869162e-01 -7.738324e-01 -2.000000e+00 2.900000e+00 7.802039e-01 7.802039e-01 3.901019e-01 -7.802039e-01 -1.900000e+00 2.900000e+00 7.863132e-01 7.863132e-01 3.931566e-01 -7.863132e-01 -1.800000e+00 2.900000e+00 7.921535e-01 7.921535e-01 3.960768e-01 -7.921535e-01 -1.700000e+00 2.900000e+00 7.977180e-01 7.977180e-01 3.988590e-01 -7.977180e-01 -1.600000e+00 2.900000e+00 8.030005e-01 8.030005e-01 4.015002e-01 -8.030005e-01 -1.500000e+00 2.900000e+00 8.079945e-01 8.079945e-01 4.039972e-01 -8.079945e-01 -1.400000e+00 2.900000e+00 8.126945e-01 8.126945e-01 4.063472e-01 -8.126945e-01 -1.300000e+00 2.900000e+00 8.170949e-01 8.170949e-01 4.085475e-01 -8.170949e-01 -1.200000e+00 2.900000e+00 8.211906e-01 8.211906e-01 4.105953e-01 -8.211906e-01 -1.100000e+00 2.900000e+00 8.249768e-01 8.249768e-01 4.124884e-01 -8.249768e-01 -1.000000e+00 2.900000e+00 8.284490e-01 8.284490e-01 4.142245e-01 -8.284490e-01 -9.000000e-01 2.900000e+00 8.316031e-01 8.316031e-01 4.158015e-01 -8.316031e-01 -8.000000e-01 2.900000e+00 8.344353e-01 8.344353e-01 4.172177e-01 -8.344353e-01 -7.000000e-01 2.900000e+00 8.369424e-01 8.369424e-01 4.184712e-01 -8.369424e-01 -6.000000e-01 2.900000e+00 8.391213e-01 8.391213e-01 4.195606e-01 -8.391213e-01 -5.000000e-01 2.900000e+00 8.409694e-01 8.409694e-01 4.204847e-01 -8.409694e-01 -4.000000e-01 2.900000e+00 8.424845e-01 8.424845e-01 4.212422e-01 -8.424845e-01 -3.000000e-01 2.900000e+00 8.436648e-01 8.436648e-01 4.218324e-01 -8.436648e-01 -2.000000e-01 2.900000e+00 8.445089e-01 8.445089e-01 4.222544e-01 -8.445089e-01 -1.000000e-01 2.900000e+00 8.450157e-01 8.450157e-01 4.225079e-01 -8.450157e-01 0.000000e+00 2.900000e+00 8.451847e-01 8.451847e-01 4.225924e-01 -8.451847e-01 1.000000e-01 2.900000e+00 8.450157e-01 8.450157e-01 4.225079e-01 -8.450157e-01 2.000000e-01 2.900000e+00 8.445089e-01 8.445089e-01 4.222544e-01 -8.445089e-01 3.000000e-01 2.900000e+00 8.436648e-01 8.436648e-01 4.218324e-01 -8.436648e-01 4.000000e-01 2.900000e+00 8.424845e-01 8.424845e-01 4.212422e-01 -8.424845e-01 5.000000e-01 2.900000e+00 8.409694e-01 8.409694e-01 4.204847e-01 -8.409694e-01 6.000000e-01 2.900000e+00 8.391213e-01 8.391213e-01 4.195606e-01 -8.391213e-01 7.000000e-01 2.900000e+00 8.369424e-01 8.369424e-01 4.184712e-01 -8.369424e-01 8.000000e-01 2.900000e+00 8.344353e-01 8.344353e-01 4.172177e-01 -8.344353e-01 9.000000e-01 2.900000e+00 8.316031e-01 8.316031e-01 4.158015e-01 -8.316031e-01 1.000000e+00 2.900000e+00 8.284490e-01 8.284490e-01 4.142245e-01 -8.284490e-01 1.100000e+00 2.900000e+00 8.249768e-01 8.249768e-01 4.124884e-01 -8.249768e-01 1.200000e+00 2.900000e+00 8.211906e-01 8.211906e-01 4.105953e-01 -8.211906e-01 1.300000e+00 2.900000e+00 8.170949e-01 8.170949e-01 4.085475e-01 -8.170949e-01 1.400000e+00 2.900000e+00 8.126945e-01 8.126945e-01 4.063472e-01 -8.126945e-01 1.500000e+00 2.900000e+00 8.079945e-01 8.079945e-01 4.039972e-01 -8.079945e-01 1.600000e+00 2.900000e+00 8.030005e-01 8.030005e-01 4.015002e-01 -8.030005e-01 1.700000e+00 2.900000e+00 7.977180e-01 7.977180e-01 3.988590e-01 -7.977180e-01 1.800000e+00 2.900000e+00 7.921535e-01 7.921535e-01 3.960768e-01 -7.921535e-01 1.900000e+00 2.900000e+00 7.863132e-01 7.863132e-01 3.931566e-01 -7.863132e-01 2.000000e+00 2.900000e+00 7.802039e-01 7.802039e-01 3.901019e-01 -7.802039e-01 2.100000e+00 2.900000e+00 7.738324e-01 7.738324e-01 3.869162e-01 -7.738324e-01 2.200000e+00 2.900000e+00 7.672059e-01 7.672059e-01 3.836029e-01 -7.672059e-01 2.300000e+00 2.900000e+00 7.603320e-01 7.603320e-01 3.801660e-01 -7.603320e-01 2.400000e+00 2.900000e+00 7.532184e-01 7.532184e-01 3.766092e-01 -7.532184e-01 2.500000e+00 2.900000e+00 7.458729e-01 7.458729e-01 3.729365e-01 -7.458729e-01 2.600000e+00 2.900000e+00 7.383037e-01 7.383037e-01 3.691518e-01 -7.383037e-01 2.700000e+00 2.900000e+00 7.305190e-01 7.305190e-01 3.652595e-01 -7.305190e-01 2.800000e+00 2.900000e+00 7.225273e-01 7.225273e-01 3.612637e-01 -7.225273e-01 2.900000e+00 2.900000e+00 7.143373e-01 7.143373e-01 3.571686e-01 -7.143373e-01 3.000000e+00 2.900000e+00 7.059577e-01 7.059577e-01 3.529788e-01 -7.059577e-01 3.100000e+00 2.900000e+00 6.973973e-01 6.973973e-01 3.486986e-01 -6.973973e-01 3.200000e+00 2.900000e+00 6.886652e-01 6.886652e-01 3.443326e-01 -6.886652e-01 3.300000e+00 2.900000e+00 6.797705e-01 6.797705e-01 3.398853e-01 -6.797705e-01 3.400000e+00 2.900000e+00 6.707223e-01 6.707223e-01 3.353612e-01 -6.707223e-01 3.500000e+00 2.900000e+00 6.615300e-01 6.615300e-01 3.307650e-01 -6.615300e-01 3.600000e+00 2.900000e+00 6.522026e-01 6.522026e-01 3.261013e-01 -6.522026e-01 3.700000e+00 2.900000e+00 6.427496e-01 6.427496e-01 3.213748e-01 -6.427496e-01 3.800000e+00 2.900000e+00 6.331803e-01 6.331803e-01 3.165902e-01 -6.331803e-01 3.900000e+00 2.900000e+00 6.235040e-01 6.235040e-01 3.117520e-01 -6.235040e-01 4.000000e+00 2.900000e+00 6.137301e-01 6.137301e-01 3.068650e-01 -6.137301e-01 4.100000e+00 2.900000e+00 6.038678e-01 6.038678e-01 3.019339e-01 -6.038678e-01 4.200000e+00 2.900000e+00 5.939263e-01 5.939263e-01 2.969632e-01 -5.939263e-01 4.300000e+00 2.900000e+00 5.839149e-01 5.839149e-01 2.919574e-01 -5.839149e-01 4.400000e+00 2.900000e+00 5.738426e-01 5.738426e-01 2.869213e-01 -5.738426e-01 4.500000e+00 2.900000e+00 5.637187e-01 5.637187e-01 2.818593e-01 -5.637187e-01 4.600000e+00 2.900000e+00 5.535518e-01 5.535518e-01 2.767759e-01 -5.535518e-01 4.700000e+00 2.900000e+00 5.433509e-01 5.433509e-01 2.716754e-01 -5.433509e-01 4.800000e+00 2.900000e+00 5.331246e-01 5.331246e-01 2.665623e-01 -5.331246e-01 4.900000e+00 2.900000e+00 5.228817e-01 5.228817e-01 2.614408e-01 -5.228817e-01 -5.000000e+00 3.000000e+00 5.066170e-01 5.066170e-01 2.533085e-01 -5.066170e-01 -4.900000e+00 3.000000e+00 5.167480e-01 5.167480e-01 2.583740e-01 -5.167480e-01 -4.800000e+00 3.000000e+00 5.268708e-01 5.268708e-01 2.634354e-01 -5.268708e-01 -4.700000e+00 3.000000e+00 5.369771e-01 5.369771e-01 2.684885e-01 -5.369771e-01 -4.600000e+00 3.000000e+00 5.470583e-01 5.470583e-01 2.735291e-01 -5.470583e-01 -4.500000e+00 3.000000e+00 5.571059e-01 5.571059e-01 2.785529e-01 -5.571059e-01 -4.400000e+00 3.000000e+00 5.671111e-01 5.671111e-01 2.835556e-01 -5.671111e-01 -4.300000e+00 3.000000e+00 5.770652e-01 5.770652e-01 2.885326e-01 -5.770652e-01 -4.200000e+00 3.000000e+00 5.869592e-01 5.869592e-01 2.934796e-01 -5.869592e-01 -4.100000e+00 3.000000e+00 5.967840e-01 5.967840e-01 2.983920e-01 -5.967840e-01 -4.000000e+00 3.000000e+00 6.065307e-01 6.065307e-01 3.032653e-01 -6.065307e-01 -3.900000e+00 3.000000e+00 6.161900e-01 6.161900e-01 3.080950e-01 -6.161900e-01 -3.800000e+00 3.000000e+00 6.257527e-01 6.257527e-01 3.128763e-01 -6.257527e-01 -3.700000e+00 3.000000e+00 6.352097e-01 6.352097e-01 3.176049e-01 -6.352097e-01 -3.600000e+00 3.000000e+00 6.445519e-01 6.445519e-01 3.222759e-01 -6.445519e-01 -3.500000e+00 3.000000e+00 6.537698e-01 6.537698e-01 3.268849e-01 -6.537698e-01 -3.400000e+00 3.000000e+00 6.628543e-01 6.628543e-01 3.314272e-01 -6.628543e-01 -3.300000e+00 3.000000e+00 6.717964e-01 6.717964e-01 3.358982e-01 -6.717964e-01 -3.200000e+00 3.000000e+00 6.805868e-01 6.805868e-01 3.402934e-01 -6.805868e-01 -3.100000e+00 3.000000e+00 6.892164e-01 6.892164e-01 3.446082e-01 -6.892164e-01 -3.000000e+00 3.000000e+00 6.976763e-01 6.976763e-01 3.488382e-01 -6.976763e-01 -2.900000e+00 3.000000e+00 7.059577e-01 7.059577e-01 3.529788e-01 -7.059577e-01 -2.800000e+00 3.000000e+00 7.140516e-01 7.140516e-01 3.570258e-01 -7.140516e-01 -2.700000e+00 3.000000e+00 7.219496e-01 7.219496e-01 3.609748e-01 -7.219496e-01 -2.600000e+00 3.000000e+00 7.296429e-01 7.296429e-01 3.648215e-01 -7.296429e-01 -2.500000e+00 3.000000e+00 7.371234e-01 7.371234e-01 3.685617e-01 -7.371234e-01 -2.400000e+00 3.000000e+00 7.443827e-01 7.443827e-01 3.721913e-01 -7.443827e-01 -2.300000e+00 3.000000e+00 7.514129e-01 7.514129e-01 3.757065e-01 -7.514129e-01 -2.200000e+00 3.000000e+00 7.582061e-01 7.582061e-01 3.791031e-01 -7.582061e-01 -2.100000e+00 3.000000e+00 7.647548e-01 7.647548e-01 3.823774e-01 -7.647548e-01 -2.000000e+00 3.000000e+00 7.710516e-01 7.710516e-01 3.855258e-01 -7.710516e-01 -1.900000e+00 3.000000e+00 7.770893e-01 7.770893e-01 3.885446e-01 -7.770893e-01 -1.800000e+00 3.000000e+00 7.828611e-01 7.828611e-01 3.914306e-01 -7.828611e-01 -1.700000e+00 3.000000e+00 7.883604e-01 7.883604e-01 3.941802e-01 -7.883604e-01 -1.600000e+00 3.000000e+00 7.935807e-01 7.935807e-01 3.967904e-01 -7.935807e-01 -1.500000e+00 3.000000e+00 7.985162e-01 7.985162e-01 3.992581e-01 -7.985162e-01 -1.400000e+00 3.000000e+00 8.031611e-01 8.031611e-01 4.015805e-01 -8.031611e-01 -1.300000e+00 3.000000e+00 8.075098e-01 8.075098e-01 4.037549e-01 -8.075098e-01 -1.200000e+00 3.000000e+00 8.115575e-01 8.115575e-01 4.057788e-01 -8.115575e-01 -1.100000e+00 3.000000e+00 8.152993e-01 8.152993e-01 4.076496e-01 -8.152993e-01 -1.000000e+00 3.000000e+00 8.187308e-01 8.187308e-01 4.093654e-01 -8.187308e-01 -9.000000e-01 3.000000e+00 8.218479e-01 8.218479e-01 4.109239e-01 -8.218479e-01 -8.000000e-01 3.000000e+00 8.246469e-01 8.246469e-01 4.123234e-01 -8.246469e-01 -7.000000e-01 3.000000e+00 8.271245e-01 8.271245e-01 4.135623e-01 -8.271245e-01 -6.000000e-01 3.000000e+00 8.292779e-01 8.292779e-01 4.146389e-01 -8.292779e-01 -5.000000e-01 3.000000e+00 8.311043e-01 8.311043e-01 4.155521e-01 -8.311043e-01 -4.000000e-01 3.000000e+00 8.326016e-01 8.326016e-01 4.163008e-01 -8.326016e-01 -3.000000e-01 3.000000e+00 8.337681e-01 8.337681e-01 4.168840e-01 -8.337681e-01 -2.000000e-01 3.000000e+00 8.346022e-01 8.346022e-01 4.173011e-01 -8.346022e-01 -1.000000e-01 3.000000e+00 8.351032e-01 8.351032e-01 4.175516e-01 -8.351032e-01 0.000000e+00 3.000000e+00 8.352702e-01 8.352702e-01 4.176351e-01 -8.352702e-01 1.000000e-01 3.000000e+00 8.351032e-01 8.351032e-01 4.175516e-01 -8.351032e-01 2.000000e-01 3.000000e+00 8.346022e-01 8.346022e-01 4.173011e-01 -8.346022e-01 3.000000e-01 3.000000e+00 8.337681e-01 8.337681e-01 4.168840e-01 -8.337681e-01 4.000000e-01 3.000000e+00 8.326016e-01 8.326016e-01 4.163008e-01 -8.326016e-01 5.000000e-01 3.000000e+00 8.311043e-01 8.311043e-01 4.155521e-01 -8.311043e-01 6.000000e-01 3.000000e+00 8.292779e-01 8.292779e-01 4.146389e-01 -8.292779e-01 7.000000e-01 3.000000e+00 8.271245e-01 8.271245e-01 4.135623e-01 -8.271245e-01 8.000000e-01 3.000000e+00 8.246469e-01 8.246469e-01 4.123234e-01 -8.246469e-01 9.000000e-01 3.000000e+00 8.218479e-01 8.218479e-01 4.109239e-01 -8.218479e-01 1.000000e+00 3.000000e+00 8.187308e-01 8.187308e-01 4.093654e-01 -8.187308e-01 1.100000e+00 3.000000e+00 8.152993e-01 8.152993e-01 4.076496e-01 -8.152993e-01 1.200000e+00 3.000000e+00 8.115575e-01 8.115575e-01 4.057788e-01 -8.115575e-01 1.300000e+00 3.000000e+00 8.075098e-01 8.075098e-01 4.037549e-01 -8.075098e-01 1.400000e+00 3.000000e+00 8.031611e-01 8.031611e-01 4.015805e-01 -8.031611e-01 1.500000e+00 3.000000e+00 7.985162e-01 7.985162e-01 3.992581e-01 -7.985162e-01 1.600000e+00 3.000000e+00 7.935807e-01 7.935807e-01 3.967904e-01 -7.935807e-01 1.700000e+00 3.000000e+00 7.883604e-01 7.883604e-01 3.941802e-01 -7.883604e-01 1.800000e+00 3.000000e+00 7.828611e-01 7.828611e-01 3.914306e-01 -7.828611e-01 1.900000e+00 3.000000e+00 7.770893e-01 7.770893e-01 3.885446e-01 -7.770893e-01 2.000000e+00 3.000000e+00 7.710516e-01 7.710516e-01 3.855258e-01 -7.710516e-01 2.100000e+00 3.000000e+00 7.647548e-01 7.647548e-01 3.823774e-01 -7.647548e-01 2.200000e+00 3.000000e+00 7.582061e-01 7.582061e-01 3.791031e-01 -7.582061e-01 2.300000e+00 3.000000e+00 7.514129e-01 7.514129e-01 3.757065e-01 -7.514129e-01 2.400000e+00 3.000000e+00 7.443827e-01 7.443827e-01 3.721913e-01 -7.443827e-01 2.500000e+00 3.000000e+00 7.371234e-01 7.371234e-01 3.685617e-01 -7.371234e-01 2.600000e+00 3.000000e+00 7.296429e-01 7.296429e-01 3.648215e-01 -7.296429e-01 2.700000e+00 3.000000e+00 7.219496e-01 7.219496e-01 3.609748e-01 -7.219496e-01 2.800000e+00 3.000000e+00 7.140516e-01 7.140516e-01 3.570258e-01 -7.140516e-01 2.900000e+00 3.000000e+00 7.059577e-01 7.059577e-01 3.529788e-01 -7.059577e-01 3.000000e+00 3.000000e+00 6.976763e-01 6.976763e-01 3.488382e-01 -6.976763e-01 3.100000e+00 3.000000e+00 6.892164e-01 6.892164e-01 3.446082e-01 -6.892164e-01 3.200000e+00 3.000000e+00 6.805868e-01 6.805868e-01 3.402934e-01 -6.805868e-01 3.300000e+00 3.000000e+00 6.717964e-01 6.717964e-01 3.358982e-01 -6.717964e-01 3.400000e+00 3.000000e+00 6.628543e-01 6.628543e-01 3.314272e-01 -6.628543e-01 3.500000e+00 3.000000e+00 6.537698e-01 6.537698e-01 3.268849e-01 -6.537698e-01 3.600000e+00 3.000000e+00 6.445519e-01 6.445519e-01 3.222759e-01 -6.445519e-01 3.700000e+00 3.000000e+00 6.352097e-01 6.352097e-01 3.176049e-01 -6.352097e-01 3.800000e+00 3.000000e+00 6.257527e-01 6.257527e-01 3.128763e-01 -6.257527e-01 3.900000e+00 3.000000e+00 6.161900e-01 6.161900e-01 3.080950e-01 -6.161900e-01 4.000000e+00 3.000000e+00 6.065307e-01 6.065307e-01 3.032653e-01 -6.065307e-01 4.100000e+00 3.000000e+00 5.967840e-01 5.967840e-01 2.983920e-01 -5.967840e-01 4.200000e+00 3.000000e+00 5.869592e-01 5.869592e-01 2.934796e-01 -5.869592e-01 4.300000e+00 3.000000e+00 5.770652e-01 5.770652e-01 2.885326e-01 -5.770652e-01 4.400000e+00 3.000000e+00 5.671111e-01 5.671111e-01 2.835556e-01 -5.671111e-01 4.500000e+00 3.000000e+00 5.571059e-01 5.571059e-01 2.785529e-01 -5.571059e-01 4.600000e+00 3.000000e+00 5.470583e-01 5.470583e-01 2.735291e-01 -5.470583e-01 4.700000e+00 3.000000e+00 5.369771e-01 5.369771e-01 2.684885e-01 -5.369771e-01 4.800000e+00 3.000000e+00 5.268708e-01 5.268708e-01 2.634354e-01 -5.268708e-01 4.900000e+00 3.000000e+00 5.167480e-01 5.167480e-01 2.583740e-01 -5.167480e-01 -5.000000e+00 3.100000e+00 5.004738e-01 5.004738e-01 2.502369e-01 -5.004738e-01 -4.900000e+00 3.100000e+00 5.104820e-01 5.104820e-01 2.552410e-01 -5.104820e-01 -4.800000e+00 3.100000e+00 5.204820e-01 5.204820e-01 2.602410e-01 -5.204820e-01 -4.700000e+00 3.100000e+00 5.304657e-01 5.304657e-01 2.652329e-01 -5.304657e-01 -4.600000e+00 3.100000e+00 5.404247e-01 5.404247e-01 2.702124e-01 -5.404247e-01 -4.500000e+00 3.100000e+00 5.503505e-01 5.503505e-01 2.751752e-01 -5.503505e-01 -4.400000e+00 3.100000e+00 5.602344e-01 5.602344e-01 2.801172e-01 -5.602344e-01 -4.300000e+00 3.100000e+00 5.700678e-01 5.700678e-01 2.850339e-01 -5.700678e-01 -4.200000e+00 3.100000e+00 5.798418e-01 5.798418e-01 2.899209e-01 -5.798418e-01 -4.100000e+00 3.100000e+00 5.895475e-01 5.895475e-01 2.947738e-01 -5.895475e-01 -4.000000e+00 3.100000e+00 5.991759e-01 5.991759e-01 2.995880e-01 -5.991759e-01 -3.900000e+00 3.100000e+00 6.087181e-01 6.087181e-01 3.043590e-01 -6.087181e-01 -3.800000e+00 3.100000e+00 6.181649e-01 6.181649e-01 3.090824e-01 -6.181649e-01 -3.700000e+00 3.100000e+00 6.275073e-01 6.275073e-01 3.137536e-01 -6.275073e-01 -3.600000e+00 3.100000e+00 6.367361e-01 6.367361e-01 3.183680e-01 -6.367361e-01 -3.500000e+00 3.100000e+00 6.458423e-01 6.458423e-01 3.229211e-01 -6.458423e-01 -3.400000e+00 3.100000e+00 6.548166e-01 6.548166e-01 3.274083e-01 -6.548166e-01 -3.300000e+00 3.100000e+00 6.636503e-01 6.636503e-01 3.318251e-01 -6.636503e-01 -3.200000e+00 3.100000e+00 6.723340e-01 6.723340e-01 3.361670e-01 -6.723340e-01 -3.100000e+00 3.100000e+00 6.808590e-01 6.808590e-01 3.404295e-01 -6.808590e-01 -3.000000e+00 3.100000e+00 6.892164e-01 6.892164e-01 3.446082e-01 -6.892164e-01 -2.900000e+00 3.100000e+00 6.973973e-01 6.973973e-01 3.486986e-01 -6.973973e-01 -2.800000e+00 3.100000e+00 7.053931e-01 7.053931e-01 3.526966e-01 -7.053931e-01 -2.700000e+00 3.100000e+00 7.131953e-01 7.131953e-01 3.565976e-01 -7.131953e-01 -2.600000e+00 3.100000e+00 7.207954e-01 7.207954e-01 3.603977e-01 -7.207954e-01 -2.500000e+00 3.100000e+00 7.281851e-01 7.281851e-01 3.640926e-01 -7.281851e-01 -2.400000e+00 3.100000e+00 7.353564e-01 7.353564e-01 3.676782e-01 -7.353564e-01 -2.300000e+00 3.100000e+00 7.423013e-01 7.423013e-01 3.711507e-01 -7.423013e-01 -2.200000e+00 3.100000e+00 7.490122e-01 7.490122e-01 3.745061e-01 -7.490122e-01 -2.100000e+00 3.100000e+00 7.554815e-01 7.554815e-01 3.777407e-01 -7.554815e-01 -2.000000e+00 3.100000e+00 7.617019e-01 7.617019e-01 3.808509e-01 -7.617019e-01 -1.900000e+00 3.100000e+00 7.676664e-01 7.676664e-01 3.838332e-01 -7.676664e-01 -1.800000e+00 3.100000e+00 7.733682e-01 7.733682e-01 3.866841e-01 -7.733682e-01 -1.700000e+00 3.100000e+00 7.788008e-01 7.788008e-01 3.894004e-01 -7.788008e-01 -1.600000e+00 3.100000e+00 7.839578e-01 7.839578e-01 3.919789e-01 -7.839578e-01 -1.500000e+00 3.100000e+00 7.888335e-01 7.888335e-01 3.944167e-01 -7.888335e-01 -1.400000e+00 3.100000e+00 7.934220e-01 7.934220e-01 3.967110e-01 -7.934220e-01 -1.300000e+00 3.100000e+00 7.977181e-01 7.977181e-01 3.988591e-01 -7.977181e-01 -1.200000e+00 3.100000e+00 8.017167e-01 8.017167e-01 4.008583e-01 -8.017167e-01 -1.100000e+00 3.100000e+00 8.054131e-01 8.054131e-01 4.027065e-01 -8.054131e-01 -1.000000e+00 3.100000e+00 8.088029e-01 8.088029e-01 4.044015e-01 -8.088029e-01 -9.000000e-01 3.100000e+00 8.118822e-01 8.118822e-01 4.059411e-01 -8.118822e-01 -8.000000e-01 3.100000e+00 8.146473e-01 8.146473e-01 4.073237e-01 -8.146473e-01 -7.000000e-01 3.100000e+00 8.170949e-01 8.170949e-01 4.085475e-01 -8.170949e-01 -6.000000e-01 3.100000e+00 8.192222e-01 8.192222e-01 4.096111e-01 -8.192222e-01 -5.000000e-01 3.100000e+00 8.210264e-01 8.210264e-01 4.105132e-01 -8.210264e-01 -4.000000e-01 3.100000e+00 8.225056e-01 8.225056e-01 4.112528e-01 -8.225056e-01 -3.000000e-01 3.100000e+00 8.236579e-01 8.236579e-01 4.118289e-01 -8.236579e-01 -2.000000e-01 3.100000e+00 8.244820e-01 8.244820e-01 4.122410e-01 -8.244820e-01 -1.000000e-01 3.100000e+00 8.249768e-01 8.249768e-01 4.124884e-01 -8.249768e-01 0.000000e+00 3.100000e+00 8.251418e-01 8.251418e-01 4.125709e-01 -8.251418e-01 1.000000e-01 3.100000e+00 8.249768e-01 8.249768e-01 4.124884e-01 -8.249768e-01 2.000000e-01 3.100000e+00 8.244820e-01 8.244820e-01 4.122410e-01 -8.244820e-01 3.000000e-01 3.100000e+00 8.236579e-01 8.236579e-01 4.118289e-01 -8.236579e-01 4.000000e-01 3.100000e+00 8.225056e-01 8.225056e-01 4.112528e-01 -8.225056e-01 5.000000e-01 3.100000e+00 8.210264e-01 8.210264e-01 4.105132e-01 -8.210264e-01 6.000000e-01 3.100000e+00 8.192222e-01 8.192222e-01 4.096111e-01 -8.192222e-01 7.000000e-01 3.100000e+00 8.170949e-01 8.170949e-01 4.085475e-01 -8.170949e-01 8.000000e-01 3.100000e+00 8.146473e-01 8.146473e-01 4.073237e-01 -8.146473e-01 9.000000e-01 3.100000e+00 8.118822e-01 8.118822e-01 4.059411e-01 -8.118822e-01 1.000000e+00 3.100000e+00 8.088029e-01 8.088029e-01 4.044015e-01 -8.088029e-01 1.100000e+00 3.100000e+00 8.054131e-01 8.054131e-01 4.027065e-01 -8.054131e-01 1.200000e+00 3.100000e+00 8.017167e-01 8.017167e-01 4.008583e-01 -8.017167e-01 1.300000e+00 3.100000e+00 7.977181e-01 7.977181e-01 3.988591e-01 -7.977181e-01 1.400000e+00 3.100000e+00 7.934220e-01 7.934220e-01 3.967110e-01 -7.934220e-01 1.500000e+00 3.100000e+00 7.888335e-01 7.888335e-01 3.944167e-01 -7.888335e-01 1.600000e+00 3.100000e+00 7.839578e-01 7.839578e-01 3.919789e-01 -7.839578e-01 1.700000e+00 3.100000e+00 7.788008e-01 7.788008e-01 3.894004e-01 -7.788008e-01 1.800000e+00 3.100000e+00 7.733682e-01 7.733682e-01 3.866841e-01 -7.733682e-01 1.900000e+00 3.100000e+00 7.676664e-01 7.676664e-01 3.838332e-01 -7.676664e-01 2.000000e+00 3.100000e+00 7.617019e-01 7.617019e-01 3.808509e-01 -7.617019e-01 2.100000e+00 3.100000e+00 7.554815e-01 7.554815e-01 3.777407e-01 -7.554815e-01 2.200000e+00 3.100000e+00 7.490122e-01 7.490122e-01 3.745061e-01 -7.490122e-01 2.300000e+00 3.100000e+00 7.423013e-01 7.423013e-01 3.711507e-01 -7.423013e-01 2.400000e+00 3.100000e+00 7.353564e-01 7.353564e-01 3.676782e-01 -7.353564e-01 2.500000e+00 3.100000e+00 7.281851e-01 7.281851e-01 3.640926e-01 -7.281851e-01 2.600000e+00 3.100000e+00 7.207954e-01 7.207954e-01 3.603977e-01 -7.207954e-01 2.700000e+00 3.100000e+00 7.131953e-01 7.131953e-01 3.565976e-01 -7.131953e-01 2.800000e+00 3.100000e+00 7.053931e-01 7.053931e-01 3.526966e-01 -7.053931e-01 2.900000e+00 3.100000e+00 6.973973e-01 6.973973e-01 3.486986e-01 -6.973973e-01 3.000000e+00 3.100000e+00 6.892164e-01 6.892164e-01 3.446082e-01 -6.892164e-01 3.100000e+00 3.100000e+00 6.808590e-01 6.808590e-01 3.404295e-01 -6.808590e-01 3.200000e+00 3.100000e+00 6.723340e-01 6.723340e-01 3.361670e-01 -6.723340e-01 3.300000e+00 3.100000e+00 6.636503e-01 6.636503e-01 3.318251e-01 -6.636503e-01 3.400000e+00 3.100000e+00 6.548166e-01 6.548166e-01 3.274083e-01 -6.548166e-01 3.500000e+00 3.100000e+00 6.458423e-01 6.458423e-01 3.229211e-01 -6.458423e-01 3.600000e+00 3.100000e+00 6.367361e-01 6.367361e-01 3.183680e-01 -6.367361e-01 3.700000e+00 3.100000e+00 6.275073e-01 6.275073e-01 3.137536e-01 -6.275073e-01 3.800000e+00 3.100000e+00 6.181649e-01 6.181649e-01 3.090824e-01 -6.181649e-01 3.900000e+00 3.100000e+00 6.087181e-01 6.087181e-01 3.043590e-01 -6.087181e-01 4.000000e+00 3.100000e+00 5.991759e-01 5.991759e-01 2.995880e-01 -5.991759e-01 4.100000e+00 3.100000e+00 5.895475e-01 5.895475e-01 2.947738e-01 -5.895475e-01 4.200000e+00 3.100000e+00 5.798418e-01 5.798418e-01 2.899209e-01 -5.798418e-01 4.300000e+00 3.100000e+00 5.700678e-01 5.700678e-01 2.850339e-01 -5.700678e-01 4.400000e+00 3.100000e+00 5.602344e-01 5.602344e-01 2.801172e-01 -5.602344e-01 4.500000e+00 3.100000e+00 5.503505e-01 5.503505e-01 2.751752e-01 -5.503505e-01 4.600000e+00 3.100000e+00 5.404247e-01 5.404247e-01 2.702124e-01 -5.404247e-01 4.700000e+00 3.100000e+00 5.304657e-01 5.304657e-01 2.652329e-01 -5.304657e-01 4.800000e+00 3.100000e+00 5.204820e-01 5.204820e-01 2.602410e-01 -5.204820e-01 4.900000e+00 3.100000e+00 5.104820e-01 5.104820e-01 2.552410e-01 -5.104820e-01 -5.000000e+00 3.200000e+00 4.942074e-01 4.942074e-01 2.471037e-01 -4.942074e-01 -4.900000e+00 3.200000e+00 5.040902e-01 5.040902e-01 2.520451e-01 -5.040902e-01 -4.800000e+00 3.200000e+00 5.139651e-01 5.139651e-01 2.569825e-01 -5.139651e-01 -4.700000e+00 3.200000e+00 5.238238e-01 5.238238e-01 2.619119e-01 -5.238238e-01 -4.600000e+00 3.200000e+00 5.336581e-01 5.336581e-01 2.668290e-01 -5.336581e-01 -4.500000e+00 3.200000e+00 5.434595e-01 5.434595e-01 2.717298e-01 -5.434595e-01 -4.400000e+00 3.200000e+00 5.532197e-01 5.532197e-01 2.766099e-01 -5.532197e-01 -4.300000e+00 3.200000e+00 5.629300e-01 5.629300e-01 2.814650e-01 -5.629300e-01 -4.200000e+00 3.200000e+00 5.725816e-01 5.725816e-01 2.862908e-01 -5.725816e-01 -4.100000e+00 3.200000e+00 5.821658e-01 5.821658e-01 2.910829e-01 -5.821658e-01 -4.000000e+00 3.200000e+00 5.916737e-01 5.916737e-01 2.958368e-01 -5.916737e-01 -3.900000e+00 3.200000e+00 6.010964e-01 6.010964e-01 3.005482e-01 -6.010964e-01 -3.800000e+00 3.200000e+00 6.104249e-01 6.104249e-01 3.052124e-01 -6.104249e-01 -3.700000e+00 3.200000e+00 6.196503e-01 6.196503e-01 3.098252e-01 -6.196503e-01 -3.600000e+00 3.200000e+00 6.287636e-01 6.287636e-01 3.143818e-01 -6.287636e-01 -3.500000e+00 3.200000e+00 6.377557e-01 6.377557e-01 3.188778e-01 -6.377557e-01 -3.400000e+00 3.200000e+00 6.466177e-01 6.466177e-01 3.233089e-01 -6.466177e-01 -3.300000e+00 3.200000e+00 6.553407e-01 6.553407e-01 3.276704e-01 -6.553407e-01 -3.200000e+00 3.200000e+00 6.639158e-01 6.639158e-01 3.319579e-01 -6.639158e-01 -3.100000e+00 3.200000e+00 6.723340e-01 6.723340e-01 3.361670e-01 -6.723340e-01 -3.000000e+00 3.200000e+00 6.805868e-01 6.805868e-01 3.402934e-01 -6.805868e-01 -2.900000e+00 3.200000e+00 6.886652e-01 6.886652e-01 3.443326e-01 -6.886652e-01 -2.800000e+00 3.200000e+00 6.965610e-01 6.965610e-01 3.482805e-01 -6.965610e-01 -2.700000e+00 3.200000e+00 7.042654e-01 7.042654e-01 3.521327e-01 -7.042654e-01 -2.600000e+00 3.200000e+00 7.117704e-01 7.117704e-01 3.558852e-01 -7.117704e-01 -2.500000e+00 3.200000e+00 7.190675e-01 7.190675e-01 3.595338e-01 -7.190675e-01 -2.400000e+00 3.200000e+00 7.261490e-01 7.261490e-01 3.630745e-01 -7.261490e-01 -2.300000e+00 3.200000e+00 7.330070e-01 7.330070e-01 3.665035e-01 -7.330070e-01 -2.200000e+00 3.200000e+00 7.396339e-01 7.396339e-01 3.698169e-01 -7.396339e-01 -2.100000e+00 3.200000e+00 7.460222e-01 7.460222e-01 3.730111e-01 -7.460222e-01 -2.000000e+00 3.200000e+00 7.521647e-01 7.521647e-01 3.760823e-01 -7.521647e-01 -1.900000e+00 3.200000e+00 7.580545e-01 7.580545e-01 3.790272e-01 -7.580545e-01 -1.800000e+00 3.200000e+00 7.636849e-01 7.636849e-01 3.818425e-01 -7.636849e-01 -1.700000e+00 3.200000e+00 7.690495e-01 7.690495e-01 3.845247e-01 -7.690495e-01 -1.600000e+00 3.200000e+00 7.741420e-01 7.741420e-01 3.870710e-01 -7.741420e-01 -1.500000e+00 3.200000e+00 7.789565e-01 7.789565e-01 3.894783e-01 -7.789565e-01 -1.400000e+00 3.200000e+00 7.834876e-01 7.834876e-01 3.917438e-01 -7.834876e-01 -1.300000e+00 3.200000e+00 7.877299e-01 7.877299e-01 3.938650e-01 -7.877299e-01 -1.200000e+00 3.200000e+00 7.916784e-01 7.916784e-01 3.958392e-01 -7.916784e-01 -1.100000e+00 3.200000e+00 7.953286e-01 7.953286e-01 3.976643e-01 -7.953286e-01 -1.000000e+00 3.200000e+00 7.986760e-01 7.986760e-01 3.993380e-01 -7.986760e-01 -9.000000e-01 3.200000e+00 8.017167e-01 8.017167e-01 4.008583e-01 -8.017167e-01 -8.000000e-01 3.200000e+00 8.044472e-01 8.044472e-01 4.022236e-01 -8.044472e-01 -7.000000e-01 3.200000e+00 8.068641e-01 8.068641e-01 4.034321e-01 -8.068641e-01 -6.000000e-01 3.200000e+00 8.089647e-01 8.089647e-01 4.044824e-01 -8.089647e-01 -5.000000e-01 3.200000e+00 8.107464e-01 8.107464e-01 4.053732e-01 -8.107464e-01 -4.000000e-01 3.200000e+00 8.122070e-01 8.122070e-01 4.061035e-01 -8.122070e-01 -3.000000e-01 3.200000e+00 8.133450e-01 8.133450e-01 4.066725e-01 -8.133450e-01 -2.000000e-01 3.200000e+00 8.141587e-01 8.141587e-01 4.070793e-01 -8.141587e-01 -1.000000e-01 3.200000e+00 8.146473e-01 8.146473e-01 4.073237e-01 -8.146473e-01 0.000000e+00 3.200000e+00 8.148103e-01 8.148103e-01 4.074051e-01 -8.148103e-01 1.000000e-01 3.200000e+00 8.146473e-01 8.146473e-01 4.073237e-01 -8.146473e-01 2.000000e-01 3.200000e+00 8.141587e-01 8.141587e-01 4.070793e-01 -8.141587e-01 3.000000e-01 3.200000e+00 8.133450e-01 8.133450e-01 4.066725e-01 -8.133450e-01 4.000000e-01 3.200000e+00 8.122070e-01 8.122070e-01 4.061035e-01 -8.122070e-01 5.000000e-01 3.200000e+00 8.107464e-01 8.107464e-01 4.053732e-01 -8.107464e-01 6.000000e-01 3.200000e+00 8.089647e-01 8.089647e-01 4.044824e-01 -8.089647e-01 7.000000e-01 3.200000e+00 8.068641e-01 8.068641e-01 4.034321e-01 -8.068641e-01 8.000000e-01 3.200000e+00 8.044472e-01 8.044472e-01 4.022236e-01 -8.044472e-01 9.000000e-01 3.200000e+00 8.017167e-01 8.017167e-01 4.008583e-01 -8.017167e-01 1.000000e+00 3.200000e+00 7.986760e-01 7.986760e-01 3.993380e-01 -7.986760e-01 1.100000e+00 3.200000e+00 7.953286e-01 7.953286e-01 3.976643e-01 -7.953286e-01 1.200000e+00 3.200000e+00 7.916784e-01 7.916784e-01 3.958392e-01 -7.916784e-01 1.300000e+00 3.200000e+00 7.877299e-01 7.877299e-01 3.938650e-01 -7.877299e-01 1.400000e+00 3.200000e+00 7.834876e-01 7.834876e-01 3.917438e-01 -7.834876e-01 1.500000e+00 3.200000e+00 7.789565e-01 7.789565e-01 3.894783e-01 -7.789565e-01 1.600000e+00 3.200000e+00 7.741420e-01 7.741420e-01 3.870710e-01 -7.741420e-01 1.700000e+00 3.200000e+00 7.690495e-01 7.690495e-01 3.845247e-01 -7.690495e-01 1.800000e+00 3.200000e+00 7.636849e-01 7.636849e-01 3.818425e-01 -7.636849e-01 1.900000e+00 3.200000e+00 7.580545e-01 7.580545e-01 3.790272e-01 -7.580545e-01 2.000000e+00 3.200000e+00 7.521647e-01 7.521647e-01 3.760823e-01 -7.521647e-01 2.100000e+00 3.200000e+00 7.460222e-01 7.460222e-01 3.730111e-01 -7.460222e-01 2.200000e+00 3.200000e+00 7.396339e-01 7.396339e-01 3.698169e-01 -7.396339e-01 2.300000e+00 3.200000e+00 7.330070e-01 7.330070e-01 3.665035e-01 -7.330070e-01 2.400000e+00 3.200000e+00 7.261490e-01 7.261490e-01 3.630745e-01 -7.261490e-01 2.500000e+00 3.200000e+00 7.190675e-01 7.190675e-01 3.595338e-01 -7.190675e-01 2.600000e+00 3.200000e+00 7.117704e-01 7.117704e-01 3.558852e-01 -7.117704e-01 2.700000e+00 3.200000e+00 7.042654e-01 7.042654e-01 3.521327e-01 -7.042654e-01 2.800000e+00 3.200000e+00 6.965610e-01 6.965610e-01 3.482805e-01 -6.965610e-01 2.900000e+00 3.200000e+00 6.886652e-01 6.886652e-01 3.443326e-01 -6.886652e-01 3.000000e+00 3.200000e+00 6.805868e-01 6.805868e-01 3.402934e-01 -6.805868e-01 3.100000e+00 3.200000e+00 6.723340e-01 6.723340e-01 3.361670e-01 -6.723340e-01 3.200000e+00 3.200000e+00 6.639158e-01 6.639158e-01 3.319579e-01 -6.639158e-01 3.300000e+00 3.200000e+00 6.553407e-01 6.553407e-01 3.276704e-01 -6.553407e-01 3.400000e+00 3.200000e+00 6.466177e-01 6.466177e-01 3.233089e-01 -6.466177e-01 3.500000e+00 3.200000e+00 6.377557e-01 6.377557e-01 3.188778e-01 -6.377557e-01 3.600000e+00 3.200000e+00 6.287636e-01 6.287636e-01 3.143818e-01 -6.287636e-01 3.700000e+00 3.200000e+00 6.196503e-01 6.196503e-01 3.098252e-01 -6.196503e-01 3.800000e+00 3.200000e+00 6.104249e-01 6.104249e-01 3.052124e-01 -6.104249e-01 3.900000e+00 3.200000e+00 6.010964e-01 6.010964e-01 3.005482e-01 -6.010964e-01 4.000000e+00 3.200000e+00 5.916737e-01 5.916737e-01 2.958368e-01 -5.916737e-01 4.100000e+00 3.200000e+00 5.821658e-01 5.821658e-01 2.910829e-01 -5.821658e-01 4.200000e+00 3.200000e+00 5.725816e-01 5.725816e-01 2.862908e-01 -5.725816e-01 4.300000e+00 3.200000e+00 5.629300e-01 5.629300e-01 2.814650e-01 -5.629300e-01 4.400000e+00 3.200000e+00 5.532197e-01 5.532197e-01 2.766099e-01 -5.532197e-01 4.500000e+00 3.200000e+00 5.434595e-01 5.434595e-01 2.717298e-01 -5.434595e-01 4.600000e+00 3.200000e+00 5.336581e-01 5.336581e-01 2.668290e-01 -5.336581e-01 4.700000e+00 3.200000e+00 5.238238e-01 5.238238e-01 2.619119e-01 -5.238238e-01 4.800000e+00 3.200000e+00 5.139651e-01 5.139651e-01 2.569825e-01 -5.139651e-01 4.900000e+00 3.200000e+00 5.040902e-01 5.040902e-01 2.520451e-01 -5.040902e-01 -5.000000e+00 3.300000e+00 4.878243e-01 4.878243e-01 2.439122e-01 -4.878243e-01 -4.900000e+00 3.300000e+00 4.975795e-01 4.975795e-01 2.487897e-01 -4.975795e-01 -4.800000e+00 3.300000e+00 5.073267e-01 5.073267e-01 2.536634e-01 -5.073267e-01 -4.700000e+00 3.300000e+00 5.170582e-01 5.170582e-01 2.585291e-01 -5.170582e-01 -4.600000e+00 3.300000e+00 5.267655e-01 5.267655e-01 2.633827e-01 -5.267655e-01 -4.500000e+00 3.300000e+00 5.364403e-01 5.364403e-01 2.682202e-01 -5.364403e-01 -4.400000e+00 3.300000e+00 5.460745e-01 5.460745e-01 2.730372e-01 -5.460745e-01 -4.300000e+00 3.300000e+00 5.556593e-01 5.556593e-01 2.778296e-01 -5.556593e-01 -4.200000e+00 3.300000e+00 5.651863e-01 5.651863e-01 2.825931e-01 -5.651863e-01 -4.100000e+00 3.300000e+00 5.746467e-01 5.746467e-01 2.873233e-01 -5.746467e-01 -4.000000e+00 3.300000e+00 5.840317e-01 5.840317e-01 2.920159e-01 -5.840317e-01 -3.900000e+00 3.300000e+00 5.933327e-01 5.933327e-01 2.966664e-01 -5.933327e-01 -3.800000e+00 3.300000e+00 6.025407e-01 6.025407e-01 3.012704e-01 -6.025407e-01 -3.700000e+00 3.300000e+00 6.116470e-01 6.116470e-01 3.058235e-01 -6.116470e-01 -3.600000e+00 3.300000e+00 6.206425e-01 6.206425e-01 3.103213e-01 -6.206425e-01 -3.500000e+00 3.300000e+00 6.295186e-01 6.295186e-01 3.147593e-01 -6.295186e-01 -3.400000e+00 3.300000e+00 6.382661e-01 6.382661e-01 3.191330e-01 -6.382661e-01 -3.300000e+00 3.300000e+00 6.468765e-01 6.468765e-01 3.234382e-01 -6.468765e-01 -3.200000e+00 3.300000e+00 6.553407e-01 6.553407e-01 3.276704e-01 -6.553407e-01 -3.100000e+00 3.300000e+00 6.636503e-01 6.636503e-01 3.318251e-01 -6.636503e-01 -3.000000e+00 3.300000e+00 6.717964e-01 6.717964e-01 3.358982e-01 -6.717964e-01 -2.900000e+00 3.300000e+00 6.797705e-01 6.797705e-01 3.398853e-01 -6.797705e-01 -2.800000e+00 3.300000e+00 6.875643e-01 6.875643e-01 3.437821e-01 -6.875643e-01 -2.700000e+00 3.300000e+00 6.951692e-01 6.951692e-01 3.475846e-01 -6.951692e-01 -2.600000e+00 3.300000e+00 7.025772e-01 7.025772e-01 3.512886e-01 -7.025772e-01 -2.500000e+00 3.300000e+00 7.097802e-01 7.097802e-01 3.548901e-01 -7.097802e-01 -2.400000e+00 3.300000e+00 7.167702e-01 7.167702e-01 3.583851e-01 -7.167702e-01 -2.300000e+00 3.300000e+00 7.235397e-01 7.235397e-01 3.617698e-01 -7.235397e-01 -2.200000e+00 3.300000e+00 7.300808e-01 7.300808e-01 3.650404e-01 -7.300808e-01 -2.100000e+00 3.300000e+00 7.363867e-01 7.363867e-01 3.681933e-01 -7.363867e-01 -2.000000e+00 3.300000e+00 7.424498e-01 7.424498e-01 3.712249e-01 -7.424498e-01 -1.900000e+00 3.300000e+00 7.482636e-01 7.482636e-01 3.741318e-01 -7.482636e-01 -1.800000e+00 3.300000e+00 7.538213e-01 7.538213e-01 3.769106e-01 -7.538213e-01 -1.700000e+00 3.300000e+00 7.591165e-01 7.591165e-01 3.795583e-01 -7.591165e-01 -1.600000e+00 3.300000e+00 7.641433e-01 7.641433e-01 3.820716e-01 -7.641433e-01 -1.500000e+00 3.300000e+00 7.688957e-01 7.688957e-01 3.844478e-01 -7.688957e-01 -1.400000e+00 3.300000e+00 7.733682e-01 7.733682e-01 3.866841e-01 -7.733682e-01 -1.300000e+00 3.300000e+00 7.775557e-01 7.775557e-01 3.887779e-01 -7.775557e-01 -1.200000e+00 3.300000e+00 7.814533e-01 7.814533e-01 3.907266e-01 -7.814533e-01 -1.100000e+00 3.300000e+00 7.850562e-01 7.850562e-01 3.925281e-01 -7.850562e-01 -1.000000e+00 3.300000e+00 7.883604e-01 7.883604e-01 3.941802e-01 -7.883604e-01 -9.000000e-01 3.300000e+00 7.913619e-01 7.913619e-01 3.956809e-01 -7.913619e-01 -8.000000e-01 3.300000e+00 7.940571e-01 7.940571e-01 3.970285e-01 -7.940571e-01 -7.000000e-01 3.300000e+00 7.964428e-01 7.964428e-01 3.982214e-01 -7.964428e-01 -6.000000e-01 3.300000e+00 7.985162e-01 7.985162e-01 3.992581e-01 -7.985162e-01 -5.000000e-01 3.300000e+00 8.002749e-01 8.002749e-01 4.001375e-01 -8.002749e-01 -4.000000e-01 3.300000e+00 8.017167e-01 8.017167e-01 4.008583e-01 -8.017167e-01 -3.000000e-01 3.300000e+00 8.028399e-01 8.028399e-01 4.014199e-01 -8.028399e-01 -2.000000e-01 3.300000e+00 8.036431e-01 8.036431e-01 4.018216e-01 -8.036431e-01 -1.000000e-01 3.300000e+00 8.041254e-01 8.041254e-01 4.020627e-01 -8.041254e-01 0.000000e+00 3.300000e+00 8.042863e-01 8.042863e-01 4.021432e-01 -8.042863e-01 1.000000e-01 3.300000e+00 8.041254e-01 8.041254e-01 4.020627e-01 -8.041254e-01 2.000000e-01 3.300000e+00 8.036431e-01 8.036431e-01 4.018216e-01 -8.036431e-01 3.000000e-01 3.300000e+00 8.028399e-01 8.028399e-01 4.014199e-01 -8.028399e-01 4.000000e-01 3.300000e+00 8.017167e-01 8.017167e-01 4.008583e-01 -8.017167e-01 5.000000e-01 3.300000e+00 8.002749e-01 8.002749e-01 4.001375e-01 -8.002749e-01 6.000000e-01 3.300000e+00 7.985162e-01 7.985162e-01 3.992581e-01 -7.985162e-01 7.000000e-01 3.300000e+00 7.964428e-01 7.964428e-01 3.982214e-01 -7.964428e-01 8.000000e-01 3.300000e+00 7.940571e-01 7.940571e-01 3.970285e-01 -7.940571e-01 9.000000e-01 3.300000e+00 7.913619e-01 7.913619e-01 3.956809e-01 -7.913619e-01 1.000000e+00 3.300000e+00 7.883604e-01 7.883604e-01 3.941802e-01 -7.883604e-01 1.100000e+00 3.300000e+00 7.850562e-01 7.850562e-01 3.925281e-01 -7.850562e-01 1.200000e+00 3.300000e+00 7.814533e-01 7.814533e-01 3.907266e-01 -7.814533e-01 1.300000e+00 3.300000e+00 7.775557e-01 7.775557e-01 3.887779e-01 -7.775557e-01 1.400000e+00 3.300000e+00 7.733682e-01 7.733682e-01 3.866841e-01 -7.733682e-01 1.500000e+00 3.300000e+00 7.688957e-01 7.688957e-01 3.844478e-01 -7.688957e-01 1.600000e+00 3.300000e+00 7.641433e-01 7.641433e-01 3.820716e-01 -7.641433e-01 1.700000e+00 3.300000e+00 7.591165e-01 7.591165e-01 3.795583e-01 -7.591165e-01 1.800000e+00 3.300000e+00 7.538213e-01 7.538213e-01 3.769106e-01 -7.538213e-01 1.900000e+00 3.300000e+00 7.482636e-01 7.482636e-01 3.741318e-01 -7.482636e-01 2.000000e+00 3.300000e+00 7.424498e-01 7.424498e-01 3.712249e-01 -7.424498e-01 2.100000e+00 3.300000e+00 7.363867e-01 7.363867e-01 3.681933e-01 -7.363867e-01 2.200000e+00 3.300000e+00 7.300808e-01 7.300808e-01 3.650404e-01 -7.300808e-01 2.300000e+00 3.300000e+00 7.235397e-01 7.235397e-01 3.617698e-01 -7.235397e-01 2.400000e+00 3.300000e+00 7.167702e-01 7.167702e-01 3.583851e-01 -7.167702e-01 2.500000e+00 3.300000e+00 7.097802e-01 7.097802e-01 3.548901e-01 -7.097802e-01 2.600000e+00 3.300000e+00 7.025772e-01 7.025772e-01 3.512886e-01 -7.025772e-01 2.700000e+00 3.300000e+00 6.951692e-01 6.951692e-01 3.475846e-01 -6.951692e-01 2.800000e+00 3.300000e+00 6.875643e-01 6.875643e-01 3.437821e-01 -6.875643e-01 2.900000e+00 3.300000e+00 6.797705e-01 6.797705e-01 3.398853e-01 -6.797705e-01 3.000000e+00 3.300000e+00 6.717964e-01 6.717964e-01 3.358982e-01 -6.717964e-01 3.100000e+00 3.300000e+00 6.636503e-01 6.636503e-01 3.318251e-01 -6.636503e-01 3.200000e+00 3.300000e+00 6.553407e-01 6.553407e-01 3.276704e-01 -6.553407e-01 3.300000e+00 3.300000e+00 6.468765e-01 6.468765e-01 3.234382e-01 -6.468765e-01 3.400000e+00 3.300000e+00 6.382661e-01 6.382661e-01 3.191330e-01 -6.382661e-01 3.500000e+00 3.300000e+00 6.295186e-01 6.295186e-01 3.147593e-01 -6.295186e-01 3.600000e+00 3.300000e+00 6.206425e-01 6.206425e-01 3.103213e-01 -6.206425e-01 3.700000e+00 3.300000e+00 6.116470e-01 6.116470e-01 3.058235e-01 -6.116470e-01 3.800000e+00 3.300000e+00 6.025407e-01 6.025407e-01 3.012704e-01 -6.025407e-01 3.900000e+00 3.300000e+00 5.933327e-01 5.933327e-01 2.966664e-01 -5.933327e-01 4.000000e+00 3.300000e+00 5.840317e-01 5.840317e-01 2.920159e-01 -5.840317e-01 4.100000e+00 3.300000e+00 5.746467e-01 5.746467e-01 2.873233e-01 -5.746467e-01 4.200000e+00 3.300000e+00 5.651863e-01 5.651863e-01 2.825931e-01 -5.651863e-01 4.300000e+00 3.300000e+00 5.556593e-01 5.556593e-01 2.778296e-01 -5.556593e-01 4.400000e+00 3.300000e+00 5.460745e-01 5.460745e-01 2.730372e-01 -5.460745e-01 4.500000e+00 3.300000e+00 5.364403e-01 5.364403e-01 2.682202e-01 -5.364403e-01 4.600000e+00 3.300000e+00 5.267655e-01 5.267655e-01 2.633827e-01 -5.267655e-01 4.700000e+00 3.300000e+00 5.170582e-01 5.170582e-01 2.585291e-01 -5.170582e-01 4.800000e+00 3.300000e+00 5.073267e-01 5.073267e-01 2.536634e-01 -5.073267e-01 4.900000e+00 3.300000e+00 4.975795e-01 4.975795e-01 2.487897e-01 -4.975795e-01 -5.000000e+00 3.400000e+00 4.813311e-01 4.813311e-01 2.406655e-01 -4.813311e-01 -4.900000e+00 3.400000e+00 4.909564e-01 4.909564e-01 2.454782e-01 -4.909564e-01 -4.800000e+00 3.400000e+00 5.005739e-01 5.005739e-01 2.502870e-01 -5.005739e-01 -4.700000e+00 3.400000e+00 5.101758e-01 5.101758e-01 2.550879e-01 -5.101758e-01 -4.600000e+00 3.400000e+00 5.197538e-01 5.197538e-01 2.598769e-01 -5.197538e-01 -4.500000e+00 3.400000e+00 5.293000e-01 5.293000e-01 2.646500e-01 -5.293000e-01 -4.400000e+00 3.400000e+00 5.388058e-01 5.388058e-01 2.694029e-01 -5.388058e-01 -4.300000e+00 3.400000e+00 5.482631e-01 5.482631e-01 2.741315e-01 -5.482631e-01 -4.200000e+00 3.400000e+00 5.576633e-01 5.576633e-01 2.788316e-01 -5.576633e-01 -4.100000e+00 3.400000e+00 5.669977e-01 5.669977e-01 2.834989e-01 -5.669977e-01 -4.000000e+00 3.400000e+00 5.762579e-01 5.762579e-01 2.881289e-01 -5.762579e-01 -3.900000e+00 3.400000e+00 5.854350e-01 5.854350e-01 2.927175e-01 -5.854350e-01 -3.800000e+00 3.400000e+00 5.945206e-01 5.945206e-01 2.972603e-01 -5.945206e-01 -3.700000e+00 3.400000e+00 6.035056e-01 6.035056e-01 3.017528e-01 -6.035056e-01 -3.600000e+00 3.400000e+00 6.123814e-01 6.123814e-01 3.061907e-01 -6.123814e-01 -3.500000e+00 3.400000e+00 6.211392e-01 6.211392e-01 3.105696e-01 -6.211392e-01 -3.400000e+00 3.400000e+00 6.297704e-01 6.297704e-01 3.148852e-01 -6.297704e-01 -3.300000e+00 3.400000e+00 6.382661e-01 6.382661e-01 3.191330e-01 -6.382661e-01 -3.200000e+00 3.400000e+00 6.466177e-01 6.466177e-01 3.233089e-01 -6.466177e-01 -3.100000e+00 3.400000e+00 6.548166e-01 6.548166e-01 3.274083e-01 -6.548166e-01 -3.000000e+00 3.400000e+00 6.628543e-01 6.628543e-01 3.314272e-01 -6.628543e-01 -2.900000e+00 3.400000e+00 6.707223e-01 6.707223e-01 3.353612e-01 -6.707223e-01 -2.800000e+00 3.400000e+00 6.784123e-01 6.784123e-01 3.392062e-01 -6.784123e-01 -2.700000e+00 3.400000e+00 6.859161e-01 6.859161e-01 3.429580e-01 -6.859161e-01 -2.600000e+00 3.400000e+00 6.932254e-01 6.932254e-01 3.466127e-01 -6.932254e-01 -2.500000e+00 3.400000e+00 7.003325e-01 7.003325e-01 3.501663e-01 -7.003325e-01 -2.400000e+00 3.400000e+00 7.072295e-01 7.072295e-01 3.536147e-01 -7.072295e-01 -2.300000e+00 3.400000e+00 7.139089e-01 7.139089e-01 3.569544e-01 -7.139089e-01 -2.200000e+00 3.400000e+00 7.203630e-01 7.203630e-01 3.601815e-01 -7.203630e-01 -2.100000e+00 3.400000e+00 7.265849e-01 7.265849e-01 3.632924e-01 -7.265849e-01 -2.000000e+00 3.400000e+00 7.325673e-01 7.325673e-01 3.662837e-01 -7.325673e-01 -1.900000e+00 3.400000e+00 7.383037e-01 7.383037e-01 3.691519e-01 -7.383037e-01 -1.800000e+00 3.400000e+00 7.437874e-01 7.437874e-01 3.718937e-01 -7.437874e-01 -1.700000e+00 3.400000e+00 7.490122e-01 7.490122e-01 3.745061e-01 -7.490122e-01 -1.600000e+00 3.400000e+00 7.539721e-01 7.539721e-01 3.769860e-01 -7.539721e-01 -1.500000e+00 3.400000e+00 7.586612e-01 7.586612e-01 3.793306e-01 -7.586612e-01 -1.400000e+00 3.400000e+00 7.630742e-01 7.630742e-01 3.815371e-01 -7.630742e-01 -1.300000e+00 3.400000e+00 7.672060e-01 7.672060e-01 3.836030e-01 -7.672060e-01 -1.200000e+00 3.400000e+00 7.710516e-01 7.710516e-01 3.855258e-01 -7.710516e-01 -1.100000e+00 3.400000e+00 7.746066e-01 7.746066e-01 3.873033e-01 -7.746066e-01 -1.000000e+00 3.400000e+00 7.778668e-01 7.778668e-01 3.889334e-01 -7.778668e-01 -9.000000e-01 3.400000e+00 7.808283e-01 7.808283e-01 3.904141e-01 -7.808283e-01 -8.000000e-01 3.400000e+00 7.834876e-01 7.834876e-01 3.917438e-01 -7.834876e-01 -7.000000e-01 3.400000e+00 7.858416e-01 7.858416e-01 3.929208e-01 -7.858416e-01 -6.000000e-01 3.400000e+00 7.878875e-01 7.878875e-01 3.939437e-01 -7.878875e-01 -5.000000e-01 3.400000e+00 7.896227e-01 7.896227e-01 3.948114e-01 -7.896227e-01 -4.000000e-01 3.400000e+00 7.910453e-01 7.910453e-01 3.955227e-01 -7.910453e-01 -3.000000e-01 3.400000e+00 7.921535e-01 7.921535e-01 3.960768e-01 -7.921535e-01 -2.000000e-01 3.400000e+00 7.929461e-01 7.929461e-01 3.964731e-01 -7.929461e-01 -1.000000e-01 3.400000e+00 7.934220e-01 7.934220e-01 3.967110e-01 -7.934220e-01 0.000000e+00 3.400000e+00 7.935807e-01 7.935807e-01 3.967904e-01 -7.935807e-01 1.000000e-01 3.400000e+00 7.934220e-01 7.934220e-01 3.967110e-01 -7.934220e-01 2.000000e-01 3.400000e+00 7.929461e-01 7.929461e-01 3.964731e-01 -7.929461e-01 3.000000e-01 3.400000e+00 7.921535e-01 7.921535e-01 3.960768e-01 -7.921535e-01 4.000000e-01 3.400000e+00 7.910453e-01 7.910453e-01 3.955227e-01 -7.910453e-01 5.000000e-01 3.400000e+00 7.896227e-01 7.896227e-01 3.948114e-01 -7.896227e-01 6.000000e-01 3.400000e+00 7.878875e-01 7.878875e-01 3.939437e-01 -7.878875e-01 7.000000e-01 3.400000e+00 7.858416e-01 7.858416e-01 3.929208e-01 -7.858416e-01 8.000000e-01 3.400000e+00 7.834876e-01 7.834876e-01 3.917438e-01 -7.834876e-01 9.000000e-01 3.400000e+00 7.808283e-01 7.808283e-01 3.904141e-01 -7.808283e-01 1.000000e+00 3.400000e+00 7.778668e-01 7.778668e-01 3.889334e-01 -7.778668e-01 1.100000e+00 3.400000e+00 7.746066e-01 7.746066e-01 3.873033e-01 -7.746066e-01 1.200000e+00 3.400000e+00 7.710516e-01 7.710516e-01 3.855258e-01 -7.710516e-01 1.300000e+00 3.400000e+00 7.672060e-01 7.672060e-01 3.836030e-01 -7.672060e-01 1.400000e+00 3.400000e+00 7.630742e-01 7.630742e-01 3.815371e-01 -7.630742e-01 1.500000e+00 3.400000e+00 7.586612e-01 7.586612e-01 3.793306e-01 -7.586612e-01 1.600000e+00 3.400000e+00 7.539721e-01 7.539721e-01 3.769860e-01 -7.539721e-01 1.700000e+00 3.400000e+00 7.490122e-01 7.490122e-01 3.745061e-01 -7.490122e-01 1.800000e+00 3.400000e+00 7.437874e-01 7.437874e-01 3.718937e-01 -7.437874e-01 1.900000e+00 3.400000e+00 7.383037e-01 7.383037e-01 3.691519e-01 -7.383037e-01 2.000000e+00 3.400000e+00 7.325673e-01 7.325673e-01 3.662837e-01 -7.325673e-01 2.100000e+00 3.400000e+00 7.265849e-01 7.265849e-01 3.632924e-01 -7.265849e-01 2.200000e+00 3.400000e+00 7.203630e-01 7.203630e-01 3.601815e-01 -7.203630e-01 2.300000e+00 3.400000e+00 7.139089e-01 7.139089e-01 3.569544e-01 -7.139089e-01 2.400000e+00 3.400000e+00 7.072295e-01 7.072295e-01 3.536147e-01 -7.072295e-01 2.500000e+00 3.400000e+00 7.003325e-01 7.003325e-01 3.501663e-01 -7.003325e-01 2.600000e+00 3.400000e+00 6.932254e-01 6.932254e-01 3.466127e-01 -6.932254e-01 2.700000e+00 3.400000e+00 6.859161e-01 6.859161e-01 3.429580e-01 -6.859161e-01 2.800000e+00 3.400000e+00 6.784123e-01 6.784123e-01 3.392062e-01 -6.784123e-01 2.900000e+00 3.400000e+00 6.707223e-01 6.707223e-01 3.353612e-01 -6.707223e-01 3.000000e+00 3.400000e+00 6.628543e-01 6.628543e-01 3.314272e-01 -6.628543e-01 3.100000e+00 3.400000e+00 6.548166e-01 6.548166e-01 3.274083e-01 -6.548166e-01 3.200000e+00 3.400000e+00 6.466177e-01 6.466177e-01 3.233089e-01 -6.466177e-01 3.300000e+00 3.400000e+00 6.382661e-01 6.382661e-01 3.191330e-01 -6.382661e-01 3.400000e+00 3.400000e+00 6.297704e-01 6.297704e-01 3.148852e-01 -6.297704e-01 3.500000e+00 3.400000e+00 6.211392e-01 6.211392e-01 3.105696e-01 -6.211392e-01 3.600000e+00 3.400000e+00 6.123814e-01 6.123814e-01 3.061907e-01 -6.123814e-01 3.700000e+00 3.400000e+00 6.035056e-01 6.035056e-01 3.017528e-01 -6.035056e-01 3.800000e+00 3.400000e+00 5.945206e-01 5.945206e-01 2.972603e-01 -5.945206e-01 3.900000e+00 3.400000e+00 5.854350e-01 5.854350e-01 2.927175e-01 -5.854350e-01 4.000000e+00 3.400000e+00 5.762579e-01 5.762579e-01 2.881289e-01 -5.762579e-01 4.100000e+00 3.400000e+00 5.669977e-01 5.669977e-01 2.834989e-01 -5.669977e-01 4.200000e+00 3.400000e+00 5.576633e-01 5.576633e-01 2.788316e-01 -5.576633e-01 4.300000e+00 3.400000e+00 5.482631e-01 5.482631e-01 2.741315e-01 -5.482631e-01 4.400000e+00 3.400000e+00 5.388058e-01 5.388058e-01 2.694029e-01 -5.388058e-01 4.500000e+00 3.400000e+00 5.293000e-01 5.293000e-01 2.646500e-01 -5.293000e-01 4.600000e+00 3.400000e+00 5.197538e-01 5.197538e-01 2.598769e-01 -5.197538e-01 4.700000e+00 3.400000e+00 5.101758e-01 5.101758e-01 2.550879e-01 -5.101758e-01 4.800000e+00 3.400000e+00 5.005739e-01 5.005739e-01 2.502870e-01 -5.005739e-01 4.900000e+00 3.400000e+00 4.909564e-01 4.909564e-01 2.454782e-01 -4.909564e-01 -5.000000e+00 3.500000e+00 4.747343e-01 4.747343e-01 2.373672e-01 -4.747343e-01 -4.900000e+00 3.500000e+00 4.842277e-01 4.842277e-01 2.421139e-01 -4.842277e-01 -4.800000e+00 3.500000e+00 4.937134e-01 4.937134e-01 2.468567e-01 -4.937134e-01 -4.700000e+00 3.500000e+00 5.031837e-01 5.031837e-01 2.515919e-01 -5.031837e-01 -4.600000e+00 3.500000e+00 5.126305e-01 5.126305e-01 2.563153e-01 -5.126305e-01 -4.500000e+00 3.500000e+00 5.220458e-01 5.220458e-01 2.610229e-01 -5.220458e-01 -4.400000e+00 3.500000e+00 5.314214e-01 5.314214e-01 2.657107e-01 -5.314214e-01 -4.300000e+00 3.500000e+00 5.407491e-01 5.407491e-01 2.703745e-01 -5.407491e-01 -4.200000e+00 3.500000e+00 5.500204e-01 5.500204e-01 2.750102e-01 -5.500204e-01 -4.100000e+00 3.500000e+00 5.592269e-01 5.592269e-01 2.796134e-01 -5.592269e-01 -4.000000e+00 3.500000e+00 5.683601e-01 5.683601e-01 2.841801e-01 -5.683601e-01 -3.900000e+00 3.500000e+00 5.774115e-01 5.774115e-01 2.887058e-01 -5.774115e-01 -3.800000e+00 3.500000e+00 5.863725e-01 5.863725e-01 2.931862e-01 -5.863725e-01 -3.700000e+00 3.500000e+00 5.952344e-01 5.952344e-01 2.976172e-01 -5.952344e-01 -3.600000e+00 3.500000e+00 6.039886e-01 6.039886e-01 3.019943e-01 -6.039886e-01 -3.500000e+00 3.500000e+00 6.126264e-01 6.126264e-01 3.063132e-01 -6.126264e-01 -3.400000e+00 3.500000e+00 6.211392e-01 6.211392e-01 3.105696e-01 -6.211392e-01 -3.300000e+00 3.500000e+00 6.295186e-01 6.295186e-01 3.147593e-01 -6.295186e-01 -3.200000e+00 3.500000e+00 6.377557e-01 6.377557e-01 3.188778e-01 -6.377557e-01 -3.100000e+00 3.500000e+00 6.458423e-01 6.458423e-01 3.229211e-01 -6.458423e-01 -3.000000e+00 3.500000e+00 6.537698e-01 6.537698e-01 3.268849e-01 -6.537698e-01 -2.900000e+00 3.500000e+00 6.615300e-01 6.615300e-01 3.307650e-01 -6.615300e-01 -2.800000e+00 3.500000e+00 6.691146e-01 6.691146e-01 3.345573e-01 -6.691146e-01 -2.700000e+00 3.500000e+00 6.765155e-01 6.765155e-01 3.382577e-01 -6.765155e-01 -2.600000e+00 3.500000e+00 6.837247e-01 6.837247e-01 3.418624e-01 -6.837247e-01 -2.500000e+00 3.500000e+00 6.907343e-01 6.907343e-01 3.453672e-01 -6.907343e-01 -2.400000e+00 3.500000e+00 6.975368e-01 6.975368e-01 3.487684e-01 -6.975368e-01 -2.300000e+00 3.500000e+00 7.041246e-01 7.041246e-01 3.520623e-01 -7.041246e-01 -2.200000e+00 3.500000e+00 7.104903e-01 7.104903e-01 3.552451e-01 -7.104903e-01 -2.100000e+00 3.500000e+00 7.166269e-01 7.166269e-01 3.583134e-01 -7.166269e-01 -2.000000e+00 3.500000e+00 7.225274e-01 7.225274e-01 3.612637e-01 -7.225274e-01 -1.900000e+00 3.500000e+00 7.281851e-01 7.281851e-01 3.640926e-01 -7.281851e-01 -1.800000e+00 3.500000e+00 7.335937e-01 7.335937e-01 3.667969e-01 -7.335937e-01 -1.700000e+00 3.500000e+00 7.387468e-01 7.387468e-01 3.693734e-01 -7.387468e-01 -1.600000e+00 3.500000e+00 7.436387e-01 7.436387e-01 3.718193e-01 -7.436387e-01 -1.500000e+00 3.500000e+00 7.482636e-01 7.482636e-01 3.741318e-01 -7.482636e-01 -1.400000e+00 3.500000e+00 7.526161e-01 7.526161e-01 3.763081e-01 -7.526161e-01 -1.300000e+00 3.500000e+00 7.566912e-01 7.566912e-01 3.783456e-01 -7.566912e-01 -1.200000e+00 3.500000e+00 7.604842e-01 7.604842e-01 3.802421e-01 -7.604842e-01 -1.100000e+00 3.500000e+00 7.639905e-01 7.639905e-01 3.819952e-01 -7.639905e-01 -1.000000e+00 3.500000e+00 7.672060e-01 7.672060e-01 3.836030e-01 -7.672060e-01 -9.000000e-01 3.500000e+00 7.701269e-01 7.701269e-01 3.850634e-01 -7.701269e-01 -8.000000e-01 3.500000e+00 7.727498e-01 7.727498e-01 3.863749e-01 -7.727498e-01 -7.000000e-01 3.500000e+00 7.750715e-01 7.750715e-01 3.875358e-01 -7.750715e-01 -6.000000e-01 3.500000e+00 7.770893e-01 7.770893e-01 3.885446e-01 -7.770893e-01 -5.000000e-01 3.500000e+00 7.788008e-01 7.788008e-01 3.894004e-01 -7.788008e-01 -4.000000e-01 3.500000e+00 7.802039e-01 7.802039e-01 3.901019e-01 -7.802039e-01 -3.000000e-01 3.500000e+00 7.812970e-01 7.812970e-01 3.906485e-01 -7.812970e-01 -2.000000e-01 3.500000e+00 7.820786e-01 7.820786e-01 3.910393e-01 -7.820786e-01 -1.000000e-01 3.500000e+00 7.825480e-01 7.825480e-01 3.912740e-01 -7.825480e-01 0.000000e+00 3.500000e+00 7.827045e-01 7.827045e-01 3.913523e-01 -7.827045e-01 1.000000e-01 3.500000e+00 7.825480e-01 7.825480e-01 3.912740e-01 -7.825480e-01 2.000000e-01 3.500000e+00 7.820786e-01 7.820786e-01 3.910393e-01 -7.820786e-01 3.000000e-01 3.500000e+00 7.812970e-01 7.812970e-01 3.906485e-01 -7.812970e-01 4.000000e-01 3.500000e+00 7.802039e-01 7.802039e-01 3.901019e-01 -7.802039e-01 5.000000e-01 3.500000e+00 7.788008e-01 7.788008e-01 3.894004e-01 -7.788008e-01 6.000000e-01 3.500000e+00 7.770893e-01 7.770893e-01 3.885446e-01 -7.770893e-01 7.000000e-01 3.500000e+00 7.750715e-01 7.750715e-01 3.875358e-01 -7.750715e-01 8.000000e-01 3.500000e+00 7.727498e-01 7.727498e-01 3.863749e-01 -7.727498e-01 9.000000e-01 3.500000e+00 7.701269e-01 7.701269e-01 3.850634e-01 -7.701269e-01 1.000000e+00 3.500000e+00 7.672060e-01 7.672060e-01 3.836030e-01 -7.672060e-01 1.100000e+00 3.500000e+00 7.639905e-01 7.639905e-01 3.819952e-01 -7.639905e-01 1.200000e+00 3.500000e+00 7.604842e-01 7.604842e-01 3.802421e-01 -7.604842e-01 1.300000e+00 3.500000e+00 7.566912e-01 7.566912e-01 3.783456e-01 -7.566912e-01 1.400000e+00 3.500000e+00 7.526161e-01 7.526161e-01 3.763081e-01 -7.526161e-01 1.500000e+00 3.500000e+00 7.482636e-01 7.482636e-01 3.741318e-01 -7.482636e-01 1.600000e+00 3.500000e+00 7.436387e-01 7.436387e-01 3.718193e-01 -7.436387e-01 1.700000e+00 3.500000e+00 7.387468e-01 7.387468e-01 3.693734e-01 -7.387468e-01 1.800000e+00 3.500000e+00 7.335937e-01 7.335937e-01 3.667969e-01 -7.335937e-01 1.900000e+00 3.500000e+00 7.281851e-01 7.281851e-01 3.640926e-01 -7.281851e-01 2.000000e+00 3.500000e+00 7.225274e-01 7.225274e-01 3.612637e-01 -7.225274e-01 2.100000e+00 3.500000e+00 7.166269e-01 7.166269e-01 3.583134e-01 -7.166269e-01 2.200000e+00 3.500000e+00 7.104903e-01 7.104903e-01 3.552451e-01 -7.104903e-01 2.300000e+00 3.500000e+00 7.041246e-01 7.041246e-01 3.520623e-01 -7.041246e-01 2.400000e+00 3.500000e+00 6.975368e-01 6.975368e-01 3.487684e-01 -6.975368e-01 2.500000e+00 3.500000e+00 6.907343e-01 6.907343e-01 3.453672e-01 -6.907343e-01 2.600000e+00 3.500000e+00 6.837247e-01 6.837247e-01 3.418624e-01 -6.837247e-01 2.700000e+00 3.500000e+00 6.765155e-01 6.765155e-01 3.382577e-01 -6.765155e-01 2.800000e+00 3.500000e+00 6.691146e-01 6.691146e-01 3.345573e-01 -6.691146e-01 2.900000e+00 3.500000e+00 6.615300e-01 6.615300e-01 3.307650e-01 -6.615300e-01 3.000000e+00 3.500000e+00 6.537698e-01 6.537698e-01 3.268849e-01 -6.537698e-01 3.100000e+00 3.500000e+00 6.458423e-01 6.458423e-01 3.229211e-01 -6.458423e-01 3.200000e+00 3.500000e+00 6.377557e-01 6.377557e-01 3.188778e-01 -6.377557e-01 3.300000e+00 3.500000e+00 6.295186e-01 6.295186e-01 3.147593e-01 -6.295186e-01 3.400000e+00 3.500000e+00 6.211392e-01 6.211392e-01 3.105696e-01 -6.211392e-01 3.500000e+00 3.500000e+00 6.126264e-01 6.126264e-01 3.063132e-01 -6.126264e-01 3.600000e+00 3.500000e+00 6.039886e-01 6.039886e-01 3.019943e-01 -6.039886e-01 3.700000e+00 3.500000e+00 5.952344e-01 5.952344e-01 2.976172e-01 -5.952344e-01 3.800000e+00 3.500000e+00 5.863725e-01 5.863725e-01 2.931862e-01 -5.863725e-01 3.900000e+00 3.500000e+00 5.774115e-01 5.774115e-01 2.887058e-01 -5.774115e-01 4.000000e+00 3.500000e+00 5.683601e-01 5.683601e-01 2.841801e-01 -5.683601e-01 4.100000e+00 3.500000e+00 5.592269e-01 5.592269e-01 2.796134e-01 -5.592269e-01 4.200000e+00 3.500000e+00 5.500204e-01 5.500204e-01 2.750102e-01 -5.500204e-01 4.300000e+00 3.500000e+00 5.407491e-01 5.407491e-01 2.703745e-01 -5.407491e-01 4.400000e+00 3.500000e+00 5.314214e-01 5.314214e-01 2.657107e-01 -5.314214e-01 4.500000e+00 3.500000e+00 5.220458e-01 5.220458e-01 2.610229e-01 -5.220458e-01 4.600000e+00 3.500000e+00 5.126305e-01 5.126305e-01 2.563153e-01 -5.126305e-01 4.700000e+00 3.500000e+00 5.031837e-01 5.031837e-01 2.515919e-01 -5.031837e-01 4.800000e+00 3.500000e+00 4.937134e-01 4.937134e-01 2.468567e-01 -4.937134e-01 4.900000e+00 3.500000e+00 4.842277e-01 4.842277e-01 2.421139e-01 -4.842277e-01 -5.000000e+00 3.600000e+00 4.680407e-01 4.680407e-01 2.340204e-01 -4.680407e-01 -4.900000e+00 3.600000e+00 4.774002e-01 4.774002e-01 2.387001e-01 -4.774002e-01 -4.800000e+00 3.600000e+00 4.867522e-01 4.867522e-01 2.433761e-01 -4.867522e-01 -4.700000e+00 3.600000e+00 4.960890e-01 4.960890e-01 2.480445e-01 -4.960890e-01 -4.600000e+00 3.600000e+00 5.054026e-01 5.054026e-01 2.527013e-01 -5.054026e-01 -4.500000e+00 3.600000e+00 5.146852e-01 5.146852e-01 2.573426e-01 -5.146852e-01 -4.400000e+00 3.600000e+00 5.239285e-01 5.239285e-01 2.619643e-01 -5.239285e-01 -4.300000e+00 3.600000e+00 5.331247e-01 5.331247e-01 2.665623e-01 -5.331247e-01 -4.200000e+00 3.600000e+00 5.422652e-01 5.422652e-01 2.711326e-01 -5.422652e-01 -4.100000e+00 3.600000e+00 5.513420e-01 5.513420e-01 2.756710e-01 -5.513420e-01 -4.000000e+00 3.600000e+00 5.603464e-01 5.603464e-01 2.801732e-01 -5.603464e-01 -3.900000e+00 3.600000e+00 5.692703e-01 5.692703e-01 2.846351e-01 -5.692703e-01 -3.800000e+00 3.600000e+00 5.781049e-01 5.781049e-01 2.890524e-01 -5.781049e-01 -3.700000e+00 3.600000e+00 5.868418e-01 5.868418e-01 2.934209e-01 -5.868418e-01 -3.600000e+00 3.600000e+00 5.954726e-01 5.954726e-01 2.977363e-01 -5.954726e-01 -3.500000e+00 3.600000e+00 6.039886e-01 6.039886e-01 3.019943e-01 -6.039886e-01 -3.400000e+00 3.600000e+00 6.123814e-01 6.123814e-01 3.061907e-01 -6.123814e-01 -3.300000e+00 3.600000e+00 6.206425e-01 6.206425e-01 3.103213e-01 -6.206425e-01 -3.200000e+00 3.600000e+00 6.287636e-01 6.287636e-01 3.143818e-01 -6.287636e-01 -3.100000e+00 3.600000e+00 6.367361e-01 6.367361e-01 3.183680e-01 -6.367361e-01 -3.000000e+00 3.600000e+00 6.445519e-01 6.445519e-01 3.222759e-01 -6.445519e-01 -2.900000e+00 3.600000e+00 6.522026e-01 6.522026e-01 3.261013e-01 -6.522026e-01 -2.800000e+00 3.600000e+00 6.596803e-01 6.596803e-01 3.298402e-01 -6.596803e-01 -2.700000e+00 3.600000e+00 6.669768e-01 6.669768e-01 3.334884e-01 -6.669768e-01 -2.600000e+00 3.600000e+00 6.740844e-01 6.740844e-01 3.370422e-01 -6.740844e-01 -2.500000e+00 3.600000e+00 6.809952e-01 6.809952e-01 3.404976e-01 -6.809952e-01 -2.400000e+00 3.600000e+00 6.877018e-01 6.877018e-01 3.438509e-01 -6.877018e-01 -2.300000e+00 3.600000e+00 6.941967e-01 6.941967e-01 3.470984e-01 -6.941967e-01 -2.200000e+00 3.600000e+00 7.004727e-01 7.004727e-01 3.502363e-01 -7.004727e-01 -2.100000e+00 3.600000e+00 7.065227e-01 7.065227e-01 3.532614e-01 -7.065227e-01 -2.000000e+00 3.600000e+00 7.123400e-01 7.123400e-01 3.561700e-01 -7.123400e-01 -1.900000e+00 3.600000e+00 7.179180e-01 7.179180e-01 3.589590e-01 -7.179180e-01 -1.800000e+00 3.600000e+00 7.232503e-01 7.232503e-01 3.616251e-01 -7.232503e-01 -1.700000e+00 3.600000e+00 7.283308e-01 7.283308e-01 3.641654e-01 -7.283308e-01 -1.600000e+00 3.600000e+00 7.331536e-01 7.331536e-01 3.665768e-01 -7.331536e-01 -1.500000e+00 3.600000e+00 7.377133e-01 7.377133e-01 3.688567e-01 -7.377133e-01 -1.400000e+00 3.600000e+00 7.420045e-01 7.420045e-01 3.710023e-01 -7.420045e-01 -1.300000e+00 3.600000e+00 7.460222e-01 7.460222e-01 3.730111e-01 -7.460222e-01 -1.200000e+00 3.600000e+00 7.497616e-01 7.497616e-01 3.748808e-01 -7.497616e-01 -1.100000e+00 3.600000e+00 7.532185e-01 7.532185e-01 3.766092e-01 -7.532185e-01 -1.000000e+00 3.600000e+00 7.563886e-01 7.563886e-01 3.781943e-01 -7.563886e-01 -9.000000e-01 3.600000e+00 7.592683e-01 7.592683e-01 3.796342e-01 -7.592683e-01 -8.000000e-01 3.600000e+00 7.618543e-01 7.618543e-01 3.809271e-01 -7.618543e-01 -7.000000e-01 3.600000e+00 7.641433e-01 7.641433e-01 3.820716e-01 -7.641433e-01 -6.000000e-01 3.600000e+00 7.661327e-01 7.661327e-01 3.830663e-01 -7.661327e-01 -5.000000e-01 3.600000e+00 7.678200e-01 7.678200e-01 3.839100e-01 -7.678200e-01 -4.000000e-01 3.600000e+00 7.692033e-01 7.692033e-01 3.846017e-01 -7.692033e-01 -3.000000e-01 3.600000e+00 7.702810e-01 7.702810e-01 3.851405e-01 -7.702810e-01 -2.000000e-01 3.600000e+00 7.710516e-01 7.710516e-01 3.855258e-01 -7.710516e-01 -1.000000e-01 3.600000e+00 7.715144e-01 7.715144e-01 3.857572e-01 -7.715144e-01 0.000000e+00 3.600000e+00 7.716687e-01 7.716687e-01 3.858343e-01 -7.716687e-01 1.000000e-01 3.600000e+00 7.715144e-01 7.715144e-01 3.857572e-01 -7.715144e-01 2.000000e-01 3.600000e+00 7.710516e-01 7.710516e-01 3.855258e-01 -7.710516e-01 3.000000e-01 3.600000e+00 7.702810e-01 7.702810e-01 3.851405e-01 -7.702810e-01 4.000000e-01 3.600000e+00 7.692033e-01 7.692033e-01 3.846017e-01 -7.692033e-01 5.000000e-01 3.600000e+00 7.678200e-01 7.678200e-01 3.839100e-01 -7.678200e-01 6.000000e-01 3.600000e+00 7.661327e-01 7.661327e-01 3.830663e-01 -7.661327e-01 7.000000e-01 3.600000e+00 7.641433e-01 7.641433e-01 3.820716e-01 -7.641433e-01 8.000000e-01 3.600000e+00 7.618543e-01 7.618543e-01 3.809271e-01 -7.618543e-01 9.000000e-01 3.600000e+00 7.592683e-01 7.592683e-01 3.796342e-01 -7.592683e-01 1.000000e+00 3.600000e+00 7.563886e-01 7.563886e-01 3.781943e-01 -7.563886e-01 1.100000e+00 3.600000e+00 7.532185e-01 7.532185e-01 3.766092e-01 -7.532185e-01 1.200000e+00 3.600000e+00 7.497616e-01 7.497616e-01 3.748808e-01 -7.497616e-01 1.300000e+00 3.600000e+00 7.460222e-01 7.460222e-01 3.730111e-01 -7.460222e-01 1.400000e+00 3.600000e+00 7.420045e-01 7.420045e-01 3.710023e-01 -7.420045e-01 1.500000e+00 3.600000e+00 7.377133e-01 7.377133e-01 3.688567e-01 -7.377133e-01 1.600000e+00 3.600000e+00 7.331536e-01 7.331536e-01 3.665768e-01 -7.331536e-01 1.700000e+00 3.600000e+00 7.283308e-01 7.283308e-01 3.641654e-01 -7.283308e-01 1.800000e+00 3.600000e+00 7.232503e-01 7.232503e-01 3.616251e-01 -7.232503e-01 1.900000e+00 3.600000e+00 7.179180e-01 7.179180e-01 3.589590e-01 -7.179180e-01 2.000000e+00 3.600000e+00 7.123400e-01 7.123400e-01 3.561700e-01 -7.123400e-01 2.100000e+00 3.600000e+00 7.065227e-01 7.065227e-01 3.532614e-01 -7.065227e-01 2.200000e+00 3.600000e+00 7.004727e-01 7.004727e-01 3.502363e-01 -7.004727e-01 2.300000e+00 3.600000e+00 6.941967e-01 6.941967e-01 3.470984e-01 -6.941967e-01 2.400000e+00 3.600000e+00 6.877018e-01 6.877018e-01 3.438509e-01 -6.877018e-01 2.500000e+00 3.600000e+00 6.809952e-01 6.809952e-01 3.404976e-01 -6.809952e-01 2.600000e+00 3.600000e+00 6.740844e-01 6.740844e-01 3.370422e-01 -6.740844e-01 2.700000e+00 3.600000e+00 6.669768e-01 6.669768e-01 3.334884e-01 -6.669768e-01 2.800000e+00 3.600000e+00 6.596803e-01 6.596803e-01 3.298402e-01 -6.596803e-01 2.900000e+00 3.600000e+00 6.522026e-01 6.522026e-01 3.261013e-01 -6.522026e-01 3.000000e+00 3.600000e+00 6.445519e-01 6.445519e-01 3.222759e-01 -6.445519e-01 3.100000e+00 3.600000e+00 6.367361e-01 6.367361e-01 3.183680e-01 -6.367361e-01 3.200000e+00 3.600000e+00 6.287636e-01 6.287636e-01 3.143818e-01 -6.287636e-01 3.300000e+00 3.600000e+00 6.206425e-01 6.206425e-01 3.103213e-01 -6.206425e-01 3.400000e+00 3.600000e+00 6.123814e-01 6.123814e-01 3.061907e-01 -6.123814e-01 3.500000e+00 3.600000e+00 6.039886e-01 6.039886e-01 3.019943e-01 -6.039886e-01 3.600000e+00 3.600000e+00 5.954726e-01 5.954726e-01 2.977363e-01 -5.954726e-01 3.700000e+00 3.600000e+00 5.868418e-01 5.868418e-01 2.934209e-01 -5.868418e-01 3.800000e+00 3.600000e+00 5.781049e-01 5.781049e-01 2.890524e-01 -5.781049e-01 3.900000e+00 3.600000e+00 5.692703e-01 5.692703e-01 2.846351e-01 -5.692703e-01 4.000000e+00 3.600000e+00 5.603464e-01 5.603464e-01 2.801732e-01 -5.603464e-01 4.100000e+00 3.600000e+00 5.513420e-01 5.513420e-01 2.756710e-01 -5.513420e-01 4.200000e+00 3.600000e+00 5.422652e-01 5.422652e-01 2.711326e-01 -5.422652e-01 4.300000e+00 3.600000e+00 5.331247e-01 5.331247e-01 2.665623e-01 -5.331247e-01 4.400000e+00 3.600000e+00 5.239285e-01 5.239285e-01 2.619643e-01 -5.239285e-01 4.500000e+00 3.600000e+00 5.146852e-01 5.146852e-01 2.573426e-01 -5.146852e-01 4.600000e+00 3.600000e+00 5.054026e-01 5.054026e-01 2.527013e-01 -5.054026e-01 4.700000e+00 3.600000e+00 4.960890e-01 4.960890e-01 2.480445e-01 -4.960890e-01 4.800000e+00 3.600000e+00 4.867522e-01 4.867522e-01 2.433761e-01 -4.867522e-01 4.900000e+00 3.600000e+00 4.774002e-01 4.774002e-01 2.387001e-01 -4.774002e-01 -5.000000e+00 3.700000e+00 4.612570e-01 4.612570e-01 2.306285e-01 -4.612570e-01 -4.900000e+00 3.700000e+00 4.704808e-01 4.704808e-01 2.352404e-01 -4.704808e-01 -4.800000e+00 3.700000e+00 4.796973e-01 4.796973e-01 2.398486e-01 -4.796973e-01 -4.700000e+00 3.700000e+00 4.888987e-01 4.888987e-01 2.444493e-01 -4.888987e-01 -4.600000e+00 3.700000e+00 4.980773e-01 4.980773e-01 2.490387e-01 -4.980773e-01 -4.500000e+00 3.700000e+00 5.072253e-01 5.072253e-01 2.536126e-01 -5.072253e-01 -4.400000e+00 3.700000e+00 5.163347e-01 5.163347e-01 2.581674e-01 -5.163347e-01 -4.300000e+00 3.700000e+00 5.253976e-01 5.253976e-01 2.626988e-01 -5.253976e-01 -4.200000e+00 3.700000e+00 5.344057e-01 5.344057e-01 2.672029e-01 -5.344057e-01 -4.100000e+00 3.700000e+00 5.433509e-01 5.433509e-01 2.716754e-01 -5.433509e-01 -4.000000e+00 3.700000e+00 5.522248e-01 5.522248e-01 2.761124e-01 -5.522248e-01 -3.900000e+00 3.700000e+00 5.610192e-01 5.610192e-01 2.805096e-01 -5.610192e-01 -3.800000e+00 3.700000e+00 5.697258e-01 5.697258e-01 2.848629e-01 -5.697258e-01 -3.700000e+00 3.700000e+00 5.783361e-01 5.783361e-01 2.891681e-01 -5.783361e-01 -3.600000e+00 3.700000e+00 5.868418e-01 5.868418e-01 2.934209e-01 -5.868418e-01 -3.500000e+00 3.700000e+00 5.952344e-01 5.952344e-01 2.976172e-01 -5.952344e-01 -3.400000e+00 3.700000e+00 6.035056e-01 6.035056e-01 3.017528e-01 -6.035056e-01 -3.300000e+00 3.700000e+00 6.116470e-01 6.116470e-01 3.058235e-01 -6.116470e-01 -3.200000e+00 3.700000e+00 6.196503e-01 6.196503e-01 3.098252e-01 -6.196503e-01 -3.100000e+00 3.700000e+00 6.275073e-01 6.275073e-01 3.137536e-01 -6.275073e-01 -3.000000e+00 3.700000e+00 6.352097e-01 6.352097e-01 3.176049e-01 -6.352097e-01 -2.900000e+00 3.700000e+00 6.427496e-01 6.427496e-01 3.213748e-01 -6.427496e-01 -2.800000e+00 3.700000e+00 6.501189e-01 6.501189e-01 3.250594e-01 -6.501189e-01 -2.700000e+00 3.700000e+00 6.573097e-01 6.573097e-01 3.286549e-01 -6.573097e-01 -2.600000e+00 3.700000e+00 6.643142e-01 6.643142e-01 3.321571e-01 -6.643142e-01 -2.500000e+00 3.700000e+00 6.711249e-01 6.711249e-01 3.355624e-01 -6.711249e-01 -2.400000e+00 3.700000e+00 6.777343e-01 6.777343e-01 3.388671e-01 -6.777343e-01 -2.300000e+00 3.700000e+00 6.841350e-01 6.841350e-01 3.420675e-01 -6.841350e-01 -2.200000e+00 3.700000e+00 6.903200e-01 6.903200e-01 3.451600e-01 -6.903200e-01 -2.100000e+00 3.700000e+00 6.962823e-01 6.962823e-01 3.481412e-01 -6.962823e-01 -2.000000e+00 3.700000e+00 7.020153e-01 7.020153e-01 3.510077e-01 -7.020153e-01 -1.900000e+00 3.700000e+00 7.075125e-01 7.075125e-01 3.537562e-01 -7.075125e-01 -1.800000e+00 3.700000e+00 7.127675e-01 7.127675e-01 3.563837e-01 -7.127675e-01 -1.700000e+00 3.700000e+00 7.177744e-01 7.177744e-01 3.588872e-01 -7.177744e-01 -1.600000e+00 3.700000e+00 7.225273e-01 7.225273e-01 3.612637e-01 -7.225273e-01 -1.500000e+00 3.700000e+00 7.270209e-01 7.270209e-01 3.635105e-01 -7.270209e-01 -1.400000e+00 3.700000e+00 7.312499e-01 7.312499e-01 3.656249e-01 -7.312499e-01 -1.300000e+00 3.700000e+00 7.352093e-01 7.352093e-01 3.676047e-01 -7.352093e-01 -1.200000e+00 3.700000e+00 7.388946e-01 7.388946e-01 3.694473e-01 -7.388946e-01 -1.100000e+00 3.700000e+00 7.423013e-01 7.423013e-01 3.711507e-01 -7.423013e-01 -1.000000e+00 3.700000e+00 7.454255e-01 7.454255e-01 3.727128e-01 -7.454255e-01 -9.000000e-01 3.700000e+00 7.482635e-01 7.482635e-01 3.741318e-01 -7.482635e-01 -8.000000e-01 3.700000e+00 7.508120e-01 7.508120e-01 3.754060e-01 -7.508120e-01 -7.000000e-01 3.700000e+00 7.530678e-01 7.530678e-01 3.765339e-01 -7.530678e-01 -6.000000e-01 3.700000e+00 7.550283e-01 7.550283e-01 3.775142e-01 -7.550283e-01 -5.000000e-01 3.700000e+00 7.566912e-01 7.566912e-01 3.783456e-01 -7.566912e-01 -4.000000e-01 3.700000e+00 7.580545e-01 7.580545e-01 3.790272e-01 -7.580545e-01 -3.000000e-01 3.700000e+00 7.591165e-01 7.591165e-01 3.795583e-01 -7.591165e-01 -2.000000e-01 3.700000e+00 7.598760e-01 7.598760e-01 3.799380e-01 -7.598760e-01 -1.000000e-01 3.700000e+00 7.603320e-01 7.603320e-01 3.801660e-01 -7.603320e-01 0.000000e+00 3.700000e+00 7.604842e-01 7.604842e-01 3.802421e-01 -7.604842e-01 1.000000e-01 3.700000e+00 7.603320e-01 7.603320e-01 3.801660e-01 -7.603320e-01 2.000000e-01 3.700000e+00 7.598760e-01 7.598760e-01 3.799380e-01 -7.598760e-01 3.000000e-01 3.700000e+00 7.591165e-01 7.591165e-01 3.795583e-01 -7.591165e-01 4.000000e-01 3.700000e+00 7.580545e-01 7.580545e-01 3.790272e-01 -7.580545e-01 5.000000e-01 3.700000e+00 7.566912e-01 7.566912e-01 3.783456e-01 -7.566912e-01 6.000000e-01 3.700000e+00 7.550283e-01 7.550283e-01 3.775142e-01 -7.550283e-01 7.000000e-01 3.700000e+00 7.530678e-01 7.530678e-01 3.765339e-01 -7.530678e-01 8.000000e-01 3.700000e+00 7.508120e-01 7.508120e-01 3.754060e-01 -7.508120e-01 9.000000e-01 3.700000e+00 7.482635e-01 7.482635e-01 3.741318e-01 -7.482635e-01 1.000000e+00 3.700000e+00 7.454255e-01 7.454255e-01 3.727128e-01 -7.454255e-01 1.100000e+00 3.700000e+00 7.423013e-01 7.423013e-01 3.711507e-01 -7.423013e-01 1.200000e+00 3.700000e+00 7.388946e-01 7.388946e-01 3.694473e-01 -7.388946e-01 1.300000e+00 3.700000e+00 7.352093e-01 7.352093e-01 3.676047e-01 -7.352093e-01 1.400000e+00 3.700000e+00 7.312499e-01 7.312499e-01 3.656249e-01 -7.312499e-01 1.500000e+00 3.700000e+00 7.270209e-01 7.270209e-01 3.635105e-01 -7.270209e-01 1.600000e+00 3.700000e+00 7.225273e-01 7.225273e-01 3.612637e-01 -7.225273e-01 1.700000e+00 3.700000e+00 7.177744e-01 7.177744e-01 3.588872e-01 -7.177744e-01 1.800000e+00 3.700000e+00 7.127675e-01 7.127675e-01 3.563837e-01 -7.127675e-01 1.900000e+00 3.700000e+00 7.075125e-01 7.075125e-01 3.537562e-01 -7.075125e-01 2.000000e+00 3.700000e+00 7.020153e-01 7.020153e-01 3.510077e-01 -7.020153e-01 2.100000e+00 3.700000e+00 6.962823e-01 6.962823e-01 3.481412e-01 -6.962823e-01 2.200000e+00 3.700000e+00 6.903200e-01 6.903200e-01 3.451600e-01 -6.903200e-01 2.300000e+00 3.700000e+00 6.841350e-01 6.841350e-01 3.420675e-01 -6.841350e-01 2.400000e+00 3.700000e+00 6.777343e-01 6.777343e-01 3.388671e-01 -6.777343e-01 2.500000e+00 3.700000e+00 6.711249e-01 6.711249e-01 3.355624e-01 -6.711249e-01 2.600000e+00 3.700000e+00 6.643142e-01 6.643142e-01 3.321571e-01 -6.643142e-01 2.700000e+00 3.700000e+00 6.573097e-01 6.573097e-01 3.286549e-01 -6.573097e-01 2.800000e+00 3.700000e+00 6.501189e-01 6.501189e-01 3.250594e-01 -6.501189e-01 2.900000e+00 3.700000e+00 6.427496e-01 6.427496e-01 3.213748e-01 -6.427496e-01 3.000000e+00 3.700000e+00 6.352097e-01 6.352097e-01 3.176049e-01 -6.352097e-01 3.100000e+00 3.700000e+00 6.275073e-01 6.275073e-01 3.137536e-01 -6.275073e-01 3.200000e+00 3.700000e+00 6.196503e-01 6.196503e-01 3.098252e-01 -6.196503e-01 3.300000e+00 3.700000e+00 6.116470e-01 6.116470e-01 3.058235e-01 -6.116470e-01 3.400000e+00 3.700000e+00 6.035056e-01 6.035056e-01 3.017528e-01 -6.035056e-01 3.500000e+00 3.700000e+00 5.952344e-01 5.952344e-01 2.976172e-01 -5.952344e-01 3.600000e+00 3.700000e+00 5.868418e-01 5.868418e-01 2.934209e-01 -5.868418e-01 3.700000e+00 3.700000e+00 5.783361e-01 5.783361e-01 2.891681e-01 -5.783361e-01 3.800000e+00 3.700000e+00 5.697258e-01 5.697258e-01 2.848629e-01 -5.697258e-01 3.900000e+00 3.700000e+00 5.610192e-01 5.610192e-01 2.805096e-01 -5.610192e-01 4.000000e+00 3.700000e+00 5.522248e-01 5.522248e-01 2.761124e-01 -5.522248e-01 4.100000e+00 3.700000e+00 5.433509e-01 5.433509e-01 2.716754e-01 -5.433509e-01 4.200000e+00 3.700000e+00 5.344057e-01 5.344057e-01 2.672029e-01 -5.344057e-01 4.300000e+00 3.700000e+00 5.253976e-01 5.253976e-01 2.626988e-01 -5.253976e-01 4.400000e+00 3.700000e+00 5.163347e-01 5.163347e-01 2.581674e-01 -5.163347e-01 4.500000e+00 3.700000e+00 5.072253e-01 5.072253e-01 2.536126e-01 -5.072253e-01 4.600000e+00 3.700000e+00 4.980773e-01 4.980773e-01 2.490387e-01 -4.980773e-01 4.700000e+00 3.700000e+00 4.888987e-01 4.888987e-01 2.444493e-01 -4.888987e-01 4.800000e+00 3.700000e+00 4.796973e-01 4.796973e-01 2.398486e-01 -4.796973e-01 4.900000e+00 3.700000e+00 4.704808e-01 4.704808e-01 2.352404e-01 -4.704808e-01 -5.000000e+00 3.800000e+00 4.543897e-01 4.543897e-01 2.271949e-01 -4.543897e-01 -4.900000e+00 3.800000e+00 4.634763e-01 4.634763e-01 2.317382e-01 -4.634763e-01 -4.800000e+00 3.800000e+00 4.725555e-01 4.725555e-01 2.362778e-01 -4.725555e-01 -4.700000e+00 3.800000e+00 4.816200e-01 4.816200e-01 2.408100e-01 -4.816200e-01 -4.600000e+00 3.800000e+00 4.906619e-01 4.906619e-01 2.453310e-01 -4.906619e-01 -4.500000e+00 3.800000e+00 4.996737e-01 4.996737e-01 2.498369e-01 -4.996737e-01 -4.400000e+00 3.800000e+00 5.086475e-01 5.086475e-01 2.543238e-01 -5.086475e-01 -4.300000e+00 3.800000e+00 5.175754e-01 5.175754e-01 2.587877e-01 -5.175754e-01 -4.200000e+00 3.800000e+00 5.264494e-01 5.264494e-01 2.632247e-01 -5.264494e-01 -4.100000e+00 3.800000e+00 5.352615e-01 5.352615e-01 2.676307e-01 -5.352615e-01 -4.000000e+00 3.800000e+00 5.440032e-01 5.440032e-01 2.720016e-01 -5.440032e-01 -3.900000e+00 3.800000e+00 5.526668e-01 5.526668e-01 2.763334e-01 -5.526668e-01 -3.800000e+00 3.800000e+00 5.612437e-01 5.612437e-01 2.806219e-01 -5.612437e-01 -3.700000e+00 3.800000e+00 5.697258e-01 5.697258e-01 2.848629e-01 -5.697258e-01 -3.600000e+00 3.800000e+00 5.781049e-01 5.781049e-01 2.890524e-01 -5.781049e-01 -3.500000e+00 3.800000e+00 5.863725e-01 5.863725e-01 2.931862e-01 -5.863725e-01 -3.400000e+00 3.800000e+00 5.945206e-01 5.945206e-01 2.972603e-01 -5.945206e-01 -3.300000e+00 3.800000e+00 6.025407e-01 6.025407e-01 3.012704e-01 -6.025407e-01 -3.200000e+00 3.800000e+00 6.104249e-01 6.104249e-01 3.052124e-01 -6.104249e-01 -3.100000e+00 3.800000e+00 6.181649e-01 6.181649e-01 3.090824e-01 -6.181649e-01 -3.000000e+00 3.800000e+00 6.257527e-01 6.257527e-01 3.128763e-01 -6.257527e-01 -2.900000e+00 3.800000e+00 6.331803e-01 6.331803e-01 3.165902e-01 -6.331803e-01 -2.800000e+00 3.800000e+00 6.404399e-01 6.404399e-01 3.202199e-01 -6.404399e-01 -2.700000e+00 3.800000e+00 6.475236e-01 6.475236e-01 3.237618e-01 -6.475236e-01 -2.600000e+00 3.800000e+00 6.544239e-01 6.544239e-01 3.272119e-01 -6.544239e-01 -2.500000e+00 3.800000e+00 6.611332e-01 6.611332e-01 3.305666e-01 -6.611332e-01 -2.400000e+00 3.800000e+00 6.676441e-01 6.676441e-01 3.338220e-01 -6.676441e-01 -2.300000e+00 3.800000e+00 6.739496e-01 6.739496e-01 3.369748e-01 -6.739496e-01 -2.200000e+00 3.800000e+00 6.800425e-01 6.800425e-01 3.400213e-01 -6.800425e-01 -2.100000e+00 3.800000e+00 6.859161e-01 6.859161e-01 3.429580e-01 -6.859161e-01 -2.000000e+00 3.800000e+00 6.915637e-01 6.915637e-01 3.457819e-01 -6.915637e-01 -1.900000e+00 3.800000e+00 6.969790e-01 6.969790e-01 3.484895e-01 -6.969790e-01 -1.800000e+00 3.800000e+00 7.021558e-01 7.021558e-01 3.510779e-01 -7.021558e-01 -1.700000e+00 3.800000e+00 7.070881e-01 7.070881e-01 3.535441e-01 -7.070881e-01 -1.600000e+00 3.800000e+00 7.117703e-01 7.117703e-01 3.558851e-01 -7.117703e-01 -1.500000e+00 3.800000e+00 7.161970e-01 7.161970e-01 3.580985e-01 -7.161970e-01 -1.400000e+00 3.800000e+00 7.203630e-01 7.203630e-01 3.601815e-01 -7.203630e-01 -1.300000e+00 3.800000e+00 7.242635e-01 7.242635e-01 3.621317e-01 -7.242635e-01 -1.200000e+00 3.800000e+00 7.278939e-01 7.278939e-01 3.639469e-01 -7.278939e-01 -1.100000e+00 3.800000e+00 7.312499e-01 7.312499e-01 3.656250e-01 -7.312499e-01 -1.000000e+00 3.800000e+00 7.343276e-01 7.343276e-01 3.671638e-01 -7.343276e-01 -9.000000e-01 3.800000e+00 7.371234e-01 7.371234e-01 3.685617e-01 -7.371234e-01 -8.000000e-01 3.800000e+00 7.396339e-01 7.396339e-01 3.698169e-01 -7.396339e-01 -7.000000e-01 3.800000e+00 7.418561e-01 7.418561e-01 3.709280e-01 -7.418561e-01 -6.000000e-01 3.800000e+00 7.437874e-01 7.437874e-01 3.718937e-01 -7.437874e-01 -5.000000e-01 3.800000e+00 7.454256e-01 7.454256e-01 3.727128e-01 -7.454256e-01 -4.000000e-01 3.800000e+00 7.467685e-01 7.467685e-01 3.733843e-01 -7.467685e-01 -3.000000e-01 3.800000e+00 7.478147e-01 7.478147e-01 3.739074e-01 -7.478147e-01 -2.000000e-01 3.800000e+00 7.485629e-01 7.485629e-01 3.742815e-01 -7.485629e-01 -1.000000e-01 3.800000e+00 7.490122e-01 7.490122e-01 3.745061e-01 -7.490122e-01 0.000000e+00 3.800000e+00 7.491620e-01 7.491620e-01 3.745810e-01 -7.491620e-01 1.000000e-01 3.800000e+00 7.490122e-01 7.490122e-01 3.745061e-01 -7.490122e-01 2.000000e-01 3.800000e+00 7.485629e-01 7.485629e-01 3.742815e-01 -7.485629e-01 3.000000e-01 3.800000e+00 7.478147e-01 7.478147e-01 3.739074e-01 -7.478147e-01 4.000000e-01 3.800000e+00 7.467685e-01 7.467685e-01 3.733843e-01 -7.467685e-01 5.000000e-01 3.800000e+00 7.454256e-01 7.454256e-01 3.727128e-01 -7.454256e-01 6.000000e-01 3.800000e+00 7.437874e-01 7.437874e-01 3.718937e-01 -7.437874e-01 7.000000e-01 3.800000e+00 7.418561e-01 7.418561e-01 3.709280e-01 -7.418561e-01 8.000000e-01 3.800000e+00 7.396339e-01 7.396339e-01 3.698169e-01 -7.396339e-01 9.000000e-01 3.800000e+00 7.371234e-01 7.371234e-01 3.685617e-01 -7.371234e-01 1.000000e+00 3.800000e+00 7.343276e-01 7.343276e-01 3.671638e-01 -7.343276e-01 1.100000e+00 3.800000e+00 7.312499e-01 7.312499e-01 3.656250e-01 -7.312499e-01 1.200000e+00 3.800000e+00 7.278939e-01 7.278939e-01 3.639469e-01 -7.278939e-01 1.300000e+00 3.800000e+00 7.242635e-01 7.242635e-01 3.621317e-01 -7.242635e-01 1.400000e+00 3.800000e+00 7.203630e-01 7.203630e-01 3.601815e-01 -7.203630e-01 1.500000e+00 3.800000e+00 7.161970e-01 7.161970e-01 3.580985e-01 -7.161970e-01 1.600000e+00 3.800000e+00 7.117703e-01 7.117703e-01 3.558851e-01 -7.117703e-01 1.700000e+00 3.800000e+00 7.070881e-01 7.070881e-01 3.535441e-01 -7.070881e-01 1.800000e+00 3.800000e+00 7.021558e-01 7.021558e-01 3.510779e-01 -7.021558e-01 1.900000e+00 3.800000e+00 6.969790e-01 6.969790e-01 3.484895e-01 -6.969790e-01 2.000000e+00 3.800000e+00 6.915637e-01 6.915637e-01 3.457819e-01 -6.915637e-01 2.100000e+00 3.800000e+00 6.859161e-01 6.859161e-01 3.429580e-01 -6.859161e-01 2.200000e+00 3.800000e+00 6.800425e-01 6.800425e-01 3.400213e-01 -6.800425e-01 2.300000e+00 3.800000e+00 6.739496e-01 6.739496e-01 3.369748e-01 -6.739496e-01 2.400000e+00 3.800000e+00 6.676441e-01 6.676441e-01 3.338220e-01 -6.676441e-01 2.500000e+00 3.800000e+00 6.611332e-01 6.611332e-01 3.305666e-01 -6.611332e-01 2.600000e+00 3.800000e+00 6.544239e-01 6.544239e-01 3.272119e-01 -6.544239e-01 2.700000e+00 3.800000e+00 6.475236e-01 6.475236e-01 3.237618e-01 -6.475236e-01 2.800000e+00 3.800000e+00 6.404399e-01 6.404399e-01 3.202199e-01 -6.404399e-01 2.900000e+00 3.800000e+00 6.331803e-01 6.331803e-01 3.165902e-01 -6.331803e-01 3.000000e+00 3.800000e+00 6.257527e-01 6.257527e-01 3.128763e-01 -6.257527e-01 3.100000e+00 3.800000e+00 6.181649e-01 6.181649e-01 3.090824e-01 -6.181649e-01 3.200000e+00 3.800000e+00 6.104249e-01 6.104249e-01 3.052124e-01 -6.104249e-01 3.300000e+00 3.800000e+00 6.025407e-01 6.025407e-01 3.012704e-01 -6.025407e-01 3.400000e+00 3.800000e+00 5.945206e-01 5.945206e-01 2.972603e-01 -5.945206e-01 3.500000e+00 3.800000e+00 5.863725e-01 5.863725e-01 2.931862e-01 -5.863725e-01 3.600000e+00 3.800000e+00 5.781049e-01 5.781049e-01 2.890524e-01 -5.781049e-01 3.700000e+00 3.800000e+00 5.697258e-01 5.697258e-01 2.848629e-01 -5.697258e-01 3.800000e+00 3.800000e+00 5.612437e-01 5.612437e-01 2.806219e-01 -5.612437e-01 3.900000e+00 3.800000e+00 5.526668e-01 5.526668e-01 2.763334e-01 -5.526668e-01 4.000000e+00 3.800000e+00 5.440032e-01 5.440032e-01 2.720016e-01 -5.440032e-01 4.100000e+00 3.800000e+00 5.352615e-01 5.352615e-01 2.676307e-01 -5.352615e-01 4.200000e+00 3.800000e+00 5.264494e-01 5.264494e-01 2.632247e-01 -5.264494e-01 4.300000e+00 3.800000e+00 5.175754e-01 5.175754e-01 2.587877e-01 -5.175754e-01 4.400000e+00 3.800000e+00 5.086475e-01 5.086475e-01 2.543238e-01 -5.086475e-01 4.500000e+00 3.800000e+00 4.996737e-01 4.996737e-01 2.498369e-01 -4.996737e-01 4.600000e+00 3.800000e+00 4.906619e-01 4.906619e-01 2.453310e-01 -4.906619e-01 4.700000e+00 3.800000e+00 4.816200e-01 4.816200e-01 2.408100e-01 -4.816200e-01 4.800000e+00 3.800000e+00 4.725555e-01 4.725555e-01 2.362778e-01 -4.725555e-01 4.900000e+00 3.800000e+00 4.634763e-01 4.634763e-01 2.317382e-01 -4.634763e-01 -5.000000e+00 3.900000e+00 4.474457e-01 4.474457e-01 2.237229e-01 -4.474457e-01 -4.900000e+00 3.900000e+00 4.563934e-01 4.563934e-01 2.281967e-01 -4.563934e-01 -4.800000e+00 3.900000e+00 4.653339e-01 4.653339e-01 2.326670e-01 -4.653339e-01 -4.700000e+00 3.900000e+00 4.742598e-01 4.742598e-01 2.371299e-01 -4.742598e-01 -4.600000e+00 3.900000e+00 4.831636e-01 4.831636e-01 2.415818e-01 -4.831636e-01 -4.500000e+00 3.900000e+00 4.920377e-01 4.920377e-01 2.460188e-01 -4.920377e-01 -4.400000e+00 3.900000e+00 5.008743e-01 5.008743e-01 2.504372e-01 -5.008743e-01 -4.300000e+00 3.900000e+00 5.096658e-01 5.096658e-01 2.548329e-01 -5.096658e-01 -4.200000e+00 3.900000e+00 5.184042e-01 5.184042e-01 2.592021e-01 -5.184042e-01 -4.100000e+00 3.900000e+00 5.270815e-01 5.270815e-01 2.635408e-01 -5.270815e-01 -4.000000e+00 3.900000e+00 5.356898e-01 5.356898e-01 2.678449e-01 -5.356898e-01 -3.900000e+00 3.900000e+00 5.442209e-01 5.442209e-01 2.721105e-01 -5.442209e-01 -3.800000e+00 3.900000e+00 5.526668e-01 5.526668e-01 2.763334e-01 -5.526668e-01 -3.700000e+00 3.900000e+00 5.610192e-01 5.610192e-01 2.805096e-01 -5.610192e-01 -3.600000e+00 3.900000e+00 5.692703e-01 5.692703e-01 2.846351e-01 -5.692703e-01 -3.500000e+00 3.900000e+00 5.774115e-01 5.774115e-01 2.887058e-01 -5.774115e-01 -3.400000e+00 3.900000e+00 5.854350e-01 5.854350e-01 2.927175e-01 -5.854350e-01 -3.300000e+00 3.900000e+00 5.933327e-01 5.933327e-01 2.966664e-01 -5.933327e-01 -3.200000e+00 3.900000e+00 6.010964e-01 6.010964e-01 3.005482e-01 -6.010964e-01 -3.100000e+00 3.900000e+00 6.087181e-01 6.087181e-01 3.043590e-01 -6.087181e-01 -3.000000e+00 3.900000e+00 6.161900e-01 6.161900e-01 3.080950e-01 -6.161900e-01 -2.900000e+00 3.900000e+00 6.235040e-01 6.235040e-01 3.117520e-01 -6.235040e-01 -2.800000e+00 3.900000e+00 6.306527e-01 6.306527e-01 3.153263e-01 -6.306527e-01 -2.700000e+00 3.900000e+00 6.376281e-01 6.376281e-01 3.188141e-01 -6.376281e-01 -2.600000e+00 3.900000e+00 6.444229e-01 6.444229e-01 3.222115e-01 -6.444229e-01 -2.500000e+00 3.900000e+00 6.510297e-01 6.510297e-01 3.255149e-01 -6.510297e-01 -2.400000e+00 3.900000e+00 6.574411e-01 6.574411e-01 3.287206e-01 -6.574411e-01 -2.300000e+00 3.900000e+00 6.636502e-01 6.636502e-01 3.318251e-01 -6.636502e-01 -2.200000e+00 3.900000e+00 6.696500e-01 6.696500e-01 3.348250e-01 -6.696500e-01 -2.100000e+00 3.900000e+00 6.754339e-01 6.754339e-01 3.377169e-01 -6.754339e-01 -2.000000e+00 3.900000e+00 6.809952e-01 6.809952e-01 3.404976e-01 -6.809952e-01 -1.900000e+00 3.900000e+00 6.863278e-01 6.863278e-01 3.431639e-01 -6.863278e-01 -1.800000e+00 3.900000e+00 6.914254e-01 6.914254e-01 3.457127e-01 -6.914254e-01 -1.700000e+00 3.900000e+00 6.962823e-01 6.962823e-01 3.481412e-01 -6.962823e-01 -1.600000e+00 3.900000e+00 7.008930e-01 7.008930e-01 3.504465e-01 -7.008930e-01 -1.500000e+00 3.900000e+00 7.052521e-01 7.052521e-01 3.526260e-01 -7.052521e-01 -1.400000e+00 3.900000e+00 7.093544e-01 7.093544e-01 3.546772e-01 -7.093544e-01 -1.300000e+00 3.900000e+00 7.131953e-01 7.131953e-01 3.565976e-01 -7.131953e-01 -1.200000e+00 3.900000e+00 7.167702e-01 7.167702e-01 3.583851e-01 -7.167702e-01 -1.100000e+00 3.900000e+00 7.200749e-01 7.200749e-01 3.600374e-01 -7.200749e-01 -1.000000e+00 3.900000e+00 7.231056e-01 7.231056e-01 3.615528e-01 -7.231056e-01 -9.000000e-01 3.900000e+00 7.258586e-01 7.258586e-01 3.629293e-01 -7.258586e-01 -8.000000e-01 3.900000e+00 7.283307e-01 7.283307e-01 3.641654e-01 -7.283307e-01 -7.000000e-01 3.900000e+00 7.305190e-01 7.305190e-01 3.652595e-01 -7.305190e-01 -6.000000e-01 3.900000e+00 7.324208e-01 7.324208e-01 3.662104e-01 -7.324208e-01 -5.000000e-01 3.900000e+00 7.340339e-01 7.340339e-01 3.670170e-01 -7.340339e-01 -4.000000e-01 3.900000e+00 7.353564e-01 7.353564e-01 3.676782e-01 -7.353564e-01 -3.000000e-01 3.900000e+00 7.363866e-01 7.363866e-01 3.681933e-01 -7.363866e-01 -2.000000e-01 3.900000e+00 7.371234e-01 7.371234e-01 3.685617e-01 -7.371234e-01 -1.000000e-01 3.900000e+00 7.375658e-01 7.375658e-01 3.687829e-01 -7.375658e-01 0.000000e+00 3.900000e+00 7.377133e-01 7.377133e-01 3.688566e-01 -7.377133e-01 1.000000e-01 3.900000e+00 7.375658e-01 7.375658e-01 3.687829e-01 -7.375658e-01 2.000000e-01 3.900000e+00 7.371234e-01 7.371234e-01 3.685617e-01 -7.371234e-01 3.000000e-01 3.900000e+00 7.363866e-01 7.363866e-01 3.681933e-01 -7.363866e-01 4.000000e-01 3.900000e+00 7.353564e-01 7.353564e-01 3.676782e-01 -7.353564e-01 5.000000e-01 3.900000e+00 7.340339e-01 7.340339e-01 3.670170e-01 -7.340339e-01 6.000000e-01 3.900000e+00 7.324208e-01 7.324208e-01 3.662104e-01 -7.324208e-01 7.000000e-01 3.900000e+00 7.305190e-01 7.305190e-01 3.652595e-01 -7.305190e-01 8.000000e-01 3.900000e+00 7.283307e-01 7.283307e-01 3.641654e-01 -7.283307e-01 9.000000e-01 3.900000e+00 7.258586e-01 7.258586e-01 3.629293e-01 -7.258586e-01 1.000000e+00 3.900000e+00 7.231056e-01 7.231056e-01 3.615528e-01 -7.231056e-01 1.100000e+00 3.900000e+00 7.200749e-01 7.200749e-01 3.600374e-01 -7.200749e-01 1.200000e+00 3.900000e+00 7.167702e-01 7.167702e-01 3.583851e-01 -7.167702e-01 1.300000e+00 3.900000e+00 7.131953e-01 7.131953e-01 3.565976e-01 -7.131953e-01 1.400000e+00 3.900000e+00 7.093544e-01 7.093544e-01 3.546772e-01 -7.093544e-01 1.500000e+00 3.900000e+00 7.052521e-01 7.052521e-01 3.526260e-01 -7.052521e-01 1.600000e+00 3.900000e+00 7.008930e-01 7.008930e-01 3.504465e-01 -7.008930e-01 1.700000e+00 3.900000e+00 6.962823e-01 6.962823e-01 3.481412e-01 -6.962823e-01 1.800000e+00 3.900000e+00 6.914254e-01 6.914254e-01 3.457127e-01 -6.914254e-01 1.900000e+00 3.900000e+00 6.863278e-01 6.863278e-01 3.431639e-01 -6.863278e-01 2.000000e+00 3.900000e+00 6.809952e-01 6.809952e-01 3.404976e-01 -6.809952e-01 2.100000e+00 3.900000e+00 6.754339e-01 6.754339e-01 3.377169e-01 -6.754339e-01 2.200000e+00 3.900000e+00 6.696500e-01 6.696500e-01 3.348250e-01 -6.696500e-01 2.300000e+00 3.900000e+00 6.636502e-01 6.636502e-01 3.318251e-01 -6.636502e-01 2.400000e+00 3.900000e+00 6.574411e-01 6.574411e-01 3.287206e-01 -6.574411e-01 2.500000e+00 3.900000e+00 6.510297e-01 6.510297e-01 3.255149e-01 -6.510297e-01 2.600000e+00 3.900000e+00 6.444229e-01 6.444229e-01 3.222115e-01 -6.444229e-01 2.700000e+00 3.900000e+00 6.376281e-01 6.376281e-01 3.188141e-01 -6.376281e-01 2.800000e+00 3.900000e+00 6.306527e-01 6.306527e-01 3.153263e-01 -6.306527e-01 2.900000e+00 3.900000e+00 6.235040e-01 6.235040e-01 3.117520e-01 -6.235040e-01 3.000000e+00 3.900000e+00 6.161900e-01 6.161900e-01 3.080950e-01 -6.161900e-01 3.100000e+00 3.900000e+00 6.087181e-01 6.087181e-01 3.043590e-01 -6.087181e-01 3.200000e+00 3.900000e+00 6.010964e-01 6.010964e-01 3.005482e-01 -6.010964e-01 3.300000e+00 3.900000e+00 5.933327e-01 5.933327e-01 2.966664e-01 -5.933327e-01 3.400000e+00 3.900000e+00 5.854350e-01 5.854350e-01 2.927175e-01 -5.854350e-01 3.500000e+00 3.900000e+00 5.774115e-01 5.774115e-01 2.887058e-01 -5.774115e-01 3.600000e+00 3.900000e+00 5.692703e-01 5.692703e-01 2.846351e-01 -5.692703e-01 3.700000e+00 3.900000e+00 5.610192e-01 5.610192e-01 2.805096e-01 -5.610192e-01 3.800000e+00 3.900000e+00 5.526668e-01 5.526668e-01 2.763334e-01 -5.526668e-01 3.900000e+00 3.900000e+00 5.442209e-01 5.442209e-01 2.721105e-01 -5.442209e-01 4.000000e+00 3.900000e+00 5.356898e-01 5.356898e-01 2.678449e-01 -5.356898e-01 4.100000e+00 3.900000e+00 5.270815e-01 5.270815e-01 2.635408e-01 -5.270815e-01 4.200000e+00 3.900000e+00 5.184042e-01 5.184042e-01 2.592021e-01 -5.184042e-01 4.300000e+00 3.900000e+00 5.096658e-01 5.096658e-01 2.548329e-01 -5.096658e-01 4.400000e+00 3.900000e+00 5.008743e-01 5.008743e-01 2.504372e-01 -5.008743e-01 4.500000e+00 3.900000e+00 4.920377e-01 4.920377e-01 2.460188e-01 -4.920377e-01 4.600000e+00 3.900000e+00 4.831636e-01 4.831636e-01 2.415818e-01 -4.831636e-01 4.700000e+00 3.900000e+00 4.742598e-01 4.742598e-01 2.371299e-01 -4.742598e-01 4.800000e+00 3.900000e+00 4.653339e-01 4.653339e-01 2.326670e-01 -4.653339e-01 4.900000e+00 3.900000e+00 4.563934e-01 4.563934e-01 2.281967e-01 -4.563934e-01 -5.000000e+00 4.000000e+00 4.404316e-01 4.404316e-01 2.202158e-01 -4.404316e-01 -4.900000e+00 4.000000e+00 4.492391e-01 4.492391e-01 2.246195e-01 -4.492391e-01 -4.800000e+00 4.000000e+00 4.580394e-01 4.580394e-01 2.290197e-01 -4.580394e-01 -4.700000e+00 4.000000e+00 4.668254e-01 4.668254e-01 2.334127e-01 -4.668254e-01 -4.600000e+00 4.000000e+00 4.755896e-01 4.755896e-01 2.377948e-01 -4.755896e-01 -4.500000e+00 4.000000e+00 4.843245e-01 4.843245e-01 2.421623e-01 -4.843245e-01 -4.400000e+00 4.000000e+00 4.930227e-01 4.930227e-01 2.465114e-01 -4.930227e-01 -4.300000e+00 4.000000e+00 5.016764e-01 5.016764e-01 2.508382e-01 -5.016764e-01 -4.200000e+00 4.000000e+00 5.102778e-01 5.102778e-01 2.551389e-01 -5.102778e-01 -4.100000e+00 4.000000e+00 5.188191e-01 5.188191e-01 2.594095e-01 -5.188191e-01 -4.000000e+00 4.000000e+00 5.272924e-01 5.272924e-01 2.636462e-01 -5.272924e-01 -3.900000e+00 4.000000e+00 5.356898e-01 5.356898e-01 2.678449e-01 -5.356898e-01 -3.800000e+00 4.000000e+00 5.440032e-01 5.440032e-01 2.720016e-01 -5.440032e-01 -3.700000e+00 4.000000e+00 5.522248e-01 5.522248e-01 2.761124e-01 -5.522248e-01 -3.600000e+00 4.000000e+00 5.603464e-01 5.603464e-01 2.801732e-01 -5.603464e-01 -3.500000e+00 4.000000e+00 5.683601e-01 5.683601e-01 2.841801e-01 -5.683601e-01 -3.400000e+00 4.000000e+00 5.762579e-01 5.762579e-01 2.881289e-01 -5.762579e-01 -3.300000e+00 4.000000e+00 5.840317e-01 5.840317e-01 2.920159e-01 -5.840317e-01 -3.200000e+00 4.000000e+00 5.916737e-01 5.916737e-01 2.958368e-01 -5.916737e-01 -3.100000e+00 4.000000e+00 5.991759e-01 5.991759e-01 2.995880e-01 -5.991759e-01 -3.000000e+00 4.000000e+00 6.065307e-01 6.065307e-01 3.032653e-01 -6.065307e-01 -2.900000e+00 4.000000e+00 6.137301e-01 6.137301e-01 3.068650e-01 -6.137301e-01 -2.800000e+00 4.000000e+00 6.207666e-01 6.207666e-01 3.103833e-01 -6.207666e-01 -2.700000e+00 4.000000e+00 6.276328e-01 6.276328e-01 3.138164e-01 -6.276328e-01 -2.600000e+00 4.000000e+00 6.343211e-01 6.343211e-01 3.171605e-01 -6.343211e-01 -2.500000e+00 4.000000e+00 6.408243e-01 6.408243e-01 3.204121e-01 -6.408243e-01 -2.400000e+00 4.000000e+00 6.471352e-01 6.471352e-01 3.235676e-01 -6.471352e-01 -2.300000e+00 4.000000e+00 6.532469e-01 6.532469e-01 3.266235e-01 -6.532469e-01 -2.200000e+00 4.000000e+00 6.591527e-01 6.591527e-01 3.295764e-01 -6.591527e-01 -2.100000e+00 4.000000e+00 6.648459e-01 6.648459e-01 3.324229e-01 -6.648459e-01 -2.000000e+00 4.000000e+00 6.703200e-01 6.703200e-01 3.351600e-01 -6.703200e-01 -1.900000e+00 4.000000e+00 6.755690e-01 6.755690e-01 3.377845e-01 -6.755690e-01 -1.800000e+00 4.000000e+00 6.805868e-01 6.805868e-01 3.402934e-01 -6.805868e-01 -1.700000e+00 4.000000e+00 6.853675e-01 6.853675e-01 3.426838e-01 -6.853675e-01 -1.600000e+00 4.000000e+00 6.899059e-01 6.899059e-01 3.449530e-01 -6.899059e-01 -1.500000e+00 4.000000e+00 6.941966e-01 6.941966e-01 3.470983e-01 -6.941966e-01 -1.400000e+00 4.000000e+00 6.982347e-01 6.982347e-01 3.491173e-01 -6.982347e-01 -1.300000e+00 4.000000e+00 7.020153e-01 7.020153e-01 3.510077e-01 -7.020153e-01 -1.200000e+00 4.000000e+00 7.055342e-01 7.055342e-01 3.527671e-01 -7.055342e-01 -1.100000e+00 4.000000e+00 7.087871e-01 7.087871e-01 3.543936e-01 -7.087871e-01 -1.000000e+00 4.000000e+00 7.117703e-01 7.117703e-01 3.558851e-01 -7.117703e-01 -9.000000e-01 4.000000e+00 7.144802e-01 7.144802e-01 3.572401e-01 -7.144802e-01 -8.000000e-01 4.000000e+00 7.169135e-01 7.169135e-01 3.584568e-01 -7.169135e-01 -7.000000e-01 4.000000e+00 7.190675e-01 7.190675e-01 3.595338e-01 -7.190675e-01 -6.000000e-01 4.000000e+00 7.209395e-01 7.209395e-01 3.604698e-01 -7.209395e-01 -5.000000e-01 4.000000e+00 7.225273e-01 7.225273e-01 3.612637e-01 -7.225273e-01 -4.000000e-01 4.000000e+00 7.238291e-01 7.238291e-01 3.619145e-01 -7.238291e-01 -3.000000e-01 4.000000e+00 7.248431e-01 7.248431e-01 3.624216e-01 -7.248431e-01 -2.000000e-01 4.000000e+00 7.255683e-01 7.255683e-01 3.627841e-01 -7.255683e-01 -1.000000e-01 4.000000e+00 7.260038e-01 7.260038e-01 3.630019e-01 -7.260038e-01 0.000000e+00 4.000000e+00 7.261490e-01 7.261490e-01 3.630745e-01 -7.261490e-01 1.000000e-01 4.000000e+00 7.260038e-01 7.260038e-01 3.630019e-01 -7.260038e-01 2.000000e-01 4.000000e+00 7.255683e-01 7.255683e-01 3.627841e-01 -7.255683e-01 3.000000e-01 4.000000e+00 7.248431e-01 7.248431e-01 3.624216e-01 -7.248431e-01 4.000000e-01 4.000000e+00 7.238291e-01 7.238291e-01 3.619145e-01 -7.238291e-01 5.000000e-01 4.000000e+00 7.225273e-01 7.225273e-01 3.612637e-01 -7.225273e-01 6.000000e-01 4.000000e+00 7.209395e-01 7.209395e-01 3.604698e-01 -7.209395e-01 7.000000e-01 4.000000e+00 7.190675e-01 7.190675e-01 3.595338e-01 -7.190675e-01 8.000000e-01 4.000000e+00 7.169135e-01 7.169135e-01 3.584568e-01 -7.169135e-01 9.000000e-01 4.000000e+00 7.144802e-01 7.144802e-01 3.572401e-01 -7.144802e-01 1.000000e+00 4.000000e+00 7.117703e-01 7.117703e-01 3.558851e-01 -7.117703e-01 1.100000e+00 4.000000e+00 7.087871e-01 7.087871e-01 3.543936e-01 -7.087871e-01 1.200000e+00 4.000000e+00 7.055342e-01 7.055342e-01 3.527671e-01 -7.055342e-01 1.300000e+00 4.000000e+00 7.020153e-01 7.020153e-01 3.510077e-01 -7.020153e-01 1.400000e+00 4.000000e+00 6.982347e-01 6.982347e-01 3.491173e-01 -6.982347e-01 1.500000e+00 4.000000e+00 6.941966e-01 6.941966e-01 3.470983e-01 -6.941966e-01 1.600000e+00 4.000000e+00 6.899059e-01 6.899059e-01 3.449530e-01 -6.899059e-01 1.700000e+00 4.000000e+00 6.853675e-01 6.853675e-01 3.426838e-01 -6.853675e-01 1.800000e+00 4.000000e+00 6.805868e-01 6.805868e-01 3.402934e-01 -6.805868e-01 1.900000e+00 4.000000e+00 6.755690e-01 6.755690e-01 3.377845e-01 -6.755690e-01 2.000000e+00 4.000000e+00 6.703200e-01 6.703200e-01 3.351600e-01 -6.703200e-01 2.100000e+00 4.000000e+00 6.648459e-01 6.648459e-01 3.324229e-01 -6.648459e-01 2.200000e+00 4.000000e+00 6.591527e-01 6.591527e-01 3.295764e-01 -6.591527e-01 2.300000e+00 4.000000e+00 6.532469e-01 6.532469e-01 3.266235e-01 -6.532469e-01 2.400000e+00 4.000000e+00 6.471352e-01 6.471352e-01 3.235676e-01 -6.471352e-01 2.500000e+00 4.000000e+00 6.408243e-01 6.408243e-01 3.204121e-01 -6.408243e-01 2.600000e+00 4.000000e+00 6.343211e-01 6.343211e-01 3.171605e-01 -6.343211e-01 2.700000e+00 4.000000e+00 6.276328e-01 6.276328e-01 3.138164e-01 -6.276328e-01 2.800000e+00 4.000000e+00 6.207666e-01 6.207666e-01 3.103833e-01 -6.207666e-01 2.900000e+00 4.000000e+00 6.137301e-01 6.137301e-01 3.068650e-01 -6.137301e-01 3.000000e+00 4.000000e+00 6.065307e-01 6.065307e-01 3.032653e-01 -6.065307e-01 3.100000e+00 4.000000e+00 5.991759e-01 5.991759e-01 2.995880e-01 -5.991759e-01 3.200000e+00 4.000000e+00 5.916737e-01 5.916737e-01 2.958368e-01 -5.916737e-01 3.300000e+00 4.000000e+00 5.840317e-01 5.840317e-01 2.920159e-01 -5.840317e-01 3.400000e+00 4.000000e+00 5.762579e-01 5.762579e-01 2.881289e-01 -5.762579e-01 3.500000e+00 4.000000e+00 5.683601e-01 5.683601e-01 2.841801e-01 -5.683601e-01 3.600000e+00 4.000000e+00 5.603464e-01 5.603464e-01 2.801732e-01 -5.603464e-01 3.700000e+00 4.000000e+00 5.522248e-01 5.522248e-01 2.761124e-01 -5.522248e-01 3.800000e+00 4.000000e+00 5.440032e-01 5.440032e-01 2.720016e-01 -5.440032e-01 3.900000e+00 4.000000e+00 5.356898e-01 5.356898e-01 2.678449e-01 -5.356898e-01 4.000000e+00 4.000000e+00 5.272924e-01 5.272924e-01 2.636462e-01 -5.272924e-01 4.100000e+00 4.000000e+00 5.188191e-01 5.188191e-01 2.594095e-01 -5.188191e-01 4.200000e+00 4.000000e+00 5.102778e-01 5.102778e-01 2.551389e-01 -5.102778e-01 4.300000e+00 4.000000e+00 5.016764e-01 5.016764e-01 2.508382e-01 -5.016764e-01 4.400000e+00 4.000000e+00 4.930227e-01 4.930227e-01 2.465114e-01 -4.930227e-01 4.500000e+00 4.000000e+00 4.843245e-01 4.843245e-01 2.421623e-01 -4.843245e-01 4.600000e+00 4.000000e+00 4.755896e-01 4.755896e-01 2.377948e-01 -4.755896e-01 4.700000e+00 4.000000e+00 4.668254e-01 4.668254e-01 2.334127e-01 -4.668254e-01 4.800000e+00 4.000000e+00 4.580394e-01 4.580394e-01 2.290197e-01 -4.580394e-01 4.900000e+00 4.000000e+00 4.492391e-01 4.492391e-01 2.246195e-01 -4.492391e-01 -5.000000e+00 4.100000e+00 4.333541e-01 4.333541e-01 2.166771e-01 -4.333541e-01 -4.900000e+00 4.100000e+00 4.420200e-01 4.420200e-01 2.210100e-01 -4.420200e-01 -4.800000e+00 4.100000e+00 4.506789e-01 4.506789e-01 2.253395e-01 -4.506789e-01 -4.700000e+00 4.100000e+00 4.593238e-01 4.593238e-01 2.296619e-01 -4.593238e-01 -4.600000e+00 4.100000e+00 4.679471e-01 4.679471e-01 2.339736e-01 -4.679471e-01 -4.500000e+00 4.100000e+00 4.765417e-01 4.765417e-01 2.382709e-01 -4.765417e-01 -4.400000e+00 4.100000e+00 4.851001e-01 4.851001e-01 2.425501e-01 -4.851001e-01 -4.300000e+00 4.100000e+00 4.936147e-01 4.936147e-01 2.468074e-01 -4.936147e-01 -4.200000e+00 4.100000e+00 5.020779e-01 5.020779e-01 2.510389e-01 -5.020779e-01 -4.100000e+00 4.100000e+00 5.104820e-01 5.104820e-01 2.552410e-01 -5.104820e-01 -4.000000e+00 4.100000e+00 5.188191e-01 5.188191e-01 2.594095e-01 -5.188191e-01 -3.900000e+00 4.100000e+00 5.270815e-01 5.270815e-01 2.635408e-01 -5.270815e-01 -3.800000e+00 4.100000e+00 5.352615e-01 5.352615e-01 2.676307e-01 -5.352615e-01 -3.700000e+00 4.100000e+00 5.433509e-01 5.433509e-01 2.716754e-01 -5.433509e-01 -3.600000e+00 4.100000e+00 5.513420e-01 5.513420e-01 2.756710e-01 -5.513420e-01 -3.500000e+00 4.100000e+00 5.592269e-01 5.592269e-01 2.796134e-01 -5.592269e-01 -3.400000e+00 4.100000e+00 5.669977e-01 5.669977e-01 2.834989e-01 -5.669977e-01 -3.300000e+00 4.100000e+00 5.746467e-01 5.746467e-01 2.873233e-01 -5.746467e-01 -3.200000e+00 4.100000e+00 5.821658e-01 5.821658e-01 2.910829e-01 -5.821658e-01 -3.100000e+00 4.100000e+00 5.895475e-01 5.895475e-01 2.947738e-01 -5.895475e-01 -3.000000e+00 4.100000e+00 5.967840e-01 5.967840e-01 2.983920e-01 -5.967840e-01 -2.900000e+00 4.100000e+00 6.038678e-01 6.038678e-01 3.019339e-01 -6.038678e-01 -2.800000e+00 4.100000e+00 6.107913e-01 6.107913e-01 3.053956e-01 -6.107913e-01 -2.700000e+00 4.100000e+00 6.175471e-01 6.175471e-01 3.087735e-01 -6.175471e-01 -2.600000e+00 4.100000e+00 6.241279e-01 6.241279e-01 3.120639e-01 -6.241279e-01 -2.500000e+00 4.100000e+00 6.305265e-01 6.305265e-01 3.152633e-01 -6.305265e-01 -2.400000e+00 4.100000e+00 6.367361e-01 6.367361e-01 3.183680e-01 -6.367361e-01 -2.300000e+00 4.100000e+00 6.427497e-01 6.427497e-01 3.213748e-01 -6.427497e-01 -2.200000e+00 4.100000e+00 6.485605e-01 6.485605e-01 3.242802e-01 -6.485605e-01 -2.100000e+00 4.100000e+00 6.541622e-01 6.541622e-01 3.270811e-01 -6.541622e-01 -2.000000e+00 4.100000e+00 6.595483e-01 6.595483e-01 3.297742e-01 -6.595483e-01 -1.900000e+00 4.100000e+00 6.647130e-01 6.647130e-01 3.323565e-01 -6.647130e-01 -1.800000e+00 4.100000e+00 6.696501e-01 6.696501e-01 3.348250e-01 -6.696501e-01 -1.700000e+00 4.100000e+00 6.743541e-01 6.743541e-01 3.371770e-01 -6.743541e-01 -1.600000e+00 4.100000e+00 6.788195e-01 6.788195e-01 3.394098e-01 -6.788195e-01 -1.500000e+00 4.100000e+00 6.830413e-01 6.830413e-01 3.415206e-01 -6.830413e-01 -1.400000e+00 4.100000e+00 6.870144e-01 6.870144e-01 3.435072e-01 -6.870144e-01 -1.300000e+00 4.100000e+00 6.907343e-01 6.907343e-01 3.453672e-01 -6.907343e-01 -1.200000e+00 4.100000e+00 6.941966e-01 6.941966e-01 3.470983e-01 -6.941966e-01 -1.100000e+00 4.100000e+00 6.973973e-01 6.973973e-01 3.486986e-01 -6.973973e-01 -1.000000e+00 4.100000e+00 7.003325e-01 7.003325e-01 3.501663e-01 -7.003325e-01 -9.000000e-01 4.100000e+00 7.029989e-01 7.029989e-01 3.514994e-01 -7.029989e-01 -8.000000e-01 4.100000e+00 7.053931e-01 7.053931e-01 3.526966e-01 -7.053931e-01 -7.000000e-01 4.100000e+00 7.075125e-01 7.075125e-01 3.537562e-01 -7.075125e-01 -6.000000e-01 4.100000e+00 7.093544e-01 7.093544e-01 3.546772e-01 -7.093544e-01 -5.000000e-01 4.100000e+00 7.109167e-01 7.109167e-01 3.554583e-01 -7.109167e-01 -4.000000e-01 4.100000e+00 7.121975e-01 7.121975e-01 3.560988e-01 -7.121975e-01 -3.000000e-01 4.100000e+00 7.131953e-01 7.131953e-01 3.565976e-01 -7.131953e-01 -2.000000e-01 4.100000e+00 7.139089e-01 7.139089e-01 3.569544e-01 -7.139089e-01 -1.000000e-01 4.100000e+00 7.143373e-01 7.143373e-01 3.571686e-01 -7.143373e-01 0.000000e+00 4.100000e+00 7.144802e-01 7.144802e-01 3.572401e-01 -7.144802e-01 1.000000e-01 4.100000e+00 7.143373e-01 7.143373e-01 3.571686e-01 -7.143373e-01 2.000000e-01 4.100000e+00 7.139089e-01 7.139089e-01 3.569544e-01 -7.139089e-01 3.000000e-01 4.100000e+00 7.131953e-01 7.131953e-01 3.565976e-01 -7.131953e-01 4.000000e-01 4.100000e+00 7.121975e-01 7.121975e-01 3.560988e-01 -7.121975e-01 5.000000e-01 4.100000e+00 7.109167e-01 7.109167e-01 3.554583e-01 -7.109167e-01 6.000000e-01 4.100000e+00 7.093544e-01 7.093544e-01 3.546772e-01 -7.093544e-01 7.000000e-01 4.100000e+00 7.075125e-01 7.075125e-01 3.537562e-01 -7.075125e-01 8.000000e-01 4.100000e+00 7.053931e-01 7.053931e-01 3.526966e-01 -7.053931e-01 9.000000e-01 4.100000e+00 7.029989e-01 7.029989e-01 3.514994e-01 -7.029989e-01 1.000000e+00 4.100000e+00 7.003325e-01 7.003325e-01 3.501663e-01 -7.003325e-01 1.100000e+00 4.100000e+00 6.973973e-01 6.973973e-01 3.486986e-01 -6.973973e-01 1.200000e+00 4.100000e+00 6.941966e-01 6.941966e-01 3.470983e-01 -6.941966e-01 1.300000e+00 4.100000e+00 6.907343e-01 6.907343e-01 3.453672e-01 -6.907343e-01 1.400000e+00 4.100000e+00 6.870144e-01 6.870144e-01 3.435072e-01 -6.870144e-01 1.500000e+00 4.100000e+00 6.830413e-01 6.830413e-01 3.415206e-01 -6.830413e-01 1.600000e+00 4.100000e+00 6.788195e-01 6.788195e-01 3.394098e-01 -6.788195e-01 1.700000e+00 4.100000e+00 6.743541e-01 6.743541e-01 3.371770e-01 -6.743541e-01 1.800000e+00 4.100000e+00 6.696501e-01 6.696501e-01 3.348250e-01 -6.696501e-01 1.900000e+00 4.100000e+00 6.647130e-01 6.647130e-01 3.323565e-01 -6.647130e-01 2.000000e+00 4.100000e+00 6.595483e-01 6.595483e-01 3.297742e-01 -6.595483e-01 2.100000e+00 4.100000e+00 6.541622e-01 6.541622e-01 3.270811e-01 -6.541622e-01 2.200000e+00 4.100000e+00 6.485605e-01 6.485605e-01 3.242802e-01 -6.485605e-01 2.300000e+00 4.100000e+00 6.427497e-01 6.427497e-01 3.213748e-01 -6.427497e-01 2.400000e+00 4.100000e+00 6.367361e-01 6.367361e-01 3.183680e-01 -6.367361e-01 2.500000e+00 4.100000e+00 6.305265e-01 6.305265e-01 3.152633e-01 -6.305265e-01 2.600000e+00 4.100000e+00 6.241279e-01 6.241279e-01 3.120639e-01 -6.241279e-01 2.700000e+00 4.100000e+00 6.175471e-01 6.175471e-01 3.087735e-01 -6.175471e-01 2.800000e+00 4.100000e+00 6.107913e-01 6.107913e-01 3.053956e-01 -6.107913e-01 2.900000e+00 4.100000e+00 6.038678e-01 6.038678e-01 3.019339e-01 -6.038678e-01 3.000000e+00 4.100000e+00 5.967840e-01 5.967840e-01 2.983920e-01 -5.967840e-01 3.100000e+00 4.100000e+00 5.895475e-01 5.895475e-01 2.947738e-01 -5.895475e-01 3.200000e+00 4.100000e+00 5.821658e-01 5.821658e-01 2.910829e-01 -5.821658e-01 3.300000e+00 4.100000e+00 5.746467e-01 5.746467e-01 2.873233e-01 -5.746467e-01 3.400000e+00 4.100000e+00 5.669977e-01 5.669977e-01 2.834989e-01 -5.669977e-01 3.500000e+00 4.100000e+00 5.592269e-01 5.592269e-01 2.796134e-01 -5.592269e-01 3.600000e+00 4.100000e+00 5.513420e-01 5.513420e-01 2.756710e-01 -5.513420e-01 3.700000e+00 4.100000e+00 5.433509e-01 5.433509e-01 2.716754e-01 -5.433509e-01 3.800000e+00 4.100000e+00 5.352615e-01 5.352615e-01 2.676307e-01 -5.352615e-01 3.900000e+00 4.100000e+00 5.270815e-01 5.270815e-01 2.635408e-01 -5.270815e-01 4.000000e+00 4.100000e+00 5.188191e-01 5.188191e-01 2.594095e-01 -5.188191e-01 4.100000e+00 4.100000e+00 5.104820e-01 5.104820e-01 2.552410e-01 -5.104820e-01 4.200000e+00 4.100000e+00 5.020779e-01 5.020779e-01 2.510389e-01 -5.020779e-01 4.300000e+00 4.100000e+00 4.936147e-01 4.936147e-01 2.468074e-01 -4.936147e-01 4.400000e+00 4.100000e+00 4.851001e-01 4.851001e-01 2.425501e-01 -4.851001e-01 4.500000e+00 4.100000e+00 4.765417e-01 4.765417e-01 2.382709e-01 -4.765417e-01 4.600000e+00 4.100000e+00 4.679471e-01 4.679471e-01 2.339736e-01 -4.679471e-01 4.700000e+00 4.100000e+00 4.593238e-01 4.593238e-01 2.296619e-01 -4.593238e-01 4.800000e+00 4.100000e+00 4.506789e-01 4.506789e-01 2.253395e-01 -4.506789e-01 4.900000e+00 4.100000e+00 4.420200e-01 4.420200e-01 2.210100e-01 -4.420200e-01 -5.000000e+00 4.200000e+00 4.262199e-01 4.262199e-01 2.131099e-01 -4.262199e-01 -4.900000e+00 4.200000e+00 4.347431e-01 4.347431e-01 2.173716e-01 -4.347431e-01 -4.800000e+00 4.200000e+00 4.432594e-01 4.432594e-01 2.216297e-01 -4.432594e-01 -4.700000e+00 4.200000e+00 4.517620e-01 4.517620e-01 2.258810e-01 -4.517620e-01 -4.600000e+00 4.200000e+00 4.602433e-01 4.602433e-01 2.301217e-01 -4.602433e-01 -4.500000e+00 4.200000e+00 4.686964e-01 4.686964e-01 2.343482e-01 -4.686964e-01 -4.400000e+00 4.200000e+00 4.771139e-01 4.771139e-01 2.385570e-01 -4.771139e-01 -4.300000e+00 4.200000e+00 4.854884e-01 4.854884e-01 2.427442e-01 -4.854884e-01 -4.200000e+00 4.200000e+00 4.938122e-01 4.938122e-01 2.469061e-01 -4.938122e-01 -4.100000e+00 4.200000e+00 5.020779e-01 5.020779e-01 2.510389e-01 -5.020779e-01 -4.000000e+00 4.200000e+00 5.102778e-01 5.102778e-01 2.551389e-01 -5.102778e-01 -3.900000e+00 4.200000e+00 5.184042e-01 5.184042e-01 2.592021e-01 -5.184042e-01 -3.800000e+00 4.200000e+00 5.264494e-01 5.264494e-01 2.632247e-01 -5.264494e-01 -3.700000e+00 4.200000e+00 5.344057e-01 5.344057e-01 2.672029e-01 -5.344057e-01 -3.600000e+00 4.200000e+00 5.422652e-01 5.422652e-01 2.711326e-01 -5.422652e-01 -3.500000e+00 4.200000e+00 5.500204e-01 5.500204e-01 2.750102e-01 -5.500204e-01 -3.400000e+00 4.200000e+00 5.576633e-01 5.576633e-01 2.788316e-01 -5.576633e-01 -3.300000e+00 4.200000e+00 5.651863e-01 5.651863e-01 2.825931e-01 -5.651863e-01 -3.200000e+00 4.200000e+00 5.725816e-01 5.725816e-01 2.862908e-01 -5.725816e-01 -3.100000e+00 4.200000e+00 5.798418e-01 5.798418e-01 2.899209e-01 -5.798418e-01 -3.000000e+00 4.200000e+00 5.869592e-01 5.869592e-01 2.934796e-01 -5.869592e-01 -2.900000e+00 4.200000e+00 5.939263e-01 5.939263e-01 2.969632e-01 -5.939263e-01 -2.800000e+00 4.200000e+00 6.007358e-01 6.007358e-01 3.003679e-01 -6.007358e-01 -2.700000e+00 4.200000e+00 6.073804e-01 6.073804e-01 3.036902e-01 -6.073804e-01 -2.600000e+00 4.200000e+00 6.138529e-01 6.138529e-01 3.069264e-01 -6.138529e-01 -2.500000e+00 4.200000e+00 6.201462e-01 6.201462e-01 3.100731e-01 -6.201462e-01 -2.400000e+00 4.200000e+00 6.262535e-01 6.262535e-01 3.131268e-01 -6.262535e-01 -2.300000e+00 4.200000e+00 6.321681e-01 6.321681e-01 3.160840e-01 -6.321681e-01 -2.200000e+00 4.200000e+00 6.378832e-01 6.378832e-01 3.189416e-01 -6.378832e-01 -2.100000e+00 4.200000e+00 6.433927e-01 6.433927e-01 3.216964e-01 -6.433927e-01 -2.000000e+00 4.200000e+00 6.486902e-01 6.486902e-01 3.243451e-01 -6.486902e-01 -1.900000e+00 4.200000e+00 6.537698e-01 6.537698e-01 3.268849e-01 -6.537698e-01 -1.800000e+00 4.200000e+00 6.586257e-01 6.586257e-01 3.293128e-01 -6.586257e-01 -1.700000e+00 4.200000e+00 6.632522e-01 6.632522e-01 3.316261e-01 -6.632522e-01 -1.600000e+00 4.200000e+00 6.676441e-01 6.676441e-01 3.338221e-01 -6.676441e-01 -1.500000e+00 4.200000e+00 6.717964e-01 6.717964e-01 3.358982e-01 -6.717964e-01 -1.400000e+00 4.200000e+00 6.757041e-01 6.757041e-01 3.378521e-01 -6.757041e-01 -1.300000e+00 4.200000e+00 6.793628e-01 6.793628e-01 3.396814e-01 -6.793628e-01 -1.200000e+00 4.200000e+00 6.827681e-01 6.827681e-01 3.413841e-01 -6.827681e-01 -1.100000e+00 4.200000e+00 6.859161e-01 6.859161e-01 3.429580e-01 -6.859161e-01 -1.000000e+00 4.200000e+00 6.888030e-01 6.888030e-01 3.444015e-01 -6.888030e-01 -9.000000e-01 4.200000e+00 6.914254e-01 6.914254e-01 3.457127e-01 -6.914254e-01 -8.000000e-01 4.200000e+00 6.937802e-01 6.937802e-01 3.468901e-01 -6.937802e-01 -7.000000e-01 4.200000e+00 6.958647e-01 6.958647e-01 3.479324e-01 -6.958647e-01 -6.000000e-01 4.200000e+00 6.976764e-01 6.976764e-01 3.488382e-01 -6.976764e-01 -5.000000e-01 4.200000e+00 6.992129e-01 6.992129e-01 3.496065e-01 -6.992129e-01 -4.000000e-01 4.200000e+00 7.004727e-01 7.004727e-01 3.502363e-01 -7.004727e-01 -3.000000e-01 4.200000e+00 7.014540e-01 7.014540e-01 3.507270e-01 -7.014540e-01 -2.000000e-01 4.200000e+00 7.021558e-01 7.021558e-01 3.510779e-01 -7.021558e-01 -1.000000e-01 4.200000e+00 7.025772e-01 7.025772e-01 3.512886e-01 -7.025772e-01 0.000000e+00 4.200000e+00 7.027177e-01 7.027177e-01 3.513589e-01 -7.027177e-01 1.000000e-01 4.200000e+00 7.025772e-01 7.025772e-01 3.512886e-01 -7.025772e-01 2.000000e-01 4.200000e+00 7.021558e-01 7.021558e-01 3.510779e-01 -7.021558e-01 3.000000e-01 4.200000e+00 7.014540e-01 7.014540e-01 3.507270e-01 -7.014540e-01 4.000000e-01 4.200000e+00 7.004727e-01 7.004727e-01 3.502363e-01 -7.004727e-01 5.000000e-01 4.200000e+00 6.992129e-01 6.992129e-01 3.496065e-01 -6.992129e-01 6.000000e-01 4.200000e+00 6.976764e-01 6.976764e-01 3.488382e-01 -6.976764e-01 7.000000e-01 4.200000e+00 6.958647e-01 6.958647e-01 3.479324e-01 -6.958647e-01 8.000000e-01 4.200000e+00 6.937802e-01 6.937802e-01 3.468901e-01 -6.937802e-01 9.000000e-01 4.200000e+00 6.914254e-01 6.914254e-01 3.457127e-01 -6.914254e-01 1.000000e+00 4.200000e+00 6.888030e-01 6.888030e-01 3.444015e-01 -6.888030e-01 1.100000e+00 4.200000e+00 6.859161e-01 6.859161e-01 3.429580e-01 -6.859161e-01 1.200000e+00 4.200000e+00 6.827681e-01 6.827681e-01 3.413841e-01 -6.827681e-01 1.300000e+00 4.200000e+00 6.793628e-01 6.793628e-01 3.396814e-01 -6.793628e-01 1.400000e+00 4.200000e+00 6.757041e-01 6.757041e-01 3.378521e-01 -6.757041e-01 1.500000e+00 4.200000e+00 6.717964e-01 6.717964e-01 3.358982e-01 -6.717964e-01 1.600000e+00 4.200000e+00 6.676441e-01 6.676441e-01 3.338221e-01 -6.676441e-01 1.700000e+00 4.200000e+00 6.632522e-01 6.632522e-01 3.316261e-01 -6.632522e-01 1.800000e+00 4.200000e+00 6.586257e-01 6.586257e-01 3.293128e-01 -6.586257e-01 1.900000e+00 4.200000e+00 6.537698e-01 6.537698e-01 3.268849e-01 -6.537698e-01 2.000000e+00 4.200000e+00 6.486902e-01 6.486902e-01 3.243451e-01 -6.486902e-01 2.100000e+00 4.200000e+00 6.433927e-01 6.433927e-01 3.216964e-01 -6.433927e-01 2.200000e+00 4.200000e+00 6.378832e-01 6.378832e-01 3.189416e-01 -6.378832e-01 2.300000e+00 4.200000e+00 6.321681e-01 6.321681e-01 3.160840e-01 -6.321681e-01 2.400000e+00 4.200000e+00 6.262535e-01 6.262535e-01 3.131268e-01 -6.262535e-01 2.500000e+00 4.200000e+00 6.201462e-01 6.201462e-01 3.100731e-01 -6.201462e-01 2.600000e+00 4.200000e+00 6.138529e-01 6.138529e-01 3.069264e-01 -6.138529e-01 2.700000e+00 4.200000e+00 6.073804e-01 6.073804e-01 3.036902e-01 -6.073804e-01 2.800000e+00 4.200000e+00 6.007358e-01 6.007358e-01 3.003679e-01 -6.007358e-01 2.900000e+00 4.200000e+00 5.939263e-01 5.939263e-01 2.969632e-01 -5.939263e-01 3.000000e+00 4.200000e+00 5.869592e-01 5.869592e-01 2.934796e-01 -5.869592e-01 3.100000e+00 4.200000e+00 5.798418e-01 5.798418e-01 2.899209e-01 -5.798418e-01 3.200000e+00 4.200000e+00 5.725816e-01 5.725816e-01 2.862908e-01 -5.725816e-01 3.300000e+00 4.200000e+00 5.651863e-01 5.651863e-01 2.825931e-01 -5.651863e-01 3.400000e+00 4.200000e+00 5.576633e-01 5.576633e-01 2.788316e-01 -5.576633e-01 3.500000e+00 4.200000e+00 5.500204e-01 5.500204e-01 2.750102e-01 -5.500204e-01 3.600000e+00 4.200000e+00 5.422652e-01 5.422652e-01 2.711326e-01 -5.422652e-01 3.700000e+00 4.200000e+00 5.344057e-01 5.344057e-01 2.672029e-01 -5.344057e-01 3.800000e+00 4.200000e+00 5.264494e-01 5.264494e-01 2.632247e-01 -5.264494e-01 3.900000e+00 4.200000e+00 5.184042e-01 5.184042e-01 2.592021e-01 -5.184042e-01 4.000000e+00 4.200000e+00 5.102778e-01 5.102778e-01 2.551389e-01 -5.102778e-01 4.100000e+00 4.200000e+00 5.020779e-01 5.020779e-01 2.510389e-01 -5.020779e-01 4.200000e+00 4.200000e+00 4.938122e-01 4.938122e-01 2.469061e-01 -4.938122e-01 4.300000e+00 4.200000e+00 4.854884e-01 4.854884e-01 2.427442e-01 -4.854884e-01 4.400000e+00 4.200000e+00 4.771139e-01 4.771139e-01 2.385570e-01 -4.771139e-01 4.500000e+00 4.200000e+00 4.686964e-01 4.686964e-01 2.343482e-01 -4.686964e-01 4.600000e+00 4.200000e+00 4.602433e-01 4.602433e-01 2.301217e-01 -4.602433e-01 4.700000e+00 4.200000e+00 4.517620e-01 4.517620e-01 2.258810e-01 -4.517620e-01 4.800000e+00 4.200000e+00 4.432594e-01 4.432594e-01 2.216297e-01 -4.432594e-01 4.900000e+00 4.200000e+00 4.347431e-01 4.347431e-01 2.173716e-01 -4.347431e-01 -5.000000e+00 4.300000e+00 4.190353e-01 4.190353e-01 2.095177e-01 -4.190353e-01 -4.900000e+00 4.300000e+00 4.274149e-01 4.274149e-01 2.137075e-01 -4.274149e-01 -4.800000e+00 4.300000e+00 4.357877e-01 4.357877e-01 2.178939e-01 -4.357877e-01 -4.700000e+00 4.300000e+00 4.441469e-01 4.441469e-01 2.220734e-01 -4.441469e-01 -4.600000e+00 4.300000e+00 4.524853e-01 4.524853e-01 2.262427e-01 -4.524853e-01 -4.500000e+00 4.300000e+00 4.607960e-01 4.607960e-01 2.303980e-01 -4.607960e-01 -4.400000e+00 4.300000e+00 4.690715e-01 4.690715e-01 2.345358e-01 -4.690715e-01 -4.300000e+00 4.300000e+00 4.773048e-01 4.773048e-01 2.386524e-01 -4.773048e-01 -4.200000e+00 4.300000e+00 4.854884e-01 4.854884e-01 2.427442e-01 -4.854884e-01 -4.100000e+00 4.300000e+00 4.936147e-01 4.936147e-01 2.468074e-01 -4.936147e-01 -4.000000e+00 4.300000e+00 5.016764e-01 5.016764e-01 2.508382e-01 -5.016764e-01 -3.900000e+00 4.300000e+00 5.096658e-01 5.096658e-01 2.548329e-01 -5.096658e-01 -3.800000e+00 4.300000e+00 5.175754e-01 5.175754e-01 2.587877e-01 -5.175754e-01 -3.700000e+00 4.300000e+00 5.253976e-01 5.253976e-01 2.626988e-01 -5.253976e-01 -3.600000e+00 4.300000e+00 5.331247e-01 5.331247e-01 2.665623e-01 -5.331247e-01 -3.500000e+00 4.300000e+00 5.407491e-01 5.407491e-01 2.703745e-01 -5.407491e-01 -3.400000e+00 4.300000e+00 5.482631e-01 5.482631e-01 2.741315e-01 -5.482631e-01 -3.300000e+00 4.300000e+00 5.556593e-01 5.556593e-01 2.778296e-01 -5.556593e-01 -3.200000e+00 4.300000e+00 5.629300e-01 5.629300e-01 2.814650e-01 -5.629300e-01 -3.100000e+00 4.300000e+00 5.700678e-01 5.700678e-01 2.850339e-01 -5.700678e-01 -3.000000e+00 4.300000e+00 5.770652e-01 5.770652e-01 2.885326e-01 -5.770652e-01 -2.900000e+00 4.300000e+00 5.839149e-01 5.839149e-01 2.919574e-01 -5.839149e-01 -2.800000e+00 4.300000e+00 5.906096e-01 5.906096e-01 2.953048e-01 -5.906096e-01 -2.700000e+00 4.300000e+00 5.971422e-01 5.971422e-01 2.985711e-01 -5.971422e-01 -2.600000e+00 4.300000e+00 6.035056e-01 6.035056e-01 3.017528e-01 -6.035056e-01 -2.500000e+00 4.300000e+00 6.096928e-01 6.096928e-01 3.048464e-01 -6.096928e-01 -2.400000e+00 4.300000e+00 6.156972e-01 6.156972e-01 3.078486e-01 -6.156972e-01 -2.300000e+00 4.300000e+00 6.215121e-01 6.215121e-01 3.107560e-01 -6.215121e-01 -2.200000e+00 4.300000e+00 6.271309e-01 6.271309e-01 3.135654e-01 -6.271309e-01 -2.100000e+00 4.300000e+00 6.325475e-01 6.325475e-01 3.162737e-01 -6.325475e-01 -2.000000e+00 4.300000e+00 6.377557e-01 6.377557e-01 3.188778e-01 -6.377557e-01 -1.900000e+00 4.300000e+00 6.427496e-01 6.427496e-01 3.213748e-01 -6.427496e-01 -1.800000e+00 4.300000e+00 6.475236e-01 6.475236e-01 3.237618e-01 -6.475236e-01 -1.700000e+00 4.300000e+00 6.520722e-01 6.520722e-01 3.260361e-01 -6.520722e-01 -1.600000e+00 4.300000e+00 6.563901e-01 6.563901e-01 3.281950e-01 -6.563901e-01 -1.500000e+00 4.300000e+00 6.604724e-01 6.604724e-01 3.302362e-01 -6.604724e-01 -1.400000e+00 4.300000e+00 6.643142e-01 6.643142e-01 3.321571e-01 -6.643142e-01 -1.300000e+00 4.300000e+00 6.679112e-01 6.679112e-01 3.339556e-01 -6.679112e-01 -1.200000e+00 4.300000e+00 6.712592e-01 6.712592e-01 3.356296e-01 -6.712592e-01 -1.100000e+00 4.300000e+00 6.743541e-01 6.743541e-01 3.371770e-01 -6.743541e-01 -1.000000e+00 4.300000e+00 6.771923e-01 6.771923e-01 3.385961e-01 -6.771923e-01 -9.000000e-01 4.300000e+00 6.797705e-01 6.797705e-01 3.398853e-01 -6.797705e-01 -8.000000e-01 4.300000e+00 6.820857e-01 6.820857e-01 3.410428e-01 -6.820857e-01 -7.000000e-01 4.300000e+00 6.841350e-01 6.841350e-01 3.420675e-01 -6.841350e-01 -6.000000e-01 4.300000e+00 6.859161e-01 6.859161e-01 3.429580e-01 -6.859161e-01 -5.000000e-01 4.300000e+00 6.874267e-01 6.874267e-01 3.437134e-01 -6.874267e-01 -4.000000e-01 4.300000e+00 6.886652e-01 6.886652e-01 3.443326e-01 -6.886652e-01 -3.000000e-01 4.300000e+00 6.896300e-01 6.896300e-01 3.448150e-01 -6.896300e-01 -2.000000e-01 4.300000e+00 6.903200e-01 6.903200e-01 3.451600e-01 -6.903200e-01 -1.000000e-01 4.300000e+00 6.907343e-01 6.907343e-01 3.453672e-01 -6.907343e-01 0.000000e+00 4.300000e+00 6.908725e-01 6.908725e-01 3.454362e-01 -6.908725e-01 1.000000e-01 4.300000e+00 6.907343e-01 6.907343e-01 3.453672e-01 -6.907343e-01 2.000000e-01 4.300000e+00 6.903200e-01 6.903200e-01 3.451600e-01 -6.903200e-01 3.000000e-01 4.300000e+00 6.896300e-01 6.896300e-01 3.448150e-01 -6.896300e-01 4.000000e-01 4.300000e+00 6.886652e-01 6.886652e-01 3.443326e-01 -6.886652e-01 5.000000e-01 4.300000e+00 6.874267e-01 6.874267e-01 3.437134e-01 -6.874267e-01 6.000000e-01 4.300000e+00 6.859161e-01 6.859161e-01 3.429580e-01 -6.859161e-01 7.000000e-01 4.300000e+00 6.841350e-01 6.841350e-01 3.420675e-01 -6.841350e-01 8.000000e-01 4.300000e+00 6.820857e-01 6.820857e-01 3.410428e-01 -6.820857e-01 9.000000e-01 4.300000e+00 6.797705e-01 6.797705e-01 3.398853e-01 -6.797705e-01 1.000000e+00 4.300000e+00 6.771923e-01 6.771923e-01 3.385961e-01 -6.771923e-01 1.100000e+00 4.300000e+00 6.743541e-01 6.743541e-01 3.371770e-01 -6.743541e-01 1.200000e+00 4.300000e+00 6.712592e-01 6.712592e-01 3.356296e-01 -6.712592e-01 1.300000e+00 4.300000e+00 6.679112e-01 6.679112e-01 3.339556e-01 -6.679112e-01 1.400000e+00 4.300000e+00 6.643142e-01 6.643142e-01 3.321571e-01 -6.643142e-01 1.500000e+00 4.300000e+00 6.604724e-01 6.604724e-01 3.302362e-01 -6.604724e-01 1.600000e+00 4.300000e+00 6.563901e-01 6.563901e-01 3.281950e-01 -6.563901e-01 1.700000e+00 4.300000e+00 6.520722e-01 6.520722e-01 3.260361e-01 -6.520722e-01 1.800000e+00 4.300000e+00 6.475236e-01 6.475236e-01 3.237618e-01 -6.475236e-01 1.900000e+00 4.300000e+00 6.427496e-01 6.427496e-01 3.213748e-01 -6.427496e-01 2.000000e+00 4.300000e+00 6.377557e-01 6.377557e-01 3.188778e-01 -6.377557e-01 2.100000e+00 4.300000e+00 6.325475e-01 6.325475e-01 3.162737e-01 -6.325475e-01 2.200000e+00 4.300000e+00 6.271309e-01 6.271309e-01 3.135654e-01 -6.271309e-01 2.300000e+00 4.300000e+00 6.215121e-01 6.215121e-01 3.107560e-01 -6.215121e-01 2.400000e+00 4.300000e+00 6.156972e-01 6.156972e-01 3.078486e-01 -6.156972e-01 2.500000e+00 4.300000e+00 6.096928e-01 6.096928e-01 3.048464e-01 -6.096928e-01 2.600000e+00 4.300000e+00 6.035056e-01 6.035056e-01 3.017528e-01 -6.035056e-01 2.700000e+00 4.300000e+00 5.971422e-01 5.971422e-01 2.985711e-01 -5.971422e-01 2.800000e+00 4.300000e+00 5.906096e-01 5.906096e-01 2.953048e-01 -5.906096e-01 2.900000e+00 4.300000e+00 5.839149e-01 5.839149e-01 2.919574e-01 -5.839149e-01 3.000000e+00 4.300000e+00 5.770652e-01 5.770652e-01 2.885326e-01 -5.770652e-01 3.100000e+00 4.300000e+00 5.700678e-01 5.700678e-01 2.850339e-01 -5.700678e-01 3.200000e+00 4.300000e+00 5.629300e-01 5.629300e-01 2.814650e-01 -5.629300e-01 3.300000e+00 4.300000e+00 5.556593e-01 5.556593e-01 2.778296e-01 -5.556593e-01 3.400000e+00 4.300000e+00 5.482631e-01 5.482631e-01 2.741315e-01 -5.482631e-01 3.500000e+00 4.300000e+00 5.407491e-01 5.407491e-01 2.703745e-01 -5.407491e-01 3.600000e+00 4.300000e+00 5.331247e-01 5.331247e-01 2.665623e-01 -5.331247e-01 3.700000e+00 4.300000e+00 5.253976e-01 5.253976e-01 2.626988e-01 -5.253976e-01 3.800000e+00 4.300000e+00 5.175754e-01 5.175754e-01 2.587877e-01 -5.175754e-01 3.900000e+00 4.300000e+00 5.096658e-01 5.096658e-01 2.548329e-01 -5.096658e-01 4.000000e+00 4.300000e+00 5.016764e-01 5.016764e-01 2.508382e-01 -5.016764e-01 4.100000e+00 4.300000e+00 4.936147e-01 4.936147e-01 2.468074e-01 -4.936147e-01 4.200000e+00 4.300000e+00 4.854884e-01 4.854884e-01 2.427442e-01 -4.854884e-01 4.300000e+00 4.300000e+00 4.773048e-01 4.773048e-01 2.386524e-01 -4.773048e-01 4.400000e+00 4.300000e+00 4.690715e-01 4.690715e-01 2.345358e-01 -4.690715e-01 4.500000e+00 4.300000e+00 4.607960e-01 4.607960e-01 2.303980e-01 -4.607960e-01 4.600000e+00 4.300000e+00 4.524853e-01 4.524853e-01 2.262427e-01 -4.524853e-01 4.700000e+00 4.300000e+00 4.441469e-01 4.441469e-01 2.220734e-01 -4.441469e-01 4.800000e+00 4.300000e+00 4.357877e-01 4.357877e-01 2.178939e-01 -4.357877e-01 4.900000e+00 4.300000e+00 4.274149e-01 4.274149e-01 2.137075e-01 -4.274149e-01 -5.000000e+00 4.400000e+00 4.118072e-01 4.118072e-01 2.059036e-01 -4.118072e-01 -4.900000e+00 4.400000e+00 4.200422e-01 4.200422e-01 2.100211e-01 -4.200422e-01 -4.800000e+00 4.400000e+00 4.282706e-01 4.282706e-01 2.141353e-01 -4.282706e-01 -4.700000e+00 4.400000e+00 4.364856e-01 4.364856e-01 2.182428e-01 -4.364856e-01 -4.600000e+00 4.400000e+00 4.446802e-01 4.446802e-01 2.223401e-01 -4.446802e-01 -4.500000e+00 4.400000e+00 4.528475e-01 4.528475e-01 2.264237e-01 -4.528475e-01 -4.400000e+00 4.400000e+00 4.609803e-01 4.609803e-01 2.304901e-01 -4.609803e-01 -4.300000e+00 4.400000e+00 4.690715e-01 4.690715e-01 2.345358e-01 -4.690715e-01 -4.200000e+00 4.400000e+00 4.771139e-01 4.771139e-01 2.385570e-01 -4.771139e-01 -4.100000e+00 4.400000e+00 4.851001e-01 4.851001e-01 2.425501e-01 -4.851001e-01 -4.000000e+00 4.400000e+00 4.930227e-01 4.930227e-01 2.465114e-01 -4.930227e-01 -3.900000e+00 4.400000e+00 5.008743e-01 5.008743e-01 2.504372e-01 -5.008743e-01 -3.800000e+00 4.400000e+00 5.086475e-01 5.086475e-01 2.543238e-01 -5.086475e-01 -3.700000e+00 4.400000e+00 5.163347e-01 5.163347e-01 2.581674e-01 -5.163347e-01 -3.600000e+00 4.400000e+00 5.239285e-01 5.239285e-01 2.619643e-01 -5.239285e-01 -3.500000e+00 4.400000e+00 5.314214e-01 5.314214e-01 2.657107e-01 -5.314214e-01 -3.400000e+00 4.400000e+00 5.388058e-01 5.388058e-01 2.694029e-01 -5.388058e-01 -3.300000e+00 4.400000e+00 5.460745e-01 5.460745e-01 2.730372e-01 -5.460745e-01 -3.200000e+00 4.400000e+00 5.532197e-01 5.532197e-01 2.766099e-01 -5.532197e-01 -3.100000e+00 4.400000e+00 5.602344e-01 5.602344e-01 2.801172e-01 -5.602344e-01 -3.000000e+00 4.400000e+00 5.671111e-01 5.671111e-01 2.835556e-01 -5.671111e-01 -2.900000e+00 4.400000e+00 5.738426e-01 5.738426e-01 2.869213e-01 -5.738426e-01 -2.800000e+00 4.400000e+00 5.804219e-01 5.804219e-01 2.902110e-01 -5.804219e-01 -2.700000e+00 4.400000e+00 5.868418e-01 5.868418e-01 2.934209e-01 -5.868418e-01 -2.600000e+00 4.400000e+00 5.930954e-01 5.930954e-01 2.965477e-01 -5.930954e-01 -2.500000e+00 4.400000e+00 5.991759e-01 5.991759e-01 2.995880e-01 -5.991759e-01 -2.400000e+00 4.400000e+00 6.050767e-01 6.050767e-01 3.025384e-01 -6.050767e-01 -2.300000e+00 4.400000e+00 6.107913e-01 6.107913e-01 3.053956e-01 -6.107913e-01 -2.200000e+00 4.400000e+00 6.163132e-01 6.163132e-01 3.081566e-01 -6.163132e-01 -2.100000e+00 4.400000e+00 6.216363e-01 6.216363e-01 3.108182e-01 -6.216363e-01 -2.000000e+00 4.400000e+00 6.267547e-01 6.267547e-01 3.133774e-01 -6.267547e-01 -1.900000e+00 4.400000e+00 6.316625e-01 6.316625e-01 3.158313e-01 -6.316625e-01 -1.800000e+00 4.400000e+00 6.363541e-01 6.363541e-01 3.181771e-01 -6.363541e-01 -1.700000e+00 4.400000e+00 6.408243e-01 6.408243e-01 3.204121e-01 -6.408243e-01 -1.600000e+00 4.400000e+00 6.450677e-01 6.450677e-01 3.225338e-01 -6.450677e-01 -1.500000e+00 4.400000e+00 6.490796e-01 6.490796e-01 3.245398e-01 -6.490796e-01 -1.400000e+00 4.400000e+00 6.528552e-01 6.528552e-01 3.264276e-01 -6.528552e-01 -1.300000e+00 4.400000e+00 6.563901e-01 6.563901e-01 3.281950e-01 -6.563901e-01 -1.200000e+00 4.400000e+00 6.596802e-01 6.596802e-01 3.298401e-01 -6.596802e-01 -1.100000e+00 4.400000e+00 6.627218e-01 6.627218e-01 3.313609e-01 -6.627218e-01 -1.000000e+00 4.400000e+00 6.655111e-01 6.655111e-01 3.327555e-01 -6.655111e-01 -9.000000e-01 4.400000e+00 6.680448e-01 6.680448e-01 3.340224e-01 -6.680448e-01 -8.000000e-01 4.400000e+00 6.703200e-01 6.703200e-01 3.351600e-01 -6.703200e-01 -7.000000e-01 4.400000e+00 6.723340e-01 6.723340e-01 3.361670e-01 -6.723340e-01 -6.000000e-01 4.400000e+00 6.740844e-01 6.740844e-01 3.370422e-01 -6.740844e-01 -5.000000e-01 4.400000e+00 6.755690e-01 6.755690e-01 3.377845e-01 -6.755690e-01 -4.000000e-01 4.400000e+00 6.767861e-01 6.767861e-01 3.383931e-01 -6.767861e-01 -3.000000e-01 4.400000e+00 6.777343e-01 6.777343e-01 3.388671e-01 -6.777343e-01 -2.000000e-01 4.400000e+00 6.784123e-01 6.784123e-01 3.392062e-01 -6.784123e-01 -1.000000e-01 4.400000e+00 6.788195e-01 6.788195e-01 3.394098e-01 -6.788195e-01 0.000000e+00 4.400000e+00 6.789553e-01 6.789553e-01 3.394777e-01 -6.789553e-01 1.000000e-01 4.400000e+00 6.788195e-01 6.788195e-01 3.394098e-01 -6.788195e-01 2.000000e-01 4.400000e+00 6.784123e-01 6.784123e-01 3.392062e-01 -6.784123e-01 3.000000e-01 4.400000e+00 6.777343e-01 6.777343e-01 3.388671e-01 -6.777343e-01 4.000000e-01 4.400000e+00 6.767861e-01 6.767861e-01 3.383931e-01 -6.767861e-01 5.000000e-01 4.400000e+00 6.755690e-01 6.755690e-01 3.377845e-01 -6.755690e-01 6.000000e-01 4.400000e+00 6.740844e-01 6.740844e-01 3.370422e-01 -6.740844e-01 7.000000e-01 4.400000e+00 6.723340e-01 6.723340e-01 3.361670e-01 -6.723340e-01 8.000000e-01 4.400000e+00 6.703200e-01 6.703200e-01 3.351600e-01 -6.703200e-01 9.000000e-01 4.400000e+00 6.680448e-01 6.680448e-01 3.340224e-01 -6.680448e-01 1.000000e+00 4.400000e+00 6.655111e-01 6.655111e-01 3.327555e-01 -6.655111e-01 1.100000e+00 4.400000e+00 6.627218e-01 6.627218e-01 3.313609e-01 -6.627218e-01 1.200000e+00 4.400000e+00 6.596802e-01 6.596802e-01 3.298401e-01 -6.596802e-01 1.300000e+00 4.400000e+00 6.563901e-01 6.563901e-01 3.281950e-01 -6.563901e-01 1.400000e+00 4.400000e+00 6.528552e-01 6.528552e-01 3.264276e-01 -6.528552e-01 1.500000e+00 4.400000e+00 6.490796e-01 6.490796e-01 3.245398e-01 -6.490796e-01 1.600000e+00 4.400000e+00 6.450677e-01 6.450677e-01 3.225338e-01 -6.450677e-01 1.700000e+00 4.400000e+00 6.408243e-01 6.408243e-01 3.204121e-01 -6.408243e-01 1.800000e+00 4.400000e+00 6.363541e-01 6.363541e-01 3.181771e-01 -6.363541e-01 1.900000e+00 4.400000e+00 6.316625e-01 6.316625e-01 3.158313e-01 -6.316625e-01 2.000000e+00 4.400000e+00 6.267547e-01 6.267547e-01 3.133774e-01 -6.267547e-01 2.100000e+00 4.400000e+00 6.216363e-01 6.216363e-01 3.108182e-01 -6.216363e-01 2.200000e+00 4.400000e+00 6.163132e-01 6.163132e-01 3.081566e-01 -6.163132e-01 2.300000e+00 4.400000e+00 6.107913e-01 6.107913e-01 3.053956e-01 -6.107913e-01 2.400000e+00 4.400000e+00 6.050767e-01 6.050767e-01 3.025384e-01 -6.050767e-01 2.500000e+00 4.400000e+00 5.991759e-01 5.991759e-01 2.995880e-01 -5.991759e-01 2.600000e+00 4.400000e+00 5.930954e-01 5.930954e-01 2.965477e-01 -5.930954e-01 2.700000e+00 4.400000e+00 5.868418e-01 5.868418e-01 2.934209e-01 -5.868418e-01 2.800000e+00 4.400000e+00 5.804219e-01 5.804219e-01 2.902110e-01 -5.804219e-01 2.900000e+00 4.400000e+00 5.738426e-01 5.738426e-01 2.869213e-01 -5.738426e-01 3.000000e+00 4.400000e+00 5.671111e-01 5.671111e-01 2.835556e-01 -5.671111e-01 3.100000e+00 4.400000e+00 5.602344e-01 5.602344e-01 2.801172e-01 -5.602344e-01 3.200000e+00 4.400000e+00 5.532197e-01 5.532197e-01 2.766099e-01 -5.532197e-01 3.300000e+00 4.400000e+00 5.460745e-01 5.460745e-01 2.730372e-01 -5.460745e-01 3.400000e+00 4.400000e+00 5.388058e-01 5.388058e-01 2.694029e-01 -5.388058e-01 3.500000e+00 4.400000e+00 5.314214e-01 5.314214e-01 2.657107e-01 -5.314214e-01 3.600000e+00 4.400000e+00 5.239285e-01 5.239285e-01 2.619643e-01 -5.239285e-01 3.700000e+00 4.400000e+00 5.163347e-01 5.163347e-01 2.581674e-01 -5.163347e-01 3.800000e+00 4.400000e+00 5.086475e-01 5.086475e-01 2.543238e-01 -5.086475e-01 3.900000e+00 4.400000e+00 5.008743e-01 5.008743e-01 2.504372e-01 -5.008743e-01 4.000000e+00 4.400000e+00 4.930227e-01 4.930227e-01 2.465114e-01 -4.930227e-01 4.100000e+00 4.400000e+00 4.851001e-01 4.851001e-01 2.425501e-01 -4.851001e-01 4.200000e+00 4.400000e+00 4.771139e-01 4.771139e-01 2.385570e-01 -4.771139e-01 4.300000e+00 4.400000e+00 4.690715e-01 4.690715e-01 2.345358e-01 -4.690715e-01 4.400000e+00 4.400000e+00 4.609803e-01 4.609803e-01 2.304901e-01 -4.609803e-01 4.500000e+00 4.400000e+00 4.528475e-01 4.528475e-01 2.264237e-01 -4.528475e-01 4.600000e+00 4.400000e+00 4.446802e-01 4.446802e-01 2.223401e-01 -4.446802e-01 4.700000e+00 4.400000e+00 4.364856e-01 4.364856e-01 2.182428e-01 -4.364856e-01 4.800000e+00 4.400000e+00 4.282706e-01 4.282706e-01 2.141353e-01 -4.282706e-01 4.900000e+00 4.400000e+00 4.200422e-01 4.200422e-01 2.100211e-01 -4.200422e-01 -5.000000e+00 4.500000e+00 4.045419e-01 4.045419e-01 2.022710e-01 -4.045419e-01 -4.900000e+00 4.500000e+00 4.126316e-01 4.126316e-01 2.063158e-01 -4.126316e-01 -4.800000e+00 4.500000e+00 4.207148e-01 4.207148e-01 2.103574e-01 -4.207148e-01 -4.700000e+00 4.500000e+00 4.287849e-01 4.287849e-01 2.143924e-01 -4.287849e-01 -4.600000e+00 4.500000e+00 4.368349e-01 4.368349e-01 2.184175e-01 -4.368349e-01 -4.500000e+00 4.500000e+00 4.448581e-01 4.448581e-01 2.224291e-01 -4.448581e-01 -4.400000e+00 4.500000e+00 4.528475e-01 4.528475e-01 2.264237e-01 -4.528475e-01 -4.300000e+00 4.500000e+00 4.607960e-01 4.607960e-01 2.303980e-01 -4.607960e-01 -4.200000e+00 4.500000e+00 4.686964e-01 4.686964e-01 2.343482e-01 -4.686964e-01 -4.100000e+00 4.500000e+00 4.765417e-01 4.765417e-01 2.382709e-01 -4.765417e-01 -4.000000e+00 4.500000e+00 4.843245e-01 4.843245e-01 2.421623e-01 -4.843245e-01 -3.900000e+00 4.500000e+00 4.920377e-01 4.920377e-01 2.460188e-01 -4.920377e-01 -3.800000e+00 4.500000e+00 4.996737e-01 4.996737e-01 2.498369e-01 -4.996737e-01 -3.700000e+00 4.500000e+00 5.072253e-01 5.072253e-01 2.536126e-01 -5.072253e-01 -3.600000e+00 4.500000e+00 5.146852e-01 5.146852e-01 2.573426e-01 -5.146852e-01 -3.500000e+00 4.500000e+00 5.220458e-01 5.220458e-01 2.610229e-01 -5.220458e-01 -3.400000e+00 4.500000e+00 5.293000e-01 5.293000e-01 2.646500e-01 -5.293000e-01 -3.300000e+00 4.500000e+00 5.364403e-01 5.364403e-01 2.682202e-01 -5.364403e-01 -3.200000e+00 4.500000e+00 5.434595e-01 5.434595e-01 2.717298e-01 -5.434595e-01 -3.100000e+00 4.500000e+00 5.503505e-01 5.503505e-01 2.751752e-01 -5.503505e-01 -3.000000e+00 4.500000e+00 5.571059e-01 5.571059e-01 2.785529e-01 -5.571059e-01 -2.900000e+00 4.500000e+00 5.637187e-01 5.637187e-01 2.818593e-01 -5.637187e-01 -2.800000e+00 4.500000e+00 5.701818e-01 5.701818e-01 2.850909e-01 -5.701818e-01 -2.700000e+00 4.500000e+00 5.764884e-01 5.764884e-01 2.882442e-01 -5.764884e-01 -2.600000e+00 4.500000e+00 5.826317e-01 5.826317e-01 2.913159e-01 -5.826317e-01 -2.500000e+00 4.500000e+00 5.886050e-01 5.886050e-01 2.943025e-01 -5.886050e-01 -2.400000e+00 4.500000e+00 5.944017e-01 5.944017e-01 2.972008e-01 -5.944017e-01 -2.300000e+00 4.500000e+00 6.000154e-01 6.000154e-01 3.000077e-01 -6.000154e-01 -2.200000e+00 4.500000e+00 6.054399e-01 6.054399e-01 3.027200e-01 -6.054399e-01 -2.100000e+00 4.500000e+00 6.106691e-01 6.106691e-01 3.053346e-01 -6.106691e-01 -2.000000e+00 4.500000e+00 6.156972e-01 6.156972e-01 3.078486e-01 -6.156972e-01 -1.900000e+00 4.500000e+00 6.205184e-01 6.205184e-01 3.102592e-01 -6.205184e-01 -1.800000e+00 4.500000e+00 6.251273e-01 6.251273e-01 3.125637e-01 -6.251273e-01 -1.700000e+00 4.500000e+00 6.295186e-01 6.295186e-01 3.147593e-01 -6.295186e-01 -1.600000e+00 4.500000e+00 6.336871e-01 6.336871e-01 3.168435e-01 -6.336871e-01 -1.500000e+00 4.500000e+00 6.376281e-01 6.376281e-01 3.188141e-01 -6.376281e-01 -1.400000e+00 4.500000e+00 6.413372e-01 6.413372e-01 3.206686e-01 -6.413372e-01 -1.300000e+00 4.500000e+00 6.448097e-01 6.448097e-01 3.224049e-01 -6.448097e-01 -1.200000e+00 4.500000e+00 6.480418e-01 6.480418e-01 3.240209e-01 -6.480418e-01 -1.100000e+00 4.500000e+00 6.510297e-01 6.510297e-01 3.255149e-01 -6.510297e-01 -1.000000e+00 4.500000e+00 6.537698e-01 6.537698e-01 3.268849e-01 -6.537698e-01 -9.000000e-01 4.500000e+00 6.562589e-01 6.562589e-01 3.281294e-01 -6.562589e-01 -8.000000e-01 4.500000e+00 6.584939e-01 6.584939e-01 3.292470e-01 -6.584939e-01 -7.000000e-01 4.500000e+00 6.604724e-01 6.604724e-01 3.302362e-01 -6.604724e-01 -6.000000e-01 4.500000e+00 6.621919e-01 6.621919e-01 3.310959e-01 -6.621919e-01 -5.000000e-01 4.500000e+00 6.636503e-01 6.636503e-01 3.318251e-01 -6.636503e-01 -4.000000e-01 4.500000e+00 6.648459e-01 6.648459e-01 3.324230e-01 -6.648459e-01 -3.000000e-01 4.500000e+00 6.657773e-01 6.657773e-01 3.328887e-01 -6.657773e-01 -2.000000e-01 4.500000e+00 6.664435e-01 6.664435e-01 3.332217e-01 -6.664435e-01 -1.000000e-01 4.500000e+00 6.668435e-01 6.668435e-01 3.334217e-01 -6.668435e-01 0.000000e+00 4.500000e+00 6.669768e-01 6.669768e-01 3.334884e-01 -6.669768e-01 1.000000e-01 4.500000e+00 6.668435e-01 6.668435e-01 3.334217e-01 -6.668435e-01 2.000000e-01 4.500000e+00 6.664435e-01 6.664435e-01 3.332217e-01 -6.664435e-01 3.000000e-01 4.500000e+00 6.657773e-01 6.657773e-01 3.328887e-01 -6.657773e-01 4.000000e-01 4.500000e+00 6.648459e-01 6.648459e-01 3.324230e-01 -6.648459e-01 5.000000e-01 4.500000e+00 6.636503e-01 6.636503e-01 3.318251e-01 -6.636503e-01 6.000000e-01 4.500000e+00 6.621919e-01 6.621919e-01 3.310959e-01 -6.621919e-01 7.000000e-01 4.500000e+00 6.604724e-01 6.604724e-01 3.302362e-01 -6.604724e-01 8.000000e-01 4.500000e+00 6.584939e-01 6.584939e-01 3.292470e-01 -6.584939e-01 9.000000e-01 4.500000e+00 6.562589e-01 6.562589e-01 3.281294e-01 -6.562589e-01 1.000000e+00 4.500000e+00 6.537698e-01 6.537698e-01 3.268849e-01 -6.537698e-01 1.100000e+00 4.500000e+00 6.510297e-01 6.510297e-01 3.255149e-01 -6.510297e-01 1.200000e+00 4.500000e+00 6.480418e-01 6.480418e-01 3.240209e-01 -6.480418e-01 1.300000e+00 4.500000e+00 6.448097e-01 6.448097e-01 3.224049e-01 -6.448097e-01 1.400000e+00 4.500000e+00 6.413372e-01 6.413372e-01 3.206686e-01 -6.413372e-01 1.500000e+00 4.500000e+00 6.376281e-01 6.376281e-01 3.188141e-01 -6.376281e-01 1.600000e+00 4.500000e+00 6.336871e-01 6.336871e-01 3.168435e-01 -6.336871e-01 1.700000e+00 4.500000e+00 6.295186e-01 6.295186e-01 3.147593e-01 -6.295186e-01 1.800000e+00 4.500000e+00 6.251273e-01 6.251273e-01 3.125637e-01 -6.251273e-01 1.900000e+00 4.500000e+00 6.205184e-01 6.205184e-01 3.102592e-01 -6.205184e-01 2.000000e+00 4.500000e+00 6.156972e-01 6.156972e-01 3.078486e-01 -6.156972e-01 2.100000e+00 4.500000e+00 6.106691e-01 6.106691e-01 3.053346e-01 -6.106691e-01 2.200000e+00 4.500000e+00 6.054399e-01 6.054399e-01 3.027200e-01 -6.054399e-01 2.300000e+00 4.500000e+00 6.000154e-01 6.000154e-01 3.000077e-01 -6.000154e-01 2.400000e+00 4.500000e+00 5.944017e-01 5.944017e-01 2.972008e-01 -5.944017e-01 2.500000e+00 4.500000e+00 5.886050e-01 5.886050e-01 2.943025e-01 -5.886050e-01 2.600000e+00 4.500000e+00 5.826317e-01 5.826317e-01 2.913159e-01 -5.826317e-01 2.700000e+00 4.500000e+00 5.764884e-01 5.764884e-01 2.882442e-01 -5.764884e-01 2.800000e+00 4.500000e+00 5.701818e-01 5.701818e-01 2.850909e-01 -5.701818e-01 2.900000e+00 4.500000e+00 5.637187e-01 5.637187e-01 2.818593e-01 -5.637187e-01 3.000000e+00 4.500000e+00 5.571059e-01 5.571059e-01 2.785529e-01 -5.571059e-01 3.100000e+00 4.500000e+00 5.503505e-01 5.503505e-01 2.751752e-01 -5.503505e-01 3.200000e+00 4.500000e+00 5.434595e-01 5.434595e-01 2.717298e-01 -5.434595e-01 3.300000e+00 4.500000e+00 5.364403e-01 5.364403e-01 2.682202e-01 -5.364403e-01 3.400000e+00 4.500000e+00 5.293000e-01 5.293000e-01 2.646500e-01 -5.293000e-01 3.500000e+00 4.500000e+00 5.220458e-01 5.220458e-01 2.610229e-01 -5.220458e-01 3.600000e+00 4.500000e+00 5.146852e-01 5.146852e-01 2.573426e-01 -5.146852e-01 3.700000e+00 4.500000e+00 5.072253e-01 5.072253e-01 2.536126e-01 -5.072253e-01 3.800000e+00 4.500000e+00 4.996737e-01 4.996737e-01 2.498369e-01 -4.996737e-01 3.900000e+00 4.500000e+00 4.920377e-01 4.920377e-01 2.460188e-01 -4.920377e-01 4.000000e+00 4.500000e+00 4.843245e-01 4.843245e-01 2.421623e-01 -4.843245e-01 4.100000e+00 4.500000e+00 4.765417e-01 4.765417e-01 2.382709e-01 -4.765417e-01 4.200000e+00 4.500000e+00 4.686964e-01 4.686964e-01 2.343482e-01 -4.686964e-01 4.300000e+00 4.500000e+00 4.607960e-01 4.607960e-01 2.303980e-01 -4.607960e-01 4.400000e+00 4.500000e+00 4.528475e-01 4.528475e-01 2.264237e-01 -4.528475e-01 4.500000e+00 4.500000e+00 4.448581e-01 4.448581e-01 2.224291e-01 -4.448581e-01 4.600000e+00 4.500000e+00 4.368349e-01 4.368349e-01 2.184175e-01 -4.368349e-01 4.700000e+00 4.500000e+00 4.287849e-01 4.287849e-01 2.143924e-01 -4.287849e-01 4.800000e+00 4.500000e+00 4.207148e-01 4.207148e-01 2.103574e-01 -4.207148e-01 4.900000e+00 4.500000e+00 4.126316e-01 4.126316e-01 2.063158e-01 -4.126316e-01 -5.000000e+00 4.600000e+00 3.972458e-01 3.972458e-01 1.986229e-01 -3.972458e-01 -4.900000e+00 4.600000e+00 4.051897e-01 4.051897e-01 2.025948e-01 -4.051897e-01 -4.800000e+00 4.600000e+00 4.131271e-01 4.131271e-01 2.065636e-01 -4.131271e-01 -4.700000e+00 4.600000e+00 4.210516e-01 4.210516e-01 2.105258e-01 -4.210516e-01 -4.600000e+00 4.600000e+00 4.289564e-01 4.289564e-01 2.144782e-01 -4.289564e-01 -4.500000e+00 4.600000e+00 4.368349e-01 4.368349e-01 2.184175e-01 -4.368349e-01 -4.400000e+00 4.600000e+00 4.446802e-01 4.446802e-01 2.223401e-01 -4.446802e-01 -4.300000e+00 4.600000e+00 4.524853e-01 4.524853e-01 2.262427e-01 -4.524853e-01 -4.200000e+00 4.600000e+00 4.602433e-01 4.602433e-01 2.301217e-01 -4.602433e-01 -4.100000e+00 4.600000e+00 4.679471e-01 4.679471e-01 2.339736e-01 -4.679471e-01 -4.000000e+00 4.600000e+00 4.755896e-01 4.755896e-01 2.377948e-01 -4.755896e-01 -3.900000e+00 4.600000e+00 4.831636e-01 4.831636e-01 2.415818e-01 -4.831636e-01 -3.800000e+00 4.600000e+00 4.906619e-01 4.906619e-01 2.453310e-01 -4.906619e-01 -3.700000e+00 4.600000e+00 4.980773e-01 4.980773e-01 2.490387e-01 -4.980773e-01 -3.600000e+00 4.600000e+00 5.054026e-01 5.054026e-01 2.527013e-01 -5.054026e-01 -3.500000e+00 4.600000e+00 5.126305e-01 5.126305e-01 2.563153e-01 -5.126305e-01 -3.400000e+00 4.600000e+00 5.197538e-01 5.197538e-01 2.598769e-01 -5.197538e-01 -3.300000e+00 4.600000e+00 5.267655e-01 5.267655e-01 2.633827e-01 -5.267655e-01 -3.200000e+00 4.600000e+00 5.336581e-01 5.336581e-01 2.668290e-01 -5.336581e-01 -3.100000e+00 4.600000e+00 5.404247e-01 5.404247e-01 2.702124e-01 -5.404247e-01 -3.000000e+00 4.600000e+00 5.470583e-01 5.470583e-01 2.735291e-01 -5.470583e-01 -2.900000e+00 4.600000e+00 5.535518e-01 5.535518e-01 2.767759e-01 -5.535518e-01 -2.800000e+00 4.600000e+00 5.598984e-01 5.598984e-01 2.799492e-01 -5.598984e-01 -2.700000e+00 4.600000e+00 5.660913e-01 5.660913e-01 2.830456e-01 -5.660913e-01 -2.600000e+00 4.600000e+00 5.721238e-01 5.721238e-01 2.860619e-01 -5.721238e-01 -2.500000e+00 4.600000e+00 5.779893e-01 5.779893e-01 2.889946e-01 -5.779893e-01 -2.400000e+00 4.600000e+00 5.836814e-01 5.836814e-01 2.918407e-01 -5.836814e-01 -2.300000e+00 4.600000e+00 5.891939e-01 5.891939e-01 2.945970e-01 -5.891939e-01 -2.200000e+00 4.600000e+00 5.945206e-01 5.945206e-01 2.972603e-01 -5.945206e-01 -2.100000e+00 4.600000e+00 5.996555e-01 5.996555e-01 2.998278e-01 -5.996555e-01 -2.000000e+00 4.600000e+00 6.045929e-01 6.045929e-01 3.022965e-01 -6.045929e-01 -1.900000e+00 4.600000e+00 6.093271e-01 6.093271e-01 3.046636e-01 -6.093271e-01 -1.800000e+00 4.600000e+00 6.138529e-01 6.138529e-01 3.069265e-01 -6.138529e-01 -1.700000e+00 4.600000e+00 6.181650e-01 6.181650e-01 3.090825e-01 -6.181650e-01 -1.600000e+00 4.600000e+00 6.222583e-01 6.222583e-01 3.111292e-01 -6.222583e-01 -1.500000e+00 4.600000e+00 6.261283e-01 6.261283e-01 3.130642e-01 -6.261283e-01 -1.400000e+00 4.600000e+00 6.297704e-01 6.297704e-01 3.148852e-01 -6.297704e-01 -1.300000e+00 4.600000e+00 6.331804e-01 6.331804e-01 3.165902e-01 -6.331804e-01 -1.200000e+00 4.600000e+00 6.363542e-01 6.363542e-01 3.181771e-01 -6.363542e-01 -1.100000e+00 4.600000e+00 6.392882e-01 6.392882e-01 3.196441e-01 -6.392882e-01 -1.000000e+00 4.600000e+00 6.419788e-01 6.419788e-01 3.209894e-01 -6.419788e-01 -9.000000e-01 4.600000e+00 6.444230e-01 6.444230e-01 3.222115e-01 -6.444230e-01 -8.000000e-01 4.600000e+00 6.466178e-01 6.466178e-01 3.233089e-01 -6.466178e-01 -7.000000e-01 4.600000e+00 6.485605e-01 6.485605e-01 3.242803e-01 -6.485605e-01 -6.000000e-01 4.600000e+00 6.502489e-01 6.502489e-01 3.251245e-01 -6.502489e-01 -5.000000e-01 4.600000e+00 6.516811e-01 6.516811e-01 3.258406e-01 -6.516811e-01 -4.000000e-01 4.600000e+00 6.528552e-01 6.528552e-01 3.264276e-01 -6.528552e-01 -3.000000e-01 4.600000e+00 6.537698e-01 6.537698e-01 3.268849e-01 -6.537698e-01 -2.000000e-01 4.600000e+00 6.544239e-01 6.544239e-01 3.272119e-01 -6.544239e-01 -1.000000e-01 4.600000e+00 6.548167e-01 6.548167e-01 3.274083e-01 -6.548167e-01 0.000000e+00 4.600000e+00 6.549476e-01 6.549476e-01 3.274738e-01 -6.549476e-01 1.000000e-01 4.600000e+00 6.548167e-01 6.548167e-01 3.274083e-01 -6.548167e-01 2.000000e-01 4.600000e+00 6.544239e-01 6.544239e-01 3.272119e-01 -6.544239e-01 3.000000e-01 4.600000e+00 6.537698e-01 6.537698e-01 3.268849e-01 -6.537698e-01 4.000000e-01 4.600000e+00 6.528552e-01 6.528552e-01 3.264276e-01 -6.528552e-01 5.000000e-01 4.600000e+00 6.516811e-01 6.516811e-01 3.258406e-01 -6.516811e-01 6.000000e-01 4.600000e+00 6.502489e-01 6.502489e-01 3.251245e-01 -6.502489e-01 7.000000e-01 4.600000e+00 6.485605e-01 6.485605e-01 3.242803e-01 -6.485605e-01 8.000000e-01 4.600000e+00 6.466178e-01 6.466178e-01 3.233089e-01 -6.466178e-01 9.000000e-01 4.600000e+00 6.444230e-01 6.444230e-01 3.222115e-01 -6.444230e-01 1.000000e+00 4.600000e+00 6.419788e-01 6.419788e-01 3.209894e-01 -6.419788e-01 1.100000e+00 4.600000e+00 6.392882e-01 6.392882e-01 3.196441e-01 -6.392882e-01 1.200000e+00 4.600000e+00 6.363542e-01 6.363542e-01 3.181771e-01 -6.363542e-01 1.300000e+00 4.600000e+00 6.331804e-01 6.331804e-01 3.165902e-01 -6.331804e-01 1.400000e+00 4.600000e+00 6.297704e-01 6.297704e-01 3.148852e-01 -6.297704e-01 1.500000e+00 4.600000e+00 6.261283e-01 6.261283e-01 3.130642e-01 -6.261283e-01 1.600000e+00 4.600000e+00 6.222583e-01 6.222583e-01 3.111292e-01 -6.222583e-01 1.700000e+00 4.600000e+00 6.181650e-01 6.181650e-01 3.090825e-01 -6.181650e-01 1.800000e+00 4.600000e+00 6.138529e-01 6.138529e-01 3.069265e-01 -6.138529e-01 1.900000e+00 4.600000e+00 6.093271e-01 6.093271e-01 3.046636e-01 -6.093271e-01 2.000000e+00 4.600000e+00 6.045929e-01 6.045929e-01 3.022965e-01 -6.045929e-01 2.100000e+00 4.600000e+00 5.996555e-01 5.996555e-01 2.998278e-01 -5.996555e-01 2.200000e+00 4.600000e+00 5.945206e-01 5.945206e-01 2.972603e-01 -5.945206e-01 2.300000e+00 4.600000e+00 5.891939e-01 5.891939e-01 2.945970e-01 -5.891939e-01 2.400000e+00 4.600000e+00 5.836814e-01 5.836814e-01 2.918407e-01 -5.836814e-01 2.500000e+00 4.600000e+00 5.779893e-01 5.779893e-01 2.889946e-01 -5.779893e-01 2.600000e+00 4.600000e+00 5.721238e-01 5.721238e-01 2.860619e-01 -5.721238e-01 2.700000e+00 4.600000e+00 5.660913e-01 5.660913e-01 2.830456e-01 -5.660913e-01 2.800000e+00 4.600000e+00 5.598984e-01 5.598984e-01 2.799492e-01 -5.598984e-01 2.900000e+00 4.600000e+00 5.535518e-01 5.535518e-01 2.767759e-01 -5.535518e-01 3.000000e+00 4.600000e+00 5.470583e-01 5.470583e-01 2.735291e-01 -5.470583e-01 3.100000e+00 4.600000e+00 5.404247e-01 5.404247e-01 2.702124e-01 -5.404247e-01 3.200000e+00 4.600000e+00 5.336581e-01 5.336581e-01 2.668290e-01 -5.336581e-01 3.300000e+00 4.600000e+00 5.267655e-01 5.267655e-01 2.633827e-01 -5.267655e-01 3.400000e+00 4.600000e+00 5.197538e-01 5.197538e-01 2.598769e-01 -5.197538e-01 3.500000e+00 4.600000e+00 5.126305e-01 5.126305e-01 2.563153e-01 -5.126305e-01 3.600000e+00 4.600000e+00 5.054026e-01 5.054026e-01 2.527013e-01 -5.054026e-01 3.700000e+00 4.600000e+00 4.980773e-01 4.980773e-01 2.490387e-01 -4.980773e-01 3.800000e+00 4.600000e+00 4.906619e-01 4.906619e-01 2.453310e-01 -4.906619e-01 3.900000e+00 4.600000e+00 4.831636e-01 4.831636e-01 2.415818e-01 -4.831636e-01 4.000000e+00 4.600000e+00 4.755896e-01 4.755896e-01 2.377948e-01 -4.755896e-01 4.100000e+00 4.600000e+00 4.679471e-01 4.679471e-01 2.339736e-01 -4.679471e-01 4.200000e+00 4.600000e+00 4.602433e-01 4.602433e-01 2.301217e-01 -4.602433e-01 4.300000e+00 4.600000e+00 4.524853e-01 4.524853e-01 2.262427e-01 -4.524853e-01 4.400000e+00 4.600000e+00 4.446802e-01 4.446802e-01 2.223401e-01 -4.446802e-01 4.500000e+00 4.600000e+00 4.368349e-01 4.368349e-01 2.184175e-01 -4.368349e-01 4.600000e+00 4.600000e+00 4.289564e-01 4.289564e-01 2.144782e-01 -4.289564e-01 4.700000e+00 4.600000e+00 4.210516e-01 4.210516e-01 2.105258e-01 -4.210516e-01 4.800000e+00 4.600000e+00 4.131271e-01 4.131271e-01 2.065636e-01 -4.131271e-01 4.900000e+00 4.600000e+00 4.051897e-01 4.051897e-01 2.025948e-01 -4.051897e-01 -5.000000e+00 4.700000e+00 3.899254e-01 3.899254e-01 1.949627e-01 -3.899254e-01 -4.900000e+00 4.700000e+00 3.977228e-01 3.977228e-01 1.988614e-01 -3.977228e-01 -4.800000e+00 4.700000e+00 4.055140e-01 4.055140e-01 2.027570e-01 -4.055140e-01 -4.700000e+00 4.700000e+00 4.132924e-01 4.132924e-01 2.066462e-01 -4.132924e-01 -4.600000e+00 4.700000e+00 4.210516e-01 4.210516e-01 2.105258e-01 -4.210516e-01 -4.500000e+00 4.700000e+00 4.287849e-01 4.287849e-01 2.143924e-01 -4.287849e-01 -4.400000e+00 4.700000e+00 4.364856e-01 4.364856e-01 2.182428e-01 -4.364856e-01 -4.300000e+00 4.700000e+00 4.441469e-01 4.441469e-01 2.220734e-01 -4.441469e-01 -4.200000e+00 4.700000e+00 4.517620e-01 4.517620e-01 2.258810e-01 -4.517620e-01 -4.100000e+00 4.700000e+00 4.593238e-01 4.593238e-01 2.296619e-01 -4.593238e-01 -4.000000e+00 4.700000e+00 4.668254e-01 4.668254e-01 2.334127e-01 -4.668254e-01 -3.900000e+00 4.700000e+00 4.742598e-01 4.742598e-01 2.371299e-01 -4.742598e-01 -3.800000e+00 4.700000e+00 4.816200e-01 4.816200e-01 2.408100e-01 -4.816200e-01 -3.700000e+00 4.700000e+00 4.888987e-01 4.888987e-01 2.444493e-01 -4.888987e-01 -3.600000e+00 4.700000e+00 4.960890e-01 4.960890e-01 2.480445e-01 -4.960890e-01 -3.500000e+00 4.700000e+00 5.031837e-01 5.031837e-01 2.515919e-01 -5.031837e-01 -3.400000e+00 4.700000e+00 5.101758e-01 5.101758e-01 2.550879e-01 -5.101758e-01 -3.300000e+00 4.700000e+00 5.170582e-01 5.170582e-01 2.585291e-01 -5.170582e-01 -3.200000e+00 4.700000e+00 5.238238e-01 5.238238e-01 2.619119e-01 -5.238238e-01 -3.100000e+00 4.700000e+00 5.304657e-01 5.304657e-01 2.652329e-01 -5.304657e-01 -3.000000e+00 4.700000e+00 5.369771e-01 5.369771e-01 2.684885e-01 -5.369771e-01 -2.900000e+00 4.700000e+00 5.433509e-01 5.433509e-01 2.716754e-01 -5.433509e-01 -2.800000e+00 4.700000e+00 5.495806e-01 5.495806e-01 2.747903e-01 -5.495806e-01 -2.700000e+00 4.700000e+00 5.556593e-01 5.556593e-01 2.778296e-01 -5.556593e-01 -2.600000e+00 4.700000e+00 5.615807e-01 5.615807e-01 2.807903e-01 -5.615807e-01 -2.500000e+00 4.700000e+00 5.673380e-01 5.673380e-01 2.836690e-01 -5.673380e-01 -2.400000e+00 4.700000e+00 5.729253e-01 5.729253e-01 2.864627e-01 -5.729253e-01 -2.300000e+00 4.700000e+00 5.783362e-01 5.783362e-01 2.891681e-01 -5.783362e-01 -2.200000e+00 4.700000e+00 5.835647e-01 5.835647e-01 2.917823e-01 -5.835647e-01 -2.100000e+00 4.700000e+00 5.886050e-01 5.886050e-01 2.943025e-01 -5.886050e-01 -2.000000e+00 4.700000e+00 5.934514e-01 5.934514e-01 2.967257e-01 -5.934514e-01 -1.900000e+00 4.700000e+00 5.980985e-01 5.980985e-01 2.990492e-01 -5.980985e-01 -1.800000e+00 4.700000e+00 6.025408e-01 6.025408e-01 3.012704e-01 -6.025408e-01 -1.700000e+00 4.700000e+00 6.067734e-01 6.067734e-01 3.033867e-01 -6.067734e-01 -1.600000e+00 4.700000e+00 6.107913e-01 6.107913e-01 3.053957e-01 -6.107913e-01 -1.500000e+00 4.700000e+00 6.145900e-01 6.145900e-01 3.072950e-01 -6.145900e-01 -1.400000e+00 4.700000e+00 6.181650e-01 6.181650e-01 3.090825e-01 -6.181650e-01 -1.300000e+00 4.700000e+00 6.215121e-01 6.215121e-01 3.107560e-01 -6.215121e-01 -1.200000e+00 4.700000e+00 6.246274e-01 6.246274e-01 3.123137e-01 -6.246274e-01 -1.100000e+00 4.700000e+00 6.275073e-01 6.275073e-01 3.137537e-01 -6.275073e-01 -1.000000e+00 4.700000e+00 6.301484e-01 6.301484e-01 3.150742e-01 -6.301484e-01 -9.000000e-01 4.700000e+00 6.325475e-01 6.325475e-01 3.162737e-01 -6.325475e-01 -8.000000e-01 4.700000e+00 6.347018e-01 6.347018e-01 3.173509e-01 -6.347018e-01 -7.000000e-01 4.700000e+00 6.366088e-01 6.366088e-01 3.183044e-01 -6.366088e-01 -6.000000e-01 4.700000e+00 6.382661e-01 6.382661e-01 3.191331e-01 -6.382661e-01 -5.000000e-01 4.700000e+00 6.396719e-01 6.396719e-01 3.198359e-01 -6.396719e-01 -4.000000e-01 4.700000e+00 6.408243e-01 6.408243e-01 3.204122e-01 -6.408243e-01 -3.000000e-01 4.700000e+00 6.417221e-01 6.417221e-01 3.208610e-01 -6.417221e-01 -2.000000e-01 4.700000e+00 6.423641e-01 6.423641e-01 3.211821e-01 -6.423641e-01 -1.000000e-01 4.700000e+00 6.427497e-01 6.427497e-01 3.213748e-01 -6.427497e-01 0.000000e+00 4.700000e+00 6.428782e-01 6.428782e-01 3.214391e-01 -6.428782e-01 1.000000e-01 4.700000e+00 6.427497e-01 6.427497e-01 3.213748e-01 -6.427497e-01 2.000000e-01 4.700000e+00 6.423641e-01 6.423641e-01 3.211821e-01 -6.423641e-01 3.000000e-01 4.700000e+00 6.417221e-01 6.417221e-01 3.208610e-01 -6.417221e-01 4.000000e-01 4.700000e+00 6.408243e-01 6.408243e-01 3.204122e-01 -6.408243e-01 5.000000e-01 4.700000e+00 6.396719e-01 6.396719e-01 3.198359e-01 -6.396719e-01 6.000000e-01 4.700000e+00 6.382661e-01 6.382661e-01 3.191331e-01 -6.382661e-01 7.000000e-01 4.700000e+00 6.366088e-01 6.366088e-01 3.183044e-01 -6.366088e-01 8.000000e-01 4.700000e+00 6.347018e-01 6.347018e-01 3.173509e-01 -6.347018e-01 9.000000e-01 4.700000e+00 6.325475e-01 6.325475e-01 3.162737e-01 -6.325475e-01 1.000000e+00 4.700000e+00 6.301484e-01 6.301484e-01 3.150742e-01 -6.301484e-01 1.100000e+00 4.700000e+00 6.275073e-01 6.275073e-01 3.137537e-01 -6.275073e-01 1.200000e+00 4.700000e+00 6.246274e-01 6.246274e-01 3.123137e-01 -6.246274e-01 1.300000e+00 4.700000e+00 6.215121e-01 6.215121e-01 3.107560e-01 -6.215121e-01 1.400000e+00 4.700000e+00 6.181650e-01 6.181650e-01 3.090825e-01 -6.181650e-01 1.500000e+00 4.700000e+00 6.145900e-01 6.145900e-01 3.072950e-01 -6.145900e-01 1.600000e+00 4.700000e+00 6.107913e-01 6.107913e-01 3.053957e-01 -6.107913e-01 1.700000e+00 4.700000e+00 6.067734e-01 6.067734e-01 3.033867e-01 -6.067734e-01 1.800000e+00 4.700000e+00 6.025408e-01 6.025408e-01 3.012704e-01 -6.025408e-01 1.900000e+00 4.700000e+00 5.980985e-01 5.980985e-01 2.990492e-01 -5.980985e-01 2.000000e+00 4.700000e+00 5.934514e-01 5.934514e-01 2.967257e-01 -5.934514e-01 2.100000e+00 4.700000e+00 5.886050e-01 5.886050e-01 2.943025e-01 -5.886050e-01 2.200000e+00 4.700000e+00 5.835647e-01 5.835647e-01 2.917823e-01 -5.835647e-01 2.300000e+00 4.700000e+00 5.783362e-01 5.783362e-01 2.891681e-01 -5.783362e-01 2.400000e+00 4.700000e+00 5.729253e-01 5.729253e-01 2.864627e-01 -5.729253e-01 2.500000e+00 4.700000e+00 5.673380e-01 5.673380e-01 2.836690e-01 -5.673380e-01 2.600000e+00 4.700000e+00 5.615807e-01 5.615807e-01 2.807903e-01 -5.615807e-01 2.700000e+00 4.700000e+00 5.556593e-01 5.556593e-01 2.778296e-01 -5.556593e-01 2.800000e+00 4.700000e+00 5.495806e-01 5.495806e-01 2.747903e-01 -5.495806e-01 2.900000e+00 4.700000e+00 5.433509e-01 5.433509e-01 2.716754e-01 -5.433509e-01 3.000000e+00 4.700000e+00 5.369771e-01 5.369771e-01 2.684885e-01 -5.369771e-01 3.100000e+00 4.700000e+00 5.304657e-01 5.304657e-01 2.652329e-01 -5.304657e-01 3.200000e+00 4.700000e+00 5.238238e-01 5.238238e-01 2.619119e-01 -5.238238e-01 3.300000e+00 4.700000e+00 5.170582e-01 5.170582e-01 2.585291e-01 -5.170582e-01 3.400000e+00 4.700000e+00 5.101758e-01 5.101758e-01 2.550879e-01 -5.101758e-01 3.500000e+00 4.700000e+00 5.031837e-01 5.031837e-01 2.515919e-01 -5.031837e-01 3.600000e+00 4.700000e+00 4.960890e-01 4.960890e-01 2.480445e-01 -4.960890e-01 3.700000e+00 4.700000e+00 4.888987e-01 4.888987e-01 2.444493e-01 -4.888987e-01 3.800000e+00 4.700000e+00 4.816200e-01 4.816200e-01 2.408100e-01 -4.816200e-01 3.900000e+00 4.700000e+00 4.742598e-01 4.742598e-01 2.371299e-01 -4.742598e-01 4.000000e+00 4.700000e+00 4.668254e-01 4.668254e-01 2.334127e-01 -4.668254e-01 4.100000e+00 4.700000e+00 4.593238e-01 4.593238e-01 2.296619e-01 -4.593238e-01 4.200000e+00 4.700000e+00 4.517620e-01 4.517620e-01 2.258810e-01 -4.517620e-01 4.300000e+00 4.700000e+00 4.441469e-01 4.441469e-01 2.220734e-01 -4.441469e-01 4.400000e+00 4.700000e+00 4.364856e-01 4.364856e-01 2.182428e-01 -4.364856e-01 4.500000e+00 4.700000e+00 4.287849e-01 4.287849e-01 2.143924e-01 -4.287849e-01 4.600000e+00 4.700000e+00 4.210516e-01 4.210516e-01 2.105258e-01 -4.210516e-01 4.700000e+00 4.700000e+00 4.132924e-01 4.132924e-01 2.066462e-01 -4.132924e-01 4.800000e+00 4.700000e+00 4.055140e-01 4.055140e-01 2.027570e-01 -4.055140e-01 4.900000e+00 4.700000e+00 3.977228e-01 3.977228e-01 1.988614e-01 -3.977228e-01 -5.000000e+00 4.800000e+00 3.825867e-01 3.825867e-01 1.912933e-01 -3.825867e-01 -4.900000e+00 4.800000e+00 3.902374e-01 3.902374e-01 1.951187e-01 -3.902374e-01 -4.800000e+00 4.800000e+00 3.978819e-01 3.978819e-01 1.989409e-01 -3.978819e-01 -4.700000e+00 4.800000e+00 4.055140e-01 4.055140e-01 2.027570e-01 -4.055140e-01 -4.600000e+00 4.800000e+00 4.131271e-01 4.131271e-01 2.065636e-01 -4.131271e-01 -4.500000e+00 4.800000e+00 4.207148e-01 4.207148e-01 2.103574e-01 -4.207148e-01 -4.400000e+00 4.800000e+00 4.282706e-01 4.282706e-01 2.141353e-01 -4.282706e-01 -4.300000e+00 4.800000e+00 4.357877e-01 4.357877e-01 2.178939e-01 -4.357877e-01 -4.200000e+00 4.800000e+00 4.432594e-01 4.432594e-01 2.216297e-01 -4.432594e-01 -4.100000e+00 4.800000e+00 4.506789e-01 4.506789e-01 2.253395e-01 -4.506789e-01 -4.000000e+00 4.800000e+00 4.580394e-01 4.580394e-01 2.290197e-01 -4.580394e-01 -3.900000e+00 4.800000e+00 4.653339e-01 4.653339e-01 2.326670e-01 -4.653339e-01 -3.800000e+00 4.800000e+00 4.725555e-01 4.725555e-01 2.362778e-01 -4.725555e-01 -3.700000e+00 4.800000e+00 4.796973e-01 4.796973e-01 2.398486e-01 -4.796973e-01 -3.600000e+00 4.800000e+00 4.867522e-01 4.867522e-01 2.433761e-01 -4.867522e-01 -3.500000e+00 4.800000e+00 4.937134e-01 4.937134e-01 2.468567e-01 -4.937134e-01 -3.400000e+00 4.800000e+00 5.005739e-01 5.005739e-01 2.502870e-01 -5.005739e-01 -3.300000e+00 4.800000e+00 5.073267e-01 5.073267e-01 2.536634e-01 -5.073267e-01 -3.200000e+00 4.800000e+00 5.139651e-01 5.139651e-01 2.569825e-01 -5.139651e-01 -3.100000e+00 4.800000e+00 5.204820e-01 5.204820e-01 2.602410e-01 -5.204820e-01 -3.000000e+00 4.800000e+00 5.268708e-01 5.268708e-01 2.634354e-01 -5.268708e-01 -2.900000e+00 4.800000e+00 5.331246e-01 5.331246e-01 2.665623e-01 -5.331246e-01 -2.800000e+00 4.800000e+00 5.392370e-01 5.392370e-01 2.696185e-01 -5.392370e-01 -2.700000e+00 4.800000e+00 5.452014e-01 5.452014e-01 2.726007e-01 -5.452014e-01 -2.600000e+00 4.800000e+00 5.510113e-01 5.510113e-01 2.755056e-01 -5.510113e-01 -2.500000e+00 4.800000e+00 5.566604e-01 5.566604e-01 2.783302e-01 -5.566604e-01 -2.400000e+00 4.800000e+00 5.621424e-01 5.621424e-01 2.810712e-01 -5.621424e-01 -2.300000e+00 4.800000e+00 5.674515e-01 5.674515e-01 2.837257e-01 -5.674515e-01 -2.200000e+00 4.800000e+00 5.725816e-01 5.725816e-01 2.862908e-01 -5.725816e-01 -2.100000e+00 4.800000e+00 5.775270e-01 5.775270e-01 2.887635e-01 -5.775270e-01 -2.000000e+00 4.800000e+00 5.822822e-01 5.822822e-01 2.911411e-01 -5.822822e-01 -1.900000e+00 4.800000e+00 5.868418e-01 5.868418e-01 2.934209e-01 -5.868418e-01 -1.800000e+00 4.800000e+00 5.912005e-01 5.912005e-01 2.956003e-01 -5.912005e-01 -1.700000e+00 4.800000e+00 5.953534e-01 5.953534e-01 2.976767e-01 -5.953534e-01 -1.600000e+00 4.800000e+00 5.992958e-01 5.992958e-01 2.996479e-01 -5.992958e-01 -1.500000e+00 4.800000e+00 6.030229e-01 6.030229e-01 3.015115e-01 -6.030229e-01 -1.400000e+00 4.800000e+00 6.065307e-01 6.065307e-01 3.032653e-01 -6.065307e-01 -1.300000e+00 4.800000e+00 6.098148e-01 6.098148e-01 3.049074e-01 -6.098148e-01 -1.200000e+00 4.800000e+00 6.128715e-01 6.128715e-01 3.064357e-01 -6.128715e-01 -1.100000e+00 4.800000e+00 6.156972e-01 6.156972e-01 3.078486e-01 -6.156972e-01 -1.000000e+00 4.800000e+00 6.182885e-01 6.182885e-01 3.091443e-01 -6.182885e-01 -9.000000e-01 4.800000e+00 6.206425e-01 6.206425e-01 3.103212e-01 -6.206425e-01 -8.000000e-01 4.800000e+00 6.227563e-01 6.227563e-01 3.113782e-01 -6.227563e-01 -7.000000e-01 4.800000e+00 6.246274e-01 6.246274e-01 3.123137e-01 -6.246274e-01 -6.000000e-01 4.800000e+00 6.262535e-01 6.262535e-01 3.131267e-01 -6.262535e-01 -5.000000e-01 4.800000e+00 6.276328e-01 6.276328e-01 3.138164e-01 -6.276328e-01 -4.000000e-01 4.800000e+00 6.287636e-01 6.287636e-01 3.143818e-01 -6.287636e-01 -3.000000e-01 4.800000e+00 6.296445e-01 6.296445e-01 3.148222e-01 -6.296445e-01 -2.000000e-01 4.800000e+00 6.302744e-01 6.302744e-01 3.151372e-01 -6.302744e-01 -1.000000e-01 4.800000e+00 6.306527e-01 6.306527e-01 3.153263e-01 -6.306527e-01 0.000000e+00 4.800000e+00 6.307788e-01 6.307788e-01 3.153894e-01 -6.307788e-01 1.000000e-01 4.800000e+00 6.306527e-01 6.306527e-01 3.153263e-01 -6.306527e-01 2.000000e-01 4.800000e+00 6.302744e-01 6.302744e-01 3.151372e-01 -6.302744e-01 3.000000e-01 4.800000e+00 6.296445e-01 6.296445e-01 3.148222e-01 -6.296445e-01 4.000000e-01 4.800000e+00 6.287636e-01 6.287636e-01 3.143818e-01 -6.287636e-01 5.000000e-01 4.800000e+00 6.276328e-01 6.276328e-01 3.138164e-01 -6.276328e-01 6.000000e-01 4.800000e+00 6.262535e-01 6.262535e-01 3.131267e-01 -6.262535e-01 7.000000e-01 4.800000e+00 6.246274e-01 6.246274e-01 3.123137e-01 -6.246274e-01 8.000000e-01 4.800000e+00 6.227563e-01 6.227563e-01 3.113782e-01 -6.227563e-01 9.000000e-01 4.800000e+00 6.206425e-01 6.206425e-01 3.103212e-01 -6.206425e-01 1.000000e+00 4.800000e+00 6.182885e-01 6.182885e-01 3.091443e-01 -6.182885e-01 1.100000e+00 4.800000e+00 6.156972e-01 6.156972e-01 3.078486e-01 -6.156972e-01 1.200000e+00 4.800000e+00 6.128715e-01 6.128715e-01 3.064357e-01 -6.128715e-01 1.300000e+00 4.800000e+00 6.098148e-01 6.098148e-01 3.049074e-01 -6.098148e-01 1.400000e+00 4.800000e+00 6.065307e-01 6.065307e-01 3.032653e-01 -6.065307e-01 1.500000e+00 4.800000e+00 6.030229e-01 6.030229e-01 3.015115e-01 -6.030229e-01 1.600000e+00 4.800000e+00 5.992958e-01 5.992958e-01 2.996479e-01 -5.992958e-01 1.700000e+00 4.800000e+00 5.953534e-01 5.953534e-01 2.976767e-01 -5.953534e-01 1.800000e+00 4.800000e+00 5.912005e-01 5.912005e-01 2.956003e-01 -5.912005e-01 1.900000e+00 4.800000e+00 5.868418e-01 5.868418e-01 2.934209e-01 -5.868418e-01 2.000000e+00 4.800000e+00 5.822822e-01 5.822822e-01 2.911411e-01 -5.822822e-01 2.100000e+00 4.800000e+00 5.775270e-01 5.775270e-01 2.887635e-01 -5.775270e-01 2.200000e+00 4.800000e+00 5.725816e-01 5.725816e-01 2.862908e-01 -5.725816e-01 2.300000e+00 4.800000e+00 5.674515e-01 5.674515e-01 2.837257e-01 -5.674515e-01 2.400000e+00 4.800000e+00 5.621424e-01 5.621424e-01 2.810712e-01 -5.621424e-01 2.500000e+00 4.800000e+00 5.566604e-01 5.566604e-01 2.783302e-01 -5.566604e-01 2.600000e+00 4.800000e+00 5.510113e-01 5.510113e-01 2.755056e-01 -5.510113e-01 2.700000e+00 4.800000e+00 5.452014e-01 5.452014e-01 2.726007e-01 -5.452014e-01 2.800000e+00 4.800000e+00 5.392370e-01 5.392370e-01 2.696185e-01 -5.392370e-01 2.900000e+00 4.800000e+00 5.331246e-01 5.331246e-01 2.665623e-01 -5.331246e-01 3.000000e+00 4.800000e+00 5.268708e-01 5.268708e-01 2.634354e-01 -5.268708e-01 3.100000e+00 4.800000e+00 5.204820e-01 5.204820e-01 2.602410e-01 -5.204820e-01 3.200000e+00 4.800000e+00 5.139651e-01 5.139651e-01 2.569825e-01 -5.139651e-01 3.300000e+00 4.800000e+00 5.073267e-01 5.073267e-01 2.536634e-01 -5.073267e-01 3.400000e+00 4.800000e+00 5.005739e-01 5.005739e-01 2.502870e-01 -5.005739e-01 3.500000e+00 4.800000e+00 4.937134e-01 4.937134e-01 2.468567e-01 -4.937134e-01 3.600000e+00 4.800000e+00 4.867522e-01 4.867522e-01 2.433761e-01 -4.867522e-01 3.700000e+00 4.800000e+00 4.796973e-01 4.796973e-01 2.398486e-01 -4.796973e-01 3.800000e+00 4.800000e+00 4.725555e-01 4.725555e-01 2.362778e-01 -4.725555e-01 3.900000e+00 4.800000e+00 4.653339e-01 4.653339e-01 2.326670e-01 -4.653339e-01 4.000000e+00 4.800000e+00 4.580394e-01 4.580394e-01 2.290197e-01 -4.580394e-01 4.100000e+00 4.800000e+00 4.506789e-01 4.506789e-01 2.253395e-01 -4.506789e-01 4.200000e+00 4.800000e+00 4.432594e-01 4.432594e-01 2.216297e-01 -4.432594e-01 4.300000e+00 4.800000e+00 4.357877e-01 4.357877e-01 2.178939e-01 -4.357877e-01 4.400000e+00 4.800000e+00 4.282706e-01 4.282706e-01 2.141353e-01 -4.282706e-01 4.500000e+00 4.800000e+00 4.207148e-01 4.207148e-01 2.103574e-01 -4.207148e-01 4.600000e+00 4.800000e+00 4.131271e-01 4.131271e-01 2.065636e-01 -4.131271e-01 4.700000e+00 4.800000e+00 4.055140e-01 4.055140e-01 2.027570e-01 -4.055140e-01 4.800000e+00 4.800000e+00 3.978819e-01 3.978819e-01 1.989409e-01 -3.978819e-01 4.900000e+00 4.800000e+00 3.902374e-01 3.902374e-01 1.951187e-01 -3.902374e-01 -5.000000e+00 4.900000e+00 3.752360e-01 3.752360e-01 1.876180e-01 -3.752360e-01 -4.900000e+00 4.900000e+00 3.827398e-01 3.827398e-01 1.913699e-01 -3.827398e-01 -4.800000e+00 4.900000e+00 3.902374e-01 3.902374e-01 1.951187e-01 -3.902374e-01 -4.700000e+00 4.900000e+00 3.977228e-01 3.977228e-01 1.988614e-01 -3.977228e-01 -4.600000e+00 4.900000e+00 4.051897e-01 4.051897e-01 2.025948e-01 -4.051897e-01 -4.500000e+00 4.900000e+00 4.126316e-01 4.126316e-01 2.063158e-01 -4.126316e-01 -4.400000e+00 4.900000e+00 4.200422e-01 4.200422e-01 2.100211e-01 -4.200422e-01 -4.300000e+00 4.900000e+00 4.274149e-01 4.274149e-01 2.137075e-01 -4.274149e-01 -4.200000e+00 4.900000e+00 4.347431e-01 4.347431e-01 2.173716e-01 -4.347431e-01 -4.100000e+00 4.900000e+00 4.420200e-01 4.420200e-01 2.210100e-01 -4.420200e-01 -4.000000e+00 4.900000e+00 4.492391e-01 4.492391e-01 2.246195e-01 -4.492391e-01 -3.900000e+00 4.900000e+00 4.563934e-01 4.563934e-01 2.281967e-01 -4.563934e-01 -3.800000e+00 4.900000e+00 4.634763e-01 4.634763e-01 2.317382e-01 -4.634763e-01 -3.700000e+00 4.900000e+00 4.704808e-01 4.704808e-01 2.352404e-01 -4.704808e-01 -3.600000e+00 4.900000e+00 4.774002e-01 4.774002e-01 2.387001e-01 -4.774002e-01 -3.500000e+00 4.900000e+00 4.842277e-01 4.842277e-01 2.421139e-01 -4.842277e-01 -3.400000e+00 4.900000e+00 4.909564e-01 4.909564e-01 2.454782e-01 -4.909564e-01 -3.300000e+00 4.900000e+00 4.975795e-01 4.975795e-01 2.487897e-01 -4.975795e-01 -3.200000e+00 4.900000e+00 5.040902e-01 5.040902e-01 2.520451e-01 -5.040902e-01 -3.100000e+00 4.900000e+00 5.104820e-01 5.104820e-01 2.552410e-01 -5.104820e-01 -3.000000e+00 4.900000e+00 5.167480e-01 5.167480e-01 2.583740e-01 -5.167480e-01 -2.900000e+00 4.900000e+00 5.228817e-01 5.228817e-01 2.614408e-01 -5.228817e-01 -2.800000e+00 4.900000e+00 5.288767e-01 5.288767e-01 2.644383e-01 -5.288767e-01 -2.700000e+00 4.900000e+00 5.347264e-01 5.347264e-01 2.673632e-01 -5.347264e-01 -2.600000e+00 4.900000e+00 5.404246e-01 5.404246e-01 2.702123e-01 -5.404246e-01 -2.500000e+00 4.900000e+00 5.459652e-01 5.459652e-01 2.729826e-01 -5.459652e-01 -2.400000e+00 4.900000e+00 5.513420e-01 5.513420e-01 2.756710e-01 -5.513420e-01 -2.300000e+00 4.900000e+00 5.565490e-01 5.565490e-01 2.782745e-01 -5.565490e-01 -2.200000e+00 4.900000e+00 5.615806e-01 5.615806e-01 2.807903e-01 -5.615806e-01 -2.100000e+00 4.900000e+00 5.664310e-01 5.664310e-01 2.832155e-01 -5.664310e-01 -2.000000e+00 4.900000e+00 5.710948e-01 5.710948e-01 2.855474e-01 -5.710948e-01 -1.900000e+00 4.900000e+00 5.755668e-01 5.755668e-01 2.877834e-01 -5.755668e-01 -1.800000e+00 4.900000e+00 5.798418e-01 5.798418e-01 2.899209e-01 -5.798418e-01 -1.700000e+00 4.900000e+00 5.839149e-01 5.839149e-01 2.919574e-01 -5.839149e-01 -1.600000e+00 4.900000e+00 5.877815e-01 5.877815e-01 2.938907e-01 -5.877815e-01 -1.500000e+00 4.900000e+00 5.914370e-01 5.914370e-01 2.957185e-01 -5.914370e-01 -1.400000e+00 4.900000e+00 5.948774e-01 5.948774e-01 2.974387e-01 -5.948774e-01 -1.300000e+00 4.900000e+00 5.980984e-01 5.980984e-01 2.990492e-01 -5.980984e-01 -1.200000e+00 4.900000e+00 6.010964e-01 6.010964e-01 3.005482e-01 -6.010964e-01 -1.100000e+00 4.900000e+00 6.038678e-01 6.038678e-01 3.019339e-01 -6.038678e-01 -1.000000e+00 4.900000e+00 6.064094e-01 6.064094e-01 3.032047e-01 -6.064094e-01 -9.000000e-01 4.900000e+00 6.087181e-01 6.087181e-01 3.043590e-01 -6.087181e-01 -8.000000e-01 4.900000e+00 6.107913e-01 6.107913e-01 3.053956e-01 -6.107913e-01 -7.000000e-01 4.900000e+00 6.126264e-01 6.126264e-01 3.063132e-01 -6.126264e-01 -6.000000e-01 4.900000e+00 6.142213e-01 6.142213e-01 3.071106e-01 -6.142213e-01 -5.000000e-01 4.900000e+00 6.155741e-01 6.155741e-01 3.077870e-01 -6.155741e-01 -4.000000e-01 4.900000e+00 6.166831e-01 6.166831e-01 3.083415e-01 -6.166831e-01 -3.000000e-01 4.900000e+00 6.175470e-01 6.175470e-01 3.087735e-01 -6.175470e-01 -2.000000e-01 4.900000e+00 6.181649e-01 6.181649e-01 3.090824e-01 -6.181649e-01 -1.000000e-01 4.900000e+00 6.185359e-01 6.185359e-01 3.092680e-01 -6.185359e-01 0.000000e+00 4.900000e+00 6.186596e-01 6.186596e-01 3.093298e-01 -6.186596e-01 1.000000e-01 4.900000e+00 6.185359e-01 6.185359e-01 3.092680e-01 -6.185359e-01 2.000000e-01 4.900000e+00 6.181649e-01 6.181649e-01 3.090824e-01 -6.181649e-01 3.000000e-01 4.900000e+00 6.175470e-01 6.175470e-01 3.087735e-01 -6.175470e-01 4.000000e-01 4.900000e+00 6.166831e-01 6.166831e-01 3.083415e-01 -6.166831e-01 5.000000e-01 4.900000e+00 6.155741e-01 6.155741e-01 3.077870e-01 -6.155741e-01 6.000000e-01 4.900000e+00 6.142213e-01 6.142213e-01 3.071106e-01 -6.142213e-01 7.000000e-01 4.900000e+00 6.126264e-01 6.126264e-01 3.063132e-01 -6.126264e-01 8.000000e-01 4.900000e+00 6.107913e-01 6.107913e-01 3.053956e-01 -6.107913e-01 9.000000e-01 4.900000e+00 6.087181e-01 6.087181e-01 3.043590e-01 -6.087181e-01 1.000000e+00 4.900000e+00 6.064094e-01 6.064094e-01 3.032047e-01 -6.064094e-01 1.100000e+00 4.900000e+00 6.038678e-01 6.038678e-01 3.019339e-01 -6.038678e-01 1.200000e+00 4.900000e+00 6.010964e-01 6.010964e-01 3.005482e-01 -6.010964e-01 1.300000e+00 4.900000e+00 5.980984e-01 5.980984e-01 2.990492e-01 -5.980984e-01 1.400000e+00 4.900000e+00 5.948774e-01 5.948774e-01 2.974387e-01 -5.948774e-01 1.500000e+00 4.900000e+00 5.914370e-01 5.914370e-01 2.957185e-01 -5.914370e-01 1.600000e+00 4.900000e+00 5.877815e-01 5.877815e-01 2.938907e-01 -5.877815e-01 1.700000e+00 4.900000e+00 5.839149e-01 5.839149e-01 2.919574e-01 -5.839149e-01 1.800000e+00 4.900000e+00 5.798418e-01 5.798418e-01 2.899209e-01 -5.798418e-01 1.900000e+00 4.900000e+00 5.755668e-01 5.755668e-01 2.877834e-01 -5.755668e-01 2.000000e+00 4.900000e+00 5.710948e-01 5.710948e-01 2.855474e-01 -5.710948e-01 2.100000e+00 4.900000e+00 5.664310e-01 5.664310e-01 2.832155e-01 -5.664310e-01 2.200000e+00 4.900000e+00 5.615806e-01 5.615806e-01 2.807903e-01 -5.615806e-01 2.300000e+00 4.900000e+00 5.565490e-01 5.565490e-01 2.782745e-01 -5.565490e-01 2.400000e+00 4.900000e+00 5.513420e-01 5.513420e-01 2.756710e-01 -5.513420e-01 2.500000e+00 4.900000e+00 5.459652e-01 5.459652e-01 2.729826e-01 -5.459652e-01 2.600000e+00 4.900000e+00 5.404246e-01 5.404246e-01 2.702123e-01 -5.404246e-01 2.700000e+00 4.900000e+00 5.347264e-01 5.347264e-01 2.673632e-01 -5.347264e-01 2.800000e+00 4.900000e+00 5.288767e-01 5.288767e-01 2.644383e-01 -5.288767e-01 2.900000e+00 4.900000e+00 5.228817e-01 5.228817e-01 2.614408e-01 -5.228817e-01 3.000000e+00 4.900000e+00 5.167480e-01 5.167480e-01 2.583740e-01 -5.167480e-01 3.100000e+00 4.900000e+00 5.104820e-01 5.104820e-01 2.552410e-01 -5.104820e-01 3.200000e+00 4.900000e+00 5.040902e-01 5.040902e-01 2.520451e-01 -5.040902e-01 3.300000e+00 4.900000e+00 4.975795e-01 4.975795e-01 2.487897e-01 -4.975795e-01 3.400000e+00 4.900000e+00 4.909564e-01 4.909564e-01 2.454782e-01 -4.909564e-01 3.500000e+00 4.900000e+00 4.842277e-01 4.842277e-01 2.421139e-01 -4.842277e-01 3.600000e+00 4.900000e+00 4.774002e-01 4.774002e-01 2.387001e-01 -4.774002e-01 3.700000e+00 4.900000e+00 4.704808e-01 4.704808e-01 2.352404e-01 -4.704808e-01 3.800000e+00 4.900000e+00 4.634763e-01 4.634763e-01 2.317382e-01 -4.634763e-01 3.900000e+00 4.900000e+00 4.563934e-01 4.563934e-01 2.281967e-01 -4.563934e-01 4.000000e+00 4.900000e+00 4.492391e-01 4.492391e-01 2.246195e-01 -4.492391e-01 4.100000e+00 4.900000e+00 4.420200e-01 4.420200e-01 2.210100e-01 -4.420200e-01 4.200000e+00 4.900000e+00 4.347431e-01 4.347431e-01 2.173716e-01 -4.347431e-01 4.300000e+00 4.900000e+00 4.274149e-01 4.274149e-01 2.137075e-01 -4.274149e-01 4.400000e+00 4.900000e+00 4.200422e-01 4.200422e-01 2.100211e-01 -4.200422e-01 4.500000e+00 4.900000e+00 4.126316e-01 4.126316e-01 2.063158e-01 -4.126316e-01 4.600000e+00 4.900000e+00 4.051897e-01 4.051897e-01 2.025948e-01 -4.051897e-01 4.700000e+00 4.900000e+00 3.977228e-01 3.977228e-01 1.988614e-01 -3.977228e-01 4.800000e+00 4.900000e+00 3.902374e-01 3.902374e-01 1.951187e-01 -3.902374e-01 4.900000e+00 4.900000e+00 3.827398e-01 3.827398e-01 1.913699e-01 -3.827398e-01 Sigima-1.1.1/sigima/data/tests/image_formats/coordinated_text/complex_ref_image.txt000066400000000000000000015617161514013333200306450ustar00rootroot00000000000000# Created on 2015-09-22 10:00:04.554000 # By Username # nx : 100 # ny : 100 # X : xlabel (xunit) # Y : ylabel (yunit) # Zre : Real(zlabel) (zunit) # Zim : Imaginary(zlabel) (zunit) # Zre Error (zunit) # Zim Error (zunit) -5 -5 0.367879 0.367879 0.18394 -0.367879 -4.9 -5 0.375236 0.375236 0.187618 -0.375236 -4.8 -5 0.382587 0.382587 0.191293 -0.382587 -4.7 -5 0.389925 0.389925 0.194963 -0.389925 -4.6 -5 0.397246 0.397246 0.198623 -0.397246 -4.5 -5 0.404542 0.404542 0.202271 -0.404542 -4.4 -5 0.411807 0.411807 0.205904 -0.411807 -4.3 -5 0.419035 0.419035 0.209518 -0.419035 -4.2 -5 0.42622 0.42622 0.21311 -0.42622 -4.1 -5 0.433354 0.433354 0.216677 -0.433354 -4 -5 0.440432 0.440432 0.220216 -0.440432 -3.9 -5 0.447446 0.447446 0.223723 -0.447446 -3.8 -5 0.45439 0.45439 0.227195 -0.45439 -3.7 -5 0.461257 0.461257 0.230628 -0.461257 -3.6 -5 0.468041 0.468041 0.23402 -0.468041 -3.5 -5 0.474734 0.474734 0.237367 -0.474734 -3.4 -5 0.481331 0.481331 0.240666 -0.481331 -3.3 -5 0.487824 0.487824 0.243912 -0.487824 -3.2 -5 0.494207 0.494207 0.247104 -0.494207 -3.1 -5 0.500474 0.500474 0.250237 -0.500474 -3 -5 0.506617 0.506617 0.253308 -0.506617 -2.9 -5 0.51263 0.51263 0.256315 -0.51263 -2.8 -5 0.518508 0.518508 0.259254 -0.518508 -2.7 -5 0.524243 0.524243 0.262121 -0.524243 -2.6 -5 0.52983 0.52983 0.264915 -0.52983 -2.5 -5 0.535261 0.535261 0.267631 -0.535261 -2.4 -5 0.540533 0.540533 0.270266 -0.540533 -2.3 -5 0.545638 0.545638 0.272819 -0.545638 -2.2 -5 0.550571 0.550571 0.275285 -0.550571 -2.1 -5 0.555326 0.555326 0.277663 -0.555326 -2 -5 0.559898 0.559898 0.279949 -0.559898 -1.9 -5 0.564283 0.564283 0.282141 -0.564283 -1.8 -5 0.568474 0.568474 0.284237 -0.568474 -1.7 -5 0.572467 0.572467 0.286234 -0.572467 -1.6 -5 0.576258 0.576258 0.288129 -0.576258 -1.5 -5 0.579842 0.579842 0.289921 -0.579842 -1.4 -5 0.583215 0.583215 0.291607 -0.583215 -1.3 -5 0.586373 0.586373 0.293186 -0.586373 -1.2 -5 0.589312 0.589312 0.294656 -0.589312 -1.1 -5 0.592029 0.592029 0.296014 -0.592029 -1 -5 0.594521 0.594521 0.29726 -0.594521 -0.9 -5 0.596784 0.596784 0.298392 -0.596784 -0.8 -5 0.598817 0.598817 0.299408 -0.598817 -0.7 -5 0.600616 0.600616 0.300308 -0.600616 -0.6 -5 0.602179 0.602179 0.30109 -0.602179 -0.5 -5 0.603506 0.603506 0.301753 -0.603506 -0.4 -5 0.604593 0.604593 0.302296 -0.604593 -0.3 -5 0.60544 0.60544 0.30272 -0.60544 -0.2 -5 0.606046 0.606046 0.303023 -0.606046 -0.1 -5 0.606409 0.606409 0.303205 -0.606409 0 -5 0.606531 0.606531 0.303265 -0.606531 0.1 -5 0.606409 0.606409 0.303205 -0.606409 0.2 -5 0.606046 0.606046 0.303023 -0.606046 0.3 -5 0.60544 0.60544 0.30272 -0.60544 0.4 -5 0.604593 0.604593 0.302296 -0.604593 0.5 -5 0.603506 0.603506 0.301753 -0.603506 0.6 -5 0.602179 0.602179 0.30109 -0.602179 0.7 -5 0.600616 0.600616 0.300308 -0.600616 0.8 -5 0.598817 0.598817 0.299408 -0.598817 0.9 -5 0.596784 0.596784 0.298392 -0.596784 1 -5 0.594521 0.594521 0.29726 -0.594521 1.1 -5 0.592029 0.592029 0.296014 -0.592029 1.2 -5 0.589312 0.589312 0.294656 -0.589312 1.3 -5 0.586373 0.586373 0.293186 -0.586373 1.4 -5 0.583215 0.583215 0.291607 -0.583215 1.5 -5 0.579842 0.579842 0.289921 -0.579842 1.6 -5 0.576258 0.576258 0.288129 -0.576258 1.7 -5 0.572467 0.572467 0.286234 -0.572467 1.8 -5 0.568474 0.568474 0.284237 -0.568474 1.9 -5 0.564283 0.564283 0.282141 -0.564283 2 -5 0.559898 0.559898 0.279949 -0.559898 2.1 -5 0.555326 0.555326 0.277663 -0.555326 2.2 -5 0.550571 0.550571 0.275285 -0.550571 2.3 -5 0.545638 0.545638 0.272819 -0.545638 2.4 -5 0.540533 0.540533 0.270266 -0.540533 2.5 -5 0.535261 0.535261 0.267631 -0.535261 2.6 -5 0.52983 0.52983 0.264915 -0.52983 2.7 -5 0.524243 0.524243 0.262121 -0.524243 2.8 -5 0.518508 0.518508 0.259254 -0.518508 2.9 -5 0.51263 0.51263 0.256315 -0.51263 3 -5 0.506617 0.506617 0.253308 -0.506617 3.1 -5 0.500474 0.500474 0.250237 -0.500474 3.2 -5 0.494207 0.494207 0.247104 -0.494207 3.3 -5 0.487824 0.487824 0.243912 -0.487824 3.4 -5 0.481331 0.481331 0.240666 -0.481331 3.5 -5 0.474734 0.474734 0.237367 -0.474734 3.6 -5 0.468041 0.468041 0.23402 -0.468041 3.7 -5 0.461257 0.461257 0.230628 -0.461257 3.8 -5 0.45439 0.45439 0.227195 -0.45439 3.9 -5 0.447446 0.447446 0.223723 -0.447446 4 -5 0.440432 0.440432 0.220216 -0.440432 4.1 -5 0.433354 0.433354 0.216677 -0.433354 4.2 -5 0.42622 0.42622 0.21311 -0.42622 4.3 -5 0.419035 0.419035 0.209518 -0.419035 4.4 -5 0.411807 0.411807 0.205904 -0.411807 4.5 -5 0.404542 0.404542 0.202271 -0.404542 4.6 -5 0.397246 0.397246 0.198623 -0.397246 4.7 -5 0.389925 0.389925 0.194963 -0.389925 4.8 -5 0.382587 0.382587 0.191293 -0.382587 4.9 -5 0.375236 0.375236 0.187618 -0.375236 -5 -4.9 0.375236 0.375236 0.187618 -0.375236 -4.9 -4.9 0.38274 0.38274 0.19137 -0.38274 -4.8 -4.9 0.390237 0.390237 0.195119 -0.390237 -4.7 -4.9 0.397723 0.397723 0.198861 -0.397723 -4.6 -4.9 0.40519 0.40519 0.202595 -0.40519 -4.5 -4.9 0.412632 0.412632 0.206316 -0.412632 -4.4 -4.9 0.420042 0.420042 0.210021 -0.420042 -4.3 -4.9 0.427415 0.427415 0.213707 -0.427415 -4.2 -4.9 0.434743 0.434743 0.217372 -0.434743 -4.1 -4.9 0.44202 0.44202 0.22101 -0.44202 -4 -4.9 0.449239 0.449239 0.22462 -0.449239 -3.9 -4.9 0.456393 0.456393 0.228197 -0.456393 -3.8 -4.9 0.463476 0.463476 0.231738 -0.463476 -3.7 -4.9 0.470481 0.470481 0.23524 -0.470481 -3.6 -4.9 0.4774 0.4774 0.2387 -0.4774 -3.5 -4.9 0.484228 0.484228 0.242114 -0.484228 -3.4 -4.9 0.490956 0.490956 0.245478 -0.490956 -3.3 -4.9 0.497579 0.497579 0.24879 -0.497579 -3.2 -4.9 0.50409 0.50409 0.252045 -0.50409 -3.1 -4.9 0.510482 0.510482 0.255241 -0.510482 -3 -4.9 0.516748 0.516748 0.258374 -0.516748 -2.9 -4.9 0.522882 0.522882 0.261441 -0.522882 -2.8 -4.9 0.528877 0.528877 0.264438 -0.528877 -2.7 -4.9 0.534726 0.534726 0.267363 -0.534726 -2.6 -4.9 0.540425 0.540425 0.270212 -0.540425 -2.5 -4.9 0.545965 0.545965 0.272983 -0.545965 -2.4 -4.9 0.551342 0.551342 0.275671 -0.551342 -2.3 -4.9 0.556549 0.556549 0.278275 -0.556549 -2.2 -4.9 0.561581 0.561581 0.28079 -0.561581 -2.1 -4.9 0.566431 0.566431 0.283216 -0.566431 -2 -4.9 0.571095 0.571095 0.285547 -0.571095 -1.9 -4.9 0.575567 0.575567 0.287783 -0.575567 -1.8 -4.9 0.579842 0.579842 0.289921 -0.579842 -1.7 -4.9 0.583915 0.583915 0.291957 -0.583915 -1.6 -4.9 0.587781 0.587781 0.293891 -0.587781 -1.5 -4.9 0.591437 0.591437 0.295719 -0.591437 -1.4 -4.9 0.594877 0.594877 0.297439 -0.594877 -1.3 -4.9 0.598098 0.598098 0.299049 -0.598098 -1.2 -4.9 0.601096 0.601096 0.300548 -0.601096 -1.1 -4.9 0.603868 0.603868 0.301934 -0.603868 -1 -4.9 0.606409 0.606409 0.303205 -0.606409 -0.9 -4.9 0.608718 0.608718 0.304359 -0.608718 -0.8 -4.9 0.610791 0.610791 0.305396 -0.610791 -0.7 -4.9 0.612626 0.612626 0.306313 -0.612626 -0.6 -4.9 0.614221 0.614221 0.307111 -0.614221 -0.5 -4.9 0.615574 0.615574 0.307787 -0.615574 -0.4 -4.9 0.616683 0.616683 0.308342 -0.616683 -0.3 -4.9 0.617547 0.617547 0.308774 -0.617547 -0.2 -4.9 0.618165 0.618165 0.309082 -0.618165 -0.1 -4.9 0.618536 0.618536 0.309268 -0.618536 0 -4.9 0.61866 0.61866 0.30933 -0.61866 0.1 -4.9 0.618536 0.618536 0.309268 -0.618536 0.2 -4.9 0.618165 0.618165 0.309082 -0.618165 0.3 -4.9 0.617547 0.617547 0.308774 -0.617547 0.4 -4.9 0.616683 0.616683 0.308342 -0.616683 0.5 -4.9 0.615574 0.615574 0.307787 -0.615574 0.6 -4.9 0.614221 0.614221 0.307111 -0.614221 0.7 -4.9 0.612626 0.612626 0.306313 -0.612626 0.8 -4.9 0.610791 0.610791 0.305396 -0.610791 0.9 -4.9 0.608718 0.608718 0.304359 -0.608718 1 -4.9 0.606409 0.606409 0.303205 -0.606409 1.1 -4.9 0.603868 0.603868 0.301934 -0.603868 1.2 -4.9 0.601096 0.601096 0.300548 -0.601096 1.3 -4.9 0.598098 0.598098 0.299049 -0.598098 1.4 -4.9 0.594877 0.594877 0.297439 -0.594877 1.5 -4.9 0.591437 0.591437 0.295719 -0.591437 1.6 -4.9 0.587781 0.587781 0.293891 -0.587781 1.7 -4.9 0.583915 0.583915 0.291957 -0.583915 1.8 -4.9 0.579842 0.579842 0.289921 -0.579842 1.9 -4.9 0.575567 0.575567 0.287783 -0.575567 2 -4.9 0.571095 0.571095 0.285547 -0.571095 2.1 -4.9 0.566431 0.566431 0.283216 -0.566431 2.2 -4.9 0.561581 0.561581 0.28079 -0.561581 2.3 -4.9 0.556549 0.556549 0.278275 -0.556549 2.4 -4.9 0.551342 0.551342 0.275671 -0.551342 2.5 -4.9 0.545965 0.545965 0.272983 -0.545965 2.6 -4.9 0.540425 0.540425 0.270212 -0.540425 2.7 -4.9 0.534726 0.534726 0.267363 -0.534726 2.8 -4.9 0.528877 0.528877 0.264438 -0.528877 2.9 -4.9 0.522882 0.522882 0.261441 -0.522882 3 -4.9 0.516748 0.516748 0.258374 -0.516748 3.1 -4.9 0.510482 0.510482 0.255241 -0.510482 3.2 -4.9 0.50409 0.50409 0.252045 -0.50409 3.3 -4.9 0.497579 0.497579 0.24879 -0.497579 3.4 -4.9 0.490956 0.490956 0.245478 -0.490956 3.5 -4.9 0.484228 0.484228 0.242114 -0.484228 3.6 -4.9 0.4774 0.4774 0.2387 -0.4774 3.7 -4.9 0.470481 0.470481 0.23524 -0.470481 3.8 -4.9 0.463476 0.463476 0.231738 -0.463476 3.9 -4.9 0.456393 0.456393 0.228197 -0.456393 4 -4.9 0.449239 0.449239 0.22462 -0.449239 4.1 -4.9 0.44202 0.44202 0.22101 -0.44202 4.2 -4.9 0.434743 0.434743 0.217372 -0.434743 4.3 -4.9 0.427415 0.427415 0.213707 -0.427415 4.4 -4.9 0.420042 0.420042 0.210021 -0.420042 4.5 -4.9 0.412632 0.412632 0.206316 -0.412632 4.6 -4.9 0.40519 0.40519 0.202595 -0.40519 4.7 -4.9 0.397723 0.397723 0.198861 -0.397723 4.8 -4.9 0.390237 0.390237 0.195119 -0.390237 4.9 -4.9 0.38274 0.38274 0.19137 -0.38274 -5 -4.8 0.382587 0.382587 0.191293 -0.382587 -4.9 -4.8 0.390237 0.390237 0.195119 -0.390237 -4.8 -4.8 0.397882 0.397882 0.198941 -0.397882 -4.7 -4.8 0.405514 0.405514 0.202757 -0.405514 -4.6 -4.8 0.413127 0.413127 0.206564 -0.413127 -4.5 -4.8 0.420715 0.420715 0.210357 -0.420715 -4.4 -4.8 0.428271 0.428271 0.214135 -0.428271 -4.3 -4.8 0.435788 0.435788 0.217894 -0.435788 -4.2 -4.8 0.443259 0.443259 0.22163 -0.443259 -4.1 -4.8 0.450679 0.450679 0.225339 -0.450679 -4 -4.8 0.458039 0.458039 0.22902 -0.458039 -3.9 -4.8 0.465334 0.465334 0.232667 -0.465334 -3.8 -4.8 0.472556 0.472556 0.236278 -0.472556 -3.7 -4.8 0.479697 0.479697 0.239849 -0.479697 -3.6 -4.8 0.486752 0.486752 0.243376 -0.486752 -3.5 -4.8 0.493713 0.493713 0.246857 -0.493713 -3.4 -4.8 0.500574 0.500574 0.250287 -0.500574 -3.3 -4.8 0.507327 0.507327 0.253663 -0.507327 -3.2 -4.8 0.513965 0.513965 0.256983 -0.513965 -3.1 -4.8 0.520482 0.520482 0.260241 -0.520482 -3 -4.8 0.526871 0.526871 0.263435 -0.526871 -2.9 -4.8 0.533125 0.533125 0.266562 -0.533125 -2.8 -4.8 0.539237 0.539237 0.269619 -0.539237 -2.7 -4.8 0.545201 0.545201 0.272601 -0.545201 -2.6 -4.8 0.551011 0.551011 0.275506 -0.551011 -2.5 -4.8 0.55666 0.55666 0.27833 -0.55666 -2.4 -4.8 0.562142 0.562142 0.281071 -0.562142 -2.3 -4.8 0.567451 0.567451 0.283726 -0.567451 -2.2 -4.8 0.572582 0.572582 0.286291 -0.572582 -2.1 -4.8 0.577527 0.577527 0.288764 -0.577527 -2 -4.8 0.582282 0.582282 0.291141 -0.582282 -1.9 -4.8 0.586842 0.586842 0.293421 -0.586842 -1.8 -4.8 0.591201 0.591201 0.2956 -0.591201 -1.7 -4.8 0.595353 0.595353 0.297677 -0.595353 -1.6 -4.8 0.599296 0.599296 0.299648 -0.599296 -1.5 -4.8 0.603023 0.603023 0.301511 -0.603023 -1.4 -4.8 0.606531 0.606531 0.303265 -0.606531 -1.3 -4.8 0.609815 0.609815 0.304907 -0.609815 -1.2 -4.8 0.612871 0.612871 0.306436 -0.612871 -1.1 -4.8 0.615697 0.615697 0.307849 -0.615697 -1 -4.8 0.618289 0.618289 0.309144 -0.618289 -0.9 -4.8 0.620643 0.620643 0.310321 -0.620643 -0.8 -4.8 0.622756 0.622756 0.311378 -0.622756 -0.7 -4.8 0.624627 0.624627 0.312314 -0.624627 -0.6 -4.8 0.626254 0.626254 0.313127 -0.626254 -0.5 -4.8 0.627633 0.627633 0.313816 -0.627633 -0.4 -4.8 0.628764 0.628764 0.314382 -0.628764 -0.3 -4.8 0.629644 0.629644 0.314822 -0.629644 -0.2 -4.8 0.630274 0.630274 0.315137 -0.630274 -0.1 -4.8 0.630653 0.630653 0.315326 -0.630653 0 -4.8 0.630779 0.630779 0.315389 -0.630779 0.1 -4.8 0.630653 0.630653 0.315326 -0.630653 0.2 -4.8 0.630274 0.630274 0.315137 -0.630274 0.3 -4.8 0.629644 0.629644 0.314822 -0.629644 0.4 -4.8 0.628764 0.628764 0.314382 -0.628764 0.5 -4.8 0.627633 0.627633 0.313816 -0.627633 0.6 -4.8 0.626254 0.626254 0.313127 -0.626254 0.7 -4.8 0.624627 0.624627 0.312314 -0.624627 0.8 -4.8 0.622756 0.622756 0.311378 -0.622756 0.9 -4.8 0.620643 0.620643 0.310321 -0.620643 1 -4.8 0.618289 0.618289 0.309144 -0.618289 1.1 -4.8 0.615697 0.615697 0.307849 -0.615697 1.2 -4.8 0.612871 0.612871 0.306436 -0.612871 1.3 -4.8 0.609815 0.609815 0.304907 -0.609815 1.4 -4.8 0.606531 0.606531 0.303265 -0.606531 1.5 -4.8 0.603023 0.603023 0.301511 -0.603023 1.6 -4.8 0.599296 0.599296 0.299648 -0.599296 1.7 -4.8 0.595353 0.595353 0.297677 -0.595353 1.8 -4.8 0.591201 0.591201 0.2956 -0.591201 1.9 -4.8 0.586842 0.586842 0.293421 -0.586842 2 -4.8 0.582282 0.582282 0.291141 -0.582282 2.1 -4.8 0.577527 0.577527 0.288764 -0.577527 2.2 -4.8 0.572582 0.572582 0.286291 -0.572582 2.3 -4.8 0.567451 0.567451 0.283726 -0.567451 2.4 -4.8 0.562142 0.562142 0.281071 -0.562142 2.5 -4.8 0.55666 0.55666 0.27833 -0.55666 2.6 -4.8 0.551011 0.551011 0.275506 -0.551011 2.7 -4.8 0.545201 0.545201 0.272601 -0.545201 2.8 -4.8 0.539237 0.539237 0.269619 -0.539237 2.9 -4.8 0.533125 0.533125 0.266562 -0.533125 3 -4.8 0.526871 0.526871 0.263435 -0.526871 3.1 -4.8 0.520482 0.520482 0.260241 -0.520482 3.2 -4.8 0.513965 0.513965 0.256983 -0.513965 3.3 -4.8 0.507327 0.507327 0.253663 -0.507327 3.4 -4.8 0.500574 0.500574 0.250287 -0.500574 3.5 -4.8 0.493713 0.493713 0.246857 -0.493713 3.6 -4.8 0.486752 0.486752 0.243376 -0.486752 3.7 -4.8 0.479697 0.479697 0.239849 -0.479697 3.8 -4.8 0.472556 0.472556 0.236278 -0.472556 3.9 -4.8 0.465334 0.465334 0.232667 -0.465334 4 -4.8 0.458039 0.458039 0.22902 -0.458039 4.1 -4.8 0.450679 0.450679 0.225339 -0.450679 4.2 -4.8 0.443259 0.443259 0.22163 -0.443259 4.3 -4.8 0.435788 0.435788 0.217894 -0.435788 4.4 -4.8 0.428271 0.428271 0.214135 -0.428271 4.5 -4.8 0.420715 0.420715 0.210357 -0.420715 4.6 -4.8 0.413127 0.413127 0.206564 -0.413127 4.7 -4.8 0.405514 0.405514 0.202757 -0.405514 4.8 -4.8 0.397882 0.397882 0.198941 -0.397882 4.9 -4.8 0.390237 0.390237 0.195119 -0.390237 -5 -4.7 0.389925 0.389925 0.194963 -0.389925 -4.9 -4.7 0.397723 0.397723 0.198861 -0.397723 -4.8 -4.7 0.405514 0.405514 0.202757 -0.405514 -4.7 -4.7 0.413292 0.413292 0.206646 -0.413292 -4.6 -4.7 0.421052 0.421052 0.210526 -0.421052 -4.5 -4.7 0.428785 0.428785 0.214392 -0.428785 -4.4 -4.7 0.436486 0.436486 0.218243 -0.436486 -4.3 -4.7 0.444147 0.444147 0.222073 -0.444147 -4.2 -4.7 0.451762 0.451762 0.225881 -0.451762 -4.1 -4.7 0.459324 0.459324 0.229662 -0.459324 -4 -4.7 0.466825 0.466825 0.233413 -0.466825 -3.9 -4.7 0.47426 0.47426 0.23713 -0.47426 -3.8 -4.7 0.48162 0.48162 0.24081 -0.48162 -3.7 -4.7 0.488899 0.488899 0.244449 -0.488899 -3.6 -4.7 0.496089 0.496089 0.248044 -0.496089 -3.5 -4.7 0.503184 0.503184 0.251592 -0.503184 -3.4 -4.7 0.510176 0.510176 0.255088 -0.510176 -3.3 -4.7 0.517058 0.517058 0.258529 -0.517058 -3.2 -4.7 0.523824 0.523824 0.261912 -0.523824 -3.1 -4.7 0.530466 0.530466 0.265233 -0.530466 -3 -4.7 0.536977 0.536977 0.268489 -0.536977 -2.9 -4.7 0.543351 0.543351 0.271675 -0.543351 -2.8 -4.7 0.549581 0.549581 0.27479 -0.549581 -2.7 -4.7 0.555659 0.555659 0.27783 -0.555659 -2.6 -4.7 0.561581 0.561581 0.28079 -0.561581 -2.5 -4.7 0.567338 0.567338 0.283669 -0.567338 -2.4 -4.7 0.572925 0.572925 0.286463 -0.572925 -2.3 -4.7 0.578336 0.578336 0.289168 -0.578336 -2.2 -4.7 0.583565 0.583565 0.291782 -0.583565 -2.1 -4.7 0.588605 0.588605 0.294302 -0.588605 -2 -4.7 0.593451 0.593451 0.296726 -0.593451 -1.9 -4.7 0.598098 0.598098 0.299049 -0.598098 -1.8 -4.7 0.602541 0.602541 0.30127 -0.602541 -1.7 -4.7 0.606773 0.606773 0.303387 -0.606773 -1.6 -4.7 0.610791 0.610791 0.305396 -0.610791 -1.5 -4.7 0.61459 0.61459 0.307295 -0.61459 -1.4 -4.7 0.618165 0.618165 0.309082 -0.618165 -1.3 -4.7 0.621512 0.621512 0.310756 -0.621512 -1.2 -4.7 0.624627 0.624627 0.312314 -0.624627 -1.1 -4.7 0.627507 0.627507 0.313754 -0.627507 -1 -4.7 0.630148 0.630148 0.315074 -0.630148 -0.9 -4.7 0.632547 0.632547 0.316274 -0.632547 -0.8 -4.7 0.634702 0.634702 0.317351 -0.634702 -0.7 -4.7 0.636609 0.636609 0.318304 -0.636609 -0.6 -4.7 0.638266 0.638266 0.319133 -0.638266 -0.5 -4.7 0.639672 0.639672 0.319836 -0.639672 -0.4 -4.7 0.640824 0.640824 0.320412 -0.640824 -0.3 -4.7 0.641722 0.641722 0.320861 -0.641722 -0.2 -4.7 0.642364 0.642364 0.321182 -0.642364 -0.1 -4.7 0.64275 0.64275 0.321375 -0.64275 0 -4.7 0.642878 0.642878 0.321439 -0.642878 0.1 -4.7 0.64275 0.64275 0.321375 -0.64275 0.2 -4.7 0.642364 0.642364 0.321182 -0.642364 0.3 -4.7 0.641722 0.641722 0.320861 -0.641722 0.4 -4.7 0.640824 0.640824 0.320412 -0.640824 0.5 -4.7 0.639672 0.639672 0.319836 -0.639672 0.6 -4.7 0.638266 0.638266 0.319133 -0.638266 0.7 -4.7 0.636609 0.636609 0.318304 -0.636609 0.8 -4.7 0.634702 0.634702 0.317351 -0.634702 0.9 -4.7 0.632547 0.632547 0.316274 -0.632547 1 -4.7 0.630148 0.630148 0.315074 -0.630148 1.1 -4.7 0.627507 0.627507 0.313754 -0.627507 1.2 -4.7 0.624627 0.624627 0.312314 -0.624627 1.3 -4.7 0.621512 0.621512 0.310756 -0.621512 1.4 -4.7 0.618165 0.618165 0.309082 -0.618165 1.5 -4.7 0.61459 0.61459 0.307295 -0.61459 1.6 -4.7 0.610791 0.610791 0.305396 -0.610791 1.7 -4.7 0.606773 0.606773 0.303387 -0.606773 1.8 -4.7 0.602541 0.602541 0.30127 -0.602541 1.9 -4.7 0.598098 0.598098 0.299049 -0.598098 2 -4.7 0.593451 0.593451 0.296726 -0.593451 2.1 -4.7 0.588605 0.588605 0.294302 -0.588605 2.2 -4.7 0.583565 0.583565 0.291782 -0.583565 2.3 -4.7 0.578336 0.578336 0.289168 -0.578336 2.4 -4.7 0.572925 0.572925 0.286463 -0.572925 2.5 -4.7 0.567338 0.567338 0.283669 -0.567338 2.6 -4.7 0.561581 0.561581 0.28079 -0.561581 2.7 -4.7 0.555659 0.555659 0.27783 -0.555659 2.8 -4.7 0.549581 0.549581 0.27479 -0.549581 2.9 -4.7 0.543351 0.543351 0.271675 -0.543351 3 -4.7 0.536977 0.536977 0.268489 -0.536977 3.1 -4.7 0.530466 0.530466 0.265233 -0.530466 3.2 -4.7 0.523824 0.523824 0.261912 -0.523824 3.3 -4.7 0.517058 0.517058 0.258529 -0.517058 3.4 -4.7 0.510176 0.510176 0.255088 -0.510176 3.5 -4.7 0.503184 0.503184 0.251592 -0.503184 3.6 -4.7 0.496089 0.496089 0.248044 -0.496089 3.7 -4.7 0.488899 0.488899 0.244449 -0.488899 3.8 -4.7 0.48162 0.48162 0.24081 -0.48162 3.9 -4.7 0.47426 0.47426 0.23713 -0.47426 4 -4.7 0.466825 0.466825 0.233413 -0.466825 4.1 -4.7 0.459324 0.459324 0.229662 -0.459324 4.2 -4.7 0.451762 0.451762 0.225881 -0.451762 4.3 -4.7 0.444147 0.444147 0.222073 -0.444147 4.4 -4.7 0.436486 0.436486 0.218243 -0.436486 4.5 -4.7 0.428785 0.428785 0.214392 -0.428785 4.6 -4.7 0.421052 0.421052 0.210526 -0.421052 4.7 -4.7 0.413292 0.413292 0.206646 -0.413292 4.8 -4.7 0.405514 0.405514 0.202757 -0.405514 4.9 -4.7 0.397723 0.397723 0.198861 -0.397723 -5 -4.6 0.397246 0.397246 0.198623 -0.397246 -4.9 -4.6 0.40519 0.40519 0.202595 -0.40519 -4.8 -4.6 0.413127 0.413127 0.206564 -0.413127 -4.7 -4.6 0.421052 0.421052 0.210526 -0.421052 -4.6 -4.6 0.428956 0.428956 0.214478 -0.428956 -4.5 -4.6 0.436835 0.436835 0.218417 -0.436835 -4.4 -4.6 0.44468 0.44468 0.22234 -0.44468 -4.3 -4.6 0.452485 0.452485 0.226243 -0.452485 -4.2 -4.6 0.460243 0.460243 0.230122 -0.460243 -4.1 -4.6 0.467947 0.467947 0.233974 -0.467947 -4 -4.6 0.47559 0.47559 0.237795 -0.47559 -3.9 -4.6 0.483164 0.483164 0.241582 -0.483164 -3.8 -4.6 0.490662 0.490662 0.245331 -0.490662 -3.7 -4.6 0.498077 0.498077 0.249039 -0.498077 -3.6 -4.6 0.505403 0.505403 0.252701 -0.505403 -3.5 -4.6 0.51263 0.51263 0.256315 -0.51263 -3.4 -4.6 0.519754 0.519754 0.259877 -0.519754 -3.3 -4.6 0.526765 0.526765 0.263383 -0.526765 -3.2 -4.6 0.533658 0.533658 0.266829 -0.533658 -3.1 -4.6 0.540425 0.540425 0.270212 -0.540425 -3 -4.6 0.547058 0.547058 0.273529 -0.547058 -2.9 -4.6 0.553552 0.553552 0.276776 -0.553552 -2.8 -4.6 0.559898 0.559898 0.279949 -0.559898 -2.7 -4.6 0.566091 0.566091 0.283046 -0.566091 -2.6 -4.6 0.572124 0.572124 0.286062 -0.572124 -2.5 -4.6 0.577989 0.577989 0.288995 -0.577989 -2.4 -4.6 0.583681 0.583681 0.291841 -0.583681 -2.3 -4.6 0.589194 0.589194 0.294597 -0.589194 -2.2 -4.6 0.594521 0.594521 0.29726 -0.594521 -2.1 -4.6 0.599655 0.599655 0.299828 -0.599655 -2 -4.6 0.604593 0.604593 0.302296 -0.604593 -1.9 -4.6 0.609327 0.609327 0.304664 -0.609327 -1.8 -4.6 0.613853 0.613853 0.306926 -0.613853 -1.7 -4.6 0.618165 0.618165 0.309082 -0.618165 -1.6 -4.6 0.622258 0.622258 0.311129 -0.622258 -1.5 -4.6 0.626128 0.626128 0.313064 -0.626128 -1.4 -4.6 0.62977 0.62977 0.314885 -0.62977 -1.3 -4.6 0.63318 0.63318 0.31659 -0.63318 -1.2 -4.6 0.636354 0.636354 0.318177 -0.636354 -1.1 -4.6 0.639288 0.639288 0.319644 -0.639288 -1 -4.6 0.641979 0.641979 0.320989 -0.641979 -0.9 -4.6 0.644423 0.644423 0.322211 -0.644423 -0.8 -4.6 0.646618 0.646618 0.323309 -0.646618 -0.7 -4.6 0.64856 0.64856 0.32428 -0.64856 -0.6 -4.6 0.650249 0.650249 0.325124 -0.650249 -0.5 -4.6 0.651681 0.651681 0.325841 -0.651681 -0.4 -4.6 0.652855 0.652855 0.326428 -0.652855 -0.3 -4.6 0.65377 0.65377 0.326885 -0.65377 -0.2 -4.6 0.654424 0.654424 0.327212 -0.654424 -0.1 -4.6 0.654817 0.654817 0.327408 -0.654817 0 -4.6 0.654948 0.654948 0.327474 -0.654948 0.1 -4.6 0.654817 0.654817 0.327408 -0.654817 0.2 -4.6 0.654424 0.654424 0.327212 -0.654424 0.3 -4.6 0.65377 0.65377 0.326885 -0.65377 0.4 -4.6 0.652855 0.652855 0.326428 -0.652855 0.5 -4.6 0.651681 0.651681 0.325841 -0.651681 0.6 -4.6 0.650249 0.650249 0.325124 -0.650249 0.7 -4.6 0.64856 0.64856 0.32428 -0.64856 0.8 -4.6 0.646618 0.646618 0.323309 -0.646618 0.9 -4.6 0.644423 0.644423 0.322211 -0.644423 1 -4.6 0.641979 0.641979 0.320989 -0.641979 1.1 -4.6 0.639288 0.639288 0.319644 -0.639288 1.2 -4.6 0.636354 0.636354 0.318177 -0.636354 1.3 -4.6 0.63318 0.63318 0.31659 -0.63318 1.4 -4.6 0.62977 0.62977 0.314885 -0.62977 1.5 -4.6 0.626128 0.626128 0.313064 -0.626128 1.6 -4.6 0.622258 0.622258 0.311129 -0.622258 1.7 -4.6 0.618165 0.618165 0.309082 -0.618165 1.8 -4.6 0.613853 0.613853 0.306926 -0.613853 1.9 -4.6 0.609327 0.609327 0.304664 -0.609327 2 -4.6 0.604593 0.604593 0.302296 -0.604593 2.1 -4.6 0.599655 0.599655 0.299828 -0.599655 2.2 -4.6 0.594521 0.594521 0.29726 -0.594521 2.3 -4.6 0.589194 0.589194 0.294597 -0.589194 2.4 -4.6 0.583681 0.583681 0.291841 -0.583681 2.5 -4.6 0.577989 0.577989 0.288995 -0.577989 2.6 -4.6 0.572124 0.572124 0.286062 -0.572124 2.7 -4.6 0.566091 0.566091 0.283046 -0.566091 2.8 -4.6 0.559898 0.559898 0.279949 -0.559898 2.9 -4.6 0.553552 0.553552 0.276776 -0.553552 3 -4.6 0.547058 0.547058 0.273529 -0.547058 3.1 -4.6 0.540425 0.540425 0.270212 -0.540425 3.2 -4.6 0.533658 0.533658 0.266829 -0.533658 3.3 -4.6 0.526765 0.526765 0.263383 -0.526765 3.4 -4.6 0.519754 0.519754 0.259877 -0.519754 3.5 -4.6 0.51263 0.51263 0.256315 -0.51263 3.6 -4.6 0.505403 0.505403 0.252701 -0.505403 3.7 -4.6 0.498077 0.498077 0.249039 -0.498077 3.8 -4.6 0.490662 0.490662 0.245331 -0.490662 3.9 -4.6 0.483164 0.483164 0.241582 -0.483164 4 -4.6 0.47559 0.47559 0.237795 -0.47559 4.1 -4.6 0.467947 0.467947 0.233974 -0.467947 4.2 -4.6 0.460243 0.460243 0.230122 -0.460243 4.3 -4.6 0.452485 0.452485 0.226243 -0.452485 4.4 -4.6 0.44468 0.44468 0.22234 -0.44468 4.5 -4.6 0.436835 0.436835 0.218417 -0.436835 4.6 -4.6 0.428956 0.428956 0.214478 -0.428956 4.7 -4.6 0.421052 0.421052 0.210526 -0.421052 4.8 -4.6 0.413127 0.413127 0.206564 -0.413127 4.9 -4.6 0.40519 0.40519 0.202595 -0.40519 -5 -4.5 0.404542 0.404542 0.202271 -0.404542 -4.9 -4.5 0.412632 0.412632 0.206316 -0.412632 -4.8 -4.5 0.420715 0.420715 0.210357 -0.420715 -4.7 -4.5 0.428785 0.428785 0.214392 -0.428785 -4.6 -4.5 0.436835 0.436835 0.218417 -0.436835 -4.5 -4.5 0.444858 0.444858 0.222429 -0.444858 -4.4 -4.5 0.452847 0.452847 0.226424 -0.452847 -4.3 -4.5 0.460796 0.460796 0.230398 -0.460796 -4.2 -4.5 0.468696 0.468696 0.234348 -0.468696 -4.1 -4.5 0.476542 0.476542 0.238271 -0.476542 -4 -4.5 0.484325 0.484325 0.242162 -0.484325 -3.9 -4.5 0.492038 0.492038 0.246019 -0.492038 -3.8 -4.5 0.499674 0.499674 0.249837 -0.499674 -3.7 -4.5 0.507225 0.507225 0.253613 -0.507225 -3.6 -4.5 0.514685 0.514685 0.257343 -0.514685 -3.5 -4.5 0.522046 0.522046 0.261023 -0.522046 -3.4 -4.5 0.5293 0.5293 0.26465 -0.5293 -3.3 -4.5 0.53644 0.53644 0.26822 -0.53644 -3.2 -4.5 0.54346 0.54346 0.27173 -0.54346 -3.1 -4.5 0.55035 0.55035 0.275175 -0.55035 -3 -4.5 0.557106 0.557106 0.278553 -0.557106 -2.9 -4.5 0.563719 0.563719 0.281859 -0.563719 -2.8 -4.5 0.570182 0.570182 0.285091 -0.570182 -2.7 -4.5 0.576488 0.576488 0.288244 -0.576488 -2.6 -4.5 0.582632 0.582632 0.291316 -0.582632 -2.5 -4.5 0.588605 0.588605 0.294302 -0.588605 -2.4 -4.5 0.594402 0.594402 0.297201 -0.594402 -2.3 -4.5 0.600015 0.600015 0.300008 -0.600015 -2.2 -4.5 0.60544 0.60544 0.30272 -0.60544 -2.1 -4.5 0.610669 0.610669 0.305335 -0.610669 -2 -4.5 0.615697 0.615697 0.307849 -0.615697 -1.9 -4.5 0.620518 0.620518 0.310259 -0.620518 -1.8 -4.5 0.625127 0.625127 0.312564 -0.625127 -1.7 -4.5 0.629519 0.629519 0.314759 -0.629519 -1.6 -4.5 0.633687 0.633687 0.316844 -0.633687 -1.5 -4.5 0.637628 0.637628 0.318814 -0.637628 -1.4 -4.5 0.641337 0.641337 0.320669 -0.641337 -1.3 -4.5 0.64481 0.64481 0.322405 -0.64481 -1.2 -4.5 0.648042 0.648042 0.324021 -0.648042 -1.1 -4.5 0.65103 0.65103 0.325515 -0.65103 -1 -4.5 0.65377 0.65377 0.326885 -0.65377 -0.9 -4.5 0.656259 0.656259 0.328129 -0.656259 -0.8 -4.5 0.658494 0.658494 0.329247 -0.658494 -0.7 -4.5 0.660472 0.660472 0.330236 -0.660472 -0.6 -4.5 0.662192 0.662192 0.331096 -0.662192 -0.5 -4.5 0.66365 0.66365 0.331825 -0.66365 -0.4 -4.5 0.664846 0.664846 0.332423 -0.664846 -0.3 -4.5 0.665777 0.665777 0.332889 -0.665777 -0.2 -4.5 0.666443 0.666443 0.333222 -0.666443 -0.1 -4.5 0.666843 0.666843 0.333422 -0.666843 0 -4.5 0.666977 0.666977 0.333488 -0.666977 0.1 -4.5 0.666843 0.666843 0.333422 -0.666843 0.2 -4.5 0.666443 0.666443 0.333222 -0.666443 0.3 -4.5 0.665777 0.665777 0.332889 -0.665777 0.4 -4.5 0.664846 0.664846 0.332423 -0.664846 0.5 -4.5 0.66365 0.66365 0.331825 -0.66365 0.6 -4.5 0.662192 0.662192 0.331096 -0.662192 0.7 -4.5 0.660472 0.660472 0.330236 -0.660472 0.8 -4.5 0.658494 0.658494 0.329247 -0.658494 0.9 -4.5 0.656259 0.656259 0.328129 -0.656259 1 -4.5 0.65377 0.65377 0.326885 -0.65377 1.1 -4.5 0.65103 0.65103 0.325515 -0.65103 1.2 -4.5 0.648042 0.648042 0.324021 -0.648042 1.3 -4.5 0.64481 0.64481 0.322405 -0.64481 1.4 -4.5 0.641337 0.641337 0.320669 -0.641337 1.5 -4.5 0.637628 0.637628 0.318814 -0.637628 1.6 -4.5 0.633687 0.633687 0.316844 -0.633687 1.7 -4.5 0.629519 0.629519 0.314759 -0.629519 1.8 -4.5 0.625127 0.625127 0.312564 -0.625127 1.9 -4.5 0.620518 0.620518 0.310259 -0.620518 2 -4.5 0.615697 0.615697 0.307849 -0.615697 2.1 -4.5 0.610669 0.610669 0.305335 -0.610669 2.2 -4.5 0.60544 0.60544 0.30272 -0.60544 2.3 -4.5 0.600015 0.600015 0.300008 -0.600015 2.4 -4.5 0.594402 0.594402 0.297201 -0.594402 2.5 -4.5 0.588605 0.588605 0.294302 -0.588605 2.6 -4.5 0.582632 0.582632 0.291316 -0.582632 2.7 -4.5 0.576488 0.576488 0.288244 -0.576488 2.8 -4.5 0.570182 0.570182 0.285091 -0.570182 2.9 -4.5 0.563719 0.563719 0.281859 -0.563719 3 -4.5 0.557106 0.557106 0.278553 -0.557106 3.1 -4.5 0.55035 0.55035 0.275175 -0.55035 3.2 -4.5 0.54346 0.54346 0.27173 -0.54346 3.3 -4.5 0.53644 0.53644 0.26822 -0.53644 3.4 -4.5 0.5293 0.5293 0.26465 -0.5293 3.5 -4.5 0.522046 0.522046 0.261023 -0.522046 3.6 -4.5 0.514685 0.514685 0.257343 -0.514685 3.7 -4.5 0.507225 0.507225 0.253613 -0.507225 3.8 -4.5 0.499674 0.499674 0.249837 -0.499674 3.9 -4.5 0.492038 0.492038 0.246019 -0.492038 4 -4.5 0.484325 0.484325 0.242162 -0.484325 4.1 -4.5 0.476542 0.476542 0.238271 -0.476542 4.2 -4.5 0.468696 0.468696 0.234348 -0.468696 4.3 -4.5 0.460796 0.460796 0.230398 -0.460796 4.4 -4.5 0.452847 0.452847 0.226424 -0.452847 4.5 -4.5 0.444858 0.444858 0.222429 -0.444858 4.6 -4.5 0.436835 0.436835 0.218417 -0.436835 4.7 -4.5 0.428785 0.428785 0.214392 -0.428785 4.8 -4.5 0.420715 0.420715 0.210357 -0.420715 4.9 -4.5 0.412632 0.412632 0.206316 -0.412632 -5 -4.4 0.411807 0.411807 0.205904 -0.411807 -4.9 -4.4 0.420042 0.420042 0.210021 -0.420042 -4.8 -4.4 0.428271 0.428271 0.214135 -0.428271 -4.7 -4.4 0.436486 0.436486 0.218243 -0.436486 -4.6 -4.4 0.44468 0.44468 0.22234 -0.44468 -4.5 -4.4 0.452847 0.452847 0.226424 -0.452847 -4.4 -4.4 0.46098 0.46098 0.23049 -0.46098 -4.3 -4.4 0.469072 0.469072 0.234536 -0.469072 -4.2 -4.4 0.477114 0.477114 0.238557 -0.477114 -4.1 -4.4 0.4851 0.4851 0.24255 -0.4851 -4 -4.4 0.493023 0.493023 0.246511 -0.493023 -3.9 -4.4 0.500874 0.500874 0.250437 -0.500874 -3.8 -4.4 0.508648 0.508648 0.254324 -0.508648 -3.7 -4.4 0.516335 0.516335 0.258167 -0.516335 -3.6 -4.4 0.523929 0.523929 0.261964 -0.523929 -3.5 -4.4 0.531421 0.531421 0.265711 -0.531421 -3.4 -4.4 0.538806 0.538806 0.269403 -0.538806 -3.3 -4.4 0.546074 0.546074 0.273037 -0.546074 -3.2 -4.4 0.55322 0.55322 0.27661 -0.55322 -3.1 -4.4 0.560234 0.560234 0.280117 -0.560234 -3 -4.4 0.567111 0.567111 0.283556 -0.567111 -2.9 -4.4 0.573843 0.573843 0.286921 -0.573843 -2.8 -4.4 0.580422 0.580422 0.290211 -0.580422 -2.7 -4.4 0.586842 0.586842 0.293421 -0.586842 -2.6 -4.4 0.593095 0.593095 0.296548 -0.593095 -2.5 -4.4 0.599176 0.599176 0.299588 -0.599176 -2.4 -4.4 0.605077 0.605077 0.302538 -0.605077 -2.3 -4.4 0.610791 0.610791 0.305396 -0.610791 -2.2 -4.4 0.616313 0.616313 0.308157 -0.616313 -2.1 -4.4 0.621636 0.621636 0.310818 -0.621636 -2 -4.4 0.626755 0.626755 0.313377 -0.626755 -1.9 -4.4 0.631663 0.631663 0.315831 -0.631663 -1.8 -4.4 0.636354 0.636354 0.318177 -0.636354 -1.7 -4.4 0.640824 0.640824 0.320412 -0.640824 -1.6 -4.4 0.645068 0.645068 0.322534 -0.645068 -1.5 -4.4 0.64908 0.64908 0.32454 -0.64908 -1.4 -4.4 0.652855 0.652855 0.326428 -0.652855 -1.3 -4.4 0.65639 0.65639 0.328195 -0.65639 -1.2 -4.4 0.65968 0.65968 0.32984 -0.65968 -1.1 -4.4 0.662722 0.662722 0.331361 -0.662722 -1 -4.4 0.665511 0.665511 0.332756 -0.665511 -0.9 -4.4 0.668045 0.668045 0.334022 -0.668045 -0.8 -4.4 0.67032 0.67032 0.33516 -0.67032 -0.7 -4.4 0.672334 0.672334 0.336167 -0.672334 -0.6 -4.4 0.674084 0.674084 0.337042 -0.674084 -0.5 -4.4 0.675569 0.675569 0.337784 -0.675569 -0.4 -4.4 0.676786 0.676786 0.338393 -0.676786 -0.3 -4.4 0.677734 0.677734 0.338867 -0.677734 -0.2 -4.4 0.678412 0.678412 0.339206 -0.678412 -0.1 -4.4 0.67882 0.67882 0.33941 -0.67882 0 -4.4 0.678955 0.678955 0.339478 -0.678955 0.1 -4.4 0.67882 0.67882 0.33941 -0.67882 0.2 -4.4 0.678412 0.678412 0.339206 -0.678412 0.3 -4.4 0.677734 0.677734 0.338867 -0.677734 0.4 -4.4 0.676786 0.676786 0.338393 -0.676786 0.5 -4.4 0.675569 0.675569 0.337784 -0.675569 0.6 -4.4 0.674084 0.674084 0.337042 -0.674084 0.7 -4.4 0.672334 0.672334 0.336167 -0.672334 0.8 -4.4 0.67032 0.67032 0.33516 -0.67032 0.9 -4.4 0.668045 0.668045 0.334022 -0.668045 1 -4.4 0.665511 0.665511 0.332756 -0.665511 1.1 -4.4 0.662722 0.662722 0.331361 -0.662722 1.2 -4.4 0.65968 0.65968 0.32984 -0.65968 1.3 -4.4 0.65639 0.65639 0.328195 -0.65639 1.4 -4.4 0.652855 0.652855 0.326428 -0.652855 1.5 -4.4 0.64908 0.64908 0.32454 -0.64908 1.6 -4.4 0.645068 0.645068 0.322534 -0.645068 1.7 -4.4 0.640824 0.640824 0.320412 -0.640824 1.8 -4.4 0.636354 0.636354 0.318177 -0.636354 1.9 -4.4 0.631663 0.631663 0.315831 -0.631663 2 -4.4 0.626755 0.626755 0.313377 -0.626755 2.1 -4.4 0.621636 0.621636 0.310818 -0.621636 2.2 -4.4 0.616313 0.616313 0.308157 -0.616313 2.3 -4.4 0.610791 0.610791 0.305396 -0.610791 2.4 -4.4 0.605077 0.605077 0.302538 -0.605077 2.5 -4.4 0.599176 0.599176 0.299588 -0.599176 2.6 -4.4 0.593095 0.593095 0.296548 -0.593095 2.7 -4.4 0.586842 0.586842 0.293421 -0.586842 2.8 -4.4 0.580422 0.580422 0.290211 -0.580422 2.9 -4.4 0.573843 0.573843 0.286921 -0.573843 3 -4.4 0.567111 0.567111 0.283556 -0.567111 3.1 -4.4 0.560234 0.560234 0.280117 -0.560234 3.2 -4.4 0.55322 0.55322 0.27661 -0.55322 3.3 -4.4 0.546074 0.546074 0.273037 -0.546074 3.4 -4.4 0.538806 0.538806 0.269403 -0.538806 3.5 -4.4 0.531421 0.531421 0.265711 -0.531421 3.6 -4.4 0.523929 0.523929 0.261964 -0.523929 3.7 -4.4 0.516335 0.516335 0.258167 -0.516335 3.8 -4.4 0.508648 0.508648 0.254324 -0.508648 3.9 -4.4 0.500874 0.500874 0.250437 -0.500874 4 -4.4 0.493023 0.493023 0.246511 -0.493023 4.1 -4.4 0.4851 0.4851 0.24255 -0.4851 4.2 -4.4 0.477114 0.477114 0.238557 -0.477114 4.3 -4.4 0.469072 0.469072 0.234536 -0.469072 4.4 -4.4 0.46098 0.46098 0.23049 -0.46098 4.5 -4.4 0.452847 0.452847 0.226424 -0.452847 4.6 -4.4 0.44468 0.44468 0.22234 -0.44468 4.7 -4.4 0.436486 0.436486 0.218243 -0.436486 4.8 -4.4 0.428271 0.428271 0.214135 -0.428271 4.9 -4.4 0.420042 0.420042 0.210021 -0.420042 -5 -4.3 0.419035 0.419035 0.209518 -0.419035 -4.9 -4.3 0.427415 0.427415 0.213707 -0.427415 -4.8 -4.3 0.435788 0.435788 0.217894 -0.435788 -4.7 -4.3 0.444147 0.444147 0.222073 -0.444147 -4.6 -4.3 0.452485 0.452485 0.226243 -0.452485 -4.5 -4.3 0.460796 0.460796 0.230398 -0.460796 -4.4 -4.3 0.469072 0.469072 0.234536 -0.469072 -4.3 -4.3 0.477305 0.477305 0.238652 -0.477305 -4.2 -4.3 0.485488 0.485488 0.242744 -0.485488 -4.1 -4.3 0.493615 0.493615 0.246807 -0.493615 -4 -4.3 0.501676 0.501676 0.250838 -0.501676 -3.9 -4.3 0.509666 0.509666 0.254833 -0.509666 -3.8 -4.3 0.517575 0.517575 0.258788 -0.517575 -3.7 -4.3 0.525398 0.525398 0.262699 -0.525398 -3.6 -4.3 0.533125 0.533125 0.266562 -0.533125 -3.5 -4.3 0.540749 0.540749 0.270375 -0.540749 -3.4 -4.3 0.548263 0.548263 0.274132 -0.548263 -3.3 -4.3 0.555659 0.555659 0.27783 -0.555659 -3.2 -4.3 0.56293 0.56293 0.281465 -0.56293 -3.1 -4.3 0.570068 0.570068 0.285034 -0.570068 -3 -4.3 0.577065 0.577065 0.288533 -0.577065 -2.9 -4.3 0.583915 0.583915 0.291957 -0.583915 -2.8 -4.3 0.59061 0.59061 0.295305 -0.59061 -2.7 -4.3 0.597142 0.597142 0.298571 -0.597142 -2.6 -4.3 0.603506 0.603506 0.301753 -0.603506 -2.5 -4.3 0.609693 0.609693 0.304846 -0.609693 -2.4 -4.3 0.615697 0.615697 0.307849 -0.615697 -2.3 -4.3 0.621512 0.621512 0.310756 -0.621512 -2.2 -4.3 0.627131 0.627131 0.313565 -0.627131 -2.1 -4.3 0.632547 0.632547 0.316274 -0.632547 -2 -4.3 0.637756 0.637756 0.318878 -0.637756 -1.9 -4.3 0.64275 0.64275 0.321375 -0.64275 -1.8 -4.3 0.647524 0.647524 0.323762 -0.647524 -1.7 -4.3 0.652072 0.652072 0.326036 -0.652072 -1.6 -4.3 0.65639 0.65639 0.328195 -0.65639 -1.5 -4.3 0.660472 0.660472 0.330236 -0.660472 -1.4 -4.3 0.664314 0.664314 0.332157 -0.664314 -1.3 -4.3 0.667911 0.667911 0.333956 -0.667911 -1.2 -4.3 0.671259 0.671259 0.33563 -0.671259 -1.1 -4.3 0.674354 0.674354 0.337177 -0.674354 -1 -4.3 0.677192 0.677192 0.338596 -0.677192 -0.9 -4.3 0.679771 0.679771 0.339885 -0.679771 -0.8 -4.3 0.682086 0.682086 0.341043 -0.682086 -0.7 -4.3 0.684135 0.684135 0.342068 -0.684135 -0.6 -4.3 0.685916 0.685916 0.342958 -0.685916 -0.5 -4.3 0.687427 0.687427 0.343713 -0.687427 -0.4 -4.3 0.688665 0.688665 0.344333 -0.688665 -0.3 -4.3 0.68963 0.68963 0.344815 -0.68963 -0.2 -4.3 0.69032 0.69032 0.34516 -0.69032 -0.1 -4.3 0.690734 0.690734 0.345367 -0.690734 0 -4.3 0.690872 0.690872 0.345436 -0.690872 0.1 -4.3 0.690734 0.690734 0.345367 -0.690734 0.2 -4.3 0.69032 0.69032 0.34516 -0.69032 0.3 -4.3 0.68963 0.68963 0.344815 -0.68963 0.4 -4.3 0.688665 0.688665 0.344333 -0.688665 0.5 -4.3 0.687427 0.687427 0.343713 -0.687427 0.6 -4.3 0.685916 0.685916 0.342958 -0.685916 0.7 -4.3 0.684135 0.684135 0.342068 -0.684135 0.8 -4.3 0.682086 0.682086 0.341043 -0.682086 0.9 -4.3 0.679771 0.679771 0.339885 -0.679771 1 -4.3 0.677192 0.677192 0.338596 -0.677192 1.1 -4.3 0.674354 0.674354 0.337177 -0.674354 1.2 -4.3 0.671259 0.671259 0.33563 -0.671259 1.3 -4.3 0.667911 0.667911 0.333956 -0.667911 1.4 -4.3 0.664314 0.664314 0.332157 -0.664314 1.5 -4.3 0.660472 0.660472 0.330236 -0.660472 1.6 -4.3 0.65639 0.65639 0.328195 -0.65639 1.7 -4.3 0.652072 0.652072 0.326036 -0.652072 1.8 -4.3 0.647524 0.647524 0.323762 -0.647524 1.9 -4.3 0.64275 0.64275 0.321375 -0.64275 2 -4.3 0.637756 0.637756 0.318878 -0.637756 2.1 -4.3 0.632547 0.632547 0.316274 -0.632547 2.2 -4.3 0.627131 0.627131 0.313565 -0.627131 2.3 -4.3 0.621512 0.621512 0.310756 -0.621512 2.4 -4.3 0.615697 0.615697 0.307849 -0.615697 2.5 -4.3 0.609693 0.609693 0.304846 -0.609693 2.6 -4.3 0.603506 0.603506 0.301753 -0.603506 2.7 -4.3 0.597142 0.597142 0.298571 -0.597142 2.8 -4.3 0.59061 0.59061 0.295305 -0.59061 2.9 -4.3 0.583915 0.583915 0.291957 -0.583915 3 -4.3 0.577065 0.577065 0.288533 -0.577065 3.1 -4.3 0.570068 0.570068 0.285034 -0.570068 3.2 -4.3 0.56293 0.56293 0.281465 -0.56293 3.3 -4.3 0.555659 0.555659 0.27783 -0.555659 3.4 -4.3 0.548263 0.548263 0.274132 -0.548263 3.5 -4.3 0.540749 0.540749 0.270375 -0.540749 3.6 -4.3 0.533125 0.533125 0.266562 -0.533125 3.7 -4.3 0.525398 0.525398 0.262699 -0.525398 3.8 -4.3 0.517575 0.517575 0.258788 -0.517575 3.9 -4.3 0.509666 0.509666 0.254833 -0.509666 4 -4.3 0.501676 0.501676 0.250838 -0.501676 4.1 -4.3 0.493615 0.493615 0.246807 -0.493615 4.2 -4.3 0.485488 0.485488 0.242744 -0.485488 4.3 -4.3 0.477305 0.477305 0.238652 -0.477305 4.4 -4.3 0.469072 0.469072 0.234536 -0.469072 4.5 -4.3 0.460796 0.460796 0.230398 -0.460796 4.6 -4.3 0.452485 0.452485 0.226243 -0.452485 4.7 -4.3 0.444147 0.444147 0.222073 -0.444147 4.8 -4.3 0.435788 0.435788 0.217894 -0.435788 4.9 -4.3 0.427415 0.427415 0.213707 -0.427415 -5 -4.2 0.42622 0.42622 0.21311 -0.42622 -4.9 -4.2 0.434743 0.434743 0.217372 -0.434743 -4.8 -4.2 0.443259 0.443259 0.22163 -0.443259 -4.7 -4.2 0.451762 0.451762 0.225881 -0.451762 -4.6 -4.2 0.460243 0.460243 0.230122 -0.460243 -4.5 -4.2 0.468696 0.468696 0.234348 -0.468696 -4.4 -4.2 0.477114 0.477114 0.238557 -0.477114 -4.3 -4.2 0.485488 0.485488 0.242744 -0.485488 -4.2 -4.2 0.493812 0.493812 0.246906 -0.493812 -4.1 -4.2 0.502078 0.502078 0.251039 -0.502078 -4 -4.2 0.510278 0.510278 0.255139 -0.510278 -3.9 -4.2 0.518404 0.518404 0.259202 -0.518404 -3.8 -4.2 0.526449 0.526449 0.263225 -0.526449 -3.7 -4.2 0.534406 0.534406 0.267203 -0.534406 -3.6 -4.2 0.542265 0.542265 0.271133 -0.542265 -3.5 -4.2 0.55002 0.55002 0.27501 -0.55002 -3.4 -4.2 0.557663 0.557663 0.278832 -0.557663 -3.3 -4.2 0.565186 0.565186 0.282593 -0.565186 -3.2 -4.2 0.572582 0.572582 0.286291 -0.572582 -3.1 -4.2 0.579842 0.579842 0.289921 -0.579842 -3 -4.2 0.586959 0.586959 0.29348 -0.586959 -2.9 -4.2 0.593926 0.593926 0.296963 -0.593926 -2.8 -4.2 0.600736 0.600736 0.300368 -0.600736 -2.7 -4.2 0.60738 0.60738 0.30369 -0.60738 -2.6 -4.2 0.613853 0.613853 0.306926 -0.613853 -2.5 -4.2 0.620146 0.620146 0.310073 -0.620146 -2.4 -4.2 0.626254 0.626254 0.313127 -0.626254 -2.3 -4.2 0.632168 0.632168 0.316084 -0.632168 -2.2 -4.2 0.637883 0.637883 0.318942 -0.637883 -2.1 -4.2 0.643393 0.643393 0.321696 -0.643393 -2 -4.2 0.64869 0.64869 0.324345 -0.64869 -1.9 -4.2 0.65377 0.65377 0.326885 -0.65377 -1.8 -4.2 0.658626 0.658626 0.329313 -0.658626 -1.7 -4.2 0.663252 0.663252 0.331626 -0.663252 -1.6 -4.2 0.667644 0.667644 0.333822 -0.667644 -1.5 -4.2 0.671796 0.671796 0.335898 -0.671796 -1.4 -4.2 0.675704 0.675704 0.337852 -0.675704 -1.3 -4.2 0.679363 0.679363 0.339681 -0.679363 -1.2 -4.2 0.682768 0.682768 0.341384 -0.682768 -1.1 -4.2 0.685916 0.685916 0.342958 -0.685916 -1 -4.2 0.688803 0.688803 0.344401 -0.688803 -0.9 -4.2 0.691425 0.691425 0.345713 -0.691425 -0.8 -4.2 0.69378 0.69378 0.34689 -0.69378 -0.7 -4.2 0.695865 0.695865 0.347932 -0.695865 -0.6 -4.2 0.697676 0.697676 0.348838 -0.697676 -0.5 -4.2 0.699213 0.699213 0.349606 -0.699213 -0.4 -4.2 0.700473 0.700473 0.350236 -0.700473 -0.3 -4.2 0.701454 0.701454 0.350727 -0.701454 -0.2 -4.2 0.702156 0.702156 0.351078 -0.702156 -0.1 -4.2 0.702577 0.702577 0.351289 -0.702577 0 -4.2 0.702718 0.702718 0.351359 -0.702718 0.1 -4.2 0.702577 0.702577 0.351289 -0.702577 0.2 -4.2 0.702156 0.702156 0.351078 -0.702156 0.3 -4.2 0.701454 0.701454 0.350727 -0.701454 0.4 -4.2 0.700473 0.700473 0.350236 -0.700473 0.5 -4.2 0.699213 0.699213 0.349606 -0.699213 0.6 -4.2 0.697676 0.697676 0.348838 -0.697676 0.7 -4.2 0.695865 0.695865 0.347932 -0.695865 0.8 -4.2 0.69378 0.69378 0.34689 -0.69378 0.9 -4.2 0.691425 0.691425 0.345713 -0.691425 1 -4.2 0.688803 0.688803 0.344401 -0.688803 1.1 -4.2 0.685916 0.685916 0.342958 -0.685916 1.2 -4.2 0.682768 0.682768 0.341384 -0.682768 1.3 -4.2 0.679363 0.679363 0.339681 -0.679363 1.4 -4.2 0.675704 0.675704 0.337852 -0.675704 1.5 -4.2 0.671796 0.671796 0.335898 -0.671796 1.6 -4.2 0.667644 0.667644 0.333822 -0.667644 1.7 -4.2 0.663252 0.663252 0.331626 -0.663252 1.8 -4.2 0.658626 0.658626 0.329313 -0.658626 1.9 -4.2 0.65377 0.65377 0.326885 -0.65377 2 -4.2 0.64869 0.64869 0.324345 -0.64869 2.1 -4.2 0.643393 0.643393 0.321696 -0.643393 2.2 -4.2 0.637883 0.637883 0.318942 -0.637883 2.3 -4.2 0.632168 0.632168 0.316084 -0.632168 2.4 -4.2 0.626254 0.626254 0.313127 -0.626254 2.5 -4.2 0.620146 0.620146 0.310073 -0.620146 2.6 -4.2 0.613853 0.613853 0.306926 -0.613853 2.7 -4.2 0.60738 0.60738 0.30369 -0.60738 2.8 -4.2 0.600736 0.600736 0.300368 -0.600736 2.9 -4.2 0.593926 0.593926 0.296963 -0.593926 3 -4.2 0.586959 0.586959 0.29348 -0.586959 3.1 -4.2 0.579842 0.579842 0.289921 -0.579842 3.2 -4.2 0.572582 0.572582 0.286291 -0.572582 3.3 -4.2 0.565186 0.565186 0.282593 -0.565186 3.4 -4.2 0.557663 0.557663 0.278832 -0.557663 3.5 -4.2 0.55002 0.55002 0.27501 -0.55002 3.6 -4.2 0.542265 0.542265 0.271133 -0.542265 3.7 -4.2 0.534406 0.534406 0.267203 -0.534406 3.8 -4.2 0.526449 0.526449 0.263225 -0.526449 3.9 -4.2 0.518404 0.518404 0.259202 -0.518404 4 -4.2 0.510278 0.510278 0.255139 -0.510278 4.1 -4.2 0.502078 0.502078 0.251039 -0.502078 4.2 -4.2 0.493812 0.493812 0.246906 -0.493812 4.3 -4.2 0.485488 0.485488 0.242744 -0.485488 4.4 -4.2 0.477114 0.477114 0.238557 -0.477114 4.5 -4.2 0.468696 0.468696 0.234348 -0.468696 4.6 -4.2 0.460243 0.460243 0.230122 -0.460243 4.7 -4.2 0.451762 0.451762 0.225881 -0.451762 4.8 -4.2 0.443259 0.443259 0.22163 -0.443259 4.9 -4.2 0.434743 0.434743 0.217372 -0.434743 -5 -4.1 0.433354 0.433354 0.216677 -0.433354 -4.9 -4.1 0.44202 0.44202 0.22101 -0.44202 -4.8 -4.1 0.450679 0.450679 0.225339 -0.450679 -4.7 -4.1 0.459324 0.459324 0.229662 -0.459324 -4.6 -4.1 0.467947 0.467947 0.233974 -0.467947 -4.5 -4.1 0.476542 0.476542 0.238271 -0.476542 -4.4 -4.1 0.4851 0.4851 0.24255 -0.4851 -4.3 -4.1 0.493615 0.493615 0.246807 -0.493615 -4.2 -4.1 0.502078 0.502078 0.251039 -0.502078 -4.1 -4.1 0.510482 0.510482 0.255241 -0.510482 -4 -4.1 0.518819 0.518819 0.25941 -0.518819 -3.9 -4.1 0.527082 0.527082 0.263541 -0.527082 -3.8 -4.1 0.535261 0.535261 0.267631 -0.535261 -3.7 -4.1 0.543351 0.543351 0.271675 -0.543351 -3.6 -4.1 0.551342 0.551342 0.275671 -0.551342 -3.5 -4.1 0.559227 0.559227 0.279613 -0.559227 -3.4 -4.1 0.566998 0.566998 0.283499 -0.566998 -3.3 -4.1 0.574647 0.574647 0.287323 -0.574647 -3.2 -4.1 0.582166 0.582166 0.291083 -0.582166 -3.1 -4.1 0.589547 0.589547 0.294774 -0.589547 -3 -4.1 0.596784 0.596784 0.298392 -0.596784 -2.9 -4.1 0.603868 0.603868 0.301934 -0.603868 -2.8 -4.1 0.610791 0.610791 0.305396 -0.610791 -2.7 -4.1 0.617547 0.617547 0.308774 -0.617547 -2.6 -4.1 0.624128 0.624128 0.312064 -0.624128 -2.5 -4.1 0.630527 0.630527 0.315263 -0.630527 -2.4 -4.1 0.636736 0.636736 0.318368 -0.636736 -2.3 -4.1 0.64275 0.64275 0.321375 -0.64275 -2.2 -4.1 0.64856 0.64856 0.32428 -0.64856 -2.1 -4.1 0.654162 0.654162 0.327081 -0.654162 -2 -4.1 0.659548 0.659548 0.329774 -0.659548 -1.9 -4.1 0.664713 0.664713 0.332356 -0.664713 -1.8 -4.1 0.66965 0.66965 0.334825 -0.66965 -1.7 -4.1 0.674354 0.674354 0.337177 -0.674354 -1.6 -4.1 0.67882 0.67882 0.33941 -0.67882 -1.5 -4.1 0.683041 0.683041 0.341521 -0.683041 -1.4 -4.1 0.687014 0.687014 0.343507 -0.687014 -1.3 -4.1 0.690734 0.690734 0.345367 -0.690734 -1.2 -4.1 0.694197 0.694197 0.347098 -0.694197 -1.1 -4.1 0.697397 0.697397 0.348699 -0.697397 -1 -4.1 0.700333 0.700333 0.350166 -0.700333 -0.9 -4.1 0.702999 0.702999 0.351499 -0.702999 -0.8 -4.1 0.705393 0.705393 0.352697 -0.705393 -0.7 -4.1 0.707512 0.707512 0.353756 -0.707512 -0.6 -4.1 0.709354 0.709354 0.354677 -0.709354 -0.5 -4.1 0.710917 0.710917 0.355458 -0.710917 -0.4 -4.1 0.712198 0.712198 0.356099 -0.712198 -0.3 -4.1 0.713195 0.713195 0.356598 -0.713195 -0.2 -4.1 0.713909 0.713909 0.356954 -0.713909 -0.1 -4.1 0.714337 0.714337 0.357169 -0.714337 0 -4.1 0.71448 0.71448 0.35724 -0.71448 0.1 -4.1 0.714337 0.714337 0.357169 -0.714337 0.2 -4.1 0.713909 0.713909 0.356954 -0.713909 0.3 -4.1 0.713195 0.713195 0.356598 -0.713195 0.4 -4.1 0.712198 0.712198 0.356099 -0.712198 0.5 -4.1 0.710917 0.710917 0.355458 -0.710917 0.6 -4.1 0.709354 0.709354 0.354677 -0.709354 0.7 -4.1 0.707512 0.707512 0.353756 -0.707512 0.8 -4.1 0.705393 0.705393 0.352697 -0.705393 0.9 -4.1 0.702999 0.702999 0.351499 -0.702999 1 -4.1 0.700333 0.700333 0.350166 -0.700333 1.1 -4.1 0.697397 0.697397 0.348699 -0.697397 1.2 -4.1 0.694197 0.694197 0.347098 -0.694197 1.3 -4.1 0.690734 0.690734 0.345367 -0.690734 1.4 -4.1 0.687014 0.687014 0.343507 -0.687014 1.5 -4.1 0.683041 0.683041 0.341521 -0.683041 1.6 -4.1 0.67882 0.67882 0.33941 -0.67882 1.7 -4.1 0.674354 0.674354 0.337177 -0.674354 1.8 -4.1 0.66965 0.66965 0.334825 -0.66965 1.9 -4.1 0.664713 0.664713 0.332356 -0.664713 2 -4.1 0.659548 0.659548 0.329774 -0.659548 2.1 -4.1 0.654162 0.654162 0.327081 -0.654162 2.2 -4.1 0.64856 0.64856 0.32428 -0.64856 2.3 -4.1 0.64275 0.64275 0.321375 -0.64275 2.4 -4.1 0.636736 0.636736 0.318368 -0.636736 2.5 -4.1 0.630527 0.630527 0.315263 -0.630527 2.6 -4.1 0.624128 0.624128 0.312064 -0.624128 2.7 -4.1 0.617547 0.617547 0.308774 -0.617547 2.8 -4.1 0.610791 0.610791 0.305396 -0.610791 2.9 -4.1 0.603868 0.603868 0.301934 -0.603868 3 -4.1 0.596784 0.596784 0.298392 -0.596784 3.1 -4.1 0.589547 0.589547 0.294774 -0.589547 3.2 -4.1 0.582166 0.582166 0.291083 -0.582166 3.3 -4.1 0.574647 0.574647 0.287323 -0.574647 3.4 -4.1 0.566998 0.566998 0.283499 -0.566998 3.5 -4.1 0.559227 0.559227 0.279613 -0.559227 3.6 -4.1 0.551342 0.551342 0.275671 -0.551342 3.7 -4.1 0.543351 0.543351 0.271675 -0.543351 3.8 -4.1 0.535261 0.535261 0.267631 -0.535261 3.9 -4.1 0.527082 0.527082 0.263541 -0.527082 4 -4.1 0.518819 0.518819 0.25941 -0.518819 4.1 -4.1 0.510482 0.510482 0.255241 -0.510482 4.2 -4.1 0.502078 0.502078 0.251039 -0.502078 4.3 -4.1 0.493615 0.493615 0.246807 -0.493615 4.4 -4.1 0.4851 0.4851 0.24255 -0.4851 4.5 -4.1 0.476542 0.476542 0.238271 -0.476542 4.6 -4.1 0.467947 0.467947 0.233974 -0.467947 4.7 -4.1 0.459324 0.459324 0.229662 -0.459324 4.8 -4.1 0.450679 0.450679 0.225339 -0.450679 4.9 -4.1 0.44202 0.44202 0.22101 -0.44202 -5 -4 0.440432 0.440432 0.220216 -0.440432 -4.9 -4 0.449239 0.449239 0.22462 -0.449239 -4.8 -4 0.458039 0.458039 0.22902 -0.458039 -4.7 -4 0.466825 0.466825 0.233413 -0.466825 -4.6 -4 0.47559 0.47559 0.237795 -0.47559 -4.5 -4 0.484325 0.484325 0.242162 -0.484325 -4.4 -4 0.493023 0.493023 0.246511 -0.493023 -4.3 -4 0.501676 0.501676 0.250838 -0.501676 -4.2 -4 0.510278 0.510278 0.255139 -0.510278 -4.1 -4 0.518819 0.518819 0.25941 -0.518819 -4 -4 0.527292 0.527292 0.263646 -0.527292 -3.9 -4 0.53569 0.53569 0.267845 -0.53569 -3.8 -4 0.544003 0.544003 0.272002 -0.544003 -3.7 -4 0.552225 0.552225 0.276112 -0.552225 -3.6 -4 0.560346 0.560346 0.280173 -0.560346 -3.5 -4 0.56836 0.56836 0.28418 -0.56836 -3.4 -4 0.576258 0.576258 0.288129 -0.576258 -3.3 -4 0.584032 0.584032 0.292016 -0.584032 -3.2 -4 0.591674 0.591674 0.295837 -0.591674 -3.1 -4 0.599176 0.599176 0.299588 -0.599176 -3 -4 0.606531 0.606531 0.303265 -0.606531 -2.9 -4 0.61373 0.61373 0.306865 -0.61373 -2.8 -4 0.620767 0.620767 0.310383 -0.620767 -2.7 -4 0.627633 0.627633 0.313816 -0.627633 -2.6 -4 0.634321 0.634321 0.317161 -0.634321 -2.5 -4 0.640824 0.640824 0.320412 -0.640824 -2.4 -4 0.647135 0.647135 0.323568 -0.647135 -2.3 -4 0.653247 0.653247 0.326623 -0.653247 -2.2 -4 0.659153 0.659153 0.329576 -0.659153 -2.1 -4 0.664846 0.664846 0.332423 -0.664846 -2 -4 0.67032 0.67032 0.33516 -0.67032 -1.9 -4 0.675569 0.675569 0.337784 -0.675569 -1.8 -4 0.680587 0.680587 0.340293 -0.680587 -1.7 -4 0.685368 0.685368 0.342684 -0.685368 -1.6 -4 0.689906 0.689906 0.344953 -0.689906 -1.5 -4 0.694197 0.694197 0.347098 -0.694197 -1.4 -4 0.698235 0.698235 0.349117 -0.698235 -1.3 -4 0.702015 0.702015 0.351008 -0.702015 -1.2 -4 0.705534 0.705534 0.352767 -0.705534 -1.1 -4 0.708787 0.708787 0.354394 -0.708787 -1 -4 0.71177 0.71177 0.355885 -0.71177 -0.9 -4 0.71448 0.71448 0.35724 -0.71448 -0.8 -4 0.716914 0.716914 0.358457 -0.716914 -0.7 -4 0.719068 0.719068 0.359534 -0.719068 -0.6 -4 0.72094 0.72094 0.36047 -0.72094 -0.5 -4 0.722527 0.722527 0.361264 -0.722527 -0.4 -4 0.723829 0.723829 0.361915 -0.723829 -0.3 -4 0.724843 0.724843 0.362422 -0.724843 -0.2 -4 0.725568 0.725568 0.362784 -0.725568 -0.1 -4 0.726004 0.726004 0.363002 -0.726004 0 -4 0.726149 0.726149 0.363075 -0.726149 0.1 -4 0.726004 0.726004 0.363002 -0.726004 0.2 -4 0.725568 0.725568 0.362784 -0.725568 0.3 -4 0.724843 0.724843 0.362422 -0.724843 0.4 -4 0.723829 0.723829 0.361915 -0.723829 0.5 -4 0.722527 0.722527 0.361264 -0.722527 0.6 -4 0.72094 0.72094 0.36047 -0.72094 0.7 -4 0.719068 0.719068 0.359534 -0.719068 0.8 -4 0.716914 0.716914 0.358457 -0.716914 0.9 -4 0.71448 0.71448 0.35724 -0.71448 1 -4 0.71177 0.71177 0.355885 -0.71177 1.1 -4 0.708787 0.708787 0.354394 -0.708787 1.2 -4 0.705534 0.705534 0.352767 -0.705534 1.3 -4 0.702015 0.702015 0.351008 -0.702015 1.4 -4 0.698235 0.698235 0.349117 -0.698235 1.5 -4 0.694197 0.694197 0.347098 -0.694197 1.6 -4 0.689906 0.689906 0.344953 -0.689906 1.7 -4 0.685368 0.685368 0.342684 -0.685368 1.8 -4 0.680587 0.680587 0.340293 -0.680587 1.9 -4 0.675569 0.675569 0.337784 -0.675569 2 -4 0.67032 0.67032 0.33516 -0.67032 2.1 -4 0.664846 0.664846 0.332423 -0.664846 2.2 -4 0.659153 0.659153 0.329576 -0.659153 2.3 -4 0.653247 0.653247 0.326623 -0.653247 2.4 -4 0.647135 0.647135 0.323568 -0.647135 2.5 -4 0.640824 0.640824 0.320412 -0.640824 2.6 -4 0.634321 0.634321 0.317161 -0.634321 2.7 -4 0.627633 0.627633 0.313816 -0.627633 2.8 -4 0.620767 0.620767 0.310383 -0.620767 2.9 -4 0.61373 0.61373 0.306865 -0.61373 3 -4 0.606531 0.606531 0.303265 -0.606531 3.1 -4 0.599176 0.599176 0.299588 -0.599176 3.2 -4 0.591674 0.591674 0.295837 -0.591674 3.3 -4 0.584032 0.584032 0.292016 -0.584032 3.4 -4 0.576258 0.576258 0.288129 -0.576258 3.5 -4 0.56836 0.56836 0.28418 -0.56836 3.6 -4 0.560346 0.560346 0.280173 -0.560346 3.7 -4 0.552225 0.552225 0.276112 -0.552225 3.8 -4 0.544003 0.544003 0.272002 -0.544003 3.9 -4 0.53569 0.53569 0.267845 -0.53569 4 -4 0.527292 0.527292 0.263646 -0.527292 4.1 -4 0.518819 0.518819 0.25941 -0.518819 4.2 -4 0.510278 0.510278 0.255139 -0.510278 4.3 -4 0.501676 0.501676 0.250838 -0.501676 4.4 -4 0.493023 0.493023 0.246511 -0.493023 4.5 -4 0.484325 0.484325 0.242162 -0.484325 4.6 -4 0.47559 0.47559 0.237795 -0.47559 4.7 -4 0.466825 0.466825 0.233413 -0.466825 4.8 -4 0.458039 0.458039 0.22902 -0.458039 4.9 -4 0.449239 0.449239 0.22462 -0.449239 -5 -3.9 0.447446 0.447446 0.223723 -0.447446 -4.9 -3.9 0.456393 0.456393 0.228197 -0.456393 -4.8 -3.9 0.465334 0.465334 0.232667 -0.465334 -4.7 -3.9 0.47426 0.47426 0.23713 -0.47426 -4.6 -3.9 0.483164 0.483164 0.241582 -0.483164 -4.5 -3.9 0.492038 0.492038 0.246019 -0.492038 -4.4 -3.9 0.500874 0.500874 0.250437 -0.500874 -4.3 -3.9 0.509666 0.509666 0.254833 -0.509666 -4.2 -3.9 0.518404 0.518404 0.259202 -0.518404 -4.1 -3.9 0.527082 0.527082 0.263541 -0.527082 -4 -3.9 0.53569 0.53569 0.267845 -0.53569 -3.9 -3.9 0.544221 0.544221 0.27211 -0.544221 -3.8 -3.9 0.552667 0.552667 0.276333 -0.552667 -3.7 -3.9 0.561019 0.561019 0.28051 -0.561019 -3.6 -3.9 0.56927 0.56927 0.284635 -0.56927 -3.5 -3.9 0.577412 0.577412 0.288706 -0.577412 -3.4 -3.9 0.585435 0.585435 0.292718 -0.585435 -3.3 -3.9 0.593333 0.593333 0.296666 -0.593333 -3.2 -3.9 0.601096 0.601096 0.300548 -0.601096 -3.1 -3.9 0.608718 0.608718 0.304359 -0.608718 -3 -3.9 0.61619 0.61619 0.308095 -0.61619 -2.9 -3.9 0.623504 0.623504 0.311752 -0.623504 -2.8 -3.9 0.630653 0.630653 0.315326 -0.630653 -2.7 -3.9 0.637628 0.637628 0.318814 -0.637628 -2.6 -3.9 0.644423 0.644423 0.322211 -0.644423 -2.5 -3.9 0.65103 0.65103 0.325515 -0.65103 -2.4 -3.9 0.657441 0.657441 0.328721 -0.657441 -2.3 -3.9 0.66365 0.66365 0.331825 -0.66365 -2.2 -3.9 0.66965 0.66965 0.334825 -0.66965 -2.1 -3.9 0.675434 0.675434 0.337717 -0.675434 -2 -3.9 0.680995 0.680995 0.340498 -0.680995 -1.9 -3.9 0.686328 0.686328 0.343164 -0.686328 -1.8 -3.9 0.691425 0.691425 0.345713 -0.691425 -1.7 -3.9 0.696282 0.696282 0.348141 -0.696282 -1.6 -3.9 0.700893 0.700893 0.350447 -0.700893 -1.5 -3.9 0.705252 0.705252 0.352626 -0.705252 -1.4 -3.9 0.709354 0.709354 0.354677 -0.709354 -1.3 -3.9 0.713195 0.713195 0.356598 -0.713195 -1.2 -3.9 0.71677 0.71677 0.358385 -0.71677 -1.1 -3.9 0.720075 0.720075 0.360037 -0.720075 -1 -3.9 0.723106 0.723106 0.361553 -0.723106 -0.9 -3.9 0.725859 0.725859 0.362929 -0.725859 -0.8 -3.9 0.728331 0.728331 0.364165 -0.728331 -0.7 -3.9 0.730519 0.730519 0.36526 -0.730519 -0.6 -3.9 0.732421 0.732421 0.36621 -0.732421 -0.5 -3.9 0.734034 0.734034 0.367017 -0.734034 -0.4 -3.9 0.735356 0.735356 0.367678 -0.735356 -0.3 -3.9 0.736387 0.736387 0.368193 -0.736387 -0.2 -3.9 0.737123 0.737123 0.368562 -0.737123 -0.1 -3.9 0.737566 0.737566 0.368783 -0.737566 0 -3.9 0.737713 0.737713 0.368857 -0.737713 0.1 -3.9 0.737566 0.737566 0.368783 -0.737566 0.2 -3.9 0.737123 0.737123 0.368562 -0.737123 0.3 -3.9 0.736387 0.736387 0.368193 -0.736387 0.4 -3.9 0.735356 0.735356 0.367678 -0.735356 0.5 -3.9 0.734034 0.734034 0.367017 -0.734034 0.6 -3.9 0.732421 0.732421 0.36621 -0.732421 0.7 -3.9 0.730519 0.730519 0.36526 -0.730519 0.8 -3.9 0.728331 0.728331 0.364165 -0.728331 0.9 -3.9 0.725859 0.725859 0.362929 -0.725859 1 -3.9 0.723106 0.723106 0.361553 -0.723106 1.1 -3.9 0.720075 0.720075 0.360037 -0.720075 1.2 -3.9 0.71677 0.71677 0.358385 -0.71677 1.3 -3.9 0.713195 0.713195 0.356598 -0.713195 1.4 -3.9 0.709354 0.709354 0.354677 -0.709354 1.5 -3.9 0.705252 0.705252 0.352626 -0.705252 1.6 -3.9 0.700893 0.700893 0.350447 -0.700893 1.7 -3.9 0.696282 0.696282 0.348141 -0.696282 1.8 -3.9 0.691425 0.691425 0.345713 -0.691425 1.9 -3.9 0.686328 0.686328 0.343164 -0.686328 2 -3.9 0.680995 0.680995 0.340498 -0.680995 2.1 -3.9 0.675434 0.675434 0.337717 -0.675434 2.2 -3.9 0.66965 0.66965 0.334825 -0.66965 2.3 -3.9 0.66365 0.66365 0.331825 -0.66365 2.4 -3.9 0.657441 0.657441 0.328721 -0.657441 2.5 -3.9 0.65103 0.65103 0.325515 -0.65103 2.6 -3.9 0.644423 0.644423 0.322211 -0.644423 2.7 -3.9 0.637628 0.637628 0.318814 -0.637628 2.8 -3.9 0.630653 0.630653 0.315326 -0.630653 2.9 -3.9 0.623504 0.623504 0.311752 -0.623504 3 -3.9 0.61619 0.61619 0.308095 -0.61619 3.1 -3.9 0.608718 0.608718 0.304359 -0.608718 3.2 -3.9 0.601096 0.601096 0.300548 -0.601096 3.3 -3.9 0.593333 0.593333 0.296666 -0.593333 3.4 -3.9 0.585435 0.585435 0.292718 -0.585435 3.5 -3.9 0.577412 0.577412 0.288706 -0.577412 3.6 -3.9 0.56927 0.56927 0.284635 -0.56927 3.7 -3.9 0.561019 0.561019 0.28051 -0.561019 3.8 -3.9 0.552667 0.552667 0.276333 -0.552667 3.9 -3.9 0.544221 0.544221 0.27211 -0.544221 4 -3.9 0.53569 0.53569 0.267845 -0.53569 4.1 -3.9 0.527082 0.527082 0.263541 -0.527082 4.2 -3.9 0.518404 0.518404 0.259202 -0.518404 4.3 -3.9 0.509666 0.509666 0.254833 -0.509666 4.4 -3.9 0.500874 0.500874 0.250437 -0.500874 4.5 -3.9 0.492038 0.492038 0.246019 -0.492038 4.6 -3.9 0.483164 0.483164 0.241582 -0.483164 4.7 -3.9 0.47426 0.47426 0.23713 -0.47426 4.8 -3.9 0.465334 0.465334 0.232667 -0.465334 4.9 -3.9 0.456393 0.456393 0.228197 -0.456393 -5 -3.8 0.45439 0.45439 0.227195 -0.45439 -4.9 -3.8 0.463476 0.463476 0.231738 -0.463476 -4.8 -3.8 0.472556 0.472556 0.236278 -0.472556 -4.7 -3.8 0.48162 0.48162 0.24081 -0.48162 -4.6 -3.8 0.490662 0.490662 0.245331 -0.490662 -4.5 -3.8 0.499674 0.499674 0.249837 -0.499674 -4.4 -3.8 0.508648 0.508648 0.254324 -0.508648 -4.3 -3.8 0.517575 0.517575 0.258788 -0.517575 -4.2 -3.8 0.526449 0.526449 0.263225 -0.526449 -4.1 -3.8 0.535261 0.535261 0.267631 -0.535261 -4 -3.8 0.544003 0.544003 0.272002 -0.544003 -3.9 -3.8 0.552667 0.552667 0.276333 -0.552667 -3.8 -3.8 0.561244 0.561244 0.280622 -0.561244 -3.7 -3.8 0.569726 0.569726 0.284863 -0.569726 -3.6 -3.8 0.578105 0.578105 0.289052 -0.578105 -3.5 -3.8 0.586373 0.586373 0.293186 -0.586373 -3.4 -3.8 0.594521 0.594521 0.29726 -0.594521 -3.3 -3.8 0.602541 0.602541 0.30127 -0.602541 -3.2 -3.8 0.610425 0.610425 0.305212 -0.610425 -3.1 -3.8 0.618165 0.618165 0.309082 -0.618165 -3 -3.8 0.625753 0.625753 0.312876 -0.625753 -2.9 -3.8 0.63318 0.63318 0.31659 -0.63318 -2.8 -3.8 0.64044 0.64044 0.32022 -0.64044 -2.7 -3.8 0.647524 0.647524 0.323762 -0.647524 -2.6 -3.8 0.654424 0.654424 0.327212 -0.654424 -2.5 -3.8 0.661133 0.661133 0.330567 -0.661133 -2.4 -3.8 0.667644 0.667644 0.333822 -0.667644 -2.3 -3.8 0.67395 0.67395 0.336975 -0.67395 -2.2 -3.8 0.680042 0.680042 0.340021 -0.680042 -2.1 -3.8 0.685916 0.685916 0.342958 -0.685916 -2 -3.8 0.691564 0.691564 0.345782 -0.691564 -1.9 -3.8 0.696979 0.696979 0.348489 -0.696979 -1.8 -3.8 0.702156 0.702156 0.351078 -0.702156 -1.7 -3.8 0.707088 0.707088 0.353544 -0.707088 -1.6 -3.8 0.71177 0.71177 0.355885 -0.71177 -1.5 -3.8 0.716197 0.716197 0.358099 -0.716197 -1.4 -3.8 0.720363 0.720363 0.360182 -0.720363 -1.3 -3.8 0.724264 0.724264 0.362132 -0.724264 -1.2 -3.8 0.727894 0.727894 0.363947 -0.727894 -1.1 -3.8 0.73125 0.73125 0.365625 -0.73125 -1 -3.8 0.734328 0.734328 0.367164 -0.734328 -0.9 -3.8 0.737123 0.737123 0.368562 -0.737123 -0.8 -3.8 0.739634 0.739634 0.369817 -0.739634 -0.7 -3.8 0.741856 0.741856 0.370928 -0.741856 -0.6 -3.8 0.743787 0.743787 0.371894 -0.743787 -0.5 -3.8 0.745426 0.745426 0.372713 -0.745426 -0.4 -3.8 0.746769 0.746769 0.373384 -0.746769 -0.3 -3.8 0.747815 0.747815 0.373907 -0.747815 -0.2 -3.8 0.748563 0.748563 0.374281 -0.748563 -0.1 -3.8 0.749012 0.749012 0.374506 -0.749012 0 -3.8 0.749162 0.749162 0.374581 -0.749162 0.1 -3.8 0.749012 0.749012 0.374506 -0.749012 0.2 -3.8 0.748563 0.748563 0.374281 -0.748563 0.3 -3.8 0.747815 0.747815 0.373907 -0.747815 0.4 -3.8 0.746769 0.746769 0.373384 -0.746769 0.5 -3.8 0.745426 0.745426 0.372713 -0.745426 0.6 -3.8 0.743787 0.743787 0.371894 -0.743787 0.7 -3.8 0.741856 0.741856 0.370928 -0.741856 0.8 -3.8 0.739634 0.739634 0.369817 -0.739634 0.9 -3.8 0.737123 0.737123 0.368562 -0.737123 1 -3.8 0.734328 0.734328 0.367164 -0.734328 1.1 -3.8 0.73125 0.73125 0.365625 -0.73125 1.2 -3.8 0.727894 0.727894 0.363947 -0.727894 1.3 -3.8 0.724264 0.724264 0.362132 -0.724264 1.4 -3.8 0.720363 0.720363 0.360182 -0.720363 1.5 -3.8 0.716197 0.716197 0.358099 -0.716197 1.6 -3.8 0.71177 0.71177 0.355885 -0.71177 1.7 -3.8 0.707088 0.707088 0.353544 -0.707088 1.8 -3.8 0.702156 0.702156 0.351078 -0.702156 1.9 -3.8 0.696979 0.696979 0.348489 -0.696979 2 -3.8 0.691564 0.691564 0.345782 -0.691564 2.1 -3.8 0.685916 0.685916 0.342958 -0.685916 2.2 -3.8 0.680042 0.680042 0.340021 -0.680042 2.3 -3.8 0.67395 0.67395 0.336975 -0.67395 2.4 -3.8 0.667644 0.667644 0.333822 -0.667644 2.5 -3.8 0.661133 0.661133 0.330567 -0.661133 2.6 -3.8 0.654424 0.654424 0.327212 -0.654424 2.7 -3.8 0.647524 0.647524 0.323762 -0.647524 2.8 -3.8 0.64044 0.64044 0.32022 -0.64044 2.9 -3.8 0.63318 0.63318 0.31659 -0.63318 3 -3.8 0.625753 0.625753 0.312876 -0.625753 3.1 -3.8 0.618165 0.618165 0.309082 -0.618165 3.2 -3.8 0.610425 0.610425 0.305212 -0.610425 3.3 -3.8 0.602541 0.602541 0.30127 -0.602541 3.4 -3.8 0.594521 0.594521 0.29726 -0.594521 3.5 -3.8 0.586373 0.586373 0.293186 -0.586373 3.6 -3.8 0.578105 0.578105 0.289052 -0.578105 3.7 -3.8 0.569726 0.569726 0.284863 -0.569726 3.8 -3.8 0.561244 0.561244 0.280622 -0.561244 3.9 -3.8 0.552667 0.552667 0.276333 -0.552667 4 -3.8 0.544003 0.544003 0.272002 -0.544003 4.1 -3.8 0.535261 0.535261 0.267631 -0.535261 4.2 -3.8 0.526449 0.526449 0.263225 -0.526449 4.3 -3.8 0.517575 0.517575 0.258788 -0.517575 4.4 -3.8 0.508648 0.508648 0.254324 -0.508648 4.5 -3.8 0.499674 0.499674 0.249837 -0.499674 4.6 -3.8 0.490662 0.490662 0.245331 -0.490662 4.7 -3.8 0.48162 0.48162 0.24081 -0.48162 4.8 -3.8 0.472556 0.472556 0.236278 -0.472556 4.9 -3.8 0.463476 0.463476 0.231738 -0.463476 -5 -3.7 0.461257 0.461257 0.230628 -0.461257 -4.9 -3.7 0.470481 0.470481 0.23524 -0.470481 -4.8 -3.7 0.479697 0.479697 0.239849 -0.479697 -4.7 -3.7 0.488899 0.488899 0.244449 -0.488899 -4.6 -3.7 0.498077 0.498077 0.249039 -0.498077 -4.5 -3.7 0.507225 0.507225 0.253613 -0.507225 -4.4 -3.7 0.516335 0.516335 0.258167 -0.516335 -4.3 -3.7 0.525398 0.525398 0.262699 -0.525398 -4.2 -3.7 0.534406 0.534406 0.267203 -0.534406 -4.1 -3.7 0.543351 0.543351 0.271675 -0.543351 -4 -3.7 0.552225 0.552225 0.276112 -0.552225 -3.9 -3.7 0.561019 0.561019 0.28051 -0.561019 -3.8 -3.7 0.569726 0.569726 0.284863 -0.569726 -3.7 -3.7 0.578336 0.578336 0.289168 -0.578336 -3.6 -3.7 0.586842 0.586842 0.293421 -0.586842 -3.5 -3.7 0.595234 0.595234 0.297617 -0.595234 -3.4 -3.7 0.603506 0.603506 0.301753 -0.603506 -3.3 -3.7 0.611647 0.611647 0.305823 -0.611647 -3.2 -3.7 0.61965 0.61965 0.309825 -0.61965 -3.1 -3.7 0.627507 0.627507 0.313754 -0.627507 -3 -3.7 0.63521 0.63521 0.317605 -0.63521 -2.9 -3.7 0.64275 0.64275 0.321375 -0.64275 -2.8 -3.7 0.650119 0.650119 0.325059 -0.650119 -2.7 -3.7 0.65731 0.65731 0.328655 -0.65731 -2.6 -3.7 0.664314 0.664314 0.332157 -0.664314 -2.5 -3.7 0.671125 0.671125 0.335562 -0.671125 -2.4 -3.7 0.677734 0.677734 0.338867 -0.677734 -2.3 -3.7 0.684135 0.684135 0.342068 -0.684135 -2.2 -3.7 0.69032 0.69032 0.34516 -0.69032 -2.1 -3.7 0.696282 0.696282 0.348141 -0.696282 -2 -3.7 0.702015 0.702015 0.351008 -0.702015 -1.9 -3.7 0.707512 0.707512 0.353756 -0.707512 -1.8 -3.7 0.712767 0.712767 0.356384 -0.712767 -1.7 -3.7 0.717774 0.717774 0.358887 -0.717774 -1.6 -3.7 0.722527 0.722527 0.361264 -0.722527 -1.5 -3.7 0.727021 0.727021 0.36351 -0.727021 -1.4 -3.7 0.73125 0.73125 0.365625 -0.73125 -1.3 -3.7 0.735209 0.735209 0.367605 -0.735209 -1.2 -3.7 0.738895 0.738895 0.369447 -0.738895 -1.1 -3.7 0.742301 0.742301 0.371151 -0.742301 -1 -3.7 0.745426 0.745426 0.372713 -0.745426 -0.9 -3.7 0.748264 0.748264 0.374132 -0.748264 -0.8 -3.7 0.750812 0.750812 0.375406 -0.750812 -0.7 -3.7 0.753068 0.753068 0.376534 -0.753068 -0.6 -3.7 0.755028 0.755028 0.377514 -0.755028 -0.5 -3.7 0.756691 0.756691 0.378346 -0.756691 -0.4 -3.7 0.758054 0.758054 0.379027 -0.758054 -0.3 -3.7 0.759117 0.759117 0.379558 -0.759117 -0.2 -3.7 0.759876 0.759876 0.379938 -0.759876 -0.1 -3.7 0.760332 0.760332 0.380166 -0.760332 0 -3.7 0.760484 0.760484 0.380242 -0.760484 0.1 -3.7 0.760332 0.760332 0.380166 -0.760332 0.2 -3.7 0.759876 0.759876 0.379938 -0.759876 0.3 -3.7 0.759117 0.759117 0.379558 -0.759117 0.4 -3.7 0.758054 0.758054 0.379027 -0.758054 0.5 -3.7 0.756691 0.756691 0.378346 -0.756691 0.6 -3.7 0.755028 0.755028 0.377514 -0.755028 0.7 -3.7 0.753068 0.753068 0.376534 -0.753068 0.8 -3.7 0.750812 0.750812 0.375406 -0.750812 0.9 -3.7 0.748264 0.748264 0.374132 -0.748264 1 -3.7 0.745426 0.745426 0.372713 -0.745426 1.1 -3.7 0.742301 0.742301 0.371151 -0.742301 1.2 -3.7 0.738895 0.738895 0.369447 -0.738895 1.3 -3.7 0.735209 0.735209 0.367605 -0.735209 1.4 -3.7 0.73125 0.73125 0.365625 -0.73125 1.5 -3.7 0.727021 0.727021 0.36351 -0.727021 1.6 -3.7 0.722527 0.722527 0.361264 -0.722527 1.7 -3.7 0.717774 0.717774 0.358887 -0.717774 1.8 -3.7 0.712767 0.712767 0.356384 -0.712767 1.9 -3.7 0.707512 0.707512 0.353756 -0.707512 2 -3.7 0.702015 0.702015 0.351008 -0.702015 2.1 -3.7 0.696282 0.696282 0.348141 -0.696282 2.2 -3.7 0.69032 0.69032 0.34516 -0.69032 2.3 -3.7 0.684135 0.684135 0.342068 -0.684135 2.4 -3.7 0.677734 0.677734 0.338867 -0.677734 2.5 -3.7 0.671125 0.671125 0.335562 -0.671125 2.6 -3.7 0.664314 0.664314 0.332157 -0.664314 2.7 -3.7 0.65731 0.65731 0.328655 -0.65731 2.8 -3.7 0.650119 0.650119 0.325059 -0.650119 2.9 -3.7 0.64275 0.64275 0.321375 -0.64275 3 -3.7 0.63521 0.63521 0.317605 -0.63521 3.1 -3.7 0.627507 0.627507 0.313754 -0.627507 3.2 -3.7 0.61965 0.61965 0.309825 -0.61965 3.3 -3.7 0.611647 0.611647 0.305823 -0.611647 3.4 -3.7 0.603506 0.603506 0.301753 -0.603506 3.5 -3.7 0.595234 0.595234 0.297617 -0.595234 3.6 -3.7 0.586842 0.586842 0.293421 -0.586842 3.7 -3.7 0.578336 0.578336 0.289168 -0.578336 3.8 -3.7 0.569726 0.569726 0.284863 -0.569726 3.9 -3.7 0.561019 0.561019 0.28051 -0.561019 4 -3.7 0.552225 0.552225 0.276112 -0.552225 4.1 -3.7 0.543351 0.543351 0.271675 -0.543351 4.2 -3.7 0.534406 0.534406 0.267203 -0.534406 4.3 -3.7 0.525398 0.525398 0.262699 -0.525398 4.4 -3.7 0.516335 0.516335 0.258167 -0.516335 4.5 -3.7 0.507225 0.507225 0.253613 -0.507225 4.6 -3.7 0.498077 0.498077 0.249039 -0.498077 4.7 -3.7 0.488899 0.488899 0.244449 -0.488899 4.8 -3.7 0.479697 0.479697 0.239849 -0.479697 4.9 -3.7 0.470481 0.470481 0.23524 -0.470481 -5 -3.6 0.468041 0.468041 0.23402 -0.468041 -4.9 -3.6 0.4774 0.4774 0.2387 -0.4774 -4.8 -3.6 0.486752 0.486752 0.243376 -0.486752 -4.7 -3.6 0.496089 0.496089 0.248044 -0.496089 -4.6 -3.6 0.505403 0.505403 0.252701 -0.505403 -4.5 -3.6 0.514685 0.514685 0.257343 -0.514685 -4.4 -3.6 0.523929 0.523929 0.261964 -0.523929 -4.3 -3.6 0.533125 0.533125 0.266562 -0.533125 -4.2 -3.6 0.542265 0.542265 0.271133 -0.542265 -4.1 -3.6 0.551342 0.551342 0.275671 -0.551342 -4 -3.6 0.560346 0.560346 0.280173 -0.560346 -3.9 -3.6 0.56927 0.56927 0.284635 -0.56927 -3.8 -3.6 0.578105 0.578105 0.289052 -0.578105 -3.7 -3.6 0.586842 0.586842 0.293421 -0.586842 -3.6 -3.6 0.595473 0.595473 0.297736 -0.595473 -3.5 -3.6 0.603989 0.603989 0.301994 -0.603989 -3.4 -3.6 0.612381 0.612381 0.306191 -0.612381 -3.3 -3.6 0.620643 0.620643 0.310321 -0.620643 -3.2 -3.6 0.628764 0.628764 0.314382 -0.628764 -3.1 -3.6 0.636736 0.636736 0.318368 -0.636736 -3 -3.6 0.644552 0.644552 0.322276 -0.644552 -2.9 -3.6 0.652203 0.652203 0.326101 -0.652203 -2.8 -3.6 0.65968 0.65968 0.32984 -0.65968 -2.7 -3.6 0.666977 0.666977 0.333488 -0.666977 -2.6 -3.6 0.674084 0.674084 0.337042 -0.674084 -2.5 -3.6 0.680995 0.680995 0.340498 -0.680995 -2.4 -3.6 0.687702 0.687702 0.343851 -0.687702 -2.3 -3.6 0.694197 0.694197 0.347098 -0.694197 -2.2 -3.6 0.700473 0.700473 0.350236 -0.700473 -2.1 -3.6 0.706523 0.706523 0.353261 -0.706523 -2 -3.6 0.71234 0.71234 0.35617 -0.71234 -1.9 -3.6 0.717918 0.717918 0.358959 -0.717918 -1.8 -3.6 0.72325 0.72325 0.361625 -0.72325 -1.7 -3.6 0.728331 0.728331 0.364165 -0.728331 -1.6 -3.6 0.733154 0.733154 0.366577 -0.733154 -1.5 -3.6 0.737713 0.737713 0.368857 -0.737713 -1.4 -3.6 0.742004 0.742004 0.371002 -0.742004 -1.3 -3.6 0.746022 0.746022 0.373011 -0.746022 -1.2 -3.6 0.749762 0.749762 0.374881 -0.749762 -1.1 -3.6 0.753218 0.753218 0.376609 -0.753218 -1 -3.6 0.756389 0.756389 0.378194 -0.756389 -0.9 -3.6 0.759268 0.759268 0.379634 -0.759268 -0.8 -3.6 0.761854 0.761854 0.380927 -0.761854 -0.7 -3.6 0.764143 0.764143 0.382072 -0.764143 -0.6 -3.6 0.766133 0.766133 0.383066 -0.766133 -0.5 -3.6 0.76782 0.76782 0.38391 -0.76782 -0.4 -3.6 0.769203 0.769203 0.384602 -0.769203 -0.3 -3.6 0.770281 0.770281 0.38514 -0.770281 -0.2 -3.6 0.771052 0.771052 0.385526 -0.771052 -0.1 -3.6 0.771514 0.771514 0.385757 -0.771514 0 -3.6 0.771669 0.771669 0.385834 -0.771669 0.1 -3.6 0.771514 0.771514 0.385757 -0.771514 0.2 -3.6 0.771052 0.771052 0.385526 -0.771052 0.3 -3.6 0.770281 0.770281 0.38514 -0.770281 0.4 -3.6 0.769203 0.769203 0.384602 -0.769203 0.5 -3.6 0.76782 0.76782 0.38391 -0.76782 0.6 -3.6 0.766133 0.766133 0.383066 -0.766133 0.7 -3.6 0.764143 0.764143 0.382072 -0.764143 0.8 -3.6 0.761854 0.761854 0.380927 -0.761854 0.9 -3.6 0.759268 0.759268 0.379634 -0.759268 1 -3.6 0.756389 0.756389 0.378194 -0.756389 1.1 -3.6 0.753218 0.753218 0.376609 -0.753218 1.2 -3.6 0.749762 0.749762 0.374881 -0.749762 1.3 -3.6 0.746022 0.746022 0.373011 -0.746022 1.4 -3.6 0.742004 0.742004 0.371002 -0.742004 1.5 -3.6 0.737713 0.737713 0.368857 -0.737713 1.6 -3.6 0.733154 0.733154 0.366577 -0.733154 1.7 -3.6 0.728331 0.728331 0.364165 -0.728331 1.8 -3.6 0.72325 0.72325 0.361625 -0.72325 1.9 -3.6 0.717918 0.717918 0.358959 -0.717918 2 -3.6 0.71234 0.71234 0.35617 -0.71234 2.1 -3.6 0.706523 0.706523 0.353261 -0.706523 2.2 -3.6 0.700473 0.700473 0.350236 -0.700473 2.3 -3.6 0.694197 0.694197 0.347098 -0.694197 2.4 -3.6 0.687702 0.687702 0.343851 -0.687702 2.5 -3.6 0.680995 0.680995 0.340498 -0.680995 2.6 -3.6 0.674084 0.674084 0.337042 -0.674084 2.7 -3.6 0.666977 0.666977 0.333488 -0.666977 2.8 -3.6 0.65968 0.65968 0.32984 -0.65968 2.9 -3.6 0.652203 0.652203 0.326101 -0.652203 3 -3.6 0.644552 0.644552 0.322276 -0.644552 3.1 -3.6 0.636736 0.636736 0.318368 -0.636736 3.2 -3.6 0.628764 0.628764 0.314382 -0.628764 3.3 -3.6 0.620643 0.620643 0.310321 -0.620643 3.4 -3.6 0.612381 0.612381 0.306191 -0.612381 3.5 -3.6 0.603989 0.603989 0.301994 -0.603989 3.6 -3.6 0.595473 0.595473 0.297736 -0.595473 3.7 -3.6 0.586842 0.586842 0.293421 -0.586842 3.8 -3.6 0.578105 0.578105 0.289052 -0.578105 3.9 -3.6 0.56927 0.56927 0.284635 -0.56927 4 -3.6 0.560346 0.560346 0.280173 -0.560346 4.1 -3.6 0.551342 0.551342 0.275671 -0.551342 4.2 -3.6 0.542265 0.542265 0.271133 -0.542265 4.3 -3.6 0.533125 0.533125 0.266562 -0.533125 4.4 -3.6 0.523929 0.523929 0.261964 -0.523929 4.5 -3.6 0.514685 0.514685 0.257343 -0.514685 4.6 -3.6 0.505403 0.505403 0.252701 -0.505403 4.7 -3.6 0.496089 0.496089 0.248044 -0.496089 4.8 -3.6 0.486752 0.486752 0.243376 -0.486752 4.9 -3.6 0.4774 0.4774 0.2387 -0.4774 -5 -3.5 0.474734 0.474734 0.237367 -0.474734 -4.9 -3.5 0.484228 0.484228 0.242114 -0.484228 -4.8 -3.5 0.493713 0.493713 0.246857 -0.493713 -4.7 -3.5 0.503184 0.503184 0.251592 -0.503184 -4.6 -3.5 0.51263 0.51263 0.256315 -0.51263 -4.5 -3.5 0.522046 0.522046 0.261023 -0.522046 -4.4 -3.5 0.531421 0.531421 0.265711 -0.531421 -4.3 -3.5 0.540749 0.540749 0.270375 -0.540749 -4.2 -3.5 0.55002 0.55002 0.27501 -0.55002 -4.1 -3.5 0.559227 0.559227 0.279613 -0.559227 -4 -3.5 0.56836 0.56836 0.28418 -0.56836 -3.9 -3.5 0.577412 0.577412 0.288706 -0.577412 -3.8 -3.5 0.586373 0.586373 0.293186 -0.586373 -3.7 -3.5 0.595234 0.595234 0.297617 -0.595234 -3.6 -3.5 0.603989 0.603989 0.301994 -0.603989 -3.5 -3.5 0.612626 0.612626 0.306313 -0.612626 -3.4 -3.5 0.621139 0.621139 0.31057 -0.621139 -3.3 -3.5 0.629519 0.629519 0.314759 -0.629519 -3.2 -3.5 0.637756 0.637756 0.318878 -0.637756 -3.1 -3.5 0.645842 0.645842 0.322921 -0.645842 -3 -3.5 0.65377 0.65377 0.326885 -0.65377 -2.9 -3.5 0.66153 0.66153 0.330765 -0.66153 -2.8 -3.5 0.669115 0.669115 0.334557 -0.669115 -2.7 -3.5 0.676515 0.676515 0.338258 -0.676515 -2.6 -3.5 0.683725 0.683725 0.341862 -0.683725 -2.5 -3.5 0.690734 0.690734 0.345367 -0.690734 -2.4 -3.5 0.697537 0.697537 0.348768 -0.697537 -2.3 -3.5 0.704125 0.704125 0.352062 -0.704125 -2.2 -3.5 0.71049 0.71049 0.355245 -0.71049 -2.1 -3.5 0.716627 0.716627 0.358313 -0.716627 -2 -3.5 0.722527 0.722527 0.361264 -0.722527 -1.9 -3.5 0.728185 0.728185 0.364093 -0.728185 -1.8 -3.5 0.733594 0.733594 0.366797 -0.733594 -1.7 -3.5 0.738747 0.738747 0.369373 -0.738747 -1.6 -3.5 0.743639 0.743639 0.371819 -0.743639 -1.5 -3.5 0.748264 0.748264 0.374132 -0.748264 -1.4 -3.5 0.752616 0.752616 0.376308 -0.752616 -1.3 -3.5 0.756691 0.756691 0.378346 -0.756691 -1.2 -3.5 0.760484 0.760484 0.380242 -0.760484 -1.1 -3.5 0.76399 0.76399 0.381995 -0.76399 -1 -3.5 0.767206 0.767206 0.383603 -0.767206 -0.9 -3.5 0.770127 0.770127 0.385063 -0.770127 -0.8 -3.5 0.77275 0.77275 0.386375 -0.77275 -0.7 -3.5 0.775071 0.775071 0.387536 -0.775071 -0.6 -3.5 0.777089 0.777089 0.388545 -0.777089 -0.5 -3.5 0.778801 0.778801 0.3894 -0.778801 -0.4 -3.5 0.780204 0.780204 0.390102 -0.780204 -0.3 -3.5 0.781297 0.781297 0.390648 -0.781297 -0.2 -3.5 0.782079 0.782079 0.391039 -0.782079 -0.1 -3.5 0.782548 0.782548 0.391274 -0.782548 0 -3.5 0.782705 0.782705 0.391352 -0.782705 0.1 -3.5 0.782548 0.782548 0.391274 -0.782548 0.2 -3.5 0.782079 0.782079 0.391039 -0.782079 0.3 -3.5 0.781297 0.781297 0.390648 -0.781297 0.4 -3.5 0.780204 0.780204 0.390102 -0.780204 0.5 -3.5 0.778801 0.778801 0.3894 -0.778801 0.6 -3.5 0.777089 0.777089 0.388545 -0.777089 0.7 -3.5 0.775071 0.775071 0.387536 -0.775071 0.8 -3.5 0.77275 0.77275 0.386375 -0.77275 0.9 -3.5 0.770127 0.770127 0.385063 -0.770127 1 -3.5 0.767206 0.767206 0.383603 -0.767206 1.1 -3.5 0.76399 0.76399 0.381995 -0.76399 1.2 -3.5 0.760484 0.760484 0.380242 -0.760484 1.3 -3.5 0.756691 0.756691 0.378346 -0.756691 1.4 -3.5 0.752616 0.752616 0.376308 -0.752616 1.5 -3.5 0.748264 0.748264 0.374132 -0.748264 1.6 -3.5 0.743639 0.743639 0.371819 -0.743639 1.7 -3.5 0.738747 0.738747 0.369373 -0.738747 1.8 -3.5 0.733594 0.733594 0.366797 -0.733594 1.9 -3.5 0.728185 0.728185 0.364093 -0.728185 2 -3.5 0.722527 0.722527 0.361264 -0.722527 2.1 -3.5 0.716627 0.716627 0.358313 -0.716627 2.2 -3.5 0.71049 0.71049 0.355245 -0.71049 2.3 -3.5 0.704125 0.704125 0.352062 -0.704125 2.4 -3.5 0.697537 0.697537 0.348768 -0.697537 2.5 -3.5 0.690734 0.690734 0.345367 -0.690734 2.6 -3.5 0.683725 0.683725 0.341862 -0.683725 2.7 -3.5 0.676515 0.676515 0.338258 -0.676515 2.8 -3.5 0.669115 0.669115 0.334557 -0.669115 2.9 -3.5 0.66153 0.66153 0.330765 -0.66153 3 -3.5 0.65377 0.65377 0.326885 -0.65377 3.1 -3.5 0.645842 0.645842 0.322921 -0.645842 3.2 -3.5 0.637756 0.637756 0.318878 -0.637756 3.3 -3.5 0.629519 0.629519 0.314759 -0.629519 3.4 -3.5 0.621139 0.621139 0.31057 -0.621139 3.5 -3.5 0.612626 0.612626 0.306313 -0.612626 3.6 -3.5 0.603989 0.603989 0.301994 -0.603989 3.7 -3.5 0.595234 0.595234 0.297617 -0.595234 3.8 -3.5 0.586373 0.586373 0.293186 -0.586373 3.9 -3.5 0.577412 0.577412 0.288706 -0.577412 4 -3.5 0.56836 0.56836 0.28418 -0.56836 4.1 -3.5 0.559227 0.559227 0.279613 -0.559227 4.2 -3.5 0.55002 0.55002 0.27501 -0.55002 4.3 -3.5 0.540749 0.540749 0.270375 -0.540749 4.4 -3.5 0.531421 0.531421 0.265711 -0.531421 4.5 -3.5 0.522046 0.522046 0.261023 -0.522046 4.6 -3.5 0.51263 0.51263 0.256315 -0.51263 4.7 -3.5 0.503184 0.503184 0.251592 -0.503184 4.8 -3.5 0.493713 0.493713 0.246857 -0.493713 4.9 -3.5 0.484228 0.484228 0.242114 -0.484228 -5 -3.4 0.481331 0.481331 0.240666 -0.481331 -4.9 -3.4 0.490956 0.490956 0.245478 -0.490956 -4.8 -3.4 0.500574 0.500574 0.250287 -0.500574 -4.7 -3.4 0.510176 0.510176 0.255088 -0.510176 -4.6 -3.4 0.519754 0.519754 0.259877 -0.519754 -4.5 -3.4 0.5293 0.5293 0.26465 -0.5293 -4.4 -3.4 0.538806 0.538806 0.269403 -0.538806 -4.3 -3.4 0.548263 0.548263 0.274132 -0.548263 -4.2 -3.4 0.557663 0.557663 0.278832 -0.557663 -4.1 -3.4 0.566998 0.566998 0.283499 -0.566998 -4 -3.4 0.576258 0.576258 0.288129 -0.576258 -3.9 -3.4 0.585435 0.585435 0.292718 -0.585435 -3.8 -3.4 0.594521 0.594521 0.29726 -0.594521 -3.7 -3.4 0.603506 0.603506 0.301753 -0.603506 -3.6 -3.4 0.612381 0.612381 0.306191 -0.612381 -3.5 -3.4 0.621139 0.621139 0.31057 -0.621139 -3.4 -3.4 0.62977 0.62977 0.314885 -0.62977 -3.3 -3.4 0.638266 0.638266 0.319133 -0.638266 -3.2 -3.4 0.646618 0.646618 0.323309 -0.646618 -3.1 -3.4 0.654817 0.654817 0.327408 -0.654817 -3 -3.4 0.662854 0.662854 0.331427 -0.662854 -2.9 -3.4 0.670722 0.670722 0.335361 -0.670722 -2.8 -3.4 0.678412 0.678412 0.339206 -0.678412 -2.7 -3.4 0.685916 0.685916 0.342958 -0.685916 -2.6 -3.4 0.693225 0.693225 0.346613 -0.693225 -2.5 -3.4 0.700333 0.700333 0.350166 -0.700333 -2.4 -3.4 0.70723 0.70723 0.353615 -0.70723 -2.3 -3.4 0.713909 0.713909 0.356954 -0.713909 -2.2 -3.4 0.720363 0.720363 0.360182 -0.720363 -2.1 -3.4 0.726585 0.726585 0.363292 -0.726585 -2 -3.4 0.732567 0.732567 0.366284 -0.732567 -1.9 -3.4 0.738304 0.738304 0.369152 -0.738304 -1.8 -3.4 0.743787 0.743787 0.371894 -0.743787 -1.7 -3.4 0.749012 0.749012 0.374506 -0.749012 -1.6 -3.4 0.753972 0.753972 0.376986 -0.753972 -1.5 -3.4 0.758661 0.758661 0.379331 -0.758661 -1.4 -3.4 0.763074 0.763074 0.381537 -0.763074 -1.3 -3.4 0.767206 0.767206 0.383603 -0.767206 -1.2 -3.4 0.771052 0.771052 0.385526 -0.771052 -1.1 -3.4 0.774607 0.774607 0.387303 -0.774607 -1 -3.4 0.777867 0.777867 0.388933 -0.777867 -0.9 -3.4 0.780828 0.780828 0.390414 -0.780828 -0.8 -3.4 0.783488 0.783488 0.391744 -0.783488 -0.7 -3.4 0.785842 0.785842 0.392921 -0.785842 -0.6 -3.4 0.787887 0.787887 0.393944 -0.787887 -0.5 -3.4 0.789623 0.789623 0.394811 -0.789623 -0.4 -3.4 0.791045 0.791045 0.395523 -0.791045 -0.3 -3.4 0.792154 0.792154 0.396077 -0.792154 -0.2 -3.4 0.792946 0.792946 0.396473 -0.792946 -0.1 -3.4 0.793422 0.793422 0.396711 -0.793422 0 -3.4 0.793581 0.793581 0.39679 -0.793581 0.1 -3.4 0.793422 0.793422 0.396711 -0.793422 0.2 -3.4 0.792946 0.792946 0.396473 -0.792946 0.3 -3.4 0.792154 0.792154 0.396077 -0.792154 0.4 -3.4 0.791045 0.791045 0.395523 -0.791045 0.5 -3.4 0.789623 0.789623 0.394811 -0.789623 0.6 -3.4 0.787887 0.787887 0.393944 -0.787887 0.7 -3.4 0.785842 0.785842 0.392921 -0.785842 0.8 -3.4 0.783488 0.783488 0.391744 -0.783488 0.9 -3.4 0.780828 0.780828 0.390414 -0.780828 1 -3.4 0.777867 0.777867 0.388933 -0.777867 1.1 -3.4 0.774607 0.774607 0.387303 -0.774607 1.2 -3.4 0.771052 0.771052 0.385526 -0.771052 1.3 -3.4 0.767206 0.767206 0.383603 -0.767206 1.4 -3.4 0.763074 0.763074 0.381537 -0.763074 1.5 -3.4 0.758661 0.758661 0.379331 -0.758661 1.6 -3.4 0.753972 0.753972 0.376986 -0.753972 1.7 -3.4 0.749012 0.749012 0.374506 -0.749012 1.8 -3.4 0.743787 0.743787 0.371894 -0.743787 1.9 -3.4 0.738304 0.738304 0.369152 -0.738304 2 -3.4 0.732567 0.732567 0.366284 -0.732567 2.1 -3.4 0.726585 0.726585 0.363292 -0.726585 2.2 -3.4 0.720363 0.720363 0.360182 -0.720363 2.3 -3.4 0.713909 0.713909 0.356954 -0.713909 2.4 -3.4 0.70723 0.70723 0.353615 -0.70723 2.5 -3.4 0.700333 0.700333 0.350166 -0.700333 2.6 -3.4 0.693225 0.693225 0.346613 -0.693225 2.7 -3.4 0.685916 0.685916 0.342958 -0.685916 2.8 -3.4 0.678412 0.678412 0.339206 -0.678412 2.9 -3.4 0.670722 0.670722 0.335361 -0.670722 3 -3.4 0.662854 0.662854 0.331427 -0.662854 3.1 -3.4 0.654817 0.654817 0.327408 -0.654817 3.2 -3.4 0.646618 0.646618 0.323309 -0.646618 3.3 -3.4 0.638266 0.638266 0.319133 -0.638266 3.4 -3.4 0.62977 0.62977 0.314885 -0.62977 3.5 -3.4 0.621139 0.621139 0.31057 -0.621139 3.6 -3.4 0.612381 0.612381 0.306191 -0.612381 3.7 -3.4 0.603506 0.603506 0.301753 -0.603506 3.8 -3.4 0.594521 0.594521 0.29726 -0.594521 3.9 -3.4 0.585435 0.585435 0.292718 -0.585435 4 -3.4 0.576258 0.576258 0.288129 -0.576258 4.1 -3.4 0.566998 0.566998 0.283499 -0.566998 4.2 -3.4 0.557663 0.557663 0.278832 -0.557663 4.3 -3.4 0.548263 0.548263 0.274132 -0.548263 4.4 -3.4 0.538806 0.538806 0.269403 -0.538806 4.5 -3.4 0.5293 0.5293 0.26465 -0.5293 4.6 -3.4 0.519754 0.519754 0.259877 -0.519754 4.7 -3.4 0.510176 0.510176 0.255088 -0.510176 4.8 -3.4 0.500574 0.500574 0.250287 -0.500574 4.9 -3.4 0.490956 0.490956 0.245478 -0.490956 -5 -3.3 0.487824 0.487824 0.243912 -0.487824 -4.9 -3.3 0.497579 0.497579 0.24879 -0.497579 -4.8 -3.3 0.507327 0.507327 0.253663 -0.507327 -4.7 -3.3 0.517058 0.517058 0.258529 -0.517058 -4.6 -3.3 0.526765 0.526765 0.263383 -0.526765 -4.5 -3.3 0.53644 0.53644 0.26822 -0.53644 -4.4 -3.3 0.546074 0.546074 0.273037 -0.546074 -4.3 -3.3 0.555659 0.555659 0.27783 -0.555659 -4.2 -3.3 0.565186 0.565186 0.282593 -0.565186 -4.1 -3.3 0.574647 0.574647 0.287323 -0.574647 -4 -3.3 0.584032 0.584032 0.292016 -0.584032 -3.9 -3.3 0.593333 0.593333 0.296666 -0.593333 -3.8 -3.3 0.602541 0.602541 0.30127 -0.602541 -3.7 -3.3 0.611647 0.611647 0.305823 -0.611647 -3.6 -3.3 0.620643 0.620643 0.310321 -0.620643 -3.5 -3.3 0.629519 0.629519 0.314759 -0.629519 -3.4 -3.3 0.638266 0.638266 0.319133 -0.638266 -3.3 -3.3 0.646876 0.646876 0.323438 -0.646876 -3.2 -3.3 0.655341 0.655341 0.32767 -0.655341 -3.1 -3.3 0.66365 0.66365 0.331825 -0.66365 -3 -3.3 0.671796 0.671796 0.335898 -0.671796 -2.9 -3.3 0.679771 0.679771 0.339885 -0.679771 -2.8 -3.3 0.687564 0.687564 0.343782 -0.687564 -2.7 -3.3 0.695169 0.695169 0.347585 -0.695169 -2.6 -3.3 0.702577 0.702577 0.351289 -0.702577 -2.5 -3.3 0.70978 0.70978 0.35489 -0.70978 -2.4 -3.3 0.71677 0.71677 0.358385 -0.71677 -2.3 -3.3 0.72354 0.72354 0.36177 -0.72354 -2.2 -3.3 0.730081 0.730081 0.36504 -0.730081 -2.1 -3.3 0.736387 0.736387 0.368193 -0.736387 -2 -3.3 0.74245 0.74245 0.371225 -0.74245 -1.9 -3.3 0.748264 0.748264 0.374132 -0.748264 -1.8 -3.3 0.753821 0.753821 0.376911 -0.753821 -1.7 -3.3 0.759117 0.759117 0.379558 -0.759117 -1.6 -3.3 0.764143 0.764143 0.382072 -0.764143 -1.5 -3.3 0.768896 0.768896 0.384448 -0.768896 -1.4 -3.3 0.773368 0.773368 0.386684 -0.773368 -1.3 -3.3 0.777556 0.777556 0.388778 -0.777556 -1.2 -3.3 0.781453 0.781453 0.390727 -0.781453 -1.1 -3.3 0.785056 0.785056 0.392528 -0.785056 -1 -3.3 0.78836 0.78836 0.39418 -0.78836 -0.9 -3.3 0.791362 0.791362 0.395681 -0.791362 -0.8 -3.3 0.794057 0.794057 0.397029 -0.794057 -0.7 -3.3 0.796443 0.796443 0.398221 -0.796443 -0.6 -3.3 0.798516 0.798516 0.399258 -0.798516 -0.5 -3.3 0.800275 0.800275 0.400137 -0.800275 -0.4 -3.3 0.801717 0.801717 0.400858 -0.801717 -0.3 -3.3 0.80284 0.80284 0.40142 -0.80284 -0.2 -3.3 0.803643 0.803643 0.401822 -0.803643 -0.1 -3.3 0.804125 0.804125 0.402063 -0.804125 0 -3.3 0.804286 0.804286 0.402143 -0.804286 0.1 -3.3 0.804125 0.804125 0.402063 -0.804125 0.2 -3.3 0.803643 0.803643 0.401822 -0.803643 0.3 -3.3 0.80284 0.80284 0.40142 -0.80284 0.4 -3.3 0.801717 0.801717 0.400858 -0.801717 0.5 -3.3 0.800275 0.800275 0.400137 -0.800275 0.6 -3.3 0.798516 0.798516 0.399258 -0.798516 0.7 -3.3 0.796443 0.796443 0.398221 -0.796443 0.8 -3.3 0.794057 0.794057 0.397029 -0.794057 0.9 -3.3 0.791362 0.791362 0.395681 -0.791362 1 -3.3 0.78836 0.78836 0.39418 -0.78836 1.1 -3.3 0.785056 0.785056 0.392528 -0.785056 1.2 -3.3 0.781453 0.781453 0.390727 -0.781453 1.3 -3.3 0.777556 0.777556 0.388778 -0.777556 1.4 -3.3 0.773368 0.773368 0.386684 -0.773368 1.5 -3.3 0.768896 0.768896 0.384448 -0.768896 1.6 -3.3 0.764143 0.764143 0.382072 -0.764143 1.7 -3.3 0.759117 0.759117 0.379558 -0.759117 1.8 -3.3 0.753821 0.753821 0.376911 -0.753821 1.9 -3.3 0.748264 0.748264 0.374132 -0.748264 2 -3.3 0.74245 0.74245 0.371225 -0.74245 2.1 -3.3 0.736387 0.736387 0.368193 -0.736387 2.2 -3.3 0.730081 0.730081 0.36504 -0.730081 2.3 -3.3 0.72354 0.72354 0.36177 -0.72354 2.4 -3.3 0.71677 0.71677 0.358385 -0.71677 2.5 -3.3 0.70978 0.70978 0.35489 -0.70978 2.6 -3.3 0.702577 0.702577 0.351289 -0.702577 2.7 -3.3 0.695169 0.695169 0.347585 -0.695169 2.8 -3.3 0.687564 0.687564 0.343782 -0.687564 2.9 -3.3 0.679771 0.679771 0.339885 -0.679771 3 -3.3 0.671796 0.671796 0.335898 -0.671796 3.1 -3.3 0.66365 0.66365 0.331825 -0.66365 3.2 -3.3 0.655341 0.655341 0.32767 -0.655341 3.3 -3.3 0.646876 0.646876 0.323438 -0.646876 3.4 -3.3 0.638266 0.638266 0.319133 -0.638266 3.5 -3.3 0.629519 0.629519 0.314759 -0.629519 3.6 -3.3 0.620643 0.620643 0.310321 -0.620643 3.7 -3.3 0.611647 0.611647 0.305823 -0.611647 3.8 -3.3 0.602541 0.602541 0.30127 -0.602541 3.9 -3.3 0.593333 0.593333 0.296666 -0.593333 4 -3.3 0.584032 0.584032 0.292016 -0.584032 4.1 -3.3 0.574647 0.574647 0.287323 -0.574647 4.2 -3.3 0.565186 0.565186 0.282593 -0.565186 4.3 -3.3 0.555659 0.555659 0.27783 -0.555659 4.4 -3.3 0.546074 0.546074 0.273037 -0.546074 4.5 -3.3 0.53644 0.53644 0.26822 -0.53644 4.6 -3.3 0.526765 0.526765 0.263383 -0.526765 4.7 -3.3 0.517058 0.517058 0.258529 -0.517058 4.8 -3.3 0.507327 0.507327 0.253663 -0.507327 4.9 -3.3 0.497579 0.497579 0.24879 -0.497579 -5 -3.2 0.494207 0.494207 0.247104 -0.494207 -4.9 -3.2 0.50409 0.50409 0.252045 -0.50409 -4.8 -3.2 0.513965 0.513965 0.256983 -0.513965 -4.7 -3.2 0.523824 0.523824 0.261912 -0.523824 -4.6 -3.2 0.533658 0.533658 0.266829 -0.533658 -4.5 -3.2 0.54346 0.54346 0.27173 -0.54346 -4.4 -3.2 0.55322 0.55322 0.27661 -0.55322 -4.3 -3.2 0.56293 0.56293 0.281465 -0.56293 -4.2 -3.2 0.572582 0.572582 0.286291 -0.572582 -4.1 -3.2 0.582166 0.582166 0.291083 -0.582166 -4 -3.2 0.591674 0.591674 0.295837 -0.591674 -3.9 -3.2 0.601096 0.601096 0.300548 -0.601096 -3.8 -3.2 0.610425 0.610425 0.305212 -0.610425 -3.7 -3.2 0.61965 0.61965 0.309825 -0.61965 -3.6 -3.2 0.628764 0.628764 0.314382 -0.628764 -3.5 -3.2 0.637756 0.637756 0.318878 -0.637756 -3.4 -3.2 0.646618 0.646618 0.323309 -0.646618 -3.3 -3.2 0.655341 0.655341 0.32767 -0.655341 -3.2 -3.2 0.663916 0.663916 0.331958 -0.663916 -3.1 -3.2 0.672334 0.672334 0.336167 -0.672334 -3 -3.2 0.680587 0.680587 0.340293 -0.680587 -2.9 -3.2 0.688665 0.688665 0.344333 -0.688665 -2.8 -3.2 0.696561 0.696561 0.34828 -0.696561 -2.7 -3.2 0.704265 0.704265 0.352133 -0.704265 -2.6 -3.2 0.71177 0.71177 0.355885 -0.71177 -2.5 -3.2 0.719068 0.719068 0.359534 -0.719068 -2.4 -3.2 0.726149 0.726149 0.363075 -0.726149 -2.3 -3.2 0.733007 0.733007 0.366504 -0.733007 -2.2 -3.2 0.739634 0.739634 0.369817 -0.739634 -2.1 -3.2 0.746022 0.746022 0.373011 -0.746022 -2 -3.2 0.752165 0.752165 0.376082 -0.752165 -1.9 -3.2 0.758054 0.758054 0.379027 -0.758054 -1.8 -3.2 0.763685 0.763685 0.381842 -0.763685 -1.7 -3.2 0.769049 0.769049 0.384525 -0.769049 -1.6 -3.2 0.774142 0.774142 0.387071 -0.774142 -1.5 -3.2 0.778957 0.778957 0.389478 -0.778957 -1.4 -3.2 0.783488 0.783488 0.391744 -0.783488 -1.3 -3.2 0.78773 0.78773 0.393865 -0.78773 -1.2 -3.2 0.791678 0.791678 0.395839 -0.791678 -1.1 -3.2 0.795329 0.795329 0.397664 -0.795329 -1 -3.2 0.798676 0.798676 0.399338 -0.798676 -0.9 -3.2 0.801717 0.801717 0.400858 -0.801717 -0.8 -3.2 0.804447 0.804447 0.402224 -0.804447 -0.7 -3.2 0.806864 0.806864 0.403432 -0.806864 -0.6 -3.2 0.808965 0.808965 0.404482 -0.808965 -0.5 -3.2 0.810746 0.810746 0.405373 -0.810746 -0.4 -3.2 0.812207 0.812207 0.406104 -0.812207 -0.3 -3.2 0.813345 0.813345 0.406672 -0.813345 -0.2 -3.2 0.814159 0.814159 0.407079 -0.814159 -0.1 -3.2 0.814647 0.814647 0.407324 -0.814647 0 -3.2 0.81481 0.81481 0.407405 -0.81481 0.1 -3.2 0.814647 0.814647 0.407324 -0.814647 0.2 -3.2 0.814159 0.814159 0.407079 -0.814159 0.3 -3.2 0.813345 0.813345 0.406672 -0.813345 0.4 -3.2 0.812207 0.812207 0.406104 -0.812207 0.5 -3.2 0.810746 0.810746 0.405373 -0.810746 0.6 -3.2 0.808965 0.808965 0.404482 -0.808965 0.7 -3.2 0.806864 0.806864 0.403432 -0.806864 0.8 -3.2 0.804447 0.804447 0.402224 -0.804447 0.9 -3.2 0.801717 0.801717 0.400858 -0.801717 1 -3.2 0.798676 0.798676 0.399338 -0.798676 1.1 -3.2 0.795329 0.795329 0.397664 -0.795329 1.2 -3.2 0.791678 0.791678 0.395839 -0.791678 1.3 -3.2 0.78773 0.78773 0.393865 -0.78773 1.4 -3.2 0.783488 0.783488 0.391744 -0.783488 1.5 -3.2 0.778957 0.778957 0.389478 -0.778957 1.6 -3.2 0.774142 0.774142 0.387071 -0.774142 1.7 -3.2 0.769049 0.769049 0.384525 -0.769049 1.8 -3.2 0.763685 0.763685 0.381842 -0.763685 1.9 -3.2 0.758054 0.758054 0.379027 -0.758054 2 -3.2 0.752165 0.752165 0.376082 -0.752165 2.1 -3.2 0.746022 0.746022 0.373011 -0.746022 2.2 -3.2 0.739634 0.739634 0.369817 -0.739634 2.3 -3.2 0.733007 0.733007 0.366504 -0.733007 2.4 -3.2 0.726149 0.726149 0.363075 -0.726149 2.5 -3.2 0.719068 0.719068 0.359534 -0.719068 2.6 -3.2 0.71177 0.71177 0.355885 -0.71177 2.7 -3.2 0.704265 0.704265 0.352133 -0.704265 2.8 -3.2 0.696561 0.696561 0.34828 -0.696561 2.9 -3.2 0.688665 0.688665 0.344333 -0.688665 3 -3.2 0.680587 0.680587 0.340293 -0.680587 3.1 -3.2 0.672334 0.672334 0.336167 -0.672334 3.2 -3.2 0.663916 0.663916 0.331958 -0.663916 3.3 -3.2 0.655341 0.655341 0.32767 -0.655341 3.4 -3.2 0.646618 0.646618 0.323309 -0.646618 3.5 -3.2 0.637756 0.637756 0.318878 -0.637756 3.6 -3.2 0.628764 0.628764 0.314382 -0.628764 3.7 -3.2 0.61965 0.61965 0.309825 -0.61965 3.8 -3.2 0.610425 0.610425 0.305212 -0.610425 3.9 -3.2 0.601096 0.601096 0.300548 -0.601096 4 -3.2 0.591674 0.591674 0.295837 -0.591674 4.1 -3.2 0.582166 0.582166 0.291083 -0.582166 4.2 -3.2 0.572582 0.572582 0.286291 -0.572582 4.3 -3.2 0.56293 0.56293 0.281465 -0.56293 4.4 -3.2 0.55322 0.55322 0.27661 -0.55322 4.5 -3.2 0.54346 0.54346 0.27173 -0.54346 4.6 -3.2 0.533658 0.533658 0.266829 -0.533658 4.7 -3.2 0.523824 0.523824 0.261912 -0.523824 4.8 -3.2 0.513965 0.513965 0.256983 -0.513965 4.9 -3.2 0.50409 0.50409 0.252045 -0.50409 -5 -3.1 0.500474 0.500474 0.250237 -0.500474 -4.9 -3.1 0.510482 0.510482 0.255241 -0.510482 -4.8 -3.1 0.520482 0.520482 0.260241 -0.520482 -4.7 -3.1 0.530466 0.530466 0.265233 -0.530466 -4.6 -3.1 0.540425 0.540425 0.270212 -0.540425 -4.5 -3.1 0.55035 0.55035 0.275175 -0.55035 -4.4 -3.1 0.560234 0.560234 0.280117 -0.560234 -4.3 -3.1 0.570068 0.570068 0.285034 -0.570068 -4.2 -3.1 0.579842 0.579842 0.289921 -0.579842 -4.1 -3.1 0.589547 0.589547 0.294774 -0.589547 -4 -3.1 0.599176 0.599176 0.299588 -0.599176 -3.9 -3.1 0.608718 0.608718 0.304359 -0.608718 -3.8 -3.1 0.618165 0.618165 0.309082 -0.618165 -3.7 -3.1 0.627507 0.627507 0.313754 -0.627507 -3.6 -3.1 0.636736 0.636736 0.318368 -0.636736 -3.5 -3.1 0.645842 0.645842 0.322921 -0.645842 -3.4 -3.1 0.654817 0.654817 0.327408 -0.654817 -3.3 -3.1 0.66365 0.66365 0.331825 -0.66365 -3.2 -3.1 0.672334 0.672334 0.336167 -0.672334 -3.1 -3.1 0.680859 0.680859 0.34043 -0.680859 -3 -3.1 0.689216 0.689216 0.344608 -0.689216 -2.9 -3.1 0.697397 0.697397 0.348699 -0.697397 -2.8 -3.1 0.705393 0.705393 0.352697 -0.705393 -2.7 -3.1 0.713195 0.713195 0.356598 -0.713195 -2.6 -3.1 0.720795 0.720795 0.360398 -0.720795 -2.5 -3.1 0.728185 0.728185 0.364093 -0.728185 -2.4 -3.1 0.735356 0.735356 0.367678 -0.735356 -2.3 -3.1 0.742301 0.742301 0.371151 -0.742301 -2.2 -3.1 0.749012 0.749012 0.374506 -0.749012 -2.1 -3.1 0.755481 0.755481 0.377741 -0.755481 -2 -3.1 0.761702 0.761702 0.380851 -0.761702 -1.9 -3.1 0.767666 0.767666 0.383833 -0.767666 -1.8 -3.1 0.773368 0.773368 0.386684 -0.773368 -1.7 -3.1 0.778801 0.778801 0.3894 -0.778801 -1.6 -3.1 0.783958 0.783958 0.391979 -0.783958 -1.5 -3.1 0.788834 0.788834 0.394417 -0.788834 -1.4 -3.1 0.793422 0.793422 0.396711 -0.793422 -1.3 -3.1 0.797718 0.797718 0.398859 -0.797718 -1.2 -3.1 0.801717 0.801717 0.400858 -0.801717 -1.1 -3.1 0.805413 0.805413 0.402707 -0.805413 -1 -3.1 0.808803 0.808803 0.404401 -0.808803 -0.9 -3.1 0.811882 0.811882 0.405941 -0.811882 -0.8 -3.1 0.814647 0.814647 0.407324 -0.814647 -0.7 -3.1 0.817095 0.817095 0.408547 -0.817095 -0.6 -3.1 0.819222 0.819222 0.409611 -0.819222 -0.5 -3.1 0.821026 0.821026 0.410513 -0.821026 -0.4 -3.1 0.822506 0.822506 0.411253 -0.822506 -0.3 -3.1 0.823658 0.823658 0.411829 -0.823658 -0.2 -3.1 0.824482 0.824482 0.412241 -0.824482 -0.1 -3.1 0.824977 0.824977 0.412488 -0.824977 0 -3.1 0.825142 0.825142 0.412571 -0.825142 0.1 -3.1 0.824977 0.824977 0.412488 -0.824977 0.2 -3.1 0.824482 0.824482 0.412241 -0.824482 0.3 -3.1 0.823658 0.823658 0.411829 -0.823658 0.4 -3.1 0.822506 0.822506 0.411253 -0.822506 0.5 -3.1 0.821026 0.821026 0.410513 -0.821026 0.6 -3.1 0.819222 0.819222 0.409611 -0.819222 0.7 -3.1 0.817095 0.817095 0.408547 -0.817095 0.8 -3.1 0.814647 0.814647 0.407324 -0.814647 0.9 -3.1 0.811882 0.811882 0.405941 -0.811882 1 -3.1 0.808803 0.808803 0.404401 -0.808803 1.1 -3.1 0.805413 0.805413 0.402707 -0.805413 1.2 -3.1 0.801717 0.801717 0.400858 -0.801717 1.3 -3.1 0.797718 0.797718 0.398859 -0.797718 1.4 -3.1 0.793422 0.793422 0.396711 -0.793422 1.5 -3.1 0.788834 0.788834 0.394417 -0.788834 1.6 -3.1 0.783958 0.783958 0.391979 -0.783958 1.7 -3.1 0.778801 0.778801 0.3894 -0.778801 1.8 -3.1 0.773368 0.773368 0.386684 -0.773368 1.9 -3.1 0.767666 0.767666 0.383833 -0.767666 2 -3.1 0.761702 0.761702 0.380851 -0.761702 2.1 -3.1 0.755481 0.755481 0.377741 -0.755481 2.2 -3.1 0.749012 0.749012 0.374506 -0.749012 2.3 -3.1 0.742301 0.742301 0.371151 -0.742301 2.4 -3.1 0.735356 0.735356 0.367678 -0.735356 2.5 -3.1 0.728185 0.728185 0.364093 -0.728185 2.6 -3.1 0.720795 0.720795 0.360398 -0.720795 2.7 -3.1 0.713195 0.713195 0.356598 -0.713195 2.8 -3.1 0.705393 0.705393 0.352697 -0.705393 2.9 -3.1 0.697397 0.697397 0.348699 -0.697397 3 -3.1 0.689216 0.689216 0.344608 -0.689216 3.1 -3.1 0.680859 0.680859 0.34043 -0.680859 3.2 -3.1 0.672334 0.672334 0.336167 -0.672334 3.3 -3.1 0.66365 0.66365 0.331825 -0.66365 3.4 -3.1 0.654817 0.654817 0.327408 -0.654817 3.5 -3.1 0.645842 0.645842 0.322921 -0.645842 3.6 -3.1 0.636736 0.636736 0.318368 -0.636736 3.7 -3.1 0.627507 0.627507 0.313754 -0.627507 3.8 -3.1 0.618165 0.618165 0.309082 -0.618165 3.9 -3.1 0.608718 0.608718 0.304359 -0.608718 4 -3.1 0.599176 0.599176 0.299588 -0.599176 4.1 -3.1 0.589547 0.589547 0.294774 -0.589547 4.2 -3.1 0.579842 0.579842 0.289921 -0.579842 4.3 -3.1 0.570068 0.570068 0.285034 -0.570068 4.4 -3.1 0.560234 0.560234 0.280117 -0.560234 4.5 -3.1 0.55035 0.55035 0.275175 -0.55035 4.6 -3.1 0.540425 0.540425 0.270212 -0.540425 4.7 -3.1 0.530466 0.530466 0.265233 -0.530466 4.8 -3.1 0.520482 0.520482 0.260241 -0.520482 4.9 -3.1 0.510482 0.510482 0.255241 -0.510482 -5 -3 0.506617 0.506617 0.253308 -0.506617 -4.9 -3 0.516748 0.516748 0.258374 -0.516748 -4.8 -3 0.526871 0.526871 0.263435 -0.526871 -4.7 -3 0.536977 0.536977 0.268489 -0.536977 -4.6 -3 0.547058 0.547058 0.273529 -0.547058 -4.5 -3 0.557106 0.557106 0.278553 -0.557106 -4.4 -3 0.567111 0.567111 0.283556 -0.567111 -4.3 -3 0.577065 0.577065 0.288533 -0.577065 -4.2 -3 0.586959 0.586959 0.29348 -0.586959 -4.1 -3 0.596784 0.596784 0.298392 -0.596784 -4 -3 0.606531 0.606531 0.303265 -0.606531 -3.9 -3 0.61619 0.61619 0.308095 -0.61619 -3.8 -3 0.625753 0.625753 0.312876 -0.625753 -3.7 -3 0.63521 0.63521 0.317605 -0.63521 -3.6 -3 0.644552 0.644552 0.322276 -0.644552 -3.5 -3 0.65377 0.65377 0.326885 -0.65377 -3.4 -3 0.662854 0.662854 0.331427 -0.662854 -3.3 -3 0.671796 0.671796 0.335898 -0.671796 -3.2 -3 0.680587 0.680587 0.340293 -0.680587 -3.1 -3 0.689216 0.689216 0.344608 -0.689216 -3 -3 0.697676 0.697676 0.348838 -0.697676 -2.9 -3 0.705958 0.705958 0.352979 -0.705958 -2.8 -3 0.714052 0.714052 0.357026 -0.714052 -2.7 -3 0.72195 0.72195 0.360975 -0.72195 -2.6 -3 0.729643 0.729643 0.364821 -0.729643 -2.5 -3 0.737123 0.737123 0.368562 -0.737123 -2.4 -3 0.744383 0.744383 0.372191 -0.744383 -2.3 -3 0.751413 0.751413 0.375706 -0.751413 -2.2 -3 0.758206 0.758206 0.379103 -0.758206 -2.1 -3 0.764755 0.764755 0.382377 -0.764755 -2 -3 0.771052 0.771052 0.385526 -0.771052 -1.9 -3 0.777089 0.777089 0.388545 -0.777089 -1.8 -3 0.782861 0.782861 0.391431 -0.782861 -1.7 -3 0.78836 0.78836 0.39418 -0.78836 -1.6 -3 0.793581 0.793581 0.39679 -0.793581 -1.5 -3 0.798516 0.798516 0.399258 -0.798516 -1.4 -3 0.803161 0.803161 0.401581 -0.803161 -1.3 -3 0.80751 0.80751 0.403755 -0.80751 -1.2 -3 0.811558 0.811558 0.405779 -0.811558 -1.1 -3 0.815299 0.815299 0.40765 -0.815299 -1 -3 0.818731 0.818731 0.409365 -0.818731 -0.9 -3 0.821848 0.821848 0.410924 -0.821848 -0.8 -3 0.824647 0.824647 0.412323 -0.824647 -0.7 -3 0.827125 0.827125 0.413562 -0.827125 -0.6 -3 0.829278 0.829278 0.414639 -0.829278 -0.5 -3 0.831104 0.831104 0.415552 -0.831104 -0.4 -3 0.832602 0.832602 0.416301 -0.832602 -0.3 -3 0.833768 0.833768 0.416884 -0.833768 -0.2 -3 0.834602 0.834602 0.417301 -0.834602 -0.1 -3 0.835103 0.835103 0.417552 -0.835103 0 -3 0.83527 0.83527 0.417635 -0.83527 0.1 -3 0.835103 0.835103 0.417552 -0.835103 0.2 -3 0.834602 0.834602 0.417301 -0.834602 0.3 -3 0.833768 0.833768 0.416884 -0.833768 0.4 -3 0.832602 0.832602 0.416301 -0.832602 0.5 -3 0.831104 0.831104 0.415552 -0.831104 0.6 -3 0.829278 0.829278 0.414639 -0.829278 0.7 -3 0.827125 0.827125 0.413562 -0.827125 0.8 -3 0.824647 0.824647 0.412323 -0.824647 0.9 -3 0.821848 0.821848 0.410924 -0.821848 1 -3 0.818731 0.818731 0.409365 -0.818731 1.1 -3 0.815299 0.815299 0.40765 -0.815299 1.2 -3 0.811558 0.811558 0.405779 -0.811558 1.3 -3 0.80751 0.80751 0.403755 -0.80751 1.4 -3 0.803161 0.803161 0.401581 -0.803161 1.5 -3 0.798516 0.798516 0.399258 -0.798516 1.6 -3 0.793581 0.793581 0.39679 -0.793581 1.7 -3 0.78836 0.78836 0.39418 -0.78836 1.8 -3 0.782861 0.782861 0.391431 -0.782861 1.9 -3 0.777089 0.777089 0.388545 -0.777089 2 -3 0.771052 0.771052 0.385526 -0.771052 2.1 -3 0.764755 0.764755 0.382377 -0.764755 2.2 -3 0.758206 0.758206 0.379103 -0.758206 2.3 -3 0.751413 0.751413 0.375706 -0.751413 2.4 -3 0.744383 0.744383 0.372191 -0.744383 2.5 -3 0.737123 0.737123 0.368562 -0.737123 2.6 -3 0.729643 0.729643 0.364821 -0.729643 2.7 -3 0.72195 0.72195 0.360975 -0.72195 2.8 -3 0.714052 0.714052 0.357026 -0.714052 2.9 -3 0.705958 0.705958 0.352979 -0.705958 3 -3 0.697676 0.697676 0.348838 -0.697676 3.1 -3 0.689216 0.689216 0.344608 -0.689216 3.2 -3 0.680587 0.680587 0.340293 -0.680587 3.3 -3 0.671796 0.671796 0.335898 -0.671796 3.4 -3 0.662854 0.662854 0.331427 -0.662854 3.5 -3 0.65377 0.65377 0.326885 -0.65377 3.6 -3 0.644552 0.644552 0.322276 -0.644552 3.7 -3 0.63521 0.63521 0.317605 -0.63521 3.8 -3 0.625753 0.625753 0.312876 -0.625753 3.9 -3 0.61619 0.61619 0.308095 -0.61619 4 -3 0.606531 0.606531 0.303265 -0.606531 4.1 -3 0.596784 0.596784 0.298392 -0.596784 4.2 -3 0.586959 0.586959 0.29348 -0.586959 4.3 -3 0.577065 0.577065 0.288533 -0.577065 4.4 -3 0.567111 0.567111 0.283556 -0.567111 4.5 -3 0.557106 0.557106 0.278553 -0.557106 4.6 -3 0.547058 0.547058 0.273529 -0.547058 4.7 -3 0.536977 0.536977 0.268489 -0.536977 4.8 -3 0.526871 0.526871 0.263435 -0.526871 4.9 -3 0.516748 0.516748 0.258374 -0.516748 -5 -2.9 0.51263 0.51263 0.256315 -0.51263 -4.9 -2.9 0.522882 0.522882 0.261441 -0.522882 -4.8 -2.9 0.533125 0.533125 0.266562 -0.533125 -4.7 -2.9 0.543351 0.543351 0.271675 -0.543351 -4.6 -2.9 0.553552 0.553552 0.276776 -0.553552 -4.5 -2.9 0.563719 0.563719 0.281859 -0.563719 -4.4 -2.9 0.573843 0.573843 0.286921 -0.573843 -4.3 -2.9 0.583915 0.583915 0.291957 -0.583915 -4.2 -2.9 0.593926 0.593926 0.296963 -0.593926 -4.1 -2.9 0.603868 0.603868 0.301934 -0.603868 -4 -2.9 0.61373 0.61373 0.306865 -0.61373 -3.9 -2.9 0.623504 0.623504 0.311752 -0.623504 -3.8 -2.9 0.63318 0.63318 0.31659 -0.63318 -3.7 -2.9 0.64275 0.64275 0.321375 -0.64275 -3.6 -2.9 0.652203 0.652203 0.326101 -0.652203 -3.5 -2.9 0.66153 0.66153 0.330765 -0.66153 -3.4 -2.9 0.670722 0.670722 0.335361 -0.670722 -3.3 -2.9 0.679771 0.679771 0.339885 -0.679771 -3.2 -2.9 0.688665 0.688665 0.344333 -0.688665 -3.1 -2.9 0.697397 0.697397 0.348699 -0.697397 -3 -2.9 0.705958 0.705958 0.352979 -0.705958 -2.9 -2.9 0.714337 0.714337 0.357169 -0.714337 -2.8 -2.9 0.722527 0.722527 0.361264 -0.722527 -2.7 -2.9 0.730519 0.730519 0.36526 -0.730519 -2.6 -2.9 0.738304 0.738304 0.369152 -0.738304 -2.5 -2.9 0.745873 0.745873 0.372936 -0.745873 -2.4 -2.9 0.753218 0.753218 0.376609 -0.753218 -2.3 -2.9 0.760332 0.760332 0.380166 -0.760332 -2.2 -2.9 0.767206 0.767206 0.383603 -0.767206 -2.1 -2.9 0.773832 0.773832 0.386916 -0.773832 -2 -2.9 0.780204 0.780204 0.390102 -0.780204 -1.9 -2.9 0.786313 0.786313 0.393157 -0.786313 -1.8 -2.9 0.792154 0.792154 0.396077 -0.792154 -1.7 -2.9 0.797718 0.797718 0.398859 -0.797718 -1.6 -2.9 0.803 0.803 0.4015 -0.803 -1.5 -2.9 0.807995 0.807995 0.403997 -0.807995 -1.4 -2.9 0.812695 0.812695 0.406347 -0.812695 -1.3 -2.9 0.817095 0.817095 0.408547 -0.817095 -1.2 -2.9 0.821191 0.821191 0.410595 -0.821191 -1.1 -2.9 0.824977 0.824977 0.412488 -0.824977 -1 -2.9 0.828449 0.828449 0.414225 -0.828449 -0.9 -2.9 0.831603 0.831603 0.415802 -0.831603 -0.8 -2.9 0.834435 0.834435 0.417218 -0.834435 -0.7 -2.9 0.836942 0.836942 0.418471 -0.836942 -0.6 -2.9 0.839121 0.839121 0.419561 -0.839121 -0.5 -2.9 0.840969 0.840969 0.420485 -0.840969 -0.4 -2.9 0.842485 0.842485 0.421242 -0.842485 -0.3 -2.9 0.843665 0.843665 0.421832 -0.843665 -0.2 -2.9 0.844509 0.844509 0.422254 -0.844509 -0.1 -2.9 0.845016 0.845016 0.422508 -0.845016 0 -2.9 0.845185 0.845185 0.422592 -0.845185 0.1 -2.9 0.845016 0.845016 0.422508 -0.845016 0.2 -2.9 0.844509 0.844509 0.422254 -0.844509 0.3 -2.9 0.843665 0.843665 0.421832 -0.843665 0.4 -2.9 0.842485 0.842485 0.421242 -0.842485 0.5 -2.9 0.840969 0.840969 0.420485 -0.840969 0.6 -2.9 0.839121 0.839121 0.419561 -0.839121 0.7 -2.9 0.836942 0.836942 0.418471 -0.836942 0.8 -2.9 0.834435 0.834435 0.417218 -0.834435 0.9 -2.9 0.831603 0.831603 0.415802 -0.831603 1 -2.9 0.828449 0.828449 0.414225 -0.828449 1.1 -2.9 0.824977 0.824977 0.412488 -0.824977 1.2 -2.9 0.821191 0.821191 0.410595 -0.821191 1.3 -2.9 0.817095 0.817095 0.408547 -0.817095 1.4 -2.9 0.812695 0.812695 0.406347 -0.812695 1.5 -2.9 0.807995 0.807995 0.403997 -0.807995 1.6 -2.9 0.803 0.803 0.4015 -0.803 1.7 -2.9 0.797718 0.797718 0.398859 -0.797718 1.8 -2.9 0.792154 0.792154 0.396077 -0.792154 1.9 -2.9 0.786313 0.786313 0.393157 -0.786313 2 -2.9 0.780204 0.780204 0.390102 -0.780204 2.1 -2.9 0.773832 0.773832 0.386916 -0.773832 2.2 -2.9 0.767206 0.767206 0.383603 -0.767206 2.3 -2.9 0.760332 0.760332 0.380166 -0.760332 2.4 -2.9 0.753218 0.753218 0.376609 -0.753218 2.5 -2.9 0.745873 0.745873 0.372936 -0.745873 2.6 -2.9 0.738304 0.738304 0.369152 -0.738304 2.7 -2.9 0.730519 0.730519 0.36526 -0.730519 2.8 -2.9 0.722527 0.722527 0.361264 -0.722527 2.9 -2.9 0.714337 0.714337 0.357169 -0.714337 3 -2.9 0.705958 0.705958 0.352979 -0.705958 3.1 -2.9 0.697397 0.697397 0.348699 -0.697397 3.2 -2.9 0.688665 0.688665 0.344333 -0.688665 3.3 -2.9 0.679771 0.679771 0.339885 -0.679771 3.4 -2.9 0.670722 0.670722 0.335361 -0.670722 3.5 -2.9 0.66153 0.66153 0.330765 -0.66153 3.6 -2.9 0.652203 0.652203 0.326101 -0.652203 3.7 -2.9 0.64275 0.64275 0.321375 -0.64275 3.8 -2.9 0.63318 0.63318 0.31659 -0.63318 3.9 -2.9 0.623504 0.623504 0.311752 -0.623504 4 -2.9 0.61373 0.61373 0.306865 -0.61373 4.1 -2.9 0.603868 0.603868 0.301934 -0.603868 4.2 -2.9 0.593926 0.593926 0.296963 -0.593926 4.3 -2.9 0.583915 0.583915 0.291957 -0.583915 4.4 -2.9 0.573843 0.573843 0.286921 -0.573843 4.5 -2.9 0.563719 0.563719 0.281859 -0.563719 4.6 -2.9 0.553552 0.553552 0.276776 -0.553552 4.7 -2.9 0.543351 0.543351 0.271675 -0.543351 4.8 -2.9 0.533125 0.533125 0.266562 -0.533125 4.9 -2.9 0.522882 0.522882 0.261441 -0.522882 -5 -2.8 0.518508 0.518508 0.259254 -0.518508 -4.9 -2.8 0.528877 0.528877 0.264438 -0.528877 -4.8 -2.8 0.539237 0.539237 0.269619 -0.539237 -4.7 -2.8 0.549581 0.549581 0.27479 -0.549581 -4.6 -2.8 0.559898 0.559898 0.279949 -0.559898 -4.5 -2.8 0.570182 0.570182 0.285091 -0.570182 -4.4 -2.8 0.580422 0.580422 0.290211 -0.580422 -4.3 -2.8 0.59061 0.59061 0.295305 -0.59061 -4.2 -2.8 0.600736 0.600736 0.300368 -0.600736 -4.1 -2.8 0.610791 0.610791 0.305396 -0.610791 -4 -2.8 0.620767 0.620767 0.310383 -0.620767 -3.9 -2.8 0.630653 0.630653 0.315326 -0.630653 -3.8 -2.8 0.64044 0.64044 0.32022 -0.64044 -3.7 -2.8 0.650119 0.650119 0.325059 -0.650119 -3.6 -2.8 0.65968 0.65968 0.32984 -0.65968 -3.5 -2.8 0.669115 0.669115 0.334557 -0.669115 -3.4 -2.8 0.678412 0.678412 0.339206 -0.678412 -3.3 -2.8 0.687564 0.687564 0.343782 -0.687564 -3.2 -2.8 0.696561 0.696561 0.34828 -0.696561 -3.1 -2.8 0.705393 0.705393 0.352697 -0.705393 -3 -2.8 0.714052 0.714052 0.357026 -0.714052 -2.9 -2.8 0.722527 0.722527 0.361264 -0.722527 -2.8 -2.8 0.730811 0.730811 0.365406 -0.730811 -2.7 -2.8 0.738895 0.738895 0.369447 -0.738895 -2.6 -2.8 0.746769 0.746769 0.373384 -0.746769 -2.5 -2.8 0.754425 0.754425 0.377212 -0.754425 -2.4 -2.8 0.761854 0.761854 0.380927 -0.761854 -2.3 -2.8 0.769049 0.769049 0.384525 -0.769049 -2.2 -2.8 0.776002 0.776002 0.388001 -0.776002 -2.1 -2.8 0.782705 0.782705 0.391352 -0.782705 -2 -2.8 0.789149 0.789149 0.394575 -0.789149 -1.9 -2.8 0.795329 0.795329 0.397664 -0.795329 -1.8 -2.8 0.801236 0.801236 0.400618 -0.801236 -1.7 -2.8 0.806864 0.806864 0.403432 -0.806864 -1.6 -2.8 0.812207 0.812207 0.406104 -0.812207 -1.5 -2.8 0.817258 0.817258 0.408629 -0.817258 -1.4 -2.8 0.822012 0.822012 0.411006 -0.822012 -1.3 -2.8 0.826463 0.826463 0.413232 -0.826463 -1.2 -2.8 0.830606 0.830606 0.415303 -0.830606 -1.1 -2.8 0.834435 0.834435 0.417218 -0.834435 -1 -2.8 0.837947 0.837947 0.418974 -0.837947 -0.9 -2.8 0.841138 0.841138 0.420569 -0.841138 -0.8 -2.8 0.844002 0.844002 0.422001 -0.844002 -0.7 -2.8 0.846538 0.846538 0.423269 -0.846538 -0.6 -2.8 0.848742 0.848742 0.424371 -0.848742 -0.5 -2.8 0.850611 0.850611 0.425306 -0.850611 -0.4 -2.8 0.852144 0.852144 0.426072 -0.852144 -0.3 -2.8 0.853338 0.853338 0.426669 -0.853338 -0.2 -2.8 0.854191 0.854191 0.427096 -0.854191 -0.1 -2.8 0.854704 0.854704 0.427352 -0.854704 0 -2.8 0.854875 0.854875 0.427438 -0.854875 0.1 -2.8 0.854704 0.854704 0.427352 -0.854704 0.2 -2.8 0.854191 0.854191 0.427096 -0.854191 0.3 -2.8 0.853338 0.853338 0.426669 -0.853338 0.4 -2.8 0.852144 0.852144 0.426072 -0.852144 0.5 -2.8 0.850611 0.850611 0.425306 -0.850611 0.6 -2.8 0.848742 0.848742 0.424371 -0.848742 0.7 -2.8 0.846538 0.846538 0.423269 -0.846538 0.8 -2.8 0.844002 0.844002 0.422001 -0.844002 0.9 -2.8 0.841138 0.841138 0.420569 -0.841138 1 -2.8 0.837947 0.837947 0.418974 -0.837947 1.1 -2.8 0.834435 0.834435 0.417218 -0.834435 1.2 -2.8 0.830606 0.830606 0.415303 -0.830606 1.3 -2.8 0.826463 0.826463 0.413232 -0.826463 1.4 -2.8 0.822012 0.822012 0.411006 -0.822012 1.5 -2.8 0.817258 0.817258 0.408629 -0.817258 1.6 -2.8 0.812207 0.812207 0.406104 -0.812207 1.7 -2.8 0.806864 0.806864 0.403432 -0.806864 1.8 -2.8 0.801236 0.801236 0.400618 -0.801236 1.9 -2.8 0.795329 0.795329 0.397664 -0.795329 2 -2.8 0.789149 0.789149 0.394575 -0.789149 2.1 -2.8 0.782705 0.782705 0.391352 -0.782705 2.2 -2.8 0.776002 0.776002 0.388001 -0.776002 2.3 -2.8 0.769049 0.769049 0.384525 -0.769049 2.4 -2.8 0.761854 0.761854 0.380927 -0.761854 2.5 -2.8 0.754425 0.754425 0.377212 -0.754425 2.6 -2.8 0.746769 0.746769 0.373384 -0.746769 2.7 -2.8 0.738895 0.738895 0.369447 -0.738895 2.8 -2.8 0.730811 0.730811 0.365406 -0.730811 2.9 -2.8 0.722527 0.722527 0.361264 -0.722527 3 -2.8 0.714052 0.714052 0.357026 -0.714052 3.1 -2.8 0.705393 0.705393 0.352697 -0.705393 3.2 -2.8 0.696561 0.696561 0.34828 -0.696561 3.3 -2.8 0.687564 0.687564 0.343782 -0.687564 3.4 -2.8 0.678412 0.678412 0.339206 -0.678412 3.5 -2.8 0.669115 0.669115 0.334557 -0.669115 3.6 -2.8 0.65968 0.65968 0.32984 -0.65968 3.7 -2.8 0.650119 0.650119 0.325059 -0.650119 3.8 -2.8 0.64044 0.64044 0.32022 -0.64044 3.9 -2.8 0.630653 0.630653 0.315326 -0.630653 4 -2.8 0.620767 0.620767 0.310383 -0.620767 4.1 -2.8 0.610791 0.610791 0.305396 -0.610791 4.2 -2.8 0.600736 0.600736 0.300368 -0.600736 4.3 -2.8 0.59061 0.59061 0.295305 -0.59061 4.4 -2.8 0.580422 0.580422 0.290211 -0.580422 4.5 -2.8 0.570182 0.570182 0.285091 -0.570182 4.6 -2.8 0.559898 0.559898 0.279949 -0.559898 4.7 -2.8 0.549581 0.549581 0.27479 -0.549581 4.8 -2.8 0.539237 0.539237 0.269619 -0.539237 4.9 -2.8 0.528877 0.528877 0.264438 -0.528877 -5 -2.7 0.524243 0.524243 0.262121 -0.524243 -4.9 -2.7 0.534726 0.534726 0.267363 -0.534726 -4.8 -2.7 0.545201 0.545201 0.272601 -0.545201 -4.7 -2.7 0.555659 0.555659 0.27783 -0.555659 -4.6 -2.7 0.566091 0.566091 0.283046 -0.566091 -4.5 -2.7 0.576488 0.576488 0.288244 -0.576488 -4.4 -2.7 0.586842 0.586842 0.293421 -0.586842 -4.3 -2.7 0.597142 0.597142 0.298571 -0.597142 -4.2 -2.7 0.60738 0.60738 0.30369 -0.60738 -4.1 -2.7 0.617547 0.617547 0.308774 -0.617547 -4 -2.7 0.627633 0.627633 0.313816 -0.627633 -3.9 -2.7 0.637628 0.637628 0.318814 -0.637628 -3.8 -2.7 0.647524 0.647524 0.323762 -0.647524 -3.7 -2.7 0.65731 0.65731 0.328655 -0.65731 -3.6 -2.7 0.666977 0.666977 0.333488 -0.666977 -3.5 -2.7 0.676515 0.676515 0.338258 -0.676515 -3.4 -2.7 0.685916 0.685916 0.342958 -0.685916 -3.3 -2.7 0.695169 0.695169 0.347585 -0.695169 -3.2 -2.7 0.704265 0.704265 0.352133 -0.704265 -3.1 -2.7 0.713195 0.713195 0.356598 -0.713195 -3 -2.7 0.72195 0.72195 0.360975 -0.72195 -2.9 -2.7 0.730519 0.730519 0.36526 -0.730519 -2.8 -2.7 0.738895 0.738895 0.369447 -0.738895 -2.7 -2.7 0.747067 0.747067 0.373534 -0.747067 -2.6 -2.7 0.755028 0.755028 0.377514 -0.755028 -2.5 -2.7 0.762769 0.762769 0.381385 -0.762769 -2.4 -2.7 0.770281 0.770281 0.38514 -0.770281 -2.3 -2.7 0.777556 0.777556 0.388778 -0.777556 -2.2 -2.7 0.784585 0.784585 0.392293 -0.784585 -2.1 -2.7 0.791362 0.791362 0.395681 -0.791362 -2 -2.7 0.797878 0.797878 0.398939 -0.797878 -1.9 -2.7 0.804125 0.804125 0.402063 -0.804125 -1.8 -2.7 0.810098 0.810098 0.405049 -0.810098 -1.7 -2.7 0.815789 0.815789 0.407894 -0.815789 -1.6 -2.7 0.821191 0.821191 0.410595 -0.821191 -1.5 -2.7 0.826298 0.826298 0.413149 -0.826298 -1.4 -2.7 0.831104 0.831104 0.415552 -0.831104 -1.3 -2.7 0.835604 0.835604 0.417802 -0.835604 -1.2 -2.7 0.839793 0.839793 0.419896 -0.839793 -1.1 -2.7 0.843665 0.843665 0.421832 -0.843665 -1 -2.7 0.847216 0.847216 0.423608 -0.847216 -0.9 -2.7 0.850441 0.850441 0.425221 -0.850441 -0.8 -2.7 0.853338 0.853338 0.426669 -0.853338 -0.7 -2.7 0.855901 0.855901 0.427951 -0.855901 -0.6 -2.7 0.85813 0.85813 0.429065 -0.85813 -0.5 -2.7 0.86002 0.86002 0.43001 -0.86002 -0.4 -2.7 0.861569 0.861569 0.430785 -0.861569 -0.3 -2.7 0.862776 0.862776 0.431388 -0.862776 -0.2 -2.7 0.863639 0.863639 0.43182 -0.863639 -0.1 -2.7 0.864158 0.864158 0.432079 -0.864158 0 -2.7 0.864331 0.864331 0.432165 -0.864331 0.1 -2.7 0.864158 0.864158 0.432079 -0.864158 0.2 -2.7 0.863639 0.863639 0.43182 -0.863639 0.3 -2.7 0.862776 0.862776 0.431388 -0.862776 0.4 -2.7 0.861569 0.861569 0.430785 -0.861569 0.5 -2.7 0.86002 0.86002 0.43001 -0.86002 0.6 -2.7 0.85813 0.85813 0.429065 -0.85813 0.7 -2.7 0.855901 0.855901 0.427951 -0.855901 0.8 -2.7 0.853338 0.853338 0.426669 -0.853338 0.9 -2.7 0.850441 0.850441 0.425221 -0.850441 1 -2.7 0.847216 0.847216 0.423608 -0.847216 1.1 -2.7 0.843665 0.843665 0.421832 -0.843665 1.2 -2.7 0.839793 0.839793 0.419896 -0.839793 1.3 -2.7 0.835604 0.835604 0.417802 -0.835604 1.4 -2.7 0.831104 0.831104 0.415552 -0.831104 1.5 -2.7 0.826298 0.826298 0.413149 -0.826298 1.6 -2.7 0.821191 0.821191 0.410595 -0.821191 1.7 -2.7 0.815789 0.815789 0.407894 -0.815789 1.8 -2.7 0.810098 0.810098 0.405049 -0.810098 1.9 -2.7 0.804125 0.804125 0.402063 -0.804125 2 -2.7 0.797878 0.797878 0.398939 -0.797878 2.1 -2.7 0.791362 0.791362 0.395681 -0.791362 2.2 -2.7 0.784585 0.784585 0.392293 -0.784585 2.3 -2.7 0.777556 0.777556 0.388778 -0.777556 2.4 -2.7 0.770281 0.770281 0.38514 -0.770281 2.5 -2.7 0.762769 0.762769 0.381385 -0.762769 2.6 -2.7 0.755028 0.755028 0.377514 -0.755028 2.7 -2.7 0.747067 0.747067 0.373534 -0.747067 2.8 -2.7 0.738895 0.738895 0.369447 -0.738895 2.9 -2.7 0.730519 0.730519 0.36526 -0.730519 3 -2.7 0.72195 0.72195 0.360975 -0.72195 3.1 -2.7 0.713195 0.713195 0.356598 -0.713195 3.2 -2.7 0.704265 0.704265 0.352133 -0.704265 3.3 -2.7 0.695169 0.695169 0.347585 -0.695169 3.4 -2.7 0.685916 0.685916 0.342958 -0.685916 3.5 -2.7 0.676515 0.676515 0.338258 -0.676515 3.6 -2.7 0.666977 0.666977 0.333488 -0.666977 3.7 -2.7 0.65731 0.65731 0.328655 -0.65731 3.8 -2.7 0.647524 0.647524 0.323762 -0.647524 3.9 -2.7 0.637628 0.637628 0.318814 -0.637628 4 -2.7 0.627633 0.627633 0.313816 -0.627633 4.1 -2.7 0.617547 0.617547 0.308774 -0.617547 4.2 -2.7 0.60738 0.60738 0.30369 -0.60738 4.3 -2.7 0.597142 0.597142 0.298571 -0.597142 4.4 -2.7 0.586842 0.586842 0.293421 -0.586842 4.5 -2.7 0.576488 0.576488 0.288244 -0.576488 4.6 -2.7 0.566091 0.566091 0.283046 -0.566091 4.7 -2.7 0.555659 0.555659 0.27783 -0.555659 4.8 -2.7 0.545201 0.545201 0.272601 -0.545201 4.9 -2.7 0.534726 0.534726 0.267363 -0.534726 -5 -2.6 0.52983 0.52983 0.264915 -0.52983 -4.9 -2.6 0.540425 0.540425 0.270212 -0.540425 -4.8 -2.6 0.551011 0.551011 0.275506 -0.551011 -4.7 -2.6 0.561581 0.561581 0.28079 -0.561581 -4.6 -2.6 0.572124 0.572124 0.286062 -0.572124 -4.5 -2.6 0.582632 0.582632 0.291316 -0.582632 -4.4 -2.6 0.593095 0.593095 0.296548 -0.593095 -4.3 -2.6 0.603506 0.603506 0.301753 -0.603506 -4.2 -2.6 0.613853 0.613853 0.306926 -0.613853 -4.1 -2.6 0.624128 0.624128 0.312064 -0.624128 -4 -2.6 0.634321 0.634321 0.317161 -0.634321 -3.9 -2.6 0.644423 0.644423 0.322211 -0.644423 -3.8 -2.6 0.654424 0.654424 0.327212 -0.654424 -3.7 -2.6 0.664314 0.664314 0.332157 -0.664314 -3.6 -2.6 0.674084 0.674084 0.337042 -0.674084 -3.5 -2.6 0.683725 0.683725 0.341862 -0.683725 -3.4 -2.6 0.693225 0.693225 0.346613 -0.693225 -3.3 -2.6 0.702577 0.702577 0.351289 -0.702577 -3.2 -2.6 0.71177 0.71177 0.355885 -0.71177 -3.1 -2.6 0.720795 0.720795 0.360398 -0.720795 -3 -2.6 0.729643 0.729643 0.364821 -0.729643 -2.9 -2.6 0.738304 0.738304 0.369152 -0.738304 -2.8 -2.6 0.746769 0.746769 0.373384 -0.746769 -2.7 -2.6 0.755028 0.755028 0.377514 -0.755028 -2.6 -2.6 0.763074 0.763074 0.381537 -0.763074 -2.5 -2.6 0.770897 0.770897 0.385449 -0.770897 -2.4 -2.6 0.778489 0.778489 0.389245 -0.778489 -2.3 -2.6 0.785842 0.785842 0.392921 -0.785842 -2.2 -2.6 0.792946 0.792946 0.396473 -0.792946 -2.1 -2.6 0.799795 0.799795 0.399897 -0.799795 -2 -2.6 0.80638 0.80638 0.40319 -0.80638 -1.9 -2.6 0.812695 0.812695 0.406347 -0.812695 -1.8 -2.6 0.818731 0.818731 0.409365 -0.818731 -1.7 -2.6 0.824482 0.824482 0.412241 -0.824482 -1.6 -2.6 0.829942 0.829942 0.414971 -0.829942 -1.5 -2.6 0.835103 0.835103 0.417552 -0.835103 -1.4 -2.6 0.839961 0.839961 0.41998 -0.839961 -1.3 -2.6 0.844509 0.844509 0.422254 -0.844509 -1.2 -2.6 0.848742 0.848742 0.424371 -0.848742 -1.1 -2.6 0.852655 0.852655 0.426328 -0.852655 -1 -2.6 0.856244 0.856244 0.428122 -0.856244 -0.9 -2.6 0.859504 0.859504 0.429752 -0.859504 -0.8 -2.6 0.862431 0.862431 0.431216 -0.862431 -0.7 -2.6 0.865022 0.865022 0.432511 -0.865022 -0.6 -2.6 0.867274 0.867274 0.433637 -0.867274 -0.5 -2.6 0.869184 0.869184 0.434592 -0.869184 -0.4 -2.6 0.87075 0.87075 0.435375 -0.87075 -0.3 -2.6 0.87197 0.87197 0.435985 -0.87197 -0.2 -2.6 0.872843 0.872843 0.436421 -0.872843 -0.1 -2.6 0.873366 0.873366 0.436683 -0.873366 0 -2.6 0.873541 0.873541 0.436771 -0.873541 0.1 -2.6 0.873366 0.873366 0.436683 -0.873366 0.2 -2.6 0.872843 0.872843 0.436421 -0.872843 0.3 -2.6 0.87197 0.87197 0.435985 -0.87197 0.4 -2.6 0.87075 0.87075 0.435375 -0.87075 0.5 -2.6 0.869184 0.869184 0.434592 -0.869184 0.6 -2.6 0.867274 0.867274 0.433637 -0.867274 0.7 -2.6 0.865022 0.865022 0.432511 -0.865022 0.8 -2.6 0.862431 0.862431 0.431216 -0.862431 0.9 -2.6 0.859504 0.859504 0.429752 -0.859504 1 -2.6 0.856244 0.856244 0.428122 -0.856244 1.1 -2.6 0.852655 0.852655 0.426328 -0.852655 1.2 -2.6 0.848742 0.848742 0.424371 -0.848742 1.3 -2.6 0.844509 0.844509 0.422254 -0.844509 1.4 -2.6 0.839961 0.839961 0.41998 -0.839961 1.5 -2.6 0.835103 0.835103 0.417552 -0.835103 1.6 -2.6 0.829942 0.829942 0.414971 -0.829942 1.7 -2.6 0.824482 0.824482 0.412241 -0.824482 1.8 -2.6 0.818731 0.818731 0.409365 -0.818731 1.9 -2.6 0.812695 0.812695 0.406347 -0.812695 2 -2.6 0.80638 0.80638 0.40319 -0.80638 2.1 -2.6 0.799795 0.799795 0.399897 -0.799795 2.2 -2.6 0.792946 0.792946 0.396473 -0.792946 2.3 -2.6 0.785842 0.785842 0.392921 -0.785842 2.4 -2.6 0.778489 0.778489 0.389245 -0.778489 2.5 -2.6 0.770897 0.770897 0.385449 -0.770897 2.6 -2.6 0.763074 0.763074 0.381537 -0.763074 2.7 -2.6 0.755028 0.755028 0.377514 -0.755028 2.8 -2.6 0.746769 0.746769 0.373384 -0.746769 2.9 -2.6 0.738304 0.738304 0.369152 -0.738304 3 -2.6 0.729643 0.729643 0.364821 -0.729643 3.1 -2.6 0.720795 0.720795 0.360398 -0.720795 3.2 -2.6 0.71177 0.71177 0.355885 -0.71177 3.3 -2.6 0.702577 0.702577 0.351289 -0.702577 3.4 -2.6 0.693225 0.693225 0.346613 -0.693225 3.5 -2.6 0.683725 0.683725 0.341862 -0.683725 3.6 -2.6 0.674084 0.674084 0.337042 -0.674084 3.7 -2.6 0.664314 0.664314 0.332157 -0.664314 3.8 -2.6 0.654424 0.654424 0.327212 -0.654424 3.9 -2.6 0.644423 0.644423 0.322211 -0.644423 4 -2.6 0.634321 0.634321 0.317161 -0.634321 4.1 -2.6 0.624128 0.624128 0.312064 -0.624128 4.2 -2.6 0.613853 0.613853 0.306926 -0.613853 4.3 -2.6 0.603506 0.603506 0.301753 -0.603506 4.4 -2.6 0.593095 0.593095 0.296548 -0.593095 4.5 -2.6 0.582632 0.582632 0.291316 -0.582632 4.6 -2.6 0.572124 0.572124 0.286062 -0.572124 4.7 -2.6 0.561581 0.561581 0.28079 -0.561581 4.8 -2.6 0.551011 0.551011 0.275506 -0.551011 4.9 -2.6 0.540425 0.540425 0.270212 -0.540425 -5 -2.5 0.535261 0.535261 0.267631 -0.535261 -4.9 -2.5 0.545965 0.545965 0.272983 -0.545965 -4.8 -2.5 0.55666 0.55666 0.27833 -0.55666 -4.7 -2.5 0.567338 0.567338 0.283669 -0.567338 -4.6 -2.5 0.577989 0.577989 0.288995 -0.577989 -4.5 -2.5 0.588605 0.588605 0.294302 -0.588605 -4.4 -2.5 0.599176 0.599176 0.299588 -0.599176 -4.3 -2.5 0.609693 0.609693 0.304846 -0.609693 -4.2 -2.5 0.620146 0.620146 0.310073 -0.620146 -4.1 -2.5 0.630527 0.630527 0.315263 -0.630527 -4 -2.5 0.640824 0.640824 0.320412 -0.640824 -3.9 -2.5 0.65103 0.65103 0.325515 -0.65103 -3.8 -2.5 0.661133 0.661133 0.330567 -0.661133 -3.7 -2.5 0.671125 0.671125 0.335562 -0.671125 -3.6 -2.5 0.680995 0.680995 0.340498 -0.680995 -3.5 -2.5 0.690734 0.690734 0.345367 -0.690734 -3.4 -2.5 0.700333 0.700333 0.350166 -0.700333 -3.3 -2.5 0.70978 0.70978 0.35489 -0.70978 -3.2 -2.5 0.719068 0.719068 0.359534 -0.719068 -3.1 -2.5 0.728185 0.728185 0.364093 -0.728185 -3 -2.5 0.737123 0.737123 0.368562 -0.737123 -2.9 -2.5 0.745873 0.745873 0.372936 -0.745873 -2.8 -2.5 0.754425 0.754425 0.377212 -0.754425 -2.7 -2.5 0.762769 0.762769 0.381385 -0.762769 -2.6 -2.5 0.770897 0.770897 0.385449 -0.770897 -2.5 -2.5 0.778801 0.778801 0.3894 -0.778801 -2.4 -2.5 0.786471 0.786471 0.393235 -0.786471 -2.3 -2.5 0.793898 0.793898 0.396949 -0.793898 -2.2 -2.5 0.801076 0.801076 0.400538 -0.801076 -2.1 -2.5 0.807995 0.807995 0.403997 -0.807995 -2 -2.5 0.814647 0.814647 0.407324 -0.814647 -1.9 -2.5 0.821026 0.821026 0.410513 -0.821026 -1.8 -2.5 0.827125 0.827125 0.413562 -0.827125 -1.7 -2.5 0.832935 0.832935 0.416467 -0.832935 -1.6 -2.5 0.83845 0.83845 0.419225 -0.83845 -1.5 -2.5 0.843665 0.843665 0.421832 -0.843665 -1.4 -2.5 0.848572 0.848572 0.424286 -0.848572 -1.3 -2.5 0.853167 0.853167 0.426583 -0.853167 -1.2 -2.5 0.857443 0.857443 0.428722 -0.857443 -1.1 -2.5 0.861397 0.861397 0.430698 -0.861397 -1 -2.5 0.865022 0.865022 0.432511 -0.865022 -0.9 -2.5 0.868316 0.868316 0.434158 -0.868316 -0.8 -2.5 0.871273 0.871273 0.435636 -0.871273 -0.7 -2.5 0.873891 0.873891 0.436945 -0.873891 -0.6 -2.5 0.876166 0.876166 0.438083 -0.876166 -0.5 -2.5 0.878095 0.878095 0.439048 -0.878095 -0.4 -2.5 0.879677 0.879677 0.439839 -0.879677 -0.3 -2.5 0.88091 0.88091 0.440455 -0.88091 -0.2 -2.5 0.881791 0.881791 0.440896 -0.881791 -0.1 -2.5 0.88232 0.88232 0.44116 -0.88232 0 -2.5 0.882497 0.882497 0.441248 -0.882497 0.1 -2.5 0.88232 0.88232 0.44116 -0.88232 0.2 -2.5 0.881791 0.881791 0.440896 -0.881791 0.3 -2.5 0.88091 0.88091 0.440455 -0.88091 0.4 -2.5 0.879677 0.879677 0.439839 -0.879677 0.5 -2.5 0.878095 0.878095 0.439048 -0.878095 0.6 -2.5 0.876166 0.876166 0.438083 -0.876166 0.7 -2.5 0.873891 0.873891 0.436945 -0.873891 0.8 -2.5 0.871273 0.871273 0.435636 -0.871273 0.9 -2.5 0.868316 0.868316 0.434158 -0.868316 1 -2.5 0.865022 0.865022 0.432511 -0.865022 1.1 -2.5 0.861397 0.861397 0.430698 -0.861397 1.2 -2.5 0.857443 0.857443 0.428722 -0.857443 1.3 -2.5 0.853167 0.853167 0.426583 -0.853167 1.4 -2.5 0.848572 0.848572 0.424286 -0.848572 1.5 -2.5 0.843665 0.843665 0.421832 -0.843665 1.6 -2.5 0.83845 0.83845 0.419225 -0.83845 1.7 -2.5 0.832935 0.832935 0.416467 -0.832935 1.8 -2.5 0.827125 0.827125 0.413562 -0.827125 1.9 -2.5 0.821026 0.821026 0.410513 -0.821026 2 -2.5 0.814647 0.814647 0.407324 -0.814647 2.1 -2.5 0.807995 0.807995 0.403997 -0.807995 2.2 -2.5 0.801076 0.801076 0.400538 -0.801076 2.3 -2.5 0.793898 0.793898 0.396949 -0.793898 2.4 -2.5 0.786471 0.786471 0.393235 -0.786471 2.5 -2.5 0.778801 0.778801 0.3894 -0.778801 2.6 -2.5 0.770897 0.770897 0.385449 -0.770897 2.7 -2.5 0.762769 0.762769 0.381385 -0.762769 2.8 -2.5 0.754425 0.754425 0.377212 -0.754425 2.9 -2.5 0.745873 0.745873 0.372936 -0.745873 3 -2.5 0.737123 0.737123 0.368562 -0.737123 3.1 -2.5 0.728185 0.728185 0.364093 -0.728185 3.2 -2.5 0.719068 0.719068 0.359534 -0.719068 3.3 -2.5 0.70978 0.70978 0.35489 -0.70978 3.4 -2.5 0.700333 0.700333 0.350166 -0.700333 3.5 -2.5 0.690734 0.690734 0.345367 -0.690734 3.6 -2.5 0.680995 0.680995 0.340498 -0.680995 3.7 -2.5 0.671125 0.671125 0.335562 -0.671125 3.8 -2.5 0.661133 0.661133 0.330567 -0.661133 3.9 -2.5 0.65103 0.65103 0.325515 -0.65103 4 -2.5 0.640824 0.640824 0.320412 -0.640824 4.1 -2.5 0.630527 0.630527 0.315263 -0.630527 4.2 -2.5 0.620146 0.620146 0.310073 -0.620146 4.3 -2.5 0.609693 0.609693 0.304846 -0.609693 4.4 -2.5 0.599176 0.599176 0.299588 -0.599176 4.5 -2.5 0.588605 0.588605 0.294302 -0.588605 4.6 -2.5 0.577989 0.577989 0.288995 -0.577989 4.7 -2.5 0.567338 0.567338 0.283669 -0.567338 4.8 -2.5 0.55666 0.55666 0.27833 -0.55666 4.9 -2.5 0.545965 0.545965 0.272983 -0.545965 -5 -2.4 0.540533 0.540533 0.270266 -0.540533 -4.9 -2.4 0.551342 0.551342 0.275671 -0.551342 -4.8 -2.4 0.562142 0.562142 0.281071 -0.562142 -4.7 -2.4 0.572925 0.572925 0.286463 -0.572925 -4.6 -2.4 0.583681 0.583681 0.291841 -0.583681 -4.5 -2.4 0.594402 0.594402 0.297201 -0.594402 -4.4 -2.4 0.605077 0.605077 0.302538 -0.605077 -4.3 -2.4 0.615697 0.615697 0.307849 -0.615697 -4.2 -2.4 0.626254 0.626254 0.313127 -0.626254 -4.1 -2.4 0.636736 0.636736 0.318368 -0.636736 -4 -2.4 0.647135 0.647135 0.323568 -0.647135 -3.9 -2.4 0.657441 0.657441 0.328721 -0.657441 -3.8 -2.4 0.667644 0.667644 0.333822 -0.667644 -3.7 -2.4 0.677734 0.677734 0.338867 -0.677734 -3.6 -2.4 0.687702 0.687702 0.343851 -0.687702 -3.5 -2.4 0.697537 0.697537 0.348768 -0.697537 -3.4 -2.4 0.70723 0.70723 0.353615 -0.70723 -3.3 -2.4 0.71677 0.71677 0.358385 -0.71677 -3.2 -2.4 0.726149 0.726149 0.363075 -0.726149 -3.1 -2.4 0.735356 0.735356 0.367678 -0.735356 -3 -2.4 0.744383 0.744383 0.372191 -0.744383 -2.9 -2.4 0.753218 0.753218 0.376609 -0.753218 -2.8 -2.4 0.761854 0.761854 0.380927 -0.761854 -2.7 -2.4 0.770281 0.770281 0.38514 -0.770281 -2.6 -2.4 0.778489 0.778489 0.389245 -0.778489 -2.5 -2.4 0.786471 0.786471 0.393235 -0.786471 -2.4 -2.4 0.794216 0.794216 0.397108 -0.794216 -2.3 -2.4 0.801717 0.801717 0.400858 -0.801717 -2.2 -2.4 0.808965 0.808965 0.404482 -0.808965 -2.1 -2.4 0.815952 0.815952 0.407976 -0.815952 -2 -2.4 0.82267 0.82267 0.411335 -0.82267 -1.9 -2.4 0.829112 0.829112 0.414556 -0.829112 -1.8 -2.4 0.83527 0.83527 0.417635 -0.83527 -1.7 -2.4 0.841138 0.841138 0.420569 -0.841138 -1.6 -2.4 0.846707 0.846707 0.423354 -0.846707 -1.5 -2.4 0.851973 0.851973 0.425987 -0.851973 -1.4 -2.4 0.856929 0.856929 0.428465 -0.856929 -1.3 -2.4 0.861569 0.861569 0.430785 -0.861569 -1.2 -2.4 0.865888 0.865888 0.432944 -0.865888 -1.1 -2.4 0.86988 0.86988 0.43494 -0.86988 -1 -2.4 0.873541 0.873541 0.436771 -0.873541 -0.9 -2.4 0.876867 0.876867 0.438433 -0.876867 -0.8 -2.4 0.879853 0.879853 0.439927 -0.879853 -0.7 -2.4 0.882497 0.882497 0.441248 -0.882497 -0.6 -2.4 0.884794 0.884794 0.442397 -0.884794 -0.5 -2.4 0.886743 0.886743 0.443372 -0.886743 -0.4 -2.4 0.888341 0.888341 0.44417 -0.888341 -0.3 -2.4 0.889585 0.889585 0.444793 -0.889585 -0.2 -2.4 0.890475 0.890475 0.445238 -0.890475 -0.1 -2.4 0.89101 0.89101 0.445505 -0.89101 0 -2.4 0.891188 0.891188 0.445594 -0.891188 0.1 -2.4 0.89101 0.89101 0.445505 -0.89101 0.2 -2.4 0.890475 0.890475 0.445238 -0.890475 0.3 -2.4 0.889585 0.889585 0.444793 -0.889585 0.4 -2.4 0.888341 0.888341 0.44417 -0.888341 0.5 -2.4 0.886743 0.886743 0.443372 -0.886743 0.6 -2.4 0.884794 0.884794 0.442397 -0.884794 0.7 -2.4 0.882497 0.882497 0.441248 -0.882497 0.8 -2.4 0.879853 0.879853 0.439927 -0.879853 0.9 -2.4 0.876867 0.876867 0.438433 -0.876867 1 -2.4 0.873541 0.873541 0.436771 -0.873541 1.1 -2.4 0.86988 0.86988 0.43494 -0.86988 1.2 -2.4 0.865888 0.865888 0.432944 -0.865888 1.3 -2.4 0.861569 0.861569 0.430785 -0.861569 1.4 -2.4 0.856929 0.856929 0.428465 -0.856929 1.5 -2.4 0.851973 0.851973 0.425987 -0.851973 1.6 -2.4 0.846707 0.846707 0.423354 -0.846707 1.7 -2.4 0.841138 0.841138 0.420569 -0.841138 1.8 -2.4 0.83527 0.83527 0.417635 -0.83527 1.9 -2.4 0.829112 0.829112 0.414556 -0.829112 2 -2.4 0.82267 0.82267 0.411335 -0.82267 2.1 -2.4 0.815952 0.815952 0.407976 -0.815952 2.2 -2.4 0.808965 0.808965 0.404482 -0.808965 2.3 -2.4 0.801717 0.801717 0.400858 -0.801717 2.4 -2.4 0.794216 0.794216 0.397108 -0.794216 2.5 -2.4 0.786471 0.786471 0.393235 -0.786471 2.6 -2.4 0.778489 0.778489 0.389245 -0.778489 2.7 -2.4 0.770281 0.770281 0.38514 -0.770281 2.8 -2.4 0.761854 0.761854 0.380927 -0.761854 2.9 -2.4 0.753218 0.753218 0.376609 -0.753218 3 -2.4 0.744383 0.744383 0.372191 -0.744383 3.1 -2.4 0.735356 0.735356 0.367678 -0.735356 3.2 -2.4 0.726149 0.726149 0.363075 -0.726149 3.3 -2.4 0.71677 0.71677 0.358385 -0.71677 3.4 -2.4 0.70723 0.70723 0.353615 -0.70723 3.5 -2.4 0.697537 0.697537 0.348768 -0.697537 3.6 -2.4 0.687702 0.687702 0.343851 -0.687702 3.7 -2.4 0.677734 0.677734 0.338867 -0.677734 3.8 -2.4 0.667644 0.667644 0.333822 -0.667644 3.9 -2.4 0.657441 0.657441 0.328721 -0.657441 4 -2.4 0.647135 0.647135 0.323568 -0.647135 4.1 -2.4 0.636736 0.636736 0.318368 -0.636736 4.2 -2.4 0.626254 0.626254 0.313127 -0.626254 4.3 -2.4 0.615697 0.615697 0.307849 -0.615697 4.4 -2.4 0.605077 0.605077 0.302538 -0.605077 4.5 -2.4 0.594402 0.594402 0.297201 -0.594402 4.6 -2.4 0.583681 0.583681 0.291841 -0.583681 4.7 -2.4 0.572925 0.572925 0.286463 -0.572925 4.8 -2.4 0.562142 0.562142 0.281071 -0.562142 4.9 -2.4 0.551342 0.551342 0.275671 -0.551342 -5 -2.3 0.545638 0.545638 0.272819 -0.545638 -4.9 -2.3 0.556549 0.556549 0.278275 -0.556549 -4.8 -2.3 0.567451 0.567451 0.283726 -0.567451 -4.7 -2.3 0.578336 0.578336 0.289168 -0.578336 -4.6 -2.3 0.589194 0.589194 0.294597 -0.589194 -4.5 -2.3 0.600015 0.600015 0.300008 -0.600015 -4.4 -2.3 0.610791 0.610791 0.305396 -0.610791 -4.3 -2.3 0.621512 0.621512 0.310756 -0.621512 -4.2 -2.3 0.632168 0.632168 0.316084 -0.632168 -4.1 -2.3 0.64275 0.64275 0.321375 -0.64275 -4 -2.3 0.653247 0.653247 0.326623 -0.653247 -3.9 -2.3 0.66365 0.66365 0.331825 -0.66365 -3.8 -2.3 0.67395 0.67395 0.336975 -0.67395 -3.7 -2.3 0.684135 0.684135 0.342068 -0.684135 -3.6 -2.3 0.694197 0.694197 0.347098 -0.694197 -3.5 -2.3 0.704125 0.704125 0.352062 -0.704125 -3.4 -2.3 0.713909 0.713909 0.356954 -0.713909 -3.3 -2.3 0.72354 0.72354 0.36177 -0.72354 -3.2 -2.3 0.733007 0.733007 0.366504 -0.733007 -3.1 -2.3 0.742301 0.742301 0.371151 -0.742301 -3 -2.3 0.751413 0.751413 0.375706 -0.751413 -2.9 -2.3 0.760332 0.760332 0.380166 -0.760332 -2.8 -2.3 0.769049 0.769049 0.384525 -0.769049 -2.7 -2.3 0.777556 0.777556 0.388778 -0.777556 -2.6 -2.3 0.785842 0.785842 0.392921 -0.785842 -2.5 -2.3 0.793898 0.793898 0.396949 -0.793898 -2.4 -2.3 0.801717 0.801717 0.400858 -0.801717 -2.3 -2.3 0.809288 0.809288 0.404644 -0.809288 -2.2 -2.3 0.816605 0.816605 0.408302 -0.816605 -2.1 -2.3 0.823658 0.823658 0.411829 -0.823658 -2 -2.3 0.83044 0.83044 0.41522 -0.83044 -1.9 -2.3 0.836942 0.836942 0.418471 -0.836942 -1.8 -2.3 0.843159 0.843159 0.421579 -0.843159 -1.7 -2.3 0.849082 0.849082 0.424541 -0.849082 -1.6 -2.3 0.854704 0.854704 0.427352 -0.854704 -1.5 -2.3 0.86002 0.86002 0.43001 -0.86002 -1.4 -2.3 0.865022 0.865022 0.432511 -0.865022 -1.3 -2.3 0.869706 0.869706 0.434853 -0.869706 -1.2 -2.3 0.874065 0.874065 0.437033 -0.874065 -1.1 -2.3 0.878095 0.878095 0.439048 -0.878095 -1 -2.3 0.881791 0.881791 0.440896 -0.881791 -0.9 -2.3 0.885148 0.885148 0.442574 -0.885148 -0.8 -2.3 0.888163 0.888163 0.444081 -0.888163 -0.7 -2.3 0.890831 0.890831 0.445416 -0.890831 -0.6 -2.3 0.893151 0.893151 0.446575 -0.893151 -0.5 -2.3 0.895118 0.895118 0.447559 -0.895118 -0.4 -2.3 0.89673 0.89673 0.448365 -0.89673 -0.3 -2.3 0.897987 0.897987 0.448993 -0.897987 -0.2 -2.3 0.898885 0.898885 0.449443 -0.898885 -0.1 -2.3 0.899425 0.899425 0.449712 -0.899425 0 -2.3 0.899605 0.899605 0.449802 -0.899605 0.1 -2.3 0.899425 0.899425 0.449712 -0.899425 0.2 -2.3 0.898885 0.898885 0.449443 -0.898885 0.3 -2.3 0.897987 0.897987 0.448993 -0.897987 0.4 -2.3 0.89673 0.89673 0.448365 -0.89673 0.5 -2.3 0.895118 0.895118 0.447559 -0.895118 0.6 -2.3 0.893151 0.893151 0.446575 -0.893151 0.7 -2.3 0.890831 0.890831 0.445416 -0.890831 0.8 -2.3 0.888163 0.888163 0.444081 -0.888163 0.9 -2.3 0.885148 0.885148 0.442574 -0.885148 1 -2.3 0.881791 0.881791 0.440896 -0.881791 1.1 -2.3 0.878095 0.878095 0.439048 -0.878095 1.2 -2.3 0.874065 0.874065 0.437033 -0.874065 1.3 -2.3 0.869706 0.869706 0.434853 -0.869706 1.4 -2.3 0.865022 0.865022 0.432511 -0.865022 1.5 -2.3 0.86002 0.86002 0.43001 -0.86002 1.6 -2.3 0.854704 0.854704 0.427352 -0.854704 1.7 -2.3 0.849082 0.849082 0.424541 -0.849082 1.8 -2.3 0.843159 0.843159 0.421579 -0.843159 1.9 -2.3 0.836942 0.836942 0.418471 -0.836942 2 -2.3 0.83044 0.83044 0.41522 -0.83044 2.1 -2.3 0.823658 0.823658 0.411829 -0.823658 2.2 -2.3 0.816605 0.816605 0.408302 -0.816605 2.3 -2.3 0.809288 0.809288 0.404644 -0.809288 2.4 -2.3 0.801717 0.801717 0.400858 -0.801717 2.5 -2.3 0.793898 0.793898 0.396949 -0.793898 2.6 -2.3 0.785842 0.785842 0.392921 -0.785842 2.7 -2.3 0.777556 0.777556 0.388778 -0.777556 2.8 -2.3 0.769049 0.769049 0.384525 -0.769049 2.9 -2.3 0.760332 0.760332 0.380166 -0.760332 3 -2.3 0.751413 0.751413 0.375706 -0.751413 3.1 -2.3 0.742301 0.742301 0.371151 -0.742301 3.2 -2.3 0.733007 0.733007 0.366504 -0.733007 3.3 -2.3 0.72354 0.72354 0.36177 -0.72354 3.4 -2.3 0.713909 0.713909 0.356954 -0.713909 3.5 -2.3 0.704125 0.704125 0.352062 -0.704125 3.6 -2.3 0.694197 0.694197 0.347098 -0.694197 3.7 -2.3 0.684135 0.684135 0.342068 -0.684135 3.8 -2.3 0.67395 0.67395 0.336975 -0.67395 3.9 -2.3 0.66365 0.66365 0.331825 -0.66365 4 -2.3 0.653247 0.653247 0.326623 -0.653247 4.1 -2.3 0.64275 0.64275 0.321375 -0.64275 4.2 -2.3 0.632168 0.632168 0.316084 -0.632168 4.3 -2.3 0.621512 0.621512 0.310756 -0.621512 4.4 -2.3 0.610791 0.610791 0.305396 -0.610791 4.5 -2.3 0.600015 0.600015 0.300008 -0.600015 4.6 -2.3 0.589194 0.589194 0.294597 -0.589194 4.7 -2.3 0.578336 0.578336 0.289168 -0.578336 4.8 -2.3 0.567451 0.567451 0.283726 -0.567451 4.9 -2.3 0.556549 0.556549 0.278275 -0.556549 -5 -2.2 0.550571 0.550571 0.275285 -0.550571 -4.9 -2.2 0.561581 0.561581 0.28079 -0.561581 -4.8 -2.2 0.572582 0.572582 0.286291 -0.572582 -4.7 -2.2 0.583565 0.583565 0.291782 -0.583565 -4.6 -2.2 0.594521 0.594521 0.29726 -0.594521 -4.5 -2.2 0.60544 0.60544 0.30272 -0.60544 -4.4 -2.2 0.616313 0.616313 0.308157 -0.616313 -4.3 -2.2 0.627131 0.627131 0.313565 -0.627131 -4.2 -2.2 0.637883 0.637883 0.318942 -0.637883 -4.1 -2.2 0.64856 0.64856 0.32428 -0.64856 -4 -2.2 0.659153 0.659153 0.329576 -0.659153 -3.9 -2.2 0.66965 0.66965 0.334825 -0.66965 -3.8 -2.2 0.680042 0.680042 0.340021 -0.680042 -3.7 -2.2 0.69032 0.69032 0.34516 -0.69032 -3.6 -2.2 0.700473 0.700473 0.350236 -0.700473 -3.5 -2.2 0.71049 0.71049 0.355245 -0.71049 -3.4 -2.2 0.720363 0.720363 0.360182 -0.720363 -3.3 -2.2 0.730081 0.730081 0.36504 -0.730081 -3.2 -2.2 0.739634 0.739634 0.369817 -0.739634 -3.1 -2.2 0.749012 0.749012 0.374506 -0.749012 -3 -2.2 0.758206 0.758206 0.379103 -0.758206 -2.9 -2.2 0.767206 0.767206 0.383603 -0.767206 -2.8 -2.2 0.776002 0.776002 0.388001 -0.776002 -2.7 -2.2 0.784585 0.784585 0.392293 -0.784585 -2.6 -2.2 0.792946 0.792946 0.396473 -0.792946 -2.5 -2.2 0.801076 0.801076 0.400538 -0.801076 -2.4 -2.2 0.808965 0.808965 0.404482 -0.808965 -2.3 -2.2 0.816605 0.816605 0.408302 -0.816605 -2.2 -2.2 0.823987 0.823987 0.411994 -0.823987 -2.1 -2.2 0.831104 0.831104 0.415552 -0.831104 -2 -2.2 0.837947 0.837947 0.418974 -0.837947 -1.9 -2.2 0.844509 0.844509 0.422254 -0.844509 -1.8 -2.2 0.850781 0.850781 0.425391 -0.850781 -1.7 -2.2 0.856758 0.856758 0.428379 -0.856758 -1.6 -2.2 0.862431 0.862431 0.431216 -0.862431 -1.5 -2.2 0.867795 0.867795 0.433897 -0.867795 -1.4 -2.2 0.872843 0.872843 0.436421 -0.872843 -1.3 -2.2 0.877569 0.877569 0.438784 -0.877569 -1.2 -2.2 0.881968 0.881968 0.440984 -0.881968 -1.1 -2.2 0.886034 0.886034 0.443017 -0.886034 -1 -2.2 0.889763 0.889763 0.444882 -0.889763 -0.9 -2.2 0.893151 0.893151 0.446575 -0.893151 -0.8 -2.2 0.896193 0.896193 0.448096 -0.896193 -0.7 -2.2 0.898885 0.898885 0.449443 -0.898885 -0.6 -2.2 0.901225 0.901225 0.450613 -0.901225 -0.5 -2.2 0.90321 0.90321 0.451605 -0.90321 -0.4 -2.2 0.904837 0.904837 0.452419 -0.904837 -0.3 -2.2 0.906105 0.906105 0.453053 -0.906105 -0.2 -2.2 0.907012 0.907012 0.453506 -0.907012 -0.1 -2.2 0.907556 0.907556 0.453778 -0.907556 0 -2.2 0.907738 0.907738 0.453869 -0.907738 0.1 -2.2 0.907556 0.907556 0.453778 -0.907556 0.2 -2.2 0.907012 0.907012 0.453506 -0.907012 0.3 -2.2 0.906105 0.906105 0.453053 -0.906105 0.4 -2.2 0.904837 0.904837 0.452419 -0.904837 0.5 -2.2 0.90321 0.90321 0.451605 -0.90321 0.6 -2.2 0.901225 0.901225 0.450613 -0.901225 0.7 -2.2 0.898885 0.898885 0.449443 -0.898885 0.8 -2.2 0.896193 0.896193 0.448096 -0.896193 0.9 -2.2 0.893151 0.893151 0.446575 -0.893151 1 -2.2 0.889763 0.889763 0.444882 -0.889763 1.1 -2.2 0.886034 0.886034 0.443017 -0.886034 1.2 -2.2 0.881968 0.881968 0.440984 -0.881968 1.3 -2.2 0.877569 0.877569 0.438784 -0.877569 1.4 -2.2 0.872843 0.872843 0.436421 -0.872843 1.5 -2.2 0.867795 0.867795 0.433897 -0.867795 1.6 -2.2 0.862431 0.862431 0.431216 -0.862431 1.7 -2.2 0.856758 0.856758 0.428379 -0.856758 1.8 -2.2 0.850781 0.850781 0.425391 -0.850781 1.9 -2.2 0.844509 0.844509 0.422254 -0.844509 2 -2.2 0.837947 0.837947 0.418974 -0.837947 2.1 -2.2 0.831104 0.831104 0.415552 -0.831104 2.2 -2.2 0.823987 0.823987 0.411994 -0.823987 2.3 -2.2 0.816605 0.816605 0.408302 -0.816605 2.4 -2.2 0.808965 0.808965 0.404482 -0.808965 2.5 -2.2 0.801076 0.801076 0.400538 -0.801076 2.6 -2.2 0.792946 0.792946 0.396473 -0.792946 2.7 -2.2 0.784585 0.784585 0.392293 -0.784585 2.8 -2.2 0.776002 0.776002 0.388001 -0.776002 2.9 -2.2 0.767206 0.767206 0.383603 -0.767206 3 -2.2 0.758206 0.758206 0.379103 -0.758206 3.1 -2.2 0.749012 0.749012 0.374506 -0.749012 3.2 -2.2 0.739634 0.739634 0.369817 -0.739634 3.3 -2.2 0.730081 0.730081 0.36504 -0.730081 3.4 -2.2 0.720363 0.720363 0.360182 -0.720363 3.5 -2.2 0.71049 0.71049 0.355245 -0.71049 3.6 -2.2 0.700473 0.700473 0.350236 -0.700473 3.7 -2.2 0.69032 0.69032 0.34516 -0.69032 3.8 -2.2 0.680042 0.680042 0.340021 -0.680042 3.9 -2.2 0.66965 0.66965 0.334825 -0.66965 4 -2.2 0.659153 0.659153 0.329576 -0.659153 4.1 -2.2 0.64856 0.64856 0.32428 -0.64856 4.2 -2.2 0.637883 0.637883 0.318942 -0.637883 4.3 -2.2 0.627131 0.627131 0.313565 -0.627131 4.4 -2.2 0.616313 0.616313 0.308157 -0.616313 4.5 -2.2 0.60544 0.60544 0.30272 -0.60544 4.6 -2.2 0.594521 0.594521 0.29726 -0.594521 4.7 -2.2 0.583565 0.583565 0.291782 -0.583565 4.8 -2.2 0.572582 0.572582 0.286291 -0.572582 4.9 -2.2 0.561581 0.561581 0.28079 -0.561581 -5 -2.1 0.555326 0.555326 0.277663 -0.555326 -4.9 -2.1 0.566431 0.566431 0.283216 -0.566431 -4.8 -2.1 0.577527 0.577527 0.288764 -0.577527 -4.7 -2.1 0.588605 0.588605 0.294302 -0.588605 -4.6 -2.1 0.599655 0.599655 0.299828 -0.599655 -4.5 -2.1 0.610669 0.610669 0.305335 -0.610669 -4.4 -2.1 0.621636 0.621636 0.310818 -0.621636 -4.3 -2.1 0.632547 0.632547 0.316274 -0.632547 -4.2 -2.1 0.643393 0.643393 0.321696 -0.643393 -4.1 -2.1 0.654162 0.654162 0.327081 -0.654162 -4 -2.1 0.664846 0.664846 0.332423 -0.664846 -3.9 -2.1 0.675434 0.675434 0.337717 -0.675434 -3.8 -2.1 0.685916 0.685916 0.342958 -0.685916 -3.7 -2.1 0.696282 0.696282 0.348141 -0.696282 -3.6 -2.1 0.706523 0.706523 0.353261 -0.706523 -3.5 -2.1 0.716627 0.716627 0.358313 -0.716627 -3.4 -2.1 0.726585 0.726585 0.363292 -0.726585 -3.3 -2.1 0.736387 0.736387 0.368193 -0.736387 -3.2 -2.1 0.746022 0.746022 0.373011 -0.746022 -3.1 -2.1 0.755481 0.755481 0.377741 -0.755481 -3 -2.1 0.764755 0.764755 0.382377 -0.764755 -2.9 -2.1 0.773832 0.773832 0.386916 -0.773832 -2.8 -2.1 0.782705 0.782705 0.391352 -0.782705 -2.7 -2.1 0.791362 0.791362 0.395681 -0.791362 -2.6 -2.1 0.799795 0.799795 0.399897 -0.799795 -2.5 -2.1 0.807995 0.807995 0.403997 -0.807995 -2.4 -2.1 0.815952 0.815952 0.407976 -0.815952 -2.3 -2.1 0.823658 0.823658 0.411829 -0.823658 -2.2 -2.1 0.831104 0.831104 0.415552 -0.831104 -2.1 -2.1 0.838283 0.838283 0.419141 -0.838283 -2 -2.1 0.845185 0.845185 0.422592 -0.845185 -1.9 -2.1 0.851803 0.851803 0.425901 -0.851803 -1.8 -2.1 0.85813 0.85813 0.429065 -0.85813 -1.7 -2.1 0.864158 0.864158 0.432079 -0.864158 -1.6 -2.1 0.86988 0.86988 0.43494 -0.86988 -1.5 -2.1 0.87529 0.87529 0.437645 -0.87529 -1.4 -2.1 0.880381 0.880381 0.440191 -0.880381 -1.3 -2.1 0.885148 0.885148 0.442574 -0.885148 -1.2 -2.1 0.889585 0.889585 0.444793 -0.889585 -1.1 -2.1 0.893687 0.893687 0.446843 -0.893687 -1 -2.1 0.897448 0.897448 0.448724 -0.897448 -0.9 -2.1 0.900865 0.900865 0.450432 -0.900865 -0.8 -2.1 0.903933 0.903933 0.451967 -0.903933 -0.7 -2.1 0.906649 0.906649 0.453324 -0.906649 -0.6 -2.1 0.909009 0.909009 0.454505 -0.909009 -0.5 -2.1 0.911011 0.911011 0.455506 -0.911011 -0.4 -2.1 0.912653 0.912653 0.456326 -0.912653 -0.3 -2.1 0.913931 0.913931 0.456966 -0.913931 -0.2 -2.1 0.914846 0.914846 0.457423 -0.914846 -0.1 -2.1 0.915395 0.915395 0.457697 -0.915395 0 -2.1 0.915578 0.915578 0.457789 -0.915578 0.1 -2.1 0.915395 0.915395 0.457697 -0.915395 0.2 -2.1 0.914846 0.914846 0.457423 -0.914846 0.3 -2.1 0.913931 0.913931 0.456966 -0.913931 0.4 -2.1 0.912653 0.912653 0.456326 -0.912653 0.5 -2.1 0.911011 0.911011 0.455506 -0.911011 0.6 -2.1 0.909009 0.909009 0.454505 -0.909009 0.7 -2.1 0.906649 0.906649 0.453324 -0.906649 0.8 -2.1 0.903933 0.903933 0.451967 -0.903933 0.9 -2.1 0.900865 0.900865 0.450432 -0.900865 1 -2.1 0.897448 0.897448 0.448724 -0.897448 1.1 -2.1 0.893687 0.893687 0.446843 -0.893687 1.2 -2.1 0.889585 0.889585 0.444793 -0.889585 1.3 -2.1 0.885148 0.885148 0.442574 -0.885148 1.4 -2.1 0.880381 0.880381 0.440191 -0.880381 1.5 -2.1 0.87529 0.87529 0.437645 -0.87529 1.6 -2.1 0.86988 0.86988 0.43494 -0.86988 1.7 -2.1 0.864158 0.864158 0.432079 -0.864158 1.8 -2.1 0.85813 0.85813 0.429065 -0.85813 1.9 -2.1 0.851803 0.851803 0.425901 -0.851803 2 -2.1 0.845185 0.845185 0.422592 -0.845185 2.1 -2.1 0.838283 0.838283 0.419141 -0.838283 2.2 -2.1 0.831104 0.831104 0.415552 -0.831104 2.3 -2.1 0.823658 0.823658 0.411829 -0.823658 2.4 -2.1 0.815952 0.815952 0.407976 -0.815952 2.5 -2.1 0.807995 0.807995 0.403997 -0.807995 2.6 -2.1 0.799795 0.799795 0.399897 -0.799795 2.7 -2.1 0.791362 0.791362 0.395681 -0.791362 2.8 -2.1 0.782705 0.782705 0.391352 -0.782705 2.9 -2.1 0.773832 0.773832 0.386916 -0.773832 3 -2.1 0.764755 0.764755 0.382377 -0.764755 3.1 -2.1 0.755481 0.755481 0.377741 -0.755481 3.2 -2.1 0.746022 0.746022 0.373011 -0.746022 3.3 -2.1 0.736387 0.736387 0.368193 -0.736387 3.4 -2.1 0.726585 0.726585 0.363292 -0.726585 3.5 -2.1 0.716627 0.716627 0.358313 -0.716627 3.6 -2.1 0.706523 0.706523 0.353261 -0.706523 3.7 -2.1 0.696282 0.696282 0.348141 -0.696282 3.8 -2.1 0.685916 0.685916 0.342958 -0.685916 3.9 -2.1 0.675434 0.675434 0.337717 -0.675434 4 -2.1 0.664846 0.664846 0.332423 -0.664846 4.1 -2.1 0.654162 0.654162 0.327081 -0.654162 4.2 -2.1 0.643393 0.643393 0.321696 -0.643393 4.3 -2.1 0.632547 0.632547 0.316274 -0.632547 4.4 -2.1 0.621636 0.621636 0.310818 -0.621636 4.5 -2.1 0.610669 0.610669 0.305335 -0.610669 4.6 -2.1 0.599655 0.599655 0.299828 -0.599655 4.7 -2.1 0.588605 0.588605 0.294302 -0.588605 4.8 -2.1 0.577527 0.577527 0.288764 -0.577527 4.9 -2.1 0.566431 0.566431 0.283216 -0.566431 -5 -2 0.559898 0.559898 0.279949 -0.559898 -4.9 -2 0.571095 0.571095 0.285547 -0.571095 -4.8 -2 0.582282 0.582282 0.291141 -0.582282 -4.7 -2 0.593451 0.593451 0.296726 -0.593451 -4.6 -2 0.604593 0.604593 0.302296 -0.604593 -4.5 -2 0.615697 0.615697 0.307849 -0.615697 -4.4 -2 0.626755 0.626755 0.313377 -0.626755 -4.3 -2 0.637756 0.637756 0.318878 -0.637756 -4.2 -2 0.64869 0.64869 0.324345 -0.64869 -4.1 -2 0.659548 0.659548 0.329774 -0.659548 -4 -2 0.67032 0.67032 0.33516 -0.67032 -3.9 -2 0.680995 0.680995 0.340498 -0.680995 -3.8 -2 0.691564 0.691564 0.345782 -0.691564 -3.7 -2 0.702015 0.702015 0.351008 -0.702015 -3.6 -2 0.71234 0.71234 0.35617 -0.71234 -3.5 -2 0.722527 0.722527 0.361264 -0.722527 -3.4 -2 0.732567 0.732567 0.366284 -0.732567 -3.3 -2 0.74245 0.74245 0.371225 -0.74245 -3.2 -2 0.752165 0.752165 0.376082 -0.752165 -3.1 -2 0.761702 0.761702 0.380851 -0.761702 -3 -2 0.771052 0.771052 0.385526 -0.771052 -2.9 -2 0.780204 0.780204 0.390102 -0.780204 -2.8 -2 0.789149 0.789149 0.394575 -0.789149 -2.7 -2 0.797878 0.797878 0.398939 -0.797878 -2.6 -2 0.80638 0.80638 0.40319 -0.80638 -2.5 -2 0.814647 0.814647 0.407324 -0.814647 -2.4 -2 0.82267 0.82267 0.411335 -0.82267 -2.3 -2 0.83044 0.83044 0.41522 -0.83044 -2.2 -2 0.837947 0.837947 0.418974 -0.837947 -2.1 -2 0.845185 0.845185 0.422592 -0.845185 -2 -2 0.852144 0.852144 0.426072 -0.852144 -1.9 -2 0.858817 0.858817 0.429408 -0.858817 -1.8 -2 0.865195 0.865195 0.432598 -0.865195 -1.7 -2 0.871273 0.871273 0.435636 -0.871273 -1.6 -2 0.877042 0.877042 0.438521 -0.877042 -1.5 -2 0.882497 0.882497 0.441248 -0.882497 -1.4 -2 0.88763 0.88763 0.443815 -0.88763 -1.3 -2 0.892436 0.892436 0.446218 -0.892436 -1.2 -2 0.89691 0.89691 0.448455 -0.89691 -1.1 -2 0.901045 0.901045 0.450523 -0.901045 -1 -2 0.904837 0.904837 0.452419 -0.904837 -0.9 -2 0.908282 0.908282 0.454141 -0.908282 -0.8 -2 0.911376 0.911376 0.455688 -0.911376 -0.7 -2 0.914114 0.914114 0.457057 -0.914114 -0.6 -2 0.916494 0.916494 0.458247 -0.916494 -0.5 -2 0.918512 0.918512 0.459256 -0.918512 -0.4 -2 0.920167 0.920167 0.460084 -0.920167 -0.3 -2 0.921456 0.921456 0.460728 -0.921456 -0.2 -2 0.922378 0.922378 0.461189 -0.922378 -0.1 -2 0.922932 0.922932 0.461466 -0.922932 0 -2 0.923116 0.923116 0.461558 -0.923116 0.1 -2 0.922932 0.922932 0.461466 -0.922932 0.2 -2 0.922378 0.922378 0.461189 -0.922378 0.3 -2 0.921456 0.921456 0.460728 -0.921456 0.4 -2 0.920167 0.920167 0.460084 -0.920167 0.5 -2 0.918512 0.918512 0.459256 -0.918512 0.6 -2 0.916494 0.916494 0.458247 -0.916494 0.7 -2 0.914114 0.914114 0.457057 -0.914114 0.8 -2 0.911376 0.911376 0.455688 -0.911376 0.9 -2 0.908282 0.908282 0.454141 -0.908282 1 -2 0.904837 0.904837 0.452419 -0.904837 1.1 -2 0.901045 0.901045 0.450523 -0.901045 1.2 -2 0.89691 0.89691 0.448455 -0.89691 1.3 -2 0.892436 0.892436 0.446218 -0.892436 1.4 -2 0.88763 0.88763 0.443815 -0.88763 1.5 -2 0.882497 0.882497 0.441248 -0.882497 1.6 -2 0.877042 0.877042 0.438521 -0.877042 1.7 -2 0.871273 0.871273 0.435636 -0.871273 1.8 -2 0.865195 0.865195 0.432598 -0.865195 1.9 -2 0.858817 0.858817 0.429408 -0.858817 2 -2 0.852144 0.852144 0.426072 -0.852144 2.1 -2 0.845185 0.845185 0.422592 -0.845185 2.2 -2 0.837947 0.837947 0.418974 -0.837947 2.3 -2 0.83044 0.83044 0.41522 -0.83044 2.4 -2 0.82267 0.82267 0.411335 -0.82267 2.5 -2 0.814647 0.814647 0.407324 -0.814647 2.6 -2 0.80638 0.80638 0.40319 -0.80638 2.7 -2 0.797878 0.797878 0.398939 -0.797878 2.8 -2 0.789149 0.789149 0.394575 -0.789149 2.9 -2 0.780204 0.780204 0.390102 -0.780204 3 -2 0.771052 0.771052 0.385526 -0.771052 3.1 -2 0.761702 0.761702 0.380851 -0.761702 3.2 -2 0.752165 0.752165 0.376082 -0.752165 3.3 -2 0.74245 0.74245 0.371225 -0.74245 3.4 -2 0.732567 0.732567 0.366284 -0.732567 3.5 -2 0.722527 0.722527 0.361264 -0.722527 3.6 -2 0.71234 0.71234 0.35617 -0.71234 3.7 -2 0.702015 0.702015 0.351008 -0.702015 3.8 -2 0.691564 0.691564 0.345782 -0.691564 3.9 -2 0.680995 0.680995 0.340498 -0.680995 4 -2 0.67032 0.67032 0.33516 -0.67032 4.1 -2 0.659548 0.659548 0.329774 -0.659548 4.2 -2 0.64869 0.64869 0.324345 -0.64869 4.3 -2 0.637756 0.637756 0.318878 -0.637756 4.4 -2 0.626755 0.626755 0.313377 -0.626755 4.5 -2 0.615697 0.615697 0.307849 -0.615697 4.6 -2 0.604593 0.604593 0.302296 -0.604593 4.7 -2 0.593451 0.593451 0.296726 -0.593451 4.8 -2 0.582282 0.582282 0.291141 -0.582282 4.9 -2 0.571095 0.571095 0.285547 -0.571095 -5 -1.9 0.564283 0.564283 0.282141 -0.564283 -4.9 -1.9 0.575567 0.575567 0.287783 -0.575567 -4.8 -1.9 0.586842 0.586842 0.293421 -0.586842 -4.7 -1.9 0.598098 0.598098 0.299049 -0.598098 -4.6 -1.9 0.609327 0.609327 0.304664 -0.609327 -4.5 -1.9 0.620518 0.620518 0.310259 -0.620518 -4.4 -1.9 0.631663 0.631663 0.315831 -0.631663 -4.3 -1.9 0.64275 0.64275 0.321375 -0.64275 -4.2 -1.9 0.65377 0.65377 0.326885 -0.65377 -4.1 -1.9 0.664713 0.664713 0.332356 -0.664713 -4 -1.9 0.675569 0.675569 0.337784 -0.675569 -3.9 -1.9 0.686328 0.686328 0.343164 -0.686328 -3.8 -1.9 0.696979 0.696979 0.348489 -0.696979 -3.7 -1.9 0.707512 0.707512 0.353756 -0.707512 -3.6 -1.9 0.717918 0.717918 0.358959 -0.717918 -3.5 -1.9 0.728185 0.728185 0.364093 -0.728185 -3.4 -1.9 0.738304 0.738304 0.369152 -0.738304 -3.3 -1.9 0.748264 0.748264 0.374132 -0.748264 -3.2 -1.9 0.758054 0.758054 0.379027 -0.758054 -3.1 -1.9 0.767666 0.767666 0.383833 -0.767666 -3 -1.9 0.777089 0.777089 0.388545 -0.777089 -2.9 -1.9 0.786313 0.786313 0.393157 -0.786313 -2.8 -1.9 0.795329 0.795329 0.397664 -0.795329 -2.7 -1.9 0.804125 0.804125 0.402063 -0.804125 -2.6 -1.9 0.812695 0.812695 0.406347 -0.812695 -2.5 -1.9 0.821026 0.821026 0.410513 -0.821026 -2.4 -1.9 0.829112 0.829112 0.414556 -0.829112 -2.3 -1.9 0.836942 0.836942 0.418471 -0.836942 -2.2 -1.9 0.844509 0.844509 0.422254 -0.844509 -2.1 -1.9 0.851803 0.851803 0.425901 -0.851803 -2 -1.9 0.858817 0.858817 0.429408 -0.858817 -1.9 -1.9 0.865541 0.865541 0.432771 -0.865541 -1.8 -1.9 0.87197 0.87197 0.435985 -0.87197 -1.7 -1.9 0.878095 0.878095 0.439048 -0.878095 -1.6 -1.9 0.88391 0.88391 0.441955 -0.88391 -1.5 -1.9 0.889407 0.889407 0.444704 -0.889407 -1.4 -1.9 0.894581 0.894581 0.44729 -0.894581 -1.3 -1.9 0.899425 0.899425 0.449712 -0.899425 -1.2 -1.9 0.903933 0.903933 0.451967 -0.903933 -1.1 -1.9 0.908101 0.908101 0.45405 -0.908101 -1 -1.9 0.911923 0.911923 0.455961 -0.911923 -0.9 -1.9 0.915395 0.915395 0.457697 -0.915395 -0.8 -1.9 0.918512 0.918512 0.459256 -0.918512 -0.7 -1.9 0.921272 0.921272 0.460636 -0.921272 -0.6 -1.9 0.92367 0.92367 0.461835 -0.92367 -0.5 -1.9 0.925705 0.925705 0.462852 -0.925705 -0.4 -1.9 0.927372 0.927372 0.463686 -0.927372 -0.3 -1.9 0.928672 0.928672 0.464336 -0.928672 -0.2 -1.9 0.929601 0.929601 0.4648 -0.929601 -0.1 -1.9 0.930159 0.930159 0.465079 -0.930159 0 -1.9 0.930345 0.930345 0.465172 -0.930345 0.1 -1.9 0.930159 0.930159 0.465079 -0.930159 0.2 -1.9 0.929601 0.929601 0.4648 -0.929601 0.3 -1.9 0.928672 0.928672 0.464336 -0.928672 0.4 -1.9 0.927372 0.927372 0.463686 -0.927372 0.5 -1.9 0.925705 0.925705 0.462852 -0.925705 0.6 -1.9 0.92367 0.92367 0.461835 -0.92367 0.7 -1.9 0.921272 0.921272 0.460636 -0.921272 0.8 -1.9 0.918512 0.918512 0.459256 -0.918512 0.9 -1.9 0.915395 0.915395 0.457697 -0.915395 1 -1.9 0.911923 0.911923 0.455961 -0.911923 1.1 -1.9 0.908101 0.908101 0.45405 -0.908101 1.2 -1.9 0.903933 0.903933 0.451967 -0.903933 1.3 -1.9 0.899425 0.899425 0.449712 -0.899425 1.4 -1.9 0.894581 0.894581 0.44729 -0.894581 1.5 -1.9 0.889407 0.889407 0.444704 -0.889407 1.6 -1.9 0.88391 0.88391 0.441955 -0.88391 1.7 -1.9 0.878095 0.878095 0.439048 -0.878095 1.8 -1.9 0.87197 0.87197 0.435985 -0.87197 1.9 -1.9 0.865541 0.865541 0.432771 -0.865541 2 -1.9 0.858817 0.858817 0.429408 -0.858817 2.1 -1.9 0.851803 0.851803 0.425901 -0.851803 2.2 -1.9 0.844509 0.844509 0.422254 -0.844509 2.3 -1.9 0.836942 0.836942 0.418471 -0.836942 2.4 -1.9 0.829112 0.829112 0.414556 -0.829112 2.5 -1.9 0.821026 0.821026 0.410513 -0.821026 2.6 -1.9 0.812695 0.812695 0.406347 -0.812695 2.7 -1.9 0.804125 0.804125 0.402063 -0.804125 2.8 -1.9 0.795329 0.795329 0.397664 -0.795329 2.9 -1.9 0.786313 0.786313 0.393157 -0.786313 3 -1.9 0.777089 0.777089 0.388545 -0.777089 3.1 -1.9 0.767666 0.767666 0.383833 -0.767666 3.2 -1.9 0.758054 0.758054 0.379027 -0.758054 3.3 -1.9 0.748264 0.748264 0.374132 -0.748264 3.4 -1.9 0.738304 0.738304 0.369152 -0.738304 3.5 -1.9 0.728185 0.728185 0.364093 -0.728185 3.6 -1.9 0.717918 0.717918 0.358959 -0.717918 3.7 -1.9 0.707512 0.707512 0.353756 -0.707512 3.8 -1.9 0.696979 0.696979 0.348489 -0.696979 3.9 -1.9 0.686328 0.686328 0.343164 -0.686328 4 -1.9 0.675569 0.675569 0.337784 -0.675569 4.1 -1.9 0.664713 0.664713 0.332356 -0.664713 4.2 -1.9 0.65377 0.65377 0.326885 -0.65377 4.3 -1.9 0.64275 0.64275 0.321375 -0.64275 4.4 -1.9 0.631663 0.631663 0.315831 -0.631663 4.5 -1.9 0.620518 0.620518 0.310259 -0.620518 4.6 -1.9 0.609327 0.609327 0.304664 -0.609327 4.7 -1.9 0.598098 0.598098 0.299049 -0.598098 4.8 -1.9 0.586842 0.586842 0.293421 -0.586842 4.9 -1.9 0.575567 0.575567 0.287783 -0.575567 -5 -1.8 0.568474 0.568474 0.284237 -0.568474 -4.9 -1.8 0.579842 0.579842 0.289921 -0.579842 -4.8 -1.8 0.591201 0.591201 0.2956 -0.591201 -4.7 -1.8 0.602541 0.602541 0.30127 -0.602541 -4.6 -1.8 0.613853 0.613853 0.306926 -0.613853 -4.5 -1.8 0.625127 0.625127 0.312564 -0.625127 -4.4 -1.8 0.636354 0.636354 0.318177 -0.636354 -4.3 -1.8 0.647524 0.647524 0.323762 -0.647524 -4.2 -1.8 0.658626 0.658626 0.329313 -0.658626 -4.1 -1.8 0.66965 0.66965 0.334825 -0.66965 -4 -1.8 0.680587 0.680587 0.340293 -0.680587 -3.9 -1.8 0.691425 0.691425 0.345713 -0.691425 -3.8 -1.8 0.702156 0.702156 0.351078 -0.702156 -3.7 -1.8 0.712767 0.712767 0.356384 -0.712767 -3.6 -1.8 0.72325 0.72325 0.361625 -0.72325 -3.5 -1.8 0.733594 0.733594 0.366797 -0.733594 -3.4 -1.8 0.743787 0.743787 0.371894 -0.743787 -3.3 -1.8 0.753821 0.753821 0.376911 -0.753821 -3.2 -1.8 0.763685 0.763685 0.381842 -0.763685 -3.1 -1.8 0.773368 0.773368 0.386684 -0.773368 -3 -1.8 0.782861 0.782861 0.391431 -0.782861 -2.9 -1.8 0.792154 0.792154 0.396077 -0.792154 -2.8 -1.8 0.801236 0.801236 0.400618 -0.801236 -2.7 -1.8 0.810098 0.810098 0.405049 -0.810098 -2.6 -1.8 0.818731 0.818731 0.409365 -0.818731 -2.5 -1.8 0.827125 0.827125 0.413562 -0.827125 -2.4 -1.8 0.83527 0.83527 0.417635 -0.83527 -2.3 -1.8 0.843159 0.843159 0.421579 -0.843159 -2.2 -1.8 0.850781 0.850781 0.425391 -0.850781 -2.1 -1.8 0.85813 0.85813 0.429065 -0.85813 -2 -1.8 0.865195 0.865195 0.432598 -0.865195 -1.9 -1.8 0.87197 0.87197 0.435985 -0.87197 -1.8 -1.8 0.878447 0.878447 0.439223 -0.878447 -1.7 -1.8 0.884617 0.884617 0.442309 -0.884617 -1.6 -1.8 0.890475 0.890475 0.445238 -0.890475 -1.5 -1.8 0.896013 0.896013 0.448007 -0.896013 -1.4 -1.8 0.901225 0.901225 0.450613 -0.901225 -1.3 -1.8 0.906105 0.906105 0.453053 -0.906105 -1.2 -1.8 0.910647 0.910647 0.455323 -0.910647 -1.1 -1.8 0.914846 0.914846 0.457423 -0.914846 -1 -1.8 0.918696 0.918696 0.459348 -0.918696 -0.9 -1.8 0.922194 0.922194 0.461097 -0.922194 -0.8 -1.8 0.925334 0.925334 0.462667 -0.925334 -0.7 -1.8 0.928115 0.928115 0.464057 -0.928115 -0.6 -1.8 0.930531 0.930531 0.465265 -0.930531 -0.5 -1.8 0.93258 0.93258 0.46629 -0.93258 -0.4 -1.8 0.93426 0.93426 0.46713 -0.93426 -0.3 -1.8 0.935569 0.935569 0.467785 -0.935569 -0.2 -1.8 0.936505 0.936505 0.468253 -0.936505 -0.1 -1.8 0.937067 0.937067 0.468534 -0.937067 0 -1.8 0.937255 0.937255 0.468627 -0.937255 0.1 -1.8 0.937067 0.937067 0.468534 -0.937067 0.2 -1.8 0.936505 0.936505 0.468253 -0.936505 0.3 -1.8 0.935569 0.935569 0.467785 -0.935569 0.4 -1.8 0.93426 0.93426 0.46713 -0.93426 0.5 -1.8 0.93258 0.93258 0.46629 -0.93258 0.6 -1.8 0.930531 0.930531 0.465265 -0.930531 0.7 -1.8 0.928115 0.928115 0.464057 -0.928115 0.8 -1.8 0.925334 0.925334 0.462667 -0.925334 0.9 -1.8 0.922194 0.922194 0.461097 -0.922194 1 -1.8 0.918696 0.918696 0.459348 -0.918696 1.1 -1.8 0.914846 0.914846 0.457423 -0.914846 1.2 -1.8 0.910647 0.910647 0.455323 -0.910647 1.3 -1.8 0.906105 0.906105 0.453053 -0.906105 1.4 -1.8 0.901225 0.901225 0.450613 -0.901225 1.5 -1.8 0.896013 0.896013 0.448007 -0.896013 1.6 -1.8 0.890475 0.890475 0.445238 -0.890475 1.7 -1.8 0.884617 0.884617 0.442309 -0.884617 1.8 -1.8 0.878447 0.878447 0.439223 -0.878447 1.9 -1.8 0.87197 0.87197 0.435985 -0.87197 2 -1.8 0.865195 0.865195 0.432598 -0.865195 2.1 -1.8 0.85813 0.85813 0.429065 -0.85813 2.2 -1.8 0.850781 0.850781 0.425391 -0.850781 2.3 -1.8 0.843159 0.843159 0.421579 -0.843159 2.4 -1.8 0.83527 0.83527 0.417635 -0.83527 2.5 -1.8 0.827125 0.827125 0.413562 -0.827125 2.6 -1.8 0.818731 0.818731 0.409365 -0.818731 2.7 -1.8 0.810098 0.810098 0.405049 -0.810098 2.8 -1.8 0.801236 0.801236 0.400618 -0.801236 2.9 -1.8 0.792154 0.792154 0.396077 -0.792154 3 -1.8 0.782861 0.782861 0.391431 -0.782861 3.1 -1.8 0.773368 0.773368 0.386684 -0.773368 3.2 -1.8 0.763685 0.763685 0.381842 -0.763685 3.3 -1.8 0.753821 0.753821 0.376911 -0.753821 3.4 -1.8 0.743787 0.743787 0.371894 -0.743787 3.5 -1.8 0.733594 0.733594 0.366797 -0.733594 3.6 -1.8 0.72325 0.72325 0.361625 -0.72325 3.7 -1.8 0.712767 0.712767 0.356384 -0.712767 3.8 -1.8 0.702156 0.702156 0.351078 -0.702156 3.9 -1.8 0.691425 0.691425 0.345713 -0.691425 4 -1.8 0.680587 0.680587 0.340293 -0.680587 4.1 -1.8 0.66965 0.66965 0.334825 -0.66965 4.2 -1.8 0.658626 0.658626 0.329313 -0.658626 4.3 -1.8 0.647524 0.647524 0.323762 -0.647524 4.4 -1.8 0.636354 0.636354 0.318177 -0.636354 4.5 -1.8 0.625127 0.625127 0.312564 -0.625127 4.6 -1.8 0.613853 0.613853 0.306926 -0.613853 4.7 -1.8 0.602541 0.602541 0.30127 -0.602541 4.8 -1.8 0.591201 0.591201 0.2956 -0.591201 4.9 -1.8 0.579842 0.579842 0.289921 -0.579842 -5 -1.7 0.572467 0.572467 0.286234 -0.572467 -4.9 -1.7 0.583915 0.583915 0.291957 -0.583915 -4.8 -1.7 0.595353 0.595353 0.297677 -0.595353 -4.7 -1.7 0.606773 0.606773 0.303387 -0.606773 -4.6 -1.7 0.618165 0.618165 0.309082 -0.618165 -4.5 -1.7 0.629519 0.629519 0.314759 -0.629519 -4.4 -1.7 0.640824 0.640824 0.320412 -0.640824 -4.3 -1.7 0.652072 0.652072 0.326036 -0.652072 -4.2 -1.7 0.663252 0.663252 0.331626 -0.663252 -4.1 -1.7 0.674354 0.674354 0.337177 -0.674354 -4 -1.7 0.685368 0.685368 0.342684 -0.685368 -3.9 -1.7 0.696282 0.696282 0.348141 -0.696282 -3.8 -1.7 0.707088 0.707088 0.353544 -0.707088 -3.7 -1.7 0.717774 0.717774 0.358887 -0.717774 -3.6 -1.7 0.728331 0.728331 0.364165 -0.728331 -3.5 -1.7 0.738747 0.738747 0.369373 -0.738747 -3.4 -1.7 0.749012 0.749012 0.374506 -0.749012 -3.3 -1.7 0.759117 0.759117 0.379558 -0.759117 -3.2 -1.7 0.769049 0.769049 0.384525 -0.769049 -3.1 -1.7 0.778801 0.778801 0.3894 -0.778801 -3 -1.7 0.78836 0.78836 0.39418 -0.78836 -2.9 -1.7 0.797718 0.797718 0.398859 -0.797718 -2.8 -1.7 0.806864 0.806864 0.403432 -0.806864 -2.7 -1.7 0.815789 0.815789 0.407894 -0.815789 -2.6 -1.7 0.824482 0.824482 0.412241 -0.824482 -2.5 -1.7 0.832935 0.832935 0.416467 -0.832935 -2.4 -1.7 0.841138 0.841138 0.420569 -0.841138 -2.3 -1.7 0.849082 0.849082 0.424541 -0.849082 -2.2 -1.7 0.856758 0.856758 0.428379 -0.856758 -2.1 -1.7 0.864158 0.864158 0.432079 -0.864158 -2 -1.7 0.871273 0.871273 0.435636 -0.871273 -1.9 -1.7 0.878095 0.878095 0.439048 -0.878095 -1.8 -1.7 0.884617 0.884617 0.442309 -0.884617 -1.7 -1.7 0.890831 0.890831 0.445416 -0.890831 -1.6 -1.7 0.89673 0.89673 0.448365 -0.89673 -1.5 -1.7 0.902307 0.902307 0.451154 -0.902307 -1.4 -1.7 0.907556 0.907556 0.453778 -0.907556 -1.3 -1.7 0.91247 0.91247 0.456235 -0.91247 -1.2 -1.7 0.917044 0.917044 0.458522 -0.917044 -1.1 -1.7 0.921272 0.921272 0.460636 -0.921272 -1 -1.7 0.925149 0.925149 0.462575 -0.925149 -0.9 -1.7 0.928672 0.928672 0.464336 -0.928672 -0.8 -1.7 0.931835 0.931835 0.465917 -0.931835 -0.7 -1.7 0.934634 0.934634 0.467317 -0.934634 -0.6 -1.7 0.937067 0.937067 0.468534 -0.937067 -0.5 -1.7 0.939131 0.939131 0.469566 -0.939131 -0.4 -1.7 0.940823 0.940823 0.470412 -0.940823 -0.3 -1.7 0.942141 0.942141 0.471071 -0.942141 -0.2 -1.7 0.943084 0.943084 0.471542 -0.943084 -0.1 -1.7 0.94365 0.94365 0.471825 -0.94365 0 -1.7 0.943839 0.943839 0.471919 -0.943839 0.1 -1.7 0.94365 0.94365 0.471825 -0.94365 0.2 -1.7 0.943084 0.943084 0.471542 -0.943084 0.3 -1.7 0.942141 0.942141 0.471071 -0.942141 0.4 -1.7 0.940823 0.940823 0.470412 -0.940823 0.5 -1.7 0.939131 0.939131 0.469566 -0.939131 0.6 -1.7 0.937067 0.937067 0.468534 -0.937067 0.7 -1.7 0.934634 0.934634 0.467317 -0.934634 0.8 -1.7 0.931835 0.931835 0.465917 -0.931835 0.9 -1.7 0.928672 0.928672 0.464336 -0.928672 1 -1.7 0.925149 0.925149 0.462575 -0.925149 1.1 -1.7 0.921272 0.921272 0.460636 -0.921272 1.2 -1.7 0.917044 0.917044 0.458522 -0.917044 1.3 -1.7 0.91247 0.91247 0.456235 -0.91247 1.4 -1.7 0.907556 0.907556 0.453778 -0.907556 1.5 -1.7 0.902307 0.902307 0.451154 -0.902307 1.6 -1.7 0.89673 0.89673 0.448365 -0.89673 1.7 -1.7 0.890831 0.890831 0.445416 -0.890831 1.8 -1.7 0.884617 0.884617 0.442309 -0.884617 1.9 -1.7 0.878095 0.878095 0.439048 -0.878095 2 -1.7 0.871273 0.871273 0.435636 -0.871273 2.1 -1.7 0.864158 0.864158 0.432079 -0.864158 2.2 -1.7 0.856758 0.856758 0.428379 -0.856758 2.3 -1.7 0.849082 0.849082 0.424541 -0.849082 2.4 -1.7 0.841138 0.841138 0.420569 -0.841138 2.5 -1.7 0.832935 0.832935 0.416467 -0.832935 2.6 -1.7 0.824482 0.824482 0.412241 -0.824482 2.7 -1.7 0.815789 0.815789 0.407894 -0.815789 2.8 -1.7 0.806864 0.806864 0.403432 -0.806864 2.9 -1.7 0.797718 0.797718 0.398859 -0.797718 3 -1.7 0.78836 0.78836 0.39418 -0.78836 3.1 -1.7 0.778801 0.778801 0.3894 -0.778801 3.2 -1.7 0.769049 0.769049 0.384525 -0.769049 3.3 -1.7 0.759117 0.759117 0.379558 -0.759117 3.4 -1.7 0.749012 0.749012 0.374506 -0.749012 3.5 -1.7 0.738747 0.738747 0.369373 -0.738747 3.6 -1.7 0.728331 0.728331 0.364165 -0.728331 3.7 -1.7 0.717774 0.717774 0.358887 -0.717774 3.8 -1.7 0.707088 0.707088 0.353544 -0.707088 3.9 -1.7 0.696282 0.696282 0.348141 -0.696282 4 -1.7 0.685368 0.685368 0.342684 -0.685368 4.1 -1.7 0.674354 0.674354 0.337177 -0.674354 4.2 -1.7 0.663252 0.663252 0.331626 -0.663252 4.3 -1.7 0.652072 0.652072 0.326036 -0.652072 4.4 -1.7 0.640824 0.640824 0.320412 -0.640824 4.5 -1.7 0.629519 0.629519 0.314759 -0.629519 4.6 -1.7 0.618165 0.618165 0.309082 -0.618165 4.7 -1.7 0.606773 0.606773 0.303387 -0.606773 4.8 -1.7 0.595353 0.595353 0.297677 -0.595353 4.9 -1.7 0.583915 0.583915 0.291957 -0.583915 -5 -1.6 0.576258 0.576258 0.288129 -0.576258 -4.9 -1.6 0.587781 0.587781 0.293891 -0.587781 -4.8 -1.6 0.599296 0.599296 0.299648 -0.599296 -4.7 -1.6 0.610791 0.610791 0.305396 -0.610791 -4.6 -1.6 0.622258 0.622258 0.311129 -0.622258 -4.5 -1.6 0.633687 0.633687 0.316844 -0.633687 -4.4 -1.6 0.645068 0.645068 0.322534 -0.645068 -4.3 -1.6 0.65639 0.65639 0.328195 -0.65639 -4.2 -1.6 0.667644 0.667644 0.333822 -0.667644 -4.1 -1.6 0.67882 0.67882 0.33941 -0.67882 -4 -1.6 0.689906 0.689906 0.344953 -0.689906 -3.9 -1.6 0.700893 0.700893 0.350447 -0.700893 -3.8 -1.6 0.71177 0.71177 0.355885 -0.71177 -3.7 -1.6 0.722527 0.722527 0.361264 -0.722527 -3.6 -1.6 0.733154 0.733154 0.366577 -0.733154 -3.5 -1.6 0.743639 0.743639 0.371819 -0.743639 -3.4 -1.6 0.753972 0.753972 0.376986 -0.753972 -3.3 -1.6 0.764143 0.764143 0.382072 -0.764143 -3.2 -1.6 0.774142 0.774142 0.387071 -0.774142 -3.1 -1.6 0.783958 0.783958 0.391979 -0.783958 -3 -1.6 0.793581 0.793581 0.39679 -0.793581 -2.9 -1.6 0.803 0.803 0.4015 -0.803 -2.8 -1.6 0.812207 0.812207 0.406104 -0.812207 -2.7 -1.6 0.821191 0.821191 0.410595 -0.821191 -2.6 -1.6 0.829942 0.829942 0.414971 -0.829942 -2.5 -1.6 0.83845 0.83845 0.419225 -0.83845 -2.4 -1.6 0.846707 0.846707 0.423354 -0.846707 -2.3 -1.6 0.854704 0.854704 0.427352 -0.854704 -2.2 -1.6 0.862431 0.862431 0.431216 -0.862431 -2.1 -1.6 0.86988 0.86988 0.43494 -0.86988 -2 -1.6 0.877042 0.877042 0.438521 -0.877042 -1.9 -1.6 0.88391 0.88391 0.441955 -0.88391 -1.8 -1.6 0.890475 0.890475 0.445238 -0.890475 -1.7 -1.6 0.89673 0.89673 0.448365 -0.89673 -1.6 -1.6 0.902668 0.902668 0.451334 -0.902668 -1.5 -1.6 0.908282 0.908282 0.454141 -0.908282 -1.4 -1.6 0.913566 0.913566 0.456783 -0.913566 -1.3 -1.6 0.918512 0.918512 0.459256 -0.918512 -1.2 -1.6 0.923116 0.923116 0.461558 -0.923116 -1.1 -1.6 0.927372 0.927372 0.463686 -0.927372 -1 -1.6 0.931276 0.931276 0.465638 -0.931276 -0.9 -1.6 0.934821 0.934821 0.467411 -0.934821 -0.8 -1.6 0.938005 0.938005 0.469002 -0.938005 -0.7 -1.6 0.940823 0.940823 0.470412 -0.940823 -0.6 -1.6 0.943273 0.943273 0.471636 -0.943273 -0.5 -1.6 0.94535 0.94535 0.472675 -0.94535 -0.4 -1.6 0.947053 0.947053 0.473527 -0.947053 -0.3 -1.6 0.94838 0.94838 0.47419 -0.94838 -0.2 -1.6 0.949329 0.949329 0.474664 -0.949329 -0.1 -1.6 0.949899 0.949899 0.474949 -0.949899 0 -1.6 0.950089 0.950089 0.475044 -0.950089 0.1 -1.6 0.949899 0.949899 0.474949 -0.949899 0.2 -1.6 0.949329 0.949329 0.474664 -0.949329 0.3 -1.6 0.94838 0.94838 0.47419 -0.94838 0.4 -1.6 0.947053 0.947053 0.473527 -0.947053 0.5 -1.6 0.94535 0.94535 0.472675 -0.94535 0.6 -1.6 0.943273 0.943273 0.471636 -0.943273 0.7 -1.6 0.940823 0.940823 0.470412 -0.940823 0.8 -1.6 0.938005 0.938005 0.469002 -0.938005 0.9 -1.6 0.934821 0.934821 0.467411 -0.934821 1 -1.6 0.931276 0.931276 0.465638 -0.931276 1.1 -1.6 0.927372 0.927372 0.463686 -0.927372 1.2 -1.6 0.923116 0.923116 0.461558 -0.923116 1.3 -1.6 0.918512 0.918512 0.459256 -0.918512 1.4 -1.6 0.913566 0.913566 0.456783 -0.913566 1.5 -1.6 0.908282 0.908282 0.454141 -0.908282 1.6 -1.6 0.902668 0.902668 0.451334 -0.902668 1.7 -1.6 0.89673 0.89673 0.448365 -0.89673 1.8 -1.6 0.890475 0.890475 0.445238 -0.890475 1.9 -1.6 0.88391 0.88391 0.441955 -0.88391 2 -1.6 0.877042 0.877042 0.438521 -0.877042 2.1 -1.6 0.86988 0.86988 0.43494 -0.86988 2.2 -1.6 0.862431 0.862431 0.431216 -0.862431 2.3 -1.6 0.854704 0.854704 0.427352 -0.854704 2.4 -1.6 0.846707 0.846707 0.423354 -0.846707 2.5 -1.6 0.83845 0.83845 0.419225 -0.83845 2.6 -1.6 0.829942 0.829942 0.414971 -0.829942 2.7 -1.6 0.821191 0.821191 0.410595 -0.821191 2.8 -1.6 0.812207 0.812207 0.406104 -0.812207 2.9 -1.6 0.803 0.803 0.4015 -0.803 3 -1.6 0.793581 0.793581 0.39679 -0.793581 3.1 -1.6 0.783958 0.783958 0.391979 -0.783958 3.2 -1.6 0.774142 0.774142 0.387071 -0.774142 3.3 -1.6 0.764143 0.764143 0.382072 -0.764143 3.4 -1.6 0.753972 0.753972 0.376986 -0.753972 3.5 -1.6 0.743639 0.743639 0.371819 -0.743639 3.6 -1.6 0.733154 0.733154 0.366577 -0.733154 3.7 -1.6 0.722527 0.722527 0.361264 -0.722527 3.8 -1.6 0.71177 0.71177 0.355885 -0.71177 3.9 -1.6 0.700893 0.700893 0.350447 -0.700893 4 -1.6 0.689906 0.689906 0.344953 -0.689906 4.1 -1.6 0.67882 0.67882 0.33941 -0.67882 4.2 -1.6 0.667644 0.667644 0.333822 -0.667644 4.3 -1.6 0.65639 0.65639 0.328195 -0.65639 4.4 -1.6 0.645068 0.645068 0.322534 -0.645068 4.5 -1.6 0.633687 0.633687 0.316844 -0.633687 4.6 -1.6 0.622258 0.622258 0.311129 -0.622258 4.7 -1.6 0.610791 0.610791 0.305396 -0.610791 4.8 -1.6 0.599296 0.599296 0.299648 -0.599296 4.9 -1.6 0.587781 0.587781 0.293891 -0.587781 -5 -1.5 0.579842 0.579842 0.289921 -0.579842 -4.9 -1.5 0.591437 0.591437 0.295719 -0.591437 -4.8 -1.5 0.603023 0.603023 0.301511 -0.603023 -4.7 -1.5 0.61459 0.61459 0.307295 -0.61459 -4.6 -1.5 0.626128 0.626128 0.313064 -0.626128 -4.5 -1.5 0.637628 0.637628 0.318814 -0.637628 -4.4 -1.5 0.64908 0.64908 0.32454 -0.64908 -4.3 -1.5 0.660472 0.660472 0.330236 -0.660472 -4.2 -1.5 0.671796 0.671796 0.335898 -0.671796 -4.1 -1.5 0.683041 0.683041 0.341521 -0.683041 -4 -1.5 0.694197 0.694197 0.347098 -0.694197 -3.9 -1.5 0.705252 0.705252 0.352626 -0.705252 -3.8 -1.5 0.716197 0.716197 0.358099 -0.716197 -3.7 -1.5 0.727021 0.727021 0.36351 -0.727021 -3.6 -1.5 0.737713 0.737713 0.368857 -0.737713 -3.5 -1.5 0.748264 0.748264 0.374132 -0.748264 -3.4 -1.5 0.758661 0.758661 0.379331 -0.758661 -3.3 -1.5 0.768896 0.768896 0.384448 -0.768896 -3.2 -1.5 0.778957 0.778957 0.389478 -0.778957 -3.1 -1.5 0.788834 0.788834 0.394417 -0.788834 -3 -1.5 0.798516 0.798516 0.399258 -0.798516 -2.9 -1.5 0.807995 0.807995 0.403997 -0.807995 -2.8 -1.5 0.817258 0.817258 0.408629 -0.817258 -2.7 -1.5 0.826298 0.826298 0.413149 -0.826298 -2.6 -1.5 0.835103 0.835103 0.417552 -0.835103 -2.5 -1.5 0.843665 0.843665 0.421832 -0.843665 -2.4 -1.5 0.851973 0.851973 0.425987 -0.851973 -2.3 -1.5 0.86002 0.86002 0.43001 -0.86002 -2.2 -1.5 0.867795 0.867795 0.433897 -0.867795 -2.1 -1.5 0.87529 0.87529 0.437645 -0.87529 -2 -1.5 0.882497 0.882497 0.441248 -0.882497 -1.9 -1.5 0.889407 0.889407 0.444704 -0.889407 -1.8 -1.5 0.896013 0.896013 0.448007 -0.896013 -1.7 -1.5 0.902307 0.902307 0.451154 -0.902307 -1.6 -1.5 0.908282 0.908282 0.454141 -0.908282 -1.5 -1.5 0.913931 0.913931 0.456966 -0.913931 -1.4 -1.5 0.919247 0.919247 0.459624 -0.919247 -1.3 -1.5 0.924225 0.924225 0.462112 -0.924225 -1.2 -1.5 0.928857 0.928857 0.464429 -0.928857 -1.1 -1.5 0.93314 0.93314 0.46657 -0.93314 -1 -1.5 0.937067 0.937067 0.468534 -0.937067 -0.9 -1.5 0.940635 0.940635 0.470318 -0.940635 -0.8 -1.5 0.943839 0.943839 0.471919 -0.943839 -0.7 -1.5 0.946674 0.946674 0.473337 -0.946674 -0.6 -1.5 0.949139 0.949139 0.47457 -0.949139 -0.5 -1.5 0.951229 0.951229 0.475615 -0.951229 -0.4 -1.5 0.952943 0.952943 0.476472 -0.952943 -0.3 -1.5 0.954278 0.954278 0.477139 -0.954278 -0.2 -1.5 0.955233 0.955233 0.477616 -0.955233 -0.1 -1.5 0.955806 0.955806 0.477903 -0.955806 0 -1.5 0.955997 0.955997 0.477999 -0.955997 0.1 -1.5 0.955806 0.955806 0.477903 -0.955806 0.2 -1.5 0.955233 0.955233 0.477616 -0.955233 0.3 -1.5 0.954278 0.954278 0.477139 -0.954278 0.4 -1.5 0.952943 0.952943 0.476472 -0.952943 0.5 -1.5 0.951229 0.951229 0.475615 -0.951229 0.6 -1.5 0.949139 0.949139 0.47457 -0.949139 0.7 -1.5 0.946674 0.946674 0.473337 -0.946674 0.8 -1.5 0.943839 0.943839 0.471919 -0.943839 0.9 -1.5 0.940635 0.940635 0.470318 -0.940635 1 -1.5 0.937067 0.937067 0.468534 -0.937067 1.1 -1.5 0.93314 0.93314 0.46657 -0.93314 1.2 -1.5 0.928857 0.928857 0.464429 -0.928857 1.3 -1.5 0.924225 0.924225 0.462112 -0.924225 1.4 -1.5 0.919247 0.919247 0.459624 -0.919247 1.5 -1.5 0.913931 0.913931 0.456966 -0.913931 1.6 -1.5 0.908282 0.908282 0.454141 -0.908282 1.7 -1.5 0.902307 0.902307 0.451154 -0.902307 1.8 -1.5 0.896013 0.896013 0.448007 -0.896013 1.9 -1.5 0.889407 0.889407 0.444704 -0.889407 2 -1.5 0.882497 0.882497 0.441248 -0.882497 2.1 -1.5 0.87529 0.87529 0.437645 -0.87529 2.2 -1.5 0.867795 0.867795 0.433897 -0.867795 2.3 -1.5 0.86002 0.86002 0.43001 -0.86002 2.4 -1.5 0.851973 0.851973 0.425987 -0.851973 2.5 -1.5 0.843665 0.843665 0.421832 -0.843665 2.6 -1.5 0.835103 0.835103 0.417552 -0.835103 2.7 -1.5 0.826298 0.826298 0.413149 -0.826298 2.8 -1.5 0.817258 0.817258 0.408629 -0.817258 2.9 -1.5 0.807995 0.807995 0.403997 -0.807995 3 -1.5 0.798516 0.798516 0.399258 -0.798516 3.1 -1.5 0.788834 0.788834 0.394417 -0.788834 3.2 -1.5 0.778957 0.778957 0.389478 -0.778957 3.3 -1.5 0.768896 0.768896 0.384448 -0.768896 3.4 -1.5 0.758661 0.758661 0.379331 -0.758661 3.5 -1.5 0.748264 0.748264 0.374132 -0.748264 3.6 -1.5 0.737713 0.737713 0.368857 -0.737713 3.7 -1.5 0.727021 0.727021 0.36351 -0.727021 3.8 -1.5 0.716197 0.716197 0.358099 -0.716197 3.9 -1.5 0.705252 0.705252 0.352626 -0.705252 4 -1.5 0.694197 0.694197 0.347098 -0.694197 4.1 -1.5 0.683041 0.683041 0.341521 -0.683041 4.2 -1.5 0.671796 0.671796 0.335898 -0.671796 4.3 -1.5 0.660472 0.660472 0.330236 -0.660472 4.4 -1.5 0.64908 0.64908 0.32454 -0.64908 4.5 -1.5 0.637628 0.637628 0.318814 -0.637628 4.6 -1.5 0.626128 0.626128 0.313064 -0.626128 4.7 -1.5 0.61459 0.61459 0.307295 -0.61459 4.8 -1.5 0.603023 0.603023 0.301511 -0.603023 4.9 -1.5 0.591437 0.591437 0.295719 -0.591437 -5 -1.4 0.583215 0.583215 0.291607 -0.583215 -4.9 -1.4 0.594877 0.594877 0.297439 -0.594877 -4.8 -1.4 0.606531 0.606531 0.303265 -0.606531 -4.7 -1.4 0.618165 0.618165 0.309082 -0.618165 -4.6 -1.4 0.62977 0.62977 0.314885 -0.62977 -4.5 -1.4 0.641337 0.641337 0.320669 -0.641337 -4.4 -1.4 0.652855 0.652855 0.326428 -0.652855 -4.3 -1.4 0.664314 0.664314 0.332157 -0.664314 -4.2 -1.4 0.675704 0.675704 0.337852 -0.675704 -4.1 -1.4 0.687014 0.687014 0.343507 -0.687014 -4 -1.4 0.698235 0.698235 0.349117 -0.698235 -3.9 -1.4 0.709354 0.709354 0.354677 -0.709354 -3.8 -1.4 0.720363 0.720363 0.360182 -0.720363 -3.7 -1.4 0.73125 0.73125 0.365625 -0.73125 -3.6 -1.4 0.742004 0.742004 0.371002 -0.742004 -3.5 -1.4 0.752616 0.752616 0.376308 -0.752616 -3.4 -1.4 0.763074 0.763074 0.381537 -0.763074 -3.3 -1.4 0.773368 0.773368 0.386684 -0.773368 -3.2 -1.4 0.783488 0.783488 0.391744 -0.783488 -3.1 -1.4 0.793422 0.793422 0.396711 -0.793422 -3 -1.4 0.803161 0.803161 0.401581 -0.803161 -2.9 -1.4 0.812695 0.812695 0.406347 -0.812695 -2.8 -1.4 0.822012 0.822012 0.411006 -0.822012 -2.7 -1.4 0.831104 0.831104 0.415552 -0.831104 -2.6 -1.4 0.839961 0.839961 0.41998 -0.839961 -2.5 -1.4 0.848572 0.848572 0.424286 -0.848572 -2.4 -1.4 0.856929 0.856929 0.428465 -0.856929 -2.3 -1.4 0.865022 0.865022 0.432511 -0.865022 -2.2 -1.4 0.872843 0.872843 0.436421 -0.872843 -2.1 -1.4 0.880381 0.880381 0.440191 -0.880381 -2 -1.4 0.88763 0.88763 0.443815 -0.88763 -1.9 -1.4 0.894581 0.894581 0.44729 -0.894581 -1.8 -1.4 0.901225 0.901225 0.450613 -0.901225 -1.7 -1.4 0.907556 0.907556 0.453778 -0.907556 -1.6 -1.4 0.913566 0.913566 0.456783 -0.913566 -1.5 -1.4 0.919247 0.919247 0.459624 -0.919247 -1.4 -1.4 0.924595 0.924595 0.462297 -0.924595 -1.3 -1.4 0.929601 0.929601 0.4648 -0.929601 -1.2 -1.4 0.93426 0.93426 0.46713 -0.93426 -1.1 -1.4 0.938568 0.938568 0.469284 -0.938568 -1 -1.4 0.942518 0.942518 0.471259 -0.942518 -0.9 -1.4 0.946107 0.946107 0.473053 -0.946107 -0.8 -1.4 0.949329 0.949329 0.474664 -0.949329 -0.7 -1.4 0.952181 0.952181 0.476091 -0.952181 -0.6 -1.4 0.95466 0.95466 0.47733 -0.95466 -0.5 -1.4 0.956763 0.956763 0.478381 -0.956763 -0.4 -1.4 0.958486 0.958486 0.479243 -0.958486 -0.3 -1.4 0.959829 0.959829 0.479915 -0.959829 -0.2 -1.4 0.960789 0.960789 0.480395 -0.960789 -0.1 -1.4 0.961366 0.961366 0.480683 -0.961366 0 -1.4 0.961558 0.961558 0.480779 -0.961558 0.1 -1.4 0.961366 0.961366 0.480683 -0.961366 0.2 -1.4 0.960789 0.960789 0.480395 -0.960789 0.3 -1.4 0.959829 0.959829 0.479915 -0.959829 0.4 -1.4 0.958486 0.958486 0.479243 -0.958486 0.5 -1.4 0.956763 0.956763 0.478381 -0.956763 0.6 -1.4 0.95466 0.95466 0.47733 -0.95466 0.7 -1.4 0.952181 0.952181 0.476091 -0.952181 0.8 -1.4 0.949329 0.949329 0.474664 -0.949329 0.9 -1.4 0.946107 0.946107 0.473053 -0.946107 1 -1.4 0.942518 0.942518 0.471259 -0.942518 1.1 -1.4 0.938568 0.938568 0.469284 -0.938568 1.2 -1.4 0.93426 0.93426 0.46713 -0.93426 1.3 -1.4 0.929601 0.929601 0.4648 -0.929601 1.4 -1.4 0.924595 0.924595 0.462297 -0.924595 1.5 -1.4 0.919247 0.919247 0.459624 -0.919247 1.6 -1.4 0.913566 0.913566 0.456783 -0.913566 1.7 -1.4 0.907556 0.907556 0.453778 -0.907556 1.8 -1.4 0.901225 0.901225 0.450613 -0.901225 1.9 -1.4 0.894581 0.894581 0.44729 -0.894581 2 -1.4 0.88763 0.88763 0.443815 -0.88763 2.1 -1.4 0.880381 0.880381 0.440191 -0.880381 2.2 -1.4 0.872843 0.872843 0.436421 -0.872843 2.3 -1.4 0.865022 0.865022 0.432511 -0.865022 2.4 -1.4 0.856929 0.856929 0.428465 -0.856929 2.5 -1.4 0.848572 0.848572 0.424286 -0.848572 2.6 -1.4 0.839961 0.839961 0.41998 -0.839961 2.7 -1.4 0.831104 0.831104 0.415552 -0.831104 2.8 -1.4 0.822012 0.822012 0.411006 -0.822012 2.9 -1.4 0.812695 0.812695 0.406347 -0.812695 3 -1.4 0.803161 0.803161 0.401581 -0.803161 3.1 -1.4 0.793422 0.793422 0.396711 -0.793422 3.2 -1.4 0.783488 0.783488 0.391744 -0.783488 3.3 -1.4 0.773368 0.773368 0.386684 -0.773368 3.4 -1.4 0.763074 0.763074 0.381537 -0.763074 3.5 -1.4 0.752616 0.752616 0.376308 -0.752616 3.6 -1.4 0.742004 0.742004 0.371002 -0.742004 3.7 -1.4 0.73125 0.73125 0.365625 -0.73125 3.8 -1.4 0.720363 0.720363 0.360182 -0.720363 3.9 -1.4 0.709354 0.709354 0.354677 -0.709354 4 -1.4 0.698235 0.698235 0.349117 -0.698235 4.1 -1.4 0.687014 0.687014 0.343507 -0.687014 4.2 -1.4 0.675704 0.675704 0.337852 -0.675704 4.3 -1.4 0.664314 0.664314 0.332157 -0.664314 4.4 -1.4 0.652855 0.652855 0.326428 -0.652855 4.5 -1.4 0.641337 0.641337 0.320669 -0.641337 4.6 -1.4 0.62977 0.62977 0.314885 -0.62977 4.7 -1.4 0.618165 0.618165 0.309082 -0.618165 4.8 -1.4 0.606531 0.606531 0.303265 -0.606531 4.9 -1.4 0.594877 0.594877 0.297439 -0.594877 -5 -1.3 0.586373 0.586373 0.293186 -0.586373 -4.9 -1.3 0.598098 0.598098 0.299049 -0.598098 -4.8 -1.3 0.609815 0.609815 0.304907 -0.609815 -4.7 -1.3 0.621512 0.621512 0.310756 -0.621512 -4.6 -1.3 0.63318 0.63318 0.31659 -0.63318 -4.5 -1.3 0.64481 0.64481 0.322405 -0.64481 -4.4 -1.3 0.65639 0.65639 0.328195 -0.65639 -4.3 -1.3 0.667911 0.667911 0.333956 -0.667911 -4.2 -1.3 0.679363 0.679363 0.339681 -0.679363 -4.1 -1.3 0.690734 0.690734 0.345367 -0.690734 -4 -1.3 0.702015 0.702015 0.351008 -0.702015 -3.9 -1.3 0.713195 0.713195 0.356598 -0.713195 -3.8 -1.3 0.724264 0.724264 0.362132 -0.724264 -3.7 -1.3 0.735209 0.735209 0.367605 -0.735209 -3.6 -1.3 0.746022 0.746022 0.373011 -0.746022 -3.5 -1.3 0.756691 0.756691 0.378346 -0.756691 -3.4 -1.3 0.767206 0.767206 0.383603 -0.767206 -3.3 -1.3 0.777556 0.777556 0.388778 -0.777556 -3.2 -1.3 0.78773 0.78773 0.393865 -0.78773 -3.1 -1.3 0.797718 0.797718 0.398859 -0.797718 -3 -1.3 0.80751 0.80751 0.403755 -0.80751 -2.9 -1.3 0.817095 0.817095 0.408547 -0.817095 -2.8 -1.3 0.826463 0.826463 0.413232 -0.826463 -2.7 -1.3 0.835604 0.835604 0.417802 -0.835604 -2.6 -1.3 0.844509 0.844509 0.422254 -0.844509 -2.5 -1.3 0.853167 0.853167 0.426583 -0.853167 -2.4 -1.3 0.861569 0.861569 0.430785 -0.861569 -2.3 -1.3 0.869706 0.869706 0.434853 -0.869706 -2.2 -1.3 0.877569 0.877569 0.438784 -0.877569 -2.1 -1.3 0.885148 0.885148 0.442574 -0.885148 -2 -1.3 0.892436 0.892436 0.446218 -0.892436 -1.9 -1.3 0.899425 0.899425 0.449712 -0.899425 -1.8 -1.3 0.906105 0.906105 0.453053 -0.906105 -1.7 -1.3 0.91247 0.91247 0.456235 -0.91247 -1.6 -1.3 0.918512 0.918512 0.459256 -0.918512 -1.5 -1.3 0.924225 0.924225 0.462112 -0.924225 -1.4 -1.3 0.929601 0.929601 0.4648 -0.929601 -1.3 -1.3 0.934634 0.934634 0.467317 -0.934634 -1.2 -1.3 0.939319 0.939319 0.46966 -0.939319 -1.1 -1.3 0.94365 0.94365 0.471825 -0.94365 -1 -1.3 0.947622 0.947622 0.473811 -0.947622 -0.9 -1.3 0.951229 0.951229 0.475615 -0.951229 -0.8 -1.3 0.954469 0.954469 0.477235 -0.954469 -0.7 -1.3 0.957337 0.957337 0.478668 -0.957337 -0.6 -1.3 0.959829 0.959829 0.479915 -0.959829 -0.5 -1.3 0.961943 0.961943 0.480972 -0.961943 -0.4 -1.3 0.963676 0.963676 0.481838 -0.963676 -0.3 -1.3 0.965026 0.965026 0.482513 -0.965026 -0.2 -1.3 0.965992 0.965992 0.482996 -0.965992 -0.1 -1.3 0.966572 0.966572 0.483286 -0.966572 0 -1.3 0.966765 0.966765 0.483382 -0.966765 0.1 -1.3 0.966572 0.966572 0.483286 -0.966572 0.2 -1.3 0.965992 0.965992 0.482996 -0.965992 0.3 -1.3 0.965026 0.965026 0.482513 -0.965026 0.4 -1.3 0.963676 0.963676 0.481838 -0.963676 0.5 -1.3 0.961943 0.961943 0.480972 -0.961943 0.6 -1.3 0.959829 0.959829 0.479915 -0.959829 0.7 -1.3 0.957337 0.957337 0.478668 -0.957337 0.8 -1.3 0.954469 0.954469 0.477235 -0.954469 0.9 -1.3 0.951229 0.951229 0.475615 -0.951229 1 -1.3 0.947622 0.947622 0.473811 -0.947622 1.1 -1.3 0.94365 0.94365 0.471825 -0.94365 1.2 -1.3 0.939319 0.939319 0.46966 -0.939319 1.3 -1.3 0.934634 0.934634 0.467317 -0.934634 1.4 -1.3 0.929601 0.929601 0.4648 -0.929601 1.5 -1.3 0.924225 0.924225 0.462112 -0.924225 1.6 -1.3 0.918512 0.918512 0.459256 -0.918512 1.7 -1.3 0.91247 0.91247 0.456235 -0.91247 1.8 -1.3 0.906105 0.906105 0.453053 -0.906105 1.9 -1.3 0.899425 0.899425 0.449712 -0.899425 2 -1.3 0.892436 0.892436 0.446218 -0.892436 2.1 -1.3 0.885148 0.885148 0.442574 -0.885148 2.2 -1.3 0.877569 0.877569 0.438784 -0.877569 2.3 -1.3 0.869706 0.869706 0.434853 -0.869706 2.4 -1.3 0.861569 0.861569 0.430785 -0.861569 2.5 -1.3 0.853167 0.853167 0.426583 -0.853167 2.6 -1.3 0.844509 0.844509 0.422254 -0.844509 2.7 -1.3 0.835604 0.835604 0.417802 -0.835604 2.8 -1.3 0.826463 0.826463 0.413232 -0.826463 2.9 -1.3 0.817095 0.817095 0.408547 -0.817095 3 -1.3 0.80751 0.80751 0.403755 -0.80751 3.1 -1.3 0.797718 0.797718 0.398859 -0.797718 3.2 -1.3 0.78773 0.78773 0.393865 -0.78773 3.3 -1.3 0.777556 0.777556 0.388778 -0.777556 3.4 -1.3 0.767206 0.767206 0.383603 -0.767206 3.5 -1.3 0.756691 0.756691 0.378346 -0.756691 3.6 -1.3 0.746022 0.746022 0.373011 -0.746022 3.7 -1.3 0.735209 0.735209 0.367605 -0.735209 3.8 -1.3 0.724264 0.724264 0.362132 -0.724264 3.9 -1.3 0.713195 0.713195 0.356598 -0.713195 4 -1.3 0.702015 0.702015 0.351008 -0.702015 4.1 -1.3 0.690734 0.690734 0.345367 -0.690734 4.2 -1.3 0.679363 0.679363 0.339681 -0.679363 4.3 -1.3 0.667911 0.667911 0.333956 -0.667911 4.4 -1.3 0.65639 0.65639 0.328195 -0.65639 4.5 -1.3 0.64481 0.64481 0.322405 -0.64481 4.6 -1.3 0.63318 0.63318 0.31659 -0.63318 4.7 -1.3 0.621512 0.621512 0.310756 -0.621512 4.8 -1.3 0.609815 0.609815 0.304907 -0.609815 4.9 -1.3 0.598098 0.598098 0.299049 -0.598098 -5 -1.2 0.589312 0.589312 0.294656 -0.589312 -4.9 -1.2 0.601096 0.601096 0.300548 -0.601096 -4.8 -1.2 0.612871 0.612871 0.306436 -0.612871 -4.7 -1.2 0.624627 0.624627 0.312314 -0.624627 -4.6 -1.2 0.636354 0.636354 0.318177 -0.636354 -4.5 -1.2 0.648042 0.648042 0.324021 -0.648042 -4.4 -1.2 0.65968 0.65968 0.32984 -0.65968 -4.3 -1.2 0.671259 0.671259 0.33563 -0.671259 -4.2 -1.2 0.682768 0.682768 0.341384 -0.682768 -4.1 -1.2 0.694197 0.694197 0.347098 -0.694197 -4 -1.2 0.705534 0.705534 0.352767 -0.705534 -3.9 -1.2 0.71677 0.71677 0.358385 -0.71677 -3.8 -1.2 0.727894 0.727894 0.363947 -0.727894 -3.7 -1.2 0.738895 0.738895 0.369447 -0.738895 -3.6 -1.2 0.749762 0.749762 0.374881 -0.749762 -3.5 -1.2 0.760484 0.760484 0.380242 -0.760484 -3.4 -1.2 0.771052 0.771052 0.385526 -0.771052 -3.3 -1.2 0.781453 0.781453 0.390727 -0.781453 -3.2 -1.2 0.791678 0.791678 0.395839 -0.791678 -3.1 -1.2 0.801717 0.801717 0.400858 -0.801717 -3 -1.2 0.811558 0.811558 0.405779 -0.811558 -2.9 -1.2 0.821191 0.821191 0.410595 -0.821191 -2.8 -1.2 0.830606 0.830606 0.415303 -0.830606 -2.7 -1.2 0.839793 0.839793 0.419896 -0.839793 -2.6 -1.2 0.848742 0.848742 0.424371 -0.848742 -2.5 -1.2 0.857443 0.857443 0.428722 -0.857443 -2.4 -1.2 0.865888 0.865888 0.432944 -0.865888 -2.3 -1.2 0.874065 0.874065 0.437033 -0.874065 -2.2 -1.2 0.881968 0.881968 0.440984 -0.881968 -2.1 -1.2 0.889585 0.889585 0.444793 -0.889585 -2 -1.2 0.89691 0.89691 0.448455 -0.89691 -1.9 -1.2 0.903933 0.903933 0.451967 -0.903933 -1.8 -1.2 0.910647 0.910647 0.455323 -0.910647 -1.7 -1.2 0.917044 0.917044 0.458522 -0.917044 -1.6 -1.2 0.923116 0.923116 0.461558 -0.923116 -1.5 -1.2 0.928857 0.928857 0.464429 -0.928857 -1.4 -1.2 0.93426 0.93426 0.46713 -0.93426 -1.3 -1.2 0.939319 0.939319 0.46966 -0.939319 -1.2 -1.2 0.944027 0.944027 0.472014 -0.944027 -1.1 -1.2 0.94838 0.94838 0.47419 -0.94838 -1 -1.2 0.952372 0.952372 0.476186 -0.952372 -0.9 -1.2 0.955997 0.955997 0.477999 -0.955997 -0.8 -1.2 0.959253 0.959253 0.479627 -0.959253 -0.7 -1.2 0.962135 0.962135 0.481068 -0.962135 -0.6 -1.2 0.96464 0.96464 0.48232 -0.96464 -0.5 -1.2 0.966765 0.966765 0.483382 -0.966765 -0.4 -1.2 0.968507 0.968507 0.484253 -0.968507 -0.3 -1.2 0.969863 0.969863 0.484932 -0.969863 -0.2 -1.2 0.970834 0.970834 0.485417 -0.970834 -0.1 -1.2 0.971416 0.971416 0.485708 -0.971416 0 -1.2 0.971611 0.971611 0.485805 -0.971611 0.1 -1.2 0.971416 0.971416 0.485708 -0.971416 0.2 -1.2 0.970834 0.970834 0.485417 -0.970834 0.3 -1.2 0.969863 0.969863 0.484932 -0.969863 0.4 -1.2 0.968507 0.968507 0.484253 -0.968507 0.5 -1.2 0.966765 0.966765 0.483382 -0.966765 0.6 -1.2 0.96464 0.96464 0.48232 -0.96464 0.7 -1.2 0.962135 0.962135 0.481068 -0.962135 0.8 -1.2 0.959253 0.959253 0.479627 -0.959253 0.9 -1.2 0.955997 0.955997 0.477999 -0.955997 1 -1.2 0.952372 0.952372 0.476186 -0.952372 1.1 -1.2 0.94838 0.94838 0.47419 -0.94838 1.2 -1.2 0.944027 0.944027 0.472014 -0.944027 1.3 -1.2 0.939319 0.939319 0.46966 -0.939319 1.4 -1.2 0.93426 0.93426 0.46713 -0.93426 1.5 -1.2 0.928857 0.928857 0.464429 -0.928857 1.6 -1.2 0.923116 0.923116 0.461558 -0.923116 1.7 -1.2 0.917044 0.917044 0.458522 -0.917044 1.8 -1.2 0.910647 0.910647 0.455323 -0.910647 1.9 -1.2 0.903933 0.903933 0.451967 -0.903933 2 -1.2 0.89691 0.89691 0.448455 -0.89691 2.1 -1.2 0.889585 0.889585 0.444793 -0.889585 2.2 -1.2 0.881968 0.881968 0.440984 -0.881968 2.3 -1.2 0.874065 0.874065 0.437033 -0.874065 2.4 -1.2 0.865888 0.865888 0.432944 -0.865888 2.5 -1.2 0.857443 0.857443 0.428722 -0.857443 2.6 -1.2 0.848742 0.848742 0.424371 -0.848742 2.7 -1.2 0.839793 0.839793 0.419896 -0.839793 2.8 -1.2 0.830606 0.830606 0.415303 -0.830606 2.9 -1.2 0.821191 0.821191 0.410595 -0.821191 3 -1.2 0.811558 0.811558 0.405779 -0.811558 3.1 -1.2 0.801717 0.801717 0.400858 -0.801717 3.2 -1.2 0.791678 0.791678 0.395839 -0.791678 3.3 -1.2 0.781453 0.781453 0.390727 -0.781453 3.4 -1.2 0.771052 0.771052 0.385526 -0.771052 3.5 -1.2 0.760484 0.760484 0.380242 -0.760484 3.6 -1.2 0.749762 0.749762 0.374881 -0.749762 3.7 -1.2 0.738895 0.738895 0.369447 -0.738895 3.8 -1.2 0.727894 0.727894 0.363947 -0.727894 3.9 -1.2 0.71677 0.71677 0.358385 -0.71677 4 -1.2 0.705534 0.705534 0.352767 -0.705534 4.1 -1.2 0.694197 0.694197 0.347098 -0.694197 4.2 -1.2 0.682768 0.682768 0.341384 -0.682768 4.3 -1.2 0.671259 0.671259 0.33563 -0.671259 4.4 -1.2 0.65968 0.65968 0.32984 -0.65968 4.5 -1.2 0.648042 0.648042 0.324021 -0.648042 4.6 -1.2 0.636354 0.636354 0.318177 -0.636354 4.7 -1.2 0.624627 0.624627 0.312314 -0.624627 4.8 -1.2 0.612871 0.612871 0.306436 -0.612871 4.9 -1.2 0.601096 0.601096 0.300548 -0.601096 -5 -1.1 0.592029 0.592029 0.296014 -0.592029 -4.9 -1.1 0.603868 0.603868 0.301934 -0.603868 -4.8 -1.1 0.615697 0.615697 0.307849 -0.615697 -4.7 -1.1 0.627507 0.627507 0.313754 -0.627507 -4.6 -1.1 0.639288 0.639288 0.319644 -0.639288 -4.5 -1.1 0.65103 0.65103 0.325515 -0.65103 -4.4 -1.1 0.662722 0.662722 0.331361 -0.662722 -4.3 -1.1 0.674354 0.674354 0.337177 -0.674354 -4.2 -1.1 0.685916 0.685916 0.342958 -0.685916 -4.1 -1.1 0.697397 0.697397 0.348699 -0.697397 -4 -1.1 0.708787 0.708787 0.354394 -0.708787 -3.9 -1.1 0.720075 0.720075 0.360037 -0.720075 -3.8 -1.1 0.73125 0.73125 0.365625 -0.73125 -3.7 -1.1 0.742301 0.742301 0.371151 -0.742301 -3.6 -1.1 0.753218 0.753218 0.376609 -0.753218 -3.5 -1.1 0.76399 0.76399 0.381995 -0.76399 -3.4 -1.1 0.774607 0.774607 0.387303 -0.774607 -3.3 -1.1 0.785056 0.785056 0.392528 -0.785056 -3.2 -1.1 0.795329 0.795329 0.397664 -0.795329 -3.1 -1.1 0.805413 0.805413 0.402707 -0.805413 -3 -1.1 0.815299 0.815299 0.40765 -0.815299 -2.9 -1.1 0.824977 0.824977 0.412488 -0.824977 -2.8 -1.1 0.834435 0.834435 0.417218 -0.834435 -2.7 -1.1 0.843665 0.843665 0.421832 -0.843665 -2.6 -1.1 0.852655 0.852655 0.426328 -0.852655 -2.5 -1.1 0.861397 0.861397 0.430698 -0.861397 -2.4 -1.1 0.86988 0.86988 0.43494 -0.86988 -2.3 -1.1 0.878095 0.878095 0.439048 -0.878095 -2.2 -1.1 0.886034 0.886034 0.443017 -0.886034 -2.1 -1.1 0.893687 0.893687 0.446843 -0.893687 -2 -1.1 0.901045 0.901045 0.450523 -0.901045 -1.9 -1.1 0.908101 0.908101 0.45405 -0.908101 -1.8 -1.1 0.914846 0.914846 0.457423 -0.914846 -1.7 -1.1 0.921272 0.921272 0.460636 -0.921272 -1.6 -1.1 0.927372 0.927372 0.463686 -0.927372 -1.5 -1.1 0.93314 0.93314 0.46657 -0.93314 -1.4 -1.1 0.938568 0.938568 0.469284 -0.938568 -1.3 -1.1 0.94365 0.94365 0.471825 -0.94365 -1.2 -1.1 0.94838 0.94838 0.47419 -0.94838 -1.1 -1.1 0.952753 0.952753 0.476376 -0.952753 -1 -1.1 0.956763 0.956763 0.478381 -0.956763 -0.9 -1.1 0.960405 0.960405 0.480203 -0.960405 -0.8 -1.1 0.963676 0.963676 0.481838 -0.963676 -0.7 -1.1 0.966572 0.966572 0.483286 -0.966572 -0.6 -1.1 0.969088 0.969088 0.484544 -0.969088 -0.5 -1.1 0.971222 0.971222 0.485611 -0.971222 -0.4 -1.1 0.972972 0.972972 0.486486 -0.972972 -0.3 -1.1 0.974335 0.974335 0.487168 -0.974335 -0.2 -1.1 0.97531 0.97531 0.487655 -0.97531 -0.1 -1.1 0.975895 0.975895 0.487948 -0.975895 0 -1.1 0.97609 0.97609 0.488045 -0.97609 0.1 -1.1 0.975895 0.975895 0.487948 -0.975895 0.2 -1.1 0.97531 0.97531 0.487655 -0.97531 0.3 -1.1 0.974335 0.974335 0.487168 -0.974335 0.4 -1.1 0.972972 0.972972 0.486486 -0.972972 0.5 -1.1 0.971222 0.971222 0.485611 -0.971222 0.6 -1.1 0.969088 0.969088 0.484544 -0.969088 0.7 -1.1 0.966572 0.966572 0.483286 -0.966572 0.8 -1.1 0.963676 0.963676 0.481838 -0.963676 0.9 -1.1 0.960405 0.960405 0.480203 -0.960405 1 -1.1 0.956763 0.956763 0.478381 -0.956763 1.1 -1.1 0.952753 0.952753 0.476376 -0.952753 1.2 -1.1 0.94838 0.94838 0.47419 -0.94838 1.3 -1.1 0.94365 0.94365 0.471825 -0.94365 1.4 -1.1 0.938568 0.938568 0.469284 -0.938568 1.5 -1.1 0.93314 0.93314 0.46657 -0.93314 1.6 -1.1 0.927372 0.927372 0.463686 -0.927372 1.7 -1.1 0.921272 0.921272 0.460636 -0.921272 1.8 -1.1 0.914846 0.914846 0.457423 -0.914846 1.9 -1.1 0.908101 0.908101 0.45405 -0.908101 2 -1.1 0.901045 0.901045 0.450523 -0.901045 2.1 -1.1 0.893687 0.893687 0.446843 -0.893687 2.2 -1.1 0.886034 0.886034 0.443017 -0.886034 2.3 -1.1 0.878095 0.878095 0.439048 -0.878095 2.4 -1.1 0.86988 0.86988 0.43494 -0.86988 2.5 -1.1 0.861397 0.861397 0.430698 -0.861397 2.6 -1.1 0.852655 0.852655 0.426328 -0.852655 2.7 -1.1 0.843665 0.843665 0.421832 -0.843665 2.8 -1.1 0.834435 0.834435 0.417218 -0.834435 2.9 -1.1 0.824977 0.824977 0.412488 -0.824977 3 -1.1 0.815299 0.815299 0.40765 -0.815299 3.1 -1.1 0.805413 0.805413 0.402707 -0.805413 3.2 -1.1 0.795329 0.795329 0.397664 -0.795329 3.3 -1.1 0.785056 0.785056 0.392528 -0.785056 3.4 -1.1 0.774607 0.774607 0.387303 -0.774607 3.5 -1.1 0.76399 0.76399 0.381995 -0.76399 3.6 -1.1 0.753218 0.753218 0.376609 -0.753218 3.7 -1.1 0.742301 0.742301 0.371151 -0.742301 3.8 -1.1 0.73125 0.73125 0.365625 -0.73125 3.9 -1.1 0.720075 0.720075 0.360037 -0.720075 4 -1.1 0.708787 0.708787 0.354394 -0.708787 4.1 -1.1 0.697397 0.697397 0.348699 -0.697397 4.2 -1.1 0.685916 0.685916 0.342958 -0.685916 4.3 -1.1 0.674354 0.674354 0.337177 -0.674354 4.4 -1.1 0.662722 0.662722 0.331361 -0.662722 4.5 -1.1 0.65103 0.65103 0.325515 -0.65103 4.6 -1.1 0.639288 0.639288 0.319644 -0.639288 4.7 -1.1 0.627507 0.627507 0.313754 -0.627507 4.8 -1.1 0.615697 0.615697 0.307849 -0.615697 4.9 -1.1 0.603868 0.603868 0.301934 -0.603868 -5 -1 0.594521 0.594521 0.29726 -0.594521 -4.9 -1 0.606409 0.606409 0.303205 -0.606409 -4.8 -1 0.618289 0.618289 0.309144 -0.618289 -4.7 -1 0.630148 0.630148 0.315074 -0.630148 -4.6 -1 0.641979 0.641979 0.320989 -0.641979 -4.5 -1 0.65377 0.65377 0.326885 -0.65377 -4.4 -1 0.665511 0.665511 0.332756 -0.665511 -4.3 -1 0.677192 0.677192 0.338596 -0.677192 -4.2 -1 0.688803 0.688803 0.344401 -0.688803 -4.1 -1 0.700333 0.700333 0.350166 -0.700333 -4 -1 0.71177 0.71177 0.355885 -0.71177 -3.9 -1 0.723106 0.723106 0.361553 -0.723106 -3.8 -1 0.734328 0.734328 0.367164 -0.734328 -3.7 -1 0.745426 0.745426 0.372713 -0.745426 -3.6 -1 0.756389 0.756389 0.378194 -0.756389 -3.5 -1 0.767206 0.767206 0.383603 -0.767206 -3.4 -1 0.777867 0.777867 0.388933 -0.777867 -3.3 -1 0.78836 0.78836 0.39418 -0.78836 -3.2 -1 0.798676 0.798676 0.399338 -0.798676 -3.1 -1 0.808803 0.808803 0.404401 -0.808803 -3 -1 0.818731 0.818731 0.409365 -0.818731 -2.9 -1 0.828449 0.828449 0.414225 -0.828449 -2.8 -1 0.837947 0.837947 0.418974 -0.837947 -2.7 -1 0.847216 0.847216 0.423608 -0.847216 -2.6 -1 0.856244 0.856244 0.428122 -0.856244 -2.5 -1 0.865022 0.865022 0.432511 -0.865022 -2.4 -1 0.873541 0.873541 0.436771 -0.873541 -2.3 -1 0.881791 0.881791 0.440896 -0.881791 -2.2 -1 0.889763 0.889763 0.444882 -0.889763 -2.1 -1 0.897448 0.897448 0.448724 -0.897448 -2 -1 0.904837 0.904837 0.452419 -0.904837 -1.9 -1 0.911923 0.911923 0.455961 -0.911923 -1.8 -1 0.918696 0.918696 0.459348 -0.918696 -1.7 -1 0.925149 0.925149 0.462575 -0.925149 -1.6 -1 0.931276 0.931276 0.465638 -0.931276 -1.5 -1 0.937067 0.937067 0.468534 -0.937067 -1.4 -1 0.942518 0.942518 0.471259 -0.942518 -1.3 -1 0.947622 0.947622 0.473811 -0.947622 -1.2 -1 0.952372 0.952372 0.476186 -0.952372 -1.1 -1 0.956763 0.956763 0.478381 -0.956763 -1 -1 0.960789 0.960789 0.480395 -0.960789 -0.9 -1 0.964447 0.964447 0.482224 -0.964447 -0.8 -1 0.967732 0.967732 0.483866 -0.967732 -0.7 -1 0.97064 0.97064 0.48532 -0.97064 -0.6 -1 0.973167 0.973167 0.486583 -0.973167 -0.5 -1 0.97531 0.97531 0.487655 -0.97531 -0.4 -1 0.977067 0.977067 0.488534 -0.977067 -0.3 -1 0.978436 0.978436 0.489218 -0.978436 -0.2 -1 0.979415 0.979415 0.489707 -0.979415 -0.1 -1 0.980003 0.980003 0.490001 -0.980003 0 -1 0.980199 0.980199 0.490099 -0.980199 0.1 -1 0.980003 0.980003 0.490001 -0.980003 0.2 -1 0.979415 0.979415 0.489707 -0.979415 0.3 -1 0.978436 0.978436 0.489218 -0.978436 0.4 -1 0.977067 0.977067 0.488534 -0.977067 0.5 -1 0.97531 0.97531 0.487655 -0.97531 0.6 -1 0.973167 0.973167 0.486583 -0.973167 0.7 -1 0.97064 0.97064 0.48532 -0.97064 0.8 -1 0.967732 0.967732 0.483866 -0.967732 0.9 -1 0.964447 0.964447 0.482224 -0.964447 1 -1 0.960789 0.960789 0.480395 -0.960789 1.1 -1 0.956763 0.956763 0.478381 -0.956763 1.2 -1 0.952372 0.952372 0.476186 -0.952372 1.3 -1 0.947622 0.947622 0.473811 -0.947622 1.4 -1 0.942518 0.942518 0.471259 -0.942518 1.5 -1 0.937067 0.937067 0.468534 -0.937067 1.6 -1 0.931276 0.931276 0.465638 -0.931276 1.7 -1 0.925149 0.925149 0.462575 -0.925149 1.8 -1 0.918696 0.918696 0.459348 -0.918696 1.9 -1 0.911923 0.911923 0.455961 -0.911923 2 -1 0.904837 0.904837 0.452419 -0.904837 2.1 -1 0.897448 0.897448 0.448724 -0.897448 2.2 -1 0.889763 0.889763 0.444882 -0.889763 2.3 -1 0.881791 0.881791 0.440896 -0.881791 2.4 -1 0.873541 0.873541 0.436771 -0.873541 2.5 -1 0.865022 0.865022 0.432511 -0.865022 2.6 -1 0.856244 0.856244 0.428122 -0.856244 2.7 -1 0.847216 0.847216 0.423608 -0.847216 2.8 -1 0.837947 0.837947 0.418974 -0.837947 2.9 -1 0.828449 0.828449 0.414225 -0.828449 3 -1 0.818731 0.818731 0.409365 -0.818731 3.1 -1 0.808803 0.808803 0.404401 -0.808803 3.2 -1 0.798676 0.798676 0.399338 -0.798676 3.3 -1 0.78836 0.78836 0.39418 -0.78836 3.4 -1 0.777867 0.777867 0.388933 -0.777867 3.5 -1 0.767206 0.767206 0.383603 -0.767206 3.6 -1 0.756389 0.756389 0.378194 -0.756389 3.7 -1 0.745426 0.745426 0.372713 -0.745426 3.8 -1 0.734328 0.734328 0.367164 -0.734328 3.9 -1 0.723106 0.723106 0.361553 -0.723106 4 -1 0.71177 0.71177 0.355885 -0.71177 4.1 -1 0.700333 0.700333 0.350166 -0.700333 4.2 -1 0.688803 0.688803 0.344401 -0.688803 4.3 -1 0.677192 0.677192 0.338596 -0.677192 4.4 -1 0.665511 0.665511 0.332756 -0.665511 4.5 -1 0.65377 0.65377 0.326885 -0.65377 4.6 -1 0.641979 0.641979 0.320989 -0.641979 4.7 -1 0.630148 0.630148 0.315074 -0.630148 4.8 -1 0.618289 0.618289 0.309144 -0.618289 4.9 -1 0.606409 0.606409 0.303205 -0.606409 -5 -0.9 0.596784 0.596784 0.298392 -0.596784 -4.9 -0.9 0.608718 0.608718 0.304359 -0.608718 -4.8 -0.9 0.620643 0.620643 0.310321 -0.620643 -4.7 -0.9 0.632547 0.632547 0.316274 -0.632547 -4.6 -0.9 0.644423 0.644423 0.322211 -0.644423 -4.5 -0.9 0.656259 0.656259 0.328129 -0.656259 -4.4 -0.9 0.668045 0.668045 0.334022 -0.668045 -4.3 -0.9 0.679771 0.679771 0.339885 -0.679771 -4.2 -0.9 0.691425 0.691425 0.345713 -0.691425 -4.1 -0.9 0.702999 0.702999 0.351499 -0.702999 -4 -0.9 0.71448 0.71448 0.35724 -0.71448 -3.9 -0.9 0.725859 0.725859 0.362929 -0.725859 -3.8 -0.9 0.737123 0.737123 0.368562 -0.737123 -3.7 -0.9 0.748264 0.748264 0.374132 -0.748264 -3.6 -0.9 0.759268 0.759268 0.379634 -0.759268 -3.5 -0.9 0.770127 0.770127 0.385063 -0.770127 -3.4 -0.9 0.780828 0.780828 0.390414 -0.780828 -3.3 -0.9 0.791362 0.791362 0.395681 -0.791362 -3.2 -0.9 0.801717 0.801717 0.400858 -0.801717 -3.1 -0.9 0.811882 0.811882 0.405941 -0.811882 -3 -0.9 0.821848 0.821848 0.410924 -0.821848 -2.9 -0.9 0.831603 0.831603 0.415802 -0.831603 -2.8 -0.9 0.841138 0.841138 0.420569 -0.841138 -2.7 -0.9 0.850441 0.850441 0.425221 -0.850441 -2.6 -0.9 0.859504 0.859504 0.429752 -0.859504 -2.5 -0.9 0.868316 0.868316 0.434158 -0.868316 -2.4 -0.9 0.876867 0.876867 0.438433 -0.876867 -2.3 -0.9 0.885148 0.885148 0.442574 -0.885148 -2.2 -0.9 0.893151 0.893151 0.446575 -0.893151 -2.1 -0.9 0.900865 0.900865 0.450432 -0.900865 -2 -0.9 0.908282 0.908282 0.454141 -0.908282 -1.9 -0.9 0.915395 0.915395 0.457697 -0.915395 -1.8 -0.9 0.922194 0.922194 0.461097 -0.922194 -1.7 -0.9 0.928672 0.928672 0.464336 -0.928672 -1.6 -0.9 0.934821 0.934821 0.467411 -0.934821 -1.5 -0.9 0.940635 0.940635 0.470318 -0.940635 -1.4 -0.9 0.946107 0.946107 0.473053 -0.946107 -1.3 -0.9 0.951229 0.951229 0.475615 -0.951229 -1.2 -0.9 0.955997 0.955997 0.477999 -0.955997 -1.1 -0.9 0.960405 0.960405 0.480203 -0.960405 -1 -0.9 0.964447 0.964447 0.482224 -0.964447 -0.9 -0.9 0.968119 0.968119 0.48406 -0.968119 -0.8 -0.9 0.971416 0.971416 0.485708 -0.971416 -0.7 -0.9 0.974335 0.974335 0.487168 -0.974335 -0.6 -0.9 0.976872 0.976872 0.488436 -0.976872 -0.5 -0.9 0.979023 0.979023 0.489512 -0.979023 -0.4 -0.9 0.980787 0.980787 0.490393 -0.980787 -0.3 -0.9 0.982161 0.982161 0.491081 -0.982161 -0.2 -0.9 0.983144 0.983144 0.491572 -0.983144 -0.1 -0.9 0.983734 0.983734 0.491867 -0.983734 0 -0.9 0.983931 0.983931 0.491965 -0.983931 0.1 -0.9 0.983734 0.983734 0.491867 -0.983734 0.2 -0.9 0.983144 0.983144 0.491572 -0.983144 0.3 -0.9 0.982161 0.982161 0.491081 -0.982161 0.4 -0.9 0.980787 0.980787 0.490393 -0.980787 0.5 -0.9 0.979023 0.979023 0.489512 -0.979023 0.6 -0.9 0.976872 0.976872 0.488436 -0.976872 0.7 -0.9 0.974335 0.974335 0.487168 -0.974335 0.8 -0.9 0.971416 0.971416 0.485708 -0.971416 0.9 -0.9 0.968119 0.968119 0.48406 -0.968119 1 -0.9 0.964447 0.964447 0.482224 -0.964447 1.1 -0.9 0.960405 0.960405 0.480203 -0.960405 1.2 -0.9 0.955997 0.955997 0.477999 -0.955997 1.3 -0.9 0.951229 0.951229 0.475615 -0.951229 1.4 -0.9 0.946107 0.946107 0.473053 -0.946107 1.5 -0.9 0.940635 0.940635 0.470318 -0.940635 1.6 -0.9 0.934821 0.934821 0.467411 -0.934821 1.7 -0.9 0.928672 0.928672 0.464336 -0.928672 1.8 -0.9 0.922194 0.922194 0.461097 -0.922194 1.9 -0.9 0.915395 0.915395 0.457697 -0.915395 2 -0.9 0.908282 0.908282 0.454141 -0.908282 2.1 -0.9 0.900865 0.900865 0.450432 -0.900865 2.2 -0.9 0.893151 0.893151 0.446575 -0.893151 2.3 -0.9 0.885148 0.885148 0.442574 -0.885148 2.4 -0.9 0.876867 0.876867 0.438433 -0.876867 2.5 -0.9 0.868316 0.868316 0.434158 -0.868316 2.6 -0.9 0.859504 0.859504 0.429752 -0.859504 2.7 -0.9 0.850441 0.850441 0.425221 -0.850441 2.8 -0.9 0.841138 0.841138 0.420569 -0.841138 2.9 -0.9 0.831603 0.831603 0.415802 -0.831603 3 -0.9 0.821848 0.821848 0.410924 -0.821848 3.1 -0.9 0.811882 0.811882 0.405941 -0.811882 3.2 -0.9 0.801717 0.801717 0.400858 -0.801717 3.3 -0.9 0.791362 0.791362 0.395681 -0.791362 3.4 -0.9 0.780828 0.780828 0.390414 -0.780828 3.5 -0.9 0.770127 0.770127 0.385063 -0.770127 3.6 -0.9 0.759268 0.759268 0.379634 -0.759268 3.7 -0.9 0.748264 0.748264 0.374132 -0.748264 3.8 -0.9 0.737123 0.737123 0.368562 -0.737123 3.9 -0.9 0.725859 0.725859 0.362929 -0.725859 4 -0.9 0.71448 0.71448 0.35724 -0.71448 4.1 -0.9 0.702999 0.702999 0.351499 -0.702999 4.2 -0.9 0.691425 0.691425 0.345713 -0.691425 4.3 -0.9 0.679771 0.679771 0.339885 -0.679771 4.4 -0.9 0.668045 0.668045 0.334022 -0.668045 4.5 -0.9 0.656259 0.656259 0.328129 -0.656259 4.6 -0.9 0.644423 0.644423 0.322211 -0.644423 4.7 -0.9 0.632547 0.632547 0.316274 -0.632547 4.8 -0.9 0.620643 0.620643 0.310321 -0.620643 4.9 -0.9 0.608718 0.608718 0.304359 -0.608718 -5 -0.8 0.598817 0.598817 0.299408 -0.598817 -4.9 -0.8 0.610791 0.610791 0.305396 -0.610791 -4.8 -0.8 0.622756 0.622756 0.311378 -0.622756 -4.7 -0.8 0.634702 0.634702 0.317351 -0.634702 -4.6 -0.8 0.646618 0.646618 0.323309 -0.646618 -4.5 -0.8 0.658494 0.658494 0.329247 -0.658494 -4.4 -0.8 0.67032 0.67032 0.33516 -0.67032 -4.3 -0.8 0.682086 0.682086 0.341043 -0.682086 -4.2 -0.8 0.69378 0.69378 0.34689 -0.69378 -4.1 -0.8 0.705393 0.705393 0.352697 -0.705393 -4 -0.8 0.716914 0.716914 0.358457 -0.716914 -3.9 -0.8 0.728331 0.728331 0.364165 -0.728331 -3.8 -0.8 0.739634 0.739634 0.369817 -0.739634 -3.7 -0.8 0.750812 0.750812 0.375406 -0.750812 -3.6 -0.8 0.761854 0.761854 0.380927 -0.761854 -3.5 -0.8 0.77275 0.77275 0.386375 -0.77275 -3.4 -0.8 0.783488 0.783488 0.391744 -0.783488 -3.3 -0.8 0.794057 0.794057 0.397029 -0.794057 -3.2 -0.8 0.804447 0.804447 0.402224 -0.804447 -3.1 -0.8 0.814647 0.814647 0.407324 -0.814647 -3 -0.8 0.824647 0.824647 0.412323 -0.824647 -2.9 -0.8 0.834435 0.834435 0.417218 -0.834435 -2.8 -0.8 0.844002 0.844002 0.422001 -0.844002 -2.7 -0.8 0.853338 0.853338 0.426669 -0.853338 -2.6 -0.8 0.862431 0.862431 0.431216 -0.862431 -2.5 -0.8 0.871273 0.871273 0.435636 -0.871273 -2.4 -0.8 0.879853 0.879853 0.439927 -0.879853 -2.3 -0.8 0.888163 0.888163 0.444081 -0.888163 -2.2 -0.8 0.896193 0.896193 0.448096 -0.896193 -2.1 -0.8 0.903933 0.903933 0.451967 -0.903933 -2 -0.8 0.911376 0.911376 0.455688 -0.911376 -1.9 -0.8 0.918512 0.918512 0.459256 -0.918512 -1.8 -0.8 0.925334 0.925334 0.462667 -0.925334 -1.7 -0.8 0.931835 0.931835 0.465917 -0.931835 -1.6 -0.8 0.938005 0.938005 0.469002 -0.938005 -1.5 -0.8 0.943839 0.943839 0.471919 -0.943839 -1.4 -0.8 0.949329 0.949329 0.474664 -0.949329 -1.3 -0.8 0.954469 0.954469 0.477235 -0.954469 -1.2 -0.8 0.959253 0.959253 0.479627 -0.959253 -1.1 -0.8 0.963676 0.963676 0.481838 -0.963676 -1 -0.8 0.967732 0.967732 0.483866 -0.967732 -0.9 -0.8 0.971416 0.971416 0.485708 -0.971416 -0.8 -0.8 0.974725 0.974725 0.487362 -0.974725 -0.7 -0.8 0.977653 0.977653 0.488827 -0.977653 -0.6 -0.8 0.980199 0.980199 0.490099 -0.980199 -0.5 -0.8 0.982357 0.982357 0.491179 -0.982357 -0.4 -0.8 0.984127 0.984127 0.492064 -0.984127 -0.3 -0.8 0.985506 0.985506 0.492753 -0.985506 -0.2 -0.8 0.986492 0.986492 0.493246 -0.986492 -0.1 -0.8 0.987084 0.987084 0.493542 -0.987084 0 -0.8 0.987282 0.987282 0.493641 -0.987282 0.1 -0.8 0.987084 0.987084 0.493542 -0.987084 0.2 -0.8 0.986492 0.986492 0.493246 -0.986492 0.3 -0.8 0.985506 0.985506 0.492753 -0.985506 0.4 -0.8 0.984127 0.984127 0.492064 -0.984127 0.5 -0.8 0.982357 0.982357 0.491179 -0.982357 0.6 -0.8 0.980199 0.980199 0.490099 -0.980199 0.7 -0.8 0.977653 0.977653 0.488827 -0.977653 0.8 -0.8 0.974725 0.974725 0.487362 -0.974725 0.9 -0.8 0.971416 0.971416 0.485708 -0.971416 1 -0.8 0.967732 0.967732 0.483866 -0.967732 1.1 -0.8 0.963676 0.963676 0.481838 -0.963676 1.2 -0.8 0.959253 0.959253 0.479627 -0.959253 1.3 -0.8 0.954469 0.954469 0.477235 -0.954469 1.4 -0.8 0.949329 0.949329 0.474664 -0.949329 1.5 -0.8 0.943839 0.943839 0.471919 -0.943839 1.6 -0.8 0.938005 0.938005 0.469002 -0.938005 1.7 -0.8 0.931835 0.931835 0.465917 -0.931835 1.8 -0.8 0.925334 0.925334 0.462667 -0.925334 1.9 -0.8 0.918512 0.918512 0.459256 -0.918512 2 -0.8 0.911376 0.911376 0.455688 -0.911376 2.1 -0.8 0.903933 0.903933 0.451967 -0.903933 2.2 -0.8 0.896193 0.896193 0.448096 -0.896193 2.3 -0.8 0.888163 0.888163 0.444081 -0.888163 2.4 -0.8 0.879853 0.879853 0.439927 -0.879853 2.5 -0.8 0.871273 0.871273 0.435636 -0.871273 2.6 -0.8 0.862431 0.862431 0.431216 -0.862431 2.7 -0.8 0.853338 0.853338 0.426669 -0.853338 2.8 -0.8 0.844002 0.844002 0.422001 -0.844002 2.9 -0.8 0.834435 0.834435 0.417218 -0.834435 3 -0.8 0.824647 0.824647 0.412323 -0.824647 3.1 -0.8 0.814647 0.814647 0.407324 -0.814647 3.2 -0.8 0.804447 0.804447 0.402224 -0.804447 3.3 -0.8 0.794057 0.794057 0.397029 -0.794057 3.4 -0.8 0.783488 0.783488 0.391744 -0.783488 3.5 -0.8 0.77275 0.77275 0.386375 -0.77275 3.6 -0.8 0.761854 0.761854 0.380927 -0.761854 3.7 -0.8 0.750812 0.750812 0.375406 -0.750812 3.8 -0.8 0.739634 0.739634 0.369817 -0.739634 3.9 -0.8 0.728331 0.728331 0.364165 -0.728331 4 -0.8 0.716914 0.716914 0.358457 -0.716914 4.1 -0.8 0.705393 0.705393 0.352697 -0.705393 4.2 -0.8 0.69378 0.69378 0.34689 -0.69378 4.3 -0.8 0.682086 0.682086 0.341043 -0.682086 4.4 -0.8 0.67032 0.67032 0.33516 -0.67032 4.5 -0.8 0.658494 0.658494 0.329247 -0.658494 4.6 -0.8 0.646618 0.646618 0.323309 -0.646618 4.7 -0.8 0.634702 0.634702 0.317351 -0.634702 4.8 -0.8 0.622756 0.622756 0.311378 -0.622756 4.9 -0.8 0.610791 0.610791 0.305396 -0.610791 -5 -0.7 0.600616 0.600616 0.300308 -0.600616 -4.9 -0.7 0.612626 0.612626 0.306313 -0.612626 -4.8 -0.7 0.624627 0.624627 0.312314 -0.624627 -4.7 -0.7 0.636609 0.636609 0.318304 -0.636609 -4.6 -0.7 0.64856 0.64856 0.32428 -0.64856 -4.5 -0.7 0.660472 0.660472 0.330236 -0.660472 -4.4 -0.7 0.672334 0.672334 0.336167 -0.672334 -4.3 -0.7 0.684135 0.684135 0.342068 -0.684135 -4.2 -0.7 0.695865 0.695865 0.347932 -0.695865 -4.1 -0.7 0.707512 0.707512 0.353756 -0.707512 -4 -0.7 0.719068 0.719068 0.359534 -0.719068 -3.9 -0.7 0.730519 0.730519 0.36526 -0.730519 -3.8 -0.7 0.741856 0.741856 0.370928 -0.741856 -3.7 -0.7 0.753068 0.753068 0.376534 -0.753068 -3.6 -0.7 0.764143 0.764143 0.382072 -0.764143 -3.5 -0.7 0.775071 0.775071 0.387536 -0.775071 -3.4 -0.7 0.785842 0.785842 0.392921 -0.785842 -3.3 -0.7 0.796443 0.796443 0.398221 -0.796443 -3.2 -0.7 0.806864 0.806864 0.403432 -0.806864 -3.1 -0.7 0.817095 0.817095 0.408547 -0.817095 -3 -0.7 0.827125 0.827125 0.413562 -0.827125 -2.9 -0.7 0.836942 0.836942 0.418471 -0.836942 -2.8 -0.7 0.846538 0.846538 0.423269 -0.846538 -2.7 -0.7 0.855901 0.855901 0.427951 -0.855901 -2.6 -0.7 0.865022 0.865022 0.432511 -0.865022 -2.5 -0.7 0.873891 0.873891 0.436945 -0.873891 -2.4 -0.7 0.882497 0.882497 0.441248 -0.882497 -2.3 -0.7 0.890831 0.890831 0.445416 -0.890831 -2.2 -0.7 0.898885 0.898885 0.449443 -0.898885 -2.1 -0.7 0.906649 0.906649 0.453324 -0.906649 -2 -0.7 0.914114 0.914114 0.457057 -0.914114 -1.9 -0.7 0.921272 0.921272 0.460636 -0.921272 -1.8 -0.7 0.928115 0.928115 0.464057 -0.928115 -1.7 -0.7 0.934634 0.934634 0.467317 -0.934634 -1.6 -0.7 0.940823 0.940823 0.470412 -0.940823 -1.5 -0.7 0.946674 0.946674 0.473337 -0.946674 -1.4 -0.7 0.952181 0.952181 0.476091 -0.952181 -1.3 -0.7 0.957337 0.957337 0.478668 -0.957337 -1.2 -0.7 0.962135 0.962135 0.481068 -0.962135 -1.1 -0.7 0.966572 0.966572 0.483286 -0.966572 -1 -0.7 0.97064 0.97064 0.48532 -0.97064 -0.9 -0.7 0.974335 0.974335 0.487168 -0.974335 -0.8 -0.7 0.977653 0.977653 0.488827 -0.977653 -0.7 -0.7 0.980591 0.980591 0.490295 -0.980591 -0.6 -0.7 0.983144 0.983144 0.491572 -0.983144 -0.5 -0.7 0.985309 0.985309 0.492654 -0.985309 -0.4 -0.7 0.987084 0.987084 0.493542 -0.987084 -0.3 -0.7 0.988467 0.988467 0.494234 -0.988467 -0.2 -0.7 0.989456 0.989456 0.494728 -0.989456 -0.1 -0.7 0.99005 0.99005 0.495025 -0.99005 0 -0.7 0.990248 0.990248 0.495124 -0.990248 0.1 -0.7 0.99005 0.99005 0.495025 -0.99005 0.2 -0.7 0.989456 0.989456 0.494728 -0.989456 0.3 -0.7 0.988467 0.988467 0.494234 -0.988467 0.4 -0.7 0.987084 0.987084 0.493542 -0.987084 0.5 -0.7 0.985309 0.985309 0.492654 -0.985309 0.6 -0.7 0.983144 0.983144 0.491572 -0.983144 0.7 -0.7 0.980591 0.980591 0.490295 -0.980591 0.8 -0.7 0.977653 0.977653 0.488827 -0.977653 0.9 -0.7 0.974335 0.974335 0.487168 -0.974335 1 -0.7 0.97064 0.97064 0.48532 -0.97064 1.1 -0.7 0.966572 0.966572 0.483286 -0.966572 1.2 -0.7 0.962135 0.962135 0.481068 -0.962135 1.3 -0.7 0.957337 0.957337 0.478668 -0.957337 1.4 -0.7 0.952181 0.952181 0.476091 -0.952181 1.5 -0.7 0.946674 0.946674 0.473337 -0.946674 1.6 -0.7 0.940823 0.940823 0.470412 -0.940823 1.7 -0.7 0.934634 0.934634 0.467317 -0.934634 1.8 -0.7 0.928115 0.928115 0.464057 -0.928115 1.9 -0.7 0.921272 0.921272 0.460636 -0.921272 2 -0.7 0.914114 0.914114 0.457057 -0.914114 2.1 -0.7 0.906649 0.906649 0.453324 -0.906649 2.2 -0.7 0.898885 0.898885 0.449443 -0.898885 2.3 -0.7 0.890831 0.890831 0.445416 -0.890831 2.4 -0.7 0.882497 0.882497 0.441248 -0.882497 2.5 -0.7 0.873891 0.873891 0.436945 -0.873891 2.6 -0.7 0.865022 0.865022 0.432511 -0.865022 2.7 -0.7 0.855901 0.855901 0.427951 -0.855901 2.8 -0.7 0.846538 0.846538 0.423269 -0.846538 2.9 -0.7 0.836942 0.836942 0.418471 -0.836942 3 -0.7 0.827125 0.827125 0.413562 -0.827125 3.1 -0.7 0.817095 0.817095 0.408547 -0.817095 3.2 -0.7 0.806864 0.806864 0.403432 -0.806864 3.3 -0.7 0.796443 0.796443 0.398221 -0.796443 3.4 -0.7 0.785842 0.785842 0.392921 -0.785842 3.5 -0.7 0.775071 0.775071 0.387536 -0.775071 3.6 -0.7 0.764143 0.764143 0.382072 -0.764143 3.7 -0.7 0.753068 0.753068 0.376534 -0.753068 3.8 -0.7 0.741856 0.741856 0.370928 -0.741856 3.9 -0.7 0.730519 0.730519 0.36526 -0.730519 4 -0.7 0.719068 0.719068 0.359534 -0.719068 4.1 -0.7 0.707512 0.707512 0.353756 -0.707512 4.2 -0.7 0.695865 0.695865 0.347932 -0.695865 4.3 -0.7 0.684135 0.684135 0.342068 -0.684135 4.4 -0.7 0.672334 0.672334 0.336167 -0.672334 4.5 -0.7 0.660472 0.660472 0.330236 -0.660472 4.6 -0.7 0.64856 0.64856 0.32428 -0.64856 4.7 -0.7 0.636609 0.636609 0.318304 -0.636609 4.8 -0.7 0.624627 0.624627 0.312314 -0.624627 4.9 -0.7 0.612626 0.612626 0.306313 -0.612626 -5 -0.6 0.602179 0.602179 0.30109 -0.602179 -4.9 -0.6 0.614221 0.614221 0.307111 -0.614221 -4.8 -0.6 0.626254 0.626254 0.313127 -0.626254 -4.7 -0.6 0.638266 0.638266 0.319133 -0.638266 -4.6 -0.6 0.650249 0.650249 0.325124 -0.650249 -4.5 -0.6 0.662192 0.662192 0.331096 -0.662192 -4.4 -0.6 0.674084 0.674084 0.337042 -0.674084 -4.3 -0.6 0.685916 0.685916 0.342958 -0.685916 -4.2 -0.6 0.697676 0.697676 0.348838 -0.697676 -4.1 -0.6 0.709354 0.709354 0.354677 -0.709354 -4 -0.6 0.72094 0.72094 0.36047 -0.72094 -3.9 -0.6 0.732421 0.732421 0.36621 -0.732421 -3.8 -0.6 0.743787 0.743787 0.371894 -0.743787 -3.7 -0.6 0.755028 0.755028 0.377514 -0.755028 -3.6 -0.6 0.766133 0.766133 0.383066 -0.766133 -3.5 -0.6 0.777089 0.777089 0.388545 -0.777089 -3.4 -0.6 0.787887 0.787887 0.393944 -0.787887 -3.3 -0.6 0.798516 0.798516 0.399258 -0.798516 -3.2 -0.6 0.808965 0.808965 0.404482 -0.808965 -3.1 -0.6 0.819222 0.819222 0.409611 -0.819222 -3 -0.6 0.829278 0.829278 0.414639 -0.829278 -2.9 -0.6 0.839121 0.839121 0.419561 -0.839121 -2.8 -0.6 0.848742 0.848742 0.424371 -0.848742 -2.7 -0.6 0.85813 0.85813 0.429065 -0.85813 -2.6 -0.6 0.867274 0.867274 0.433637 -0.867274 -2.5 -0.6 0.876166 0.876166 0.438083 -0.876166 -2.4 -0.6 0.884794 0.884794 0.442397 -0.884794 -2.3 -0.6 0.893151 0.893151 0.446575 -0.893151 -2.2 -0.6 0.901225 0.901225 0.450613 -0.901225 -2.1 -0.6 0.909009 0.909009 0.454505 -0.909009 -2 -0.6 0.916494 0.916494 0.458247 -0.916494 -1.9 -0.6 0.92367 0.92367 0.461835 -0.92367 -1.8 -0.6 0.930531 0.930531 0.465265 -0.930531 -1.7 -0.6 0.937067 0.937067 0.468534 -0.937067 -1.6 -0.6 0.943273 0.943273 0.471636 -0.943273 -1.5 -0.6 0.949139 0.949139 0.47457 -0.949139 -1.4 -0.6 0.95466 0.95466 0.47733 -0.95466 -1.3 -0.6 0.959829 0.959829 0.479915 -0.959829 -1.2 -0.6 0.96464 0.96464 0.48232 -0.96464 -1.1 -0.6 0.969088 0.969088 0.484544 -0.969088 -1 -0.6 0.973167 0.973167 0.486583 -0.973167 -0.9 -0.6 0.976872 0.976872 0.488436 -0.976872 -0.8 -0.6 0.980199 0.980199 0.490099 -0.980199 -0.7 -0.6 0.983144 0.983144 0.491572 -0.983144 -0.6 -0.6 0.985703 0.985703 0.492852 -0.985703 -0.5 -0.6 0.987874 0.987874 0.493937 -0.987874 -0.4 -0.6 0.989654 0.989654 0.494827 -0.989654 -0.3 -0.6 0.99104 0.99104 0.49552 -0.99104 -0.2 -0.6 0.992032 0.992032 0.496016 -0.992032 -0.1 -0.6 0.992627 0.992627 0.496314 -0.992627 0 -0.6 0.992826 0.992826 0.496413 -0.992826 0.1 -0.6 0.992627 0.992627 0.496314 -0.992627 0.2 -0.6 0.992032 0.992032 0.496016 -0.992032 0.3 -0.6 0.99104 0.99104 0.49552 -0.99104 0.4 -0.6 0.989654 0.989654 0.494827 -0.989654 0.5 -0.6 0.987874 0.987874 0.493937 -0.987874 0.6 -0.6 0.985703 0.985703 0.492852 -0.985703 0.7 -0.6 0.983144 0.983144 0.491572 -0.983144 0.8 -0.6 0.980199 0.980199 0.490099 -0.980199 0.9 -0.6 0.976872 0.976872 0.488436 -0.976872 1 -0.6 0.973167 0.973167 0.486583 -0.973167 1.1 -0.6 0.969088 0.969088 0.484544 -0.969088 1.2 -0.6 0.96464 0.96464 0.48232 -0.96464 1.3 -0.6 0.959829 0.959829 0.479915 -0.959829 1.4 -0.6 0.95466 0.95466 0.47733 -0.95466 1.5 -0.6 0.949139 0.949139 0.47457 -0.949139 1.6 -0.6 0.943273 0.943273 0.471636 -0.943273 1.7 -0.6 0.937067 0.937067 0.468534 -0.937067 1.8 -0.6 0.930531 0.930531 0.465265 -0.930531 1.9 -0.6 0.92367 0.92367 0.461835 -0.92367 2 -0.6 0.916494 0.916494 0.458247 -0.916494 2.1 -0.6 0.909009 0.909009 0.454505 -0.909009 2.2 -0.6 0.901225 0.901225 0.450613 -0.901225 2.3 -0.6 0.893151 0.893151 0.446575 -0.893151 2.4 -0.6 0.884794 0.884794 0.442397 -0.884794 2.5 -0.6 0.876166 0.876166 0.438083 -0.876166 2.6 -0.6 0.867274 0.867274 0.433637 -0.867274 2.7 -0.6 0.85813 0.85813 0.429065 -0.85813 2.8 -0.6 0.848742 0.848742 0.424371 -0.848742 2.9 -0.6 0.839121 0.839121 0.419561 -0.839121 3 -0.6 0.829278 0.829278 0.414639 -0.829278 3.1 -0.6 0.819222 0.819222 0.409611 -0.819222 3.2 -0.6 0.808965 0.808965 0.404482 -0.808965 3.3 -0.6 0.798516 0.798516 0.399258 -0.798516 3.4 -0.6 0.787887 0.787887 0.393944 -0.787887 3.5 -0.6 0.777089 0.777089 0.388545 -0.777089 3.6 -0.6 0.766133 0.766133 0.383066 -0.766133 3.7 -0.6 0.755028 0.755028 0.377514 -0.755028 3.8 -0.6 0.743787 0.743787 0.371894 -0.743787 3.9 -0.6 0.732421 0.732421 0.36621 -0.732421 4 -0.6 0.72094 0.72094 0.36047 -0.72094 4.1 -0.6 0.709354 0.709354 0.354677 -0.709354 4.2 -0.6 0.697676 0.697676 0.348838 -0.697676 4.3 -0.6 0.685916 0.685916 0.342958 -0.685916 4.4 -0.6 0.674084 0.674084 0.337042 -0.674084 4.5 -0.6 0.662192 0.662192 0.331096 -0.662192 4.6 -0.6 0.650249 0.650249 0.325124 -0.650249 4.7 -0.6 0.638266 0.638266 0.319133 -0.638266 4.8 -0.6 0.626254 0.626254 0.313127 -0.626254 4.9 -0.6 0.614221 0.614221 0.307111 -0.614221 -5 -0.5 0.603506 0.603506 0.301753 -0.603506 -4.9 -0.5 0.615574 0.615574 0.307787 -0.615574 -4.8 -0.5 0.627633 0.627633 0.313816 -0.627633 -4.7 -0.5 0.639672 0.639672 0.319836 -0.639672 -4.6 -0.5 0.651681 0.651681 0.325841 -0.651681 -4.5 -0.5 0.66365 0.66365 0.331825 -0.66365 -4.4 -0.5 0.675569 0.675569 0.337784 -0.675569 -4.3 -0.5 0.687427 0.687427 0.343713 -0.687427 -4.2 -0.5 0.699213 0.699213 0.349606 -0.699213 -4.1 -0.5 0.710917 0.710917 0.355458 -0.710917 -4 -0.5 0.722527 0.722527 0.361264 -0.722527 -3.9 -0.5 0.734034 0.734034 0.367017 -0.734034 -3.8 -0.5 0.745426 0.745426 0.372713 -0.745426 -3.7 -0.5 0.756691 0.756691 0.378346 -0.756691 -3.6 -0.5 0.76782 0.76782 0.38391 -0.76782 -3.5 -0.5 0.778801 0.778801 0.3894 -0.778801 -3.4 -0.5 0.789623 0.789623 0.394811 -0.789623 -3.3 -0.5 0.800275 0.800275 0.400137 -0.800275 -3.2 -0.5 0.810746 0.810746 0.405373 -0.810746 -3.1 -0.5 0.821026 0.821026 0.410513 -0.821026 -3 -0.5 0.831104 0.831104 0.415552 -0.831104 -2.9 -0.5 0.840969 0.840969 0.420485 -0.840969 -2.8 -0.5 0.850611 0.850611 0.425306 -0.850611 -2.7 -0.5 0.86002 0.86002 0.43001 -0.86002 -2.6 -0.5 0.869184 0.869184 0.434592 -0.869184 -2.5 -0.5 0.878095 0.878095 0.439048 -0.878095 -2.4 -0.5 0.886743 0.886743 0.443372 -0.886743 -2.3 -0.5 0.895118 0.895118 0.447559 -0.895118 -2.2 -0.5 0.90321 0.90321 0.451605 -0.90321 -2.1 -0.5 0.911011 0.911011 0.455506 -0.911011 -2 -0.5 0.918512 0.918512 0.459256 -0.918512 -1.9 -0.5 0.925705 0.925705 0.462852 -0.925705 -1.8 -0.5 0.93258 0.93258 0.46629 -0.93258 -1.7 -0.5 0.939131 0.939131 0.469566 -0.939131 -1.6 -0.5 0.94535 0.94535 0.472675 -0.94535 -1.5 -0.5 0.951229 0.951229 0.475615 -0.951229 -1.4 -0.5 0.956763 0.956763 0.478381 -0.956763 -1.3 -0.5 0.961943 0.961943 0.480972 -0.961943 -1.2 -0.5 0.966765 0.966765 0.483382 -0.966765 -1.1 -0.5 0.971222 0.971222 0.485611 -0.971222 -1 -0.5 0.97531 0.97531 0.487655 -0.97531 -0.9 -0.5 0.979023 0.979023 0.489512 -0.979023 -0.8 -0.5 0.982357 0.982357 0.491179 -0.982357 -0.7 -0.5 0.985309 0.985309 0.492654 -0.985309 -0.6 -0.5 0.987874 0.987874 0.493937 -0.987874 -0.5 -0.5 0.99005 0.99005 0.495025 -0.99005 -0.4 -0.5 0.991834 0.991834 0.495917 -0.991834 -0.3 -0.5 0.993223 0.993223 0.496612 -0.993223 -0.2 -0.5 0.994217 0.994217 0.497108 -0.994217 -0.1 -0.5 0.994813 0.994813 0.497407 -0.994813 0 -0.5 0.995012 0.995012 0.497506 -0.995012 0.1 -0.5 0.994813 0.994813 0.497407 -0.994813 0.2 -0.5 0.994217 0.994217 0.497108 -0.994217 0.3 -0.5 0.993223 0.993223 0.496612 -0.993223 0.4 -0.5 0.991834 0.991834 0.495917 -0.991834 0.5 -0.5 0.99005 0.99005 0.495025 -0.99005 0.6 -0.5 0.987874 0.987874 0.493937 -0.987874 0.7 -0.5 0.985309 0.985309 0.492654 -0.985309 0.8 -0.5 0.982357 0.982357 0.491179 -0.982357 0.9 -0.5 0.979023 0.979023 0.489512 -0.979023 1 -0.5 0.97531 0.97531 0.487655 -0.97531 1.1 -0.5 0.971222 0.971222 0.485611 -0.971222 1.2 -0.5 0.966765 0.966765 0.483382 -0.966765 1.3 -0.5 0.961943 0.961943 0.480972 -0.961943 1.4 -0.5 0.956763 0.956763 0.478381 -0.956763 1.5 -0.5 0.951229 0.951229 0.475615 -0.951229 1.6 -0.5 0.94535 0.94535 0.472675 -0.94535 1.7 -0.5 0.939131 0.939131 0.469566 -0.939131 1.8 -0.5 0.93258 0.93258 0.46629 -0.93258 1.9 -0.5 0.925705 0.925705 0.462852 -0.925705 2 -0.5 0.918512 0.918512 0.459256 -0.918512 2.1 -0.5 0.911011 0.911011 0.455506 -0.911011 2.2 -0.5 0.90321 0.90321 0.451605 -0.90321 2.3 -0.5 0.895118 0.895118 0.447559 -0.895118 2.4 -0.5 0.886743 0.886743 0.443372 -0.886743 2.5 -0.5 0.878095 0.878095 0.439048 -0.878095 2.6 -0.5 0.869184 0.869184 0.434592 -0.869184 2.7 -0.5 0.86002 0.86002 0.43001 -0.86002 2.8 -0.5 0.850611 0.850611 0.425306 -0.850611 2.9 -0.5 0.840969 0.840969 0.420485 -0.840969 3 -0.5 0.831104 0.831104 0.415552 -0.831104 3.1 -0.5 0.821026 0.821026 0.410513 -0.821026 3.2 -0.5 0.810746 0.810746 0.405373 -0.810746 3.3 -0.5 0.800275 0.800275 0.400137 -0.800275 3.4 -0.5 0.789623 0.789623 0.394811 -0.789623 3.5 -0.5 0.778801 0.778801 0.3894 -0.778801 3.6 -0.5 0.76782 0.76782 0.38391 -0.76782 3.7 -0.5 0.756691 0.756691 0.378346 -0.756691 3.8 -0.5 0.745426 0.745426 0.372713 -0.745426 3.9 -0.5 0.734034 0.734034 0.367017 -0.734034 4 -0.5 0.722527 0.722527 0.361264 -0.722527 4.1 -0.5 0.710917 0.710917 0.355458 -0.710917 4.2 -0.5 0.699213 0.699213 0.349606 -0.699213 4.3 -0.5 0.687427 0.687427 0.343713 -0.687427 4.4 -0.5 0.675569 0.675569 0.337784 -0.675569 4.5 -0.5 0.66365 0.66365 0.331825 -0.66365 4.6 -0.5 0.651681 0.651681 0.325841 -0.651681 4.7 -0.5 0.639672 0.639672 0.319836 -0.639672 4.8 -0.5 0.627633 0.627633 0.313816 -0.627633 4.9 -0.5 0.615574 0.615574 0.307787 -0.615574 -5 -0.4 0.604593 0.604593 0.302296 -0.604593 -4.9 -0.4 0.616683 0.616683 0.308342 -0.616683 -4.8 -0.4 0.628764 0.628764 0.314382 -0.628764 -4.7 -0.4 0.640824 0.640824 0.320412 -0.640824 -4.6 -0.4 0.652855 0.652855 0.326428 -0.652855 -4.5 -0.4 0.664846 0.664846 0.332423 -0.664846 -4.4 -0.4 0.676786 0.676786 0.338393 -0.676786 -4.3 -0.4 0.688665 0.688665 0.344333 -0.688665 -4.2 -0.4 0.700473 0.700473 0.350236 -0.700473 -4.1 -0.4 0.712198 0.712198 0.356099 -0.712198 -4 -0.4 0.723829 0.723829 0.361915 -0.723829 -3.9 -0.4 0.735356 0.735356 0.367678 -0.735356 -3.8 -0.4 0.746769 0.746769 0.373384 -0.746769 -3.7 -0.4 0.758054 0.758054 0.379027 -0.758054 -3.6 -0.4 0.769203 0.769203 0.384602 -0.769203 -3.5 -0.4 0.780204 0.780204 0.390102 -0.780204 -3.4 -0.4 0.791045 0.791045 0.395523 -0.791045 -3.3 -0.4 0.801717 0.801717 0.400858 -0.801717 -3.2 -0.4 0.812207 0.812207 0.406104 -0.812207 -3.1 -0.4 0.822506 0.822506 0.411253 -0.822506 -3 -0.4 0.832602 0.832602 0.416301 -0.832602 -2.9 -0.4 0.842485 0.842485 0.421242 -0.842485 -2.8 -0.4 0.852144 0.852144 0.426072 -0.852144 -2.7 -0.4 0.861569 0.861569 0.430785 -0.861569 -2.6 -0.4 0.87075 0.87075 0.435375 -0.87075 -2.5 -0.4 0.879677 0.879677 0.439839 -0.879677 -2.4 -0.4 0.888341 0.888341 0.44417 -0.888341 -2.3 -0.4 0.89673 0.89673 0.448365 -0.89673 -2.2 -0.4 0.904837 0.904837 0.452419 -0.904837 -2.1 -0.4 0.912653 0.912653 0.456326 -0.912653 -2 -0.4 0.920167 0.920167 0.460084 -0.920167 -1.9 -0.4 0.927372 0.927372 0.463686 -0.927372 -1.8 -0.4 0.93426 0.93426 0.46713 -0.93426 -1.7 -0.4 0.940823 0.940823 0.470412 -0.940823 -1.6 -0.4 0.947053 0.947053 0.473527 -0.947053 -1.5 -0.4 0.952943 0.952943 0.476472 -0.952943 -1.4 -0.4 0.958486 0.958486 0.479243 -0.958486 -1.3 -0.4 0.963676 0.963676 0.481838 -0.963676 -1.2 -0.4 0.968507 0.968507 0.484253 -0.968507 -1.1 -0.4 0.972972 0.972972 0.486486 -0.972972 -1 -0.4 0.977067 0.977067 0.488534 -0.977067 -0.9 -0.4 0.980787 0.980787 0.490393 -0.980787 -0.8 -0.4 0.984127 0.984127 0.492064 -0.984127 -0.7 -0.4 0.987084 0.987084 0.493542 -0.987084 -0.6 -0.4 0.989654 0.989654 0.494827 -0.989654 -0.5 -0.4 0.991834 0.991834 0.495917 -0.991834 -0.4 -0.4 0.99362 0.99362 0.49681 -0.99362 -0.3 -0.4 0.995012 0.995012 0.497506 -0.995012 -0.2 -0.4 0.996008 0.996008 0.498004 -0.996008 -0.1 -0.4 0.996606 0.996606 0.498303 -0.996606 0 -0.4 0.996805 0.996805 0.498403 -0.996805 0.1 -0.4 0.996606 0.996606 0.498303 -0.996606 0.2 -0.4 0.996008 0.996008 0.498004 -0.996008 0.3 -0.4 0.995012 0.995012 0.497506 -0.995012 0.4 -0.4 0.99362 0.99362 0.49681 -0.99362 0.5 -0.4 0.991834 0.991834 0.495917 -0.991834 0.6 -0.4 0.989654 0.989654 0.494827 -0.989654 0.7 -0.4 0.987084 0.987084 0.493542 -0.987084 0.8 -0.4 0.984127 0.984127 0.492064 -0.984127 0.9 -0.4 0.980787 0.980787 0.490393 -0.980787 1 -0.4 0.977067 0.977067 0.488534 -0.977067 1.1 -0.4 0.972972 0.972972 0.486486 -0.972972 1.2 -0.4 0.968507 0.968507 0.484253 -0.968507 1.3 -0.4 0.963676 0.963676 0.481838 -0.963676 1.4 -0.4 0.958486 0.958486 0.479243 -0.958486 1.5 -0.4 0.952943 0.952943 0.476472 -0.952943 1.6 -0.4 0.947053 0.947053 0.473527 -0.947053 1.7 -0.4 0.940823 0.940823 0.470412 -0.940823 1.8 -0.4 0.93426 0.93426 0.46713 -0.93426 1.9 -0.4 0.927372 0.927372 0.463686 -0.927372 2 -0.4 0.920167 0.920167 0.460084 -0.920167 2.1 -0.4 0.912653 0.912653 0.456326 -0.912653 2.2 -0.4 0.904837 0.904837 0.452419 -0.904837 2.3 -0.4 0.89673 0.89673 0.448365 -0.89673 2.4 -0.4 0.888341 0.888341 0.44417 -0.888341 2.5 -0.4 0.879677 0.879677 0.439839 -0.879677 2.6 -0.4 0.87075 0.87075 0.435375 -0.87075 2.7 -0.4 0.861569 0.861569 0.430785 -0.861569 2.8 -0.4 0.852144 0.852144 0.426072 -0.852144 2.9 -0.4 0.842485 0.842485 0.421242 -0.842485 3 -0.4 0.832602 0.832602 0.416301 -0.832602 3.1 -0.4 0.822506 0.822506 0.411253 -0.822506 3.2 -0.4 0.812207 0.812207 0.406104 -0.812207 3.3 -0.4 0.801717 0.801717 0.400858 -0.801717 3.4 -0.4 0.791045 0.791045 0.395523 -0.791045 3.5 -0.4 0.780204 0.780204 0.390102 -0.780204 3.6 -0.4 0.769203 0.769203 0.384602 -0.769203 3.7 -0.4 0.758054 0.758054 0.379027 -0.758054 3.8 -0.4 0.746769 0.746769 0.373384 -0.746769 3.9 -0.4 0.735356 0.735356 0.367678 -0.735356 4 -0.4 0.723829 0.723829 0.361915 -0.723829 4.1 -0.4 0.712198 0.712198 0.356099 -0.712198 4.2 -0.4 0.700473 0.700473 0.350236 -0.700473 4.3 -0.4 0.688665 0.688665 0.344333 -0.688665 4.4 -0.4 0.676786 0.676786 0.338393 -0.676786 4.5 -0.4 0.664846 0.664846 0.332423 -0.664846 4.6 -0.4 0.652855 0.652855 0.326428 -0.652855 4.7 -0.4 0.640824 0.640824 0.320412 -0.640824 4.8 -0.4 0.628764 0.628764 0.314382 -0.628764 4.9 -0.4 0.616683 0.616683 0.308342 -0.616683 -5 -0.3 0.60544 0.60544 0.30272 -0.60544 -4.9 -0.3 0.617547 0.617547 0.308774 -0.617547 -4.8 -0.3 0.629644 0.629644 0.314822 -0.629644 -4.7 -0.3 0.641722 0.641722 0.320861 -0.641722 -4.6 -0.3 0.65377 0.65377 0.326885 -0.65377 -4.5 -0.3 0.665777 0.665777 0.332889 -0.665777 -4.4 -0.3 0.677734 0.677734 0.338867 -0.677734 -4.3 -0.3 0.68963 0.68963 0.344815 -0.68963 -4.2 -0.3 0.701454 0.701454 0.350727 -0.701454 -4.1 -0.3 0.713195 0.713195 0.356598 -0.713195 -4 -0.3 0.724843 0.724843 0.362422 -0.724843 -3.9 -0.3 0.736387 0.736387 0.368193 -0.736387 -3.8 -0.3 0.747815 0.747815 0.373907 -0.747815 -3.7 -0.3 0.759117 0.759117 0.379558 -0.759117 -3.6 -0.3 0.770281 0.770281 0.38514 -0.770281 -3.5 -0.3 0.781297 0.781297 0.390648 -0.781297 -3.4 -0.3 0.792154 0.792154 0.396077 -0.792154 -3.3 -0.3 0.80284 0.80284 0.40142 -0.80284 -3.2 -0.3 0.813345 0.813345 0.406672 -0.813345 -3.1 -0.3 0.823658 0.823658 0.411829 -0.823658 -3 -0.3 0.833768 0.833768 0.416884 -0.833768 -2.9 -0.3 0.843665 0.843665 0.421832 -0.843665 -2.8 -0.3 0.853338 0.853338 0.426669 -0.853338 -2.7 -0.3 0.862776 0.862776 0.431388 -0.862776 -2.6 -0.3 0.87197 0.87197 0.435985 -0.87197 -2.5 -0.3 0.88091 0.88091 0.440455 -0.88091 -2.4 -0.3 0.889585 0.889585 0.444793 -0.889585 -2.3 -0.3 0.897987 0.897987 0.448993 -0.897987 -2.2 -0.3 0.906105 0.906105 0.453053 -0.906105 -2.1 -0.3 0.913931 0.913931 0.456966 -0.913931 -2 -0.3 0.921456 0.921456 0.460728 -0.921456 -1.9 -0.3 0.928672 0.928672 0.464336 -0.928672 -1.8 -0.3 0.935569 0.935569 0.467785 -0.935569 -1.7 -0.3 0.942141 0.942141 0.471071 -0.942141 -1.6 -0.3 0.94838 0.94838 0.47419 -0.94838 -1.5 -0.3 0.954278 0.954278 0.477139 -0.954278 -1.4 -0.3 0.959829 0.959829 0.479915 -0.959829 -1.3 -0.3 0.965026 0.965026 0.482513 -0.965026 -1.2 -0.3 0.969863 0.969863 0.484932 -0.969863 -1.1 -0.3 0.974335 0.974335 0.487168 -0.974335 -1 -0.3 0.978436 0.978436 0.489218 -0.978436 -0.9 -0.3 0.982161 0.982161 0.491081 -0.982161 -0.8 -0.3 0.985506 0.985506 0.492753 -0.985506 -0.7 -0.3 0.988467 0.988467 0.494234 -0.988467 -0.6 -0.3 0.99104 0.99104 0.49552 -0.99104 -0.5 -0.3 0.993223 0.993223 0.496612 -0.993223 -0.4 -0.3 0.995012 0.995012 0.497506 -0.995012 -0.3 -0.3 0.996406 0.996406 0.498203 -0.996406 -0.2 -0.3 0.997403 0.997403 0.498702 -0.997403 -0.1 -0.3 0.998002 0.998002 0.499001 -0.998002 0 -0.3 0.998202 0.998202 0.499101 -0.998202 0.1 -0.3 0.998002 0.998002 0.499001 -0.998002 0.2 -0.3 0.997403 0.997403 0.498702 -0.997403 0.3 -0.3 0.996406 0.996406 0.498203 -0.996406 0.4 -0.3 0.995012 0.995012 0.497506 -0.995012 0.5 -0.3 0.993223 0.993223 0.496612 -0.993223 0.6 -0.3 0.99104 0.99104 0.49552 -0.99104 0.7 -0.3 0.988467 0.988467 0.494234 -0.988467 0.8 -0.3 0.985506 0.985506 0.492753 -0.985506 0.9 -0.3 0.982161 0.982161 0.491081 -0.982161 1 -0.3 0.978436 0.978436 0.489218 -0.978436 1.1 -0.3 0.974335 0.974335 0.487168 -0.974335 1.2 -0.3 0.969863 0.969863 0.484932 -0.969863 1.3 -0.3 0.965026 0.965026 0.482513 -0.965026 1.4 -0.3 0.959829 0.959829 0.479915 -0.959829 1.5 -0.3 0.954278 0.954278 0.477139 -0.954278 1.6 -0.3 0.94838 0.94838 0.47419 -0.94838 1.7 -0.3 0.942141 0.942141 0.471071 -0.942141 1.8 -0.3 0.935569 0.935569 0.467785 -0.935569 1.9 -0.3 0.928672 0.928672 0.464336 -0.928672 2 -0.3 0.921456 0.921456 0.460728 -0.921456 2.1 -0.3 0.913931 0.913931 0.456966 -0.913931 2.2 -0.3 0.906105 0.906105 0.453053 -0.906105 2.3 -0.3 0.897987 0.897987 0.448993 -0.897987 2.4 -0.3 0.889585 0.889585 0.444793 -0.889585 2.5 -0.3 0.88091 0.88091 0.440455 -0.88091 2.6 -0.3 0.87197 0.87197 0.435985 -0.87197 2.7 -0.3 0.862776 0.862776 0.431388 -0.862776 2.8 -0.3 0.853338 0.853338 0.426669 -0.853338 2.9 -0.3 0.843665 0.843665 0.421832 -0.843665 3 -0.3 0.833768 0.833768 0.416884 -0.833768 3.1 -0.3 0.823658 0.823658 0.411829 -0.823658 3.2 -0.3 0.813345 0.813345 0.406672 -0.813345 3.3 -0.3 0.80284 0.80284 0.40142 -0.80284 3.4 -0.3 0.792154 0.792154 0.396077 -0.792154 3.5 -0.3 0.781297 0.781297 0.390648 -0.781297 3.6 -0.3 0.770281 0.770281 0.38514 -0.770281 3.7 -0.3 0.759117 0.759117 0.379558 -0.759117 3.8 -0.3 0.747815 0.747815 0.373907 -0.747815 3.9 -0.3 0.736387 0.736387 0.368193 -0.736387 4 -0.3 0.724843 0.724843 0.362422 -0.724843 4.1 -0.3 0.713195 0.713195 0.356598 -0.713195 4.2 -0.3 0.701454 0.701454 0.350727 -0.701454 4.3 -0.3 0.68963 0.68963 0.344815 -0.68963 4.4 -0.3 0.677734 0.677734 0.338867 -0.677734 4.5 -0.3 0.665777 0.665777 0.332889 -0.665777 4.6 -0.3 0.65377 0.65377 0.326885 -0.65377 4.7 -0.3 0.641722 0.641722 0.320861 -0.641722 4.8 -0.3 0.629644 0.629644 0.314822 -0.629644 4.9 -0.3 0.617547 0.617547 0.308774 -0.617547 -5 -0.2 0.606046 0.606046 0.303023 -0.606046 -4.9 -0.2 0.618165 0.618165 0.309082 -0.618165 -4.8 -0.2 0.630274 0.630274 0.315137 -0.630274 -4.7 -0.2 0.642364 0.642364 0.321182 -0.642364 -4.6 -0.2 0.654424 0.654424 0.327212 -0.654424 -4.5 -0.2 0.666443 0.666443 0.333222 -0.666443 -4.4 -0.2 0.678412 0.678412 0.339206 -0.678412 -4.3 -0.2 0.69032 0.69032 0.34516 -0.69032 -4.2 -0.2 0.702156 0.702156 0.351078 -0.702156 -4.1 -0.2 0.713909 0.713909 0.356954 -0.713909 -4 -0.2 0.725568 0.725568 0.362784 -0.725568 -3.9 -0.2 0.737123 0.737123 0.368562 -0.737123 -3.8 -0.2 0.748563 0.748563 0.374281 -0.748563 -3.7 -0.2 0.759876 0.759876 0.379938 -0.759876 -3.6 -0.2 0.771052 0.771052 0.385526 -0.771052 -3.5 -0.2 0.782079 0.782079 0.391039 -0.782079 -3.4 -0.2 0.792946 0.792946 0.396473 -0.792946 -3.3 -0.2 0.803643 0.803643 0.401822 -0.803643 -3.2 -0.2 0.814159 0.814159 0.407079 -0.814159 -3.1 -0.2 0.824482 0.824482 0.412241 -0.824482 -3 -0.2 0.834602 0.834602 0.417301 -0.834602 -2.9 -0.2 0.844509 0.844509 0.422254 -0.844509 -2.8 -0.2 0.854191 0.854191 0.427096 -0.854191 -2.7 -0.2 0.863639 0.863639 0.43182 -0.863639 -2.6 -0.2 0.872843 0.872843 0.436421 -0.872843 -2.5 -0.2 0.881791 0.881791 0.440896 -0.881791 -2.4 -0.2 0.890475 0.890475 0.445238 -0.890475 -2.3 -0.2 0.898885 0.898885 0.449443 -0.898885 -2.2 -0.2 0.907012 0.907012 0.453506 -0.907012 -2.1 -0.2 0.914846 0.914846 0.457423 -0.914846 -2 -0.2 0.922378 0.922378 0.461189 -0.922378 -1.9 -0.2 0.929601 0.929601 0.4648 -0.929601 -1.8 -0.2 0.936505 0.936505 0.468253 -0.936505 -1.7 -0.2 0.943084 0.943084 0.471542 -0.943084 -1.6 -0.2 0.949329 0.949329 0.474664 -0.949329 -1.5 -0.2 0.955233 0.955233 0.477616 -0.955233 -1.4 -0.2 0.960789 0.960789 0.480395 -0.960789 -1.3 -0.2 0.965992 0.965992 0.482996 -0.965992 -1.2 -0.2 0.970834 0.970834 0.485417 -0.970834 -1.1 -0.2 0.97531 0.97531 0.487655 -0.97531 -1 -0.2 0.979415 0.979415 0.489707 -0.979415 -0.9 -0.2 0.983144 0.983144 0.491572 -0.983144 -0.8 -0.2 0.986492 0.986492 0.493246 -0.986492 -0.7 -0.2 0.989456 0.989456 0.494728 -0.989456 -0.6 -0.2 0.992032 0.992032 0.496016 -0.992032 -0.5 -0.2 0.994217 0.994217 0.497108 -0.994217 -0.4 -0.2 0.996008 0.996008 0.498004 -0.996008 -0.3 -0.2 0.997403 0.997403 0.498702 -0.997403 -0.2 -0.2 0.998401 0.998401 0.499201 -0.998401 -0.1 -0.2 0.999 0.999 0.4995 -0.999 0 -0.2 0.9992 0.9992 0.4996 -0.9992 0.1 -0.2 0.999 0.999 0.4995 -0.999 0.2 -0.2 0.998401 0.998401 0.499201 -0.998401 0.3 -0.2 0.997403 0.997403 0.498702 -0.997403 0.4 -0.2 0.996008 0.996008 0.498004 -0.996008 0.5 -0.2 0.994217 0.994217 0.497108 -0.994217 0.6 -0.2 0.992032 0.992032 0.496016 -0.992032 0.7 -0.2 0.989456 0.989456 0.494728 -0.989456 0.8 -0.2 0.986492 0.986492 0.493246 -0.986492 0.9 -0.2 0.983144 0.983144 0.491572 -0.983144 1 -0.2 0.979415 0.979415 0.489707 -0.979415 1.1 -0.2 0.97531 0.97531 0.487655 -0.97531 1.2 -0.2 0.970834 0.970834 0.485417 -0.970834 1.3 -0.2 0.965992 0.965992 0.482996 -0.965992 1.4 -0.2 0.960789 0.960789 0.480395 -0.960789 1.5 -0.2 0.955233 0.955233 0.477616 -0.955233 1.6 -0.2 0.949329 0.949329 0.474664 -0.949329 1.7 -0.2 0.943084 0.943084 0.471542 -0.943084 1.8 -0.2 0.936505 0.936505 0.468253 -0.936505 1.9 -0.2 0.929601 0.929601 0.4648 -0.929601 2 -0.2 0.922378 0.922378 0.461189 -0.922378 2.1 -0.2 0.914846 0.914846 0.457423 -0.914846 2.2 -0.2 0.907012 0.907012 0.453506 -0.907012 2.3 -0.2 0.898885 0.898885 0.449443 -0.898885 2.4 -0.2 0.890475 0.890475 0.445238 -0.890475 2.5 -0.2 0.881791 0.881791 0.440896 -0.881791 2.6 -0.2 0.872843 0.872843 0.436421 -0.872843 2.7 -0.2 0.863639 0.863639 0.43182 -0.863639 2.8 -0.2 0.854191 0.854191 0.427096 -0.854191 2.9 -0.2 0.844509 0.844509 0.422254 -0.844509 3 -0.2 0.834602 0.834602 0.417301 -0.834602 3.1 -0.2 0.824482 0.824482 0.412241 -0.824482 3.2 -0.2 0.814159 0.814159 0.407079 -0.814159 3.3 -0.2 0.803643 0.803643 0.401822 -0.803643 3.4 -0.2 0.792946 0.792946 0.396473 -0.792946 3.5 -0.2 0.782079 0.782079 0.391039 -0.782079 3.6 -0.2 0.771052 0.771052 0.385526 -0.771052 3.7 -0.2 0.759876 0.759876 0.379938 -0.759876 3.8 -0.2 0.748563 0.748563 0.374281 -0.748563 3.9 -0.2 0.737123 0.737123 0.368562 -0.737123 4 -0.2 0.725568 0.725568 0.362784 -0.725568 4.1 -0.2 0.713909 0.713909 0.356954 -0.713909 4.2 -0.2 0.702156 0.702156 0.351078 -0.702156 4.3 -0.2 0.69032 0.69032 0.34516 -0.69032 4.4 -0.2 0.678412 0.678412 0.339206 -0.678412 4.5 -0.2 0.666443 0.666443 0.333222 -0.666443 4.6 -0.2 0.654424 0.654424 0.327212 -0.654424 4.7 -0.2 0.642364 0.642364 0.321182 -0.642364 4.8 -0.2 0.630274 0.630274 0.315137 -0.630274 4.9 -0.2 0.618165 0.618165 0.309082 -0.618165 -5 -0.1 0.606409 0.606409 0.303205 -0.606409 -4.9 -0.1 0.618536 0.618536 0.309268 -0.618536 -4.8 -0.1 0.630653 0.630653 0.315326 -0.630653 -4.7 -0.1 0.64275 0.64275 0.321375 -0.64275 -4.6 -0.1 0.654817 0.654817 0.327408 -0.654817 -4.5 -0.1 0.666843 0.666843 0.333422 -0.666843 -4.4 -0.1 0.67882 0.67882 0.33941 -0.67882 -4.3 -0.1 0.690734 0.690734 0.345367 -0.690734 -4.2 -0.1 0.702577 0.702577 0.351289 -0.702577 -4.1 -0.1 0.714337 0.714337 0.357169 -0.714337 -4 -0.1 0.726004 0.726004 0.363002 -0.726004 -3.9 -0.1 0.737566 0.737566 0.368783 -0.737566 -3.8 -0.1 0.749012 0.749012 0.374506 -0.749012 -3.7 -0.1 0.760332 0.760332 0.380166 -0.760332 -3.6 -0.1 0.771514 0.771514 0.385757 -0.771514 -3.5 -0.1 0.782548 0.782548 0.391274 -0.782548 -3.4 -0.1 0.793422 0.793422 0.396711 -0.793422 -3.3 -0.1 0.804125 0.804125 0.402063 -0.804125 -3.2 -0.1 0.814647 0.814647 0.407324 -0.814647 -3.1 -0.1 0.824977 0.824977 0.412488 -0.824977 -3 -0.1 0.835103 0.835103 0.417552 -0.835103 -2.9 -0.1 0.845016 0.845016 0.422508 -0.845016 -2.8 -0.1 0.854704 0.854704 0.427352 -0.854704 -2.7 -0.1 0.864158 0.864158 0.432079 -0.864158 -2.6 -0.1 0.873366 0.873366 0.436683 -0.873366 -2.5 -0.1 0.88232 0.88232 0.44116 -0.88232 -2.4 -0.1 0.89101 0.89101 0.445505 -0.89101 -2.3 -0.1 0.899425 0.899425 0.449712 -0.899425 -2.2 -0.1 0.907556 0.907556 0.453778 -0.907556 -2.1 -0.1 0.915395 0.915395 0.457697 -0.915395 -2 -0.1 0.922932 0.922932 0.461466 -0.922932 -1.9 -0.1 0.930159 0.930159 0.465079 -0.930159 -1.8 -0.1 0.937067 0.937067 0.468534 -0.937067 -1.7 -0.1 0.94365 0.94365 0.471825 -0.94365 -1.6 -0.1 0.949899 0.949899 0.474949 -0.949899 -1.5 -0.1 0.955806 0.955806 0.477903 -0.955806 -1.4 -0.1 0.961366 0.961366 0.480683 -0.961366 -1.3 -0.1 0.966572 0.966572 0.483286 -0.966572 -1.2 -0.1 0.971416 0.971416 0.485708 -0.971416 -1.1 -0.1 0.975895 0.975895 0.487948 -0.975895 -1 -0.1 0.980003 0.980003 0.490001 -0.980003 -0.9 -0.1 0.983734 0.983734 0.491867 -0.983734 -0.8 -0.1 0.987084 0.987084 0.493542 -0.987084 -0.7 -0.1 0.99005 0.99005 0.495025 -0.99005 -0.6 -0.1 0.992627 0.992627 0.496314 -0.992627 -0.5 -0.1 0.994813 0.994813 0.497407 -0.994813 -0.4 -0.1 0.996606 0.996606 0.498303 -0.996606 -0.3 -0.1 0.998002 0.998002 0.499001 -0.998002 -0.2 -0.1 0.999 0.999 0.4995 -0.999 -0.1 -0.1 0.9996 0.9996 0.4998 -0.9996 0 -0.1 0.9998 0.9998 0.4999 -0.9998 0.1 -0.1 0.9996 0.9996 0.4998 -0.9996 0.2 -0.1 0.999 0.999 0.4995 -0.999 0.3 -0.1 0.998002 0.998002 0.499001 -0.998002 0.4 -0.1 0.996606 0.996606 0.498303 -0.996606 0.5 -0.1 0.994813 0.994813 0.497407 -0.994813 0.6 -0.1 0.992627 0.992627 0.496314 -0.992627 0.7 -0.1 0.99005 0.99005 0.495025 -0.99005 0.8 -0.1 0.987084 0.987084 0.493542 -0.987084 0.9 -0.1 0.983734 0.983734 0.491867 -0.983734 1 -0.1 0.980003 0.980003 0.490001 -0.980003 1.1 -0.1 0.975895 0.975895 0.487948 -0.975895 1.2 -0.1 0.971416 0.971416 0.485708 -0.971416 1.3 -0.1 0.966572 0.966572 0.483286 -0.966572 1.4 -0.1 0.961366 0.961366 0.480683 -0.961366 1.5 -0.1 0.955806 0.955806 0.477903 -0.955806 1.6 -0.1 0.949899 0.949899 0.474949 -0.949899 1.7 -0.1 0.94365 0.94365 0.471825 -0.94365 1.8 -0.1 0.937067 0.937067 0.468534 -0.937067 1.9 -0.1 0.930159 0.930159 0.465079 -0.930159 2 -0.1 0.922932 0.922932 0.461466 -0.922932 2.1 -0.1 0.915395 0.915395 0.457697 -0.915395 2.2 -0.1 0.907556 0.907556 0.453778 -0.907556 2.3 -0.1 0.899425 0.899425 0.449712 -0.899425 2.4 -0.1 0.89101 0.89101 0.445505 -0.89101 2.5 -0.1 0.88232 0.88232 0.44116 -0.88232 2.6 -0.1 0.873366 0.873366 0.436683 -0.873366 2.7 -0.1 0.864158 0.864158 0.432079 -0.864158 2.8 -0.1 0.854704 0.854704 0.427352 -0.854704 2.9 -0.1 0.845016 0.845016 0.422508 -0.845016 3 -0.1 0.835103 0.835103 0.417552 -0.835103 3.1 -0.1 0.824977 0.824977 0.412488 -0.824977 3.2 -0.1 0.814647 0.814647 0.407324 -0.814647 3.3 -0.1 0.804125 0.804125 0.402063 -0.804125 3.4 -0.1 0.793422 0.793422 0.396711 -0.793422 3.5 -0.1 0.782548 0.782548 0.391274 -0.782548 3.6 -0.1 0.771514 0.771514 0.385757 -0.771514 3.7 -0.1 0.760332 0.760332 0.380166 -0.760332 3.8 -0.1 0.749012 0.749012 0.374506 -0.749012 3.9 -0.1 0.737566 0.737566 0.368783 -0.737566 4 -0.1 0.726004 0.726004 0.363002 -0.726004 4.1 -0.1 0.714337 0.714337 0.357169 -0.714337 4.2 -0.1 0.702577 0.702577 0.351289 -0.702577 4.3 -0.1 0.690734 0.690734 0.345367 -0.690734 4.4 -0.1 0.67882 0.67882 0.33941 -0.67882 4.5 -0.1 0.666843 0.666843 0.333422 -0.666843 4.6 -0.1 0.654817 0.654817 0.327408 -0.654817 4.7 -0.1 0.64275 0.64275 0.321375 -0.64275 4.8 -0.1 0.630653 0.630653 0.315326 -0.630653 4.9 -0.1 0.618536 0.618536 0.309268 -0.618536 -5 0 0.606531 0.606531 0.303265 -0.606531 -4.9 0 0.61866 0.61866 0.30933 -0.61866 -4.8 0 0.630779 0.630779 0.315389 -0.630779 -4.7 0 0.642878 0.642878 0.321439 -0.642878 -4.6 0 0.654948 0.654948 0.327474 -0.654948 -4.5 0 0.666977 0.666977 0.333488 -0.666977 -4.4 0 0.678955 0.678955 0.339478 -0.678955 -4.3 0 0.690872 0.690872 0.345436 -0.690872 -4.2 0 0.702718 0.702718 0.351359 -0.702718 -4.1 0 0.71448 0.71448 0.35724 -0.71448 -4 0 0.726149 0.726149 0.363075 -0.726149 -3.9 0 0.737713 0.737713 0.368857 -0.737713 -3.8 0 0.749162 0.749162 0.374581 -0.749162 -3.7 0 0.760484 0.760484 0.380242 -0.760484 -3.6 0 0.771669 0.771669 0.385834 -0.771669 -3.5 0 0.782705 0.782705 0.391352 -0.782705 -3.4 0 0.793581 0.793581 0.39679 -0.793581 -3.3 0 0.804286 0.804286 0.402143 -0.804286 -3.2 0 0.81481 0.81481 0.407405 -0.81481 -3.1 0 0.825142 0.825142 0.412571 -0.825142 -3 0 0.83527 0.83527 0.417635 -0.83527 -2.9 0 0.845185 0.845185 0.422592 -0.845185 -2.8 0 0.854875 0.854875 0.427438 -0.854875 -2.7 0 0.864331 0.864331 0.432165 -0.864331 -2.6 0 0.873541 0.873541 0.436771 -0.873541 -2.5 0 0.882497 0.882497 0.441248 -0.882497 -2.4 0 0.891188 0.891188 0.445594 -0.891188 -2.3 0 0.899605 0.899605 0.449802 -0.899605 -2.2 0 0.907738 0.907738 0.453869 -0.907738 -2.1 0 0.915578 0.915578 0.457789 -0.915578 -2 0 0.923116 0.923116 0.461558 -0.923116 -1.9 0 0.930345 0.930345 0.465172 -0.930345 -1.8 0 0.937255 0.937255 0.468627 -0.937255 -1.7 0 0.943839 0.943839 0.471919 -0.943839 -1.6 0 0.950089 0.950089 0.475044 -0.950089 -1.5 0 0.955997 0.955997 0.477999 -0.955997 -1.4 0 0.961558 0.961558 0.480779 -0.961558 -1.3 0 0.966765 0.966765 0.483382 -0.966765 -1.2 0 0.971611 0.971611 0.485805 -0.971611 -1.1 0 0.97609 0.97609 0.488045 -0.97609 -1 0 0.980199 0.980199 0.490099 -0.980199 -0.9 0 0.983931 0.983931 0.491965 -0.983931 -0.8 0 0.987282 0.987282 0.493641 -0.987282 -0.7 0 0.990248 0.990248 0.495124 -0.990248 -0.6 0 0.992826 0.992826 0.496413 -0.992826 -0.5 0 0.995012 0.995012 0.497506 -0.995012 -0.4 0 0.996805 0.996805 0.498403 -0.996805 -0.3 0 0.998202 0.998202 0.499101 -0.998202 -0.2 0 0.9992 0.9992 0.4996 -0.9992 -0.1 0 0.9998 0.9998 0.4999 -0.9998 0 0 1 1 0.5 -1 0.1 0 0.9998 0.9998 0.4999 -0.9998 0.2 0 0.9992 0.9992 0.4996 -0.9992 0.3 0 0.998202 0.998202 0.499101 -0.998202 0.4 0 0.996805 0.996805 0.498403 -0.996805 0.5 0 0.995012 0.995012 0.497506 -0.995012 0.6 0 0.992826 0.992826 0.496413 -0.992826 0.7 0 0.990248 0.990248 0.495124 -0.990248 0.8 0 0.987282 0.987282 0.493641 -0.987282 0.9 0 0.983931 0.983931 0.491965 -0.983931 1 0 0.980199 0.980199 0.490099 -0.980199 1.1 0 0.97609 0.97609 0.488045 -0.97609 1.2 0 0.971611 0.971611 0.485805 -0.971611 1.3 0 0.966765 0.966765 0.483382 -0.966765 1.4 0 0.961558 0.961558 0.480779 -0.961558 1.5 0 0.955997 0.955997 0.477999 -0.955997 1.6 0 0.950089 0.950089 0.475044 -0.950089 1.7 0 0.943839 0.943839 0.471919 -0.943839 1.8 0 0.937255 0.937255 0.468627 -0.937255 1.9 0 0.930345 0.930345 0.465172 -0.930345 2 0 0.923116 0.923116 0.461558 -0.923116 2.1 0 0.915578 0.915578 0.457789 -0.915578 2.2 0 0.907738 0.907738 0.453869 -0.907738 2.3 0 0.899605 0.899605 0.449802 -0.899605 2.4 0 0.891188 0.891188 0.445594 -0.891188 2.5 0 0.882497 0.882497 0.441248 -0.882497 2.6 0 0.873541 0.873541 0.436771 -0.873541 2.7 0 0.864331 0.864331 0.432165 -0.864331 2.8 0 0.854875 0.854875 0.427438 -0.854875 2.9 0 0.845185 0.845185 0.422592 -0.845185 3 0 0.83527 0.83527 0.417635 -0.83527 3.1 0 0.825142 0.825142 0.412571 -0.825142 3.2 0 0.81481 0.81481 0.407405 -0.81481 3.3 0 0.804286 0.804286 0.402143 -0.804286 3.4 0 0.793581 0.793581 0.39679 -0.793581 3.5 0 0.782705 0.782705 0.391352 -0.782705 3.6 0 0.771669 0.771669 0.385834 -0.771669 3.7 0 0.760484 0.760484 0.380242 -0.760484 3.8 0 0.749162 0.749162 0.374581 -0.749162 3.9 0 0.737713 0.737713 0.368857 -0.737713 4 0 0.726149 0.726149 0.363075 -0.726149 4.1 0 0.71448 0.71448 0.35724 -0.71448 4.2 0 0.702718 0.702718 0.351359 -0.702718 4.3 0 0.690872 0.690872 0.345436 -0.690872 4.4 0 0.678955 0.678955 0.339478 -0.678955 4.5 0 0.666977 0.666977 0.333488 -0.666977 4.6 0 0.654948 0.654948 0.327474 -0.654948 4.7 0 0.642878 0.642878 0.321439 -0.642878 4.8 0 0.630779 0.630779 0.315389 -0.630779 4.9 0 0.61866 0.61866 0.30933 -0.61866 -5 0.1 0.606409 0.606409 0.303205 -0.606409 -4.9 0.1 0.618536 0.618536 0.309268 -0.618536 -4.8 0.1 0.630653 0.630653 0.315326 -0.630653 -4.7 0.1 0.64275 0.64275 0.321375 -0.64275 -4.6 0.1 0.654817 0.654817 0.327408 -0.654817 -4.5 0.1 0.666843 0.666843 0.333422 -0.666843 -4.4 0.1 0.67882 0.67882 0.33941 -0.67882 -4.3 0.1 0.690734 0.690734 0.345367 -0.690734 -4.2 0.1 0.702577 0.702577 0.351289 -0.702577 -4.1 0.1 0.714337 0.714337 0.357169 -0.714337 -4 0.1 0.726004 0.726004 0.363002 -0.726004 -3.9 0.1 0.737566 0.737566 0.368783 -0.737566 -3.8 0.1 0.749012 0.749012 0.374506 -0.749012 -3.7 0.1 0.760332 0.760332 0.380166 -0.760332 -3.6 0.1 0.771514 0.771514 0.385757 -0.771514 -3.5 0.1 0.782548 0.782548 0.391274 -0.782548 -3.4 0.1 0.793422 0.793422 0.396711 -0.793422 -3.3 0.1 0.804125 0.804125 0.402063 -0.804125 -3.2 0.1 0.814647 0.814647 0.407324 -0.814647 -3.1 0.1 0.824977 0.824977 0.412488 -0.824977 -3 0.1 0.835103 0.835103 0.417552 -0.835103 -2.9 0.1 0.845016 0.845016 0.422508 -0.845016 -2.8 0.1 0.854704 0.854704 0.427352 -0.854704 -2.7 0.1 0.864158 0.864158 0.432079 -0.864158 -2.6 0.1 0.873366 0.873366 0.436683 -0.873366 -2.5 0.1 0.88232 0.88232 0.44116 -0.88232 -2.4 0.1 0.89101 0.89101 0.445505 -0.89101 -2.3 0.1 0.899425 0.899425 0.449712 -0.899425 -2.2 0.1 0.907556 0.907556 0.453778 -0.907556 -2.1 0.1 0.915395 0.915395 0.457697 -0.915395 -2 0.1 0.922932 0.922932 0.461466 -0.922932 -1.9 0.1 0.930159 0.930159 0.465079 -0.930159 -1.8 0.1 0.937067 0.937067 0.468534 -0.937067 -1.7 0.1 0.94365 0.94365 0.471825 -0.94365 -1.6 0.1 0.949899 0.949899 0.474949 -0.949899 -1.5 0.1 0.955806 0.955806 0.477903 -0.955806 -1.4 0.1 0.961366 0.961366 0.480683 -0.961366 -1.3 0.1 0.966572 0.966572 0.483286 -0.966572 -1.2 0.1 0.971416 0.971416 0.485708 -0.971416 -1.1 0.1 0.975895 0.975895 0.487948 -0.975895 -1 0.1 0.980003 0.980003 0.490001 -0.980003 -0.9 0.1 0.983734 0.983734 0.491867 -0.983734 -0.8 0.1 0.987084 0.987084 0.493542 -0.987084 -0.7 0.1 0.99005 0.99005 0.495025 -0.99005 -0.6 0.1 0.992627 0.992627 0.496314 -0.992627 -0.5 0.1 0.994813 0.994813 0.497407 -0.994813 -0.4 0.1 0.996606 0.996606 0.498303 -0.996606 -0.3 0.1 0.998002 0.998002 0.499001 -0.998002 -0.2 0.1 0.999 0.999 0.4995 -0.999 -0.1 0.1 0.9996 0.9996 0.4998 -0.9996 0 0.1 0.9998 0.9998 0.4999 -0.9998 0.1 0.1 0.9996 0.9996 0.4998 -0.9996 0.2 0.1 0.999 0.999 0.4995 -0.999 0.3 0.1 0.998002 0.998002 0.499001 -0.998002 0.4 0.1 0.996606 0.996606 0.498303 -0.996606 0.5 0.1 0.994813 0.994813 0.497407 -0.994813 0.6 0.1 0.992627 0.992627 0.496314 -0.992627 0.7 0.1 0.99005 0.99005 0.495025 -0.99005 0.8 0.1 0.987084 0.987084 0.493542 -0.987084 0.9 0.1 0.983734 0.983734 0.491867 -0.983734 1 0.1 0.980003 0.980003 0.490001 -0.980003 1.1 0.1 0.975895 0.975895 0.487948 -0.975895 1.2 0.1 0.971416 0.971416 0.485708 -0.971416 1.3 0.1 0.966572 0.966572 0.483286 -0.966572 1.4 0.1 0.961366 0.961366 0.480683 -0.961366 1.5 0.1 0.955806 0.955806 0.477903 -0.955806 1.6 0.1 0.949899 0.949899 0.474949 -0.949899 1.7 0.1 0.94365 0.94365 0.471825 -0.94365 1.8 0.1 0.937067 0.937067 0.468534 -0.937067 1.9 0.1 0.930159 0.930159 0.465079 -0.930159 2 0.1 0.922932 0.922932 0.461466 -0.922932 2.1 0.1 0.915395 0.915395 0.457697 -0.915395 2.2 0.1 0.907556 0.907556 0.453778 -0.907556 2.3 0.1 0.899425 0.899425 0.449712 -0.899425 2.4 0.1 0.89101 0.89101 0.445505 -0.89101 2.5 0.1 0.88232 0.88232 0.44116 -0.88232 2.6 0.1 0.873366 0.873366 0.436683 -0.873366 2.7 0.1 0.864158 0.864158 0.432079 -0.864158 2.8 0.1 0.854704 0.854704 0.427352 -0.854704 2.9 0.1 0.845016 0.845016 0.422508 -0.845016 3 0.1 0.835103 0.835103 0.417552 -0.835103 3.1 0.1 0.824977 0.824977 0.412488 -0.824977 3.2 0.1 0.814647 0.814647 0.407324 -0.814647 3.3 0.1 0.804125 0.804125 0.402063 -0.804125 3.4 0.1 0.793422 0.793422 0.396711 -0.793422 3.5 0.1 0.782548 0.782548 0.391274 -0.782548 3.6 0.1 0.771514 0.771514 0.385757 -0.771514 3.7 0.1 0.760332 0.760332 0.380166 -0.760332 3.8 0.1 0.749012 0.749012 0.374506 -0.749012 3.9 0.1 0.737566 0.737566 0.368783 -0.737566 4 0.1 0.726004 0.726004 0.363002 -0.726004 4.1 0.1 0.714337 0.714337 0.357169 -0.714337 4.2 0.1 0.702577 0.702577 0.351289 -0.702577 4.3 0.1 0.690734 0.690734 0.345367 -0.690734 4.4 0.1 0.67882 0.67882 0.33941 -0.67882 4.5 0.1 0.666843 0.666843 0.333422 -0.666843 4.6 0.1 0.654817 0.654817 0.327408 -0.654817 4.7 0.1 0.64275 0.64275 0.321375 -0.64275 4.8 0.1 0.630653 0.630653 0.315326 -0.630653 4.9 0.1 0.618536 0.618536 0.309268 -0.618536 -5 0.2 0.606046 0.606046 0.303023 -0.606046 -4.9 0.2 0.618165 0.618165 0.309082 -0.618165 -4.8 0.2 0.630274 0.630274 0.315137 -0.630274 -4.7 0.2 0.642364 0.642364 0.321182 -0.642364 -4.6 0.2 0.654424 0.654424 0.327212 -0.654424 -4.5 0.2 0.666443 0.666443 0.333222 -0.666443 -4.4 0.2 0.678412 0.678412 0.339206 -0.678412 -4.3 0.2 0.69032 0.69032 0.34516 -0.69032 -4.2 0.2 0.702156 0.702156 0.351078 -0.702156 -4.1 0.2 0.713909 0.713909 0.356954 -0.713909 -4 0.2 0.725568 0.725568 0.362784 -0.725568 -3.9 0.2 0.737123 0.737123 0.368562 -0.737123 -3.8 0.2 0.748563 0.748563 0.374281 -0.748563 -3.7 0.2 0.759876 0.759876 0.379938 -0.759876 -3.6 0.2 0.771052 0.771052 0.385526 -0.771052 -3.5 0.2 0.782079 0.782079 0.391039 -0.782079 -3.4 0.2 0.792946 0.792946 0.396473 -0.792946 -3.3 0.2 0.803643 0.803643 0.401822 -0.803643 -3.2 0.2 0.814159 0.814159 0.407079 -0.814159 -3.1 0.2 0.824482 0.824482 0.412241 -0.824482 -3 0.2 0.834602 0.834602 0.417301 -0.834602 -2.9 0.2 0.844509 0.844509 0.422254 -0.844509 -2.8 0.2 0.854191 0.854191 0.427096 -0.854191 -2.7 0.2 0.863639 0.863639 0.43182 -0.863639 -2.6 0.2 0.872843 0.872843 0.436421 -0.872843 -2.5 0.2 0.881791 0.881791 0.440896 -0.881791 -2.4 0.2 0.890475 0.890475 0.445238 -0.890475 -2.3 0.2 0.898885 0.898885 0.449443 -0.898885 -2.2 0.2 0.907012 0.907012 0.453506 -0.907012 -2.1 0.2 0.914846 0.914846 0.457423 -0.914846 -2 0.2 0.922378 0.922378 0.461189 -0.922378 -1.9 0.2 0.929601 0.929601 0.4648 -0.929601 -1.8 0.2 0.936505 0.936505 0.468253 -0.936505 -1.7 0.2 0.943084 0.943084 0.471542 -0.943084 -1.6 0.2 0.949329 0.949329 0.474664 -0.949329 -1.5 0.2 0.955233 0.955233 0.477616 -0.955233 -1.4 0.2 0.960789 0.960789 0.480395 -0.960789 -1.3 0.2 0.965992 0.965992 0.482996 -0.965992 -1.2 0.2 0.970834 0.970834 0.485417 -0.970834 -1.1 0.2 0.97531 0.97531 0.487655 -0.97531 -1 0.2 0.979415 0.979415 0.489707 -0.979415 -0.9 0.2 0.983144 0.983144 0.491572 -0.983144 -0.8 0.2 0.986492 0.986492 0.493246 -0.986492 -0.7 0.2 0.989456 0.989456 0.494728 -0.989456 -0.6 0.2 0.992032 0.992032 0.496016 -0.992032 -0.5 0.2 0.994217 0.994217 0.497108 -0.994217 -0.4 0.2 0.996008 0.996008 0.498004 -0.996008 -0.3 0.2 0.997403 0.997403 0.498702 -0.997403 -0.2 0.2 0.998401 0.998401 0.499201 -0.998401 -0.1 0.2 0.999 0.999 0.4995 -0.999 0 0.2 0.9992 0.9992 0.4996 -0.9992 0.1 0.2 0.999 0.999 0.4995 -0.999 0.2 0.2 0.998401 0.998401 0.499201 -0.998401 0.3 0.2 0.997403 0.997403 0.498702 -0.997403 0.4 0.2 0.996008 0.996008 0.498004 -0.996008 0.5 0.2 0.994217 0.994217 0.497108 -0.994217 0.6 0.2 0.992032 0.992032 0.496016 -0.992032 0.7 0.2 0.989456 0.989456 0.494728 -0.989456 0.8 0.2 0.986492 0.986492 0.493246 -0.986492 0.9 0.2 0.983144 0.983144 0.491572 -0.983144 1 0.2 0.979415 0.979415 0.489707 -0.979415 1.1 0.2 0.97531 0.97531 0.487655 -0.97531 1.2 0.2 0.970834 0.970834 0.485417 -0.970834 1.3 0.2 0.965992 0.965992 0.482996 -0.965992 1.4 0.2 0.960789 0.960789 0.480395 -0.960789 1.5 0.2 0.955233 0.955233 0.477616 -0.955233 1.6 0.2 0.949329 0.949329 0.474664 -0.949329 1.7 0.2 0.943084 0.943084 0.471542 -0.943084 1.8 0.2 0.936505 0.936505 0.468253 -0.936505 1.9 0.2 0.929601 0.929601 0.4648 -0.929601 2 0.2 0.922378 0.922378 0.461189 -0.922378 2.1 0.2 0.914846 0.914846 0.457423 -0.914846 2.2 0.2 0.907012 0.907012 0.453506 -0.907012 2.3 0.2 0.898885 0.898885 0.449443 -0.898885 2.4 0.2 0.890475 0.890475 0.445238 -0.890475 2.5 0.2 0.881791 0.881791 0.440896 -0.881791 2.6 0.2 0.872843 0.872843 0.436421 -0.872843 2.7 0.2 0.863639 0.863639 0.43182 -0.863639 2.8 0.2 0.854191 0.854191 0.427096 -0.854191 2.9 0.2 0.844509 0.844509 0.422254 -0.844509 3 0.2 0.834602 0.834602 0.417301 -0.834602 3.1 0.2 0.824482 0.824482 0.412241 -0.824482 3.2 0.2 0.814159 0.814159 0.407079 -0.814159 3.3 0.2 0.803643 0.803643 0.401822 -0.803643 3.4 0.2 0.792946 0.792946 0.396473 -0.792946 3.5 0.2 0.782079 0.782079 0.391039 -0.782079 3.6 0.2 0.771052 0.771052 0.385526 -0.771052 3.7 0.2 0.759876 0.759876 0.379938 -0.759876 3.8 0.2 0.748563 0.748563 0.374281 -0.748563 3.9 0.2 0.737123 0.737123 0.368562 -0.737123 4 0.2 0.725568 0.725568 0.362784 -0.725568 4.1 0.2 0.713909 0.713909 0.356954 -0.713909 4.2 0.2 0.702156 0.702156 0.351078 -0.702156 4.3 0.2 0.69032 0.69032 0.34516 -0.69032 4.4 0.2 0.678412 0.678412 0.339206 -0.678412 4.5 0.2 0.666443 0.666443 0.333222 -0.666443 4.6 0.2 0.654424 0.654424 0.327212 -0.654424 4.7 0.2 0.642364 0.642364 0.321182 -0.642364 4.8 0.2 0.630274 0.630274 0.315137 -0.630274 4.9 0.2 0.618165 0.618165 0.309082 -0.618165 -5 0.3 0.60544 0.60544 0.30272 -0.60544 -4.9 0.3 0.617547 0.617547 0.308774 -0.617547 -4.8 0.3 0.629644 0.629644 0.314822 -0.629644 -4.7 0.3 0.641722 0.641722 0.320861 -0.641722 -4.6 0.3 0.65377 0.65377 0.326885 -0.65377 -4.5 0.3 0.665777 0.665777 0.332889 -0.665777 -4.4 0.3 0.677734 0.677734 0.338867 -0.677734 -4.3 0.3 0.68963 0.68963 0.344815 -0.68963 -4.2 0.3 0.701454 0.701454 0.350727 -0.701454 -4.1 0.3 0.713195 0.713195 0.356598 -0.713195 -4 0.3 0.724843 0.724843 0.362422 -0.724843 -3.9 0.3 0.736387 0.736387 0.368193 -0.736387 -3.8 0.3 0.747815 0.747815 0.373907 -0.747815 -3.7 0.3 0.759117 0.759117 0.379558 -0.759117 -3.6 0.3 0.770281 0.770281 0.38514 -0.770281 -3.5 0.3 0.781297 0.781297 0.390648 -0.781297 -3.4 0.3 0.792154 0.792154 0.396077 -0.792154 -3.3 0.3 0.80284 0.80284 0.40142 -0.80284 -3.2 0.3 0.813345 0.813345 0.406672 -0.813345 -3.1 0.3 0.823658 0.823658 0.411829 -0.823658 -3 0.3 0.833768 0.833768 0.416884 -0.833768 -2.9 0.3 0.843665 0.843665 0.421832 -0.843665 -2.8 0.3 0.853338 0.853338 0.426669 -0.853338 -2.7 0.3 0.862776 0.862776 0.431388 -0.862776 -2.6 0.3 0.87197 0.87197 0.435985 -0.87197 -2.5 0.3 0.88091 0.88091 0.440455 -0.88091 -2.4 0.3 0.889585 0.889585 0.444793 -0.889585 -2.3 0.3 0.897987 0.897987 0.448993 -0.897987 -2.2 0.3 0.906105 0.906105 0.453053 -0.906105 -2.1 0.3 0.913931 0.913931 0.456966 -0.913931 -2 0.3 0.921456 0.921456 0.460728 -0.921456 -1.9 0.3 0.928672 0.928672 0.464336 -0.928672 -1.8 0.3 0.935569 0.935569 0.467785 -0.935569 -1.7 0.3 0.942141 0.942141 0.471071 -0.942141 -1.6 0.3 0.94838 0.94838 0.47419 -0.94838 -1.5 0.3 0.954278 0.954278 0.477139 -0.954278 -1.4 0.3 0.959829 0.959829 0.479915 -0.959829 -1.3 0.3 0.965026 0.965026 0.482513 -0.965026 -1.2 0.3 0.969863 0.969863 0.484932 -0.969863 -1.1 0.3 0.974335 0.974335 0.487168 -0.974335 -1 0.3 0.978436 0.978436 0.489218 -0.978436 -0.9 0.3 0.982161 0.982161 0.491081 -0.982161 -0.8 0.3 0.985506 0.985506 0.492753 -0.985506 -0.7 0.3 0.988467 0.988467 0.494234 -0.988467 -0.6 0.3 0.99104 0.99104 0.49552 -0.99104 -0.5 0.3 0.993223 0.993223 0.496612 -0.993223 -0.4 0.3 0.995012 0.995012 0.497506 -0.995012 -0.3 0.3 0.996406 0.996406 0.498203 -0.996406 -0.2 0.3 0.997403 0.997403 0.498702 -0.997403 -0.1 0.3 0.998002 0.998002 0.499001 -0.998002 0 0.3 0.998202 0.998202 0.499101 -0.998202 0.1 0.3 0.998002 0.998002 0.499001 -0.998002 0.2 0.3 0.997403 0.997403 0.498702 -0.997403 0.3 0.3 0.996406 0.996406 0.498203 -0.996406 0.4 0.3 0.995012 0.995012 0.497506 -0.995012 0.5 0.3 0.993223 0.993223 0.496612 -0.993223 0.6 0.3 0.99104 0.99104 0.49552 -0.99104 0.7 0.3 0.988467 0.988467 0.494234 -0.988467 0.8 0.3 0.985506 0.985506 0.492753 -0.985506 0.9 0.3 0.982161 0.982161 0.491081 -0.982161 1 0.3 0.978436 0.978436 0.489218 -0.978436 1.1 0.3 0.974335 0.974335 0.487168 -0.974335 1.2 0.3 0.969863 0.969863 0.484932 -0.969863 1.3 0.3 0.965026 0.965026 0.482513 -0.965026 1.4 0.3 0.959829 0.959829 0.479915 -0.959829 1.5 0.3 0.954278 0.954278 0.477139 -0.954278 1.6 0.3 0.94838 0.94838 0.47419 -0.94838 1.7 0.3 0.942141 0.942141 0.471071 -0.942141 1.8 0.3 0.935569 0.935569 0.467785 -0.935569 1.9 0.3 0.928672 0.928672 0.464336 -0.928672 2 0.3 0.921456 0.921456 0.460728 -0.921456 2.1 0.3 0.913931 0.913931 0.456966 -0.913931 2.2 0.3 0.906105 0.906105 0.453053 -0.906105 2.3 0.3 0.897987 0.897987 0.448993 -0.897987 2.4 0.3 0.889585 0.889585 0.444793 -0.889585 2.5 0.3 0.88091 0.88091 0.440455 -0.88091 2.6 0.3 0.87197 0.87197 0.435985 -0.87197 2.7 0.3 0.862776 0.862776 0.431388 -0.862776 2.8 0.3 0.853338 0.853338 0.426669 -0.853338 2.9 0.3 0.843665 0.843665 0.421832 -0.843665 3 0.3 0.833768 0.833768 0.416884 -0.833768 3.1 0.3 0.823658 0.823658 0.411829 -0.823658 3.2 0.3 0.813345 0.813345 0.406672 -0.813345 3.3 0.3 0.80284 0.80284 0.40142 -0.80284 3.4 0.3 0.792154 0.792154 0.396077 -0.792154 3.5 0.3 0.781297 0.781297 0.390648 -0.781297 3.6 0.3 0.770281 0.770281 0.38514 -0.770281 3.7 0.3 0.759117 0.759117 0.379558 -0.759117 3.8 0.3 0.747815 0.747815 0.373907 -0.747815 3.9 0.3 0.736387 0.736387 0.368193 -0.736387 4 0.3 0.724843 0.724843 0.362422 -0.724843 4.1 0.3 0.713195 0.713195 0.356598 -0.713195 4.2 0.3 0.701454 0.701454 0.350727 -0.701454 4.3 0.3 0.68963 0.68963 0.344815 -0.68963 4.4 0.3 0.677734 0.677734 0.338867 -0.677734 4.5 0.3 0.665777 0.665777 0.332889 -0.665777 4.6 0.3 0.65377 0.65377 0.326885 -0.65377 4.7 0.3 0.641722 0.641722 0.320861 -0.641722 4.8 0.3 0.629644 0.629644 0.314822 -0.629644 4.9 0.3 0.617547 0.617547 0.308774 -0.617547 -5 0.4 0.604593 0.604593 0.302296 -0.604593 -4.9 0.4 0.616683 0.616683 0.308342 -0.616683 -4.8 0.4 0.628764 0.628764 0.314382 -0.628764 -4.7 0.4 0.640824 0.640824 0.320412 -0.640824 -4.6 0.4 0.652855 0.652855 0.326428 -0.652855 -4.5 0.4 0.664846 0.664846 0.332423 -0.664846 -4.4 0.4 0.676786 0.676786 0.338393 -0.676786 -4.3 0.4 0.688665 0.688665 0.344333 -0.688665 -4.2 0.4 0.700473 0.700473 0.350236 -0.700473 -4.1 0.4 0.712198 0.712198 0.356099 -0.712198 -4 0.4 0.723829 0.723829 0.361915 -0.723829 -3.9 0.4 0.735356 0.735356 0.367678 -0.735356 -3.8 0.4 0.746769 0.746769 0.373384 -0.746769 -3.7 0.4 0.758054 0.758054 0.379027 -0.758054 -3.6 0.4 0.769203 0.769203 0.384602 -0.769203 -3.5 0.4 0.780204 0.780204 0.390102 -0.780204 -3.4 0.4 0.791045 0.791045 0.395523 -0.791045 -3.3 0.4 0.801717 0.801717 0.400858 -0.801717 -3.2 0.4 0.812207 0.812207 0.406104 -0.812207 -3.1 0.4 0.822506 0.822506 0.411253 -0.822506 -3 0.4 0.832602 0.832602 0.416301 -0.832602 -2.9 0.4 0.842485 0.842485 0.421242 -0.842485 -2.8 0.4 0.852144 0.852144 0.426072 -0.852144 -2.7 0.4 0.861569 0.861569 0.430785 -0.861569 -2.6 0.4 0.87075 0.87075 0.435375 -0.87075 -2.5 0.4 0.879677 0.879677 0.439839 -0.879677 -2.4 0.4 0.888341 0.888341 0.44417 -0.888341 -2.3 0.4 0.89673 0.89673 0.448365 -0.89673 -2.2 0.4 0.904837 0.904837 0.452419 -0.904837 -2.1 0.4 0.912653 0.912653 0.456326 -0.912653 -2 0.4 0.920167 0.920167 0.460084 -0.920167 -1.9 0.4 0.927372 0.927372 0.463686 -0.927372 -1.8 0.4 0.93426 0.93426 0.46713 -0.93426 -1.7 0.4 0.940823 0.940823 0.470412 -0.940823 -1.6 0.4 0.947053 0.947053 0.473527 -0.947053 -1.5 0.4 0.952943 0.952943 0.476472 -0.952943 -1.4 0.4 0.958486 0.958486 0.479243 -0.958486 -1.3 0.4 0.963676 0.963676 0.481838 -0.963676 -1.2 0.4 0.968507 0.968507 0.484253 -0.968507 -1.1 0.4 0.972972 0.972972 0.486486 -0.972972 -1 0.4 0.977067 0.977067 0.488534 -0.977067 -0.9 0.4 0.980787 0.980787 0.490393 -0.980787 -0.8 0.4 0.984127 0.984127 0.492064 -0.984127 -0.7 0.4 0.987084 0.987084 0.493542 -0.987084 -0.6 0.4 0.989654 0.989654 0.494827 -0.989654 -0.5 0.4 0.991834 0.991834 0.495917 -0.991834 -0.4 0.4 0.99362 0.99362 0.49681 -0.99362 -0.3 0.4 0.995012 0.995012 0.497506 -0.995012 -0.2 0.4 0.996008 0.996008 0.498004 -0.996008 -0.1 0.4 0.996606 0.996606 0.498303 -0.996606 0 0.4 0.996805 0.996805 0.498403 -0.996805 0.1 0.4 0.996606 0.996606 0.498303 -0.996606 0.2 0.4 0.996008 0.996008 0.498004 -0.996008 0.3 0.4 0.995012 0.995012 0.497506 -0.995012 0.4 0.4 0.99362 0.99362 0.49681 -0.99362 0.5 0.4 0.991834 0.991834 0.495917 -0.991834 0.6 0.4 0.989654 0.989654 0.494827 -0.989654 0.7 0.4 0.987084 0.987084 0.493542 -0.987084 0.8 0.4 0.984127 0.984127 0.492064 -0.984127 0.9 0.4 0.980787 0.980787 0.490393 -0.980787 1 0.4 0.977067 0.977067 0.488534 -0.977067 1.1 0.4 0.972972 0.972972 0.486486 -0.972972 1.2 0.4 0.968507 0.968507 0.484253 -0.968507 1.3 0.4 0.963676 0.963676 0.481838 -0.963676 1.4 0.4 0.958486 0.958486 0.479243 -0.958486 1.5 0.4 0.952943 0.952943 0.476472 -0.952943 1.6 0.4 0.947053 0.947053 0.473527 -0.947053 1.7 0.4 0.940823 0.940823 0.470412 -0.940823 1.8 0.4 0.93426 0.93426 0.46713 -0.93426 1.9 0.4 0.927372 0.927372 0.463686 -0.927372 2 0.4 0.920167 0.920167 0.460084 -0.920167 2.1 0.4 0.912653 0.912653 0.456326 -0.912653 2.2 0.4 0.904837 0.904837 0.452419 -0.904837 2.3 0.4 0.89673 0.89673 0.448365 -0.89673 2.4 0.4 0.888341 0.888341 0.44417 -0.888341 2.5 0.4 0.879677 0.879677 0.439839 -0.879677 2.6 0.4 0.87075 0.87075 0.435375 -0.87075 2.7 0.4 0.861569 0.861569 0.430785 -0.861569 2.8 0.4 0.852144 0.852144 0.426072 -0.852144 2.9 0.4 0.842485 0.842485 0.421242 -0.842485 3 0.4 0.832602 0.832602 0.416301 -0.832602 3.1 0.4 0.822506 0.822506 0.411253 -0.822506 3.2 0.4 0.812207 0.812207 0.406104 -0.812207 3.3 0.4 0.801717 0.801717 0.400858 -0.801717 3.4 0.4 0.791045 0.791045 0.395523 -0.791045 3.5 0.4 0.780204 0.780204 0.390102 -0.780204 3.6 0.4 0.769203 0.769203 0.384602 -0.769203 3.7 0.4 0.758054 0.758054 0.379027 -0.758054 3.8 0.4 0.746769 0.746769 0.373384 -0.746769 3.9 0.4 0.735356 0.735356 0.367678 -0.735356 4 0.4 0.723829 0.723829 0.361915 -0.723829 4.1 0.4 0.712198 0.712198 0.356099 -0.712198 4.2 0.4 0.700473 0.700473 0.350236 -0.700473 4.3 0.4 0.688665 0.688665 0.344333 -0.688665 4.4 0.4 0.676786 0.676786 0.338393 -0.676786 4.5 0.4 0.664846 0.664846 0.332423 -0.664846 4.6 0.4 0.652855 0.652855 0.326428 -0.652855 4.7 0.4 0.640824 0.640824 0.320412 -0.640824 4.8 0.4 0.628764 0.628764 0.314382 -0.628764 4.9 0.4 0.616683 0.616683 0.308342 -0.616683 -5 0.5 0.603506 0.603506 0.301753 -0.603506 -4.9 0.5 0.615574 0.615574 0.307787 -0.615574 -4.8 0.5 0.627633 0.627633 0.313816 -0.627633 -4.7 0.5 0.639672 0.639672 0.319836 -0.639672 -4.6 0.5 0.651681 0.651681 0.325841 -0.651681 -4.5 0.5 0.66365 0.66365 0.331825 -0.66365 -4.4 0.5 0.675569 0.675569 0.337784 -0.675569 -4.3 0.5 0.687427 0.687427 0.343713 -0.687427 -4.2 0.5 0.699213 0.699213 0.349606 -0.699213 -4.1 0.5 0.710917 0.710917 0.355458 -0.710917 -4 0.5 0.722527 0.722527 0.361264 -0.722527 -3.9 0.5 0.734034 0.734034 0.367017 -0.734034 -3.8 0.5 0.745426 0.745426 0.372713 -0.745426 -3.7 0.5 0.756691 0.756691 0.378346 -0.756691 -3.6 0.5 0.76782 0.76782 0.38391 -0.76782 -3.5 0.5 0.778801 0.778801 0.3894 -0.778801 -3.4 0.5 0.789623 0.789623 0.394811 -0.789623 -3.3 0.5 0.800275 0.800275 0.400137 -0.800275 -3.2 0.5 0.810746 0.810746 0.405373 -0.810746 -3.1 0.5 0.821026 0.821026 0.410513 -0.821026 -3 0.5 0.831104 0.831104 0.415552 -0.831104 -2.9 0.5 0.840969 0.840969 0.420485 -0.840969 -2.8 0.5 0.850611 0.850611 0.425306 -0.850611 -2.7 0.5 0.86002 0.86002 0.43001 -0.86002 -2.6 0.5 0.869184 0.869184 0.434592 -0.869184 -2.5 0.5 0.878095 0.878095 0.439048 -0.878095 -2.4 0.5 0.886743 0.886743 0.443372 -0.886743 -2.3 0.5 0.895118 0.895118 0.447559 -0.895118 -2.2 0.5 0.90321 0.90321 0.451605 -0.90321 -2.1 0.5 0.911011 0.911011 0.455506 -0.911011 -2 0.5 0.918512 0.918512 0.459256 -0.918512 -1.9 0.5 0.925705 0.925705 0.462852 -0.925705 -1.8 0.5 0.93258 0.93258 0.46629 -0.93258 -1.7 0.5 0.939131 0.939131 0.469566 -0.939131 -1.6 0.5 0.94535 0.94535 0.472675 -0.94535 -1.5 0.5 0.951229 0.951229 0.475615 -0.951229 -1.4 0.5 0.956763 0.956763 0.478381 -0.956763 -1.3 0.5 0.961943 0.961943 0.480972 -0.961943 -1.2 0.5 0.966765 0.966765 0.483382 -0.966765 -1.1 0.5 0.971222 0.971222 0.485611 -0.971222 -1 0.5 0.97531 0.97531 0.487655 -0.97531 -0.9 0.5 0.979023 0.979023 0.489512 -0.979023 -0.8 0.5 0.982357 0.982357 0.491179 -0.982357 -0.7 0.5 0.985309 0.985309 0.492654 -0.985309 -0.6 0.5 0.987874 0.987874 0.493937 -0.987874 -0.5 0.5 0.99005 0.99005 0.495025 -0.99005 -0.4 0.5 0.991834 0.991834 0.495917 -0.991834 -0.3 0.5 0.993223 0.993223 0.496612 -0.993223 -0.2 0.5 0.994217 0.994217 0.497108 -0.994217 -0.1 0.5 0.994813 0.994813 0.497407 -0.994813 0 0.5 0.995012 0.995012 0.497506 -0.995012 0.1 0.5 0.994813 0.994813 0.497407 -0.994813 0.2 0.5 0.994217 0.994217 0.497108 -0.994217 0.3 0.5 0.993223 0.993223 0.496612 -0.993223 0.4 0.5 0.991834 0.991834 0.495917 -0.991834 0.5 0.5 0.99005 0.99005 0.495025 -0.99005 0.6 0.5 0.987874 0.987874 0.493937 -0.987874 0.7 0.5 0.985309 0.985309 0.492654 -0.985309 0.8 0.5 0.982357 0.982357 0.491179 -0.982357 0.9 0.5 0.979023 0.979023 0.489512 -0.979023 1 0.5 0.97531 0.97531 0.487655 -0.97531 1.1 0.5 0.971222 0.971222 0.485611 -0.971222 1.2 0.5 0.966765 0.966765 0.483382 -0.966765 1.3 0.5 0.961943 0.961943 0.480972 -0.961943 1.4 0.5 0.956763 0.956763 0.478381 -0.956763 1.5 0.5 0.951229 0.951229 0.475615 -0.951229 1.6 0.5 0.94535 0.94535 0.472675 -0.94535 1.7 0.5 0.939131 0.939131 0.469566 -0.939131 1.8 0.5 0.93258 0.93258 0.46629 -0.93258 1.9 0.5 0.925705 0.925705 0.462852 -0.925705 2 0.5 0.918512 0.918512 0.459256 -0.918512 2.1 0.5 0.911011 0.911011 0.455506 -0.911011 2.2 0.5 0.90321 0.90321 0.451605 -0.90321 2.3 0.5 0.895118 0.895118 0.447559 -0.895118 2.4 0.5 0.886743 0.886743 0.443372 -0.886743 2.5 0.5 0.878095 0.878095 0.439048 -0.878095 2.6 0.5 0.869184 0.869184 0.434592 -0.869184 2.7 0.5 0.86002 0.86002 0.43001 -0.86002 2.8 0.5 0.850611 0.850611 0.425306 -0.850611 2.9 0.5 0.840969 0.840969 0.420485 -0.840969 3 0.5 0.831104 0.831104 0.415552 -0.831104 3.1 0.5 0.821026 0.821026 0.410513 -0.821026 3.2 0.5 0.810746 0.810746 0.405373 -0.810746 3.3 0.5 0.800275 0.800275 0.400137 -0.800275 3.4 0.5 0.789623 0.789623 0.394811 -0.789623 3.5 0.5 0.778801 0.778801 0.3894 -0.778801 3.6 0.5 0.76782 0.76782 0.38391 -0.76782 3.7 0.5 0.756691 0.756691 0.378346 -0.756691 3.8 0.5 0.745426 0.745426 0.372713 -0.745426 3.9 0.5 0.734034 0.734034 0.367017 -0.734034 4 0.5 0.722527 0.722527 0.361264 -0.722527 4.1 0.5 0.710917 0.710917 0.355458 -0.710917 4.2 0.5 0.699213 0.699213 0.349606 -0.699213 4.3 0.5 0.687427 0.687427 0.343713 -0.687427 4.4 0.5 0.675569 0.675569 0.337784 -0.675569 4.5 0.5 0.66365 0.66365 0.331825 -0.66365 4.6 0.5 0.651681 0.651681 0.325841 -0.651681 4.7 0.5 0.639672 0.639672 0.319836 -0.639672 4.8 0.5 0.627633 0.627633 0.313816 -0.627633 4.9 0.5 0.615574 0.615574 0.307787 -0.615574 -5 0.6 0.602179 0.602179 0.30109 -0.602179 -4.9 0.6 0.614221 0.614221 0.307111 -0.614221 -4.8 0.6 0.626254 0.626254 0.313127 -0.626254 -4.7 0.6 0.638266 0.638266 0.319133 -0.638266 -4.6 0.6 0.650249 0.650249 0.325124 -0.650249 -4.5 0.6 0.662192 0.662192 0.331096 -0.662192 -4.4 0.6 0.674084 0.674084 0.337042 -0.674084 -4.3 0.6 0.685916 0.685916 0.342958 -0.685916 -4.2 0.6 0.697676 0.697676 0.348838 -0.697676 -4.1 0.6 0.709354 0.709354 0.354677 -0.709354 -4 0.6 0.72094 0.72094 0.36047 -0.72094 -3.9 0.6 0.732421 0.732421 0.36621 -0.732421 -3.8 0.6 0.743787 0.743787 0.371894 -0.743787 -3.7 0.6 0.755028 0.755028 0.377514 -0.755028 -3.6 0.6 0.766133 0.766133 0.383066 -0.766133 -3.5 0.6 0.777089 0.777089 0.388545 -0.777089 -3.4 0.6 0.787887 0.787887 0.393944 -0.787887 -3.3 0.6 0.798516 0.798516 0.399258 -0.798516 -3.2 0.6 0.808965 0.808965 0.404482 -0.808965 -3.1 0.6 0.819222 0.819222 0.409611 -0.819222 -3 0.6 0.829278 0.829278 0.414639 -0.829278 -2.9 0.6 0.839121 0.839121 0.419561 -0.839121 -2.8 0.6 0.848742 0.848742 0.424371 -0.848742 -2.7 0.6 0.85813 0.85813 0.429065 -0.85813 -2.6 0.6 0.867274 0.867274 0.433637 -0.867274 -2.5 0.6 0.876166 0.876166 0.438083 -0.876166 -2.4 0.6 0.884794 0.884794 0.442397 -0.884794 -2.3 0.6 0.893151 0.893151 0.446575 -0.893151 -2.2 0.6 0.901225 0.901225 0.450613 -0.901225 -2.1 0.6 0.909009 0.909009 0.454505 -0.909009 -2 0.6 0.916494 0.916494 0.458247 -0.916494 -1.9 0.6 0.92367 0.92367 0.461835 -0.92367 -1.8 0.6 0.930531 0.930531 0.465265 -0.930531 -1.7 0.6 0.937067 0.937067 0.468534 -0.937067 -1.6 0.6 0.943273 0.943273 0.471636 -0.943273 -1.5 0.6 0.949139 0.949139 0.47457 -0.949139 -1.4 0.6 0.95466 0.95466 0.47733 -0.95466 -1.3 0.6 0.959829 0.959829 0.479915 -0.959829 -1.2 0.6 0.96464 0.96464 0.48232 -0.96464 -1.1 0.6 0.969088 0.969088 0.484544 -0.969088 -1 0.6 0.973167 0.973167 0.486583 -0.973167 -0.9 0.6 0.976872 0.976872 0.488436 -0.976872 -0.8 0.6 0.980199 0.980199 0.490099 -0.980199 -0.7 0.6 0.983144 0.983144 0.491572 -0.983144 -0.6 0.6 0.985703 0.985703 0.492852 -0.985703 -0.5 0.6 0.987874 0.987874 0.493937 -0.987874 -0.4 0.6 0.989654 0.989654 0.494827 -0.989654 -0.3 0.6 0.99104 0.99104 0.49552 -0.99104 -0.2 0.6 0.992032 0.992032 0.496016 -0.992032 -0.1 0.6 0.992627 0.992627 0.496314 -0.992627 0 0.6 0.992826 0.992826 0.496413 -0.992826 0.1 0.6 0.992627 0.992627 0.496314 -0.992627 0.2 0.6 0.992032 0.992032 0.496016 -0.992032 0.3 0.6 0.99104 0.99104 0.49552 -0.99104 0.4 0.6 0.989654 0.989654 0.494827 -0.989654 0.5 0.6 0.987874 0.987874 0.493937 -0.987874 0.6 0.6 0.985703 0.985703 0.492852 -0.985703 0.7 0.6 0.983144 0.983144 0.491572 -0.983144 0.8 0.6 0.980199 0.980199 0.490099 -0.980199 0.9 0.6 0.976872 0.976872 0.488436 -0.976872 1 0.6 0.973167 0.973167 0.486583 -0.973167 1.1 0.6 0.969088 0.969088 0.484544 -0.969088 1.2 0.6 0.96464 0.96464 0.48232 -0.96464 1.3 0.6 0.959829 0.959829 0.479915 -0.959829 1.4 0.6 0.95466 0.95466 0.47733 -0.95466 1.5 0.6 0.949139 0.949139 0.47457 -0.949139 1.6 0.6 0.943273 0.943273 0.471636 -0.943273 1.7 0.6 0.937067 0.937067 0.468534 -0.937067 1.8 0.6 0.930531 0.930531 0.465265 -0.930531 1.9 0.6 0.92367 0.92367 0.461835 -0.92367 2 0.6 0.916494 0.916494 0.458247 -0.916494 2.1 0.6 0.909009 0.909009 0.454505 -0.909009 2.2 0.6 0.901225 0.901225 0.450613 -0.901225 2.3 0.6 0.893151 0.893151 0.446575 -0.893151 2.4 0.6 0.884794 0.884794 0.442397 -0.884794 2.5 0.6 0.876166 0.876166 0.438083 -0.876166 2.6 0.6 0.867274 0.867274 0.433637 -0.867274 2.7 0.6 0.85813 0.85813 0.429065 -0.85813 2.8 0.6 0.848742 0.848742 0.424371 -0.848742 2.9 0.6 0.839121 0.839121 0.419561 -0.839121 3 0.6 0.829278 0.829278 0.414639 -0.829278 3.1 0.6 0.819222 0.819222 0.409611 -0.819222 3.2 0.6 0.808965 0.808965 0.404482 -0.808965 3.3 0.6 0.798516 0.798516 0.399258 -0.798516 3.4 0.6 0.787887 0.787887 0.393944 -0.787887 3.5 0.6 0.777089 0.777089 0.388545 -0.777089 3.6 0.6 0.766133 0.766133 0.383066 -0.766133 3.7 0.6 0.755028 0.755028 0.377514 -0.755028 3.8 0.6 0.743787 0.743787 0.371894 -0.743787 3.9 0.6 0.732421 0.732421 0.36621 -0.732421 4 0.6 0.72094 0.72094 0.36047 -0.72094 4.1 0.6 0.709354 0.709354 0.354677 -0.709354 4.2 0.6 0.697676 0.697676 0.348838 -0.697676 4.3 0.6 0.685916 0.685916 0.342958 -0.685916 4.4 0.6 0.674084 0.674084 0.337042 -0.674084 4.5 0.6 0.662192 0.662192 0.331096 -0.662192 4.6 0.6 0.650249 0.650249 0.325124 -0.650249 4.7 0.6 0.638266 0.638266 0.319133 -0.638266 4.8 0.6 0.626254 0.626254 0.313127 -0.626254 4.9 0.6 0.614221 0.614221 0.307111 -0.614221 -5 0.7 0.600616 0.600616 0.300308 -0.600616 -4.9 0.7 0.612626 0.612626 0.306313 -0.612626 -4.8 0.7 0.624627 0.624627 0.312314 -0.624627 -4.7 0.7 0.636609 0.636609 0.318304 -0.636609 -4.6 0.7 0.64856 0.64856 0.32428 -0.64856 -4.5 0.7 0.660472 0.660472 0.330236 -0.660472 -4.4 0.7 0.672334 0.672334 0.336167 -0.672334 -4.3 0.7 0.684135 0.684135 0.342068 -0.684135 -4.2 0.7 0.695865 0.695865 0.347932 -0.695865 -4.1 0.7 0.707512 0.707512 0.353756 -0.707512 -4 0.7 0.719068 0.719068 0.359534 -0.719068 -3.9 0.7 0.730519 0.730519 0.36526 -0.730519 -3.8 0.7 0.741856 0.741856 0.370928 -0.741856 -3.7 0.7 0.753068 0.753068 0.376534 -0.753068 -3.6 0.7 0.764143 0.764143 0.382072 -0.764143 -3.5 0.7 0.775071 0.775071 0.387536 -0.775071 -3.4 0.7 0.785842 0.785842 0.392921 -0.785842 -3.3 0.7 0.796443 0.796443 0.398221 -0.796443 -3.2 0.7 0.806864 0.806864 0.403432 -0.806864 -3.1 0.7 0.817095 0.817095 0.408547 -0.817095 -3 0.7 0.827125 0.827125 0.413562 -0.827125 -2.9 0.7 0.836942 0.836942 0.418471 -0.836942 -2.8 0.7 0.846538 0.846538 0.423269 -0.846538 -2.7 0.7 0.855901 0.855901 0.427951 -0.855901 -2.6 0.7 0.865022 0.865022 0.432511 -0.865022 -2.5 0.7 0.873891 0.873891 0.436945 -0.873891 -2.4 0.7 0.882497 0.882497 0.441248 -0.882497 -2.3 0.7 0.890831 0.890831 0.445416 -0.890831 -2.2 0.7 0.898885 0.898885 0.449443 -0.898885 -2.1 0.7 0.906649 0.906649 0.453324 -0.906649 -2 0.7 0.914114 0.914114 0.457057 -0.914114 -1.9 0.7 0.921272 0.921272 0.460636 -0.921272 -1.8 0.7 0.928115 0.928115 0.464057 -0.928115 -1.7 0.7 0.934634 0.934634 0.467317 -0.934634 -1.6 0.7 0.940823 0.940823 0.470412 -0.940823 -1.5 0.7 0.946674 0.946674 0.473337 -0.946674 -1.4 0.7 0.952181 0.952181 0.476091 -0.952181 -1.3 0.7 0.957337 0.957337 0.478668 -0.957337 -1.2 0.7 0.962135 0.962135 0.481068 -0.962135 -1.1 0.7 0.966572 0.966572 0.483286 -0.966572 -1 0.7 0.97064 0.97064 0.48532 -0.97064 -0.9 0.7 0.974335 0.974335 0.487168 -0.974335 -0.8 0.7 0.977653 0.977653 0.488827 -0.977653 -0.7 0.7 0.980591 0.980591 0.490295 -0.980591 -0.6 0.7 0.983144 0.983144 0.491572 -0.983144 -0.5 0.7 0.985309 0.985309 0.492654 -0.985309 -0.4 0.7 0.987084 0.987084 0.493542 -0.987084 -0.3 0.7 0.988467 0.988467 0.494234 -0.988467 -0.2 0.7 0.989456 0.989456 0.494728 -0.989456 -0.1 0.7 0.99005 0.99005 0.495025 -0.99005 0 0.7 0.990248 0.990248 0.495124 -0.990248 0.1 0.7 0.99005 0.99005 0.495025 -0.99005 0.2 0.7 0.989456 0.989456 0.494728 -0.989456 0.3 0.7 0.988467 0.988467 0.494234 -0.988467 0.4 0.7 0.987084 0.987084 0.493542 -0.987084 0.5 0.7 0.985309 0.985309 0.492654 -0.985309 0.6 0.7 0.983144 0.983144 0.491572 -0.983144 0.7 0.7 0.980591 0.980591 0.490295 -0.980591 0.8 0.7 0.977653 0.977653 0.488827 -0.977653 0.9 0.7 0.974335 0.974335 0.487168 -0.974335 1 0.7 0.97064 0.97064 0.48532 -0.97064 1.1 0.7 0.966572 0.966572 0.483286 -0.966572 1.2 0.7 0.962135 0.962135 0.481068 -0.962135 1.3 0.7 0.957337 0.957337 0.478668 -0.957337 1.4 0.7 0.952181 0.952181 0.476091 -0.952181 1.5 0.7 0.946674 0.946674 0.473337 -0.946674 1.6 0.7 0.940823 0.940823 0.470412 -0.940823 1.7 0.7 0.934634 0.934634 0.467317 -0.934634 1.8 0.7 0.928115 0.928115 0.464057 -0.928115 1.9 0.7 0.921272 0.921272 0.460636 -0.921272 2 0.7 0.914114 0.914114 0.457057 -0.914114 2.1 0.7 0.906649 0.906649 0.453324 -0.906649 2.2 0.7 0.898885 0.898885 0.449443 -0.898885 2.3 0.7 0.890831 0.890831 0.445416 -0.890831 2.4 0.7 0.882497 0.882497 0.441248 -0.882497 2.5 0.7 0.873891 0.873891 0.436945 -0.873891 2.6 0.7 0.865022 0.865022 0.432511 -0.865022 2.7 0.7 0.855901 0.855901 0.427951 -0.855901 2.8 0.7 0.846538 0.846538 0.423269 -0.846538 2.9 0.7 0.836942 0.836942 0.418471 -0.836942 3 0.7 0.827125 0.827125 0.413562 -0.827125 3.1 0.7 0.817095 0.817095 0.408547 -0.817095 3.2 0.7 0.806864 0.806864 0.403432 -0.806864 3.3 0.7 0.796443 0.796443 0.398221 -0.796443 3.4 0.7 0.785842 0.785842 0.392921 -0.785842 3.5 0.7 0.775071 0.775071 0.387536 -0.775071 3.6 0.7 0.764143 0.764143 0.382072 -0.764143 3.7 0.7 0.753068 0.753068 0.376534 -0.753068 3.8 0.7 0.741856 0.741856 0.370928 -0.741856 3.9 0.7 0.730519 0.730519 0.36526 -0.730519 4 0.7 0.719068 0.719068 0.359534 -0.719068 4.1 0.7 0.707512 0.707512 0.353756 -0.707512 4.2 0.7 0.695865 0.695865 0.347932 -0.695865 4.3 0.7 0.684135 0.684135 0.342068 -0.684135 4.4 0.7 0.672334 0.672334 0.336167 -0.672334 4.5 0.7 0.660472 0.660472 0.330236 -0.660472 4.6 0.7 0.64856 0.64856 0.32428 -0.64856 4.7 0.7 0.636609 0.636609 0.318304 -0.636609 4.8 0.7 0.624627 0.624627 0.312314 -0.624627 4.9 0.7 0.612626 0.612626 0.306313 -0.612626 -5 0.8 0.598817 0.598817 0.299408 -0.598817 -4.9 0.8 0.610791 0.610791 0.305396 -0.610791 -4.8 0.8 0.622756 0.622756 0.311378 -0.622756 -4.7 0.8 0.634702 0.634702 0.317351 -0.634702 -4.6 0.8 0.646618 0.646618 0.323309 -0.646618 -4.5 0.8 0.658494 0.658494 0.329247 -0.658494 -4.4 0.8 0.67032 0.67032 0.33516 -0.67032 -4.3 0.8 0.682086 0.682086 0.341043 -0.682086 -4.2 0.8 0.69378 0.69378 0.34689 -0.69378 -4.1 0.8 0.705393 0.705393 0.352697 -0.705393 -4 0.8 0.716914 0.716914 0.358457 -0.716914 -3.9 0.8 0.728331 0.728331 0.364165 -0.728331 -3.8 0.8 0.739634 0.739634 0.369817 -0.739634 -3.7 0.8 0.750812 0.750812 0.375406 -0.750812 -3.6 0.8 0.761854 0.761854 0.380927 -0.761854 -3.5 0.8 0.77275 0.77275 0.386375 -0.77275 -3.4 0.8 0.783488 0.783488 0.391744 -0.783488 -3.3 0.8 0.794057 0.794057 0.397029 -0.794057 -3.2 0.8 0.804447 0.804447 0.402224 -0.804447 -3.1 0.8 0.814647 0.814647 0.407324 -0.814647 -3 0.8 0.824647 0.824647 0.412323 -0.824647 -2.9 0.8 0.834435 0.834435 0.417218 -0.834435 -2.8 0.8 0.844002 0.844002 0.422001 -0.844002 -2.7 0.8 0.853338 0.853338 0.426669 -0.853338 -2.6 0.8 0.862431 0.862431 0.431216 -0.862431 -2.5 0.8 0.871273 0.871273 0.435636 -0.871273 -2.4 0.8 0.879853 0.879853 0.439927 -0.879853 -2.3 0.8 0.888163 0.888163 0.444081 -0.888163 -2.2 0.8 0.896193 0.896193 0.448096 -0.896193 -2.1 0.8 0.903933 0.903933 0.451967 -0.903933 -2 0.8 0.911376 0.911376 0.455688 -0.911376 -1.9 0.8 0.918512 0.918512 0.459256 -0.918512 -1.8 0.8 0.925334 0.925334 0.462667 -0.925334 -1.7 0.8 0.931835 0.931835 0.465917 -0.931835 -1.6 0.8 0.938005 0.938005 0.469002 -0.938005 -1.5 0.8 0.943839 0.943839 0.471919 -0.943839 -1.4 0.8 0.949329 0.949329 0.474664 -0.949329 -1.3 0.8 0.954469 0.954469 0.477235 -0.954469 -1.2 0.8 0.959253 0.959253 0.479627 -0.959253 -1.1 0.8 0.963676 0.963676 0.481838 -0.963676 -1 0.8 0.967732 0.967732 0.483866 -0.967732 -0.9 0.8 0.971416 0.971416 0.485708 -0.971416 -0.8 0.8 0.974725 0.974725 0.487362 -0.974725 -0.7 0.8 0.977653 0.977653 0.488827 -0.977653 -0.6 0.8 0.980199 0.980199 0.490099 -0.980199 -0.5 0.8 0.982357 0.982357 0.491179 -0.982357 -0.4 0.8 0.984127 0.984127 0.492064 -0.984127 -0.3 0.8 0.985506 0.985506 0.492753 -0.985506 -0.2 0.8 0.986492 0.986492 0.493246 -0.986492 -0.1 0.8 0.987084 0.987084 0.493542 -0.987084 0 0.8 0.987282 0.987282 0.493641 -0.987282 0.1 0.8 0.987084 0.987084 0.493542 -0.987084 0.2 0.8 0.986492 0.986492 0.493246 -0.986492 0.3 0.8 0.985506 0.985506 0.492753 -0.985506 0.4 0.8 0.984127 0.984127 0.492064 -0.984127 0.5 0.8 0.982357 0.982357 0.491179 -0.982357 0.6 0.8 0.980199 0.980199 0.490099 -0.980199 0.7 0.8 0.977653 0.977653 0.488827 -0.977653 0.8 0.8 0.974725 0.974725 0.487362 -0.974725 0.9 0.8 0.971416 0.971416 0.485708 -0.971416 1 0.8 0.967732 0.967732 0.483866 -0.967732 1.1 0.8 0.963676 0.963676 0.481838 -0.963676 1.2 0.8 0.959253 0.959253 0.479627 -0.959253 1.3 0.8 0.954469 0.954469 0.477235 -0.954469 1.4 0.8 0.949329 0.949329 0.474664 -0.949329 1.5 0.8 0.943839 0.943839 0.471919 -0.943839 1.6 0.8 0.938005 0.938005 0.469002 -0.938005 1.7 0.8 0.931835 0.931835 0.465917 -0.931835 1.8 0.8 0.925334 0.925334 0.462667 -0.925334 1.9 0.8 0.918512 0.918512 0.459256 -0.918512 2 0.8 0.911376 0.911376 0.455688 -0.911376 2.1 0.8 0.903933 0.903933 0.451967 -0.903933 2.2 0.8 0.896193 0.896193 0.448096 -0.896193 2.3 0.8 0.888163 0.888163 0.444081 -0.888163 2.4 0.8 0.879853 0.879853 0.439927 -0.879853 2.5 0.8 0.871273 0.871273 0.435636 -0.871273 2.6 0.8 0.862431 0.862431 0.431216 -0.862431 2.7 0.8 0.853338 0.853338 0.426669 -0.853338 2.8 0.8 0.844002 0.844002 0.422001 -0.844002 2.9 0.8 0.834435 0.834435 0.417218 -0.834435 3 0.8 0.824647 0.824647 0.412323 -0.824647 3.1 0.8 0.814647 0.814647 0.407324 -0.814647 3.2 0.8 0.804447 0.804447 0.402224 -0.804447 3.3 0.8 0.794057 0.794057 0.397029 -0.794057 3.4 0.8 0.783488 0.783488 0.391744 -0.783488 3.5 0.8 0.77275 0.77275 0.386375 -0.77275 3.6 0.8 0.761854 0.761854 0.380927 -0.761854 3.7 0.8 0.750812 0.750812 0.375406 -0.750812 3.8 0.8 0.739634 0.739634 0.369817 -0.739634 3.9 0.8 0.728331 0.728331 0.364165 -0.728331 4 0.8 0.716914 0.716914 0.358457 -0.716914 4.1 0.8 0.705393 0.705393 0.352697 -0.705393 4.2 0.8 0.69378 0.69378 0.34689 -0.69378 4.3 0.8 0.682086 0.682086 0.341043 -0.682086 4.4 0.8 0.67032 0.67032 0.33516 -0.67032 4.5 0.8 0.658494 0.658494 0.329247 -0.658494 4.6 0.8 0.646618 0.646618 0.323309 -0.646618 4.7 0.8 0.634702 0.634702 0.317351 -0.634702 4.8 0.8 0.622756 0.622756 0.311378 -0.622756 4.9 0.8 0.610791 0.610791 0.305396 -0.610791 -5 0.9 0.596784 0.596784 0.298392 -0.596784 -4.9 0.9 0.608718 0.608718 0.304359 -0.608718 -4.8 0.9 0.620643 0.620643 0.310321 -0.620643 -4.7 0.9 0.632547 0.632547 0.316274 -0.632547 -4.6 0.9 0.644423 0.644423 0.322211 -0.644423 -4.5 0.9 0.656259 0.656259 0.328129 -0.656259 -4.4 0.9 0.668045 0.668045 0.334022 -0.668045 -4.3 0.9 0.679771 0.679771 0.339885 -0.679771 -4.2 0.9 0.691425 0.691425 0.345713 -0.691425 -4.1 0.9 0.702999 0.702999 0.351499 -0.702999 -4 0.9 0.71448 0.71448 0.35724 -0.71448 -3.9 0.9 0.725859 0.725859 0.362929 -0.725859 -3.8 0.9 0.737123 0.737123 0.368562 -0.737123 -3.7 0.9 0.748264 0.748264 0.374132 -0.748264 -3.6 0.9 0.759268 0.759268 0.379634 -0.759268 -3.5 0.9 0.770127 0.770127 0.385063 -0.770127 -3.4 0.9 0.780828 0.780828 0.390414 -0.780828 -3.3 0.9 0.791362 0.791362 0.395681 -0.791362 -3.2 0.9 0.801717 0.801717 0.400858 -0.801717 -3.1 0.9 0.811882 0.811882 0.405941 -0.811882 -3 0.9 0.821848 0.821848 0.410924 -0.821848 -2.9 0.9 0.831603 0.831603 0.415802 -0.831603 -2.8 0.9 0.841138 0.841138 0.420569 -0.841138 -2.7 0.9 0.850441 0.850441 0.425221 -0.850441 -2.6 0.9 0.859504 0.859504 0.429752 -0.859504 -2.5 0.9 0.868316 0.868316 0.434158 -0.868316 -2.4 0.9 0.876867 0.876867 0.438433 -0.876867 -2.3 0.9 0.885148 0.885148 0.442574 -0.885148 -2.2 0.9 0.893151 0.893151 0.446575 -0.893151 -2.1 0.9 0.900865 0.900865 0.450432 -0.900865 -2 0.9 0.908282 0.908282 0.454141 -0.908282 -1.9 0.9 0.915395 0.915395 0.457697 -0.915395 -1.8 0.9 0.922194 0.922194 0.461097 -0.922194 -1.7 0.9 0.928672 0.928672 0.464336 -0.928672 -1.6 0.9 0.934821 0.934821 0.467411 -0.934821 -1.5 0.9 0.940635 0.940635 0.470318 -0.940635 -1.4 0.9 0.946107 0.946107 0.473053 -0.946107 -1.3 0.9 0.951229 0.951229 0.475615 -0.951229 -1.2 0.9 0.955997 0.955997 0.477999 -0.955997 -1.1 0.9 0.960405 0.960405 0.480203 -0.960405 -1 0.9 0.964447 0.964447 0.482224 -0.964447 -0.9 0.9 0.968119 0.968119 0.48406 -0.968119 -0.8 0.9 0.971416 0.971416 0.485708 -0.971416 -0.7 0.9 0.974335 0.974335 0.487168 -0.974335 -0.6 0.9 0.976872 0.976872 0.488436 -0.976872 -0.5 0.9 0.979023 0.979023 0.489512 -0.979023 -0.4 0.9 0.980787 0.980787 0.490393 -0.980787 -0.3 0.9 0.982161 0.982161 0.491081 -0.982161 -0.2 0.9 0.983144 0.983144 0.491572 -0.983144 -0.1 0.9 0.983734 0.983734 0.491867 -0.983734 0 0.9 0.983931 0.983931 0.491965 -0.983931 0.1 0.9 0.983734 0.983734 0.491867 -0.983734 0.2 0.9 0.983144 0.983144 0.491572 -0.983144 0.3 0.9 0.982161 0.982161 0.491081 -0.982161 0.4 0.9 0.980787 0.980787 0.490393 -0.980787 0.5 0.9 0.979023 0.979023 0.489512 -0.979023 0.6 0.9 0.976872 0.976872 0.488436 -0.976872 0.7 0.9 0.974335 0.974335 0.487168 -0.974335 0.8 0.9 0.971416 0.971416 0.485708 -0.971416 0.9 0.9 0.968119 0.968119 0.48406 -0.968119 1 0.9 0.964447 0.964447 0.482224 -0.964447 1.1 0.9 0.960405 0.960405 0.480203 -0.960405 1.2 0.9 0.955997 0.955997 0.477999 -0.955997 1.3 0.9 0.951229 0.951229 0.475615 -0.951229 1.4 0.9 0.946107 0.946107 0.473053 -0.946107 1.5 0.9 0.940635 0.940635 0.470318 -0.940635 1.6 0.9 0.934821 0.934821 0.467411 -0.934821 1.7 0.9 0.928672 0.928672 0.464336 -0.928672 1.8 0.9 0.922194 0.922194 0.461097 -0.922194 1.9 0.9 0.915395 0.915395 0.457697 -0.915395 2 0.9 0.908282 0.908282 0.454141 -0.908282 2.1 0.9 0.900865 0.900865 0.450432 -0.900865 2.2 0.9 0.893151 0.893151 0.446575 -0.893151 2.3 0.9 0.885148 0.885148 0.442574 -0.885148 2.4 0.9 0.876867 0.876867 0.438433 -0.876867 2.5 0.9 0.868316 0.868316 0.434158 -0.868316 2.6 0.9 0.859504 0.859504 0.429752 -0.859504 2.7 0.9 0.850441 0.850441 0.425221 -0.850441 2.8 0.9 0.841138 0.841138 0.420569 -0.841138 2.9 0.9 0.831603 0.831603 0.415802 -0.831603 3 0.9 0.821848 0.821848 0.410924 -0.821848 3.1 0.9 0.811882 0.811882 0.405941 -0.811882 3.2 0.9 0.801717 0.801717 0.400858 -0.801717 3.3 0.9 0.791362 0.791362 0.395681 -0.791362 3.4 0.9 0.780828 0.780828 0.390414 -0.780828 3.5 0.9 0.770127 0.770127 0.385063 -0.770127 3.6 0.9 0.759268 0.759268 0.379634 -0.759268 3.7 0.9 0.748264 0.748264 0.374132 -0.748264 3.8 0.9 0.737123 0.737123 0.368562 -0.737123 3.9 0.9 0.725859 0.725859 0.362929 -0.725859 4 0.9 0.71448 0.71448 0.35724 -0.71448 4.1 0.9 0.702999 0.702999 0.351499 -0.702999 4.2 0.9 0.691425 0.691425 0.345713 -0.691425 4.3 0.9 0.679771 0.679771 0.339885 -0.679771 4.4 0.9 0.668045 0.668045 0.334022 -0.668045 4.5 0.9 0.656259 0.656259 0.328129 -0.656259 4.6 0.9 0.644423 0.644423 0.322211 -0.644423 4.7 0.9 0.632547 0.632547 0.316274 -0.632547 4.8 0.9 0.620643 0.620643 0.310321 -0.620643 4.9 0.9 0.608718 0.608718 0.304359 -0.608718 -5 1 0.594521 0.594521 0.29726 -0.594521 -4.9 1 0.606409 0.606409 0.303205 -0.606409 -4.8 1 0.618289 0.618289 0.309144 -0.618289 -4.7 1 0.630148 0.630148 0.315074 -0.630148 -4.6 1 0.641979 0.641979 0.320989 -0.641979 -4.5 1 0.65377 0.65377 0.326885 -0.65377 -4.4 1 0.665511 0.665511 0.332756 -0.665511 -4.3 1 0.677192 0.677192 0.338596 -0.677192 -4.2 1 0.688803 0.688803 0.344401 -0.688803 -4.1 1 0.700333 0.700333 0.350166 -0.700333 -4 1 0.71177 0.71177 0.355885 -0.71177 -3.9 1 0.723106 0.723106 0.361553 -0.723106 -3.8 1 0.734328 0.734328 0.367164 -0.734328 -3.7 1 0.745426 0.745426 0.372713 -0.745426 -3.6 1 0.756389 0.756389 0.378194 -0.756389 -3.5 1 0.767206 0.767206 0.383603 -0.767206 -3.4 1 0.777867 0.777867 0.388933 -0.777867 -3.3 1 0.78836 0.78836 0.39418 -0.78836 -3.2 1 0.798676 0.798676 0.399338 -0.798676 -3.1 1 0.808803 0.808803 0.404401 -0.808803 -3 1 0.818731 0.818731 0.409365 -0.818731 -2.9 1 0.828449 0.828449 0.414225 -0.828449 -2.8 1 0.837947 0.837947 0.418974 -0.837947 -2.7 1 0.847216 0.847216 0.423608 -0.847216 -2.6 1 0.856244 0.856244 0.428122 -0.856244 -2.5 1 0.865022 0.865022 0.432511 -0.865022 -2.4 1 0.873541 0.873541 0.436771 -0.873541 -2.3 1 0.881791 0.881791 0.440896 -0.881791 -2.2 1 0.889763 0.889763 0.444882 -0.889763 -2.1 1 0.897448 0.897448 0.448724 -0.897448 -2 1 0.904837 0.904837 0.452419 -0.904837 -1.9 1 0.911923 0.911923 0.455961 -0.911923 -1.8 1 0.918696 0.918696 0.459348 -0.918696 -1.7 1 0.925149 0.925149 0.462575 -0.925149 -1.6 1 0.931276 0.931276 0.465638 -0.931276 -1.5 1 0.937067 0.937067 0.468534 -0.937067 -1.4 1 0.942518 0.942518 0.471259 -0.942518 -1.3 1 0.947622 0.947622 0.473811 -0.947622 -1.2 1 0.952372 0.952372 0.476186 -0.952372 -1.1 1 0.956763 0.956763 0.478381 -0.956763 -1 1 0.960789 0.960789 0.480395 -0.960789 -0.9 1 0.964447 0.964447 0.482224 -0.964447 -0.8 1 0.967732 0.967732 0.483866 -0.967732 -0.7 1 0.97064 0.97064 0.48532 -0.97064 -0.6 1 0.973167 0.973167 0.486583 -0.973167 -0.5 1 0.97531 0.97531 0.487655 -0.97531 -0.4 1 0.977067 0.977067 0.488534 -0.977067 -0.3 1 0.978436 0.978436 0.489218 -0.978436 -0.2 1 0.979415 0.979415 0.489707 -0.979415 -0.1 1 0.980003 0.980003 0.490001 -0.980003 0 1 0.980199 0.980199 0.490099 -0.980199 0.1 1 0.980003 0.980003 0.490001 -0.980003 0.2 1 0.979415 0.979415 0.489707 -0.979415 0.3 1 0.978436 0.978436 0.489218 -0.978436 0.4 1 0.977067 0.977067 0.488534 -0.977067 0.5 1 0.97531 0.97531 0.487655 -0.97531 0.6 1 0.973167 0.973167 0.486583 -0.973167 0.7 1 0.97064 0.97064 0.48532 -0.97064 0.8 1 0.967732 0.967732 0.483866 -0.967732 0.9 1 0.964447 0.964447 0.482224 -0.964447 1 1 0.960789 0.960789 0.480395 -0.960789 1.1 1 0.956763 0.956763 0.478381 -0.956763 1.2 1 0.952372 0.952372 0.476186 -0.952372 1.3 1 0.947622 0.947622 0.473811 -0.947622 1.4 1 0.942518 0.942518 0.471259 -0.942518 1.5 1 0.937067 0.937067 0.468534 -0.937067 1.6 1 0.931276 0.931276 0.465638 -0.931276 1.7 1 0.925149 0.925149 0.462575 -0.925149 1.8 1 0.918696 0.918696 0.459348 -0.918696 1.9 1 0.911923 0.911923 0.455961 -0.911923 2 1 0.904837 0.904837 0.452419 -0.904837 2.1 1 0.897448 0.897448 0.448724 -0.897448 2.2 1 0.889763 0.889763 0.444882 -0.889763 2.3 1 0.881791 0.881791 0.440896 -0.881791 2.4 1 0.873541 0.873541 0.436771 -0.873541 2.5 1 0.865022 0.865022 0.432511 -0.865022 2.6 1 0.856244 0.856244 0.428122 -0.856244 2.7 1 0.847216 0.847216 0.423608 -0.847216 2.8 1 0.837947 0.837947 0.418974 -0.837947 2.9 1 0.828449 0.828449 0.414225 -0.828449 3 1 0.818731 0.818731 0.409365 -0.818731 3.1 1 0.808803 0.808803 0.404401 -0.808803 3.2 1 0.798676 0.798676 0.399338 -0.798676 3.3 1 0.78836 0.78836 0.39418 -0.78836 3.4 1 0.777867 0.777867 0.388933 -0.777867 3.5 1 0.767206 0.767206 0.383603 -0.767206 3.6 1 0.756389 0.756389 0.378194 -0.756389 3.7 1 0.745426 0.745426 0.372713 -0.745426 3.8 1 0.734328 0.734328 0.367164 -0.734328 3.9 1 0.723106 0.723106 0.361553 -0.723106 4 1 0.71177 0.71177 0.355885 -0.71177 4.1 1 0.700333 0.700333 0.350166 -0.700333 4.2 1 0.688803 0.688803 0.344401 -0.688803 4.3 1 0.677192 0.677192 0.338596 -0.677192 4.4 1 0.665511 0.665511 0.332756 -0.665511 4.5 1 0.65377 0.65377 0.326885 -0.65377 4.6 1 0.641979 0.641979 0.320989 -0.641979 4.7 1 0.630148 0.630148 0.315074 -0.630148 4.8 1 0.618289 0.618289 0.309144 -0.618289 4.9 1 0.606409 0.606409 0.303205 -0.606409 -5 1.1 0.592029 0.592029 0.296014 -0.592029 -4.9 1.1 0.603868 0.603868 0.301934 -0.603868 -4.8 1.1 0.615697 0.615697 0.307849 -0.615697 -4.7 1.1 0.627507 0.627507 0.313754 -0.627507 -4.6 1.1 0.639288 0.639288 0.319644 -0.639288 -4.5 1.1 0.65103 0.65103 0.325515 -0.65103 -4.4 1.1 0.662722 0.662722 0.331361 -0.662722 -4.3 1.1 0.674354 0.674354 0.337177 -0.674354 -4.2 1.1 0.685916 0.685916 0.342958 -0.685916 -4.1 1.1 0.697397 0.697397 0.348699 -0.697397 -4 1.1 0.708787 0.708787 0.354394 -0.708787 -3.9 1.1 0.720075 0.720075 0.360037 -0.720075 -3.8 1.1 0.73125 0.73125 0.365625 -0.73125 -3.7 1.1 0.742301 0.742301 0.371151 -0.742301 -3.6 1.1 0.753218 0.753218 0.376609 -0.753218 -3.5 1.1 0.76399 0.76399 0.381995 -0.76399 -3.4 1.1 0.774607 0.774607 0.387303 -0.774607 -3.3 1.1 0.785056 0.785056 0.392528 -0.785056 -3.2 1.1 0.795329 0.795329 0.397664 -0.795329 -3.1 1.1 0.805413 0.805413 0.402707 -0.805413 -3 1.1 0.815299 0.815299 0.40765 -0.815299 -2.9 1.1 0.824977 0.824977 0.412488 -0.824977 -2.8 1.1 0.834435 0.834435 0.417218 -0.834435 -2.7 1.1 0.843665 0.843665 0.421832 -0.843665 -2.6 1.1 0.852655 0.852655 0.426328 -0.852655 -2.5 1.1 0.861397 0.861397 0.430698 -0.861397 -2.4 1.1 0.86988 0.86988 0.43494 -0.86988 -2.3 1.1 0.878095 0.878095 0.439048 -0.878095 -2.2 1.1 0.886034 0.886034 0.443017 -0.886034 -2.1 1.1 0.893687 0.893687 0.446843 -0.893687 -2 1.1 0.901045 0.901045 0.450523 -0.901045 -1.9 1.1 0.908101 0.908101 0.45405 -0.908101 -1.8 1.1 0.914846 0.914846 0.457423 -0.914846 -1.7 1.1 0.921272 0.921272 0.460636 -0.921272 -1.6 1.1 0.927372 0.927372 0.463686 -0.927372 -1.5 1.1 0.93314 0.93314 0.46657 -0.93314 -1.4 1.1 0.938568 0.938568 0.469284 -0.938568 -1.3 1.1 0.94365 0.94365 0.471825 -0.94365 -1.2 1.1 0.94838 0.94838 0.47419 -0.94838 -1.1 1.1 0.952753 0.952753 0.476376 -0.952753 -1 1.1 0.956763 0.956763 0.478381 -0.956763 -0.9 1.1 0.960405 0.960405 0.480203 -0.960405 -0.8 1.1 0.963676 0.963676 0.481838 -0.963676 -0.7 1.1 0.966572 0.966572 0.483286 -0.966572 -0.6 1.1 0.969088 0.969088 0.484544 -0.969088 -0.5 1.1 0.971222 0.971222 0.485611 -0.971222 -0.4 1.1 0.972972 0.972972 0.486486 -0.972972 -0.3 1.1 0.974335 0.974335 0.487168 -0.974335 -0.2 1.1 0.97531 0.97531 0.487655 -0.97531 -0.1 1.1 0.975895 0.975895 0.487948 -0.975895 0 1.1 0.97609 0.97609 0.488045 -0.97609 0.1 1.1 0.975895 0.975895 0.487948 -0.975895 0.2 1.1 0.97531 0.97531 0.487655 -0.97531 0.3 1.1 0.974335 0.974335 0.487168 -0.974335 0.4 1.1 0.972972 0.972972 0.486486 -0.972972 0.5 1.1 0.971222 0.971222 0.485611 -0.971222 0.6 1.1 0.969088 0.969088 0.484544 -0.969088 0.7 1.1 0.966572 0.966572 0.483286 -0.966572 0.8 1.1 0.963676 0.963676 0.481838 -0.963676 0.9 1.1 0.960405 0.960405 0.480203 -0.960405 1 1.1 0.956763 0.956763 0.478381 -0.956763 1.1 1.1 0.952753 0.952753 0.476376 -0.952753 1.2 1.1 0.94838 0.94838 0.47419 -0.94838 1.3 1.1 0.94365 0.94365 0.471825 -0.94365 1.4 1.1 0.938568 0.938568 0.469284 -0.938568 1.5 1.1 0.93314 0.93314 0.46657 -0.93314 1.6 1.1 0.927372 0.927372 0.463686 -0.927372 1.7 1.1 0.921272 0.921272 0.460636 -0.921272 1.8 1.1 0.914846 0.914846 0.457423 -0.914846 1.9 1.1 0.908101 0.908101 0.45405 -0.908101 2 1.1 0.901045 0.901045 0.450523 -0.901045 2.1 1.1 0.893687 0.893687 0.446843 -0.893687 2.2 1.1 0.886034 0.886034 0.443017 -0.886034 2.3 1.1 0.878095 0.878095 0.439048 -0.878095 2.4 1.1 0.86988 0.86988 0.43494 -0.86988 2.5 1.1 0.861397 0.861397 0.430698 -0.861397 2.6 1.1 0.852655 0.852655 0.426328 -0.852655 2.7 1.1 0.843665 0.843665 0.421832 -0.843665 2.8 1.1 0.834435 0.834435 0.417218 -0.834435 2.9 1.1 0.824977 0.824977 0.412488 -0.824977 3 1.1 0.815299 0.815299 0.40765 -0.815299 3.1 1.1 0.805413 0.805413 0.402707 -0.805413 3.2 1.1 0.795329 0.795329 0.397664 -0.795329 3.3 1.1 0.785056 0.785056 0.392528 -0.785056 3.4 1.1 0.774607 0.774607 0.387303 -0.774607 3.5 1.1 0.76399 0.76399 0.381995 -0.76399 3.6 1.1 0.753218 0.753218 0.376609 -0.753218 3.7 1.1 0.742301 0.742301 0.371151 -0.742301 3.8 1.1 0.73125 0.73125 0.365625 -0.73125 3.9 1.1 0.720075 0.720075 0.360037 -0.720075 4 1.1 0.708787 0.708787 0.354394 -0.708787 4.1 1.1 0.697397 0.697397 0.348699 -0.697397 4.2 1.1 0.685916 0.685916 0.342958 -0.685916 4.3 1.1 0.674354 0.674354 0.337177 -0.674354 4.4 1.1 0.662722 0.662722 0.331361 -0.662722 4.5 1.1 0.65103 0.65103 0.325515 -0.65103 4.6 1.1 0.639288 0.639288 0.319644 -0.639288 4.7 1.1 0.627507 0.627507 0.313754 -0.627507 4.8 1.1 0.615697 0.615697 0.307849 -0.615697 4.9 1.1 0.603868 0.603868 0.301934 -0.603868 -5 1.2 0.589312 0.589312 0.294656 -0.589312 -4.9 1.2 0.601096 0.601096 0.300548 -0.601096 -4.8 1.2 0.612871 0.612871 0.306436 -0.612871 -4.7 1.2 0.624627 0.624627 0.312314 -0.624627 -4.6 1.2 0.636354 0.636354 0.318177 -0.636354 -4.5 1.2 0.648042 0.648042 0.324021 -0.648042 -4.4 1.2 0.65968 0.65968 0.32984 -0.65968 -4.3 1.2 0.671259 0.671259 0.33563 -0.671259 -4.2 1.2 0.682768 0.682768 0.341384 -0.682768 -4.1 1.2 0.694197 0.694197 0.347098 -0.694197 -4 1.2 0.705534 0.705534 0.352767 -0.705534 -3.9 1.2 0.71677 0.71677 0.358385 -0.71677 -3.8 1.2 0.727894 0.727894 0.363947 -0.727894 -3.7 1.2 0.738895 0.738895 0.369447 -0.738895 -3.6 1.2 0.749762 0.749762 0.374881 -0.749762 -3.5 1.2 0.760484 0.760484 0.380242 -0.760484 -3.4 1.2 0.771052 0.771052 0.385526 -0.771052 -3.3 1.2 0.781453 0.781453 0.390727 -0.781453 -3.2 1.2 0.791678 0.791678 0.395839 -0.791678 -3.1 1.2 0.801717 0.801717 0.400858 -0.801717 -3 1.2 0.811558 0.811558 0.405779 -0.811558 -2.9 1.2 0.821191 0.821191 0.410595 -0.821191 -2.8 1.2 0.830606 0.830606 0.415303 -0.830606 -2.7 1.2 0.839793 0.839793 0.419896 -0.839793 -2.6 1.2 0.848742 0.848742 0.424371 -0.848742 -2.5 1.2 0.857443 0.857443 0.428722 -0.857443 -2.4 1.2 0.865888 0.865888 0.432944 -0.865888 -2.3 1.2 0.874065 0.874065 0.437033 -0.874065 -2.2 1.2 0.881968 0.881968 0.440984 -0.881968 -2.1 1.2 0.889585 0.889585 0.444793 -0.889585 -2 1.2 0.89691 0.89691 0.448455 -0.89691 -1.9 1.2 0.903933 0.903933 0.451967 -0.903933 -1.8 1.2 0.910647 0.910647 0.455323 -0.910647 -1.7 1.2 0.917044 0.917044 0.458522 -0.917044 -1.6 1.2 0.923116 0.923116 0.461558 -0.923116 -1.5 1.2 0.928857 0.928857 0.464429 -0.928857 -1.4 1.2 0.93426 0.93426 0.46713 -0.93426 -1.3 1.2 0.939319 0.939319 0.46966 -0.939319 -1.2 1.2 0.944027 0.944027 0.472014 -0.944027 -1.1 1.2 0.94838 0.94838 0.47419 -0.94838 -1 1.2 0.952372 0.952372 0.476186 -0.952372 -0.9 1.2 0.955997 0.955997 0.477999 -0.955997 -0.8 1.2 0.959253 0.959253 0.479627 -0.959253 -0.7 1.2 0.962135 0.962135 0.481068 -0.962135 -0.6 1.2 0.96464 0.96464 0.48232 -0.96464 -0.5 1.2 0.966765 0.966765 0.483382 -0.966765 -0.4 1.2 0.968507 0.968507 0.484253 -0.968507 -0.3 1.2 0.969863 0.969863 0.484932 -0.969863 -0.2 1.2 0.970834 0.970834 0.485417 -0.970834 -0.1 1.2 0.971416 0.971416 0.485708 -0.971416 0 1.2 0.971611 0.971611 0.485805 -0.971611 0.1 1.2 0.971416 0.971416 0.485708 -0.971416 0.2 1.2 0.970834 0.970834 0.485417 -0.970834 0.3 1.2 0.969863 0.969863 0.484932 -0.969863 0.4 1.2 0.968507 0.968507 0.484253 -0.968507 0.5 1.2 0.966765 0.966765 0.483382 -0.966765 0.6 1.2 0.96464 0.96464 0.48232 -0.96464 0.7 1.2 0.962135 0.962135 0.481068 -0.962135 0.8 1.2 0.959253 0.959253 0.479627 -0.959253 0.9 1.2 0.955997 0.955997 0.477999 -0.955997 1 1.2 0.952372 0.952372 0.476186 -0.952372 1.1 1.2 0.94838 0.94838 0.47419 -0.94838 1.2 1.2 0.944027 0.944027 0.472014 -0.944027 1.3 1.2 0.939319 0.939319 0.46966 -0.939319 1.4 1.2 0.93426 0.93426 0.46713 -0.93426 1.5 1.2 0.928857 0.928857 0.464429 -0.928857 1.6 1.2 0.923116 0.923116 0.461558 -0.923116 1.7 1.2 0.917044 0.917044 0.458522 -0.917044 1.8 1.2 0.910647 0.910647 0.455323 -0.910647 1.9 1.2 0.903933 0.903933 0.451967 -0.903933 2 1.2 0.89691 0.89691 0.448455 -0.89691 2.1 1.2 0.889585 0.889585 0.444793 -0.889585 2.2 1.2 0.881968 0.881968 0.440984 -0.881968 2.3 1.2 0.874065 0.874065 0.437033 -0.874065 2.4 1.2 0.865888 0.865888 0.432944 -0.865888 2.5 1.2 0.857443 0.857443 0.428722 -0.857443 2.6 1.2 0.848742 0.848742 0.424371 -0.848742 2.7 1.2 0.839793 0.839793 0.419896 -0.839793 2.8 1.2 0.830606 0.830606 0.415303 -0.830606 2.9 1.2 0.821191 0.821191 0.410595 -0.821191 3 1.2 0.811558 0.811558 0.405779 -0.811558 3.1 1.2 0.801717 0.801717 0.400858 -0.801717 3.2 1.2 0.791678 0.791678 0.395839 -0.791678 3.3 1.2 0.781453 0.781453 0.390727 -0.781453 3.4 1.2 0.771052 0.771052 0.385526 -0.771052 3.5 1.2 0.760484 0.760484 0.380242 -0.760484 3.6 1.2 0.749762 0.749762 0.374881 -0.749762 3.7 1.2 0.738895 0.738895 0.369447 -0.738895 3.8 1.2 0.727894 0.727894 0.363947 -0.727894 3.9 1.2 0.71677 0.71677 0.358385 -0.71677 4 1.2 0.705534 0.705534 0.352767 -0.705534 4.1 1.2 0.694197 0.694197 0.347098 -0.694197 4.2 1.2 0.682768 0.682768 0.341384 -0.682768 4.3 1.2 0.671259 0.671259 0.33563 -0.671259 4.4 1.2 0.65968 0.65968 0.32984 -0.65968 4.5 1.2 0.648042 0.648042 0.324021 -0.648042 4.6 1.2 0.636354 0.636354 0.318177 -0.636354 4.7 1.2 0.624627 0.624627 0.312314 -0.624627 4.8 1.2 0.612871 0.612871 0.306436 -0.612871 4.9 1.2 0.601096 0.601096 0.300548 -0.601096 -5 1.3 0.586373 0.586373 0.293186 -0.586373 -4.9 1.3 0.598098 0.598098 0.299049 -0.598098 -4.8 1.3 0.609815 0.609815 0.304907 -0.609815 -4.7 1.3 0.621512 0.621512 0.310756 -0.621512 -4.6 1.3 0.63318 0.63318 0.31659 -0.63318 -4.5 1.3 0.64481 0.64481 0.322405 -0.64481 -4.4 1.3 0.65639 0.65639 0.328195 -0.65639 -4.3 1.3 0.667911 0.667911 0.333956 -0.667911 -4.2 1.3 0.679363 0.679363 0.339681 -0.679363 -4.1 1.3 0.690734 0.690734 0.345367 -0.690734 -4 1.3 0.702015 0.702015 0.351008 -0.702015 -3.9 1.3 0.713195 0.713195 0.356598 -0.713195 -3.8 1.3 0.724264 0.724264 0.362132 -0.724264 -3.7 1.3 0.735209 0.735209 0.367605 -0.735209 -3.6 1.3 0.746022 0.746022 0.373011 -0.746022 -3.5 1.3 0.756691 0.756691 0.378346 -0.756691 -3.4 1.3 0.767206 0.767206 0.383603 -0.767206 -3.3 1.3 0.777556 0.777556 0.388778 -0.777556 -3.2 1.3 0.78773 0.78773 0.393865 -0.78773 -3.1 1.3 0.797718 0.797718 0.398859 -0.797718 -3 1.3 0.80751 0.80751 0.403755 -0.80751 -2.9 1.3 0.817095 0.817095 0.408547 -0.817095 -2.8 1.3 0.826463 0.826463 0.413232 -0.826463 -2.7 1.3 0.835604 0.835604 0.417802 -0.835604 -2.6 1.3 0.844509 0.844509 0.422254 -0.844509 -2.5 1.3 0.853167 0.853167 0.426583 -0.853167 -2.4 1.3 0.861569 0.861569 0.430785 -0.861569 -2.3 1.3 0.869706 0.869706 0.434853 -0.869706 -2.2 1.3 0.877569 0.877569 0.438784 -0.877569 -2.1 1.3 0.885148 0.885148 0.442574 -0.885148 -2 1.3 0.892436 0.892436 0.446218 -0.892436 -1.9 1.3 0.899425 0.899425 0.449712 -0.899425 -1.8 1.3 0.906105 0.906105 0.453053 -0.906105 -1.7 1.3 0.91247 0.91247 0.456235 -0.91247 -1.6 1.3 0.918512 0.918512 0.459256 -0.918512 -1.5 1.3 0.924225 0.924225 0.462112 -0.924225 -1.4 1.3 0.929601 0.929601 0.4648 -0.929601 -1.3 1.3 0.934634 0.934634 0.467317 -0.934634 -1.2 1.3 0.939319 0.939319 0.46966 -0.939319 -1.1 1.3 0.94365 0.94365 0.471825 -0.94365 -1 1.3 0.947622 0.947622 0.473811 -0.947622 -0.9 1.3 0.951229 0.951229 0.475615 -0.951229 -0.8 1.3 0.954469 0.954469 0.477235 -0.954469 -0.7 1.3 0.957337 0.957337 0.478668 -0.957337 -0.6 1.3 0.959829 0.959829 0.479915 -0.959829 -0.5 1.3 0.961943 0.961943 0.480972 -0.961943 -0.4 1.3 0.963676 0.963676 0.481838 -0.963676 -0.3 1.3 0.965026 0.965026 0.482513 -0.965026 -0.2 1.3 0.965992 0.965992 0.482996 -0.965992 -0.1 1.3 0.966572 0.966572 0.483286 -0.966572 0 1.3 0.966765 0.966765 0.483382 -0.966765 0.1 1.3 0.966572 0.966572 0.483286 -0.966572 0.2 1.3 0.965992 0.965992 0.482996 -0.965992 0.3 1.3 0.965026 0.965026 0.482513 -0.965026 0.4 1.3 0.963676 0.963676 0.481838 -0.963676 0.5 1.3 0.961943 0.961943 0.480972 -0.961943 0.6 1.3 0.959829 0.959829 0.479915 -0.959829 0.7 1.3 0.957337 0.957337 0.478668 -0.957337 0.8 1.3 0.954469 0.954469 0.477235 -0.954469 0.9 1.3 0.951229 0.951229 0.475615 -0.951229 1 1.3 0.947622 0.947622 0.473811 -0.947622 1.1 1.3 0.94365 0.94365 0.471825 -0.94365 1.2 1.3 0.939319 0.939319 0.46966 -0.939319 1.3 1.3 0.934634 0.934634 0.467317 -0.934634 1.4 1.3 0.929601 0.929601 0.4648 -0.929601 1.5 1.3 0.924225 0.924225 0.462112 -0.924225 1.6 1.3 0.918512 0.918512 0.459256 -0.918512 1.7 1.3 0.91247 0.91247 0.456235 -0.91247 1.8 1.3 0.906105 0.906105 0.453053 -0.906105 1.9 1.3 0.899425 0.899425 0.449712 -0.899425 2 1.3 0.892436 0.892436 0.446218 -0.892436 2.1 1.3 0.885148 0.885148 0.442574 -0.885148 2.2 1.3 0.877569 0.877569 0.438784 -0.877569 2.3 1.3 0.869706 0.869706 0.434853 -0.869706 2.4 1.3 0.861569 0.861569 0.430785 -0.861569 2.5 1.3 0.853167 0.853167 0.426583 -0.853167 2.6 1.3 0.844509 0.844509 0.422254 -0.844509 2.7 1.3 0.835604 0.835604 0.417802 -0.835604 2.8 1.3 0.826463 0.826463 0.413232 -0.826463 2.9 1.3 0.817095 0.817095 0.408547 -0.817095 3 1.3 0.80751 0.80751 0.403755 -0.80751 3.1 1.3 0.797718 0.797718 0.398859 -0.797718 3.2 1.3 0.78773 0.78773 0.393865 -0.78773 3.3 1.3 0.777556 0.777556 0.388778 -0.777556 3.4 1.3 0.767206 0.767206 0.383603 -0.767206 3.5 1.3 0.756691 0.756691 0.378346 -0.756691 3.6 1.3 0.746022 0.746022 0.373011 -0.746022 3.7 1.3 0.735209 0.735209 0.367605 -0.735209 3.8 1.3 0.724264 0.724264 0.362132 -0.724264 3.9 1.3 0.713195 0.713195 0.356598 -0.713195 4 1.3 0.702015 0.702015 0.351008 -0.702015 4.1 1.3 0.690734 0.690734 0.345367 -0.690734 4.2 1.3 0.679363 0.679363 0.339681 -0.679363 4.3 1.3 0.667911 0.667911 0.333956 -0.667911 4.4 1.3 0.65639 0.65639 0.328195 -0.65639 4.5 1.3 0.64481 0.64481 0.322405 -0.64481 4.6 1.3 0.63318 0.63318 0.31659 -0.63318 4.7 1.3 0.621512 0.621512 0.310756 -0.621512 4.8 1.3 0.609815 0.609815 0.304907 -0.609815 4.9 1.3 0.598098 0.598098 0.299049 -0.598098 -5 1.4 0.583215 0.583215 0.291607 -0.583215 -4.9 1.4 0.594877 0.594877 0.297439 -0.594877 -4.8 1.4 0.606531 0.606531 0.303265 -0.606531 -4.7 1.4 0.618165 0.618165 0.309082 -0.618165 -4.6 1.4 0.62977 0.62977 0.314885 -0.62977 -4.5 1.4 0.641337 0.641337 0.320669 -0.641337 -4.4 1.4 0.652855 0.652855 0.326428 -0.652855 -4.3 1.4 0.664314 0.664314 0.332157 -0.664314 -4.2 1.4 0.675704 0.675704 0.337852 -0.675704 -4.1 1.4 0.687014 0.687014 0.343507 -0.687014 -4 1.4 0.698235 0.698235 0.349117 -0.698235 -3.9 1.4 0.709354 0.709354 0.354677 -0.709354 -3.8 1.4 0.720363 0.720363 0.360182 -0.720363 -3.7 1.4 0.73125 0.73125 0.365625 -0.73125 -3.6 1.4 0.742004 0.742004 0.371002 -0.742004 -3.5 1.4 0.752616 0.752616 0.376308 -0.752616 -3.4 1.4 0.763074 0.763074 0.381537 -0.763074 -3.3 1.4 0.773368 0.773368 0.386684 -0.773368 -3.2 1.4 0.783488 0.783488 0.391744 -0.783488 -3.1 1.4 0.793422 0.793422 0.396711 -0.793422 -3 1.4 0.803161 0.803161 0.401581 -0.803161 -2.9 1.4 0.812695 0.812695 0.406347 -0.812695 -2.8 1.4 0.822012 0.822012 0.411006 -0.822012 -2.7 1.4 0.831104 0.831104 0.415552 -0.831104 -2.6 1.4 0.839961 0.839961 0.41998 -0.839961 -2.5 1.4 0.848572 0.848572 0.424286 -0.848572 -2.4 1.4 0.856929 0.856929 0.428465 -0.856929 -2.3 1.4 0.865022 0.865022 0.432511 -0.865022 -2.2 1.4 0.872843 0.872843 0.436421 -0.872843 -2.1 1.4 0.880381 0.880381 0.440191 -0.880381 -2 1.4 0.88763 0.88763 0.443815 -0.88763 -1.9 1.4 0.894581 0.894581 0.44729 -0.894581 -1.8 1.4 0.901225 0.901225 0.450613 -0.901225 -1.7 1.4 0.907556 0.907556 0.453778 -0.907556 -1.6 1.4 0.913566 0.913566 0.456783 -0.913566 -1.5 1.4 0.919247 0.919247 0.459624 -0.919247 -1.4 1.4 0.924595 0.924595 0.462297 -0.924595 -1.3 1.4 0.929601 0.929601 0.4648 -0.929601 -1.2 1.4 0.93426 0.93426 0.46713 -0.93426 -1.1 1.4 0.938568 0.938568 0.469284 -0.938568 -1 1.4 0.942518 0.942518 0.471259 -0.942518 -0.9 1.4 0.946107 0.946107 0.473053 -0.946107 -0.8 1.4 0.949329 0.949329 0.474664 -0.949329 -0.7 1.4 0.952181 0.952181 0.476091 -0.952181 -0.6 1.4 0.95466 0.95466 0.47733 -0.95466 -0.5 1.4 0.956763 0.956763 0.478381 -0.956763 -0.4 1.4 0.958486 0.958486 0.479243 -0.958486 -0.3 1.4 0.959829 0.959829 0.479915 -0.959829 -0.2 1.4 0.960789 0.960789 0.480395 -0.960789 -0.1 1.4 0.961366 0.961366 0.480683 -0.961366 0 1.4 0.961558 0.961558 0.480779 -0.961558 0.1 1.4 0.961366 0.961366 0.480683 -0.961366 0.2 1.4 0.960789 0.960789 0.480395 -0.960789 0.3 1.4 0.959829 0.959829 0.479915 -0.959829 0.4 1.4 0.958486 0.958486 0.479243 -0.958486 0.5 1.4 0.956763 0.956763 0.478381 -0.956763 0.6 1.4 0.95466 0.95466 0.47733 -0.95466 0.7 1.4 0.952181 0.952181 0.476091 -0.952181 0.8 1.4 0.949329 0.949329 0.474664 -0.949329 0.9 1.4 0.946107 0.946107 0.473053 -0.946107 1 1.4 0.942518 0.942518 0.471259 -0.942518 1.1 1.4 0.938568 0.938568 0.469284 -0.938568 1.2 1.4 0.93426 0.93426 0.46713 -0.93426 1.3 1.4 0.929601 0.929601 0.4648 -0.929601 1.4 1.4 0.924595 0.924595 0.462297 -0.924595 1.5 1.4 0.919247 0.919247 0.459624 -0.919247 1.6 1.4 0.913566 0.913566 0.456783 -0.913566 1.7 1.4 0.907556 0.907556 0.453778 -0.907556 1.8 1.4 0.901225 0.901225 0.450613 -0.901225 1.9 1.4 0.894581 0.894581 0.44729 -0.894581 2 1.4 0.88763 0.88763 0.443815 -0.88763 2.1 1.4 0.880381 0.880381 0.440191 -0.880381 2.2 1.4 0.872843 0.872843 0.436421 -0.872843 2.3 1.4 0.865022 0.865022 0.432511 -0.865022 2.4 1.4 0.856929 0.856929 0.428465 -0.856929 2.5 1.4 0.848572 0.848572 0.424286 -0.848572 2.6 1.4 0.839961 0.839961 0.41998 -0.839961 2.7 1.4 0.831104 0.831104 0.415552 -0.831104 2.8 1.4 0.822012 0.822012 0.411006 -0.822012 2.9 1.4 0.812695 0.812695 0.406347 -0.812695 3 1.4 0.803161 0.803161 0.401581 -0.803161 3.1 1.4 0.793422 0.793422 0.396711 -0.793422 3.2 1.4 0.783488 0.783488 0.391744 -0.783488 3.3 1.4 0.773368 0.773368 0.386684 -0.773368 3.4 1.4 0.763074 0.763074 0.381537 -0.763074 3.5 1.4 0.752616 0.752616 0.376308 -0.752616 3.6 1.4 0.742004 0.742004 0.371002 -0.742004 3.7 1.4 0.73125 0.73125 0.365625 -0.73125 3.8 1.4 0.720363 0.720363 0.360182 -0.720363 3.9 1.4 0.709354 0.709354 0.354677 -0.709354 4 1.4 0.698235 0.698235 0.349117 -0.698235 4.1 1.4 0.687014 0.687014 0.343507 -0.687014 4.2 1.4 0.675704 0.675704 0.337852 -0.675704 4.3 1.4 0.664314 0.664314 0.332157 -0.664314 4.4 1.4 0.652855 0.652855 0.326428 -0.652855 4.5 1.4 0.641337 0.641337 0.320669 -0.641337 4.6 1.4 0.62977 0.62977 0.314885 -0.62977 4.7 1.4 0.618165 0.618165 0.309082 -0.618165 4.8 1.4 0.606531 0.606531 0.303265 -0.606531 4.9 1.4 0.594877 0.594877 0.297439 -0.594877 -5 1.5 0.579842 0.579842 0.289921 -0.579842 -4.9 1.5 0.591437 0.591437 0.295719 -0.591437 -4.8 1.5 0.603023 0.603023 0.301511 -0.603023 -4.7 1.5 0.61459 0.61459 0.307295 -0.61459 -4.6 1.5 0.626128 0.626128 0.313064 -0.626128 -4.5 1.5 0.637628 0.637628 0.318814 -0.637628 -4.4 1.5 0.64908 0.64908 0.32454 -0.64908 -4.3 1.5 0.660472 0.660472 0.330236 -0.660472 -4.2 1.5 0.671796 0.671796 0.335898 -0.671796 -4.1 1.5 0.683041 0.683041 0.341521 -0.683041 -4 1.5 0.694197 0.694197 0.347098 -0.694197 -3.9 1.5 0.705252 0.705252 0.352626 -0.705252 -3.8 1.5 0.716197 0.716197 0.358099 -0.716197 -3.7 1.5 0.727021 0.727021 0.36351 -0.727021 -3.6 1.5 0.737713 0.737713 0.368857 -0.737713 -3.5 1.5 0.748264 0.748264 0.374132 -0.748264 -3.4 1.5 0.758661 0.758661 0.379331 -0.758661 -3.3 1.5 0.768896 0.768896 0.384448 -0.768896 -3.2 1.5 0.778957 0.778957 0.389478 -0.778957 -3.1 1.5 0.788834 0.788834 0.394417 -0.788834 -3 1.5 0.798516 0.798516 0.399258 -0.798516 -2.9 1.5 0.807995 0.807995 0.403997 -0.807995 -2.8 1.5 0.817258 0.817258 0.408629 -0.817258 -2.7 1.5 0.826298 0.826298 0.413149 -0.826298 -2.6 1.5 0.835103 0.835103 0.417552 -0.835103 -2.5 1.5 0.843665 0.843665 0.421832 -0.843665 -2.4 1.5 0.851973 0.851973 0.425987 -0.851973 -2.3 1.5 0.86002 0.86002 0.43001 -0.86002 -2.2 1.5 0.867795 0.867795 0.433897 -0.867795 -2.1 1.5 0.87529 0.87529 0.437645 -0.87529 -2 1.5 0.882497 0.882497 0.441248 -0.882497 -1.9 1.5 0.889407 0.889407 0.444704 -0.889407 -1.8 1.5 0.896013 0.896013 0.448007 -0.896013 -1.7 1.5 0.902307 0.902307 0.451154 -0.902307 -1.6 1.5 0.908282 0.908282 0.454141 -0.908282 -1.5 1.5 0.913931 0.913931 0.456966 -0.913931 -1.4 1.5 0.919247 0.919247 0.459624 -0.919247 -1.3 1.5 0.924225 0.924225 0.462112 -0.924225 -1.2 1.5 0.928857 0.928857 0.464429 -0.928857 -1.1 1.5 0.93314 0.93314 0.46657 -0.93314 -1 1.5 0.937067 0.937067 0.468534 -0.937067 -0.9 1.5 0.940635 0.940635 0.470318 -0.940635 -0.8 1.5 0.943839 0.943839 0.471919 -0.943839 -0.7 1.5 0.946674 0.946674 0.473337 -0.946674 -0.6 1.5 0.949139 0.949139 0.47457 -0.949139 -0.5 1.5 0.951229 0.951229 0.475615 -0.951229 -0.4 1.5 0.952943 0.952943 0.476472 -0.952943 -0.3 1.5 0.954278 0.954278 0.477139 -0.954278 -0.2 1.5 0.955233 0.955233 0.477616 -0.955233 -0.1 1.5 0.955806 0.955806 0.477903 -0.955806 0 1.5 0.955997 0.955997 0.477999 -0.955997 0.1 1.5 0.955806 0.955806 0.477903 -0.955806 0.2 1.5 0.955233 0.955233 0.477616 -0.955233 0.3 1.5 0.954278 0.954278 0.477139 -0.954278 0.4 1.5 0.952943 0.952943 0.476472 -0.952943 0.5 1.5 0.951229 0.951229 0.475615 -0.951229 0.6 1.5 0.949139 0.949139 0.47457 -0.949139 0.7 1.5 0.946674 0.946674 0.473337 -0.946674 0.8 1.5 0.943839 0.943839 0.471919 -0.943839 0.9 1.5 0.940635 0.940635 0.470318 -0.940635 1 1.5 0.937067 0.937067 0.468534 -0.937067 1.1 1.5 0.93314 0.93314 0.46657 -0.93314 1.2 1.5 0.928857 0.928857 0.464429 -0.928857 1.3 1.5 0.924225 0.924225 0.462112 -0.924225 1.4 1.5 0.919247 0.919247 0.459624 -0.919247 1.5 1.5 0.913931 0.913931 0.456966 -0.913931 1.6 1.5 0.908282 0.908282 0.454141 -0.908282 1.7 1.5 0.902307 0.902307 0.451154 -0.902307 1.8 1.5 0.896013 0.896013 0.448007 -0.896013 1.9 1.5 0.889407 0.889407 0.444704 -0.889407 2 1.5 0.882497 0.882497 0.441248 -0.882497 2.1 1.5 0.87529 0.87529 0.437645 -0.87529 2.2 1.5 0.867795 0.867795 0.433897 -0.867795 2.3 1.5 0.86002 0.86002 0.43001 -0.86002 2.4 1.5 0.851973 0.851973 0.425987 -0.851973 2.5 1.5 0.843665 0.843665 0.421832 -0.843665 2.6 1.5 0.835103 0.835103 0.417552 -0.835103 2.7 1.5 0.826298 0.826298 0.413149 -0.826298 2.8 1.5 0.817258 0.817258 0.408629 -0.817258 2.9 1.5 0.807995 0.807995 0.403997 -0.807995 3 1.5 0.798516 0.798516 0.399258 -0.798516 3.1 1.5 0.788834 0.788834 0.394417 -0.788834 3.2 1.5 0.778957 0.778957 0.389478 -0.778957 3.3 1.5 0.768896 0.768896 0.384448 -0.768896 3.4 1.5 0.758661 0.758661 0.379331 -0.758661 3.5 1.5 0.748264 0.748264 0.374132 -0.748264 3.6 1.5 0.737713 0.737713 0.368857 -0.737713 3.7 1.5 0.727021 0.727021 0.36351 -0.727021 3.8 1.5 0.716197 0.716197 0.358099 -0.716197 3.9 1.5 0.705252 0.705252 0.352626 -0.705252 4 1.5 0.694197 0.694197 0.347098 -0.694197 4.1 1.5 0.683041 0.683041 0.341521 -0.683041 4.2 1.5 0.671796 0.671796 0.335898 -0.671796 4.3 1.5 0.660472 0.660472 0.330236 -0.660472 4.4 1.5 0.64908 0.64908 0.32454 -0.64908 4.5 1.5 0.637628 0.637628 0.318814 -0.637628 4.6 1.5 0.626128 0.626128 0.313064 -0.626128 4.7 1.5 0.61459 0.61459 0.307295 -0.61459 4.8 1.5 0.603023 0.603023 0.301511 -0.603023 4.9 1.5 0.591437 0.591437 0.295719 -0.591437 -5 1.6 0.576258 0.576258 0.288129 -0.576258 -4.9 1.6 0.587781 0.587781 0.293891 -0.587781 -4.8 1.6 0.599296 0.599296 0.299648 -0.599296 -4.7 1.6 0.610791 0.610791 0.305396 -0.610791 -4.6 1.6 0.622258 0.622258 0.311129 -0.622258 -4.5 1.6 0.633687 0.633687 0.316844 -0.633687 -4.4 1.6 0.645068 0.645068 0.322534 -0.645068 -4.3 1.6 0.65639 0.65639 0.328195 -0.65639 -4.2 1.6 0.667644 0.667644 0.333822 -0.667644 -4.1 1.6 0.67882 0.67882 0.33941 -0.67882 -4 1.6 0.689906 0.689906 0.344953 -0.689906 -3.9 1.6 0.700893 0.700893 0.350447 -0.700893 -3.8 1.6 0.71177 0.71177 0.355885 -0.71177 -3.7 1.6 0.722527 0.722527 0.361264 -0.722527 -3.6 1.6 0.733154 0.733154 0.366577 -0.733154 -3.5 1.6 0.743639 0.743639 0.371819 -0.743639 -3.4 1.6 0.753972 0.753972 0.376986 -0.753972 -3.3 1.6 0.764143 0.764143 0.382072 -0.764143 -3.2 1.6 0.774142 0.774142 0.387071 -0.774142 -3.1 1.6 0.783958 0.783958 0.391979 -0.783958 -3 1.6 0.793581 0.793581 0.39679 -0.793581 -2.9 1.6 0.803 0.803 0.4015 -0.803 -2.8 1.6 0.812207 0.812207 0.406104 -0.812207 -2.7 1.6 0.821191 0.821191 0.410595 -0.821191 -2.6 1.6 0.829942 0.829942 0.414971 -0.829942 -2.5 1.6 0.83845 0.83845 0.419225 -0.83845 -2.4 1.6 0.846707 0.846707 0.423354 -0.846707 -2.3 1.6 0.854704 0.854704 0.427352 -0.854704 -2.2 1.6 0.862431 0.862431 0.431216 -0.862431 -2.1 1.6 0.86988 0.86988 0.43494 -0.86988 -2 1.6 0.877042 0.877042 0.438521 -0.877042 -1.9 1.6 0.88391 0.88391 0.441955 -0.88391 -1.8 1.6 0.890475 0.890475 0.445238 -0.890475 -1.7 1.6 0.89673 0.89673 0.448365 -0.89673 -1.6 1.6 0.902668 0.902668 0.451334 -0.902668 -1.5 1.6 0.908282 0.908282 0.454141 -0.908282 -1.4 1.6 0.913566 0.913566 0.456783 -0.913566 -1.3 1.6 0.918512 0.918512 0.459256 -0.918512 -1.2 1.6 0.923116 0.923116 0.461558 -0.923116 -1.1 1.6 0.927372 0.927372 0.463686 -0.927372 -1 1.6 0.931276 0.931276 0.465638 -0.931276 -0.9 1.6 0.934821 0.934821 0.467411 -0.934821 -0.8 1.6 0.938005 0.938005 0.469002 -0.938005 -0.7 1.6 0.940823 0.940823 0.470412 -0.940823 -0.6 1.6 0.943273 0.943273 0.471636 -0.943273 -0.5 1.6 0.94535 0.94535 0.472675 -0.94535 -0.4 1.6 0.947053 0.947053 0.473527 -0.947053 -0.3 1.6 0.94838 0.94838 0.47419 -0.94838 -0.2 1.6 0.949329 0.949329 0.474664 -0.949329 -0.1 1.6 0.949899 0.949899 0.474949 -0.949899 0 1.6 0.950089 0.950089 0.475044 -0.950089 0.1 1.6 0.949899 0.949899 0.474949 -0.949899 0.2 1.6 0.949329 0.949329 0.474664 -0.949329 0.3 1.6 0.94838 0.94838 0.47419 -0.94838 0.4 1.6 0.947053 0.947053 0.473527 -0.947053 0.5 1.6 0.94535 0.94535 0.472675 -0.94535 0.6 1.6 0.943273 0.943273 0.471636 -0.943273 0.7 1.6 0.940823 0.940823 0.470412 -0.940823 0.8 1.6 0.938005 0.938005 0.469002 -0.938005 0.9 1.6 0.934821 0.934821 0.467411 -0.934821 1 1.6 0.931276 0.931276 0.465638 -0.931276 1.1 1.6 0.927372 0.927372 0.463686 -0.927372 1.2 1.6 0.923116 0.923116 0.461558 -0.923116 1.3 1.6 0.918512 0.918512 0.459256 -0.918512 1.4 1.6 0.913566 0.913566 0.456783 -0.913566 1.5 1.6 0.908282 0.908282 0.454141 -0.908282 1.6 1.6 0.902668 0.902668 0.451334 -0.902668 1.7 1.6 0.89673 0.89673 0.448365 -0.89673 1.8 1.6 0.890475 0.890475 0.445238 -0.890475 1.9 1.6 0.88391 0.88391 0.441955 -0.88391 2 1.6 0.877042 0.877042 0.438521 -0.877042 2.1 1.6 0.86988 0.86988 0.43494 -0.86988 2.2 1.6 0.862431 0.862431 0.431216 -0.862431 2.3 1.6 0.854704 0.854704 0.427352 -0.854704 2.4 1.6 0.846707 0.846707 0.423354 -0.846707 2.5 1.6 0.83845 0.83845 0.419225 -0.83845 2.6 1.6 0.829942 0.829942 0.414971 -0.829942 2.7 1.6 0.821191 0.821191 0.410595 -0.821191 2.8 1.6 0.812207 0.812207 0.406104 -0.812207 2.9 1.6 0.803 0.803 0.4015 -0.803 3 1.6 0.793581 0.793581 0.39679 -0.793581 3.1 1.6 0.783958 0.783958 0.391979 -0.783958 3.2 1.6 0.774142 0.774142 0.387071 -0.774142 3.3 1.6 0.764143 0.764143 0.382072 -0.764143 3.4 1.6 0.753972 0.753972 0.376986 -0.753972 3.5 1.6 0.743639 0.743639 0.371819 -0.743639 3.6 1.6 0.733154 0.733154 0.366577 -0.733154 3.7 1.6 0.722527 0.722527 0.361264 -0.722527 3.8 1.6 0.71177 0.71177 0.355885 -0.71177 3.9 1.6 0.700893 0.700893 0.350447 -0.700893 4 1.6 0.689906 0.689906 0.344953 -0.689906 4.1 1.6 0.67882 0.67882 0.33941 -0.67882 4.2 1.6 0.667644 0.667644 0.333822 -0.667644 4.3 1.6 0.65639 0.65639 0.328195 -0.65639 4.4 1.6 0.645068 0.645068 0.322534 -0.645068 4.5 1.6 0.633687 0.633687 0.316844 -0.633687 4.6 1.6 0.622258 0.622258 0.311129 -0.622258 4.7 1.6 0.610791 0.610791 0.305396 -0.610791 4.8 1.6 0.599296 0.599296 0.299648 -0.599296 4.9 1.6 0.587781 0.587781 0.293891 -0.587781 -5 1.7 0.572467 0.572467 0.286234 -0.572467 -4.9 1.7 0.583915 0.583915 0.291957 -0.583915 -4.8 1.7 0.595353 0.595353 0.297677 -0.595353 -4.7 1.7 0.606773 0.606773 0.303387 -0.606773 -4.6 1.7 0.618165 0.618165 0.309082 -0.618165 -4.5 1.7 0.629519 0.629519 0.314759 -0.629519 -4.4 1.7 0.640824 0.640824 0.320412 -0.640824 -4.3 1.7 0.652072 0.652072 0.326036 -0.652072 -4.2 1.7 0.663252 0.663252 0.331626 -0.663252 -4.1 1.7 0.674354 0.674354 0.337177 -0.674354 -4 1.7 0.685368 0.685368 0.342684 -0.685368 -3.9 1.7 0.696282 0.696282 0.348141 -0.696282 -3.8 1.7 0.707088 0.707088 0.353544 -0.707088 -3.7 1.7 0.717774 0.717774 0.358887 -0.717774 -3.6 1.7 0.728331 0.728331 0.364165 -0.728331 -3.5 1.7 0.738747 0.738747 0.369373 -0.738747 -3.4 1.7 0.749012 0.749012 0.374506 -0.749012 -3.3 1.7 0.759117 0.759117 0.379558 -0.759117 -3.2 1.7 0.769049 0.769049 0.384525 -0.769049 -3.1 1.7 0.778801 0.778801 0.3894 -0.778801 -3 1.7 0.78836 0.78836 0.39418 -0.78836 -2.9 1.7 0.797718 0.797718 0.398859 -0.797718 -2.8 1.7 0.806864 0.806864 0.403432 -0.806864 -2.7 1.7 0.815789 0.815789 0.407894 -0.815789 -2.6 1.7 0.824482 0.824482 0.412241 -0.824482 -2.5 1.7 0.832935 0.832935 0.416467 -0.832935 -2.4 1.7 0.841138 0.841138 0.420569 -0.841138 -2.3 1.7 0.849082 0.849082 0.424541 -0.849082 -2.2 1.7 0.856758 0.856758 0.428379 -0.856758 -2.1 1.7 0.864158 0.864158 0.432079 -0.864158 -2 1.7 0.871273 0.871273 0.435636 -0.871273 -1.9 1.7 0.878095 0.878095 0.439048 -0.878095 -1.8 1.7 0.884617 0.884617 0.442309 -0.884617 -1.7 1.7 0.890831 0.890831 0.445416 -0.890831 -1.6 1.7 0.89673 0.89673 0.448365 -0.89673 -1.5 1.7 0.902307 0.902307 0.451154 -0.902307 -1.4 1.7 0.907556 0.907556 0.453778 -0.907556 -1.3 1.7 0.91247 0.91247 0.456235 -0.91247 -1.2 1.7 0.917044 0.917044 0.458522 -0.917044 -1.1 1.7 0.921272 0.921272 0.460636 -0.921272 -1 1.7 0.925149 0.925149 0.462575 -0.925149 -0.9 1.7 0.928672 0.928672 0.464336 -0.928672 -0.8 1.7 0.931835 0.931835 0.465917 -0.931835 -0.7 1.7 0.934634 0.934634 0.467317 -0.934634 -0.6 1.7 0.937067 0.937067 0.468534 -0.937067 -0.5 1.7 0.939131 0.939131 0.469566 -0.939131 -0.4 1.7 0.940823 0.940823 0.470412 -0.940823 -0.3 1.7 0.942141 0.942141 0.471071 -0.942141 -0.2 1.7 0.943084 0.943084 0.471542 -0.943084 -0.1 1.7 0.94365 0.94365 0.471825 -0.94365 0 1.7 0.943839 0.943839 0.471919 -0.943839 0.1 1.7 0.94365 0.94365 0.471825 -0.94365 0.2 1.7 0.943084 0.943084 0.471542 -0.943084 0.3 1.7 0.942141 0.942141 0.471071 -0.942141 0.4 1.7 0.940823 0.940823 0.470412 -0.940823 0.5 1.7 0.939131 0.939131 0.469566 -0.939131 0.6 1.7 0.937067 0.937067 0.468534 -0.937067 0.7 1.7 0.934634 0.934634 0.467317 -0.934634 0.8 1.7 0.931835 0.931835 0.465917 -0.931835 0.9 1.7 0.928672 0.928672 0.464336 -0.928672 1 1.7 0.925149 0.925149 0.462575 -0.925149 1.1 1.7 0.921272 0.921272 0.460636 -0.921272 1.2 1.7 0.917044 0.917044 0.458522 -0.917044 1.3 1.7 0.91247 0.91247 0.456235 -0.91247 1.4 1.7 0.907556 0.907556 0.453778 -0.907556 1.5 1.7 0.902307 0.902307 0.451154 -0.902307 1.6 1.7 0.89673 0.89673 0.448365 -0.89673 1.7 1.7 0.890831 0.890831 0.445416 -0.890831 1.8 1.7 0.884617 0.884617 0.442309 -0.884617 1.9 1.7 0.878095 0.878095 0.439048 -0.878095 2 1.7 0.871273 0.871273 0.435636 -0.871273 2.1 1.7 0.864158 0.864158 0.432079 -0.864158 2.2 1.7 0.856758 0.856758 0.428379 -0.856758 2.3 1.7 0.849082 0.849082 0.424541 -0.849082 2.4 1.7 0.841138 0.841138 0.420569 -0.841138 2.5 1.7 0.832935 0.832935 0.416467 -0.832935 2.6 1.7 0.824482 0.824482 0.412241 -0.824482 2.7 1.7 0.815789 0.815789 0.407894 -0.815789 2.8 1.7 0.806864 0.806864 0.403432 -0.806864 2.9 1.7 0.797718 0.797718 0.398859 -0.797718 3 1.7 0.78836 0.78836 0.39418 -0.78836 3.1 1.7 0.778801 0.778801 0.3894 -0.778801 3.2 1.7 0.769049 0.769049 0.384525 -0.769049 3.3 1.7 0.759117 0.759117 0.379558 -0.759117 3.4 1.7 0.749012 0.749012 0.374506 -0.749012 3.5 1.7 0.738747 0.738747 0.369373 -0.738747 3.6 1.7 0.728331 0.728331 0.364165 -0.728331 3.7 1.7 0.717774 0.717774 0.358887 -0.717774 3.8 1.7 0.707088 0.707088 0.353544 -0.707088 3.9 1.7 0.696282 0.696282 0.348141 -0.696282 4 1.7 0.685368 0.685368 0.342684 -0.685368 4.1 1.7 0.674354 0.674354 0.337177 -0.674354 4.2 1.7 0.663252 0.663252 0.331626 -0.663252 4.3 1.7 0.652072 0.652072 0.326036 -0.652072 4.4 1.7 0.640824 0.640824 0.320412 -0.640824 4.5 1.7 0.629519 0.629519 0.314759 -0.629519 4.6 1.7 0.618165 0.618165 0.309082 -0.618165 4.7 1.7 0.606773 0.606773 0.303387 -0.606773 4.8 1.7 0.595353 0.595353 0.297677 -0.595353 4.9 1.7 0.583915 0.583915 0.291957 -0.583915 -5 1.8 0.568474 0.568474 0.284237 -0.568474 -4.9 1.8 0.579842 0.579842 0.289921 -0.579842 -4.8 1.8 0.591201 0.591201 0.2956 -0.591201 -4.7 1.8 0.602541 0.602541 0.30127 -0.602541 -4.6 1.8 0.613853 0.613853 0.306926 -0.613853 -4.5 1.8 0.625127 0.625127 0.312564 -0.625127 -4.4 1.8 0.636354 0.636354 0.318177 -0.636354 -4.3 1.8 0.647524 0.647524 0.323762 -0.647524 -4.2 1.8 0.658626 0.658626 0.329313 -0.658626 -4.1 1.8 0.66965 0.66965 0.334825 -0.66965 -4 1.8 0.680587 0.680587 0.340293 -0.680587 -3.9 1.8 0.691425 0.691425 0.345713 -0.691425 -3.8 1.8 0.702156 0.702156 0.351078 -0.702156 -3.7 1.8 0.712767 0.712767 0.356384 -0.712767 -3.6 1.8 0.72325 0.72325 0.361625 -0.72325 -3.5 1.8 0.733594 0.733594 0.366797 -0.733594 -3.4 1.8 0.743787 0.743787 0.371894 -0.743787 -3.3 1.8 0.753821 0.753821 0.376911 -0.753821 -3.2 1.8 0.763685 0.763685 0.381842 -0.763685 -3.1 1.8 0.773368 0.773368 0.386684 -0.773368 -3 1.8 0.782861 0.782861 0.391431 -0.782861 -2.9 1.8 0.792154 0.792154 0.396077 -0.792154 -2.8 1.8 0.801236 0.801236 0.400618 -0.801236 -2.7 1.8 0.810098 0.810098 0.405049 -0.810098 -2.6 1.8 0.818731 0.818731 0.409365 -0.818731 -2.5 1.8 0.827125 0.827125 0.413562 -0.827125 -2.4 1.8 0.83527 0.83527 0.417635 -0.83527 -2.3 1.8 0.843159 0.843159 0.421579 -0.843159 -2.2 1.8 0.850781 0.850781 0.425391 -0.850781 -2.1 1.8 0.85813 0.85813 0.429065 -0.85813 -2 1.8 0.865195 0.865195 0.432598 -0.865195 -1.9 1.8 0.87197 0.87197 0.435985 -0.87197 -1.8 1.8 0.878447 0.878447 0.439223 -0.878447 -1.7 1.8 0.884617 0.884617 0.442309 -0.884617 -1.6 1.8 0.890475 0.890475 0.445238 -0.890475 -1.5 1.8 0.896013 0.896013 0.448007 -0.896013 -1.4 1.8 0.901225 0.901225 0.450613 -0.901225 -1.3 1.8 0.906105 0.906105 0.453053 -0.906105 -1.2 1.8 0.910647 0.910647 0.455323 -0.910647 -1.1 1.8 0.914846 0.914846 0.457423 -0.914846 -1 1.8 0.918696 0.918696 0.459348 -0.918696 -0.9 1.8 0.922194 0.922194 0.461097 -0.922194 -0.8 1.8 0.925334 0.925334 0.462667 -0.925334 -0.7 1.8 0.928115 0.928115 0.464057 -0.928115 -0.6 1.8 0.930531 0.930531 0.465265 -0.930531 -0.5 1.8 0.93258 0.93258 0.46629 -0.93258 -0.4 1.8 0.93426 0.93426 0.46713 -0.93426 -0.3 1.8 0.935569 0.935569 0.467785 -0.935569 -0.2 1.8 0.936505 0.936505 0.468253 -0.936505 -0.1 1.8 0.937067 0.937067 0.468534 -0.937067 0 1.8 0.937255 0.937255 0.468627 -0.937255 0.1 1.8 0.937067 0.937067 0.468534 -0.937067 0.2 1.8 0.936505 0.936505 0.468253 -0.936505 0.3 1.8 0.935569 0.935569 0.467785 -0.935569 0.4 1.8 0.93426 0.93426 0.46713 -0.93426 0.5 1.8 0.93258 0.93258 0.46629 -0.93258 0.6 1.8 0.930531 0.930531 0.465265 -0.930531 0.7 1.8 0.928115 0.928115 0.464057 -0.928115 0.8 1.8 0.925334 0.925334 0.462667 -0.925334 0.9 1.8 0.922194 0.922194 0.461097 -0.922194 1 1.8 0.918696 0.918696 0.459348 -0.918696 1.1 1.8 0.914846 0.914846 0.457423 -0.914846 1.2 1.8 0.910647 0.910647 0.455323 -0.910647 1.3 1.8 0.906105 0.906105 0.453053 -0.906105 1.4 1.8 0.901225 0.901225 0.450613 -0.901225 1.5 1.8 0.896013 0.896013 0.448007 -0.896013 1.6 1.8 0.890475 0.890475 0.445238 -0.890475 1.7 1.8 0.884617 0.884617 0.442309 -0.884617 1.8 1.8 0.878447 0.878447 0.439223 -0.878447 1.9 1.8 0.87197 0.87197 0.435985 -0.87197 2 1.8 0.865195 0.865195 0.432598 -0.865195 2.1 1.8 0.85813 0.85813 0.429065 -0.85813 2.2 1.8 0.850781 0.850781 0.425391 -0.850781 2.3 1.8 0.843159 0.843159 0.421579 -0.843159 2.4 1.8 0.83527 0.83527 0.417635 -0.83527 2.5 1.8 0.827125 0.827125 0.413562 -0.827125 2.6 1.8 0.818731 0.818731 0.409365 -0.818731 2.7 1.8 0.810098 0.810098 0.405049 -0.810098 2.8 1.8 0.801236 0.801236 0.400618 -0.801236 2.9 1.8 0.792154 0.792154 0.396077 -0.792154 3 1.8 0.782861 0.782861 0.391431 -0.782861 3.1 1.8 0.773368 0.773368 0.386684 -0.773368 3.2 1.8 0.763685 0.763685 0.381842 -0.763685 3.3 1.8 0.753821 0.753821 0.376911 -0.753821 3.4 1.8 0.743787 0.743787 0.371894 -0.743787 3.5 1.8 0.733594 0.733594 0.366797 -0.733594 3.6 1.8 0.72325 0.72325 0.361625 -0.72325 3.7 1.8 0.712767 0.712767 0.356384 -0.712767 3.8 1.8 0.702156 0.702156 0.351078 -0.702156 3.9 1.8 0.691425 0.691425 0.345713 -0.691425 4 1.8 0.680587 0.680587 0.340293 -0.680587 4.1 1.8 0.66965 0.66965 0.334825 -0.66965 4.2 1.8 0.658626 0.658626 0.329313 -0.658626 4.3 1.8 0.647524 0.647524 0.323762 -0.647524 4.4 1.8 0.636354 0.636354 0.318177 -0.636354 4.5 1.8 0.625127 0.625127 0.312564 -0.625127 4.6 1.8 0.613853 0.613853 0.306926 -0.613853 4.7 1.8 0.602541 0.602541 0.30127 -0.602541 4.8 1.8 0.591201 0.591201 0.2956 -0.591201 4.9 1.8 0.579842 0.579842 0.289921 -0.579842 -5 1.9 0.564283 0.564283 0.282141 -0.564283 -4.9 1.9 0.575567 0.575567 0.287783 -0.575567 -4.8 1.9 0.586842 0.586842 0.293421 -0.586842 -4.7 1.9 0.598098 0.598098 0.299049 -0.598098 -4.6 1.9 0.609327 0.609327 0.304664 -0.609327 -4.5 1.9 0.620518 0.620518 0.310259 -0.620518 -4.4 1.9 0.631663 0.631663 0.315831 -0.631663 -4.3 1.9 0.64275 0.64275 0.321375 -0.64275 -4.2 1.9 0.65377 0.65377 0.326885 -0.65377 -4.1 1.9 0.664713 0.664713 0.332356 -0.664713 -4 1.9 0.675569 0.675569 0.337784 -0.675569 -3.9 1.9 0.686328 0.686328 0.343164 -0.686328 -3.8 1.9 0.696979 0.696979 0.348489 -0.696979 -3.7 1.9 0.707512 0.707512 0.353756 -0.707512 -3.6 1.9 0.717918 0.717918 0.358959 -0.717918 -3.5 1.9 0.728185 0.728185 0.364093 -0.728185 -3.4 1.9 0.738304 0.738304 0.369152 -0.738304 -3.3 1.9 0.748264 0.748264 0.374132 -0.748264 -3.2 1.9 0.758054 0.758054 0.379027 -0.758054 -3.1 1.9 0.767666 0.767666 0.383833 -0.767666 -3 1.9 0.777089 0.777089 0.388545 -0.777089 -2.9 1.9 0.786313 0.786313 0.393157 -0.786313 -2.8 1.9 0.795329 0.795329 0.397664 -0.795329 -2.7 1.9 0.804125 0.804125 0.402063 -0.804125 -2.6 1.9 0.812695 0.812695 0.406347 -0.812695 -2.5 1.9 0.821026 0.821026 0.410513 -0.821026 -2.4 1.9 0.829112 0.829112 0.414556 -0.829112 -2.3 1.9 0.836942 0.836942 0.418471 -0.836942 -2.2 1.9 0.844509 0.844509 0.422254 -0.844509 -2.1 1.9 0.851803 0.851803 0.425901 -0.851803 -2 1.9 0.858817 0.858817 0.429408 -0.858817 -1.9 1.9 0.865541 0.865541 0.432771 -0.865541 -1.8 1.9 0.87197 0.87197 0.435985 -0.87197 -1.7 1.9 0.878095 0.878095 0.439048 -0.878095 -1.6 1.9 0.88391 0.88391 0.441955 -0.88391 -1.5 1.9 0.889407 0.889407 0.444704 -0.889407 -1.4 1.9 0.894581 0.894581 0.44729 -0.894581 -1.3 1.9 0.899425 0.899425 0.449712 -0.899425 -1.2 1.9 0.903933 0.903933 0.451967 -0.903933 -1.1 1.9 0.908101 0.908101 0.45405 -0.908101 -1 1.9 0.911923 0.911923 0.455961 -0.911923 -0.9 1.9 0.915395 0.915395 0.457697 -0.915395 -0.8 1.9 0.918512 0.918512 0.459256 -0.918512 -0.7 1.9 0.921272 0.921272 0.460636 -0.921272 -0.6 1.9 0.92367 0.92367 0.461835 -0.92367 -0.5 1.9 0.925705 0.925705 0.462852 -0.925705 -0.4 1.9 0.927372 0.927372 0.463686 -0.927372 -0.3 1.9 0.928672 0.928672 0.464336 -0.928672 -0.2 1.9 0.929601 0.929601 0.4648 -0.929601 -0.1 1.9 0.930159 0.930159 0.465079 -0.930159 0 1.9 0.930345 0.930345 0.465172 -0.930345 0.1 1.9 0.930159 0.930159 0.465079 -0.930159 0.2 1.9 0.929601 0.929601 0.4648 -0.929601 0.3 1.9 0.928672 0.928672 0.464336 -0.928672 0.4 1.9 0.927372 0.927372 0.463686 -0.927372 0.5 1.9 0.925705 0.925705 0.462852 -0.925705 0.6 1.9 0.92367 0.92367 0.461835 -0.92367 0.7 1.9 0.921272 0.921272 0.460636 -0.921272 0.8 1.9 0.918512 0.918512 0.459256 -0.918512 0.9 1.9 0.915395 0.915395 0.457697 -0.915395 1 1.9 0.911923 0.911923 0.455961 -0.911923 1.1 1.9 0.908101 0.908101 0.45405 -0.908101 1.2 1.9 0.903933 0.903933 0.451967 -0.903933 1.3 1.9 0.899425 0.899425 0.449712 -0.899425 1.4 1.9 0.894581 0.894581 0.44729 -0.894581 1.5 1.9 0.889407 0.889407 0.444704 -0.889407 1.6 1.9 0.88391 0.88391 0.441955 -0.88391 1.7 1.9 0.878095 0.878095 0.439048 -0.878095 1.8 1.9 0.87197 0.87197 0.435985 -0.87197 1.9 1.9 0.865541 0.865541 0.432771 -0.865541 2 1.9 0.858817 0.858817 0.429408 -0.858817 2.1 1.9 0.851803 0.851803 0.425901 -0.851803 2.2 1.9 0.844509 0.844509 0.422254 -0.844509 2.3 1.9 0.836942 0.836942 0.418471 -0.836942 2.4 1.9 0.829112 0.829112 0.414556 -0.829112 2.5 1.9 0.821026 0.821026 0.410513 -0.821026 2.6 1.9 0.812695 0.812695 0.406347 -0.812695 2.7 1.9 0.804125 0.804125 0.402063 -0.804125 2.8 1.9 0.795329 0.795329 0.397664 -0.795329 2.9 1.9 0.786313 0.786313 0.393157 -0.786313 3 1.9 0.777089 0.777089 0.388545 -0.777089 3.1 1.9 0.767666 0.767666 0.383833 -0.767666 3.2 1.9 0.758054 0.758054 0.379027 -0.758054 3.3 1.9 0.748264 0.748264 0.374132 -0.748264 3.4 1.9 0.738304 0.738304 0.369152 -0.738304 3.5 1.9 0.728185 0.728185 0.364093 -0.728185 3.6 1.9 0.717918 0.717918 0.358959 -0.717918 3.7 1.9 0.707512 0.707512 0.353756 -0.707512 3.8 1.9 0.696979 0.696979 0.348489 -0.696979 3.9 1.9 0.686328 0.686328 0.343164 -0.686328 4 1.9 0.675569 0.675569 0.337784 -0.675569 4.1 1.9 0.664713 0.664713 0.332356 -0.664713 4.2 1.9 0.65377 0.65377 0.326885 -0.65377 4.3 1.9 0.64275 0.64275 0.321375 -0.64275 4.4 1.9 0.631663 0.631663 0.315831 -0.631663 4.5 1.9 0.620518 0.620518 0.310259 -0.620518 4.6 1.9 0.609327 0.609327 0.304664 -0.609327 4.7 1.9 0.598098 0.598098 0.299049 -0.598098 4.8 1.9 0.586842 0.586842 0.293421 -0.586842 4.9 1.9 0.575567 0.575567 0.287783 -0.575567 -5 2 0.559898 0.559898 0.279949 -0.559898 -4.9 2 0.571095 0.571095 0.285547 -0.571095 -4.8 2 0.582282 0.582282 0.291141 -0.582282 -4.7 2 0.593451 0.593451 0.296726 -0.593451 -4.6 2 0.604593 0.604593 0.302296 -0.604593 -4.5 2 0.615697 0.615697 0.307849 -0.615697 -4.4 2 0.626755 0.626755 0.313377 -0.626755 -4.3 2 0.637756 0.637756 0.318878 -0.637756 -4.2 2 0.64869 0.64869 0.324345 -0.64869 -4.1 2 0.659548 0.659548 0.329774 -0.659548 -4 2 0.67032 0.67032 0.33516 -0.67032 -3.9 2 0.680995 0.680995 0.340498 -0.680995 -3.8 2 0.691564 0.691564 0.345782 -0.691564 -3.7 2 0.702015 0.702015 0.351008 -0.702015 -3.6 2 0.71234 0.71234 0.35617 -0.71234 -3.5 2 0.722527 0.722527 0.361264 -0.722527 -3.4 2 0.732567 0.732567 0.366284 -0.732567 -3.3 2 0.74245 0.74245 0.371225 -0.74245 -3.2 2 0.752165 0.752165 0.376082 -0.752165 -3.1 2 0.761702 0.761702 0.380851 -0.761702 -3 2 0.771052 0.771052 0.385526 -0.771052 -2.9 2 0.780204 0.780204 0.390102 -0.780204 -2.8 2 0.789149 0.789149 0.394575 -0.789149 -2.7 2 0.797878 0.797878 0.398939 -0.797878 -2.6 2 0.80638 0.80638 0.40319 -0.80638 -2.5 2 0.814647 0.814647 0.407324 -0.814647 -2.4 2 0.82267 0.82267 0.411335 -0.82267 -2.3 2 0.83044 0.83044 0.41522 -0.83044 -2.2 2 0.837947 0.837947 0.418974 -0.837947 -2.1 2 0.845185 0.845185 0.422592 -0.845185 -2 2 0.852144 0.852144 0.426072 -0.852144 -1.9 2 0.858817 0.858817 0.429408 -0.858817 -1.8 2 0.865195 0.865195 0.432598 -0.865195 -1.7 2 0.871273 0.871273 0.435636 -0.871273 -1.6 2 0.877042 0.877042 0.438521 -0.877042 -1.5 2 0.882497 0.882497 0.441248 -0.882497 -1.4 2 0.88763 0.88763 0.443815 -0.88763 -1.3 2 0.892436 0.892436 0.446218 -0.892436 -1.2 2 0.89691 0.89691 0.448455 -0.89691 -1.1 2 0.901045 0.901045 0.450523 -0.901045 -1 2 0.904837 0.904837 0.452419 -0.904837 -0.9 2 0.908282 0.908282 0.454141 -0.908282 -0.8 2 0.911376 0.911376 0.455688 -0.911376 -0.7 2 0.914114 0.914114 0.457057 -0.914114 -0.6 2 0.916494 0.916494 0.458247 -0.916494 -0.5 2 0.918512 0.918512 0.459256 -0.918512 -0.4 2 0.920167 0.920167 0.460084 -0.920167 -0.3 2 0.921456 0.921456 0.460728 -0.921456 -0.2 2 0.922378 0.922378 0.461189 -0.922378 -0.1 2 0.922932 0.922932 0.461466 -0.922932 0 2 0.923116 0.923116 0.461558 -0.923116 0.1 2 0.922932 0.922932 0.461466 -0.922932 0.2 2 0.922378 0.922378 0.461189 -0.922378 0.3 2 0.921456 0.921456 0.460728 -0.921456 0.4 2 0.920167 0.920167 0.460084 -0.920167 0.5 2 0.918512 0.918512 0.459256 -0.918512 0.6 2 0.916494 0.916494 0.458247 -0.916494 0.7 2 0.914114 0.914114 0.457057 -0.914114 0.8 2 0.911376 0.911376 0.455688 -0.911376 0.9 2 0.908282 0.908282 0.454141 -0.908282 1 2 0.904837 0.904837 0.452419 -0.904837 1.1 2 0.901045 0.901045 0.450523 -0.901045 1.2 2 0.89691 0.89691 0.448455 -0.89691 1.3 2 0.892436 0.892436 0.446218 -0.892436 1.4 2 0.88763 0.88763 0.443815 -0.88763 1.5 2 0.882497 0.882497 0.441248 -0.882497 1.6 2 0.877042 0.877042 0.438521 -0.877042 1.7 2 0.871273 0.871273 0.435636 -0.871273 1.8 2 0.865195 0.865195 0.432598 -0.865195 1.9 2 0.858817 0.858817 0.429408 -0.858817 2 2 0.852144 0.852144 0.426072 -0.852144 2.1 2 0.845185 0.845185 0.422592 -0.845185 2.2 2 0.837947 0.837947 0.418974 -0.837947 2.3 2 0.83044 0.83044 0.41522 -0.83044 2.4 2 0.82267 0.82267 0.411335 -0.82267 2.5 2 0.814647 0.814647 0.407324 -0.814647 2.6 2 0.80638 0.80638 0.40319 -0.80638 2.7 2 0.797878 0.797878 0.398939 -0.797878 2.8 2 0.789149 0.789149 0.394575 -0.789149 2.9 2 0.780204 0.780204 0.390102 -0.780204 3 2 0.771052 0.771052 0.385526 -0.771052 3.1 2 0.761702 0.761702 0.380851 -0.761702 3.2 2 0.752165 0.752165 0.376082 -0.752165 3.3 2 0.74245 0.74245 0.371225 -0.74245 3.4 2 0.732567 0.732567 0.366284 -0.732567 3.5 2 0.722527 0.722527 0.361264 -0.722527 3.6 2 0.71234 0.71234 0.35617 -0.71234 3.7 2 0.702015 0.702015 0.351008 -0.702015 3.8 2 0.691564 0.691564 0.345782 -0.691564 3.9 2 0.680995 0.680995 0.340498 -0.680995 4 2 0.67032 0.67032 0.33516 -0.67032 4.1 2 0.659548 0.659548 0.329774 -0.659548 4.2 2 0.64869 0.64869 0.324345 -0.64869 4.3 2 0.637756 0.637756 0.318878 -0.637756 4.4 2 0.626755 0.626755 0.313377 -0.626755 4.5 2 0.615697 0.615697 0.307849 -0.615697 4.6 2 0.604593 0.604593 0.302296 -0.604593 4.7 2 0.593451 0.593451 0.296726 -0.593451 4.8 2 0.582282 0.582282 0.291141 -0.582282 4.9 2 0.571095 0.571095 0.285547 -0.571095 -5 2.1 0.555326 0.555326 0.277663 -0.555326 -4.9 2.1 0.566431 0.566431 0.283216 -0.566431 -4.8 2.1 0.577527 0.577527 0.288764 -0.577527 -4.7 2.1 0.588605 0.588605 0.294302 -0.588605 -4.6 2.1 0.599655 0.599655 0.299828 -0.599655 -4.5 2.1 0.610669 0.610669 0.305335 -0.610669 -4.4 2.1 0.621636 0.621636 0.310818 -0.621636 -4.3 2.1 0.632547 0.632547 0.316274 -0.632547 -4.2 2.1 0.643393 0.643393 0.321696 -0.643393 -4.1 2.1 0.654162 0.654162 0.327081 -0.654162 -4 2.1 0.664846 0.664846 0.332423 -0.664846 -3.9 2.1 0.675434 0.675434 0.337717 -0.675434 -3.8 2.1 0.685916 0.685916 0.342958 -0.685916 -3.7 2.1 0.696282 0.696282 0.348141 -0.696282 -3.6 2.1 0.706523 0.706523 0.353261 -0.706523 -3.5 2.1 0.716627 0.716627 0.358313 -0.716627 -3.4 2.1 0.726585 0.726585 0.363292 -0.726585 -3.3 2.1 0.736387 0.736387 0.368193 -0.736387 -3.2 2.1 0.746022 0.746022 0.373011 -0.746022 -3.1 2.1 0.755481 0.755481 0.377741 -0.755481 -3 2.1 0.764755 0.764755 0.382377 -0.764755 -2.9 2.1 0.773832 0.773832 0.386916 -0.773832 -2.8 2.1 0.782705 0.782705 0.391352 -0.782705 -2.7 2.1 0.791362 0.791362 0.395681 -0.791362 -2.6 2.1 0.799795 0.799795 0.399897 -0.799795 -2.5 2.1 0.807995 0.807995 0.403997 -0.807995 -2.4 2.1 0.815952 0.815952 0.407976 -0.815952 -2.3 2.1 0.823658 0.823658 0.411829 -0.823658 -2.2 2.1 0.831104 0.831104 0.415552 -0.831104 -2.1 2.1 0.838283 0.838283 0.419141 -0.838283 -2 2.1 0.845185 0.845185 0.422592 -0.845185 -1.9 2.1 0.851803 0.851803 0.425901 -0.851803 -1.8 2.1 0.85813 0.85813 0.429065 -0.85813 -1.7 2.1 0.864158 0.864158 0.432079 -0.864158 -1.6 2.1 0.86988 0.86988 0.43494 -0.86988 -1.5 2.1 0.87529 0.87529 0.437645 -0.87529 -1.4 2.1 0.880381 0.880381 0.440191 -0.880381 -1.3 2.1 0.885148 0.885148 0.442574 -0.885148 -1.2 2.1 0.889585 0.889585 0.444793 -0.889585 -1.1 2.1 0.893687 0.893687 0.446843 -0.893687 -1 2.1 0.897448 0.897448 0.448724 -0.897448 -0.9 2.1 0.900865 0.900865 0.450432 -0.900865 -0.8 2.1 0.903933 0.903933 0.451967 -0.903933 -0.7 2.1 0.906649 0.906649 0.453324 -0.906649 -0.6 2.1 0.909009 0.909009 0.454505 -0.909009 -0.5 2.1 0.911011 0.911011 0.455506 -0.911011 -0.4 2.1 0.912653 0.912653 0.456326 -0.912653 -0.3 2.1 0.913931 0.913931 0.456966 -0.913931 -0.2 2.1 0.914846 0.914846 0.457423 -0.914846 -0.1 2.1 0.915395 0.915395 0.457697 -0.915395 0 2.1 0.915578 0.915578 0.457789 -0.915578 0.1 2.1 0.915395 0.915395 0.457697 -0.915395 0.2 2.1 0.914846 0.914846 0.457423 -0.914846 0.3 2.1 0.913931 0.913931 0.456966 -0.913931 0.4 2.1 0.912653 0.912653 0.456326 -0.912653 0.5 2.1 0.911011 0.911011 0.455506 -0.911011 0.6 2.1 0.909009 0.909009 0.454505 -0.909009 0.7 2.1 0.906649 0.906649 0.453324 -0.906649 0.8 2.1 0.903933 0.903933 0.451967 -0.903933 0.9 2.1 0.900865 0.900865 0.450432 -0.900865 1 2.1 0.897448 0.897448 0.448724 -0.897448 1.1 2.1 0.893687 0.893687 0.446843 -0.893687 1.2 2.1 0.889585 0.889585 0.444793 -0.889585 1.3 2.1 0.885148 0.885148 0.442574 -0.885148 1.4 2.1 0.880381 0.880381 0.440191 -0.880381 1.5 2.1 0.87529 0.87529 0.437645 -0.87529 1.6 2.1 0.86988 0.86988 0.43494 -0.86988 1.7 2.1 0.864158 0.864158 0.432079 -0.864158 1.8 2.1 0.85813 0.85813 0.429065 -0.85813 1.9 2.1 0.851803 0.851803 0.425901 -0.851803 2 2.1 0.845185 0.845185 0.422592 -0.845185 2.1 2.1 0.838283 0.838283 0.419141 -0.838283 2.2 2.1 0.831104 0.831104 0.415552 -0.831104 2.3 2.1 0.823658 0.823658 0.411829 -0.823658 2.4 2.1 0.815952 0.815952 0.407976 -0.815952 2.5 2.1 0.807995 0.807995 0.403997 -0.807995 2.6 2.1 0.799795 0.799795 0.399897 -0.799795 2.7 2.1 0.791362 0.791362 0.395681 -0.791362 2.8 2.1 0.782705 0.782705 0.391352 -0.782705 2.9 2.1 0.773832 0.773832 0.386916 -0.773832 3 2.1 0.764755 0.764755 0.382377 -0.764755 3.1 2.1 0.755481 0.755481 0.377741 -0.755481 3.2 2.1 0.746022 0.746022 0.373011 -0.746022 3.3 2.1 0.736387 0.736387 0.368193 -0.736387 3.4 2.1 0.726585 0.726585 0.363292 -0.726585 3.5 2.1 0.716627 0.716627 0.358313 -0.716627 3.6 2.1 0.706523 0.706523 0.353261 -0.706523 3.7 2.1 0.696282 0.696282 0.348141 -0.696282 3.8 2.1 0.685916 0.685916 0.342958 -0.685916 3.9 2.1 0.675434 0.675434 0.337717 -0.675434 4 2.1 0.664846 0.664846 0.332423 -0.664846 4.1 2.1 0.654162 0.654162 0.327081 -0.654162 4.2 2.1 0.643393 0.643393 0.321696 -0.643393 4.3 2.1 0.632547 0.632547 0.316274 -0.632547 4.4 2.1 0.621636 0.621636 0.310818 -0.621636 4.5 2.1 0.610669 0.610669 0.305335 -0.610669 4.6 2.1 0.599655 0.599655 0.299828 -0.599655 4.7 2.1 0.588605 0.588605 0.294302 -0.588605 4.8 2.1 0.577527 0.577527 0.288764 -0.577527 4.9 2.1 0.566431 0.566431 0.283216 -0.566431 -5 2.2 0.550571 0.550571 0.275285 -0.550571 -4.9 2.2 0.561581 0.561581 0.28079 -0.561581 -4.8 2.2 0.572582 0.572582 0.286291 -0.572582 -4.7 2.2 0.583565 0.583565 0.291782 -0.583565 -4.6 2.2 0.594521 0.594521 0.29726 -0.594521 -4.5 2.2 0.60544 0.60544 0.30272 -0.60544 -4.4 2.2 0.616313 0.616313 0.308157 -0.616313 -4.3 2.2 0.627131 0.627131 0.313565 -0.627131 -4.2 2.2 0.637883 0.637883 0.318942 -0.637883 -4.1 2.2 0.64856 0.64856 0.32428 -0.64856 -4 2.2 0.659153 0.659153 0.329576 -0.659153 -3.9 2.2 0.66965 0.66965 0.334825 -0.66965 -3.8 2.2 0.680042 0.680042 0.340021 -0.680042 -3.7 2.2 0.69032 0.69032 0.34516 -0.69032 -3.6 2.2 0.700473 0.700473 0.350236 -0.700473 -3.5 2.2 0.71049 0.71049 0.355245 -0.71049 -3.4 2.2 0.720363 0.720363 0.360182 -0.720363 -3.3 2.2 0.730081 0.730081 0.36504 -0.730081 -3.2 2.2 0.739634 0.739634 0.369817 -0.739634 -3.1 2.2 0.749012 0.749012 0.374506 -0.749012 -3 2.2 0.758206 0.758206 0.379103 -0.758206 -2.9 2.2 0.767206 0.767206 0.383603 -0.767206 -2.8 2.2 0.776002 0.776002 0.388001 -0.776002 -2.7 2.2 0.784585 0.784585 0.392293 -0.784585 -2.6 2.2 0.792946 0.792946 0.396473 -0.792946 -2.5 2.2 0.801076 0.801076 0.400538 -0.801076 -2.4 2.2 0.808965 0.808965 0.404482 -0.808965 -2.3 2.2 0.816605 0.816605 0.408302 -0.816605 -2.2 2.2 0.823987 0.823987 0.411994 -0.823987 -2.1 2.2 0.831104 0.831104 0.415552 -0.831104 -2 2.2 0.837947 0.837947 0.418974 -0.837947 -1.9 2.2 0.844509 0.844509 0.422254 -0.844509 -1.8 2.2 0.850781 0.850781 0.425391 -0.850781 -1.7 2.2 0.856758 0.856758 0.428379 -0.856758 -1.6 2.2 0.862431 0.862431 0.431216 -0.862431 -1.5 2.2 0.867795 0.867795 0.433897 -0.867795 -1.4 2.2 0.872843 0.872843 0.436421 -0.872843 -1.3 2.2 0.877569 0.877569 0.438784 -0.877569 -1.2 2.2 0.881968 0.881968 0.440984 -0.881968 -1.1 2.2 0.886034 0.886034 0.443017 -0.886034 -1 2.2 0.889763 0.889763 0.444882 -0.889763 -0.9 2.2 0.893151 0.893151 0.446575 -0.893151 -0.8 2.2 0.896193 0.896193 0.448096 -0.896193 -0.7 2.2 0.898885 0.898885 0.449443 -0.898885 -0.6 2.2 0.901225 0.901225 0.450613 -0.901225 -0.5 2.2 0.90321 0.90321 0.451605 -0.90321 -0.4 2.2 0.904837 0.904837 0.452419 -0.904837 -0.3 2.2 0.906105 0.906105 0.453053 -0.906105 -0.2 2.2 0.907012 0.907012 0.453506 -0.907012 -0.1 2.2 0.907556 0.907556 0.453778 -0.907556 0 2.2 0.907738 0.907738 0.453869 -0.907738 0.1 2.2 0.907556 0.907556 0.453778 -0.907556 0.2 2.2 0.907012 0.907012 0.453506 -0.907012 0.3 2.2 0.906105 0.906105 0.453053 -0.906105 0.4 2.2 0.904837 0.904837 0.452419 -0.904837 0.5 2.2 0.90321 0.90321 0.451605 -0.90321 0.6 2.2 0.901225 0.901225 0.450613 -0.901225 0.7 2.2 0.898885 0.898885 0.449443 -0.898885 0.8 2.2 0.896193 0.896193 0.448096 -0.896193 0.9 2.2 0.893151 0.893151 0.446575 -0.893151 1 2.2 0.889763 0.889763 0.444882 -0.889763 1.1 2.2 0.886034 0.886034 0.443017 -0.886034 1.2 2.2 0.881968 0.881968 0.440984 -0.881968 1.3 2.2 0.877569 0.877569 0.438784 -0.877569 1.4 2.2 0.872843 0.872843 0.436421 -0.872843 1.5 2.2 0.867795 0.867795 0.433897 -0.867795 1.6 2.2 0.862431 0.862431 0.431216 -0.862431 1.7 2.2 0.856758 0.856758 0.428379 -0.856758 1.8 2.2 0.850781 0.850781 0.425391 -0.850781 1.9 2.2 0.844509 0.844509 0.422254 -0.844509 2 2.2 0.837947 0.837947 0.418974 -0.837947 2.1 2.2 0.831104 0.831104 0.415552 -0.831104 2.2 2.2 0.823987 0.823987 0.411994 -0.823987 2.3 2.2 0.816605 0.816605 0.408302 -0.816605 2.4 2.2 0.808965 0.808965 0.404482 -0.808965 2.5 2.2 0.801076 0.801076 0.400538 -0.801076 2.6 2.2 0.792946 0.792946 0.396473 -0.792946 2.7 2.2 0.784585 0.784585 0.392293 -0.784585 2.8 2.2 0.776002 0.776002 0.388001 -0.776002 2.9 2.2 0.767206 0.767206 0.383603 -0.767206 3 2.2 0.758206 0.758206 0.379103 -0.758206 3.1 2.2 0.749012 0.749012 0.374506 -0.749012 3.2 2.2 0.739634 0.739634 0.369817 -0.739634 3.3 2.2 0.730081 0.730081 0.36504 -0.730081 3.4 2.2 0.720363 0.720363 0.360182 -0.720363 3.5 2.2 0.71049 0.71049 0.355245 -0.71049 3.6 2.2 0.700473 0.700473 0.350236 -0.700473 3.7 2.2 0.69032 0.69032 0.34516 -0.69032 3.8 2.2 0.680042 0.680042 0.340021 -0.680042 3.9 2.2 0.66965 0.66965 0.334825 -0.66965 4 2.2 0.659153 0.659153 0.329576 -0.659153 4.1 2.2 0.64856 0.64856 0.32428 -0.64856 4.2 2.2 0.637883 0.637883 0.318942 -0.637883 4.3 2.2 0.627131 0.627131 0.313565 -0.627131 4.4 2.2 0.616313 0.616313 0.308157 -0.616313 4.5 2.2 0.60544 0.60544 0.30272 -0.60544 4.6 2.2 0.594521 0.594521 0.29726 -0.594521 4.7 2.2 0.583565 0.583565 0.291782 -0.583565 4.8 2.2 0.572582 0.572582 0.286291 -0.572582 4.9 2.2 0.561581 0.561581 0.28079 -0.561581 -5 2.3 0.545638 0.545638 0.272819 -0.545638 -4.9 2.3 0.556549 0.556549 0.278275 -0.556549 -4.8 2.3 0.567451 0.567451 0.283726 -0.567451 -4.7 2.3 0.578336 0.578336 0.289168 -0.578336 -4.6 2.3 0.589194 0.589194 0.294597 -0.589194 -4.5 2.3 0.600015 0.600015 0.300008 -0.600015 -4.4 2.3 0.610791 0.610791 0.305396 -0.610791 -4.3 2.3 0.621512 0.621512 0.310756 -0.621512 -4.2 2.3 0.632168 0.632168 0.316084 -0.632168 -4.1 2.3 0.64275 0.64275 0.321375 -0.64275 -4 2.3 0.653247 0.653247 0.326623 -0.653247 -3.9 2.3 0.66365 0.66365 0.331825 -0.66365 -3.8 2.3 0.67395 0.67395 0.336975 -0.67395 -3.7 2.3 0.684135 0.684135 0.342068 -0.684135 -3.6 2.3 0.694197 0.694197 0.347098 -0.694197 -3.5 2.3 0.704125 0.704125 0.352062 -0.704125 -3.4 2.3 0.713909 0.713909 0.356954 -0.713909 -3.3 2.3 0.72354 0.72354 0.36177 -0.72354 -3.2 2.3 0.733007 0.733007 0.366504 -0.733007 -3.1 2.3 0.742301 0.742301 0.371151 -0.742301 -3 2.3 0.751413 0.751413 0.375706 -0.751413 -2.9 2.3 0.760332 0.760332 0.380166 -0.760332 -2.8 2.3 0.769049 0.769049 0.384525 -0.769049 -2.7 2.3 0.777556 0.777556 0.388778 -0.777556 -2.6 2.3 0.785842 0.785842 0.392921 -0.785842 -2.5 2.3 0.793898 0.793898 0.396949 -0.793898 -2.4 2.3 0.801717 0.801717 0.400858 -0.801717 -2.3 2.3 0.809288 0.809288 0.404644 -0.809288 -2.2 2.3 0.816605 0.816605 0.408302 -0.816605 -2.1 2.3 0.823658 0.823658 0.411829 -0.823658 -2 2.3 0.83044 0.83044 0.41522 -0.83044 -1.9 2.3 0.836942 0.836942 0.418471 -0.836942 -1.8 2.3 0.843159 0.843159 0.421579 -0.843159 -1.7 2.3 0.849082 0.849082 0.424541 -0.849082 -1.6 2.3 0.854704 0.854704 0.427352 -0.854704 -1.5 2.3 0.86002 0.86002 0.43001 -0.86002 -1.4 2.3 0.865022 0.865022 0.432511 -0.865022 -1.3 2.3 0.869706 0.869706 0.434853 -0.869706 -1.2 2.3 0.874065 0.874065 0.437033 -0.874065 -1.1 2.3 0.878095 0.878095 0.439048 -0.878095 -1 2.3 0.881791 0.881791 0.440896 -0.881791 -0.9 2.3 0.885148 0.885148 0.442574 -0.885148 -0.8 2.3 0.888163 0.888163 0.444081 -0.888163 -0.7 2.3 0.890831 0.890831 0.445416 -0.890831 -0.6 2.3 0.893151 0.893151 0.446575 -0.893151 -0.5 2.3 0.895118 0.895118 0.447559 -0.895118 -0.4 2.3 0.89673 0.89673 0.448365 -0.89673 -0.3 2.3 0.897987 0.897987 0.448993 -0.897987 -0.2 2.3 0.898885 0.898885 0.449443 -0.898885 -0.1 2.3 0.899425 0.899425 0.449712 -0.899425 0 2.3 0.899605 0.899605 0.449802 -0.899605 0.1 2.3 0.899425 0.899425 0.449712 -0.899425 0.2 2.3 0.898885 0.898885 0.449443 -0.898885 0.3 2.3 0.897987 0.897987 0.448993 -0.897987 0.4 2.3 0.89673 0.89673 0.448365 -0.89673 0.5 2.3 0.895118 0.895118 0.447559 -0.895118 0.6 2.3 0.893151 0.893151 0.446575 -0.893151 0.7 2.3 0.890831 0.890831 0.445416 -0.890831 0.8 2.3 0.888163 0.888163 0.444081 -0.888163 0.9 2.3 0.885148 0.885148 0.442574 -0.885148 1 2.3 0.881791 0.881791 0.440896 -0.881791 1.1 2.3 0.878095 0.878095 0.439048 -0.878095 1.2 2.3 0.874065 0.874065 0.437033 -0.874065 1.3 2.3 0.869706 0.869706 0.434853 -0.869706 1.4 2.3 0.865022 0.865022 0.432511 -0.865022 1.5 2.3 0.86002 0.86002 0.43001 -0.86002 1.6 2.3 0.854704 0.854704 0.427352 -0.854704 1.7 2.3 0.849082 0.849082 0.424541 -0.849082 1.8 2.3 0.843159 0.843159 0.421579 -0.843159 1.9 2.3 0.836942 0.836942 0.418471 -0.836942 2 2.3 0.83044 0.83044 0.41522 -0.83044 2.1 2.3 0.823658 0.823658 0.411829 -0.823658 2.2 2.3 0.816605 0.816605 0.408302 -0.816605 2.3 2.3 0.809288 0.809288 0.404644 -0.809288 2.4 2.3 0.801717 0.801717 0.400858 -0.801717 2.5 2.3 0.793898 0.793898 0.396949 -0.793898 2.6 2.3 0.785842 0.785842 0.392921 -0.785842 2.7 2.3 0.777556 0.777556 0.388778 -0.777556 2.8 2.3 0.769049 0.769049 0.384525 -0.769049 2.9 2.3 0.760332 0.760332 0.380166 -0.760332 3 2.3 0.751413 0.751413 0.375706 -0.751413 3.1 2.3 0.742301 0.742301 0.371151 -0.742301 3.2 2.3 0.733007 0.733007 0.366504 -0.733007 3.3 2.3 0.72354 0.72354 0.36177 -0.72354 3.4 2.3 0.713909 0.713909 0.356954 -0.713909 3.5 2.3 0.704125 0.704125 0.352062 -0.704125 3.6 2.3 0.694197 0.694197 0.347098 -0.694197 3.7 2.3 0.684135 0.684135 0.342068 -0.684135 3.8 2.3 0.67395 0.67395 0.336975 -0.67395 3.9 2.3 0.66365 0.66365 0.331825 -0.66365 4 2.3 0.653247 0.653247 0.326623 -0.653247 4.1 2.3 0.64275 0.64275 0.321375 -0.64275 4.2 2.3 0.632168 0.632168 0.316084 -0.632168 4.3 2.3 0.621512 0.621512 0.310756 -0.621512 4.4 2.3 0.610791 0.610791 0.305396 -0.610791 4.5 2.3 0.600015 0.600015 0.300008 -0.600015 4.6 2.3 0.589194 0.589194 0.294597 -0.589194 4.7 2.3 0.578336 0.578336 0.289168 -0.578336 4.8 2.3 0.567451 0.567451 0.283726 -0.567451 4.9 2.3 0.556549 0.556549 0.278275 -0.556549 -5 2.4 0.540533 0.540533 0.270266 -0.540533 -4.9 2.4 0.551342 0.551342 0.275671 -0.551342 -4.8 2.4 0.562142 0.562142 0.281071 -0.562142 -4.7 2.4 0.572925 0.572925 0.286463 -0.572925 -4.6 2.4 0.583681 0.583681 0.291841 -0.583681 -4.5 2.4 0.594402 0.594402 0.297201 -0.594402 -4.4 2.4 0.605077 0.605077 0.302538 -0.605077 -4.3 2.4 0.615697 0.615697 0.307849 -0.615697 -4.2 2.4 0.626254 0.626254 0.313127 -0.626254 -4.1 2.4 0.636736 0.636736 0.318368 -0.636736 -4 2.4 0.647135 0.647135 0.323568 -0.647135 -3.9 2.4 0.657441 0.657441 0.328721 -0.657441 -3.8 2.4 0.667644 0.667644 0.333822 -0.667644 -3.7 2.4 0.677734 0.677734 0.338867 -0.677734 -3.6 2.4 0.687702 0.687702 0.343851 -0.687702 -3.5 2.4 0.697537 0.697537 0.348768 -0.697537 -3.4 2.4 0.70723 0.70723 0.353615 -0.70723 -3.3 2.4 0.71677 0.71677 0.358385 -0.71677 -3.2 2.4 0.726149 0.726149 0.363075 -0.726149 -3.1 2.4 0.735356 0.735356 0.367678 -0.735356 -3 2.4 0.744383 0.744383 0.372191 -0.744383 -2.9 2.4 0.753218 0.753218 0.376609 -0.753218 -2.8 2.4 0.761854 0.761854 0.380927 -0.761854 -2.7 2.4 0.770281 0.770281 0.38514 -0.770281 -2.6 2.4 0.778489 0.778489 0.389245 -0.778489 -2.5 2.4 0.786471 0.786471 0.393235 -0.786471 -2.4 2.4 0.794216 0.794216 0.397108 -0.794216 -2.3 2.4 0.801717 0.801717 0.400858 -0.801717 -2.2 2.4 0.808965 0.808965 0.404482 -0.808965 -2.1 2.4 0.815952 0.815952 0.407976 -0.815952 -2 2.4 0.82267 0.82267 0.411335 -0.82267 -1.9 2.4 0.829112 0.829112 0.414556 -0.829112 -1.8 2.4 0.83527 0.83527 0.417635 -0.83527 -1.7 2.4 0.841138 0.841138 0.420569 -0.841138 -1.6 2.4 0.846707 0.846707 0.423354 -0.846707 -1.5 2.4 0.851973 0.851973 0.425987 -0.851973 -1.4 2.4 0.856929 0.856929 0.428465 -0.856929 -1.3 2.4 0.861569 0.861569 0.430785 -0.861569 -1.2 2.4 0.865888 0.865888 0.432944 -0.865888 -1.1 2.4 0.86988 0.86988 0.43494 -0.86988 -1 2.4 0.873541 0.873541 0.436771 -0.873541 -0.9 2.4 0.876867 0.876867 0.438433 -0.876867 -0.8 2.4 0.879853 0.879853 0.439927 -0.879853 -0.7 2.4 0.882497 0.882497 0.441248 -0.882497 -0.6 2.4 0.884794 0.884794 0.442397 -0.884794 -0.5 2.4 0.886743 0.886743 0.443372 -0.886743 -0.4 2.4 0.888341 0.888341 0.44417 -0.888341 -0.3 2.4 0.889585 0.889585 0.444793 -0.889585 -0.2 2.4 0.890475 0.890475 0.445238 -0.890475 -0.1 2.4 0.89101 0.89101 0.445505 -0.89101 0 2.4 0.891188 0.891188 0.445594 -0.891188 0.1 2.4 0.89101 0.89101 0.445505 -0.89101 0.2 2.4 0.890475 0.890475 0.445238 -0.890475 0.3 2.4 0.889585 0.889585 0.444793 -0.889585 0.4 2.4 0.888341 0.888341 0.44417 -0.888341 0.5 2.4 0.886743 0.886743 0.443372 -0.886743 0.6 2.4 0.884794 0.884794 0.442397 -0.884794 0.7 2.4 0.882497 0.882497 0.441248 -0.882497 0.8 2.4 0.879853 0.879853 0.439927 -0.879853 0.9 2.4 0.876867 0.876867 0.438433 -0.876867 1 2.4 0.873541 0.873541 0.436771 -0.873541 1.1 2.4 0.86988 0.86988 0.43494 -0.86988 1.2 2.4 0.865888 0.865888 0.432944 -0.865888 1.3 2.4 0.861569 0.861569 0.430785 -0.861569 1.4 2.4 0.856929 0.856929 0.428465 -0.856929 1.5 2.4 0.851973 0.851973 0.425987 -0.851973 1.6 2.4 0.846707 0.846707 0.423354 -0.846707 1.7 2.4 0.841138 0.841138 0.420569 -0.841138 1.8 2.4 0.83527 0.83527 0.417635 -0.83527 1.9 2.4 0.829112 0.829112 0.414556 -0.829112 2 2.4 0.82267 0.82267 0.411335 -0.82267 2.1 2.4 0.815952 0.815952 0.407976 -0.815952 2.2 2.4 0.808965 0.808965 0.404482 -0.808965 2.3 2.4 0.801717 0.801717 0.400858 -0.801717 2.4 2.4 0.794216 0.794216 0.397108 -0.794216 2.5 2.4 0.786471 0.786471 0.393235 -0.786471 2.6 2.4 0.778489 0.778489 0.389245 -0.778489 2.7 2.4 0.770281 0.770281 0.38514 -0.770281 2.8 2.4 0.761854 0.761854 0.380927 -0.761854 2.9 2.4 0.753218 0.753218 0.376609 -0.753218 3 2.4 0.744383 0.744383 0.372191 -0.744383 3.1 2.4 0.735356 0.735356 0.367678 -0.735356 3.2 2.4 0.726149 0.726149 0.363075 -0.726149 3.3 2.4 0.71677 0.71677 0.358385 -0.71677 3.4 2.4 0.70723 0.70723 0.353615 -0.70723 3.5 2.4 0.697537 0.697537 0.348768 -0.697537 3.6 2.4 0.687702 0.687702 0.343851 -0.687702 3.7 2.4 0.677734 0.677734 0.338867 -0.677734 3.8 2.4 0.667644 0.667644 0.333822 -0.667644 3.9 2.4 0.657441 0.657441 0.328721 -0.657441 4 2.4 0.647135 0.647135 0.323568 -0.647135 4.1 2.4 0.636736 0.636736 0.318368 -0.636736 4.2 2.4 0.626254 0.626254 0.313127 -0.626254 4.3 2.4 0.615697 0.615697 0.307849 -0.615697 4.4 2.4 0.605077 0.605077 0.302538 -0.605077 4.5 2.4 0.594402 0.594402 0.297201 -0.594402 4.6 2.4 0.583681 0.583681 0.291841 -0.583681 4.7 2.4 0.572925 0.572925 0.286463 -0.572925 4.8 2.4 0.562142 0.562142 0.281071 -0.562142 4.9 2.4 0.551342 0.551342 0.275671 -0.551342 -5 2.5 0.535261 0.535261 0.267631 -0.535261 -4.9 2.5 0.545965 0.545965 0.272983 -0.545965 -4.8 2.5 0.55666 0.55666 0.27833 -0.55666 -4.7 2.5 0.567338 0.567338 0.283669 -0.567338 -4.6 2.5 0.577989 0.577989 0.288995 -0.577989 -4.5 2.5 0.588605 0.588605 0.294302 -0.588605 -4.4 2.5 0.599176 0.599176 0.299588 -0.599176 -4.3 2.5 0.609693 0.609693 0.304846 -0.609693 -4.2 2.5 0.620146 0.620146 0.310073 -0.620146 -4.1 2.5 0.630527 0.630527 0.315263 -0.630527 -4 2.5 0.640824 0.640824 0.320412 -0.640824 -3.9 2.5 0.65103 0.65103 0.325515 -0.65103 -3.8 2.5 0.661133 0.661133 0.330567 -0.661133 -3.7 2.5 0.671125 0.671125 0.335562 -0.671125 -3.6 2.5 0.680995 0.680995 0.340498 -0.680995 -3.5 2.5 0.690734 0.690734 0.345367 -0.690734 -3.4 2.5 0.700333 0.700333 0.350166 -0.700333 -3.3 2.5 0.70978 0.70978 0.35489 -0.70978 -3.2 2.5 0.719068 0.719068 0.359534 -0.719068 -3.1 2.5 0.728185 0.728185 0.364093 -0.728185 -3 2.5 0.737123 0.737123 0.368562 -0.737123 -2.9 2.5 0.745873 0.745873 0.372936 -0.745873 -2.8 2.5 0.754425 0.754425 0.377212 -0.754425 -2.7 2.5 0.762769 0.762769 0.381385 -0.762769 -2.6 2.5 0.770897 0.770897 0.385449 -0.770897 -2.5 2.5 0.778801 0.778801 0.3894 -0.778801 -2.4 2.5 0.786471 0.786471 0.393235 -0.786471 -2.3 2.5 0.793898 0.793898 0.396949 -0.793898 -2.2 2.5 0.801076 0.801076 0.400538 -0.801076 -2.1 2.5 0.807995 0.807995 0.403997 -0.807995 -2 2.5 0.814647 0.814647 0.407324 -0.814647 -1.9 2.5 0.821026 0.821026 0.410513 -0.821026 -1.8 2.5 0.827125 0.827125 0.413562 -0.827125 -1.7 2.5 0.832935 0.832935 0.416467 -0.832935 -1.6 2.5 0.83845 0.83845 0.419225 -0.83845 -1.5 2.5 0.843665 0.843665 0.421832 -0.843665 -1.4 2.5 0.848572 0.848572 0.424286 -0.848572 -1.3 2.5 0.853167 0.853167 0.426583 -0.853167 -1.2 2.5 0.857443 0.857443 0.428722 -0.857443 -1.1 2.5 0.861397 0.861397 0.430698 -0.861397 -1 2.5 0.865022 0.865022 0.432511 -0.865022 -0.9 2.5 0.868316 0.868316 0.434158 -0.868316 -0.8 2.5 0.871273 0.871273 0.435636 -0.871273 -0.7 2.5 0.873891 0.873891 0.436945 -0.873891 -0.6 2.5 0.876166 0.876166 0.438083 -0.876166 -0.5 2.5 0.878095 0.878095 0.439048 -0.878095 -0.4 2.5 0.879677 0.879677 0.439839 -0.879677 -0.3 2.5 0.88091 0.88091 0.440455 -0.88091 -0.2 2.5 0.881791 0.881791 0.440896 -0.881791 -0.1 2.5 0.88232 0.88232 0.44116 -0.88232 0 2.5 0.882497 0.882497 0.441248 -0.882497 0.1 2.5 0.88232 0.88232 0.44116 -0.88232 0.2 2.5 0.881791 0.881791 0.440896 -0.881791 0.3 2.5 0.88091 0.88091 0.440455 -0.88091 0.4 2.5 0.879677 0.879677 0.439839 -0.879677 0.5 2.5 0.878095 0.878095 0.439048 -0.878095 0.6 2.5 0.876166 0.876166 0.438083 -0.876166 0.7 2.5 0.873891 0.873891 0.436945 -0.873891 0.8 2.5 0.871273 0.871273 0.435636 -0.871273 0.9 2.5 0.868316 0.868316 0.434158 -0.868316 1 2.5 0.865022 0.865022 0.432511 -0.865022 1.1 2.5 0.861397 0.861397 0.430698 -0.861397 1.2 2.5 0.857443 0.857443 0.428722 -0.857443 1.3 2.5 0.853167 0.853167 0.426583 -0.853167 1.4 2.5 0.848572 0.848572 0.424286 -0.848572 1.5 2.5 0.843665 0.843665 0.421832 -0.843665 1.6 2.5 0.83845 0.83845 0.419225 -0.83845 1.7 2.5 0.832935 0.832935 0.416467 -0.832935 1.8 2.5 0.827125 0.827125 0.413562 -0.827125 1.9 2.5 0.821026 0.821026 0.410513 -0.821026 2 2.5 0.814647 0.814647 0.407324 -0.814647 2.1 2.5 0.807995 0.807995 0.403997 -0.807995 2.2 2.5 0.801076 0.801076 0.400538 -0.801076 2.3 2.5 0.793898 0.793898 0.396949 -0.793898 2.4 2.5 0.786471 0.786471 0.393235 -0.786471 2.5 2.5 0.778801 0.778801 0.3894 -0.778801 2.6 2.5 0.770897 0.770897 0.385449 -0.770897 2.7 2.5 0.762769 0.762769 0.381385 -0.762769 2.8 2.5 0.754425 0.754425 0.377212 -0.754425 2.9 2.5 0.745873 0.745873 0.372936 -0.745873 3 2.5 0.737123 0.737123 0.368562 -0.737123 3.1 2.5 0.728185 0.728185 0.364093 -0.728185 3.2 2.5 0.719068 0.719068 0.359534 -0.719068 3.3 2.5 0.70978 0.70978 0.35489 -0.70978 3.4 2.5 0.700333 0.700333 0.350166 -0.700333 3.5 2.5 0.690734 0.690734 0.345367 -0.690734 3.6 2.5 0.680995 0.680995 0.340498 -0.680995 3.7 2.5 0.671125 0.671125 0.335562 -0.671125 3.8 2.5 0.661133 0.661133 0.330567 -0.661133 3.9 2.5 0.65103 0.65103 0.325515 -0.65103 4 2.5 0.640824 0.640824 0.320412 -0.640824 4.1 2.5 0.630527 0.630527 0.315263 -0.630527 4.2 2.5 0.620146 0.620146 0.310073 -0.620146 4.3 2.5 0.609693 0.609693 0.304846 -0.609693 4.4 2.5 0.599176 0.599176 0.299588 -0.599176 4.5 2.5 0.588605 0.588605 0.294302 -0.588605 4.6 2.5 0.577989 0.577989 0.288995 -0.577989 4.7 2.5 0.567338 0.567338 0.283669 -0.567338 4.8 2.5 0.55666 0.55666 0.27833 -0.55666 4.9 2.5 0.545965 0.545965 0.272983 -0.545965 -5 2.6 0.52983 0.52983 0.264915 -0.52983 -4.9 2.6 0.540425 0.540425 0.270212 -0.540425 -4.8 2.6 0.551011 0.551011 0.275506 -0.551011 -4.7 2.6 0.561581 0.561581 0.28079 -0.561581 -4.6 2.6 0.572124 0.572124 0.286062 -0.572124 -4.5 2.6 0.582632 0.582632 0.291316 -0.582632 -4.4 2.6 0.593095 0.593095 0.296548 -0.593095 -4.3 2.6 0.603506 0.603506 0.301753 -0.603506 -4.2 2.6 0.613853 0.613853 0.306926 -0.613853 -4.1 2.6 0.624128 0.624128 0.312064 -0.624128 -4 2.6 0.634321 0.634321 0.317161 -0.634321 -3.9 2.6 0.644423 0.644423 0.322211 -0.644423 -3.8 2.6 0.654424 0.654424 0.327212 -0.654424 -3.7 2.6 0.664314 0.664314 0.332157 -0.664314 -3.6 2.6 0.674084 0.674084 0.337042 -0.674084 -3.5 2.6 0.683725 0.683725 0.341862 -0.683725 -3.4 2.6 0.693225 0.693225 0.346613 -0.693225 -3.3 2.6 0.702577 0.702577 0.351289 -0.702577 -3.2 2.6 0.71177 0.71177 0.355885 -0.71177 -3.1 2.6 0.720795 0.720795 0.360398 -0.720795 -3 2.6 0.729643 0.729643 0.364821 -0.729643 -2.9 2.6 0.738304 0.738304 0.369152 -0.738304 -2.8 2.6 0.746769 0.746769 0.373384 -0.746769 -2.7 2.6 0.755028 0.755028 0.377514 -0.755028 -2.6 2.6 0.763074 0.763074 0.381537 -0.763074 -2.5 2.6 0.770897 0.770897 0.385449 -0.770897 -2.4 2.6 0.778489 0.778489 0.389245 -0.778489 -2.3 2.6 0.785842 0.785842 0.392921 -0.785842 -2.2 2.6 0.792946 0.792946 0.396473 -0.792946 -2.1 2.6 0.799795 0.799795 0.399897 -0.799795 -2 2.6 0.80638 0.80638 0.40319 -0.80638 -1.9 2.6 0.812695 0.812695 0.406347 -0.812695 -1.8 2.6 0.818731 0.818731 0.409365 -0.818731 -1.7 2.6 0.824482 0.824482 0.412241 -0.824482 -1.6 2.6 0.829942 0.829942 0.414971 -0.829942 -1.5 2.6 0.835103 0.835103 0.417552 -0.835103 -1.4 2.6 0.839961 0.839961 0.41998 -0.839961 -1.3 2.6 0.844509 0.844509 0.422254 -0.844509 -1.2 2.6 0.848742 0.848742 0.424371 -0.848742 -1.1 2.6 0.852655 0.852655 0.426328 -0.852655 -1 2.6 0.856244 0.856244 0.428122 -0.856244 -0.9 2.6 0.859504 0.859504 0.429752 -0.859504 -0.8 2.6 0.862431 0.862431 0.431216 -0.862431 -0.7 2.6 0.865022 0.865022 0.432511 -0.865022 -0.6 2.6 0.867274 0.867274 0.433637 -0.867274 -0.5 2.6 0.869184 0.869184 0.434592 -0.869184 -0.4 2.6 0.87075 0.87075 0.435375 -0.87075 -0.3 2.6 0.87197 0.87197 0.435985 -0.87197 -0.2 2.6 0.872843 0.872843 0.436421 -0.872843 -0.1 2.6 0.873366 0.873366 0.436683 -0.873366 0 2.6 0.873541 0.873541 0.436771 -0.873541 0.1 2.6 0.873366 0.873366 0.436683 -0.873366 0.2 2.6 0.872843 0.872843 0.436421 -0.872843 0.3 2.6 0.87197 0.87197 0.435985 -0.87197 0.4 2.6 0.87075 0.87075 0.435375 -0.87075 0.5 2.6 0.869184 0.869184 0.434592 -0.869184 0.6 2.6 0.867274 0.867274 0.433637 -0.867274 0.7 2.6 0.865022 0.865022 0.432511 -0.865022 0.8 2.6 0.862431 0.862431 0.431216 -0.862431 0.9 2.6 0.859504 0.859504 0.429752 -0.859504 1 2.6 0.856244 0.856244 0.428122 -0.856244 1.1 2.6 0.852655 0.852655 0.426328 -0.852655 1.2 2.6 0.848742 0.848742 0.424371 -0.848742 1.3 2.6 0.844509 0.844509 0.422254 -0.844509 1.4 2.6 0.839961 0.839961 0.41998 -0.839961 1.5 2.6 0.835103 0.835103 0.417552 -0.835103 1.6 2.6 0.829942 0.829942 0.414971 -0.829942 1.7 2.6 0.824482 0.824482 0.412241 -0.824482 1.8 2.6 0.818731 0.818731 0.409365 -0.818731 1.9 2.6 0.812695 0.812695 0.406347 -0.812695 2 2.6 0.80638 0.80638 0.40319 -0.80638 2.1 2.6 0.799795 0.799795 0.399897 -0.799795 2.2 2.6 0.792946 0.792946 0.396473 -0.792946 2.3 2.6 0.785842 0.785842 0.392921 -0.785842 2.4 2.6 0.778489 0.778489 0.389245 -0.778489 2.5 2.6 0.770897 0.770897 0.385449 -0.770897 2.6 2.6 0.763074 0.763074 0.381537 -0.763074 2.7 2.6 0.755028 0.755028 0.377514 -0.755028 2.8 2.6 0.746769 0.746769 0.373384 -0.746769 2.9 2.6 0.738304 0.738304 0.369152 -0.738304 3 2.6 0.729643 0.729643 0.364821 -0.729643 3.1 2.6 0.720795 0.720795 0.360398 -0.720795 3.2 2.6 0.71177 0.71177 0.355885 -0.71177 3.3 2.6 0.702577 0.702577 0.351289 -0.702577 3.4 2.6 0.693225 0.693225 0.346613 -0.693225 3.5 2.6 0.683725 0.683725 0.341862 -0.683725 3.6 2.6 0.674084 0.674084 0.337042 -0.674084 3.7 2.6 0.664314 0.664314 0.332157 -0.664314 3.8 2.6 0.654424 0.654424 0.327212 -0.654424 3.9 2.6 0.644423 0.644423 0.322211 -0.644423 4 2.6 0.634321 0.634321 0.317161 -0.634321 4.1 2.6 0.624128 0.624128 0.312064 -0.624128 4.2 2.6 0.613853 0.613853 0.306926 -0.613853 4.3 2.6 0.603506 0.603506 0.301753 -0.603506 4.4 2.6 0.593095 0.593095 0.296548 -0.593095 4.5 2.6 0.582632 0.582632 0.291316 -0.582632 4.6 2.6 0.572124 0.572124 0.286062 -0.572124 4.7 2.6 0.561581 0.561581 0.28079 -0.561581 4.8 2.6 0.551011 0.551011 0.275506 -0.551011 4.9 2.6 0.540425 0.540425 0.270212 -0.540425 -5 2.7 0.524243 0.524243 0.262121 -0.524243 -4.9 2.7 0.534726 0.534726 0.267363 -0.534726 -4.8 2.7 0.545201 0.545201 0.272601 -0.545201 -4.7 2.7 0.555659 0.555659 0.27783 -0.555659 -4.6 2.7 0.566091 0.566091 0.283046 -0.566091 -4.5 2.7 0.576488 0.576488 0.288244 -0.576488 -4.4 2.7 0.586842 0.586842 0.293421 -0.586842 -4.3 2.7 0.597142 0.597142 0.298571 -0.597142 -4.2 2.7 0.60738 0.60738 0.30369 -0.60738 -4.1 2.7 0.617547 0.617547 0.308774 -0.617547 -4 2.7 0.627633 0.627633 0.313816 -0.627633 -3.9 2.7 0.637628 0.637628 0.318814 -0.637628 -3.8 2.7 0.647524 0.647524 0.323762 -0.647524 -3.7 2.7 0.65731 0.65731 0.328655 -0.65731 -3.6 2.7 0.666977 0.666977 0.333488 -0.666977 -3.5 2.7 0.676515 0.676515 0.338258 -0.676515 -3.4 2.7 0.685916 0.685916 0.342958 -0.685916 -3.3 2.7 0.695169 0.695169 0.347585 -0.695169 -3.2 2.7 0.704265 0.704265 0.352133 -0.704265 -3.1 2.7 0.713195 0.713195 0.356598 -0.713195 -3 2.7 0.72195 0.72195 0.360975 -0.72195 -2.9 2.7 0.730519 0.730519 0.36526 -0.730519 -2.8 2.7 0.738895 0.738895 0.369447 -0.738895 -2.7 2.7 0.747067 0.747067 0.373534 -0.747067 -2.6 2.7 0.755028 0.755028 0.377514 -0.755028 -2.5 2.7 0.762769 0.762769 0.381385 -0.762769 -2.4 2.7 0.770281 0.770281 0.38514 -0.770281 -2.3 2.7 0.777556 0.777556 0.388778 -0.777556 -2.2 2.7 0.784585 0.784585 0.392293 -0.784585 -2.1 2.7 0.791362 0.791362 0.395681 -0.791362 -2 2.7 0.797878 0.797878 0.398939 -0.797878 -1.9 2.7 0.804125 0.804125 0.402063 -0.804125 -1.8 2.7 0.810098 0.810098 0.405049 -0.810098 -1.7 2.7 0.815789 0.815789 0.407894 -0.815789 -1.6 2.7 0.821191 0.821191 0.410595 -0.821191 -1.5 2.7 0.826298 0.826298 0.413149 -0.826298 -1.4 2.7 0.831104 0.831104 0.415552 -0.831104 -1.3 2.7 0.835604 0.835604 0.417802 -0.835604 -1.2 2.7 0.839793 0.839793 0.419896 -0.839793 -1.1 2.7 0.843665 0.843665 0.421832 -0.843665 -1 2.7 0.847216 0.847216 0.423608 -0.847216 -0.9 2.7 0.850441 0.850441 0.425221 -0.850441 -0.8 2.7 0.853338 0.853338 0.426669 -0.853338 -0.7 2.7 0.855901 0.855901 0.427951 -0.855901 -0.6 2.7 0.85813 0.85813 0.429065 -0.85813 -0.5 2.7 0.86002 0.86002 0.43001 -0.86002 -0.4 2.7 0.861569 0.861569 0.430785 -0.861569 -0.3 2.7 0.862776 0.862776 0.431388 -0.862776 -0.2 2.7 0.863639 0.863639 0.43182 -0.863639 -0.1 2.7 0.864158 0.864158 0.432079 -0.864158 0 2.7 0.864331 0.864331 0.432165 -0.864331 0.1 2.7 0.864158 0.864158 0.432079 -0.864158 0.2 2.7 0.863639 0.863639 0.43182 -0.863639 0.3 2.7 0.862776 0.862776 0.431388 -0.862776 0.4 2.7 0.861569 0.861569 0.430785 -0.861569 0.5 2.7 0.86002 0.86002 0.43001 -0.86002 0.6 2.7 0.85813 0.85813 0.429065 -0.85813 0.7 2.7 0.855901 0.855901 0.427951 -0.855901 0.8 2.7 0.853338 0.853338 0.426669 -0.853338 0.9 2.7 0.850441 0.850441 0.425221 -0.850441 1 2.7 0.847216 0.847216 0.423608 -0.847216 1.1 2.7 0.843665 0.843665 0.421832 -0.843665 1.2 2.7 0.839793 0.839793 0.419896 -0.839793 1.3 2.7 0.835604 0.835604 0.417802 -0.835604 1.4 2.7 0.831104 0.831104 0.415552 -0.831104 1.5 2.7 0.826298 0.826298 0.413149 -0.826298 1.6 2.7 0.821191 0.821191 0.410595 -0.821191 1.7 2.7 0.815789 0.815789 0.407894 -0.815789 1.8 2.7 0.810098 0.810098 0.405049 -0.810098 1.9 2.7 0.804125 0.804125 0.402063 -0.804125 2 2.7 0.797878 0.797878 0.398939 -0.797878 2.1 2.7 0.791362 0.791362 0.395681 -0.791362 2.2 2.7 0.784585 0.784585 0.392293 -0.784585 2.3 2.7 0.777556 0.777556 0.388778 -0.777556 2.4 2.7 0.770281 0.770281 0.38514 -0.770281 2.5 2.7 0.762769 0.762769 0.381385 -0.762769 2.6 2.7 0.755028 0.755028 0.377514 -0.755028 2.7 2.7 0.747067 0.747067 0.373534 -0.747067 2.8 2.7 0.738895 0.738895 0.369447 -0.738895 2.9 2.7 0.730519 0.730519 0.36526 -0.730519 3 2.7 0.72195 0.72195 0.360975 -0.72195 3.1 2.7 0.713195 0.713195 0.356598 -0.713195 3.2 2.7 0.704265 0.704265 0.352133 -0.704265 3.3 2.7 0.695169 0.695169 0.347585 -0.695169 3.4 2.7 0.685916 0.685916 0.342958 -0.685916 3.5 2.7 0.676515 0.676515 0.338258 -0.676515 3.6 2.7 0.666977 0.666977 0.333488 -0.666977 3.7 2.7 0.65731 0.65731 0.328655 -0.65731 3.8 2.7 0.647524 0.647524 0.323762 -0.647524 3.9 2.7 0.637628 0.637628 0.318814 -0.637628 4 2.7 0.627633 0.627633 0.313816 -0.627633 4.1 2.7 0.617547 0.617547 0.308774 -0.617547 4.2 2.7 0.60738 0.60738 0.30369 -0.60738 4.3 2.7 0.597142 0.597142 0.298571 -0.597142 4.4 2.7 0.586842 0.586842 0.293421 -0.586842 4.5 2.7 0.576488 0.576488 0.288244 -0.576488 4.6 2.7 0.566091 0.566091 0.283046 -0.566091 4.7 2.7 0.555659 0.555659 0.27783 -0.555659 4.8 2.7 0.545201 0.545201 0.272601 -0.545201 4.9 2.7 0.534726 0.534726 0.267363 -0.534726 -5 2.8 0.518508 0.518508 0.259254 -0.518508 -4.9 2.8 0.528877 0.528877 0.264438 -0.528877 -4.8 2.8 0.539237 0.539237 0.269619 -0.539237 -4.7 2.8 0.549581 0.549581 0.27479 -0.549581 -4.6 2.8 0.559898 0.559898 0.279949 -0.559898 -4.5 2.8 0.570182 0.570182 0.285091 -0.570182 -4.4 2.8 0.580422 0.580422 0.290211 -0.580422 -4.3 2.8 0.59061 0.59061 0.295305 -0.59061 -4.2 2.8 0.600736 0.600736 0.300368 -0.600736 -4.1 2.8 0.610791 0.610791 0.305396 -0.610791 -4 2.8 0.620767 0.620767 0.310383 -0.620767 -3.9 2.8 0.630653 0.630653 0.315326 -0.630653 -3.8 2.8 0.64044 0.64044 0.32022 -0.64044 -3.7 2.8 0.650119 0.650119 0.325059 -0.650119 -3.6 2.8 0.65968 0.65968 0.32984 -0.65968 -3.5 2.8 0.669115 0.669115 0.334557 -0.669115 -3.4 2.8 0.678412 0.678412 0.339206 -0.678412 -3.3 2.8 0.687564 0.687564 0.343782 -0.687564 -3.2 2.8 0.696561 0.696561 0.34828 -0.696561 -3.1 2.8 0.705393 0.705393 0.352697 -0.705393 -3 2.8 0.714052 0.714052 0.357026 -0.714052 -2.9 2.8 0.722527 0.722527 0.361264 -0.722527 -2.8 2.8 0.730811 0.730811 0.365406 -0.730811 -2.7 2.8 0.738895 0.738895 0.369447 -0.738895 -2.6 2.8 0.746769 0.746769 0.373384 -0.746769 -2.5 2.8 0.754425 0.754425 0.377212 -0.754425 -2.4 2.8 0.761854 0.761854 0.380927 -0.761854 -2.3 2.8 0.769049 0.769049 0.384525 -0.769049 -2.2 2.8 0.776002 0.776002 0.388001 -0.776002 -2.1 2.8 0.782705 0.782705 0.391352 -0.782705 -2 2.8 0.789149 0.789149 0.394575 -0.789149 -1.9 2.8 0.795329 0.795329 0.397664 -0.795329 -1.8 2.8 0.801236 0.801236 0.400618 -0.801236 -1.7 2.8 0.806864 0.806864 0.403432 -0.806864 -1.6 2.8 0.812207 0.812207 0.406104 -0.812207 -1.5 2.8 0.817258 0.817258 0.408629 -0.817258 -1.4 2.8 0.822012 0.822012 0.411006 -0.822012 -1.3 2.8 0.826463 0.826463 0.413232 -0.826463 -1.2 2.8 0.830606 0.830606 0.415303 -0.830606 -1.1 2.8 0.834435 0.834435 0.417218 -0.834435 -1 2.8 0.837947 0.837947 0.418974 -0.837947 -0.9 2.8 0.841138 0.841138 0.420569 -0.841138 -0.8 2.8 0.844002 0.844002 0.422001 -0.844002 -0.7 2.8 0.846538 0.846538 0.423269 -0.846538 -0.6 2.8 0.848742 0.848742 0.424371 -0.848742 -0.5 2.8 0.850611 0.850611 0.425306 -0.850611 -0.4 2.8 0.852144 0.852144 0.426072 -0.852144 -0.3 2.8 0.853338 0.853338 0.426669 -0.853338 -0.2 2.8 0.854191 0.854191 0.427096 -0.854191 -0.1 2.8 0.854704 0.854704 0.427352 -0.854704 0 2.8 0.854875 0.854875 0.427438 -0.854875 0.1 2.8 0.854704 0.854704 0.427352 -0.854704 0.2 2.8 0.854191 0.854191 0.427096 -0.854191 0.3 2.8 0.853338 0.853338 0.426669 -0.853338 0.4 2.8 0.852144 0.852144 0.426072 -0.852144 0.5 2.8 0.850611 0.850611 0.425306 -0.850611 0.6 2.8 0.848742 0.848742 0.424371 -0.848742 0.7 2.8 0.846538 0.846538 0.423269 -0.846538 0.8 2.8 0.844002 0.844002 0.422001 -0.844002 0.9 2.8 0.841138 0.841138 0.420569 -0.841138 1 2.8 0.837947 0.837947 0.418974 -0.837947 1.1 2.8 0.834435 0.834435 0.417218 -0.834435 1.2 2.8 0.830606 0.830606 0.415303 -0.830606 1.3 2.8 0.826463 0.826463 0.413232 -0.826463 1.4 2.8 0.822012 0.822012 0.411006 -0.822012 1.5 2.8 0.817258 0.817258 0.408629 -0.817258 1.6 2.8 0.812207 0.812207 0.406104 -0.812207 1.7 2.8 0.806864 0.806864 0.403432 -0.806864 1.8 2.8 0.801236 0.801236 0.400618 -0.801236 1.9 2.8 0.795329 0.795329 0.397664 -0.795329 2 2.8 0.789149 0.789149 0.394575 -0.789149 2.1 2.8 0.782705 0.782705 0.391352 -0.782705 2.2 2.8 0.776002 0.776002 0.388001 -0.776002 2.3 2.8 0.769049 0.769049 0.384525 -0.769049 2.4 2.8 0.761854 0.761854 0.380927 -0.761854 2.5 2.8 0.754425 0.754425 0.377212 -0.754425 2.6 2.8 0.746769 0.746769 0.373384 -0.746769 2.7 2.8 0.738895 0.738895 0.369447 -0.738895 2.8 2.8 0.730811 0.730811 0.365406 -0.730811 2.9 2.8 0.722527 0.722527 0.361264 -0.722527 3 2.8 0.714052 0.714052 0.357026 -0.714052 3.1 2.8 0.705393 0.705393 0.352697 -0.705393 3.2 2.8 0.696561 0.696561 0.34828 -0.696561 3.3 2.8 0.687564 0.687564 0.343782 -0.687564 3.4 2.8 0.678412 0.678412 0.339206 -0.678412 3.5 2.8 0.669115 0.669115 0.334557 -0.669115 3.6 2.8 0.65968 0.65968 0.32984 -0.65968 3.7 2.8 0.650119 0.650119 0.325059 -0.650119 3.8 2.8 0.64044 0.64044 0.32022 -0.64044 3.9 2.8 0.630653 0.630653 0.315326 -0.630653 4 2.8 0.620767 0.620767 0.310383 -0.620767 4.1 2.8 0.610791 0.610791 0.305396 -0.610791 4.2 2.8 0.600736 0.600736 0.300368 -0.600736 4.3 2.8 0.59061 0.59061 0.295305 -0.59061 4.4 2.8 0.580422 0.580422 0.290211 -0.580422 4.5 2.8 0.570182 0.570182 0.285091 -0.570182 4.6 2.8 0.559898 0.559898 0.279949 -0.559898 4.7 2.8 0.549581 0.549581 0.27479 -0.549581 4.8 2.8 0.539237 0.539237 0.269619 -0.539237 4.9 2.8 0.528877 0.528877 0.264438 -0.528877 -5 2.9 0.51263 0.51263 0.256315 -0.51263 -4.9 2.9 0.522882 0.522882 0.261441 -0.522882 -4.8 2.9 0.533125 0.533125 0.266562 -0.533125 -4.7 2.9 0.543351 0.543351 0.271675 -0.543351 -4.6 2.9 0.553552 0.553552 0.276776 -0.553552 -4.5 2.9 0.563719 0.563719 0.281859 -0.563719 -4.4 2.9 0.573843 0.573843 0.286921 -0.573843 -4.3 2.9 0.583915 0.583915 0.291957 -0.583915 -4.2 2.9 0.593926 0.593926 0.296963 -0.593926 -4.1 2.9 0.603868 0.603868 0.301934 -0.603868 -4 2.9 0.61373 0.61373 0.306865 -0.61373 -3.9 2.9 0.623504 0.623504 0.311752 -0.623504 -3.8 2.9 0.63318 0.63318 0.31659 -0.63318 -3.7 2.9 0.64275 0.64275 0.321375 -0.64275 -3.6 2.9 0.652203 0.652203 0.326101 -0.652203 -3.5 2.9 0.66153 0.66153 0.330765 -0.66153 -3.4 2.9 0.670722 0.670722 0.335361 -0.670722 -3.3 2.9 0.679771 0.679771 0.339885 -0.679771 -3.2 2.9 0.688665 0.688665 0.344333 -0.688665 -3.1 2.9 0.697397 0.697397 0.348699 -0.697397 -3 2.9 0.705958 0.705958 0.352979 -0.705958 -2.9 2.9 0.714337 0.714337 0.357169 -0.714337 -2.8 2.9 0.722527 0.722527 0.361264 -0.722527 -2.7 2.9 0.730519 0.730519 0.36526 -0.730519 -2.6 2.9 0.738304 0.738304 0.369152 -0.738304 -2.5 2.9 0.745873 0.745873 0.372936 -0.745873 -2.4 2.9 0.753218 0.753218 0.376609 -0.753218 -2.3 2.9 0.760332 0.760332 0.380166 -0.760332 -2.2 2.9 0.767206 0.767206 0.383603 -0.767206 -2.1 2.9 0.773832 0.773832 0.386916 -0.773832 -2 2.9 0.780204 0.780204 0.390102 -0.780204 -1.9 2.9 0.786313 0.786313 0.393157 -0.786313 -1.8 2.9 0.792154 0.792154 0.396077 -0.792154 -1.7 2.9 0.797718 0.797718 0.398859 -0.797718 -1.6 2.9 0.803 0.803 0.4015 -0.803 -1.5 2.9 0.807995 0.807995 0.403997 -0.807995 -1.4 2.9 0.812695 0.812695 0.406347 -0.812695 -1.3 2.9 0.817095 0.817095 0.408547 -0.817095 -1.2 2.9 0.821191 0.821191 0.410595 -0.821191 -1.1 2.9 0.824977 0.824977 0.412488 -0.824977 -1 2.9 0.828449 0.828449 0.414225 -0.828449 -0.9 2.9 0.831603 0.831603 0.415802 -0.831603 -0.8 2.9 0.834435 0.834435 0.417218 -0.834435 -0.7 2.9 0.836942 0.836942 0.418471 -0.836942 -0.6 2.9 0.839121 0.839121 0.419561 -0.839121 -0.5 2.9 0.840969 0.840969 0.420485 -0.840969 -0.4 2.9 0.842485 0.842485 0.421242 -0.842485 -0.3 2.9 0.843665 0.843665 0.421832 -0.843665 -0.2 2.9 0.844509 0.844509 0.422254 -0.844509 -0.1 2.9 0.845016 0.845016 0.422508 -0.845016 0 2.9 0.845185 0.845185 0.422592 -0.845185 0.1 2.9 0.845016 0.845016 0.422508 -0.845016 0.2 2.9 0.844509 0.844509 0.422254 -0.844509 0.3 2.9 0.843665 0.843665 0.421832 -0.843665 0.4 2.9 0.842485 0.842485 0.421242 -0.842485 0.5 2.9 0.840969 0.840969 0.420485 -0.840969 0.6 2.9 0.839121 0.839121 0.419561 -0.839121 0.7 2.9 0.836942 0.836942 0.418471 -0.836942 0.8 2.9 0.834435 0.834435 0.417218 -0.834435 0.9 2.9 0.831603 0.831603 0.415802 -0.831603 1 2.9 0.828449 0.828449 0.414225 -0.828449 1.1 2.9 0.824977 0.824977 0.412488 -0.824977 1.2 2.9 0.821191 0.821191 0.410595 -0.821191 1.3 2.9 0.817095 0.817095 0.408547 -0.817095 1.4 2.9 0.812695 0.812695 0.406347 -0.812695 1.5 2.9 0.807995 0.807995 0.403997 -0.807995 1.6 2.9 0.803 0.803 0.4015 -0.803 1.7 2.9 0.797718 0.797718 0.398859 -0.797718 1.8 2.9 0.792154 0.792154 0.396077 -0.792154 1.9 2.9 0.786313 0.786313 0.393157 -0.786313 2 2.9 0.780204 0.780204 0.390102 -0.780204 2.1 2.9 0.773832 0.773832 0.386916 -0.773832 2.2 2.9 0.767206 0.767206 0.383603 -0.767206 2.3 2.9 0.760332 0.760332 0.380166 -0.760332 2.4 2.9 0.753218 0.753218 0.376609 -0.753218 2.5 2.9 0.745873 0.745873 0.372936 -0.745873 2.6 2.9 0.738304 0.738304 0.369152 -0.738304 2.7 2.9 0.730519 0.730519 0.36526 -0.730519 2.8 2.9 0.722527 0.722527 0.361264 -0.722527 2.9 2.9 0.714337 0.714337 0.357169 -0.714337 3 2.9 0.705958 0.705958 0.352979 -0.705958 3.1 2.9 0.697397 0.697397 0.348699 -0.697397 3.2 2.9 0.688665 0.688665 0.344333 -0.688665 3.3 2.9 0.679771 0.679771 0.339885 -0.679771 3.4 2.9 0.670722 0.670722 0.335361 -0.670722 3.5 2.9 0.66153 0.66153 0.330765 -0.66153 3.6 2.9 0.652203 0.652203 0.326101 -0.652203 3.7 2.9 0.64275 0.64275 0.321375 -0.64275 3.8 2.9 0.63318 0.63318 0.31659 -0.63318 3.9 2.9 0.623504 0.623504 0.311752 -0.623504 4 2.9 0.61373 0.61373 0.306865 -0.61373 4.1 2.9 0.603868 0.603868 0.301934 -0.603868 4.2 2.9 0.593926 0.593926 0.296963 -0.593926 4.3 2.9 0.583915 0.583915 0.291957 -0.583915 4.4 2.9 0.573843 0.573843 0.286921 -0.573843 4.5 2.9 0.563719 0.563719 0.281859 -0.563719 4.6 2.9 0.553552 0.553552 0.276776 -0.553552 4.7 2.9 0.543351 0.543351 0.271675 -0.543351 4.8 2.9 0.533125 0.533125 0.266562 -0.533125 4.9 2.9 0.522882 0.522882 0.261441 -0.522882 -5 3 0.506617 0.506617 0.253308 -0.506617 -4.9 3 0.516748 0.516748 0.258374 -0.516748 -4.8 3 0.526871 0.526871 0.263435 -0.526871 -4.7 3 0.536977 0.536977 0.268489 -0.536977 -4.6 3 0.547058 0.547058 0.273529 -0.547058 -4.5 3 0.557106 0.557106 0.278553 -0.557106 -4.4 3 0.567111 0.567111 0.283556 -0.567111 -4.3 3 0.577065 0.577065 0.288533 -0.577065 -4.2 3 0.586959 0.586959 0.29348 -0.586959 -4.1 3 0.596784 0.596784 0.298392 -0.596784 -4 3 0.606531 0.606531 0.303265 -0.606531 -3.9 3 0.61619 0.61619 0.308095 -0.61619 -3.8 3 0.625753 0.625753 0.312876 -0.625753 -3.7 3 0.63521 0.63521 0.317605 -0.63521 -3.6 3 0.644552 0.644552 0.322276 -0.644552 -3.5 3 0.65377 0.65377 0.326885 -0.65377 -3.4 3 0.662854 0.662854 0.331427 -0.662854 -3.3 3 0.671796 0.671796 0.335898 -0.671796 -3.2 3 0.680587 0.680587 0.340293 -0.680587 -3.1 3 0.689216 0.689216 0.344608 -0.689216 -3 3 0.697676 0.697676 0.348838 -0.697676 -2.9 3 0.705958 0.705958 0.352979 -0.705958 -2.8 3 0.714052 0.714052 0.357026 -0.714052 -2.7 3 0.72195 0.72195 0.360975 -0.72195 -2.6 3 0.729643 0.729643 0.364821 -0.729643 -2.5 3 0.737123 0.737123 0.368562 -0.737123 -2.4 3 0.744383 0.744383 0.372191 -0.744383 -2.3 3 0.751413 0.751413 0.375706 -0.751413 -2.2 3 0.758206 0.758206 0.379103 -0.758206 -2.1 3 0.764755 0.764755 0.382377 -0.764755 -2 3 0.771052 0.771052 0.385526 -0.771052 -1.9 3 0.777089 0.777089 0.388545 -0.777089 -1.8 3 0.782861 0.782861 0.391431 -0.782861 -1.7 3 0.78836 0.78836 0.39418 -0.78836 -1.6 3 0.793581 0.793581 0.39679 -0.793581 -1.5 3 0.798516 0.798516 0.399258 -0.798516 -1.4 3 0.803161 0.803161 0.401581 -0.803161 -1.3 3 0.80751 0.80751 0.403755 -0.80751 -1.2 3 0.811558 0.811558 0.405779 -0.811558 -1.1 3 0.815299 0.815299 0.40765 -0.815299 -1 3 0.818731 0.818731 0.409365 -0.818731 -0.9 3 0.821848 0.821848 0.410924 -0.821848 -0.8 3 0.824647 0.824647 0.412323 -0.824647 -0.7 3 0.827125 0.827125 0.413562 -0.827125 -0.6 3 0.829278 0.829278 0.414639 -0.829278 -0.5 3 0.831104 0.831104 0.415552 -0.831104 -0.4 3 0.832602 0.832602 0.416301 -0.832602 -0.3 3 0.833768 0.833768 0.416884 -0.833768 -0.2 3 0.834602 0.834602 0.417301 -0.834602 -0.1 3 0.835103 0.835103 0.417552 -0.835103 0 3 0.83527 0.83527 0.417635 -0.83527 0.1 3 0.835103 0.835103 0.417552 -0.835103 0.2 3 0.834602 0.834602 0.417301 -0.834602 0.3 3 0.833768 0.833768 0.416884 -0.833768 0.4 3 0.832602 0.832602 0.416301 -0.832602 0.5 3 0.831104 0.831104 0.415552 -0.831104 0.6 3 0.829278 0.829278 0.414639 -0.829278 0.7 3 0.827125 0.827125 0.413562 -0.827125 0.8 3 0.824647 0.824647 0.412323 -0.824647 0.9 3 0.821848 0.821848 0.410924 -0.821848 1 3 0.818731 0.818731 0.409365 -0.818731 1.1 3 0.815299 0.815299 0.40765 -0.815299 1.2 3 0.811558 0.811558 0.405779 -0.811558 1.3 3 0.80751 0.80751 0.403755 -0.80751 1.4 3 0.803161 0.803161 0.401581 -0.803161 1.5 3 0.798516 0.798516 0.399258 -0.798516 1.6 3 0.793581 0.793581 0.39679 -0.793581 1.7 3 0.78836 0.78836 0.39418 -0.78836 1.8 3 0.782861 0.782861 0.391431 -0.782861 1.9 3 0.777089 0.777089 0.388545 -0.777089 2 3 0.771052 0.771052 0.385526 -0.771052 2.1 3 0.764755 0.764755 0.382377 -0.764755 2.2 3 0.758206 0.758206 0.379103 -0.758206 2.3 3 0.751413 0.751413 0.375706 -0.751413 2.4 3 0.744383 0.744383 0.372191 -0.744383 2.5 3 0.737123 0.737123 0.368562 -0.737123 2.6 3 0.729643 0.729643 0.364821 -0.729643 2.7 3 0.72195 0.72195 0.360975 -0.72195 2.8 3 0.714052 0.714052 0.357026 -0.714052 2.9 3 0.705958 0.705958 0.352979 -0.705958 3 3 0.697676 0.697676 0.348838 -0.697676 3.1 3 0.689216 0.689216 0.344608 -0.689216 3.2 3 0.680587 0.680587 0.340293 -0.680587 3.3 3 0.671796 0.671796 0.335898 -0.671796 3.4 3 0.662854 0.662854 0.331427 -0.662854 3.5 3 0.65377 0.65377 0.326885 -0.65377 3.6 3 0.644552 0.644552 0.322276 -0.644552 3.7 3 0.63521 0.63521 0.317605 -0.63521 3.8 3 0.625753 0.625753 0.312876 -0.625753 3.9 3 0.61619 0.61619 0.308095 -0.61619 4 3 0.606531 0.606531 0.303265 -0.606531 4.1 3 0.596784 0.596784 0.298392 -0.596784 4.2 3 0.586959 0.586959 0.29348 -0.586959 4.3 3 0.577065 0.577065 0.288533 -0.577065 4.4 3 0.567111 0.567111 0.283556 -0.567111 4.5 3 0.557106 0.557106 0.278553 -0.557106 4.6 3 0.547058 0.547058 0.273529 -0.547058 4.7 3 0.536977 0.536977 0.268489 -0.536977 4.8 3 0.526871 0.526871 0.263435 -0.526871 4.9 3 0.516748 0.516748 0.258374 -0.516748 -5 3.1 0.500474 0.500474 0.250237 -0.500474 -4.9 3.1 0.510482 0.510482 0.255241 -0.510482 -4.8 3.1 0.520482 0.520482 0.260241 -0.520482 -4.7 3.1 0.530466 0.530466 0.265233 -0.530466 -4.6 3.1 0.540425 0.540425 0.270212 -0.540425 -4.5 3.1 0.55035 0.55035 0.275175 -0.55035 -4.4 3.1 0.560234 0.560234 0.280117 -0.560234 -4.3 3.1 0.570068 0.570068 0.285034 -0.570068 -4.2 3.1 0.579842 0.579842 0.289921 -0.579842 -4.1 3.1 0.589547 0.589547 0.294774 -0.589547 -4 3.1 0.599176 0.599176 0.299588 -0.599176 -3.9 3.1 0.608718 0.608718 0.304359 -0.608718 -3.8 3.1 0.618165 0.618165 0.309082 -0.618165 -3.7 3.1 0.627507 0.627507 0.313754 -0.627507 -3.6 3.1 0.636736 0.636736 0.318368 -0.636736 -3.5 3.1 0.645842 0.645842 0.322921 -0.645842 -3.4 3.1 0.654817 0.654817 0.327408 -0.654817 -3.3 3.1 0.66365 0.66365 0.331825 -0.66365 -3.2 3.1 0.672334 0.672334 0.336167 -0.672334 -3.1 3.1 0.680859 0.680859 0.34043 -0.680859 -3 3.1 0.689216 0.689216 0.344608 -0.689216 -2.9 3.1 0.697397 0.697397 0.348699 -0.697397 -2.8 3.1 0.705393 0.705393 0.352697 -0.705393 -2.7 3.1 0.713195 0.713195 0.356598 -0.713195 -2.6 3.1 0.720795 0.720795 0.360398 -0.720795 -2.5 3.1 0.728185 0.728185 0.364093 -0.728185 -2.4 3.1 0.735356 0.735356 0.367678 -0.735356 -2.3 3.1 0.742301 0.742301 0.371151 -0.742301 -2.2 3.1 0.749012 0.749012 0.374506 -0.749012 -2.1 3.1 0.755481 0.755481 0.377741 -0.755481 -2 3.1 0.761702 0.761702 0.380851 -0.761702 -1.9 3.1 0.767666 0.767666 0.383833 -0.767666 -1.8 3.1 0.773368 0.773368 0.386684 -0.773368 -1.7 3.1 0.778801 0.778801 0.3894 -0.778801 -1.6 3.1 0.783958 0.783958 0.391979 -0.783958 -1.5 3.1 0.788834 0.788834 0.394417 -0.788834 -1.4 3.1 0.793422 0.793422 0.396711 -0.793422 -1.3 3.1 0.797718 0.797718 0.398859 -0.797718 -1.2 3.1 0.801717 0.801717 0.400858 -0.801717 -1.1 3.1 0.805413 0.805413 0.402707 -0.805413 -1 3.1 0.808803 0.808803 0.404401 -0.808803 -0.9 3.1 0.811882 0.811882 0.405941 -0.811882 -0.8 3.1 0.814647 0.814647 0.407324 -0.814647 -0.7 3.1 0.817095 0.817095 0.408547 -0.817095 -0.6 3.1 0.819222 0.819222 0.409611 -0.819222 -0.5 3.1 0.821026 0.821026 0.410513 -0.821026 -0.4 3.1 0.822506 0.822506 0.411253 -0.822506 -0.3 3.1 0.823658 0.823658 0.411829 -0.823658 -0.2 3.1 0.824482 0.824482 0.412241 -0.824482 -0.1 3.1 0.824977 0.824977 0.412488 -0.824977 0 3.1 0.825142 0.825142 0.412571 -0.825142 0.1 3.1 0.824977 0.824977 0.412488 -0.824977 0.2 3.1 0.824482 0.824482 0.412241 -0.824482 0.3 3.1 0.823658 0.823658 0.411829 -0.823658 0.4 3.1 0.822506 0.822506 0.411253 -0.822506 0.5 3.1 0.821026 0.821026 0.410513 -0.821026 0.6 3.1 0.819222 0.819222 0.409611 -0.819222 0.7 3.1 0.817095 0.817095 0.408547 -0.817095 0.8 3.1 0.814647 0.814647 0.407324 -0.814647 0.9 3.1 0.811882 0.811882 0.405941 -0.811882 1 3.1 0.808803 0.808803 0.404401 -0.808803 1.1 3.1 0.805413 0.805413 0.402707 -0.805413 1.2 3.1 0.801717 0.801717 0.400858 -0.801717 1.3 3.1 0.797718 0.797718 0.398859 -0.797718 1.4 3.1 0.793422 0.793422 0.396711 -0.793422 1.5 3.1 0.788834 0.788834 0.394417 -0.788834 1.6 3.1 0.783958 0.783958 0.391979 -0.783958 1.7 3.1 0.778801 0.778801 0.3894 -0.778801 1.8 3.1 0.773368 0.773368 0.386684 -0.773368 1.9 3.1 0.767666 0.767666 0.383833 -0.767666 2 3.1 0.761702 0.761702 0.380851 -0.761702 2.1 3.1 0.755481 0.755481 0.377741 -0.755481 2.2 3.1 0.749012 0.749012 0.374506 -0.749012 2.3 3.1 0.742301 0.742301 0.371151 -0.742301 2.4 3.1 0.735356 0.735356 0.367678 -0.735356 2.5 3.1 0.728185 0.728185 0.364093 -0.728185 2.6 3.1 0.720795 0.720795 0.360398 -0.720795 2.7 3.1 0.713195 0.713195 0.356598 -0.713195 2.8 3.1 0.705393 0.705393 0.352697 -0.705393 2.9 3.1 0.697397 0.697397 0.348699 -0.697397 3 3.1 0.689216 0.689216 0.344608 -0.689216 3.1 3.1 0.680859 0.680859 0.34043 -0.680859 3.2 3.1 0.672334 0.672334 0.336167 -0.672334 3.3 3.1 0.66365 0.66365 0.331825 -0.66365 3.4 3.1 0.654817 0.654817 0.327408 -0.654817 3.5 3.1 0.645842 0.645842 0.322921 -0.645842 3.6 3.1 0.636736 0.636736 0.318368 -0.636736 3.7 3.1 0.627507 0.627507 0.313754 -0.627507 3.8 3.1 0.618165 0.618165 0.309082 -0.618165 3.9 3.1 0.608718 0.608718 0.304359 -0.608718 4 3.1 0.599176 0.599176 0.299588 -0.599176 4.1 3.1 0.589547 0.589547 0.294774 -0.589547 4.2 3.1 0.579842 0.579842 0.289921 -0.579842 4.3 3.1 0.570068 0.570068 0.285034 -0.570068 4.4 3.1 0.560234 0.560234 0.280117 -0.560234 4.5 3.1 0.55035 0.55035 0.275175 -0.55035 4.6 3.1 0.540425 0.540425 0.270212 -0.540425 4.7 3.1 0.530466 0.530466 0.265233 -0.530466 4.8 3.1 0.520482 0.520482 0.260241 -0.520482 4.9 3.1 0.510482 0.510482 0.255241 -0.510482 -5 3.2 0.494207 0.494207 0.247104 -0.494207 -4.9 3.2 0.50409 0.50409 0.252045 -0.50409 -4.8 3.2 0.513965 0.513965 0.256983 -0.513965 -4.7 3.2 0.523824 0.523824 0.261912 -0.523824 -4.6 3.2 0.533658 0.533658 0.266829 -0.533658 -4.5 3.2 0.54346 0.54346 0.27173 -0.54346 -4.4 3.2 0.55322 0.55322 0.27661 -0.55322 -4.3 3.2 0.56293 0.56293 0.281465 -0.56293 -4.2 3.2 0.572582 0.572582 0.286291 -0.572582 -4.1 3.2 0.582166 0.582166 0.291083 -0.582166 -4 3.2 0.591674 0.591674 0.295837 -0.591674 -3.9 3.2 0.601096 0.601096 0.300548 -0.601096 -3.8 3.2 0.610425 0.610425 0.305212 -0.610425 -3.7 3.2 0.61965 0.61965 0.309825 -0.61965 -3.6 3.2 0.628764 0.628764 0.314382 -0.628764 -3.5 3.2 0.637756 0.637756 0.318878 -0.637756 -3.4 3.2 0.646618 0.646618 0.323309 -0.646618 -3.3 3.2 0.655341 0.655341 0.32767 -0.655341 -3.2 3.2 0.663916 0.663916 0.331958 -0.663916 -3.1 3.2 0.672334 0.672334 0.336167 -0.672334 -3 3.2 0.680587 0.680587 0.340293 -0.680587 -2.9 3.2 0.688665 0.688665 0.344333 -0.688665 -2.8 3.2 0.696561 0.696561 0.34828 -0.696561 -2.7 3.2 0.704265 0.704265 0.352133 -0.704265 -2.6 3.2 0.71177 0.71177 0.355885 -0.71177 -2.5 3.2 0.719068 0.719068 0.359534 -0.719068 -2.4 3.2 0.726149 0.726149 0.363075 -0.726149 -2.3 3.2 0.733007 0.733007 0.366504 -0.733007 -2.2 3.2 0.739634 0.739634 0.369817 -0.739634 -2.1 3.2 0.746022 0.746022 0.373011 -0.746022 -2 3.2 0.752165 0.752165 0.376082 -0.752165 -1.9 3.2 0.758054 0.758054 0.379027 -0.758054 -1.8 3.2 0.763685 0.763685 0.381842 -0.763685 -1.7 3.2 0.769049 0.769049 0.384525 -0.769049 -1.6 3.2 0.774142 0.774142 0.387071 -0.774142 -1.5 3.2 0.778957 0.778957 0.389478 -0.778957 -1.4 3.2 0.783488 0.783488 0.391744 -0.783488 -1.3 3.2 0.78773 0.78773 0.393865 -0.78773 -1.2 3.2 0.791678 0.791678 0.395839 -0.791678 -1.1 3.2 0.795329 0.795329 0.397664 -0.795329 -1 3.2 0.798676 0.798676 0.399338 -0.798676 -0.9 3.2 0.801717 0.801717 0.400858 -0.801717 -0.8 3.2 0.804447 0.804447 0.402224 -0.804447 -0.7 3.2 0.806864 0.806864 0.403432 -0.806864 -0.6 3.2 0.808965 0.808965 0.404482 -0.808965 -0.5 3.2 0.810746 0.810746 0.405373 -0.810746 -0.4 3.2 0.812207 0.812207 0.406104 -0.812207 -0.3 3.2 0.813345 0.813345 0.406672 -0.813345 -0.2 3.2 0.814159 0.814159 0.407079 -0.814159 -0.1 3.2 0.814647 0.814647 0.407324 -0.814647 0 3.2 0.81481 0.81481 0.407405 -0.81481 0.1 3.2 0.814647 0.814647 0.407324 -0.814647 0.2 3.2 0.814159 0.814159 0.407079 -0.814159 0.3 3.2 0.813345 0.813345 0.406672 -0.813345 0.4 3.2 0.812207 0.812207 0.406104 -0.812207 0.5 3.2 0.810746 0.810746 0.405373 -0.810746 0.6 3.2 0.808965 0.808965 0.404482 -0.808965 0.7 3.2 0.806864 0.806864 0.403432 -0.806864 0.8 3.2 0.804447 0.804447 0.402224 -0.804447 0.9 3.2 0.801717 0.801717 0.400858 -0.801717 1 3.2 0.798676 0.798676 0.399338 -0.798676 1.1 3.2 0.795329 0.795329 0.397664 -0.795329 1.2 3.2 0.791678 0.791678 0.395839 -0.791678 1.3 3.2 0.78773 0.78773 0.393865 -0.78773 1.4 3.2 0.783488 0.783488 0.391744 -0.783488 1.5 3.2 0.778957 0.778957 0.389478 -0.778957 1.6 3.2 0.774142 0.774142 0.387071 -0.774142 1.7 3.2 0.769049 0.769049 0.384525 -0.769049 1.8 3.2 0.763685 0.763685 0.381842 -0.763685 1.9 3.2 0.758054 0.758054 0.379027 -0.758054 2 3.2 0.752165 0.752165 0.376082 -0.752165 2.1 3.2 0.746022 0.746022 0.373011 -0.746022 2.2 3.2 0.739634 0.739634 0.369817 -0.739634 2.3 3.2 0.733007 0.733007 0.366504 -0.733007 2.4 3.2 0.726149 0.726149 0.363075 -0.726149 2.5 3.2 0.719068 0.719068 0.359534 -0.719068 2.6 3.2 0.71177 0.71177 0.355885 -0.71177 2.7 3.2 0.704265 0.704265 0.352133 -0.704265 2.8 3.2 0.696561 0.696561 0.34828 -0.696561 2.9 3.2 0.688665 0.688665 0.344333 -0.688665 3 3.2 0.680587 0.680587 0.340293 -0.680587 3.1 3.2 0.672334 0.672334 0.336167 -0.672334 3.2 3.2 0.663916 0.663916 0.331958 -0.663916 3.3 3.2 0.655341 0.655341 0.32767 -0.655341 3.4 3.2 0.646618 0.646618 0.323309 -0.646618 3.5 3.2 0.637756 0.637756 0.318878 -0.637756 3.6 3.2 0.628764 0.628764 0.314382 -0.628764 3.7 3.2 0.61965 0.61965 0.309825 -0.61965 3.8 3.2 0.610425 0.610425 0.305212 -0.610425 3.9 3.2 0.601096 0.601096 0.300548 -0.601096 4 3.2 0.591674 0.591674 0.295837 -0.591674 4.1 3.2 0.582166 0.582166 0.291083 -0.582166 4.2 3.2 0.572582 0.572582 0.286291 -0.572582 4.3 3.2 0.56293 0.56293 0.281465 -0.56293 4.4 3.2 0.55322 0.55322 0.27661 -0.55322 4.5 3.2 0.54346 0.54346 0.27173 -0.54346 4.6 3.2 0.533658 0.533658 0.266829 -0.533658 4.7 3.2 0.523824 0.523824 0.261912 -0.523824 4.8 3.2 0.513965 0.513965 0.256983 -0.513965 4.9 3.2 0.50409 0.50409 0.252045 -0.50409 -5 3.3 0.487824 0.487824 0.243912 -0.487824 -4.9 3.3 0.497579 0.497579 0.24879 -0.497579 -4.8 3.3 0.507327 0.507327 0.253663 -0.507327 -4.7 3.3 0.517058 0.517058 0.258529 -0.517058 -4.6 3.3 0.526765 0.526765 0.263383 -0.526765 -4.5 3.3 0.53644 0.53644 0.26822 -0.53644 -4.4 3.3 0.546074 0.546074 0.273037 -0.546074 -4.3 3.3 0.555659 0.555659 0.27783 -0.555659 -4.2 3.3 0.565186 0.565186 0.282593 -0.565186 -4.1 3.3 0.574647 0.574647 0.287323 -0.574647 -4 3.3 0.584032 0.584032 0.292016 -0.584032 -3.9 3.3 0.593333 0.593333 0.296666 -0.593333 -3.8 3.3 0.602541 0.602541 0.30127 -0.602541 -3.7 3.3 0.611647 0.611647 0.305823 -0.611647 -3.6 3.3 0.620643 0.620643 0.310321 -0.620643 -3.5 3.3 0.629519 0.629519 0.314759 -0.629519 -3.4 3.3 0.638266 0.638266 0.319133 -0.638266 -3.3 3.3 0.646876 0.646876 0.323438 -0.646876 -3.2 3.3 0.655341 0.655341 0.32767 -0.655341 -3.1 3.3 0.66365 0.66365 0.331825 -0.66365 -3 3.3 0.671796 0.671796 0.335898 -0.671796 -2.9 3.3 0.679771 0.679771 0.339885 -0.679771 -2.8 3.3 0.687564 0.687564 0.343782 -0.687564 -2.7 3.3 0.695169 0.695169 0.347585 -0.695169 -2.6 3.3 0.702577 0.702577 0.351289 -0.702577 -2.5 3.3 0.70978 0.70978 0.35489 -0.70978 -2.4 3.3 0.71677 0.71677 0.358385 -0.71677 -2.3 3.3 0.72354 0.72354 0.36177 -0.72354 -2.2 3.3 0.730081 0.730081 0.36504 -0.730081 -2.1 3.3 0.736387 0.736387 0.368193 -0.736387 -2 3.3 0.74245 0.74245 0.371225 -0.74245 -1.9 3.3 0.748264 0.748264 0.374132 -0.748264 -1.8 3.3 0.753821 0.753821 0.376911 -0.753821 -1.7 3.3 0.759117 0.759117 0.379558 -0.759117 -1.6 3.3 0.764143 0.764143 0.382072 -0.764143 -1.5 3.3 0.768896 0.768896 0.384448 -0.768896 -1.4 3.3 0.773368 0.773368 0.386684 -0.773368 -1.3 3.3 0.777556 0.777556 0.388778 -0.777556 -1.2 3.3 0.781453 0.781453 0.390727 -0.781453 -1.1 3.3 0.785056 0.785056 0.392528 -0.785056 -1 3.3 0.78836 0.78836 0.39418 -0.78836 -0.9 3.3 0.791362 0.791362 0.395681 -0.791362 -0.8 3.3 0.794057 0.794057 0.397029 -0.794057 -0.7 3.3 0.796443 0.796443 0.398221 -0.796443 -0.6 3.3 0.798516 0.798516 0.399258 -0.798516 -0.5 3.3 0.800275 0.800275 0.400137 -0.800275 -0.4 3.3 0.801717 0.801717 0.400858 -0.801717 -0.3 3.3 0.80284 0.80284 0.40142 -0.80284 -0.2 3.3 0.803643 0.803643 0.401822 -0.803643 -0.1 3.3 0.804125 0.804125 0.402063 -0.804125 0 3.3 0.804286 0.804286 0.402143 -0.804286 0.1 3.3 0.804125 0.804125 0.402063 -0.804125 0.2 3.3 0.803643 0.803643 0.401822 -0.803643 0.3 3.3 0.80284 0.80284 0.40142 -0.80284 0.4 3.3 0.801717 0.801717 0.400858 -0.801717 0.5 3.3 0.800275 0.800275 0.400137 -0.800275 0.6 3.3 0.798516 0.798516 0.399258 -0.798516 0.7 3.3 0.796443 0.796443 0.398221 -0.796443 0.8 3.3 0.794057 0.794057 0.397029 -0.794057 0.9 3.3 0.791362 0.791362 0.395681 -0.791362 1 3.3 0.78836 0.78836 0.39418 -0.78836 1.1 3.3 0.785056 0.785056 0.392528 -0.785056 1.2 3.3 0.781453 0.781453 0.390727 -0.781453 1.3 3.3 0.777556 0.777556 0.388778 -0.777556 1.4 3.3 0.773368 0.773368 0.386684 -0.773368 1.5 3.3 0.768896 0.768896 0.384448 -0.768896 1.6 3.3 0.764143 0.764143 0.382072 -0.764143 1.7 3.3 0.759117 0.759117 0.379558 -0.759117 1.8 3.3 0.753821 0.753821 0.376911 -0.753821 1.9 3.3 0.748264 0.748264 0.374132 -0.748264 2 3.3 0.74245 0.74245 0.371225 -0.74245 2.1 3.3 0.736387 0.736387 0.368193 -0.736387 2.2 3.3 0.730081 0.730081 0.36504 -0.730081 2.3 3.3 0.72354 0.72354 0.36177 -0.72354 2.4 3.3 0.71677 0.71677 0.358385 -0.71677 2.5 3.3 0.70978 0.70978 0.35489 -0.70978 2.6 3.3 0.702577 0.702577 0.351289 -0.702577 2.7 3.3 0.695169 0.695169 0.347585 -0.695169 2.8 3.3 0.687564 0.687564 0.343782 -0.687564 2.9 3.3 0.679771 0.679771 0.339885 -0.679771 3 3.3 0.671796 0.671796 0.335898 -0.671796 3.1 3.3 0.66365 0.66365 0.331825 -0.66365 3.2 3.3 0.655341 0.655341 0.32767 -0.655341 3.3 3.3 0.646876 0.646876 0.323438 -0.646876 3.4 3.3 0.638266 0.638266 0.319133 -0.638266 3.5 3.3 0.629519 0.629519 0.314759 -0.629519 3.6 3.3 0.620643 0.620643 0.310321 -0.620643 3.7 3.3 0.611647 0.611647 0.305823 -0.611647 3.8 3.3 0.602541 0.602541 0.30127 -0.602541 3.9 3.3 0.593333 0.593333 0.296666 -0.593333 4 3.3 0.584032 0.584032 0.292016 -0.584032 4.1 3.3 0.574647 0.574647 0.287323 -0.574647 4.2 3.3 0.565186 0.565186 0.282593 -0.565186 4.3 3.3 0.555659 0.555659 0.27783 -0.555659 4.4 3.3 0.546074 0.546074 0.273037 -0.546074 4.5 3.3 0.53644 0.53644 0.26822 -0.53644 4.6 3.3 0.526765 0.526765 0.263383 -0.526765 4.7 3.3 0.517058 0.517058 0.258529 -0.517058 4.8 3.3 0.507327 0.507327 0.253663 -0.507327 4.9 3.3 0.497579 0.497579 0.24879 -0.497579 -5 3.4 0.481331 0.481331 0.240666 -0.481331 -4.9 3.4 0.490956 0.490956 0.245478 -0.490956 -4.8 3.4 0.500574 0.500574 0.250287 -0.500574 -4.7 3.4 0.510176 0.510176 0.255088 -0.510176 -4.6 3.4 0.519754 0.519754 0.259877 -0.519754 -4.5 3.4 0.5293 0.5293 0.26465 -0.5293 -4.4 3.4 0.538806 0.538806 0.269403 -0.538806 -4.3 3.4 0.548263 0.548263 0.274132 -0.548263 -4.2 3.4 0.557663 0.557663 0.278832 -0.557663 -4.1 3.4 0.566998 0.566998 0.283499 -0.566998 -4 3.4 0.576258 0.576258 0.288129 -0.576258 -3.9 3.4 0.585435 0.585435 0.292718 -0.585435 -3.8 3.4 0.594521 0.594521 0.29726 -0.594521 -3.7 3.4 0.603506 0.603506 0.301753 -0.603506 -3.6 3.4 0.612381 0.612381 0.306191 -0.612381 -3.5 3.4 0.621139 0.621139 0.31057 -0.621139 -3.4 3.4 0.62977 0.62977 0.314885 -0.62977 -3.3 3.4 0.638266 0.638266 0.319133 -0.638266 -3.2 3.4 0.646618 0.646618 0.323309 -0.646618 -3.1 3.4 0.654817 0.654817 0.327408 -0.654817 -3 3.4 0.662854 0.662854 0.331427 -0.662854 -2.9 3.4 0.670722 0.670722 0.335361 -0.670722 -2.8 3.4 0.678412 0.678412 0.339206 -0.678412 -2.7 3.4 0.685916 0.685916 0.342958 -0.685916 -2.6 3.4 0.693225 0.693225 0.346613 -0.693225 -2.5 3.4 0.700333 0.700333 0.350166 -0.700333 -2.4 3.4 0.70723 0.70723 0.353615 -0.70723 -2.3 3.4 0.713909 0.713909 0.356954 -0.713909 -2.2 3.4 0.720363 0.720363 0.360182 -0.720363 -2.1 3.4 0.726585 0.726585 0.363292 -0.726585 -2 3.4 0.732567 0.732567 0.366284 -0.732567 -1.9 3.4 0.738304 0.738304 0.369152 -0.738304 -1.8 3.4 0.743787 0.743787 0.371894 -0.743787 -1.7 3.4 0.749012 0.749012 0.374506 -0.749012 -1.6 3.4 0.753972 0.753972 0.376986 -0.753972 -1.5 3.4 0.758661 0.758661 0.379331 -0.758661 -1.4 3.4 0.763074 0.763074 0.381537 -0.763074 -1.3 3.4 0.767206 0.767206 0.383603 -0.767206 -1.2 3.4 0.771052 0.771052 0.385526 -0.771052 -1.1 3.4 0.774607 0.774607 0.387303 -0.774607 -1 3.4 0.777867 0.777867 0.388933 -0.777867 -0.9 3.4 0.780828 0.780828 0.390414 -0.780828 -0.8 3.4 0.783488 0.783488 0.391744 -0.783488 -0.7 3.4 0.785842 0.785842 0.392921 -0.785842 -0.6 3.4 0.787887 0.787887 0.393944 -0.787887 -0.5 3.4 0.789623 0.789623 0.394811 -0.789623 -0.4 3.4 0.791045 0.791045 0.395523 -0.791045 -0.3 3.4 0.792154 0.792154 0.396077 -0.792154 -0.2 3.4 0.792946 0.792946 0.396473 -0.792946 -0.1 3.4 0.793422 0.793422 0.396711 -0.793422 0 3.4 0.793581 0.793581 0.39679 -0.793581 0.1 3.4 0.793422 0.793422 0.396711 -0.793422 0.2 3.4 0.792946 0.792946 0.396473 -0.792946 0.3 3.4 0.792154 0.792154 0.396077 -0.792154 0.4 3.4 0.791045 0.791045 0.395523 -0.791045 0.5 3.4 0.789623 0.789623 0.394811 -0.789623 0.6 3.4 0.787887 0.787887 0.393944 -0.787887 0.7 3.4 0.785842 0.785842 0.392921 -0.785842 0.8 3.4 0.783488 0.783488 0.391744 -0.783488 0.9 3.4 0.780828 0.780828 0.390414 -0.780828 1 3.4 0.777867 0.777867 0.388933 -0.777867 1.1 3.4 0.774607 0.774607 0.387303 -0.774607 1.2 3.4 0.771052 0.771052 0.385526 -0.771052 1.3 3.4 0.767206 0.767206 0.383603 -0.767206 1.4 3.4 0.763074 0.763074 0.381537 -0.763074 1.5 3.4 0.758661 0.758661 0.379331 -0.758661 1.6 3.4 0.753972 0.753972 0.376986 -0.753972 1.7 3.4 0.749012 0.749012 0.374506 -0.749012 1.8 3.4 0.743787 0.743787 0.371894 -0.743787 1.9 3.4 0.738304 0.738304 0.369152 -0.738304 2 3.4 0.732567 0.732567 0.366284 -0.732567 2.1 3.4 0.726585 0.726585 0.363292 -0.726585 2.2 3.4 0.720363 0.720363 0.360182 -0.720363 2.3 3.4 0.713909 0.713909 0.356954 -0.713909 2.4 3.4 0.70723 0.70723 0.353615 -0.70723 2.5 3.4 0.700333 0.700333 0.350166 -0.700333 2.6 3.4 0.693225 0.693225 0.346613 -0.693225 2.7 3.4 0.685916 0.685916 0.342958 -0.685916 2.8 3.4 0.678412 0.678412 0.339206 -0.678412 2.9 3.4 0.670722 0.670722 0.335361 -0.670722 3 3.4 0.662854 0.662854 0.331427 -0.662854 3.1 3.4 0.654817 0.654817 0.327408 -0.654817 3.2 3.4 0.646618 0.646618 0.323309 -0.646618 3.3 3.4 0.638266 0.638266 0.319133 -0.638266 3.4 3.4 0.62977 0.62977 0.314885 -0.62977 3.5 3.4 0.621139 0.621139 0.31057 -0.621139 3.6 3.4 0.612381 0.612381 0.306191 -0.612381 3.7 3.4 0.603506 0.603506 0.301753 -0.603506 3.8 3.4 0.594521 0.594521 0.29726 -0.594521 3.9 3.4 0.585435 0.585435 0.292718 -0.585435 4 3.4 0.576258 0.576258 0.288129 -0.576258 4.1 3.4 0.566998 0.566998 0.283499 -0.566998 4.2 3.4 0.557663 0.557663 0.278832 -0.557663 4.3 3.4 0.548263 0.548263 0.274132 -0.548263 4.4 3.4 0.538806 0.538806 0.269403 -0.538806 4.5 3.4 0.5293 0.5293 0.26465 -0.5293 4.6 3.4 0.519754 0.519754 0.259877 -0.519754 4.7 3.4 0.510176 0.510176 0.255088 -0.510176 4.8 3.4 0.500574 0.500574 0.250287 -0.500574 4.9 3.4 0.490956 0.490956 0.245478 -0.490956 -5 3.5 0.474734 0.474734 0.237367 -0.474734 -4.9 3.5 0.484228 0.484228 0.242114 -0.484228 -4.8 3.5 0.493713 0.493713 0.246857 -0.493713 -4.7 3.5 0.503184 0.503184 0.251592 -0.503184 -4.6 3.5 0.51263 0.51263 0.256315 -0.51263 -4.5 3.5 0.522046 0.522046 0.261023 -0.522046 -4.4 3.5 0.531421 0.531421 0.265711 -0.531421 -4.3 3.5 0.540749 0.540749 0.270375 -0.540749 -4.2 3.5 0.55002 0.55002 0.27501 -0.55002 -4.1 3.5 0.559227 0.559227 0.279613 -0.559227 -4 3.5 0.56836 0.56836 0.28418 -0.56836 -3.9 3.5 0.577412 0.577412 0.288706 -0.577412 -3.8 3.5 0.586373 0.586373 0.293186 -0.586373 -3.7 3.5 0.595234 0.595234 0.297617 -0.595234 -3.6 3.5 0.603989 0.603989 0.301994 -0.603989 -3.5 3.5 0.612626 0.612626 0.306313 -0.612626 -3.4 3.5 0.621139 0.621139 0.31057 -0.621139 -3.3 3.5 0.629519 0.629519 0.314759 -0.629519 -3.2 3.5 0.637756 0.637756 0.318878 -0.637756 -3.1 3.5 0.645842 0.645842 0.322921 -0.645842 -3 3.5 0.65377 0.65377 0.326885 -0.65377 -2.9 3.5 0.66153 0.66153 0.330765 -0.66153 -2.8 3.5 0.669115 0.669115 0.334557 -0.669115 -2.7 3.5 0.676515 0.676515 0.338258 -0.676515 -2.6 3.5 0.683725 0.683725 0.341862 -0.683725 -2.5 3.5 0.690734 0.690734 0.345367 -0.690734 -2.4 3.5 0.697537 0.697537 0.348768 -0.697537 -2.3 3.5 0.704125 0.704125 0.352062 -0.704125 -2.2 3.5 0.71049 0.71049 0.355245 -0.71049 -2.1 3.5 0.716627 0.716627 0.358313 -0.716627 -2 3.5 0.722527 0.722527 0.361264 -0.722527 -1.9 3.5 0.728185 0.728185 0.364093 -0.728185 -1.8 3.5 0.733594 0.733594 0.366797 -0.733594 -1.7 3.5 0.738747 0.738747 0.369373 -0.738747 -1.6 3.5 0.743639 0.743639 0.371819 -0.743639 -1.5 3.5 0.748264 0.748264 0.374132 -0.748264 -1.4 3.5 0.752616 0.752616 0.376308 -0.752616 -1.3 3.5 0.756691 0.756691 0.378346 -0.756691 -1.2 3.5 0.760484 0.760484 0.380242 -0.760484 -1.1 3.5 0.76399 0.76399 0.381995 -0.76399 -1 3.5 0.767206 0.767206 0.383603 -0.767206 -0.9 3.5 0.770127 0.770127 0.385063 -0.770127 -0.8 3.5 0.77275 0.77275 0.386375 -0.77275 -0.7 3.5 0.775071 0.775071 0.387536 -0.775071 -0.6 3.5 0.777089 0.777089 0.388545 -0.777089 -0.5 3.5 0.778801 0.778801 0.3894 -0.778801 -0.4 3.5 0.780204 0.780204 0.390102 -0.780204 -0.3 3.5 0.781297 0.781297 0.390648 -0.781297 -0.2 3.5 0.782079 0.782079 0.391039 -0.782079 -0.1 3.5 0.782548 0.782548 0.391274 -0.782548 0 3.5 0.782705 0.782705 0.391352 -0.782705 0.1 3.5 0.782548 0.782548 0.391274 -0.782548 0.2 3.5 0.782079 0.782079 0.391039 -0.782079 0.3 3.5 0.781297 0.781297 0.390648 -0.781297 0.4 3.5 0.780204 0.780204 0.390102 -0.780204 0.5 3.5 0.778801 0.778801 0.3894 -0.778801 0.6 3.5 0.777089 0.777089 0.388545 -0.777089 0.7 3.5 0.775071 0.775071 0.387536 -0.775071 0.8 3.5 0.77275 0.77275 0.386375 -0.77275 0.9 3.5 0.770127 0.770127 0.385063 -0.770127 1 3.5 0.767206 0.767206 0.383603 -0.767206 1.1 3.5 0.76399 0.76399 0.381995 -0.76399 1.2 3.5 0.760484 0.760484 0.380242 -0.760484 1.3 3.5 0.756691 0.756691 0.378346 -0.756691 1.4 3.5 0.752616 0.752616 0.376308 -0.752616 1.5 3.5 0.748264 0.748264 0.374132 -0.748264 1.6 3.5 0.743639 0.743639 0.371819 -0.743639 1.7 3.5 0.738747 0.738747 0.369373 -0.738747 1.8 3.5 0.733594 0.733594 0.366797 -0.733594 1.9 3.5 0.728185 0.728185 0.364093 -0.728185 2 3.5 0.722527 0.722527 0.361264 -0.722527 2.1 3.5 0.716627 0.716627 0.358313 -0.716627 2.2 3.5 0.71049 0.71049 0.355245 -0.71049 2.3 3.5 0.704125 0.704125 0.352062 -0.704125 2.4 3.5 0.697537 0.697537 0.348768 -0.697537 2.5 3.5 0.690734 0.690734 0.345367 -0.690734 2.6 3.5 0.683725 0.683725 0.341862 -0.683725 2.7 3.5 0.676515 0.676515 0.338258 -0.676515 2.8 3.5 0.669115 0.669115 0.334557 -0.669115 2.9 3.5 0.66153 0.66153 0.330765 -0.66153 3 3.5 0.65377 0.65377 0.326885 -0.65377 3.1 3.5 0.645842 0.645842 0.322921 -0.645842 3.2 3.5 0.637756 0.637756 0.318878 -0.637756 3.3 3.5 0.629519 0.629519 0.314759 -0.629519 3.4 3.5 0.621139 0.621139 0.31057 -0.621139 3.5 3.5 0.612626 0.612626 0.306313 -0.612626 3.6 3.5 0.603989 0.603989 0.301994 -0.603989 3.7 3.5 0.595234 0.595234 0.297617 -0.595234 3.8 3.5 0.586373 0.586373 0.293186 -0.586373 3.9 3.5 0.577412 0.577412 0.288706 -0.577412 4 3.5 0.56836 0.56836 0.28418 -0.56836 4.1 3.5 0.559227 0.559227 0.279613 -0.559227 4.2 3.5 0.55002 0.55002 0.27501 -0.55002 4.3 3.5 0.540749 0.540749 0.270375 -0.540749 4.4 3.5 0.531421 0.531421 0.265711 -0.531421 4.5 3.5 0.522046 0.522046 0.261023 -0.522046 4.6 3.5 0.51263 0.51263 0.256315 -0.51263 4.7 3.5 0.503184 0.503184 0.251592 -0.503184 4.8 3.5 0.493713 0.493713 0.246857 -0.493713 4.9 3.5 0.484228 0.484228 0.242114 -0.484228 -5 3.6 0.468041 0.468041 0.23402 -0.468041 -4.9 3.6 0.4774 0.4774 0.2387 -0.4774 -4.8 3.6 0.486752 0.486752 0.243376 -0.486752 -4.7 3.6 0.496089 0.496089 0.248044 -0.496089 -4.6 3.6 0.505403 0.505403 0.252701 -0.505403 -4.5 3.6 0.514685 0.514685 0.257343 -0.514685 -4.4 3.6 0.523929 0.523929 0.261964 -0.523929 -4.3 3.6 0.533125 0.533125 0.266562 -0.533125 -4.2 3.6 0.542265 0.542265 0.271133 -0.542265 -4.1 3.6 0.551342 0.551342 0.275671 -0.551342 -4 3.6 0.560346 0.560346 0.280173 -0.560346 -3.9 3.6 0.56927 0.56927 0.284635 -0.56927 -3.8 3.6 0.578105 0.578105 0.289052 -0.578105 -3.7 3.6 0.586842 0.586842 0.293421 -0.586842 -3.6 3.6 0.595473 0.595473 0.297736 -0.595473 -3.5 3.6 0.603989 0.603989 0.301994 -0.603989 -3.4 3.6 0.612381 0.612381 0.306191 -0.612381 -3.3 3.6 0.620643 0.620643 0.310321 -0.620643 -3.2 3.6 0.628764 0.628764 0.314382 -0.628764 -3.1 3.6 0.636736 0.636736 0.318368 -0.636736 -3 3.6 0.644552 0.644552 0.322276 -0.644552 -2.9 3.6 0.652203 0.652203 0.326101 -0.652203 -2.8 3.6 0.65968 0.65968 0.32984 -0.65968 -2.7 3.6 0.666977 0.666977 0.333488 -0.666977 -2.6 3.6 0.674084 0.674084 0.337042 -0.674084 -2.5 3.6 0.680995 0.680995 0.340498 -0.680995 -2.4 3.6 0.687702 0.687702 0.343851 -0.687702 -2.3 3.6 0.694197 0.694197 0.347098 -0.694197 -2.2 3.6 0.700473 0.700473 0.350236 -0.700473 -2.1 3.6 0.706523 0.706523 0.353261 -0.706523 -2 3.6 0.71234 0.71234 0.35617 -0.71234 -1.9 3.6 0.717918 0.717918 0.358959 -0.717918 -1.8 3.6 0.72325 0.72325 0.361625 -0.72325 -1.7 3.6 0.728331 0.728331 0.364165 -0.728331 -1.6 3.6 0.733154 0.733154 0.366577 -0.733154 -1.5 3.6 0.737713 0.737713 0.368857 -0.737713 -1.4 3.6 0.742004 0.742004 0.371002 -0.742004 -1.3 3.6 0.746022 0.746022 0.373011 -0.746022 -1.2 3.6 0.749762 0.749762 0.374881 -0.749762 -1.1 3.6 0.753218 0.753218 0.376609 -0.753218 -1 3.6 0.756389 0.756389 0.378194 -0.756389 -0.9 3.6 0.759268 0.759268 0.379634 -0.759268 -0.8 3.6 0.761854 0.761854 0.380927 -0.761854 -0.7 3.6 0.764143 0.764143 0.382072 -0.764143 -0.6 3.6 0.766133 0.766133 0.383066 -0.766133 -0.5 3.6 0.76782 0.76782 0.38391 -0.76782 -0.4 3.6 0.769203 0.769203 0.384602 -0.769203 -0.3 3.6 0.770281 0.770281 0.38514 -0.770281 -0.2 3.6 0.771052 0.771052 0.385526 -0.771052 -0.1 3.6 0.771514 0.771514 0.385757 -0.771514 0 3.6 0.771669 0.771669 0.385834 -0.771669 0.1 3.6 0.771514 0.771514 0.385757 -0.771514 0.2 3.6 0.771052 0.771052 0.385526 -0.771052 0.3 3.6 0.770281 0.770281 0.38514 -0.770281 0.4 3.6 0.769203 0.769203 0.384602 -0.769203 0.5 3.6 0.76782 0.76782 0.38391 -0.76782 0.6 3.6 0.766133 0.766133 0.383066 -0.766133 0.7 3.6 0.764143 0.764143 0.382072 -0.764143 0.8 3.6 0.761854 0.761854 0.380927 -0.761854 0.9 3.6 0.759268 0.759268 0.379634 -0.759268 1 3.6 0.756389 0.756389 0.378194 -0.756389 1.1 3.6 0.753218 0.753218 0.376609 -0.753218 1.2 3.6 0.749762 0.749762 0.374881 -0.749762 1.3 3.6 0.746022 0.746022 0.373011 -0.746022 1.4 3.6 0.742004 0.742004 0.371002 -0.742004 1.5 3.6 0.737713 0.737713 0.368857 -0.737713 1.6 3.6 0.733154 0.733154 0.366577 -0.733154 1.7 3.6 0.728331 0.728331 0.364165 -0.728331 1.8 3.6 0.72325 0.72325 0.361625 -0.72325 1.9 3.6 0.717918 0.717918 0.358959 -0.717918 2 3.6 0.71234 0.71234 0.35617 -0.71234 2.1 3.6 0.706523 0.706523 0.353261 -0.706523 2.2 3.6 0.700473 0.700473 0.350236 -0.700473 2.3 3.6 0.694197 0.694197 0.347098 -0.694197 2.4 3.6 0.687702 0.687702 0.343851 -0.687702 2.5 3.6 0.680995 0.680995 0.340498 -0.680995 2.6 3.6 0.674084 0.674084 0.337042 -0.674084 2.7 3.6 0.666977 0.666977 0.333488 -0.666977 2.8 3.6 0.65968 0.65968 0.32984 -0.65968 2.9 3.6 0.652203 0.652203 0.326101 -0.652203 3 3.6 0.644552 0.644552 0.322276 -0.644552 3.1 3.6 0.636736 0.636736 0.318368 -0.636736 3.2 3.6 0.628764 0.628764 0.314382 -0.628764 3.3 3.6 0.620643 0.620643 0.310321 -0.620643 3.4 3.6 0.612381 0.612381 0.306191 -0.612381 3.5 3.6 0.603989 0.603989 0.301994 -0.603989 3.6 3.6 0.595473 0.595473 0.297736 -0.595473 3.7 3.6 0.586842 0.586842 0.293421 -0.586842 3.8 3.6 0.578105 0.578105 0.289052 -0.578105 3.9 3.6 0.56927 0.56927 0.284635 -0.56927 4 3.6 0.560346 0.560346 0.280173 -0.560346 4.1 3.6 0.551342 0.551342 0.275671 -0.551342 4.2 3.6 0.542265 0.542265 0.271133 -0.542265 4.3 3.6 0.533125 0.533125 0.266562 -0.533125 4.4 3.6 0.523929 0.523929 0.261964 -0.523929 4.5 3.6 0.514685 0.514685 0.257343 -0.514685 4.6 3.6 0.505403 0.505403 0.252701 -0.505403 4.7 3.6 0.496089 0.496089 0.248044 -0.496089 4.8 3.6 0.486752 0.486752 0.243376 -0.486752 4.9 3.6 0.4774 0.4774 0.2387 -0.4774 -5 3.7 0.461257 0.461257 0.230628 -0.461257 -4.9 3.7 0.470481 0.470481 0.23524 -0.470481 -4.8 3.7 0.479697 0.479697 0.239849 -0.479697 -4.7 3.7 0.488899 0.488899 0.244449 -0.488899 -4.6 3.7 0.498077 0.498077 0.249039 -0.498077 -4.5 3.7 0.507225 0.507225 0.253613 -0.507225 -4.4 3.7 0.516335 0.516335 0.258167 -0.516335 -4.3 3.7 0.525398 0.525398 0.262699 -0.525398 -4.2 3.7 0.534406 0.534406 0.267203 -0.534406 -4.1 3.7 0.543351 0.543351 0.271675 -0.543351 -4 3.7 0.552225 0.552225 0.276112 -0.552225 -3.9 3.7 0.561019 0.561019 0.28051 -0.561019 -3.8 3.7 0.569726 0.569726 0.284863 -0.569726 -3.7 3.7 0.578336 0.578336 0.289168 -0.578336 -3.6 3.7 0.586842 0.586842 0.293421 -0.586842 -3.5 3.7 0.595234 0.595234 0.297617 -0.595234 -3.4 3.7 0.603506 0.603506 0.301753 -0.603506 -3.3 3.7 0.611647 0.611647 0.305823 -0.611647 -3.2 3.7 0.61965 0.61965 0.309825 -0.61965 -3.1 3.7 0.627507 0.627507 0.313754 -0.627507 -3 3.7 0.63521 0.63521 0.317605 -0.63521 -2.9 3.7 0.64275 0.64275 0.321375 -0.64275 -2.8 3.7 0.650119 0.650119 0.325059 -0.650119 -2.7 3.7 0.65731 0.65731 0.328655 -0.65731 -2.6 3.7 0.664314 0.664314 0.332157 -0.664314 -2.5 3.7 0.671125 0.671125 0.335562 -0.671125 -2.4 3.7 0.677734 0.677734 0.338867 -0.677734 -2.3 3.7 0.684135 0.684135 0.342068 -0.684135 -2.2 3.7 0.69032 0.69032 0.34516 -0.69032 -2.1 3.7 0.696282 0.696282 0.348141 -0.696282 -2 3.7 0.702015 0.702015 0.351008 -0.702015 -1.9 3.7 0.707512 0.707512 0.353756 -0.707512 -1.8 3.7 0.712767 0.712767 0.356384 -0.712767 -1.7 3.7 0.717774 0.717774 0.358887 -0.717774 -1.6 3.7 0.722527 0.722527 0.361264 -0.722527 -1.5 3.7 0.727021 0.727021 0.36351 -0.727021 -1.4 3.7 0.73125 0.73125 0.365625 -0.73125 -1.3 3.7 0.735209 0.735209 0.367605 -0.735209 -1.2 3.7 0.738895 0.738895 0.369447 -0.738895 -1.1 3.7 0.742301 0.742301 0.371151 -0.742301 -1 3.7 0.745426 0.745426 0.372713 -0.745426 -0.9 3.7 0.748264 0.748264 0.374132 -0.748264 -0.8 3.7 0.750812 0.750812 0.375406 -0.750812 -0.7 3.7 0.753068 0.753068 0.376534 -0.753068 -0.6 3.7 0.755028 0.755028 0.377514 -0.755028 -0.5 3.7 0.756691 0.756691 0.378346 -0.756691 -0.4 3.7 0.758054 0.758054 0.379027 -0.758054 -0.3 3.7 0.759117 0.759117 0.379558 -0.759117 -0.2 3.7 0.759876 0.759876 0.379938 -0.759876 -0.1 3.7 0.760332 0.760332 0.380166 -0.760332 0 3.7 0.760484 0.760484 0.380242 -0.760484 0.1 3.7 0.760332 0.760332 0.380166 -0.760332 0.2 3.7 0.759876 0.759876 0.379938 -0.759876 0.3 3.7 0.759117 0.759117 0.379558 -0.759117 0.4 3.7 0.758054 0.758054 0.379027 -0.758054 0.5 3.7 0.756691 0.756691 0.378346 -0.756691 0.6 3.7 0.755028 0.755028 0.377514 -0.755028 0.7 3.7 0.753068 0.753068 0.376534 -0.753068 0.8 3.7 0.750812 0.750812 0.375406 -0.750812 0.9 3.7 0.748264 0.748264 0.374132 -0.748264 1 3.7 0.745426 0.745426 0.372713 -0.745426 1.1 3.7 0.742301 0.742301 0.371151 -0.742301 1.2 3.7 0.738895 0.738895 0.369447 -0.738895 1.3 3.7 0.735209 0.735209 0.367605 -0.735209 1.4 3.7 0.73125 0.73125 0.365625 -0.73125 1.5 3.7 0.727021 0.727021 0.36351 -0.727021 1.6 3.7 0.722527 0.722527 0.361264 -0.722527 1.7 3.7 0.717774 0.717774 0.358887 -0.717774 1.8 3.7 0.712767 0.712767 0.356384 -0.712767 1.9 3.7 0.707512 0.707512 0.353756 -0.707512 2 3.7 0.702015 0.702015 0.351008 -0.702015 2.1 3.7 0.696282 0.696282 0.348141 -0.696282 2.2 3.7 0.69032 0.69032 0.34516 -0.69032 2.3 3.7 0.684135 0.684135 0.342068 -0.684135 2.4 3.7 0.677734 0.677734 0.338867 -0.677734 2.5 3.7 0.671125 0.671125 0.335562 -0.671125 2.6 3.7 0.664314 0.664314 0.332157 -0.664314 2.7 3.7 0.65731 0.65731 0.328655 -0.65731 2.8 3.7 0.650119 0.650119 0.325059 -0.650119 2.9 3.7 0.64275 0.64275 0.321375 -0.64275 3 3.7 0.63521 0.63521 0.317605 -0.63521 3.1 3.7 0.627507 0.627507 0.313754 -0.627507 3.2 3.7 0.61965 0.61965 0.309825 -0.61965 3.3 3.7 0.611647 0.611647 0.305823 -0.611647 3.4 3.7 0.603506 0.603506 0.301753 -0.603506 3.5 3.7 0.595234 0.595234 0.297617 -0.595234 3.6 3.7 0.586842 0.586842 0.293421 -0.586842 3.7 3.7 0.578336 0.578336 0.289168 -0.578336 3.8 3.7 0.569726 0.569726 0.284863 -0.569726 3.9 3.7 0.561019 0.561019 0.28051 -0.561019 4 3.7 0.552225 0.552225 0.276112 -0.552225 4.1 3.7 0.543351 0.543351 0.271675 -0.543351 4.2 3.7 0.534406 0.534406 0.267203 -0.534406 4.3 3.7 0.525398 0.525398 0.262699 -0.525398 4.4 3.7 0.516335 0.516335 0.258167 -0.516335 4.5 3.7 0.507225 0.507225 0.253613 -0.507225 4.6 3.7 0.498077 0.498077 0.249039 -0.498077 4.7 3.7 0.488899 0.488899 0.244449 -0.488899 4.8 3.7 0.479697 0.479697 0.239849 -0.479697 4.9 3.7 0.470481 0.470481 0.23524 -0.470481 -5 3.8 0.45439 0.45439 0.227195 -0.45439 -4.9 3.8 0.463476 0.463476 0.231738 -0.463476 -4.8 3.8 0.472556 0.472556 0.236278 -0.472556 -4.7 3.8 0.48162 0.48162 0.24081 -0.48162 -4.6 3.8 0.490662 0.490662 0.245331 -0.490662 -4.5 3.8 0.499674 0.499674 0.249837 -0.499674 -4.4 3.8 0.508648 0.508648 0.254324 -0.508648 -4.3 3.8 0.517575 0.517575 0.258788 -0.517575 -4.2 3.8 0.526449 0.526449 0.263225 -0.526449 -4.1 3.8 0.535261 0.535261 0.267631 -0.535261 -4 3.8 0.544003 0.544003 0.272002 -0.544003 -3.9 3.8 0.552667 0.552667 0.276333 -0.552667 -3.8 3.8 0.561244 0.561244 0.280622 -0.561244 -3.7 3.8 0.569726 0.569726 0.284863 -0.569726 -3.6 3.8 0.578105 0.578105 0.289052 -0.578105 -3.5 3.8 0.586373 0.586373 0.293186 -0.586373 -3.4 3.8 0.594521 0.594521 0.29726 -0.594521 -3.3 3.8 0.602541 0.602541 0.30127 -0.602541 -3.2 3.8 0.610425 0.610425 0.305212 -0.610425 -3.1 3.8 0.618165 0.618165 0.309082 -0.618165 -3 3.8 0.625753 0.625753 0.312876 -0.625753 -2.9 3.8 0.63318 0.63318 0.31659 -0.63318 -2.8 3.8 0.64044 0.64044 0.32022 -0.64044 -2.7 3.8 0.647524 0.647524 0.323762 -0.647524 -2.6 3.8 0.654424 0.654424 0.327212 -0.654424 -2.5 3.8 0.661133 0.661133 0.330567 -0.661133 -2.4 3.8 0.667644 0.667644 0.333822 -0.667644 -2.3 3.8 0.67395 0.67395 0.336975 -0.67395 -2.2 3.8 0.680042 0.680042 0.340021 -0.680042 -2.1 3.8 0.685916 0.685916 0.342958 -0.685916 -2 3.8 0.691564 0.691564 0.345782 -0.691564 -1.9 3.8 0.696979 0.696979 0.348489 -0.696979 -1.8 3.8 0.702156 0.702156 0.351078 -0.702156 -1.7 3.8 0.707088 0.707088 0.353544 -0.707088 -1.6 3.8 0.71177 0.71177 0.355885 -0.71177 -1.5 3.8 0.716197 0.716197 0.358099 -0.716197 -1.4 3.8 0.720363 0.720363 0.360182 -0.720363 -1.3 3.8 0.724264 0.724264 0.362132 -0.724264 -1.2 3.8 0.727894 0.727894 0.363947 -0.727894 -1.1 3.8 0.73125 0.73125 0.365625 -0.73125 -1 3.8 0.734328 0.734328 0.367164 -0.734328 -0.9 3.8 0.737123 0.737123 0.368562 -0.737123 -0.8 3.8 0.739634 0.739634 0.369817 -0.739634 -0.7 3.8 0.741856 0.741856 0.370928 -0.741856 -0.6 3.8 0.743787 0.743787 0.371894 -0.743787 -0.5 3.8 0.745426 0.745426 0.372713 -0.745426 -0.4 3.8 0.746769 0.746769 0.373384 -0.746769 -0.3 3.8 0.747815 0.747815 0.373907 -0.747815 -0.2 3.8 0.748563 0.748563 0.374281 -0.748563 -0.1 3.8 0.749012 0.749012 0.374506 -0.749012 0 3.8 0.749162 0.749162 0.374581 -0.749162 0.1 3.8 0.749012 0.749012 0.374506 -0.749012 0.2 3.8 0.748563 0.748563 0.374281 -0.748563 0.3 3.8 0.747815 0.747815 0.373907 -0.747815 0.4 3.8 0.746769 0.746769 0.373384 -0.746769 0.5 3.8 0.745426 0.745426 0.372713 -0.745426 0.6 3.8 0.743787 0.743787 0.371894 -0.743787 0.7 3.8 0.741856 0.741856 0.370928 -0.741856 0.8 3.8 0.739634 0.739634 0.369817 -0.739634 0.9 3.8 0.737123 0.737123 0.368562 -0.737123 1 3.8 0.734328 0.734328 0.367164 -0.734328 1.1 3.8 0.73125 0.73125 0.365625 -0.73125 1.2 3.8 0.727894 0.727894 0.363947 -0.727894 1.3 3.8 0.724264 0.724264 0.362132 -0.724264 1.4 3.8 0.720363 0.720363 0.360182 -0.720363 1.5 3.8 0.716197 0.716197 0.358099 -0.716197 1.6 3.8 0.71177 0.71177 0.355885 -0.71177 1.7 3.8 0.707088 0.707088 0.353544 -0.707088 1.8 3.8 0.702156 0.702156 0.351078 -0.702156 1.9 3.8 0.696979 0.696979 0.348489 -0.696979 2 3.8 0.691564 0.691564 0.345782 -0.691564 2.1 3.8 0.685916 0.685916 0.342958 -0.685916 2.2 3.8 0.680042 0.680042 0.340021 -0.680042 2.3 3.8 0.67395 0.67395 0.336975 -0.67395 2.4 3.8 0.667644 0.667644 0.333822 -0.667644 2.5 3.8 0.661133 0.661133 0.330567 -0.661133 2.6 3.8 0.654424 0.654424 0.327212 -0.654424 2.7 3.8 0.647524 0.647524 0.323762 -0.647524 2.8 3.8 0.64044 0.64044 0.32022 -0.64044 2.9 3.8 0.63318 0.63318 0.31659 -0.63318 3 3.8 0.625753 0.625753 0.312876 -0.625753 3.1 3.8 0.618165 0.618165 0.309082 -0.618165 3.2 3.8 0.610425 0.610425 0.305212 -0.610425 3.3 3.8 0.602541 0.602541 0.30127 -0.602541 3.4 3.8 0.594521 0.594521 0.29726 -0.594521 3.5 3.8 0.586373 0.586373 0.293186 -0.586373 3.6 3.8 0.578105 0.578105 0.289052 -0.578105 3.7 3.8 0.569726 0.569726 0.284863 -0.569726 3.8 3.8 0.561244 0.561244 0.280622 -0.561244 3.9 3.8 0.552667 0.552667 0.276333 -0.552667 4 3.8 0.544003 0.544003 0.272002 -0.544003 4.1 3.8 0.535261 0.535261 0.267631 -0.535261 4.2 3.8 0.526449 0.526449 0.263225 -0.526449 4.3 3.8 0.517575 0.517575 0.258788 -0.517575 4.4 3.8 0.508648 0.508648 0.254324 -0.508648 4.5 3.8 0.499674 0.499674 0.249837 -0.499674 4.6 3.8 0.490662 0.490662 0.245331 -0.490662 4.7 3.8 0.48162 0.48162 0.24081 -0.48162 4.8 3.8 0.472556 0.472556 0.236278 -0.472556 4.9 3.8 0.463476 0.463476 0.231738 -0.463476 -5 3.9 0.447446 0.447446 0.223723 -0.447446 -4.9 3.9 0.456393 0.456393 0.228197 -0.456393 -4.8 3.9 0.465334 0.465334 0.232667 -0.465334 -4.7 3.9 0.47426 0.47426 0.23713 -0.47426 -4.6 3.9 0.483164 0.483164 0.241582 -0.483164 -4.5 3.9 0.492038 0.492038 0.246019 -0.492038 -4.4 3.9 0.500874 0.500874 0.250437 -0.500874 -4.3 3.9 0.509666 0.509666 0.254833 -0.509666 -4.2 3.9 0.518404 0.518404 0.259202 -0.518404 -4.1 3.9 0.527082 0.527082 0.263541 -0.527082 -4 3.9 0.53569 0.53569 0.267845 -0.53569 -3.9 3.9 0.544221 0.544221 0.27211 -0.544221 -3.8 3.9 0.552667 0.552667 0.276333 -0.552667 -3.7 3.9 0.561019 0.561019 0.28051 -0.561019 -3.6 3.9 0.56927 0.56927 0.284635 -0.56927 -3.5 3.9 0.577412 0.577412 0.288706 -0.577412 -3.4 3.9 0.585435 0.585435 0.292718 -0.585435 -3.3 3.9 0.593333 0.593333 0.296666 -0.593333 -3.2 3.9 0.601096 0.601096 0.300548 -0.601096 -3.1 3.9 0.608718 0.608718 0.304359 -0.608718 -3 3.9 0.61619 0.61619 0.308095 -0.61619 -2.9 3.9 0.623504 0.623504 0.311752 -0.623504 -2.8 3.9 0.630653 0.630653 0.315326 -0.630653 -2.7 3.9 0.637628 0.637628 0.318814 -0.637628 -2.6 3.9 0.644423 0.644423 0.322211 -0.644423 -2.5 3.9 0.65103 0.65103 0.325515 -0.65103 -2.4 3.9 0.657441 0.657441 0.328721 -0.657441 -2.3 3.9 0.66365 0.66365 0.331825 -0.66365 -2.2 3.9 0.66965 0.66965 0.334825 -0.66965 -2.1 3.9 0.675434 0.675434 0.337717 -0.675434 -2 3.9 0.680995 0.680995 0.340498 -0.680995 -1.9 3.9 0.686328 0.686328 0.343164 -0.686328 -1.8 3.9 0.691425 0.691425 0.345713 -0.691425 -1.7 3.9 0.696282 0.696282 0.348141 -0.696282 -1.6 3.9 0.700893 0.700893 0.350447 -0.700893 -1.5 3.9 0.705252 0.705252 0.352626 -0.705252 -1.4 3.9 0.709354 0.709354 0.354677 -0.709354 -1.3 3.9 0.713195 0.713195 0.356598 -0.713195 -1.2 3.9 0.71677 0.71677 0.358385 -0.71677 -1.1 3.9 0.720075 0.720075 0.360037 -0.720075 -1 3.9 0.723106 0.723106 0.361553 -0.723106 -0.9 3.9 0.725859 0.725859 0.362929 -0.725859 -0.8 3.9 0.728331 0.728331 0.364165 -0.728331 -0.7 3.9 0.730519 0.730519 0.36526 -0.730519 -0.6 3.9 0.732421 0.732421 0.36621 -0.732421 -0.5 3.9 0.734034 0.734034 0.367017 -0.734034 -0.4 3.9 0.735356 0.735356 0.367678 -0.735356 -0.3 3.9 0.736387 0.736387 0.368193 -0.736387 -0.2 3.9 0.737123 0.737123 0.368562 -0.737123 -0.1 3.9 0.737566 0.737566 0.368783 -0.737566 0 3.9 0.737713 0.737713 0.368857 -0.737713 0.1 3.9 0.737566 0.737566 0.368783 -0.737566 0.2 3.9 0.737123 0.737123 0.368562 -0.737123 0.3 3.9 0.736387 0.736387 0.368193 -0.736387 0.4 3.9 0.735356 0.735356 0.367678 -0.735356 0.5 3.9 0.734034 0.734034 0.367017 -0.734034 0.6 3.9 0.732421 0.732421 0.36621 -0.732421 0.7 3.9 0.730519 0.730519 0.36526 -0.730519 0.8 3.9 0.728331 0.728331 0.364165 -0.728331 0.9 3.9 0.725859 0.725859 0.362929 -0.725859 1 3.9 0.723106 0.723106 0.361553 -0.723106 1.1 3.9 0.720075 0.720075 0.360037 -0.720075 1.2 3.9 0.71677 0.71677 0.358385 -0.71677 1.3 3.9 0.713195 0.713195 0.356598 -0.713195 1.4 3.9 0.709354 0.709354 0.354677 -0.709354 1.5 3.9 0.705252 0.705252 0.352626 -0.705252 1.6 3.9 0.700893 0.700893 0.350447 -0.700893 1.7 3.9 0.696282 0.696282 0.348141 -0.696282 1.8 3.9 0.691425 0.691425 0.345713 -0.691425 1.9 3.9 0.686328 0.686328 0.343164 -0.686328 2 3.9 0.680995 0.680995 0.340498 -0.680995 2.1 3.9 0.675434 0.675434 0.337717 -0.675434 2.2 3.9 0.66965 0.66965 0.334825 -0.66965 2.3 3.9 0.66365 0.66365 0.331825 -0.66365 2.4 3.9 0.657441 0.657441 0.328721 -0.657441 2.5 3.9 0.65103 0.65103 0.325515 -0.65103 2.6 3.9 0.644423 0.644423 0.322211 -0.644423 2.7 3.9 0.637628 0.637628 0.318814 -0.637628 2.8 3.9 0.630653 0.630653 0.315326 -0.630653 2.9 3.9 0.623504 0.623504 0.311752 -0.623504 3 3.9 0.61619 0.61619 0.308095 -0.61619 3.1 3.9 0.608718 0.608718 0.304359 -0.608718 3.2 3.9 0.601096 0.601096 0.300548 -0.601096 3.3 3.9 0.593333 0.593333 0.296666 -0.593333 3.4 3.9 0.585435 0.585435 0.292718 -0.585435 3.5 3.9 0.577412 0.577412 0.288706 -0.577412 3.6 3.9 0.56927 0.56927 0.284635 -0.56927 3.7 3.9 0.561019 0.561019 0.28051 -0.561019 3.8 3.9 0.552667 0.552667 0.276333 -0.552667 3.9 3.9 0.544221 0.544221 0.27211 -0.544221 4 3.9 0.53569 0.53569 0.267845 -0.53569 4.1 3.9 0.527082 0.527082 0.263541 -0.527082 4.2 3.9 0.518404 0.518404 0.259202 -0.518404 4.3 3.9 0.509666 0.509666 0.254833 -0.509666 4.4 3.9 0.500874 0.500874 0.250437 -0.500874 4.5 3.9 0.492038 0.492038 0.246019 -0.492038 4.6 3.9 0.483164 0.483164 0.241582 -0.483164 4.7 3.9 0.47426 0.47426 0.23713 -0.47426 4.8 3.9 0.465334 0.465334 0.232667 -0.465334 4.9 3.9 0.456393 0.456393 0.228197 -0.456393 -5 4 0.440432 0.440432 0.220216 -0.440432 -4.9 4 0.449239 0.449239 0.22462 -0.449239 -4.8 4 0.458039 0.458039 0.22902 -0.458039 -4.7 4 0.466825 0.466825 0.233413 -0.466825 -4.6 4 0.47559 0.47559 0.237795 -0.47559 -4.5 4 0.484325 0.484325 0.242162 -0.484325 -4.4 4 0.493023 0.493023 0.246511 -0.493023 -4.3 4 0.501676 0.501676 0.250838 -0.501676 -4.2 4 0.510278 0.510278 0.255139 -0.510278 -4.1 4 0.518819 0.518819 0.25941 -0.518819 -4 4 0.527292 0.527292 0.263646 -0.527292 -3.9 4 0.53569 0.53569 0.267845 -0.53569 -3.8 4 0.544003 0.544003 0.272002 -0.544003 -3.7 4 0.552225 0.552225 0.276112 -0.552225 -3.6 4 0.560346 0.560346 0.280173 -0.560346 -3.5 4 0.56836 0.56836 0.28418 -0.56836 -3.4 4 0.576258 0.576258 0.288129 -0.576258 -3.3 4 0.584032 0.584032 0.292016 -0.584032 -3.2 4 0.591674 0.591674 0.295837 -0.591674 -3.1 4 0.599176 0.599176 0.299588 -0.599176 -3 4 0.606531 0.606531 0.303265 -0.606531 -2.9 4 0.61373 0.61373 0.306865 -0.61373 -2.8 4 0.620767 0.620767 0.310383 -0.620767 -2.7 4 0.627633 0.627633 0.313816 -0.627633 -2.6 4 0.634321 0.634321 0.317161 -0.634321 -2.5 4 0.640824 0.640824 0.320412 -0.640824 -2.4 4 0.647135 0.647135 0.323568 -0.647135 -2.3 4 0.653247 0.653247 0.326623 -0.653247 -2.2 4 0.659153 0.659153 0.329576 -0.659153 -2.1 4 0.664846 0.664846 0.332423 -0.664846 -2 4 0.67032 0.67032 0.33516 -0.67032 -1.9 4 0.675569 0.675569 0.337784 -0.675569 -1.8 4 0.680587 0.680587 0.340293 -0.680587 -1.7 4 0.685368 0.685368 0.342684 -0.685368 -1.6 4 0.689906 0.689906 0.344953 -0.689906 -1.5 4 0.694197 0.694197 0.347098 -0.694197 -1.4 4 0.698235 0.698235 0.349117 -0.698235 -1.3 4 0.702015 0.702015 0.351008 -0.702015 -1.2 4 0.705534 0.705534 0.352767 -0.705534 -1.1 4 0.708787 0.708787 0.354394 -0.708787 -1 4 0.71177 0.71177 0.355885 -0.71177 -0.9 4 0.71448 0.71448 0.35724 -0.71448 -0.8 4 0.716914 0.716914 0.358457 -0.716914 -0.7 4 0.719068 0.719068 0.359534 -0.719068 -0.6 4 0.72094 0.72094 0.36047 -0.72094 -0.5 4 0.722527 0.722527 0.361264 -0.722527 -0.4 4 0.723829 0.723829 0.361915 -0.723829 -0.3 4 0.724843 0.724843 0.362422 -0.724843 -0.2 4 0.725568 0.725568 0.362784 -0.725568 -0.1 4 0.726004 0.726004 0.363002 -0.726004 0 4 0.726149 0.726149 0.363075 -0.726149 0.1 4 0.726004 0.726004 0.363002 -0.726004 0.2 4 0.725568 0.725568 0.362784 -0.725568 0.3 4 0.724843 0.724843 0.362422 -0.724843 0.4 4 0.723829 0.723829 0.361915 -0.723829 0.5 4 0.722527 0.722527 0.361264 -0.722527 0.6 4 0.72094 0.72094 0.36047 -0.72094 0.7 4 0.719068 0.719068 0.359534 -0.719068 0.8 4 0.716914 0.716914 0.358457 -0.716914 0.9 4 0.71448 0.71448 0.35724 -0.71448 1 4 0.71177 0.71177 0.355885 -0.71177 1.1 4 0.708787 0.708787 0.354394 -0.708787 1.2 4 0.705534 0.705534 0.352767 -0.705534 1.3 4 0.702015 0.702015 0.351008 -0.702015 1.4 4 0.698235 0.698235 0.349117 -0.698235 1.5 4 0.694197 0.694197 0.347098 -0.694197 1.6 4 0.689906 0.689906 0.344953 -0.689906 1.7 4 0.685368 0.685368 0.342684 -0.685368 1.8 4 0.680587 0.680587 0.340293 -0.680587 1.9 4 0.675569 0.675569 0.337784 -0.675569 2 4 0.67032 0.67032 0.33516 -0.67032 2.1 4 0.664846 0.664846 0.332423 -0.664846 2.2 4 0.659153 0.659153 0.329576 -0.659153 2.3 4 0.653247 0.653247 0.326623 -0.653247 2.4 4 0.647135 0.647135 0.323568 -0.647135 2.5 4 0.640824 0.640824 0.320412 -0.640824 2.6 4 0.634321 0.634321 0.317161 -0.634321 2.7 4 0.627633 0.627633 0.313816 -0.627633 2.8 4 0.620767 0.620767 0.310383 -0.620767 2.9 4 0.61373 0.61373 0.306865 -0.61373 3 4 0.606531 0.606531 0.303265 -0.606531 3.1 4 0.599176 0.599176 0.299588 -0.599176 3.2 4 0.591674 0.591674 0.295837 -0.591674 3.3 4 0.584032 0.584032 0.292016 -0.584032 3.4 4 0.576258 0.576258 0.288129 -0.576258 3.5 4 0.56836 0.56836 0.28418 -0.56836 3.6 4 0.560346 0.560346 0.280173 -0.560346 3.7 4 0.552225 0.552225 0.276112 -0.552225 3.8 4 0.544003 0.544003 0.272002 -0.544003 3.9 4 0.53569 0.53569 0.267845 -0.53569 4 4 0.527292 0.527292 0.263646 -0.527292 4.1 4 0.518819 0.518819 0.25941 -0.518819 4.2 4 0.510278 0.510278 0.255139 -0.510278 4.3 4 0.501676 0.501676 0.250838 -0.501676 4.4 4 0.493023 0.493023 0.246511 -0.493023 4.5 4 0.484325 0.484325 0.242162 -0.484325 4.6 4 0.47559 0.47559 0.237795 -0.47559 4.7 4 0.466825 0.466825 0.233413 -0.466825 4.8 4 0.458039 0.458039 0.22902 -0.458039 4.9 4 0.449239 0.449239 0.22462 -0.449239 -5 4.1 0.433354 0.433354 0.216677 -0.433354 -4.9 4.1 0.44202 0.44202 0.22101 -0.44202 -4.8 4.1 0.450679 0.450679 0.225339 -0.450679 -4.7 4.1 0.459324 0.459324 0.229662 -0.459324 -4.6 4.1 0.467947 0.467947 0.233974 -0.467947 -4.5 4.1 0.476542 0.476542 0.238271 -0.476542 -4.4 4.1 0.4851 0.4851 0.24255 -0.4851 -4.3 4.1 0.493615 0.493615 0.246807 -0.493615 -4.2 4.1 0.502078 0.502078 0.251039 -0.502078 -4.1 4.1 0.510482 0.510482 0.255241 -0.510482 -4 4.1 0.518819 0.518819 0.25941 -0.518819 -3.9 4.1 0.527082 0.527082 0.263541 -0.527082 -3.8 4.1 0.535261 0.535261 0.267631 -0.535261 -3.7 4.1 0.543351 0.543351 0.271675 -0.543351 -3.6 4.1 0.551342 0.551342 0.275671 -0.551342 -3.5 4.1 0.559227 0.559227 0.279613 -0.559227 -3.4 4.1 0.566998 0.566998 0.283499 -0.566998 -3.3 4.1 0.574647 0.574647 0.287323 -0.574647 -3.2 4.1 0.582166 0.582166 0.291083 -0.582166 -3.1 4.1 0.589547 0.589547 0.294774 -0.589547 -3 4.1 0.596784 0.596784 0.298392 -0.596784 -2.9 4.1 0.603868 0.603868 0.301934 -0.603868 -2.8 4.1 0.610791 0.610791 0.305396 -0.610791 -2.7 4.1 0.617547 0.617547 0.308774 -0.617547 -2.6 4.1 0.624128 0.624128 0.312064 -0.624128 -2.5 4.1 0.630527 0.630527 0.315263 -0.630527 -2.4 4.1 0.636736 0.636736 0.318368 -0.636736 -2.3 4.1 0.64275 0.64275 0.321375 -0.64275 -2.2 4.1 0.64856 0.64856 0.32428 -0.64856 -2.1 4.1 0.654162 0.654162 0.327081 -0.654162 -2 4.1 0.659548 0.659548 0.329774 -0.659548 -1.9 4.1 0.664713 0.664713 0.332356 -0.664713 -1.8 4.1 0.66965 0.66965 0.334825 -0.66965 -1.7 4.1 0.674354 0.674354 0.337177 -0.674354 -1.6 4.1 0.67882 0.67882 0.33941 -0.67882 -1.5 4.1 0.683041 0.683041 0.341521 -0.683041 -1.4 4.1 0.687014 0.687014 0.343507 -0.687014 -1.3 4.1 0.690734 0.690734 0.345367 -0.690734 -1.2 4.1 0.694197 0.694197 0.347098 -0.694197 -1.1 4.1 0.697397 0.697397 0.348699 -0.697397 -1 4.1 0.700333 0.700333 0.350166 -0.700333 -0.9 4.1 0.702999 0.702999 0.351499 -0.702999 -0.8 4.1 0.705393 0.705393 0.352697 -0.705393 -0.7 4.1 0.707512 0.707512 0.353756 -0.707512 -0.6 4.1 0.709354 0.709354 0.354677 -0.709354 -0.5 4.1 0.710917 0.710917 0.355458 -0.710917 -0.4 4.1 0.712198 0.712198 0.356099 -0.712198 -0.3 4.1 0.713195 0.713195 0.356598 -0.713195 -0.2 4.1 0.713909 0.713909 0.356954 -0.713909 -0.1 4.1 0.714337 0.714337 0.357169 -0.714337 0 4.1 0.71448 0.71448 0.35724 -0.71448 0.1 4.1 0.714337 0.714337 0.357169 -0.714337 0.2 4.1 0.713909 0.713909 0.356954 -0.713909 0.3 4.1 0.713195 0.713195 0.356598 -0.713195 0.4 4.1 0.712198 0.712198 0.356099 -0.712198 0.5 4.1 0.710917 0.710917 0.355458 -0.710917 0.6 4.1 0.709354 0.709354 0.354677 -0.709354 0.7 4.1 0.707512 0.707512 0.353756 -0.707512 0.8 4.1 0.705393 0.705393 0.352697 -0.705393 0.9 4.1 0.702999 0.702999 0.351499 -0.702999 1 4.1 0.700333 0.700333 0.350166 -0.700333 1.1 4.1 0.697397 0.697397 0.348699 -0.697397 1.2 4.1 0.694197 0.694197 0.347098 -0.694197 1.3 4.1 0.690734 0.690734 0.345367 -0.690734 1.4 4.1 0.687014 0.687014 0.343507 -0.687014 1.5 4.1 0.683041 0.683041 0.341521 -0.683041 1.6 4.1 0.67882 0.67882 0.33941 -0.67882 1.7 4.1 0.674354 0.674354 0.337177 -0.674354 1.8 4.1 0.66965 0.66965 0.334825 -0.66965 1.9 4.1 0.664713 0.664713 0.332356 -0.664713 2 4.1 0.659548 0.659548 0.329774 -0.659548 2.1 4.1 0.654162 0.654162 0.327081 -0.654162 2.2 4.1 0.64856 0.64856 0.32428 -0.64856 2.3 4.1 0.64275 0.64275 0.321375 -0.64275 2.4 4.1 0.636736 0.636736 0.318368 -0.636736 2.5 4.1 0.630527 0.630527 0.315263 -0.630527 2.6 4.1 0.624128 0.624128 0.312064 -0.624128 2.7 4.1 0.617547 0.617547 0.308774 -0.617547 2.8 4.1 0.610791 0.610791 0.305396 -0.610791 2.9 4.1 0.603868 0.603868 0.301934 -0.603868 3 4.1 0.596784 0.596784 0.298392 -0.596784 3.1 4.1 0.589547 0.589547 0.294774 -0.589547 3.2 4.1 0.582166 0.582166 0.291083 -0.582166 3.3 4.1 0.574647 0.574647 0.287323 -0.574647 3.4 4.1 0.566998 0.566998 0.283499 -0.566998 3.5 4.1 0.559227 0.559227 0.279613 -0.559227 3.6 4.1 0.551342 0.551342 0.275671 -0.551342 3.7 4.1 0.543351 0.543351 0.271675 -0.543351 3.8 4.1 0.535261 0.535261 0.267631 -0.535261 3.9 4.1 0.527082 0.527082 0.263541 -0.527082 4 4.1 0.518819 0.518819 0.25941 -0.518819 4.1 4.1 0.510482 0.510482 0.255241 -0.510482 4.2 4.1 0.502078 0.502078 0.251039 -0.502078 4.3 4.1 0.493615 0.493615 0.246807 -0.493615 4.4 4.1 0.4851 0.4851 0.24255 -0.4851 4.5 4.1 0.476542 0.476542 0.238271 -0.476542 4.6 4.1 0.467947 0.467947 0.233974 -0.467947 4.7 4.1 0.459324 0.459324 0.229662 -0.459324 4.8 4.1 0.450679 0.450679 0.225339 -0.450679 4.9 4.1 0.44202 0.44202 0.22101 -0.44202 -5 4.2 0.42622 0.42622 0.21311 -0.42622 -4.9 4.2 0.434743 0.434743 0.217372 -0.434743 -4.8 4.2 0.443259 0.443259 0.22163 -0.443259 -4.7 4.2 0.451762 0.451762 0.225881 -0.451762 -4.6 4.2 0.460243 0.460243 0.230122 -0.460243 -4.5 4.2 0.468696 0.468696 0.234348 -0.468696 -4.4 4.2 0.477114 0.477114 0.238557 -0.477114 -4.3 4.2 0.485488 0.485488 0.242744 -0.485488 -4.2 4.2 0.493812 0.493812 0.246906 -0.493812 -4.1 4.2 0.502078 0.502078 0.251039 -0.502078 -4 4.2 0.510278 0.510278 0.255139 -0.510278 -3.9 4.2 0.518404 0.518404 0.259202 -0.518404 -3.8 4.2 0.526449 0.526449 0.263225 -0.526449 -3.7 4.2 0.534406 0.534406 0.267203 -0.534406 -3.6 4.2 0.542265 0.542265 0.271133 -0.542265 -3.5 4.2 0.55002 0.55002 0.27501 -0.55002 -3.4 4.2 0.557663 0.557663 0.278832 -0.557663 -3.3 4.2 0.565186 0.565186 0.282593 -0.565186 -3.2 4.2 0.572582 0.572582 0.286291 -0.572582 -3.1 4.2 0.579842 0.579842 0.289921 -0.579842 -3 4.2 0.586959 0.586959 0.29348 -0.586959 -2.9 4.2 0.593926 0.593926 0.296963 -0.593926 -2.8 4.2 0.600736 0.600736 0.300368 -0.600736 -2.7 4.2 0.60738 0.60738 0.30369 -0.60738 -2.6 4.2 0.613853 0.613853 0.306926 -0.613853 -2.5 4.2 0.620146 0.620146 0.310073 -0.620146 -2.4 4.2 0.626254 0.626254 0.313127 -0.626254 -2.3 4.2 0.632168 0.632168 0.316084 -0.632168 -2.2 4.2 0.637883 0.637883 0.318942 -0.637883 -2.1 4.2 0.643393 0.643393 0.321696 -0.643393 -2 4.2 0.64869 0.64869 0.324345 -0.64869 -1.9 4.2 0.65377 0.65377 0.326885 -0.65377 -1.8 4.2 0.658626 0.658626 0.329313 -0.658626 -1.7 4.2 0.663252 0.663252 0.331626 -0.663252 -1.6 4.2 0.667644 0.667644 0.333822 -0.667644 -1.5 4.2 0.671796 0.671796 0.335898 -0.671796 -1.4 4.2 0.675704 0.675704 0.337852 -0.675704 -1.3 4.2 0.679363 0.679363 0.339681 -0.679363 -1.2 4.2 0.682768 0.682768 0.341384 -0.682768 -1.1 4.2 0.685916 0.685916 0.342958 -0.685916 -1 4.2 0.688803 0.688803 0.344401 -0.688803 -0.9 4.2 0.691425 0.691425 0.345713 -0.691425 -0.8 4.2 0.69378 0.69378 0.34689 -0.69378 -0.7 4.2 0.695865 0.695865 0.347932 -0.695865 -0.6 4.2 0.697676 0.697676 0.348838 -0.697676 -0.5 4.2 0.699213 0.699213 0.349606 -0.699213 -0.4 4.2 0.700473 0.700473 0.350236 -0.700473 -0.3 4.2 0.701454 0.701454 0.350727 -0.701454 -0.2 4.2 0.702156 0.702156 0.351078 -0.702156 -0.1 4.2 0.702577 0.702577 0.351289 -0.702577 0 4.2 0.702718 0.702718 0.351359 -0.702718 0.1 4.2 0.702577 0.702577 0.351289 -0.702577 0.2 4.2 0.702156 0.702156 0.351078 -0.702156 0.3 4.2 0.701454 0.701454 0.350727 -0.701454 0.4 4.2 0.700473 0.700473 0.350236 -0.700473 0.5 4.2 0.699213 0.699213 0.349606 -0.699213 0.6 4.2 0.697676 0.697676 0.348838 -0.697676 0.7 4.2 0.695865 0.695865 0.347932 -0.695865 0.8 4.2 0.69378 0.69378 0.34689 -0.69378 0.9 4.2 0.691425 0.691425 0.345713 -0.691425 1 4.2 0.688803 0.688803 0.344401 -0.688803 1.1 4.2 0.685916 0.685916 0.342958 -0.685916 1.2 4.2 0.682768 0.682768 0.341384 -0.682768 1.3 4.2 0.679363 0.679363 0.339681 -0.679363 1.4 4.2 0.675704 0.675704 0.337852 -0.675704 1.5 4.2 0.671796 0.671796 0.335898 -0.671796 1.6 4.2 0.667644 0.667644 0.333822 -0.667644 1.7 4.2 0.663252 0.663252 0.331626 -0.663252 1.8 4.2 0.658626 0.658626 0.329313 -0.658626 1.9 4.2 0.65377 0.65377 0.326885 -0.65377 2 4.2 0.64869 0.64869 0.324345 -0.64869 2.1 4.2 0.643393 0.643393 0.321696 -0.643393 2.2 4.2 0.637883 0.637883 0.318942 -0.637883 2.3 4.2 0.632168 0.632168 0.316084 -0.632168 2.4 4.2 0.626254 0.626254 0.313127 -0.626254 2.5 4.2 0.620146 0.620146 0.310073 -0.620146 2.6 4.2 0.613853 0.613853 0.306926 -0.613853 2.7 4.2 0.60738 0.60738 0.30369 -0.60738 2.8 4.2 0.600736 0.600736 0.300368 -0.600736 2.9 4.2 0.593926 0.593926 0.296963 -0.593926 3 4.2 0.586959 0.586959 0.29348 -0.586959 3.1 4.2 0.579842 0.579842 0.289921 -0.579842 3.2 4.2 0.572582 0.572582 0.286291 -0.572582 3.3 4.2 0.565186 0.565186 0.282593 -0.565186 3.4 4.2 0.557663 0.557663 0.278832 -0.557663 3.5 4.2 0.55002 0.55002 0.27501 -0.55002 3.6 4.2 0.542265 0.542265 0.271133 -0.542265 3.7 4.2 0.534406 0.534406 0.267203 -0.534406 3.8 4.2 0.526449 0.526449 0.263225 -0.526449 3.9 4.2 0.518404 0.518404 0.259202 -0.518404 4 4.2 0.510278 0.510278 0.255139 -0.510278 4.1 4.2 0.502078 0.502078 0.251039 -0.502078 4.2 4.2 0.493812 0.493812 0.246906 -0.493812 4.3 4.2 0.485488 0.485488 0.242744 -0.485488 4.4 4.2 0.477114 0.477114 0.238557 -0.477114 4.5 4.2 0.468696 0.468696 0.234348 -0.468696 4.6 4.2 0.460243 0.460243 0.230122 -0.460243 4.7 4.2 0.451762 0.451762 0.225881 -0.451762 4.8 4.2 0.443259 0.443259 0.22163 -0.443259 4.9 4.2 0.434743 0.434743 0.217372 -0.434743 -5 4.3 0.419035 0.419035 0.209518 -0.419035 -4.9 4.3 0.427415 0.427415 0.213707 -0.427415 -4.8 4.3 0.435788 0.435788 0.217894 -0.435788 -4.7 4.3 0.444147 0.444147 0.222073 -0.444147 -4.6 4.3 0.452485 0.452485 0.226243 -0.452485 -4.5 4.3 0.460796 0.460796 0.230398 -0.460796 -4.4 4.3 0.469072 0.469072 0.234536 -0.469072 -4.3 4.3 0.477305 0.477305 0.238652 -0.477305 -4.2 4.3 0.485488 0.485488 0.242744 -0.485488 -4.1 4.3 0.493615 0.493615 0.246807 -0.493615 -4 4.3 0.501676 0.501676 0.250838 -0.501676 -3.9 4.3 0.509666 0.509666 0.254833 -0.509666 -3.8 4.3 0.517575 0.517575 0.258788 -0.517575 -3.7 4.3 0.525398 0.525398 0.262699 -0.525398 -3.6 4.3 0.533125 0.533125 0.266562 -0.533125 -3.5 4.3 0.540749 0.540749 0.270375 -0.540749 -3.4 4.3 0.548263 0.548263 0.274132 -0.548263 -3.3 4.3 0.555659 0.555659 0.27783 -0.555659 -3.2 4.3 0.56293 0.56293 0.281465 -0.56293 -3.1 4.3 0.570068 0.570068 0.285034 -0.570068 -3 4.3 0.577065 0.577065 0.288533 -0.577065 -2.9 4.3 0.583915 0.583915 0.291957 -0.583915 -2.8 4.3 0.59061 0.59061 0.295305 -0.59061 -2.7 4.3 0.597142 0.597142 0.298571 -0.597142 -2.6 4.3 0.603506 0.603506 0.301753 -0.603506 -2.5 4.3 0.609693 0.609693 0.304846 -0.609693 -2.4 4.3 0.615697 0.615697 0.307849 -0.615697 -2.3 4.3 0.621512 0.621512 0.310756 -0.621512 -2.2 4.3 0.627131 0.627131 0.313565 -0.627131 -2.1 4.3 0.632547 0.632547 0.316274 -0.632547 -2 4.3 0.637756 0.637756 0.318878 -0.637756 -1.9 4.3 0.64275 0.64275 0.321375 -0.64275 -1.8 4.3 0.647524 0.647524 0.323762 -0.647524 -1.7 4.3 0.652072 0.652072 0.326036 -0.652072 -1.6 4.3 0.65639 0.65639 0.328195 -0.65639 -1.5 4.3 0.660472 0.660472 0.330236 -0.660472 -1.4 4.3 0.664314 0.664314 0.332157 -0.664314 -1.3 4.3 0.667911 0.667911 0.333956 -0.667911 -1.2 4.3 0.671259 0.671259 0.33563 -0.671259 -1.1 4.3 0.674354 0.674354 0.337177 -0.674354 -1 4.3 0.677192 0.677192 0.338596 -0.677192 -0.9 4.3 0.679771 0.679771 0.339885 -0.679771 -0.8 4.3 0.682086 0.682086 0.341043 -0.682086 -0.7 4.3 0.684135 0.684135 0.342068 -0.684135 -0.6 4.3 0.685916 0.685916 0.342958 -0.685916 -0.5 4.3 0.687427 0.687427 0.343713 -0.687427 -0.4 4.3 0.688665 0.688665 0.344333 -0.688665 -0.3 4.3 0.68963 0.68963 0.344815 -0.68963 -0.2 4.3 0.69032 0.69032 0.34516 -0.69032 -0.1 4.3 0.690734 0.690734 0.345367 -0.690734 0 4.3 0.690872 0.690872 0.345436 -0.690872 0.1 4.3 0.690734 0.690734 0.345367 -0.690734 0.2 4.3 0.69032 0.69032 0.34516 -0.69032 0.3 4.3 0.68963 0.68963 0.344815 -0.68963 0.4 4.3 0.688665 0.688665 0.344333 -0.688665 0.5 4.3 0.687427 0.687427 0.343713 -0.687427 0.6 4.3 0.685916 0.685916 0.342958 -0.685916 0.7 4.3 0.684135 0.684135 0.342068 -0.684135 0.8 4.3 0.682086 0.682086 0.341043 -0.682086 0.9 4.3 0.679771 0.679771 0.339885 -0.679771 1 4.3 0.677192 0.677192 0.338596 -0.677192 1.1 4.3 0.674354 0.674354 0.337177 -0.674354 1.2 4.3 0.671259 0.671259 0.33563 -0.671259 1.3 4.3 0.667911 0.667911 0.333956 -0.667911 1.4 4.3 0.664314 0.664314 0.332157 -0.664314 1.5 4.3 0.660472 0.660472 0.330236 -0.660472 1.6 4.3 0.65639 0.65639 0.328195 -0.65639 1.7 4.3 0.652072 0.652072 0.326036 -0.652072 1.8 4.3 0.647524 0.647524 0.323762 -0.647524 1.9 4.3 0.64275 0.64275 0.321375 -0.64275 2 4.3 0.637756 0.637756 0.318878 -0.637756 2.1 4.3 0.632547 0.632547 0.316274 -0.632547 2.2 4.3 0.627131 0.627131 0.313565 -0.627131 2.3 4.3 0.621512 0.621512 0.310756 -0.621512 2.4 4.3 0.615697 0.615697 0.307849 -0.615697 2.5 4.3 0.609693 0.609693 0.304846 -0.609693 2.6 4.3 0.603506 0.603506 0.301753 -0.603506 2.7 4.3 0.597142 0.597142 0.298571 -0.597142 2.8 4.3 0.59061 0.59061 0.295305 -0.59061 2.9 4.3 0.583915 0.583915 0.291957 -0.583915 3 4.3 0.577065 0.577065 0.288533 -0.577065 3.1 4.3 0.570068 0.570068 0.285034 -0.570068 3.2 4.3 0.56293 0.56293 0.281465 -0.56293 3.3 4.3 0.555659 0.555659 0.27783 -0.555659 3.4 4.3 0.548263 0.548263 0.274132 -0.548263 3.5 4.3 0.540749 0.540749 0.270375 -0.540749 3.6 4.3 0.533125 0.533125 0.266562 -0.533125 3.7 4.3 0.525398 0.525398 0.262699 -0.525398 3.8 4.3 0.517575 0.517575 0.258788 -0.517575 3.9 4.3 0.509666 0.509666 0.254833 -0.509666 4 4.3 0.501676 0.501676 0.250838 -0.501676 4.1 4.3 0.493615 0.493615 0.246807 -0.493615 4.2 4.3 0.485488 0.485488 0.242744 -0.485488 4.3 4.3 0.477305 0.477305 0.238652 -0.477305 4.4 4.3 0.469072 0.469072 0.234536 -0.469072 4.5 4.3 0.460796 0.460796 0.230398 -0.460796 4.6 4.3 0.452485 0.452485 0.226243 -0.452485 4.7 4.3 0.444147 0.444147 0.222073 -0.444147 4.8 4.3 0.435788 0.435788 0.217894 -0.435788 4.9 4.3 0.427415 0.427415 0.213707 -0.427415 -5 4.4 0.411807 0.411807 0.205904 -0.411807 -4.9 4.4 0.420042 0.420042 0.210021 -0.420042 -4.8 4.4 0.428271 0.428271 0.214135 -0.428271 -4.7 4.4 0.436486 0.436486 0.218243 -0.436486 -4.6 4.4 0.44468 0.44468 0.22234 -0.44468 -4.5 4.4 0.452847 0.452847 0.226424 -0.452847 -4.4 4.4 0.46098 0.46098 0.23049 -0.46098 -4.3 4.4 0.469072 0.469072 0.234536 -0.469072 -4.2 4.4 0.477114 0.477114 0.238557 -0.477114 -4.1 4.4 0.4851 0.4851 0.24255 -0.4851 -4 4.4 0.493023 0.493023 0.246511 -0.493023 -3.9 4.4 0.500874 0.500874 0.250437 -0.500874 -3.8 4.4 0.508648 0.508648 0.254324 -0.508648 -3.7 4.4 0.516335 0.516335 0.258167 -0.516335 -3.6 4.4 0.523929 0.523929 0.261964 -0.523929 -3.5 4.4 0.531421 0.531421 0.265711 -0.531421 -3.4 4.4 0.538806 0.538806 0.269403 -0.538806 -3.3 4.4 0.546074 0.546074 0.273037 -0.546074 -3.2 4.4 0.55322 0.55322 0.27661 -0.55322 -3.1 4.4 0.560234 0.560234 0.280117 -0.560234 -3 4.4 0.567111 0.567111 0.283556 -0.567111 -2.9 4.4 0.573843 0.573843 0.286921 -0.573843 -2.8 4.4 0.580422 0.580422 0.290211 -0.580422 -2.7 4.4 0.586842 0.586842 0.293421 -0.586842 -2.6 4.4 0.593095 0.593095 0.296548 -0.593095 -2.5 4.4 0.599176 0.599176 0.299588 -0.599176 -2.4 4.4 0.605077 0.605077 0.302538 -0.605077 -2.3 4.4 0.610791 0.610791 0.305396 -0.610791 -2.2 4.4 0.616313 0.616313 0.308157 -0.616313 -2.1 4.4 0.621636 0.621636 0.310818 -0.621636 -2 4.4 0.626755 0.626755 0.313377 -0.626755 -1.9 4.4 0.631663 0.631663 0.315831 -0.631663 -1.8 4.4 0.636354 0.636354 0.318177 -0.636354 -1.7 4.4 0.640824 0.640824 0.320412 -0.640824 -1.6 4.4 0.645068 0.645068 0.322534 -0.645068 -1.5 4.4 0.64908 0.64908 0.32454 -0.64908 -1.4 4.4 0.652855 0.652855 0.326428 -0.652855 -1.3 4.4 0.65639 0.65639 0.328195 -0.65639 -1.2 4.4 0.65968 0.65968 0.32984 -0.65968 -1.1 4.4 0.662722 0.662722 0.331361 -0.662722 -1 4.4 0.665511 0.665511 0.332756 -0.665511 -0.9 4.4 0.668045 0.668045 0.334022 -0.668045 -0.8 4.4 0.67032 0.67032 0.33516 -0.67032 -0.7 4.4 0.672334 0.672334 0.336167 -0.672334 -0.6 4.4 0.674084 0.674084 0.337042 -0.674084 -0.5 4.4 0.675569 0.675569 0.337784 -0.675569 -0.4 4.4 0.676786 0.676786 0.338393 -0.676786 -0.3 4.4 0.677734 0.677734 0.338867 -0.677734 -0.2 4.4 0.678412 0.678412 0.339206 -0.678412 -0.1 4.4 0.67882 0.67882 0.33941 -0.67882 0 4.4 0.678955 0.678955 0.339478 -0.678955 0.1 4.4 0.67882 0.67882 0.33941 -0.67882 0.2 4.4 0.678412 0.678412 0.339206 -0.678412 0.3 4.4 0.677734 0.677734 0.338867 -0.677734 0.4 4.4 0.676786 0.676786 0.338393 -0.676786 0.5 4.4 0.675569 0.675569 0.337784 -0.675569 0.6 4.4 0.674084 0.674084 0.337042 -0.674084 0.7 4.4 0.672334 0.672334 0.336167 -0.672334 0.8 4.4 0.67032 0.67032 0.33516 -0.67032 0.9 4.4 0.668045 0.668045 0.334022 -0.668045 1 4.4 0.665511 0.665511 0.332756 -0.665511 1.1 4.4 0.662722 0.662722 0.331361 -0.662722 1.2 4.4 0.65968 0.65968 0.32984 -0.65968 1.3 4.4 0.65639 0.65639 0.328195 -0.65639 1.4 4.4 0.652855 0.652855 0.326428 -0.652855 1.5 4.4 0.64908 0.64908 0.32454 -0.64908 1.6 4.4 0.645068 0.645068 0.322534 -0.645068 1.7 4.4 0.640824 0.640824 0.320412 -0.640824 1.8 4.4 0.636354 0.636354 0.318177 -0.636354 1.9 4.4 0.631663 0.631663 0.315831 -0.631663 2 4.4 0.626755 0.626755 0.313377 -0.626755 2.1 4.4 0.621636 0.621636 0.310818 -0.621636 2.2 4.4 0.616313 0.616313 0.308157 -0.616313 2.3 4.4 0.610791 0.610791 0.305396 -0.610791 2.4 4.4 0.605077 0.605077 0.302538 -0.605077 2.5 4.4 0.599176 0.599176 0.299588 -0.599176 2.6 4.4 0.593095 0.593095 0.296548 -0.593095 2.7 4.4 0.586842 0.586842 0.293421 -0.586842 2.8 4.4 0.580422 0.580422 0.290211 -0.580422 2.9 4.4 0.573843 0.573843 0.286921 -0.573843 3 4.4 0.567111 0.567111 0.283556 -0.567111 3.1 4.4 0.560234 0.560234 0.280117 -0.560234 3.2 4.4 0.55322 0.55322 0.27661 -0.55322 3.3 4.4 0.546074 0.546074 0.273037 -0.546074 3.4 4.4 0.538806 0.538806 0.269403 -0.538806 3.5 4.4 0.531421 0.531421 0.265711 -0.531421 3.6 4.4 0.523929 0.523929 0.261964 -0.523929 3.7 4.4 0.516335 0.516335 0.258167 -0.516335 3.8 4.4 0.508648 0.508648 0.254324 -0.508648 3.9 4.4 0.500874 0.500874 0.250437 -0.500874 4 4.4 0.493023 0.493023 0.246511 -0.493023 4.1 4.4 0.4851 0.4851 0.24255 -0.4851 4.2 4.4 0.477114 0.477114 0.238557 -0.477114 4.3 4.4 0.469072 0.469072 0.234536 -0.469072 4.4 4.4 0.46098 0.46098 0.23049 -0.46098 4.5 4.4 0.452847 0.452847 0.226424 -0.452847 4.6 4.4 0.44468 0.44468 0.22234 -0.44468 4.7 4.4 0.436486 0.436486 0.218243 -0.436486 4.8 4.4 0.428271 0.428271 0.214135 -0.428271 4.9 4.4 0.420042 0.420042 0.210021 -0.420042 -5 4.5 0.404542 0.404542 0.202271 -0.404542 -4.9 4.5 0.412632 0.412632 0.206316 -0.412632 -4.8 4.5 0.420715 0.420715 0.210357 -0.420715 -4.7 4.5 0.428785 0.428785 0.214392 -0.428785 -4.6 4.5 0.436835 0.436835 0.218417 -0.436835 -4.5 4.5 0.444858 0.444858 0.222429 -0.444858 -4.4 4.5 0.452847 0.452847 0.226424 -0.452847 -4.3 4.5 0.460796 0.460796 0.230398 -0.460796 -4.2 4.5 0.468696 0.468696 0.234348 -0.468696 -4.1 4.5 0.476542 0.476542 0.238271 -0.476542 -4 4.5 0.484325 0.484325 0.242162 -0.484325 -3.9 4.5 0.492038 0.492038 0.246019 -0.492038 -3.8 4.5 0.499674 0.499674 0.249837 -0.499674 -3.7 4.5 0.507225 0.507225 0.253613 -0.507225 -3.6 4.5 0.514685 0.514685 0.257343 -0.514685 -3.5 4.5 0.522046 0.522046 0.261023 -0.522046 -3.4 4.5 0.5293 0.5293 0.26465 -0.5293 -3.3 4.5 0.53644 0.53644 0.26822 -0.53644 -3.2 4.5 0.54346 0.54346 0.27173 -0.54346 -3.1 4.5 0.55035 0.55035 0.275175 -0.55035 -3 4.5 0.557106 0.557106 0.278553 -0.557106 -2.9 4.5 0.563719 0.563719 0.281859 -0.563719 -2.8 4.5 0.570182 0.570182 0.285091 -0.570182 -2.7 4.5 0.576488 0.576488 0.288244 -0.576488 -2.6 4.5 0.582632 0.582632 0.291316 -0.582632 -2.5 4.5 0.588605 0.588605 0.294302 -0.588605 -2.4 4.5 0.594402 0.594402 0.297201 -0.594402 -2.3 4.5 0.600015 0.600015 0.300008 -0.600015 -2.2 4.5 0.60544 0.60544 0.30272 -0.60544 -2.1 4.5 0.610669 0.610669 0.305335 -0.610669 -2 4.5 0.615697 0.615697 0.307849 -0.615697 -1.9 4.5 0.620518 0.620518 0.310259 -0.620518 -1.8 4.5 0.625127 0.625127 0.312564 -0.625127 -1.7 4.5 0.629519 0.629519 0.314759 -0.629519 -1.6 4.5 0.633687 0.633687 0.316844 -0.633687 -1.5 4.5 0.637628 0.637628 0.318814 -0.637628 -1.4 4.5 0.641337 0.641337 0.320669 -0.641337 -1.3 4.5 0.64481 0.64481 0.322405 -0.64481 -1.2 4.5 0.648042 0.648042 0.324021 -0.648042 -1.1 4.5 0.65103 0.65103 0.325515 -0.65103 -1 4.5 0.65377 0.65377 0.326885 -0.65377 -0.9 4.5 0.656259 0.656259 0.328129 -0.656259 -0.8 4.5 0.658494 0.658494 0.329247 -0.658494 -0.7 4.5 0.660472 0.660472 0.330236 -0.660472 -0.6 4.5 0.662192 0.662192 0.331096 -0.662192 -0.5 4.5 0.66365 0.66365 0.331825 -0.66365 -0.4 4.5 0.664846 0.664846 0.332423 -0.664846 -0.3 4.5 0.665777 0.665777 0.332889 -0.665777 -0.2 4.5 0.666443 0.666443 0.333222 -0.666443 -0.1 4.5 0.666843 0.666843 0.333422 -0.666843 0 4.5 0.666977 0.666977 0.333488 -0.666977 0.1 4.5 0.666843 0.666843 0.333422 -0.666843 0.2 4.5 0.666443 0.666443 0.333222 -0.666443 0.3 4.5 0.665777 0.665777 0.332889 -0.665777 0.4 4.5 0.664846 0.664846 0.332423 -0.664846 0.5 4.5 0.66365 0.66365 0.331825 -0.66365 0.6 4.5 0.662192 0.662192 0.331096 -0.662192 0.7 4.5 0.660472 0.660472 0.330236 -0.660472 0.8 4.5 0.658494 0.658494 0.329247 -0.658494 0.9 4.5 0.656259 0.656259 0.328129 -0.656259 1 4.5 0.65377 0.65377 0.326885 -0.65377 1.1 4.5 0.65103 0.65103 0.325515 -0.65103 1.2 4.5 0.648042 0.648042 0.324021 -0.648042 1.3 4.5 0.64481 0.64481 0.322405 -0.64481 1.4 4.5 0.641337 0.641337 0.320669 -0.641337 1.5 4.5 0.637628 0.637628 0.318814 -0.637628 1.6 4.5 0.633687 0.633687 0.316844 -0.633687 1.7 4.5 0.629519 0.629519 0.314759 -0.629519 1.8 4.5 0.625127 0.625127 0.312564 -0.625127 1.9 4.5 0.620518 0.620518 0.310259 -0.620518 2 4.5 0.615697 0.615697 0.307849 -0.615697 2.1 4.5 0.610669 0.610669 0.305335 -0.610669 2.2 4.5 0.60544 0.60544 0.30272 -0.60544 2.3 4.5 0.600015 0.600015 0.300008 -0.600015 2.4 4.5 0.594402 0.594402 0.297201 -0.594402 2.5 4.5 0.588605 0.588605 0.294302 -0.588605 2.6 4.5 0.582632 0.582632 0.291316 -0.582632 2.7 4.5 0.576488 0.576488 0.288244 -0.576488 2.8 4.5 0.570182 0.570182 0.285091 -0.570182 2.9 4.5 0.563719 0.563719 0.281859 -0.563719 3 4.5 0.557106 0.557106 0.278553 -0.557106 3.1 4.5 0.55035 0.55035 0.275175 -0.55035 3.2 4.5 0.54346 0.54346 0.27173 -0.54346 3.3 4.5 0.53644 0.53644 0.26822 -0.53644 3.4 4.5 0.5293 0.5293 0.26465 -0.5293 3.5 4.5 0.522046 0.522046 0.261023 -0.522046 3.6 4.5 0.514685 0.514685 0.257343 -0.514685 3.7 4.5 0.507225 0.507225 0.253613 -0.507225 3.8 4.5 0.499674 0.499674 0.249837 -0.499674 3.9 4.5 0.492038 0.492038 0.246019 -0.492038 4 4.5 0.484325 0.484325 0.242162 -0.484325 4.1 4.5 0.476542 0.476542 0.238271 -0.476542 4.2 4.5 0.468696 0.468696 0.234348 -0.468696 4.3 4.5 0.460796 0.460796 0.230398 -0.460796 4.4 4.5 0.452847 0.452847 0.226424 -0.452847 4.5 4.5 0.444858 0.444858 0.222429 -0.444858 4.6 4.5 0.436835 0.436835 0.218417 -0.436835 4.7 4.5 0.428785 0.428785 0.214392 -0.428785 4.8 4.5 0.420715 0.420715 0.210357 -0.420715 4.9 4.5 0.412632 0.412632 0.206316 -0.412632 -5 4.6 0.397246 0.397246 0.198623 -0.397246 -4.9 4.6 0.40519 0.40519 0.202595 -0.40519 -4.8 4.6 0.413127 0.413127 0.206564 -0.413127 -4.7 4.6 0.421052 0.421052 0.210526 -0.421052 -4.6 4.6 0.428956 0.428956 0.214478 -0.428956 -4.5 4.6 0.436835 0.436835 0.218417 -0.436835 -4.4 4.6 0.44468 0.44468 0.22234 -0.44468 -4.3 4.6 0.452485 0.452485 0.226243 -0.452485 -4.2 4.6 0.460243 0.460243 0.230122 -0.460243 -4.1 4.6 0.467947 0.467947 0.233974 -0.467947 -4 4.6 0.47559 0.47559 0.237795 -0.47559 -3.9 4.6 0.483164 0.483164 0.241582 -0.483164 -3.8 4.6 0.490662 0.490662 0.245331 -0.490662 -3.7 4.6 0.498077 0.498077 0.249039 -0.498077 -3.6 4.6 0.505403 0.505403 0.252701 -0.505403 -3.5 4.6 0.51263 0.51263 0.256315 -0.51263 -3.4 4.6 0.519754 0.519754 0.259877 -0.519754 -3.3 4.6 0.526765 0.526765 0.263383 -0.526765 -3.2 4.6 0.533658 0.533658 0.266829 -0.533658 -3.1 4.6 0.540425 0.540425 0.270212 -0.540425 -3 4.6 0.547058 0.547058 0.273529 -0.547058 -2.9 4.6 0.553552 0.553552 0.276776 -0.553552 -2.8 4.6 0.559898 0.559898 0.279949 -0.559898 -2.7 4.6 0.566091 0.566091 0.283046 -0.566091 -2.6 4.6 0.572124 0.572124 0.286062 -0.572124 -2.5 4.6 0.577989 0.577989 0.288995 -0.577989 -2.4 4.6 0.583681 0.583681 0.291841 -0.583681 -2.3 4.6 0.589194 0.589194 0.294597 -0.589194 -2.2 4.6 0.594521 0.594521 0.29726 -0.594521 -2.1 4.6 0.599655 0.599655 0.299828 -0.599655 -2 4.6 0.604593 0.604593 0.302296 -0.604593 -1.9 4.6 0.609327 0.609327 0.304664 -0.609327 -1.8 4.6 0.613853 0.613853 0.306926 -0.613853 -1.7 4.6 0.618165 0.618165 0.309082 -0.618165 -1.6 4.6 0.622258 0.622258 0.311129 -0.622258 -1.5 4.6 0.626128 0.626128 0.313064 -0.626128 -1.4 4.6 0.62977 0.62977 0.314885 -0.62977 -1.3 4.6 0.63318 0.63318 0.31659 -0.63318 -1.2 4.6 0.636354 0.636354 0.318177 -0.636354 -1.1 4.6 0.639288 0.639288 0.319644 -0.639288 -1 4.6 0.641979 0.641979 0.320989 -0.641979 -0.9 4.6 0.644423 0.644423 0.322211 -0.644423 -0.8 4.6 0.646618 0.646618 0.323309 -0.646618 -0.7 4.6 0.64856 0.64856 0.32428 -0.64856 -0.6 4.6 0.650249 0.650249 0.325124 -0.650249 -0.5 4.6 0.651681 0.651681 0.325841 -0.651681 -0.4 4.6 0.652855 0.652855 0.326428 -0.652855 -0.3 4.6 0.65377 0.65377 0.326885 -0.65377 -0.2 4.6 0.654424 0.654424 0.327212 -0.654424 -0.1 4.6 0.654817 0.654817 0.327408 -0.654817 0 4.6 0.654948 0.654948 0.327474 -0.654948 0.1 4.6 0.654817 0.654817 0.327408 -0.654817 0.2 4.6 0.654424 0.654424 0.327212 -0.654424 0.3 4.6 0.65377 0.65377 0.326885 -0.65377 0.4 4.6 0.652855 0.652855 0.326428 -0.652855 0.5 4.6 0.651681 0.651681 0.325841 -0.651681 0.6 4.6 0.650249 0.650249 0.325124 -0.650249 0.7 4.6 0.64856 0.64856 0.32428 -0.64856 0.8 4.6 0.646618 0.646618 0.323309 -0.646618 0.9 4.6 0.644423 0.644423 0.322211 -0.644423 1 4.6 0.641979 0.641979 0.320989 -0.641979 1.1 4.6 0.639288 0.639288 0.319644 -0.639288 1.2 4.6 0.636354 0.636354 0.318177 -0.636354 1.3 4.6 0.63318 0.63318 0.31659 -0.63318 1.4 4.6 0.62977 0.62977 0.314885 -0.62977 1.5 4.6 0.626128 0.626128 0.313064 -0.626128 1.6 4.6 0.622258 0.622258 0.311129 -0.622258 1.7 4.6 0.618165 0.618165 0.309082 -0.618165 1.8 4.6 0.613853 0.613853 0.306926 -0.613853 1.9 4.6 0.609327 0.609327 0.304664 -0.609327 2 4.6 0.604593 0.604593 0.302296 -0.604593 2.1 4.6 0.599655 0.599655 0.299828 -0.599655 2.2 4.6 0.594521 0.594521 0.29726 -0.594521 2.3 4.6 0.589194 0.589194 0.294597 -0.589194 2.4 4.6 0.583681 0.583681 0.291841 -0.583681 2.5 4.6 0.577989 0.577989 0.288995 -0.577989 2.6 4.6 0.572124 0.572124 0.286062 -0.572124 2.7 4.6 0.566091 0.566091 0.283046 -0.566091 2.8 4.6 0.559898 0.559898 0.279949 -0.559898 2.9 4.6 0.553552 0.553552 0.276776 -0.553552 3 4.6 0.547058 0.547058 0.273529 -0.547058 3.1 4.6 0.540425 0.540425 0.270212 -0.540425 3.2 4.6 0.533658 0.533658 0.266829 -0.533658 3.3 4.6 0.526765 0.526765 0.263383 -0.526765 3.4 4.6 0.519754 0.519754 0.259877 -0.519754 3.5 4.6 0.51263 0.51263 0.256315 -0.51263 3.6 4.6 0.505403 0.505403 0.252701 -0.505403 3.7 4.6 0.498077 0.498077 0.249039 -0.498077 3.8 4.6 0.490662 0.490662 0.245331 -0.490662 3.9 4.6 0.483164 0.483164 0.241582 -0.483164 4 4.6 0.47559 0.47559 0.237795 -0.47559 4.1 4.6 0.467947 0.467947 0.233974 -0.467947 4.2 4.6 0.460243 0.460243 0.230122 -0.460243 4.3 4.6 0.452485 0.452485 0.226243 -0.452485 4.4 4.6 0.44468 0.44468 0.22234 -0.44468 4.5 4.6 0.436835 0.436835 0.218417 -0.436835 4.6 4.6 0.428956 0.428956 0.214478 -0.428956 4.7 4.6 0.421052 0.421052 0.210526 -0.421052 4.8 4.6 0.413127 0.413127 0.206564 -0.413127 4.9 4.6 0.40519 0.40519 0.202595 -0.40519 -5 4.7 0.389925 0.389925 0.194963 -0.389925 -4.9 4.7 0.397723 0.397723 0.198861 -0.397723 -4.8 4.7 0.405514 0.405514 0.202757 -0.405514 -4.7 4.7 0.413292 0.413292 0.206646 -0.413292 -4.6 4.7 0.421052 0.421052 0.210526 -0.421052 -4.5 4.7 0.428785 0.428785 0.214392 -0.428785 -4.4 4.7 0.436486 0.436486 0.218243 -0.436486 -4.3 4.7 0.444147 0.444147 0.222073 -0.444147 -4.2 4.7 0.451762 0.451762 0.225881 -0.451762 -4.1 4.7 0.459324 0.459324 0.229662 -0.459324 -4 4.7 0.466825 0.466825 0.233413 -0.466825 -3.9 4.7 0.47426 0.47426 0.23713 -0.47426 -3.8 4.7 0.48162 0.48162 0.24081 -0.48162 -3.7 4.7 0.488899 0.488899 0.244449 -0.488899 -3.6 4.7 0.496089 0.496089 0.248044 -0.496089 -3.5 4.7 0.503184 0.503184 0.251592 -0.503184 -3.4 4.7 0.510176 0.510176 0.255088 -0.510176 -3.3 4.7 0.517058 0.517058 0.258529 -0.517058 -3.2 4.7 0.523824 0.523824 0.261912 -0.523824 -3.1 4.7 0.530466 0.530466 0.265233 -0.530466 -3 4.7 0.536977 0.536977 0.268489 -0.536977 -2.9 4.7 0.543351 0.543351 0.271675 -0.543351 -2.8 4.7 0.549581 0.549581 0.27479 -0.549581 -2.7 4.7 0.555659 0.555659 0.27783 -0.555659 -2.6 4.7 0.561581 0.561581 0.28079 -0.561581 -2.5 4.7 0.567338 0.567338 0.283669 -0.567338 -2.4 4.7 0.572925 0.572925 0.286463 -0.572925 -2.3 4.7 0.578336 0.578336 0.289168 -0.578336 -2.2 4.7 0.583565 0.583565 0.291782 -0.583565 -2.1 4.7 0.588605 0.588605 0.294302 -0.588605 -2 4.7 0.593451 0.593451 0.296726 -0.593451 -1.9 4.7 0.598098 0.598098 0.299049 -0.598098 -1.8 4.7 0.602541 0.602541 0.30127 -0.602541 -1.7 4.7 0.606773 0.606773 0.303387 -0.606773 -1.6 4.7 0.610791 0.610791 0.305396 -0.610791 -1.5 4.7 0.61459 0.61459 0.307295 -0.61459 -1.4 4.7 0.618165 0.618165 0.309082 -0.618165 -1.3 4.7 0.621512 0.621512 0.310756 -0.621512 -1.2 4.7 0.624627 0.624627 0.312314 -0.624627 -1.1 4.7 0.627507 0.627507 0.313754 -0.627507 -1 4.7 0.630148 0.630148 0.315074 -0.630148 -0.9 4.7 0.632547 0.632547 0.316274 -0.632547 -0.8 4.7 0.634702 0.634702 0.317351 -0.634702 -0.7 4.7 0.636609 0.636609 0.318304 -0.636609 -0.6 4.7 0.638266 0.638266 0.319133 -0.638266 -0.5 4.7 0.639672 0.639672 0.319836 -0.639672 -0.4 4.7 0.640824 0.640824 0.320412 -0.640824 -0.3 4.7 0.641722 0.641722 0.320861 -0.641722 -0.2 4.7 0.642364 0.642364 0.321182 -0.642364 -0.1 4.7 0.64275 0.64275 0.321375 -0.64275 0 4.7 0.642878 0.642878 0.321439 -0.642878 0.1 4.7 0.64275 0.64275 0.321375 -0.64275 0.2 4.7 0.642364 0.642364 0.321182 -0.642364 0.3 4.7 0.641722 0.641722 0.320861 -0.641722 0.4 4.7 0.640824 0.640824 0.320412 -0.640824 0.5 4.7 0.639672 0.639672 0.319836 -0.639672 0.6 4.7 0.638266 0.638266 0.319133 -0.638266 0.7 4.7 0.636609 0.636609 0.318304 -0.636609 0.8 4.7 0.634702 0.634702 0.317351 -0.634702 0.9 4.7 0.632547 0.632547 0.316274 -0.632547 1 4.7 0.630148 0.630148 0.315074 -0.630148 1.1 4.7 0.627507 0.627507 0.313754 -0.627507 1.2 4.7 0.624627 0.624627 0.312314 -0.624627 1.3 4.7 0.621512 0.621512 0.310756 -0.621512 1.4 4.7 0.618165 0.618165 0.309082 -0.618165 1.5 4.7 0.61459 0.61459 0.307295 -0.61459 1.6 4.7 0.610791 0.610791 0.305396 -0.610791 1.7 4.7 0.606773 0.606773 0.303387 -0.606773 1.8 4.7 0.602541 0.602541 0.30127 -0.602541 1.9 4.7 0.598098 0.598098 0.299049 -0.598098 2 4.7 0.593451 0.593451 0.296726 -0.593451 2.1 4.7 0.588605 0.588605 0.294302 -0.588605 2.2 4.7 0.583565 0.583565 0.291782 -0.583565 2.3 4.7 0.578336 0.578336 0.289168 -0.578336 2.4 4.7 0.572925 0.572925 0.286463 -0.572925 2.5 4.7 0.567338 0.567338 0.283669 -0.567338 2.6 4.7 0.561581 0.561581 0.28079 -0.561581 2.7 4.7 0.555659 0.555659 0.27783 -0.555659 2.8 4.7 0.549581 0.549581 0.27479 -0.549581 2.9 4.7 0.543351 0.543351 0.271675 -0.543351 3 4.7 0.536977 0.536977 0.268489 -0.536977 3.1 4.7 0.530466 0.530466 0.265233 -0.530466 3.2 4.7 0.523824 0.523824 0.261912 -0.523824 3.3 4.7 0.517058 0.517058 0.258529 -0.517058 3.4 4.7 0.510176 0.510176 0.255088 -0.510176 3.5 4.7 0.503184 0.503184 0.251592 -0.503184 3.6 4.7 0.496089 0.496089 0.248044 -0.496089 3.7 4.7 0.488899 0.488899 0.244449 -0.488899 3.8 4.7 0.48162 0.48162 0.24081 -0.48162 3.9 4.7 0.47426 0.47426 0.23713 -0.47426 4 4.7 0.466825 0.466825 0.233413 -0.466825 4.1 4.7 0.459324 0.459324 0.229662 -0.459324 4.2 4.7 0.451762 0.451762 0.225881 -0.451762 4.3 4.7 0.444147 0.444147 0.222073 -0.444147 4.4 4.7 0.436486 0.436486 0.218243 -0.436486 4.5 4.7 0.428785 0.428785 0.214392 -0.428785 4.6 4.7 0.421052 0.421052 0.210526 -0.421052 4.7 4.7 0.413292 0.413292 0.206646 -0.413292 4.8 4.7 0.405514 0.405514 0.202757 -0.405514 4.9 4.7 0.397723 0.397723 0.198861 -0.397723 -5 4.8 0.382587 0.382587 0.191293 -0.382587 -4.9 4.8 0.390237 0.390237 0.195119 -0.390237 -4.8 4.8 0.397882 0.397882 0.198941 -0.397882 -4.7 4.8 0.405514 0.405514 0.202757 -0.405514 -4.6 4.8 0.413127 0.413127 0.206564 -0.413127 -4.5 4.8 0.420715 0.420715 0.210357 -0.420715 -4.4 4.8 0.428271 0.428271 0.214135 -0.428271 -4.3 4.8 0.435788 0.435788 0.217894 -0.435788 -4.2 4.8 0.443259 0.443259 0.22163 -0.443259 -4.1 4.8 0.450679 0.450679 0.225339 -0.450679 -4 4.8 0.458039 0.458039 0.22902 -0.458039 -3.9 4.8 0.465334 0.465334 0.232667 -0.465334 -3.8 4.8 0.472556 0.472556 0.236278 -0.472556 -3.7 4.8 0.479697 0.479697 0.239849 -0.479697 -3.6 4.8 0.486752 0.486752 0.243376 -0.486752 -3.5 4.8 0.493713 0.493713 0.246857 -0.493713 -3.4 4.8 0.500574 0.500574 0.250287 -0.500574 -3.3 4.8 0.507327 0.507327 0.253663 -0.507327 -3.2 4.8 0.513965 0.513965 0.256983 -0.513965 -3.1 4.8 0.520482 0.520482 0.260241 -0.520482 -3 4.8 0.526871 0.526871 0.263435 -0.526871 -2.9 4.8 0.533125 0.533125 0.266562 -0.533125 -2.8 4.8 0.539237 0.539237 0.269619 -0.539237 -2.7 4.8 0.545201 0.545201 0.272601 -0.545201 -2.6 4.8 0.551011 0.551011 0.275506 -0.551011 -2.5 4.8 0.55666 0.55666 0.27833 -0.55666 -2.4 4.8 0.562142 0.562142 0.281071 -0.562142 -2.3 4.8 0.567451 0.567451 0.283726 -0.567451 -2.2 4.8 0.572582 0.572582 0.286291 -0.572582 -2.1 4.8 0.577527 0.577527 0.288764 -0.577527 -2 4.8 0.582282 0.582282 0.291141 -0.582282 -1.9 4.8 0.586842 0.586842 0.293421 -0.586842 -1.8 4.8 0.591201 0.591201 0.2956 -0.591201 -1.7 4.8 0.595353 0.595353 0.297677 -0.595353 -1.6 4.8 0.599296 0.599296 0.299648 -0.599296 -1.5 4.8 0.603023 0.603023 0.301511 -0.603023 -1.4 4.8 0.606531 0.606531 0.303265 -0.606531 -1.3 4.8 0.609815 0.609815 0.304907 -0.609815 -1.2 4.8 0.612871 0.612871 0.306436 -0.612871 -1.1 4.8 0.615697 0.615697 0.307849 -0.615697 -1 4.8 0.618289 0.618289 0.309144 -0.618289 -0.9 4.8 0.620643 0.620643 0.310321 -0.620643 -0.8 4.8 0.622756 0.622756 0.311378 -0.622756 -0.7 4.8 0.624627 0.624627 0.312314 -0.624627 -0.6 4.8 0.626254 0.626254 0.313127 -0.626254 -0.5 4.8 0.627633 0.627633 0.313816 -0.627633 -0.4 4.8 0.628764 0.628764 0.314382 -0.628764 -0.3 4.8 0.629644 0.629644 0.314822 -0.629644 -0.2 4.8 0.630274 0.630274 0.315137 -0.630274 -0.1 4.8 0.630653 0.630653 0.315326 -0.630653 0 4.8 0.630779 0.630779 0.315389 -0.630779 0.1 4.8 0.630653 0.630653 0.315326 -0.630653 0.2 4.8 0.630274 0.630274 0.315137 -0.630274 0.3 4.8 0.629644 0.629644 0.314822 -0.629644 0.4 4.8 0.628764 0.628764 0.314382 -0.628764 0.5 4.8 0.627633 0.627633 0.313816 -0.627633 0.6 4.8 0.626254 0.626254 0.313127 -0.626254 0.7 4.8 0.624627 0.624627 0.312314 -0.624627 0.8 4.8 0.622756 0.622756 0.311378 -0.622756 0.9 4.8 0.620643 0.620643 0.310321 -0.620643 1 4.8 0.618289 0.618289 0.309144 -0.618289 1.1 4.8 0.615697 0.615697 0.307849 -0.615697 1.2 4.8 0.612871 0.612871 0.306436 -0.612871 1.3 4.8 0.609815 0.609815 0.304907 -0.609815 1.4 4.8 0.606531 0.606531 0.303265 -0.606531 1.5 4.8 0.603023 0.603023 0.301511 -0.603023 1.6 4.8 0.599296 0.599296 0.299648 -0.599296 1.7 4.8 0.595353 0.595353 0.297677 -0.595353 1.8 4.8 0.591201 0.591201 0.2956 -0.591201 1.9 4.8 0.586842 0.586842 0.293421 -0.586842 2 4.8 0.582282 0.582282 0.291141 -0.582282 2.1 4.8 0.577527 0.577527 0.288764 -0.577527 2.2 4.8 0.572582 0.572582 0.286291 -0.572582 2.3 4.8 0.567451 0.567451 0.283726 -0.567451 2.4 4.8 0.562142 0.562142 0.281071 -0.562142 2.5 4.8 0.55666 0.55666 0.27833 -0.55666 2.6 4.8 0.551011 0.551011 0.275506 -0.551011 2.7 4.8 0.545201 0.545201 0.272601 -0.545201 2.8 4.8 0.539237 0.539237 0.269619 -0.539237 2.9 4.8 0.533125 0.533125 0.266562 -0.533125 3 4.8 0.526871 0.526871 0.263435 -0.526871 3.1 4.8 0.520482 0.520482 0.260241 -0.520482 3.2 4.8 0.513965 0.513965 0.256983 -0.513965 3.3 4.8 0.507327 0.507327 0.253663 -0.507327 3.4 4.8 0.500574 0.500574 0.250287 -0.500574 3.5 4.8 0.493713 0.493713 0.246857 -0.493713 3.6 4.8 0.486752 0.486752 0.243376 -0.486752 3.7 4.8 0.479697 0.479697 0.239849 -0.479697 3.8 4.8 0.472556 0.472556 0.236278 -0.472556 3.9 4.8 0.465334 0.465334 0.232667 -0.465334 4 4.8 0.458039 0.458039 0.22902 -0.458039 4.1 4.8 0.450679 0.450679 0.225339 -0.450679 4.2 4.8 0.443259 0.443259 0.22163 -0.443259 4.3 4.8 0.435788 0.435788 0.217894 -0.435788 4.4 4.8 0.428271 0.428271 0.214135 -0.428271 4.5 4.8 0.420715 0.420715 0.210357 -0.420715 4.6 4.8 0.413127 0.413127 0.206564 -0.413127 4.7 4.8 0.405514 0.405514 0.202757 -0.405514 4.8 4.8 0.397882 0.397882 0.198941 -0.397882 4.9 4.8 0.390237 0.390237 0.195119 -0.390237 -5 4.9 0.375236 0.375236 0.187618 -0.375236 -4.9 4.9 0.38274 0.38274 0.19137 -0.38274 -4.8 4.9 0.390237 0.390237 0.195119 -0.390237 -4.7 4.9 0.397723 0.397723 0.198861 -0.397723 -4.6 4.9 0.40519 0.40519 0.202595 -0.40519 -4.5 4.9 0.412632 0.412632 0.206316 -0.412632 -4.4 4.9 0.420042 0.420042 0.210021 -0.420042 -4.3 4.9 0.427415 0.427415 0.213707 -0.427415 -4.2 4.9 0.434743 0.434743 0.217372 -0.434743 -4.1 4.9 0.44202 0.44202 0.22101 -0.44202 -4 4.9 0.449239 0.449239 0.22462 -0.449239 -3.9 4.9 0.456393 0.456393 0.228197 -0.456393 -3.8 4.9 0.463476 0.463476 0.231738 -0.463476 -3.7 4.9 0.470481 0.470481 0.23524 -0.470481 -3.6 4.9 0.4774 0.4774 0.2387 -0.4774 -3.5 4.9 0.484228 0.484228 0.242114 -0.484228 -3.4 4.9 0.490956 0.490956 0.245478 -0.490956 -3.3 4.9 0.497579 0.497579 0.24879 -0.497579 -3.2 4.9 0.50409 0.50409 0.252045 -0.50409 -3.1 4.9 0.510482 0.510482 0.255241 -0.510482 -3 4.9 0.516748 0.516748 0.258374 -0.516748 -2.9 4.9 0.522882 0.522882 0.261441 -0.522882 -2.8 4.9 0.528877 0.528877 0.264438 -0.528877 -2.7 4.9 0.534726 0.534726 0.267363 -0.534726 -2.6 4.9 0.540425 0.540425 0.270212 -0.540425 -2.5 4.9 0.545965 0.545965 0.272983 -0.545965 -2.4 4.9 0.551342 0.551342 0.275671 -0.551342 -2.3 4.9 0.556549 0.556549 0.278275 -0.556549 -2.2 4.9 0.561581 0.561581 0.28079 -0.561581 -2.1 4.9 0.566431 0.566431 0.283216 -0.566431 -2 4.9 0.571095 0.571095 0.285547 -0.571095 -1.9 4.9 0.575567 0.575567 0.287783 -0.575567 -1.8 4.9 0.579842 0.579842 0.289921 -0.579842 -1.7 4.9 0.583915 0.583915 0.291957 -0.583915 -1.6 4.9 0.587781 0.587781 0.293891 -0.587781 -1.5 4.9 0.591437 0.591437 0.295719 -0.591437 -1.4 4.9 0.594877 0.594877 0.297439 -0.594877 -1.3 4.9 0.598098 0.598098 0.299049 -0.598098 -1.2 4.9 0.601096 0.601096 0.300548 -0.601096 -1.1 4.9 0.603868 0.603868 0.301934 -0.603868 -1 4.9 0.606409 0.606409 0.303205 -0.606409 -0.9 4.9 0.608718 0.608718 0.304359 -0.608718 -0.8 4.9 0.610791 0.610791 0.305396 -0.610791 -0.7 4.9 0.612626 0.612626 0.306313 -0.612626 -0.6 4.9 0.614221 0.614221 0.307111 -0.614221 -0.5 4.9 0.615574 0.615574 0.307787 -0.615574 -0.4 4.9 0.616683 0.616683 0.308342 -0.616683 -0.3 4.9 0.617547 0.617547 0.308774 -0.617547 -0.2 4.9 0.618165 0.618165 0.309082 -0.618165 -0.1 4.9 0.618536 0.618536 0.309268 -0.618536 0 4.9 0.61866 0.61866 0.30933 -0.61866 0.1 4.9 0.618536 0.618536 0.309268 -0.618536 0.2 4.9 0.618165 0.618165 0.309082 -0.618165 0.3 4.9 0.617547 0.617547 0.308774 -0.617547 0.4 4.9 0.616683 0.616683 0.308342 -0.616683 0.5 4.9 0.615574 0.615574 0.307787 -0.615574 0.6 4.9 0.614221 0.614221 0.307111 -0.614221 0.7 4.9 0.612626 0.612626 0.306313 -0.612626 0.8 4.9 0.610791 0.610791 0.305396 -0.610791 0.9 4.9 0.608718 0.608718 0.304359 -0.608718 1 4.9 0.606409 0.606409 0.303205 -0.606409 1.1 4.9 0.603868 0.603868 0.301934 -0.603868 1.2 4.9 0.601096 0.601096 0.300548 -0.601096 1.3 4.9 0.598098 0.598098 0.299049 -0.598098 1.4 4.9 0.594877 0.594877 0.297439 -0.594877 1.5 4.9 0.591437 0.591437 0.295719 -0.591437 1.6 4.9 0.587781 0.587781 0.293891 -0.587781 1.7 4.9 0.583915 0.583915 0.291957 -0.583915 1.8 4.9 0.579842 0.579842 0.289921 -0.579842 1.9 4.9 0.575567 0.575567 0.287783 -0.575567 2 4.9 0.571095 0.571095 0.285547 -0.571095 2.1 4.9 0.566431 0.566431 0.283216 -0.566431 2.2 4.9 0.561581 0.561581 0.28079 -0.561581 2.3 4.9 0.556549 0.556549 0.278275 -0.556549 2.4 4.9 0.551342 0.551342 0.275671 -0.551342 2.5 4.9 0.545965 0.545965 0.272983 -0.545965 2.6 4.9 0.540425 0.540425 0.270212 -0.540425 2.7 4.9 0.534726 0.534726 0.267363 -0.534726 2.8 4.9 0.528877 0.528877 0.264438 -0.528877 2.9 4.9 0.522882 0.522882 0.261441 -0.522882 3 4.9 0.516748 0.516748 0.258374 -0.516748 3.1 4.9 0.510482 0.510482 0.255241 -0.510482 3.2 4.9 0.50409 0.50409 0.252045 -0.50409 3.3 4.9 0.497579 0.497579 0.24879 -0.497579 3.4 4.9 0.490956 0.490956 0.245478 -0.490956 3.5 4.9 0.484228 0.484228 0.242114 -0.484228 3.6 4.9 0.4774 0.4774 0.2387 -0.4774 3.7 4.9 0.470481 0.470481 0.23524 -0.470481 3.8 4.9 0.463476 0.463476 0.231738 -0.463476 3.9 4.9 0.456393 0.456393 0.228197 -0.456393 4 4.9 0.449239 0.449239 0.22462 -0.449239 4.1 4.9 0.44202 0.44202 0.22101 -0.44202 4.2 4.9 0.434743 0.434743 0.217372 -0.434743 4.3 4.9 0.427415 0.427415 0.213707 -0.427415 4.4 4.9 0.420042 0.420042 0.210021 -0.420042 4.5 4.9 0.412632 0.412632 0.206316 -0.412632 4.6 4.9 0.40519 0.40519 0.202595 -0.40519 4.7 4.9 0.397723 0.397723 0.198861 -0.397723 4.8 4.9 0.390237 0.390237 0.195119 -0.390237 4.9 4.9 0.38274 0.38274 0.19137 -0.38274 Sigima-1.1.1/sigima/data/tests/image_formats/coordinated_text/image.txt000066400000000000000000000003251514013333200262410ustar00rootroot00000000000000############################## # Created on 2013-05-16 09:45:41.203000 # By Username # nx : 3 # ny : 2 # X : (pixel) # Y : (pixel) # Z : (lsb) ############################## 0 0 1 1 0 2 2 0 3 0 1 4 1 1 5 2 1 6 Sigima-1.1.1/sigima/data/tests/image_formats/coordinated_text/image2.txt000066400000000000000000000005651514013333200263310ustar00rootroot00000000000000# Created on 2020-12-03 09:35:33.049769 # By Username # Using matrislib 3.2.0 # nx : 3 # ny : 2 # X : (pixel) # Y : (pixel) # Z : (lsb) 0.000000e+00 0.000000e+00 1.000000e+00 1.000000e+00 0.000000e+00 2.000000e+00 2.000000e+00 0.000000e+00 3.000000e+00 0.000000e+00 1.000000e+00 4.000000e+00 1.000000e+00 1.000000e+00 5.000000e+00 2.000000e+00 1.000000e+00 6.000000e+00 Sigima-1.1.1/sigima/data/tests/image_formats/coordinated_text/image_no_unit_no_label.txt000066400000000000000000000005421514013333200316300ustar00rootroot00000000000000# Created on 2016-03-22 11:47:58.738000 # By Username # Using matrislib 3.0.0alpha5 # nx : 3 # ny : 2 # X : # Y : # Z : 0.000000e+00 0.000000e+00 1.000000e+00 1.000000e+00 0.000000e+00 2.000000e+00 2.000000e+00 0.000000e+00 3.000000e+00 0.000000e+00 1.000000e+00 4.000000e+00 1.000000e+00 1.000000e+00 5.000000e+00 2.000000e+00 1.000000e+00 6.000000e+00 Sigima-1.1.1/sigima/data/tests/image_formats/coordinated_text/image_with_nan.txt000066400000000000000000000003331514013333200301270ustar00rootroot00000000000000############################## # Created on 2013-05-16 09:45:41.203000 # By Username # nx : 3 # ny : 2 # X : (pixel) # Y : (pixel) # Z : (lsb) ############################## 0 0 1 1 0 2 2 0 NaN 0 1 NaN 1 1 NaN 2 1 6 Sigima-1.1.1/sigima/data/tests/image_formats/coordinated_text/image_with_unit.txt000066400000000000000000000005631514013333200303370ustar00rootroot00000000000000# Created on 2016-03-22 11:47:58.738000 # By Username # Using matrislib 3.0.0alpha5 # nx : 3 # ny : 2 # X : (mm) # Y : (nm) # Z : (A) 0.000000e+00 0.000000e+00 1.000000e+00 1.000000e+00 0.000000e+00 2.000000e+00 2.000000e+00 0.000000e+00 3.000000e+00 0.000000e+00 1.000000e+00 4.000000e+00 1.000000e+00 1.000000e+00 5.000000e+00 2.000000e+00 1.000000e+00 6.000000e+00 Sigima-1.1.1/sigima/data/tests/image_formats/fiber.bmp000066400000000000000000011320661514013333200226570ustar00rootroot00000000000000BM66(   """###!!!$$$%%%&&&''')))(((***---,,,+++...000///222111888777444999===@@@:::555GGGBBBDDDKKKMMMHHHNNNQQQEEEFFF333CCCJJJ<<>>AAAPPPRRRIIILLLYYY\\\___XXXWWW^^^fffgggaaa```SSS[[[ZZZjjjlllkkkOOOVVVccchhhooorrrpppiii]]]eeedddnnntttvvvuuummmUUUTTTqqqbbbzzzsss}}}wwwyyy|||{{{xxx~~~   &%! !!$%##" +4229-$!),/.-,&&!")/JEMrqqM?JI.428KG329/-*'%!##" ##%%&&'/4I3I-&!" *2;OBL5.'! """!$%#!      $('(&  " #+040-% $'((%&% "%-8@=CEG3D, !*0G666340DDDD-)! (*141+( " !$)+D234*&!#$# $&$!"!$&-.-*)#     #%&,'%!##" !'-43J839/'%#&05EP=N@BK/$!$'1328GJ2.*)%# &&&'-IH?M[[AP?EK50&)D5J682I44394D,& !&&')($  &,10/(  ###()'&!""#&&,/1/,$       $#$$ #&%#  !&/49I01-'$! $/5;OAb]rFKD&!$'.444II0/'&%$#$$#"$''),-4J?MqbqA@?:EGD,"(/2J52I40D4D4DD/,(%# #!"!"#(,'$!!'+-+,(#$# !#(,)++)$" "            &)(#   $$#!%! ""!!!(16?[U\QTrFKD(" $#&),,-+))((,-/00-(" &,+*+,)/36B?P>F:BK31'" &/433490.....001.D0-/*($ !  &)-1/'$ '+-.*)(&%!#$$$&'(% !$!"          !%'%! "#$!""$#,3B@bRSRT@aqbaCKD1.D5GJ24./.9G6G2D*% $&&(&#             " "!(,,'%! ,IKE:;69-&!"!%'*08HHHJ5D,$ &%(''(!""!(&'*/D990+$ $%$"$*052ID0.-1I7>NQ][OGD.-4JK6JI/**/441/(!!#$(,'&                   $)-.0D-'! ,426G30*%" #%)/4J;BaCLI*)&'+)& !'*9J8G51(" $&&$              #()/49I41)% "" (/442D/+'%#(*02J859)!"###!"$%#!&*D95291)!"+2HBBKI+&!" !'1JKH69*&""#%&$!    ""&(&#         "$))*.1./+($ !" %*/I8D/,&$#&+.353I.$"! "!$%"""(-02G685.,%  +48684+  #!!*DJK831(# ""!%'))'%#  " ""!%&$"       "!$$'***-*,'$ " #!" (/II9.+$ !&-9230+! !&&$!"" !" "  #+.I56G24/( #)/491+"!&')(#!,12341,$ ""!#&)*/1*&!  "#$#"        """!#%()*10-+(#!"! ! ""&*0440'#!+D331'" "!%()'#! "!#!$%&&$""""$,/4294D*%" $&(% !,///'#"#'/.11-)% !&*/-,(!"" $%'*1DD/(! !! "$!          ""!$##!" !#+0444.,&""## # "(*.0D.( ")14I.) !""!$#&','(((&#$$%(''% "$(,/..+,)!$+1I4-(!"&+**)! &/9GKJGI-)%""!%%$ ""#&*1DI4/,#"!!###! "             $%()))&!"!)128JI9-(!"" !!%!" #)-11-$&-.0/'! "" ##$&(%()&')&&&$%'))))%! !'(''(#!%.5H7J9*%!$),))! (0G;::BL84+%!" # (+.II94*$#&&&(%$&  "   ! $"         "#&,,/***'$#-3K<:GI1'$"#&($"!$&*422G4-( "$&(&!$'+,)((((!   &'))$       " #'+*,'"""#(+/D25531(&0L>MaFE3*(!!" " "" %+/.+& $(%#"""#()()%! "!"!!##!&4HOMAFH9*)%($! '4;FNq@OEK3-)&" %(&! $(,D92540)"$()&$$%%&((')($ $'('&#       "$(%$! "&+0DD-( #" #+/4IG6J0(%D7PrN?73-'## ""#)++,&"" #(&&$ "#&''$""!  #&%% %0JBPa=L4*)(%%! (06<>>?<784-'% !%$##(*193291, "$((%!"!#! !((&%%  !%''(&#"        "&'))& &/3320' ##$  &+0286J4," 17F[A=L3.)&%#!""%&,,'$ $'/.D*'%# #(&&!" #!"#%"#$('&$ &.27CC;J1'$$%% !'.IK;LLG5D1+&!" !#%+.999I.,$#%%#" %%%$!  "!&'%##          "$,*,+)( %-IG84+! !$%$ $,/98J82*"*G:a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ra?G0$               &')+**+,''&))*.45J391'! (DLO<5/(#"" !! " """#()*/-'#"(-DD1/+))$ "!%)($#"!#$% +IGL<7G90142JJI.)%! !%,+/.,&"(,)( )9<[RRq:G1# #$&$&%#""" """ !$&&(),14330,  -3K7K4+              "   $(+1I5HEE764*!"'D6BPMPBJ1*%"""" ""! ""#$%! ! &*1//+&&*D4./.+)&#!""$%)+))&! #&('&# ,4K<:CK828KLBQSiMBLKCMqA:J-$"(-I7LKD,&!&*056K;LG55I94.D/*.*-///11.1/10DD1-,&%%$##!"              "%,**)'%!"$9<64'!)./*&  %,*.*)% %%# +5?rVQM:L6H:FFH4)"&1JHEK9*,'*43KEbb@EK856H72/(!#)DGH780*()*19J67LH77E:B7KJID/.*-1004I2J88G83I0-)! "!!"        #&',*+)'#(97>]R][<0$%/42GG5I9DI86L<@NUTAPP;D%  (08E>ANa?LI)"'-IG3.& ! ")2EFOC63//453/+,)*13883.)%!%),0935226KLC<77H21.-)*.14IGJGG6GG5D-)& "('(&        $&'-*,)$ " $'47O[Ub@L1&#)*DD1/-..0357B@QiccQNC62IIID1+,,-0999I91/-*))''&$$#"#',/D./&)0251+ $/H@Tra6+ ! $+3H?@>@:74(,.G7K3+#"#%$$$#"$/IGHK3.,&,*+-/DII8G89.)! "$()---*1D93H;77629/+**/458K7K6J5I4.'& $,./,("        "#%+,(&#"#))*/.D2E:PMM?J.%%'++))$#&'-098HO]k`ehi[<623I4/+'&&,**-/*(&!""!"! " !##!%%),++(! .JLL8-$ *LaQRr:I% ###)087C=FBGD('I;;qUq=H4+&!!!$&###" #"&06K.!%1K??E2("!+I8I41/IL>]ZZ\r=9#*2KHG0,'&,'++,',)%#"%.8;O>?73,-G=b\\N>B8D+(&### ")3?PP=<8D/-03GKK59937MjoyX[;4*+/D994/($'*--*-146qbqM?;HJ66KK84.,)%! !$&&$" ,1429D1-,'&"*KAthtrH'%*1D0,($$'''+***+,%!"+5<>NMOK4%(9CqiVVVQ=73.)&$!!,2<>a@:GD+,.5LBCF:LG83GJ665341,'$ " $'*//' (/DI930.+))#""&GAY`hRO9! &+,,&!!!$'+/.141.,$!(I<=NbM:8/#"-H>VWdjYT>;3*(%"$-2LOFC721,+/JC?=F:L7BNYmːxY@K1-*-049.(! #$!$%'.05;:O?E69/(#" "$)DIII1)! !!!!"!##!# "     !%),*-'!"" #$()*111*%#'+.438L>[R_vspWU?9%*8[rN=i^o}vX]>8*$"!$$% #,/42GGG3/+#"$&,)$""!!!%$(,,-**,&!!$$#%$###        %)--+)(($  #!$$$&'',--/,)$ )-.1.//1IJBP@N@O;9' #,.I9/("!(.D9-%$*//*(%###%&)))+./*&# #,02HGI.&#$$###!")8atWYi=J/&$&')'($#&-47:MrAO78D..--*&"'IBUZcj]@L0& -HM]cjtQ@L4*$"$)/441-+($(*-19I26LFAbqM=L235H>]k`jV[;4)!(+.0940/,&"!#""!##"!#$&&+..1//*%! $(%!$"      !(+-*++,)&!"!!#%!##$&',),(&$ "&+.1/*,'')/I5GK69/&"$'++&!%+,%!&),%""" #$%)+-*+($#'1IGHG20)$""" #D:USZ]=6D)&(&()(&&'.8BATTqO;I1..11-'! )I?]Y`^YbCG-! ,5OqiZ]aB8.'"(-I8KHG9-&%).IJ7B?AqQqNFGID437P[bbA?J1&!%(,.00.+)%!"$)*,% """"#(,+1I41-)% "##$#""     $',.1/1.,%"!!!!!! !$!&&#$! (,-/+%#"#&)*+)&!"$#""!&''#" !#&)-..*,)*48KHK80*'! ""*G@T\T>K0,')')(&%$'/JO[Q]rF60**-1/-&#",8aS^sgdR=K.& '3E@UTA:G0)#""'-DKBFF:H4,""&*IHBPMNUrr@:631.19H<<:EGI+$""!!!"#%),+-/111/,% '/D94/%" "" &'+1DDD-'#"     "&)/1.D0/' !! ! "" ""!&,)(! %''%!!$'/10./14JLEEH51/)&#!&&$ "'97F@>CJD,),''%$$!$)IBa[b@L1)%&(*+'!!-7Atfom`RaK0'!!'47FNa:6D,#%*0JCarrMOG/!#,D6C=NqqqN=CLG9010928559.(# $$ %'*109255901-&!"!&-3K7J4+" """ ! "!%(,.-*)$          (),.001,%"!!$#! "%$$ $'*,&"!'*11.1I67:?BH20*+)%# $+*..*)#!-IH;L6ID*++,)%$%/2;?O79'""&)'!"%DLqhemshbC8.&!!(0LO?:L4,$!!(-I;=[QRbME0%$/3KE=aPMaOBEH2D0D.00D.+,&!#$#$% "" !$##!#&,/0867;7HG3D,'$ "%-3K><5/'#!##%(,.27;L2/% $),*+*+*10ID40( $'(% (,'!%1EbSddiML9, &.IGHJ.&!!#! !(-96;?Mrr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qr=H4,%%'.5LBFE9'",03J8D'#-4GHKJI-(""#!#$"#')(($# ! " $!$(,/2J7HH6II.)%        " !##!#$&&&'%$$&%%$  (,+1DI25J7CaFB788HC@\RTMB3)##%(&%# " #'D3G7JI401I91*%%-6rWefeR>CC=PFB81+*D2J3/&!1EbtXtQ@KI1+(%"""%&',-+( '.4I9-+-14GHKJ4+)% """$'+*+%%*+)$"&+091/+&! $+9<[RY]PG'(110,# (*D0/.-/,%#"""! %%!"""!#&%($#!#! """(+43GLECC7J9.(     !!&(,-/1D49I34.'$"!&'*..98;Fab\rPCJI5E@UR\A:2,"!&&($"""#)/IKHHGI00D9D/(#!*LRswzgROJIG7LGI/)*D854/("" (IFSlmgkqB8D*)&$  &'+.0D-' "&+**)&!(*D5GHGI0-+)(##'-/+%"$,+,$!'/D41*($#%(.6?UZYR>J)#)+*( "&,//''(',,&$#%'),(% "!$),(&#""" #(*02G6;;659*&           " $%(+-.42JG65I1,$#'--/D42GC>QYjYqPH536:@TUMB4(!! &($!" #!(*457E;7J3D44D/$"+ESnvZCD*/II41,)-I2531,&%$$+6r`||^]O80-+()$! ""#&+/499D/'# $%&%$"!'.I2523.-1/+' $(++,(!$),)%"#,140.+%#!$)4GOUSRr=8, &)'#&139.+&!! %(##%)*1/-)(!" #,)$%$" " %),1433I4.)         !%'*13GHGKJ9/&!!'1I2J55GHC[VjdWSr<839GC=FC6-%" #!$!!#'+-13G7E;7639II0+#""/?Wxi<.&&+.1+'+.9G7K31/*($!/;ifz`R:59.//-)& ""#%)-025291/+')&#&*090DD-/11-( !$''&$ !&)+'$ #,0D0-,$ ##'05CNUU@L3+"$$#&0KB780&!! "!%,*1D1-*'#!"%')(%!!&)++,)'#        """#&)1I6GJJ21)%'0JO?>@[SXkiqOG.-*-D0//($! " &-004258KLLBCE;HLH9*)-HTvuc?.$ $((',-IH:@>?EJI/%#4:ifyxlS@;3I0099D.,%""$,.I6H:B:FMT]QMCG0*'(,,-*,,++)(%!+/44D4942GLBCCBOC;G29J=Sy{kOD% !$(%,03BMqNM:E81%$DBi`v_kbBJ0111DD4.-'%" "$+02EF>=E3)#(&"#&)++(# $##!"" !$!" ! "!##&)/0I9.,&""#!"*LT`feYM8,#$)/382591)!!%),()($ ""    ! """""  "!!!$$',)'(%$  &)+/.0.+'(,/I2) !##%).5E=aA@=;2*!&4EbZZRM:G0-+--/DI11/,&%$$$"#*37?FM?6-"#$#"$)-11-(! ##$" " $ "#$(('-*)&# #$/BR^fetPJ.$! )1922I1)%#$)*))&#!   ! "!!#""  "$$%+++))'$  ""! ! "$(),/1/*),/9H=rY```tT>H3//.98683D/'$$#%'/I6H;;69, &-.//+(%'+.98LFO=P=?C@\`xcP2)$"!#$&/IJE=>O?HI,!%/K>ANP;31+,(),*/./.1/-**+)(&# ""!$)08<=M?K9'!!! "!(-4223D/'$ """" " $#!" " ""! " !#&(&%$"""###+7rtdWQCJ.)&# "(+/D0/,%" ##&)&%#!" " $&&#    "" !!!  !$&'+,,)%%$!$%&(++'%!""#&)*/.*-/*145B@Ttd`hVqBG.'##(,...-,'$#!(-15EBO:B61( $'+,)%%!"#(/I6;EB?::?a\jo{ugiCI*$" #'-I8ECB;G0)!*5HEBGI.)&%%" !%$$%$#(,)*1I529D-)&&$&$%'())+*'&(''),-/0D10492G7F;20+)(')'$! ! !#%&$%&'&'-////+'((),+'&))+-11.-/+,)))),**+/-*1104D1*'%""&1II9/,#!! " #!#!"%,D8?b]RRUT\YhdjUL1(&*3B=PC74,%&.6Fb]i\rPEG85I383240/-*-*-.D3HOA\V\NFB7KLLLH9.(#!"" "%+05J80) $/994/&!! #$#$)*48GG7765I9II9II0*&" $&),&&$" #!%'+,'&!       #! ""&*.95D4.+,+.142G76HG8J55GK;OOO:H2.)$#()+*)%! "$%&(',))+*,,'&&(,,/-,*--/44I9..-*),'((),)('&&$%$## "(12221)%" $&%  &',+9LMiccV]QQZd^dT:9(%+2[RZRrBI,'/9GHG9-$$+9KLB?:@QkpgpV>CCFrTqP6/((+485I-& #(*43253-,!#)./+% #&&&-2;Mi\[:JD1I6C?;3,!""!#'/982D*$ !! "%)/1.+% "#,.45G5I0+(%! #*3E@ArMFBHJ3D/,)($       " $),'(% """"" #$(,,**-.-+**+++,,)'(%$$ "#,138HBCEE7G825J667HKH7K8D-(!"#%)-.03DDD44D4944D11D100*%%+491)$"%%'+/.D95HCaUR]q>>M]WglWbCK6LOFFE2-(%+094.+&! $'*1110*'# #((%"!$$#'/8E==<5*()08UScVQN@MUYWWR>73I67EBHD)$&+/491*)',*1D4//,#""! " ##%(156G4,!"$/GCO<3,# %)+)$%-IG67JI/$"(+-+'& #%$"" "$)/1I9.*'##!$!#,JCMQQTN>:H20-)%!       "!$',*+'(%# !%%%%%#$&&*-+)''%##! !!!!#(.26EBC76GGJ6LC?C:qbQTqNrrN==E5/%!#&'*,(% !&+DIID1/-03L>TStibMA>MT\]M;2D036;K3/&!#(-04DDD14I2I1+'"##$%&)/40,  0G?F:8.'$$+/-+&"$+057L772/%)/1D/+# %$#"%+/994.)## #! %07P[r[MF:C?=>OE50.03K7K4,#" %*.D328JH7G5D-%"!""#%%#'+/1*&"#0HF>?71,)'/11-&"&-IJHELG4) "(.9I4.& !&'(%# (/09I1/( !!!!"*5;?P=BCH51+%        " $&%$#!!$#%,*.1.4-'&#" !#%#%,'(,,&$$%$&+-1.-'%$!""%)-09990/-.2HEO==?LG3D401D3HBFF@POEGD-'(,D7aij^hWkYttZSVr:J1+*-,,)&%)/367G2D+&(,46?EGKKGKJ90-+0J6J80%"%*19GHE:CE7G4,&%$#!!(((,/DD.'!&4L=@F;3-**-0.*& (*D2HKKI*&!'.4DD/&! &,,)& %192590)!"!"""$*4GK6J29/,%!             !(')'''(&(,-1DII341*'%# """$#$')(,'&$!"!&(*1401+&$ !!$',/101--')-IK?>>=;650//.D2G:@[Q\T[=;20,&&-JFbSXXkZZSRiZZ\>B8.*-/*+'(,0G;CLJ4)$ !)1I7;LH539D94.*++*DI229,#!,08;?P=F?;5D*'$  $##! #(,*.42251)%#(07F>PB8D--/1+(!")D285I.%  $+*1/)%!##! #&++*&#$-D8J29,&! " "$+-..-,)&!       $+--+**,))-/093225ID/*'(!" " !%(++)'(#! " &*.01.,%%##%&)-0D1.+)&'/I6OM@:720+*,*1I6CNQYjcRb=H5.,))D6Fb]RiUNrNAbTQ@B64.-++'%(,05L:BKI*# %*DD940.-+*,+,+-1I38I.)  )4GC>a>?CK4.-+)(%($ !%! #&).38KLH50-''1GCO=:63D-++'$"'-190-(#!$&+&!"#%),((#!%,++(% " ! !(.26J3.)&#$#""#"""#$$#!         "%,-1./10++*.435JGJ2I44/*'&!"" !((*--,(%"$(*-*,(#$%(')/49ID1*)%)-3;===CJ0*',)**18EaQSk^k\NO;K24/096:=PF?;K6L:=@O<89/*+'(&)+06B:?EJ/#$)*-*,)))''+-.4952ID*%!+4H?>>=;6ID+)*-./-,(%#!### !)*DJ7:L244435J521-+1D3HH631*,(%(&(+0JB:PCL2, &)'+,((%&+*9IG6J4//+$$/5EOaPCK4*&%'*13994-+'$%%%$ $).4KB:P>C72.*+187;BH654-)%""  (')+&!!" !!" $(($% $&),./*)$ "!$$##!!%%,/.11,$$/DIID1///.*(!" &(+(&% " ! ""       !%+,/DD10,+*-./1D44D04D10.+'&!!""$+/99I.*'" #%(()),/.0D04II4D*,'+03L:?72.,,*.4D0-.46>USttiRQ\TqM<64/+,,+,$"#)14D0*'&#!!%'*05<=@=:G1&#),*)&%#)/0J;aPL3,!$(*+)'%%,18EOCE8/+(()''('*06K;E64, "(+4555D-+,,,)% !%+05H<=PFMP<8.$ %,11-,&$,06:=P<2/,)*149D10426GJ9,!(-92221-++''&!%,1D26E2.),13G7729.044/+#"$)04D.+,(%$""!&'**195KKG54-(##$)02J8291+&#!"!&-DI253D-'! +2;P@A>:6I0-+,%#"" "%+D56KJ9-$ !$,.27<K/$#$'+)&" %(&',+*-08GE?B73,$$-04D.,%%,47FP=;9+$)9HOFC73..-+(!$,//*&%!  %$$(&&),+-043I1*(! !&-438824.+(!!! &)/935I0*( "+5:[\]bA?H34.*)&%! &*D25821("!)1JBC;8ID000/,$(/DD4/&""!/37684)%!#! """!&+*,%"" !%'''($"$+D8HL6I-(" !$$%((%&)*-19I34D-'$  !#&$##$#$!!!%(',,+++,&$$#" %(,-02949I0/,& $-4JLB::E650)%#!!(('&$#%-97K.)%(,98;CB<7KJID-+)##$#(,&&#!(*,'$$$%)19I0./,'',**( !),*-,)% "$*4KCFF70)%)9LP>C61&$%$!%+19DD4+&$"&-..0.-'$ #',,'# #!$$%-027:L7C;HL:==CKI11G>]YcVM79/*.09D9IKFbSXjSNBI01IKOMra?H59.144/-,')(')'##/0D0-//43HH8I/& #).DD1+$#"$,*-.,$ #!%,.2H@?L4&#,DGKJ9D-)'&%# "!%%%$ $%(& #!,9G2-$%'..,&")DI520,#*45GJ31) "(.I58G53D/,(#"  "" !!!$#%()+/-/-+)#!)-44434D00D2GKKJ4-),*DIJJ50/036K631'$(-JC>?L85JHCOC73942:MTq@B2.**114.148EaRkjtbOK59J:>Mb>@?GI)#$%&*../....-,( #+13823013H=AM?6/$#+034.-)'(--*,% " $,.0I2J8541-,)))('$%'*D2J29/$#&',,('($#  ')'&  &*958851+% "" " ### #&,-D5HCF=B5/&!(/3GGG30/*-./''&$! !!$&+,(  %%!#-9D-$$+.41,$&*1/+%#*14329-%#%&'($!   "" !!!! "" " !$$!!#! """""!!$$#!!  $&)'+*-*'('&$$''+.0D2GLEBJ2J7CO;80))*4259/+(,.9923286E??;KG66G63.( $%,/94I41-,%$&*.38524--D6=qSYQO6/$ $&+.00-,(&((%#!!#$&('+-/4I94.,($!$&+.9JJJ30*(##!"!#(-.D.+'! # ! $%&('(##)*01//*)!!# #&%$%'-040+$#$,95J3.)%!#'),'&$ !#"(+-/'!%*/-(!&($"(/I22.("!"!,42584+%"" "" $&(''(  "!#$&%$$!!##$$%%%%((((((&&&%(&(,,*-//-./,,'%%$!"" $%',*.0D23II41D043J;Far\iRQM;9)!$/6MikcQa;HEFaAMBJ9//033D-)')/.0225JL3*$#&)*+*,)(%$#$!" "$((',-9355ID*%##&).D9339D.-,'($"#'/D224-&"!%(&%%$$&''&# !&)..--)& " &+& !$! !$%&!!).I21) #()(%!!!!"&-DD-'#!'/41*!"+05JJ9+#%-IJ659*# #$#$#"$(*-+*+%   "!%%$&$#%##%&(,)'',),*,+++++--/.0D4DI9I590D/,+'##!#%((+138K6JG8IDDDI2GCPURVRUaB3,$$*G@RkdcQA>N\ctVqOH5993341+,*.D4I28LBF>@O;GJH7:B;L;?aUikkYV]NPBK3/..**+,++--.IJJ2D-(!#).9334+&! #-2BA[AN=C754-)&%('&(%! !#('(%  (+42HEL<;GI/&%#&.0I88I0--.1041,$""!&-I55I.(  !$!# !$%)(&! !$$%$$!"$)..+& "(.26J4'"##%*..)"""#(+&  -9J21+))-D91'# ,D2JGJ9+$! "'0I230)#"#+14230+&##),+/.-)&%"     #$%'((&$$$('++00D400DDI258886;77FEEB=UTSjWjZVU@OE6394I9DD0D.1I3JK21*(&'-D251-(! $,D6L<:?B:BLG4/+'%&)(&! &)/1.-)!!)4KBAMaaC64*%%'*IG6K21/,)-DD3I.+(! !&*0339*( "" $&''(! $$ "%-090*% &/2E?EJ.!!$ $,-*(&+/*&!-96G9.'(+0ID-( %-28J5D*+#!$""!+DI1*'#"!&/I6K66I.'#"$,,+-*)$!     #%%(&'&%(&%,-.49I43335GLLBBE?F==M>P=O=PO=PFFCCETc`fy{~u`RNFE7L6682558G;7BP>[qqq@F=abQ\\U@:EC?NURZXWYYi\M=:BHGG6HK6555I52GGI.+',.95J20+$!'14385J;AAAAbTUQTrbbrA[[AM@=F::HK6JHKKLFCLK8GE?MiWf||_tNF<<;EENTQbr[ATZd_`dRaC77BOAbTUUTqNA@F=FFOPMrq[N>F?LK6294027:==Fih^WR@K4/15;@rrA:61*+/1286LL689-')&&))(&$!""#$'*-,&$"" !#$ "$,--'##%-6:F@?4# $&%!#&%,**--.0433993I90)#-KCOL4##*I23D'###&/100-,($"!&')&%)--*((&&''&" $,D56KH80,$   #$#%%#%&,*/D335JGKHL:ParQRZjWheplfse`^WckctVi\UNrN@F:CE;OL6G7EBa\jg}nmpcr?L6LLEBF=PNNr[Aa>AUUUrNNrS`sxogSAB667BO@@@a>PO:?BBCFPMTYYtV\q@F;J9442<@q\]rFK4..-*.*+'',1I7?aqqraFK83.-//97=q]\ACI+,+8:qVtkbO6I48EM\VVU=73DD0I2J6HH6220*)%&&%&$# " """!%,*../*+*,,,')'&%#" $()%" ,8<:FB3'!&'&$')*.9D010I2566G6HJD+$ 0;=MF8,$-00-%"%*.4400/,%" !%,/-*% ),''$#$&&%& "!'.3589.+#   " !###&',*.DI35JHLHCO>[Q]VWdlsmmu}|zxsgl`pXcYtS\]bN[@=?EBB;LLH;K534.***..4367:=aa?BHJ288L>[VkddYqF;G8H7EPMqq]VViQMMrTUQrNbi^n~xkr;828L<:C::BE7H6KJ6LFNRWp_`dZb@EJ3DIKFQcdkRMB652I00/-//D2K:@qTQQr>BG59D0IG:N\SVr:21')9KONqTaC65JB@\cXtRMrQZkhgfyw~zoonvffg_XWcScVQ[@=FFOCC<;E6G54111/1DI5K;:O=CTjgvos_ZqC8I95C[Y_l_tb=B7KG3D111IJHC@rQ\ZVTNOL6525HBPq\ZirOG0+'-4HB?OC;66;PTj``j\r=E;H659DDDI0D0.+($!!!##!!#""#$'*''&# !%)/IJHLBCCCEK9/&#"#&'%""(16E<<6D/,,*10+,)'*14I3.+,*.192J8GG9+""/7N]\=5'$%# ",/032I1*'($#(*023D-'#"!#%$$!"$&&# '/D4.)# %)),)$    ""!$$(+/09356HLE:>@q\Ztp}y~{z|}uosge^jSiQqaaaaO:CCE7J2399DD936HCB:B783D0//0JHB?=:CLKJ6K<=[Qjll^dSQb[MMN[qbYs|S:899IJ66KG8234.-*/D2EAtpm}ngc]>HI3J?Tcpf`j]P:[\Skpmz~~xllpdtV]RQA@a>CCB;66G2866HLL;LK5I0//+*DI8HEC?<???789/.D5F?H8I1+&&()*493GK;CaT]VZT[A=?BEH51+))'**+((%#%(&$$#!"#&)+,($"!%/27FAUqN@C61(!'/*+&# !&-D38JG6;E<7J4+&()+,'! #$%&()**+#)G>QRqFG-$$(('$!&+*+''%" (+/45I9D.*,'$!%( ",D2891'#!$!"" """$('%#" "   "$',+.495J67;:O>q]Zdex˰nfvpXkVRRUqbq[aO:E;LLLHH;HK2I0..//04IKEB=O:===@NQik_lpdZqa=?OOPqildME3DI26JKKG6G2I.-)'+9J:[V^_lWRM?LJ6:@QVZ\q>=FOOBJ0*+.37CF>aM[Ubr[P::C>MMAa?BL84D/-)(&%&)/I87EEOaMAbNPPF??BLHI-'('',+,&#$&(',,''&$"$'+,)$!""(1JCPNqA=<8/!%+.1.,& !$)*0I5HEEC<6I-(%&$% """$',-("%4E[]UaC800190,%" %(% " &).9I3I41.,%$('#$+044-%" ""##!"#$##""$&),($$     !&',/492K6EEBF>bRS^fuȠLjƭ˻wxslhhpXXkZU[NF?OC@>==CCF[UqaOL21,,)',,)%%&'/9JL<:==FO?;LE7HL7G8D*')',+)'($()-.D44/-)$#%)),&#!"&18;OF=CK9+"%*00.*& !#'.98;OC;J4)%# " &**-(#+8Or[@=CELL7630&"#$!"$(*DI22D.*(" ())&!&,'%"!#!$"#&')%$# "!!#$&),(&%#!""  "$)+/D93JKL@F7I+&%).38G7;C:O?BCrr[aaANPO;91)&''%$ !,-4524D-' !(**)!"!! !$! !'+*--'%  #$$&&'),&&& "  #()-/D357EBG/%!#%,-D5G7H7;;L[bQitW^^^pXtRN:K4+').IE@QZcVbF6.(#"!%,193JJJGK;C==FBH0-)+457CBEG2D4I2KHLCB7G890.11...,14000-'&$%)-DI2KE:aT]\T@79+$$(-.4991*'$" !!# $'D33I1( $'+++1D43341+,*/*.*& !%).90-' )DI30,#!(/9G:NUYW`hcSc]QU@?61(!)0I3I9/'$  $)-/-)!"&+00*(  (+.0/)$"!!       #%(,.D3JHBC?=ArQ]Rk_m{՝Ĉ~{us`jQAFNqr]ZXfuԖ|ogXiN>OC:B?:]j`myy}yvehiNFEKL7H68300D8;?P[Vc_oomflXjZQA?791-*0GA>F?C;;PTcyǹ{ljZWpxwmkTPO@qidf}|`S[=<:CC<;KJ23GL:=MTc_n}}}ejc\U@:;54/0IG<@qRSSR[P;89-'$%,)/D2KH;::BH89/+*4JB>qUr[=BKID1/0D93855D.-///*/.4I94.1+,0HC@a?LD*-9L@rqaB5/'%%',+)($ #,186BC::==P==?CATT[a>CH5D/,&''*/2K;C??<7JD.-.42LF@A>>OE6I.++*/4955241-,,+,*/199D01/46=QVZ[L4&!,I;=aPLI*$!##%&$ "!&,D2;BBB6D'" %)DH2GJI1.'%$# !!#$#$! #&&&%&$$ ##$#!! !+DGEFa@P=NM@N>@a]ds˧`TP?:=ArbU[rr[@@==@qVdgsehZqN@FE65I492G;CF=aA==O:LK8D1&$&,.2HEO==:;K299D4IJ;C?C<;62D,)()*138GJ31*)%'')+-D4111DKP]`p_Q?D!",2L?[TUZW_v|Ɵ|o__XZ]NC7L>cxvY\V^pVAPaTWn˴_T=OOMbQRYtXhjiUM=OabZ^^dtTAP:<768339267;B:?C:C<;EE621-&''.3HB>a@POEH682344355G5I41.,&&')08KLHJ3.,''''(,+*--15CUWnygc>4#$18659+$""" """!(/9G;CC781&!$%#"!&)/.-))&(''&!$%#"" #&)-/.+(!!&*D99D/++,+-..1/+,'$ "&''(($" $#)05LE;6I1'  $$##      " !$&'+*.367q\\Ydm}wvWQM?FaUtjt]AF:CH8J22J8J74!'*4D*( "! " "(+D6LE<72.'!"#(&%# #&(),&$$%,*/,(! ##"!'+03I4-& )+*/)%  $#$%%&&&# &),,,'$"##&$# " '08H77KI.'  ##%'&%%#$     """!%%',-/D2GE?PANqijdlx{{퓖ķxf_Yr@AQdȽ_WdgǷȩ}WUNarV`x|pRbNA[\YWv}Wr?OPN]iTAFBH6J29558H7B=>>P?;G6KE?=>=B731+.0GC>rUUqNMPB75D1-***)(')(%%$%,.27?:C7290-//**,()*.8F\hvvpS?4$ (),+# %('&$! '-IG6HJ1*&!" &',,% $((,'$#%,D2JI/%"!""!%)05830*%#$&$!" $%$" $,++/,'%!"" !!$(&%(%#"$,/986J30-'#!%%'),,($!       """ ! !%$&')*042H;:==AUiYh_nynfXcRVXv~}_py~`ZraaUthvnpki]TVtk_weUOCOPrbaOE639D493JH7?aArbNP;G86EC@bUN=E50.ILa]kWWST>O75ID.D4.*+'&%&#!%(,05HBE68449224D.,',-46FMrb@<8-&# "%-4865D,  '*10.+&#!%,1DD1+$ !&),,'&$$'47FAM?5+"" $(.3J524'$ ""!$# !$(+*D90-%"!$$!!#$&%&)+-*+)(((,*1409I401/*)#"##$()*,),'$    #!##!#!#$!##%',.DI28L;<:@rRSj`vo}~ц|}you˼|}w~zvtUN=?@MMRd`fommogsf_emu̪g]=;CFFC75.)'),138;>rQW_mwɏҬ˹{ughkU@OE7;:Pqkd`myzwzznsyÖɃhAE;;EC79+&$&*486N\YYXj\A:682G:rcesmgtA;HENWxviP731D86L<;K8449I2I1+'%$%(($# $(,.D9.-*)%&'+,))&%&(()'$&9LAbr=J,!)D520) !$%%!#'.3H7J9/'#!#&(($ &.KPbb>H1$"(*1./)&()+-/,%!" %(,+-//...-.*''$#" !(+++'$ "&/9583/& $%&(%&(&$##$'*D8;ECE;KI1-($#" $()&&& &"  "$! %$&)')'& """!$#(,+*/0438<:=[iZ^fwԋį~ȷzovof`Wir=B7LECC>icdfn}}nvvso{ԖԴj=K67E;KD)$&*IGEB?ParQVckY\NO7J3GB[Vdsofhi>FMVuȶzY>HID45H;:C;H85GHKKJI-(# ! "!$(*1.0-%%!"$$##  #'+++%"$D;qZSrL0!$-J775*#"!$#$$,.3H7K20,#"! !""#.6F[MOG- "&+4524/,'%%&(%"$)*09I5232I99D.+,'('+*.-.)%!"!*95K24,!"!!# ""!)0JE>[NaPEG24*'(%&,**+)'$"    "!!$&'+++)(! """" $$(,+++.00I86?@USjpyuǦϖƪwwn}uz{unsehWcqMOC;L;MA[qTYZV]MOEKGGL=\cpyxlWV\Yvɘ~hb73938;BFO;HKJH;<:;54*'&&$$!!##&)+/-,&# "" !%)*.*&"!$&!-LqjhZ>J("%.GP<2'"&.5G68I/'&$!! '-428JG88GJ8J399IDI54ID-)$!#!  '0JH62D,#"%*5CNT]]qMCH54/)'++-01*+("   !!$',*//+)%%%%#$$#%%$$$)*-'+--1445L:A]kdgvx͝֎ʀ˃ugg_p`lf}nv_`cSQAOEELLEC:M[URVkjXXktYdmy]:H7O;H;;<[tlxysp^fȦůeT?H6GHE?F=::B<<:M\`u{y}zo\AO:BC:C?=:MM=<64*&$$%)+(&#!,057K62D.-,&&!""$.7P[TTQ[PBH5/*('+/..1/'(!   !('+-/-++,/..14D.111D44D40.-+-/.46B>[Ydpsfn|ťڤwns`VRVQ]Sdfuwz|xspcUM=EH;MNqTUQ\RUQ]Zpy~^b=<]^y{xc]N@=PPPP=?EG5GKC730'&$#(')+++,(#   %&(*,+,+/D4I3229925285244.-,),,-9HFATSjX^lsfyˀߓ~xfp^kSRVtj`xw{u}m`tU>:BCC=@[r[rb]QRR]]TrRWv~|^\aPa>FCG443;PQQrPLJI3JK:@[qQTTqMP::a\^n~mhiTrqr@PaP:L84I8J777LHG7:O:BHI/+,+**+)&#'02J5.#!,DI/#!5boV<+ $1L:QRZYtXdsyΆڅƯzms_jcYWd`fuu{~{wx_RAFF=aMAUbU]\\\RR\\bU]Z`nfW]M@[NaCJD0I7Prr@B6I1-DJ;=AbRRR]r@=>N\Wx~z{ȹwgXYiRTbA@PFC724..98KHKGK7BO=:69-'%,+--+'(!""%038I*"%14/$4re|YE* !.2KE61'!"#%#"%+,' $+922ID00433D.)! &,*-)'$ $/D3J24.'$!"!)D7?MTr@B3+%#(-D341*,+,))*-0IK77620+),+,'% &-43554.)&"    " !$(-14I8GGKLL7;LLG6K5I1.)'')-02H?ANUqT]\Z`oįwwxvfvfvo}|{fY]raMrrbi\RZZVR\i\bqqbVXen|}^Z][NrbNC64/05BP=?E51-,/37?r]YtZVQA@aA]ksxuumvlfw{wxp^ZS\QUrMPPP<72/+,.95J88H7;:BE3*(##'+-./,*+&$ #-490)%-1-$/>dyoRL)!,4J68.&" #!"#&&# )9KEB8.%!%*D2530../.1.-/43K;LK9/,''))'($ #!"#')(&&      !%+/4I2GK7H77L;;L7KJ249.-)+1/IJL==aaAaNbSdf~ˁ֍̭{{w~ǘydVq@NN[TVYYjkcjV]UbAMMbSk`p^jRbbTQQNB81/0IH?FB7J9.-.4K:[VWkkZQMaaNRjesg`WYZkhlspjS\rqqa@=O:C?PBH24/,&!  ,3HEC;8D)#*8L7L81(! (03G6JIDDI34010D56:O=>NqUTq[r[r]TAC84*,12KBC:EEH522H@\hvolZTA>a[T\RirP=F:>@MAa@OCBLH6599I2JJ54/*-1D90../.11+&"!&,-1111D9D+&!%(&"$''&$" (/8KH8.&#()+,&##! !$%! '0K?PaM:qQ\Y`vsoo|~؍҆Þ˻Ƞ|pQMO;EO@bZdsfnvv^ZQM?EBB:Fa===F>P@brPE80+,*.8RhoosjUaPPMNU[@FEEEE:?=POEK6J529-)+-1DDD./.004I1/*,')( "&,+.D0/.DD.-'!"#! &'''&$&'*-*&!"#$$((&$ $')%!#&'&%#$'18;?FC<720)  !()(& "*5;=>>OG0'!" $%')'''(%%#$"(46HH7KJJ6G8I-,,DHBO?K/ %+)(! #((,)&%!    #$%((,+/.DDDI33G6KHL7HH6523904233K7EP>AURYdhgfsow~ȊՖ…ëĊweW\MO;Spv}xXRAFOPaPC:;J6KL[MO79*(! #(+/101,($ 'DJ6HKK666K29)&).GBFBK-!#(')&" !$('''&$   " #%&'***/03GKKK7HHK852940139KEB>NMUTRSchfsoy{ڎӣߜ؎ΆÒ˼{uwn_t]a=?ONQt^ow}_ZU=TXlfej\q>?;763/.05HBO:<7K82341/*,,++--+,++-1.1.+(%  (*10D1-)&((&# " !$(,-110+(# "!$&%!")/I54+  '1I4.& "!$#%%&'*D2523D1../-+'')'$$"$,/111+# ""!'(-02;CO@>?H9/)%(*/45GG4-&""(03J8GJG7L7G9+&%,4K7H5-!&&%## "!$&%%#    !$('-044IIII3411*/*136<@r]ZSYcXdlfoy~Г盜ٖ{{|ynl`hddkjktVShlo|zedT>CHJ341/-+)--/-+'!"!#('-32J6L;LHLFNVd_^ciq@?EG9/,'+DGBE@?H29/...**))',+'*/-01D0101..049-,% "!&'*..*(#"    "#&())')(#$!##$'-5L>[Shdpgefu˴ͣώofmy~|mlj]aO;LHG58299D/*'&,/3;F@AQVVtcWdW^XtSVVbTrM:L5D,((,.00I24238JG90+++/4I5667LCFA[a@OL7JID11I5H:FCH9-! +4534-'# !#(')''&&%(! '.2GKHG84-)%&(*.DD+%"%(,+/D5J6LLEOa[[rPE5D14866J3.)$$  (-0D0)%$&))(%  (/DD/)))+4G776541.9K?>A@=B68228390*)%&&%$$'),,,))++.041-+%!!%)-044-'%""          "$(()'()%$$$%,.IHBA]YW^p_`s}ƅӋϕIJ~˨}uyz|nmlY][MFEBE;;HG8I1*)+4G?qSZj`d`fmnof`WkS\QUTN?;J9/***/11D9I5KL;EH5DD.*-0045KE?aqqbAaOEJ2DD49GB@rA?K0&!,5HLK3*% $)+-*)%$&$! $)/4388590/'&(',*00,)$##(,/955KG6;:arqb>721.D877EJ4+%" '1411*)'&+/,(!&/D4/,'%,48HLH2DD92;=qTb@?7GGJ6J24.)($"""!!$## "#$'+//+'$ #&,43390,$"##""            #%()'()(&'+/D5JC>A\RSkWWWho|ȀΗˀɴɈ~uovx}wzunptSbA=P>=OB;7890-/9H>]kWdpllfywwxgXtV]TqbAOE8DD./-*.0DD2GEBF>P:;7G4/*+,057?Mr]]qAFB690*/4G:AUUb:3(+8E:>FO?EG2D/037PUtW```svuww}sXV]bbTQ[F;G2440..1/042HL?AT\\TqPL3*((+1J<@bT[raOEJ9/**.2O?=OO;GI4D2HOrRZccjjheonsdSTUb[qqAFEK53I4D../042KNA>F:LJ4-,&(17MQS]@H+!1H;7I+$!'DGE7GD-'')-*1093JGGKJ591-)($!!%(+*1-*)#""$*14I1*)/3HCOF?76G2JLB@NAN[TiSjhjjYb@arANN@?EGJ8332D11D422HOA]WgyzoXq;1&#)16EF>=:B7GG4-%!$+8?r]qaL. +365-% -J:>=BJ.,,+/D267;:BEH;B:F@a:<;LLPP=OFE8G8GB>btcYTA:ELL=>aNFB;2/$"$&,'&"'3:qQ[:J0)(*0D8LB?@rN[N>NNr[@@P@a@=BKI1IBNWooscNL4//IJ8529DI333D*'$(,-I6;:CEK8I0*)%",IE>@?G1&""%&*D5LB@[NNMF;69/*)%$#!$'+/.//-,(%#$#+48L7J1'#%(1G;L631+)*-/-+'!%,D40D*'%"" ! " !$&%$$&%&(&%$###$%')+)&$ "&,052390-&!" !"" !&+D87HKJI.'! !#%$&()/.11493JJJ2ID.)$       $$(*36BPUR\QN>?BHI998;>]k`sghY\[arTcl{Ɩի–ŏ蛔ҝٝĻ_R\iWuˈ~oYMNrqNNNMArbUb>EJ1/3EbdelZAL9./92GG2I9928ID1*(('*087<:?CEKJD*( "(.8L780%!&)036<=P>FBJ24.-,+'&$%&&,*+,**'(&()1IJ7K80(%%-37EMAM>?PFM]js˺{vfxDzÝΥŇfciikpǩyX]>E76K7LE=[QVcYiaHID8BRpmysXQM?C;L<<<=FCC?OM]cs}hS\UTkpo}uz}fvlevwߛ𣫄n`jttpyƭĈekb=:LKGH;=rRdWcR>K40JPtgsgW\MF:CEOFCON\kccUPL242<@b]]PK1+)-4328G77L7G20-+'))*13KC<6D+%"#%%!  %)D567L8D.,$%&',,(&#"""#&)+,+,.-.DI90-,&(,46?@a:G0&"#(,.1-(!"$()*))(&%!#"!#(,+,'%&('+.0D0.*&% !&(*./.*')# %((('(%! " %+.93259/,&$!!""!""#&,.I26HKG830+%"!#%&&%#     #'*.955J53952322D4J6HOAAAF?:CB::@q]Z^fx|eXVMF::>A]VtkZR]\QQte|ߕ܍ŀxme^dW`m{o^ZbFLHJ6B>TcpshiaH49HaiWhYrP<UiYcVqFH35HCAqMOK.)&'-1I8KEPMrRStcVbM:<;;:PNTqbr[Nr[r\huƥًЎ٣ќߝ{unff_pp^n~ʒ~npcTFB;K;@Tjlfo_R=6DI7Pb]]AEGJ7FNTUrPB7EC:FC:B<<:=aNURiRq>E88K7=>:B5+%##%+-9HECF:E65D.*'$ %+D5;BB;8D/,$"" ! "%(+/0D1-'#" $&,&# $,+--,,+)'),$$#$+I7FNqa<2-!#)-0D/)!"! !!!!#! &&'(((&$%(+13I29*&  $',***+($##$$&%&&!"##$$$"" $)-95331/'#"!$&)--10III5291+% #(((&!        "#%$&&&&&%%))*//-/DIGHE?CCE<POOF@MUrA@PPFOO@[AUrrTrbTUUZ`yĚ̥̫Σ؝Ԛ|nxuyunvsvzƒɿwvdS]aFC:=UjmzzsSF64DKFMMP;292:Qhelj]M=?:BBCFP@MAAAaaqqrUAC7GJHB?B79*%""$).2;:OFC<7J3D.)$&(-9KLLKI1*'! #(()($$!!&&()+**)'& !&()%!!&+-/*,,''&%%!" %*47O>MMCJ+!#)..1,$" " $ "" !$%%%#""!&,0440-& $&%)(''$!#$(*-11/*( "!! !!#&/98I29/,& " "!&('(,**/4I584.,#%(&(%         " !!#" """!#&&+-/.0426HGLLLC?PMMa=F===>[TT\\R]Q]QTQVZSStctc_vɪŚԖːwnx|{~~wu|Įf`WVRbaMArkmsZF5DIG>aMPBH888LBLH9*%  %+96;:FF?:?BH81($&*4GK7G9*'&  &,-**,+&&(''+(')&%%! ! &)+,%%" (/.01.+(%#$!!#$('-D8;COFEJ.##'),'$"""#!"##!!#(++'(#! #$%&!$#'*1IJH75D.&!" ! " &-09323.+'($" $!##! !$$$&,/45G5I-&$"!(''$       " !!"""%#,./1043285K7LC=aqUbNa@>>[]YX^_fvpXWtjh_gnvvsgm}{ĭĪ|xmuğm_XYiV\Q]iYlu~gQO394IHKJID5BixfZq@@=@qidgghVA?EE:F:E62287L7H2.'# "!)187CF?PNrN@E3*')12HKJ5D)%!#'*/..++''-*1/*,&$$!#$#()*+*,&%  $).02I4.)&# "!#%)*-143677KJ9(!$$%!""#!""### "" ###$'*DJ7CF:E80) $## " #&+04339D0-++%! %&%#!" %,12259-(#"$&)&$!    !###! ""#'*.1049I32G6;?MUU\iRTr[NTZ`v|{|fl_pfu~~{w|zǘ}vev|Ǹu^XtStcttctXgy~}dbE5D938539IEqfeVq>PNUt_yxpcqC6HBBi^msYr;3D9GL77I-'&&(% !'-1/--+*14JK541($!$#&+-.D0..+)&%%%&)-143824*(# !#%+--+'%%'+094D/% " """"" ! #$$)/37OAqAPHD,#$(&'(',,.93I25322I34D1(#"$(,)&#"%,++'!  $((#"     !#%&%$#" $%)+11434DI67:PrVXll`WcRiSXm}fvnu{{{u|}fsmfnuzxg`ph^vˊȸwo_dktjhlvfphjjcXXkZT@EG558GG5HOQeΝ͊oZrOE?[ihgl^\>LG6H7HG2256E:::H51-,,/4JLE7JJH:Q`xnlQ:GII7L78D*'')**)$',-/-+'+12K;H64,&# !(*/0101.-*+'))'++-19I24-'# !',++'& "#'09I4/("! ! " "!!!"" "" "$*9KOMNNF79+%" %(',--/12JG8JKJ86GKJ34/(#"!(+'(!"$#$!""!%## "      ""!#$((%!!"" #%(-1-.443JKEPMQk^emg_dVVZteyngWjeow{w|vfp^d`lfy|vs^jXlxȿwomoxsphXkX_fxnsXSQUQ\\]r=CBE;;EECOrcf̅ƲfVM?7B=qZjXSTPL7E?K4)$#!&+-+**-/432889.*,')+.1/,%$!"#%$##""!,D5H654.,$ #$!"#%,,,($$#""!'*D40-)$ "!%%&&$!"&-IK;LJ4,(! $%',-14G;EO=OFB<;aqQVRRAFB7G7L:?OO?B;LEEEPbtp|{m_WWjWXdWdXkXX^pgyo`tZSXeozxo`jb>?HG7:@Qcdc\QQQiSkWZiiZWhp_XjWtjpgv}gSrP>r\ZjcZ]qaP@NRc`ou|wyskb?G9J7CC;51'&%(%$(,DGLKD("!/7AU>C21/1365D,(,D6?OE8*%#$&(($!"(9<[iYRrC9,###$&%!" -37BC<7541-,+,,'&% !,5?qZXt\PH9.*)*-*/I56G2.$$.38834.)%'-4829D01//.D2JLLKK2/%"!  #$$&,.56KL7H6GG582D,$ (/3GAM:LJI228JKEL7HG868GBailw{oshXjjjtZVVVRUU]iXv}yys^SRRYtcWcRrM>:EKJJBaTchjSR]\YckXjkdXXhXkZ\VSYhfx~~|pY[O?PaUTRQqAPFM[RWpo{l]OG3JB:=CK9&    !!&(,--D4D..+(&$!"" %('+,+*+)(%#" #').93I44D49G;EMAM@FOOPNTkpx{~fS@;JJB?E63/1IKG5.%"!,141(" /8778409HBOE81)$##%),),'()-..+'! $#$  %)157;:?:L2-$      !#%'**-//,)&#""#'+/DI990D1+'$! %(,-*--),,*028J59D1D/DI885KHKJ25G7Fqj_}w~}ffldkjir@@MNAMPCLL:MSj`lcQN=?:OB=:?:<:=[]WvynYNE77B?L8ID3HO=B9($*.+( !+4JJ2I95;OOEG3D9JHHJD,  &&$!"$16>R`l_tNE0%!$(),$").1-,(&)135652D/(#!'9a>=@Tij^^dj][aP:::=?O::CF@N]YewsZMbRhsfgplo|ɢȹ}fWbOL549JL?FFa@M>OF=ANiWp}{u_i[C<;;L68357>qQaK*"#((% $'19I9I2E>@P=:B?:?FOP@qTUi]TMF::F>@O=7JHCq_z{}hkiZjXjWiTN=CCO=NRYgu{~{ɭʄȸod\a<5I35HOaMOLJD04H>QtWjYUPBB?@qbR]r[@>arQZdenfeWQ>C<CJD/--*-**',/0I34.' "" $%&'&$  !(,*,'(((()*144D/,++'&('('$ !!!#%&(%&$!    %+/45JKK6540.+)( #!$%()-1I8GbiZkZiUq[rQicXll^kQAO<7HJ54D4G:A\U@K1)!"#%# $(*1D1/492HH2.&"$','%$/D4.--1IEAQiSRTaB2'  &),'&#!!#$!"*3G;76J0+,% !)08EAZXpfdi=GD-,+/928H<;;K3/*'',/0994/'$ #%)*/1.,&!%/8EAQ]r=69,'%!$%&$',-DID/'#"!!$')',)$"!$&!$&#%'*.9I3ID/*,'&%$$!" " !$%$%     $(*DI55394D.+'(%$$##(*.0IJG;F>[bU\SiVi][A>=FFF>>ANMNaO<63I35GJ852JL[l~ħ˽ngl`_XcR]T\tj_}uȱŏnd\NP:BbiZ]M[TQViRV]rA@OOB;<:=:F>=OC75D0.DI3235KO]f}g_^dWcjkXpsxǶw_tbP?B?=Pr]tWddWVU>BH7<=M[[[AP?:ON]RSiRUq]YdpssgXcRMCLHK83I0.197?>aPE21*,,(#""#)1991)%%,D2J30*('+--'##)/324-+-36OArqTA:6D(&+/*,),'&!#/J;;GI*'&#!$,*/D987?>FCK0,#" %,.D8GKJ241-++*-**-+(#""!$(($(',--)$#-JF[]]bF8+& " " !#&)(','&&!" #%&&&%% "#%()($#"&-DI33ID*(&$ "    !%(,/./.0D40/*+'&((+/.138KLBFaA[U[qbN=O:ELGG28HKB?:CLG3D/*/4332G>==OOBBFPAAa@=PMqtloz|shSN?E6G6829D.027:OP:K2440/,#(.9G8.(""$/2K6K2DI3ID+&" )43ID-',08B=AqNa?L4&%+--/-,,&#!.J7H51)#!$&),,,)/5J66I-(  ,.4I3339./+*,,*,','%!" &&('((%(),'$" )4E=N[>L9*#"$%%%! #!#&'++*)(#"!%'),*(# "#&%#""&+-10D-)%!"      $%')*-/1924D/*,'',*/14I95JHE>?BLJJ6FG,",3a@Nr\RT\QqN>=F@N]S_xɦzvsh`heciiUrNaA@M@NqVtk_s|p\P766GKG5II04D/-1DH@to}^Q>E7B>Ui\rAOE7L;HKKGKL:O:8/  1EqTrBI$'3TVV]M=??==F==aMN\Z`m{ȯmhXVRZi]\Q]rrqQ]TQQRVVSk^v~~`qB62GKG62I410433KE>il~eZM?ECATjdWdVr@ONRje|}dT=B;OUZpgeg^t]M?LJ1/4G?[UaH-$8MkspZP8*%'/37O@r]]UA;3+#"#(*101/*-42;PbVYST?8D0IH<:BKI,(&)--*),*/4GKJ9-( !$&),'))+*-+,'%#%&&),(#""!$&,))%"##!""$-37CF:L8D*$#!#$+1I8230+#"#(+/*+(!" $(((&$   &*/D44/*,++.I56K620)!!+06?N]RUMCG0*),-DGLC@NqTiZVQrP?7J6HBP[iYtWWtckW_m~m^YUNN@@>ArqUU\Ycd`ll`dWjcZtdfhq:KLF754IJ;N]k`ln|}`ZABLB>]jlsmfpWcTP74+,1JFbba7*(Gq^vo^NL0)&'/9GEPN[a>E9)#! %'*1D1.1926=r]i]AC8D48CAbNB8*'(*042I0.4JG8G2.-(% !%+/1./1-,+-''(%&'',+)#" $,-//*&! " " &.G:PaAPBG4D/*)'+-14D1/,#"&,.01*)$%%%(!   %*/1D/.-//186LAqq]iSjd`lse_hkZYR\Yhn}dqCEHEP[[><2326@Y_mwwu}os`Vr?LLB@UZW^^hhjjRAK.($-2OqT@6,'KU`mo`UO5+&#&,.36BOF:LGKCM\`n{{xlkVQQY_n|{ypcba>PFF=>PNr]VtWdW^`h^WSTbbbTVc`pehSqOHL?FQRUaFE6L:rks|~oltU[Mrclu}eYQM>?=POFArq\kdjWktSQQbMMa>@MNQ\qN=;LL:A]tY]a;887@Yf{vd\NFLHG566;L<:C:OPb]\RA7.%!)4L>M:8+%#*8@]ZVQ>H.)$" #%+/DIID/)!"%*./4493HaF:BLKKKKG3D/)$$+I5J63I1&!"!$&&%%# %,/95JJ9.,$  $##"'IBM]ZZZjXddkR[:80)$"!*4340/,%" "#)''%$$#"#%(),%       "%)-0D4D110456L:=C:B6K66H;?OP=OB63/(&*06OMUUTT[[]]SZiTra?7<=UYpwn_S[P=@T^w{fjRr>=?:FPMqRttYZ\UMP==?PF::EE<;7HKLEF[Vh`j\aH3JHMYf|gYAOH82258JG6G5I38K?@qqFK0(#%.GBBL2*'(-8C>M=:H9-'$# !%),-//..+'!"()-.092G6HG1)$ '5qe~`=0),4L>NMPCH8GKHHG9.' &-4JKH21+$!!%%$!  %(+.2853/+'$ ""#%!'3EM]VZkdpvxngdT?J,! #+/10D/(##'-111*+,%! %')''&!"    "!## #&,..DDD.-//45KC:CC;;HHHL<<<7KGD*,))1K<=[bU[MFFMQitk\bA:;<=rZ_ox|zo^ir=B?rXw~ojQr=CQZZtZ][PBE7;;<I''1KOMa=;J526KH631)$%+08J83*&%"#$!" !!&,049I/+'&$!!  #!'9L@q]iZX`x{{gt[;3,!!',-./,$""$+143991.'# !()''$       #%%&&#""$(*04D4/,'',138H;E;;6GJJ6G82491-*.48:P@[bMOCBC[WɄɸlVNFCBC=N]Zcci[=C6567^ǧl@4#!(DK=Pa]Wgvnvki>HI/'%!!$#$%#"!!$(''%# %'1I552ID/'!    "" $%&&&% ""#(.D9I3I1+'$%(,/444I400D9I39I2I26LBFP>FBL89IJCqcsyx`iN?LBFAihplgomf^tTaO@RsƊXrFAitccVb>V^m~Ɋz^]@CK8901-.D4322404/)+)('-*+0932ID.*'((,*-DG;CF@F<89.**.001,$%*D8HLH63*%"!+G[^WO/ (.5EK2.'$%&*D00*$"!$### " ()'& $%$  #$%(('))&#(9HCOB;;<>bZdg^c]?;81/-+,-.1/-'%%$#%$ " #&+.094.*,%"  " #&$$$#!&*19G6G540-'%%(++-0///-D5228J2JH7BCCC<789//DJ=Q_y|n`Z[=CFAVXplgegp^WVTP:=[jyȲgZa:CEONUZZYY][:L6J6BFaA>FEJ85GC@UYd`^_W]F840I;NtpxĨ}YN?K30-1I8GJ6J30*+,,,+,,,)*/1D44.-+)+/D98EOMNbqNP;20.14394*,#!'/3HBOC<2-$!-HrkovQL+$*3G84*$**-+# $)*/+(!%((%"!%',*+)$$+9HBB;K55K:>qR\T>>rZ`v}xo_dktZ]NP<;Fbdx{fZ[?:B:>NQiSi\bPB;6GK;O>A>O;66G7L5-/5?qjvx{zjN<20,*086;B784-'&&)*/+*(',*-1.1*++,.936B>qiStiT@;3.0033299,(# $,15;?P=E3+! /GOihoylY>8+,9431'&,,'  " $+.D4.( !((%"#(+//-,  ""!'0J;C:=BHHGKECB;HK7EOF:7I/.8O\_xxyyz~nkr;I,&,127B:72/(!%',1D1*((')+.-*))+-D9GE=bSWh^kQ>E2014II55I*,$!#,48L=aP:G-# '2FCCE7KK7C=[qUN=?K0% %*D0-'"!$#" (-9GHG3/( !$%#!""%,/0DD/' ""#&,/1IGEEOB<6I.-*/0D940.-+*.1367CAbcez{xhTPEG586L7K;C?PFCBK225JK;EC:E:O?FO:CLHGG88233I8K7B;G4(!%-JOFO?LHBNYplpcq@MNRXplhS>K0' %/8;C<51)!$,.8654/'(')--,)'('*1192;>]j_^Yr?51,*-/1101+)&! #'/5KLCL2*$(.IJL<;72/$""%-..-% !$(%""!$$# ""(.3KEH5-&"!!$## "&+-0ID/)#  $',-98KE:?B;G5D--*+../-+(((,,02G;K80( #%$&'+D38H<:?:;G2/)#%&*.-+(#   !&''&((! $&,,)+-1011+&$%%&,*1367<<;<:FAUR\QAPBK241*)%!#!!#%'+9JHEEE<7I..4GqZW^Y[<85GOQYdjV@;D'%,0GE@>Aq]VRbN=E7J30-,%%#!$&%)-4358G88KEaV`sfs^tr:20/.9GCaU\\UMBG3DDI5JJ24D103KBO=O?EK201++,-0I57L;7I1*.5FQX_XVbN[UQ]NB5.*IL@]kkTPH.,+.5;;L89+&'05;B7J0'$%)-D.1/1D40-% #'3?qViiA<30+'%!$$'))($ #'--**& "" $'*03I1/,&(',/D1*(  (,*,'!(/I59-$$46CBK9+%"" $%$!! "$',-.00.+)&&#"!!$&/D8JK7KH683I0D44DD0/'#"""#,/DD/,# %&'&('*DI6LC?:?B75.'"$)*//+'!      #&)'&% "#&(+/-+,)+)')(!!"'0J<=[[brrU\RQ[POCH683D/)$! #'(.93JGJ23095CM\XdXSUF;591DJ<@]j``k]a;59I5GK8I1*+-45EO>>F?BGI0--'(,-I5K77G3I8BUjs}o^RqN@PO<5.+*3L@]S\MC21.42;?OE84.-0JbQT@UTqA=EK8235K?qYg||stT?838GH7G8/,'*IJ7BPaM@OBH89*)'()-02JGH7KEaipuz}`iM:7H820-19JBarqa?K4.95B>@@:K5I3HCFP?6D)!%)1DI22J7;UZl}}fdU:JD-*0102L?=@@=78.)-IE>[TAOE7;C>aA>E2*#!'/92688KLCOOLD& )9BNqqN=BG0'""%*.1*+'&$ #""!!#%%%!!&-0I3I9D45JKL690)$$/43JI-!'G?AMB1%&0HCBK4+(###$%'.I3GG29/)$$$$%$!###$()*+/-)(!"!%(%! !$,****+*10IG6L;HJ4+# !""!)D3859+&! !$'*10.00-)$ $$#        """ "$'-49D1+#" #'/..-'% ")DG?b\RV]]r@FBJ53I3KK850+'%&)13;=Arra:2*&#(/9JHKGGJGH;<:?>QWvwxptrCEECPO>?GD' #/5:qQbAF:FaNU]b>K1&!%*456GGGG;P@P<8*##)47=MNN>CK9'"%*.4I411/*+)'((')(% ")1D3I440IJLEEH8D,# "$.45GGD'/KPbN:3'!)3LBEK9-&#$$(+136BOBHG9/*,''( """$',1.*,$ $(,(& """ #%&&&((*.4G7EB<69+$"! ""'0JHLJ3-$""!%),)'(%%# #& "       " &)1339/'#"#'*1DD*'%$'1JCaq]\U[A?L50/-DD95JI0-)&(+03EFA\Q[FJ1&!$'/435I4387PAbSjVb?8*#%)4JHK66G6EO@PCG.)(+46COP>=;61&$+1385559D.1.--//*& "&*0I4//.4J;CK4,&$#%)15LFNNAO;62ID1,&!#'.0.-%!()+*,$ ! " $%'-D5KL;LKI*&  $$# !+37?CH5+!#$!$#"""$%#  #!"       "#(/425I1,$ &,-.1-,(&(-27?aNrNP:H5D-'')+/DI940,,+-D3G<@bbrFK1&""%+.0D1/D57O@MN[P?;76JJJJGEAShl`jUC511D93853286LBFP@MPCJ1+),0KF[b]UMF<2-# '4F>TklljU;4,%'D6;EHG83GE:=OCK4-+*15K;L4+*06C>a?K4+($#$,5H@T\\q>:EHG680)$"#'-D0.' &,*-,(%"" &,145HH621*&!!$'&%% %08C=OL9' "##$&## #&%$!     "!'.9I59/'$!%(+,+'%$#$).3H::C<;K3D-(#%&'*.DD9DD.*-/.36<=A>F?BE;782HPTk`_tNE2436;C=B6J256;BC:EKJ.),*47aTVYSNF<6I*'&+4GCMA>F:F[VhflkA71'+1GBO?;534I6BRjWVa72I7:arbN?7J35GK;LGI4--/Iqk`^Yq<9.DJBaa=aa>FOELEBaTZkZrOGI48<@M@BKI/**.19I9229990/)$$#%&% ""!%()%" &'&&&'/2HF>O74) (,)(%$(*9J;72.%"$&(''%%%#%(-I6L69* 9?Q\QaH3+&# !'4CUkjRABKHObYjZN<0)!"%,044/' " (*.,'%""&*.0991+,,+.952D)! "#(,*14499--(""!$&(('(''&',(&%    #$$!""$,092859D*&#%$$',*/987EE;K50("!'-9323I.'""-HrjlgdT>@NbScSQ@E20/.93GHLB::@[RtcVU:9-+4KFMTrM@=C::::=rT\Rr:J9I8;FMA=L9*''')*.109I2I9D*,&$$&%$! &,144.'"!%%$" #)4HO>=E8-!"#,-++)&'+9H7K21&#&&('#  (02G2-$!9?qb[:69++,'##*Ga]iqFG48CrW`hSPH0&$# ,1431+$"#,*11/'#"&+D044.-))+-101+$ "" (,/422330-( " #('))+-/-/*(%#"   """%+0GEA[UU\RVqF79/18CN\RN@CECOPA[qUQUMB80D5L=MNAC6.&#%(()**.D9I940-)()'),)&%+13GKG5-%%#&&(&!""&1IEO:L5-(!!'/1.-,&)+DJKK20) #%%! $*041*"%2?aMOKI114D.(!"$.7>MPLD+D7[W^XZ[:5-'%(*0222D,!"+039.(" &'.--/*+(&')+*)&!#!!"%,.92J894+( #$(',-11D1//)&!   ,0J<=@a=<81+&#!(*126;:PPF?LI)  '.19940.*(!,5FZlfsdAL0($*044.,%$().I8LLHKKGJHHEC>rTiSZS\bA>OL20146FAbbaL9*$$$%%&'',/10D0-)))/-/.-(,.37?AP;G9.,/-+)&$"%*9H;<73/)'')D3I0*(&)*96831)# !#$ "!)..-')8EO:6I115L?;I,$&)-.D499D0-(# %-8=cpf`iP8+!%+03I4*($%'/04I90D926:@MrU]YkXhWir=EGI.-)$# !%-3LPqTUUAP?BLG6H890+)*1DJJ24*'(,13JI1,! %'**&#!" ""&*+,$!! (15584,&)3F\ZSqL*"(4GJ4%.K<>>?H2I2J7:aAN?J+"(../,# #""%'%# #%),##*09D/(" $,/14399D1.+'#   !).2E=P=:8-&!"'/3;:O>a>@@F:KI.,''&(',/0458590)#" $+9H=Q\]@K/! !-56;731*+-.001'(%)D7MRjWcZQQQSZ\NCG1($ "!#%,/4HCP>=:G39D8L?MbSt^dS=J1.5B[YjS[B51,),087O>=O;6332339...D0/,$  (157LH8.,)1KaS_l^tb@OC:B7G31--/DI24/+&(+198I1' "!&)'%!"!" &)()'%%&*1I2D*#!'2aZ^eYP9(%'3KJ4&!-IKK8ID136CMQQqP6-"&-/+% %%$! %&& $',+($)-*)!#(+.DD9D0D-*,#"       $)4GHLK5.%#*37:=>>==?F=C:EG9.*($&)-198G8I.)# ""$(/5BaT[FK-(#(08LE7J0..192224+',1H>QtciU@F>[UQ[FYpsj[K-,.57<8*""%*-,),-D6CATiT@H.!"%))( "$()'% $&% #! "#')+'"#&&!$(,-/000./-)&!     $,194.)!)96CO==O<;;;?O=FCKI-'&(,*035529/)$###%(*4KO[r>;I-(-I6;O>M>?L3-')+*-*)($#%+11-,!$+--'# !! "#()))&$$%)*-*("".O\h_XbC3D9HC:E9(  &-GCM]QTa70%"!('(! %,*,&"$&&##$$$""!%)+&# #"$(&+-11//*'&!      ! ',)&&DGB=??BHGGJK<>MaPCG9+,,+.92G840/+('))'+/9;aTQbME2DD56L;K30.037OAN>;80/D6:F?LI--I7M\YQaCG33JHEBBCCHK6G750.*,-D9GLEF>[[a<9)%*9GEL5914567LJI1/*11DJHL;7L6LB?>P?L9/.9HC>NPL3-$!*G:A]iba=:FFM@:KD+$$(,,''%##&'+*'# )/4I.+# $&$!"&&('&!!%&')($,8OUZiMEG35;=@FH0# (47=rbqOG.( #(,+)%!)/--(! ((&$"#'+)$!#&')%"  "$%',*---+'%!      !!! #-JFBL24DIJ?E3,('-I23D/DHONra<5/,',*9886GG58K<=MN=BJ3IJBP>M?6I) !*5;?FO@?60'""#$&&%$$$$&$##*9J65D' "&)+%" #&%$" !#&$  )5<>=C722GCabACJ* $*2B@a=C5.&#&+*/-' $-1D1'!"$'+,% ##%,/.-'!" %%$ "#$&),,((#"     $-5AMCH4' ,4HB:OH8IIHEC<<6I4DJK?AbTM==aR_ul\?J90*,(&(+47?aUq>E5-%$#','%"!)2OR_epXt\\RtWkSrOH858GL;KJ886K830*/3LC?L3-')/1D113LNkvosZaL4D000III4.-/4K:>aF:7H7;??OL5D-)$ ""!&+/*/437:?O75*"#&(%#!$  ,36;L64&#,*-(  &'+*))-0GE?POL8/( %-I67H89,%#%,/00+'  $,**,#"!$%!#'122I1& &&#""(/D01+%  " ""   "" !##"#+37PA@>:60)&$&*D6?>>PFCG252E@bYWk][Artm{fZ=G4+''%&)08LCPaO;51(!#&(+)('+07[c_ggjctWdllXtq<6338L;;L677LH7J41D8;??L5.**4399D2BQe{~vSaLG593909.+--02HC:BL6J8HHHK20/--+'% %((,/48LB<74' $)((% ! &18K764(#(*-& #) $%'.GLB<7G1)! (-D3230'!! '-1./)$$()*/)"!%&%(/IGLH3) $%&##(*D91+%        ! ""!# "%.8;@NMPKI-($!&*4JB??OB5.)#"#(*D6B?rqQTr@O>]`x~sZA??>aN:H4///957H6HHBO:K31/D6CPFG9-DCRe|n^UOH3-'%#%&(+-/DI2II1-+)''&##$*4G6G8D1///**'&'+-/*)&# %&&&#&',(#!',*,%"'.DII.)$$(('%!" " $)($ !)0K:?EJ+"&,/4441+!%+10/)!"#$$     ## " " ! """ "#*D56KJ4*&#" #'-4JH7;;LPaN[A@?LK?2)"" "#()-,&!",099D098B6J5224/+'$" %,+--*')&&!%(+04DD//1I8834)! !&,/D2I9/&"$(&'(&(&$#&$$$"$,-1.,%!$,.D24/' "!#" "&-959/%"""!'0G;::72/$!%)--*)$"!)06ELK8D'"###"      #!! "!'14KRYRA70(#'0JLB<5,$!&%# !!&& !+094--08<=aNa:L21,#$/J=Vex}nskRU>C6I.)$%(%(&%)*D5JJI,%(-8B>>L4,&+47EE[A=74)#!'/26G9+$ '/J;H5-#"#$$! $',+)''+9HB?CH84/+,((*IHOqRiibaFH9'&',,'%((&((&(+056GG541.1///-4J;O@Aa=?;EEHGI,# '-0D-',.3BNiWWZqA[:2+ "&-9I0-+&%%$&&)-19D11/-1DD44045H;?POB78-(%"!%%()&'&$((,05KHLK2D0D6=rVkjWYSSVQqAP>ridesgcb?H2I32GG8J5ID-))'-0049104367H54.1DI320("",05653*#"#&')'''((%!(4HOA@?K0(!+0491*'((((+*'$ &,*.+)& "%-490*$!&'% #'-D5KEC:CB;J1&""(0KCF:;I, "&1J?AQQTM?6D-'#(#       !"&&$!"1F?Pa=:61&"!'/.-+,/9HPQkjtTFJ.&#%/3KH89)#""(*45I1(" -KPAAC9) )DJ;630-%$%$()))+)(((+03223I32867BC;H80*,&()+,',***0232GLKKG5004G:[VW_d`^hdWVTAF>NTZXdSN=LJ8GHL677KK84...9IJJ5JJGEBEK2.-.4GLG31%%/J7L6I-& #('($! ")5NqUa;I, #),++()0G@UZkYQPL9*(&+D3JG50*')*D2GKH4,"'I;=C6.# ,5B7JJKHH7;EE;HJ553GL;E6HL[NF79,!&+-,++((),-.-,&!" !!+3KHKD'"&((!!&,028GE:PaAaOK.$!+96K50)  ,.G7<:BK5.)%      &,/-)#$DBaTQ[MO7L?aUQTNEI)" &%(('-5?UYkZTPK9*,)*195J8591D26EF>PC6D$ ,4J6D'"-H@Qq=Ma=LD&$&.6@P?64, "#$$&$$!#&',,)% "!$#!$/8ECKI($$(& " $,-DI87O>[rPB5)"$*0I9.(" !" (-928J9.,#"       "$'-1-*&&4;F>>?HG56E=[rM?6*#" ##!'4;AYdji@H9+(+1D238HHJ6HE>NQSSiq=K/# (-0,$"DBqSiA?8+%"! ""! &'-/.//1.1.03J7:P>PB6241.1.19L@\`v_^i@<690-,,-08L?PrRk`fghi=J.),1288I0..0428HCCF==F:??O?C<<;:@Nb=ED$"!,2Eaa?8/$%,-/+$ $&&! " $)'++)%   "$'+--+(! )9LiWhSA71'%,198KG6H;;C=TYdleggd\>G-" %&#"&I:bYSq:8,!""!$!$&$',*+,,+/--*-126:P@FBJD/++*+-3UY`_t]F2,&(,.4.-+)'+1D987BF>>>=@=FFBE;KCPAr>;9#'46E73-$"#(*109D,& "!$%$%*3883D*(&((%!" $&')($*5ECO7D%%,'$"!#!# "$&+D5EBCL5.$#&))$" $%(%!     "$&)++)&# %.3;<750-))*D3241' !.HaZWkTE0&!$+4877H66:FAUc_v{w|xXT?5+!# !-8OUcSqC4'$&))*++,(')()+-./)+-1JCO=CK9-)'&(()0Lbvw^UBG3/-,)),--D36ObVZVq:8-&'+*/-+(&&'*/.I87:?@==F?OFB68JL?[QqC2&$/866I-$"!$%*144D-(" $%&&%!#'+/,,(# $%(($"""!$$&%&'()('%$/G:>O61  &'(! &)')# )/3J659,  &'&# "#((&$"      "!"""!#()('&$#%+0JLLKI+%$!$('(#!0LaVkR>G*!$'056KK6GKB=rthfu~|npZ[;0&""$$$,0H>TVVq<4((*D4D0.+(#&(*10ID*)',4KBCE51)'&'(%%,KrfɳviP7834--,',(,+D6CMqr@;51-*-./+,'')+-/-DI5HL;B:CB:EH592K=[rrFJ( +452D*& " $(,.4230*#!&),,($!$&&""$')&""%',***,''$&($" +2EPMC5* ')(# (-1D/'! '*DI4*'  $',))%!$''&$"        #$!" !!!#%%$%$!&(-IJ7781& !#"(9CNQSr<5)%'/JKG2II3G7:NRY^ouzuxs^tTF8.$ %,-/2C>qiTMK1##/33J20-'$0,,DGKK8.)&,.5LE62.,,-+)&!%4PdxS@:LI,&)18L;H2I928JI+ ,7R|ȼnSP<82J558290*')*09566853I3901/.1935533499I9D410I2I-*,-97Pqq=K+!#)/-)%%! $')1IG;K63-%"&).I4-+#!('($ $)++(!#&(+-+(!%*IKEHJ4*("",9EMbNED%"(')$$*D99*& #(,/-+&#%+1I234.-'''++,,'$        !$$!" !'.IGG84,!!(-42J8I-($(.5?rbrPE852JL763*'''*936;?=q]i]b@M>O;60( !%.IJEBC=>>OqbA:8-,,DKBa<9%#IA_{_R?H895G7;;LJ4-(''*DI33582I4D4D45JGKH77HG8291-+*-1*+& $/JH4-.3L?C;E?>]SiMH, 0BZnwscr:GI32HBOAa?74,&&&+1IJ8JJG53I0356;CB?=PFBK3+($%&')(""$/8KL79)$""!((&%!" $'-0IG6GG34+! (.DI9/)$ ! "'03GJ8D0//.D4./,&!!&(%'(',+13JHK83.( "'0K=[QTM:J*& #-JFr[PH/ $**+&!'+,))%" &*D5GK84*!"(/4J6522523533I1+&"  #$#!        "###! ""!&+.1/( %*4J@a>F:=a@OL3+$" &('),0KCPPEJ0+,-1/)($&-5:MrM@FBEG84.+,+*D901)#" (/8:r\\qMEGI2KELEE<@]XdW\:1#%.CVenmeZM[]RUN?81& !#&%"(/9I4-%%#$((,'!! "(*09I8J22D-%#+0D34*%"## $.G;:OC7653222330/-1.0.-**-19GH;EKJ0,% !+9LA]Zk\aE9,$!#16OrA?J,"&..+%!%$#"(-I;CO:K4'!"#(*4II4I358GG6JI.'!  " $$# "        "! " #$)+)$""!).2L?arqTT[=L5D.IJLB?@@aAarqMOL2*$"!&&$&%'IH=NaC81'%&)+'&#)97P]\U>:6I9DD//-*/1./,&#!$)1G<>Mr[@CZ_yneWTP<83JEM\j`Zb?2+! $,1I5G6K6683IIJKC[SXhjZA;4+!!!%#"#'((%&(('*//'$ "!%+0I3441-'%  %/9991&  #$#!" ,I6C@[a?EKGH66H8582KGJ8ID.01I8GL7GI0,$#%+IMMFHD,"!')+-**.4I8HLK3D,  "" !! !          $&'(&!%)*I8LOaMNqrA=BH3D1I6HC???=MANAaB62/'%&(&$%&-6=URRq;9*'')+(&&/5FQYkRP<21//*-/01/./*(%$$(-IGLB:>>P>>MaPaPFLJ3/-*+,'&(+5=QXggcAEI1---)',0LMijj\@6D*''+/149411*)(%'*1928G6H<>rQTNA:2/+1LNtWSA6*'0OY|ǷmWQ>>Ucl}uoc[7-&%&,0DI86LBE;J41D3;rkf}gjUCI)$##%#!&/36LK84' " $,/0-,&#+04D*$"!$&%#  $*J<>[Ura=?BLLL:G1*((%! %*98HEK9)"%,0/,% '9;PqqAOH9,#"%*4382D*% !%#!      "$(*1027C?F=?L659III041/0986HL7COFF??;784.10/-,+*4EqhnzgSA;839D.-/3Brt^ZU?3,&%(+/425J3D.(',*0933I942EPQSYZbC2+(*8PQiq?5)+2AgƗpYRidx|oXb71'&,-//04JK7;H21-+DLrZeo_tMK.&!#%%(!""&0H:LH830-15B[VZQ>K/$"&*186K;689+),*9GG59019K>]jkYbC2)&/5FrbAL9+/KQxňsWj_ouyft@HD++-**---03K6J4*')1K@Vj^jbCI,$"!$%%#! $!"!,I7:=OB8*$"!$%&&!&***,#"$&%&%##+5CaRZZ]q=?E7LaO72/')$!#"#,/1+'#       "" %()056BPM[MPCG0&"%''))(').0I66K668400.1D900**)'.K@SvnX\[=<631/.IL=ANaH9) (-9JE:?BH2-+*.8LLK51.96OUZkVAE4,,.8Cara;I*0;4,%$&'(% !%%),(&$! #$&%&&$!"#!$(+/*,%!,/./,$"&18L<:BHI1+'((('#""(,-,%      "$$'*DJ7L3, %-.0/&!" "&-IJJ89-,%%(,/.11*(&&'1KOUcX_jRUAFCLJI.),-0234*& %+I;@UQT@K.'&-6Fr[FK2005H:?B7I.+).2;OFOBH6;:T^zuehtYRir>79---.0/,%" %,//-/')+-43II0)#" """%'(&  %+09991'!"!!',)& "%,1941,! #$! %*994*$-KMS_fo`\N=BH67L:O@MO;5-$" &'&##,/111/,'!"!$#%,'%$! #%$!$+-/-'$"!##&$  (.I2ID.,%&&,*.1.*%"#(($%      " &*.2KBF>[rAPB8/#"!(0223.( $+0394.)$$$&,.0/*(%%$,06CAU]UA=::B;K5D-))',--(!"#(-2;AZZRN7/%!+6>qqA<2.,+.43I1*'()-08HEBE@OEK3.--*.DD.,#" %+1DDD1*''&### "$%('$!""#($# #''&! &+11-+.D5<=>=CG.)&#!!"!##$#!!*I6B78*% !+6@Zemf^i>E62583GJLL763.%"(**)%#*2KC?E76I-(#  &','($!&+&$ #',-,($  #&&%(#""&&)(#"#%)++'&#"""$%&)'$!    $(,*193H;E:?::H2.'&(-I;??<6D)#)*-,&&##%(*.../)%$&)/4JHL;K540*+/11//*,(((%!"#&(*2bUMPLI/'&$%## #$%$"#1GF<2*(%(.3J5D)$!'1I885358KLEL8D*)''*/1000,',')*.326KHJJ8I1049GKG30+'&)032239DI8GL<;7K2I99.+)&,/43J2I0)&%.8EBL9," &,+**08FUccirCJ4/..,,)&&''&"&DEO=F<51**15

>?8*#"&*.*,)&(%$ "(,,'  (-990/+%!# ! "#'.2G7HI.'%%'',))$""!! !$$%'($          !%+-.1.1/++),,)+-*++(()-D2KHG2D,&#&)'&$ !$$%!$*.426G86JI40*(!!)0JHE;KJI1-*),-.428851)&&'*00.,&(+I7OMa>BLLEF@@FEJ0/*,,,*--/+++-/12JH6685I0D95HB?:7I.)'-D8G5D-/4JC>MM=EH801*($().I8G554-&)4;?OC5-""&'($&*2?TkcSAC894934.+(&%&&#'07C?B7I-,),1IK76G0(!#((%%# "#%%%!"$&++&$%,9JELH2-&$#%'))$!""#&%%&%&%&&%$$        #%)+-01/+,'$#!$$%%&(&#$&)*.I3D/+(%%(('$ %'+/0I926LL6G9/'"!,IL?=:;624.*++)''++-,&#!%()/.*').2CrRkST>B;7332GG8D*("" (.5KHG2D-'!"#&),)$ ""#,D5G684-## !#%%'+-./+'&##          &)*--*,&$ %%&$# "!&)(%"#!$%#$%)16O@[raC3, #.5;4,$%)1JHE76D+))-439ID/,'('&#"" &/37:NZ_ynY:3/,4KB>M@CEK5III4DD111D9D1..)%%%'.G@jvxoY@6.*DHCBLD( %0E[iV[:GD+,''% $'-0390("#+D32D,$!%)+'$" /B]h`WU<833GHK8.% )/001/,(% %)*)!" #$!"#',*--/./.94D1+$!&%&))*--+'$          $')+*)($!#$&($ " %&++'($!(-3E@U]b[?J4.-.9288I.)#!$(.I8665I941+&! $,47FrRXfyc:9(#%.8KBCC5+! *JOrbaE5D1.1/-(!"#*/4JG9-#!'/D0+(%&+10-&"&2>V^pY[L392J6K3+"#'/-**,( " (*-*+##&''%"$'*045JJG8330**% ""#!##!&',&#"         $&)*+)&# " #%&(#" !&''$!#" &)-..0-+-02L=ArNa:7823I225I/)""$/IKLBB;L650+'%'1K?rSc^szzj>8' !%*4286;EEF@M@:EG24.*)'%!##!#&-8acsvgSOI/.J?rq@L.!"%/GC?CKID4IG52D)&%(-9GHH3/& " '+./'')-0I41(!!+KMj`XiFG1158681' ()''($""&*0..)!!%% "&*/*)&  (+D9GEBK2D*(%!"#$$##+3B\WldQBI-.6aTV\P5'""&.2685332KE;763.+.03K;;JD&!!$'++,+,+45G81,!$.;qkpZ[<4*13KK5.%"!! "$('((# "%)194/("!&+'&"!'.111,&! #(*13GEO>>=BKI/&!"$(&&!##!"!       #&+*/-)'(&&,,++-/*+--''$"!%%%% )16;7K621*,&$$(/2LC>A@?:BLH2938GKLBB<CK4*'%%! " &)+(""#)+++'$!"%$       $'+-/-+-+),--.4440000-)(  #! )1K?=FFCK20/(&(+4G:ATiSRq=E64*+*D2H<=P=:?QVVSU@CKJ884.,*DGCN\ttV][PBH9,&!"$&&%$%(9KO@[AH303<68D.-*02;FrSc_WZq?J/% (08;>MMr[M>CB72411926;EK29.+0I57;EE6I-((-2H?@bU[@@=OF:TRRR\Tq@=Pa[brN>O<7Mbii\Ura>=??E;<:MU]\qPK0/,),+%" !%/5GHHKG5J6BNQitR[C5/'##%%(('+-*-,'&&('+*,&!$)*040/+/0DI31,)',.1.,%$*IK7L63*$""%+/1/("#'-/*$"  !%!" # "%/I3D1,($$('''$#)06Fa@BKI/,(&)+)',***,(# " ## '135I90,#"#())(% #(*0258KH7BE764-&   "#&''),,,-,%%%&(),**+)(%& #0NrqB8-$#.LNdvxm^R>L3-,-4J=Qt_spk]F8*##*7[ZpvlYNB724D/-)(%&)*19I0+$&4LAScZQ>BG941/-*)&#$ ""#%),+)%%(-57O;9( $,104.+&! !$%%##$'.IGKHJ85GL<:BH0$(*/-'$(,'('&%%$$#%/GLLK4'"!$,DG;;BGD'##%'/../+&# " " %''&% !%,1I8HLLCB7J4.) "" "    "!%&'(,+'(#&DLaZ^pltM70%""" #%&!!!$'+.14J8HG9.*,)+/.I2J;P[U]NC5+$,9:]Wp`WVaL5-&! '0JOATVQA?J-$#'DEqt`lXYbO;G34.1*'&$$'+-1*'$ $-6:[UbNM:;EHHH6J894/'$" $)-D335J;Fa[a;5*$",1385I.,($(''(%!"!&+.28H7E?PAaP<4().0.'"!""! #&((')+))(&$"$+9K7KI)  $)*D3231)& $,/IG5I0'!"""!$&$# "&+.42GJGG83D/' "     "$'+/..1*/,!  '3BqcdhcrC/$" " ! !%&(*.09.)$ "!%,-.36BaqbPE3)%)D6@qTqA?H34-& "#)08BaM>F;8.(%%/5OQk^Wt\aL4("$+//-'$&)+'(%%$#%%)-../,'$$+D26JI-!!#(,+--+&# "&-3HE;J9*%#" ""!#$!" %&*10D9D40-)&""   !&'-1I4DD1.)# '9H@\tSrC3( &%# """ $%'-+(%" &%(-96C>>O64)&%*467;GJI1/*)$"!'/IGL;??<<CBEL;651+,+,*.D2H7;H34+$%/Jato|gS@KD+/8L4-$#!%,1I53D-)((-937Oaqba:G*! *2H@OL5,"$*2LF@@?;GID--)%%!$+97AiVb>;4*'()+/D5HOqSckY\AQRiV][@CL541,&'0KaSjciA;3)#!!%)DHPQYdkQFJ995LO=?7D%!',/1/**''*0I6CAU\\]bAOCO?=[SjXcTCI+$&*D4D)!#,5FbQrFG/+*02884/,(&,-425K;7;H6J2I32GK<>M@?J*!!/3HBK20(! "#$%% #'/I8768.*($%(&($!##%'*.0D.+)&$""!#%#!"     " %+D01-% """ " $(,.I8L=a@CG1(!" %(*-*+'&#$(4EAZjjSNCI)%%*4GFqSX_`jVT@<64+,*17@ihhk]F6.( "#'.GOqScVrC3.4JC@AM?2) "$,/./*,'%%(+.3GHLELE<;qYpphYN6+!"%/9I0(%%-G>]RQ>GD/-0424.*'()*/D35K;79*%! &.G:biVTML0.D7>b\bO5' #)/D1/,($ ##%'+/./.D9487BPbS^gphQ?I$$/339*((.LaU\UOK4.-.D91,',',-.-DIJ7B:::BH6241//1D4.+ '0I221,,'%$# !##! ! " !%).3JK65D)#"!$%!"!(/GBF@@?:H2.(! !$%('(!"!     !,10*(!(**(#!#))-...I2I00*,)(,,'''%((%%$(+2<>NN>BJI1+,)/1I:qWonpSaL4'#(9BUYXWQ@7I/((%)DKC[U]rF630JFbSt\O3("%-9J3/)%" ###&&)-/D2HZv}_TB4'#$/KPqRibFH31,')+DG:MqrrOK55LAZjc]:4 ,9G68D'!"""#'*.D2JKFG*""-2H7G9+(-4JBOFL20-(&,****..**+%!!""#$(*D2JG2D,  #%&')++**'% "!%#!$#&()+,,+*+*//100///*($#$(-9I5I1)$%&-5CN[q[=EJ0&  $ %)-.+'%"    " #&)%%"(.234-##$%$%&&&%(,.3LBOFB7K6GHLOPaN@:KI-)),*0II9ID01-.++/+..-,')-4K>Ys|}^TB4&!&).253I.+,',,,003KA@O;HL;B>ANr[PCJ0*)+1452G2401-.1/1.10.//**/97NZ_x}v`Q?5+$$$&*/1,&%! %'(++098LC;>PC74+)+-0.+!+8C@>FLJGKr[@:LL;?a[bUqa:759-*/4J7CB;GI425K;EH533I94.*/D8:qZkkir<9*$!!"""""" #'.8HEEE<UQr=K4*($ ! " "!$),-/-,(     "!#   #()('%""#(+-00.*+'''(((&%&)%###&-2B=Ma?LK6;>rbbM>C7834/*/4G:=PFE6JG7?FPCLGI32I91DD5LPNbTAOG.*$!" #/3KEEE;7LC>>?E80*-4928I-),/D8K7HKJ58I40/,($# $(&%  -JBPM[b\RVT[:5-$ (')))% !#)0JB=:ATRSQ@K1&!,**-'!!)0KOFP=BK4*'()**+'%$(*9KLHJ0(  $,'(&# ##!%)+.DI594-(!$/2E>AaOE51-**-.+#&IBbYkjR>79*(!"!" " #$&'(&$!     " "!(%$%!""!#$&&%$! #'-1II390*)'$#%$!!"$/5L:=E8913CrRRr:KDD332I34I;>T\br?LB>AT\UP72I2G77KK6LBE:H2.,,,*0-)( !$! " (D2K7J3D//DI52D-(&%$%(,-.IHOJ.18C@[><85L=NbNCJ408E=@@=::EK9) ,5OTiiq?8/)%!%,+)'$!!(,++'$$%(-425I0,&! !&/8E<<60+#!%,*.1./*+'$!#'-3HLG0%$16B?E2D,&')-42;C@A@PBJ/+(%!##%&,4J>@OCEHD(,Kace_Yq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lxxvXb70&%&'-43J6HL7H31+((,---,*.IHEsSB?LLK6I/,+-986HKJ9/)%""!!'-IKL:PPCK4( #.7=NQQ[aP=FOPF:6/! &+--)$# #&,+& "&'&&#"$&'&&)-952ID)#!&$#!#((&   ##!   !##()&'$!  #'1J;C:EG4,&# $%&')*.0D/+%" """ ! """$,.5KHLB;;;E5+ !%%#""!%),,)$"$(-1.)%"!&,.0/,$!""(+,%" #%!    !%%%&(% "   $'0JHE;H8.)$ """#(+/.*,!" "#$&(&$""" #)DG;;bRQAEI--DHP\`f|sZP5,""!(,D386853334-&&46C==FC784*&#!+5:qZWciN?73+&"!$$('%%&('((# $*9J6J59.'#$,--%"#%+*'& "  "" $($!     #(-1//*( !'-0941) #'/48LC:<64+$""# !$&+48J84*!##$## !#!!"!$,3;=[r@FLG39928J59*%"%*87;EH34092I3JH?N\YZqED*)16=SeyW[6*% !##$%)-D8G6849901*#'4JLaF6D/,,.D55GI-& !'06B>PBGI9I9325;=QjXkTCI+(/7aVggiC0+,))'#!&+967;H5DD941,#!+4GH6J31,%%-GB=@>E8/(!'.8;<;6D)% !$&($ "!'/9I0/)$!'.956HLHG9-$$(((!!(-0D01,!"" " !  #%$"    !$'((&!"&*09940+%"#,.8EP]itkR>;1(#!$%,'*/4I854*%!"""!)1G?=@F79*%!$+.3853/($#*2EATbaBK53332GE>\j_XUB9*+0LMVgzdMLI1-*,$ %+2;83.)$ ,J=[NaCK3223I1)$"%)136JI.(" '*444D*$ +D32I+# *8;=O70) %/IG59*!$-05HLH6I)# %+1D9I4.+'%&&$%$" &(($"  !(%%###$%#!#" !(++/*,'%!"%-3LP]jevs`]:2(  ),.D49I9D./+',))+*,&  %-5L>NN>:J+ !'/D934-&%,DEbYhpX\A:78525;@VdXV[E28Bqkfw`T?E89,!*Ka\iU>;8522531,',/1JG2I*&!'*/.-'(! ,03I-&! )2F[i]@H* "$-D559,!#)02559/% ##  "&+09II4..+',)&%# !$(&$  #)+++''$$#$#%&&),&%$!#"" &/5L=TWgxvhTC4%!"#'.149D234I41114I3I9/(!$*2E@QT\aCJ*(#%'*0D01,$$)2?i`svlcb@EK52J;M\tc]>6JEbemc[CJ3*#"",Ga]SVNBG39I22I1+.98GKGI*#!'*0../*'%!#'-94*,$'9?]W^XT<.!!'03ID,# %)**,$ %')%$!!)/.4I1/01+,)$$ "!#%&$!"       &*/0-+,%#!###'()$# !# !(+3L=\XevedU;/#"$*0949D933523J86KL;G3*(# !,47>]YYZ]F6D+&%(().0.*&!%,8PSe}yvhQaOK228EaQYiM73H>^yjNB63.( !+8=QRiqBGI3323I4.956L;6I/%#/13239D1+&!""$)-01*,)-5>jfoeVC0 $-100+%" " !!()-,'(%!"%'*././-/-+'&# #$ "    %(.0D.*+(%# %)-,'$"$(&(%" !&+D6OrY_l`cAK-#"&/94II3885J67E>:H91'#(18?bShXZ]A<81,),,+..-'% !+JPS_mnfhQNFLJ387F[Qq?JDGU|}S=7GID+$$'9<@qq@L2D0494013IJ;?BLJ0'""&.426GG834+(#"#'-10.-+0HMcvyp\C1  )-//*%" "&).--.,'$! !" "&(*/,-*,,'$$""" ""#""""      %+1D4D-+'%%!  '..D.,&#,/00-&$$((.2EN\chjQP8- "$-D35542KK7\c`hji[?K5D/*+*-,'$ #+J>V`pgdtUAOBJ44JEFM?H4/5U{uhqV^pjrK*&*+/)! "" !&'.1/.*,,&$  $# "" " !  $&('&(&%%# ! !"" ""        (+100.*'&&%$"$+042JI.+ '13889/,%$$)46?URYtU?81%%,/28KG56EECFaMN[TRZcRb?6I//8EaUSXXtRNFL6J4D.*-+$"!*J=UZtciQaP=EJD.137EH5/)2Toc[EI1.4290+)-.9253D1+),)'+13KB75I6B@qiYZiQNF:K8D01*+'%"!)5CMUTq[@:::L81))*9J84,'9anfcRaL4)'+135I.+(('+*/*'%&$&&'/IHCMNMFL3+! &,02J7;;E69-& #)42JJ21.45COP=G)#&,/,+'$!""!$# #('),''),+,'$ " %!!#$  !!"" !#  ! " ""    "$)-1/-+'%%%(&%!).36LB<78.& "&*3E;6J6<=aAUqNr@?<7K2D0/+)% !)97C>=CB;L<64,!!'-935I*&##%&'%#$! "#'/I7?@[aO79+$ &+/I28J77G9*($%-ILBH51++/5GGK0#"'*.-/,$!"%+-+'!#$$##('',,%  ! "#%# """"""""     #')*-*(($$(+'$&-4JLC::C79+%$(.GLBC72.%$.ILPaMa?LGGKH;:;7KBCB=aO?OBBC76G23I1/(# $+367EK85I87EE60&"&-9ID0D6A_~kME5D/)(! (/D584/%!! "!!#! ,/2;F>aOE8.(#""#'--1993JJ3D-'#(.JBFCJ1(!(*499- )1DD./)$ "!#!!'.4D*%"!&'($""#%$ """   #&))+,&%%&),'(!!(/2H:>P=?L3*(%'.37B;H3-$")9GC>a=?aq[rNA[bUUTUNPB<MPOC:?==>F?CELL77L768I9328G5J886G5290.1I8K;78D,(,4KB>@C5D-.9H::;J9D5?AQq=74-+/0D939DDD49./)%!"##""""%,D8H<<;J4*% " %*10.**)',*./+*-.5EOF<8) "!12HG3,"!'-I23ID*(! !%,10D-'!"&/D./'"  #&%!      "&((+'))',//-,%#&-3JLLEBE64,$%&,.55J31'!%-05HB:O?C;HH883D926K<::?P?64*).27LK2.//08KLLHJ5ID.*)(((%$$! "!#)1IGL;LKI/(!"!&*1I39-,'%$'),++-48E:CK9'" &97:?H9'"(-4383I1+'!!%/9252D)&-.+%""$((%     !$(,,,**-1.-+("!$,0D5JGKG3-)$%(+/959D-'  ,03KEFO??LHGI1-,1I5HL776J291/-/.//0DIG6E78I1+),*.D492JK77M[[[a?H3,##(DENcepk\bFCOPM@C2,"!(+0D4448EaN[M>?K9)#%+3CUWgs`tb@O:C@PLJ/$" &.0999I6;FrbrrF<621*++-00I0001D436L;;;;7J840049JH76G3.'!"!',-45GJI/$(8=[]NO5+""%,14225ID/'#,9KHJD,!!$! %%$! !&'&!        $)*/D3582DD)!" !!#%## !!%)-/-1.-*&")13H:PNA@CK0'$$(/988G8301-+'%"#*26<:L9*%""!%)(',*.IKCPAr[ra?;21,'+15?Tj_spjbPE7;:O;G9,!%)/4II9I26;=NrqN>BHGI0DDI55283I28KLC:?<77K6J552GHH7KG54/( "#&,.95J59-##DLPM>C8-$""!%+-19539D+%&*4I94*#"%$$$  !%!! "&&%!       %)*.D358ID-&! $%'*-/-1*)(##,1JLO[Ur[OGD,%$).388J33901.-,($)D6:OF;I, "%'$&&%+15EFaMAaOL50*)-D5E@TkheWSN?K5G7;LKI/(()/2832942GEPrU[bN@?78238GHLLHH7;4)#&+D88J83I44339I-)(#!%.5E@@O79&"#&($! %*DJaM@Aa>PC73D101100049I23KG621-($!(.5<=>PB8) &+*-*++,,'!$'/0..*(# "#$(,+,,,*)((          #$&,(&%# #'0DI3D.+(# !).5;FqicYir?8D-,1I8GJI003JHEE<6I0-*.6CFN>CJ,!,*'%"!*9I3JI0-*-4G7CMbUbNAOBHG31/+/45JJ394326<:;J0-,*I7=QZddcYbF;65G7EO@M[Uq[a:H9.+('),)*-*/043J67HJ4+# %-GONUQ[:3,  #&))/.0-% '+*,($ !%(,)&&&(&)&#"    " "" &*D2J8I*)% $,02HObSjkZrOKI/-4258I0D15H<::OL89.12KBaraC9&%-/.&!)D949-+*-.8C@bQV\[PCK341/,),*DII2I987B?OF:89/*/IHOqtWckSUF784I8HB>[bqqrPE5-&# !#&(((,+/IG;BCBG/% ,5?[YjST?5*%!&+13I.'""!$$ "!$$%##!#%&'#"     &135830-'#%,.DKCM\Zk\[FKI10DI53D0/15LC=F?;8I.03G;PaOK/"")00.) $+.DDD*))*4H>TtkZ\NC50-,('(&',+/0436E:P@aOBGD./D27=[\RiYQACJD**15LFNbbUABG4'""!$$%&)*D6=E84/-487:C7I,#*3I1)#" &-D4D.*+,1KOqYXWiq=K1)%$&('&$(&).9GC=[rqbPL0*'$('''%###'/I:?K1)!!!,/*)%$'1D1*&&%'/DJ66J5I9IGEO>OEGD+',*1I3II4/.03EaYpxzfjbC78G6LRtXkU:I% &.4567LHK5.,%!!!%(&$&!"!(/IG6J9+%            !())'&%##!! #,46L;L65D+--*,)%  )4HOAbAOL8.%#%','##*00D-,)(*/9GGGJ2ID9267;H20+),/D2566HKGK7G*""!()+09934.)%! ""#,D87L780)         !$&''&&&(&&%#""!$'/26KLK24+',,,(% ,47FNUM:KI) $''& #+D49D//-/.I5I8IIDD0042ID.+,').9JKBC:=Pa@M[RjglpdRN?aa:J/&!$')'%%%%).26HHLL6J83D1-*)''$#!##()+.1..0I3JMrbQ]bP70$&DHC?C74-%"#,3ORhx||lYaK41)+04JCbjfmgXRN=O?EBG0( &*//*(# $),+)&##!""$)13JH6J24+& "#$$!"        #%'+../+(% !%,1454I30D1*,,,($(',/92KE?=P=E2+!"""&1J;:F<64) #'-*//.-.DD4285JG6J8I0-(%$ " %+45HKJGI*+D7NZgyvdQC84987L:P@N]\iT@G-&&*9H:FO<50+$!+3?]pz{zgSa;I/,),.IcgugkA6.,*026;COaqZkS]>H4.1IHECCE64/'!",3:TXvwx^QP7D+'&).9;A\kjj\M?B<:BCL3- #'*/*)%!""""""$%%&()$! ""#,-D2832I1*,&# $)14I24-'"              !%,1100.,,&!" #*13J67;L68901,#!#!$)*DI6<>ArbMB8-"#%!""#*4J;76I+$""$)-/0D10D.*+(%(-/1II4D*,'#"!(15LO@aFLI*)/5Pt^spRB9' &-4225K<>QjWtTPL228GL;;LG90+(#!"(1EAS`p`Yr<2/'! %+0GFbVRbPV`_cq7.$ #*1D01D5E>RYS\[O;KJ6L77K8ID/)$!"%-8OqVSRrF60("" '0JOMAa?789955JG80,# #'),( " ""! "  &,,*0D1001/)+',D37F[N>qbNaC2)"&++,$"&.I5831)$"%&)*-.1-,(!"$+.43ID1+(&#%'/3K?rQTQqOL9/0G=Vhj\=6*! !)//,'(+0K?NTT[@:<;KHKHJ29.))&#")4HFMMP?H9)!'15E:6*"'149*$'.1D.,% "" !"#%,*,**'% !&,.D9D04-+++*18L=[RYkYTMCG58C[VctU:9'# %)//)$!)DK:O>PP?BELJ5D-*)$% "(.42230-( !(/04.)$"$',+,,&"#$%$ "##!"" "#&*-/01001JC[Vhes_\=J*     !&'-*//++'%##'*/D3J833I40+,%#"""!$&)*0I5K;CCH4("-43I*%&--1/'!"" ##!#%%%'&),%$!$(-.0DD0D4.-*+*D8EPqSjhjSrB7G7:rZZR[EI) !$,//+("%.57CFP=O:\ckdWSqFEE;?NbTb=K1$ $'13530-#"&.2KEO?>P?BJD+$"!$%%'&%!!##&(**++$!!!(),.//*,)$  #!  !!!"#&(*5<@]d^`Xi>7D&"     "!! "!(+-0...-,&$  %,-101-#'4J6I+$$MK($%+,+-,($# $$&)+0.10D9.1*,)+/14I.+),.I7PTSjXcYQFEKHC=M[><2*! (-3GG6I-$!)05GPFB69)!" !#%&&(((''),+,,''(1D43ID0/./'' "#!! !#$ "#'0JFBLJ5555D,##&$!"#!"$+D6=L9+!!$&,&#!!%'/DI32D*(# "#(/5BPq[AO<686KK51&%&%!"!!  &/43LB?@>PC8-#    "#!",04I.("#(//)'&#%()+)$" /3KHKK30/,!%)/.,# !+5C[\\UN=7I.%""#!  )056L6I+(#" %+0JOLG3II90/( "## " !#$#%! "$%&,/2HLLJD(         &-4II0,#!#'+./*(!#+4I441)'%$ %$!"" )3BAbr>C79-'%"!(****,($ !%,DGB?O78.%"!&,48H;LJ2/(#&/27?:?F?;21,!#-386H8D.,'$#!!"""!',*/-+(  "%+19I9.%"        $).D9D.,(('+/41*'  "')+(#!#%$!#"""!!'0HO@@O7G0/-*.9925I1*,($$"# $'&&'(#" #)0G;BL3*!!')-I867;63/%$)DK:>M>CK3/'! (+1I4./,& !$&,*12290,!!'*/1-,("      %,*101*,,)*-10.+$"  %%#""##!"! ! $)4H:OF<831.456ECPB;720-))&&%$%$#&&%((#! #(-26KJ.%%)+*.D5G6G9)# (1KFANMMaP;I.'"!$%&$!!%,*-.145HB=O?H9$"$%$!#       #((()&%$&)*11D.(   $"" "&-966590.96EaQYkWjQaOJ30/-*+*,((((&&''$#$'.920,#$,+)%%%,191*$&4;PNA:60(#""""!$)/DI4IJG<@[qaPK-           "#!%! !$(-11.-&   "#! "!'1DD0-,.3Qkpsfs`tT>7I1*+*,*/,,&%#&((((+-1441$$-40)" %%!&DE>a=79% !! "#)/D28G7;E@bSkWRP5&      &'*--(! "### "!$%('*3\jjZb<0"       #&%%! #&#!  ,12E@]X^_^`XZUaBK31)&!#! !$(/D41) -865-!"(08;?;J0(#&%&"!!" " $(&)+DJFbVcSb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igima-1.1.1/sigima/data/tests/image_formats/fiber.csv000066400000000000000000031365371514013333200227050ustar00rootroot000000000000002,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,4,4,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,6,6,6,6,6,6,6,7,7,7,8,8,9,9,9,8,7,6,5,5,5,5,6,7,8,8,9,9,10,10,11,12,12,11,10,9,9,8,8,7,7,7,6,6,5,5,5,5,6,8,9,10,11,11,11,9,8,8,7,7,6,5,5,6,5,5,5,5,6,7,8,9,9,9,9,9,9,9,9,7,7,7,7,7,7,7,6,6,6,6,6,6,6,6,6,5,5,5,4,4,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,2,2,1,1,2,2,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,4,4,4,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,6,6,6,6,6,6,6,7,7,7,8,8,9,9,9,8,7,6,5,5,5,5,6,7,8,8,9,10,10,11,11,12,12,11,11,10,9,9,9,7,7,7,6,6,6,5,5,5,6,7,9,10,11,11,11,9,9,8,8,7,6,6,5,6,6,5,5,6,6,7,8,9,9,9,9,9,9,9,9,9,8,8,8,7,6,6,6,6,6,6,6,6,6,6,6,5,5,5,4,4,4,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,2,2,1,1,2,2,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,4,4,4,5,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,6,6,6,6,6,6,6,7,7,7,8,8,9,9,9,8,7,6,5,5,5,5,6,7,7,8,9,10,11,11,12,11,11,11,11,11,10,10,10,7,7,7,7,6,6,6,5,4,5,7,9,10,10,11,11,10,10,9,8,7,7,6,6,6,6,5,5,6,7,8,8,10,10,10,10,10,10,10,10,11,10,9,8,7,6,5,5,6,6,6,6,6,6,6,6,5,5,5,5,4,4,4,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,2,2,1,1,2,2,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,6,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,4,4,4,5,5,5,6,6,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,7,7,7,8,8,9,9,9,8,7,6,5,5,5,5,6,7,7,8,9,10,11,12,13,12,12,12,12,12,11,11,11,8,8,7,7,7,6,6,6,4,5,7,9,10,11,11,11,11,11,10,9,8,7,6,6,7,6,6,6,6,7,8,9,10,10,10,10,11,11,11,11,12,12,11,9,8,7,5,5,7,7,7,7,7,7,7,7,6,6,5,5,5,4,4,4,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,2,2,1,1,2,2,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,7,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,4,4,5,5,5,6,6,6,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,7,7,7,8,8,9,9,9,8,7,6,5,5,5,5,6,7,7,8,10,11,12,13,14,13,13,13,13,12,12,12,12,8,8,8,7,7,7,6,6,5,6,8,9,11,11,12,12,13,12,11,10,9,7,7,6,7,7,6,6,7,7,8,9,10,10,11,11,12,12,13,13,13,13,11,10,9,7,6,6,7,7,7,7,7,7,7,7,6,6,6,5,5,5,4,4,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,2,2,1,1,2,2,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,6,7,7,7,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,5,5,5,5,6,6,6,7,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,7,7,7,7,7,7,7,7,6,6,6,6,6,6,6,6,7,7,7,8,8,9,9,9,8,7,6,5,5,5,5,6,7,7,8,10,11,13,14,15,15,15,14,14,13,12,11,11,9,8,8,8,7,7,7,7,7,8,9,11,12,13,13,13,14,14,12,11,9,8,7,6,7,7,7,7,7,8,9,9,10,11,11,12,13,13,14,14,13,13,12,11,10,9,8,7,8,8,8,8,8,8,8,8,7,6,6,6,5,5,5,5,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,5,4,4,3,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,2,2,1,1,2,2,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,6,7,8,8,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,5,5,5,6,6,6,7,7,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,7,7,7,7,7,7,7,7,6,6,6,6,6,6,6,6,7,7,7,8,8,9,9,9,8,7,6,5,5,5,5,6,7,7,8,10,12,13,15,15,18,17,16,15,13,12,10,10,9,9,8,8,8,7,7,7,8,9,11,12,14,14,15,15,15,14,13,12,10,8,7,6,8,7,7,7,7,8,9,10,10,11,11,12,13,14,15,15,12,12,12,11,10,10,10,9,8,8,8,8,8,8,8,8,7,7,6,6,6,5,5,5,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,5,4,4,3,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,2,2,1,1,2,2,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,6,7,7,8,9,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,5,5,5,6,6,7,7,7,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,7,7,7,7,7,7,7,7,6,6,6,6,6,6,6,6,7,7,7,8,8,9,9,9,8,7,6,5,5,5,5,6,6,7,8,10,12,14,15,16,19,18,17,15,13,11,10,9,9,9,9,8,8,7,7,7,9,10,12,13,15,15,16,16,16,15,14,12,10,9,7,7,8,7,7,7,7,8,9,10,11,11,12,13,14,14,15,16,12,11,11,11,11,11,11,11,8,8,8,8,8,8,8,8,7,7,7,6,6,5,5,5,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,5,4,4,3,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,2,2,1,1,2,2,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,4,4,4,4,4,4,4,4,5,5,6,6,6,6,7,7,8,8,7,7,7,6,6,6,6,6,6,6,6,6,6,6,5,5,5,6,6,7,7,7,8,8,8,7,7,6,6,6,7,7,7,7,7,7,7,7,5,5,5,5,5,5,5,5,7,7,7,7,7,7,7,7,6,7,8,8,9,10,11,11,9,9,8,7,7,6,5,5,7,8,9,11,13,15,16,17,16,16,16,16,15,14,13,12,12,11,10,9,8,7,8,8,9,10,12,13,14,15,15,15,15,14,12,10,8,7,7,7,7,7,8,9,9,10,11,11,10,11,12,12,13,12,12,12,10,10,10,9,8,8,7,7,8,9,9,10,10,9,9,8,8,8,8,7,7,6,6,6,7,7,7,7,7,7,7,7,7,7,7,6,6,5,5,5,4,4,4,5,5,6,6,6,6,6,6,6,6,6,6,6,6,7,7,8,8,7,7,6,6,6,6,5,5,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,4,4,4,4,4,4,4,4,5,5,6,6,6,7,7,7,8,8,8,7,7,7,6,6,6,6,6,6,6,6,6,6,5,5,6,6,6,7,7,7,8,8,8,7,7,6,6,6,7,7,7,7,7,7,7,7,5,5,5,5,5,5,5,5,7,7,7,7,7,7,7,7,7,7,8,9,10,10,11,11,9,9,8,8,7,6,5,5,8,9,10,12,14,16,18,18,17,17,17,16,16,14,13,12,12,11,10,9,8,8,8,8,9,10,12,13,14,15,15,15,15,14,12,10,8,7,7,7,7,7,8,9,10,10,11,11,11,12,13,14,14,14,14,13,12,12,11,10,9,8,8,7,8,9,9,10,10,9,9,8,8,8,8,7,7,6,6,6,7,7,7,7,7,7,7,7,7,7,7,6,6,5,5,5,4,4,5,5,5,6,6,6,6,6,6,6,6,6,6,6,6,7,8,8,8,8,7,6,6,6,6,5,5,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,4,4,4,4,4,4,4,4,5,5,6,6,7,7,7,8,9,9,8,8,8,7,7,7,6,6,6,6,6,6,6,6,5,6,6,6,7,7,7,7,8,8,8,7,7,6,6,6,7,7,7,7,7,7,7,7,5,5,5,5,5,5,5,5,7,7,7,7,7,8,8,8,8,8,8,9,10,10,11,11,9,9,9,8,7,6,6,5,9,10,11,13,15,17,19,19,17,17,17,17,16,15,14,13,12,12,10,9,8,8,8,8,9,10,12,13,14,15,15,15,15,14,12,10,9,8,7,7,7,8,8,9,10,11,11,11,13,14,15,16,16,16,16,16,15,15,14,12,11,10,9,8,9,9,10,10,10,10,9,9,8,8,8,7,7,6,6,6,6,6,6,6,6,6,6,6,7,7,7,6,6,5,5,5,4,5,5,5,6,6,6,6,6,6,6,6,6,6,6,6,7,7,8,9,9,8,7,7,6,6,6,5,5,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,5,5,5,5,5,5,5,5,5,5,6,6,7,8,8,9,10,9,9,9,8,8,8,8,7,7,7,7,7,7,7,7,6,6,6,7,7,7,8,8,8,8,8,7,7,6,6,6,7,7,7,7,7,7,7,7,6,6,6,6,6,6,6,6,7,7,7,8,8,8,8,9,8,9,9,10,10,11,11,11,10,10,9,8,7,7,6,6,8,9,11,13,15,17,18,19,18,18,18,18,17,16,14,14,13,12,11,9,9,8,8,9,9,10,12,13,14,15,15,15,16,15,13,11,9,8,8,7,8,8,9,9,10,11,12,12,14,15,16,18,18,18,18,18,18,18,16,14,13,11,10,9,9,9,10,11,11,10,9,9,8,8,8,7,7,6,6,6,6,6,6,6,6,6,6,6,7,7,7,6,6,5,5,5,5,5,5,6,6,6,7,7,7,7,7,7,7,7,7,7,8,8,9,9,9,9,8,8,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,5,5,5,5,5,5,5,5,5,5,6,7,8,9,9,10,10,10,10,10,9,9,9,8,7,7,7,7,7,7,7,7,6,6,7,7,7,8,8,8,8,8,8,7,7,6,6,6,7,7,7,7,7,7,7,7,6,6,6,6,6,6,6,6,7,7,7,8,8,9,9,10,9,10,10,10,10,11,11,11,10,10,9,9,8,7,6,6,7,8,9,11,13,15,17,18,19,19,19,19,18,17,15,15,13,12,11,10,9,9,9,9,9,10,12,13,14,15,15,15,16,15,13,11,10,9,8,8,8,8,9,10,11,11,12,12,14,15,16,18,19,19,19,19,19,19,17,16,14,12,11,10,9,10,11,11,11,11,10,9,8,8,8,7,7,6,6,6,6,6,6,6,6,6,6,6,7,7,7,6,6,5,5,5,5,5,6,6,6,7,7,7,7,7,7,7,7,7,7,7,9,9,10,10,10,10,9,9,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,6,6,6,6,6,6,6,6,5,5,6,7,8,9,10,10,11,11,11,10,10,10,9,9,8,8,8,8,8,8,8,8,7,7,7,7,8,8,8,9,8,8,8,7,7,6,6,6,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,8,8,9,10,10,10,10,10,10,11,11,11,11,11,11,10,10,9,8,7,7,7,7,7,9,11,13,15,16,17,19,20,20,19,19,17,16,15,13,13,11,10,9,9,9,9,9,10,12,13,14,15,15,15,17,15,14,12,10,9,8,8,9,9,9,10,11,12,12,13,13,14,15,17,18,19,19,19,19,18,17,16,14,13,12,11,10,10,11,11,11,11,10,10,8,8,8,7,7,6,6,6,7,7,7,7,7,7,7,7,7,7,7,6,6,5,5,5,6,6,6,6,7,7,7,8,8,8,8,8,8,8,8,8,9,10,11,11,11,11,10,9,6,6,6,5,5,4,4,4,5,5,5,5,5,5,5,5,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,6,6,6,6,6,6,6,6,5,5,6,7,9,10,11,11,12,12,11,11,11,10,10,10,8,8,8,8,8,8,8,8,7,7,7,8,8,8,9,9,8,8,8,7,7,6,6,6,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,8,8,9,10,11,11,11,11,11,11,11,11,11,11,11,11,10,9,8,8,7,7,8,8,10,12,14,16,17,18,20,20,20,20,19,18,17,16,14,13,12,10,10,9,9,10,9,10,12,13,14,15,15,15,17,16,14,12,10,9,9,9,9,9,10,10,11,12,13,13,11,12,13,15,16,17,17,17,18,17,17,16,15,14,13,13,10,11,11,12,12,11,11,10,8,8,8,7,7,6,6,6,8,8,8,8,8,8,8,8,7,7,7,6,6,5,5,5,6,6,6,7,7,7,8,8,8,8,8,8,8,8,8,8,10,10,11,12,12,11,10,10,6,6,6,5,5,4,4,4,5,5,5,5,5,5,5,5,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,6,6,6,6,6,6,6,6,5,5,6,7,9,10,11,12,12,12,12,11,11,11,10,10,8,8,8,8,8,8,8,8,7,7,7,8,8,9,9,9,8,8,8,7,7,6,6,6,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,8,9,10,10,11,12,11,11,11,11,11,11,11,11,11,11,10,9,9,8,7,7,9,10,11,13,15,17,18,19,20,21,21,20,19,18,17,16,14,13,12,11,10,10,10,10,9,10,12,13,14,15,15,15,17,16,14,12,10,9,9,9,9,9,10,11,11,12,13,13,9,10,12,14,15,16,16,16,16,16,16,15,15,14,14,13,10,11,11,12,12,11,11,10,8,8,8,7,7,6,6,6,9,9,9,9,9,9,9,9,7,7,7,6,6,5,5,5,6,6,6,7,7,8,8,8,8,8,8,8,8,8,8,8,10,11,11,12,12,11,11,10,6,6,6,5,5,4,4,4,5,5,5,5,5,5,5,5,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,4,4,5,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,6,6,7,7,8,8,8,9,9,9,9,9,7,6,6,7,7,7,8,9,10,11,12,15,15,15,14,13,12,11,10,9,9,9,9,9,9,9,9,8,8,8,8,8,8,8,8,9,9,9,8,8,7,7,7,8,8,8,8,8,8,8,8,7,7,7,7,7,7,7,7,7,8,9,10,11,12,12,13,13,13,14,14,14,13,12,11,11,11,11,11,11,11,11,11,9,10,11,13,15,18,21,22,26,25,24,23,21,18,16,15,15,14,13,12,11,11,11,11,11,12,13,14,15,16,16,16,15,14,13,11,9,9,8,8,7,8,9,11,13,15,16,17,16,16,15,14,13,13,12,11,14,14,14,14,14,14,14,14,13,13,13,13,12,11,10,9,9,9,8,7,7,7,8,8,10,10,11,12,12,12,11,11,8,8,6,5,5,5,5,5,7,7,7,7,7,7,7,7,7,7,8,9,9,10,11,11,11,11,10,10,10,10,9,9,6,5,5,4,4,5,5,6,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,4,4,4,5,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,6,6,7,7,8,8,8,9,9,9,9,9,8,7,6,8,7,7,8,9,10,11,12,14,14,14,14,13,12,10,10,9,9,9,9,9,9,9,9,8,8,8,8,8,8,8,8,9,9,9,8,8,8,7,7,8,8,8,8,8,8,8,8,7,7,7,7,7,7,7,7,7,7,8,9,10,11,12,13,13,14,14,14,14,13,12,12,11,11,11,11,11,11,11,11,11,11,12,14,17,20,22,24,26,25,25,23,21,18,16,15,15,14,13,11,10,10,10,10,11,12,13,14,15,16,16,15,15,14,13,11,10,9,9,9,9,10,11,12,14,16,17,18,17,16,16,15,14,13,12,12,13,13,13,13,13,13,13,13,14,14,14,14,13,12,10,10,9,9,8,7,7,8,8,9,10,11,11,12,12,11,11,10,8,7,6,6,5,5,5,6,7,7,7,7,7,7,7,7,7,7,8,9,10,10,11,11,11,11,10,10,10,10,9,9,6,5,5,4,4,5,5,6,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,4,4,4,5,5,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,6,6,7,7,8,8,8,8,9,9,9,9,8,7,7,8,8,8,8,9,10,11,12,13,13,13,13,12,11,10,9,10,10,10,10,10,10,10,10,9,9,9,9,9,9,9,9,9,9,9,9,8,8,8,7,8,8,8,8,8,8,8,8,7,7,7,7,7,7,7,7,6,7,7,9,10,11,12,13,15,15,15,15,15,14,13,12,11,11,11,11,11,12,12,12,13,13,14,16,18,21,23,25,26,25,25,23,21,19,17,16,14,13,12,11,10,10,10,10,11,12,13,14,15,15,15,15,15,14,12,11,10,9,9,9,10,11,12,13,15,16,18,18,17,17,16,15,15,14,13,13,13,13,13,13,13,13,13,13,15,15,15,15,14,13,11,11,9,9,8,8,8,8,9,9,10,11,11,12,12,11,10,10,8,7,7,6,5,6,6,6,8,8,8,8,8,8,8,8,7,8,8,9,10,11,11,11,11,11,11,10,10,9,9,9,6,5,5,4,4,5,5,6,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,5,6,6,6,6,6,6,6,6,6,6,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,6,6,6,7,7,8,8,8,8,9,9,10,10,9,8,8,8,8,8,8,8,9,10,11,12,12,13,13,12,11,10,9,11,11,11,11,11,11,11,11,10,10,10,10,10,10,10,10,10,10,9,9,9,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,6,6,7,9,10,12,13,13,16,17,17,17,16,15,14,13,11,11,11,12,12,12,12,13,14,14,15,16,19,21,23,25,25,25,25,23,22,20,18,16,14,14,12,11,10,10,10,10,12,13,14,15,15,15,15,15,14,13,12,11,10,9,9,9,10,11,12,13,14,16,17,17,17,16,16,16,15,15,14,14,12,12,12,12,12,12,12,12,15,16,16,15,15,13,12,11,9,8,8,8,8,9,10,10,11,11,12,12,12,11,10,9,8,7,7,6,6,6,7,7,9,9,9,9,9,9,9,9,8,8,9,9,10,11,12,12,12,12,11,10,10,9,8,8,6,5,5,4,4,5,5,6,6,6,6,6,6,6,6,6,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,5,5,5,6,6,6,6,6,6,6,6,6,6,6,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,6,6,6,7,7,8,8,8,8,9,9,10,10,10,9,9,9,9,8,8,8,9,10,11,12,12,13,13,13,12,11,11,11,11,11,11,11,11,11,11,10,10,10,10,10,10,10,10,10,10,10,9,9,9,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,6,6,8,9,11,13,14,15,18,18,18,18,17,16,14,13,11,11,11,12,12,13,13,14,14,14,15,16,18,20,22,23,25,25,25,24,22,20,19,18,15,14,13,12,11,11,11,11,12,13,14,15,15,15,14,14,14,13,12,11,10,10,10,10,9,10,11,12,13,14,15,15,16,16,15,15,15,15,14,14,12,12,12,12,12,12,12,12,15,16,16,15,15,13,12,11,9,8,8,8,9,10,11,11,12,12,12,12,12,11,10,9,8,7,7,6,6,7,8,8,9,9,9,9,9,9,9,9,8,8,9,10,11,11,12,12,12,12,11,10,10,9,8,8,6,5,5,4,4,5,5,6,6,6,6,6,6,6,6,6,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,5,5,5,5,6,6,6,7,7,7,7,7,7,7,7,7,6,6,6,6,6,6,6,6,5,5,5,5,5,5,5,5,6,6,6,7,7,8,8,8,8,9,9,10,11,10,10,10,10,9,9,8,8,9,10,10,13,13,14,14,14,13,13,12,12,12,12,12,12,12,12,12,11,11,11,11,11,11,11,11,11,10,10,10,9,9,9,9,8,8,8,8,8,8,8,8,9,9,9,9,9,9,9,9,7,7,9,11,13,15,16,17,20,20,20,19,18,16,15,14,11,11,12,12,13,14,14,14,14,15,15,16,18,20,22,23,25,25,25,24,23,21,19,18,17,16,15,13,12,12,12,12,13,13,14,15,15,14,14,13,13,12,11,10,10,10,10,11,9,10,10,11,12,13,14,14,14,14,14,14,14,14,14,14,13,13,13,13,13,13,13,13,15,15,15,15,14,13,11,11,9,8,8,8,9,10,12,12,12,12,12,12,11,10,9,8,8,7,7,7,7,8,9,9,10,10,10,10,10,10,10,10,9,9,9,10,11,12,12,13,13,12,12,11,9,8,8,7,6,5,5,4,4,5,5,6,7,7,7,7,7,7,7,7,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,5,5,5,6,6,6,7,7,7,7,7,7,7,7,7,7,6,6,6,6,6,6,6,6,5,5,5,5,5,5,5,5,6,6,6,7,7,8,8,8,8,9,10,10,11,11,11,10,10,9,9,8,8,9,9,10,13,14,15,15,15,15,14,14,13,13,13,13,13,13,13,13,12,12,12,12,12,12,12,12,11,11,10,10,10,9,9,9,8,8,8,8,8,8,8,8,9,9,9,9,9,9,9,9,8,9,10,12,14,16,18,19,21,21,21,20,19,17,16,15,11,11,12,12,13,14,15,15,16,16,17,18,20,21,23,24,25,25,25,24,23,22,20,19,18,17,16,15,14,14,14,14,13,14,14,15,15,14,14,13,13,12,11,10,10,10,11,11,11,11,12,12,13,14,14,15,12,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,14,14,14,14,13,12,10,10,8,8,8,9,10,11,12,13,12,13,13,12,11,10,9,8,7,7,7,7,7,8,9,10,11,11,11,11,11,11,11,11,9,9,10,10,11,12,13,13,13,13,12,11,9,8,7,7,6,5,5,4,4,5,5,6,7,7,7,7,7,7,7,7,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,5,5,5,6,6,7,7,7,7,7,7,7,7,7,7,7,6,6,6,6,6,6,6,6,5,5,5,5,5,5,5,5,6,6,6,7,7,8,8,8,8,8,10,11,11,11,11,11,10,10,9,8,8,8,9,9,14,15,15,16,16,16,15,15,13,13,13,13,13,13,13,13,12,12,12,12,12,12,12,12,11,11,11,10,10,9,9,9,8,8,8,8,8,8,8,8,9,9,9,9,9,9,9,9,9,9,11,13,15,17,19,20,22,22,21,21,19,17,16,15,11,11,12,13,14,14,15,16,18,18,19,20,21,23,25,26,25,25,25,24,23,22,20,19,19,18,17,16,15,15,15,15,14,14,15,15,15,14,13,13,12,12,11,10,10,10,11,11,12,13,13,14,14,15,15,16,11,11,12,12,12,12,12,12,14,14,14,14,14,14,14,14,13,13,13,13,12,11,10,9,8,8,8,9,10,11,12,13,13,13,13,12,11,10,9,8,7,7,7,7,7,9,10,10,11,11,11,11,11,11,11,11,9,9,10,11,11,12,13,13,14,13,12,11,9,8,7,6,6,5,5,4,4,5,5,6,7,7,7,7,7,7,7,7,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,6,6,7,8,8,9,9,10,10,10,9,8,8,5,6,6,6,6,6,6,6,6,6,6,5,5,4,4,4,6,6,7,7,7,7,8,8,10,11,12,13,13,13,13,12,9,9,8,8,8,9,10,10,15,16,17,19,19,18,17,16,13,12,12,12,12,12,11,11,12,12,12,12,12,12,12,12,12,12,12,12,11,10,9,8,10,10,11,11,11,11,11,12,11,10,10,9,9,9,10,11,11,11,12,14,16,19,22,23,23,23,24,24,22,19,16,14,12,12,12,13,15,17,19,20,21,21,22,23,24,25,26,27,26,26,25,24,23,23,22,22,19,18,17,17,16,15,14,14,15,15,14,14,14,15,16,16,14,13,12,11,11,11,11,11,11,13,15,18,19,18,17,16,13,13,12,10,10,10,10,10,11,12,12,13,13,14,14,15,14,14,13,11,10,9,8,8,8,9,10,11,13,14,15,15,17,16,15,13,11,9,8,7,6,7,8,9,10,10,10,10,10,10,11,12,12,12,11,11,10,10,10,11,11,12,12,12,14,13,11,9,7,6,6,5,5,5,5,6,6,6,7,7,7,7,7,7,7,7,7,7,7,7,7,6,6,5,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,6,6,7,8,8,8,9,10,10,10,9,9,8,6,6,6,6,6,6,6,7,6,6,6,5,5,5,4,4,6,6,7,7,7,8,8,8,10,11,12,13,13,13,13,12,10,9,9,8,8,9,10,10,14,16,17,18,19,18,17,16,13,13,13,12,12,12,12,11,13,13,12,12,12,12,12,12,14,14,14,14,13,12,10,10,10,11,11,11,12,12,12,12,12,11,10,10,9,10,10,10,10,11,12,14,16,19,22,23,23,24,25,25,23,20,17,15,12,12,12,13,15,17,19,20,22,22,23,25,26,27,28,28,28,27,26,25,24,23,22,21,18,18,17,16,15,14,14,13,16,15,15,14,14,15,15,16,14,13,13,12,11,11,11,11,12,14,16,18,19,19,18,17,14,13,12,11,10,10,10,10,11,12,12,13,14,14,15,15,14,14,13,12,11,10,9,8,9,9,10,12,13,14,15,16,16,16,14,13,11,9,8,8,6,7,9,10,11,11,11,11,10,11,11,12,12,12,11,10,10,10,10,11,11,12,12,12,14,13,11,9,7,6,6,5,5,5,6,6,6,7,7,7,7,7,7,7,7,7,7,7,7,7,7,6,6,6,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,6,6,7,8,8,8,9,10,10,10,10,9,9,7,7,7,7,7,7,7,7,6,6,6,6,5,5,5,4,6,6,7,7,8,8,8,9,11,11,12,13,13,13,13,13,10,10,9,9,9,9,10,10,14,15,17,18,19,18,17,17,14,14,14,13,13,12,12,12,14,14,13,13,12,12,11,11,15,15,16,15,14,13,12,11,11,11,12,12,12,13,13,13,13,12,11,10,10,10,10,10,10,11,12,14,16,19,21,23,25,25,26,26,24,22,18,16,12,12,12,12,14,16,19,20,23,24,26,27,28,29,29,30,30,29,28,26,24,22,21,20,17,17,16,15,15,14,13,13,16,16,15,14,14,15,15,16,13,13,13,13,12,12,12,12,14,16,18,19,20,20,19,18,15,14,12,11,10,10,10,10,11,11,12,13,14,15,15,16,15,15,14,13,12,10,10,9,10,10,11,12,13,14,15,16,16,15,14,12,11,9,8,8,7,8,9,11,11,12,12,11,11,11,12,12,12,12,11,10,10,10,10,11,11,12,12,12,13,12,10,9,7,6,6,5,6,6,6,7,7,7,8,8,8,8,8,8,8,8,8,8,7,7,7,7,6,6,6,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,6,6,7,8,8,8,9,10,10,11,11,10,10,9,9,9,9,8,8,8,8,7,7,6,6,6,5,5,5,6,6,7,7,8,9,9,10,11,12,13,13,14,14,13,13,11,11,10,9,9,9,9,10,14,15,17,18,19,19,18,17,15,15,15,14,13,13,12,12,15,14,14,13,12,12,11,11,16,16,16,16,15,13,12,11,12,12,12,13,14,14,15,15,15,14,13,11,10,10,10,10,10,10,11,13,16,18,21,22,26,26,27,27,26,23,19,17,12,12,11,11,13,16,19,21,25,26,28,30,31,32,31,31,32,31,29,27,24,22,20,19,16,16,15,15,14,14,14,13,17,16,15,14,14,14,15,15,14,14,14,14,14,14,13,13,16,17,19,20,20,20,20,19,15,15,13,12,10,10,10,10,11,11,12,13,14,15,16,17,16,16,15,14,13,12,11,10,11,12,12,13,14,15,16,16,15,14,13,12,11,9,8,8,8,9,11,12,13,13,13,13,12,12,13,13,12,12,11,10,10,10,10,11,11,12,12,12,12,11,10,8,7,6,6,6,7,7,7,7,8,8,8,9,9,9,9,9,9,9,9,9,8,8,7,7,7,6,6,6,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,6,6,7,8,8,8,9,10,11,11,11,11,11,11,11,10,10,9,9,8,8,7,7,7,6,6,6,5,5,6,6,7,8,9,10,10,11,11,12,13,14,14,14,14,13,12,12,11,10,9,9,9,10,13,14,16,18,19,19,18,18,17,16,16,15,14,13,12,12,15,14,14,13,13,12,12,12,15,15,15,15,14,13,12,11,12,13,13,14,15,16,17,17,17,16,14,12,11,10,10,10,9,10,11,13,15,18,20,22,26,27,28,28,26,23,20,18,12,11,10,10,12,15,18,21,26,28,30,32,34,34,33,32,32,31,29,26,24,21,19,18,16,16,15,15,15,15,14,14,17,16,15,14,14,14,14,14,14,15,16,17,17,17,16,15,18,19,19,20,20,20,20,20,16,15,14,12,11,10,10,10,11,11,12,14,15,16,17,18,18,17,16,15,14,13,12,12,13,13,13,14,15,15,16,16,14,13,12,11,10,9,8,8,10,11,12,13,14,14,14,14,13,13,13,13,13,12,11,10,10,10,10,11,11,12,12,12,11,11,9,8,6,6,6,6,7,8,8,8,9,9,9,9,9,9,9,9,9,9,9,9,8,8,8,7,7,7,6,6,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,6,6,7,8,8,8,9,10,11,12,12,12,12,13,12,12,11,10,10,9,9,8,7,7,7,6,6,6,6,6,6,7,8,9,10,11,11,12,12,13,14,15,15,14,14,13,13,11,10,9,9,9,10,12,14,16,18,19,19,19,18,18,18,17,16,15,14,13,12,13,13,13,14,14,14,14,14,15,15,15,15,14,13,12,11,13,13,14,15,16,17,18,19,19,18,16,13,11,10,9,9,9,9,11,12,15,18,20,21,26,27,27,27,26,23,20,17,13,11,10,9,11,14,18,21,26,28,31,34,35,35,33,32,31,30,28,25,23,20,18,17,16,16,16,16,16,16,16,16,18,17,16,15,14,14,14,14,16,17,19,20,20,20,18,18,19,19,19,19,19,19,19,19,17,16,14,13,11,10,10,9,11,11,12,14,15,17,18,19,19,18,18,16,15,14,13,13,14,14,14,15,15,16,16,16,13,12,12,11,10,9,8,8,11,12,13,14,15,15,15,15,14,14,14,14,13,12,11,10,10,10,10,11,11,12,12,12,11,10,8,7,6,6,6,6,8,8,9,9,9,10,10,10,10,10,10,10,10,10,10,10,9,8,8,8,7,7,7,7,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,6,6,7,8,8,8,9,10,11,12,12,12,12,14,14,13,12,11,10,10,9,8,8,7,7,7,6,6,6,6,6,7,8,10,11,12,12,12,13,14,14,15,15,14,14,14,13,12,11,10,9,9,9,12,14,16,18,19,20,19,19,19,19,18,16,15,14,13,12,12,12,13,14,14,15,15,16,17,17,17,17,16,15,13,13,13,14,15,16,17,19,19,20,20,19,17,14,12,10,9,9,9,9,10,12,15,17,20,21,25,26,27,27,25,22,19,17,13,11,9,9,10,14,18,21,26,28,32,34,36,35,33,32,28,28,26,24,22,19,18,17,17,17,17,17,17,17,17,18,18,17,16,15,14,13,13,14,17,19,21,23,23,22,21,20,19,19,18,18,18,18,18,19,18,17,15,13,11,10,10,9,11,11,12,14,16,17,19,19,20,19,18,17,16,15,14,14,15,15,15,16,16,16,16,17,12,12,11,11,10,9,9,8,12,13,14,15,16,16,16,16,14,14,14,14,13,12,11,10,10,10,10,11,11,12,12,12,10,9,8,7,6,6,6,6,9,9,9,10,10,10,11,11,11,11,11,11,11,11,11,11,9,9,8,8,8,7,7,7,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,6,6,7,8,8,8,9,10,11,12,13,13,13,15,14,14,13,12,11,10,10,8,8,8,7,7,6,6,6,6,6,7,8,10,11,12,13,12,13,14,15,15,15,15,14,14,13,12,11,10,9,9,9,12,13,16,18,19,20,19,19,20,19,18,17,15,14,13,13,11,11,12,13,15,16,17,17,18,19,19,18,18,16,15,14,14,14,15,16,18,19,20,21,21,20,17,14,12,10,9,9,9,9,10,12,14,17,20,21,25,25,26,26,25,22,18,16,13,11,9,8,10,14,18,21,26,28,32,35,36,35,33,32,27,26,25,23,21,19,18,17,18,18,18,18,18,18,19,19,18,17,16,15,14,13,13,13,19,20,23,24,25,24,23,21,19,19,18,17,17,17,18,18,18,17,15,13,11,10,10,9,10,11,12,14,16,18,19,20,20,20,19,18,17,15,14,14,15,16,16,16,16,16,17,17,12,11,11,10,10,9,9,8,12,13,14,16,16,17,17,16,15,15,15,14,13,12,11,10,10,10,10,11,11,12,12,12,9,9,8,6,6,6,6,6,9,9,10,10,10,11,11,11,11,11,11,11,11,11,11,11,9,9,9,8,8,7,7,7,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,4,4,5,5,5,4,4,4,5,5,6,6,6,6,6,6,6,6,6,6,6,5,5,5,4,4,3,3,3,4,4,4,5,5,6,6,6,5,5,5,5,5,6,8,8,9,9,11,12,14,15,17,17,17,16,14,13,12,12,13,14,12,11,10,9,8,7,7,6,6,7,7,8,10,11,11,12,13,13,13,14,14,15,15,15,16,15,14,12,11,10,10,10,10,12,16,19,21,22,22,21,19,18,16,14,13,13,13,14,13,13,13,14,15,18,21,22,24,24,24,23,21,19,17,16,15,16,16,18,20,22,24,26,25,24,22,19,16,14,12,11,11,11,11,12,15,18,21,22,25,26,26,25,23,20,18,16,15,13,11,10,11,14,17,20,25,27,31,34,35,35,34,34,29,27,25,22,20,20,20,20,18,18,17,17,17,18,19,20,20,19,17,16,15,16,16,17,19,21,24,26,28,27,26,25,20,20,20,19,18,18,18,17,15,15,15,14,13,12,10,9,11,12,13,15,17,18,18,18,19,19,18,17,17,17,18,18,17,17,18,18,17,17,16,15,15,14,13,11,11,12,13,14,16,17,19,20,21,20,20,19,16,16,16,15,14,13,11,10,11,11,11,10,10,9,9,9,9,8,8,7,7,8,9,9,11,11,11,12,12,13,13,13,13,13,14,14,14,13,12,11,10,10,9,8,8,7,6,6,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,4,4,4,5,5,5,4,4,5,5,5,6,6,6,6,6,6,6,6,6,6,6,5,5,5,4,4,4,3,3,4,4,5,5,5,6,6,6,6,5,5,5,6,6,7,8,9,9,11,12,14,15,17,17,17,16,14,13,13,13,14,14,12,12,11,10,9,8,7,6,6,7,7,9,10,11,12,12,13,13,13,14,14,15,15,15,16,15,13,11,10,9,9,9,10,12,16,19,22,23,23,22,20,18,16,14,13,13,13,14,14,14,14,15,16,19,21,23,24,24,24,23,22,20,19,18,17,17,18,19,21,24,26,27,27,26,24,21,17,14,12,11,10,10,11,13,15,18,21,22,24,24,24,23,22,20,18,16,15,13,12,11,12,14,17,19,26,28,31,34,35,36,35,34,29,28,25,23,21,20,20,21,19,19,18,17,17,18,18,19,20,19,17,16,15,16,17,17,20,22,25,28,29,29,28,27,23,22,21,20,19,18,17,17,15,15,15,14,13,12,10,9,10,11,13,14,16,17,18,18,20,19,19,19,19,19,19,19,18,19,19,19,18,17,16,15,14,13,12,11,11,12,14,15,19,19,21,22,22,22,21,20,18,18,17,17,16,14,12,11,11,11,11,10,10,9,9,9,8,8,7,7,7,8,9,9,11,11,11,12,12,13,13,13,13,14,14,14,14,13,12,11,10,10,9,9,8,7,6,6,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,4,4,4,5,5,5,5,4,5,5,5,6,6,6,6,6,6,6,6,6,6,6,6,5,5,5,5,4,4,4,3,4,5,5,5,6,6,6,6,6,6,6,5,6,7,7,8,9,9,11,12,14,15,17,17,17,16,15,14,14,14,15,15,13,13,12,10,9,8,7,6,6,7,8,9,10,11,12,13,14,14,14,14,15,15,15,15,15,14,12,11,10,9,9,9,11,13,17,20,22,24,24,24,21,19,17,15,14,13,14,14,15,15,15,16,17,19,21,22,23,23,24,24,23,23,22,21,19,19,20,22,24,26,28,30,31,30,27,23,19,15,12,10,10,11,12,15,17,20,22,23,22,22,21,20,19,18,18,17,15,14,12,12,12,14,17,19,26,28,31,34,36,36,35,34,30,28,26,23,22,21,21,22,21,20,19,18,17,17,17,17,19,18,17,16,15,16,17,18,22,24,27,30,32,33,32,31,28,26,24,22,20,18,17,17,16,16,15,15,13,12,10,9,9,10,11,13,15,16,18,18,20,20,20,20,21,21,21,21,21,21,21,21,20,18,17,16,13,12,11,11,12,14,15,17,22,23,23,24,23,22,21,21,19,19,19,18,17,15,14,13,11,11,11,10,10,9,9,9,7,7,7,7,7,8,9,10,11,11,12,12,12,13,13,13,14,14,15,15,14,14,13,12,10,10,10,9,8,7,7,6,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,5,6,6,5,5,5,6,6,6,7,7,7,7,7,7,7,7,7,7,6,6,5,5,5,4,4,4,5,5,5,6,6,6,7,7,7,7,6,6,6,7,7,8,9,9,11,12,14,15,17,17,17,17,16,16,16,16,16,16,14,14,13,11,10,8,7,7,6,7,8,9,11,12,13,14,14,15,15,15,15,15,15,15,15,14,12,10,9,9,8,8,12,14,17,20,23,25,26,26,22,21,18,16,14,14,14,14,14,14,15,16,17,19,20,21,22,23,24,25,25,25,24,24,22,22,23,24,26,29,31,32,35,33,30,25,20,15,12,10,10,11,14,17,20,22,23,24,21,20,19,18,17,17,17,18,15,14,13,13,13,15,17,18,25,27,30,33,35,35,34,33,29,28,26,23,22,22,22,23,22,21,20,18,17,16,15,15,19,18,16,15,15,16,17,18,23,25,29,33,36,37,36,36,33,31,28,24,21,19,17,17,17,17,17,16,14,12,10,9,9,10,11,12,14,16,18,19,21,21,22,22,22,22,22,22,24,24,24,22,21,19,17,16,12,11,11,12,13,16,18,20,26,25,25,24,23,21,20,20,19,19,19,18,17,15,13,13,11,11,11,10,10,9,9,9,7,6,6,7,8,9,11,12,13,13,13,13,13,13,13,13,15,15,16,16,15,14,13,13,11,11,10,9,8,8,7,7,6,6,6,6,6,6,6,6,5,5,5,5,5,5,5,5,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,5,5,5,6,6,6,5,5,6,6,6,7,7,7,7,7,7,7,7,7,7,7,6,6,6,5,5,5,4,4,5,5,6,6,6,7,7,7,8,8,7,6,6,7,7,8,9,9,11,12,14,15,17,17,17,17,18,18,18,18,18,18,16,15,14,12,11,9,8,7,6,6,8,9,11,13,14,15,16,15,15,15,15,15,15,15,15,14,12,11,10,9,9,9,12,14,16,19,22,25,26,27,24,22,19,17,15,14,14,15,13,14,15,16,17,18,19,19,21,22,23,25,26,26,26,26,24,24,25,26,28,31,33,34,37,35,31,26,21,16,12,10,10,13,17,21,24,25,26,25,21,20,17,15,15,16,17,18,16,15,14,14,14,15,16,17,24,26,29,32,34,34,33,32,28,27,25,23,22,22,22,23,23,22,20,18,16,15,15,15,18,17,16,15,15,16,18,19,24,26,31,35,38,40,40,40,38,35,31,26,22,20,19,19,19,19,19,17,16,13,12,10,10,10,10,12,14,17,19,21,21,22,23,25,25,25,24,24,27,26,25,24,21,18,16,15,11,11,11,13,15,19,22,24,29,28,26,24,22,20,19,18,18,18,18,17,16,14,13,12,11,11,11,10,10,9,9,9,7,7,7,8,9,11,13,14,15,15,15,15,15,15,14,14,16,16,16,16,16,15,14,14,11,11,10,10,9,8,7,7,6,6,6,6,6,6,6,6,5,5,5,5,5,5,5,5,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,5,5,5,5,6,6,6,7,6,6,6,6,7,7,7,8,8,8,8,8,8,8,8,8,7,6,6,6,5,5,5,5,6,6,6,6,7,7,7,8,9,9,8,7,7,7,7,8,9,9,11,12,14,15,17,17,17,18,19,20,20,20,19,19,17,16,15,13,11,9,8,7,6,6,8,10,12,13,15,16,16,16,16,16,15,15,15,15,16,15,14,12,11,10,10,10,11,13,15,18,21,24,26,28,25,23,20,18,16,15,15,15,14,15,17,18,19,19,19,19,21,22,23,24,25,26,26,26,25,25,26,28,30,32,34,35,38,36,32,27,22,16,13,11,12,15,20,25,28,29,29,28,23,21,17,14,13,15,17,18,16,16,15,15,15,15,16,17,22,24,27,30,32,32,31,30,27,25,24,22,21,21,22,22,22,21,20,18,16,16,15,15,18,17,16,15,16,17,18,19,24,27,31,37,40,43,43,43,41,38,33,28,24,22,21,21,22,22,21,20,18,15,13,12,11,11,11,12,15,18,21,23,24,25,27,29,30,29,28,28,29,28,26,24,21,18,15,13,11,11,12,15,18,22,26,28,32,30,27,24,21,19,18,17,18,18,17,17,16,14,12,11,11,11,11,10,10,9,9,9,7,8,8,10,11,14,16,17,18,18,17,17,17,16,16,16,16,17,17,17,17,16,15,14,12,11,11,10,9,8,8,8,7,7,7,7,7,7,7,7,6,6,6,6,6,6,6,6,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,5,5,5,6,6,6,7,7,6,6,6,7,7,7,8,8,8,8,8,8,8,8,8,8,7,7,6,6,6,5,5,5,6,6,6,7,7,7,8,8,10,9,8,7,7,7,7,7,9,9,11,12,14,15,17,17,17,18,20,21,21,21,20,20,18,17,16,14,12,10,8,7,6,6,8,10,12,14,15,16,17,17,17,16,16,15,15,15,17,16,15,13,12,11,11,11,11,12,13,16,20,23,26,28,26,24,21,18,16,15,15,15,17,18,19,21,22,22,21,21,21,22,23,24,25,25,25,24,26,26,27,28,30,33,35,36,37,35,32,27,22,17,13,11,13,17,23,28,32,32,31,30,26,23,18,14,13,14,16,18,16,16,16,16,16,16,16,16,20,22,26,28,30,30,29,29,25,24,22,20,20,20,21,21,21,21,19,18,17,16,16,16,17,17,16,15,16,17,19,20,23,27,32,37,41,44,45,45,44,40,35,29,25,23,23,23,25,24,23,22,20,17,15,14,12,12,12,13,15,19,23,25,28,30,32,34,35,35,34,33,29,28,27,24,20,17,13,12,12,12,14,16,20,25,29,32,36,34,30,26,22,20,18,18,19,19,19,18,17,15,14,13,11,11,11,10,10,9,9,9,8,9,10,11,13,16,18,19,20,20,20,19,19,18,18,18,17,17,18,18,17,16,16,15,12,12,11,10,9,9,8,8,7,7,7,7,7,7,7,7,6,6,6,6,6,6,6,6,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,5,5,5,6,6,7,7,7,6,6,6,7,7,8,8,8,8,8,8,8,8,8,8,8,7,7,7,6,6,5,5,5,6,6,6,7,7,8,8,8,10,10,9,7,7,7,7,7,9,9,11,12,14,15,17,17,17,18,20,21,22,22,21,20,19,18,16,14,12,10,8,8,5,6,8,10,12,14,16,17,17,17,17,16,16,15,15,15,18,17,16,14,13,12,12,12,10,11,13,15,19,22,26,27,26,25,22,19,16,15,15,15,19,20,22,24,24,24,23,22,21,21,23,23,24,24,24,23,26,26,27,28,30,33,35,36,37,35,31,27,21,17,13,11,14,18,24,30,34,34,33,31,28,24,19,14,12,13,16,18,16,16,16,16,16,16,16,16,19,21,24,27,29,29,28,27,24,23,21,20,19,19,20,21,21,20,19,18,17,17,17,17,17,16,16,15,16,17,19,20,23,26,32,37,42,45,46,46,44,41,36,30,26,24,24,24,26,26,25,23,21,18,16,15,13,13,12,13,16,20,24,26,32,34,36,39,40,39,38,37,30,29,27,24,20,16,13,11,12,13,14,17,22,27,31,34,39,36,32,28,24,21,19,19,20,20,20,19,18,17,15,14,11,11,11,10,10,9,9,9,9,9,10,12,15,17,20,21,22,22,21,21,20,20,19,19,17,18,18,18,18,17,16,15,12,12,11,10,10,9,8,8,7,7,7,7,7,7,7,7,6,6,6,6,6,6,6,6,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,6,6,6,7,7,7,8,8,10,10,10,9,9,8,8,7,8,7,7,7,7,7,6,6,6,6,6,7,7,8,8,8,8,9,9,10,10,9,8,8,8,8,9,9,11,13,14,15,17,19,21,22,23,23,22,21,19,19,19,17,16,14,12,11,9,9,9,10,12,14,16,17,19,18,17,16,15,15,15,15,16,16,16,16,15,14,13,12,12,13,15,17,20,23,25,26,24,23,20,16,13,13,15,18,19,20,23,26,27,26,25,24,21,21,21,21,22,23,24,24,28,28,27,27,28,30,32,33,34,34,33,30,25,19,14,11,11,15,21,29,36,40,39,38,32,27,20,14,12,12,15,17,18,18,19,19,19,18,17,16,18,20,23,26,28,29,29,29,23,20,16,14,15,17,19,19,22,21,20,18,17,16,16,15,18,17,16,16,17,18,20,21,22,25,30,35,40,43,45,46,46,42,37,32,28,26,26,26,29,28,27,25,22,19,17,15,13,13,14,16,19,24,28,31,35,38,42,45,45,43,41,38,33,31,27,23,19,16,14,13,12,13,16,20,26,31,35,37,42,39,35,31,29,25,21,18,21,21,21,20,19,17,16,15,14,14,13,11,11,11,11,11,8,9,11,14,16,19,20,21,23,23,23,23,23,21,20,20,22,21,21,20,18,17,17,16,12,11,10,9,9,9,9,10,8,8,8,7,7,6,6,6,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,6,6,6,6,6,7,7,7,8,8,8,10,10,10,9,9,9,8,8,8,8,8,7,7,7,7,6,6,6,7,7,7,8,8,8,9,9,10,10,10,9,9,8,9,9,9,10,11,13,14,15,17,18,20,22,23,23,22,21,20,20,19,18,17,15,13,12,9,9,10,11,12,14,16,17,18,18,16,15,15,14,14,15,16,17,17,17,16,15,14,14,14,14,16,18,21,23,25,26,25,24,21,17,13,13,16,19,21,23,26,29,30,29,27,26,22,22,22,22,22,23,24,25,27,27,26,26,27,29,31,32,34,34,33,30,26,20,15,12,12,15,22,30,38,42,42,41,34,30,22,16,12,12,15,17,18,19,19,20,19,18,17,16,17,19,22,25,27,28,28,28,22,19,15,14,16,18,20,20,22,21,20,18,16,15,15,15,17,17,16,16,18,19,21,22,23,25,29,34,39,42,44,45,44,41,37,32,29,27,27,28,31,30,29,27,24,21,18,17,14,15,15,17,21,26,30,33,38,40,43,45,45,43,40,38,34,32,28,23,19,15,13,12,13,15,18,23,28,33,37,39,42,39,34,31,29,26,22,19,22,22,22,21,20,18,17,16,15,14,13,12,11,11,11,11,9,10,12,14,17,19,21,22,23,23,23,23,23,22,21,20,22,21,21,19,18,17,16,16,12,11,10,9,9,9,9,10,8,8,8,7,7,7,6,6,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,6,6,6,6,7,7,7,8,8,8,9,9,11,11,10,10,10,9,9,9,9,9,9,8,8,7,7,7,6,7,7,7,8,8,8,8,9,9,10,11,11,10,10,9,9,9,9,10,11,13,14,15,17,18,20,22,23,22,22,21,21,21,20,19,17,15,14,12,9,10,10,11,13,15,17,18,18,18,16,15,14,14,14,14,17,17,18,18,18,17,16,16,17,17,19,20,22,24,25,25,25,24,22,18,14,14,17,19,25,27,30,33,34,33,30,29,23,23,22,22,23,23,24,25,26,25,24,24,25,26,28,29,33,33,33,30,27,22,17,14,13,17,23,33,41,46,48,47,40,35,27,19,14,13,14,16,18,19,20,21,20,19,17,16,16,18,22,25,27,27,27,26,20,18,15,15,17,20,21,22,23,21,19,17,16,15,14,14,17,17,17,18,19,21,23,24,24,26,29,33,37,40,42,43,43,40,36,33,30,29,30,30,33,32,31,29,26,23,20,18,15,16,17,20,23,28,32,35,40,42,44,46,46,43,40,38,35,32,28,22,18,14,12,11,14,17,21,27,32,37,40,42,41,38,34,31,29,27,24,22,23,23,23,22,21,19,18,17,16,15,13,12,11,11,11,11,10,11,13,15,18,20,22,22,22,23,23,23,23,22,21,21,22,21,20,19,18,17,16,15,12,11,10,9,9,9,9,10,8,8,8,8,7,7,7,6,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,6,6,6,7,7,8,8,8,8,9,9,9,10,11,11,11,11,11,10,10,10,10,10,10,9,8,8,7,7,7,7,7,8,8,8,9,9,9,10,11,11,12,11,11,11,10,10,10,10,11,13,14,15,17,18,20,21,22,22,21,21,22,21,21,20,18,16,14,13,10,10,11,12,14,16,17,19,19,18,17,15,14,14,13,13,17,18,19,19,20,19,19,18,20,21,21,22,24,25,25,26,27,26,23,19,15,15,18,21,27,30,33,36,37,35,32,30,23,22,22,21,22,22,23,23,24,23,22,22,22,24,26,27,32,32,32,30,27,23,18,16,15,18,25,36,45,52,55,55,48,42,33,23,17,14,14,15,19,20,21,22,22,20,18,16,15,18,22,25,27,27,25,24,19,16,15,15,18,21,23,23,23,21,20,17,16,15,14,14,17,17,18,19,21,22,24,25,26,27,30,33,37,40,42,43,42,40,37,35,33,32,33,33,34,34,32,29,26,23,20,18,15,16,18,21,25,30,33,36,40,41,44,46,46,45,43,41,36,32,27,22,17,13,12,11,15,18,23,30,35,39,41,42,40,37,33,30,29,27,25,24,24,24,24,23,22,21,19,18,16,16,14,13,11,11,11,11,12,12,14,16,18,20,22,23,22,23,23,24,24,23,22,22,22,21,20,19,17,16,15,14,12,11,10,9,9,9,9,10,9,9,8,8,8,7,7,7,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,7,7,7,8,9,9,9,10,10,10,10,11,11,11,11,11,12,12,12,12,11,11,10,9,8,7,7,7,7,8,8,8,9,9,9,9,10,11,12,12,13,12,12,11,11,11,11,12,13,14,15,16,17,19,21,22,22,21,20,22,21,21,20,18,16,14,13,11,11,12,13,14,16,18,19,21,20,18,16,15,14,14,14,17,18,19,20,21,21,21,20,23,23,24,25,25,26,27,27,28,27,24,20,17,17,19,22,29,31,35,38,38,36,32,30,22,22,21,21,20,21,21,22,23,22,21,20,21,22,23,24,30,30,31,30,27,23,19,17,17,20,28,39,50,58,63,64,57,50,40,29,20,16,15,15,19,20,22,23,23,21,18,17,15,18,22,26,27,27,25,23,18,16,15,16,19,22,23,23,22,21,20,18,17,16,16,16,18,19,20,21,23,24,24,25,27,28,30,33,37,40,43,45,42,41,39,37,36,36,36,36,35,34,32,29,26,22,19,17,15,17,19,23,27,31,35,37,39,40,43,45,46,45,44,44,35,32,26,20,16,13,12,12,16,20,26,32,37,40,41,41,38,35,31,28,27,27,26,25,25,25,24,24,23,21,19,18,17,16,15,13,12,11,11,11,12,13,14,16,18,20,21,22,22,23,23,24,24,24,23,23,22,22,20,19,17,15,14,13,12,11,10,9,9,9,9,10,9,9,9,8,8,8,7,7,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,6,6,6,6,7,7,7,8,9,9,10,10,10,11,11,11,11,11,12,12,12,13,13,13,13,13,12,11,10,9,8,7,8,8,8,8,9,9,9,10,10,10,11,13,13,14,13,13,12,12,12,12,12,13,14,15,16,17,19,21,21,21,20,20,21,21,20,19,17,15,14,12,12,12,12,14,15,17,19,20,22,21,20,18,16,15,15,15,16,17,18,20,21,22,22,22,24,25,25,26,27,28,29,30,29,28,25,21,18,18,20,23,30,33,37,40,40,37,33,30,24,23,22,21,21,21,22,22,23,22,20,19,20,21,22,23,27,28,29,28,26,23,20,18,18,22,30,42,54,64,70,72,66,59,47,34,24,18,16,15,19,21,23,25,24,22,19,17,16,19,23,27,28,27,25,23,18,17,16,17,20,23,23,23,22,21,20,19,19,19,19,19,20,21,22,23,24,24,24,24,26,27,29,32,36,40,43,45,45,44,42,41,40,39,39,39,36,35,33,30,27,23,19,18,17,18,22,26,30,34,37,39,39,40,42,44,44,44,44,43,34,30,25,19,15,13,13,14,19,23,29,35,40,41,40,40,36,32,28,26,26,26,26,26,24,24,24,23,22,21,19,18,18,17,15,14,12,11,11,10,12,13,14,16,17,19,20,21,22,23,23,24,25,24,24,24,22,22,20,18,16,15,13,12,12,11,10,9,9,9,9,10,10,9,9,9,8,8,8,8,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,6,6,6,7,7,7,8,8,10,10,10,11,11,11,12,12,12,12,12,13,13,13,14,14,14,14,13,11,10,9,8,7,8,8,8,9,9,9,10,10,10,11,12,13,14,14,14,14,13,12,12,12,12,13,14,15,15,17,19,20,21,21,20,20,20,20,19,18,17,15,13,12,12,13,13,14,16,18,20,21,24,23,21,19,18,16,16,16,15,16,18,19,21,22,22,22,25,25,26,28,29,30,31,32,30,29,26,22,19,19,21,24,31,34,39,42,42,39,34,31,26,25,24,24,23,23,23,24,23,22,20,19,19,20,21,22,25,26,27,27,25,23,20,18,20,23,32,44,58,69,75,78,73,66,53,39,28,21,17,16,19,21,24,26,25,23,19,17,17,20,25,28,30,28,25,23,19,17,17,18,21,23,23,22,21,21,20,20,21,22,22,23,22,23,24,25,25,24,23,23,22,23,25,28,33,38,42,44,47,47,46,44,43,42,41,41,38,37,35,32,28,24,21,19,19,21,25,30,34,38,41,43,42,42,43,43,42,41,40,39,32,29,23,18,15,14,14,15,23,27,33,40,43,43,41,39,33,30,26,23,24,25,26,26,24,24,24,23,22,20,18,17,19,18,16,14,12,11,11,10,12,12,13,15,16,18,19,20,22,23,24,24,25,25,25,24,22,22,20,18,16,14,13,12,12,11,10,9,9,9,9,10,10,10,9,9,9,8,8,8,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,6,6,6,7,7,8,8,8,10,10,11,11,11,12,12,12,12,12,12,13,13,14,14,15,15,14,13,12,10,9,8,8,8,8,8,9,9,10,10,10,10,11,12,13,14,15,15,15,13,13,12,12,12,13,14,14,15,17,18,20,21,21,20,19,19,19,19,17,16,14,12,11,13,13,13,14,16,18,20,21,26,24,22,20,18,17,17,16,14,15,17,19,21,22,22,22,25,26,27,28,30,32,33,33,30,29,27,22,19,19,22,24,33,36,41,44,44,40,35,32,28,28,27,26,25,25,25,26,23,22,21,19,19,20,21,22,23,24,25,26,25,22,19,17,20,24,33,45,59,71,78,81,78,70,56,42,30,22,18,17,19,21,24,26,26,23,20,17,18,21,26,29,31,29,25,23,19,18,18,19,21,23,22,21,21,21,21,21,22,23,25,25,23,24,25,26,26,24,23,22,19,20,22,26,31,36,41,43,49,49,48,46,45,43,42,42,40,39,37,34,30,26,23,21,22,24,28,33,38,41,44,45,45,45,44,43,41,38,36,35,31,28,22,17,14,14,15,17,26,30,37,43,45,45,42,40,32,28,24,22,23,25,26,26,23,23,23,22,21,19,18,17,19,18,16,14,12,11,11,10,11,12,13,14,16,17,18,19,22,22,24,25,25,25,25,25,23,22,20,18,16,14,12,11,12,11,10,9,9,9,9,10,10,10,10,9,9,8,8,8,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,6,7,7,8,9,9,11,11,11,11,11,11,11,11,13,13,14,15,15,16,17,17,14,14,14,14,13,12,11,10,10,9,9,8,8,9,9,10,11,12,14,15,16,17,17,17,17,16,14,13,12,12,13,14,17,17,17,17,17,17,17,17,17,16,16,15,14,13,12,12,14,13,13,14,17,21,25,27,26,26,25,24,22,19,17,16,14,16,17,17,17,18,21,24,24,27,30,33,35,35,35,34,36,32,27,23,21,21,23,24,31,34,39,43,44,43,39,37,32,31,30,28,27,27,27,27,25,24,21,20,19,20,22,23,23,24,26,26,25,22,20,18,18,24,34,46,57,67,74,78,78,70,58,44,31,23,18,16,14,18,22,26,27,24,21,18,21,23,26,31,33,32,27,23,21,20,20,21,24,24,23,21,23,23,24,25,26,27,28,28,28,27,27,27,27,26,23,20,18,18,20,23,27,33,38,41,48,47,46,45,44,42,41,41,43,42,39,36,32,29,26,24,24,28,34,40,45,47,48,47,46,43,39,37,36,35,33,31,34,21,14,15,13,7,11,21,28,34,42,48,50,47,41,37,30,27,23,22,24,26,28,28,23,23,22,21,20,20,19,18,20,19,17,14,12,11,10,10,13,13,13,14,15,17,18,19,20,22,25,27,27,26,23,21,20,19,17,15,13,12,12,11,11,11,11,11,11,11,11,11,10,10,10,9,9,8,8,8,7,7,7,6,6,5,5,5,6,5,5,4,4,5,5,6,5,5,5,4,4,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,6,7,7,8,9,9,11,11,11,11,11,11,11,11,13,13,14,15,16,16,17,17,15,15,15,15,14,13,11,10,10,10,9,8,8,9,10,10,11,12,14,15,17,17,17,17,18,17,15,14,13,13,13,14,16,16,16,16,16,16,16,16,16,15,15,14,13,12,12,11,13,13,13,15,18,22,26,28,28,28,26,24,22,19,17,15,14,16,17,17,17,18,21,23,25,28,31,34,36,37,36,36,35,32,28,24,21,22,23,25,31,35,39,43,45,44,41,39,35,34,32,30,30,29,30,30,27,26,24,22,21,22,23,24,24,25,26,26,25,23,21,19,19,23,31,41,52,62,69,73,72,66,55,43,32,23,17,15,15,17,21,24,25,23,20,18,21,23,27,32,34,33,28,24,20,20,20,22,25,26,25,24,25,25,26,27,28,29,30,31,30,29,29,30,30,29,25,22,17,17,18,20,25,31,37,41,46,45,44,43,42,42,42,41,44,42,40,37,33,29,26,25,25,29,34,40,44,47,47,47,44,41,38,35,34,33,31,28,25,19,19,26,26,17,15,21,32,37,45,50,51,46,40,35,30,27,23,22,24,26,28,28,24,23,23,22,21,20,19,19,19,18,16,14,12,11,10,10,12,12,12,13,14,16,17,19,21,22,25,27,27,25,23,21,20,19,17,15,13,12,11,11,11,11,11,11,11,11,11,11,10,10,9,9,9,8,8,8,7,7,7,6,6,5,5,5,6,5,5,4,4,5,5,6,5,5,5,4,4,4,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,6,7,7,8,9,9,11,11,11,11,11,12,12,12,13,14,14,15,16,17,17,17,15,16,16,15,15,13,12,11,11,10,9,9,9,9,10,11,12,13,14,16,17,18,18,18,19,18,17,15,14,14,14,14,15,15,15,15,15,15,15,15,14,14,14,13,12,11,11,11,12,12,13,16,19,24,28,30,31,30,28,25,22,18,16,15,14,16,17,17,17,18,20,22,27,29,32,36,38,39,38,37,35,32,28,24,22,23,24,25,32,35,39,44,45,45,42,41,37,36,34,33,32,32,33,34,30,29,28,26,25,25,25,25,25,26,26,27,26,24,22,21,20,23,28,35,44,53,61,65,64,60,52,43,33,24,18,14,16,18,20,22,22,21,19,17,21,23,27,33,36,34,30,25,20,19,20,22,26,29,29,29,28,28,29,30,32,33,34,34,32,32,32,34,34,31,27,23,16,16,16,17,22,28,35,39,42,41,41,40,40,41,41,42,44,43,41,38,34,30,27,25,26,29,34,39,43,45,46,46,42,39,35,33,31,29,27,25,19,16,19,28,29,23,21,25,37,42,49,53,52,46,38,32,29,27,24,23,25,27,27,26,24,23,23,22,21,21,20,20,18,17,15,13,12,11,11,10,12,11,11,11,12,14,16,18,21,22,24,26,26,24,22,20,19,18,16,14,13,12,11,11,11,11,11,11,11,11,11,11,10,9,9,9,8,8,8,8,7,7,6,6,6,6,5,5,6,6,5,5,5,5,6,6,5,5,5,5,4,4,4,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,6,7,7,8,9,9,11,11,11,12,12,12,12,13,14,14,15,15,16,17,18,18,17,17,17,17,16,15,13,12,11,11,10,10,10,10,11,11,12,13,15,17,18,19,20,20,20,20,19,17,16,15,15,15,14,14,14,14,14,14,14,14,13,13,13,12,12,11,11,11,12,12,14,17,21,26,29,31,33,32,29,25,21,18,15,14,14,16,17,17,16,17,19,22,27,29,33,37,39,40,40,39,35,33,29,26,24,24,25,26,32,34,39,43,45,44,43,42,37,36,34,33,33,34,36,37,34,33,33,32,31,29,28,28,27,28,28,28,27,26,24,23,23,24,26,30,36,44,51,55,55,53,50,44,36,28,20,16,18,19,20,21,21,19,18,17,18,21,27,33,36,35,30,25,19,19,20,23,28,31,33,33,31,32,33,35,36,37,39,39,33,33,34,35,35,32,26,22,16,15,14,15,20,26,33,37,38,37,37,37,38,39,41,42,44,44,42,39,36,31,28,25,27,29,33,37,41,42,43,43,39,36,32,29,28,26,23,21,21,15,13,16,19,20,25,33,41,46,52,55,53,47,38,32,29,27,25,25,26,27,26,25,23,23,22,22,21,21,20,20,17,16,15,13,12,12,12,12,11,10,9,9,11,13,16,17,21,22,24,25,24,23,21,20,18,17,15,13,12,11,11,11,10,10,10,10,10,10,10,10,9,9,9,8,8,8,7,7,6,6,6,6,6,6,6,6,7,6,5,5,5,5,6,7,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,6,7,7,8,9,9,11,11,11,12,12,13,13,14,14,14,15,16,17,17,18,18,18,18,18,18,17,16,15,14,12,12,11,11,11,11,12,12,12,13,15,17,19,20,21,21,22,22,21,20,18,17,16,15,14,14,14,14,14,14,14,14,13,12,12,12,12,11,11,11,12,13,16,19,23,27,30,32,34,32,28,24,20,17,15,14,15,16,17,16,16,16,18,21,26,29,32,36,39,40,40,39,34,33,30,27,26,25,26,27,31,34,37,41,42,42,41,40,35,34,32,32,33,36,39,41,39,39,40,40,39,37,35,34,33,33,32,32,30,29,28,27,28,27,26,27,31,37,42,46,48,48,48,45,40,32,25,20,20,21,22,22,22,20,18,17,16,20,26,33,36,35,30,25,19,19,19,23,28,33,36,36,35,35,36,38,40,42,43,43,36,35,35,34,33,30,24,20,15,15,14,16,20,26,32,35,34,34,33,33,34,37,39,41,44,43,42,40,36,32,27,25,26,28,31,34,36,38,39,39,36,33,29,26,25,23,21,19,21,16,12,12,15,21,30,38,46,49,54,56,53,46,38,32,28,27,26,26,27,27,25,23,21,21,21,21,21,20,20,20,17,16,15,14,13,13,13,14,11,10,9,8,10,12,15,18,22,22,23,23,23,21,20,19,16,15,14,12,11,11,11,11,10,10,10,10,10,10,10,10,9,9,8,8,8,7,7,7,6,6,6,6,6,6,6,6,7,7,6,5,5,6,7,7,6,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,6,7,7,8,9,9,11,11,12,12,13,14,14,14,15,15,15,16,17,18,18,19,19,19,19,19,18,17,16,15,13,13,12,11,11,12,13,13,12,14,16,18,20,21,22,22,23,23,23,22,20,18,17,16,14,14,14,14,14,14,14,14,13,13,13,13,12,12,12,12,14,15,18,21,25,28,30,32,33,31,27,22,18,16,14,14,15,16,17,16,15,15,18,20,24,26,30,34,37,38,38,38,34,33,30,28,27,27,27,27,30,32,35,37,39,38,37,36,32,31,30,30,33,37,42,45,46,47,49,50,50,48,46,44,43,42,40,39,36,35,33,32,32,31,29,28,29,32,35,38,41,43,44,44,41,35,28,24,23,24,25,26,25,22,19,18,15,19,26,34,38,37,32,27,19,18,19,22,28,33,36,38,37,38,39,41,43,45,46,47,40,38,35,33,31,27,22,18,15,15,16,18,22,27,32,34,32,31,30,30,31,34,37,39,42,42,42,40,36,31,26,24,24,25,27,29,31,32,33,33,32,30,26,24,23,22,20,18,19,18,19,21,26,32,38,42,53,54,56,55,50,43,36,31,27,27,26,27,28,27,24,21,19,19,19,19,19,19,19,19,17,16,16,15,15,15,16,16,12,11,9,8,9,12,16,18,22,22,22,22,21,20,19,18,15,14,13,11,11,10,10,10,9,9,9,9,9,9,9,9,8,8,8,8,7,7,7,6,5,5,6,6,6,6,7,7,7,7,6,6,6,6,7,7,7,6,6,6,5,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,6,7,7,8,9,9,11,11,12,12,13,14,15,15,15,15,16,16,17,18,19,19,20,20,20,20,19,18,17,16,14,13,12,12,12,12,13,14,13,14,16,18,21,22,23,23,25,25,25,24,22,20,17,16,15,15,15,15,15,15,15,15,13,13,13,13,14,14,14,14,15,17,20,23,26,28,30,31,32,29,25,20,17,15,14,14,15,16,17,16,15,15,17,19,21,24,28,32,35,36,36,36,34,33,31,29,28,28,28,28,29,31,33,34,35,34,33,32,30,29,29,30,34,40,46,50,54,56,59,62,62,60,58,56,54,53,50,47,44,42,40,39,37,35,33,31,30,30,31,32,35,37,40,41,40,35,30,26,25,27,29,30,29,25,21,18,17,21,29,37,41,40,34,30,19,18,18,21,27,33,36,38,38,39,40,42,45,47,48,49,45,42,37,32,29,25,21,17,15,16,19,22,25,29,32,34,31,30,28,27,28,31,34,37,41,41,41,39,36,30,25,22,21,22,23,25,26,27,28,28,30,27,24,23,22,22,20,19,19,21,24,28,35,43,49,52,61,61,58,54,47,39,31,27,27,27,27,28,29,27,23,20,18,18,18,18,18,18,18,18,18,17,17,16,17,17,18,18,13,12,9,8,9,13,17,20,22,22,22,21,20,19,18,18,14,13,12,11,10,10,10,10,9,9,9,9,9,9,9,9,8,8,8,7,7,7,6,6,5,5,5,6,6,7,7,7,8,7,7,6,6,7,7,8,7,7,6,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,6,7,7,8,9,9,11,11,12,13,14,14,15,16,15,15,16,17,17,18,19,19,20,21,21,20,20,18,17,16,14,13,13,12,12,13,13,14,13,14,16,19,21,23,23,24,25,25,25,25,23,20,18,16,15,15,15,15,15,15,15,15,14,14,14,14,14,14,14,15,17,18,21,24,26,28,29,30,30,28,23,19,16,14,14,14,15,16,17,16,14,15,17,19,20,22,26,31,34,35,35,35,34,33,31,30,29,28,28,28,29,30,31,32,32,31,30,29,29,29,29,31,35,42,49,53,59,62,66,69,70,68,65,63,62,60,57,53,50,47,45,44,39,38,35,33,31,30,30,30,31,34,37,39,38,35,30,27,26,29,32,33,32,27,22,18,18,23,31,39,44,43,37,32,20,18,18,21,26,32,36,37,39,39,41,43,45,47,49,50,49,45,38,32,28,24,21,18,15,17,21,24,28,31,33,33,31,29,27,26,27,30,33,35,40,40,40,39,35,30,25,21,19,20,21,22,23,24,25,25,28,26,23,22,22,22,21,19,22,23,24,27,35,48,58,63,68,65,60,53,44,35,27,23,26,26,27,29,29,27,23,19,16,16,17,17,17,17,17,17,18,18,17,17,18,18,19,20,14,12,10,8,10,13,17,20,22,22,21,20,19,19,18,17,13,13,12,10,10,10,10,10,9,9,9,9,9,9,9,9,8,8,8,7,7,6,6,6,5,5,5,6,6,7,7,7,8,7,7,6,6,7,7,8,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,5,5,5,5,5,5,5,5,6,5,5,5,5,6,7,8,10,10,11,12,14,15,16,16,14,15,16,16,17,18,19,19,20,20,20,20,20,19,17,17,14,14,13,13,13,14,14,15,15,16,17,19,21,22,24,24,25,26,27,27,26,23,20,18,17,16,15,14,14,14,14,15,16,16,15,15,15,15,16,16,19,19,21,23,25,28,31,32,31,28,24,22,20,19,17,15,18,18,17,16,15,15,14,14,14,17,22,26,28,31,34,37,37,35,32,31,30,29,27,26,31,32,33,31,28,26,25,25,22,26,31,34,37,42,49,55,62,71,78,80,81,83,81,77,75,71,65,60,57,54,51,49,45,41,36,32,30,28,26,24,29,30,32,33,34,34,33,32,33,34,36,37,37,33,27,22,20,23,30,41,50,51,43,35,27,21,16,17,25,32,35,34,38,39,39,40,43,48,54,58,51,47,42,35,28,23,19,17,19,21,25,29,31,32,32,32,28,27,25,24,24,27,30,32,38,38,39,38,35,30,25,22,18,18,17,16,17,18,20,21,25,27,28,27,25,24,24,24,25,25,28,36,47,59,67,71,77,72,65,54,43,33,25,21,26,29,31,31,28,24,21,20,15,15,16,17,17,18,19,19,18,19,21,23,24,24,23,22,16,14,11,10,11,15,19,22,24,24,23,22,20,17,15,14,15,14,12,11,9,9,9,9,9,9,9,9,9,9,9,9,8,8,8,7,7,6,6,6,5,6,7,8,8,8,7,7,9,9,8,7,6,6,5,4,7,7,7,7,7,7,7,7,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,5,5,5,5,5,5,5,5,6,6,5,5,6,6,7,8,10,10,11,12,14,15,16,16,15,15,16,17,18,18,19,19,19,20,20,20,19,19,18,17,16,15,15,14,14,14,15,15,16,17,18,19,21,23,24,25,25,26,27,27,26,23,20,19,18,17,16,15,15,15,15,16,18,18,18,17,17,18,18,18,19,20,22,24,28,31,33,35,33,30,25,22,21,19,16,14,17,18,18,18,17,16,15,14,14,17,21,24,26,30,34,37,38,36,32,30,29,28,27,27,32,33,34,32,29,26,24,24,21,25,29,32,35,40,48,55,65,75,84,88,90,92,90,86,83,78,72,66,61,57,53,50,44,41,36,33,31,29,26,24,28,29,31,33,34,34,33,33,35,37,39,41,41,36,28,22,20,23,31,42,52,54,47,39,30,23,17,18,25,32,35,35,36,37,38,40,44,50,57,61,55,51,45,37,30,24,20,18,19,22,27,31,34,34,33,32,28,26,23,22,23,26,30,33,37,38,38,37,34,29,24,21,18,17,16,16,16,18,20,21,25,27,29,29,27,27,27,28,31,32,36,44,56,68,76,81,81,75,65,53,41,31,24,20,25,28,30,30,26,22,20,19,15,15,16,17,18,18,19,19,19,20,22,24,25,25,24,23,18,16,14,12,13,17,20,23,25,24,23,22,20,18,15,14,15,14,13,11,10,9,9,9,9,9,9,9,9,9,9,9,8,8,8,7,7,6,6,6,5,6,7,8,8,8,8,7,10,9,9,8,7,6,5,5,7,7,7,7,7,7,7,7,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,5,5,6,7,8,8,10,10,11,12,14,15,16,16,16,16,16,17,18,18,19,19,19,19,19,20,19,18,18,17,18,17,16,15,15,15,15,15,17,17,19,20,22,23,24,25,25,26,26,26,25,23,21,19,20,19,18,17,17,17,17,17,21,21,21,21,21,21,21,21,20,21,24,27,30,34,36,38,37,33,27,23,21,18,16,13,16,17,18,19,19,18,16,15,15,16,18,20,23,27,33,37,38,36,33,29,27,26,27,28,32,34,35,33,29,25,24,23,22,26,29,31,34,40,49,56,67,78,90,96,100,103,101,97,94,89,81,74,67,61,55,51,43,40,36,33,32,30,28,26,27,28,30,32,33,34,35,35,39,41,44,47,46,39,30,22,21,24,32,44,55,58,52,46,33,26,18,18,24,31,35,35,32,33,35,40,46,55,62,67,61,57,49,40,31,25,21,19,21,25,30,35,38,37,35,33,26,24,21,20,21,25,30,34,37,37,37,35,32,27,23,20,16,16,15,15,16,18,20,21,25,27,30,31,31,32,33,35,37,39,43,53,66,78,87,91,88,80,66,51,38,28,22,19,23,26,28,27,24,20,18,17,15,16,16,17,18,19,19,19,21,22,24,26,26,26,25,25,21,19,17,15,16,18,22,24,25,24,24,22,20,18,16,14,15,15,14,13,12,10,10,9,8,8,8,8,8,8,8,8,8,8,7,7,7,7,6,6,6,7,8,8,9,9,8,8,10,9,9,8,7,7,6,6,7,7,7,7,7,7,7,7,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,6,6,6,6,6,6,6,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,6,6,6,6,7,8,9,10,10,11,12,14,15,16,16,16,17,17,18,18,19,19,19,18,18,19,19,19,18,18,17,20,19,18,16,16,16,16,16,18,19,20,21,22,24,24,25,25,26,26,26,25,23,22,20,21,21,20,19,19,19,19,19,22,22,23,23,23,23,22,22,20,21,25,29,33,36,38,40,40,35,29,24,20,18,15,13,15,16,18,20,20,20,18,17,16,17,17,17,19,24,31,36,38,37,33,29,26,25,26,28,33,34,35,34,30,26,24,23,25,28,31,33,35,41,50,57,65,77,91,100,106,110,109,105,103,98,89,80,72,63,55,50,42,40,37,35,34,33,30,28,27,28,30,32,34,35,36,37,41,44,49,52,51,43,32,23,21,24,32,45,57,61,57,51,35,27,18,17,23,30,33,33,29,30,33,39,49,60,68,72,66,61,51,40,31,24,21,19,23,27,33,39,41,39,36,34,25,23,20,18,20,24,30,33,35,35,35,33,29,25,21,19,15,15,15,15,17,19,21,23,25,28,32,35,36,38,40,42,41,43,49,59,72,85,94,98,95,85,68,50,35,26,21,20,22,24,25,24,21,18,16,16,16,16,17,17,18,19,20,20,22,23,25,27,28,28,27,26,22,21,18,17,17,19,22,23,25,25,24,23,21,18,16,15,16,16,15,14,13,12,11,10,8,8,8,8,8,8,8,8,7,7,7,7,7,7,7,7,7,7,8,9,10,10,9,9,10,10,9,9,8,8,7,7,7,7,7,7,7,7,7,7,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,6,6,6,6,6,6,6,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,6,6,7,7,8,9,10,10,11,12,14,15,16,16,17,18,18,18,18,19,19,19,17,17,18,19,19,18,18,17,19,19,18,17,16,16,17,17,20,20,21,22,23,24,25,25,25,25,25,25,24,23,22,22,23,22,21,20,20,20,20,21,22,23,24,25,25,24,23,22,21,23,26,31,35,38,40,40,42,37,29,23,19,17,14,12,14,15,17,19,20,20,20,20,18,18,17,16,17,22,29,34,37,37,34,30,25,23,25,27,32,34,36,35,31,27,24,23,25,28,31,33,34,39,48,54,63,76,91,102,109,115,116,112,108,103,94,84,74,64,54,48,42,40,38,37,37,36,33,31,29,30,31,32,34,36,38,39,43,47,52,56,54,46,34,25,21,24,31,44,57,61,58,52,34,26,19,17,23,29,32,32,28,28,31,39,52,64,72,76,69,62,51,39,29,23,20,18,24,28,34,40,41,40,36,34,25,23,20,18,20,24,28,32,33,33,32,30,27,23,20,18,15,15,15,16,18,20,23,25,27,30,35,39,41,44,47,50,47,49,55,65,78,90,98,102,99,88,69,49,34,24,21,20,21,22,23,22,19,16,15,15,16,16,17,18,19,19,20,20,23,24,26,28,29,28,28,27,23,21,20,18,18,19,21,22,26,25,25,23,21,19,16,15,17,17,17,16,15,13,12,10,8,8,8,8,8,8,8,8,7,7,7,7,7,7,7,7,8,8,9,10,10,10,10,10,10,10,10,10,9,9,9,9,7,7,7,7,7,7,7,7,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,7,7,7,7,7,8,9,9,10,10,11,12,14,15,16,16,18,18,18,19,19,19,19,19,16,16,17,18,18,18,18,17,18,17,17,16,16,17,18,18,21,21,22,23,24,24,25,25,25,25,25,24,24,23,23,23,23,22,22,21,20,20,21,21,24,25,26,27,27,26,25,24,24,26,30,34,38,40,41,42,42,36,28,22,18,16,13,12,13,14,15,16,18,20,21,22,21,20,19,17,17,20,26,30,35,36,36,32,26,22,23,25,30,33,36,36,32,28,26,24,24,28,31,33,34,37,43,48,61,74,89,100,110,117,119,117,110,104,96,86,75,64,54,47,42,41,40,40,41,40,37,35,32,32,33,34,35,37,39,40,44,47,52,56,55,47,36,28,21,23,30,42,54,58,55,49,33,26,20,20,26,31,33,31,28,28,30,40,53,66,75,78,71,64,51,38,28,22,19,19,25,28,34,38,40,39,36,34,25,24,22,20,21,24,27,29,30,29,28,27,25,22,20,19,16,15,16,17,19,22,25,27,29,33,38,43,46,49,53,56,55,57,63,73,85,95,102,105,98,86,67,47,31,23,20,20,20,22,22,21,17,15,14,14,17,17,17,18,19,20,20,21,23,24,26,28,29,29,28,27,24,23,21,20,19,20,20,21,26,26,25,23,21,19,17,16,17,18,18,18,17,15,12,11,9,9,9,9,9,9,9,9,6,6,7,7,7,7,8,8,8,9,10,11,11,11,11,10,10,10,10,10,10,10,10,10,7,7,7,7,7,7,7,7,6,6,6,6,6,6,6,6,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,8,8,8,8,8,8,8,8,9,9,9,9,9,9,9,9,8,7,7,7,7,8,9,10,10,10,11,12,14,15,16,16,19,19,19,19,19,19,19,19,15,16,17,18,18,18,18,18,15,15,15,15,16,17,18,19,22,22,23,23,24,25,25,26,25,25,24,24,23,23,23,24,23,22,21,21,20,20,21,21,26,27,29,30,30,29,27,26,29,31,35,39,42,44,44,44,41,35,27,21,17,15,13,12,13,12,12,13,16,19,22,24,23,23,21,19,18,19,23,27,32,36,37,34,27,22,22,23,28,32,35,36,33,30,27,26,27,31,36,38,37,38,42,46,56,69,84,95,105,114,118,116,110,105,96,87,76,65,55,48,43,42,42,43,44,43,40,38,36,36,35,35,36,38,40,41,43,46,51,54,54,47,37,30,21,22,28,39,50,54,50,45,33,27,23,24,30,35,35,33,30,29,31,40,55,68,75,78,73,65,52,38,28,22,21,21,25,28,32,35,37,36,35,33,26,25,24,23,23,24,25,26,26,26,25,25,23,22,21,20,16,16,17,18,21,24,28,29,32,36,41,46,49,53,57,60,60,62,68,77,88,97,103,105,93,82,63,43,28,20,18,18,21,22,22,20,17,14,14,15,17,17,18,18,19,20,21,21,23,24,26,28,28,28,27,27,27,26,24,23,22,21,22,22,26,26,25,24,22,19,17,16,18,18,19,19,18,16,13,11,10,10,10,10,10,10,10,10,6,6,6,7,7,8,8,8,9,10,10,11,12,12,11,11,11,11,11,11,11,11,11,11,7,7,7,7,7,7,7,7,6,6,6,6,6,6,6,6,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,8,8,8,8,8,8,8,8,9,9,9,9,9,9,9,9,8,7,7,7,7,8,9,10,10,10,11,12,14,15,16,16,19,19,19,19,19,19,19,19,15,15,16,18,18,18,18,18,14,14,14,14,16,17,19,20,22,23,23,24,24,25,26,26,25,25,24,23,23,23,24,24,23,22,21,20,20,20,20,21,28,29,31,33,33,31,29,28,32,35,39,43,45,46,46,46,40,34,26,20,16,14,13,12,13,12,11,11,14,18,23,26,24,24,23,21,19,19,22,24,31,35,38,35,28,22,21,22,27,31,35,36,34,31,28,27,32,36,42,43,43,42,45,48,51,63,78,88,99,109,113,113,110,105,97,88,77,66,56,49,44,43,43,44,46,45,42,40,38,38,37,36,37,38,40,41,43,45,50,53,53,47,38,31,20,22,27,37,47,51,47,41,33,28,25,27,34,38,37,35,31,29,31,40,55,68,76,78,74,66,53,39,29,23,22,23,26,28,31,33,35,35,34,33,26,26,26,25,25,25,24,24,25,24,24,23,22,22,21,21,17,17,18,19,22,26,29,31,34,37,43,47,51,55,59,62,62,64,69,77,87,96,101,102,89,78,59,40,26,18,16,16,21,22,22,20,16,14,14,15,17,17,18,19,19,20,21,21,22,23,25,27,28,28,27,26,29,28,26,25,24,23,23,23,26,26,25,24,22,19,17,16,18,19,20,20,19,16,13,12,11,11,11,11,11,11,11,11,6,6,6,7,7,8,8,8,9,10,11,12,12,12,12,11,11,11,11,11,11,11,11,11,7,7,7,7,7,7,7,7,6,6,6,6,6,6,6,6,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,4,4,4,5,5,6,6,6,5,5,5,6,6,7,7,7,7,7,7,8,8,9,9,9,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,12,12,13,14,15,16,16,17,19,19,18,18,18,18,17,17,16,16,15,15,15,15,14,14,16,16,16,17,18,20,21,22,24,25,26,27,28,29,28,28,26,25,24,23,23,23,23,24,24,23,22,19,17,18,21,25,27,32,35,35,35,37,35,30,35,37,41,46,50,50,47,44,38,33,25,17,13,12,13,15,14,15,15,14,13,15,19,22,28,28,27,25,21,19,19,20,30,35,38,36,28,22,21,21,23,27,32,34,32,29,27,26,32,39,48,53,52,48,44,43,49,55,66,80,93,103,107,107,108,104,96,86,74,64,56,52,47,47,46,46,45,44,44,44,40,40,40,40,40,39,38,37,40,42,46,50,51,47,39,33,20,20,23,31,40,46,47,45,33,31,31,36,43,46,44,40,34,31,30,37,50,66,77,83,78,69,57,45,36,30,25,23,25,26,29,31,32,33,33,32,31,30,28,26,26,26,27,28,22,22,23,23,23,23,23,23,20,20,21,23,25,28,30,32,34,36,40,45,50,54,57,58,62,63,67,74,82,89,93,94,82,69,50,33,22,18,17,18,20,19,17,15,15,15,16,17,18,19,21,20,19,19,21,23,21,23,26,26,25,25,26,27,28,28,29,29,28,27,26,25,27,27,27,24,21,19,18,19,18,18,19,19,18,16,14,13,11,11,11,12,12,13,13,13,9,9,9,9,9,8,8,8,10,11,12,13,14,13,12,11,9,9,9,10,10,11,11,11,9,8,7,6,6,6,6,7,7,7,6,6,6,5,5,5,6,6,6,5,5,4,4,4,5,5,5,5,5,5,5,5,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,4,4,4,5,5,6,6,6,5,5,6,6,6,7,7,7,7,7,8,8,8,9,9,9,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,11,12,12,13,14,15,15,16,18,18,18,18,18,18,18,18,16,16,15,15,15,14,14,14,15,15,15,16,17,19,20,21,24,25,26,27,28,29,28,28,26,25,24,24,23,23,24,24,23,22,21,18,17,18,21,24,30,35,39,39,40,42,39,35,37,39,42,46,50,50,48,46,40,35,27,20,15,14,15,17,17,17,16,15,14,16,20,23,30,31,31,28,25,23,22,23,30,34,38,36,29,23,22,23,25,28,32,34,33,31,30,30,38,46,55,61,60,56,52,50,48,51,59,70,82,91,96,98,102,98,91,81,71,61,54,50,47,46,45,44,43,42,42,41,40,40,40,40,40,39,38,37,37,41,46,51,53,49,41,35,24,23,24,30,38,43,45,44,38,36,37,42,49,51,49,45,35,32,31,37,51,66,77,82,79,71,60,48,40,33,28,25,27,28,29,31,32,33,33,33,33,33,31,30,29,29,28,28,23,23,23,24,24,25,25,26,22,22,23,24,26,28,29,30,33,35,38,43,47,50,53,54,56,58,62,70,78,83,86,86,74,62,45,29,20,16,16,17,20,19,17,16,16,16,17,18,19,20,21,20,19,18,20,21,23,25,27,27,26,26,27,28,30,31,32,32,32,31,29,28,28,28,27,25,22,20,20,20,19,19,19,19,18,16,14,13,11,11,11,12,12,12,13,13,11,10,10,10,9,9,9,9,10,11,12,13,13,13,12,11,9,9,9,10,10,11,11,11,9,8,7,7,6,6,7,7,7,7,7,6,6,6,5,5,6,6,6,5,5,5,4,4,5,5,5,5,5,5,5,5,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,4,4,4,5,5,6,6,6,5,6,6,6,7,7,7,7,7,8,8,8,9,9,9,9,10,10,10,10,10,11,11,11,11,11,11,11,11,11,11,11,11,11,11,12,13,14,14,14,18,18,18,18,18,18,18,18,16,16,15,15,14,14,14,13,14,14,14,15,16,18,20,20,24,25,26,27,28,29,28,28,26,26,25,24,23,23,24,24,21,21,20,18,17,18,21,24,33,39,43,44,46,48,46,41,40,40,42,46,49,51,49,48,42,38,30,23,19,18,19,20,21,20,18,15,14,15,20,24,32,33,35,34,31,28,27,27,31,35,37,35,30,25,24,24,26,29,33,34,34,33,33,34,42,50,61,69,70,66,61,57,49,50,52,58,67,76,82,85,90,87,80,73,64,56,50,47,45,44,43,41,40,39,38,38,39,39,40,40,39,38,37,37,34,39,46,54,57,54,47,41,31,28,25,28,34,40,42,42,43,43,45,50,55,57,54,50,38,34,33,38,51,65,76,81,81,74,64,54,46,39,33,30,28,28,29,30,31,32,34,35,37,37,38,37,35,33,31,29,23,23,24,25,26,27,28,28,25,25,25,26,26,27,28,28,31,33,36,39,42,45,46,47,49,51,56,63,70,74,74,72,62,52,37,24,17,15,16,16,21,20,18,17,17,18,19,19,22,22,22,20,18,17,18,20,24,26,28,28,27,26,27,28,31,33,36,38,38,37,34,33,30,29,27,25,24,23,22,22,20,20,20,19,18,16,14,13,10,10,11,11,12,12,12,12,12,12,12,11,11,10,10,10,9,10,11,12,13,13,12,12,10,10,10,10,11,11,11,11,9,9,8,7,6,6,7,7,8,8,7,7,7,6,6,6,6,6,6,6,5,5,5,4,5,5,5,5,5,5,5,5,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,4,4,4,5,5,6,6,6,6,6,6,7,7,7,8,8,8,8,8,9,9,9,10,10,10,10,10,11,11,11,11,12,12,12,12,12,12,12,12,12,11,11,11,12,12,13,13,13,16,17,17,18,18,19,19,20,17,17,16,16,15,14,14,13,14,14,14,14,16,17,19,20,24,25,26,27,28,29,28,28,27,26,25,24,24,24,24,25,20,21,20,18,17,18,20,23,33,40,45,47,50,52,50,45,42,42,42,44,48,50,50,49,43,39,32,26,22,20,21,22,24,23,19,15,13,14,19,22,31,34,38,39,37,34,32,31,33,36,37,35,31,27,26,26,27,29,32,33,33,33,35,36,42,50,62,72,75,72,66,62,55,52,49,50,55,62,68,71,74,72,67,61,55,50,45,43,43,41,39,37,36,36,36,36,38,38,39,38,38,37,35,35,34,39,48,58,63,61,55,49,37,32,26,26,31,38,41,43,46,47,51,56,61,61,58,54,41,37,35,39,51,64,74,79,81,76,67,59,52,45,38,33,28,28,27,27,29,32,35,37,43,44,44,44,41,37,33,31,24,25,25,26,27,28,29,29,28,28,28,28,28,27,27,26,29,30,33,35,37,39,40,40,42,45,50,57,62,64,61,59,50,42,31,21,17,16,17,18,22,21,20,19,18,19,21,22,24,24,23,20,17,16,17,18,24,26,28,28,27,26,27,28,33,36,40,44,44,42,39,36,31,29,27,25,25,26,25,25,23,22,21,20,18,16,15,14,10,11,11,11,12,12,12,12,14,13,13,12,12,11,10,10,9,10,10,11,12,12,13,13,10,11,11,11,11,11,11,11,10,9,8,7,7,7,7,8,9,8,8,8,7,7,7,7,7,7,6,6,6,5,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,4,4,4,5,5,6,6,6,6,6,7,7,7,8,8,8,8,8,9,9,9,10,10,10,10,10,10,11,11,12,12,13,14,14,14,14,14,14,14,14,11,11,11,12,12,12,12,13,15,16,17,17,19,19,20,21,19,18,18,17,16,15,14,14,14,14,14,14,16,17,19,20,24,25,26,27,28,29,28,28,27,26,25,25,24,24,25,25,21,22,22,20,18,18,19,21,30,38,44,48,51,54,52,47,44,42,40,41,44,48,49,49,44,40,34,28,24,22,23,23,26,24,21,17,14,14,17,20,29,34,40,43,42,40,37,36,37,37,37,36,32,29,27,26,26,29,31,33,32,33,34,36,40,48,60,72,78,77,72,68,60,54,48,44,45,49,53,55,57,56,53,49,46,42,40,38,39,37,35,34,33,34,36,37,39,39,38,38,36,35,33,32,35,41,50,61,68,68,63,59,43,36,28,26,30,36,41,43,49,52,58,63,66,65,61,58,43,39,36,39,50,62,71,75,80,76,69,63,56,48,41,35,27,26,25,25,28,34,39,43,50,51,52,51,48,43,37,34,29,29,29,29,29,29,29,29,30,30,30,30,29,28,26,25,27,28,30,32,34,35,35,35,39,41,46,52,55,55,51,47,41,34,26,20,18,19,20,21,23,22,21,20,20,21,23,24,26,26,24,20,16,15,16,18,23,25,27,28,27,27,28,29,35,39,45,49,50,46,41,38,33,29,26,25,26,28,27,26,25,24,23,20,18,16,15,14,11,11,12,12,12,13,13,13,15,14,14,13,12,11,10,10,9,9,9,10,11,12,13,13,12,11,11,11,11,11,11,11,10,9,8,8,7,7,8,8,9,9,9,9,8,8,8,7,7,7,7,6,6,6,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,4,4,4,5,5,6,6,6,7,7,7,7,8,8,8,9,9,9,9,9,10,10,10,11,10,10,11,11,12,13,13,13,15,15,15,15,15,15,15,15,12,12,12,12,13,13,13,13,14,15,16,17,19,20,21,22,21,21,20,19,18,17,16,15,14,14,14,15,16,18,20,20,24,25,26,27,28,29,28,28,27,27,26,25,25,25,25,25,24,24,24,22,19,18,19,20,27,35,42,47,51,54,53,48,44,41,37,37,40,44,47,48,45,41,36,31,27,25,25,26,28,27,25,20,16,15,16,18,27,33,42,48,49,46,44,42,40,40,38,36,33,30,27,26,26,29,33,34,33,33,33,34,39,46,58,72,81,83,79,75,63,57,48,42,39,39,40,40,41,41,40,38,37,36,35,34,34,33,31,31,32,35,38,40,43,42,41,39,37,34,32,31,37,42,51,62,69,72,69,66,50,42,32,28,30,35,39,41,50,55,62,67,69,67,62,59,45,40,36,39,48,59,68,72,76,73,69,64,58,50,41,35,26,25,23,25,30,38,47,52,61,61,61,59,55,49,43,40,37,36,35,33,32,30,29,29,31,32,32,32,31,29,26,25,26,27,29,31,32,32,33,33,37,39,42,46,48,47,42,38,33,29,23,20,20,22,23,23,24,23,22,22,22,23,25,26,27,26,23,19,16,14,16,18,22,25,27,29,29,29,31,33,38,43,50,55,55,51,44,39,33,29,24,24,27,29,29,27,28,26,24,21,18,16,15,14,13,13,13,14,14,14,15,15,15,15,14,13,11,10,10,9,8,8,8,9,10,12,13,14,12,12,12,12,11,11,11,11,10,10,9,8,8,8,8,8,10,10,10,9,9,9,8,8,8,7,7,7,6,6,6,6,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,4,4,4,5,5,6,6,6,7,7,7,8,8,8,9,9,9,9,9,10,10,10,11,11,10,10,11,11,12,13,14,14,16,16,16,16,16,16,16,16,14,14,14,14,13,13,13,13,13,14,15,17,19,21,22,23,23,23,22,21,19,18,17,17,15,15,15,16,17,19,20,21,24,25,26,27,28,29,28,28,28,27,26,25,25,25,25,26,27,27,27,24,20,18,18,19,24,32,41,46,51,55,53,48,42,39,34,33,36,40,44,46,47,44,39,34,30,29,28,28,31,31,30,26,21,18,17,17,26,34,45,52,55,53,50,49,44,42,39,36,33,30,27,25,28,31,35,37,36,34,33,33,35,42,54,68,80,85,83,80,69,63,53,45,40,36,33,31,29,29,30,30,30,31,31,31,29,28,28,29,32,36,41,43,48,47,46,43,40,36,33,31,37,42,50,60,68,72,72,70,59,50,38,31,31,33,35,36,46,52,60,65,66,63,58,55,46,41,36,38,47,57,65,68,72,70,68,64,58,50,40,34,26,25,24,26,33,44,56,63,71,71,69,66,61,56,50,47,46,45,42,39,36,33,31,29,32,32,33,33,32,30,27,25,26,27,28,30,31,32,32,32,36,37,39,41,42,40,35,31,27,24,21,20,21,23,24,24,25,24,23,23,23,25,26,27,27,26,23,19,15,15,17,19,23,26,29,31,32,33,36,37,42,48,56,61,61,55,47,41,33,28,22,22,26,30,29,28,30,28,25,21,18,16,15,14,14,14,15,15,15,16,16,16,15,14,13,12,11,10,9,8,8,8,8,8,9,11,13,15,13,13,13,12,12,11,11,11,11,10,9,8,8,8,8,9,11,11,10,10,10,9,9,9,8,8,7,7,7,6,6,6,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,4,4,4,5,5,6,6,6,7,7,7,8,8,9,9,9,9,9,9,10,10,11,11,11,10,10,11,12,13,13,14,15,16,16,16,16,16,16,16,16,15,14,14,14,14,14,14,14,13,14,15,17,19,21,22,23,25,24,23,22,21,19,18,18,16,16,16,17,18,20,21,22,24,25,26,27,28,29,28,28,28,27,26,25,25,25,25,26,29,29,28,25,21,18,17,18,23,32,41,46,51,55,54,49,42,37,32,31,33,38,43,45,49,46,41,37,33,31,31,31,33,34,33,30,25,20,18,18,26,35,47,56,59,58,55,53,46,44,40,37,34,30,27,24,29,33,38,40,39,36,34,33,32,38,49,64,78,84,84,81,74,68,59,51,43,37,32,28,23,23,24,25,27,28,29,29,26,26,26,28,32,37,43,46,53,52,49,46,42,38,34,32,37,41,48,58,67,71,72,71,65,55,42,34,31,32,32,32,40,46,55,60,61,57,52,49,46,41,36,37,46,56,63,66,70,68,66,63,58,49,39,32,27,26,25,28,37,49,62,70,79,77,75,71,66,60,55,52,53,51,48,44,39,35,32,31,31,32,34,34,33,31,28,26,26,27,28,30,31,32,33,33,35,35,36,37,38,36,31,27,24,22,19,19,21,23,24,23,25,25,24,23,24,25,27,28,26,25,23,18,15,15,17,20,24,27,31,33,35,37,39,41,46,52,60,65,65,58,49,42,33,27,21,21,26,30,30,28,31,29,25,21,18,16,15,15,15,15,16,16,16,17,17,17,14,14,13,12,10,9,8,7,8,8,7,8,9,11,14,15,13,13,13,12,12,11,11,11,11,10,9,8,8,8,8,9,11,11,11,10,10,10,9,9,8,8,8,7,7,6,6,6,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,6,6,7,7,7,8,8,8,9,9,10,10,10,9,10,10,11,11,10,9,9,11,11,12,12,14,16,17,18,20,20,20,21,21,20,19,18,18,18,18,17,16,15,13,12,15,16,17,19,21,23,24,25,24,25,26,26,26,25,23,22,20,20,18,18,18,19,21,22,25,26,27,28,28,28,27,27,28,28,27,25,23,23,26,28,31,31,30,29,26,22,19,17,22,25,33,44,53,55,50,45,42,34,28,28,31,34,40,46,39,51,46,33,35,36,34,35,38,38,37,35,31,26,21,18,26,35,47,59,65,65,62,58,52,49,44,39,33,30,27,26,30,35,41,45,45,41,34,30,29,34,45,59,73,84,89,90,83,77,69,60,50,41,32,27,26,27,29,30,30,29,27,26,23,25,27,28,30,37,46,54,58,57,55,50,43,38,36,36,36,41,48,54,60,66,71,75,72,65,54,42,34,30,29,30,35,39,45,50,52,51,47,45,40,39,38,39,43,48,54,58,63,65,66,62,54,45,38,34,23,24,26,30,39,53,68,78,85,84,81,76,69,65,63,63,59,58,55,48,40,34,30,29,33,36,39,40,36,32,29,27,26,28,31,32,32,32,33,35,34,36,37,35,30,26,23,22,19,20,21,22,24,25,26,27,22,22,22,22,23,24,25,26,25,23,19,15,11,11,14,17,24,28,33,36,38,41,46,50,59,62,66,69,67,59,47,39,31,25,18,19,24,30,32,31,29,27,24,21,18,17,16,16,16,17,19,19,19,18,17,16,15,14,14,13,11,10,10,9,8,8,8,9,10,11,13,14,17,17,16,16,14,12,11,10,10,10,11,12,12,11,11,10,13,13,12,12,12,12,11,11,10,9,8,7,7,7,7,8,5,5,5,5,5,5,5,5,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,6,6,7,7,7,8,8,8,9,9,10,10,10,10,10,11,11,11,11,10,9,12,12,12,13,14,16,17,18,19,20,21,21,21,21,21,20,20,20,20,19,18,17,15,14,15,16,17,18,20,22,24,24,26,27,28,29,29,28,27,26,25,24,23,22,21,22,23,23,26,26,27,28,29,29,29,29,29,29,28,25,24,24,27,30,35,35,34,33,30,26,22,19,20,24,32,43,52,55,51,46,40,32,25,24,27,29,35,42,48,48,40,38,43,37,32,39,42,42,41,38,34,29,25,22,27,35,46,57,63,64,62,60,54,51,47,41,36,31,29,28,32,36,42,46,47,43,37,33,31,35,45,58,72,83,89,91,87,82,74,64,54,45,38,33,31,33,35,35,35,33,30,28,24,25,26,28,31,39,49,57,62,62,59,53,45,38,35,34,35,40,46,53,59,66,73,77,75,68,58,47,38,32,30,29,33,37,42,46,48,46,42,40,34,34,33,34,38,43,48,51,57,60,61,59,52,44,38,34,27,28,30,34,42,55,69,78,84,84,81,75,69,64,62,62,61,60,56,49,40,34,30,29,33,36,39,39,36,32,28,27,26,28,30,31,31,31,33,35,34,36,36,34,29,24,21,20,18,19,20,22,23,25,26,26,23,23,22,22,23,24,25,26,24,22,20,15,13,13,16,20,26,30,36,40,43,47,53,57,67,69,72,73,70,61,49,40,29,23,18,18,24,29,31,31,30,28,25,22,19,18,18,18,18,19,20,21,20,19,17,16,14,14,13,12,11,11,10,10,9,9,9,9,10,11,13,13,16,16,16,15,14,12,11,10,10,10,11,12,12,12,11,11,13,13,13,12,12,12,11,11,10,9,8,7,7,7,7,8,5,5,5,5,5,5,5,5,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,6,6,7,7,7,8,8,8,9,9,10,10,10,10,11,11,12,12,12,11,11,12,12,12,13,14,16,17,18,19,20,21,22,23,24,23,23,23,23,23,22,21,19,18,17,16,16,17,17,19,21,22,23,28,29,31,33,34,34,33,33,32,31,29,27,26,25,25,25,26,26,27,28,29,30,31,31,28,28,28,26,25,26,29,32,39,39,39,38,34,29,24,21,18,22,30,42,52,56,53,49,40,31,23,22,24,26,32,38,50,41,33,39,48,39,33,44,48,47,45,43,39,34,29,27,29,35,44,53,60,63,63,62,57,54,50,44,39,35,32,30,35,39,44,49,50,46,41,37,34,37,45,57,71,83,90,94,93,89,81,72,61,52,46,42,40,42,45,46,44,40,34,31,26,26,26,28,33,42,54,61,68,67,63,56,47,38,33,31,33,38,44,51,58,66,74,79,79,73,64,53,43,36,31,29,32,34,38,41,41,39,35,33,29,29,29,31,34,38,43,45,49,52,55,55,50,44,38,36,32,33,36,39,46,56,68,76,82,82,79,74,68,62,60,60,62,60,56,48,39,32,29,28,33,36,39,39,35,31,28,27,26,28,30,30,30,30,32,34,35,36,36,32,27,21,18,17,16,17,19,21,23,24,24,25,23,23,22,22,22,23,24,24,22,21,19,16,15,16,19,23,30,34,39,45,50,57,63,68,75,76,77,76,71,60,47,38,26,22,18,19,24,28,30,30,29,28,25,22,21,20,20,20,22,22,23,23,21,19,17,16,14,14,13,12,12,11,11,11,10,10,10,10,10,11,13,13,15,15,15,15,13,12,10,9,10,10,11,12,13,13,13,12,14,13,13,13,12,12,11,11,10,9,8,7,7,7,7,8,6,6,6,5,5,5,5,5,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,6,6,7,7,7,8,8,8,9,9,10,10,10,11,11,12,13,13,13,13,12,13,13,13,13,14,16,17,18,19,20,22,24,26,27,27,27,27,26,26,25,24,22,20,19,17,17,17,17,18,20,21,23,29,30,33,36,38,39,39,38,38,37,35,33,30,29,27,26,26,26,26,27,28,30,31,32,27,28,27,26,25,27,31,34,41,42,43,42,37,31,24,20,18,22,30,42,53,58,56,53,43,33,24,22,23,26,31,38,40,40,35,36,44,41,38,47,50,49,47,45,41,36,33,31,32,35,42,49,55,59,61,62,58,56,52,48,43,38,35,34,38,41,47,51,52,49,45,41,38,40,46,57,71,84,92,96,100,96,89,79,68,60,54,52,51,54,57,59,56,49,41,36,29,28,27,29,36,46,57,64,71,70,65,57,46,37,31,29,32,36,43,50,57,65,74,79,82,77,69,59,49,39,32,29,31,33,35,36,35,33,30,28,27,27,28,30,33,37,40,42,43,46,50,51,48,43,40,38,36,38,40,42,47,54,63,70,76,76,75,70,64,59,57,56,59,57,52,45,36,29,27,26,33,36,38,38,34,31,28,27,27,28,29,29,29,29,32,34,36,36,35,31,24,19,16,15,15,17,19,21,22,23,22,22,22,21,21,20,20,21,21,22,20,20,19,18,17,19,23,26,34,37,43,51,59,68,75,79,83,82,79,75,67,55,42,33,23,21,19,20,23,27,29,29,27,26,24,22,20,20,21,21,25,25,25,24,22,20,17,16,14,14,13,13,13,13,13,12,12,11,11,11,11,12,12,13,14,14,14,14,13,11,10,9,9,10,11,13,14,14,14,14,15,14,14,13,12,12,11,11,10,9,8,7,7,7,7,8,7,6,6,6,6,5,5,5,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,6,6,7,7,7,8,8,8,9,9,10,10,10,11,12,13,14,15,15,14,14,14,14,14,14,15,16,17,18,19,20,23,26,28,30,31,32,30,30,29,28,26,24,22,21,20,19,17,17,17,19,21,23,28,30,33,37,40,42,43,43,43,42,40,38,35,32,29,28,26,26,26,26,27,28,30,31,27,27,27,27,27,29,33,37,43,45,46,45,40,32,24,19,19,22,30,43,54,60,59,56,43,33,24,21,22,25,31,37,34,52,49,35,36,42,42,44,49,48,46,43,40,37,34,33,34,37,40,45,50,54,57,58,56,54,52,49,46,42,40,38,40,44,49,52,53,50,46,43,41,43,49,59,73,86,95,99,104,101,95,84,73,64,61,60,61,65,70,72,68,58,48,41,32,30,29,31,38,48,57,63,69,67,62,53,43,35,30,29,33,37,44,51,58,65,73,78,81,78,71,62,52,42,34,30,32,33,33,33,32,30,27,25,25,26,28,30,33,36,38,39,40,43,46,46,45,42,41,41,39,40,42,43,45,49,54,58,65,66,66,64,59,55,53,52,53,51,46,39,31,26,24,24,34,36,37,37,33,30,28,28,28,29,30,29,28,29,32,34,36,36,34,29,23,17,15,14,16,17,19,21,22,21,20,19,19,18,18,18,18,19,20,20,20,21,21,21,21,23,26,30,37,41,49,59,70,80,86,89,91,87,81,73,62,50,38,30,23,21,21,22,24,26,27,27,24,23,21,20,19,20,21,22,26,26,26,25,23,20,18,16,14,14,14,15,15,15,15,15,14,13,12,12,11,12,12,13,13,13,13,13,12,11,10,9,9,10,12,13,15,16,16,16,16,15,15,14,13,12,11,11,10,9,8,7,7,7,7,8,8,7,7,6,6,5,5,5,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,5,5,5,6,6,7,7,7,8,8,8,9,9,10,10,10,12,13,14,15,16,16,16,16,15,15,15,15,15,16,17,18,19,20,23,27,30,33,35,36,34,34,33,32,30,28,26,24,22,21,19,18,18,19,22,23,27,30,34,39,43,45,47,48,48,47,46,43,40,36,33,31,29,28,27,27,27,28,30,31,28,29,30,30,30,33,38,42,47,49,51,49,44,35,25,19,19,22,30,42,53,59,59,57,42,32,22,19,20,23,30,37,39,64,61,38,33,41,41,38,46,45,43,41,39,37,35,35,37,38,40,42,45,48,50,51,50,50,50,49,47,46,44,43,43,45,49,52,52,49,45,42,44,47,52,63,76,88,97,101,105,103,97,86,74,66,64,65,68,73,80,83,78,67,54,46,34,32,31,34,41,49,55,59,62,59,53,45,37,31,30,31,37,42,49,56,62,67,73,76,78,75,69,61,52,43,36,32,33,33,32,31,29,27,26,25,24,25,28,31,33,35,36,37,39,41,42,41,39,39,41,42,41,42,43,42,41,42,43,45,52,54,56,55,52,50,49,49,45,44,39,33,27,24,23,25,34,36,37,36,32,29,28,28,30,31,31,30,29,30,33,35,36,36,33,28,22,17,15,15,18,20,21,23,22,21,18,17,17,17,17,17,18,19,20,21,24,26,27,27,27,29,32,35,42,47,56,69,82,92,97,98,99,93,82,69,57,46,36,30,23,24,24,24,25,25,25,25,22,21,20,19,19,20,22,23,26,26,26,25,23,21,18,16,15,15,16,17,17,18,18,19,16,15,14,13,12,12,12,12,11,12,12,12,11,10,9,9,9,10,12,14,16,17,18,18,16,16,15,14,13,12,11,11,10,9,8,7,7,7,7,8,8,8,8,7,6,6,5,5,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,5,5,5,6,6,7,7,7,8,8,8,9,9,10,10,10,13,13,15,16,17,17,17,17,16,15,15,15,15,16,17,18,18,21,24,28,32,35,38,39,40,39,38,37,35,32,30,29,25,23,20,18,18,20,22,24,27,30,35,41,45,49,51,52,52,52,50,48,45,41,38,36,34,33,31,29,29,30,31,32,31,33,34,34,35,38,44,47,53,55,58,56,50,40,30,23,18,21,28,40,51,57,57,55,44,33,23,20,22,25,33,40,44,60,55,38,36,38,36,37,42,42,40,39,38,37,37,37,40,40,40,41,42,42,43,43,44,45,46,48,48,48,47,47,44,46,49,51,51,47,43,40,47,49,56,67,80,91,99,102,104,103,97,86,73,66,65,67,73,79,87,91,86,74,59,50,37,35,33,36,42,48,52,53,52,49,43,36,30,28,31,33,44,49,57,63,68,71,74,76,74,71,66,59,50,43,37,33,32,32,30,29,27,26,25,24,26,28,31,35,37,38,38,38,40,39,38,35,33,34,38,41,43,44,44,42,39,36,35,35,39,42,45,47,46,45,45,46,39,38,35,29,25,23,25,27,34,35,36,35,32,29,28,28,32,33,32,31,30,31,34,37,36,36,33,28,22,18,16,16,21,22,24,24,23,20,17,14,16,16,17,18,19,21,23,24,31,32,34,34,34,35,39,41,47,53,64,79,94,103,106,106,103,93,78,63,50,40,32,27,25,26,27,27,26,25,24,24,22,21,20,20,20,22,24,25,24,25,25,25,23,21,18,17,17,17,18,19,19,20,21,21,17,16,15,13,12,12,12,12,10,11,11,11,11,10,9,9,8,10,12,14,17,18,19,19,17,17,16,15,13,12,11,11,10,9,8,7,7,7,7,8,9,9,8,7,6,6,5,5,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,5,5,5,6,6,7,7,7,8,8,8,9,9,10,10,10,13,14,15,16,17,18,18,18,16,16,15,15,15,16,17,17,18,21,24,29,33,37,39,40,43,43,42,40,38,36,33,32,26,24,21,19,19,20,23,25,28,31,36,42,48,52,54,55,55,55,54,52,49,45,41,39,38,36,33,31,30,31,33,34,34,36,37,37,39,42,48,52,58,61,63,62,56,45,34,27,17,20,26,37,48,55,55,52,46,36,26,23,25,29,37,44,43,47,41,36,39,35,31,38,41,40,39,38,38,38,38,38,41,41,41,40,40,39,38,38,40,41,44,47,48,49,49,49,45,47,49,51,49,46,42,39,48,51,58,69,82,93,100,103,103,102,96,85,72,65,65,67,75,82,90,95,90,77,62,52,38,36,35,38,43,48,49,49,46,43,36,30,26,27,31,35,49,54,63,69,72,74,75,76,71,68,63,56,49,42,37,35,31,30,29,27,25,24,24,24,30,33,36,40,42,43,43,42,39,38,35,31,29,31,35,39,44,45,45,42,38,33,30,30,31,34,39,42,43,43,43,44,36,35,32,28,25,24,27,29,34,35,36,34,31,29,28,28,34,34,33,31,30,31,34,37,36,35,33,28,22,19,17,18,23,24,25,25,23,20,16,13,17,17,18,19,21,24,26,27,36,37,39,39,39,40,43,46,51,57,70,86,101,110,111,110,102,91,74,57,43,34,27,24,26,28,29,29,27,24,23,23,22,22,21,21,22,24,26,27,23,24,24,24,23,21,19,17,17,18,19,20,21,22,23,23,18,17,15,14,13,12,12,12,10,10,11,11,11,10,9,8,8,10,12,15,17,19,20,20,18,17,16,15,13,12,11,11,10,9,8,7,7,7,7,8,10,9,8,8,7,6,5,5,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,6,6,6,7,7,8,8,8,7,7,7,7,7,7,7,7,5,6,7,7,8,9,10,10,13,14,14,15,17,18,18,19,19,18,18,17,17,18,18,19,18,21,26,30,34,38,43,46,44,45,46,46,44,41,38,36,31,29,25,22,21,22,24,25,26,30,36,41,45,50,54,57,56,56,56,55,53,50,47,45,43,40,36,33,32,32,34,35,37,39,41,43,45,49,54,58,62,67,70,68,64,55,41,28,21,22,26,35,45,52,54,52,45,39,31,26,26,32,41,47,48,48,46,42,37,33,33,33,35,34,34,35,36,39,41,43,43,43,42,41,39,36,34,32,31,33,37,41,46,49,51,52,52,51,50,49,47,46,45,44,46,51,59,67,76,86,95,101,106,100,93,84,71,60,58,62,71,82,94,97,94,83,66,52,41,34,32,39,47,49,48,48,42,33,27,26,26,28,37,49,57,62,70,75,77,76,74,73,66,63,58,52,46,41,37,35,36,33,32,32,29,24,24,28,29,37,43,46,48,50,47,42,45,37,30,29,30,30,33,37,41,45,49,48,42,34,28,26,28,30,34,36,38,40,42,44,38,35,30,26,25,27,30,33,35,37,37,36,32,29,28,29,33,34,35,34,32,31,32,33,36,34,30,26,23,20,19,19,24,25,26,25,22,20,20,21,20,21,22,23,23,26,31,35,39,41,44,45,44,44,45,47,53,66,82,93,103,110,113,110,103,87,67,51,37,27,24,26,26,27,29,30,28,25,22,19,21,22,24,25,25,24,22,20,24,23,22,20,19,18,18,18,19,19,20,20,20,19,18,18,16,16,15,14,13,11,11,10,10,9,9,8,8,9,9,10,10,11,14,17,18,19,19,19,19,18,17,15,14,13,13,13,12,11,9,7,6,6,7,7,8,8,7,6,6,5,4,4,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,6,6,7,7,7,8,8,8,7,7,7,7,7,7,7,7,6,6,7,8,9,9,10,10,13,14,14,15,17,18,18,19,19,19,18,18,18,18,19,19,18,22,26,30,33,37,42,45,46,47,47,47,46,43,39,37,32,30,26,23,22,22,24,25,24,28,34,38,42,47,51,55,59,59,60,60,58,56,53,52,46,43,39,35,33,33,33,34,36,39,41,44,46,51,56,60,69,74,77,75,70,61,47,34,22,22,25,32,42,49,52,51,44,38,31,26,27,34,42,48,50,50,48,44,38,34,33,34,33,33,33,34,36,39,42,44,43,43,43,42,39,36,32,30,27,28,32,36,40,45,48,50,54,53,52,50,48,46,44,44,44,49,57,65,74,84,93,99,102,96,89,81,69,58,56,60,69,82,95,100,96,86,68,54,42,34,31,37,43,45,44,44,35,29,26,30,34,40,51,62,71,73,77,78,76,73,69,67,63,61,57,52,46,42,39,37,37,34,33,33,29,24,25,29,33,41,48,52,55,57,54,48,48,40,32,30,30,29,31,35,41,46,52,53,48,41,36,34,31,33,35,38,40,42,44,45,41,38,32,28,27,28,32,34,37,38,38,35,31,28,28,28,33,34,35,34,32,31,32,33,35,33,30,26,24,22,21,20,24,25,26,24,22,20,21,21,23,25,26,27,28,31,36,39,45,47,49,49,48,48,49,51,57,68,83,94,105,112,112,107,96,80,60,45,33,25,23,25,27,29,30,30,29,26,22,20,22,23,24,25,25,24,22,20,22,21,20,19,18,18,18,18,19,20,20,20,19,18,17,16,14,14,13,13,12,11,11,10,10,9,9,8,8,9,9,10,11,12,15,17,19,20,20,19,19,18,16,14,13,13,12,12,12,10,9,7,6,6,7,7,8,8,7,6,6,5,4,4,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,6,7,7,7,8,8,8,8,8,8,8,8,8,8,8,8,7,7,7,8,9,9,10,10,13,13,14,15,17,18,19,19,20,20,20,20,20,20,20,20,19,22,25,28,31,35,39,43,47,48,49,49,48,45,42,40,34,32,28,25,23,23,24,24,23,26,31,35,39,43,48,51,59,60,62,63,63,61,59,58,51,48,43,39,35,33,33,33,36,38,42,45,48,53,59,63,75,80,83,81,76,67,52,39,25,23,23,28,37,44,48,49,42,37,31,27,29,36,45,51,54,53,51,46,40,35,33,33,31,31,32,34,36,40,43,46,44,45,45,44,41,36,31,28,24,25,28,32,37,43,48,50,56,55,53,50,47,44,42,41,41,46,53,61,70,79,89,95,96,91,85,77,65,54,52,56,65,79,95,102,100,90,72,56,44,36,31,36,42,43,42,43,33,30,31,39,47,57,68,77,82,81,80,77,73,68,65,62,61,59,56,52,48,45,42,41,39,36,34,34,30,26,27,31,37,46,56,62,66,69,65,59,55,45,36,32,30,28,29,33,40,46,55,59,58,54,49,46,37,38,39,40,43,45,47,48,46,42,36,31,29,30,34,36,40,40,38,35,30,28,27,28,33,34,35,34,32,31,32,33,33,32,30,28,25,24,23,23,24,25,25,24,21,21,22,23,27,29,32,33,35,38,42,45,49,51,52,52,50,49,51,52,58,67,79,91,103,109,105,97,83,68,50,37,28,21,21,25,29,30,31,31,29,26,23,21,23,24,25,25,25,23,21,20,18,18,17,16,16,17,17,18,20,20,20,19,18,17,15,14,11,11,11,11,11,11,11,11,10,9,9,8,8,9,9,10,12,13,16,18,20,20,20,20,18,17,15,14,12,12,11,11,11,10,9,7,7,7,7,7,8,8,7,6,6,5,4,4,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,7,7,7,8,8,8,9,9,9,9,9,9,9,9,9,9,7,8,8,9,9,10,10,10,12,13,14,15,17,18,19,20,21,21,21,22,22,21,21,21,21,23,25,27,28,32,36,40,48,49,50,50,49,47,44,42,37,34,31,28,25,24,24,24,23,26,30,33,36,40,44,48,55,57,60,63,64,63,62,60,55,52,48,42,38,35,33,33,36,38,42,45,49,55,61,66,78,83,86,83,78,70,55,42,27,24,21,24,31,39,44,45,40,36,31,29,31,39,48,54,57,56,54,48,41,35,32,31,29,29,30,33,36,41,45,47,47,47,48,47,44,39,34,30,27,27,29,33,38,44,50,54,56,54,52,48,45,41,39,37,38,42,48,55,63,73,83,89,93,88,82,74,62,51,48,52,61,76,94,104,104,94,76,60,46,37,32,36,43,45,46,47,40,40,44,52,63,74,82,88,86,82,76,71,67,65,63,61,61,60,58,55,52,48,46,44,39,36,34,34,31,27,29,34,41,52,65,73,79,82,78,72,63,52,41,36,32,28,29,32,39,46,57,66,69,67,63,60,48,46,45,46,48,51,52,53,52,47,40,34,31,32,35,37,42,41,39,35,30,28,28,29,32,34,35,34,32,31,32,34,33,32,31,30,28,27,27,27,25,26,25,23,21,22,24,26,31,33,37,40,41,43,47,49,49,50,50,49,46,45,46,48,54,62,72,83,94,99,92,82,71,57,42,31,25,20,21,26,30,31,31,31,29,27,24,22,24,24,25,24,23,22,20,19,15,15,14,14,15,16,17,18,19,19,19,18,17,15,13,12,9,9,9,10,10,11,11,11,10,9,9,8,8,9,9,10,13,15,17,19,20,21,20,20,17,16,14,12,11,11,10,10,10,9,9,8,7,7,7,7,7,7,7,6,6,5,5,5,6,6,6,6,6,6,6,6,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,7,7,8,8,8,9,9,9,9,9,9,9,9,9,9,9,8,9,9,9,9,10,10,10,12,12,13,15,17,19,20,20,22,22,23,24,24,23,22,22,22,23,24,25,26,28,33,36,45,47,49,50,50,48,46,44,39,37,34,30,27,25,23,23,24,26,29,31,33,37,42,45,52,55,59,63,65,64,63,61,57,55,50,45,41,37,35,34,35,38,42,46,50,55,62,67,78,83,87,85,80,72,58,45,30,25,20,21,27,35,39,41,38,35,31,30,34,42,51,57,60,60,57,51,42,35,30,28,27,28,29,32,36,41,45,48,49,50,51,50,48,44,39,36,32,32,33,36,41,47,52,55,54,52,49,46,41,38,35,33,34,37,42,48,56,65,75,81,89,85,79,72,59,48,44,48,57,74,94,106,108,99,82,66,47,38,32,37,44,48,50,53,49,52,57,66,78,89,94,95,89,82,72,65,62,62,62,62,64,63,61,58,55,51,47,45,38,35,33,33,31,28,31,37,45,58,73,84,92,96,92,85,73,61,48,41,35,31,31,34,39,46,59,71,79,80,77,74,62,58,54,53,55,57,58,58,56,51,43,35,31,32,35,38,43,43,41,37,33,30,29,30,32,33,34,34,32,32,33,34,34,34,34,33,32,31,30,30,27,27,25,23,22,23,27,30,34,37,42,45,46,48,50,51,49,49,48,45,42,40,41,43,50,56,64,73,82,86,78,67,59,47,35,28,24,21,22,26,30,30,30,30,29,27,25,24,25,24,24,23,21,20,18,17,13,13,13,13,14,15,16,17,18,18,18,17,15,14,12,11,8,8,9,9,10,11,11,12,10,9,9,8,8,9,9,10,14,15,17,19,20,20,20,19,15,14,13,11,10,9,9,9,8,8,9,8,8,8,7,7,7,7,6,6,6,6,5,5,6,6,6,6,6,6,6,6,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,8,8,8,8,9,9,9,10,10,10,10,10,10,10,10,10,9,9,9,10,10,10,10,10,11,12,13,15,17,19,20,21,23,24,25,26,26,25,24,23,23,24,24,23,23,26,30,33,41,43,45,48,49,48,47,46,42,40,37,33,29,26,23,22,24,25,27,29,30,33,38,42,49,53,58,62,65,65,63,61,57,55,51,47,43,39,37,36,36,38,42,45,49,55,61,66,76,82,86,85,81,73,60,47,32,27,21,20,25,32,35,36,36,33,31,31,36,45,54,60,65,64,61,54,45,36,30,28,26,27,29,32,36,41,45,48,50,51,51,51,50,48,46,44,38,39,40,42,45,49,53,55,52,50,47,44,39,35,32,31,31,33,37,42,48,56,65,72,82,78,74,68,57,46,43,46,57,75,95,108,112,105,89,75,50,40,34,38,46,51,54,58,57,62,68,77,88,99,100,97,88,78,66,58,57,60,63,64,68,67,65,61,56,50,45,42,35,32,31,32,31,30,34,41,49,64,82,95,105,109,105,98,82,70,56,47,40,35,35,38,42,49,61,76,87,92,91,89,77,71,64,61,62,64,65,64,59,53,44,35,31,31,34,36,43,44,44,41,37,33,31,31,31,33,34,34,32,32,33,35,37,37,37,37,36,35,34,33,29,29,27,24,23,26,31,35,38,42,47,50,51,51,52,53,49,49,47,43,39,37,37,39,45,51,57,63,69,71,64,55,48,39,31,28,25,22,23,26,28,28,28,28,28,27,26,26,25,24,22,21,19,17,16,15,13,13,13,13,13,14,15,16,16,16,16,16,14,13,12,11,8,9,9,10,10,11,11,11,10,9,9,8,8,9,9,10,14,15,17,19,20,19,19,18,14,13,12,10,9,8,8,8,7,8,8,9,9,8,7,7,6,6,6,6,6,6,6,6,7,7,7,7,7,7,7,7,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,8,8,8,9,9,9,10,10,11,11,11,11,11,11,11,11,10,10,10,10,10,10,10,10,11,11,13,15,17,19,21,21,23,25,26,28,28,26,25,23,24,24,23,22,21,23,27,31,36,38,42,45,48,48,48,47,44,42,39,34,30,26,23,22,22,24,25,25,26,30,34,38,44,48,54,59,61,61,59,57,54,53,50,47,44,41,39,38,36,38,42,45,49,54,60,64,71,77,81,81,78,71,58,46,34,28,22,21,25,30,33,33,34,32,31,32,38,47,57,63,70,69,66,59,49,39,32,29,27,27,29,31,36,40,44,47,49,49,49,49,49,50,50,51,48,49,50,51,53,55,56,57,51,50,47,43,39,35,33,31,29,30,33,36,41,49,58,64,71,69,67,63,54,45,44,48,60,77,98,112,117,112,98,84,60,49,42,45,52,57,61,64,68,73,78,83,92,100,96,88,77,66,52,46,49,57,63,67,71,70,66,61,54,46,39,35,32,29,28,30,30,31,36,43,54,70,89,105,116,121,116,109,89,76,62,52,45,39,39,42,46,53,65,80,94,101,102,101,90,82,73,68,69,70,70,68,61,54,44,34,29,29,32,34,42,44,46,45,41,37,34,33,31,32,34,34,32,32,34,35,40,40,41,40,40,38,36,35,32,30,28,25,25,28,34,39,43,47,52,55,55,54,54,54,48,47,44,39,35,32,33,34,37,44,50,52,54,54,50,44,40,33,28,27,26,22,22,24,25,26,26,27,27,27,27,27,24,23,21,18,16,15,13,13,14,14,13,13,13,14,15,15,14,14,14,14,14,13,12,11,10,10,10,10,11,11,11,11,10,9,9,8,8,9,9,10,13,14,16,18,19,18,17,17,13,12,11,9,8,7,7,7,6,7,8,9,9,9,8,7,6,6,6,6,6,6,6,6,7,7,7,7,7,7,7,7,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,8,8,8,9,9,10,10,10,11,11,11,11,11,11,11,11,10,10,10,10,10,10,10,10,10,11,13,15,17,19,21,22,24,25,27,29,29,27,25,24,24,24,23,21,20,22,26,30,33,35,40,44,47,48,48,48,45,43,40,35,31,27,23,22,21,22,23,23,24,27,32,35,39,43,49,54,56,56,54,52,53,52,50,47,45,42,40,40,36,38,42,45,48,53,59,63,64,71,76,76,73,67,54,42,34,29,23,21,25,29,31,31,33,32,31,32,39,48,58,64,74,73,70,62,51,41,34,30,27,27,29,31,35,40,44,46,48,47,47,47,48,50,53,54,56,57,58,60,60,61,60,60,51,50,47,44,40,36,34,32,28,29,31,33,37,44,53,59,63,61,61,59,53,45,45,49,63,80,101,115,120,116,103,90,70,59,50,52,58,63,66,70,78,82,85,87,92,96,88,76,61,51,38,35,42,54,64,70,73,71,67,61,52,43,35,30,30,27,27,29,30,31,37,45,57,74,94,111,123,128,123,115,93,80,65,55,48,42,42,45,50,56,67,83,98,107,109,108,97,88,78,72,73,74,73,70,61,54,43,34,28,28,30,33,41,44,47,47,44,39,35,34,30,32,34,34,32,32,34,36,42,42,43,43,41,39,37,36,33,31,29,26,25,29,36,41,46,50,56,59,58,56,55,55,45,44,41,35,30,28,28,30,30,38,43,43,42,42,40,36,35,29,26,27,26,22,20,22,23,24,25,25,26,27,28,28,24,22,20,17,15,13,12,12,15,14,14,13,13,14,14,15,13,13,13,14,14,13,12,12,11,11,11,11,11,11,11,11,10,9,9,8,8,9,9,10,13,14,16,17,18,17,17,16,13,12,10,9,7,7,7,7,6,7,8,10,10,9,8,7,6,6,6,6,6,6,6,6,7,7,7,7,7,7,7,7,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,5,5,5,6,6,7,7,7,8,8,7,8,9,10,11,12,13,13,14,15,15,14,14,13,11,11,11,11,11,11,11,11,14,14,15,16,18,19,20,21,25,26,26,27,27,26,26,25,25,24,22,21,20,20,21,22,26,29,33,37,41,44,46,46,40,39,37,34,30,26,23,21,22,21,21,22,23,26,28,30,34,37,42,46,50,52,52,52,46,46,47,46,45,43,41,39,43,42,41,41,43,47,51,54,64,65,67,69,69,64,57,51,38,31,23,22,26,31,33,33,29,26,27,32,38,46,59,71,74,73,72,67,56,43,35,32,27,26,27,31,37,42,45,46,44,44,42,40,41,45,51,56,62,62,63,64,65,64,61,58,54,52,49,45,41,38,36,35,32,32,32,33,34,39,44,48,55,56,56,53,49,47,49,51,68,83,100,113,122,123,110,95,80,68,60,62,67,69,75,81,78,83,85,86,89,88,76,61,44,39,33,33,40,53,64,71,76,71,63,53,44,37,32,30,23,24,26,26,27,31,38,43,54,72,91,104,119,130,123,108,93,80,64,54,47,43,45,50,53,62,74,86,100,113,116,114,101,90,80,75,73,69,66,67,61,49,38,33,28,25,29,38,41,43,46,48,46,41,35,31,29,28,26,26,28,32,36,38,43,43,42,40,37,35,36,38,32,32,31,30,30,33,38,42,48,55,61,60,60,60,57,53,43,39,33,27,24,24,25,27,31,32,34,36,36,35,33,32,25,26,27,27,26,25,23,22,23,24,25,26,27,28,27,27,26,23,20,16,14,14,14,15,15,16,17,18,17,16,14,13,12,12,12,12,12,13,14,14,13,13,12,12,12,11,11,11,11,11,9,8,8,9,11,12,15,16,17,17,16,15,13,12,11,11,10,9,9,8,7,7,9,9,9,9,9,9,9,9,6,5,5,5,5,6,7,8,5,6,6,7,7,8,8,8,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,5,5,5,6,6,7,7,7,8,8,7,8,9,10,11,12,13,14,15,15,16,15,15,15,14,14,13,13,12,12,12,11,13,14,15,16,17,19,20,20,24,24,25,26,27,27,26,26,26,25,23,21,20,20,21,21,24,26,30,34,37,40,41,42,38,38,36,33,29,25,22,20,22,21,21,21,22,24,26,27,31,33,37,42,45,47,48,48,45,46,46,47,46,44,43,41,42,41,40,40,41,45,48,51,59,61,64,68,68,64,58,52,41,34,27,25,29,33,35,34,31,28,27,32,38,46,60,72,76,76,75,70,59,47,38,34,25,25,25,29,34,39,41,42,42,41,40,38,38,43,50,55,62,63,63,64,64,63,60,58,54,52,50,47,44,41,39,38,36,36,36,36,37,39,43,46,47,49,51,51,50,52,55,59,69,82,97,108,117,118,108,96,86,77,72,75,79,79,81,85,79,81,82,81,83,81,69,56,39,34,30,31,38,51,62,69,70,66,57,48,39,33,29,27,22,25,27,28,29,32,38,43,49,66,84,97,112,123,118,105,87,74,59,50,45,43,47,52,54,63,75,87,101,113,117,115,105,93,80,74,70,64,62,62,56,46,35,29,25,23,28,35,41,43,46,47,44,39,33,28,26,25,24,24,26,30,35,38,42,42,41,39,36,34,35,36,33,33,33,32,32,35,40,44,51,59,64,64,62,61,57,52,40,36,30,25,22,22,23,25,27,28,30,31,31,30,28,26,24,25,26,26,26,24,23,22,23,24,25,27,28,28,27,27,25,23,20,17,16,15,16,17,16,17,18,18,18,17,15,14,13,13,13,13,14,15,16,16,15,15,14,13,12,11,11,11,10,10,9,8,9,10,12,13,15,16,16,16,16,14,13,11,10,10,10,9,9,9,9,8,9,9,9,9,9,9,9,9,6,6,5,5,6,7,7,8,6,6,7,7,7,8,8,8,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,5,5,5,6,6,7,7,7,8,8,7,8,9,10,11,12,14,15,16,17,17,17,17,17,18,17,17,15,14,13,12,12,13,14,15,16,17,18,19,19,21,22,24,25,27,27,27,27,27,26,24,22,21,20,20,20,20,21,24,27,30,33,34,35,35,34,33,30,27,24,22,20,21,21,20,20,21,22,23,23,26,28,32,36,39,41,42,42,44,44,45,45,45,45,44,43,41,40,38,37,38,40,43,45,51,54,59,64,67,65,59,54,45,39,32,30,32,36,37,37,34,30,28,31,37,45,60,73,78,80,80,74,64,53,43,38,27,26,25,28,32,36,39,39,39,38,36,34,35,39,46,52,61,62,62,62,61,59,57,56,53,53,52,51,49,47,45,44,42,42,41,40,40,41,42,43,42,44,46,48,50,55,60,65,70,79,91,100,107,109,103,95,91,86,86,91,94,92,89,87,80,79,76,74,74,72,62,50,38,34,30,31,39,50,61,66,65,60,53,44,36,30,27,25,23,25,28,31,33,35,39,42,47,60,74,86,100,110,107,96,79,66,52,45,42,42,47,53,55,64,76,88,102,114,118,115,108,94,79,70,63,56,53,54,49,40,32,27,24,24,30,36,42,44,46,46,42,36,30,25,24,22,21,21,23,28,34,37,40,40,39,37,33,32,32,33,33,34,34,34,34,38,43,47,53,61,67,67,63,60,54,48,35,32,28,23,20,20,21,22,25,26,27,27,26,25,23,22,23,24,24,24,24,23,22,22,23,24,26,28,28,28,28,27,24,22,21,19,18,18,19,20,18,19,19,19,19,18,17,16,15,15,16,17,18,19,20,20,18,17,15,14,12,11,10,10,9,8,9,9,10,12,13,14,16,16,16,16,15,13,12,11,9,9,9,10,10,10,11,11,10,10,10,9,9,9,9,9,7,6,6,6,6,7,8,9,7,7,7,8,8,8,9,9,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,5,5,5,6,6,7,7,7,8,8,7,8,9,10,11,12,14,15,17,18,19,20,20,19,20,20,18,17,15,13,12,11,13,13,14,15,16,17,17,18,19,20,22,24,26,27,28,28,28,27,25,23,22,20,19,18,16,17,19,21,23,25,26,27,30,30,29,27,25,23,21,19,20,20,19,19,19,19,19,20,23,25,28,32,35,37,39,39,42,42,42,43,43,43,43,43,38,37,36,35,35,36,37,39,42,46,53,60,65,65,61,57,50,45,38,35,36,38,39,39,37,31,28,30,34,43,57,70,77,82,83,77,67,58,48,40,32,30,29,30,34,37,40,40,37,36,33,30,31,35,43,49,57,59,59,58,56,53,52,52,53,54,55,55,55,53,51,50,47,46,45,46,46,45,43,41,44,44,44,45,49,54,60,64,70,75,82,89,93,95,94,91,90,91,96,103,106,103,95,88,80,76,70,68,68,66,59,51,44,41,37,37,43,52,59,63,61,57,50,42,35,30,28,27,24,27,32,36,39,40,41,42,47,56,66,75,87,95,93,85,73,60,47,40,38,39,44,51,55,64,76,87,101,113,116,114,108,92,74,62,54,46,43,44,40,35,30,27,28,31,37,41,45,46,46,44,40,34,28,24,23,22,20,20,23,27,32,36,37,37,36,34,30,28,29,30,33,33,34,34,35,40,45,50,54,62,68,67,62,57,49,42,32,30,26,23,20,20,20,20,25,25,25,25,24,22,21,19,22,22,22,22,22,22,21,21,23,24,26,28,29,29,28,27,23,22,22,21,21,21,22,23,21,21,21,21,20,20,19,19,17,18,19,21,22,23,23,23,21,19,17,14,12,11,10,10,8,8,9,11,12,14,16,17,16,16,15,14,13,12,11,10,8,9,9,10,11,12,13,13,11,10,10,10,10,9,9,9,7,7,7,7,7,8,9,9,8,8,8,9,9,9,9,9,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,5,5,5,6,6,7,7,7,8,8,7,8,9,10,11,12,14,15,17,19,20,21,21,21,21,20,19,17,15,13,12,11,13,13,14,14,15,16,16,16,18,19,21,23,25,27,27,28,28,27,26,24,23,21,19,18,15,15,15,16,18,19,20,21,25,25,25,24,23,21,20,19,19,19,19,19,18,18,17,17,21,23,26,30,33,37,39,40,40,40,40,39,39,39,39,39,36,35,33,32,32,32,33,33,36,40,47,55,62,65,63,61,55,51,45,41,39,40,40,40,39,33,29,30,33,40,54,66,74,81,84,78,70,62,52,42,36,33,31,31,34,38,41,41,38,35,32,28,28,32,40,46,53,54,55,53,49,46,46,47,52,54,56,58,59,57,55,53,49,49,50,52,54,53,49,46,46,44,42,43,47,53,59,62,67,68,71,75,77,78,80,82,86,91,101,110,116,113,102,92,81,73,65,63,64,64,60,57,53,50,45,44,47,51,55,57,55,52,46,39,33,30,28,27,28,31,37,43,47,47,45,44,44,49,55,64,75,83,83,79,67,56,43,37,35,35,39,45,53,62,73,85,98,110,113,110,102,85,66,52,43,36,34,36,32,32,31,31,34,40,45,47,49,48,46,43,38,33,29,26,26,25,24,24,26,29,32,34,34,35,34,30,27,25,25,26,30,31,32,33,35,39,46,50,56,64,69,67,61,55,46,38,30,28,26,24,22,21,20,20,23,22,22,21,20,19,18,17,20,20,20,20,20,20,21,21,22,24,27,30,30,30,28,27,23,23,23,23,24,24,25,26,23,23,22,22,21,21,21,21,20,21,23,24,25,25,25,25,22,20,17,13,11,10,10,10,9,10,11,13,15,17,18,19,16,16,14,13,12,11,10,9,9,9,10,11,12,13,14,14,12,11,11,10,10,9,9,9,8,8,7,7,8,9,10,10,10,10,10,9,9,9,9,9,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,5,5,5,6,6,7,7,7,8,8,7,8,9,10,11,12,13,14,16,19,20,22,22,23,22,21,20,18,16,15,13,13,13,13,13,14,14,15,15,15,17,19,21,23,25,26,26,27,26,26,26,25,24,22,20,19,15,15,14,14,14,15,16,17,20,20,21,21,21,20,19,18,17,18,18,19,19,18,17,16,20,22,25,29,33,38,41,43,42,41,39,37,36,35,35,35,33,32,31,30,30,30,30,30,33,36,42,51,59,64,66,65,61,57,52,47,44,43,43,44,43,37,32,32,34,39,50,61,69,80,85,79,72,67,57,45,37,34,31,31,35,39,41,42,40,37,32,27,26,30,37,43,49,51,52,49,43,40,40,42,50,53,57,60,61,59,56,54,51,51,54,60,65,65,61,56,49,45,41,41,45,52,57,60,63,60,60,62,61,60,64,69,78,88,101,112,120,120,110,98,84,72,62,60,62,63,63,63,61,57,53,50,50,51,52,51,49,46,41,35,31,28,27,26,32,36,43,51,55,55,51,46,40,41,44,53,64,72,75,75,62,51,41,36,34,33,35,40,49,58,69,80,93,105,108,105,94,77,56,43,35,30,30,33,30,35,39,40,45,51,54,53,55,52,47,41,37,34,32,32,32,32,32,32,32,32,32,33,32,32,31,27,23,21,21,22,25,26,28,29,32,37,44,49,58,65,68,65,58,52,44,36,27,27,26,25,23,22,21,20,19,18,18,17,16,16,15,15,19,18,18,18,18,19,20,20,22,24,28,31,31,30,28,26,25,25,25,26,26,27,27,27,26,25,24,23,23,23,23,24,23,24,26,27,27,27,26,25,22,19,16,12,10,9,10,10,11,12,14,16,18,19,20,20,17,16,14,12,10,9,9,9,10,10,11,12,13,14,14,15,12,12,12,11,10,10,9,9,9,9,8,8,9,9,10,11,11,11,11,10,10,10,9,9,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,5,5,5,6,6,7,7,7,8,8,7,8,9,10,11,12,12,13,15,18,20,22,23,23,23,22,21,20,19,17,16,16,12,13,13,13,13,14,14,14,18,19,21,22,24,25,25,25,25,25,26,26,25,23,21,20,17,16,15,14,13,14,15,15,16,17,18,18,19,19,18,18,16,17,18,19,19,19,18,17,18,20,23,28,34,39,43,45,45,44,41,37,35,33,32,32,30,30,30,29,29,29,29,29,32,34,39,47,57,64,68,69,67,65,60,54,50,47,47,48,47,42,37,36,36,39,49,59,67,79,86,81,75,72,62,49,40,37,34,34,37,42,45,46,43,40,34,28,25,29,36,41,48,50,51,47,40,37,38,41,49,52,57,61,62,60,56,53,52,54,59,68,76,79,74,69,57,51,44,40,42,47,51,53,58,54,51,51,48,45,49,57,67,80,95,108,118,122,113,100,88,73,61,58,60,61,63,66,68,65,60,57,56,55,53,52,47,45,40,35,31,29,28,28,36,40,48,57,63,62,55,49,42,39,39,44,53,60,64,65,56,47,39,36,35,33,34,38,44,53,64,75,88,100,103,100,87,70,49,37,30,28,30,35,41,48,55,57,61,66,65,61,60,55,48,41,36,35,36,38,40,40,40,40,38,36,33,31,30,30,29,25,21,19,19,20,20,21,23,25,28,34,41,46,55,61,63,58,52,46,39,32,25,25,25,25,24,22,20,19,18,17,17,16,16,16,17,17,18,17,16,16,16,18,19,20,22,25,28,31,32,31,28,26,26,27,27,28,28,28,28,28,28,27,25,24,24,24,25,26,25,26,28,29,29,27,25,24,20,18,14,10,9,9,10,11,14,15,17,19,21,22,21,21,17,15,13,11,9,8,8,8,11,11,12,12,13,14,14,14,13,13,12,11,10,10,9,9,10,9,9,9,9,10,11,12,12,12,11,11,11,10,10,10,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,5,5,5,6,6,7,7,7,8,8,7,8,9,10,11,12,11,12,15,18,20,22,23,23,24,24,23,22,21,19,19,18,12,12,13,13,13,13,13,14,18,19,21,22,23,24,24,24,24,25,26,26,25,24,22,21,18,17,15,14,13,13,14,15,14,15,16,17,18,18,18,18,15,16,18,19,20,19,18,18,17,19,22,27,33,39,44,47,49,46,42,38,34,32,31,30,29,29,29,29,29,29,29,29,32,33,37,45,55,64,69,71,71,69,65,59,53,50,50,51,51,45,41,40,39,41,48,57,66,79,87,82,78,75,66,52,44,41,38,38,41,46,50,51,46,42,35,29,25,28,35,41,48,51,51,46,39,36,37,41,48,52,57,61,62,60,55,52,53,55,62,73,84,88,84,78,67,59,48,41,40,42,43,44,55,49,46,45,41,36,41,50,58,71,88,101,113,119,112,100,91,75,60,57,59,59,62,67,74,70,66,64,62,61,58,56,49,46,42,37,34,32,32,32,39,43,52,61,67,66,58,51,48,42,38,40,46,50,52,54,51,43,37,36,36,34,35,38,41,50,61,72,85,96,99,96,83,66,46,34,29,28,32,38,53,62,69,71,74,78,75,68,63,57,48,40,36,36,39,42,44,45,46,45,43,38,34,31,29,29,27,24,20,17,17,18,17,18,20,22,26,32,39,45,50,55,56,51,44,39,32,26,23,23,24,24,23,21,19,18,19,19,18,18,18,19,20,20,17,16,15,15,16,17,19,20,22,25,29,32,32,31,28,26,27,28,28,29,29,29,28,28,29,28,26,25,24,25,26,27,27,28,29,30,29,27,24,23,19,17,13,9,8,8,10,11,16,17,19,21,23,23,22,22,17,15,13,10,8,8,8,8,12,12,13,13,13,14,14,14,14,13,12,12,11,10,9,9,10,10,9,9,9,10,11,12,13,12,12,11,11,10,10,10,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,5,5,5,6,6,7,7,7,7,7,7,8,8,9,9,9,13,14,15,16,18,21,23,25,22,22,23,24,23,22,20,19,18,17,16,14,14,15,16,17,19,19,20,21,22,22,23,23,22,23,25,26,27,27,26,25,20,20,19,17,14,13,13,15,17,17,16,16,16,17,18,18,17,17,17,17,17,17,17,17,16,19,25,30,35,41,47,52,53,51,47,42,37,32,28,26,27,26,26,27,28,30,33,34,36,38,42,47,54,65,76,84,87,83,75,64,55,50,50,51,55,52,46,41,38,41,47,53,62,70,78,81,80,75,66,56,45,43,41,43,47,52,56,57,52,43,34,27,22,22,30,39,49,52,52,48,41,35,33,34,44,53,59,59,58,56,52,47,50,60,70,78,89,98,98,92,77,69,57,45,38,38,41,44,46,46,45,41,36,35,38,42,54,61,74,89,102,106,104,99,85,73,63,60,58,56,60,67,72,71,70,68,66,65,63,63,59,52,46,42,36,30,29,32,38,46,59,70,75,73,67,62,54,48,41,37,37,40,44,46,41,42,41,39,36,35,35,37,38,47,58,69,82,92,94,90,73,57,39,30,29,35,46,57,72,79,85,88,88,85,75,65,60,55,47,39,36,37,41,43,48,50,53,51,46,39,34,31,25,24,22,20,18,17,16,16,20,20,20,21,25,30,35,38,46,46,45,42,38,33,29,26,22,23,25,26,26,24,22,20,19,20,20,21,21,21,21,20,19,17,15,14,15,16,18,20,21,23,27,30,31,31,29,27,27,28,28,29,30,30,31,31,29,27,25,23,23,24,25,27,29,28,27,26,25,24,23,22,15,13,11,9,9,10,12,14,17,19,23,26,27,26,24,22,15,14,12,11,10,10,11,12,13,13,14,15,16,16,16,15,15,14,13,12,11,10,11,11,8,9,10,10,11,12,13,13,12,12,11,10,10,9,8,8,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,6,6,5,5,5,4,4,4,5,5,5,4,4,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,5,5,5,6,6,7,7,7,7,7,7,8,8,9,9,9,13,13,14,16,18,20,23,24,23,23,24,25,24,23,21,20,19,17,16,15,14,15,16,17,18,18,19,20,21,21,22,22,21,23,24,26,26,26,26,25,22,23,23,22,19,17,17,18,17,17,16,16,16,17,17,18,17,17,17,17,17,17,17,17,15,19,23,28,34,41,48,54,54,52,49,44,39,34,31,29,27,26,26,26,28,31,33,35,38,40,45,50,58,69,81,88,93,88,80,69,59,53,53,54,55,53,49,44,41,43,48,52,60,69,76,79,78,75,66,57,48,46,44,46,51,57,62,64,57,47,36,28,22,21,28,38,49,52,53,50,43,36,33,33,41,49,56,56,54,53,48,43,48,57,68,77,88,99,100,96,88,79,66,52,42,38,38,39,40,41,41,38,35,35,38,41,50,56,67,81,92,97,96,93,85,74,65,60,57,54,57,62,67,68,70,72,72,72,71,71,69,61,53,47,41,35,34,37,44,52,65,75,80,79,73,69,54,48,39,33,31,33,36,37,38,39,39,37,35,34,36,37,40,48,59,68,79,87,87,82,69,54,37,30,32,39,52,64,83,90,95,94,91,86,75,64,55,49,42,35,33,35,40,44,50,52,54,52,46,38,31,28,23,22,21,21,20,19,19,19,19,19,19,21,24,28,32,35,38,37,35,33,30,27,25,23,22,23,25,27,27,25,23,21,20,21,23,25,25,24,23,22,21,19,17,15,15,16,18,19,20,23,26,29,31,31,29,28,27,27,28,28,29,29,30,30,27,26,24,22,22,23,24,25,26,26,25,24,23,22,21,21,15,13,11,10,10,12,14,15,19,21,24,27,27,26,23,21,15,14,12,11,10,11,12,12,14,14,15,16,17,17,16,16,15,14,13,12,11,10,11,11,9,9,10,11,12,12,13,13,12,12,11,10,10,9,8,8,6,6,6,6,6,6,6,6,5,5,5,5,5,5,5,5,6,6,6,5,5,5,4,4,5,5,5,4,4,4,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,5,5,5,6,6,7,7,7,7,7,7,8,8,9,9,9,13,13,14,15,17,19,21,23,24,25,26,27,26,25,24,22,19,18,16,15,14,15,16,16,17,17,18,18,19,20,20,21,21,22,23,25,26,26,26,26,25,27,29,28,25,23,22,22,18,18,18,18,17,17,17,17,17,17,16,16,16,16,16,16,15,17,21,26,32,40,50,56,55,54,51,47,43,38,34,32,27,26,26,26,27,30,34,36,40,44,49,56,65,76,87,94,97,92,84,72,61,54,53,53,54,54,53,49,47,46,48,50,58,66,74,76,76,74,66,57,51,49,48,51,57,65,70,73,65,54,41,31,23,20,26,35,48,51,54,51,44,37,33,32,38,46,53,53,52,50,46,41,45,52,62,73,86,97,101,99,96,88,75,61,49,42,39,38,37,38,38,37,37,37,40,43,47,51,59,69,79,84,86,85,83,75,67,61,56,51,51,55,61,65,71,77,82,84,84,83,82,72,61,54,46,40,39,43,52,59,70,80,85,84,80,77,60,52,41,32,28,28,29,30,34,35,36,35,34,35,37,39,42,50,59,67,75,81,78,72,62,48,35,31,36,46,62,75,95,100,103,98,91,82,69,58,48,43,36,31,30,35,42,47,52,54,56,53,46,36,28,24,20,20,22,23,23,24,24,24,19,20,20,21,23,25,28,29,28,27,26,24,23,22,22,22,24,25,27,29,29,28,26,25,23,25,28,30,31,29,27,25,24,22,19,16,15,15,17,18,19,22,25,28,30,30,29,28,27,27,27,27,27,28,28,28,25,23,22,20,20,21,22,23,22,22,22,22,21,20,19,19,15,14,12,11,12,14,17,18,23,24,27,28,27,25,22,20,15,14,12,11,11,11,13,13,16,16,17,18,18,18,18,17,15,14,13,12,11,10,11,11,10,10,10,11,12,12,13,13,12,12,11,10,10,9,8,8,5,5,5,5,5,5,5,5,7,7,7,7,7,7,7,7,7,7,6,6,6,5,5,5,5,5,5,5,4,4,4,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,5,5,5,6,6,7,7,7,7,7,7,8,8,9,9,9,12,12,13,14,16,18,20,21,25,26,27,28,28,27,25,24,19,18,16,15,14,14,15,16,15,16,16,17,18,18,19,19,20,21,22,23,24,25,26,26,27,30,33,33,31,29,27,27,22,22,22,21,20,19,18,17,17,17,17,17,16,16,16,16,15,17,20,24,30,39,50,56,58,57,54,50,45,40,36,33,28,27,26,25,27,30,33,35,42,47,54,62,71,82,92,99,98,93,84,72,60,52,49,49,53,55,56,55,52,50,49,49,57,65,72,74,74,72,66,58,53,52,51,54,62,71,78,81,73,62,47,35,25,20,24,32,44,48,52,50,43,35,31,29,37,45,52,53,52,51,47,42,42,47,55,66,79,90,96,98,96,90,80,69,59,51,47,45,41,41,41,40,41,43,46,48,49,50,54,60,66,72,76,78,79,75,69,61,54,48,47,48,55,62,72,83,91,94,95,94,92,81,68,59,51,45,45,50,57,63,73,82,86,86,83,81,70,61,49,38,32,30,30,29,31,33,35,35,35,36,39,42,44,51,60,66,72,75,71,64,54,43,33,33,40,53,70,83,99,103,103,94,82,70,56,45,40,37,32,29,30,36,43,48,53,55,56,53,44,34,26,22,19,21,24,27,29,30,30,30,25,25,24,24,24,23,23,22,22,21,20,19,20,21,23,24,27,29,31,33,34,33,31,30,27,30,33,36,36,34,30,28,26,24,21,18,16,16,17,17,18,20,23,26,27,28,27,27,26,26,26,26,26,26,25,25,22,21,20,19,18,19,19,20,18,19,20,21,21,20,19,18,16,15,13,13,14,16,19,21,26,27,29,29,28,24,21,18,14,13,12,11,11,12,14,15,18,18,19,19,20,19,19,18,15,14,13,12,11,10,11,11,10,11,11,12,12,13,13,13,12,12,11,10,10,9,8,8,5,5,5,5,5,5,5,5,7,7,7,7,7,7,7,7,8,7,7,7,6,6,6,6,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,5,5,5,6,6,7,7,7,7,7,7,8,8,9,9,9,11,11,12,13,14,16,18,19,24,25,27,28,28,27,26,25,20,19,17,15,14,14,15,15,14,15,15,16,17,18,18,19,19,20,21,22,23,24,26,26,27,30,34,36,35,33,33,33,29,29,28,27,25,23,20,19,19,18,18,18,17,17,16,16,16,17,20,24,29,38,47,54,59,58,56,52,47,42,36,33,31,29,27,25,26,29,32,34,43,48,56,65,74,85,94,101,98,94,85,72,60,51,47,46,51,54,58,59,57,53,50,49,57,64,69,70,71,70,64,58,52,50,50,54,62,72,80,84,79,67,53,40,28,21,23,29,39,44,48,47,40,33,29,28,35,43,51,53,53,52,49,44,43,44,48,58,69,79,86,89,92,89,84,77,69,62,56,53,48,46,44,43,44,47,50,51,54,54,54,55,58,63,69,72,73,73,68,60,51,47,45,45,53,61,74,87,96,100,101,100,98,87,74,65,57,52,53,58,63,68,75,82,86,87,85,83,77,68,57,46,39,36,34,33,34,36,38,38,38,40,43,46,46,53,60,64,69,71,66,59,48,38,32,35,44,57,73,85,96,99,96,84,69,56,44,35,32,30,28,28,31,36,41,45,51,53,53,50,42,33,26,23,21,24,29,33,36,37,36,35,33,32,30,27,25,22,20,19,19,19,18,19,20,22,24,26,30,32,35,37,38,38,37,36,32,34,37,39,39,36,32,29,27,25,22,19,17,17,18,19,19,20,22,24,25,25,25,25,26,26,25,25,24,23,23,23,20,19,18,18,17,17,17,17,16,17,20,21,22,22,21,20,18,17,16,15,16,19,21,23,27,29,30,30,27,23,19,16,13,13,12,11,12,13,15,16,19,19,20,20,20,20,19,18,15,14,13,12,11,10,11,11,11,12,12,12,12,13,13,13,12,12,11,10,10,9,8,8,6,6,6,6,6,6,6,6,7,7,7,7,7,7,7,7,8,8,8,8,7,7,7,6,6,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,5,5,5,6,6,7,7,7,7,7,7,8,8,9,9,9,11,11,11,12,13,15,16,17,22,24,25,26,27,26,25,24,21,19,17,15,14,14,14,15,14,15,15,16,17,18,18,18,19,19,19,20,22,24,26,27,28,31,35,37,38,38,40,41,39,38,37,35,32,27,24,21,21,20,20,19,18,18,17,17,17,19,22,25,29,35,43,49,55,55,54,52,48,43,39,36,34,31,28,25,25,27,30,32,41,47,56,65,75,84,93,98,98,93,85,72,60,50,45,44,49,53,58,61,59,56,52,51,55,61,65,66,65,65,60,54,48,46,45,49,58,69,78,83,81,71,58,45,32,23,23,28,36,40,44,43,38,32,30,29,34,43,51,54,55,56,54,50,49,45,45,52,60,65,72,77,87,87,86,84,79,74,68,65,58,54,48,45,46,49,51,53,59,58,55,52,52,55,61,66,66,69,66,57,49,46,46,45,55,63,75,88,97,101,101,100,98,88,77,69,63,58,61,66,68,71,77,82,85,85,84,83,78,71,62,53,48,44,40,38,41,43,44,44,44,45,48,50,50,55,59,61,64,65,60,53,43,36,32,37,47,58,71,82,88,90,85,70,55,44,35,29,26,27,30,33,36,39,40,41,48,48,48,44,38,32,28,26,27,30,36,41,43,43,42,40,38,36,33,29,25,22,20,19,20,20,21,22,23,25,26,27,32,34,37,40,42,42,41,40,37,39,40,41,39,36,32,30,26,24,22,20,19,20,22,23,22,23,24,24,25,25,24,24,25,25,24,23,22,21,20,20,18,18,18,17,17,17,16,16,16,18,21,24,25,25,24,23,21,20,18,17,18,20,22,24,27,28,29,29,26,22,18,15,13,12,11,11,12,14,17,18,20,20,20,21,20,20,19,18,15,14,13,12,11,10,11,11,12,12,12,13,13,13,13,13,12,12,11,10,10,9,8,8,8,8,8,8,8,8,8,8,7,7,7,7,7,7,7,7,9,9,9,8,8,8,7,7,7,6,6,6,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,5,5,5,6,6,7,7,7,7,7,7,8,8,9,9,9,10,10,10,11,12,14,15,16,20,21,23,24,25,24,23,23,21,19,17,15,14,13,14,14,15,15,16,16,17,18,18,19,18,18,18,19,21,23,25,27,29,32,35,38,40,43,46,49,48,47,46,43,38,32,27,24,23,22,22,21,20,19,18,18,19,21,24,26,29,33,39,43,47,49,50,50,49,46,42,40,37,34,29,25,24,25,28,30,39,45,54,64,73,82,89,94,94,90,81,69,57,47,42,40,46,51,58,61,60,57,54,53,52,57,61,60,59,59,54,48,43,40,39,43,52,63,73,78,81,72,61,49,37,26,24,27,34,38,42,41,37,33,32,33,38,47,57,60,63,65,63,59,57,49,45,49,52,54,59,66,77,80,85,89,90,88,85,82,72,64,55,49,49,51,54,55,62,60,55,50,46,47,53,58,59,64,63,53,46,47,49,49,59,66,77,88,95,98,98,97,90,81,72,67,63,60,62,68,69,71,74,78,80,80,79,79,78,73,67,61,57,53,49,46,50,51,51,51,50,50,52,54,55,58,59,57,57,58,52,45,40,34,33,39,48,56,66,75,76,78,71,56,41,32,28,25,28,33,39,45,48,47,44,42,43,43,42,39,35,32,31,31,33,37,42,47,50,49,46,44,38,36,32,28,25,23,23,23,26,27,28,29,31,31,31,31,32,34,37,40,42,42,42,41,42,42,41,40,38,34,31,29,24,22,21,20,21,23,25,27,27,27,27,27,27,26,26,25,25,24,23,22,21,20,19,18,17,18,18,18,17,17,16,15,18,20,24,27,29,29,28,27,23,22,20,19,19,21,23,24,26,27,28,28,26,21,17,14,12,12,11,12,13,15,17,19,20,20,20,20,20,19,18,17,15,14,13,12,11,10,11,11,13,13,13,13,13,13,13,13,12,12,11,10,10,9,8,8,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,10,10,9,9,9,8,8,8,7,7,6,6,6,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,5,5,5,6,6,7,7,7,7,7,7,8,8,9,9,9,10,10,10,11,12,13,15,15,19,20,22,23,24,23,22,22,21,20,17,15,14,13,14,14,15,15,16,17,17,18,19,19,18,18,18,18,20,23,25,27,30,33,36,39,42,46,51,54,53,53,51,47,42,35,29,25,24,23,23,22,21,20,19,19,20,23,25,27,29,32,36,39,41,43,46,49,49,48,46,44,39,35,30,25,23,24,27,29,37,43,53,63,72,80,87,91,89,85,77,65,52,43,37,36,45,50,57,61,60,58,55,54,49,54,57,56,55,54,50,44,39,37,35,39,48,60,69,74,80,72,62,52,39,28,25,27,34,38,41,40,37,34,35,36,43,53,63,68,71,73,72,69,63,53,46,48,49,48,52,59,67,73,83,92,98,100,99,98,83,73,61,54,52,55,58,59,62,60,55,47,42,42,47,52,55,61,61,51,45,47,51,51,62,68,78,87,93,95,95,93,82,74,66,62,59,57,60,66,66,68,70,72,74,74,74,73,79,76,71,68,65,61,57,53,55,56,56,55,53,53,54,56,58,60,59,54,53,52,46,39,39,34,33,40,48,55,63,70,66,67,61,45,30,24,23,22,34,40,49,57,59,56,50,46,40,40,39,36,33,31,33,35,37,41,47,52,53,52,48,45,36,34,29,26,24,24,26,27,33,34,36,37,38,38,37,36,31,33,36,40,42,42,41,41,44,43,42,39,36,33,30,28,22,21,20,20,21,24,27,29,32,31,31,30,29,28,27,27,25,24,23,22,20,19,17,17,17,18,18,18,18,17,16,15,19,22,26,30,32,32,31,30,25,24,21,20,20,21,23,24,25,26,28,27,25,21,17,14,12,11,11,12,13,16,18,20,20,20,20,20,19,18,17,17,15,14,13,12,11,10,11,11,13,13,13,13,13,13,13,13,12,12,11,10,10,9,8,8,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,9,9,9,8,8,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,6,6,7,7,7,7,7,7,8,8,9,9,9,11,11,11,11,11,11,11,11,16,17,19,21,23,23,22,22,22,22,21,20,18,17,16,15,16,16,17,17,17,17,18,18,19,20,21,21,21,22,24,27,30,33,38,42,45,49,53,56,59,58,56,52,47,40,34,30,26,25,25,24,25,25,26,27,26,27,29,32,34,36,36,37,39,42,46,48,48,47,46,46,44,40,35,30,27,26,26,27,37,43,51,60,67,75,81,86,83,81,73,62,49,40,37,38,44,47,52,56,58,58,56,54,55,52,49,47,46,44,40,38,30,29,29,33,40,51,62,69,75,72,66,56,45,36,31,29,32,34,36,37,38,39,41,43,51,58,68,75,79,80,81,81,67,64,58,51,46,45,48,51,56,66,77,88,99,108,109,104,96,86,71,61,57,60,64,67,62,61,56,47,38,35,39,44,57,56,53,52,53,55,57,58,67,72,79,86,88,86,81,78,71,65,58,54,54,56,59,60,62,63,64,64,64,66,70,73,72,74,73,67,65,66,64,60,59,57,57,58,61,64,64,64,61,60,57,54,48,43,38,35,34,37,40,43,47,52,59,63,60,58,50,38,25,20,23,28,39,54,67,72,69,63,55,47,39,37,35,34,33,34,36,37,45,49,54,58,57,54,48,44,34,30,25,22,23,28,35,39,41,44,48,48,44,38,33,31,25,27,31,35,38,39,39,39,39,37,34,32,31,29,26,24,21,20,20,22,27,31,33,34,36,36,35,34,32,30,28,27,27,26,23,21,20,19,20,20,20,21,21,20,19,20,22,24,21,25,30,35,37,35,33,31,24,23,21,20,21,22,23,24,25,25,25,24,22,19,16,15,10,10,12,14,16,18,19,20,21,20,20,19,19,18,17,17,15,14,13,12,12,12,13,13,15,14,13,13,12,12,13,13,11,12,12,13,13,12,12,11,10,10,10,11,11,11,12,12,11,11,11,12,12,12,12,12,10,10,9,8,8,8,9,9,7,7,7,6,6,5,5,5,5,5,5,4,4,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,6,6,7,7,7,7,7,7,8,8,9,9,9,11,11,11,11,11,11,11,11,15,16,18,20,21,21,21,21,22,22,21,20,19,17,16,16,16,16,17,17,17,18,18,18,19,20,22,22,21,22,25,27,30,33,38,42,44,48,52,55,57,57,55,52,47,41,35,31,27,27,26,26,27,29,30,31,33,34,35,37,37,37,36,35,36,39,43,46,47,48,48,49,46,43,37,32,28,27,27,28,34,40,47,55,63,70,77,82,80,78,72,61,49,41,37,36,44,47,53,57,60,59,57,55,52,49,46,43,41,39,35,33,29,28,27,30,37,46,56,62,69,67,62,53,44,36,32,31,36,38,40,41,41,42,44,46,55,61,70,77,80,82,83,83,79,74,66,56,47,42,41,42,48,59,73,87,101,111,113,108,99,89,75,66,64,67,71,73,65,62,54,45,38,38,44,49,51,52,52,52,53,57,62,65,78,80,84,86,83,77,70,65,61,57,52,50,51,54,57,58,55,56,57,57,57,59,63,66,69,72,71,67,65,65,63,59,58,56,55,56,60,63,64,64,62,60,56,51,45,40,35,33,33,35,39,43,47,52,58,62,58,56,49,38,26,23,27,33,49,63,77,80,75,67,56,46,35,34,33,33,35,38,42,44,49,52,55,57,56,51,45,41,31,28,24,22,25,31,39,44,53,55,55,51,44,36,30,26,22,25,29,33,36,37,36,35,35,33,30,29,29,28,26,23,22,21,21,23,28,32,34,35,37,36,36,34,33,31,29,28,27,25,23,20,19,19,20,20,21,22,23,22,21,20,21,23,23,27,32,36,38,36,33,31,24,23,21,20,20,21,22,23,23,23,23,23,21,18,16,14,11,11,13,15,17,19,20,21,21,21,20,20,19,18,18,17,14,14,13,12,12,12,12,13,13,13,12,12,11,12,12,13,13,13,14,14,14,14,13,13,12,12,12,13,13,14,14,14,13,13,13,13,13,13,13,13,11,10,9,8,8,8,9,9,7,7,7,6,6,6,5,5,5,5,5,4,4,4,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,6,6,7,7,7,7,7,7,8,8,9,9,9,11,11,11,11,11,11,11,11,13,14,15,17,18,19,19,19,22,22,21,20,19,18,17,16,16,16,17,17,18,18,18,19,19,20,22,22,21,23,25,28,31,34,39,42,44,46,50,52,54,54,54,52,48,43,37,34,29,29,29,29,31,34,36,38,43,44,45,45,43,40,37,35,33,35,39,44,47,50,51,51,49,45,39,33,29,28,29,30,34,39,46,53,60,67,74,79,76,75,69,61,51,42,37,36,44,47,53,59,61,61,59,57,53,49,45,41,39,36,33,30,31,30,30,32,37,45,53,58,65,64,59,52,44,38,35,35,41,43,45,46,46,47,49,51,60,65,72,78,81,83,84,85,86,82,73,61,49,40,36,35,41,53,70,86,101,112,112,107,98,89,77,71,71,74,77,78,65,58,47,37,31,34,42,49,50,51,53,53,54,59,66,73,86,86,86,83,76,67,58,53,49,47,44,45,47,51,53,53,49,49,50,49,49,52,56,59,65,68,69,65,63,63,60,55,54,52,51,52,56,60,62,63,64,60,54,48,41,36,32,31,32,35,39,43,47,52,57,61,58,56,50,39,29,27,33,40,59,73,87,89,82,70,56,44,31,31,31,33,38,43,49,53,55,56,57,56,53,47,41,37,26,24,23,24,29,37,45,50,61,61,59,52,42,33,26,22,20,23,28,32,34,34,32,31,28,26,25,25,26,26,24,23,23,22,21,24,28,32,35,35,37,36,35,34,32,31,30,29,26,24,22,19,18,18,19,20,23,25,26,25,23,21,21,22,27,30,35,38,39,37,34,31,24,23,21,19,19,19,20,21,21,21,22,21,20,17,15,14,12,13,15,16,19,20,22,23,23,22,22,21,20,19,18,18,14,14,13,12,11,11,12,12,12,11,11,10,11,11,12,13,15,15,16,16,16,16,15,15,15,15,15,15,16,16,17,17,15,15,15,15,15,15,15,15,11,11,10,9,8,8,9,9,7,7,7,7,6,6,6,5,5,5,5,5,4,4,4,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,6,6,7,7,7,7,7,7,8,8,9,9,9,11,11,11,11,11,11,11,11,11,12,13,14,16,17,17,17,21,21,20,19,18,17,17,16,16,16,17,17,18,19,19,20,19,20,22,22,22,23,26,29,32,35,39,42,43,45,47,49,49,50,51,51,48,44,39,35,30,30,31,32,35,39,43,46,52,53,54,53,51,46,42,39,33,34,37,42,48,51,52,52,52,47,40,34,29,28,29,30,36,41,48,54,61,67,74,78,74,72,68,62,54,47,42,39,43,47,54,59,62,62,61,59,58,54,49,45,43,40,38,35,38,38,38,39,44,50,57,60,65,64,60,54,47,41,39,39,43,45,48,49,50,52,54,57,64,67,72,76,78,80,82,84,82,79,73,63,52,42,37,35,39,52,69,84,98,106,104,98,90,82,73,70,73,78,79,78,66,56,42,31,28,32,40,46,52,54,55,54,53,58,67,75,83,82,80,76,69,61,53,49,43,41,40,41,44,46,47,47,45,45,45,44,44,47,52,56,60,65,66,64,61,60,55,48,46,44,43,45,50,56,60,62,64,59,52,44,38,33,31,30,34,37,41,44,48,52,58,62,61,59,53,42,32,30,36,42,61,76,89,91,83,69,53,41,29,30,31,35,40,47,54,58,59,59,57,54,48,42,36,33,24,24,25,28,34,43,52,57,61,60,56,48,38,29,24,21,21,25,30,34,36,34,31,28,22,21,20,21,23,24,24,22,23,22,21,23,28,32,34,34,35,34,33,32,30,29,29,28,26,24,21,18,17,18,20,21,26,27,29,27,24,22,21,21,30,33,37,40,40,37,33,30,23,22,20,18,18,18,19,19,19,20,20,20,19,17,15,14,15,15,17,19,21,23,24,25,24,24,23,22,21,20,19,19,15,14,13,12,11,11,11,11,10,10,10,10,11,12,13,13,16,17,17,18,18,17,17,16,16,17,17,17,18,18,18,18,18,18,18,17,17,17,17,17,12,12,10,9,9,8,9,9,8,8,7,7,7,6,6,6,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,6,6,7,7,7,7,7,7,8,8,9,9,9,11,11,11,11,11,11,11,11,10,11,11,12,13,15,16,16,19,19,19,18,17,17,16,16,16,16,17,18,19,20,20,21,18,20,22,22,23,24,27,30,32,36,40,42,43,43,44,45,44,46,49,50,48,44,39,35,30,30,31,34,38,44,49,53,58,60,62,62,59,54,48,44,36,36,38,43,49,53,54,54,53,48,41,33,28,27,28,29,38,43,50,57,62,67,72,76,72,71,67,63,59,54,49,47,45,48,54,59,63,64,64,63,65,61,55,52,50,49,47,45,48,48,48,49,52,57,61,64,65,64,61,55,48,43,41,41,44,47,50,52,53,55,58,61,65,67,69,70,70,72,74,76,74,73,70,63,54,44,38,35,38,50,66,80,92,97,94,86,79,72,66,67,73,78,78,76,68,57,43,35,35,40,46,49,53,53,52,49,49,55,64,71,75,74,71,67,62,56,51,48,44,42,40,40,42,42,41,40,41,41,40,39,39,42,47,51,57,62,65,63,60,57,51,43,40,37,35,37,43,51,56,59,61,57,50,43,37,34,33,33,39,41,43,45,48,53,59,64,66,65,59,47,36,32,35,41,56,69,82,83,75,62,47,36,29,30,33,37,43,49,55,58,60,58,55,50,44,38,33,30,25,26,28,32,39,47,55,59,60,58,53,44,35,27,23,22,27,31,36,40,40,36,31,27,18,17,17,19,22,24,24,24,23,22,21,23,27,31,33,33,33,32,30,28,27,27,27,27,26,24,21,18,17,19,21,23,28,29,29,28,25,22,22,22,33,35,39,41,40,36,31,28,21,20,18,17,16,17,18,19,19,20,21,21,20,19,17,16,17,18,19,21,23,25,27,27,26,26,25,23,22,21,20,19,16,16,14,13,12,12,12,12,11,10,11,11,12,14,15,16,18,18,19,19,19,19,18,18,18,18,18,18,19,19,19,20,20,20,20,19,19,18,18,18,13,13,11,10,9,9,9,9,8,8,8,7,7,7,6,6,6,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,6,6,7,7,7,7,7,7,8,8,9,9,9,11,11,11,11,11,11,11,11,10,10,10,11,12,14,15,16,17,17,16,16,15,15,15,14,16,16,17,18,19,20,21,21,18,20,22,23,23,25,28,31,33,37,41,43,42,41,41,41,40,43,46,48,46,42,37,34,29,29,31,34,40,47,54,58,63,66,68,69,66,60,52,48,39,38,39,44,52,58,59,58,55,50,42,33,28,27,28,29,38,44,52,60,65,68,71,73,71,69,66,64,62,61,58,55,50,52,56,60,64,67,69,70,71,67,63,60,59,60,59,58,61,60,59,59,59,61,63,64,64,64,61,56,50,46,45,45,49,51,54,55,55,57,59,61,62,63,62,61,59,60,62,65,67,68,68,64,55,46,39,35,37,49,62,74,83,87,82,74,66,61,57,62,71,77,75,72,61,52,44,42,48,56,60,61,58,54,48,44,46,51,58,62,66,64,62,58,55,51,49,48,47,44,41,40,40,39,37,36,35,35,34,32,32,36,41,46,53,59,65,65,63,60,52,44,39,36,32,32,37,45,51,54,56,53,48,43,40,38,39,39,45,45,45,45,47,52,59,65,71,70,65,53,41,34,34,38,49,61,71,71,63,52,40,30,27,30,34,40,45,51,55,57,58,55,50,45,39,35,32,30,28,29,31,34,40,46,52,56,60,57,51,42,32,26,25,25,34,38,43,46,44,38,31,26,18,17,18,20,24,26,26,26,25,23,22,24,28,31,33,33,31,30,28,26,25,25,26,26,28,25,21,18,18,20,23,25,29,29,29,26,23,22,23,24,33,36,38,40,38,34,28,25,19,18,16,16,16,17,18,19,20,21,22,23,23,22,20,19,19,20,22,23,26,27,29,30,28,27,26,25,23,22,20,20,18,18,16,14,13,13,13,13,12,12,12,13,15,17,18,19,21,21,22,22,22,22,21,21,19,19,20,20,21,21,21,21,22,21,21,20,19,19,18,18,14,13,12,10,9,9,8,9,9,8,8,8,7,7,7,7,7,6,6,6,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,6,6,7,7,7,7,7,7,8,8,9,9,9,11,11,11,11,11,11,11,11,10,10,10,10,11,13,15,16,15,15,14,14,14,13,13,13,16,16,17,18,20,21,22,22,18,20,22,23,23,25,28,31,34,37,41,43,42,40,39,39,38,40,44,46,45,41,35,32,27,28,29,33,40,48,56,61,69,71,74,74,70,63,54,49,40,38,39,46,56,63,65,64,59,53,44,35,29,28,29,31,40,47,57,66,70,72,72,72,69,66,63,62,64,65,64,62,56,57,59,63,67,72,75,78,79,76,72,71,72,74,75,75,76,74,72,69,66,64,63,62,66,66,64,61,56,54,54,55,57,59,60,59,57,57,58,59,59,58,55,51,48,48,50,53,59,62,66,64,58,50,43,39,42,52,62,69,74,75,68,59,52,47,46,53,64,71,68,63,55,51,50,58,72,84,87,86,76,66,54,46,46,48,50,50,54,53,51,50,50,50,51,52,49,46,41,38,37,37,35,34,32,32,30,28,28,32,38,43,49,57,65,68,68,67,60,52,45,40,34,31,34,39,45,48,51,49,46,44,43,44,45,46,49,48,45,43,44,49,58,64,73,73,69,58,45,36,34,36,46,56,63,60,51,43,34,26,24,28,34,42,48,52,55,55,54,51,46,40,36,33,32,32,30,31,32,35,38,42,46,48,51,49,43,36,29,27,28,30,41,44,49,51,48,40,31,25,20,19,19,22,26,28,29,28,28,26,25,27,30,34,35,35,31,30,27,25,25,25,26,27,29,26,22,19,19,21,25,27,30,29,27,24,21,21,24,27,33,35,37,38,36,31,25,21,16,15,15,14,15,17,19,20,22,23,24,25,25,25,23,22,21,22,23,25,27,29,31,31,29,28,27,26,24,22,21,20,20,19,18,16,15,14,14,14,14,14,15,16,18,20,22,23,25,25,26,26,26,26,25,25,22,22,22,23,23,24,24,24,22,22,21,21,20,19,18,18,15,14,12,11,9,9,8,8,9,9,8,8,8,7,7,7,7,7,6,6,6,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,6,6,7,7,7,7,7,7,8,8,9,9,9,11,11,11,11,11,11,11,11,10,10,10,10,11,13,15,17,13,13,13,13,13,12,12,12,16,16,17,18,20,21,22,23,18,20,22,23,24,25,29,32,34,37,41,43,41,39,38,37,36,39,43,45,44,39,34,30,26,26,28,32,40,49,57,62,73,75,78,77,72,63,54,48,39,38,39,47,58,67,70,69,61,55,46,37,31,29,31,32,44,52,63,72,76,76,76,75,68,64,60,60,63,66,67,66,61,61,62,65,69,75,80,83,87,84,80,80,82,85,87,87,88,86,82,77,72,67,63,61,68,69,69,66,64,62,63,65,64,65,64,62,59,56,56,57,56,54,50,45,41,40,43,45,52,57,63,65,61,55,49,46,50,57,64,67,68,65,56,46,41,37,36,45,57,64,61,55,59,58,63,78,98,113,116,114,96,82,64,52,49,47,44,40,43,43,43,44,47,52,56,58,49,45,40,37,36,36,35,34,32,32,30,28,28,32,38,43,46,56,65,70,73,72,66,58,51,45,37,32,33,36,41,43,47,47,46,45,46,48,49,50,52,49,45,41,41,47,56,63,73,74,71,61,48,38,35,36,46,54,59,54,45,38,30,23,21,26,34,43,49,53,55,55,51,47,42,37,34,32,32,33,31,32,32,34,36,39,41,42,39,37,34,29,26,27,31,35,44,48,52,54,49,40,30,23,21,21,21,23,27,30,30,29,30,29,27,29,32,36,37,38,32,30,28,26,25,26,27,29,30,27,23,19,19,22,26,28,30,29,26,22,20,21,25,28,33,34,37,37,34,29,23,19,14,14,13,14,15,17,19,21,23,24,26,27,27,27,25,25,22,23,24,26,28,30,32,32,30,29,28,26,24,23,21,21,22,21,19,17,16,15,15,15,15,16,16,18,20,22,24,25,28,28,29,29,29,29,28,28,24,24,25,25,25,26,26,26,23,22,21,21,20,19,18,18,15,14,13,11,10,9,8,8,9,9,9,8,8,7,7,7,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,6,6,6,6,6,6,6,6,8,8,8,8,8,8,8,8,12,12,12,12,12,12,12,12,10,10,11,12,12,13,14,14,12,11,10,9,10,11,12,13,14,15,16,17,19,20,21,22,22,22,22,21,21,24,29,33,36,39,43,47,47,44,40,38,38,37,38,39,39,37,32,28,23,23,25,29,36,45,53,58,63,67,71,72,69,61,52,46,36,36,40,48,59,68,71,71,67,58,48,39,31,26,30,36,48,57,67,75,81,84,79,71,67,60,56,60,64,64,65,67,67,65,64,65,70,76,83,88,88,88,88,88,90,93,95,97,101,94,87,80,71,62,60,64,67,69,72,74,75,74,72,71,75,69,66,66,64,58,53,53,49,48,46,41,36,33,33,34,42,53,62,64,63,62,59,55,57,61,66,68,67,60,49,39,28,32,40,47,52,53,52,51,50,61,81,110,140,159,157,146,128,102,83,72,57,50,50,45,40,35,35,41,48,51,55,60,54,47,39,34,34,36,36,35,36,35,33,32,31,33,37,40,49,54,64,75,81,80,73,68,58,50,41,37,33,32,35,41,43,46,49,52,53,56,59,62,55,54,49,42,37,40,50,59,68,71,71,62,49,40,38,41,48,49,54,56,46,29,20,20,23,26,33,42,49,51,50,48,47,42,36,31,30,31,32,32,33,33,32,32,32,32,33,33,31,31,28,24,22,23,29,34,46,49,51,51,48,40,32,27,19,20,23,26,29,31,32,33,32,31,32,35,38,41,42,41,37,33,28,26,27,30,32,32,33,29,25,23,24,26,27,28,29,29,26,22,18,20,25,30,37,37,37,35,30,24,19,15,15,15,16,17,19,21,23,24,28,30,32,34,32,29,24,22,24,24,25,26,28,31,33,34,33,32,30,27,25,23,22,22,21,21,20,18,17,16,15,14,15,17,20,24,27,28,29,29,30,30,31,31,30,29,29,28,29,29,29,29,28,27,26,25,26,24,21,18,17,17,18,19,13,13,12,12,12,11,11,11,8,9,10,11,10,9,8,7,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,6,6,6,6,6,6,6,6,8,8,8,8,8,8,8,8,11,11,11,11,11,11,11,11,10,10,11,12,12,13,14,14,13,12,10,10,9,10,11,12,13,14,15,17,19,21,22,23,21,22,22,21,21,24,29,32,36,39,44,47,48,46,43,40,39,38,38,39,39,36,31,27,23,23,24,28,34,42,50,54,61,64,69,70,67,58,49,42,33,33,36,45,56,64,68,68,64,56,47,40,33,29,32,39,51,60,71,79,85,86,80,71,64,56,51,54,59,61,63,66,66,65,65,66,70,76,82,86,89,89,89,91,93,96,99,101,99,92,84,76,67,59,58,62,69,72,78,82,85,85,83,81,78,72,67,66,63,56,52,51,47,46,43,39,34,31,31,33,41,53,66,71,74,75,73,69,63,66,68,68,65,59,48,40,36,40,46,51,53,51,47,44,53,69,98,135,172,193,192,181,153,125,104,91,75,65,61,53,42,37,36,42,48,52,55,59,53,46,39,35,36,38,38,37,39,38,36,33,33,34,38,40,47,53,63,74,81,81,76,72,62,53,43,37,32,30,34,40,46,50,54,57,59,61,63,65,56,54,49,41,35,38,47,55,62,66,66,59,48,41,43,47,56,58,62,63,53,36,26,24,25,28,33,40,46,49,47,45,44,40,35,32,31,32,32,32,32,31,30,29,29,29,29,29,26,25,23,20,18,20,25,30,41,43,46,46,42,36,28,24,20,21,24,28,31,34,36,36,36,36,35,37,40,42,42,41,38,35,30,28,30,32,34,35,34,30,26,24,24,26,27,27,27,27,25,21,19,21,27,32,37,37,35,32,27,22,18,15,15,15,16,18,20,23,25,26,30,32,34,34,32,29,24,22,24,24,25,27,30,32,34,35,33,32,31,28,27,25,24,24,24,23,22,20,19,18,17,17,17,19,22,25,28,30,31,32,31,32,32,32,31,31,30,29,29,29,30,30,29,29,28,27,25,24,21,18,17,17,18,18,15,15,14,14,14,13,13,13,9,9,10,11,10,9,8,7,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,7,7,7,7,7,7,7,7,8,8,8,8,8,8,8,8,11,11,11,11,11,11,11,11,10,10,11,12,12,13,14,14,13,13,11,10,10,9,10,10,12,13,14,16,19,21,22,23,21,22,22,21,21,23,28,31,35,39,44,49,50,49,46,44,40,40,39,39,38,35,30,26,22,22,23,26,31,38,44,48,55,59,64,66,62,54,44,37,31,31,34,42,53,61,64,64,60,52,45,40,35,32,37,44,55,65,77,86,91,91,82,71,60,51,44,46,51,55,60,65,65,64,64,65,68,74,79,82,86,86,87,89,93,97,100,103,97,88,79,70,61,54,55,60,69,75,84,92,97,97,94,92,82,74,68,65,61,53,49,49,45,44,41,36,31,29,30,32,43,56,71,81,87,90,88,83,75,73,71,69,64,57,49,43,44,48,54,58,57,52,45,40,54,78,117,163,204,227,225,214,184,155,132,117,100,89,79,65,49,43,39,44,50,52,54,57,50,45,39,38,41,44,45,44,45,43,39,37,36,37,39,41,46,52,61,72,80,82,79,76,67,56,44,36,31,28,32,39,47,52,58,62,64,64,65,66,58,55,48,40,34,35,42,49,55,59,60,55,47,45,50,56,69,72,76,75,63,44,32,27,27,29,33,39,44,46,44,42,40,37,34,32,33,33,33,32,30,29,28,26,25,24,24,24,22,21,20,17,16,17,21,25,33,34,36,36,34,29,24,20,21,23,27,31,35,39,41,42,43,42,41,41,43,44,43,41,38,35,31,30,32,35,37,37,35,32,27,24,24,25,26,26,24,24,23,21,21,24,30,34,37,35,32,27,23,19,16,15,16,16,17,20,22,25,28,29,34,34,35,34,32,28,24,22,23,24,26,28,31,34,36,37,34,34,33,31,30,29,28,27,27,26,24,23,22,21,21,21,21,22,25,28,31,33,34,35,33,33,33,33,32,32,32,31,30,30,31,31,31,30,29,29,24,22,20,18,17,17,18,18,17,17,16,16,16,15,15,15,10,11,11,11,10,9,8,8,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,5,5,5,5,5,5,5,5,6,6,6,6,6,6,6,6,8,8,8,8,8,8,8,8,9,9,9,9,9,9,9,9,10,10,10,10,10,10,10,10,10,10,11,12,12,13,14,14,14,14,13,11,10,10,9,9,11,12,14,16,18,21,22,23,21,21,22,21,21,23,27,30,34,38,44,49,52,51,49,47,42,41,39,39,37,34,30,26,23,22,23,24,28,33,38,41,49,53,58,60,57,49,39,33,30,30,32,40,50,57,60,59,53,47,42,39,37,36,42,50,60,72,85,94,99,96,85,73,58,47,38,38,43,48,55,62,61,61,61,62,65,69,73,75,78,79,80,83,87,91,95,98,92,83,72,63,54,49,51,58,67,75,87,98,103,103,99,95,84,75,67,62,57,50,46,47,45,44,41,36,32,30,31,32,45,59,76,88,96,100,97,91,88,82,75,71,65,57,51,48,49,55,62,67,65,58,49,42,55,83,127,177,219,241,237,224,201,175,154,140,126,116,102,82,64,54,48,49,52,52,51,52,45,43,42,45,52,57,58,57,52,48,44,41,40,41,42,42,48,52,60,70,77,80,78,75,67,56,43,35,30,28,33,40,46,51,58,63,64,64,63,63,59,55,48,40,34,35,40,45,50,53,55,52,47,49,58,67,84,88,92,88,73,53,37,29,26,28,32,38,43,45,44,43,36,34,32,32,33,34,33,32,30,29,27,25,24,22,22,22,22,21,20,17,16,17,19,20,24,25,26,27,26,24,21,20,22,24,28,33,38,42,45,47,48,46,44,44,44,44,42,40,36,33,30,30,32,35,37,38,36,32,27,24,23,24,24,24,22,21,21,20,22,26,32,35,36,33,28,22,18,16,15,15,17,17,19,21,24,28,31,32,36,36,35,33,30,26,23,21,21,23,26,29,32,35,37,38,36,36,36,35,34,33,32,31,29,28,26,24,23,23,24,24,25,26,28,31,33,35,36,37,35,35,34,33,33,33,33,33,33,33,33,32,31,29,28,27,22,21,20,19,18,18,19,19,18,18,17,17,17,16,16,16,12,12,12,11,11,10,9,8,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,5,5,5,5,5,5,5,5,6,6,6,6,6,6,6,6,8,8,8,8,8,8,8,8,9,9,9,9,9,9,9,9,10,10,10,10,10,10,10,10,10,10,11,12,12,13,14,14,15,15,14,13,12,11,10,9,11,12,14,16,18,20,21,22,20,21,22,22,21,22,25,28,33,37,43,49,51,51,49,48,43,41,39,38,37,34,30,27,23,23,23,23,26,29,32,34,41,45,50,53,51,45,37,32,29,28,29,35,43,49,50,49,45,40,38,38,38,40,48,56,66,78,92,102,106,102,89,76,58,46,34,33,37,42,50,58,56,56,57,58,60,63,65,67,71,72,73,75,79,83,87,89,84,75,65,56,48,44,47,54,65,74,88,100,106,104,98,94,83,73,63,57,51,45,43,45,46,46,44,40,36,33,33,34,46,60,78,93,105,111,108,101,99,88,79,73,67,58,53,54,57,64,73,78,75,65,53,45,59,87,130,178,217,237,233,221,200,180,166,158,148,141,126,103,81,69,57,55,54,51,47,46,40,41,46,56,66,72,73,71,58,54,48,45,45,46,46,45,51,54,59,66,72,74,73,71,63,53,41,34,29,29,35,42,45,51,58,63,64,62,60,60,57,53,46,39,35,36,40,44,48,51,52,49,46,51,64,75,98,105,109,102,84,63,43,32,24,27,32,39,45,47,47,45,34,33,31,31,33,34,33,32,32,31,29,26,24,23,22,22,24,22,20,19,18,18,18,17,19,19,20,21,21,21,21,21,21,24,28,34,39,44,47,49,50,48,45,44,43,41,38,36,30,28,26,27,30,34,35,36,35,31,25,22,22,23,23,23,22,21,20,20,24,28,32,34,34,30,24,19,15,14,15,16,18,18,20,22,25,29,32,33,36,35,33,30,27,24,22,20,20,22,26,30,34,38,39,40,39,40,40,40,39,37,35,34,30,29,27,25,24,25,26,27,30,30,31,32,34,35,36,37,35,34,33,32,32,32,33,33,35,35,34,32,29,27,24,23,21,21,20,20,20,20,20,20,18,18,18,17,17,17,16,16,14,14,13,12,11,10,10,9,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,5,5,5,5,5,5,5,5,7,7,7,7,7,7,7,7,9,9,9,9,9,9,9,9,10,10,10,10,10,10,10,10,11,11,11,11,11,11,11,11,10,10,11,12,12,13,14,14,15,15,16,16,15,14,12,12,12,13,14,16,17,19,20,20,20,21,22,22,21,22,24,27,31,35,41,47,50,50,48,46,42,40,38,37,36,34,31,28,25,24,23,23,24,25,27,28,34,37,42,45,45,42,38,35,29,27,27,30,36,40,39,37,37,34,33,36,39,43,52,61,72,84,98,108,112,108,95,82,61,48,35,31,34,38,46,53,52,53,54,55,57,58,59,60,65,65,66,67,70,73,77,79,73,65,55,48,42,38,42,49,61,71,85,98,104,102,96,91,79,68,57,50,45,41,41,44,46,47,48,45,41,37,36,36,44,59,78,95,111,120,119,113,104,90,79,74,67,58,55,59,67,75,84,89,85,73,58,47,63,87,124,164,199,219,218,208,187,176,171,169,162,157,142,118,94,79,64,58,56,49,43,39,36,41,52,66,79,86,84,81,63,58,51,49,50,51,50,48,52,53,56,61,66,68,68,66,59,49,38,33,30,29,35,42,47,52,58,61,61,59,57,56,52,47,41,36,35,37,41,45,49,51,50,46,43,49,64,77,105,114,118,110,92,71,49,35,25,28,34,42,48,50,48,46,35,32,30,29,31,33,33,33,33,32,30,28,26,25,24,24,24,23,21,22,23,23,22,20,22,21,20,19,19,20,21,21,20,23,27,33,38,43,46,48,49,46,43,40,39,37,33,31,25,23,22,24,28,31,33,33,32,28,23,20,20,22,22,22,23,21,20,21,24,28,31,31,30,27,22,17,14,14,16,17,19,20,21,23,26,29,31,33,34,33,30,26,23,21,19,19,21,24,28,34,38,42,44,44,43,44,44,44,42,40,38,36,33,31,29,27,26,27,29,30,34,33,33,32,33,33,34,35,34,33,31,30,29,30,31,32,34,33,32,30,27,24,22,20,21,21,21,22,22,22,22,22,19,19,19,18,18,18,17,17,16,15,13,12,11,10,10,10,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,5,5,5,5,5,5,5,5,7,7,7,7,7,7,7,7,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,11,11,11,11,11,11,11,11,10,10,11,12,12,13,14,14,15,16,17,18,17,16,15,14,14,14,15,16,17,17,18,18,19,21,22,22,21,22,24,25,29,33,39,45,47,47,45,43,41,39,37,36,36,35,32,30,27,26,24,23,23,23,24,24,28,31,35,39,41,41,40,39,34,31,29,31,34,35,33,30,30,28,29,35,39,45,54,64,76,88,102,112,116,112,100,87,66,52,38,32,33,36,42,49,50,51,53,54,56,56,56,55,58,58,57,58,59,61,64,65,61,54,46,41,35,32,36,43,51,61,76,90,97,96,91,86,74,63,51,44,40,37,39,43,45,48,50,49,45,40,37,36,44,57,75,93,110,121,120,114,103,88,77,73,67,56,55,60,71,80,91,98,95,82,66,55,60,78,106,136,165,183,185,179,169,165,169,171,164,160,145,120,100,83,66,59,55,48,40,35,35,43,57,75,89,94,90,84,67,61,54,51,53,55,54,51,50,50,52,56,61,64,64,64,56,47,37,33,29,28,33,39,46,50,54,56,55,52,50,50,44,40,34,32,33,37,42,45,50,51,48,42,38,45,61,74,98,109,116,109,92,72,51,35,27,31,39,47,52,52,48,44,36,33,29,27,29,31,33,33,33,32,30,28,27,26,26,25,26,25,26,29,33,35,34,32,30,28,25,21,19,18,19,19,18,21,25,31,36,40,43,45,45,42,39,36,34,32,28,26,21,20,20,22,26,30,32,32,29,25,21,18,19,21,21,21,26,23,20,21,25,28,29,28,27,24,20,16,15,15,17,19,20,21,22,23,25,28,30,32,31,29,26,22,19,18,18,18,24,27,33,39,44,47,49,50,47,47,48,47,45,42,39,37,36,34,31,29,29,30,32,34,36,35,33,32,31,31,31,32,32,31,29,27,27,28,29,30,29,28,28,27,25,23,21,20,21,22,23,24,24,24,24,24,21,21,21,20,20,20,19,19,17,16,14,12,11,10,11,11,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,5,5,5,5,5,5,5,5,7,7,7,7,7,7,7,7,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,12,12,12,12,12,12,12,12,10,10,11,12,12,13,14,14,15,16,18,19,19,18,17,16,15,15,15,16,16,17,17,17,19,21,22,22,21,22,23,25,28,32,38,43,46,45,43,41,41,39,37,36,36,35,33,31,28,27,25,24,22,22,22,22,25,28,31,36,39,41,42,43,41,37,34,34,36,36,33,29,27,25,27,34,39,45,56,66,79,91,104,113,118,115,103,91,69,55,40,34,33,35,41,46,50,51,53,55,56,55,55,54,51,51,50,49,50,52,53,55,53,46,40,35,31,28,32,39,42,52,67,82,90,90,86,82,71,59,47,41,37,35,38,43,44,48,51,51,47,42,37,35,45,57,73,90,106,116,115,108,101,86,74,72,65,55,54,61,69,79,93,102,101,90,74,64,54,67,87,110,134,150,153,148,155,156,165,168,161,156,141,116,101,84,66,58,54,47,38,34,35,44,61,80,93,96,90,84,68,62,55,53,55,57,56,53,48,48,49,53,58,62,63,63,55,46,37,33,29,27,31,36,43,46,49,50,48,46,44,44,38,34,30,28,31,37,42,45,51,50,46,39,35,41,57,71,88,101,109,103,88,70,49,32,30,35,42,50,55,53,47,42,37,33,28,26,27,30,32,33,32,31,30,28,27,26,26,26,30,30,31,37,43,46,46,44,38,34,29,23,19,17,17,17,17,20,24,29,34,38,41,43,42,39,36,33,31,29,25,22,19,18,19,21,26,30,32,32,27,23,19,17,18,20,21,21,27,24,21,22,25,27,27,26,24,22,19,16,15,16,18,20,21,21,22,23,25,27,29,30,29,27,23,19,17,16,16,17,26,30,36,42,48,51,53,54,49,49,50,49,47,43,39,37,38,36,33,31,31,33,35,37,38,36,34,31,29,29,29,29,31,30,27,25,25,26,28,29,24,24,25,25,24,23,22,22,22,22,23,25,25,26,25,25,23,23,23,22,22,22,21,21,18,17,14,12,11,10,11,11,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,6,6,7,7,8,8,8,7,8,10,11,12,11,10,9,10,11,11,12,12,11,11,10,12,12,13,13,14,15,16,16,14,13,12,11,11,11,11,12,14,15,17,19,20,20,20,19,21,20,18,16,15,15,16,16,17,18,20,22,23,23,23,22,27,29,33,36,38,38,38,37,36,36,37,37,36,36,35,34,32,30,27,24,22,21,21,21,24,28,32,35,37,39,42,44,47,46,45,42,38,34,30,28,28,26,27,34,41,47,56,64,76,87,100,110,115,115,105,94,71,56,40,33,32,33,38,43,47,48,49,51,54,53,50,48,48,45,43,43,44,46,46,45,43,39,34,29,27,29,31,34,38,47,56,64,75,85,84,76,71,57,44,37,31,29,35,45,45,50,55,56,51,45,41,39,41,53,68,83,97,107,108,103,86,79,70,63,59,58,58,58,65,79,96,103,101,94,80,69,59,59,66,82,99,112,123,132,137,149,160,164,159,146,127,111,87,74,61,56,52,44,34,29,34,43,60,78,90,91,84,77,61,58,56,56,57,56,52,49,46,44,42,45,51,55,57,56,55,47,38,32,27,23,25,30,37,42,46,45,45,46,43,38,37,29,23,25,29,34,42,49,56,51,47,43,35,32,43,57,75,84,94,93,80,61,45,37,35,38,44,51,57,56,51,45,34,30,26,24,26,29,31,32,29,28,26,25,25,26,27,28,32,37,44,51,56,57,55,54,46,40,31,23,19,17,16,16,14,16,21,26,30,33,35,36,34,33,32,30,29,27,25,25,21,20,21,23,26,28,27,26,24,21,17,16,19,23,26,27,30,27,23,22,23,24,25,25,20,19,18,17,17,19,20,21,21,20,20,20,21,23,25,27,26,23,19,16,15,16,17,19,29,33,39,46,50,53,54,54,53,51,47,44,41,41,41,41,35,34,32,31,32,35,39,41,39,37,33,29,26,24,23,22,26,26,25,24,23,22,21,20,21,22,23,24,25,26,26,25,23,24,24,25,27,29,31,32,29,27,24,24,24,25,23,22,20,17,14,12,12,13,12,11,9,8,7,6,6,6,6,7,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,6,6,7,7,8,8,8,8,9,10,11,12,11,10,10,10,11,12,12,12,12,11,10,12,12,13,14,15,15,16,16,14,14,13,12,11,11,11,11,12,14,16,19,20,21,21,21,22,20,18,17,15,15,16,16,17,18,20,21,22,22,22,21,25,27,30,33,34,35,34,33,34,35,36,38,38,37,36,35,33,31,29,26,24,23,23,23,23,26,30,33,36,40,45,48,49,49,48,46,42,36,31,28,26,24,26,33,40,46,54,62,73,83,96,104,110,109,100,89,69,55,40,34,33,34,38,43,47,47,49,52,55,55,53,51,45,41,37,35,36,38,39,39,39,36,32,29,28,29,31,33,34,42,50,58,69,80,81,75,71,58,45,37,32,30,35,43,47,52,56,57,52,45,40,38,38,49,63,76,89,97,97,92,79,73,65,59,57,57,57,58,68,81,96,105,106,99,84,70,51,49,52,65,80,93,106,116,129,140,152,154,147,133,113,96,79,67,56,53,51,43,35,30,36,44,59,74,84,85,78,71,58,56,55,55,55,53,48,44,34,33,35,40,48,55,58,59,56,48,39,34,29,24,26,30,36,43,49,51,52,54,50,45,39,30,23,24,29,35,43,51,57,54,51,46,37,32,38,49,58,67,76,76,66,51,39,33,36,39,46,53,58,57,51,46,34,30,26,24,25,27,28,29,26,25,23,23,24,27,29,31,39,44,51,59,63,64,62,60,50,43,34,26,21,18,16,15,16,18,21,25,28,30,32,32,33,32,30,28,26,25,24,24,22,22,22,24,27,29,28,26,23,20,17,18,22,26,30,31,33,29,25,22,23,23,24,23,21,20,19,19,19,20,22,23,19,19,19,19,21,23,25,26,25,22,19,16,16,17,19,21,31,35,41,48,52,54,53,52,49,47,43,40,38,38,38,39,35,34,33,32,33,35,38,40,39,37,33,28,25,22,21,21,24,24,23,22,22,21,20,20,20,21,22,24,25,26,27,27,24,24,25,26,28,30,31,33,31,28,26,25,25,25,24,23,21,18,14,12,12,12,11,10,9,8,7,6,6,6,6,7,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,6,6,7,7,8,8,8,8,9,10,11,11,11,11,10,11,11,12,13,13,12,11,11,13,13,14,14,15,16,17,17,16,15,14,13,12,12,11,11,11,12,15,18,20,22,23,23,22,21,20,18,17,16,16,16,16,17,18,20,20,21,20,20,23,25,27,29,30,29,29,28,30,33,36,39,41,40,39,37,35,34,31,28,26,25,24,25,21,23,26,30,34,39,46,51,52,52,52,50,45,38,31,27,23,21,23,31,38,43,51,58,67,77,88,95,99,98,90,80,64,51,39,35,34,35,38,43,45,46,47,51,55,57,56,54,44,39,33,29,29,31,32,33,34,33,31,29,29,29,31,31,31,36,43,50,61,72,77,76,74,64,52,43,37,35,38,44,50,54,58,58,53,46,39,35,35,45,57,68,79,86,85,79,69,64,59,55,55,56,57,57,69,80,94,103,107,102,86,70,52,46,44,53,66,81,97,109,128,139,149,149,140,123,100,82,66,56,48,48,47,42,36,33,38,45,56,68,75,74,69,63,54,53,54,54,53,48,42,37,27,28,31,38,47,55,60,62,59,50,42,37,32,27,27,31,34,43,53,58,62,65,61,55,45,35,27,26,30,36,45,53,60,60,58,53,43,34,33,38,41,47,54,55,49,41,34,32,37,41,47,54,58,57,51,46,34,31,27,26,26,27,26,26,22,21,20,21,24,29,34,38,47,51,58,65,68,67,65,63,51,44,35,27,22,19,16,14,18,19,21,24,26,27,28,28,31,29,27,24,23,22,23,23,23,22,23,25,28,29,28,26,20,19,18,21,26,31,35,37,37,32,27,23,22,22,22,21,21,21,21,20,21,22,23,24,17,17,17,18,20,23,25,26,23,22,19,17,17,19,22,24,33,38,44,51,54,53,51,49,41,39,37,34,33,33,34,35,35,35,34,33,34,35,37,39,37,35,31,26,23,20,19,18,22,21,21,20,20,19,18,18,19,20,21,23,25,27,28,29,26,26,26,27,29,31,33,34,33,30,28,26,27,26,25,23,22,19,15,12,12,11,10,8,9,8,7,6,6,6,6,7,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,6,6,7,7,8,8,8,9,9,10,10,11,11,11,11,12,12,13,13,13,13,12,12,14,14,14,15,16,17,17,18,17,17,16,16,15,13,12,11,11,12,14,17,20,22,24,25,23,22,21,20,18,17,17,16,16,17,17,18,19,19,19,19,23,23,25,26,26,26,25,24,27,31,36,41,44,45,43,42,39,37,33,30,27,26,25,25,22,23,24,26,30,36,44,49,52,53,53,51,46,38,30,25,21,19,21,29,35,40,47,54,60,68,77,82,85,85,77,67,56,45,35,33,34,34,36,40,41,41,44,49,54,57,58,57,48,42,34,28,27,29,32,33,32,32,32,31,31,31,31,31,30,33,38,45,55,66,75,78,80,73,63,54,48,45,46,48,53,56,58,58,53,46,38,33,33,42,53,62,72,78,76,70,60,56,53,52,54,56,58,58,65,75,87,98,104,100,84,67,54,46,42,49,62,79,97,112,130,140,148,145,134,114,90,71,53,45,40,42,43,40,36,36,41,46,54,62,66,65,60,57,51,52,52,52,48,42,35,30,28,30,35,43,51,58,63,65,62,54,47,42,36,30,29,32,33,45,58,67,74,77,74,68,58,46,36,33,34,39,47,56,65,67,68,63,52,40,34,33,33,37,40,40,37,34,33,33,36,40,46,52,55,53,48,44,36,33,31,30,30,29,27,24,21,20,19,21,26,34,42,47,53,56,61,64,65,62,58,55,44,39,31,25,21,19,17,16,19,20,21,23,24,26,27,27,29,27,24,22,20,20,21,22,22,21,22,24,26,27,26,24,19,18,20,24,31,37,41,42,40,35,28,23,21,20,20,19,20,20,20,21,21,22,23,24,15,16,17,19,21,23,24,25,23,21,19,18,19,21,24,27,35,40,46,52,53,51,47,43,33,31,29,27,27,28,29,31,35,35,34,34,34,35,35,36,35,32,28,24,20,17,16,16,18,18,18,18,18,17,17,17,18,19,20,22,25,27,30,31,28,28,28,29,31,33,35,36,35,33,30,28,28,27,25,24,23,19,15,12,11,10,8,7,9,8,7,6,6,6,6,7,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,6,6,7,7,8,8,8,9,9,9,9,10,10,11,11,13,13,14,14,14,14,13,13,14,15,15,16,17,18,18,18,18,19,19,19,18,16,15,14,13,13,15,17,19,21,23,24,22,22,22,21,21,20,19,18,17,17,17,17,17,18,18,19,22,23,23,24,24,23,23,23,26,30,36,43,48,49,49,48,44,41,37,33,30,27,26,26,24,24,24,24,26,32,39,45,51,51,51,49,43,35,27,22,20,18,20,27,33,36,42,48,53,59,65,68,70,70,63,54,46,37,30,31,33,33,33,36,35,36,39,45,52,57,59,60,52,46,37,31,30,33,36,37,36,36,36,36,35,35,34,33,33,33,37,44,53,64,75,82,84,81,75,67,60,56,54,51,56,56,57,56,52,45,37,32,29,38,47,56,64,70,68,62,53,51,50,50,54,57,58,58,62,71,82,92,99,97,82,67,52,44,39,46,59,77,96,111,126,135,141,136,123,104,79,61,45,38,34,36,38,37,36,38,43,48,54,59,61,59,56,55,51,52,52,49,43,36,30,26,29,34,42,51,59,64,68,70,66,59,53,48,42,34,32,34,37,50,66,78,87,92,88,82,72,60,48,42,42,44,51,58,69,74,77,73,63,52,42,37,35,35,33,31,30,29,31,32,33,37,42,46,47,46,43,41,38,37,36,36,35,33,29,26,22,21,22,25,31,40,49,54,59,60,60,59,56,52,47,44,33,29,24,21,20,20,20,19,21,22,22,23,24,26,27,28,27,25,23,21,20,20,20,21,20,20,20,22,24,25,23,22,18,19,22,28,35,41,44,45,40,35,27,21,19,19,19,18,18,18,19,20,21,22,22,23,17,17,19,21,23,24,25,25,23,21,19,19,20,23,27,29,36,40,46,50,50,46,40,36,25,24,22,21,22,24,26,28,33,34,34,34,34,33,33,32,30,28,25,21,17,15,14,14,15,16,16,16,16,16,17,17,18,18,20,21,24,28,30,32,30,30,30,31,33,35,37,38,37,35,31,29,28,27,25,23,22,19,15,12,11,10,8,6,9,8,7,6,6,6,6,7,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,6,6,7,7,8,8,8,10,9,9,9,9,10,11,12,13,14,15,15,15,15,14,13,15,15,16,17,18,18,19,19,19,20,21,22,22,20,19,17,16,16,16,17,18,19,21,22,21,21,22,23,23,22,21,21,19,18,17,17,17,18,18,19,21,21,21,21,22,22,22,22,26,30,37,44,50,54,56,56,51,49,44,38,34,30,28,27,27,27,26,26,27,31,37,42,49,49,48,45,40,32,25,21,21,19,21,27,31,33,37,43,46,51,55,56,57,56,50,41,38,31,27,29,33,32,32,33,31,32,35,42,51,58,61,63,56,51,43,38,38,41,44,45,46,45,44,42,40,39,38,37,37,36,39,46,54,63,75,86,86,88,87,80,74,69,63,56,58,56,54,52,49,44,37,32,28,36,44,50,58,63,60,54,49,48,47,50,53,56,57,57,59,67,78,86,92,92,81,70,53,46,42,49,61,76,92,105,117,125,130,126,114,97,76,59,42,35,30,31,33,33,36,40,44,49,55,60,60,59,57,57,55,54,51,45,38,31,27,26,29,38,50,61,68,72,75,76,71,65,59,54,48,39,35,37,43,56,73,86,96,102,99,93,82,70,57,52,50,50,55,62,71,78,82,79,72,65,55,47,39,36,31,27,25,26,28,30,31,34,38,39,39,38,38,39,40,39,40,41,41,38,32,28,23,24,25,29,36,45,53,58,62,60,57,52,46,41,36,34,24,22,19,19,21,24,25,26,27,27,26,25,25,26,27,27,25,25,24,24,23,22,21,20,20,19,19,20,22,23,22,20,19,20,24,30,38,43,45,45,38,32,25,19,17,18,19,19,17,18,19,21,22,22,22,22,20,21,23,24,25,26,26,26,24,22,21,20,21,24,28,30,36,39,43,45,43,39,33,29,20,19,18,17,19,21,24,26,32,32,33,34,33,32,30,28,26,24,21,17,15,14,13,13,14,14,14,15,15,16,17,17,19,19,20,21,24,27,30,32,32,32,32,33,35,37,39,40,38,36,32,29,28,27,24,22,21,18,14,11,10,10,8,7,9,8,7,6,6,6,6,7,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,6,6,7,7,8,8,8,10,10,9,8,9,10,11,12,14,14,15,16,16,15,14,14,16,16,17,17,18,19,20,20,20,21,23,25,25,24,23,21,20,19,18,17,17,17,18,19,19,20,22,24,24,24,24,23,20,19,18,17,17,18,19,20,19,18,18,19,19,20,21,22,27,31,37,45,52,58,61,63,60,57,51,45,39,34,32,30,29,29,30,29,30,33,39,43,48,47,46,42,37,31,25,21,23,20,22,27,30,31,34,39,40,44,46,46,46,46,40,32,33,27,25,30,34,33,31,32,29,30,34,42,51,60,64,66,63,58,52,49,49,53,56,57,57,55,52,48,45,43,42,41,41,39,41,49,55,63,76,89,92,98,101,96,91,85,74,64,59,55,51,48,46,43,37,33,33,39,46,50,56,59,56,49,46,45,46,48,52,54,54,53,53,63,73,79,83,84,78,70,58,51,48,54,63,72,82,92,99,107,113,111,103,91,74,60,43,36,29,29,29,30,35,41,44,50,57,62,63,62,61,62,60,57,51,42,33,27,27,28,38,49,63,75,80,81,80,80,75,69,64,60,53,43,39,39,43,57,73,86,97,103,101,96,85,74,63,58,56,56,60,66,70,78,84,82,79,75,68,59,44,39,31,26,24,25,28,30,31,33,35,34,32,32,35,38,39,40,42,44,44,40,34,29,24,25,28,33,40,48,55,59,60,56,49,42,35,30,27,26,22,20,19,21,25,29,32,32,36,34,31,28,26,25,25,25,24,25,26,27,26,24,22,20,20,20,19,21,23,23,22,20,20,22,26,32,39,43,44,44,35,29,22,17,16,17,19,20,17,18,20,22,24,24,24,24,24,25,26,28,28,28,27,27,25,24,22,21,22,25,28,31,36,37,39,39,36,31,26,23,16,15,15,15,17,20,24,26,30,31,32,33,32,30,27,25,22,20,17,15,13,13,13,13,13,13,14,14,15,16,17,17,20,20,20,21,23,26,30,32,33,33,34,35,36,38,40,41,39,36,32,29,28,26,23,21,19,16,13,11,10,10,9,8,9,8,7,6,6,6,6,7,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,6,6,7,7,8,8,8,11,10,9,8,9,10,12,13,14,15,15,16,16,15,15,14,16,16,17,18,19,19,20,20,20,22,24,26,27,27,25,24,23,21,19,17,16,16,16,17,18,20,22,24,25,26,25,25,21,20,19,18,17,18,19,20,16,16,16,17,18,19,20,21,28,32,38,45,53,60,65,67,66,63,57,49,43,38,34,33,30,31,32,32,34,37,42,46,47,46,44,41,36,30,26,23,24,22,23,27,30,30,32,36,37,41,42,41,40,40,34,27,31,26,25,31,35,34,32,32,28,30,34,42,52,61,67,69,70,65,60,58,60,63,66,67,64,61,57,52,48,45,44,43,43,40,43,51,56,62,75,89,98,107,112,108,103,97,85,72,59,55,49,46,44,42,38,34,40,45,51,54,57,59,55,48,44,43,44,47,50,52,52,50,47,57,68,73,75,76,73,68,58,52,49,53,59,63,70,76,80,88,95,95,90,81,68,56,45,37,29,27,27,29,35,42,43,50,59,64,65,64,64,65,63,60,52,40,30,26,27,30,50,61,76,87,89,86,82,80,78,72,67,63,55,46,40,41,40,53,69,82,92,99,98,93,84,74,64,61,60,60,64,69,68,77,83,82,81,81,75,67,48,42,34,27,26,28,31,33,31,33,33,31,29,30,34,38,38,39,42,45,45,41,35,30,24,26,29,34,41,48,54,58,55,50,42,33,26,22,21,20,23,22,22,24,29,33,36,37,42,40,35,31,27,24,23,22,24,25,28,29,28,26,22,20,22,21,21,22,24,24,22,21,21,23,27,33,40,43,43,42,32,27,20,15,15,17,20,21,18,19,22,24,25,26,25,25,27,28,29,30,30,29,28,27,26,24,22,21,22,25,28,31,35,36,36,35,32,27,22,19,14,14,13,14,16,20,24,26,28,30,32,33,31,28,25,23,19,18,16,14,13,12,13,14,12,13,13,14,16,17,17,18,21,21,20,21,23,26,29,31,34,34,34,36,37,39,41,42,39,36,32,29,27,25,23,20,18,15,12,10,10,11,10,9,9,8,7,6,6,6,6,7,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,6,6,6,7,7,8,8,8,8,8,8,9,9,10,10,10,14,14,13,13,13,14,15,16,17,17,17,18,18,19,19,19,23,25,27,28,29,29,29,28,26,25,23,20,18,16,16,15,15,17,20,24,26,27,28,28,27,25,24,22,20,19,19,19,17,17,17,17,18,19,20,21,27,29,33,40,49,59,68,72,71,68,62,53,44,38,36,36,34,36,39,40,40,41,44,46,49,48,46,42,37,32,27,24,25,27,29,31,33,33,33,33,31,32,33,35,36,35,33,30,29,28,29,33,33,30,31,35,33,34,39,49,58,63,66,69,65,65,66,67,68,70,73,76,69,66,62,56,51,46,43,41,37,42,47,50,54,62,73,83,97,111,120,116,110,104,87,68,56,49,40,37,38,42,43,44,49,50,53,58,63,61,55,50,45,42,41,45,50,51,48,43,43,55,60,62,80,102,94,70,68,63,58,58,59,58,53,48,56,60,66,71,72,69,65,62,50,44,35,31,31,33,34,34,44,48,55,62,67,70,71,72,66,61,51,38,28,27,36,44,63,71,82,90,91,88,83,80,75,76,73,65,56,50,41,33,38,46,59,73,82,87,86,85,75,71,65,62,61,62,62,61,67,69,75,80,83,81,75,70,56,44,31,27,26,27,31,36,39,39,38,35,32,31,33,35,38,40,43,44,42,38,32,29,28,30,34,39,42,45,46,47,43,37,29,23,23,25,28,29,30,30,31,34,37,41,45,48,49,48,45,39,31,25,22,21,26,28,31,33,34,33,30,29,26,24,24,24,25,24,22,20,18,21,26,34,41,43,42,41,31,27,22,20,19,20,20,20,23,23,23,26,29,31,30,29,33,33,33,32,30,27,24,22,22,22,21,23,26,29,30,30,38,38,36,33,29,23,18,15,11,12,14,16,19,20,21,22,30,30,31,31,29,26,22,20,13,13,12,11,11,11,12,12,15,15,15,16,17,18,19,20,22,23,23,23,22,24,27,30,33,34,36,38,40,41,41,42,37,35,32,29,27,23,19,15,16,15,12,10,9,10,11,12,9,9,9,8,8,7,7,7,5,5,5,5,5,5,5,5,5,5,5,4,4,3,3,3,5,5,5,4,4,3,3,3,4,4,4,3,3,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,6,6,7,7,7,8,8,8,8,8,8,9,9,9,10,10,13,13,13,13,13,14,15,16,17,17,18,18,19,20,20,20,22,23,25,27,28,28,28,28,27,25,23,21,19,17,16,16,15,16,19,22,25,26,27,27,26,25,24,23,21,20,19,19,17,17,16,16,16,18,19,20,26,28,33,40,49,59,67,72,72,69,62,53,44,38,36,37,37,40,43,46,46,48,50,52,55,54,52,48,43,37,32,29,29,30,32,34,34,33,32,31,29,30,31,33,35,35,34,32,34,31,31,33,31,29,31,37,45,48,55,63,68,69,67,65,64,65,67,68,69,71,73,75,70,68,63,57,51,47,43,42,39,43,48,51,54,61,71,79,95,109,119,116,110,102,84,65,49,43,37,36,40,46,50,51,59,59,61,64,67,64,56,50,43,41,40,42,47,48,45,41,44,53,58,62,77,93,89,72,72,67,63,61,61,57,50,44,44,48,54,59,62,62,61,59,53,47,40,35,34,34,33,32,43,47,53,61,67,71,73,74,68,63,52,39,29,30,38,46,64,71,81,87,88,84,79,76,72,75,74,66,59,52,43,34,34,41,53,66,76,80,80,78,71,67,61,58,57,58,58,58,59,61,67,73,78,78,75,72,58,46,33,28,27,29,34,40,44,44,43,41,37,34,34,35,37,39,42,43,41,36,31,28,24,26,30,34,37,38,39,39,36,32,26,24,26,30,33,35,40,39,39,40,43,48,53,56,55,54,51,44,36,30,26,25,28,31,35,38,38,37,34,31,29,27,26,26,27,27,25,23,19,21,26,33,38,41,40,38,32,29,24,22,23,24,24,24,26,25,26,28,31,33,33,32,33,33,32,30,28,25,23,21,22,23,24,27,30,31,32,31,37,37,36,34,29,24,18,15,14,15,17,19,20,21,22,23,29,29,30,30,28,24,21,19,13,12,12,11,11,12,12,13,16,16,16,16,17,18,19,20,21,22,23,22,22,23,27,30,32,34,36,38,40,42,42,42,37,34,31,28,26,23,19,15,16,15,12,10,9,10,11,12,9,9,9,8,8,7,7,7,5,5,5,5,5,5,5,5,5,5,5,4,4,3,3,3,5,5,5,4,4,3,3,3,4,4,4,3,3,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,6,6,6,6,6,6,6,6,7,7,7,8,8,8,8,7,7,8,8,9,9,9,9,11,11,11,12,13,14,16,17,17,17,18,19,20,21,22,22,21,22,24,25,27,27,28,28,27,26,24,21,19,18,17,17,14,15,18,21,23,25,26,26,26,26,25,25,24,22,21,20,17,16,15,15,15,16,17,18,25,27,32,40,49,58,66,70,72,69,62,53,44,39,37,38,42,45,50,53,55,57,59,61,61,60,58,53,48,42,37,33,34,35,37,38,37,34,30,28,27,28,29,31,33,34,35,36,40,37,35,34,30,27,31,39,53,62,74,82,84,78,68,61,60,61,63,65,68,69,70,71,68,66,62,56,51,47,44,43,42,46,50,53,55,60,68,74,90,104,114,113,107,96,76,58,38,35,33,37,46,56,63,65,73,72,71,71,70,64,55,47,41,39,37,39,43,43,41,37,37,42,48,56,67,76,76,70,74,71,68,66,63,57,48,40,36,39,43,47,51,54,56,57,55,51,46,42,39,37,34,31,40,44,51,59,66,71,74,75,70,64,53,40,32,32,40,48,65,70,77,81,80,76,72,69,69,73,75,70,64,57,46,37,31,37,46,58,68,73,73,71,66,61,55,51,51,52,53,53,49,51,56,63,70,74,74,73,61,49,35,29,28,30,37,45,51,52,52,49,44,39,37,36,37,39,40,41,39,34,29,26,23,24,27,30,32,33,33,32,28,26,25,27,32,39,43,45,50,48,45,44,47,53,59,63,64,62,58,51,41,34,30,28,30,33,39,43,44,41,37,34,33,31,29,29,30,30,28,26,21,22,26,31,35,38,36,35,33,30,27,26,27,28,28,28,28,28,28,30,33,35,35,34,33,32,30,28,26,23,21,20,23,26,29,33,35,35,34,33,37,37,37,35,32,26,21,17,19,19,20,21,22,22,23,23,27,28,28,28,26,22,19,16,13,12,12,11,11,12,13,13,16,16,17,17,18,19,19,20,20,21,22,22,21,23,26,29,32,33,36,39,41,42,43,43,36,33,29,26,24,22,18,15,16,14,12,11,10,10,11,12,9,9,9,8,8,7,7,7,5,5,5,5,5,5,5,5,5,5,5,4,4,3,3,3,5,5,5,4,4,3,3,3,4,4,4,3,3,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,6,6,6,6,6,6,6,7,7,7,7,7,7,7,7,7,7,7,8,8,8,9,9,7,8,8,8,9,9,9,9,10,10,10,11,12,14,15,16,17,17,18,19,21,22,23,24,21,21,22,24,25,26,27,27,27,25,24,21,20,18,18,18,13,15,17,19,22,24,25,26,26,27,28,29,28,26,24,23,19,17,15,14,14,15,17,18,24,27,32,39,48,56,63,67,70,67,60,51,42,38,37,38,44,49,55,60,62,64,66,67,64,63,60,56,50,44,39,35,38,40,41,41,39,35,30,27,27,28,29,30,31,33,37,40,47,44,41,37,29,24,30,40,56,71,89,99,98,87,71,58,50,52,54,58,62,63,62,61,59,58,56,53,50,47,45,44,45,48,53,56,58,61,66,70,83,95,105,106,99,85,65,48,30,30,33,43,57,71,79,83,86,82,78,75,71,63,52,44,39,37,36,36,38,38,36,34,32,34,41,52,59,63,67,73,73,73,73,72,69,61,51,43,41,40,40,42,44,48,51,54,54,53,51,49,45,41,36,33,37,41,48,56,64,70,74,75,68,62,51,40,33,34,41,47,61,65,69,71,68,64,61,59,65,71,76,74,69,62,52,41,33,36,44,55,65,71,72,70,62,56,50,46,45,46,47,47,42,44,47,54,62,68,71,72,63,51,37,30,28,30,39,48,57,59,60,57,51,45,40,39,38,39,40,40,37,32,27,24,23,25,27,29,30,30,30,29,24,24,27,33,42,49,54,56,54,51,46,44,46,52,60,66,71,69,64,55,44,35,30,28,30,35,41,45,46,43,38,35,33,32,30,31,32,32,30,28,23,23,25,29,33,35,34,33,33,31,30,30,31,32,31,30,29,28,27,29,32,35,35,35,33,31,28,26,23,21,20,20,25,30,36,40,41,39,37,35,38,39,40,39,36,30,25,22,22,22,21,21,21,21,22,22,26,26,27,26,24,20,16,14,12,12,11,11,11,12,13,14,17,17,18,19,19,20,20,19,19,20,21,21,21,23,26,29,31,33,36,40,42,42,42,42,34,31,27,24,22,20,17,15,15,14,13,11,10,10,11,11,9,9,9,8,8,7,7,7,5,5,5,5,5,5,5,5,5,5,5,4,4,3,3,3,5,5,5,4,4,3,3,3,4,4,4,3,3,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,6,6,6,6,6,6,6,7,7,7,7,7,7,7,7,7,7,8,8,8,9,9,9,8,8,9,9,9,10,10,10,10,10,10,10,11,13,14,15,15,16,17,19,21,23,24,25,22,22,22,23,24,25,26,26,26,25,23,21,19,18,18,18,14,14,16,18,21,23,25,26,28,30,33,34,34,32,29,27,22,20,17,15,14,15,17,19,25,27,32,39,47,54,60,63,65,61,55,46,38,35,35,37,44,50,57,63,66,68,69,70,66,64,62,58,52,46,41,38,41,42,43,42,40,36,32,29,30,31,31,30,30,33,39,43,53,52,50,43,31,24,30,41,63,83,105,114,109,94,71,53,39,40,44,50,54,55,52,49,47,48,49,50,49,48,47,46,46,50,55,59,62,64,66,67,77,85,93,94,86,71,52,38,27,29,38,53,71,87,95,98,98,92,84,77,70,62,52,44,39,37,35,34,34,34,33,31,33,34,42,53,58,60,67,77,72,74,77,79,76,70,61,54,50,47,43,40,39,41,45,47,52,53,54,53,49,44,39,36,35,38,44,52,59,65,70,72,64,58,49,39,34,34,40,44,54,56,58,57,54,51,49,49,60,68,75,76,73,67,56,46,38,39,44,54,66,73,75,73,61,55,48,42,41,42,43,43,41,42,45,50,58,65,68,70,64,52,40,32,28,29,38,48,59,61,62,61,55,49,44,42,42,42,42,40,36,30,25,22,22,24,26,28,29,30,29,29,27,29,34,42,51,58,61,62,54,50,44,41,43,51,60,66,77,74,68,58,46,36,30,27,30,34,40,44,45,41,36,32,31,30,30,32,34,33,31,29,25,24,25,28,32,35,35,35,35,34,33,33,34,34,32,30,27,26,25,26,30,32,33,33,32,30,26,23,21,21,21,22,28,34,42,46,45,41,38,37,39,40,42,43,40,35,30,26,23,22,21,20,19,20,20,21,25,26,26,25,22,19,15,12,11,11,11,11,11,12,13,14,18,18,19,20,21,20,20,19,18,19,20,20,20,22,26,29,31,33,37,40,41,41,40,39,33,29,25,22,20,19,16,14,15,14,13,12,11,11,10,10,9,9,9,8,8,7,7,7,5,5,5,5,5,5,5,5,5,5,5,4,4,3,3,3,5,5,5,4,4,3,3,3,4,4,4,3,3,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,6,6,6,6,6,6,6,6,7,7,7,7,7,7,7,7,8,8,8,8,8,8,8,8,8,8,8,8,9,9,9,10,10,10,10,11,11,11,12,12,11,10,10,10,10,11,12,12,14,15,16,18,21,23,24,25,25,24,24,23,23,24,24,25,24,23,21,20,18,18,17,17,15,15,16,18,20,23,26,27,32,34,38,41,41,39,35,33,26,23,20,17,16,17,19,20,26,29,33,39,46,51,56,58,57,54,47,39,33,31,33,35,43,49,58,64,68,68,68,69,66,65,63,59,54,49,44,41,40,41,41,41,40,38,36,34,37,37,36,32,30,33,40,46,60,62,62,54,39,27,31,42,71,95,119,125,116,97,70,47,31,33,38,45,51,51,46,41,38,42,47,51,53,52,49,48,47,50,56,62,66,68,68,68,72,77,82,81,72,58,41,30,26,32,46,65,86,100,107,109,105,97,85,75,68,60,52,47,40,38,36,34,32,31,31,30,30,33,40,47,51,54,61,68,69,73,78,82,81,76,69,65,55,50,43,38,35,36,39,41,51,53,56,54,50,44,39,37,33,36,41,47,54,59,63,65,60,55,47,39,36,36,38,40,46,47,47,44,41,39,40,41,54,63,71,73,72,68,58,49,40,40,43,53,66,75,77,76,64,58,49,42,40,40,41,41,43,44,46,51,58,65,68,69,66,55,43,35,29,29,37,47,56,58,60,60,56,51,48,47,48,47,45,42,36,30,24,20,20,22,25,27,29,30,30,30,34,37,43,51,58,62,62,61,51,47,41,38,41,49,58,64,75,73,67,58,46,37,31,28,31,34,38,41,41,37,32,29,26,27,30,34,37,36,33,30,26,25,25,28,33,37,39,40,39,38,37,37,37,35,31,28,25,23,22,23,26,30,31,31,31,28,25,22,20,21,23,25,33,39,47,50,47,42,39,38,38,41,43,45,43,38,32,29,23,22,20,18,18,18,19,20,25,26,26,25,22,18,14,11,11,11,11,11,12,13,14,15,18,19,21,22,22,21,20,19,16,18,19,19,19,22,25,29,31,33,36,39,40,39,37,35,31,27,23,20,18,17,15,14,14,14,13,12,12,11,10,10,9,9,9,8,8,7,7,7,5,5,5,5,5,5,5,5,5,5,5,4,4,3,3,3,5,5,5,4,4,3,3,3,4,4,4,3,3,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,6,6,6,6,6,6,6,6,7,7,7,7,7,7,7,7,9,9,9,9,9,9,9,9,8,8,8,9,9,9,10,10,11,11,12,12,12,13,13,13,12,11,10,10,9,9,10,10,12,13,15,17,20,22,24,25,28,27,25,24,23,23,23,24,22,21,20,18,17,17,16,17,16,16,16,18,20,24,26,28,35,38,43,47,47,45,41,38,30,27,23,19,18,19,21,23,28,30,34,39,44,49,52,54,49,46,40,33,28,27,30,33,43,49,58,65,68,68,68,67,62,61,59,56,52,47,43,40,39,38,38,38,39,39,40,40,44,43,40,35,31,33,41,48,66,71,74,67,48,33,35,44,71,98,123,128,117,98,69,44,31,33,38,47,54,54,47,40,37,43,50,57,59,57,53,50,46,50,57,65,71,73,72,70,71,72,73,70,62,48,34,27,28,36,53,75,96,109,114,113,104,94,80,68,60,55,49,45,41,40,38,35,32,30,30,31,27,32,37,39,41,46,50,51,60,65,72,77,77,73,69,66,54,50,42,36,34,35,38,41,52,55,57,55,48,41,37,35,32,34,38,43,48,53,56,58,56,52,46,41,39,38,37,37,39,39,38,35,33,33,35,37,48,57,65,68,69,66,57,49,39,37,38,48,63,73,77,75,69,62,52,44,41,40,41,41,45,46,48,54,61,68,71,72,68,59,48,40,32,30,37,47,50,53,56,56,55,52,51,51,54,53,49,44,37,30,23,20,21,23,26,30,33,35,36,36,41,44,50,57,61,62,59,55,45,41,36,34,37,45,54,60,64,63,59,51,41,34,29,28,32,34,37,38,37,33,29,26,23,26,31,37,41,40,35,31,26,25,26,29,35,40,44,45,45,44,43,42,41,37,31,27,24,22,20,21,25,28,30,30,30,27,24,21,20,22,26,28,37,44,51,52,47,41,38,38,36,39,42,44,43,38,33,29,23,22,20,18,18,19,20,22,26,26,26,25,22,18,13,11,11,10,10,11,12,13,14,15,19,20,22,23,23,22,20,18,15,17,18,18,19,21,25,28,31,33,36,39,39,36,33,31,30,26,21,18,17,16,15,13,14,14,13,13,12,11,10,9,9,9,9,8,8,7,7,7,5,5,5,5,5,5,5,5,5,5,5,4,4,3,3,3,5,5,5,4,4,3,3,3,4,4,4,3,3,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,6,6,6,6,6,6,6,6,7,7,7,7,7,7,7,7,9,9,9,9,9,9,9,9,8,8,8,9,9,10,10,10,12,12,13,13,13,14,14,14,13,12,11,9,9,8,9,9,11,12,14,16,19,22,24,25,30,29,26,24,23,22,23,23,21,20,19,18,16,16,16,16,16,16,17,18,21,24,27,29,37,41,46,50,51,48,44,41,32,29,25,21,20,20,23,25,29,31,35,39,44,48,50,51,44,41,35,29,24,24,28,32,43,49,59,66,69,68,67,66,56,56,55,52,48,44,40,37,37,37,36,37,38,40,43,44,48,47,44,37,32,33,42,49,70,77,82,75,55,38,37,46,64,93,119,125,115,97,69,45,33,35,41,50,58,57,50,42,40,46,55,62,64,61,55,51,46,50,58,67,73,75,74,72,72,70,69,65,56,42,31,26,28,38,57,80,101,113,116,114,99,88,72,60,52,48,45,42,42,41,39,35,32,30,30,31,30,37,40,37,39,45,47,43,51,57,64,69,69,66,63,61,53,48,42,37,35,37,41,44,54,57,58,55,47,39,34,32,31,33,36,40,45,49,52,53,55,52,47,43,41,39,38,36,36,35,34,31,29,30,33,36,43,52,61,64,65,63,56,48,35,33,34,44,59,71,75,74,72,65,54,46,42,41,41,41,46,47,50,57,64,71,74,75,70,62,52,43,35,31,38,47,47,49,52,54,53,52,53,54,58,56,52,46,38,30,23,19,24,26,30,34,38,41,42,42,46,49,54,59,62,60,55,50,38,35,31,29,33,41,50,56,53,52,49,43,35,29,26,26,34,35,36,37,35,31,27,25,21,25,32,39,44,42,37,33,26,25,26,30,36,43,47,49,50,48,47,46,43,38,32,27,24,22,20,21,24,27,29,30,30,27,23,20,20,23,27,30,39,46,52,53,47,41,38,38,34,37,41,43,42,38,32,28,24,22,20,19,18,20,22,23,26,27,26,25,22,18,14,11,10,10,10,11,12,13,14,15,19,20,22,24,23,22,20,18,15,16,17,18,19,21,25,28,31,33,36,38,38,35,31,28,29,25,20,17,16,15,14,13,13,13,13,13,12,11,10,9,9,9,9,8,8,7,7,7,5,5,5,5,5,5,5,5,5,5,5,4,4,3,3,3,5,5,5,4,4,3,3,3,4,4,4,3,3,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,6,5,5,6,6,8,9,10,14,13,12,10,10,10,10,10,11,10,10,10,10,10,9,9,12,12,12,12,13,14,15,16,17,17,15,13,12,10,8,8,10,11,11,12,15,18,21,23,28,28,26,25,25,24,25,25,21,20,19,17,17,16,16,16,17,17,18,18,19,23,29,34,43,46,50,53,53,51,47,44,36,33,28,24,23,24,26,28,27,28,31,35,39,43,46,47,44,38,30,23,20,21,25,29,39,45,53,62,66,67,65,63,57,55,51,46,42,39,37,36,34,34,34,33,35,39,46,51,53,55,53,42,31,31,43,56,73,87,96,86,67,52,45,42,62,81,100,107,101,87,65,46,39,46,58,69,72,68,58,51,49,55,65,74,77,73,63,55,51,51,55,65,76,82,80,77,73,71,68,61,52,41,32,27,30,44,61,78,96,108,106,97,85,73,60,53,47,43,44,47,39,39,39,37,33,29,28,28,35,38,40,39,35,33,34,37,43,48,55,62,65,61,54,48,45,42,37,32,31,36,45,52,58,60,61,58,50,41,34,30,30,30,32,34,38,44,49,52,51,49,47,45,44,42,38,35,37,31,28,28,28,26,28,33,36,43,51,58,65,67,59,49,40,31,26,34,47,58,69,76,73,68,59,49,41,38,40,43,48,51,56,63,69,74,78,80,76,68,57,47,41,38,36,36,37,39,42,44,47,52,59,63,67,65,60,51,39,29,23,20,21,26,33,39,42,45,48,50,50,54,58,61,59,54,48,44,34,31,29,28,30,35,40,44,44,43,40,36,31,30,31,32,40,42,42,40,35,29,26,25,26,30,37,43,46,43,37,32,28,27,29,38,50,58,60,59,63,59,54,51,47,41,32,26,25,23,22,24,27,30,32,32,27,26,25,25,26,29,32,33,40,44,48,47,42,37,34,33,32,34,37,38,37,34,30,28,22,21,20,18,18,21,26,30,32,31,29,26,23,19,15,13,14,13,13,13,13,14,15,16,20,21,22,22,21,19,18,16,16,16,16,17,20,24,28,31,30,30,32,32,32,31,29,28,26,24,21,18,15,14,13,13,15,15,14,13,11,10,9,9,7,7,7,7,7,7,7,7,5,5,5,5,5,5,5,5,6,6,6,5,5,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,6,6,6,6,7,8,10,10,13,13,12,11,10,10,10,11,11,11,11,11,10,10,10,9,11,11,11,12,13,14,16,16,19,18,17,15,14,12,11,11,12,11,11,11,13,16,20,22,27,27,27,27,27,27,27,27,23,22,20,19,17,16,16,16,16,17,18,18,20,24,29,34,42,44,48,51,52,49,45,43,35,33,29,26,25,25,27,28,27,29,32,35,39,42,45,46,42,37,30,24,21,22,25,27,36,42,50,58,63,64,62,61,56,53,48,43,39,36,35,35,33,33,33,33,34,39,46,51,57,59,57,47,36,34,44,56,77,92,102,93,75,60,51,46,57,73,90,96,92,80,63,47,48,56,69,79,82,77,67,59,57,63,73,82,85,79,69,60,52,52,56,65,74,80,79,76,71,70,66,60,52,42,33,28,30,42,58,73,89,98,95,86,71,60,49,43,39,36,38,42,41,42,41,38,34,32,32,33,40,43,45,44,39,36,36,37,42,46,53,58,59,55,47,42,40,37,34,31,32,39,49,56,66,67,67,63,54,44,36,32,30,30,30,31,34,38,43,45,49,48,47,47,46,44,40,36,36,31,28,29,29,27,29,34,34,41,49,56,63,66,60,50,41,31,25,29,40,51,62,70,71,67,58,49,41,38,40,43,47,51,57,65,72,76,79,80,76,68,58,49,43,40,38,37,36,37,39,41,45,52,60,65,71,69,63,54,42,31,25,22,25,30,36,41,43,45,48,49,50,53,57,58,56,51,46,42,34,33,31,30,31,34,37,40,39,38,36,33,31,32,36,39,45,47,47,45,40,35,31,30,32,36,42,47,48,44,37,32,27,28,34,45,59,69,72,72,68,63,57,53,49,43,36,30,25,23,23,24,28,31,33,33,28,27,26,26,27,29,32,33,38,41,44,43,38,34,31,31,30,31,33,35,33,30,27,24,20,20,20,20,20,22,27,31,32,32,30,28,25,21,18,16,16,16,15,14,14,14,15,16,20,21,22,22,21,19,18,16,17,16,17,18,20,24,28,30,29,30,30,30,30,28,27,26,24,23,20,18,16,15,14,14,15,15,14,12,11,10,9,9,7,7,7,7,7,7,7,7,5,5,5,5,5,5,5,5,6,6,6,5,5,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,7,7,7,7,8,9,11,11,13,13,12,11,11,11,12,12,12,12,12,11,11,11,10,10,10,10,11,11,13,15,16,17,20,20,19,18,18,17,16,16,14,13,11,10,11,14,18,20,25,26,28,30,31,31,30,29,26,25,23,21,19,17,17,16,16,17,18,19,20,24,29,33,38,41,45,48,48,46,43,41,34,32,30,28,27,27,28,29,29,31,33,36,39,41,43,43,40,36,31,26,23,23,25,26,33,38,47,55,60,61,59,58,54,50,45,39,35,33,33,34,32,32,32,32,33,39,46,52,63,65,64,54,42,39,46,55,78,93,104,99,82,67,55,48,51,63,75,79,77,70,59,49,59,68,80,90,92,85,75,67,65,71,81,90,92,86,74,65,53,53,57,64,72,76,75,72,70,69,67,62,55,46,39,34,32,40,53,65,76,82,77,69,54,44,36,33,31,30,33,37,43,43,41,37,35,35,37,40,47,51,53,51,45,40,38,39,42,45,50,53,52,46,40,35,34,33,31,30,33,42,53,60,72,73,73,68,58,48,39,35,34,32,30,29,30,33,36,39,46,46,47,48,49,46,42,38,34,30,28,30,31,30,32,37,35,42,50,57,65,69,64,56,47,34,24,24,31,40,51,61,66,63,56,47,40,38,39,41,44,50,59,68,75,79,81,81,74,68,59,51,46,43,40,39,35,36,36,38,43,51,61,68,76,73,67,57,45,35,28,26,30,34,39,43,44,45,46,48,48,50,53,54,52,48,43,40,37,36,35,34,33,34,34,35,32,32,32,31,33,38,45,50,55,56,56,52,47,42,39,38,40,44,49,51,49,43,36,31,28,32,42,56,71,81,84,84,77,70,61,54,50,44,38,33,25,24,24,26,29,32,34,33,30,29,28,28,28,30,32,33,35,37,37,35,32,28,27,27,26,27,28,29,27,24,21,19,17,19,21,22,23,25,29,32,32,32,32,30,28,25,22,20,20,19,17,16,15,15,16,16,20,21,22,22,21,19,18,16,18,18,18,19,21,24,27,29,28,28,28,27,26,25,24,23,23,22,20,18,17,16,16,16,15,14,13,12,11,10,9,8,7,7,7,7,7,7,7,7,5,5,5,5,5,5,5,5,6,6,6,5,5,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,8,8,8,8,9,10,11,12,13,13,12,12,12,13,13,14,14,14,13,13,12,11,11,11,10,10,10,11,13,15,17,18,21,21,21,21,21,21,21,21,18,16,13,11,11,13,17,19,22,24,28,31,33,33,33,32,30,29,26,23,21,19,18,17,17,18,19,20,20,23,27,31,34,36,40,43,44,43,41,39,32,32,31,30,29,29,29,29,31,33,35,37,39,40,40,40,38,36,32,29,27,26,27,28,33,38,45,52,57,58,56,55,52,49,43,38,34,33,34,34,33,32,31,31,33,39,47,53,67,70,70,61,50,44,48,54,73,88,100,97,84,70,56,47,49,55,62,65,64,60,56,53,64,73,86,95,94,87,77,70,69,75,85,93,94,87,75,66,54,55,57,62,67,70,69,68,67,68,68,65,60,54,47,43,36,40,47,55,63,64,58,51,41,33,27,27,28,29,32,37,42,40,37,34,32,35,40,45,54,57,59,57,50,44,42,42,44,47,50,51,48,42,37,34,33,33,33,33,36,44,53,59,71,72,73,69,61,52,45,41,40,37,34,31,30,31,33,35,43,44,46,49,50,48,43,39,32,28,28,31,33,34,37,42,44,50,57,63,72,78,75,67,55,42,29,24,26,32,42,52,59,57,51,44,38,35,37,39,42,49,60,71,78,81,81,80,71,66,57,51,47,44,42,41,36,36,36,37,41,51,62,70,77,75,68,58,46,37,31,29,33,37,41,43,43,43,43,44,43,45,47,48,48,46,44,42,42,42,41,40,38,35,33,32,28,29,30,32,37,45,56,63,67,67,65,60,53,47,43,42,46,49,52,52,47,40,33,29,32,38,51,67,82,90,92,91,83,75,63,54,48,42,36,32,26,25,25,27,31,33,33,33,31,30,30,30,30,31,32,33,33,32,30,28,25,24,23,23,23,23,23,22,21,19,16,15,16,19,23,25,26,28,31,33,33,34,34,34,32,30,27,25,24,22,20,17,16,16,17,17,20,21,22,22,21,19,18,16,19,19,19,20,21,23,25,27,26,25,25,24,23,22,20,20,21,20,20,19,18,18,17,17,14,14,13,12,11,9,9,8,7,7,7,7,7,7,7,7,6,6,6,6,6,6,6,6,6,6,6,5,5,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,8,8,8,8,9,10,11,12,13,12,12,12,13,14,15,16,16,16,15,14,13,12,12,11,10,10,11,12,13,15,16,17,21,21,22,23,24,25,25,25,22,20,17,14,13,14,16,17,20,22,26,30,33,34,34,33,33,32,29,26,23,21,20,19,19,20,21,21,21,22,25,28,29,32,35,38,40,39,38,37,31,31,30,30,29,30,30,30,33,35,37,39,39,39,38,37,36,35,32,30,30,30,31,32,36,40,46,52,55,55,53,52,50,47,43,38,36,35,36,36,35,34,32,31,33,39,48,54,68,72,74,68,58,51,51,54,68,81,93,92,84,73,60,50,52,53,56,57,55,53,54,56,66,75,87,93,91,83,74,69,70,75,84,91,92,85,74,66,55,55,57,59,62,63,63,62,62,64,68,69,67,61,55,51,43,42,43,47,51,49,44,39,33,27,23,25,27,28,31,36,37,36,32,29,29,34,41,47,58,61,63,61,55,49,48,48,51,54,56,54,49,43,40,39,38,39,39,40,41,44,50,54,65,68,71,70,65,59,54,51,44,42,39,36,33,32,32,32,40,41,44,47,48,47,42,38,30,26,26,30,35,38,44,51,58,63,68,73,81,88,86,80,66,53,38,30,27,29,37,46,51,50,46,41,35,33,34,35,42,49,61,72,78,80,78,76,66,60,53,47,45,44,44,44,40,39,37,37,40,49,60,68,73,71,65,55,44,36,32,31,34,38,41,42,41,40,39,39,37,38,40,42,44,45,46,46,48,48,48,46,43,38,34,31,27,29,31,35,42,52,64,73,77,76,72,65,56,48,44,42,47,49,51,48,42,35,30,28,35,44,61,78,92,99,99,97,83,73,60,50,43,38,33,29,27,26,26,28,31,32,32,30,30,30,30,30,31,32,33,34,31,29,26,23,22,21,20,20,20,20,19,18,16,15,14,13,16,20,24,27,29,31,33,35,35,36,38,38,37,34,31,29,26,24,21,18,16,16,18,19,20,21,22,22,21,19,18,16,19,19,19,20,21,22,23,23,23,23,22,21,20,19,19,19,20,20,20,20,19,19,18,18,14,13,13,11,10,9,8,8,7,7,7,7,7,7,7,7,6,6,6,6,6,6,6,6,6,6,6,5,5,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,7,7,7,7,8,9,11,11,12,12,12,13,14,15,17,18,18,17,16,15,14,13,12,12,12,12,12,12,13,14,15,16,20,20,21,23,25,26,28,28,27,25,22,20,18,17,16,16,19,21,24,27,30,32,33,33,35,34,31,28,25,23,22,22,21,22,23,22,21,21,22,24,25,27,30,34,35,36,35,34,31,30,28,28,28,29,31,32,35,37,39,40,39,38,35,34,33,32,30,30,30,32,34,36,41,44,48,51,52,51,48,46,46,44,42,40,38,38,38,38,38,37,34,32,34,40,48,55,69,74,78,74,66,58,56,57,67,78,87,89,86,79,69,60,58,56,54,54,52,49,51,56,65,74,84,88,84,76,69,66,68,72,79,85,86,81,72,65,55,55,56,56,57,56,56,55,56,62,69,75,76,71,65,60,53,46,41,42,42,39,35,34,30,24,21,24,26,27,29,33,34,32,30,28,29,35,44,50,61,64,66,63,59,56,57,59,63,65,65,60,52,46,44,44,45,47,49,49,47,45,45,46,56,60,66,68,67,64,61,60,48,47,45,43,40,37,35,34,38,39,40,43,45,43,40,36,28,24,23,29,35,41,51,60,71,74,77,80,88,95,94,88,76,64,50,40,33,31,35,42,46,45,43,39,35,32,32,34,43,50,61,70,76,76,73,70,59,53,46,41,40,42,45,46,44,42,39,37,38,45,54,61,65,62,57,49,40,34,31,31,35,37,40,41,39,37,36,36,33,34,35,38,41,45,48,50,54,53,52,50,46,40,35,32,28,31,34,39,46,57,68,76,80,79,74,66,56,48,43,41,45,47,46,42,35,30,29,30,38,50,69,87,99,102,100,97,74,65,53,44,39,35,31,28,28,28,27,29,30,30,29,27,28,28,29,30,32,33,34,34,30,27,24,22,22,21,19,17,19,18,17,15,15,14,15,15,19,22,26,28,30,32,34,36,38,39,41,42,41,38,34,32,27,25,21,18,16,17,19,20,20,21,22,22,21,19,18,16,19,19,19,19,19,20,20,20,21,20,19,18,18,18,19,19,20,21,21,21,20,19,18,17,14,13,12,11,10,9,8,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,6,6,6,5,5,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,6,6,6,6,7,8,10,10,12,12,12,13,15,16,18,19,19,18,18,16,15,14,13,12,14,13,13,12,12,13,14,14,18,18,20,22,25,27,29,29,30,29,28,25,22,19,17,16,18,19,21,24,27,29,31,32,36,35,32,30,27,26,25,24,24,24,25,23,20,19,20,21,22,24,27,30,32,33,33,33,30,29,26,25,26,28,31,33,37,38,40,41,39,37,33,31,29,28,27,26,28,32,36,39,45,47,49,50,49,46,43,40,40,40,40,40,40,40,39,39,42,40,37,34,34,40,48,55,69,75,81,81,74,66,62,61,66,75,83,86,86,85,79,71,64,59,56,55,51,46,48,54,61,69,77,79,74,66,61,60,61,64,69,74,76,72,65,60,54,54,55,54,52,51,50,50,57,65,77,86,89,86,79,73,61,50,41,39,38,34,33,34,32,26,24,27,29,28,29,32,33,32,31,30,32,39,48,54,64,66,68,66,63,63,67,71,77,78,75,67,56,48,45,46,50,54,57,57,53,47,43,40,44,50,57,62,63,63,62,61,55,55,55,54,52,47,43,41,37,37,37,39,40,39,37,34,26,22,21,27,35,45,57,68,78,80,80,82,88,95,94,89,82,72,60,50,40,33,34,39,43,43,42,39,36,33,33,34,45,51,60,68,72,71,67,64,52,46,38,34,35,40,45,48,46,44,40,36,35,39,46,51,54,53,48,41,34,30,29,30,35,38,41,41,39,36,35,35,33,33,33,35,39,43,48,50,56,56,54,51,46,41,36,33,30,32,37,42,48,57,67,74,78,76,71,63,54,47,43,42,42,43,42,36,29,27,30,34,44,56,74,89,96,94,87,82,62,55,45,39,37,36,34,31,30,29,28,29,29,28,25,23,25,26,28,30,32,33,34,35,30,27,24,23,24,23,19,16,18,17,16,15,14,15,17,18,22,24,27,29,30,32,35,38,41,42,44,45,44,41,36,34,27,24,20,17,16,17,20,21,20,21,22,22,21,19,18,16,18,18,18,18,18,18,17,17,19,18,17,17,17,18,19,20,21,21,22,22,21,19,17,16,13,13,12,11,10,8,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,6,6,6,5,5,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,6,5,5,6,6,8,9,10,12,12,13,13,15,17,19,20,20,19,18,17,15,14,13,13,15,14,13,12,12,12,13,13,16,17,19,22,24,27,29,30,32,32,31,29,26,22,18,16,18,18,19,21,24,27,30,31,36,35,33,30,28,27,26,26,25,26,26,24,20,18,18,19,20,22,25,28,30,32,32,32,30,28,25,23,24,27,31,34,38,39,41,41,39,36,32,30,26,25,23,23,26,31,36,40,47,48,49,49,47,43,39,36,36,37,39,40,41,40,39,38,44,42,38,35,35,40,49,55,70,77,84,84,79,71,67,65,65,72,79,82,85,87,83,77,68,61,57,56,50,44,46,52,57,64,71,71,65,58,54,54,54,56,60,64,66,64,59,54,54,54,54,52,49,47,47,47,62,71,85,97,102,98,91,85,67,53,41,38,36,32,32,36,36,31,28,31,32,31,31,33,34,34,33,33,36,42,51,58,65,67,69,68,66,68,74,79,86,86,82,71,58,48,45,46,53,57,62,62,57,49,42,38,35,41,49,55,57,58,57,58,62,63,65,65,62,57,52,49,37,36,35,36,37,37,35,33,25,20,19,25,35,46,61,73,80,81,80,81,86,92,92,86,85,76,65,55,44,35,34,37,42,43,43,41,37,35,35,35,46,52,60,66,69,68,64,61,48,42,34,29,31,38,44,49,47,45,40,35,33,35,40,44,48,46,42,37,31,28,28,29,36,38,41,41,39,37,35,35,35,34,33,34,37,42,46,49,57,56,54,50,45,40,35,33,30,33,38,43,49,57,65,71,74,73,68,61,53,46,43,43,41,41,39,33,27,26,32,38,49,61,77,88,89,82,71,64,53,47,40,36,37,38,37,35,30,29,28,28,28,27,23,20,23,24,27,29,32,34,35,35,30,28,25,25,25,24,20,16,19,17,16,15,15,17,19,20,24,26,28,29,30,32,35,38,42,44,46,47,46,42,37,34,26,23,19,16,16,17,20,22,20,21,22,22,21,19,18,16,17,17,18,18,17,16,15,15,18,17,16,16,17,18,20,21,22,22,23,22,21,19,17,15,13,13,12,11,9,8,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,6,6,6,5,5,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,5,5,6,7,7,8,9,9,11,11,12,14,15,16,17,18,20,19,19,18,18,19,19,20,19,17,15,13,12,11,12,12,15,16,17,19,23,27,31,33,32,32,31,29,27,24,22,20,17,17,17,17,19,22,25,26,30,29,27,25,25,25,26,26,26,26,25,25,23,22,20,19,17,18,20,23,26,28,30,31,32,30,28,26,27,29,32,34,36,38,41,44,43,41,37,34,32,28,23,22,25,31,37,41,47,50,53,51,46,38,31,28,33,35,38,40,42,43,43,42,41,40,39,38,39,43,50,55,69,75,81,84,80,73,67,63,66,69,74,79,83,86,87,87,77,71,61,51,45,44,46,48,54,58,63,63,59,54,52,51,54,54,54,53,53,53,53,53,54,50,49,49,47,46,49,56,66,78,93,104,110,109,98,87,71,58,44,38,36,35,37,40,38,38,38,35,33,31,32,33,37,37,37,39,43,49,55,58,66,64,65,68,70,72,80,89,96,95,88,75,58,46,42,42,52,59,67,69,62,50,39,33,33,35,39,44,49,53,56,58,63,66,70,73,72,69,65,62,46,40,35,36,42,45,41,37,29,22,19,23,31,43,58,71,80,81,79,76,73,73,76,79,78,77,71,61,48,39,36,36,39,41,42,41,39,39,41,45,44,48,53,57,58,55,51,48,34,31,27,27,30,38,46,52,51,48,43,37,34,33,33,34,36,36,34,31,27,26,27,28,30,33,37,40,39,38,38,39,37,37,36,35,35,37,42,46,50,50,49,48,45,41,37,35,39,40,41,42,44,50,58,63,67,65,61,56,51,46,42,40,39,38,35,30,27,30,36,42,56,69,80,80,74,69,59,50,36,38,38,38,42,48,46,41,39,37,34,31,29,26,21,18,17,19,23,27,29,30,29,28,30,29,29,27,26,25,24,23,18,16,13,14,17,20,22,22,25,25,24,25,27,30,34,36,43,45,48,49,48,44,40,37,25,22,18,15,14,16,19,21,26,26,26,25,23,20,17,15,17,16,15,15,14,14,15,15,18,18,19,20,21,21,21,20,21,21,21,21,19,16,14,12,10,10,10,9,9,9,8,8,8,8,8,7,7,6,6,6,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,5,5,6,7,7,8,9,9,10,10,11,12,14,15,16,16,19,18,18,18,18,19,20,21,20,19,16,14,13,12,12,12,14,14,15,17,21,24,28,30,31,31,30,29,28,25,24,22,18,17,17,17,18,20,22,23,27,26,24,23,22,22,23,23,23,23,24,24,23,22,20,19,17,18,19,21,23,26,29,30,30,29,28,27,27,29,31,32,34,36,38,40,40,40,38,37,35,30,25,22,24,29,35,39,48,51,54,52,46,38,31,27,31,33,35,38,40,41,41,41,40,40,39,39,40,44,51,56,67,72,79,81,78,72,66,63,65,68,73,78,81,83,83,83,74,68,58,49,44,43,45,48,53,56,60,60,56,52,51,50,48,48,48,49,50,51,52,52,51,47,45,46,46,47,54,63,82,94,108,118,122,118,104,91,70,57,43,38,37,38,41,46,44,44,44,41,37,35,36,37,40,40,41,44,48,54,59,62,69,66,66,69,71,74,83,93,102,101,94,79,61,47,41,40,49,57,67,70,64,53,41,34,29,31,34,38,43,46,49,50,58,63,70,76,77,74,68,64,51,45,39,41,47,51,49,45,35,27,22,24,30,41,56,69,77,77,74,69,64,62,65,68,72,72,70,62,52,44,40,40,39,41,42,42,40,40,43,45,49,51,53,54,52,48,43,40,32,30,28,28,32,39,48,53,55,51,46,40,35,32,31,30,30,29,28,26,23,22,24,27,31,35,38,40,40,40,41,42,39,39,37,35,34,36,39,43,48,47,46,45,42,40,38,37,40,41,42,42,43,47,53,57,59,58,56,53,49,46,43,42,40,39,36,32,30,33,40,45,55,65,72,69,62,56,49,41,37,41,45,48,54,59,58,52,46,42,37,33,30,26,22,18,18,20,22,24,26,27,28,28,29,30,30,30,29,27,25,24,20,17,15,16,19,22,23,24,25,24,23,23,25,29,33,36,45,46,48,48,45,41,36,33,25,23,19,16,16,17,20,22,26,26,25,24,22,19,16,14,15,15,14,13,13,14,14,15,17,18,20,21,22,22,21,21,21,21,21,20,18,16,13,12,10,9,9,9,8,8,8,8,8,8,8,7,7,6,6,6,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,5,5,6,7,7,8,9,9,8,9,10,11,12,13,14,14,17,17,17,17,19,20,22,23,22,20,18,16,15,13,13,13,13,13,14,15,17,21,24,26,29,29,30,29,29,28,26,26,20,19,18,17,16,17,18,19,23,22,20,19,18,18,18,19,19,20,22,24,24,22,20,19,18,17,17,18,20,23,27,29,28,28,28,28,29,29,30,30,31,32,33,34,36,38,40,41,38,34,28,23,23,27,32,37,51,53,56,53,47,38,31,27,27,29,32,35,37,38,38,38,39,39,39,38,40,45,51,56,63,68,73,75,72,67,63,60,60,63,68,73,77,78,78,77,69,63,54,45,41,41,44,47,49,52,54,54,52,50,49,50,46,46,45,45,45,46,47,47,47,42,40,42,45,51,63,74,100,112,124,131,131,122,105,90,68,54,41,36,38,41,48,55,55,55,53,49,45,42,41,42,44,44,47,50,55,60,65,68,73,70,68,69,70,74,86,98,107,106,99,83,63,45,36,34,44,54,65,71,68,57,44,36,26,28,30,33,36,39,41,42,50,57,67,76,79,76,70,65,56,52,48,51,57,62,62,60,46,36,27,25,28,37,52,65,72,71,67,59,52,49,51,55,64,67,70,67,59,50,45,44,39,40,42,42,42,42,44,46,50,50,49,47,44,40,37,34,31,30,30,32,37,44,51,56,59,55,49,42,35,30,27,25,24,24,23,22,20,21,24,27,33,36,39,41,41,41,43,44,42,41,39,36,33,33,35,38,44,43,42,40,39,39,39,39,41,43,44,43,43,44,47,49,50,50,50,50,48,47,45,45,41,40,37,34,34,38,44,50,56,61,63,56,48,43,40,36,39,47,56,62,70,74,71,65,56,51,43,36,31,27,23,20,20,20,21,22,23,25,26,27,29,30,32,34,33,30,27,25,22,20,18,19,22,25,26,26,25,23,21,20,22,27,32,36,46,47,47,46,42,37,32,29,25,23,20,18,18,20,22,24,26,26,24,23,20,17,14,13,13,13,12,12,12,13,14,14,17,19,21,22,23,23,23,22,20,20,19,18,17,15,13,12,9,9,9,8,8,7,7,7,8,8,8,7,7,6,6,6,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,6,6,7,7,8,8,8,7,7,8,9,10,11,11,12,14,15,15,16,18,20,22,23,22,21,20,18,17,15,14,14,13,12,12,13,15,17,20,21,27,27,28,29,29,29,28,28,24,22,20,18,17,17,17,18,19,19,18,17,16,15,15,15,15,17,20,23,23,22,21,19,18,17,16,15,17,21,25,28,27,28,30,31,31,31,30,29,28,28,27,28,31,36,41,44,43,39,32,25,22,24,30,34,51,53,55,53,46,38,30,26,24,26,28,31,33,34,35,34,35,35,36,36,38,42,49,53,57,61,64,65,62,58,55,54,52,55,60,65,69,70,70,70,63,57,49,42,39,40,43,45,44,45,47,48,48,49,50,51,51,49,47,45,43,42,42,43,43,38,36,40,47,58,74,88,113,123,133,136,132,119,99,82,63,50,37,34,39,46,56,65,69,68,65,59,53,48,46,46,45,46,49,54,60,66,71,73,76,73,69,68,66,71,84,98,107,107,101,85,63,43,31,26,40,49,62,70,69,60,47,38,28,28,29,31,32,35,36,37,41,47,57,66,71,70,67,64,60,59,60,66,74,78,77,75,59,47,33,26,26,32,45,58,65,65,61,52,44,40,44,48,60,66,72,73,66,56,49,46,40,41,42,44,44,45,46,46,46,45,43,41,39,37,35,35,34,35,37,40,45,51,57,60,62,58,51,43,35,28,24,21,23,24,23,21,21,23,27,30,35,37,40,41,41,42,44,46,44,43,41,37,32,31,31,33,39,38,37,36,36,37,39,40,41,43,44,45,44,43,44,45,46,47,48,49,49,49,48,47,44,42,38,36,37,41,48,52,58,59,56,49,41,38,39,41,46,57,69,77,83,86,81,74,66,59,49,40,34,29,25,23,22,21,20,20,21,23,25,27,29,31,35,37,37,34,29,26,24,22,21,22,25,27,28,28,25,22,19,17,20,25,31,35,45,46,46,44,41,36,32,29,26,24,22,20,20,21,24,25,26,25,23,21,18,15,13,11,12,11,11,11,12,13,14,15,18,20,22,24,25,24,23,22,19,18,18,17,15,14,13,12,9,9,8,8,7,7,7,7,8,8,8,7,7,6,6,6,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,6,7,7,7,7,8,8,6,7,7,8,9,9,10,10,12,12,13,15,16,19,21,22,21,21,20,20,18,17,16,15,14,13,12,12,13,15,16,18,23,24,25,27,28,28,28,28,26,25,22,20,19,18,19,19,18,18,18,17,16,15,14,14,14,16,19,21,22,22,21,21,19,18,16,16,17,20,24,27,28,29,31,32,33,32,31,30,27,25,24,24,27,34,40,45,46,43,37,29,24,24,28,32,47,50,53,51,45,37,30,26,23,25,27,30,31,32,32,31,30,31,32,32,34,37,43,47,51,54,56,55,52,49,48,47,47,49,52,56,59,60,61,61,55,51,46,41,38,39,41,43,40,40,40,43,47,52,56,58,58,56,52,49,46,45,44,44,42,37,37,43,53,67,86,101,123,131,137,136,129,114,93,76,58,45,34,34,42,52,65,75,83,81,76,68,59,52,48,47,43,45,48,54,61,68,75,79,80,75,70,65,61,63,77,92,103,105,101,87,65,44,30,25,36,44,56,66,67,60,48,40,29,29,29,29,30,32,33,34,35,39,46,52,57,60,61,60,62,65,72,82,90,94,91,88,73,58,41,30,25,28,38,49,59,61,58,51,42,39,43,49,60,69,78,80,73,61,51,46,42,42,43,45,47,47,46,45,45,43,41,38,36,36,36,36,40,43,46,51,56,60,63,64,63,58,51,43,35,29,25,23,27,26,24,22,21,23,27,31,36,38,41,42,42,42,43,44,44,43,41,37,32,29,29,30,35,34,34,34,35,37,39,40,38,41,44,44,44,43,44,45,45,47,49,51,52,52,51,50,46,43,38,36,38,42,47,51,55,53,48,43,38,37,43,50,59,70,83,89,92,92,85,77,69,62,51,42,35,31,27,25,23,22,20,20,21,23,26,29,30,33,37,40,39,35,30,27,24,23,23,24,27,29,29,28,24,21,18,17,19,24,30,34,42,42,42,42,40,36,33,31,26,25,23,22,21,22,24,25,24,23,21,18,16,13,12,11,11,11,11,12,13,14,16,17,20,22,24,26,27,25,23,22,18,17,16,15,13,13,12,12,9,9,9,8,8,7,7,7,8,8,8,7,7,6,6,6,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,7,7,7,7,7,7,7,7,6,7,7,7,8,8,9,9,10,11,11,12,14,16,18,20,19,19,20,20,19,18,17,17,16,15,14,13,13,14,15,16,20,21,22,24,25,26,26,26,26,24,22,21,20,20,21,21,20,20,20,20,19,18,16,16,16,17,18,20,21,22,23,23,21,20,19,18,19,22,24,26,27,29,30,31,32,31,30,30,27,25,23,22,25,32,39,44,47,46,42,35,27,24,27,30,41,44,48,48,43,36,30,27,24,26,28,29,30,30,29,29,27,28,28,29,30,33,37,41,46,48,49,49,47,46,47,48,48,48,48,49,49,50,51,51,48,46,43,41,40,40,41,41,38,37,38,42,51,60,66,69,68,65,60,55,51,49,48,48,42,39,41,50,62,77,96,112,130,134,136,131,122,108,89,73,54,42,34,37,48,61,75,86,95,92,85,74,62,53,47,45,40,42,45,51,60,70,79,84,84,80,73,64,56,55,67,81,97,100,100,90,70,50,36,30,35,40,50,58,62,57,49,41,31,30,29,29,29,31,33,34,35,37,39,43,48,52,55,57,63,68,78,90,99,103,102,100,86,70,51,36,27,26,33,43,54,57,58,52,43,40,44,50,63,72,83,86,79,66,54,48,44,44,45,47,48,48,46,44,46,45,42,40,38,37,37,38,48,51,56,61,65,66,67,66,63,58,51,43,37,34,32,32,33,31,28,24,21,22,26,29,38,42,45,46,45,44,43,43,42,42,40,36,32,29,28,29,31,32,32,33,35,37,38,39,37,39,41,42,41,41,42,43,45,47,51,54,55,55,54,54,48,43,37,35,36,40,43,45,47,43,40,37,35,36,45,56,69,80,91,94,93,90,82,75,64,58,48,40,34,30,27,25,24,23,22,22,24,26,29,31,33,36,39,40,39,35,30,27,24,23,23,24,27,29,29,28,23,21,18,18,20,24,30,33,37,38,38,38,37,35,33,32,27,26,24,23,22,22,22,23,22,20,18,16,14,12,12,12,12,12,13,14,15,17,19,20,22,24,27,28,28,26,23,20,16,16,14,13,12,12,12,12,10,10,10,9,9,9,8,8,8,8,8,7,7,6,6,6,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,7,7,7,7,7,7,7,7,7,7,7,8,8,8,9,9,9,9,10,10,12,14,15,17,16,17,18,19,20,19,19,18,19,17,16,14,13,14,14,15,17,18,19,21,22,23,23,23,23,22,20,19,20,20,22,23,23,23,24,24,23,21,20,19,19,19,18,19,20,22,23,25,22,22,22,22,22,24,25,26,26,27,28,28,29,29,28,28,28,26,23,22,25,30,37,41,47,48,47,40,31,26,27,30,34,38,43,44,41,35,30,28,27,28,29,30,30,29,28,27,26,27,27,27,27,30,33,37,42,44,46,47,48,50,53,56,56,53,49,45,42,41,41,42,42,42,42,42,42,41,40,39,38,37,38,45,57,70,79,83,83,78,70,62,54,49,46,45,43,42,47,58,71,85,103,118,126,128,126,118,108,97,80,67,52,42,36,42,55,70,85,96,103,99,91,78,64,52,45,42,38,39,42,48,58,71,83,90,90,84,76,65,52,48,58,72,86,92,96,89,73,54,40,34,34,37,43,51,55,54,48,42,36,35,33,32,33,34,36,38,40,40,41,43,47,50,53,55,63,69,78,89,100,106,109,109,98,82,61,44,32,27,32,39,50,55,58,53,44,40,44,49,65,75,86,90,83,70,58,51,47,46,46,48,50,49,45,42,44,43,43,42,42,43,44,45,55,58,64,68,70,70,68,66,63,59,51,45,41,40,42,44,42,40,35,29,25,24,27,30,42,46,50,52,50,47,44,42,40,40,39,36,32,29,29,29,29,30,32,34,36,37,37,38,36,37,38,38,36,36,38,39,43,46,50,55,58,59,58,58,50,44,36,32,33,36,38,39,40,36,34,35,34,36,46,58,71,80,88,88,84,79,73,66,55,49,41,35,30,27,25,23,24,24,24,25,27,30,32,34,36,38,40,40,38,34,29,26,22,22,22,24,27,28,27,26,22,21,19,19,21,25,30,32,34,34,35,34,33,31,30,28,28,27,25,23,21,21,20,20,19,18,16,14,12,12,12,12,14,14,15,16,18,20,22,23,25,27,29,30,29,25,21,19,16,15,13,11,11,11,11,12,11,11,11,11,10,10,9,9,8,8,8,7,7,6,6,6,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,7,7,7,7,7,7,7,7,7,7,8,8,8,8,9,9,9,8,9,9,10,12,14,14,14,15,17,19,20,20,19,19,20,19,17,15,14,14,15,15,15,16,17,19,20,20,21,20,20,19,18,18,19,20,22,23,25,26,26,27,26,24,22,21,21,20,19,18,19,21,24,26,23,23,24,24,25,25,25,25,25,25,25,25,26,26,27,27,30,27,24,22,24,29,35,39,47,49,49,43,34,28,27,29,30,34,39,41,39,34,30,28,29,30,31,31,30,29,27,26,26,27,27,27,27,28,32,35,41,43,46,48,51,55,60,64,63,59,52,44,39,36,36,36,39,40,42,43,43,42,40,38,40,39,40,48,62,77,88,93,97,91,79,67,55,46,40,37,44,45,51,63,77,91,108,121,118,119,114,105,95,84,70,58,52,43,39,46,60,75,91,102,107,103,93,79,64,51,43,39,38,38,40,47,58,72,85,93,93,88,79,66,51,44,53,66,78,85,90,86,72,54,41,35,35,36,40,46,51,51,47,43,41,40,38,37,38,39,42,43,44,44,46,47,50,52,53,54,64,68,76,86,97,106,112,115,105,89,67,49,36,29,32,38,48,54,58,54,44,39,41,47,66,76,88,92,86,73,61,54,49,47,47,49,50,49,45,41,39,39,41,43,46,49,52,54,58,62,67,72,73,71,67,65,64,59,52,46,44,46,49,52,51,48,42,35,29,27,29,32,45,49,54,56,54,49,45,42,38,39,38,36,32,29,29,30,28,30,32,35,36,37,37,36,36,37,36,35,33,32,33,35,40,43,49,54,59,61,61,60,50,44,35,31,31,33,34,34,38,34,33,35,36,37,47,60,66,75,81,78,73,69,63,57,47,42,36,31,27,25,22,20,24,25,26,28,30,32,35,36,38,39,40,39,37,33,29,26,21,21,21,23,26,27,26,25,21,21,20,21,23,26,29,32,33,33,32,31,30,28,26,25,29,28,25,23,21,20,19,19,18,16,14,13,12,12,13,13,15,15,16,18,20,22,24,25,27,28,30,31,29,25,21,18,15,14,12,11,10,10,11,12,12,12,12,11,11,11,10,10,8,8,8,7,7,6,6,6,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,6,6,7,7,8,8,8,8,8,8,9,9,10,10,10,10,10,10,9,9,8,8,7,10,10,9,9,9,9,8,8,13,14,16,18,20,20,19,19,19,19,19,18,17,15,14,13,14,14,14,14,14,15,17,17,17,17,17,18,19,20,22,23,26,28,31,34,34,33,30,29,27,25,23,22,22,23,25,27,23,24,25,26,28,29,31,31,31,28,25,22,21,22,25,27,27,29,31,30,30,33,39,44,50,50,48,45,39,33,27,24,29,30,32,32,32,32,30,29,29,30,32,33,33,30,27,25,25,25,25,26,28,32,34,36,41,43,47,51,58,66,75,82,79,71,61,50,42,38,35,33,39,43,46,47,45,42,41,40,33,34,40,52,68,84,94,99,103,95,82,65,50,40,37,37,45,50,60,72,85,96,105,109,104,100,95,88,80,70,59,52,47,44,42,48,61,78,94,103,106,100,88,74,60,48,39,34,32,36,41,48,59,72,85,94,99,95,86,70,55,49,54,61,72,77,83,82,72,57,43,34,30,33,37,42,45,47,47,47,42,38,37,39,39,41,47,56,58,64,67,65,65,68,69,67,67,67,72,81,87,92,101,110,104,97,82,63,45,35,34,36,45,50,54,51,43,39,41,45,63,74,87,94,89,75,60,50,46,47,50,53,55,53,49,45,44,40,40,46,51,52,55,59,64,67,70,70,68,64,61,61,57,56,54,53,54,57,61,63,67,61,52,41,32,30,32,35,46,54,61,61,58,54,47,41,34,34,34,33,32,31,30,29,28,30,32,34,35,35,35,34,34,32,29,26,26,27,29,31,34,40,50,59,64,64,60,57,52,44,34,31,33,37,38,37,35,35,34,35,37,43,51,56,61,60,58,58,56,53,47,43,38,35,31,27,23,22,22,22,23,24,25,28,31,35,38,40,40,39,37,35,32,28,25,24,20,21,22,23,23,23,23,23,22,22,22,23,25,27,29,30,30,29,27,25,24,23,23,23,25,24,24,23,22,21,20,19,20,18,16,14,13,14,15,17,18,20,23,25,27,27,26,25,28,28,28,28,26,23,21,19,15,15,15,15,15,15,15,15,13,13,13,12,11,11,10,10,9,8,8,7,7,8,8,9,5,6,6,6,6,6,6,6,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,6,7,7,7,8,8,8,8,8,9,9,9,10,10,10,11,10,10,10,9,9,8,8,10,10,9,9,9,8,8,8,11,12,14,16,18,18,18,18,19,19,19,19,18,16,15,14,15,14,14,14,14,15,16,17,16,16,17,17,19,20,22,23,27,29,32,35,37,36,35,34,31,30,28,26,25,26,27,28,23,23,24,25,26,28,30,31,29,27,24,21,21,22,23,25,27,30,32,33,34,37,42,46,50,50,50,47,42,36,30,27,27,28,30,31,32,32,31,31,31,33,34,35,34,31,28,26,25,25,26,27,30,33,36,38,41,44,49,55,62,71,81,88,85,77,64,52,42,37,34,33,41,44,48,49,47,44,41,40,34,35,39,50,66,81,93,98,100,93,80,64,49,40,36,36,43,51,63,76,86,92,95,96,91,86,80,73,66,59,52,47,43,41,41,47,60,77,92,100,101,94,82,68,55,44,38,34,36,39,45,52,62,74,88,97,102,100,90,75,58,50,52,57,67,71,75,74,64,51,38,30,29,31,36,40,44,47,49,50,47,43,41,41,42,44,52,61,72,81,88,89,89,90,87,82,74,71,70,74,78,83,93,103,104,99,87,71,54,43,40,40,46,51,53,49,41,36,37,41,61,71,84,91,86,72,57,47,43,46,50,55,58,56,51,47,43,39,38,43,48,51,54,58,63,65,67,67,64,61,59,58,53,54,55,58,63,70,76,79,78,71,58,44,33,28,29,31,45,55,63,64,61,56,49,41,33,33,33,32,31,30,29,29,28,30,32,35,36,37,36,36,33,31,28,26,25,26,28,29,34,39,48,56,61,61,59,57,50,44,37,35,37,40,40,38,37,36,36,36,38,42,47,51,51,49,47,45,43,40,36,32,32,30,26,23,21,20,21,21,21,22,24,26,29,33,35,37,37,36,35,33,30,26,24,22,19,20,21,22,22,22,22,22,22,22,23,25,26,27,28,29,28,27,26,24,23,22,22,22,23,23,22,22,21,20,20,20,20,19,17,16,15,16,18,19,20,22,24,27,28,28,27,26,27,27,27,26,25,23,21,19,15,15,15,16,16,16,16,16,15,15,14,13,12,11,11,10,9,8,7,7,7,7,8,9,6,6,6,6,6,6,6,7,6,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,7,7,7,8,8,8,8,8,9,9,9,10,10,10,10,11,11,11,11,10,10,10,10,10,10,10,9,9,8,8,8,8,9,11,13,15,16,17,17,19,19,19,19,19,18,17,16,15,15,14,14,15,15,16,17,16,16,16,17,18,20,21,22,27,29,33,37,39,41,41,41,39,37,35,33,31,30,30,30,24,23,22,23,24,27,30,32,32,30,28,26,24,24,24,24,27,30,33,36,38,41,44,47,49,50,51,50,47,41,35,31,27,28,29,31,32,33,33,33,34,35,36,37,35,32,29,27,25,25,26,28,31,35,38,41,42,46,51,57,65,75,85,92,89,81,67,52,41,35,33,33,43,47,51,52,50,45,41,40,37,36,39,47,60,74,86,92,92,86,74,60,47,38,35,35,45,54,67,80,86,87,83,79,74,69,62,55,51,48,45,42,39,38,41,49,62,78,90,97,94,86,73,60,48,41,37,36,40,43,47,54,63,75,88,96,103,101,95,82,67,57,55,57,63,66,68,64,56,44,35,29,28,30,34,39,44,48,52,53,55,49,45,44,45,48,57,66,85,98,111,117,118,115,108,100,86,78,69,65,64,69,81,93,100,98,92,80,65,53,47,45,49,52,53,48,39,33,33,35,56,66,78,83,79,66,51,42,39,43,51,59,64,62,57,52,44,38,36,40,45,47,51,56,61,63,63,61,58,55,54,54,50,52,57,63,71,80,87,91,86,78,64,47,34,28,28,30,44,55,66,68,65,60,50,41,33,32,31,30,29,29,29,29,29,31,34,37,39,39,38,37,32,30,27,25,24,25,26,27,33,37,43,49,54,55,56,55,48,45,42,43,45,47,45,42,41,40,39,38,39,40,42,44,40,37,34,31,30,29,26,24,25,23,21,18,17,18,19,20,20,20,21,23,26,29,32,33,33,33,31,29,27,24,21,19,18,19,20,21,21,21,20,20,22,23,25,27,28,28,28,27,26,25,24,22,21,20,20,20,21,21,21,21,21,21,21,21,21,20,19,18,19,20,21,23,24,26,27,29,29,29,28,27,25,25,25,25,24,22,21,20,16,16,17,17,18,18,19,19,18,18,17,15,14,13,12,11,9,8,7,7,7,7,8,9,7,7,7,7,7,7,7,7,6,6,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 5,5,5,5,5,5,5,5,6,6,6,6,6,6,6,6,7,7,7,8,8,8,9,9,9,9,9,10,10,10,11,11,12,12,12,12,12,12,12,12,12,12,11,10,10,9,9,8,6,7,8,10,12,14,15,16,18,19,20,20,20,20,19,19,17,16,16,15,15,16,17,17,16,16,16,17,18,20,21,22,26,28,32,36,40,43,45,46,46,45,43,41,39,36,34,33,26,24,22,21,23,27,31,34,40,40,39,37,34,30,27,24,26,28,32,36,39,42,44,45,46,48,50,51,49,44,39,36,31,31,32,32,33,33,33,33,35,36,36,36,34,32,29,27,24,24,25,28,31,35,39,41,43,45,50,54,61,70,79,86,83,76,63,48,38,33,34,36,47,50,54,55,51,45,40,37,37,36,37,41,50,61,72,78,77,73,65,54,43,37,35,35,47,55,67,78,81,78,71,66,59,55,50,46,44,42,40,39,36,38,43,53,66,80,89,94,87,79,66,53,44,39,39,40,43,45,49,54,62,73,84,92,99,100,97,88,76,67,64,64,63,64,64,59,51,42,36,32,30,32,35,40,45,51,55,58,60,53,47,45,45,48,58,69,88,104,123,134,137,134,124,114,99,86,70,59,53,56,69,81,91,94,94,87,75,62,53,50,52,54,54,48,39,33,31,32,49,57,67,72,67,56,44,36,36,42,53,64,71,70,64,59,46,39,35,37,41,43,48,54,59,59,58,55,51,48,48,48,50,53,58,65,73,81,87,90,85,77,63,47,34,29,30,33,44,56,67,70,68,61,50,40,32,30,29,27,27,28,29,30,31,34,37,40,41,41,40,38,30,29,27,25,24,24,25,26,32,33,37,41,44,47,49,50,48,48,50,53,56,55,52,48,46,44,42,41,41,40,39,37,34,30,27,25,25,26,26,25,23,21,19,17,16,17,18,20,19,20,20,22,24,26,28,29,30,29,28,27,24,22,20,18,18,19,19,20,20,20,19,19,22,24,26,29,29,28,27,25,24,23,21,20,19,19,19,19,19,19,20,20,21,22,23,23,22,22,22,21,22,23,25,26,29,29,30,30,30,29,28,27,23,23,23,23,22,22,21,21,18,18,19,19,20,21,21,22,21,21,19,17,16,14,13,12,9,9,8,7,7,8,9,9,9,9,9,9,8,8,8,8,7,7,6,6,6,5,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 5,5,5,5,5,5,5,5,6,6,6,6,6,6,6,6,7,7,8,8,8,9,9,9,9,9,10,10,10,11,11,11,14,14,14,14,14,14,14,14,14,14,13,12,11,10,10,9,6,7,8,9,11,13,14,15,18,19,20,21,22,22,22,22,19,18,18,17,17,17,18,18,17,17,17,18,19,21,22,23,25,27,29,33,37,42,45,47,50,50,49,48,45,42,39,37,29,26,23,21,23,27,33,38,48,50,52,51,47,39,31,25,26,27,30,33,37,39,40,40,41,43,46,48,47,45,41,39,37,37,36,34,33,32,32,31,33,34,34,33,32,30,28,27,24,24,25,27,31,35,39,41,42,44,46,48,51,57,64,69,68,63,53,42,35,34,38,43,52,55,57,56,50,43,38,35,33,33,33,35,39,46,52,57,61,59,54,46,39,35,34,35,45,51,60,67,70,67,61,57,50,48,45,43,42,41,37,35,33,37,45,57,70,81,87,89,83,75,62,50,43,41,43,45,47,48,51,54,60,70,80,87,96,97,96,90,81,73,70,69,64,64,61,56,49,42,38,37,35,37,40,44,50,55,59,62,62,55,47,44,42,45,54,65,85,104,125,140,145,143,134,124,108,93,74,58,49,48,58,70,83,88,93,91,81,70,61,57,56,57,55,50,41,35,32,32,41,47,55,57,53,45,37,31,35,43,56,69,78,78,73,67,53,44,37,36,37,39,44,50,55,56,54,51,46,42,41,41,48,51,57,64,71,77,82,84,79,72,59,44,33,28,30,33,44,56,66,69,66,59,48,38,30,29,26,25,26,28,31,33,36,38,41,44,44,42,39,37,29,29,27,26,26,26,27,27,30,31,32,33,36,39,42,43,47,51,57,63,65,64,59,55,51,48,45,44,43,41,37,34,29,27,24,23,26,29,30,31,25,23,21,18,17,18,19,20,21,21,21,22,23,25,27,28,28,28,27,26,24,22,20,19,20,20,21,21,21,20,20,19,23,24,27,28,29,27,25,24,22,21,20,19,18,18,18,18,18,19,20,22,23,25,26,27,25,25,25,26,26,27,28,29,32,32,32,31,29,28,27,26,21,21,21,21,22,22,23,23,21,21,22,22,23,23,23,24,22,22,20,19,17,15,14,13,10,10,9,9,9,9,10,10,11,11,10,10,9,9,8,8,7,7,7,6,6,6,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 6,6,6,6,6,6,6,6,7,7,7,7,7,7,7,7,8,8,8,8,9,9,9,10,10,10,10,10,11,11,11,12,15,15,15,15,16,16,16,16,17,16,16,14,13,12,11,11,9,9,9,9,11,12,14,15,17,18,20,22,23,24,24,24,22,21,20,19,19,19,20,20,18,18,19,19,21,22,24,25,25,26,27,30,34,39,43,46,50,51,52,52,50,47,44,42,34,30,25,22,24,30,37,42,54,59,65,67,63,52,39,31,28,27,27,29,32,35,35,34,35,36,39,41,42,42,41,40,40,39,37,34,32,31,31,30,31,31,31,31,30,29,28,27,26,26,27,29,32,36,39,42,42,42,41,40,39,42,46,50,50,49,45,39,35,38,46,53,61,62,62,58,50,43,37,35,31,33,36,37,37,39,41,44,50,49,46,42,37,34,34,35,39,44,50,56,59,59,56,54,48,46,44,43,42,40,36,33,35,40,50,64,76,84,87,87,81,73,61,50,44,43,46,49,51,51,52,54,58,65,74,81,91,91,89,84,77,71,68,67,65,65,62,56,49,44,42,41,43,45,48,52,56,60,63,65,62,54,46,42,39,40,48,58,81,98,119,133,140,141,135,128,110,96,78,62,50,44,50,58,73,80,88,89,84,74,67,64,58,58,56,51,44,38,34,33,35,39,43,45,42,37,33,31,37,45,59,74,84,85,81,76,62,52,41,36,35,36,40,46,52,53,52,48,43,38,36,35,41,45,51,59,66,72,75,77,70,64,54,41,31,27,28,31,46,55,63,64,59,54,44,36,29,27,25,24,26,30,35,38,42,44,46,47,46,42,38,35,29,29,28,28,29,29,30,31,31,31,30,30,31,33,35,37,46,52,61,68,71,69,64,60,53,49,45,43,43,41,36,32,26,24,22,23,26,29,31,32,27,25,23,21,20,21,22,23,25,24,24,24,25,26,27,28,29,29,28,28,26,24,23,22,22,23,23,23,23,22,21,21,24,25,26,27,26,25,24,23,21,20,19,18,18,18,18,18,19,20,22,24,27,29,31,32,31,31,32,32,32,32,32,32,34,33,32,30,27,25,24,23,20,20,20,21,22,23,24,25,25,25,25,25,24,24,24,24,22,21,20,19,17,16,15,14,12,12,11,10,10,11,12,12,13,12,12,11,10,10,9,9,8,7,7,7,6,6,6,6,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 6,6,6,6,6,6,6,6,7,7,7,7,7,7,7,7,8,8,8,9,9,9,10,10,10,10,10,11,11,11,12,12,15,16,16,16,17,17,18,18,19,19,18,17,15,14,13,13,12,12,11,11,11,12,14,15,17,18,20,23,24,26,26,27,24,23,22,21,21,21,21,22,20,20,20,21,22,24,25,26,27,27,27,28,32,36,41,44,49,51,53,54,54,51,48,45,38,34,27,24,25,32,41,47,59,68,79,85,82,70,54,44,32,29,26,26,29,31,30,29,29,30,32,34,36,38,39,40,38,37,34,32,31,30,30,30,29,29,30,30,30,29,29,29,30,30,30,32,35,38,41,43,41,40,38,34,31,31,34,37,39,40,41,39,39,44,55,63,71,70,67,60,51,43,38,36,37,42,47,50,49,47,46,47,46,46,44,41,36,33,32,33,35,40,47,54,58,60,59,58,56,53,48,44,42,41,39,37,43,49,61,75,87,92,92,90,79,71,60,50,45,45,48,51,49,49,49,49,51,57,65,70,78,77,75,71,67,65,64,65,70,69,67,61,55,50,49,49,51,53,56,60,63,65,66,66,62,54,46,41,36,36,42,51,72,86,103,114,121,125,123,118,107,96,80,66,53,43,43,48,60,68,78,81,78,72,67,65,57,56,54,50,45,40,36,35,32,34,36,36,34,32,32,33,40,48,62,78,88,91,87,83,72,59,45,38,34,33,37,43,49,50,50,47,41,35,31,30,34,38,44,51,57,61,62,63,57,54,47,39,32,30,32,35,48,55,59,57,52,47,40,33,27,25,23,23,26,32,38,42,48,50,51,51,47,41,35,31,29,29,30,31,32,33,34,35,34,33,32,30,30,31,32,33,43,50,61,70,73,70,66,62,53,47,42,39,40,39,35,31,27,25,23,24,26,29,30,30,26,25,23,22,22,24,27,28,29,28,28,27,28,28,29,30,30,31,30,30,29,27,26,25,25,25,26,26,25,24,23,23,25,25,24,24,24,23,22,22,20,20,19,18,18,18,18,19,20,22,24,27,30,33,35,36,38,39,39,39,39,38,38,37,34,33,31,28,25,23,21,20,20,20,20,21,22,24,26,28,28,28,27,27,26,25,25,24,21,20,20,19,18,17,16,16,14,13,13,12,12,13,13,14,14,14,13,12,11,10,10,9,8,8,7,7,7,6,6,6,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 6,6,6,6,6,6,6,6,7,7,7,7,7,7,7,7,8,8,8,9,9,10,10,10,10,10,10,11,11,12,12,12,16,16,16,17,17,18,18,19,21,20,19,18,17,15,14,14,15,14,13,12,12,13,14,15,17,18,20,23,25,27,27,28,26,25,24,23,22,22,22,23,21,21,21,22,23,25,26,27,29,28,27,28,31,35,40,43,47,50,53,55,55,53,50,47,41,36,29,25,27,34,43,49,65,75,89,98,97,84,68,56,35,31,26,25,27,29,28,27,25,26,27,29,32,35,38,39,35,33,31,30,29,29,30,30,29,29,29,30,30,30,31,31,33,33,33,35,37,40,43,45,41,39,36,31,28,27,29,31,34,37,40,41,43,50,61,70,77,76,71,62,52,44,39,38,44,51,60,64,63,59,57,56,46,46,45,41,36,32,31,31,35,40,49,57,63,65,65,64,66,60,52,46,44,44,43,43,52,59,72,86,97,102,100,97,77,70,60,51,46,46,49,51,45,45,44,43,44,48,56,61,65,64,62,60,60,61,64,66,76,75,73,67,61,57,55,55,56,58,62,65,68,68,68,67,62,54,46,40,35,33,39,46,62,74,87,96,102,107,108,105,103,94,81,69,55,43,40,42,50,58,68,73,71,67,64,63,55,54,53,49,45,40,37,36,32,33,33,32,30,31,33,36,42,50,64,80,91,94,90,86,77,64,48,39,34,32,35,41,48,49,50,47,41,34,29,27,30,33,38,44,48,49,49,49,45,44,41,37,34,35,39,42,49,54,57,52,47,43,37,32,26,24,22,23,26,33,40,45,52,53,54,52,48,41,34,29,29,30,31,32,34,36,37,38,37,36,34,32,31,31,31,32,41,49,60,69,72,70,66,63,51,45,39,36,38,38,34,30,29,27,26,26,28,29,28,27,24,23,22,22,24,27,30,32,31,31,30,30,30,30,31,31,32,32,32,32,31,29,28,27,27,27,28,27,27,26,25,24,26,25,23,22,22,21,22,22,20,20,19,18,18,18,19,19,22,23,25,29,32,35,38,39,44,44,44,44,43,42,41,40,34,33,30,27,23,21,19,19,20,20,20,21,22,25,27,29,30,30,29,28,27,26,25,24,19,19,19,18,18,17,17,16,15,15,14,13,13,14,15,15,15,14,14,13,12,11,10,10,8,8,8,7,7,6,6,6,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 4,4,4,5,5,6,6,6,8,8,8,8,8,8,8,8,10,10,10,10,10,10,10,10,12,11,11,11,11,12,13,14,15,15,16,17,18,20,21,22,21,21,20,19,18,17,17,16,16,16,16,15,14,14,13,13,18,19,21,23,25,27,29,30,29,28,28,27,26,25,25,24,27,25,24,23,23,25,28,30,26,27,28,27,27,29,32,35,39,41,44,47,48,48,47,46,41,37,32,28,28,35,46,54,67,85,100,104,104,102,88,70,50,40,29,25,27,30,28,24,24,25,25,27,29,32,34,36,34,30,27,26,29,33,36,37,34,30,29,30,30,28,30,34,32,34,37,39,40,43,47,50,52,49,43,38,34,32,32,32,38,42,46,50,54,62,72,80,84,85,81,68,53,42,40,43,49,65,80,85,85,85,78,70,65,55,47,43,40,34,31,31,36,42,49,57,68,79,80,77,77,68,57,49,41,37,40,48,61,75,91,101,105,104,98,90,78,69,59,53,52,52,49,46,41,42,41,39,38,42,51,58,52,50,47,43,43,49,60,68,76,79,81,77,70,64,64,66,61,63,65,66,66,64,62,60,54,49,41,35,33,36,41,44,54,59,64,68,71,76,83,89,88,87,82,71,57,44,37,35,39,47,58,65,66,64,60,58,47,44,42,42,44,44,41,38,32,31,29,29,32,37,43,47,55,59,66,75,83,88,88,87,77,69,56,41,31,29,33,37,42,46,49,47,39,31,26,24,24,28,33,36,38,40,42,44,39,38,37,36,36,38,39,40,46,47,46,45,43,40,37,35,25,22,22,26,29,34,43,52,59,61,60,56,47,36,28,23,24,25,29,33,34,33,38,46,44,45,46,44,40,37,35,35,39,44,52,61,66,65,59,55,41,40,38,35,33,32,31,31,28,27,27,27,27,27,27,27,21,21,22,24,26,29,31,33,32,29,27,27,29,31,32,32,36,35,34,33,31,30,28,28,26,27,28,29,29,27,26,25,25,25,25,25,24,23,21,21,21,21,20,20,20,21,21,22,25,27,31,34,36,40,45,49,53,54,55,54,52,49,46,44,38,35,31,27,25,23,19,17,19,20,22,24,26,28,29,30,32,32,31,30,28,26,24,23,20,19,18,17,17,18,20,21,19,19,19,18,17,17,16,16,18,17,16,15,13,12,11,11,8,8,8,8,8,8,8,8,6,6,6,7,7,8,8,8,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 4,4,4,5,5,6,6,6,8,8,8,8,8,8,8,8,10,10,10,10,10,10,10,10,12,12,11,11,12,12,13,14,15,15,16,16,18,19,21,22,21,21,21,20,20,19,19,19,19,18,18,17,16,15,14,14,17,18,20,22,25,28,30,31,30,30,30,29,29,28,28,27,28,27,25,24,25,27,29,31,27,28,29,28,27,28,30,33,36,37,39,41,43,43,43,43,39,36,32,28,28,34,43,49,64,82,98,104,107,107,95,79,59,48,36,30,31,34,33,30,29,29,30,31,32,34,35,36,34,31,28,27,30,34,37,38,39,34,31,33,32,30,32,36,38,41,45,48,50,53,56,59,61,58,53,47,44,42,43,43,48,51,54,56,59,65,75,82,87,87,83,71,55,43,40,41,55,72,91,101,106,108,103,95,78,66,54,47,42,35,33,34,41,49,59,69,81,91,92,87,83,72,58,48,39,36,42,51,68,83,99,107,109,106,97,89,74,67,58,53,52,51,48,45,39,39,38,37,38,41,47,51,46,43,38,35,36,45,58,68,82,86,88,84,76,69,67,68,59,60,61,61,60,57,55,53,47,43,37,33,32,34,39,42,49,52,56,57,58,62,69,75,83,83,79,69,55,43,35,33,34,40,49,57,59,57,53,50,43,40,37,37,39,39,38,36,36,35,35,36,40,45,50,54,57,59,62,68,75,79,81,80,74,66,54,40,30,27,30,34,41,46,49,47,40,31,25,23,22,25,29,32,33,33,34,35,34,35,36,38,39,40,41,41,44,44,44,43,40,37,34,32,26,23,23,26,30,35,45,55,61,62,60,54,44,34,26,22,24,25,29,34,34,34,40,48,50,53,55,54,49,43,38,36,37,41,47,54,58,57,53,48,39,38,36,34,32,30,29,29,27,27,28,28,28,26,25,24,20,22,24,27,29,31,32,33,30,28,27,28,30,33,35,35,38,37,36,34,31,29,27,27,25,26,27,28,28,27,26,25,25,26,26,26,26,24,23,22,22,22,21,21,21,22,23,24,28,31,35,39,42,47,52,55,59,60,61,61,58,54,50,47,39,35,30,27,25,23,21,19,22,23,24,26,28,29,31,31,32,32,31,29,27,25,23,22,20,19,18,18,18,20,21,22,21,21,20,20,19,18,18,17,17,17,16,15,13,12,11,11,8,8,8,8,8,8,8,8,6,6,6,7,7,8,8,8,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 4,4,4,5,5,6,6,6,8,8,8,8,8,8,8,8,10,10,10,10,10,11,11,11,12,12,11,11,12,13,14,14,15,15,15,16,17,18,20,21,21,21,21,22,22,23,23,23,22,22,21,19,18,16,15,15,17,18,19,22,25,28,31,32,33,33,33,33,33,33,32,32,31,30,28,27,27,29,31,33,30,31,31,29,27,26,28,30,32,32,32,33,34,35,37,37,34,33,30,27,27,30,36,41,56,74,92,102,109,112,104,92,73,61,47,39,38,41,41,40,37,37,38,38,38,39,39,39,37,35,32,32,35,38,40,41,44,39,35,35,33,32,34,39,44,48,55,61,64,67,70,72,74,71,65,60,56,55,55,55,62,63,63,62,62,67,75,82,89,89,86,74,58,45,39,38,54,71,93,109,118,121,117,111,92,78,62,52,44,38,38,42,49,60,74,86,98,105,103,97,90,76,59,45,36,35,45,56,77,91,106,112,111,104,92,81,68,62,56,52,50,49,45,42,38,37,37,39,43,45,46,46,41,37,31,28,32,44,60,71,89,92,94,90,81,72,66,64,55,56,56,55,52,49,46,45,40,37,34,32,32,35,38,41,45,46,47,45,44,47,54,60,75,76,74,66,53,41,34,31,31,35,41,48,52,51,46,42,38,36,33,33,34,35,36,35,37,38,40,44,48,53,58,60,60,58,56,57,61,66,69,70,68,62,51,38,29,25,27,29,40,45,50,48,40,31,25,22,21,24,27,29,28,27,27,27,28,31,36,41,43,43,41,40,39,39,39,38,36,33,31,29,27,24,23,26,30,36,47,58,64,63,60,52,41,31,24,21,24,25,29,34,35,36,43,51,59,64,68,67,61,51,42,37,35,37,41,46,50,50,46,43,37,36,34,32,30,28,27,26,26,27,29,30,29,26,23,21,19,21,26,30,32,33,32,31,27,25,25,27,31,36,38,39,42,41,39,35,32,29,26,25,24,25,26,26,27,26,26,25,26,27,28,29,28,27,26,25,23,23,22,21,22,23,25,26,31,35,40,45,49,54,59,63,65,66,68,68,64,58,52,48,40,36,30,26,24,24,23,22,26,27,28,30,31,32,33,33,32,32,30,28,26,24,22,22,19,19,19,19,20,22,24,25,24,24,23,22,21,20,20,19,16,16,15,14,13,12,11,11,8,8,8,8,8,8,8,8,6,6,7,7,7,7,8,8,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 4,4,4,5,5,6,6,6,7,7,8,8,8,8,9,9,10,10,10,11,11,11,11,12,13,12,12,12,12,13,14,15,15,15,15,15,16,17,19,20,20,21,22,23,24,25,26,26,26,25,24,22,20,18,17,16,17,18,19,21,24,28,31,33,36,36,36,37,37,38,38,38,35,34,32,31,31,32,34,36,34,35,35,33,29,28,28,29,30,29,27,26,27,28,30,32,29,29,28,26,24,25,28,31,46,62,81,95,106,112,109,101,86,75,60,50,47,49,50,50,47,47,47,47,47,47,47,47,46,45,43,44,46,47,47,46,48,41,36,35,33,32,36,42,48,54,64,72,78,82,85,87,87,83,77,71,66,63,63,63,69,69,67,63,60,62,69,75,85,87,84,75,60,46,37,34,47,62,84,102,114,117,113,108,95,81,65,54,46,43,47,53,59,72,87,99,108,112,108,100,91,76,58,43,34,35,47,59,83,96,108,112,107,97,82,70,60,57,52,50,48,46,42,39,39,39,41,47,53,55,52,49,43,38,32,31,38,52,69,80,95,96,95,89,78,67,59,55,51,51,50,48,45,42,39,38,36,34,33,33,34,36,39,41,44,44,42,38,36,39,46,52,65,68,67,61,50,40,34,32,34,36,40,45,49,48,44,40,37,35,33,32,32,33,34,35,36,39,44,50,55,59,62,63,61,56,49,46,48,52,56,59,61,56,47,36,27,23,24,26,39,45,49,48,40,31,24,21,21,24,27,29,27,25,24,23,25,29,36,42,45,43,39,36,32,33,34,34,33,31,29,28,28,24,22,26,30,36,48,59,65,63,58,49,39,30,24,22,26,27,30,35,36,37,45,53,66,72,78,78,70,58,45,38,33,34,36,40,44,45,44,42,37,36,35,33,31,28,26,25,25,28,30,32,30,26,21,18,17,21,27,32,34,33,31,28,22,21,22,26,32,38,41,42,47,45,42,38,33,28,25,23,23,23,24,25,25,26,26,26,28,29,31,32,32,30,28,27,24,23,22,22,23,25,28,29,34,38,44,50,54,59,65,68,69,71,73,72,67,60,52,47,40,35,29,25,24,25,25,25,29,30,32,33,34,34,33,33,31,30,28,26,24,22,21,21,18,19,20,21,23,25,26,27,27,26,25,24,23,22,21,21,16,15,15,14,13,12,11,11,9,9,9,9,9,9,9,9,7,7,7,7,7,7,7,7,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 4,4,4,5,5,6,6,6,7,7,7,8,8,9,9,9,10,10,10,11,11,12,12,13,13,13,12,12,13,13,14,15,15,14,14,14,15,16,17,18,19,20,21,22,24,26,27,28,28,27,26,24,22,21,19,18,18,18,19,21,24,27,31,34,37,37,38,39,40,41,42,43,40,38,36,34,34,36,38,39,39,40,40,38,34,32,32,32,31,29,26,24,23,24,26,27,24,25,25,24,22,21,23,24,35,48,66,82,96,105,107,105,94,84,71,60,56,56,56,56,56,55,54,54,55,56,57,58,61,61,61,61,62,60,56,53,49,41,34,33,32,33,39,46,55,62,73,83,90,95,98,100,98,94,87,79,72,69,67,66,68,67,64,59,53,53,58,63,77,79,79,73,61,48,38,33,40,50,68,87,100,104,103,102,86,76,64,56,52,51,58,67,73,85,98,106,110,110,104,97,87,74,58,46,39,40,51,63,87,98,107,106,99,87,71,59,53,51,48,46,44,42,39,36,38,40,45,53,60,62,58,54,47,43,39,41,50,64,79,88,99,97,92,83,71,59,50,45,43,43,42,41,39,36,35,34,34,33,32,33,34,36,39,41,43,42,40,35,32,35,43,49,57,60,61,56,48,40,36,36,39,40,43,45,47,45,42,40,37,36,35,32,31,30,31,32,36,41,48,56,62,64,64,63,58,51,42,37,38,42,48,51,56,52,44,34,26,23,24,26,40,44,49,47,39,30,24,21,20,23,27,29,27,24,22,21,24,29,36,41,43,41,36,33,28,29,30,31,31,30,29,28,26,23,22,25,29,35,46,56,63,61,56,48,39,31,27,25,30,30,33,36,37,38,45,54,68,74,81,82,75,61,48,40,31,31,32,36,40,42,42,41,39,39,38,36,34,31,28,26,26,28,32,33,32,27,22,18,18,22,28,33,35,33,28,25,19,19,20,25,33,40,44,46,51,49,45,40,34,29,25,23,23,23,23,24,25,26,27,28,30,32,34,35,35,33,31,29,25,24,22,22,24,26,30,32,38,42,49,55,59,64,68,71,73,74,75,74,69,61,52,47,38,33,27,24,24,25,26,27,30,32,33,35,35,34,32,31,28,27,25,23,21,20,20,20,19,19,21,23,25,27,28,28,28,28,27,25,24,23,22,21,15,14,14,13,12,12,11,11,9,9,9,9,9,9,9,9,7,7,7,7,7,7,7,7,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 4,4,4,5,5,6,6,6,6,6,7,8,8,9,10,10,10,10,11,11,12,13,13,13,13,13,13,13,13,14,15,15,14,14,14,14,14,15,16,17,18,18,19,21,23,24,26,26,28,28,27,25,24,22,21,21,20,20,20,20,23,26,30,33,37,37,38,40,42,44,45,46,44,42,40,38,38,39,41,42,43,45,46,44,42,39,39,39,35,33,29,26,24,23,23,24,23,24,25,24,22,21,21,23,27,37,51,68,82,94,100,102,97,89,79,70,64,61,60,59,60,58,57,57,59,64,68,71,78,78,80,81,79,73,64,58,47,39,32,30,31,35,43,52,65,72,82,91,97,101,104,106,101,96,89,80,74,69,67,67,64,64,61,55,49,46,48,52,65,69,72,71,63,52,41,35,32,35,47,64,77,84,87,90,76,70,64,62,60,61,68,77,84,93,101,102,102,100,95,89,81,72,62,56,52,52,60,70,89,97,102,97,88,76,62,51,47,46,44,42,40,38,36,35,37,41,49,57,63,63,60,57,51,49,50,55,65,77,87,93,98,93,84,72,61,51,44,40,37,37,37,36,36,36,36,36,36,35,34,33,34,36,39,41,41,41,38,34,31,33,39,46,50,53,55,52,47,42,42,43,44,46,48,46,43,41,40,40,40,40,39,36,32,29,27,28,37,44,53,62,67,67,63,61,51,45,37,32,33,39,44,47,52,48,41,33,26,24,27,30,41,45,48,45,37,29,24,23,20,24,28,29,27,23,20,19,23,27,33,38,40,38,35,32,29,30,31,31,31,30,28,27,24,21,21,25,28,32,41,51,58,57,54,48,41,35,32,31,36,35,36,38,37,37,44,53,66,73,80,81,75,63,51,44,32,32,33,36,39,41,40,39,42,42,42,40,37,34,30,28,27,29,32,34,33,29,24,21,21,25,31,35,36,33,28,24,19,19,21,27,36,44,49,51,54,51,47,41,35,30,25,23,23,23,23,24,25,27,29,30,34,36,38,39,38,35,32,30,24,23,22,21,23,27,31,34,42,46,53,58,61,65,68,70,74,74,74,72,67,59,51,46,34,30,26,23,24,25,26,26,30,31,33,34,33,31,29,27,24,22,20,19,18,18,19,20,20,21,23,25,27,28,29,29,28,27,26,25,23,22,21,20,14,13,13,13,12,12,11,11,10,10,10,10,10,10,10,10,8,8,7,7,7,7,6,6,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 4,4,4,5,5,6,6,6,6,6,7,8,8,9,10,10,10,10,11,11,12,13,14,14,14,13,13,13,13,14,15,16,14,14,13,13,14,14,15,16,16,17,18,19,21,22,23,24,27,27,26,25,24,24,23,22,23,22,20,20,22,25,29,31,35,36,38,40,42,44,46,47,47,45,43,41,40,41,43,44,47,49,51,50,48,47,46,47,40,38,34,30,27,24,23,23,24,26,27,26,24,23,24,25,24,29,40,55,70,82,92,98,94,90,83,76,70,65,61,58,59,57,56,56,60,68,76,81,91,93,96,97,93,83,70,60,46,38,31,30,32,37,48,58,73,78,85,91,95,97,99,100,92,88,81,74,68,64,63,63,62,62,61,55,48,44,44,47,54,60,67,70,66,57,47,41,32,28,32,44,55,62,69,75,72,70,70,71,70,70,75,82,85,91,94,90,85,83,81,77,76,72,70,71,69,68,72,79,87,92,92,84,74,64,53,44,43,43,41,38,36,35,35,35,39,46,55,62,64,62,60,58,57,58,62,71,82,91,95,96,90,82,70,57,48,42,39,37,37,38,38,40,42,44,45,46,45,43,40,38,38,40,43,45,43,43,40,35,31,31,36,42,46,49,51,49,46,45,47,50,50,53,55,51,43,38,40,44,48,49,49,45,38,32,29,28,36,43,54,63,67,65,59,54,43,39,33,30,33,39,44,47,50,46,39,31,26,26,31,35,42,45,47,43,35,28,25,24,27,30,34,34,30,24,20,18,21,24,28,33,36,36,36,35,34,35,35,34,32,29,26,24,21,19,20,24,27,29,36,44,52,53,52,49,44,40,38,37,41,39,39,39,37,36,42,50,64,70,76,78,73,64,55,49,42,41,41,42,44,44,42,40,44,44,44,42,40,36,32,29,28,30,33,34,34,31,27,25,27,30,35,38,38,34,28,25,22,22,25,31,40,48,54,56,55,53,48,43,36,31,26,24,23,23,23,24,26,28,31,32,37,39,41,42,40,37,32,29,24,22,21,20,23,27,32,35,41,45,51,55,58,59,61,63,68,68,67,64,59,52,46,42,30,27,24,23,24,25,25,25,28,29,31,32,31,28,25,23,19,18,16,15,15,16,18,19,21,23,25,27,29,29,29,29,27,26,25,24,22,20,19,18,13,13,13,12,12,12,11,11,10,10,10,10,10,10,10,10,8,8,8,7,7,6,6,6,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 4,4,4,5,5,6,6,6,6,6,7,8,8,9,10,10,10,10,11,12,13,13,14,15,14,13,13,13,13,14,15,16,14,14,13,13,13,14,15,15,15,16,17,18,19,21,22,22,27,26,26,25,25,24,24,24,24,23,21,20,21,24,28,30,35,36,37,40,42,45,46,47,48,47,44,42,42,43,44,45,48,51,54,54,53,52,52,52,44,42,38,34,30,26,24,22,27,28,29,28,26,26,27,28,23,26,35,49,63,76,87,95,92,90,85,79,73,66,60,57,57,55,53,54,60,69,80,86,98,101,105,107,101,88,72,61,45,37,30,30,33,40,51,62,76,79,84,88,89,89,90,92,81,77,71,65,60,58,57,57,61,63,62,57,50,45,44,45,48,55,64,70,68,61,51,45,42,33,30,37,46,51,59,67,72,72,75,79,78,75,78,84,81,85,84,77,71,70,69,67,74,74,77,81,82,79,81,85,83,86,84,74,63,54,45,37,41,41,39,36,33,33,34,35,44,52,61,66,65,62,60,59,62,65,72,83,94,101,101,99,80,71,57,45,37,35,34,35,41,42,44,46,50,53,56,58,54,51,47,44,43,45,48,50,47,46,44,38,33,32,36,40,44,47,48,47,45,46,51,55,55,60,62,56,45,39,42,48,56,58,59,54,46,38,33,31,33,41,52,61,64,60,53,48,39,35,31,30,34,40,45,48,49,45,38,31,26,28,33,38,43,46,46,41,34,27,25,25,35,38,40,39,34,27,22,19,18,21,25,29,33,36,38,38,40,39,38,36,32,28,24,21,19,17,19,24,26,27,33,40,48,50,51,50,46,43,41,41,45,42,41,40,37,35,41,49,62,68,74,76,72,64,57,53,52,51,50,51,51,49,45,42,45,45,45,43,40,36,32,29,29,30,33,34,34,32,30,28,32,34,38,40,39,35,30,26,25,25,28,34,43,52,57,59,56,53,49,43,37,31,27,25,24,24,24,25,27,29,32,34,39,41,43,43,41,37,32,29,23,22,20,20,22,27,32,35,37,41,46,50,52,52,54,55,62,61,59,56,51,45,39,36,28,26,24,23,25,25,25,24,27,28,30,31,29,26,22,20,17,15,14,13,13,15,18,19,23,24,26,28,29,30,29,29,26,26,24,23,21,19,18,17,13,13,12,12,12,12,11,11,10,10,10,10,10,10,10,10,8,8,8,7,7,6,6,6,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 4,4,4,4,4,4,4,4,6,6,6,7,7,8,8,8,9,9,10,11,11,12,13,13,13,13,13,14,14,15,15,15,14,14,14,14,14,14,14,14,14,14,15,16,18,21,23,24,24,24,25,25,25,26,26,26,28,26,24,23,23,24,26,27,31,31,33,36,39,43,46,47,47,46,46,45,44,45,45,45,50,52,54,55,55,54,52,50,48,46,43,39,34,30,26,24,27,28,31,33,34,33,32,31,27,26,28,34,45,61,76,85,84,83,80,76,70,62,56,52,47,46,46,49,56,66,77,83,97,100,103,103,96,84,71,62,44,39,33,34,41,51,59,63,82,82,82,83,83,80,74,70,68,64,57,50,47,49,54,58,57,64,68,64,58,54,49,43,50,53,59,65,68,69,68,66,53,44,39,41,45,51,63,75,80,86,86,80,76,77,76,72,74,72,67,59,53,54,60,66,74,79,87,94,97,95,92,89,81,78,71,62,53,45,39,36,41,40,41,40,35,31,36,45,53,62,72,75,70,63,59,58,58,69,83,96,106,109,100,89,77,59,41,34,33,32,35,41,42,44,48,54,59,62,64,64,66,61,54,50,50,52,54,56,56,55,51,43,36,33,36,40,41,45,49,50,49,50,54,57,68,64,59,53,43,36,39,47,58,69,76,71,60,49,39,31,37,44,54,62,64,60,51,45,37,32,29,30,36,43,46,47,44,40,34,29,28,31,36,39,43,45,46,40,32,27,27,29,36,41,46,46,40,32,26,24,20,22,24,28,32,36,39,41,42,44,45,42,36,28,23,20,16,18,20,22,23,27,32,36,43,47,51,52,51,48,47,46,46,44,41,38,37,38,40,41,51,54,59,61,61,61,61,61,63,63,63,61,57,52,46,43,41,43,44,44,42,38,34,31,31,32,34,34,33,31,29,27,31,35,41,45,44,38,31,25,24,26,30,36,42,49,54,57,56,53,48,42,36,32,29,28,25,26,26,26,26,27,30,33,35,39,42,42,38,32,28,25,19,18,18,19,22,27,32,35,35,39,43,44,43,43,45,48,51,50,48,47,45,40,34,30,21,22,22,22,22,22,23,23,25,25,24,23,22,21,20,20,14,13,12,13,15,18,21,23,23,25,28,31,32,31,29,27,23,23,22,20,18,17,16,15,12,12,12,13,13,14,14,14,12,12,12,11,11,10,10,10,9,8,7,6,5,4,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,5,4,2,2,3,4,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 4,4,4,4,4,4,4,4,6,6,6,7,7,8,8,8,9,9,10,10,11,12,13,13,13,13,13,14,14,15,15,15,14,14,14,14,14,14,14,14,14,14,15,16,18,20,22,23,23,24,24,24,25,25,25,26,27,26,24,23,23,24,26,27,29,30,31,34,37,41,44,45,47,46,45,44,44,44,44,44,48,50,52,53,53,52,50,48,47,45,42,38,34,30,28,26,26,28,30,33,34,35,34,34,30,29,29,32,41,53,65,73,77,76,74,70,64,58,52,49,42,41,42,45,53,63,73,79,89,91,92,91,85,75,66,60,50,46,42,43,50,58,64,67,74,74,74,73,72,68,62,57,54,50,45,41,40,44,50,55,64,71,75,71,66,61,56,50,50,52,56,60,65,68,71,72,69,62,57,60,64,69,78,89,92,96,94,84,75,71,65,59,60,59,55,49,45,46,52,58,74,80,88,95,97,94,89,84,74,70,63,54,46,39,34,32,39,39,39,39,35,34,41,51,62,71,80,81,73,63,56,54,56,67,82,95,105,105,95,82,65,50,35,32,34,37,41,45,49,51,54,59,64,68,69,70,67,62,55,50,51,54,57,59,59,58,53,46,38,34,36,39,42,45,48,48,47,49,53,57,66,63,59,53,43,36,39,47,64,76,85,83,72,60,47,38,38,44,54,62,64,59,50,43,35,31,28,31,37,42,45,45,41,37,32,28,28,31,35,39,41,44,44,39,32,28,28,30,38,43,49,49,44,37,30,27,22,23,25,27,31,35,39,41,44,45,46,43,36,29,23,21,17,18,20,21,22,25,30,33,42,46,51,53,52,49,47,46,43,41,38,35,35,35,37,39,47,50,54,57,59,60,62,63,71,72,72,70,65,58,51,46,41,42,42,41,39,36,33,31,30,31,32,33,32,31,30,29,32,36,41,44,43,37,30,25,23,25,28,34,39,45,50,52,51,48,44,39,35,32,30,29,27,27,27,26,25,25,28,30,33,37,40,40,37,32,27,25,19,19,19,21,24,27,31,33,28,31,34,34,33,34,36,39,42,40,39,38,37,33,28,24,21,21,21,21,22,22,22,22,23,22,21,20,19,18,17,17,14,13,13,13,15,17,20,22,23,25,28,30,30,29,27,25,21,21,20,19,17,16,15,14,12,12,12,13,13,14,14,14,12,12,12,11,11,11,10,10,9,8,7,6,5,5,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,4,3,2,2,3,3,2,1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 4,4,4,4,4,4,4,4,6,6,6,7,7,8,8,8,9,9,9,10,11,12,12,13,13,13,13,14,14,15,15,15,14,14,14,14,14,14,14,14,14,14,15,16,17,19,21,22,22,22,23,23,24,24,24,24,26,25,24,23,23,24,25,27,27,28,29,32,35,39,42,43,46,45,44,42,41,41,41,41,44,45,47,48,48,47,45,44,44,42,40,37,34,31,29,27,25,26,29,32,34,36,37,38,35,33,30,30,34,42,51,57,65,64,62,59,55,50,46,43,37,37,38,42,48,57,66,71,78,77,76,74,71,67,64,62,58,56,54,56,60,64,67,68,67,66,65,64,62,56,48,43,38,35,32,31,35,42,49,54,69,76,79,76,72,68,62,55,49,49,50,53,59,68,76,81,85,81,80,83,87,92,99,107,107,107,101,87,72,62,53,46,44,45,45,42,40,42,49,54,75,81,89,95,96,90,83,77,66,62,55,47,40,35,32,30,37,36,36,37,36,38,48,61,76,85,93,92,80,65,53,48,53,65,81,94,101,99,85,71,49,39,30,32,39,45,49,53,55,55,57,61,66,70,72,72,66,60,53,49,50,55,59,62,62,61,57,49,40,35,35,37,42,44,46,45,44,46,51,56,64,61,59,53,44,37,40,47,69,83,95,96,87,74,57,45,40,46,55,62,64,59,48,40,32,29,27,30,36,41,42,41,36,33,29,26,27,30,35,38,39,41,42,38,33,29,30,31,39,44,51,53,50,42,35,31,25,24,24,25,27,32,36,39,44,45,46,42,36,29,24,21,17,19,20,20,21,23,27,30,39,44,50,53,52,49,46,44,38,36,34,32,31,32,33,34,40,43,48,51,54,58,62,65,76,78,79,78,72,63,53,47,41,40,38,37,34,32,31,30,28,29,29,29,30,30,30,30,34,37,41,43,41,35,29,24,21,23,26,30,35,40,43,45,42,40,37,34,32,31,30,30,29,29,28,25,22,22,23,25,30,33,37,38,35,31,27,26,20,21,22,25,27,28,29,30,23,24,24,24,23,24,27,30,31,30,29,29,28,26,22,19,20,20,20,21,21,22,22,22,20,19,18,17,16,15,14,13,13,13,13,13,15,17,20,21,24,25,27,28,28,26,24,22,19,18,18,17,16,15,14,13,12,12,12,13,13,13,13,14,12,12,12,12,11,11,11,10,9,9,7,6,5,5,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,2,2,1,0,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 5,5,5,5,5,5,5,5,6,6,6,7,7,8,8,8,8,8,9,10,11,11,12,12,13,13,13,14,14,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,16,18,19,20,21,21,21,22,22,22,23,23,25,24,23,23,23,24,25,26,27,27,29,32,35,39,42,43,44,43,41,39,38,36,36,36,38,39,40,40,40,40,39,38,38,37,36,34,32,30,29,28,23,24,27,29,33,36,39,40,38,36,32,29,30,35,40,44,51,51,50,48,45,42,39,37,35,35,36,40,45,51,56,60,65,63,61,59,60,63,66,69,69,69,68,67,67,66,64,63,63,62,62,61,58,52,44,38,31,29,27,29,36,45,54,59,69,74,76,73,70,67,61,54,47,45,43,45,53,65,77,85,92,93,96,101,108,114,120,125,122,116,102,83,65,51,43,39,36,40,44,46,47,49,55,60,73,78,86,91,90,84,75,68,62,58,52,45,40,36,35,34,36,34,34,36,36,42,56,70,92,100,108,104,89,68,52,44,49,62,77,89,95,91,74,58,38,33,31,37,48,56,61,62,57,55,54,56,61,65,66,65,60,54,47,44,46,52,58,61,64,64,59,51,41,35,34,36,42,43,44,42,41,42,47,52,59,58,56,53,44,37,39,46,67,83,99,104,98,84,65,50,44,48,55,62,64,58,47,38,28,26,25,28,33,37,37,35,30,29,27,26,28,32,36,39,39,40,40,37,33,31,31,32,38,43,50,54,52,46,39,34,26,24,22,21,23,27,32,36,40,42,42,39,33,27,22,21,18,19,20,20,19,21,24,27,36,42,49,52,51,47,43,41,33,31,29,28,27,28,29,30,33,36,40,45,49,54,60,65,75,77,79,77,72,62,52,45,40,38,35,32,29,28,27,27,25,25,25,25,26,28,29,30,34,37,40,41,39,33,27,23,20,21,24,27,31,33,35,36,32,31,30,28,28,29,30,31,29,29,27,23,19,18,18,20,26,30,34,35,33,31,29,28,22,24,27,30,31,30,29,27,22,21,20,19,18,20,23,25,24,23,22,23,24,23,21,18,19,19,20,20,21,22,22,22,19,18,17,16,14,13,12,11,13,13,13,13,15,17,19,20,24,24,25,26,25,23,20,19,16,16,16,15,14,14,13,13,13,13,13,13,13,13,14,14,13,13,12,12,12,11,11,11,10,9,8,6,6,5,5,6,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,1,2,4,4,2,1,0,0,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 5,5,5,5,5,5,5,5,6,6,6,7,7,8,8,8,8,8,9,9,10,11,12,12,13,13,13,14,14,15,15,15,15,15,15,15,15,15,15,15,15,15,14,14,15,16,17,18,19,19,20,20,20,21,21,21,23,23,23,23,24,24,25,26,28,29,30,33,36,40,43,45,43,42,39,37,34,32,31,31,32,32,33,33,33,33,32,32,32,32,31,31,30,30,29,29,23,24,25,27,31,35,38,40,40,37,33,30,29,31,34,36,40,39,39,37,36,34,32,31,35,35,37,39,42,45,47,49,50,48,46,47,52,60,69,75,82,82,81,77,71,64,58,55,56,57,58,60,58,54,46,41,34,31,29,32,40,50,57,60,65,68,68,65,63,61,56,50,43,40,38,39,47,60,74,82,93,98,105,114,123,133,139,142,136,123,102,77,56,41,36,37,38,44,52,57,58,60,63,67,68,72,78,81,80,74,66,60,57,54,50,45,42,40,39,39,36,34,34,36,38,45,61,76,102,111,118,113,96,73,54,45,47,58,72,82,87,81,64,48,34,34,38,47,60,70,72,70,59,55,50,51,54,57,57,54,49,44,39,37,40,47,53,56,64,63,58,49,39,33,33,35,41,44,45,44,41,40,43,46,53,53,53,50,42,35,37,43,63,80,99,107,105,92,73,56,49,51,55,61,64,59,49,40,28,25,23,25,30,33,32,30,27,27,27,28,31,36,40,43,41,41,40,38,35,32,32,32,35,39,45,50,51,47,40,35,27,24,20,18,18,22,27,30,34,36,36,34,29,24,20,19,19,20,20,19,19,20,23,25,34,39,46,49,47,43,38,36,28,27,26,25,25,25,26,27,27,30,35,39,44,49,55,60,67,69,71,71,66,59,51,46,42,39,35,30,27,25,24,24,23,23,23,23,24,26,27,28,34,35,37,38,35,31,25,22,20,21,23,25,27,28,28,28,25,24,24,24,25,27,29,30,28,27,25,21,17,15,15,17,24,28,32,34,33,32,31,31,28,30,34,36,36,33,30,27,23,21,18,17,17,18,20,21,19,18,17,18,20,21,19,18,19,19,20,21,22,22,23,23,21,20,19,17,15,14,12,12,12,13,13,14,15,16,17,18,22,23,23,23,21,20,18,17,15,15,15,15,15,14,14,14,15,15,15,15,14,14,14,14,13,13,13,12,12,12,11,11,10,9,8,7,6,6,6,6,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,0,2,4,4,2,0,1,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 6,6,6,6,6,6,6,6,6,6,6,7,7,8,8,8,7,8,8,9,10,11,11,11,13,13,13,14,14,15,15,15,16,16,16,16,16,16,16,16,15,15,14,14,14,15,16,16,18,18,18,18,19,19,20,20,21,22,22,23,24,24,25,25,29,30,32,34,38,41,44,46,44,42,39,36,33,31,29,29,28,28,28,28,28,28,28,28,28,28,29,29,30,31,31,31,27,26,26,27,30,34,38,40,41,38,34,31,29,29,31,32,32,32,31,30,29,28,27,27,32,33,36,38,40,41,41,41,38,37,36,39,46,58,69,77,90,90,88,82,71,60,51,46,46,49,53,58,60,58,53,48,42,37,34,36,43,51,55,57,60,61,58,54,53,54,50,45,38,36,34,36,43,54,65,73,87,95,105,116,128,141,149,150,143,125,100,74,51,37,36,40,48,55,64,68,68,67,66,67,61,63,66,67,66,62,57,54,52,50,49,46,44,43,42,42,38,36,36,38,40,47,63,78,105,114,121,116,99,76,57,47,46,55,66,74,77,72,56,41,34,39,47,58,73,84,84,78,65,58,50,47,49,50,48,45,40,36,32,32,37,43,49,52,60,59,53,44,35,31,32,35,43,47,50,50,45,41,40,40,46,46,48,47,39,32,33,39,58,75,95,107,108,99,81,65,55,54,55,60,63,61,52,43,31,27,24,24,27,30,29,27,26,27,28,32,36,41,45,48,46,44,42,39,36,33,31,30,31,34,39,45,47,45,40,35,28,25,20,17,17,19,23,26,28,30,30,29,25,21,19,19,20,20,21,20,19,20,23,26,32,36,42,43,41,36,32,30,25,25,24,24,24,24,24,25,23,26,31,36,39,43,48,52,57,58,59,60,59,56,53,50,46,44,39,34,29,25,23,23,22,22,23,24,25,26,27,27,31,32,34,34,32,28,24,22,21,22,24,25,25,24,23,22,20,20,20,20,22,24,27,28,27,27,25,21,17,15,16,17,23,27,32,34,35,35,35,36,36,38,40,42,40,37,33,30,24,22,19,17,18,18,18,17,15,13,13,14,16,18,17,16,19,20,20,22,23,24,25,25,23,22,21,19,17,15,13,13,12,12,13,14,15,16,16,17,20,20,20,20,19,17,16,15,15,16,16,16,16,16,17,17,17,17,17,16,16,16,16,15,14,13,13,13,12,12,12,12,10,10,8,7,6,6,6,6,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,0,2,4,3,1,1,5,8,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 6,6,6,6,6,6,6,6,6,6,6,7,7,8,8,8,7,7,8,9,10,10,11,11,13,13,13,14,14,15,15,15,16,16,16,16,16,16,16,16,15,15,14,14,13,14,14,15,16,17,17,17,18,18,18,19,20,21,22,23,24,25,25,25,29,30,32,34,38,41,44,46,47,45,42,38,35,32,30,29,28,27,27,27,27,27,27,28,26,27,28,30,31,33,34,35,33,31,29,29,30,34,38,41,41,39,35,31,28,27,27,27,28,28,27,26,25,25,25,25,26,28,32,35,38,38,38,37,36,35,35,38,46,58,70,77,88,89,86,78,65,52,42,37,37,41,49,57,64,65,62,59,53,47,42,41,46,51,53,52,53,52,46,41,41,44,42,37,33,33,33,35,40,48,56,61,71,81,93,103,117,133,141,141,136,118,95,73,55,43,45,53,63,70,78,80,76,69,65,63,55,54,54,53,52,51,50,50,49,49,50,50,49,48,46,45,41,39,39,40,41,47,62,77,102,110,118,114,98,76,59,50,46,53,61,66,68,65,51,38,34,42,54,67,83,95,94,86,71,61,50,45,45,44,40,36,34,32,30,32,37,43,48,50,56,53,47,38,30,28,32,36,46,52,58,58,52,45,39,37,40,41,43,43,36,29,29,35,52,68,88,102,107,102,87,72,60,56,55,58,63,62,55,48,37,32,26,25,27,29,29,28,26,28,31,36,41,47,51,53,51,48,45,41,37,34,30,28,30,31,34,40,44,44,40,36,30,27,23,19,18,19,22,24,24,25,27,26,23,21,20,20,20,21,21,20,20,21,24,27,31,34,38,38,35,30,27,25,24,24,24,24,24,24,24,24,21,25,30,34,36,38,41,43,44,45,45,47,49,51,53,54,53,51,46,40,34,29,25,23,24,25,27,28,29,28,28,27,28,29,30,30,29,26,23,21,23,24,25,26,25,22,20,18,18,18,18,18,20,22,25,26,28,27,26,23,20,18,20,21,24,27,32,35,36,37,39,40,43,45,46,46,44,40,36,33,27,25,22,21,22,22,19,16,14,13,12,13,15,17,17,16,20,21,21,23,24,25,26,27,24,23,21,19,17,15,14,13,12,12,13,14,15,15,16,16,18,18,18,17,17,16,15,15,17,17,17,18,18,19,19,19,19,19,19,18,18,17,17,17,14,14,13,13,13,12,12,12,11,10,9,7,7,6,6,7,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,0,3,4,3,0,2,8,14,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 6,6,6,6,6,6,6,6,6,6,6,7,7,8,8,8,7,7,8,9,9,10,11,11,13,13,13,14,14,15,15,15,16,16,16,16,16,16,16,16,16,15,14,13,13,13,14,14,16,16,16,17,17,17,18,18,20,21,22,23,24,25,25,25,29,29,31,34,37,41,44,45,50,48,44,40,36,33,31,30,29,28,27,27,27,27,28,29,27,27,29,31,33,35,37,38,37,35,32,31,32,35,39,41,42,39,35,31,27,25,24,23,27,26,25,24,23,23,23,24,21,24,29,33,36,37,37,36,39,38,39,42,50,61,71,78,82,83,80,72,58,44,34,29,33,38,47,59,68,71,70,67,62,55,48,46,49,52,52,50,47,44,37,31,31,35,35,31,30,31,32,35,39,45,50,53,55,66,78,88,102,119,127,127,125,109,90,74,61,52,56,66,75,81,88,88,81,71,63,59,50,49,46,44,44,45,47,48,49,50,53,54,54,53,51,49,43,41,41,42,42,47,61,76,98,107,114,111,96,76,59,51,46,52,58,61,63,61,49,37,33,43,57,72,89,102,100,90,73,62,49,42,41,39,34,29,32,30,30,33,39,45,49,50,53,50,43,34,26,26,31,37,48,55,63,65,58,48,39,35,36,37,41,41,34,27,27,33,46,62,82,97,104,101,87,74,62,58,55,57,63,63,57,51,42,36,29,26,28,30,30,29,27,29,33,39,44,50,54,57,54,51,47,42,38,34,29,26,29,30,32,37,42,44,41,37,31,29,25,22,20,20,22,23,22,23,25,24,22,21,21,22,20,21,21,21,20,22,25,28,30,33,35,34,31,26,23,22,24,24,24,24,24,24,24,24,21,25,30,33,35,35,36,37,35,34,34,36,40,46,52,55,58,56,51,45,38,32,27,25,26,27,30,32,32,31,29,28,26,27,28,28,27,25,23,21,24,25,26,26,25,22,19,17,18,18,17,17,19,21,23,25,29,29,28,25,22,22,23,25,24,28,33,36,38,39,41,43,48,49,49,49,47,42,38,35,31,29,26,26,27,26,22,18,16,14,13,14,17,18,19,18,21,21,22,23,25,26,27,28,24,23,21,19,17,15,13,13,12,12,13,14,15,15,15,15,17,17,16,16,16,15,15,15,17,18,18,19,20,20,21,21,21,20,20,20,19,18,18,18,14,14,14,13,13,12,12,12,11,10,9,8,7,7,7,7,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,1,3,4,2,0,3,11,18,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 6,6,6,7,7,8,8,8,6,7,8,9,9,9,8,8,9,9,9,9,9,9,9,9,12,12,12,13,13,14,14,14,15,16,17,18,19,20,19,19,19,18,16,14,13,13,14,14,15,14,14,15,16,17,19,19,19,21,23,23,23,23,25,27,24,27,31,35,37,41,45,48,47,48,47,44,39,36,35,36,33,32,31,31,34,35,35,35,35,34,33,35,39,42,43,43,43,41,38,36,35,36,39,40,41,39,35,28,23,22,24,26,30,29,28,29,29,28,25,22,23,24,26,29,32,35,37,38,38,43,48,51,57,66,70,69,75,72,66,58,48,39,31,27,30,35,46,58,69,74,75,73,64,61,56,52,48,48,48,49,38,39,38,34,34,37,38,35,33,32,34,38,43,46,46,45,47,51,59,72,88,102,112,117,111,102,87,73,65,64,68,72,87,88,87,82,74,63,53,46,42,42,42,42,43,44,45,46,48,50,52,55,57,58,58,58,51,50,48,46,47,53,62,68,83,91,99,97,85,68,56,49,44,49,56,61,61,55,47,42,39,46,61,79,95,100,96,89,74,67,56,46,39,35,33,31,29,33,39,45,50,53,53,53,54,46,39,34,29,28,34,42,54,63,70,69,63,54,43,33,32,34,36,37,37,34,31,29,40,55,75,93,105,106,94,80,60,56,52,54,58,60,56,52,44,40,36,33,33,32,31,29,30,31,34,41,49,57,62,63,62,55,49,47,42,35,31,32,31,36,41,42,43,43,37,30,30,28,27,28,29,28,26,24,28,26,25,25,26,26,25,23,25,23,23,24,27,30,30,30,34,32,29,26,24,23,23,23,25,26,28,29,29,27,25,24,23,24,26,28,30,31,31,31,28,29,30,31,35,42,51,57,59,61,60,54,44,35,30,29,30,33,36,38,38,35,32,29,28,27,26,25,25,25,25,26,26,26,25,25,23,22,20,19,20,22,23,23,23,23,25,26,26,26,27,28,28,28,27,27,28,29,32,34,37,38,39,40,45,46,47,48,46,42,38,36,37,36,35,35,34,30,25,21,17,16,15,14,14,16,17,18,19,21,24,27,29,30,29,28,24,23,21,18,16,15,14,13,12,12,13,14,15,16,16,17,14,13,13,13,13,14,15,16,18,18,18,19,19,19,20,20,21,21,21,21,20,19,18,17,17,17,16,15,15,14,13,13,11,11,10,9,9,8,7,7,7,7,7,6,6,5,5,5,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 6,6,7,7,7,8,8,8,6,7,8,9,9,9,9,8,9,9,9,9,9,9,9,9,12,12,12,13,13,14,14,14,15,16,17,18,19,19,19,19,18,17,16,14,13,13,13,14,14,14,14,14,15,16,18,19,19,21,22,23,23,23,25,27,25,28,32,35,37,40,44,47,48,48,48,45,42,39,39,39,37,36,35,36,38,39,39,38,36,36,37,41,46,51,53,54,51,48,44,40,38,38,40,42,41,39,35,29,24,23,24,26,31,30,31,32,33,32,29,26,26,26,27,29,32,36,40,42,46,51,54,55,58,65,67,65,63,60,55,48,41,34,29,26,30,35,43,55,65,71,72,71,65,62,56,51,48,46,46,46,39,42,43,41,42,45,44,40,37,35,36,39,44,47,47,46,41,43,48,59,72,86,96,101,96,89,79,70,66,69,74,79,85,83,80,74,66,57,49,44,42,43,44,45,46,47,48,48,50,52,54,56,59,60,61,62,55,54,52,49,49,52,58,63,71,79,86,85,75,61,51,46,43,47,54,59,60,55,49,44,43,48,60,75,89,93,89,84,72,66,57,49,43,39,36,34,33,37,43,49,54,56,56,56,53,46,39,34,29,27,33,41,55,64,72,71,65,57,45,35,30,32,35,37,37,36,33,32,41,55,74,91,102,104,92,79,65,59,54,54,57,58,55,51,43,41,38,36,35,34,32,30,28,29,33,40,50,59,65,67,64,57,51,48,43,38,36,38,39,45,49,49,48,46,39,30,29,28,29,31,33,33,31,29,31,30,28,28,29,28,26,24,24,24,24,26,30,33,34,33,33,31,28,24,23,23,24,25,31,33,35,36,35,32,29,27,24,24,25,27,28,30,32,32,28,29,30,31,34,40,48,54,63,65,65,60,50,41,36,34,33,35,38,40,40,37,34,31,28,28,26,25,25,24,25,25,25,24,24,24,23,21,20,19,21,22,24,23,22,22,23,25,26,26,28,29,29,29,29,28,28,29,30,32,33,35,36,37,41,42,44,44,43,41,38,36,38,37,36,36,34,31,26,22,17,16,15,15,15,16,18,19,19,21,24,27,28,28,28,27,24,23,21,18,16,14,13,13,11,11,12,13,14,15,15,16,14,14,13,13,14,15,16,16,18,19,19,19,20,20,20,20,22,22,22,22,21,20,18,18,17,17,16,15,14,14,13,13,11,11,10,9,9,8,7,7,7,7,7,6,6,5,5,5,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 6,7,7,7,8,8,8,8,7,8,9,9,10,10,9,9,10,10,10,10,10,10,10,10,12,12,12,12,13,13,13,13,15,15,17,18,19,19,19,19,18,17,15,14,13,13,14,14,13,13,13,13,14,15,16,17,18,20,22,23,22,23,25,27,26,29,32,35,37,39,43,46,48,49,49,47,45,43,44,45,44,43,42,43,45,46,44,42,40,40,41,46,53,58,61,62,60,56,49,42,38,38,39,40,40,39,36,31,27,24,25,26,32,33,34,37,40,39,35,32,30,29,29,29,33,38,44,47,55,59,60,58,59,61,60,56,49,47,44,40,35,32,30,29,32,35,41,50,58,64,66,65,62,60,55,50,46,44,43,43,43,48,52,54,57,59,55,48,42,39,37,40,45,50,50,49,40,38,39,44,53,65,74,79,78,74,68,64,65,69,75,79,77,73,67,59,52,47,44,43,40,42,43,45,46,46,45,45,46,47,49,51,54,58,61,62,60,60,58,54,51,51,53,56,59,66,72,72,64,54,46,43,41,45,52,57,59,56,51,48,48,51,58,68,78,81,78,74,67,63,57,53,49,45,41,39,38,42,48,54,58,59,58,57,51,45,38,34,29,27,32,39,53,63,72,72,67,58,46,36,27,29,34,38,40,40,38,37,43,56,73,89,100,102,91,79,68,61,53,51,52,53,50,47,42,41,39,39,39,37,33,30,25,26,31,40,51,62,69,73,69,61,53,49,45,42,44,49,53,59,63,62,57,51,41,32,28,29,31,35,39,40,38,36,36,35,33,32,32,31,28,25,24,24,26,30,35,39,39,39,34,31,26,23,22,24,28,30,38,40,43,44,42,38,33,29,26,25,24,25,26,29,32,34,30,30,30,31,33,38,45,50,62,66,68,64,55,46,40,38,36,38,41,43,42,39,36,33,29,28,27,25,24,24,24,24,24,23,23,23,22,21,21,20,22,23,24,23,21,20,21,22,25,26,28,30,31,31,31,30,28,28,27,27,28,29,31,32,35,36,38,39,39,38,37,36,40,39,38,37,36,32,27,23,18,17,16,15,16,17,19,20,21,22,25,27,28,28,26,25,24,23,20,17,15,13,12,11,10,11,11,12,12,13,14,14,15,15,14,14,14,15,16,17,19,19,19,20,20,21,21,21,22,22,23,22,21,20,19,18,17,16,16,15,14,13,13,13,11,11,10,9,9,8,7,7,7,7,7,6,6,5,5,5,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 7,7,7,8,8,8,9,9,8,8,9,10,11,11,10,10,11,11,11,11,11,11,11,11,12,12,12,12,12,12,12,13,14,15,16,18,18,19,19,18,17,17,16,15,15,14,14,14,13,13,13,13,13,14,15,16,18,20,22,22,22,23,25,27,27,29,32,34,36,38,41,43,46,48,49,49,48,48,49,51,50,49,50,51,52,52,49,46,43,42,44,48,55,61,64,66,67,61,52,43,37,34,34,35,38,38,37,35,30,28,27,28,34,35,38,42,45,45,42,39,35,33,31,30,34,40,48,52,59,63,63,59,56,54,50,45,42,40,39,37,36,35,35,36,37,38,40,45,51,54,55,55,55,53,50,46,44,43,43,43,49,56,64,70,75,76,68,58,44,40,37,41,49,56,58,58,49,44,38,36,40,48,55,59,62,60,57,56,57,61,65,68,64,59,52,45,41,40,42,44,46,47,49,49,48,46,43,41,42,42,44,47,52,57,61,64,62,62,61,57,53,50,50,50,54,58,63,63,57,50,44,41,40,44,50,55,58,57,55,53,52,53,56,61,65,67,65,63,61,59,56,54,53,50,46,42,41,44,49,54,57,58,56,55,49,43,37,34,29,26,30,37,48,58,67,67,62,55,43,34,26,29,34,40,44,45,45,44,48,59,74,88,98,101,92,80,70,61,51,46,46,47,45,41,40,40,40,41,42,39,34,31,22,24,29,39,52,64,73,77,74,65,56,50,46,46,52,61,69,77,81,78,70,59,46,34,29,31,34,39,44,46,44,43,42,40,38,37,36,33,29,26,23,25,28,34,40,44,44,43,35,32,27,24,25,30,35,39,46,49,51,52,49,43,36,31,28,26,24,24,25,29,33,36,34,34,33,32,33,36,42,46,56,61,64,62,54,45,39,37,37,39,42,44,43,40,36,34,29,28,27,26,25,25,25,25,24,24,23,22,22,22,22,22,23,24,24,23,20,19,19,20,23,25,28,30,32,32,31,30,27,25,24,22,23,24,27,28,31,31,33,34,35,36,36,36,42,40,39,38,37,33,27,23,18,18,17,16,17,19,21,22,24,25,27,29,29,28,26,24,23,21,19,16,14,12,11,10,10,10,10,11,11,12,12,12,15,15,14,14,15,16,17,17,19,19,20,20,21,21,21,21,23,23,23,23,22,21,19,18,16,16,15,15,14,13,12,12,11,11,10,9,9,8,7,7,7,7,7,6,6,5,5,5,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 7,7,8,8,8,9,9,9,9,9,10,11,11,11,11,11,11,11,11,11,11,11,11,11,12,12,12,12,12,12,12,11,14,15,16,17,18,18,18,18,17,17,17,17,17,16,16,15,14,14,13,13,13,14,15,15,17,19,21,22,22,22,24,26,27,29,32,33,34,35,38,40,44,46,48,50,50,51,54,56,56,56,57,59,60,58,54,50,43,42,43,47,55,63,69,72,71,65,56,46,38,34,32,32,35,37,39,38,35,33,31,31,35,37,40,44,48,49,47,44,40,37,33,32,35,41,50,55,58,62,62,58,53,50,44,37,39,38,38,38,39,40,40,41,42,41,41,42,44,45,44,42,44,43,42,42,42,43,44,45,54,63,74,83,90,90,79,66,45,39,36,41,53,64,69,69,62,54,42,34,33,37,42,45,47,46,46,46,47,50,53,55,50,46,41,37,37,40,45,49,58,58,59,58,55,52,48,46,44,45,47,50,55,61,65,68,63,63,63,59,54,50,48,48,51,54,56,56,52,46,40,37,39,42,47,53,56,58,57,57,55,54,53,53,54,54,53,52,53,52,52,53,53,51,47,44,40,42,46,49,51,52,51,50,46,41,37,34,29,26,28,34,39,49,57,58,54,47,38,29,27,31,37,43,47,50,50,50,53,63,75,86,96,99,92,82,70,61,50,44,44,44,42,39,38,38,40,41,42,40,35,31,22,23,28,38,51,64,73,77,77,68,58,51,46,47,57,68,81,91,97,94,83,69,53,41,34,35,38,43,48,50,49,48,48,46,44,42,39,35,30,26,24,26,31,37,44,47,46,45,36,33,30,28,31,38,46,51,57,59,61,60,56,48,40,35,30,28,25,24,26,30,35,38,38,38,37,35,34,36,40,43,49,54,59,58,51,43,38,36,37,39,42,43,42,39,35,32,29,29,28,27,26,27,27,27,28,27,25,24,23,23,24,24,24,25,25,23,21,19,19,20,22,25,28,31,32,32,31,30,25,24,22,21,21,23,26,27,30,30,31,32,33,35,36,37,43,41,40,39,37,33,27,23,19,18,18,18,18,20,22,24,28,29,30,31,30,28,25,23,20,19,17,15,13,11,10,10,10,10,10,11,11,11,11,11,15,14,14,14,14,15,16,17,19,19,19,20,20,21,21,21,22,22,22,22,21,20,19,18,16,16,15,14,13,13,12,12,11,11,10,9,9,8,7,7,7,7,7,6,6,5,5,5,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 8,8,8,8,9,9,9,10,9,10,11,12,12,12,12,11,12,12,12,12,12,12,12,12,12,12,12,12,11,11,11,11,14,14,16,17,18,18,18,18,18,18,19,19,19,19,18,17,15,15,14,14,14,14,15,16,17,19,21,22,21,22,24,26,26,28,30,31,31,32,34,36,40,42,46,49,51,53,57,60,62,63,64,66,67,64,59,54,44,42,41,44,53,64,73,78,73,68,60,50,41,35,32,30,33,37,41,42,41,38,37,36,37,37,39,43,47,49,49,47,44,41,36,34,36,42,50,55,57,62,64,60,56,53,46,39,40,41,42,43,43,43,42,42,44,43,41,41,40,39,36,33,33,34,35,37,39,42,44,46,56,66,79,91,99,98,85,70,46,39,35,42,57,71,78,80,72,61,47,35,30,31,34,37,36,36,36,38,40,44,47,48,42,41,39,40,42,47,52,55,62,62,62,62,61,59,57,55,53,54,55,58,61,64,67,68,66,66,65,61,56,51,48,48,47,49,51,52,49,44,38,34,37,40,44,48,52,55,57,58,55,53,51,48,46,44,44,43,45,45,46,48,49,48,45,42,38,38,40,41,42,43,43,43,44,39,36,34,29,25,27,32,33,42,49,48,45,40,33,26,28,32,38,45,49,52,52,52,54,62,72,81,90,95,89,80,69,60,49,44,44,44,41,38,36,36,37,39,40,38,34,30,24,24,28,36,49,61,70,75,75,66,56,48,43,45,56,69,85,97,108,106,96,82,66,53,44,44,45,47,51,53,53,52,54,53,50,48,44,39,32,27,24,27,32,39,45,47,45,43,35,33,32,33,38,46,55,61,68,69,69,66,61,52,45,40,31,29,27,26,28,32,36,39,42,42,40,37,35,34,37,39,44,49,54,53,47,41,37,37,37,39,42,43,42,38,34,31,29,29,28,28,29,30,30,31,33,32,29,27,26,25,26,26,24,26,26,24,22,20,21,22,24,26,30,33,34,33,31,29,24,24,24,24,26,28,30,32,33,33,32,32,32,34,36,38,43,42,40,39,36,32,27,22,20,19,18,19,20,22,24,25,30,30,31,31,29,26,23,21,17,16,15,13,12,11,11,11,11,11,11,11,11,11,11,11,14,13,13,13,13,14,15,16,18,18,18,19,19,19,20,20,21,21,21,21,20,19,18,17,15,15,15,14,13,12,12,11,11,11,10,9,9,8,7,7,7,7,7,6,6,5,5,5,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 8,8,8,9,9,9,10,10,10,11,11,12,13,13,12,12,13,13,13,13,13,13,13,13,12,12,12,11,11,10,10,10,13,14,15,17,17,18,18,17,19,19,21,21,22,21,20,19,16,16,15,15,15,15,16,16,17,19,21,21,21,22,23,25,25,27,29,29,29,29,31,33,36,39,43,47,50,54,58,62,68,69,71,74,74,70,64,59,48,44,39,39,46,56,66,72,71,67,60,51,42,35,30,27,31,36,42,46,46,43,42,41,38,37,38,40,44,47,48,48,47,43,38,35,37,42,48,53,59,65,68,67,65,62,56,49,45,47,49,50,49,47,45,43,43,42,40,40,39,36,32,29,26,28,30,33,36,39,42,44,56,66,79,92,102,101,86,69,48,40,36,42,59,75,84,86,77,66,51,38,33,32,35,37,34,34,34,35,37,40,43,45,41,42,45,49,53,56,59,61,64,65,67,69,72,74,75,76,74,74,74,74,74,73,73,72,73,72,70,65,58,52,49,48,45,46,49,51,50,46,39,35,34,36,39,43,47,51,54,55,54,52,49,45,41,38,38,38,38,38,39,42,44,44,42,39,36,35,34,33,34,35,37,38,42,38,35,34,29,24,25,30,31,38,44,42,39,37,32,26,29,33,38,44,49,51,51,51,51,58,66,73,82,87,82,74,63,55,45,41,41,41,38,34,34,34,34,36,37,36,33,30,26,26,29,35,46,58,66,70,70,62,52,43,37,39,52,65,81,97,112,114,106,94,80,69,56,54,52,52,54,56,56,56,61,60,57,54,50,43,36,30,25,28,34,40,45,46,43,39,32,32,32,35,43,52,62,68,72,72,70,66,59,51,44,39,32,31,29,29,31,34,38,40,43,43,41,37,33,32,33,35,39,43,47,47,42,37,35,35,38,40,43,44,42,39,35,32,29,29,29,30,31,33,34,35,38,36,33,30,28,28,28,29,25,26,27,25,23,22,23,24,28,30,34,36,37,35,33,31,26,26,28,31,33,36,38,39,39,37,35,33,33,35,37,38,43,41,39,38,36,31,26,21,20,20,19,19,21,23,25,27,29,30,30,29,27,23,20,17,14,14,13,12,11,11,12,12,12,12,12,12,12,11,11,11,12,12,12,12,12,13,14,15,17,17,17,17,18,18,19,19,20,20,20,20,19,18,17,16,15,15,14,14,13,12,11,11,11,11,10,9,9,8,7,7,7,7,7,6,6,5,5,5,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 8,8,8,9,9,10,10,10,10,11,12,13,13,13,13,12,13,13,13,13,13,13,13,13,12,12,12,11,11,10,10,10,13,14,15,16,17,17,17,17,19,20,22,23,23,22,21,20,17,17,16,15,15,16,16,17,17,19,21,21,21,21,23,25,25,26,28,28,27,27,29,31,33,37,42,46,50,54,59,62,72,73,76,78,78,74,67,62,54,47,38,34,37,46,55,60,66,63,57,49,40,33,26,23,30,36,43,48,48,47,45,44,39,37,36,38,42,46,48,48,48,44,39,36,37,41,47,51,61,68,73,73,72,71,65,58,51,53,56,57,55,52,47,44,41,40,39,40,39,36,32,28,24,25,27,31,34,37,40,41,55,64,78,91,101,100,84,67,50,42,36,43,60,77,86,88,80,69,54,42,37,37,39,41,39,38,37,36,37,38,40,42,43,46,51,57,61,63,63,63,71,73,76,81,87,93,98,101,98,98,97,95,92,89,85,83,79,78,74,67,59,52,49,48,44,46,50,53,53,50,43,39,32,33,35,39,43,47,51,53,52,51,48,44,39,36,35,35,34,34,35,37,40,41,39,37,35,33,30,29,29,31,34,36,41,38,35,34,29,24,25,29,31,38,42,40,37,36,32,27,29,32,38,43,47,49,49,49,47,53,60,67,76,81,77,69,56,48,39,36,37,37,33,30,33,32,32,33,35,35,32,30,28,28,29,35,45,55,63,67,66,58,48,39,33,34,47,61,77,94,112,118,113,102,89,79,64,61,57,56,57,58,59,58,66,64,61,58,54,47,38,33,26,29,34,40,45,44,40,37,30,30,32,37,45,55,65,71,72,70,67,62,55,47,40,36,32,32,31,31,33,36,39,41,43,43,41,36,32,30,30,32,35,38,42,41,36,32,32,33,39,41,44,45,43,40,35,32,29,29,29,31,32,34,36,38,42,40,36,32,30,29,29,30,25,26,27,26,24,23,24,25,31,33,37,39,39,37,34,32,27,29,32,36,39,42,44,45,42,40,37,34,34,35,37,39,42,41,39,38,35,31,25,21,20,20,19,20,21,23,26,27,28,29,29,28,25,21,17,15,12,12,11,11,11,12,12,13,12,12,12,12,12,12,12,12,12,11,11,11,11,12,13,14,16,16,16,17,17,17,18,18,19,19,19,19,18,17,16,15,15,15,14,13,13,12,11,11,11,11,10,9,9,8,7,7,7,7,7,6,6,5,5,5,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 8,8,8,9,9,10,10,10,10,10,11,12,12,13,14,14,15,15,15,15,15,15,15,15,13,13,12,12,12,11,11,11,14,14,13,13,13,14,15,16,18,18,19,19,19,20,20,20,22,21,19,18,17,18,19,19,18,18,18,19,19,20,20,20,22,24,24,24,23,23,25,28,30,32,35,39,43,50,57,62,73,75,78,82,85,82,75,68,56,49,39,31,30,35,43,49,57,57,54,49,42,35,32,31,30,34,41,51,58,58,53,47,41,40,38,38,40,44,48,51,44,45,43,38,34,35,43,50,58,70,83,89,91,90,84,77,70,69,68,66,61,54,48,44,44,43,42,45,47,47,43,38,33,27,24,28,32,35,39,44,53,67,84,94,96,91,78,66,48,41,37,44,60,76,86,90,78,70,57,46,41,43,48,53,56,53,49,44,42,42,44,46,47,58,68,70,69,69,67,64,71,76,84,96,109,122,131,137,136,134,131,124,116,108,100,96,87,87,83,76,71,66,58,49,45,45,45,46,48,49,44,37,31,31,32,36,42,47,49,50,47,45,43,44,45,45,44,42,40,39,36,34,33,34,35,36,32,31,28,27,28,30,33,36,42,41,39,36,31,29,30,31,39,44,46,44,42,42,37,31,32,34,38,44,47,46,42,39,37,41,47,54,61,63,61,58,49,43,35,32,33,35,36,36,33,34,36,35,33,31,31,32,29,29,31,35,41,49,56,60,57,50,41,35,30,30,39,50,73,87,104,116,120,116,102,88,74,70,64,60,58,60,63,66,68,70,72,68,59,48,38,33,30,31,34,39,42,41,38,34,29,27,29,37,43,48,54,61,61,60,57,53,47,42,37,35,34,33,32,32,33,36,39,41,42,42,40,36,32,30,31,33,35,37,39,36,32,29,31,33,37,41,46,47,45,40,37,35,29,29,29,31,33,36,39,41,41,39,36,33,30,28,27,26,28,29,30,27,23,22,25,29,34,39,44,47,46,43,41,40,35,35,36,39,43,47,48,47,44,41,36,32,30,32,35,37,39,39,38,36,33,29,26,24,19,19,20,21,23,24,25,25,29,29,28,26,23,20,16,14,12,13,13,14,14,14,13,13,17,16,15,13,12,12,12,12,11,11,10,10,10,11,12,12,13,13,13,14,14,15,15,15,19,19,19,18,17,16,15,14,14,14,14,13,12,11,10,9,10,10,10,9,9,9,8,8,7,7,7,6,6,5,5,5,4,4,4,3,3,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 8,8,8,9,9,9,10,10,10,10,11,12,12,13,14,14,15,15,15,15,15,15,15,15,13,13,13,12,12,12,11,11,13,13,13,13,13,14,15,15,19,19,19,19,20,20,20,21,21,20,19,18,18,18,19,20,19,19,19,19,19,19,20,20,22,23,24,23,22,22,24,26,29,31,35,38,42,47,53,57,66,68,73,80,86,86,82,78,64,56,44,33,28,29,33,37,48,49,49,46,41,36,34,33,33,36,43,52,58,59,55,50,44,42,40,38,40,43,47,50,46,46,44,39,35,36,43,49,61,74,89,98,103,103,98,90,82,80,76,71,65,59,52,48,44,43,45,49,54,55,51,47,39,32,27,28,31,33,38,44,53,66,80,89,91,87,76,64,47,42,39,46,60,74,81,83,69,63,55,49,49,55,63,68,73,69,61,53,46,43,43,44,53,64,73,74,71,68,64,59,64,73,88,106,124,142,156,164,168,165,158,148,135,122,110,104,95,96,94,87,81,75,65,55,48,47,45,46,48,48,44,38,32,32,33,37,43,47,49,49,45,44,42,44,47,51,52,53,51,48,43,38,34,33,33,34,33,32,30,29,30,32,35,37,41,41,39,35,32,32,34,37,44,50,53,52,50,48,42,34,32,33,36,40,43,42,39,36,32,34,38,44,50,52,51,49,42,37,31,28,30,34,36,36,35,36,36,34,31,29,29,30,30,30,32,34,39,45,51,54,52,45,38,32,26,25,34,44,65,79,97,110,116,113,102,90,80,75,69,63,61,63,67,70,73,76,78,75,66,55,45,39,31,32,35,38,41,39,35,32,25,23,25,31,37,40,46,52,50,49,47,45,41,36,33,31,34,33,33,33,34,36,39,40,40,40,38,35,32,30,32,34,35,37,37,34,29,26,27,30,37,41,46,47,45,40,37,35,30,30,30,31,32,35,37,39,39,37,34,31,29,28,28,28,29,31,31,28,25,25,29,33,41,46,52,55,54,50,47,45,38,37,38,41,45,48,48,48,42,38,32,28,26,28,32,35,40,40,39,36,33,29,25,23,20,20,21,22,23,25,26,26,27,27,26,24,22,19,17,16,17,18,19,19,20,19,19,19,19,18,16,15,13,12,12,12,12,11,11,10,10,11,11,12,13,13,13,14,14,14,15,15,18,18,18,18,17,16,15,14,13,13,13,13,12,11,9,8,10,9,9,9,8,8,8,7,7,7,7,6,6,5,5,5,4,4,4,3,3,3,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 8,8,8,8,9,9,9,10,10,10,11,12,12,13,14,14,15,15,15,15,15,15,15,15,14,14,13,13,13,12,12,12,13,12,12,12,12,13,14,15,18,18,19,19,20,20,20,20,20,19,19,18,19,19,20,21,20,20,20,19,19,19,19,19,21,22,22,22,20,21,23,25,27,30,33,36,39,42,46,49,58,61,68,77,84,87,87,85,71,63,51,38,30,26,27,28,37,40,43,43,41,38,37,37,38,40,46,53,58,60,58,56,51,48,45,42,41,44,47,49,49,49,47,42,38,38,43,48,61,76,94,107,117,120,115,108,96,90,82,74,67,61,55,51,44,45,49,57,65,68,65,62,51,41,31,28,29,32,38,45,52,63,74,80,82,79,71,61,46,43,42,48,60,69,73,73,60,57,53,52,57,67,78,85,91,86,75,63,51,45,44,45,59,70,79,79,73,67,59,52,55,70,93,117,141,162,180,191,192,188,178,165,148,130,115,107,102,106,107,102,97,88,75,63,52,49,46,46,48,47,43,40,35,35,37,41,46,49,50,50,44,42,41,44,51,60,66,70,69,64,55,46,39,34,32,31,34,33,32,32,33,35,37,38,40,39,37,34,32,34,38,42,50,58,64,65,62,58,48,39,33,33,34,36,38,38,36,33,27,28,29,33,37,39,39,38,33,29,25,24,27,31,35,37,38,38,37,33,29,26,26,27,30,30,31,33,36,40,44,46,45,40,34,29,24,22,28,38,55,70,88,101,108,109,101,91,83,78,71,65,63,66,71,75,80,83,86,83,74,62,51,45,33,34,36,38,39,37,32,28,23,20,22,27,31,32,36,41,40,40,40,39,37,34,32,30,33,33,34,35,36,37,38,39,38,38,36,34,32,32,34,37,39,40,39,34,28,24,26,28,36,41,46,48,45,41,37,35,31,30,30,29,30,32,33,35,35,33,29,27,26,26,28,30,30,31,32,30,28,29,35,40,48,54,61,65,63,57,51,48,42,40,40,42,44,46,45,44,37,33,28,23,23,26,32,35,42,41,40,37,33,28,24,21,20,20,21,22,24,25,26,26,25,24,22,21,20,20,19,19,22,22,23,24,25,25,25,24,22,21,19,16,15,13,13,12,12,12,11,10,10,11,11,12,13,13,13,13,14,14,14,15,17,17,18,17,17,15,14,14,12,12,12,12,11,10,9,8,9,8,8,8,7,7,7,6,7,7,7,6,6,5,5,5,4,4,4,4,3,3,3,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 7,7,8,8,8,9,9,9,10,10,11,12,12,13,14,14,15,15,15,15,15,15,15,15,15,14,14,14,13,13,13,13,12,12,12,12,12,13,14,15,17,17,17,18,18,18,19,19,19,19,19,19,20,20,21,21,21,20,20,20,20,19,19,19,21,22,22,21,20,20,22,24,26,29,32,34,35,36,39,40,53,56,62,69,76,80,82,82,75,68,58,47,39,33,31,31,31,35,40,42,42,41,41,41,43,46,50,55,59,62,62,62,60,58,53,49,47,48,49,50,53,52,50,46,42,41,44,47,59,74,95,112,126,132,128,120,103,94,82,72,65,59,54,50,45,48,55,66,76,82,82,79,64,51,38,31,30,31,38,46,51,60,67,70,71,70,65,57,44,43,43,49,58,64,65,63,57,54,51,52,60,73,87,96,99,94,83,68,55,47,46,48,60,72,82,82,75,66,55,46,49,67,94,122,147,170,188,200,196,191,181,167,149,131,116,107,104,110,115,115,111,102,86,72,57,50,45,46,47,45,43,43,40,41,43,47,52,54,53,52,44,41,41,46,56,70,81,88,90,83,71,58,46,38,33,31,35,35,35,35,36,37,38,38,38,37,34,31,30,33,38,43,55,64,72,74,72,65,54,43,35,34,33,34,36,37,35,34,28,26,24,25,28,30,30,30,25,23,21,21,25,31,37,40,42,42,39,34,28,24,23,24,27,28,29,32,34,37,40,41,42,38,34,30,25,22,28,37,51,66,83,94,100,102,97,89,80,75,68,64,63,68,74,79,84,88,90,87,77,63,52,45,37,37,38,40,40,37,31,27,25,22,22,26,28,28,31,36,37,38,41,42,42,40,38,36,34,35,36,37,38,38,38,37,36,36,36,34,33,35,39,43,47,47,45,38,30,26,27,29,35,40,46,48,46,41,37,35,30,29,28,26,26,27,28,29,29,27,23,21,21,24,28,30,29,30,31,29,29,32,40,46,55,61,69,72,69,61,53,48,43,42,40,39,40,39,38,36,30,27,23,20,22,28,35,40,45,44,42,38,33,28,23,20,18,19,20,21,22,23,24,24,22,21,20,19,19,21,22,23,25,25,26,27,28,28,27,27,24,23,21,18,16,14,13,13,13,12,11,10,10,10,11,11,12,12,13,13,13,14,14,14,16,16,17,16,16,15,14,13,10,11,11,11,10,9,8,8,8,8,7,7,7,6,6,6,7,7,7,6,6,5,5,5,5,5,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 7,7,7,8,8,8,9,9,10,10,11,12,12,13,14,14,15,15,15,15,15,15,15,15,15,15,15,15,14,14,14,13,13,13,12,12,12,13,14,15,15,15,15,16,16,17,17,17,20,20,20,20,21,21,20,20,20,20,20,20,20,20,20,20,22,23,23,22,20,20,22,24,26,29,31,33,32,32,34,35,44,48,53,59,64,69,73,76,78,74,67,60,52,46,43,41,37,40,44,46,45,44,45,45,49,51,55,58,62,64,66,68,70,68,64,60,57,54,53,53,54,53,51,48,45,44,44,46,56,71,92,111,127,135,131,123,102,92,77,67,61,57,53,49,45,49,57,70,84,93,95,93,76,62,46,37,33,33,39,46,50,56,61,61,61,62,58,53,43,42,43,48,54,58,58,57,55,51,49,50,60,75,90,100,100,95,85,70,55,46,45,47,57,71,84,86,79,68,54,43,45,62,90,119,145,167,184,193,192,187,176,161,144,127,113,105,100,110,119,123,122,114,98,83,61,51,43,44,45,43,44,47,47,48,51,55,59,60,58,55,45,43,42,48,61,78,93,101,107,99,86,70,55,44,36,33,36,37,37,37,37,37,36,36,35,34,31,28,27,30,35,40,55,65,74,76,74,68,56,44,37,35,34,35,37,39,38,37,30,27,23,22,22,23,24,23,21,20,20,21,25,31,39,44,46,45,42,36,30,24,22,22,23,24,27,31,34,37,39,40,41,38,35,33,29,28,34,43,55,68,83,90,93,94,90,84,75,71,66,63,65,70,77,82,88,91,92,88,77,63,51,45,41,41,42,43,43,40,34,29,29,25,23,25,26,26,30,35,41,45,49,53,54,51,47,44,37,38,38,38,38,37,37,36,36,36,36,35,36,40,46,50,54,54,50,43,33,27,26,28,34,39,46,49,47,42,37,35,28,27,25,23,22,22,23,23,23,21,19,17,18,22,26,29,27,29,29,29,30,35,45,53,64,70,77,79,74,64,54,48,42,40,37,35,34,32,29,26,22,20,18,18,22,30,38,44,49,47,45,40,34,28,23,19,16,16,17,18,19,20,21,22,21,21,20,20,21,23,25,27,29,30,30,31,31,30,30,29,25,24,21,19,17,15,14,14,13,12,11,10,10,10,10,10,12,12,12,13,13,13,14,14,15,15,15,16,15,15,14,13,10,10,11,11,11,10,9,8,8,8,7,7,7,6,6,6,7,7,7,6,6,5,5,5,5,5,5,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 6,7,7,7,8,8,8,8,10,10,11,12,12,13,14,14,15,15,15,15,15,15,15,15,16,16,16,15,15,15,14,14,14,14,13,13,14,14,15,16,15,15,15,16,16,16,17,17,21,21,22,22,21,20,19,18,19,20,20,20,21,21,22,22,25,26,26,24,22,22,24,25,28,30,31,31,30,30,32,33,36,39,44,48,52,57,64,68,77,76,74,70,65,60,56,54,52,54,54,53,50,48,48,49,52,56,60,63,65,67,70,72,77,76,74,70,66,62,58,55,52,51,49,47,45,44,43,43,53,66,84,103,119,127,123,114,93,82,68,59,56,54,51,47,44,47,55,69,85,96,101,101,84,71,55,45,40,37,40,46,49,53,56,54,54,55,53,48,42,41,41,44,49,52,54,54,53,52,51,54,63,76,90,98,96,93,85,70,54,44,42,44,58,74,89,93,86,73,57,44,42,56,81,109,137,158,171,178,176,169,157,142,125,110,98,92,94,105,118,126,127,120,104,89,62,49,40,42,43,41,44,50,52,54,58,62,65,65,61,58,49,47,46,52,66,83,99,108,116,109,95,79,63,50,40,35,37,37,38,38,37,35,32,31,31,30,28,26,26,28,33,37,51,60,69,71,69,64,54,43,36,35,35,37,41,43,43,42,35,31,26,22,21,21,20,19,20,20,21,21,25,31,40,46,49,49,47,41,34,27,23,21,21,23,27,32,35,38,39,39,40,37,35,35,33,34,42,52,62,73,84,87,87,85,82,78,72,69,66,65,67,72,78,82,88,89,90,85,75,63,53,47,45,45,46,48,49,46,40,36,33,27,24,25,26,27,32,38,51,56,63,69,69,64,57,52,42,41,40,39,37,36,35,35,34,35,35,36,38,43,51,56,58,58,55,47,36,28,25,25,33,38,46,49,48,43,37,35,27,25,23,21,20,19,20,20,20,19,17,17,19,22,26,28,27,28,28,28,31,39,50,59,73,78,84,83,76,65,54,47,39,36,33,32,31,29,26,23,18,18,18,21,27,35,43,48,53,51,48,43,36,29,23,19,14,14,15,16,18,19,20,20,22,22,22,23,25,27,28,29,34,35,35,34,34,32,31,30,24,23,21,19,17,16,15,15,14,13,12,11,10,10,10,10,11,12,12,12,13,13,13,13,13,14,14,15,15,14,13,13,10,10,11,11,11,11,10,9,9,8,8,8,7,7,7,6,7,7,7,6,6,5,5,5,6,5,5,5,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 6,6,7,7,7,8,8,8,10,10,11,12,12,13,14,14,15,15,15,15,15,15,15,15,17,17,16,16,16,15,15,15,15,15,14,14,15,16,17,17,16,16,17,17,18,18,18,18,22,23,23,23,22,20,18,17,18,18,19,20,21,23,23,24,28,28,28,27,25,24,26,27,30,31,31,30,29,29,32,34,36,38,40,41,42,45,51,56,67,69,72,75,75,74,71,69,71,70,67,61,55,51,50,51,55,59,64,67,68,69,72,74,80,80,80,78,73,67,60,56,47,46,44,43,43,41,40,38,45,56,71,88,103,111,106,97,79,68,54,48,48,48,46,43,41,43,51,64,80,94,100,102,89,77,62,53,46,41,42,45,47,51,53,50,50,51,48,44,41,40,39,40,43,49,53,55,58,59,61,65,71,77,83,87,86,86,82,70,56,47,46,49,64,81,98,103,95,81,62,48,42,51,70,96,123,142,151,153,147,140,127,112,98,86,78,74,84,97,111,120,122,116,100,85,62,47,37,39,41,40,44,53,55,57,61,66,68,67,62,58,54,51,50,55,69,86,101,110,118,111,99,84,68,54,43,37,37,37,38,38,36,32,28,26,25,25,26,26,26,29,34,38,46,54,60,62,61,58,50,41,32,33,35,39,43,46,47,46,43,38,33,29,26,25,22,21,20,21,21,22,24,30,39,45,51,52,51,46,38,30,25,22,22,24,29,34,37,38,38,38,37,34,33,34,35,38,48,59,66,77,85,85,81,79,76,72,69,67,65,64,66,69,73,76,80,81,82,78,69,60,53,49,48,48,50,53,54,52,47,43,40,33,28,28,29,32,39,47,64,71,80,86,85,77,67,59,47,45,42,39,36,34,34,34,32,32,33,35,38,45,53,59,64,64,62,54,42,31,26,24,32,38,46,50,48,43,38,34,27,25,23,21,20,20,20,21,20,19,19,20,21,24,27,28,27,28,29,30,33,43,56,66,79,82,85,83,74,61,50,43,35,33,31,31,32,31,30,28,25,26,27,31,37,44,50,54,57,55,51,45,38,30,24,20,14,14,15,17,18,19,20,20,23,24,25,27,29,30,31,31,36,36,35,34,33,31,29,28,23,22,20,18,17,16,16,16,14,13,12,11,10,9,9,10,11,11,12,12,12,13,13,13,12,13,13,14,14,14,13,13,10,11,12,12,12,12,11,11,10,9,9,9,8,8,8,7,7,7,7,6,6,5,5,5,6,6,5,5,5,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 6,6,6,7,7,8,8,8,10,10,11,12,12,13,14,14,15,15,15,15,15,15,15,15,17,17,17,16,16,16,15,15,16,16,15,15,16,16,17,18,18,18,19,19,19,20,20,20,24,24,24,23,22,19,17,15,17,18,19,20,22,23,24,25,29,30,30,29,26,26,27,29,32,32,31,29,28,29,32,35,41,42,41,38,35,36,40,45,54,59,67,75,80,83,83,82,84,81,75,67,59,53,51,52,56,60,66,69,69,70,73,76,80,82,83,82,77,69,61,56,43,42,41,40,40,39,37,35,37,46,60,74,89,96,91,82,66,55,43,38,40,42,41,38,38,40,46,59,76,90,98,101,92,80,66,58,50,44,43,45,46,50,51,48,48,49,46,42,41,39,37,37,40,47,53,56,66,68,72,75,77,77,76,75,76,79,78,70,59,52,53,57,70,88,105,110,102,86,66,51,43,49,63,86,111,127,132,131,125,118,106,93,81,73,68,66,76,89,104,113,115,109,93,78,62,46,35,38,40,39,44,54,56,58,62,67,69,67,62,58,56,53,52,57,70,87,101,110,116,111,100,86,71,56,44,37,37,37,38,37,35,30,26,23,20,22,25,26,28,32,36,40,42,49,54,55,54,53,47,39,30,31,34,39,45,48,49,48,50,46,40,36,33,30,27,25,20,21,22,22,23,29,37,44,52,54,54,50,42,33,26,22,24,27,31,35,38,38,37,36,34,32,31,33,34,39,50,63,68,78,85,83,78,75,72,69,66,65,63,62,62,64,66,68,71,72,73,70,63,56,51,49,49,50,53,56,58,56,52,48,47,39,33,33,34,38,47,56,75,82,93,99,97,87,75,66,50,47,43,38,35,33,33,33,30,30,31,33,37,45,54,60,69,70,68,60,48,36,29,26,31,38,46,50,48,43,38,34,27,26,24,22,21,21,21,22,21,21,21,23,24,26,28,29,29,30,30,31,35,46,60,70,79,82,84,80,70,57,45,38,32,31,30,32,34,35,35,34,35,36,38,42,47,53,58,61,59,57,53,47,39,31,24,20,15,15,16,17,19,20,21,21,23,25,28,30,32,32,32,32,34,34,33,32,30,27,25,23,21,20,19,18,17,16,16,16,14,13,12,11,10,9,9,9,11,11,11,12,12,13,13,13,12,12,13,14,14,13,13,12,11,11,12,13,13,13,12,12,10,10,10,9,9,9,8,8,7,7,7,6,6,5,5,5,6,6,6,5,5,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 6,6,6,7,7,8,8,8,10,10,10,10,10,10,10,10,12,12,13,13,13,14,14,14,16,15,15,15,15,15,15,15,15,15,15,16,16,17,17,17,19,19,19,20,20,21,21,21,23,23,24,24,23,21,18,17,21,22,22,21,20,22,26,29,30,32,35,36,35,34,34,35,33,33,33,32,31,32,36,39,41,42,42,39,33,30,32,34,44,49,57,64,70,76,82,86,92,89,83,75,66,58,51,47,53,61,67,70,73,78,80,78,77,79,82,85,84,76,63,53,42,38,34,33,36,39,39,39,41,46,53,63,74,83,80,73,61,51,40,37,40,43,42,39,39,39,42,51,63,77,88,94,86,82,72,62,58,58,53,47,47,46,46,46,46,46,45,45,43,40,36,33,35,42,52,60,67,77,85,86,83,78,71,63,67,69,70,67,62,60,63,67,80,92,104,108,106,95,72,50,40,40,52,76,98,109,115,120,110,99,85,75,65,57,56,59,66,77,92,104,105,97,84,75,53,42,34,35,38,42,50,59,56,59,63,64,63,61,59,58,55,55,57,62,71,84,95,102,106,102,94,82,68,54,43,37,35,36,37,36,32,29,28,27,27,33,37,39,43,45,42,35,41,40,39,42,46,47,44,40,32,33,35,39,44,49,54,57,55,52,49,46,43,38,33,30,27,25,22,21,23,28,33,37,51,52,54,53,48,40,32,27,26,27,30,35,38,39,36,34,30,29,28,29,33,43,54,62,72,77,81,80,74,67,63,61,62,63,64,62,59,57,56,57,62,61,58,56,53,51,50,49,48,51,57,63,67,66,61,56,52,44,37,36,39,44,55,65,80,91,101,101,95,84,70,58,48,41,34,31,32,33,29,26,27,26,28,32,35,39,50,62,71,77,78,68,54,42,32,24,29,34,42,49,51,47,38,32,23,23,23,26,28,30,29,27,31,30,28,27,27,28,29,30,29,28,29,32,39,49,59,65,80,81,80,74,63,51,41,36,28,29,32,36,40,44,48,49,47,48,51,54,57,60,62,63,63,58,51,44,37,30,23,18,14,15,16,17,20,22,25,26,28,30,32,34,35,35,35,34,36,34,31,28,25,23,22,21,18,17,16,15,15,15,16,16,13,13,12,11,11,11,12,12,12,12,12,13,13,14,14,14,14,14,14,14,14,14,14,14,13,13,13,13,13,13,13,13,11,10,9,8,8,8,8,9,8,8,7,6,6,6,7,7,6,6,6,5,5,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 6,6,6,7,7,8,8,8,10,10,10,10,10,10,10,10,12,12,12,13,13,13,14,14,15,15,15,15,14,14,14,14,16,16,16,17,17,18,18,18,18,19,19,20,20,21,21,22,24,24,25,26,25,24,22,21,22,23,22,21,20,21,24,27,29,32,36,37,36,34,34,34,32,32,33,32,32,35,40,43,47,48,47,42,35,31,31,32,34,39,45,52,58,66,73,78,87,85,81,74,66,57,49,44,50,58,67,71,75,80,79,76,75,75,76,78,78,73,63,55,44,39,34,33,35,39,41,42,39,44,50,57,68,75,73,66,61,53,45,43,47,49,46,42,41,40,41,47,58,70,80,85,81,78,72,65,63,63,58,50,47,45,44,44,46,48,49,50,47,43,38,33,33,39,49,56,71,81,89,90,85,79,69,60,53,58,63,66,66,66,67,68,78,88,99,104,102,91,69,49,36,37,49,74,97,109,116,121,109,97,82,71,62,55,55,58,64,72,85,93,93,85,73,65,50,41,35,37,41,44,51,59,56,58,61,61,60,58,56,55,57,57,59,63,70,78,86,91,93,90,83,73,61,50,40,35,36,38,39,37,34,30,29,28,32,39,45,49,52,53,47,39,38,36,35,38,42,43,40,37,33,34,35,38,43,48,53,56,58,56,54,52,49,44,37,33,29,27,24,22,24,28,33,36,46,49,52,54,51,45,38,33,28,28,30,33,36,37,35,33,30,29,28,27,31,39,49,57,65,69,72,70,64,58,55,55,56,58,59,58,55,51,49,49,50,49,48,47,46,46,46,46,49,52,57,63,67,66,61,57,51,43,36,35,38,43,54,64,80,90,99,98,92,81,67,56,45,39,33,30,32,32,29,25,24,23,24,28,32,37,49,61,74,80,81,71,57,45,34,25,28,33,40,47,50,46,38,31,25,25,27,30,34,36,36,35,35,33,31,29,28,28,29,30,30,30,30,33,40,49,57,62,70,71,70,64,54,43,34,30,29,32,36,41,46,50,53,54,53,54,55,56,59,61,62,63,59,54,48,41,35,29,23,18,13,13,13,15,17,20,24,26,31,32,34,35,36,36,35,34,34,32,29,26,23,21,20,19,16,16,15,15,15,16,16,17,14,13,12,11,11,11,12,12,12,12,12,13,13,14,14,14,15,15,15,15,15,15,15,15,14,14,14,14,14,14,14,14,12,11,10,9,9,9,9,9,9,8,7,6,6,6,7,7,6,6,6,5,5,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 6,6,6,7,7,8,8,8,10,10,10,10,10,10,10,10,11,11,12,12,12,13,13,13,13,13,13,13,14,14,14,14,17,17,17,17,18,18,18,19,17,18,19,19,21,21,22,23,25,26,28,29,30,29,28,27,25,26,25,23,21,21,23,25,29,32,36,38,37,35,33,33,31,32,32,33,34,39,45,49,55,56,54,48,39,31,29,29,26,29,33,37,43,50,58,64,73,73,73,69,63,54,45,40,44,54,65,72,78,82,79,74,70,68,66,67,69,68,63,59,47,42,37,35,37,41,45,47,48,52,57,62,71,79,78,72,68,63,58,57,59,58,53,47,42,39,38,42,50,61,69,74,73,74,73,71,71,71,64,55,47,44,41,41,45,50,55,57,52,48,41,35,32,36,45,51,72,83,92,92,87,78,65,54,44,49,57,66,72,72,69,65,71,80,89,94,93,82,63,45,31,34,48,73,98,115,123,127,113,99,81,69,60,54,54,58,63,68,75,80,78,70,60,53,46,40,37,40,45,48,53,58,57,57,58,58,57,54,52,51,57,58,61,64,67,71,74,75,76,74,69,63,55,47,40,36,40,41,42,41,37,33,31,31,39,48,58,64,67,64,55,44,36,34,32,35,39,41,39,37,35,35,36,38,41,46,51,53,61,61,60,60,57,51,42,37,30,28,24,22,23,27,32,35,41,45,51,55,54,50,43,39,30,29,28,30,32,34,33,32,29,28,26,25,26,33,42,48,56,59,61,58,52,47,46,47,47,50,53,52,48,43,40,38,37,37,38,39,40,41,42,42,47,50,54,60,63,63,59,55,49,40,33,32,35,40,51,61,75,84,91,89,82,72,60,49,40,36,31,30,31,30,27,24,21,19,20,24,28,34,47,60,76,83,85,76,62,49,36,27,27,31,37,44,47,44,37,31,25,26,29,34,39,43,44,44,40,38,34,31,28,28,28,28,30,30,31,34,39,46,52,56,59,59,58,52,43,35,28,25,30,34,41,48,54,57,59,59,56,56,56,56,56,57,58,58,53,49,43,38,33,28,22,18,15,14,13,13,16,20,24,27,33,34,35,36,36,35,34,33,30,29,26,23,20,18,17,16,14,14,15,15,16,17,18,18,15,14,13,12,12,12,12,12,13,13,13,13,14,14,14,14,15,15,15,15,15,15,15,15,14,14,14,14,14,14,14,14,13,12,11,10,10,10,10,11,9,8,7,6,6,6,6,7,6,6,6,5,5,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 6,6,6,7,7,8,8,8,9,9,9,9,9,9,9,9,10,11,11,11,12,12,12,12,12,12,12,13,13,13,13,14,16,16,17,17,17,18,18,18,17,18,18,19,21,22,22,23,25,27,29,32,33,34,33,33,30,30,29,26,23,22,23,24,27,31,36,38,37,35,34,33,31,32,33,34,36,41,48,54,60,61,60,52,41,32,27,26,25,26,27,28,30,35,41,46,53,56,58,59,55,48,40,35,38,49,62,72,81,85,81,74,65,60,55,54,58,62,64,64,52,48,43,40,42,47,52,56,62,67,71,76,85,93,93,89,84,81,78,76,75,69,60,52,41,38,36,38,45,53,60,64,67,72,75,77,79,78,68,57,47,42,37,37,43,51,58,61,58,54,46,38,34,36,42,47,65,76,86,87,82,73,60,49,45,47,54,64,72,72,65,58,62,67,74,79,78,69,52,39,30,36,53,79,107,128,138,141,124,107,86,72,62,56,55,58,62,64,67,67,64,57,50,45,42,41,42,46,51,54,56,57,58,57,55,55,54,52,50,48,54,56,59,62,63,63,63,62,62,61,60,57,53,49,44,42,45,47,48,46,42,38,36,36,46,57,69,76,78,73,60,46,37,34,33,35,40,43,42,40,37,36,36,36,39,43,47,50,61,62,63,64,62,55,45,38,30,27,24,21,22,25,30,33,39,44,50,55,55,51,45,40,31,29,27,27,29,30,31,30,29,27,25,22,22,27,34,40,48,50,51,47,41,38,38,40,40,44,48,48,43,37,32,29,30,31,33,35,36,37,38,39,41,43,47,51,55,55,52,49,44,36,29,28,30,35,45,55,64,72,78,75,68,60,50,41,36,33,31,30,30,29,26,23,20,18,19,22,26,32,45,58,74,82,86,78,65,51,38,27,25,28,34,41,44,42,37,32,24,25,28,35,42,47,49,49,43,40,35,30,27,25,25,25,28,28,30,33,37,42,46,49,52,52,49,44,36,30,27,26,31,36,44,52,57,60,60,60,53,52,50,49,48,48,49,49,47,43,39,34,31,27,22,18,17,16,14,13,16,20,25,28,32,32,33,34,33,32,30,29,26,25,23,20,18,16,15,14,13,14,16,17,18,19,20,20,16,16,14,13,13,12,13,13,13,14,14,14,14,14,14,14,16,16,16,16,16,16,16,16,15,15,15,15,15,15,15,15,14,13,12,11,11,11,11,12,10,9,8,7,6,6,6,6,6,6,6,5,5,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 6,6,6,7,7,8,8,8,9,9,9,9,9,9,9,9,10,10,10,10,11,11,11,12,12,12,12,13,13,14,14,14,16,16,16,16,17,17,17,18,18,18,19,20,20,21,22,22,25,27,30,33,35,36,36,36,33,34,33,30,26,24,24,25,26,30,35,37,37,36,35,36,33,34,34,34,36,42,49,55,62,63,62,56,44,34,28,26,28,29,28,26,24,24,26,29,35,38,42,45,44,40,35,32,34,45,58,70,82,89,86,79,63,55,47,44,48,56,63,66,57,54,50,48,48,53,60,65,72,79,85,91,100,109,111,109,105,102,97,93,86,75,62,53,37,35,34,36,41,49,54,57,63,70,78,83,86,84,72,59,48,41,33,33,40,50,57,61,60,57,50,42,37,37,41,45,53,64,74,75,72,65,54,44,44,44,49,58,67,68,62,54,53,54,57,62,62,54,42,34,34,43,63,91,121,144,154,155,136,117,94,77,66,59,56,58,58,58,57,55,52,47,43,41,42,45,50,55,60,63,61,58,60,57,53,52,52,51,49,46,48,50,53,56,57,57,55,54,51,52,54,54,54,53,51,50,53,54,55,53,49,45,43,42,53,64,77,84,84,77,61,46,34,33,33,37,43,46,46,44,39,38,36,35,37,40,44,47,56,58,61,64,62,55,45,38,29,26,22,20,21,24,28,32,40,44,49,53,52,47,41,37,30,27,25,24,26,28,28,28,28,26,23,20,19,23,29,34,40,42,42,38,33,30,31,33,36,40,45,45,41,34,28,25,27,28,30,31,32,32,32,32,32,33,36,40,44,44,43,40,37,30,24,24,26,30,38,47,54,61,65,62,57,51,44,37,34,33,32,32,31,29,25,23,21,19,20,23,25,31,43,55,68,78,84,79,67,53,39,28,24,27,32,38,42,41,37,33,25,27,30,37,44,49,51,52,43,39,33,27,23,22,22,23,24,26,29,32,36,40,43,44,48,46,42,36,30,27,26,27,31,36,43,51,55,56,55,54,46,45,43,41,40,41,42,43,43,40,36,32,30,26,22,19,18,16,13,12,14,18,22,25,27,28,28,29,28,26,24,23,22,21,20,18,16,16,15,15,15,16,18,21,22,23,23,23,19,18,17,16,15,14,14,14,15,14,14,14,14,14,14,14,16,16,16,16,16,16,16,16,15,15,15,15,15,15,15,15,14,14,13,12,11,11,12,12,10,9,8,7,6,5,5,5,6,6,6,5,5,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 6,6,6,7,7,8,8,8,8,8,8,8,8,8,8,8,9,9,9,10,10,10,11,11,12,12,12,13,14,15,15,15,16,17,17,17,18,18,18,19,19,19,20,20,20,20,21,21,23,25,28,32,34,35,36,36,34,35,34,32,28,25,24,24,25,29,33,35,36,37,38,40,38,37,36,35,36,40,47,53,60,63,64,59,49,39,33,31,31,33,33,31,27,24,22,22,25,27,30,33,34,33,32,30,32,41,54,68,82,93,92,86,68,57,44,38,41,49,57,62,60,59,57,55,55,60,67,72,82,91,100,107,115,124,128,126,120,116,108,99,87,73,58,49,34,33,32,34,39,44,47,49,58,67,78,86,91,89,76,63,50,41,31,29,36,46,53,55,57,55,51,45,40,39,40,43,42,52,60,62,60,56,50,42,39,40,45,54,64,66,62,56,50,46,45,48,49,44,37,34,39,52,74,102,132,155,163,160,141,120,96,79,68,60,56,55,50,49,47,45,43,42,41,40,47,54,62,68,73,74,69,62,59,55,50,48,50,50,48,46,43,44,47,49,50,51,51,50,47,49,52,55,58,59,59,59,61,63,63,61,57,52,50,50,59,69,81,86,85,76,59,44,30,30,32,38,46,50,49,47,41,39,36,34,34,37,41,44,49,51,56,60,59,53,44,37,28,25,22,20,21,25,29,33,41,44,47,48,46,41,35,31,27,25,23,23,24,26,27,26,26,25,22,20,19,21,27,32,35,37,38,35,29,26,27,29,35,39,43,43,40,33,28,25,24,25,26,27,27,26,25,24,25,25,27,30,34,35,35,33,31,25,22,24,25,27,33,40,46,53,56,53,49,47,43,38,34,35,35,35,33,29,25,23,24,22,22,25,26,29,39,49,60,71,80,78,68,55,41,30,23,26,30,36,41,41,38,35,30,31,34,39,46,50,52,52,40,37,31,25,21,20,21,22,23,26,31,36,40,44,45,46,45,43,37,30,25,23,25,28,32,36,41,47,49,48,46,44,39,38,36,35,35,37,40,41,41,39,35,32,30,27,23,20,17,15,13,12,12,15,18,20,21,22,23,23,23,21,20,18,19,18,18,17,17,17,18,18,19,20,23,25,27,27,26,26,22,21,20,18,17,16,16,16,15,15,15,15,14,14,14,14,15,15,15,15,15,15,15,15,14,14,14,14,14,14,14,14,14,13,12,11,11,11,12,12,11,10,8,7,6,5,5,5,6,6,6,5,5,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 6,6,6,7,7,8,8,8,8,8,8,8,8,8,8,8,8,8,9,9,9,10,10,10,12,13,13,14,15,16,16,17,19,19,19,20,20,21,21,21,21,21,20,20,20,20,19,19,21,23,26,30,32,33,34,34,33,34,33,31,27,24,23,23,25,27,30,33,34,37,41,44,42,41,38,35,34,38,44,49,57,62,65,62,54,45,40,38,35,39,43,44,41,36,32,30,27,27,27,27,28,29,30,30,31,39,50,64,82,96,99,95,77,64,47,36,35,42,49,54,61,61,61,59,59,63,70,75,86,96,106,114,122,130,133,132,124,119,108,95,79,64,50,42,31,31,31,34,37,39,40,39,51,62,76,87,95,94,82,68,51,41,29,27,33,42,46,48,50,50,49,46,42,39,40,41,37,45,52,52,51,50,47,42,40,43,51,61,68,69,65,60,52,44,39,41,43,39,37,38,44,59,82,108,137,157,161,155,135,115,91,76,66,57,52,51,45,44,43,42,42,43,45,46,55,65,75,81,86,86,78,68,57,51,45,44,46,48,47,44,41,41,41,42,44,45,47,48,50,53,57,62,66,68,70,70,69,70,70,68,63,59,57,56,65,74,83,86,84,74,57,42,29,30,35,43,52,56,55,52,43,40,36,33,33,35,38,41,43,45,50,55,56,51,43,37,28,26,23,22,23,27,32,36,41,42,43,42,39,34,29,26,24,22,21,22,24,26,25,25,24,24,22,20,19,22,28,32,37,39,41,38,33,30,30,31,34,38,41,42,38,33,29,27,22,23,24,25,25,24,22,21,22,21,22,25,29,31,31,30,28,24,23,26,27,27,30,36,38,44,47,45,43,43,42,38,36,37,39,38,35,30,26,23,25,23,24,26,26,26,33,42,52,66,77,78,70,58,44,33,24,25,30,35,40,41,39,36,32,32,34,38,43,47,47,47,39,35,29,23,20,20,22,24,25,29,36,43,48,51,52,53,46,43,36,28,23,23,27,30,34,37,40,43,43,40,37,35,31,30,28,29,31,34,38,41,42,39,35,32,30,28,24,21,20,19,17,16,15,16,17,18,17,18,19,20,19,18,17,16,17,17,17,17,18,19,21,22,23,25,28,30,31,31,29,29,25,24,22,21,19,19,18,18,16,16,16,15,15,14,14,14,15,15,15,15,15,15,15,15,14,14,14,14,14,14,14,14,13,13,12,11,10,10,11,11,11,10,9,7,6,5,5,5,6,6,6,5,5,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 6,6,6,7,7,8,8,8,8,8,8,8,8,8,8,8,8,8,8,9,9,9,10,10,13,13,14,15,16,17,17,18,21,21,22,22,22,23,23,23,22,22,21,20,20,19,18,18,20,22,25,28,30,32,32,32,31,32,32,30,26,23,21,21,24,26,29,31,34,38,43,47,45,43,40,35,33,36,41,46,56,61,65,64,58,50,45,43,38,44,51,55,54,50,45,42,31,30,28,26,26,27,29,31,31,38,48,62,81,98,103,100,84,70,50,36,32,37,43,47,60,61,62,61,61,64,70,76,80,91,103,110,118,125,127,125,123,116,104,89,72,56,43,35,30,30,31,33,35,36,34,32,47,59,74,87,96,97,85,72,52,41,29,25,31,38,42,42,45,46,47,45,42,39,39,39,38,44,48,47,46,47,46,43,46,51,61,70,75,74,68,63,56,45,38,39,41,39,39,43,47,63,86,110,137,155,156,148,128,108,85,71,63,55,49,47,44,43,43,43,45,48,50,52,60,72,84,90,94,94,85,72,55,49,42,41,44,46,45,43,41,40,39,38,39,42,45,47,56,59,63,69,73,76,78,79,73,74,74,72,67,63,61,60,68,77,84,85,82,73,56,42,30,32,39,49,58,63,61,57,44,41,36,32,32,34,37,40,39,42,47,52,53,50,43,37,29,27,24,23,25,30,35,39,40,40,40,38,35,31,27,24,22,21,20,22,24,26,25,24,23,23,22,20,20,23,29,33,41,44,47,45,40,36,35,36,34,37,40,41,38,33,30,29,21,23,25,26,26,25,23,22,21,20,21,23,27,30,30,29,26,23,24,28,29,28,30,34,30,36,40,38,37,39,39,37,37,39,41,40,36,30,26,23,25,24,25,27,25,24,29,37,49,63,76,78,71,60,46,35,24,25,29,35,40,41,40,38,31,31,32,35,39,42,42,41,38,34,28,23,21,21,24,26,28,33,41,49,55,58,59,59,49,45,38,30,25,25,29,34,37,38,40,40,39,35,32,29,23,23,22,23,26,31,36,39,43,40,36,33,31,28,25,22,25,24,23,21,20,19,19,19,15,16,17,18,18,17,16,15,16,16,16,17,19,21,23,24,26,28,30,33,33,33,31,30,27,26,24,22,21,20,20,20,16,16,16,15,15,14,14,14,14,14,14,14,14,14,14,14,13,13,13,13,13,13,13,13,13,12,11,10,10,10,10,11,11,10,9,7,5,5,4,4,6,6,6,5,5,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 8,8,8,8,8,8,8,8,9,9,9,10,10,9,8,8,9,9,9,9,9,9,9,9,12,12,13,14,16,17,18,18,20,21,23,25,26,26,25,24,25,24,23,23,24,23,21,19,20,20,20,20,21,22,23,24,26,27,27,27,26,23,20,18,23,25,28,33,38,42,45,47,47,46,42,35,30,30,36,41,54,65,73,71,64,58,52,47,50,53,59,68,74,73,66,60,48,39,28,24,26,30,32,31,35,38,45,58,74,90,102,109,96,83,65,50,41,38,43,49,56,57,59,61,63,64,63,63,72,77,86,96,104,109,111,112,109,102,91,75,58,43,33,27,27,35,40,37,33,32,30,27,41,52,70,88,98,96,85,75,55,43,32,30,32,33,34,37,33,35,37,38,39,40,43,46,45,46,46,45,44,44,46,48,47,55,62,66,71,76,75,71,59,54,47,43,43,45,47,47,58,68,87,109,126,132,130,126,106,94,77,63,54,49,45,43,47,43,44,51,56,57,62,69,81,86,95,105,109,102,86,73,57,44,36,41,49,49,47,46,44,43,43,42,43,46,51,55,61,64,69,74,77,78,78,77,78,77,75,73,70,68,66,65,73,77,81,84,79,65,49,37,28,33,42,54,64,66,62,57,44,38,31,28,30,31,31,30,36,39,44,50,53,53,48,44,38,35,30,27,26,29,32,35,38,38,35,31,26,22,21,22,23,24,24,24,23,22,21,20,18,19,19,19,21,26,33,38,49,54,57,56,54,52,46,39,42,39,38,39,36,29,25,26,25,26,27,27,26,26,28,31,25,26,28,30,31,31,31,30,26,26,27,27,27,28,28,28,30,30,29,30,31,32,34,36,39,41,42,40,36,31,27,25,22,26,28,26,23,23,28,33,43,54,65,70,69,64,52,41,29,26,26,32,41,44,40,34,35,34,32,32,34,36,36,35,36,33,30,27,27,29,32,35,38,45,53,59,67,73,71,66,56,47,36,27,25,28,32,35,44,43,41,38,33,29,26,24,19,20,22,26,29,34,37,39,42,40,37,33,31,31,31,32,32,32,33,32,29,26,22,20,21,19,17,15,14,14,15,16,16,16,16,17,19,22,25,27,34,33,33,32,31,30,30,29,25,24,24,23,22,21,20,19,16,16,15,14,14,13,12,12,10,10,10,11,11,12,12,12,14,14,14,13,13,12,12,12,12,12,11,10,10,9,8,8,9,9,8,7,7,6,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 8,8,8,8,8,8,8,8,8,9,9,10,10,9,9,8,9,9,9,9,9,9,9,9,11,12,13,14,15,16,17,18,20,22,24,26,27,28,27,27,27,26,24,24,25,24,22,19,19,18,18,18,19,20,21,21,24,25,26,26,25,23,20,18,23,25,28,32,37,41,44,46,46,45,40,33,27,28,34,39,52,65,76,77,74,71,66,61,57,59,65,74,81,82,77,72,58,48,36,30,30,34,36,36,37,38,43,53,68,83,97,104,102,91,75,60,49,42,42,44,51,52,55,58,61,62,61,60,60,64,70,78,85,90,94,95,94,88,76,62,48,36,29,26,34,43,49,46,41,37,32,27,38,49,67,85,95,93,82,73,56,45,35,33,34,34,34,36,34,35,37,37,38,40,45,48,46,47,48,48,47,47,49,51,53,61,68,71,75,79,77,73,61,56,50,46,45,46,47,47,54,62,77,95,109,114,112,108,92,83,70,60,53,50,47,45,45,44,49,59,67,71,78,86,91,95,103,111,114,105,90,77,61,48,40,45,53,57,57,58,53,52,50,48,49,52,56,59,63,65,69,73,75,75,74,73,73,73,72,71,69,68,66,66,71,75,79,81,77,64,49,38,31,36,45,57,66,67,62,57,44,38,31,28,30,32,31,30,34,36,41,48,53,55,53,50,43,39,33,28,26,28,31,33,35,35,33,29,25,22,21,22,24,24,25,26,26,25,23,22,20,20,19,19,21,27,35,40,55,62,67,67,65,62,54,46,43,38,35,35,32,27,26,28,28,29,31,31,30,30,31,33,29,31,33,35,36,35,33,32,28,28,27,27,27,27,27,27,26,26,25,25,27,29,31,32,37,39,41,40,36,31,27,24,22,25,27,25,22,23,27,32,40,51,63,68,68,63,52,40,29,26,25,31,39,43,40,36,34,32,30,30,31,33,32,31,31,30,30,31,34,38,42,45,47,54,62,68,75,80,77,71,57,48,36,28,27,31,36,40,46,44,41,37,33,28,25,23,20,21,23,25,29,33,36,38,39,37,34,33,33,34,37,39,42,43,43,41,38,33,28,25,23,22,20,18,17,16,16,16,17,17,17,18,20,23,26,27,32,32,31,30,29,28,27,27,24,23,23,22,22,21,20,20,16,16,15,14,13,12,11,11,10,10,10,10,11,11,12,12,14,14,13,13,13,12,12,12,12,12,11,10,10,9,8,8,9,9,8,7,7,6,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 8,8,8,8,8,8,8,8,9,9,10,10,10,10,9,9,10,10,10,10,10,10,10,10,11,11,12,13,15,16,17,17,21,22,25,28,30,31,31,31,30,28,27,26,27,25,23,20,17,17,16,16,16,17,18,18,21,22,23,24,23,22,20,19,22,23,27,31,35,39,42,44,45,43,37,29,23,24,30,36,52,66,80,86,86,85,80,75,65,66,71,79,86,89,86,82,66,56,42,34,33,35,38,39,41,40,41,47,58,73,87,96,103,97,87,74,62,52,45,41,44,45,48,53,57,59,58,57,49,50,52,56,61,67,72,75,76,70,60,48,37,31,30,31,44,54,61,59,51,43,34,26,33,45,62,79,88,86,76,68,56,46,38,37,37,35,34,36,36,36,35,35,36,40,46,51,49,50,52,52,51,51,52,54,53,60,67,69,72,74,71,66,59,55,50,48,47,47,47,46,51,56,65,77,85,89,88,86,75,70,63,57,54,51,49,48,46,48,56,69,80,87,94,101,102,105,110,115,115,106,92,81,66,55,48,53,63,69,72,74,65,62,58,55,55,57,61,63,65,67,69,72,72,70,68,66,66,66,67,67,67,67,66,65,69,71,76,78,74,63,50,40,36,41,49,60,68,68,62,55,42,36,30,28,30,32,31,30,31,33,37,45,53,58,59,59,51,46,38,31,27,27,29,32,32,32,31,28,25,23,23,24,26,27,29,30,30,28,26,24,22,21,20,19,21,27,36,43,59,68,76,79,77,72,62,52,43,36,31,29,27,25,28,32,33,35,38,38,37,36,36,36,36,38,41,43,42,39,36,33,28,28,28,27,26,26,25,25,22,22,21,21,23,25,27,29,34,36,38,38,36,32,27,24,22,24,25,24,21,22,26,30,36,48,60,66,67,62,51,40,30,27,25,29,37,42,41,38,33,31,28,27,28,29,28,27,28,30,33,37,42,48,52,55,58,65,72,77,81,84,79,71,54,46,35,28,29,36,44,50,52,49,44,38,32,27,23,22,20,21,22,25,28,31,33,35,33,32,32,32,36,42,47,51,57,57,56,53,48,42,35,32,28,27,25,22,20,19,18,18,18,18,19,20,22,25,27,28,29,29,28,27,25,24,23,23,22,22,22,22,22,21,21,21,16,16,15,14,12,11,10,9,10,10,10,10,11,11,11,11,14,13,13,13,12,12,12,12,12,12,11,10,10,9,8,8,9,9,8,7,7,6,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 8,8,8,8,8,9,9,9,9,10,11,11,12,12,11,11,11,11,11,11,11,11,11,11,11,11,12,13,14,15,16,17,21,23,26,29,32,33,34,34,32,30,29,28,28,27,24,22,18,17,16,16,15,16,16,17,19,19,20,21,21,21,20,19,20,22,25,29,33,37,40,42,43,40,34,26,20,21,27,34,54,68,84,93,96,96,90,84,72,72,73,77,83,86,85,82,64,55,42,33,31,34,39,42,45,43,41,42,49,61,76,86,96,97,95,87,77,66,54,44,38,39,42,48,55,59,58,56,46,44,41,40,43,49,56,61,64,59,51,41,33,31,35,40,53,64,73,71,61,49,36,26,32,42,58,72,78,74,66,58,51,43,38,39,39,37,36,38,38,38,36,35,36,40,47,52,53,54,55,55,53,53,54,56,52,59,65,66,67,67,62,56,52,49,46,45,45,46,46,45,49,51,55,60,65,68,69,69,64,63,61,59,57,54,52,50,49,54,64,77,88,96,101,105,107,109,111,113,110,102,89,80,69,64,62,68,79,86,88,88,75,70,63,58,58,60,63,65,65,67,68,69,67,64,60,58,57,58,60,62,63,64,64,63,65,67,71,74,71,63,52,44,42,45,52,61,68,66,59,52,39,34,29,27,29,31,31,29,28,30,34,42,52,60,65,67,60,53,44,34,29,27,29,31,29,30,30,28,26,25,27,28,31,33,34,35,34,31,28,26,25,23,21,19,20,27,37,44,58,69,79,83,82,76,64,53,42,34,27,25,24,24,30,37,40,43,46,46,44,42,40,40,41,43,46,48,46,42,37,33,27,27,26,26,25,24,24,23,22,22,22,23,24,26,28,30,33,34,35,36,36,32,27,23,22,23,23,22,21,21,25,28,34,45,57,63,64,61,51,40,31,27,25,28,34,40,41,40,35,32,28,26,26,27,26,26,31,34,38,44,50,54,58,60,66,72,77,79,80,79,71,62,47,40,32,29,34,44,54,61,61,57,49,41,33,26,22,20,20,20,21,23,25,27,29,31,29,29,31,35,42,51,60,65,71,70,68,63,56,48,41,36,32,31,29,27,25,23,22,21,20,21,21,23,24,26,27,28,26,25,25,23,22,21,20,20,21,21,21,21,21,22,22,22,17,16,15,13,12,10,9,9,10,10,10,10,10,11,11,11,13,13,13,12,12,12,11,11,11,11,11,10,10,9,9,9,8,8,8,7,7,6,6,6,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 8,8,9,9,10,10,11,11,11,11,12,13,14,14,14,13,13,13,13,13,13,13,13,13,11,11,12,13,15,16,17,17,21,23,26,30,33,34,35,35,32,31,30,29,30,29,26,23,20,19,18,17,16,16,16,17,17,17,18,18,19,19,18,18,19,20,23,27,31,35,38,39,40,38,32,25,19,19,26,32,53,67,85,97,104,106,102,95,81,77,73,72,75,76,75,73,57,49,38,30,29,34,41,46,48,46,43,41,43,53,66,76,88,96,100,96,88,77,61,47,37,36,38,46,55,61,62,60,49,44,37,32,33,38,46,51,57,55,49,40,33,33,40,47,61,73,82,80,69,56,41,29,33,41,53,62,65,60,53,48,44,39,36,39,40,38,40,43,42,42,41,39,39,42,46,50,55,56,56,54,53,53,55,57,58,65,69,69,67,65,58,51,43,41,39,39,41,43,43,43,44,45,45,46,49,52,56,59,61,62,63,63,60,56,52,50,50,58,70,82,93,101,104,104,105,106,106,105,102,94,85,79,74,75,80,89,99,104,102,97,82,75,65,59,59,61,63,64,63,64,65,64,62,57,53,50,48,50,53,56,58,59,59,58,59,61,65,68,68,63,55,49,45,47,52,59,63,61,53,46,35,31,26,26,28,30,29,27,27,28,32,39,49,59,65,68,63,57,47,37,31,29,30,31,29,30,31,30,28,29,31,33,38,39,39,39,38,35,32,30,30,28,24,21,21,27,35,42,55,66,78,82,82,76,64,52,41,33,25,23,24,26,33,42,47,49,52,51,48,44,42,41,42,44,47,48,46,41,35,31,24,24,24,24,24,24,24,24,26,27,29,31,33,34,35,35,34,33,33,34,35,33,28,24,23,23,22,21,21,21,24,26,32,42,53,58,60,57,49,40,30,27,25,27,33,38,41,41,37,34,29,27,27,27,27,27,32,35,41,47,53,58,62,63,71,75,77,76,73,69,60,49,38,34,30,32,41,53,63,70,69,64,54,43,34,26,22,20,21,21,21,21,23,24,26,27,28,29,33,40,50,61,71,77,83,81,76,70,61,52,45,40,35,35,33,31,29,27,25,24,23,23,24,25,25,26,26,26,23,22,22,21,20,20,19,19,20,20,20,21,21,21,21,21,16,16,15,14,12,11,10,10,12,12,11,11,11,11,11,11,13,13,12,12,12,11,11,11,11,11,10,10,10,10,9,9,8,8,7,7,7,7,6,6,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 9,10,10,11,12,12,13,13,13,14,15,16,17,17,17,17,15,15,15,15,15,15,15,15,12,12,13,15,16,17,18,18,20,22,25,29,31,33,34,34,32,30,29,30,30,30,28,25,22,21,19,18,17,16,16,16,16,16,16,16,16,16,16,17,17,19,22,25,29,32,35,37,37,36,32,26,21,21,26,32,47,62,81,96,108,114,111,105,88,81,72,66,65,64,63,61,49,43,35,30,30,35,43,49,50,49,47,43,43,48,59,68,83,95,104,102,96,86,68,51,40,38,38,46,57,66,69,68,56,49,38,30,28,33,41,46,54,54,50,43,35,34,40,46,64,76,84,82,72,59,45,34,34,40,48,53,52,48,44,41,41,37,36,38,40,39,42,47,50,51,51,49,47,46,47,49,54,54,52,50,50,52,57,60,64,70,74,72,69,65,56,47,39,37,34,34,37,40,41,42,39,39,37,36,36,40,46,51,60,63,66,65,61,55,51,48,50,61,74,85,94,101,102,98,97,97,96,94,90,85,80,76,77,84,94,103,112,115,109,100,84,75,63,56,56,59,61,61,59,59,60,59,56,52,47,44,41,43,47,50,52,52,52,51,51,53,57,61,63,61,56,52,47,47,49,53,56,53,46,40,31,27,23,23,26,28,27,25,25,25,28,35,44,52,58,60,59,54,46,38,32,29,29,30,29,30,31,30,30,30,32,35,42,42,42,41,41,40,39,38,38,35,31,26,25,28,34,39,52,62,73,77,77,72,61,51,39,32,26,25,27,30,37,45,52,53,53,51,46,42,39,39,40,41,42,42,40,35,30,27,22,23,24,25,26,27,28,29,33,36,40,44,46,46,44,43,37,34,32,32,33,33,29,25,24,23,22,21,21,22,24,25,31,39,47,51,52,51,45,38,29,27,26,28,32,37,40,41,39,35,31,28,28,29,30,30,32,35,40,47,53,59,63,65,71,74,73,69,64,59,50,40,31,31,33,39,50,61,70,74,72,65,55,44,34,28,24,23,23,23,22,22,23,23,24,25,30,33,39,48,59,71,81,87,91,87,80,71,61,53,46,43,37,36,36,35,33,30,28,27,25,26,26,26,25,24,23,22,20,20,20,20,20,20,20,20,21,21,21,20,20,20,20,20,16,16,15,15,14,13,13,12,14,13,13,13,13,12,12,12,12,12,12,12,11,11,11,10,10,10,10,10,10,10,10,10,7,7,7,7,7,7,7,7,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 11,11,12,13,14,14,15,15,15,16,17,18,19,19,19,19,18,18,18,18,18,18,18,18,13,14,15,16,17,18,19,19,20,21,24,27,30,31,31,31,30,29,28,29,31,31,29,27,22,21,19,18,16,16,15,15,16,15,15,14,14,14,14,15,16,18,20,24,27,31,33,35,34,34,33,28,23,23,28,32,42,56,74,90,103,111,109,103,89,79,66,57,53,52,50,48,41,38,32,28,28,33,41,47,51,52,51,48,45,47,55,62,75,91,104,105,102,96,79,61,45,41,40,47,61,72,77,76,65,56,44,34,30,33,41,46,54,56,55,48,39,35,38,43,59,69,77,74,65,54,42,33,32,37,42,44,42,40,38,38,43,39,37,39,40,40,44,50,58,61,63,62,58,53,49,48,48,48,46,45,46,52,60,66,74,80,83,80,75,69,59,50,43,39,35,33,35,38,40,41,39,38,35,32,31,34,41,47,58,62,65,64,58,52,47,45,52,63,75,83,89,93,89,82,83,83,82,80,76,73,71,71,75,85,96,104,111,113,105,94,78,68,55,47,47,50,53,53,54,54,55,55,52,47,43,40,37,39,43,46,47,46,45,44,42,44,48,53,58,58,55,53,47,46,45,46,47,45,39,34,27,24,21,21,25,27,25,23,22,22,24,29,37,43,47,49,52,48,42,36,31,29,28,27,28,29,30,30,29,30,32,34,42,41,41,42,43,45,47,48,46,44,39,34,30,30,34,38,47,56,65,68,68,65,57,47,37,32,28,29,31,34,40,48,53,53,51,46,40,36,33,33,35,35,36,35,33,29,25,23,22,23,25,27,30,33,35,36,39,44,51,56,58,57,53,50,42,37,31,30,32,33,30,27,26,24,22,22,22,23,24,25,28,35,41,42,43,44,40,34,27,26,27,29,33,36,39,40,40,36,31,28,29,31,32,32,35,37,40,45,50,54,58,60,65,66,64,58,54,50,42,33,31,33,39,48,59,68,73,75,67,61,51,41,33,29,28,28,27,27,26,25,25,25,26,26,33,37,45,56,68,79,87,92,90,85,75,64,54,46,41,39,37,37,37,37,35,33,31,30,27,28,27,27,25,22,20,18,18,19,19,20,21,22,22,23,22,22,21,20,20,19,19,18,16,16,15,15,15,15,15,15,15,15,15,14,14,14,13,13,12,12,12,11,11,11,10,10,10,10,10,10,10,10,10,10,7,7,7,7,7,7,7,7,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 12,12,13,14,15,16,16,17,16,17,18,20,21,21,21,21,19,19,19,19,19,19,19,19,14,15,15,17,18,19,20,20,19,21,24,26,28,29,29,29,28,28,27,29,31,31,30,28,22,21,19,17,15,14,14,14,16,15,14,13,13,13,13,13,16,17,20,23,27,30,32,34,32,34,33,30,26,25,29,33,39,52,69,83,95,102,100,93,86,75,60,49,44,42,41,39,36,33,29,25,25,30,38,43,51,54,54,51,47,47,53,59,67,85,101,105,106,104,90,72,49,44,42,49,63,76,82,82,72,63,50,38,34,36,43,48,57,60,60,53,43,36,38,41,51,60,67,64,56,47,36,28,30,34,38,39,37,36,37,39,46,42,40,41,40,40,45,52,64,68,71,70,65,58,51,48,43,42,41,41,44,52,63,71,87,92,95,92,86,79,68,58,49,44,38,35,35,38,40,41,41,40,37,33,30,33,40,47,56,60,63,62,56,49,44,43,54,65,76,79,81,82,75,65,71,71,70,68,65,64,64,65,71,81,92,98,104,106,97,86,70,59,46,38,38,42,44,45,50,51,52,52,49,45,41,38,35,37,40,43,44,43,41,39,36,38,42,48,53,55,54,52,47,44,42,42,42,40,35,30,25,22,19,20,24,26,24,22,20,20,21,25,31,37,39,40,45,43,39,34,30,27,26,25,27,28,29,29,28,28,31,33,40,40,40,41,45,49,53,56,52,50,45,39,34,33,35,37,42,50,57,60,60,58,51,43,36,32,29,32,34,36,42,49,52,51,48,42,35,30,29,29,31,31,31,30,27,24,21,20,22,23,26,29,33,37,39,41,43,48,57,63,66,63,58,54,45,38,31,29,31,33,31,28,27,25,23,22,23,24,25,24,27,32,36,37,37,39,36,31,26,26,27,30,33,36,39,40,39,35,30,28,29,31,33,33,42,42,42,44,46,48,50,52,57,58,55,49,46,43,36,28,33,37,44,55,65,72,74,74,62,56,47,38,32,30,30,31,31,30,29,28,27,27,27,27,36,41,50,61,73,83,90,94,85,79,68,56,46,39,35,33,36,37,37,37,36,34,32,31,29,29,28,27,24,21,18,16,18,18,19,20,22,23,24,25,23,22,21,20,19,18,18,17,15,15,16,16,16,17,17,17,17,16,16,16,15,14,14,14,12,12,12,11,11,10,10,10,10,10,10,10,10,10,10,10,7,7,7,7,7,7,7,7,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 9,10,12,14,15,17,17,17,16,17,19,21,24,25,26,26,23,22,22,23,25,25,24,22,23,21,19,18,19,20,19,18,21,20,20,22,25,28,29,29,27,27,27,26,26,26,25,25,24,23,21,18,16,15,14,14,13,13,13,13,13,13,13,13,18,20,22,25,29,32,34,35,35,34,34,33,33,32,31,31,41,47,57,68,78,84,87,89,73,67,58,48,41,37,35,35,33,28,26,28,30,31,36,42,52,54,56,56,55,54,55,56,74,85,97,107,112,109,95,81,62,51,45,52,66,77,86,92,87,74,59,48,39,35,39,46,60,64,67,62,48,36,31,33,39,41,47,51,46,38,34,36,33,35,37,35,31,30,33,36,41,46,49,46,41,41,47,54,64,71,76,75,72,67,57,48,43,37,34,36,43,53,70,84,97,108,116,112,101,90,79,71,66,60,52,45,41,39,37,36,40,39,36,33,33,36,43,48,56,59,60,55,47,42,43,46,56,67,79,81,73,63,57,56,52,55,61,66,66,62,59,60,67,72,79,85,88,84,77,70,49,44,37,31,30,34,40,45,48,47,45,44,44,42,39,37,36,36,37,40,43,44,43,41,37,38,41,46,52,55,56,55,48,43,38,34,32,30,29,27,24,24,23,23,23,24,25,25,24,24,23,24,25,27,30,31,35,32,29,28,28,28,27,25,27,26,25,23,23,25,29,32,34,37,42,45,46,50,56,61,57,54,47,39,32,29,31,33,36,42,48,52,51,48,45,43,40,38,36,35,36,39,43,45,44,41,36,31,27,25,24,24,28,28,27,24,21,19,19,20,25,30,37,41,42,40,39,39,44,47,55,63,69,67,59,53,41,36,31,29,31,33,33,32,28,28,28,28,27,25,24,23,23,24,27,29,31,31,31,30,29,29,30,31,33,34,35,36,31,31,29,26,25,28,33,37,46,46,45,42,40,39,41,43,49,48,45,41,37,35,36,38,40,48,58,65,67,65,62,60,47,44,41,38,37,38,40,42,39,35,32,32,31,28,29,33,44,48,54,62,70,77,81,84,75,67,54,43,36,33,31,30,34,36,38,40,39,37,34,32,29,27,25,23,21,20,19,19,18,20,22,25,26,27,27,26,27,26,23,21,18,16,15,15,16,17,18,19,19,19,19,18,15,15,14,14,13,12,11,11,10,10,10,10,10,10,10,10,9,9,9,10,10,11,11,11,9,9,9,9,9,9,9,9,7,7,7,6,6,5,5,5,6,6,6,5,5,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 10,11,13,15,16,17,18,18,17,18,21,23,25,26,27,28,26,25,25,26,28,28,27,25,25,23,20,20,21,21,20,19,21,19,19,21,24,27,28,27,26,26,26,25,25,25,25,25,23,22,20,18,16,15,15,15,14,14,14,14,14,14,14,14,19,21,23,26,29,32,34,35,35,35,35,34,33,32,32,31,35,39,47,56,63,69,72,73,63,60,53,46,41,38,37,37,35,30,27,29,30,31,36,42,51,53,57,58,59,59,60,61,73,84,97,107,113,110,97,83,63,52,46,53,67,79,88,95,92,80,64,52,42,38,42,49,61,66,71,67,55,41,35,34,34,35,40,44,41,35,33,36,36,38,38,36,32,30,32,35,43,48,52,50,45,45,50,55,68,75,80,80,77,73,64,55,48,41,37,39,46,59,77,93,108,118,125,120,109,99,90,83,75,69,61,52,46,41,38,36,41,40,39,37,37,39,45,49,57,59,59,53,44,40,42,45,61,71,80,79,67,53,45,42,47,53,62,69,70,66,62,61,61,63,66,70,71,68,61,56,42,39,33,29,29,33,39,43,49,47,45,44,43,41,38,36,37,37,38,41,45,47,46,45,41,42,44,48,52,55,56,55,46,42,35,31,29,28,26,25,25,25,24,24,24,25,25,25,25,24,24,24,24,25,27,28,30,28,27,28,30,31,29,28,25,24,23,22,22,24,28,31,33,36,40,42,44,48,54,59,56,53,47,39,32,28,29,30,34,39,44,47,47,45,43,42,39,38,36,36,37,38,41,42,39,37,32,27,24,22,21,21,27,27,26,23,20,19,21,23,32,37,43,47,46,44,41,40,42,45,52,60,64,62,55,49,37,34,30,30,32,33,33,31,28,28,27,26,25,24,23,22,21,22,24,26,28,29,30,30,30,30,30,31,31,32,33,33,30,29,27,25,25,29,35,40,48,49,47,44,40,37,36,37,42,41,40,37,35,36,39,42,54,60,67,70,67,61,55,52,40,39,38,38,39,40,42,43,41,36,32,31,30,27,29,34,40,45,54,63,69,73,74,73,65,57,46,37,32,29,28,28,33,35,37,38,38,35,32,30,27,26,25,23,21,20,20,20,19,21,23,26,27,27,27,26,25,24,22,19,17,16,15,14,17,17,18,19,19,19,19,19,15,15,14,14,13,12,12,11,10,10,10,10,10,10,10,10,9,9,9,10,10,11,11,11,9,9,9,9,9,9,9,9,7,7,7,6,6,6,5,5,6,6,6,5,5,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 10,12,13,15,17,18,19,19,19,21,23,25,27,29,29,30,29,28,28,30,32,32,31,29,27,25,23,22,23,23,22,20,20,18,17,19,22,24,25,25,24,24,24,24,24,24,24,25,21,20,19,18,17,17,17,17,17,17,17,17,17,17,17,17,21,22,24,26,29,31,33,34,36,36,35,34,34,33,32,32,31,33,37,42,47,51,53,54,50,49,47,45,44,42,41,40,38,32,29,30,31,32,36,42,49,53,58,62,63,63,65,66,72,82,95,105,112,111,99,86,65,55,49,55,68,81,92,101,99,87,71,56,45,39,43,51,63,71,79,77,66,53,43,38,30,29,32,35,35,32,34,39,42,44,43,39,32,29,30,32,43,49,54,54,51,50,53,58,70,77,83,83,82,79,72,64,56,48,43,44,52,67,88,106,121,129,134,127,115,106,98,93,86,81,72,62,52,44,39,36,40,42,43,44,44,46,49,52,61,61,59,51,42,38,41,45,64,73,80,76,62,45,35,31,45,55,68,77,79,75,69,65,58,56,54,53,51,49,44,41,36,34,32,31,33,37,41,45,50,47,44,42,41,39,36,34,36,36,38,41,47,50,52,51,49,48,48,50,54,56,56,55,48,42,35,30,28,28,27,27,26,26,26,26,26,26,26,26,27,27,26,25,25,24,24,24,24,24,25,28,32,33,32,30,23,22,20,20,21,25,28,31,33,35,37,38,41,45,51,55,54,52,46,39,31,27,26,26,31,34,39,41,40,40,39,40,36,36,36,36,36,37,37,37,33,31,27,23,20,18,18,19,26,25,23,21,19,20,24,27,38,43,48,50,48,44,40,38,38,41,47,52,55,53,47,42,31,30,30,31,33,34,33,31,29,28,26,24,23,22,22,22,20,20,21,22,24,27,30,32,33,32,31,30,29,29,29,29,27,26,25,23,25,31,40,47,54,54,52,47,40,34,30,28,31,32,32,33,34,38,44,48,63,67,71,70,64,54,46,41,31,33,36,39,42,44,44,45,42,36,31,29,28,26,29,34,35,41,51,60,65,65,61,59,49,43,35,28,25,25,25,25,32,34,35,36,35,32,29,27,25,25,23,22,21,20,20,21,21,22,24,26,27,28,27,26,23,22,20,17,16,14,14,13,16,17,18,19,19,19,18,18,15,14,14,13,12,12,11,11,9,9,9,9,9,9,9,9,9,9,9,10,10,11,11,11,9,9,9,9,9,9,9,9,7,7,7,7,6,6,6,5,6,6,6,5,5,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 11,12,14,16,18,19,19,20,21,22,24,27,29,30,31,31,32,31,32,33,36,36,35,33,30,28,25,24,25,25,24,22,19,17,16,17,20,22,22,22,22,22,22,23,23,24,24,25,21,20,19,18,18,18,19,19,19,19,19,19,19,19,19,19,23,23,25,27,29,30,32,33,36,36,35,35,34,34,33,33,33,33,34,35,36,38,40,41,38,40,44,47,49,50,49,48,44,37,33,32,32,32,36,43,49,54,60,64,65,66,66,67,69,79,91,101,109,110,100,89,69,59,53,59,71,84,97,107,106,94,78,62,48,40,44,52,68,80,91,91,82,68,53,43,32,28,28,31,33,34,38,44,51,52,50,44,36,29,28,29,40,45,51,54,53,54,57,60,68,75,80,81,81,82,77,71,66,57,51,52,60,75,98,116,129,135,136,125,112,102,96,91,92,88,81,70,58,47,40,36,39,43,47,51,52,54,56,57,65,65,62,53,43,39,42,47,62,70,78,74,61,45,36,33,48,63,80,91,94,90,81,73,62,57,50,44,41,38,36,35,36,35,36,37,40,44,48,51,50,47,44,41,40,38,35,32,34,34,35,40,47,53,57,58,57,55,53,53,54,56,55,55,50,45,38,33,32,33,33,33,30,30,29,28,27,27,26,26,31,31,30,30,28,26,24,23,22,23,25,29,32,33,31,29,23,21,20,20,23,27,30,32,33,33,33,33,36,41,47,50,51,49,45,38,30,25,23,23,27,30,33,34,34,34,35,36,33,34,35,36,36,35,33,32,29,27,23,20,18,17,18,18,23,23,21,19,19,22,27,32,41,45,49,50,46,40,35,32,33,36,40,43,44,42,38,34,27,29,31,34,35,35,33,31,30,28,26,25,23,23,23,23,21,21,20,21,24,28,32,35,36,34,32,29,27,26,25,25,26,25,23,23,26,34,45,53,61,61,59,53,43,32,25,21,24,25,28,30,34,41,49,54,61,64,66,63,55,45,36,32,26,30,36,42,46,47,47,46,40,33,27,25,24,23,26,32,33,38,47,54,56,54,49,45,35,30,25,21,21,22,23,23,31,32,32,32,31,29,27,25,24,23,22,21,20,20,20,21,22,23,25,26,27,27,26,25,20,19,17,15,14,13,13,13,14,15,16,17,17,17,17,16,13,13,12,12,11,10,9,9,9,9,9,9,9,9,9,9,9,9,9,10,10,11,11,11,9,9,9,9,9,9,9,9,8,8,7,7,7,6,6,6,6,6,6,5,5,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 11,12,14,16,18,19,19,20,21,23,25,27,29,31,32,32,33,33,33,35,37,38,37,36,32,30,27,26,26,26,25,23,19,17,16,16,19,20,20,19,20,20,21,22,23,24,25,25,22,21,20,20,20,20,21,21,21,21,21,21,21,21,21,21,23,24,25,26,27,29,30,30,34,34,34,34,34,34,34,34,34,34,32,31,31,31,32,32,32,36,44,51,57,59,59,59,52,44,38,36,34,33,37,42,48,54,60,65,66,66,65,64,66,74,84,93,102,106,99,89,73,63,57,61,72,85,100,111,115,104,89,72,56,47,50,58,77,93,106,107,98,84,66,51,39,33,30,32,35,38,43,50,59,60,59,52,42,33,29,28,34,39,46,50,52,54,57,61,65,70,75,76,79,83,83,80,78,69,62,62,68,82,102,120,133,137,134,120,103,92,85,81,88,87,83,73,61,49,42,39,40,45,52,57,59,60,61,62,68,69,66,58,48,43,45,49,61,70,77,74,62,50,44,42,58,77,98,109,111,107,95,82,68,61,51,43,38,37,36,35,37,38,40,42,46,50,53,55,52,49,45,42,40,38,36,34,33,32,34,39,47,55,60,62,61,58,54,52,53,53,53,53,49,45,39,37,37,38,40,40,36,35,32,30,28,27,26,26,34,35,35,35,33,30,27,25,25,25,27,29,31,31,28,26,24,22,22,25,30,34,35,35,34,32,29,29,32,38,43,46,48,46,42,35,27,22,21,21,25,27,29,29,29,29,30,31,30,31,33,34,34,32,30,29,27,25,23,20,19,19,20,21,21,21,21,21,22,27,33,38,46,49,51,49,43,37,31,29,29,31,34,35,35,33,31,29,27,30,35,37,38,36,33,32,31,30,29,28,27,27,27,27,25,24,23,23,26,31,36,39,39,36,33,28,25,23,22,22,25,25,24,24,29,38,49,57,68,68,65,57,45,33,24,19,20,23,27,32,37,43,50,56,58,59,58,53,45,36,29,26,28,33,40,46,49,49,46,44,35,29,23,21,20,19,23,29,33,36,40,44,44,42,38,35,25,22,19,18,20,22,23,24,29,29,30,30,29,27,25,24,23,22,21,20,19,19,20,20,21,22,24,25,25,24,23,22,18,17,15,14,13,12,12,13,12,13,13,14,15,15,14,14,12,12,11,11,10,9,8,8,9,9,9,9,9,9,9,9,9,9,9,10,10,11,11,11,9,9,9,9,9,9,9,9,8,8,8,7,7,7,6,6,6,6,6,5,5,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 10,12,13,15,17,18,19,19,21,22,24,26,28,30,31,31,32,32,32,34,37,38,37,36,34,31,28,27,27,27,25,24,19,17,16,16,18,19,19,18,19,20,21,22,24,25,26,27,24,24,23,22,22,22,23,23,22,22,22,22,22,22,22,22,24,24,24,25,26,26,27,27,30,30,31,32,33,34,35,36,33,32,31,29,28,27,27,27,30,35,45,55,63,68,69,69,61,52,44,40,36,34,37,42,46,52,61,66,68,66,65,64,64,70,76,84,93,99,95,88,75,65,58,61,70,83,99,112,120,112,100,86,70,60,63,71,89,107,121,122,114,100,79,60,48,40,34,35,38,41,46,52,62,65,66,61,51,41,35,33,32,36,41,45,48,51,54,57,60,65,68,69,75,84,89,89,91,83,76,74,78,87,104,119,132,135,129,113,94,82,74,69,77,79,79,74,63,53,47,45,45,50,57,61,63,63,62,62,68,71,71,65,55,48,47,50,62,69,75,72,62,53,50,51,71,92,114,123,125,119,104,88,71,64,53,45,40,39,38,38,39,39,41,44,48,52,55,56,56,53,48,45,44,43,42,40,38,36,36,39,46,54,59,62,61,57,51,48,47,48,48,48,44,41,39,39,42,44,46,46,44,41,35,30,27,26,26,27,36,37,39,40,39,36,32,29,29,28,28,28,29,28,26,23,26,26,28,33,40,43,42,39,36,31,27,26,29,35,40,43,45,43,38,31,24,20,20,21,24,26,28,28,26,25,26,27,27,28,30,31,31,30,29,28,27,25,23,21,21,22,24,25,22,24,25,27,29,35,41,46,53,54,53,49,42,36,32,30,27,29,31,31,30,28,28,29,32,35,40,41,40,36,34,33,32,32,33,34,34,33,32,32,29,28,27,27,30,34,38,41,41,38,34,28,24,22,22,22,27,27,27,28,32,41,52,59,72,72,68,59,47,34,25,20,21,25,30,35,39,43,48,51,54,54,51,45,37,31,27,26,34,38,45,49,50,47,42,38,30,24,19,19,19,18,22,27,32,33,35,36,35,32,29,26,19,18,16,17,20,23,24,24,27,27,27,28,27,26,26,25,23,22,21,19,19,18,18,18,20,20,22,22,22,21,19,18,16,15,14,13,13,13,13,13,11,12,13,14,14,14,14,13,14,13,13,12,11,10,10,9,10,10,10,10,10,10,10,10,9,9,9,10,10,11,11,11,9,9,9,9,9,9,9,9,9,8,8,8,7,7,7,7,6,6,6,5,5,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 10,11,13,15,16,17,18,18,19,20,22,25,27,28,29,29,30,30,30,32,35,37,36,34,34,32,29,27,27,27,25,23,20,18,16,16,18,19,18,17,19,20,21,23,24,26,27,28,27,27,26,24,24,24,24,24,23,23,23,23,23,23,23,23,23,23,23,24,24,24,24,24,26,27,29,31,33,35,36,37,32,32,31,30,29,28,27,27,30,36,47,58,68,73,76,76,68,59,50,44,38,35,37,42,43,50,60,67,70,69,68,67,62,65,69,74,83,91,91,86,75,65,57,58,66,79,95,109,117,112,105,95,81,72,76,84,101,119,134,133,126,112,89,67,55,45,38,37,39,41,45,50,59,64,69,68,61,51,45,42,35,37,39,41,43,46,49,52,53,56,58,59,67,81,91,94,104,97,90,87,87,92,104,115,125,127,122,105,86,73,64,59,65,70,74,73,65,58,54,53,54,58,63,65,64,61,59,59,65,70,74,70,60,52,48,48,58,65,70,68,60,55,56,60,80,103,125,132,132,125,108,89,71,65,56,49,45,44,43,42,42,43,44,46,49,52,56,58,62,58,54,51,50,50,49,48,48,45,42,42,46,51,56,58,56,51,45,40,39,40,41,41,41,40,41,44,49,53,54,54,51,46,38,30,25,24,26,27,35,37,40,42,42,39,35,33,31,29,27,27,27,27,25,23,29,30,34,42,49,52,48,43,37,32,25,24,27,34,39,41,43,41,35,28,22,19,20,22,24,26,28,28,26,23,22,22,25,26,27,28,29,29,29,29,27,25,23,22,23,24,27,28,25,28,31,35,39,44,51,55,57,56,54,48,40,35,32,31,28,30,32,31,29,28,30,32,38,41,45,45,41,37,35,34,33,35,38,40,41,40,38,37,31,31,30,31,32,35,39,41,43,40,34,29,24,22,22,22,29,29,30,32,36,43,53,59,73,72,67,58,46,34,26,22,23,28,33,38,39,41,42,43,44,43,40,35,31,29,31,33,41,44,48,50,48,42,34,30,25,20,18,19,20,19,22,27,29,31,32,32,30,26,22,19,17,16,15,17,21,23,24,23,25,25,26,26,27,27,27,27,24,23,21,19,18,17,16,16,17,18,19,19,19,17,16,15,15,15,14,13,13,13,14,14,13,13,14,15,15,15,15,15,17,16,16,15,14,13,13,13,11,11,11,11,11,11,11,11,9,9,9,10,10,11,11,11,9,9,9,9,9,9,9,9,9,9,8,8,8,7,7,7,6,6,6,5,5,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 9,10,12,14,15,17,17,17,18,19,21,24,26,27,28,28,29,28,29,31,34,35,35,33,35,32,29,27,27,27,25,23,21,19,17,17,18,19,18,17,19,20,21,23,25,27,28,29,29,29,27,26,25,25,25,25,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,24,25,27,29,32,35,37,38,32,33,33,33,32,31,29,29,30,37,48,59,69,76,79,80,73,63,53,46,40,35,37,41,41,49,60,68,72,72,71,70,61,63,65,68,77,87,88,84,73,63,55,55,62,75,92,106,111,109,105,97,86,78,82,91,107,126,141,140,132,119,95,72,58,48,39,37,39,39,42,46,55,62,70,72,67,59,52,49,39,39,39,39,40,43,46,48,46,49,49,51,60,76,89,94,112,105,99,96,94,95,103,113,117,120,115,98,79,66,58,53,57,64,71,72,67,61,59,59,60,63,66,67,64,59,56,55,63,69,75,73,63,53,48,47,51,58,64,64,59,57,62,67,85,108,129,135,134,127,108,88,72,66,59,53,50,48,47,46,47,47,47,48,51,54,58,60,66,62,58,56,55,56,55,54,56,52,47,45,46,50,53,54,52,47,40,35,34,35,35,36,41,42,44,50,56,60,61,61,55,49,39,30,24,23,25,27,33,36,40,43,43,41,37,34,32,29,27,26,26,26,25,24,31,33,38,47,56,57,52,46,38,32,25,23,27,33,38,40,42,39,33,26,20,18,21,23,25,27,29,29,26,23,21,20,24,25,25,26,27,28,29,30,26,25,23,23,23,25,28,29,28,32,36,41,45,51,57,61,58,56,52,45,38,32,31,31,30,32,34,33,30,30,33,36,42,45,48,47,42,37,35,35,33,36,40,44,46,44,42,40,32,32,32,32,34,36,38,40,44,41,35,29,25,23,22,22,30,31,33,35,38,45,53,59,72,70,66,56,45,34,27,23,25,29,35,39,39,38,37,37,32,31,29,27,26,29,35,40,46,48,50,50,45,37,29,23,23,19,18,20,21,21,23,28,26,28,31,32,29,24,18,14,16,15,15,17,21,23,23,23,24,24,25,26,26,27,28,28,24,23,21,19,17,16,15,15,16,16,17,18,17,15,13,12,15,15,14,13,13,14,14,15,14,15,16,17,17,17,17,16,19,19,19,18,17,16,16,15,12,12,12,12,12,12,12,12,9,9,9,10,10,11,11,11,9,9,9,9,9,9,9,9,9,9,9,8,8,7,7,7,6,6,6,5,5,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 10,10,11,12,14,15,16,17,16,16,17,18,20,23,25,26,26,26,27,28,29,30,31,31,29,28,27,26,25,23,22,22,19,19,18,17,16,16,16,16,15,17,21,24,27,29,30,30,30,29,27,24,23,21,21,21,21,21,20,20,20,21,22,23,20,21,21,21,21,20,19,18,20,21,22,25,28,32,35,36,34,33,31,31,32,31,30,28,34,36,44,57,66,71,76,82,75,70,62,51,42,36,36,37,44,53,62,70,77,81,77,70,60,56,55,61,71,76,75,71,66,62,56,53,57,67,78,86,94,99,100,93,84,81,88,96,118,131,143,144,135,118,95,76,61,52,45,43,39,35,37,43,49,57,66,72,77,80,75,67,57,51,42,37,35,37,39,40,41,43,44,45,49,63,84,101,109,112,112,107,98,94,98,103,107,107,104,96,84,71,60,55,56,59,64,67,68,66,62,59,63,64,64,61,56,52,49,48,59,64,69,71,67,58,49,43,48,48,53,56,53,50,58,70,91,111,130,133,125,112,94,78,67,62,56,53,53,53,52,50,46,45,43,43,46,55,65,73,72,70,67,63,59,59,63,66,65,64,58,50,47,48,46,42,41,37,33,31,33,36,38,39,38,39,44,52,62,68,68,67,62,54,42,31,24,24,27,29,34,37,42,43,41,38,36,35,33,31,28,23,21,22,26,30,29,40,51,58,63,64,59,53,39,34,28,25,29,36,43,47,47,42,35,28,23,21,22,23,30,32,32,31,28,26,25,26,21,23,27,29,29,26,23,21,23,22,23,28,33,34,35,36,39,38,41,49,60,69,72,72,68,59,50,44,37,29,27,29,30,30,29,28,29,33,39,44,54,55,55,52,46,39,35,34,38,42,47,51,51,47,41,37,32,31,30,29,31,34,38,41,45,44,41,36,30,27,27,28,31,36,41,40,37,39,47,55,64,63,59,52,42,33,27,24,27,32,38,41,39,35,32,30,25,24,23,24,28,35,42,47,54,51,47,40,34,29,26,24,17,20,22,24,23,24,25,27,29,31,32,30,26,21,18,17,14,15,17,20,22,23,24,24,25,26,27,28,29,30,30,30,28,27,24,21,18,16,15,14,14,15,16,17,17,15,14,13,14,13,11,10,11,13,15,17,20,20,20,21,22,24,25,26,25,25,24,22,20,19,18,17,16,15,14,13,13,13,13,13,12,12,11,11,11,10,10,10,10,10,10,10,10,10,10,10,8,8,8,7,7,6,6,6,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 9,10,11,12,13,14,15,16,15,16,16,17,19,21,23,24,24,25,25,26,27,28,29,29,27,27,26,25,24,22,21,21,19,18,17,16,16,16,16,16,15,17,20,23,26,27,28,28,28,27,25,23,21,20,19,19,19,19,19,19,19,20,20,21,20,20,20,20,20,19,18,18,19,20,21,23,26,30,33,34,33,31,29,29,30,30,28,26,29,30,36,48,58,64,72,79,78,75,68,58,49,43,41,42,46,55,65,72,79,82,78,71,62,57,53,57,65,70,70,67,66,62,56,53,54,60,68,73,81,85,87,82,74,73,81,90,109,121,132,133,124,109,89,72,60,53,48,46,43,38,38,43,46,54,64,72,79,84,81,75,64,56,46,39,37,38,40,42,38,39,38,37,40,55,77,93,106,110,111,106,96,91,92,96,98,99,99,93,83,71,62,57,54,56,60,63,64,62,59,56,59,61,61,58,54,49,47,47,58,63,69,70,66,58,49,43,42,44,49,53,50,47,54,64,82,100,117,120,112,98,80,66,52,49,48,49,52,55,54,53,51,50,49,49,52,60,70,77,76,74,69,63,60,60,64,68,71,70,65,56,51,48,44,38,36,34,32,33,37,41,45,46,47,47,50,57,66,72,73,71,63,55,43,32,25,24,26,29,34,37,41,42,40,37,35,34,34,32,29,25,22,22,26,29,33,43,54,61,65,65,59,52,37,33,27,26,29,36,43,47,45,41,34,27,23,22,24,25,32,33,34,32,29,27,27,28,25,27,30,30,29,26,24,23,25,26,30,37,42,45,44,44,44,44,48,58,69,75,75,72,64,55,45,39,33,26,25,27,24,25,27,28,32,39,48,54,61,62,62,58,51,44,39,36,40,43,48,51,50,46,40,36,29,28,27,28,30,34,39,41,47,46,43,37,32,28,27,28,31,35,39,38,34,36,43,50,56,56,54,49,41,33,29,27,29,33,38,40,38,32,28,25,21,21,22,25,31,38,45,49,52,49,44,38,33,30,27,27,24,25,26,26,24,24,25,26,26,28,29,28,23,19,16,15,14,16,18,20,22,24,24,25,26,27,28,29,30,31,31,31,29,28,26,23,20,18,17,16,15,15,16,16,16,15,13,12,14,13,12,11,12,15,17,19,22,22,23,25,26,28,30,31,32,31,29,27,25,23,22,21,18,17,16,14,13,13,13,13,13,12,12,12,11,11,11,10,10,10,10,10,10,10,10,10,8,8,7,7,7,6,6,6,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 9,9,10,11,12,13,14,14,14,14,15,16,17,19,21,22,22,22,23,23,24,25,25,26,25,25,24,23,22,20,20,19,18,17,16,16,15,15,16,16,16,17,19,21,23,24,24,24,25,23,22,20,18,17,17,17,17,17,17,17,18,18,19,19,19,19,19,19,18,18,18,17,17,18,19,21,24,27,29,31,32,31,30,30,31,31,29,27,26,24,28,38,48,56,66,75,79,77,73,66,57,50,47,46,49,58,68,75,82,85,80,72,65,57,50,49,55,60,62,61,65,61,56,52,50,52,54,56,64,68,70,67,62,63,72,81,98,109,118,117,109,97,81,68,58,55,53,53,50,44,42,43,42,51,62,71,82,89,89,84,71,63,51,43,40,42,45,47,42,40,35,31,34,48,69,85,102,106,107,102,92,83,81,82,85,88,90,88,81,72,65,61,55,56,59,61,60,58,55,53,53,54,55,54,51,49,49,49,60,65,70,70,65,55,47,42,38,42,49,53,50,47,50,57,72,86,99,102,94,80,65,53,41,41,43,47,52,56,58,58,56,56,55,55,58,64,73,80,81,77,70,63,58,59,64,69,77,79,75,65,57,50,42,34,31,30,32,37,45,52,57,59,60,58,57,61,69,74,76,76,66,58,46,35,28,26,28,30,35,37,40,40,38,35,35,35,36,35,32,27,24,23,26,28,35,46,56,62,65,64,57,49,35,31,27,26,30,37,43,46,41,37,32,26,24,24,27,29,35,36,36,34,32,30,30,31,32,33,34,32,29,26,25,25,27,33,41,50,58,60,58,54,51,52,57,67,78,81,77,72,61,51,39,33,28,24,23,26,21,23,26,29,35,45,55,63,70,71,70,64,56,47,40,37,41,44,48,50,49,43,37,32,25,24,24,25,29,34,39,42,49,48,45,39,33,29,27,27,30,34,36,35,31,31,37,43,47,48,47,44,38,33,29,28,29,33,38,39,35,28,22,19,16,18,22,28,34,41,47,51,47,44,39,35,31,30,31,31,32,32,31,28,24,23,24,26,25,27,28,27,23,19,16,15,15,16,18,21,23,24,25,25,28,28,29,29,30,31,31,31,31,30,28,26,24,21,20,19,17,17,17,16,15,14,12,11,13,13,13,13,15,17,20,21,27,27,29,31,33,36,37,38,38,36,34,32,29,26,24,23,20,19,17,15,14,13,13,13,14,13,13,13,12,12,12,11,10,10,10,10,10,10,10,10,8,7,7,7,6,6,6,6,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 8,9,9,10,11,12,13,13,14,14,14,14,15,17,18,19,19,19,20,20,21,21,21,22,22,21,21,20,19,18,17,17,17,16,15,15,15,15,15,16,16,17,18,19,19,20,20,20,22,21,19,17,16,15,15,15,16,16,17,18,19,19,19,19,19,19,18,18,17,17,17,17,16,17,18,19,21,24,26,28,33,32,32,34,36,36,34,32,27,24,24,31,39,48,60,70,75,75,75,71,64,57,52,50,51,60,70,77,83,86,81,73,65,56,47,43,45,51,54,55,62,60,57,53,50,47,45,44,52,55,57,54,52,55,64,73,88,98,105,102,93,83,71,62,56,57,59,60,58,53,48,45,42,50,60,69,80,89,90,86,72,64,53,46,45,49,55,58,55,51,43,35,35,47,66,80,96,99,99,94,83,72,67,65,70,74,79,80,77,72,67,65,59,60,61,61,59,55,51,49,46,48,51,52,53,54,56,58,67,72,75,73,64,53,44,39,41,47,55,59,56,52,50,52,63,72,82,84,79,68,56,48,43,43,44,48,52,57,61,63,60,60,59,59,61,66,74,79,81,76,68,59,54,55,61,66,78,82,81,73,63,53,42,33,28,30,36,46,57,67,73,75,72,68,64,65,71,76,78,78,69,62,51,40,33,31,32,34,37,39,39,38,36,35,35,36,39,38,36,31,27,25,26,27,35,44,54,59,60,58,51,42,32,29,26,27,31,37,41,44,37,34,29,26,25,27,30,33,38,38,38,37,34,33,34,35,37,38,38,34,28,25,26,27,32,42,56,67,75,77,71,63,58,57,61,70,80,83,77,70,58,46,34,28,25,22,22,25,24,25,27,31,38,48,59,67,77,77,75,69,58,47,39,35,39,42,46,48,46,40,33,28,21,21,21,23,27,33,39,42,50,49,46,41,34,29,26,26,28,31,33,31,28,28,32,36,40,41,42,39,34,30,28,27,26,31,35,36,32,26,20,17,15,18,23,30,37,42,46,48,42,39,35,31,30,32,34,36,39,37,33,28,23,21,22,24,26,28,29,28,24,20,17,16,16,17,19,21,23,25,26,26,27,27,27,27,28,28,29,30,31,31,30,28,26,24,23,22,19,18,17,16,15,13,12,11,13,13,14,15,18,21,23,25,32,34,36,38,41,43,44,45,40,39,36,33,30,26,24,23,22,20,18,16,14,13,12,12,14,14,14,13,13,13,12,12,9,9,9,9,9,9,9,9,7,7,7,6,6,6,5,5,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 9,9,10,10,11,12,12,13,14,13,13,13,14,15,16,17,17,17,17,17,18,18,18,18,18,18,18,17,16,16,15,15,15,15,14,14,14,14,15,16,16,16,16,17,17,17,18,18,20,19,17,16,15,14,14,14,16,17,19,20,21,22,21,21,20,19,18,17,16,17,17,18,16,17,17,19,20,23,25,26,31,32,34,37,41,43,41,40,33,27,23,25,31,39,50,61,70,73,75,74,70,64,60,58,55,63,70,76,81,83,78,71,61,53,43,38,39,44,49,51,58,58,57,55,52,47,42,39,43,45,46,44,43,47,57,65,80,88,93,87,77,67,58,51,53,57,63,66,65,61,54,49,44,51,58,65,74,81,82,77,65,59,51,48,51,60,68,73,73,66,56,46,44,52,67,78,91,92,90,82,71,60,53,50,57,62,67,70,70,68,66,66,62,63,63,62,58,52,47,43,41,45,50,54,58,63,69,73,78,82,84,78,65,51,41,37,46,54,64,67,64,59,53,49,55,59,64,67,65,59,53,51,48,48,48,49,52,57,63,67,64,64,64,63,63,67,72,76,76,70,61,51,46,48,54,60,71,78,82,76,66,57,46,37,29,34,43,57,71,83,89,92,85,79,73,71,74,78,79,79,71,65,54,45,38,37,38,40,41,42,41,38,36,35,37,39,44,43,41,36,31,27,27,27,32,40,48,51,52,50,43,35,30,28,27,28,32,37,39,40,34,31,27,25,25,29,33,36,40,41,40,38,36,36,37,39,41,43,42,36,29,25,27,29,42,57,74,87,94,94,82,69,60,57,58,66,76,78,72,65,50,38,26,23,22,21,22,24,27,28,30,34,41,52,64,72,84,84,81,73,61,48,38,33,36,39,43,45,43,37,30,26,20,20,20,22,26,32,37,41,48,48,46,41,34,28,25,25,26,28,30,29,27,27,29,32,38,39,39,36,31,27,24,23,23,27,31,32,29,25,20,18,17,20,26,32,37,40,42,42,37,35,32,30,31,34,38,41,41,38,33,26,20,19,22,25,28,29,30,29,24,19,16,15,16,18,20,22,24,26,26,27,25,24,24,23,23,24,26,26,30,30,30,30,28,26,24,23,20,20,18,17,15,14,13,13,13,14,16,19,23,26,29,30,38,40,42,44,46,47,47,47,41,39,37,33,30,26,24,23,22,20,18,16,14,13,12,12,14,14,14,13,13,13,12,12,9,9,9,9,9,9,9,9,7,7,6,6,6,5,5,5,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 10,10,11,11,12,12,13,13,14,14,13,13,13,14,14,15,15,15,15,15,15,16,16,16,15,15,15,14,14,13,13,13,14,13,13,13,13,14,15,15,16,16,15,15,15,16,17,18,19,19,17,16,15,15,15,15,17,18,20,22,24,24,23,23,21,20,18,17,17,17,18,19,18,18,19,19,21,23,24,25,29,31,35,41,47,51,51,50,44,35,27,25,26,31,41,50,65,69,74,77,76,72,69,68,63,68,72,73,75,75,70,63,55,49,41,37,38,42,47,49,55,56,58,57,54,48,43,39,35,36,37,36,37,44,54,62,75,83,86,77,64,53,45,40,46,55,63,67,68,66,58,51,47,51,55,58,64,69,68,63,54,50,47,49,57,70,81,88,86,80,70,61,58,63,73,80,88,86,81,71,59,49,43,40,46,50,55,58,59,59,61,62,62,63,65,64,60,53,46,42,41,45,52,58,65,73,80,85,89,93,93,84,68,52,42,38,49,60,72,76,74,69,59,51,51,49,49,53,53,52,53,56,52,53,53,53,54,57,63,67,66,66,66,64,63,64,67,70,67,61,53,44,39,40,46,51,61,71,78,75,67,58,48,40,33,40,52,68,84,96,102,104,95,88,80,76,77,79,79,78,69,64,55,47,43,42,44,46,47,46,43,39,37,37,40,43,48,48,46,42,35,30,28,28,30,37,43,44,44,43,38,30,29,28,27,29,33,36,37,36,31,29,26,24,26,30,35,38,42,42,41,39,37,37,39,42,44,47,47,41,33,28,29,33,51,70,91,103,108,104,87,68,56,52,51,59,69,72,64,55,40,29,20,20,24,27,28,31,32,33,35,39,46,58,71,79,89,89,86,78,65,50,39,33,32,35,40,43,42,37,31,27,21,21,21,22,25,30,35,39,45,45,43,39,32,27,24,23,23,25,27,28,27,28,30,32,38,39,39,35,30,25,22,21,22,25,28,29,26,24,22,21,20,23,27,32,35,37,37,37,33,32,31,31,33,37,41,43,41,37,30,23,18,19,23,28,30,32,32,30,24,19,15,14,17,18,21,23,25,26,27,28,23,22,20,20,20,21,22,23,28,29,29,29,28,26,24,23,22,21,19,18,17,16,16,16,17,18,22,25,30,33,36,38,44,45,47,48,48,48,47,46,40,39,37,33,30,27,24,23,20,19,17,15,14,13,13,13,14,13,13,13,12,12,12,11,8,8,8,8,8,8,8,8,6,6,6,6,5,5,5,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 12,12,12,12,13,13,13,13,15,14,14,13,13,13,14,14,14,14,14,14,14,14,14,14,13,13,12,12,12,11,11,11,13,13,12,12,13,14,15,15,16,15,15,14,15,16,18,19,20,19,18,17,16,16,16,16,16,18,21,23,24,24,23,23,23,21,19,18,17,18,19,21,20,20,20,21,22,23,25,26,31,34,40,49,57,63,64,63,59,48,37,31,28,29,36,45,57,63,70,75,76,76,75,74,73,75,74,70,67,65,58,51,47,44,40,38,39,43,47,49,54,56,58,58,55,49,43,38,32,33,34,35,38,47,58,66,79,86,87,75,59,47,39,34,39,50,60,64,66,67,60,51,47,50,51,51,54,57,55,50,44,42,43,49,62,77,90,97,96,91,84,77,75,78,84,89,89,84,75,63,51,43,38,37,38,40,43,45,47,49,52,55,62,65,69,71,68,61,54,48,45,49,55,62,70,78,87,93,96,100,100,90,72,55,45,42,51,66,80,86,87,83,72,60,54,46,42,44,47,48,54,61,62,64,66,64,61,59,59,61,62,63,62,59,57,56,57,59,58,54,46,38,33,34,40,45,52,63,73,71,64,57,49,42,37,45,58,76,92,104,109,111,97,90,81,76,75,75,74,72,65,61,53,47,44,45,48,50,51,50,46,41,38,39,43,47,53,53,51,46,39,33,30,28,31,37,41,40,40,41,37,31,28,28,28,31,33,35,34,33,30,28,25,24,26,31,36,39,43,43,42,40,38,38,41,43,47,51,52,47,38,32,33,37,55,76,98,109,112,105,82,59,47,44,45,55,65,66,56,44,33,24,19,25,34,40,44,46,43,43,43,45,51,61,74,82,90,90,87,78,64,49,37,31,30,34,39,43,43,40,34,31,24,23,22,22,25,29,33,36,41,41,40,37,31,25,22,21,21,23,26,28,29,30,32,33,38,38,38,35,30,25,22,21,24,26,27,26,24,22,22,23,22,24,27,30,33,34,34,34,30,30,31,32,35,39,42,44,40,36,29,22,18,21,27,33,37,39,38,35,29,23,19,17,18,19,21,24,26,27,28,28,22,21,19,18,18,19,21,22,25,26,28,28,28,26,23,22,23,22,20,19,18,19,19,20,22,24,28,33,38,42,45,46,48,49,50,50,49,46,44,42,36,35,33,30,27,24,21,20,18,17,16,14,13,13,13,13,13,12,12,12,11,11,11,10,8,8,8,8,8,8,8,8,6,6,6,5,5,5,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 13,13,13,13,13,14,14,14,16,15,14,13,13,13,14,14,14,14,14,14,14,14,14,13,11,11,11,11,11,10,10,10,12,12,12,12,12,13,14,15,16,15,14,14,15,16,18,19,21,20,19,18,17,17,17,17,15,17,20,23,24,24,23,22,24,22,20,18,18,19,20,22,22,22,22,22,23,24,26,26,35,39,46,56,66,73,75,75,72,60,47,39,33,32,37,45,50,56,64,71,74,75,76,76,81,81,76,68,62,58,50,42,42,41,39,39,41,44,48,50,54,56,58,58,55,49,42,37,32,33,34,37,43,53,65,73,85,91,92,78,61,47,39,34,34,46,57,61,64,66,60,50,46,48,48,46,48,50,47,42,38,38,41,49,64,80,94,101,102,99,94,89,88,90,94,98,90,83,72,59,48,40,37,36,33,34,36,37,39,42,46,50,64,68,74,78,76,70,62,57,48,52,58,65,72,80,89,95,100,104,104,94,75,59,49,46,54,70,87,95,97,95,83,70,59,49,41,42,45,48,56,66,74,77,79,76,69,61,55,53,57,57,56,53,49,47,48,49,53,49,42,35,31,32,37,41,47,59,69,69,62,55,48,42,40,47,61,79,96,107,112,113,94,87,78,73,71,70,67,65,62,57,51,46,44,46,50,52,54,52,47,42,39,41,46,50,55,55,53,49,41,35,31,29,33,38,40,39,39,40,38,33,28,28,29,31,34,34,32,30,30,28,25,24,26,31,36,40,43,43,42,40,38,38,41,44,49,54,56,51,42,36,37,40,53,76,98,108,109,100,74,48,41,39,42,54,64,64,50,37,31,24,22,32,45,54,58,61,55,54,52,51,54,62,72,80,87,87,84,75,61,46,34,27,29,33,39,44,45,42,37,34,26,25,23,23,25,28,32,34,38,39,38,35,29,24,21,20,20,22,25,28,30,32,34,35,37,38,38,35,30,26,23,22,27,27,27,25,22,20,21,23,22,23,26,29,31,33,33,33,29,30,31,34,37,40,43,45,39,35,28,21,19,23,30,37,45,46,45,42,35,28,24,22,18,19,21,24,26,27,28,28,22,21,19,17,17,18,20,22,24,25,26,27,27,25,23,21,23,22,21,20,20,20,22,22,26,29,33,38,43,48,51,52,50,51,51,51,48,45,41,39,30,29,27,25,22,19,17,16,16,15,14,13,13,13,13,13,12,12,11,11,11,10,10,10,8,8,8,8,8,8,8,8,6,6,6,5,5,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 10,10,11,12,13,13,14,15,14,14,14,14,14,14,14,14,13,13,13,13,13,13,13,13,11,11,11,11,11,11,11,11,13,13,13,14,14,15,15,15,19,18,16,15,16,18,20,22,23,24,25,23,21,19,19,20,20,22,24,24,23,24,26,27,26,26,26,23,20,19,20,21,23,24,25,25,24,26,29,32,36,42,53,65,76,82,85,86,77,70,58,46,38,34,35,36,44,52,62,68,70,74,79,85,83,80,74,66,56,47,40,36,33,35,39,42,45,47,48,48,53,54,54,53,50,44,38,34,33,33,36,41,46,56,75,92,98,100,98,87,68,50,39,35,39,43,50,56,57,54,49,45,40,42,45,47,48,48,47,46,41,41,44,52,64,76,86,92,95,93,92,93,95,98,100,101,89,82,72,61,52,45,39,35,37,33,31,32,35,38,46,55,61,74,85,84,81,79,73,66,59,61,62,63,66,73,84,92,97,101,104,97,83,67,56,52,57,68,85,101,108,104,93,84,73,58,46,42,43,46,55,65,79,81,81,76,67,57,51,49,45,47,49,48,44,42,43,45,46,45,43,41,40,39,39,39,48,50,55,60,61,57,49,43,46,50,61,76,90,98,100,98,88,79,68,63,65,66,63,59,53,49,44,42,45,49,54,56,60,57,52,45,41,41,45,49,54,55,54,49,41,34,32,33,31,38,43,42,40,40,38,35,33,32,31,32,33,33,32,30,26,25,24,22,23,28,35,41,45,46,45,41,35,34,37,40,49,57,61,56,49,45,43,41,55,73,91,99,97,85,63,44,31,34,43,54,61,59,48,39,31,31,35,47,62,72,75,74,75,66,57,55,57,59,66,72,77,79,79,73,61,46,34,27,28,32,40,48,51,49,42,36,33,29,24,22,24,27,29,30,32,33,33,33,30,27,24,21,23,23,24,25,26,28,30,31,39,39,38,36,34,32,30,29,30,29,29,28,28,27,27,27,27,28,28,29,29,28,28,27,29,31,33,34,35,37,40,43,34,31,26,23,25,31,39,44,52,52,51,48,43,36,30,26,23,24,26,27,28,29,29,29,26,25,23,21,21,21,22,23,26,26,25,24,22,21,20,20,21,20,20,21,23,25,28,29,34,37,42,47,51,53,54,54,54,52,50,47,45,41,36,32,26,25,22,20,18,17,17,17,15,15,15,14,14,14,13,13,12,12,12,11,11,11,10,10,8,8,8,7,7,6,6,6,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 9,10,10,11,12,13,14,14,14,14,14,14,14,14,14,14,13,13,13,13,13,13,13,13,11,11,11,11,11,11,11,11,13,13,13,14,14,15,15,15,17,16,15,15,17,19,22,24,25,26,27,25,23,21,22,23,22,23,25,25,24,24,26,28,28,28,28,25,23,21,22,24,25,26,27,26,25,26,29,31,37,43,53,65,74,81,84,85,82,75,64,52,43,39,39,39,42,50,59,64,67,71,77,82,80,78,73,65,56,46,37,32,29,32,36,41,45,48,50,51,52,53,52,50,46,41,35,32,32,31,34,39,45,56,76,93,108,110,109,97,76,56,42,36,38,43,49,54,55,51,46,42,37,39,43,47,50,52,53,53,50,50,51,55,62,70,77,81,88,89,92,96,100,102,102,101,93,86,76,67,59,53,48,45,43,37,34,34,36,39,47,56,64,76,85,86,84,83,80,74,71,71,69,65,62,63,70,75,88,94,99,97,85,71,60,55,59,68,83,96,103,101,94,89,78,66,54,48,45,46,54,64,80,83,86,82,73,62,53,48,39,41,43,42,39,38,39,41,45,46,45,45,44,43,41,40,46,47,50,53,54,51,46,41,46,50,59,72,84,90,89,86,76,68,58,54,56,57,55,51,47,43,39,39,44,51,57,60,64,60,54,46,41,40,44,47,53,55,55,50,42,37,35,36,38,45,50,49,46,45,41,36,32,31,31,32,34,35,33,31,30,29,26,23,23,27,34,40,45,46,44,39,34,32,34,37,48,58,66,64,59,54,49,45,49,63,78,83,81,70,52,36,31,36,46,58,65,61,50,40,32,35,43,58,76,87,90,89,82,71,60,55,54,55,60,66,71,73,73,69,58,44,33,26,27,32,41,50,54,52,46,40,32,28,24,22,23,26,28,28,31,32,32,32,30,27,24,22,25,25,25,26,27,29,30,31,36,37,38,38,38,36,34,33,32,32,31,31,31,31,32,32,31,30,30,29,28,28,28,28,29,31,34,35,35,36,38,40,33,30,27,25,28,34,42,47,55,55,54,51,45,38,32,28,24,25,26,27,28,29,29,29,27,26,25,24,23,23,23,23,25,24,24,23,22,22,21,21,21,21,22,23,25,28,30,32,40,43,47,51,54,55,55,55,51,49,46,43,41,37,32,28,24,22,20,17,15,15,15,15,15,14,14,14,13,13,13,12,12,11,11,11,10,10,10,9,8,8,8,7,7,6,6,6,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 9,10,10,11,12,12,13,13,13,13,13,13,13,13,13,13,12,12,12,12,12,12,12,12,11,11,11,11,11,11,11,11,13,13,13,14,14,15,15,15,15,15,15,16,18,21,24,25,27,28,29,27,25,24,24,25,24,25,26,26,25,26,28,30,30,31,30,28,25,24,25,26,28,28,29,28,26,26,28,30,37,42,51,61,69,75,79,80,77,71,61,50,42,38,36,36,40,46,53,58,62,66,72,77,76,75,72,65,56,45,35,29,26,29,34,40,46,51,54,56,52,52,50,46,41,35,30,27,29,28,30,35,42,54,75,93,111,115,115,105,85,63,47,40,39,43,48,52,52,48,43,39,36,38,42,48,54,59,63,66,65,63,61,60,60,61,64,65,71,76,83,91,95,96,95,93,93,88,82,75,70,66,61,58,52,45,39,38,39,42,49,57,66,75,84,86,86,87,87,85,85,83,78,69,59,54,55,57,73,82,92,95,89,78,67,62,64,70,78,87,93,94,94,92,84,77,68,59,50,47,52,60,75,81,87,87,79,66,54,46,36,37,38,38,36,37,38,40,46,47,49,50,50,47,44,42,45,44,45,46,47,46,43,40,45,48,55,66,75,77,74,69,61,53,46,43,46,48,46,43,39,36,33,36,44,54,62,67,69,64,56,47,40,38,41,44,52,53,54,50,43,39,39,41,46,54,59,58,53,49,43,36,30,30,30,33,35,37,36,34,34,32,28,24,23,27,34,40,48,48,45,38,31,28,29,32,42,56,70,73,71,65,56,48,46,54,62,64,61,53,41,30,34,41,53,66,72,67,54,44,37,42,54,73,91,101,102,98,88,75,61,53,49,47,51,56,60,63,66,63,54,42,32,27,28,33,42,51,57,55,49,44,32,28,24,22,23,25,26,26,29,30,30,30,29,26,24,22,26,26,26,27,27,28,28,28,31,34,38,41,42,42,41,39,38,37,36,36,36,37,38,39,37,35,32,28,26,26,26,27,29,32,35,36,36,34,34,34,31,30,28,29,33,39,46,51,58,58,56,53,48,41,35,31,26,27,27,28,28,29,29,30,29,29,29,28,27,26,25,24,23,23,23,23,23,23,23,23,23,24,25,27,30,33,35,37,45,47,50,53,54,54,52,51,46,44,40,38,35,31,26,23,21,19,17,14,13,12,12,13,14,13,13,13,12,12,12,11,11,10,10,10,9,9,9,8,8,8,8,7,7,6,6,6,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 9,9,10,10,11,11,12,12,12,12,12,12,12,12,12,12,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,13,13,13,14,14,15,15,15,16,16,16,17,19,21,23,24,27,28,29,28,26,24,25,26,26,27,28,28,27,28,31,34,33,34,33,30,27,26,27,28,28,29,30,29,27,26,27,28,34,38,45,53,60,66,69,70,65,61,54,46,40,36,34,34,38,42,47,52,55,60,66,70,72,72,71,66,57,46,35,29,27,30,34,40,46,52,56,58,53,51,47,42,36,31,27,24,26,25,26,31,37,50,71,90,104,110,113,106,88,68,53,46,42,46,50,53,52,48,42,38,39,41,46,53,61,69,75,79,78,76,71,64,57,53,51,51,57,64,74,82,86,87,86,84,86,85,85,86,85,81,75,71,61,52,44,42,43,45,52,59,66,72,79,82,83,86,89,92,94,92,87,75,62,52,48,48,59,69,82,91,91,84,77,72,70,72,75,77,80,84,88,90,89,87,81,70,58,50,51,56,65,72,81,86,82,70,56,47,39,39,39,38,39,40,43,45,47,49,53,55,55,51,47,44,45,43,41,41,42,43,42,40,41,43,48,57,63,64,59,53,47,42,37,37,40,42,41,39,34,32,31,36,46,59,69,75,73,67,58,47,38,35,37,40,48,50,50,47,43,40,42,44,52,60,65,63,57,51,42,33,30,29,30,33,37,39,39,38,34,32,29,26,25,30,37,43,53,53,49,41,31,25,25,26,36,52,70,79,80,74,62,51,48,51,52,51,47,42,36,31,40,49,64,78,83,76,62,51,45,51,64,83,99,106,103,97,86,73,57,48,42,39,42,47,51,55,59,58,52,42,34,30,29,34,42,50,55,54,49,44,32,29,25,23,23,25,25,25,28,28,28,28,28,26,25,24,25,26,26,26,26,26,25,25,28,32,38,44,47,48,47,46,45,44,41,40,40,41,44,45,43,39,34,28,24,23,24,25,28,32,36,37,36,32,30,29,29,29,30,32,37,43,50,54,59,59,58,55,50,44,37,33,28,28,28,28,28,28,29,29,30,30,31,31,30,28,26,24,21,21,22,23,24,25,26,26,27,28,30,33,35,38,40,42,46,47,49,50,50,48,46,44,41,38,35,32,30,27,23,19,19,17,15,13,11,11,12,12,13,13,12,12,12,11,11,11,10,10,9,9,9,8,8,8,8,8,8,7,7,6,6,6,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 9,9,9,9,10,10,10,10,10,10,10,10,10,10,10,10,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,13,13,13,14,14,15,15,15,18,18,18,18,19,20,21,22,25,27,27,27,25,24,25,26,28,29,29,29,29,32,36,39,37,37,36,33,29,27,27,29,28,30,30,29,27,25,26,27,29,32,37,43,49,54,58,59,56,54,50,45,42,39,38,37,37,39,42,45,49,53,58,62,68,69,69,66,59,49,38,32,28,30,34,39,45,50,55,57,56,52,46,40,33,29,26,24,25,24,25,29,34,45,64,82,98,105,109,103,88,70,57,51,50,52,56,58,57,52,47,43,46,49,54,61,69,78,84,88,86,83,76,66,55,48,46,46,57,64,74,80,82,81,80,79,76,80,88,96,99,96,88,82,67,57,49,47,49,51,55,61,63,66,70,73,74,77,84,91,100,100,96,85,71,57,49,46,51,60,73,83,87,86,81,78,74,74,73,70,69,72,78,83,90,93,92,82,69,59,54,53,55,63,74,82,83,75,63,54,45,43,41,41,42,46,49,50,50,52,55,57,56,53,49,47,43,40,38,37,38,39,39,38,35,36,40,46,52,52,47,42,35,33,31,33,36,39,39,38,35,34,35,41,52,64,74,79,74,68,57,44,35,31,33,36,43,45,46,43,40,39,42,45,53,61,66,63,57,49,39,30,30,30,31,34,38,41,41,40,34,33,31,30,30,35,42,47,59,59,56,47,35,27,23,23,34,51,71,84,87,83,70,58,53,49,45,42,39,35,34,35,48,59,76,90,94,86,72,61,51,57,70,87,102,106,100,92,76,63,49,40,35,32,35,40,43,48,54,55,51,44,38,34,31,34,40,46,50,49,45,40,35,31,27,25,25,26,26,25,27,27,27,27,27,27,26,26,25,26,26,27,26,25,24,23,28,32,39,45,50,51,51,50,50,48,45,42,42,45,48,50,50,45,37,30,24,22,21,22,28,32,36,37,35,30,27,26,27,28,31,35,40,45,50,53,57,58,57,55,50,44,39,35,30,29,28,27,27,27,28,29,30,30,31,31,29,27,25,23,19,20,21,23,26,28,29,30,33,34,36,38,40,42,43,44,44,45,46,46,45,43,40,38,37,34,30,28,26,24,21,18,18,17,15,13,12,12,12,13,13,13,12,12,12,11,11,11,10,10,9,9,9,8,8,8,8,8,8,7,7,6,6,6,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,10,10,10,10,10,10,10,10,11,11,11,11,11,11,11,11,13,13,13,14,14,15,15,15,19,19,19,19,20,20,20,20,24,25,26,26,24,23,24,26,28,29,30,30,32,35,40,44,43,43,41,37,32,29,29,30,28,30,32,31,29,27,27,28,28,29,33,37,41,46,49,51,48,48,46,45,43,41,40,39,38,38,38,40,43,47,52,55,62,63,65,64,59,51,43,38,30,32,35,39,45,50,55,58,59,54,47,39,33,29,27,27,29,27,28,30,33,41,58,73,95,101,104,99,85,70,60,57,59,62,65,66,65,61,56,53,56,59,64,70,77,83,87,90,87,84,76,65,54,47,47,49,61,69,78,82,79,74,70,69,68,75,87,99,105,102,94,87,69,59,52,52,55,56,59,63,61,59,60,61,62,64,74,84,100,103,103,96,82,66,55,49,51,56,64,72,77,79,78,77,75,75,73,68,64,65,71,77,89,96,100,94,83,72,61,52,50,57,67,77,82,79,71,64,51,48,44,43,45,49,52,54,55,55,55,55,54,52,50,48,39,38,37,37,38,38,37,35,32,31,33,37,42,43,39,35,27,27,28,32,36,40,41,40,40,40,42,48,58,67,75,78,71,65,53,41,31,28,30,33,39,41,42,40,37,37,41,45,52,60,65,62,55,47,38,29,31,31,32,36,40,42,42,41,36,37,37,37,38,42,47,51,63,64,63,55,44,33,27,25,36,53,73,86,92,90,79,67,54,47,41,37,34,32,34,39,56,68,86,100,102,94,81,71,58,63,73,88,99,102,95,87,64,52,40,33,30,27,30,34,38,44,50,54,51,46,41,37,31,33,36,41,44,45,42,39,38,35,31,29,29,28,27,26,26,26,27,27,28,28,29,29,28,29,30,31,31,30,28,27,31,34,40,45,50,52,52,52,50,47,44,42,43,47,52,56,56,51,43,34,27,23,21,20,28,31,35,36,33,29,26,24,26,28,32,36,41,45,48,49,53,53,54,52,49,44,39,36,30,29,27,25,25,25,26,27,29,29,28,27,26,24,22,21,18,19,22,25,28,31,33,35,37,38,39,40,41,41,41,41,40,41,42,42,41,38,35,33,31,28,25,23,22,22,20,18,18,17,15,13,12,12,13,13,14,13,13,13,12,12,12,11,11,10,10,10,9,9,9,8,8,8,8,7,7,6,6,6,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,9,9,9,9,9,9,9,9,11,11,11,11,11,11,11,11,13,13,13,14,14,15,15,15,17,17,19,20,21,22,22,22,24,25,26,26,24,24,25,27,28,29,30,31,33,38,44,49,50,50,47,42,36,32,31,32,30,32,34,34,32,31,31,31,29,30,32,35,39,43,46,48,49,49,49,49,48,45,43,42,40,38,36,36,39,43,47,49,56,57,59,60,57,52,46,42,36,37,40,45,51,57,62,65,62,57,48,40,34,31,31,31,34,33,34,35,35,40,53,67,87,92,95,90,80,70,65,65,69,71,74,75,74,71,66,63,65,68,72,77,81,84,85,86,83,81,74,63,53,49,52,57,69,78,88,90,83,72,64,59,60,68,79,91,97,96,89,82,68,59,53,55,59,61,62,64,59,55,52,52,51,52,63,75,90,97,104,103,93,78,66,60,58,57,58,60,63,66,68,69,74,75,74,69,64,64,69,74,88,98,106,105,98,86,69,55,48,52,59,69,76,78,74,70,58,54,48,47,50,54,57,58,59,58,54,52,50,49,49,49,41,41,41,43,44,43,39,36,32,30,29,31,34,35,33,30,27,28,32,37,42,45,47,47,45,46,48,54,62,68,72,73,67,61,49,37,27,25,28,31,38,40,41,39,36,37,41,45,53,60,64,61,55,48,39,31,32,32,33,37,40,43,43,42,43,45,46,47,47,49,52,54,62,65,68,63,54,43,36,33,39,53,70,83,91,92,83,73,56,47,39,36,34,32,36,43,61,74,92,105,107,99,86,77,67,69,74,84,91,91,82,74,55,44,35,30,27,25,27,31,34,40,48,52,51,46,42,39,31,31,32,36,40,43,43,42,41,38,35,33,32,31,29,28,26,26,27,27,28,30,31,32,34,35,37,39,39,38,36,35,35,37,41,45,48,50,51,51,45,42,40,40,43,50,58,62,63,58,50,40,32,26,22,21,28,31,34,34,31,28,25,24,26,28,32,37,40,43,44,44,47,48,49,49,47,43,38,35,30,29,26,24,23,23,24,25,28,27,25,23,21,20,19,19,18,19,22,26,30,34,37,38,39,39,40,40,39,38,36,35,33,34,35,35,34,32,29,27,26,23,20,19,19,19,18,17,17,15,13,12,11,11,12,13,15,14,14,14,13,13,13,12,12,11,11,11,10,10,10,9,8,8,8,7,7,6,6,6,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,9,9,9,9,9,9,9,9,11,11,11,11,11,11,11,11,13,13,13,14,14,15,15,15,14,16,18,20,22,23,24,24,24,26,27,27,25,25,26,28,27,28,30,32,34,40,47,52,55,54,51,46,40,35,33,33,31,34,36,37,35,34,33,34,32,32,33,35,39,42,46,48,58,58,59,59,57,54,51,49,42,39,35,35,37,40,44,45,51,53,55,56,55,52,47,45,42,43,47,52,59,66,72,75,64,58,49,41,35,33,33,34,39,38,38,39,37,40,51,63,76,81,85,82,75,70,69,71,75,77,79,81,80,77,73,70,70,73,76,80,82,83,83,82,79,77,71,61,52,51,57,63,79,90,101,104,94,79,65,58,55,61,70,80,86,85,80,75,67,58,53,57,62,64,64,65,59,52,48,46,44,45,56,70,79,89,101,105,100,88,78,72,63,59,54,52,53,56,59,61,72,74,75,71,66,65,69,74,87,99,109,111,107,96,76,57,46,48,53,61,69,73,72,70,65,59,53,51,54,59,62,62,62,59,54,49,47,47,48,50,44,45,48,50,51,49,44,40,34,30,27,27,30,31,29,27,30,32,37,43,48,52,54,54,49,50,52,57,63,67,69,69,64,58,46,34,25,23,26,30,38,40,41,39,36,37,41,46,54,61,65,62,56,50,42,34,33,33,34,37,41,43,43,42,49,51,53,54,53,53,54,56,60,65,70,68,60,50,43,39,38,51,67,79,87,90,83,74,58,48,40,38,36,34,39,47,64,76,94,107,109,100,88,80,74,73,75,80,83,79,69,60,50,41,33,29,27,24,25,28,32,38,46,51,50,46,42,39,29,29,30,33,38,43,45,45,43,41,37,35,34,33,31,29,27,27,27,28,29,31,32,33,39,41,43,45,46,45,43,42,38,40,42,45,47,49,50,51,39,38,36,38,43,52,61,67,68,63,55,45,36,29,24,22,28,31,33,33,30,27,25,25,26,28,32,37,40,41,41,41,44,45,46,47,45,41,37,35,30,28,25,23,22,22,23,24,27,25,22,20,18,17,17,18,18,20,23,27,32,36,39,41,39,39,39,38,37,34,31,30,25,26,28,29,28,26,24,22,22,19,16,16,17,18,17,17,15,14,12,11,10,10,11,12,15,15,15,14,14,14,13,13,12,12,12,11,11,11,10,10,8,8,8,7,7,6,6,6,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 6,6,6,7,7,8,8,8,8,8,8,8,8,8,8,7,7,8,9,10,11,11,11,10,12,12,12,12,11,11,11,10,13,13,13,13,13,13,13,13,15,17,20,23,25,26,26,26,29,29,28,27,27,27,28,28,27,28,29,30,33,40,47,53,56,56,54,49,42,35,31,29,31,33,37,41,43,43,42,41,38,34,33,38,43,49,57,65,70,73,73,68,64,62,57,50,48,44,39,36,38,42,45,46,52,52,52,51,50,49,47,47,47,48,52,60,69,77,81,82,70,59,46,38,33,32,37,45,46,47,47,43,41,44,52,60,69,75,81,80,75,73,77,83,89,91,94,92,87,80,74,71,77,80,83,83,80,75,72,70,66,67,67,62,58,60,67,74,89,99,108,107,100,86,66,50,53,55,60,65,70,70,68,65,56,56,58,62,67,70,72,72,66,62,54,48,44,45,48,51,63,76,88,94,98,97,87,74,73,62,52,46,39,35,40,50,61,70,80,83,78,73,72,73,83,91,103,113,114,100,80,64,48,44,41,46,57,68,73,74,61,58,54,52,54,59,66,70,71,69,64,55,47,43,44,48,52,57,60,59,60,60,54,47,38,35,29,24,22,24,28,30,35,40,47,53,56,58,60,61,56,55,55,55,56,58,60,61,54,49,40,31,25,25,30,34,39,44,47,45,39,37,42,47,56,59,64,65,62,55,46,40,38,36,37,39,39,37,40,46,51,56,61,61,57,53,51,51,53,61,69,72,73,69,58,47,45,48,56,68,80,84,80,74,62,52,42,38,37,36,40,45,62,71,85,97,101,97,88,81,74,71,68,68,68,65,56,49,40,35,28,23,21,23,28,31,32,38,46,52,53,48,40,35,28,27,26,28,34,40,44,46,44,43,42,39,35,31,28,26,26,28,30,31,31,33,36,38,44,48,52,53,55,56,51,44,44,39,35,36,42,46,46,44,39,37,36,37,44,54,64,71,75,71,62,50,38,29,25,24,28,29,31,32,32,30,28,26,26,27,30,32,34,34,34,33,38,39,41,43,42,40,37,35,28,26,23,21,20,20,21,22,21,20,19,18,18,18,18,19,18,21,26,31,35,38,40,41,40,39,37,34,31,27,23,22,19,19,19,20,21,21,21,22,18,18,16,15,14,13,13,14,12,12,12,13,13,14,14,14,15,15,14,14,14,14,13,13,14,13,12,11,9,8,7,7,8,8,8,7,7,6,6,6,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 6,6,7,7,7,8,8,8,9,8,8,8,8,8,8,8,9,9,11,12,13,13,13,12,14,14,14,14,14,14,14,13,14,14,14,13,13,13,13,13,14,16,18,21,24,25,26,26,29,29,28,28,28,29,29,30,28,29,30,31,34,39,46,52,55,55,54,49,42,35,31,30,31,34,39,44,47,47,46,45,42,37,36,41,47,53,62,71,79,82,82,78,74,71,65,58,51,47,42,40,42,46,49,50,54,53,51,49,47,46,45,44,52,55,60,68,77,84,86,86,72,60,48,40,35,34,39,46,49,50,50,48,46,48,56,63,68,73,77,77,75,77,84,91,103,105,105,101,93,83,76,72,75,78,82,82,78,72,67,65,61,63,63,61,59,62,69,76,94,103,111,110,102,89,71,56,49,49,51,54,57,58,56,54,55,57,60,65,71,76,79,80,82,77,69,59,51,45,44,44,53,64,75,82,88,91,85,76,75,66,55,47,39,33,36,43,54,65,78,84,82,78,75,75,80,87,98,108,110,100,82,68,49,44,39,42,51,61,68,70,63,61,58,56,59,65,71,76,72,70,63,54,45,43,46,50,57,62,67,67,67,67,61,53,43,38,30,24,23,25,30,33,40,45,51,56,58,58,59,60,54,53,51,51,51,52,54,55,49,45,38,30,26,27,33,37,42,47,50,48,43,41,46,51,58,62,66,68,64,57,48,42,38,36,35,37,37,36,40,47,51,56,61,61,56,49,45,44,50,60,70,76,79,75,64,52,44,45,51,62,74,80,78,73,62,52,42,38,37,36,39,44,56,65,78,89,93,90,83,78,70,66,62,62,62,59,52,46,36,34,30,26,25,26,28,30,34,39,47,52,52,47,40,34,28,26,25,28,34,40,44,46,45,44,41,38,35,32,30,29,28,30,31,31,32,34,38,41,49,54,58,59,61,62,57,49,44,39,34,35,39,43,43,41,35,32,31,32,38,49,60,66,73,70,63,53,41,32,27,25,29,30,32,34,34,32,30,29,28,29,30,31,31,31,31,30,33,35,38,40,40,38,35,33,29,28,26,23,22,22,23,24,20,19,18,17,17,17,17,18,18,21,25,29,33,36,37,37,36,35,33,30,27,23,20,19,17,17,17,18,18,19,19,19,17,17,15,14,13,13,13,13,12,12,13,13,13,14,14,14,15,15,14,14,14,13,13,13,13,13,12,11,9,8,7,7,8,8,8,7,7,6,6,6,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 6,7,7,7,8,8,8,8,9,9,9,9,9,9,9,9,11,12,13,15,16,16,16,16,18,18,19,19,20,19,19,19,16,16,15,15,14,13,13,13,12,14,16,19,22,24,25,25,29,29,30,30,31,31,32,32,30,31,32,32,34,38,44,49,54,54,53,49,42,36,32,31,31,35,42,47,51,51,49,47,43,39,38,43,50,58,69,79,87,91,92,87,83,80,73,66,56,53,48,47,49,52,55,56,58,55,51,47,44,42,42,42,54,58,66,75,84,88,88,86,72,61,49,41,37,35,41,48,53,55,56,54,53,54,60,65,66,70,73,74,75,82,94,104,118,118,116,109,98,86,77,72,70,74,78,78,73,66,60,56,54,56,59,59,60,65,73,79,96,103,109,106,99,88,72,59,47,44,42,42,44,45,45,45,54,56,61,67,75,82,87,91,98,94,87,75,61,49,42,39,42,51,60,67,74,81,82,80,78,71,61,51,41,33,32,36,47,59,75,86,88,84,79,77,75,80,89,99,103,97,84,74,53,46,38,36,42,51,59,63,63,61,59,59,63,69,75,79,74,70,61,50,42,41,47,53,62,70,76,77,77,75,68,60,48,42,32,24,22,26,32,37,45,50,55,58,58,57,55,55,51,49,47,45,45,46,47,49,44,41,36,30,28,30,36,41,45,50,54,53,49,47,51,55,61,64,68,69,66,59,50,44,38,35,33,34,33,34,40,47,51,57,62,61,54,44,37,34,42,54,68,78,83,81,68,56,41,40,43,52,64,73,74,73,62,52,43,39,37,35,38,43,49,56,66,76,80,80,76,73,64,60,55,52,51,50,45,41,33,32,31,30,30,30,30,31,38,42,47,51,50,45,38,33,26,25,25,28,34,39,43,45,45,43,39,35,33,32,32,33,32,33,34,34,34,37,41,45,53,59,63,65,67,67,61,52,44,39,34,33,35,38,38,37,32,30,27,28,34,44,55,62,70,68,64,55,45,36,30,28,30,32,34,37,38,37,36,34,33,32,31,29,28,27,27,26,27,30,34,37,38,37,34,32,31,30,29,27,25,25,25,25,19,19,18,17,17,17,17,17,19,21,25,28,31,33,33,33,31,30,28,25,22,19,17,15,15,15,15,15,16,16,16,16,16,15,14,13,12,12,12,12,12,13,13,13,14,14,14,14,15,15,14,14,13,13,13,12,12,12,11,10,9,8,7,7,8,8,8,7,7,6,6,6,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 7,7,7,8,8,8,9,9,10,10,10,10,11,11,11,11,14,15,16,18,19,20,20,20,22,23,24,25,26,26,25,25,20,19,18,17,16,15,14,13,12,13,15,17,20,22,24,24,28,29,30,31,33,33,34,34,31,32,32,33,33,37,42,46,52,53,52,49,43,37,34,33,32,36,42,47,49,48,45,43,38,34,35,42,51,61,74,85,90,94,95,91,87,85,79,72,64,61,56,55,56,59,61,61,61,58,51,45,41,40,40,41,50,55,64,74,82,84,82,79,69,58,47,41,38,38,44,52,59,61,62,61,59,59,61,63,65,67,68,70,75,87,103,115,124,123,119,110,98,84,75,70,65,69,74,74,69,60,52,48,47,50,54,58,62,68,76,82,90,96,98,95,88,79,66,55,46,43,39,37,39,42,45,46,53,56,61,68,76,85,94,100,108,107,102,90,73,58,48,43,41,45,50,55,62,70,76,79,78,75,69,60,49,40,36,36,45,56,73,86,90,88,81,77,70,72,78,86,92,91,85,79,59,50,39,34,36,44,52,57,59,58,57,59,63,68,74,78,75,69,58,45,36,37,45,52,66,75,83,84,82,78,71,63,51,44,33,24,22,26,33,39,47,51,55,56,54,50,48,47,44,43,41,39,39,41,42,44,40,38,35,31,29,31,37,41,46,51,56,56,53,51,53,56,60,63,67,68,65,58,50,45,38,33,30,31,30,32,39,48,52,58,62,60,51,39,31,26,31,46,63,76,83,81,68,55,38,35,35,42,55,66,71,72,63,53,43,39,37,35,36,41,43,48,55,63,67,69,67,66,58,53,47,43,42,42,40,39,33,33,32,32,33,33,34,35,41,44,47,49,47,42,35,31,26,25,25,28,33,38,42,43,42,40,36,33,31,33,35,37,38,39,39,38,38,41,46,50,53,58,63,65,67,66,60,51,44,39,33,31,32,34,34,34,34,31,27,27,32,41,51,58,63,63,62,56,47,39,34,31,32,35,38,41,43,43,43,42,41,38,35,30,27,25,24,23,24,27,31,35,37,36,34,32,33,32,31,30,28,27,26,25,21,20,19,18,18,18,18,19,22,23,26,28,30,31,31,31,28,26,24,21,18,16,15,14,14,14,14,15,15,15,15,15,14,14,12,12,11,11,11,12,13,13,13,14,14,14,15,15,15,15,14,14,13,12,12,11,12,11,11,10,9,8,7,7,8,8,8,7,7,6,6,6,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 7,7,8,8,8,9,9,9,10,10,11,11,12,12,13,13,16,17,19,21,22,23,23,23,25,27,29,31,32,32,31,31,24,24,22,20,18,16,15,14,13,13,14,16,18,20,22,23,27,28,30,32,33,33,33,33,30,31,32,32,33,35,39,43,48,50,50,48,43,39,37,36,35,37,41,44,44,41,37,35,31,28,30,39,50,61,75,86,90,94,94,91,89,88,84,79,73,70,65,62,62,63,64,63,62,58,51,45,40,39,40,41,45,49,58,67,74,76,73,70,64,54,45,41,41,44,52,61,69,70,71,70,67,63,60,59,62,63,64,67,74,88,106,118,127,126,120,108,93,79,68,63,60,64,69,69,64,56,48,44,43,46,52,57,64,71,78,82,82,86,86,80,74,68,59,50,45,41,38,38,41,47,51,53,58,60,63,68,75,86,99,108,119,119,115,103,86,69,59,54,48,48,48,49,51,56,64,71,75,77,77,72,64,55,48,43,48,56,68,81,87,86,80,75,66,65,66,71,77,81,81,79,65,56,44,36,35,40,47,52,56,56,56,58,62,66,71,74,72,65,52,39,31,33,42,51,68,78,87,87,82,76,68,60,50,43,33,25,23,27,34,39,45,47,49,48,45,41,38,37,34,34,33,34,35,36,38,39,38,37,35,31,30,31,36,40,46,50,55,56,54,52,52,52,55,58,61,63,61,55,48,43,37,32,29,29,29,31,39,49,53,57,60,57,47,35,27,23,27,41,59,73,80,78,66,53,35,31,29,36,49,62,69,71,63,53,44,39,37,34,35,38,40,43,48,53,56,58,58,58,50,46,41,37,36,36,37,38,37,36,34,34,35,37,39,41,43,44,46,46,43,38,33,30,26,25,25,28,33,37,39,40,38,36,33,31,32,35,39,42,45,46,46,45,44,46,50,53,52,57,61,63,64,64,57,49,43,39,33,30,30,32,34,35,36,33,29,28,30,37,44,50,54,56,56,53,47,41,37,35,36,38,43,47,50,51,51,51,49,46,41,35,30,26,24,23,24,26,30,33,35,36,35,34,34,34,34,33,31,29,26,25,23,22,21,20,20,20,21,21,24,25,27,29,30,31,30,29,26,24,22,19,17,15,15,15,15,15,15,15,15,15,15,15,13,13,12,11,11,11,11,12,13,13,14,14,14,15,15,15,15,15,14,13,12,11,11,10,11,10,10,9,8,8,7,7,8,8,8,7,7,6,6,6,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 8,8,8,8,9,9,9,10,11,11,12,12,13,14,14,15,18,19,21,23,24,25,26,26,28,30,33,36,37,37,36,35,29,28,26,24,21,19,17,16,15,15,15,16,17,19,20,21,26,27,29,31,31,31,30,29,28,29,31,31,31,34,37,40,44,46,48,47,44,42,40,41,38,39,41,41,39,36,32,29,27,25,28,38,49,59,72,82,88,91,92,89,88,91,90,87,82,78,72,68,66,65,64,62,59,55,49,43,39,38,39,40,43,46,52,60,66,68,67,64,60,52,46,45,49,55,66,76,85,85,85,82,76,69,61,56,58,58,58,62,70,84,100,110,125,122,115,102,86,71,60,54,56,60,64,65,61,54,48,45,43,46,52,58,66,72,78,80,77,79,76,69,63,59,53,47,42,40,39,41,46,52,56,58,64,64,64,64,69,81,97,108,124,125,122,111,93,78,70,67,61,58,54,50,46,45,51,59,70,78,85,85,79,72,61,52,50,53,60,70,78,80,76,71,63,59,55,56,62,70,74,75,69,62,51,41,37,39,44,47,55,55,56,57,60,63,66,68,64,58,46,34,28,32,44,54,72,82,90,87,80,72,63,55,47,42,34,28,26,30,35,39,42,43,43,40,36,33,32,32,27,29,30,32,34,34,34,34,37,36,35,32,30,32,35,38,45,49,54,55,54,51,48,47,48,51,55,57,56,51,45,42,36,32,29,29,30,32,39,48,51,53,54,49,40,31,25,24,29,42,57,68,75,73,62,50,32,28,27,34,48,61,68,70,63,53,44,40,37,33,33,36,38,40,42,45,47,48,49,49,43,40,36,32,31,33,35,37,40,39,38,37,38,41,43,45,43,43,43,42,39,35,31,29,27,26,26,28,32,35,36,36,35,33,32,32,35,40,45,49,52,53,54,53,51,51,53,55,53,57,60,60,61,62,56,49,41,38,34,30,30,32,36,39,38,36,32,29,30,32,36,39,44,46,48,47,44,41,39,38,40,43,48,53,57,59,60,60,58,55,50,44,37,31,27,25,25,27,29,31,33,35,36,36,36,37,38,38,36,32,29,26,24,24,23,22,21,21,22,22,24,26,28,29,30,30,29,28,25,23,21,18,16,15,16,16,16,16,16,16,15,15,15,15,13,12,12,11,11,11,12,13,14,14,14,14,15,15,15,16,15,15,14,13,12,11,10,10,10,9,9,9,8,8,7,7,8,8,8,7,7,6,6,6,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 8,8,8,9,9,9,10,10,11,12,12,13,14,15,16,16,19,20,22,24,25,26,27,27,30,32,36,39,41,41,40,39,34,32,30,27,24,21,19,18,18,17,17,16,17,18,19,20,25,26,28,29,29,28,27,25,25,27,29,29,30,32,36,39,40,43,46,46,45,44,44,44,42,42,41,40,37,34,32,30,30,28,32,41,50,58,67,76,83,85,85,83,85,90,93,92,89,85,78,72,68,65,62,59,53,50,45,41,38,37,37,38,41,42,46,51,57,61,61,60,61,54,50,53,59,69,82,94,103,102,100,96,88,76,64,56,52,52,53,57,65,77,89,98,109,107,101,90,77,64,55,51,53,57,61,62,59,54,50,48,45,48,53,60,67,73,76,78,73,73,69,60,54,52,49,44,41,41,43,47,53,59,61,62,64,62,58,55,57,69,86,100,115,118,116,107,93,82,79,80,79,73,66,60,50,42,45,54,65,79,92,95,92,84,71,59,49,48,49,57,66,72,72,69,62,55,46,44,50,59,66,69,70,65,56,46,40,39,41,43,52,52,52,54,55,57,58,59,55,50,41,32,29,36,50,61,78,88,93,88,78,68,59,52,44,41,37,33,32,34,37,40,41,41,39,35,31,29,30,32,31,33,36,39,39,38,36,34,33,34,34,32,31,33,36,39,45,49,53,55,53,49,45,43,43,46,50,52,52,49,44,41,35,31,29,30,31,33,40,48,47,48,46,40,32,26,24,25,31,41,53,61,66,64,54,43,29,26,27,35,49,61,68,69,63,53,44,40,37,33,32,35,37,38,39,40,40,40,39,39,35,33,31,29,28,30,34,37,41,42,43,44,44,45,45,45,42,42,40,38,35,32,30,28,29,28,27,29,31,33,33,32,33,33,34,36,41,47,52,56,58,59,61,60,58,56,55,56,52,55,56,55,56,57,54,47,40,37,34,31,31,34,39,43,44,42,38,35,32,31,32,32,35,37,40,41,40,39,40,41,43,46,52,58,63,66,67,68,66,63,58,52,45,38,32,29,27,27,27,27,29,32,35,37,40,41,43,43,41,37,32,29,24,23,22,21,21,21,21,22,23,24,26,28,29,28,28,27,24,22,19,17,15,15,16,16,16,16,16,15,15,14,14,14,13,13,12,12,12,12,13,14,14,14,14,15,15,15,16,16,15,15,14,13,11,10,9,9,9,9,9,8,8,8,7,7,8,8,8,7,7,6,6,6,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 8,8,8,9,9,10,10,10,12,12,13,14,15,16,16,17,19,20,22,24,26,27,28,28,30,33,37,41,43,43,41,40,36,35,32,29,26,23,20,19,20,19,18,17,16,17,18,19,24,25,27,28,28,26,24,23,23,25,27,28,29,31,35,38,38,41,44,46,45,45,46,46,45,44,42,40,38,35,34,33,34,33,36,44,52,57,64,71,77,80,79,77,80,88,93,93,93,88,81,74,69,64,60,57,48,45,42,38,36,36,36,36,39,39,41,45,50,55,57,57,62,56,54,59,67,79,94,106,115,114,111,105,95,81,67,57,47,47,49,53,60,71,81,88,90,89,86,79,69,60,54,51,51,55,59,60,58,54,52,50,47,50,54,61,68,73,75,76,69,69,63,54,48,48,46,42,43,44,47,53,59,64,65,65,60,57,51,44,45,56,76,90,101,104,105,99,89,83,84,88,92,85,78,69,56,45,46,55,62,79,96,101,99,91,76,61,47,43,41,47,58,67,69,68,62,53,42,38,43,52,61,65,70,65,58,49,42,39,39,41,48,48,48,49,49,50,51,51,49,45,38,31,31,40,56,68,83,92,96,89,77,67,58,51,43,41,39,37,37,38,39,40,42,41,38,33,29,29,31,33,38,41,45,48,47,44,40,37,31,32,32,32,32,34,38,41,46,49,53,55,53,49,44,40,40,43,47,50,50,48,44,41,35,31,30,31,32,33,40,48,44,43,40,34,26,22,24,26,31,39,49,54,57,56,46,36,28,26,28,37,51,63,68,68,63,54,45,40,37,32,32,34,36,36,37,37,36,35,34,33,30,29,28,27,26,29,33,36,41,43,46,49,49,48,45,43,41,40,39,36,33,31,29,28,30,28,28,29,31,32,31,30,33,33,35,39,45,52,57,61,61,63,65,65,62,58,56,56,50,52,52,50,51,53,50,45,39,37,34,31,32,36,42,47,50,48,45,41,37,33,31,30,30,32,35,37,37,38,40,42,45,48,54,61,66,69,71,72,70,68,64,58,50,42,35,31,28,27,25,25,27,30,34,37,43,45,46,47,44,40,35,32,23,22,21,20,20,20,21,21,21,22,24,26,27,27,26,26,23,21,18,15,14,14,15,16,15,15,15,14,14,13,13,13,14,13,13,12,12,13,14,14,14,14,14,15,15,16,16,16,15,15,14,13,11,10,9,8,9,9,8,8,8,8,7,7,8,8,8,7,7,6,6,6,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 9,9,9,10,10,11,11,11,13,13,14,15,16,17,17,18,18,19,21,22,24,26,28,28,31,33,36,39,41,41,41,40,39,37,35,32,29,26,23,22,23,23,23,23,23,23,23,23,26,27,29,29,29,27,24,23,19,20,21,23,26,28,31,32,37,39,42,43,44,45,47,50,49,48,46,44,41,40,39,39,44,45,48,51,56,60,64,67,66,67,69,71,74,81,89,95,88,86,82,76,68,62,56,53,47,45,42,39,37,35,35,34,38,40,43,47,53,59,63,66,68,69,70,70,74,84,98,108,122,130,130,118,108,99,81,62,53,50,48,51,59,67,72,74,76,73,72,72,70,65,59,56,51,55,58,59,59,61,62,61,61,63,64,64,68,74,74,70,69,66,62,59,57,54,52,49,51,50,51,55,62,66,67,66,64,51,39,37,39,47,62,77,90,91,86,77,71,75,87,97,102,103,99,84,67,57,58,64,76,90,99,99,98,96,82,63,50,42,35,37,48,60,67,68,63,56,45,37,35,41,50,57,63,64,62,54,45,39,40,43,44,46,47,46,44,43,44,45,46,46,44,43,46,56,71,82,96,102,102,92,78,66,54,45,43,41,41,42,45,46,45,44,43,40,35,32,31,34,37,40,46,54,59,59,56,52,42,33,31,25,24,30,36,40,45,49,53,57,58,56,53,48,39,29,32,34,39,44,48,48,44,40,35,31,28,29,33,37,38,37,42,39,33,29,26,26,28,29,32,36,41,45,46,43,39,36,27,29,34,41,50,59,67,71,62,57,48,38,31,30,33,37,37,38,38,38,37,35,33,31,31,29,26,25,25,27,30,32,41,42,46,51,53,52,48,44,41,37,33,30,30,31,32,32,31,31,31,30,30,30,29,29,32,36,42,45,48,52,59,65,69,67,66,65,63,60,56,53,50,48,47,47,48,47,45,44,39,37,34,33,35,40,46,49,56,57,57,52,44,36,30,28,27,30,34,38,41,43,42,42,48,50,55,60,65,70,73,75,74,71,66,58,49,40,33,29,28,26,23,21,23,27,32,36,43,45,48,49,47,42,36,31,26,25,22,20,19,19,20,21,22,22,23,24,25,26,26,27,20,19,18,16,14,14,13,13,14,14,14,14,14,14,14,14,12,13,15,17,18,19,19,19,18,18,17,16,15,15,15,15,14,13,12,11,9,8,7,6,8,8,8,8,8,8,8,8,7,7,7,7,7,7,7,7,8,7,6,5,5,5,5,6,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 9,9,9,10,10,10,11,11,12,12,13,14,15,16,16,17,17,18,19,21,23,24,26,26,28,30,33,36,38,38,37,37,36,35,33,30,28,25,24,23,23,23,24,24,25,25,26,26,27,28,29,30,29,27,25,23,20,20,20,21,23,25,28,29,35,37,40,41,42,43,46,49,51,51,50,48,47,46,46,45,49,49,50,52,54,57,60,62,58,59,61,63,66,72,80,86,86,84,80,74,68,61,56,53,49,47,44,41,38,36,35,35,34,36,41,49,58,67,75,79,82,81,80,78,79,87,99,109,125,133,135,126,116,108,91,73,62,59,55,56,58,61,62,61,71,71,72,75,75,71,66,62,55,57,59,60,62,66,69,70,68,70,70,69,71,75,74,69,68,65,62,60,59,59,58,56,57,55,54,57,62,66,68,67,64,51,40,36,38,45,60,74,75,76,72,65,62,69,84,96,107,110,108,98,84,76,77,81,91,103,109,107,103,98,82,64,49,41,34,36,47,59,66,69,66,59,48,38,36,39,46,51,59,60,59,53,45,40,40,43,43,45,46,45,43,42,43,44,49,50,50,51,55,65,79,90,101,107,107,97,84,72,59,50,46,45,45,46,49,50,50,49,45,41,37,33,33,36,41,45,55,63,68,67,63,57,46,36,31,26,26,33,41,47,52,58,63,66,66,61,56,50,40,30,32,34,39,45,49,49,45,41,34,29,26,27,32,36,38,38,38,35,30,26,24,25,27,29,31,33,36,38,37,35,32,30,28,30,34,40,48,57,64,69,62,57,49,39,31,29,31,34,36,37,38,38,37,35,33,32,31,30,27,25,26,27,30,32,40,42,46,51,53,52,47,42,38,35,30,28,29,31,32,32,31,31,30,29,28,28,29,29,33,37,42,45,47,51,58,64,69,69,69,68,65,61,56,52,46,45,44,46,48,49,48,47,44,42,40,39,41,46,51,55,62,63,63,59,51,42,35,32,29,31,33,36,39,40,40,40,46,49,53,59,64,67,69,70,70,67,62,56,48,40,34,30,27,25,23,22,24,28,32,36,42,44,47,47,45,39,33,29,23,22,19,17,17,17,19,20,20,20,21,22,23,23,24,24,19,18,17,15,14,13,13,13,13,13,13,14,14,15,15,15,16,17,18,19,20,20,20,20,19,18,17,16,15,14,14,14,13,13,12,11,9,8,7,7,8,8,8,8,8,8,8,8,7,7,7,7,7,7,7,7,8,7,6,5,5,5,5,6,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 9,9,9,9,10,10,10,11,11,11,12,12,13,14,14,15,15,16,17,18,20,21,22,23,23,25,28,30,32,32,32,31,31,30,29,28,26,25,24,23,24,25,25,26,28,29,29,30,29,30,31,31,30,29,26,25,23,22,20,20,20,22,25,26,32,34,36,37,38,41,44,47,53,53,54,55,55,55,55,55,54,53,52,51,51,51,53,53,49,50,52,54,57,63,70,75,82,80,76,71,66,62,58,56,53,52,49,46,42,39,37,36,33,36,42,52,64,77,88,95,98,96,91,85,82,86,96,105,122,131,136,130,123,115,101,86,77,75,72,70,68,66,62,59,66,70,76,82,86,86,80,75,65,63,61,62,65,71,76,81,79,81,80,78,78,78,74,68,67,64,62,61,63,66,67,67,66,62,59,59,61,65,68,70,65,55,46,43,44,50,61,72,66,64,59,53,52,62,79,93,110,115,118,114,106,102,105,110,116,124,126,119,111,100,82,63,50,43,35,37,47,58,66,69,70,63,52,42,37,37,40,43,52,55,55,52,46,41,41,42,42,44,45,45,43,41,41,42,49,51,55,58,63,73,86,96,105,109,109,100,88,77,64,54,49,49,49,51,54,56,55,54,47,43,38,34,35,40,47,52,64,71,76,74,69,61,48,37,30,27,29,38,49,57,66,73,79,82,80,71,62,52,41,31,31,34,40,47,51,51,46,42,31,27,23,24,29,35,38,38,35,31,26,22,21,23,26,28,30,30,30,29,28,27,26,26,30,31,34,39,45,53,60,63,61,57,49,39,31,28,28,30,35,36,38,38,38,36,33,32,31,30,28,26,26,27,29,31,38,41,46,51,53,50,44,39,34,31,27,25,27,30,31,32,32,30,28,26,26,27,29,30,33,37,40,42,44,48,55,61,68,70,71,71,67,61,55,51,45,45,45,47,50,52,51,50,50,48,45,44,46,51,56,60,66,68,68,64,56,46,39,35,31,32,33,34,35,36,36,37,42,45,49,55,59,61,62,62,61,59,56,51,45,39,34,31,27,26,24,23,25,28,32,35,40,42,43,43,39,34,28,25,18,17,16,15,15,15,17,18,18,18,19,20,20,21,21,22,18,17,16,14,13,13,12,13,12,13,14,15,16,17,18,18,22,22,23,23,23,23,22,22,20,19,17,16,14,13,13,13,13,12,12,11,9,8,8,7,8,8,8,8,8,8,8,8,7,7,7,7,7,7,7,7,8,7,6,5,5,5,5,6,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 8,8,9,9,9,10,10,10,10,10,11,11,12,12,12,13,13,14,15,16,17,18,18,19,19,20,22,24,25,26,26,25,25,25,25,25,24,24,24,24,24,25,26,28,30,31,32,33,32,33,33,33,33,32,30,29,28,26,23,21,21,22,24,25,28,30,32,33,35,37,42,45,52,54,56,59,61,61,61,61,56,54,51,48,46,45,45,45,44,46,47,49,51,56,63,67,73,72,69,67,64,62,61,60,61,60,58,54,50,45,41,38,36,39,45,55,69,85,99,107,111,107,99,88,81,81,88,94,110,120,128,127,123,116,105,95,88,88,86,84,80,74,68,64,65,75,86,97,104,107,102,94,79,72,66,65,67,72,79,86,88,90,90,87,85,83,76,68,66,63,61,62,66,71,75,77,73,69,64,60,60,64,68,71,69,65,62,62,63,67,72,76,71,64,55,49,49,57,74,90,109,115,121,123,123,126,133,141,145,148,144,132,118,102,81,64,53,46,39,39,47,58,66,69,71,65,55,46,39,36,36,37,46,49,51,49,46,42,41,42,44,46,47,47,45,42,42,42,44,48,54,59,64,74,85,94,101,105,105,98,88,78,65,55,50,50,51,54,57,58,57,56,47,43,38,35,37,43,52,57,67,74,79,76,70,60,46,35,30,28,32,43,56,68,81,91,99,101,96,84,69,55,41,30,29,33,41,48,53,52,47,42,29,24,21,22,28,35,38,39,35,31,25,20,18,20,23,25,31,29,27,25,25,25,27,28,32,32,33,36,41,47,53,56,58,54,48,39,31,27,26,27,33,34,37,38,38,36,34,32,30,29,27,26,26,27,29,30,37,40,45,50,52,48,42,36,29,26,23,22,25,28,30,31,32,30,27,25,24,26,28,30,32,35,37,37,38,42,50,56,63,67,71,71,67,60,53,49,50,50,52,55,58,58,57,55,55,52,49,47,48,52,56,60,65,67,68,65,57,47,39,35,34,33,33,32,32,32,33,33,36,39,43,48,51,52,52,51,51,50,48,45,42,38,35,33,29,28,27,26,27,29,32,33,35,36,36,35,32,28,23,20,15,15,14,14,14,15,16,17,18,18,19,19,20,20,21,21,19,18,17,16,15,14,14,14,14,15,16,18,19,21,22,23,27,27,27,27,26,25,24,23,21,20,18,15,13,12,12,11,12,12,11,10,10,9,8,8,8,8,8,8,8,8,8,8,7,7,7,7,7,7,7,7,8,7,6,5,5,5,5,6,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 8,8,8,9,9,9,10,10,10,10,10,10,11,11,11,11,12,12,13,13,14,14,15,15,15,16,17,18,19,20,20,21,20,20,21,21,22,23,23,23,23,24,25,27,29,31,32,33,34,34,35,35,35,35,35,34,34,32,29,26,25,25,25,26,27,28,29,30,31,34,38,42,48,51,55,59,62,62,61,60,54,51,47,43,41,40,41,42,43,44,46,46,48,51,56,60,63,63,62,61,61,62,63,64,68,68,67,64,59,53,48,45,39,41,47,57,73,91,108,117,118,114,104,91,80,76,79,84,95,105,116,119,118,114,108,102,96,96,94,90,83,76,70,67,72,86,103,116,127,132,126,115,97,84,71,68,68,70,76,84,92,95,96,93,91,87,79,69,66,63,60,62,67,74,79,82,78,73,67,61,58,61,66,70,73,77,82,86,89,91,90,88,79,68,56,50,49,55,72,89,106,112,121,128,134,144,156,165,170,166,157,141,123,104,83,69,58,52,45,44,49,57,63,66,68,64,57,50,44,40,37,36,43,44,46,46,45,43,42,42,47,49,51,51,48,45,44,44,41,46,51,56,60,68,78,85,93,97,97,92,85,77,66,55,49,49,50,53,56,57,55,53,45,41,36,34,36,43,52,58,66,73,77,74,68,59,45,34,30,29,34,46,60,76,93,107,117,119,114,98,78,59,42,30,28,33,41,51,56,54,48,43,29,25,22,24,30,37,40,41,38,34,26,20,17,18,20,23,29,28,26,24,25,27,30,32,34,33,32,32,35,39,44,47,52,51,46,39,32,27,25,25,31,33,36,38,38,37,34,32,28,27,27,26,27,28,29,30,38,40,44,48,49,46,39,34,26,23,20,20,23,27,29,30,32,30,27,25,24,26,28,30,30,32,32,31,30,35,43,49,57,62,68,70,66,59,53,51,55,58,62,68,72,73,70,67,62,58,54,50,49,51,55,57,61,63,65,62,55,47,41,37,36,35,34,32,31,31,31,31,30,32,36,39,41,41,41,40,41,41,41,41,41,39,38,38,34,33,32,30,29,29,30,30,28,28,28,28,26,23,20,18,16,16,16,15,16,16,17,17,20,20,20,20,20,21,21,21,21,20,19,18,17,17,17,17,17,18,19,21,23,25,26,27,29,29,29,29,27,26,24,23,20,19,17,15,13,12,11,11,12,12,11,10,10,9,8,8,8,8,8,8,8,8,8,8,7,7,7,7,7,7,7,7,8,7,6,5,5,5,5,6,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 7,8,8,8,9,9,9,9,10,10,10,10,10,10,11,11,12,12,12,12,12,12,12,12,13,13,14,14,15,16,17,17,16,16,17,18,19,21,21,22,21,22,23,25,27,28,30,30,32,33,33,34,35,36,37,38,37,36,34,32,30,29,28,27,27,27,28,28,28,31,35,39,44,48,53,57,60,59,58,56,48,46,43,40,39,40,42,44,45,46,47,47,47,48,52,55,57,56,56,56,57,59,61,63,69,70,71,70,68,63,59,56,44,45,49,58,73,92,110,121,122,118,109,95,82,74,74,76,83,93,105,112,113,112,111,111,109,107,103,96,86,78,73,70,82,101,122,137,150,155,147,134,114,95,78,72,69,67,72,80,89,94,97,97,95,92,82,72,66,63,59,60,65,72,79,82,78,74,67,60,56,57,62,67,75,85,96,103,109,111,107,102,86,72,59,53,51,54,69,86,102,109,120,130,141,153,166,175,176,169,155,137,119,100,83,73,61,56,51,48,50,53,57,58,61,60,57,54,50,46,43,41,42,42,43,44,44,44,43,43,49,52,54,54,51,48,46,46,41,45,49,51,53,58,66,72,80,85,86,84,81,76,65,55,46,47,48,51,53,53,51,48,40,37,33,31,34,41,49,54,63,70,73,70,65,58,47,37,32,30,34,45,61,79,101,119,134,137,131,113,88,65,44,30,29,35,44,55,60,59,52,46,33,30,28,31,37,43,45,44,42,37,29,22,18,19,22,24,29,28,28,28,29,30,32,33,35,33,30,28,29,32,36,39,46,45,44,39,33,28,26,25,29,31,35,38,39,37,34,32,27,27,28,28,29,31,33,33,39,40,42,45,46,43,38,33,25,22,19,19,22,26,28,29,32,30,28,26,26,27,29,30,29,30,28,26,24,29,37,44,53,60,67,70,67,62,58,57,63,68,77,86,92,92,88,83,69,65,59,53,49,49,51,53,55,57,58,56,51,46,42,40,38,37,36,35,33,32,31,30,28,29,30,31,32,32,32,32,36,37,39,41,43,44,45,45,41,40,38,35,32,29,27,26,22,22,22,22,22,21,20,20,20,20,20,20,20,20,20,19,21,21,21,21,21,21,21,21,21,21,20,19,18,18,19,19,19,20,21,23,25,26,28,28,29,29,28,28,26,25,23,22,19,18,16,14,13,12,12,11,11,11,11,10,10,9,9,9,8,8,8,8,8,8,8,8,7,7,7,7,7,7,7,7,8,7,6,5,5,5,5,6,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 7,7,8,8,8,9,9,9,11,11,11,11,11,11,11,11,12,11,11,11,11,11,11,11,12,12,12,12,13,14,15,16,14,14,15,16,17,19,20,20,19,20,21,22,23,25,26,26,28,29,30,31,33,36,38,39,39,38,38,37,35,32,29,28,28,28,28,26,26,29,33,37,42,45,51,55,57,56,53,50,43,41,39,38,40,44,48,51,52,53,53,52,50,51,53,55,55,54,53,52,53,55,57,58,63,66,70,73,74,72,69,67,56,54,54,59,70,86,102,112,120,117,109,96,81,72,69,69,73,82,95,104,108,109,113,117,117,114,108,97,86,78,76,76,92,114,138,154,167,173,163,147,126,104,84,76,72,67,70,78,84,90,96,98,98,95,86,76,67,63,58,57,62,69,75,79,75,72,66,58,53,53,58,63,73,85,99,108,115,121,119,112,99,82,65,58,53,51,63,78,94,103,117,130,142,152,161,166,163,153,137,121,104,89,77,71,62,59,54,50,49,49,49,49,53,54,56,56,55,53,50,48,43,42,41,42,43,44,44,44,50,53,56,56,53,49,47,46,41,43,45,44,43,46,52,58,65,70,73,73,73,71,61,51,45,45,47,49,51,50,46,43,34,32,29,28,31,37,44,48,58,63,66,64,60,56,47,39,33,31,33,43,59,80,106,126,147,151,147,127,99,72,48,33,32,38,49,60,66,64,57,51,40,38,38,41,47,51,51,49,44,39,31,24,21,22,26,29,34,35,36,36,37,36,36,35,35,32,28,24,24,26,29,32,39,40,41,38,34,29,27,27,27,30,35,38,39,37,34,32,28,29,30,32,34,36,38,39,40,40,41,42,43,41,37,33,25,22,19,18,21,25,27,28,31,31,30,29,28,28,29,29,30,29,27,23,21,25,34,41,53,61,70,73,71,68,67,68,79,85,95,105,109,106,98,91,73,68,60,52,46,44,44,44,45,47,48,47,43,41,40,40,39,39,39,38,37,34,32,30,28,28,27,26,26,27,28,29,35,37,40,44,48,51,53,54,48,46,44,40,34,29,24,22,18,18,19,20,21,23,24,24,26,26,26,25,25,24,23,22,21,21,21,21,21,21,21,21,21,20,19,18,18,18,19,19,20,20,21,22,24,25,26,27,26,26,26,26,24,23,21,21,17,17,15,14,13,12,12,12,11,11,10,10,10,10,9,9,8,8,8,8,8,8,8,8,7,7,7,7,7,7,7,7,8,7,6,5,5,5,5,6,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 7,7,7,8,8,9,9,9,11,11,11,11,11,11,11,11,12,12,11,11,11,10,10,10,12,12,12,12,12,13,15,15,13,13,14,15,16,18,18,19,18,18,19,20,21,22,23,24,25,25,27,29,31,34,37,39,38,39,40,39,37,34,30,28,29,29,28,26,25,27,32,35,41,44,50,54,56,54,50,47,39,38,37,38,42,47,53,57,59,60,60,58,56,55,57,58,56,54,52,50,50,51,53,54,57,61,68,74,77,78,76,75,68,65,61,60,67,79,92,101,116,114,107,94,79,69,64,64,67,75,88,98,103,106,112,119,112,109,102,91,80,75,74,76,98,121,146,163,176,182,170,153,133,109,88,79,74,68,70,78,80,87,94,97,99,97,88,78,68,63,57,56,59,66,73,76,73,71,65,57,51,51,56,61,70,83,96,105,115,123,123,118,112,93,74,64,55,49,57,71,87,98,114,129,140,146,151,154,146,135,119,103,90,77,69,66,62,60,55,51,48,45,44,43,48,51,54,58,59,57,55,53,44,42,40,40,42,44,45,45,50,53,56,56,53,49,47,46,40,41,40,38,35,36,41,46,53,58,61,63,65,65,56,46,44,45,46,48,49,48,44,40,30,28,26,26,29,34,40,44,52,57,60,58,55,52,46,38,34,31,33,42,57,79,107,129,154,159,156,135,106,77,51,35,34,41,53,64,70,68,61,54,45,44,44,48,54,57,55,53,45,39,32,25,23,25,30,33,41,42,44,45,44,42,39,38,35,32,27,22,21,22,25,28,35,37,39,38,34,31,28,28,26,29,34,38,39,38,34,32,30,31,33,35,38,40,42,43,41,40,40,40,41,39,36,33,25,22,19,18,21,24,27,27,31,31,31,30,30,30,29,29,31,30,27,22,20,24,33,41,55,63,72,76,75,73,74,76,93,99,109,117,119,112,100,91,72,67,58,48,41,37,36,37,37,38,39,38,36,35,36,37,39,40,41,41,39,36,33,31,30,28,26,24,24,25,27,28,36,38,42,47,52,56,58,60,52,51,47,42,36,29,23,19,17,17,18,20,22,25,27,28,30,30,30,29,28,27,25,24,20,20,20,20,20,20,20,20,20,19,18,17,17,17,18,18,19,19,20,21,23,24,25,25,24,24,24,24,23,22,20,20,16,16,14,13,13,13,13,13,11,11,10,10,10,10,9,9,8,8,8,8,8,8,8,8,7,7,7,7,7,7,7,7,8,7,6,5,5,5,5,6,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 8,8,7,8,9,10,11,12,13,12,12,11,11,11,12,12,14,14,14,14,14,14,14,14,13,13,13,14,14,14,14,14,14,15,16,17,18,20,21,21,21,20,19,18,18,19,21,22,26,25,26,26,28,31,34,36,37,38,40,40,38,34,30,28,26,25,25,25,26,29,33,35,43,47,51,53,51,48,45,44,41,41,44,49,56,62,65,66,67,65,64,62,61,61,62,63,59,61,58,53,50,50,47,43,49,49,56,69,78,81,82,85,79,76,71,67,69,77,88,97,102,100,95,88,80,72,66,62,75,81,92,103,111,116,117,117,116,107,95,85,76,70,73,80,103,125,153,171,179,175,162,150,123,109,95,84,76,69,68,71,74,80,89,96,99,96,90,86,78,71,62,58,59,63,66,68,65,65,63,57,51,48,50,53,64,70,80,92,104,113,119,122,111,99,81,65,56,57,63,68,83,99,118,130,137,139,134,128,116,103,89,81,73,64,61,65,59,59,57,53,48,44,41,40,42,50,59,64,67,68,63,57,44,39,35,37,46,53,56,55,60,53,49,49,49,47,48,52,50,50,46,38,35,38,40,39,44,46,49,52,53,51,49,47,47,45,43,44,45,44,40,36,27,26,24,24,28,33,40,44,49,51,53,55,55,52,49,47,39,33,30,35,48,72,103,128,151,162,163,143,110,78,54,41,37,44,56,67,74,74,68,63,53,51,51,55,62,64,61,57,47,43,36,29,24,26,31,35,45,49,54,56,53,48,43,41,36,32,27,22,20,20,23,25,29,31,33,34,34,31,28,25,29,31,33,35,36,37,36,36,33,35,40,44,47,47,47,46,46,44,41,39,38,36,33,30,28,25,22,19,19,21,24,26,29,32,35,35,32,29,28,27,28,25,24,24,22,22,30,40,51,61,74,81,82,84,90,96,100,113,126,129,126,119,103,88,74,64,50,41,37,34,30,26,31,30,29,29,29,30,32,33,36,41,44,42,42,42,38,32,31,29,24,21,20,22,24,26,30,35,43,51,56,59,58,58,50,48,45,40,34,28,23,21,15,17,21,25,29,33,35,36,38,37,35,32,30,27,25,24,24,23,21,19,17,16,16,16,17,17,16,16,16,16,16,16,15,16,17,19,21,22,22,22,21,21,20,19,18,18,19,19,17,16,15,14,13,12,12,12,13,13,12,11,10,10,9,8,10,10,9,9,9,8,8,8,6,6,6,6,6,6,6,6,7,7,7,6,6,5,5,5,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 8,8,8,8,9,10,11,12,14,13,13,12,12,12,13,14,16,16,16,16,16,16,16,16,15,15,15,15,15,16,16,16,16,17,17,18,19,20,21,22,22,21,20,19,19,20,21,22,24,24,25,26,27,29,31,32,34,35,36,36,35,31,28,25,25,24,24,26,28,32,36,38,44,48,51,53,51,49,48,47,46,47,50,56,63,68,70,70,69,67,64,62,61,62,64,66,66,68,67,61,57,55,50,44,45,45,50,62,72,77,81,86,85,83,79,76,76,82,90,96,100,97,92,85,78,72,67,65,76,83,95,107,116,120,121,120,115,106,94,84,76,71,75,83,104,123,147,161,165,160,147,135,114,102,90,81,74,68,67,69,74,79,87,95,98,96,93,90,82,75,68,64,64,66,68,68,69,68,65,61,56,54,54,55,59,63,70,79,90,100,109,113,112,103,87,70,58,55,59,64,79,95,114,127,132,131,124,116,103,90,77,70,63,56,55,59,59,59,58,55,51,47,44,43,47,55,64,70,75,77,70,61,46,40,35,38,47,55,59,60,62,54,47,46,46,47,52,58,60,62,59,51,46,46,45,41,39,40,42,43,44,45,44,44,47,45,44,45,46,44,39,35,27,26,25,26,30,35,41,45,48,50,52,55,56,56,55,54,43,36,31,34,45,67,97,121,148,158,160,140,107,76,52,39,41,49,61,73,79,78,73,68,59,57,56,59,63,64,60,55,46,42,36,29,26,27,33,38,46,51,56,58,56,50,45,43,36,33,28,23,21,22,24,25,28,30,33,35,35,34,31,30,30,31,32,33,34,35,36,36,36,39,45,49,52,52,50,49,46,43,39,37,36,34,31,29,27,24,21,19,20,22,25,27,31,33,36,35,32,29,27,27,27,24,23,24,23,23,31,40,55,65,78,86,88,90,96,101,106,117,126,127,123,114,99,85,65,55,43,35,31,30,26,23,26,25,24,23,23,25,27,28,35,41,45,45,45,45,41,35,33,31,26,23,22,23,25,26,31,35,42,49,53,55,55,54,49,47,43,38,32,27,23,21,18,20,24,29,34,38,40,41,39,38,36,33,31,28,26,25,23,22,20,18,16,14,14,13,14,14,14,14,14,14,14,14,13,14,15,17,18,19,19,20,19,18,18,17,17,17,18,18,17,16,15,14,13,12,12,12,13,13,12,12,11,10,9,9,10,10,10,9,9,9,8,8,6,6,6,6,6,6,6,6,7,7,7,6,6,5,5,5,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 8,8,8,8,9,10,12,12,15,15,14,14,14,15,15,16,19,19,19,19,19,19,19,19,18,18,18,18,18,18,18,18,19,20,20,20,21,22,22,22,25,24,23,22,21,21,21,21,23,24,25,26,27,27,27,27,30,31,32,32,30,27,24,22,22,22,24,26,30,35,39,42,46,49,52,53,52,51,51,52,54,55,60,66,71,74,73,71,68,65,62,59,60,63,67,70,72,76,77,73,68,63,55,47,43,40,42,52,62,70,79,86,89,89,88,86,85,87,91,94,97,93,88,81,75,71,68,66,75,84,99,113,123,127,127,125,116,106,94,85,77,74,80,88,108,123,139,147,146,139,126,114,102,92,83,78,74,69,69,71,75,79,86,92,97,98,97,96,89,85,80,76,74,74,73,72,75,73,70,68,68,67,66,65,62,61,62,66,74,85,95,102,107,102,92,76,61,55,57,62,79,96,117,129,134,131,121,112,94,83,71,64,58,54,53,56,59,60,60,60,58,56,53,52,57,63,71,79,86,87,76,63,47,41,36,38,49,60,67,69,66,56,45,41,42,47,58,69,75,78,78,70,61,55,49,42,36,35,35,35,36,39,42,44,48,48,47,48,46,43,37,33,27,27,27,29,33,38,43,46,48,49,52,55,58,61,63,64,50,42,34,33,41,59,87,109,137,147,149,131,102,74,52,40,45,53,66,77,82,80,75,71,65,63,61,63,64,63,57,53,45,42,37,30,27,29,34,39,46,52,58,62,59,54,49,46,37,35,30,27,25,25,26,27,27,30,33,37,38,38,36,34,30,30,30,30,31,33,35,37,40,44,50,56,58,57,54,52,45,41,37,34,33,31,30,28,25,24,21,20,21,23,27,29,33,35,37,36,32,28,26,25,24,23,23,24,24,24,31,41,57,67,81,90,93,96,100,104,108,115,120,119,112,101,87,75,55,47,37,30,28,27,25,24,23,22,20,19,19,21,24,25,35,42,48,49,50,50,45,39,36,33,29,26,24,24,25,26,32,35,40,44,47,48,47,46,45,43,39,35,30,26,24,23,23,25,29,34,38,42,45,46,40,38,36,34,31,28,26,25,22,21,18,16,14,12,11,11,11,11,11,11,11,12,12,12,11,12,12,13,14,15,16,16,16,15,15,14,14,15,16,16,16,16,14,13,12,12,12,13,13,13,12,12,11,10,10,10,11,11,10,10,10,9,9,9,7,7,7,7,7,7,7,7,7,7,7,6,6,5,5,5,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 9,8,8,9,9,11,12,13,17,16,16,16,16,17,17,18,21,21,21,21,21,21,21,21,21,21,21,21,21,20,20,20,22,22,22,22,23,23,23,23,27,26,25,24,23,22,22,22,23,25,26,28,28,27,26,25,26,27,28,27,26,24,21,19,19,20,23,27,32,38,42,45,48,49,51,52,51,52,53,55,61,63,67,72,75,74,69,65,60,57,54,52,55,61,67,72,74,81,85,83,79,73,63,54,46,40,38,44,54,63,73,82,87,90,92,93,92,92,93,94,96,92,86,78,72,68,65,65,72,82,98,114,126,131,131,129,118,108,96,88,82,80,87,96,114,124,134,135,129,120,108,97,90,82,77,76,75,72,72,75,78,81,86,92,97,100,102,103,99,97,94,91,88,85,82,80,81,79,78,80,85,88,87,85,79,73,66,63,65,73,83,90,95,96,92,80,65,57,59,63,77,95,116,130,136,135,126,117,101,93,82,74,68,63,60,60,61,62,64,67,70,71,71,70,71,76,81,88,94,92,78,62,47,40,35,39,52,66,76,80,71,58,44,36,36,45,63,79,88,94,96,87,75,63,51,42,36,34,32,32,35,40,46,50,53,53,53,51,48,42,36,31,27,28,30,34,38,42,46,48,50,51,53,56,61,66,70,73,62,52,41,37,40,53,77,97,120,130,133,118,93,70,52,42,45,54,66,76,79,77,73,70,65,64,63,64,63,60,55,50,46,43,37,31,27,28,32,36,45,51,59,63,61,56,51,48,40,38,35,32,30,30,31,31,30,32,36,39,40,39,38,36,31,30,28,27,29,32,35,37,42,47,53,59,60,58,54,50,42,39,34,31,30,29,28,27,25,24,22,21,22,25,28,30,34,36,38,36,32,28,25,24,23,22,23,26,25,26,32,41,56,66,80,90,94,96,99,101,102,104,105,101,93,81,69,60,49,43,36,32,30,30,30,28,25,23,21,20,20,22,25,27,35,43,50,52,54,54,49,42,38,35,31,28,25,25,26,26,30,32,35,37,39,39,38,38,39,37,34,32,29,28,27,27,28,30,33,36,39,42,43,44,37,36,34,31,29,26,24,23,22,21,19,16,14,13,12,11,11,11,11,12,12,12,12,13,12,12,12,12,13,14,15,15,13,13,12,12,12,13,14,15,15,15,14,13,12,12,12,13,13,13,13,12,12,11,11,10,12,11,11,11,10,10,10,10,8,8,8,8,7,7,7,7,7,7,7,6,6,5,5,5,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 9,9,9,9,10,11,12,13,17,17,17,17,17,18,19,20,23,23,23,23,23,23,23,23,23,23,23,22,22,21,21,21,23,23,23,24,24,24,24,24,28,28,28,27,26,25,24,23,26,27,28,29,30,29,27,26,26,26,26,26,25,23,21,20,19,21,24,29,35,40,45,47,49,50,50,50,49,50,54,57,65,66,69,72,72,67,60,54,48,45,42,42,47,55,63,69,73,82,90,92,90,85,75,65,52,44,39,42,48,55,65,74,82,86,91,95,96,96,96,97,96,92,85,77,70,65,62,61,68,77,92,108,120,126,128,127,118,109,100,93,89,88,96,105,118,126,130,126,118,110,98,89,81,75,72,73,74,73,74,77,82,84,87,91,96,101,105,107,107,107,107,104,100,95,91,89,87,86,87,93,103,110,113,113,105,96,83,70,65,66,71,76,85,89,88,80,67,58,57,60,69,86,106,121,129,132,128,121,116,111,103,94,86,80,72,67,64,65,67,74,82,88,90,91,90,92,94,97,99,95,79,62,46,40,36,41,56,72,84,89,75,60,43,33,32,43,65,84,100,108,110,101,84,68,54,43,36,35,33,34,39,46,53,58,62,62,60,56,49,42,35,31,29,31,34,38,42,45,47,48,53,53,56,59,65,71,76,80,74,63,51,44,42,50,69,87,107,115,116,102,81,62,48,39,46,54,65,72,73,70,68,66,61,61,62,62,61,57,52,48,45,43,37,30,26,25,29,32,43,48,56,60,59,55,51,49,44,42,40,38,37,36,36,36,35,37,39,41,41,39,37,35,31,30,27,26,28,31,35,37,43,47,52,57,57,54,49,45,38,35,32,30,29,29,28,26,25,24,23,23,24,26,29,30,34,36,37,35,31,26,23,22,23,23,25,28,28,27,33,41,55,64,78,88,92,93,93,94,90,88,85,81,73,63,54,50,46,43,40,37,36,35,34,33,27,25,23,21,21,24,27,29,36,44,51,53,54,54,49,42,37,35,32,28,26,25,25,26,26,27,29,30,31,31,31,31,33,32,32,31,31,31,32,32,31,32,33,35,36,36,36,36,31,30,29,27,25,23,22,21,23,22,20,18,16,15,15,14,14,14,15,15,16,16,16,17,15,14,14,13,13,14,15,16,13,12,12,11,12,12,13,13,14,14,13,12,12,12,12,13,13,13,13,12,12,12,12,11,12,12,12,12,11,11,11,10,10,10,9,9,8,8,7,7,7,7,7,6,6,5,5,5,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 9,9,9,9,10,11,13,13,17,17,17,17,18,19,20,21,23,23,23,23,23,23,23,23,24,23,23,22,21,21,20,20,23,23,23,24,25,25,25,26,29,29,29,29,28,27,26,25,28,29,29,30,30,30,30,29,27,28,28,27,26,25,24,23,23,25,28,33,39,44,47,49,50,50,48,46,45,47,52,56,63,64,66,67,65,58,49,42,36,34,32,33,38,46,54,60,69,79,90,95,96,92,82,72,58,49,41,42,45,50,58,65,76,80,86,91,94,96,98,99,95,91,85,77,70,64,61,59,65,72,84,96,107,113,116,117,113,106,100,98,96,98,106,116,124,130,132,127,119,111,102,94,84,77,73,74,75,74,75,78,84,85,87,91,95,99,103,105,109,111,112,110,105,100,97,96,92,93,97,105,117,129,137,142,133,122,104,86,72,65,63,63,78,81,82,76,66,56,53,53,63,78,94,106,116,124,125,123,122,123,120,113,105,97,84,73,67,66,69,77,89,99,104,106,107,108,106,103,100,94,79,65,48,42,38,44,59,75,86,91,78,63,44,31,29,40,64,85,108,116,118,107,88,70,55,44,37,37,38,41,48,56,63,68,73,72,68,61,51,42,35,33,31,34,39,43,46,48,48,48,53,54,58,63,70,77,83,86,84,73,61,51,46,49,63,77,96,101,99,85,67,52,42,35,47,53,61,65,64,62,61,61,57,58,60,60,58,53,48,45,41,39,34,28,24,23,26,29,38,44,50,54,54,51,49,48,45,45,44,43,41,40,39,38,38,39,42,43,42,39,36,33,31,30,28,27,28,31,35,37,42,45,49,51,50,46,41,37,34,32,30,30,31,30,28,26,26,25,25,24,25,27,28,29,32,34,35,34,30,25,22,21,24,25,28,32,31,29,33,41,54,63,75,85,89,88,85,84,76,71,67,63,57,50,46,47,44,44,45,44,42,39,36,34,28,26,23,21,21,24,28,30,38,44,50,51,51,50,45,39,34,33,30,27,25,25,25,25,23,24,24,25,26,27,28,28,31,32,33,34,34,34,34,33,30,30,30,30,30,29,28,28,25,25,24,23,22,21,21,20,22,21,20,19,18,18,18,18,18,18,19,19,20,21,21,22,19,18,16,15,14,15,16,17,15,14,13,12,12,12,12,12,13,13,12,12,12,12,13,13,13,13,13,13,13,12,12,12,13,13,13,12,12,12,11,11,11,11,10,10,9,8,8,7,7,7,7,6,6,5,5,5,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 10,9,9,10,10,12,13,14,17,17,17,17,18,19,20,21,23,23,23,23,23,23,23,23,23,23,22,21,20,19,19,18,21,22,23,24,25,26,27,27,28,29,30,31,31,30,29,28,29,29,28,29,29,30,31,32,31,31,30,30,29,28,27,27,29,31,35,39,44,48,50,52,50,49,46,43,42,44,49,54,58,58,59,60,58,51,42,36,30,28,26,26,30,37,44,49,60,71,83,89,91,89,79,70,58,50,43,42,44,47,52,58,67,71,77,81,85,88,92,95,91,88,84,78,72,66,62,59,66,69,76,84,91,97,100,102,102,98,97,99,102,107,116,127,134,140,142,137,130,125,118,111,99,91,84,82,81,78,78,81,84,85,86,89,92,95,98,100,105,107,110,109,104,100,98,98,96,99,106,114,126,140,153,162,158,146,127,105,86,71,62,58,69,71,73,71,64,57,52,50,59,69,80,87,96,107,113,114,118,124,128,125,120,111,95,81,69,67,68,75,89,102,109,112,113,114,109,101,95,88,77,66,52,46,42,47,60,74,84,87,79,64,45,31,27,37,61,82,107,115,117,104,83,65,50,41,41,43,47,53,61,69,76,80,84,82,76,65,52,42,36,35,34,37,42,47,50,50,48,47,50,53,58,66,75,83,90,93,90,80,68,57,49,48,58,70,81,85,82,69,55,47,41,37,44,49,55,55,52,50,51,53,56,58,60,60,56,50,44,41,34,33,29,25,22,22,26,29,34,38,44,47,47,46,46,46,45,45,45,44,43,41,40,39,38,40,42,43,42,39,36,33,31,30,29,29,30,32,35,37,42,44,46,46,44,39,34,31,29,29,29,31,33,32,30,27,27,27,26,26,26,27,28,28,30,32,33,32,28,24,22,21,26,27,31,35,33,31,34,40,50,58,70,79,82,79,74,70,62,55,49,48,45,40,41,46,46,49,52,53,50,44,39,36,31,28,25,23,23,26,30,33,40,45,48,47,46,46,41,34,31,29,28,26,24,24,24,24,22,22,22,23,25,27,29,30,33,35,37,38,38,36,33,31,25,26,26,26,25,24,23,23,21,21,21,21,21,21,21,21,20,20,19,19,19,19,20,20,21,21,22,23,24,24,25,25,21,19,17,15,15,16,17,18,18,17,15,14,13,12,12,12,13,12,12,11,11,12,13,13,13,13,13,13,13,13,13,13,14,14,13,13,13,12,12,12,12,12,11,10,9,8,8,7,7,7,7,6,6,5,5,5,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 10,10,10,10,11,12,13,14,16,16,16,17,18,19,20,21,22,22,22,22,22,22,22,22,22,22,21,20,19,18,18,17,20,21,22,23,25,26,27,28,28,29,31,32,32,31,30,29,29,28,27,27,28,30,32,33,33,33,32,32,31,31,30,30,34,36,39,43,47,51,53,54,51,49,45,41,39,42,47,52,53,54,55,55,54,48,40,34,29,27,24,24,26,31,37,41,51,62,75,81,84,81,72,63,57,49,43,42,44,45,49,54,60,63,68,72,75,80,85,88,87,86,83,79,73,68,63,61,67,69,71,75,80,85,89,91,94,92,93,99,105,112,123,133,143,149,152,148,143,139,133,127,115,105,96,92,88,83,82,84,83,84,85,87,89,92,94,96,100,103,106,105,101,98,97,98,99,103,110,119,129,144,160,172,173,162,143,120,97,78,65,59,60,62,64,66,64,60,55,52,51,58,64,68,76,87,96,99,112,122,131,131,128,120,103,87,71,67,66,73,87,100,109,112,112,113,107,97,87,81,73,66,56,50,45,49,61,73,80,83,80,65,46,32,26,35,59,80,103,110,111,97,76,58,44,36,45,49,55,63,72,80,86,90,90,88,80,67,53,42,37,36,35,39,44,49,51,50,48,46,46,50,58,67,78,87,94,98,92,83,71,60,51,47,55,65,68,71,69,59,50,46,45,44,40,44,48,47,42,40,42,46,57,59,61,60,55,48,42,38,29,28,25,22,21,22,27,31,31,35,40,42,43,43,44,44,43,44,44,44,43,41,39,38,37,39,41,43,42,40,37,35,30,30,30,30,31,33,35,37,43,43,44,43,40,35,30,27,26,27,29,32,34,34,30,27,29,28,27,26,26,26,27,27,28,30,32,31,27,24,21,20,28,29,33,36,35,31,34,40,45,53,64,72,74,70,64,59,51,43,37,38,36,34,37,45,49,54,59,60,56,49,42,38,34,32,28,25,26,29,33,36,41,45,47,45,43,42,38,32,28,27,26,24,23,23,23,23,22,22,22,23,25,28,31,32,36,38,40,41,40,36,31,28,22,22,23,23,23,22,22,21,19,19,20,20,21,22,22,22,19,18,18,18,19,20,21,21,22,22,23,24,25,26,27,27,22,20,17,15,14,15,17,18,20,19,17,15,14,13,12,12,12,12,11,11,11,12,13,13,13,13,13,13,13,13,13,13,14,14,14,13,13,13,12,12,13,12,11,11,10,9,8,8,7,7,7,6,6,5,5,5,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 9,9,10,11,11,12,13,13,16,15,15,16,17,18,20,21,20,20,20,20,20,20,20,20,21,20,18,16,15,14,13,13,17,17,18,20,21,22,23,24,27,28,29,30,31,32,33,33,33,31,27,24,24,26,29,32,31,32,33,34,35,36,36,36,38,38,40,44,49,52,53,52,50,48,44,42,41,43,45,47,50,51,51,49,45,41,38,38,33,32,31,30,31,33,36,37,48,53,59,64,66,64,61,58,48,46,44,45,48,51,53,53,53,57,61,63,65,68,74,78,82,82,82,80,78,76,74,74,69,74,76,75,75,77,76,72,81,84,89,96,106,117,129,137,149,157,162,159,157,157,154,148,142,131,116,106,100,97,93,90,93,91,88,88,88,88,86,85,90,92,93,91,89,89,92,96,95,100,108,118,130,145,161,172,167,166,153,129,105,87,71,58,59,61,63,62,58,54,52,51,50,52,54,53,53,57,67,75,91,111,129,134,135,131,114,95,82,75,68,69,79,92,101,104,102,99,94,85,76,70,67,66,58,56,54,56,62,70,77,81,73,61,45,33,29,36,54,72,96,100,99,85,64,45,37,36,39,48,62,74,81,87,93,97,90,88,82,69,55,43,38,36,40,43,48,51,51,48,44,42,47,53,61,67,77,89,96,97,92,82,69,58,49,44,47,55,58,59,58,55,50,45,43,42,40,37,36,35,33,32,38,47,51,58,62,57,51,44,35,27,27,25,21,18,19,22,27,30,32,34,35,36,35,35,37,39,42,42,43,42,41,39,37,36,36,38,41,43,43,41,39,37,33,34,34,35,36,37,37,38,40,39,39,37,34,30,27,25,30,31,34,36,36,36,34,33,33,33,34,33,31,28,24,22,27,25,25,26,25,21,23,28,29,37,42,42,41,42,40,37,42,48,57,67,70,66,57,50,42,37,31,26,26,31,38,42,56,59,62,63,59,51,42,36,30,29,29,30,32,36,40,43,46,46,45,43,39,34,29,26,23,24,25,25,26,25,25,24,26,26,26,27,29,32,35,37,39,40,41,40,37,32,26,22,18,17,17,17,18,20,22,23,23,21,20,21,22,21,19,17,16,16,17,19,21,22,24,24,21,22,24,25,26,26,25,24,24,23,20,18,17,18,19,20,21,21,20,19,18,16,14,13,14,14,13,13,13,13,14,14,16,15,14,13,13,13,13,13,17,17,16,15,13,12,11,11,10,11,11,11,11,10,9,8,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 9,9,10,11,11,12,13,13,15,15,15,15,16,17,18,19,19,19,19,19,19,19,19,19,20,19,17,15,14,13,13,13,15,16,17,18,19,20,21,22,26,26,28,29,30,32,33,33,32,30,27,25,24,25,27,28,30,31,33,35,36,37,37,37,40,40,42,46,51,54,54,53,50,47,44,42,42,43,45,47,48,50,51,50,47,44,43,43,47,46,44,42,40,39,39,39,49,52,56,60,60,58,54,52,46,45,45,48,52,55,56,56,53,55,57,57,57,59,64,68,75,76,78,80,83,86,89,92,87,90,89,83,78,76,73,69,81,85,90,97,106,119,131,140,153,162,168,167,167,168,166,161,158,148,134,123,116,112,109,106,107,104,99,95,92,87,82,79,78,79,80,79,79,83,89,95,97,101,107,115,124,137,151,160,157,156,146,125,105,90,76,65,61,63,64,63,59,56,54,54,48,50,50,48,46,48,55,61,79,100,119,128,132,132,118,102,87,78,68,65,71,80,87,91,91,89,83,76,69,65,64,65,65,62,59,59,62,67,72,75,71,59,45,34,30,35,52,68,85,88,87,74,54,37,31,31,41,51,65,75,82,86,90,93,89,87,80,67,52,41,37,36,42,45,49,52,50,47,43,41,46,53,61,67,76,87,93,93,90,80,66,55,44,38,40,47,53,54,55,54,49,45,42,41,39,36,33,32,29,29,36,46,53,59,61,56,49,42,34,26,26,24,21,20,21,25,29,32,32,33,33,32,30,31,34,36,41,41,41,41,39,37,34,32,35,38,41,43,44,43,41,39,36,36,37,38,38,39,39,39,40,39,38,36,34,31,28,26,30,32,36,38,39,38,36,34,34,35,35,35,32,29,25,22,24,22,22,25,24,22,25,30,40,47,52,51,47,45,40,34,38,43,51,58,62,59,51,45,40,36,31,27,27,32,38,43,54,56,59,59,55,48,40,34,30,30,31,33,36,39,42,44,44,44,42,39,35,31,27,25,23,24,25,27,27,27,27,27,28,27,28,29,31,34,37,38,40,40,40,38,34,29,24,21,18,18,19,20,22,24,26,27,27,25,24,23,23,22,20,17,16,17,18,19,21,22,23,24,21,22,24,25,25,25,24,24,23,22,20,18,18,19,20,22,22,22,22,21,19,18,16,15,16,16,16,15,15,16,16,16,17,16,15,14,13,13,13,13,17,17,16,14,13,12,11,11,10,10,11,11,10,9,9,8,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 9,9,10,11,11,12,13,13,14,13,13,14,14,15,17,17,17,17,17,17,17,17,17,17,18,17,15,14,13,12,12,12,13,13,14,15,16,17,18,18,23,23,25,26,28,30,31,32,31,30,28,26,24,23,23,23,28,30,32,34,36,37,38,39,43,43,44,48,52,54,55,54,49,47,44,42,41,43,45,47,47,49,52,52,52,51,52,53,61,60,59,57,55,52,50,48,53,55,56,57,56,52,48,46,45,46,48,53,58,61,61,60,56,55,53,50,48,50,54,58,65,68,72,77,84,93,103,110,114,117,114,105,95,89,83,77,83,85,90,96,105,117,129,137,150,158,166,170,172,175,175,172,171,163,151,140,133,129,126,125,125,121,116,110,103,94,85,79,73,71,68,66,68,74,83,90,98,101,106,112,119,128,137,143,141,140,133,117,102,90,81,74,64,65,66,65,62,59,58,59,55,57,57,54,50,49,52,56,68,87,108,120,129,132,123,110,95,85,71,62,62,67,72,75,76,73,69,63,59,58,61,65,72,69,66,62,61,63,65,67,65,56,45,37,32,34,47,61,73,75,73,61,44,31,27,28,44,54,66,75,79,80,82,84,83,80,73,61,48,39,36,36,43,47,52,53,50,45,41,40,46,54,61,67,75,84,88,87,86,75,61,48,37,29,31,38,46,49,51,51,48,45,42,41,39,34,30,27,25,26,35,45,56,61,61,55,47,40,32,25,24,23,22,23,25,28,32,34,36,35,33,30,28,30,34,37,44,44,43,42,39,36,32,30,34,37,41,45,46,46,45,43,40,41,42,42,42,42,41,41,40,40,38,36,33,31,30,29,31,34,38,41,42,41,38,36,36,37,38,37,35,31,26,23,20,19,20,23,24,24,29,36,49,57,63,61,56,51,42,35,36,38,43,49,52,50,45,40,36,34,30,28,29,33,39,42,50,52,53,53,50,43,37,32,30,31,34,37,40,43,44,45,43,41,38,35,31,28,26,25,24,25,27,29,30,30,29,29,29,28,29,29,31,34,37,39,39,38,36,33,29,25,22,20,20,21,23,26,29,32,34,35,34,32,29,27,26,24,21,19,18,18,19,20,21,22,23,23,21,22,23,24,24,24,24,23,22,21,20,19,19,21,22,23,24,24,24,23,22,21,19,18,19,19,19,19,19,19,19,19,18,17,16,14,13,13,13,13,17,16,15,14,13,12,11,10,9,10,10,10,10,9,8,7,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 9,9,10,11,11,12,13,13,13,12,12,12,13,14,15,15,15,15,15,15,15,15,15,15,15,15,14,13,12,12,12,12,11,12,12,13,14,15,16,16,18,19,21,22,24,26,28,28,29,29,28,27,25,23,21,20,26,28,30,33,36,38,40,40,45,45,46,48,52,53,53,52,48,46,43,41,41,42,45,47,47,50,54,56,57,59,62,65,68,69,71,72,71,70,68,66,63,63,62,60,57,53,49,47,50,52,55,60,65,66,65,63,59,56,51,47,45,47,51,55,59,62,66,71,80,94,110,121,134,139,140,131,119,110,100,93,87,89,92,95,101,110,121,128,136,143,153,160,165,169,172,172,172,167,159,149,142,139,139,140,141,139,134,129,121,110,98,91,80,75,67,62,62,67,76,82,94,98,104,111,116,121,125,127,124,122,115,104,93,85,79,77,69,70,70,69,66,64,64,64,67,68,69,67,63,61,61,62,67,83,101,114,124,128,123,115,104,92,77,65,60,61,64,66,63,61,57,52,51,54,60,65,74,73,71,66,62,59,58,58,59,52,44,38,33,33,42,53,65,66,64,54,41,31,30,32,45,54,65,71,72,70,69,69,70,68,63,53,42,36,35,37,44,49,54,54,49,44,40,39,47,55,63,69,76,83,84,82,80,69,55,42,31,24,26,32,41,45,49,50,48,45,43,42,39,34,28,25,22,24,34,46,58,62,62,54,46,40,33,26,24,24,24,26,29,32,35,37,41,39,36,33,32,35,41,46,51,50,48,45,41,36,33,31,35,38,42,47,50,50,50,49,46,46,46,46,45,45,44,43,42,41,39,36,34,33,31,31,32,35,39,43,44,42,39,37,38,39,41,41,38,34,29,25,20,18,19,23,26,28,35,43,53,63,71,71,66,59,48,39,37,37,39,42,44,44,41,38,32,31,30,29,31,35,38,41,47,48,48,48,44,40,35,31,30,32,36,40,43,45,45,45,42,40,36,32,29,28,27,28,28,30,31,33,33,31,30,28,28,28,27,28,30,33,35,37,34,33,31,28,25,23,22,21,24,26,30,34,38,41,43,44,42,39,35,32,30,27,24,21,21,21,21,22,22,22,23,23,22,22,22,23,23,23,23,22,20,20,20,20,21,22,24,25,26,26,26,26,25,24,23,22,21,21,22,22,22,22,21,21,20,19,18,16,14,13,13,13,16,16,15,14,13,11,11,10,9,9,9,9,9,8,7,7,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 9,9,10,11,11,12,13,13,13,12,12,11,12,13,13,14,13,13,13,13,13,13,13,13,14,13,13,12,12,12,13,13,12,12,13,13,14,15,15,15,16,16,17,19,21,23,24,24,27,27,27,27,25,23,21,20,25,27,30,34,38,41,43,44,48,47,47,49,51,51,49,48,45,43,41,39,39,41,44,46,48,51,55,59,62,66,70,74,76,79,82,85,86,86,85,83,76,74,72,68,64,61,58,56,60,61,64,68,71,71,68,65,60,55,49,45,45,48,52,55,55,57,61,66,76,94,115,130,145,154,159,152,139,125,112,103,97,98,98,99,100,105,111,116,121,126,136,145,152,157,162,167,166,165,161,154,148,147,151,155,157,156,154,150,143,130,117,108,92,84,73,65,62,66,72,76,86,90,99,107,113,116,115,113,108,103,96,88,79,73,73,74,74,76,77,75,72,70,69,69,74,76,79,80,79,77,75,74,76,86,99,109,117,121,119,114,106,97,83,70,63,60,61,62,58,56,52,48,47,52,59,65,72,74,74,71,64,57,53,51,51,47,43,39,34,32,38,47,58,59,57,50,41,35,36,38,46,53,61,63,61,56,53,53,54,54,52,45,37,33,34,37,44,49,55,55,49,44,41,41,49,58,67,73,79,84,83,79,74,63,50,39,28,22,26,32,40,43,47,48,47,45,44,43,40,35,29,25,22,24,35,47,59,64,63,56,48,42,36,29,27,27,27,29,31,34,37,39,43,42,42,41,42,47,54,59,62,59,54,47,41,36,32,30,37,40,45,50,54,55,55,54,51,50,49,48,46,46,45,45,44,43,41,39,37,35,33,32,31,34,38,41,43,42,39,38,39,41,43,44,42,37,32,29,23,21,22,26,30,33,42,51,63,73,82,82,77,67,54,43,37,36,35,36,38,38,37,35,29,30,31,33,35,37,38,39,45,44,44,42,40,36,33,31,30,33,37,41,43,44,43,43,40,38,34,31,29,30,31,32,35,36,37,37,35,32,29,26,25,25,25,25,27,29,32,33,29,28,26,25,24,24,25,25,30,33,38,43,48,50,51,52,47,44,39,35,33,31,28,25,25,25,24,24,24,23,23,23,22,22,22,21,21,21,21,22,20,20,21,21,22,24,25,26,27,27,28,28,28,27,27,26,23,24,25,25,25,25,24,23,23,22,20,18,16,15,14,14,16,15,15,13,12,11,10,10,8,8,9,9,8,7,6,6,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 9,9,10,11,11,12,13,13,13,12,12,11,12,12,13,13,12,12,12,12,12,12,12,12,13,13,12,12,12,13,14,14,14,15,15,15,16,16,17,17,16,16,17,18,19,21,21,22,25,25,26,26,26,25,24,23,27,29,33,37,42,46,48,50,53,51,50,50,50,49,46,44,43,41,38,37,37,39,42,44,48,51,55,59,63,68,73,77,85,87,90,92,94,93,92,91,85,82,78,74,71,69,68,68,70,70,72,75,77,76,73,70,60,56,50,47,48,52,55,57,54,56,58,61,72,92,118,136,157,167,173,166,150,135,120,110,107,107,106,104,101,101,102,104,109,111,119,129,136,142,150,158,158,160,160,156,151,152,158,165,169,170,171,170,163,151,136,126,107,98,85,75,70,70,72,73,76,80,88,97,104,106,105,102,95,88,79,71,64,61,65,71,80,83,84,83,80,75,73,72,79,83,89,94,96,95,92,90,85,90,96,102,107,110,111,110,104,98,89,78,70,64,62,61,59,57,53,49,48,52,59,64,71,75,79,77,68,57,50,46,45,42,40,39,35,31,36,43,50,52,52,48,42,39,40,43,49,54,58,57,51,44,41,40,43,44,44,40,35,31,32,35,41,48,55,55,50,45,43,45,52,62,72,78,84,87,85,80,72,62,49,39,30,25,28,35,41,43,45,46,44,42,42,43,40,35,29,26,23,25,35,47,59,64,65,60,53,48,41,34,33,32,30,30,32,35,38,40,42,45,49,53,58,64,72,77,74,69,60,50,41,36,33,32,40,44,49,54,58,60,59,59,56,53,50,47,45,45,46,47,46,46,45,44,41,37,33,31,29,31,34,37,38,38,38,37,39,42,45,47,45,41,36,33,28,25,25,29,32,37,46,56,74,84,92,92,84,73,58,46,37,35,33,32,33,34,33,32,31,33,36,38,40,41,40,40,42,41,39,37,34,32,31,30,30,32,35,38,40,40,39,39,37,35,33,31,31,32,34,35,39,40,41,41,38,34,29,26,23,23,22,23,24,26,28,30,27,27,27,27,27,28,29,30,36,39,45,50,54,55,55,55,50,46,41,38,36,34,32,31,29,29,28,27,26,25,24,24,23,22,21,20,20,20,20,21,21,21,22,23,24,25,25,26,28,28,29,30,30,30,29,29,27,28,29,30,30,29,28,27,27,26,23,21,18,17,16,15,16,15,14,13,12,11,10,9,7,7,8,8,7,7,6,5,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 9,9,10,11,11,12,13,13,14,13,12,12,12,12,13,13,12,12,12,12,12,12,12,12,13,13,12,13,13,14,15,16,18,18,18,18,19,19,19,19,19,19,20,20,21,21,21,22,23,23,24,25,26,27,28,28,30,33,37,43,48,52,55,57,58,56,53,52,51,48,45,42,40,38,36,34,35,37,40,42,47,49,53,57,61,66,72,76,83,85,87,89,91,92,91,91,87,84,80,76,73,73,74,75,77,77,78,80,82,81,78,76,66,61,55,53,55,58,60,61,58,58,56,56,64,84,111,131,155,165,170,162,146,131,119,111,109,109,109,105,99,95,92,92,96,95,100,109,117,122,132,143,146,151,153,150,146,147,155,164,170,174,179,182,179,170,156,147,129,119,104,91,83,77,73,70,69,70,74,81,89,93,94,93,86,76,65,58,53,52,60,71,85,88,91,90,86,80,76,73,78,83,91,99,104,103,100,96,88,88,89,92,96,100,104,107,106,103,98,90,81,73,67,64,62,60,56,52,50,52,57,61,72,79,86,85,74,59,48,42,40,38,38,38,34,31,35,42,45,47,48,47,45,43,45,47,55,58,59,54,46,38,34,34,38,41,42,40,34,30,30,31,37,46,54,55,50,46,46,49,55,65,77,84,89,92,88,82,75,65,52,42,32,27,31,38,42,43,43,42,39,38,39,40,39,34,29,26,23,25,34,46,57,64,67,64,59,54,47,40,39,36,33,31,31,34,37,40,45,51,60,70,78,86,93,98,90,82,69,56,46,40,38,37,44,47,53,58,62,63,63,62,59,55,50,44,42,43,46,48,48,49,50,48,45,39,34,30,27,28,30,31,33,34,35,36,39,42,46,49,48,45,40,37,32,28,27,30,33,38,48,58,74,85,93,93,86,75,61,49,40,37,34,33,34,34,33,32,35,38,42,46,47,46,44,43,38,36,34,31,29,28,28,28,30,31,33,35,36,35,35,34,32,31,31,31,32,34,36,37,41,42,43,43,41,36,31,28,22,22,21,22,23,25,27,28,31,32,32,33,33,33,34,34,39,43,48,53,56,56,55,53,50,46,42,39,38,37,36,35,33,32,31,30,28,27,26,25,23,22,20,19,19,19,20,20,22,22,23,24,25,25,25,25,28,28,29,30,31,31,31,30,31,32,34,35,35,34,32,31,30,29,26,23,21,19,18,17,15,15,14,13,12,10,9,9,6,7,7,7,7,6,5,4,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 9,9,10,11,11,12,13,13,14,14,13,12,12,13,13,13,12,12,12,12,12,12,12,12,13,13,13,13,14,15,16,17,20,20,20,20,21,21,21,21,22,22,22,22,22,22,22,22,22,22,23,24,26,29,31,32,34,36,41,47,52,57,60,62,62,59,56,54,52,49,44,41,39,37,35,33,34,36,39,41,45,48,51,54,58,63,69,74,75,76,79,82,85,87,88,89,86,83,78,75,73,74,76,78,80,80,80,82,84,85,83,81,73,68,62,60,62,65,65,65,62,60,56,52,56,73,100,119,141,151,155,146,131,119,111,105,106,107,106,102,96,89,85,83,84,81,84,93,100,106,117,129,136,141,145,142,137,138,147,156,165,171,180,187,189,182,171,162,150,139,122,106,93,82,73,67,66,64,64,68,76,83,87,87,81,69,57,51,47,48,59,72,88,92,95,95,90,83,77,74,70,75,84,94,99,100,95,91,86,84,82,85,88,93,99,105,109,109,107,100,91,80,73,69,65,63,59,54,51,52,55,59,74,83,91,90,78,61,47,39,37,36,36,37,34,31,34,41,43,46,48,49,48,47,48,50,60,61,60,54,44,36,32,32,38,41,43,41,35,30,28,28,35,44,53,55,51,47,48,51,57,68,79,87,92,95,91,84,78,68,55,44,34,29,32,39,43,43,41,39,36,35,36,38,37,33,28,26,23,24,33,44,56,64,69,67,62,57,50,43,43,40,35,32,31,33,37,40,50,58,70,83,94,103,110,114,102,93,78,63,51,45,44,44,46,50,55,60,64,65,65,64,61,56,49,43,40,42,45,48,50,51,52,51,47,41,34,29,26,26,27,28,30,32,34,35,38,42,46,50,50,47,42,39,34,30,28,30,33,38,48,58,67,78,88,89,84,75,62,51,44,41,38,37,37,37,36,35,39,42,47,51,52,50,47,45,35,33,30,27,25,25,26,26,30,31,31,32,32,32,32,32,28,28,29,30,32,34,36,37,40,42,44,44,42,38,34,31,23,22,21,22,23,25,27,28,36,36,37,38,37,37,36,35,40,44,49,54,56,55,53,51,49,46,41,39,39,39,39,38,35,34,33,31,29,28,27,26,23,22,20,19,18,18,19,20,22,23,24,25,25,25,25,24,27,28,29,31,31,31,31,31,34,36,38,39,39,38,36,34,32,31,28,25,22,20,19,18,15,15,14,13,11,10,9,9,6,6,7,7,7,6,5,4,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 13,13,12,12,12,13,14,14,14,14,13,13,13,14,14,15,14,14,13,12,12,11,10,10,13,12,12,12,13,15,17,19,21,23,25,26,25,24,25,27,28,28,27,26,25,24,24,24,23,23,23,23,25,28,30,32,38,40,45,51,57,62,66,67,65,62,58,52,47,43,39,38,38,37,35,33,33,35,37,38,38,41,45,50,54,57,59,59,69,69,69,71,72,75,77,78,76,73,70,67,67,69,72,74,70,75,81,86,88,90,92,93,90,82,74,70,71,76,79,80,74,71,66,60,60,71,90,104,124,127,126,118,105,95,93,95,100,102,102,99,93,86,81,79,71,70,70,74,81,91,101,108,122,126,130,128,124,126,133,141,154,163,172,176,179,180,175,169,154,144,130,119,108,95,79,67,60,56,53,55,63,71,77,80,76,66,57,52,49,51,64,79,88,93,100,103,99,89,77,69,69,72,77,83,88,90,88,86,81,80,78,77,80,88,98,106,109,117,120,112,98,86,76,69,67,67,65,61,56,54,57,60,70,78,88,90,81,63,45,34,30,32,36,38,38,37,35,34,39,45,51,54,53,52,53,56,63,65,66,63,56,47,40,36,40,44,47,45,39,33,29,28,34,40,46,48,47,45,44,45,54,68,83,92,97,100,100,96,82,70,56,46,37,32,34,40,43,43,42,36,30,27,29,32,35,34,29,23,19,23,31,39,51,60,65,64,63,62,55,46,46,42,36,31,30,32,35,38,51,60,75,92,108,119,125,128,114,97,78,65,54,44,42,46,54,55,57,62,67,69,69,68,64,55,47,43,41,39,43,49,51,56,58,54,49,43,34,26,25,24,23,24,27,29,29,28,33,37,42,47,48,46,42,39,36,32,27,25,28,35,43,49,63,70,78,81,77,68,59,54,43,44,45,45,45,45,44,44,45,47,51,55,56,53,46,41,32,29,26,23,22,24,27,29,29,29,30,30,30,29,29,28,26,27,29,30,32,32,32,32,36,36,38,40,40,38,32,28,26,24,22,21,23,29,34,38,42,44,46,46,43,40,38,38,39,41,45,49,51,51,50,49,43,42,41,40,39,39,39,39,40,39,36,33,30,27,26,25,22,20,18,16,15,16,18,19,20,21,23,24,25,24,23,22,25,26,27,29,31,33,35,36,34,36,38,39,40,40,39,39,35,33,31,29,28,26,22,19,18,17,15,13,11,10,10,9,8,8,8,7,7,6,6,6,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 13,13,13,12,13,13,14,15,16,15,15,14,14,14,14,15,14,14,13,12,12,11,10,10,12,12,11,12,13,16,18,19,22,24,27,28,27,28,29,30,35,35,35,34,33,31,30,29,24,24,23,24,26,29,32,34,39,42,46,51,57,61,65,66,64,61,57,52,47,42,39,38,36,36,35,34,34,35,37,37,36,38,41,45,49,52,54,55,61,61,61,61,62,64,66,68,69,67,65,63,63,65,67,68,67,70,76,81,86,91,97,100,99,93,86,82,83,85,86,87,83,79,73,66,63,70,84,96,106,108,107,98,87,80,80,84,95,99,102,102,96,87,79,74,69,67,66,66,71,78,86,91,108,112,115,113,110,111,118,125,139,148,157,162,164,166,162,157,151,142,131,121,112,100,86,76,61,57,53,53,58,65,70,73,78,70,64,63,62,65,76,89,96,98,101,101,97,88,78,72,71,73,76,79,82,82,80,78,76,76,76,78,83,92,103,111,119,126,129,120,106,93,81,72,66,67,67,63,59,56,56,58,68,76,86,89,80,63,44,33,30,33,38,41,40,38,35,34,37,43,50,53,52,52,53,55,65,67,69,67,60,52,45,42,44,48,51,50,44,37,32,30,33,37,43,45,43,41,40,40,50,64,79,89,96,102,103,101,87,74,59,47,38,32,35,40,43,43,40,34,28,25,28,32,36,35,32,27,24,26,32,39,49,57,63,63,63,62,56,48,45,41,35,31,29,31,34,37,47,57,75,95,114,127,135,139,122,105,84,69,58,49,48,52,55,55,58,62,67,70,71,70,67,58,48,43,40,39,44,51,56,61,62,58,53,47,38,30,26,24,23,23,26,27,28,27,31,34,39,44,45,43,40,37,32,29,25,24,27,34,42,47,57,63,70,73,71,64,57,53,51,52,54,56,56,54,52,51,48,49,52,54,55,51,45,40,29,26,23,20,19,21,24,27,28,29,29,29,29,28,27,27,25,26,28,30,31,31,31,31,34,35,36,39,40,38,33,29,25,23,21,20,22,27,33,36,43,45,47,47,44,40,38,38,35,37,40,43,45,45,45,44,43,42,42,42,43,44,45,46,44,43,40,37,33,29,25,23,21,19,17,15,14,15,17,18,20,21,23,25,26,25,24,23,25,25,26,28,30,32,33,34,34,35,37,39,40,40,39,38,35,33,31,30,29,26,23,20,18,17,15,13,11,10,10,9,8,8,8,7,7,6,6,6,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 14,13,13,13,14,15,16,16,18,17,17,16,16,15,15,15,14,14,13,13,12,11,10,10,11,11,11,12,14,16,19,21,23,26,29,31,31,32,34,36,41,42,43,43,41,39,36,34,28,27,25,25,26,30,33,36,40,42,46,50,55,58,61,62,60,58,54,49,45,41,38,37,34,35,36,37,38,38,38,38,36,37,39,42,46,49,53,54,56,54,53,52,52,53,56,57,61,61,61,61,61,61,61,62,63,66,70,76,84,95,106,113,115,111,106,102,100,99,98,96,94,91,84,75,70,71,79,86,87,87,84,76,68,65,70,75,91,97,104,105,99,88,77,70,69,67,64,63,65,69,74,77,91,94,97,96,93,95,101,108,120,130,139,142,144,145,143,139,141,136,128,122,115,107,96,89,74,69,64,61,63,67,71,73,79,76,76,79,81,85,94,103,109,107,104,99,92,85,79,76,72,73,74,75,74,73,71,70,71,73,77,82,89,100,112,120,131,138,139,129,113,98,83,72,65,67,68,67,63,58,55,54,63,71,82,85,77,60,43,32,30,35,41,45,43,39,35,33,36,43,51,55,55,54,55,56,66,69,72,71,66,58,52,49,50,53,57,56,51,43,37,33,31,35,39,40,39,36,34,34,44,57,72,84,94,104,108,107,94,80,63,50,39,33,35,40,44,42,38,31,25,23,27,32,37,39,39,36,32,32,36,40,47,54,60,62,63,61,55,48,43,39,34,30,28,29,32,35,43,54,73,95,116,131,141,145,129,111,89,71,59,52,53,57,56,56,59,63,69,73,74,73,71,60,49,43,39,39,45,53,60,64,65,61,55,50,41,32,27,25,23,23,24,26,26,26,28,31,35,38,40,38,35,33,26,24,23,23,27,33,40,45,50,54,60,63,62,58,55,54,58,61,65,67,67,64,61,58,51,50,51,51,51,47,41,37,27,25,21,18,18,20,23,26,28,28,28,28,28,27,26,25,24,25,28,30,31,31,31,31,32,33,35,38,40,39,35,32,27,25,22,21,22,27,32,36,43,45,47,46,43,39,37,36,31,31,32,34,35,37,38,38,39,40,41,43,46,49,52,53,52,51,49,46,40,33,26,22,19,18,15,14,13,14,16,18,20,22,24,27,27,27,26,25,24,24,24,25,27,28,30,31,33,34,36,38,39,39,38,37,35,33,31,30,29,27,23,21,17,16,14,13,11,10,10,9,8,8,8,8,7,7,7,7,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 14,14,14,14,15,16,17,18,19,19,19,19,18,17,16,16,15,15,14,13,13,12,11,11,11,11,11,12,14,17,20,21,24,27,31,33,35,36,39,41,44,45,47,48,47,44,40,37,35,33,30,28,28,30,33,35,39,40,43,47,50,52,54,54,53,51,48,44,40,37,35,34,35,37,40,42,44,44,43,43,43,43,44,46,50,54,58,60,58,55,52,49,48,49,51,53,57,58,60,61,61,60,58,57,60,62,66,73,83,98,113,124,129,127,125,121,117,113,108,105,102,99,93,85,79,77,79,82,79,77,73,67,62,64,72,79,96,101,107,107,101,90,80,74,74,72,71,69,69,70,72,73,78,81,83,82,80,83,90,96,107,116,124,125,124,124,123,120,125,123,120,117,114,109,104,100,90,86,80,75,74,75,77,79,82,84,89,95,101,107,112,116,121,115,105,95,86,80,78,77,73,74,75,74,72,70,69,69,71,75,82,90,100,112,124,132,142,147,146,134,116,99,81,68,62,65,69,70,67,61,54,50,55,63,73,76,69,55,40,31,31,38,45,48,45,39,33,31,36,44,54,60,60,57,56,56,64,68,72,73,68,62,56,52,54,58,62,63,59,51,43,37,32,34,36,37,36,34,32,30,37,49,63,76,90,103,110,111,100,85,67,52,40,33,35,40,43,42,37,30,23,23,28,33,42,45,48,48,44,41,41,43,47,52,57,60,60,57,51,46,41,38,33,29,27,28,31,33,40,50,69,90,110,125,135,140,128,112,88,68,56,51,52,55,56,57,59,64,70,74,76,76,72,61,48,41,37,38,45,54,60,64,65,60,54,49,41,33,29,26,23,22,23,25,25,25,26,28,31,33,34,33,31,29,21,21,22,24,29,35,40,44,46,49,53,55,55,55,55,56,61,65,71,74,74,70,64,60,51,49,46,45,43,40,35,32,27,25,22,20,20,22,24,26,27,28,28,28,28,27,26,25,25,26,29,32,34,35,34,34,34,34,36,39,42,42,39,36,31,28,25,23,24,27,32,35,40,42,44,43,39,35,33,32,27,27,26,26,28,29,31,32,34,35,38,42,47,52,57,59,62,62,61,57,50,40,31,25,18,17,14,13,13,14,16,17,21,23,26,29,30,29,27,25,23,23,22,22,23,24,26,27,31,32,34,36,36,36,35,35,33,31,29,29,28,27,23,21,16,15,14,12,11,10,10,10,8,8,8,8,8,8,8,7,7,7,7,7,7,7,7,7,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 15,15,15,15,16,18,19,20,20,21,21,21,21,20,18,18,17,16,16,15,14,14,13,13,12,12,12,13,14,17,20,21,23,27,31,34,36,38,40,43,46,48,50,51,50,47,44,42,42,40,36,32,30,30,31,32,36,37,39,41,43,44,44,45,44,43,40,37,35,33,32,32,37,39,44,48,51,52,52,51,51,51,52,55,58,63,67,69,66,62,57,52,50,50,52,54,57,59,61,62,62,60,57,55,57,59,62,69,81,97,114,125,137,138,137,134,127,120,113,109,104,102,99,94,89,86,85,86,82,80,76,72,71,76,85,93,108,111,112,109,102,94,87,83,83,83,83,82,80,77,74,72,70,71,70,68,68,72,79,86,97,106,112,110,106,105,104,102,106,108,110,110,108,106,105,104,99,97,92,87,84,83,84,85,90,95,102,110,118,124,127,127,125,116,102,87,78,74,74,75,76,78,80,79,75,73,74,75,75,80,89,98,109,120,131,138,146,149,146,133,115,97,78,64,59,63,68,71,70,63,54,48,48,54,61,63,58,48,38,33,35,42,51,52,46,38,32,30,36,46,59,66,65,59,54,51,58,62,68,70,66,60,54,51,54,58,64,68,67,59,48,41,35,36,37,37,37,35,33,31,33,42,55,67,83,99,108,109,101,87,69,54,42,34,35,40,43,41,37,30,25,25,30,35,47,53,58,59,55,50,48,47,50,51,54,57,55,50,45,42,39,37,32,29,27,28,29,31,36,45,61,81,100,115,126,131,121,107,85,65,53,50,51,51,56,56,57,62,68,72,75,75,70,58,45,38,34,36,44,53,60,63,64,59,54,50,42,35,30,26,23,22,23,25,26,26,26,27,28,29,29,27,26,25,18,20,24,28,34,39,43,45,48,50,51,52,52,53,55,58,62,67,73,77,77,71,64,59,47,43,39,35,34,32,29,27,25,24,23,22,22,23,25,26,27,28,29,29,29,29,28,28,28,30,35,39,42,42,42,41,40,40,42,44,46,46,44,42,34,31,26,23,23,25,29,31,34,37,38,38,34,31,29,28,25,24,23,22,23,25,27,28,31,33,37,43,49,56,61,64,71,72,71,67,59,47,36,29,18,17,15,14,14,15,17,19,23,25,29,31,32,30,27,25,22,21,19,18,18,20,21,22,27,28,30,31,32,32,31,31,29,27,26,26,26,25,22,19,15,15,13,12,10,10,10,10,8,8,8,8,8,8,8,9,7,7,7,7,7,7,7,7,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 16,16,16,16,18,19,21,22,20,21,23,24,24,23,21,20,19,19,18,17,16,16,15,15,14,14,13,13,15,17,19,20,22,25,29,32,34,36,39,41,47,48,50,52,52,50,48,47,46,44,41,37,34,32,32,31,33,34,35,36,36,36,36,36,35,34,33,32,31,31,31,31,38,41,47,52,57,60,61,61,60,61,63,67,71,75,79,81,77,72,65,58,55,55,57,59,62,63,65,66,65,62,58,56,57,59,63,69,80,95,110,121,138,140,141,137,129,120,112,108,102,102,101,100,98,97,96,95,91,90,88,87,89,95,104,111,123,122,119,112,104,97,94,92,94,96,99,100,97,90,82,77,73,70,65,60,59,63,71,77,91,100,105,100,94,92,91,90,95,99,103,103,100,99,100,102,104,105,104,101,97,94,94,95,99,105,111,118,126,134,134,131,121,111,96,82,74,72,76,79,85,88,90,88,83,78,77,78,78,84,92,102,111,120,128,134,141,142,138,125,109,93,76,62,55,59,65,71,71,65,54,47,42,45,49,50,47,42,39,38,42,50,57,57,48,38,32,30,39,51,66,74,71,62,52,46,51,56,62,65,62,56,50,46,50,55,64,71,71,65,54,45,38,38,37,38,39,38,36,33,31,38,47,58,75,92,102,103,99,86,69,56,44,35,35,39,41,41,38,33,28,29,34,39,52,59,66,68,63,57,53,51,51,49,49,51,49,43,40,41,39,36,32,29,27,28,29,30,32,39,52,69,87,103,115,121,110,100,82,63,53,51,50,47,52,51,52,56,61,66,69,69,64,52,40,34,31,32,40,49,58,62,63,58,54,51,45,38,30,27,23,22,24,26,28,29,28,28,28,27,25,24,22,21,18,22,28,35,41,46,49,50,51,51,51,50,49,50,52,55,60,64,71,75,74,68,61,56,42,37,31,27,25,25,25,25,24,25,26,27,27,27,26,25,28,29,30,31,32,32,32,32,33,37,42,48,52,53,53,53,51,50,50,52,53,52,50,47,37,33,27,23,20,21,24,26,28,31,33,33,30,27,25,25,24,23,22,21,21,22,24,25,30,32,37,43,51,58,64,67,75,75,75,71,62,51,39,32,20,19,17,16,16,18,20,21,26,28,32,34,33,31,27,24,21,20,17,15,14,15,17,18,21,23,25,26,27,27,26,26,24,23,22,22,23,22,19,17,15,14,12,11,10,10,10,10,8,8,8,8,9,9,9,9,8,8,8,8,8,8,8,8,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 16,16,16,17,18,20,22,23,19,21,23,25,26,25,24,23,21,21,20,19,19,18,17,17,16,15,14,14,14,16,18,19,20,23,28,30,32,34,37,39,44,45,46,47,48,48,48,48,45,44,43,41,38,36,34,33,32,32,33,33,32,31,30,30,29,29,29,29,30,31,32,33,39,42,47,54,60,65,68,69,70,73,77,81,86,90,93,95,91,85,76,68,63,63,65,68,73,74,75,74,72,69,65,63,65,67,71,76,85,97,110,118,134,137,139,135,126,115,108,104,101,101,102,104,105,106,105,104,103,103,103,105,109,115,123,127,133,130,125,116,107,100,98,97,104,110,118,123,123,116,106,100,89,83,73,64,61,64,71,77,90,99,103,98,90,88,89,89,93,98,102,101,95,92,94,97,102,105,108,108,105,101,101,101,101,106,111,115,123,131,130,125,117,109,96,85,80,81,87,92,98,101,103,98,89,80,77,76,77,82,91,99,106,112,117,121,124,125,121,110,98,86,71,59,52,56,63,69,71,65,55,47,40,41,41,39,38,39,42,45,52,59,65,62,52,40,35,33,47,61,79,88,83,70,55,46,45,50,57,60,57,51,45,41,45,51,61,71,74,69,57,48,40,38,38,39,41,41,38,35,31,36,42,51,67,84,94,95,94,82,68,56,45,36,35,38,40,40,40,36,33,33,38,43,55,62,70,72,67,60,55,53,50,45,43,45,44,39,39,42,39,36,33,30,28,28,29,30,31,35,44,56,70,85,97,104,96,91,77,60,51,50,47,41,45,45,45,48,53,57,60,61,56,46,35,30,27,29,37,46,54,58,58,54,51,49,44,37,31,27,23,22,25,28,31,32,32,31,29,26,23,21,19,19,20,25,33,42,49,53,54,55,53,52,51,48,45,45,47,49,53,57,63,67,66,60,53,49,37,32,25,21,20,22,24,25,27,29,33,36,36,34,31,29,29,30,32,34,35,36,37,37,39,43,50,57,62,64,65,65,62,61,59,59,60,58,55,52,43,39,32,26,22,22,23,25,24,27,29,30,28,25,24,24,22,22,21,21,20,21,21,21,26,28,33,39,47,54,60,63,72,73,72,68,60,49,38,32,22,21,19,18,19,20,23,24,29,31,34,36,35,31,26,23,21,18,15,12,11,12,14,15,17,18,20,21,22,22,21,21,20,19,18,18,19,18,16,14,14,13,12,11,10,10,10,10,8,8,8,9,9,10,10,10,8,8,8,8,8,8,8,8,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 16,16,17,18,19,21,22,23,19,21,23,26,27,27,26,25,22,22,21,21,20,19,19,18,18,17,15,14,14,15,17,18,19,22,26,29,30,32,34,37,39,40,40,42,43,44,45,46,42,42,43,43,41,39,37,35,32,32,32,32,31,29,28,27,26,27,27,28,30,32,33,34,38,41,47,54,61,67,71,73,79,82,87,93,99,102,105,106,101,95,85,76,71,70,73,75,84,84,84,83,80,77,73,70,73,76,80,85,92,102,112,119,131,134,136,132,122,112,104,101,100,100,102,105,108,110,110,109,112,113,115,118,123,129,135,139,137,134,128,119,109,102,99,99,111,119,132,143,146,141,132,126,108,99,86,74,68,70,77,83,92,101,105,100,93,91,93,94,95,100,104,101,93,88,89,92,93,98,103,105,102,99,98,98,99,103,106,108,115,123,123,116,117,110,99,91,88,93,100,106,108,111,112,105,92,80,74,72,74,80,87,94,99,104,107,110,108,109,105,96,87,78,66,56,50,54,61,68,71,66,55,47,40,39,36,34,34,38,45,50,58,65,70,66,54,42,37,36,57,72,90,100,94,78,61,50,42,48,55,58,55,48,42,38,41,48,59,70,75,71,59,49,40,38,37,39,42,42,40,37,32,36,40,47,62,79,88,89,91,80,67,56,46,37,34,37,39,40,41,38,36,36,40,45,56,63,71,73,68,61,56,54,48,42,39,42,41,37,39,44,39,37,33,30,29,29,30,30,32,34,38,46,56,69,80,86,86,83,72,57,49,48,43,36,41,40,40,42,47,51,53,54,52,42,32,27,26,27,35,43,49,52,53,50,47,45,41,35,31,27,24,23,25,29,32,34,34,32,29,26,23,20,18,17,22,27,36,46,53,57,58,58,53,52,50,46,42,40,42,43,46,50,55,58,57,52,46,41,35,30,22,18,18,21,24,26,32,35,40,44,45,42,38,35,29,30,33,35,37,39,40,40,43,47,55,62,68,71,72,72,69,67,65,64,64,62,58,55,50,45,38,31,26,25,26,27,22,25,28,29,27,25,24,24,21,21,20,20,20,19,19,19,21,23,28,34,41,48,54,58,69,69,68,64,57,46,36,30,23,22,21,20,20,22,25,26,31,33,36,37,35,31,25,22,20,18,14,11,10,10,12,14,14,15,17,19,19,19,18,18,17,16,15,16,17,16,14,12,13,13,12,10,10,10,10,10,8,8,8,9,9,10,10,10,8,8,8,8,8,8,8,8,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 17,17,18,19,20,20,21,21,20,21,23,25,26,25,23,22,24,24,24,23,22,21,20,19,19,19,19,19,19,19,19,19,20,20,21,23,26,29,31,33,36,36,36,37,37,37,37,37,40,40,40,40,40,39,38,37,35,34,32,30,28,27,26,26,31,30,29,29,31,34,37,39,40,43,48,53,58,63,70,74,76,82,91,100,108,113,115,116,107,102,93,84,79,82,89,95,99,105,105,98,91,88,87,84,89,92,96,103,109,114,118,120,127,127,126,125,121,114,104,97,91,96,104,110,114,118,121,123,124,125,127,130,134,137,139,141,141,134,126,118,106,97,100,109,116,128,144,156,165,167,160,150,137,126,110,96,89,87,88,90,97,99,100,97,95,94,98,101,103,110,111,102,93,88,83,77,86,90,94,96,95,93,92,91,87,92,97,97,96,97,103,108,105,111,115,115,119,125,130,130,133,125,114,103,94,83,72,64,70,75,80,86,95,101,98,92,92,85,81,84,83,75,64,59,54,56,60,67,72,71,65,59,49,42,37,38,40,43,50,58,65,71,74,67,54,44,43,46,68,89,111,117,107,89,69,56,47,51,56,58,55,48,40,34,36,43,54,65,69,64,53,45,33,33,33,36,40,43,43,43,39,39,41,46,55,67,78,84,82,75,64,51,42,38,37,37,39,42,44,44,42,41,44,46,55,58,63,65,63,58,52,48,43,42,42,43,45,46,44,42,37,35,33,32,34,36,36,36,34,33,34,37,45,55,64,70,73,70,65,58,51,44,39,37,34,34,35,36,38,40,42,43,37,34,29,26,27,32,38,42,47,47,46,45,43,40,37,35,28,26,25,26,29,32,33,33,34,31,28,24,21,20,21,21,26,32,41,50,55,56,55,53,47,45,42,38,37,36,37,37,40,42,45,47,47,44,40,38,29,28,26,23,22,24,28,32,40,47,54,55,55,53,46,39,34,33,33,35,39,43,44,44,46,50,58,66,72,76,78,79,76,72,68,68,71,71,67,63,56,51,44,38,34,30,26,23,28,29,30,32,32,32,31,30,27,26,24,22,20,19,19,18,21,23,26,30,35,40,44,46,52,53,53,51,46,39,31,27,22,23,25,27,29,31,32,33,35,34,34,34,34,31,26,23,16,15,14,12,10,10,9,9,9,11,14,16,17,17,15,14,13,13,14,14,14,15,15,15,13,13,13,13,12,11,10,9,8,9,11,12,13,12,11,11,10,11,11,11,11,10,9,8,8,8,8,7,7,6,6,6,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 17,17,17,18,19,20,20,21,20,21,23,25,25,25,23,22,24,24,24,24,23,21,20,19,19,19,19,19,19,19,19,19,19,20,20,22,24,26,28,30,32,32,32,32,33,33,33,33,37,37,38,39,39,39,38,38,37,36,34,32,30,29,29,28,32,31,31,32,34,37,41,43,43,45,49,52,56,61,67,72,77,83,92,102,110,115,117,118,110,105,97,89,87,91,100,107,112,117,118,111,103,99,96,92,102,105,111,117,122,125,127,127,127,126,125,123,119,112,103,97,94,99,105,111,115,119,122,125,131,133,135,137,139,140,141,141,137,131,125,118,108,100,103,111,121,135,152,166,178,182,176,167,150,140,125,113,105,103,103,103,107,107,106,103,100,100,103,107,110,117,117,107,97,92,86,80,83,86,90,90,88,84,82,81,76,80,83,83,81,83,89,95,103,113,125,134,145,155,159,159,153,142,125,109,95,82,70,62,69,74,81,88,96,100,95,87,83,76,71,74,75,69,62,58,55,56,60,66,72,72,68,63,54,47,42,41,42,44,50,58,67,72,74,67,55,47,47,51,75,96,117,122,112,95,75,61,50,54,59,61,58,51,43,37,37,43,52,60,63,59,50,42,31,30,31,35,39,42,43,43,40,40,41,45,53,64,74,80,79,72,61,50,42,37,36,37,40,43,46,46,45,44,45,47,51,54,57,59,58,54,49,46,42,42,43,45,48,48,45,43,38,35,32,32,34,37,38,38,37,35,33,33,37,44,52,57,65,63,60,55,49,42,37,34,30,29,29,29,30,32,34,35,35,32,29,27,28,31,36,39,44,44,44,43,41,38,36,34,28,26,25,25,28,31,32,33,33,31,27,24,22,21,21,21,28,32,40,47,51,51,49,47,40,38,35,33,32,32,33,33,33,35,37,39,39,37,35,34,30,29,28,25,25,27,32,36,46,55,62,64,64,61,52,43,36,34,33,35,38,42,43,44,47,51,57,64,70,73,75,76,73,69,65,66,69,70,67,63,58,54,47,41,36,32,28,25,28,30,33,35,36,35,33,32,29,27,25,23,21,20,19,19,21,22,25,29,33,36,38,38,40,41,41,40,37,32,27,24,22,24,26,29,31,33,33,33,34,33,32,32,32,29,25,21,16,15,14,12,11,10,10,10,9,11,13,15,16,16,14,14,13,13,13,13,14,14,14,15,12,13,13,13,13,12,11,11,9,10,12,13,14,13,12,11,10,11,11,11,11,10,9,8,8,8,8,7,7,6,6,6,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 16,16,17,17,18,19,20,20,20,21,23,24,25,24,23,22,24,24,24,24,23,22,21,20,19,19,19,19,19,19,19,19,19,19,19,20,21,23,24,25,26,26,27,27,28,28,28,29,31,32,34,36,37,38,39,39,39,38,36,34,32,32,31,31,33,33,33,35,38,41,45,47,47,48,50,51,54,58,64,68,75,80,90,100,108,113,116,117,108,104,98,93,93,101,112,120,127,133,134,127,118,112,107,102,113,118,125,132,135,136,134,132,130,127,124,121,118,113,107,102,102,106,112,116,120,123,127,130,134,136,137,139,138,137,135,133,127,123,118,113,106,100,103,109,121,136,155,172,185,192,188,180,163,155,143,132,125,122,120,119,116,114,110,105,102,102,105,109,115,120,119,111,102,95,91,87,87,89,91,89,83,76,71,69,64,66,67,66,65,68,74,80,98,114,136,156,175,188,192,189,175,160,137,114,96,81,69,62,68,76,85,94,101,103,95,85,76,68,62,64,67,65,61,60,56,56,58,64,71,73,71,68,60,53,47,45,44,45,49,56,67,71,72,66,56,52,55,61,84,103,121,124,114,97,78,64,53,56,62,64,62,55,47,41,39,42,48,53,55,51,43,37,28,28,29,33,38,42,44,44,43,42,42,45,51,59,68,73,72,66,57,47,40,36,35,36,41,44,48,49,49,48,47,48,47,48,49,50,49,47,45,44,42,43,46,50,52,51,48,44,39,36,32,32,34,38,41,42,41,37,33,30,31,36,43,47,54,54,53,50,45,38,32,28,26,26,24,24,24,26,27,28,33,31,30,29,29,32,35,36,39,39,39,38,37,35,33,32,28,26,24,25,28,30,31,31,31,30,27,24,23,22,22,22,29,32,37,41,43,42,40,38,30,29,27,26,26,26,27,28,28,28,30,31,32,32,32,31,32,31,30,29,29,33,38,43,54,63,73,76,74,69,58,48,39,36,34,34,37,40,43,44,48,51,55,60,64,67,69,69,67,64,62,63,66,67,65,62,60,55,49,42,38,34,29,27,29,32,36,39,40,38,36,34,30,29,26,24,22,20,19,19,21,23,27,31,33,33,32,31,30,30,30,29,28,26,24,23,23,26,30,33,35,35,34,33,32,31,30,29,29,27,23,19,16,15,14,12,11,10,10,10,9,10,12,14,15,14,13,13,12,12,12,13,13,14,14,14,12,12,13,14,14,14,13,13,11,12,14,15,16,15,14,13,11,11,11,11,11,10,9,9,8,8,8,7,7,6,6,6,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 15,15,15,16,17,18,18,19,20,21,22,23,23,23,22,22,23,23,24,24,23,22,21,20,19,19,19,19,19,19,19,19,19,19,18,18,19,19,20,21,22,22,23,24,24,25,25,26,27,28,31,33,36,37,38,39,39,38,36,34,33,32,32,32,32,32,34,36,40,44,47,49,50,51,51,51,52,55,61,65,70,75,84,94,102,107,109,110,101,98,94,91,94,104,117,126,136,142,144,137,127,120,114,109,115,121,130,138,141,140,136,133,132,129,125,123,122,119,116,114,115,118,121,124,127,130,134,137,137,138,140,140,138,135,131,128,124,122,119,114,108,104,105,108,115,129,148,165,179,186,183,175,164,158,150,143,139,136,133,131,122,118,110,103,98,98,101,103,112,115,115,110,104,100,99,99,102,103,103,97,87,76,67,62,57,58,57,56,56,59,65,70,90,111,139,168,192,207,209,205,186,168,141,115,96,82,73,68,72,81,93,103,111,112,103,91,77,67,59,61,64,64,63,63,56,55,56,61,68,72,72,71,64,56,49,47,44,42,46,51,62,65,66,63,58,58,64,71,91,106,120,120,109,92,73,60,52,57,62,66,64,58,50,44,41,41,43,45,45,42,36,32,26,26,28,33,39,44,46,47,46,45,44,45,49,56,62,66,64,59,52,44,39,36,35,35,41,44,48,51,51,50,49,48,44,43,42,42,41,42,42,43,43,45,50,54,57,56,51,47,40,37,32,31,34,39,43,45,43,40,35,32,33,38,44,48,51,51,50,47,42,34,27,22,25,25,24,24,24,26,28,29,32,32,32,32,32,33,34,35,34,34,34,34,33,32,32,32,29,27,25,25,27,29,30,30,30,29,27,25,24,24,24,24,30,31,33,34,34,33,30,29,24,24,23,22,23,23,24,25,27,27,27,28,30,31,33,33,34,34,33,33,34,39,45,50,60,70,80,83,81,74,61,50,41,38,34,32,35,38,41,43,46,47,50,53,56,59,61,61,61,59,58,59,61,62,61,59,58,54,47,41,37,33,29,26,29,32,37,42,43,42,38,36,30,29,27,24,22,21,20,20,23,26,32,36,38,36,33,31,29,28,27,25,24,24,25,25,24,28,33,37,39,38,35,33,30,29,27,26,26,24,20,17,16,15,14,12,11,11,11,11,9,10,12,13,13,13,13,12,12,12,12,12,13,13,14,14,12,13,14,15,16,16,15,15,14,15,16,17,17,16,15,14,11,11,12,12,11,11,10,9,8,8,8,7,7,6,6,6,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 13,14,14,15,16,17,17,17,19,19,20,21,21,21,21,21,22,22,22,23,22,22,21,20,19,19,19,19,19,19,19,19,19,19,18,18,17,18,19,19,21,21,22,23,24,25,25,26,25,26,29,32,34,36,37,38,37,36,35,33,32,32,32,32,30,32,34,37,40,44,47,49,52,53,53,53,53,55,59,63,67,72,80,89,96,100,101,102,93,91,88,88,92,101,114,123,135,142,144,138,129,122,116,111,114,120,129,137,141,140,137,134,131,129,127,127,129,131,132,131,128,130,131,132,133,135,139,142,145,146,148,148,146,143,139,136,134,133,130,124,118,115,112,111,112,124,140,154,166,172,169,162,156,153,149,147,146,146,144,143,130,123,112,103,97,95,96,97,105,106,107,106,104,104,109,115,119,120,119,111,96,80,65,57,53,54,54,54,54,56,59,62,80,102,133,165,193,211,213,208,188,170,142,115,96,85,77,73,77,87,100,111,120,121,112,100,80,69,61,61,65,65,64,65,56,54,54,58,65,70,71,70,62,55,48,45,41,38,40,45,52,56,60,61,60,64,71,78,95,105,113,110,98,82,65,52,49,54,60,64,64,59,52,47,42,41,40,39,38,35,31,27,26,27,29,34,41,46,49,49,49,48,46,46,48,52,57,60,56,52,47,42,38,35,35,35,41,43,46,49,51,51,49,47,42,41,38,37,36,38,40,41,45,48,52,57,60,58,52,48,41,37,33,32,35,40,44,46,46,44,40,38,39,43,48,51,54,53,50,45,38,30,22,18,23,24,25,26,28,30,31,32,32,33,33,34,34,34,34,34,30,30,30,30,30,31,32,32,30,28,26,26,27,29,29,29,29,29,28,27,27,27,27,27,29,29,29,28,27,26,24,24,25,25,25,24,24,24,25,25,27,27,27,28,29,31,33,35,35,36,36,36,38,43,50,55,65,75,83,85,82,75,62,51,41,37,33,31,33,37,40,41,41,42,43,46,48,51,53,55,57,56,55,55,56,56,55,54,52,48,42,36,33,30,26,24,28,31,37,41,43,42,39,37,30,29,27,25,24,23,22,22,28,32,39,45,47,45,41,38,33,31,28,25,24,24,25,25,26,29,35,40,41,39,36,34,29,27,25,24,23,21,18,16,16,15,14,13,12,12,12,12,11,11,12,12,12,12,12,12,12,12,12,13,13,14,14,14,13,14,15,16,17,17,17,16,15,16,18,18,18,17,16,15,11,12,12,12,12,11,10,9,8,8,8,7,7,6,6,6,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 12,12,13,14,15,15,16,16,17,17,18,18,18,19,19,19,20,20,21,21,21,20,20,19,19,19,19,19,19,19,19,19,20,19,19,18,18,18,19,19,21,21,22,23,24,25,26,27,25,26,29,31,33,34,35,36,36,35,34,32,32,31,31,31,30,32,34,37,41,44,46,48,51,53,55,55,56,57,60,62,67,72,79,86,91,93,94,93,86,85,84,84,88,96,107,114,123,130,133,127,120,116,112,108,111,116,123,129,133,133,131,129,124,123,125,129,136,143,147,148,143,143,143,141,140,141,145,148,153,154,156,157,157,155,153,151,149,149,145,136,128,123,116,110,115,125,136,145,154,159,156,149,145,144,144,147,151,155,157,157,143,134,121,110,102,98,96,95,100,98,98,100,100,104,114,125,127,129,129,121,105,84,66,55,50,52,54,56,57,57,56,55,69,87,116,147,177,197,202,198,178,160,134,110,94,84,78,75,79,89,100,111,119,121,113,102,80,70,63,65,68,67,65,65,58,55,54,57,63,67,68,66,58,51,44,41,38,34,36,40,45,51,57,61,64,68,74,79,92,99,101,95,83,71,57,46,44,50,57,63,64,60,54,49,43,40,37,36,34,31,28,25,27,27,30,35,42,47,49,50,49,48,46,45,45,48,51,54,49,47,44,40,38,36,35,35,39,40,42,45,48,49,47,45,42,39,36,34,33,35,37,39,46,48,52,57,58,56,50,46,40,37,33,33,35,39,42,44,48,46,45,44,45,48,52,54,60,56,50,42,34,27,21,18,22,24,27,30,32,33,33,33,32,33,33,34,34,34,33,32,27,27,27,28,29,31,33,34,33,30,27,27,28,29,30,29,29,30,30,30,30,30,30,30,29,28,27,26,25,25,25,25,31,31,30,29,28,27,27,26,27,27,27,28,29,31,33,34,36,37,37,37,40,45,52,57,68,76,82,81,77,71,60,49,37,34,31,30,33,36,38,38,37,37,38,39,42,46,50,52,55,54,53,52,51,50,49,48,45,41,35,31,28,26,23,21,26,29,34,38,41,40,39,37,31,31,29,28,27,27,27,27,34,39,46,52,54,53,49,46,36,34,30,26,24,23,23,24,28,31,36,40,41,40,37,34,28,26,23,22,21,20,17,15,16,15,14,13,13,13,13,13,12,12,12,12,12,13,13,13,13,13,14,14,14,15,15,15,15,16,17,17,18,17,17,17,16,17,18,19,19,17,16,15,12,12,13,13,12,11,10,10,8,8,8,7,7,6,6,6,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 11,12,12,13,14,15,15,15,15,15,15,15,16,16,17,18,18,18,19,20,20,19,19,18,19,19,19,19,19,19,19,19,21,20,20,19,19,20,21,21,21,21,22,24,25,26,27,28,27,28,30,31,32,33,33,33,36,35,34,33,32,32,32,32,32,33,36,39,42,45,46,47,49,52,56,58,59,60,62,63,66,70,76,81,84,85,84,83,79,79,79,79,82,88,95,101,103,110,113,108,103,102,101,98,102,104,108,112,114,115,114,114,112,114,119,128,140,151,158,161,162,160,158,154,151,152,155,158,163,164,166,168,170,172,172,172,171,171,165,152,142,134,124,114,116,123,130,135,141,145,142,136,133,134,137,145,154,162,167,169,156,146,132,119,110,104,99,95,96,91,88,89,90,95,109,123,128,132,135,129,112,89,68,56,49,52,57,62,63,61,56,51,56,70,92,118,145,165,171,168,151,137,115,97,86,80,77,74,78,85,94,102,109,111,104,93,80,72,67,70,74,72,69,68,61,58,57,59,64,67,66,64,53,47,41,38,35,32,34,38,43,50,58,65,68,71,74,76,82,85,84,76,67,58,48,40,41,46,55,62,64,61,56,52,43,40,37,34,32,30,26,23,26,27,29,34,40,46,48,48,47,45,43,42,42,43,46,47,44,43,41,40,38,37,36,36,37,36,37,40,44,46,45,42,41,38,35,32,31,32,34,35,46,47,50,53,54,51,46,42,40,37,34,34,36,39,40,40,45,46,48,51,55,59,62,64,64,58,49,39,30,25,22,21,26,29,33,37,38,37,35,33,31,31,31,31,31,31,31,30,26,26,26,27,29,32,34,36,35,32,29,28,29,30,30,29,30,30,31,32,33,33,33,33,31,29,27,26,26,28,30,31,38,38,37,35,33,30,28,27,29,29,30,31,32,33,34,34,37,37,38,38,40,45,52,58,64,70,72,69,65,60,51,42,33,31,29,30,32,35,36,36,34,34,34,36,40,45,50,53,55,54,53,50,47,44,42,42,38,34,30,26,25,23,21,19,23,26,30,34,36,37,37,37,34,33,33,32,32,33,33,34,40,44,50,56,58,56,52,49,38,36,32,29,26,25,24,24,29,32,36,39,41,39,37,35,28,25,22,21,20,19,17,15,16,15,14,13,13,13,13,14,14,14,13,13,13,13,14,14,14,14,15,15,16,16,16,16,17,18,18,19,18,18,17,16,17,18,19,19,19,17,15,14,12,12,13,13,12,12,11,10,8,8,8,7,7,6,6,6,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 11,11,12,12,13,14,15,15,14,14,14,14,14,15,16,17,17,17,18,19,19,18,18,17,19,19,19,19,19,19,19,19,21,21,20,20,21,21,22,23,21,21,22,23,25,26,27,28,29,29,31,32,32,32,32,32,36,36,35,33,33,33,33,33,33,35,37,40,43,45,47,47,47,51,57,60,61,62,63,64,64,67,72,76,78,78,76,74,74,74,75,75,76,80,86,90,86,93,96,92,89,89,90,88,91,92,93,95,96,97,97,97,104,107,114,126,141,154,162,166,176,174,171,166,162,162,165,168,176,177,179,182,186,189,191,193,194,194,186,172,159,150,137,125,113,118,123,126,130,134,132,126,124,126,132,141,154,165,172,175,163,153,138,125,115,107,100,95,93,85,80,80,80,85,100,116,127,133,137,133,117,94,72,59,50,55,62,68,70,65,57,51,47,57,73,93,116,135,141,138,125,113,97,84,78,76,75,74,76,81,88,93,99,101,94,84,80,74,71,76,81,79,74,72,64,61,59,61,65,67,65,62,51,44,39,37,34,31,33,37,44,51,61,68,71,72,72,73,71,73,70,62,54,49,42,35,39,45,54,61,65,63,58,54,43,40,37,34,32,29,26,23,25,26,28,33,39,44,46,46,45,43,41,39,39,40,42,43,41,41,40,39,38,37,37,37,36,34,34,36,41,43,43,41,40,37,34,30,29,29,31,32,45,45,47,49,50,48,43,38,39,37,35,34,36,38,38,38,40,43,49,56,63,70,74,76,65,58,47,36,28,24,24,24,31,34,39,43,44,41,37,33,29,29,29,29,29,28,29,29,26,26,26,27,30,33,36,37,36,33,30,29,30,31,31,30,30,31,32,34,35,35,35,35,32,31,29,28,29,31,34,37,43,42,40,38,35,32,29,27,32,33,34,35,36,36,36,36,37,37,38,38,40,45,52,57,58,62,63,58,54,49,42,34,30,29,28,30,32,35,35,35,33,33,33,35,40,45,51,55,55,55,53,49,44,40,39,38,35,31,27,24,23,22,21,19,22,24,27,31,34,35,36,36,36,36,35,35,36,37,38,39,43,47,52,57,58,56,52,49,39,37,35,31,29,28,27,27,30,32,36,39,40,39,37,36,28,25,22,20,20,19,17,15,15,15,14,13,13,13,14,14,15,15,14,13,13,14,14,15,15,15,16,16,16,17,17,17,19,19,19,19,19,18,16,16,17,18,18,19,18,17,15,14,12,13,13,13,13,12,11,10,8,8,8,7,7,6,6,6,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 10,10,10,11,11,12,12,12,12,12,12,13,13,14,14,14,15,15,15,16,16,17,17,17,18,18,18,19,19,20,20,20,21,21,21,21,21,22,23,24,24,25,25,26,27,28,29,29,29,30,31,30,30,30,33,35,37,38,40,40,40,39,38,37,40,42,45,48,49,48,46,45,51,55,59,61,66,71,70,65,68,65,67,72,75,73,72,74,73,77,81,82,85,87,83,76,76,75,74,73,74,76,78,80,84,84,85,85,86,87,88,89,87,93,104,120,138,155,170,178,189,190,190,188,186,186,187,188,186,190,194,195,197,203,214,222,222,219,208,191,176,163,145,130,122,119,118,120,121,119,117,117,113,117,125,135,147,160,172,180,175,163,147,134,123,114,103,95,90,80,72,69,71,77,88,99,114,122,128,123,111,95,75,60,46,52,62,73,80,80,74,69,55,54,57,70,89,104,110,111,99,91,81,73,70,69,68,67,71,73,76,77,78,80,83,86,73,80,85,84,85,87,81,71,63,61,59,61,68,74,70,62,55,46,38,35,33,33,38,45,52,58,66,72,74,72,70,68,64,58,54,52,48,41,38,40,40,46,53,59,65,68,63,55,46,46,43,37,31,26,24,25,24,24,26,29,34,38,40,41,41,41,40,37,35,36,39,41,39,43,45,43,43,45,42,38,35,33,31,31,35,38,41,41,37,35,31,28,27,28,29,31,34,38,44,47,47,46,45,44,39,39,39,39,38,36,34,33,39,45,54,65,74,80,82,82,70,60,47,37,27,21,23,29,39,42,47,50,49,43,36,31,29,28,27,26,26,27,29,30,33,32,31,31,31,33,35,36,36,34,32,29,28,27,27,28,30,31,33,35,36,37,38,38,37,35,34,34,36,40,45,49,52,53,52,46,38,31,29,29,34,35,37,38,40,41,42,42,40,39,38,37,39,41,44,46,50,49,46,43,39,36,33,31,26,27,29,31,33,33,33,32,37,35,34,36,40,47,55,59,53,52,51,48,44,39,34,31,29,29,28,27,26,25,24,24,21,22,25,28,30,32,33,33,37,38,40,42,44,45,46,46,50,51,54,57,57,53,46,41,36,34,32,29,28,27,27,28,31,33,37,40,40,38,35,33,31,29,26,23,21,20,20,21,15,15,15,15,15,15,15,15,15,15,14,13,12,12,11,11,15,15,16,16,16,17,17,17,18,19,19,19,19,18,17,16,16,17,17,17,17,16,15,14,12,12,12,11,11,10,10,10,7,7,7,6,6,5,5,5,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 10,10,10,11,11,12,12,12,12,12,12,13,13,14,14,14,15,15,15,16,16,17,17,17,18,18,18,19,19,20,20,20,21,21,21,21,22,24,25,26,26,26,27,27,28,29,29,29,29,30,31,30,30,31,34,36,40,41,44,46,46,46,44,43,46,47,50,51,52,51,49,48,52,58,62,65,70,75,73,68,72,69,70,74,77,76,78,81,78,84,91,94,98,99,94,86,79,76,72,69,70,74,79,82,86,86,85,84,83,83,83,83,84,92,106,122,140,158,175,185,197,200,205,206,206,204,204,204,202,204,207,207,208,213,222,230,234,231,219,201,185,171,153,138,129,125,121,119,116,112,108,106,106,111,120,133,147,162,176,183,177,166,152,139,129,118,107,99,86,77,68,65,65,69,78,88,103,112,120,117,108,94,76,61,49,53,63,76,86,90,86,81,64,60,58,64,75,85,87,86,84,79,72,68,69,71,73,73,68,69,70,69,69,71,74,77,83,89,93,91,89,86,77,67,57,58,59,63,73,80,76,68,55,46,39,36,37,38,43,50,56,61,67,72,73,70,67,65,56,51,48,47,44,38,37,40,43,50,57,63,69,72,67,58,50,48,43,37,31,28,26,26,23,23,24,26,29,31,32,33,34,34,34,32,30,31,34,37,38,44,47,47,47,49,46,41,36,34,32,32,35,39,41,41,38,36,32,29,28,29,30,31,33,37,43,46,46,45,44,44,41,42,42,42,40,38,35,34,39,44,54,66,75,80,80,80,67,57,45,36,28,24,28,34,42,45,49,50,48,43,36,31,27,27,27,27,28,30,31,33,35,35,34,33,33,34,35,35,35,34,31,29,27,26,27,27,30,31,34,37,39,39,39,39,39,37,36,36,39,43,48,51,54,54,52,46,39,33,31,32,35,36,39,41,43,44,44,43,41,40,38,36,36,37,39,41,41,40,37,34,31,28,26,25,27,29,31,34,36,36,35,35,35,35,35,37,41,48,54,58,55,54,51,47,43,37,33,31,31,31,30,30,28,27,25,25,21,22,24,26,29,31,33,34,38,39,42,45,47,49,51,51,52,53,54,55,54,49,42,36,32,31,29,27,26,27,28,28,30,32,36,40,41,40,37,36,33,31,28,25,23,21,21,21,17,17,17,17,17,17,17,17,16,15,15,14,13,12,12,11,15,15,15,16,16,16,17,17,18,18,19,19,18,17,16,16,16,16,17,17,16,15,14,14,12,12,11,11,11,10,10,10,7,7,7,6,6,5,5,5,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 10,10,10,11,11,12,12,12,12,12,12,13,13,14,14,14,15,15,15,16,16,17,17,17,18,18,18,19,19,20,20,20,21,21,21,22,23,25,27,28,28,29,29,29,29,29,29,29,29,30,31,30,30,32,36,38,45,48,51,55,57,57,55,54,55,55,56,56,55,54,53,52,55,62,69,74,79,83,80,73,73,69,67,70,72,74,78,84,88,97,107,115,120,121,114,105,90,84,76,69,69,75,83,89,100,99,98,96,94,92,90,89,89,99,113,127,142,161,181,194,212,218,226,231,232,230,228,227,223,224,224,222,221,224,231,237,246,242,230,212,195,179,162,150,140,136,129,122,116,110,104,99,101,105,115,128,144,161,174,181,176,168,156,144,132,120,107,98,83,74,65,62,60,62,69,77,89,99,108,110,105,94,77,63,52,54,62,78,94,103,102,98,85,77,69,67,70,73,73,71,71,68,64,64,67,72,75,77,72,72,71,69,68,69,72,75,91,97,100,97,92,84,72,62,52,56,62,69,80,86,82,73,56,48,41,40,42,44,49,55,60,63,67,70,70,67,63,60,51,46,43,43,42,39,40,43,47,55,63,69,74,76,71,63,55,50,42,36,32,30,29,28,27,27,28,27,27,26,25,25,28,29,28,27,26,28,32,35,38,45,51,53,55,56,53,48,40,37,34,34,37,40,41,42,39,37,34,32,30,31,32,33,34,38,42,44,44,44,44,44,45,46,47,47,46,42,38,36,38,43,53,65,75,79,78,76,63,53,41,34,30,28,33,40,45,47,49,49,46,41,34,30,25,26,27,28,31,33,36,37,39,39,38,37,36,35,35,34,34,33,30,28,26,25,26,26,29,32,36,40,42,42,41,40,40,40,39,40,42,46,50,53,55,54,51,45,39,35,34,35,36,39,42,44,46,46,45,44,42,40,37,34,32,32,33,34,32,31,29,26,25,23,23,23,31,33,36,38,39,39,37,36,34,34,35,38,42,48,53,57,58,56,52,47,42,37,33,31,32,33,33,33,32,30,27,26,23,23,23,25,27,30,33,35,39,41,44,48,52,55,57,58,56,56,55,53,50,44,36,30,26,26,25,25,25,27,29,30,30,32,36,39,41,40,39,37,34,32,29,26,23,22,21,21,19,19,19,19,19,19,19,19,17,16,16,15,14,13,13,12,14,14,15,15,15,16,16,16,17,17,18,18,17,17,16,15,15,15,16,16,15,15,14,13,12,11,11,11,10,10,10,10,7,7,7,6,6,5,5,5,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 10,10,10,11,11,12,12,12,12,12,12,13,13,14,14,14,15,15,15,16,16,17,17,17,18,18,18,19,19,20,20,20,20,20,21,22,24,26,28,30,31,30,30,30,30,30,29,29,29,30,31,31,32,34,39,42,51,55,61,66,69,69,68,67,64,62,61,59,57,55,55,54,58,66,76,83,90,93,89,82,76,71,68,69,70,73,81,90,101,112,127,138,146,149,142,132,117,108,96,86,84,90,101,108,119,121,123,123,121,116,111,108,109,117,127,136,147,166,189,206,231,236,244,248,249,248,247,247,240,239,237,234,231,232,236,239,247,241,230,215,199,184,172,164,155,153,145,135,126,118,108,100,99,101,109,121,137,153,165,172,172,165,155,142,128,113,98,88,78,71,64,62,61,62,67,74,82,92,101,104,102,93,78,64,54,53,59,76,97,112,115,112,103,94,82,74,72,72,70,68,68,66,65,65,68,71,75,77,78,78,76,74,72,73,76,79,92,97,100,97,89,77,65,57,50,58,68,78,88,92,86,76,61,51,44,44,47,49,53,58,60,61,64,66,66,64,60,56,51,46,43,43,43,42,45,49,53,61,69,73,77,77,72,65,58,51,42,35,32,32,32,31,37,38,39,37,33,29,25,24,26,26,27,27,27,30,34,38,41,49,57,61,63,65,61,55,46,43,40,39,40,42,43,43,39,38,36,34,33,34,35,36,37,40,43,44,44,43,44,45,49,51,54,55,53,48,43,39,37,42,51,63,74,78,76,72,61,50,39,33,31,31,36,43,46,47,47,46,42,36,31,28,24,25,27,31,34,38,41,43,43,43,42,40,38,36,35,34,34,32,30,27,25,25,25,25,29,32,38,42,45,44,43,41,40,40,40,42,44,47,49,51,52,50,46,41,37,35,35,36,38,40,43,46,47,46,45,43,41,38,34,30,28,27,27,27,27,27,27,27,28,29,30,31,38,39,41,42,41,39,37,35,32,33,35,38,43,48,53,55,58,56,52,48,43,39,36,34,33,34,35,35,34,32,30,28,25,24,24,25,27,31,35,37,41,43,47,52,57,60,63,64,60,58,55,51,46,39,31,25,23,23,23,23,25,28,31,32,32,34,36,39,39,38,37,35,33,31,28,24,22,20,19,19,19,19,19,19,19,19,19,19,17,17,16,16,15,14,13,13,13,14,14,14,15,15,15,15,16,16,17,17,16,15,14,14,14,14,15,15,14,13,12,12,11,11,11,10,10,10,9,9,7,7,7,6,6,5,5,5,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 10,10,10,11,11,12,12,12,12,12,12,13,13,14,14,14,15,15,15,16,16,17,17,17,18,18,18,19,19,20,20,20,20,20,21,22,24,26,28,30,31,31,31,30,30,30,30,30,31,31,32,33,34,38,43,47,58,62,70,77,81,81,79,78,71,68,64,59,56,55,55,55,61,71,83,92,101,105,101,93,88,82,77,76,76,80,91,102,114,128,145,160,172,177,172,163,150,141,127,116,113,119,129,136,145,149,154,158,157,151,144,140,140,144,150,154,163,181,206,225,247,250,254,255,255,255,255,255,251,250,248,244,240,238,238,239,241,234,225,213,201,190,184,182,178,178,171,157,143,131,115,101,96,96,100,111,127,144,156,162,167,162,152,139,122,104,87,77,69,64,61,63,64,65,69,75,82,90,97,100,99,93,78,65,54,51,54,70,93,111,117,117,111,102,88,77,71,68,66,65,69,69,70,70,71,73,76,78,79,79,79,77,76,76,79,82,90,92,94,90,79,65,55,50,49,61,76,89,98,100,91,80,65,55,47,47,51,53,55,58,57,56,57,59,62,61,57,54,52,46,43,43,44,44,48,54,58,66,73,74,74,74,69,63,56,50,42,35,32,32,33,35,45,49,52,51,44,36,30,27,25,26,27,28,30,33,39,43,47,55,64,68,71,73,68,62,55,51,46,44,44,44,44,43,39,38,37,37,37,38,39,40,42,43,45,45,43,43,44,45,52,55,59,61,60,54,47,43,37,40,48,60,70,75,72,68,60,49,38,35,34,34,37,42,45,44,43,40,35,31,26,24,23,25,28,33,38,42,46,47,47,45,43,41,38,36,34,33,34,32,30,27,25,25,25,25,30,33,38,42,45,44,42,41,39,39,40,41,43,45,46,46,46,43,39,36,35,35,35,36,39,40,42,44,44,43,41,40,37,35,31,27,24,23,23,24,25,27,30,33,36,39,41,42,45,45,44,42,40,37,34,33,32,33,35,38,43,48,52,55,58,56,54,50,46,42,39,38,33,34,35,35,35,34,32,32,29,28,28,29,31,35,39,41,44,46,50,54,58,62,64,65,62,59,54,49,43,36,29,23,22,22,22,23,26,29,32,34,34,35,36,37,36,34,32,30,30,28,25,21,19,17,17,17,17,17,17,17,17,17,17,17,17,17,16,16,15,14,13,13,13,13,13,13,14,14,14,15,15,15,15,15,15,14,13,13,13,13,13,13,13,12,11,11,11,11,10,10,10,9,9,9,7,7,7,6,6,5,5,5,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 10,10,10,11,11,12,12,12,12,12,12,13,13,14,14,14,15,15,15,16,16,17,17,17,18,18,18,19,19,20,20,20,21,21,21,22,23,25,27,28,30,30,30,30,30,30,30,30,33,33,34,35,37,41,48,52,63,69,78,86,90,90,88,86,77,73,66,59,55,53,54,55,64,75,88,100,110,116,112,106,98,92,86,83,82,85,98,110,126,140,159,176,192,201,199,193,177,169,158,149,147,152,161,167,186,191,197,201,202,197,192,187,180,182,183,185,192,208,229,245,255,255,255,255,254,254,255,255,255,255,255,252,248,244,240,238,234,227,218,210,202,197,198,203,207,210,203,186,167,149,125,104,93,91,92,101,118,136,150,157,162,158,148,134,116,96,80,71,58,55,56,62,65,67,72,77,84,89,93,95,95,90,77,64,53,49,50,63,83,101,111,114,116,107,93,81,72,67,64,63,69,71,73,74,74,76,79,81,82,83,83,82,81,80,82,84,86,86,84,80,68,54,47,47,53,68,87,102,110,109,97,85,66,56,47,49,53,55,56,58,55,53,52,54,58,59,55,52,49,44,40,41,42,44,50,57,63,69,73,71,67,66,62,57,50,47,41,35,30,30,34,37,51,57,64,65,57,46,38,33,26,28,29,31,34,38,44,49,55,63,71,75,77,78,74,68,62,57,52,47,45,44,42,41,38,38,38,39,41,42,44,45,45,46,46,43,41,40,41,43,50,54,60,64,63,57,49,44,37,38,43,54,66,71,69,64,60,49,40,39,39,39,40,43,43,41,38,34,30,26,23,22,23,25,30,36,41,46,49,51,48,46,42,39,36,34,34,34,34,33,30,28,26,25,26,26,31,33,37,40,42,41,40,39,38,39,40,41,41,41,41,41,40,38,36,35,37,38,38,38,39,39,39,38,37,36,34,34,32,30,27,24,23,23,23,24,27,30,35,41,46,48,49,49,48,46,43,39,36,33,32,32,33,33,34,37,41,47,52,55,59,59,57,54,50,45,41,38,32,32,32,33,33,34,35,35,33,33,34,35,38,41,44,46,48,49,52,55,58,59,61,61,59,55,50,45,40,34,27,23,22,22,22,23,25,28,30,32,33,34,34,33,32,29,27,26,26,24,21,18,16,15,15,16,16,16,16,16,16,16,16,16,17,16,16,15,14,13,13,12,12,12,12,13,13,13,14,14,13,14,14,14,14,13,12,11,11,12,12,12,12,11,10,9,10,10,10,10,9,9,9,8,7,7,7,6,6,5,5,5,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 10,10,10,11,11,12,12,12,12,12,12,13,13,14,14,14,15,15,15,16,16,17,17,17,18,18,18,19,19,20,20,20,21,21,21,21,22,24,25,26,28,28,28,29,30,30,31,31,34,35,36,37,39,44,51,57,67,73,83,92,96,96,93,90,82,77,68,60,55,53,54,55,67,78,92,104,116,124,122,116,108,102,96,92,89,92,104,118,136,149,168,187,205,218,221,217,208,203,196,192,192,197,204,209,230,232,235,238,238,237,236,234,226,225,223,222,226,235,247,255,255,255,255,255,253,253,255,255,255,255,255,255,252,246,239,235,228,220,212,206,201,200,208,219,233,239,235,217,196,173,143,117,99,93,90,96,111,129,143,150,154,150,141,127,109,90,75,67,52,51,55,63,68,70,74,80,84,86,88,88,89,86,75,63,52,49,49,56,72,90,103,109,113,105,93,82,74,69,66,65,70,73,75,75,74,74,76,78,81,83,84,83,80,78,77,77,77,74,73,70,61,51,50,56,67,83,103,116,120,114,98,83,64,53,46,48,55,58,59,60,56,53,51,52,56,57,54,50,46,40,37,39,42,46,54,62,66,71,72,65,59,56,53,49,42,43,42,35,28,27,33,40,55,65,76,79,71,58,48,42,31,33,35,38,41,47,53,58,63,70,77,79,81,81,77,71,66,61,54,48,45,42,39,37,36,37,38,41,43,46,48,49,47,47,45,41,37,36,37,38,45,51,59,64,63,57,49,43,37,36,39,49,61,68,66,62,60,50,43,44,47,47,46,48,42,39,35,31,27,24,22,22,23,26,31,38,44,48,51,53,49,45,40,36,33,32,33,34,35,34,31,29,27,26,27,27,32,33,35,37,38,38,37,37,38,39,40,41,41,39,37,36,38,36,36,38,42,44,44,43,38,37,34,32,29,28,27,27,27,26,23,22,22,23,25,27,33,37,44,51,55,55,54,52,46,43,39,34,32,31,32,33,34,33,33,35,39,46,52,57,63,63,62,59,54,47,40,35,30,29,29,29,31,33,36,38,37,38,40,42,44,47,49,50,51,52,53,54,55,55,55,55,53,49,44,39,35,31,26,22,22,22,21,21,23,25,27,28,29,30,30,29,28,26,25,24,23,21,19,17,15,15,16,16,16,16,16,16,16,16,16,16,16,15,15,14,13,12,12,11,11,11,12,12,12,13,13,13,13,13,13,13,13,12,11,10,11,11,11,11,11,10,9,8,10,10,10,9,9,9,8,8,7,7,7,6,6,5,5,5,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 10,10,10,11,11,12,12,12,12,12,12,13,13,14,14,14,15,15,15,16,16,17,17,17,18,18,18,19,19,20,20,20,21,21,21,21,21,22,23,24,26,27,27,28,29,30,31,32,36,36,37,38,41,46,54,59,69,76,86,94,99,99,95,92,85,79,70,61,55,53,54,56,68,79,94,107,120,128,128,123,119,114,108,103,99,101,114,128,141,154,172,191,211,227,233,230,238,236,233,232,234,239,245,249,254,254,253,253,253,255,255,255,255,255,253,250,249,251,254,255,254,255,255,255,254,253,254,255,254,254,255,255,252,245,236,230,225,215,207,203,199,200,212,226,247,255,255,239,218,194,161,132,107,99,92,94,106,123,136,142,146,143,135,121,103,86,72,65,52,52,56,65,71,74,78,83,81,83,83,82,84,83,73,61,52,49,48,53,66,82,96,105,102,96,87,77,71,67,66,66,73,75,77,76,72,70,71,72,74,76,78,76,72,68,65,64,66,64,63,64,58,53,59,69,82,98,117,126,126,114,94,76,61,51,44,48,55,59,61,62,59,55,51,52,56,56,53,48,44,39,36,39,44,49,59,68,68,72,70,62,54,50,47,44,37,41,42,35,26,25,32,41,59,71,84,89,81,68,56,50,37,39,42,45,49,54,61,66,68,75,80,81,82,83,79,73,68,62,55,48,43,40,36,34,35,36,38,42,45,48,50,52,47,46,43,39,34,32,33,35,41,48,56,62,62,56,47,41,38,35,37,46,58,65,64,60,59,51,45,48,53,53,51,52,42,39,34,29,25,23,22,22,24,27,32,39,45,49,52,54,49,45,39,33,30,31,33,35,36,34,32,29,28,27,27,28,33,33,34,35,36,36,35,35,39,40,41,42,41,38,35,34,38,37,37,41,47,50,49,47,38,35,31,27,24,23,23,23,24,23,21,21,22,24,27,29,40,45,52,58,61,60,57,54,44,40,35,31,29,30,33,35,35,33,32,34,38,45,53,57,67,67,66,63,56,47,38,32,28,27,26,26,29,33,37,40,40,41,44,46,49,51,52,52,53,54,54,54,53,52,51,51,48,45,40,35,32,29,25,22,22,21,20,20,21,22,24,25,26,26,26,27,26,25,24,24,22,20,18,17,16,16,17,17,17,17,17,17,17,17,17,17,15,15,14,13,12,12,11,11,11,11,11,12,12,12,13,13,12,12,13,13,12,12,11,10,10,10,11,11,10,10,9,8,10,10,10,9,9,8,8,8,7,7,7,6,6,5,5,5,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 10,10,11,11,11,12,12,12,11,11,12,12,12,13,13,13,14,14,15,15,15,16,16,16,15,15,16,17,18,18,19,19,20,20,20,20,20,20,20,20,22,23,24,24,25,27,31,34,32,34,38,41,44,48,52,56,67,71,79,90,98,101,97,93,87,79,68,60,57,57,57,56,68,78,93,108,119,127,131,134,126,117,114,116,115,113,124,140,149,161,179,197,212,227,239,247,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,253,254,255,254,253,253,249,253,255,254,249,242,233,225,214,209,204,199,193,195,212,232,251,253,253,251,241,216,176,144,119,105,94,95,105,117,129,138,147,145,137,122,104,88,77,73,59,58,59,63,69,75,78,79,78,78,77,75,74,72,71,71,57,58,60,63,69,78,88,95,99,96,90,82,73,67,65,65,77,79,81,80,76,72,68,67,65,67,68,67,62,59,60,61,63,62,60,56,55,61,74,84,101,118,131,130,123,111,88,65,52,48,45,49,57,64,66,65,60,58,57,56,55,53,49,45,43,37,32,34,44,57,66,71,79,74,67,58,45,34,32,36,38,42,44,38,29,27,35,43,58,70,85,90,83,70,58,52,40,42,44,49,55,61,66,70,72,75,79,82,82,79,75,72,62,57,50,43,37,33,32,32,28,31,37,42,47,49,51,51,46,43,39,34,31,30,29,29,34,43,54,61,60,52,43,37,32,38,45,50,58,65,64,60,59,55,53,53,57,58,57,54,47,41,33,26,22,21,21,20,23,27,33,40,45,49,51,52,47,43,37,33,31,33,37,40,41,40,38,33,28,25,25,26,29,32,35,35,33,32,35,39,38,41,44,45,43,41,39,39,40,44,50,57,61,61,56,52,47,39,29,24,23,23,23,22,22,22,21,21,23,26,30,32,40,45,52,57,58,55,50,46,33,31,29,29,31,34,36,36,35,34,33,35,39,47,54,59,63,63,63,59,52,43,34,28,21,21,22,25,28,32,36,38,42,43,45,47,49,51,53,54,52,51,49,47,45,43,41,40,35,34,33,31,28,25,22,20,18,18,18,19,20,21,22,23,24,23,23,22,21,21,20,20,19,18,16,14,14,14,15,16,15,15,16,17,17,17,16,16,13,13,13,12,12,11,11,11,13,12,12,11,11,12,12,13,12,12,12,11,11,10,10,10,11,11,11,10,10,9,9,9,10,10,10,9,9,8,8,8,8,8,8,7,7,6,6,6,6,6,6,5,5,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 9,10,10,10,11,11,11,12,11,11,11,11,12,12,12,13,13,13,13,14,14,15,15,15,14,14,15,16,17,17,18,18,20,20,20,20,20,20,20,20,20,22,23,23,24,26,30,33,32,35,38,41,43,47,51,55,64,67,75,85,94,97,94,91,90,83,73,67,64,64,63,63,73,83,97,111,122,130,137,140,137,129,127,129,127,124,133,148,156,165,181,197,212,227,240,248,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,251,243,234,225,218,206,202,198,194,187,188,204,221,243,249,255,254,244,219,180,149,125,111,99,99,108,119,130,139,143,141,134,122,106,92,82,78,66,65,65,67,72,76,78,78,72,70,68,66,66,68,69,71,65,66,67,69,73,80,88,94,100,98,93,86,78,74,72,73,77,79,81,79,75,69,65,64,60,62,63,61,57,54,55,56,54,56,58,58,62,71,84,95,108,122,130,126,116,103,80,59,46,43,43,49,58,66,68,68,66,64,62,61,59,55,51,47,41,37,34,39,51,65,75,81,81,74,64,53,40,29,29,34,40,46,49,45,36,31,34,40,52,64,79,85,80,69,58,53,41,43,45,49,54,60,64,67,72,74,77,79,78,74,70,67,57,53,47,40,35,32,31,31,29,32,37,43,47,49,50,50,45,42,38,33,30,29,29,30,35,42,52,58,56,49,42,37,32,40,48,54,62,68,67,61,57,54,52,54,58,60,59,57,49,42,33,26,22,21,21,21,23,27,32,39,44,49,51,52,48,44,39,35,33,36,39,42,42,41,38,33,27,25,25,26,30,33,36,36,34,34,37,41,41,44,47,48,46,44,42,42,47,51,58,66,70,70,64,60,50,43,33,28,27,28,27,26,28,27,25,25,26,28,30,32,40,44,49,52,52,48,42,37,28,26,25,27,31,35,37,37,34,33,33,34,39,46,53,58,63,62,60,55,47,38,30,26,19,20,22,25,28,33,37,39,42,44,46,48,49,50,51,51,47,46,44,42,39,37,35,34,31,30,29,27,25,22,20,19,16,16,16,17,18,19,21,22,23,23,23,22,21,21,21,20,21,20,18,16,15,15,16,16,16,16,17,17,17,16,15,15,13,13,12,12,12,11,11,11,12,12,12,12,12,12,12,12,12,12,12,11,11,11,10,10,11,11,11,10,10,9,9,9,10,10,9,9,9,8,8,8,8,8,7,7,7,6,6,6,6,6,6,5,5,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 8,9,9,9,10,10,10,11,10,10,10,11,11,12,12,12,11,12,12,12,13,13,13,14,13,13,14,14,15,16,17,17,20,20,19,19,19,19,19,19,19,20,21,22,22,24,28,31,33,35,39,41,43,46,49,52,58,61,68,77,85,89,89,87,90,85,79,74,72,72,71,71,80,87,99,111,123,133,141,146,149,144,143,146,144,141,148,160,167,174,185,199,213,228,242,250,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,253,255,255,255,255,255,255,255,255,255,248,239,228,217,208,203,194,193,191,186,180,180,191,204,224,235,245,247,237,213,178,151,130,116,104,104,111,121,131,138,137,136,131,122,109,97,88,84,74,73,71,71,73,75,75,74,64,61,57,55,57,63,69,74,82,83,84,84,86,90,97,102,106,104,100,94,87,83,81,82,79,81,82,79,73,67,62,60,56,57,56,54,51,49,49,50,49,53,58,63,70,80,92,102,112,121,124,115,102,88,67,49,39,39,42,50,61,69,73,73,74,71,68,65,62,57,51,47,39,36,36,44,58,74,85,90,85,75,62,48,33,24,26,34,45,52,59,56,46,37,35,36,45,56,70,77,74,66,57,52,42,43,45,48,52,56,59,61,67,68,71,72,70,66,62,59,50,47,43,37,33,31,31,31,31,34,39,44,47,48,48,47,44,41,36,31,28,28,30,31,36,42,50,54,52,47,42,39,37,45,54,61,68,72,69,62,54,52,51,55,60,64,63,61,52,44,34,26,22,21,21,22,23,26,31,37,43,47,51,52,49,45,41,37,37,39,43,46,44,42,38,32,27,24,25,27,32,36,39,39,37,37,40,43,46,49,53,54,51,49,47,46,53,58,67,76,81,79,74,68,57,49,40,35,35,36,35,34,36,34,32,30,29,29,31,32,37,40,43,44,42,37,30,26,20,20,21,25,31,36,39,39,35,34,34,35,40,46,53,57,63,60,55,48,40,32,25,21,18,19,21,25,29,33,37,39,42,44,46,48,49,48,47,45,39,38,37,34,32,30,28,27,26,25,25,24,22,20,18,17,14,15,15,16,17,19,21,22,24,24,23,23,23,22,22,22,24,22,20,18,16,16,16,16,17,17,17,17,16,15,14,13,12,12,12,12,11,11,10,10,11,12,13,14,14,13,12,11,12,12,12,12,11,11,11,10,11,11,11,10,10,9,9,9,10,9,9,9,8,8,8,8,8,7,7,7,6,6,6,6,6,6,6,5,5,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 8,8,8,9,9,9,10,10,10,10,10,10,11,11,12,12,10,11,11,11,12,12,12,13,12,13,13,14,15,15,16,16,20,20,20,20,19,19,19,19,18,19,20,21,21,23,27,31,33,36,39,41,42,44,46,48,51,54,60,67,74,79,81,82,86,84,82,80,80,80,79,79,85,91,101,111,122,134,144,151,157,156,159,164,163,161,165,174,180,184,191,202,216,232,246,254,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,253,255,255,254,252,253,254,254,251,242,231,219,205,192,185,183,181,183,183,180,174,172,178,186,197,209,221,223,214,195,168,148,131,117,106,107,114,122,130,136,133,132,127,119,109,99,91,86,80,77,74,73,72,71,69,67,59,55,51,49,53,63,73,80,96,97,98,98,99,103,107,111,117,115,111,104,96,90,88,87,83,84,84,80,73,65,60,57,53,53,52,50,48,47,47,47,51,55,61,68,74,82,91,98,106,110,107,96,83,71,55,41,35,38,44,54,65,74,79,80,80,77,73,68,64,57,51,46,39,37,39,49,64,79,89,94,89,77,61,45,30,23,27,36,51,60,68,66,56,44,36,34,41,50,61,68,66,60,53,49,41,42,43,45,47,49,51,52,55,57,60,62,61,59,55,53,48,45,41,38,35,33,33,33,33,36,41,45,48,48,46,45,42,38,33,29,27,29,31,33,40,44,50,52,51,48,45,44,45,54,63,70,75,75,68,59,51,50,51,55,62,66,66,64,54,46,35,27,22,22,22,23,23,25,29,35,40,46,50,52,50,47,43,40,40,43,46,49,45,43,38,31,26,24,26,29,36,39,42,42,40,40,42,46,51,54,58,59,57,53,51,50,55,61,71,81,87,86,80,74,64,57,49,45,45,46,45,44,43,41,37,33,31,30,30,31,31,33,35,36,33,28,22,18,16,17,20,26,33,38,41,42,36,36,36,38,42,48,54,58,61,57,51,42,33,26,21,18,17,18,21,25,29,33,36,38,40,42,45,46,46,44,41,39,33,32,31,29,26,24,23,22,22,23,22,22,21,19,18,17,16,16,17,18,20,22,24,25,27,26,26,26,25,25,25,25,26,24,22,19,17,16,16,16,18,18,18,17,16,15,13,13,12,12,12,12,11,11,11,10,10,12,14,15,15,14,12,10,13,13,12,12,12,11,11,11,11,11,11,10,10,9,9,9,9,9,9,8,8,8,7,7,7,7,7,6,6,6,5,5,6,6,6,5,5,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 8,8,8,9,9,9,10,10,10,10,10,11,11,12,12,12,11,11,11,12,12,12,13,13,13,13,14,15,16,16,17,17,22,21,21,21,20,20,19,19,18,19,21,21,22,24,28,31,34,37,40,42,42,42,43,45,45,47,52,56,62,67,72,75,81,83,86,88,89,89,90,90,94,98,106,115,125,137,148,156,164,168,175,182,183,182,185,190,192,194,198,206,220,236,250,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,254,255,255,251,250,254,255,253,237,224,209,197,182,169,163,165,166,172,176,174,169,167,169,171,172,181,190,190,184,173,157,144,128,116,108,109,116,122,127,131,131,127,121,113,104,95,87,83,82,79,76,73,72,69,65,62,57,53,49,48,54,65,78,86,99,102,104,106,107,110,114,118,126,124,119,111,102,94,90,89,87,87,87,82,74,65,59,56,53,52,50,49,48,49,49,49,53,56,62,68,74,80,85,89,89,89,85,75,65,56,47,39,39,42,49,59,69,78,84,86,85,82,77,73,67,60,53,48,45,44,47,56,69,82,90,93,89,77,60,44,31,25,31,41,56,64,72,71,61,48,38,34,39,46,54,59,58,53,47,43,39,39,40,40,41,41,41,41,41,44,48,51,53,54,53,52,49,48,44,41,38,37,36,35,36,39,43,47,48,47,44,42,38,35,32,29,29,31,34,36,44,48,52,54,53,52,51,51,57,65,73,78,79,76,66,55,49,49,50,56,63,67,67,65,54,47,36,28,24,24,24,24,23,25,28,32,38,44,49,52,50,48,45,42,42,44,47,49,46,43,37,30,25,25,28,32,40,43,46,45,42,41,43,46,54,57,61,63,60,56,53,51,56,63,73,84,90,90,84,79,70,64,57,54,54,55,54,52,47,44,40,35,32,30,30,30,27,28,30,30,29,25,21,19,18,20,24,30,37,41,43,43,38,38,38,40,44,50,55,58,59,55,47,38,30,24,20,18,18,20,22,25,29,32,34,35,37,38,41,42,41,38,34,32,29,29,27,26,24,23,22,21,22,23,23,22,21,20,19,18,19,20,21,22,25,27,29,31,31,30,30,29,28,27,27,27,25,24,21,18,17,16,16,16,18,18,18,17,16,15,13,13,13,13,13,12,12,12,11,11,11,12,14,16,16,14,12,11,13,13,13,12,12,12,11,11,11,11,11,10,10,9,9,9,9,9,8,8,8,7,7,7,7,7,6,6,6,5,5,5,6,6,6,5,5,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 8,9,9,9,10,10,10,11,11,11,12,12,12,13,13,13,13,13,13,13,14,14,15,15,15,15,16,17,18,18,19,19,24,23,23,22,21,21,20,20,20,21,22,23,23,26,29,33,35,38,41,42,41,40,40,41,40,42,44,47,50,56,63,67,77,83,90,95,98,100,101,102,104,108,114,121,130,142,154,161,171,179,190,198,201,200,201,203,200,199,201,209,223,239,252,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,254,255,255,252,253,255,255,246,221,205,189,177,162,148,144,148,149,158,166,167,164,162,160,157,153,159,162,161,159,156,148,140,128,118,112,115,120,123,123,125,125,119,110,102,94,86,79,75,79,77,74,72,70,66,62,59,54,51,47,47,54,66,78,87,100,103,107,110,113,115,119,122,125,124,119,112,103,96,91,90,88,89,88,83,74,65,59,56,51,49,47,47,49,50,51,51,52,54,59,64,70,74,77,78,69,67,63,58,53,49,45,43,47,50,55,63,72,79,85,89,88,85,80,76,70,64,56,51,51,51,53,61,73,82,87,88,82,71,57,43,31,27,34,44,58,64,70,68,60,48,39,35,38,42,47,51,51,47,42,39,38,38,38,37,36,34,32,31,30,33,39,44,49,52,53,54,54,52,50,46,43,40,38,38,39,41,46,49,49,46,42,39,33,32,31,31,32,34,37,39,46,50,54,57,57,57,58,59,66,74,80,83,82,77,65,53,49,48,50,56,63,66,65,63,52,46,37,31,27,26,26,25,23,24,26,30,36,42,49,52,50,48,45,43,42,44,46,47,45,42,36,29,25,26,31,35,44,47,49,47,43,41,43,46,54,58,63,64,61,57,53,51,56,62,72,83,90,91,86,81,73,67,61,58,59,60,59,57,49,46,41,37,33,31,31,31,28,29,31,32,31,29,27,26,27,28,32,37,42,45,44,43,38,38,39,41,45,50,54,57,56,52,45,37,30,25,22,21,21,22,24,26,28,29,30,30,33,34,35,35,34,31,28,26,26,26,26,25,25,24,24,24,24,24,24,23,22,21,19,19,21,21,23,25,27,30,33,34,34,34,32,31,29,28,27,26,23,21,19,16,15,15,15,15,17,17,17,17,16,15,14,13,15,15,14,14,14,13,13,13,12,13,14,15,15,14,13,12,14,13,13,13,12,12,12,12,11,11,11,10,10,9,9,9,8,8,8,8,7,7,7,6,6,6,6,6,5,5,5,4,6,6,6,5,5,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 9,10,10,10,11,11,11,12,12,12,13,13,14,14,14,14,15,15,15,16,16,16,17,17,18,18,19,19,20,21,21,22,26,25,25,24,23,22,21,21,22,23,25,25,25,28,32,35,36,38,41,42,41,39,38,39,37,38,39,39,41,47,55,61,71,79,90,99,103,106,108,109,110,113,119,125,134,144,155,162,175,186,200,208,210,210,208,207,202,200,201,209,223,239,251,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,253,255,255,253,254,255,243,225,205,188,170,158,144,128,124,130,132,144,155,158,158,156,151,145,141,142,142,140,142,145,142,136,133,125,120,123,126,124,121,119,116,108,97,88,81,76,71,67,70,68,66,65,63,60,56,53,47,45,44,45,52,62,73,81,94,97,102,105,108,110,113,115,114,114,112,108,102,96,94,93,88,88,87,82,73,64,58,54,48,45,42,43,47,50,51,51,53,54,56,59,63,65,66,65,54,52,49,48,47,47,49,51,54,57,61,65,71,78,84,88,85,82,78,73,69,62,55,51,52,51,54,61,70,78,80,80,71,62,50,40,30,27,33,43,57,60,63,60,53,44,38,35,36,38,42,45,46,44,41,38,38,38,37,36,33,30,27,25,26,29,35,42,48,53,56,57,59,57,54,50,46,42,39,38,40,43,47,50,49,45,40,36,28,29,30,33,35,38,41,42,46,50,56,59,61,61,63,64,71,78,84,85,84,78,66,54,49,49,50,56,62,64,62,59,49,45,38,33,30,29,27,26,23,23,25,28,34,41,48,52,50,48,45,42,41,42,44,45,44,41,34,28,25,27,33,38,48,50,51,48,43,41,42,44,53,58,62,64,61,56,51,49,52,57,66,77,84,86,83,79,71,66,60,58,59,60,59,57,50,47,43,39,35,34,34,34,35,36,37,38,37,37,35,34,37,38,41,45,48,48,45,42,36,37,38,40,44,48,52,55,53,50,44,38,32,28,26,25,25,26,27,27,27,27,26,25,29,29,29,28,27,25,24,22,24,24,24,25,25,26,26,26,25,25,25,24,23,21,19,18,19,20,21,24,27,30,33,34,36,35,33,31,28,26,24,23,19,18,16,14,13,13,14,14,16,16,17,17,17,16,15,15,16,16,16,15,15,15,14,14,14,14,14,14,14,14,14,14,14,14,13,13,13,12,12,12,11,11,11,10,10,9,9,9,8,8,8,7,7,7,6,6,6,6,6,5,5,5,4,4,6,6,6,5,5,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 10,10,11,11,11,12,12,12,13,13,14,14,14,15,15,15,16,16,17,17,18,18,18,18,19,20,20,21,22,23,23,23,27,26,26,25,24,23,22,22,24,25,26,26,27,29,33,36,36,39,42,42,40,38,37,37,36,36,36,35,36,42,51,58,65,74,87,98,103,106,109,111,111,114,119,125,133,143,153,160,176,188,203,211,212,211,208,205,201,199,200,209,223,239,250,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,253,255,255,254,253,249,227,203,195,176,158,146,131,114,110,117,120,135,148,152,153,152,145,137,133,133,131,130,134,139,138,132,139,131,127,129,131,126,119,116,109,100,88,79,73,69,65,62,61,59,58,57,56,54,49,46,42,41,40,42,49,58,68,74,80,84,89,92,94,96,98,100,103,105,105,103,100,97,96,96,86,87,86,81,72,63,56,53,45,41,39,40,45,49,51,50,57,56,56,56,57,57,56,54,48,45,43,44,46,48,53,57,59,61,63,66,70,76,82,87,79,76,72,68,64,58,52,47,48,47,50,57,66,72,73,72,62,54,45,37,29,25,32,42,55,56,57,54,47,40,36,34,34,35,38,42,44,44,41,38,39,39,38,36,33,28,25,23,25,29,35,42,49,54,57,59,62,60,56,52,47,43,39,37,41,44,48,50,49,45,39,35,25,27,30,34,38,41,43,43,46,50,56,60,62,63,65,66,73,79,85,86,85,80,68,56,50,49,51,56,61,63,60,57,47,44,38,35,32,30,28,26,23,23,24,27,33,40,48,52,50,48,45,42,41,41,42,43,44,40,34,27,25,28,35,40,50,52,52,49,43,40,41,43,53,57,62,63,60,55,50,48,46,51,60,70,78,80,78,75,69,64,59,57,58,59,58,56,50,48,44,40,37,36,36,37,42,42,43,43,43,42,41,40,45,45,47,50,52,50,45,41,35,35,36,38,42,46,50,53,51,49,44,39,34,31,29,28,27,28,28,28,27,25,23,22,26,26,25,24,23,22,21,21,22,23,24,25,26,27,28,28,26,25,25,24,22,20,18,17,17,18,19,22,25,28,31,33,36,34,32,30,26,24,22,20,17,16,14,12,12,12,13,14,15,15,16,17,17,17,16,16,17,17,17,16,16,16,15,15,15,14,14,13,13,14,14,15,14,14,14,13,13,12,12,12,11,11,11,10,10,9,9,9,8,8,8,7,7,6,6,6,6,6,6,5,5,4,4,4,6,6,6,5,5,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 9,10,12,12,11,12,13,15,14,15,17,17,16,17,18,20,18,19,20,20,21,20,20,19,20,20,21,22,22,23,23,23,26,27,27,26,24,23,23,24,22,23,25,26,27,29,34,37,44,44,45,45,45,43,41,40,37,35,34,33,35,40,45,48,66,73,85,95,102,107,110,112,112,117,123,126,130,137,148,157,171,182,193,199,203,207,206,203,202,200,199,202,213,229,245,255,255,255,254,253,253,253,254,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,254,255,255,255,242,223,203,191,176,167,154,138,124,114,109,106,110,117,127,138,145,145,139,134,129,127,126,127,132,137,140,142,140,144,145,140,133,126,116,107,101,94,84,74,67,62,59,56,50,48,48,49,50,50,48,46,40,40,40,41,45,51,56,60,63,69,74,76,76,77,83,88,87,89,91,91,91,92,93,95,89,85,81,77,72,64,53,45,42,40,40,42,47,52,56,57,55,56,58,58,57,54,51,50,46,43,42,45,52,58,61,62,65,63,61,60,62,65,70,73,71,69,65,60,55,51,48,47,46,48,50,53,57,60,63,64,59,52,42,33,29,31,35,39,45,45,45,42,39,36,36,36,33,35,37,38,37,36,37,38,38,39,40,38,33,29,27,26,30,33,38,44,51,57,62,64,66,63,58,51,43,38,35,35,42,45,50,53,50,44,35,30,27,27,30,35,40,44,45,45,51,52,53,56,58,60,62,63,70,74,80,84,82,75,66,60,52,54,57,58,58,56,53,50,41,41,41,40,38,35,32,30,26,26,27,29,34,40,46,50,47,45,41,37,35,35,37,38,36,35,33,30,29,31,37,41,49,51,52,48,42,40,43,47,53,57,61,64,62,56,49,44,42,49,56,62,70,77,77,73,62,58,52,48,47,47,47,46,43,43,42,42,42,41,41,40,48,49,51,51,50,49,49,50,53,50,48,51,54,52,45,39,39,32,30,35,40,42,44,46,47,45,40,36,33,31,31,32,34,32,30,27,24,22,21,20,20,21,23,24,24,23,21,19,24,25,26,27,28,28,28,28,28,26,24,21,19,17,16,16,18,18,19,19,21,23,25,26,27,27,27,26,24,21,18,17,13,12,12,12,12,13,14,15,16,16,17,18,18,17,16,16,20,20,19,18,16,15,14,14,13,13,13,13,13,13,13,13,14,14,14,13,13,12,12,12,11,11,10,10,10,9,9,9,9,8,7,6,6,6,6,7,6,6,6,5,5,4,4,4,6,5,4,3,3,3,3,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 9,11,13,13,12,12,14,16,14,16,18,18,17,18,19,21,20,21,21,22,22,22,21,21,22,22,22,22,23,23,23,23,27,28,28,27,25,23,24,25,23,25,27,28,29,31,35,39,44,44,46,46,46,45,43,42,42,40,38,37,38,41,45,48,61,68,79,89,97,102,105,108,109,113,118,121,124,131,141,149,158,169,181,188,193,198,198,195,192,192,195,201,213,229,244,253,255,255,255,255,255,254,252,251,254,254,254,254,254,254,255,255,255,254,253,254,255,255,255,253,255,251,242,233,221,204,184,170,162,154,141,129,120,112,106,102,107,112,120,129,134,134,129,125,123,123,124,127,131,137,143,147,148,152,153,147,139,131,120,110,96,89,79,69,62,57,54,51,46,44,43,44,45,46,44,43,37,36,35,36,39,44,49,53,54,60,66,68,68,70,74,79,78,80,84,87,90,93,96,98,93,88,83,78,73,65,55,47,40,38,38,41,46,53,57,58,57,58,58,57,55,53,51,49,47,45,45,48,55,61,64,65,63,61,58,57,57,60,64,66,64,62,58,53,48,45,42,41,40,41,43,46,49,52,55,56,54,49,41,34,30,32,36,39,39,39,38,36,33,31,32,33,33,35,36,35,34,33,34,36,36,37,39,37,35,33,32,32,36,37,41,45,50,56,60,62,62,61,57,50,41,36,35,36,44,48,54,58,55,48,38,32,27,29,32,38,44,47,47,45,48,49,50,52,55,57,58,59,64,69,75,79,78,72,64,59,53,54,56,56,54,52,48,46,39,39,39,38,37,34,32,30,27,27,29,33,37,42,47,50,46,43,38,33,31,32,34,35,36,35,33,30,29,32,37,41,47,50,51,48,44,43,47,52,58,60,63,64,61,54,47,42,41,48,54,60,68,74,74,70,57,53,46,42,40,40,40,40,39,40,42,44,46,47,47,48,52,54,56,56,55,53,52,51,51,48,48,51,56,56,49,43,40,33,28,31,36,38,40,43,45,43,40,37,34,33,32,32,34,32,29,26,24,21,20,19,20,21,22,24,24,24,23,22,26,27,29,30,30,29,28,27,26,25,23,21,19,18,17,17,17,17,17,17,18,20,21,22,24,24,24,24,22,19,17,15,12,12,11,11,12,13,14,15,18,19,20,20,20,20,19,18,20,20,19,18,17,16,15,14,13,13,13,13,13,13,13,13,14,14,14,13,13,12,12,12,11,11,11,10,10,10,9,9,9,8,7,7,6,6,7,7,6,6,6,5,5,4,4,4,6,5,4,3,3,3,3,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 11,12,14,14,14,14,15,17,16,18,19,20,19,19,21,23,23,23,24,24,24,24,23,22,24,24,24,24,23,23,23,23,28,29,29,28,26,24,25,26,26,28,30,31,32,34,37,40,45,46,48,49,49,49,47,47,50,47,44,42,42,43,46,48,58,64,74,84,91,96,100,103,103,106,110,113,115,121,129,135,143,154,166,173,179,185,186,183,182,185,191,200,212,224,235,241,248,251,255,255,255,255,254,252,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,253,255,242,224,210,199,186,168,155,147,139,129,122,118,114,106,100,104,106,109,114,117,116,113,109,111,115,120,124,128,135,144,151,154,158,159,152,143,133,120,109,90,84,74,65,59,54,50,48,45,43,41,40,42,44,44,44,38,36,33,32,34,38,43,47,46,51,57,60,61,62,65,69,66,70,76,84,92,97,101,103,98,92,85,79,74,67,58,51,41,39,39,42,49,56,61,63,63,62,61,59,56,54,52,51,48,47,46,49,55,61,64,66,58,56,53,51,51,53,56,58,57,55,51,47,42,39,36,35,35,35,36,38,41,45,49,51,50,46,41,36,34,34,36,38,35,35,33,31,28,28,30,33,34,34,34,31,29,28,30,32,33,35,37,38,37,38,40,42,44,44,44,45,47,50,53,55,54,55,54,46,37,32,33,37,44,49,57,61,59,50,38,31,28,30,36,43,49,51,49,46,43,44,45,47,49,50,52,52,56,60,67,71,71,67,61,57,54,54,53,52,49,45,42,40,38,37,37,36,35,33,31,30,28,30,33,38,42,46,49,50,45,41,34,29,26,27,29,32,36,35,34,31,30,32,36,40,45,47,50,49,48,50,55,60,66,67,67,64,59,52,44,40,40,46,52,57,64,70,70,65,53,48,40,34,32,33,33,33,34,37,41,46,51,54,56,56,58,59,62,63,61,58,54,51,46,45,46,52,59,60,55,49,43,33,26,26,30,32,35,38,41,41,40,38,36,35,34,33,33,32,29,26,23,21,19,19,21,21,22,23,25,26,26,27,31,32,33,33,32,30,27,25,23,22,21,19,19,19,19,19,18,18,17,16,16,16,17,17,21,21,22,21,20,17,15,14,11,11,11,12,13,14,16,16,21,21,22,23,23,22,21,21,21,20,19,18,17,16,15,15,13,13,13,13,13,13,13,13,14,14,14,14,13,13,13,13,12,12,11,11,11,10,10,10,9,9,8,7,6,6,7,7,6,6,6,5,5,4,4,4,6,5,4,3,3,3,3,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 12,13,15,15,15,15,16,18,17,19,21,21,20,21,22,24,25,25,26,26,26,25,24,24,26,26,25,24,24,23,23,23,27,29,29,28,26,25,26,27,29,31,33,34,35,37,39,42,48,50,52,54,54,54,54,53,57,54,51,48,46,46,47,48,57,63,71,79,85,91,95,98,96,99,102,104,107,111,118,123,130,141,152,159,165,171,173,171,177,182,189,198,207,215,220,223,231,235,241,247,252,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,252,249,238,225,207,193,182,172,159,150,140,132,124,121,122,119,111,104,104,103,101,101,101,99,95,93,96,103,111,117,122,130,142,151,153,157,157,149,139,128,114,102,86,80,72,65,59,55,52,49,49,46,43,43,45,48,49,49,44,41,36,33,33,37,42,46,45,50,56,60,61,61,63,64,62,66,74,85,96,104,108,109,100,94,85,78,73,67,61,55,46,44,43,46,53,60,66,68,70,68,65,62,58,56,54,53,48,47,46,47,50,54,57,59,51,50,47,46,46,48,51,53,53,51,48,44,40,36,34,33,31,31,31,33,37,43,47,51,50,48,44,41,39,37,37,37,36,36,34,31,28,29,33,36,35,34,32,28,24,23,25,27,30,32,35,38,40,42,46,49,50,48,45,43,42,41,42,43,44,47,47,41,32,28,31,36,41,47,55,60,57,47,35,27,28,32,39,47,53,53,49,45,38,38,39,41,42,43,45,45,48,52,58,63,65,63,58,55,52,51,50,48,45,41,38,36,38,37,36,35,33,31,29,28,28,31,36,42,46,49,49,49,45,40,32,25,22,23,26,29,35,35,34,32,31,32,35,37,42,45,49,51,54,58,65,69,75,74,70,65,58,50,43,39,40,46,51,55,61,66,65,60,51,45,36,30,28,28,28,29,30,34,41,48,54,58,60,61,60,61,64,65,64,60,53,48,41,41,44,52,61,63,59,53,45,34,24,22,24,26,30,35,39,39,39,38,37,36,34,33,32,30,28,25,22,20,19,19,22,22,23,24,26,29,31,32,35,36,36,36,34,30,26,24,20,19,19,19,19,20,21,21,22,21,20,18,17,16,16,16,19,20,21,21,19,18,15,14,13,13,13,14,15,16,18,19,21,22,23,23,23,23,22,21,21,20,19,18,17,16,15,14,12,12,12,12,12,12,12,12,14,14,14,14,14,14,14,13,13,12,12,12,11,11,11,11,10,9,8,7,7,7,7,8,6,6,6,5,5,4,4,4,6,5,4,3,3,3,3,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 12,14,16,16,15,15,17,19,18,20,22,22,21,21,23,25,26,26,27,27,26,25,24,23,26,26,25,24,24,23,23,23,27,28,29,29,28,27,28,30,32,34,37,39,39,40,42,44,53,55,57,59,60,60,60,59,61,59,56,52,50,49,49,49,55,60,66,73,78,83,88,91,91,93,95,98,102,106,111,114,121,130,139,144,151,158,162,162,174,179,187,196,203,207,209,209,214,216,219,225,231,238,244,247,247,248,250,251,252,252,252,251,248,246,244,243,241,238,234,231,212,205,194,181,169,159,151,146,137,130,124,124,126,126,118,111,111,107,100,95,90,86,82,79,82,89,99,107,113,122,134,143,146,150,149,141,130,119,104,93,80,75,69,64,61,58,55,53,53,51,48,48,51,54,56,56,51,47,40,35,35,38,43,47,53,57,62,66,68,67,66,66,63,67,77,89,102,110,113,113,101,93,83,76,72,69,65,61,52,50,48,49,55,61,67,69,72,70,66,62,59,56,54,53,47,46,44,43,42,44,46,48,45,44,43,43,44,47,49,51,50,48,45,41,38,35,33,32,28,28,27,29,34,40,46,50,51,50,49,46,43,41,38,37,39,38,36,33,30,30,33,37,35,34,31,26,22,21,22,24,27,30,35,38,41,45,49,52,51,49,45,40,36,33,31,31,36,38,39,34,29,26,30,34,41,46,53,57,54,45,33,26,29,33,41,49,54,53,47,42,33,34,35,36,37,37,38,39,42,46,52,56,58,57,54,52,48,48,49,48,46,43,40,38,42,41,38,35,32,29,28,27,27,31,37,43,47,49,48,48,44,39,31,24,21,22,25,28,33,33,34,32,31,31,32,34,39,42,47,52,58,66,73,77,82,78,72,64,55,47,42,39,40,46,50,53,58,62,60,54,46,41,33,27,25,25,24,24,28,33,41,49,55,59,60,60,59,60,62,64,63,58,50,43,37,38,43,52,62,66,62,56,46,34,23,20,22,24,29,34,38,38,38,37,36,34,32,31,29,28,26,24,22,20,20,20,24,25,26,27,30,33,35,37,38,38,38,36,33,29,25,22,18,18,18,19,20,21,22,23,27,26,24,22,20,19,18,18,19,20,21,21,21,19,17,16,16,16,16,16,17,18,20,20,20,20,21,21,21,21,20,20,20,19,18,17,16,15,14,14,12,12,12,12,12,12,12,12,14,14,14,14,14,14,14,15,13,13,13,13,12,12,12,11,10,9,8,8,7,7,8,8,6,6,6,5,5,4,4,4,6,5,4,3,3,3,3,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 12,14,15,15,15,15,17,18,18,20,22,22,21,21,23,25,26,26,26,26,25,24,23,22,24,24,24,24,23,23,23,23,27,29,31,32,31,32,33,35,37,40,43,45,45,45,47,49,57,59,61,63,64,64,63,62,62,60,57,54,52,51,50,50,53,56,61,65,69,73,78,82,87,89,91,96,100,105,110,112,116,123,130,134,141,151,159,160,175,179,187,195,201,203,204,204,202,201,201,203,207,214,221,225,230,231,235,238,240,242,242,242,232,228,223,219,215,211,206,202,197,194,188,179,168,157,150,146,136,131,127,128,131,131,127,122,124,117,106,96,88,80,74,70,72,79,88,97,105,114,125,132,137,139,137,129,118,108,96,85,73,69,65,63,63,62,61,59,58,56,55,56,59,62,63,63,57,51,43,37,36,39,45,49,61,64,69,73,74,72,69,66,65,69,79,93,107,115,116,114,100,92,81,74,72,72,71,70,61,57,53,53,56,61,65,67,70,69,66,63,59,55,52,51,48,47,45,42,39,38,40,42,43,42,42,43,45,47,50,51,48,46,44,40,37,35,33,33,28,26,25,25,29,35,42,46,51,51,50,49,46,44,41,40,42,41,39,35,31,30,31,33,34,34,32,27,23,21,21,22,24,28,34,39,42,44,47,49,47,46,43,39,35,31,28,27,32,32,31,30,28,28,31,33,43,46,50,52,49,41,32,27,29,33,40,48,51,49,43,38,31,31,32,32,33,33,34,34,38,41,46,49,51,50,48,46,45,47,50,53,53,52,50,48,49,46,42,37,32,28,26,24,26,30,36,42,45,47,46,45,41,36,30,24,21,22,25,27,30,32,33,32,30,29,30,31,35,37,43,50,59,69,77,81,83,78,69,59,50,43,39,37,39,44,48,50,53,56,53,47,41,36,30,26,24,23,22,21,26,32,41,50,56,60,60,60,59,58,59,61,62,57,48,41,37,38,44,54,65,68,64,59,47,35,24,21,23,26,31,36,40,39,37,35,32,30,29,28,26,25,24,22,22,21,21,21,27,28,30,32,35,37,39,40,40,39,37,34,30,27,24,22,19,19,19,20,21,23,24,25,29,28,26,23,21,20,19,19,19,20,21,22,22,21,19,18,18,17,17,17,17,18,19,20,17,18,18,19,19,18,18,17,18,18,17,16,15,14,13,12,11,11,11,11,11,11,11,11,14,14,14,14,15,15,15,15,14,14,14,13,13,13,12,12,10,10,9,8,8,8,8,8,6,6,6,5,5,4,4,4,6,5,4,3,3,3,3,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 11,13,15,15,14,14,16,18,18,20,21,22,21,21,23,25,24,25,25,24,23,22,21,20,22,22,22,22,23,23,23,23,29,32,34,36,36,38,40,43,44,47,50,52,52,52,53,54,59,61,62,64,65,64,63,63,61,59,57,55,53,52,52,52,54,56,59,62,64,68,73,76,85,87,90,96,102,108,112,114,115,122,127,131,140,154,165,170,183,187,192,196,200,201,201,200,196,194,192,191,194,198,204,208,212,215,220,225,229,232,233,233,222,216,208,200,194,189,184,181,187,184,179,175,171,164,155,149,136,134,133,134,136,139,139,138,137,129,116,102,90,80,72,67,68,72,80,89,99,109,117,121,125,127,124,115,105,97,86,77,69,67,66,66,68,69,69,69,66,65,65,67,71,73,73,73,62,56,47,40,38,42,49,53,64,67,71,75,76,72,67,62,63,68,78,93,108,116,117,114,100,91,80,73,73,76,78,78,74,69,63,59,60,63,66,68,71,70,69,66,63,59,55,52,51,51,49,45,41,40,42,45,45,45,45,45,46,48,49,50,51,49,46,43,41,39,37,37,33,30,26,24,26,30,37,41,47,48,48,48,47,46,45,45,46,46,43,39,34,31,30,31,34,34,33,30,25,22,21,22,23,28,35,40,42,42,43,44,41,42,42,42,40,37,34,32,32,29,27,28,31,33,34,33,43,44,45,44,41,35,29,26,29,33,39,45,48,45,38,33,30,30,30,30,31,31,31,31,35,37,40,43,44,43,41,39,43,48,54,61,64,64,62,61,56,53,47,40,33,28,24,22,24,27,33,38,42,43,43,42,36,33,28,23,21,22,23,25,28,30,31,31,29,27,27,28,29,32,37,46,57,68,77,81,80,74,64,53,44,38,36,35,36,41,44,45,48,50,47,40,39,36,31,28,27,25,23,21,25,31,41,51,58,62,62,61,60,59,58,60,62,58,50,43,40,41,47,58,68,72,67,61,47,35,25,23,26,29,35,40,42,40,36,32,29,26,25,25,23,22,22,21,21,22,23,23,29,31,34,37,39,41,41,41,41,38,35,31,27,24,22,22,20,20,20,21,22,24,25,26,27,26,24,22,20,18,17,17,18,19,20,21,22,21,19,19,18,18,17,16,16,16,16,17,16,17,17,18,18,17,17,16,17,16,16,14,13,12,11,11,11,11,11,11,11,11,11,11,14,14,14,15,15,16,16,16,15,15,14,14,14,13,13,13,11,10,9,8,8,8,8,9,6,6,6,5,5,4,4,4,6,5,4,3,3,3,3,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 11,12,14,14,14,14,15,17,18,19,21,21,21,21,22,24,23,24,23,23,22,21,19,18,20,20,21,22,22,23,23,23,31,34,37,39,40,42,45,48,48,51,55,56,56,56,57,58,60,61,62,64,64,63,62,61,59,58,57,55,54,53,53,53,57,59,61,62,64,67,72,75,85,86,90,96,104,110,114,116,118,124,129,133,143,160,174,181,194,196,198,199,199,198,197,196,193,192,190,190,191,195,199,202,203,206,212,218,223,227,229,229,221,214,204,194,186,181,176,173,176,170,165,165,168,166,157,148,137,137,138,139,142,145,149,151,146,137,122,107,93,81,71,66,67,70,76,85,97,106,112,115,116,117,114,104,95,88,79,71,70,69,68,70,74,76,77,77,73,73,74,77,80,82,82,80,67,61,51,44,42,46,53,58,64,67,70,74,74,70,63,58,61,65,75,92,108,116,116,113,100,91,80,74,75,79,83,84,84,79,71,67,66,68,70,71,73,74,73,72,68,64,59,56,53,54,53,49,45,44,46,50,49,48,48,47,47,48,49,49,55,53,51,48,46,44,42,42,39,35,30,26,26,29,34,38,43,44,45,46,47,48,48,48,51,50,48,44,38,33,31,30,33,34,34,31,27,23,22,22,22,27,35,40,41,41,40,40,37,39,42,44,44,43,40,38,33,29,25,27,33,37,37,34,40,40,39,37,33,29,25,23,29,32,37,43,45,42,35,30,30,30,30,30,30,30,30,30,33,35,37,39,39,38,36,34,43,49,58,67,72,73,72,70,61,57,50,42,34,27,23,21,22,26,31,36,39,41,41,40,33,30,26,23,21,21,22,23,26,29,31,30,28,26,26,26,25,28,33,43,55,67,75,79,77,71,60,48,40,35,33,33,34,38,41,42,44,46,42,36,40,38,35,33,32,30,27,24,24,31,41,53,60,64,64,63,63,60,59,61,63,60,52,45,43,44,50,61,71,74,69,63,47,36,26,25,29,32,37,43,44,41,36,30,26,24,23,22,21,21,21,21,21,23,24,24,30,33,36,40,42,43,42,41,41,38,33,28,24,22,22,22,21,21,21,22,23,24,26,27,25,23,21,19,17,16,15,15,17,18,19,21,21,20,19,18,18,17,16,14,14,13,14,14,16,16,17,18,18,17,16,16,16,15,15,13,12,11,10,10,11,11,11,11,11,11,11,11,14,14,14,15,15,16,16,16,15,15,15,14,14,14,13,13,11,10,9,8,8,8,8,9,6,6,6,5,5,4,4,4,6,5,4,3,3,3,3,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 12,12,13,14,14,15,16,16,20,20,19,19,19,19,19,19,21,21,21,20,20,20,19,19,19,21,23,23,23,24,27,29,30,34,40,45,47,49,51,52,56,58,60,62,63,63,62,62,61,61,60,60,59,58,58,57,54,53,52,51,51,55,60,65,60,61,64,68,68,68,74,82,91,95,102,111,119,124,126,125,120,127,136,144,153,168,189,204,206,208,211,213,212,210,206,204,198,199,201,203,206,208,209,210,208,211,216,220,224,225,225,226,218,209,200,193,184,172,166,166,160,159,160,162,162,157,149,142,139,138,137,137,141,147,153,158,152,145,132,117,102,88,79,74,72,75,81,88,94,100,104,106,113,110,105,98,91,85,81,79,69,73,76,76,81,87,89,87,86,82,80,82,87,88,85,80,69,59,50,46,45,47,56,65,68,70,71,69,65,60,57,56,55,64,77,90,105,117,118,114,97,88,80,79,80,82,88,94,94,92,87,80,74,71,73,76,77,82,84,79,76,75,72,69,65,63,58,55,53,53,55,56,61,60,56,51,46,45,47,49,50,51,52,51,50,49,50,51,49,47,41,34,28,27,29,32,39,41,45,48,51,52,51,51,52,51,48,40,32,27,28,30,35,39,43,41,34,26,22,20,26,33,40,43,40,36,35,34,32,41,49,53,61,66,59,45,43,33,27,32,38,41,42,43,44,42,37,32,27,24,24,25,26,28,32,35,36,35,34,32,31,32,32,31,29,28,28,30,31,35,38,38,34,31,32,34,44,51,62,72,79,80,78,76,67,61,51,41,34,28,23,20,26,29,34,36,37,36,35,35,31,29,26,24,23,24,25,26,27,28,29,30,29,26,24,22,23,26,32,42,53,64,73,79,73,67,57,47,38,34,32,32,33,34,36,35,34,34,35,36,37,42,44,42,40,38,32,25,27,30,38,50,61,66,65,62,59,57,55,57,61,60,54,49,47,49,54,63,71,72,66,60,45,37,30,29,34,40,43,44,43,38,32,26,23,21,18,16,20,19,19,19,21,23,26,27,31,35,40,44,44,42,37,34,31,27,23,21,22,22,20,17,22,22,22,24,26,26,24,22,21,20,17,15,13,13,13,13,16,16,17,18,19,19,18,18,17,17,18,19,19,18,17,17,17,17,18,19,20,20,20,19,16,15,15,13,12,11,10,10,9,9,9,9,9,11,12,12,15,16,16,15,14,13,15,17,18,17,16,15,13,12,11,11,12,12,11,11,10,9,8,8,7,7,7,6,6,5,5,5,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 12,12,13,14,14,15,16,16,19,18,18,18,18,18,18,18,20,20,20,19,19,19,19,19,20,22,24,25,25,26,28,31,34,39,45,49,52,53,56,57,61,62,64,65,66,66,65,65,62,62,60,59,57,55,54,53,49,50,50,50,51,56,62,67,69,69,71,74,73,72,78,86,99,104,112,121,129,134,135,134,133,139,147,156,168,185,204,217,226,225,223,221,218,215,213,212,218,220,223,226,227,226,224,223,218,216,217,221,227,229,226,222,218,208,197,188,176,164,156,155,149,148,148,149,149,146,140,135,133,133,134,136,140,146,151,155,151,145,133,118,103,90,81,76,76,79,83,89,95,100,103,105,107,105,100,94,89,84,80,78,74,78,81,83,89,96,98,96,91,86,83,84,88,90,86,82,68,59,49,46,46,49,58,67,69,69,68,65,59,54,52,51,55,64,75,87,100,111,112,107,97,89,81,79,80,82,89,96,102,101,98,92,85,82,82,84,87,93,96,92,87,84,80,75,76,74,70,67,64,63,64,64,66,64,59,53,47,45,46,48,49,51,52,52,51,51,53,55,57,54,48,41,34,31,32,34,39,41,45,48,50,50,50,49,49,48,44,37,29,26,28,31,38,42,46,43,36,28,23,22,26,33,41,43,40,35,32,31,31,44,57,67,79,87,79,65,48,37,29,32,39,43,45,48,45,43,37,31,26,24,24,24,25,26,29,31,32,32,32,31,32,33,33,31,28,26,27,28,31,35,38,37,33,30,30,32,42,50,61,72,78,79,77,74,65,60,52,44,38,33,28,25,26,28,30,32,32,32,31,31,28,27,25,24,24,26,27,28,29,29,30,30,28,26,24,22,21,25,33,42,53,63,71,76,70,65,55,45,37,32,30,30,28,29,30,29,28,29,32,34,42,48,53,52,50,47,39,31,29,32,38,49,59,64,64,61,57,55,53,55,58,58,53,48,49,50,55,63,70,70,64,57,44,38,32,31,35,40,42,42,40,35,29,24,21,20,18,17,18,18,19,20,22,25,28,30,32,35,39,42,42,38,34,31,28,24,21,20,22,24,23,22,26,25,25,26,27,26,24,21,18,17,15,14,13,13,14,15,16,17,17,18,18,18,18,18,17,17,18,19,19,18,17,17,18,18,19,20,21,21,20,20,17,16,15,14,13,12,11,10,9,9,9,9,9,10,11,12,14,15,16,15,13,13,15,17,17,16,16,14,13,12,11,10,12,12,11,10,9,9,8,8,7,7,6,6,6,5,5,5,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 12,12,13,14,14,15,16,16,17,17,17,17,17,17,17,17,18,18,18,18,18,19,19,19,22,24,27,28,28,29,31,33,38,42,48,52,55,57,59,61,64,65,66,67,67,66,66,65,63,62,60,57,53,51,48,47,43,44,47,49,53,59,66,72,77,77,79,82,82,82,88,96,106,113,123,133,141,145,145,145,147,152,160,174,191,210,227,236,251,248,243,238,235,234,235,235,241,243,247,249,248,245,242,239,233,227,222,225,231,232,225,217,211,200,187,176,165,152,144,142,136,134,132,132,132,130,128,125,125,126,129,134,138,143,147,149,149,142,131,117,103,91,83,78,80,82,86,90,94,98,100,101,101,99,96,93,88,85,82,80,79,84,89,93,101,109,111,108,98,92,87,86,90,91,87,83,68,58,50,47,48,53,63,73,71,69,66,59,53,48,46,47,54,63,73,83,93,102,103,99,97,89,82,80,80,82,90,98,110,112,112,108,101,97,96,97,104,110,113,108,102,97,90,84,88,87,83,80,76,74,72,72,71,69,63,55,48,45,46,48,50,51,53,54,54,55,58,61,65,63,58,50,42,36,34,34,40,42,45,47,48,48,47,46,44,43,39,32,26,25,29,34,43,47,50,47,39,31,25,24,26,34,42,45,41,34,28,26,31,48,68,86,103,111,100,83,56,42,31,32,40,47,51,55,49,45,38,32,27,25,25,25,25,25,25,26,27,29,30,31,35,35,33,30,26,25,26,27,32,35,37,36,31,27,27,28,39,47,58,69,75,76,72,69,61,58,52,48,44,40,35,32,27,27,27,26,26,26,27,27,24,24,25,26,27,30,32,33,32,32,31,30,28,26,23,22,21,26,34,44,54,62,68,71,66,61,52,42,35,30,29,28,25,26,25,24,25,27,32,36,48,57,64,65,63,58,48,38,33,34,38,47,56,61,60,58,53,51,49,51,54,54,51,48,50,52,56,63,68,67,61,55,44,40,36,35,38,41,41,40,37,32,26,22,20,20,19,19,18,18,19,20,23,27,30,32,33,35,37,39,37,33,29,26,22,21,20,21,25,29,31,31,34,32,30,29,29,27,23,21,15,14,14,14,15,16,17,18,19,19,19,19,19,18,18,18,18,19,19,20,20,19,19,18,19,19,20,21,21,21,21,20,18,17,16,15,14,13,12,11,10,9,9,9,9,10,11,11,13,14,14,13,12,12,13,15,16,15,14,13,12,11,10,10,11,11,10,10,9,8,7,7,7,6,6,6,5,5,5,5,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 12,12,13,14,14,15,16,16,15,15,16,16,16,16,17,17,17,17,17,18,18,19,19,20,25,27,30,31,32,33,35,37,40,43,48,52,54,56,59,61,63,63,64,64,63,63,62,62,62,61,58,54,50,46,43,42,39,41,45,50,56,64,73,79,83,83,86,90,91,93,100,110,117,125,138,149,157,160,162,162,162,167,178,196,217,235,246,251,255,255,254,251,251,252,254,255,253,254,255,255,255,254,252,250,247,241,235,233,234,230,221,213,199,186,172,161,151,140,132,131,125,122,118,115,114,114,115,115,117,121,126,132,136,139,140,141,142,136,125,113,100,89,82,78,81,83,85,88,91,93,94,95,97,96,95,93,91,88,86,85,82,88,94,101,112,122,124,121,105,97,89,85,87,88,86,82,69,59,51,49,51,58,69,80,76,73,66,58,50,45,45,46,55,63,73,80,89,96,97,93,95,88,81,79,79,82,91,101,114,119,123,122,116,112,112,114,125,130,131,125,116,109,101,94,94,93,90,87,83,79,76,75,75,72,65,56,49,45,46,48,54,55,57,58,58,60,64,67,71,69,64,57,47,40,36,34,41,42,45,46,46,45,43,42,38,37,34,28,23,24,30,36,49,52,55,51,43,33,28,26,28,36,46,49,44,35,27,23,32,52,79,102,121,128,112,92,62,46,32,33,43,52,58,62,55,49,40,33,29,28,28,28,26,25,24,23,25,27,31,33,38,37,34,30,26,24,26,28,34,37,39,36,30,26,24,25,34,42,53,63,68,68,64,61,55,54,52,51,50,46,41,38,31,28,24,22,22,23,24,24,21,23,25,29,32,36,38,39,37,36,34,31,28,25,24,23,23,28,36,46,54,60,63,65,59,55,48,40,34,30,29,29,27,27,26,25,26,30,37,42,54,64,74,77,75,69,57,45,38,37,38,44,51,56,56,55,49,47,45,46,48,49,48,46,48,51,56,63,67,66,61,56,46,44,41,41,42,43,41,39,35,31,26,23,22,23,22,22,20,20,20,21,24,27,30,31,33,34,35,35,32,28,24,21,19,20,22,27,32,38,42,44,44,41,38,35,32,29,25,22,15,16,17,19,20,22,24,25,25,24,23,22,21,20,20,20,21,21,22,22,22,22,21,21,20,21,21,22,22,22,21,21,18,18,17,16,15,13,13,12,10,9,9,8,8,9,10,10,11,12,13,12,10,10,12,14,14,14,13,12,11,10,10,9,10,10,10,9,8,7,7,6,6,6,6,5,5,5,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 12,12,13,14,14,15,16,16,14,15,15,15,16,16,17,17,17,17,18,19,20,21,22,22,27,30,34,36,36,37,39,40,42,45,48,51,53,55,58,60,61,60,60,60,59,59,59,60,59,58,55,52,48,44,41,40,39,43,48,55,63,72,81,87,93,92,95,99,100,102,111,120,133,143,157,169,177,182,185,187,188,193,205,223,240,252,255,255,253,253,254,254,255,255,255,255,255,255,254,254,254,255,255,255,255,253,249,243,236,227,218,212,191,176,160,148,139,128,120,118,114,110,105,100,98,100,103,107,115,119,125,130,134,134,133,132,131,126,116,105,94,84,77,74,78,79,81,84,86,87,88,88,91,91,92,92,91,90,89,88,83,89,97,108,122,134,136,131,113,103,89,81,81,82,81,79,70,61,53,51,54,62,74,86,82,78,71,61,52,48,48,50,57,66,75,80,87,93,94,91,90,84,79,77,77,81,92,104,118,125,132,132,128,125,128,131,147,151,151,142,132,122,112,104,95,93,91,88,84,81,78,76,76,73,66,57,50,47,49,51,60,61,62,61,61,63,67,70,75,73,69,62,53,45,40,38,42,43,45,45,44,42,39,37,33,33,30,26,23,25,32,38,52,55,57,54,45,36,30,28,31,40,49,52,46,36,27,23,32,55,85,112,134,139,120,96,65,48,33,35,47,57,64,68,59,52,42,35,32,32,33,33,29,28,25,24,25,29,33,36,39,37,34,29,26,26,29,32,39,42,43,39,32,26,24,25,30,36,45,53,57,57,54,51,48,49,51,54,55,52,47,42,35,30,24,21,21,22,23,23,21,23,28,34,39,43,45,47,43,41,37,33,29,26,25,24,26,31,38,46,53,56,57,58,52,49,43,38,34,32,32,32,31,31,30,29,30,35,43,48,62,72,82,86,84,78,66,54,44,40,38,40,46,51,52,51,46,44,42,41,42,43,43,43,45,49,55,62,66,65,61,57,49,48,46,45,45,43,41,39,35,32,28,26,26,27,26,25,23,23,22,22,23,25,27,28,32,32,32,31,28,24,21,19,20,24,30,37,44,50,55,58,56,52,47,42,38,34,29,25,21,22,24,27,29,31,32,33,31,30,28,26,24,23,23,23,24,24,25,25,25,25,24,24,21,21,22,22,22,21,21,20,18,18,17,16,15,13,13,12,10,9,9,8,8,8,9,9,10,11,11,10,9,8,10,12,12,12,11,11,10,9,9,9,10,9,9,8,7,6,6,6,6,6,5,5,5,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 12,12,13,14,14,15,16,16,14,14,15,16,16,17,18,18,18,19,20,21,23,24,25,26,29,33,37,40,40,41,42,44,44,46,49,50,51,52,55,57,57,56,56,55,55,56,57,58,54,53,52,49,47,44,43,42,44,48,55,63,71,80,90,96,105,105,107,110,111,114,122,133,147,157,172,185,194,200,206,210,223,226,234,245,254,255,255,253,254,255,255,255,255,255,255,253,255,254,252,252,252,254,255,255,255,255,255,251,241,229,218,213,191,174,155,141,131,119,111,108,103,100,96,91,89,93,99,104,118,122,127,130,131,129,126,123,120,115,107,96,86,78,72,69,72,73,76,78,80,82,83,83,85,87,88,90,90,90,89,88,85,92,101,115,132,146,148,142,122,108,89,76,73,75,76,75,70,61,52,51,55,63,76,88,88,84,77,67,59,55,56,58,64,72,80,82,85,90,91,88,84,79,75,73,74,79,92,106,123,130,136,136,132,132,137,143,162,167,169,160,148,134,119,108,91,90,87,84,81,80,78,78,76,72,66,58,53,52,55,59,67,67,66,64,62,63,66,69,75,74,70,63,55,49,45,44,43,44,45,44,42,39,35,33,30,31,30,27,24,27,34,40,52,56,58,55,46,37,31,29,34,42,51,53,47,37,28,24,33,56,88,117,140,144,124,98,63,46,33,37,51,62,68,70,62,53,42,35,34,35,37,37,32,30,27,26,27,31,35,38,39,37,34,29,27,29,34,38,46,48,48,43,35,28,26,26,27,31,38,44,46,46,43,41,44,47,52,57,60,58,52,46,37,31,24,21,22,24,23,22,22,26,33,40,46,51,53,54,49,46,41,35,30,27,26,26,29,33,38,44,48,50,50,49,44,42,40,37,36,37,38,39,37,36,36,35,36,41,49,54,68,78,87,90,89,83,72,62,49,43,38,37,41,46,48,47,43,42,39,36,35,36,38,39,43,48,55,62,65,64,61,58,50,49,48,46,44,41,39,37,35,33,31,31,31,30,28,26,24,23,22,22,22,23,25,26,30,30,29,27,25,23,21,20,25,32,43,52,59,65,69,72,67,62,56,50,45,40,34,31,30,31,33,36,38,39,40,40,37,35,32,29,27,25,25,25,25,26,26,27,27,26,26,25,20,21,21,21,21,20,19,19,18,17,16,15,14,13,12,11,10,9,9,8,7,8,8,8,8,9,10,9,7,7,9,11,10,10,10,9,9,9,8,8,9,9,8,7,6,6,5,5,5,5,5,5,4,4,4,3,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 12,12,13,14,14,15,16,16,14,15,15,16,17,18,19,19,20,21,22,24,25,27,28,29,31,35,40,43,44,44,45,46,43,44,46,46,46,46,49,51,50,49,49,49,49,51,52,53,49,49,48,48,47,46,45,45,50,55,62,70,79,88,97,103,112,112,115,121,125,130,141,152,163,175,190,203,212,221,229,235,248,249,251,254,255,255,255,254,255,255,255,255,255,255,255,255,255,254,254,253,254,255,255,255,255,255,255,254,248,237,223,213,191,173,152,139,129,118,110,107,97,96,93,90,91,96,105,112,124,126,129,131,129,125,119,116,111,107,99,90,81,73,68,66,67,69,71,74,77,79,80,81,84,85,88,90,91,91,90,89,89,96,107,123,143,157,159,153,131,113,89,72,67,69,72,73,68,59,50,49,53,61,75,87,92,88,82,73,66,62,63,65,71,79,85,84,84,85,85,83,77,73,70,69,70,77,92,107,124,130,134,132,127,128,136,144,163,173,179,173,159,140,118,102,84,82,79,76,75,75,76,77,75,72,67,61,57,59,64,68,72,71,68,63,60,59,61,63,68,67,64,58,52,47,45,46,44,45,45,43,40,36,32,30,29,30,31,29,27,29,35,41,51,55,58,54,46,37,32,30,34,42,50,52,46,36,28,25,38,59,89,116,138,140,117,89,58,43,32,39,55,66,70,71,61,51,39,33,33,36,38,38,33,31,29,28,29,32,36,39,38,36,33,30,29,32,39,44,52,54,53,48,39,32,28,28,28,30,34,37,38,38,36,35,42,47,54,62,65,63,56,50,37,31,23,21,23,25,23,21,25,30,37,46,53,57,59,59,54,50,44,37,32,29,28,28,31,33,36,39,41,42,41,41,38,38,37,38,39,42,45,46,45,45,45,45,46,50,57,61,69,77,85,86,85,81,72,63,53,46,38,35,38,42,44,45,42,40,37,33,31,31,33,35,44,49,57,62,64,61,58,56,49,49,47,44,40,37,35,34,33,33,33,34,34,32,28,24,22,21,20,20,21,23,25,27,28,27,26,25,23,22,22,22,32,42,55,67,74,78,80,82,76,71,63,56,51,45,40,37,37,39,41,43,44,44,44,44,39,37,33,30,27,26,26,26,24,25,26,26,26,26,25,24,20,20,21,21,20,19,18,18,17,16,15,14,13,12,11,10,10,9,8,8,7,7,7,8,7,8,9,7,6,6,8,9,9,9,9,9,8,8,8,7,8,8,7,7,6,5,4,4,5,5,5,4,4,4,3,3,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 12,12,13,14,14,15,16,16,15,15,16,17,18,18,19,20,21,22,24,25,27,29,31,31,32,36,41,44,45,46,47,48,39,41,42,41,40,40,42,45,43,42,42,42,43,45,47,48,46,46,46,47,47,47,48,48,55,60,67,75,83,92,101,107,112,113,119,127,135,143,157,170,183,194,209,222,232,242,252,255,255,255,254,254,253,254,255,255,254,254,254,254,254,255,255,255,254,254,255,255,255,254,253,252,255,254,252,253,253,244,228,214,189,171,150,138,130,122,115,112,96,96,95,94,96,103,114,123,128,130,132,131,128,122,116,112,107,103,96,87,78,71,66,64,64,66,69,73,76,78,80,81,85,87,90,93,94,94,93,92,92,99,111,128,149,165,166,160,136,117,90,70,64,66,70,72,67,57,48,47,50,59,73,86,93,90,84,76,70,66,67,69,77,84,88,86,82,82,81,78,73,70,67,67,68,76,92,108,122,127,130,125,119,120,130,140,159,171,181,178,163,140,113,93,77,75,71,69,68,70,72,74,76,73,68,63,61,63,69,74,74,72,68,62,57,55,56,58,61,60,57,51,46,43,43,44,45,45,45,43,40,35,31,28,28,30,32,31,29,31,36,41,50,54,57,54,46,37,32,30,34,41,48,50,44,35,28,25,43,63,89,114,132,132,106,77,55,40,31,40,57,68,71,70,59,49,37,30,32,36,38,38,32,31,29,29,30,33,36,39,38,36,33,30,30,34,42,48,56,58,57,51,42,34,30,30,29,30,32,34,34,34,33,32,42,47,56,65,69,66,59,53,36,30,23,21,23,25,23,20,27,32,40,49,56,60,62,63,57,53,46,38,33,30,29,29,31,32,34,36,36,36,36,35,35,35,36,38,41,45,49,51,53,54,54,54,55,58,64,68,66,73,79,80,79,76,69,61,55,47,38,34,36,40,43,43,42,40,36,31,28,28,31,33,46,51,58,62,62,59,56,53,48,48,46,42,37,34,32,32,32,32,34,35,35,32,27,23,19,19,19,19,21,24,26,28,26,25,24,23,23,23,23,23,37,48,63,75,82,85,87,88,81,75,68,60,54,49,44,40,42,43,45,46,47,47,46,45,40,38,33,29,26,25,25,25,23,24,24,25,25,24,24,23,19,20,20,20,19,18,17,17,16,15,15,13,12,11,10,10,10,10,8,7,7,7,7,7,6,7,8,7,5,5,7,9,9,8,8,8,8,8,7,7,8,8,7,6,5,5,4,4,5,5,5,4,4,3,3,3,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 13,13,14,15,15,16,17,17,16,16,17,18,20,21,22,23,22,23,24,27,29,31,33,34,37,38,40,42,44,45,46,46,38,38,37,36,35,35,35,36,36,37,38,37,38,39,43,46,43,45,46,47,47,48,51,53,58,61,71,82,89,94,104,114,111,125,139,144,149,161,177,187,203,217,235,249,254,254,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,248,251,255,248,238,225,207,191,181,164,147,133,124,118,115,115,109,107,110,112,113,121,132,139,144,143,134,126,122,115,107,105,101,94,88,82,76,69,65,68,67,67,69,72,77,82,85,93,95,99,102,103,103,102,100,99,105,118,138,165,182,181,172,151,122,88,68,62,63,67,71,66,60,51,43,42,50,62,71,84,84,84,82,79,78,79,81,86,88,90,91,88,82,75,70,63,63,63,66,73,85,99,108,125,124,122,116,107,105,115,128,154,168,180,178,163,139,110,90,69,61,56,59,65,68,71,75,74,70,66,63,62,65,69,71,71,69,64,58,52,47,44,42,43,42,41,39,39,40,42,42,44,45,45,43,38,33,31,30,31,32,33,32,32,32,35,37,45,48,50,48,41,35,32,32,30,36,43,44,38,32,30,30,38,61,91,112,118,109,88,70,43,39,38,46,61,70,71,67,53,44,34,29,31,34,34,33,33,31,28,27,28,33,38,41,35,33,31,31,35,42,49,54,65,63,58,51,42,35,32,31,31,33,33,33,32,32,34,36,37,46,57,65,72,73,64,52,45,33,23,22,24,24,25,26,28,32,40,50,59,64,65,65,57,51,43,37,33,31,30,29,28,28,29,29,28,28,27,26,29,34,41,47,50,53,56,58,56,57,59,60,61,62,62,62,64,65,66,66,65,63,61,59,52,48,43,38,35,36,39,41,34,33,30,26,24,25,29,32,43,49,57,63,64,59,52,47,42,40,37,34,32,30,30,30,26,27,29,31,30,27,24,22,19,19,19,20,22,24,26,27,28,30,31,27,23,22,27,32,42,51,66,81,89,91,89,86,82,77,69,61,55,50,45,41,41,43,47,49,49,47,44,42,36,34,30,26,23,22,22,22,21,22,23,24,24,23,21,20,17,17,16,16,16,15,15,15,13,13,13,13,12,11,10,9,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,8,7,7,6,6,7,7,8,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 12,13,14,14,16,16,17,18,16,16,17,18,20,21,22,22,22,23,25,27,30,32,34,35,36,37,39,41,43,44,44,45,37,36,35,33,33,33,33,33,31,32,34,34,34,36,40,43,43,45,47,48,49,50,54,57,66,70,79,90,96,102,111,121,121,134,146,153,163,181,200,211,229,237,248,254,254,253,253,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,251,254,255,245,234,222,205,190,180,165,151,140,134,129,127,123,119,118,122,125,128,135,144,142,145,143,134,127,123,117,110,112,108,101,94,88,80,73,69,66,65,64,66,71,78,85,90,99,102,107,110,111,110,107,105,106,112,124,145,170,188,188,180,154,126,92,71,63,62,65,69,64,58,49,41,39,44,55,63,73,75,77,78,79,81,84,87,91,93,95,94,90,83,75,70,60,60,62,66,75,89,102,111,121,118,113,105,94,90,100,113,141,155,168,167,154,132,105,85,65,58,53,57,62,65,69,73,72,69,65,61,60,62,65,68,69,65,59,52,46,41,38,37,39,38,37,36,36,38,40,41,46,47,46,43,39,34,32,32,32,33,33,31,30,31,34,36,43,46,48,46,40,34,30,29,27,33,39,40,35,31,31,32,44,64,88,103,107,98,78,61,40,36,36,45,59,68,67,63,50,42,32,28,29,32,32,31,31,29,27,26,28,32,37,40,36,35,33,33,38,45,53,58,64,62,58,50,42,35,33,32,32,33,34,33,31,30,32,33,38,48,60,70,78,78,68,56,45,33,23,23,26,27,27,29,28,32,39,48,56,61,62,60,53,48,42,37,35,34,33,32,29,29,28,27,27,27,27,27,30,35,42,47,51,54,57,59,58,58,59,59,58,58,57,56,55,55,55,55,54,54,53,53,50,47,42,38,35,35,36,37,32,31,28,25,23,25,30,34,43,49,57,62,62,56,48,42,37,36,33,31,29,28,27,27,25,26,27,28,27,25,23,22,23,24,25,26,28,29,30,31,29,31,32,29,25,26,31,36,47,56,69,82,89,90,87,84,76,71,64,57,52,47,43,39,40,42,46,48,48,46,43,40,35,33,29,26,23,22,21,21,19,20,21,22,21,20,19,18,17,17,17,16,16,16,15,15,13,13,14,13,13,11,10,9,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,6,6,6,6,7,7,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 11,12,13,14,16,17,18,19,16,16,17,18,19,20,21,21,23,24,26,28,31,33,35,36,34,35,37,39,40,41,42,42,35,34,33,31,30,30,30,30,29,31,33,34,35,37,40,43,43,46,49,51,53,56,61,64,71,75,83,94,100,106,115,126,136,147,160,172,188,210,230,240,252,255,255,255,253,251,253,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,252,255,252,236,224,214,199,182,174,162,152,145,141,139,138,132,130,131,137,142,145,150,156,147,146,141,133,127,125,122,118,120,115,108,101,93,84,76,71,66,64,63,65,72,81,91,97,107,111,116,121,122,119,115,112,112,118,130,149,175,193,195,188,159,132,98,75,65,62,63,67,64,59,50,41,36,39,47,53,62,65,69,72,76,80,86,90,95,97,98,97,91,82,73,67,57,57,61,68,80,94,107,115,119,113,104,92,79,73,81,93,121,136,150,151,141,122,97,79,62,54,50,53,59,62,66,70,70,67,62,58,57,58,60,62,63,59,52,45,39,35,33,33,36,35,34,33,34,37,40,42,49,49,48,45,40,36,35,35,36,37,36,34,32,32,35,37,42,44,46,44,39,32,27,25,24,28,32,33,31,30,32,35,52,67,84,93,92,83,65,50,35,33,34,43,56,63,62,58,44,38,30,26,26,28,29,28,26,25,25,25,28,32,35,38,38,36,35,36,41,49,57,62,63,61,56,49,41,35,33,33,35,36,36,34,31,29,29,30,38,49,62,74,83,83,73,60,46,34,25,25,29,30,30,32,28,31,37,44,51,55,55,54,47,44,41,39,39,40,40,39,32,30,28,27,26,27,28,29,31,36,42,46,50,52,55,58,56,56,56,55,53,51,49,48,44,43,43,42,43,44,45,46,47,45,42,38,35,33,31,31,29,28,26,23,22,26,32,36,44,49,56,61,59,52,42,36,31,30,28,27,25,25,25,25,25,25,25,25,24,24,24,24,27,28,31,33,35,35,35,35,33,34,34,32,30,31,36,42,51,58,69,78,83,82,79,76,66,61,55,50,46,42,39,36,38,40,43,45,45,43,40,38,33,32,29,27,24,23,22,22,19,19,19,19,19,18,16,16,18,18,17,17,17,16,16,16,14,14,14,14,13,11,10,9,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,6,6,5,5,6,6,7,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 11,12,13,14,16,17,18,19,16,16,17,18,19,20,20,21,24,25,26,29,31,33,35,36,32,33,35,37,38,39,39,39,35,34,33,31,30,30,30,30,32,35,38,40,41,43,47,49,47,50,54,58,61,65,71,75,79,82,90,100,107,112,123,133,148,162,180,198,217,237,251,255,255,255,255,254,252,251,254,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,253,252,254,246,224,211,202,187,171,164,155,146,142,140,138,138,135,136,141,148,154,158,160,161,150,145,137,130,127,127,128,128,127,122,114,105,96,86,77,71,68,66,65,67,74,85,96,103,111,115,121,126,127,125,121,118,114,120,131,149,173,192,196,191,165,138,105,82,69,64,64,67,67,62,54,44,38,37,42,46,55,58,63,67,71,77,83,87,97,99,100,97,91,80,69,63,55,56,61,71,85,99,111,117,119,110,97,83,68,61,68,79,103,118,133,136,129,113,93,77,62,54,49,52,57,60,63,67,66,63,58,54,52,52,54,55,55,51,45,39,36,35,36,37,38,37,36,35,37,40,44,46,52,51,50,46,41,38,38,39,42,43,43,41,39,38,38,40,40,42,43,41,37,31,25,22,23,25,26,27,27,29,33,37,55,67,80,85,82,72,56,41,32,31,33,41,52,58,56,51,39,34,27,24,24,25,25,25,21,22,23,25,28,32,34,36,38,37,36,37,42,50,58,63,61,59,54,47,39,35,34,34,38,39,39,37,33,30,30,30,37,48,63,76,85,86,75,62,48,37,28,28,31,31,31,31,28,30,34,40,46,48,48,46,41,40,39,41,44,46,46,46,37,35,31,27,27,28,30,32,33,36,40,43,44,46,48,50,50,49,49,48,46,44,42,40,37,36,34,33,35,38,41,43,43,42,40,38,34,30,27,25,26,25,24,23,23,28,34,39,47,51,57,59,56,47,37,31,26,26,25,25,25,25,25,25,27,26,25,24,24,25,27,28,31,33,36,39,40,40,39,38,39,40,39,37,35,36,41,45,51,56,63,68,70,68,64,61,54,50,45,41,38,36,33,31,35,37,39,41,42,40,38,37,34,33,32,31,29,27,25,25,21,20,20,19,18,17,16,16,19,18,18,18,17,17,17,17,15,15,15,14,13,12,10,9,7,7,7,7,7,7,7,7,8,8,8,8,8,8,8,8,6,6,5,5,5,5,6,6,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 12,12,13,14,16,17,18,18,16,16,17,17,18,19,19,20,22,23,25,27,30,32,34,35,31,32,34,35,36,37,37,37,36,35,34,33,33,33,33,34,36,39,43,46,48,51,54,57,55,58,63,68,72,78,84,88,93,95,103,113,121,127,138,149,161,180,204,224,241,253,255,255,253,254,254,254,253,253,254,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,254,254,240,215,201,192,176,162,155,146,138,134,131,130,129,134,138,145,154,162,167,165,162,150,141,131,125,126,130,135,139,138,131,121,109,99,88,79,73,70,69,69,72,80,90,100,106,113,116,120,123,124,123,120,118,114,119,129,145,168,187,193,190,167,143,111,88,74,67,67,70,69,65,58,48,41,38,39,41,48,52,57,62,67,74,80,85,97,99,101,99,92,81,70,63,56,57,63,73,88,101,110,114,113,103,88,73,60,53,60,71,92,105,119,123,118,107,91,78,65,56,51,52,56,58,60,63,60,58,54,50,47,47,47,48,46,44,41,38,39,41,45,48,47,45,43,42,43,46,50,52,53,52,50,46,42,40,42,43,46,49,52,52,50,46,44,43,40,40,40,38,36,31,26,23,23,23,23,23,24,29,34,38,53,64,75,79,76,66,51,37,30,30,32,39,47,51,49,45,34,31,26,23,23,23,23,23,19,21,24,28,32,34,36,37,39,37,35,36,40,47,55,60,57,55,51,44,37,33,33,34,40,42,42,40,37,34,32,32,39,51,65,78,87,87,76,63,50,39,30,29,31,30,29,29,27,28,31,36,40,42,41,40,36,36,39,44,49,52,52,51,43,39,34,30,28,29,31,33,32,35,37,37,36,36,37,39,40,40,40,39,38,37,35,34,31,30,28,27,29,33,37,40,39,39,39,37,33,29,24,22,24,25,25,25,27,31,37,42,50,53,56,56,51,43,33,27,23,24,25,26,27,28,28,28,30,29,28,27,28,30,32,33,38,39,42,44,45,44,42,41,45,45,44,42,41,42,44,46,51,53,56,59,58,54,50,47,43,39,35,32,30,29,27,26,31,32,35,37,38,38,36,36,36,37,37,36,35,33,31,29,25,24,23,21,20,19,18,18,19,19,19,19,18,18,18,17,16,16,15,15,13,12,10,9,7,7,7,7,7,7,7,7,8,8,8,8,8,8,8,8,7,6,6,5,5,6,6,7,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 13,13,14,15,15,16,17,17,16,16,17,17,18,18,18,19,20,21,23,25,27,30,31,32,31,32,33,35,35,36,36,36,36,36,36,35,36,37,38,38,39,43,47,51,54,57,60,63,66,69,75,80,85,91,98,103,105,107,115,126,134,142,154,165,179,200,226,244,254,255,255,251,253,254,255,255,255,255,254,253,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,253,235,208,195,184,166,153,147,137,129,124,121,118,116,126,134,145,156,167,174,170,163,147,134,122,119,123,131,141,150,149,141,127,114,101,91,82,77,73,75,78,83,91,100,108,113,117,116,116,115,114,113,112,111,111,116,125,139,160,179,187,185,165,142,113,90,76,69,69,73,72,69,63,54,46,41,40,41,42,46,52,58,64,71,78,83,94,96,99,99,93,83,72,65,58,59,63,74,87,98,104,105,99,89,76,63,52,48,55,65,85,97,109,112,109,101,89,79,70,60,53,53,55,55,55,58,54,52,49,45,43,42,43,43,39,39,39,41,45,51,56,60,57,55,51,49,49,51,54,57,53,51,49,45,42,42,45,48,51,57,65,68,66,59,52,48,42,40,37,36,35,33,30,27,25,24,22,22,24,29,34,38,48,58,67,70,67,60,47,36,30,29,29,34,39,42,40,37,31,29,27,24,23,22,22,22,20,24,29,35,39,41,42,42,40,38,35,35,37,43,50,55,54,52,47,40,34,31,32,34,40,42,44,43,40,37,36,36,43,54,67,78,86,86,75,62,48,37,29,29,31,30,28,28,27,27,29,32,36,38,37,36,33,35,40,47,54,56,56,54,46,43,37,32,29,28,30,31,29,31,31,30,29,28,29,30,32,33,33,33,32,31,30,30,26,25,23,23,25,28,32,35,37,37,37,36,33,28,24,21,23,25,28,30,32,36,40,44,52,53,53,50,45,37,29,25,22,24,26,28,30,31,32,32,33,32,32,32,33,35,37,38,45,46,47,47,47,46,44,43,46,46,47,47,47,48,48,48,51,52,53,52,49,44,40,37,34,31,27,24,24,23,22,21,26,27,30,33,35,36,36,36,38,40,41,42,41,38,35,33,30,28,26,24,22,21,20,20,20,20,20,19,19,19,18,18,17,17,16,15,14,12,10,9,7,7,7,7,7,7,7,7,9,9,9,9,9,9,9,9,8,7,7,6,6,7,7,8,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 15,15,15,15,15,15,15,15,16,16,17,17,17,18,18,18,17,18,20,22,25,27,29,30,31,32,33,34,35,35,35,35,36,36,36,37,38,39,41,42,43,47,52,57,60,63,66,69,77,80,86,91,97,103,110,115,117,120,128,139,148,156,170,182,200,220,242,253,255,255,255,253,255,255,255,255,255,255,255,253,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,248,227,200,187,175,153,143,137,127,119,113,109,106,103,112,123,138,153,168,177,173,163,143,127,114,113,121,133,147,158,156,146,130,113,100,90,82,78,81,85,92,101,111,119,125,128,123,119,112,106,102,100,100,101,105,110,117,129,148,168,176,176,159,137,111,90,76,70,71,75,78,76,72,65,57,51,48,48,44,47,52,57,61,67,73,77,85,89,93,94,90,81,71,64,59,59,63,72,84,92,94,93,85,75,65,56,49,47,55,65,81,91,100,102,99,95,86,78,74,64,55,53,53,51,50,52,49,47,44,42,40,39,39,40,35,36,40,45,51,58,65,68,65,62,57,53,51,53,55,58,51,50,47,44,42,43,48,52,60,70,82,89,87,78,66,59,44,40,36,34,35,35,34,32,29,26,24,23,25,30,34,36,45,52,58,57,55,51,43,35,29,27,26,28,31,33,32,30,30,29,28,26,24,22,22,23,25,30,36,43,48,50,50,49,43,40,37,34,36,40,46,50,51,48,44,37,32,30,31,33,37,40,43,43,41,39,38,38,43,52,63,73,79,79,68,56,42,32,25,27,31,31,29,30,26,26,27,30,34,35,35,33,32,35,42,50,57,59,58,55,47,44,38,32,28,26,26,26,24,25,26,25,24,24,25,27,31,31,31,30,30,28,27,26,25,24,23,23,25,28,31,33,36,36,36,34,32,28,25,22,24,27,32,35,38,40,43,45,52,51,48,43,38,31,25,22,21,23,26,30,33,34,35,36,34,34,34,35,37,38,40,41,47,46,45,44,43,42,41,40,42,44,47,50,53,54,52,51,51,50,49,46,41,36,32,29,29,25,22,19,19,19,18,16,21,23,26,30,33,35,36,36,39,41,43,45,44,41,38,36,33,31,28,26,23,22,22,22,21,21,20,20,20,19,19,19,17,17,17,16,14,12,10,9,7,7,7,7,7,7,7,7,9,9,9,9,9,9,9,9,9,9,8,8,8,8,9,9,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 16,16,16,15,15,14,14,14,16,16,17,17,17,17,18,18,15,16,18,20,23,25,27,28,31,32,33,34,35,35,35,35,35,35,35,37,38,41,42,44,47,51,57,62,65,68,72,74,83,87,92,98,104,110,117,122,130,133,141,153,162,172,185,198,215,233,250,255,254,254,255,255,253,253,253,254,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,250,242,219,192,180,166,143,135,129,119,111,105,100,97,94,100,113,131,148,166,177,173,162,140,123,109,109,120,133,149,163,157,146,128,111,97,87,80,76,89,95,105,117,128,135,140,142,128,121,111,101,94,91,92,93,98,103,109,120,139,158,167,167,154,133,108,88,76,69,71,76,85,84,81,74,66,60,57,56,49,52,55,57,59,62,66,70,76,80,85,88,85,77,67,61,59,59,61,70,80,87,87,85,76,68,59,53,48,48,56,66,78,87,95,95,93,90,84,77,76,65,55,52,51,47,46,47,46,45,42,40,38,37,38,38,33,36,41,47,55,62,68,71,69,65,59,54,52,52,55,57,50,49,46,43,42,44,49,54,69,81,96,106,104,93,79,70,45,40,35,33,35,37,37,36,31,28,25,24,26,30,33,35,44,49,50,48,46,44,40,34,28,25,23,23,25,27,26,25,29,30,29,27,25,23,23,23,30,34,42,49,54,56,56,55,46,42,38,35,35,39,44,47,49,46,42,35,30,28,30,33,34,37,41,42,41,39,39,39,40,48,58,66,72,72,61,49,37,28,22,25,30,31,31,32,25,25,26,29,32,34,34,32,32,36,43,51,58,60,58,55,47,44,38,32,27,24,22,22,20,22,23,23,22,23,25,28,31,31,31,30,29,27,25,24,26,26,26,26,27,29,32,33,35,35,35,34,31,28,26,24,24,29,34,39,41,42,44,46,51,49,44,39,33,27,22,20,21,23,26,30,34,36,37,37,33,34,35,37,38,40,41,41,44,43,41,39,37,36,35,35,39,41,46,52,57,58,56,54,49,47,45,40,35,30,26,23,26,23,19,17,17,16,15,14,19,21,24,28,31,34,36,37,39,41,44,46,45,42,39,36,34,32,29,26,24,22,22,22,21,21,21,20,20,20,19,19,18,18,17,16,14,12,10,9,7,7,7,7,7,7,7,7,9,9,9,9,9,9,9,9,10,10,9,8,8,9,10,10,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 15,15,15,15,15,15,15,15,15,15,16,16,16,17,17,17,18,18,18,18,19,21,24,25,27,28,29,30,31,32,33,33,34,36,38,39,40,42,45,48,53,57,63,68,72,76,80,84,86,91,99,105,111,118,127,134,138,143,152,161,171,184,199,210,234,244,253,254,254,255,255,254,255,255,255,255,255,255,255,255,254,254,254,254,254,254,254,254,255,254,252,252,253,255,255,255,253,255,255,255,255,251,246,243,231,229,217,199,183,171,156,142,128,122,115,108,96,85,81,83,89,105,127,149,166,173,166,155,133,109,97,102,112,132,150,152,154,138,118,101,87,78,78,83,95,108,123,136,147,156,156,153,141,126,108,95,86,80,79,83,93,95,102,114,129,140,146,148,132,121,102,84,72,70,76,82,86,91,91,82,72,67,64,62,57,54,53,57,58,58,60,65,67,72,76,75,74,73,68,62,60,62,66,72,76,77,75,72,61,55,48,43,45,52,62,69,80,82,84,85,84,82,80,78,71,65,57,51,48,46,45,45,43,43,42,41,41,40,39,39,35,37,41,48,57,64,68,69,70,64,57,51,48,47,46,45,46,44,42,39,39,43,50,55,70,88,105,113,117,113,93,70,53,40,30,32,36,39,42,47,46,40,33,28,27,29,31,32,37,38,40,41,39,36,32,29,23,23,22,21,22,23,25,26,32,32,31,29,26,25,27,29,34,39,47,56,61,62,61,60,52,46,39,35,34,36,38,39,40,40,38,34,29,27,28,29,38,38,39,40,41,40,37,34,36,40,47,54,56,53,45,39,30,26,23,26,32,35,34,32,31,29,27,27,30,32,33,32,37,39,44,51,57,58,54,49,44,39,32,25,20,20,21,23,18,20,21,21,21,23,27,30,36,38,40,39,35,30,27,25,29,28,28,29,32,33,32,31,36,36,35,33,30,28,26,24,25,28,33,38,41,43,44,44,44,42,38,34,29,24,21,19,19,20,23,26,28,29,29,29,33,33,34,35,37,38,39,40,38,38,36,32,29,29,31,33,38,43,48,52,58,63,62,57,51,46,39,33,29,26,24,21,22,21,20,18,18,17,17,17,20,21,23,26,29,33,36,38,40,41,42,42,41,39,36,34,32,31,29,26,24,23,22,22,23,22,20,19,18,17,17,17,17,17,16,15,13,12,11,10,11,10,9,8,8,8,8,9,12,12,11,11,11,10,10,10,10,10,9,9,9,8,8,8,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 14,14,14,14,14,14,14,14,15,15,15,15,16,16,16,17,18,17,17,17,19,21,23,24,26,27,28,29,30,31,32,32,33,35,38,39,41,43,47,50,54,58,64,69,73,77,81,85,87,92,100,107,112,120,129,136,144,150,159,169,179,192,207,217,238,247,254,255,254,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,252,255,255,254,244,229,217,212,211,196,194,184,169,156,146,133,121,119,113,107,100,89,77,73,74,82,98,122,145,162,168,160,148,126,103,93,99,109,129,146,149,149,134,114,98,85,78,79,85,99,113,129,144,157,168,170,167,146,129,107,91,80,75,78,83,92,93,98,106,116,123,126,126,112,105,92,79,72,74,82,89,94,99,99,89,79,73,70,67,63,59,57,58,58,56,57,61,63,69,72,72,72,72,69,63,66,66,68,70,71,69,65,61,54,50,44,42,45,54,64,71,79,80,81,81,80,77,73,71,66,61,55,51,49,49,48,47,48,48,47,45,43,41,39,38,37,38,42,49,57,63,67,68,65,60,53,47,45,44,43,43,43,43,43,42,42,46,51,56,73,90,108,117,122,118,98,76,51,38,29,30,36,41,46,52,52,45,37,31,29,30,32,33,33,34,34,34,33,30,27,25,23,22,21,21,22,23,25,27,33,33,33,31,28,28,29,31,38,43,51,59,65,66,66,64,54,47,39,33,32,34,36,37,40,39,37,33,29,27,28,29,35,36,38,41,43,43,40,37,37,39,44,48,50,46,40,34,30,27,25,28,34,37,35,32,30,28,26,27,30,32,33,33,36,38,43,49,54,54,50,45,39,35,29,24,21,21,22,24,22,23,24,24,25,28,32,35,41,43,46,45,41,36,33,31,34,33,34,36,39,40,40,39,39,38,36,33,30,27,25,23,25,28,33,38,41,43,43,42,40,38,34,30,26,22,19,17,18,19,21,23,25,26,26,26,28,29,31,34,36,37,38,38,36,35,33,29,26,25,27,29,35,42,48,54,60,65,63,58,53,48,40,33,30,27,25,24,24,23,21,20,18,18,17,17,19,20,23,26,29,32,35,36,38,39,40,40,38,36,34,32,31,30,29,27,25,23,23,22,22,21,20,19,18,18,18,18,18,17,16,15,14,12,11,11,11,11,10,9,8,8,9,9,13,12,12,12,11,11,11,10,11,10,10,10,9,9,9,8,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 14,14,14,14,14,14,14,14,14,14,14,15,15,16,16,16,17,16,17,17,18,20,21,22,25,25,26,27,29,30,31,31,32,34,37,40,42,45,50,53,57,61,66,71,74,78,82,85,87,93,101,108,115,123,132,139,152,158,168,178,188,201,215,225,242,250,255,255,254,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,254,252,255,254,241,219,194,178,172,172,163,161,153,142,133,125,115,105,108,103,98,92,82,70,65,66,76,94,119,143,160,164,154,141,116,96,88,96,107,125,142,144,142,127,108,94,83,78,81,87,105,118,135,149,164,175,178,176,152,132,106,87,75,71,75,82,87,88,91,95,100,103,103,101,91,87,80,74,73,78,88,95,104,108,107,97,86,80,76,72,70,65,60,59,57,53,54,58,59,65,69,69,71,74,72,68,70,70,69,68,66,61,55,50,45,43,40,40,46,55,65,71,77,78,78,77,73,68,63,60,58,55,53,52,54,55,55,55,57,57,55,53,49,44,40,38,39,40,43,50,57,62,65,65,59,54,48,44,42,41,40,40,42,43,45,46,46,49,52,55,70,87,105,116,122,118,99,79,49,38,28,29,38,47,55,60,61,54,44,36,32,32,33,33,32,32,31,30,28,26,24,23,23,22,21,21,22,24,26,27,33,33,34,33,31,31,33,35,40,45,53,61,66,69,68,67,57,49,39,31,28,30,33,35,38,38,36,32,29,27,28,29,32,34,38,43,48,48,46,43,40,40,41,42,42,39,34,29,30,29,29,33,37,39,37,33,29,27,26,27,30,33,34,34,35,37,41,46,49,48,43,40,32,30,27,24,23,24,25,27,27,28,28,28,29,32,36,40,46,50,53,54,51,47,45,43,43,43,44,47,49,50,49,47,44,42,38,34,29,26,23,22,24,27,33,38,41,42,41,39,35,33,30,26,22,19,17,16,18,18,19,20,21,21,22,22,22,24,28,31,34,36,37,37,33,33,30,26,22,21,22,24,32,40,49,56,64,68,66,59,56,50,41,34,30,28,28,27,27,26,24,21,19,18,17,17,18,20,23,26,29,32,34,35,36,36,35,35,34,32,30,29,29,28,27,26,24,23,22,22,20,19,19,18,18,18,19,19,18,17,16,15,14,13,12,12,12,11,10,10,9,9,10,10,14,13,13,13,12,12,12,11,12,11,11,11,10,10,10,9,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 13,13,13,13,13,13,13,13,14,14,14,14,15,15,16,16,16,16,16,17,18,19,20,21,23,24,25,26,28,29,30,31,30,33,37,40,43,47,52,56,59,62,67,72,75,78,82,85,88,94,103,110,117,125,135,143,158,165,175,185,195,207,220,229,243,252,255,255,254,255,255,255,255,255,255,255,255,255,255,255,254,254,254,254,254,254,254,254,255,254,251,250,252,254,255,255,247,236,216,191,169,154,148,147,144,140,134,126,119,112,104,97,98,94,91,87,78,68,64,65,79,96,122,145,161,164,153,139,111,93,88,97,107,123,138,139,134,119,102,89,80,76,81,88,105,117,133,146,158,169,171,169,152,132,107,87,75,70,73,80,81,82,83,85,86,87,85,84,77,76,75,75,77,84,93,100,111,114,112,102,92,86,81,76,75,68,62,59,55,52,52,57,59,65,69,71,75,80,80,76,74,72,69,66,63,58,51,46,40,39,38,41,46,55,63,69,74,74,74,72,68,61,55,51,51,50,51,55,61,66,68,69,68,67,65,61,55,49,43,40,41,42,45,50,56,60,61,60,54,50,45,42,41,41,40,39,43,46,49,50,50,50,50,51,61,75,93,105,112,108,92,75,48,39,30,32,43,55,65,70,70,62,51,41,36,35,35,35,36,35,33,32,30,28,27,26,23,23,22,22,23,24,26,28,31,32,33,33,32,32,34,36,39,44,51,59,65,68,68,68,60,52,39,30,26,28,30,32,36,36,34,31,28,27,28,30,31,34,40,47,53,55,54,51,47,44,42,40,38,36,32,30,31,31,33,36,39,40,37,34,28,27,26,28,31,35,37,37,35,37,39,42,42,40,37,34,29,28,28,28,29,30,30,31,31,31,31,30,29,32,37,40,49,54,60,63,63,62,60,60,59,59,60,61,62,60,56,53,47,44,39,33,28,24,22,21,23,27,32,38,41,41,39,38,33,31,28,24,21,19,18,17,19,19,18,18,19,19,20,20,19,22,26,30,34,36,36,36,34,33,30,26,21,20,21,23,31,40,51,59,67,72,68,61,57,50,41,33,30,30,30,30,30,29,26,23,21,19,18,17,18,20,24,28,31,33,33,33,33,33,31,30,28,27,26,26,26,25,25,24,23,22,21,20,17,17,17,16,16,17,18,19,18,18,17,16,15,14,14,13,13,13,12,11,10,10,11,11,14,14,14,13,13,13,12,12,12,12,12,11,11,11,10,10,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 13,13,13,13,13,13,13,13,14,14,14,15,15,16,16,16,16,16,17,18,19,19,19,19,22,23,24,26,28,29,30,31,30,33,37,41,44,49,54,58,60,64,69,73,75,78,82,84,89,95,104,113,120,129,140,147,166,173,183,193,201,211,222,229,241,250,255,255,254,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,254,254,255,255,255,254,251,228,211,188,168,156,147,140,134,132,126,120,113,106,98,90,86,89,85,83,81,75,67,65,68,84,101,124,144,158,161,149,135,110,94,93,102,109,121,133,133,125,111,94,83,76,75,82,91,101,112,126,136,147,155,157,154,142,125,104,89,78,71,71,75,76,76,75,74,72,70,69,69,68,70,74,78,84,93,102,109,116,119,116,106,98,93,87,82,78,70,62,58,54,50,52,57,60,67,73,77,82,88,89,86,81,77,70,64,59,53,47,43,39,39,40,43,48,55,60,64,71,71,72,70,65,58,51,46,47,48,51,58,68,76,80,82,78,76,73,67,61,53,48,44,43,44,47,51,56,58,58,56,52,49,45,43,43,43,43,42,46,49,53,54,52,49,47,46,52,62,76,88,96,94,81,68,49,43,37,40,52,67,76,79,77,68,55,44,39,37,37,37,40,39,38,35,33,31,30,29,25,24,23,22,23,24,26,27,28,30,32,32,31,31,33,34,38,43,50,58,64,67,68,68,62,53,40,30,26,26,28,30,32,33,32,30,28,28,30,32,34,37,43,51,58,61,61,59,55,51,46,41,39,38,36,34,33,34,35,37,39,38,35,33,28,27,27,29,33,37,40,40,38,38,39,38,35,33,31,30,30,32,34,36,37,36,35,34,32,32,30,29,28,30,35,39,51,57,66,73,76,76,77,77,81,80,79,79,77,71,64,59,49,45,39,32,26,23,21,21,23,26,32,37,40,41,40,39,36,34,30,26,23,22,21,21,21,21,22,22,22,22,22,22,20,22,26,30,33,35,36,37,36,35,32,28,23,22,23,25,32,41,52,61,68,72,68,60,54,48,39,32,30,31,31,32,31,30,27,24,21,19,18,17,20,23,27,31,34,35,34,34,32,31,28,26,24,23,23,23,22,23,23,23,23,22,20,19,16,16,16,15,16,16,17,18,18,18,17,17,16,15,15,15,14,14,13,12,12,12,12,12,14,14,14,13,13,13,12,12,12,12,12,11,11,11,10,10,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 14,14,14,14,14,14,14,14,15,15,16,16,16,17,17,17,16,17,18,19,20,20,19,19,22,23,24,26,28,30,31,32,33,36,40,44,47,52,57,61,63,67,71,75,77,80,83,85,92,98,108,117,125,135,146,153,173,181,190,199,205,213,221,227,234,244,253,254,254,255,255,254,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,255,251,254,255,255,255,249,237,229,205,188,166,152,148,144,135,127,127,120,112,106,98,88,80,78,78,75,74,74,71,67,68,73,90,103,122,138,150,152,141,129,112,97,97,105,109,117,126,124,113,100,85,77,73,76,85,96,101,110,121,128,134,140,139,135,123,110,96,85,77,69,67,70,71,70,67,62,58,55,56,57,64,68,74,81,90,100,110,117,119,120,118,110,104,100,95,88,79,71,62,57,52,49,51,56,60,69,77,83,89,95,95,92,88,81,70,59,52,46,41,38,40,41,43,47,51,55,58,60,67,69,70,69,65,59,52,47,46,47,51,58,69,78,85,88,84,81,76,69,62,55,51,48,48,48,51,54,58,59,57,54,52,49,46,45,46,47,46,46,48,51,55,55,52,48,45,43,46,51,60,71,79,79,72,64,51,49,47,51,64,79,86,85,80,71,57,46,40,38,39,39,43,42,42,40,37,35,32,31,27,26,24,23,23,23,24,25,27,29,31,32,31,30,31,32,38,42,49,56,63,66,68,69,61,52,40,30,25,24,25,26,28,29,29,28,28,29,32,35,38,40,45,52,59,64,65,65,60,56,49,44,42,42,41,40,36,36,37,37,36,34,32,30,29,28,28,31,36,41,43,44,43,42,39,34,30,27,28,29,35,37,41,44,44,42,38,36,31,30,29,28,28,31,37,42,56,63,74,83,88,90,91,91,99,98,97,94,89,81,71,64,48,43,36,29,24,22,22,23,24,27,31,36,40,42,43,43,42,39,35,31,28,26,26,26,25,26,28,29,29,28,27,26,24,25,27,29,31,33,35,36,36,35,32,28,24,23,25,27,32,41,51,59,65,68,64,56,48,43,36,31,30,31,32,32,31,30,27,24,22,20,18,18,22,26,31,36,39,38,37,35,33,30,27,23,21,21,22,23,22,23,24,25,24,23,22,21,19,18,17,17,17,17,17,18,18,18,18,17,17,16,16,16,16,15,14,13,13,13,13,14,14,13,13,13,12,12,12,11,12,11,11,11,10,10,10,9,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 14,14,14,14,14,14,14,14,16,16,17,17,18,18,18,18,17,18,20,21,21,21,20,19,22,23,25,27,29,31,32,33,38,41,45,49,52,56,61,65,68,71,75,78,80,83,86,88,96,103,113,122,131,141,152,160,177,184,193,200,204,209,215,220,226,238,249,253,254,255,255,253,255,255,255,255,255,255,255,255,254,254,254,254,254,254,254,254,250,250,249,245,236,222,207,196,179,166,151,143,142,139,132,125,127,118,109,104,96,84,76,75,72,69,68,69,69,69,74,81,95,106,120,132,141,143,134,122,112,99,99,106,106,111,116,113,101,89,77,71,72,78,91,103,109,116,121,122,122,121,117,110,103,93,82,76,70,64,62,64,64,63,59,54,49,49,52,56,66,70,76,83,91,100,109,116,116,117,115,109,105,103,98,91,82,73,62,55,50,46,48,53,58,68,79,86,93,98,97,93,85,76,63,51,43,39,37,36,40,42,46,50,54,57,59,60,65,67,70,71,68,62,56,52,48,47,49,55,64,74,81,84,85,81,74,67,60,55,52,50,54,54,56,59,62,61,58,55,51,49,47,47,48,50,49,48,47,50,54,55,52,48,45,43,43,43,47,56,63,66,63,61,54,56,58,63,76,90,93,89,80,71,57,46,40,39,40,41,46,47,47,46,43,40,36,34,30,28,26,24,23,22,23,23,27,30,32,32,31,30,30,31,34,38,45,53,59,63,65,66,57,49,38,28,23,21,21,21,24,25,27,27,28,30,35,38,40,41,45,51,58,63,66,66,61,56,50,45,44,44,44,44,38,38,37,35,32,29,28,28,30,29,29,33,38,43,46,47,48,45,40,32,25,24,27,30,40,43,47,50,49,44,38,34,28,29,29,29,31,37,44,50,64,72,83,92,97,99,100,100,105,104,103,100,94,84,72,64,45,41,33,27,22,22,23,24,25,27,30,35,39,43,46,47,47,44,39,34,31,29,29,30,28,31,34,37,38,36,33,31,28,28,27,26,28,30,32,34,33,32,30,26,23,22,24,26,32,40,48,54,59,62,57,49,42,38,33,30,30,31,32,32,30,29,26,24,21,20,19,18,25,29,35,40,43,42,39,37,34,31,26,22,20,20,22,23,23,25,26,28,28,27,25,24,23,22,21,20,19,19,19,20,19,18,18,18,18,17,17,17,17,16,15,14,14,14,14,14,13,12,12,12,11,11,11,10,11,10,10,10,9,9,9,8,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 15,15,15,15,15,15,15,15,17,17,18,18,18,19,19,19,18,19,20,22,22,21,20,19,23,23,25,27,29,31,33,34,42,45,49,52,55,59,65,68,71,74,78,81,83,85,88,90,100,107,117,126,135,146,157,165,176,182,191,197,201,204,209,213,221,234,247,252,254,255,255,253,255,255,255,255,255,255,255,255,250,250,250,250,250,250,250,250,252,245,233,220,206,193,180,173,158,151,143,139,137,135,130,126,125,114,105,101,92,79,72,71,71,68,67,69,70,73,80,88,100,109,119,129,137,139,131,120,112,99,99,105,104,106,109,105,92,81,71,68,71,81,96,109,119,123,124,119,112,106,97,89,90,81,71,67,63,59,58,61,57,57,54,50,48,50,57,63,72,75,79,84,89,96,104,109,111,113,110,105,103,102,97,90,85,74,63,55,48,43,45,50,56,66,78,87,94,98,97,92,78,69,55,44,38,37,37,38,40,42,47,52,57,59,60,60,64,66,70,72,70,65,60,56,49,48,48,52,60,69,75,79,84,79,72,64,57,53,51,51,58,58,60,63,65,64,60,57,51,49,47,48,49,51,50,50,45,49,53,54,52,48,46,45,40,37,39,45,53,57,57,57,56,61,64,70,83,96,97,90,79,70,57,46,40,40,41,43,50,51,52,52,49,45,40,37,31,29,27,24,23,22,22,22,28,31,33,33,32,30,30,30,30,34,40,48,54,58,61,62,53,46,35,27,21,19,18,17,22,23,25,27,28,31,36,39,42,42,44,49,56,62,65,66,60,55,49,45,44,45,45,45,39,39,37,33,29,26,26,26,31,30,30,34,40,45,48,49,51,48,40,31,23,22,26,31,42,46,50,53,51,45,37,32,27,27,28,30,34,42,51,57,71,78,89,98,103,104,105,105,103,103,101,98,92,81,69,61,43,38,31,25,21,22,24,26,26,27,30,34,39,44,48,50,50,47,42,36,33,31,31,31,31,34,39,42,43,41,38,35,31,29,26,25,25,27,30,32,30,29,27,24,21,21,23,25,31,38,45,50,55,57,52,44,37,34,30,29,30,31,31,31,29,28,25,23,21,20,19,19,27,31,38,43,45,44,41,39,35,31,27,22,20,20,22,23,25,27,29,31,31,30,28,27,27,26,25,23,22,22,21,22,19,19,18,18,18,18,18,17,17,16,15,15,14,14,15,15,12,12,11,11,11,10,10,10,10,10,9,9,9,8,8,8,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 13,13,14,14,15,16,17,17,17,18,20,21,22,21,20,19,20,20,21,22,22,23,23,24,26,27,29,31,35,38,41,43,44,47,51,54,57,60,65,68,73,77,81,83,85,89,96,101,106,113,124,133,141,150,160,167,173,175,181,189,192,194,200,208,214,220,231,242,250,253,253,252,253,254,255,253,247,241,236,234,230,227,223,221,221,221,220,219,213,209,200,188,175,163,153,147,135,132,128,126,124,123,120,118,112,108,102,95,86,79,73,70,67,67,68,70,75,81,87,91,94,104,113,118,122,127,124,117,105,101,99,99,101,99,92,86,78,70,64,67,76,91,111,127,136,146,147,136,122,109,92,76,73,66,62,64,65,61,58,57,57,55,51,49,50,54,59,62,71,74,78,81,84,89,94,98,102,106,108,106,104,103,98,92,85,77,64,51,42,41,44,48,54,63,77,89,96,94,88,83,74,60,46,39,36,33,34,37,42,47,54,58,58,57,58,60,59,64,71,74,74,71,68,67,50,47,43,44,49,57,64,67,73,67,61,57,52,49,53,60,60,62,65,68,69,66,62,58,53,50,48,48,50,50,47,44,45,47,50,51,48,46,45,44,36,38,40,42,44,48,54,58,62,66,73,80,85,88,89,90,74,64,52,45,40,37,40,46,46,48,51,52,50,46,40,37,31,27,23,19,19,22,26,29,35,35,35,34,33,30,27,26,26,29,35,43,50,54,55,54,46,40,32,25,22,22,21,21,20,21,22,25,29,34,39,41,41,44,48,50,51,52,54,56,52,48,43,42,44,46,47,46,43,40,35,30,28,27,27,28,27,29,31,34,37,42,48,53,50,48,42,33,25,22,26,30,41,50,58,58,50,40,34,32,31,32,35,42,48,53,59,64,85,90,97,104,106,104,99,96,96,92,88,85,81,72,58,47,37,32,25,22,22,24,24,23,24,26,29,35,42,49,55,59,56,52,47,41,36,33,32,31,36,38,42,47,49,47,42,37,29,26,23,22,23,25,26,26,25,24,22,21,20,21,22,22,26,33,41,44,47,49,46,40,34,30,26,25,27,30,33,34,29,27,24,21,19,19,20,21,29,33,40,45,48,47,44,42,38,34,29,23,20,19,21,22,25,27,30,33,35,35,35,34,33,32,31,28,26,24,22,21,23,22,21,20,20,20,20,20,18,18,17,16,14,13,12,12,12,12,11,10,10,9,8,8,8,8,8,8,8,8,8,8,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 13,14,14,15,16,17,17,17,17,18,20,21,21,21,20,20,20,21,21,22,23,23,24,24,27,28,29,32,35,39,42,43,46,49,53,57,59,63,67,70,73,77,82,85,87,92,99,105,113,120,130,137,144,152,161,167,172,173,178,185,187,188,193,200,201,207,217,227,234,236,236,236,235,234,232,229,224,219,213,210,202,198,194,192,191,191,190,188,183,179,172,162,150,140,131,127,119,116,112,109,108,107,105,103,99,97,93,87,80,74,69,67,65,66,69,73,78,84,89,92,95,103,110,112,115,119,116,110,103,99,96,95,95,91,84,77,70,63,60,66,79,98,121,139,155,164,165,151,133,116,94,76,70,63,59,62,63,59,56,56,58,57,55,54,55,58,61,64,67,69,71,73,75,79,84,88,97,102,105,104,102,100,95,88,80,74,64,53,46,45,47,50,54,62,74,85,91,89,83,78,67,55,42,37,36,35,37,41,46,51,56,59,60,60,61,63,62,65,71,76,78,76,72,69,53,47,41,38,40,46,52,55,62,57,53,51,48,46,50,56,63,65,68,71,71,68,63,59,54,51,48,48,50,51,49,47,46,48,49,49,47,45,45,46,39,40,41,42,43,47,53,57,61,65,71,77,82,83,83,82,67,58,47,41,37,35,38,45,47,48,51,51,49,45,40,37,32,28,23,20,20,24,29,33,38,39,40,39,37,34,30,27,23,25,29,36,43,46,46,45,39,33,26,21,19,19,19,18,19,19,21,25,30,35,40,43,43,45,47,47,46,46,47,49,45,42,39,40,44,48,50,51,48,45,39,33,29,27,27,27,28,29,31,32,34,38,45,49,47,44,39,30,23,22,26,31,42,49,56,55,47,38,33,32,33,36,43,52,60,66,73,77,88,92,97,100,99,95,88,84,80,76,72,70,67,59,48,39,34,29,24,22,22,24,24,23,23,25,29,35,42,49,55,58,56,53,47,41,36,32,30,29,35,37,42,47,49,46,40,35,26,23,20,20,21,22,23,22,25,23,21,19,18,18,19,20,24,31,38,41,43,45,42,36,31,28,25,25,28,31,33,33,31,28,25,22,21,21,21,22,29,34,40,45,48,47,44,42,38,35,30,25,22,21,22,23,27,29,32,34,36,36,36,35,38,37,36,34,32,29,28,27,25,24,23,22,22,21,21,21,18,18,17,16,14,13,12,12,12,12,11,10,10,9,8,8,8,8,8,8,8,8,8,8,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 14,14,15,16,16,17,18,18,18,18,19,20,21,21,20,20,21,21,22,23,24,25,25,26,28,29,30,33,36,40,43,44,49,52,56,59,62,65,69,72,72,77,83,87,91,97,105,112,121,127,135,141,146,151,158,163,167,167,170,175,177,176,180,185,190,195,203,211,216,218,218,217,215,210,204,200,197,193,186,181,171,168,164,161,159,158,156,155,152,148,142,134,125,116,110,106,99,96,92,89,89,88,87,85,83,82,80,77,73,68,65,63,62,64,69,75,81,87,90,93,94,99,103,103,105,108,106,103,102,98,93,90,87,82,74,68,65,60,60,68,83,105,132,152,175,185,185,169,148,125,99,77,67,60,56,58,60,57,55,55,60,60,59,59,60,61,63,64,63,63,63,63,64,68,75,79,92,98,102,101,99,97,90,83,72,69,63,58,54,53,54,55,57,62,70,79,83,82,76,71,59,48,38,36,38,40,43,48,53,57,61,63,64,65,66,67,66,67,71,77,83,83,79,74,59,52,42,35,34,37,40,43,50,46,45,45,44,42,46,53,64,67,71,73,73,70,65,62,56,54,51,51,52,53,53,53,49,50,50,48,45,44,45,46,43,43,42,41,42,45,50,54,57,61,67,72,74,74,71,69,56,48,40,36,33,32,36,42,46,47,49,49,47,43,38,35,31,28,24,22,24,30,37,42,47,48,50,49,46,40,33,29,21,22,25,30,34,37,37,36,31,27,22,18,18,18,19,18,17,18,20,24,30,37,43,46,47,47,46,43,40,37,37,38,37,36,36,39,46,52,57,59,57,53,46,39,33,29,28,27,30,30,29,28,28,32,38,43,43,41,36,28,23,23,29,35,43,48,53,50,42,35,33,34,39,46,56,65,72,78,82,84,88,90,92,92,88,80,71,65,59,56,53,51,50,45,38,32,30,27,24,22,23,24,24,23,23,26,30,37,44,50,55,58,57,54,48,41,35,30,27,26,32,36,42,47,49,45,37,31,22,20,19,19,21,22,22,21,25,23,20,17,16,16,16,17,21,28,34,36,38,39,36,30,28,26,25,27,30,32,33,33,32,30,27,24,22,22,23,24,30,34,40,45,47,47,44,42,39,36,31,27,24,23,24,25,29,31,33,36,37,38,37,37,41,41,40,39,37,34,32,31,28,27,27,26,25,24,23,23,18,18,17,16,14,13,12,12,12,12,11,10,10,9,8,8,8,8,8,8,8,8,8,8,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 14,15,15,16,17,18,18,18,18,18,19,19,20,20,20,20,22,22,23,24,25,26,27,27,29,30,31,34,37,41,44,46,51,53,57,60,63,65,69,72,72,77,84,89,94,102,111,118,125,130,137,142,144,147,152,156,159,157,159,164,165,164,166,171,178,182,188,193,197,198,197,196,194,186,177,172,170,166,159,153,146,143,138,134,133,131,129,127,126,123,118,111,103,97,92,90,84,81,78,76,75,75,74,73,71,70,69,67,64,62,59,58,58,62,68,75,82,86,88,89,91,92,94,95,97,99,101,101,105,101,95,89,83,76,68,63,67,64,65,73,88,110,138,159,186,196,198,183,160,134,105,81,65,58,54,57,59,57,56,56,63,63,63,63,62,61,59,58,55,55,55,55,57,63,72,78,91,97,101,100,97,93,85,77,66,65,65,65,67,67,66,65,64,66,69,74,78,76,70,65,53,43,36,37,43,47,53,58,62,64,67,69,70,71,72,72,70,69,71,78,85,88,83,78,68,60,49,40,36,36,38,39,44,42,41,43,42,41,44,50,60,64,69,73,73,71,69,68,62,60,58,56,56,58,59,59,56,55,53,48,44,42,43,44,44,44,43,40,39,41,45,48,51,55,59,63,64,61,57,54,45,38,32,31,30,29,34,40,44,45,45,44,42,38,35,33,28,26,25,26,31,39,48,54,61,62,63,61,55,46,37,31,23,23,23,26,29,30,29,28,26,23,20,19,20,21,22,22,17,17,20,24,30,38,45,49,51,50,47,41,35,32,31,32,32,33,36,42,50,57,64,67,66,61,54,45,38,33,31,30,32,31,28,25,24,26,31,35,38,37,33,28,24,25,32,39,44,47,48,44,36,32,34,37,50,60,71,76,77,78,78,75,79,80,81,79,72,63,53,47,42,40,38,38,39,37,34,31,27,26,25,24,25,25,25,25,26,29,35,41,47,52,56,58,56,53,47,41,34,29,25,24,31,34,41,46,48,43,34,27,20,19,20,22,26,28,28,28,29,26,22,18,16,15,16,17,19,26,31,32,33,34,31,25,26,26,27,29,33,35,35,33,33,31,28,25,23,23,24,25,30,33,38,43,45,45,43,41,38,36,32,28,26,25,26,27,31,32,34,36,37,38,38,38,40,41,41,40,39,36,34,33,31,31,30,29,27,26,24,24,18,18,17,16,14,13,12,12,12,12,11,10,10,9,8,8,9,9,8,8,8,8,7,7,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 14,14,15,16,16,17,18,18,18,18,18,18,19,19,20,20,22,23,24,25,26,28,29,29,30,31,33,35,38,42,45,47,51,53,57,60,62,65,68,71,73,78,85,91,96,104,113,121,127,133,139,143,143,144,147,151,152,149,150,155,157,156,157,160,163,165,168,171,172,172,171,170,167,159,149,144,142,139,132,127,122,118,113,110,108,106,103,102,102,99,94,88,82,77,74,72,73,71,69,68,68,68,66,64,61,60,58,56,54,53,52,51,56,60,67,74,79,81,82,81,83,83,84,88,92,96,100,104,109,105,99,92,85,77,70,65,70,68,71,79,93,113,140,161,191,202,204,189,166,139,107,82,64,57,53,56,59,58,58,59,64,64,64,63,60,56,52,50,45,46,47,49,55,64,76,83,96,102,104,101,96,90,80,71,62,64,68,74,80,83,81,79,75,73,71,72,74,73,67,61,51,43,38,42,49,56,62,68,70,72,74,76,78,79,78,77,73,70,70,75,83,86,84,80,73,66,57,49,45,44,43,43,43,40,40,41,40,38,42,48,54,59,65,69,71,72,74,76,71,70,68,66,64,64,65,65,64,62,57,50,44,40,40,41,43,43,42,40,38,37,40,42,44,47,50,52,52,49,44,41,37,31,27,28,29,29,34,40,42,42,41,39,37,34,31,29,26,26,27,32,40,50,60,67,75,75,75,72,64,52,40,33,25,23,21,21,23,24,23,22,22,20,19,19,22,24,24,24,18,19,20,24,30,37,45,49,53,51,46,40,33,30,31,32,35,38,42,47,54,61,68,72,72,67,59,50,43,38,36,35,34,33,30,25,22,23,26,29,33,33,31,27,25,27,34,40,45,46,44,38,31,31,36,43,61,73,83,83,78,75,69,62,64,64,65,63,57,48,40,34,29,29,30,31,33,35,34,34,29,29,28,28,27,27,28,29,33,36,41,47,51,54,56,56,53,50,46,40,34,29,25,23,30,33,39,45,45,40,31,24,19,21,24,30,36,40,41,40,35,32,27,22,18,17,18,19,19,25,30,30,31,33,29,24,27,27,28,31,35,36,36,34,33,31,27,24,23,23,24,24,28,31,36,40,42,41,39,38,36,34,31,28,26,26,26,27,30,31,32,34,35,35,36,36,39,40,41,41,40,38,36,34,32,32,32,31,29,27,24,23,18,18,17,16,14,13,12,12,12,12,11,10,10,9,8,8,9,9,9,8,8,7,7,7,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 13,13,14,14,15,16,17,17,18,18,17,17,18,19,20,20,23,23,25,26,28,29,30,31,31,32,34,36,40,43,46,48,51,53,57,60,61,64,67,70,74,79,86,91,96,104,113,120,128,133,140,143,143,143,145,148,148,144,143,148,150,149,148,150,150,151,152,152,152,150,149,148,142,136,129,124,121,117,112,108,104,101,96,92,90,88,86,84,84,82,77,72,68,65,64,63,65,65,64,65,66,64,61,58,55,53,50,47,46,46,48,49,58,61,67,72,75,75,74,72,75,73,76,83,89,95,101,108,112,109,103,95,87,80,75,72,72,72,75,83,94,111,136,157,187,198,202,187,164,136,104,79,64,56,52,56,59,60,60,62,63,63,62,60,57,52,47,44,38,40,44,50,59,71,84,93,106,109,109,102,94,85,74,64,59,62,70,81,92,97,96,93,87,80,74,72,73,71,65,60,54,46,42,47,56,63,70,75,77,78,81,84,87,86,83,80,74,71,69,70,75,79,80,79,75,71,66,61,58,54,50,48,43,40,39,39,38,37,41,48,52,56,62,65,68,71,78,83,82,83,82,79,74,71,70,70,68,66,61,53,46,41,40,40,42,43,44,42,39,37,37,37,39,41,42,43,42,40,37,35,33,28,26,29,30,31,36,42,42,41,39,36,33,31,29,28,26,28,32,40,49,60,69,75,83,83,82,77,68,56,44,37,26,23,19,18,18,18,18,17,18,17,18,20,23,25,25,25,22,21,22,24,29,36,43,48,50,48,44,38,33,33,35,38,43,46,50,53,57,61,66,70,72,67,60,52,45,41,39,39,38,38,35,31,27,25,26,28,29,31,31,30,28,30,36,41,46,45,40,33,27,30,40,49,69,83,92,86,77,70,61,51,47,48,50,49,45,38,31,27,22,24,27,31,34,37,38,39,34,34,34,32,30,30,33,35,40,43,48,52,54,55,53,52,48,47,43,39,34,29,26,24,30,33,38,42,42,37,29,22,21,23,29,37,45,50,51,51,42,38,31,25,21,20,20,21,21,27,31,31,32,34,31,27,28,28,28,31,34,36,35,34,31,29,26,23,21,21,22,23,25,28,32,35,37,37,35,34,32,31,29,26,25,25,25,25,28,28,29,30,30,31,32,32,38,39,41,42,41,39,37,35,33,33,33,32,29,26,23,21,18,18,17,16,14,13,12,12,12,12,11,10,10,9,8,8,10,10,9,8,8,7,6,6,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 12,12,12,13,14,15,15,16,18,18,17,17,17,18,20,21,23,24,25,27,29,30,31,32,32,33,35,37,40,44,47,49,52,54,58,60,62,64,68,70,75,80,86,91,95,102,111,117,124,130,137,140,140,140,141,144,143,137,135,138,140,137,135,136,137,137,136,134,132,130,129,127,118,116,112,107,102,98,95,94,91,87,82,79,78,76,74,73,70,68,65,62,60,59,60,60,62,63,65,67,68,65,60,56,54,51,47,44,44,47,51,54,63,65,69,71,72,70,67,65,67,65,69,79,88,93,101,109,111,108,104,97,89,83,79,77,77,77,81,86,92,104,125,143,169,182,187,175,154,129,99,75,62,55,51,54,59,59,60,63,59,59,59,57,54,50,46,44,40,43,50,58,69,83,97,106,115,116,113,102,90,80,68,57,57,61,70,85,99,106,106,103,95,86,76,71,71,69,64,58,57,49,46,51,60,67,73,79,82,83,86,91,94,92,87,82,75,72,68,65,66,70,75,78,79,78,77,75,72,66,59,54,46,42,40,41,40,40,46,54,53,57,61,63,65,70,80,87,93,94,94,91,84,77,74,73,69,67,63,56,49,44,42,42,42,44,46,46,42,39,36,36,37,37,38,38,37,36,34,33,32,29,28,31,33,34,38,44,43,42,39,35,32,30,29,29,30,33,39,47,57,66,73,77,83,83,82,77,69,58,48,41,29,26,21,18,18,18,18,18,19,19,20,23,27,29,29,28,26,24,23,24,28,35,41,45,45,43,40,36,34,36,41,45,52,55,57,58,57,58,61,64,67,63,57,50,45,42,41,41,44,44,43,39,34,31,30,31,33,36,39,39,37,38,42,46,46,43,37,29,25,31,44,56,75,90,96,86,71,61,49,37,36,37,39,40,37,33,27,24,22,25,31,36,40,43,45,47,41,41,39,36,33,33,37,41,46,48,52,55,55,53,49,47,44,43,40,38,34,31,28,26,31,33,36,39,39,35,27,21,23,26,33,42,50,55,56,55,46,42,35,27,23,21,21,22,24,29,33,34,35,37,35,31,29,27,27,28,31,33,32,31,29,27,23,21,19,19,20,20,22,24,28,31,32,32,31,30,29,28,26,25,24,23,23,23,25,25,25,25,26,27,28,29,34,35,38,39,39,37,34,32,32,32,32,31,29,25,21,19,18,18,17,16,14,13,12,12,12,12,11,10,10,9,8,8,10,10,9,8,8,7,6,6,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 11,11,12,12,13,14,15,15,19,18,17,16,17,18,20,21,24,24,26,27,29,31,32,33,33,33,35,38,41,45,48,49,53,56,59,61,63,65,68,71,76,80,86,90,94,100,109,115,119,125,132,136,136,135,137,139,138,131,128,130,131,127,123,123,123,122,120,118,115,113,111,110,98,97,96,91,86,81,79,79,78,75,70,68,66,65,63,62,57,55,53,52,51,53,55,56,62,64,67,71,72,68,62,57,57,53,49,46,47,52,58,63,67,69,70,71,70,67,64,62,64,61,66,77,86,91,100,109,109,107,103,96,89,84,81,80,84,83,85,88,89,96,113,129,150,164,171,162,145,123,96,73,61,54,50,53,58,59,60,63,57,57,56,55,53,50,47,46,45,50,57,67,79,94,108,117,120,121,114,101,88,76,63,53,55,59,70,86,102,111,111,108,99,89,77,71,70,68,63,57,58,51,48,53,61,68,74,79,84,85,89,95,98,96,89,82,75,72,67,62,60,64,71,76,84,84,85,86,83,75,66,59,50,46,44,44,44,46,53,62,57,60,62,63,64,70,80,89,99,101,102,98,89,81,76,75,67,66,63,58,51,47,45,45,42,46,49,49,45,41,37,36,36,36,36,36,35,35,35,35,33,29,29,33,36,36,40,46,45,43,40,36,33,31,30,30,33,37,44,52,61,68,74,76,81,81,80,76,68,59,50,44,34,30,25,21,21,21,21,21,22,23,24,28,32,34,33,32,28,26,25,25,28,33,40,44,40,39,36,34,33,37,44,49,58,60,61,60,57,55,57,59,62,59,53,48,44,42,42,42,48,49,48,45,40,36,34,34,39,43,47,48,47,47,50,53,46,43,36,27,24,31,47,59,79,94,98,83,64,51,37,23,31,33,35,36,34,30,26,23,25,30,36,42,47,50,52,54,45,45,43,38,35,35,40,45,48,51,54,56,54,51,46,43,41,40,39,37,34,32,29,28,31,33,35,37,37,33,26,21,24,28,35,44,52,56,57,55,48,44,36,28,23,21,21,22,25,31,35,35,37,40,38,34,28,27,25,26,28,30,30,29,27,25,22,19,17,17,18,19,20,22,25,28,30,30,29,28,27,26,25,23,22,22,22,22,22,22,22,22,23,24,25,26,28,30,33,35,35,33,30,28,32,32,32,31,28,24,20,17,18,18,17,16,14,13,12,12,12,12,11,10,10,9,8,8,10,10,9,8,8,7,6,6,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 12,12,11,12,13,14,15,16,16,16,16,16,16,17,19,19,24,25,27,30,32,33,34,34,37,37,37,39,42,45,49,51,55,57,59,60,61,64,68,72,74,78,83,89,94,99,105,109,118,119,123,126,128,129,130,130,128,123,117,116,118,118,115,111,110,107,103,99,96,95,95,95,86,83,78,75,74,74,72,70,68,68,68,66,63,59,55,52,51,52,52,50,48,50,55,60,61,65,71,76,77,73,66,61,54,53,51,50,54,61,69,74,83,86,88,85,76,67,61,58,59,60,63,71,80,89,94,96,101,101,99,95,89,84,82,82,85,88,88,85,83,90,104,116,131,143,152,148,132,110,86,69,56,56,56,58,62,64,65,64,63,62,60,58,56,55,54,54,57,60,66,77,90,101,109,113,115,111,104,94,83,71,61,56,51,55,66,82,98,107,108,106,98,88,76,68,66,64,61,58,51,51,51,50,52,57,65,70,78,82,88,92,94,92,89,86,70,66,59,55,54,58,64,68,76,86,96,98,95,86,72,59,49,44,40,44,54,65,71,72,74,71,64,60,60,67,78,86,98,106,110,103,92,83,75,69,65,62,58,55,54,53,52,50,51,51,51,50,48,44,40,37,37,37,36,35,35,35,36,36,33,33,33,34,36,39,41,43,44,42,39,37,35,34,34,34,37,42,48,54,59,63,67,69,69,70,70,67,61,53,45,40,35,33,29,26,23,21,21,20,23,25,28,31,32,32,32,31,28,24,21,22,26,32,37,40,42,38,33,30,32,41,54,63,66,68,66,60,52,45,42,43,47,48,48,45,41,39,42,46,49,53,56,54,49,45,44,45,47,51,55,58,59,59,59,60,52,42,32,25,24,31,48,65,83,90,92,79,57,37,28,27,27,32,38,40,38,33,30,28,30,36,44,50,53,54,55,56,51,47,41,36,35,37,40,43,51,54,57,54,47,40,37,36,32,34,36,36,34,32,31,32,35,37,38,39,37,33,28,25,24,26,31,40,48,50,48,45,38,35,30,25,23,23,25,26,33,34,37,42,44,44,41,37,32,31,28,26,24,23,23,24,22,20,18,16,15,16,17,19,19,21,23,26,28,28,28,28,26,25,24,23,21,20,19,18,19,19,19,19,20,21,22,22,28,29,30,31,31,30,29,28,27,27,28,27,25,21,18,15,15,15,15,14,14,14,13,13,11,11,11,10,10,9,9,9,12,11,10,9,7,6,5,4,7,7,7,6,6,5,5,5,6,6,6,5,5,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 12,12,12,12,13,14,15,16,16,16,16,16,17,18,19,20,25,26,28,31,33,34,35,35,37,37,38,39,42,45,49,51,55,56,58,59,60,63,67,70,72,76,82,87,91,96,102,106,112,114,117,120,122,123,123,123,122,117,111,109,110,110,106,102,102,100,96,92,89,87,86,86,80,77,73,71,70,70,68,67,66,66,65,63,59,55,51,49,46,47,48,47,46,49,55,60,67,71,76,80,80,75,68,63,56,56,56,59,65,75,85,92,101,103,103,97,85,73,64,59,60,60,62,68,76,82,86,87,94,94,93,90,85,82,81,81,86,89,89,85,82,86,96,106,117,128,136,131,118,101,81,66,57,57,58,62,66,69,69,68,69,68,66,64,62,61,60,59,64,66,71,80,91,101,107,109,107,104,97,89,78,68,60,55,52,54,62,76,90,99,101,99,91,81,69,60,57,56,53,51,47,47,46,45,46,50,56,61,72,77,84,90,91,89,84,81,67,63,56,51,49,52,56,59,71,82,92,95,92,84,70,57,48,44,43,49,61,73,81,83,86,80,70,60,56,60,69,76,90,100,105,100,89,79,70,63,60,58,55,54,54,55,55,54,58,57,56,54,50,46,42,40,37,37,36,36,36,36,36,36,34,33,33,33,34,37,39,40,40,39,37,35,34,34,34,35,40,44,49,52,54,55,57,59,57,58,58,56,52,46,40,36,35,33,30,27,25,23,22,22,23,25,27,30,31,31,30,30,27,24,21,21,26,31,36,38,41,38,33,30,32,41,54,63,69,69,66,58,47,38,35,35,39,42,44,42,40,39,42,45,49,53,56,55,50,47,47,48,51,54,58,60,60,60,61,62,53,44,33,27,25,32,50,66,79,85,85,73,51,34,27,28,32,37,43,45,41,35,31,29,30,36,44,50,53,53,53,54,50,46,41,36,35,37,40,43,50,52,53,48,39,33,30,30,32,34,37,38,36,35,34,34,35,37,38,39,36,32,28,25,24,25,29,36,42,44,41,38,32,30,26,24,22,23,24,26,34,36,40,46,50,51,48,45,37,35,32,28,25,23,22,22,20,19,18,16,16,17,18,18,20,22,24,26,26,26,26,25,25,24,23,22,21,20,20,19,19,19,19,19,19,20,21,22,26,27,28,29,29,28,27,26,25,26,26,25,23,20,16,14,15,15,14,14,13,13,13,13,11,11,11,10,10,9,9,9,11,11,10,9,7,6,5,5,7,7,7,6,6,5,5,5,6,6,6,5,5,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 12,12,12,12,13,14,16,16,17,17,17,17,18,19,21,21,26,28,30,32,34,36,36,37,38,38,39,40,42,45,48,50,54,56,58,59,59,61,65,68,71,74,79,84,87,92,97,100,103,104,107,110,112,112,112,112,112,107,102,100,99,98,95,91,91,90,87,84,81,77,75,74,72,69,67,66,66,66,65,64,64,63,61,58,54,50,46,44,44,44,45,46,49,53,60,65,72,75,79,80,78,73,67,62,59,61,65,70,79,91,103,111,120,121,119,112,99,84,71,65,63,62,62,65,70,74,75,75,83,84,85,83,81,79,79,80,87,89,90,86,82,81,87,93,106,115,121,117,108,96,81,69,58,59,62,68,73,76,77,76,79,78,76,74,72,70,68,68,71,72,74,80,88,94,98,100,94,91,87,80,72,65,59,55,52,53,57,66,77,85,89,89,83,74,61,52,48,46,45,43,45,44,43,41,40,43,48,53,65,71,79,86,87,83,77,73,63,59,53,48,45,45,48,50,64,75,86,89,87,80,66,54,45,45,47,56,71,86,95,99,97,88,74,60,52,53,59,65,79,89,96,94,85,75,64,55,53,51,50,51,54,58,59,59,63,61,58,54,49,45,41,40,37,38,38,38,37,36,35,34,33,33,32,31,31,33,34,35,35,34,33,32,32,33,35,36,43,45,48,48,46,44,43,44,42,43,43,43,42,39,37,35,35,34,31,29,26,25,24,23,23,24,26,28,29,29,29,28,26,24,21,22,27,32,37,39,41,38,34,31,34,43,56,65,73,72,66,55,41,30,26,25,30,34,39,40,38,37,40,42,46,49,53,52,50,48,50,52,54,56,59,60,60,60,61,63,53,44,34,28,27,34,50,66,74,77,75,62,43,30,27,30,40,45,51,51,45,38,33,31,31,37,45,50,52,51,49,49,47,43,39,35,34,36,39,41,48,48,46,39,30,24,22,23,32,35,39,41,40,39,38,38,36,37,39,39,37,33,29,26,23,24,26,30,33,33,30,28,24,23,23,23,23,24,25,26,33,35,41,49,55,58,56,54,46,43,38,32,27,23,21,20,18,18,18,19,19,20,20,20,23,24,25,26,25,24,23,22,23,23,22,22,21,21,20,20,19,19,18,18,19,19,20,21,24,24,25,26,26,25,24,24,23,23,23,22,20,17,15,13,14,14,13,13,13,12,12,12,10,10,10,10,9,9,9,9,11,10,10,9,7,6,6,5,7,7,7,6,6,5,5,5,6,6,6,5,5,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 13,12,12,13,13,15,16,17,17,17,17,18,19,21,22,23,28,29,31,34,36,37,38,38,39,39,39,40,42,45,47,49,53,55,58,59,59,60,63,65,69,72,76,79,82,85,90,93,92,94,96,99,100,100,100,100,99,96,92,91,90,89,86,84,83,82,80,78,74,70,67,65,65,64,62,63,65,66,65,64,64,62,59,55,50,47,44,42,45,46,48,51,56,62,68,73,73,75,76,75,71,65,60,58,62,67,74,81,90,102,114,123,132,132,131,124,112,97,83,74,68,66,65,65,66,67,67,66,72,74,76,76,76,76,78,79,85,88,90,88,83,80,81,84,96,104,110,108,102,93,81,69,62,64,68,74,81,85,86,86,89,88,87,84,81,78,76,74,73,73,73,75,79,83,84,85,80,78,75,71,67,62,59,57,53,51,51,55,62,70,74,76,77,68,56,47,42,40,39,38,44,44,43,42,41,42,46,50,60,66,75,81,82,77,70,64,58,55,50,46,44,43,44,45,57,67,78,82,81,74,62,50,42,44,50,62,78,93,104,110,100,91,76,60,49,48,52,58,67,78,87,86,80,71,59,49,46,45,45,48,54,59,62,63,64,61,56,50,45,41,39,38,39,40,40,40,39,37,34,33,31,30,28,27,27,28,29,30,30,29,29,30,31,33,36,37,43,44,45,43,38,34,32,32,32,32,33,34,35,36,37,37,34,33,31,29,27,26,25,24,23,24,26,27,28,27,27,27,24,22,21,24,30,37,42,44,45,42,37,35,37,47,60,70,79,76,68,54,38,26,20,20,26,31,37,39,37,35,36,37,39,42,45,46,44,45,48,52,53,55,56,55,54,53,55,57,50,42,34,29,28,33,48,63,68,69,65,52,37,28,29,34,47,53,59,57,49,40,35,34,33,39,46,50,50,47,44,42,41,38,34,31,30,32,35,38,43,42,39,32,23,19,20,23,33,37,43,46,45,43,41,41,38,39,40,40,38,34,30,28,23,23,23,23,23,22,21,19,19,21,23,26,28,29,30,30,31,34,40,49,57,62,62,61,56,52,46,39,32,26,23,21,19,20,21,23,24,25,25,25,27,27,28,27,26,24,21,20,22,22,21,21,21,21,21,21,19,18,18,18,18,18,19,20,21,21,21,22,22,21,21,21,20,20,20,19,17,15,13,11,13,13,12,12,11,11,11,11,10,9,9,9,9,9,9,9,10,10,9,8,8,7,6,6,7,7,7,6,6,5,5,5,6,6,6,5,5,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 13,13,13,13,14,15,16,17,18,18,18,19,20,22,24,25,29,30,32,34,36,38,39,39,40,39,39,39,41,43,45,47,52,55,57,58,58,58,60,62,65,68,71,73,75,77,81,83,82,83,86,87,88,88,88,87,86,85,83,83,83,83,81,79,77,76,74,72,68,65,61,60,61,60,60,62,65,67,67,66,65,62,58,53,49,46,44,43,47,48,52,57,64,70,75,78,75,75,73,68,62,57,55,55,63,71,82,92,101,111,122,131,139,139,138,133,122,107,91,81,73,70,67,65,65,64,62,60,63,65,68,70,71,72,75,77,81,85,89,88,84,80,79,79,85,93,99,100,96,89,76,64,66,68,72,79,87,92,94,94,97,96,94,91,87,82,78,76,72,70,69,69,71,72,72,71,67,67,65,64,62,61,60,59,53,50,47,46,50,56,61,65,68,62,52,44,38,35,34,34,41,43,45,46,46,47,50,52,61,66,72,77,76,70,62,57,48,47,45,43,41,41,41,42,50,60,69,73,72,67,56,46,38,42,50,62,77,92,103,109,98,90,76,60,48,43,45,48,57,67,76,78,75,68,57,48,43,42,43,47,53,58,62,63,62,58,52,46,42,40,39,39,43,44,45,44,42,38,33,31,26,25,24,23,23,24,26,27,28,28,28,29,31,34,36,38,40,41,41,38,33,29,26,25,24,25,26,28,31,34,36,37,32,32,31,30,29,27,26,25,25,25,26,26,26,26,26,26,22,22,22,27,34,42,48,50,49,46,41,38,41,50,63,73,83,79,69,54,37,25,21,20,28,33,38,39,35,31,30,31,29,32,35,36,36,38,43,48,50,50,49,46,43,42,43,45,43,38,32,29,28,31,44,56,62,61,55,43,32,27,33,39,52,58,63,60,50,41,38,38,38,42,47,49,46,42,38,36,33,31,28,26,25,27,30,33,37,36,33,28,22,21,24,29,37,42,48,51,50,47,44,42,40,40,41,40,38,35,31,29,23,22,21,19,17,16,16,16,20,23,29,33,36,37,36,35,33,35,41,49,57,64,66,67,63,59,52,44,36,30,26,24,21,22,25,27,29,31,31,32,32,33,32,31,29,26,23,21,21,21,21,21,21,21,20,20,19,18,17,17,17,17,18,18,19,19,18,18,18,18,19,19,18,18,17,16,15,13,11,10,11,11,11,11,10,10,9,9,8,9,9,9,9,9,9,9,10,10,9,8,8,7,6,6,7,7,7,6,6,5,5,5,6,6,6,5,5,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 13,13,13,13,14,15,17,17,19,19,19,20,22,24,25,27,29,30,32,34,37,38,39,39,39,39,38,38,39,41,43,44,49,52,54,55,55,54,56,57,59,61,64,65,66,67,70,72,72,73,75,76,77,76,76,75,74,75,75,76,75,75,74,73,69,68,65,63,60,57,56,55,56,56,57,61,65,68,68,67,66,62,57,52,48,46,45,46,49,51,57,64,72,77,79,79,78,76,71,62,54,51,53,57,64,75,90,101,108,115,124,130,137,138,137,134,124,109,92,81,73,70,66,64,62,61,58,56,56,58,61,64,65,67,70,73,78,82,86,87,84,80,77,76,80,87,92,94,93,88,77,66,68,69,72,79,87,94,97,98,101,100,97,93,87,81,76,73,68,66,63,62,63,63,62,60,57,56,56,56,57,58,60,61,54,50,45,41,42,46,52,56,60,56,49,42,37,33,31,31,36,40,47,52,55,56,58,60,66,68,70,70,67,61,55,51,39,39,39,39,39,38,38,37,44,52,59,61,60,57,49,40,34,39,47,58,70,82,91,96,93,87,76,62,49,41,38,38,48,57,65,67,68,65,57,49,43,42,42,45,51,56,58,59,58,53,47,42,39,40,42,44,48,49,50,49,45,39,33,29,22,22,21,21,22,24,26,28,30,30,30,30,32,34,37,38,39,40,40,36,31,26,23,22,19,20,22,25,28,31,33,34,32,32,32,32,31,30,28,27,27,26,26,26,26,26,25,25,22,22,24,29,37,45,51,53,50,47,42,38,40,49,62,71,79,75,65,51,36,26,23,24,31,35,39,37,32,27,25,25,22,25,28,28,29,32,39,45,47,46,43,38,33,31,32,33,37,33,31,30,29,30,39,50,55,53,47,37,28,27,35,43,54,60,64,59,49,41,40,43,44,47,48,47,42,36,32,29,27,26,23,22,22,24,27,29,31,32,31,27,23,24,30,35,42,47,53,56,54,49,44,41,39,39,39,38,36,33,31,29,23,22,20,17,14,14,16,18,24,29,36,43,46,45,42,40,37,37,40,46,54,62,66,68,64,60,54,46,39,34,30,28,24,25,27,29,32,35,37,38,39,39,38,36,34,30,27,25,22,22,21,21,20,20,19,19,18,18,17,16,16,16,16,17,17,17,16,16,16,16,17,17,17,16,15,14,13,12,11,10,10,10,10,9,9,9,8,8,8,8,8,8,9,9,9,9,9,9,9,8,8,7,7,7,7,7,7,6,6,5,5,5,6,6,6,5,5,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 14,13,13,14,14,16,17,18,19,19,20,21,23,25,27,28,28,30,32,34,36,38,38,39,39,38,37,37,37,39,41,42,45,47,50,51,50,49,50,51,52,54,56,56,56,57,59,60,63,64,65,66,67,66,65,64,65,67,68,68,67,65,64,64,58,57,54,51,49,48,48,48,49,50,53,58,63,66,67,66,65,61,56,51,47,46,47,47,55,58,64,73,82,85,84,81,79,76,67,56,46,45,51,58,70,82,97,106,108,108,111,115,121,122,123,123,117,104,88,77,68,65,62,59,58,57,54,52,50,53,56,58,59,61,64,66,76,79,83,84,82,77,73,71,75,80,83,84,86,86,78,69,68,68,69,75,83,91,96,99,102,100,97,92,85,78,71,67,60,57,54,53,54,54,52,51,48,48,49,50,53,56,58,60,55,51,45,39,38,41,46,51,56,55,51,46,40,36,33,32,33,41,52,62,67,70,71,72,71,70,67,64,58,53,48,45,36,37,38,39,39,37,36,35,38,45,49,49,49,47,40,33,31,35,43,51,60,68,75,79,80,78,72,62,51,43,38,36,41,48,54,57,60,62,58,51,46,44,43,45,49,52,54,54,49,45,40,35,34,38,43,46,53,54,54,53,47,40,32,27,20,20,21,22,24,27,30,32,34,33,32,32,33,35,37,38,39,40,40,36,30,25,22,21,19,20,23,26,28,30,31,32,34,35,35,35,35,33,32,31,29,28,27,26,26,26,26,26,24,24,25,30,38,45,49,51,48,44,39,34,36,44,56,65,71,67,58,45,33,25,25,27,32,35,38,35,29,23,22,22,20,22,24,25,25,30,38,44,47,45,40,32,26,23,23,25,32,31,31,33,31,31,37,45,49,46,40,31,25,27,36,44,53,59,62,57,46,40,42,47,50,51,50,45,38,31,27,25,24,23,21,20,20,23,25,27,28,30,30,27,25,27,33,39,47,52,58,60,57,50,43,40,37,36,36,35,32,30,28,26,22,22,20,16,14,15,20,24,29,35,43,50,53,51,46,43,37,35,35,38,46,54,60,63,61,58,52,46,40,35,32,31,25,25,27,29,33,37,41,43,44,44,43,42,39,35,32,29,23,22,22,21,20,19,18,17,18,18,17,16,15,15,16,16,17,16,15,14,14,15,16,17,17,16,15,13,12,11,11,11,9,9,9,9,8,8,7,7,7,7,7,8,8,9,9,9,9,9,8,8,8,8,7,7,7,7,7,6,6,5,5,5,6,6,6,5,5,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 14,14,14,14,15,16,17,18,19,20,20,21,23,25,27,28,28,29,31,34,36,37,38,38,38,37,36,36,36,38,40,41,41,44,47,48,46,45,46,46,46,48,50,50,49,50,51,53,57,58,59,60,60,60,58,57,61,62,63,63,60,58,57,56,51,49,45,42,41,40,41,42,45,46,49,54,60,64,64,64,64,60,55,50,47,46,47,48,61,64,71,81,90,92,89,85,78,74,63,50,40,40,48,57,76,88,101,107,103,98,96,96,101,103,108,111,109,99,85,74,64,61,57,55,54,53,51,49,47,49,52,54,55,57,60,62,75,78,81,81,79,75,70,67,66,69,70,71,75,78,74,67,67,66,67,71,80,88,95,98,101,100,97,91,83,75,67,63,51,49,46,46,46,46,45,43,43,43,44,46,49,53,57,59,55,51,45,39,36,38,44,48,57,57,55,51,45,40,37,36,34,44,58,71,78,81,82,82,74,71,65,59,52,47,43,41,39,40,41,42,41,39,36,35,34,40,43,42,41,40,35,29,29,33,40,46,52,58,63,67,67,68,67,62,54,46,41,39,37,43,48,51,55,59,57,52,48,46,45,45,47,50,51,50,42,38,32,29,29,34,41,45,56,57,57,55,49,40,31,26,20,20,21,23,26,30,33,35,36,35,34,33,34,35,37,38,41,42,41,37,31,25,21,20,21,23,26,29,31,32,32,32,36,37,38,38,38,36,35,33,30,29,28,27,26,26,26,26,26,25,26,30,37,43,47,48,45,41,35,31,31,39,51,60,64,61,52,41,30,24,26,29,32,34,36,32,26,21,20,21,20,22,24,24,25,30,38,45,49,46,39,31,23,20,20,21,30,30,32,35,33,31,36,43,44,42,35,28,23,26,35,44,52,57,60,54,44,39,43,49,54,53,50,44,35,28,24,22,23,22,21,20,21,23,25,27,27,29,30,28,26,28,34,39,50,55,61,63,58,50,43,38,34,34,33,32,29,27,25,24,22,22,20,17,14,16,23,28,32,38,47,55,57,54,48,44,34,31,29,30,37,45,52,56,58,55,50,44,39,35,33,32,25,25,26,28,32,37,42,45,47,47,47,45,42,38,35,33,24,23,22,21,19,18,17,16,18,17,16,15,15,15,15,15,16,16,14,13,13,14,16,16,16,16,14,13,12,11,11,11,9,9,8,8,8,7,7,7,7,7,7,8,8,9,9,9,9,9,8,8,8,8,7,7,7,7,7,6,6,5,5,5,6,6,6,5,5,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 17,16,16,16,16,17,18,19,21,21,23,24,26,27,29,29,30,31,32,33,35,36,37,38,37,37,37,37,37,38,38,38,40,40,40,40,41,41,41,41,43,43,43,43,43,44,44,44,45,46,47,48,50,51,52,52,54,54,54,53,52,49,47,45,42,40,36,33,33,34,37,40,41,44,48,53,57,60,62,63,61,58,54,51,50,51,54,56,62,68,77,85,90,91,89,88,80,67,52,41,35,36,47,60,80,90,102,104,97,86,78,74,82,88,97,101,97,86,73,64,54,54,55,56,55,52,47,43,42,44,47,49,50,52,55,58,64,67,72,77,78,73,66,60,62,62,64,70,75,75,71,66,59,59,60,66,75,85,93,97,97,96,93,86,76,67,60,57,51,48,45,43,42,41,39,38,39,39,40,42,46,51,56,58,58,53,47,41,38,39,41,44,49,53,56,54,49,43,40,39,38,44,57,74,88,94,92,88,77,69,59,50,44,42,40,39,41,42,44,43,40,38,38,39,32,34,36,36,33,31,30,30,31,33,35,39,43,46,49,50,54,57,60,60,57,50,43,38,32,35,40,45,50,54,56,57,50,48,47,47,47,47,46,44,37,35,31,30,31,36,42,46,57,58,58,55,49,41,33,28,22,22,22,23,26,30,35,37,43,41,38,37,38,38,37,35,42,40,38,34,30,27,25,23,23,25,27,28,28,28,29,30,34,37,40,43,44,42,39,37,35,32,28,26,26,26,26,26,24,25,26,29,32,36,39,41,36,32,26,22,24,31,40,46,51,47,41,34,28,26,28,30,35,35,35,32,28,25,25,25,29,29,28,26,27,32,39,44,55,53,46,36,27,22,24,27,32,34,37,37,35,34,34,34,34,34,32,27,24,28,38,46,56,56,52,45,38,38,44,50,53,52,48,41,34,28,26,25,25,26,25,24,21,21,22,24,24,26,27,25,25,28,36,42,52,57,62,63,57,48,39,33,27,26,25,26,28,29,28,26,21,21,20,17,15,18,24,30,38,47,55,59,60,60,53,46,34,30,27,26,29,34,38,41,43,44,43,39,35,32,31,32,26,25,24,24,26,30,35,37,43,46,49,50,49,45,40,37,33,31,27,22,19,17,17,17,17,18,19,19,20,19,19,19,17,16,16,15,15,16,16,17,15,15,14,13,13,12,11,11,9,9,9,8,8,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 17,17,16,16,17,17,18,19,21,21,23,24,26,27,29,29,31,31,32,33,35,36,37,38,37,37,37,36,36,36,36,36,37,37,37,37,38,38,38,39,40,40,40,40,41,41,41,41,42,42,43,45,46,47,48,49,46,47,46,46,44,42,39,38,38,36,35,34,34,36,39,40,43,45,47,51,53,55,56,57,56,54,51,49,49,51,54,56,66,71,79,86,91,93,91,90,79,67,52,41,35,37,48,60,79,88,98,99,90,78,68,65,66,72,80,84,80,70,58,51,49,50,53,55,55,52,46,42,40,43,48,51,52,53,55,57,61,64,68,73,74,70,62,56,55,55,57,62,67,69,66,62,59,57,58,63,72,82,90,94,95,94,89,81,72,64,60,58,54,53,50,47,44,40,37,34,35,36,38,41,45,49,53,55,57,53,48,43,40,39,40,41,47,52,56,57,53,48,45,43,43,49,61,77,90,97,95,91,74,66,55,45,41,40,41,42,44,45,46,44,41,39,39,40,35,36,37,36,33,30,30,31,32,34,36,38,41,43,44,45,52,54,57,58,55,50,43,39,33,35,39,43,47,52,55,56,57,55,52,48,46,43,40,38,35,33,31,30,32,37,42,45,54,55,54,52,46,39,32,28,21,21,22,24,27,31,35,37,40,38,36,36,38,39,39,38,42,40,37,33,29,26,24,22,22,25,27,28,27,28,29,31,35,38,43,46,47,46,43,41,37,33,29,26,25,25,24,23,23,24,24,26,28,30,33,34,31,28,23,20,22,28,35,40,44,41,36,29,24,23,26,29,34,35,35,34,32,31,32,34,38,37,35,32,32,36,43,48,55,54,50,41,32,28,28,31,36,38,40,39,37,35,34,35,33,34,32,28,25,29,38,47,53,52,48,42,36,35,41,47,51,49,44,37,31,27,27,28,31,31,29,26,23,21,22,23,24,25,26,25,24,28,35,41,50,55,60,60,54,44,35,30,24,23,23,26,29,30,29,28,24,23,21,17,15,18,24,29,37,46,54,57,59,58,52,45,35,31,26,24,25,29,32,33,37,38,39,37,34,31,30,31,26,25,23,23,24,27,30,32,37,39,43,45,45,43,39,37,33,31,27,22,19,18,18,18,18,19,20,21,21,21,21,20,18,18,16,16,15,15,15,16,15,15,14,13,12,12,11,11,9,9,9,8,8,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 17,17,16,16,17,18,19,19,21,21,23,24,26,27,29,29,32,32,33,34,35,36,37,37,37,36,36,35,35,34,34,33,33,33,34,34,35,35,35,36,37,37,37,37,37,37,37,37,37,37,38,39,40,41,42,42,40,40,39,38,37,35,33,32,32,33,34,36,38,39,41,42,45,45,46,46,47,47,47,47,47,47,47,47,49,51,54,56,67,70,76,83,87,89,89,88,78,66,52,42,36,38,48,60,76,84,92,90,80,67,57,54,58,63,70,72,67,58,49,44,42,46,52,56,57,53,47,43,39,44,50,54,55,55,55,55,58,61,66,70,72,68,61,55,49,48,49,54,60,62,60,57,56,55,55,60,70,81,89,94,94,91,84,75,66,61,60,61,61,61,59,55,49,41,35,31,30,32,36,40,44,47,50,51,55,53,49,45,42,39,38,37,44,49,55,58,57,54,51,49,48,53,63,76,89,95,93,90,71,61,48,39,35,38,42,45,50,50,49,46,43,40,41,42,39,39,39,36,32,30,30,31,35,36,37,39,41,42,42,42,50,51,54,54,52,47,42,39,35,35,37,39,43,49,53,56,62,59,55,49,44,39,36,35,33,32,31,32,34,37,41,44,49,49,48,46,41,35,30,27,21,22,23,25,28,31,33,35,34,33,32,34,37,40,41,40,42,40,36,31,26,23,21,21,22,24,26,27,26,27,29,31,36,40,45,50,52,51,49,47,40,36,30,26,24,23,22,20,22,22,21,21,22,24,26,27,26,24,21,20,22,26,30,34,37,35,31,26,22,23,27,31,35,36,38,38,39,42,46,49,51,48,43,39,36,39,45,50,56,57,55,49,41,36,35,36,42,43,44,42,39,36,35,35,33,33,32,29,27,31,40,47,48,47,43,37,32,32,38,43,46,43,38,31,26,26,29,33,40,39,36,31,25,22,21,22,23,24,25,23,23,26,33,40,48,52,56,56,49,40,31,27,20,21,23,27,32,34,34,32,28,26,22,18,16,18,24,28,35,44,52,55,57,57,51,44,37,32,25,21,20,22,24,24,28,31,33,34,32,31,31,31,27,26,24,23,22,23,24,25,29,32,36,40,41,41,39,37,33,30,27,23,20,19,19,19,20,21,22,23,23,23,23,23,20,19,18,16,15,14,14,14,15,14,14,13,12,11,11,11,9,9,9,8,8,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 18,17,17,17,17,18,19,20,21,21,23,24,26,27,29,29,32,32,33,33,34,35,35,35,36,35,35,34,33,32,31,30,30,31,31,32,33,33,34,34,35,35,35,35,34,34,34,34,31,32,32,33,34,35,36,36,37,37,36,35,34,33,32,32,30,32,36,40,43,44,45,45,46,45,43,40,39,38,37,37,39,40,43,46,49,52,54,56,62,64,68,72,75,78,80,80,73,62,50,42,37,37,47,58,71,78,83,81,70,59,52,49,58,63,67,66,59,50,44,41,39,46,55,61,61,56,50,46,42,48,56,60,61,59,56,55,56,60,66,72,74,71,64,58,47,46,45,49,55,58,58,56,53,52,54,60,71,83,93,97,96,90,81,70,62,60,63,67,69,70,70,65,56,46,37,32,30,32,37,41,45,47,48,48,52,51,50,47,44,39,36,33,37,43,50,56,59,58,55,53,48,51,59,70,81,86,86,83,66,56,42,33,31,37,44,48,54,53,51,47,43,41,42,43,43,43,41,37,32,30,31,33,37,39,41,44,46,47,47,47,51,51,51,50,48,44,41,39,37,36,35,36,40,46,53,57,61,59,55,48,42,37,35,35,32,32,33,35,37,39,41,42,44,43,42,39,36,32,29,27,24,25,25,27,28,29,29,30,28,27,27,31,35,40,41,42,41,38,32,27,22,20,19,18,21,23,24,25,25,26,29,31,38,42,48,54,56,56,53,51,43,39,32,27,24,22,20,18,21,20,19,19,20,22,24,26,26,26,25,25,26,28,30,32,34,32,29,26,24,26,31,35,37,39,42,45,49,54,60,65,64,59,52,43,38,38,43,47,56,59,60,57,50,44,41,41,46,47,47,44,40,37,36,36,33,33,32,30,30,34,40,46,45,43,38,33,29,30,36,40,42,38,32,25,23,26,33,39,49,47,42,35,27,22,21,21,22,24,24,22,22,25,32,38,47,50,53,52,46,37,29,25,20,22,26,32,37,40,40,39,33,29,24,19,17,19,24,28,34,43,50,54,56,56,51,44,37,32,25,19,18,19,19,20,21,25,29,32,33,33,34,35,31,30,28,26,24,23,22,21,24,27,30,34,36,37,37,37,32,29,26,22,20,19,20,20,21,22,23,25,25,25,25,25,22,21,19,17,15,14,13,13,14,14,13,13,12,11,10,10,9,9,9,8,8,7,7,7,7,7,7,7,7,7,7,7,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 18,18,17,17,18,18,19,20,21,21,23,24,26,27,29,29,32,32,32,32,33,33,33,33,34,33,32,31,30,29,29,28,29,29,30,31,32,33,34,34,35,34,34,34,33,33,32,32,28,28,28,29,30,31,31,31,35,35,34,34,34,34,34,34,33,36,40,45,47,48,47,46,45,42,38,34,31,30,30,30,34,36,41,46,50,53,54,55,56,56,58,60,62,66,69,71,67,58,49,43,38,38,45,54,64,69,73,70,62,54,51,52,58,61,63,58,49,41,37,37,42,50,62,68,67,62,56,52,50,56,63,67,66,62,57,54,52,58,66,75,79,77,69,63,49,46,43,45,50,54,54,53,50,51,55,63,76,89,98,103,97,90,78,66,59,59,65,70,75,78,79,74,64,52,43,38,34,37,41,44,47,47,46,45,47,48,49,47,44,39,34,30,31,35,43,50,56,57,55,53,48,49,54,63,72,77,77,74,60,51,39,30,30,37,45,50,55,54,50,45,41,40,41,43,45,45,42,38,34,32,32,34,39,41,46,50,54,57,58,58,56,54,50,46,43,42,41,41,41,39,36,36,39,45,52,56,59,58,54,46,38,33,32,33,33,35,37,40,42,42,42,41,40,38,36,33,31,29,28,28,29,29,30,30,29,28,26,25,23,23,24,28,34,39,41,42,39,35,29,23,18,17,17,18,21,23,24,24,25,26,30,33,40,45,51,57,60,58,55,52,45,40,34,29,25,23,21,19,21,20,19,20,22,25,29,31,32,32,33,34,34,35,35,35,34,32,29,26,24,26,32,36,39,42,47,52,57,64,71,76,76,69,59,47,39,37,41,45,55,60,63,61,55,49,45,44,47,47,46,43,39,36,36,37,34,33,32,32,32,36,40,44,42,40,35,30,28,30,35,39,38,34,28,22,21,27,37,44,56,53,46,37,28,23,21,21,22,24,24,22,21,24,31,37,47,49,51,50,43,35,29,26,23,25,31,38,45,48,47,45,37,32,25,20,18,21,25,28,35,43,50,53,56,56,52,46,38,32,25,20,18,19,19,19,18,22,27,31,34,36,39,41,39,38,37,34,31,28,26,24,23,24,26,28,30,31,31,31,30,28,24,21,19,19,20,21,21,22,23,25,26,26,26,26,23,22,20,17,15,14,13,13,14,14,13,12,11,11,10,10,9,9,9,8,8,7,7,7,7,7,7,7,7,7,7,7,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 18,18,18,18,18,19,20,20,21,21,23,24,26,27,29,29,31,31,31,31,31,30,30,30,31,30,30,29,29,28,28,27,28,28,29,30,31,32,33,34,34,34,33,33,32,31,31,30,26,27,27,27,28,28,29,29,33,33,33,33,34,35,37,38,39,41,45,48,49,48,47,45,41,38,33,29,26,25,26,27,32,36,42,48,52,54,54,54,52,50,49,49,52,56,60,63,62,56,50,46,42,40,44,51,56,59,61,58,51,48,51,55,60,63,62,56,45,38,37,39,49,58,70,75,73,67,61,57,59,64,70,72,69,62,56,52,48,56,69,81,88,86,78,71,54,49,44,43,46,49,50,49,49,52,58,68,81,93,102,105,95,87,74,61,53,55,62,69,76,80,83,79,70,58,50,47,42,43,46,47,47,46,44,43,43,44,46,46,43,38,32,29,27,30,35,43,50,53,53,51,48,48,50,57,65,69,69,67,56,48,38,32,33,39,46,50,54,52,47,42,37,37,40,43,46,46,44,41,37,34,34,35,39,42,49,55,61,65,67,68,60,55,48,42,40,41,45,47,49,46,41,39,39,43,49,52,58,56,52,43,33,27,27,28,36,39,43,47,47,46,43,40,37,35,32,29,28,28,30,31,33,34,35,35,34,31,27,25,23,23,24,28,34,39,41,42,38,34,27,21,17,17,18,20,24,25,27,27,27,29,33,37,45,50,56,62,63,60,56,53,45,41,35,30,28,26,24,22,24,23,22,22,25,29,34,37,39,40,41,42,42,41,41,40,36,34,31,26,24,25,30,34,39,44,50,57,63,69,75,79,80,73,60,47,38,36,40,44,54,59,63,62,56,49,45,44,44,44,43,40,37,35,36,37,35,35,34,33,34,37,40,41,40,37,32,28,27,30,34,37,36,32,26,21,21,29,40,49,58,55,48,38,28,23,21,21,23,24,25,23,21,24,31,37,45,48,49,47,41,35,30,27,27,31,37,45,51,54,52,49,40,34,25,20,20,23,27,29,37,44,51,54,57,58,55,49,39,34,26,21,19,19,19,19,18,22,26,31,34,39,44,48,49,49,48,46,43,39,36,34,27,27,27,26,26,26,25,25,27,25,22,20,18,18,19,20,20,21,22,24,25,26,26,26,23,22,20,18,16,15,14,14,13,13,13,12,11,10,10,9,9,9,9,8,8,7,7,7,7,7,7,7,7,7,7,7,5,5,5,5,5,5,5,5,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 19,18,18,18,18,19,20,21,21,21,23,24,26,27,29,29,30,30,30,29,29,28,28,27,28,28,28,28,28,27,27,27,26,27,27,29,30,31,32,33,33,32,32,31,30,29,29,28,27,27,27,27,28,28,28,28,33,33,33,35,37,40,42,44,44,45,47,49,48,46,44,42,38,34,29,25,23,23,25,27,33,37,44,50,54,55,54,52,47,44,41,40,41,46,52,56,59,55,53,51,48,43,45,49,48,50,49,45,40,41,48,55,60,63,62,54,44,39,41,46,55,65,76,81,77,69,64,61,66,70,74,74,68,60,53,49,49,59,76,92,101,100,91,83,62,56,48,45,47,49,50,49,51,54,61,73,85,95,101,103,91,82,68,54,46,48,56,63,73,79,83,81,72,62,57,55,49,49,49,48,47,44,42,40,39,41,43,43,41,37,32,28,25,26,30,37,45,50,50,49,47,46,46,51,57,62,62,61,53,47,39,35,37,41,46,49,50,48,43,37,34,34,38,41,44,45,45,43,39,36,35,35,38,42,49,57,64,69,71,72,62,56,46,39,38,43,51,57,59,55,49,43,40,41,43,45,51,50,47,38,29,24,26,29,40,44,49,52,52,49,44,40,36,34,30,27,27,29,32,34,37,38,40,41,40,37,34,31,26,26,27,30,36,41,43,43,40,35,28,22,19,19,22,25,29,30,31,31,32,34,39,42,52,56,62,67,67,63,57,53,45,41,35,32,30,29,27,26,28,26,25,25,27,32,37,40,45,45,46,46,46,45,45,44,43,41,36,30,26,26,30,33,37,43,51,58,64,68,73,76,73,66,53,40,32,32,37,42,52,57,61,60,54,47,43,42,39,39,38,36,34,34,35,37,37,36,35,35,36,38,39,39,38,33,28,25,25,29,33,35,36,32,26,22,23,31,43,52,59,55,47,37,28,22,21,22,24,25,25,23,22,24,31,37,43,45,46,44,39,33,30,28,31,35,41,49,55,56,53,50,42,35,25,20,21,25,29,31,39,46,53,56,59,60,57,52,42,36,27,21,18,18,17,17,19,21,25,29,34,40,47,52,58,59,59,58,56,52,48,45,40,38,35,32,29,27,26,25,25,23,20,18,17,17,18,19,18,19,20,22,23,24,24,24,22,21,20,18,16,15,15,15,13,13,12,12,11,10,9,9,9,9,9,8,8,7,7,7,7,7,7,7,7,7,7,7,5,5,5,5,5,5,5,5,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 19,18,18,18,18,19,20,21,21,21,23,24,26,27,29,29,30,29,29,28,27,27,26,26,26,26,26,27,27,27,27,27,24,25,26,27,29,30,31,31,31,31,30,29,28,27,27,26,27,27,28,28,28,28,29,29,35,35,36,38,41,44,48,50,47,48,48,48,47,44,41,39,35,32,27,23,21,23,26,28,34,38,45,52,56,55,53,51,42,39,35,33,34,39,46,50,58,56,55,55,52,46,46,50,43,44,41,36,32,35,44,53,55,58,57,50,41,37,41,47,60,69,80,83,78,70,65,63,70,73,76,74,67,58,50,46,53,64,84,102,113,111,102,94,70,63,54,50,50,52,53,52,52,56,64,75,87,95,99,100,86,77,63,49,41,43,51,58,70,76,81,80,72,64,60,59,53,53,51,49,45,42,40,38,37,39,41,41,40,36,31,29,25,25,28,34,42,48,49,48,44,42,42,45,51,56,56,55,51,46,41,38,39,43,47,48,48,45,40,35,31,32,36,40,43,45,46,45,41,38,36,36,37,41,49,57,64,69,71,72,62,55,44,37,38,46,56,64,67,62,54,46,41,38,38,39,42,43,41,35,28,25,29,33,43,47,52,56,55,51,44,40,36,33,29,26,26,29,33,36,38,40,43,46,46,43,40,37,29,29,30,33,38,42,44,45,41,36,29,23,20,22,25,28,33,34,35,35,36,38,43,47,57,61,66,70,69,65,58,54,44,41,36,32,31,31,30,29,31,29,27,27,29,33,37,41,47,47,48,48,47,47,46,45,50,47,42,35,30,29,32,35,35,41,50,58,63,67,70,72,64,56,44,32,25,27,33,39,51,56,60,59,52,46,42,41,35,35,35,34,32,33,35,37,39,37,36,36,37,38,38,37,36,31,26,23,24,27,31,33,36,32,27,23,25,33,45,54,58,54,46,36,27,22,21,22,25,26,26,24,22,25,31,37,41,42,43,42,37,32,29,28,33,37,43,51,57,57,53,49,43,35,25,20,22,26,30,32,40,48,54,57,60,62,59,54,44,37,28,21,17,16,15,14,19,21,24,27,32,40,48,54,64,65,66,66,64,60,55,53,52,49,45,39,35,31,29,29,24,22,19,17,16,16,18,19,16,17,19,21,22,23,23,23,22,21,19,18,17,16,16,16,13,13,12,11,11,10,9,9,9,9,9,8,8,7,7,7,7,7,7,7,7,7,7,7,5,5,5,5,5,5,5,5,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 19,18,18,18,18,19,20,21,21,21,22,23,24,24,25,26,26,26,25,25,24,23,22,22,24,24,25,25,25,26,26,26,26,27,28,30,30,29,28,28,30,29,28,27,27,27,27,27,26,28,30,31,30,31,33,35,35,35,36,37,39,42,44,45,50,50,50,49,46,42,38,36,31,30,28,27,27,30,33,35,42,44,48,52,56,56,53,50,42,38,33,30,31,36,42,47,55,57,59,61,60,57,53,50,45,42,37,34,34,37,42,46,52,52,51,45,39,38,43,49,65,71,77,77,72,66,64,65,64,67,73,72,60,47,42,45,54,72,98,119,133,134,120,105,87,72,57,53,55,55,55,56,62,64,69,78,88,92,91,88,74,65,52,41,37,39,45,49,61,64,68,70,68,65,62,61,54,50,46,42,41,39,37,35,38,39,41,41,39,35,31,28,26,27,31,36,40,42,42,41,36,36,36,38,42,46,51,54,49,50,49,47,44,42,43,44,43,40,35,30,26,27,32,36,39,41,44,45,44,41,37,34,34,36,42,53,64,72,74,73,62,53,42,36,41,54,67,76,74,71,63,50,37,31,33,37,36,36,35,31,27,27,31,35,47,49,51,53,51,48,43,40,34,31,28,25,25,27,30,32,39,42,47,51,52,50,47,44,40,37,35,36,40,42,42,40,34,31,27,25,25,28,32,35,36,37,37,35,35,38,44,50,58,61,66,69,68,62,55,51,45,41,38,35,35,35,33,32,35,32,29,27,29,33,38,41,42,42,41,40,41,45,50,55,58,57,53,47,40,36,34,35,40,44,50,56,60,60,59,57,51,44,33,25,23,28,36,42,50,55,55,48,44,43,38,30,32,31,29,28,29,32,35,37,37,37,37,36,36,36,36,35,31,27,22,20,24,32,38,42,42,39,34,31,33,37,44,48,52,47,39,32,27,26,27,29,33,30,27,25,25,28,31,34,37,41,44,40,33,28,28,30,36,41,48,53,54,51,46,42,33,30,25,21,22,26,32,36,40,48,56,60,63,65,61,55,45,38,29,22,18,18,18,18,20,21,22,27,33,41,48,53,61,63,65,68,68,66,63,62,59,58,54,50,45,39,35,33,31,27,22,18,16,16,14,13,13,13,14,15,17,20,22,23,20,19,18,17,15,14,13,13,14,13,12,10,9,8,8,8,8,8,8,8,8,8,8,8,6,6,6,6,6,6,6,6,6,6,6,5,5,4,4,4,5,5,5,5,5,5,5,5,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 19,18,18,18,18,19,20,21,20,21,21,22,23,24,25,25,26,25,25,24,23,22,22,22,23,24,24,24,25,25,25,26,25,26,27,29,29,29,28,27,28,27,27,26,26,27,27,28,29,31,33,34,33,33,34,36,35,35,36,37,39,41,43,44,47,48,48,47,44,41,37,35,33,32,31,31,32,35,38,41,47,48,50,53,56,55,51,48,38,35,30,27,28,33,39,44,56,59,63,66,66,63,59,57,48,45,40,36,35,36,40,43,47,48,46,41,37,38,44,50,65,70,75,75,69,63,60,61,59,61,65,64,54,44,42,47,62,82,109,131,144,143,128,112,88,73,58,53,54,55,56,57,60,62,68,76,84,86,83,78,64,56,46,39,37,40,45,48,54,56,59,61,61,61,60,60,55,50,44,40,38,38,38,37,41,42,42,41,39,37,35,34,35,36,38,40,41,40,37,35,33,34,34,37,40,45,49,52,50,50,50,47,44,42,43,44,43,41,37,32,28,27,30,33,38,41,45,47,47,43,39,36,33,35,40,51,63,71,73,72,60,52,43,40,46,58,71,79,82,78,69,53,38,30,29,31,30,31,31,30,29,31,36,41,46,47,47,48,47,44,42,40,34,32,28,25,24,26,28,30,37,40,45,49,50,50,47,46,42,40,37,38,40,42,41,39,33,32,30,29,30,32,35,37,37,38,37,36,36,40,46,52,58,61,65,67,65,60,53,48,42,39,36,35,35,36,35,34,36,34,31,29,29,31,35,37,38,37,36,34,36,41,50,56,66,66,63,58,51,45,41,40,41,44,49,53,55,54,52,50,40,35,27,22,22,29,38,44,51,55,53,46,41,39,34,27,27,26,24,24,25,28,31,33,35,35,35,35,35,35,35,35,30,26,21,21,27,35,43,48,50,46,40,35,34,36,40,43,47,43,37,31,28,28,31,33,35,32,28,25,24,26,29,31,34,37,39,36,31,27,28,30,36,40,46,50,51,47,42,39,30,27,24,22,22,26,30,34,39,47,56,60,63,65,62,56,46,40,31,24,20,19,19,19,19,20,23,27,32,39,44,48,55,56,59,61,63,62,62,61,60,60,58,56,52,47,43,40,34,30,24,20,18,17,15,13,11,12,12,13,15,17,19,20,19,19,18,17,15,14,13,13,14,13,11,9,8,7,7,7,8,8,8,8,8,8,8,8,6,6,6,6,6,6,6,6,6,6,6,5,5,5,4,4,5,5,5,5,5,5,5,5,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 18,18,18,18,18,19,20,20,20,21,21,22,23,23,24,24,25,25,24,23,22,22,21,21,22,22,23,23,24,24,24,24,24,25,26,27,27,27,26,26,26,25,25,26,26,28,29,30,35,36,38,38,36,35,36,37,35,35,35,36,38,39,41,42,44,44,44,44,42,40,37,36,35,35,36,37,40,43,46,48,53,53,53,53,53,51,47,43,35,32,28,26,28,32,38,42,55,59,65,69,71,69,65,63,54,50,44,39,36,36,37,38,41,41,40,37,35,39,46,53,64,68,72,70,64,58,54,53,52,52,53,52,45,40,43,50,69,91,119,142,152,148,131,113,88,73,58,53,53,53,55,58,60,62,68,75,80,79,72,66,50,45,40,38,40,44,48,50,48,48,50,52,55,57,59,61,56,50,42,37,37,39,42,43,49,47,44,42,40,40,40,40,42,43,44,45,43,39,35,32,30,31,32,34,38,42,46,49,51,51,50,47,44,43,44,46,45,44,42,37,32,29,29,30,36,40,46,50,51,47,42,39,32,33,39,49,61,69,71,71,58,51,44,43,50,63,76,83,88,83,72,57,41,31,29,30,27,28,28,28,29,33,38,42,43,42,40,39,39,39,40,40,35,33,29,25,24,24,26,27,34,36,40,44,47,47,47,46,45,42,40,39,40,40,39,38,32,33,34,35,37,38,40,40,38,38,37,36,37,42,49,54,59,61,63,64,61,55,48,44,38,36,35,35,37,38,38,38,40,38,35,32,30,30,30,30,31,30,27,26,30,39,51,59,75,77,77,74,66,57,50,47,45,46,49,50,49,46,42,40,29,25,22,21,24,32,41,47,52,53,50,42,36,33,28,22,23,22,21,21,22,25,28,30,33,33,33,33,33,34,34,34,28,25,22,24,31,42,51,56,56,52,46,40,36,36,38,39,40,37,34,31,31,33,36,39,38,34,29,25,23,24,27,29,31,33,34,32,28,27,29,33,37,40,44,46,45,42,37,34,26,25,24,23,24,26,29,31,38,46,54,59,63,66,63,58,48,42,33,26,23,22,21,21,19,21,24,27,32,36,39,40,45,46,48,50,52,54,56,56,56,57,58,58,57,53,49,47,38,34,28,24,21,18,15,13,10,10,10,11,12,14,16,17,18,18,17,16,15,14,13,13,13,12,10,9,8,7,7,7,8,8,8,8,8,8,8,8,6,6,6,6,6,6,6,6,6,6,6,6,5,5,5,4,5,5,5,5,5,5,5,5,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 18,18,17,17,18,18,19,20,20,20,21,21,22,22,23,23,24,23,23,22,21,20,20,20,21,21,21,22,22,22,23,23,23,23,24,24,25,25,25,25,24,25,25,26,28,30,31,33,38,40,42,41,39,37,36,37,34,34,34,34,35,37,38,39,40,41,41,41,41,40,38,37,38,39,41,44,47,50,53,55,56,54,52,51,49,46,41,38,34,32,30,29,31,35,40,44,51,56,63,69,71,70,66,64,58,55,49,43,39,36,35,36,36,36,35,34,35,41,50,57,64,66,68,65,59,52,47,45,45,43,42,41,38,38,45,54,74,95,123,143,150,142,123,105,83,69,56,51,50,50,53,56,61,63,67,73,76,72,62,54,40,38,37,41,47,52,54,54,48,46,45,46,51,56,60,62,56,50,42,38,40,46,52,56,61,57,50,43,40,39,41,43,43,45,47,46,43,38,35,33,28,28,30,32,36,40,43,45,51,51,49,47,44,44,46,49,50,51,50,46,40,34,30,29,34,39,46,52,53,51,45,42,33,34,39,49,61,69,72,72,58,51,43,41,48,63,77,86,86,81,71,58,45,37,34,35,30,29,28,27,27,30,34,37,37,35,32,31,31,34,38,40,38,35,31,27,25,24,25,25,29,31,34,37,40,42,44,44,44,43,41,40,39,39,38,38,33,35,39,41,43,43,42,42,38,37,35,36,38,44,51,55,60,60,60,58,54,49,43,40,36,35,35,37,41,43,44,44,43,42,39,36,32,29,26,25,24,22,20,20,27,40,55,66,82,86,89,86,78,67,58,52,50,50,50,48,45,40,36,33,24,23,23,25,31,39,47,52,53,51,46,38,32,27,23,20,23,22,21,21,23,25,27,29,30,30,31,31,32,32,33,33,28,26,24,28,37,49,59,65,61,56,49,42,38,36,37,38,33,33,32,32,34,38,42,45,42,38,31,25,23,23,26,28,30,31,32,31,29,30,33,37,39,40,42,42,40,37,33,30,24,24,25,26,27,29,30,31,36,44,52,56,61,64,62,57,48,42,34,28,25,24,23,22,21,23,26,29,31,33,34,34,36,36,36,37,39,41,44,45,45,48,51,54,55,53,50,47,41,37,31,26,23,20,16,13,10,10,10,10,11,13,14,15,18,17,17,16,15,14,13,13,13,12,10,8,7,7,6,6,8,8,8,8,8,8,8,8,7,7,7,7,7,7,7,7,7,7,6,6,6,5,5,5,5,5,5,5,5,5,5,5,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 18,17,17,17,17,18,19,20,20,20,20,20,21,21,21,21,22,22,22,21,20,19,19,18,19,19,20,20,20,21,21,21,21,21,21,21,22,22,23,23,24,24,25,27,29,31,33,35,38,41,42,42,39,36,35,34,32,32,31,32,32,33,34,35,36,37,38,39,39,39,39,39,40,42,45,48,51,54,56,57,55,52,48,45,43,40,36,33,33,32,31,31,33,37,42,44,51,55,61,66,68,67,64,62,59,56,51,46,41,37,35,34,34,33,33,34,38,45,54,60,63,64,63,60,53,46,41,38,40,36,34,35,35,37,47,57,78,98,122,137,140,130,111,95,75,63,52,47,46,46,49,53,57,59,63,68,70,64,53,44,36,36,39,47,56,62,63,60,49,46,42,43,49,56,61,63,58,53,47,46,51,59,67,72,74,67,56,45,39,37,39,41,44,46,47,44,39,34,32,31,28,28,30,32,35,38,40,42,48,48,48,46,45,47,51,54,59,60,60,56,48,40,34,31,32,37,45,52,54,52,47,43,36,37,41,51,62,71,75,75,61,52,41,37,44,58,73,83,82,77,69,58,48,42,39,39,33,31,28,26,26,28,30,32,31,29,27,26,28,33,38,42,42,39,36,32,29,27,27,27,26,26,28,30,33,36,38,40,40,40,40,39,38,39,39,40,38,41,45,48,48,46,43,41,36,35,34,36,41,47,52,55,59,58,56,53,48,43,38,36,35,35,37,41,46,49,50,50,47,46,43,38,34,29,25,23,20,19,18,20,28,43,60,71,86,91,95,93,85,74,63,56,54,53,50,47,43,38,35,32,27,29,31,35,41,47,53,56,53,48,41,35,28,23,20,20,23,22,22,22,23,24,26,27,28,28,29,30,31,32,32,33,29,28,29,35,45,56,65,69,66,60,51,42,36,33,33,33,31,32,33,35,39,44,48,51,46,41,34,27,24,25,28,30,34,34,34,34,34,35,38,41,41,41,41,39,36,33,30,28,23,25,27,29,31,32,33,33,35,43,50,53,56,59,57,52,45,40,33,27,25,24,23,23,23,24,27,29,30,30,29,28,29,28,27,26,26,28,29,31,34,37,42,46,48,48,46,44,41,37,32,28,25,21,17,14,11,11,11,11,12,13,14,14,17,16,16,15,14,14,13,13,13,12,10,9,8,7,7,7,8,8,8,8,8,8,8,8,7,7,7,7,7,7,7,7,7,7,7,6,6,6,5,5,5,5,5,5,5,5,5,5,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 17,17,16,16,17,18,19,19,20,20,20,20,20,20,20,20,21,21,20,20,19,18,17,17,18,18,18,18,19,19,20,20,20,20,19,19,19,20,21,22,23,24,25,26,28,31,33,34,35,37,40,39,36,33,31,31,30,29,29,28,29,29,30,31,32,32,33,35,36,38,39,40,41,43,47,50,53,54,54,54,51,48,43,40,38,36,34,31,31,30,30,31,34,38,42,44,52,55,59,62,63,61,59,57,55,53,49,45,40,37,34,33,32,32,32,35,40,48,55,59,62,61,59,55,50,43,37,33,36,32,30,32,34,37,46,56,78,95,114,124,123,114,99,86,65,56,48,45,44,43,45,50,52,53,57,62,63,57,46,38,36,37,41,52,63,69,68,64,49,45,40,42,49,57,63,65,64,61,58,60,66,75,83,87,84,75,61,47,37,34,35,37,45,46,45,39,31,26,26,27,30,30,32,33,35,37,38,39,44,44,45,45,47,51,57,61,68,69,69,64,55,45,37,34,31,36,43,49,52,50,47,44,38,39,43,52,64,73,77,77,64,55,43,36,40,52,65,74,76,71,64,56,50,45,43,43,38,34,30,27,27,28,29,29,26,26,26,28,32,38,43,46,46,44,41,37,34,32,32,31,26,26,25,25,27,30,33,36,36,37,39,40,40,41,44,47,48,50,53,55,53,49,43,40,34,34,35,39,45,51,55,56,58,56,52,47,42,38,35,33,35,35,38,43,49,53,54,54,51,49,45,40,35,31,27,25,21,20,21,24,32,45,60,70,84,88,92,90,83,72,62,56,51,50,47,44,40,37,35,33,32,35,40,45,51,55,58,59,53,46,38,32,27,21,20,23,24,23,23,22,22,23,23,24,26,27,28,29,30,32,33,33,32,33,35,42,52,61,67,70,68,61,50,39,31,28,28,29,33,34,37,40,45,49,53,55,48,44,36,30,28,29,33,36,39,39,39,39,40,41,42,43,42,40,38,35,32,29,27,26,23,25,27,30,32,33,34,35,35,41,47,49,51,53,50,45,39,35,29,25,23,23,22,22,23,24,25,27,27,26,25,24,24,23,21,19,18,18,19,20,25,28,33,37,40,41,40,39,37,34,30,27,25,22,18,15,13,13,12,12,12,12,13,14,16,15,15,15,14,14,13,13,14,13,12,10,9,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,7,7,7,6,6,6,6,5,5,5,5,5,5,5,5,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 17,17,16,16,17,17,18,19,19,19,19,19,19,19,19,19,20,20,20,19,18,17,17,16,16,17,17,17,18,18,18,19,19,18,17,17,17,19,20,21,22,22,23,24,26,28,30,32,30,33,35,36,33,29,27,27,28,27,26,26,25,26,26,27,26,27,28,30,32,35,37,38,42,44,47,50,52,51,50,49,47,44,39,37,36,35,34,33,31,32,33,35,38,41,45,47,52,53,54,55,54,52,50,48,46,45,43,41,38,35,32,31,30,30,32,36,42,48,53,56,61,59,56,52,47,41,35,31,32,28,27,30,33,37,44,52,67,81,95,100,98,93,83,73,57,51,46,45,44,43,44,48,51,52,55,60,62,57,47,39,37,37,42,53,66,72,69,64,50,45,42,45,54,64,70,72,73,72,71,74,81,88,94,96,87,78,62,47,36,32,33,34,39,40,38,32,24,21,23,27,33,33,34,35,36,37,37,37,39,41,42,44,48,54,62,68,75,75,74,68,58,48,39,35,31,35,41,46,48,48,45,43,40,40,43,52,64,73,78,78,66,58,47,40,41,48,56,61,64,61,57,53,51,51,51,51,50,44,37,31,29,28,26,24,24,26,29,34,40,45,50,53,51,49,46,43,40,38,37,37,30,28,25,23,24,27,30,33,32,35,39,41,43,46,51,56,60,61,63,62,58,51,44,40,34,35,38,44,51,57,58,57,56,53,49,43,38,35,32,31,34,35,38,44,50,54,55,55,53,51,46,41,37,33,30,29,24,25,26,29,35,44,56,63,74,77,79,77,70,60,52,48,45,43,41,38,36,35,34,34,34,38,45,52,57,60,60,60,52,43,35,31,26,21,23,28,28,27,26,26,25,24,24,24,25,26,27,29,31,32,34,34,36,37,42,49,57,64,67,68,61,54,43,33,27,27,30,33,37,39,42,45,49,53,55,57,50,46,39,33,31,34,39,42,44,43,44,44,45,45,44,43,40,38,34,30,27,25,24,23,22,23,26,28,31,33,35,35,35,41,45,45,45,46,43,37,33,29,24,21,21,21,21,20,21,22,22,22,22,21,21,20,20,19,18,17,16,15,15,15,18,20,23,27,30,32,32,32,32,30,28,26,25,23,19,16,13,13,12,11,11,11,12,12,15,15,15,14,14,14,13,13,15,14,13,11,10,9,9,9,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,7,7,7,6,6,6,5,5,5,5,5,5,5,5,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 17,16,16,16,16,17,18,19,19,19,19,19,19,19,19,19,20,20,19,18,17,17,16,16,16,16,16,17,17,17,18,18,18,18,17,16,16,18,19,20,20,20,21,22,24,26,28,29,26,29,32,33,30,27,25,24,26,26,25,24,24,24,24,25,22,23,24,26,29,32,35,37,42,44,47,50,50,49,47,46,45,41,37,35,35,36,36,35,34,35,37,39,42,46,49,51,50,50,49,48,46,43,41,40,40,40,39,37,35,33,31,29,29,29,31,36,42,48,51,53,60,58,55,51,46,40,34,30,29,26,26,30,33,36,42,49,53,65,76,79,77,74,68,62,53,48,45,46,45,43,44,48,53,54,57,62,64,61,52,45,37,37,42,53,65,71,68,62,52,48,45,50,61,72,79,80,80,80,80,84,90,96,99,100,88,78,63,47,36,32,32,33,31,32,31,26,20,20,25,31,35,36,36,37,37,37,36,36,37,38,41,44,49,56,65,72,78,78,76,70,59,48,40,36,31,34,39,44,46,46,44,43,39,39,43,51,63,73,78,78,67,60,51,44,44,46,50,52,53,51,49,50,53,56,59,60,62,54,44,36,30,26,21,18,24,27,32,39,46,52,56,57,53,52,49,46,44,42,41,40,33,30,26,23,23,26,29,32,30,34,40,43,46,50,57,62,68,69,69,66,61,53,45,40,35,36,40,48,56,60,60,59,55,52,46,41,36,33,31,31,33,34,38,44,50,54,55,55,54,52,47,42,37,34,32,32,28,29,31,33,36,43,51,57,63,65,66,63,57,49,42,39,39,37,35,34,33,33,33,34,33,38,46,54,59,61,61,61,52,42,34,31,27,22,25,31,33,32,31,30,29,28,27,26,25,26,27,29,31,33,34,35,38,40,45,53,61,65,67,66,51,45,35,28,26,30,36,41,40,42,45,49,52,55,56,57,51,47,40,35,34,37,43,46,46,46,46,47,48,47,44,42,38,36,31,27,24,22,22,22,21,22,24,26,29,32,34,35,35,40,43,42,42,42,38,33,29,25,21,19,19,20,20,19,20,19,19,19,18,18,18,18,18,18,17,17,16,16,15,15,12,13,16,19,22,24,25,26,29,27,25,25,24,23,20,17,13,12,11,10,10,10,11,11,15,15,14,14,14,14,13,13,16,15,14,12,11,10,10,10,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,7,7,6,6,6,5,5,5,5,5,5,5,5,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 14,14,15,16,17,17,18,18,18,18,18,17,17,17,16,16,19,19,19,19,18,16,15,14,13,13,14,14,14,15,15,15,14,14,15,16,17,17,18,18,22,21,21,21,22,23,24,25,25,25,24,24,24,24,24,24,24,23,23,22,22,21,21,20,19,20,21,23,27,31,35,38,41,44,48,51,52,51,49,47,42,42,42,41,41,41,40,40,45,44,43,44,46,47,46,44,47,46,43,40,37,35,34,33,37,36,36,34,32,29,27,26,25,26,29,34,40,46,52,55,57,55,52,47,41,35,31,28,24,25,27,31,34,38,40,42,48,50,54,57,59,58,56,55,53,53,53,52,50,47,44,42,48,52,57,63,66,64,58,53,42,41,42,49,57,60,58,53,46,45,47,55,66,78,85,88,93,90,88,90,95,97,94,90,81,70,55,45,41,39,36,33,35,29,25,27,26,25,30,39,43,44,45,43,40,37,34,34,36,38,41,44,47,55,64,72,79,79,75,67,55,43,34,30,29,31,36,41,44,44,41,39,38,40,45,51,58,65,70,73,65,58,48,41,38,38,39,40,38,36,39,46,53,57,63,70,67,61,51,42,34,30,29,28,29,33,40,47,53,57,59,59,52,47,42,41,44,44,40,36,33,31,27,25,24,26,28,30,28,32,38,44,50,57,64,69,77,77,75,70,63,55,48,44,41,44,49,56,61,63,62,60,56,52,45,38,32,29,27,27,29,31,35,39,43,46,47,48,45,41,35,32,32,32,32,32,34,34,33,34,37,41,45,47,50,48,46,42,38,34,31,30,28,28,29,30,31,30,30,30,37,39,44,50,55,56,54,51,45,41,37,32,31,33,36,39,38,39,39,36,31,28,26,26,28,29,30,32,33,33,34,33,40,43,49,56,61,61,58,55,44,38,30,26,27,33,38,41,45,44,45,48,52,54,53,52,46,41,35,33,35,40,45,48,50,49,47,45,43,42,41,41,38,34,29,24,20,19,19,20,18,19,22,25,27,29,30,31,33,33,34,36,37,36,33,30,22,20,17,15,14,16,19,21,18,18,18,18,17,16,14,13,16,17,19,20,21,20,19,18,16,16,17,18,18,19,19,20,22,22,21,21,20,19,19,19,15,14,12,11,10,10,11,12,12,12,13,14,15,16,16,17,13,13,13,12,12,11,11,10,11,11,11,10,10,9,9,9,8,8,8,9,9,10,10,10,8,8,8,7,7,6,6,6,7,6,5,4,4,4,4,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 14,14,15,15,16,17,18,18,18,18,17,17,17,16,16,16,18,18,18,18,17,15,14,13,12,12,13,13,14,14,14,14,13,14,14,15,16,17,17,18,21,20,20,20,20,21,21,22,21,21,21,22,22,23,23,23,24,23,23,22,21,21,20,20,18,19,20,23,27,31,35,38,42,44,48,51,51,50,48,46,44,45,46,48,49,50,51,51,52,50,49,49,50,50,48,47,44,42,39,36,34,33,33,33,35,35,35,33,31,28,25,23,23,25,28,33,38,45,50,53,54,53,50,45,40,35,30,28,25,27,30,33,36,38,39,40,40,42,45,48,50,51,51,51,53,53,53,52,49,45,42,40,47,51,58,66,70,68,63,58,46,43,42,45,51,54,52,49,47,48,53,62,75,87,94,97,96,92,88,88,90,90,85,81,71,62,52,46,45,46,44,41,43,37,33,34,35,35,41,49,53,52,50,47,43,39,38,37,38,40,43,46,50,57,67,74,78,76,71,62,50,39,31,28,29,31,36,40,44,44,42,40,38,39,42,47,53,59,64,67,64,58,50,44,41,40,39,39,35,33,35,43,50,56,64,72,73,68,60,51,43,38,35,34,35,39,44,50,53,55,55,54,48,43,39,39,41,42,38,35,32,30,27,25,25,26,28,30,30,34,40,46,52,59,66,71,76,76,73,68,60,53,47,44,45,48,54,60,64,64,61,59,53,50,44,38,32,28,26,26,25,28,32,36,39,40,41,41,35,32,30,30,33,36,38,38,38,37,35,33,34,36,39,41,40,39,37,33,29,26,23,21,25,26,27,28,28,28,28,27,32,34,38,43,48,49,47,45,42,39,36,34,34,36,39,41,41,41,40,36,31,28,27,28,30,31,33,34,35,35,34,34,39,41,46,53,57,57,54,51,41,36,30,28,31,37,43,46,50,48,47,48,50,51,51,50,43,39,33,31,34,39,44,46,46,45,43,41,39,39,39,39,33,30,26,21,19,17,18,18,18,19,21,24,26,28,30,30,31,31,32,34,35,35,32,29,22,20,17,14,14,15,18,19,19,20,20,19,18,17,16,15,17,18,20,21,22,21,20,19,16,16,16,17,17,18,18,19,20,20,20,19,19,19,19,19,16,15,13,11,10,10,11,11,11,11,12,13,14,15,15,16,14,13,13,13,12,12,11,11,11,11,11,10,10,10,9,9,8,8,8,9,9,10,10,10,8,8,8,7,7,6,6,6,7,6,5,4,4,4,4,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 13,13,14,15,16,16,17,17,17,17,17,16,16,16,15,15,16,16,16,16,15,14,13,12,11,11,12,12,12,13,13,13,12,13,13,14,15,16,16,17,19,19,18,17,17,17,18,18,16,17,18,19,20,21,22,23,24,24,23,22,21,20,20,19,17,18,19,22,27,32,36,39,45,46,48,50,50,49,46,45,45,47,50,53,56,58,60,61,58,55,53,52,51,50,48,45,39,36,33,30,29,30,32,33,33,33,34,33,30,26,22,20,21,23,26,31,37,42,47,50,50,49,46,43,38,34,30,27,27,29,33,37,39,40,40,40,36,37,38,40,42,44,46,47,54,54,54,53,50,45,41,39,43,49,58,68,74,74,70,65,52,47,42,41,44,46,46,45,48,52,59,71,85,96,103,106,99,94,87,83,80,76,71,66,56,53,50,51,55,58,58,56,55,50,46,47,48,50,56,63,64,61,56,50,45,42,40,39,38,40,42,45,51,59,68,74,75,72,65,54,43,34,28,27,30,33,37,41,44,44,43,42,39,40,41,44,48,53,57,59,61,57,53,49,46,43,39,36,31,28,30,38,47,54,64,73,78,75,69,62,54,47,42,39,43,45,49,51,52,51,49,47,42,39,36,36,38,39,36,33,31,30,27,26,25,26,28,30,32,36,42,47,53,60,67,71,74,73,70,64,56,49,45,44,51,56,62,67,68,65,60,56,50,47,43,37,32,28,25,24,21,24,28,31,33,33,32,30,26,26,26,30,35,40,42,43,43,40,36,32,31,31,34,35,33,32,30,27,23,20,16,15,21,22,23,24,24,24,24,24,25,26,29,33,38,39,38,36,37,36,36,36,38,41,43,45,45,44,41,36,31,29,29,31,34,35,36,37,37,36,35,34,37,38,42,47,51,51,48,45,37,34,31,32,37,44,50,53,55,52,48,46,46,47,46,46,39,35,31,30,32,37,41,44,41,39,36,34,33,34,35,36,30,28,25,22,20,19,19,19,18,19,20,23,25,27,29,30,28,28,29,31,33,34,32,29,24,21,18,15,14,15,17,18,21,21,22,21,21,19,18,17,19,20,22,23,24,23,22,21,16,17,17,17,17,17,18,18,17,18,18,18,18,18,19,19,17,16,14,12,11,10,10,10,10,10,11,11,12,13,13,14,14,14,14,13,13,13,12,12,11,11,11,11,10,10,10,9,8,8,9,9,9,9,10,10,8,8,8,7,7,6,6,6,7,6,5,4,4,4,4,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 12,13,13,14,15,16,16,16,16,16,16,16,15,15,15,14,14,14,14,14,14,13,12,11,10,10,10,11,11,12,12,12,12,12,13,13,14,15,16,16,18,17,16,15,14,14,14,15,14,15,17,19,21,23,24,25,25,25,24,23,22,21,20,19,18,19,20,24,28,33,38,40,47,48,49,49,48,47,45,44,44,47,50,54,57,60,61,62,57,54,51,49,47,45,42,39,33,30,27,24,24,26,30,32,32,33,33,33,30,26,22,20,21,23,26,30,35,40,44,46,46,45,43,40,37,33,30,28,28,31,36,41,44,45,45,44,40,39,37,37,38,41,44,46,54,54,54,53,50,46,41,39,40,46,56,67,75,77,74,71,57,51,44,40,41,43,45,46,50,55,65,78,90,99,104,106,98,91,82,74,67,61,55,51,47,49,54,62,70,75,76,75,71,67,63,63,65,69,74,77,73,67,58,50,45,43,41,41,38,38,40,44,50,58,67,72,72,68,59,47,37,30,28,28,32,36,41,45,46,46,45,45,43,43,43,43,45,47,50,51,56,55,54,53,50,45,38,33,28,25,26,34,44,52,64,74,79,78,75,69,62,54,46,42,46,47,48,49,48,46,43,41,38,36,34,35,36,36,34,32,30,29,27,26,26,27,29,30,33,37,42,47,52,58,64,69,70,69,65,58,49,44,44,45,57,63,70,74,71,65,57,53,47,45,42,38,34,29,25,23,19,21,25,28,29,28,25,23,25,25,28,33,39,43,44,44,47,43,37,32,29,30,33,35,35,34,32,30,26,22,18,16,18,19,20,21,21,21,21,20,20,20,22,25,29,31,30,29,31,32,34,37,40,43,45,46,47,45,40,35,30,29,31,34,38,39,40,40,40,38,35,34,34,35,37,40,43,43,40,38,33,32,33,37,44,51,57,59,58,53,47,42,40,40,40,40,34,31,28,28,31,35,38,40,37,34,31,28,28,29,32,33,31,30,29,27,26,24,24,24,20,20,21,22,24,26,28,29,27,27,28,30,32,33,32,30,26,24,20,17,15,16,17,19,23,23,23,23,23,22,21,20,21,22,24,25,25,25,24,23,19,19,19,19,19,18,18,18,15,16,16,17,17,18,18,19,18,17,15,13,12,10,9,8,9,9,10,10,11,11,11,12,14,14,14,13,13,13,13,13,12,12,11,11,11,10,10,10,9,9,9,9,9,9,9,9,8,8,8,7,7,6,6,6,7,6,5,4,4,4,4,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 12,12,12,13,14,15,15,16,16,15,15,15,14,14,14,14,12,13,13,13,13,12,11,11,10,10,10,10,11,11,12,12,12,12,13,13,14,15,16,16,17,16,15,14,13,13,13,13,15,16,18,21,23,25,27,28,27,26,25,24,23,22,21,20,20,20,22,25,29,34,39,41,47,47,47,46,45,45,44,44,45,47,50,54,56,57,57,57,53,50,47,44,42,39,36,33,28,26,23,21,21,24,28,31,32,33,33,33,30,27,24,22,23,24,27,31,35,38,40,42,43,42,41,39,37,35,32,31,30,33,39,44,48,50,50,49,45,42,39,36,35,37,40,42,48,50,51,51,49,45,41,38,39,44,54,65,74,77,76,73,61,56,49,44,43,45,48,49,54,61,71,81,90,95,99,101,91,84,74,64,56,49,44,41,45,51,62,75,86,92,93,92,88,85,81,80,83,88,90,89,77,70,59,51,47,46,45,44,40,40,40,44,51,59,66,71,68,63,54,43,34,30,31,33,38,44,50,53,53,51,49,49,46,46,45,45,44,44,44,44,50,51,53,55,54,48,39,32,28,24,26,33,42,51,62,71,77,77,77,74,68,60,52,47,44,44,43,42,41,39,37,36,36,35,35,35,36,35,33,31,29,28,27,27,27,28,29,30,33,36,40,44,48,53,58,62,64,63,59,50,42,39,42,46,62,69,76,77,72,62,54,49,44,44,43,41,37,31,26,23,19,21,24,27,27,26,24,23,26,28,32,39,46,49,50,49,46,42,36,31,29,32,36,39,41,40,39,36,32,27,23,20,17,18,19,20,20,20,19,19,19,18,19,21,25,27,27,26,28,29,32,35,38,41,43,44,43,41,37,32,28,29,32,35,40,41,42,42,41,37,34,32,30,30,31,34,36,36,34,32,31,31,35,41,49,56,60,61,56,51,43,38,35,35,35,34,31,29,26,27,29,33,35,35,34,31,27,25,25,28,32,35,37,37,36,35,33,31,29,28,24,24,24,24,25,26,28,29,28,27,27,29,32,33,32,31,28,26,22,18,17,18,19,21,24,24,25,25,25,24,23,22,22,23,25,26,27,26,25,24,23,23,22,22,21,20,20,20,15,15,16,16,17,18,18,18,18,17,16,14,13,11,9,8,9,9,9,9,10,10,10,10,13,13,13,13,13,13,13,13,12,12,12,11,11,11,10,10,9,9,9,9,9,9,9,9,8,8,8,7,7,6,6,6,7,6,5,4,4,4,4,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 11,11,12,12,13,14,15,15,15,15,14,14,14,13,13,13,12,12,13,13,13,13,12,11,10,10,10,11,11,12,12,12,12,13,13,14,15,16,16,17,16,15,14,14,13,14,14,14,18,19,21,23,26,28,30,31,29,29,28,26,24,23,22,21,21,22,23,25,29,33,37,40,44,43,42,41,40,40,41,41,45,47,50,53,54,54,53,52,48,45,42,39,38,35,32,29,24,23,21,20,21,23,26,29,32,31,31,30,29,27,26,25,27,28,30,33,36,37,38,39,41,41,41,40,39,37,35,34,32,35,40,45,48,50,51,51,44,41,37,33,32,33,35,37,42,44,47,49,49,46,42,40,42,46,53,63,71,75,75,74,65,61,55,50,48,48,50,52,56,63,72,79,84,87,89,90,81,75,66,56,48,43,40,40,49,57,71,86,96,102,103,102,98,98,95,93,95,99,97,92,76,68,57,51,49,49,48,47,44,42,41,45,51,59,66,69,64,60,52,43,36,35,38,42,49,56,64,67,65,60,57,56,50,51,51,50,48,46,43,41,46,49,54,58,57,51,42,35,31,27,29,35,43,49,58,67,73,74,75,75,71,64,57,53,42,40,37,34,32,32,32,33,35,35,36,36,35,33,31,30,28,28,27,27,27,28,29,30,32,35,38,41,43,47,51,55,57,56,51,42,35,34,41,48,65,71,78,77,69,58,50,45,44,45,46,44,41,34,28,24,21,22,24,26,27,28,27,27,29,32,39,47,55,58,57,55,44,40,33,29,29,34,40,44,46,46,45,42,37,31,25,22,18,19,20,20,21,21,20,20,21,19,19,20,23,25,26,26,26,27,29,31,33,35,37,38,34,33,31,28,26,28,32,36,41,42,43,43,40,36,31,28,27,26,26,28,30,31,30,28,29,32,36,44,52,57,59,58,51,46,39,35,33,33,32,32,30,28,26,26,29,31,32,31,29,27,24,23,26,31,38,43,48,48,47,46,43,39,36,34,31,30,28,27,27,27,29,30,29,28,27,28,30,32,31,30,27,25,21,19,17,18,20,22,24,25,25,26,26,25,24,24,23,24,25,27,27,27,25,25,26,25,24,24,22,21,21,20,16,16,17,17,17,17,17,18,16,16,16,15,14,12,10,9,9,9,9,9,9,9,10,10,11,11,11,12,12,12,13,13,13,12,12,12,11,11,11,11,10,10,9,9,9,9,8,8,8,8,8,7,7,6,6,6,7,6,5,4,4,4,4,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 10,10,11,12,13,13,14,14,14,14,14,13,13,13,12,12,12,12,13,14,14,13,13,12,11,11,11,11,12,12,12,13,13,14,14,15,16,17,17,18,15,15,15,14,15,15,16,17,20,21,23,25,27,29,31,32,31,31,30,28,26,25,23,23,21,21,22,24,27,30,34,36,38,37,35,34,34,35,36,37,42,44,47,50,51,50,48,47,41,38,35,34,33,31,28,26,23,22,21,21,22,23,25,27,30,29,28,26,26,26,27,28,31,32,34,36,37,37,37,36,40,41,41,41,41,40,39,38,36,37,40,42,45,46,47,48,41,38,34,31,30,31,33,35,42,45,49,53,54,53,50,48,48,50,55,62,69,73,74,74,68,66,62,57,52,50,50,51,51,57,65,70,72,73,75,76,72,68,60,51,45,42,43,44,53,63,77,91,100,104,105,104,98,99,97,94,96,98,92,82,67,59,50,45,46,47,46,45,43,40,38,41,48,55,60,62,61,58,52,45,41,41,46,50,61,69,79,83,78,71,66,64,60,62,63,63,60,55,49,46,46,49,55,61,62,56,47,40,35,32,33,39,44,48,54,61,64,66,69,70,68,64,58,55,43,40,34,28,26,26,28,30,33,35,36,36,33,30,28,27,27,27,27,27,28,29,29,29,33,35,38,39,40,43,46,49,50,49,45,36,29,30,40,49,66,72,77,75,65,54,46,43,44,46,48,48,45,38,31,26,22,22,24,25,27,30,31,32,39,42,49,56,62,63,60,57,41,37,31,26,27,33,41,46,51,51,49,45,40,32,26,22,20,21,22,22,23,23,22,22,23,21,19,20,22,25,26,26,26,26,26,26,27,28,30,31,25,25,25,24,24,27,32,36,41,42,43,42,39,34,28,25,24,23,22,24,26,28,28,27,30,32,38,46,53,56,55,54,47,43,37,34,33,33,33,33,30,28,26,27,28,29,29,28,24,22,21,23,29,38,48,55,63,63,62,60,56,51,46,43,37,35,33,30,29,29,29,30,29,27,26,26,28,29,28,27,24,22,19,17,16,17,20,21,24,25,25,26,26,25,25,24,23,24,25,27,27,26,25,25,26,26,25,24,22,21,20,19,18,18,18,18,17,17,17,17,15,15,16,16,15,13,11,10,10,10,10,10,10,10,10,10,9,10,10,10,11,11,12,12,13,13,12,12,12,11,11,11,10,10,10,9,9,8,8,8,8,8,8,7,7,6,6,6,7,6,5,4,4,4,4,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 10,10,11,11,12,13,14,14,14,14,13,13,13,12,12,12,12,12,13,14,14,14,13,13,11,11,12,12,12,13,13,13,14,14,15,16,17,17,18,18,15,15,15,15,16,17,18,19,21,22,23,25,27,29,31,32,33,32,31,29,27,26,24,24,20,20,21,22,24,28,31,33,33,32,30,29,29,30,32,34,37,39,43,46,47,46,44,43,34,32,29,28,28,27,24,22,22,22,22,22,23,24,25,25,28,27,25,23,23,25,27,29,34,35,37,38,38,37,36,35,41,41,42,42,42,42,41,40,39,39,39,40,41,42,43,43,39,37,34,31,31,32,34,36,45,49,54,59,62,61,58,56,52,53,56,62,68,73,74,74,70,69,66,61,55,51,48,48,43,49,56,60,61,62,64,66,67,63,57,49,44,44,46,49,56,65,80,92,100,103,103,102,92,94,92,89,90,91,83,71,58,50,42,38,41,43,42,40,39,36,34,36,43,50,54,56,60,57,52,46,44,46,51,56,69,78,89,93,88,79,72,70,70,72,74,75,71,65,58,53,46,50,57,63,65,60,51,44,38,35,36,41,45,47,52,58,56,59,62,64,64,60,56,53,46,40,33,26,22,23,26,28,32,34,36,35,32,28,26,25,27,27,27,28,28,29,29,29,34,36,38,39,39,40,44,46,46,46,41,32,25,28,39,50,66,72,76,73,63,51,44,41,45,47,50,50,47,40,32,27,22,22,23,24,27,31,34,36,49,52,57,63,66,64,59,54,40,35,29,24,26,32,40,46,55,54,52,48,42,34,27,23,21,22,23,24,24,24,24,24,24,22,20,20,22,25,26,27,26,25,24,23,23,24,25,26,18,19,21,21,23,26,31,35,41,42,42,42,38,32,27,23,23,21,20,22,24,26,27,26,30,33,39,47,53,55,53,50,44,41,37,34,34,35,35,34,30,28,27,27,28,29,27,26,19,18,19,23,32,44,56,64,76,76,75,72,68,62,56,52,41,39,35,32,30,29,30,31,28,26,24,24,26,27,26,25,22,20,17,15,15,16,19,21,24,24,25,26,26,26,25,25,22,23,25,26,27,26,25,24,26,25,24,23,21,20,19,18,20,19,19,18,18,17,17,16,14,15,16,16,15,14,12,11,10,10,10,10,10,10,10,10,8,9,9,10,10,11,11,11,13,13,13,12,12,11,11,11,10,10,10,9,9,8,8,8,8,8,8,7,7,6,6,6,7,6,5,4,4,4,4,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 10,10,11,12,13,13,14,14,14,13,13,12,12,13,13,14,12,12,11,12,13,14,15,16,12,12,12,13,13,13,13,13,17,17,17,18,18,19,19,19,19,18,17,16,16,16,16,17,21,21,22,23,26,29,32,34,33,33,32,32,30,28,27,26,20,20,20,21,22,23,25,26,27,25,23,21,23,26,30,33,36,40,44,46,45,42,40,39,35,32,28,25,23,23,24,25,24,25,25,25,25,24,23,23,26,26,27,28,30,33,35,36,37,38,38,38,39,39,39,39,41,42,44,46,46,44,42,41,38,37,36,35,34,34,34,34,32,32,31,29,28,30,35,38,51,55,61,66,68,66,63,60,60,60,60,62,64,67,71,72,71,68,65,61,58,54,49,45,43,43,42,43,45,49,53,55,57,57,55,54,53,53,53,54,63,69,77,84,88,88,85,82,81,82,83,82,77,70,62,56,42,39,36,35,38,41,43,44,39,35,32,32,37,44,50,53,52,51,49,46,46,50,59,66,79,88,98,101,95,87,81,79,79,81,85,91,91,82,67,54,53,52,55,61,66,65,56,48,38,37,38,41,46,50,51,50,53,50,49,50,54,57,56,55,45,41,35,29,26,26,27,29,28,30,31,29,26,25,27,30,31,31,30,28,26,25,27,30,29,33,37,39,38,39,43,47,53,51,44,34,27,28,37,46,60,71,77,70,57,47,40,35,40,43,46,47,45,38,31,26,23,24,24,24,26,31,37,43,51,59,66,68,67,64,56,48,32,29,25,24,27,34,42,47,50,49,47,43,38,32,27,24,22,23,26,29,30,30,29,28,29,25,21,21,24,27,27,26,28,27,25,23,21,20,19,19,16,16,16,17,20,24,28,31,36,36,35,34,31,28,24,22,17,19,21,22,21,22,24,26,32,39,45,47,50,53,51,47,39,37,36,36,37,37,35,33,31,29,27,26,26,25,23,21,17,17,20,26,38,52,65,73,84,84,83,80,74,66,59,54,48,44,38,35,34,33,32,31,28,27,26,24,22,20,19,18,16,16,16,16,17,18,20,20,26,25,24,23,22,22,22,22,20,21,23,25,26,27,26,25,25,24,23,22,21,19,18,18,16,16,16,15,15,15,14,14,15,15,15,14,14,14,13,13,12,12,11,10,10,9,8,8,7,7,7,8,9,10,11,12,13,13,13,13,13,13,13,13,9,9,9,8,8,7,7,7,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 10,10,11,11,12,13,14,14,14,13,13,12,12,13,13,14,12,12,11,12,13,14,15,16,14,14,14,15,15,15,15,16,17,17,17,18,18,19,19,19,18,18,17,16,16,17,17,17,21,21,22,24,26,29,32,34,34,33,33,32,30,28,26,25,20,20,20,20,21,22,23,24,25,23,22,21,23,27,31,34,37,40,44,45,43,39,37,36,31,30,27,25,24,25,26,27,27,27,27,28,27,27,26,26,28,28,29,31,33,35,37,38,41,41,41,41,41,41,40,40,42,43,43,43,43,41,39,37,37,36,34,32,31,30,29,29,27,28,29,29,30,34,39,43,53,57,63,68,70,69,66,64,60,60,60,61,62,64,67,68,68,66,63,61,59,55,49,45,39,38,36,36,38,41,45,47,52,52,52,53,53,53,53,53,58,61,67,71,73,73,70,69,66,68,69,68,64,57,50,45,35,34,33,36,40,45,47,47,40,37,32,31,35,40,45,48,49,49,49,47,47,52,59,65,76,85,96,99,95,87,82,79,83,86,93,100,101,92,76,63,55,55,58,64,70,68,59,51,40,39,39,42,47,50,51,50,47,44,41,42,45,49,50,49,47,44,40,35,31,30,29,29,26,27,27,26,24,25,29,32,34,34,32,29,26,25,27,29,32,35,37,38,38,41,47,53,61,60,54,44,35,34,42,49,60,70,75,68,55,45,37,32,36,38,42,44,42,37,31,26,23,24,24,24,26,31,39,44,54,61,65,64,60,55,46,37,29,27,24,24,27,33,40,45,46,45,42,38,34,29,25,23,23,25,30,33,35,35,34,33,31,27,22,21,23,26,27,27,28,27,25,23,21,19,18,18,18,17,17,17,20,24,27,30,34,34,34,33,30,27,24,22,19,20,21,22,22,24,27,30,35,42,48,49,51,53,51,46,40,38,36,36,36,36,34,32,30,28,26,25,25,24,22,20,19,20,23,31,42,56,69,77,88,88,87,83,77,70,63,59,50,46,41,38,36,35,33,32,27,26,25,23,21,20,19,18,17,17,17,18,19,20,22,22,26,25,24,22,21,21,21,21,19,21,23,24,25,25,25,24,23,22,21,20,19,18,17,16,15,15,15,14,14,14,13,13,14,14,14,14,14,14,14,14,12,12,11,10,10,9,8,8,7,7,7,8,9,10,11,12,13,13,13,13,13,13,13,13,9,9,9,8,8,7,7,7,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 9,9,10,11,12,12,13,13,13,13,12,12,12,12,13,13,12,12,11,12,13,14,15,16,16,16,16,17,17,18,18,18,17,17,18,18,18,19,19,19,18,17,17,17,17,17,18,19,22,22,23,25,27,30,32,34,34,34,33,31,29,26,24,23,20,19,19,18,19,19,20,20,22,21,21,22,24,28,32,34,39,41,43,42,39,35,33,32,26,26,26,26,27,28,30,31,31,31,31,31,32,32,32,32,33,34,35,37,39,41,42,43,46,46,46,46,46,45,43,43,46,45,44,43,41,39,37,37,37,36,33,30,28,26,25,24,22,24,27,29,32,38,44,49,54,58,64,69,71,70,67,65,59,58,58,58,59,60,61,62,62,62,61,61,60,57,51,47,38,36,33,31,32,35,39,41,47,48,50,52,53,53,52,52,51,51,52,53,53,53,52,51,49,50,51,51,48,42,36,33,26,28,32,38,45,50,52,52,43,38,33,30,31,35,37,39,43,44,46,47,49,53,58,61,70,78,88,93,91,85,80,77,83,90,100,110,111,102,86,73,59,60,64,71,77,75,66,57,45,42,40,42,48,52,53,51,42,39,35,34,36,41,44,46,50,50,48,45,41,37,33,31,25,25,24,23,23,26,32,36,40,39,37,33,29,27,27,29,36,37,37,37,39,46,57,65,74,73,68,57,47,42,46,51,60,69,73,65,53,43,34,28,29,32,36,38,38,34,29,26,24,24,25,25,28,33,40,46,54,59,61,57,51,45,36,26,23,23,23,24,28,33,37,40,41,39,36,32,28,25,23,22,24,28,34,40,43,43,41,39,34,30,24,21,22,25,27,28,28,27,26,24,22,20,18,18,20,19,18,18,20,23,26,28,32,32,33,32,30,28,25,24,22,23,23,23,23,27,32,36,42,48,53,53,53,54,50,44,40,38,36,35,35,35,32,30,27,25,23,23,23,23,21,19,20,21,25,33,45,58,71,78,89,88,86,82,77,70,64,60,52,48,44,41,39,37,34,32,26,25,23,21,20,19,18,18,18,19,19,21,22,24,25,25,26,25,23,21,20,19,19,19,19,20,22,23,24,24,23,22,19,19,18,17,16,15,14,14,13,13,13,12,12,12,11,11,11,12,12,13,14,14,15,15,12,12,11,10,10,9,8,8,8,7,7,7,8,9,11,11,12,12,12,12,12,12,12,12,9,9,9,8,8,7,7,7,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 8,9,9,10,11,12,12,12,13,13,12,11,11,12,13,13,12,12,11,12,13,14,15,16,16,16,17,18,18,19,19,20,19,19,19,19,19,19,19,19,18,17,17,17,17,18,19,19,21,22,23,25,27,30,31,32,34,34,32,30,28,25,22,21,19,18,17,17,17,17,17,18,19,20,21,23,26,29,32,34,40,41,41,39,35,31,29,28,23,25,27,30,32,34,35,36,36,36,36,36,36,37,38,39,41,41,43,45,47,48,49,50,52,52,53,53,52,50,49,48,49,48,45,42,40,40,40,40,41,39,36,32,28,26,24,23,22,24,27,31,34,40,46,51,53,56,60,63,64,63,60,57,53,54,54,55,55,56,57,58,58,58,60,62,62,59,54,49,42,40,36,33,32,35,38,41,45,46,49,51,51,50,48,47,43,41,40,38,37,37,37,38,37,38,39,39,37,33,29,26,23,27,34,43,51,55,56,54,45,40,33,29,29,30,31,31,36,38,41,45,48,51,53,54,59,66,76,81,81,77,73,71,77,86,100,112,115,106,91,79,67,68,73,81,87,84,74,64,48,44,41,43,49,55,56,54,44,40,34,31,32,36,42,46,54,55,57,57,54,48,41,37,28,26,24,23,25,30,37,41,48,47,44,39,34,31,31,32,39,39,39,39,43,54,69,81,89,89,84,72,59,50,49,52,62,70,72,64,53,43,34,27,25,27,31,33,33,31,28,26,24,25,26,27,29,35,43,48,52,56,56,50,44,39,30,22,18,20,22,25,28,31,34,35,36,34,31,28,25,24,24,24,26,30,38,44,48,49,48,46,39,34,28,23,22,24,27,30,31,30,29,27,25,22,20,19,21,20,19,19,20,22,25,27,31,32,33,34,34,32,31,30,29,28,27,26,27,31,38,43,50,56,59,57,56,54,49,43,39,37,34,33,33,32,29,27,23,22,20,20,21,21,20,18,18,20,25,33,44,56,67,74,82,81,78,74,69,63,58,56,51,48,45,42,40,37,33,30,24,23,21,19,18,18,18,19,20,21,22,24,25,27,27,28,26,25,23,21,19,18,18,18,19,20,21,23,23,22,21,20,16,16,15,14,13,12,12,11,12,11,11,11,10,10,10,9,9,10,10,12,13,14,15,16,12,12,11,10,10,9,8,8,8,7,7,7,8,9,10,10,11,11,11,11,11,11,11,11,9,9,9,8,8,7,7,7,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 8,8,8,9,10,11,11,12,13,12,11,11,11,11,12,13,12,12,11,12,13,14,15,16,16,16,17,18,19,19,20,21,21,21,21,21,21,21,20,20,19,18,18,17,17,18,19,19,20,21,23,25,27,29,30,30,32,32,30,28,26,23,20,18,18,17,16,16,15,16,16,17,18,19,22,24,28,31,33,35,39,39,38,35,30,27,26,26,24,27,31,36,39,41,41,41,40,40,40,40,41,43,44,45,49,50,52,54,55,55,55,55,55,56,58,59,59,58,56,55,51,48,44,40,38,39,40,42,45,43,40,36,32,29,27,26,25,28,31,33,36,40,45,49,48,50,53,55,54,52,48,46,46,47,49,50,52,53,54,54,54,55,57,60,62,60,55,52,47,44,40,37,36,37,40,42,42,43,45,46,46,44,41,39,35,33,31,28,27,28,28,29,31,31,32,32,30,28,25,23,25,30,38,47,55,58,56,54,45,40,34,29,28,27,27,27,30,32,36,41,45,46,46,45,47,52,59,64,66,65,63,62,70,80,96,109,113,106,94,84,76,78,83,92,97,93,81,71,51,45,40,43,52,59,61,60,49,45,38,32,30,33,39,44,55,59,65,68,67,61,53,48,37,33,29,28,31,36,42,46,54,53,50,45,40,37,36,37,40,41,41,42,49,63,80,93,104,104,99,87,71,59,55,56,65,71,72,65,54,45,36,28,24,25,28,30,31,30,28,26,25,26,27,28,31,38,45,51,55,57,55,47,39,34,26,18,16,18,22,25,28,30,30,30,32,30,28,26,25,25,26,27,27,31,37,43,48,50,51,51,43,39,33,27,24,25,28,31,34,34,33,31,29,25,23,21,22,21,20,19,20,23,25,27,32,33,36,38,40,40,40,39,38,37,35,33,33,37,44,49,56,60,62,59,56,53,47,40,35,33,31,30,29,28,26,24,21,19,18,18,20,20,19,17,19,21,26,33,43,53,62,67,72,70,67,63,59,55,52,50,48,46,44,42,40,37,32,28,23,22,20,18,17,18,19,20,22,23,25,27,28,29,29,28,25,24,22,21,19,19,18,18,20,20,22,22,22,21,20,18,14,13,13,12,12,11,10,10,10,10,10,9,9,9,8,8,8,8,9,11,12,14,15,16,12,12,11,10,10,9,8,8,8,7,7,7,7,8,9,9,11,11,11,11,11,11,11,11,9,9,9,8,8,7,7,7,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 7,7,8,8,9,10,11,11,12,12,11,11,11,11,12,12,12,12,11,12,13,14,15,16,16,17,18,19,20,21,22,22,24,24,23,23,23,22,22,22,21,20,19,18,18,18,18,18,19,20,22,24,26,27,28,28,29,28,27,26,23,21,18,17,16,16,15,15,15,16,16,17,19,21,24,27,30,32,34,34,36,36,34,31,27,25,25,26,29,32,38,44,48,48,47,46,44,43,43,43,45,47,49,51,56,57,59,60,60,59,58,57,57,59,62,65,66,66,65,64,54,50,44,39,36,37,39,41,46,45,42,38,35,32,30,30,30,32,34,36,37,39,42,45,44,45,47,48,47,44,41,39,41,42,44,47,48,49,50,50,51,51,53,56,58,58,55,52,47,45,42,40,39,39,40,41,40,40,41,41,40,38,37,35,33,32,30,28,27,26,26,25,28,28,27,26,25,24,22,21,28,33,41,50,56,58,55,52,44,40,34,30,28,28,28,27,29,30,33,38,41,41,39,36,36,38,42,47,50,52,52,52,63,73,89,102,108,104,96,90,83,85,91,99,104,98,85,74,51,44,39,43,54,64,67,66,55,50,42,34,29,30,35,40,54,61,70,77,79,74,67,61,50,45,40,38,40,44,48,50,57,56,54,49,44,41,41,43,42,43,44,47,53,67,84,97,111,111,107,95,79,67,62,63,67,72,72,65,55,47,38,30,27,28,29,30,30,29,28,27,25,26,28,29,33,40,48,54,61,62,56,45,36,29,21,14,16,19,22,26,28,28,28,27,27,27,27,26,27,27,28,29,28,30,33,37,42,47,51,53,47,44,39,32,27,27,29,32,37,36,36,34,31,28,24,22,22,21,20,20,21,23,26,28,32,34,38,42,46,48,50,50,49,48,45,42,41,43,49,53,56,60,62,58,53,50,43,35,30,28,25,25,25,24,22,20,19,17,16,17,19,20,19,18,21,23,28,34,42,50,56,60,61,59,56,53,50,47,46,45,44,43,42,41,40,37,31,27,23,21,19,17,17,19,21,22,24,25,27,29,30,29,28,28,24,23,22,21,20,20,20,20,21,22,23,23,22,21,19,18,13,13,12,12,11,11,11,10,10,10,9,9,9,8,8,8,7,8,9,10,12,13,14,14,12,12,11,10,10,9,8,8,8,8,7,7,7,7,8,8,10,10,10,10,10,10,10,10,9,9,9,8,8,7,7,7,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 6,6,7,8,9,9,10,10,12,11,11,10,10,11,11,12,12,12,11,12,13,14,15,16,18,18,19,21,22,23,24,25,26,26,26,25,25,24,24,24,23,22,20,19,17,17,17,17,17,19,21,23,25,26,26,25,25,25,24,23,21,19,17,16,15,15,15,15,15,16,18,18,21,23,26,30,32,34,34,34,33,32,31,28,24,23,25,27,35,39,46,52,55,55,52,50,46,45,45,45,47,50,53,55,60,61,62,62,61,59,57,55,57,60,64,69,72,72,72,71,64,59,50,42,37,37,39,41,44,42,40,37,35,33,32,31,33,35,37,37,37,38,41,43,40,42,44,46,46,44,42,40,40,41,43,44,45,45,45,44,47,47,48,50,53,53,51,49,46,45,44,43,42,41,40,40,41,41,41,41,41,41,41,41,40,40,40,38,36,33,30,28,28,27,26,25,24,23,22,22,29,33,40,49,55,56,53,49,42,38,34,31,30,31,30,30,31,31,32,36,39,38,34,30,29,29,30,33,37,41,43,45,56,65,80,93,99,99,95,92,86,89,95,103,106,100,85,73,50,42,37,43,56,68,73,73,63,58,50,39,31,30,34,38,53,61,73,83,87,85,79,74,63,58,52,48,49,52,53,53,56,56,54,50,46,44,45,46,44,46,48,50,55,66,81,91,104,105,102,92,78,68,65,66,66,71,70,63,55,48,40,32,32,32,31,31,30,29,28,27,26,27,28,30,34,41,50,56,62,61,55,43,34,28,21,15,18,20,23,26,27,27,26,25,23,24,25,27,28,29,29,29,28,28,27,29,34,41,49,53,49,48,44,37,31,28,30,33,37,37,37,35,32,28,24,22,22,21,20,20,21,24,27,29,31,34,39,45,50,54,57,58,59,57,54,50,48,48,52,55,53,57,58,53,48,44,37,29,24,22,20,20,20,20,18,16,18,16,16,17,19,20,19,18,22,23,27,32,37,43,47,50,49,48,45,42,40,39,39,40,41,41,41,42,42,38,33,28,23,22,19,18,18,20,22,24,26,27,29,30,30,29,27,26,24,23,22,22,22,22,23,23,22,23,24,24,23,21,19,18,13,13,13,13,12,12,12,12,10,10,9,9,9,8,8,8,8,8,9,10,11,12,12,13,12,12,11,10,10,9,8,8,8,8,7,6,6,7,7,8,9,9,9,9,9,9,9,9,9,9,9,8,8,7,7,7,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 6,6,7,7,8,9,10,10,12,11,11,10,10,11,11,12,12,12,11,12,13,14,15,16,20,20,21,22,24,25,26,27,28,28,27,27,26,26,25,25,24,23,21,19,17,16,16,16,16,18,20,23,24,25,24,24,22,22,22,21,20,18,16,15,14,14,14,15,16,17,19,19,22,24,28,31,34,35,34,34,30,30,28,26,23,23,25,28,39,44,51,57,60,58,55,52,47,46,46,46,48,51,55,57,61,62,62,62,61,58,55,53,57,60,66,71,75,76,76,76,74,68,57,47,41,40,41,43,40,39,37,35,33,32,32,31,34,36,38,38,38,38,40,42,39,41,44,46,48,47,46,45,40,41,42,43,43,42,41,40,44,44,44,46,48,50,49,47,46,46,46,46,45,43,42,41,45,45,45,45,46,47,48,49,49,50,50,49,46,41,36,32,31,30,28,26,25,24,24,24,27,31,39,47,53,54,51,48,41,38,33,31,32,33,33,32,33,33,33,36,38,37,32,28,26,24,23,25,30,35,39,41,49,59,72,84,91,93,92,90,87,90,96,104,107,99,84,71,49,41,36,42,57,71,77,76,69,65,56,44,35,31,34,39,52,60,74,86,92,91,86,82,72,66,59,55,55,56,56,55,54,54,53,49,46,45,46,48,46,48,50,51,55,64,76,85,94,96,94,85,74,65,64,66,65,69,69,62,55,49,40,32,35,34,33,32,31,29,28,27,26,27,29,31,35,42,51,57,57,57,51,41,33,29,25,19,20,22,24,26,27,26,25,24,20,22,24,27,29,29,29,29,29,26,24,24,28,37,47,53,51,50,47,41,34,30,31,33,36,37,37,35,32,28,24,21,21,20,20,20,21,24,28,30,30,33,39,46,52,58,61,62,64,63,60,56,52,51,53,56,50,54,54,49,44,40,32,24,20,18,17,17,18,18,16,15,17,16,16,17,19,20,20,19,19,21,24,28,32,37,40,41,41,39,36,34,32,33,34,35,40,41,42,43,43,40,34,29,23,22,19,18,18,20,23,25,27,28,30,31,30,29,26,25,23,23,22,22,23,23,24,25,23,24,24,24,23,21,19,18,14,14,13,13,13,13,13,12,10,10,10,9,9,8,8,8,8,8,9,10,10,11,12,12,12,12,11,10,10,9,8,8,8,8,7,6,6,6,7,7,9,9,9,9,9,9,9,9,9,9,9,8,8,7,7,7,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 7,7,7,8,8,9,9,9,10,10,9,9,9,10,11,11,11,12,12,13,15,17,19,20,21,22,24,26,27,28,28,28,30,30,31,31,30,28,26,24,24,23,21,19,17,16,16,16,15,15,16,18,19,20,21,22,21,21,20,20,18,17,15,14,16,17,17,16,16,17,20,22,28,31,35,38,39,38,35,33,30,29,26,25,26,30,34,37,44,48,53,58,59,57,53,50,48,44,41,42,46,51,53,53,59,59,59,57,56,53,51,50,57,61,66,71,75,80,86,90,83,76,67,60,54,48,42,37,40,36,32,30,32,35,37,37,36,38,40,38,36,36,38,41,45,47,50,54,56,56,53,49,48,43,39,39,38,34,35,39,37,40,43,44,43,41,41,41,38,39,41,43,46,48,49,50,50,47,48,52,55,56,59,65,69,71,70,64,59,53,44,34,35,33,30,28,28,28,28,27,32,36,41,44,50,54,50,43,42,33,26,29,35,38,40,42,40,41,39,36,36,37,32,24,23,22,21,22,25,30,36,40,45,55,69,79,83,84,85,85,82,86,92,98,97,87,72,61,44,41,42,48,60,70,74,74,70,62,52,45,38,32,34,39,46,54,67,82,92,96,93,90,82,76,68,63,60,57,54,51,48,48,48,46,44,43,44,45,43,43,44,47,52,58,63,66,75,75,74,71,68,64,60,57,57,56,53,50,46,43,40,38,37,39,39,38,34,30,28,28,26,27,29,33,38,44,49,52,56,53,46,39,32,27,24,22,21,22,24,26,27,27,26,25,22,18,18,23,28,30,34,39,32,32,28,23,26,36,46,49,51,51,49,44,37,32,30,30,31,33,35,34,30,26,23,22,20,21,22,23,24,25,26,26,32,34,39,44,49,54,56,58,64,63,62,59,56,53,51,49,49,48,46,42,37,31,26,23,16,16,15,15,15,17,19,20,20,20,20,20,20,20,21,21,24,24,26,27,30,32,35,36,36,35,34,33,33,33,33,34,39,41,45,46,45,41,37,33,23,22,20,20,20,20,22,22,26,27,28,28,28,26,24,23,23,22,22,21,21,22,23,23,26,26,26,25,24,23,21,20,20,19,17,15,13,12,11,11,11,11,11,11,10,9,8,7,8,8,8,9,9,10,10,11,9,9,9,8,8,7,7,7,7,7,7,8,8,9,9,9,10,10,10,10,10,10,10,10,9,9,9,8,8,7,7,7,8,8,7,6,6,5,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 7,7,7,8,8,8,9,9,10,10,9,9,9,10,11,12,13,13,13,14,16,18,20,21,23,24,25,27,28,29,29,29,31,31,32,32,31,29,26,25,24,23,21,19,17,16,16,15,14,14,15,17,18,19,20,21,19,19,19,18,17,16,15,14,16,17,18,18,18,20,23,26,31,33,37,40,41,39,37,35,32,31,28,27,29,32,36,39,44,48,52,56,56,54,50,47,43,39,36,36,40,44,46,47,54,54,55,54,53,52,50,49,50,54,61,67,75,83,90,96,96,90,81,72,63,54,44,38,38,35,31,30,33,36,38,39,38,39,40,38,36,37,41,44,49,51,56,61,65,64,59,56,51,45,40,38,36,32,33,38,37,40,42,42,40,38,37,36,36,38,41,44,48,51,53,55,58,56,57,61,64,67,73,80,89,91,88,79,71,62,50,39,36,33,30,29,29,30,31,32,37,43,48,51,56,58,53,45,42,32,26,29,35,39,43,47,46,46,42,38,37,38,34,27,25,25,24,25,29,34,39,42,46,54,64,72,75,76,76,76,72,75,79,83,82,74,62,53,45,44,46,54,65,72,74,72,65,57,49,44,38,32,33,38,44,50,62,75,86,90,89,86,81,75,67,60,57,53,49,46,45,46,46,44,41,40,41,42,41,41,42,44,46,50,53,54,57,58,58,58,56,54,51,50,51,50,47,44,42,39,38,37,37,39,40,38,34,31,29,29,28,29,31,34,38,42,46,48,51,48,43,37,31,27,24,23,24,25,26,28,28,28,27,26,23,18,16,21,26,32,39,46,48,48,43,35,34,39,43,44,50,49,46,40,34,29,28,28,30,32,34,33,29,25,22,22,19,20,23,25,27,28,29,29,31,33,36,40,44,48,52,53,58,58,57,56,54,51,48,47,45,45,43,41,36,31,26,24,20,19,18,17,17,18,19,20,20,20,20,20,20,20,19,19,22,23,24,26,29,32,34,36,35,34,33,32,32,33,33,34,38,41,44,47,47,44,40,37,27,25,23,20,19,19,20,21,23,24,25,25,25,24,23,22,23,22,21,21,21,21,21,22,25,25,25,25,24,23,22,21,21,19,18,16,14,13,12,12,12,12,12,12,11,10,9,8,7,8,8,8,9,9,10,10,9,9,8,8,8,7,7,7,7,7,7,8,8,8,9,9,10,10,10,10,10,10,10,10,9,9,9,8,8,7,7,7,8,8,7,6,6,5,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 7,7,7,7,8,8,8,9,10,10,9,9,10,11,12,12,14,15,15,16,18,20,22,23,25,26,27,29,30,31,31,31,32,33,33,33,31,29,27,25,23,22,20,18,17,15,15,15,13,13,14,15,16,17,18,19,17,17,17,16,16,15,15,15,16,17,20,21,22,24,28,31,34,36,40,42,43,42,40,38,35,34,32,31,32,35,39,41,43,45,49,51,50,47,43,41,37,34,31,31,33,37,39,40,46,47,49,50,50,49,48,47,46,50,56,64,72,83,93,99,104,101,94,86,75,62,49,41,36,34,32,32,36,40,42,43,42,41,40,37,36,38,43,46,53,56,63,70,74,72,67,62,53,45,39,35,32,29,32,37,39,41,42,41,37,34,32,32,35,37,42,47,53,57,60,62,68,65,65,70,74,79,90,100,113,115,110,98,84,70,55,43,36,34,31,30,30,33,37,39,44,51,57,60,62,62,55,46,41,32,26,29,36,42,49,55,56,55,50,42,39,40,37,31,30,30,30,31,34,39,43,46,47,52,58,62,63,63,63,63,60,61,62,63,62,57,51,45,44,46,52,62,70,74,71,67,57,50,44,41,37,32,32,36,40,44,53,64,74,79,80,79,76,71,63,56,51,47,43,41,42,42,42,39,37,35,36,37,37,38,38,39,39,39,39,39,37,38,40,42,43,43,42,42,42,41,38,36,35,35,35,36,37,38,39,37,34,31,30,30,31,32,33,36,38,40,42,43,43,41,37,33,29,27,26,25,28,28,29,30,30,30,29,29,25,19,15,19,25,34,48,59,66,67,63,53,45,44,43,40,48,46,42,35,29,25,24,25,28,31,32,31,28,24,22,21,19,21,25,30,33,34,34,34,33,33,33,34,36,39,42,44,47,48,49,50,49,46,44,42,40,41,40,39,36,32,28,25,25,24,23,22,21,20,20,21,21,21,20,20,19,18,18,17,19,20,21,24,27,30,33,34,33,33,32,32,32,33,33,34,37,40,44,46,47,45,42,39,31,28,24,20,18,18,19,20,20,20,21,22,22,22,21,21,23,22,21,20,19,19,20,20,23,23,24,24,24,24,23,22,21,20,19,17,15,14,14,14,13,13,13,13,12,11,9,9,7,7,7,8,8,8,9,9,9,8,8,8,7,7,7,7,7,7,7,7,8,8,8,9,10,10,10,10,10,10,10,10,9,9,8,8,8,8,7,7,8,8,7,6,6,5,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 6,6,7,7,7,8,8,8,10,10,9,10,10,11,13,13,16,16,17,18,20,22,23,25,27,28,30,31,32,32,32,32,33,34,34,34,32,30,27,26,22,21,19,17,16,15,14,14,12,12,13,14,15,16,16,17,15,15,15,15,15,15,15,16,16,19,22,24,26,29,33,36,37,39,42,44,44,43,41,40,37,36,34,33,34,36,39,41,39,40,42,43,41,38,35,33,32,30,28,27,28,31,34,36,40,42,44,46,48,47,46,46,46,49,54,60,68,79,91,98,105,104,101,94,84,70,57,48,38,37,37,40,44,47,49,49,48,45,40,36,35,37,41,45,52,57,64,71,76,74,67,62,49,41,34,30,28,27,31,37,42,44,44,42,38,34,32,32,37,41,46,53,60,65,68,70,73,70,69,73,78,87,102,116,130,131,126,111,92,74,56,43,37,35,33,32,32,37,43,47,50,58,66,68,68,65,57,47,41,33,26,29,37,45,56,65,69,67,60,50,44,43,40,36,36,36,37,38,41,44,47,49,49,50,52,52,52,51,51,51,50,48,47,46,45,44,43,42,43,49,58,68,74,72,66,60,47,41,38,38,36,33,32,34,35,37,42,50,59,65,68,69,67,63,56,50,45,41,39,37,37,38,37,35,32,31,32,33,33,34,35,36,35,33,30,29,27,29,31,34,36,36,36,36,33,32,31,29,30,31,33,34,35,36,37,35,33,31,31,32,32,33,35,37,38,38,38,38,35,33,31,29,27,27,27,27,29,29,30,32,32,33,34,34,29,22,16,18,26,39,58,73,81,84,81,70,59,52,46,41,44,42,37,30,24,21,21,23,27,29,31,30,27,23,21,20,20,24,30,36,40,42,42,42,38,36,33,31,30,30,31,32,34,36,39,41,41,39,37,35,37,38,39,39,38,35,31,29,30,30,28,26,24,22,21,21,21,21,20,19,18,17,16,16,16,17,19,21,24,28,31,33,33,32,32,32,32,33,34,34,36,38,41,43,43,41,39,36,30,27,23,19,17,17,18,20,18,18,19,20,20,21,21,21,23,22,21,19,19,18,19,19,21,22,23,24,25,25,24,24,22,21,20,18,17,16,16,16,15,15,15,15,13,12,10,10,7,7,7,8,8,8,8,8,8,8,8,7,7,7,6,6,6,6,7,7,7,8,8,8,9,9,9,9,9,9,9,9,8,8,8,8,8,8,8,8,8,8,7,6,6,5,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 6,6,6,7,7,7,8,8,10,10,10,10,11,12,14,14,17,18,18,19,21,23,25,26,29,30,31,32,33,33,33,33,34,34,34,34,32,29,27,25,22,20,19,17,15,14,13,13,12,12,12,13,14,14,15,15,14,14,13,13,14,15,17,18,19,22,25,28,30,32,35,38,39,40,42,43,44,43,41,40,38,36,34,33,33,34,35,36,32,33,33,33,32,30,27,26,26,25,24,22,23,26,30,33,38,40,43,46,47,47,46,45,45,46,50,55,63,75,88,96,104,105,104,99,89,75,63,56,46,47,50,54,58,59,58,56,53,48,41,36,34,36,39,41,49,52,58,64,67,66,60,55,42,34,27,25,25,26,32,39,46,47,47,45,41,39,38,38,44,48,54,60,66,71,73,74,75,71,69,71,76,88,108,125,138,140,135,119,97,76,57,43,36,36,35,34,35,39,47,53,59,68,75,76,74,70,60,51,43,34,27,29,37,48,63,75,82,82,75,63,54,50,45,40,41,42,43,44,46,48,50,50,50,48,46,44,43,42,42,41,39,37,35,33,33,35,38,40,48,55,65,74,77,71,62,54,39,33,31,34,35,34,33,35,32,32,34,39,46,52,56,58,55,53,48,42,38,35,34,35,33,33,33,31,29,28,29,31,31,32,34,35,34,32,29,27,26,28,30,32,33,33,32,32,28,28,27,27,28,30,31,32,33,34,35,34,33,32,33,35,34,36,38,39,39,38,36,35,30,29,27,26,26,27,28,29,28,29,30,32,34,36,37,38,32,25,19,20,28,43,65,84,97,102,100,87,71,59,48,41,40,37,33,27,21,19,20,22,26,28,30,30,27,23,21,21,24,28,34,41,46,49,50,50,46,43,37,32,27,24,23,23,24,26,29,31,32,32,31,30,36,37,40,42,41,39,36,33,34,33,31,29,26,24,22,20,20,20,19,18,17,16,15,15,15,16,17,20,23,26,29,30,32,32,31,31,31,32,32,33,34,35,37,38,37,35,32,30,26,23,20,18,17,18,20,21,19,19,19,19,20,21,21,22,22,21,20,19,19,19,19,19,22,22,24,25,25,26,26,25,23,23,21,20,18,18,18,18,17,17,17,16,15,13,12,11,8,8,8,8,8,8,8,8,8,8,7,7,7,6,6,6,6,6,6,7,7,7,8,8,9,9,9,9,9,9,9,9,8,8,8,8,8,8,8,8,8,8,7,6,6,5,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 5,6,6,6,7,7,7,7,10,9,10,10,11,13,14,15,18,18,19,20,21,23,25,26,30,31,32,33,33,33,33,33,34,34,34,33,31,28,26,24,21,20,18,16,14,13,13,12,12,12,13,13,14,14,14,15,13,13,12,13,14,16,19,20,22,25,29,31,32,33,35,37,38,39,40,41,41,40,39,38,36,35,33,30,29,28,29,29,26,26,26,26,25,24,24,23,21,22,21,20,20,23,28,32,40,43,46,49,50,49,46,45,39,40,42,47,55,69,83,93,104,105,105,99,89,77,67,62,58,61,66,72,75,74,69,64,56,50,43,38,36,38,40,41,46,46,49,52,54,53,49,45,35,29,23,23,24,26,33,41,48,49,50,49,47,46,46,48,53,56,61,66,70,73,73,74,74,69,65,65,69,83,107,127,142,146,142,124,100,77,56,42,35,36,37,37,37,41,49,55,66,75,83,83,79,73,65,57,45,36,29,30,37,50,68,83,96,97,93,81,69,61,53,46,46,47,48,49,50,50,49,49,47,43,40,37,37,37,36,35,30,29,28,27,28,31,37,42,55,62,72,78,77,69,58,51,33,27,24,29,34,35,35,37,32,31,30,33,38,44,48,49,46,45,41,36,31,29,29,31,29,30,30,29,28,28,29,31,32,33,35,35,35,33,31,29,29,30,31,32,32,31,29,28,28,29,29,30,31,31,31,32,32,33,35,35,35,36,39,41,41,43,44,45,43,39,35,32,28,28,26,26,26,28,29,30,29,29,30,31,33,35,37,39,33,26,21,22,29,44,68,88,109,114,113,98,78,61,47,39,35,34,31,26,21,19,20,22,26,28,30,30,27,24,22,21,26,30,36,43,48,52,54,55,53,49,43,36,30,24,21,19,20,21,22,24,26,27,27,28,35,38,41,44,44,42,39,36,34,34,32,30,27,24,21,20,19,18,18,17,16,16,15,15,16,16,17,19,22,24,27,28,31,31,30,29,28,28,29,29,30,31,32,32,31,29,26,24,22,21,20,19,20,20,22,23,20,20,19,19,19,20,21,22,21,21,20,20,20,20,21,22,23,24,25,26,27,27,27,26,24,24,22,21,20,20,20,20,19,19,19,18,16,14,13,12,10,10,10,9,9,9,8,8,7,7,7,7,6,6,6,5,5,6,6,6,7,7,7,7,8,8,8,8,8,8,8,8,7,7,8,8,8,8,9,9,8,8,7,6,6,5,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 5,5,6,6,6,7,7,7,9,9,10,10,12,13,15,16,18,18,18,20,21,23,25,26,31,31,32,33,33,33,33,32,33,33,33,32,30,27,24,23,20,19,17,15,14,13,12,12,13,13,13,14,14,14,14,15,13,12,12,12,14,17,20,22,25,28,31,33,33,33,34,35,36,36,37,38,38,37,36,35,34,33,30,27,24,22,21,21,21,21,21,22,22,23,23,24,22,24,24,24,24,27,33,38,45,48,51,53,53,51,47,45,37,37,37,39,46,59,73,83,95,96,96,92,84,75,70,68,70,75,82,90,92,87,79,72,57,51,44,41,41,43,44,44,45,43,41,41,41,41,39,37,34,28,23,24,26,28,34,42,48,49,51,51,51,52,55,57,60,62,66,69,71,71,70,69,68,62,56,54,57,72,98,121,143,148,144,126,100,75,53,39,33,36,39,40,39,42,49,56,67,76,83,82,77,72,64,57,47,38,30,30,38,52,72,88,108,112,110,99,84,72,61,52,49,50,51,52,51,50,48,46,41,38,34,32,33,34,33,31,26,28,29,29,31,35,43,48,59,65,73,76,73,63,52,45,30,23,20,26,33,36,37,40,36,33,31,32,36,40,43,44,41,41,37,32,25,22,23,26,26,28,29,28,28,28,31,33,35,36,36,36,35,34,32,31,34,34,35,35,34,33,31,29,31,32,34,35,35,34,32,31,33,34,36,37,39,41,45,49,52,53,54,52,48,41,34,30,29,28,27,27,27,28,30,31,31,31,30,30,31,32,34,35,31,26,22,23,29,43,66,86,106,113,112,97,75,57,44,35,31,31,30,27,23,21,22,23,26,28,31,30,28,25,23,22,28,30,35,41,47,52,55,57,55,53,48,42,35,29,24,22,20,20,20,21,23,25,27,29,35,37,42,45,45,43,40,37,33,33,32,30,27,24,21,19,17,17,16,16,16,16,16,16,17,18,18,19,21,23,25,26,29,28,26,25,23,23,23,23,25,26,28,28,28,26,24,22,22,23,23,23,24,23,23,23,21,20,19,18,18,18,19,20,20,20,20,20,21,22,23,24,26,26,27,28,28,28,27,27,25,24,23,22,21,21,21,21,21,21,20,19,17,15,14,12,12,11,11,11,10,10,9,9,7,7,7,6,6,6,5,5,5,5,6,6,6,7,7,7,8,8,8,8,8,8,8,8,7,7,7,8,8,9,9,9,8,8,7,6,6,5,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 5,5,5,6,6,7,7,7,9,9,10,11,12,14,15,16,18,18,18,19,21,23,25,26,31,31,32,33,33,33,32,32,33,33,33,32,29,26,23,22,20,19,17,15,13,12,12,12,13,14,14,14,14,14,15,15,13,13,12,13,15,18,22,24,27,30,33,34,33,33,33,34,34,35,35,35,35,35,34,33,33,31,28,24,21,18,17,16,19,19,19,20,21,23,25,25,27,28,30,29,29,33,40,45,49,51,54,56,55,52,48,46,39,37,35,34,39,49,63,72,82,85,86,83,78,74,73,74,78,84,93,100,102,95,84,76,56,51,45,43,45,48,49,49,46,42,37,34,34,34,33,32,35,29,25,26,28,29,35,41,47,49,51,52,53,56,59,62,64,66,69,71,71,69,66,64,61,54,47,44,46,61,89,113,143,148,144,125,98,71,49,34,32,36,40,41,40,42,49,55,64,73,80,78,73,68,61,55,48,39,31,30,38,52,73,91,116,121,121,110,95,80,66,56,51,52,53,53,52,49,46,45,37,33,30,29,31,32,31,29,28,30,33,35,37,42,49,55,58,64,70,72,66,56,45,38,28,21,18,24,32,36,39,41,39,36,34,33,36,40,42,42,40,40,36,29,22,18,19,21,25,27,28,28,28,29,32,34,38,38,38,37,35,34,32,31,38,38,39,39,38,36,34,33,33,35,37,39,39,36,33,31,34,36,38,40,42,45,50,54,61,62,61,58,51,42,34,28,30,30,28,27,28,29,30,31,34,33,31,30,29,29,30,31,29,24,21,23,28,41,63,83,95,103,104,90,70,53,41,33,28,29,29,28,25,23,23,24,26,29,31,31,28,25,23,23,28,30,34,39,45,50,55,57,56,54,51,46,40,33,29,26,22,21,20,20,22,25,28,30,34,37,41,45,45,43,39,37,32,32,31,30,27,24,20,18,15,15,16,16,16,16,16,16,19,19,19,20,21,22,24,25,26,25,23,21,20,19,18,18,22,23,25,26,26,26,24,23,24,25,26,27,27,25,24,23,21,20,18,17,16,16,17,18,20,20,20,21,22,24,25,26,28,28,29,29,29,28,28,27,26,25,24,23,22,22,22,22,22,22,21,20,18,16,14,13,13,12,12,11,11,10,10,10,7,7,7,6,6,5,5,5,5,5,5,6,6,7,7,7,8,8,8,8,8,8,8,8,7,7,7,8,8,9,9,9,8,8,7,6,6,5,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 7,7,7,8,8,9,9,9,10,10,11,12,14,15,16,17,19,19,21,22,24,26,27,28,27,28,29,30,30,30,30,30,30,29,28,26,24,21,19,17,17,16,14,13,12,12,13,14,16,15,14,13,13,13,14,14,14,14,14,15,17,20,23,25,30,31,32,32,32,30,29,27,26,27,29,30,30,29,28,27,28,27,24,21,18,16,14,14,16,17,20,22,25,26,27,28,31,31,30,31,35,40,45,48,58,59,61,62,59,53,48,44,35,32,29,29,33,42,51,57,65,69,73,71,67,66,69,73,84,94,103,105,103,97,84,73,62,55,50,52,59,63,62,59,54,46,36,28,26,28,30,32,29,29,29,29,31,33,36,38,41,44,48,51,54,57,62,65,66,67,66,63,59,56,56,56,49,45,40,35,35,49,80,108,135,143,142,123,95,68,47,34,35,40,44,44,41,40,45,50,56,61,67,68,63,57,53,52,40,37,35,33,35,47,73,96,121,129,131,121,104,86,69,56,53,51,50,50,49,47,43,39,36,31,26,25,28,31,33,33,32,34,37,42,46,51,54,56,60,56,52,52,52,49,41,35,28,24,22,24,31,39,44,46,46,46,46,45,43,44,46,49,46,41,34,27,21,18,18,18,23,25,27,28,29,32,35,38,38,39,39,38,35,33,33,34,38,41,42,40,35,31,30,31,35,39,44,47,47,43,38,34,35,34,36,42,47,53,63,73,77,76,71,63,51,39,31,27,26,26,26,25,25,26,30,34,36,35,32,28,25,25,28,31,25,22,20,19,25,37,51,62,79,81,79,69,54,40,32,30,29,32,33,32,29,27,27,29,26,27,27,27,27,26,25,24,29,31,33,35,37,41,45,49,53,53,52,50,46,41,36,33,28,27,26,25,25,26,27,28,38,40,42,44,43,39,35,32,31,31,31,30,27,24,21,19,17,17,16,15,15,16,16,17,20,20,20,20,20,20,20,20,20,20,18,17,17,19,20,21,21,23,25,25,25,25,27,28,30,34,36,34,34,34,31,26,24,22,19,16,15,15,16,17,16,15,16,17,19,22,25,26,29,30,32,33,32,31,28,27,26,26,24,23,22,21,21,21,21,20,19,19,18,17,16,16,17,16,15,13,12,11,10,10,9,9,9,8,8,7,7,7,7,7,7,6,6,5,5,5,7,7,7,6,6,5,5,5,8,8,8,8,8,8,8,8,8,8,8,7,7,6,6,6,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 7,7,7,8,8,8,9,9,9,10,11,12,13,15,16,16,18,19,20,22,23,25,26,27,26,27,28,29,29,29,29,29,28,27,26,25,23,20,18,17,17,16,14,13,13,14,15,15,16,16,14,13,13,13,13,13,14,14,15,16,18,21,24,26,30,31,31,30,29,27,25,24,23,25,26,28,28,28,27,26,26,25,22,19,17,15,14,14,18,20,22,25,27,29,30,31,34,34,35,37,40,44,48,51,59,60,62,61,58,52,46,42,33,30,27,26,30,37,45,50,53,57,61,61,59,60,65,69,82,92,101,103,101,94,82,70,58,55,54,60,69,75,75,71,57,49,36,27,24,25,28,30,31,32,32,33,34,35,36,36,37,40,44,47,50,55,61,65,65,65,64,61,56,54,54,55,49,45,39,33,33,47,76,103,130,138,138,121,94,69,49,37,40,44,49,47,43,41,44,48,54,59,63,63,57,50,46,45,38,35,33,32,33,45,69,92,117,127,131,124,108,91,73,60,50,48,46,45,44,42,39,36,35,31,27,26,29,31,32,32,35,37,41,45,49,52,54,55,54,49,45,44,45,44,40,35,31,27,24,25,32,39,45,48,51,51,51,48,46,45,47,49,45,41,34,27,22,20,19,20,24,26,28,29,31,33,37,40,41,41,39,36,32,30,31,32,37,40,43,41,36,32,30,31,36,40,45,49,49,45,40,36,36,34,36,42,49,56,68,79,86,84,79,69,55,42,32,28,24,25,24,23,23,25,29,32,37,36,34,30,27,25,26,28,24,22,20,18,22,31,43,51,67,69,68,61,48,37,31,30,32,35,36,34,30,27,26,27,25,25,26,26,26,26,26,25,28,30,31,32,33,36,40,43,47,48,49,49,47,44,40,37,33,32,30,28,27,28,29,30,36,38,40,42,41,39,35,32,31,31,31,30,27,24,22,20,19,18,17,16,15,15,16,16,19,20,20,21,21,21,20,19,20,19,18,17,17,18,20,21,23,25,28,29,30,32,34,37,39,44,46,43,41,41,36,30,25,23,20,17,15,15,16,16,16,15,16,17,18,21,23,25,27,29,30,32,32,31,29,28,27,26,24,23,21,20,20,20,20,20,19,18,17,16,16,15,17,16,14,13,11,11,10,10,9,9,9,8,8,8,7,7,7,7,7,6,6,6,5,5,7,7,7,6,6,5,5,5,8,8,8,8,8,8,8,8,8,8,7,7,7,6,6,6,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 7,7,7,7,8,8,8,9,9,10,11,12,13,14,15,15,17,18,19,20,22,23,24,25,25,25,26,27,28,27,27,27,25,25,24,23,21,19,16,15,16,16,15,15,15,16,17,17,17,16,15,13,12,12,12,12,14,14,15,17,20,23,25,27,30,29,29,27,25,23,20,19,19,20,23,24,26,26,25,25,24,22,20,17,16,15,15,15,21,23,25,28,31,32,33,34,37,38,40,43,46,49,52,53,59,59,60,59,55,48,42,38,30,28,24,23,25,31,37,42,42,45,49,50,51,55,61,66,78,88,96,98,95,89,77,65,56,56,61,70,81,87,85,81,65,54,40,28,23,24,27,30,33,35,37,38,38,36,34,33,33,34,37,40,44,51,58,64,63,63,61,57,53,51,52,53,51,46,39,33,32,44,71,96,123,131,133,118,94,71,53,42,47,52,56,53,47,43,44,46,53,57,59,57,50,42,38,37,35,32,30,30,31,41,63,83,108,119,127,122,109,92,73,60,49,46,43,41,40,38,36,34,33,31,28,28,29,31,31,30,36,39,43,48,51,52,53,52,46,41,35,34,36,39,39,38,37,33,29,29,34,41,48,52,58,57,56,53,48,46,46,47,43,39,33,28,24,22,22,22,26,27,29,31,32,35,40,43,45,43,39,34,28,26,27,29,37,41,44,43,38,33,31,31,37,41,47,51,51,47,42,38,37,34,35,42,49,59,73,86,95,93,87,75,59,43,31,26,22,22,21,20,20,23,27,31,39,39,38,35,29,25,23,23,23,22,20,18,18,24,31,37,51,53,54,50,43,36,33,33,38,39,39,37,32,27,25,24,23,23,24,24,25,26,26,27,28,29,30,29,29,29,32,34,38,40,44,47,47,45,42,40,37,35,33,30,29,29,31,32,34,36,39,40,40,38,35,33,31,32,32,31,29,26,23,22,21,20,18,16,15,15,15,16,18,20,22,23,23,21,19,18,19,18,17,16,17,19,20,21,25,28,32,36,38,42,46,49,50,55,57,54,50,47,41,34,27,25,21,18,15,14,15,15,15,15,15,16,17,19,21,22,25,26,28,30,31,30,30,29,27,26,24,22,20,19,18,18,19,19,18,18,17,16,16,15,16,15,14,12,11,11,10,11,9,9,9,9,8,8,8,7,7,7,7,7,6,6,6,5,7,7,7,6,6,5,5,5,8,8,8,8,8,8,8,8,8,7,7,7,6,6,6,6,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 6,6,7,7,7,8,8,8,9,9,10,11,12,13,13,14,16,16,17,18,20,21,22,22,23,24,24,25,25,25,24,24,22,21,21,20,19,17,15,14,16,16,16,16,17,18,18,19,17,16,15,13,12,11,11,11,14,15,16,19,21,24,26,27,28,27,25,23,21,18,16,15,15,17,19,21,23,23,23,23,21,19,17,15,15,16,17,18,25,26,28,31,33,35,35,36,38,40,43,46,49,51,51,52,54,55,55,53,48,42,36,32,29,27,24,22,23,27,32,36,38,40,43,46,48,53,59,64,72,80,88,89,86,81,70,59,57,60,67,78,88,91,87,82,70,60,44,32,27,27,30,32,34,36,39,40,39,36,33,30,30,31,32,34,38,46,55,61,62,62,59,55,51,50,51,52,54,49,42,36,34,44,68,90,114,123,126,113,93,74,60,51,58,62,65,61,52,46,45,47,54,57,58,54,46,38,33,32,32,29,28,28,30,38,56,74,95,107,116,113,101,85,68,56,50,46,42,38,37,36,34,32,30,29,28,28,29,29,29,29,34,37,42,46,49,50,49,48,40,35,29,27,31,37,43,46,46,43,38,36,39,45,52,57,62,61,59,54,48,44,42,42,39,36,32,28,25,24,25,25,28,29,31,31,33,36,41,45,48,45,39,31,25,23,25,28,37,41,45,44,38,33,30,30,36,41,47,51,52,49,44,41,37,34,34,39,48,59,74,88,99,96,89,76,59,42,29,22,19,20,19,18,19,22,28,32,42,43,43,39,33,26,21,19,21,21,20,19,18,20,25,28,39,42,45,45,43,40,39,39,43,43,41,38,32,27,23,21,21,21,22,22,24,25,27,27,29,30,30,29,27,25,26,28,31,34,39,43,44,43,40,38,35,34,32,30,30,31,32,34,34,35,38,40,40,39,36,35,32,33,33,33,31,29,27,25,22,20,17,15,14,14,15,16,20,22,24,25,25,22,19,17,18,17,16,16,17,19,21,23,27,31,37,42,46,51,57,60,60,64,65,61,56,52,44,36,30,27,23,19,16,14,14,15,14,14,15,15,16,17,18,18,22,23,25,27,28,29,29,29,27,26,24,21,19,17,16,16,18,18,17,17,16,16,15,15,15,15,13,12,11,11,11,11,10,10,9,9,9,8,8,8,8,8,7,7,7,6,6,6,7,7,7,6,6,5,5,5,7,7,7,7,7,7,7,7,7,7,7,6,6,6,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 6,6,6,7,7,7,8,8,9,9,10,10,11,12,12,12,14,15,15,16,18,19,19,20,21,22,22,23,23,22,21,21,19,19,19,18,17,16,15,14,15,16,17,17,18,18,19,19,16,15,14,12,11,11,11,11,15,16,17,19,22,23,24,25,25,23,21,19,17,15,13,12,14,15,17,20,21,22,21,21,19,18,16,15,16,18,20,22,28,29,31,33,35,35,36,36,37,38,41,44,46,47,46,46,46,47,46,44,40,35,30,27,28,27,25,24,25,28,31,34,39,40,43,45,48,52,56,59,65,72,78,78,76,72,63,54,58,63,71,82,90,91,86,81,68,58,45,35,30,31,33,34,35,36,38,39,39,36,33,31,31,31,31,32,35,41,50,56,61,61,59,55,51,49,50,51,56,51,45,40,37,45,64,83,104,113,117,108,92,79,70,65,73,76,76,68,57,48,46,47,54,58,59,56,47,38,33,31,30,27,27,28,29,35,50,64,84,95,102,99,88,76,63,52,49,46,41,37,35,33,31,29,28,28,28,28,28,28,30,31,31,34,38,42,44,44,43,42,37,32,28,27,31,40,49,54,55,52,48,45,46,50,57,61,63,62,59,53,46,39,36,35,35,33,30,28,26,26,27,28,30,30,31,31,32,35,40,44,47,44,38,30,24,23,26,28,39,43,45,43,37,31,29,29,33,38,45,50,52,51,47,43,38,34,32,37,44,54,70,83,96,94,88,76,59,42,28,21,18,18,18,18,19,24,31,37,47,48,48,44,36,28,21,18,20,21,21,21,20,21,23,26,34,39,44,48,49,49,48,47,47,44,40,36,31,26,22,19,20,20,20,20,22,24,26,27,32,33,33,31,28,25,25,26,28,30,34,37,37,36,33,31,30,30,29,30,31,33,34,35,35,36,38,39,39,38,37,36,33,34,34,34,33,31,29,28,21,19,16,14,14,15,17,18,24,26,27,28,27,23,19,17,17,17,17,17,18,21,23,25,29,33,39,45,50,56,62,66,66,70,70,65,60,55,47,40,31,28,24,20,16,15,15,15,15,15,15,16,16,16,15,15,19,20,22,23,25,26,27,27,26,25,22,20,17,16,15,14,16,16,16,16,15,15,15,15,14,14,12,11,11,10,11,11,10,10,10,9,9,9,8,8,8,8,8,7,7,7,6,6,7,7,7,6,6,5,5,5,7,7,7,7,7,7,7,7,7,7,6,6,6,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 5,6,6,6,7,7,7,7,9,9,9,10,10,11,11,11,13,13,14,15,16,16,17,17,19,20,20,20,20,19,18,18,17,17,17,17,17,16,15,14,16,16,17,18,18,18,17,17,14,13,13,12,11,12,12,12,15,16,18,20,21,22,22,22,20,19,17,16,14,13,13,13,14,16,18,20,21,21,20,20,19,18,17,16,18,21,25,28,33,34,35,36,37,37,36,36,35,36,38,39,40,39,38,38,37,37,37,36,33,29,26,23,27,26,26,26,28,30,33,35,40,42,44,47,49,52,54,55,60,65,69,68,66,65,60,53,57,62,70,79,85,85,81,77,59,52,44,38,36,36,37,37,36,37,37,37,37,37,36,36,36,35,34,33,34,38,45,50,58,59,58,56,51,48,48,48,53,49,44,41,39,44,59,74,91,101,107,101,92,86,85,84,93,93,88,76,61,49,45,45,52,56,60,57,49,39,33,30,30,27,27,29,30,34,46,57,74,82,86,81,73,66,59,53,49,46,41,38,35,33,29,27,28,28,29,28,28,30,33,36,34,36,38,39,40,39,37,36,33,30,28,29,34,43,53,59,60,59,56,53,51,54,59,63,61,60,57,51,42,34,30,28,30,29,27,26,26,27,28,29,31,31,31,30,30,33,38,42,44,42,37,30,26,25,28,32,42,44,45,41,34,28,26,27,30,36,43,50,54,53,50,48,41,36,33,35,40,48,61,74,88,87,83,74,59,43,31,25,18,18,18,19,22,29,37,44,52,53,52,48,40,30,23,19,21,22,23,23,22,22,25,27,36,41,48,55,58,57,55,53,48,43,37,31,28,24,21,19,19,19,18,19,20,23,25,26,34,35,36,34,30,28,27,27,28,29,31,31,31,29,27,25,27,28,31,33,35,36,37,37,35,36,37,38,37,36,35,34,32,32,33,34,33,32,30,29,20,19,17,15,16,19,22,25,31,31,31,30,27,24,20,17,18,17,17,18,20,23,25,27,31,34,40,45,50,55,61,65,68,71,69,63,58,55,48,42,31,29,25,20,17,16,16,16,18,18,19,19,18,17,16,15,17,17,18,20,21,22,23,24,24,23,21,18,16,15,14,14,15,15,15,15,15,15,15,15,13,13,12,11,10,10,11,11,11,10,10,10,9,9,9,9,9,8,8,8,7,7,7,7,7,7,7,6,6,5,5,5,6,6,6,6,6,6,6,6,6,6,6,6,5,5,5,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 5,5,6,6,6,7,7,7,8,9,9,9,9,10,10,10,12,12,13,13,14,15,15,16,18,18,19,19,18,17,16,16,16,16,17,17,17,16,15,14,16,16,17,18,18,17,15,14,12,12,11,11,11,12,13,14,16,17,18,20,20,20,19,18,16,15,14,13,13,14,14,15,16,18,19,21,21,21,20,19,20,19,18,18,20,25,29,33,39,40,40,40,39,38,37,37,34,34,34,34,33,32,31,31,30,30,31,31,29,27,24,23,25,25,26,27,30,33,36,38,42,44,47,51,54,56,56,55,58,62,63,61,61,62,60,56,57,60,65,69,72,70,66,62,51,49,46,45,45,46,45,43,39,38,36,35,36,39,42,44,42,41,39,36,34,36,41,44,54,56,57,55,51,47,44,44,46,43,40,39,38,40,51,63,77,88,96,95,92,95,101,104,113,110,100,83,62,47,41,40,47,52,58,57,49,39,32,28,30,28,28,30,32,34,43,53,61,66,67,61,56,56,56,55,53,50,47,44,41,37,33,29,30,31,31,30,30,33,39,44,43,43,42,40,38,35,32,31,28,28,28,30,36,44,54,60,62,62,61,58,55,55,58,62,59,59,56,49,39,31,25,23,26,25,25,25,26,27,29,30,32,31,30,28,27,29,34,38,39,38,35,31,28,29,32,36,45,46,44,38,30,25,24,25,29,35,43,52,56,57,55,53,45,40,36,36,38,42,53,64,75,76,74,67,56,42,32,26,18,19,20,22,26,34,44,51,56,57,56,51,42,33,26,22,23,24,25,24,23,23,25,27,39,44,53,61,64,63,58,53,47,40,32,26,24,23,21,20,20,19,18,18,19,21,23,25,34,36,37,36,33,30,29,29,30,30,29,28,27,25,24,23,30,33,37,40,42,41,39,38,34,34,35,35,34,33,31,30,28,29,30,31,31,29,28,27,21,20,18,18,21,25,30,33,38,37,35,32,28,24,20,18,18,18,18,20,22,25,28,29,31,35,40,44,47,52,56,60,62,64,61,55,50,48,44,38,31,29,25,21,18,17,17,17,23,24,24,24,23,21,19,18,15,15,16,16,17,19,20,21,22,21,19,17,16,15,15,15,14,14,14,14,14,14,14,14,13,12,11,10,10,10,11,11,11,11,10,10,10,9,9,9,9,9,8,8,8,7,7,7,7,7,7,6,6,5,5,5,6,6,6,6,6,6,6,6,6,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 5,5,5,6,6,7,7,7,8,8,9,9,9,9,9,10,11,11,12,12,13,14,14,15,17,18,18,18,17,16,15,15,15,16,16,17,17,16,15,15,16,17,17,18,17,16,14,13,11,11,11,11,12,13,14,15,17,17,19,19,19,18,17,16,14,13,12,12,13,14,16,17,18,19,21,22,22,21,20,19,21,20,19,19,22,27,32,36,43,43,43,43,42,40,39,38,33,33,32,31,29,28,27,27,26,27,28,28,28,26,25,23,23,24,25,28,31,34,37,39,45,47,51,56,60,61,60,58,58,61,61,58,58,61,61,58,58,59,60,60,58,54,49,46,49,49,50,52,54,55,53,50,41,39,36,34,36,40,46,49,46,45,42,39,36,35,38,41,51,53,55,54,50,45,42,40,40,37,37,37,35,36,45,56,68,80,89,91,93,101,112,118,126,121,108,87,62,45,37,36,42,48,55,56,48,38,30,26,31,29,29,32,33,35,42,51,50,53,52,46,43,48,53,56,58,56,53,51,48,43,38,34,32,33,33,32,32,36,43,49,52,50,47,42,37,33,30,28,24,25,27,31,36,44,53,59,62,63,63,60,56,55,57,60,59,58,55,48,38,29,24,21,23,23,23,24,26,27,29,30,32,31,29,26,25,27,32,36,36,36,34,32,30,31,35,38,47,47,44,37,28,22,22,24,29,35,44,53,58,60,58,57,49,43,38,37,37,39,48,57,64,65,65,61,51,39,30,25,19,20,21,23,28,37,48,55,58,59,57,52,43,34,28,24,25,26,26,24,22,22,24,26,40,46,55,64,68,65,58,52,46,38,29,23,21,22,22,21,20,19,18,17,18,20,23,24,33,35,37,36,34,31,30,30,31,30,28,26,25,24,24,24,34,38,42,46,47,45,41,39,33,33,33,32,31,30,28,27,25,26,28,28,28,27,26,25,22,21,20,21,24,30,35,39,42,40,37,33,28,24,21,19,19,19,19,20,23,26,29,31,31,35,39,42,45,49,53,56,54,55,52,46,41,40,38,33,31,28,25,21,18,18,18,18,27,28,28,28,26,24,22,21,14,14,14,14,15,16,18,18,20,19,18,17,16,15,15,15,14,14,14,14,14,14,14,14,12,12,11,10,10,10,11,11,11,11,11,10,10,9,9,9,9,9,9,8,8,7,7,7,7,7,7,6,6,5,5,5,6,6,6,6,6,6,6,6,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 5,5,5,6,6,7,7,7,8,8,8,8,8,8,8,8,9,9,9,10,10,11,11,11,15,15,16,16,16,15,14,14,14,15,16,17,17,17,17,16,15,16,16,16,16,15,14,13,9,9,10,11,11,12,13,13,16,17,18,18,18,16,14,13,11,11,12,13,15,17,19,20,21,22,24,24,23,20,17,15,20,20,20,23,28,34,41,44,47,46,46,46,46,43,39,35,31,28,24,22,23,24,24,24,26,26,26,27,27,29,30,31,26,27,29,32,36,39,41,42,51,50,51,54,57,58,58,56,59,56,53,54,57,59,58,56,57,56,53,49,43,40,40,41,42,52,63,69,71,69,61,52,43,35,30,32,36,42,49,57,57,59,57,49,40,35,35,38,46,49,51,49,44,38,33,31,33,31,28,25,26,30,38,44,56,65,77,88,99,113,129,141,147,141,125,99,69,45,31,27,35,43,52,54,49,42,38,36,34,35,35,34,34,35,38,41,43,42,39,36,34,39,48,56,65,65,64,59,52,44,39,37,35,35,35,36,39,45,53,59,63,60,55,48,41,35,30,27,27,26,26,27,32,40,47,52,58,59,59,58,56,54,55,56,54,57,56,49,43,39,34,28,28,21,18,22,26,27,28,30,31,30,27,26,25,26,27,28,30,33,35,35,34,36,41,45,44,45,43,35,25,20,20,23,33,39,48,57,61,61,59,56,51,46,40,35,34,38,43,47,55,55,55,52,47,40,32,28,24,22,21,24,32,42,51,55,60,61,60,54,44,34,27,25,27,27,26,26,26,27,28,28,39,45,54,63,67,64,56,49,38,34,28,24,23,23,22,22,25,23,21,19,19,20,23,25,31,32,33,34,34,33,31,30,27,27,27,25,24,25,29,32,35,45,55,57,56,53,47,40,36,32,26,23,21,21,21,21,21,22,25,27,28,28,28,28,23,23,24,27,32,37,43,46,48,45,41,36,29,24,19,17,19,20,22,23,25,25,26,26,31,34,37,40,42,41,39,38,37,36,36,34,33,32,31,31,29,27,23,21,19,20,22,23,25,27,30,32,31,27,23,20,18,17,15,13,14,15,17,19,18,18,17,17,17,16,16,15,13,13,12,11,11,12,12,13,13,13,13,12,12,11,11,11,9,9,9,9,9,9,9,9,8,9,9,10,10,9,9,8,7,7,7,6,6,5,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 5,5,5,6,6,6,7,7,8,8,8,8,8,8,8,8,9,9,9,10,10,10,11,11,14,15,15,16,16,15,14,14,14,15,16,16,17,17,16,16,15,15,16,15,15,14,13,12,9,9,10,11,12,12,13,13,16,16,17,17,16,15,13,12,12,12,13,14,16,19,20,21,23,23,23,23,22,21,19,18,21,22,23,26,31,36,41,44,45,44,44,44,44,41,37,33,28,25,21,20,21,23,24,23,26,26,27,28,29,30,31,32,27,28,30,33,35,38,41,42,48,48,49,52,56,58,57,56,58,55,53,53,55,56,56,54,52,51,47,42,38,36,38,40,47,58,71,77,80,77,68,58,46,38,32,35,40,47,55,63,63,63,61,53,43,37,36,39,43,46,47,45,40,34,30,28,29,28,27,25,26,29,35,40,50,59,72,86,100,118,138,152,153,147,131,104,73,47,32,27,34,42,50,53,49,43,40,39,38,38,37,35,34,34,37,40,38,38,36,33,32,38,48,57,67,67,65,60,53,46,42,41,40,41,41,42,45,52,61,67,72,68,61,52,43,34,27,23,25,24,23,25,29,35,42,46,53,54,55,54,52,51,52,53,57,62,64,60,56,51,45,38,32,24,19,21,25,27,28,31,32,31,29,27,26,26,27,27,29,31,33,33,34,36,41,45,44,44,41,33,24,19,20,23,34,39,47,55,58,57,54,51,46,43,38,34,34,37,41,45,49,50,50,48,44,38,32,28,25,23,22,25,33,42,50,54,58,59,57,51,42,33,28,26,27,27,27,27,28,29,29,30,37,42,50,58,62,59,52,46,38,34,29,25,24,25,24,24,26,24,22,20,20,21,23,24,29,30,32,33,33,32,31,30,28,27,26,24,23,25,30,34,39,50,59,62,60,56,48,40,32,28,23,20,19,20,20,20,22,23,25,27,28,28,28,27,25,25,27,29,34,40,45,48,49,46,41,35,28,23,19,16,19,20,22,24,25,26,27,27,28,30,33,36,37,36,34,32,31,30,30,30,29,29,28,28,28,26,23,20,19,20,22,23,27,29,31,33,32,29,25,22,19,17,15,14,14,15,18,19,18,18,18,17,17,16,15,15,13,13,12,11,11,11,12,12,13,13,12,12,12,11,11,11,8,8,8,8,8,8,8,8,8,9,9,10,10,9,9,8,7,7,7,6,6,5,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 5,5,5,5,6,6,6,7,8,8,8,8,8,8,8,8,9,9,9,9,10,10,10,11,13,14,14,15,15,15,14,14,14,14,15,16,17,17,16,16,15,15,15,14,13,12,11,10,9,10,10,11,12,13,13,13,16,16,16,15,15,13,12,11,13,14,15,17,19,21,23,24,25,24,23,22,22,21,21,21,24,25,27,31,34,38,41,42,42,42,41,41,40,38,33,29,23,21,18,17,19,22,23,23,27,27,28,29,31,32,33,34,30,30,31,33,35,37,39,40,44,44,45,49,54,56,57,56,57,54,51,50,51,52,52,51,47,45,41,35,32,32,36,40,52,65,79,87,89,85,73,62,46,38,33,36,43,51,61,70,70,70,66,58,48,40,38,39,40,41,42,39,35,30,27,27,26,27,28,28,28,30,33,36,42,51,64,78,95,117,140,157,166,160,144,117,84,56,39,33,33,40,48,51,49,45,43,43,44,43,40,36,33,33,36,38,35,35,33,31,31,37,47,56,68,67,64,59,53,48,46,46,46,47,47,48,52,58,67,73,77,73,65,55,44,34,26,22,22,21,21,21,25,29,34,38,45,47,48,48,47,46,48,49,58,66,73,74,73,68,59,49,38,28,21,21,25,26,29,33,34,33,32,31,29,28,27,27,27,29,31,32,34,37,42,46,44,43,38,30,23,20,22,25,36,40,46,50,52,50,46,43,39,37,34,32,32,35,38,40,40,41,42,42,40,36,31,28,27,25,24,27,34,42,48,51,55,54,51,45,37,31,28,27,26,26,27,28,29,31,32,32,35,39,45,51,54,53,47,42,38,34,30,27,27,28,27,27,27,26,24,22,22,22,23,24,27,28,29,30,31,31,31,31,29,28,26,23,23,26,31,36,44,55,64,66,63,57,48,39,26,23,19,17,18,20,22,22,25,26,28,29,29,29,28,27,28,28,29,32,36,42,47,50,49,46,40,33,26,21,17,16,18,19,21,23,25,26,27,27,25,26,28,30,30,28,26,25,22,22,22,23,23,24,24,24,26,24,21,19,18,19,21,22,28,29,31,33,32,29,26,24,20,18,16,15,15,16,18,19,19,20,20,19,18,17,16,15,14,13,12,11,11,11,11,11,13,12,12,12,11,11,11,11,8,8,8,8,8,8,8,8,8,8,9,9,9,9,8,8,7,7,7,6,6,5,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 4,4,5,5,5,6,6,6,7,7,7,7,7,7,7,7,8,8,9,9,9,10,10,10,12,12,13,14,14,14,14,13,13,14,15,16,16,16,16,15,14,14,14,13,12,11,9,8,10,10,11,11,12,13,14,14,15,15,14,14,13,12,11,11,15,16,18,20,22,24,25,25,26,25,23,21,21,22,24,25,26,28,31,34,37,38,39,39,39,38,37,37,37,34,29,26,21,19,16,17,19,22,24,25,27,28,30,32,33,35,36,36,32,32,32,32,33,34,36,37,38,38,40,45,50,54,54,54,53,51,48,46,45,46,47,47,45,43,38,34,31,33,38,42,57,70,84,91,92,86,72,60,44,36,32,36,44,52,63,72,76,75,70,62,52,44,40,39,38,39,38,35,31,28,27,27,28,31,34,35,35,33,33,34,37,45,56,69,85,107,132,150,170,165,151,125,92,63,45,37,34,39,46,49,49,47,47,47,48,46,42,37,33,32,35,38,38,38,36,32,31,35,45,52,63,63,60,56,52,50,51,53,51,52,51,52,54,60,68,73,73,69,62,53,43,34,28,24,21,20,20,20,22,25,29,31,38,40,42,42,42,42,44,45,57,68,79,86,88,83,71,59,44,33,23,21,24,26,30,35,37,37,37,36,35,32,29,28,27,28,30,32,36,40,44,47,45,42,37,30,24,23,26,29,36,38,42,45,45,42,38,35,31,31,30,29,30,31,32,33,33,34,36,37,37,34,32,30,28,26,26,28,34,41,45,47,47,45,41,36,31,28,26,25,23,24,26,28,30,32,33,34,36,37,40,44,47,46,43,39,38,34,31,29,30,30,30,29,28,28,26,25,24,23,23,23,25,25,27,28,29,30,31,31,31,29,26,23,22,26,33,38,47,57,66,67,63,56,45,36,22,20,17,17,20,24,26,27,30,31,32,32,32,30,28,27,29,29,29,32,36,41,46,49,47,43,37,30,23,19,16,15,17,18,20,22,23,24,25,25,23,23,24,25,24,22,20,19,15,16,17,18,19,20,21,22,22,21,19,18,18,19,20,21,26,28,30,31,30,28,25,24,21,19,17,15,15,16,18,19,21,22,22,22,22,20,18,17,16,15,13,12,11,10,10,11,12,12,12,11,11,11,10,10,7,7,7,7,7,7,7,7,7,8,9,9,9,9,8,7,7,7,7,6,6,5,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 4,4,4,5,5,5,6,6,7,7,7,7,7,7,7,7,8,8,8,9,9,9,10,10,10,11,12,13,14,14,13,13,13,14,15,15,16,16,15,15,13,13,13,13,12,11,9,8,10,10,11,12,13,13,14,14,14,14,13,13,12,12,12,12,17,18,20,22,24,25,25,25,25,24,22,20,20,22,25,27,27,29,32,34,36,36,35,35,34,33,33,34,34,31,27,23,21,18,17,17,21,24,26,27,27,29,31,34,36,38,38,39,33,32,30,29,29,30,32,33,32,32,35,40,45,49,50,50,47,46,43,40,39,39,41,43,45,44,41,38,36,38,42,46,61,73,85,91,90,82,68,55,43,37,34,39,47,55,64,73,76,74,70,63,54,47,42,40,39,38,36,33,29,27,28,30,34,38,43,44,43,39,36,35,33,40,49,59,74,96,121,138,159,156,145,122,92,65,47,39,35,39,43,46,47,47,48,48,49,47,42,36,32,33,37,41,46,46,43,38,34,35,40,46,54,54,54,53,52,54,59,62,62,61,58,56,56,59,65,70,67,64,58,50,41,33,27,24,23,23,23,23,24,26,27,28,35,37,39,39,39,39,41,43,57,69,83,93,98,94,81,67,47,35,24,22,24,26,31,36,40,41,42,43,41,37,33,30,28,29,30,33,37,42,46,48,45,42,37,31,27,27,30,33,34,36,39,40,40,37,34,32,29,29,28,28,28,27,27,27,28,30,32,34,34,33,32,31,27,26,26,28,33,37,40,41,39,36,32,28,25,24,23,23,20,22,25,28,31,33,35,35,37,37,37,38,40,41,39,37,38,35,32,31,32,32,32,31,30,30,29,28,27,25,23,23,23,23,24,26,28,30,32,33,33,31,28,24,23,26,32,37,46,55,63,63,58,50,40,30,21,19,18,20,25,31,35,36,39,39,39,38,36,32,30,28,27,27,27,29,32,36,40,43,41,39,34,28,23,19,16,15,16,17,19,20,21,22,22,22,22,23,23,23,21,19,17,16,13,14,15,16,17,18,19,20,19,18,17,17,17,18,19,20,23,24,26,27,27,25,23,22,21,19,17,15,14,15,17,18,23,24,25,26,25,24,22,21,18,17,15,13,12,11,11,11,12,12,11,11,11,10,10,10,7,7,7,7,7,7,7,7,7,7,8,9,9,8,7,7,7,7,7,6,6,5,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,4,4,4,5,5,5,5,6,6,6,6,6,6,6,6,7,8,8,8,9,9,9,9,9,10,11,12,13,13,13,13,13,13,14,15,15,15,15,15,12,12,13,13,13,12,11,10,11,11,11,12,13,14,14,15,13,12,12,12,12,13,14,15,19,20,22,24,25,25,24,23,23,22,21,20,20,22,25,27,28,29,30,32,32,32,31,30,30,29,30,31,32,30,26,23,21,19,17,18,21,25,27,28,27,29,33,36,39,41,41,41,33,31,28,25,24,25,26,27,26,27,29,34,40,44,45,45,41,40,38,35,32,33,36,40,45,45,45,44,43,43,45,47,61,71,81,85,83,76,64,52,44,39,37,43,51,57,64,71,70,68,65,60,54,48,43,40,40,39,35,31,28,27,30,33,41,45,50,51,48,42,37,34,30,35,42,50,62,82,105,122,141,140,134,117,91,67,50,43,36,37,39,40,42,43,44,44,47,44,39,34,31,34,40,45,53,53,51,45,38,35,36,39,45,47,50,53,57,63,70,75,76,74,69,63,58,58,61,64,64,61,55,48,41,34,28,25,29,29,29,30,30,31,31,31,35,37,39,39,39,39,41,43,56,68,83,94,101,98,84,69,48,36,25,22,24,27,32,37,39,42,45,47,45,41,35,32,29,28,29,32,37,42,45,46,44,41,37,32,30,31,33,34,34,36,38,39,39,38,36,35,33,32,31,29,28,26,25,24,26,27,29,31,31,31,31,30,26,25,24,27,30,33,34,34,31,28,24,23,23,23,22,21,19,21,25,30,34,36,37,38,39,36,33,33,34,36,36,36,38,36,33,32,33,33,32,30,31,32,32,31,29,26,24,22,22,22,23,25,28,31,33,35,35,33,30,26,24,26,31,35,43,52,58,56,50,43,34,25,21,20,20,24,31,38,44,46,49,49,47,44,40,35,31,29,26,25,25,25,27,30,33,35,36,35,32,29,26,22,20,18,18,18,19,20,21,21,20,20,23,23,22,21,20,19,17,16,15,15,15,16,16,17,17,17,16,16,15,16,16,17,18,19,21,21,23,24,23,22,21,20,20,18,16,14,13,14,15,16,22,23,26,27,28,27,25,23,21,20,18,15,14,12,12,11,11,11,11,11,10,10,10,9,8,8,8,8,8,8,8,8,7,7,8,8,8,8,7,7,7,7,7,6,6,5,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,4,4,4,5,5,5,6,6,6,6,6,6,6,6,7,7,8,8,8,9,9,9,8,9,10,12,13,13,13,13,12,13,14,15,15,15,15,14,11,12,12,13,14,13,13,13,11,11,12,12,13,14,15,15,12,12,11,12,13,15,17,18,21,22,24,25,25,24,22,21,21,20,20,20,21,22,24,25,27,27,28,28,27,27,26,25,26,26,27,29,31,30,27,24,22,19,17,18,21,24,26,27,28,30,34,38,41,43,43,43,32,29,25,22,20,20,21,22,22,23,25,30,36,39,40,40,35,34,33,29,27,28,33,37,42,45,48,49,47,45,44,44,54,63,71,73,72,68,59,49,43,39,39,45,51,55,60,66,62,61,59,56,53,48,44,41,40,38,34,29,26,27,31,35,45,49,53,54,49,42,36,32,28,32,36,40,47,62,82,96,115,117,115,103,83,62,48,42,35,34,33,34,35,37,38,38,43,40,35,31,30,35,43,49,56,58,57,51,42,36,33,34,39,43,50,57,66,75,84,90,89,85,77,67,59,54,55,56,58,57,53,49,44,40,36,35,34,35,36,37,38,37,37,36,38,40,41,41,40,40,42,43,51,62,75,87,94,93,79,65,47,35,25,22,24,27,32,37,37,40,45,48,47,42,36,32,28,27,26,29,35,40,42,43,42,39,35,33,32,33,33,34,35,37,39,41,42,43,43,43,41,39,37,33,30,27,25,24,24,25,26,28,28,28,28,27,23,23,23,24,27,29,29,27,26,23,21,21,23,24,23,21,20,23,27,33,37,40,41,42,39,35,30,27,28,31,33,34,38,36,34,33,33,32,31,29,32,33,34,33,31,28,24,21,21,22,23,25,28,32,35,37,36,35,33,29,26,26,29,32,41,48,53,50,44,38,30,22,21,20,21,26,35,44,50,53,58,57,55,50,44,38,33,30,26,24,23,22,23,25,27,29,32,32,33,33,31,28,26,24,22,22,22,22,22,21,20,19,22,22,21,20,19,18,17,16,17,17,16,16,15,15,14,14,13,14,14,15,16,17,18,18,19,20,21,22,22,21,20,20,19,18,15,13,12,12,14,15,18,20,24,27,28,27,26,24,23,22,20,17,15,14,13,12,11,11,11,10,10,10,9,9,8,8,8,8,8,8,8,8,6,7,7,8,8,7,7,6,7,7,7,6,6,5,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,4,4,5,5,5,6,6,6,6,6,6,6,6,7,7,7,8,8,9,9,9,8,8,10,11,12,13,13,13,12,13,14,15,15,15,15,14,10,11,12,14,14,15,14,14,11,11,12,13,13,14,15,15,11,11,11,12,13,16,19,20,22,23,25,26,25,23,21,19,19,19,19,20,21,22,24,24,27,26,26,25,24,23,23,23,24,24,26,28,30,30,27,25,21,19,17,17,20,23,25,26,28,30,35,39,42,44,44,44,31,28,24,19,17,17,18,19,20,21,23,27,33,37,37,37,31,31,30,27,24,26,31,36,40,44,49,51,49,46,43,41,46,54,60,62,62,61,54,46,40,37,37,44,49,52,55,59,57,56,54,53,51,48,44,41,40,38,33,28,25,26,31,36,47,50,54,53,48,40,33,29,29,31,32,32,35,45,61,73,89,93,94,85,68,50,38,32,33,31,30,29,30,32,32,32,40,37,33,30,30,36,45,52,57,59,59,53,44,36,32,31,36,42,51,61,72,83,94,100,94,89,80,68,57,50,49,49,52,52,51,50,48,47,46,46,38,39,41,42,43,42,41,40,40,42,43,43,42,41,43,44,45,55,67,78,86,85,72,58,46,35,24,23,25,27,32,37,34,38,44,48,47,42,36,31,27,25,24,27,33,38,40,40,39,37,34,32,33,33,33,32,36,38,40,43,46,47,48,49,47,45,41,37,32,29,27,26,23,24,25,25,26,26,25,25,22,21,21,23,25,26,25,24,24,22,20,21,24,26,24,21,21,24,29,35,40,43,44,45,39,34,27,24,25,28,30,32,38,36,34,33,33,32,30,28,33,34,35,35,32,28,24,21,21,22,23,25,28,32,36,38,37,36,34,30,27,26,28,30,39,46,50,46,40,35,28,21,21,20,22,28,37,47,54,57,64,62,59,54,47,40,34,30,26,24,22,21,21,22,24,26,30,32,34,36,35,33,30,28,25,25,25,24,23,22,21,20,21,21,20,20,19,18,17,17,18,18,17,16,14,13,12,12,12,12,13,14,15,16,17,18,19,20,21,21,22,21,21,20,19,17,14,12,11,11,13,14,15,18,22,25,27,27,25,24,25,24,21,19,16,14,13,13,11,11,11,10,10,9,9,9,9,9,9,9,9,9,9,9,6,7,7,8,8,7,7,6,7,7,7,6,6,5,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 4,4,4,4,4,4,4,4,5,5,5,6,6,7,7,7,6,6,6,7,7,8,8,8,9,9,9,10,10,11,11,11,8,9,10,11,12,13,12,12,12,12,12,12,12,12,12,12,16,16,15,14,14,14,15,15,14,13,13,13,15,17,19,21,23,23,24,23,22,20,18,16,17,19,21,22,23,23,22,22,21,21,21,22,22,23,23,23,26,27,29,30,30,29,27,25,20,19,18,18,19,22,25,27,29,33,38,43,45,44,42,40,30,27,22,18,16,17,19,21,21,23,26,29,31,32,33,32,31,29,26,22,21,24,30,35,45,49,54,55,50,43,36,32,38,43,48,53,54,51,46,42,35,34,33,36,41,44,44,42,46,47,47,45,42,40,40,41,40,37,33,27,24,25,30,34,46,49,52,49,41,33,28,27,27,29,30,29,30,34,42,49,66,68,69,62,50,38,30,27,25,27,27,26,24,23,24,25,30,31,31,31,33,37,43,48,58,58,55,48,38,31,29,30,37,48,59,68,78,92,102,107,100,93,80,66,53,46,44,44,47,51,57,60,61,59,57,56,50,48,47,48,51,51,47,43,44,43,42,44,46,45,40,36,42,45,51,60,66,66,60,54,39,33,27,24,26,28,28,26,32,32,34,38,42,42,38,33,25,23,22,24,28,32,34,34,34,32,31,32,34,37,38,37,40,41,44,46,50,53,55,56,57,54,49,43,37,33,31,29,26,27,27,27,27,26,25,24,22,23,24,25,26,26,26,26,21,21,22,23,24,25,25,26,21,24,30,37,43,46,45,43,39,34,27,21,20,24,30,34,39,39,38,34,31,28,29,30,31,33,35,35,32,28,26,26,21,23,25,26,27,30,34,38,37,36,33,29,27,27,31,34,43,44,46,46,42,36,29,25,23,24,26,31,37,45,51,55,60,61,61,59,53,45,38,33,26,24,21,19,18,20,22,24,30,33,37,40,41,38,35,32,31,28,24,22,23,24,24,24,22,22,21,20,18,17,16,16,17,17,16,15,14,12,10,9,11,11,11,12,13,14,15,16,19,20,23,24,24,23,21,20,19,18,17,15,13,12,10,10,15,17,20,24,26,26,26,25,27,26,24,22,20,18,16,16,14,13,12,11,11,11,11,12,11,10,9,8,7,6,7,7,7,7,7,6,6,5,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 4,4,4,4,4,4,4,4,5,5,5,6,6,6,7,7,6,6,6,7,7,7,8,8,9,9,9,10,10,10,11,11,8,9,10,11,12,13,12,12,13,13,13,13,13,13,13,13,16,15,15,14,14,14,15,16,15,15,14,15,16,18,20,21,22,23,23,23,21,19,17,16,17,18,20,21,22,22,21,20,19,19,19,20,21,23,24,25,28,29,30,30,29,28,26,24,19,19,18,19,20,23,26,28,31,34,39,42,44,42,39,37,28,26,22,19,18,19,21,23,23,24,26,27,28,29,29,28,28,27,24,22,21,23,29,33,44,48,52,53,48,41,34,30,31,35,41,46,47,44,40,37,34,32,31,33,36,38,37,35,42,43,44,42,39,37,36,37,36,35,31,27,24,25,28,32,42,45,47,44,37,31,28,28,33,35,36,34,31,30,33,37,46,50,51,48,40,32,28,27,28,29,31,29,26,23,22,22,25,27,29,30,32,37,42,46,52,52,49,43,35,30,30,32,40,52,64,74,84,95,103,105,94,86,73,58,47,41,40,40,49,54,61,67,68,67,64,63,55,52,50,50,51,50,46,42,42,41,42,46,50,49,45,40,37,38,41,47,53,54,50,46,37,33,28,27,28,29,28,25,28,28,30,35,40,40,36,32,24,23,22,23,27,31,33,33,34,33,32,33,37,40,41,41,44,45,46,48,51,54,56,58,60,57,53,47,42,38,36,35,33,33,33,33,31,28,25,24,23,23,24,25,26,26,26,26,23,24,26,27,28,28,28,28,23,25,29,36,42,45,44,43,36,32,26,21,21,26,32,37,41,41,40,36,32,30,29,30,31,33,35,34,31,28,27,27,25,26,27,27,27,28,32,34,35,34,32,30,28,30,34,37,44,45,46,44,41,34,28,24,22,23,25,29,35,42,48,51,58,59,59,58,53,46,39,34,28,26,23,20,19,20,22,24,31,34,40,44,45,42,38,35,32,29,25,23,24,25,25,24,23,22,22,21,20,19,18,18,17,17,17,16,15,13,11,10,12,12,12,12,13,14,15,16,19,21,23,25,25,25,23,22,21,20,19,17,15,13,11,10,14,16,18,21,23,24,25,25,25,25,23,22,20,19,18,17,15,14,13,12,12,11,12,12,11,10,9,8,7,7,7,7,7,7,7,6,6,5,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 4,4,4,4,4,4,4,4,5,5,5,5,6,6,6,7,6,6,6,6,7,7,7,8,9,9,9,9,10,10,10,11,8,9,10,11,12,13,12,12,13,13,13,13,13,13,13,13,15,15,14,14,14,14,15,16,16,16,16,17,18,20,21,22,22,22,22,21,20,18,17,16,17,17,18,19,19,19,18,18,17,17,17,18,20,23,26,28,31,31,31,30,28,26,24,23,19,19,19,21,23,26,29,31,34,36,39,41,41,38,34,32,25,23,21,19,19,21,24,26,26,26,26,25,25,25,24,24,24,24,23,22,22,24,28,31,42,46,49,49,44,37,31,27,25,29,34,39,40,38,35,32,32,30,28,28,29,30,29,28,37,39,40,38,35,32,30,30,31,31,29,27,24,24,25,28,35,38,40,37,32,28,28,30,37,41,44,42,36,30,27,26,29,32,35,33,29,26,27,29,34,36,38,37,32,26,21,19,21,23,26,29,31,35,39,43,44,45,43,38,33,31,33,37,45,57,70,79,88,96,99,97,84,75,61,47,38,34,35,36,42,48,57,65,70,69,66,63,58,54,50,49,49,48,44,40,38,39,43,50,56,57,53,48,36,33,32,34,38,41,40,38,35,32,30,31,33,33,29,25,25,24,26,31,36,38,35,32,25,23,21,22,26,30,32,33,36,35,35,38,42,46,48,49,50,49,48,48,50,52,55,57,60,58,55,51,48,45,44,43,42,43,43,42,38,33,28,25,24,24,25,25,25,25,25,25,27,29,32,34,35,34,32,31,26,27,29,34,39,43,43,43,33,30,25,23,25,30,37,42,46,46,45,41,37,33,32,32,33,34,35,33,31,29,29,30,31,32,31,29,27,26,27,29,31,31,31,31,31,33,38,42,45,46,45,43,39,33,27,23,21,21,23,26,31,36,42,45,54,55,56,56,52,46,40,37,31,29,26,23,21,21,22,23,31,35,42,47,49,46,42,39,32,29,26,24,25,25,24,23,23,23,22,22,21,20,20,20,18,18,18,18,17,15,14,13,13,13,12,13,13,15,16,16,20,21,23,25,26,26,26,25,23,23,22,21,19,16,14,13,14,15,16,17,19,21,23,24,23,23,22,21,20,20,19,19,17,16,15,14,13,12,12,12,11,11,9,8,7,7,7,7,7,7,7,6,6,5,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 4,4,4,4,4,4,4,4,4,4,5,5,5,6,6,6,5,5,6,6,6,7,7,7,8,8,9,9,9,10,10,10,8,9,10,11,12,13,12,12,14,14,14,14,14,14,14,14,14,14,13,13,14,14,15,16,18,18,18,19,20,21,22,22,21,21,21,20,18,17,16,15,16,16,16,17,17,17,17,16,16,16,17,18,21,26,30,32,35,34,32,29,26,24,22,21,20,20,21,23,26,29,32,34,36,37,39,39,38,34,30,27,21,20,18,18,19,22,25,27,26,25,24,24,23,23,23,23,21,23,24,23,23,24,27,29,39,42,44,43,39,32,27,24,22,26,32,36,38,36,33,30,28,26,25,24,24,25,25,25,34,36,38,37,33,29,26,25,25,27,28,26,24,23,23,24,30,32,34,32,29,28,30,33,42,47,53,52,45,35,28,24,25,28,30,29,26,26,30,34,43,46,49,47,41,32,25,21,20,22,26,28,29,31,34,37,38,40,39,37,33,34,38,43,48,59,72,79,85,88,85,80,70,61,47,35,29,29,31,32,35,40,50,59,65,66,63,59,54,49,44,43,43,43,40,36,35,37,44,55,64,67,65,61,44,38,31,29,31,33,34,34,32,32,33,37,40,39,33,27,24,23,24,29,34,37,36,33,27,25,23,23,27,31,34,35,39,39,41,46,51,55,57,57,54,52,48,44,44,45,48,50,53,53,52,51,51,50,50,50,50,51,52,51,47,41,35,31,27,27,26,26,26,26,26,26,31,34,38,41,42,39,36,33,30,29,29,32,37,41,42,42,32,30,28,28,32,38,45,50,54,54,53,49,43,39,36,36,35,36,36,34,33,33,35,37,40,40,38,34,29,25,24,24,26,28,30,32,34,37,41,45,47,47,45,42,37,32,27,23,20,20,20,23,26,31,36,39,50,51,52,52,50,46,41,38,34,32,28,25,23,21,21,21,28,33,40,47,49,47,42,39,31,28,25,24,24,24,23,22,22,22,21,21,20,20,20,19,19,19,19,19,18,17,16,15,14,14,13,14,14,15,16,17,20,21,23,25,27,27,27,27,27,27,27,26,24,22,20,18,15,15,14,14,15,18,21,23,20,20,20,20,20,20,20,20,19,18,16,15,14,13,13,13,12,11,10,8,8,7,7,8,7,7,7,6,6,5,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 4,4,4,4,4,4,4,4,4,4,4,5,5,5,6,6,5,5,5,6,6,6,7,7,8,8,8,9,9,9,10,10,8,9,10,11,12,13,12,12,14,14,14,14,14,14,14,14,13,13,13,13,13,14,15,16,18,19,20,21,21,22,22,22,21,20,19,18,16,15,15,15,15,15,15,15,15,16,16,16,17,18,19,22,26,30,34,36,38,36,32,28,25,22,21,21,22,23,24,26,29,32,34,36,36,37,38,37,35,31,27,24,18,17,16,16,17,20,23,24,23,23,24,24,24,24,24,24,21,22,24,24,23,24,26,28,34,37,39,37,33,28,24,22,22,25,30,34,35,34,31,29,24,23,23,22,22,24,26,28,34,37,39,39,34,29,25,23,22,24,27,27,25,23,23,24,27,30,32,31,30,30,35,39,50,57,64,64,55,42,32,26,26,28,30,30,29,31,37,42,53,56,59,58,50,40,31,26,23,25,27,27,27,28,29,31,34,36,37,36,34,35,40,45,50,59,67,72,74,73,66,58,50,43,33,26,24,26,28,29,33,36,43,52,60,62,59,56,44,39,34,33,35,36,35,33,33,37,46,60,72,79,79,76,58,49,38,31,29,31,31,30,31,33,37,44,48,47,40,33,28,26,25,29,34,38,37,35,30,27,25,26,30,35,39,40,45,47,51,57,63,66,65,64,56,52,45,38,35,35,38,40,44,46,47,50,52,54,55,56,56,57,58,58,54,49,43,39,32,31,30,28,28,28,28,29,34,37,42,45,46,43,39,36,32,31,30,32,35,39,40,40,34,33,33,35,41,48,55,59,63,63,62,57,51,45,41,40,38,38,37,36,36,38,43,47,49,49,46,40,32,26,23,22,23,26,29,33,35,39,43,46,48,47,44,40,36,31,26,24,19,19,19,20,24,28,32,35,45,46,48,48,47,44,40,38,35,33,30,27,24,22,21,21,24,29,36,42,44,42,39,36,28,26,24,24,24,24,23,22,21,21,20,20,19,18,18,17,18,19,19,19,19,19,18,17,15,15,15,14,15,15,16,17,20,21,22,24,25,26,27,27,29,30,31,31,30,28,25,24,18,16,14,13,14,16,19,21,17,17,18,18,19,19,19,19,19,18,16,15,14,14,14,14,12,11,10,9,8,8,8,8,7,7,7,6,6,5,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 4,4,4,4,4,4,4,4,3,4,4,4,5,5,5,5,4,5,5,5,6,6,6,6,7,8,8,8,9,9,9,9,8,9,10,11,12,13,12,12,13,13,13,13,13,13,13,13,12,12,12,12,13,14,15,16,19,19,20,21,22,22,21,21,20,19,18,16,15,14,14,14,13,13,13,13,14,16,17,18,20,21,24,28,33,36,39,40,40,37,32,27,24,22,21,21,25,26,27,29,32,34,35,36,35,35,35,35,32,29,25,23,17,16,16,16,16,18,20,21,21,23,25,27,27,27,26,25,21,22,23,22,21,21,23,25,29,31,33,32,28,24,22,21,21,24,28,31,31,30,27,25,22,23,23,22,22,24,28,32,36,39,42,41,37,30,25,22,21,24,27,27,26,25,24,25,28,31,35,35,35,36,41,45,61,68,74,73,62,48,37,31,26,29,32,32,33,36,43,49,58,62,65,63,55,45,36,30,26,27,28,27,26,26,28,30,32,36,38,38,37,37,41,45,49,55,59,60,60,58,49,40,34,29,24,23,27,30,31,31,31,31,33,39,46,50,49,47,37,31,26,25,28,31,31,30,33,37,48,64,80,90,93,92,75,64,50,39,34,31,29,27,32,35,42,50,57,56,48,42,34,31,29,30,34,37,37,35,32,29,27,28,33,39,44,46,53,56,63,71,76,76,73,69,56,50,41,32,28,29,32,35,43,45,48,52,55,58,60,61,61,62,62,62,59,54,49,46,38,36,34,32,31,31,32,32,36,39,43,46,46,43,39,36,33,32,31,32,35,37,38,37,36,36,38,42,48,56,63,67,70,70,68,63,56,49,44,43,39,39,37,37,38,43,50,56,59,58,54,47,37,29,23,21,20,24,29,33,36,39,42,45,45,44,40,36,32,28,25,23,19,18,18,20,23,27,31,33,41,42,44,44,43,41,38,37,35,33,31,27,24,22,21,20,20,24,29,34,36,36,33,32,26,25,24,24,26,26,25,24,22,22,21,19,18,17,16,15,17,18,19,19,20,19,19,18,17,16,16,15,15,16,17,17,19,20,20,21,22,23,24,25,29,30,32,33,33,32,30,28,21,20,17,15,15,16,17,18,15,15,15,16,16,17,17,17,17,16,15,14,14,14,15,15,12,12,10,9,8,8,8,8,7,7,7,6,6,5,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 4,4,4,4,4,4,4,4,3,3,4,4,4,5,5,5,4,4,5,5,5,6,6,6,7,7,8,8,8,9,9,9,8,9,10,11,12,13,12,12,13,13,13,13,13,13,13,13,12,12,12,12,13,14,15,16,18,19,20,21,22,21,20,20,20,19,17,15,13,13,13,14,12,12,12,13,14,16,19,20,23,26,30,35,40,42,43,44,41,37,32,26,23,21,22,22,27,28,30,32,34,35,36,36,32,33,33,32,31,28,25,23,19,19,18,17,17,17,18,19,22,25,28,30,31,29,26,24,21,21,20,18,17,17,19,21,25,27,28,27,24,22,21,21,23,25,28,30,30,28,25,23,22,23,23,22,21,23,28,32,37,40,44,44,38,31,25,22,22,25,27,28,27,26,27,28,31,35,39,41,41,43,47,51,65,72,78,77,67,55,45,40,33,35,37,37,36,37,43,48,58,61,64,62,55,45,37,32,28,29,28,27,25,27,30,33,37,41,45,46,43,42,44,47,47,51,52,50,50,48,40,31,29,27,27,32,40,44,44,41,32,28,26,28,35,40,41,39,35,29,23,22,25,28,29,29,33,38,50,67,85,98,104,105,92,81,65,51,43,36,31,27,33,37,45,55,63,63,57,51,39,35,31,31,34,36,35,33,32,29,27,29,34,41,47,50,60,65,74,82,87,85,78,72,54,48,38,30,26,28,33,37,50,52,55,59,62,64,65,65,67,67,66,64,60,56,52,50,43,41,38,36,34,34,35,36,37,39,42,45,45,42,39,37,34,33,32,33,35,36,35,34,37,38,42,47,53,61,68,72,73,73,72,66,58,50,45,43,38,37,36,35,38,46,55,62,66,65,61,53,42,32,25,22,20,24,29,33,36,37,40,42,41,39,35,31,27,24,22,21,19,18,18,20,23,27,31,33,38,39,40,41,40,38,36,34,34,32,30,27,25,22,20,20,18,20,24,28,29,30,29,28,26,25,25,26,29,30,29,27,25,24,23,21,19,17,16,15,16,17,18,19,19,19,19,19,18,17,17,16,16,16,17,17,18,18,18,18,19,20,21,21,25,27,30,33,34,33,31,30,25,23,21,18,17,16,16,16,13,13,14,14,14,14,15,15,14,14,14,13,14,15,15,16,13,12,11,9,9,8,8,9,7,7,7,6,6,5,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 4,4,4,4,4,4,4,4,3,3,3,4,4,5,5,5,4,4,4,5,5,6,6,6,7,7,7,8,8,9,9,9,8,9,10,11,12,13,12,12,12,12,12,12,12,12,12,12,11,11,11,12,13,14,15,16,18,19,20,21,22,21,20,19,20,18,16,14,13,12,13,13,12,11,11,12,14,17,20,22,25,29,34,40,44,46,46,45,41,37,31,26,22,21,22,23,29,30,32,33,35,36,36,36,30,31,31,31,30,28,25,24,22,21,20,18,18,18,18,18,24,27,31,33,33,30,26,23,20,20,18,15,13,13,16,18,22,24,25,25,22,21,20,21,26,28,30,32,31,29,26,24,24,24,24,22,20,21,27,31,37,41,45,44,39,31,25,21,24,26,28,28,27,27,28,30,33,38,43,46,46,47,51,55,63,69,76,77,70,61,53,50,42,44,44,41,38,37,39,43,56,59,62,60,53,44,36,32,29,29,28,26,26,28,33,36,44,49,53,54,51,49,49,50,46,48,47,45,45,44,37,28,30,31,34,43,53,58,56,53,40,34,27,28,33,39,41,41,37,30,24,21,24,27,28,28,34,39,51,68,88,103,110,112,105,93,77,62,51,42,35,29,34,38,47,58,67,68,62,56,42,37,32,31,33,34,33,31,31,28,26,28,35,42,49,52,65,71,80,90,93,89,80,73,53,46,37,29,27,30,37,42,57,59,62,65,67,68,69,68,71,70,68,64,60,56,52,50,46,44,41,38,36,36,37,38,37,39,41,43,43,41,38,36,34,33,33,34,36,36,34,32,37,39,43,48,55,63,69,73,74,74,73,67,59,50,45,42,36,35,34,34,38,46,57,65,71,69,65,56,45,34,27,24,19,24,29,33,35,36,38,39,37,35,31,27,23,21,20,19,19,19,19,20,23,27,32,34,37,38,38,39,38,36,34,33,32,31,30,27,25,22,20,19,18,19,22,24,26,26,26,26,26,26,26,29,31,33,32,31,27,26,25,22,20,18,16,15,15,16,17,18,19,19,19,19,18,18,17,16,16,17,17,18,18,18,17,17,17,18,18,19,22,24,28,31,33,32,31,30,27,26,24,21,18,16,15,15,12,12,13,13,13,13,13,13,13,13,12,13,13,15,16,17,13,12,11,10,9,9,9,9,7,7,7,6,6,5,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,6,6,6,7,7,8,8,8,10,10,10,11,11,12,12,13,13,12,12,12,11,10,10,10,12,11,11,12,13,16,18,20,18,19,20,21,20,19,18,17,16,16,16,16,15,14,13,12,14,15,15,16,17,21,27,32,36,41,44,45,47,51,50,47,42,38,32,26,22,21,21,22,30,32,35,37,38,37,36,35,31,29,28,29,31,32,32,31,26,24,24,23,19,15,17,23,27,32,37,39,37,33,29,27,20,17,17,18,19,19,20,23,23,24,25,25,24,24,25,26,28,27,26,26,26,25,23,21,22,22,23,23,24,26,28,29,37,41,44,44,40,35,30,28,24,25,26,28,29,30,30,30,36,40,46,50,51,51,52,52,60,64,70,73,72,66,58,52,47,44,41,37,34,33,32,32,44,45,46,46,44,40,35,33,31,28,27,26,25,25,33,43,55,61,67,68,62,54,49,47,44,43,42,41,39,36,34,33,33,37,45,58,70,75,72,66,55,44,32,29,33,39,40,39,35,30,26,26,30,33,31,28,34,39,50,67,85,101,112,117,114,106,92,75,58,46,37,33,30,38,49,61,73,79,73,64,51,45,37,31,29,29,29,29,27,26,26,29,34,41,48,52,67,72,81,89,93,88,76,67,53,38,27,31,35,36,44,56,61,67,74,79,80,78,76,74,73,66,61,58,54,49,49,53,50,54,53,48,45,44,39,34,36,37,37,36,34,32,32,33,31,32,34,35,36,36,35,34,37,40,44,48,51,56,61,65,65,64,62,59,54,49,44,41,35,34,32,33,38,46,54,59,69,69,66,59,47,35,26,21,21,24,27,31,34,35,34,34,31,29,26,23,21,20,21,22,23,23,22,23,25,28,31,34,38,38,39,39,37,34,31,28,30,29,29,28,26,24,22,20,18,19,20,22,23,25,26,27,25,27,31,34,37,39,40,40,40,37,33,28,23,19,16,15,14,15,16,19,21,23,25,25,25,24,22,20,19,20,20,21,22,21,19,18,17,17,17,17,21,23,25,27,29,29,29,28,27,26,25,23,21,18,15,14,12,11,10,9,9,9,9,10,11,12,13,14,15,16,16,16,12,13,13,13,13,12,11,10,8,8,7,6,5,5,4,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,6,6,6,7,7,8,8,8,10,10,10,11,11,11,12,12,11,11,11,10,10,10,9,9,11,11,11,12,14,16,19,20,19,20,20,21,20,19,17,16,15,16,16,16,16,15,14,14,15,16,17,17,19,23,29,34,37,42,45,45,47,50,50,46,40,36,31,26,23,22,23,24,30,31,34,36,37,36,35,34,32,31,30,31,33,34,33,32,30,27,26,25,22,19,22,29,34,38,42,43,40,35,32,30,24,24,25,27,28,29,30,32,29,29,28,26,25,25,27,28,31,30,29,28,27,26,24,23,26,26,26,26,25,25,26,28,32,36,40,41,38,33,28,26,25,26,28,29,31,32,32,32,37,41,46,49,49,49,49,49,54,59,65,69,68,63,56,51,46,43,39,35,31,29,29,29,35,37,39,40,39,37,34,32,31,28,26,26,26,29,39,50,66,72,78,77,69,58,50,47,43,43,43,42,40,38,36,35,40,44,52,66,78,84,82,77,62,52,41,36,40,45,46,44,40,35,30,29,31,33,30,27,30,35,46,63,82,99,111,117,113,106,92,76,61,48,40,36,32,40,51,63,75,82,77,68,59,53,44,36,32,31,30,29,26,26,26,28,32,39,45,49,63,68,76,85,87,82,71,62,50,36,28,32,38,41,50,61,68,72,79,83,85,83,80,78,70,63,57,54,52,49,51,56,56,59,59,55,50,47,41,35,34,34,33,32,30,29,30,31,30,31,33,35,36,35,34,33,32,35,38,41,43,47,52,55,57,57,57,55,52,48,44,41,35,34,32,32,35,41,48,53,63,63,61,54,44,33,25,21,21,23,27,31,34,34,34,34,30,28,25,22,20,20,21,22,25,24,24,24,26,28,30,32,34,35,36,36,35,33,31,29,30,30,29,28,26,24,23,21,19,20,21,22,24,25,27,27,30,32,35,39,42,45,46,46,43,41,37,31,26,21,17,16,15,16,17,20,22,25,27,28,28,27,25,23,22,22,23,23,23,22,21,20,19,19,19,19,20,22,24,25,27,27,26,26,25,25,24,22,20,18,16,15,12,11,10,9,9,9,9,10,11,12,13,14,15,15,15,15,12,12,13,13,12,12,11,10,8,8,7,7,6,5,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,6,6,6,7,7,8,8,8,9,9,10,10,10,11,11,11,10,9,9,9,9,8,8,8,9,10,10,12,14,17,19,21,20,20,20,20,19,18,16,15,15,16,17,17,18,17,17,17,17,18,19,20,22,26,32,36,40,45,47,45,46,49,48,44,36,34,30,26,24,25,26,28,30,31,33,35,36,36,35,34,35,34,34,35,37,38,37,35,36,31,28,27,25,24,28,35,42,45,47,47,43,39,36,35,31,33,37,40,42,44,44,43,38,36,32,29,27,29,31,32,37,36,33,30,28,27,27,27,33,34,33,31,27,25,25,26,29,33,38,40,38,34,29,27,26,27,29,31,33,34,35,35,39,43,46,47,46,45,44,44,46,51,58,64,64,60,54,49,45,41,36,31,27,25,25,25,27,28,31,33,34,34,32,31,32,27,25,25,27,33,47,61,79,85,89,87,75,61,50,44,41,42,43,43,42,40,38,37,44,48,58,71,84,90,90,87,70,60,49,45,46,49,49,48,45,40,34,32,32,32,29,26,27,32,42,58,77,94,106,112,112,105,92,77,62,50,41,37,34,43,54,66,79,87,85,78,69,62,51,42,35,31,29,27,26,25,25,26,30,35,41,44,55,60,68,76,77,72,62,54,45,34,29,35,41,45,55,66,71,74,80,85,87,86,83,81,68,60,53,50,49,50,56,63,66,70,71,65,60,54,45,37,31,30,28,26,26,26,27,27,28,29,32,34,35,35,33,32,28,30,33,34,35,37,41,43,47,48,49,50,49,47,44,42,37,35,32,30,32,36,41,44,53,54,52,47,39,30,24,22,21,23,27,31,33,34,34,33,28,26,23,21,20,21,22,23,27,27,27,27,27,28,28,28,29,30,31,32,32,31,31,30,31,30,30,29,28,26,24,23,20,21,22,24,25,27,28,29,34,36,39,42,46,48,50,51,48,46,41,36,30,24,20,18,16,17,19,21,24,28,30,32,33,32,31,29,27,26,26,26,25,25,23,22,21,21,21,21,20,20,22,22,23,23,22,22,22,22,21,21,20,18,16,15,12,11,10,9,9,9,9,10,11,11,12,14,14,15,14,14,12,12,13,13,12,11,10,10,8,8,7,7,6,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,6,6,6,7,7,8,8,8,9,9,9,9,9,10,10,10,8,8,7,7,7,7,7,7,8,9,10,12,15,17,19,20,21,21,20,19,18,17,16,15,15,16,17,19,19,20,20,20,19,20,22,24,26,30,35,39,43,47,47,44,44,46,44,41,32,30,28,26,26,27,29,30,31,32,34,35,36,36,36,36,39,39,39,41,43,43,41,39,39,33,28,27,27,27,33,40,46,48,50,49,46,43,41,41,42,48,53,56,59,61,58,54,47,42,35,30,30,33,37,39,45,43,39,35,31,29,31,32,41,42,42,38,31,26,25,26,28,33,40,43,42,38,34,32,29,30,32,34,36,38,38,39,42,44,46,46,43,40,39,39,41,46,54,61,63,60,54,50,42,38,32,26,23,22,23,24,26,28,30,32,33,33,32,32,33,28,24,24,27,36,53,69,88,93,96,91,77,61,47,40,38,39,41,42,42,41,39,38,42,47,56,69,81,88,89,88,72,64,54,49,48,49,48,47,46,42,36,32,30,28,25,23,26,31,40,55,73,88,99,104,108,101,88,73,58,46,38,34,34,44,57,71,85,95,95,90,79,71,58,47,38,32,28,25,26,25,24,25,27,31,35,38,46,51,58,64,65,60,53,47,41,35,33,38,43,47,54,62,65,68,73,80,85,86,84,82,70,61,53,50,51,55,64,73,82,86,86,79,71,62,50,39,30,28,25,24,24,25,26,26,26,28,31,33,34,33,32,31,27,29,30,30,30,31,33,36,37,40,43,46,48,48,46,45,42,39,35,31,30,32,34,37,43,44,43,39,33,27,24,23,22,24,28,31,33,33,32,32,25,24,22,20,20,22,24,25,29,30,30,30,29,28,26,24,25,25,26,27,28,29,30,30,31,31,30,30,28,27,25,24,23,24,25,26,28,30,31,31,34,36,39,42,45,48,50,51,51,49,45,39,33,27,22,20,18,18,20,22,26,30,33,35,37,37,35,34,32,31,30,30,28,27,26,25,24,24,24,24,20,20,20,20,19,19,18,18,18,18,19,19,18,18,17,16,12,11,10,9,9,9,9,10,10,11,12,13,13,14,13,13,11,12,12,12,12,11,10,9,8,8,8,7,7,6,6,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,6,6,6,7,7,8,8,8,9,9,9,9,9,8,8,8,6,6,6,6,6,7,7,7,8,9,11,13,15,17,18,19,20,20,19,18,17,16,16,16,16,17,19,20,21,22,22,22,20,22,25,27,29,33,38,42,45,47,46,42,40,41,39,35,28,27,26,25,26,28,30,32,33,34,35,36,37,37,37,37,41,42,44,46,48,48,44,41,38,31,25,25,26,28,34,41,46,47,49,49,48,48,49,51,60,69,76,78,79,79,73,64,52,44,34,29,31,38,44,48,55,52,47,40,34,33,36,39,49,51,51,45,36,29,27,28,30,36,43,47,47,43,39,37,34,35,37,39,40,42,42,42,45,46,47,45,40,37,35,35,39,44,53,60,62,59,54,50,38,35,29,24,22,23,26,29,35,36,36,37,37,36,35,34,35,29,24,24,28,39,58,76,96,99,99,91,76,58,45,39,34,36,39,41,41,40,38,36,39,43,52,62,72,79,82,82,72,65,56,50,48,47,46,44,42,39,34,30,27,24,22,21,24,29,39,54,72,87,96,100,101,93,80,64,50,39,32,29,34,46,62,76,91,102,104,100,89,80,66,53,43,36,31,28,27,26,25,24,25,27,30,31,38,42,48,52,52,49,45,43,40,39,40,44,46,47,50,54,55,58,64,73,81,85,85,83,75,65,57,55,58,64,76,88,101,104,102,93,81,69,54,42,32,29,26,26,28,29,29,27,27,28,29,30,30,30,30,29,26,27,28,28,26,27,29,31,34,37,43,48,51,52,52,51,49,45,40,34,31,30,31,32,34,35,34,31,27,24,24,24,24,26,28,31,32,31,30,29,23,22,21,20,21,23,26,28,32,33,35,35,33,29,25,23,22,22,22,22,24,26,28,29,30,30,30,30,28,27,25,25,25,26,27,29,30,32,33,34,35,36,38,40,43,46,48,50,50,48,45,41,35,30,25,22,19,19,20,22,25,30,34,36,39,38,38,37,35,34,33,32,30,29,28,27,26,26,26,26,22,21,20,18,17,16,16,15,15,16,16,17,17,17,16,15,12,11,10,9,9,9,9,10,10,11,12,12,13,12,12,12,11,11,12,12,11,11,10,9,8,8,8,7,7,7,7,6,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,6,6,6,7,7,8,8,8,9,9,8,8,8,7,7,7,6,6,6,6,7,7,7,7,9,10,12,14,16,17,17,17,19,19,18,17,16,17,17,17,18,19,20,22,23,23,23,23,20,23,26,29,32,35,40,43,45,47,44,38,35,35,33,29,24,24,24,24,25,28,30,32,33,33,34,35,35,36,37,37,41,42,45,48,50,49,45,41,35,27,22,23,26,29,34,40,44,46,48,50,53,57,62,66,81,93,100,99,97,94,84,71,52,43,31,27,32,43,52,58,64,62,55,45,38,36,41,46,55,58,59,53,42,34,32,33,35,41,49,54,54,50,46,43,42,43,44,46,47,48,48,48,48,48,47,44,39,35,33,33,37,42,51,57,59,56,51,47,34,31,26,22,23,28,34,38,45,45,44,43,42,40,39,38,36,30,26,26,31,44,65,83,103,103,99,88,71,54,42,37,33,35,38,40,41,39,37,35,38,42,48,56,63,68,71,72,68,62,55,49,46,44,42,40,35,33,30,26,23,22,21,21,21,27,40,57,74,88,96,99,90,81,67,52,40,31,27,26,36,50,68,83,96,106,107,103,95,86,72,59,49,41,36,33,28,27,25,24,24,25,26,26,31,34,38,40,40,40,41,42,44,47,52,54,53,50,48,48,49,51,57,67,78,84,85,83,76,68,61,62,67,77,92,105,121,122,117,105,90,75,58,45,37,34,32,33,36,37,35,32,30,29,28,27,26,27,27,28,25,26,27,27,26,26,28,30,36,41,47,54,58,59,59,58,54,51,44,38,33,30,29,28,28,29,28,26,24,23,24,26,26,28,30,31,31,29,27,25,22,22,21,21,23,26,29,31,37,39,41,42,40,34,28,24,23,22,20,19,20,23,25,27,29,29,29,29,28,27,25,24,25,26,27,29,30,32,33,34,35,36,36,38,40,42,45,46,45,44,43,40,36,31,27,24,19,19,19,20,24,28,32,35,37,37,37,37,36,35,34,33,31,31,29,28,27,27,27,27,25,23,21,18,16,15,14,14,14,14,15,15,16,15,15,14,12,11,10,9,9,9,9,10,10,10,11,12,12,11,11,10,11,11,11,11,11,10,9,9,8,8,8,8,8,7,7,7,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,6,6,6,7,7,8,8,8,8,8,8,7,7,7,6,6,6,6,6,6,7,7,8,8,10,11,13,15,16,16,15,15,18,17,16,16,16,17,18,19,20,21,22,23,24,24,24,23,20,23,27,30,33,36,41,44,44,45,42,35,31,30,28,23,21,21,22,23,25,27,29,30,31,31,31,32,33,34,35,35,38,40,43,47,49,47,42,38,32,24,20,22,26,29,33,38,44,46,50,54,60,68,77,84,97,109,116,113,107,101,87,70,50,39,27,24,32,47,59,66,72,69,61,50,41,39,45,51,59,63,65,59,47,39,37,38,45,51,60,65,65,61,56,53,51,52,53,54,55,55,54,54,49,49,48,44,38,34,32,32,34,39,47,53,54,51,45,41,31,28,24,22,26,33,42,48,51,50,49,48,46,44,42,41,36,31,27,29,37,51,74,93,108,105,96,80,61,44,35,31,33,36,39,42,42,40,37,35,36,40,45,50,54,57,60,61,59,55,49,44,40,37,34,33,29,28,26,24,22,21,22,23,27,33,46,62,76,86,91,91,78,69,55,41,31,27,27,28,41,56,75,89,100,106,105,100,93,85,72,59,49,42,37,35,29,28,26,25,23,23,23,23,27,29,31,32,32,34,39,43,49,57,65,67,63,57,51,47,44,45,50,61,73,80,81,79,74,67,63,67,77,90,108,122,137,137,129,113,96,78,61,47,43,40,39,42,46,46,42,37,33,31,27,24,22,23,25,27,27,29,30,30,29,30,33,35,42,47,54,61,65,67,66,65,58,54,47,40,33,29,27,26,25,25,25,23,22,22,25,27,29,30,31,31,30,27,24,22,22,21,21,22,24,28,31,34,42,45,48,50,47,41,34,29,25,23,20,18,18,20,23,25,28,28,28,28,27,26,25,24,23,24,25,26,28,29,31,31,32,32,32,32,33,35,37,39,39,39,39,38,35,31,28,26,19,19,18,19,21,25,30,33,34,35,36,36,36,35,34,33,32,31,30,29,28,27,28,28,28,26,23,19,17,15,14,14,13,13,14,14,14,14,13,12,12,11,10,9,9,9,9,10,10,10,11,11,11,10,10,9,10,11,11,11,11,10,9,8,8,8,8,8,8,8,8,8,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,6,6,6,7,7,8,8,8,8,8,8,7,7,6,6,5,6,6,6,7,7,8,8,8,11,12,14,15,16,15,14,14,17,16,15,15,16,17,19,21,21,22,23,24,24,24,24,23,20,23,27,31,33,37,41,44,44,44,40,33,28,27,24,20,20,20,21,22,24,26,28,29,29,29,29,30,30,32,33,34,35,37,41,45,47,45,40,35,31,23,19,22,27,30,33,37,44,47,52,58,66,77,88,95,103,116,123,117,109,102,84,66,47,36,24,22,32,49,63,71,77,73,65,53,43,41,48,55,61,65,68,62,50,42,40,42,54,61,70,75,74,70,65,62,58,59,59,60,60,59,59,58,50,50,48,44,38,34,32,32,32,37,44,49,50,46,40,35,29,26,23,23,28,37,48,54,53,52,51,49,47,45,44,43,35,30,28,32,41,57,80,100,109,104,91,72,51,35,27,24,35,37,41,43,43,41,38,35,35,37,41,44,47,49,51,53,51,48,43,37,33,30,27,26,25,25,24,23,21,22,24,26,36,42,53,66,77,83,83,82,70,62,48,35,27,26,28,31,45,61,79,93,101,105,102,96,89,80,68,56,47,40,36,33,30,29,27,25,23,22,21,21,26,27,28,27,28,32,39,45,53,63,73,76,71,63,55,48,40,41,45,56,67,75,75,73,70,65,63,70,82,98,117,133,146,145,136,118,99,80,62,48,47,45,44,48,53,52,47,41,35,32,26,22,20,21,24,26,31,33,34,35,35,36,39,42,47,51,59,66,70,72,71,70,59,55,48,40,33,29,26,25,24,24,24,22,21,22,25,28,31,31,32,31,29,26,22,20,22,21,21,22,25,29,33,35,46,49,53,55,53,46,38,33,27,24,20,17,17,18,21,23,27,27,27,27,26,25,24,23,21,21,22,24,26,27,28,29,28,27,26,26,27,28,30,31,34,35,36,36,34,31,28,26,19,18,17,17,20,24,28,31,31,32,34,35,36,35,34,33,32,31,30,29,28,28,28,28,30,27,24,20,17,15,14,14,13,13,14,14,14,13,12,11,12,11,10,9,9,9,9,10,9,10,10,11,11,10,9,9,10,11,11,11,11,10,9,8,8,8,8,8,8,8,8,8,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,6,6,7,7,8,8,8,7,7,7,6,6,5,5,5,4,5,6,6,7,8,9,9,10,12,13,14,15,14,13,13,14,15,16,17,19,20,21,22,23,24,24,24,24,23,22,21,22,24,27,31,35,38,40,40,41,38,33,28,24,22,21,21,18,18,19,20,22,23,24,24,28,27,27,27,27,28,29,30,31,32,33,37,39,38,35,32,23,20,18,17,20,27,35,40,44,49,58,65,72,82,93,100,111,115,116,111,102,90,71,56,39,29,23,26,35,48,63,76,79,73,60,46,36,34,41,48,60,64,64,57,46,43,48,56,67,77,86,88,85,81,73,64,60,60,60,63,64,62,56,51,46,45,42,39,36,33,30,29,33,34,36,38,40,37,32,28,23,23,26,29,35,42,48,52,56,53,49,47,46,45,43,41,31,30,30,32,42,61,83,99,108,97,81,63,43,28,25,29,36,45,52,50,47,45,42,39,42,42,43,43,44,44,45,45,46,44,40,35,30,26,23,21,20,22,22,22,21,22,25,27,32,44,58,68,77,82,79,74,65,52,36,26,21,21,29,38,54,68,84,91,94,94,91,86,72,63,53,47,45,43,39,36,31,30,28,26,25,24,25,25,28,30,30,27,25,28,36,43,55,68,79,80,77,72,62,51,43,44,48,56,65,70,70,68,63,62,63,70,84,104,124,136,146,142,132,115,94,74,60,52,45,47,50,54,55,52,46,42,34,30,24,19,18,21,25,29,34,37,40,41,41,42,44,46,54,58,64,69,72,72,70,68,61,56,48,41,36,32,29,26,20,18,18,21,21,21,25,31,35,40,40,34,28,26,22,17,18,19,22,26,30,35,39,41,50,52,57,60,61,56,48,42,29,26,22,18,16,17,19,21,24,25,26,26,25,24,22,20,22,22,22,23,23,24,24,24,22,21,20,20,21,23,25,26,29,31,32,33,33,31,28,26,20,19,17,16,17,19,21,23,28,29,30,32,33,33,33,33,29,29,28,28,27,26,26,25,24,23,22,19,17,15,13,12,12,12,12,11,11,10,10,10,10,10,10,9,9,8,8,8,9,9,9,9,9,9,9,9,10,10,10,9,9,8,8,8,8,8,8,7,7,6,6,6,5,5,5,5,5,5,5,5,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,6,6,7,7,7,8,8,7,7,7,6,6,5,5,5,5,5,6,7,8,8,9,9,10,11,13,14,14,14,13,12,13,14,15,17,19,21,22,23,24,24,24,24,23,23,22,21,23,25,27,31,34,36,37,38,38,35,31,26,23,20,20,20,18,18,19,20,21,22,23,23,24,25,26,27,28,29,29,29,29,29,31,33,35,34,31,28,22,20,17,17,21,27,35,40,45,51,60,67,73,82,91,98,103,106,106,99,90,79,62,48,36,28,23,27,36,47,61,72,71,66,55,41,31,30,36,43,53,57,59,54,46,46,55,63,81,91,98,97,92,84,74,65,62,61,61,62,62,59,53,48,42,41,39,37,34,31,29,27,28,28,29,31,33,31,28,25,23,24,27,31,37,43,48,51,51,49,46,44,43,41,39,36,29,29,28,32,43,61,83,98,103,91,74,56,38,25,25,32,45,55,62,60,55,51,45,40,42,42,43,43,43,43,43,43,43,41,38,34,29,25,22,21,20,22,23,24,24,24,27,29,36,47,60,68,74,77,73,67,56,44,31,24,21,24,33,44,60,73,86,90,89,86,80,74,61,53,45,41,41,41,38,35,34,32,29,26,25,25,26,27,31,32,32,29,26,28,35,42,54,66,76,78,75,70,60,50,45,45,48,54,60,62,61,58,53,54,57,65,81,101,120,131,137,132,120,103,83,64,51,45,44,46,49,53,54,51,44,39,30,26,22,18,19,22,27,31,39,42,44,45,44,44,45,47,55,59,65,70,73,72,69,66,59,54,47,40,35,31,28,25,22,19,19,21,21,21,27,34,37,42,43,38,33,30,25,20,20,21,23,27,31,36,39,42,50,52,56,60,60,56,48,42,32,29,24,19,17,17,18,20,24,25,26,26,26,24,22,21,21,21,21,21,21,22,22,22,20,19,18,18,18,20,22,23,28,29,31,32,31,29,27,25,20,19,17,16,16,18,21,22,27,27,29,30,31,31,31,31,28,28,27,27,26,25,24,24,23,22,21,19,17,15,13,12,12,12,11,11,11,10,10,10,10,10,10,9,9,8,8,8,9,9,9,9,9,9,9,9,10,10,9,9,9,8,8,8,8,8,7,7,7,6,6,6,5,5,5,5,5,5,5,5,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,6,6,6,7,7,7,8,7,7,6,6,6,6,5,5,6,6,6,7,8,8,9,9,10,11,12,13,13,13,13,12,12,13,15,17,19,21,23,24,24,24,23,23,23,22,22,22,24,25,27,29,31,33,33,34,33,30,27,23,20,18,18,18,19,18,18,18,19,20,21,22,21,23,26,29,30,30,30,29,27,27,27,28,30,29,26,23,20,18,17,17,21,28,34,39,45,52,61,68,73,79,87,92,91,94,92,85,78,68,54,42,34,27,23,28,36,45,55,64,62,57,49,37,28,27,32,38,45,49,52,50,48,53,65,76,95,103,108,105,97,88,77,67,64,62,61,60,57,53,47,43,37,36,36,34,32,30,28,26,24,23,23,25,26,26,25,23,24,25,29,33,38,43,47,49,45,43,41,40,39,37,34,31,27,26,26,30,42,61,82,96,96,83,65,47,32,24,28,37,57,68,75,73,65,56,46,38,40,41,41,41,41,40,40,39,39,38,36,33,29,25,22,20,20,22,25,26,27,28,31,33,41,51,62,68,71,72,66,59,45,35,25,21,22,28,40,51,66,78,88,87,81,73,64,56,45,40,35,34,36,38,37,36,37,34,31,28,26,27,29,30,35,35,34,30,27,28,33,39,51,60,69,71,68,63,55,47,47,48,50,53,55,54,50,47,43,45,50,59,74,91,107,117,123,117,104,87,68,52,42,38,41,43,47,50,51,46,39,34,24,22,20,19,21,26,32,36,47,49,50,49,47,46,47,48,54,59,66,71,73,71,67,63,57,52,45,39,35,31,27,24,23,20,18,20,21,22,28,36,39,45,48,45,40,35,29,23,22,23,25,28,32,36,40,42,49,51,53,56,57,52,46,40,32,29,25,20,17,17,17,18,24,24,26,26,26,25,23,22,20,20,20,20,20,19,19,19,18,17,16,15,15,16,17,18,25,26,28,29,29,27,25,23,19,18,16,15,15,17,19,21,24,25,26,27,28,28,28,28,26,26,25,25,24,23,22,22,22,21,19,18,16,14,13,12,12,11,11,11,10,10,10,10,10,10,10,9,9,8,8,8,9,9,9,9,9,9,9,9,10,9,9,9,8,8,8,8,8,7,7,7,6,6,6,6,5,5,5,5,5,5,5,5,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,7,7,7,6,6,6,6,6,6,6,6,6,7,7,8,8,9,9,9,10,10,11,12,12,12,12,12,12,13,15,17,19,21,23,24,23,23,22,22,21,21,21,21,24,25,26,28,29,29,29,29,27,25,23,20,18,17,17,16,19,18,18,17,18,19,20,21,20,23,28,32,35,34,33,31,28,27,25,25,26,25,22,20,18,17,16,18,21,27,33,37,43,49,58,64,67,71,77,81,80,82,82,77,72,66,55,45,35,29,25,29,35,40,47,54,54,51,45,36,29,27,31,36,39,44,48,49,52,62,77,89,102,109,112,106,97,87,76,66,63,61,59,55,51,46,41,38,34,34,34,34,33,31,29,28,26,24,23,23,25,26,26,25,26,28,31,35,39,42,44,45,41,40,39,39,38,36,32,29,25,24,24,29,41,59,78,90,89,76,58,42,29,26,35,47,68,78,86,82,71,58,45,35,36,37,38,38,37,36,34,33,35,35,35,34,31,28,24,22,20,23,26,28,30,32,36,38,46,55,64,68,70,69,62,53,39,30,22,21,24,31,44,56,69,79,85,81,71,61,49,40,33,31,29,31,35,38,39,39,39,36,32,29,28,29,31,33,38,37,35,31,28,28,32,35,44,50,57,59,57,52,47,43,48,50,51,52,51,47,43,39,37,40,45,53,65,79,91,98,108,101,89,73,56,43,36,33,35,37,41,44,45,41,34,28,22,22,21,23,27,33,39,43,54,54,54,51,48,46,46,48,54,58,65,70,72,69,64,61,55,51,45,39,35,31,27,24,24,20,18,19,19,21,28,37,40,47,52,50,45,41,34,27,24,25,27,29,32,36,39,41,45,46,48,50,50,46,40,35,28,26,22,19,17,16,17,18,22,23,25,26,26,26,24,23,21,21,20,20,20,20,19,19,18,17,15,14,13,14,15,16,22,23,25,26,26,25,23,21,19,17,15,14,14,16,18,19,21,22,23,24,24,24,24,24,24,23,23,22,21,20,20,19,19,19,18,16,15,14,13,12,11,11,11,10,10,10,9,9,10,10,10,9,9,8,8,8,9,9,9,9,9,9,9,9,9,9,9,8,8,8,7,7,7,7,7,6,6,6,5,5,5,5,5,5,5,5,5,5,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,6,6,6,7,7,6,6,6,6,6,6,6,6,7,8,8,8,8,9,9,9,10,10,10,10,10,11,12,12,13,13,15,17,19,21,23,23,22,22,20,19,19,19,20,20,23,24,25,25,26,25,25,25,22,22,20,19,18,17,17,16,19,18,17,17,17,19,21,23,23,27,32,37,40,39,37,36,32,29,26,24,24,23,21,19,17,17,17,18,22,26,31,34,37,43,50,54,56,58,63,66,67,71,74,74,73,70,62,53,41,33,28,29,32,34,39,45,47,46,43,37,31,29,32,36,40,44,49,53,59,70,86,97,108,113,112,103,91,81,70,61,59,58,55,51,45,41,37,36,36,37,38,39,38,36,34,32,30,28,26,26,27,29,29,28,29,31,33,36,38,40,40,41,39,39,39,41,41,39,35,31,25,23,22,27,38,54,70,79,80,68,52,39,30,31,43,56,77,87,92,86,73,59,44,32,31,32,33,34,33,31,29,28,32,33,35,35,34,31,27,25,21,23,26,28,31,35,41,45,50,59,67,70,71,69,61,52,39,31,23,22,26,33,45,57,66,74,78,72,61,50,39,31,28,28,29,32,37,40,42,42,39,36,33,30,29,29,31,32,37,36,33,30,28,28,30,32,36,39,42,44,43,40,39,40,46,49,51,51,48,43,38,35,33,36,41,48,58,68,77,82,89,84,75,62,48,38,32,30,30,32,35,39,40,38,32,28,27,27,28,31,36,42,47,51,58,57,55,52,47,45,45,46,52,56,63,68,69,67,63,59,55,52,46,42,38,34,30,27,25,20,18,18,18,20,27,35,39,47,53,52,47,43,36,28,25,26,27,29,31,34,37,38,40,39,40,41,41,38,32,28,21,20,18,16,15,16,17,19,20,22,23,25,26,25,24,24,22,22,22,22,22,22,22,21,21,19,17,15,14,14,14,15,19,21,23,24,24,23,21,20,18,17,15,13,13,14,16,18,19,19,20,21,21,21,21,20,21,20,20,19,18,17,17,16,17,17,16,15,14,13,12,12,11,11,10,10,10,9,9,9,10,10,10,9,9,8,8,8,9,9,9,9,9,9,9,9,9,9,8,8,8,7,7,7,7,7,6,6,6,5,5,5,5,5,5,5,5,5,5,5,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,4,5,5,5,6,6,6,6,5,5,6,6,6,6,7,7,8,8,8,9,9,9,9,9,10,9,9,9,9,10,11,12,14,15,16,17,19,20,21,22,21,20,18,17,16,17,18,19,22,22,23,23,23,23,22,22,20,19,19,19,19,18,18,18,19,18,17,16,18,20,23,25,28,31,36,41,43,43,41,39,35,32,27,24,22,21,20,18,17,17,18,19,22,25,28,30,31,36,41,43,43,44,48,52,55,63,71,75,78,77,70,60,46,37,28,27,28,30,36,42,43,45,45,41,36,34,36,39,46,49,53,58,64,75,89,98,110,112,107,94,81,71,62,54,55,55,52,48,43,39,39,39,43,45,46,47,46,44,41,40,36,34,32,31,32,33,32,31,34,34,34,35,35,35,36,36,38,39,41,45,46,45,40,36,28,24,22,25,34,47,59,66,68,59,46,37,32,34,48,62,82,90,93,84,70,55,41,30,27,28,30,31,31,29,27,25,29,31,34,36,36,33,29,26,21,23,25,27,31,37,45,51,56,65,72,75,74,71,62,53,41,32,25,23,26,32,43,54,61,68,70,62,51,42,34,27,27,29,32,35,38,40,41,42,36,35,33,31,29,29,29,30,34,32,29,27,26,27,28,29,32,30,31,32,32,32,36,42,47,50,53,53,48,42,37,34,34,36,40,46,53,61,67,71,69,67,63,55,45,36,31,29,30,31,33,37,40,40,38,35,37,38,40,43,47,52,56,58,60,59,56,51,46,43,43,44,50,54,59,63,65,64,61,59,58,54,50,46,43,39,35,31,26,22,20,21,20,20,26,33,37,45,51,49,46,42,35,28,25,25,26,27,29,31,33,34,34,33,33,33,32,30,26,22,17,16,15,14,15,16,17,18,18,19,21,23,24,24,24,23,22,22,23,23,24,24,24,25,24,22,20,17,15,14,15,15,17,19,21,23,23,22,20,19,17,16,14,12,12,13,15,16,17,18,19,19,19,19,18,18,18,18,17,16,15,15,14,14,15,14,14,14,13,12,12,12,10,10,10,10,9,9,9,8,10,10,10,9,9,8,8,8,9,9,9,9,9,9,9,9,8,8,8,8,7,7,7,6,6,6,6,6,5,5,5,4,5,5,5,5,5,5,5,5,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,4,4,5,5,5,6,6,6,5,5,5,6,6,7,7,7,9,9,9,9,9,9,9,9,10,9,8,8,8,9,11,12,16,16,17,18,18,19,20,20,19,18,16,14,14,15,16,17,20,20,21,22,22,21,20,20,18,19,19,20,20,20,20,20,18,17,16,16,18,22,26,28,32,35,38,42,44,44,43,41,38,33,27,23,21,20,18,17,18,18,19,20,22,23,25,26,27,30,33,33,32,33,37,41,51,61,73,81,86,86,77,66,49,38,27,24,25,28,36,44,47,50,52,50,46,44,45,48,52,55,58,62,67,76,87,94,99,99,93,80,69,62,57,52,53,53,52,48,43,42,43,46,52,53,55,56,55,53,49,47,45,43,42,41,42,41,39,37,38,37,35,33,32,31,32,32,37,39,43,48,51,50,45,41,31,26,22,23,30,41,49,54,56,48,40,34,31,35,48,62,79,85,85,75,60,46,34,25,25,26,29,31,31,30,28,26,24,27,32,35,36,33,29,26,22,23,23,25,29,38,48,55,64,72,79,79,77,72,62,53,41,32,24,23,25,30,41,51,58,63,63,54,43,36,30,25,27,30,33,36,37,37,38,38,33,32,32,31,30,28,27,26,29,27,25,24,25,26,27,28,33,27,25,26,27,29,38,48,56,60,63,62,55,48,42,39,45,45,45,46,49,52,54,56,56,57,58,55,48,41,35,32,33,34,35,40,44,48,48,48,49,50,52,54,57,61,63,65,61,60,56,51,45,43,43,44,48,51,55,59,61,62,61,60,61,58,54,51,48,44,39,36,30,26,24,25,23,22,26,32,35,42,47,45,42,39,33,27,24,24,24,25,26,28,30,31,31,30,28,28,27,25,21,18,17,17,16,15,15,16,16,17,16,17,19,22,23,23,23,23,21,21,22,23,24,25,26,26,26,24,21,18,16,14,14,14,16,18,20,22,23,22,20,19,17,15,13,11,11,12,13,15,17,17,18,18,18,18,17,16,16,16,15,14,13,13,12,12,13,13,13,12,12,12,12,12,10,10,10,9,9,9,8,8,10,10,10,9,9,8,8,8,9,9,9,9,9,9,9,9,8,8,8,7,7,7,6,6,6,6,6,5,5,5,4,4,5,5,5,5,5,5,5,5,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,4,4,4,5,5,6,6,6,5,5,5,6,6,7,7,7,9,9,9,9,9,9,9,9,9,9,8,7,8,9,10,12,17,17,17,18,18,19,19,19,18,17,14,12,12,13,15,16,19,19,20,20,21,20,20,19,18,18,20,21,21,21,21,21,18,17,16,17,19,23,28,31,34,36,39,42,44,44,43,42,38,34,27,22,20,19,17,16,18,19,19,20,21,22,23,24,25,27,29,28,26,27,31,36,52,64,78,88,94,93,83,71,50,37,25,21,23,28,38,48,53,57,60,59,56,54,54,56,56,58,61,64,68,75,84,90,83,84,79,68,60,57,56,53,52,53,52,49,45,44,47,51,58,59,61,62,61,58,54,52,54,52,51,50,50,49,46,43,41,38,35,31,29,29,29,30,36,38,43,49,53,52,48,44,33,28,22,22,28,37,43,47,47,41,35,32,30,34,47,60,73,78,76,64,49,37,26,18,24,26,29,32,32,31,29,27,21,25,30,34,35,32,28,25,23,22,22,23,28,38,50,58,70,78,83,83,79,73,62,52,39,31,23,22,24,29,39,49,56,60,59,49,38,32,28,24,28,30,34,36,35,34,34,34,30,31,31,31,30,28,25,24,25,24,22,22,24,26,27,27,35,27,23,24,26,30,41,54,67,71,74,71,64,55,49,46,58,56,52,48,46,44,43,43,51,54,58,58,53,47,41,38,38,37,39,43,49,54,57,57,57,58,59,61,64,66,67,68,62,60,57,51,46,43,43,45,47,49,52,56,59,60,61,61,63,60,57,54,51,47,43,39,32,29,28,28,26,24,26,32,33,40,44,42,39,37,32,26,22,22,23,23,24,26,27,28,30,28,26,26,25,23,19,17,20,19,18,16,16,15,15,16,14,16,18,21,22,23,22,22,19,20,21,22,24,25,27,27,26,24,21,18,15,14,13,13,16,18,20,22,23,22,20,19,17,15,13,11,10,11,13,14,16,17,17,18,18,17,16,16,15,14,14,13,12,12,11,11,12,12,12,12,12,12,12,12,10,10,10,9,9,8,8,8,10,10,10,9,9,8,8,8,9,9,9,9,9,9,9,9,8,8,8,7,7,6,6,6,6,6,6,5,5,4,4,4,5,5,5,5,5,5,5,5,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,6,6,6,6,6,6,6,6,8,8,8,8,8,8,8,8,7,7,7,8,9,10,12,13,16,16,17,18,18,18,17,17,13,13,12,11,11,12,12,13,14,14,15,16,17,17,18,18,18,18,19,20,20,20,19,19,18,18,18,19,22,27,32,36,41,42,42,42,41,40,38,36,31,29,26,23,20,19,18,18,16,16,17,18,18,19,20,20,20,23,24,23,21,23,30,37,55,69,84,93,94,88,74,61,42,35,25,21,26,36,47,53,64,65,66,66,64,60,56,54,54,55,58,61,65,68,70,72,71,67,60,54,51,52,54,57,58,55,51,47,46,47,49,51,59,62,65,66,63,60,58,57,58,58,58,58,57,55,51,48,44,36,30,31,31,26,26,30,37,40,45,51,54,52,47,42,35,31,26,25,27,32,35,37,35,32,27,25,29,36,45,51,66,65,61,52,41,30,23,20,21,30,37,39,40,40,34,26,26,26,27,29,32,32,30,28,23,21,20,22,29,41,53,60,72,76,81,83,80,72,62,56,38,32,25,21,24,31,39,43,51,50,48,42,36,30,28,28,27,30,33,33,30,28,29,32,32,36,38,36,34,34,31,25,26,23,20,21,25,31,35,37,34,33,29,26,28,39,54,65,78,86,87,76,66,61,58,55,59,66,68,58,45,39,37,36,42,50,60,66,65,58,50,44,41,41,43,48,54,60,63,64,66,64,63,64,66,68,68,68,62,60,56,52,49,47,47,46,49,49,51,52,54,56,58,58,60,60,59,58,54,50,45,43,36,35,34,33,31,29,28,27,30,31,32,33,32,30,27,25,18,18,19,20,21,23,24,24,21,23,24,24,23,22,23,24,22,21,21,20,19,18,17,17,14,15,17,18,19,20,20,20,21,20,20,20,21,23,26,27,27,26,24,21,19,16,14,13,15,16,17,19,19,20,20,19,16,15,13,11,10,10,10,11,14,15,15,16,16,15,15,14,12,12,12,11,11,10,10,10,13,13,12,11,10,10,10,10,11,11,10,9,8,8,7,6,7,7,7,8,8,9,9,9,10,10,10,10,10,10,10,10,7,7,7,7,7,7,7,7,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,6,6,6,6,6,6,6,6,8,8,8,8,8,8,8,8,7,7,7,8,9,10,12,13,16,16,17,17,17,17,16,16,13,12,12,11,11,11,12,12,13,14,14,15,16,17,17,18,18,18,19,19,19,19,19,18,19,18,18,20,24,29,34,37,42,42,42,42,40,38,35,34,31,29,25,22,20,18,18,18,16,16,17,18,18,19,20,20,18,21,22,21,20,22,29,35,53,66,80,87,88,82,68,56,39,33,26,24,30,40,50,56,66,67,67,65,62,57,52,48,47,48,49,52,55,57,59,60,58,56,52,50,50,52,55,57,58,55,50,45,43,44,46,48,56,58,61,61,58,56,55,55,57,57,58,58,57,55,52,50,48,40,36,37,37,33,32,35,37,39,44,49,53,52,48,44,37,33,28,26,27,30,32,33,33,30,27,25,29,35,43,48,57,55,51,44,35,27,22,20,25,33,41,43,44,42,35,27,25,25,26,29,32,34,32,31,26,25,23,25,31,41,51,58,68,72,77,79,76,69,60,54,38,32,25,22,25,31,38,42,49,49,46,40,34,29,28,28,29,32,35,35,32,31,34,37,40,45,47,46,44,43,38,32,29,26,23,24,28,33,36,38,36,34,31,28,31,43,59,71,84,91,91,80,70,66,65,63,69,76,75,64,49,40,35,32,41,49,60,67,67,60,52,46,45,45,46,50,57,62,66,67,68,65,63,62,63,63,62,61,58,56,53,50,48,47,46,46,48,49,50,51,52,54,54,55,57,57,56,55,52,47,43,41,37,36,35,34,32,31,30,29,29,30,31,32,31,29,27,25,20,19,19,20,21,22,24,25,23,24,25,25,24,24,25,27,26,26,26,24,22,20,18,17,16,17,18,19,19,19,19,19,19,19,18,19,20,22,25,26,26,25,23,21,18,16,14,13,14,15,17,18,19,19,19,19,16,15,13,12,11,11,12,13,14,15,15,16,16,15,15,14,12,12,12,11,11,11,10,10,12,12,11,10,10,10,11,11,11,11,10,10,9,8,7,7,7,7,7,8,8,9,9,9,10,10,10,10,10,10,10,10,7,7,7,7,7,7,7,7,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,6,6,6,6,6,6,6,6,7,7,7,7,7,7,7,7,7,7,7,8,9,10,12,13,15,15,16,16,16,16,15,14,12,11,11,10,10,11,12,12,12,13,13,14,15,16,16,17,18,18,18,18,18,18,18,17,19,19,20,22,25,31,35,38,43,42,41,40,37,34,32,30,29,27,24,21,19,17,17,17,16,16,17,18,18,19,20,20,16,18,20,20,20,22,28,34,50,61,73,78,77,71,59,48,34,31,27,29,36,45,54,58,66,66,64,60,55,48,42,39,37,38,40,42,44,45,47,48,43,44,45,47,50,53,57,58,58,54,48,43,40,40,41,43,50,51,52,52,50,49,50,51,53,54,55,56,55,54,52,51,50,45,43,45,45,42,40,41,38,40,43,47,50,50,47,44,40,36,31,28,28,29,30,30,30,28,27,27,29,34,40,44,45,44,40,34,27,23,21,22,30,38,46,49,48,45,37,28,24,24,26,29,34,36,36,35,32,30,28,29,33,41,49,54,61,65,69,71,69,63,56,51,38,33,26,24,26,32,38,42,48,46,43,37,31,28,28,29,32,35,38,37,35,35,39,43,49,55,59,58,56,54,47,40,35,32,29,30,33,37,40,41,38,36,33,30,34,46,63,75,87,91,90,80,70,67,68,69,78,84,84,73,58,46,37,31,39,46,57,66,67,61,51,44,40,39,40,43,50,56,61,62,67,64,60,58,56,55,53,51,51,50,48,47,46,46,46,46,48,48,48,48,49,49,49,49,51,51,51,49,47,43,40,38,37,37,36,35,34,34,33,32,30,31,32,32,31,30,28,26,23,22,21,20,20,22,25,26,25,26,27,26,25,25,27,29,31,31,32,31,28,25,21,19,20,20,20,20,20,19,18,17,16,16,16,16,18,21,23,25,25,24,22,20,18,16,14,13,13,14,15,17,17,18,18,17,15,14,13,12,11,12,14,14,15,15,16,16,16,16,15,15,12,12,12,12,11,11,11,10,11,10,10,10,10,11,11,12,11,11,10,10,9,8,8,8,7,7,7,8,8,9,9,9,10,10,10,10,10,10,10,10,7,7,7,7,7,7,7,7,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,7,7,7,8,9,10,12,13,14,14,15,15,14,14,13,12,10,10,10,9,10,10,11,12,12,12,13,13,14,15,16,16,18,17,17,16,16,16,16,16,19,19,21,23,27,31,36,38,42,41,39,36,33,30,28,26,27,25,22,19,17,16,16,16,16,16,17,18,18,19,20,20,17,18,20,20,21,23,28,32,45,54,63,65,64,59,49,39,30,29,29,33,40,48,54,57,60,59,56,51,45,37,31,28,29,30,32,34,36,39,40,41,38,40,45,50,55,58,60,61,58,53,46,39,35,34,36,37,41,42,42,40,39,39,41,43,46,48,50,51,50,49,49,50,50,49,49,52,54,52,50,48,44,43,43,44,46,45,43,41,39,36,32,30,30,30,30,29,29,29,28,29,31,35,38,41,40,38,34,28,23,21,22,24,35,43,51,53,52,48,38,29,23,23,25,30,35,39,41,40,38,37,35,34,36,40,45,49,53,56,59,61,60,56,51,48,40,35,29,27,30,35,40,42,47,45,41,35,30,29,31,34,38,41,43,42,40,41,45,49,57,63,68,68,66,62,54,45,41,38,36,36,39,43,45,46,42,40,36,32,33,44,60,71,81,82,80,71,62,60,63,67,79,87,89,81,68,56,45,37,37,43,52,59,61,55,45,37,30,29,29,33,40,47,52,54,59,56,51,48,47,45,42,40,42,42,42,43,43,44,44,45,46,46,45,45,44,43,43,43,44,44,44,43,41,38,36,34,37,37,37,36,36,36,36,35,33,33,34,35,34,33,32,32,29,26,23,20,20,23,26,28,26,27,28,27,25,25,26,28,32,33,35,35,34,30,26,24,23,23,23,22,20,19,17,16,13,13,13,14,16,19,22,23,23,22,21,19,17,16,14,14,12,13,14,15,16,17,16,16,13,13,11,11,11,12,13,15,15,15,16,17,17,16,15,15,13,13,12,12,12,11,11,11,9,9,9,9,10,11,12,13,11,11,11,10,10,9,9,8,7,7,7,8,8,9,9,9,9,9,9,9,9,9,9,9,7,7,7,7,7,7,7,7,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,7,7,7,8,9,10,12,13,13,13,13,13,13,12,11,10,9,9,8,9,9,10,11,12,12,12,13,13,14,15,16,16,18,17,16,14,14,14,15,15,19,19,21,23,26,30,33,35,37,36,34,31,28,26,24,23,25,23,20,18,16,15,15,15,16,16,17,18,18,19,20,20,19,20,21,22,23,25,28,31,38,46,52,52,51,48,40,32,29,28,30,34,41,47,50,51,48,47,44,40,34,28,23,20,22,24,26,29,32,36,38,39,42,45,52,58,62,64,64,64,56,50,42,34,30,29,30,32,34,34,33,31,29,29,32,35,37,40,42,43,41,41,43,45,50,52,56,61,64,65,61,57,51,48,44,42,41,40,38,36,36,34,31,31,32,32,32,31,30,30,30,32,33,36,38,39,39,37,34,28,24,23,26,28,38,46,53,54,52,48,39,30,23,23,25,30,37,42,44,45,43,42,40,39,39,40,42,43,45,46,49,51,51,50,47,45,42,38,33,31,33,38,41,43,46,43,39,33,30,32,36,41,49,51,54,52,50,49,52,56,63,70,75,74,72,67,58,49,44,42,40,41,44,47,49,49,46,43,38,32,31,37,50,60,70,70,67,60,52,49,54,61,78,87,93,88,78,66,53,42,37,40,45,49,50,45,36,29,24,24,24,28,35,42,46,48,46,43,39,37,36,35,33,31,34,35,37,38,40,41,42,42,43,43,42,40,39,38,37,36,38,38,37,36,35,33,32,31,35,36,36,36,36,37,37,37,36,37,38,39,39,40,40,40,35,31,26,22,21,24,28,31,30,32,32,30,27,25,25,25,28,30,33,35,36,34,31,30,26,26,25,24,21,19,17,15,12,12,12,13,14,17,19,21,21,21,20,18,17,16,15,14,12,13,14,15,16,16,16,16,12,12,10,10,10,11,13,14,15,16,17,17,17,17,16,15,13,13,13,12,12,12,11,11,9,9,9,9,9,10,11,12,11,11,11,10,10,10,10,9,7,7,7,8,8,9,9,9,9,9,9,9,9,9,9,9,7,7,7,7,7,7,7,7,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,6,6,6,6,6,6,6,6,5,5,5,5,5,5,5,5,7,7,7,8,9,10,12,13,12,12,12,12,11,10,9,8,8,8,7,8,8,10,11,11,12,13,13,14,15,16,16,17,18,17,15,13,12,12,13,14,18,19,20,22,24,27,29,31,31,30,28,26,24,23,22,22,23,21,18,16,14,13,14,14,16,16,17,18,18,19,20,20,21,21,22,22,23,25,27,28,31,37,41,40,40,39,35,28,30,30,31,34,38,41,41,41,36,35,33,31,28,25,23,21,20,22,24,28,31,35,38,39,48,52,58,63,66,67,66,64,53,47,38,30,25,24,26,28,29,30,29,26,24,23,25,27,29,33,35,35,33,32,35,39,48,55,62,68,74,76,72,66,56,51,44,39,36,35,34,33,33,32,31,32,34,34,33,32,31,31,31,32,34,35,37,38,39,37,35,31,27,27,30,32,40,47,52,52,50,47,39,31,24,24,26,31,38,44,47,48,46,45,44,42,41,39,39,39,37,39,41,43,44,44,44,44,42,39,35,34,36,39,41,42,43,40,35,31,29,34,41,47,59,62,65,63,59,57,58,60,65,71,76,75,72,67,58,49,43,42,41,42,45,49,50,50,48,45,39,32,28,30,39,46,60,58,56,51,44,41,46,55,74,84,93,92,84,73,58,46,40,38,38,39,40,38,31,25,22,21,22,25,30,34,36,36,34,32,29,27,27,27,25,24,28,29,32,34,37,38,39,39,40,39,38,36,35,33,32,31,33,32,32,31,30,30,29,29,32,33,34,34,35,36,37,37,38,39,40,42,44,46,47,48,42,37,29,24,22,26,31,35,39,41,42,39,34,29,25,24,24,26,29,32,34,34,34,33,28,28,27,25,22,20,17,16,13,12,12,12,13,15,17,19,19,19,18,17,16,15,15,14,12,13,14,15,16,16,16,16,14,13,11,10,10,11,12,13,16,16,17,17,17,17,16,16,14,13,13,13,12,12,12,12,10,9,9,8,9,9,10,11,11,11,11,11,11,10,10,10,7,7,7,8,8,9,9,9,8,8,8,8,8,8,8,8,7,7,7,7,7,7,7,7,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,7,7,7,8,9,10,12,13,11,11,11,11,10,9,7,6,7,7,7,7,8,9,10,11,13,14,14,15,16,17,17,18,18,16,14,12,11,11,12,13,17,18,19,20,22,24,25,26,25,24,22,21,20,20,21,21,21,20,17,15,13,13,13,13,16,16,17,18,18,19,20,20,22,21,21,21,23,23,23,23,24,29,32,32,32,34,32,27,33,32,31,32,33,33,32,30,26,27,27,28,28,28,28,28,26,27,30,32,36,38,41,42,50,54,59,63,66,65,64,62,51,45,35,27,22,21,24,26,29,29,29,26,23,21,22,23,24,28,31,30,26,26,30,34,42,52,62,69,77,81,77,69,58,52,43,36,34,33,34,34,33,32,32,33,35,35,33,31,31,31,30,31,32,33,35,36,35,35,34,31,30,30,33,36,39,45,49,48,47,45,39,32,25,25,27,32,39,45,49,50,47,47,46,44,42,39,36,35,32,33,35,37,39,40,42,43,41,38,34,33,35,38,40,40,39,36,31,27,28,34,44,52,63,67,70,68,62,57,55,56,60,66,69,67,64,60,51,43,39,38,37,39,43,47,48,48,47,45,40,32,26,26,31,37,51,48,46,44,38,33,39,49,63,76,88,93,90,81,66,53,43,38,33,32,34,35,33,30,27,27,27,28,30,30,28,26,28,26,23,22,22,21,20,18,23,25,28,31,34,36,36,36,36,36,35,33,32,30,29,28,29,29,28,28,27,28,28,28,29,30,31,32,34,35,36,37,39,39,41,44,47,50,52,54,47,41,33,26,24,27,33,38,51,53,54,52,45,36,29,25,21,22,25,27,30,32,32,33,29,29,27,26,23,21,18,17,14,14,13,12,13,14,16,17,18,18,17,17,16,15,15,15,13,13,15,16,17,17,17,17,17,16,14,13,12,12,13,14,16,17,17,18,18,17,17,16,14,14,13,13,13,12,12,12,11,10,9,8,8,8,9,9,11,11,11,11,11,11,11,11,7,7,7,8,8,9,9,9,8,8,8,8,8,8,8,8,7,7,7,7,7,7,7,7,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,5,5,5,6,6,6,6,6,6,6,6,4,4,4,4,4,4,4,4,7,7,7,8,9,10,12,13,10,11,11,10,9,8,6,6,6,6,6,7,8,9,10,11,14,14,15,16,17,17,18,18,18,16,13,11,10,10,12,13,17,17,18,19,20,21,22,22,21,20,19,18,18,19,20,21,20,19,16,14,12,12,12,13,16,16,17,18,18,19,20,20,22,21,20,20,21,22,21,20,21,25,28,27,28,31,31,27,35,33,31,30,30,28,25,23,22,23,25,27,30,32,34,35,34,35,37,39,41,43,44,45,49,52,57,61,63,63,61,59,49,43,33,25,20,20,22,25,30,30,30,28,24,21,21,22,22,26,29,27,23,23,27,31,35,46,58,66,75,80,76,67,57,51,41,35,32,33,34,35,34,33,33,34,35,34,32,29,30,30,29,29,30,31,34,35,30,31,32,31,31,32,35,37,39,44,47,46,44,43,38,32,26,26,27,32,39,46,50,51,48,48,47,45,42,39,35,33,30,30,32,33,36,39,41,42,39,36,33,32,34,37,38,38,36,33,28,25,26,34,45,53,61,65,69,67,60,53,50,49,53,59,61,59,55,51,43,35,35,34,34,37,41,45,46,46,46,45,40,33,26,24,28,33,44,41,40,39,33,27,33,44,52,67,83,92,93,87,74,62,46,39,31,29,33,36,37,35,39,39,38,38,37,35,30,26,26,24,21,19,19,19,17,15,21,23,26,30,32,34,35,35,34,34,33,31,30,28,27,27,27,27,26,26,26,26,27,28,27,28,29,31,33,34,35,36,38,39,41,44,48,52,55,57,50,44,34,27,25,28,35,40,59,62,64,61,52,42,33,28,20,21,22,24,27,29,30,31,29,29,28,26,24,21,19,17,16,15,13,12,12,13,15,16,17,17,17,16,16,15,15,15,13,14,15,16,17,18,18,17,20,19,17,15,14,14,15,15,16,17,17,18,18,17,17,16,14,14,14,13,13,12,12,12,11,11,10,8,8,8,8,8,11,11,11,11,11,11,11,11,7,7,7,8,8,9,9,9,8,8,8,8,8,8,8,8,7,7,7,7,7,7,7,7,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,4,4,4,5,5,6,6,6,6,7,8,9,10,11,11,11,8,8,8,7,7,6,6,6,8,8,9,10,10,11,12,12,13,13,13,14,14,15,15,15,14,13,12,11,11,11,11,12,14,14,15,15,15,14,14,13,12,14,16,19,20,21,21,20,21,19,16,13,12,12,13,14,15,17,19,19,18,18,19,20,21,21,20,20,20,21,21,22,20,22,25,28,30,31,31,31,30,29,28,26,25,24,23,23,23,25,30,35,39,42,44,45,45,45,44,43,42,40,40,39,41,44,48,52,54,55,55,55,49,43,33,25,20,20,23,25,33,34,34,30,24,20,21,23,23,26,28,28,26,25,24,25,31,39,51,62,68,69,66,63,48,44,38,34,33,32,32,31,35,35,36,38,40,39,36,33,31,30,28,27,27,28,29,30,26,28,29,30,30,31,33,36,38,39,40,41,39,36,34,32,24,27,32,38,42,44,45,45,44,43,40,38,35,32,30,29,26,28,31,33,35,36,36,36,34,32,29,29,32,34,36,36,33,28,23,20,23,30,39,46,57,60,61,57,50,43,40,40,41,46,49,47,45,43,38,31,26,27,28,31,34,38,41,42,45,43,39,33,28,25,25,26,35,40,45,43,37,31,30,31,50,59,74,87,91,85,73,63,51,41,32,31,34,40,49,58,55,56,56,53,47,38,30,25,21,20,18,17,16,16,17,18,17,19,23,27,30,31,30,30,29,30,30,30,30,29,28,27,27,26,25,24,24,24,26,27,29,29,30,31,33,34,35,35,37,37,39,41,44,48,50,52,48,43,35,27,24,28,35,42,58,67,73,71,64,55,43,33,21,19,18,18,20,23,24,23,27,27,27,27,26,24,22,20,19,17,15,12,11,11,12,13,15,15,16,17,17,17,16,16,18,17,17,17,18,20,22,24,22,22,21,19,18,16,15,15,15,15,16,17,17,16,16,15,14,13,13,12,12,13,14,14,11,11,11,10,10,9,9,9,10,10,10,10,10,10,10,10,10,11,11,11,11,10,9,8,7,7,7,7,7,7,7,7,7,8,8,9,9,8,8,7,5,6,6,6,6,5,4,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,4,4,4,5,5,6,6,6,6,7,8,9,10,10,10,10,8,8,8,7,7,6,6,6,8,8,9,10,10,11,12,12,13,13,13,14,14,14,15,15,14,13,12,11,11,11,11,12,13,13,14,14,14,13,13,13,12,14,17,19,21,22,22,22,21,19,16,13,12,12,13,14,17,18,20,20,19,18,19,20,20,21,21,21,22,22,23,23,22,23,25,27,28,29,29,29,29,28,26,25,24,24,25,25,31,33,37,41,45,48,50,51,49,48,46,44,41,39,37,36,37,39,43,48,51,53,53,53,49,43,33,25,21,22,26,29,37,39,39,35,29,24,24,25,25,28,31,32,30,27,25,25,30,37,47,56,61,61,57,54,45,41,37,35,35,36,36,35,39,38,39,41,42,41,38,35,30,29,27,26,26,27,29,30,26,27,28,27,26,27,30,32,35,36,38,38,37,35,33,31,25,28,32,36,39,42,42,43,40,39,37,34,32,32,31,31,30,31,34,36,36,36,35,34,31,29,28,29,32,35,37,37,34,29,23,20,21,28,36,42,51,53,55,51,44,38,36,37,37,43,47,47,45,43,37,29,26,26,27,28,30,33,36,38,43,42,40,35,30,28,28,29,37,42,47,46,40,34,32,32,39,49,64,79,87,85,76,68,55,45,37,36,41,48,59,68,73,72,69,62,53,41,31,24,21,20,18,17,17,17,18,18,17,20,24,28,30,31,31,30,29,29,30,30,29,28,27,27,26,26,25,24,24,25,27,28,28,28,29,31,33,34,36,37,38,38,38,39,41,44,46,48,47,43,35,28,24,27,34,40,57,67,75,74,68,59,47,37,25,22,19,18,19,20,20,20,23,24,26,27,27,26,24,23,21,19,16,14,12,12,13,13,16,16,17,18,18,17,17,16,17,16,16,16,18,20,23,24,24,24,24,23,21,19,17,16,16,16,17,17,17,16,15,15,13,13,12,12,12,13,13,14,11,11,11,10,10,9,9,9,10,10,10,10,10,10,10,10,10,10,11,11,10,10,9,8,7,7,7,7,7,7,7,7,7,8,8,9,9,8,8,7,5,6,6,6,6,5,4,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,4,4,4,5,5,6,6,6,6,7,8,9,10,10,10,10,8,8,7,7,7,7,6,6,8,8,9,10,10,11,12,12,13,13,13,13,14,14,14,15,13,13,12,11,11,11,11,11,11,12,12,12,12,12,12,12,13,14,17,20,23,24,24,24,20,18,16,13,12,12,14,15,18,19,20,20,18,17,18,19,20,21,22,24,25,25,26,26,25,25,26,26,26,26,26,26,26,25,24,24,25,26,28,29,39,40,42,46,49,52,54,55,52,50,47,43,39,35,32,31,29,32,37,42,47,51,53,54,51,44,35,26,23,25,30,34,42,44,44,39,32,27,25,26,28,31,35,37,34,29,26,24,28,33,41,48,51,50,46,44,41,39,38,39,41,43,43,42,44,43,43,44,45,44,41,39,30,29,26,25,25,27,29,31,31,31,30,28,26,25,27,29,31,32,33,34,34,33,32,31,27,28,31,33,36,37,38,38,35,33,31,29,30,32,34,36,37,39,40,40,39,37,34,33,28,27,27,30,34,37,39,39,36,31,24,19,19,24,31,36,42,45,46,43,37,32,32,33,34,42,48,50,49,46,38,29,28,27,25,25,26,28,31,33,38,39,39,37,33,31,31,32,38,44,50,51,46,39,35,33,32,40,55,69,79,80,74,69,56,47,40,42,48,57,69,80,88,85,79,70,57,44,32,25,21,20,19,18,18,18,18,19,19,21,25,28,31,32,31,31,28,28,29,29,29,28,27,26,25,24,24,24,25,26,27,28,27,27,28,30,32,35,37,39,39,38,36,35,35,37,39,41,44,41,34,28,24,26,31,35,52,63,74,76,72,65,53,43,33,28,23,19,17,17,17,16,18,20,23,27,28,29,28,27,24,22,20,17,15,14,15,15,17,17,18,18,18,18,17,17,15,15,15,16,17,20,23,24,27,28,28,28,27,24,21,19,17,17,17,17,17,16,14,14,13,13,12,11,11,12,12,13,11,11,10,10,10,10,9,9,10,10,10,10,10,10,10,10,10,10,11,11,10,9,8,8,7,7,7,7,7,7,7,7,7,7,8,8,8,8,7,7,5,6,6,6,6,5,4,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,6,7,8,9,9,9,9,9,7,7,7,7,7,7,7,7,8,8,9,10,10,11,12,12,12,12,13,13,13,14,14,14,13,12,11,11,10,10,11,11,10,10,10,10,10,10,11,12,13,15,18,21,24,25,25,25,20,18,15,13,12,13,14,15,18,19,19,18,16,15,17,18,21,23,25,28,29,30,29,29,28,27,26,24,23,23,23,23,21,21,22,24,27,31,34,36,41,42,42,44,47,50,52,54,52,50,46,41,35,30,26,24,22,25,31,38,46,52,56,58,55,48,38,29,26,28,34,38,44,46,45,40,32,26,25,25,30,35,40,41,37,31,25,22,25,29,35,40,42,42,39,37,40,40,41,45,49,52,52,51,49,48,47,47,48,47,44,42,32,30,27,25,26,29,34,36,39,39,37,33,29,26,27,28,26,27,29,30,31,31,31,30,28,29,29,30,31,32,33,34,31,29,27,26,29,34,39,43,48,48,49,47,44,40,35,32,28,28,29,33,38,42,43,42,38,33,25,19,18,21,27,31,36,38,39,37,32,29,31,33,38,47,55,58,57,53,43,33,30,29,26,24,24,26,28,29,33,35,36,36,33,32,32,32,40,46,53,55,51,45,38,35,33,39,50,61,69,70,66,62,55,46,41,44,52,62,74,84,90,86,79,68,56,42,32,25,20,20,20,19,19,19,19,20,20,23,26,30,32,33,32,31,28,28,29,29,28,27,26,26,22,22,23,23,24,25,25,26,25,25,26,28,31,35,38,40,41,38,35,32,30,31,32,33,38,36,32,26,23,23,26,29,42,54,67,72,71,67,59,50,41,35,28,22,19,17,16,15,14,16,21,26,29,31,32,32,28,26,24,21,19,17,17,17,17,17,18,18,18,17,16,16,14,14,14,15,17,20,22,24,29,30,32,33,31,28,24,22,20,19,19,19,17,16,14,13,13,12,11,11,10,11,11,11,10,10,10,10,10,10,10,10,9,9,9,9,9,9,9,9,9,10,10,10,10,9,8,7,6,6,6,6,6,6,6,6,6,7,8,8,8,8,7,6,5,6,6,6,6,5,4,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,6,7,8,8,9,9,8,8,7,7,7,7,7,7,7,7,8,8,9,10,10,11,12,12,12,12,12,13,13,13,14,14,13,12,11,10,10,10,10,11,9,9,8,8,9,10,11,12,14,16,19,22,24,25,25,25,19,18,15,13,12,13,15,16,16,17,17,16,14,14,16,18,24,27,30,33,35,34,33,32,30,28,25,22,20,20,20,21,18,20,23,27,32,37,41,43,41,40,40,40,42,44,47,49,48,46,42,37,31,26,22,19,17,21,28,37,46,54,60,63,59,52,42,34,30,32,37,40,47,48,46,40,32,27,26,28,34,39,43,44,40,32,26,22,23,26,30,35,37,38,38,37,42,43,47,52,57,60,59,57,53,51,49,49,49,48,45,43,34,32,29,27,29,34,40,44,48,47,45,40,33,28,26,26,24,25,26,28,29,30,30,31,30,29,28,27,27,28,30,31,29,27,26,27,32,39,47,51,59,59,59,56,52,45,39,35,32,32,35,39,44,47,47,46,39,34,27,21,19,21,26,29,34,36,37,34,31,31,34,38,47,56,65,68,66,61,49,39,32,31,28,27,26,27,28,29,29,31,33,32,31,29,30,30,39,45,53,57,55,49,42,38,37,40,46,53,59,61,59,56,53,46,41,45,53,62,72,81,85,80,73,62,49,38,28,23,20,20,20,21,21,21,21,20,22,24,28,31,33,33,33,32,28,29,29,29,29,28,27,26,20,21,21,22,23,23,23,23,23,23,24,26,29,33,37,39,41,39,35,31,28,26,26,26,30,29,28,24,21,20,22,24,30,42,54,61,64,64,59,53,46,41,33,27,23,20,17,16,12,14,19,24,28,32,35,36,32,31,29,26,23,21,19,19,17,17,18,18,17,16,15,14,14,14,13,14,16,18,21,23,29,30,33,34,33,31,27,25,23,23,22,21,19,16,14,13,13,12,11,10,10,9,10,10,10,10,10,10,10,10,10,10,9,9,9,9,9,9,9,9,9,9,10,10,9,9,8,7,6,6,6,6,6,6,6,6,6,6,7,8,8,7,6,6,5,6,6,6,6,5,4,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,5,5,6,6,6,6,7,8,8,8,8,7,7,6,6,7,7,7,7,8,8,8,8,9,10,10,11,12,12,11,12,12,12,13,13,13,13,12,12,11,10,9,9,10,10,9,8,8,7,8,10,12,13,15,17,19,22,23,24,24,23,19,17,15,13,12,13,15,16,16,16,16,15,14,15,18,20,28,31,36,39,40,39,36,34,32,29,24,20,18,17,19,20,20,23,28,34,39,42,44,45,40,39,36,35,36,38,42,44,43,41,38,33,28,24,20,19,18,21,28,36,45,54,60,64,59,54,46,39,36,37,41,44,52,51,48,41,33,29,30,33,40,44,48,48,42,35,28,24,23,25,28,32,35,37,38,38,45,47,52,58,63,64,62,59,54,52,49,48,48,46,44,42,35,33,30,29,32,39,47,53,56,56,54,49,40,32,27,25,24,25,26,27,28,30,31,31,31,29,27,25,25,26,28,29,29,29,29,32,38,46,55,60,70,70,69,66,60,52,44,39,37,38,40,45,49,51,49,47,40,35,29,23,21,23,27,30,34,36,37,35,33,34,39,44,55,64,72,73,70,63,51,40,32,31,31,30,29,30,30,30,28,29,30,29,27,26,27,28,38,43,50,56,56,52,46,41,38,39,41,46,51,54,54,53,52,45,42,46,52,58,65,72,75,71,63,52,41,31,23,19,19,20,21,22,22,22,22,21,24,26,29,32,34,34,33,33,29,30,30,30,30,29,28,27,21,21,22,23,23,22,21,21,22,22,22,23,26,30,35,37,42,40,36,32,28,24,22,21,23,24,25,24,21,20,20,21,22,32,42,47,51,55,55,52,47,43,36,31,27,24,20,17,13,15,17,21,26,32,36,39,36,35,33,30,27,24,22,20,19,19,19,19,18,17,16,15,14,14,13,14,15,17,19,20,27,28,30,32,32,31,29,28,27,26,25,23,20,17,15,13,12,12,11,9,9,8,9,9,9,9,10,10,10,10,11,11,8,8,8,8,8,8,8,8,9,9,9,9,9,8,7,7,5,5,5,5,5,5,5,5,6,6,7,7,7,7,6,6,5,6,6,6,6,5,4,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,5,5,6,6,6,6,7,8,8,8,7,7,6,6,6,6,7,7,8,8,8,8,8,9,10,10,11,12,12,11,11,12,12,12,13,13,13,12,11,10,10,9,9,10,10,10,9,8,7,8,10,13,14,16,18,20,22,22,22,22,21,18,17,14,13,12,13,15,17,16,17,17,16,16,18,21,24,33,36,41,44,45,42,38,36,32,29,23,18,16,16,18,19,25,29,35,41,44,45,44,42,37,34,31,28,28,31,35,37,38,37,34,31,28,25,22,21,22,25,30,36,44,51,57,60,56,52,47,42,41,43,46,49,52,51,46,37,30,28,31,35,48,51,53,52,46,38,31,28,26,27,28,30,33,35,36,37,47,50,55,61,65,65,61,57,53,51,48,46,45,44,42,40,35,32,29,29,34,43,52,59,67,68,67,61,52,41,33,29,26,26,27,27,28,30,31,32,32,29,26,24,23,25,28,29,31,32,34,38,45,54,62,67,79,79,78,74,67,58,49,44,41,42,45,49,52,52,49,46,40,36,30,26,24,26,30,33,35,37,37,36,35,38,44,50,58,66,73,73,68,60,47,36,29,30,31,32,33,32,31,31,30,30,29,27,24,23,25,26,36,41,47,53,56,54,48,44,40,39,38,39,43,46,48,48,48,42,40,43,47,49,52,56,57,54,47,39,32,25,21,18,19,20,22,23,23,23,22,22,25,27,30,33,35,35,34,33,31,31,31,31,31,30,29,28,24,24,25,25,24,23,21,20,21,20,20,21,23,28,32,35,41,40,38,34,29,24,20,17,19,21,24,25,23,22,21,21,21,28,34,35,38,44,47,47,44,41,37,33,30,27,22,19,16,16,17,19,24,30,37,40,39,38,36,33,30,26,23,22,21,22,22,21,20,19,18,17,16,15,14,13,14,15,17,18,24,25,27,28,30,30,30,30,30,29,28,25,22,19,16,14,12,11,10,9,8,8,8,8,9,9,9,10,10,11,11,11,8,8,8,8,8,8,8,8,8,9,9,9,9,8,7,6,5,5,5,5,5,5,5,5,5,6,6,7,7,6,6,5,5,6,6,6,6,5,4,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,5,5,6,6,6,7,7,8,8,8,7,6,6,6,6,6,7,7,8,8,8,8,8,9,10,10,11,12,12,11,11,11,12,12,13,13,13,12,11,10,9,9,9,9,10,10,9,8,7,8,10,13,15,17,18,20,21,22,21,20,19,18,17,14,13,12,14,15,17,17,18,18,18,18,20,24,28,35,39,44,47,47,44,40,36,32,28,22,17,15,15,18,19,31,35,40,45,47,45,42,39,32,29,25,22,22,25,28,31,36,35,33,31,29,26,25,24,26,28,31,36,42,48,53,56,52,50,46,44,44,47,50,53,50,48,42,33,26,24,29,34,53,55,57,54,48,40,34,31,28,28,29,30,31,33,35,36,48,51,56,62,65,64,58,54,53,50,46,44,44,42,40,38,33,31,28,28,34,44,55,61,77,78,78,72,62,50,40,35,28,27,27,28,29,30,31,32,32,30,26,23,23,25,28,30,33,34,37,42,49,58,66,71,83,83,82,78,71,62,52,47,43,44,47,50,53,52,48,44,40,37,31,27,26,29,33,36,36,37,38,37,36,40,47,53,58,66,71,70,64,56,42,31,26,28,31,33,34,34,32,31,33,32,30,26,23,22,24,26,35,39,45,51,55,54,50,46,44,41,37,36,37,40,41,41,43,37,35,39,41,40,41,43,39,37,33,29,25,22,21,20,19,20,22,23,24,24,23,22,26,28,31,34,35,35,34,33,31,32,32,32,32,31,30,29,27,27,28,27,26,24,22,20,21,20,19,19,22,26,30,33,41,41,39,36,31,25,19,16,17,21,25,26,25,24,22,22,23,28,30,29,31,37,42,43,40,38,36,34,32,28,23,19,19,17,17,18,22,29,37,41,41,40,38,35,31,28,24,22,24,24,24,24,23,21,20,19,16,16,14,13,13,14,16,17,22,23,24,26,28,29,31,32,32,31,29,27,23,20,17,15,12,11,10,9,8,7,7,7,9,9,9,10,10,11,11,11,8,8,8,8,8,8,8,8,8,9,9,9,9,8,7,6,5,5,5,5,5,5,5,5,5,6,6,7,7,6,6,5,5,6,6,6,6,5,4,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,4,5,6,6,7,8,5,5,5,5,5,5,5,5,6,6,6,7,7,8,8,8,8,8,8,8,8,8,8,8,9,10,12,13,14,14,13,12,12,12,12,11,11,10,10,10,7,7,7,8,10,12,14,15,17,18,20,22,21,20,18,16,15,15,15,15,15,15,15,15,20,19,18,18,20,24,29,31,40,43,47,50,50,46,41,37,29,25,19,15,14,17,22,26,37,42,48,52,52,48,42,38,27,23,18,16,19,24,28,31,35,35,35,34,33,32,31,30,30,31,32,35,38,42,45,47,48,47,45,47,50,53,54,54,52,43,33,27,23,24,33,43,53,60,64,58,50,44,38,33,33,33,32,31,31,31,32,32,42,47,53,57,57,55,53,52,49,45,42,40,40,39,35,32,27,26,24,24,30,41,55,64,82,83,83,77,66,52,41,35,30,29,29,30,31,32,33,34,30,26,22,18,18,22,26,29,37,39,42,45,50,57,65,70,78,80,80,76,67,58,50,46,40,43,46,49,49,45,41,38,32,30,29,30,33,36,37,38,37,37,37,37,39,41,44,45,60,62,64,63,57,48,38,31,25,24,26,31,36,39,38,36,38,39,39,34,28,24,25,27,32,35,40,46,50,50,47,45,44,43,41,40,38,37,37,36,39,38,37,37,37,35,31,28,28,27,26,25,23,22,21,20,23,22,21,20,20,21,23,24,28,30,33,36,37,38,37,36,33,33,34,35,36,36,35,35,34,34,33,31,29,26,22,20,21,21,21,22,24,27,30,31,34,36,38,38,35,28,21,17,17,18,20,22,24,26,27,28,29,28,27,26,26,28,29,30,32,32,31,29,27,25,23,22,18,18,18,18,20,25,32,37,40,40,39,38,35,32,29,27,25,25,25,25,24,23,22,21,19,18,17,16,14,14,14,14,17,18,21,25,28,30,32,33,32,32,31,29,26,22,19,16,11,11,10,8,8,8,8,8,10,10,10,11,11,12,12,13,10,10,10,9,9,8,8,8,9,9,9,8,8,7,7,7,7,7,7,6,6,5,5,5,6,6,6,6,6,6,6,6,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,4,4,5,6,7,7,5,5,5,5,5,5,5,5,6,6,6,7,7,7,8,8,8,8,8,8,8,8,8,8,9,10,12,13,13,13,12,12,12,12,12,11,11,10,10,10,7,7,8,9,10,12,14,15,18,19,21,21,21,19,17,15,14,14,15,15,16,16,16,17,22,21,21,22,25,29,34,36,42,44,47,49,48,43,38,35,27,23,18,15,15,19,25,29,40,45,51,54,54,48,41,36,26,22,17,16,19,23,28,30,34,34,35,35,35,33,31,29,29,30,31,32,34,37,39,40,43,43,44,47,52,55,56,56,50,41,31,25,23,25,36,47,58,65,68,62,54,47,41,35,35,34,33,32,31,31,31,31,38,42,47,50,50,49,49,49,46,43,39,37,37,35,32,29,27,25,23,23,28,38,51,61,78,80,79,74,63,51,41,35,29,29,29,29,30,32,33,34,30,26,21,18,18,22,27,31,39,40,42,44,47,53,60,65,70,71,70,66,58,50,43,40,37,39,43,45,44,41,37,34,29,29,29,31,34,37,37,36,34,33,32,32,34,37,40,42,54,56,58,57,52,44,35,29,24,24,26,30,36,39,40,38,43,45,45,41,35,30,29,30,33,36,39,44,46,47,45,43,43,43,42,41,40,39,38,37,39,38,36,35,35,32,28,25,23,23,23,23,23,23,23,24,24,23,21,20,20,21,22,23,27,29,32,35,36,37,36,35,33,34,35,37,38,38,38,38,37,37,35,33,30,26,23,21,21,22,23,24,26,27,28,29,33,35,37,37,35,29,23,20,18,19,21,23,25,27,29,30,30,29,27,25,25,25,26,27,28,28,27,26,25,23,22,21,17,18,18,17,19,23,29,34,38,38,38,37,35,32,29,27,26,26,26,26,25,24,23,23,21,20,18,17,15,14,14,14,14,15,18,22,25,28,29,30,33,32,32,29,26,22,19,16,12,11,10,9,8,8,8,8,9,9,10,10,11,11,11,12,10,10,9,9,9,8,8,8,9,9,8,8,8,7,7,7,7,7,6,6,6,5,5,5,6,6,6,6,6,6,6,6,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,4,4,5,6,6,6,5,5,5,5,5,5,5,5,6,6,6,6,7,7,7,8,8,8,8,8,8,8,8,8,9,10,11,12,12,12,12,11,11,11,11,11,10,10,10,10,7,8,8,9,11,13,15,16,20,20,21,21,20,18,16,14,13,13,14,15,16,17,18,19,22,22,22,24,28,33,37,40,44,45,47,47,44,39,33,30,23,20,17,15,17,23,29,33,45,49,55,58,55,48,38,32,24,20,17,16,19,23,26,28,32,34,36,37,36,34,31,29,28,28,28,28,29,31,32,33,37,39,43,49,55,58,59,58,46,37,27,22,22,27,41,53,65,72,74,68,58,51,44,38,37,36,34,32,31,30,29,29,34,37,40,41,42,42,43,45,43,40,36,34,32,30,28,25,26,24,22,21,25,34,46,54,70,72,72,67,58,48,39,35,27,27,28,28,30,31,33,34,29,26,21,18,18,23,29,33,39,40,41,41,42,46,51,55,59,59,57,53,46,40,36,35,33,35,37,38,37,34,30,28,26,26,29,32,36,38,36,34,29,28,26,25,27,31,35,38,46,48,50,50,46,38,31,26,24,24,25,29,35,39,42,42,48,52,53,50,43,36,33,33,35,36,38,39,40,41,41,41,43,44,45,46,46,44,42,40,42,40,37,35,33,30,25,22,19,19,20,21,23,25,27,28,26,25,23,22,21,21,22,23,26,28,30,33,34,35,35,34,32,34,36,39,41,43,43,44,43,42,39,35,31,27,24,22,22,24,26,28,29,29,28,27,31,33,35,35,34,31,27,24,20,21,23,25,28,30,32,33,33,31,27,24,22,22,23,24,24,23,23,22,21,20,19,19,16,17,17,16,16,20,25,29,35,36,37,37,36,34,31,29,27,27,27,27,26,26,26,25,24,22,20,18,16,15,14,14,11,12,15,18,21,24,26,27,33,33,32,30,26,22,19,16,13,12,11,9,9,8,8,8,8,8,9,9,9,10,10,10,10,9,9,9,8,8,8,8,9,8,8,8,7,7,7,7,7,6,6,6,5,5,5,5,6,6,6,6,6,6,6,6,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,4,4,5,5,6,5,5,5,5,5,5,5,5,5,5,6,6,6,7,7,7,7,7,8,8,8,8,9,9,10,10,10,11,11,11,11,10,11,10,10,10,10,10,10,10,8,8,9,10,12,14,15,17,21,21,21,20,19,17,15,13,12,13,14,16,17,19,20,21,19,20,21,24,28,33,38,41,44,45,44,42,39,33,28,24,18,17,15,15,19,25,32,37,48,52,57,59,55,46,35,28,22,19,16,16,19,23,25,26,31,33,36,38,37,35,31,28,26,26,26,26,27,28,30,30,37,40,45,53,59,61,59,57,42,33,24,20,22,30,45,60,72,78,80,73,63,55,47,41,39,38,36,33,31,29,28,28,31,33,34,35,35,37,40,43,42,40,36,32,29,27,25,24,26,25,23,22,24,31,40,47,59,61,61,58,50,42,36,33,26,26,26,27,28,30,32,33,29,26,21,19,20,25,31,36,39,39,39,38,36,37,40,43,48,48,45,41,35,32,31,32,30,31,31,31,29,27,23,22,22,24,28,34,38,38,35,32,26,24,21,20,22,27,32,36,40,41,43,43,40,34,28,24,23,23,24,28,33,39,44,47,54,58,61,59,51,42,36,34,36,37,37,36,35,35,37,38,45,48,52,55,55,53,49,47,47,44,40,36,33,29,24,21,19,19,20,21,24,27,30,31,31,30,27,25,23,23,23,23,25,26,28,30,32,33,33,33,32,34,37,41,44,47,49,50,49,47,42,36,31,27,24,23,25,28,32,34,35,32,29,27,29,30,31,32,33,32,30,29,24,25,27,29,31,34,35,36,36,34,29,25,22,21,22,22,21,20,19,18,17,17,17,16,15,16,15,14,14,16,20,24,32,34,36,38,38,37,35,33,29,29,28,27,27,27,27,27,26,24,22,19,17,15,14,14,10,11,13,15,18,21,24,25,32,32,31,29,26,22,19,16,14,13,12,10,9,9,9,9,8,8,8,8,8,8,8,8,9,9,9,8,8,8,7,7,8,8,8,7,7,7,6,6,6,6,6,5,5,5,4,4,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,4,4,4,4,5,5,5,5,5,5,5,5,5,5,5,5,6,6,6,7,7,7,7,7,8,8,9,9,9,10,10,10,9,9,9,9,10,9,10,10,10,10,10,10,10,9,9,10,11,12,14,16,17,21,21,20,19,18,16,14,14,12,13,15,16,18,20,22,22,19,20,22,25,29,34,38,40,42,41,40,37,33,27,23,20,15,14,13,15,20,27,34,38,48,51,55,56,52,43,32,25,21,19,17,18,20,23,25,25,29,32,35,37,37,34,30,28,24,24,25,26,28,30,32,34,41,44,50,56,61,61,57,54,39,31,23,21,23,33,49,64,75,81,83,75,64,56,48,42,39,38,36,33,31,30,29,29,31,31,32,32,33,36,40,44,43,41,37,32,28,25,24,24,26,27,27,26,26,30,35,39,47,48,49,47,42,36,33,31,26,26,26,26,27,28,29,30,28,26,23,22,24,29,34,38,37,38,37,34,32,31,32,34,38,37,35,31,27,26,27,29,30,30,29,27,25,22,19,18,21,23,28,34,38,37,33,29,25,22,20,19,21,26,32,36,37,38,39,39,37,33,28,25,22,23,24,26,32,39,47,52,63,67,71,68,59,49,41,38,37,38,37,34,31,31,35,38,49,54,60,66,67,64,59,56,53,49,44,39,35,31,26,22,23,22,22,23,25,28,31,33,37,35,32,28,26,24,24,24,23,24,26,28,29,31,31,32,33,35,38,43,47,51,53,55,53,49,43,36,30,26,24,23,28,32,36,40,40,37,32,29,27,27,28,29,30,31,32,33,29,30,31,33,35,37,38,39,39,36,31,26,23,22,23,24,22,21,19,17,15,14,14,14,14,14,14,13,12,14,17,20,29,32,36,40,41,40,39,37,32,31,29,28,27,27,27,28,26,25,22,20,17,16,15,14,12,12,13,14,17,19,22,24,29,29,29,27,25,22,19,17,16,15,13,11,10,9,9,9,8,8,8,8,8,7,7,7,9,9,8,8,8,7,7,7,8,8,7,7,7,6,6,6,6,6,5,5,5,4,4,4,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,4,4,4,5,5,5,5,5,5,5,5,4,5,5,5,6,6,6,6,6,6,7,8,8,9,10,10,11,10,9,8,8,8,8,9,9,9,9,9,10,10,10,10,10,10,10,12,13,15,17,18,20,20,19,18,17,16,15,15,14,14,16,17,19,21,22,23,23,23,25,27,30,34,37,38,38,36,34,31,27,22,19,17,13,12,12,15,19,26,33,37,45,48,51,51,46,38,29,23,20,19,18,19,22,24,25,24,28,30,33,34,34,32,30,28,24,24,25,27,30,33,36,37,45,47,52,58,61,59,54,50,38,31,24,23,26,35,51,66,74,81,82,74,64,55,47,41,37,36,35,33,32,32,32,32,31,32,33,33,34,37,42,45,45,43,39,33,27,24,24,25,28,30,32,33,32,31,32,34,37,38,40,38,35,32,31,31,27,27,26,25,25,26,27,27,27,26,25,26,29,33,37,40,37,37,37,34,30,28,28,30,30,30,28,26,23,24,26,29,32,31,29,26,23,20,18,17,21,24,29,34,37,36,31,27,23,22,20,20,22,27,32,35,36,37,37,37,35,32,28,26,22,22,23,25,30,39,50,57,71,76,79,75,65,54,46,43,38,39,38,35,31,30,34,38,53,59,68,76,78,74,68,63,58,53,47,41,37,32,28,24,25,24,23,24,26,29,33,35,40,38,34,30,27,25,24,23,22,23,24,25,27,28,30,30,33,35,39,44,49,53,56,57,54,50,43,35,29,25,23,23,30,33,38,42,42,39,34,31,25,24,24,25,27,30,33,34,34,35,36,37,38,39,40,40,39,35,30,25,23,23,25,26,27,25,21,18,15,13,12,12,12,13,13,12,12,13,16,18,26,29,34,39,42,42,41,40,34,33,30,28,26,26,26,26,25,23,21,19,17,16,15,15,14,14,13,13,15,17,19,21,25,25,25,25,24,21,19,18,17,16,14,12,11,10,9,9,9,9,8,8,8,7,7,7,8,8,8,8,7,7,7,6,7,7,7,7,6,6,6,5,5,5,5,5,4,4,4,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,5,5,5,5,5,5,5,5,4,4,5,5,5,6,6,6,6,6,7,8,8,9,10,10,11,10,8,7,7,7,8,8,8,8,8,9,9,10,10,10,10,11,11,12,14,16,18,19,19,19,18,17,16,16,16,16,15,16,17,18,19,21,22,22,24,24,25,27,29,31,32,33,32,31,28,25,22,19,17,16,12,12,12,14,18,24,30,34,41,43,45,44,41,34,27,22,20,19,19,21,24,26,25,24,28,29,30,31,32,31,29,28,25,26,27,29,31,34,37,38,46,47,51,56,58,56,51,47,39,32,26,26,29,37,52,66,71,78,80,72,62,53,45,39,34,34,33,33,33,34,35,35,31,33,34,34,35,38,43,46,46,44,40,33,26,23,23,25,30,34,38,40,38,34,31,30,31,33,34,34,32,31,31,32,28,27,26,25,24,24,24,24,26,27,28,31,34,37,40,41,38,39,38,36,32,30,30,30,29,30,30,28,27,28,31,34,36,34,30,27,23,20,19,18,23,25,29,33,36,34,29,25,22,21,21,22,24,28,32,34,37,37,36,35,33,30,28,26,21,22,22,24,29,39,52,61,74,78,80,76,65,53,45,42,37,40,40,37,32,31,35,39,55,62,73,82,85,81,74,68,59,55,48,42,38,33,29,26,23,23,22,23,25,30,34,37,41,39,34,30,26,23,21,21,21,21,22,23,25,27,28,29,33,36,40,45,50,54,57,59,54,49,41,33,26,23,22,23,29,33,37,41,42,39,35,32,24,23,21,22,24,28,32,35,39,39,39,40,40,41,41,41,36,33,28,23,22,23,26,28,33,30,25,20,15,13,11,11,11,12,13,12,12,13,15,18,21,25,31,38,41,42,41,40,37,34,31,27,25,24,24,24,23,22,20,18,17,16,16,16,16,14,13,12,12,14,16,17,20,21,22,23,22,21,19,18,18,17,15,13,11,10,9,9,10,10,9,9,8,8,8,7,8,8,8,7,7,7,6,6,7,7,7,6,6,6,5,5,5,5,5,4,4,4,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,5,5,5,5,5,5,5,5,4,4,4,5,5,6,6,6,6,6,7,8,8,9,10,10,11,10,8,7,6,6,7,8,8,8,8,9,9,10,10,10,11,11,11,12,14,16,18,19,18,18,17,16,16,16,17,17,16,17,17,18,20,21,22,22,22,22,23,24,25,26,27,27,29,28,25,22,19,17,16,15,12,12,12,14,17,23,29,32,39,40,41,40,37,31,26,22,20,20,20,22,25,27,26,24,28,28,29,29,30,29,29,28,27,27,28,30,31,34,36,37,44,46,49,53,56,54,50,46,39,33,28,28,31,38,52,65,69,76,77,70,60,52,44,38,32,32,32,33,34,35,37,37,31,33,34,35,36,39,43,47,46,44,40,33,25,21,23,25,32,36,42,44,41,36,31,28,29,30,32,32,31,31,33,34,29,28,26,25,23,23,22,22,25,27,30,33,37,39,41,42,40,41,40,38,34,32,32,32,33,34,35,34,34,35,38,41,38,36,32,28,24,21,20,19,24,26,29,33,35,33,28,24,20,20,21,22,25,28,31,33,37,36,36,34,32,29,27,26,21,21,22,24,28,39,53,63,72,76,77,72,61,50,42,39,37,40,41,38,33,32,36,40,55,63,75,85,88,84,77,71,60,55,48,42,37,33,29,26,21,20,20,21,25,30,35,38,41,38,34,29,24,21,19,19,20,21,21,22,24,26,28,29,34,36,40,45,50,55,57,59,53,48,39,31,25,22,22,22,28,31,36,39,40,38,35,33,23,22,20,20,22,26,31,34,42,42,42,41,41,41,41,41,33,30,25,22,21,23,26,28,37,34,28,22,16,13,11,10,10,11,12,12,12,13,15,18,17,22,29,36,40,41,40,39,38,35,31,27,24,23,23,23,21,20,19,18,17,16,16,16,16,14,12,11,10,12,13,15,17,18,20,21,22,21,20,19,18,17,15,13,11,10,10,9,11,10,10,9,9,8,8,8,8,8,8,7,7,6,6,6,7,7,7,6,6,5,5,5,5,5,5,4,4,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,6,6,6,7,7,8,8,8,9,9,9,9,9,9,9,9,8,8,9,9,9,9,10,10,13,13,13,14,14,15,15,15,15,15,15,15,15,15,15,15,17,18,19,20,21,22,22,22,21,21,22,23,24,25,25,26,21,21,21,20,18,15,12,10,10,10,11,14,17,21,25,27,33,33,33,32,30,27,24,23,20,21,23,25,26,27,28,28,23,24,26,27,28,28,28,28,27,27,28,29,30,32,34,35,39,41,43,45,46,46,44,43,38,34,29,27,29,36,45,50,62,64,65,65,60,51,42,37,32,32,32,32,34,35,37,38,35,34,34,35,38,42,46,48,47,43,36,28,22,22,26,29,37,42,46,45,43,41,35,29,28,27,25,26,29,32,33,33,35,32,29,26,23,23,23,24,26,28,32,35,39,40,41,41,42,42,41,41,40,39,39,38,40,39,37,36,37,38,39,40,41,39,34,29,25,22,20,19,23,25,28,31,31,30,28,26,22,22,23,24,27,31,35,37,37,37,37,37,34,31,27,25,24,22,21,23,31,41,52,59,73,73,71,64,53,43,38,36,38,42,43,40,34,31,33,36,48,56,68,79,84,82,76,72,58,55,48,41,35,30,28,27,23,22,23,24,27,31,35,38,42,37,31,24,20,19,21,22,21,23,24,25,25,27,30,33,33,37,42,47,52,54,56,56,51,46,38,30,25,24,25,27,28,30,32,34,34,33,31,30,23,21,19,18,20,24,29,32,43,43,44,44,43,41,38,37,32,29,24,19,16,19,24,29,33,33,33,30,26,20,14,10,12,10,9,9,11,13,13,12,14,18,23,30,35,38,40,40,37,36,33,29,25,22,19,17,17,17,17,17,17,17,17,17,15,14,13,13,12,11,10,10,14,15,16,18,19,19,19,19,16,17,17,17,16,14,12,11,9,10,10,11,11,10,9,8,8,8,7,7,7,7,7,6,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,6,6,6,7,7,8,8,8,8,8,8,8,8,8,8,8,8,8,9,9,9,10,10,10,13,13,14,14,15,15,15,15,15,15,15,15,15,15,15,15,17,17,19,20,21,21,21,21,20,21,21,22,22,23,23,23,21,21,20,19,17,14,12,10,11,11,12,14,17,21,24,26,30,30,29,29,27,24,22,20,21,22,25,27,28,28,27,26,22,23,23,24,25,26,26,26,26,26,26,27,28,30,32,33,36,38,40,42,42,42,41,40,36,34,30,28,30,36,43,47,57,58,60,60,55,48,40,35,31,32,33,34,35,36,36,37,33,33,33,34,38,42,47,50,49,45,38,30,24,23,27,30,40,46,49,47,45,42,35,28,28,26,25,26,29,33,34,34,34,32,29,26,24,24,24,25,27,28,31,34,36,38,38,38,40,41,42,42,42,41,39,39,40,39,38,37,38,39,40,41,42,39,35,30,26,23,22,21,25,27,29,32,32,31,29,27,23,24,24,26,30,33,37,39,40,41,41,41,38,34,29,27,25,24,23,25,31,40,50,56,65,64,61,53,44,38,35,35,39,42,44,41,35,32,33,36,41,48,58,68,73,72,68,65,55,52,46,39,34,30,28,28,24,24,24,25,27,31,35,37,37,33,26,21,18,20,22,25,26,27,29,29,28,29,30,32,33,36,41,46,50,53,54,54,49,44,37,29,24,23,23,24,27,28,30,32,32,31,29,28,22,20,19,18,20,23,28,31,38,39,40,40,39,38,37,36,32,30,25,19,16,17,22,26,31,32,33,32,28,22,16,12,12,10,8,9,11,12,13,12,12,15,19,25,29,33,36,37,35,34,31,28,24,21,19,17,17,17,17,17,17,17,17,17,14,14,13,12,11,11,10,10,13,14,15,16,17,18,18,18,16,16,17,17,16,14,12,11,11,12,12,12,11,10,9,9,8,7,7,7,7,6,6,6,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,6,6,6,7,7,8,8,8,8,8,8,8,8,8,8,8,8,8,9,9,10,10,10,11,14,14,14,14,15,15,15,15,14,14,14,14,14,14,14,14,16,17,18,19,20,20,20,20,19,19,19,20,20,20,20,20,20,20,20,18,16,14,12,10,12,12,13,15,18,21,23,25,25,25,25,24,22,21,19,18,21,24,27,30,31,29,26,24,20,20,20,20,21,22,23,24,23,23,23,24,25,27,28,29,33,33,35,36,37,37,37,37,34,32,31,30,32,36,41,44,50,52,53,52,49,44,38,34,31,32,34,35,36,36,35,34,31,31,31,33,37,43,49,52,51,47,40,33,27,26,29,32,44,49,52,50,46,43,35,27,26,24,23,25,29,33,35,35,33,31,29,26,25,25,25,25,28,28,30,31,32,33,33,33,36,38,41,43,43,42,39,38,38,38,38,38,38,39,40,41,41,39,35,31,28,26,25,24,27,29,31,33,33,32,30,29,26,26,27,30,33,37,41,43,46,47,48,48,45,39,34,30,27,26,25,26,30,37,45,50,54,52,47,41,35,33,35,37,42,45,46,42,36,32,31,32,33,38,46,54,58,60,59,58,50,47,42,36,32,30,28,28,27,26,26,27,28,31,33,35,30,27,21,18,18,21,27,31,34,36,37,36,33,32,31,32,33,35,40,44,48,51,52,53,47,43,36,29,24,22,22,22,25,26,28,28,28,27,26,25,21,19,18,17,19,22,26,29,32,33,34,35,35,35,35,34,33,30,25,20,15,15,19,22,29,31,34,35,32,26,20,16,13,10,8,8,10,12,12,12,11,12,14,18,22,26,30,32,32,31,29,26,23,20,18,17,17,17,17,17,17,16,16,16,13,13,13,12,11,11,10,10,12,12,14,15,15,16,16,15,15,15,15,15,15,14,12,12,14,14,14,14,13,11,10,9,8,7,7,7,6,6,5,5,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,6,6,6,7,7,8,8,8,7,7,7,7,7,7,7,7,8,8,9,9,10,11,11,12,14,14,14,15,15,15,15,15,13,13,13,13,14,14,14,14,15,16,17,18,19,19,18,18,18,18,18,18,18,18,18,18,21,20,19,18,16,14,13,12,13,14,15,16,18,20,22,23,21,21,21,21,20,19,18,18,23,26,30,33,32,29,24,21,18,17,17,17,18,19,21,22,20,20,20,21,22,24,25,26,30,30,31,31,32,33,34,34,31,32,32,34,36,38,40,42,46,47,47,46,44,40,36,34,31,33,35,36,36,35,33,31,28,29,30,33,38,45,51,55,52,49,43,36,30,29,32,35,46,52,55,52,48,43,34,25,23,22,21,23,28,32,34,34,32,31,29,27,26,25,25,26,28,28,28,28,28,28,28,28,32,35,39,42,43,40,37,34,34,34,35,35,36,38,39,39,40,38,35,31,29,27,27,27,29,30,32,33,34,32,31,30,28,29,30,33,37,41,45,48,53,55,56,55,51,45,38,34,27,26,25,26,28,33,37,40,43,40,35,31,30,33,38,43,48,49,47,43,36,30,27,27,29,32,37,42,46,49,51,51,44,41,37,33,30,28,28,28,28,28,28,28,29,30,32,33,26,23,19,18,20,27,35,40,45,46,46,44,39,35,33,33,33,35,39,43,46,49,50,51,45,42,36,30,25,23,22,22,24,24,25,25,24,23,22,21,19,18,17,16,18,21,24,26,27,27,29,30,32,33,34,34,33,31,26,20,16,14,16,19,25,29,34,37,36,31,25,21,15,12,9,8,10,12,12,12,10,10,11,13,16,21,25,27,28,27,25,23,21,19,18,17,17,17,17,16,16,16,16,15,13,12,12,11,11,10,10,10,10,11,12,13,14,14,13,13,14,14,14,14,14,13,13,13,17,17,16,15,14,12,10,9,8,8,7,7,6,5,5,5,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,6,6,6,7,7,8,8,8,7,7,7,7,7,7,7,7,8,8,9,10,11,12,12,13,14,14,14,14,14,14,13,13,11,11,12,12,13,13,14,14,15,15,16,17,17,17,17,16,17,17,17,17,18,18,18,18,21,21,19,18,16,15,14,14,15,15,16,18,19,20,21,21,20,20,20,19,19,19,20,20,24,27,32,34,33,28,22,18,15,15,15,16,17,18,19,20,17,18,18,19,21,23,25,26,29,29,28,28,29,30,32,33,30,32,35,38,40,42,43,43,46,46,45,43,40,38,35,34,32,33,35,35,35,32,30,28,26,27,30,34,40,47,53,56,52,49,44,38,33,32,35,38,47,53,56,54,50,44,35,26,22,21,20,22,27,31,33,33,33,32,30,29,27,26,25,25,26,26,26,25,25,25,25,26,30,33,37,40,39,36,31,28,28,29,30,32,33,34,35,35,37,35,33,30,28,28,28,28,30,31,32,32,32,31,30,29,29,30,31,34,39,44,48,51,59,59,59,57,53,47,40,36,26,26,25,25,26,28,30,31,32,29,25,24,29,36,44,49,56,54,49,42,35,28,25,23,27,28,30,32,36,39,41,43,38,36,32,29,27,26,27,27,28,28,28,28,29,29,30,30,25,24,22,22,27,35,44,49,55,55,53,49,42,37,34,33,33,35,37,40,43,46,48,49,43,41,36,32,28,25,24,23,23,22,22,21,20,19,18,17,17,17,16,16,17,19,21,23,24,24,26,27,30,32,34,35,33,31,27,22,17,14,15,16,22,26,32,37,38,35,30,26,19,16,11,9,10,11,12,11,11,11,10,11,13,17,21,24,23,22,21,20,19,18,17,17,17,17,17,16,16,15,15,14,12,11,11,11,11,10,10,10,10,10,11,12,12,12,12,11,12,12,12,12,12,13,13,13,17,17,17,16,15,13,11,10,10,9,9,8,7,6,5,5,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,6,6,6,7,7,8,8,8,8,8,8,8,8,8,8,8,8,8,9,10,11,12,13,13,13,13,13,12,12,12,12,11,10,10,11,11,12,13,13,14,14,15,15,16,16,16,15,15,16,17,17,18,19,20,20,21,23,22,20,18,17,16,16,16,16,17,18,19,20,20,20,19,19,19,19,19,19,20,21,22,26,29,32,33,31,26,20,15,14,15,16,17,18,18,18,18,15,16,17,19,21,24,26,28,28,27,25,24,25,28,30,32,31,33,37,41,44,46,47,48,49,47,44,40,37,35,33,33,33,33,33,33,32,29,27,26,25,27,32,38,44,50,54,56,50,48,44,39,36,35,38,41,47,53,58,56,53,48,39,30,24,23,22,24,28,31,33,34,34,33,32,30,28,26,24,23,24,24,23,23,23,24,25,26,31,33,36,38,36,31,26,23,22,24,26,28,30,31,32,32,32,31,29,28,27,27,28,28,29,30,30,30,30,29,28,28,28,29,31,35,40,45,50,53,60,59,58,54,49,43,38,34,26,26,26,26,26,26,26,26,23,21,21,25,33,44,52,57,63,58,51,43,35,30,27,26,29,28,27,27,28,30,32,34,34,32,29,26,24,24,25,25,27,27,27,28,28,28,29,29,27,26,27,29,35,44,52,57,61,60,56,49,41,35,33,32,31,32,34,36,39,41,43,44,40,38,36,32,29,27,25,25,22,22,20,19,18,16,15,15,16,15,15,15,16,17,19,21,22,22,23,25,27,30,33,34,32,32,29,24,18,15,15,16,19,23,30,36,38,37,34,32,25,20,15,11,11,11,11,11,12,11,10,10,12,15,18,20,18,18,18,18,17,17,17,17,17,17,16,16,15,14,14,14,11,11,11,10,10,10,10,10,10,10,11,12,12,11,11,10,11,11,11,11,11,12,14,14,17,17,17,16,15,13,12,11,12,11,10,9,8,7,6,6,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,6,6,6,7,7,8,8,8,8,8,8,8,8,8,8,8,8,8,9,10,12,13,14,14,12,12,11,11,11,10,10,10,9,9,10,11,12,13,13,14,14,14,15,15,15,15,14,13,16,17,18,19,21,22,23,24,25,23,21,19,18,18,18,19,17,18,19,20,20,20,19,18,18,18,18,18,19,21,22,24,28,29,31,32,29,24,18,14,12,14,17,20,21,20,18,17,14,15,16,19,22,26,29,31,26,24,22,21,22,25,28,30,32,35,39,44,48,51,52,53,51,48,43,38,34,31,30,30,33,33,32,30,28,26,25,24,24,28,35,42,48,52,54,55,47,46,44,40,37,37,41,44,47,55,60,60,58,53,44,35,29,27,26,27,31,34,35,36,35,35,33,31,28,25,23,21,21,21,21,21,22,24,26,28,36,37,38,37,34,28,23,19,19,21,24,26,29,30,30,30,28,27,26,25,25,25,27,28,28,28,28,28,27,27,26,26,27,28,31,34,39,45,50,53,58,56,52,47,42,36,32,29,27,27,28,29,28,26,25,23,22,22,24,33,45,57,65,68,67,61,52,44,38,36,35,35,34,33,30,28,27,28,29,30,31,29,26,23,22,22,22,23,25,25,26,27,27,28,28,27,29,29,31,36,42,49,56,60,63,60,54,45,36,31,30,30,27,27,29,31,33,35,37,39,35,35,33,32,30,28,26,25,22,21,20,18,16,15,14,13,15,14,14,14,15,16,18,18,20,20,21,22,25,28,30,32,32,32,30,25,20,17,16,16,17,21,27,33,37,38,38,37,30,25,18,13,11,11,11,10,11,11,10,10,11,13,15,16,15,15,15,16,16,16,16,16,17,17,16,16,15,14,13,13,10,10,10,10,10,10,10,10,10,11,11,12,12,11,10,10,10,10,9,9,10,12,14,15,15,15,15,15,15,14,13,12,14,13,12,11,10,8,7,7,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,6,6,6,7,7,8,8,8,9,9,9,9,9,9,9,9,8,8,9,10,12,13,14,15,11,11,11,10,9,9,9,8,8,9,10,10,11,12,13,13,13,14,14,15,15,14,13,13,16,17,18,20,22,24,26,26,26,24,22,20,19,19,20,20,18,19,20,21,21,20,18,17,17,17,17,17,18,20,23,24,29,30,31,30,27,22,17,13,12,15,19,22,23,21,18,16,13,14,16,19,23,27,31,33,25,23,20,18,19,22,26,29,33,36,40,46,50,54,56,57,53,49,43,36,31,29,28,28,34,33,30,28,26,24,24,23,24,29,36,44,50,54,54,54,46,45,43,40,38,39,42,45,48,56,62,63,61,57,49,40,33,31,29,30,33,36,37,37,36,36,34,31,28,25,22,20,20,19,19,20,22,25,28,29,39,40,39,37,33,27,22,18,18,20,23,26,28,30,30,30,26,25,24,23,23,24,26,27,27,27,27,26,25,25,24,24,26,27,30,34,39,45,50,53,55,52,47,41,35,31,27,25,28,29,30,31,30,28,25,23,25,26,31,42,56,68,76,78,69,62,53,45,41,41,42,43,41,39,36,32,30,29,29,30,30,28,25,22,20,20,21,22,23,24,25,26,27,27,27,27,29,31,34,39,45,52,58,61,62,58,51,41,32,27,27,28,24,24,25,27,29,31,33,35,32,32,31,30,29,27,26,25,23,21,19,17,15,14,13,13,14,14,14,14,14,15,17,17,19,18,19,20,22,25,28,30,32,32,30,27,22,18,17,17,16,20,26,32,36,39,39,39,33,28,20,15,12,11,10,10,10,10,10,10,11,12,13,13,13,13,14,14,15,16,16,16,17,17,16,15,14,14,13,12,10,10,10,10,10,10,10,10,11,11,12,12,12,11,10,10,10,9,9,9,10,12,14,15,14,14,15,15,15,14,13,13,15,14,13,12,11,9,8,8,6,6,6,5,5,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,6,6,6,6,6,6,6,6,7,7,7,8,8,9,9,9,9,9,9,10,10,11,11,11,10,9,9,8,8,9,9,10,10,10,10,11,11,12,12,12,13,12,12,12,12,13,14,15,15,17,20,22,24,25,25,25,23,22,20,19,18,19,20,21,19,18,17,17,16,16,17,17,18,17,16,17,19,22,25,27,29,30,31,29,24,19,16,15,14,18,24,29,30,27,22,18,16,16,18,23,29,33,32,31,26,23,19,16,17,20,26,29,33,34,38,44,50,53,53,52,54,48,40,32,27,27,29,31,32,33,32,28,22,20,22,25,28,37,47,52,55,57,53,47,46,39,34,35,38,39,42,47,53,57,64,68,67,61,54,49,38,34,31,30,33,38,41,43,40,39,37,34,30,26,22,20,20,21,22,23,24,29,35,40,42,45,47,44,38,30,24,21,17,19,24,27,29,29,28,27,23,22,20,19,19,20,22,24,23,23,22,22,22,21,21,21,24,26,30,35,38,40,40,40,41,37,32,27,25,26,28,30,32,35,37,38,36,34,32,32,31,36,45,59,72,82,86,87,73,64,52,43,42,46,52,57,48,47,43,38,33,31,31,33,38,36,33,29,25,22,20,19,22,22,23,24,26,27,28,28,33,34,37,40,44,48,51,52,48,44,37,30,24,22,21,22,22,22,22,22,21,21,21,20,24,25,27,29,29,28,26,24,22,21,20,18,16,15,13,13,12,12,11,11,12,14,16,17,18,19,19,21,22,23,24,24,27,28,28,28,26,22,19,16,16,19,24,30,34,37,38,38,34,30,24,18,13,11,10,11,9,10,12,13,14,13,12,11,11,12,13,14,15,16,17,17,17,17,17,16,15,13,12,11,12,12,11,9,9,9,9,9,10,10,10,10,10,10,10,10,10,9,9,8,9,10,12,13,12,12,13,14,15,15,16,16,18,17,15,13,11,9,7,6,6,5,4,3,3,3,3,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,6,6,6,6,6,6,6,6,7,7,7,8,8,8,9,9,9,9,9,10,10,11,11,11,10,9,9,8,8,9,9,10,10,10,10,11,11,11,12,12,12,12,12,12,13,14,16,16,18,19,21,23,25,25,25,25,22,21,20,19,18,19,19,20,18,17,16,16,16,16,17,17,18,17,16,17,18,21,24,26,29,29,29,26,22,18,16,15,17,21,26,30,30,27,22,19,17,18,20,25,31,33,32,30,24,22,18,16,17,20,25,28,31,32,36,42,47,51,51,50,47,42,34,27,23,22,25,27,31,32,31,27,23,21,24,27,34,43,52,57,60,60,55,47,46,39,34,35,38,39,42,47,53,57,63,67,66,61,55,50,39,36,33,32,35,38,41,42,39,38,35,32,29,27,25,24,27,28,30,31,32,36,41,45,46,48,50,47,41,32,26,22,19,21,24,26,28,28,27,26,26,24,22,20,19,19,20,21,23,23,23,23,22,22,21,21,23,26,31,35,38,39,38,38,35,31,26,22,21,24,28,31,41,44,46,46,45,42,41,41,42,46,56,68,79,86,89,88,74,65,53,46,45,49,55,59,56,55,50,45,40,38,39,42,42,40,37,33,29,26,23,22,22,22,22,23,24,26,28,29,33,35,37,40,43,45,46,46,40,36,30,24,19,17,16,17,19,19,19,19,19,19,18,18,19,21,23,24,24,23,22,21,20,19,18,17,16,15,14,13,13,12,11,11,12,14,16,17,18,19,19,20,21,21,22,22,25,26,26,26,24,22,19,17,16,19,23,28,32,34,36,37,33,30,25,20,15,12,11,10,10,11,12,13,14,13,12,12,11,11,12,13,14,15,16,16,17,17,17,16,15,14,13,12,13,12,11,10,9,9,9,9,10,10,10,10,10,10,10,10,10,9,9,8,9,10,11,12,12,12,12,13,14,15,15,16,17,17,15,13,11,9,7,6,6,5,4,4,3,3,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,6,6,6,6,6,6,6,6,7,7,7,7,8,8,8,9,9,9,9,9,10,10,10,10,9,9,8,8,8,8,9,9,10,10,10,10,11,11,11,12,11,11,11,12,14,16,18,19,22,23,24,24,25,25,24,24,21,20,19,18,18,18,19,19,16,16,15,15,15,15,16,17,17,17,16,17,18,21,23,25,28,27,26,22,18,15,16,17,21,24,28,31,30,27,22,19,19,20,23,28,32,33,31,29,23,22,19,18,19,22,25,27,28,29,32,37,41,44,44,43,39,35,28,22,20,21,24,26,31,32,31,28,24,24,28,33,42,52,62,66,68,66,58,50,47,40,35,36,38,38,41,46,52,55,61,64,64,60,54,50,41,38,34,33,36,39,41,41,39,37,34,31,29,29,29,30,33,36,38,40,41,43,46,49,51,53,54,52,44,36,29,25,24,25,26,28,29,29,29,29,28,27,24,21,19,18,19,19,24,24,24,24,23,23,23,23,24,27,32,36,38,38,36,34,29,26,22,20,23,28,35,40,53,55,57,56,53,51,50,50,51,56,65,75,84,88,88,86,73,65,55,49,49,53,58,62,62,60,55,49,45,45,48,52,51,49,46,42,37,32,28,25,22,22,21,21,23,26,29,31,34,36,38,40,41,40,39,37,31,28,23,18,15,13,12,13,15,15,16,17,17,17,16,16,16,17,19,20,21,20,19,18,17,16,16,16,15,15,15,15,13,13,12,11,12,14,16,17,19,19,19,19,19,19,19,19,21,22,23,23,22,20,18,17,17,19,21,24,28,31,33,34,32,30,27,22,18,14,11,9,10,11,12,13,13,13,13,12,11,11,12,12,13,13,14,14,16,16,17,17,16,15,14,13,14,13,12,10,10,9,9,9,10,10,10,10,10,10,10,10,10,9,9,9,9,10,11,11,11,11,12,12,13,14,15,15,16,16,14,13,11,9,8,7,6,6,5,4,3,3,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,6,7,7,7,8,8,8,9,9,9,9,9,9,9,10,9,9,8,7,7,8,9,9,9,9,10,10,10,11,11,11,10,10,11,13,15,17,20,21,25,25,25,25,24,23,22,22,20,19,19,18,18,18,18,18,14,14,14,14,14,15,16,17,17,17,17,18,19,21,23,24,26,25,22,18,15,14,17,20,27,28,30,31,30,26,22,19,19,22,26,30,33,32,30,29,25,24,23,22,23,24,26,27,26,26,27,30,33,35,34,32,31,28,23,20,20,23,28,31,33,34,33,29,26,28,34,39,51,61,71,75,76,73,64,55,51,43,38,37,38,37,40,44,48,52,56,60,60,57,52,49,40,37,34,33,35,37,39,39,38,36,33,30,30,32,34,37,39,42,45,46,46,46,47,48,54,56,58,55,48,39,33,29,29,29,30,31,31,32,33,33,29,28,25,23,21,19,19,18,25,25,25,25,25,26,26,26,27,30,34,38,39,37,34,32,28,26,24,25,31,40,50,56,64,65,65,62,57,53,51,50,53,57,66,75,82,84,82,78,69,63,54,50,50,54,58,61,58,56,52,48,46,48,54,59,62,60,57,52,45,38,32,28,23,22,21,21,23,27,32,34,36,38,40,40,39,36,32,29,25,23,20,17,15,13,12,12,13,14,16,17,18,17,17,16,16,17,18,19,19,19,19,18,14,14,14,15,15,15,16,16,14,13,12,12,12,14,16,17,19,18,18,18,17,17,16,16,18,18,19,20,20,19,18,18,18,19,20,22,24,27,29,31,30,29,27,25,21,16,12,10,11,11,12,12,13,13,13,13,11,11,12,12,12,12,12,12,15,15,16,17,17,16,16,15,15,14,13,11,10,10,10,10,9,9,9,9,9,9,9,9,9,9,9,9,9,9,10,10,10,10,10,11,12,13,13,14,15,14,13,12,10,9,8,8,7,6,5,4,4,4,4,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,6,6,7,7,7,8,8,9,9,9,9,9,9,9,8,9,8,7,7,7,7,8,9,9,9,9,10,10,10,11,11,10,11,12,13,16,18,21,22,26,26,24,23,22,21,20,20,18,18,18,18,18,17,17,16,13,13,13,14,15,16,17,18,18,18,18,19,20,22,23,24,24,23,20,16,14,16,21,25,32,32,32,32,29,25,21,18,19,22,26,29,30,30,29,29,28,28,28,28,28,28,27,27,25,24,23,24,26,26,25,23,22,20,18,18,21,26,31,35,35,35,34,30,28,31,38,45,57,67,77,82,83,81,72,63,58,49,42,40,39,36,37,40,43,45,49,52,53,51,48,46,38,35,33,32,34,36,37,37,39,36,33,31,32,35,40,43,45,48,51,51,49,47,47,47,54,56,58,56,50,42,36,33,30,31,32,33,35,36,37,38,32,31,29,27,24,22,21,21,26,26,27,28,29,30,31,31,32,34,38,40,40,37,34,32,29,28,29,33,41,52,63,69,72,72,69,64,57,51,48,47,48,53,60,69,76,77,73,70,61,56,50,46,47,50,53,54,48,47,45,43,44,49,56,62,69,68,65,60,52,43,35,30,25,24,23,23,26,30,35,38,39,40,41,40,37,33,28,25,22,21,20,18,16,14,13,13,14,16,18,21,22,21,21,20,17,17,18,18,18,17,17,17,13,13,14,14,15,16,17,17,15,14,13,12,13,14,16,17,18,18,17,17,16,15,15,15,15,16,17,17,18,18,18,18,19,19,19,20,22,24,26,27,27,27,26,25,22,18,14,11,11,11,11,11,12,12,13,13,12,12,12,12,12,12,11,11,13,14,15,17,17,18,17,17,17,16,14,12,11,10,10,10,9,9,9,9,9,9,9,9,9,9,9,9,9,9,8,8,8,9,9,10,11,12,12,12,13,13,12,11,10,9,9,8,7,6,5,5,4,4,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,6,6,6,7,7,7,7,9,9,9,9,8,8,8,8,8,8,7,7,7,7,8,8,8,9,9,9,10,10,10,10,11,12,13,14,16,19,21,23,25,24,22,20,18,17,17,17,17,17,18,18,18,17,16,15,13,13,13,14,15,17,19,20,19,20,20,21,22,23,24,24,22,21,19,16,16,19,26,30,35,35,34,31,27,23,19,17,17,20,24,26,26,27,28,29,31,32,33,33,31,29,27,25,24,22,21,21,22,23,22,20,17,16,15,16,20,26,32,35,36,36,33,29,27,31,40,47,59,69,80,86,88,88,81,73,67,57,48,44,39,35,34,36,35,38,41,44,45,44,42,41,35,33,31,32,34,36,36,36,39,38,35,34,36,39,44,47,53,54,55,54,50,47,45,45,49,52,55,55,50,44,39,37,31,32,35,38,41,43,45,45,41,40,37,34,31,28,25,24,26,27,28,31,33,35,37,37,40,41,42,42,41,38,35,34,32,32,34,38,46,56,66,71,74,73,69,62,53,47,43,42,44,47,53,61,66,67,64,60,51,47,42,40,40,42,43,44,39,39,39,39,41,47,55,60,68,68,66,62,55,45,37,31,26,26,26,28,31,35,39,42,42,42,42,40,37,32,28,25,22,22,22,21,19,17,15,14,17,19,22,25,26,26,25,24,18,18,17,17,16,15,15,14,13,14,14,15,16,17,17,18,16,15,14,13,13,14,15,16,18,18,17,17,16,16,15,15,15,15,15,16,16,17,17,17,19,19,20,21,22,22,23,23,24,24,24,23,21,18,16,14,12,11,11,11,11,12,13,14,14,14,13,13,12,12,11,11,12,13,15,17,18,19,19,19,18,17,15,13,12,11,10,10,8,8,8,8,8,8,8,8,8,9,9,9,9,8,7,7,7,7,8,9,10,10,11,11,12,12,11,11,10,10,9,9,7,7,6,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,6,6,6,7,7,7,9,9,9,8,8,7,7,7,8,7,7,6,6,7,7,8,8,8,9,9,9,10,10,10,13,13,14,15,17,19,21,22,23,21,19,17,15,15,15,15,16,17,17,18,17,16,15,14,13,13,14,15,17,19,21,22,21,21,22,23,24,25,25,25,19,19,19,18,19,24,30,35,38,37,34,30,26,21,17,15,15,18,21,22,22,23,27,30,33,34,35,35,33,29,25,22,22,20,19,21,23,25,25,24,20,19,18,19,22,27,32,35,35,34,31,26,24,29,38,46,59,69,80,86,91,93,89,82,75,65,54,47,40,33,30,32,29,30,33,36,37,37,36,35,34,33,31,32,35,37,38,38,40,39,38,38,40,43,47,49,55,56,55,51,46,41,39,39,43,47,51,52,50,45,41,39,35,38,43,49,53,56,57,58,53,52,48,44,38,33,29,26,26,27,30,33,36,40,42,43,47,46,45,44,42,40,38,37,38,39,40,44,49,56,62,66,66,65,61,54,46,39,36,36,39,41,45,50,54,54,51,48,42,38,34,32,32,33,33,32,31,32,33,34,36,41,47,52,60,61,61,59,54,46,38,33,28,28,30,33,36,40,43,45,44,44,42,40,37,33,30,28,27,28,28,27,26,23,20,19,19,21,25,28,30,30,29,28,23,22,21,19,17,16,15,15,15,15,15,16,17,17,18,18,17,16,14,13,13,14,15,16,17,17,17,17,17,16,16,16,16,16,15,15,16,16,17,17,19,20,21,22,23,22,21,20,21,21,21,21,20,19,18,17,12,12,11,10,11,12,13,14,16,16,15,14,13,12,11,11,11,13,15,17,19,20,21,21,19,18,16,14,12,11,10,10,8,8,8,8,8,8,8,8,8,9,9,10,9,8,7,6,6,7,7,8,9,10,10,10,11,11,11,10,10,10,10,9,8,7,6,5,5,5,5,6,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,6,6,7,7,7,9,9,9,8,8,7,7,7,8,7,7,6,6,7,7,8,8,8,8,9,9,10,10,10,14,14,14,15,17,19,21,22,21,19,17,15,13,13,13,13,15,16,17,18,17,16,14,13,13,13,14,15,17,20,22,23,22,22,24,25,25,25,25,25,18,18,19,19,21,26,33,39,39,37,34,29,25,20,16,14,14,16,19,19,19,21,26,31,33,34,36,36,33,28,23,19,20,19,19,21,25,28,30,29,26,24,23,23,25,29,33,36,34,32,29,24,22,26,36,44,58,68,79,86,92,96,93,88,80,69,57,49,41,32,28,29,24,26,28,31,32,33,33,32,34,33,32,34,37,39,40,39,41,40,40,40,42,45,48,50,54,54,51,46,40,35,33,33,39,43,48,50,49,45,42,41,41,45,52,59,64,67,69,69,63,61,56,50,43,36,31,27,26,28,30,34,39,42,45,47,52,50,48,45,42,41,40,39,45,45,46,48,52,56,59,62,57,56,52,46,38,33,30,30,34,35,38,41,44,44,41,38,36,33,29,27,27,27,26,25,25,26,28,29,30,34,39,43,51,53,56,56,53,46,39,35,28,30,32,36,39,43,45,47,46,45,42,40,37,34,32,31,33,34,35,34,32,29,26,24,19,22,26,30,32,32,30,29,29,27,25,23,21,19,18,18,16,16,16,17,17,18,18,18,17,16,15,13,13,14,15,16,17,17,17,17,17,17,17,17,16,16,16,15,15,16,17,17,19,20,22,24,23,22,19,18,19,19,19,19,19,19,19,19,13,12,11,10,11,12,14,15,17,17,16,15,14,13,12,11,11,12,14,17,19,20,21,22,19,18,16,14,12,11,11,10,8,8,8,8,8,8,8,8,8,9,9,10,9,8,6,5,6,6,7,7,8,9,10,10,10,10,10,10,10,10,10,10,8,7,6,5,5,5,5,6,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,7,7,7,7,7,7,7,7,7,7,7,8,8,9,9,9,10,10,9,9,9,10,11,11,11,12,14,16,18,19,19,20,21,18,15,11,10,11,12,14,17,17,18,18,17,15,13,12,13,15,16,17,20,24,24,22,26,27,28,29,29,28,27,26,16,16,16,20,27,34,38,40,44,39,30,23,19,17,16,14,17,17,16,17,19,22,26,28,33,34,36,36,33,28,23,19,17,19,23,28,31,34,35,36,33,32,31,32,33,34,33,31,35,32,27,22,20,24,31,37,50,59,72,82,87,88,88,87,79,73,64,52,41,33,27,24,21,23,26,27,27,28,30,32,32,37,40,39,39,44,46,46,45,43,40,40,42,45,46,46,51,48,44,39,33,29,26,25,32,36,41,44,45,44,44,44,42,51,59,65,72,78,79,76,72,68,62,56,49,41,33,27,22,24,27,32,39,46,51,55,57,55,52,49,47,47,48,49,52,51,49,49,50,50,49,48,45,42,39,35,32,31,31,32,31,32,33,34,34,33,31,30,30,29,28,25,22,22,24,26,25,26,27,27,26,27,29,32,40,43,46,48,47,42,36,32,28,31,35,40,43,45,45,45,41,40,39,38,37,37,37,37,39,40,41,41,39,35,31,28,24,24,26,30,34,36,35,33,32,30,28,25,23,23,23,23,22,22,22,22,22,22,22,22,16,16,16,16,16,16,16,16,17,16,15,15,16,17,19,20,21,21,20,20,20,19,19,19,24,24,24,24,24,23,22,21,17,18,19,20,20,20,20,19,16,15,13,12,11,11,12,13,15,16,16,16,15,13,11,10,9,10,13,15,17,17,17,17,15,14,13,13,12,11,10,10,10,9,9,8,8,9,9,10,10,10,10,9,9,8,8,8,7,7,7,7,7,7,7,7,8,8,9,9,9,10,10,10,7,7,7,7,7,7,7,7,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,7,7,7,7,7,7,7,7,7,7,7,8,8,8,9,9,10,10,9,9,9,10,11,12,12,13,15,17,18,19,19,19,19,17,14,11,11,12,13,15,17,17,18,18,17,15,14,12,16,18,20,22,25,28,28,26,28,29,31,32,32,30,28,26,18,18,18,22,29,35,39,40,41,36,28,22,18,16,15,14,16,15,15,16,18,22,25,28,33,34,34,34,31,27,23,21,23,26,30,35,40,43,45,46,42,40,38,37,37,36,34,33,31,28,24,19,18,21,28,33,44,53,66,77,85,89,90,91,80,74,63,51,40,32,27,24,23,25,27,28,27,28,31,33,35,41,44,43,44,48,50,49,47,44,40,39,40,42,43,42,45,43,39,35,30,27,24,23,31,35,40,43,43,43,44,44,49,58,67,73,79,84,84,80,74,70,65,58,51,42,33,27,21,22,26,31,39,46,53,57,59,57,54,51,49,49,50,51,55,53,49,46,44,42,39,38,39,38,37,35,33,32,32,32,30,30,30,30,30,30,29,29,28,28,26,24,22,23,27,30,29,30,31,29,27,25,25,26,32,35,40,43,43,40,35,31,28,31,35,40,43,44,44,43,39,38,37,36,35,36,37,37,39,41,43,43,41,37,32,28,24,24,26,29,33,35,34,33,33,32,29,27,26,25,26,26,24,23,23,23,22,22,22,21,17,17,17,17,17,17,17,17,17,17,16,15,16,17,19,20,22,22,21,21,21,20,20,19,23,23,24,24,23,22,21,21,17,18,18,19,19,20,19,19,16,15,14,12,11,11,12,13,15,15,16,16,15,13,11,10,9,10,12,14,15,15,15,15,14,14,13,12,11,10,10,9,10,9,9,8,8,9,9,10,10,10,9,9,9,8,8,8,7,7,7,7,7,7,7,7,8,8,8,9,9,9,10,10,7,7,7,7,7,7,7,7,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,7,7,7,7,7,7,7,7,7,7,7,7,8,8,8,9,10,9,9,9,9,10,11,12,15,16,17,18,18,18,18,17,16,15,13,11,11,13,15,17,17,17,17,17,17,15,14,13,16,17,20,24,26,28,29,30,32,34,37,38,36,33,28,26,20,20,21,25,31,36,38,39,36,31,24,19,17,15,14,13,14,14,13,14,17,21,25,27,32,32,32,31,29,27,25,23,28,31,37,43,48,52,54,56,51,48,44,40,38,36,33,31,26,24,20,16,15,17,23,28,37,45,57,68,76,82,86,89,81,74,62,49,38,31,27,25,27,28,29,29,29,30,32,34,39,46,50,50,51,55,56,54,49,46,41,38,38,38,37,36,36,34,32,28,25,23,22,21,29,33,37,40,41,42,44,45,54,63,73,79,84,88,86,81,75,72,66,59,52,42,33,26,19,20,24,30,39,48,56,61,61,59,56,53,52,51,52,53,54,52,47,42,37,33,31,30,33,35,36,37,37,35,34,32,30,29,27,26,25,26,27,27,26,26,26,25,25,28,33,37,38,39,38,35,29,24,21,20,24,28,33,38,39,37,33,30,27,30,35,40,43,43,41,40,36,35,33,32,32,34,36,38,39,42,45,47,45,39,33,29,25,25,25,27,31,33,33,32,34,33,31,29,28,28,29,30,27,26,25,24,23,22,21,20,19,19,19,19,19,19,19,19,18,17,16,15,15,17,18,19,23,23,23,23,23,22,21,21,22,23,23,23,23,22,21,21,17,17,18,18,18,19,19,19,17,16,14,13,12,12,12,12,13,14,15,15,14,13,11,10,9,10,11,12,12,12,12,12,13,13,12,12,11,10,10,9,9,9,8,8,8,8,9,9,10,9,9,9,8,8,8,8,7,7,7,7,7,7,7,7,7,7,8,8,8,9,9,9,7,7,7,7,7,7,7,7,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,6,6,6,6,6,6,6,6,6,7,7,7,8,8,8,9,9,9,9,10,11,12,13,18,18,18,18,18,17,16,16,14,13,12,12,12,14,17,18,17,17,17,17,16,15,15,14,19,18,20,24,27,28,33,38,38,40,42,43,40,35,29,25,21,21,22,26,31,34,36,35,30,26,21,17,16,15,15,14,13,13,12,13,16,20,23,26,30,30,29,27,27,26,26,26,30,34,39,46,51,56,59,60,56,52,46,41,37,33,29,26,22,21,18,15,13,16,21,25,33,39,48,57,64,71,76,80,80,72,60,47,36,30,27,26,30,31,32,32,31,32,35,37,43,51,57,57,58,60,59,56,51,47,41,37,35,33,32,30,28,26,25,23,21,20,20,19,27,30,34,37,38,40,43,45,54,63,73,79,83,85,81,75,72,69,63,57,49,40,30,24,18,20,24,31,40,50,58,63,62,60,57,54,52,52,53,54,50,48,43,38,32,30,30,31,33,36,40,43,43,40,36,34,30,28,25,23,23,24,26,28,27,28,29,29,31,35,40,45,48,49,48,42,34,26,21,18,21,25,30,35,36,34,31,28,26,30,35,39,41,41,38,36,33,32,30,30,31,33,36,38,39,42,47,49,47,41,35,30,26,24,23,25,28,30,31,31,33,32,30,29,29,29,30,31,30,30,28,26,24,22,21,20,21,21,21,21,21,21,21,21,19,18,17,15,15,16,17,18,23,24,25,25,25,24,22,21,21,21,22,22,22,22,21,20,17,17,17,17,17,18,18,19,17,16,15,14,13,12,12,11,11,12,13,14,14,13,11,10,9,10,10,10,10,9,9,9,12,12,11,11,10,10,9,9,9,9,8,7,7,8,9,9,9,9,9,8,8,8,7,7,6,6,6,6,6,6,6,6,6,7,7,7,8,8,8,8,7,7,7,7,7,7,7,7,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,6,6,6,6,6,6,6,6,6,6,7,7,7,8,8,8,8,8,9,10,11,12,13,18,18,19,18,17,16,15,14,12,12,12,12,13,15,17,19,17,17,16,16,16,15,16,16,24,21,23,27,29,31,38,47,43,45,46,45,41,35,28,23,20,20,22,25,29,31,31,30,25,22,18,16,16,17,17,16,14,13,13,13,15,19,22,24,28,27,26,25,25,26,27,28,32,36,41,47,53,57,60,61,58,53,46,40,35,30,26,24,21,20,19,16,14,16,20,23,29,34,42,50,57,64,71,75,74,67,56,44,35,30,28,28,33,34,34,34,33,35,38,41,47,55,62,64,63,64,61,57,51,46,40,35,32,30,27,25,22,21,20,20,19,19,20,20,27,29,32,34,35,38,42,45,52,61,70,75,78,79,74,68,65,61,55,49,42,35,27,21,20,23,28,35,43,51,58,61,60,58,55,52,50,50,51,52,48,47,43,36,31,29,31,34,39,43,48,51,50,45,39,34,30,27,24,22,22,24,27,30,32,33,35,36,38,41,46,50,57,57,54,48,39,30,23,20,23,27,32,36,37,34,30,27,27,30,34,37,39,38,35,34,32,31,30,30,31,33,36,38,39,42,46,49,47,42,35,31,26,23,21,21,24,27,28,29,29,28,27,26,27,28,30,31,33,32,30,28,26,23,21,20,23,23,23,23,23,23,23,23,20,19,17,16,15,15,16,17,24,25,26,27,26,25,23,22,19,20,21,21,21,21,21,20,17,16,16,15,16,17,18,19,17,17,16,15,14,12,11,10,9,10,12,13,13,13,11,11,9,9,9,8,8,8,8,8,10,10,10,10,9,9,9,9,9,8,7,7,7,7,8,9,9,9,8,8,8,7,7,7,6,6,6,6,6,6,6,6,6,6,6,6,7,7,7,8,7,7,7,7,7,7,7,7,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,6,6,6,7,7,7,7,8,8,8,9,10,11,13,14,17,17,18,17,16,15,14,13,11,11,12,13,14,16,17,18,17,17,16,15,15,16,16,17,20,18,21,29,30,29,37,48,48,48,48,45,40,33,26,22,19,19,22,25,28,29,27,24,22,19,17,17,18,19,20,19,16,15,14,14,15,18,21,23,24,24,24,24,25,26,27,28,36,39,43,49,53,57,59,60,57,52,44,38,33,29,26,24,20,20,19,17,16,17,20,22,25,30,38,47,54,62,69,73,66,60,51,41,34,30,29,29,35,36,36,36,36,38,43,46,51,60,68,70,68,67,62,56,49,44,38,33,29,27,25,23,21,20,20,20,20,21,21,22,27,28,30,31,32,35,39,43,50,58,66,69,71,72,67,61,57,52,45,39,34,29,24,21,25,28,33,40,46,51,55,57,56,53,50,47,46,46,46,47,48,47,43,36,30,29,34,39,50,53,57,58,55,47,39,33,27,26,23,22,23,26,29,31,36,39,42,44,44,46,48,50,58,57,55,48,39,31,26,24,28,31,36,39,40,36,32,28,29,30,33,35,35,35,33,32,32,32,32,32,33,35,36,37,38,40,44,46,45,40,35,31,25,22,18,17,20,23,25,26,25,24,23,23,24,26,28,30,35,34,32,30,27,25,23,22,24,24,24,24,24,24,24,24,21,20,18,16,15,15,15,16,23,24,26,27,27,25,23,21,18,19,20,20,21,21,20,20,16,16,15,14,14,16,17,19,18,18,17,16,15,13,11,10,8,9,11,12,13,12,12,11,9,8,8,7,7,7,8,8,9,9,9,9,9,9,9,9,8,8,7,7,7,7,8,8,8,8,8,8,7,7,7,6,5,5,5,5,5,5,5,5,5,5,5,6,6,6,7,7,7,7,7,7,7,7,7,7,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,6,6,6,7,7,7,8,8,8,9,10,12,13,14,16,16,16,16,15,14,13,12,11,12,12,13,14,15,17,17,17,16,15,15,15,16,17,18,16,17,26,38,39,34,38,48,52,51,48,44,38,31,24,20,19,20,22,26,28,28,24,21,20,19,17,18,20,22,23,22,19,18,16,15,15,17,19,21,20,21,22,24,25,27,28,28,37,39,43,48,51,53,55,55,51,46,38,32,29,26,24,22,19,20,19,18,16,17,19,21,22,28,35,43,49,55,61,65,57,53,46,39,34,31,30,30,36,37,37,37,38,41,46,50,56,66,74,75,73,70,63,56,46,42,35,31,28,26,24,22,22,22,22,22,22,23,24,25,28,28,29,29,29,32,37,41,46,53,59,61,62,63,59,53,50,44,37,31,28,26,24,22,30,33,39,45,50,52,52,52,50,48,45,42,40,40,41,42,43,43,41,35,31,33,40,47,62,64,65,64,57,47,36,30,23,22,22,22,24,26,30,32,40,43,47,49,48,47,47,47,53,52,49,43,36,30,26,25,29,33,38,42,42,39,35,32,31,31,31,32,32,32,32,32,32,33,35,36,37,36,36,35,37,39,41,43,42,38,34,31,24,20,16,14,16,19,22,23,22,22,21,22,23,25,28,29,35,35,33,31,28,26,24,24,24,24,24,24,24,24,24,24,22,21,18,16,15,14,15,15,22,24,26,27,27,25,22,20,17,18,19,20,20,20,20,20,16,15,14,13,13,15,17,18,18,18,18,17,15,13,11,9,6,8,10,11,12,12,12,11,9,8,7,6,7,8,9,10,8,8,8,8,8,8,8,8,8,7,7,6,6,7,7,8,8,8,8,7,7,7,6,6,5,5,5,5,5,5,5,5,4,4,5,5,5,6,6,6,7,7,7,7,7,7,7,7,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,6,6,7,7,7,7,7,8,8,10,12,13,14,14,15,15,15,14,13,12,12,12,12,13,13,14,15,16,16,17,16,15,14,14,16,17,18,21,24,37,53,54,45,46,55,53,52,48,43,36,29,23,19,19,21,23,27,29,28,24,20,20,18,18,19,22,24,25,24,21,19,17,16,16,17,19,20,18,19,22,24,26,27,27,28,36,38,41,45,47,49,50,50,44,39,32,26,24,22,20,19,18,19,19,18,16,16,18,20,22,27,33,39,43,47,50,53,51,48,43,38,34,32,31,31,36,37,37,37,39,43,48,53,60,70,78,79,76,72,64,57,44,40,34,29,27,26,24,22,24,23,23,23,24,25,26,27,28,28,28,27,28,31,36,40,42,48,53,54,54,55,52,47,46,40,32,26,24,24,24,24,33,37,43,49,52,52,50,48,47,45,42,39,37,37,38,39,35,36,36,33,32,37,47,56,68,69,69,66,58,46,34,27,20,20,20,21,24,26,29,31,41,45,50,51,50,47,44,43,48,47,44,38,32,27,25,26,29,33,38,43,44,41,37,35,32,31,31,30,30,30,31,32,33,34,37,39,39,38,36,35,36,38,40,40,39,36,33,31,23,19,14,12,14,17,20,21,21,21,21,21,23,25,28,30,36,35,33,31,29,27,26,25,24,24,24,24,24,24,24,24,23,21,19,16,15,14,14,15,22,23,26,27,27,25,22,20,17,17,18,19,20,20,20,20,16,15,13,12,13,14,17,18,18,18,18,18,16,13,11,9,5,7,9,11,12,12,12,11,8,8,7,6,7,8,10,11,8,8,8,8,8,8,8,8,8,7,7,6,6,7,7,8,8,8,8,7,7,6,6,6,5,5,5,5,5,5,5,5,4,4,4,5,5,5,6,6,7,7,7,7,7,7,7,7,5,5,5,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,4,4,5,5,5,6,6,6,6,6,6,6,6,6,7,8,10,12,12,13,13,15,15,14,13,12,12,12,12,11,11,12,13,14,14,14,14,14,15,16,15,14,14,16,18,22,24,27,31,37,44,49,53,57,53,47,39,32,25,20,18,19,21,24,26,26,25,22,20,16,18,20,22,24,25,26,26,23,22,21,19,19,18,18,18,17,19,23,24,25,26,28,30,32,37,41,42,45,49,48,45,40,36,29,23,19,18,18,19,21,20,19,18,18,19,20,21,23,25,27,31,34,38,41,42,42,40,37,34,32,32,33,34,33,35,37,38,38,42,50,56,68,76,82,82,78,71,60,49,42,38,33,29,28,27,25,24,21,22,24,27,31,33,32,30,30,28,26,26,28,32,37,40,43,45,47,48,48,47,45,43,38,33,27,22,20,22,26,29,41,46,51,54,53,50,46,45,38,36,33,30,29,30,32,33,30,31,32,33,36,43,52,58,70,70,68,61,51,39,31,26,23,25,25,23,22,24,30,35,43,49,55,55,50,43,38,37,36,35,33,31,29,27,26,26,31,35,42,47,48,46,42,38,35,35,34,31,30,30,33,36,39,40,42,42,40,37,33,30,34,34,34,36,36,35,31,28,20,18,14,11,11,13,16,18,17,18,18,18,19,22,27,30,31,33,36,35,32,28,26,26,24,24,25,25,25,24,23,23,21,20,17,15,13,13,13,13,18,19,21,23,23,21,19,18,17,18,18,19,19,20,20,20,16,15,13,12,12,13,15,16,19,19,19,19,17,14,12,10,9,9,9,9,9,9,9,9,8,8,8,7,7,6,6,6,7,7,7,7,7,7,7,7,7,7,7,6,6,5,5,5,6,6,6,6,6,6,6,6,7,7,7,6,6,5,5,5,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,4,4,5,5,5,6,6,6,6,6,6,6,6,6,7,8,10,11,12,12,12,15,14,13,12,12,12,12,12,12,12,13,14,14,14,13,13,14,15,15,15,13,14,16,18,21,23,26,32,38,44,49,52,56,52,45,37,30,24,19,17,20,22,24,26,27,25,22,20,17,18,21,23,25,26,27,27,23,22,21,20,19,19,20,20,19,21,23,24,24,25,26,28,31,36,40,41,43,46,45,41,35,32,27,22,19,19,20,22,23,22,21,20,21,22,23,24,23,23,25,27,30,32,34,35,37,36,34,32,31,31,31,31,31,33,35,36,37,42,51,58,69,77,82,82,77,70,59,48,42,38,34,31,29,29,27,26,25,25,27,31,35,36,35,34,31,29,27,26,28,32,36,39,41,42,43,44,43,42,40,38,33,29,23,19,18,22,28,32,43,48,53,54,52,47,42,40,33,31,28,26,25,27,29,30,29,30,31,32,35,42,50,56,62,62,60,53,43,34,27,24,25,26,27,25,22,24,29,34,43,49,56,56,50,42,36,33,30,29,28,26,25,25,24,24,31,35,41,46,48,46,42,39,36,36,35,32,30,30,33,35,41,42,43,43,41,37,33,31,31,31,31,33,34,33,29,26,20,18,14,11,10,12,15,17,16,17,18,18,18,21,26,29,32,34,36,35,32,29,27,26,24,24,25,25,25,24,24,23,21,20,18,16,14,14,14,14,18,19,21,22,21,20,18,16,17,17,18,19,20,21,21,22,18,16,14,12,12,13,14,15,17,18,18,18,17,15,13,11,9,9,9,9,9,9,9,9,8,8,7,7,7,6,6,6,7,7,7,7,7,7,7,7,7,7,6,6,6,5,5,5,6,6,6,6,6,6,6,6,7,7,6,6,6,5,5,5,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,4,4,5,5,5,6,6,6,6,6,6,6,6,6,7,8,10,11,12,12,12,14,13,12,12,11,11,12,12,13,14,14,15,14,14,13,12,13,14,15,14,13,14,16,18,21,23,27,33,39,45,50,52,53,49,42,34,27,22,18,17,21,23,25,27,27,25,22,20,18,19,21,24,26,27,28,29,23,23,22,21,21,21,22,22,22,23,24,23,22,22,24,26,28,34,39,40,42,44,42,37,30,28,23,20,19,20,23,25,24,24,24,24,24,25,26,27,23,23,22,23,23,24,25,26,30,30,30,30,30,29,28,27,29,30,32,33,35,42,53,62,72,79,84,82,77,70,58,48,42,39,36,34,33,32,31,29,30,31,32,36,39,40,39,38,32,30,28,27,28,30,34,36,37,38,38,38,37,35,33,31,26,23,18,15,17,23,31,36,46,50,54,54,49,42,36,33,27,25,23,21,21,22,24,26,27,28,30,31,34,39,46,51,55,54,50,44,36,29,25,24,28,30,30,27,24,24,28,32,43,49,56,57,50,40,32,29,24,24,24,24,25,25,25,26,32,36,40,44,46,45,43,41,37,37,36,34,31,30,32,34,41,42,43,43,41,37,33,30,27,27,27,28,30,29,26,23,20,17,14,11,10,11,13,15,16,17,17,17,17,20,24,28,32,34,36,35,32,28,26,26,23,24,24,25,25,25,24,24,21,20,19,17,16,16,16,16,18,19,20,20,20,18,16,15,15,16,17,18,20,21,22,23,19,18,15,13,12,12,13,13,15,16,17,17,17,15,13,12,9,9,9,9,9,8,8,8,8,7,7,7,6,6,6,6,7,7,7,7,7,7,7,7,7,6,6,6,5,5,5,5,6,6,6,6,6,6,6,6,7,6,6,6,5,5,5,5,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,4,4,5,5,5,6,6,6,6,6,6,6,6,6,7,8,10,11,11,11,11,13,12,11,11,11,11,11,12,14,15,15,15,14,13,12,11,12,13,14,14,13,14,16,18,22,25,30,36,42,47,50,52,49,44,37,29,23,19,18,17,23,25,27,28,28,25,22,20,17,19,21,24,26,28,29,29,25,24,24,23,23,24,24,25,25,25,24,22,19,19,21,24,25,32,38,40,42,44,41,36,27,25,21,19,19,21,24,26,26,26,26,27,28,28,29,30,25,24,22,20,19,19,19,19,25,26,28,29,29,28,27,25,26,28,29,30,34,43,56,65,77,83,87,84,79,71,60,49,43,41,39,38,39,38,36,34,35,35,36,39,42,43,41,39,32,31,29,27,28,30,32,34,34,34,34,33,31,29,27,26,21,19,15,15,19,27,35,41,48,51,53,51,44,36,29,26,22,21,20,19,19,20,22,23,26,27,29,30,32,37,42,46,48,47,43,38,32,28,27,28,33,34,34,30,26,25,28,31,42,48,55,56,48,38,29,25,24,25,27,29,30,31,31,31,34,36,39,42,43,43,42,41,38,38,37,35,32,30,31,33,39,40,42,42,40,36,31,29,24,23,23,24,25,24,22,20,19,17,14,11,10,11,12,14,16,16,17,16,16,19,23,27,32,34,36,35,31,28,25,25,22,23,24,24,25,25,24,24,21,21,20,19,19,18,18,18,18,19,19,19,18,16,14,13,14,15,16,18,20,21,23,23,20,19,17,15,13,12,12,12,13,14,15,16,16,15,14,13,9,9,9,8,8,8,8,7,7,7,7,6,6,6,5,5,6,6,6,6,6,6,6,6,6,6,6,5,5,5,4,4,5,5,5,5,5,5,5,5,6,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,4,4,5,5,5,6,6,6,6,6,6,6,6,6,7,8,9,10,10,10,10,11,11,10,10,10,10,11,12,14,14,14,14,13,12,11,10,11,12,13,13,13,13,16,18,23,27,32,38,44,47,49,50,43,39,31,24,19,17,18,19,25,26,28,29,28,25,22,19,16,18,20,23,26,28,29,30,28,27,26,25,25,25,26,26,26,25,23,20,17,18,21,23,25,32,39,42,44,45,41,35,26,24,21,19,19,21,25,27,29,29,30,30,31,31,31,31,28,26,23,20,17,16,16,17,23,25,27,29,30,28,26,24,24,26,28,30,35,44,57,67,81,87,90,86,81,73,62,52,44,43,43,44,45,45,42,40,39,39,39,41,42,42,40,37,32,30,29,28,28,29,31,32,33,32,31,30,28,26,24,23,20,18,16,17,22,30,39,44,48,49,49,45,38,30,25,22,21,21,20,19,19,20,21,22,24,26,29,30,32,34,38,42,42,41,38,33,29,29,31,33,39,40,40,35,29,26,28,30,40,46,51,51,43,34,27,25,26,29,33,37,39,38,37,35,36,37,38,39,39,40,40,39,37,38,37,35,32,30,31,32,36,37,38,39,37,34,30,27,23,22,20,20,21,21,19,16,19,17,15,12,11,12,13,14,16,17,17,16,16,19,23,26,31,33,35,34,30,26,24,23,20,21,22,23,24,24,23,23,21,21,21,21,21,21,20,20,20,20,19,18,16,15,13,12,13,14,15,17,18,20,22,22,21,20,18,16,14,12,11,11,11,12,14,15,15,15,14,13,9,9,9,8,8,7,7,6,7,7,6,6,6,5,5,5,6,6,6,6,6,6,6,6,6,6,5,5,5,4,4,4,5,5,5,5,5,5,5,5,6,6,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,4,4,5,5,5,6,6,6,6,6,6,6,6,6,7,8,9,9,9,9,9,10,9,9,9,9,10,11,11,11,11,12,12,12,11,10,10,10,12,13,13,12,13,16,18,23,27,33,39,43,45,45,45,37,33,26,19,16,16,19,21,27,28,30,30,29,25,22,19,17,19,21,25,27,29,31,31,31,30,29,28,27,26,26,27,25,24,21,18,16,17,21,25,29,37,44,46,47,47,41,34,25,23,20,19,20,23,28,30,33,34,35,35,35,34,34,33,30,28,24,20,18,17,17,18,23,24,27,28,28,27,25,24,22,25,28,31,36,46,59,68,82,87,90,87,81,74,64,54,46,46,48,50,52,52,49,46,43,42,42,42,42,40,37,34,30,30,28,28,28,29,31,32,31,30,29,27,25,24,23,22,20,19,19,21,26,32,39,43,45,44,42,37,31,25,22,22,23,22,21,21,21,21,21,22,24,26,29,31,32,33,36,38,36,35,34,31,29,31,35,38,46,47,45,40,33,28,28,30,38,42,45,43,37,31,28,27,30,35,42,47,49,46,42,38,38,37,36,35,35,35,36,36,34,35,36,34,32,30,30,31,32,33,36,37,36,33,30,28,24,22,20,19,19,18,16,14,18,17,15,14,13,14,15,16,17,18,18,17,17,19,23,26,30,32,34,32,28,24,21,20,18,19,20,21,22,22,22,22,21,21,22,23,23,23,22,22,22,21,20,18,16,14,13,12,12,13,14,15,16,18,19,19,20,19,18,17,15,13,12,11,11,12,13,14,15,14,13,12,9,9,8,8,7,6,6,6,6,6,6,6,5,5,5,4,5,5,5,5,5,5,5,5,5,5,5,5,4,4,4,3,4,4,4,4,4,4,4,4,5,5,5,5,4,4,4,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,4,4,5,5,5,6,6,6,6,6,6,6,6,6,7,8,9,9,9,9,8,9,9,8,8,9,10,11,11,8,9,10,10,11,10,10,10,9,11,12,12,12,13,16,18,22,26,32,37,40,41,40,38,32,28,21,15,13,16,20,23,28,29,31,31,29,26,22,19,20,21,24,27,30,32,34,35,34,33,31,29,28,27,26,26,23,22,19,16,15,17,23,28,38,45,51,52,50,47,39,31,22,20,19,19,22,27,32,35,40,40,41,41,40,39,37,36,31,28,24,20,18,18,18,19,23,24,25,26,26,25,23,22,21,25,30,34,39,48,59,68,80,86,88,85,80,74,64,54,48,49,52,55,58,57,54,51,47,46,44,43,42,39,35,32,29,28,28,28,28,30,31,32,29,28,26,25,23,22,21,21,20,20,22,24,28,32,36,38,41,39,36,30,25,22,22,23,24,24,23,22,22,21,21,21,24,27,30,32,32,33,34,36,35,35,35,34,34,36,41,45,51,52,50,44,36,31,29,31,36,38,39,35,30,28,29,32,39,45,54,61,62,57,49,43,40,38,35,32,31,31,32,33,31,33,34,33,31,30,30,31,30,32,34,36,36,34,32,30,27,24,21,19,18,16,14,12,17,16,15,15,15,16,17,18,19,19,19,18,18,20,24,27,29,31,32,30,26,22,19,18,16,17,18,19,20,20,20,20,21,22,23,25,25,25,24,24,24,23,21,18,16,14,13,13,11,12,12,13,14,15,16,16,19,19,18,17,16,14,13,12,11,12,13,14,14,13,11,10,9,9,8,8,7,6,5,5,6,6,6,5,5,5,4,4,5,5,5,5,5,5,5,5,5,5,5,4,4,4,3,3,4,4,4,4,4,4,4,4,5,5,5,4,4,4,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,4,4,5,5,5,6,6,6,6,6,6,6,6,7,7,8,9,9,9,8,8,8,8,8,8,8,9,10,11,6,7,8,9,10,10,10,10,9,11,12,12,12,13,16,18,20,24,30,35,38,37,35,33,29,25,18,13,12,15,21,25,29,30,31,31,29,26,22,19,22,23,26,30,33,35,36,37,36,35,33,30,28,27,26,26,22,20,17,15,14,18,24,29,45,52,57,56,52,47,37,27,19,18,18,19,23,29,36,40,44,44,45,45,44,42,39,38,31,28,24,20,18,18,19,20,23,24,24,24,23,23,22,21,21,25,31,35,41,49,60,68,78,84,86,83,78,73,63,54,49,51,54,58,61,61,57,54,50,49,46,45,43,39,34,30,28,27,27,28,29,30,31,32,27,26,24,23,21,21,21,21,20,21,23,26,29,31,33,34,38,36,32,26,21,20,22,25,25,25,24,23,22,21,20,20,24,27,31,33,33,32,33,35,37,38,39,39,40,43,47,51,54,55,53,47,38,32,30,31,35,36,35,30,26,26,30,34,47,54,64,72,72,65,55,48,41,38,34,31,29,29,30,31,29,31,33,32,31,29,30,31,29,31,34,37,37,36,34,32,29,25,22,19,18,16,13,11,16,16,16,16,17,18,19,20,20,20,20,19,18,20,24,28,28,30,31,29,25,21,18,17,14,15,17,18,19,19,20,19,21,22,24,25,26,26,25,24,25,24,21,19,16,14,13,13,11,11,12,12,13,14,14,14,18,18,18,17,16,15,13,12,11,12,13,14,13,12,10,9,9,9,8,7,6,6,5,4,6,6,6,5,5,4,4,4,5,5,5,5,5,5,5,5,5,5,5,4,4,3,3,3,4,4,4,4,4,4,4,4,5,5,5,4,4,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2 Sigima-1.1.1/sigima/data/tests/image_formats/fiber.jpg000066400000000000000000000523461514013333200226620ustar00rootroot00000000000000JFIFC    $.' ",#(7),01444'9=82<.342  }!1AQa"q2#BR$3br %&'()*456789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz?((((JZ)h4bP)H4\uR:5 \Y})F)(5&dM$Yp)ɧ'IɧGvU7z\Rb((((((((()hS")Sfa5:\Rc=)YxBiM>X Z3⯤cnj)H* /H8*4҅\SS94M"IIEQKIEQEQEQEQEQEQKEQE-(RE(6gE$c5.1LpsS1MpԨs4/Jl ZnZt'c`Ui# RD 8B݈*)T <*B!cRdPW34QERQEQEQEQEQEQEREQN4\RO J)icך{(aSG:S$O !,`ҔHCRC_m<"jVzWIDye42^iآOksTݣ›`ȫ2+J QXrj/-H+*!`0*q%]T!M5)c94JLRQE%QEQEQEQEQE-bSH"E)d tTlUmīҒ[-Q rB㊚Ԥ;Ԛn\ gZq ;{S'Dq*ͬ7JdܭZ0kcB.e0>#P,n6`lnT:h[rpțA@-ǚEȭ {p$`TR j%&bO i:Aw ZbsKbǽ1vHPev)Qw b=ibQIE%QEQEQEQERE-(K1SM <~YϞ=} ֺ'B +SYXf/1ҹiL22ͺO nw75bHwE~lM\ҵj֧w29ݮ4lW-kl4Te皒K $qToP(˚ HZt[ڰ iY_nr*춅ʞ՛qqI8tu$>Yg W"d ۱c#u;ƻ.O\ (E qQda0w )+S9 9~ .86J(((Z)qE-8Sǥ?oZS #">^Sw"8r hLP\ڴmȤ,=(Ae1}kM{ʴ)\W-b{k8*-Vu=%_ho8Y$,[GQWt-qQ3c[1\88-Ԑ]L[*4ɓZkZVjFS4~c֪wjib\nfg8xpr3V(~ag\j F$ #Uf95Y 41ⴞ DـMcM̄V#{SU5!f`%!i3)Ȍ947Ii>O#ԛRy7ZV#U MP MIEQEQE.P)M865qUm'3]=cIm6?7QXoYA Kو@YBǭg֧Jc= M[b{U]Y LUZfl D⭥<؅SȪu4 椏zYKvBzOHJ9" GS|uja!LS%QEQESF}Vuz_9-YqP%ЖrvQ޺y?Ui7 ] VF¶v d=N5$I&LCͅ"EDÚm%%QE(*`)xKTx`+UWz@CYQtIڨ&fBqN!M7Bv!bͦ'*+$w:]DbE<4\zl7R3ݩcO>ј047l@!da5f@Fc^O,wc֙ FqV|ޮxfo8D$5iҢiՉq8I).UkH S\$Ov#'kFB `$KsQYTv)BK Vl|hwNի%f2J084*uC$QO8ZpCT29i֪HH3R)XT,j&i((Z}!Z9>1ɠ 6"3DF:ݶvJ::sM'nߕA57Zmk4KNxO8`zWayHnddiP#cH$H8ȭY#6{fRQ+*8difZ6:Qm#/8aRkhrVw MI!6. Cn#G.sZiOⳊg h6qN<ۃT|ZGqV-Um\Yoj k#ٝyTOƵRli:tQ*3Bx4iŲ*3)4M"J((SN O5 SNu5!Π$H=X+F*8.-e՚0ˆm'76x - ^VKuI{8Zt,C3>X=鷐8aV7SÎEC#8&fW ,I \kmox+M2ۻk7_E|k5I|&<)S9͌=*K{$8j5TӘ(a:yr>lVdRDTSR@Xk!3p+BYSjˌҖ9ZқPTr5_FXV"ԇWmA;kfW2ڈ+ m,{YcK3[YUvxZ-BT0Y0 ޫNR#$۴QGӒwa4gQg*P!⅁ɨ" 7Ⓤa5piQIEQEUDM)0Z=)HiyRQIEQEU\Tjj%rԊKS2O4(TJ*:j^wn`ֵ`@kr͢=qT4_ѫloՍCfPvɑStmLWi g%j >\5(AOQ9xGZ;jKH5i-Hڶa5sqs1N( ɹ>hdR[b,T;T/) M38w& *x').Jl1֐]2nWGREm$8̢€3M[-ulsu5dt6݂x8ҮjQACV4=b8ϵ@y-6xfbʹijDv&A#99*Hք6r\)* Ki_[6IQW-\ .sC"ȐA" /0 O=c[,˓jܚZPH#ȧ3g"(bE2{qNX$|)4 ނjGj[q%TM1jȎh^qTlH\sS4 )[ iF3Lޱyo'o-I՝>͚p$_խƐUH5Mvl^%7sUS} 7&bnZE (D5Kn ^֤7om^YOƻKq*XnL!P7i MF`8xJިl#mOkL3sMc <+3!N)P}h a DYQƟ.*Zi0i)((5:@ dsPIJ#b &¸"O\y끚deڠg-!-Tgž+F$uV$"oh*Ɲ4SN!E_&0"V,l`zY+~wPԑbӹ!XM?3aV}&!n>A.-pJ)su.#{mrS&D֯XŞC,bM͊q7z"gPYy"#@jږ 4\*2`ǚ+ҥd{|Y35f$J~j6|nC;O᪷Gm>~ ]cRPi<r͸u$`6$:ؔ o1H+3sy/zt2=8%KI * Y-tB˴i[7bX/fc;L$J#TlsM4IIEQEQSO EH39 0Eqi*x!5C!V'楚NpUyt1wFsVKDiOֶ.=>Yioa5gP p*W`Fj|nJ0)+mѼp)㚍ܠ1橆?jQ3ZW3@6e$8ZE;i֒[6ia/5B{3B#!LwI* x c޷4Ԏ:vs"FcD*I&QQ֛#NlLO̐c4zƢB(7v8.NM<R}8dEm%QEQE^TɧYFhA¨fxxjlEZB:S&25k\:HnM9u9=!ZIBʧmm]V0u5l10Mw*h"OTI|J5{ȧTpė1BȪIz\n>zEnw|"$%jMn'h5J&pZ[P" +EAsA5SݡRG&,̧O$R[EE%Ki{ULҺ]d˓io23YrTwQvŠo V UׁT预:Tv6rj\Q^Ngu"2vp*P"$j6K{S5~RrMݒ( 6NN* h˜q$k19^B0II 52[GgجTphZޕTTw;Ep)# 1Umb$f$Sޫ)MM bKhdqQe%QEQVE8S}FGP^N }ULu p*.=)R_a5J)(( Ӏ4!R*Hny`ײն,5[ s]6gq1fs9hɰu4QME @&w1ۿ8erR[5cTrj:c[^MW5_C/$W8JP\6ZګWZB;"q3W7/$zսG_76gp1[Oy4Q"ҠegTi.h$O*oqUEF*n[,hyQf+E!g [յuW vdrW5Ilfbzh&c1lhn#,UhVT685$m_g4~zT72ǽAӬXRKMA(uaT2HF:TA~0KQMrӰZyPZu2 c֕/YjwA3dǘr.k.;.5jY"]Rj -M2Eg\\3fh0YUb$/"o,+/s*:gjRnXsҖP[46%Dɩ2Lvi4FG4HzQIEQEqiR*3UȭqV}*f'U:IAidP{W}6YC]NXtKoZVZ#WX&e\%-A خZk]Ig[\Tdt]FͷͶ/ $Q'K{TZz|k EH;m"b 1? kh%ێ o uB_[Ÿ#5JJV/!Q ⣑vZ)M.] Ip^۬rAQ9PzTvNd- U."xj"G4٠TfB+%֍8iڹ̶˒yܻ]Iⴙ& FVug-#]=-s5걱lj\'<rjջ="[ 6Nh2S[nX ciP*,ӼE 3S 4RQEQE]^:VB7k1ջ{7|سd]zVe{WxsPAMp8k$ơTv(/nG ^OPK12jM:32qU-Ɂ{qXxQӴvV[»aqȮ#5]C47EZ]?Zмd6PG(o!ckv[I3s| ͸ę 2޿p)eu cENty"`mQh*vb Υ^Dm:V=>O&+ zԶ>*žԟp*T堌i͸yF$ TAvRO47 ͨ8PTs~QHJqp!5 iD,g[F3R-bri&,P4q0*9- ٪f+Q8iqIi((Ӏ4IXYȭHu59^+4K(*͊`ehTLTZ!iU\.9̥lb/zൿ^JV=%w{%5Ief;Y3o$۩5]}Qte'@8\{o=*ZlDToL՛(Fp+3msZ6xr[U ˁlLhU[R_1)$e*KvleEžiЩ8e/#߷b}5*7cez[e䅪 ^OlXf^H#8թmSCsMF#Ki0ճf-c+6䬒tRLu$;j&8Hl)sA44J)((T3W-Ӛ׶P1ttj̻dT+V-o 0kNhk>< .J:[DȨ`84QG5<:i]72n^Rr&H2539$UǑ՛xz$ Uİ8 qJ4N*iA۬I?J+9 Y穫 AxV˶68-4rc5f7CLLdyd+E:U*Ϛ$@1R:˞*3Ujii)((*jdLU+UUi[ji9$ZMhNf2x~j3d26vSZY<;gb >Ygִ5k+3k&zW6f'cTQտ?"VuFk.92 椺!P[Q΢ox&cpi-\IqZo|`k&cqI=rwj.DjmLf&>eC<1P71oT7S=ۨ3θrqPInqLKi 'vP^?XkI(XԱ JZVA՗fWH=,HLe֪駒fUSVMC5Vf-̑ެ%'Ʈوr3Um5N;0{wx}iiyQ)# znsHM!IEQEVeYIN3ޅqRy&`ns4ޘjU]ڴ-TOUZK3W|Ȓla }ͨf''ֳ.Mh -«-hZT1Hj{Z=ҊrűOnՙ N֟$7~*kd)`1j9j(pNdW$ڲyW2ii2$2nlV֧hg%Ml*Hƣ.iU֚piiRQEQETԊ2jh3VIJF暬E(%*P U&*5/ٵE2;LhnZiWsV cx}+!4Y[Rhˀ2[[t/Y)|`v!aW2ӢalrkGedP2+$= l$ YPy3֖lYq,gq) kjJBFXpnd'5cI⠼w?jf#<ے;Q4ҿ-ҍ.'˸UidiT^LeIWJVXd*9 (*ŭȼi4RhsK"c5FH9 oJȶs0 ~ZUMnxO!k\Y\XW0P-(隙7E=) H9Ubڂ<#areL1[J9ju៌p)gmn!5VD5ǷnFzVGsʆV%h R7R]Uu%G"nWh43sf2V$|ːjBM334RRQE%QEQE:Piӗ;PrjUP9wHOAnK7vH&ivG;aS r8  <չDR-ÈpIg݀q35X1 ޭmpW{C4Y\ޟub[0j۬.+^Q YWT;EIozYG_{UWB<޵N;h؝Y4B2i XdnQͱW5`ۛY1Pϧ*02TyD'vmn&]؈9kLLNvGYrVȫ1sU,I~:aPšV\`Ӛ]r D FpzRuQ0i))(((ZZQNؤMM)DyՋhA`j̰{UWɩԌc5(6T 615#Z[5-щ;T9Bzn,L!J3ۂAS*Ksjfyڕ;E(\3f>_c#5$6p* w&H]6*9W&c͖EvxjWK7ޠsMFM]lْ+VXf;0ka5vh:ӌ8mICjd]S$P#GGmqV;}sZ7dB{y -r'e,k2C<3cjRKYrjp9: <̑ K܋{ڧԧnsVu(miXh;rG)Svi \/z#SCkvS-\V77ZwgH !Ҥo:,rX;NIk3_W;k^Y"*G+ɹԑD*R'f^IR3WH{@ʆ~EqYN8H2OCQdn7JU}zN@4ꈚCE!4i)QIEQEQEQJ)nZɁL RiK@ʭSt T-H,gkOJ?cҨ@I:M"%wq*H75su| RqGVc3 #֫;9T#,8vyKENѢuW54qi7u#,[+5P f! Z:x@bmV|PGi:[^+0ȭ[J)hJ'Yb;VInbۖItSNъhy4gJd*/ld MHT3/^85 F۩N)܊~8Ȧh#4Km4Pi(((Z(p):֞ 4h IYMI fPmT@ K ms>>$i⣞}G"C*fpjK{-⬥K4PET,AleqUČvd[Z<f5TK[i%js?8ܧ*x@nn*ݭ?Z.Ɍf2°皳a( R -SI3@r:T9iVsj#qc\C(x+um*@H欘׎\ 'ZLOiIIE%QEQEQE-R)iAi۱:5c".zըb*mZMiDh)I>x8H@X1ɪPf5X'C ˲3֒ H%Ws\V`}#UŸx Kq".#lFX3:V.]MCd<6z֕GFjvL(kIt$fk23@5N5'4#nv ^*mՄ7xl4L)fwC㔫+Iq4yWu pjg"54xN4ܑHM!4h&h((()hS/4٩SԱMIjC#?Ş j)anNv槂&f:Է7 c\ j\=)`EXlYr)%94$paXsLIsVY\Tֱ+5XLg ]KFL`۸6 $SԦ<*ǘhBg,x- :Tc5Z}vFaWy6qg܃Rpќg|y889۸ca)(((((4i&yRƹ<8髖5*)4tt%Q{i!e ҘԱ]fy&yI 9ZǸLwzԢMOHLҦͻor@xi\ nEHR"X$ B$% i+8e-?4_>^f߼ +j\/! uGdwZzPO`yY&;OQ^4FlUB 0#inVG'" 0 :OYYYa&~`e0ڹ쭮u-GY'#'vI[f"\U64;k\[u ~~AWA[ $4TS{՘؀O&rW0vA.%'H, l;O U߷ 䬞n}"z+ց m]\ S²]ƬjzeE K}ij{1[LO9%Y>s7܃˚;Ծh:8~cL %6j T"񨐤Xѩ[Qy0"^ØQ*9Y9Xer /UMr_2 [ɾ t-‹F-~%[=+yƤ+zJV#`UY 7sb3e@HZ$8P <F7qGl.Y&b[ku`sO`[ޘc2`s{;ʦ:6$= އIZ8k≮<}9U W/umILj&/Z]% NTBo[=K[x6s V-ϙ1Hh>jv{GZJ-) "ڿfb4輾5̨W:D/o\%/u>XZz |@uR}^fM[+zZ{PK2QKY̥7/0m'qn/+7y@55(@ %hF– 5PjB&/I6zBai 1\Ty.NL_h^$W^o;)0zQqKFJq)'nSURj޹ߠեZ:aE_0(uj)MTV)5 BH( `h55IA)&Ε<$;O5_w`cYEYʍz#ӜuIYub|?O!Pk^qksE<`N`yϒXq!ROclחͣ~ƨTx~9()%*5Zc\g9.|F*˵BUgoゕ [iϷxJ'ZNv.KJ{oz= {ɨoO`^u.8IuP,ϣyU-"ҮYF8Lprp"k VW}3Ga*H3a4Gy6DX(dDլk6ށmi͓Z$n48AA[u­-[Z_IwΊ4sms:.;Kaߵg=$1d_,|;YF!ofwb4x:ɔf7ײl!uQxx>B Ux: ] C:(AVHIvy{61͖|;I6rt\gfa>S:1/÷.F3~2},*lJh7*8u6^CvvSN  c[ҰZ?y Lj'U5dy"0R0kn2]:31U+Ă!Ɯxj%ЏZKS+-jlX\ALYW:HPdpRlE= ;_ sε{!L F3Zڼ`_PIsfbupdޗ1f;o(aYj6Mbltn䙖 KzvU:bv|-.p&(`wR.IzިwX^';X:YF:4}9q2&Mm}j^S\=ϩSYV͹JOI&>@,8h9i78P8^%0%S*&]:-9S50ې&9h{W2`Ɍ ;ٍH.9)ymyc-ud_o4mQ'{뽏X7D[Lɟ_ X;{z6d0}lO8yYef,4l6S59vsQ4O 4\ & 'PXZ%I}SECħ2qI/\G/Z2N%pK7BpbtD7 @c9nY`}7gߐГ͹vx+9<, I7lNb D5;!kw$KQ4K X%Է$TUպ4BHC clF"Av|8Ҙ FJBaI5Dʒ̩͛ Z(mL7JU^"j?W,f.>sdBmp硂7ol:FP0]N;{hPnt5DUa4Xا9bf5&M f_[ԗ544,^*Y+wZl,ZbCjO$W[sN\Rab'քj"&^RA7Ϳn֛W(|\H7?j7 xPhsV\渷Y0fncڱT-ie.c@^9pcu3ȕ&zV7[L*eqj64o)D?1JXIĜfKLO;߮>y+ŔoԨhr^c~Loߛg:+FT'㫢nia!s/nr,jR/ xZW7cʌQ;4p MLѫ6,;a&g )L&i462:=d:`#ܜN$*v}^$& L0,"q{FF\.e8w/:IX?̡J!zPݼq}8M3/UM덢2A7H؍Vp-vX$"xC ^xnϊT_%ӛ]~:X}xc pycoע/!$q[.U9}#e~C#!RξZ3g}ae5iPy ӀkA0)wۘ3OE%/*;P^\dꯚDQFILM˕^_0k|ūꋸV/KaQ&NspGOp@Ee_,z΋i\yQUL2Șn%{q%pՍAR (7 $MOJ)$seg)/>N*(!T}`EI1d& )0.{D5dq[& ر\5hIٱV\~v,- %#;|O ěD p0A钀YĦMdJ.)$m2%a#,jW;oMG: b.;915DޫrH+X2 }ھVG<.mܺsF|#),S9]8i7f-~iWFn*XN4["qƅ&jp.>Z,J6-or t[LK YNfʯWk?-4<)Ӫҽq\\H0gupϖ1/gN|zBs8H:'Kk=LFr0YJa~s/$rMg(9Lteacc.-LH0QPPL>dZfy@:bLhɐ)#;N? ?s zqzNthq@'O$ݍN@̠//fMQ[M[x.#Kc/'.3ZsTZ)B,~}ÔbYfd 0\MPk,,3f(MݓTZ( #9`,7) 6qP[9#+?iW U=Mn cLŘUI=ZӮ^co.xǤkV}iܛPt(E'Oܤp 9=5hnmi\υUe@Ni\LKe5JJ_zg$qsD1Mn逵ܚ}A ,okùVcKfdRX9aM~Q7dV<9&4Yu+9w*3qe( fA阃 (I!! jQ?$EJ2`DL*am3{L~WoΓGzSH/]uKԻMK^BмVvU)sra0'Gm貘%֡gūq. OV0r`=JȢ0d)$YyA"͚ BP I!]h'kNԙ,; )頹[#,-9ߚ.xTa$5!A&ﰜH /AU.ŽG}17wYM_\ΝGo$2-v9/ݰh8$La1 5 S5Ct7J$y50qGq.2jQk'CQ>f ].ּ(/:(J*OE|þX;߿ȝw26.\xe j[A*.ŚIX$g 1(@ e)3~(f1s^ D2kpI6o͈8#YZVw i<34 đ8|aDD30\ՑXkqdq$rgh2)d2/yW*asi+dOzJ<Ë`s-g<,g roo$aῳX߂^{L" /Ej쉵7.C2h`9Ȱ9+ 4qȪҚ;{3#Ӑ6pHt+&`)K@g!i= KY&gH mk5UOL z&ՒLc- acRuzݸw5rEJN\9Pދ F6c3'` ߤPS&O9?+$T-gN{?m24#2? XԅO:`N4&JLɠjfB`Ppב( yuഄy7Æ AeO E*_mP Fc #I&#*Z˅h-К@j5^k nB]p, Dnumf%/gExI~kvZk]-@!))}pA%X*17: jFʱF^L r~|3 tdg\ $AOn*Xt3'̈a{f&eIga*^y5?R/8jIq9cH٢r8Uo*/o.XzSfpչ]bDXJok],o׉//MM ކH #ʌ"F65sM2N=!1၌b24"J"P jV R²r=nEJ߶Yl}`w k$7:,xNdgwu0YmMԌ᩺z~}1d`w?Z&}%hbg7 B96´vPI a8 ZPjO DԜd>՚*I6[TS/(̒J l-0$%c?- p9I(k@5&iⲱR!ef"3d *-N"A9xQdUfM [J xoqE N/ιI-<>Ћ䝗gDr/Er JO  ; 4ۇ g-Tjyq5c^qFԼ!衐Da)$$;S e"TlA$:qIbf`(T(ma~DTHB }/7=.fwЯ}S\#.V]%:&GJ<h 4̩2s'Dluie'.>Z=#))KgN˨;4\ZH>JDOtqC zPi^lX"I>>O)ZMIҙ@V!zki:'*faLnfpIEb5KM)PO8yg+!KwOa[觅id`Qj0*=O[jDQ&d@4_JI%Ðn|~;;{yn.\`MY@ڀH ̼R2 n<]H4U!!*o˳tX5)yYES nݜoҼp <ߣ l7qD3i#TSQ{"i]v IfWa@Z)$ A Ch2x_%6f)̜R\nWWC0c5$ ,]| $zQ[0&-c!YJ^ť(8qӕT@h͞ߔ74W+k;YDto=-A:F,Z?pݎG3'"o8s:˲9RBJe 75IMCIG#c31iCƬî%)e8AA7w7hn#ɴ#-iaae'dpN8&es8kxNyR+|į=ޫizQ?ڮm%"w%sb9g߿ ЇO>oF!qHNcZ9}d%/%0#ƯѴd/nF+ [uCJJBt4cG$u B(`8:ظmLttD^ȡz2kgqh aĝ\K9Nd a{ƕ?-7:l!ލ+ ` c}.^\ZƩXh0]ce^S*#o_BrjrZ#RftoC'䢁=p.N}k@2gs(5YoP63[782CE$#F43ÚUt|A_~:StR؀%MTVHD5.B}kF| X7)o{e\+3!V;u62Y}.Oc˶L>p˜T.Kq|XW=oa Pb紾0k.BLG@*8aPOeTWѳQ{s*́ l:Gt= {7")sQhL=O0Of YԀwlǒ(RSrV.g:0Xxח+nD NqV%вoy3Υ[+gpc:p^1 A-* ӽ-$:`$H1YDQ&ֶM/:ۡ8HۣuM ?MB͏czʺQ331v;$/f4]-:1#rK(IzkZCt'މgzh A̛ t{b%PgxfH fn;.^t[NƴkĻ{䞈׃x)f8СbFT5h]P0mLT\:܎?ϑ(%& [^%E,h޸vy"m/cM#p J&|kM/Umխ_K˻eƃtˋXs*|f!k'/I Xi&- k 5VeyV5f StX*ȡW=Y`E"?:P2jC֢g 9]d*=Sɍ͝?)-Qxh 7-9Ozk WBiqJ\i;"?#Z mPZRHă[qfРݜjLݤBӢ[+LކKЪri5ϛC/" sva3"O%H,Cr ȹ-l,z$i&%G/g^${`lnmfQ#m۲EH!e+G 3:ܳY[dl"NpȞ?d|!d8rBo޸={̼t=Bv3(fvjHa [=SY|o ȋv@T8AȴԬjL2 :%Qx]OFr5[Z&J\싎V_H;[c^XwL1:,&J+, ?8i<&=@mAY:hx#òk{36e"C26Ex|BQ@@am,k֧=#3x43Ϩ]am{>[fi\z{GG{T:77>0)(Rx;S9װBnyM&Xuy|oW6࿶oRoI_rl 2w>=ɛLxrk(e#hldK3U1/zM¢ER7Ьlu=#‚0ғ֏ңǎ1ltni)d$}CNcO2g. aѓCc^F:TH X֕ua HV\9bOW&0L&>rV'͵++垃5Ia້(s r\4_}f5垸R([:a#DHZz03`U;I2?"p#}CУg6dޑ :HxFx̷#4aѻ^~S=C;3Zfڣ=6SwkB;֘ѻN2LB [m{z9 8`14\Fc9L9:>C7UZ_1PRljҬ+l׾.vK |/3Dn2ZҕEt4!2hqk/RAiMfVYhd47gZKfs࡞M2Ҋ[kLy4mɌc<:weP6[Nf5i3c%whamPf[{|`I=kċoa/ /ǵ7:6ܼSR>zuד:~>M첹ˆ_q{ 3y~Lyz % l41'̲R#-Ǽ܍Dxn:FչMTnte#@0Z{ʬdP$GJI&`y3e<2"٤L0(yYE>-o_o曄YkfXҬ\,S$6+/\ʜkv`IW鉕,J1'n`ҝk/Z=%+_7KI$N\yu)UT?ɏZfdSd.'T(R@NcX#HkU&wFo~ܡ#4sU MZ==Ce#Ձ}HWz[[Ғ'2Rpmk?b*zkk8rvmicA`xu?.11:jy~߀o4%oy'8ݸ Iӎn [Eǵ{L|x*ą¨h0fbTFj9ݘ@VdAJ&I &lLѐO#qKP [\zVٯHb0b*l|:UoSLCZTk[{(o"b;(A1P[{lGسw*S!5ãq])t½.LjI`9@۞?i}/71@&r.G1-sXVA+w&%}kkD?^NdQ4ѬoXs]YLIxA7(yy湾9J|[PuK\,:^^<:շvs73?r8<rnM"}fťZSeBEǘ|kaF0m{&LI; Q!hYޤl{DEHG3e=sI5cs/Fk'h4sF+&C]6r6q >)&%d& TFϕp[v K[{,ԊNV5^ϯn:ywѽdu@N6 o\҆5p020<0d0miW42_Kpg4\P,VՅ6T$R]fGSio_? =3}CBq*U i_heRJ@&7Қcxy_+6%q3S቞p1co۲\p5ҷ=qDqu.y=m;2 o,wo]usd,X6z&ZZ!Ŧ%h:=[cT?R˫ e"tt`D9QE9d^ jQRI:RatEXSZ/`*<Լ[#ZTc羌5TC#]ץ,@9]ȣky(?2 /#{ rY%7LhhΖ贔dM#mC'v!jzm-o?_?0t f,7GpWs|=ݡle]PrmvHx},j$SCs|0<&$XΘ[.ܳdfy \X'yaܹ.ОJOU> }멙(tU e iuhݼN*l@h4*Õ)(^oѷޑj2e詜fS=F>~aڶ5<ڏ_չ0GPG/g]Gzs{>CaԀd;8 ݚ͂Gl8XߏR dPlpg({=Yq"dAݷ}ۃfqo£g*7)>|Y# K낱)-Z6ABŐFu&YQ_^} -yF fq c/љWKNl\ ]^/YJw.R.;ppy_aQ7_ֳY KȊU!h\ EŰJ uc>Jf֣l Qޚђ aI -ޞ?ù5kLx?;2=;v!Z?4463Z :,zdfS`;LXš'ͬ%SG=ԑ)Ȳϳ|'}Ui aS:3~)}//=,WE.:SyYP栬]TZN6s&N_*][fR"79̀0 L@xt/XYTkkQ1PuIrȄ.8LlaLGn{7%xqdhT80͙fdG< zdӠ 6we=B<*օrZ @/U%rdfh%g8.ְ/nkrzYn+;v-bn7U|&ֆË/ 1b!{ y! yl0Ba)e))aܞ]JAb@0+F;a<_iF בȔ)PC; H!; E Ff#yh.ڽdH|)kdf,GbCŵ8tyZC0]⯜ᓴꇾNnHjA}./˰ur)I5qI^4kS4lV/ń#虦8V fﵼ3Fdi-$: dvmlTgtσ:$tӒ6)HwKك-8[/G*Nto=gߏpf2Fͱzek:RF9mѳJ4!B(TP$c\]󴒱%E9 |RD97O2_=9z\676n/);A7SL&!S :!GnV9` @ZTًv.:RޠN5&>ÀhIf-ZM (Afu9eD¥=g /;'Gx= }{~e'HfpX,s"BY-vE?z&@FA˓3"Y (6lkRCXv2c'?˝q?0i2vC'?Pwr˿$<8hE$5ƥJ/ zz>te8x'THn0)3 6&=zv>tv-3գY{[kkY,RfG&llG=sK!&"lnfzq)¶ob C(iTWƾGۚ3ut nJBȜFEwc{]1G,3H1FVbSHdd7bp̝-l^W rqpڸ%o ouETRhrn^5ieuRN%]e= aDҒWY;I^:eȣ=#>;臧r֚o l$RV;Hl23:??s摦\[43^M= Zqq?׫_hH%B@i`]GU!q-/VaY,jCvľg[{<҅dÔštڃnMBx=DVr3ޣfd*(-+ǠxG5O&UbE?x49MLs!NsɨJ.8UooEsKi \z۵EQ _,Rb8 !Vޓ$5bBdL1,$#Y$=}4R@c6%3s5۞ft!e jXqAd|>O)ص bGF揇obgvssl|Ͽ?gq;Y>g>0T04`F&eq*eLA7,@E9_z{ Mi2H&9.I#Vk95^y) h]\\/w@0V~"UF*XVPj^oPPo -/c:R.h؞gh/9Fʢe7X,0hC&m:h&1ʔv?ڦ% 0zKdEs/NFH#b>m{EdG:ii=+ق|m9!3cKONi܌}? R H4Cd ٘?ҎO4m RRf܊CLQÆd60W sI.駗)bʅ5FDfN=ur<)<=et3%/%IK%)Y>GϏJDk,6ۑ ؕ+Tf˦6tf#'a]Lػr cǞatQf 7o GYAFDs~?n/HtfDt}l(]\P5QcU$RcЖp\03Y-+e l]Ocک7*HBa^8Z%'lR(6O4Jyd4[WEˌp#[Y7ӣ=>;:c{ABf h֞ۆBH,GF?zOkSw<~{;`WHn2ZRGBͼiT-fz YۊQ25shݳiȱڬ+$~Xs.z뀌bhOX<" YDkϟgWNm({쑠ogH:b$"]Ui4wXo,shj RG\_FsÅ!Z:gkW7T޲Wg1 "jUs'o-pMweq3ܔkXYNݧ~i[4Bo%DoZ:6R[D&mS:1[64^paA1J=P^nⱥ"cߏ%vF;={]p/Q MoG$eqxp{;=2a#`!w31%3 2^P $2(W Ks mqfCNw O|%.&|A:NZ޼x%^8-D^嘢(@W̭=0Z ԓih)7 E!YvL4I#f}~>qx7\0d3Ố/-[O=NK!Z,4yqpK߼l-W3y*Lɤi۵Tr\HI|Z{k)mϧA=Mj 9oA:,2##h2U{w? GO?>_}O|,;z#:-sT2+zT?{4#܀nx|pK5ilP3Iя>W,Xم+~2<71M c45Veo~r1^|ylM]Vj/˰g G-=M%ɆgM rZ2@IIfy s# xXh75{dKԱ㡴-G@#̙w<핊{?_:҂ނY~L<>=3`t:Ͷ8p}u {/T{z?5oEh(5pcV|JMI#* !͜3I:G, `61hBi.vP!IG%O?)8ggtmF8= J Cӈ瑻:7X} 2r#d(]*B? uY1!Q Y֤V>MQ;g/g%n</}B" vBO.ACz syK& Hw ߬ygo XުB)ywɰF6O ct7748,L4=_wQfpѲZXƥVzqm<\̴hPB)uf歕eOTs kh`Eg4ά%4g V(). a:g\qߩ_PG_D$cE5yiaBY6iX1t٢N_ɯ, g %DGO`qRC{>o|~^Pz̶qk|ВfvRa;@mƽ3i>~xq3?dzr͙$7*_JjTkl]boik}&189xC]!Sb,Q d*A@4ED !"F\>н@,sN >an[1׈uzcӠ<=e R˅%.t* Dij{K<,p5Dh!"2}<'xdk-{Oj`Ͽ?? lϏG'c{<2R}p3`v!L23IO/v>&BC:HS@l4p.9?$4л(VQY@#DpjgP97N*d8}3%]we/|=\7U.'bî}l&DzL\"rޢP)tDtio{0`GL:̝~-s/x@ӌ㱡q=w8^hӢQ%2ۏ˦{fz]:O TF%3{)1ZJe@DvFѫ97n7%R.Y0KxU荅k:3w88Wnf<1ndMCV!Bϐ)C("V 7{>q{4”4 &~F۶ݬc=$%YcQL@ޘ54 C{)JEi9s!g@t %6Cu@B! ɛ١CLZ$3d V*,(KMn4shN0p6'2Abޣ^.{Mcv^w) f2+kd܎rֵ%>[XidfPbI=ج+yl+c,^djCڃFp;yӯ>~ϯ_Lu3s?"`{Jgv;8"tfb^?2JZ@Ȳag?!'2Me97@@pқa0ՀΪETirvCʐWEPJ&7jinKU]1ӦuOhOZA(f wVt2ɜ؜#B~=1݌ڏPXY$!' ~/>k|1:>ǯ3[FTzuMt 8tt?tJf|hχeG)fd ) pe)3r͒|6{3Y"g ؐYBRkLmI!?1SPKi'j÷([xU{FV V`H/"J(6ӆ,݃5^:l@8fR a ՚oTнhp 4HΌܕ0=pG:B5+PH-:nVSWr?㵓ng(: r:.c{xƮT^cmW7TkffQ5D B~I0EDO|8ABN zߗ9r55TǢwzck8@0boO-Nu$^K# 4!@ u Vu#,z%袤Sןw3 o4"N3?GB\{G~lfyqk`A=SP{w"榌bSq4Ie~-#n<|KıwɋHnKM5'߇Qf@fuFZ})Qͬ9~ge)hGu)Ns!#4IL]B_N)s.h,5Dmpˬ8h8<; ąVY(CW  fBi|oȴva7zSX&"eTf *@U`3c3fft`g3Ѱ'[x׶eDF{Jp=Ħt؏8)^[A3mPwud4)5sȘtmFN!!ޣ,MHeddTuVnCT6ZiXX|W2Dф%E0'9ç샸gfiw*bӣ-JΡt>(4H?Ebc{XٚOdg1}["#|#3֙7>ةؘ[K@LжL<֏?yU)~?[sw0Z`芒ndifm#R֦4V2\S}W"gq X]n=2aZ'\_3bJWѹiE5.웫3Rzd̒^,,hlC_Ou6c#43) D8L_! [QBEx@ϧffb'@ɌdK^`M.oO{)ѷ{u^Bliʾ5x!LޞMTLKE+T͊ΐ؜0CTы^Unқ@0 3Šbxhe'KZ(nVEYhN oh.ό-S.YIg.Ř|:HܘMW$*#˙zk9 I3W 0+~}?hz$iÈ8LQdkEjO"p zvz6"F͑px%rz*P Emfd֞=3Ҹ5i xÜ4db[rUy@aS/dit)O PKǚjxe鴼ZWS?7ƹ;{FY^:*Bh -(ޕ[aF-0ͱ)mCJGbj,=o?{4zh!93k{t, t7GKsKdÎ|a*H2NuEdL";)xp!`!"yxٻ5;wn̂#G/ 8)IQCL÷M ѡlkT2Rg"j~zmo#B6ߏxjfk9Rfy< -+2Y&+wGGzw_i-<h4w/YOD04{fFpV S(YY}(L U{pD"#3 2v8˝w yjl-opL|XOSle;Je= 7 M !G~GjYfk̦Ld=s{sFAG=G[L}2?:~6ǫPY޷G*RhB~dXO d=g5ն3z#o{SG{Bi5q5#;$5YSV>iQ ,s$&b^Ƅ4Ç!"#oA˯ZSE@!%dRIɟQ68 cZr !|s+HC8"sߏ$Ta|m6׾[컫?>",^Û[|3#j̣677'G*bE5@종Jhͼp{r$ȾE6,!3VmHF^7:P$#=hn*E3@T2q'iMy'N?z;e/ml7U.s.ih1`9쑊frͶF ?~I~nַO2#FhnPן@vLmԱ~=fY ?2 A/>!X?oL#96æpaږQ\Jsf{2weaۣոfa =R1̆S`- 0D@L)By, 6W.\v7yڢa\2O O2ˠN9>ש<=z-ܫiYdq/!ʠWaL O0Sw? 񷏭g=" $" k?7/Ƕ9nbWwkr#I(j2{ܙ$0S0O0kfN&I`*r"do#P+ɖI [:Qmΐ3+ة skgh=YYez bح_A}"p5%%#3ADt D ;o~Lުr~-33DBX=g[A50(9`zbD9ET3\jB$]ai iK iE( ̭9R7%rk@Jta_Tr%ȭI1G̒!Vl"3{dsofPaUvh{Qh#3 SKM c`~ǁ`f}qL%k$`tB6)H"xr.D, rf8z}Tf ^ӡEsk ^! ?x\mN{ls);{(탎eeѶœ!dT[e148Q5f8,f:d+Kz?.fxz1IG5 R3sZg<>_1B5P򘙫u)tp æz6yրTDf Uzl8Xp>jږ>_QsTaC!\%q>XElz_Ӈܾ27K]9LT\{lRU.F}~ўJqcBc0~I,N 4XfeK ;B1@9 $҆`  :Rfs M5?;=uG)ZFl^&6 &:|1#5!51*A gEgM@o]7_ق5h;{""@)Zz%(Z{p^Ok+%8m% <ߧQ-ثEzwPuVX^u>SDe2ׇDKfc@YMlu\#8btS!IBng3~8ˑnز:S"ꗣG(l+)vR`lׄ ITcCn%@ɡ0=EԔ"Ds-p`o].<&g-R).^ЁqH;^3bPғr><>!+384XW:CD-Z;Ggf(Xϗ[r]he7xkȠ1ir Pt%v-J1JO'渏ogQPJcZl藭-IjQ +&[rwfCK8Lp0Er#dLe:%'6 l5\?\y9G=ZΥ+`$Z>:' `ݧ(~{QJ s0*ms_~<2D%D$Sc,U*0feRKF6N4+|-.ROIO77w񎣤p~ ~)~jOB`<øDƄ'CizN62☕1NjzmC엏Nݶuv_TuAۂ9\]ѷ4.4s]fmۮW^r܎YG̣hgXf(IKkJ%:eBȔ@Hl'Qik̙]?z$rEr%`'-WdY#Aj X;"qd}^&r.F i;z7(T[DsF.DZRD4mV y^O)lŹ.q\l9Z4ޝm[oǏsWVz>v˅8XU3Gab,#LTb>R@h x@j&Ln0K  R8OB'"x@ ch<1g"EB}/}\)߹O2B'82}M6WbM.(hj@2\Z=UL26!a2EtHйkp=`pt}@1HDMsD1)V:>c? Ht&\1ޏp@\2r[72#$2h#c3a-@8${u5.baUb]\z)箑$gzܢr w=~}]o[Y?H|w[zl߲Nu_YJFyhV$"ȶ+Z$9{ӝA39 J+eZ"kd5HБ1q;H8Dw1"%MQR1*V_cW_>xC=BᖭiĘX9% U1~VH=S ;z Q*`ܧ_)gjNċ;\'\=0gf3rSXV!1V = @oyI{5BZebP9[Щe)bS2k(,MҰ[Eݗc^-Z83V;QCRc^ږ7gf' Xǘ`wd(9+nAhǦv0*5$1v.=6~c)UO36&ۼ&u,ygVrh]&!EuニRZ+Xgqf ûAT@K%#b־YP&⁢$P`FDy^t,2gL}E~~qRȐl8kA$SpgtϏڦNǀ˶<sNѶi3 q-GbWeV׌-2c#XOub/^u}0[cJF,?v [c4 g:%W"0D:Ҏ벞`d$ϊem\[:WsǷo{b?w8Cx}]2G>')#{lkN'\V,bXf`2[>/Yr k.Er^ocH]F珿- TXҘ#jqiR:dGxԐ]{߽w{n8@f\. YEۚ Gwʑ9kkf@6UҸ p2$zDgҊ:i6\\?[e|I y8b!r'sh=!jhgn#X[\T_]$8O1\DTs$?6 R頋%5Hg)] jDK Q34Lg8̊Ȗqٮnd^GIfd,m?6,*bw'V]Ҙ1͐4jG^i}uҭj~(]`^E`ִ e!~\<T2朕y4S2'q3ׁ˵*eT-IEޮjs97&[d#V[ 4!k.[pLdoc{YZnTV'|YU| X_[k̈́jU8R6Vb\dM$g> CcF<9.3aI`{Cezݺ p:5jHV1Jpi\#[8c -1E2#{(F̶]z\99FsuXWw̏}>+/>7b5ƴ\bdY*]U,RA͉@ `*Vգ@ỳ-erơ\jn J#4FX%;s>& ailђ2木C јmd=ek='X չMrRL*jl;E߷cDdza{jΥr6!f@/-E, Ƹn"a"&Bt:y|dntEo} {Zq.Ef0K%%YfP;|}EfNXsaXiW^J@?ϏO8;<:W~>~y{|V XV5hr=OY9^,/fG %q jeIvp3gk殩Yz_4j}֥#{ݪ¸+zr9]uѮm=5UDn?|<_tԲ C*Q޲ 5FTư BL .ҏϙ%ǃ4"g-sN#{l\恌\JAD":kΪ+KW`Doź|QtW y* ~WYg&k?E5xmVdpT` X(Yo7ֺl ];2_ g8FiV@ѷ 53!9q}i~McKce`:zܒc9vKv3R68(T.`NtbZKآ!JL,d;ٳG%4`2"A'&ktUsβSCщc[[2?4C'|0"p!j1M+Rkd+6;ZL GXI!2emkт9 flܔGup6&0__s(,Ңby"ITMZc23z9!fb<,Q})d$! Kd*!U >e)udn-Ԅ‚$4duB uX!6!jzQ*;YLriXD0<+7w4g~Rot /:zuԃ#nϬ5G*RfMazuQrYcf۵GV5WYhI0Ƅƶm@lەs`ln_~(1o?.=.KחZZ 9Taա3?k\Y!P% ЊeW ފVQcB2je΍NDp[OhʒI]f}, +%CEQ$%7snK$;| w=;1l5~x[+@QjH'6lY~F#:Ҙ8j7G]]C~8z3o{|}esVaαk ?zM___gc\:&fT#G݀`ɳ Ijst&[DTjn4X eh`Tz00 * [;[;=HRRq>pg O!Y -ˣò2݅P hXsYsLwcVhQum[ CG?.{oG= }?ncexsޓ*~ݾfuEzU @dOϕQ,^YDKZ s%nơBp"VQ(ZQ4gZ"m%?0ʄ!] ^At*g$cMۈl%ǥ3psP+0_OŭܲvX;7@F+Nњ JTB5&`,QC喗 3{8v5]sV fF~^D߷3t* x 9KݮIf@iȕ(sTbDֲ˜콢T1dI=)ay ,ΠHd(VAi#ȳKz7T\5vw`-kzgMo_wV[/?6nazKt=+o~7՜>C-rIgrh=bM E%΄+T.u-'9p$1=g5ƴ\s1.ToaQRbl̾k}F1_(W!9dUomm07B层d$5P<Oy1 U P"")Qt_McMS X=1Cf 3NR$Jn%>Gj4K^W%!+coB];|[bmENh=+q^|2DX:G0d,L lDZ6n+8f)S%7Z?FjIDrM]Gad ]#<[~~ZbXYJή:Jl~%x-s[BFZ9CZM ډ4!%TC idHDJ֢Oː}0{w`/K}_:!>&k>e)PJWP-4BdyH@Y""de'g-3so{mڂjα`c܏Op~u@M/ UDG1.c\nBG rAj=k]6e`ּ(i LprkBziM %16SZu^b"}~t[qnTz/R_g9j~'J?o*su˘]I4oPG֧sxD8p3B CDO :A"rf-v 8n8rv{RqQsG̯mvx> BN68~EVdfoIZb}k*z2LXs;q0F#@L`jN(-hR[&1Ɉ5&hQpbUeql?[ΐ2;eeO=6ϗ^lOЛ./S{Nj~'](HBox\ΨO׉qKZ>%jv aB#37Y8 ST1&@RYQƘ:Z-jn}sXഉY>5ln~p NlB-'QqomݔQZh FdI6#9g!"KlbX1<<Ygo3/oLe4Zvxa'{J0CE}"eS\_\!تBe,8SH>/3f~3zoZ}۫3gu<WK/:\=56)5]L$"2R-[!1<5OEk3qsJNbDdUԤvcz˶L11~%]e22# qʹ²{<` "fr(v [C,ȃU-2Ec1 |Fq4F-Gsi`2n\&F,0vh}b7.|{ oWů ǡS&q,G|Ȩc c3$\ zjinDF}fa:l{ghl=m} H;8,A𔜽)ocjM}?hvtZ{VhiVB FJ:h-MԜwƜuJ;J%'A'QL]\1 fϒrU̖O]PYeF XA>5H]Xd.9t_OrrMZg(Ts咳}Hz=p|}]<6묹N}Dﮟp<0|rNw UԌr2N blGrG֩`1L"U_c:2??~&G>4*YUłytn'(2^蘓e,ꮟdo'/m ~2}]uK^|=Xng!sZ=L=2 sǣ+k n-h+37[& L 2$pRYӅ̄AbD'[Y[k εMS3j$f!UYs  J\|C8w4$ Z4ǜtl,!FĚǜ[4[nq0ctp-@VM-ïmĺgrIfd&RHFH湄[vmΫ39G8boWc{'8=;sv:`>Νףg`BqEPmsee#%49j!`ZGd&r544nW^3lѨ~2aURlٴ=xi<BcCe Qixǜl# LAV@FB2ֵHUcN^I 26H8QH0%2#ׁG ,DP ׹[ 2>TU8#i3׻y337T>焋rLQd/ m6#r [򱰚,]8$%)!5 sg}S DdĬ\BÚe:FiD&fFM+yO!c={OLP`kIj(j["\l^>z/AW95Ώ7qzW\L D^O@Yd4bDFΚ1Kh 8@X~Ʊӕyۏ}B Se1BC_7k{>ތrҘ~&#Wv`kۖ!΀k[sAV_b<@t}m۶my]C_=TYhXX7HRn@`%Uk&2j5ƂGBP pi r1q93:E98Y b[V1m~ 趽azI'DᛊǷJ+pATQH>B<疻q6KUsԘ-ͤ[#˄mWX.vx :q sG̚p- p asCtr1jhkrOƗ`-0"uxFS1O&*GUtf=6VrvI43rB2eՙ6 .K8cR_u3%R1)-8i@,Zx\'봱YǤu~{$]?v3_g/|ϫvPtbA_*bQ@"/DDD l[lƊBNu4jG*>[_eT˽Xm<"_Gș/[ r.șjpF4GG%倳X eW-|xoR\NDcYkmR b(u] 8 FlK((Q5&l֨0|>nTVUx*Bߚ 7Ղ_9ƻZ3m7q%=C[n2iRh"]m Zne$ f+tTQ4K:].}؞m,$ٳ[]Ǩ_c×};v~"yySJ3Y%\ D.ϐU~CJ!W\mk,K2<F$,j5zM.h}1]8T4[ۥ1B)" Us#y5(U$֮xY8bЧ8ķ32̥gz[vk߉kJ/z7>뿑˞4aXڷ+.-sQfKBh:j.#rc~$H`BcaZGcYDGX-| }__RK"UEEn~cEǀsc[`E'׊Q;jYfQv0~Ԯ6cK ѯ.g*#'HFd.+\QzE|=+A·7߉FO-_$!L/Т=,ek1/IFkvXwCk~\ g sȫݯWc9m@.Th$2A0hﱏ_߿'.ٔh-/!+&<3]US)T\II`kc &`e"r9|qsXj=hZc&YոD?zzמK0+ g^.̵Z9VH3S2؝SXy*V3Ghyz|e,|׿IWjmG#xp:z ijV jc-cΙ.Hq5 624&18~77}`j9 dR骼0/K𫷪š1-t=譅 X$SgdDdd9@"䀠bZ Ql;:|?\@Ckh;+Pvq\zb2NE^;f8ƢDE"ά_Ɇ ]+NhOڣlxPx6oڮGS^?hIjM|֣絳9:}t OW0 ̅jDm/ cМzp}b1. ADZ[^y`%]zO?~a~W5T:L*5QffjԜǽ>wuC-p,dcy'h( \;2s]J!SYo?/.[Xgԙ Dͬc?Tm0EQZDI3c%r&5Z:#5y*>p~=~A^x=~ ?$-D}tC rnjO[^<`FT1va+Q$Q+(W4բ% 5cߕ%1ž_qۿns.z=Ĵ8~vaQHeE#!B06Ƹ Ul)xm1)P`l~).X[5Chi%3In__G9K@`J[?f7X5]wG3wA![z\-lS^M?Ns_iUT BgD9cK洫LqԬ;9u;=$77DdĆlFF΋&~¿^~}sQN Ʈh-{z9,-I_1[ьct{w9'faxjUu> [e%"Zk&mi#}1AK в1% G$JKp|Z%ʱ ;'|ux|=}>@4'ƄI/? ̺NEdi\kQy6jSo[KϽ^[ܼAkl}Ϟ5/QsE{]cLץ.:.cUYeh?~DWjc?*ж H2Yc=c3<9Ha4(zIc1y֘yfcF_yoIM)[DZ#18r&LWMus%^S+j0SOe2BZx%o3 ͯv'tړZl|\7!>>9W c!3D.3bu2`"3A=jJq3j/~n͗z^eqP4  }c/"[qfj&kqySw#3gk맅X-BIEo-~\vhG@p ʅb/Q]t.I*BsoUsfp0U:] vLn5扒 H (GiX^a`gDK&L³5W%bc7G f8S'abI攠K*w.Cy91`Md0媕9k`iTnKŶQaN2tO?boXq=qvcH? +lMh#YQDݩHzUS61jT׏{6[lkhcԸoӦl~Ine1wmeDClU޸M3d5@)ܮGT` A- ;fi~=ꐧBQC `nvhj.cfr>:1c&k.1hHsZ`۩JR^Ѳmk[j'V Ƭi9ͧ\zph'9Z1~^j7kw~A)a_;'AOF-;ɱ"qYzk k6@DDhu%[L8뾏YjOί<,7&xߎ}ÒrLsdNk4U"r@5Cdn>2"_{푎W,vVx YsRZb%\cHg\j*yy$Zk'(j<щgkւ d9bgDk/@`h窂 Q0$N$dQn6 6oM ~N^^C-.{T9ӜOcS:"r=m8qJ?ջ:s^eKYэ8#߿Y@U*5c$~{5},-RZ.KK0×+E߮'z`6lK*2y*g+ 0{m[%bܢ}&jc!lrX^@B,-' k3)9'˔كѢ_`-@JWX' w=.o)zu[{oLe<5ksp ׀X1l@d52ĸUmr"Zl?6$g_6_GlcQ4 \V8. ,z|$v\z\tnn"Z \V6#L̵^;Zxrh6]B+Ԭ2W whkrl1+Ӄ4e$?.K ~ɂ}M|xb%5͛ad76#EO]-&iIFUp7֢;mqמj1c]@u<4*#k*ycݯ1C&Gdl`F[4a22mkQ!ZRHGDF鴬" Dž1J\",a1ΟF8+PGO:iZu-{mD.y%)m cD O[Hɵյʏޛ_|>d~UfoFǯoOm=[ ޹q{L[N\62 Ib׆A$ݧ@ /O;D L0 {I}xZmȘdȁ$)[fѰ*!4{v`dd]0It+ Ueo=P0"z@mJ*3Zw5s1 S͵Kڇu-¥_zU!_?&c ::EFfqBl]mk۵OC~[iʘ0 P!Av=b 3x1[ɭt-@<) 3,լmu#+V?2J3V"۔FQsnG)׏PU|~n=Q$a^V-z$xΏyO/@T _+߷.&Fぅ>Yz )^(XAA1DTxM쇎YQ3ǘo[h:^${Ҏ\`\#ƜhٖsP[+ shD"b4``f#s<yq gñհ Nؒl>mTLڤ;DtPctUi3=8Q<ܽ-rhAYQR`$ݵ}ڪA2"Ϗ+|_H) xţr>(^bMUv7qkbm[R]@oD`+q)6u4 \'&f5UAEݪ\2 6cVwz *Xh=ԽJ(b]Q,"/=3<azts,yPbfh_CjVa(h sTɃj~yCL>=¶-1!1ɖ`}KԱW RLS'7 V0r اo׏g'`n׏k}SȐ98Td>H|X#J|*>s> m^r,/K s rYb8}q>T5gJ͈ zml_qcg@n[j1 =K9kõyg<Gu~J"s4]ryS^Zϸ06Qa19=GͩHF1w(e60#J"2KHD\1fpUEncG^؏nDLdv\5,>NJ!]2Y+3oM8? io1ĶaX7" =9:: ߮ q5R*ä(!.o3/]cT9t7$LM#sFcB"t⒖F߿孴MFuaHGLkʐ^E5D*DƲAӱB$cL Uٶhiftdz4'd Ѡ:>5r62 õo_Y*aڨ>׼!?\MG%J=`O|=FB\@/%\XrR'QtsneL&qY[-5&1%Ȗv\BTCvq5Z~@;>)23:[8DiDF!-Z ^mǴ rNjT{vdR5:\2(֩銒%1 mKbm‘!cX8f~n; ` C#ZԅL]p'6fۻ9O  |i2҉bPFhmVrWT523:$GDUdl@qwy0 YW_>>9F㨖}EkjagE@Mfgdj3 \39--:)B.-Ӆ)R}qB @c%jR2u4fֱ﷯i+D֮ĭb <rјGv:dGD;=GI@l GskñjLU+ܒkӴ\s`q'>a/2o ƜN" QF Hd3v~J.pȘm7@;ﵸ @-aʏFYf*1 F?b⦾(Y ..Ï|1"GOP҂VΏ5 ({/pE~>o/LFkmpjlA/.{mk썌Z2³.'sΪ @6"r5UKVd8ceECFG"t(bmDRFn1 gQ? Fr I{%qb1)B5qAHC?XDٗ[?/ JEny]QF|ߟ?J?.ȍovp &16$ReJ/pi/l5k%uZJ-#h!/Ͽ~lmCJ.pu iKmz!lzXDEUѭϿgzPLV0Oo2\ Iq"_Py߿[C^(\2Q09Ǐ9FΈmU JpEOf8U뤞.yzR]!tB"4h[߶5HթE=-8tyy8Zyn2Y(hRmKjǘ_(#CKȍU8k~P "Ih~>NkqROa[ǔU铌JBR{ZP`˵z*+-yKVqxṳq45x#?+=V->~T4G\:ȹ}־ jdnf L$G8qV%3.~8>wNdS2$Cd։9fM8BoIL -2]` -dEDeF0{CSַƪ}YQa$BIP8s~;`1^J{<_&/Lp",ZKT 8&5~s#;_Xq=6+ixC@?c &ٶᘼP'zC9vM eِq&}3`"1KL] D\6IbD>a )Ue6n>j]>},C}lQ1s0H]+Ȝհk,۴aE%]ZC"@ZOPDM,6lhd2Qv(Ee;QoBV gAi'g txe(г*$ P/BZCF } h&Pl=1&ipk_01gYJp$8r.-`6F@bc\P9=s^Ql c яK\cOe^J"͑2Ue-}?& ѶΑAe( I;2,ZeO%fY@6pd_&ֱRqf٨9"ITN08uy/,7Ô^>_f~҂ c-:A "Qbb+H.CTKrgwj3ջY߿!qh=j޿n_M~HrKKn)r.}JM b dŬyt%Z;ZVs6̆5HN`ªqU KRڨ9=m m2/mWӪ's` 9mƆ *{.gLPfۄ6RBlֲ1X\x_] YCc?#ᅏyP_-䯵i~ I%r?R$s۾N31-6)Qh+ŏ0=ecdN5qF}KǜǸݏZohQ]wGd>6vT#'rYYH  ȶ] "c6FcQa;;vU0KZyvI#"{5l *&CV\Pr-q"#chQa LL.:Lfdl-㜦4ۧNO*o׈q'~31h䷷m[N,*.*C 83?5n_|d%">p,-՚G1Z[.1ٶ6skq~?4@&wglid5Og^2Y1[c=F;v9GC0'RXQ0]5 MdNhٶߪl>~a jj\L,/H3T XFm!@2ږ螮5s[iK;D:-{f2jNsNY@:K~TϜK}Fc9B/ mRH+biYU: ̾˕gռ#)1yCprIp@۶3bczvL-3[qxǴ0/uMQjሦKhKI8@CchIj!6FQc!e̱ hUjA5!9 R-pot8Ǐs`Υ1VիGg$9$]PDU=2@v97iU,.$.pZַOxɷ1B$WBM,U_DB.5}_g]Z/>Yu^d?"WC/9cٰvrcd; NºM3/o7}+3'p@2AARo;8<6oo`CDml:bvuyll9pp89k;ZP (-BplI_Cj@0GOʘh(K+.X m,#" #6yx{_f2{gRFZ}/v_WhKqE (ϋ>ҳa{5::c4Uk{A`03ԕjo}UffQ4SޏpV@lsE2WȔ7fzǷ.LJI b^SW;ty?Ώ# =s.ނWF4J,JbDb o}0?b62޾o߼Y+n D*ٵ~UVtuM $@U {(>ח(MAlsnMj*ϬRVVLO45_EgM_.!O{xϫ@DǓ 4<ݒg;= AiF[?s&L="o?-(d7WFm3b;$n>=f-{[&ev*G4Lͥ ϻz~ǜ&3B0~B纏l~N ޹>~(n7l8G^Q!ڥޭuk5KhѽІ Uevw!JmG5MAʬp/9}}g_z|I2$uضz{z*Ů}*A.A"@\#)eu5 u4H޳3sh&3cű86so6 cӜeTa͕y{ff;e6n p7J)R$`l]rYm 3ܬ.l=61Son(oDhN:fδ= 23YvjG7lYX[W9MIa뭧 ՠJf#ʬyvZKr@Abd=zs<6yM/7ۦ9r3rȼPJmFSy I6Q\U,gcmiKfz @r=[F|_hWBٓ(ng$o9~,/VRl+'%!pdX0֌͆9jBfqsa*RX3 anDVloyX~ f*,9n7`v?bNP}Dwzf7X]nQY="p% KrnҪ& 4$16q?D{kT^M ;aKTJ4VHUvօwnto| XjB X bc}E77KwܫǿE?$/Eu}~ t}@ԋkHӆv@ШnPw@.uOQ2ƾy'}a!ۈ:5ueu{11GpҬdw6ؔG~wB51b5Y[d Uug+#hmaN@oJp;NY'O\^t ^qANquڇI6jc^>Uij>RmF#9Qۡm;wvn93;UIt5^pl9N`ݟ6y-џ~a] eΪՔX '@+kz;>gs.}|^./4? xB 0De2E6rQ f S(0UgAu;s%!@V%۶:Ǹ*dUo<4u>R݅՘ ѧm&8+@w0s,K]('p m) }a+z`g!3N"HF*q5_f\u!^g Jn Bub)JZ^q5׸gViRҋ3½$_\0 >%c~ %نT /Ah4j: ldl:Xeo+HDUjlZ~^Crbt@OU79yn'aa)s=Sm@yXf{VQ:ui@3RFhbS{<3yvNYM[Ttds. Z]j]moPTo4 W! TF n.$Bva5:d}-?wD_}r?*=!l0l]N9fSY첧@z!j50ԙEBߐ`)Pژ4s";+>{}~,OTK]39φY\@ 04L>G|> =g񶇍QӺ e8ZDW@ݝ4[e^ Uj͊` 眳Hf:LN5gZ< >_1(.xQ!pa#HR-H08ҟBw/E;^k/~^|5'lwS :|5SɕE^(IfUaEXY;97uu@ZUmFHu@(tu :DVgg5^_5hHP\mktԾF,1AuݕH4ňiWv[j@a5>gZ^ѧWOEB|kn "Wz;O~-F::D8FlaTPߎ]sI:{1c폍rIc8ؓa֜ }t 9g %cT?9'ɢ{;n&8f ^V O41 sx$1m*:[AcơΔ̼ƺ{5T7˽'[hЍn(bS?i0.HZݦ_RWyĩФlQ⧘`u צ+jjbA.*Uh5y}eK8=h$.؜&2+_n߾0 -Q7QdeGXl'@&hA BgOmpwwof%-m۶akHMMhc{>N^hͻ+{]0=;[FjZIC2yv. }/,*21eZ QrTRc2t"ee9iY-Tk=]W* °&ڡ-lF]O3oO_r|yk>'1j6链Y }~iZE eeUFQ+%5 |OsiESP#g+6۷yʻ<枨j4|7qրnM 6XUty>l>|/$u5$5}9FG"bX1Ŷ7qՋTUZDw/jHX0"ӈ(@= N?4F -7 s. cxVh^ٲZ I(fVf"kXNAr.;g5~(SuX }g_΂I|kM`^0'O,s]ӼsxY-=2r3)!j#Θbĸ}/k۷}??$Yf%s]k̺am|(7sx 5M^kM f3d&GLJR·Dg *[Ft*쯉%oUlRʚm'Z͌Sp7!412TnW~>j~I")/H-8ey[Qֆza Ď_R _l/sh:8LgVk^ 5w6\62\uMhU@8gT h1$vS>>vKn}w/|Neጌl ?NcoclF+lLuXȔ24Sb C.PbQ9[=~̆0-`/IB: >z;l,ZjpCae<5)*!UF ZfU's&U^ %Ums|WZ1"^/&N\$~]̿D-UhwS@Ff+g\0`GmRٳsyTeo﷿r4ю-ae'غΪ3nBDlB*4ˮH+]Bՠ5K2bfo0a!6fHZXh | A7ճia}m]K*V`*F3UP=w^> F3jYs(R<1VO KOkyl|@_hsA?e%44X2:H3WVRO5R5+in I5X#I̼Q)@m#}~yDMmTbP=z!fVѭǟG69asZ7nlvoGDey83s"{ХMη$MKJ7@CTm&t %^;2QnT~jV}LJZ{0W6di%Ia6 ,|kxZRah5^ﳎyu7E9w來>%:^0n=3Jjm)7/zSQY^&.1QYG8u>6B-!ex <ϒowdG ?f+$Ua+cl69Ǐ1iVS=ECЈH+mPvu{Ϛ5zRֲhov] Ǎ,oÝDWpnv,v, JՊ5yad0x4ww?}ܳ*.fC)ac8d][h. h֔G Ǹ^ͪ{އY+=Nkqzf)}2ӬjjyTMN_cZuBo;IFX*ظ-_cT ,:3sf۶16;]MAe1fmR%%V{STł,6ZHa[cٕ)_ 33D7)~0-"VHvI{gŤ>3b{^gO#%yEax4 \X}!^q,QWm3 z VgxqaFtW{7 ̱]gE׉`M;'0R~?iXsGMtW3_ N܄\ٮe*jx30!{WZ}^|aF} n@/Z/_WкїrFp_elcyN"b'cxʟFp찞VN y8y1"ȝRs~3擪T)v#Zooy̿>L%tH`44oXGNtaͨ\Lj\3V-b35^2i ]U57||:~>.E~1K2R*iQL"B/̓|½UaWxp)g3vn_V].&b!Ǻ.uG'`}h/2`ܼ9!clUSnr8,ޔ2T|ʟ^ӣ0(FN 9l{߫&}5BwU!w=VĸP'&Q΍(53|Y篓#Pdg^5 v- #vdRY-T-&q!K-0-jxۊs[ނp36{I߿Z!{sY mI7dt<uhߍZ;zh0 2a!-~sAtfjl% z: fK*}fp{2!D l7^0|x'~,=p'66S޿g?Jom6Bt[y&:hTVK:caAi%c-̀eTY˟I*_ǰk>>1a[X1Tf+?&uSN,'b0x^S)45d*fWF //~`eKqg5k; E-@E ~@=<(4;ҕy?*ύ>bd]7َ*$nv T僜n|߭ǏRv7p?`߶ 9[-1n=rZtxI|m1]` YyGxfEgǮ=YeNIVxe}f-cS鵦sa.<ekk7A'ݸB)u}Ji*pmU 'wO諱]~_חO_" ^,,7Lp-:/=0S\tW1=Hy46(g41 > s<~bӕ5[vCxyXF{l;qMGrvvDyy6 q c­@GQ4U}]i ꚷu]Uy B^KӗG<ꞇ8>5ʺs5n,s>/rqE<d$&Bǹb^ϥD|jlE~Uί!}kZOd5rbā[NՈU |X?y< FǸu17m7z?~l I ENXov=𶏏sf^NUVè]my+= Bwgw!nj@&^w_- JZw*P5& M]$x,@lU5S.)MZhS+CXV"R]Լ/_}_ ы0£PqY@ FT@ʚ&khnq{7G.$NMLFOypyD@Zciθ~YV!4.MdO4 u_Xzk%P~ ^-Z\۝~JǠ E$"b]z)Pyf1noGZ"(Oo|vm;)9?#~yXhs>{İV1v4oq.j Mj{#t&=-l8Ȯ"QӞkdMڰ8f8FFs4_/ v~yjvfeM$ӴVu..Yr%0''u ' Iў#@Z.,zF>ŸbWEsy9<~oŸW'Ϯ XRI2;fK*ehҪ Q7t^H7PuRq3Y:ǯ6w?nY'q|9 RU3aZjvnb߶Ϗ9pw'Ji[ա ݜ:jI gW`a4E6psAjm/X 0ʀ{S(.D_ `vO~.!o/DaOXͪ|qz`hVa@%LֳBB.V\nf?nSg?9+mMwʸ[0}m<i[˪N_9z=3VNo(I=:!5f1hWEhPBJb}>77 [ fͶIЏU-YEᕧ hi%VҬlRXf?EDg$:<רHWA|ʅ$ <5XPƁ' ϓ`kZ}aMp?4n7NVQ<6rlz8)|pa Ĥˍ8r$csJR^)b: y@T.3)}Ͷn=qf*,:ˤFI+ e_9CC\QE$\_)-ZV&*6jȴՔ H>j~Bg(Z_O_=ƃch[\O̖7@:͡5,WֻE 22ˬ9MhǨǯ߆tʹ97vqo6'&y{̶[x >JSJ2:4YԇDdZT8nR(Wgfpa20e*3O)۶?F1"9pP% tZBu&~3Jήu&.z5Ե(XIryYͶKV8 Zr*:r*}Eoo4}}f@s@:ί,&#.;ndjY{MPrqȆ:6qjczϟ6?s"mݬ]zY(<Mc<jo>n3aɆyŀg, %0i]u3|N ܜI%ۚ|l(j,n 35Uj:k B 権]ݴvZZ[m`em]2^U&]T- :l#jmz_9[ Z&~ R_g5_\z?1a5ve I@<@"eU2ֺ$=Z+I7cg 8=h`4sȨYJShqT\bmm1oq3Pn?M ?PnsOۜUg64FvϹ3ۯ:_L.!D.czưMp7}`޲UrC;Yսn}:YgfVbTN>RCoJ CSs+xi=mTmo|f6ժbŞǾ .#P*uJ*ڭjJضWm%Mԏ794 Mp7 tjm`2L\xd :|æ9e7>FhC53:)4f)kFM}ll豎欓8<0O4:EeN1p8ժrNۻsfQ ȚZŚR|lcl]xl(sΙPyȵ+fx b~XWe]ViZ37F5n{mT_uO—XJ 'u݈+ڽ\'ETl[nl]veː:wm>ՇclyT83E۷m׷_?bS#ۘJUB<}mgΙ>QNtqdO[!Vave}c=&ԭfs_|3&yeXw@u "ۊ͟gͬ)LhTYgvE#Rض-] ֌9Td|/. : [u$@S- S˧R5{y~{/ҿ)_/p n*%' /2 rJ.^Ek1&N#Zۻϙ[m>eU|`kۜnǶ9|yIc*cYo1f?ݪ|*Wf%Oym g[ @۷m܄Z#5_aY-!aʉ.{.s6RLѕSfJɾUl`aV]I +T ƶm3'4:-(+Qu5weώU<{%ɡXl]KT& |DcҫZ}~~_{@~l>{R!bIv;oN1ivʫC& zw>Olp#rZfnasn_Cm^P;nTKwa?}?TY1L!۴o߶ƖBՉYBҌ)eCB[S2̬I0ga۶oi. 'k^o|{d$ǰD~)H,v1~FqtFW/m-1/g8CU־܌VM"ӳjl!IjQjMwrv%!(Gz)+G3ꕥ6 .vwʽjQM/IVU=s:.Cˬ8]Şg9Y4/%Ä2/>&L3Tǯ1?5Ar{dYB8EPv;~<\](Q`lsβؒhtg7u%1gUk\Bw \Ynl:BʅJ]_~.$ '|xZjIhԲ˺RU0'C&X1:GZ,-:U9Eyh&o+d z_{,6m5B]զe65zkdUw^UYaʔ@7ԃn[tBEZ dyC<+6I }A}CZ]?߿}Ϗ}4m5 B*"XǯGeVN.LVH.)e/j{:2dK-ֲ^HE\, j^a3ZbhZ.Tv"(۶`VÇa+U#t<Ř\z7T}"|F~x~r-K^+ )1PK#mTjKSy~lVD.Fcuϼ*o&7h.α ~4T>6v;rm0/)ǝ Dt?_??FLF`GPQ)tg9PY2$go7u~ v4[p!^FH=UygsY3\q:yD 0tE7H^ ϹF,׺W'U5heB?/ o`~~ ;G1wE(6.$0үr _D]۾վ3{Q|LmcT=}#;-}qڙ?s?Ǚh̒Øm_us,=lFŝLO:- ,է-,mp5e d:/Y7="b Dn ӄS8κl:7J44xF`N/BǬ]n3'kL ZgWnZkԗD&S&f@\i-L _wxkTwj0Fo4Jqo06zĬ6̛%pƄlnQk,50E3B{!ZP%1_{;qH}OےWoy43hėޔmenTÃ1oG9T8{x2*@8]{L۲19+É3|!7qLw):N76;Ū3ϪFҏhiZ=huG҄6Ymde m c cM&ڀ M1d5&p* 8A )[Ċh;i 8pe\0[WPC^U^nZ|IzO?_r /+XWY''^hJ+<|C"&vvF|qEXfo=޿}[eEۯǯeGWtǰTU#t]0J`f=g%Rn[De-eG=>k}8u2Jvf,6Εh/PINiUe4; 5CYWEc[)Sr`.eU6MV";XF֕6:gUxcK7d|喯2^ski@7z*? O[]eYu9Ek%$Lw1{lSYv?zscm|~#C??1qxsy||U 4tX [Pc7s٨>̺c#lcADَO\c5f#߇B<chμoGտW޿ېk'ݿg=mW]u:,?FIZ9K"af7-QWtZ(2.uusb&& *S]^{j׋nύ"-Ƕ,]2[kC5\俅VUs^yka m5 ?bT|ﻻWoWE9'V۷?n̙>/G lRYja}f`Y };~v)G'XFaW]%̳%l@UzeJ܂n̳;%ȗQkی Wַ-0s:xmCb\?JdLnӛRK6omcP z31#XS5 7Q#nv@|fǙ或[ӢcGGgUjU(;Tn-CY.~ff۶f2>t75ՂG60+`v'jcݾ9^E!\s(?ZsJN2lͨz>В/*܇2f(]kE@ڪd? ߶%օ&(Qi:3Z0sȲeԥf fz&BWz]I 4؈arWe44{ô2b#y肑;Gg>a?oW ?wh1b%Σ-Da[Ht"] Ά1zno;Rǟ^9fnͶmzgdo[B9yzYPY愵blJ,>ƾb4|vZ%ülȖ﷍fa5y9{>cV10{:KUլ냋/ |jUϟ'ԴvqO,N__A6U^Yg$b}dmlհVM mn.7}m6և~>Φ!\|d:<[n0Ķq{-"dj6ܼSqor݇'0ȱYb{z>n>݂YYгV0nY2 KgqZb[r0c &[̜R =QXR]5Sf-`B_׭>S0>߾Rw|?>__mXf8YhJF_Бțc{iPc)[C?>Vgr |t5ZJ};6)ӍQujqlْoG:3ՒNa`kU͍=LvS*:2YJ\Tj>|2m[pJA-C+Y5EALPBբjX|'.x?/Ra/9LA_/M~P_?\A/AаddDɦF0o7۷3jX~Ǐδe϶Ծש:IK*P-DIrPQGjDhGX>fGO*9g)Q%X{TU̸ΔL-tZ/*1Pj3%EuY2NW&ʌ ctђ-Xs!Nj>wm@dHi5g__~/A^.]$ץD`FbGCߵpi؋cqc x??a#; ==yuBUgfj1K5e׏hg_Oәuqlv#tQy^8h{aIt*A fG3PyNURUy.ʦN3UmF TSf>L@P:N+ʆѝl^gkJZr-NtWɬ:7oN:eu pNdh9jtW*la7Js&3Y*Hq7 ؾPHAᵉ, \p-0.[*=ZjG tڨDrCb?~??%?щ7<g5sjOՖne;j4a ɊmYة3`5 (Y}l|`4&az+ `ٹ*Iݕc#\NCQ۠e&%5xrkNo}=pmh.LFkv/_˙^$Wp`r lJTǻ|-6;UIum#ǏGۊFvU5D̶!(ɱ&MYղFͪV1FF,KnnNsti-IU &i uOHU%m3_橶q>X:09CMen]}Ap- 6U·A%k4G F@a;Lԕw˗ F s~W_akQ:ZV$5Xd\K 1Q]dgW!=wo|Oo}z=mܯю]U?QgYytG`09g&`)#է&-|X(m AA{6UTahӵ&N8-.WרRMSdflVNPe59e&+ZRJR& nW ~nf{Ьن:ȬEHKÃTJͫR jfp37KgϜrjڪQWKϞ2Lœd^r{ =%H_;$(kq{MU!\!{.1 Q"{'ާ}~}eo‰y?]8*,fQ;xCqS0Py,l6z{%uۆQDXT*^ 5`I2~2vCnuiL>ʮBEΑf2٩NseXpVʬRY_jZ BadF }h!>X] /{FUx9j׼Z ]_1z`;Ĝ_ǧ-sw_J Np7l-EmS}xc|73㟙3IjYo; G}=yn9F:iN $jln-9Q 1XCLfi4iHk8ߒDAAVgYMQ@͆[l& - %l#,ܫ晙.5k !Wha tj4'Huv7~E z=@vX'`ik]~eX>#3FY y:+J}Vj!3Hߖ4QKŭaڱmA>'kszksY~w{cU;p?1[?j׊Sh+T*{!O_8*,z!J2Ѕ{f:B2GWpZEBY YݬP jm! 5[Umu!+~Rm 8D3X7p͢;͖7R-dh&c:ٯr?qUBH1wK$G&,jxD&i!}ڛ%.dF9"{v=U]( 0Sai ~I^S/`~\"=2C:xEhqYA11p H` 1n> <9t&&*gՏ 8\gّvfsL#=3E94O=n*wPb(rv \FZc@g8 v$>~#ի^sp#wE-薊d9%˫% `3'wv ]0 Idwr0ګFKt_y~ҴQ,> <]O-T?;uN+/mbp }1T1#f:ىlk14߾svxq<ϑ7qj(]CUcY9כrrĈgi]+1)'<og)b,f#Qn(m=`۷Q"xUA{d}8c W{IF'oIU%{9":Ƴ݃^`(#U^7ueW s3+FTyWѥFŤ$_O&/vg_K_Xτ7 ;$98a*Zťox{>o{gC8 ?b VͨZKl ۼE/;V !3gUR zjIqiHN.=+N=K %PGo*t|2F,dluRBH¾uob9!I]k=k/LEi#rk"^~ݏB(ұKAB&*Z]3'e,u¸ı_n9p͊ßҬL`iekr}ſǕ4X]L`20BaѝLY{{r7~W?><۳|^OiFަ*T}$ےGc.fcuf5g Vw${Ƿ[P谵9{ !| fAKҜ_zx%/v~ҿPE|sl :>pmCM:N3\\َ 6#8~ߎ^?n|_XѸvVv-p瀙y񸧊H9Gyi/'Y!4#'l ti@42N-rbϳ(rw= "$612mA"[)@!w+{mLGbCpۭ=p Ymwa?= po'|6Aێb&AWNN(n|Α_y/; |3|oX?p ±[$qjyKv1g23Goo訿oQꐏq .T_|C'V'l}w9nj׸@Z:d +X  zVϟ b`Yy"7qbFډ8Rvmg\d9du oUԱ\K. ;+]ٴ 1n#QvrBwk#oXGW}|ʶ>_;۸˳z_l_[!cZ#6 q6Wa qL7z/z ԃ?3"ƷDԑnhۚ1na,=t-tWfvN F9W;ǣv?SB١nZ%](lکlGuHQѪVe[48& Ed%""FKƼ~jqd!F;seݱUgh}r@1GDgFFUKچGy&kWxWJ᳖~±t{۸&N("2e΃s~>?j=s>ypqg}2ݫDFo61oy$xSxGV:s`w7}ݖBvZ {!YvmPG1'raZhˈA5(9rgp=TT-V%،62eThYɑǣ˯r0nj^tYF6vy[t}/w:_j_Q0>(n|{Bk;oD0ļE q?NDrߩ'W^%L ٮ]2hJwheW"B|DS°}`YZK1>"a؝m_8w<~ף&<dv"x8&ӜʮvlgDe#ce1OuYgUǸAqRƣ-F\{Gl(kSؙ9# ZA033 f;u.$^PmgDǵ5[I%"K,  EatA:7 ƈq9pǸ緜۷߾xϟQkzd}~n81oU<"3H7DgTW3+z>g ׃~쾕]*`+r#q<Asδ xfqǸuspbsH;9ªg3O[*LΪ!0\u~F 2ˇ.s^/8|~-_YW_%Ž Rs'n(r#c1=Ƿu>||?u7$Ec ۿ~8~?Yk\GF0B#~׹5i-H S}K KKv &|O>{\3qpT Injsg(YDnXը*ѿ#r2 g\9Á@^Ofρ)lhU~ثDgz߼tJѻ+ğ+8eњ/V_lx`\ey;ڤ1f#y{~??z?~OXߞ~z<~?g?x?(0=g᧳p +nz58*Tv9=`_MÈ->&$y3m /yљG怢Yu1!/Q{y;ڳ݈`U!D^S vX{ZZ%Âb"Y钵ĤrNfn;ٷPA>I;qDJS 7'̿~q $- f?k KN'yv?8ӏ~y<]!.y{R%,9sqHkMH R D#2jKm㫍%mT] !ק#*S7,t kAլ6H#A|-)ŎEKWp@I}N8b{$w/)H,< GO-%LYf W8XwkOK&T{Ϳ*>~g|ղ{>dg@2ܿi/W^h~?(E8ٽUV 1mJ1ݛN0c#gGۭ޻*=xvkV=6}jt1$l A褻̃(m1ΫcXԈ[õyF3b?º27_s=4_/θ pE.kh͑#1"G1=!??Ѓk]<`W|(X>ђ1>vs43 QzjU[eՊ}d F* r~ڞq>9pm^E$567u9$X~6}c:#rv[n҆4s۴|z%6UDׯ1=2 7`w ¢n{دկ^*עkmr/_p_qV|ï8c\871312cq{#Yt*9ܴlcGd1r Fw}ҼSmn9&v9wA<7}hX[g/.'rWfoP[t\VhrCQ|_?`m_kr+ Ur]Mߝ& D99r<Q?oz\??X1xs=1T=wu\i{lr`*j/`2t=gPLV,e0#S~l-e9b=o߾ݪ4"\ ©E4d)䀓Ay? %63UZ"y| Iv@K E/묪zm#s X2;f@^ G"i_4[i_ï{:lbwIB̑1f xU[yŮެEReq;&KҔ,~}y>sAMuY?%Tk=H4b?qku>2f܇'z cג~v伿@Ddu)uGISqrgm@56#& ]#'qܾ}|k%K+X ùI3LZՀCɶmD Όmf\#\+a7>E2q_ŬBy`Ag7Wu$#rĈq'g~ø{ofv?}>Ng?Ð#Zh)xzۿ}ٵL0c nZ%IYԑ9'Xztֳ#'#cUlsQt6I 8JhWFHtJt/G(wg ys0223}6>;kǧ:߯ع絉V\{dbc<~tsϣ~Y]+R=|m= 9z-C9?`tUf3g̣DNXF&G)i&}#%7'|'}Egx)C!1sa* | 3^@Xj$yV`2{c혡:xx 7ڣ@sI /{Q`lFERC8?} _[~5^_C_C`l='M =sGT,ߞ~xz%4\c ']G`UӉ',գ·}ʑ{%"+,Xw~8McD?糖9 <}̣698 DـBY9܏mjI(GGQP]K߾1CKz{GFF`[ KjrGzC8p$jɤA 冕xJ޽LťE0_D6܋Nl}dG Č@UuxS>''-dy7oogmtء :['{-IMyo=TfG ;ZAd9k{mChsiՅ}ZRC; 2Blc1nuYcXv$Z9~mL;xzv``.9FЯmvnI!K @ZEv{Hw v|5ྈCĿ~aF;55#z&xLwepcYv@^?OUg/] E( HM< q'b[8[Ȅ[g"<O\pmju/`܏cN,0b <ӷvYHB<ӎE,Z`Ƿ\Cq7ѶڑLj1ے[pd,q~ի~<];bܾΌ Fc>O{[{tyz)Xn"c'tMVJbSwh&}|JwPYO ~nеՉ'QiFΈ 5usD27=\ϳOaVݹJe2*C-|M~PehR[D8W۷k>dE1`OFoخ8Y'$4Ub@3̼}~YP /RGl9GNC[#s`|Vѵ|k=ETe"gs&` v;' m_d^_*썛k5{?/.Iחa`|ps.d4s][y5~*W$"A gp| g%=fgU[5yo߾$'ۑuⱀlf#b[OOcI#ߪo+9ݥѸLjeUPGW^m9Ō #mv5rȍ/INqvZ?|GNydI'z8FRd2E!!8n3VF`Y.0Mf #>u}}u]<iˏſriW%GsX2F ş͓Et*{SU'SF!μ#Adm{F#q8|U{?Nʀ1߾RQҳH&"zIt&8|.$rЎ13.tLV_!T1- A[+dA%"ۘ'%DpBg9rN ,XGpǟ'ba"8CiŘ#Z fdC .$ta[`GC{౗t+L6Ƌ%YiWU8֗3J_Xp#`C3rB#0P-wՆOj@{kXF>JY}vfYNG@)-] i.F򽃩U.xkIxߏdz;-s d1Tt@3YRȌ}@G5F_\F"q?ZU@N"ɑsLƅqn&Vt&ƢYgl+*I)UZHW:mn"g[ޏ3+ %'4_/d97 }1DDq8q(N,U\kgrH#h#1 d6;w@&mc`dc1vb6jk(ү/$^d_ DI:";Ұ[mm.8uG:U]VpUS&fo}~fXZl>C@)ՙcLr PYQ^Sn~JKlf[+8~{@bzP,ûy")^kou7fe@jiLj#gw#{8ܣl L4 )6 P)FL*d:lc[{ƿXZM{_`t# 6kN{Զf?~BbgׇZ]i&0)Zc;l$߳ ,^TD4UL1Y;r7VtWb; '{[Lqa]4Zώlmg`TiTeZVqN|KyܿIurDB!x RA@rbˆGBdfZNZYADEUKq\J0(TwW~B@7Y& LD$""cpe|qs]|i˅J1|#q+HROAK]9Sxc"%?f!q<W@n%̼sҘC{BӋMGP.Z|<#-Dɶfc捐P|e61F:r뭺20UaSM &}t}z I'0؛IBI"4l[ niqik3LUg~Qٽa@(5y+CUPC7I=Vl0:=Hu#ZE"2qDysNP}Uj=~X k QU]Kf %]﫠-wuT3 3#I p/AdNR\|bƆ \Py co\;jK`R=z.R<Zf']]"kqh@W9?#5LzyXQ7HQr"s cՋ:C2{r:8x ѱ.֎ ce-: ߘy٪cq|;v|= ksLL 1Zp@h-Cˊ\g⊋tTnF22bԾ0S=&ђ!M+\R:;e>(`62.^P" 窒6#bck=[;S\֞E@v;vׄ#2/]Gi㋹S?"/xX۟v`S;v..l>=ҫdC1lyO~c9p z<)al4_z_vAxݔMJ;m! X`v3 ہKXD+(艵7GG>r\pGnkfW?8e5Sf]z𚬪ǣj0 F r眶[a @`vKRh>wEta"QWq_)PsΧəqwT5to3h-`ئBlcUw;7 @o# ~fjߢݎ]>_~wk&Q>&+'JC,+hꅾ߆+@c`=ѮNPB(2IZM 9 jRZ}Zu?9ؚȰЍ1\`N0RG`,==LT=8315v#2@C`ݶˏluE5ÉjVCbt3DB#WNC0]tAnyre+_on&nAp3,M2E=Sd(93BӾSL[?˯UyE _/g~׹'%ʍU@^≗3 !jdU] pd3z?"qƾgC Ou7a[9Q(\=:?gC-˞7yb uKm}2 N%7FdFA#pl22rlVtHr2smԨ6ogq*q/,jZ2"ڕ "/[ DѪqfl (z` P?~jb _A/^m01@M.Tljs&Bii =QZer tg{G.M9z q:bܲ5#mW63'[yoT& ruwg,V7S`RLf 2GPQZ4Nk6zMl51oskCv 12G+8ih8>%!$QCKVK2ݎY]yե̽ J9PW9'nbc^E jw^i _܉rr^cڔс>EvjVȫƏd^0r$Lβ-gZf͜ŏ>%!0s6,(gbF^~53ww}_C-M DoJHo36AfyD-,Faz'SI<-/~Urd3ϟ?X==T% #@-Վ71)R#N2³JlN!`f\mhf`XՈU^Yz$ƌ` Gx>wS}[9f2HR:IS1y}wfePjv79}I̽G.]I|^>8_gs/! lh5EE#SB7Hp12/{AAnTޮ䒺f?#޾+2B ?$X vkiW#blx/!uF#Z*2} =B`\mʍhC5d8-,DƠ)ei \-mG:H=8;r_Ne;xA:|2DU*0־N_M&#S-鄐OvCW_ם@ \1B`H֎_Eewǯ/[d.˺~a.%"TnqxJ6vtD8V}n{n,xPϟ2FX1D #tw#rk-i+A @ 3z ],aWw|1 LFD Ɔ)F*T, ΀(f<Xn?c>7!^0~YjvH>kZV2AC؝103vOBpQWߍ2װڲ}G^T_ rh:̗"1:(ȄJo$9g=~ve {l^K BBfiCbs0;>)(丽/Xog{3WȫB+>6)r1-Bd\olEhk\X @YPf>nu}TE`GEq{1s\.U{c4 i3bD͍N/nTǘ$3%h;1Մcގ)B-.uZǮ1װڍM3 r%\a9fȏ1sMrs5@h@G:OAr 66n\k8]OOIʞGc_.h Ykx9{gwSivU[_}zdH lsZDIXӲ5^hHB^w^Mu jiI'~1hH-2mn p}.oOWH?99yΖv+1o{yvCt>ķ8֒ l YUW5+ / 1]"Bw\gsd߯"b/70vCiBTJꒄ+!ǶY@盢4&۟kOkK|_hyrA|E{|\u5TL(=kin G]f9 ܎=jXsGyU6#F'۞~tkaW=ܱz}=[l;ᑬZg՞(/{FInG1gKn;-344' 166Auys4QK-LA[j F2{"|ţ,Թ8yD,rچ!tUu{<^F (B[F)~!dOJܹP%.s"aA 1i >|YAâx=;^vUKw]G!#wUߡ6mI{^& bFD;*u`Iy3V?< !?[3:}و`q:W;"!Dr}tq 9#8cLɧolH]aZ|;"N_=/e3&˔ѐYv)"JFFr qr'su| H'{[vt6 a~26 KN03L᪠[eM?pxi|e_%+NgZy͢JҙgRpd"Q*.;ֶ|Ҟg!{EΝ̻LcU(=vFg2wJ@jx 7D,tz<~!ZRj IEDz1#@NjD3[c-XTB$̱W@԰1{0,H3мT4V/n%}Ġ9XlP%|䲮i%C26J>]WFlnu0_wq\u;{4,ۢd T^FWCʾ>hf^hw>g S33|>qsŋ,J4@4ԨnᘪMp9r7&{Ybl8H@ѹwm3Rp]دb|3k@ ƒx8>!F-(,'~oQ@H+NfuUKK# a`ȤR)1&Do5FED\|s3f*a j5o-SRrbH)U twmՔex2^i S8Ƒ+,ujKa8Pkktgjd[ qd7bo68/.ᇽBL͏{Y^A}}aYzE n wgrn?2ee`"<ӑ]谽cNyK]~܃C=/%h:ÞPysy;)y|/`9zQՎ|{g (g(n7=[qEFBOtF? ݽ p)_kcft*9pܸH a) >v%!v{{f4vXauϫB@ m>.]-5,;6`?Lb|=v5e8~[%JW/xWyk8^[דޓ@2mi1vY%VAx[Aovow@UʐZ9'YhP@Xj=Fbx磎 ]B?K+ز9c޾Zk82 nS1Ue h,ҹFTlɖζh}vU()js7Yђ8J3B vf?3csa]\HDcOH_%: sg;+_Jd{ABs>WƆ`^?ghwYޯr$!bCkgKJҦ2x{OcFʃ(PabA$rfT&e+vĈT3^1×OavPת8G\$k=>KNZ57=v12عaK uG.mH@N`蕬R\s|P$_CɄJZ~jNkcƋvdH^ءSnn(Ħ@G[پ 3`j^'l 82#X #mr_,}ܦgaD%zVf2 Lr~Χ<撐cnQK%#4#r)Eu2Fx<:3RoѤ6ɝ9ocDe~"t#d4>qޞK6|w);weB2Ze۠~//Pk2Յ怯/+#] +_]&3@@fyǼòK{zyA:.AႽ K;8J䘑F OV o6:N"qlqK1ýK̷q{Kj|>tU[@] GofñcD#1m2'ܯ@YZvF0x`Wa=c0C0Jzl,+w𙎾'x Vx%0efòy"1.;nmKP ѴC6UOHڨ6sLF $cA-_mNݣIs`eFvtZmpLEЖ(?ȓyo>g)ن[sX<,D6:&yr9:Z[zچ;eDjZFItLE\]-j#R'j]쒍6:[R`]һZ8k ؤ}=PY͗ČW/M%8 ]}a[ 8؁S*s E-8IB sΌ ̌3Kʝ4wQ!3`#vF8`y`6/[׼I1q79ou躍bOky>,cBA"mV1X9șJf;:̐Z1h#>ū11#ֹܸ;5„׳BiKiX ]E{_+'=IΟGk.C_׷ڗMW/JJDe9k\/3v 齶 *TCY~e,58rUcÜx-7`MDc'E;a1Sje61 1cF[m>crm< qp6ڙ+/^ᵞ>d 4Β';2N)h]ɵ "^}[BL\OF4h&wl9/@:dlc}~|"R3Ǟ/GW9ȯK|1E~Q7,uT4ja50GĀc'Ƒ#YTiĩ)<{Ĉ[@2C{@u#{M†81#$Ƹ;ןc@y1(rZC&L&Ȍx.cV/l3b hc--=S7ZbD%g&UOdq9AXB9@iKZH)^;S)f(V$v3{P!&]^dwUh&J 4A|yE/W_!C+g ^:23##%阪n8R#Hw1c;4o׺_U-5?Ճޞ_91Ū; #-%|#eS1bsĂ-kնV{sMĩ1r^T!=Nň8m2ob(1}4ϳz#'IjLb.HzTpȽ-3{W~C??T]e*&0g]G%}Kk)E/$~þ{Bp~6ch z~y ?x@Q?}$/L˛kHC2HNҗ1#"c?BVBxY2 !ϣsfw>y. # G9A۷88Aq{T`16x\Yi-#bގm>yHC]ǀj2T {f_ZH:>ZT03sZ)<":G'C2{CvX؊k!I05]R'].ൡ }$^"ڙkL/Tc|G`W`TEc3TBJN_y; K6(pe0K!>{p"sng4пo? n_ה5t_b~5?HKV}jER{H%E "wRkF08fF[m{?gBnmKbHg|OH$j!zCcztW_Eq1Y]8\^7fd 2{3D1 11 #x)y|\d 9D.R_$H: 7Yooq]eNoGm# ~`}೓Kbdu1-[~;L7qٛbi;--`Y7½ذ@# 2󘷍 atȎqZd Ps͟ݵ: Og={)E|="L`qNsgcj9ddlX6pI>yTcVlSGvYAF%V1J8@BؗK RhO٥Vh DmIŏF@@h߯?| c$q_þ/hBdr?ajWbUe n1ʗe#FeF2``g^B& CoUX ''S-q+\8dFWz(  r1Fg͔#bC>_UYgyMposQ78IBD흦Be:FB{$jtbpM4^ML":&_~a/ϟ/k0~U /W+kPՄ#e;q0*݃ "#"*u*瑨eܿݾdB93F+L<A<ˆޟqq)TS`4TR1#WcDZ^d{7h҈4zOOB3QC9M7c!IJ_ ;G&}aٕ¼+m>@¯kkO8?}_q۳ ,=|އZ7/TKH#>Qr{zV-PZ1?{>gu3FfPٌ2zu6맻:í>]ϟQ*zKW z.Dw͑ghI]#"0'mv!->T;Tqg"?ؽݩ(RPN ʾFq`;Asس%^>^bMT.J_x#_W՝|~__f/d\ bo+]M-ǚ?.2{fl2=+V8ѫ 6i򘉱TcXi]9RFL4wLjhM4Z,Y.u`Su#̴u 1r=@ We=nUS~յ1n"EƑMl8b_݇gp̈́?iG7)Ǹ嘑}]I 9"iv1ݕpSfUS:Q'0Sѓ2V.Uvv<}Vխ?e#ƟrbyEnykpN4ЯDJRdT$ nG2;CM-/ @ByE^RC1v Q]GWBo"|ăDJ<_1w5˾n4˳2ˤ$0r9Y)IN,I9y+a<ƶEG?]+6rX+[B[v,pX$[cҧ:1)݆uOΎsZuKOQ|Id>7>?kbmm7] 'Z"gG5i $&yٴ*JqƑ}ˇʬ5Jc*H;_|"1I5w5[vHI"(24:jЅJl>PcU9LbPc32@C==}mls@h9N0&6_1U%i #z|=Bڞ lR[x}(oiЈ';ѵ:b9YT]U9Qs@\\Y 헊s&1#8,B;ZV+(VA#GoJdVtK7Wrn;= {wjZ r^%#@EUMY8&$d1 *̜e<k#|lj2AdOx;ܤSk*yb:"HE7+_Ri6^015_@ur[l<&͑+bQW0zRmߡ+Wo-'\sj'rVFÑk |`DNd9C$ Ô.QMZmS#":8=gͤCaj/<_fͧ~LB5*a t0Q#GT5J\Z{*sVfO=iT͗$1QeUe.+VBIdY ,VkF/iTN6ڀXc*(y$Xkw n947m3_^_A-mk[DRہi-딵 ՟b3W @2Y ÕZA#noh(ElљRhPm].'cL_bՀ k&B&춹fe3|\!\Y!J(`g5tG)co"sց:jHHeM2d褁5as4L_&O7ӶnЉo~Ӷ;4Pm5^*~@| nT:"wY>Z䟊q+&y|s4Su6B@zX0fEYp5JBȚj8$ t"+ o]0}Yn2ЁnCKtV礚6/ h .Yӕ.K}eRN k QUDf|{NLj،Cc<z:_5I'K!0\ǾGsPćv5EVdU(K󀳚H C<@B xl출i>M8] 5WwAḧ{ӵNH~e6&vY#P#~|80[V췽2{s]Yx:* Pտҕ8,FDzkS̬y$xg0zy.p} xM,i%q:6GW!1ZɈb60Ut+ K3z4%4 ,9jMP"%ئ3sFJ ?7PyCn?q֢|,hݒ:le^> k@o4OلJ!įZLʣYNKڪ8ro#g+ѳ U9WJ9'bl9_Anrw6W9(c ̘Z1bw%df#ry*$@Uidz:,.+`6\G4twDk~NW ˉͶMaLjeZc󥔒"F2%XNjg ʆ5< w6ٛ^Ə迧]}/<we w|N_SxӒ12Z #4ɬ~9B 9g4FY^XyŜHٯLbo/x%Qƶ !>Ԯc(CާL:]%';f)Ttf㴳U5QtPE5 aGf{+ˣpAЧ"' V6Oj+b돷NOGxܻ NkxKxZ0(*I6Sk!"M ʜY.͏} frfAŴ,׌FZO~a8f :*nbe+SݫĊJ`|mcxd1$kpDZ;m )` S_jx }^.&вFfeyd@ՊTɖbNW5;]!g(]òM_+Od\cv% &`*WE%P/蕟]ܝ ! Y,T0U3]ZGp4!ENxk$Ub|mܐ%Q!gJ(8?M;g0f&)F|mm IB:Vl/ic<":.n50+g6i23z 7(`$.K6 d'51;*50\/Lш`O(z EVxNYie e Ky`[R b 'v~+c}* Z}z'-Y!uEly; ~!h*C HI7.t@Ɔ!#t[+J9O}2{Yc^Jpemtz?HlOW\1z~muL3x0bK(3; <ع^0Do9M#p^|/ ?q`? l_4k਷΍ q0y IH1LKl7\΢f Y5e-XZpC@QUUĜ }} J{:xǃI$ i;$]_Jz<QStr. eVr(D. U_6L:ҲVe` b +y,7J}ϼHn2\OEo~\=ǻCNPDz0 =79_c-fmqWlb.|iDldj!BjTSY91"9$]4ɀky;B2^\#8G TxqJ89c6|b[+x|:2k]Z'\yZ|7i':nֹB }3s7!^ƽˑA٤2V|{Jc*IJڏb`q3B޿Kmi2`RgzSQ3&x׳mESAͲsGRSJMj1چ>[&16Ǵ_#\(0^#@Qs:f3DlQPaRDF.:rM`F.wj&oQA%Y'ZҼԁvR}S| |g# _ٛoMYCu}>ʲ cW!0…ApZ;Wދ폧mK"k&ryRG4-{Gg%}9mhwxW;[?"#zb=r*b(1ΉK8ʃissfY=689zXEsH*gUw#Ͽ^UzkTړFTjg-3p*+ÛUΠVR<|lbv.gx+1a1r.14WL'5tnt>~NbH[k{ .V?R^5XYYp]*GLl1____18=cg2{p YyLc!*gXь1ec{?~0`\:FUNZϱq?$r bĈǗHG*U[H5|VgjȔOb7.x~rT&5OX+ gkw?\;xE]?ǭv|[\1H jB"bY*,rH̜s4y`^GND2ԓ4Q̚(ב=xT*yV k~~xn,>|~ VcB:>*4!!++wC1WZM T$ ɢT1\t%*X ^goszl|FF_R7嫳ߋ2wwԦ.lX4 ?h0M:z9/ > -a\&=w~qzo.X)_юt"bR%_FY_#eĈ# Jɣژ H҂Btv.O-µ&>W,,h?o,MǾAK"pjweWIVYȈ8+d*@84LHp (FdAbaH# vZF9*83<}Ƿgf+՘\eaBvfLHO="@Ret(یթ!e/2g.:N>8$ GP>Q7R&_xvzoI Kɬ3ۋZz#{  PM,wRȜǟVc/c<#!ƃ11cfLU^<c/g0dTec$MI[00+_ AIckR㱍10Ǩusӛ?yL߯9U!ޤŘl镫ҫ .ʪ1ДS |eYFH*s+'9]CވIV]u| gGLj{nv|܌y~\aPEUuձ[{!=}T~yJ?">? xҰqYO}_ 00 :n%݉?ok!\T`@ DZ!h`ALWY$1DBIGLV8OO. t/g5LBU%aT:gbEUb֑8}fHJl8^GۚsY0݉r\ES( XBD"rMŵ*٧R]B Ũ q<}^tU:ޜ#=^n޵|/[{vlؿflW:۴/RW7Ķ:kŗUkprMm)Tfαiv(IT᰾y3%rgN:Y8Xgv3 2Su3*"ϴ=PzV4}==_ۥK.BU'檆;Z*&xUU{p1'tn{ơEEȇjwbrP 9A,u^oQviDDq2ޏJT8Duߢ_wz65'LWeD#s|_U<Ӫ.j2X(\y~";u62ԻkO]>O?,?0g͗Kh/z5+ ~ɱAC#"RMzcaqGt*148Bm\3JtVa﹎I0Y ıIV;4= =dA `LDa 6_#;]u*Y+_cIU8K w(4~8ٖ~o?qx_Ƌv]&&7W(q?wJ|ks+ }K:WE%K锋ׅ"P n\zyvlm0[9%SHz7m80k2 Yh,ֈ<1b(":BpW1q15QY4tMBt`@#A,UWQ5QJU{_2b2')nCdmtMf,)M .3:i|OrU},~F~P7Zs!`{|L8Ll-3[h 3r)#pz`ffcɈg=Ie6n tdAYۗ!L!)Ȕ_ۨzEYc0PТ(U-: 5܀i 7{?HM49(X0 F#P bZ(GM#nܓ͊ӂY7KHfQqxVl}e֏CU'TUM|+:5 +ScH1Ovlk#+bM%]NN9g%"t?c) m!s|D4EqH"_[DY੶ S!C,#*ZXખPkP.bZ.%dDvPi@~"BEXt4hG:/;V7݅w@?oqǦ7-ǔ;mܨ3􍛾75µIpiXk*V9xƩ VsU\GK\ ÔgbF+#aJSRt\9vݙBRfk+Pd$I:T̙fMWC80% ʪ\3;ْ2#b!a"Aj !DKzh%8zEjeޥBp];S Vլ#+I2ܘ#͋&Ƶ[SJ?H[uA8u.:/`Y3BF[̠Y(#Fu(dm"L^f3`cKmCjwfAd&(%~=) T WTREKMֆDL,0D P@^Xր Q| NsVY3\̛D#e8u}|+~|"3ܵz{Dxwvl; UF%^f QUyd?"4CA f9RDTy~A)F[L+ZR[t5h O),j{lAzdK; !VJVmo[Yhx4!  UtZrBz̸0rnVөt+W8F]W3'?ޓl_a70իeP*ŧJbރN]]PULLjcMaEj 60ؔ`^=5EFcd %!U`QHtyvttUU&.`l5bo0罢EX 1 ecPh!iNLEy-зց,_+3o3n3 &x`cNɛ-Y״"aXg*P5%fN$hL s|iBHTǯ) =G"l!'"R@d`7ldN @sja#_B.S2$0 فJMsAlgrsMlqhu<:ޝ.ۮʷ7ѻWcDO| Z4kNe;IIKVGIZe]Oh.\]֨ kXWS@{<|ryxh ֩HQFJνP ,s#+F&36]N}rV<,vDdYYՙ[B.WJ\JF0gܧş?ć 1s.@ثigns87Tsv%`ؾſCpWVe4خ^LTD0$v3}{WڑvqZ%!ޣf5B#IxsIsɾ=9rQ =1,֘@SLaEЏ}!fmZ|¬gx*{{_>㇢fqgUr,)/@L1޷~7?[h}_Yk63ANVgs jEipAb骬jdb8$v@Y * p+2މ K=#ƘS"5#,x3*܇Xsj޴=OgDB̪6ztkj3ښU~6lTX֒tVWd[@w;>.t/$5&>)O;+!d|oM?.幝>\WtyF+:\ K;SzЏ4 -JUf6* ilxقcQV ) F8OJ/Մ@qK(gَ#U}SfNB?_1x^js`ʶ5iUoOYLoYT]9Y+қh_&lsm'7%0BjX~fQ__fY B_{w]rL5>K8 U@D (Wfɕ3Ѩtd6<ϴ ijIg޶1+@OVsN(Υuͤs[wa|_^!Veg 1q|*z 32$RfZP\{Z<|E{Zwo˵g'9~ocۅ}(޴cԝܐˬtqpP{XlGDo>?CN9 Mb,=ҝ唣pcU8GhV٧y姾(W^D@r__`vXyYiْ·,:mVpCd Ĩ/gQo V>Vw%koVyGzܼh;pyg}q\lwDp^ˠC5i\""6yn1NUYx n#{_*0୷ :}yPHlKӄN\Y<*qHD8k˗8g *H r<_ \9̻$],D2搤S)tw7{ J5LZ"Yw~31B-~Λ oX{nc' ZSwX sWi`&餫ZپٻrDQX)ŪCX(ŸYJ7!tJJ!)~mɟ+isAVM2T22mb,BA è!U 54*"Ч4[- L\(FA Y`=AJ_CyA"'g ΢=9V9m չ/\"8F>Zx+"fx(]uG9?L,džW{ـ==¿DWH u>wչ2捝L+AY,<(3zGЬLC 夞]3{lӊx|1 ~0} kVtbm G5*I !Ɉׯ?zF{&s(iphxe %p(|stL9Ow5w*UT/y\=]6:*f-ǹ` P8MC>+SP!po7rq?S\|C:P-ժy f¬h`F:”J:5ȕ`4! NCթդm1\i;:^XP^U!lQAk{n#"g~Fn3ҘDqc͍66z R,8"OT#tt +9T[,mS+hm =st=gЅܛzA܌GvIrnךN9מ79(˵LrgX Oqtun2#Y=%D}rwHB>tYY bAFF0=k܌ȐmPLO(b@a#9gP}c4bi2#b@),skFbWmC%%:Z}F+Xw&ΐTyȋ5y'}wȹZA?d{IoဠNY¸ofW5-"3p$6}_}OPޙ a(pTߴN\u7OEܫKTh_—H1_NsP2)ShZ3=kGa:YDau\/4_d"Y!p9n]LY;Åܣ܎7U8 ;<5{YVޥwlv>Natw]uq{,vNllﲗIF?2/:xac K|jS_sJ}}Vk]jyI)1&EMb`-f LH9t(mlY`:kڹoO8M&Nf>,1ܷ=01x*ԢO'-p0XusY 隴3ʬZrE ˶Τ J\3RZg4AUw>w|,CsQp{-q fߩ41`;7?"Ə?&9Z6¶$0E$yTo @Q$㹑rrVլз*h?ٍrG΄AóҹIG,BSU (bD%^t 6߬9 x@ S\.T/D3) +vYN"cñXP̈́K/lpieɿaP?揜Ho UxXy_5#]wU6 qZjf28N;Lg±=-Y2Y"ϗ9ZM"4UtM5ArOǑ=uDsi-5HQƃ;)3)]W%T\g5I!1ZUU|sR/zdEnAp MV/pyD/47)fYHn8;\2"NnԬl_XGnVZ ce upά.^ȴz=a~;ݵgΊGWvfM0U3G:&c,mjԦf7`k-#R8h58 H:fڽuk$aUZ6Qk!4&z"N7r]<>Dµb|HxP +cr}xWf+_9"ƈ*U;6ر让&GSgH=512 p|Ҫ2#OI}>#~q\.B$'ކ79CL>Y䍾q;'Iu|kw?6ھIހqQ~D9^7;0[(,K֘xk@v<9As/VG=:S2Uu&p;'W]#0*UWSc.N*s1QR~泟GIexNB9oSW`rC ;#TNziXG9ϥUC̕ҷĄ[\W.0ӓ>f}Nm{l9w soAFP9kr.a+,H؜2*WP!WʃŽ|8%/3uf~3?];rq - ~u\θ !>E?9otW7ۚՓ;L 1gvvJ Q`8z 28y$"cf aU*CCBXs55L{rgz}T1[0ř9  F9z -"{=cNΘjJmN).?6],|D7+&z_d?6qx6?ŷL?ywX6"Ăsu:;AM%HLUr֜VhSj(}R%#[x{i3HB܈:^Y0 K5_a)^6HB.I љٞ ~[6QT.*Q,d/W"^dz'OT_ %cybc?LQg H}Τy;/C }Y?g d5щsV56̀|h4Ð` ӊ ( Rfl0LRZ.OOU23 |nPN՜08YRYT(:si(l^n>ʕFQo{R0k)xxse]޶>Qv?MqZu۽D6Yedm8?\A0߃>̻{i-#Cr̂8C1* ki!nLQ5bkxGH"7,vܡT5gUVdGZ*5Y6"pmOc] 4+^ %YgtSdkF:]],쫫ٽa?X6Ju=7?.ϸm7c} ԁwWHi:t۽s?ʝs늛E#Q$D3;d( KKGcYMXZd)U%(^sc9INJe%J7m.OW/" NՍ9^{߀Wڑq?6 ?w-1?7譫;kX[:I,j lWuB W2s"ufx|} t`YGS dk F YٺCs6ODeX:5'}sV&=a$=(I BMindeh V554p*zwL͟۶+Û>O'uďۖ&,o\tIENDB`Sigima-1.1.1/sigima/data/tests/image_formats/fiber.txt000066400000000000000000031365371514013333200227310ustar00rootroot000000000000002 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 4 4 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 7 7 7 8 8 9 9 9 8 7 6 5 5 5 5 6 7 8 8 9 9 10 10 11 12 12 11 10 9 9 8 8 7 7 7 6 6 5 5 5 5 6 8 9 10 11 11 11 9 8 8 7 7 6 5 5 6 5 5 5 5 6 7 8 9 9 9 9 9 9 9 9 7 7 7 7 7 7 7 6 6 6 6 6 6 6 6 6 5 5 5 4 4 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 2 2 1 1 2 2 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 4 4 4 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 7 7 7 8 8 9 9 9 8 7 6 5 5 5 5 6 7 8 8 9 10 10 11 11 12 12 11 11 10 9 9 9 7 7 7 6 6 6 5 5 5 6 7 9 10 11 11 11 9 9 8 8 7 6 6 5 6 6 5 5 6 6 7 8 9 9 9 9 9 9 9 9 9 8 8 8 7 6 6 6 6 6 6 6 6 6 6 6 5 5 5 4 4 4 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 2 2 1 1 2 2 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 4 4 4 5 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 7 7 7 8 8 9 9 9 8 7 6 5 5 5 5 6 7 7 8 9 10 11 11 12 11 11 11 11 11 10 10 10 7 7 7 7 6 6 6 5 4 5 7 9 10 10 11 11 10 10 9 8 7 7 6 6 6 6 5 5 6 7 8 8 10 10 10 10 10 10 10 10 11 10 9 8 7 6 5 5 6 6 6 6 6 6 6 6 5 5 5 5 4 4 4 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 2 2 1 1 2 2 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 6 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 4 4 4 5 5 5 6 6 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 7 7 7 8 8 9 9 9 8 7 6 5 5 5 5 6 7 7 8 9 10 11 12 13 12 12 12 12 12 11 11 11 8 8 7 7 7 6 6 6 4 5 7 9 10 11 11 11 11 11 10 9 8 7 6 6 7 6 6 6 6 7 8 9 10 10 10 10 11 11 11 11 12 12 11 9 8 7 5 5 7 7 7 7 7 7 7 7 6 6 5 5 5 4 4 4 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 2 2 1 1 2 2 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 7 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 4 4 5 5 5 6 6 6 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 7 7 7 8 8 9 9 9 8 7 6 5 5 5 5 6 7 7 8 10 11 12 13 14 13 13 13 13 12 12 12 12 8 8 8 7 7 7 6 6 5 6 8 9 11 11 12 12 13 12 11 10 9 7 7 6 7 7 6 6 7 7 8 9 10 10 11 11 12 12 13 13 13 13 11 10 9 7 6 6 7 7 7 7 7 7 7 7 6 6 6 5 5 5 4 4 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 2 2 1 1 2 2 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 6 7 7 7 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 5 5 5 5 6 6 6 7 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 6 6 6 6 6 6 6 6 7 7 7 8 8 9 9 9 8 7 6 5 5 5 5 6 7 7 8 10 11 13 14 15 15 15 14 14 13 12 11 11 9 8 8 8 7 7 7 7 7 8 9 11 12 13 13 13 14 14 12 11 9 8 7 6 7 7 7 7 7 8 9 9 10 11 11 12 13 13 14 14 13 13 12 11 10 9 8 7 8 8 8 8 8 8 8 8 7 6 6 6 5 5 5 5 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 5 4 4 3 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 2 2 1 1 2 2 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 6 7 8 8 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 5 5 5 6 6 6 7 7 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 6 6 6 6 6 6 6 6 7 7 7 8 8 9 9 9 8 7 6 5 5 5 5 6 7 7 8 10 12 13 15 15 18 17 16 15 13 12 10 10 9 9 8 8 8 7 7 7 8 9 11 12 14 14 15 15 15 14 13 12 10 8 7 6 8 7 7 7 7 8 9 10 10 11 11 12 13 14 15 15 12 12 12 11 10 10 10 9 8 8 8 8 8 8 8 8 7 7 6 6 6 5 5 5 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 5 4 4 3 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 2 2 1 1 2 2 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 6 7 7 8 9 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 5 5 5 6 6 7 7 7 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 6 6 6 6 6 6 6 6 7 7 7 8 8 9 9 9 8 7 6 5 5 5 5 6 6 7 8 10 12 14 15 16 19 18 17 15 13 11 10 9 9 9 9 8 8 7 7 7 9 10 12 13 15 15 16 16 16 15 14 12 10 9 7 7 8 7 7 7 7 8 9 10 11 11 12 13 14 14 15 16 12 11 11 11 11 11 11 11 8 8 8 8 8 8 8 8 7 7 7 6 6 5 5 5 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 5 4 4 3 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 2 2 1 1 2 2 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 4 4 4 4 4 4 4 4 5 5 6 6 6 6 7 7 8 8 7 7 7 6 6 6 6 6 6 6 6 6 6 6 5 5 5 6 6 7 7 7 8 8 8 7 7 6 6 6 7 7 7 7 7 7 7 7 5 5 5 5 5 5 5 5 7 7 7 7 7 7 7 7 6 7 8 8 9 10 11 11 9 9 8 7 7 6 5 5 7 8 9 11 13 15 16 17 16 16 16 16 15 14 13 12 12 11 10 9 8 7 8 8 9 10 12 13 14 15 15 15 15 14 12 10 8 7 7 7 7 7 8 9 9 10 11 11 10 11 12 12 13 12 12 12 10 10 10 9 8 8 7 7 8 9 9 10 10 9 9 8 8 8 8 7 7 6 6 6 7 7 7 7 7 7 7 7 7 7 7 6 6 5 5 5 4 4 4 5 5 6 6 6 6 6 6 6 6 6 6 6 6 7 7 8 8 7 7 6 6 6 6 5 5 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 4 4 4 4 4 4 4 4 5 5 6 6 6 7 7 7 8 8 8 7 7 7 6 6 6 6 6 6 6 6 6 6 5 5 6 6 6 7 7 7 8 8 8 7 7 6 6 6 7 7 7 7 7 7 7 7 5 5 5 5 5 5 5 5 7 7 7 7 7 7 7 7 7 7 8 9 10 10 11 11 9 9 8 8 7 6 5 5 8 9 10 12 14 16 18 18 17 17 17 16 16 14 13 12 12 11 10 9 8 8 8 8 9 10 12 13 14 15 15 15 15 14 12 10 8 7 7 7 7 7 8 9 10 10 11 11 11 12 13 14 14 14 14 13 12 12 11 10 9 8 8 7 8 9 9 10 10 9 9 8 8 8 8 7 7 6 6 6 7 7 7 7 7 7 7 7 7 7 7 6 6 5 5 5 4 4 5 5 5 6 6 6 6 6 6 6 6 6 6 6 6 7 8 8 8 8 7 6 6 6 6 5 5 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 4 4 4 4 4 4 4 4 5 5 6 6 7 7 7 8 9 9 8 8 8 7 7 7 6 6 6 6 6 6 6 6 5 6 6 6 7 7 7 7 8 8 8 7 7 6 6 6 7 7 7 7 7 7 7 7 5 5 5 5 5 5 5 5 7 7 7 7 7 8 8 8 8 8 8 9 10 10 11 11 9 9 9 8 7 6 6 5 9 10 11 13 15 17 19 19 17 17 17 17 16 15 14 13 12 12 10 9 8 8 8 8 9 10 12 13 14 15 15 15 15 14 12 10 9 8 7 7 7 8 8 9 10 11 11 11 13 14 15 16 16 16 16 16 15 15 14 12 11 10 9 8 9 9 10 10 10 10 9 9 8 8 8 7 7 6 6 6 6 6 6 6 6 6 6 6 7 7 7 6 6 5 5 5 4 5 5 5 6 6 6 6 6 6 6 6 6 6 6 6 7 7 8 9 9 8 7 7 6 6 6 5 5 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 5 5 5 5 5 5 5 5 5 5 6 6 7 8 8 9 10 9 9 9 8 8 8 8 7 7 7 7 7 7 7 7 6 6 6 7 7 7 8 8 8 8 8 7 7 6 6 6 7 7 7 7 7 7 7 7 6 6 6 6 6 6 6 6 7 7 7 8 8 8 8 9 8 9 9 10 10 11 11 11 10 10 9 8 7 7 6 6 8 9 11 13 15 17 18 19 18 18 18 18 17 16 14 14 13 12 11 9 9 8 8 9 9 10 12 13 14 15 15 15 16 15 13 11 9 8 8 7 8 8 9 9 10 11 12 12 14 15 16 18 18 18 18 18 18 18 16 14 13 11 10 9 9 9 10 11 11 10 9 9 8 8 8 7 7 6 6 6 6 6 6 6 6 6 6 6 7 7 7 6 6 5 5 5 5 5 5 6 6 6 7 7 7 7 7 7 7 7 7 7 8 8 9 9 9 9 8 8 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 5 5 5 5 5 5 5 5 5 5 6 7 8 9 9 10 10 10 10 10 9 9 9 8 7 7 7 7 7 7 7 7 6 6 7 7 7 8 8 8 8 8 8 7 7 6 6 6 7 7 7 7 7 7 7 7 6 6 6 6 6 6 6 6 7 7 7 8 8 9 9 10 9 10 10 10 10 11 11 11 10 10 9 9 8 7 6 6 7 8 9 11 13 15 17 18 19 19 19 19 18 17 15 15 13 12 11 10 9 9 9 9 9 10 12 13 14 15 15 15 16 15 13 11 10 9 8 8 8 8 9 10 11 11 12 12 14 15 16 18 19 19 19 19 19 19 17 16 14 12 11 10 9 10 11 11 11 11 10 9 8 8 8 7 7 6 6 6 6 6 6 6 6 6 6 6 7 7 7 6 6 5 5 5 5 5 6 6 6 7 7 7 7 7 7 7 7 7 7 7 9 9 10 10 10 10 9 9 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 6 6 6 6 6 6 6 6 5 5 6 7 8 9 10 10 11 11 11 10 10 10 9 9 8 8 8 8 8 8 8 8 7 7 7 7 8 8 8 9 8 8 8 7 7 6 6 6 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 8 8 9 10 10 10 10 10 10 11 11 11 11 11 11 10 10 9 8 7 7 7 7 7 9 11 13 15 16 17 19 20 20 19 19 17 16 15 13 13 11 10 9 9 9 9 9 10 12 13 14 15 15 15 17 15 14 12 10 9 8 8 9 9 9 10 11 12 12 13 13 14 15 17 18 19 19 19 19 18 17 16 14 13 12 11 10 10 11 11 11 11 10 10 8 8 8 7 7 6 6 6 7 7 7 7 7 7 7 7 7 7 7 6 6 5 5 5 6 6 6 6 7 7 7 8 8 8 8 8 8 8 8 8 9 10 11 11 11 11 10 9 6 6 6 5 5 4 4 4 5 5 5 5 5 5 5 5 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 6 6 6 6 6 6 6 6 5 5 6 7 9 10 11 11 12 12 11 11 11 10 10 10 8 8 8 8 8 8 8 8 7 7 7 8 8 8 9 9 8 8 8 7 7 6 6 6 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 8 8 9 10 11 11 11 11 11 11 11 11 11 11 11 11 10 9 8 8 7 7 8 8 10 12 14 16 17 18 20 20 20 20 19 18 17 16 14 13 12 10 10 9 9 10 9 10 12 13 14 15 15 15 17 16 14 12 10 9 9 9 9 9 10 10 11 12 13 13 11 12 13 15 16 17 17 17 18 17 17 16 15 14 13 13 10 11 11 12 12 11 11 10 8 8 8 7 7 6 6 6 8 8 8 8 8 8 8 8 7 7 7 6 6 5 5 5 6 6 6 7 7 7 8 8 8 8 8 8 8 8 8 8 10 10 11 12 12 11 10 10 6 6 6 5 5 4 4 4 5 5 5 5 5 5 5 5 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 6 6 6 6 6 6 6 6 5 5 6 7 9 10 11 12 12 12 12 11 11 11 10 10 8 8 8 8 8 8 8 8 7 7 7 8 8 9 9 9 8 8 8 7 7 6 6 6 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 8 9 10 10 11 12 11 11 11 11 11 11 11 11 11 11 10 9 9 8 7 7 9 10 11 13 15 17 18 19 20 21 21 20 19 18 17 16 14 13 12 11 10 10 10 10 9 10 12 13 14 15 15 15 17 16 14 12 10 9 9 9 9 9 10 11 11 12 13 13 9 10 12 14 15 16 16 16 16 16 16 15 15 14 14 13 10 11 11 12 12 11 11 10 8 8 8 7 7 6 6 6 9 9 9 9 9 9 9 9 7 7 7 6 6 5 5 5 6 6 6 7 7 8 8 8 8 8 8 8 8 8 8 8 10 11 11 12 12 11 11 10 6 6 6 5 5 4 4 4 5 5 5 5 5 5 5 5 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 4 4 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 7 7 8 8 8 9 9 9 9 9 7 6 6 7 7 7 8 9 10 11 12 15 15 15 14 13 12 11 10 9 9 9 9 9 9 9 9 8 8 8 8 8 8 8 8 9 9 9 8 8 7 7 7 8 8 8 8 8 8 8 8 7 7 7 7 7 7 7 7 7 8 9 10 11 12 12 13 13 13 14 14 14 13 12 11 11 11 11 11 11 11 11 11 9 10 11 13 15 18 21 22 26 25 24 23 21 18 16 15 15 14 13 12 11 11 11 11 11 12 13 14 15 16 16 16 15 14 13 11 9 9 8 8 7 8 9 11 13 15 16 17 16 16 15 14 13 13 12 11 14 14 14 14 14 14 14 14 13 13 13 13 12 11 10 9 9 9 8 7 7 7 8 8 10 10 11 12 12 12 11 11 8 8 6 5 5 5 5 5 7 7 7 7 7 7 7 7 7 7 8 9 9 10 11 11 11 11 10 10 10 10 9 9 6 5 5 4 4 5 5 6 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 4 4 4 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 7 7 8 8 8 9 9 9 9 9 8 7 6 8 7 7 8 9 10 11 12 14 14 14 14 13 12 10 10 9 9 9 9 9 9 9 9 8 8 8 8 8 8 8 8 9 9 9 8 8 8 7 7 8 8 8 8 8 8 8 8 7 7 7 7 7 7 7 7 7 7 8 9 10 11 12 13 13 14 14 14 14 13 12 12 11 11 11 11 11 11 11 11 11 11 12 14 17 20 22 24 26 25 25 23 21 18 16 15 15 14 13 11 10 10 10 10 11 12 13 14 15 16 16 15 15 14 13 11 10 9 9 9 9 10 11 12 14 16 17 18 17 16 16 15 14 13 12 12 13 13 13 13 13 13 13 13 14 14 14 14 13 12 10 10 9 9 8 7 7 8 8 9 10 11 11 12 12 11 11 10 8 7 6 6 5 5 5 6 7 7 7 7 7 7 7 7 7 7 8 9 10 10 11 11 11 11 10 10 10 10 9 9 6 5 5 4 4 5 5 6 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 4 4 4 5 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 7 7 8 8 8 8 9 9 9 9 8 7 7 8 8 8 8 9 10 11 12 13 13 13 13 12 11 10 9 10 10 10 10 10 10 10 10 9 9 9 9 9 9 9 9 9 9 9 9 8 8 8 7 8 8 8 8 8 8 8 8 7 7 7 7 7 7 7 7 6 7 7 9 10 11 12 13 15 15 15 15 15 14 13 12 11 11 11 11 11 12 12 12 13 13 14 16 18 21 23 25 26 25 25 23 21 19 17 16 14 13 12 11 10 10 10 10 11 12 13 14 15 15 15 15 15 14 12 11 10 9 9 9 10 11 12 13 15 16 18 18 17 17 16 15 15 14 13 13 13 13 13 13 13 13 13 13 15 15 15 15 14 13 11 11 9 9 8 8 8 8 9 9 10 11 11 12 12 11 10 10 8 7 7 6 5 6 6 6 8 8 8 8 8 8 8 8 7 8 8 9 10 11 11 11 11 11 11 10 10 9 9 9 6 5 5 4 4 5 5 6 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 5 6 6 6 6 6 6 6 6 6 6 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 6 6 6 7 7 8 8 8 8 9 9 10 10 9 8 8 8 8 8 8 8 9 10 11 12 12 13 13 12 11 10 9 11 11 11 11 11 11 11 11 10 10 10 10 10 10 10 10 10 10 9 9 9 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 6 6 7 9 10 12 13 13 16 17 17 17 16 15 14 13 11 11 11 12 12 12 12 13 14 14 15 16 19 21 23 25 25 25 25 23 22 20 18 16 14 14 12 11 10 10 10 10 12 13 14 15 15 15 15 15 14 13 12 11 10 9 9 9 10 11 12 13 14 16 17 17 17 16 16 16 15 15 14 14 12 12 12 12 12 12 12 12 15 16 16 15 15 13 12 11 9 8 8 8 8 9 10 10 11 11 12 12 12 11 10 9 8 7 7 6 6 6 7 7 9 9 9 9 9 9 9 9 8 8 9 9 10 11 12 12 12 12 11 10 10 9 8 8 6 5 5 4 4 5 5 6 6 6 6 6 6 6 6 6 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 5 5 5 6 6 6 6 6 6 6 6 6 6 6 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 6 6 6 7 7 8 8 8 8 9 9 10 10 10 9 9 9 9 8 8 8 9 10 11 12 12 13 13 13 12 11 11 11 11 11 11 11 11 11 11 10 10 10 10 10 10 10 10 10 10 10 9 9 9 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 6 6 8 9 11 13 14 15 18 18 18 18 17 16 14 13 11 11 11 12 12 13 13 14 14 14 15 16 18 20 22 23 25 25 25 24 22 20 19 18 15 14 13 12 11 11 11 11 12 13 14 15 15 15 14 14 14 13 12 11 10 10 10 10 9 10 11 12 13 14 15 15 16 16 15 15 15 15 14 14 12 12 12 12 12 12 12 12 15 16 16 15 15 13 12 11 9 8 8 8 9 10 11 11 12 12 12 12 12 11 10 9 8 7 7 6 6 7 8 8 9 9 9 9 9 9 9 9 8 8 9 10 11 11 12 12 12 12 11 10 10 9 8 8 6 5 5 4 4 5 5 6 6 6 6 6 6 6 6 6 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 5 5 5 5 6 6 6 7 7 7 7 7 7 7 7 7 6 6 6 6 6 6 6 6 5 5 5 5 5 5 5 5 6 6 6 7 7 8 8 8 8 9 9 10 11 10 10 10 10 9 9 8 8 9 10 10 13 13 14 14 14 13 13 12 12 12 12 12 12 12 12 12 11 11 11 11 11 11 11 11 11 10 10 10 9 9 9 9 8 8 8 8 8 8 8 8 9 9 9 9 9 9 9 9 7 7 9 11 13 15 16 17 20 20 20 19 18 16 15 14 11 11 12 12 13 14 14 14 14 15 15 16 18 20 22 23 25 25 25 24 23 21 19 18 17 16 15 13 12 12 12 12 13 13 14 15 15 14 14 13 13 12 11 10 10 10 10 11 9 10 10 11 12 13 14 14 14 14 14 14 14 14 14 14 13 13 13 13 13 13 13 13 15 15 15 15 14 13 11 11 9 8 8 8 9 10 12 12 12 12 12 12 11 10 9 8 8 7 7 7 7 8 9 9 10 10 10 10 10 10 10 10 9 9 9 10 11 12 12 13 13 12 12 11 9 8 8 7 6 5 5 4 4 5 5 6 7 7 7 7 7 7 7 7 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 5 5 5 6 6 6 7 7 7 7 7 7 7 7 7 7 6 6 6 6 6 6 6 6 5 5 5 5 5 5 5 5 6 6 6 7 7 8 8 8 8 9 10 10 11 11 11 10 10 9 9 8 8 9 9 10 13 14 15 15 15 15 14 14 13 13 13 13 13 13 13 13 12 12 12 12 12 12 12 12 11 11 10 10 10 9 9 9 8 8 8 8 8 8 8 8 9 9 9 9 9 9 9 9 8 9 10 12 14 16 18 19 21 21 21 20 19 17 16 15 11 11 12 12 13 14 15 15 16 16 17 18 20 21 23 24 25 25 25 24 23 22 20 19 18 17 16 15 14 14 14 14 13 14 14 15 15 14 14 13 13 12 11 10 10 10 11 11 11 11 12 12 13 14 14 15 12 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 14 14 14 14 13 12 10 10 8 8 8 9 10 11 12 13 12 13 13 12 11 10 9 8 7 7 7 7 7 8 9 10 11 11 11 11 11 11 11 11 9 9 10 10 11 12 13 13 13 13 12 11 9 8 7 7 6 5 5 4 4 5 5 6 7 7 7 7 7 7 7 7 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 5 5 5 6 6 7 7 7 7 7 7 7 7 7 7 7 6 6 6 6 6 6 6 6 5 5 5 5 5 5 5 5 6 6 6 7 7 8 8 8 8 8 10 11 11 11 11 11 10 10 9 8 8 8 9 9 14 15 15 16 16 16 15 15 13 13 13 13 13 13 13 13 12 12 12 12 12 12 12 12 11 11 11 10 10 9 9 9 8 8 8 8 8 8 8 8 9 9 9 9 9 9 9 9 9 9 11 13 15 17 19 20 22 22 21 21 19 17 16 15 11 11 12 13 14 14 15 16 18 18 19 20 21 23 25 26 25 25 25 24 23 22 20 19 19 18 17 16 15 15 15 15 14 14 15 15 15 14 13 13 12 12 11 10 10 10 11 11 12 13 13 14 14 15 15 16 11 11 12 12 12 12 12 12 14 14 14 14 14 14 14 14 13 13 13 13 12 11 10 9 8 8 8 9 10 11 12 13 13 13 13 12 11 10 9 8 7 7 7 7 7 9 10 10 11 11 11 11 11 11 11 11 9 9 10 11 11 12 13 13 14 13 12 11 9 8 7 6 6 5 5 4 4 5 5 6 7 7 7 7 7 7 7 7 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 6 6 7 8 8 9 9 10 10 10 9 8 8 5 6 6 6 6 6 6 6 6 6 6 5 5 4 4 4 6 6 7 7 7 7 8 8 10 11 12 13 13 13 13 12 9 9 8 8 8 9 10 10 15 16 17 19 19 18 17 16 13 12 12 12 12 12 11 11 12 12 12 12 12 12 12 12 12 12 12 12 11 10 9 8 10 10 11 11 11 11 11 12 11 10 10 9 9 9 10 11 11 11 12 14 16 19 22 23 23 23 24 24 22 19 16 14 12 12 12 13 15 17 19 20 21 21 22 23 24 25 26 27 26 26 25 24 23 23 22 22 19 18 17 17 16 15 14 14 15 15 14 14 14 15 16 16 14 13 12 11 11 11 11 11 11 13 15 18 19 18 17 16 13 13 12 10 10 10 10 10 11 12 12 13 13 14 14 15 14 14 13 11 10 9 8 8 8 9 10 11 13 14 15 15 17 16 15 13 11 9 8 7 6 7 8 9 10 10 10 10 10 10 11 12 12 12 11 11 10 10 10 11 11 12 12 12 14 13 11 9 7 6 6 5 5 5 5 6 6 6 7 7 7 7 7 7 7 7 7 7 7 7 7 6 6 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 6 6 7 8 8 8 9 10 10 10 9 9 8 6 6 6 6 6 6 6 7 6 6 6 5 5 5 4 4 6 6 7 7 7 8 8 8 10 11 12 13 13 13 13 12 10 9 9 8 8 9 10 10 14 16 17 18 19 18 17 16 13 13 13 12 12 12 12 11 13 13 12 12 12 12 12 12 14 14 14 14 13 12 10 10 10 11 11 11 12 12 12 12 12 11 10 10 9 10 10 10 10 11 12 14 16 19 22 23 23 24 25 25 23 20 17 15 12 12 12 13 15 17 19 20 22 22 23 25 26 27 28 28 28 27 26 25 24 23 22 21 18 18 17 16 15 14 14 13 16 15 15 14 14 15 15 16 14 13 13 12 11 11 11 11 12 14 16 18 19 19 18 17 14 13 12 11 10 10 10 10 11 12 12 13 14 14 15 15 14 14 13 12 11 10 9 8 9 9 10 12 13 14 15 16 16 16 14 13 11 9 8 8 6 7 9 10 11 11 11 11 10 11 11 12 12 12 11 10 10 10 10 11 11 12 12 12 14 13 11 9 7 6 6 5 5 5 6 6 6 7 7 7 7 7 7 7 7 7 7 7 7 7 7 6 6 6 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 6 6 7 8 8 8 9 10 10 10 10 9 9 7 7 7 7 7 7 7 7 6 6 6 6 5 5 5 4 6 6 7 7 8 8 8 9 11 11 12 13 13 13 13 13 10 10 9 9 9 9 10 10 14 15 17 18 19 18 17 17 14 14 14 13 13 12 12 12 14 14 13 13 12 12 11 11 15 15 16 15 14 13 12 11 11 11 12 12 12 13 13 13 13 12 11 10 10 10 10 10 10 11 12 14 16 19 21 23 25 25 26 26 24 22 18 16 12 12 12 12 14 16 19 20 23 24 26 27 28 29 29 30 30 29 28 26 24 22 21 20 17 17 16 15 15 14 13 13 16 16 15 14 14 15 15 16 13 13 13 13 12 12 12 12 14 16 18 19 20 20 19 18 15 14 12 11 10 10 10 10 11 11 12 13 14 15 15 16 15 15 14 13 12 10 10 9 10 10 11 12 13 14 15 16 16 15 14 12 11 9 8 8 7 8 9 11 11 12 12 11 11 11 12 12 12 12 11 10 10 10 10 11 11 12 12 12 13 12 10 9 7 6 6 5 6 6 6 7 7 7 8 8 8 8 8 8 8 8 8 8 7 7 7 7 6 6 6 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 6 6 7 8 8 8 9 10 10 11 11 10 10 9 9 9 9 8 8 8 8 7 7 6 6 6 5 5 5 6 6 7 7 8 9 9 10 11 12 13 13 14 14 13 13 11 11 10 9 9 9 9 10 14 15 17 18 19 19 18 17 15 15 15 14 13 13 12 12 15 14 14 13 12 12 11 11 16 16 16 16 15 13 12 11 12 12 12 13 14 14 15 15 15 14 13 11 10 10 10 10 10 10 11 13 16 18 21 22 26 26 27 27 26 23 19 17 12 12 11 11 13 16 19 21 25 26 28 30 31 32 31 31 32 31 29 27 24 22 20 19 16 16 15 15 14 14 14 13 17 16 15 14 14 14 15 15 14 14 14 14 14 14 13 13 16 17 19 20 20 20 20 19 15 15 13 12 10 10 10 10 11 11 12 13 14 15 16 17 16 16 15 14 13 12 11 10 11 12 12 13 14 15 16 16 15 14 13 12 11 9 8 8 8 9 11 12 13 13 13 13 12 12 13 13 12 12 11 10 10 10 10 11 11 12 12 12 12 11 10 8 7 6 6 6 7 7 7 7 8 8 8 9 9 9 9 9 9 9 9 9 8 8 7 7 7 6 6 6 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 6 6 7 8 8 8 9 10 11 11 11 11 11 11 11 10 10 9 9 8 8 7 7 7 6 6 6 5 5 6 6 7 8 9 10 10 11 11 12 13 14 14 14 14 13 12 12 11 10 9 9 9 10 13 14 16 18 19 19 18 18 17 16 16 15 14 13 12 12 15 14 14 13 13 12 12 12 15 15 15 15 14 13 12 11 12 13 13 14 15 16 17 17 17 16 14 12 11 10 10 10 9 10 11 13 15 18 20 22 26 27 28 28 26 23 20 18 12 11 10 10 12 15 18 21 26 28 30 32 34 34 33 32 32 31 29 26 24 21 19 18 16 16 15 15 15 15 14 14 17 16 15 14 14 14 14 14 14 15 16 17 17 17 16 15 18 19 19 20 20 20 20 20 16 15 14 12 11 10 10 10 11 11 12 14 15 16 17 18 18 17 16 15 14 13 12 12 13 13 13 14 15 15 16 16 14 13 12 11 10 9 8 8 10 11 12 13 14 14 14 14 13 13 13 13 13 12 11 10 10 10 10 11 11 12 12 12 11 11 9 8 6 6 6 6 7 8 8 8 9 9 9 9 9 9 9 9 9 9 9 9 8 8 8 7 7 7 6 6 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 6 6 7 8 8 8 9 10 11 12 12 12 12 13 12 12 11 10 10 9 9 8 7 7 7 6 6 6 6 6 6 7 8 9 10 11 11 12 12 13 14 15 15 14 14 13 13 11 10 9 9 9 10 12 14 16 18 19 19 19 18 18 18 17 16 15 14 13 12 13 13 13 14 14 14 14 14 15 15 15 15 14 13 12 11 13 13 14 15 16 17 18 19 19 18 16 13 11 10 9 9 9 9 11 12 15 18 20 21 26 27 27 27 26 23 20 17 13 11 10 9 11 14 18 21 26 28 31 34 35 35 33 32 31 30 28 25 23 20 18 17 16 16 16 16 16 16 16 16 18 17 16 15 14 14 14 14 16 17 19 20 20 20 18 18 19 19 19 19 19 19 19 19 17 16 14 13 11 10 10 9 11 11 12 14 15 17 18 19 19 18 18 16 15 14 13 13 14 14 14 15 15 16 16 16 13 12 12 11 10 9 8 8 11 12 13 14 15 15 15 15 14 14 14 14 13 12 11 10 10 10 10 11 11 12 12 12 11 10 8 7 6 6 6 6 8 8 9 9 9 10 10 10 10 10 10 10 10 10 10 10 9 8 8 8 7 7 7 7 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 6 6 7 8 8 8 9 10 11 12 12 12 12 14 14 13 12 11 10 10 9 8 8 7 7 7 6 6 6 6 6 7 8 10 11 12 12 12 13 14 14 15 15 14 14 14 13 12 11 10 9 9 9 12 14 16 18 19 20 19 19 19 19 18 16 15 14 13 12 12 12 13 14 14 15 15 16 17 17 17 17 16 15 13 13 13 14 15 16 17 19 19 20 20 19 17 14 12 10 9 9 9 9 10 12 15 17 20 21 25 26 27 27 25 22 19 17 13 11 9 9 10 14 18 21 26 28 32 34 36 35 33 32 28 28 26 24 22 19 18 17 17 17 17 17 17 17 17 18 18 17 16 15 14 13 13 14 17 19 21 23 23 22 21 20 19 19 18 18 18 18 18 19 18 17 15 13 11 10 10 9 11 11 12 14 16 17 19 19 20 19 18 17 16 15 14 14 15 15 15 16 16 16 16 17 12 12 11 11 10 9 9 8 12 13 14 15 16 16 16 16 14 14 14 14 13 12 11 10 10 10 10 11 11 12 12 12 10 9 8 7 6 6 6 6 9 9 9 10 10 10 11 11 11 11 11 11 11 11 11 11 9 9 8 8 8 7 7 7 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 6 6 7 8 8 8 9 10 11 12 13 13 13 15 14 14 13 12 11 10 10 8 8 8 7 7 6 6 6 6 6 7 8 10 11 12 13 12 13 14 15 15 15 15 14 14 13 12 11 10 9 9 9 12 13 16 18 19 20 19 19 20 19 18 17 15 14 13 13 11 11 12 13 15 16 17 17 18 19 19 18 18 16 15 14 14 14 15 16 18 19 20 21 21 20 17 14 12 10 9 9 9 9 10 12 14 17 20 21 25 25 26 26 25 22 18 16 13 11 9 8 10 14 18 21 26 28 32 35 36 35 33 32 27 26 25 23 21 19 18 17 18 18 18 18 18 18 19 19 18 17 16 15 14 13 13 13 19 20 23 24 25 24 23 21 19 19 18 17 17 17 18 18 18 17 15 13 11 10 10 9 10 11 12 14 16 18 19 20 20 20 19 18 17 15 14 14 15 16 16 16 16 16 17 17 12 11 11 10 10 9 9 8 12 13 14 16 16 17 17 16 15 15 15 14 13 12 11 10 10 10 10 11 11 12 12 12 9 9 8 6 6 6 6 6 9 9 10 10 10 11 11 11 11 11 11 11 11 11 11 11 9 9 9 8 8 7 7 7 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 4 4 5 5 5 4 4 4 5 5 6 6 6 6 6 6 6 6 6 6 6 5 5 5 4 4 3 3 3 4 4 4 5 5 6 6 6 5 5 5 5 5 6 8 8 9 9 11 12 14 15 17 17 17 16 14 13 12 12 13 14 12 11 10 9 8 7 7 6 6 7 7 8 10 11 11 12 13 13 13 14 14 15 15 15 16 15 14 12 11 10 10 10 10 12 16 19 21 22 22 21 19 18 16 14 13 13 13 14 13 13 13 14 15 18 21 22 24 24 24 23 21 19 17 16 15 16 16 18 20 22 24 26 25 24 22 19 16 14 12 11 11 11 11 12 15 18 21 22 25 26 26 25 23 20 18 16 15 13 11 10 11 14 17 20 25 27 31 34 35 35 34 34 29 27 25 22 20 20 20 20 18 18 17 17 17 18 19 20 20 19 17 16 15 16 16 17 19 21 24 26 28 27 26 25 20 20 20 19 18 18 18 17 15 15 15 14 13 12 10 9 11 12 13 15 17 18 18 18 19 19 18 17 17 17 18 18 17 17 18 18 17 17 16 15 15 14 13 11 11 12 13 14 16 17 19 20 21 20 20 19 16 16 16 15 14 13 11 10 11 11 11 10 10 9 9 9 9 8 8 7 7 8 9 9 11 11 11 12 12 13 13 13 13 13 14 14 14 13 12 11 10 10 9 8 8 7 6 6 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 4 4 4 5 5 5 4 4 5 5 5 6 6 6 6 6 6 6 6 6 6 6 5 5 5 4 4 4 3 3 4 4 5 5 5 6 6 6 6 5 5 5 6 6 7 8 9 9 11 12 14 15 17 17 17 16 14 13 13 13 14 14 12 12 11 10 9 8 7 6 6 7 7 9 10 11 12 12 13 13 13 14 14 15 15 15 16 15 13 11 10 9 9 9 10 12 16 19 22 23 23 22 20 18 16 14 13 13 13 14 14 14 14 15 16 19 21 23 24 24 24 23 22 20 19 18 17 17 18 19 21 24 26 27 27 26 24 21 17 14 12 11 10 10 11 13 15 18 21 22 24 24 24 23 22 20 18 16 15 13 12 11 12 14 17 19 26 28 31 34 35 36 35 34 29 28 25 23 21 20 20 21 19 19 18 17 17 18 18 19 20 19 17 16 15 16 17 17 20 22 25 28 29 29 28 27 23 22 21 20 19 18 17 17 15 15 15 14 13 12 10 9 10 11 13 14 16 17 18 18 20 19 19 19 19 19 19 19 18 19 19 19 18 17 16 15 14 13 12 11 11 12 14 15 19 19 21 22 22 22 21 20 18 18 17 17 16 14 12 11 11 11 11 10 10 9 9 9 8 8 7 7 7 8 9 9 11 11 11 12 12 13 13 13 13 14 14 14 14 13 12 11 10 10 9 9 8 7 6 6 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 4 4 4 5 5 5 5 4 5 5 5 6 6 6 6 6 6 6 6 6 6 6 6 5 5 5 5 4 4 4 3 4 5 5 5 6 6 6 6 6 6 6 5 6 7 7 8 9 9 11 12 14 15 17 17 17 16 15 14 14 14 15 15 13 13 12 10 9 8 7 6 6 7 8 9 10 11 12 13 14 14 14 14 15 15 15 15 15 14 12 11 10 9 9 9 11 13 17 20 22 24 24 24 21 19 17 15 14 13 14 14 15 15 15 16 17 19 21 22 23 23 24 24 23 23 22 21 19 19 20 22 24 26 28 30 31 30 27 23 19 15 12 10 10 11 12 15 17 20 22 23 22 22 21 20 19 18 18 17 15 14 12 12 12 14 17 19 26 28 31 34 36 36 35 34 30 28 26 23 22 21 21 22 21 20 19 18 17 17 17 17 19 18 17 16 15 16 17 18 22 24 27 30 32 33 32 31 28 26 24 22 20 18 17 17 16 16 15 15 13 12 10 9 9 10 11 13 15 16 18 18 20 20 20 20 21 21 21 21 21 21 21 21 20 18 17 16 13 12 11 11 12 14 15 17 22 23 23 24 23 22 21 21 19 19 19 18 17 15 14 13 11 11 11 10 10 9 9 9 7 7 7 7 7 8 9 10 11 11 12 12 12 13 13 13 14 14 15 15 14 14 13 12 10 10 10 9 8 7 7 6 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 5 6 6 5 5 5 6 6 6 7 7 7 7 7 7 7 7 7 7 6 6 5 5 5 4 4 4 5 5 5 6 6 6 7 7 7 7 6 6 6 7 7 8 9 9 11 12 14 15 17 17 17 17 16 16 16 16 16 16 14 14 13 11 10 8 7 7 6 7 8 9 11 12 13 14 14 15 15 15 15 15 15 15 15 14 12 10 9 9 8 8 12 14 17 20 23 25 26 26 22 21 18 16 14 14 14 14 14 14 15 16 17 19 20 21 22 23 24 25 25 25 24 24 22 22 23 24 26 29 31 32 35 33 30 25 20 15 12 10 10 11 14 17 20 22 23 24 21 20 19 18 17 17 17 18 15 14 13 13 13 15 17 18 25 27 30 33 35 35 34 33 29 28 26 23 22 22 22 23 22 21 20 18 17 16 15 15 19 18 16 15 15 16 17 18 23 25 29 33 36 37 36 36 33 31 28 24 21 19 17 17 17 17 17 16 14 12 10 9 9 10 11 12 14 16 18 19 21 21 22 22 22 22 22 22 24 24 24 22 21 19 17 16 12 11 11 12 13 16 18 20 26 25 25 24 23 21 20 20 19 19 19 18 17 15 13 13 11 11 11 10 10 9 9 9 7 6 6 7 8 9 11 12 13 13 13 13 13 13 13 13 15 15 16 16 15 14 13 13 11 11 10 9 8 8 7 7 6 6 6 6 6 6 6 6 5 5 5 5 5 5 5 5 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 5 5 5 6 6 6 5 5 6 6 6 7 7 7 7 7 7 7 7 7 7 7 6 6 6 5 5 5 4 4 5 5 6 6 6 7 7 7 8 8 7 6 6 7 7 8 9 9 11 12 14 15 17 17 17 17 18 18 18 18 18 18 16 15 14 12 11 9 8 7 6 6 8 9 11 13 14 15 16 15 15 15 15 15 15 15 15 14 12 11 10 9 9 9 12 14 16 19 22 25 26 27 24 22 19 17 15 14 14 15 13 14 15 16 17 18 19 19 21 22 23 25 26 26 26 26 24 24 25 26 28 31 33 34 37 35 31 26 21 16 12 10 10 13 17 21 24 25 26 25 21 20 17 15 15 16 17 18 16 15 14 14 14 15 16 17 24 26 29 32 34 34 33 32 28 27 25 23 22 22 22 23 23 22 20 18 16 15 15 15 18 17 16 15 15 16 18 19 24 26 31 35 38 40 40 40 38 35 31 26 22 20 19 19 19 19 19 17 16 13 12 10 10 10 10 12 14 17 19 21 21 22 23 25 25 25 24 24 27 26 25 24 21 18 16 15 11 11 11 13 15 19 22 24 29 28 26 24 22 20 19 18 18 18 18 17 16 14 13 12 11 11 11 10 10 9 9 9 7 7 7 8 9 11 13 14 15 15 15 15 15 15 14 14 16 16 16 16 16 15 14 14 11 11 10 10 9 8 7 7 6 6 6 6 6 6 6 6 5 5 5 5 5 5 5 5 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 5 5 5 5 6 6 6 7 6 6 6 6 7 7 7 8 8 8 8 8 8 8 8 8 7 6 6 6 5 5 5 5 6 6 6 6 7 7 7 8 9 9 8 7 7 7 7 8 9 9 11 12 14 15 17 17 17 18 19 20 20 20 19 19 17 16 15 13 11 9 8 7 6 6 8 10 12 13 15 16 16 16 16 16 15 15 15 15 16 15 14 12 11 10 10 10 11 13 15 18 21 24 26 28 25 23 20 18 16 15 15 15 14 15 17 18 19 19 19 19 21 22 23 24 25 26 26 26 25 25 26 28 30 32 34 35 38 36 32 27 22 16 13 11 12 15 20 25 28 29 29 28 23 21 17 14 13 15 17 18 16 16 15 15 15 15 16 17 22 24 27 30 32 32 31 30 27 25 24 22 21 21 22 22 22 21 20 18 16 16 15 15 18 17 16 15 16 17 18 19 24 27 31 37 40 43 43 43 41 38 33 28 24 22 21 21 22 22 21 20 18 15 13 12 11 11 11 12 15 18 21 23 24 25 27 29 30 29 28 28 29 28 26 24 21 18 15 13 11 11 12 15 18 22 26 28 32 30 27 24 21 19 18 17 18 18 17 17 16 14 12 11 11 11 11 10 10 9 9 9 7 8 8 10 11 14 16 17 18 18 17 17 17 16 16 16 16 17 17 17 17 16 15 14 12 11 11 10 9 8 8 8 7 7 7 7 7 7 7 7 6 6 6 6 6 6 6 6 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 5 5 5 6 6 6 7 7 6 6 6 7 7 7 8 8 8 8 8 8 8 8 8 8 7 7 6 6 6 5 5 5 6 6 6 7 7 7 8 8 10 9 8 7 7 7 7 7 9 9 11 12 14 15 17 17 17 18 20 21 21 21 20 20 18 17 16 14 12 10 8 7 6 6 8 10 12 14 15 16 17 17 17 16 16 15 15 15 17 16 15 13 12 11 11 11 11 12 13 16 20 23 26 28 26 24 21 18 16 15 15 15 17 18 19 21 22 22 21 21 21 22 23 24 25 25 25 24 26 26 27 28 30 33 35 36 37 35 32 27 22 17 13 11 13 17 23 28 32 32 31 30 26 23 18 14 13 14 16 18 16 16 16 16 16 16 16 16 20 22 26 28 30 30 29 29 25 24 22 20 20 20 21 21 21 21 19 18 17 16 16 16 17 17 16 15 16 17 19 20 23 27 32 37 41 44 45 45 44 40 35 29 25 23 23 23 25 24 23 22 20 17 15 14 12 12 12 13 15 19 23 25 28 30 32 34 35 35 34 33 29 28 27 24 20 17 13 12 12 12 14 16 20 25 29 32 36 34 30 26 22 20 18 18 19 19 19 18 17 15 14 13 11 11 11 10 10 9 9 9 8 9 10 11 13 16 18 19 20 20 20 19 19 18 18 18 17 17 18 18 17 16 16 15 12 12 11 10 9 9 8 8 7 7 7 7 7 7 7 7 6 6 6 6 6 6 6 6 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 5 5 5 6 6 7 7 7 6 6 6 7 7 8 8 8 8 8 8 8 8 8 8 8 7 7 7 6 6 5 5 5 6 6 6 7 7 8 8 8 10 10 9 7 7 7 7 7 9 9 11 12 14 15 17 17 17 18 20 21 22 22 21 20 19 18 16 14 12 10 8 8 5 6 8 10 12 14 16 17 17 17 17 16 16 15 15 15 18 17 16 14 13 12 12 12 10 11 13 15 19 22 26 27 26 25 22 19 16 15 15 15 19 20 22 24 24 24 23 22 21 21 23 23 24 24 24 23 26 26 27 28 30 33 35 36 37 35 31 27 21 17 13 11 14 18 24 30 34 34 33 31 28 24 19 14 12 13 16 18 16 16 16 16 16 16 16 16 19 21 24 27 29 29 28 27 24 23 21 20 19 19 20 21 21 20 19 18 17 17 17 17 17 16 16 15 16 17 19 20 23 26 32 37 42 45 46 46 44 41 36 30 26 24 24 24 26 26 25 23 21 18 16 15 13 13 12 13 16 20 24 26 32 34 36 39 40 39 38 37 30 29 27 24 20 16 13 11 12 13 14 17 22 27 31 34 39 36 32 28 24 21 19 19 20 20 20 19 18 17 15 14 11 11 11 10 10 9 9 9 9 9 10 12 15 17 20 21 22 22 21 21 20 20 19 19 17 18 18 18 18 17 16 15 12 12 11 10 10 9 8 8 7 7 7 7 7 7 7 7 6 6 6 6 6 6 6 6 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 6 6 6 7 7 7 8 8 10 10 10 9 9 8 8 7 8 7 7 7 7 7 6 6 6 6 6 7 7 8 8 8 8 9 9 10 10 9 8 8 8 8 9 9 11 13 14 15 17 19 21 22 23 23 22 21 19 19 19 17 16 14 12 11 9 9 9 10 12 14 16 17 19 18 17 16 15 15 15 15 16 16 16 16 15 14 13 12 12 13 15 17 20 23 25 26 24 23 20 16 13 13 15 18 19 20 23 26 27 26 25 24 21 21 21 21 22 23 24 24 28 28 27 27 28 30 32 33 34 34 33 30 25 19 14 11 11 15 21 29 36 40 39 38 32 27 20 14 12 12 15 17 18 18 19 19 19 18 17 16 18 20 23 26 28 29 29 29 23 20 16 14 15 17 19 19 22 21 20 18 17 16 16 15 18 17 16 16 17 18 20 21 22 25 30 35 40 43 45 46 46 42 37 32 28 26 26 26 29 28 27 25 22 19 17 15 13 13 14 16 19 24 28 31 35 38 42 45 45 43 41 38 33 31 27 23 19 16 14 13 12 13 16 20 26 31 35 37 42 39 35 31 29 25 21 18 21 21 21 20 19 17 16 15 14 14 13 11 11 11 11 11 8 9 11 14 16 19 20 21 23 23 23 23 23 21 20 20 22 21 21 20 18 17 17 16 12 11 10 9 9 9 9 10 8 8 8 7 7 6 6 6 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 6 6 6 6 6 7 7 7 8 8 8 10 10 10 9 9 9 8 8 8 8 8 7 7 7 7 6 6 6 7 7 7 8 8 8 9 9 10 10 10 9 9 8 9 9 9 10 11 13 14 15 17 18 20 22 23 23 22 21 20 20 19 18 17 15 13 12 9 9 10 11 12 14 16 17 18 18 16 15 15 14 14 15 16 17 17 17 16 15 14 14 14 14 16 18 21 23 25 26 25 24 21 17 13 13 16 19 21 23 26 29 30 29 27 26 22 22 22 22 22 23 24 25 27 27 26 26 27 29 31 32 34 34 33 30 26 20 15 12 12 15 22 30 38 42 42 41 34 30 22 16 12 12 15 17 18 19 19 20 19 18 17 16 17 19 22 25 27 28 28 28 22 19 15 14 16 18 20 20 22 21 20 18 16 15 15 15 17 17 16 16 18 19 21 22 23 25 29 34 39 42 44 45 44 41 37 32 29 27 27 28 31 30 29 27 24 21 18 17 14 15 15 17 21 26 30 33 38 40 43 45 45 43 40 38 34 32 28 23 19 15 13 12 13 15 18 23 28 33 37 39 42 39 34 31 29 26 22 19 22 22 22 21 20 18 17 16 15 14 13 12 11 11 11 11 9 10 12 14 17 19 21 22 23 23 23 23 23 22 21 20 22 21 21 19 18 17 16 16 12 11 10 9 9 9 9 10 8 8 8 7 7 7 6 6 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 6 6 6 6 7 7 7 8 8 8 9 9 11 11 10 10 10 9 9 9 9 9 9 8 8 7 7 7 6 7 7 7 8 8 8 8 9 9 10 11 11 10 10 9 9 9 9 10 11 13 14 15 17 18 20 22 23 22 22 21 21 21 20 19 17 15 14 12 9 10 10 11 13 15 17 18 18 18 16 15 14 14 14 14 17 17 18 18 18 17 16 16 17 17 19 20 22 24 25 25 25 24 22 18 14 14 17 19 25 27 30 33 34 33 30 29 23 23 22 22 23 23 24 25 26 25 24 24 25 26 28 29 33 33 33 30 27 22 17 14 13 17 23 33 41 46 48 47 40 35 27 19 14 13 14 16 18 19 20 21 20 19 17 16 16 18 22 25 27 27 27 26 20 18 15 15 17 20 21 22 23 21 19 17 16 15 14 14 17 17 17 18 19 21 23 24 24 26 29 33 37 40 42 43 43 40 36 33 30 29 30 30 33 32 31 29 26 23 20 18 15 16 17 20 23 28 32 35 40 42 44 46 46 43 40 38 35 32 28 22 18 14 12 11 14 17 21 27 32 37 40 42 41 38 34 31 29 27 24 22 23 23 23 22 21 19 18 17 16 15 13 12 11 11 11 11 10 11 13 15 18 20 22 22 22 23 23 23 23 22 21 21 22 21 20 19 18 17 16 15 12 11 10 9 9 9 9 10 8 8 8 8 7 7 7 6 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 6 6 6 7 7 8 8 8 8 9 9 9 10 11 11 11 11 11 10 10 10 10 10 10 9 8 8 7 7 7 7 7 8 8 8 9 9 9 10 11 11 12 11 11 11 10 10 10 10 11 13 14 15 17 18 20 21 22 22 21 21 22 21 21 20 18 16 14 13 10 10 11 12 14 16 17 19 19 18 17 15 14 14 13 13 17 18 19 19 20 19 19 18 20 21 21 22 24 25 25 26 27 26 23 19 15 15 18 21 27 30 33 36 37 35 32 30 23 22 22 21 22 22 23 23 24 23 22 22 22 24 26 27 32 32 32 30 27 23 18 16 15 18 25 36 45 52 55 55 48 42 33 23 17 14 14 15 19 20 21 22 22 20 18 16 15 18 22 25 27 27 25 24 19 16 15 15 18 21 23 23 23 21 20 17 16 15 14 14 17 17 18 19 21 22 24 25 26 27 30 33 37 40 42 43 42 40 37 35 33 32 33 33 34 34 32 29 26 23 20 18 15 16 18 21 25 30 33 36 40 41 44 46 46 45 43 41 36 32 27 22 17 13 12 11 15 18 23 30 35 39 41 42 40 37 33 30 29 27 25 24 24 24 24 23 22 21 19 18 16 16 14 13 11 11 11 11 12 12 14 16 18 20 22 23 22 23 23 24 24 23 22 22 22 21 20 19 17 16 15 14 12 11 10 9 9 9 9 10 9 9 8 8 8 7 7 7 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 7 7 7 8 9 9 9 10 10 10 10 11 11 11 11 11 12 12 12 12 11 11 10 9 8 7 7 7 7 8 8 8 9 9 9 9 10 11 12 12 13 12 12 11 11 11 11 12 13 14 15 16 17 19 21 22 22 21 20 22 21 21 20 18 16 14 13 11 11 12 13 14 16 18 19 21 20 18 16 15 14 14 14 17 18 19 20 21 21 21 20 23 23 24 25 25 26 27 27 28 27 24 20 17 17 19 22 29 31 35 38 38 36 32 30 22 22 21 21 20 21 21 22 23 22 21 20 21 22 23 24 30 30 31 30 27 23 19 17 17 20 28 39 50 58 63 64 57 50 40 29 20 16 15 15 19 20 22 23 23 21 18 17 15 18 22 26 27 27 25 23 18 16 15 16 19 22 23 23 22 21 20 18 17 16 16 16 18 19 20 21 23 24 24 25 27 28 30 33 37 40 43 45 42 41 39 37 36 36 36 36 35 34 32 29 26 22 19 17 15 17 19 23 27 31 35 37 39 40 43 45 46 45 44 44 35 32 26 20 16 13 12 12 16 20 26 32 37 40 41 41 38 35 31 28 27 27 26 25 25 25 24 24 23 21 19 18 17 16 15 13 12 11 11 11 12 13 14 16 18 20 21 22 22 23 23 24 24 24 23 23 22 22 20 19 17 15 14 13 12 11 10 9 9 9 9 10 9 9 9 8 8 8 7 7 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 6 6 6 6 7 7 7 8 9 9 10 10 10 11 11 11 11 11 12 12 12 13 13 13 13 13 12 11 10 9 8 7 8 8 8 8 9 9 9 10 10 10 11 13 13 14 13 13 12 12 12 12 12 13 14 15 16 17 19 21 21 21 20 20 21 21 20 19 17 15 14 12 12 12 12 14 15 17 19 20 22 21 20 18 16 15 15 15 16 17 18 20 21 22 22 22 24 25 25 26 27 28 29 30 29 28 25 21 18 18 20 23 30 33 37 40 40 37 33 30 24 23 22 21 21 21 22 22 23 22 20 19 20 21 22 23 27 28 29 28 26 23 20 18 18 22 30 42 54 64 70 72 66 59 47 34 24 18 16 15 19 21 23 25 24 22 19 17 16 19 23 27 28 27 25 23 18 17 16 17 20 23 23 23 22 21 20 19 19 19 19 19 20 21 22 23 24 24 24 24 26 27 29 32 36 40 43 45 45 44 42 41 40 39 39 39 36 35 33 30 27 23 19 18 17 18 22 26 30 34 37 39 39 40 42 44 44 44 44 43 34 30 25 19 15 13 13 14 19 23 29 35 40 41 40 40 36 32 28 26 26 26 26 26 24 24 24 23 22 21 19 18 18 17 15 14 12 11 11 10 12 13 14 16 17 19 20 21 22 23 23 24 25 24 24 24 22 22 20 18 16 15 13 12 12 11 10 9 9 9 9 10 10 9 9 9 8 8 8 8 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 6 6 6 7 7 7 8 8 10 10 10 11 11 11 12 12 12 12 12 13 13 13 14 14 14 14 13 11 10 9 8 7 8 8 8 9 9 9 10 10 10 11 12 13 14 14 14 14 13 12 12 12 12 13 14 15 15 17 19 20 21 21 20 20 20 20 19 18 17 15 13 12 12 13 13 14 16 18 20 21 24 23 21 19 18 16 16 16 15 16 18 19 21 22 22 22 25 25 26 28 29 30 31 32 30 29 26 22 19 19 21 24 31 34 39 42 42 39 34 31 26 25 24 24 23 23 23 24 23 22 20 19 19 20 21 22 25 26 27 27 25 23 20 18 20 23 32 44 58 69 75 78 73 66 53 39 28 21 17 16 19 21 24 26 25 23 19 17 17 20 25 28 30 28 25 23 19 17 17 18 21 23 23 22 21 21 20 20 21 22 22 23 22 23 24 25 25 24 23 23 22 23 25 28 33 38 42 44 47 47 46 44 43 42 41 41 38 37 35 32 28 24 21 19 19 21 25 30 34 38 41 43 42 42 43 43 42 41 40 39 32 29 23 18 15 14 14 15 23 27 33 40 43 43 41 39 33 30 26 23 24 25 26 26 24 24 24 23 22 20 18 17 19 18 16 14 12 11 11 10 12 12 13 15 16 18 19 20 22 23 24 24 25 25 25 24 22 22 20 18 16 14 13 12 12 11 10 9 9 9 9 10 10 10 9 9 9 8 8 8 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 6 6 6 7 7 8 8 8 10 10 11 11 11 12 12 12 12 12 12 13 13 14 14 15 15 14 13 12 10 9 8 8 8 8 8 9 9 10 10 10 10 11 12 13 14 15 15 15 13 13 12 12 12 13 14 14 15 17 18 20 21 21 20 19 19 19 19 17 16 14 12 11 13 13 13 14 16 18 20 21 26 24 22 20 18 17 17 16 14 15 17 19 21 22 22 22 25 26 27 28 30 32 33 33 30 29 27 22 19 19 22 24 33 36 41 44 44 40 35 32 28 28 27 26 25 25 25 26 23 22 21 19 19 20 21 22 23 24 25 26 25 22 19 17 20 24 33 45 59 71 78 81 78 70 56 42 30 22 18 17 19 21 24 26 26 23 20 17 18 21 26 29 31 29 25 23 19 18 18 19 21 23 22 21 21 21 21 21 22 23 25 25 23 24 25 26 26 24 23 22 19 20 22 26 31 36 41 43 49 49 48 46 45 43 42 42 40 39 37 34 30 26 23 21 22 24 28 33 38 41 44 45 45 45 44 43 41 38 36 35 31 28 22 17 14 14 15 17 26 30 37 43 45 45 42 40 32 28 24 22 23 25 26 26 23 23 23 22 21 19 18 17 19 18 16 14 12 11 11 10 11 12 13 14 16 17 18 19 22 22 24 25 25 25 25 25 23 22 20 18 16 14 12 11 12 11 10 9 9 9 9 10 10 10 10 9 9 8 8 8 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 6 7 7 8 9 9 11 11 11 11 11 11 11 11 13 13 14 15 15 16 17 17 14 14 14 14 13 12 11 10 10 9 9 8 8 9 9 10 11 12 14 15 16 17 17 17 17 16 14 13 12 12 13 14 17 17 17 17 17 17 17 17 17 16 16 15 14 13 12 12 14 13 13 14 17 21 25 27 26 26 25 24 22 19 17 16 14 16 17 17 17 18 21 24 24 27 30 33 35 35 35 34 36 32 27 23 21 21 23 24 31 34 39 43 44 43 39 37 32 31 30 28 27 27 27 27 25 24 21 20 19 20 22 23 23 24 26 26 25 22 20 18 18 24 34 46 57 67 74 78 78 70 58 44 31 23 18 16 14 18 22 26 27 24 21 18 21 23 26 31 33 32 27 23 21 20 20 21 24 24 23 21 23 23 24 25 26 27 28 28 28 27 27 27 27 26 23 20 18 18 20 23 27 33 38 41 48 47 46 45 44 42 41 41 43 42 39 36 32 29 26 24 24 28 34 40 45 47 48 47 46 43 39 37 36 35 33 31 34 21 14 15 13 7 11 21 28 34 42 48 50 47 41 37 30 27 23 22 24 26 28 28 23 23 22 21 20 20 19 18 20 19 17 14 12 11 10 10 13 13 13 14 15 17 18 19 20 22 25 27 27 26 23 21 20 19 17 15 13 12 12 11 11 11 11 11 11 11 11 11 10 10 10 9 9 8 8 8 7 7 7 6 6 5 5 5 6 5 5 4 4 5 5 6 5 5 5 4 4 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 6 7 7 8 9 9 11 11 11 11 11 11 11 11 13 13 14 15 16 16 17 17 15 15 15 15 14 13 11 10 10 10 9 8 8 9 10 10 11 12 14 15 17 17 17 17 18 17 15 14 13 13 13 14 16 16 16 16 16 16 16 16 16 15 15 14 13 12 12 11 13 13 13 15 18 22 26 28 28 28 26 24 22 19 17 15 14 16 17 17 17 18 21 23 25 28 31 34 36 37 36 36 35 32 28 24 21 22 23 25 31 35 39 43 45 44 41 39 35 34 32 30 30 29 30 30 27 26 24 22 21 22 23 24 24 25 26 26 25 23 21 19 19 23 31 41 52 62 69 73 72 66 55 43 32 23 17 15 15 17 21 24 25 23 20 18 21 23 27 32 34 33 28 24 20 20 20 22 25 26 25 24 25 25 26 27 28 29 30 31 30 29 29 30 30 29 25 22 17 17 18 20 25 31 37 41 46 45 44 43 42 42 42 41 44 42 40 37 33 29 26 25 25 29 34 40 44 47 47 47 44 41 38 35 34 33 31 28 25 19 19 26 26 17 15 21 32 37 45 50 51 46 40 35 30 27 23 22 24 26 28 28 24 23 23 22 21 20 19 19 19 18 16 14 12 11 10 10 12 12 12 13 14 16 17 19 21 22 25 27 27 25 23 21 20 19 17 15 13 12 11 11 11 11 11 11 11 11 11 11 10 10 9 9 9 8 8 8 7 7 7 6 6 5 5 5 6 5 5 4 4 5 5 6 5 5 5 4 4 4 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 6 7 7 8 9 9 11 11 11 11 11 12 12 12 13 14 14 15 16 17 17 17 15 16 16 15 15 13 12 11 11 10 9 9 9 9 10 11 12 13 14 16 17 18 18 18 19 18 17 15 14 14 14 14 15 15 15 15 15 15 15 15 14 14 14 13 12 11 11 11 12 12 13 16 19 24 28 30 31 30 28 25 22 18 16 15 14 16 17 17 17 18 20 22 27 29 32 36 38 39 38 37 35 32 28 24 22 23 24 25 32 35 39 44 45 45 42 41 37 36 34 33 32 32 33 34 30 29 28 26 25 25 25 25 25 26 26 27 26 24 22 21 20 23 28 35 44 53 61 65 64 60 52 43 33 24 18 14 16 18 20 22 22 21 19 17 21 23 27 33 36 34 30 25 20 19 20 22 26 29 29 29 28 28 29 30 32 33 34 34 32 32 32 34 34 31 27 23 16 16 16 17 22 28 35 39 42 41 41 40 40 41 41 42 44 43 41 38 34 30 27 25 26 29 34 39 43 45 46 46 42 39 35 33 31 29 27 25 19 16 19 28 29 23 21 25 37 42 49 53 52 46 38 32 29 27 24 23 25 27 27 26 24 23 23 22 21 21 20 20 18 17 15 13 12 11 11 10 12 11 11 11 12 14 16 18 21 22 24 26 26 24 22 20 19 18 16 14 13 12 11 11 11 11 11 11 11 11 11 11 10 9 9 9 8 8 8 8 7 7 6 6 6 6 5 5 6 6 5 5 5 5 6 6 5 5 5 5 4 4 4 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 6 7 7 8 9 9 11 11 11 12 12 12 12 13 14 14 15 15 16 17 18 18 17 17 17 17 16 15 13 12 11 11 10 10 10 10 11 11 12 13 15 17 18 19 20 20 20 20 19 17 16 15 15 15 14 14 14 14 14 14 14 14 13 13 13 12 12 11 11 11 12 12 14 17 21 26 29 31 33 32 29 25 21 18 15 14 14 16 17 17 16 17 19 22 27 29 33 37 39 40 40 39 35 33 29 26 24 24 25 26 32 34 39 43 45 44 43 42 37 36 34 33 33 34 36 37 34 33 33 32 31 29 28 28 27 28 28 28 27 26 24 23 23 24 26 30 36 44 51 55 55 53 50 44 36 28 20 16 18 19 20 21 21 19 18 17 18 21 27 33 36 35 30 25 19 19 20 23 28 31 33 33 31 32 33 35 36 37 39 39 33 33 34 35 35 32 26 22 16 15 14 15 20 26 33 37 38 37 37 37 38 39 41 42 44 44 42 39 36 31 28 25 27 29 33 37 41 42 43 43 39 36 32 29 28 26 23 21 21 15 13 16 19 20 25 33 41 46 52 55 53 47 38 32 29 27 25 25 26 27 26 25 23 23 22 22 21 21 20 20 17 16 15 13 12 12 12 12 11 10 9 9 11 13 16 17 21 22 24 25 24 23 21 20 18 17 15 13 12 11 11 11 10 10 10 10 10 10 10 10 9 9 9 8 8 8 7 7 6 6 6 6 6 6 6 6 7 6 5 5 5 5 6 7 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 6 7 7 8 9 9 11 11 11 12 12 13 13 14 14 14 15 16 17 17 18 18 18 18 18 18 17 16 15 14 12 12 11 11 11 11 12 12 12 13 15 17 19 20 21 21 22 22 21 20 18 17 16 15 14 14 14 14 14 14 14 14 13 12 12 12 12 11 11 11 12 13 16 19 23 27 30 32 34 32 28 24 20 17 15 14 15 16 17 16 16 16 18 21 26 29 32 36 39 40 40 39 34 33 30 27 26 25 26 27 31 34 37 41 42 42 41 40 35 34 32 32 33 36 39 41 39 39 40 40 39 37 35 34 33 33 32 32 30 29 28 27 28 27 26 27 31 37 42 46 48 48 48 45 40 32 25 20 20 21 22 22 22 20 18 17 16 20 26 33 36 35 30 25 19 19 19 23 28 33 36 36 35 35 36 38 40 42 43 43 36 35 35 34 33 30 24 20 15 15 14 16 20 26 32 35 34 34 33 33 34 37 39 41 44 43 42 40 36 32 27 25 26 28 31 34 36 38 39 39 36 33 29 26 25 23 21 19 21 16 12 12 15 21 30 38 46 49 54 56 53 46 38 32 28 27 26 26 27 27 25 23 21 21 21 21 21 20 20 20 17 16 15 14 13 13 13 14 11 10 9 8 10 12 15 18 22 22 23 23 23 21 20 19 16 15 14 12 11 11 11 11 10 10 10 10 10 10 10 10 9 9 8 8 8 7 7 7 6 6 6 6 6 6 6 6 7 7 6 5 5 6 7 7 6 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 6 7 7 8 9 9 11 11 12 12 13 14 14 14 15 15 15 16 17 18 18 19 19 19 19 19 18 17 16 15 13 13 12 11 11 12 13 13 12 14 16 18 20 21 22 22 23 23 23 22 20 18 17 16 14 14 14 14 14 14 14 14 13 13 13 13 12 12 12 12 14 15 18 21 25 28 30 32 33 31 27 22 18 16 14 14 15 16 17 16 15 15 18 20 24 26 30 34 37 38 38 38 34 33 30 28 27 27 27 27 30 32 35 37 39 38 37 36 32 31 30 30 33 37 42 45 46 47 49 50 50 48 46 44 43 42 40 39 36 35 33 32 32 31 29 28 29 32 35 38 41 43 44 44 41 35 28 24 23 24 25 26 25 22 19 18 15 19 26 34 38 37 32 27 19 18 19 22 28 33 36 38 37 38 39 41 43 45 46 47 40 38 35 33 31 27 22 18 15 15 16 18 22 27 32 34 32 31 30 30 31 34 37 39 42 42 42 40 36 31 26 24 24 25 27 29 31 32 33 33 32 30 26 24 23 22 20 18 19 18 19 21 26 32 38 42 53 54 56 55 50 43 36 31 27 27 26 27 28 27 24 21 19 19 19 19 19 19 19 19 17 16 16 15 15 15 16 16 12 11 9 8 9 12 16 18 22 22 22 22 21 20 19 18 15 14 13 11 11 10 10 10 9 9 9 9 9 9 9 9 8 8 8 8 7 7 7 6 5 5 6 6 6 6 7 7 7 7 6 6 6 6 7 7 7 6 6 6 5 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 6 7 7 8 9 9 11 11 12 12 13 14 15 15 15 15 16 16 17 18 19 19 20 20 20 20 19 18 17 16 14 13 12 12 12 12 13 14 13 14 16 18 21 22 23 23 25 25 25 24 22 20 17 16 15 15 15 15 15 15 15 15 13 13 13 13 14 14 14 14 15 17 20 23 26 28 30 31 32 29 25 20 17 15 14 14 15 16 17 16 15 15 17 19 21 24 28 32 35 36 36 36 34 33 31 29 28 28 28 28 29 31 33 34 35 34 33 32 30 29 29 30 34 40 46 50 54 56 59 62 62 60 58 56 54 53 50 47 44 42 40 39 37 35 33 31 30 30 31 32 35 37 40 41 40 35 30 26 25 27 29 30 29 25 21 18 17 21 29 37 41 40 34 30 19 18 18 21 27 33 36 38 38 39 40 42 45 47 48 49 45 42 37 32 29 25 21 17 15 16 19 22 25 29 32 34 31 30 28 27 28 31 34 37 41 41 41 39 36 30 25 22 21 22 23 25 26 27 28 28 30 27 24 23 22 22 20 19 19 21 24 28 35 43 49 52 61 61 58 54 47 39 31 27 27 27 27 28 29 27 23 20 18 18 18 18 18 18 18 18 18 17 17 16 17 17 18 18 13 12 9 8 9 13 17 20 22 22 22 21 20 19 18 18 14 13 12 11 10 10 10 10 9 9 9 9 9 9 9 9 8 8 8 7 7 7 6 6 5 5 5 6 6 7 7 7 8 7 7 6 6 7 7 8 7 7 6 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 6 7 7 8 9 9 11 11 12 13 14 14 15 16 15 15 16 17 17 18 19 19 20 21 21 20 20 18 17 16 14 13 13 12 12 13 13 14 13 14 16 19 21 23 23 24 25 25 25 25 23 20 18 16 15 15 15 15 15 15 15 15 14 14 14 14 14 14 14 15 17 18 21 24 26 28 29 30 30 28 23 19 16 14 14 14 15 16 17 16 14 15 17 19 20 22 26 31 34 35 35 35 34 33 31 30 29 28 28 28 29 30 31 32 32 31 30 29 29 29 29 31 35 42 49 53 59 62 66 69 70 68 65 63 62 60 57 53 50 47 45 44 39 38 35 33 31 30 30 30 31 34 37 39 38 35 30 27 26 29 32 33 32 27 22 18 18 23 31 39 44 43 37 32 20 18 18 21 26 32 36 37 39 39 41 43 45 47 49 50 49 45 38 32 28 24 21 18 15 17 21 24 28 31 33 33 31 29 27 26 27 30 33 35 40 40 40 39 35 30 25 21 19 20 21 22 23 24 25 25 28 26 23 22 22 22 21 19 22 23 24 27 35 48 58 63 68 65 60 53 44 35 27 23 26 26 27 29 29 27 23 19 16 16 17 17 17 17 17 17 18 18 17 17 18 18 19 20 14 12 10 8 10 13 17 20 22 22 21 20 19 19 18 17 13 13 12 10 10 10 10 10 9 9 9 9 9 9 9 9 8 8 8 7 7 6 6 6 5 5 5 6 6 7 7 7 8 7 7 6 6 7 7 8 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 5 5 5 5 5 5 5 5 6 5 5 5 5 6 7 8 10 10 11 12 14 15 16 16 14 15 16 16 17 18 19 19 20 20 20 20 20 19 17 17 14 14 13 13 13 14 14 15 15 16 17 19 21 22 24 24 25 26 27 27 26 23 20 18 17 16 15 14 14 14 14 15 16 16 15 15 15 15 16 16 19 19 21 23 25 28 31 32 31 28 24 22 20 19 17 15 18 18 17 16 15 15 14 14 14 17 22 26 28 31 34 37 37 35 32 31 30 29 27 26 31 32 33 31 28 26 25 25 22 26 31 34 37 42 49 55 62 71 78 80 81 83 81 77 75 71 65 60 57 54 51 49 45 41 36 32 30 28 26 24 29 30 32 33 34 34 33 32 33 34 36 37 37 33 27 22 20 23 30 41 50 51 43 35 27 21 16 17 25 32 35 34 38 39 39 40 43 48 54 58 51 47 42 35 28 23 19 17 19 21 25 29 31 32 32 32 28 27 25 24 24 27 30 32 38 38 39 38 35 30 25 22 18 18 17 16 17 18 20 21 25 27 28 27 25 24 24 24 25 25 28 36 47 59 67 71 77 72 65 54 43 33 25 21 26 29 31 31 28 24 21 20 15 15 16 17 17 18 19 19 18 19 21 23 24 24 23 22 16 14 11 10 11 15 19 22 24 24 23 22 20 17 15 14 15 14 12 11 9 9 9 9 9 9 9 9 9 9 9 9 8 8 8 7 7 6 6 6 5 6 7 8 8 8 7 7 9 9 8 7 6 6 5 4 7 7 7 7 7 7 7 7 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 5 5 5 5 5 5 5 5 6 6 5 5 6 6 7 8 10 10 11 12 14 15 16 16 15 15 16 17 18 18 19 19 19 20 20 20 19 19 18 17 16 15 15 14 14 14 15 15 16 17 18 19 21 23 24 25 25 26 27 27 26 23 20 19 18 17 16 15 15 15 15 16 18 18 18 17 17 18 18 18 19 20 22 24 28 31 33 35 33 30 25 22 21 19 16 14 17 18 18 18 17 16 15 14 14 17 21 24 26 30 34 37 38 36 32 30 29 28 27 27 32 33 34 32 29 26 24 24 21 25 29 32 35 40 48 55 65 75 84 88 90 92 90 86 83 78 72 66 61 57 53 50 44 41 36 33 31 29 26 24 28 29 31 33 34 34 33 33 35 37 39 41 41 36 28 22 20 23 31 42 52 54 47 39 30 23 17 18 25 32 35 35 36 37 38 40 44 50 57 61 55 51 45 37 30 24 20 18 19 22 27 31 34 34 33 32 28 26 23 22 23 26 30 33 37 38 38 37 34 29 24 21 18 17 16 16 16 18 20 21 25 27 29 29 27 27 27 28 31 32 36 44 56 68 76 81 81 75 65 53 41 31 24 20 25 28 30 30 26 22 20 19 15 15 16 17 18 18 19 19 19 20 22 24 25 25 24 23 18 16 14 12 13 17 20 23 25 24 23 22 20 18 15 14 15 14 13 11 10 9 9 9 9 9 9 9 9 9 9 9 8 8 8 7 7 6 6 6 5 6 7 8 8 8 8 7 10 9 9 8 7 6 5 5 7 7 7 7 7 7 7 7 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 5 5 6 7 8 8 10 10 11 12 14 15 16 16 16 16 16 17 18 18 19 19 19 19 19 20 19 18 18 17 18 17 16 15 15 15 15 15 17 17 19 20 22 23 24 25 25 26 26 26 25 23 21 19 20 19 18 17 17 17 17 17 21 21 21 21 21 21 21 21 20 21 24 27 30 34 36 38 37 33 27 23 21 18 16 13 16 17 18 19 19 18 16 15 15 16 18 20 23 27 33 37 38 36 33 29 27 26 27 28 32 34 35 33 29 25 24 23 22 26 29 31 34 40 49 56 67 78 90 96 100 103 101 97 94 89 81 74 67 61 55 51 43 40 36 33 32 30 28 26 27 28 30 32 33 34 35 35 39 41 44 47 46 39 30 22 21 24 32 44 55 58 52 46 33 26 18 18 24 31 35 35 32 33 35 40 46 55 62 67 61 57 49 40 31 25 21 19 21 25 30 35 38 37 35 33 26 24 21 20 21 25 30 34 37 37 37 35 32 27 23 20 16 16 15 15 16 18 20 21 25 27 30 31 31 32 33 35 37 39 43 53 66 78 87 91 88 80 66 51 38 28 22 19 23 26 28 27 24 20 18 17 15 16 16 17 18 19 19 19 21 22 24 26 26 26 25 25 21 19 17 15 16 18 22 24 25 24 24 22 20 18 16 14 15 15 14 13 12 10 10 9 8 8 8 8 8 8 8 8 8 8 7 7 7 7 6 6 6 7 8 8 9 9 8 8 10 9 9 8 7 7 6 6 7 7 7 7 7 7 7 7 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 6 6 6 6 7 8 9 10 10 11 12 14 15 16 16 16 17 17 18 18 19 19 19 18 18 19 19 19 18 18 17 20 19 18 16 16 16 16 16 18 19 20 21 22 24 24 25 25 26 26 26 25 23 22 20 21 21 20 19 19 19 19 19 22 22 23 23 23 23 22 22 20 21 25 29 33 36 38 40 40 35 29 24 20 18 15 13 15 16 18 20 20 20 18 17 16 17 17 17 19 24 31 36 38 37 33 29 26 25 26 28 33 34 35 34 30 26 24 23 25 28 31 33 35 41 50 57 65 77 91 100 106 110 109 105 103 98 89 80 72 63 55 50 42 40 37 35 34 33 30 28 27 28 30 32 34 35 36 37 41 44 49 52 51 43 32 23 21 24 32 45 57 61 57 51 35 27 18 17 23 30 33 33 29 30 33 39 49 60 68 72 66 61 51 40 31 24 21 19 23 27 33 39 41 39 36 34 25 23 20 18 20 24 30 33 35 35 35 33 29 25 21 19 15 15 15 15 17 19 21 23 25 28 32 35 36 38 40 42 41 43 49 59 72 85 94 98 95 85 68 50 35 26 21 20 22 24 25 24 21 18 16 16 16 16 17 17 18 19 20 20 22 23 25 27 28 28 27 26 22 21 18 17 17 19 22 23 25 25 24 23 21 18 16 15 16 16 15 14 13 12 11 10 8 8 8 8 8 8 8 8 7 7 7 7 7 7 7 7 7 7 8 9 10 10 9 9 10 10 9 9 8 8 7 7 7 7 7 7 7 7 7 7 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 6 6 7 7 8 9 10 10 11 12 14 15 16 16 17 18 18 18 18 19 19 19 17 17 18 19 19 18 18 17 19 19 18 17 16 16 17 17 20 20 21 22 23 24 25 25 25 25 25 25 24 23 22 22 23 22 21 20 20 20 20 21 22 23 24 25 25 24 23 22 21 23 26 31 35 38 40 40 42 37 29 23 19 17 14 12 14 15 17 19 20 20 20 20 18 18 17 16 17 22 29 34 37 37 34 30 25 23 25 27 32 34 36 35 31 27 24 23 25 28 31 33 34 39 48 54 63 76 91 102 109 115 116 112 108 103 94 84 74 64 54 48 42 40 38 37 37 36 33 31 29 30 31 32 34 36 38 39 43 47 52 56 54 46 34 25 21 24 31 44 57 61 58 52 34 26 19 17 23 29 32 32 28 28 31 39 52 64 72 76 69 62 51 39 29 23 20 18 24 28 34 40 41 40 36 34 25 23 20 18 20 24 28 32 33 33 32 30 27 23 20 18 15 15 15 16 18 20 23 25 27 30 35 39 41 44 47 50 47 49 55 65 78 90 98 102 99 88 69 49 34 24 21 20 21 22 23 22 19 16 15 15 16 16 17 18 19 19 20 20 23 24 26 28 29 28 28 27 23 21 20 18 18 19 21 22 26 25 25 23 21 19 16 15 17 17 17 16 15 13 12 10 8 8 8 8 8 8 8 8 7 7 7 7 7 7 7 7 8 8 9 10 10 10 10 10 10 10 10 10 9 9 9 9 7 7 7 7 7 7 7 7 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 7 7 7 7 7 8 9 9 10 10 11 12 14 15 16 16 18 18 18 19 19 19 19 19 16 16 17 18 18 18 18 17 18 17 17 16 16 17 18 18 21 21 22 23 24 24 25 25 25 25 25 24 24 23 23 23 23 22 22 21 20 20 21 21 24 25 26 27 27 26 25 24 24 26 30 34 38 40 41 42 42 36 28 22 18 16 13 12 13 14 15 16 18 20 21 22 21 20 19 17 17 20 26 30 35 36 36 32 26 22 23 25 30 33 36 36 32 28 26 24 24 28 31 33 34 37 43 48 61 74 89 100 110 117 119 117 110 104 96 86 75 64 54 47 42 41 40 40 41 40 37 35 32 32 33 34 35 37 39 40 44 47 52 56 55 47 36 28 21 23 30 42 54 58 55 49 33 26 20 20 26 31 33 31 28 28 30 40 53 66 75 78 71 64 51 38 28 22 19 19 25 28 34 38 40 39 36 34 25 24 22 20 21 24 27 29 30 29 28 27 25 22 20 19 16 15 16 17 19 22 25 27 29 33 38 43 46 49 53 56 55 57 63 73 85 95 102 105 98 86 67 47 31 23 20 20 20 22 22 21 17 15 14 14 17 17 17 18 19 20 20 21 23 24 26 28 29 29 28 27 24 23 21 20 19 20 20 21 26 26 25 23 21 19 17 16 17 18 18 18 17 15 12 11 9 9 9 9 9 9 9 9 6 6 7 7 7 7 8 8 8 9 10 11 11 11 11 10 10 10 10 10 10 10 10 10 7 7 7 7 7 7 7 7 6 6 6 6 6 6 6 6 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 8 8 8 8 8 8 8 8 9 9 9 9 9 9 9 9 8 7 7 7 7 8 9 10 10 10 11 12 14 15 16 16 19 19 19 19 19 19 19 19 15 16 17 18 18 18 18 18 15 15 15 15 16 17 18 19 22 22 23 23 24 25 25 26 25 25 24 24 23 23 23 24 23 22 21 21 20 20 21 21 26 27 29 30 30 29 27 26 29 31 35 39 42 44 44 44 41 35 27 21 17 15 13 12 13 12 12 13 16 19 22 24 23 23 21 19 18 19 23 27 32 36 37 34 27 22 22 23 28 32 35 36 33 30 27 26 27 31 36 38 37 38 42 46 56 69 84 95 105 114 118 116 110 105 96 87 76 65 55 48 43 42 42 43 44 43 40 38 36 36 35 35 36 38 40 41 43 46 51 54 54 47 37 30 21 22 28 39 50 54 50 45 33 27 23 24 30 35 35 33 30 29 31 40 55 68 75 78 73 65 52 38 28 22 21 21 25 28 32 35 37 36 35 33 26 25 24 23 23 24 25 26 26 26 25 25 23 22 21 20 16 16 17 18 21 24 28 29 32 36 41 46 49 53 57 60 60 62 68 77 88 97 103 105 93 82 63 43 28 20 18 18 21 22 22 20 17 14 14 15 17 17 18 18 19 20 21 21 23 24 26 28 28 28 27 27 27 26 24 23 22 21 22 22 26 26 25 24 22 19 17 16 18 18 19 19 18 16 13 11 10 10 10 10 10 10 10 10 6 6 6 7 7 8 8 8 9 10 10 11 12 12 11 11 11 11 11 11 11 11 11 11 7 7 7 7 7 7 7 7 6 6 6 6 6 6 6 6 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 8 8 8 8 8 8 8 8 9 9 9 9 9 9 9 9 8 7 7 7 7 8 9 10 10 10 11 12 14 15 16 16 19 19 19 19 19 19 19 19 15 15 16 18 18 18 18 18 14 14 14 14 16 17 19 20 22 23 23 24 24 25 26 26 25 25 24 23 23 23 24 24 23 22 21 20 20 20 20 21 28 29 31 33 33 31 29 28 32 35 39 43 45 46 46 46 40 34 26 20 16 14 13 12 13 12 11 11 14 18 23 26 24 24 23 21 19 19 22 24 31 35 38 35 28 22 21 22 27 31 35 36 34 31 28 27 32 36 42 43 43 42 45 48 51 63 78 88 99 109 113 113 110 105 97 88 77 66 56 49 44 43 43 44 46 45 42 40 38 38 37 36 37 38 40 41 43 45 50 53 53 47 38 31 20 22 27 37 47 51 47 41 33 28 25 27 34 38 37 35 31 29 31 40 55 68 76 78 74 66 53 39 29 23 22 23 26 28 31 33 35 35 34 33 26 26 26 25 25 25 24 24 25 24 24 23 22 22 21 21 17 17 18 19 22 26 29 31 34 37 43 47 51 55 59 62 62 64 69 77 87 96 101 102 89 78 59 40 26 18 16 16 21 22 22 20 16 14 14 15 17 17 18 19 19 20 21 21 22 23 25 27 28 28 27 26 29 28 26 25 24 23 23 23 26 26 25 24 22 19 17 16 18 19 20 20 19 16 13 12 11 11 11 11 11 11 11 11 6 6 6 7 7 8 8 8 9 10 11 12 12 12 12 11 11 11 11 11 11 11 11 11 7 7 7 7 7 7 7 7 6 6 6 6 6 6 6 6 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 4 4 4 5 5 6 6 6 5 5 5 6 6 7 7 7 7 7 7 8 8 9 9 9 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 12 12 13 14 15 16 16 17 19 19 18 18 18 18 17 17 16 16 15 15 15 15 14 14 16 16 16 17 18 20 21 22 24 25 26 27 28 29 28 28 26 25 24 23 23 23 23 24 24 23 22 19 17 18 21 25 27 32 35 35 35 37 35 30 35 37 41 46 50 50 47 44 38 33 25 17 13 12 13 15 14 15 15 14 13 15 19 22 28 28 27 25 21 19 19 20 30 35 38 36 28 22 21 21 23 27 32 34 32 29 27 26 32 39 48 53 52 48 44 43 49 55 66 80 93 103 107 107 108 104 96 86 74 64 56 52 47 47 46 46 45 44 44 44 40 40 40 40 40 39 38 37 40 42 46 50 51 47 39 33 20 20 23 31 40 46 47 45 33 31 31 36 43 46 44 40 34 31 30 37 50 66 77 83 78 69 57 45 36 30 25 23 25 26 29 31 32 33 33 32 31 30 28 26 26 26 27 28 22 22 23 23 23 23 23 23 20 20 21 23 25 28 30 32 34 36 40 45 50 54 57 58 62 63 67 74 82 89 93 94 82 69 50 33 22 18 17 18 20 19 17 15 15 15 16 17 18 19 21 20 19 19 21 23 21 23 26 26 25 25 26 27 28 28 29 29 28 27 26 25 27 27 27 24 21 19 18 19 18 18 19 19 18 16 14 13 11 11 11 12 12 13 13 13 9 9 9 9 9 8 8 8 10 11 12 13 14 13 12 11 9 9 9 10 10 11 11 11 9 8 7 6 6 6 6 7 7 7 6 6 6 5 5 5 6 6 6 5 5 4 4 4 5 5 5 5 5 5 5 5 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 4 4 4 5 5 6 6 6 5 5 6 6 6 7 7 7 7 7 8 8 8 9 9 9 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 11 12 12 13 14 15 15 16 18 18 18 18 18 18 18 18 16 16 15 15 15 14 14 14 15 15 15 16 17 19 20 21 24 25 26 27 28 29 28 28 26 25 24 24 23 23 24 24 23 22 21 18 17 18 21 24 30 35 39 39 40 42 39 35 37 39 42 46 50 50 48 46 40 35 27 20 15 14 15 17 17 17 16 15 14 16 20 23 30 31 31 28 25 23 22 23 30 34 38 36 29 23 22 23 25 28 32 34 33 31 30 30 38 46 55 61 60 56 52 50 48 51 59 70 82 91 96 98 102 98 91 81 71 61 54 50 47 46 45 44 43 42 42 41 40 40 40 40 40 39 38 37 37 41 46 51 53 49 41 35 24 23 24 30 38 43 45 44 38 36 37 42 49 51 49 45 35 32 31 37 51 66 77 82 79 71 60 48 40 33 28 25 27 28 29 31 32 33 33 33 33 33 31 30 29 29 28 28 23 23 23 24 24 25 25 26 22 22 23 24 26 28 29 30 33 35 38 43 47 50 53 54 56 58 62 70 78 83 86 86 74 62 45 29 20 16 16 17 20 19 17 16 16 16 17 18 19 20 21 20 19 18 20 21 23 25 27 27 26 26 27 28 30 31 32 32 32 31 29 28 28 28 27 25 22 20 20 20 19 19 19 19 18 16 14 13 11 11 11 12 12 12 13 13 11 10 10 10 9 9 9 9 10 11 12 13 13 13 12 11 9 9 9 10 10 11 11 11 9 8 7 7 6 6 7 7 7 7 7 6 6 6 5 5 6 6 6 5 5 5 4 4 5 5 5 5 5 5 5 5 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 4 4 4 5 5 6 6 6 5 6 6 6 7 7 7 7 7 8 8 8 9 9 9 9 10 10 10 10 10 11 11 11 11 11 11 11 11 11 11 11 11 11 11 12 13 14 14 14 18 18 18 18 18 18 18 18 16 16 15 15 14 14 14 13 14 14 14 15 16 18 20 20 24 25 26 27 28 29 28 28 26 26 25 24 23 23 24 24 21 21 20 18 17 18 21 24 33 39 43 44 46 48 46 41 40 40 42 46 49 51 49 48 42 38 30 23 19 18 19 20 21 20 18 15 14 15 20 24 32 33 35 34 31 28 27 27 31 35 37 35 30 25 24 24 26 29 33 34 34 33 33 34 42 50 61 69 70 66 61 57 49 50 52 58 67 76 82 85 90 87 80 73 64 56 50 47 45 44 43 41 40 39 38 38 39 39 40 40 39 38 37 37 34 39 46 54 57 54 47 41 31 28 25 28 34 40 42 42 43 43 45 50 55 57 54 50 38 34 33 38 51 65 76 81 81 74 64 54 46 39 33 30 28 28 29 30 31 32 34 35 37 37 38 37 35 33 31 29 23 23 24 25 26 27 28 28 25 25 25 26 26 27 28 28 31 33 36 39 42 45 46 47 49 51 56 63 70 74 74 72 62 52 37 24 17 15 16 16 21 20 18 17 17 18 19 19 22 22 22 20 18 17 18 20 24 26 28 28 27 26 27 28 31 33 36 38 38 37 34 33 30 29 27 25 24 23 22 22 20 20 20 19 18 16 14 13 10 10 11 11 12 12 12 12 12 12 12 11 11 10 10 10 9 10 11 12 13 13 12 12 10 10 10 10 11 11 11 11 9 9 8 7 6 6 7 7 8 8 7 7 7 6 6 6 6 6 6 6 5 5 5 4 5 5 5 5 5 5 5 5 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 4 4 4 5 5 6 6 6 6 6 6 7 7 7 8 8 8 8 8 9 9 9 10 10 10 10 10 11 11 11 11 12 12 12 12 12 12 12 12 12 11 11 11 12 12 13 13 13 16 17 17 18 18 19 19 20 17 17 16 16 15 14 14 13 14 14 14 14 16 17 19 20 24 25 26 27 28 29 28 28 27 26 25 24 24 24 24 25 20 21 20 18 17 18 20 23 33 40 45 47 50 52 50 45 42 42 42 44 48 50 50 49 43 39 32 26 22 20 21 22 24 23 19 15 13 14 19 22 31 34 38 39 37 34 32 31 33 36 37 35 31 27 26 26 27 29 32 33 33 33 35 36 42 50 62 72 75 72 66 62 55 52 49 50 55 62 68 71 74 72 67 61 55 50 45 43 43 41 39 37 36 36 36 36 38 38 39 38 38 37 35 35 34 39 48 58 63 61 55 49 37 32 26 26 31 38 41 43 46 47 51 56 61 61 58 54 41 37 35 39 51 64 74 79 81 76 67 59 52 45 38 33 28 28 27 27 29 32 35 37 43 44 44 44 41 37 33 31 24 25 25 26 27 28 29 29 28 28 28 28 28 27 27 26 29 30 33 35 37 39 40 40 42 45 50 57 62 64 61 59 50 42 31 21 17 16 17 18 22 21 20 19 18 19 21 22 24 24 23 20 17 16 17 18 24 26 28 28 27 26 27 28 33 36 40 44 44 42 39 36 31 29 27 25 25 26 25 25 23 22 21 20 18 16 15 14 10 11 11 11 12 12 12 12 14 13 13 12 12 11 10 10 9 10 10 11 12 12 13 13 10 11 11 11 11 11 11 11 10 9 8 7 7 7 7 8 9 8 8 8 7 7 7 7 7 7 6 6 6 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 4 4 4 5 5 6 6 6 6 6 7 7 7 8 8 8 8 8 9 9 9 10 10 10 10 10 10 11 11 12 12 13 14 14 14 14 14 14 14 14 11 11 11 12 12 12 12 13 15 16 17 17 19 19 20 21 19 18 18 17 16 15 14 14 14 14 14 14 16 17 19 20 24 25 26 27 28 29 28 28 27 26 25 25 24 24 25 25 21 22 22 20 18 18 19 21 30 38 44 48 51 54 52 47 44 42 40 41 44 48 49 49 44 40 34 28 24 22 23 23 26 24 21 17 14 14 17 20 29 34 40 43 42 40 37 36 37 37 37 36 32 29 27 26 26 29 31 33 32 33 34 36 40 48 60 72 78 77 72 68 60 54 48 44 45 49 53 55 57 56 53 49 46 42 40 38 39 37 35 34 33 34 36 37 39 39 38 38 36 35 33 32 35 41 50 61 68 68 63 59 43 36 28 26 30 36 41 43 49 52 58 63 66 65 61 58 43 39 36 39 50 62 71 75 80 76 69 63 56 48 41 35 27 26 25 25 28 34 39 43 50 51 52 51 48 43 37 34 29 29 29 29 29 29 29 29 30 30 30 30 29 28 26 25 27 28 30 32 34 35 35 35 39 41 46 52 55 55 51 47 41 34 26 20 18 19 20 21 23 22 21 20 20 21 23 24 26 26 24 20 16 15 16 18 23 25 27 28 27 27 28 29 35 39 45 49 50 46 41 38 33 29 26 25 26 28 27 26 25 24 23 20 18 16 15 14 11 11 12 12 12 13 13 13 15 14 14 13 12 11 10 10 9 9 9 10 11 12 13 13 12 11 11 11 11 11 11 11 10 9 8 8 7 7 8 8 9 9 9 9 8 8 8 7 7 7 7 6 6 6 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 4 4 4 5 5 6 6 6 7 7 7 7 8 8 8 9 9 9 9 9 10 10 10 11 10 10 11 11 12 13 13 13 15 15 15 15 15 15 15 15 12 12 12 12 13 13 13 13 14 15 16 17 19 20 21 22 21 21 20 19 18 17 16 15 14 14 14 15 16 18 20 20 24 25 26 27 28 29 28 28 27 27 26 25 25 25 25 25 24 24 24 22 19 18 19 20 27 35 42 47 51 54 53 48 44 41 37 37 40 44 47 48 45 41 36 31 27 25 25 26 28 27 25 20 16 15 16 18 27 33 42 48 49 46 44 42 40 40 38 36 33 30 27 26 26 29 33 34 33 33 33 34 39 46 58 72 81 83 79 75 63 57 48 42 39 39 40 40 41 41 40 38 37 36 35 34 34 33 31 31 32 35 38 40 43 42 41 39 37 34 32 31 37 42 51 62 69 72 69 66 50 42 32 28 30 35 39 41 50 55 62 67 69 67 62 59 45 40 36 39 48 59 68 72 76 73 69 64 58 50 41 35 26 25 23 25 30 38 47 52 61 61 61 59 55 49 43 40 37 36 35 33 32 30 29 29 31 32 32 32 31 29 26 25 26 27 29 31 32 32 33 33 37 39 42 46 48 47 42 38 33 29 23 20 20 22 23 23 24 23 22 22 22 23 25 26 27 26 23 19 16 14 16 18 22 25 27 29 29 29 31 33 38 43 50 55 55 51 44 39 33 29 24 24 27 29 29 27 28 26 24 21 18 16 15 14 13 13 13 14 14 14 15 15 15 15 14 13 11 10 10 9 8 8 8 9 10 12 13 14 12 12 12 12 11 11 11 11 10 10 9 8 8 8 8 8 10 10 10 9 9 9 8 8 8 7 7 7 6 6 6 6 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 4 4 4 5 5 6 6 6 7 7 7 8 8 8 9 9 9 9 9 10 10 10 11 11 10 10 11 11 12 13 14 14 16 16 16 16 16 16 16 16 14 14 14 14 13 13 13 13 13 14 15 17 19 21 22 23 23 23 22 21 19 18 17 17 15 15 15 16 17 19 20 21 24 25 26 27 28 29 28 28 28 27 26 25 25 25 25 26 27 27 27 24 20 18 18 19 24 32 41 46 51 55 53 48 42 39 34 33 36 40 44 46 47 44 39 34 30 29 28 28 31 31 30 26 21 18 17 17 26 34 45 52 55 53 50 49 44 42 39 36 33 30 27 25 28 31 35 37 36 34 33 33 35 42 54 68 80 85 83 80 69 63 53 45 40 36 33 31 29 29 30 30 30 31 31 31 29 28 28 29 32 36 41 43 48 47 46 43 40 36 33 31 37 42 50 60 68 72 72 70 59 50 38 31 31 33 35 36 46 52 60 65 66 63 58 55 46 41 36 38 47 57 65 68 72 70 68 64 58 50 40 34 26 25 24 26 33 44 56 63 71 71 69 66 61 56 50 47 46 45 42 39 36 33 31 29 32 32 33 33 32 30 27 25 26 27 28 30 31 32 32 32 36 37 39 41 42 40 35 31 27 24 21 20 21 23 24 24 25 24 23 23 23 25 26 27 27 26 23 19 15 15 17 19 23 26 29 31 32 33 36 37 42 48 56 61 61 55 47 41 33 28 22 22 26 30 29 28 30 28 25 21 18 16 15 14 14 14 15 15 15 16 16 16 15 14 13 12 11 10 9 8 8 8 8 8 9 11 13 15 13 13 13 12 12 11 11 11 11 10 9 8 8 8 8 9 11 11 10 10 10 9 9 9 8 8 7 7 7 6 6 6 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 4 4 4 5 5 6 6 6 7 7 7 8 8 9 9 9 9 9 9 10 10 11 11 11 10 10 11 12 13 13 14 15 16 16 16 16 16 16 16 16 15 14 14 14 14 14 14 14 13 14 15 17 19 21 22 23 25 24 23 22 21 19 18 18 16 16 16 17 18 20 21 22 24 25 26 27 28 29 28 28 28 27 26 25 25 25 25 26 29 29 28 25 21 18 17 18 23 32 41 46 51 55 54 49 42 37 32 31 33 38 43 45 49 46 41 37 33 31 31 31 33 34 33 30 25 20 18 18 26 35 47 56 59 58 55 53 46 44 40 37 34 30 27 24 29 33 38 40 39 36 34 33 32 38 49 64 78 84 84 81 74 68 59 51 43 37 32 28 23 23 24 25 27 28 29 29 26 26 26 28 32 37 43 46 53 52 49 46 42 38 34 32 37 41 48 58 67 71 72 71 65 55 42 34 31 32 32 32 40 46 55 60 61 57 52 49 46 41 36 37 46 56 63 66 70 68 66 63 58 49 39 32 27 26 25 28 37 49 62 70 79 77 75 71 66 60 55 52 53 51 48 44 39 35 32 31 31 32 34 34 33 31 28 26 26 27 28 30 31 32 33 33 35 35 36 37 38 36 31 27 24 22 19 19 21 23 24 23 25 25 24 23 24 25 27 28 26 25 23 18 15 15 17 20 24 27 31 33 35 37 39 41 46 52 60 65 65 58 49 42 33 27 21 21 26 30 30 28 31 29 25 21 18 16 15 15 15 15 16 16 16 17 17 17 14 14 13 12 10 9 8 7 8 8 7 8 9 11 14 15 13 13 13 12 12 11 11 11 11 10 9 8 8 8 8 9 11 11 11 10 10 10 9 9 8 8 8 7 7 6 6 6 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 6 6 7 7 7 8 8 8 9 9 10 10 10 9 10 10 11 11 10 9 9 11 11 12 12 14 16 17 18 20 20 20 21 21 20 19 18 18 18 18 17 16 15 13 12 15 16 17 19 21 23 24 25 24 25 26 26 26 25 23 22 20 20 18 18 18 19 21 22 25 26 27 28 28 28 27 27 28 28 27 25 23 23 26 28 31 31 30 29 26 22 19 17 22 25 33 44 53 55 50 45 42 34 28 28 31 34 40 46 39 51 46 33 35 36 34 35 38 38 37 35 31 26 21 18 26 35 47 59 65 65 62 58 52 49 44 39 33 30 27 26 30 35 41 45 45 41 34 30 29 34 45 59 73 84 89 90 83 77 69 60 50 41 32 27 26 27 29 30 30 29 27 26 23 25 27 28 30 37 46 54 58 57 55 50 43 38 36 36 36 41 48 54 60 66 71 75 72 65 54 42 34 30 29 30 35 39 45 50 52 51 47 45 40 39 38 39 43 48 54 58 63 65 66 62 54 45 38 34 23 24 26 30 39 53 68 78 85 84 81 76 69 65 63 63 59 58 55 48 40 34 30 29 33 36 39 40 36 32 29 27 26 28 31 32 32 32 33 35 34 36 37 35 30 26 23 22 19 20 21 22 24 25 26 27 22 22 22 22 23 24 25 26 25 23 19 15 11 11 14 17 24 28 33 36 38 41 46 50 59 62 66 69 67 59 47 39 31 25 18 19 24 30 32 31 29 27 24 21 18 17 16 16 16 17 19 19 19 18 17 16 15 14 14 13 11 10 10 9 8 8 8 9 10 11 13 14 17 17 16 16 14 12 11 10 10 10 11 12 12 11 11 10 13 13 12 12 12 12 11 11 10 9 8 7 7 7 7 8 5 5 5 5 5 5 5 5 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 6 6 7 7 7 8 8 8 9 9 10 10 10 10 10 11 11 11 11 10 9 12 12 12 13 14 16 17 18 19 20 21 21 21 21 21 20 20 20 20 19 18 17 15 14 15 16 17 18 20 22 24 24 26 27 28 29 29 28 27 26 25 24 23 22 21 22 23 23 26 26 27 28 29 29 29 29 29 29 28 25 24 24 27 30 35 35 34 33 30 26 22 19 20 24 32 43 52 55 51 46 40 32 25 24 27 29 35 42 48 48 40 38 43 37 32 39 42 42 41 38 34 29 25 22 27 35 46 57 63 64 62 60 54 51 47 41 36 31 29 28 32 36 42 46 47 43 37 33 31 35 45 58 72 83 89 91 87 82 74 64 54 45 38 33 31 33 35 35 35 33 30 28 24 25 26 28 31 39 49 57 62 62 59 53 45 38 35 34 35 40 46 53 59 66 73 77 75 68 58 47 38 32 30 29 33 37 42 46 48 46 42 40 34 34 33 34 38 43 48 51 57 60 61 59 52 44 38 34 27 28 30 34 42 55 69 78 84 84 81 75 69 64 62 62 61 60 56 49 40 34 30 29 33 36 39 39 36 32 28 27 26 28 30 31 31 31 33 35 34 36 36 34 29 24 21 20 18 19 20 22 23 25 26 26 23 23 22 22 23 24 25 26 24 22 20 15 13 13 16 20 26 30 36 40 43 47 53 57 67 69 72 73 70 61 49 40 29 23 18 18 24 29 31 31 30 28 25 22 19 18 18 18 18 19 20 21 20 19 17 16 14 14 13 12 11 11 10 10 9 9 9 9 10 11 13 13 16 16 16 15 14 12 11 10 10 10 11 12 12 12 11 11 13 13 13 12 12 12 11 11 10 9 8 7 7 7 7 8 5 5 5 5 5 5 5 5 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 6 6 7 7 7 8 8 8 9 9 10 10 10 10 11 11 12 12 12 11 11 12 12 12 13 14 16 17 18 19 20 21 22 23 24 23 23 23 23 23 22 21 19 18 17 16 16 17 17 19 21 22 23 28 29 31 33 34 34 33 33 32 31 29 27 26 25 25 25 26 26 27 28 29 30 31 31 28 28 28 26 25 26 29 32 39 39 39 38 34 29 24 21 18 22 30 42 52 56 53 49 40 31 23 22 24 26 32 38 50 41 33 39 48 39 33 44 48 47 45 43 39 34 29 27 29 35 44 53 60 63 63 62 57 54 50 44 39 35 32 30 35 39 44 49 50 46 41 37 34 37 45 57 71 83 90 94 93 89 81 72 61 52 46 42 40 42 45 46 44 40 34 31 26 26 26 28 33 42 54 61 68 67 63 56 47 38 33 31 33 38 44 51 58 66 74 79 79 73 64 53 43 36 31 29 32 34 38 41 41 39 35 33 29 29 29 31 34 38 43 45 49 52 55 55 50 44 38 36 32 33 36 39 46 56 68 76 82 82 79 74 68 62 60 60 62 60 56 48 39 32 29 28 33 36 39 39 35 31 28 27 26 28 30 30 30 30 32 34 35 36 36 32 27 21 18 17 16 17 19 21 23 24 24 25 23 23 22 22 22 23 24 24 22 21 19 16 15 16 19 23 30 34 39 45 50 57 63 68 75 76 77 76 71 60 47 38 26 22 18 19 24 28 30 30 29 28 25 22 21 20 20 20 22 22 23 23 21 19 17 16 14 14 13 12 12 11 11 11 10 10 10 10 10 11 13 13 15 15 15 15 13 12 10 9 10 10 11 12 13 13 13 12 14 13 13 13 12 12 11 11 10 9 8 7 7 7 7 8 6 6 6 5 5 5 5 5 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 6 6 7 7 7 8 8 8 9 9 10 10 10 11 11 12 13 13 13 13 12 13 13 13 13 14 16 17 18 19 20 22 24 26 27 27 27 27 26 26 25 24 22 20 19 17 17 17 17 18 20 21 23 29 30 33 36 38 39 39 38 38 37 35 33 30 29 27 26 26 26 26 27 28 30 31 32 27 28 27 26 25 27 31 34 41 42 43 42 37 31 24 20 18 22 30 42 53 58 56 53 43 33 24 22 23 26 31 38 40 40 35 36 44 41 38 47 50 49 47 45 41 36 33 31 32 35 42 49 55 59 61 62 58 56 52 48 43 38 35 34 38 41 47 51 52 49 45 41 38 40 46 57 71 84 92 96 100 96 89 79 68 60 54 52 51 54 57 59 56 49 41 36 29 28 27 29 36 46 57 64 71 70 65 57 46 37 31 29 32 36 43 50 57 65 74 79 82 77 69 59 49 39 32 29 31 33 35 36 35 33 30 28 27 27 28 30 33 37 40 42 43 46 50 51 48 43 40 38 36 38 40 42 47 54 63 70 76 76 75 70 64 59 57 56 59 57 52 45 36 29 27 26 33 36 38 38 34 31 28 27 27 28 29 29 29 29 32 34 36 36 35 31 24 19 16 15 15 17 19 21 22 23 22 22 22 21 21 20 20 21 21 22 20 20 19 18 17 19 23 26 34 37 43 51 59 68 75 79 83 82 79 75 67 55 42 33 23 21 19 20 23 27 29 29 27 26 24 22 20 20 21 21 25 25 25 24 22 20 17 16 14 14 13 13 13 13 13 12 12 11 11 11 11 12 12 13 14 14 14 14 13 11 10 9 9 10 11 13 14 14 14 14 15 14 14 13 12 12 11 11 10 9 8 7 7 7 7 8 7 6 6 6 6 5 5 5 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 6 6 7 7 7 8 8 8 9 9 10 10 10 11 12 13 14 15 15 14 14 14 14 14 14 15 16 17 18 19 20 23 26 28 30 31 32 30 30 29 28 26 24 22 21 20 19 17 17 17 19 21 23 28 30 33 37 40 42 43 43 43 42 40 38 35 32 29 28 26 26 26 26 27 28 30 31 27 27 27 27 27 29 33 37 43 45 46 45 40 32 24 19 19 22 30 43 54 60 59 56 43 33 24 21 22 25 31 37 34 52 49 35 36 42 42 44 49 48 46 43 40 37 34 33 34 37 40 45 50 54 57 58 56 54 52 49 46 42 40 38 40 44 49 52 53 50 46 43 41 43 49 59 73 86 95 99 104 101 95 84 73 64 61 60 61 65 70 72 68 58 48 41 32 30 29 31 38 48 57 63 69 67 62 53 43 35 30 29 33 37 44 51 58 65 73 78 81 78 71 62 52 42 34 30 32 33 33 33 32 30 27 25 25 26 28 30 33 36 38 39 40 43 46 46 45 42 41 41 39 40 42 43 45 49 54 58 65 66 66 64 59 55 53 52 53 51 46 39 31 26 24 24 34 36 37 37 33 30 28 28 28 29 30 29 28 29 32 34 36 36 34 29 23 17 15 14 16 17 19 21 22 21 20 19 19 18 18 18 18 19 20 20 20 21 21 21 21 23 26 30 37 41 49 59 70 80 86 89 91 87 81 73 62 50 38 30 23 21 21 22 24 26 27 27 24 23 21 20 19 20 21 22 26 26 26 25 23 20 18 16 14 14 14 15 15 15 15 15 14 13 12 12 11 12 12 13 13 13 13 13 12 11 10 9 9 10 12 13 15 16 16 16 16 15 15 14 13 12 11 11 10 9 8 7 7 7 7 8 8 7 7 6 6 5 5 5 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 5 5 5 6 6 7 7 7 8 8 8 9 9 10 10 10 12 13 14 15 16 16 16 16 15 15 15 15 15 16 17 18 19 20 23 27 30 33 35 36 34 34 33 32 30 28 26 24 22 21 19 18 18 19 22 23 27 30 34 39 43 45 47 48 48 47 46 43 40 36 33 31 29 28 27 27 27 28 30 31 28 29 30 30 30 33 38 42 47 49 51 49 44 35 25 19 19 22 30 42 53 59 59 57 42 32 22 19 20 23 30 37 39 64 61 38 33 41 41 38 46 45 43 41 39 37 35 35 37 38 40 42 45 48 50 51 50 50 50 49 47 46 44 43 43 45 49 52 52 49 45 42 44 47 52 63 76 88 97 101 105 103 97 86 74 66 64 65 68 73 80 83 78 67 54 46 34 32 31 34 41 49 55 59 62 59 53 45 37 31 30 31 37 42 49 56 62 67 73 76 78 75 69 61 52 43 36 32 33 33 32 31 29 27 26 25 24 25 28 31 33 35 36 37 39 41 42 41 39 39 41 42 41 42 43 42 41 42 43 45 52 54 56 55 52 50 49 49 45 44 39 33 27 24 23 25 34 36 37 36 32 29 28 28 30 31 31 30 29 30 33 35 36 36 33 28 22 17 15 15 18 20 21 23 22 21 18 17 17 17 17 17 18 19 20 21 24 26 27 27 27 29 32 35 42 47 56 69 82 92 97 98 99 93 82 69 57 46 36 30 23 24 24 24 25 25 25 25 22 21 20 19 19 20 22 23 26 26 26 25 23 21 18 16 15 15 16 17 17 18 18 19 16 15 14 13 12 12 12 12 11 12 12 12 11 10 9 9 9 10 12 14 16 17 18 18 16 16 15 14 13 12 11 11 10 9 8 7 7 7 7 8 8 8 8 7 6 6 5 5 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 5 5 5 6 6 7 7 7 8 8 8 9 9 10 10 10 13 13 15 16 17 17 17 17 16 15 15 15 15 16 17 18 18 21 24 28 32 35 38 39 40 39 38 37 35 32 30 29 25 23 20 18 18 20 22 24 27 30 35 41 45 49 51 52 52 52 50 48 45 41 38 36 34 33 31 29 29 30 31 32 31 33 34 34 35 38 44 47 53 55 58 56 50 40 30 23 18 21 28 40 51 57 57 55 44 33 23 20 22 25 33 40 44 60 55 38 36 38 36 37 42 42 40 39 38 37 37 37 40 40 40 41 42 42 43 43 44 45 46 48 48 48 47 47 44 46 49 51 51 47 43 40 47 49 56 67 80 91 99 102 104 103 97 86 73 66 65 67 73 79 87 91 86 74 59 50 37 35 33 36 42 48 52 53 52 49 43 36 30 28 31 33 44 49 57 63 68 71 74 76 74 71 66 59 50 43 37 33 32 32 30 29 27 26 25 24 26 28 31 35 37 38 38 38 40 39 38 35 33 34 38 41 43 44 44 42 39 36 35 35 39 42 45 47 46 45 45 46 39 38 35 29 25 23 25 27 34 35 36 35 32 29 28 28 32 33 32 31 30 31 34 37 36 36 33 28 22 18 16 16 21 22 24 24 23 20 17 14 16 16 17 18 19 21 23 24 31 32 34 34 34 35 39 41 47 53 64 79 94 103 106 106 103 93 78 63 50 40 32 27 25 26 27 27 26 25 24 24 22 21 20 20 20 22 24 25 24 25 25 25 23 21 18 17 17 17 18 19 19 20 21 21 17 16 15 13 12 12 12 12 10 11 11 11 11 10 9 9 8 10 12 14 17 18 19 19 17 17 16 15 13 12 11 11 10 9 8 7 7 7 7 8 9 9 8 7 6 6 5 5 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 5 5 5 6 6 7 7 7 8 8 8 9 9 10 10 10 13 14 15 16 17 18 18 18 16 16 15 15 15 16 17 17 18 21 24 29 33 37 39 40 43 43 42 40 38 36 33 32 26 24 21 19 19 20 23 25 28 31 36 42 48 52 54 55 55 55 54 52 49 45 41 39 38 36 33 31 30 31 33 34 34 36 37 37 39 42 48 52 58 61 63 62 56 45 34 27 17 20 26 37 48 55 55 52 46 36 26 23 25 29 37 44 43 47 41 36 39 35 31 38 41 40 39 38 38 38 38 38 41 41 41 40 40 39 38 38 40 41 44 47 48 49 49 49 45 47 49 51 49 46 42 39 48 51 58 69 82 93 100 103 103 102 96 85 72 65 65 67 75 82 90 95 90 77 62 52 38 36 35 38 43 48 49 49 46 43 36 30 26 27 31 35 49 54 63 69 72 74 75 76 71 68 63 56 49 42 37 35 31 30 29 27 25 24 24 24 30 33 36 40 42 43 43 42 39 38 35 31 29 31 35 39 44 45 45 42 38 33 30 30 31 34 39 42 43 43 43 44 36 35 32 28 25 24 27 29 34 35 36 34 31 29 28 28 34 34 33 31 30 31 34 37 36 35 33 28 22 19 17 18 23 24 25 25 23 20 16 13 17 17 18 19 21 24 26 27 36 37 39 39 39 40 43 46 51 57 70 86 101 110 111 110 102 91 74 57 43 34 27 24 26 28 29 29 27 24 23 23 22 22 21 21 22 24 26 27 23 24 24 24 23 21 19 17 17 18 19 20 21 22 23 23 18 17 15 14 13 12 12 12 10 10 11 11 11 10 9 8 8 10 12 15 17 19 20 20 18 17 16 15 13 12 11 11 10 9 8 7 7 7 7 8 10 9 8 8 7 6 5 5 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 6 6 6 7 7 8 8 8 7 7 7 7 7 7 7 7 5 6 7 7 8 9 10 10 13 14 14 15 17 18 18 19 19 18 18 17 17 18 18 19 18 21 26 30 34 38 43 46 44 45 46 46 44 41 38 36 31 29 25 22 21 22 24 25 26 30 36 41 45 50 54 57 56 56 56 55 53 50 47 45 43 40 36 33 32 32 34 35 37 39 41 43 45 49 54 58 62 67 70 68 64 55 41 28 21 22 26 35 45 52 54 52 45 39 31 26 26 32 41 47 48 48 46 42 37 33 33 33 35 34 34 35 36 39 41 43 43 43 42 41 39 36 34 32 31 33 37 41 46 49 51 52 52 51 50 49 47 46 45 44 46 51 59 67 76 86 95 101 106 100 93 84 71 60 58 62 71 82 94 97 94 83 66 52 41 34 32 39 47 49 48 48 42 33 27 26 26 28 37 49 57 62 70 75 77 76 74 73 66 63 58 52 46 41 37 35 36 33 32 32 29 24 24 28 29 37 43 46 48 50 47 42 45 37 30 29 30 30 33 37 41 45 49 48 42 34 28 26 28 30 34 36 38 40 42 44 38 35 30 26 25 27 30 33 35 37 37 36 32 29 28 29 33 34 35 34 32 31 32 33 36 34 30 26 23 20 19 19 24 25 26 25 22 20 20 21 20 21 22 23 23 26 31 35 39 41 44 45 44 44 45 47 53 66 82 93 103 110 113 110 103 87 67 51 37 27 24 26 26 27 29 30 28 25 22 19 21 22 24 25 25 24 22 20 24 23 22 20 19 18 18 18 19 19 20 20 20 19 18 18 16 16 15 14 13 11 11 10 10 9 9 8 8 9 9 10 10 11 14 17 18 19 19 19 19 18 17 15 14 13 13 13 12 11 9 7 6 6 7 7 8 8 7 6 6 5 4 4 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 6 6 7 7 7 8 8 8 7 7 7 7 7 7 7 7 6 6 7 8 9 9 10 10 13 14 14 15 17 18 18 19 19 19 18 18 18 18 19 19 18 22 26 30 33 37 42 45 46 47 47 47 46 43 39 37 32 30 26 23 22 22 24 25 24 28 34 38 42 47 51 55 59 59 60 60 58 56 53 52 46 43 39 35 33 33 33 34 36 39 41 44 46 51 56 60 69 74 77 75 70 61 47 34 22 22 25 32 42 49 52 51 44 38 31 26 27 34 42 48 50 50 48 44 38 34 33 34 33 33 33 34 36 39 42 44 43 43 43 42 39 36 32 30 27 28 32 36 40 45 48 50 54 53 52 50 48 46 44 44 44 49 57 65 74 84 93 99 102 96 89 81 69 58 56 60 69 82 95 100 96 86 68 54 42 34 31 37 43 45 44 44 35 29 26 30 34 40 51 62 71 73 77 78 76 73 69 67 63 61 57 52 46 42 39 37 37 34 33 33 29 24 25 29 33 41 48 52 55 57 54 48 48 40 32 30 30 29 31 35 41 46 52 53 48 41 36 34 31 33 35 38 40 42 44 45 41 38 32 28 27 28 32 34 37 38 38 35 31 28 28 28 33 34 35 34 32 31 32 33 35 33 30 26 24 22 21 20 24 25 26 24 22 20 21 21 23 25 26 27 28 31 36 39 45 47 49 49 48 48 49 51 57 68 83 94 105 112 112 107 96 80 60 45 33 25 23 25 27 29 30 30 29 26 22 20 22 23 24 25 25 24 22 20 22 21 20 19 18 18 18 18 19 20 20 20 19 18 17 16 14 14 13 13 12 11 11 10 10 9 9 8 8 9 9 10 11 12 15 17 19 20 20 19 19 18 16 14 13 13 12 12 12 10 9 7 6 6 7 7 8 8 7 6 6 5 4 4 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 6 7 7 7 8 8 8 8 8 8 8 8 8 8 8 8 7 7 7 8 9 9 10 10 13 13 14 15 17 18 19 19 20 20 20 20 20 20 20 20 19 22 25 28 31 35 39 43 47 48 49 49 48 45 42 40 34 32 28 25 23 23 24 24 23 26 31 35 39 43 48 51 59 60 62 63 63 61 59 58 51 48 43 39 35 33 33 33 36 38 42 45 48 53 59 63 75 80 83 81 76 67 52 39 25 23 23 28 37 44 48 49 42 37 31 27 29 36 45 51 54 53 51 46 40 35 33 33 31 31 32 34 36 40 43 46 44 45 45 44 41 36 31 28 24 25 28 32 37 43 48 50 56 55 53 50 47 44 42 41 41 46 53 61 70 79 89 95 96 91 85 77 65 54 52 56 65 79 95 102 100 90 72 56 44 36 31 36 42 43 42 43 33 30 31 39 47 57 68 77 82 81 80 77 73 68 65 62 61 59 56 52 48 45 42 41 39 36 34 34 30 26 27 31 37 46 56 62 66 69 65 59 55 45 36 32 30 28 29 33 40 46 55 59 58 54 49 46 37 38 39 40 43 45 47 48 46 42 36 31 29 30 34 36 40 40 38 35 30 28 27 28 33 34 35 34 32 31 32 33 33 32 30 28 25 24 23 23 24 25 25 24 21 21 22 23 27 29 32 33 35 38 42 45 49 51 52 52 50 49 51 52 58 67 79 91 103 109 105 97 83 68 50 37 28 21 21 25 29 30 31 31 29 26 23 21 23 24 25 25 25 23 21 20 18 18 17 16 16 17 17 18 20 20 20 19 18 17 15 14 11 11 11 11 11 11 11 11 10 9 9 8 8 9 9 10 12 13 16 18 20 20 20 20 18 17 15 14 12 12 11 11 11 10 9 7 7 7 7 7 8 8 7 6 6 5 4 4 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 7 7 7 8 8 8 9 9 9 9 9 9 9 9 9 9 7 8 8 9 9 10 10 10 12 13 14 15 17 18 19 20 21 21 21 22 22 21 21 21 21 23 25 27 28 32 36 40 48 49 50 50 49 47 44 42 37 34 31 28 25 24 24 24 23 26 30 33 36 40 44 48 55 57 60 63 64 63 62 60 55 52 48 42 38 35 33 33 36 38 42 45 49 55 61 66 78 83 86 83 78 70 55 42 27 24 21 24 31 39 44 45 40 36 31 29 31 39 48 54 57 56 54 48 41 35 32 31 29 29 30 33 36 41 45 47 47 47 48 47 44 39 34 30 27 27 29 33 38 44 50 54 56 54 52 48 45 41 39 37 38 42 48 55 63 73 83 89 93 88 82 74 62 51 48 52 61 76 94 104 104 94 76 60 46 37 32 36 43 45 46 47 40 40 44 52 63 74 82 88 86 82 76 71 67 65 63 61 61 60 58 55 52 48 46 44 39 36 34 34 31 27 29 34 41 52 65 73 79 82 78 72 63 52 41 36 32 28 29 32 39 46 57 66 69 67 63 60 48 46 45 46 48 51 52 53 52 47 40 34 31 32 35 37 42 41 39 35 30 28 28 29 32 34 35 34 32 31 32 34 33 32 31 30 28 27 27 27 25 26 25 23 21 22 24 26 31 33 37 40 41 43 47 49 49 50 50 49 46 45 46 48 54 62 72 83 94 99 92 82 71 57 42 31 25 20 21 26 30 31 31 31 29 27 24 22 24 24 25 24 23 22 20 19 15 15 14 14 15 16 17 18 19 19 19 18 17 15 13 12 9 9 9 10 10 11 11 11 10 9 9 8 8 9 9 10 13 15 17 19 20 21 20 20 17 16 14 12 11 11 10 10 10 9 9 8 7 7 7 7 7 7 7 6 6 5 5 5 6 6 6 6 6 6 6 6 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 7 7 8 8 8 9 9 9 9 9 9 9 9 9 9 9 8 9 9 9 9 10 10 10 12 12 13 15 17 19 20 20 22 22 23 24 24 23 22 22 22 23 24 25 26 28 33 36 45 47 49 50 50 48 46 44 39 37 34 30 27 25 23 23 24 26 29 31 33 37 42 45 52 55 59 63 65 64 63 61 57 55 50 45 41 37 35 34 35 38 42 46 50 55 62 67 78 83 87 85 80 72 58 45 30 25 20 21 27 35 39 41 38 35 31 30 34 42 51 57 60 60 57 51 42 35 30 28 27 28 29 32 36 41 45 48 49 50 51 50 48 44 39 36 32 32 33 36 41 47 52 55 54 52 49 46 41 38 35 33 34 37 42 48 56 65 75 81 89 85 79 72 59 48 44 48 57 74 94 106 108 99 82 66 47 38 32 37 44 48 50 53 49 52 57 66 78 89 94 95 89 82 72 65 62 62 62 62 64 63 61 58 55 51 47 45 38 35 33 33 31 28 31 37 45 58 73 84 92 96 92 85 73 61 48 41 35 31 31 34 39 46 59 71 79 80 77 74 62 58 54 53 55 57 58 58 56 51 43 35 31 32 35 38 43 43 41 37 33 30 29 30 32 33 34 34 32 32 33 34 34 34 34 33 32 31 30 30 27 27 25 23 22 23 27 30 34 37 42 45 46 48 50 51 49 49 48 45 42 40 41 43 50 56 64 73 82 86 78 67 59 47 35 28 24 21 22 26 30 30 30 30 29 27 25 24 25 24 24 23 21 20 18 17 13 13 13 13 14 15 16 17 18 18 18 17 15 14 12 11 8 8 9 9 10 11 11 12 10 9 9 8 8 9 9 10 14 15 17 19 20 20 20 19 15 14 13 11 10 9 9 9 8 8 9 8 8 8 7 7 7 7 6 6 6 6 5 5 6 6 6 6 6 6 6 6 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 8 8 8 8 9 9 9 10 10 10 10 10 10 10 10 10 9 9 9 10 10 10 10 10 11 12 13 15 17 19 20 21 23 24 25 26 26 25 24 23 23 24 24 23 23 26 30 33 41 43 45 48 49 48 47 46 42 40 37 33 29 26 23 22 24 25 27 29 30 33 38 42 49 53 58 62 65 65 63 61 57 55 51 47 43 39 37 36 36 38 42 45 49 55 61 66 76 82 86 85 81 73 60 47 32 27 21 20 25 32 35 36 36 33 31 31 36 45 54 60 65 64 61 54 45 36 30 28 26 27 29 32 36 41 45 48 50 51 51 51 50 48 46 44 38 39 40 42 45 49 53 55 52 50 47 44 39 35 32 31 31 33 37 42 48 56 65 72 82 78 74 68 57 46 43 46 57 75 95 108 112 105 89 75 50 40 34 38 46 51 54 58 57 62 68 77 88 99 100 97 88 78 66 58 57 60 63 64 68 67 65 61 56 50 45 42 35 32 31 32 31 30 34 41 49 64 82 95 105 109 105 98 82 70 56 47 40 35 35 38 42 49 61 76 87 92 91 89 77 71 64 61 62 64 65 64 59 53 44 35 31 31 34 36 43 44 44 41 37 33 31 31 31 33 34 34 32 32 33 35 37 37 37 37 36 35 34 33 29 29 27 24 23 26 31 35 38 42 47 50 51 51 52 53 49 49 47 43 39 37 37 39 45 51 57 63 69 71 64 55 48 39 31 28 25 22 23 26 28 28 28 28 28 27 26 26 25 24 22 21 19 17 16 15 13 13 13 13 13 14 15 16 16 16 16 16 14 13 12 11 8 9 9 10 10 11 11 11 10 9 9 8 8 9 9 10 14 15 17 19 20 19 19 18 14 13 12 10 9 8 8 8 7 8 8 9 9 8 7 7 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 8 8 8 9 9 9 10 10 11 11 11 11 11 11 11 11 10 10 10 10 10 10 10 10 11 11 13 15 17 19 21 21 23 25 26 28 28 26 25 23 24 24 23 22 21 23 27 31 36 38 42 45 48 48 48 47 44 42 39 34 30 26 23 22 22 24 25 25 26 30 34 38 44 48 54 59 61 61 59 57 54 53 50 47 44 41 39 38 36 38 42 45 49 54 60 64 71 77 81 81 78 71 58 46 34 28 22 21 25 30 33 33 34 32 31 32 38 47 57 63 70 69 66 59 49 39 32 29 27 27 29 31 36 40 44 47 49 49 49 49 49 50 50 51 48 49 50 51 53 55 56 57 51 50 47 43 39 35 33 31 29 30 33 36 41 49 58 64 71 69 67 63 54 45 44 48 60 77 98 112 117 112 98 84 60 49 42 45 52 57 61 64 68 73 78 83 92 100 96 88 77 66 52 46 49 57 63 67 71 70 66 61 54 46 39 35 32 29 28 30 30 31 36 43 54 70 89 105 116 121 116 109 89 76 62 52 45 39 39 42 46 53 65 80 94 101 102 101 90 82 73 68 69 70 70 68 61 54 44 34 29 29 32 34 42 44 46 45 41 37 34 33 31 32 34 34 32 32 34 35 40 40 41 40 40 38 36 35 32 30 28 25 25 28 34 39 43 47 52 55 55 54 54 54 48 47 44 39 35 32 33 34 37 44 50 52 54 54 50 44 40 33 28 27 26 22 22 24 25 26 26 27 27 27 27 27 24 23 21 18 16 15 13 13 14 14 13 13 13 14 15 15 14 14 14 14 14 13 12 11 10 10 10 10 11 11 11 11 10 9 9 8 8 9 9 10 13 14 16 18 19 18 17 17 13 12 11 9 8 7 7 7 6 7 8 9 9 9 8 7 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 8 8 8 9 9 10 10 10 11 11 11 11 11 11 11 11 10 10 10 10 10 10 10 10 10 11 13 15 17 19 21 22 24 25 27 29 29 27 25 24 24 24 23 21 20 22 26 30 33 35 40 44 47 48 48 48 45 43 40 35 31 27 23 22 21 22 23 23 24 27 32 35 39 43 49 54 56 56 54 52 53 52 50 47 45 42 40 40 36 38 42 45 48 53 59 63 64 71 76 76 73 67 54 42 34 29 23 21 25 29 31 31 33 32 31 32 39 48 58 64 74 73 70 62 51 41 34 30 27 27 29 31 35 40 44 46 48 47 47 47 48 50 53 54 56 57 58 60 60 61 60 60 51 50 47 44 40 36 34 32 28 29 31 33 37 44 53 59 63 61 61 59 53 45 45 49 63 80 101 115 120 116 103 90 70 59 50 52 58 63 66 70 78 82 85 87 92 96 88 76 61 51 38 35 42 54 64 70 73 71 67 61 52 43 35 30 30 27 27 29 30 31 37 45 57 74 94 111 123 128 123 115 93 80 65 55 48 42 42 45 50 56 67 83 98 107 109 108 97 88 78 72 73 74 73 70 61 54 43 34 28 28 30 33 41 44 47 47 44 39 35 34 30 32 34 34 32 32 34 36 42 42 43 43 41 39 37 36 33 31 29 26 25 29 36 41 46 50 56 59 58 56 55 55 45 44 41 35 30 28 28 30 30 38 43 43 42 42 40 36 35 29 26 27 26 22 20 22 23 24 25 25 26 27 28 28 24 22 20 17 15 13 12 12 15 14 14 13 13 14 14 15 13 13 13 14 14 13 12 12 11 11 11 11 11 11 11 11 10 9 9 8 8 9 9 10 13 14 16 17 18 17 17 16 13 12 10 9 7 7 7 7 6 7 8 10 10 9 8 7 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 5 5 5 6 6 7 7 7 8 8 7 8 9 10 11 12 13 13 14 15 15 14 14 13 11 11 11 11 11 11 11 11 14 14 15 16 18 19 20 21 25 26 26 27 27 26 26 25 25 24 22 21 20 20 21 22 26 29 33 37 41 44 46 46 40 39 37 34 30 26 23 21 22 21 21 22 23 26 28 30 34 37 42 46 50 52 52 52 46 46 47 46 45 43 41 39 43 42 41 41 43 47 51 54 64 65 67 69 69 64 57 51 38 31 23 22 26 31 33 33 29 26 27 32 38 46 59 71 74 73 72 67 56 43 35 32 27 26 27 31 37 42 45 46 44 44 42 40 41 45 51 56 62 62 63 64 65 64 61 58 54 52 49 45 41 38 36 35 32 32 32 33 34 39 44 48 55 56 56 53 49 47 49 51 68 83 100 113 122 123 110 95 80 68 60 62 67 69 75 81 78 83 85 86 89 88 76 61 44 39 33 33 40 53 64 71 76 71 63 53 44 37 32 30 23 24 26 26 27 31 38 43 54 72 91 104 119 130 123 108 93 80 64 54 47 43 45 50 53 62 74 86 100 113 116 114 101 90 80 75 73 69 66 67 61 49 38 33 28 25 29 38 41 43 46 48 46 41 35 31 29 28 26 26 28 32 36 38 43 43 42 40 37 35 36 38 32 32 31 30 30 33 38 42 48 55 61 60 60 60 57 53 43 39 33 27 24 24 25 27 31 32 34 36 36 35 33 32 25 26 27 27 26 25 23 22 23 24 25 26 27 28 27 27 26 23 20 16 14 14 14 15 15 16 17 18 17 16 14 13 12 12 12 12 12 13 14 14 13 13 12 12 12 11 11 11 11 11 9 8 8 9 11 12 15 16 17 17 16 15 13 12 11 11 10 9 9 8 7 7 9 9 9 9 9 9 9 9 6 5 5 5 5 6 7 8 5 6 6 7 7 8 8 8 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 5 5 5 6 6 7 7 7 8 8 7 8 9 10 11 12 13 14 15 15 16 15 15 15 14 14 13 13 12 12 12 11 13 14 15 16 17 19 20 20 24 24 25 26 27 27 26 26 26 25 23 21 20 20 21 21 24 26 30 34 37 40 41 42 38 38 36 33 29 25 22 20 22 21 21 21 22 24 26 27 31 33 37 42 45 47 48 48 45 46 46 47 46 44 43 41 42 41 40 40 41 45 48 51 59 61 64 68 68 64 58 52 41 34 27 25 29 33 35 34 31 28 27 32 38 46 60 72 76 76 75 70 59 47 38 34 25 25 25 29 34 39 41 42 42 41 40 38 38 43 50 55 62 63 63 64 64 63 60 58 54 52 50 47 44 41 39 38 36 36 36 36 37 39 43 46 47 49 51 51 50 52 55 59 69 82 97 108 117 118 108 96 86 77 72 75 79 79 81 85 79 81 82 81 83 81 69 56 39 34 30 31 38 51 62 69 70 66 57 48 39 33 29 27 22 25 27 28 29 32 38 43 49 66 84 97 112 123 118 105 87 74 59 50 45 43 47 52 54 63 75 87 101 113 117 115 105 93 80 74 70 64 62 62 56 46 35 29 25 23 28 35 41 43 46 47 44 39 33 28 26 25 24 24 26 30 35 38 42 42 41 39 36 34 35 36 33 33 33 32 32 35 40 44 51 59 64 64 62 61 57 52 40 36 30 25 22 22 23 25 27 28 30 31 31 30 28 26 24 25 26 26 26 24 23 22 23 24 25 27 28 28 27 27 25 23 20 17 16 15 16 17 16 17 18 18 18 17 15 14 13 13 13 13 14 15 16 16 15 15 14 13 12 11 11 11 10 10 9 8 9 10 12 13 15 16 16 16 16 14 13 11 10 10 10 9 9 9 9 8 9 9 9 9 9 9 9 9 6 6 5 5 6 7 7 8 6 6 7 7 7 8 8 8 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 5 5 5 6 6 7 7 7 8 8 7 8 9 10 11 12 14 15 16 17 17 17 17 17 18 17 17 15 14 13 12 12 13 14 15 16 17 18 19 19 21 22 24 25 27 27 27 27 27 26 24 22 21 20 20 20 20 21 24 27 30 33 34 35 35 34 33 30 27 24 22 20 21 21 20 20 21 22 23 23 26 28 32 36 39 41 42 42 44 44 45 45 45 45 44 43 41 40 38 37 38 40 43 45 51 54 59 64 67 65 59 54 45 39 32 30 32 36 37 37 34 30 28 31 37 45 60 73 78 80 80 74 64 53 43 38 27 26 25 28 32 36 39 39 39 38 36 34 35 39 46 52 61 62 62 62 61 59 57 56 53 53 52 51 49 47 45 44 42 42 41 40 40 41 42 43 42 44 46 48 50 55 60 65 70 79 91 100 107 109 103 95 91 86 86 91 94 92 89 87 80 79 76 74 74 72 62 50 38 34 30 31 39 50 61 66 65 60 53 44 36 30 27 25 23 25 28 31 33 35 39 42 47 60 74 86 100 110 107 96 79 66 52 45 42 42 47 53 55 64 76 88 102 114 118 115 108 94 79 70 63 56 53 54 49 40 32 27 24 24 30 36 42 44 46 46 42 36 30 25 24 22 21 21 23 28 34 37 40 40 39 37 33 32 32 33 33 34 34 34 34 38 43 47 53 61 67 67 63 60 54 48 35 32 28 23 20 20 21 22 25 26 27 27 26 25 23 22 23 24 24 24 24 23 22 22 23 24 26 28 28 28 28 27 24 22 21 19 18 18 19 20 18 19 19 19 19 18 17 16 15 15 16 17 18 19 20 20 18 17 15 14 12 11 10 10 9 8 9 9 10 12 13 14 16 16 16 16 15 13 12 11 9 9 9 10 10 10 11 11 10 10 10 9 9 9 9 9 7 6 6 6 6 7 8 9 7 7 7 8 8 8 9 9 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 5 5 5 6 6 7 7 7 8 8 7 8 9 10 11 12 14 15 17 18 19 20 20 19 20 20 18 17 15 13 12 11 13 13 14 15 16 17 17 18 19 20 22 24 26 27 28 28 28 27 25 23 22 20 19 18 16 17 19 21 23 25 26 27 30 30 29 27 25 23 21 19 20 20 19 19 19 19 19 20 23 25 28 32 35 37 39 39 42 42 42 43 43 43 43 43 38 37 36 35 35 36 37 39 42 46 53 60 65 65 61 57 50 45 38 35 36 38 39 39 37 31 28 30 34 43 57 70 77 82 83 77 67 58 48 40 32 30 29 30 34 37 40 40 37 36 33 30 31 35 43 49 57 59 59 58 56 53 52 52 53 54 55 55 55 53 51 50 47 46 45 46 46 45 43 41 44 44 44 45 49 54 60 64 70 75 82 89 93 95 94 91 90 91 96 103 106 103 95 88 80 76 70 68 68 66 59 51 44 41 37 37 43 52 59 63 61 57 50 42 35 30 28 27 24 27 32 36 39 40 41 42 47 56 66 75 87 95 93 85 73 60 47 40 38 39 44 51 55 64 76 87 101 113 116 114 108 92 74 62 54 46 43 44 40 35 30 27 28 31 37 41 45 46 46 44 40 34 28 24 23 22 20 20 23 27 32 36 37 37 36 34 30 28 29 30 33 33 34 34 35 40 45 50 54 62 68 67 62 57 49 42 32 30 26 23 20 20 20 20 25 25 25 25 24 22 21 19 22 22 22 22 22 22 21 21 23 24 26 28 29 29 28 27 23 22 22 21 21 21 22 23 21 21 21 21 20 20 19 19 17 18 19 21 22 23 23 23 21 19 17 14 12 11 10 10 8 8 9 11 12 14 16 17 16 16 15 14 13 12 11 10 8 9 9 10 11 12 13 13 11 10 10 10 10 9 9 9 7 7 7 7 7 8 9 9 8 8 8 9 9 9 9 9 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 5 5 5 6 6 7 7 7 8 8 7 8 9 10 11 12 14 15 17 19 20 21 21 21 21 20 19 17 15 13 12 11 13 13 14 14 15 16 16 16 18 19 21 23 25 27 27 28 28 27 26 24 23 21 19 18 15 15 15 16 18 19 20 21 25 25 25 24 23 21 20 19 19 19 19 19 18 18 17 17 21 23 26 30 33 37 39 40 40 40 40 39 39 39 39 39 36 35 33 32 32 32 33 33 36 40 47 55 62 65 63 61 55 51 45 41 39 40 40 40 39 33 29 30 33 40 54 66 74 81 84 78 70 62 52 42 36 33 31 31 34 38 41 41 38 35 32 28 28 32 40 46 53 54 55 53 49 46 46 47 52 54 56 58 59 57 55 53 49 49 50 52 54 53 49 46 46 44 42 43 47 53 59 62 67 68 71 75 77 78 80 82 86 91 101 110 116 113 102 92 81 73 65 63 64 64 60 57 53 50 45 44 47 51 55 57 55 52 46 39 33 30 28 27 28 31 37 43 47 47 45 44 44 49 55 64 75 83 83 79 67 56 43 37 35 35 39 45 53 62 73 85 98 110 113 110 102 85 66 52 43 36 34 36 32 32 31 31 34 40 45 47 49 48 46 43 38 33 29 26 26 25 24 24 26 29 32 34 34 35 34 30 27 25 25 26 30 31 32 33 35 39 46 50 56 64 69 67 61 55 46 38 30 28 26 24 22 21 20 20 23 22 22 21 20 19 18 17 20 20 20 20 20 20 21 21 22 24 27 30 30 30 28 27 23 23 23 23 24 24 25 26 23 23 22 22 21 21 21 21 20 21 23 24 25 25 25 25 22 20 17 13 11 10 10 10 9 10 11 13 15 17 18 19 16 16 14 13 12 11 10 9 9 9 10 11 12 13 14 14 12 11 11 10 10 9 9 9 8 8 7 7 8 9 10 10 10 10 10 9 9 9 9 9 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 5 5 5 6 6 7 7 7 8 8 7 8 9 10 11 12 13 14 16 19 20 22 22 23 22 21 20 18 16 15 13 13 13 13 13 14 14 15 15 15 17 19 21 23 25 26 26 27 26 26 26 25 24 22 20 19 15 15 14 14 14 15 16 17 20 20 21 21 21 20 19 18 17 18 18 19 19 18 17 16 20 22 25 29 33 38 41 43 42 41 39 37 36 35 35 35 33 32 31 30 30 30 30 30 33 36 42 51 59 64 66 65 61 57 52 47 44 43 43 44 43 37 32 32 34 39 50 61 69 80 85 79 72 67 57 45 37 34 31 31 35 39 41 42 40 37 32 27 26 30 37 43 49 51 52 49 43 40 40 42 50 53 57 60 61 59 56 54 51 51 54 60 65 65 61 56 49 45 41 41 45 52 57 60 63 60 60 62 61 60 64 69 78 88 101 112 120 120 110 98 84 72 62 60 62 63 63 63 61 57 53 50 50 51 52 51 49 46 41 35 31 28 27 26 32 36 43 51 55 55 51 46 40 41 44 53 64 72 75 75 62 51 41 36 34 33 35 40 49 58 69 80 93 105 108 105 94 77 56 43 35 30 30 33 30 35 39 40 45 51 54 53 55 52 47 41 37 34 32 32 32 32 32 32 32 32 32 33 32 32 31 27 23 21 21 22 25 26 28 29 32 37 44 49 58 65 68 65 58 52 44 36 27 27 26 25 23 22 21 20 19 18 18 17 16 16 15 15 19 18 18 18 18 19 20 20 22 24 28 31 31 30 28 26 25 25 25 26 26 27 27 27 26 25 24 23 23 23 23 24 23 24 26 27 27 27 26 25 22 19 16 12 10 9 10 10 11 12 14 16 18 19 20 20 17 16 14 12 10 9 9 9 10 10 11 12 13 14 14 15 12 12 12 11 10 10 9 9 9 9 8 8 9 9 10 11 11 11 11 10 10 10 9 9 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 5 5 5 6 6 7 7 7 8 8 7 8 9 10 11 12 12 13 15 18 20 22 23 23 23 22 21 20 19 17 16 16 12 13 13 13 13 14 14 14 18 19 21 22 24 25 25 25 25 25 26 26 25 23 21 20 17 16 15 14 13 14 15 15 16 17 18 18 19 19 18 18 16 17 18 19 19 19 18 17 18 20 23 28 34 39 43 45 45 44 41 37 35 33 32 32 30 30 30 29 29 29 29 29 32 34 39 47 57 64 68 69 67 65 60 54 50 47 47 48 47 42 37 36 36 39 49 59 67 79 86 81 75 72 62 49 40 37 34 34 37 42 45 46 43 40 34 28 25 29 36 41 48 50 51 47 40 37 38 41 49 52 57 61 62 60 56 53 52 54 59 68 76 79 74 69 57 51 44 40 42 47 51 53 58 54 51 51 48 45 49 57 67 80 95 108 118 122 113 100 88 73 61 58 60 61 63 66 68 65 60 57 56 55 53 52 47 45 40 35 31 29 28 28 36 40 48 57 63 62 55 49 42 39 39 44 53 60 64 65 56 47 39 36 35 33 34 38 44 53 64 75 88 100 103 100 87 70 49 37 30 28 30 35 41 48 55 57 61 66 65 61 60 55 48 41 36 35 36 38 40 40 40 40 38 36 33 31 30 30 29 25 21 19 19 20 20 21 23 25 28 34 41 46 55 61 63 58 52 46 39 32 25 25 25 25 24 22 20 19 18 17 17 16 16 16 17 17 18 17 16 16 16 18 19 20 22 25 28 31 32 31 28 26 26 27 27 28 28 28 28 28 28 27 25 24 24 24 25 26 25 26 28 29 29 27 25 24 20 18 14 10 9 9 10 11 14 15 17 19 21 22 21 21 17 15 13 11 9 8 8 8 11 11 12 12 13 14 14 14 13 13 12 11 10 10 9 9 10 9 9 9 9 10 11 12 12 12 11 11 11 10 10 10 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 5 5 5 6 6 7 7 7 8 8 7 8 9 10 11 12 11 12 15 18 20 22 23 23 24 24 23 22 21 19 19 18 12 12 13 13 13 13 13 14 18 19 21 22 23 24 24 24 24 25 26 26 25 24 22 21 18 17 15 14 13 13 14 15 14 15 16 17 18 18 18 18 15 16 18 19 20 19 18 18 17 19 22 27 33 39 44 47 49 46 42 38 34 32 31 30 29 29 29 29 29 29 29 29 32 33 37 45 55 64 69 71 71 69 65 59 53 50 50 51 51 45 41 40 39 41 48 57 66 79 87 82 78 75 66 52 44 41 38 38 41 46 50 51 46 42 35 29 25 28 35 41 48 51 51 46 39 36 37 41 48 52 57 61 62 60 55 52 53 55 62 73 84 88 84 78 67 59 48 41 40 42 43 44 55 49 46 45 41 36 41 50 58 71 88 101 113 119 112 100 91 75 60 57 59 59 62 67 74 70 66 64 62 61 58 56 49 46 42 37 34 32 32 32 39 43 52 61 67 66 58 51 48 42 38 40 46 50 52 54 51 43 37 36 36 34 35 38 41 50 61 72 85 96 99 96 83 66 46 34 29 28 32 38 53 62 69 71 74 78 75 68 63 57 48 40 36 36 39 42 44 45 46 45 43 38 34 31 29 29 27 24 20 17 17 18 17 18 20 22 26 32 39 45 50 55 56 51 44 39 32 26 23 23 24 24 23 21 19 18 19 19 18 18 18 19 20 20 17 16 15 15 16 17 19 20 22 25 29 32 32 31 28 26 27 28 28 29 29 29 28 28 29 28 26 25 24 25 26 27 27 28 29 30 29 27 24 23 19 17 13 9 8 8 10 11 16 17 19 21 23 23 22 22 17 15 13 10 8 8 8 8 12 12 13 13 13 14 14 14 14 13 12 12 11 10 9 9 10 10 9 9 9 10 11 12 13 12 12 11 11 10 10 10 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 5 5 5 6 6 7 7 7 7 7 7 8 8 9 9 9 13 14 15 16 18 21 23 25 22 22 23 24 23 22 20 19 18 17 16 14 14 15 16 17 19 19 20 21 22 22 23 23 22 23 25 26 27 27 26 25 20 20 19 17 14 13 13 15 17 17 16 16 16 17 18 18 17 17 17 17 17 17 17 17 16 19 25 30 35 41 47 52 53 51 47 42 37 32 28 26 27 26 26 27 28 30 33 34 36 38 42 47 54 65 76 84 87 83 75 64 55 50 50 51 55 52 46 41 38 41 47 53 62 70 78 81 80 75 66 56 45 43 41 43 47 52 56 57 52 43 34 27 22 22 30 39 49 52 52 48 41 35 33 34 44 53 59 59 58 56 52 47 50 60 70 78 89 98 98 92 77 69 57 45 38 38 41 44 46 46 45 41 36 35 38 42 54 61 74 89 102 106 104 99 85 73 63 60 58 56 60 67 72 71 70 68 66 65 63 63 59 52 46 42 36 30 29 32 38 46 59 70 75 73 67 62 54 48 41 37 37 40 44 46 41 42 41 39 36 35 35 37 38 47 58 69 82 92 94 90 73 57 39 30 29 35 46 57 72 79 85 88 88 85 75 65 60 55 47 39 36 37 41 43 48 50 53 51 46 39 34 31 25 24 22 20 18 17 16 16 20 20 20 21 25 30 35 38 46 46 45 42 38 33 29 26 22 23 25 26 26 24 22 20 19 20 20 21 21 21 21 20 19 17 15 14 15 16 18 20 21 23 27 30 31 31 29 27 27 28 28 29 30 30 31 31 29 27 25 23 23 24 25 27 29 28 27 26 25 24 23 22 15 13 11 9 9 10 12 14 17 19 23 26 27 26 24 22 15 14 12 11 10 10 11 12 13 13 14 15 16 16 16 15 15 14 13 12 11 10 11 11 8 9 10 10 11 12 13 13 12 12 11 10 10 9 8 8 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 6 6 5 5 5 4 4 4 5 5 5 4 4 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 5 5 5 6 6 7 7 7 7 7 7 8 8 9 9 9 13 13 14 16 18 20 23 24 23 23 24 25 24 23 21 20 19 17 16 15 14 15 16 17 18 18 19 20 21 21 22 22 21 23 24 26 26 26 26 25 22 23 23 22 19 17 17 18 17 17 16 16 16 17 17 18 17 17 17 17 17 17 17 17 15 19 23 28 34 41 48 54 54 52 49 44 39 34 31 29 27 26 26 26 28 31 33 35 38 40 45 50 58 69 81 88 93 88 80 69 59 53 53 54 55 53 49 44 41 43 48 52 60 69 76 79 78 75 66 57 48 46 44 46 51 57 62 64 57 47 36 28 22 21 28 38 49 52 53 50 43 36 33 33 41 49 56 56 54 53 48 43 48 57 68 77 88 99 100 96 88 79 66 52 42 38 38 39 40 41 41 38 35 35 38 41 50 56 67 81 92 97 96 93 85 74 65 60 57 54 57 62 67 68 70 72 72 72 71 71 69 61 53 47 41 35 34 37 44 52 65 75 80 79 73 69 54 48 39 33 31 33 36 37 38 39 39 37 35 34 36 37 40 48 59 68 79 87 87 82 69 54 37 30 32 39 52 64 83 90 95 94 91 86 75 64 55 49 42 35 33 35 40 44 50 52 54 52 46 38 31 28 23 22 21 21 20 19 19 19 19 19 19 21 24 28 32 35 38 37 35 33 30 27 25 23 22 23 25 27 27 25 23 21 20 21 23 25 25 24 23 22 21 19 17 15 15 16 18 19 20 23 26 29 31 31 29 28 27 27 28 28 29 29 30 30 27 26 24 22 22 23 24 25 26 26 25 24 23 22 21 21 15 13 11 10 10 12 14 15 19 21 24 27 27 26 23 21 15 14 12 11 10 11 12 12 14 14 15 16 17 17 16 16 15 14 13 12 11 10 11 11 9 9 10 11 12 12 13 13 12 12 11 10 10 9 8 8 6 6 6 6 6 6 6 6 5 5 5 5 5 5 5 5 6 6 6 5 5 5 4 4 5 5 5 4 4 4 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 5 5 5 6 6 7 7 7 7 7 7 8 8 9 9 9 13 13 14 15 17 19 21 23 24 25 26 27 26 25 24 22 19 18 16 15 14 15 16 16 17 17 18 18 19 20 20 21 21 22 23 25 26 26 26 26 25 27 29 28 25 23 22 22 18 18 18 18 17 17 17 17 17 17 16 16 16 16 16 16 15 17 21 26 32 40 50 56 55 54 51 47 43 38 34 32 27 26 26 26 27 30 34 36 40 44 49 56 65 76 87 94 97 92 84 72 61 54 53 53 54 54 53 49 47 46 48 50 58 66 74 76 76 74 66 57 51 49 48 51 57 65 70 73 65 54 41 31 23 20 26 35 48 51 54 51 44 37 33 32 38 46 53 53 52 50 46 41 45 52 62 73 86 97 101 99 96 88 75 61 49 42 39 38 37 38 38 37 37 37 40 43 47 51 59 69 79 84 86 85 83 75 67 61 56 51 51 55 61 65 71 77 82 84 84 83 82 72 61 54 46 40 39 43 52 59 70 80 85 84 80 77 60 52 41 32 28 28 29 30 34 35 36 35 34 35 37 39 42 50 59 67 75 81 78 72 62 48 35 31 36 46 62 75 95 100 103 98 91 82 69 58 48 43 36 31 30 35 42 47 52 54 56 53 46 36 28 24 20 20 22 23 23 24 24 24 19 20 20 21 23 25 28 29 28 27 26 24 23 22 22 22 24 25 27 29 29 28 26 25 23 25 28 30 31 29 27 25 24 22 19 16 15 15 17 18 19 22 25 28 30 30 29 28 27 27 27 27 27 28 28 28 25 23 22 20 20 21 22 23 22 22 22 22 21 20 19 19 15 14 12 11 12 14 17 18 23 24 27 28 27 25 22 20 15 14 12 11 11 11 13 13 16 16 17 18 18 18 18 17 15 14 13 12 11 10 11 11 10 10 10 11 12 12 13 13 12 12 11 10 10 9 8 8 5 5 5 5 5 5 5 5 7 7 7 7 7 7 7 7 7 7 6 6 6 5 5 5 5 5 5 5 4 4 4 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 5 5 5 6 6 7 7 7 7 7 7 8 8 9 9 9 12 12 13 14 16 18 20 21 25 26 27 28 28 27 25 24 19 18 16 15 14 14 15 16 15 16 16 17 18 18 19 19 20 21 22 23 24 25 26 26 27 30 33 33 31 29 27 27 22 22 22 21 20 19 18 17 17 17 17 17 16 16 16 16 15 17 20 24 30 39 50 56 58 57 54 50 45 40 36 33 28 27 26 25 27 30 33 35 42 47 54 62 71 82 92 99 98 93 84 72 60 52 49 49 53 55 56 55 52 50 49 49 57 65 72 74 74 72 66 58 53 52 51 54 62 71 78 81 73 62 47 35 25 20 24 32 44 48 52 50 43 35 31 29 37 45 52 53 52 51 47 42 42 47 55 66 79 90 96 98 96 90 80 69 59 51 47 45 41 41 41 40 41 43 46 48 49 50 54 60 66 72 76 78 79 75 69 61 54 48 47 48 55 62 72 83 91 94 95 94 92 81 68 59 51 45 45 50 57 63 73 82 86 86 83 81 70 61 49 38 32 30 30 29 31 33 35 35 35 36 39 42 44 51 60 66 72 75 71 64 54 43 33 33 40 53 70 83 99 103 103 94 82 70 56 45 40 37 32 29 30 36 43 48 53 55 56 53 44 34 26 22 19 21 24 27 29 30 30 30 25 25 24 24 24 23 23 22 22 21 20 19 20 21 23 24 27 29 31 33 34 33 31 30 27 30 33 36 36 34 30 28 26 24 21 18 16 16 17 17 18 20 23 26 27 28 27 27 26 26 26 26 26 26 25 25 22 21 20 19 18 19 19 20 18 19 20 21 21 20 19 18 16 15 13 13 14 16 19 21 26 27 29 29 28 24 21 18 14 13 12 11 11 12 14 15 18 18 19 19 20 19 19 18 15 14 13 12 11 10 11 11 10 11 11 12 12 13 13 13 12 12 11 10 10 9 8 8 5 5 5 5 5 5 5 5 7 7 7 7 7 7 7 7 8 7 7 7 6 6 6 6 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 5 5 5 6 6 7 7 7 7 7 7 8 8 9 9 9 11 11 12 13 14 16 18 19 24 25 27 28 28 27 26 25 20 19 17 15 14 14 15 15 14 15 15 16 17 18 18 19 19 20 21 22 23 24 26 26 27 30 34 36 35 33 33 33 29 29 28 27 25 23 20 19 19 18 18 18 17 17 16 16 16 17 20 24 29 38 47 54 59 58 56 52 47 42 36 33 31 29 27 25 26 29 32 34 43 48 56 65 74 85 94 101 98 94 85 72 60 51 47 46 51 54 58 59 57 53 50 49 57 64 69 70 71 70 64 58 52 50 50 54 62 72 80 84 79 67 53 40 28 21 23 29 39 44 48 47 40 33 29 28 35 43 51 53 53 52 49 44 43 44 48 58 69 79 86 89 92 89 84 77 69 62 56 53 48 46 44 43 44 47 50 51 54 54 54 55 58 63 69 72 73 73 68 60 51 47 45 45 53 61 74 87 96 100 101 100 98 87 74 65 57 52 53 58 63 68 75 82 86 87 85 83 77 68 57 46 39 36 34 33 34 36 38 38 38 40 43 46 46 53 60 64 69 71 66 59 48 38 32 35 44 57 73 85 96 99 96 84 69 56 44 35 32 30 28 28 31 36 41 45 51 53 53 50 42 33 26 23 21 24 29 33 36 37 36 35 33 32 30 27 25 22 20 19 19 19 18 19 20 22 24 26 30 32 35 37 38 38 37 36 32 34 37 39 39 36 32 29 27 25 22 19 17 17 18 19 19 20 22 24 25 25 25 25 26 26 25 25 24 23 23 23 20 19 18 18 17 17 17 17 16 17 20 21 22 22 21 20 18 17 16 15 16 19 21 23 27 29 30 30 27 23 19 16 13 13 12 11 12 13 15 16 19 19 20 20 20 20 19 18 15 14 13 12 11 10 11 11 11 12 12 12 12 13 13 13 12 12 11 10 10 9 8 8 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 8 8 8 8 7 7 7 6 6 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 5 5 5 6 6 7 7 7 7 7 7 8 8 9 9 9 11 11 11 12 13 15 16 17 22 24 25 26 27 26 25 24 21 19 17 15 14 14 14 15 14 15 15 16 17 18 18 18 19 19 19 20 22 24 26 27 28 31 35 37 38 38 40 41 39 38 37 35 32 27 24 21 21 20 20 19 18 18 17 17 17 19 22 25 29 35 43 49 55 55 54 52 48 43 39 36 34 31 28 25 25 27 30 32 41 47 56 65 75 84 93 98 98 93 85 72 60 50 45 44 49 53 58 61 59 56 52 51 55 61 65 66 65 65 60 54 48 46 45 49 58 69 78 83 81 71 58 45 32 23 23 28 36 40 44 43 38 32 30 29 34 43 51 54 55 56 54 50 49 45 45 52 60 65 72 77 87 87 86 84 79 74 68 65 58 54 48 45 46 49 51 53 59 58 55 52 52 55 61 66 66 69 66 57 49 46 46 45 55 63 75 88 97 101 101 100 98 88 77 69 63 58 61 66 68 71 77 82 85 85 84 83 78 71 62 53 48 44 40 38 41 43 44 44 44 45 48 50 50 55 59 61 64 65 60 53 43 36 32 37 47 58 71 82 88 90 85 70 55 44 35 29 26 27 30 33 36 39 40 41 48 48 48 44 38 32 28 26 27 30 36 41 43 43 42 40 38 36 33 29 25 22 20 19 20 20 21 22 23 25 26 27 32 34 37 40 42 42 41 40 37 39 40 41 39 36 32 30 26 24 22 20 19 20 22 23 22 23 24 24 25 25 24 24 25 25 24 23 22 21 20 20 18 18 18 17 17 17 16 16 16 18 21 24 25 25 24 23 21 20 18 17 18 20 22 24 27 28 29 29 26 22 18 15 13 12 11 11 12 14 17 18 20 20 20 21 20 20 19 18 15 14 13 12 11 10 11 11 12 12 12 13 13 13 13 13 12 12 11 10 10 9 8 8 8 8 8 8 8 8 8 8 7 7 7 7 7 7 7 7 9 9 9 8 8 8 7 7 7 6 6 6 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 5 5 5 6 6 7 7 7 7 7 7 8 8 9 9 9 10 10 10 11 12 14 15 16 20 21 23 24 25 24 23 23 21 19 17 15 14 13 14 14 15 15 16 16 17 18 18 19 18 18 18 19 21 23 25 27 29 32 35 38 40 43 46 49 48 47 46 43 38 32 27 24 23 22 22 21 20 19 18 18 19 21 24 26 29 33 39 43 47 49 50 50 49 46 42 40 37 34 29 25 24 25 28 30 39 45 54 64 73 82 89 94 94 90 81 69 57 47 42 40 46 51 58 61 60 57 54 53 52 57 61 60 59 59 54 48 43 40 39 43 52 63 73 78 81 72 61 49 37 26 24 27 34 38 42 41 37 33 32 33 38 47 57 60 63 65 63 59 57 49 45 49 52 54 59 66 77 80 85 89 90 88 85 82 72 64 55 49 49 51 54 55 62 60 55 50 46 47 53 58 59 64 63 53 46 47 49 49 59 66 77 88 95 98 98 97 90 81 72 67 63 60 62 68 69 71 74 78 80 80 79 79 78 73 67 61 57 53 49 46 50 51 51 51 50 50 52 54 55 58 59 57 57 58 52 45 40 34 33 39 48 56 66 75 76 78 71 56 41 32 28 25 28 33 39 45 48 47 44 42 43 43 42 39 35 32 31 31 33 37 42 47 50 49 46 44 38 36 32 28 25 23 23 23 26 27 28 29 31 31 31 31 32 34 37 40 42 42 42 41 42 42 41 40 38 34 31 29 24 22 21 20 21 23 25 27 27 27 27 27 27 26 26 25 25 24 23 22 21 20 19 18 17 18 18 18 17 17 16 15 18 20 24 27 29 29 28 27 23 22 20 19 19 21 23 24 26 27 28 28 26 21 17 14 12 12 11 12 13 15 17 19 20 20 20 20 20 19 18 17 15 14 13 12 11 10 11 11 13 13 13 13 13 13 13 13 12 12 11 10 10 9 8 8 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 10 10 9 9 9 8 8 8 7 7 6 6 6 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 5 5 5 6 6 7 7 7 7 7 7 8 8 9 9 9 10 10 10 11 12 13 15 15 19 20 22 23 24 23 22 22 21 20 17 15 14 13 14 14 15 15 16 17 17 18 19 19 18 18 18 18 20 23 25 27 30 33 36 39 42 46 51 54 53 53 51 47 42 35 29 25 24 23 23 22 21 20 19 19 20 23 25 27 29 32 36 39 41 43 46 49 49 48 46 44 39 35 30 25 23 24 27 29 37 43 53 63 72 80 87 91 89 85 77 65 52 43 37 36 45 50 57 61 60 58 55 54 49 54 57 56 55 54 50 44 39 37 35 39 48 60 69 74 80 72 62 52 39 28 25 27 34 38 41 40 37 34 35 36 43 53 63 68 71 73 72 69 63 53 46 48 49 48 52 59 67 73 83 92 98 100 99 98 83 73 61 54 52 55 58 59 62 60 55 47 42 42 47 52 55 61 61 51 45 47 51 51 62 68 78 87 93 95 95 93 82 74 66 62 59 57 60 66 66 68 70 72 74 74 74 73 79 76 71 68 65 61 57 53 55 56 56 55 53 53 54 56 58 60 59 54 53 52 46 39 39 34 33 40 48 55 63 70 66 67 61 45 30 24 23 22 34 40 49 57 59 56 50 46 40 40 39 36 33 31 33 35 37 41 47 52 53 52 48 45 36 34 29 26 24 24 26 27 33 34 36 37 38 38 37 36 31 33 36 40 42 42 41 41 44 43 42 39 36 33 30 28 22 21 20 20 21 24 27 29 32 31 31 30 29 28 27 27 25 24 23 22 20 19 17 17 17 18 18 18 18 17 16 15 19 22 26 30 32 32 31 30 25 24 21 20 20 21 23 24 25 26 28 27 25 21 17 14 12 11 11 12 13 16 18 20 20 20 20 20 19 18 17 17 15 14 13 12 11 10 11 11 13 13 13 13 13 13 13 13 12 12 11 10 10 9 8 8 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 9 9 9 8 8 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 6 6 7 7 7 7 7 7 8 8 9 9 9 11 11 11 11 11 11 11 11 16 17 19 21 23 23 22 22 22 22 21 20 18 17 16 15 16 16 17 17 17 17 18 18 19 20 21 21 21 22 24 27 30 33 38 42 45 49 53 56 59 58 56 52 47 40 34 30 26 25 25 24 25 25 26 27 26 27 29 32 34 36 36 37 39 42 46 48 48 47 46 46 44 40 35 30 27 26 26 27 37 43 51 60 67 75 81 86 83 81 73 62 49 40 37 38 44 47 52 56 58 58 56 54 55 52 49 47 46 44 40 38 30 29 29 33 40 51 62 69 75 72 66 56 45 36 31 29 32 34 36 37 38 39 41 43 51 58 68 75 79 80 81 81 67 64 58 51 46 45 48 51 56 66 77 88 99 108 109 104 96 86 71 61 57 60 64 67 62 61 56 47 38 35 39 44 57 56 53 52 53 55 57 58 67 72 79 86 88 86 81 78 71 65 58 54 54 56 59 60 62 63 64 64 64 66 70 73 72 74 73 67 65 66 64 60 59 57 57 58 61 64 64 64 61 60 57 54 48 43 38 35 34 37 40 43 47 52 59 63 60 58 50 38 25 20 23 28 39 54 67 72 69 63 55 47 39 37 35 34 33 34 36 37 45 49 54 58 57 54 48 44 34 30 25 22 23 28 35 39 41 44 48 48 44 38 33 31 25 27 31 35 38 39 39 39 39 37 34 32 31 29 26 24 21 20 20 22 27 31 33 34 36 36 35 34 32 30 28 27 27 26 23 21 20 19 20 20 20 21 21 20 19 20 22 24 21 25 30 35 37 35 33 31 24 23 21 20 21 22 23 24 25 25 25 24 22 19 16 15 10 10 12 14 16 18 19 20 21 20 20 19 19 18 17 17 15 14 13 12 12 12 13 13 15 14 13 13 12 12 13 13 11 12 12 13 13 12 12 11 10 10 10 11 11 11 12 12 11 11 11 12 12 12 12 12 10 10 9 8 8 8 9 9 7 7 7 6 6 5 5 5 5 5 5 4 4 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 6 6 7 7 7 7 7 7 8 8 9 9 9 11 11 11 11 11 11 11 11 15 16 18 20 21 21 21 21 22 22 21 20 19 17 16 16 16 16 17 17 17 18 18 18 19 20 22 22 21 22 25 27 30 33 38 42 44 48 52 55 57 57 55 52 47 41 35 31 27 27 26 26 27 29 30 31 33 34 35 37 37 37 36 35 36 39 43 46 47 48 48 49 46 43 37 32 28 27 27 28 34 40 47 55 63 70 77 82 80 78 72 61 49 41 37 36 44 47 53 57 60 59 57 55 52 49 46 43 41 39 35 33 29 28 27 30 37 46 56 62 69 67 62 53 44 36 32 31 36 38 40 41 41 42 44 46 55 61 70 77 80 82 83 83 79 74 66 56 47 42 41 42 48 59 73 87 101 111 113 108 99 89 75 66 64 67 71 73 65 62 54 45 38 38 44 49 51 52 52 52 53 57 62 65 78 80 84 86 83 77 70 65 61 57 52 50 51 54 57 58 55 56 57 57 57 59 63 66 69 72 71 67 65 65 63 59 58 56 55 56 60 63 64 64 62 60 56 51 45 40 35 33 33 35 39 43 47 52 58 62 58 56 49 38 26 23 27 33 49 63 77 80 75 67 56 46 35 34 33 33 35 38 42 44 49 52 55 57 56 51 45 41 31 28 24 22 25 31 39 44 53 55 55 51 44 36 30 26 22 25 29 33 36 37 36 35 35 33 30 29 29 28 26 23 22 21 21 23 28 32 34 35 37 36 36 34 33 31 29 28 27 25 23 20 19 19 20 20 21 22 23 22 21 20 21 23 23 27 32 36 38 36 33 31 24 23 21 20 20 21 22 23 23 23 23 23 21 18 16 14 11 11 13 15 17 19 20 21 21 21 20 20 19 18 18 17 14 14 13 12 12 12 12 13 13 13 12 12 11 12 12 13 13 13 14 14 14 14 13 13 12 12 12 13 13 14 14 14 13 13 13 13 13 13 13 13 11 10 9 8 8 8 9 9 7 7 7 6 6 6 5 5 5 5 5 4 4 4 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 6 6 7 7 7 7 7 7 8 8 9 9 9 11 11 11 11 11 11 11 11 13 14 15 17 18 19 19 19 22 22 21 20 19 18 17 16 16 16 17 17 18 18 18 19 19 20 22 22 21 23 25 28 31 34 39 42 44 46 50 52 54 54 54 52 48 43 37 34 29 29 29 29 31 34 36 38 43 44 45 45 43 40 37 35 33 35 39 44 47 50 51 51 49 45 39 33 29 28 29 30 34 39 46 53 60 67 74 79 76 75 69 61 51 42 37 36 44 47 53 59 61 61 59 57 53 49 45 41 39 36 33 30 31 30 30 32 37 45 53 58 65 64 59 52 44 38 35 35 41 43 45 46 46 47 49 51 60 65 72 78 81 83 84 85 86 82 73 61 49 40 36 35 41 53 70 86 101 112 112 107 98 89 77 71 71 74 77 78 65 58 47 37 31 34 42 49 50 51 53 53 54 59 66 73 86 86 86 83 76 67 58 53 49 47 44 45 47 51 53 53 49 49 50 49 49 52 56 59 65 68 69 65 63 63 60 55 54 52 51 52 56 60 62 63 64 60 54 48 41 36 32 31 32 35 39 43 47 52 57 61 58 56 50 39 29 27 33 40 59 73 87 89 82 70 56 44 31 31 31 33 38 43 49 53 55 56 57 56 53 47 41 37 26 24 23 24 29 37 45 50 61 61 59 52 42 33 26 22 20 23 28 32 34 34 32 31 28 26 25 25 26 26 24 23 23 22 21 24 28 32 35 35 37 36 35 34 32 31 30 29 26 24 22 19 18 18 19 20 23 25 26 25 23 21 21 22 27 30 35 38 39 37 34 31 24 23 21 19 19 19 20 21 21 21 22 21 20 17 15 14 12 13 15 16 19 20 22 23 23 22 22 21 20 19 18 18 14 14 13 12 11 11 12 12 12 11 11 10 11 11 12 13 15 15 16 16 16 16 15 15 15 15 15 15 16 16 17 17 15 15 15 15 15 15 15 15 11 11 10 9 8 8 9 9 7 7 7 7 6 6 6 5 5 5 5 5 4 4 4 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 6 6 7 7 7 7 7 7 8 8 9 9 9 11 11 11 11 11 11 11 11 11 12 13 14 16 17 17 17 21 21 20 19 18 17 17 16 16 16 17 17 18 19 19 20 19 20 22 22 22 23 26 29 32 35 39 42 43 45 47 49 49 50 51 51 48 44 39 35 30 30 31 32 35 39 43 46 52 53 54 53 51 46 42 39 33 34 37 42 48 51 52 52 52 47 40 34 29 28 29 30 36 41 48 54 61 67 74 78 74 72 68 62 54 47 42 39 43 47 54 59 62 62 61 59 58 54 49 45 43 40 38 35 38 38 38 39 44 50 57 60 65 64 60 54 47 41 39 39 43 45 48 49 50 52 54 57 64 67 72 76 78 80 82 84 82 79 73 63 52 42 37 35 39 52 69 84 98 106 104 98 90 82 73 70 73 78 79 78 66 56 42 31 28 32 40 46 52 54 55 54 53 58 67 75 83 82 80 76 69 61 53 49 43 41 40 41 44 46 47 47 45 45 45 44 44 47 52 56 60 65 66 64 61 60 55 48 46 44 43 45 50 56 60 62 64 59 52 44 38 33 31 30 34 37 41 44 48 52 58 62 61 59 53 42 32 30 36 42 61 76 89 91 83 69 53 41 29 30 31 35 40 47 54 58 59 59 57 54 48 42 36 33 24 24 25 28 34 43 52 57 61 60 56 48 38 29 24 21 21 25 30 34 36 34 31 28 22 21 20 21 23 24 24 22 23 22 21 23 28 32 34 34 35 34 33 32 30 29 29 28 26 24 21 18 17 18 20 21 26 27 29 27 24 22 21 21 30 33 37 40 40 37 33 30 23 22 20 18 18 18 19 19 19 20 20 20 19 17 15 14 15 15 17 19 21 23 24 25 24 24 23 22 21 20 19 19 15 14 13 12 11 11 11 11 10 10 10 10 11 12 13 13 16 17 17 18 18 17 17 16 16 17 17 17 18 18 18 18 18 18 18 17 17 17 17 17 12 12 10 9 9 8 9 9 8 8 7 7 7 6 6 6 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 6 6 7 7 7 7 7 7 8 8 9 9 9 11 11 11 11 11 11 11 11 10 11 11 12 13 15 16 16 19 19 19 18 17 17 16 16 16 16 17 18 19 20 20 21 18 20 22 22 23 24 27 30 32 36 40 42 43 43 44 45 44 46 49 50 48 44 39 35 30 30 31 34 38 44 49 53 58 60 62 62 59 54 48 44 36 36 38 43 49 53 54 54 53 48 41 33 28 27 28 29 38 43 50 57 62 67 72 76 72 71 67 63 59 54 49 47 45 48 54 59 63 64 64 63 65 61 55 52 50 49 47 45 48 48 48 49 52 57 61 64 65 64 61 55 48 43 41 41 44 47 50 52 53 55 58 61 65 67 69 70 70 72 74 76 74 73 70 63 54 44 38 35 38 50 66 80 92 97 94 86 79 72 66 67 73 78 78 76 68 57 43 35 35 40 46 49 53 53 52 49 49 55 64 71 75 74 71 67 62 56 51 48 44 42 40 40 42 42 41 40 41 41 40 39 39 42 47 51 57 62 65 63 60 57 51 43 40 37 35 37 43 51 56 59 61 57 50 43 37 34 33 33 39 41 43 45 48 53 59 64 66 65 59 47 36 32 35 41 56 69 82 83 75 62 47 36 29 30 33 37 43 49 55 58 60 58 55 50 44 38 33 30 25 26 28 32 39 47 55 59 60 58 53 44 35 27 23 22 27 31 36 40 40 36 31 27 18 17 17 19 22 24 24 24 23 22 21 23 27 31 33 33 33 32 30 28 27 27 27 27 26 24 21 18 17 19 21 23 28 29 29 28 25 22 22 22 33 35 39 41 40 36 31 28 21 20 18 17 16 17 18 19 19 20 21 21 20 19 17 16 17 18 19 21 23 25 27 27 26 26 25 23 22 21 20 19 16 16 14 13 12 12 12 12 11 10 11 11 12 14 15 16 18 18 19 19 19 19 18 18 18 18 18 18 19 19 19 20 20 20 20 19 19 18 18 18 13 13 11 10 9 9 9 9 8 8 8 7 7 7 6 6 6 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 6 6 7 7 7 7 7 7 8 8 9 9 9 11 11 11 11 11 11 11 11 10 10 10 11 12 14 15 16 17 17 16 16 15 15 15 14 16 16 17 18 19 20 21 21 18 20 22 23 23 25 28 31 33 37 41 43 42 41 41 41 40 43 46 48 46 42 37 34 29 29 31 34 40 47 54 58 63 66 68 69 66 60 52 48 39 38 39 44 52 58 59 58 55 50 42 33 28 27 28 29 38 44 52 60 65 68 71 73 71 69 66 64 62 61 58 55 50 52 56 60 64 67 69 70 71 67 63 60 59 60 59 58 61 60 59 59 59 61 63 64 64 64 61 56 50 46 45 45 49 51 54 55 55 57 59 61 62 63 62 61 59 60 62 65 67 68 68 64 55 46 39 35 37 49 62 74 83 87 82 74 66 61 57 62 71 77 75 72 61 52 44 42 48 56 60 61 58 54 48 44 46 51 58 62 66 64 62 58 55 51 49 48 47 44 41 40 40 39 37 36 35 35 34 32 32 36 41 46 53 59 65 65 63 60 52 44 39 36 32 32 37 45 51 54 56 53 48 43 40 38 39 39 45 45 45 45 47 52 59 65 71 70 65 53 41 34 34 38 49 61 71 71 63 52 40 30 27 30 34 40 45 51 55 57 58 55 50 45 39 35 32 30 28 29 31 34 40 46 52 56 60 57 51 42 32 26 25 25 34 38 43 46 44 38 31 26 18 17 18 20 24 26 26 26 25 23 22 24 28 31 33 33 31 30 28 26 25 25 26 26 28 25 21 18 18 20 23 25 29 29 29 26 23 22 23 24 33 36 38 40 38 34 28 25 19 18 16 16 16 17 18 19 20 21 22 23 23 22 20 19 19 20 22 23 26 27 29 30 28 27 26 25 23 22 20 20 18 18 16 14 13 13 13 13 12 12 12 13 15 17 18 19 21 21 22 22 22 22 21 21 19 19 20 20 21 21 21 21 22 21 21 20 19 19 18 18 14 13 12 10 9 9 8 9 9 8 8 8 7 7 7 7 7 6 6 6 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 6 6 7 7 7 7 7 7 8 8 9 9 9 11 11 11 11 11 11 11 11 10 10 10 10 11 13 15 16 15 15 14 14 14 13 13 13 16 16 17 18 20 21 22 22 18 20 22 23 23 25 28 31 34 37 41 43 42 40 39 39 38 40 44 46 45 41 35 32 27 28 29 33 40 48 56 61 69 71 74 74 70 63 54 49 40 38 39 46 56 63 65 64 59 53 44 35 29 28 29 31 40 47 57 66 70 72 72 72 69 66 63 62 64 65 64 62 56 57 59 63 67 72 75 78 79 76 72 71 72 74 75 75 76 74 72 69 66 64 63 62 66 66 64 61 56 54 54 55 57 59 60 59 57 57 58 59 59 58 55 51 48 48 50 53 59 62 66 64 58 50 43 39 42 52 62 69 74 75 68 59 52 47 46 53 64 71 68 63 55 51 50 58 72 84 87 86 76 66 54 46 46 48 50 50 54 53 51 50 50 50 51 52 49 46 41 38 37 37 35 34 32 32 30 28 28 32 38 43 49 57 65 68 68 67 60 52 45 40 34 31 34 39 45 48 51 49 46 44 43 44 45 46 49 48 45 43 44 49 58 64 73 73 69 58 45 36 34 36 46 56 63 60 51 43 34 26 24 28 34 42 48 52 55 55 54 51 46 40 36 33 32 32 30 31 32 35 38 42 46 48 51 49 43 36 29 27 28 30 41 44 49 51 48 40 31 25 20 19 19 22 26 28 29 28 28 26 25 27 30 34 35 35 31 30 27 25 25 25 26 27 29 26 22 19 19 21 25 27 30 29 27 24 21 21 24 27 33 35 37 38 36 31 25 21 16 15 15 14 15 17 19 20 22 23 24 25 25 25 23 22 21 22 23 25 27 29 31 31 29 28 27 26 24 22 21 20 20 19 18 16 15 14 14 14 14 14 15 16 18 20 22 23 25 25 26 26 26 26 25 25 22 22 22 23 23 24 24 24 22 22 21 21 20 19 18 18 15 14 12 11 9 9 8 8 9 9 8 8 8 7 7 7 7 7 6 6 6 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 6 6 7 7 7 7 7 7 8 8 9 9 9 11 11 11 11 11 11 11 11 10 10 10 10 11 13 15 17 13 13 13 13 13 12 12 12 16 16 17 18 20 21 22 23 18 20 22 23 24 25 29 32 34 37 41 43 41 39 38 37 36 39 43 45 44 39 34 30 26 26 28 32 40 49 57 62 73 75 78 77 72 63 54 48 39 38 39 47 58 67 70 69 61 55 46 37 31 29 31 32 44 52 63 72 76 76 76 75 68 64 60 60 63 66 67 66 61 61 62 65 69 75 80 83 87 84 80 80 82 85 87 87 88 86 82 77 72 67 63 61 68 69 69 66 64 62 63 65 64 65 64 62 59 56 56 57 56 54 50 45 41 40 43 45 52 57 63 65 61 55 49 46 50 57 64 67 68 65 56 46 41 37 36 45 57 64 61 55 59 58 63 78 98 113 116 114 96 82 64 52 49 47 44 40 43 43 43 44 47 52 56 58 49 45 40 37 36 36 35 34 32 32 30 28 28 32 38 43 46 56 65 70 73 72 66 58 51 45 37 32 33 36 41 43 47 47 46 45 46 48 49 50 52 49 45 41 41 47 56 63 73 74 71 61 48 38 35 36 46 54 59 54 45 38 30 23 21 26 34 43 49 53 55 55 51 47 42 37 34 32 32 33 31 32 32 34 36 39 41 42 39 37 34 29 26 27 31 35 44 48 52 54 49 40 30 23 21 21 21 23 27 30 30 29 30 29 27 29 32 36 37 38 32 30 28 26 25 26 27 29 30 27 23 19 19 22 26 28 30 29 26 22 20 21 25 28 33 34 37 37 34 29 23 19 14 14 13 14 15 17 19 21 23 24 26 27 27 27 25 25 22 23 24 26 28 30 32 32 30 29 28 26 24 23 21 21 22 21 19 17 16 15 15 15 15 16 16 18 20 22 24 25 28 28 29 29 29 29 28 28 24 24 25 25 25 26 26 26 23 22 21 21 20 19 18 18 15 14 13 11 10 9 8 8 9 9 9 8 8 7 7 7 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 8 8 8 8 8 8 8 8 12 12 12 12 12 12 12 12 10 10 11 12 12 13 14 14 12 11 10 9 10 11 12 13 14 15 16 17 19 20 21 22 22 22 22 21 21 24 29 33 36 39 43 47 47 44 40 38 38 37 38 39 39 37 32 28 23 23 25 29 36 45 53 58 63 67 71 72 69 61 52 46 36 36 40 48 59 68 71 71 67 58 48 39 31 26 30 36 48 57 67 75 81 84 79 71 67 60 56 60 64 64 65 67 67 65 64 65 70 76 83 88 88 88 88 88 90 93 95 97 101 94 87 80 71 62 60 64 67 69 72 74 75 74 72 71 75 69 66 66 64 58 53 53 49 48 46 41 36 33 33 34 42 53 62 64 63 62 59 55 57 61 66 68 67 60 49 39 28 32 40 47 52 53 52 51 50 61 81 110 140 159 157 146 128 102 83 72 57 50 50 45 40 35 35 41 48 51 55 60 54 47 39 34 34 36 36 35 36 35 33 32 31 33 37 40 49 54 64 75 81 80 73 68 58 50 41 37 33 32 35 41 43 46 49 52 53 56 59 62 55 54 49 42 37 40 50 59 68 71 71 62 49 40 38 41 48 49 54 56 46 29 20 20 23 26 33 42 49 51 50 48 47 42 36 31 30 31 32 32 33 33 32 32 32 32 33 33 31 31 28 24 22 23 29 34 46 49 51 51 48 40 32 27 19 20 23 26 29 31 32 33 32 31 32 35 38 41 42 41 37 33 28 26 27 30 32 32 33 29 25 23 24 26 27 28 29 29 26 22 18 20 25 30 37 37 37 35 30 24 19 15 15 15 16 17 19 21 23 24 28 30 32 34 32 29 24 22 24 24 25 26 28 31 33 34 33 32 30 27 25 23 22 22 21 21 20 18 17 16 15 14 15 17 20 24 27 28 29 29 30 30 31 31 30 29 29 28 29 29 29 29 28 27 26 25 26 24 21 18 17 17 18 19 13 13 12 12 12 11 11 11 8 9 10 11 10 9 8 7 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 8 8 8 8 8 8 8 8 11 11 11 11 11 11 11 11 10 10 11 12 12 13 14 14 13 12 10 10 9 10 11 12 13 14 15 17 19 21 22 23 21 22 22 21 21 24 29 32 36 39 44 47 48 46 43 40 39 38 38 39 39 36 31 27 23 23 24 28 34 42 50 54 61 64 69 70 67 58 49 42 33 33 36 45 56 64 68 68 64 56 47 40 33 29 32 39 51 60 71 79 85 86 80 71 64 56 51 54 59 61 63 66 66 65 65 66 70 76 82 86 89 89 89 91 93 96 99 101 99 92 84 76 67 59 58 62 69 72 78 82 85 85 83 81 78 72 67 66 63 56 52 51 47 46 43 39 34 31 31 33 41 53 66 71 74 75 73 69 63 66 68 68 65 59 48 40 36 40 46 51 53 51 47 44 53 69 98 135 172 193 192 181 153 125 104 91 75 65 61 53 42 37 36 42 48 52 55 59 53 46 39 35 36 38 38 37 39 38 36 33 33 34 38 40 47 53 63 74 81 81 76 72 62 53 43 37 32 30 34 40 46 50 54 57 59 61 63 65 56 54 49 41 35 38 47 55 62 66 66 59 48 41 43 47 56 58 62 63 53 36 26 24 25 28 33 40 46 49 47 45 44 40 35 32 31 32 32 32 32 31 30 29 29 29 29 29 26 25 23 20 18 20 25 30 41 43 46 46 42 36 28 24 20 21 24 28 31 34 36 36 36 36 35 37 40 42 42 41 38 35 30 28 30 32 34 35 34 30 26 24 24 26 27 27 27 27 25 21 19 21 27 32 37 37 35 32 27 22 18 15 15 15 16 18 20 23 25 26 30 32 34 34 32 29 24 22 24 24 25 27 30 32 34 35 33 32 31 28 27 25 24 24 24 23 22 20 19 18 17 17 17 19 22 25 28 30 31 32 31 32 32 32 31 31 30 29 29 29 30 30 29 29 28 27 25 24 21 18 17 17 18 18 15 15 14 14 14 13 13 13 9 9 10 11 10 9 8 7 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 7 7 7 7 7 7 7 7 8 8 8 8 8 8 8 8 11 11 11 11 11 11 11 11 10 10 11 12 12 13 14 14 13 13 11 10 10 9 10 10 12 13 14 16 19 21 22 23 21 22 22 21 21 23 28 31 35 39 44 49 50 49 46 44 40 40 39 39 38 35 30 26 22 22 23 26 31 38 44 48 55 59 64 66 62 54 44 37 31 31 34 42 53 61 64 64 60 52 45 40 35 32 37 44 55 65 77 86 91 91 82 71 60 51 44 46 51 55 60 65 65 64 64 65 68 74 79 82 86 86 87 89 93 97 100 103 97 88 79 70 61 54 55 60 69 75 84 92 97 97 94 92 82 74 68 65 61 53 49 49 45 44 41 36 31 29 30 32 43 56 71 81 87 90 88 83 75 73 71 69 64 57 49 43 44 48 54 58 57 52 45 40 54 78 117 163 204 227 225 214 184 155 132 117 100 89 79 65 49 43 39 44 50 52 54 57 50 45 39 38 41 44 45 44 45 43 39 37 36 37 39 41 46 52 61 72 80 82 79 76 67 56 44 36 31 28 32 39 47 52 58 62 64 64 65 66 58 55 48 40 34 35 42 49 55 59 60 55 47 45 50 56 69 72 76 75 63 44 32 27 27 29 33 39 44 46 44 42 40 37 34 32 33 33 33 32 30 29 28 26 25 24 24 24 22 21 20 17 16 17 21 25 33 34 36 36 34 29 24 20 21 23 27 31 35 39 41 42 43 42 41 41 43 44 43 41 38 35 31 30 32 35 37 37 35 32 27 24 24 25 26 26 24 24 23 21 21 24 30 34 37 35 32 27 23 19 16 15 16 16 17 20 22 25 28 29 34 34 35 34 32 28 24 22 23 24 26 28 31 34 36 37 34 34 33 31 30 29 28 27 27 26 24 23 22 21 21 21 21 22 25 28 31 33 34 35 33 33 33 33 32 32 32 31 30 30 31 31 31 30 29 29 24 22 20 18 17 17 18 18 17 17 16 16 16 15 15 15 10 11 11 11 10 9 8 8 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 8 8 8 8 8 8 8 8 9 9 9 9 9 9 9 9 10 10 10 10 10 10 10 10 10 10 11 12 12 13 14 14 14 14 13 11 10 10 9 9 11 12 14 16 18 21 22 23 21 21 22 21 21 23 27 30 34 38 44 49 52 51 49 47 42 41 39 39 37 34 30 26 23 22 23 24 28 33 38 41 49 53 58 60 57 49 39 33 30 30 32 40 50 57 60 59 53 47 42 39 37 36 42 50 60 72 85 94 99 96 85 73 58 47 38 38 43 48 55 62 61 61 61 62 65 69 73 75 78 79 80 83 87 91 95 98 92 83 72 63 54 49 51 58 67 75 87 98 103 103 99 95 84 75 67 62 57 50 46 47 45 44 41 36 32 30 31 32 45 59 76 88 96 100 97 91 88 82 75 71 65 57 51 48 49 55 62 67 65 58 49 42 55 83 127 177 219 241 237 224 201 175 154 140 126 116 102 82 64 54 48 49 52 52 51 52 45 43 42 45 52 57 58 57 52 48 44 41 40 41 42 42 48 52 60 70 77 80 78 75 67 56 43 35 30 28 33 40 46 51 58 63 64 64 63 63 59 55 48 40 34 35 40 45 50 53 55 52 47 49 58 67 84 88 92 88 73 53 37 29 26 28 32 38 43 45 44 43 36 34 32 32 33 34 33 32 30 29 27 25 24 22 22 22 22 21 20 17 16 17 19 20 24 25 26 27 26 24 21 20 22 24 28 33 38 42 45 47 48 46 44 44 44 44 42 40 36 33 30 30 32 35 37 38 36 32 27 24 23 24 24 24 22 21 21 20 22 26 32 35 36 33 28 22 18 16 15 15 17 17 19 21 24 28 31 32 36 36 35 33 30 26 23 21 21 23 26 29 32 35 37 38 36 36 36 35 34 33 32 31 29 28 26 24 23 23 24 24 25 26 28 31 33 35 36 37 35 35 34 33 33 33 33 33 33 33 33 32 31 29 28 27 22 21 20 19 18 18 19 19 18 18 17 17 17 16 16 16 12 12 12 11 11 10 9 8 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 8 8 8 8 8 8 8 8 9 9 9 9 9 9 9 9 10 10 10 10 10 10 10 10 10 10 11 12 12 13 14 14 15 15 14 13 12 11 10 9 11 12 14 16 18 20 21 22 20 21 22 22 21 22 25 28 33 37 43 49 51 51 49 48 43 41 39 38 37 34 30 27 23 23 23 23 26 29 32 34 41 45 50 53 51 45 37 32 29 28 29 35 43 49 50 49 45 40 38 38 38 40 48 56 66 78 92 102 106 102 89 76 58 46 34 33 37 42 50 58 56 56 57 58 60 63 65 67 71 72 73 75 79 83 87 89 84 75 65 56 48 44 47 54 65 74 88 100 106 104 98 94 83 73 63 57 51 45 43 45 46 46 44 40 36 33 33 34 46 60 78 93 105 111 108 101 99 88 79 73 67 58 53 54 57 64 73 78 75 65 53 45 59 87 130 178 217 237 233 221 200 180 166 158 148 141 126 103 81 69 57 55 54 51 47 46 40 41 46 56 66 72 73 71 58 54 48 45 45 46 46 45 51 54 59 66 72 74 73 71 63 53 41 34 29 29 35 42 45 51 58 63 64 62 60 60 57 53 46 39 35 36 40 44 48 51 52 49 46 51 64 75 98 105 109 102 84 63 43 32 24 27 32 39 45 47 47 45 34 33 31 31 33 34 33 32 32 31 29 26 24 23 22 22 24 22 20 19 18 18 18 17 19 19 20 21 21 21 21 21 21 24 28 34 39 44 47 49 50 48 45 44 43 41 38 36 30 28 26 27 30 34 35 36 35 31 25 22 22 23 23 23 22 21 20 20 24 28 32 34 34 30 24 19 15 14 15 16 18 18 20 22 25 29 32 33 36 35 33 30 27 24 22 20 20 22 26 30 34 38 39 40 39 40 40 40 39 37 35 34 30 29 27 25 24 25 26 27 30 30 31 32 34 35 36 37 35 34 33 32 32 32 33 33 35 35 34 32 29 27 24 23 21 21 20 20 20 20 20 20 18 18 18 17 17 17 16 16 14 14 13 12 11 10 10 9 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 5 5 5 5 5 5 5 5 7 7 7 7 7 7 7 7 9 9 9 9 9 9 9 9 10 10 10 10 10 10 10 10 11 11 11 11 11 11 11 11 10 10 11 12 12 13 14 14 15 15 16 16 15 14 12 12 12 13 14 16 17 19 20 20 20 21 22 22 21 22 24 27 31 35 41 47 50 50 48 46 42 40 38 37 36 34 31 28 25 24 23 23 24 25 27 28 34 37 42 45 45 42 38 35 29 27 27 30 36 40 39 37 37 34 33 36 39 43 52 61 72 84 98 108 112 108 95 82 61 48 35 31 34 38 46 53 52 53 54 55 57 58 59 60 65 65 66 67 70 73 77 79 73 65 55 48 42 38 42 49 61 71 85 98 104 102 96 91 79 68 57 50 45 41 41 44 46 47 48 45 41 37 36 36 44 59 78 95 111 120 119 113 104 90 79 74 67 58 55 59 67 75 84 89 85 73 58 47 63 87 124 164 199 219 218 208 187 176 171 169 162 157 142 118 94 79 64 58 56 49 43 39 36 41 52 66 79 86 84 81 63 58 51 49 50 51 50 48 52 53 56 61 66 68 68 66 59 49 38 33 30 29 35 42 47 52 58 61 61 59 57 56 52 47 41 36 35 37 41 45 49 51 50 46 43 49 64 77 105 114 118 110 92 71 49 35 25 28 34 42 48 50 48 46 35 32 30 29 31 33 33 33 33 32 30 28 26 25 24 24 24 23 21 22 23 23 22 20 22 21 20 19 19 20 21 21 20 23 27 33 38 43 46 48 49 46 43 40 39 37 33 31 25 23 22 24 28 31 33 33 32 28 23 20 20 22 22 22 23 21 20 21 24 28 31 31 30 27 22 17 14 14 16 17 19 20 21 23 26 29 31 33 34 33 30 26 23 21 19 19 21 24 28 34 38 42 44 44 43 44 44 44 42 40 38 36 33 31 29 27 26 27 29 30 34 33 33 32 33 33 34 35 34 33 31 30 29 30 31 32 34 33 32 30 27 24 22 20 21 21 21 22 22 22 22 22 19 19 19 18 18 18 17 17 16 15 13 12 11 10 10 10 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 5 5 5 5 5 5 5 5 7 7 7 7 7 7 7 7 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 11 11 11 11 11 11 11 11 10 10 11 12 12 13 14 14 15 16 17 18 17 16 15 14 14 14 15 16 17 17 18 18 19 21 22 22 21 22 24 25 29 33 39 45 47 47 45 43 41 39 37 36 36 35 32 30 27 26 24 23 23 23 24 24 28 31 35 39 41 41 40 39 34 31 29 31 34 35 33 30 30 28 29 35 39 45 54 64 76 88 102 112 116 112 100 87 66 52 38 32 33 36 42 49 50 51 53 54 56 56 56 55 58 58 57 58 59 61 64 65 61 54 46 41 35 32 36 43 51 61 76 90 97 96 91 86 74 63 51 44 40 37 39 43 45 48 50 49 45 40 37 36 44 57 75 93 110 121 120 114 103 88 77 73 67 56 55 60 71 80 91 98 95 82 66 55 60 78 106 136 165 183 185 179 169 165 169 171 164 160 145 120 100 83 66 59 55 48 40 35 35 43 57 75 89 94 90 84 67 61 54 51 53 55 54 51 50 50 52 56 61 64 64 64 56 47 37 33 29 28 33 39 46 50 54 56 55 52 50 50 44 40 34 32 33 37 42 45 50 51 48 42 38 45 61 74 98 109 116 109 92 72 51 35 27 31 39 47 52 52 48 44 36 33 29 27 29 31 33 33 33 32 30 28 27 26 26 25 26 25 26 29 33 35 34 32 30 28 25 21 19 18 19 19 18 21 25 31 36 40 43 45 45 42 39 36 34 32 28 26 21 20 20 22 26 30 32 32 29 25 21 18 19 21 21 21 26 23 20 21 25 28 29 28 27 24 20 16 15 15 17 19 20 21 22 23 25 28 30 32 31 29 26 22 19 18 18 18 24 27 33 39 44 47 49 50 47 47 48 47 45 42 39 37 36 34 31 29 29 30 32 34 36 35 33 32 31 31 31 32 32 31 29 27 27 28 29 30 29 28 28 27 25 23 21 20 21 22 23 24 24 24 24 24 21 21 21 20 20 20 19 19 17 16 14 12 11 10 11 11 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 5 5 5 5 5 5 5 5 7 7 7 7 7 7 7 7 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 12 12 12 12 12 12 12 12 10 10 11 12 12 13 14 14 15 16 18 19 19 18 17 16 15 15 15 16 16 17 17 17 19 21 22 22 21 22 23 25 28 32 38 43 46 45 43 41 41 39 37 36 36 35 33 31 28 27 25 24 22 22 22 22 25 28 31 36 39 41 42 43 41 37 34 34 36 36 33 29 27 25 27 34 39 45 56 66 79 91 104 113 118 115 103 91 69 55 40 34 33 35 41 46 50 51 53 55 56 55 55 54 51 51 50 49 50 52 53 55 53 46 40 35 31 28 32 39 42 52 67 82 90 90 86 82 71 59 47 41 37 35 38 43 44 48 51 51 47 42 37 35 45 57 73 90 106 116 115 108 101 86 74 72 65 55 54 61 69 79 93 102 101 90 74 64 54 67 87 110 134 150 153 148 155 156 165 168 161 156 141 116 101 84 66 58 54 47 38 34 35 44 61 80 93 96 90 84 68 62 55 53 55 57 56 53 48 48 49 53 58 62 63 63 55 46 37 33 29 27 31 36 43 46 49 50 48 46 44 44 38 34 30 28 31 37 42 45 51 50 46 39 35 41 57 71 88 101 109 103 88 70 49 32 30 35 42 50 55 53 47 42 37 33 28 26 27 30 32 33 32 31 30 28 27 26 26 26 30 30 31 37 43 46 46 44 38 34 29 23 19 17 17 17 17 20 24 29 34 38 41 43 42 39 36 33 31 29 25 22 19 18 19 21 26 30 32 32 27 23 19 17 18 20 21 21 27 24 21 22 25 27 27 26 24 22 19 16 15 16 18 20 21 21 22 23 25 27 29 30 29 27 23 19 17 16 16 17 26 30 36 42 48 51 53 54 49 49 50 49 47 43 39 37 38 36 33 31 31 33 35 37 38 36 34 31 29 29 29 29 31 30 27 25 25 26 28 29 24 24 25 25 24 23 22 22 22 22 23 25 25 26 25 25 23 23 23 22 22 22 21 21 18 17 14 12 11 10 11 11 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 7 7 8 8 8 7 8 10 11 12 11 10 9 10 11 11 12 12 11 11 10 12 12 13 13 14 15 16 16 14 13 12 11 11 11 11 12 14 15 17 19 20 20 20 19 21 20 18 16 15 15 16 16 17 18 20 22 23 23 23 22 27 29 33 36 38 38 38 37 36 36 37 37 36 36 35 34 32 30 27 24 22 21 21 21 24 28 32 35 37 39 42 44 47 46 45 42 38 34 30 28 28 26 27 34 41 47 56 64 76 87 100 110 115 115 105 94 71 56 40 33 32 33 38 43 47 48 49 51 54 53 50 48 48 45 43 43 44 46 46 45 43 39 34 29 27 29 31 34 38 47 56 64 75 85 84 76 71 57 44 37 31 29 35 45 45 50 55 56 51 45 41 39 41 53 68 83 97 107 108 103 86 79 70 63 59 58 58 58 65 79 96 103 101 94 80 69 59 59 66 82 99 112 123 132 137 149 160 164 159 146 127 111 87 74 61 56 52 44 34 29 34 43 60 78 90 91 84 77 61 58 56 56 57 56 52 49 46 44 42 45 51 55 57 56 55 47 38 32 27 23 25 30 37 42 46 45 45 46 43 38 37 29 23 25 29 34 42 49 56 51 47 43 35 32 43 57 75 84 94 93 80 61 45 37 35 38 44 51 57 56 51 45 34 30 26 24 26 29 31 32 29 28 26 25 25 26 27 28 32 37 44 51 56 57 55 54 46 40 31 23 19 17 16 16 14 16 21 26 30 33 35 36 34 33 32 30 29 27 25 25 21 20 21 23 26 28 27 26 24 21 17 16 19 23 26 27 30 27 23 22 23 24 25 25 20 19 18 17 17 19 20 21 21 20 20 20 21 23 25 27 26 23 19 16 15 16 17 19 29 33 39 46 50 53 54 54 53 51 47 44 41 41 41 41 35 34 32 31 32 35 39 41 39 37 33 29 26 24 23 22 26 26 25 24 23 22 21 20 21 22 23 24 25 26 26 25 23 24 24 25 27 29 31 32 29 27 24 24 24 25 23 22 20 17 14 12 12 13 12 11 9 8 7 6 6 6 6 7 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 7 7 8 8 8 8 9 10 11 12 11 10 10 10 11 12 12 12 12 11 10 12 12 13 14 15 15 16 16 14 14 13 12 11 11 11 11 12 14 16 19 20 21 21 21 22 20 18 17 15 15 16 16 17 18 20 21 22 22 22 21 25 27 30 33 34 35 34 33 34 35 36 38 38 37 36 35 33 31 29 26 24 23 23 23 23 26 30 33 36 40 45 48 49 49 48 46 42 36 31 28 26 24 26 33 40 46 54 62 73 83 96 104 110 109 100 89 69 55 40 34 33 34 38 43 47 47 49 52 55 55 53 51 45 41 37 35 36 38 39 39 39 36 32 29 28 29 31 33 34 42 50 58 69 80 81 75 71 58 45 37 32 30 35 43 47 52 56 57 52 45 40 38 38 49 63 76 89 97 97 92 79 73 65 59 57 57 57 58 68 81 96 105 106 99 84 70 51 49 52 65 80 93 106 116 129 140 152 154 147 133 113 96 79 67 56 53 51 43 35 30 36 44 59 74 84 85 78 71 58 56 55 55 55 53 48 44 34 33 35 40 48 55 58 59 56 48 39 34 29 24 26 30 36 43 49 51 52 54 50 45 39 30 23 24 29 35 43 51 57 54 51 46 37 32 38 49 58 67 76 76 66 51 39 33 36 39 46 53 58 57 51 46 34 30 26 24 25 27 28 29 26 25 23 23 24 27 29 31 39 44 51 59 63 64 62 60 50 43 34 26 21 18 16 15 16 18 21 25 28 30 32 32 33 32 30 28 26 25 24 24 22 22 22 24 27 29 28 26 23 20 17 18 22 26 30 31 33 29 25 22 23 23 24 23 21 20 19 19 19 20 22 23 19 19 19 19 21 23 25 26 25 22 19 16 16 17 19 21 31 35 41 48 52 54 53 52 49 47 43 40 38 38 38 39 35 34 33 32 33 35 38 40 39 37 33 28 25 22 21 21 24 24 23 22 22 21 20 20 20 21 22 24 25 26 27 27 24 24 25 26 28 30 31 33 31 28 26 25 25 25 24 23 21 18 14 12 12 12 11 10 9 8 7 6 6 6 6 7 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 7 7 8 8 8 8 9 10 11 11 11 11 10 11 11 12 13 13 12 11 11 13 13 14 14 15 16 17 17 16 15 14 13 12 12 11 11 11 12 15 18 20 22 23 23 22 21 20 18 17 16 16 16 16 17 18 20 20 21 20 20 23 25 27 29 30 29 29 28 30 33 36 39 41 40 39 37 35 34 31 28 26 25 24 25 21 23 26 30 34 39 46 51 52 52 52 50 45 38 31 27 23 21 23 31 38 43 51 58 67 77 88 95 99 98 90 80 64 51 39 35 34 35 38 43 45 46 47 51 55 57 56 54 44 39 33 29 29 31 32 33 34 33 31 29 29 29 31 31 31 36 43 50 61 72 77 76 74 64 52 43 37 35 38 44 50 54 58 58 53 46 39 35 35 45 57 68 79 86 85 79 69 64 59 55 55 56 57 57 69 80 94 103 107 102 86 70 52 46 44 53 66 81 97 109 128 139 149 149 140 123 100 82 66 56 48 48 47 42 36 33 38 45 56 68 75 74 69 63 54 53 54 54 53 48 42 37 27 28 31 38 47 55 60 62 59 50 42 37 32 27 27 31 34 43 53 58 62 65 61 55 45 35 27 26 30 36 45 53 60 60 58 53 43 34 33 38 41 47 54 55 49 41 34 32 37 41 47 54 58 57 51 46 34 31 27 26 26 27 26 26 22 21 20 21 24 29 34 38 47 51 58 65 68 67 65 63 51 44 35 27 22 19 16 14 18 19 21 24 26 27 28 28 31 29 27 24 23 22 23 23 23 22 23 25 28 29 28 26 20 19 18 21 26 31 35 37 37 32 27 23 22 22 22 21 21 21 21 20 21 22 23 24 17 17 17 18 20 23 25 26 23 22 19 17 17 19 22 24 33 38 44 51 54 53 51 49 41 39 37 34 33 33 34 35 35 35 34 33 34 35 37 39 37 35 31 26 23 20 19 18 22 21 21 20 20 19 18 18 19 20 21 23 25 27 28 29 26 26 26 27 29 31 33 34 33 30 28 26 27 26 25 23 22 19 15 12 12 11 10 8 9 8 7 6 6 6 6 7 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 7 7 8 8 8 9 9 10 10 11 11 11 11 12 12 13 13 13 13 12 12 14 14 14 15 16 17 17 18 17 17 16 16 15 13 12 11 11 12 14 17 20 22 24 25 23 22 21 20 18 17 17 16 16 17 17 18 19 19 19 19 23 23 25 26 26 26 25 24 27 31 36 41 44 45 43 42 39 37 33 30 27 26 25 25 22 23 24 26 30 36 44 49 52 53 53 51 46 38 30 25 21 19 21 29 35 40 47 54 60 68 77 82 85 85 77 67 56 45 35 33 34 34 36 40 41 41 44 49 54 57 58 57 48 42 34 28 27 29 32 33 32 32 32 31 31 31 31 31 30 33 38 45 55 66 75 78 80 73 63 54 48 45 46 48 53 56 58 58 53 46 38 33 33 42 53 62 72 78 76 70 60 56 53 52 54 56 58 58 65 75 87 98 104 100 84 67 54 46 42 49 62 79 97 112 130 140 148 145 134 114 90 71 53 45 40 42 43 40 36 36 41 46 54 62 66 65 60 57 51 52 52 52 48 42 35 30 28 30 35 43 51 58 63 65 62 54 47 42 36 30 29 32 33 45 58 67 74 77 74 68 58 46 36 33 34 39 47 56 65 67 68 63 52 40 34 33 33 37 40 40 37 34 33 33 36 40 46 52 55 53 48 44 36 33 31 30 30 29 27 24 21 20 19 21 26 34 42 47 53 56 61 64 65 62 58 55 44 39 31 25 21 19 17 16 19 20 21 23 24 26 27 27 29 27 24 22 20 20 21 22 22 21 22 24 26 27 26 24 19 18 20 24 31 37 41 42 40 35 28 23 21 20 20 19 20 20 20 21 21 22 23 24 15 16 17 19 21 23 24 25 23 21 19 18 19 21 24 27 35 40 46 52 53 51 47 43 33 31 29 27 27 28 29 31 35 35 34 34 34 35 35 36 35 32 28 24 20 17 16 16 18 18 18 18 18 17 17 17 18 19 20 22 25 27 30 31 28 28 28 29 31 33 35 36 35 33 30 28 28 27 25 24 23 19 15 12 11 10 8 7 9 8 7 6 6 6 6 7 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 7 7 8 8 8 9 9 9 9 10 10 11 11 13 13 14 14 14 14 13 13 14 15 15 16 17 18 18 18 18 19 19 19 18 16 15 14 13 13 15 17 19 21 23 24 22 22 22 21 21 20 19 18 17 17 17 17 17 18 18 19 22 23 23 24 24 23 23 23 26 30 36 43 48 49 49 48 44 41 37 33 30 27 26 26 24 24 24 24 26 32 39 45 51 51 51 49 43 35 27 22 20 18 20 27 33 36 42 48 53 59 65 68 70 70 63 54 46 37 30 31 33 33 33 36 35 36 39 45 52 57 59 60 52 46 37 31 30 33 36 37 36 36 36 36 35 35 34 33 33 33 37 44 53 64 75 82 84 81 75 67 60 56 54 51 56 56 57 56 52 45 37 32 29 38 47 56 64 70 68 62 53 51 50 50 54 57 58 58 62 71 82 92 99 97 82 67 52 44 39 46 59 77 96 111 126 135 141 136 123 104 79 61 45 38 34 36 38 37 36 38 43 48 54 59 61 59 56 55 51 52 52 49 43 36 30 26 29 34 42 51 59 64 68 70 66 59 53 48 42 34 32 34 37 50 66 78 87 92 88 82 72 60 48 42 42 44 51 58 69 74 77 73 63 52 42 37 35 35 33 31 30 29 31 32 33 37 42 46 47 46 43 41 38 37 36 36 35 33 29 26 22 21 22 25 31 40 49 54 59 60 60 59 56 52 47 44 33 29 24 21 20 20 20 19 21 22 22 23 24 26 27 28 27 25 23 21 20 20 20 21 20 20 20 22 24 25 23 22 18 19 22 28 35 41 44 45 40 35 27 21 19 19 19 18 18 18 19 20 21 22 22 23 17 17 19 21 23 24 25 25 23 21 19 19 20 23 27 29 36 40 46 50 50 46 40 36 25 24 22 21 22 24 26 28 33 34 34 34 34 33 33 32 30 28 25 21 17 15 14 14 15 16 16 16 16 16 17 17 18 18 20 21 24 28 30 32 30 30 30 31 33 35 37 38 37 35 31 29 28 27 25 23 22 19 15 12 11 10 8 6 9 8 7 6 6 6 6 7 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 7 7 8 8 8 10 9 9 9 9 10 11 12 13 14 15 15 15 15 14 13 15 15 16 17 18 18 19 19 19 20 21 22 22 20 19 17 16 16 16 17 18 19 21 22 21 21 22 23 23 22 21 21 19 18 17 17 17 18 18 19 21 21 21 21 22 22 22 22 26 30 37 44 50 54 56 56 51 49 44 38 34 30 28 27 27 27 26 26 27 31 37 42 49 49 48 45 40 32 25 21 21 19 21 27 31 33 37 43 46 51 55 56 57 56 50 41 38 31 27 29 33 32 32 33 31 32 35 42 51 58 61 63 56 51 43 38 38 41 44 45 46 45 44 42 40 39 38 37 37 36 39 46 54 63 75 86 86 88 87 80 74 69 63 56 58 56 54 52 49 44 37 32 28 36 44 50 58 63 60 54 49 48 47 50 53 56 57 57 59 67 78 86 92 92 81 70 53 46 42 49 61 76 92 105 117 125 130 126 114 97 76 59 42 35 30 31 33 33 36 40 44 49 55 60 60 59 57 57 55 54 51 45 38 31 27 26 29 38 50 61 68 72 75 76 71 65 59 54 48 39 35 37 43 56 73 86 96 102 99 93 82 70 57 52 50 50 55 62 71 78 82 79 72 65 55 47 39 36 31 27 25 26 28 30 31 34 38 39 39 38 38 39 40 39 40 41 41 38 32 28 23 24 25 29 36 45 53 58 62 60 57 52 46 41 36 34 24 22 19 19 21 24 25 26 27 27 26 25 25 26 27 27 25 25 24 24 23 22 21 20 20 19 19 20 22 23 22 20 19 20 24 30 38 43 45 45 38 32 25 19 17 18 19 19 17 18 19 21 22 22 22 22 20 21 23 24 25 26 26 26 24 22 21 20 21 24 28 30 36 39 43 45 43 39 33 29 20 19 18 17 19 21 24 26 32 32 33 34 33 32 30 28 26 24 21 17 15 14 13 13 14 14 14 15 15 16 17 17 19 19 20 21 24 27 30 32 32 32 32 33 35 37 39 40 38 36 32 29 28 27 24 22 21 18 14 11 10 10 8 7 9 8 7 6 6 6 6 7 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 7 7 8 8 8 10 10 9 8 9 10 11 12 14 14 15 16 16 15 14 14 16 16 17 17 18 19 20 20 20 21 23 25 25 24 23 21 20 19 18 17 17 17 18 19 19 20 22 24 24 24 24 23 20 19 18 17 17 18 19 20 19 18 18 19 19 20 21 22 27 31 37 45 52 58 61 63 60 57 51 45 39 34 32 30 29 29 30 29 30 33 39 43 48 47 46 42 37 31 25 21 23 20 22 27 30 31 34 39 40 44 46 46 46 46 40 32 33 27 25 30 34 33 31 32 29 30 34 42 51 60 64 66 63 58 52 49 49 53 56 57 57 55 52 48 45 43 42 41 41 39 41 49 55 63 76 89 92 98 101 96 91 85 74 64 59 55 51 48 46 43 37 33 33 39 46 50 56 59 56 49 46 45 46 48 52 54 54 53 53 63 73 79 83 84 78 70 58 51 48 54 63 72 82 92 99 107 113 111 103 91 74 60 43 36 29 29 29 30 35 41 44 50 57 62 63 62 61 62 60 57 51 42 33 27 27 28 38 49 63 75 80 81 80 80 75 69 64 60 53 43 39 39 43 57 73 86 97 103 101 96 85 74 63 58 56 56 60 66 70 78 84 82 79 75 68 59 44 39 31 26 24 25 28 30 31 33 35 34 32 32 35 38 39 40 42 44 44 40 34 29 24 25 28 33 40 48 55 59 60 56 49 42 35 30 27 26 22 20 19 21 25 29 32 32 36 34 31 28 26 25 25 25 24 25 26 27 26 24 22 20 20 20 19 21 23 23 22 20 20 22 26 32 39 43 44 44 35 29 22 17 16 17 19 20 17 18 20 22 24 24 24 24 24 25 26 28 28 28 27 27 25 24 22 21 22 25 28 31 36 37 39 39 36 31 26 23 16 15 15 15 17 20 24 26 30 31 32 33 32 30 27 25 22 20 17 15 13 13 13 13 13 13 14 14 15 16 17 17 20 20 20 21 23 26 30 32 33 33 34 35 36 38 40 41 39 36 32 29 28 26 23 21 19 16 13 11 10 10 9 8 9 8 7 6 6 6 6 7 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 7 7 8 8 8 11 10 9 8 9 10 12 13 14 15 15 16 16 15 15 14 16 16 17 18 19 19 20 20 20 22 24 26 27 27 25 24 23 21 19 17 16 16 16 17 18 20 22 24 25 26 25 25 21 20 19 18 17 18 19 20 16 16 16 17 18 19 20 21 28 32 38 45 53 60 65 67 66 63 57 49 43 38 34 33 30 31 32 32 34 37 42 46 47 46 44 41 36 30 26 23 24 22 23 27 30 30 32 36 37 41 42 41 40 40 34 27 31 26 25 31 35 34 32 32 28 30 34 42 52 61 67 69 70 65 60 58 60 63 66 67 64 61 57 52 48 45 44 43 43 40 43 51 56 62 75 89 98 107 112 108 103 97 85 72 59 55 49 46 44 42 38 34 40 45 51 54 57 59 55 48 44 43 44 47 50 52 52 50 47 57 68 73 75 76 73 68 58 52 49 53 59 63 70 76 80 88 95 95 90 81 68 56 45 37 29 27 27 29 35 42 43 50 59 64 65 64 64 65 63 60 52 40 30 26 27 30 50 61 76 87 89 86 82 80 78 72 67 63 55 46 40 41 40 53 69 82 92 99 98 93 84 74 64 61 60 60 64 69 68 77 83 82 81 81 75 67 48 42 34 27 26 28 31 33 31 33 33 31 29 30 34 38 38 39 42 45 45 41 35 30 24 26 29 34 41 48 54 58 55 50 42 33 26 22 21 20 23 22 22 24 29 33 36 37 42 40 35 31 27 24 23 22 24 25 28 29 28 26 22 20 22 21 21 22 24 24 22 21 21 23 27 33 40 43 43 42 32 27 20 15 15 17 20 21 18 19 22 24 25 26 25 25 27 28 29 30 30 29 28 27 26 24 22 21 22 25 28 31 35 36 36 35 32 27 22 19 14 14 13 14 16 20 24 26 28 30 32 33 31 28 25 23 19 18 16 14 13 12 13 14 12 13 13 14 16 17 17 18 21 21 20 21 23 26 29 31 34 34 34 36 37 39 41 42 39 36 32 29 27 25 23 20 18 15 12 10 10 11 10 9 9 8 7 6 6 6 6 7 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 6 6 6 7 7 8 8 8 8 8 8 9 9 10 10 10 14 14 13 13 13 14 15 16 17 17 17 18 18 19 19 19 23 25 27 28 29 29 29 28 26 25 23 20 18 16 16 15 15 17 20 24 26 27 28 28 27 25 24 22 20 19 19 19 17 17 17 17 18 19 20 21 27 29 33 40 49 59 68 72 71 68 62 53 44 38 36 36 34 36 39 40 40 41 44 46 49 48 46 42 37 32 27 24 25 27 29 31 33 33 33 33 31 32 33 35 36 35 33 30 29 28 29 33 33 30 31 35 33 34 39 49 58 63 66 69 65 65 66 67 68 70 73 76 69 66 62 56 51 46 43 41 37 42 47 50 54 62 73 83 97 111 120 116 110 104 87 68 56 49 40 37 38 42 43 44 49 50 53 58 63 61 55 50 45 42 41 45 50 51 48 43 43 55 60 62 80 102 94 70 68 63 58 58 59 58 53 48 56 60 66 71 72 69 65 62 50 44 35 31 31 33 34 34 44 48 55 62 67 70 71 72 66 61 51 38 28 27 36 44 63 71 82 90 91 88 83 80 75 76 73 65 56 50 41 33 38 46 59 73 82 87 86 85 75 71 65 62 61 62 62 61 67 69 75 80 83 81 75 70 56 44 31 27 26 27 31 36 39 39 38 35 32 31 33 35 38 40 43 44 42 38 32 29 28 30 34 39 42 45 46 47 43 37 29 23 23 25 28 29 30 30 31 34 37 41 45 48 49 48 45 39 31 25 22 21 26 28 31 33 34 33 30 29 26 24 24 24 25 24 22 20 18 21 26 34 41 43 42 41 31 27 22 20 19 20 20 20 23 23 23 26 29 31 30 29 33 33 33 32 30 27 24 22 22 22 21 23 26 29 30 30 38 38 36 33 29 23 18 15 11 12 14 16 19 20 21 22 30 30 31 31 29 26 22 20 13 13 12 11 11 11 12 12 15 15 15 16 17 18 19 20 22 23 23 23 22 24 27 30 33 34 36 38 40 41 41 42 37 35 32 29 27 23 19 15 16 15 12 10 9 10 11 12 9 9 9 8 8 7 7 7 5 5 5 5 5 5 5 5 5 5 5 4 4 3 3 3 5 5 5 4 4 3 3 3 4 4 4 3 3 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 6 6 7 7 7 8 8 8 8 8 8 9 9 9 10 10 13 13 13 13 13 14 15 16 17 17 18 18 19 20 20 20 22 23 25 27 28 28 28 28 27 25 23 21 19 17 16 16 15 16 19 22 25 26 27 27 26 25 24 23 21 20 19 19 17 17 16 16 16 18 19 20 26 28 33 40 49 59 67 72 72 69 62 53 44 38 36 37 37 40 43 46 46 48 50 52 55 54 52 48 43 37 32 29 29 30 32 34 34 33 32 31 29 30 31 33 35 35 34 32 34 31 31 33 31 29 31 37 45 48 55 63 68 69 67 65 64 65 67 68 69 71 73 75 70 68 63 57 51 47 43 42 39 43 48 51 54 61 71 79 95 109 119 116 110 102 84 65 49 43 37 36 40 46 50 51 59 59 61 64 67 64 56 50 43 41 40 42 47 48 45 41 44 53 58 62 77 93 89 72 72 67 63 61 61 57 50 44 44 48 54 59 62 62 61 59 53 47 40 35 34 34 33 32 43 47 53 61 67 71 73 74 68 63 52 39 29 30 38 46 64 71 81 87 88 84 79 76 72 75 74 66 59 52 43 34 34 41 53 66 76 80 80 78 71 67 61 58 57 58 58 58 59 61 67 73 78 78 75 72 58 46 33 28 27 29 34 40 44 44 43 41 37 34 34 35 37 39 42 43 41 36 31 28 24 26 30 34 37 38 39 39 36 32 26 24 26 30 33 35 40 39 39 40 43 48 53 56 55 54 51 44 36 30 26 25 28 31 35 38 38 37 34 31 29 27 26 26 27 27 25 23 19 21 26 33 38 41 40 38 32 29 24 22 23 24 24 24 26 25 26 28 31 33 33 32 33 33 32 30 28 25 23 21 22 23 24 27 30 31 32 31 37 37 36 34 29 24 18 15 14 15 17 19 20 21 22 23 29 29 30 30 28 24 21 19 13 12 12 11 11 12 12 13 16 16 16 16 17 18 19 20 21 22 23 22 22 23 27 30 32 34 36 38 40 42 42 42 37 34 31 28 26 23 19 15 16 15 12 10 9 10 11 12 9 9 9 8 8 7 7 7 5 5 5 5 5 5 5 5 5 5 5 4 4 3 3 3 5 5 5 4 4 3 3 3 4 4 4 3 3 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 6 7 7 7 8 8 8 8 7 7 8 8 9 9 9 9 11 11 11 12 13 14 16 17 17 17 18 19 20 21 22 22 21 22 24 25 27 27 28 28 27 26 24 21 19 18 17 17 14 15 18 21 23 25 26 26 26 26 25 25 24 22 21 20 17 16 15 15 15 16 17 18 25 27 32 40 49 58 66 70 72 69 62 53 44 39 37 38 42 45 50 53 55 57 59 61 61 60 58 53 48 42 37 33 34 35 37 38 37 34 30 28 27 28 29 31 33 34 35 36 40 37 35 34 30 27 31 39 53 62 74 82 84 78 68 61 60 61 63 65 68 69 70 71 68 66 62 56 51 47 44 43 42 46 50 53 55 60 68 74 90 104 114 113 107 96 76 58 38 35 33 37 46 56 63 65 73 72 71 71 70 64 55 47 41 39 37 39 43 43 41 37 37 42 48 56 67 76 76 70 74 71 68 66 63 57 48 40 36 39 43 47 51 54 56 57 55 51 46 42 39 37 34 31 40 44 51 59 66 71 74 75 70 64 53 40 32 32 40 48 65 70 77 81 80 76 72 69 69 73 75 70 64 57 46 37 31 37 46 58 68 73 73 71 66 61 55 51 51 52 53 53 49 51 56 63 70 74 74 73 61 49 35 29 28 30 37 45 51 52 52 49 44 39 37 36 37 39 40 41 39 34 29 26 23 24 27 30 32 33 33 32 28 26 25 27 32 39 43 45 50 48 45 44 47 53 59 63 64 62 58 51 41 34 30 28 30 33 39 43 44 41 37 34 33 31 29 29 30 30 28 26 21 22 26 31 35 38 36 35 33 30 27 26 27 28 28 28 28 28 28 30 33 35 35 34 33 32 30 28 26 23 21 20 23 26 29 33 35 35 34 33 37 37 37 35 32 26 21 17 19 19 20 21 22 22 23 23 27 28 28 28 26 22 19 16 13 12 12 11 11 12 13 13 16 16 17 17 18 19 19 20 20 21 22 22 21 23 26 29 32 33 36 39 41 42 43 43 36 33 29 26 24 22 18 15 16 14 12 11 10 10 11 12 9 9 9 8 8 7 7 7 5 5 5 5 5 5 5 5 5 5 5 4 4 3 3 3 5 5 5 4 4 3 3 3 4 4 4 3 3 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 7 7 7 8 8 8 9 9 7 8 8 8 9 9 9 9 10 10 10 11 12 14 15 16 17 17 18 19 21 22 23 24 21 21 22 24 25 26 27 27 27 25 24 21 20 18 18 18 13 15 17 19 22 24 25 26 26 27 28 29 28 26 24 23 19 17 15 14 14 15 17 18 24 27 32 39 48 56 63 67 70 67 60 51 42 38 37 38 44 49 55 60 62 64 66 67 64 63 60 56 50 44 39 35 38 40 41 41 39 35 30 27 27 28 29 30 31 33 37 40 47 44 41 37 29 24 30 40 56 71 89 99 98 87 71 58 50 52 54 58 62 63 62 61 59 58 56 53 50 47 45 44 45 48 53 56 58 61 66 70 83 95 105 106 99 85 65 48 30 30 33 43 57 71 79 83 86 82 78 75 71 63 52 44 39 37 36 36 38 38 36 34 32 34 41 52 59 63 67 73 73 73 73 72 69 61 51 43 41 40 40 42 44 48 51 54 54 53 51 49 45 41 36 33 37 41 48 56 64 70 74 75 68 62 51 40 33 34 41 47 61 65 69 71 68 64 61 59 65 71 76 74 69 62 52 41 33 36 44 55 65 71 72 70 62 56 50 46 45 46 47 47 42 44 47 54 62 68 71 72 63 51 37 30 28 30 39 48 57 59 60 57 51 45 40 39 38 39 40 40 37 32 27 24 23 25 27 29 30 30 30 29 24 24 27 33 42 49 54 56 54 51 46 44 46 52 60 66 71 69 64 55 44 35 30 28 30 35 41 45 46 43 38 35 33 32 30 31 32 32 30 28 23 23 25 29 33 35 34 33 33 31 30 30 31 32 31 30 29 28 27 29 32 35 35 35 33 31 28 26 23 21 20 20 25 30 36 40 41 39 37 35 38 39 40 39 36 30 25 22 22 22 21 21 21 21 22 22 26 26 27 26 24 20 16 14 12 12 11 11 11 12 13 14 17 17 18 19 19 20 20 19 19 20 21 21 21 23 26 29 31 33 36 40 42 42 42 42 34 31 27 24 22 20 17 15 15 14 13 11 10 10 11 11 9 9 9 8 8 7 7 7 5 5 5 5 5 5 5 5 5 5 5 4 4 3 3 3 5 5 5 4 4 3 3 3 4 4 4 3 3 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 7 7 8 8 8 9 9 9 8 8 9 9 9 10 10 10 10 10 10 10 11 13 14 15 15 16 17 19 21 23 24 25 22 22 22 23 24 25 26 26 26 25 23 21 19 18 18 18 14 14 16 18 21 23 25 26 28 30 33 34 34 32 29 27 22 20 17 15 14 15 17 19 25 27 32 39 47 54 60 63 65 61 55 46 38 35 35 37 44 50 57 63 66 68 69 70 66 64 62 58 52 46 41 38 41 42 43 42 40 36 32 29 30 31 31 30 30 33 39 43 53 52 50 43 31 24 30 41 63 83 105 114 109 94 71 53 39 40 44 50 54 55 52 49 47 48 49 50 49 48 47 46 46 50 55 59 62 64 66 67 77 85 93 94 86 71 52 38 27 29 38 53 71 87 95 98 98 92 84 77 70 62 52 44 39 37 35 34 34 34 33 31 33 34 42 53 58 60 67 77 72 74 77 79 76 70 61 54 50 47 43 40 39 41 45 47 52 53 54 53 49 44 39 36 35 38 44 52 59 65 70 72 64 58 49 39 34 34 40 44 54 56 58 57 54 51 49 49 60 68 75 76 73 67 56 46 38 39 44 54 66 73 75 73 61 55 48 42 41 42 43 43 41 42 45 50 58 65 68 70 64 52 40 32 28 29 38 48 59 61 62 61 55 49 44 42 42 42 42 40 36 30 25 22 22 24 26 28 29 30 29 29 27 29 34 42 51 58 61 62 54 50 44 41 43 51 60 66 77 74 68 58 46 36 30 27 30 34 40 44 45 41 36 32 31 30 30 32 34 33 31 29 25 24 25 28 32 35 35 35 35 34 33 33 34 34 32 30 27 26 25 26 30 32 33 33 32 30 26 23 21 21 21 22 28 34 42 46 45 41 38 37 39 40 42 43 40 35 30 26 23 22 21 20 19 20 20 21 25 26 26 25 22 19 15 12 11 11 11 11 11 12 13 14 18 18 19 20 21 20 20 19 18 19 20 20 20 22 26 29 31 33 37 40 41 41 40 39 33 29 25 22 20 19 16 14 15 14 13 12 11 11 10 10 9 9 9 8 8 7 7 7 5 5 5 5 5 5 5 5 5 5 5 4 4 3 3 3 5 5 5 4 4 3 3 3 4 4 4 3 3 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 8 8 8 8 8 8 8 8 8 8 8 8 9 9 9 10 10 10 10 11 11 11 12 12 11 10 10 10 10 11 12 12 14 15 16 18 21 23 24 25 25 24 24 23 23 24 24 25 24 23 21 20 18 18 17 17 15 15 16 18 20 23 26 27 32 34 38 41 41 39 35 33 26 23 20 17 16 17 19 20 26 29 33 39 46 51 56 58 57 54 47 39 33 31 33 35 43 49 58 64 68 68 68 69 66 65 63 59 54 49 44 41 40 41 41 41 40 38 36 34 37 37 36 32 30 33 40 46 60 62 62 54 39 27 31 42 71 95 119 125 116 97 70 47 31 33 38 45 51 51 46 41 38 42 47 51 53 52 49 48 47 50 56 62 66 68 68 68 72 77 82 81 72 58 41 30 26 32 46 65 86 100 107 109 105 97 85 75 68 60 52 47 40 38 36 34 32 31 31 30 30 33 40 47 51 54 61 68 69 73 78 82 81 76 69 65 55 50 43 38 35 36 39 41 51 53 56 54 50 44 39 37 33 36 41 47 54 59 63 65 60 55 47 39 36 36 38 40 46 47 47 44 41 39 40 41 54 63 71 73 72 68 58 49 40 40 43 53 66 75 77 76 64 58 49 42 40 40 41 41 43 44 46 51 58 65 68 69 66 55 43 35 29 29 37 47 56 58 60 60 56 51 48 47 48 47 45 42 36 30 24 20 20 22 25 27 29 30 30 30 34 37 43 51 58 62 62 61 51 47 41 38 41 49 58 64 75 73 67 58 46 37 31 28 31 34 38 41 41 37 32 29 26 27 30 34 37 36 33 30 26 25 25 28 33 37 39 40 39 38 37 37 37 35 31 28 25 23 22 23 26 30 31 31 31 28 25 22 20 21 23 25 33 39 47 50 47 42 39 38 38 41 43 45 43 38 32 29 23 22 20 18 18 18 19 20 25 26 26 25 22 18 14 11 11 11 11 11 12 13 14 15 18 19 21 22 22 21 20 19 16 18 19 19 19 22 25 29 31 33 36 39 40 39 37 35 31 27 23 20 18 17 15 14 14 14 13 12 12 11 10 10 9 9 9 8 8 7 7 7 5 5 5 5 5 5 5 5 5 5 5 4 4 3 3 3 5 5 5 4 4 3 3 3 4 4 4 3 3 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 9 9 9 9 9 9 9 9 8 8 8 9 9 9 10 10 11 11 12 12 12 13 13 13 12 11 10 10 9 9 10 10 12 13 15 17 20 22 24 25 28 27 25 24 23 23 23 24 22 21 20 18 17 17 16 17 16 16 16 18 20 24 26 28 35 38 43 47 47 45 41 38 30 27 23 19 18 19 21 23 28 30 34 39 44 49 52 54 49 46 40 33 28 27 30 33 43 49 58 65 68 68 68 67 62 61 59 56 52 47 43 40 39 38 38 38 39 39 40 40 44 43 40 35 31 33 41 48 66 71 74 67 48 33 35 44 71 98 123 128 117 98 69 44 31 33 38 47 54 54 47 40 37 43 50 57 59 57 53 50 46 50 57 65 71 73 72 70 71 72 73 70 62 48 34 27 28 36 53 75 96 109 114 113 104 94 80 68 60 55 49 45 41 40 38 35 32 30 30 31 27 32 37 39 41 46 50 51 60 65 72 77 77 73 69 66 54 50 42 36 34 35 38 41 52 55 57 55 48 41 37 35 32 34 38 43 48 53 56 58 56 52 46 41 39 38 37 37 39 39 38 35 33 33 35 37 48 57 65 68 69 66 57 49 39 37 38 48 63 73 77 75 69 62 52 44 41 40 41 41 45 46 48 54 61 68 71 72 68 59 48 40 32 30 37 47 50 53 56 56 55 52 51 51 54 53 49 44 37 30 23 20 21 23 26 30 33 35 36 36 41 44 50 57 61 62 59 55 45 41 36 34 37 45 54 60 64 63 59 51 41 34 29 28 32 34 37 38 37 33 29 26 23 26 31 37 41 40 35 31 26 25 26 29 35 40 44 45 45 44 43 42 41 37 31 27 24 22 20 21 25 28 30 30 30 27 24 21 20 22 26 28 37 44 51 52 47 41 38 38 36 39 42 44 43 38 33 29 23 22 20 18 18 19 20 22 26 26 26 25 22 18 13 11 11 10 10 11 12 13 14 15 19 20 22 23 23 22 20 18 15 17 18 18 19 21 25 28 31 33 36 39 39 36 33 31 30 26 21 18 17 16 15 13 14 14 13 13 12 11 10 9 9 9 9 8 8 7 7 7 5 5 5 5 5 5 5 5 5 5 5 4 4 3 3 3 5 5 5 4 4 3 3 3 4 4 4 3 3 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 9 9 9 9 9 9 9 9 8 8 8 9 9 10 10 10 12 12 13 13 13 14 14 14 13 12 11 9 9 8 9 9 11 12 14 16 19 22 24 25 30 29 26 24 23 22 23 23 21 20 19 18 16 16 16 16 16 16 17 18 21 24 27 29 37 41 46 50 51 48 44 41 32 29 25 21 20 20 23 25 29 31 35 39 44 48 50 51 44 41 35 29 24 24 28 32 43 49 59 66 69 68 67 66 56 56 55 52 48 44 40 37 37 37 36 37 38 40 43 44 48 47 44 37 32 33 42 49 70 77 82 75 55 38 37 46 64 93 119 125 115 97 69 45 33 35 41 50 58 57 50 42 40 46 55 62 64 61 55 51 46 50 58 67 73 75 74 72 72 70 69 65 56 42 31 26 28 38 57 80 101 113 116 114 99 88 72 60 52 48 45 42 42 41 39 35 32 30 30 31 30 37 40 37 39 45 47 43 51 57 64 69 69 66 63 61 53 48 42 37 35 37 41 44 54 57 58 55 47 39 34 32 31 33 36 40 45 49 52 53 55 52 47 43 41 39 38 36 36 35 34 31 29 30 33 36 43 52 61 64 65 63 56 48 35 33 34 44 59 71 75 74 72 65 54 46 42 41 41 41 46 47 50 57 64 71 74 75 70 62 52 43 35 31 38 47 47 49 52 54 53 52 53 54 58 56 52 46 38 30 23 19 24 26 30 34 38 41 42 42 46 49 54 59 62 60 55 50 38 35 31 29 33 41 50 56 53 52 49 43 35 29 26 26 34 35 36 37 35 31 27 25 21 25 32 39 44 42 37 33 26 25 26 30 36 43 47 49 50 48 47 46 43 38 32 27 24 22 20 21 24 27 29 30 30 27 23 20 20 23 27 30 39 46 52 53 47 41 38 38 34 37 41 43 42 38 32 28 24 22 20 19 18 20 22 23 26 27 26 25 22 18 14 11 10 10 10 11 12 13 14 15 19 20 22 24 23 22 20 18 15 16 17 18 19 21 25 28 31 33 36 38 38 35 31 28 29 25 20 17 16 15 14 13 13 13 13 13 12 11 10 9 9 9 9 8 8 7 7 7 5 5 5 5 5 5 5 5 5 5 5 4 4 3 3 3 5 5 5 4 4 3 3 3 4 4 4 3 3 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 6 5 5 6 6 8 9 10 14 13 12 10 10 10 10 10 11 10 10 10 10 10 9 9 12 12 12 12 13 14 15 16 17 17 15 13 12 10 8 8 10 11 11 12 15 18 21 23 28 28 26 25 25 24 25 25 21 20 19 17 17 16 16 16 17 17 18 18 19 23 29 34 43 46 50 53 53 51 47 44 36 33 28 24 23 24 26 28 27 28 31 35 39 43 46 47 44 38 30 23 20 21 25 29 39 45 53 62 66 67 65 63 57 55 51 46 42 39 37 36 34 34 34 33 35 39 46 51 53 55 53 42 31 31 43 56 73 87 96 86 67 52 45 42 62 81 100 107 101 87 65 46 39 46 58 69 72 68 58 51 49 55 65 74 77 73 63 55 51 51 55 65 76 82 80 77 73 71 68 61 52 41 32 27 30 44 61 78 96 108 106 97 85 73 60 53 47 43 44 47 39 39 39 37 33 29 28 28 35 38 40 39 35 33 34 37 43 48 55 62 65 61 54 48 45 42 37 32 31 36 45 52 58 60 61 58 50 41 34 30 30 30 32 34 38 44 49 52 51 49 47 45 44 42 38 35 37 31 28 28 28 26 28 33 36 43 51 58 65 67 59 49 40 31 26 34 47 58 69 76 73 68 59 49 41 38 40 43 48 51 56 63 69 74 78 80 76 68 57 47 41 38 36 36 37 39 42 44 47 52 59 63 67 65 60 51 39 29 23 20 21 26 33 39 42 45 48 50 50 54 58 61 59 54 48 44 34 31 29 28 30 35 40 44 44 43 40 36 31 30 31 32 40 42 42 40 35 29 26 25 26 30 37 43 46 43 37 32 28 27 29 38 50 58 60 59 63 59 54 51 47 41 32 26 25 23 22 24 27 30 32 32 27 26 25 25 26 29 32 33 40 44 48 47 42 37 34 33 32 34 37 38 37 34 30 28 22 21 20 18 18 21 26 30 32 31 29 26 23 19 15 13 14 13 13 13 13 14 15 16 20 21 22 22 21 19 18 16 16 16 16 17 20 24 28 31 30 30 32 32 32 31 29 28 26 24 21 18 15 14 13 13 15 15 14 13 11 10 9 9 7 7 7 7 7 7 7 7 5 5 5 5 5 5 5 5 6 6 6 5 5 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 6 6 6 6 7 8 10 10 13 13 12 11 10 10 10 11 11 11 11 11 10 10 10 9 11 11 11 12 13 14 16 16 19 18 17 15 14 12 11 11 12 11 11 11 13 16 20 22 27 27 27 27 27 27 27 27 23 22 20 19 17 16 16 16 16 17 18 18 20 24 29 34 42 44 48 51 52 49 45 43 35 33 29 26 25 25 27 28 27 29 32 35 39 42 45 46 42 37 30 24 21 22 25 27 36 42 50 58 63 64 62 61 56 53 48 43 39 36 35 35 33 33 33 33 34 39 46 51 57 59 57 47 36 34 44 56 77 92 102 93 75 60 51 46 57 73 90 96 92 80 63 47 48 56 69 79 82 77 67 59 57 63 73 82 85 79 69 60 52 52 56 65 74 80 79 76 71 70 66 60 52 42 33 28 30 42 58 73 89 98 95 86 71 60 49 43 39 36 38 42 41 42 41 38 34 32 32 33 40 43 45 44 39 36 36 37 42 46 53 58 59 55 47 42 40 37 34 31 32 39 49 56 66 67 67 63 54 44 36 32 30 30 30 31 34 38 43 45 49 48 47 47 46 44 40 36 36 31 28 29 29 27 29 34 34 41 49 56 63 66 60 50 41 31 25 29 40 51 62 70 71 67 58 49 41 38 40 43 47 51 57 65 72 76 79 80 76 68 58 49 43 40 38 37 36 37 39 41 45 52 60 65 71 69 63 54 42 31 25 22 25 30 36 41 43 45 48 49 50 53 57 58 56 51 46 42 34 33 31 30 31 34 37 40 39 38 36 33 31 32 36 39 45 47 47 45 40 35 31 30 32 36 42 47 48 44 37 32 27 28 34 45 59 69 72 72 68 63 57 53 49 43 36 30 25 23 23 24 28 31 33 33 28 27 26 26 27 29 32 33 38 41 44 43 38 34 31 31 30 31 33 35 33 30 27 24 20 20 20 20 20 22 27 31 32 32 30 28 25 21 18 16 16 16 15 14 14 14 15 16 20 21 22 22 21 19 18 16 17 16 17 18 20 24 28 30 29 30 30 30 30 28 27 26 24 23 20 18 16 15 14 14 15 15 14 12 11 10 9 9 7 7 7 7 7 7 7 7 5 5 5 5 5 5 5 5 6 6 6 5 5 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 7 7 7 7 8 9 11 11 13 13 12 11 11 11 12 12 12 12 12 11 11 11 10 10 10 10 11 11 13 15 16 17 20 20 19 18 18 17 16 16 14 13 11 10 11 14 18 20 25 26 28 30 31 31 30 29 26 25 23 21 19 17 17 16 16 17 18 19 20 24 29 33 38 41 45 48 48 46 43 41 34 32 30 28 27 27 28 29 29 31 33 36 39 41 43 43 40 36 31 26 23 23 25 26 33 38 47 55 60 61 59 58 54 50 45 39 35 33 33 34 32 32 32 32 33 39 46 52 63 65 64 54 42 39 46 55 78 93 104 99 82 67 55 48 51 63 75 79 77 70 59 49 59 68 80 90 92 85 75 67 65 71 81 90 92 86 74 65 53 53 57 64 72 76 75 72 70 69 67 62 55 46 39 34 32 40 53 65 76 82 77 69 54 44 36 33 31 30 33 37 43 43 41 37 35 35 37 40 47 51 53 51 45 40 38 39 42 45 50 53 52 46 40 35 34 33 31 30 33 42 53 60 72 73 73 68 58 48 39 35 34 32 30 29 30 33 36 39 46 46 47 48 49 46 42 38 34 30 28 30 31 30 32 37 35 42 50 57 65 69 64 56 47 34 24 24 31 40 51 61 66 63 56 47 40 38 39 41 44 50 59 68 75 79 81 81 74 68 59 51 46 43 40 39 35 36 36 38 43 51 61 68 76 73 67 57 45 35 28 26 30 34 39 43 44 45 46 48 48 50 53 54 52 48 43 40 37 36 35 34 33 34 34 35 32 32 32 31 33 38 45 50 55 56 56 52 47 42 39 38 40 44 49 51 49 43 36 31 28 32 42 56 71 81 84 84 77 70 61 54 50 44 38 33 25 24 24 26 29 32 34 33 30 29 28 28 28 30 32 33 35 37 37 35 32 28 27 27 26 27 28 29 27 24 21 19 17 19 21 22 23 25 29 32 32 32 32 30 28 25 22 20 20 19 17 16 15 15 16 16 20 21 22 22 21 19 18 16 18 18 18 19 21 24 27 29 28 28 28 27 26 25 24 23 23 22 20 18 17 16 16 16 15 14 13 12 11 10 9 8 7 7 7 7 7 7 7 7 5 5 5 5 5 5 5 5 6 6 6 5 5 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 8 8 8 8 9 10 11 12 13 13 12 12 12 13 13 14 14 14 13 13 12 11 11 11 10 10 10 11 13 15 17 18 21 21 21 21 21 21 21 21 18 16 13 11 11 13 17 19 22 24 28 31 33 33 33 32 30 29 26 23 21 19 18 17 17 18 19 20 20 23 27 31 34 36 40 43 44 43 41 39 32 32 31 30 29 29 29 29 31 33 35 37 39 40 40 40 38 36 32 29 27 26 27 28 33 38 45 52 57 58 56 55 52 49 43 38 34 33 34 34 33 32 31 31 33 39 47 53 67 70 70 61 50 44 48 54 73 88 100 97 84 70 56 47 49 55 62 65 64 60 56 53 64 73 86 95 94 87 77 70 69 75 85 93 94 87 75 66 54 55 57 62 67 70 69 68 67 68 68 65 60 54 47 43 36 40 47 55 63 64 58 51 41 33 27 27 28 29 32 37 42 40 37 34 32 35 40 45 54 57 59 57 50 44 42 42 44 47 50 51 48 42 37 34 33 33 33 33 36 44 53 59 71 72 73 69 61 52 45 41 40 37 34 31 30 31 33 35 43 44 46 49 50 48 43 39 32 28 28 31 33 34 37 42 44 50 57 63 72 78 75 67 55 42 29 24 26 32 42 52 59 57 51 44 38 35 37 39 42 49 60 71 78 81 81 80 71 66 57 51 47 44 42 41 36 36 36 37 41 51 62 70 77 75 68 58 46 37 31 29 33 37 41 43 43 43 43 44 43 45 47 48 48 46 44 42 42 42 41 40 38 35 33 32 28 29 30 32 37 45 56 63 67 67 65 60 53 47 43 42 46 49 52 52 47 40 33 29 32 38 51 67 82 90 92 91 83 75 63 54 48 42 36 32 26 25 25 27 31 33 33 33 31 30 30 30 30 31 32 33 33 32 30 28 25 24 23 23 23 23 23 22 21 19 16 15 16 19 23 25 26 28 31 33 33 34 34 34 32 30 27 25 24 22 20 17 16 16 17 17 20 21 22 22 21 19 18 16 19 19 19 20 21 23 25 27 26 25 25 24 23 22 20 20 21 20 20 19 18 18 17 17 14 14 13 12 11 9 9 8 7 7 7 7 7 7 7 7 6 6 6 6 6 6 6 6 6 6 6 5 5 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 8 8 8 8 9 10 11 12 13 12 12 12 13 14 15 16 16 16 15 14 13 12 12 11 10 10 11 12 13 15 16 17 21 21 22 23 24 25 25 25 22 20 17 14 13 14 16 17 20 22 26 30 33 34 34 33 33 32 29 26 23 21 20 19 19 20 21 21 21 22 25 28 29 32 35 38 40 39 38 37 31 31 30 30 29 30 30 30 33 35 37 39 39 39 38 37 36 35 32 30 30 30 31 32 36 40 46 52 55 55 53 52 50 47 43 38 36 35 36 36 35 34 32 31 33 39 48 54 68 72 74 68 58 51 51 54 68 81 93 92 84 73 60 50 52 53 56 57 55 53 54 56 66 75 87 93 91 83 74 69 70 75 84 91 92 85 74 66 55 55 57 59 62 63 63 62 62 64 68 69 67 61 55 51 43 42 43 47 51 49 44 39 33 27 23 25 27 28 31 36 37 36 32 29 29 34 41 47 58 61 63 61 55 49 48 48 51 54 56 54 49 43 40 39 38 39 39 40 41 44 50 54 65 68 71 70 65 59 54 51 44 42 39 36 33 32 32 32 40 41 44 47 48 47 42 38 30 26 26 30 35 38 44 51 58 63 68 73 81 88 86 80 66 53 38 30 27 29 37 46 51 50 46 41 35 33 34 35 42 49 61 72 78 80 78 76 66 60 53 47 45 44 44 44 40 39 37 37 40 49 60 68 73 71 65 55 44 36 32 31 34 38 41 42 41 40 39 39 37 38 40 42 44 45 46 46 48 48 48 46 43 38 34 31 27 29 31 35 42 52 64 73 77 76 72 65 56 48 44 42 47 49 51 48 42 35 30 28 35 44 61 78 92 99 99 97 83 73 60 50 43 38 33 29 27 26 26 28 31 32 32 30 30 30 30 30 31 32 33 34 31 29 26 23 22 21 20 20 20 20 19 18 16 15 14 13 16 20 24 27 29 31 33 35 35 36 38 38 37 34 31 29 26 24 21 18 16 16 18 19 20 21 22 22 21 19 18 16 19 19 19 20 21 22 23 23 23 23 22 21 20 19 19 19 20 20 20 20 19 19 18 18 14 13 13 11 10 9 8 8 7 7 7 7 7 7 7 7 6 6 6 6 6 6 6 6 6 6 6 5 5 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 7 7 7 7 8 9 11 11 12 12 12 13 14 15 17 18 18 17 16 15 14 13 12 12 12 12 12 12 13 14 15 16 20 20 21 23 25 26 28 28 27 25 22 20 18 17 16 16 19 21 24 27 30 32 33 33 35 34 31 28 25 23 22 22 21 22 23 22 21 21 22 24 25 27 30 34 35 36 35 34 31 30 28 28 28 29 31 32 35 37 39 40 39 38 35 34 33 32 30 30 30 32 34 36 41 44 48 51 52 51 48 46 46 44 42 40 38 38 38 38 38 37 34 32 34 40 48 55 69 74 78 74 66 58 56 57 67 78 87 89 86 79 69 60 58 56 54 54 52 49 51 56 65 74 84 88 84 76 69 66 68 72 79 85 86 81 72 65 55 55 56 56 57 56 56 55 56 62 69 75 76 71 65 60 53 46 41 42 42 39 35 34 30 24 21 24 26 27 29 33 34 32 30 28 29 35 44 50 61 64 66 63 59 56 57 59 63 65 65 60 52 46 44 44 45 47 49 49 47 45 45 46 56 60 66 68 67 64 61 60 48 47 45 43 40 37 35 34 38 39 40 43 45 43 40 36 28 24 23 29 35 41 51 60 71 74 77 80 88 95 94 88 76 64 50 40 33 31 35 42 46 45 43 39 35 32 32 34 43 50 61 70 76 76 73 70 59 53 46 41 40 42 45 46 44 42 39 37 38 45 54 61 65 62 57 49 40 34 31 31 35 37 40 41 39 37 36 36 33 34 35 38 41 45 48 50 54 53 52 50 46 40 35 32 28 31 34 39 46 57 68 76 80 79 74 66 56 48 43 41 45 47 46 42 35 30 29 30 38 50 69 87 99 102 100 97 74 65 53 44 39 35 31 28 28 28 27 29 30 30 29 27 28 28 29 30 32 33 34 34 30 27 24 22 22 21 19 17 19 18 17 15 15 14 15 15 19 22 26 28 30 32 34 36 38 39 41 42 41 38 34 32 27 25 21 18 16 17 19 20 20 21 22 22 21 19 18 16 19 19 19 19 19 20 20 20 21 20 19 18 18 18 19 19 20 21 21 21 20 19 18 17 14 13 12 11 10 9 8 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 6 6 6 5 5 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 6 6 6 6 7 8 10 10 12 12 12 13 15 16 18 19 19 18 18 16 15 14 13 12 14 13 13 12 12 13 14 14 18 18 20 22 25 27 29 29 30 29 28 25 22 19 17 16 18 19 21 24 27 29 31 32 36 35 32 30 27 26 25 24 24 24 25 23 20 19 20 21 22 24 27 30 32 33 33 33 30 29 26 25 26 28 31 33 37 38 40 41 39 37 33 31 29 28 27 26 28 32 36 39 45 47 49 50 49 46 43 40 40 40 40 40 40 40 39 39 42 40 37 34 34 40 48 55 69 75 81 81 74 66 62 61 66 75 83 86 86 85 79 71 64 59 56 55 51 46 48 54 61 69 77 79 74 66 61 60 61 64 69 74 76 72 65 60 54 54 55 54 52 51 50 50 57 65 77 86 89 86 79 73 61 50 41 39 38 34 33 34 32 26 24 27 29 28 29 32 33 32 31 30 32 39 48 54 64 66 68 66 63 63 67 71 77 78 75 67 56 48 45 46 50 54 57 57 53 47 43 40 44 50 57 62 63 63 62 61 55 55 55 54 52 47 43 41 37 37 37 39 40 39 37 34 26 22 21 27 35 45 57 68 78 80 80 82 88 95 94 89 82 72 60 50 40 33 34 39 43 43 42 39 36 33 33 34 45 51 60 68 72 71 67 64 52 46 38 34 35 40 45 48 46 44 40 36 35 39 46 51 54 53 48 41 34 30 29 30 35 38 41 41 39 36 35 35 33 33 33 35 39 43 48 50 56 56 54 51 46 41 36 33 30 32 37 42 48 57 67 74 78 76 71 63 54 47 43 42 42 43 42 36 29 27 30 34 44 56 74 89 96 94 87 82 62 55 45 39 37 36 34 31 30 29 28 29 29 28 25 23 25 26 28 30 32 33 34 35 30 27 24 23 24 23 19 16 18 17 16 15 14 15 17 18 22 24 27 29 30 32 35 38 41 42 44 45 44 41 36 34 27 24 20 17 16 17 20 21 20 21 22 22 21 19 18 16 18 18 18 18 18 18 17 17 19 18 17 17 17 18 19 20 21 21 22 22 21 19 17 16 13 13 12 11 10 8 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 6 6 6 5 5 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 6 5 5 6 6 8 9 10 12 12 13 13 15 17 19 20 20 19 18 17 15 14 13 13 15 14 13 12 12 12 13 13 16 17 19 22 24 27 29 30 32 32 31 29 26 22 18 16 18 18 19 21 24 27 30 31 36 35 33 30 28 27 26 26 25 26 26 24 20 18 18 19 20 22 25 28 30 32 32 32 30 28 25 23 24 27 31 34 38 39 41 41 39 36 32 30 26 25 23 23 26 31 36 40 47 48 49 49 47 43 39 36 36 37 39 40 41 40 39 38 44 42 38 35 35 40 49 55 70 77 84 84 79 71 67 65 65 72 79 82 85 87 83 77 68 61 57 56 50 44 46 52 57 64 71 71 65 58 54 54 54 56 60 64 66 64 59 54 54 54 54 52 49 47 47 47 62 71 85 97 102 98 91 85 67 53 41 38 36 32 32 36 36 31 28 31 32 31 31 33 34 34 33 33 36 42 51 58 65 67 69 68 66 68 74 79 86 86 82 71 58 48 45 46 53 57 62 62 57 49 42 38 35 41 49 55 57 58 57 58 62 63 65 65 62 57 52 49 37 36 35 36 37 37 35 33 25 20 19 25 35 46 61 73 80 81 80 81 86 92 92 86 85 76 65 55 44 35 34 37 42 43 43 41 37 35 35 35 46 52 60 66 69 68 64 61 48 42 34 29 31 38 44 49 47 45 40 35 33 35 40 44 48 46 42 37 31 28 28 29 36 38 41 41 39 37 35 35 35 34 33 34 37 42 46 49 57 56 54 50 45 40 35 33 30 33 38 43 49 57 65 71 74 73 68 61 53 46 43 43 41 41 39 33 27 26 32 38 49 61 77 88 89 82 71 64 53 47 40 36 37 38 37 35 30 29 28 28 28 27 23 20 23 24 27 29 32 34 35 35 30 28 25 25 25 24 20 16 19 17 16 15 15 17 19 20 24 26 28 29 30 32 35 38 42 44 46 47 46 42 37 34 26 23 19 16 16 17 20 22 20 21 22 22 21 19 18 16 17 17 18 18 17 16 15 15 18 17 16 16 17 18 20 21 22 22 23 22 21 19 17 15 13 13 12 11 9 8 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 6 6 6 5 5 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 6 7 7 8 9 9 11 11 12 14 15 16 17 18 20 19 19 18 18 19 19 20 19 17 15 13 12 11 12 12 15 16 17 19 23 27 31 33 32 32 31 29 27 24 22 20 17 17 17 17 19 22 25 26 30 29 27 25 25 25 26 26 26 26 25 25 23 22 20 19 17 18 20 23 26 28 30 31 32 30 28 26 27 29 32 34 36 38 41 44 43 41 37 34 32 28 23 22 25 31 37 41 47 50 53 51 46 38 31 28 33 35 38 40 42 43 43 42 41 40 39 38 39 43 50 55 69 75 81 84 80 73 67 63 66 69 74 79 83 86 87 87 77 71 61 51 45 44 46 48 54 58 63 63 59 54 52 51 54 54 54 53 53 53 53 53 54 50 49 49 47 46 49 56 66 78 93 104 110 109 98 87 71 58 44 38 36 35 37 40 38 38 38 35 33 31 32 33 37 37 37 39 43 49 55 58 66 64 65 68 70 72 80 89 96 95 88 75 58 46 42 42 52 59 67 69 62 50 39 33 33 35 39 44 49 53 56 58 63 66 70 73 72 69 65 62 46 40 35 36 42 45 41 37 29 22 19 23 31 43 58 71 80 81 79 76 73 73 76 79 78 77 71 61 48 39 36 36 39 41 42 41 39 39 41 45 44 48 53 57 58 55 51 48 34 31 27 27 30 38 46 52 51 48 43 37 34 33 33 34 36 36 34 31 27 26 27 28 30 33 37 40 39 38 38 39 37 37 36 35 35 37 42 46 50 50 49 48 45 41 37 35 39 40 41 42 44 50 58 63 67 65 61 56 51 46 42 40 39 38 35 30 27 30 36 42 56 69 80 80 74 69 59 50 36 38 38 38 42 48 46 41 39 37 34 31 29 26 21 18 17 19 23 27 29 30 29 28 30 29 29 27 26 25 24 23 18 16 13 14 17 20 22 22 25 25 24 25 27 30 34 36 43 45 48 49 48 44 40 37 25 22 18 15 14 16 19 21 26 26 26 25 23 20 17 15 17 16 15 15 14 14 15 15 18 18 19 20 21 21 21 20 21 21 21 21 19 16 14 12 10 10 10 9 9 9 8 8 8 8 8 7 7 6 6 6 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 6 7 7 8 9 9 10 10 11 12 14 15 16 16 19 18 18 18 18 19 20 21 20 19 16 14 13 12 12 12 14 14 15 17 21 24 28 30 31 31 30 29 28 25 24 22 18 17 17 17 18 20 22 23 27 26 24 23 22 22 23 23 23 23 24 24 23 22 20 19 17 18 19 21 23 26 29 30 30 29 28 27 27 29 31 32 34 36 38 40 40 40 38 37 35 30 25 22 24 29 35 39 48 51 54 52 46 38 31 27 31 33 35 38 40 41 41 41 40 40 39 39 40 44 51 56 67 72 79 81 78 72 66 63 65 68 73 78 81 83 83 83 74 68 58 49 44 43 45 48 53 56 60 60 56 52 51 50 48 48 48 49 50 51 52 52 51 47 45 46 46 47 54 63 82 94 108 118 122 118 104 91 70 57 43 38 37 38 41 46 44 44 44 41 37 35 36 37 40 40 41 44 48 54 59 62 69 66 66 69 71 74 83 93 102 101 94 79 61 47 41 40 49 57 67 70 64 53 41 34 29 31 34 38 43 46 49 50 58 63 70 76 77 74 68 64 51 45 39 41 47 51 49 45 35 27 22 24 30 41 56 69 77 77 74 69 64 62 65 68 72 72 70 62 52 44 40 40 39 41 42 42 40 40 43 45 49 51 53 54 52 48 43 40 32 30 28 28 32 39 48 53 55 51 46 40 35 32 31 30 30 29 28 26 23 22 24 27 31 35 38 40 40 40 41 42 39 39 37 35 34 36 39 43 48 47 46 45 42 40 38 37 40 41 42 42 43 47 53 57 59 58 56 53 49 46 43 42 40 39 36 32 30 33 40 45 55 65 72 69 62 56 49 41 37 41 45 48 54 59 58 52 46 42 37 33 30 26 22 18 18 20 22 24 26 27 28 28 29 30 30 30 29 27 25 24 20 17 15 16 19 22 23 24 25 24 23 23 25 29 33 36 45 46 48 48 45 41 36 33 25 23 19 16 16 17 20 22 26 26 25 24 22 19 16 14 15 15 14 13 13 14 14 15 17 18 20 21 22 22 21 21 21 21 21 20 18 16 13 12 10 9 9 9 8 8 8 8 8 8 8 7 7 6 6 6 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 6 7 7 8 9 9 8 9 10 11 12 13 14 14 17 17 17 17 19 20 22 23 22 20 18 16 15 13 13 13 13 13 14 15 17 21 24 26 29 29 30 29 29 28 26 26 20 19 18 17 16 17 18 19 23 22 20 19 18 18 18 19 19 20 22 24 24 22 20 19 18 17 17 18 20 23 27 29 28 28 28 28 29 29 30 30 31 32 33 34 36 38 40 41 38 34 28 23 23 27 32 37 51 53 56 53 47 38 31 27 27 29 32 35 37 38 38 38 39 39 39 38 40 45 51 56 63 68 73 75 72 67 63 60 60 63 68 73 77 78 78 77 69 63 54 45 41 41 44 47 49 52 54 54 52 50 49 50 46 46 45 45 45 46 47 47 47 42 40 42 45 51 63 74 100 112 124 131 131 122 105 90 68 54 41 36 38 41 48 55 55 55 53 49 45 42 41 42 44 44 47 50 55 60 65 68 73 70 68 69 70 74 86 98 107 106 99 83 63 45 36 34 44 54 65 71 68 57 44 36 26 28 30 33 36 39 41 42 50 57 67 76 79 76 70 65 56 52 48 51 57 62 62 60 46 36 27 25 28 37 52 65 72 71 67 59 52 49 51 55 64 67 70 67 59 50 45 44 39 40 42 42 42 42 44 46 50 50 49 47 44 40 37 34 31 30 30 32 37 44 51 56 59 55 49 42 35 30 27 25 24 24 23 22 20 21 24 27 33 36 39 41 41 41 43 44 42 41 39 36 33 33 35 38 44 43 42 40 39 39 39 39 41 43 44 43 43 44 47 49 50 50 50 50 48 47 45 45 41 40 37 34 34 38 44 50 56 61 63 56 48 43 40 36 39 47 56 62 70 74 71 65 56 51 43 36 31 27 23 20 20 20 21 22 23 25 26 27 29 30 32 34 33 30 27 25 22 20 18 19 22 25 26 26 25 23 21 20 22 27 32 36 46 47 47 46 42 37 32 29 25 23 20 18 18 20 22 24 26 26 24 23 20 17 14 13 13 13 12 12 12 13 14 14 17 19 21 22 23 23 23 22 20 20 19 18 17 15 13 12 9 9 9 8 8 7 7 7 8 8 8 7 7 6 6 6 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 7 7 8 8 8 7 7 8 9 10 11 11 12 14 15 15 16 18 20 22 23 22 21 20 18 17 15 14 14 13 12 12 13 15 17 20 21 27 27 28 29 29 29 28 28 24 22 20 18 17 17 17 18 19 19 18 17 16 15 15 15 15 17 20 23 23 22 21 19 18 17 16 15 17 21 25 28 27 28 30 31 31 31 30 29 28 28 27 28 31 36 41 44 43 39 32 25 22 24 30 34 51 53 55 53 46 38 30 26 24 26 28 31 33 34 35 34 35 35 36 36 38 42 49 53 57 61 64 65 62 58 55 54 52 55 60 65 69 70 70 70 63 57 49 42 39 40 43 45 44 45 47 48 48 49 50 51 51 49 47 45 43 42 42 43 43 38 36 40 47 58 74 88 113 123 133 136 132 119 99 82 63 50 37 34 39 46 56 65 69 68 65 59 53 48 46 46 45 46 49 54 60 66 71 73 76 73 69 68 66 71 84 98 107 107 101 85 63 43 31 26 40 49 62 70 69 60 47 38 28 28 29 31 32 35 36 37 41 47 57 66 71 70 67 64 60 59 60 66 74 78 77 75 59 47 33 26 26 32 45 58 65 65 61 52 44 40 44 48 60 66 72 73 66 56 49 46 40 41 42 44 44 45 46 46 46 45 43 41 39 37 35 35 34 35 37 40 45 51 57 60 62 58 51 43 35 28 24 21 23 24 23 21 21 23 27 30 35 37 40 41 41 42 44 46 44 43 41 37 32 31 31 33 39 38 37 36 36 37 39 40 41 43 44 45 44 43 44 45 46 47 48 49 49 49 48 47 44 42 38 36 37 41 48 52 58 59 56 49 41 38 39 41 46 57 69 77 83 86 81 74 66 59 49 40 34 29 25 23 22 21 20 20 21 23 25 27 29 31 35 37 37 34 29 26 24 22 21 22 25 27 28 28 25 22 19 17 20 25 31 35 45 46 46 44 41 36 32 29 26 24 22 20 20 21 24 25 26 25 23 21 18 15 13 11 12 11 11 11 12 13 14 15 18 20 22 24 25 24 23 22 19 18 18 17 15 14 13 12 9 9 8 8 7 7 7 7 8 8 8 7 7 6 6 6 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 7 7 7 7 8 8 6 7 7 8 9 9 10 10 12 12 13 15 16 19 21 22 21 21 20 20 18 17 16 15 14 13 12 12 13 15 16 18 23 24 25 27 28 28 28 28 26 25 22 20 19 18 19 19 18 18 18 17 16 15 14 14 14 16 19 21 22 22 21 21 19 18 16 16 17 20 24 27 28 29 31 32 33 32 31 30 27 25 24 24 27 34 40 45 46 43 37 29 24 24 28 32 47 50 53 51 45 37 30 26 23 25 27 30 31 32 32 31 30 31 32 32 34 37 43 47 51 54 56 55 52 49 48 47 47 49 52 56 59 60 61 61 55 51 46 41 38 39 41 43 40 40 40 43 47 52 56 58 58 56 52 49 46 45 44 44 42 37 37 43 53 67 86 101 123 131 137 136 129 114 93 76 58 45 34 34 42 52 65 75 83 81 76 68 59 52 48 47 43 45 48 54 61 68 75 79 80 75 70 65 61 63 77 92 103 105 101 87 65 44 30 25 36 44 56 66 67 60 48 40 29 29 29 29 30 32 33 34 35 39 46 52 57 60 61 60 62 65 72 82 90 94 91 88 73 58 41 30 25 28 38 49 59 61 58 51 42 39 43 49 60 69 78 80 73 61 51 46 42 42 43 45 47 47 46 45 45 43 41 38 36 36 36 36 40 43 46 51 56 60 63 64 63 58 51 43 35 29 25 23 27 26 24 22 21 23 27 31 36 38 41 42 42 42 43 44 44 43 41 37 32 29 29 30 35 34 34 34 35 37 39 40 38 41 44 44 44 43 44 45 45 47 49 51 52 52 51 50 46 43 38 36 38 42 47 51 55 53 48 43 38 37 43 50 59 70 83 89 92 92 85 77 69 62 51 42 35 31 27 25 23 22 20 20 21 23 26 29 30 33 37 40 39 35 30 27 24 23 23 24 27 29 29 28 24 21 18 17 19 24 30 34 42 42 42 42 40 36 33 31 26 25 23 22 21 22 24 25 24 23 21 18 16 13 12 11 11 11 11 12 13 14 16 17 20 22 24 26 27 25 23 22 18 17 16 15 13 13 12 12 9 9 9 8 8 7 7 7 8 8 8 7 7 6 6 6 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 7 7 7 7 7 7 7 7 6 7 7 7 8 8 9 9 10 11 11 12 14 16 18 20 19 19 20 20 19 18 17 17 16 15 14 13 13 14 15 16 20 21 22 24 25 26 26 26 26 24 22 21 20 20 21 21 20 20 20 20 19 18 16 16 16 17 18 20 21 22 23 23 21 20 19 18 19 22 24 26 27 29 30 31 32 31 30 30 27 25 23 22 25 32 39 44 47 46 42 35 27 24 27 30 41 44 48 48 43 36 30 27 24 26 28 29 30 30 29 29 27 28 28 29 30 33 37 41 46 48 49 49 47 46 47 48 48 48 48 49 49 50 51 51 48 46 43 41 40 40 41 41 38 37 38 42 51 60 66 69 68 65 60 55 51 49 48 48 42 39 41 50 62 77 96 112 130 134 136 131 122 108 89 73 54 42 34 37 48 61 75 86 95 92 85 74 62 53 47 45 40 42 45 51 60 70 79 84 84 80 73 64 56 55 67 81 97 100 100 90 70 50 36 30 35 40 50 58 62 57 49 41 31 30 29 29 29 31 33 34 35 37 39 43 48 52 55 57 63 68 78 90 99 103 102 100 86 70 51 36 27 26 33 43 54 57 58 52 43 40 44 50 63 72 83 86 79 66 54 48 44 44 45 47 48 48 46 44 46 45 42 40 38 37 37 38 48 51 56 61 65 66 67 66 63 58 51 43 37 34 32 32 33 31 28 24 21 22 26 29 38 42 45 46 45 44 43 43 42 42 40 36 32 29 28 29 31 32 32 33 35 37 38 39 37 39 41 42 41 41 42 43 45 47 51 54 55 55 54 54 48 43 37 35 36 40 43 45 47 43 40 37 35 36 45 56 69 80 91 94 93 90 82 75 64 58 48 40 34 30 27 25 24 23 22 22 24 26 29 31 33 36 39 40 39 35 30 27 24 23 23 24 27 29 29 28 23 21 18 18 20 24 30 33 37 38 38 38 37 35 33 32 27 26 24 23 22 22 22 23 22 20 18 16 14 12 12 12 12 12 13 14 15 17 19 20 22 24 27 28 28 26 23 20 16 16 14 13 12 12 12 12 10 10 10 9 9 9 8 8 8 8 8 7 7 6 6 6 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 7 7 7 7 7 7 7 7 7 7 7 8 8 8 9 9 9 9 10 10 12 14 15 17 16 17 18 19 20 19 19 18 19 17 16 14 13 14 14 15 17 18 19 21 22 23 23 23 23 22 20 19 20 20 22 23 23 23 24 24 23 21 20 19 19 19 18 19 20 22 23 25 22 22 22 22 22 24 25 26 26 27 28 28 29 29 28 28 28 26 23 22 25 30 37 41 47 48 47 40 31 26 27 30 34 38 43 44 41 35 30 28 27 28 29 30 30 29 28 27 26 27 27 27 27 30 33 37 42 44 46 47 48 50 53 56 56 53 49 45 42 41 41 42 42 42 42 42 42 41 40 39 38 37 38 45 57 70 79 83 83 78 70 62 54 49 46 45 43 42 47 58 71 85 103 118 126 128 126 118 108 97 80 67 52 42 36 42 55 70 85 96 103 99 91 78 64 52 45 42 38 39 42 48 58 71 83 90 90 84 76 65 52 48 58 72 86 92 96 89 73 54 40 34 34 37 43 51 55 54 48 42 36 35 33 32 33 34 36 38 40 40 41 43 47 50 53 55 63 69 78 89 100 106 109 109 98 82 61 44 32 27 32 39 50 55 58 53 44 40 44 49 65 75 86 90 83 70 58 51 47 46 46 48 50 49 45 42 44 43 43 42 42 43 44 45 55 58 64 68 70 70 68 66 63 59 51 45 41 40 42 44 42 40 35 29 25 24 27 30 42 46 50 52 50 47 44 42 40 40 39 36 32 29 29 29 29 30 32 34 36 37 37 38 36 37 38 38 36 36 38 39 43 46 50 55 58 59 58 58 50 44 36 32 33 36 38 39 40 36 34 35 34 36 46 58 71 80 88 88 84 79 73 66 55 49 41 35 30 27 25 23 24 24 24 25 27 30 32 34 36 38 40 40 38 34 29 26 22 22 22 24 27 28 27 26 22 21 19 19 21 25 30 32 34 34 35 34 33 31 30 28 28 27 25 23 21 21 20 20 19 18 16 14 12 12 12 12 14 14 15 16 18 20 22 23 25 27 29 30 29 25 21 19 16 15 13 11 11 11 11 12 11 11 11 11 10 10 9 9 8 8 8 7 7 6 6 6 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 7 7 7 7 7 7 7 7 7 7 8 8 8 8 9 9 9 8 9 9 10 12 14 14 14 15 17 19 20 20 19 19 20 19 17 15 14 14 15 15 15 16 17 19 20 20 21 20 20 19 18 18 19 20 22 23 25 26 26 27 26 24 22 21 21 20 19 18 19 21 24 26 23 23 24 24 25 25 25 25 25 25 25 25 26 26 27 27 30 27 24 22 24 29 35 39 47 49 49 43 34 28 27 29 30 34 39 41 39 34 30 28 29 30 31 31 30 29 27 26 26 27 27 27 27 28 32 35 41 43 46 48 51 55 60 64 63 59 52 44 39 36 36 36 39 40 42 43 43 42 40 38 40 39 40 48 62 77 88 93 97 91 79 67 55 46 40 37 44 45 51 63 77 91 108 121 118 119 114 105 95 84 70 58 52 43 39 46 60 75 91 102 107 103 93 79 64 51 43 39 38 38 40 47 58 72 85 93 93 88 79 66 51 44 53 66 78 85 90 86 72 54 41 35 35 36 40 46 51 51 47 43 41 40 38 37 38 39 42 43 44 44 46 47 50 52 53 54 64 68 76 86 97 106 112 115 105 89 67 49 36 29 32 38 48 54 58 54 44 39 41 47 66 76 88 92 86 73 61 54 49 47 47 49 50 49 45 41 39 39 41 43 46 49 52 54 58 62 67 72 73 71 67 65 64 59 52 46 44 46 49 52 51 48 42 35 29 27 29 32 45 49 54 56 54 49 45 42 38 39 38 36 32 29 29 30 28 30 32 35 36 37 37 36 36 37 36 35 33 32 33 35 40 43 49 54 59 61 61 60 50 44 35 31 31 33 34 34 38 34 33 35 36 37 47 60 66 75 81 78 73 69 63 57 47 42 36 31 27 25 22 20 24 25 26 28 30 32 35 36 38 39 40 39 37 33 29 26 21 21 21 23 26 27 26 25 21 21 20 21 23 26 29 32 33 33 32 31 30 28 26 25 29 28 25 23 21 20 19 19 18 16 14 13 12 12 13 13 15 15 16 18 20 22 24 25 27 28 30 31 29 25 21 18 15 14 12 11 10 10 11 12 12 12 12 11 11 11 10 10 8 8 8 7 7 6 6 6 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 7 7 8 8 8 8 8 8 9 9 10 10 10 10 10 10 9 9 8 8 7 10 10 9 9 9 9 8 8 13 14 16 18 20 20 19 19 19 19 19 18 17 15 14 13 14 14 14 14 14 15 17 17 17 17 17 18 19 20 22 23 26 28 31 34 34 33 30 29 27 25 23 22 22 23 25 27 23 24 25 26 28 29 31 31 31 28 25 22 21 22 25 27 27 29 31 30 30 33 39 44 50 50 48 45 39 33 27 24 29 30 32 32 32 32 30 29 29 30 32 33 33 30 27 25 25 25 25 26 28 32 34 36 41 43 47 51 58 66 75 82 79 71 61 50 42 38 35 33 39 43 46 47 45 42 41 40 33 34 40 52 68 84 94 99 103 95 82 65 50 40 37 37 45 50 60 72 85 96 105 109 104 100 95 88 80 70 59 52 47 44 42 48 61 78 94 103 106 100 88 74 60 48 39 34 32 36 41 48 59 72 85 94 99 95 86 70 55 49 54 61 72 77 83 82 72 57 43 34 30 33 37 42 45 47 47 47 42 38 37 39 39 41 47 56 58 64 67 65 65 68 69 67 67 67 72 81 87 92 101 110 104 97 82 63 45 35 34 36 45 50 54 51 43 39 41 45 63 74 87 94 89 75 60 50 46 47 50 53 55 53 49 45 44 40 40 46 51 52 55 59 64 67 70 70 68 64 61 61 57 56 54 53 54 57 61 63 67 61 52 41 32 30 32 35 46 54 61 61 58 54 47 41 34 34 34 33 32 31 30 29 28 30 32 34 35 35 35 34 34 32 29 26 26 27 29 31 34 40 50 59 64 64 60 57 52 44 34 31 33 37 38 37 35 35 34 35 37 43 51 56 61 60 58 58 56 53 47 43 38 35 31 27 23 22 22 22 23 24 25 28 31 35 38 40 40 39 37 35 32 28 25 24 20 21 22 23 23 23 23 23 22 22 22 23 25 27 29 30 30 29 27 25 24 23 23 23 25 24 24 23 22 21 20 19 20 18 16 14 13 14 15 17 18 20 23 25 27 27 26 25 28 28 28 28 26 23 21 19 15 15 15 15 15 15 15 15 13 13 13 12 11 11 10 10 9 8 8 7 7 8 8 9 5 6 6 6 6 6 6 6 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 7 7 7 8 8 8 8 8 9 9 9 10 10 10 11 10 10 10 9 9 8 8 10 10 9 9 9 8 8 8 11 12 14 16 18 18 18 18 19 19 19 19 18 16 15 14 15 14 14 14 14 15 16 17 16 16 17 17 19 20 22 23 27 29 32 35 37 36 35 34 31 30 28 26 25 26 27 28 23 23 24 25 26 28 30 31 29 27 24 21 21 22 23 25 27 30 32 33 34 37 42 46 50 50 50 47 42 36 30 27 27 28 30 31 32 32 31 31 31 33 34 35 34 31 28 26 25 25 26 27 30 33 36 38 41 44 49 55 62 71 81 88 85 77 64 52 42 37 34 33 41 44 48 49 47 44 41 40 34 35 39 50 66 81 93 98 100 93 80 64 49 40 36 36 43 51 63 76 86 92 95 96 91 86 80 73 66 59 52 47 43 41 41 47 60 77 92 100 101 94 82 68 55 44 38 34 36 39 45 52 62 74 88 97 102 100 90 75 58 50 52 57 67 71 75 74 64 51 38 30 29 31 36 40 44 47 49 50 47 43 41 41 42 44 52 61 72 81 88 89 89 90 87 82 74 71 70 74 78 83 93 103 104 99 87 71 54 43 40 40 46 51 53 49 41 36 37 41 61 71 84 91 86 72 57 47 43 46 50 55 58 56 51 47 43 39 38 43 48 51 54 58 63 65 67 67 64 61 59 58 53 54 55 58 63 70 76 79 78 71 58 44 33 28 29 31 45 55 63 64 61 56 49 41 33 33 33 32 31 30 29 29 28 30 32 35 36 37 36 36 33 31 28 26 25 26 28 29 34 39 48 56 61 61 59 57 50 44 37 35 37 40 40 38 37 36 36 36 38 42 47 51 51 49 47 45 43 40 36 32 32 30 26 23 21 20 21 21 21 22 24 26 29 33 35 37 37 36 35 33 30 26 24 22 19 20 21 22 22 22 22 22 22 22 23 25 26 27 28 29 28 27 26 24 23 22 22 22 23 23 22 22 21 20 20 20 20 19 17 16 15 16 18 19 20 22 24 27 28 28 27 26 27 27 27 26 25 23 21 19 15 15 15 16 16 16 16 16 15 15 14 13 12 11 11 10 9 8 7 7 7 7 8 9 6 6 6 6 6 6 6 7 6 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 7 7 7 8 8 8 8 8 9 9 9 10 10 10 10 11 11 11 11 10 10 10 10 10 10 10 9 9 8 8 8 8 9 11 13 15 16 17 17 19 19 19 19 19 18 17 16 15 15 14 14 15 15 16 17 16 16 16 17 18 20 21 22 27 29 33 37 39 41 41 41 39 37 35 33 31 30 30 30 24 23 22 23 24 27 30 32 32 30 28 26 24 24 24 24 27 30 33 36 38 41 44 47 49 50 51 50 47 41 35 31 27 28 29 31 32 33 33 33 34 35 36 37 35 32 29 27 25 25 26 28 31 35 38 41 42 46 51 57 65 75 85 92 89 81 67 52 41 35 33 33 43 47 51 52 50 45 41 40 37 36 39 47 60 74 86 92 92 86 74 60 47 38 35 35 45 54 67 80 86 87 83 79 74 69 62 55 51 48 45 42 39 38 41 49 62 78 90 97 94 86 73 60 48 41 37 36 40 43 47 54 63 75 88 96 103 101 95 82 67 57 55 57 63 66 68 64 56 44 35 29 28 30 34 39 44 48 52 53 55 49 45 44 45 48 57 66 85 98 111 117 118 115 108 100 86 78 69 65 64 69 81 93 100 98 92 80 65 53 47 45 49 52 53 48 39 33 33 35 56 66 78 83 79 66 51 42 39 43 51 59 64 62 57 52 44 38 36 40 45 47 51 56 61 63 63 61 58 55 54 54 50 52 57 63 71 80 87 91 86 78 64 47 34 28 28 30 44 55 66 68 65 60 50 41 33 32 31 30 29 29 29 29 29 31 34 37 39 39 38 37 32 30 27 25 24 25 26 27 33 37 43 49 54 55 56 55 48 45 42 43 45 47 45 42 41 40 39 38 39 40 42 44 40 37 34 31 30 29 26 24 25 23 21 18 17 18 19 20 20 20 21 23 26 29 32 33 33 33 31 29 27 24 21 19 18 19 20 21 21 21 20 20 22 23 25 27 28 28 28 27 26 25 24 22 21 20 20 20 21 21 21 21 21 21 21 21 21 20 19 18 19 20 21 23 24 26 27 29 29 29 28 27 25 25 25 25 24 22 21 20 16 16 17 17 18 18 19 19 18 18 17 15 14 13 12 11 9 8 7 7 7 7 8 9 7 7 7 7 7 7 7 7 6 6 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 7 7 7 8 8 8 9 9 9 9 9 10 10 10 11 11 12 12 12 12 12 12 12 12 12 12 11 10 10 9 9 8 6 7 8 10 12 14 15 16 18 19 20 20 20 20 19 19 17 16 16 15 15 16 17 17 16 16 16 17 18 20 21 22 26 28 32 36 40 43 45 46 46 45 43 41 39 36 34 33 26 24 22 21 23 27 31 34 40 40 39 37 34 30 27 24 26 28 32 36 39 42 44 45 46 48 50 51 49 44 39 36 31 31 32 32 33 33 33 33 35 36 36 36 34 32 29 27 24 24 25 28 31 35 39 41 43 45 50 54 61 70 79 86 83 76 63 48 38 33 34 36 47 50 54 55 51 45 40 37 37 36 37 41 50 61 72 78 77 73 65 54 43 37 35 35 47 55 67 78 81 78 71 66 59 55 50 46 44 42 40 39 36 38 43 53 66 80 89 94 87 79 66 53 44 39 39 40 43 45 49 54 62 73 84 92 99 100 97 88 76 67 64 64 63 64 64 59 51 42 36 32 30 32 35 40 45 51 55 58 60 53 47 45 45 48 58 69 88 104 123 134 137 134 124 114 99 86 70 59 53 56 69 81 91 94 94 87 75 62 53 50 52 54 54 48 39 33 31 32 49 57 67 72 67 56 44 36 36 42 53 64 71 70 64 59 46 39 35 37 41 43 48 54 59 59 58 55 51 48 48 48 50 53 58 65 73 81 87 90 85 77 63 47 34 29 30 33 44 56 67 70 68 61 50 40 32 30 29 27 27 28 29 30 31 34 37 40 41 41 40 38 30 29 27 25 24 24 25 26 32 33 37 41 44 47 49 50 48 48 50 53 56 55 52 48 46 44 42 41 41 40 39 37 34 30 27 25 25 26 26 25 23 21 19 17 16 17 18 20 19 20 20 22 24 26 28 29 30 29 28 27 24 22 20 18 18 19 19 20 20 20 19 19 22 24 26 29 29 28 27 25 24 23 21 20 19 19 19 19 19 19 20 20 21 22 23 23 22 22 22 21 22 23 25 26 29 29 30 30 30 29 28 27 23 23 23 23 22 22 21 21 18 18 19 19 20 21 21 22 21 21 19 17 16 14 13 12 9 9 8 7 7 8 9 9 9 9 9 9 8 8 8 8 7 7 6 6 6 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 7 7 8 8 8 9 9 9 9 9 10 10 10 11 11 11 14 14 14 14 14 14 14 14 14 14 13 12 11 10 10 9 6 7 8 9 11 13 14 15 18 19 20 21 22 22 22 22 19 18 18 17 17 17 18 18 17 17 17 18 19 21 22 23 25 27 29 33 37 42 45 47 50 50 49 48 45 42 39 37 29 26 23 21 23 27 33 38 48 50 52 51 47 39 31 25 26 27 30 33 37 39 40 40 41 43 46 48 47 45 41 39 37 37 36 34 33 32 32 31 33 34 34 33 32 30 28 27 24 24 25 27 31 35 39 41 42 44 46 48 51 57 64 69 68 63 53 42 35 34 38 43 52 55 57 56 50 43 38 35 33 33 33 35 39 46 52 57 61 59 54 46 39 35 34 35 45 51 60 67 70 67 61 57 50 48 45 43 42 41 37 35 33 37 45 57 70 81 87 89 83 75 62 50 43 41 43 45 47 48 51 54 60 70 80 87 96 97 96 90 81 73 70 69 64 64 61 56 49 42 38 37 35 37 40 44 50 55 59 62 62 55 47 44 42 45 54 65 85 104 125 140 145 143 134 124 108 93 74 58 49 48 58 70 83 88 93 91 81 70 61 57 56 57 55 50 41 35 32 32 41 47 55 57 53 45 37 31 35 43 56 69 78 78 73 67 53 44 37 36 37 39 44 50 55 56 54 51 46 42 41 41 48 51 57 64 71 77 82 84 79 72 59 44 33 28 30 33 44 56 66 69 66 59 48 38 30 29 26 25 26 28 31 33 36 38 41 44 44 42 39 37 29 29 27 26 26 26 27 27 30 31 32 33 36 39 42 43 47 51 57 63 65 64 59 55 51 48 45 44 43 41 37 34 29 27 24 23 26 29 30 31 25 23 21 18 17 18 19 20 21 21 21 22 23 25 27 28 28 28 27 26 24 22 20 19 20 20 21 21 21 20 20 19 23 24 27 28 29 27 25 24 22 21 20 19 18 18 18 18 18 19 20 22 23 25 26 27 25 25 25 26 26 27 28 29 32 32 32 31 29 28 27 26 21 21 21 21 22 22 23 23 21 21 22 22 23 23 23 24 22 22 20 19 17 15 14 13 10 10 9 9 9 9 10 10 11 11 10 10 9 9 8 8 7 7 7 6 6 6 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 8 8 8 8 9 9 9 10 10 10 10 10 11 11 11 12 15 15 15 15 16 16 16 16 17 16 16 14 13 12 11 11 9 9 9 9 11 12 14 15 17 18 20 22 23 24 24 24 22 21 20 19 19 19 20 20 18 18 19 19 21 22 24 25 25 26 27 30 34 39 43 46 50 51 52 52 50 47 44 42 34 30 25 22 24 30 37 42 54 59 65 67 63 52 39 31 28 27 27 29 32 35 35 34 35 36 39 41 42 42 41 40 40 39 37 34 32 31 31 30 31 31 31 31 30 29 28 27 26 26 27 29 32 36 39 42 42 42 41 40 39 42 46 50 50 49 45 39 35 38 46 53 61 62 62 58 50 43 37 35 31 33 36 37 37 39 41 44 50 49 46 42 37 34 34 35 39 44 50 56 59 59 56 54 48 46 44 43 42 40 36 33 35 40 50 64 76 84 87 87 81 73 61 50 44 43 46 49 51 51 52 54 58 65 74 81 91 91 89 84 77 71 68 67 65 65 62 56 49 44 42 41 43 45 48 52 56 60 63 65 62 54 46 42 39 40 48 58 81 98 119 133 140 141 135 128 110 96 78 62 50 44 50 58 73 80 88 89 84 74 67 64 58 58 56 51 44 38 34 33 35 39 43 45 42 37 33 31 37 45 59 74 84 85 81 76 62 52 41 36 35 36 40 46 52 53 52 48 43 38 36 35 41 45 51 59 66 72 75 77 70 64 54 41 31 27 28 31 46 55 63 64 59 54 44 36 29 27 25 24 26 30 35 38 42 44 46 47 46 42 38 35 29 29 28 28 29 29 30 31 31 31 30 30 31 33 35 37 46 52 61 68 71 69 64 60 53 49 45 43 43 41 36 32 26 24 22 23 26 29 31 32 27 25 23 21 20 21 22 23 25 24 24 24 25 26 27 28 29 29 28 28 26 24 23 22 22 23 23 23 23 22 21 21 24 25 26 27 26 25 24 23 21 20 19 18 18 18 18 18 19 20 22 24 27 29 31 32 31 31 32 32 32 32 32 32 34 33 32 30 27 25 24 23 20 20 20 21 22 23 24 25 25 25 25 25 24 24 24 24 22 21 20 19 17 16 15 14 12 12 11 10 10 11 12 12 13 12 12 11 10 10 9 9 8 7 7 7 6 6 6 6 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 8 8 8 9 9 9 10 10 10 10 10 11 11 11 12 12 15 16 16 16 17 17 18 18 19 19 18 17 15 14 13 13 12 12 11 11 11 12 14 15 17 18 20 23 24 26 26 27 24 23 22 21 21 21 21 22 20 20 20 21 22 24 25 26 27 27 27 28 32 36 41 44 49 51 53 54 54 51 48 45 38 34 27 24 25 32 41 47 59 68 79 85 82 70 54 44 32 29 26 26 29 31 30 29 29 30 32 34 36 38 39 40 38 37 34 32 31 30 30 30 29 29 30 30 30 29 29 29 30 30 30 32 35 38 41 43 41 40 38 34 31 31 34 37 39 40 41 39 39 44 55 63 71 70 67 60 51 43 38 36 37 42 47 50 49 47 46 47 46 46 44 41 36 33 32 33 35 40 47 54 58 60 59 58 56 53 48 44 42 41 39 37 43 49 61 75 87 92 92 90 79 71 60 50 45 45 48 51 49 49 49 49 51 57 65 70 78 77 75 71 67 65 64 65 70 69 67 61 55 50 49 49 51 53 56 60 63 65 66 66 62 54 46 41 36 36 42 51 72 86 103 114 121 125 123 118 107 96 80 66 53 43 43 48 60 68 78 81 78 72 67 65 57 56 54 50 45 40 36 35 32 34 36 36 34 32 32 33 40 48 62 78 88 91 87 83 72 59 45 38 34 33 37 43 49 50 50 47 41 35 31 30 34 38 44 51 57 61 62 63 57 54 47 39 32 30 32 35 48 55 59 57 52 47 40 33 27 25 23 23 26 32 38 42 48 50 51 51 47 41 35 31 29 29 30 31 32 33 34 35 34 33 32 30 30 31 32 33 43 50 61 70 73 70 66 62 53 47 42 39 40 39 35 31 27 25 23 24 26 29 30 30 26 25 23 22 22 24 27 28 29 28 28 27 28 28 29 30 30 31 30 30 29 27 26 25 25 25 26 26 25 24 23 23 25 25 24 24 24 23 22 22 20 20 19 18 18 18 18 19 20 22 24 27 30 33 35 36 38 39 39 39 39 38 38 37 34 33 31 28 25 23 21 20 20 20 20 21 22 24 26 28 28 28 27 27 26 25 25 24 21 20 20 19 18 17 16 16 14 13 13 12 12 13 13 14 14 14 13 12 11 10 10 9 8 8 7 7 7 6 6 6 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 8 8 8 9 9 10 10 10 10 10 10 11 11 12 12 12 16 16 16 17 17 18 18 19 21 20 19 18 17 15 14 14 15 14 13 12 12 13 14 15 17 18 20 23 25 27 27 28 26 25 24 23 22 22 22 23 21 21 21 22 23 25 26 27 29 28 27 28 31 35 40 43 47 50 53 55 55 53 50 47 41 36 29 25 27 34 43 49 65 75 89 98 97 84 68 56 35 31 26 25 27 29 28 27 25 26 27 29 32 35 38 39 35 33 31 30 29 29 30 30 29 29 29 30 30 30 31 31 33 33 33 35 37 40 43 45 41 39 36 31 28 27 29 31 34 37 40 41 43 50 61 70 77 76 71 62 52 44 39 38 44 51 60 64 63 59 57 56 46 46 45 41 36 32 31 31 35 40 49 57 63 65 65 64 66 60 52 46 44 44 43 43 52 59 72 86 97 102 100 97 77 70 60 51 46 46 49 51 45 45 44 43 44 48 56 61 65 64 62 60 60 61 64 66 76 75 73 67 61 57 55 55 56 58 62 65 68 68 68 67 62 54 46 40 35 33 39 46 62 74 87 96 102 107 108 105 103 94 81 69 55 43 40 42 50 58 68 73 71 67 64 63 55 54 53 49 45 40 37 36 32 33 33 32 30 31 33 36 42 50 64 80 91 94 90 86 77 64 48 39 34 32 35 41 48 49 50 47 41 34 29 27 30 33 38 44 48 49 49 49 45 44 41 37 34 35 39 42 49 54 57 52 47 43 37 32 26 24 22 23 26 33 40 45 52 53 54 52 48 41 34 29 29 30 31 32 34 36 37 38 37 36 34 32 31 31 31 32 41 49 60 69 72 70 66 63 51 45 39 36 38 38 34 30 29 27 26 26 28 29 28 27 24 23 22 22 24 27 30 32 31 31 30 30 30 30 31 31 32 32 32 32 31 29 28 27 27 27 28 27 27 26 25 24 26 25 23 22 22 21 22 22 20 20 19 18 18 18 19 19 22 23 25 29 32 35 38 39 44 44 44 44 43 42 41 40 34 33 30 27 23 21 19 19 20 20 20 21 22 25 27 29 30 30 29 28 27 26 25 24 19 19 19 18 18 17 17 16 15 15 14 13 13 14 15 15 15 14 14 13 12 11 10 10 8 8 8 7 7 6 6 6 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 4 5 5 6 6 6 8 8 8 8 8 8 8 8 10 10 10 10 10 10 10 10 12 11 11 11 11 12 13 14 15 15 16 17 18 20 21 22 21 21 20 19 18 17 17 16 16 16 16 15 14 14 13 13 18 19 21 23 25 27 29 30 29 28 28 27 26 25 25 24 27 25 24 23 23 25 28 30 26 27 28 27 27 29 32 35 39 41 44 47 48 48 47 46 41 37 32 28 28 35 46 54 67 85 100 104 104 102 88 70 50 40 29 25 27 30 28 24 24 25 25 27 29 32 34 36 34 30 27 26 29 33 36 37 34 30 29 30 30 28 30 34 32 34 37 39 40 43 47 50 52 49 43 38 34 32 32 32 38 42 46 50 54 62 72 80 84 85 81 68 53 42 40 43 49 65 80 85 85 85 78 70 65 55 47 43 40 34 31 31 36 42 49 57 68 79 80 77 77 68 57 49 41 37 40 48 61 75 91 101 105 104 98 90 78 69 59 53 52 52 49 46 41 42 41 39 38 42 51 58 52 50 47 43 43 49 60 68 76 79 81 77 70 64 64 66 61 63 65 66 66 64 62 60 54 49 41 35 33 36 41 44 54 59 64 68 71 76 83 89 88 87 82 71 57 44 37 35 39 47 58 65 66 64 60 58 47 44 42 42 44 44 41 38 32 31 29 29 32 37 43 47 55 59 66 75 83 88 88 87 77 69 56 41 31 29 33 37 42 46 49 47 39 31 26 24 24 28 33 36 38 40 42 44 39 38 37 36 36 38 39 40 46 47 46 45 43 40 37 35 25 22 22 26 29 34 43 52 59 61 60 56 47 36 28 23 24 25 29 33 34 33 38 46 44 45 46 44 40 37 35 35 39 44 52 61 66 65 59 55 41 40 38 35 33 32 31 31 28 27 27 27 27 27 27 27 21 21 22 24 26 29 31 33 32 29 27 27 29 31 32 32 36 35 34 33 31 30 28 28 26 27 28 29 29 27 26 25 25 25 25 25 24 23 21 21 21 21 20 20 20 21 21 22 25 27 31 34 36 40 45 49 53 54 55 54 52 49 46 44 38 35 31 27 25 23 19 17 19 20 22 24 26 28 29 30 32 32 31 30 28 26 24 23 20 19 18 17 17 18 20 21 19 19 19 18 17 17 16 16 18 17 16 15 13 12 11 11 8 8 8 8 8 8 8 8 6 6 6 7 7 8 8 8 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 4 5 5 6 6 6 8 8 8 8 8 8 8 8 10 10 10 10 10 10 10 10 12 12 11 11 12 12 13 14 15 15 16 16 18 19 21 22 21 21 21 20 20 19 19 19 19 18 18 17 16 15 14 14 17 18 20 22 25 28 30 31 30 30 30 29 29 28 28 27 28 27 25 24 25 27 29 31 27 28 29 28 27 28 30 33 36 37 39 41 43 43 43 43 39 36 32 28 28 34 43 49 64 82 98 104 107 107 95 79 59 48 36 30 31 34 33 30 29 29 30 31 32 34 35 36 34 31 28 27 30 34 37 38 39 34 31 33 32 30 32 36 38 41 45 48 50 53 56 59 61 58 53 47 44 42 43 43 48 51 54 56 59 65 75 82 87 87 83 71 55 43 40 41 55 72 91 101 106 108 103 95 78 66 54 47 42 35 33 34 41 49 59 69 81 91 92 87 83 72 58 48 39 36 42 51 68 83 99 107 109 106 97 89 74 67 58 53 52 51 48 45 39 39 38 37 38 41 47 51 46 43 38 35 36 45 58 68 82 86 88 84 76 69 67 68 59 60 61 61 60 57 55 53 47 43 37 33 32 34 39 42 49 52 56 57 58 62 69 75 83 83 79 69 55 43 35 33 34 40 49 57 59 57 53 50 43 40 37 37 39 39 38 36 36 35 35 36 40 45 50 54 57 59 62 68 75 79 81 80 74 66 54 40 30 27 30 34 41 46 49 47 40 31 25 23 22 25 29 32 33 33 34 35 34 35 36 38 39 40 41 41 44 44 44 43 40 37 34 32 26 23 23 26 30 35 45 55 61 62 60 54 44 34 26 22 24 25 29 34 34 34 40 48 50 53 55 54 49 43 38 36 37 41 47 54 58 57 53 48 39 38 36 34 32 30 29 29 27 27 28 28 28 26 25 24 20 22 24 27 29 31 32 33 30 28 27 28 30 33 35 35 38 37 36 34 31 29 27 27 25 26 27 28 28 27 26 25 25 26 26 26 26 24 23 22 22 22 21 21 21 22 23 24 28 31 35 39 42 47 52 55 59 60 61 61 58 54 50 47 39 35 30 27 25 23 21 19 22 23 24 26 28 29 31 31 32 32 31 29 27 25 23 22 20 19 18 18 18 20 21 22 21 21 20 20 19 18 18 17 17 17 16 15 13 12 11 11 8 8 8 8 8 8 8 8 6 6 6 7 7 8 8 8 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 4 5 5 6 6 6 8 8 8 8 8 8 8 8 10 10 10 10 10 11 11 11 12 12 11 11 12 13 14 14 15 15 15 16 17 18 20 21 21 21 21 22 22 23 23 23 22 22 21 19 18 16 15 15 17 18 19 22 25 28 31 32 33 33 33 33 33 33 32 32 31 30 28 27 27 29 31 33 30 31 31 29 27 26 28 30 32 32 32 33 34 35 37 37 34 33 30 27 27 30 36 41 56 74 92 102 109 112 104 92 73 61 47 39 38 41 41 40 37 37 38 38 38 39 39 39 37 35 32 32 35 38 40 41 44 39 35 35 33 32 34 39 44 48 55 61 64 67 70 72 74 71 65 60 56 55 55 55 62 63 63 62 62 67 75 82 89 89 86 74 58 45 39 38 54 71 93 109 118 121 117 111 92 78 62 52 44 38 38 42 49 60 74 86 98 105 103 97 90 76 59 45 36 35 45 56 77 91 106 112 111 104 92 81 68 62 56 52 50 49 45 42 38 37 37 39 43 45 46 46 41 37 31 28 32 44 60 71 89 92 94 90 81 72 66 64 55 56 56 55 52 49 46 45 40 37 34 32 32 35 38 41 45 46 47 45 44 47 54 60 75 76 74 66 53 41 34 31 31 35 41 48 52 51 46 42 38 36 33 33 34 35 36 35 37 38 40 44 48 53 58 60 60 58 56 57 61 66 69 70 68 62 51 38 29 25 27 29 40 45 50 48 40 31 25 22 21 24 27 29 28 27 27 27 28 31 36 41 43 43 41 40 39 39 39 38 36 33 31 29 27 24 23 26 30 36 47 58 64 63 60 52 41 31 24 21 24 25 29 34 35 36 43 51 59 64 68 67 61 51 42 37 35 37 41 46 50 50 46 43 37 36 34 32 30 28 27 26 26 27 29 30 29 26 23 21 19 21 26 30 32 33 32 31 27 25 25 27 31 36 38 39 42 41 39 35 32 29 26 25 24 25 26 26 27 26 26 25 26 27 28 29 28 27 26 25 23 23 22 21 22 23 25 26 31 35 40 45 49 54 59 63 65 66 68 68 64 58 52 48 40 36 30 26 24 24 23 22 26 27 28 30 31 32 33 33 32 32 30 28 26 24 22 22 19 19 19 19 20 22 24 25 24 24 23 22 21 20 20 19 16 16 15 14 13 12 11 11 8 8 8 8 8 8 8 8 6 6 7 7 7 7 8 8 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 4 5 5 6 6 6 7 7 8 8 8 8 9 9 10 10 10 11 11 11 11 12 13 12 12 12 12 13 14 15 15 15 15 15 16 17 19 20 20 21 22 23 24 25 26 26 26 25 24 22 20 18 17 16 17 18 19 21 24 28 31 33 36 36 36 37 37 38 38 38 35 34 32 31 31 32 34 36 34 35 35 33 29 28 28 29 30 29 27 26 27 28 30 32 29 29 28 26 24 25 28 31 46 62 81 95 106 112 109 101 86 75 60 50 47 49 50 50 47 47 47 47 47 47 47 47 46 45 43 44 46 47 47 46 48 41 36 35 33 32 36 42 48 54 64 72 78 82 85 87 87 83 77 71 66 63 63 63 69 69 67 63 60 62 69 75 85 87 84 75 60 46 37 34 47 62 84 102 114 117 113 108 95 81 65 54 46 43 47 53 59 72 87 99 108 112 108 100 91 76 58 43 34 35 47 59 83 96 108 112 107 97 82 70 60 57 52 50 48 46 42 39 39 39 41 47 53 55 52 49 43 38 32 31 38 52 69 80 95 96 95 89 78 67 59 55 51 51 50 48 45 42 39 38 36 34 33 33 34 36 39 41 44 44 42 38 36 39 46 52 65 68 67 61 50 40 34 32 34 36 40 45 49 48 44 40 37 35 33 32 32 33 34 35 36 39 44 50 55 59 62 63 61 56 49 46 48 52 56 59 61 56 47 36 27 23 24 26 39 45 49 48 40 31 24 21 21 24 27 29 27 25 24 23 25 29 36 42 45 43 39 36 32 33 34 34 33 31 29 28 28 24 22 26 30 36 48 59 65 63 58 49 39 30 24 22 26 27 30 35 36 37 45 53 66 72 78 78 70 58 45 38 33 34 36 40 44 45 44 42 37 36 35 33 31 28 26 25 25 28 30 32 30 26 21 18 17 21 27 32 34 33 31 28 22 21 22 26 32 38 41 42 47 45 42 38 33 28 25 23 23 23 24 25 25 26 26 26 28 29 31 32 32 30 28 27 24 23 22 22 23 25 28 29 34 38 44 50 54 59 65 68 69 71 73 72 67 60 52 47 40 35 29 25 24 25 25 25 29 30 32 33 34 34 33 33 31 30 28 26 24 22 21 21 18 19 20 21 23 25 26 27 27 26 25 24 23 22 21 21 16 15 15 14 13 12 11 11 9 9 9 9 9 9 9 9 7 7 7 7 7 7 7 7 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 4 5 5 6 6 6 7 7 7 8 8 9 9 9 10 10 10 11 11 12 12 13 13 13 12 12 13 13 14 15 15 14 14 14 15 16 17 18 19 20 21 22 24 26 27 28 28 27 26 24 22 21 19 18 18 18 19 21 24 27 31 34 37 37 38 39 40 41 42 43 40 38 36 34 34 36 38 39 39 40 40 38 34 32 32 32 31 29 26 24 23 24 26 27 24 25 25 24 22 21 23 24 35 48 66 82 96 105 107 105 94 84 71 60 56 56 56 56 56 55 54 54 55 56 57 58 61 61 61 61 62 60 56 53 49 41 34 33 32 33 39 46 55 62 73 83 90 95 98 100 98 94 87 79 72 69 67 66 68 67 64 59 53 53 58 63 77 79 79 73 61 48 38 33 40 50 68 87 100 104 103 102 86 76 64 56 52 51 58 67 73 85 98 106 110 110 104 97 87 74 58 46 39 40 51 63 87 98 107 106 99 87 71 59 53 51 48 46 44 42 39 36 38 40 45 53 60 62 58 54 47 43 39 41 50 64 79 88 99 97 92 83 71 59 50 45 43 43 42 41 39 36 35 34 34 33 32 33 34 36 39 41 43 42 40 35 32 35 43 49 57 60 61 56 48 40 36 36 39 40 43 45 47 45 42 40 37 36 35 32 31 30 31 32 36 41 48 56 62 64 64 63 58 51 42 37 38 42 48 51 56 52 44 34 26 23 24 26 40 44 49 47 39 30 24 21 20 23 27 29 27 24 22 21 24 29 36 41 43 41 36 33 28 29 30 31 31 30 29 28 26 23 22 25 29 35 46 56 63 61 56 48 39 31 27 25 30 30 33 36 37 38 45 54 68 74 81 82 75 61 48 40 31 31 32 36 40 42 42 41 39 39 38 36 34 31 28 26 26 28 32 33 32 27 22 18 18 22 28 33 35 33 28 25 19 19 20 25 33 40 44 46 51 49 45 40 34 29 25 23 23 23 23 24 25 26 27 28 30 32 34 35 35 33 31 29 25 24 22 22 24 26 30 32 38 42 49 55 59 64 68 71 73 74 75 74 69 61 52 47 38 33 27 24 24 25 26 27 30 32 33 35 35 34 32 31 28 27 25 23 21 20 20 20 19 19 21 23 25 27 28 28 28 28 27 25 24 23 22 21 15 14 14 13 12 12 11 11 9 9 9 9 9 9 9 9 7 7 7 7 7 7 7 7 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 4 5 5 6 6 6 6 6 7 8 8 9 10 10 10 10 11 11 12 13 13 13 13 13 13 13 13 14 15 15 14 14 14 14 14 15 16 17 18 18 19 21 23 24 26 26 28 28 27 25 24 22 21 21 20 20 20 20 23 26 30 33 37 37 38 40 42 44 45 46 44 42 40 38 38 39 41 42 43 45 46 44 42 39 39 39 35 33 29 26 24 23 23 24 23 24 25 24 22 21 21 23 27 37 51 68 82 94 100 102 97 89 79 70 64 61 60 59 60 58 57 57 59 64 68 71 78 78 80 81 79 73 64 58 47 39 32 30 31 35 43 52 65 72 82 91 97 101 104 106 101 96 89 80 74 69 67 67 64 64 61 55 49 46 48 52 65 69 72 71 63 52 41 35 32 35 47 64 77 84 87 90 76 70 64 62 60 61 68 77 84 93 101 102 102 100 95 89 81 72 62 56 52 52 60 70 89 97 102 97 88 76 62 51 47 46 44 42 40 38 36 35 37 41 49 57 63 63 60 57 51 49 50 55 65 77 87 93 98 93 84 72 61 51 44 40 37 37 37 36 36 36 36 36 36 35 34 33 34 36 39 41 41 41 38 34 31 33 39 46 50 53 55 52 47 42 42 43 44 46 48 46 43 41 40 40 40 40 39 36 32 29 27 28 37 44 53 62 67 67 63 61 51 45 37 32 33 39 44 47 52 48 41 33 26 24 27 30 41 45 48 45 37 29 24 23 20 24 28 29 27 23 20 19 23 27 33 38 40 38 35 32 29 30 31 31 31 30 28 27 24 21 21 25 28 32 41 51 58 57 54 48 41 35 32 31 36 35 36 38 37 37 44 53 66 73 80 81 75 63 51 44 32 32 33 36 39 41 40 39 42 42 42 40 37 34 30 28 27 29 32 34 33 29 24 21 21 25 31 35 36 33 28 24 19 19 21 27 36 44 49 51 54 51 47 41 35 30 25 23 23 23 23 24 25 27 29 30 34 36 38 39 38 35 32 30 24 23 22 21 23 27 31 34 42 46 53 58 61 65 68 70 74 74 74 72 67 59 51 46 34 30 26 23 24 25 26 26 30 31 33 34 33 31 29 27 24 22 20 19 18 18 19 20 20 21 23 25 27 28 29 29 28 27 26 25 23 22 21 20 14 13 13 13 12 12 11 11 10 10 10 10 10 10 10 10 8 8 7 7 7 7 6 6 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 4 5 5 6 6 6 6 6 7 8 8 9 10 10 10 10 11 11 12 13 14 14 14 13 13 13 13 14 15 16 14 14 13 13 14 14 15 16 16 17 18 19 21 22 23 24 27 27 26 25 24 24 23 22 23 22 20 20 22 25 29 31 35 36 38 40 42 44 46 47 47 45 43 41 40 41 43 44 47 49 51 50 48 47 46 47 40 38 34 30 27 24 23 23 24 26 27 26 24 23 24 25 24 29 40 55 70 82 92 98 94 90 83 76 70 65 61 58 59 57 56 56 60 68 76 81 91 93 96 97 93 83 70 60 46 38 31 30 32 37 48 58 73 78 85 91 95 97 99 100 92 88 81 74 68 64 63 63 62 62 61 55 48 44 44 47 54 60 67 70 66 57 47 41 32 28 32 44 55 62 69 75 72 70 70 71 70 70 75 82 85 91 94 90 85 83 81 77 76 72 70 71 69 68 72 79 87 92 92 84 74 64 53 44 43 43 41 38 36 35 35 35 39 46 55 62 64 62 60 58 57 58 62 71 82 91 95 96 90 82 70 57 48 42 39 37 37 38 38 40 42 44 45 46 45 43 40 38 38 40 43 45 43 43 40 35 31 31 36 42 46 49 51 49 46 45 47 50 50 53 55 51 43 38 40 44 48 49 49 45 38 32 29 28 36 43 54 63 67 65 59 54 43 39 33 30 33 39 44 47 50 46 39 31 26 26 31 35 42 45 47 43 35 28 25 24 27 30 34 34 30 24 20 18 21 24 28 33 36 36 36 35 34 35 35 34 32 29 26 24 21 19 20 24 27 29 36 44 52 53 52 49 44 40 38 37 41 39 39 39 37 36 42 50 64 70 76 78 73 64 55 49 42 41 41 42 44 44 42 40 44 44 44 42 40 36 32 29 28 30 33 34 34 31 27 25 27 30 35 38 38 34 28 25 22 22 25 31 40 48 54 56 55 53 48 43 36 31 26 24 23 23 23 24 26 28 31 32 37 39 41 42 40 37 32 29 24 22 21 20 23 27 32 35 41 45 51 55 58 59 61 63 68 68 67 64 59 52 46 42 30 27 24 23 24 25 25 25 28 29 31 32 31 28 25 23 19 18 16 15 15 16 18 19 21 23 25 27 29 29 29 29 27 26 25 24 22 20 19 18 13 13 13 12 12 12 11 11 10 10 10 10 10 10 10 10 8 8 8 7 7 6 6 6 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 4 5 5 6 6 6 6 6 7 8 8 9 10 10 10 10 11 12 13 13 14 15 14 13 13 13 13 14 15 16 14 14 13 13 13 14 15 15 15 16 17 18 19 21 22 22 27 26 26 25 25 24 24 24 24 23 21 20 21 24 28 30 35 36 37 40 42 45 46 47 48 47 44 42 42 43 44 45 48 51 54 54 53 52 52 52 44 42 38 34 30 26 24 22 27 28 29 28 26 26 27 28 23 26 35 49 63 76 87 95 92 90 85 79 73 66 60 57 57 55 53 54 60 69 80 86 98 101 105 107 101 88 72 61 45 37 30 30 33 40 51 62 76 79 84 88 89 89 90 92 81 77 71 65 60 58 57 57 61 63 62 57 50 45 44 45 48 55 64 70 68 61 51 45 42 33 30 37 46 51 59 67 72 72 75 79 78 75 78 84 81 85 84 77 71 70 69 67 74 74 77 81 82 79 81 85 83 86 84 74 63 54 45 37 41 41 39 36 33 33 34 35 44 52 61 66 65 62 60 59 62 65 72 83 94 101 101 99 80 71 57 45 37 35 34 35 41 42 44 46 50 53 56 58 54 51 47 44 43 45 48 50 47 46 44 38 33 32 36 40 44 47 48 47 45 46 51 55 55 60 62 56 45 39 42 48 56 58 59 54 46 38 33 31 33 41 52 61 64 60 53 48 39 35 31 30 34 40 45 48 49 45 38 31 26 28 33 38 43 46 46 41 34 27 25 25 35 38 40 39 34 27 22 19 18 21 25 29 33 36 38 38 40 39 38 36 32 28 24 21 19 17 19 24 26 27 33 40 48 50 51 50 46 43 41 41 45 42 41 40 37 35 41 49 62 68 74 76 72 64 57 53 52 51 50 51 51 49 45 42 45 45 45 43 40 36 32 29 29 30 33 34 34 32 30 28 32 34 38 40 39 35 30 26 25 25 28 34 43 52 57 59 56 53 49 43 37 31 27 25 24 24 24 25 27 29 32 34 39 41 43 43 41 37 32 29 23 22 20 20 22 27 32 35 37 41 46 50 52 52 54 55 62 61 59 56 51 45 39 36 28 26 24 23 25 25 25 24 27 28 30 31 29 26 22 20 17 15 14 13 13 15 18 19 23 24 26 28 29 30 29 29 26 26 24 23 21 19 18 17 13 13 12 12 12 12 11 11 10 10 10 10 10 10 10 10 8 8 8 7 7 6 6 6 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 4 4 4 4 4 4 6 6 6 7 7 8 8 8 9 9 10 11 11 12 13 13 13 13 13 14 14 15 15 15 14 14 14 14 14 14 14 14 14 14 15 16 18 21 23 24 24 24 25 25 25 26 26 26 28 26 24 23 23 24 26 27 31 31 33 36 39 43 46 47 47 46 46 45 44 45 45 45 50 52 54 55 55 54 52 50 48 46 43 39 34 30 26 24 27 28 31 33 34 33 32 31 27 26 28 34 45 61 76 85 84 83 80 76 70 62 56 52 47 46 46 49 56 66 77 83 97 100 103 103 96 84 71 62 44 39 33 34 41 51 59 63 82 82 82 83 83 80 74 70 68 64 57 50 47 49 54 58 57 64 68 64 58 54 49 43 50 53 59 65 68 69 68 66 53 44 39 41 45 51 63 75 80 86 86 80 76 77 76 72 74 72 67 59 53 54 60 66 74 79 87 94 97 95 92 89 81 78 71 62 53 45 39 36 41 40 41 40 35 31 36 45 53 62 72 75 70 63 59 58 58 69 83 96 106 109 100 89 77 59 41 34 33 32 35 41 42 44 48 54 59 62 64 64 66 61 54 50 50 52 54 56 56 55 51 43 36 33 36 40 41 45 49 50 49 50 54 57 68 64 59 53 43 36 39 47 58 69 76 71 60 49 39 31 37 44 54 62 64 60 51 45 37 32 29 30 36 43 46 47 44 40 34 29 28 31 36 39 43 45 46 40 32 27 27 29 36 41 46 46 40 32 26 24 20 22 24 28 32 36 39 41 42 44 45 42 36 28 23 20 16 18 20 22 23 27 32 36 43 47 51 52 51 48 47 46 46 44 41 38 37 38 40 41 51 54 59 61 61 61 61 61 63 63 63 61 57 52 46 43 41 43 44 44 42 38 34 31 31 32 34 34 33 31 29 27 31 35 41 45 44 38 31 25 24 26 30 36 42 49 54 57 56 53 48 42 36 32 29 28 25 26 26 26 26 27 30 33 35 39 42 42 38 32 28 25 19 18 18 19 22 27 32 35 35 39 43 44 43 43 45 48 51 50 48 47 45 40 34 30 21 22 22 22 22 22 23 23 25 25 24 23 22 21 20 20 14 13 12 13 15 18 21 23 23 25 28 31 32 31 29 27 23 23 22 20 18 17 16 15 12 12 12 13 13 14 14 14 12 12 12 11 11 10 10 10 9 8 7 6 5 4 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 5 4 2 2 3 4 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 4 4 4 4 4 4 6 6 6 7 7 8 8 8 9 9 10 10 11 12 13 13 13 13 13 14 14 15 15 15 14 14 14 14 14 14 14 14 14 14 15 16 18 20 22 23 23 24 24 24 25 25 25 26 27 26 24 23 23 24 26 27 29 30 31 34 37 41 44 45 47 46 45 44 44 44 44 44 48 50 52 53 53 52 50 48 47 45 42 38 34 30 28 26 26 28 30 33 34 35 34 34 30 29 29 32 41 53 65 73 77 76 74 70 64 58 52 49 42 41 42 45 53 63 73 79 89 91 92 91 85 75 66 60 50 46 42 43 50 58 64 67 74 74 74 73 72 68 62 57 54 50 45 41 40 44 50 55 64 71 75 71 66 61 56 50 50 52 56 60 65 68 71 72 69 62 57 60 64 69 78 89 92 96 94 84 75 71 65 59 60 59 55 49 45 46 52 58 74 80 88 95 97 94 89 84 74 70 63 54 46 39 34 32 39 39 39 39 35 34 41 51 62 71 80 81 73 63 56 54 56 67 82 95 105 105 95 82 65 50 35 32 34 37 41 45 49 51 54 59 64 68 69 70 67 62 55 50 51 54 57 59 59 58 53 46 38 34 36 39 42 45 48 48 47 49 53 57 66 63 59 53 43 36 39 47 64 76 85 83 72 60 47 38 38 44 54 62 64 59 50 43 35 31 28 31 37 42 45 45 41 37 32 28 28 31 35 39 41 44 44 39 32 28 28 30 38 43 49 49 44 37 30 27 22 23 25 27 31 35 39 41 44 45 46 43 36 29 23 21 17 18 20 21 22 25 30 33 42 46 51 53 52 49 47 46 43 41 38 35 35 35 37 39 47 50 54 57 59 60 62 63 71 72 72 70 65 58 51 46 41 42 42 41 39 36 33 31 30 31 32 33 32 31 30 29 32 36 41 44 43 37 30 25 23 25 28 34 39 45 50 52 51 48 44 39 35 32 30 29 27 27 27 26 25 25 28 30 33 37 40 40 37 32 27 25 19 19 19 21 24 27 31 33 28 31 34 34 33 34 36 39 42 40 39 38 37 33 28 24 21 21 21 21 22 22 22 22 23 22 21 20 19 18 17 17 14 13 13 13 15 17 20 22 23 25 28 30 30 29 27 25 21 21 20 19 17 16 15 14 12 12 12 13 13 14 14 14 12 12 12 11 11 11 10 10 9 8 7 6 5 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 3 2 2 3 3 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 4 4 4 4 4 4 6 6 6 7 7 8 8 8 9 9 9 10 11 12 12 13 13 13 13 14 14 15 15 15 14 14 14 14 14 14 14 14 14 14 15 16 17 19 21 22 22 22 23 23 24 24 24 24 26 25 24 23 23 24 25 27 27 28 29 32 35 39 42 43 46 45 44 42 41 41 41 41 44 45 47 48 48 47 45 44 44 42 40 37 34 31 29 27 25 26 29 32 34 36 37 38 35 33 30 30 34 42 51 57 65 64 62 59 55 50 46 43 37 37 38 42 48 57 66 71 78 77 76 74 71 67 64 62 58 56 54 56 60 64 67 68 67 66 65 64 62 56 48 43 38 35 32 31 35 42 49 54 69 76 79 76 72 68 62 55 49 49 50 53 59 68 76 81 85 81 80 83 87 92 99 107 107 107 101 87 72 62 53 46 44 45 45 42 40 42 49 54 75 81 89 95 96 90 83 77 66 62 55 47 40 35 32 30 37 36 36 37 36 38 48 61 76 85 93 92 80 65 53 48 53 65 81 94 101 99 85 71 49 39 30 32 39 45 49 53 55 55 57 61 66 70 72 72 66 60 53 49 50 55 59 62 62 61 57 49 40 35 35 37 42 44 46 45 44 46 51 56 64 61 59 53 44 37 40 47 69 83 95 96 87 74 57 45 40 46 55 62 64 59 48 40 32 29 27 30 36 41 42 41 36 33 29 26 27 30 35 38 39 41 42 38 33 29 30 31 39 44 51 53 50 42 35 31 25 24 24 25 27 32 36 39 44 45 46 42 36 29 24 21 17 19 20 20 21 23 27 30 39 44 50 53 52 49 46 44 38 36 34 32 31 32 33 34 40 43 48 51 54 58 62 65 76 78 79 78 72 63 53 47 41 40 38 37 34 32 31 30 28 29 29 29 30 30 30 30 34 37 41 43 41 35 29 24 21 23 26 30 35 40 43 45 42 40 37 34 32 31 30 30 29 29 28 25 22 22 23 25 30 33 37 38 35 31 27 26 20 21 22 25 27 28 29 30 23 24 24 24 23 24 27 30 31 30 29 29 28 26 22 19 20 20 20 21 21 22 22 22 20 19 18 17 16 15 14 13 13 13 13 13 15 17 20 21 24 25 27 28 28 26 24 22 19 18 18 17 16 15 14 13 12 12 12 13 13 13 13 14 12 12 12 12 11 11 11 10 9 9 7 6 5 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 2 2 1 0 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 5 5 5 5 5 5 5 5 6 6 6 7 7 8 8 8 8 8 9 10 11 11 12 12 13 13 13 14 14 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 16 18 19 20 21 21 21 22 22 22 23 23 25 24 23 23 23 24 25 26 27 27 29 32 35 39 42 43 44 43 41 39 38 36 36 36 38 39 40 40 40 40 39 38 38 37 36 34 32 30 29 28 23 24 27 29 33 36 39 40 38 36 32 29 30 35 40 44 51 51 50 48 45 42 39 37 35 35 36 40 45 51 56 60 65 63 61 59 60 63 66 69 69 69 68 67 67 66 64 63 63 62 62 61 58 52 44 38 31 29 27 29 36 45 54 59 69 74 76 73 70 67 61 54 47 45 43 45 53 65 77 85 92 93 96 101 108 114 120 125 122 116 102 83 65 51 43 39 36 40 44 46 47 49 55 60 73 78 86 91 90 84 75 68 62 58 52 45 40 36 35 34 36 34 34 36 36 42 56 70 92 100 108 104 89 68 52 44 49 62 77 89 95 91 74 58 38 33 31 37 48 56 61 62 57 55 54 56 61 65 66 65 60 54 47 44 46 52 58 61 64 64 59 51 41 35 34 36 42 43 44 42 41 42 47 52 59 58 56 53 44 37 39 46 67 83 99 104 98 84 65 50 44 48 55 62 64 58 47 38 28 26 25 28 33 37 37 35 30 29 27 26 28 32 36 39 39 40 40 37 33 31 31 32 38 43 50 54 52 46 39 34 26 24 22 21 23 27 32 36 40 42 42 39 33 27 22 21 18 19 20 20 19 21 24 27 36 42 49 52 51 47 43 41 33 31 29 28 27 28 29 30 33 36 40 45 49 54 60 65 75 77 79 77 72 62 52 45 40 38 35 32 29 28 27 27 25 25 25 25 26 28 29 30 34 37 40 41 39 33 27 23 20 21 24 27 31 33 35 36 32 31 30 28 28 29 30 31 29 29 27 23 19 18 18 20 26 30 34 35 33 31 29 28 22 24 27 30 31 30 29 27 22 21 20 19 18 20 23 25 24 23 22 23 24 23 21 18 19 19 20 20 21 22 22 22 19 18 17 16 14 13 12 11 13 13 13 13 15 17 19 20 24 24 25 26 25 23 20 19 16 16 16 15 14 14 13 13 13 13 13 13 13 13 14 14 13 13 12 12 12 11 11 11 10 9 8 6 6 5 5 6 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 4 4 2 1 0 0 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 5 5 5 5 5 5 5 5 6 6 6 7 7 8 8 8 8 8 9 9 10 11 12 12 13 13 13 14 14 15 15 15 15 15 15 15 15 15 15 15 15 15 14 14 15 16 17 18 19 19 20 20 20 21 21 21 23 23 23 23 24 24 25 26 28 29 30 33 36 40 43 45 43 42 39 37 34 32 31 31 32 32 33 33 33 33 32 32 32 32 31 31 30 30 29 29 23 24 25 27 31 35 38 40 40 37 33 30 29 31 34 36 40 39 39 37 36 34 32 31 35 35 37 39 42 45 47 49 50 48 46 47 52 60 69 75 82 82 81 77 71 64 58 55 56 57 58 60 58 54 46 41 34 31 29 32 40 50 57 60 65 68 68 65 63 61 56 50 43 40 38 39 47 60 74 82 93 98 105 114 123 133 139 142 136 123 102 77 56 41 36 37 38 44 52 57 58 60 63 67 68 72 78 81 80 74 66 60 57 54 50 45 42 40 39 39 36 34 34 36 38 45 61 76 102 111 118 113 96 73 54 45 47 58 72 82 87 81 64 48 34 34 38 47 60 70 72 70 59 55 50 51 54 57 57 54 49 44 39 37 40 47 53 56 64 63 58 49 39 33 33 35 41 44 45 44 41 40 43 46 53 53 53 50 42 35 37 43 63 80 99 107 105 92 73 56 49 51 55 61 64 59 49 40 28 25 23 25 30 33 32 30 27 27 27 28 31 36 40 43 41 41 40 38 35 32 32 32 35 39 45 50 51 47 40 35 27 24 20 18 18 22 27 30 34 36 36 34 29 24 20 19 19 20 20 19 19 20 23 25 34 39 46 49 47 43 38 36 28 27 26 25 25 25 26 27 27 30 35 39 44 49 55 60 67 69 71 71 66 59 51 46 42 39 35 30 27 25 24 24 23 23 23 23 24 26 27 28 34 35 37 38 35 31 25 22 20 21 23 25 27 28 28 28 25 24 24 24 25 27 29 30 28 27 25 21 17 15 15 17 24 28 32 34 33 32 31 31 28 30 34 36 36 33 30 27 23 21 18 17 17 18 20 21 19 18 17 18 20 21 19 18 19 19 20 21 22 22 23 23 21 20 19 17 15 14 12 12 12 13 13 14 15 16 17 18 22 23 23 23 21 20 18 17 15 15 15 15 15 14 14 14 15 15 15 15 14 14 14 14 13 13 13 12 12 12 11 11 10 9 8 7 6 6 6 6 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 2 4 4 2 0 1 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 6 6 6 6 6 6 6 6 6 6 6 7 7 8 8 8 7 8 8 9 10 11 11 11 13 13 13 14 14 15 15 15 16 16 16 16 16 16 16 16 15 15 14 14 14 15 16 16 18 18 18 18 19 19 20 20 21 22 22 23 24 24 25 25 29 30 32 34 38 41 44 46 44 42 39 36 33 31 29 29 28 28 28 28 28 28 28 28 28 28 29 29 30 31 31 31 27 26 26 27 30 34 38 40 41 38 34 31 29 29 31 32 32 32 31 30 29 28 27 27 32 33 36 38 40 41 41 41 38 37 36 39 46 58 69 77 90 90 88 82 71 60 51 46 46 49 53 58 60 58 53 48 42 37 34 36 43 51 55 57 60 61 58 54 53 54 50 45 38 36 34 36 43 54 65 73 87 95 105 116 128 141 149 150 143 125 100 74 51 37 36 40 48 55 64 68 68 67 66 67 61 63 66 67 66 62 57 54 52 50 49 46 44 43 42 42 38 36 36 38 40 47 63 78 105 114 121 116 99 76 57 47 46 55 66 74 77 72 56 41 34 39 47 58 73 84 84 78 65 58 50 47 49 50 48 45 40 36 32 32 37 43 49 52 60 59 53 44 35 31 32 35 43 47 50 50 45 41 40 40 46 46 48 47 39 32 33 39 58 75 95 107 108 99 81 65 55 54 55 60 63 61 52 43 31 27 24 24 27 30 29 27 26 27 28 32 36 41 45 48 46 44 42 39 36 33 31 30 31 34 39 45 47 45 40 35 28 25 20 17 17 19 23 26 28 30 30 29 25 21 19 19 20 20 21 20 19 20 23 26 32 36 42 43 41 36 32 30 25 25 24 24 24 24 24 25 23 26 31 36 39 43 48 52 57 58 59 60 59 56 53 50 46 44 39 34 29 25 23 23 22 22 23 24 25 26 27 27 31 32 34 34 32 28 24 22 21 22 24 25 25 24 23 22 20 20 20 20 22 24 27 28 27 27 25 21 17 15 16 17 23 27 32 34 35 35 35 36 36 38 40 42 40 37 33 30 24 22 19 17 18 18 18 17 15 13 13 14 16 18 17 16 19 20 20 22 23 24 25 25 23 22 21 19 17 15 13 13 12 12 13 14 15 16 16 17 20 20 20 20 19 17 16 15 15 16 16 16 16 16 17 17 17 17 17 16 16 16 16 15 14 13 13 13 12 12 12 12 10 10 8 7 6 6 6 6 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 2 4 3 1 1 5 8 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 6 6 6 6 6 6 6 6 6 6 6 7 7 8 8 8 7 7 8 9 10 10 11 11 13 13 13 14 14 15 15 15 16 16 16 16 16 16 16 16 15 15 14 14 13 14 14 15 16 17 17 17 18 18 18 19 20 21 22 23 24 25 25 25 29 30 32 34 38 41 44 46 47 45 42 38 35 32 30 29 28 27 27 27 27 27 27 28 26 27 28 30 31 33 34 35 33 31 29 29 30 34 38 41 41 39 35 31 28 27 27 27 28 28 27 26 25 25 25 25 26 28 32 35 38 38 38 37 36 35 35 38 46 58 70 77 88 89 86 78 65 52 42 37 37 41 49 57 64 65 62 59 53 47 42 41 46 51 53 52 53 52 46 41 41 44 42 37 33 33 33 35 40 48 56 61 71 81 93 103 117 133 141 141 136 118 95 73 55 43 45 53 63 70 78 80 76 69 65 63 55 54 54 53 52 51 50 50 49 49 50 50 49 48 46 45 41 39 39 40 41 47 62 77 102 110 118 114 98 76 59 50 46 53 61 66 68 65 51 38 34 42 54 67 83 95 94 86 71 61 50 45 45 44 40 36 34 32 30 32 37 43 48 50 56 53 47 38 30 28 32 36 46 52 58 58 52 45 39 37 40 41 43 43 36 29 29 35 52 68 88 102 107 102 87 72 60 56 55 58 63 62 55 48 37 32 26 25 27 29 29 28 26 28 31 36 41 47 51 53 51 48 45 41 37 34 30 28 30 31 34 40 44 44 40 36 30 27 23 19 18 19 22 24 24 25 27 26 23 21 20 20 20 21 21 20 20 21 24 27 31 34 38 38 35 30 27 25 24 24 24 24 24 24 24 24 21 25 30 34 36 38 41 43 44 45 45 47 49 51 53 54 53 51 46 40 34 29 25 23 24 25 27 28 29 28 28 27 28 29 30 30 29 26 23 21 23 24 25 26 25 22 20 18 18 18 18 18 20 22 25 26 28 27 26 23 20 18 20 21 24 27 32 35 36 37 39 40 43 45 46 46 44 40 36 33 27 25 22 21 22 22 19 16 14 13 12 13 15 17 17 16 20 21 21 23 24 25 26 27 24 23 21 19 17 15 14 13 12 12 13 14 15 15 16 16 18 18 18 17 17 16 15 15 17 17 17 18 18 19 19 19 19 19 19 18 18 17 17 17 14 14 13 13 13 12 12 12 11 10 9 7 7 6 6 7 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 3 4 3 0 2 8 14 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 6 6 6 6 6 6 6 6 6 6 6 7 7 8 8 8 7 7 8 9 9 10 11 11 13 13 13 14 14 15 15 15 16 16 16 16 16 16 16 16 16 15 14 13 13 13 14 14 16 16 16 17 17 17 18 18 20 21 22 23 24 25 25 25 29 29 31 34 37 41 44 45 50 48 44 40 36 33 31 30 29 28 27 27 27 27 28 29 27 27 29 31 33 35 37 38 37 35 32 31 32 35 39 41 42 39 35 31 27 25 24 23 27 26 25 24 23 23 23 24 21 24 29 33 36 37 37 36 39 38 39 42 50 61 71 78 82 83 80 72 58 44 34 29 33 38 47 59 68 71 70 67 62 55 48 46 49 52 52 50 47 44 37 31 31 35 35 31 30 31 32 35 39 45 50 53 55 66 78 88 102 119 127 127 125 109 90 74 61 52 56 66 75 81 88 88 81 71 63 59 50 49 46 44 44 45 47 48 49 50 53 54 54 53 51 49 43 41 41 42 42 47 61 76 98 107 114 111 96 76 59 51 46 52 58 61 63 61 49 37 33 43 57 72 89 102 100 90 73 62 49 42 41 39 34 29 32 30 30 33 39 45 49 50 53 50 43 34 26 26 31 37 48 55 63 65 58 48 39 35 36 37 41 41 34 27 27 33 46 62 82 97 104 101 87 74 62 58 55 57 63 63 57 51 42 36 29 26 28 30 30 29 27 29 33 39 44 50 54 57 54 51 47 42 38 34 29 26 29 30 32 37 42 44 41 37 31 29 25 22 20 20 22 23 22 23 25 24 22 21 21 22 20 21 21 21 20 22 25 28 30 33 35 34 31 26 23 22 24 24 24 24 24 24 24 24 21 25 30 33 35 35 36 37 35 34 34 36 40 46 52 55 58 56 51 45 38 32 27 25 26 27 30 32 32 31 29 28 26 27 28 28 27 25 23 21 24 25 26 26 25 22 19 17 18 18 17 17 19 21 23 25 29 29 28 25 22 22 23 25 24 28 33 36 38 39 41 43 48 49 49 49 47 42 38 35 31 29 26 26 27 26 22 18 16 14 13 14 17 18 19 18 21 21 22 23 25 26 27 28 24 23 21 19 17 15 13 13 12 12 13 14 15 15 15 15 17 17 16 16 16 15 15 15 17 18 18 19 20 20 21 21 21 20 20 20 19 18 18 18 14 14 14 13 13 12 12 12 11 10 9 8 7 7 7 7 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 3 4 2 0 3 11 18 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 6 6 6 7 7 8 8 8 6 7 8 9 9 9 8 8 9 9 9 9 9 9 9 9 12 12 12 13 13 14 14 14 15 16 17 18 19 20 19 19 19 18 16 14 13 13 14 14 15 14 14 15 16 17 19 19 19 21 23 23 23 23 25 27 24 27 31 35 37 41 45 48 47 48 47 44 39 36 35 36 33 32 31 31 34 35 35 35 35 34 33 35 39 42 43 43 43 41 38 36 35 36 39 40 41 39 35 28 23 22 24 26 30 29 28 29 29 28 25 22 23 24 26 29 32 35 37 38 38 43 48 51 57 66 70 69 75 72 66 58 48 39 31 27 30 35 46 58 69 74 75 73 64 61 56 52 48 48 48 49 38 39 38 34 34 37 38 35 33 32 34 38 43 46 46 45 47 51 59 72 88 102 112 117 111 102 87 73 65 64 68 72 87 88 87 82 74 63 53 46 42 42 42 42 43 44 45 46 48 50 52 55 57 58 58 58 51 50 48 46 47 53 62 68 83 91 99 97 85 68 56 49 44 49 56 61 61 55 47 42 39 46 61 79 95 100 96 89 74 67 56 46 39 35 33 31 29 33 39 45 50 53 53 53 54 46 39 34 29 28 34 42 54 63 70 69 63 54 43 33 32 34 36 37 37 34 31 29 40 55 75 93 105 106 94 80 60 56 52 54 58 60 56 52 44 40 36 33 33 32 31 29 30 31 34 41 49 57 62 63 62 55 49 47 42 35 31 32 31 36 41 42 43 43 37 30 30 28 27 28 29 28 26 24 28 26 25 25 26 26 25 23 25 23 23 24 27 30 30 30 34 32 29 26 24 23 23 23 25 26 28 29 29 27 25 24 23 24 26 28 30 31 31 31 28 29 30 31 35 42 51 57 59 61 60 54 44 35 30 29 30 33 36 38 38 35 32 29 28 27 26 25 25 25 25 26 26 26 25 25 23 22 20 19 20 22 23 23 23 23 25 26 26 26 27 28 28 28 27 27 28 29 32 34 37 38 39 40 45 46 47 48 46 42 38 36 37 36 35 35 34 30 25 21 17 16 15 14 14 16 17 18 19 21 24 27 29 30 29 28 24 23 21 18 16 15 14 13 12 12 13 14 15 16 16 17 14 13 13 13 13 14 15 16 18 18 18 19 19 19 20 20 21 21 21 21 20 19 18 17 17 17 16 15 15 14 13 13 11 11 10 9 9 8 7 7 7 7 7 6 6 5 5 5 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 6 6 7 7 7 8 8 8 6 7 8 9 9 9 9 8 9 9 9 9 9 9 9 9 12 12 12 13 13 14 14 14 15 16 17 18 19 19 19 19 18 17 16 14 13 13 13 14 14 14 14 14 15 16 18 19 19 21 22 23 23 23 25 27 25 28 32 35 37 40 44 47 48 48 48 45 42 39 39 39 37 36 35 36 38 39 39 38 36 36 37 41 46 51 53 54 51 48 44 40 38 38 40 42 41 39 35 29 24 23 24 26 31 30 31 32 33 32 29 26 26 26 27 29 32 36 40 42 46 51 54 55 58 65 67 65 63 60 55 48 41 34 29 26 30 35 43 55 65 71 72 71 65 62 56 51 48 46 46 46 39 42 43 41 42 45 44 40 37 35 36 39 44 47 47 46 41 43 48 59 72 86 96 101 96 89 79 70 66 69 74 79 85 83 80 74 66 57 49 44 42 43 44 45 46 47 48 48 50 52 54 56 59 60 61 62 55 54 52 49 49 52 58 63 71 79 86 85 75 61 51 46 43 47 54 59 60 55 49 44 43 48 60 75 89 93 89 84 72 66 57 49 43 39 36 34 33 37 43 49 54 56 56 56 53 46 39 34 29 27 33 41 55 64 72 71 65 57 45 35 30 32 35 37 37 36 33 32 41 55 74 91 102 104 92 79 65 59 54 54 57 58 55 51 43 41 38 36 35 34 32 30 28 29 33 40 50 59 65 67 64 57 51 48 43 38 36 38 39 45 49 49 48 46 39 30 29 28 29 31 33 33 31 29 31 30 28 28 29 28 26 24 24 24 24 26 30 33 34 33 33 31 28 24 23 23 24 25 31 33 35 36 35 32 29 27 24 24 25 27 28 30 32 32 28 29 30 31 34 40 48 54 63 65 65 60 50 41 36 34 33 35 38 40 40 37 34 31 28 28 26 25 25 24 25 25 25 24 24 24 23 21 20 19 21 22 24 23 22 22 23 25 26 26 28 29 29 29 29 28 28 29 30 32 33 35 36 37 41 42 44 44 43 41 38 36 38 37 36 36 34 31 26 22 17 16 15 15 15 16 18 19 19 21 24 27 28 28 28 27 24 23 21 18 16 14 13 13 11 11 12 13 14 15 15 16 14 14 13 13 14 15 16 16 18 19 19 19 20 20 20 20 22 22 22 22 21 20 18 18 17 17 16 15 14 14 13 13 11 11 10 9 9 8 7 7 7 7 7 6 6 5 5 5 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 6 7 7 7 8 8 8 8 7 8 9 9 10 10 9 9 10 10 10 10 10 10 10 10 12 12 12 12 13 13 13 13 15 15 17 18 19 19 19 19 18 17 15 14 13 13 14 14 13 13 13 13 14 15 16 17 18 20 22 23 22 23 25 27 26 29 32 35 37 39 43 46 48 49 49 47 45 43 44 45 44 43 42 43 45 46 44 42 40 40 41 46 53 58 61 62 60 56 49 42 38 38 39 40 40 39 36 31 27 24 25 26 32 33 34 37 40 39 35 32 30 29 29 29 33 38 44 47 55 59 60 58 59 61 60 56 49 47 44 40 35 32 30 29 32 35 41 50 58 64 66 65 62 60 55 50 46 44 43 43 43 48 52 54 57 59 55 48 42 39 37 40 45 50 50 49 40 38 39 44 53 65 74 79 78 74 68 64 65 69 75 79 77 73 67 59 52 47 44 43 40 42 43 45 46 46 45 45 46 47 49 51 54 58 61 62 60 60 58 54 51 51 53 56 59 66 72 72 64 54 46 43 41 45 52 57 59 56 51 48 48 51 58 68 78 81 78 74 67 63 57 53 49 45 41 39 38 42 48 54 58 59 58 57 51 45 38 34 29 27 32 39 53 63 72 72 67 58 46 36 27 29 34 38 40 40 38 37 43 56 73 89 100 102 91 79 68 61 53 51 52 53 50 47 42 41 39 39 39 37 33 30 25 26 31 40 51 62 69 73 69 61 53 49 45 42 44 49 53 59 63 62 57 51 41 32 28 29 31 35 39 40 38 36 36 35 33 32 32 31 28 25 24 24 26 30 35 39 39 39 34 31 26 23 22 24 28 30 38 40 43 44 42 38 33 29 26 25 24 25 26 29 32 34 30 30 30 31 33 38 45 50 62 66 68 64 55 46 40 38 36 38 41 43 42 39 36 33 29 28 27 25 24 24 24 24 24 23 23 23 22 21 21 20 22 23 24 23 21 20 21 22 25 26 28 30 31 31 31 30 28 28 27 27 28 29 31 32 35 36 38 39 39 38 37 36 40 39 38 37 36 32 27 23 18 17 16 15 16 17 19 20 21 22 25 27 28 28 26 25 24 23 20 17 15 13 12 11 10 11 11 12 12 13 14 14 15 15 14 14 14 15 16 17 19 19 19 20 20 21 21 21 22 22 23 22 21 20 19 18 17 16 16 15 14 13 13 13 11 11 10 9 9 8 7 7 7 7 7 6 6 5 5 5 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 7 7 7 8 8 8 9 9 8 8 9 10 11 11 10 10 11 11 11 11 11 11 11 11 12 12 12 12 12 12 12 13 14 15 16 18 18 19 19 18 17 17 16 15 15 14 14 14 13 13 13 13 13 14 15 16 18 20 22 22 22 23 25 27 27 29 32 34 36 38 41 43 46 48 49 49 48 48 49 51 50 49 50 51 52 52 49 46 43 42 44 48 55 61 64 66 67 61 52 43 37 34 34 35 38 38 37 35 30 28 27 28 34 35 38 42 45 45 42 39 35 33 31 30 34 40 48 52 59 63 63 59 56 54 50 45 42 40 39 37 36 35 35 36 37 38 40 45 51 54 55 55 55 53 50 46 44 43 43 43 49 56 64 70 75 76 68 58 44 40 37 41 49 56 58 58 49 44 38 36 40 48 55 59 62 60 57 56 57 61 65 68 64 59 52 45 41 40 42 44 46 47 49 49 48 46 43 41 42 42 44 47 52 57 61 64 62 62 61 57 53 50 50 50 54 58 63 63 57 50 44 41 40 44 50 55 58 57 55 53 52 53 56 61 65 67 65 63 61 59 56 54 53 50 46 42 41 44 49 54 57 58 56 55 49 43 37 34 29 26 30 37 48 58 67 67 62 55 43 34 26 29 34 40 44 45 45 44 48 59 74 88 98 101 92 80 70 61 51 46 46 47 45 41 40 40 40 41 42 39 34 31 22 24 29 39 52 64 73 77 74 65 56 50 46 46 52 61 69 77 81 78 70 59 46 34 29 31 34 39 44 46 44 43 42 40 38 37 36 33 29 26 23 25 28 34 40 44 44 43 35 32 27 24 25 30 35 39 46 49 51 52 49 43 36 31 28 26 24 24 25 29 33 36 34 34 33 32 33 36 42 46 56 61 64 62 54 45 39 37 37 39 42 44 43 40 36 34 29 28 27 26 25 25 25 25 24 24 23 22 22 22 22 22 23 24 24 23 20 19 19 20 23 25 28 30 32 32 31 30 27 25 24 22 23 24 27 28 31 31 33 34 35 36 36 36 42 40 39 38 37 33 27 23 18 18 17 16 17 19 21 22 24 25 27 29 29 28 26 24 23 21 19 16 14 12 11 10 10 10 10 11 11 12 12 12 15 15 14 14 15 16 17 17 19 19 20 20 21 21 21 21 23 23 23 23 22 21 19 18 16 16 15 15 14 13 12 12 11 11 10 9 9 8 7 7 7 7 7 6 6 5 5 5 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 7 7 8 8 8 9 9 9 9 9 10 11 11 11 11 11 11 11 11 11 11 11 11 11 12 12 12 12 12 12 12 11 14 15 16 17 18 18 18 18 17 17 17 17 17 16 16 15 14 14 13 13 13 14 15 15 17 19 21 22 22 22 24 26 27 29 32 33 34 35 38 40 44 46 48 50 50 51 54 56 56 56 57 59 60 58 54 50 43 42 43 47 55 63 69 72 71 65 56 46 38 34 32 32 35 37 39 38 35 33 31 31 35 37 40 44 48 49 47 44 40 37 33 32 35 41 50 55 58 62 62 58 53 50 44 37 39 38 38 38 39 40 40 41 42 41 41 42 44 45 44 42 44 43 42 42 42 43 44 45 54 63 74 83 90 90 79 66 45 39 36 41 53 64 69 69 62 54 42 34 33 37 42 45 47 46 46 46 47 50 53 55 50 46 41 37 37 40 45 49 58 58 59 58 55 52 48 46 44 45 47 50 55 61 65 68 63 63 63 59 54 50 48 48 51 54 56 56 52 46 40 37 39 42 47 53 56 58 57 57 55 54 53 53 54 54 53 52 53 52 52 53 53 51 47 44 40 42 46 49 51 52 51 50 46 41 37 34 29 26 28 34 39 49 57 58 54 47 38 29 27 31 37 43 47 50 50 50 53 63 75 86 96 99 92 82 70 61 50 44 44 44 42 39 38 38 40 41 42 40 35 31 22 23 28 38 51 64 73 77 77 68 58 51 46 47 57 68 81 91 97 94 83 69 53 41 34 35 38 43 48 50 49 48 48 46 44 42 39 35 30 26 24 26 31 37 44 47 46 45 36 33 30 28 31 38 46 51 57 59 61 60 56 48 40 35 30 28 25 24 26 30 35 38 38 38 37 35 34 36 40 43 49 54 59 58 51 43 38 36 37 39 42 43 42 39 35 32 29 29 28 27 26 27 27 27 28 27 25 24 23 23 24 24 24 25 25 23 21 19 19 20 22 25 28 31 32 32 31 30 25 24 22 21 21 23 26 27 30 30 31 32 33 35 36 37 43 41 40 39 37 33 27 23 19 18 18 18 18 20 22 24 28 29 30 31 30 28 25 23 20 19 17 15 13 11 10 10 10 10 10 11 11 11 11 11 15 14 14 14 14 15 16 17 19 19 19 20 20 21 21 21 22 22 22 22 21 20 19 18 16 16 15 14 13 13 12 12 11 11 10 9 9 8 7 7 7 7 7 6 6 5 5 5 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 8 8 8 8 9 9 9 10 9 10 11 12 12 12 12 11 12 12 12 12 12 12 12 12 12 12 12 12 11 11 11 11 14 14 16 17 18 18 18 18 18 18 19 19 19 19 18 17 15 15 14 14 14 14 15 16 17 19 21 22 21 22 24 26 26 28 30 31 31 32 34 36 40 42 46 49 51 53 57 60 62 63 64 66 67 64 59 54 44 42 41 44 53 64 73 78 73 68 60 50 41 35 32 30 33 37 41 42 41 38 37 36 37 37 39 43 47 49 49 47 44 41 36 34 36 42 50 55 57 62 64 60 56 53 46 39 40 41 42 43 43 43 42 42 44 43 41 41 40 39 36 33 33 34 35 37 39 42 44 46 56 66 79 91 99 98 85 70 46 39 35 42 57 71 78 80 72 61 47 35 30 31 34 37 36 36 36 38 40 44 47 48 42 41 39 40 42 47 52 55 62 62 62 62 61 59 57 55 53 54 55 58 61 64 67 68 66 66 65 61 56 51 48 48 47 49 51 52 49 44 38 34 37 40 44 48 52 55 57 58 55 53 51 48 46 44 44 43 45 45 46 48 49 48 45 42 38 38 40 41 42 43 43 43 44 39 36 34 29 25 27 32 33 42 49 48 45 40 33 26 28 32 38 45 49 52 52 52 54 62 72 81 90 95 89 80 69 60 49 44 44 44 41 38 36 36 37 39 40 38 34 30 24 24 28 36 49 61 70 75 75 66 56 48 43 45 56 69 85 97 108 106 96 82 66 53 44 44 45 47 51 53 53 52 54 53 50 48 44 39 32 27 24 27 32 39 45 47 45 43 35 33 32 33 38 46 55 61 68 69 69 66 61 52 45 40 31 29 27 26 28 32 36 39 42 42 40 37 35 34 37 39 44 49 54 53 47 41 37 37 37 39 42 43 42 38 34 31 29 29 28 28 29 30 30 31 33 32 29 27 26 25 26 26 24 26 26 24 22 20 21 22 24 26 30 33 34 33 31 29 24 24 24 24 26 28 30 32 33 33 32 32 32 34 36 38 43 42 40 39 36 32 27 22 20 19 18 19 20 22 24 25 30 30 31 31 29 26 23 21 17 16 15 13 12 11 11 11 11 11 11 11 11 11 11 11 14 13 13 13 13 14 15 16 18 18 18 19 19 19 20 20 21 21 21 21 20 19 18 17 15 15 15 14 13 12 12 11 11 11 10 9 9 8 7 7 7 7 7 6 6 5 5 5 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 8 8 8 9 9 9 10 10 10 11 11 12 13 13 12 12 13 13 13 13 13 13 13 13 12 12 12 11 11 10 10 10 13 14 15 17 17 18 18 17 19 19 21 21 22 21 20 19 16 16 15 15 15 15 16 16 17 19 21 21 21 22 23 25 25 27 29 29 29 29 31 33 36 39 43 47 50 54 58 62 68 69 71 74 74 70 64 59 48 44 39 39 46 56 66 72 71 67 60 51 42 35 30 27 31 36 42 46 46 43 42 41 38 37 38 40 44 47 48 48 47 43 38 35 37 42 48 53 59 65 68 67 65 62 56 49 45 47 49 50 49 47 45 43 43 42 40 40 39 36 32 29 26 28 30 33 36 39 42 44 56 66 79 92 102 101 86 69 48 40 36 42 59 75 84 86 77 66 51 38 33 32 35 37 34 34 34 35 37 40 43 45 41 42 45 49 53 56 59 61 64 65 67 69 72 74 75 76 74 74 74 74 74 73 73 72 73 72 70 65 58 52 49 48 45 46 49 51 50 46 39 35 34 36 39 43 47 51 54 55 54 52 49 45 41 38 38 38 38 38 39 42 44 44 42 39 36 35 34 33 34 35 37 38 42 38 35 34 29 24 25 30 31 38 44 42 39 37 32 26 29 33 38 44 49 51 51 51 51 58 66 73 82 87 82 74 63 55 45 41 41 41 38 34 34 34 34 36 37 36 33 30 26 26 29 35 46 58 66 70 70 62 52 43 37 39 52 65 81 97 112 114 106 94 80 69 56 54 52 52 54 56 56 56 61 60 57 54 50 43 36 30 25 28 34 40 45 46 43 39 32 32 32 35 43 52 62 68 72 72 70 66 59 51 44 39 32 31 29 29 31 34 38 40 43 43 41 37 33 32 33 35 39 43 47 47 42 37 35 35 38 40 43 44 42 39 35 32 29 29 29 30 31 33 34 35 38 36 33 30 28 28 28 29 25 26 27 25 23 22 23 24 28 30 34 36 37 35 33 31 26 26 28 31 33 36 38 39 39 37 35 33 33 35 37 38 43 41 39 38 36 31 26 21 20 20 19 19 21 23 25 27 29 30 30 29 27 23 20 17 14 14 13 12 11 11 12 12 12 12 12 12 12 11 11 11 12 12 12 12 12 13 14 15 17 17 17 17 18 18 19 19 20 20 20 20 19 18 17 16 15 15 14 14 13 12 11 11 11 11 10 9 9 8 7 7 7 7 7 6 6 5 5 5 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 8 8 8 9 9 10 10 10 10 11 12 13 13 13 13 12 13 13 13 13 13 13 13 13 12 12 12 11 11 10 10 10 13 14 15 16 17 17 17 17 19 20 22 23 23 22 21 20 17 17 16 15 15 16 16 17 17 19 21 21 21 21 23 25 25 26 28 28 27 27 29 31 33 37 42 46 50 54 59 62 72 73 76 78 78 74 67 62 54 47 38 34 37 46 55 60 66 63 57 49 40 33 26 23 30 36 43 48 48 47 45 44 39 37 36 38 42 46 48 48 48 44 39 36 37 41 47 51 61 68 73 73 72 71 65 58 51 53 56 57 55 52 47 44 41 40 39 40 39 36 32 28 24 25 27 31 34 37 40 41 55 64 78 91 101 100 84 67 50 42 36 43 60 77 86 88 80 69 54 42 37 37 39 41 39 38 37 36 37 38 40 42 43 46 51 57 61 63 63 63 71 73 76 81 87 93 98 101 98 98 97 95 92 89 85 83 79 78 74 67 59 52 49 48 44 46 50 53 53 50 43 39 32 33 35 39 43 47 51 53 52 51 48 44 39 36 35 35 34 34 35 37 40 41 39 37 35 33 30 29 29 31 34 36 41 38 35 34 29 24 25 29 31 38 42 40 37 36 32 27 29 32 38 43 47 49 49 49 47 53 60 67 76 81 77 69 56 48 39 36 37 37 33 30 33 32 32 33 35 35 32 30 28 28 29 35 45 55 63 67 66 58 48 39 33 34 47 61 77 94 112 118 113 102 89 79 64 61 57 56 57 58 59 58 66 64 61 58 54 47 38 33 26 29 34 40 45 44 40 37 30 30 32 37 45 55 65 71 72 70 67 62 55 47 40 36 32 32 31 31 33 36 39 41 43 43 41 36 32 30 30 32 35 38 42 41 36 32 32 33 39 41 44 45 43 40 35 32 29 29 29 31 32 34 36 38 42 40 36 32 30 29 29 30 25 26 27 26 24 23 24 25 31 33 37 39 39 37 34 32 27 29 32 36 39 42 44 45 42 40 37 34 34 35 37 39 42 41 39 38 35 31 25 21 20 20 19 20 21 23 26 27 28 29 29 28 25 21 17 15 12 12 11 11 11 12 12 13 12 12 12 12 12 12 12 12 12 11 11 11 11 12 13 14 16 16 16 17 17 17 18 18 19 19 19 19 18 17 16 15 15 15 14 13 13 12 11 11 11 11 10 9 9 8 7 7 7 7 7 6 6 5 5 5 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 8 8 8 9 9 10 10 10 10 10 11 12 12 13 14 14 15 15 15 15 15 15 15 15 13 13 12 12 12 11 11 11 14 14 13 13 13 14 15 16 18 18 19 19 19 20 20 20 22 21 19 18 17 18 19 19 18 18 18 19 19 20 20 20 22 24 24 24 23 23 25 28 30 32 35 39 43 50 57 62 73 75 78 82 85 82 75 68 56 49 39 31 30 35 43 49 57 57 54 49 42 35 32 31 30 34 41 51 58 58 53 47 41 40 38 38 40 44 48 51 44 45 43 38 34 35 43 50 58 70 83 89 91 90 84 77 70 69 68 66 61 54 48 44 44 43 42 45 47 47 43 38 33 27 24 28 32 35 39 44 53 67 84 94 96 91 78 66 48 41 37 44 60 76 86 90 78 70 57 46 41 43 48 53 56 53 49 44 42 42 44 46 47 58 68 70 69 69 67 64 71 76 84 96 109 122 131 137 136 134 131 124 116 108 100 96 87 87 83 76 71 66 58 49 45 45 45 46 48 49 44 37 31 31 32 36 42 47 49 50 47 45 43 44 45 45 44 42 40 39 36 34 33 34 35 36 32 31 28 27 28 30 33 36 42 41 39 36 31 29 30 31 39 44 46 44 42 42 37 31 32 34 38 44 47 46 42 39 37 41 47 54 61 63 61 58 49 43 35 32 33 35 36 36 33 34 36 35 33 31 31 32 29 29 31 35 41 49 56 60 57 50 41 35 30 30 39 50 73 87 104 116 120 116 102 88 74 70 64 60 58 60 63 66 68 70 72 68 59 48 38 33 30 31 34 39 42 41 38 34 29 27 29 37 43 48 54 61 61 60 57 53 47 42 37 35 34 33 32 32 33 36 39 41 42 42 40 36 32 30 31 33 35 37 39 36 32 29 31 33 37 41 46 47 45 40 37 35 29 29 29 31 33 36 39 41 41 39 36 33 30 28 27 26 28 29 30 27 23 22 25 29 34 39 44 47 46 43 41 40 35 35 36 39 43 47 48 47 44 41 36 32 30 32 35 37 39 39 38 36 33 29 26 24 19 19 20 21 23 24 25 25 29 29 28 26 23 20 16 14 12 13 13 14 14 14 13 13 17 16 15 13 12 12 12 12 11 11 10 10 10 11 12 12 13 13 13 14 14 15 15 15 19 19 19 18 17 16 15 14 14 14 14 13 12 11 10 9 10 10 10 9 9 9 8 8 7 7 7 6 6 5 5 5 4 4 4 3 3 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 8 8 8 9 9 9 10 10 10 10 11 12 12 13 14 14 15 15 15 15 15 15 15 15 13 13 13 12 12 12 11 11 13 13 13 13 13 14 15 15 19 19 19 19 20 20 20 21 21 20 19 18 18 18 19 20 19 19 19 19 19 19 20 20 22 23 24 23 22 22 24 26 29 31 35 38 42 47 53 57 66 68 73 80 86 86 82 78 64 56 44 33 28 29 33 37 48 49 49 46 41 36 34 33 33 36 43 52 58 59 55 50 44 42 40 38 40 43 47 50 46 46 44 39 35 36 43 49 61 74 89 98 103 103 98 90 82 80 76 71 65 59 52 48 44 43 45 49 54 55 51 47 39 32 27 28 31 33 38 44 53 66 80 89 91 87 76 64 47 42 39 46 60 74 81 83 69 63 55 49 49 55 63 68 73 69 61 53 46 43 43 44 53 64 73 74 71 68 64 59 64 73 88 106 124 142 156 164 168 165 158 148 135 122 110 104 95 96 94 87 81 75 65 55 48 47 45 46 48 48 44 38 32 32 33 37 43 47 49 49 45 44 42 44 47 51 52 53 51 48 43 38 34 33 33 34 33 32 30 29 30 32 35 37 41 41 39 35 32 32 34 37 44 50 53 52 50 48 42 34 32 33 36 40 43 42 39 36 32 34 38 44 50 52 51 49 42 37 31 28 30 34 36 36 35 36 36 34 31 29 29 30 30 30 32 34 39 45 51 54 52 45 38 32 26 25 34 44 65 79 97 110 116 113 102 90 80 75 69 63 61 63 67 70 73 76 78 75 66 55 45 39 31 32 35 38 41 39 35 32 25 23 25 31 37 40 46 52 50 49 47 45 41 36 33 31 34 33 33 33 34 36 39 40 40 40 38 35 32 30 32 34 35 37 37 34 29 26 27 30 37 41 46 47 45 40 37 35 30 30 30 31 32 35 37 39 39 37 34 31 29 28 28 28 29 31 31 28 25 25 29 33 41 46 52 55 54 50 47 45 38 37 38 41 45 48 48 48 42 38 32 28 26 28 32 35 40 40 39 36 33 29 25 23 20 20 21 22 23 25 26 26 27 27 26 24 22 19 17 16 17 18 19 19 20 19 19 19 19 18 16 15 13 12 12 12 12 11 11 10 10 11 11 12 13 13 13 14 14 14 15 15 18 18 18 18 17 16 15 14 13 13 13 13 12 11 9 8 10 9 9 9 8 8 8 7 7 7 7 6 6 5 5 5 4 4 4 3 3 3 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 8 8 8 8 9 9 9 10 10 10 11 12 12 13 14 14 15 15 15 15 15 15 15 15 14 14 13 13 13 12 12 12 13 12 12 12 12 13 14 15 18 18 19 19 20 20 20 20 20 19 19 18 19 19 20 21 20 20 20 19 19 19 19 19 21 22 22 22 20 21 23 25 27 30 33 36 39 42 46 49 58 61 68 77 84 87 87 85 71 63 51 38 30 26 27 28 37 40 43 43 41 38 37 37 38 40 46 53 58 60 58 56 51 48 45 42 41 44 47 49 49 49 47 42 38 38 43 48 61 76 94 107 117 120 115 108 96 90 82 74 67 61 55 51 44 45 49 57 65 68 65 62 51 41 31 28 29 32 38 45 52 63 74 80 82 79 71 61 46 43 42 48 60 69 73 73 60 57 53 52 57 67 78 85 91 86 75 63 51 45 44 45 59 70 79 79 73 67 59 52 55 70 93 117 141 162 180 191 192 188 178 165 148 130 115 107 102 106 107 102 97 88 75 63 52 49 46 46 48 47 43 40 35 35 37 41 46 49 50 50 44 42 41 44 51 60 66 70 69 64 55 46 39 34 32 31 34 33 32 32 33 35 37 38 40 39 37 34 32 34 38 42 50 58 64 65 62 58 48 39 33 33 34 36 38 38 36 33 27 28 29 33 37 39 39 38 33 29 25 24 27 31 35 37 38 38 37 33 29 26 26 27 30 30 31 33 36 40 44 46 45 40 34 29 24 22 28 38 55 70 88 101 108 109 101 91 83 78 71 65 63 66 71 75 80 83 86 83 74 62 51 45 33 34 36 38 39 37 32 28 23 20 22 27 31 32 36 41 40 40 40 39 37 34 32 30 33 33 34 35 36 37 38 39 38 38 36 34 32 32 34 37 39 40 39 34 28 24 26 28 36 41 46 48 45 41 37 35 31 30 30 29 30 32 33 35 35 33 29 27 26 26 28 30 30 31 32 30 28 29 35 40 48 54 61 65 63 57 51 48 42 40 40 42 44 46 45 44 37 33 28 23 23 26 32 35 42 41 40 37 33 28 24 21 20 20 21 22 24 25 26 26 25 24 22 21 20 20 19 19 22 22 23 24 25 25 25 24 22 21 19 16 15 13 13 12 12 12 11 10 10 11 11 12 13 13 13 13 14 14 14 15 17 17 18 17 17 15 14 14 12 12 12 12 11 10 9 8 9 8 8 8 7 7 7 6 7 7 7 6 6 5 5 5 4 4 4 4 3 3 3 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 7 7 8 8 8 9 9 9 10 10 11 12 12 13 14 14 15 15 15 15 15 15 15 15 15 14 14 14 13 13 13 13 12 12 12 12 12 13 14 15 17 17 17 18 18 18 19 19 19 19 19 19 20 20 21 21 21 20 20 20 20 19 19 19 21 22 22 21 20 20 22 24 26 29 32 34 35 36 39 40 53 56 62 69 76 80 82 82 75 68 58 47 39 33 31 31 31 35 40 42 42 41 41 41 43 46 50 55 59 62 62 62 60 58 53 49 47 48 49 50 53 52 50 46 42 41 44 47 59 74 95 112 126 132 128 120 103 94 82 72 65 59 54 50 45 48 55 66 76 82 82 79 64 51 38 31 30 31 38 46 51 60 67 70 71 70 65 57 44 43 43 49 58 64 65 63 57 54 51 52 60 73 87 96 99 94 83 68 55 47 46 48 60 72 82 82 75 66 55 46 49 67 94 122 147 170 188 200 196 191 181 167 149 131 116 107 104 110 115 115 111 102 86 72 57 50 45 46 47 45 43 43 40 41 43 47 52 54 53 52 44 41 41 46 56 70 81 88 90 83 71 58 46 38 33 31 35 35 35 35 36 37 38 38 38 37 34 31 30 33 38 43 55 64 72 74 72 65 54 43 35 34 33 34 36 37 35 34 28 26 24 25 28 30 30 30 25 23 21 21 25 31 37 40 42 42 39 34 28 24 23 24 27 28 29 32 34 37 40 41 42 38 34 30 25 22 28 37 51 66 83 94 100 102 97 89 80 75 68 64 63 68 74 79 84 88 90 87 77 63 52 45 37 37 38 40 40 37 31 27 25 22 22 26 28 28 31 36 37 38 41 42 42 40 38 36 34 35 36 37 38 38 38 37 36 36 36 34 33 35 39 43 47 47 45 38 30 26 27 29 35 40 46 48 46 41 37 35 30 29 28 26 26 27 28 29 29 27 23 21 21 24 28 30 29 30 31 29 29 32 40 46 55 61 69 72 69 61 53 48 43 42 40 39 40 39 38 36 30 27 23 20 22 28 35 40 45 44 42 38 33 28 23 20 18 19 20 21 22 23 24 24 22 21 20 19 19 21 22 23 25 25 26 27 28 28 27 27 24 23 21 18 16 14 13 13 13 12 11 10 10 10 11 11 12 12 13 13 13 14 14 14 16 16 17 16 16 15 14 13 10 11 11 11 10 9 8 8 8 8 7 7 7 6 6 6 7 7 7 6 6 5 5 5 5 5 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 7 7 7 8 8 8 9 9 10 10 11 12 12 13 14 14 15 15 15 15 15 15 15 15 15 15 15 15 14 14 14 13 13 13 12 12 12 13 14 15 15 15 15 16 16 17 17 17 20 20 20 20 21 21 20 20 20 20 20 20 20 20 20 20 22 23 23 22 20 20 22 24 26 29 31 33 32 32 34 35 44 48 53 59 64 69 73 76 78 74 67 60 52 46 43 41 37 40 44 46 45 44 45 45 49 51 55 58 62 64 66 68 70 68 64 60 57 54 53 53 54 53 51 48 45 44 44 46 56 71 92 111 127 135 131 123 102 92 77 67 61 57 53 49 45 49 57 70 84 93 95 93 76 62 46 37 33 33 39 46 50 56 61 61 61 62 58 53 43 42 43 48 54 58 58 57 55 51 49 50 60 75 90 100 100 95 85 70 55 46 45 47 57 71 84 86 79 68 54 43 45 62 90 119 145 167 184 193 192 187 176 161 144 127 113 105 100 110 119 123 122 114 98 83 61 51 43 44 45 43 44 47 47 48 51 55 59 60 58 55 45 43 42 48 61 78 93 101 107 99 86 70 55 44 36 33 36 37 37 37 37 37 36 36 35 34 31 28 27 30 35 40 55 65 74 76 74 68 56 44 37 35 34 35 37 39 38 37 30 27 23 22 22 23 24 23 21 20 20 21 25 31 39 44 46 45 42 36 30 24 22 22 23 24 27 31 34 37 39 40 41 38 35 33 29 28 34 43 55 68 83 90 93 94 90 84 75 71 66 63 65 70 77 82 88 91 92 88 77 63 51 45 41 41 42 43 43 40 34 29 29 25 23 25 26 26 30 35 41 45 49 53 54 51 47 44 37 38 38 38 38 37 37 36 36 36 36 35 36 40 46 50 54 54 50 43 33 27 26 28 34 39 46 49 47 42 37 35 28 27 25 23 22 22 23 23 23 21 19 17 18 22 26 29 27 29 29 29 30 35 45 53 64 70 77 79 74 64 54 48 42 40 37 35 34 32 29 26 22 20 18 18 22 30 38 44 49 47 45 40 34 28 23 19 16 16 17 18 19 20 21 22 21 21 20 20 21 23 25 27 29 30 30 31 31 30 30 29 25 24 21 19 17 15 14 14 13 12 11 10 10 10 10 10 12 12 12 13 13 13 14 14 15 15 15 16 15 15 14 13 10 10 11 11 11 10 9 8 8 8 7 7 7 6 6 6 7 7 7 6 6 5 5 5 5 5 5 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 6 7 7 7 8 8 8 8 10 10 11 12 12 13 14 14 15 15 15 15 15 15 15 15 16 16 16 15 15 15 14 14 14 14 13 13 14 14 15 16 15 15 15 16 16 16 17 17 21 21 22 22 21 20 19 18 19 20 20 20 21 21 22 22 25 26 26 24 22 22 24 25 28 30 31 31 30 30 32 33 36 39 44 48 52 57 64 68 77 76 74 70 65 60 56 54 52 54 54 53 50 48 48 49 52 56 60 63 65 67 70 72 77 76 74 70 66 62 58 55 52 51 49 47 45 44 43 43 53 66 84 103 119 127 123 114 93 82 68 59 56 54 51 47 44 47 55 69 85 96 101 101 84 71 55 45 40 37 40 46 49 53 56 54 54 55 53 48 42 41 41 44 49 52 54 54 53 52 51 54 63 76 90 98 96 93 85 70 54 44 42 44 58 74 89 93 86 73 57 44 42 56 81 109 137 158 171 178 176 169 157 142 125 110 98 92 94 105 118 126 127 120 104 89 62 49 40 42 43 41 44 50 52 54 58 62 65 65 61 58 49 47 46 52 66 83 99 108 116 109 95 79 63 50 40 35 37 37 38 38 37 35 32 31 31 30 28 26 26 28 33 37 51 60 69 71 69 64 54 43 36 35 35 37 41 43 43 42 35 31 26 22 21 21 20 19 20 20 21 21 25 31 40 46 49 49 47 41 34 27 23 21 21 23 27 32 35 38 39 39 40 37 35 35 33 34 42 52 62 73 84 87 87 85 82 78 72 69 66 65 67 72 78 82 88 89 90 85 75 63 53 47 45 45 46 48 49 46 40 36 33 27 24 25 26 27 32 38 51 56 63 69 69 64 57 52 42 41 40 39 37 36 35 35 34 35 35 36 38 43 51 56 58 58 55 47 36 28 25 25 33 38 46 49 48 43 37 35 27 25 23 21 20 19 20 20 20 19 17 17 19 22 26 28 27 28 28 28 31 39 50 59 73 78 84 83 76 65 54 47 39 36 33 32 31 29 26 23 18 18 18 21 27 35 43 48 53 51 48 43 36 29 23 19 14 14 15 16 18 19 20 20 22 22 22 23 25 27 28 29 34 35 35 34 34 32 31 30 24 23 21 19 17 16 15 15 14 13 12 11 10 10 10 10 11 12 12 12 13 13 13 13 13 14 14 15 15 14 13 13 10 10 11 11 11 11 10 9 9 8 8 8 7 7 7 6 7 7 7 6 6 5 5 5 6 5 5 5 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 6 6 7 7 7 8 8 8 10 10 11 12 12 13 14 14 15 15 15 15 15 15 15 15 17 17 16 16 16 15 15 15 15 15 14 14 15 16 17 17 16 16 17 17 18 18 18 18 22 23 23 23 22 20 18 17 18 18 19 20 21 23 23 24 28 28 28 27 25 24 26 27 30 31 31 30 29 29 32 34 36 38 40 41 42 45 51 56 67 69 72 75 75 74 71 69 71 70 67 61 55 51 50 51 55 59 64 67 68 69 72 74 80 80 80 78 73 67 60 56 47 46 44 43 43 41 40 38 45 56 71 88 103 111 106 97 79 68 54 48 48 48 46 43 41 43 51 64 80 94 100 102 89 77 62 53 46 41 42 45 47 51 53 50 50 51 48 44 41 40 39 40 43 49 53 55 58 59 61 65 71 77 83 87 86 86 82 70 56 47 46 49 64 81 98 103 95 81 62 48 42 51 70 96 123 142 151 153 147 140 127 112 98 86 78 74 84 97 111 120 122 116 100 85 62 47 37 39 41 40 44 53 55 57 61 66 68 67 62 58 54 51 50 55 69 86 101 110 118 111 99 84 68 54 43 37 37 37 38 38 36 32 28 26 25 25 26 26 26 29 34 38 46 54 60 62 61 58 50 41 32 33 35 39 43 46 47 46 43 38 33 29 26 25 22 21 20 21 21 22 24 30 39 45 51 52 51 46 38 30 25 22 22 24 29 34 37 38 38 38 37 34 33 34 35 38 48 59 66 77 85 85 81 79 76 72 69 67 65 64 66 69 73 76 80 81 82 78 69 60 53 49 48 48 50 53 54 52 47 43 40 33 28 28 29 32 39 47 64 71 80 86 85 77 67 59 47 45 42 39 36 34 34 34 32 32 33 35 38 45 53 59 64 64 62 54 42 31 26 24 32 38 46 50 48 43 38 34 27 25 23 21 20 20 20 21 20 19 19 20 21 24 27 28 27 28 29 30 33 43 56 66 79 82 85 83 74 61 50 43 35 33 31 31 32 31 30 28 25 26 27 31 37 44 50 54 57 55 51 45 38 30 24 20 14 14 15 17 18 19 20 20 23 24 25 27 29 30 31 31 36 36 35 34 33 31 29 28 23 22 20 18 17 16 16 16 14 13 12 11 10 9 9 10 11 11 12 12 12 13 13 13 12 13 13 14 14 14 13 13 10 11 12 12 12 12 11 11 10 9 9 9 8 8 8 7 7 7 7 6 6 5 5 5 6 6 5 5 5 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 6 6 6 7 7 8 8 8 10 10 11 12 12 13 14 14 15 15 15 15 15 15 15 15 17 17 17 16 16 16 15 15 16 16 15 15 16 16 17 18 18 18 19 19 19 20 20 20 24 24 24 23 22 19 17 15 17 18 19 20 22 23 24 25 29 30 30 29 26 26 27 29 32 32 31 29 28 29 32 35 41 42 41 38 35 36 40 45 54 59 67 75 80 83 83 82 84 81 75 67 59 53 51 52 56 60 66 69 69 70 73 76 80 82 83 82 77 69 61 56 43 42 41 40 40 39 37 35 37 46 60 74 89 96 91 82 66 55 43 38 40 42 41 38 38 40 46 59 76 90 98 101 92 80 66 58 50 44 43 45 46 50 51 48 48 49 46 42 41 39 37 37 40 47 53 56 66 68 72 75 77 77 76 75 76 79 78 70 59 52 53 57 70 88 105 110 102 86 66 51 43 49 63 86 111 127 132 131 125 118 106 93 81 73 68 66 76 89 104 113 115 109 93 78 62 46 35 38 40 39 44 54 56 58 62 67 69 67 62 58 56 53 52 57 70 87 101 110 116 111 100 86 71 56 44 37 37 37 38 37 35 30 26 23 20 22 25 26 28 32 36 40 42 49 54 55 54 53 47 39 30 31 34 39 45 48 49 48 50 46 40 36 33 30 27 25 20 21 22 22 23 29 37 44 52 54 54 50 42 33 26 22 24 27 31 35 38 38 37 36 34 32 31 33 34 39 50 63 68 78 85 83 78 75 72 69 66 65 63 62 62 64 66 68 71 72 73 70 63 56 51 49 49 50 53 56 58 56 52 48 47 39 33 33 34 38 47 56 75 82 93 99 97 87 75 66 50 47 43 38 35 33 33 33 30 30 31 33 37 45 54 60 69 70 68 60 48 36 29 26 31 38 46 50 48 43 38 34 27 26 24 22 21 21 21 22 21 21 21 23 24 26 28 29 29 30 30 31 35 46 60 70 79 82 84 80 70 57 45 38 32 31 30 32 34 35 35 34 35 36 38 42 47 53 58 61 59 57 53 47 39 31 24 20 15 15 16 17 19 20 21 21 23 25 28 30 32 32 32 32 34 34 33 32 30 27 25 23 21 20 19 18 17 16 16 16 14 13 12 11 10 9 9 9 11 11 11 12 12 13 13 13 12 12 13 14 14 13 13 12 11 11 12 13 13 13 12 12 10 10 10 9 9 9 8 8 7 7 7 6 6 5 5 5 6 6 6 5 5 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 6 6 6 7 7 8 8 8 10 10 10 10 10 10 10 10 12 12 13 13 13 14 14 14 16 15 15 15 15 15 15 15 15 15 15 16 16 17 17 17 19 19 19 20 20 21 21 21 23 23 24 24 23 21 18 17 21 22 22 21 20 22 26 29 30 32 35 36 35 34 34 35 33 33 33 32 31 32 36 39 41 42 42 39 33 30 32 34 44 49 57 64 70 76 82 86 92 89 83 75 66 58 51 47 53 61 67 70 73 78 80 78 77 79 82 85 84 76 63 53 42 38 34 33 36 39 39 39 41 46 53 63 74 83 80 73 61 51 40 37 40 43 42 39 39 39 42 51 63 77 88 94 86 82 72 62 58 58 53 47 47 46 46 46 46 46 45 45 43 40 36 33 35 42 52 60 67 77 85 86 83 78 71 63 67 69 70 67 62 60 63 67 80 92 104 108 106 95 72 50 40 40 52 76 98 109 115 120 110 99 85 75 65 57 56 59 66 77 92 104 105 97 84 75 53 42 34 35 38 42 50 59 56 59 63 64 63 61 59 58 55 55 57 62 71 84 95 102 106 102 94 82 68 54 43 37 35 36 37 36 32 29 28 27 27 33 37 39 43 45 42 35 41 40 39 42 46 47 44 40 32 33 35 39 44 49 54 57 55 52 49 46 43 38 33 30 27 25 22 21 23 28 33 37 51 52 54 53 48 40 32 27 26 27 30 35 38 39 36 34 30 29 28 29 33 43 54 62 72 77 81 80 74 67 63 61 62 63 64 62 59 57 56 57 62 61 58 56 53 51 50 49 48 51 57 63 67 66 61 56 52 44 37 36 39 44 55 65 80 91 101 101 95 84 70 58 48 41 34 31 32 33 29 26 27 26 28 32 35 39 50 62 71 77 78 68 54 42 32 24 29 34 42 49 51 47 38 32 23 23 23 26 28 30 29 27 31 30 28 27 27 28 29 30 29 28 29 32 39 49 59 65 80 81 80 74 63 51 41 36 28 29 32 36 40 44 48 49 47 48 51 54 57 60 62 63 63 58 51 44 37 30 23 18 14 15 16 17 20 22 25 26 28 30 32 34 35 35 35 34 36 34 31 28 25 23 22 21 18 17 16 15 15 15 16 16 13 13 12 11 11 11 12 12 12 12 12 13 13 14 14 14 14 14 14 14 14 14 14 14 13 13 13 13 13 13 13 13 11 10 9 8 8 8 8 9 8 8 7 6 6 6 7 7 6 6 6 5 5 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 6 6 6 7 7 8 8 8 10 10 10 10 10 10 10 10 12 12 12 13 13 13 14 14 15 15 15 15 14 14 14 14 16 16 16 17 17 18 18 18 18 19 19 20 20 21 21 22 24 24 25 26 25 24 22 21 22 23 22 21 20 21 24 27 29 32 36 37 36 34 34 34 32 32 33 32 32 35 40 43 47 48 47 42 35 31 31 32 34 39 45 52 58 66 73 78 87 85 81 74 66 57 49 44 50 58 67 71 75 80 79 76 75 75 76 78 78 73 63 55 44 39 34 33 35 39 41 42 39 44 50 57 68 75 73 66 61 53 45 43 47 49 46 42 41 40 41 47 58 70 80 85 81 78 72 65 63 63 58 50 47 45 44 44 46 48 49 50 47 43 38 33 33 39 49 56 71 81 89 90 85 79 69 60 53 58 63 66 66 66 67 68 78 88 99 104 102 91 69 49 36 37 49 74 97 109 116 121 109 97 82 71 62 55 55 58 64 72 85 93 93 85 73 65 50 41 35 37 41 44 51 59 56 58 61 61 60 58 56 55 57 57 59 63 70 78 86 91 93 90 83 73 61 50 40 35 36 38 39 37 34 30 29 28 32 39 45 49 52 53 47 39 38 36 35 38 42 43 40 37 33 34 35 38 43 48 53 56 58 56 54 52 49 44 37 33 29 27 24 22 24 28 33 36 46 49 52 54 51 45 38 33 28 28 30 33 36 37 35 33 30 29 28 27 31 39 49 57 65 69 72 70 64 58 55 55 56 58 59 58 55 51 49 49 50 49 48 47 46 46 46 46 49 52 57 63 67 66 61 57 51 43 36 35 38 43 54 64 80 90 99 98 92 81 67 56 45 39 33 30 32 32 29 25 24 23 24 28 32 37 49 61 74 80 81 71 57 45 34 25 28 33 40 47 50 46 38 31 25 25 27 30 34 36 36 35 35 33 31 29 28 28 29 30 30 30 30 33 40 49 57 62 70 71 70 64 54 43 34 30 29 32 36 41 46 50 53 54 53 54 55 56 59 61 62 63 59 54 48 41 35 29 23 18 13 13 13 15 17 20 24 26 31 32 34 35 36 36 35 34 34 32 29 26 23 21 20 19 16 16 15 15 15 16 16 17 14 13 12 11 11 11 12 12 12 12 12 13 13 14 14 14 15 15 15 15 15 15 15 15 14 14 14 14 14 14 14 14 12 11 10 9 9 9 9 9 9 8 7 6 6 6 7 7 6 6 6 5 5 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 6 6 6 7 7 8 8 8 10 10 10 10 10 10 10 10 11 11 12 12 12 13 13 13 13 13 13 13 14 14 14 14 17 17 17 17 18 18 18 19 17 18 19 19 21 21 22 23 25 26 28 29 30 29 28 27 25 26 25 23 21 21 23 25 29 32 36 38 37 35 33 33 31 32 32 33 34 39 45 49 55 56 54 48 39 31 29 29 26 29 33 37 43 50 58 64 73 73 73 69 63 54 45 40 44 54 65 72 78 82 79 74 70 68 66 67 69 68 63 59 47 42 37 35 37 41 45 47 48 52 57 62 71 79 78 72 68 63 58 57 59 58 53 47 42 39 38 42 50 61 69 74 73 74 73 71 71 71 64 55 47 44 41 41 45 50 55 57 52 48 41 35 32 36 45 51 72 83 92 92 87 78 65 54 44 49 57 66 72 72 69 65 71 80 89 94 93 82 63 45 31 34 48 73 98 115 123 127 113 99 81 69 60 54 54 58 63 68 75 80 78 70 60 53 46 40 37 40 45 48 53 58 57 57 58 58 57 54 52 51 57 58 61 64 67 71 74 75 76 74 69 63 55 47 40 36 40 41 42 41 37 33 31 31 39 48 58 64 67 64 55 44 36 34 32 35 39 41 39 37 35 35 36 38 41 46 51 53 61 61 60 60 57 51 42 37 30 28 24 22 23 27 32 35 41 45 51 55 54 50 43 39 30 29 28 30 32 34 33 32 29 28 26 25 26 33 42 48 56 59 61 58 52 47 46 47 47 50 53 52 48 43 40 38 37 37 38 39 40 41 42 42 47 50 54 60 63 63 59 55 49 40 33 32 35 40 51 61 75 84 91 89 82 72 60 49 40 36 31 30 31 30 27 24 21 19 20 24 28 34 47 60 76 83 85 76 62 49 36 27 27 31 37 44 47 44 37 31 25 26 29 34 39 43 44 44 40 38 34 31 28 28 28 28 30 30 31 34 39 46 52 56 59 59 58 52 43 35 28 25 30 34 41 48 54 57 59 59 56 56 56 56 56 57 58 58 53 49 43 38 33 28 22 18 15 14 13 13 16 20 24 27 33 34 35 36 36 35 34 33 30 29 26 23 20 18 17 16 14 14 15 15 16 17 18 18 15 14 13 12 12 12 12 12 13 13 13 13 14 14 14 14 15 15 15 15 15 15 15 15 14 14 14 14 14 14 14 14 13 12 11 10 10 10 10 11 9 8 7 6 6 6 6 7 6 6 6 5 5 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 6 6 6 7 7 8 8 8 9 9 9 9 9 9 9 9 10 11 11 11 12 12 12 12 12 12 12 13 13 13 13 14 16 16 17 17 17 18 18 18 17 18 18 19 21 22 22 23 25 27 29 32 33 34 33 33 30 30 29 26 23 22 23 24 27 31 36 38 37 35 34 33 31 32 33 34 36 41 48 54 60 61 60 52 41 32 27 26 25 26 27 28 30 35 41 46 53 56 58 59 55 48 40 35 38 49 62 72 81 85 81 74 65 60 55 54 58 62 64 64 52 48 43 40 42 47 52 56 62 67 71 76 85 93 93 89 84 81 78 76 75 69 60 52 41 38 36 38 45 53 60 64 67 72 75 77 79 78 68 57 47 42 37 37 43 51 58 61 58 54 46 38 34 36 42 47 65 76 86 87 82 73 60 49 45 47 54 64 72 72 65 58 62 67 74 79 78 69 52 39 30 36 53 79 107 128 138 141 124 107 86 72 62 56 55 58 62 64 67 67 64 57 50 45 42 41 42 46 51 54 56 57 58 57 55 55 54 52 50 48 54 56 59 62 63 63 63 62 62 61 60 57 53 49 44 42 45 47 48 46 42 38 36 36 46 57 69 76 78 73 60 46 37 34 33 35 40 43 42 40 37 36 36 36 39 43 47 50 61 62 63 64 62 55 45 38 30 27 24 21 22 25 30 33 39 44 50 55 55 51 45 40 31 29 27 27 29 30 31 30 29 27 25 22 22 27 34 40 48 50 51 47 41 38 38 40 40 44 48 48 43 37 32 29 30 31 33 35 36 37 38 39 41 43 47 51 55 55 52 49 44 36 29 28 30 35 45 55 64 72 78 75 68 60 50 41 36 33 31 30 30 29 26 23 20 18 19 22 26 32 45 58 74 82 86 78 65 51 38 27 25 28 34 41 44 42 37 32 24 25 28 35 42 47 49 49 43 40 35 30 27 25 25 25 28 28 30 33 37 42 46 49 52 52 49 44 36 30 27 26 31 36 44 52 57 60 60 60 53 52 50 49 48 48 49 49 47 43 39 34 31 27 22 18 17 16 14 13 16 20 25 28 32 32 33 34 33 32 30 29 26 25 23 20 18 16 15 14 13 14 16 17 18 19 20 20 16 16 14 13 13 12 13 13 13 14 14 14 14 14 14 14 16 16 16 16 16 16 16 16 15 15 15 15 15 15 15 15 14 13 12 11 11 11 11 12 10 9 8 7 6 6 6 6 6 6 6 5 5 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 6 6 6 7 7 8 8 8 9 9 9 9 9 9 9 9 10 10 10 10 11 11 11 12 12 12 12 13 13 14 14 14 16 16 16 16 17 17 17 18 18 18 19 20 20 21 22 22 25 27 30 33 35 36 36 36 33 34 33 30 26 24 24 25 26 30 35 37 37 36 35 36 33 34 34 34 36 42 49 55 62 63 62 56 44 34 28 26 28 29 28 26 24 24 26 29 35 38 42 45 44 40 35 32 34 45 58 70 82 89 86 79 63 55 47 44 48 56 63 66 57 54 50 48 48 53 60 65 72 79 85 91 100 109 111 109 105 102 97 93 86 75 62 53 37 35 34 36 41 49 54 57 63 70 78 83 86 84 72 59 48 41 33 33 40 50 57 61 60 57 50 42 37 37 41 45 53 64 74 75 72 65 54 44 44 44 49 58 67 68 62 54 53 54 57 62 62 54 42 34 34 43 63 91 121 144 154 155 136 117 94 77 66 59 56 58 58 58 57 55 52 47 43 41 42 45 50 55 60 63 61 58 60 57 53 52 52 51 49 46 48 50 53 56 57 57 55 54 51 52 54 54 54 53 51 50 53 54 55 53 49 45 43 42 53 64 77 84 84 77 61 46 34 33 33 37 43 46 46 44 39 38 36 35 37 40 44 47 56 58 61 64 62 55 45 38 29 26 22 20 21 24 28 32 40 44 49 53 52 47 41 37 30 27 25 24 26 28 28 28 28 26 23 20 19 23 29 34 40 42 42 38 33 30 31 33 36 40 45 45 41 34 28 25 27 28 30 31 32 32 32 32 32 33 36 40 44 44 43 40 37 30 24 24 26 30 38 47 54 61 65 62 57 51 44 37 34 33 32 32 31 29 25 23 21 19 20 23 25 31 43 55 68 78 84 79 67 53 39 28 24 27 32 38 42 41 37 33 25 27 30 37 44 49 51 52 43 39 33 27 23 22 22 23 24 26 29 32 36 40 43 44 48 46 42 36 30 27 26 27 31 36 43 51 55 56 55 54 46 45 43 41 40 41 42 43 43 40 36 32 30 26 22 19 18 16 13 12 14 18 22 25 27 28 28 29 28 26 24 23 22 21 20 18 16 16 15 15 15 16 18 21 22 23 23 23 19 18 17 16 15 14 14 14 15 14 14 14 14 14 14 14 16 16 16 16 16 16 16 16 15 15 15 15 15 15 15 15 14 14 13 12 11 11 12 12 10 9 8 7 6 5 5 5 6 6 6 5 5 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 6 6 6 7 7 8 8 8 8 8 8 8 8 8 8 8 9 9 9 10 10 10 11 11 12 12 12 13 14 15 15 15 16 17 17 17 18 18 18 19 19 19 20 20 20 20 21 21 23 25 28 32 34 35 36 36 34 35 34 32 28 25 24 24 25 29 33 35 36 37 38 40 38 37 36 35 36 40 47 53 60 63 64 59 49 39 33 31 31 33 33 31 27 24 22 22 25 27 30 33 34 33 32 30 32 41 54 68 82 93 92 86 68 57 44 38 41 49 57 62 60 59 57 55 55 60 67 72 82 91 100 107 115 124 128 126 120 116 108 99 87 73 58 49 34 33 32 34 39 44 47 49 58 67 78 86 91 89 76 63 50 41 31 29 36 46 53 55 57 55 51 45 40 39 40 43 42 52 60 62 60 56 50 42 39 40 45 54 64 66 62 56 50 46 45 48 49 44 37 34 39 52 74 102 132 155 163 160 141 120 96 79 68 60 56 55 50 49 47 45 43 42 41 40 47 54 62 68 73 74 69 62 59 55 50 48 50 50 48 46 43 44 47 49 50 51 51 50 47 49 52 55 58 59 59 59 61 63 63 61 57 52 50 50 59 69 81 86 85 76 59 44 30 30 32 38 46 50 49 47 41 39 36 34 34 37 41 44 49 51 56 60 59 53 44 37 28 25 22 20 21 25 29 33 41 44 47 48 46 41 35 31 27 25 23 23 24 26 27 26 26 25 22 20 19 21 27 32 35 37 38 35 29 26 27 29 35 39 43 43 40 33 28 25 24 25 26 27 27 26 25 24 25 25 27 30 34 35 35 33 31 25 22 24 25 27 33 40 46 53 56 53 49 47 43 38 34 35 35 35 33 29 25 23 24 22 22 25 26 29 39 49 60 71 80 78 68 55 41 30 23 26 30 36 41 41 38 35 30 31 34 39 46 50 52 52 40 37 31 25 21 20 21 22 23 26 31 36 40 44 45 46 45 43 37 30 25 23 25 28 32 36 41 47 49 48 46 44 39 38 36 35 35 37 40 41 41 39 35 32 30 27 23 20 17 15 13 12 12 15 18 20 21 22 23 23 23 21 20 18 19 18 18 17 17 17 18 18 19 20 23 25 27 27 26 26 22 21 20 18 17 16 16 16 15 15 15 15 14 14 14 14 15 15 15 15 15 15 15 15 14 14 14 14 14 14 14 14 14 13 12 11 11 11 12 12 11 10 8 7 6 5 5 5 6 6 6 5 5 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 6 6 6 7 7 8 8 8 8 8 8 8 8 8 8 8 8 8 9 9 9 10 10 10 12 13 13 14 15 16 16 17 19 19 19 20 20 21 21 21 21 21 20 20 20 20 19 19 21 23 26 30 32 33 34 34 33 34 33 31 27 24 23 23 25 27 30 33 34 37 41 44 42 41 38 35 34 38 44 49 57 62 65 62 54 45 40 38 35 39 43 44 41 36 32 30 27 27 27 27 28 29 30 30 31 39 50 64 82 96 99 95 77 64 47 36 35 42 49 54 61 61 61 59 59 63 70 75 86 96 106 114 122 130 133 132 124 119 108 95 79 64 50 42 31 31 31 34 37 39 40 39 51 62 76 87 95 94 82 68 51 41 29 27 33 42 46 48 50 50 49 46 42 39 40 41 37 45 52 52 51 50 47 42 40 43 51 61 68 69 65 60 52 44 39 41 43 39 37 38 44 59 82 108 137 157 161 155 135 115 91 76 66 57 52 51 45 44 43 42 42 43 45 46 55 65 75 81 86 86 78 68 57 51 45 44 46 48 47 44 41 41 41 42 44 45 47 48 50 53 57 62 66 68 70 70 69 70 70 68 63 59 57 56 65 74 83 86 84 74 57 42 29 30 35 43 52 56 55 52 43 40 36 33 33 35 38 41 43 45 50 55 56 51 43 37 28 26 23 22 23 27 32 36 41 42 43 42 39 34 29 26 24 22 21 22 24 26 25 25 24 24 22 20 19 22 28 32 37 39 41 38 33 30 30 31 34 38 41 42 38 33 29 27 22 23 24 25 25 24 22 21 22 21 22 25 29 31 31 30 28 24 23 26 27 27 30 36 38 44 47 45 43 43 42 38 36 37 39 38 35 30 26 23 25 23 24 26 26 26 33 42 52 66 77 78 70 58 44 33 24 25 30 35 40 41 39 36 32 32 34 38 43 47 47 47 39 35 29 23 20 20 22 24 25 29 36 43 48 51 52 53 46 43 36 28 23 23 27 30 34 37 40 43 43 40 37 35 31 30 28 29 31 34 38 41 42 39 35 32 30 28 24 21 20 19 17 16 15 16 17 18 17 18 19 20 19 18 17 16 17 17 17 17 18 19 21 22 23 25 28 30 31 31 29 29 25 24 22 21 19 19 18 18 16 16 16 15 15 14 14 14 15 15 15 15 15 15 15 15 14 14 14 14 14 14 14 14 13 13 12 11 10 10 11 11 11 10 9 7 6 5 5 5 6 6 6 5 5 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 6 6 6 7 7 8 8 8 8 8 8 8 8 8 8 8 8 8 8 9 9 9 10 10 13 13 14 15 16 17 17 18 21 21 22 22 22 23 23 23 22 22 21 20 20 19 18 18 20 22 25 28 30 32 32 32 31 32 32 30 26 23 21 21 24 26 29 31 34 38 43 47 45 43 40 35 33 36 41 46 56 61 65 64 58 50 45 43 38 44 51 55 54 50 45 42 31 30 28 26 26 27 29 31 31 38 48 62 81 98 103 100 84 70 50 36 32 37 43 47 60 61 62 61 61 64 70 76 80 91 103 110 118 125 127 125 123 116 104 89 72 56 43 35 30 30 31 33 35 36 34 32 47 59 74 87 96 97 85 72 52 41 29 25 31 38 42 42 45 46 47 45 42 39 39 39 38 44 48 47 46 47 46 43 46 51 61 70 75 74 68 63 56 45 38 39 41 39 39 43 47 63 86 110 137 155 156 148 128 108 85 71 63 55 49 47 44 43 43 43 45 48 50 52 60 72 84 90 94 94 85 72 55 49 42 41 44 46 45 43 41 40 39 38 39 42 45 47 56 59 63 69 73 76 78 79 73 74 74 72 67 63 61 60 68 77 84 85 82 73 56 42 30 32 39 49 58 63 61 57 44 41 36 32 32 34 37 40 39 42 47 52 53 50 43 37 29 27 24 23 25 30 35 39 40 40 40 38 35 31 27 24 22 21 20 22 24 26 25 24 23 23 22 20 20 23 29 33 41 44 47 45 40 36 35 36 34 37 40 41 38 33 30 29 21 23 25 26 26 25 23 22 21 20 21 23 27 30 30 29 26 23 24 28 29 28 30 34 30 36 40 38 37 39 39 37 37 39 41 40 36 30 26 23 25 24 25 27 25 24 29 37 49 63 76 78 71 60 46 35 24 25 29 35 40 41 40 38 31 31 32 35 39 42 42 41 38 34 28 23 21 21 24 26 28 33 41 49 55 58 59 59 49 45 38 30 25 25 29 34 37 38 40 40 39 35 32 29 23 23 22 23 26 31 36 39 43 40 36 33 31 28 25 22 25 24 23 21 20 19 19 19 15 16 17 18 18 17 16 15 16 16 16 17 19 21 23 24 26 28 30 33 33 33 31 30 27 26 24 22 21 20 20 20 16 16 16 15 15 14 14 14 14 14 14 14 14 14 14 14 13 13 13 13 13 13 13 13 13 12 11 10 10 10 10 11 11 10 9 7 5 5 4 4 6 6 6 5 5 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 8 8 8 8 8 8 8 8 9 9 9 10 10 9 8 8 9 9 9 9 9 9 9 9 12 12 13 14 16 17 18 18 20 21 23 25 26 26 25 24 25 24 23 23 24 23 21 19 20 20 20 20 21 22 23 24 26 27 27 27 26 23 20 18 23 25 28 33 38 42 45 47 47 46 42 35 30 30 36 41 54 65 73 71 64 58 52 47 50 53 59 68 74 73 66 60 48 39 28 24 26 30 32 31 35 38 45 58 74 90 102 109 96 83 65 50 41 38 43 49 56 57 59 61 63 64 63 63 72 77 86 96 104 109 111 112 109 102 91 75 58 43 33 27 27 35 40 37 33 32 30 27 41 52 70 88 98 96 85 75 55 43 32 30 32 33 34 37 33 35 37 38 39 40 43 46 45 46 46 45 44 44 46 48 47 55 62 66 71 76 75 71 59 54 47 43 43 45 47 47 58 68 87 109 126 132 130 126 106 94 77 63 54 49 45 43 47 43 44 51 56 57 62 69 81 86 95 105 109 102 86 73 57 44 36 41 49 49 47 46 44 43 43 42 43 46 51 55 61 64 69 74 77 78 78 77 78 77 75 73 70 68 66 65 73 77 81 84 79 65 49 37 28 33 42 54 64 66 62 57 44 38 31 28 30 31 31 30 36 39 44 50 53 53 48 44 38 35 30 27 26 29 32 35 38 38 35 31 26 22 21 22 23 24 24 24 23 22 21 20 18 19 19 19 21 26 33 38 49 54 57 56 54 52 46 39 42 39 38 39 36 29 25 26 25 26 27 27 26 26 28 31 25 26 28 30 31 31 31 30 26 26 27 27 27 28 28 28 30 30 29 30 31 32 34 36 39 41 42 40 36 31 27 25 22 26 28 26 23 23 28 33 43 54 65 70 69 64 52 41 29 26 26 32 41 44 40 34 35 34 32 32 34 36 36 35 36 33 30 27 27 29 32 35 38 45 53 59 67 73 71 66 56 47 36 27 25 28 32 35 44 43 41 38 33 29 26 24 19 20 22 26 29 34 37 39 42 40 37 33 31 31 31 32 32 32 33 32 29 26 22 20 21 19 17 15 14 14 15 16 16 16 16 17 19 22 25 27 34 33 33 32 31 30 30 29 25 24 24 23 22 21 20 19 16 16 15 14 14 13 12 12 10 10 10 11 11 12 12 12 14 14 14 13 13 12 12 12 12 12 11 10 10 9 8 8 9 9 8 7 7 6 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 8 8 8 8 8 8 8 8 8 9 9 10 10 9 9 8 9 9 9 9 9 9 9 9 11 12 13 14 15 16 17 18 20 22 24 26 27 28 27 27 27 26 24 24 25 24 22 19 19 18 18 18 19 20 21 21 24 25 26 26 25 23 20 18 23 25 28 32 37 41 44 46 46 45 40 33 27 28 34 39 52 65 76 77 74 71 66 61 57 59 65 74 81 82 77 72 58 48 36 30 30 34 36 36 37 38 43 53 68 83 97 104 102 91 75 60 49 42 42 44 51 52 55 58 61 62 61 60 60 64 70 78 85 90 94 95 94 88 76 62 48 36 29 26 34 43 49 46 41 37 32 27 38 49 67 85 95 93 82 73 56 45 35 33 34 34 34 36 34 35 37 37 38 40 45 48 46 47 48 48 47 47 49 51 53 61 68 71 75 79 77 73 61 56 50 46 45 46 47 47 54 62 77 95 109 114 112 108 92 83 70 60 53 50 47 45 45 44 49 59 67 71 78 86 91 95 103 111 114 105 90 77 61 48 40 45 53 57 57 58 53 52 50 48 49 52 56 59 63 65 69 73 75 75 74 73 73 73 72 71 69 68 66 66 71 75 79 81 77 64 49 38 31 36 45 57 66 67 62 57 44 38 31 28 30 32 31 30 34 36 41 48 53 55 53 50 43 39 33 28 26 28 31 33 35 35 33 29 25 22 21 22 24 24 25 26 26 25 23 22 20 20 19 19 21 27 35 40 55 62 67 67 65 62 54 46 43 38 35 35 32 27 26 28 28 29 31 31 30 30 31 33 29 31 33 35 36 35 33 32 28 28 27 27 27 27 27 27 26 26 25 25 27 29 31 32 37 39 41 40 36 31 27 24 22 25 27 25 22 23 27 32 40 51 63 68 68 63 52 40 29 26 25 31 39 43 40 36 34 32 30 30 31 33 32 31 31 30 30 31 34 38 42 45 47 54 62 68 75 80 77 71 57 48 36 28 27 31 36 40 46 44 41 37 33 28 25 23 20 21 23 25 29 33 36 38 39 37 34 33 33 34 37 39 42 43 43 41 38 33 28 25 23 22 20 18 17 16 16 16 17 17 17 18 20 23 26 27 32 32 31 30 29 28 27 27 24 23 23 22 22 21 20 20 16 16 15 14 13 12 11 11 10 10 10 10 11 11 12 12 14 14 13 13 13 12 12 12 12 12 11 10 10 9 8 8 9 9 8 7 7 6 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 8 8 8 8 8 8 8 8 9 9 10 10 10 10 9 9 10 10 10 10 10 10 10 10 11 11 12 13 15 16 17 17 21 22 25 28 30 31 31 31 30 28 27 26 27 25 23 20 17 17 16 16 16 17 18 18 21 22 23 24 23 22 20 19 22 23 27 31 35 39 42 44 45 43 37 29 23 24 30 36 52 66 80 86 86 85 80 75 65 66 71 79 86 89 86 82 66 56 42 34 33 35 38 39 41 40 41 47 58 73 87 96 103 97 87 74 62 52 45 41 44 45 48 53 57 59 58 57 49 50 52 56 61 67 72 75 76 70 60 48 37 31 30 31 44 54 61 59 51 43 34 26 33 45 62 79 88 86 76 68 56 46 38 37 37 35 34 36 36 36 35 35 36 40 46 51 49 50 52 52 51 51 52 54 53 60 67 69 72 74 71 66 59 55 50 48 47 47 47 46 51 56 65 77 85 89 88 86 75 70 63 57 54 51 49 48 46 48 56 69 80 87 94 101 102 105 110 115 115 106 92 81 66 55 48 53 63 69 72 74 65 62 58 55 55 57 61 63 65 67 69 72 72 70 68 66 66 66 67 67 67 67 66 65 69 71 76 78 74 63 50 40 36 41 49 60 68 68 62 55 42 36 30 28 30 32 31 30 31 33 37 45 53 58 59 59 51 46 38 31 27 27 29 32 32 32 31 28 25 23 23 24 26 27 29 30 30 28 26 24 22 21 20 19 21 27 36 43 59 68 76 79 77 72 62 52 43 36 31 29 27 25 28 32 33 35 38 38 37 36 36 36 36 38 41 43 42 39 36 33 28 28 28 27 26 26 25 25 22 22 21 21 23 25 27 29 34 36 38 38 36 32 27 24 22 24 25 24 21 22 26 30 36 48 60 66 67 62 51 40 30 27 25 29 37 42 41 38 33 31 28 27 28 29 28 27 28 30 33 37 42 48 52 55 58 65 72 77 81 84 79 71 54 46 35 28 29 36 44 50 52 49 44 38 32 27 23 22 20 21 22 25 28 31 33 35 33 32 32 32 36 42 47 51 57 57 56 53 48 42 35 32 28 27 25 22 20 19 18 18 18 18 19 20 22 25 27 28 29 29 28 27 25 24 23 23 22 22 22 22 22 21 21 21 16 16 15 14 12 11 10 9 10 10 10 10 11 11 11 11 14 13 13 13 12 12 12 12 12 12 11 10 10 9 8 8 9 9 8 7 7 6 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 8 8 8 8 8 9 9 9 9 10 11 11 12 12 11 11 11 11 11 11 11 11 11 11 11 11 12 13 14 15 16 17 21 23 26 29 32 33 34 34 32 30 29 28 28 27 24 22 18 17 16 16 15 16 16 17 19 19 20 21 21 21 20 19 20 22 25 29 33 37 40 42 43 40 34 26 20 21 27 34 54 68 84 93 96 96 90 84 72 72 73 77 83 86 85 82 64 55 42 33 31 34 39 42 45 43 41 42 49 61 76 86 96 97 95 87 77 66 54 44 38 39 42 48 55 59 58 56 46 44 41 40 43 49 56 61 64 59 51 41 33 31 35 40 53 64 73 71 61 49 36 26 32 42 58 72 78 74 66 58 51 43 38 39 39 37 36 38 38 38 36 35 36 40 47 52 53 54 55 55 53 53 54 56 52 59 65 66 67 67 62 56 52 49 46 45 45 46 46 45 49 51 55 60 65 68 69 69 64 63 61 59 57 54 52 50 49 54 64 77 88 96 101 105 107 109 111 113 110 102 89 80 69 64 62 68 79 86 88 88 75 70 63 58 58 60 63 65 65 67 68 69 67 64 60 58 57 58 60 62 63 64 64 63 65 67 71 74 71 63 52 44 42 45 52 61 68 66 59 52 39 34 29 27 29 31 31 29 28 30 34 42 52 60 65 67 60 53 44 34 29 27 29 31 29 30 30 28 26 25 27 28 31 33 34 35 34 31 28 26 25 23 21 19 20 27 37 44 58 69 79 83 82 76 64 53 42 34 27 25 24 24 30 37 40 43 46 46 44 42 40 40 41 43 46 48 46 42 37 33 27 27 26 26 25 24 24 23 22 22 22 23 24 26 28 30 33 34 35 36 36 32 27 23 22 23 23 22 21 21 25 28 34 45 57 63 64 61 51 40 31 27 25 28 34 40 41 40 35 32 28 26 26 27 26 26 31 34 38 44 50 54 58 60 66 72 77 79 80 79 71 62 47 40 32 29 34 44 54 61 61 57 49 41 33 26 22 20 20 20 21 23 25 27 29 31 29 29 31 35 42 51 60 65 71 70 68 63 56 48 41 36 32 31 29 27 25 23 22 21 20 21 21 23 24 26 27 28 26 25 25 23 22 21 20 20 21 21 21 21 21 22 22 22 17 16 15 13 12 10 9 9 10 10 10 10 10 11 11 11 13 13 13 12 12 12 11 11 11 11 11 10 10 9 9 9 8 8 8 7 7 6 6 6 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 8 8 9 9 10 10 11 11 11 11 12 13 14 14 14 13 13 13 13 13 13 13 13 13 11 11 12 13 15 16 17 17 21 23 26 30 33 34 35 35 32 31 30 29 30 29 26 23 20 19 18 17 16 16 16 17 17 17 18 18 19 19 18 18 19 20 23 27 31 35 38 39 40 38 32 25 19 19 26 32 53 67 85 97 104 106 102 95 81 77 73 72 75 76 75 73 57 49 38 30 29 34 41 46 48 46 43 41 43 53 66 76 88 96 100 96 88 77 61 47 37 36 38 46 55 61 62 60 49 44 37 32 33 38 46 51 57 55 49 40 33 33 40 47 61 73 82 80 69 56 41 29 33 41 53 62 65 60 53 48 44 39 36 39 40 38 40 43 42 42 41 39 39 42 46 50 55 56 56 54 53 53 55 57 58 65 69 69 67 65 58 51 43 41 39 39 41 43 43 43 44 45 45 46 49 52 56 59 61 62 63 63 60 56 52 50 50 58 70 82 93 101 104 104 105 106 106 105 102 94 85 79 74 75 80 89 99 104 102 97 82 75 65 59 59 61 63 64 63 64 65 64 62 57 53 50 48 50 53 56 58 59 59 58 59 61 65 68 68 63 55 49 45 47 52 59 63 61 53 46 35 31 26 26 28 30 29 27 27 28 32 39 49 59 65 68 63 57 47 37 31 29 30 31 29 30 31 30 28 29 31 33 38 39 39 39 38 35 32 30 30 28 24 21 21 27 35 42 55 66 78 82 82 76 64 52 41 33 25 23 24 26 33 42 47 49 52 51 48 44 42 41 42 44 47 48 46 41 35 31 24 24 24 24 24 24 24 24 26 27 29 31 33 34 35 35 34 33 33 34 35 33 28 24 23 23 22 21 21 21 24 26 32 42 53 58 60 57 49 40 30 27 25 27 33 38 41 41 37 34 29 27 27 27 27 27 32 35 41 47 53 58 62 63 71 75 77 76 73 69 60 49 38 34 30 32 41 53 63 70 69 64 54 43 34 26 22 20 21 21 21 21 23 24 26 27 28 29 33 40 50 61 71 77 83 81 76 70 61 52 45 40 35 35 33 31 29 27 25 24 23 23 24 25 25 26 26 26 23 22 22 21 20 20 19 19 20 20 20 21 21 21 21 21 16 16 15 14 12 11 10 10 12 12 11 11 11 11 11 11 13 13 12 12 12 11 11 11 11 11 10 10 10 10 9 9 8 8 7 7 7 7 6 6 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 9 10 10 11 12 12 13 13 13 14 15 16 17 17 17 17 15 15 15 15 15 15 15 15 12 12 13 15 16 17 18 18 20 22 25 29 31 33 34 34 32 30 29 30 30 30 28 25 22 21 19 18 17 16 16 16 16 16 16 16 16 16 16 17 17 19 22 25 29 32 35 37 37 36 32 26 21 21 26 32 47 62 81 96 108 114 111 105 88 81 72 66 65 64 63 61 49 43 35 30 30 35 43 49 50 49 47 43 43 48 59 68 83 95 104 102 96 86 68 51 40 38 38 46 57 66 69 68 56 49 38 30 28 33 41 46 54 54 50 43 35 34 40 46 64 76 84 82 72 59 45 34 34 40 48 53 52 48 44 41 41 37 36 38 40 39 42 47 50 51 51 49 47 46 47 49 54 54 52 50 50 52 57 60 64 70 74 72 69 65 56 47 39 37 34 34 37 40 41 42 39 39 37 36 36 40 46 51 60 63 66 65 61 55 51 48 50 61 74 85 94 101 102 98 97 97 96 94 90 85 80 76 77 84 94 103 112 115 109 100 84 75 63 56 56 59 61 61 59 59 60 59 56 52 47 44 41 43 47 50 52 52 52 51 51 53 57 61 63 61 56 52 47 47 49 53 56 53 46 40 31 27 23 23 26 28 27 25 25 25 28 35 44 52 58 60 59 54 46 38 32 29 29 30 29 30 31 30 30 30 32 35 42 42 42 41 41 40 39 38 38 35 31 26 25 28 34 39 52 62 73 77 77 72 61 51 39 32 26 25 27 30 37 45 52 53 53 51 46 42 39 39 40 41 42 42 40 35 30 27 22 23 24 25 26 27 28 29 33 36 40 44 46 46 44 43 37 34 32 32 33 33 29 25 24 23 22 21 21 22 24 25 31 39 47 51 52 51 45 38 29 27 26 28 32 37 40 41 39 35 31 28 28 29 30 30 32 35 40 47 53 59 63 65 71 74 73 69 64 59 50 40 31 31 33 39 50 61 70 74 72 65 55 44 34 28 24 23 23 23 22 22 23 23 24 25 30 33 39 48 59 71 81 87 91 87 80 71 61 53 46 43 37 36 36 35 33 30 28 27 25 26 26 26 25 24 23 22 20 20 20 20 20 20 20 20 21 21 21 20 20 20 20 20 16 16 15 15 14 13 13 12 14 13 13 13 13 12 12 12 12 12 12 12 11 11 11 10 10 10 10 10 10 10 10 10 7 7 7 7 7 7 7 7 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 11 11 12 13 14 14 15 15 15 16 17 18 19 19 19 19 18 18 18 18 18 18 18 18 13 14 15 16 17 18 19 19 20 21 24 27 30 31 31 31 30 29 28 29 31 31 29 27 22 21 19 18 16 16 15 15 16 15 15 14 14 14 14 15 16 18 20 24 27 31 33 35 34 34 33 28 23 23 28 32 42 56 74 90 103 111 109 103 89 79 66 57 53 52 50 48 41 38 32 28 28 33 41 47 51 52 51 48 45 47 55 62 75 91 104 105 102 96 79 61 45 41 40 47 61 72 77 76 65 56 44 34 30 33 41 46 54 56 55 48 39 35 38 43 59 69 77 74 65 54 42 33 32 37 42 44 42 40 38 38 43 39 37 39 40 40 44 50 58 61 63 62 58 53 49 48 48 48 46 45 46 52 60 66 74 80 83 80 75 69 59 50 43 39 35 33 35 38 40 41 39 38 35 32 31 34 41 47 58 62 65 64 58 52 47 45 52 63 75 83 89 93 89 82 83 83 82 80 76 73 71 71 75 85 96 104 111 113 105 94 78 68 55 47 47 50 53 53 54 54 55 55 52 47 43 40 37 39 43 46 47 46 45 44 42 44 48 53 58 58 55 53 47 46 45 46 47 45 39 34 27 24 21 21 25 27 25 23 22 22 24 29 37 43 47 49 52 48 42 36 31 29 28 27 28 29 30 30 29 30 32 34 42 41 41 42 43 45 47 48 46 44 39 34 30 30 34 38 47 56 65 68 68 65 57 47 37 32 28 29 31 34 40 48 53 53 51 46 40 36 33 33 35 35 36 35 33 29 25 23 22 23 25 27 30 33 35 36 39 44 51 56 58 57 53 50 42 37 31 30 32 33 30 27 26 24 22 22 22 23 24 25 28 35 41 42 43 44 40 34 27 26 27 29 33 36 39 40 40 36 31 28 29 31 32 32 35 37 40 45 50 54 58 60 65 66 64 58 54 50 42 33 31 33 39 48 59 68 73 75 67 61 51 41 33 29 28 28 27 27 26 25 25 25 26 26 33 37 45 56 68 79 87 92 90 85 75 64 54 46 41 39 37 37 37 37 35 33 31 30 27 28 27 27 25 22 20 18 18 19 19 20 21 22 22 23 22 22 21 20 20 19 19 18 16 16 15 15 15 15 15 15 15 15 15 14 14 14 13 13 12 12 12 11 11 11 10 10 10 10 10 10 10 10 10 10 7 7 7 7 7 7 7 7 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 12 12 13 14 15 16 16 17 16 17 18 20 21 21 21 21 19 19 19 19 19 19 19 19 14 15 15 17 18 19 20 20 19 21 24 26 28 29 29 29 28 28 27 29 31 31 30 28 22 21 19 17 15 14 14 14 16 15 14 13 13 13 13 13 16 17 20 23 27 30 32 34 32 34 33 30 26 25 29 33 39 52 69 83 95 102 100 93 86 75 60 49 44 42 41 39 36 33 29 25 25 30 38 43 51 54 54 51 47 47 53 59 67 85 101 105 106 104 90 72 49 44 42 49 63 76 82 82 72 63 50 38 34 36 43 48 57 60 60 53 43 36 38 41 51 60 67 64 56 47 36 28 30 34 38 39 37 36 37 39 46 42 40 41 40 40 45 52 64 68 71 70 65 58 51 48 43 42 41 41 44 52 63 71 87 92 95 92 86 79 68 58 49 44 38 35 35 38 40 41 41 40 37 33 30 33 40 47 56 60 63 62 56 49 44 43 54 65 76 79 81 82 75 65 71 71 70 68 65 64 64 65 71 81 92 98 104 106 97 86 70 59 46 38 38 42 44 45 50 51 52 52 49 45 41 38 35 37 40 43 44 43 41 39 36 38 42 48 53 55 54 52 47 44 42 42 42 40 35 30 25 22 19 20 24 26 24 22 20 20 21 25 31 37 39 40 45 43 39 34 30 27 26 25 27 28 29 29 28 28 31 33 40 40 40 41 45 49 53 56 52 50 45 39 34 33 35 37 42 50 57 60 60 58 51 43 36 32 29 32 34 36 42 49 52 51 48 42 35 30 29 29 31 31 31 30 27 24 21 20 22 23 26 29 33 37 39 41 43 48 57 63 66 63 58 54 45 38 31 29 31 33 31 28 27 25 23 22 23 24 25 24 27 32 36 37 37 39 36 31 26 26 27 30 33 36 39 40 39 35 30 28 29 31 33 33 42 42 42 44 46 48 50 52 57 58 55 49 46 43 36 28 33 37 44 55 65 72 74 74 62 56 47 38 32 30 30 31 31 30 29 28 27 27 27 27 36 41 50 61 73 83 90 94 85 79 68 56 46 39 35 33 36 37 37 37 36 34 32 31 29 29 28 27 24 21 18 16 18 18 19 20 22 23 24 25 23 22 21 20 19 18 18 17 15 15 16 16 16 17 17 17 17 16 16 16 15 14 14 14 12 12 12 11 11 10 10 10 10 10 10 10 10 10 10 10 7 7 7 7 7 7 7 7 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 9 10 12 14 15 17 17 17 16 17 19 21 24 25 26 26 23 22 22 23 25 25 24 22 23 21 19 18 19 20 19 18 21 20 20 22 25 28 29 29 27 27 27 26 26 26 25 25 24 23 21 18 16 15 14 14 13 13 13 13 13 13 13 13 18 20 22 25 29 32 34 35 35 34 34 33 33 32 31 31 41 47 57 68 78 84 87 89 73 67 58 48 41 37 35 35 33 28 26 28 30 31 36 42 52 54 56 56 55 54 55 56 74 85 97 107 112 109 95 81 62 51 45 52 66 77 86 92 87 74 59 48 39 35 39 46 60 64 67 62 48 36 31 33 39 41 47 51 46 38 34 36 33 35 37 35 31 30 33 36 41 46 49 46 41 41 47 54 64 71 76 75 72 67 57 48 43 37 34 36 43 53 70 84 97 108 116 112 101 90 79 71 66 60 52 45 41 39 37 36 40 39 36 33 33 36 43 48 56 59 60 55 47 42 43 46 56 67 79 81 73 63 57 56 52 55 61 66 66 62 59 60 67 72 79 85 88 84 77 70 49 44 37 31 30 34 40 45 48 47 45 44 44 42 39 37 36 36 37 40 43 44 43 41 37 38 41 46 52 55 56 55 48 43 38 34 32 30 29 27 24 24 23 23 23 24 25 25 24 24 23 24 25 27 30 31 35 32 29 28 28 28 27 25 27 26 25 23 23 25 29 32 34 37 42 45 46 50 56 61 57 54 47 39 32 29 31 33 36 42 48 52 51 48 45 43 40 38 36 35 36 39 43 45 44 41 36 31 27 25 24 24 28 28 27 24 21 19 19 20 25 30 37 41 42 40 39 39 44 47 55 63 69 67 59 53 41 36 31 29 31 33 33 32 28 28 28 28 27 25 24 23 23 24 27 29 31 31 31 30 29 29 30 31 33 34 35 36 31 31 29 26 25 28 33 37 46 46 45 42 40 39 41 43 49 48 45 41 37 35 36 38 40 48 58 65 67 65 62 60 47 44 41 38 37 38 40 42 39 35 32 32 31 28 29 33 44 48 54 62 70 77 81 84 75 67 54 43 36 33 31 30 34 36 38 40 39 37 34 32 29 27 25 23 21 20 19 19 18 20 22 25 26 27 27 26 27 26 23 21 18 16 15 15 16 17 18 19 19 19 19 18 15 15 14 14 13 12 11 11 10 10 10 10 10 10 10 10 9 9 9 10 10 11 11 11 9 9 9 9 9 9 9 9 7 7 7 6 6 5 5 5 6 6 6 5 5 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 10 11 13 15 16 17 18 18 17 18 21 23 25 26 27 28 26 25 25 26 28 28 27 25 25 23 20 20 21 21 20 19 21 19 19 21 24 27 28 27 26 26 26 25 25 25 25 25 23 22 20 18 16 15 15 15 14 14 14 14 14 14 14 14 19 21 23 26 29 32 34 35 35 35 35 34 33 32 32 31 35 39 47 56 63 69 72 73 63 60 53 46 41 38 37 37 35 30 27 29 30 31 36 42 51 53 57 58 59 59 60 61 73 84 97 107 113 110 97 83 63 52 46 53 67 79 88 95 92 80 64 52 42 38 42 49 61 66 71 67 55 41 35 34 34 35 40 44 41 35 33 36 36 38 38 36 32 30 32 35 43 48 52 50 45 45 50 55 68 75 80 80 77 73 64 55 48 41 37 39 46 59 77 93 108 118 125 120 109 99 90 83 75 69 61 52 46 41 38 36 41 40 39 37 37 39 45 49 57 59 59 53 44 40 42 45 61 71 80 79 67 53 45 42 47 53 62 69 70 66 62 61 61 63 66 70 71 68 61 56 42 39 33 29 29 33 39 43 49 47 45 44 43 41 38 36 37 37 38 41 45 47 46 45 41 42 44 48 52 55 56 55 46 42 35 31 29 28 26 25 25 25 24 24 24 25 25 25 25 24 24 24 24 25 27 28 30 28 27 28 30 31 29 28 25 24 23 22 22 24 28 31 33 36 40 42 44 48 54 59 56 53 47 39 32 28 29 30 34 39 44 47 47 45 43 42 39 38 36 36 37 38 41 42 39 37 32 27 24 22 21 21 27 27 26 23 20 19 21 23 32 37 43 47 46 44 41 40 42 45 52 60 64 62 55 49 37 34 30 30 32 33 33 31 28 28 27 26 25 24 23 22 21 22 24 26 28 29 30 30 30 30 30 31 31 32 33 33 30 29 27 25 25 29 35 40 48 49 47 44 40 37 36 37 42 41 40 37 35 36 39 42 54 60 67 70 67 61 55 52 40 39 38 38 39 40 42 43 41 36 32 31 30 27 29 34 40 45 54 63 69 73 74 73 65 57 46 37 32 29 28 28 33 35 37 38 38 35 32 30 27 26 25 23 21 20 20 20 19 21 23 26 27 27 27 26 25 24 22 19 17 16 15 14 17 17 18 19 19 19 19 19 15 15 14 14 13 12 12 11 10 10 10 10 10 10 10 10 9 9 9 10 10 11 11 11 9 9 9 9 9 9 9 9 7 7 7 6 6 6 5 5 6 6 6 5 5 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 10 12 13 15 17 18 19 19 19 21 23 25 27 29 29 30 29 28 28 30 32 32 31 29 27 25 23 22 23 23 22 20 20 18 17 19 22 24 25 25 24 24 24 24 24 24 24 25 21 20 19 18 17 17 17 17 17 17 17 17 17 17 17 17 21 22 24 26 29 31 33 34 36 36 35 34 34 33 32 32 31 33 37 42 47 51 53 54 50 49 47 45 44 42 41 40 38 32 29 30 31 32 36 42 49 53 58 62 63 63 65 66 72 82 95 105 112 111 99 86 65 55 49 55 68 81 92 101 99 87 71 56 45 39 43 51 63 71 79 77 66 53 43 38 30 29 32 35 35 32 34 39 42 44 43 39 32 29 30 32 43 49 54 54 51 50 53 58 70 77 83 83 82 79 72 64 56 48 43 44 52 67 88 106 121 129 134 127 115 106 98 93 86 81 72 62 52 44 39 36 40 42 43 44 44 46 49 52 61 61 59 51 42 38 41 45 64 73 80 76 62 45 35 31 45 55 68 77 79 75 69 65 58 56 54 53 51 49 44 41 36 34 32 31 33 37 41 45 50 47 44 42 41 39 36 34 36 36 38 41 47 50 52 51 49 48 48 50 54 56 56 55 48 42 35 30 28 28 27 27 26 26 26 26 26 26 26 26 27 27 26 25 25 24 24 24 24 24 25 28 32 33 32 30 23 22 20 20 21 25 28 31 33 35 37 38 41 45 51 55 54 52 46 39 31 27 26 26 31 34 39 41 40 40 39 40 36 36 36 36 36 37 37 37 33 31 27 23 20 18 18 19 26 25 23 21 19 20 24 27 38 43 48 50 48 44 40 38 38 41 47 52 55 53 47 42 31 30 30 31 33 34 33 31 29 28 26 24 23 22 22 22 20 20 21 22 24 27 30 32 33 32 31 30 29 29 29 29 27 26 25 23 25 31 40 47 54 54 52 47 40 34 30 28 31 32 32 33 34 38 44 48 63 67 71 70 64 54 46 41 31 33 36 39 42 44 44 45 42 36 31 29 28 26 29 34 35 41 51 60 65 65 61 59 49 43 35 28 25 25 25 25 32 34 35 36 35 32 29 27 25 25 23 22 21 20 20 21 21 22 24 26 27 28 27 26 23 22 20 17 16 14 14 13 16 17 18 19 19 19 18 18 15 14 14 13 12 12 11 11 9 9 9 9 9 9 9 9 9 9 9 10 10 11 11 11 9 9 9 9 9 9 9 9 7 7 7 7 6 6 6 5 6 6 6 5 5 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 11 12 14 16 18 19 19 20 21 22 24 27 29 30 31 31 32 31 32 33 36 36 35 33 30 28 25 24 25 25 24 22 19 17 16 17 20 22 22 22 22 22 22 23 23 24 24 25 21 20 19 18 18 18 19 19 19 19 19 19 19 19 19 19 23 23 25 27 29 30 32 33 36 36 35 35 34 34 33 33 33 33 34 35 36 38 40 41 38 40 44 47 49 50 49 48 44 37 33 32 32 32 36 43 49 54 60 64 65 66 66 67 69 79 91 101 109 110 100 89 69 59 53 59 71 84 97 107 106 94 78 62 48 40 44 52 68 80 91 91 82 68 53 43 32 28 28 31 33 34 38 44 51 52 50 44 36 29 28 29 40 45 51 54 53 54 57 60 68 75 80 81 81 82 77 71 66 57 51 52 60 75 98 116 129 135 136 125 112 102 96 91 92 88 81 70 58 47 40 36 39 43 47 51 52 54 56 57 65 65 62 53 43 39 42 47 62 70 78 74 61 45 36 33 48 63 80 91 94 90 81 73 62 57 50 44 41 38 36 35 36 35 36 37 40 44 48 51 50 47 44 41 40 38 35 32 34 34 35 40 47 53 57 58 57 55 53 53 54 56 55 55 50 45 38 33 32 33 33 33 30 30 29 28 27 27 26 26 31 31 30 30 28 26 24 23 22 23 25 29 32 33 31 29 23 21 20 20 23 27 30 32 33 33 33 33 36 41 47 50 51 49 45 38 30 25 23 23 27 30 33 34 34 34 35 36 33 34 35 36 36 35 33 32 29 27 23 20 18 17 18 18 23 23 21 19 19 22 27 32 41 45 49 50 46 40 35 32 33 36 40 43 44 42 38 34 27 29 31 34 35 35 33 31 30 28 26 25 23 23 23 23 21 21 20 21 24 28 32 35 36 34 32 29 27 26 25 25 26 25 23 23 26 34 45 53 61 61 59 53 43 32 25 21 24 25 28 30 34 41 49 54 61 64 66 63 55 45 36 32 26 30 36 42 46 47 47 46 40 33 27 25 24 23 26 32 33 38 47 54 56 54 49 45 35 30 25 21 21 22 23 23 31 32 32 32 31 29 27 25 24 23 22 21 20 20 20 21 22 23 25 26 27 27 26 25 20 19 17 15 14 13 13 13 14 15 16 17 17 17 17 16 13 13 12 12 11 10 9 9 9 9 9 9 9 9 9 9 9 9 9 10 10 11 11 11 9 9 9 9 9 9 9 9 8 8 7 7 7 6 6 6 6 6 6 5 5 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 11 12 14 16 18 19 19 20 21 23 25 27 29 31 32 32 33 33 33 35 37 38 37 36 32 30 27 26 26 26 25 23 19 17 16 16 19 20 20 19 20 20 21 22 23 24 25 25 22 21 20 20 20 20 21 21 21 21 21 21 21 21 21 21 23 24 25 26 27 29 30 30 34 34 34 34 34 34 34 34 34 34 32 31 31 31 32 32 32 36 44 51 57 59 59 59 52 44 38 36 34 33 37 42 48 54 60 65 66 66 65 64 66 74 84 93 102 106 99 89 73 63 57 61 72 85 100 111 115 104 89 72 56 47 50 58 77 93 106 107 98 84 66 51 39 33 30 32 35 38 43 50 59 60 59 52 42 33 29 28 34 39 46 50 52 54 57 61 65 70 75 76 79 83 83 80 78 69 62 62 68 82 102 120 133 137 134 120 103 92 85 81 88 87 83 73 61 49 42 39 40 45 52 57 59 60 61 62 68 69 66 58 48 43 45 49 61 70 77 74 62 50 44 42 58 77 98 109 111 107 95 82 68 61 51 43 38 37 36 35 37 38 40 42 46 50 53 55 52 49 45 42 40 38 36 34 33 32 34 39 47 55 60 62 61 58 54 52 53 53 53 53 49 45 39 37 37 38 40 40 36 35 32 30 28 27 26 26 34 35 35 35 33 30 27 25 25 25 27 29 31 31 28 26 24 22 22 25 30 34 35 35 34 32 29 29 32 38 43 46 48 46 42 35 27 22 21 21 25 27 29 29 29 29 30 31 30 31 33 34 34 32 30 29 27 25 23 20 19 19 20 21 21 21 21 21 22 27 33 38 46 49 51 49 43 37 31 29 29 31 34 35 35 33 31 29 27 30 35 37 38 36 33 32 31 30 29 28 27 27 27 27 25 24 23 23 26 31 36 39 39 36 33 28 25 23 22 22 25 25 24 24 29 38 49 57 68 68 65 57 45 33 24 19 20 23 27 32 37 43 50 56 58 59 58 53 45 36 29 26 28 33 40 46 49 49 46 44 35 29 23 21 20 19 23 29 33 36 40 44 44 42 38 35 25 22 19 18 20 22 23 24 29 29 30 30 29 27 25 24 23 22 21 20 19 19 20 20 21 22 24 25 25 24 23 22 18 17 15 14 13 12 12 13 12 13 13 14 15 15 14 14 12 12 11 11 10 9 8 8 9 9 9 9 9 9 9 9 9 9 9 10 10 11 11 11 9 9 9 9 9 9 9 9 8 8 8 7 7 7 6 6 6 6 6 5 5 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 10 12 13 15 17 18 19 19 21 22 24 26 28 30 31 31 32 32 32 34 37 38 37 36 34 31 28 27 27 27 25 24 19 17 16 16 18 19 19 18 19 20 21 22 24 25 26 27 24 24 23 22 22 22 23 23 22 22 22 22 22 22 22 22 24 24 24 25 26 26 27 27 30 30 31 32 33 34 35 36 33 32 31 29 28 27 27 27 30 35 45 55 63 68 69 69 61 52 44 40 36 34 37 42 46 52 61 66 68 66 65 64 64 70 76 84 93 99 95 88 75 65 58 61 70 83 99 112 120 112 100 86 70 60 63 71 89 107 121 122 114 100 79 60 48 40 34 35 38 41 46 52 62 65 66 61 51 41 35 33 32 36 41 45 48 51 54 57 60 65 68 69 75 84 89 89 91 83 76 74 78 87 104 119 132 135 129 113 94 82 74 69 77 79 79 74 63 53 47 45 45 50 57 61 63 63 62 62 68 71 71 65 55 48 47 50 62 69 75 72 62 53 50 51 71 92 114 123 125 119 104 88 71 64 53 45 40 39 38 38 39 39 41 44 48 52 55 56 56 53 48 45 44 43 42 40 38 36 36 39 46 54 59 62 61 57 51 48 47 48 48 48 44 41 39 39 42 44 46 46 44 41 35 30 27 26 26 27 36 37 39 40 39 36 32 29 29 28 28 28 29 28 26 23 26 26 28 33 40 43 42 39 36 31 27 26 29 35 40 43 45 43 38 31 24 20 20 21 24 26 28 28 26 25 26 27 27 28 30 31 31 30 29 28 27 25 23 21 21 22 24 25 22 24 25 27 29 35 41 46 53 54 53 49 42 36 32 30 27 29 31 31 30 28 28 29 32 35 40 41 40 36 34 33 32 32 33 34 34 33 32 32 29 28 27 27 30 34 38 41 41 38 34 28 24 22 22 22 27 27 27 28 32 41 52 59 72 72 68 59 47 34 25 20 21 25 30 35 39 43 48 51 54 54 51 45 37 31 27 26 34 38 45 49 50 47 42 38 30 24 19 19 19 18 22 27 32 33 35 36 35 32 29 26 19 18 16 17 20 23 24 24 27 27 27 28 27 26 26 25 23 22 21 19 19 18 18 18 20 20 22 22 22 21 19 18 16 15 14 13 13 13 13 13 11 12 13 14 14 14 14 13 14 13 13 12 11 10 10 9 10 10 10 10 10 10 10 10 9 9 9 10 10 11 11 11 9 9 9 9 9 9 9 9 9 8 8 8 7 7 7 7 6 6 6 5 5 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 10 11 13 15 16 17 18 18 19 20 22 25 27 28 29 29 30 30 30 32 35 37 36 34 34 32 29 27 27 27 25 23 20 18 16 16 18 19 18 17 19 20 21 23 24 26 27 28 27 27 26 24 24 24 24 24 23 23 23 23 23 23 23 23 23 23 23 24 24 24 24 24 26 27 29 31 33 35 36 37 32 32 31 30 29 28 27 27 30 36 47 58 68 73 76 76 68 59 50 44 38 35 37 42 43 50 60 67 70 69 68 67 62 65 69 74 83 91 91 86 75 65 57 58 66 79 95 109 117 112 105 95 81 72 76 84 101 119 134 133 126 112 89 67 55 45 38 37 39 41 45 50 59 64 69 68 61 51 45 42 35 37 39 41 43 46 49 52 53 56 58 59 67 81 91 94 104 97 90 87 87 92 104 115 125 127 122 105 86 73 64 59 65 70 74 73 65 58 54 53 54 58 63 65 64 61 59 59 65 70 74 70 60 52 48 48 58 65 70 68 60 55 56 60 80 103 125 132 132 125 108 89 71 65 56 49 45 44 43 42 42 43 44 46 49 52 56 58 62 58 54 51 50 50 49 48 48 45 42 42 46 51 56 58 56 51 45 40 39 40 41 41 41 40 41 44 49 53 54 54 51 46 38 30 25 24 26 27 35 37 40 42 42 39 35 33 31 29 27 27 27 27 25 23 29 30 34 42 49 52 48 43 37 32 25 24 27 34 39 41 43 41 35 28 22 19 20 22 24 26 28 28 26 23 22 22 25 26 27 28 29 29 29 29 27 25 23 22 23 24 27 28 25 28 31 35 39 44 51 55 57 56 54 48 40 35 32 31 28 30 32 31 29 28 30 32 38 41 45 45 41 37 35 34 33 35 38 40 41 40 38 37 31 31 30 31 32 35 39 41 43 40 34 29 24 22 22 22 29 29 30 32 36 43 53 59 73 72 67 58 46 34 26 22 23 28 33 38 39 41 42 43 44 43 40 35 31 29 31 33 41 44 48 50 48 42 34 30 25 20 18 19 20 19 22 27 29 31 32 32 30 26 22 19 17 16 15 17 21 23 24 23 25 25 26 26 27 27 27 27 24 23 21 19 18 17 16 16 17 18 19 19 19 17 16 15 15 15 14 13 13 13 14 14 13 13 14 15 15 15 15 15 17 16 16 15 14 13 13 13 11 11 11 11 11 11 11 11 9 9 9 10 10 11 11 11 9 9 9 9 9 9 9 9 9 9 8 8 8 7 7 7 6 6 6 5 5 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 9 10 12 14 15 17 17 17 18 19 21 24 26 27 28 28 29 28 29 31 34 35 35 33 35 32 29 27 27 27 25 23 21 19 17 17 18 19 18 17 19 20 21 23 25 27 28 29 29 29 27 26 25 25 25 25 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23 24 25 27 29 32 35 37 38 32 33 33 33 32 31 29 29 30 37 48 59 69 76 79 80 73 63 53 46 40 35 37 41 41 49 60 68 72 72 71 70 61 63 65 68 77 87 88 84 73 63 55 55 62 75 92 106 111 109 105 97 86 78 82 91 107 126 141 140 132 119 95 72 58 48 39 37 39 39 42 46 55 62 70 72 67 59 52 49 39 39 39 39 40 43 46 48 46 49 49 51 60 76 89 94 112 105 99 96 94 95 103 113 117 120 115 98 79 66 58 53 57 64 71 72 67 61 59 59 60 63 66 67 64 59 56 55 63 69 75 73 63 53 48 47 51 58 64 64 59 57 62 67 85 108 129 135 134 127 108 88 72 66 59 53 50 48 47 46 47 47 47 48 51 54 58 60 66 62 58 56 55 56 55 54 56 52 47 45 46 50 53 54 52 47 40 35 34 35 35 36 41 42 44 50 56 60 61 61 55 49 39 30 24 23 25 27 33 36 40 43 43 41 37 34 32 29 27 26 26 26 25 24 31 33 38 47 56 57 52 46 38 32 25 23 27 33 38 40 42 39 33 26 20 18 21 23 25 27 29 29 26 23 21 20 24 25 25 26 27 28 29 30 26 25 23 23 23 25 28 29 28 32 36 41 45 51 57 61 58 56 52 45 38 32 31 31 30 32 34 33 30 30 33 36 42 45 48 47 42 37 35 35 33 36 40 44 46 44 42 40 32 32 32 32 34 36 38 40 44 41 35 29 25 23 22 22 30 31 33 35 38 45 53 59 72 70 66 56 45 34 27 23 25 29 35 39 39 38 37 37 32 31 29 27 26 29 35 40 46 48 50 50 45 37 29 23 23 19 18 20 21 21 23 28 26 28 31 32 29 24 18 14 16 15 15 17 21 23 23 23 24 24 25 26 26 27 28 28 24 23 21 19 17 16 15 15 16 16 17 18 17 15 13 12 15 15 14 13 13 14 14 15 14 15 16 17 17 17 17 16 19 19 19 18 17 16 16 15 12 12 12 12 12 12 12 12 9 9 9 10 10 11 11 11 9 9 9 9 9 9 9 9 9 9 9 8 8 7 7 7 6 6 6 5 5 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 10 10 11 12 14 15 16 17 16 16 17 18 20 23 25 26 26 26 27 28 29 30 31 31 29 28 27 26 25 23 22 22 19 19 18 17 16 16 16 16 15 17 21 24 27 29 30 30 30 29 27 24 23 21 21 21 21 21 20 20 20 21 22 23 20 21 21 21 21 20 19 18 20 21 22 25 28 32 35 36 34 33 31 31 32 31 30 28 34 36 44 57 66 71 76 82 75 70 62 51 42 36 36 37 44 53 62 70 77 81 77 70 60 56 55 61 71 76 75 71 66 62 56 53 57 67 78 86 94 99 100 93 84 81 88 96 118 131 143 144 135 118 95 76 61 52 45 43 39 35 37 43 49 57 66 72 77 80 75 67 57 51 42 37 35 37 39 40 41 43 44 45 49 63 84 101 109 112 112 107 98 94 98 103 107 107 104 96 84 71 60 55 56 59 64 67 68 66 62 59 63 64 64 61 56 52 49 48 59 64 69 71 67 58 49 43 48 48 53 56 53 50 58 70 91 111 130 133 125 112 94 78 67 62 56 53 53 53 52 50 46 45 43 43 46 55 65 73 72 70 67 63 59 59 63 66 65 64 58 50 47 48 46 42 41 37 33 31 33 36 38 39 38 39 44 52 62 68 68 67 62 54 42 31 24 24 27 29 34 37 42 43 41 38 36 35 33 31 28 23 21 22 26 30 29 40 51 58 63 64 59 53 39 34 28 25 29 36 43 47 47 42 35 28 23 21 22 23 30 32 32 31 28 26 25 26 21 23 27 29 29 26 23 21 23 22 23 28 33 34 35 36 39 38 41 49 60 69 72 72 68 59 50 44 37 29 27 29 30 30 29 28 29 33 39 44 54 55 55 52 46 39 35 34 38 42 47 51 51 47 41 37 32 31 30 29 31 34 38 41 45 44 41 36 30 27 27 28 31 36 41 40 37 39 47 55 64 63 59 52 42 33 27 24 27 32 38 41 39 35 32 30 25 24 23 24 28 35 42 47 54 51 47 40 34 29 26 24 17 20 22 24 23 24 25 27 29 31 32 30 26 21 18 17 14 15 17 20 22 23 24 24 25 26 27 28 29 30 30 30 28 27 24 21 18 16 15 14 14 15 16 17 17 15 14 13 14 13 11 10 11 13 15 17 20 20 20 21 22 24 25 26 25 25 24 22 20 19 18 17 16 15 14 13 13 13 13 13 12 12 11 11 11 10 10 10 10 10 10 10 10 10 10 10 8 8 8 7 7 6 6 6 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 9 10 11 12 13 14 15 16 15 16 16 17 19 21 23 24 24 25 25 26 27 28 29 29 27 27 26 25 24 22 21 21 19 18 17 16 16 16 16 16 15 17 20 23 26 27 28 28 28 27 25 23 21 20 19 19 19 19 19 19 19 20 20 21 20 20 20 20 20 19 18 18 19 20 21 23 26 30 33 34 33 31 29 29 30 30 28 26 29 30 36 48 58 64 72 79 78 75 68 58 49 43 41 42 46 55 65 72 79 82 78 71 62 57 53 57 65 70 70 67 66 62 56 53 54 60 68 73 81 85 87 82 74 73 81 90 109 121 132 133 124 109 89 72 60 53 48 46 43 38 38 43 46 54 64 72 79 84 81 75 64 56 46 39 37 38 40 42 38 39 38 37 40 55 77 93 106 110 111 106 96 91 92 96 98 99 99 93 83 71 62 57 54 56 60 63 64 62 59 56 59 61 61 58 54 49 47 47 58 63 69 70 66 58 49 43 42 44 49 53 50 47 54 64 82 100 117 120 112 98 80 66 52 49 48 49 52 55 54 53 51 50 49 49 52 60 70 77 76 74 69 63 60 60 64 68 71 70 65 56 51 48 44 38 36 34 32 33 37 41 45 46 47 47 50 57 66 72 73 71 63 55 43 32 25 24 26 29 34 37 41 42 40 37 35 34 34 32 29 25 22 22 26 29 33 43 54 61 65 65 59 52 37 33 27 26 29 36 43 47 45 41 34 27 23 22 24 25 32 33 34 32 29 27 27 28 25 27 30 30 29 26 24 23 25 26 30 37 42 45 44 44 44 44 48 58 69 75 75 72 64 55 45 39 33 26 25 27 24 25 27 28 32 39 48 54 61 62 62 58 51 44 39 36 40 43 48 51 50 46 40 36 29 28 27 28 30 34 39 41 47 46 43 37 32 28 27 28 31 35 39 38 34 36 43 50 56 56 54 49 41 33 29 27 29 33 38 40 38 32 28 25 21 21 22 25 31 38 45 49 52 49 44 38 33 30 27 27 24 25 26 26 24 24 25 26 26 28 29 28 23 19 16 15 14 16 18 20 22 24 24 25 26 27 28 29 30 31 31 31 29 28 26 23 20 18 17 16 15 15 16 16 16 15 13 12 14 13 12 11 12 15 17 19 22 22 23 25 26 28 30 31 32 31 29 27 25 23 22 21 18 17 16 14 13 13 13 13 13 12 12 12 11 11 11 10 10 10 10 10 10 10 10 10 8 8 7 7 7 6 6 6 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 9 9 10 11 12 13 14 14 14 14 15 16 17 19 21 22 22 22 23 23 24 25 25 26 25 25 24 23 22 20 20 19 18 17 16 16 15 15 16 16 16 17 19 21 23 24 24 24 25 23 22 20 18 17 17 17 17 17 17 17 18 18 19 19 19 19 19 19 18 18 18 17 17 18 19 21 24 27 29 31 32 31 30 30 31 31 29 27 26 24 28 38 48 56 66 75 79 77 73 66 57 50 47 46 49 58 68 75 82 85 80 72 65 57 50 49 55 60 62 61 65 61 56 52 50 52 54 56 64 68 70 67 62 63 72 81 98 109 118 117 109 97 81 68 58 55 53 53 50 44 42 43 42 51 62 71 82 89 89 84 71 63 51 43 40 42 45 47 42 40 35 31 34 48 69 85 102 106 107 102 92 83 81 82 85 88 90 88 81 72 65 61 55 56 59 61 60 58 55 53 53 54 55 54 51 49 49 49 60 65 70 70 65 55 47 42 38 42 49 53 50 47 50 57 72 86 99 102 94 80 65 53 41 41 43 47 52 56 58 58 56 56 55 55 58 64 73 80 81 77 70 63 58 59 64 69 77 79 75 65 57 50 42 34 31 30 32 37 45 52 57 59 60 58 57 61 69 74 76 76 66 58 46 35 28 26 28 30 35 37 40 40 38 35 35 35 36 35 32 27 24 23 26 28 35 46 56 62 65 64 57 49 35 31 27 26 30 37 43 46 41 37 32 26 24 24 27 29 35 36 36 34 32 30 30 31 32 33 34 32 29 26 25 25 27 33 41 50 58 60 58 54 51 52 57 67 78 81 77 72 61 51 39 33 28 24 23 26 21 23 26 29 35 45 55 63 70 71 70 64 56 47 40 37 41 44 48 50 49 43 37 32 25 24 24 25 29 34 39 42 49 48 45 39 33 29 27 27 30 34 36 35 31 31 37 43 47 48 47 44 38 33 29 28 29 33 38 39 35 28 22 19 16 18 22 28 34 41 47 51 47 44 39 35 31 30 31 31 32 32 31 28 24 23 24 26 25 27 28 27 23 19 16 15 15 16 18 21 23 24 25 25 28 28 29 29 30 31 31 31 31 30 28 26 24 21 20 19 17 17 17 16 15 14 12 11 13 13 13 13 15 17 20 21 27 27 29 31 33 36 37 38 38 36 34 32 29 26 24 23 20 19 17 15 14 13 13 13 14 13 13 13 12 12 12 11 10 10 10 10 10 10 10 10 8 7 7 7 6 6 6 6 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 8 9 9 10 11 12 13 13 14 14 14 14 15 17 18 19 19 19 20 20 21 21 21 22 22 21 21 20 19 18 17 17 17 16 15 15 15 15 15 16 16 17 18 19 19 20 20 20 22 21 19 17 16 15 15 15 16 16 17 18 19 19 19 19 19 19 18 18 17 17 17 17 16 17 18 19 21 24 26 28 33 32 32 34 36 36 34 32 27 24 24 31 39 48 60 70 75 75 75 71 64 57 52 50 51 60 70 77 83 86 81 73 65 56 47 43 45 51 54 55 62 60 57 53 50 47 45 44 52 55 57 54 52 55 64 73 88 98 105 102 93 83 71 62 56 57 59 60 58 53 48 45 42 50 60 69 80 89 90 86 72 64 53 46 45 49 55 58 55 51 43 35 35 47 66 80 96 99 99 94 83 72 67 65 70 74 79 80 77 72 67 65 59 60 61 61 59 55 51 49 46 48 51 52 53 54 56 58 67 72 75 73 64 53 44 39 41 47 55 59 56 52 50 52 63 72 82 84 79 68 56 48 43 43 44 48 52 57 61 63 60 60 59 59 61 66 74 79 81 76 68 59 54 55 61 66 78 82 81 73 63 53 42 33 28 30 36 46 57 67 73 75 72 68 64 65 71 76 78 78 69 62 51 40 33 31 32 34 37 39 39 38 36 35 35 36 39 38 36 31 27 25 26 27 35 44 54 59 60 58 51 42 32 29 26 27 31 37 41 44 37 34 29 26 25 27 30 33 38 38 38 37 34 33 34 35 37 38 38 34 28 25 26 27 32 42 56 67 75 77 71 63 58 57 61 70 80 83 77 70 58 46 34 28 25 22 22 25 24 25 27 31 38 48 59 67 77 77 75 69 58 47 39 35 39 42 46 48 46 40 33 28 21 21 21 23 27 33 39 42 50 49 46 41 34 29 26 26 28 31 33 31 28 28 32 36 40 41 42 39 34 30 28 27 26 31 35 36 32 26 20 17 15 18 23 30 37 42 46 48 42 39 35 31 30 32 34 36 39 37 33 28 23 21 22 24 26 28 29 28 24 20 17 16 16 17 19 21 23 25 26 26 27 27 27 27 28 28 29 30 31 31 30 28 26 24 23 22 19 18 17 16 15 13 12 11 13 13 14 15 18 21 23 25 32 34 36 38 41 43 44 45 40 39 36 33 30 26 24 23 22 20 18 16 14 13 12 12 14 14 14 13 13 13 12 12 9 9 9 9 9 9 9 9 7 7 7 6 6 6 5 5 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 9 9 10 10 11 12 12 13 14 13 13 13 14 15 16 17 17 17 17 17 18 18 18 18 18 18 18 17 16 16 15 15 15 15 14 14 14 14 15 16 16 16 16 17 17 17 18 18 20 19 17 16 15 14 14 14 16 17 19 20 21 22 21 21 20 19 18 17 16 17 17 18 16 17 17 19 20 23 25 26 31 32 34 37 41 43 41 40 33 27 23 25 31 39 50 61 70 73 75 74 70 64 60 58 55 63 70 76 81 83 78 71 61 53 43 38 39 44 49 51 58 58 57 55 52 47 42 39 43 45 46 44 43 47 57 65 80 88 93 87 77 67 58 51 53 57 63 66 65 61 54 49 44 51 58 65 74 81 82 77 65 59 51 48 51 60 68 73 73 66 56 46 44 52 67 78 91 92 90 82 71 60 53 50 57 62 67 70 70 68 66 66 62 63 63 62 58 52 47 43 41 45 50 54 58 63 69 73 78 82 84 78 65 51 41 37 46 54 64 67 64 59 53 49 55 59 64 67 65 59 53 51 48 48 48 49 52 57 63 67 64 64 64 63 63 67 72 76 76 70 61 51 46 48 54 60 71 78 82 76 66 57 46 37 29 34 43 57 71 83 89 92 85 79 73 71 74 78 79 79 71 65 54 45 38 37 38 40 41 42 41 38 36 35 37 39 44 43 41 36 31 27 27 27 32 40 48 51 52 50 43 35 30 28 27 28 32 37 39 40 34 31 27 25 25 29 33 36 40 41 40 38 36 36 37 39 41 43 42 36 29 25 27 29 42 57 74 87 94 94 82 69 60 57 58 66 76 78 72 65 50 38 26 23 22 21 22 24 27 28 30 34 41 52 64 72 84 84 81 73 61 48 38 33 36 39 43 45 43 37 30 26 20 20 20 22 26 32 37 41 48 48 46 41 34 28 25 25 26 28 30 29 27 27 29 32 38 39 39 36 31 27 24 23 23 27 31 32 29 25 20 18 17 20 26 32 37 40 42 42 37 35 32 30 31 34 38 41 41 38 33 26 20 19 22 25 28 29 30 29 24 19 16 15 16 18 20 22 24 26 26 27 25 24 24 23 23 24 26 26 30 30 30 30 28 26 24 23 20 20 18 17 15 14 13 13 13 14 16 19 23 26 29 30 38 40 42 44 46 47 47 47 41 39 37 33 30 26 24 23 22 20 18 16 14 13 12 12 14 14 14 13 13 13 12 12 9 9 9 9 9 9 9 9 7 7 6 6 6 5 5 5 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 10 10 11 11 12 12 13 13 14 14 13 13 13 14 14 15 15 15 15 15 15 16 16 16 15 15 15 14 14 13 13 13 14 13 13 13 13 14 15 15 16 16 15 15 15 16 17 18 19 19 17 16 15 15 15 15 17 18 20 22 24 24 23 23 21 20 18 17 17 17 18 19 18 18 19 19 21 23 24 25 29 31 35 41 47 51 51 50 44 35 27 25 26 31 41 50 65 69 74 77 76 72 69 68 63 68 72 73 75 75 70 63 55 49 41 37 38 42 47 49 55 56 58 57 54 48 43 39 35 36 37 36 37 44 54 62 75 83 86 77 64 53 45 40 46 55 63 67 68 66 58 51 47 51 55 58 64 69 68 63 54 50 47 49 57 70 81 88 86 80 70 61 58 63 73 80 88 86 81 71 59 49 43 40 46 50 55 58 59 59 61 62 62 63 65 64 60 53 46 42 41 45 52 58 65 73 80 85 89 93 93 84 68 52 42 38 49 60 72 76 74 69 59 51 51 49 49 53 53 52 53 56 52 53 53 53 54 57 63 67 66 66 66 64 63 64 67 70 67 61 53 44 39 40 46 51 61 71 78 75 67 58 48 40 33 40 52 68 84 96 102 104 95 88 80 76 77 79 79 78 69 64 55 47 43 42 44 46 47 46 43 39 37 37 40 43 48 48 46 42 35 30 28 28 30 37 43 44 44 43 38 30 29 28 27 29 33 36 37 36 31 29 26 24 26 30 35 38 42 42 41 39 37 37 39 42 44 47 47 41 33 28 29 33 51 70 91 103 108 104 87 68 56 52 51 59 69 72 64 55 40 29 20 20 24 27 28 31 32 33 35 39 46 58 71 79 89 89 86 78 65 50 39 33 32 35 40 43 42 37 31 27 21 21 21 22 25 30 35 39 45 45 43 39 32 27 24 23 23 25 27 28 27 28 30 32 38 39 39 35 30 25 22 21 22 25 28 29 26 24 22 21 20 23 27 32 35 37 37 37 33 32 31 31 33 37 41 43 41 37 30 23 18 19 23 28 30 32 32 30 24 19 15 14 17 18 21 23 25 26 27 28 23 22 20 20 20 21 22 23 28 29 29 29 28 26 24 23 22 21 19 18 17 16 16 16 17 18 22 25 30 33 36 38 44 45 47 48 48 48 47 46 40 39 37 33 30 27 24 23 20 19 17 15 14 13 13 13 14 13 13 13 12 12 12 11 8 8 8 8 8 8 8 8 6 6 6 6 5 5 5 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 12 12 12 12 13 13 13 13 15 14 14 13 13 13 14 14 14 14 14 14 14 14 14 14 13 13 12 12 12 11 11 11 13 13 12 12 13 14 15 15 16 15 15 14 15 16 18 19 20 19 18 17 16 16 16 16 16 18 21 23 24 24 23 23 23 21 19 18 17 18 19 21 20 20 20 21 22 23 25 26 31 34 40 49 57 63 64 63 59 48 37 31 28 29 36 45 57 63 70 75 76 76 75 74 73 75 74 70 67 65 58 51 47 44 40 38 39 43 47 49 54 56 58 58 55 49 43 38 32 33 34 35 38 47 58 66 79 86 87 75 59 47 39 34 39 50 60 64 66 67 60 51 47 50 51 51 54 57 55 50 44 42 43 49 62 77 90 97 96 91 84 77 75 78 84 89 89 84 75 63 51 43 38 37 38 40 43 45 47 49 52 55 62 65 69 71 68 61 54 48 45 49 55 62 70 78 87 93 96 100 100 90 72 55 45 42 51 66 80 86 87 83 72 60 54 46 42 44 47 48 54 61 62 64 66 64 61 59 59 61 62 63 62 59 57 56 57 59 58 54 46 38 33 34 40 45 52 63 73 71 64 57 49 42 37 45 58 76 92 104 109 111 97 90 81 76 75 75 74 72 65 61 53 47 44 45 48 50 51 50 46 41 38 39 43 47 53 53 51 46 39 33 30 28 31 37 41 40 40 41 37 31 28 28 28 31 33 35 34 33 30 28 25 24 26 31 36 39 43 43 42 40 38 38 41 43 47 51 52 47 38 32 33 37 55 76 98 109 112 105 82 59 47 44 45 55 65 66 56 44 33 24 19 25 34 40 44 46 43 43 43 45 51 61 74 82 90 90 87 78 64 49 37 31 30 34 39 43 43 40 34 31 24 23 22 22 25 29 33 36 41 41 40 37 31 25 22 21 21 23 26 28 29 30 32 33 38 38 38 35 30 25 22 21 24 26 27 26 24 22 22 23 22 24 27 30 33 34 34 34 30 30 31 32 35 39 42 44 40 36 29 22 18 21 27 33 37 39 38 35 29 23 19 17 18 19 21 24 26 27 28 28 22 21 19 18 18 19 21 22 25 26 28 28 28 26 23 22 23 22 20 19 18 19 19 20 22 24 28 33 38 42 45 46 48 49 50 50 49 46 44 42 36 35 33 30 27 24 21 20 18 17 16 14 13 13 13 13 13 12 12 12 11 11 11 10 8 8 8 8 8 8 8 8 6 6 6 5 5 5 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 13 13 13 13 13 14 14 14 16 15 14 13 13 13 14 14 14 14 14 14 14 14 14 13 11 11 11 11 11 10 10 10 12 12 12 12 12 13 14 15 16 15 14 14 15 16 18 19 21 20 19 18 17 17 17 17 15 17 20 23 24 24 23 22 24 22 20 18 18 19 20 22 22 22 22 22 23 24 26 26 35 39 46 56 66 73 75 75 72 60 47 39 33 32 37 45 50 56 64 71 74 75 76 76 81 81 76 68 62 58 50 42 42 41 39 39 41 44 48 50 54 56 58 58 55 49 42 37 32 33 34 37 43 53 65 73 85 91 92 78 61 47 39 34 34 46 57 61 64 66 60 50 46 48 48 46 48 50 47 42 38 38 41 49 64 80 94 101 102 99 94 89 88 90 94 98 90 83 72 59 48 40 37 36 33 34 36 37 39 42 46 50 64 68 74 78 76 70 62 57 48 52 58 65 72 80 89 95 100 104 104 94 75 59 49 46 54 70 87 95 97 95 83 70 59 49 41 42 45 48 56 66 74 77 79 76 69 61 55 53 57 57 56 53 49 47 48 49 53 49 42 35 31 32 37 41 47 59 69 69 62 55 48 42 40 47 61 79 96 107 112 113 94 87 78 73 71 70 67 65 62 57 51 46 44 46 50 52 54 52 47 42 39 41 46 50 55 55 53 49 41 35 31 29 33 38 40 39 39 40 38 33 28 28 29 31 34 34 32 30 30 28 25 24 26 31 36 40 43 43 42 40 38 38 41 44 49 54 56 51 42 36 37 40 53 76 98 108 109 100 74 48 41 39 42 54 64 64 50 37 31 24 22 32 45 54 58 61 55 54 52 51 54 62 72 80 87 87 84 75 61 46 34 27 29 33 39 44 45 42 37 34 26 25 23 23 25 28 32 34 38 39 38 35 29 24 21 20 20 22 25 28 30 32 34 35 37 38 38 35 30 26 23 22 27 27 27 25 22 20 21 23 22 23 26 29 31 33 33 33 29 30 31 34 37 40 43 45 39 35 28 21 19 23 30 37 45 46 45 42 35 28 24 22 18 19 21 24 26 27 28 28 22 21 19 17 17 18 20 22 24 25 26 27 27 25 23 21 23 22 21 20 20 20 22 22 26 29 33 38 43 48 51 52 50 51 51 51 48 45 41 39 30 29 27 25 22 19 17 16 16 15 14 13 13 13 13 13 12 12 11 11 11 10 10 10 8 8 8 8 8 8 8 8 6 6 6 5 5 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 10 10 11 12 13 13 14 15 14 14 14 14 14 14 14 14 13 13 13 13 13 13 13 13 11 11 11 11 11 11 11 11 13 13 13 14 14 15 15 15 19 18 16 15 16 18 20 22 23 24 25 23 21 19 19 20 20 22 24 24 23 24 26 27 26 26 26 23 20 19 20 21 23 24 25 25 24 26 29 32 36 42 53 65 76 82 85 86 77 70 58 46 38 34 35 36 44 52 62 68 70 74 79 85 83 80 74 66 56 47 40 36 33 35 39 42 45 47 48 48 53 54 54 53 50 44 38 34 33 33 36 41 46 56 75 92 98 100 98 87 68 50 39 35 39 43 50 56 57 54 49 45 40 42 45 47 48 48 47 46 41 41 44 52 64 76 86 92 95 93 92 93 95 98 100 101 89 82 72 61 52 45 39 35 37 33 31 32 35 38 46 55 61 74 85 84 81 79 73 66 59 61 62 63 66 73 84 92 97 101 104 97 83 67 56 52 57 68 85 101 108 104 93 84 73 58 46 42 43 46 55 65 79 81 81 76 67 57 51 49 45 47 49 48 44 42 43 45 46 45 43 41 40 39 39 39 48 50 55 60 61 57 49 43 46 50 61 76 90 98 100 98 88 79 68 63 65 66 63 59 53 49 44 42 45 49 54 56 60 57 52 45 41 41 45 49 54 55 54 49 41 34 32 33 31 38 43 42 40 40 38 35 33 32 31 32 33 33 32 30 26 25 24 22 23 28 35 41 45 46 45 41 35 34 37 40 49 57 61 56 49 45 43 41 55 73 91 99 97 85 63 44 31 34 43 54 61 59 48 39 31 31 35 47 62 72 75 74 75 66 57 55 57 59 66 72 77 79 79 73 61 46 34 27 28 32 40 48 51 49 42 36 33 29 24 22 24 27 29 30 32 33 33 33 30 27 24 21 23 23 24 25 26 28 30 31 39 39 38 36 34 32 30 29 30 29 29 28 28 27 27 27 27 28 28 29 29 28 28 27 29 31 33 34 35 37 40 43 34 31 26 23 25 31 39 44 52 52 51 48 43 36 30 26 23 24 26 27 28 29 29 29 26 25 23 21 21 21 22 23 26 26 25 24 22 21 20 20 21 20 20 21 23 25 28 29 34 37 42 47 51 53 54 54 54 52 50 47 45 41 36 32 26 25 22 20 18 17 17 17 15 15 15 14 14 14 13 13 12 12 12 11 11 11 10 10 8 8 8 7 7 6 6 6 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 9 10 10 11 12 13 14 14 14 14 14 14 14 14 14 14 13 13 13 13 13 13 13 13 11 11 11 11 11 11 11 11 13 13 13 14 14 15 15 15 17 16 15 15 17 19 22 24 25 26 27 25 23 21 22 23 22 23 25 25 24 24 26 28 28 28 28 25 23 21 22 24 25 26 27 26 25 26 29 31 37 43 53 65 74 81 84 85 82 75 64 52 43 39 39 39 42 50 59 64 67 71 77 82 80 78 73 65 56 46 37 32 29 32 36 41 45 48 50 51 52 53 52 50 46 41 35 32 32 31 34 39 45 56 76 93 108 110 109 97 76 56 42 36 38 43 49 54 55 51 46 42 37 39 43 47 50 52 53 53 50 50 51 55 62 70 77 81 88 89 92 96 100 102 102 101 93 86 76 67 59 53 48 45 43 37 34 34 36 39 47 56 64 76 85 86 84 83 80 74 71 71 69 65 62 63 70 75 88 94 99 97 85 71 60 55 59 68 83 96 103 101 94 89 78 66 54 48 45 46 54 64 80 83 86 82 73 62 53 48 39 41 43 42 39 38 39 41 45 46 45 45 44 43 41 40 46 47 50 53 54 51 46 41 46 50 59 72 84 90 89 86 76 68 58 54 56 57 55 51 47 43 39 39 44 51 57 60 64 60 54 46 41 40 44 47 53 55 55 50 42 37 35 36 38 45 50 49 46 45 41 36 32 31 31 32 34 35 33 31 30 29 26 23 23 27 34 40 45 46 44 39 34 32 34 37 48 58 66 64 59 54 49 45 49 63 78 83 81 70 52 36 31 36 46 58 65 61 50 40 32 35 43 58 76 87 90 89 82 71 60 55 54 55 60 66 71 73 73 69 58 44 33 26 27 32 41 50 54 52 46 40 32 28 24 22 23 26 28 28 31 32 32 32 30 27 24 22 25 25 25 26 27 29 30 31 36 37 38 38 38 36 34 33 32 32 31 31 31 31 32 32 31 30 30 29 28 28 28 28 29 31 34 35 35 36 38 40 33 30 27 25 28 34 42 47 55 55 54 51 45 38 32 28 24 25 26 27 28 29 29 29 27 26 25 24 23 23 23 23 25 24 24 23 22 22 21 21 21 21 22 23 25 28 30 32 40 43 47 51 54 55 55 55 51 49 46 43 41 37 32 28 24 22 20 17 15 15 15 15 15 14 14 14 13 13 13 12 12 11 11 11 10 10 10 9 8 8 8 7 7 6 6 6 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 9 10 10 11 12 12 13 13 13 13 13 13 13 13 13 13 12 12 12 12 12 12 12 12 11 11 11 11 11 11 11 11 13 13 13 14 14 15 15 15 15 15 15 16 18 21 24 25 27 28 29 27 25 24 24 25 24 25 26 26 25 26 28 30 30 31 30 28 25 24 25 26 28 28 29 28 26 26 28 30 37 42 51 61 69 75 79 80 77 71 61 50 42 38 36 36 40 46 53 58 62 66 72 77 76 75 72 65 56 45 35 29 26 29 34 40 46 51 54 56 52 52 50 46 41 35 30 27 29 28 30 35 42 54 75 93 111 115 115 105 85 63 47 40 39 43 48 52 52 48 43 39 36 38 42 48 54 59 63 66 65 63 61 60 60 61 64 65 71 76 83 91 95 96 95 93 93 88 82 75 70 66 61 58 52 45 39 38 39 42 49 57 66 75 84 86 86 87 87 85 85 83 78 69 59 54 55 57 73 82 92 95 89 78 67 62 64 70 78 87 93 94 94 92 84 77 68 59 50 47 52 60 75 81 87 87 79 66 54 46 36 37 38 38 36 37 38 40 46 47 49 50 50 47 44 42 45 44 45 46 47 46 43 40 45 48 55 66 75 77 74 69 61 53 46 43 46 48 46 43 39 36 33 36 44 54 62 67 69 64 56 47 40 38 41 44 52 53 54 50 43 39 39 41 46 54 59 58 53 49 43 36 30 30 30 33 35 37 36 34 34 32 28 24 23 27 34 40 48 48 45 38 31 28 29 32 42 56 70 73 71 65 56 48 46 54 62 64 61 53 41 30 34 41 53 66 72 67 54 44 37 42 54 73 91 101 102 98 88 75 61 53 49 47 51 56 60 63 66 63 54 42 32 27 28 33 42 51 57 55 49 44 32 28 24 22 23 25 26 26 29 30 30 30 29 26 24 22 26 26 26 27 27 28 28 28 31 34 38 41 42 42 41 39 38 37 36 36 36 37 38 39 37 35 32 28 26 26 26 27 29 32 35 36 36 34 34 34 31 30 28 29 33 39 46 51 58 58 56 53 48 41 35 31 26 27 27 28 28 29 29 30 29 29 29 28 27 26 25 24 23 23 23 23 23 23 23 23 23 24 25 27 30 33 35 37 45 47 50 53 54 54 52 51 46 44 40 38 35 31 26 23 21 19 17 14 13 12 12 13 14 13 13 13 12 12 12 11 11 10 10 10 9 9 9 8 8 8 8 7 7 6 6 6 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 9 9 10 10 11 11 12 12 12 12 12 12 12 12 12 12 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 13 13 13 14 14 15 15 15 16 16 16 17 19 21 23 24 27 28 29 28 26 24 25 26 26 27 28 28 27 28 31 34 33 34 33 30 27 26 27 28 28 29 30 29 27 26 27 28 34 38 45 53 60 66 69 70 65 61 54 46 40 36 34 34 38 42 47 52 55 60 66 70 72 72 71 66 57 46 35 29 27 30 34 40 46 52 56 58 53 51 47 42 36 31 27 24 26 25 26 31 37 50 71 90 104 110 113 106 88 68 53 46 42 46 50 53 52 48 42 38 39 41 46 53 61 69 75 79 78 76 71 64 57 53 51 51 57 64 74 82 86 87 86 84 86 85 85 86 85 81 75 71 61 52 44 42 43 45 52 59 66 72 79 82 83 86 89 92 94 92 87 75 62 52 48 48 59 69 82 91 91 84 77 72 70 72 75 77 80 84 88 90 89 87 81 70 58 50 51 56 65 72 81 86 82 70 56 47 39 39 39 38 39 40 43 45 47 49 53 55 55 51 47 44 45 43 41 41 42 43 42 40 41 43 48 57 63 64 59 53 47 42 37 37 40 42 41 39 34 32 31 36 46 59 69 75 73 67 58 47 38 35 37 40 48 50 50 47 43 40 42 44 52 60 65 63 57 51 42 33 30 29 30 33 37 39 39 38 34 32 29 26 25 30 37 43 53 53 49 41 31 25 25 26 36 52 70 79 80 74 62 51 48 51 52 51 47 42 36 31 40 49 64 78 83 76 62 51 45 51 64 83 99 106 103 97 86 73 57 48 42 39 42 47 51 55 59 58 52 42 34 30 29 34 42 50 55 54 49 44 32 29 25 23 23 25 25 25 28 28 28 28 28 26 25 24 25 26 26 26 26 26 25 25 28 32 38 44 47 48 47 46 45 44 41 40 40 41 44 45 43 39 34 28 24 23 24 25 28 32 36 37 36 32 30 29 29 29 30 32 37 43 50 54 59 59 58 55 50 44 37 33 28 28 28 28 28 28 29 29 30 30 31 31 30 28 26 24 21 21 22 23 24 25 26 26 27 28 30 33 35 38 40 42 46 47 49 50 50 48 46 44 41 38 35 32 30 27 23 19 19 17 15 13 11 11 12 12 13 13 12 12 12 11 11 11 10 10 9 9 9 8 8 8 8 8 8 7 7 6 6 6 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 9 9 9 9 10 10 10 10 10 10 10 10 10 10 10 10 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 13 13 13 14 14 15 15 15 18 18 18 18 19 20 21 22 25 27 27 27 25 24 25 26 28 29 29 29 29 32 36 39 37 37 36 33 29 27 27 29 28 30 30 29 27 25 26 27 29 32 37 43 49 54 58 59 56 54 50 45 42 39 38 37 37 39 42 45 49 53 58 62 68 69 69 66 59 49 38 32 28 30 34 39 45 50 55 57 56 52 46 40 33 29 26 24 25 24 25 29 34 45 64 82 98 105 109 103 88 70 57 51 50 52 56 58 57 52 47 43 46 49 54 61 69 78 84 88 86 83 76 66 55 48 46 46 57 64 74 80 82 81 80 79 76 80 88 96 99 96 88 82 67 57 49 47 49 51 55 61 63 66 70 73 74 77 84 91 100 100 96 85 71 57 49 46 51 60 73 83 87 86 81 78 74 74 73 70 69 72 78 83 90 93 92 82 69 59 54 53 55 63 74 82 83 75 63 54 45 43 41 41 42 46 49 50 50 52 55 57 56 53 49 47 43 40 38 37 38 39 39 38 35 36 40 46 52 52 47 42 35 33 31 33 36 39 39 38 35 34 35 41 52 64 74 79 74 68 57 44 35 31 33 36 43 45 46 43 40 39 42 45 53 61 66 63 57 49 39 30 30 30 31 34 38 41 41 40 34 33 31 30 30 35 42 47 59 59 56 47 35 27 23 23 34 51 71 84 87 83 70 58 53 49 45 42 39 35 34 35 48 59 76 90 94 86 72 61 51 57 70 87 102 106 100 92 76 63 49 40 35 32 35 40 43 48 54 55 51 44 38 34 31 34 40 46 50 49 45 40 35 31 27 25 25 26 26 25 27 27 27 27 27 27 26 26 25 26 26 27 26 25 24 23 28 32 39 45 50 51 51 50 50 48 45 42 42 45 48 50 50 45 37 30 24 22 21 22 28 32 36 37 35 30 27 26 27 28 31 35 40 45 50 53 57 58 57 55 50 44 39 35 30 29 28 27 27 27 28 29 30 30 31 31 29 27 25 23 19 20 21 23 26 28 29 30 33 34 36 38 40 42 43 44 44 45 46 46 45 43 40 38 37 34 30 28 26 24 21 18 18 17 15 13 12 12 12 13 13 13 12 12 12 11 11 11 10 10 9 9 9 8 8 8 8 8 8 7 7 6 6 6 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 10 10 10 10 10 10 10 10 11 11 11 11 11 11 11 11 13 13 13 14 14 15 15 15 19 19 19 19 20 20 20 20 24 25 26 26 24 23 24 26 28 29 30 30 32 35 40 44 43 43 41 37 32 29 29 30 28 30 32 31 29 27 27 28 28 29 33 37 41 46 49 51 48 48 46 45 43 41 40 39 38 38 38 40 43 47 52 55 62 63 65 64 59 51 43 38 30 32 35 39 45 50 55 58 59 54 47 39 33 29 27 27 29 27 28 30 33 41 58 73 95 101 104 99 85 70 60 57 59 62 65 66 65 61 56 53 56 59 64 70 77 83 87 90 87 84 76 65 54 47 47 49 61 69 78 82 79 74 70 69 68 75 87 99 105 102 94 87 69 59 52 52 55 56 59 63 61 59 60 61 62 64 74 84 100 103 103 96 82 66 55 49 51 56 64 72 77 79 78 77 75 75 73 68 64 65 71 77 89 96 100 94 83 72 61 52 50 57 67 77 82 79 71 64 51 48 44 43 45 49 52 54 55 55 55 55 54 52 50 48 39 38 37 37 38 38 37 35 32 31 33 37 42 43 39 35 27 27 28 32 36 40 41 40 40 40 42 48 58 67 75 78 71 65 53 41 31 28 30 33 39 41 42 40 37 37 41 45 52 60 65 62 55 47 38 29 31 31 32 36 40 42 42 41 36 37 37 37 38 42 47 51 63 64 63 55 44 33 27 25 36 53 73 86 92 90 79 67 54 47 41 37 34 32 34 39 56 68 86 100 102 94 81 71 58 63 73 88 99 102 95 87 64 52 40 33 30 27 30 34 38 44 50 54 51 46 41 37 31 33 36 41 44 45 42 39 38 35 31 29 29 28 27 26 26 26 27 27 28 28 29 29 28 29 30 31 31 30 28 27 31 34 40 45 50 52 52 52 50 47 44 42 43 47 52 56 56 51 43 34 27 23 21 20 28 31 35 36 33 29 26 24 26 28 32 36 41 45 48 49 53 53 54 52 49 44 39 36 30 29 27 25 25 25 26 27 29 29 28 27 26 24 22 21 18 19 22 25 28 31 33 35 37 38 39 40 41 41 41 41 40 41 42 42 41 38 35 33 31 28 25 23 22 22 20 18 18 17 15 13 12 12 13 13 14 13 13 13 12 12 12 11 11 10 10 10 9 9 9 8 8 8 8 7 7 6 6 6 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 9 9 9 9 9 9 9 9 11 11 11 11 11 11 11 11 13 13 13 14 14 15 15 15 17 17 19 20 21 22 22 22 24 25 26 26 24 24 25 27 28 29 30 31 33 38 44 49 50 50 47 42 36 32 31 32 30 32 34 34 32 31 31 31 29 30 32 35 39 43 46 48 49 49 49 49 48 45 43 42 40 38 36 36 39 43 47 49 56 57 59 60 57 52 46 42 36 37 40 45 51 57 62 65 62 57 48 40 34 31 31 31 34 33 34 35 35 40 53 67 87 92 95 90 80 70 65 65 69 71 74 75 74 71 66 63 65 68 72 77 81 84 85 86 83 81 74 63 53 49 52 57 69 78 88 90 83 72 64 59 60 68 79 91 97 96 89 82 68 59 53 55 59 61 62 64 59 55 52 52 51 52 63 75 90 97 104 103 93 78 66 60 58 57 58 60 63 66 68 69 74 75 74 69 64 64 69 74 88 98 106 105 98 86 69 55 48 52 59 69 76 78 74 70 58 54 48 47 50 54 57 58 59 58 54 52 50 49 49 49 41 41 41 43 44 43 39 36 32 30 29 31 34 35 33 30 27 28 32 37 42 45 47 47 45 46 48 54 62 68 72 73 67 61 49 37 27 25 28 31 38 40 41 39 36 37 41 45 53 60 64 61 55 48 39 31 32 32 33 37 40 43 43 42 43 45 46 47 47 49 52 54 62 65 68 63 54 43 36 33 39 53 70 83 91 92 83 73 56 47 39 36 34 32 36 43 61 74 92 105 107 99 86 77 67 69 74 84 91 91 82 74 55 44 35 30 27 25 27 31 34 40 48 52 51 46 42 39 31 31 32 36 40 43 43 42 41 38 35 33 32 31 29 28 26 26 27 27 28 30 31 32 34 35 37 39 39 38 36 35 35 37 41 45 48 50 51 51 45 42 40 40 43 50 58 62 63 58 50 40 32 26 22 21 28 31 34 34 31 28 25 24 26 28 32 37 40 43 44 44 47 48 49 49 47 43 38 35 30 29 26 24 23 23 24 25 28 27 25 23 21 20 19 19 18 19 22 26 30 34 37 38 39 39 40 40 39 38 36 35 33 34 35 35 34 32 29 27 26 23 20 19 19 19 18 17 17 15 13 12 11 11 12 13 15 14 14 14 13 13 13 12 12 11 11 11 10 10 10 9 8 8 8 7 7 6 6 6 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 9 9 9 9 9 9 9 9 11 11 11 11 11 11 11 11 13 13 13 14 14 15 15 15 14 16 18 20 22 23 24 24 24 26 27 27 25 25 26 28 27 28 30 32 34 40 47 52 55 54 51 46 40 35 33 33 31 34 36 37 35 34 33 34 32 32 33 35 39 42 46 48 58 58 59 59 57 54 51 49 42 39 35 35 37 40 44 45 51 53 55 56 55 52 47 45 42 43 47 52 59 66 72 75 64 58 49 41 35 33 33 34 39 38 38 39 37 40 51 63 76 81 85 82 75 70 69 71 75 77 79 81 80 77 73 70 70 73 76 80 82 83 83 82 79 77 71 61 52 51 57 63 79 90 101 104 94 79 65 58 55 61 70 80 86 85 80 75 67 58 53 57 62 64 64 65 59 52 48 46 44 45 56 70 79 89 101 105 100 88 78 72 63 59 54 52 53 56 59 61 72 74 75 71 66 65 69 74 87 99 109 111 107 96 76 57 46 48 53 61 69 73 72 70 65 59 53 51 54 59 62 62 62 59 54 49 47 47 48 50 44 45 48 50 51 49 44 40 34 30 27 27 30 31 29 27 30 32 37 43 48 52 54 54 49 50 52 57 63 67 69 69 64 58 46 34 25 23 26 30 38 40 41 39 36 37 41 46 54 61 65 62 56 50 42 34 33 33 34 37 41 43 43 42 49 51 53 54 53 53 54 56 60 65 70 68 60 50 43 39 38 51 67 79 87 90 83 74 58 48 40 38 36 34 39 47 64 76 94 107 109 100 88 80 74 73 75 80 83 79 69 60 50 41 33 29 27 24 25 28 32 38 46 51 50 46 42 39 29 29 30 33 38 43 45 45 43 41 37 35 34 33 31 29 27 27 27 28 29 31 32 33 39 41 43 45 46 45 43 42 38 40 42 45 47 49 50 51 39 38 36 38 43 52 61 67 68 63 55 45 36 29 24 22 28 31 33 33 30 27 25 25 26 28 32 37 40 41 41 41 44 45 46 47 45 41 37 35 30 28 25 23 22 22 23 24 27 25 22 20 18 17 17 18 18 20 23 27 32 36 39 41 39 39 39 38 37 34 31 30 25 26 28 29 28 26 24 22 22 19 16 16 17 18 17 17 15 14 12 11 10 10 11 12 15 15 15 14 14 14 13 13 12 12 12 11 11 11 10 10 8 8 8 7 7 6 6 6 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 6 6 6 7 7 8 8 8 8 8 8 8 8 8 8 7 7 8 9 10 11 11 11 10 12 12 12 12 11 11 11 10 13 13 13 13 13 13 13 13 15 17 20 23 25 26 26 26 29 29 28 27 27 27 28 28 27 28 29 30 33 40 47 53 56 56 54 49 42 35 31 29 31 33 37 41 43 43 42 41 38 34 33 38 43 49 57 65 70 73 73 68 64 62 57 50 48 44 39 36 38 42 45 46 52 52 52 51 50 49 47 47 47 48 52 60 69 77 81 82 70 59 46 38 33 32 37 45 46 47 47 43 41 44 52 60 69 75 81 80 75 73 77 83 89 91 94 92 87 80 74 71 77 80 83 83 80 75 72 70 66 67 67 62 58 60 67 74 89 99 108 107 100 86 66 50 53 55 60 65 70 70 68 65 56 56 58 62 67 70 72 72 66 62 54 48 44 45 48 51 63 76 88 94 98 97 87 74 73 62 52 46 39 35 40 50 61 70 80 83 78 73 72 73 83 91 103 113 114 100 80 64 48 44 41 46 57 68 73 74 61 58 54 52 54 59 66 70 71 69 64 55 47 43 44 48 52 57 60 59 60 60 54 47 38 35 29 24 22 24 28 30 35 40 47 53 56 58 60 61 56 55 55 55 56 58 60 61 54 49 40 31 25 25 30 34 39 44 47 45 39 37 42 47 56 59 64 65 62 55 46 40 38 36 37 39 39 37 40 46 51 56 61 61 57 53 51 51 53 61 69 72 73 69 58 47 45 48 56 68 80 84 80 74 62 52 42 38 37 36 40 45 62 71 85 97 101 97 88 81 74 71 68 68 68 65 56 49 40 35 28 23 21 23 28 31 32 38 46 52 53 48 40 35 28 27 26 28 34 40 44 46 44 43 42 39 35 31 28 26 26 28 30 31 31 33 36 38 44 48 52 53 55 56 51 44 44 39 35 36 42 46 46 44 39 37 36 37 44 54 64 71 75 71 62 50 38 29 25 24 28 29 31 32 32 30 28 26 26 27 30 32 34 34 34 33 38 39 41 43 42 40 37 35 28 26 23 21 20 20 21 22 21 20 19 18 18 18 18 19 18 21 26 31 35 38 40 41 40 39 37 34 31 27 23 22 19 19 19 20 21 21 21 22 18 18 16 15 14 13 13 14 12 12 12 13 13 14 14 14 15 15 14 14 14 14 13 13 14 13 12 11 9 8 7 7 8 8 8 7 7 6 6 6 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 6 6 7 7 7 8 8 8 9 8 8 8 8 8 8 8 9 9 11 12 13 13 13 12 14 14 14 14 14 14 14 13 14 14 14 13 13 13 13 13 14 16 18 21 24 25 26 26 29 29 28 28 28 29 29 30 28 29 30 31 34 39 46 52 55 55 54 49 42 35 31 30 31 34 39 44 47 47 46 45 42 37 36 41 47 53 62 71 79 82 82 78 74 71 65 58 51 47 42 40 42 46 49 50 54 53 51 49 47 46 45 44 52 55 60 68 77 84 86 86 72 60 48 40 35 34 39 46 49 50 50 48 46 48 56 63 68 73 77 77 75 77 84 91 103 105 105 101 93 83 76 72 75 78 82 82 78 72 67 65 61 63 63 61 59 62 69 76 94 103 111 110 102 89 71 56 49 49 51 54 57 58 56 54 55 57 60 65 71 76 79 80 82 77 69 59 51 45 44 44 53 64 75 82 88 91 85 76 75 66 55 47 39 33 36 43 54 65 78 84 82 78 75 75 80 87 98 108 110 100 82 68 49 44 39 42 51 61 68 70 63 61 58 56 59 65 71 76 72 70 63 54 45 43 46 50 57 62 67 67 67 67 61 53 43 38 30 24 23 25 30 33 40 45 51 56 58 58 59 60 54 53 51 51 51 52 54 55 49 45 38 30 26 27 33 37 42 47 50 48 43 41 46 51 58 62 66 68 64 57 48 42 38 36 35 37 37 36 40 47 51 56 61 61 56 49 45 44 50 60 70 76 79 75 64 52 44 45 51 62 74 80 78 73 62 52 42 38 37 36 39 44 56 65 78 89 93 90 83 78 70 66 62 62 62 59 52 46 36 34 30 26 25 26 28 30 34 39 47 52 52 47 40 34 28 26 25 28 34 40 44 46 45 44 41 38 35 32 30 29 28 30 31 31 32 34 38 41 49 54 58 59 61 62 57 49 44 39 34 35 39 43 43 41 35 32 31 32 38 49 60 66 73 70 63 53 41 32 27 25 29 30 32 34 34 32 30 29 28 29 30 31 31 31 31 30 33 35 38 40 40 38 35 33 29 28 26 23 22 22 23 24 20 19 18 17 17 17 17 18 18 21 25 29 33 36 37 37 36 35 33 30 27 23 20 19 17 17 17 18 18 19 19 19 17 17 15 14 13 13 13 13 12 12 13 13 13 14 14 14 15 15 14 14 14 13 13 13 13 13 12 11 9 8 7 7 8 8 8 7 7 6 6 6 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 6 7 7 7 8 8 8 8 9 9 9 9 9 9 9 9 11 12 13 15 16 16 16 16 18 18 19 19 20 19 19 19 16 16 15 15 14 13 13 13 12 14 16 19 22 24 25 25 29 29 30 30 31 31 32 32 30 31 32 32 34 38 44 49 54 54 53 49 42 36 32 31 31 35 42 47 51 51 49 47 43 39 38 43 50 58 69 79 87 91 92 87 83 80 73 66 56 53 48 47 49 52 55 56 58 55 51 47 44 42 42 42 54 58 66 75 84 88 88 86 72 61 49 41 37 35 41 48 53 55 56 54 53 54 60 65 66 70 73 74 75 82 94 104 118 118 116 109 98 86 77 72 70 74 78 78 73 66 60 56 54 56 59 59 60 65 73 79 96 103 109 106 99 88 72 59 47 44 42 42 44 45 45 45 54 56 61 67 75 82 87 91 98 94 87 75 61 49 42 39 42 51 60 67 74 81 82 80 78 71 61 51 41 33 32 36 47 59 75 86 88 84 79 77 75 80 89 99 103 97 84 74 53 46 38 36 42 51 59 63 63 61 59 59 63 69 75 79 74 70 61 50 42 41 47 53 62 70 76 77 77 75 68 60 48 42 32 24 22 26 32 37 45 50 55 58 58 57 55 55 51 49 47 45 45 46 47 49 44 41 36 30 28 30 36 41 45 50 54 53 49 47 51 55 61 64 68 69 66 59 50 44 38 35 33 34 33 34 40 47 51 57 62 61 54 44 37 34 42 54 68 78 83 81 68 56 41 40 43 52 64 73 74 73 62 52 43 39 37 35 38 43 49 56 66 76 80 80 76 73 64 60 55 52 51 50 45 41 33 32 31 30 30 30 30 31 38 42 47 51 50 45 38 33 26 25 25 28 34 39 43 45 45 43 39 35 33 32 32 33 32 33 34 34 34 37 41 45 53 59 63 65 67 67 61 52 44 39 34 33 35 38 38 37 32 30 27 28 34 44 55 62 70 68 64 55 45 36 30 28 30 32 34 37 38 37 36 34 33 32 31 29 28 27 27 26 27 30 34 37 38 37 34 32 31 30 29 27 25 25 25 25 19 19 18 17 17 17 17 17 19 21 25 28 31 33 33 33 31 30 28 25 22 19 17 15 15 15 15 15 16 16 16 16 16 15 14 13 12 12 12 12 12 13 13 13 14 14 14 14 15 15 14 14 13 13 13 12 12 12 11 10 9 8 7 7 8 8 8 7 7 6 6 6 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 7 7 7 8 8 8 9 9 10 10 10 10 11 11 11 11 14 15 16 18 19 20 20 20 22 23 24 25 26 26 25 25 20 19 18 17 16 15 14 13 12 13 15 17 20 22 24 24 28 29 30 31 33 33 34 34 31 32 32 33 33 37 42 46 52 53 52 49 43 37 34 33 32 36 42 47 49 48 45 43 38 34 35 42 51 61 74 85 90 94 95 91 87 85 79 72 64 61 56 55 56 59 61 61 61 58 51 45 41 40 40 41 50 55 64 74 82 84 82 79 69 58 47 41 38 38 44 52 59 61 62 61 59 59 61 63 65 67 68 70 75 87 103 115 124 123 119 110 98 84 75 70 65 69 74 74 69 60 52 48 47 50 54 58 62 68 76 82 90 96 98 95 88 79 66 55 46 43 39 37 39 42 45 46 53 56 61 68 76 85 94 100 108 107 102 90 73 58 48 43 41 45 50 55 62 70 76 79 78 75 69 60 49 40 36 36 45 56 73 86 90 88 81 77 70 72 78 86 92 91 85 79 59 50 39 34 36 44 52 57 59 58 57 59 63 68 74 78 75 69 58 45 36 37 45 52 66 75 83 84 82 78 71 63 51 44 33 24 22 26 33 39 47 51 55 56 54 50 48 47 44 43 41 39 39 41 42 44 40 38 35 31 29 31 37 41 46 51 56 56 53 51 53 56 60 63 67 68 65 58 50 45 38 33 30 31 30 32 39 48 52 58 62 60 51 39 31 26 31 46 63 76 83 81 68 55 38 35 35 42 55 66 71 72 63 53 43 39 37 35 36 41 43 48 55 63 67 69 67 66 58 53 47 43 42 42 40 39 33 33 32 32 33 33 34 35 41 44 47 49 47 42 35 31 26 25 25 28 33 38 42 43 42 40 36 33 31 33 35 37 38 39 39 38 38 41 46 50 53 58 63 65 67 66 60 51 44 39 33 31 32 34 34 34 34 31 27 27 32 41 51 58 63 63 62 56 47 39 34 31 32 35 38 41 43 43 43 42 41 38 35 30 27 25 24 23 24 27 31 35 37 36 34 32 33 32 31 30 28 27 26 25 21 20 19 18 18 18 18 19 22 23 26 28 30 31 31 31 28 26 24 21 18 16 15 14 14 14 14 15 15 15 15 15 14 14 12 12 11 11 11 12 13 13 13 14 14 14 15 15 15 15 14 14 13 12 12 11 12 11 11 10 9 8 7 7 8 8 8 7 7 6 6 6 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 7 7 8 8 8 9 9 9 10 10 11 11 12 12 13 13 16 17 19 21 22 23 23 23 25 27 29 31 32 32 31 31 24 24 22 20 18 16 15 14 13 13 14 16 18 20 22 23 27 28 30 32 33 33 33 33 30 31 32 32 33 35 39 43 48 50 50 48 43 39 37 36 35 37 41 44 44 41 37 35 31 28 30 39 50 61 75 86 90 94 94 91 89 88 84 79 73 70 65 62 62 63 64 63 62 58 51 45 40 39 40 41 45 49 58 67 74 76 73 70 64 54 45 41 41 44 52 61 69 70 71 70 67 63 60 59 62 63 64 67 74 88 106 118 127 126 120 108 93 79 68 63 60 64 69 69 64 56 48 44 43 46 52 57 64 71 78 82 82 86 86 80 74 68 59 50 45 41 38 38 41 47 51 53 58 60 63 68 75 86 99 108 119 119 115 103 86 69 59 54 48 48 48 49 51 56 64 71 75 77 77 72 64 55 48 43 48 56 68 81 87 86 80 75 66 65 66 71 77 81 81 79 65 56 44 36 35 40 47 52 56 56 56 58 62 66 71 74 72 65 52 39 31 33 42 51 68 78 87 87 82 76 68 60 50 43 33 25 23 27 34 39 45 47 49 48 45 41 38 37 34 34 33 34 35 36 38 39 38 37 35 31 30 31 36 40 46 50 55 56 54 52 52 52 55 58 61 63 61 55 48 43 37 32 29 29 29 31 39 49 53 57 60 57 47 35 27 23 27 41 59 73 80 78 66 53 35 31 29 36 49 62 69 71 63 53 44 39 37 34 35 38 40 43 48 53 56 58 58 58 50 46 41 37 36 36 37 38 37 36 34 34 35 37 39 41 43 44 46 46 43 38 33 30 26 25 25 28 33 37 39 40 38 36 33 31 32 35 39 42 45 46 46 45 44 46 50 53 52 57 61 63 64 64 57 49 43 39 33 30 30 32 34 35 36 33 29 28 30 37 44 50 54 56 56 53 47 41 37 35 36 38 43 47 50 51 51 51 49 46 41 35 30 26 24 23 24 26 30 33 35 36 35 34 34 34 34 33 31 29 26 25 23 22 21 20 20 20 21 21 24 25 27 29 30 31 30 29 26 24 22 19 17 15 15 15 15 15 15 15 15 15 15 15 13 13 12 11 11 11 11 12 13 13 14 14 14 15 15 15 15 15 14 13 12 11 11 10 11 10 10 9 8 8 7 7 8 8 8 7 7 6 6 6 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 8 8 8 8 9 9 9 10 11 11 12 12 13 14 14 15 18 19 21 23 24 25 26 26 28 30 33 36 37 37 36 35 29 28 26 24 21 19 17 16 15 15 15 16 17 19 20 21 26 27 29 31 31 31 30 29 28 29 31 31 31 34 37 40 44 46 48 47 44 42 40 41 38 39 41 41 39 36 32 29 27 25 28 38 49 59 72 82 88 91 92 89 88 91 90 87 82 78 72 68 66 65 64 62 59 55 49 43 39 38 39 40 43 46 52 60 66 68 67 64 60 52 46 45 49 55 66 76 85 85 85 82 76 69 61 56 58 58 58 62 70 84 100 110 125 122 115 102 86 71 60 54 56 60 64 65 61 54 48 45 43 46 52 58 66 72 78 80 77 79 76 69 63 59 53 47 42 40 39 41 46 52 56 58 64 64 64 64 69 81 97 108 124 125 122 111 93 78 70 67 61 58 54 50 46 45 51 59 70 78 85 85 79 72 61 52 50 53 60 70 78 80 76 71 63 59 55 56 62 70 74 75 69 62 51 41 37 39 44 47 55 55 56 57 60 63 66 68 64 58 46 34 28 32 44 54 72 82 90 87 80 72 63 55 47 42 34 28 26 30 35 39 42 43 43 40 36 33 32 32 27 29 30 32 34 34 34 34 37 36 35 32 30 32 35 38 45 49 54 55 54 51 48 47 48 51 55 57 56 51 45 42 36 32 29 29 30 32 39 48 51 53 54 49 40 31 25 24 29 42 57 68 75 73 62 50 32 28 27 34 48 61 68 70 63 53 44 40 37 33 33 36 38 40 42 45 47 48 49 49 43 40 36 32 31 33 35 37 40 39 38 37 38 41 43 45 43 43 43 42 39 35 31 29 27 26 26 28 32 35 36 36 35 33 32 32 35 40 45 49 52 53 54 53 51 51 53 55 53 57 60 60 61 62 56 49 41 38 34 30 30 32 36 39 38 36 32 29 30 32 36 39 44 46 48 47 44 41 39 38 40 43 48 53 57 59 60 60 58 55 50 44 37 31 27 25 25 27 29 31 33 35 36 36 36 37 38 38 36 32 29 26 24 24 23 22 21 21 22 22 24 26 28 29 30 30 29 28 25 23 21 18 16 15 16 16 16 16 16 16 15 15 15 15 13 12 12 11 11 11 12 13 14 14 14 14 15 15 15 16 15 15 14 13 12 11 10 10 10 9 9 9 8 8 7 7 8 8 8 7 7 6 6 6 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 8 8 8 9 9 9 10 10 11 12 12 13 14 15 16 16 19 20 22 24 25 26 27 27 30 32 36 39 41 41 40 39 34 32 30 27 24 21 19 18 18 17 17 16 17 18 19 20 25 26 28 29 29 28 27 25 25 27 29 29 30 32 36 39 40 43 46 46 45 44 44 44 42 42 41 40 37 34 32 30 30 28 32 41 50 58 67 76 83 85 85 83 85 90 93 92 89 85 78 72 68 65 62 59 53 50 45 41 38 37 37 38 41 42 46 51 57 61 61 60 61 54 50 53 59 69 82 94 103 102 100 96 88 76 64 56 52 52 53 57 65 77 89 98 109 107 101 90 77 64 55 51 53 57 61 62 59 54 50 48 45 48 53 60 67 73 76 78 73 73 69 60 54 52 49 44 41 41 43 47 53 59 61 62 64 62 58 55 57 69 86 100 115 118 116 107 93 82 79 80 79 73 66 60 50 42 45 54 65 79 92 95 92 84 71 59 49 48 49 57 66 72 72 69 62 55 46 44 50 59 66 69 70 65 56 46 40 39 41 43 52 52 52 54 55 57 58 59 55 50 41 32 29 36 50 61 78 88 93 88 78 68 59 52 44 41 37 33 32 34 37 40 41 41 39 35 31 29 30 32 31 33 36 39 39 38 36 34 33 34 34 32 31 33 36 39 45 49 53 55 53 49 45 43 43 46 50 52 52 49 44 41 35 31 29 30 31 33 40 48 47 48 46 40 32 26 24 25 31 41 53 61 66 64 54 43 29 26 27 35 49 61 68 69 63 53 44 40 37 33 32 35 37 38 39 40 40 40 39 39 35 33 31 29 28 30 34 37 41 42 43 44 44 45 45 45 42 42 40 38 35 32 30 28 29 28 27 29 31 33 33 32 33 33 34 36 41 47 52 56 58 59 61 60 58 56 55 56 52 55 56 55 56 57 54 47 40 37 34 31 31 34 39 43 44 42 38 35 32 31 32 32 35 37 40 41 40 39 40 41 43 46 52 58 63 66 67 68 66 63 58 52 45 38 32 29 27 27 27 27 29 32 35 37 40 41 43 43 41 37 32 29 24 23 22 21 21 21 21 22 23 24 26 28 29 28 28 27 24 22 19 17 15 15 16 16 16 16 16 15 15 14 14 14 13 13 12 12 12 12 13 14 14 14 14 15 15 15 16 16 15 15 14 13 11 10 9 9 9 9 9 8 8 8 7 7 8 8 8 7 7 6 6 6 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 8 8 8 9 9 10 10 10 12 12 13 14 15 16 16 17 19 20 22 24 26 27 28 28 30 33 37 41 43 43 41 40 36 35 32 29 26 23 20 19 20 19 18 17 16 17 18 19 24 25 27 28 28 26 24 23 23 25 27 28 29 31 35 38 38 41 44 46 45 45 46 46 45 44 42 40 38 35 34 33 34 33 36 44 52 57 64 71 77 80 79 77 80 88 93 93 93 88 81 74 69 64 60 57 48 45 42 38 36 36 36 36 39 39 41 45 50 55 57 57 62 56 54 59 67 79 94 106 115 114 111 105 95 81 67 57 47 47 49 53 60 71 81 88 90 89 86 79 69 60 54 51 51 55 59 60 58 54 52 50 47 50 54 61 68 73 75 76 69 69 63 54 48 48 46 42 43 44 47 53 59 64 65 65 60 57 51 44 45 56 76 90 101 104 105 99 89 83 84 88 92 85 78 69 56 45 46 55 62 79 96 101 99 91 76 61 47 43 41 47 58 67 69 68 62 53 42 38 43 52 61 65 70 65 58 49 42 39 39 41 48 48 48 49 49 50 51 51 49 45 38 31 31 40 56 68 83 92 96 89 77 67 58 51 43 41 39 37 37 38 39 40 42 41 38 33 29 29 31 33 38 41 45 48 47 44 40 37 31 32 32 32 32 34 38 41 46 49 53 55 53 49 44 40 40 43 47 50 50 48 44 41 35 31 30 31 32 33 40 48 44 43 40 34 26 22 24 26 31 39 49 54 57 56 46 36 28 26 28 37 51 63 68 68 63 54 45 40 37 32 32 34 36 36 37 37 36 35 34 33 30 29 28 27 26 29 33 36 41 43 46 49 49 48 45 43 41 40 39 36 33 31 29 28 30 28 28 29 31 32 31 30 33 33 35 39 45 52 57 61 61 63 65 65 62 58 56 56 50 52 52 50 51 53 50 45 39 37 34 31 32 36 42 47 50 48 45 41 37 33 31 30 30 32 35 37 37 38 40 42 45 48 54 61 66 69 71 72 70 68 64 58 50 42 35 31 28 27 25 25 27 30 34 37 43 45 46 47 44 40 35 32 23 22 21 20 20 20 21 21 21 22 24 26 27 27 26 26 23 21 18 15 14 14 15 16 15 15 15 14 14 13 13 13 14 13 13 12 12 13 14 14 14 14 14 15 15 16 16 16 15 15 14 13 11 10 9 8 9 9 8 8 8 8 7 7 8 8 8 7 7 6 6 6 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 9 9 9 10 10 11 11 11 13 13 14 15 16 17 17 18 18 19 21 22 24 26 28 28 31 33 36 39 41 41 41 40 39 37 35 32 29 26 23 22 23 23 23 23 23 23 23 23 26 27 29 29 29 27 24 23 19 20 21 23 26 28 31 32 37 39 42 43 44 45 47 50 49 48 46 44 41 40 39 39 44 45 48 51 56 60 64 67 66 67 69 71 74 81 89 95 88 86 82 76 68 62 56 53 47 45 42 39 37 35 35 34 38 40 43 47 53 59 63 66 68 69 70 70 74 84 98 108 122 130 130 118 108 99 81 62 53 50 48 51 59 67 72 74 76 73 72 72 70 65 59 56 51 55 58 59 59 61 62 61 61 63 64 64 68 74 74 70 69 66 62 59 57 54 52 49 51 50 51 55 62 66 67 66 64 51 39 37 39 47 62 77 90 91 86 77 71 75 87 97 102 103 99 84 67 57 58 64 76 90 99 99 98 96 82 63 50 42 35 37 48 60 67 68 63 56 45 37 35 41 50 57 63 64 62 54 45 39 40 43 44 46 47 46 44 43 44 45 46 46 44 43 46 56 71 82 96 102 102 92 78 66 54 45 43 41 41 42 45 46 45 44 43 40 35 32 31 34 37 40 46 54 59 59 56 52 42 33 31 25 24 30 36 40 45 49 53 57 58 56 53 48 39 29 32 34 39 44 48 48 44 40 35 31 28 29 33 37 38 37 42 39 33 29 26 26 28 29 32 36 41 45 46 43 39 36 27 29 34 41 50 59 67 71 62 57 48 38 31 30 33 37 37 38 38 38 37 35 33 31 31 29 26 25 25 27 30 32 41 42 46 51 53 52 48 44 41 37 33 30 30 31 32 32 31 31 31 30 30 30 29 29 32 36 42 45 48 52 59 65 69 67 66 65 63 60 56 53 50 48 47 47 48 47 45 44 39 37 34 33 35 40 46 49 56 57 57 52 44 36 30 28 27 30 34 38 41 43 42 42 48 50 55 60 65 70 73 75 74 71 66 58 49 40 33 29 28 26 23 21 23 27 32 36 43 45 48 49 47 42 36 31 26 25 22 20 19 19 20 21 22 22 23 24 25 26 26 27 20 19 18 16 14 14 13 13 14 14 14 14 14 14 14 14 12 13 15 17 18 19 19 19 18 18 17 16 15 15 15 15 14 13 12 11 9 8 7 6 8 8 8 8 8 8 8 8 7 7 7 7 7 7 7 7 8 7 6 5 5 5 5 6 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 9 9 9 10 10 10 11 11 12 12 13 14 15 16 16 17 17 18 19 21 23 24 26 26 28 30 33 36 38 38 37 37 36 35 33 30 28 25 24 23 23 23 24 24 25 25 26 26 27 28 29 30 29 27 25 23 20 20 20 21 23 25 28 29 35 37 40 41 42 43 46 49 51 51 50 48 47 46 46 45 49 49 50 52 54 57 60 62 58 59 61 63 66 72 80 86 86 84 80 74 68 61 56 53 49 47 44 41 38 36 35 35 34 36 41 49 58 67 75 79 82 81 80 78 79 87 99 109 125 133 135 126 116 108 91 73 62 59 55 56 58 61 62 61 71 71 72 75 75 71 66 62 55 57 59 60 62 66 69 70 68 70 70 69 71 75 74 69 68 65 62 60 59 59 58 56 57 55 54 57 62 66 68 67 64 51 40 36 38 45 60 74 75 76 72 65 62 69 84 96 107 110 108 98 84 76 77 81 91 103 109 107 103 98 82 64 49 41 34 36 47 59 66 69 66 59 48 38 36 39 46 51 59 60 59 53 45 40 40 43 43 45 46 45 43 42 43 44 49 50 50 51 55 65 79 90 101 107 107 97 84 72 59 50 46 45 45 46 49 50 50 49 45 41 37 33 33 36 41 45 55 63 68 67 63 57 46 36 31 26 26 33 41 47 52 58 63 66 66 61 56 50 40 30 32 34 39 45 49 49 45 41 34 29 26 27 32 36 38 38 38 35 30 26 24 25 27 29 31 33 36 38 37 35 32 30 28 30 34 40 48 57 64 69 62 57 49 39 31 29 31 34 36 37 38 38 37 35 33 32 31 30 27 25 26 27 30 32 40 42 46 51 53 52 47 42 38 35 30 28 29 31 32 32 31 31 30 29 28 28 29 29 33 37 42 45 47 51 58 64 69 69 69 68 65 61 56 52 46 45 44 46 48 49 48 47 44 42 40 39 41 46 51 55 62 63 63 59 51 42 35 32 29 31 33 36 39 40 40 40 46 49 53 59 64 67 69 70 70 67 62 56 48 40 34 30 27 25 23 22 24 28 32 36 42 44 47 47 45 39 33 29 23 22 19 17 17 17 19 20 20 20 21 22 23 23 24 24 19 18 17 15 14 13 13 13 13 13 13 14 14 15 15 15 16 17 18 19 20 20 20 20 19 18 17 16 15 14 14 14 13 13 12 11 9 8 7 7 8 8 8 8 8 8 8 8 7 7 7 7 7 7 7 7 8 7 6 5 5 5 5 6 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 9 9 9 9 10 10 10 11 11 11 12 12 13 14 14 15 15 16 17 18 20 21 22 23 23 25 28 30 32 32 32 31 31 30 29 28 26 25 24 23 24 25 25 26 28 29 29 30 29 30 31 31 30 29 26 25 23 22 20 20 20 22 25 26 32 34 36 37 38 41 44 47 53 53 54 55 55 55 55 55 54 53 52 51 51 51 53 53 49 50 52 54 57 63 70 75 82 80 76 71 66 62 58 56 53 52 49 46 42 39 37 36 33 36 42 52 64 77 88 95 98 96 91 85 82 86 96 105 122 131 136 130 123 115 101 86 77 75 72 70 68 66 62 59 66 70 76 82 86 86 80 75 65 63 61 62 65 71 76 81 79 81 80 78 78 78 74 68 67 64 62 61 63 66 67 67 66 62 59 59 61 65 68 70 65 55 46 43 44 50 61 72 66 64 59 53 52 62 79 93 110 115 118 114 106 102 105 110 116 124 126 119 111 100 82 63 50 43 35 37 47 58 66 69 70 63 52 42 37 37 40 43 52 55 55 52 46 41 41 42 42 44 45 45 43 41 41 42 49 51 55 58 63 73 86 96 105 109 109 100 88 77 64 54 49 49 49 51 54 56 55 54 47 43 38 34 35 40 47 52 64 71 76 74 69 61 48 37 30 27 29 38 49 57 66 73 79 82 80 71 62 52 41 31 31 34 40 47 51 51 46 42 31 27 23 24 29 35 38 38 35 31 26 22 21 23 26 28 30 30 30 29 28 27 26 26 30 31 34 39 45 53 60 63 61 57 49 39 31 28 28 30 35 36 38 38 38 36 33 32 31 30 28 26 26 27 29 31 38 41 46 51 53 50 44 39 34 31 27 25 27 30 31 32 32 30 28 26 26 27 29 30 33 37 40 42 44 48 55 61 68 70 71 71 67 61 55 51 45 45 45 47 50 52 51 50 50 48 45 44 46 51 56 60 66 68 68 64 56 46 39 35 31 32 33 34 35 36 36 37 42 45 49 55 59 61 62 62 61 59 56 51 45 39 34 31 27 26 24 23 25 28 32 35 40 42 43 43 39 34 28 25 18 17 16 15 15 15 17 18 18 18 19 20 20 21 21 22 18 17 16 14 13 13 12 13 12 13 14 15 16 17 18 18 22 22 23 23 23 23 22 22 20 19 17 16 14 13 13 13 13 12 12 11 9 8 8 7 8 8 8 8 8 8 8 8 7 7 7 7 7 7 7 7 8 7 6 5 5 5 5 6 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 8 8 9 9 9 10 10 10 10 10 11 11 12 12 12 13 13 14 15 16 17 18 18 19 19 20 22 24 25 26 26 25 25 25 25 25 24 24 24 24 24 25 26 28 30 31 32 33 32 33 33 33 33 32 30 29 28 26 23 21 21 22 24 25 28 30 32 33 35 37 42 45 52 54 56 59 61 61 61 61 56 54 51 48 46 45 45 45 44 46 47 49 51 56 63 67 73 72 69 67 64 62 61 60 61 60 58 54 50 45 41 38 36 39 45 55 69 85 99 107 111 107 99 88 81 81 88 94 110 120 128 127 123 116 105 95 88 88 86 84 80 74 68 64 65 75 86 97 104 107 102 94 79 72 66 65 67 72 79 86 88 90 90 87 85 83 76 68 66 63 61 62 66 71 75 77 73 69 64 60 60 64 68 71 69 65 62 62 63 67 72 76 71 64 55 49 49 57 74 90 109 115 121 123 123 126 133 141 145 148 144 132 118 102 81 64 53 46 39 39 47 58 66 69 71 65 55 46 39 36 36 37 46 49 51 49 46 42 41 42 44 46 47 47 45 42 42 42 44 48 54 59 64 74 85 94 101 105 105 98 88 78 65 55 50 50 51 54 57 58 57 56 47 43 38 35 37 43 52 57 67 74 79 76 70 60 46 35 30 28 32 43 56 68 81 91 99 101 96 84 69 55 41 30 29 33 41 48 53 52 47 42 29 24 21 22 28 35 38 39 35 31 25 20 18 20 23 25 31 29 27 25 25 25 27 28 32 32 33 36 41 47 53 56 58 54 48 39 31 27 26 27 33 34 37 38 38 36 34 32 30 29 27 26 26 27 29 30 37 40 45 50 52 48 42 36 29 26 23 22 25 28 30 31 32 30 27 25 24 26 28 30 32 35 37 37 38 42 50 56 63 67 71 71 67 60 53 49 50 50 52 55 58 58 57 55 55 52 49 47 48 52 56 60 65 67 68 65 57 47 39 35 34 33 33 32 32 32 33 33 36 39 43 48 51 52 52 51 51 50 48 45 42 38 35 33 29 28 27 26 27 29 32 33 35 36 36 35 32 28 23 20 15 15 14 14 14 15 16 17 18 18 19 19 20 20 21 21 19 18 17 16 15 14 14 14 14 15 16 18 19 21 22 23 27 27 27 27 26 25 24 23 21 20 18 15 13 12 12 11 12 12 11 10 10 9 8 8 8 8 8 8 8 8 8 8 7 7 7 7 7 7 7 7 8 7 6 5 5 5 5 6 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 8 8 8 9 9 9 10 10 10 10 10 10 11 11 11 11 12 12 13 13 14 14 15 15 15 16 17 18 19 20 20 21 20 20 21 21 22 23 23 23 23 24 25 27 29 31 32 33 34 34 35 35 35 35 35 34 34 32 29 26 25 25 25 26 27 28 29 30 31 34 38 42 48 51 55 59 62 62 61 60 54 51 47 43 41 40 41 42 43 44 46 46 48 51 56 60 63 63 62 61 61 62 63 64 68 68 67 64 59 53 48 45 39 41 47 57 73 91 108 117 118 114 104 91 80 76 79 84 95 105 116 119 118 114 108 102 96 96 94 90 83 76 70 67 72 86 103 116 127 132 126 115 97 84 71 68 68 70 76 84 92 95 96 93 91 87 79 69 66 63 60 62 67 74 79 82 78 73 67 61 58 61 66 70 73 77 82 86 89 91 90 88 79 68 56 50 49 55 72 89 106 112 121 128 134 144 156 165 170 166 157 141 123 104 83 69 58 52 45 44 49 57 63 66 68 64 57 50 44 40 37 36 43 44 46 46 45 43 42 42 47 49 51 51 48 45 44 44 41 46 51 56 60 68 78 85 93 97 97 92 85 77 66 55 49 49 50 53 56 57 55 53 45 41 36 34 36 43 52 58 66 73 77 74 68 59 45 34 30 29 34 46 60 76 93 107 117 119 114 98 78 59 42 30 28 33 41 51 56 54 48 43 29 25 22 24 30 37 40 41 38 34 26 20 17 18 20 23 29 28 26 24 25 27 30 32 34 33 32 32 35 39 44 47 52 51 46 39 32 27 25 25 31 33 36 38 38 37 34 32 28 27 27 26 27 28 29 30 38 40 44 48 49 46 39 34 26 23 20 20 23 27 29 30 32 30 27 25 24 26 28 30 30 32 32 31 30 35 43 49 57 62 68 70 66 59 53 51 55 58 62 68 72 73 70 67 62 58 54 50 49 51 55 57 61 63 65 62 55 47 41 37 36 35 34 32 31 31 31 31 30 32 36 39 41 41 41 40 41 41 41 41 41 39 38 38 34 33 32 30 29 29 30 30 28 28 28 28 26 23 20 18 16 16 16 15 16 16 17 17 20 20 20 20 20 21 21 21 21 20 19 18 17 17 17 17 17 18 19 21 23 25 26 27 29 29 29 29 27 26 24 23 20 19 17 15 13 12 11 11 12 12 11 10 10 9 8 8 8 8 8 8 8 8 8 8 7 7 7 7 7 7 7 7 8 7 6 5 5 5 5 6 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 7 8 8 8 9 9 9 9 10 10 10 10 10 10 11 11 12 12 12 12 12 12 12 12 13 13 14 14 15 16 17 17 16 16 17 18 19 21 21 22 21 22 23 25 27 28 30 30 32 33 33 34 35 36 37 38 37 36 34 32 30 29 28 27 27 27 28 28 28 31 35 39 44 48 53 57 60 59 58 56 48 46 43 40 39 40 42 44 45 46 47 47 47 48 52 55 57 56 56 56 57 59 61 63 69 70 71 70 68 63 59 56 44 45 49 58 73 92 110 121 122 118 109 95 82 74 74 76 83 93 105 112 113 112 111 111 109 107 103 96 86 78 73 70 82 101 122 137 150 155 147 134 114 95 78 72 69 67 72 80 89 94 97 97 95 92 82 72 66 63 59 60 65 72 79 82 78 74 67 60 56 57 62 67 75 85 96 103 109 111 107 102 86 72 59 53 51 54 69 86 102 109 120 130 141 153 166 175 176 169 155 137 119 100 83 73 61 56 51 48 50 53 57 58 61 60 57 54 50 46 43 41 42 42 43 44 44 44 43 43 49 52 54 54 51 48 46 46 41 45 49 51 53 58 66 72 80 85 86 84 81 76 65 55 46 47 48 51 53 53 51 48 40 37 33 31 34 41 49 54 63 70 73 70 65 58 47 37 32 30 34 45 61 79 101 119 134 137 131 113 88 65 44 30 29 35 44 55 60 59 52 46 33 30 28 31 37 43 45 44 42 37 29 22 18 19 22 24 29 28 28 28 29 30 32 33 35 33 30 28 29 32 36 39 46 45 44 39 33 28 26 25 29 31 35 38 39 37 34 32 27 27 28 28 29 31 33 33 39 40 42 45 46 43 38 33 25 22 19 19 22 26 28 29 32 30 28 26 26 27 29 30 29 30 28 26 24 29 37 44 53 60 67 70 67 62 58 57 63 68 77 86 92 92 88 83 69 65 59 53 49 49 51 53 55 57 58 56 51 46 42 40 38 37 36 35 33 32 31 30 28 29 30 31 32 32 32 32 36 37 39 41 43 44 45 45 41 40 38 35 32 29 27 26 22 22 22 22 22 21 20 20 20 20 20 20 20 20 20 19 21 21 21 21 21 21 21 21 21 21 20 19 18 18 19 19 19 20 21 23 25 26 28 28 29 29 28 28 26 25 23 22 19 18 16 14 13 12 12 11 11 11 11 10 10 9 9 9 8 8 8 8 8 8 8 8 7 7 7 7 7 7 7 7 8 7 6 5 5 5 5 6 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 7 7 8 8 8 9 9 9 11 11 11 11 11 11 11 11 12 11 11 11 11 11 11 11 12 12 12 12 13 14 15 16 14 14 15 16 17 19 20 20 19 20 21 22 23 25 26 26 28 29 30 31 33 36 38 39 39 38 38 37 35 32 29 28 28 28 28 26 26 29 33 37 42 45 51 55 57 56 53 50 43 41 39 38 40 44 48 51 52 53 53 52 50 51 53 55 55 54 53 52 53 55 57 58 63 66 70 73 74 72 69 67 56 54 54 59 70 86 102 112 120 117 109 96 81 72 69 69 73 82 95 104 108 109 113 117 117 114 108 97 86 78 76 76 92 114 138 154 167 173 163 147 126 104 84 76 72 67 70 78 84 90 96 98 98 95 86 76 67 63 58 57 62 69 75 79 75 72 66 58 53 53 58 63 73 85 99 108 115 121 119 112 99 82 65 58 53 51 63 78 94 103 117 130 142 152 161 166 163 153 137 121 104 89 77 71 62 59 54 50 49 49 49 49 53 54 56 56 55 53 50 48 43 42 41 42 43 44 44 44 50 53 56 56 53 49 47 46 41 43 45 44 43 46 52 58 65 70 73 73 73 71 61 51 45 45 47 49 51 50 46 43 34 32 29 28 31 37 44 48 58 63 66 64 60 56 47 39 33 31 33 43 59 80 106 126 147 151 147 127 99 72 48 33 32 38 49 60 66 64 57 51 40 38 38 41 47 51 51 49 44 39 31 24 21 22 26 29 34 35 36 36 37 36 36 35 35 32 28 24 24 26 29 32 39 40 41 38 34 29 27 27 27 30 35 38 39 37 34 32 28 29 30 32 34 36 38 39 40 40 41 42 43 41 37 33 25 22 19 18 21 25 27 28 31 31 30 29 28 28 29 29 30 29 27 23 21 25 34 41 53 61 70 73 71 68 67 68 79 85 95 105 109 106 98 91 73 68 60 52 46 44 44 44 45 47 48 47 43 41 40 40 39 39 39 38 37 34 32 30 28 28 27 26 26 27 28 29 35 37 40 44 48 51 53 54 48 46 44 40 34 29 24 22 18 18 19 20 21 23 24 24 26 26 26 25 25 24 23 22 21 21 21 21 21 21 21 21 21 20 19 18 18 18 19 19 20 20 21 22 24 25 26 27 26 26 26 26 24 23 21 21 17 17 15 14 13 12 12 12 11 11 10 10 10 10 9 9 8 8 8 8 8 8 8 8 7 7 7 7 7 7 7 7 8 7 6 5 5 5 5 6 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 7 7 7 8 8 9 9 9 11 11 11 11 11 11 11 11 12 12 11 11 11 10 10 10 12 12 12 12 12 13 15 15 13 13 14 15 16 18 18 19 18 18 19 20 21 22 23 24 25 25 27 29 31 34 37 39 38 39 40 39 37 34 30 28 29 29 28 26 25 27 32 35 41 44 50 54 56 54 50 47 39 38 37 38 42 47 53 57 59 60 60 58 56 55 57 58 56 54 52 50 50 51 53 54 57 61 68 74 77 78 76 75 68 65 61 60 67 79 92 101 116 114 107 94 79 69 64 64 67 75 88 98 103 106 112 119 112 109 102 91 80 75 74 76 98 121 146 163 176 182 170 153 133 109 88 79 74 68 70 78 80 87 94 97 99 97 88 78 68 63 57 56 59 66 73 76 73 71 65 57 51 51 56 61 70 83 96 105 115 123 123 118 112 93 74 64 55 49 57 71 87 98 114 129 140 146 151 154 146 135 119 103 90 77 69 66 62 60 55 51 48 45 44 43 48 51 54 58 59 57 55 53 44 42 40 40 42 44 45 45 50 53 56 56 53 49 47 46 40 41 40 38 35 36 41 46 53 58 61 63 65 65 56 46 44 45 46 48 49 48 44 40 30 28 26 26 29 34 40 44 52 57 60 58 55 52 46 38 34 31 33 42 57 79 107 129 154 159 156 135 106 77 51 35 34 41 53 64 70 68 61 54 45 44 44 48 54 57 55 53 45 39 32 25 23 25 30 33 41 42 44 45 44 42 39 38 35 32 27 22 21 22 25 28 35 37 39 38 34 31 28 28 26 29 34 38 39 38 34 32 30 31 33 35 38 40 42 43 41 40 40 40 41 39 36 33 25 22 19 18 21 24 27 27 31 31 31 30 30 30 29 29 31 30 27 22 20 24 33 41 55 63 72 76 75 73 74 76 93 99 109 117 119 112 100 91 72 67 58 48 41 37 36 37 37 38 39 38 36 35 36 37 39 40 41 41 39 36 33 31 30 28 26 24 24 25 27 28 36 38 42 47 52 56 58 60 52 51 47 42 36 29 23 19 17 17 18 20 22 25 27 28 30 30 30 29 28 27 25 24 20 20 20 20 20 20 20 20 20 19 18 17 17 17 18 18 19 19 20 21 23 24 25 25 24 24 24 24 23 22 20 20 16 16 14 13 13 13 13 13 11 11 10 10 10 10 9 9 8 8 8 8 8 8 8 8 7 7 7 7 7 7 7 7 8 7 6 5 5 5 5 6 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 8 8 7 8 9 10 11 12 13 12 12 11 11 11 12 12 14 14 14 14 14 14 14 14 13 13 13 14 14 14 14 14 14 15 16 17 18 20 21 21 21 20 19 18 18 19 21 22 26 25 26 26 28 31 34 36 37 38 40 40 38 34 30 28 26 25 25 25 26 29 33 35 43 47 51 53 51 48 45 44 41 41 44 49 56 62 65 66 67 65 64 62 61 61 62 63 59 61 58 53 50 50 47 43 49 49 56 69 78 81 82 85 79 76 71 67 69 77 88 97 102 100 95 88 80 72 66 62 75 81 92 103 111 116 117 117 116 107 95 85 76 70 73 80 103 125 153 171 179 175 162 150 123 109 95 84 76 69 68 71 74 80 89 96 99 96 90 86 78 71 62 58 59 63 66 68 65 65 63 57 51 48 50 53 64 70 80 92 104 113 119 122 111 99 81 65 56 57 63 68 83 99 118 130 137 139 134 128 116 103 89 81 73 64 61 65 59 59 57 53 48 44 41 40 42 50 59 64 67 68 63 57 44 39 35 37 46 53 56 55 60 53 49 49 49 47 48 52 50 50 46 38 35 38 40 39 44 46 49 52 53 51 49 47 47 45 43 44 45 44 40 36 27 26 24 24 28 33 40 44 49 51 53 55 55 52 49 47 39 33 30 35 48 72 103 128 151 162 163 143 110 78 54 41 37 44 56 67 74 74 68 63 53 51 51 55 62 64 61 57 47 43 36 29 24 26 31 35 45 49 54 56 53 48 43 41 36 32 27 22 20 20 23 25 29 31 33 34 34 31 28 25 29 31 33 35 36 37 36 36 33 35 40 44 47 47 47 46 46 44 41 39 38 36 33 30 28 25 22 19 19 21 24 26 29 32 35 35 32 29 28 27 28 25 24 24 22 22 30 40 51 61 74 81 82 84 90 96 100 113 126 129 126 119 103 88 74 64 50 41 37 34 30 26 31 30 29 29 29 30 32 33 36 41 44 42 42 42 38 32 31 29 24 21 20 22 24 26 30 35 43 51 56 59 58 58 50 48 45 40 34 28 23 21 15 17 21 25 29 33 35 36 38 37 35 32 30 27 25 24 24 23 21 19 17 16 16 16 17 17 16 16 16 16 16 16 15 16 17 19 21 22 22 22 21 21 20 19 18 18 19 19 17 16 15 14 13 12 12 12 13 13 12 11 10 10 9 8 10 10 9 9 9 8 8 8 6 6 6 6 6 6 6 6 7 7 7 6 6 5 5 5 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 8 8 8 8 9 10 11 12 14 13 13 12 12 12 13 14 16 16 16 16 16 16 16 16 15 15 15 15 15 16 16 16 16 17 17 18 19 20 21 22 22 21 20 19 19 20 21 22 24 24 25 26 27 29 31 32 34 35 36 36 35 31 28 25 25 24 24 26 28 32 36 38 44 48 51 53 51 49 48 47 46 47 50 56 63 68 70 70 69 67 64 62 61 62 64 66 66 68 67 61 57 55 50 44 45 45 50 62 72 77 81 86 85 83 79 76 76 82 90 96 100 97 92 85 78 72 67 65 76 83 95 107 116 120 121 120 115 106 94 84 76 71 75 83 104 123 147 161 165 160 147 135 114 102 90 81 74 68 67 69 74 79 87 95 98 96 93 90 82 75 68 64 64 66 68 68 69 68 65 61 56 54 54 55 59 63 70 79 90 100 109 113 112 103 87 70 58 55 59 64 79 95 114 127 132 131 124 116 103 90 77 70 63 56 55 59 59 59 58 55 51 47 44 43 47 55 64 70 75 77 70 61 46 40 35 38 47 55 59 60 62 54 47 46 46 47 52 58 60 62 59 51 46 46 45 41 39 40 42 43 44 45 44 44 47 45 44 45 46 44 39 35 27 26 25 26 30 35 41 45 48 50 52 55 56 56 55 54 43 36 31 34 45 67 97 121 148 158 160 140 107 76 52 39 41 49 61 73 79 78 73 68 59 57 56 59 63 64 60 55 46 42 36 29 26 27 33 38 46 51 56 58 56 50 45 43 36 33 28 23 21 22 24 25 28 30 33 35 35 34 31 30 30 31 32 33 34 35 36 36 36 39 45 49 52 52 50 49 46 43 39 37 36 34 31 29 27 24 21 19 20 22 25 27 31 33 36 35 32 29 27 27 27 24 23 24 23 23 31 40 55 65 78 86 88 90 96 101 106 117 126 127 123 114 99 85 65 55 43 35 31 30 26 23 26 25 24 23 23 25 27 28 35 41 45 45 45 45 41 35 33 31 26 23 22 23 25 26 31 35 42 49 53 55 55 54 49 47 43 38 32 27 23 21 18 20 24 29 34 38 40 41 39 38 36 33 31 28 26 25 23 22 20 18 16 14 14 13 14 14 14 14 14 14 14 14 13 14 15 17 18 19 19 20 19 18 18 17 17 17 18 18 17 16 15 14 13 12 12 12 13 13 12 12 11 10 9 9 10 10 10 9 9 9 8 8 6 6 6 6 6 6 6 6 7 7 7 6 6 5 5 5 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 8 8 8 8 9 10 12 12 15 15 14 14 14 15 15 16 19 19 19 19 19 19 19 19 18 18 18 18 18 18 18 18 19 20 20 20 21 22 22 22 25 24 23 22 21 21 21 21 23 24 25 26 27 27 27 27 30 31 32 32 30 27 24 22 22 22 24 26 30 35 39 42 46 49 52 53 52 51 51 52 54 55 60 66 71 74 73 71 68 65 62 59 60 63 67 70 72 76 77 73 68 63 55 47 43 40 42 52 62 70 79 86 89 89 88 86 85 87 91 94 97 93 88 81 75 71 68 66 75 84 99 113 123 127 127 125 116 106 94 85 77 74 80 88 108 123 139 147 146 139 126 114 102 92 83 78 74 69 69 71 75 79 86 92 97 98 97 96 89 85 80 76 74 74 73 72 75 73 70 68 68 67 66 65 62 61 62 66 74 85 95 102 107 102 92 76 61 55 57 62 79 96 117 129 134 131 121 112 94 83 71 64 58 54 53 56 59 60 60 60 58 56 53 52 57 63 71 79 86 87 76 63 47 41 36 38 49 60 67 69 66 56 45 41 42 47 58 69 75 78 78 70 61 55 49 42 36 35 35 35 36 39 42 44 48 48 47 48 46 43 37 33 27 27 27 29 33 38 43 46 48 49 52 55 58 61 63 64 50 42 34 33 41 59 87 109 137 147 149 131 102 74 52 40 45 53 66 77 82 80 75 71 65 63 61 63 64 63 57 53 45 42 37 30 27 29 34 39 46 52 58 62 59 54 49 46 37 35 30 27 25 25 26 27 27 30 33 37 38 38 36 34 30 30 30 30 31 33 35 37 40 44 50 56 58 57 54 52 45 41 37 34 33 31 30 28 25 24 21 20 21 23 27 29 33 35 37 36 32 28 26 25 24 23 23 24 24 24 31 41 57 67 81 90 93 96 100 104 108 115 120 119 112 101 87 75 55 47 37 30 28 27 25 24 23 22 20 19 19 21 24 25 35 42 48 49 50 50 45 39 36 33 29 26 24 24 25 26 32 35 40 44 47 48 47 46 45 43 39 35 30 26 24 23 23 25 29 34 38 42 45 46 40 38 36 34 31 28 26 25 22 21 18 16 14 12 11 11 11 11 11 11 11 12 12 12 11 12 12 13 14 15 16 16 16 15 15 14 14 15 16 16 16 16 14 13 12 12 12 13 13 13 12 12 11 10 10 10 11 11 10 10 10 9 9 9 7 7 7 7 7 7 7 7 7 7 7 6 6 5 5 5 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 9 8 8 9 9 11 12 13 17 16 16 16 16 17 17 18 21 21 21 21 21 21 21 21 21 21 21 21 21 20 20 20 22 22 22 22 23 23 23 23 27 26 25 24 23 22 22 22 23 25 26 28 28 27 26 25 26 27 28 27 26 24 21 19 19 20 23 27 32 38 42 45 48 49 51 52 51 52 53 55 61 63 67 72 75 74 69 65 60 57 54 52 55 61 67 72 74 81 85 83 79 73 63 54 46 40 38 44 54 63 73 82 87 90 92 93 92 92 93 94 96 92 86 78 72 68 65 65 72 82 98 114 126 131 131 129 118 108 96 88 82 80 87 96 114 124 134 135 129 120 108 97 90 82 77 76 75 72 72 75 78 81 86 92 97 100 102 103 99 97 94 91 88 85 82 80 81 79 78 80 85 88 87 85 79 73 66 63 65 73 83 90 95 96 92 80 65 57 59 63 77 95 116 130 136 135 126 117 101 93 82 74 68 63 60 60 61 62 64 67 70 71 71 70 71 76 81 88 94 92 78 62 47 40 35 39 52 66 76 80 71 58 44 36 36 45 63 79 88 94 96 87 75 63 51 42 36 34 32 32 35 40 46 50 53 53 53 51 48 42 36 31 27 28 30 34 38 42 46 48 50 51 53 56 61 66 70 73 62 52 41 37 40 53 77 97 120 130 133 118 93 70 52 42 45 54 66 76 79 77 73 70 65 64 63 64 63 60 55 50 46 43 37 31 27 28 32 36 45 51 59 63 61 56 51 48 40 38 35 32 30 30 31 31 30 32 36 39 40 39 38 36 31 30 28 27 29 32 35 37 42 47 53 59 60 58 54 50 42 39 34 31 30 29 28 27 25 24 22 21 22 25 28 30 34 36 38 36 32 28 25 24 23 22 23 26 25 26 32 41 56 66 80 90 94 96 99 101 102 104 105 101 93 81 69 60 49 43 36 32 30 30 30 28 25 23 21 20 20 22 25 27 35 43 50 52 54 54 49 42 38 35 31 28 25 25 26 26 30 32 35 37 39 39 38 38 39 37 34 32 29 28 27 27 28 30 33 36 39 42 43 44 37 36 34 31 29 26 24 23 22 21 19 16 14 13 12 11 11 11 11 12 12 12 12 13 12 12 12 12 13 14 15 15 13 13 12 12 12 13 14 15 15 15 14 13 12 12 12 13 13 13 13 12 12 11 11 10 12 11 11 11 10 10 10 10 8 8 8 8 7 7 7 7 7 7 7 6 6 5 5 5 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 9 9 9 9 10 11 12 13 17 17 17 17 17 18 19 20 23 23 23 23 23 23 23 23 23 23 23 22 22 21 21 21 23 23 23 24 24 24 24 24 28 28 28 27 26 25 24 23 26 27 28 29 30 29 27 26 26 26 26 26 25 23 21 20 19 21 24 29 35 40 45 47 49 50 50 50 49 50 54 57 65 66 69 72 72 67 60 54 48 45 42 42 47 55 63 69 73 82 90 92 90 85 75 65 52 44 39 42 48 55 65 74 82 86 91 95 96 96 96 97 96 92 85 77 70 65 62 61 68 77 92 108 120 126 128 127 118 109 100 93 89 88 96 105 118 126 130 126 118 110 98 89 81 75 72 73 74 73 74 77 82 84 87 91 96 101 105 107 107 107 107 104 100 95 91 89 87 86 87 93 103 110 113 113 105 96 83 70 65 66 71 76 85 89 88 80 67 58 57 60 69 86 106 121 129 132 128 121 116 111 103 94 86 80 72 67 64 65 67 74 82 88 90 91 90 92 94 97 99 95 79 62 46 40 36 41 56 72 84 89 75 60 43 33 32 43 65 84 100 108 110 101 84 68 54 43 36 35 33 34 39 46 53 58 62 62 60 56 49 42 35 31 29 31 34 38 42 45 47 48 53 53 56 59 65 71 76 80 74 63 51 44 42 50 69 87 107 115 116 102 81 62 48 39 46 54 65 72 73 70 68 66 61 61 62 62 61 57 52 48 45 43 37 30 26 25 29 32 43 48 56 60 59 55 51 49 44 42 40 38 37 36 36 36 35 37 39 41 41 39 37 35 31 30 27 26 28 31 35 37 43 47 52 57 57 54 49 45 38 35 32 30 29 29 28 26 25 24 23 23 24 26 29 30 34 36 37 35 31 26 23 22 23 23 25 28 28 27 33 41 55 64 78 88 92 93 93 94 90 88 85 81 73 63 54 50 46 43 40 37 36 35 34 33 27 25 23 21 21 24 27 29 36 44 51 53 54 54 49 42 37 35 32 28 26 25 25 26 26 27 29 30 31 31 31 31 33 32 32 31 31 31 32 32 31 32 33 35 36 36 36 36 31 30 29 27 25 23 22 21 23 22 20 18 16 15 15 14 14 14 15 15 16 16 16 17 15 14 14 13 13 14 15 16 13 12 12 11 12 12 13 13 14 14 13 12 12 12 12 13 13 13 13 12 12 12 12 11 12 12 12 12 11 11 11 10 10 10 9 9 8 8 7 7 7 7 7 6 6 5 5 5 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 9 9 9 9 10 11 13 13 17 17 17 17 18 19 20 21 23 23 23 23 23 23 23 23 24 23 23 22 21 21 20 20 23 23 23 24 25 25 25 26 29 29 29 29 28 27 26 25 28 29 29 30 30 30 30 29 27 28 28 27 26 25 24 23 23 25 28 33 39 44 47 49 50 50 48 46 45 47 52 56 63 64 66 67 65 58 49 42 36 34 32 33 38 46 54 60 69 79 90 95 96 92 82 72 58 49 41 42 45 50 58 65 76 80 86 91 94 96 98 99 95 91 85 77 70 64 61 59 65 72 84 96 107 113 116 117 113 106 100 98 96 98 106 116 124 130 132 127 119 111 102 94 84 77 73 74 75 74 75 78 84 85 87 91 95 99 103 105 109 111 112 110 105 100 97 96 92 93 97 105 117 129 137 142 133 122 104 86 72 65 63 63 78 81 82 76 66 56 53 53 63 78 94 106 116 124 125 123 122 123 120 113 105 97 84 73 67 66 69 77 89 99 104 106 107 108 106 103 100 94 79 65 48 42 38 44 59 75 86 91 78 63 44 31 29 40 64 85 108 116 118 107 88 70 55 44 37 37 38 41 48 56 63 68 73 72 68 61 51 42 35 33 31 34 39 43 46 48 48 48 53 54 58 63 70 77 83 86 84 73 61 51 46 49 63 77 96 101 99 85 67 52 42 35 47 53 61 65 64 62 61 61 57 58 60 60 58 53 48 45 41 39 34 28 24 23 26 29 38 44 50 54 54 51 49 48 45 45 44 43 41 40 39 38 38 39 42 43 42 39 36 33 31 30 28 27 28 31 35 37 42 45 49 51 50 46 41 37 34 32 30 30 31 30 28 26 26 25 25 24 25 27 28 29 32 34 35 34 30 25 22 21 24 25 28 32 31 29 33 41 54 63 75 85 89 88 85 84 76 71 67 63 57 50 46 47 44 44 45 44 42 39 36 34 28 26 23 21 21 24 28 30 38 44 50 51 51 50 45 39 34 33 30 27 25 25 25 25 23 24 24 25 26 27 28 28 31 32 33 34 34 34 34 33 30 30 30 30 30 29 28 28 25 25 24 23 22 21 21 20 22 21 20 19 18 18 18 18 18 18 19 19 20 21 21 22 19 18 16 15 14 15 16 17 15 14 13 12 12 12 12 12 13 13 12 12 12 12 13 13 13 13 13 13 13 12 12 12 13 13 13 12 12 12 11 11 11 11 10 10 9 8 8 7 7 7 7 6 6 5 5 5 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 10 9 9 10 10 12 13 14 17 17 17 17 18 19 20 21 23 23 23 23 23 23 23 23 23 23 22 21 20 19 19 18 21 22 23 24 25 26 27 27 28 29 30 31 31 30 29 28 29 29 28 29 29 30 31 32 31 31 30 30 29 28 27 27 29 31 35 39 44 48 50 52 50 49 46 43 42 44 49 54 58 58 59 60 58 51 42 36 30 28 26 26 30 37 44 49 60 71 83 89 91 89 79 70 58 50 43 42 44 47 52 58 67 71 77 81 85 88 92 95 91 88 84 78 72 66 62 59 66 69 76 84 91 97 100 102 102 98 97 99 102 107 116 127 134 140 142 137 130 125 118 111 99 91 84 82 81 78 78 81 84 85 86 89 92 95 98 100 105 107 110 109 104 100 98 98 96 99 106 114 126 140 153 162 158 146 127 105 86 71 62 58 69 71 73 71 64 57 52 50 59 69 80 87 96 107 113 114 118 124 128 125 120 111 95 81 69 67 68 75 89 102 109 112 113 114 109 101 95 88 77 66 52 46 42 47 60 74 84 87 79 64 45 31 27 37 61 82 107 115 117 104 83 65 50 41 41 43 47 53 61 69 76 80 84 82 76 65 52 42 36 35 34 37 42 47 50 50 48 47 50 53 58 66 75 83 90 93 90 80 68 57 49 48 58 70 81 85 82 69 55 47 41 37 44 49 55 55 52 50 51 53 56 58 60 60 56 50 44 41 34 33 29 25 22 22 26 29 34 38 44 47 47 46 46 46 45 45 45 44 43 41 40 39 38 40 42 43 42 39 36 33 31 30 29 29 30 32 35 37 42 44 46 46 44 39 34 31 29 29 29 31 33 32 30 27 27 27 26 26 26 27 28 28 30 32 33 32 28 24 22 21 26 27 31 35 33 31 34 40 50 58 70 79 82 79 74 70 62 55 49 48 45 40 41 46 46 49 52 53 50 44 39 36 31 28 25 23 23 26 30 33 40 45 48 47 46 46 41 34 31 29 28 26 24 24 24 24 22 22 22 23 25 27 29 30 33 35 37 38 38 36 33 31 25 26 26 26 25 24 23 23 21 21 21 21 21 21 21 21 20 20 19 19 19 19 20 20 21 21 22 23 24 24 25 25 21 19 17 15 15 16 17 18 18 17 15 14 13 12 12 12 13 12 12 11 11 12 13 13 13 13 13 13 13 13 13 13 14 14 13 13 13 12 12 12 12 12 11 10 9 8 8 7 7 7 7 6 6 5 5 5 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 10 10 10 10 11 12 13 14 16 16 16 17 18 19 20 21 22 22 22 22 22 22 22 22 22 22 21 20 19 18 18 17 20 21 22 23 25 26 27 28 28 29 31 32 32 31 30 29 29 28 27 27 28 30 32 33 33 33 32 32 31 31 30 30 34 36 39 43 47 51 53 54 51 49 45 41 39 42 47 52 53 54 55 55 54 48 40 34 29 27 24 24 26 31 37 41 51 62 75 81 84 81 72 63 57 49 43 42 44 45 49 54 60 63 68 72 75 80 85 88 87 86 83 79 73 68 63 61 67 69 71 75 80 85 89 91 94 92 93 99 105 112 123 133 143 149 152 148 143 139 133 127 115 105 96 92 88 83 82 84 83 84 85 87 89 92 94 96 100 103 106 105 101 98 97 98 99 103 110 119 129 144 160 172 173 162 143 120 97 78 65 59 60 62 64 66 64 60 55 52 51 58 64 68 76 87 96 99 112 122 131 131 128 120 103 87 71 67 66 73 87 100 109 112 112 113 107 97 87 81 73 66 56 50 45 49 61 73 80 83 80 65 46 32 26 35 59 80 103 110 111 97 76 58 44 36 45 49 55 63 72 80 86 90 90 88 80 67 53 42 37 36 35 39 44 49 51 50 48 46 46 50 58 67 78 87 94 98 92 83 71 60 51 47 55 65 68 71 69 59 50 46 45 44 40 44 48 47 42 40 42 46 57 59 61 60 55 48 42 38 29 28 25 22 21 22 27 31 31 35 40 42 43 43 44 44 43 44 44 44 43 41 39 38 37 39 41 43 42 40 37 35 30 30 30 30 31 33 35 37 43 43 44 43 40 35 30 27 26 27 29 32 34 34 30 27 29 28 27 26 26 26 27 27 28 30 32 31 27 24 21 20 28 29 33 36 35 31 34 40 45 53 64 72 74 70 64 59 51 43 37 38 36 34 37 45 49 54 59 60 56 49 42 38 34 32 28 25 26 29 33 36 41 45 47 45 43 42 38 32 28 27 26 24 23 23 23 23 22 22 22 23 25 28 31 32 36 38 40 41 40 36 31 28 22 22 23 23 23 22 22 21 19 19 20 20 21 22 22 22 19 18 18 18 19 20 21 21 22 22 23 24 25 26 27 27 22 20 17 15 14 15 17 18 20 19 17 15 14 13 12 12 12 12 11 11 11 12 13 13 13 13 13 13 13 13 13 13 14 14 14 13 13 13 12 12 13 12 11 11 10 9 8 8 7 7 7 6 6 5 5 5 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 9 9 10 11 11 12 13 13 16 15 15 16 17 18 20 21 20 20 20 20 20 20 20 20 21 20 18 16 15 14 13 13 17 17 18 20 21 22 23 24 27 28 29 30 31 32 33 33 33 31 27 24 24 26 29 32 31 32 33 34 35 36 36 36 38 38 40 44 49 52 53 52 50 48 44 42 41 43 45 47 50 51 51 49 45 41 38 38 33 32 31 30 31 33 36 37 48 53 59 64 66 64 61 58 48 46 44 45 48 51 53 53 53 57 61 63 65 68 74 78 82 82 82 80 78 76 74 74 69 74 76 75 75 77 76 72 81 84 89 96 106 117 129 137 149 157 162 159 157 157 154 148 142 131 116 106 100 97 93 90 93 91 88 88 88 88 86 85 90 92 93 91 89 89 92 96 95 100 108 118 130 145 161 172 167 166 153 129 105 87 71 58 59 61 63 62 58 54 52 51 50 52 54 53 53 57 67 75 91 111 129 134 135 131 114 95 82 75 68 69 79 92 101 104 102 99 94 85 76 70 67 66 58 56 54 56 62 70 77 81 73 61 45 33 29 36 54 72 96 100 99 85 64 45 37 36 39 48 62 74 81 87 93 97 90 88 82 69 55 43 38 36 40 43 48 51 51 48 44 42 47 53 61 67 77 89 96 97 92 82 69 58 49 44 47 55 58 59 58 55 50 45 43 42 40 37 36 35 33 32 38 47 51 58 62 57 51 44 35 27 27 25 21 18 19 22 27 30 32 34 35 36 35 35 37 39 42 42 43 42 41 39 37 36 36 38 41 43 43 41 39 37 33 34 34 35 36 37 37 38 40 39 39 37 34 30 27 25 30 31 34 36 36 36 34 33 33 33 34 33 31 28 24 22 27 25 25 26 25 21 23 28 29 37 42 42 41 42 40 37 42 48 57 67 70 66 57 50 42 37 31 26 26 31 38 42 56 59 62 63 59 51 42 36 30 29 29 30 32 36 40 43 46 46 45 43 39 34 29 26 23 24 25 25 26 25 25 24 26 26 26 27 29 32 35 37 39 40 41 40 37 32 26 22 18 17 17 17 18 20 22 23 23 21 20 21 22 21 19 17 16 16 17 19 21 22 24 24 21 22 24 25 26 26 25 24 24 23 20 18 17 18 19 20 21 21 20 19 18 16 14 13 14 14 13 13 13 13 14 14 16 15 14 13 13 13 13 13 17 17 16 15 13 12 11 11 10 11 11 11 11 10 9 8 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 9 9 10 11 11 12 13 13 15 15 15 15 16 17 18 19 19 19 19 19 19 19 19 19 20 19 17 15 14 13 13 13 15 16 17 18 19 20 21 22 26 26 28 29 30 32 33 33 32 30 27 25 24 25 27 28 30 31 33 35 36 37 37 37 40 40 42 46 51 54 54 53 50 47 44 42 42 43 45 47 48 50 51 50 47 44 43 43 47 46 44 42 40 39 39 39 49 52 56 60 60 58 54 52 46 45 45 48 52 55 56 56 53 55 57 57 57 59 64 68 75 76 78 80 83 86 89 92 87 90 89 83 78 76 73 69 81 85 90 97 106 119 131 140 153 162 168 167 167 168 166 161 158 148 134 123 116 112 109 106 107 104 99 95 92 87 82 79 78 79 80 79 79 83 89 95 97 101 107 115 124 137 151 160 157 156 146 125 105 90 76 65 61 63 64 63 59 56 54 54 48 50 50 48 46 48 55 61 79 100 119 128 132 132 118 102 87 78 68 65 71 80 87 91 91 89 83 76 69 65 64 65 65 62 59 59 62 67 72 75 71 59 45 34 30 35 52 68 85 88 87 74 54 37 31 31 41 51 65 75 82 86 90 93 89 87 80 67 52 41 37 36 42 45 49 52 50 47 43 41 46 53 61 67 76 87 93 93 90 80 66 55 44 38 40 47 53 54 55 54 49 45 42 41 39 36 33 32 29 29 36 46 53 59 61 56 49 42 34 26 26 24 21 20 21 25 29 32 32 33 33 32 30 31 34 36 41 41 41 41 39 37 34 32 35 38 41 43 44 43 41 39 36 36 37 38 38 39 39 39 40 39 38 36 34 31 28 26 30 32 36 38 39 38 36 34 34 35 35 35 32 29 25 22 24 22 22 25 24 22 25 30 40 47 52 51 47 45 40 34 38 43 51 58 62 59 51 45 40 36 31 27 27 32 38 43 54 56 59 59 55 48 40 34 30 30 31 33 36 39 42 44 44 44 42 39 35 31 27 25 23 24 25 27 27 27 27 27 28 27 28 29 31 34 37 38 40 40 40 38 34 29 24 21 18 18 19 20 22 24 26 27 27 25 24 23 23 22 20 17 16 17 18 19 21 22 23 24 21 22 24 25 25 25 24 24 23 22 20 18 18 19 20 22 22 22 22 21 19 18 16 15 16 16 16 15 15 16 16 16 17 16 15 14 13 13 13 13 17 17 16 14 13 12 11 11 10 10 11 11 10 9 9 8 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 9 9 10 11 11 12 13 13 14 13 13 14 14 15 17 17 17 17 17 17 17 17 17 17 18 17 15 14 13 12 12 12 13 13 14 15 16 17 18 18 23 23 25 26 28 30 31 32 31 30 28 26 24 23 23 23 28 30 32 34 36 37 38 39 43 43 44 48 52 54 55 54 49 47 44 42 41 43 45 47 47 49 52 52 52 51 52 53 61 60 59 57 55 52 50 48 53 55 56 57 56 52 48 46 45 46 48 53 58 61 61 60 56 55 53 50 48 50 54 58 65 68 72 77 84 93 103 110 114 117 114 105 95 89 83 77 83 85 90 96 105 117 129 137 150 158 166 170 172 175 175 172 171 163 151 140 133 129 126 125 125 121 116 110 103 94 85 79 73 71 68 66 68 74 83 90 98 101 106 112 119 128 137 143 141 140 133 117 102 90 81 74 64 65 66 65 62 59 58 59 55 57 57 54 50 49 52 56 68 87 108 120 129 132 123 110 95 85 71 62 62 67 72 75 76 73 69 63 59 58 61 65 72 69 66 62 61 63 65 67 65 56 45 37 32 34 47 61 73 75 73 61 44 31 27 28 44 54 66 75 79 80 82 84 83 80 73 61 48 39 36 36 43 47 52 53 50 45 41 40 46 54 61 67 75 84 88 87 86 75 61 48 37 29 31 38 46 49 51 51 48 45 42 41 39 34 30 27 25 26 35 45 56 61 61 55 47 40 32 25 24 23 22 23 25 28 32 34 36 35 33 30 28 30 34 37 44 44 43 42 39 36 32 30 34 37 41 45 46 46 45 43 40 41 42 42 42 42 41 41 40 40 38 36 33 31 30 29 31 34 38 41 42 41 38 36 36 37 38 37 35 31 26 23 20 19 20 23 24 24 29 36 49 57 63 61 56 51 42 35 36 38 43 49 52 50 45 40 36 34 30 28 29 33 39 42 50 52 53 53 50 43 37 32 30 31 34 37 40 43 44 45 43 41 38 35 31 28 26 25 24 25 27 29 30 30 29 29 29 28 29 29 31 34 37 39 39 38 36 33 29 25 22 20 20 21 23 26 29 32 34 35 34 32 29 27 26 24 21 19 18 18 19 20 21 22 23 23 21 22 23 24 24 24 24 23 22 21 20 19 19 21 22 23 24 24 24 23 22 21 19 18 19 19 19 19 19 19 19 19 18 17 16 14 13 13 13 13 17 16 15 14 13 12 11 10 9 10 10 10 10 9 8 7 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 9 9 10 11 11 12 13 13 13 12 12 12 13 14 15 15 15 15 15 15 15 15 15 15 15 15 14 13 12 12 12 12 11 12 12 13 14 15 16 16 18 19 21 22 24 26 28 28 29 29 28 27 25 23 21 20 26 28 30 33 36 38 40 40 45 45 46 48 52 53 53 52 48 46 43 41 41 42 45 47 47 50 54 56 57 59 62 65 68 69 71 72 71 70 68 66 63 63 62 60 57 53 49 47 50 52 55 60 65 66 65 63 59 56 51 47 45 47 51 55 59 62 66 71 80 94 110 121 134 139 140 131 119 110 100 93 87 89 92 95 101 110 121 128 136 143 153 160 165 169 172 172 172 167 159 149 142 139 139 140 141 139 134 129 121 110 98 91 80 75 67 62 62 67 76 82 94 98 104 111 116 121 125 127 124 122 115 104 93 85 79 77 69 70 70 69 66 64 64 64 67 68 69 67 63 61 61 62 67 83 101 114 124 128 123 115 104 92 77 65 60 61 64 66 63 61 57 52 51 54 60 65 74 73 71 66 62 59 58 58 59 52 44 38 33 33 42 53 65 66 64 54 41 31 30 32 45 54 65 71 72 70 69 69 70 68 63 53 42 36 35 37 44 49 54 54 49 44 40 39 47 55 63 69 76 83 84 82 80 69 55 42 31 24 26 32 41 45 49 50 48 45 43 42 39 34 28 25 22 24 34 46 58 62 62 54 46 40 33 26 24 24 24 26 29 32 35 37 41 39 36 33 32 35 41 46 51 50 48 45 41 36 33 31 35 38 42 47 50 50 50 49 46 46 46 46 45 45 44 43 42 41 39 36 34 33 31 31 32 35 39 43 44 42 39 37 38 39 41 41 38 34 29 25 20 18 19 23 26 28 35 43 53 63 71 71 66 59 48 39 37 37 39 42 44 44 41 38 32 31 30 29 31 35 38 41 47 48 48 48 44 40 35 31 30 32 36 40 43 45 45 45 42 40 36 32 29 28 27 28 28 30 31 33 33 31 30 28 28 28 27 28 30 33 35 37 34 33 31 28 25 23 22 21 24 26 30 34 38 41 43 44 42 39 35 32 30 27 24 21 21 21 21 22 22 22 23 23 22 22 22 23 23 23 23 22 20 20 20 20 21 22 24 25 26 26 26 26 25 24 23 22 21 21 22 22 22 22 21 21 20 19 18 16 14 13 13 13 16 16 15 14 13 11 11 10 9 9 9 9 9 8 7 7 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 9 9 10 11 11 12 13 13 13 12 12 11 12 13 13 14 13 13 13 13 13 13 13 13 14 13 13 12 12 12 13 13 12 12 13 13 14 15 15 15 16 16 17 19 21 23 24 24 27 27 27 27 25 23 21 20 25 27 30 34 38 41 43 44 48 47 47 49 51 51 49 48 45 43 41 39 39 41 44 46 48 51 55 59 62 66 70 74 76 79 82 85 86 86 85 83 76 74 72 68 64 61 58 56 60 61 64 68 71 71 68 65 60 55 49 45 45 48 52 55 55 57 61 66 76 94 115 130 145 154 159 152 139 125 112 103 97 98 98 99 100 105 111 116 121 126 136 145 152 157 162 167 166 165 161 154 148 147 151 155 157 156 154 150 143 130 117 108 92 84 73 65 62 66 72 76 86 90 99 107 113 116 115 113 108 103 96 88 79 73 73 74 74 76 77 75 72 70 69 69 74 76 79 80 79 77 75 74 76 86 99 109 117 121 119 114 106 97 83 70 63 60 61 62 58 56 52 48 47 52 59 65 72 74 74 71 64 57 53 51 51 47 43 39 34 32 38 47 58 59 57 50 41 35 36 38 46 53 61 63 61 56 53 53 54 54 52 45 37 33 34 37 44 49 55 55 49 44 41 41 49 58 67 73 79 84 83 79 74 63 50 39 28 22 26 32 40 43 47 48 47 45 44 43 40 35 29 25 22 24 35 47 59 64 63 56 48 42 36 29 27 27 27 29 31 34 37 39 43 42 42 41 42 47 54 59 62 59 54 47 41 36 32 30 37 40 45 50 54 55 55 54 51 50 49 48 46 46 45 45 44 43 41 39 37 35 33 32 31 34 38 41 43 42 39 38 39 41 43 44 42 37 32 29 23 21 22 26 30 33 42 51 63 73 82 82 77 67 54 43 37 36 35 36 38 38 37 35 29 30 31 33 35 37 38 39 45 44 44 42 40 36 33 31 30 33 37 41 43 44 43 43 40 38 34 31 29 30 31 32 35 36 37 37 35 32 29 26 25 25 25 25 27 29 32 33 29 28 26 25 24 24 25 25 30 33 38 43 48 50 51 52 47 44 39 35 33 31 28 25 25 25 24 24 24 23 23 23 22 22 22 21 21 21 21 22 20 20 21 21 22 24 25 26 27 27 28 28 28 27 27 26 23 24 25 25 25 25 24 23 23 22 20 18 16 15 14 14 16 15 15 13 12 11 10 10 8 8 9 9 8 7 6 6 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 9 9 10 11 11 12 13 13 13 12 12 11 12 12 13 13 12 12 12 12 12 12 12 12 13 13 12 12 12 13 14 14 14 15 15 15 16 16 17 17 16 16 17 18 19 21 21 22 25 25 26 26 26 25 24 23 27 29 33 37 42 46 48 50 53 51 50 50 50 49 46 44 43 41 38 37 37 39 42 44 48 51 55 59 63 68 73 77 85 87 90 92 94 93 92 91 85 82 78 74 71 69 68 68 70 70 72 75 77 76 73 70 60 56 50 47 48 52 55 57 54 56 58 61 72 92 118 136 157 167 173 166 150 135 120 110 107 107 106 104 101 101 102 104 109 111 119 129 136 142 150 158 158 160 160 156 151 152 158 165 169 170 171 170 163 151 136 126 107 98 85 75 70 70 72 73 76 80 88 97 104 106 105 102 95 88 79 71 64 61 65 71 80 83 84 83 80 75 73 72 79 83 89 94 96 95 92 90 85 90 96 102 107 110 111 110 104 98 89 78 70 64 62 61 59 57 53 49 48 52 59 64 71 75 79 77 68 57 50 46 45 42 40 39 35 31 36 43 50 52 52 48 42 39 40 43 49 54 58 57 51 44 41 40 43 44 44 40 35 31 32 35 41 48 55 55 50 45 43 45 52 62 72 78 84 87 85 80 72 62 49 39 30 25 28 35 41 43 45 46 44 42 42 43 40 35 29 26 23 25 35 47 59 64 65 60 53 48 41 34 33 32 30 30 32 35 38 40 42 45 49 53 58 64 72 77 74 69 60 50 41 36 33 32 40 44 49 54 58 60 59 59 56 53 50 47 45 45 46 47 46 46 45 44 41 37 33 31 29 31 34 37 38 38 38 37 39 42 45 47 45 41 36 33 28 25 25 29 32 37 46 56 74 84 92 92 84 73 58 46 37 35 33 32 33 34 33 32 31 33 36 38 40 41 40 40 42 41 39 37 34 32 31 30 30 32 35 38 40 40 39 39 37 35 33 31 31 32 34 35 39 40 41 41 38 34 29 26 23 23 22 23 24 26 28 30 27 27 27 27 27 28 29 30 36 39 45 50 54 55 55 55 50 46 41 38 36 34 32 31 29 29 28 27 26 25 24 24 23 22 21 20 20 20 20 21 21 21 22 23 24 25 25 26 28 28 29 30 30 30 29 29 27 28 29 30 30 29 28 27 27 26 23 21 18 17 16 15 16 15 14 13 12 11 10 9 7 7 8 8 7 7 6 5 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 9 9 10 11 11 12 13 13 14 13 12 12 12 12 13 13 12 12 12 12 12 12 12 12 13 13 12 13 13 14 15 16 18 18 18 18 19 19 19 19 19 19 20 20 21 21 21 22 23 23 24 25 26 27 28 28 30 33 37 43 48 52 55 57 58 56 53 52 51 48 45 42 40 38 36 34 35 37 40 42 47 49 53 57 61 66 72 76 83 85 87 89 91 92 91 91 87 84 80 76 73 73 74 75 77 77 78 80 82 81 78 76 66 61 55 53 55 58 60 61 58 58 56 56 64 84 111 131 155 165 170 162 146 131 119 111 109 109 109 105 99 95 92 92 96 95 100 109 117 122 132 143 146 151 153 150 146 147 155 164 170 174 179 182 179 170 156 147 129 119 104 91 83 77 73 70 69 70 74 81 89 93 94 93 86 76 65 58 53 52 60 71 85 88 91 90 86 80 76 73 78 83 91 99 104 103 100 96 88 88 89 92 96 100 104 107 106 103 98 90 81 73 67 64 62 60 56 52 50 52 57 61 72 79 86 85 74 59 48 42 40 38 38 38 34 31 35 42 45 47 48 47 45 43 45 47 55 58 59 54 46 38 34 34 38 41 42 40 34 30 30 31 37 46 54 55 50 46 46 49 55 65 77 84 89 92 88 82 75 65 52 42 32 27 31 38 42 43 43 42 39 38 39 40 39 34 29 26 23 25 34 46 57 64 67 64 59 54 47 40 39 36 33 31 31 34 37 40 45 51 60 70 78 86 93 98 90 82 69 56 46 40 38 37 44 47 53 58 62 63 63 62 59 55 50 44 42 43 46 48 48 49 50 48 45 39 34 30 27 28 30 31 33 34 35 36 39 42 46 49 48 45 40 37 32 28 27 30 33 38 48 58 74 85 93 93 86 75 61 49 40 37 34 33 34 34 33 32 35 38 42 46 47 46 44 43 38 36 34 31 29 28 28 28 30 31 33 35 36 35 35 34 32 31 31 31 32 34 36 37 41 42 43 43 41 36 31 28 22 22 21 22 23 25 27 28 31 32 32 33 33 33 34 34 39 43 48 53 56 56 55 53 50 46 42 39 38 37 36 35 33 32 31 30 28 27 26 25 23 22 20 19 19 19 20 20 22 22 23 24 25 25 25 25 28 28 29 30 31 31 31 30 31 32 34 35 35 34 32 31 30 29 26 23 21 19 18 17 15 15 14 13 12 10 9 9 6 7 7 7 7 6 5 4 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 9 9 10 11 11 12 13 13 14 14 13 12 12 13 13 13 12 12 12 12 12 12 12 12 13 13 13 13 14 15 16 17 20 20 20 20 21 21 21 21 22 22 22 22 22 22 22 22 22 22 23 24 26 29 31 32 34 36 41 47 52 57 60 62 62 59 56 54 52 49 44 41 39 37 35 33 34 36 39 41 45 48 51 54 58 63 69 74 75 76 79 82 85 87 88 89 86 83 78 75 73 74 76 78 80 80 80 82 84 85 83 81 73 68 62 60 62 65 65 65 62 60 56 52 56 73 100 119 141 151 155 146 131 119 111 105 106 107 106 102 96 89 85 83 84 81 84 93 100 106 117 129 136 141 145 142 137 138 147 156 165 171 180 187 189 182 171 162 150 139 122 106 93 82 73 67 66 64 64 68 76 83 87 87 81 69 57 51 47 48 59 72 88 92 95 95 90 83 77 74 70 75 84 94 99 100 95 91 86 84 82 85 88 93 99 105 109 109 107 100 91 80 73 69 65 63 59 54 51 52 55 59 74 83 91 90 78 61 47 39 37 36 36 37 34 31 34 41 43 46 48 49 48 47 48 50 60 61 60 54 44 36 32 32 38 41 43 41 35 30 28 28 35 44 53 55 51 47 48 51 57 68 79 87 92 95 91 84 78 68 55 44 34 29 32 39 43 43 41 39 36 35 36 38 37 33 28 26 23 24 33 44 56 64 69 67 62 57 50 43 43 40 35 32 31 33 37 40 50 58 70 83 94 103 110 114 102 93 78 63 51 45 44 44 46 50 55 60 64 65 65 64 61 56 49 43 40 42 45 48 50 51 52 51 47 41 34 29 26 26 27 28 30 32 34 35 38 42 46 50 50 47 42 39 34 30 28 30 33 38 48 58 67 78 88 89 84 75 62 51 44 41 38 37 37 37 36 35 39 42 47 51 52 50 47 45 35 33 30 27 25 25 26 26 30 31 31 32 32 32 32 32 28 28 29 30 32 34 36 37 40 42 44 44 42 38 34 31 23 22 21 22 23 25 27 28 36 36 37 38 37 37 36 35 40 44 49 54 56 55 53 51 49 46 41 39 39 39 39 38 35 34 33 31 29 28 27 26 23 22 20 19 18 18 19 20 22 23 24 25 25 25 25 24 27 28 29 31 31 31 31 31 34 36 38 39 39 38 36 34 32 31 28 25 22 20 19 18 15 15 14 13 11 10 9 9 6 6 7 7 7 6 5 4 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 13 13 12 12 12 13 14 14 14 14 13 13 13 14 14 15 14 14 13 12 12 11 10 10 13 12 12 12 13 15 17 19 21 23 25 26 25 24 25 27 28 28 27 26 25 24 24 24 23 23 23 23 25 28 30 32 38 40 45 51 57 62 66 67 65 62 58 52 47 43 39 38 38 37 35 33 33 35 37 38 38 41 45 50 54 57 59 59 69 69 69 71 72 75 77 78 76 73 70 67 67 69 72 74 70 75 81 86 88 90 92 93 90 82 74 70 71 76 79 80 74 71 66 60 60 71 90 104 124 127 126 118 105 95 93 95 100 102 102 99 93 86 81 79 71 70 70 74 81 91 101 108 122 126 130 128 124 126 133 141 154 163 172 176 179 180 175 169 154 144 130 119 108 95 79 67 60 56 53 55 63 71 77 80 76 66 57 52 49 51 64 79 88 93 100 103 99 89 77 69 69 72 77 83 88 90 88 86 81 80 78 77 80 88 98 106 109 117 120 112 98 86 76 69 67 67 65 61 56 54 57 60 70 78 88 90 81 63 45 34 30 32 36 38 38 37 35 34 39 45 51 54 53 52 53 56 63 65 66 63 56 47 40 36 40 44 47 45 39 33 29 28 34 40 46 48 47 45 44 45 54 68 83 92 97 100 100 96 82 70 56 46 37 32 34 40 43 43 42 36 30 27 29 32 35 34 29 23 19 23 31 39 51 60 65 64 63 62 55 46 46 42 36 31 30 32 35 38 51 60 75 92 108 119 125 128 114 97 78 65 54 44 42 46 54 55 57 62 67 69 69 68 64 55 47 43 41 39 43 49 51 56 58 54 49 43 34 26 25 24 23 24 27 29 29 28 33 37 42 47 48 46 42 39 36 32 27 25 28 35 43 49 63 70 78 81 77 68 59 54 43 44 45 45 45 45 44 44 45 47 51 55 56 53 46 41 32 29 26 23 22 24 27 29 29 29 30 30 30 29 29 28 26 27 29 30 32 32 32 32 36 36 38 40 40 38 32 28 26 24 22 21 23 29 34 38 42 44 46 46 43 40 38 38 39 41 45 49 51 51 50 49 43 42 41 40 39 39 39 39 40 39 36 33 30 27 26 25 22 20 18 16 15 16 18 19 20 21 23 24 25 24 23 22 25 26 27 29 31 33 35 36 34 36 38 39 40 40 39 39 35 33 31 29 28 26 22 19 18 17 15 13 11 10 10 9 8 8 8 7 7 6 6 6 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 13 13 13 12 13 13 14 15 16 15 15 14 14 14 14 15 14 14 13 12 12 11 10 10 12 12 11 12 13 16 18 19 22 24 27 28 27 28 29 30 35 35 35 34 33 31 30 29 24 24 23 24 26 29 32 34 39 42 46 51 57 61 65 66 64 61 57 52 47 42 39 38 36 36 35 34 34 35 37 37 36 38 41 45 49 52 54 55 61 61 61 61 62 64 66 68 69 67 65 63 63 65 67 68 67 70 76 81 86 91 97 100 99 93 86 82 83 85 86 87 83 79 73 66 63 70 84 96 106 108 107 98 87 80 80 84 95 99 102 102 96 87 79 74 69 67 66 66 71 78 86 91 108 112 115 113 110 111 118 125 139 148 157 162 164 166 162 157 151 142 131 121 112 100 86 76 61 57 53 53 58 65 70 73 78 70 64 63 62 65 76 89 96 98 101 101 97 88 78 72 71 73 76 79 82 82 80 78 76 76 76 78 83 92 103 111 119 126 129 120 106 93 81 72 66 67 67 63 59 56 56 58 68 76 86 89 80 63 44 33 30 33 38 41 40 38 35 34 37 43 50 53 52 52 53 55 65 67 69 67 60 52 45 42 44 48 51 50 44 37 32 30 33 37 43 45 43 41 40 40 50 64 79 89 96 102 103 101 87 74 59 47 38 32 35 40 43 43 40 34 28 25 28 32 36 35 32 27 24 26 32 39 49 57 63 63 63 62 56 48 45 41 35 31 29 31 34 37 47 57 75 95 114 127 135 139 122 105 84 69 58 49 48 52 55 55 58 62 67 70 71 70 67 58 48 43 40 39 44 51 56 61 62 58 53 47 38 30 26 24 23 23 26 27 28 27 31 34 39 44 45 43 40 37 32 29 25 24 27 34 42 47 57 63 70 73 71 64 57 53 51 52 54 56 56 54 52 51 48 49 52 54 55 51 45 40 29 26 23 20 19 21 24 27 28 29 29 29 29 28 27 27 25 26 28 30 31 31 31 31 34 35 36 39 40 38 33 29 25 23 21 20 22 27 33 36 43 45 47 47 44 40 38 38 35 37 40 43 45 45 45 44 43 42 42 42 43 44 45 46 44 43 40 37 33 29 25 23 21 19 17 15 14 15 17 18 20 21 23 25 26 25 24 23 25 25 26 28 30 32 33 34 34 35 37 39 40 40 39 38 35 33 31 30 29 26 23 20 18 17 15 13 11 10 10 9 8 8 8 7 7 6 6 6 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 14 13 13 13 14 15 16 16 18 17 17 16 16 15 15 15 14 14 13 13 12 11 10 10 11 11 11 12 14 16 19 21 23 26 29 31 31 32 34 36 41 42 43 43 41 39 36 34 28 27 25 25 26 30 33 36 40 42 46 50 55 58 61 62 60 58 54 49 45 41 38 37 34 35 36 37 38 38 38 38 36 37 39 42 46 49 53 54 56 54 53 52 52 53 56 57 61 61 61 61 61 61 61 62 63 66 70 76 84 95 106 113 115 111 106 102 100 99 98 96 94 91 84 75 70 71 79 86 87 87 84 76 68 65 70 75 91 97 104 105 99 88 77 70 69 67 64 63 65 69 74 77 91 94 97 96 93 95 101 108 120 130 139 142 144 145 143 139 141 136 128 122 115 107 96 89 74 69 64 61 63 67 71 73 79 76 76 79 81 85 94 103 109 107 104 99 92 85 79 76 72 73 74 75 74 73 71 70 71 73 77 82 89 100 112 120 131 138 139 129 113 98 83 72 65 67 68 67 63 58 55 54 63 71 82 85 77 60 43 32 30 35 41 45 43 39 35 33 36 43 51 55 55 54 55 56 66 69 72 71 66 58 52 49 50 53 57 56 51 43 37 33 31 35 39 40 39 36 34 34 44 57 72 84 94 104 108 107 94 80 63 50 39 33 35 40 44 42 38 31 25 23 27 32 37 39 39 36 32 32 36 40 47 54 60 62 63 61 55 48 43 39 34 30 28 29 32 35 43 54 73 95 116 131 141 145 129 111 89 71 59 52 53 57 56 56 59 63 69 73 74 73 71 60 49 43 39 39 45 53 60 64 65 61 55 50 41 32 27 25 23 23 24 26 26 26 28 31 35 38 40 38 35 33 26 24 23 23 27 33 40 45 50 54 60 63 62 58 55 54 58 61 65 67 67 64 61 58 51 50 51 51 51 47 41 37 27 25 21 18 18 20 23 26 28 28 28 28 28 27 26 25 24 25 28 30 31 31 31 31 32 33 35 38 40 39 35 32 27 25 22 21 22 27 32 36 43 45 47 46 43 39 37 36 31 31 32 34 35 37 38 38 39 40 41 43 46 49 52 53 52 51 49 46 40 33 26 22 19 18 15 14 13 14 16 18 20 22 24 27 27 27 26 25 24 24 24 25 27 28 30 31 33 34 36 38 39 39 38 37 35 33 31 30 29 27 23 21 17 16 14 13 11 10 10 9 8 8 8 8 7 7 7 7 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 14 14 14 14 15 16 17 18 19 19 19 19 18 17 16 16 15 15 14 13 13 12 11 11 11 11 11 12 14 17 20 21 24 27 31 33 35 36 39 41 44 45 47 48 47 44 40 37 35 33 30 28 28 30 33 35 39 40 43 47 50 52 54 54 53 51 48 44 40 37 35 34 35 37 40 42 44 44 43 43 43 43 44 46 50 54 58 60 58 55 52 49 48 49 51 53 57 58 60 61 61 60 58 57 60 62 66 73 83 98 113 124 129 127 125 121 117 113 108 105 102 99 93 85 79 77 79 82 79 77 73 67 62 64 72 79 96 101 107 107 101 90 80 74 74 72 71 69 69 70 72 73 78 81 83 82 80 83 90 96 107 116 124 125 124 124 123 120 125 123 120 117 114 109 104 100 90 86 80 75 74 75 77 79 82 84 89 95 101 107 112 116 121 115 105 95 86 80 78 77 73 74 75 74 72 70 69 69 71 75 82 90 100 112 124 132 142 147 146 134 116 99 81 68 62 65 69 70 67 61 54 50 55 63 73 76 69 55 40 31 31 38 45 48 45 39 33 31 36 44 54 60 60 57 56 56 64 68 72 73 68 62 56 52 54 58 62 63 59 51 43 37 32 34 36 37 36 34 32 30 37 49 63 76 90 103 110 111 100 85 67 52 40 33 35 40 43 42 37 30 23 23 28 33 42 45 48 48 44 41 41 43 47 52 57 60 60 57 51 46 41 38 33 29 27 28 31 33 40 50 69 90 110 125 135 140 128 112 88 68 56 51 52 55 56 57 59 64 70 74 76 76 72 61 48 41 37 38 45 54 60 64 65 60 54 49 41 33 29 26 23 22 23 25 25 25 26 28 31 33 34 33 31 29 21 21 22 24 29 35 40 44 46 49 53 55 55 55 55 56 61 65 71 74 74 70 64 60 51 49 46 45 43 40 35 32 27 25 22 20 20 22 24 26 27 28 28 28 28 27 26 25 25 26 29 32 34 35 34 34 34 34 36 39 42 42 39 36 31 28 25 23 24 27 32 35 40 42 44 43 39 35 33 32 27 27 26 26 28 29 31 32 34 35 38 42 47 52 57 59 62 62 61 57 50 40 31 25 18 17 14 13 13 14 16 17 21 23 26 29 30 29 27 25 23 23 22 22 23 24 26 27 31 32 34 36 36 36 35 35 33 31 29 29 28 27 23 21 16 15 14 12 11 10 10 10 8 8 8 8 8 8 8 7 7 7 7 7 7 7 7 7 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 15 15 15 15 16 18 19 20 20 21 21 21 21 20 18 18 17 16 16 15 14 14 13 13 12 12 12 13 14 17 20 21 23 27 31 34 36 38 40 43 46 48 50 51 50 47 44 42 42 40 36 32 30 30 31 32 36 37 39 41 43 44 44 45 44 43 40 37 35 33 32 32 37 39 44 48 51 52 52 51 51 51 52 55 58 63 67 69 66 62 57 52 50 50 52 54 57 59 61 62 62 60 57 55 57 59 62 69 81 97 114 125 137 138 137 134 127 120 113 109 104 102 99 94 89 86 85 86 82 80 76 72 71 76 85 93 108 111 112 109 102 94 87 83 83 83 83 82 80 77 74 72 70 71 70 68 68 72 79 86 97 106 112 110 106 105 104 102 106 108 110 110 108 106 105 104 99 97 92 87 84 83 84 85 90 95 102 110 118 124 127 127 125 116 102 87 78 74 74 75 76 78 80 79 75 73 74 75 75 80 89 98 109 120 131 138 146 149 146 133 115 97 78 64 59 63 68 71 70 63 54 48 48 54 61 63 58 48 38 33 35 42 51 52 46 38 32 30 36 46 59 66 65 59 54 51 58 62 68 70 66 60 54 51 54 58 64 68 67 59 48 41 35 36 37 37 37 35 33 31 33 42 55 67 83 99 108 109 101 87 69 54 42 34 35 40 43 41 37 30 25 25 30 35 47 53 58 59 55 50 48 47 50 51 54 57 55 50 45 42 39 37 32 29 27 28 29 31 36 45 61 81 100 115 126 131 121 107 85 65 53 50 51 51 56 56 57 62 68 72 75 75 70 58 45 38 34 36 44 53 60 63 64 59 54 50 42 35 30 26 23 22 23 25 26 26 26 27 28 29 29 27 26 25 18 20 24 28 34 39 43 45 48 50 51 52 52 53 55 58 62 67 73 77 77 71 64 59 47 43 39 35 34 32 29 27 25 24 23 22 22 23 25 26 27 28 29 29 29 29 28 28 28 30 35 39 42 42 42 41 40 40 42 44 46 46 44 42 34 31 26 23 23 25 29 31 34 37 38 38 34 31 29 28 25 24 23 22 23 25 27 28 31 33 37 43 49 56 61 64 71 72 71 67 59 47 36 29 18 17 15 14 14 15 17 19 23 25 29 31 32 30 27 25 22 21 19 18 18 20 21 22 27 28 30 31 32 32 31 31 29 27 26 26 26 25 22 19 15 15 13 12 10 10 10 10 8 8 8 8 8 8 8 9 7 7 7 7 7 7 7 7 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 16 16 16 16 18 19 21 22 20 21 23 24 24 23 21 20 19 19 18 17 16 16 15 15 14 14 13 13 15 17 19 20 22 25 29 32 34 36 39 41 47 48 50 52 52 50 48 47 46 44 41 37 34 32 32 31 33 34 35 36 36 36 36 36 35 34 33 32 31 31 31 31 38 41 47 52 57 60 61 61 60 61 63 67 71 75 79 81 77 72 65 58 55 55 57 59 62 63 65 66 65 62 58 56 57 59 63 69 80 95 110 121 138 140 141 137 129 120 112 108 102 102 101 100 98 97 96 95 91 90 88 87 89 95 104 111 123 122 119 112 104 97 94 92 94 96 99 100 97 90 82 77 73 70 65 60 59 63 71 77 91 100 105 100 94 92 91 90 95 99 103 103 100 99 100 102 104 105 104 101 97 94 94 95 99 105 111 118 126 134 134 131 121 111 96 82 74 72 76 79 85 88 90 88 83 78 77 78 78 84 92 102 111 120 128 134 141 142 138 125 109 93 76 62 55 59 65 71 71 65 54 47 42 45 49 50 47 42 39 38 42 50 57 57 48 38 32 30 39 51 66 74 71 62 52 46 51 56 62 65 62 56 50 46 50 55 64 71 71 65 54 45 38 38 37 38 39 38 36 33 31 38 47 58 75 92 102 103 99 86 69 56 44 35 35 39 41 41 38 33 28 29 34 39 52 59 66 68 63 57 53 51 51 49 49 51 49 43 40 41 39 36 32 29 27 28 29 30 32 39 52 69 87 103 115 121 110 100 82 63 53 51 50 47 52 51 52 56 61 66 69 69 64 52 40 34 31 32 40 49 58 62 63 58 54 51 45 38 30 27 23 22 24 26 28 29 28 28 28 27 25 24 22 21 18 22 28 35 41 46 49 50 51 51 51 50 49 50 52 55 60 64 71 75 74 68 61 56 42 37 31 27 25 25 25 25 24 25 26 27 27 27 26 25 28 29 30 31 32 32 32 32 33 37 42 48 52 53 53 53 51 50 50 52 53 52 50 47 37 33 27 23 20 21 24 26 28 31 33 33 30 27 25 25 24 23 22 21 21 22 24 25 30 32 37 43 51 58 64 67 75 75 75 71 62 51 39 32 20 19 17 16 16 18 20 21 26 28 32 34 33 31 27 24 21 20 17 15 14 15 17 18 21 23 25 26 27 27 26 26 24 23 22 22 23 22 19 17 15 14 12 11 10 10 10 10 8 8 8 8 9 9 9 9 8 8 8 8 8 8 8 8 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 16 16 16 17 18 20 22 23 19 21 23 25 26 25 24 23 21 21 20 19 19 18 17 17 16 15 14 14 14 16 18 19 20 23 28 30 32 34 37 39 44 45 46 47 48 48 48 48 45 44 43 41 38 36 34 33 32 32 33 33 32 31 30 30 29 29 29 29 30 31 32 33 39 42 47 54 60 65 68 69 70 73 77 81 86 90 93 95 91 85 76 68 63 63 65 68 73 74 75 74 72 69 65 63 65 67 71 76 85 97 110 118 134 137 139 135 126 115 108 104 101 101 102 104 105 106 105 104 103 103 103 105 109 115 123 127 133 130 125 116 107 100 98 97 104 110 118 123 123 116 106 100 89 83 73 64 61 64 71 77 90 99 103 98 90 88 89 89 93 98 102 101 95 92 94 97 102 105 108 108 105 101 101 101 101 106 111 115 123 131 130 125 117 109 96 85 80 81 87 92 98 101 103 98 89 80 77 76 77 82 91 99 106 112 117 121 124 125 121 110 98 86 71 59 52 56 63 69 71 65 55 47 40 41 41 39 38 39 42 45 52 59 65 62 52 40 35 33 47 61 79 88 83 70 55 46 45 50 57 60 57 51 45 41 45 51 61 71 74 69 57 48 40 38 38 39 41 41 38 35 31 36 42 51 67 84 94 95 94 82 68 56 45 36 35 38 40 40 40 36 33 33 38 43 55 62 70 72 67 60 55 53 50 45 43 45 44 39 39 42 39 36 33 30 28 28 29 30 31 35 44 56 70 85 97 104 96 91 77 60 51 50 47 41 45 45 45 48 53 57 60 61 56 46 35 30 27 29 37 46 54 58 58 54 51 49 44 37 31 27 23 22 25 28 31 32 32 31 29 26 23 21 19 19 20 25 33 42 49 53 54 55 53 52 51 48 45 45 47 49 53 57 63 67 66 60 53 49 37 32 25 21 20 22 24 25 27 29 33 36 36 34 31 29 29 30 32 34 35 36 37 37 39 43 50 57 62 64 65 65 62 61 59 59 60 58 55 52 43 39 32 26 22 22 23 25 24 27 29 30 28 25 24 24 22 22 21 21 20 21 21 21 26 28 33 39 47 54 60 63 72 73 72 68 60 49 38 32 22 21 19 18 19 20 23 24 29 31 34 36 35 31 26 23 21 18 15 12 11 12 14 15 17 18 20 21 22 22 21 21 20 19 18 18 19 18 16 14 14 13 12 11 10 10 10 10 8 8 8 9 9 10 10 10 8 8 8 8 8 8 8 8 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 16 16 17 18 19 21 22 23 19 21 23 26 27 27 26 25 22 22 21 21 20 19 19 18 18 17 15 14 14 15 17 18 19 22 26 29 30 32 34 37 39 40 40 42 43 44 45 46 42 42 43 43 41 39 37 35 32 32 32 32 31 29 28 27 26 27 27 28 30 32 33 34 38 41 47 54 61 67 71 73 79 82 87 93 99 102 105 106 101 95 85 76 71 70 73 75 84 84 84 83 80 77 73 70 73 76 80 85 92 102 112 119 131 134 136 132 122 112 104 101 100 100 102 105 108 110 110 109 112 113 115 118 123 129 135 139 137 134 128 119 109 102 99 99 111 119 132 143 146 141 132 126 108 99 86 74 68 70 77 83 92 101 105 100 93 91 93 94 95 100 104 101 93 88 89 92 93 98 103 105 102 99 98 98 99 103 106 108 115 123 123 116 117 110 99 91 88 93 100 106 108 111 112 105 92 80 74 72 74 80 87 94 99 104 107 110 108 109 105 96 87 78 66 56 50 54 61 68 71 66 55 47 40 39 36 34 34 38 45 50 58 65 70 66 54 42 37 36 57 72 90 100 94 78 61 50 42 48 55 58 55 48 42 38 41 48 59 70 75 71 59 49 40 38 37 39 42 42 40 37 32 36 40 47 62 79 88 89 91 80 67 56 46 37 34 37 39 40 41 38 36 36 40 45 56 63 71 73 68 61 56 54 48 42 39 42 41 37 39 44 39 37 33 30 29 29 30 30 32 34 38 46 56 69 80 86 86 83 72 57 49 48 43 36 41 40 40 42 47 51 53 54 52 42 32 27 26 27 35 43 49 52 53 50 47 45 41 35 31 27 24 23 25 29 32 34 34 32 29 26 23 20 18 17 22 27 36 46 53 57 58 58 53 52 50 46 42 40 42 43 46 50 55 58 57 52 46 41 35 30 22 18 18 21 24 26 32 35 40 44 45 42 38 35 29 30 33 35 37 39 40 40 43 47 55 62 68 71 72 72 69 67 65 64 64 62 58 55 50 45 38 31 26 25 26 27 22 25 28 29 27 25 24 24 21 21 20 20 20 19 19 19 21 23 28 34 41 48 54 58 69 69 68 64 57 46 36 30 23 22 21 20 20 22 25 26 31 33 36 37 35 31 25 22 20 18 14 11 10 10 12 14 14 15 17 19 19 19 18 18 17 16 15 16 17 16 14 12 13 13 12 10 10 10 10 10 8 8 8 9 9 10 10 10 8 8 8 8 8 8 8 8 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 17 17 18 19 20 20 21 21 20 21 23 25 26 25 23 22 24 24 24 23 22 21 20 19 19 19 19 19 19 19 19 19 20 20 21 23 26 29 31 33 36 36 36 37 37 37 37 37 40 40 40 40 40 39 38 37 35 34 32 30 28 27 26 26 31 30 29 29 31 34 37 39 40 43 48 53 58 63 70 74 76 82 91 100 108 113 115 116 107 102 93 84 79 82 89 95 99 105 105 98 91 88 87 84 89 92 96 103 109 114 118 120 127 127 126 125 121 114 104 97 91 96 104 110 114 118 121 123 124 125 127 130 134 137 139 141 141 134 126 118 106 97 100 109 116 128 144 156 165 167 160 150 137 126 110 96 89 87 88 90 97 99 100 97 95 94 98 101 103 110 111 102 93 88 83 77 86 90 94 96 95 93 92 91 87 92 97 97 96 97 103 108 105 111 115 115 119 125 130 130 133 125 114 103 94 83 72 64 70 75 80 86 95 101 98 92 92 85 81 84 83 75 64 59 54 56 60 67 72 71 65 59 49 42 37 38 40 43 50 58 65 71 74 67 54 44 43 46 68 89 111 117 107 89 69 56 47 51 56 58 55 48 40 34 36 43 54 65 69 64 53 45 33 33 33 36 40 43 43 43 39 39 41 46 55 67 78 84 82 75 64 51 42 38 37 37 39 42 44 44 42 41 44 46 55 58 63 65 63 58 52 48 43 42 42 43 45 46 44 42 37 35 33 32 34 36 36 36 34 33 34 37 45 55 64 70 73 70 65 58 51 44 39 37 34 34 35 36 38 40 42 43 37 34 29 26 27 32 38 42 47 47 46 45 43 40 37 35 28 26 25 26 29 32 33 33 34 31 28 24 21 20 21 21 26 32 41 50 55 56 55 53 47 45 42 38 37 36 37 37 40 42 45 47 47 44 40 38 29 28 26 23 22 24 28 32 40 47 54 55 55 53 46 39 34 33 33 35 39 43 44 44 46 50 58 66 72 76 78 79 76 72 68 68 71 71 67 63 56 51 44 38 34 30 26 23 28 29 30 32 32 32 31 30 27 26 24 22 20 19 19 18 21 23 26 30 35 40 44 46 52 53 53 51 46 39 31 27 22 23 25 27 29 31 32 33 35 34 34 34 34 31 26 23 16 15 14 12 10 10 9 9 9 11 14 16 17 17 15 14 13 13 14 14 14 15 15 15 13 13 13 13 12 11 10 9 8 9 11 12 13 12 11 11 10 11 11 11 11 10 9 8 8 8 8 7 7 6 6 6 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 17 17 17 18 19 20 20 21 20 21 23 25 25 25 23 22 24 24 24 24 23 21 20 19 19 19 19 19 19 19 19 19 19 20 20 22 24 26 28 30 32 32 32 32 33 33 33 33 37 37 38 39 39 39 38 38 37 36 34 32 30 29 29 28 32 31 31 32 34 37 41 43 43 45 49 52 56 61 67 72 77 83 92 102 110 115 117 118 110 105 97 89 87 91 100 107 112 117 118 111 103 99 96 92 102 105 111 117 122 125 127 127 127 126 125 123 119 112 103 97 94 99 105 111 115 119 122 125 131 133 135 137 139 140 141 141 137 131 125 118 108 100 103 111 121 135 152 166 178 182 176 167 150 140 125 113 105 103 103 103 107 107 106 103 100 100 103 107 110 117 117 107 97 92 86 80 83 86 90 90 88 84 82 81 76 80 83 83 81 83 89 95 103 113 125 134 145 155 159 159 153 142 125 109 95 82 70 62 69 74 81 88 96 100 95 87 83 76 71 74 75 69 62 58 55 56 60 66 72 72 68 63 54 47 42 41 42 44 50 58 67 72 74 67 55 47 47 51 75 96 117 122 112 95 75 61 50 54 59 61 58 51 43 37 37 43 52 60 63 59 50 42 31 30 31 35 39 42 43 43 40 40 41 45 53 64 74 80 79 72 61 50 42 37 36 37 40 43 46 46 45 44 45 47 51 54 57 59 58 54 49 46 42 42 43 45 48 48 45 43 38 35 32 32 34 37 38 38 37 35 33 33 37 44 52 57 65 63 60 55 49 42 37 34 30 29 29 29 30 32 34 35 35 32 29 27 28 31 36 39 44 44 44 43 41 38 36 34 28 26 25 25 28 31 32 33 33 31 27 24 22 21 21 21 28 32 40 47 51 51 49 47 40 38 35 33 32 32 33 33 33 35 37 39 39 37 35 34 30 29 28 25 25 27 32 36 46 55 62 64 64 61 52 43 36 34 33 35 38 42 43 44 47 51 57 64 70 73 75 76 73 69 65 66 69 70 67 63 58 54 47 41 36 32 28 25 28 30 33 35 36 35 33 32 29 27 25 23 21 20 19 19 21 22 25 29 33 36 38 38 40 41 41 40 37 32 27 24 22 24 26 29 31 33 33 33 34 33 32 32 32 29 25 21 16 15 14 12 11 10 10 10 9 11 13 15 16 16 14 14 13 13 13 13 14 14 14 15 12 13 13 13 13 12 11 11 9 10 12 13 14 13 12 11 10 11 11 11 11 10 9 8 8 8 8 7 7 6 6 6 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 16 16 17 17 18 19 20 20 20 21 23 24 25 24 23 22 24 24 24 24 23 22 21 20 19 19 19 19 19 19 19 19 19 19 19 20 21 23 24 25 26 26 27 27 28 28 28 29 31 32 34 36 37 38 39 39 39 38 36 34 32 32 31 31 33 33 33 35 38 41 45 47 47 48 50 51 54 58 64 68 75 80 90 100 108 113 116 117 108 104 98 93 93 101 112 120 127 133 134 127 118 112 107 102 113 118 125 132 135 136 134 132 130 127 124 121 118 113 107 102 102 106 112 116 120 123 127 130 134 136 137 139 138 137 135 133 127 123 118 113 106 100 103 109 121 136 155 172 185 192 188 180 163 155 143 132 125 122 120 119 116 114 110 105 102 102 105 109 115 120 119 111 102 95 91 87 87 89 91 89 83 76 71 69 64 66 67 66 65 68 74 80 98 114 136 156 175 188 192 189 175 160 137 114 96 81 69 62 68 76 85 94 101 103 95 85 76 68 62 64 67 65 61 60 56 56 58 64 71 73 71 68 60 53 47 45 44 45 49 56 67 71 72 66 56 52 55 61 84 103 121 124 114 97 78 64 53 56 62 64 62 55 47 41 39 42 48 53 55 51 43 37 28 28 29 33 38 42 44 44 43 42 42 45 51 59 68 73 72 66 57 47 40 36 35 36 41 44 48 49 49 48 47 48 47 48 49 50 49 47 45 44 42 43 46 50 52 51 48 44 39 36 32 32 34 38 41 42 41 37 33 30 31 36 43 47 54 54 53 50 45 38 32 28 26 26 24 24 24 26 27 28 33 31 30 29 29 32 35 36 39 39 39 38 37 35 33 32 28 26 24 25 28 30 31 31 31 30 27 24 23 22 22 22 29 32 37 41 43 42 40 38 30 29 27 26 26 26 27 28 28 28 30 31 32 32 32 31 32 31 30 29 29 33 38 43 54 63 73 76 74 69 58 48 39 36 34 34 37 40 43 44 48 51 55 60 64 67 69 69 67 64 62 63 66 67 65 62 60 55 49 42 38 34 29 27 29 32 36 39 40 38 36 34 30 29 26 24 22 20 19 19 21 23 27 31 33 33 32 31 30 30 30 29 28 26 24 23 23 26 30 33 35 35 34 33 32 31 30 29 29 27 23 19 16 15 14 12 11 10 10 10 9 10 12 14 15 14 13 13 12 12 12 13 13 14 14 14 12 12 13 14 14 14 13 13 11 12 14 15 16 15 14 13 11 11 11 11 11 10 9 9 8 8 8 7 7 6 6 6 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 15 15 15 16 17 18 18 19 20 21 22 23 23 23 22 22 23 23 24 24 23 22 21 20 19 19 19 19 19 19 19 19 19 19 18 18 19 19 20 21 22 22 23 24 24 25 25 26 27 28 31 33 36 37 38 39 39 38 36 34 33 32 32 32 32 32 34 36 40 44 47 49 50 51 51 51 52 55 61 65 70 75 84 94 102 107 109 110 101 98 94 91 94 104 117 126 136 142 144 137 127 120 114 109 115 121 130 138 141 140 136 133 132 129 125 123 122 119 116 114 115 118 121 124 127 130 134 137 137 138 140 140 138 135 131 128 124 122 119 114 108 104 105 108 115 129 148 165 179 186 183 175 164 158 150 143 139 136 133 131 122 118 110 103 98 98 101 103 112 115 115 110 104 100 99 99 102 103 103 97 87 76 67 62 57 58 57 56 56 59 65 70 90 111 139 168 192 207 209 205 186 168 141 115 96 82 73 68 72 81 93 103 111 112 103 91 77 67 59 61 64 64 63 63 56 55 56 61 68 72 72 71 64 56 49 47 44 42 46 51 62 65 66 63 58 58 64 71 91 106 120 120 109 92 73 60 52 57 62 66 64 58 50 44 41 41 43 45 45 42 36 32 26 26 28 33 39 44 46 47 46 45 44 45 49 56 62 66 64 59 52 44 39 36 35 35 41 44 48 51 51 50 49 48 44 43 42 42 41 42 42 43 43 45 50 54 57 56 51 47 40 37 32 31 34 39 43 45 43 40 35 32 33 38 44 48 51 51 50 47 42 34 27 22 25 25 24 24 24 26 28 29 32 32 32 32 32 33 34 35 34 34 34 34 33 32 32 32 29 27 25 25 27 29 30 30 30 29 27 25 24 24 24 24 30 31 33 34 34 33 30 29 24 24 23 22 23 23 24 25 27 27 27 28 30 31 33 33 34 34 33 33 34 39 45 50 60 70 80 83 81 74 61 50 41 38 34 32 35 38 41 43 46 47 50 53 56 59 61 61 61 59 58 59 61 62 61 59 58 54 47 41 37 33 29 26 29 32 37 42 43 42 38 36 30 29 27 24 22 21 20 20 23 26 32 36 38 36 33 31 29 28 27 25 24 24 25 25 24 28 33 37 39 38 35 33 30 29 27 26 26 24 20 17 16 15 14 12 11 11 11 11 9 10 12 13 13 13 13 12 12 12 12 12 13 13 14 14 12 13 14 15 16 16 15 15 14 15 16 17 17 16 15 14 11 11 12 12 11 11 10 9 8 8 8 7 7 6 6 6 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 13 14 14 15 16 17 17 17 19 19 20 21 21 21 21 21 22 22 22 23 22 22 21 20 19 19 19 19 19 19 19 19 19 19 18 18 17 18 19 19 21 21 22 23 24 25 25 26 25 26 29 32 34 36 37 38 37 36 35 33 32 32 32 32 30 32 34 37 40 44 47 49 52 53 53 53 53 55 59 63 67 72 80 89 96 100 101 102 93 91 88 88 92 101 114 123 135 142 144 138 129 122 116 111 114 120 129 137 141 140 137 134 131 129 127 127 129 131 132 131 128 130 131 132 133 135 139 142 145 146 148 148 146 143 139 136 134 133 130 124 118 115 112 111 112 124 140 154 166 172 169 162 156 153 149 147 146 146 144 143 130 123 112 103 97 95 96 97 105 106 107 106 104 104 109 115 119 120 119 111 96 80 65 57 53 54 54 54 54 56 59 62 80 102 133 165 193 211 213 208 188 170 142 115 96 85 77 73 77 87 100 111 120 121 112 100 80 69 61 61 65 65 64 65 56 54 54 58 65 70 71 70 62 55 48 45 41 38 40 45 52 56 60 61 60 64 71 78 95 105 113 110 98 82 65 52 49 54 60 64 64 59 52 47 42 41 40 39 38 35 31 27 26 27 29 34 41 46 49 49 49 48 46 46 48 52 57 60 56 52 47 42 38 35 35 35 41 43 46 49 51 51 49 47 42 41 38 37 36 38 40 41 45 48 52 57 60 58 52 48 41 37 33 32 35 40 44 46 46 44 40 38 39 43 48 51 54 53 50 45 38 30 22 18 23 24 25 26 28 30 31 32 32 33 33 34 34 34 34 34 30 30 30 30 30 31 32 32 30 28 26 26 27 29 29 29 29 29 28 27 27 27 27 27 29 29 29 28 27 26 24 24 25 25 25 24 24 24 25 25 27 27 27 28 29 31 33 35 35 36 36 36 38 43 50 55 65 75 83 85 82 75 62 51 41 37 33 31 33 37 40 41 41 42 43 46 48 51 53 55 57 56 55 55 56 56 55 54 52 48 42 36 33 30 26 24 28 31 37 41 43 42 39 37 30 29 27 25 24 23 22 22 28 32 39 45 47 45 41 38 33 31 28 25 24 24 25 25 26 29 35 40 41 39 36 34 29 27 25 24 23 21 18 16 16 15 14 13 12 12 12 12 11 11 12 12 12 12 12 12 12 12 12 13 13 14 14 14 13 14 15 16 17 17 17 16 15 16 18 18 18 17 16 15 11 12 12 12 12 11 10 9 8 8 8 7 7 6 6 6 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 12 12 13 14 15 15 16 16 17 17 18 18 18 19 19 19 20 20 21 21 21 20 20 19 19 19 19 19 19 19 19 19 20 19 19 18 18 18 19 19 21 21 22 23 24 25 26 27 25 26 29 31 33 34 35 36 36 35 34 32 32 31 31 31 30 32 34 37 41 44 46 48 51 53 55 55 56 57 60 62 67 72 79 86 91 93 94 93 86 85 84 84 88 96 107 114 123 130 133 127 120 116 112 108 111 116 123 129 133 133 131 129 124 123 125 129 136 143 147 148 143 143 143 141 140 141 145 148 153 154 156 157 157 155 153 151 149 149 145 136 128 123 116 110 115 125 136 145 154 159 156 149 145 144 144 147 151 155 157 157 143 134 121 110 102 98 96 95 100 98 98 100 100 104 114 125 127 129 129 121 105 84 66 55 50 52 54 56 57 57 56 55 69 87 116 147 177 197 202 198 178 160 134 110 94 84 78 75 79 89 100 111 119 121 113 102 80 70 63 65 68 67 65 65 58 55 54 57 63 67 68 66 58 51 44 41 38 34 36 40 45 51 57 61 64 68 74 79 92 99 101 95 83 71 57 46 44 50 57 63 64 60 54 49 43 40 37 36 34 31 28 25 27 27 30 35 42 47 49 50 49 48 46 45 45 48 51 54 49 47 44 40 38 36 35 35 39 40 42 45 48 49 47 45 42 39 36 34 33 35 37 39 46 48 52 57 58 56 50 46 40 37 33 33 35 39 42 44 48 46 45 44 45 48 52 54 60 56 50 42 34 27 21 18 22 24 27 30 32 33 33 33 32 33 33 34 34 34 33 32 27 27 27 28 29 31 33 34 33 30 27 27 28 29 30 29 29 30 30 30 30 30 30 30 29 28 27 26 25 25 25 25 31 31 30 29 28 27 27 26 27 27 27 28 29 31 33 34 36 37 37 37 40 45 52 57 68 76 82 81 77 71 60 49 37 34 31 30 33 36 38 38 37 37 38 39 42 46 50 52 55 54 53 52 51 50 49 48 45 41 35 31 28 26 23 21 26 29 34 38 41 40 39 37 31 31 29 28 27 27 27 27 34 39 46 52 54 53 49 46 36 34 30 26 24 23 23 24 28 31 36 40 41 40 37 34 28 26 23 22 21 20 17 15 16 15 14 13 13 13 13 13 12 12 12 12 12 13 13 13 13 13 14 14 14 15 15 15 15 16 17 17 18 17 17 17 16 17 18 19 19 17 16 15 12 12 13 13 12 11 10 10 8 8 8 7 7 6 6 6 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 11 12 12 13 14 15 15 15 15 15 15 15 16 16 17 18 18 18 19 20 20 19 19 18 19 19 19 19 19 19 19 19 21 20 20 19 19 20 21 21 21 21 22 24 25 26 27 28 27 28 30 31 32 33 33 33 36 35 34 33 32 32 32 32 32 33 36 39 42 45 46 47 49 52 56 58 59 60 62 63 66 70 76 81 84 85 84 83 79 79 79 79 82 88 95 101 103 110 113 108 103 102 101 98 102 104 108 112 114 115 114 114 112 114 119 128 140 151 158 161 162 160 158 154 151 152 155 158 163 164 166 168 170 172 172 172 171 171 165 152 142 134 124 114 116 123 130 135 141 145 142 136 133 134 137 145 154 162 167 169 156 146 132 119 110 104 99 95 96 91 88 89 90 95 109 123 128 132 135 129 112 89 68 56 49 52 57 62 63 61 56 51 56 70 92 118 145 165 171 168 151 137 115 97 86 80 77 74 78 85 94 102 109 111 104 93 80 72 67 70 74 72 69 68 61 58 57 59 64 67 66 64 53 47 41 38 35 32 34 38 43 50 58 65 68 71 74 76 82 85 84 76 67 58 48 40 41 46 55 62 64 61 56 52 43 40 37 34 32 30 26 23 26 27 29 34 40 46 48 48 47 45 43 42 42 43 46 47 44 43 41 40 38 37 36 36 37 36 37 40 44 46 45 42 41 38 35 32 31 32 34 35 46 47 50 53 54 51 46 42 40 37 34 34 36 39 40 40 45 46 48 51 55 59 62 64 64 58 49 39 30 25 22 21 26 29 33 37 38 37 35 33 31 31 31 31 31 31 31 30 26 26 26 27 29 32 34 36 35 32 29 28 29 30 30 29 30 30 31 32 33 33 33 33 31 29 27 26 26 28 30 31 38 38 37 35 33 30 28 27 29 29 30 31 32 33 34 34 37 37 38 38 40 45 52 58 64 70 72 69 65 60 51 42 33 31 29 30 32 35 36 36 34 34 34 36 40 45 50 53 55 54 53 50 47 44 42 42 38 34 30 26 25 23 21 19 23 26 30 34 36 37 37 37 34 33 33 32 32 33 33 34 40 44 50 56 58 56 52 49 38 36 32 29 26 25 24 24 29 32 36 39 41 39 37 35 28 25 22 21 20 19 17 15 16 15 14 13 13 13 13 14 14 14 13 13 13 13 14 14 14 14 15 15 16 16 16 16 17 18 18 19 18 18 17 16 17 18 19 19 19 17 15 14 12 12 13 13 12 12 11 10 8 8 8 7 7 6 6 6 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 11 11 12 12 13 14 15 15 14 14 14 14 14 15 16 17 17 17 18 19 19 18 18 17 19 19 19 19 19 19 19 19 21 21 20 20 21 21 22 23 21 21 22 23 25 26 27 28 29 29 31 32 32 32 32 32 36 36 35 33 33 33 33 33 33 35 37 40 43 45 47 47 47 51 57 60 61 62 63 64 64 67 72 76 78 78 76 74 74 74 75 75 76 80 86 90 86 93 96 92 89 89 90 88 91 92 93 95 96 97 97 97 104 107 114 126 141 154 162 166 176 174 171 166 162 162 165 168 176 177 179 182 186 189 191 193 194 194 186 172 159 150 137 125 113 118 123 126 130 134 132 126 124 126 132 141 154 165 172 175 163 153 138 125 115 107 100 95 93 85 80 80 80 85 100 116 127 133 137 133 117 94 72 59 50 55 62 68 70 65 57 51 47 57 73 93 116 135 141 138 125 113 97 84 78 76 75 74 76 81 88 93 99 101 94 84 80 74 71 76 81 79 74 72 64 61 59 61 65 67 65 62 51 44 39 37 34 31 33 37 44 51 61 68 71 72 72 73 71 73 70 62 54 49 42 35 39 45 54 61 65 63 58 54 43 40 37 34 32 29 26 23 25 26 28 33 39 44 46 46 45 43 41 39 39 40 42 43 41 41 40 39 38 37 37 37 36 34 34 36 41 43 43 41 40 37 34 30 29 29 31 32 45 45 47 49 50 48 43 38 39 37 35 34 36 38 38 38 40 43 49 56 63 70 74 76 65 58 47 36 28 24 24 24 31 34 39 43 44 41 37 33 29 29 29 29 29 28 29 29 26 26 26 27 30 33 36 37 36 33 30 29 30 31 31 30 30 31 32 34 35 35 35 35 32 31 29 28 29 31 34 37 43 42 40 38 35 32 29 27 32 33 34 35 36 36 36 36 37 37 38 38 40 45 52 57 58 62 63 58 54 49 42 34 30 29 28 30 32 35 35 35 33 33 33 35 40 45 51 55 55 55 53 49 44 40 39 38 35 31 27 24 23 22 21 19 22 24 27 31 34 35 36 36 36 36 35 35 36 37 38 39 43 47 52 57 58 56 52 49 39 37 35 31 29 28 27 27 30 32 36 39 40 39 37 36 28 25 22 20 20 19 17 15 15 15 14 13 13 13 14 14 15 15 14 13 13 14 14 15 15 15 16 16 16 17 17 17 19 19 19 19 19 18 16 16 17 18 18 19 18 17 15 14 12 13 13 13 13 12 11 10 8 8 8 7 7 6 6 6 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 10 10 10 11 11 12 12 12 12 12 12 13 13 14 14 14 15 15 15 16 16 17 17 17 18 18 18 19 19 20 20 20 21 21 21 21 21 22 23 24 24 25 25 26 27 28 29 29 29 30 31 30 30 30 33 35 37 38 40 40 40 39 38 37 40 42 45 48 49 48 46 45 51 55 59 61 66 71 70 65 68 65 67 72 75 73 72 74 73 77 81 82 85 87 83 76 76 75 74 73 74 76 78 80 84 84 85 85 86 87 88 89 87 93 104 120 138 155 170 178 189 190 190 188 186 186 187 188 186 190 194 195 197 203 214 222 222 219 208 191 176 163 145 130 122 119 118 120 121 119 117 117 113 117 125 135 147 160 172 180 175 163 147 134 123 114 103 95 90 80 72 69 71 77 88 99 114 122 128 123 111 95 75 60 46 52 62 73 80 80 74 69 55 54 57 70 89 104 110 111 99 91 81 73 70 69 68 67 71 73 76 77 78 80 83 86 73 80 85 84 85 87 81 71 63 61 59 61 68 74 70 62 55 46 38 35 33 33 38 45 52 58 66 72 74 72 70 68 64 58 54 52 48 41 38 40 40 46 53 59 65 68 63 55 46 46 43 37 31 26 24 25 24 24 26 29 34 38 40 41 41 41 40 37 35 36 39 41 39 43 45 43 43 45 42 38 35 33 31 31 35 38 41 41 37 35 31 28 27 28 29 31 34 38 44 47 47 46 45 44 39 39 39 39 38 36 34 33 39 45 54 65 74 80 82 82 70 60 47 37 27 21 23 29 39 42 47 50 49 43 36 31 29 28 27 26 26 27 29 30 33 32 31 31 31 33 35 36 36 34 32 29 28 27 27 28 30 31 33 35 36 37 38 38 37 35 34 34 36 40 45 49 52 53 52 46 38 31 29 29 34 35 37 38 40 41 42 42 40 39 38 37 39 41 44 46 50 49 46 43 39 36 33 31 26 27 29 31 33 33 33 32 37 35 34 36 40 47 55 59 53 52 51 48 44 39 34 31 29 29 28 27 26 25 24 24 21 22 25 28 30 32 33 33 37 38 40 42 44 45 46 46 50 51 54 57 57 53 46 41 36 34 32 29 28 27 27 28 31 33 37 40 40 38 35 33 31 29 26 23 21 20 20 21 15 15 15 15 15 15 15 15 15 15 14 13 12 12 11 11 15 15 16 16 16 17 17 17 18 19 19 19 19 18 17 16 16 17 17 17 17 16 15 14 12 12 12 11 11 10 10 10 7 7 7 6 6 5 5 5 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 10 10 10 11 11 12 12 12 12 12 12 13 13 14 14 14 15 15 15 16 16 17 17 17 18 18 18 19 19 20 20 20 21 21 21 21 22 24 25 26 26 26 27 27 28 29 29 29 29 30 31 30 30 31 34 36 40 41 44 46 46 46 44 43 46 47 50 51 52 51 49 48 52 58 62 65 70 75 73 68 72 69 70 74 77 76 78 81 78 84 91 94 98 99 94 86 79 76 72 69 70 74 79 82 86 86 85 84 83 83 83 83 84 92 106 122 140 158 175 185 197 200 205 206 206 204 204 204 202 204 207 207 208 213 222 230 234 231 219 201 185 171 153 138 129 125 121 119 116 112 108 106 106 111 120 133 147 162 176 183 177 166 152 139 129 118 107 99 86 77 68 65 65 69 78 88 103 112 120 117 108 94 76 61 49 53 63 76 86 90 86 81 64 60 58 64 75 85 87 86 84 79 72 68 69 71 73 73 68 69 70 69 69 71 74 77 83 89 93 91 89 86 77 67 57 58 59 63 73 80 76 68 55 46 39 36 37 38 43 50 56 61 67 72 73 70 67 65 56 51 48 47 44 38 37 40 43 50 57 63 69 72 67 58 50 48 43 37 31 28 26 26 23 23 24 26 29 31 32 33 34 34 34 32 30 31 34 37 38 44 47 47 47 49 46 41 36 34 32 32 35 39 41 41 38 36 32 29 28 29 30 31 33 37 43 46 46 45 44 44 41 42 42 42 40 38 35 34 39 44 54 66 75 80 80 80 67 57 45 36 28 24 28 34 42 45 49 50 48 43 36 31 27 27 27 27 28 30 31 33 35 35 34 33 33 34 35 35 35 34 31 29 27 26 27 27 30 31 34 37 39 39 39 39 39 37 36 36 39 43 48 51 54 54 52 46 39 33 31 32 35 36 39 41 43 44 44 43 41 40 38 36 36 37 39 41 41 40 37 34 31 28 26 25 27 29 31 34 36 36 35 35 35 35 35 37 41 48 54 58 55 54 51 47 43 37 33 31 31 31 30 30 28 27 25 25 21 22 24 26 29 31 33 34 38 39 42 45 47 49 51 51 52 53 54 55 54 49 42 36 32 31 29 27 26 27 28 28 30 32 36 40 41 40 37 36 33 31 28 25 23 21 21 21 17 17 17 17 17 17 17 17 16 15 15 14 13 12 12 11 15 15 15 16 16 16 17 17 18 18 19 19 18 17 16 16 16 16 17 17 16 15 14 14 12 12 11 11 11 10 10 10 7 7 7 6 6 5 5 5 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 10 10 10 11 11 12 12 12 12 12 12 13 13 14 14 14 15 15 15 16 16 17 17 17 18 18 18 19 19 20 20 20 21 21 21 22 23 25 27 28 28 29 29 29 29 29 29 29 29 30 31 30 30 32 36 38 45 48 51 55 57 57 55 54 55 55 56 56 55 54 53 52 55 62 69 74 79 83 80 73 73 69 67 70 72 74 78 84 88 97 107 115 120 121 114 105 90 84 76 69 69 75 83 89 100 99 98 96 94 92 90 89 89 99 113 127 142 161 181 194 212 218 226 231 232 230 228 227 223 224 224 222 221 224 231 237 246 242 230 212 195 179 162 150 140 136 129 122 116 110 104 99 101 105 115 128 144 161 174 181 176 168 156 144 132 120 107 98 83 74 65 62 60 62 69 77 89 99 108 110 105 94 77 63 52 54 62 78 94 103 102 98 85 77 69 67 70 73 73 71 71 68 64 64 67 72 75 77 72 72 71 69 68 69 72 75 91 97 100 97 92 84 72 62 52 56 62 69 80 86 82 73 56 48 41 40 42 44 49 55 60 63 67 70 70 67 63 60 51 46 43 43 42 39 40 43 47 55 63 69 74 76 71 63 55 50 42 36 32 30 29 28 27 27 28 27 27 26 25 25 28 29 28 27 26 28 32 35 38 45 51 53 55 56 53 48 40 37 34 34 37 40 41 42 39 37 34 32 30 31 32 33 34 38 42 44 44 44 44 44 45 46 47 47 46 42 38 36 38 43 53 65 75 79 78 76 63 53 41 34 30 28 33 40 45 47 49 49 46 41 34 30 25 26 27 28 31 33 36 37 39 39 38 37 36 35 35 34 34 33 30 28 26 25 26 26 29 32 36 40 42 42 41 40 40 40 39 40 42 46 50 53 55 54 51 45 39 35 34 35 36 39 42 44 46 46 45 44 42 40 37 34 32 32 33 34 32 31 29 26 25 23 23 23 31 33 36 38 39 39 37 36 34 34 35 38 42 48 53 57 58 56 52 47 42 37 33 31 32 33 33 33 32 30 27 26 23 23 23 25 27 30 33 35 39 41 44 48 52 55 57 58 56 56 55 53 50 44 36 30 26 26 25 25 25 27 29 30 30 32 36 39 41 40 39 37 34 32 29 26 23 22 21 21 19 19 19 19 19 19 19 19 17 16 16 15 14 13 13 12 14 14 15 15 15 16 16 16 17 17 18 18 17 17 16 15 15 15 16 16 15 15 14 13 12 11 11 11 10 10 10 10 7 7 7 6 6 5 5 5 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 10 10 10 11 11 12 12 12 12 12 12 13 13 14 14 14 15 15 15 16 16 17 17 17 18 18 18 19 19 20 20 20 20 20 21 22 24 26 28 30 31 30 30 30 30 30 29 29 29 30 31 31 32 34 39 42 51 55 61 66 69 69 68 67 64 62 61 59 57 55 55 54 58 66 76 83 90 93 89 82 76 71 68 69 70 73 81 90 101 112 127 138 146 149 142 132 117 108 96 86 84 90 101 108 119 121 123 123 121 116 111 108 109 117 127 136 147 166 189 206 231 236 244 248 249 248 247 247 240 239 237 234 231 232 236 239 247 241 230 215 199 184 172 164 155 153 145 135 126 118 108 100 99 101 109 121 137 153 165 172 172 165 155 142 128 113 98 88 78 71 64 62 61 62 67 74 82 92 101 104 102 93 78 64 54 53 59 76 97 112 115 112 103 94 82 74 72 72 70 68 68 66 65 65 68 71 75 77 78 78 76 74 72 73 76 79 92 97 100 97 89 77 65 57 50 58 68 78 88 92 86 76 61 51 44 44 47 49 53 58 60 61 64 66 66 64 60 56 51 46 43 43 43 42 45 49 53 61 69 73 77 77 72 65 58 51 42 35 32 32 32 31 37 38 39 37 33 29 25 24 26 26 27 27 27 30 34 38 41 49 57 61 63 65 61 55 46 43 40 39 40 42 43 43 39 38 36 34 33 34 35 36 37 40 43 44 44 43 44 45 49 51 54 55 53 48 43 39 37 42 51 63 74 78 76 72 61 50 39 33 31 31 36 43 46 47 47 46 42 36 31 28 24 25 27 31 34 38 41 43 43 43 42 40 38 36 35 34 34 32 30 27 25 25 25 25 29 32 38 42 45 44 43 41 40 40 40 42 44 47 49 51 52 50 46 41 37 35 35 36 38 40 43 46 47 46 45 43 41 38 34 30 28 27 27 27 27 27 27 27 28 29 30 31 38 39 41 42 41 39 37 35 32 33 35 38 43 48 53 55 58 56 52 48 43 39 36 34 33 34 35 35 34 32 30 28 25 24 24 25 27 31 35 37 41 43 47 52 57 60 63 64 60 58 55 51 46 39 31 25 23 23 23 23 25 28 31 32 32 34 36 39 39 38 37 35 33 31 28 24 22 20 19 19 19 19 19 19 19 19 19 19 17 17 16 16 15 14 13 13 13 14 14 14 15 15 15 15 16 16 17 17 16 15 14 14 14 14 15 15 14 13 12 12 11 11 11 10 10 10 9 9 7 7 7 6 6 5 5 5 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 10 10 10 11 11 12 12 12 12 12 12 13 13 14 14 14 15 15 15 16 16 17 17 17 18 18 18 19 19 20 20 20 20 20 21 22 24 26 28 30 31 31 31 30 30 30 30 30 31 31 32 33 34 38 43 47 58 62 70 77 81 81 79 78 71 68 64 59 56 55 55 55 61 71 83 92 101 105 101 93 88 82 77 76 76 80 91 102 114 128 145 160 172 177 172 163 150 141 127 116 113 119 129 136 145 149 154 158 157 151 144 140 140 144 150 154 163 181 206 225 247 250 254 255 255 255 255 255 251 250 248 244 240 238 238 239 241 234 225 213 201 190 184 182 178 178 171 157 143 131 115 101 96 96 100 111 127 144 156 162 167 162 152 139 122 104 87 77 69 64 61 63 64 65 69 75 82 90 97 100 99 93 78 65 54 51 54 70 93 111 117 117 111 102 88 77 71 68 66 65 69 69 70 70 71 73 76 78 79 79 79 77 76 76 79 82 90 92 94 90 79 65 55 50 49 61 76 89 98 100 91 80 65 55 47 47 51 53 55 58 57 56 57 59 62 61 57 54 52 46 43 43 44 44 48 54 58 66 73 74 74 74 69 63 56 50 42 35 32 32 33 35 45 49 52 51 44 36 30 27 25 26 27 28 30 33 39 43 47 55 64 68 71 73 68 62 55 51 46 44 44 44 44 43 39 38 37 37 37 38 39 40 42 43 45 45 43 43 44 45 52 55 59 61 60 54 47 43 37 40 48 60 70 75 72 68 60 49 38 35 34 34 37 42 45 44 43 40 35 31 26 24 23 25 28 33 38 42 46 47 47 45 43 41 38 36 34 33 34 32 30 27 25 25 25 25 30 33 38 42 45 44 42 41 39 39 40 41 43 45 46 46 46 43 39 36 35 35 35 36 39 40 42 44 44 43 41 40 37 35 31 27 24 23 23 24 25 27 30 33 36 39 41 42 45 45 44 42 40 37 34 33 32 33 35 38 43 48 52 55 58 56 54 50 46 42 39 38 33 34 35 35 35 34 32 32 29 28 28 29 31 35 39 41 44 46 50 54 58 62 64 65 62 59 54 49 43 36 29 23 22 22 22 23 26 29 32 34 34 35 36 37 36 34 32 30 30 28 25 21 19 17 17 17 17 17 17 17 17 17 17 17 17 17 16 16 15 14 13 13 13 13 13 13 14 14 14 15 15 15 15 15 15 14 13 13 13 13 13 13 13 12 11 11 11 11 10 10 10 9 9 9 7 7 7 6 6 5 5 5 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 10 10 10 11 11 12 12 12 12 12 12 13 13 14 14 14 15 15 15 16 16 17 17 17 18 18 18 19 19 20 20 20 21 21 21 22 23 25 27 28 30 30 30 30 30 30 30 30 33 33 34 35 37 41 48 52 63 69 78 86 90 90 88 86 77 73 66 59 55 53 54 55 64 75 88 100 110 116 112 106 98 92 86 83 82 85 98 110 126 140 159 176 192 201 199 193 177 169 158 149 147 152 161 167 186 191 197 201 202 197 192 187 180 182 183 185 192 208 229 245 255 255 255 255 254 254 255 255 255 255 255 252 248 244 240 238 234 227 218 210 202 197 198 203 207 210 203 186 167 149 125 104 93 91 92 101 118 136 150 157 162 158 148 134 116 96 80 71 58 55 56 62 65 67 72 77 84 89 93 95 95 90 77 64 53 49 50 63 83 101 111 114 116 107 93 81 72 67 64 63 69 71 73 74 74 76 79 81 82 83 83 82 81 80 82 84 86 86 84 80 68 54 47 47 53 68 87 102 110 109 97 85 66 56 47 49 53 55 56 58 55 53 52 54 58 59 55 52 49 44 40 41 42 44 50 57 63 69 73 71 67 66 62 57 50 47 41 35 30 30 34 37 51 57 64 65 57 46 38 33 26 28 29 31 34 38 44 49 55 63 71 75 77 78 74 68 62 57 52 47 45 44 42 41 38 38 38 39 41 42 44 45 45 46 46 43 41 40 41 43 50 54 60 64 63 57 49 44 37 38 43 54 66 71 69 64 60 49 40 39 39 39 40 43 43 41 38 34 30 26 23 22 23 25 30 36 41 46 49 51 48 46 42 39 36 34 34 34 34 33 30 28 26 25 26 26 31 33 37 40 42 41 40 39 38 39 40 41 41 41 41 41 40 38 36 35 37 38 38 38 39 39 39 38 37 36 34 34 32 30 27 24 23 23 23 24 27 30 35 41 46 48 49 49 48 46 43 39 36 33 32 32 33 33 34 37 41 47 52 55 59 59 57 54 50 45 41 38 32 32 32 33 33 34 35 35 33 33 34 35 38 41 44 46 48 49 52 55 58 59 61 61 59 55 50 45 40 34 27 23 22 22 22 23 25 28 30 32 33 34 34 33 32 29 27 26 26 24 21 18 16 15 15 16 16 16 16 16 16 16 16 16 17 16 16 15 14 13 13 12 12 12 12 13 13 13 14 14 13 14 14 14 14 13 12 11 11 12 12 12 12 11 10 9 10 10 10 10 9 9 9 8 7 7 7 6 6 5 5 5 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 10 10 10 11 11 12 12 12 12 12 12 13 13 14 14 14 15 15 15 16 16 17 17 17 18 18 18 19 19 20 20 20 21 21 21 21 22 24 25 26 28 28 28 29 30 30 31 31 34 35 36 37 39 44 51 57 67 73 83 92 96 96 93 90 82 77 68 60 55 53 54 55 67 78 92 104 116 124 122 116 108 102 96 92 89 92 104 118 136 149 168 187 205 218 221 217 208 203 196 192 192 197 204 209 230 232 235 238 238 237 236 234 226 225 223 222 226 235 247 255 255 255 255 255 253 253 255 255 255 255 255 255 252 246 239 235 228 220 212 206 201 200 208 219 233 239 235 217 196 173 143 117 99 93 90 96 111 129 143 150 154 150 141 127 109 90 75 67 52 51 55 63 68 70 74 80 84 86 88 88 89 86 75 63 52 49 49 56 72 90 103 109 113 105 93 82 74 69 66 65 70 73 75 75 74 74 76 78 81 83 84 83 80 78 77 77 77 74 73 70 61 51 50 56 67 83 103 116 120 114 98 83 64 53 46 48 55 58 59 60 56 53 51 52 56 57 54 50 46 40 37 39 42 46 54 62 66 71 72 65 59 56 53 49 42 43 42 35 28 27 33 40 55 65 76 79 71 58 48 42 31 33 35 38 41 47 53 58 63 70 77 79 81 81 77 71 66 61 54 48 45 42 39 37 36 37 38 41 43 46 48 49 47 47 45 41 37 36 37 38 45 51 59 64 63 57 49 43 37 36 39 49 61 68 66 62 60 50 43 44 47 47 46 48 42 39 35 31 27 24 22 22 23 26 31 38 44 48 51 53 49 45 40 36 33 32 33 34 35 34 31 29 27 26 27 27 32 33 35 37 38 38 37 37 38 39 40 41 41 39 37 36 38 36 36 38 42 44 44 43 38 37 34 32 29 28 27 27 27 26 23 22 22 23 25 27 33 37 44 51 55 55 54 52 46 43 39 34 32 31 32 33 34 33 33 35 39 46 52 57 63 63 62 59 54 47 40 35 30 29 29 29 31 33 36 38 37 38 40 42 44 47 49 50 51 52 53 54 55 55 55 55 53 49 44 39 35 31 26 22 22 22 21 21 23 25 27 28 29 30 30 29 28 26 25 24 23 21 19 17 15 15 16 16 16 16 16 16 16 16 16 16 16 15 15 14 13 12 12 11 11 11 12 12 12 13 13 13 13 13 13 13 13 12 11 10 11 11 11 11 11 10 9 8 10 10 10 9 9 9 8 8 7 7 7 6 6 5 5 5 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 10 10 10 11 11 12 12 12 12 12 12 13 13 14 14 14 15 15 15 16 16 17 17 17 18 18 18 19 19 20 20 20 21 21 21 21 21 22 23 24 26 27 27 28 29 30 31 32 36 36 37 38 41 46 54 59 69 76 86 94 99 99 95 92 85 79 70 61 55 53 54 56 68 79 94 107 120 128 128 123 119 114 108 103 99 101 114 128 141 154 172 191 211 227 233 230 238 236 233 232 234 239 245 249 254 254 253 253 253 255 255 255 255 255 253 250 249 251 254 255 254 255 255 255 254 253 254 255 254 254 255 255 252 245 236 230 225 215 207 203 199 200 212 226 247 255 255 239 218 194 161 132 107 99 92 94 106 123 136 142 146 143 135 121 103 86 72 65 52 52 56 65 71 74 78 83 81 83 83 82 84 83 73 61 52 49 48 53 66 82 96 105 102 96 87 77 71 67 66 66 73 75 77 76 72 70 71 72 74 76 78 76 72 68 65 64 66 64 63 64 58 53 59 69 82 98 117 126 126 114 94 76 61 51 44 48 55 59 61 62 59 55 51 52 56 56 53 48 44 39 36 39 44 49 59 68 68 72 70 62 54 50 47 44 37 41 42 35 26 25 32 41 59 71 84 89 81 68 56 50 37 39 42 45 49 54 61 66 68 75 80 81 82 83 79 73 68 62 55 48 43 40 36 34 35 36 38 42 45 48 50 52 47 46 43 39 34 32 33 35 41 48 56 62 62 56 47 41 38 35 37 46 58 65 64 60 59 51 45 48 53 53 51 52 42 39 34 29 25 23 22 22 24 27 32 39 45 49 52 54 49 45 39 33 30 31 33 35 36 34 32 29 28 27 27 28 33 33 34 35 36 36 35 35 39 40 41 42 41 38 35 34 38 37 37 41 47 50 49 47 38 35 31 27 24 23 23 23 24 23 21 21 22 24 27 29 40 45 52 58 61 60 57 54 44 40 35 31 29 30 33 35 35 33 32 34 38 45 53 57 67 67 66 63 56 47 38 32 28 27 26 26 29 33 37 40 40 41 44 46 49 51 52 52 53 54 54 54 53 52 51 51 48 45 40 35 32 29 25 22 22 21 20 20 21 22 24 25 26 26 26 27 26 25 24 24 22 20 18 17 16 16 17 17 17 17 17 17 17 17 17 17 15 15 14 13 12 12 11 11 11 11 11 12 12 12 13 13 12 12 13 13 12 12 11 10 10 10 11 11 10 10 9 8 10 10 10 9 9 8 8 8 7 7 7 6 6 5 5 5 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 10 10 11 11 11 12 12 12 11 11 12 12 12 13 13 13 14 14 15 15 15 16 16 16 15 15 16 17 18 18 19 19 20 20 20 20 20 20 20 20 22 23 24 24 25 27 31 34 32 34 38 41 44 48 52 56 67 71 79 90 98 101 97 93 87 79 68 60 57 57 57 56 68 78 93 108 119 127 131 134 126 117 114 116 115 113 124 140 149 161 179 197 212 227 239 247 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 253 254 255 254 253 253 249 253 255 254 249 242 233 225 214 209 204 199 193 195 212 232 251 253 253 251 241 216 176 144 119 105 94 95 105 117 129 138 147 145 137 122 104 88 77 73 59 58 59 63 69 75 78 79 78 78 77 75 74 72 71 71 57 58 60 63 69 78 88 95 99 96 90 82 73 67 65 65 77 79 81 80 76 72 68 67 65 67 68 67 62 59 60 61 63 62 60 56 55 61 74 84 101 118 131 130 123 111 88 65 52 48 45 49 57 64 66 65 60 58 57 56 55 53 49 45 43 37 32 34 44 57 66 71 79 74 67 58 45 34 32 36 38 42 44 38 29 27 35 43 58 70 85 90 83 70 58 52 40 42 44 49 55 61 66 70 72 75 79 82 82 79 75 72 62 57 50 43 37 33 32 32 28 31 37 42 47 49 51 51 46 43 39 34 31 30 29 29 34 43 54 61 60 52 43 37 32 38 45 50 58 65 64 60 59 55 53 53 57 58 57 54 47 41 33 26 22 21 21 20 23 27 33 40 45 49 51 52 47 43 37 33 31 33 37 40 41 40 38 33 28 25 25 26 29 32 35 35 33 32 35 39 38 41 44 45 43 41 39 39 40 44 50 57 61 61 56 52 47 39 29 24 23 23 23 22 22 22 21 21 23 26 30 32 40 45 52 57 58 55 50 46 33 31 29 29 31 34 36 36 35 34 33 35 39 47 54 59 63 63 63 59 52 43 34 28 21 21 22 25 28 32 36 38 42 43 45 47 49 51 53 54 52 51 49 47 45 43 41 40 35 34 33 31 28 25 22 20 18 18 18 19 20 21 22 23 24 23 23 22 21 21 20 20 19 18 16 14 14 14 15 16 15 15 16 17 17 17 16 16 13 13 13 12 12 11 11 11 13 12 12 11 11 12 12 13 12 12 12 11 11 10 10 10 11 11 11 10 10 9 9 9 10 10 10 9 9 8 8 8 8 8 8 7 7 6 6 6 6 6 6 5 5 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 9 10 10 10 11 11 11 12 11 11 11 11 12 12 12 13 13 13 13 14 14 15 15 15 14 14 15 16 17 17 18 18 20 20 20 20 20 20 20 20 20 22 23 23 24 26 30 33 32 35 38 41 43 47 51 55 64 67 75 85 94 97 94 91 90 83 73 67 64 64 63 63 73 83 97 111 122 130 137 140 137 129 127 129 127 124 133 148 156 165 181 197 212 227 240 248 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 251 243 234 225 218 206 202 198 194 187 188 204 221 243 249 255 254 244 219 180 149 125 111 99 99 108 119 130 139 143 141 134 122 106 92 82 78 66 65 65 67 72 76 78 78 72 70 68 66 66 68 69 71 65 66 67 69 73 80 88 94 100 98 93 86 78 74 72 73 77 79 81 79 75 69 65 64 60 62 63 61 57 54 55 56 54 56 58 58 62 71 84 95 108 122 130 126 116 103 80 59 46 43 43 49 58 66 68 68 66 64 62 61 59 55 51 47 41 37 34 39 51 65 75 81 81 74 64 53 40 29 29 34 40 46 49 45 36 31 34 40 52 64 79 85 80 69 58 53 41 43 45 49 54 60 64 67 72 74 77 79 78 74 70 67 57 53 47 40 35 32 31 31 29 32 37 43 47 49 50 50 45 42 38 33 30 29 29 30 35 42 52 58 56 49 42 37 32 40 48 54 62 68 67 61 57 54 52 54 58 60 59 57 49 42 33 26 22 21 21 21 23 27 32 39 44 49 51 52 48 44 39 35 33 36 39 42 42 41 38 33 27 25 25 26 30 33 36 36 34 34 37 41 41 44 47 48 46 44 42 42 47 51 58 66 70 70 64 60 50 43 33 28 27 28 27 26 28 27 25 25 26 28 30 32 40 44 49 52 52 48 42 37 28 26 25 27 31 35 37 37 34 33 33 34 39 46 53 58 63 62 60 55 47 38 30 26 19 20 22 25 28 33 37 39 42 44 46 48 49 50 51 51 47 46 44 42 39 37 35 34 31 30 29 27 25 22 20 19 16 16 16 17 18 19 21 22 23 23 23 22 21 21 21 20 21 20 18 16 15 15 16 16 16 16 17 17 17 16 15 15 13 13 12 12 12 11 11 11 12 12 12 12 12 12 12 12 12 12 12 11 11 11 10 10 11 11 11 10 10 9 9 9 10 10 9 9 9 8 8 8 8 8 7 7 7 6 6 6 6 6 6 5 5 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 8 9 9 9 10 10 10 11 10 10 10 11 11 12 12 12 11 12 12 12 13 13 13 14 13 13 14 14 15 16 17 17 20 20 19 19 19 19 19 19 19 20 21 22 22 24 28 31 33 35 39 41 43 46 49 52 58 61 68 77 85 89 89 87 90 85 79 74 72 72 71 71 80 87 99 111 123 133 141 146 149 144 143 146 144 141 148 160 167 174 185 199 213 228 242 250 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 253 255 255 255 255 255 255 255 255 255 248 239 228 217 208 203 194 193 191 186 180 180 191 204 224 235 245 247 237 213 178 151 130 116 104 104 111 121 131 138 137 136 131 122 109 97 88 84 74 73 71 71 73 75 75 74 64 61 57 55 57 63 69 74 82 83 84 84 86 90 97 102 106 104 100 94 87 83 81 82 79 81 82 79 73 67 62 60 56 57 56 54 51 49 49 50 49 53 58 63 70 80 92 102 112 121 124 115 102 88 67 49 39 39 42 50 61 69 73 73 74 71 68 65 62 57 51 47 39 36 36 44 58 74 85 90 85 75 62 48 33 24 26 34 45 52 59 56 46 37 35 36 45 56 70 77 74 66 57 52 42 43 45 48 52 56 59 61 67 68 71 72 70 66 62 59 50 47 43 37 33 31 31 31 31 34 39 44 47 48 48 47 44 41 36 31 28 28 30 31 36 42 50 54 52 47 42 39 37 45 54 61 68 72 69 62 54 52 51 55 60 64 63 61 52 44 34 26 22 21 21 22 23 26 31 37 43 47 51 52 49 45 41 37 37 39 43 46 44 42 38 32 27 24 25 27 32 36 39 39 37 37 40 43 46 49 53 54 51 49 47 46 53 58 67 76 81 79 74 68 57 49 40 35 35 36 35 34 36 34 32 30 29 29 31 32 37 40 43 44 42 37 30 26 20 20 21 25 31 36 39 39 35 34 34 35 40 46 53 57 63 60 55 48 40 32 25 21 18 19 21 25 29 33 37 39 42 44 46 48 49 48 47 45 39 38 37 34 32 30 28 27 26 25 25 24 22 20 18 17 14 15 15 16 17 19 21 22 24 24 23 23 23 22 22 22 24 22 20 18 16 16 16 16 17 17 17 17 16 15 14 13 12 12 12 12 11 11 10 10 11 12 13 14 14 13 12 11 12 12 12 12 11 11 11 10 11 11 11 10 10 9 9 9 10 9 9 9 8 8 8 8 8 7 7 7 6 6 6 6 6 6 6 5 5 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 8 8 8 9 9 9 10 10 10 10 10 10 11 11 12 12 10 11 11 11 12 12 12 13 12 13 13 14 15 15 16 16 20 20 20 20 19 19 19 19 18 19 20 21 21 23 27 31 33 36 39 41 42 44 46 48 51 54 60 67 74 79 81 82 86 84 82 80 80 80 79 79 85 91 101 111 122 134 144 151 157 156 159 164 163 161 165 174 180 184 191 202 216 232 246 254 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 253 255 255 254 252 253 254 254 251 242 231 219 205 192 185 183 181 183 183 180 174 172 178 186 197 209 221 223 214 195 168 148 131 117 106 107 114 122 130 136 133 132 127 119 109 99 91 86 80 77 74 73 72 71 69 67 59 55 51 49 53 63 73 80 96 97 98 98 99 103 107 111 117 115 111 104 96 90 88 87 83 84 84 80 73 65 60 57 53 53 52 50 48 47 47 47 51 55 61 68 74 82 91 98 106 110 107 96 83 71 55 41 35 38 44 54 65 74 79 80 80 77 73 68 64 57 51 46 39 37 39 49 64 79 89 94 89 77 61 45 30 23 27 36 51 60 68 66 56 44 36 34 41 50 61 68 66 60 53 49 41 42 43 45 47 49 51 52 55 57 60 62 61 59 55 53 48 45 41 38 35 33 33 33 33 36 41 45 48 48 46 45 42 38 33 29 27 29 31 33 40 44 50 52 51 48 45 44 45 54 63 70 75 75 68 59 51 50 51 55 62 66 66 64 54 46 35 27 22 22 22 23 23 25 29 35 40 46 50 52 50 47 43 40 40 43 46 49 45 43 38 31 26 24 26 29 36 39 42 42 40 40 42 46 51 54 58 59 57 53 51 50 55 61 71 81 87 86 80 74 64 57 49 45 45 46 45 44 43 41 37 33 31 30 30 31 31 33 35 36 33 28 22 18 16 17 20 26 33 38 41 42 36 36 36 38 42 48 54 58 61 57 51 42 33 26 21 18 17 18 21 25 29 33 36 38 40 42 45 46 46 44 41 39 33 32 31 29 26 24 23 22 22 23 22 22 21 19 18 17 16 16 17 18 20 22 24 25 27 26 26 26 25 25 25 25 26 24 22 19 17 16 16 16 18 18 18 17 16 15 13 13 12 12 12 12 11 11 11 10 10 12 14 15 15 14 12 10 13 13 12 12 12 11 11 11 11 11 11 10 10 9 9 9 9 9 9 8 8 8 7 7 7 7 7 6 6 6 5 5 6 6 6 5 5 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 8 8 8 9 9 9 10 10 10 10 10 11 11 12 12 12 11 11 11 12 12 12 13 13 13 13 14 15 16 16 17 17 22 21 21 21 20 20 19 19 18 19 21 21 22 24 28 31 34 37 40 42 42 42 43 45 45 47 52 56 62 67 72 75 81 83 86 88 89 89 90 90 94 98 106 115 125 137 148 156 164 168 175 182 183 182 185 190 192 194 198 206 220 236 250 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 254 255 255 251 250 254 255 253 237 224 209 197 182 169 163 165 166 172 176 174 169 167 169 171 172 181 190 190 184 173 157 144 128 116 108 109 116 122 127 131 131 127 121 113 104 95 87 83 82 79 76 73 72 69 65 62 57 53 49 48 54 65 78 86 99 102 104 106 107 110 114 118 126 124 119 111 102 94 90 89 87 87 87 82 74 65 59 56 53 52 50 49 48 49 49 49 53 56 62 68 74 80 85 89 89 89 85 75 65 56 47 39 39 42 49 59 69 78 84 86 85 82 77 73 67 60 53 48 45 44 47 56 69 82 90 93 89 77 60 44 31 25 31 41 56 64 72 71 61 48 38 34 39 46 54 59 58 53 47 43 39 39 40 40 41 41 41 41 41 44 48 51 53 54 53 52 49 48 44 41 38 37 36 35 36 39 43 47 48 47 44 42 38 35 32 29 29 31 34 36 44 48 52 54 53 52 51 51 57 65 73 78 79 76 66 55 49 49 50 56 63 67 67 65 54 47 36 28 24 24 24 24 23 25 28 32 38 44 49 52 50 48 45 42 42 44 47 49 46 43 37 30 25 25 28 32 40 43 46 45 42 41 43 46 54 57 61 63 60 56 53 51 56 63 73 84 90 90 84 79 70 64 57 54 54 55 54 52 47 44 40 35 32 30 30 30 27 28 30 30 29 25 21 19 18 20 24 30 37 41 43 43 38 38 38 40 44 50 55 58 59 55 47 38 30 24 20 18 18 20 22 25 29 32 34 35 37 38 41 42 41 38 34 32 29 29 27 26 24 23 22 21 22 23 23 22 21 20 19 18 19 20 21 22 25 27 29 31 31 30 30 29 28 27 27 27 25 24 21 18 17 16 16 16 18 18 18 17 16 15 13 13 13 13 13 12 12 12 11 11 11 12 14 16 16 14 12 11 13 13 13 12 12 12 11 11 11 11 11 10 10 9 9 9 9 9 8 8 8 7 7 7 7 7 6 6 6 5 5 5 6 6 6 5 5 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 8 9 9 9 10 10 10 11 11 11 12 12 12 13 13 13 13 13 13 13 14 14 15 15 15 15 16 17 18 18 19 19 24 23 23 22 21 21 20 20 20 21 22 23 23 26 29 33 35 38 41 42 41 40 40 41 40 42 44 47 50 56 63 67 77 83 90 95 98 100 101 102 104 108 114 121 130 142 154 161 171 179 190 198 201 200 201 203 200 199 201 209 223 239 252 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 254 255 255 252 253 255 255 246 221 205 189 177 162 148 144 148 149 158 166 167 164 162 160 157 153 159 162 161 159 156 148 140 128 118 112 115 120 123 123 125 125 119 110 102 94 86 79 75 79 77 74 72 70 66 62 59 54 51 47 47 54 66 78 87 100 103 107 110 113 115 119 122 125 124 119 112 103 96 91 90 88 89 88 83 74 65 59 56 51 49 47 47 49 50 51 51 52 54 59 64 70 74 77 78 69 67 63 58 53 49 45 43 47 50 55 63 72 79 85 89 88 85 80 76 70 64 56 51 51 51 53 61 73 82 87 88 82 71 57 43 31 27 34 44 58 64 70 68 60 48 39 35 38 42 47 51 51 47 42 39 38 38 38 37 36 34 32 31 30 33 39 44 49 52 53 54 54 52 50 46 43 40 38 38 39 41 46 49 49 46 42 39 33 32 31 31 32 34 37 39 46 50 54 57 57 57 58 59 66 74 80 83 82 77 65 53 49 48 50 56 63 66 65 63 52 46 37 31 27 26 26 25 23 24 26 30 36 42 49 52 50 48 45 43 42 44 46 47 45 42 36 29 25 26 31 35 44 47 49 47 43 41 43 46 54 58 63 64 61 57 53 51 56 62 72 83 90 91 86 81 73 67 61 58 59 60 59 57 49 46 41 37 33 31 31 31 28 29 31 32 31 29 27 26 27 28 32 37 42 45 44 43 38 38 39 41 45 50 54 57 56 52 45 37 30 25 22 21 21 22 24 26 28 29 30 30 33 34 35 35 34 31 28 26 26 26 26 25 25 24 24 24 24 24 24 23 22 21 19 19 21 21 23 25 27 30 33 34 34 34 32 31 29 28 27 26 23 21 19 16 15 15 15 15 17 17 17 17 16 15 14 13 15 15 14 14 14 13 13 13 12 13 14 15 15 14 13 12 14 13 13 13 12 12 12 12 11 11 11 10 10 9 9 9 8 8 8 8 7 7 7 6 6 6 6 6 5 5 5 4 6 6 6 5 5 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 9 10 10 10 11 11 11 12 12 12 13 13 14 14 14 14 15 15 15 16 16 16 17 17 18 18 19 19 20 21 21 22 26 25 25 24 23 22 21 21 22 23 25 25 25 28 32 35 36 38 41 42 41 39 38 39 37 38 39 39 41 47 55 61 71 79 90 99 103 106 108 109 110 113 119 125 134 144 155 162 175 186 200 208 210 210 208 207 202 200 201 209 223 239 251 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 253 255 255 253 254 255 243 225 205 188 170 158 144 128 124 130 132 144 155 158 158 156 151 145 141 142 142 140 142 145 142 136 133 125 120 123 126 124 121 119 116 108 97 88 81 76 71 67 70 68 66 65 63 60 56 53 47 45 44 45 52 62 73 81 94 97 102 105 108 110 113 115 114 114 112 108 102 96 94 93 88 88 87 82 73 64 58 54 48 45 42 43 47 50 51 51 53 54 56 59 63 65 66 65 54 52 49 48 47 47 49 51 54 57 61 65 71 78 84 88 85 82 78 73 69 62 55 51 52 51 54 61 70 78 80 80 71 62 50 40 30 27 33 43 57 60 63 60 53 44 38 35 36 38 42 45 46 44 41 38 38 38 37 36 33 30 27 25 26 29 35 42 48 53 56 57 59 57 54 50 46 42 39 38 40 43 47 50 49 45 40 36 28 29 30 33 35 38 41 42 46 50 56 59 61 61 63 64 71 78 84 85 84 78 66 54 49 49 50 56 62 64 62 59 49 45 38 33 30 29 27 26 23 23 25 28 34 41 48 52 50 48 45 42 41 42 44 45 44 41 34 28 25 27 33 38 48 50 51 48 43 41 42 44 53 58 62 64 61 56 51 49 52 57 66 77 84 86 83 79 71 66 60 58 59 60 59 57 50 47 43 39 35 34 34 34 35 36 37 38 37 37 35 34 37 38 41 45 48 48 45 42 36 37 38 40 44 48 52 55 53 50 44 38 32 28 26 25 25 26 27 27 27 27 26 25 29 29 29 28 27 25 24 22 24 24 24 25 25 26 26 26 25 25 25 24 23 21 19 18 19 20 21 24 27 30 33 34 36 35 33 31 28 26 24 23 19 18 16 14 13 13 14 14 16 16 17 17 17 16 15 15 16 16 16 15 15 15 14 14 14 14 14 14 14 14 14 14 14 14 13 13 13 12 12 12 11 11 11 10 10 9 9 9 8 8 8 7 7 7 6 6 6 6 6 5 5 5 4 4 6 6 6 5 5 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 10 10 11 11 11 12 12 12 13 13 14 14 14 15 15 15 16 16 17 17 18 18 18 18 19 20 20 21 22 23 23 23 27 26 26 25 24 23 22 22 24 25 26 26 27 29 33 36 36 39 42 42 40 38 37 37 36 36 36 35 36 42 51 58 65 74 87 98 103 106 109 111 111 114 119 125 133 143 153 160 176 188 203 211 212 211 208 205 201 199 200 209 223 239 250 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 253 255 255 254 253 249 227 203 195 176 158 146 131 114 110 117 120 135 148 152 153 152 145 137 133 133 131 130 134 139 138 132 139 131 127 129 131 126 119 116 109 100 88 79 73 69 65 62 61 59 58 57 56 54 49 46 42 41 40 42 49 58 68 74 80 84 89 92 94 96 98 100 103 105 105 103 100 97 96 96 86 87 86 81 72 63 56 53 45 41 39 40 45 49 51 50 57 56 56 56 57 57 56 54 48 45 43 44 46 48 53 57 59 61 63 66 70 76 82 87 79 76 72 68 64 58 52 47 48 47 50 57 66 72 73 72 62 54 45 37 29 25 32 42 55 56 57 54 47 40 36 34 34 35 38 42 44 44 41 38 39 39 38 36 33 28 25 23 25 29 35 42 49 54 57 59 62 60 56 52 47 43 39 37 41 44 48 50 49 45 39 35 25 27 30 34 38 41 43 43 46 50 56 60 62 63 65 66 73 79 85 86 85 80 68 56 50 49 51 56 61 63 60 57 47 44 38 35 32 30 28 26 23 23 24 27 33 40 48 52 50 48 45 42 41 41 42 43 44 40 34 27 25 28 35 40 50 52 52 49 43 40 41 43 53 57 62 63 60 55 50 48 46 51 60 70 78 80 78 75 69 64 59 57 58 59 58 56 50 48 44 40 37 36 36 37 42 42 43 43 43 42 41 40 45 45 47 50 52 50 45 41 35 35 36 38 42 46 50 53 51 49 44 39 34 31 29 28 27 28 28 28 27 25 23 22 26 26 25 24 23 22 21 21 22 23 24 25 26 27 28 28 26 25 25 24 22 20 18 17 17 18 19 22 25 28 31 33 36 34 32 30 26 24 22 20 17 16 14 12 12 12 13 14 15 15 16 17 17 17 16 16 17 17 17 16 16 16 15 15 15 14 14 13 13 14 14 15 14 14 14 13 13 12 12 12 11 11 11 10 10 9 9 9 8 8 8 7 7 6 6 6 6 6 6 5 5 4 4 4 6 6 6 5 5 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 9 10 12 12 11 12 13 15 14 15 17 17 16 17 18 20 18 19 20 20 21 20 20 19 20 20 21 22 22 23 23 23 26 27 27 26 24 23 23 24 22 23 25 26 27 29 34 37 44 44 45 45 45 43 41 40 37 35 34 33 35 40 45 48 66 73 85 95 102 107 110 112 112 117 123 126 130 137 148 157 171 182 193 199 203 207 206 203 202 200 199 202 213 229 245 255 255 255 254 253 253 253 254 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 254 255 255 255 242 223 203 191 176 167 154 138 124 114 109 106 110 117 127 138 145 145 139 134 129 127 126 127 132 137 140 142 140 144 145 140 133 126 116 107 101 94 84 74 67 62 59 56 50 48 48 49 50 50 48 46 40 40 40 41 45 51 56 60 63 69 74 76 76 77 83 88 87 89 91 91 91 92 93 95 89 85 81 77 72 64 53 45 42 40 40 42 47 52 56 57 55 56 58 58 57 54 51 50 46 43 42 45 52 58 61 62 65 63 61 60 62 65 70 73 71 69 65 60 55 51 48 47 46 48 50 53 57 60 63 64 59 52 42 33 29 31 35 39 45 45 45 42 39 36 36 36 33 35 37 38 37 36 37 38 38 39 40 38 33 29 27 26 30 33 38 44 51 57 62 64 66 63 58 51 43 38 35 35 42 45 50 53 50 44 35 30 27 27 30 35 40 44 45 45 51 52 53 56 58 60 62 63 70 74 80 84 82 75 66 60 52 54 57 58 58 56 53 50 41 41 41 40 38 35 32 30 26 26 27 29 34 40 46 50 47 45 41 37 35 35 37 38 36 35 33 30 29 31 37 41 49 51 52 48 42 40 43 47 53 57 61 64 62 56 49 44 42 49 56 62 70 77 77 73 62 58 52 48 47 47 47 46 43 43 42 42 42 41 41 40 48 49 51 51 50 49 49 50 53 50 48 51 54 52 45 39 39 32 30 35 40 42 44 46 47 45 40 36 33 31 31 32 34 32 30 27 24 22 21 20 20 21 23 24 24 23 21 19 24 25 26 27 28 28 28 28 28 26 24 21 19 17 16 16 18 18 19 19 21 23 25 26 27 27 27 26 24 21 18 17 13 12 12 12 12 13 14 15 16 16 17 18 18 17 16 16 20 20 19 18 16 15 14 14 13 13 13 13 13 13 13 13 14 14 14 13 13 12 12 12 11 11 10 10 10 9 9 9 9 8 7 6 6 6 6 7 6 6 6 5 5 4 4 4 6 5 4 3 3 3 3 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 9 11 13 13 12 12 14 16 14 16 18 18 17 18 19 21 20 21 21 22 22 22 21 21 22 22 22 22 23 23 23 23 27 28 28 27 25 23 24 25 23 25 27 28 29 31 35 39 44 44 46 46 46 45 43 42 42 40 38 37 38 41 45 48 61 68 79 89 97 102 105 108 109 113 118 121 124 131 141 149 158 169 181 188 193 198 198 195 192 192 195 201 213 229 244 253 255 255 255 255 255 254 252 251 254 254 254 254 254 254 255 255 255 254 253 254 255 255 255 253 255 251 242 233 221 204 184 170 162 154 141 129 120 112 106 102 107 112 120 129 134 134 129 125 123 123 124 127 131 137 143 147 148 152 153 147 139 131 120 110 96 89 79 69 62 57 54 51 46 44 43 44 45 46 44 43 37 36 35 36 39 44 49 53 54 60 66 68 68 70 74 79 78 80 84 87 90 93 96 98 93 88 83 78 73 65 55 47 40 38 38 41 46 53 57 58 57 58 58 57 55 53 51 49 47 45 45 48 55 61 64 65 63 61 58 57 57 60 64 66 64 62 58 53 48 45 42 41 40 41 43 46 49 52 55 56 54 49 41 34 30 32 36 39 39 39 38 36 33 31 32 33 33 35 36 35 34 33 34 36 36 37 39 37 35 33 32 32 36 37 41 45 50 56 60 62 62 61 57 50 41 36 35 36 44 48 54 58 55 48 38 32 27 29 32 38 44 47 47 45 48 49 50 52 55 57 58 59 64 69 75 79 78 72 64 59 53 54 56 56 54 52 48 46 39 39 39 38 37 34 32 30 27 27 29 33 37 42 47 50 46 43 38 33 31 32 34 35 36 35 33 30 29 32 37 41 47 50 51 48 44 43 47 52 58 60 63 64 61 54 47 42 41 48 54 60 68 74 74 70 57 53 46 42 40 40 40 40 39 40 42 44 46 47 47 48 52 54 56 56 55 53 52 51 51 48 48 51 56 56 49 43 40 33 28 31 36 38 40 43 45 43 40 37 34 33 32 32 34 32 29 26 24 21 20 19 20 21 22 24 24 24 23 22 26 27 29 30 30 29 28 27 26 25 23 21 19 18 17 17 17 17 17 17 18 20 21 22 24 24 24 24 22 19 17 15 12 12 11 11 12 13 14 15 18 19 20 20 20 20 19 18 20 20 19 18 17 16 15 14 13 13 13 13 13 13 13 13 14 14 14 13 13 12 12 12 11 11 11 10 10 10 9 9 9 8 7 7 6 6 7 7 6 6 6 5 5 4 4 4 6 5 4 3 3 3 3 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 11 12 14 14 14 14 15 17 16 18 19 20 19 19 21 23 23 23 24 24 24 24 23 22 24 24 24 24 23 23 23 23 28 29 29 28 26 24 25 26 26 28 30 31 32 34 37 40 45 46 48 49 49 49 47 47 50 47 44 42 42 43 46 48 58 64 74 84 91 96 100 103 103 106 110 113 115 121 129 135 143 154 166 173 179 185 186 183 182 185 191 200 212 224 235 241 248 251 255 255 255 255 254 252 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 253 255 242 224 210 199 186 168 155 147 139 129 122 118 114 106 100 104 106 109 114 117 116 113 109 111 115 120 124 128 135 144 151 154 158 159 152 143 133 120 109 90 84 74 65 59 54 50 48 45 43 41 40 42 44 44 44 38 36 33 32 34 38 43 47 46 51 57 60 61 62 65 69 66 70 76 84 92 97 101 103 98 92 85 79 74 67 58 51 41 39 39 42 49 56 61 63 63 62 61 59 56 54 52 51 48 47 46 49 55 61 64 66 58 56 53 51 51 53 56 58 57 55 51 47 42 39 36 35 35 35 36 38 41 45 49 51 50 46 41 36 34 34 36 38 35 35 33 31 28 28 30 33 34 34 34 31 29 28 30 32 33 35 37 38 37 38 40 42 44 44 44 45 47 50 53 55 54 55 54 46 37 32 33 37 44 49 57 61 59 50 38 31 28 30 36 43 49 51 49 46 43 44 45 47 49 50 52 52 56 60 67 71 71 67 61 57 54 54 53 52 49 45 42 40 38 37 37 36 35 33 31 30 28 30 33 38 42 46 49 50 45 41 34 29 26 27 29 32 36 35 34 31 30 32 36 40 45 47 50 49 48 50 55 60 66 67 67 64 59 52 44 40 40 46 52 57 64 70 70 65 53 48 40 34 32 33 33 33 34 37 41 46 51 54 56 56 58 59 62 63 61 58 54 51 46 45 46 52 59 60 55 49 43 33 26 26 30 32 35 38 41 41 40 38 36 35 34 33 33 32 29 26 23 21 19 19 21 21 22 23 25 26 26 27 31 32 33 33 32 30 27 25 23 22 21 19 19 19 19 19 18 18 17 16 16 16 17 17 21 21 22 21 20 17 15 14 11 11 11 12 13 14 16 16 21 21 22 23 23 22 21 21 21 20 19 18 17 16 15 15 13 13 13 13 13 13 13 13 14 14 14 14 13 13 13 13 12 12 11 11 11 10 10 10 9 9 8 7 6 6 7 7 6 6 6 5 5 4 4 4 6 5 4 3 3 3 3 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 12 13 15 15 15 15 16 18 17 19 21 21 20 21 22 24 25 25 26 26 26 25 24 24 26 26 25 24 24 23 23 23 27 29 29 28 26 25 26 27 29 31 33 34 35 37 39 42 48 50 52 54 54 54 54 53 57 54 51 48 46 46 47 48 57 63 71 79 85 91 95 98 96 99 102 104 107 111 118 123 130 141 152 159 165 171 173 171 177 182 189 198 207 215 220 223 231 235 241 247 252 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 252 249 238 225 207 193 182 172 159 150 140 132 124 121 122 119 111 104 104 103 101 101 101 99 95 93 96 103 111 117 122 130 142 151 153 157 157 149 139 128 114 102 86 80 72 65 59 55 52 49 49 46 43 43 45 48 49 49 44 41 36 33 33 37 42 46 45 50 56 60 61 61 63 64 62 66 74 85 96 104 108 109 100 94 85 78 73 67 61 55 46 44 43 46 53 60 66 68 70 68 65 62 58 56 54 53 48 47 46 47 50 54 57 59 51 50 47 46 46 48 51 53 53 51 48 44 40 36 34 33 31 31 31 33 37 43 47 51 50 48 44 41 39 37 37 37 36 36 34 31 28 29 33 36 35 34 32 28 24 23 25 27 30 32 35 38 40 42 46 49 50 48 45 43 42 41 42 43 44 47 47 41 32 28 31 36 41 47 55 60 57 47 35 27 28 32 39 47 53 53 49 45 38 38 39 41 42 43 45 45 48 52 58 63 65 63 58 55 52 51 50 48 45 41 38 36 38 37 36 35 33 31 29 28 28 31 36 42 46 49 49 49 45 40 32 25 22 23 26 29 35 35 34 32 31 32 35 37 42 45 49 51 54 58 65 69 75 74 70 65 58 50 43 39 40 46 51 55 61 66 65 60 51 45 36 30 28 28 28 29 30 34 41 48 54 58 60 61 60 61 64 65 64 60 53 48 41 41 44 52 61 63 59 53 45 34 24 22 24 26 30 35 39 39 39 38 37 36 34 33 32 30 28 25 22 20 19 19 22 22 23 24 26 29 31 32 35 36 36 36 34 30 26 24 20 19 19 19 19 20 21 21 22 21 20 18 17 16 16 16 19 20 21 21 19 18 15 14 13 13 13 14 15 16 18 19 21 22 23 23 23 23 22 21 21 20 19 18 17 16 15 14 12 12 12 12 12 12 12 12 14 14 14 14 14 14 14 13 13 12 12 12 11 11 11 11 10 9 8 7 7 7 7 8 6 6 6 5 5 4 4 4 6 5 4 3 3 3 3 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 12 14 16 16 15 15 17 19 18 20 22 22 21 21 23 25 26 26 27 27 26 25 24 23 26 26 25 24 24 23 23 23 27 28 29 29 28 27 28 30 32 34 37 39 39 40 42 44 53 55 57 59 60 60 60 59 61 59 56 52 50 49 49 49 55 60 66 73 78 83 88 91 91 93 95 98 102 106 111 114 121 130 139 144 151 158 162 162 174 179 187 196 203 207 209 209 214 216 219 225 231 238 244 247 247 248 250 251 252 252 252 251 248 246 244 243 241 238 234 231 212 205 194 181 169 159 151 146 137 130 124 124 126 126 118 111 111 107 100 95 90 86 82 79 82 89 99 107 113 122 134 143 146 150 149 141 130 119 104 93 80 75 69 64 61 58 55 53 53 51 48 48 51 54 56 56 51 47 40 35 35 38 43 47 53 57 62 66 68 67 66 66 63 67 77 89 102 110 113 113 101 93 83 76 72 69 65 61 52 50 48 49 55 61 67 69 72 70 66 62 59 56 54 53 47 46 44 43 42 44 46 48 45 44 43 43 44 47 49 51 50 48 45 41 38 35 33 32 28 28 27 29 34 40 46 50 51 50 49 46 43 41 38 37 39 38 36 33 30 30 33 37 35 34 31 26 22 21 22 24 27 30 35 38 41 45 49 52 51 49 45 40 36 33 31 31 36 38 39 34 29 26 30 34 41 46 53 57 54 45 33 26 29 33 41 49 54 53 47 42 33 34 35 36 37 37 38 39 42 46 52 56 58 57 54 52 48 48 49 48 46 43 40 38 42 41 38 35 32 29 28 27 27 31 37 43 47 49 48 48 44 39 31 24 21 22 25 28 33 33 34 32 31 31 32 34 39 42 47 52 58 66 73 77 82 78 72 64 55 47 42 39 40 46 50 53 58 62 60 54 46 41 33 27 25 25 24 24 28 33 41 49 55 59 60 60 59 60 62 64 63 58 50 43 37 38 43 52 62 66 62 56 46 34 23 20 22 24 29 34 38 38 38 37 36 34 32 31 29 28 26 24 22 20 20 20 24 25 26 27 30 33 35 37 38 38 38 36 33 29 25 22 18 18 18 19 20 21 22 23 27 26 24 22 20 19 18 18 19 20 21 21 21 19 17 16 16 16 16 16 17 18 20 20 20 20 21 21 21 21 20 20 20 19 18 17 16 15 14 14 12 12 12 12 12 12 12 12 14 14 14 14 14 14 14 15 13 13 13 13 12 12 12 11 10 9 8 8 7 7 8 8 6 6 6 5 5 4 4 4 6 5 4 3 3 3 3 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 12 14 15 15 15 15 17 18 18 20 22 22 21 21 23 25 26 26 26 26 25 24 23 22 24 24 24 24 23 23 23 23 27 29 31 32 31 32 33 35 37 40 43 45 45 45 47 49 57 59 61 63 64 64 63 62 62 60 57 54 52 51 50 50 53 56 61 65 69 73 78 82 87 89 91 96 100 105 110 112 116 123 130 134 141 151 159 160 175 179 187 195 201 203 204 204 202 201 201 203 207 214 221 225 230 231 235 238 240 242 242 242 232 228 223 219 215 211 206 202 197 194 188 179 168 157 150 146 136 131 127 128 131 131 127 122 124 117 106 96 88 80 74 70 72 79 88 97 105 114 125 132 137 139 137 129 118 108 96 85 73 69 65 63 63 62 61 59 58 56 55 56 59 62 63 63 57 51 43 37 36 39 45 49 61 64 69 73 74 72 69 66 65 69 79 93 107 115 116 114 100 92 81 74 72 72 71 70 61 57 53 53 56 61 65 67 70 69 66 63 59 55 52 51 48 47 45 42 39 38 40 42 43 42 42 43 45 47 50 51 48 46 44 40 37 35 33 33 28 26 25 25 29 35 42 46 51 51 50 49 46 44 41 40 42 41 39 35 31 30 31 33 34 34 32 27 23 21 21 22 24 28 34 39 42 44 47 49 47 46 43 39 35 31 28 27 32 32 31 30 28 28 31 33 43 46 50 52 49 41 32 27 29 33 40 48 51 49 43 38 31 31 32 32 33 33 34 34 38 41 46 49 51 50 48 46 45 47 50 53 53 52 50 48 49 46 42 37 32 28 26 24 26 30 36 42 45 47 46 45 41 36 30 24 21 22 25 27 30 32 33 32 30 29 30 31 35 37 43 50 59 69 77 81 83 78 69 59 50 43 39 37 39 44 48 50 53 56 53 47 41 36 30 26 24 23 22 21 26 32 41 50 56 60 60 60 59 58 59 61 62 57 48 41 37 38 44 54 65 68 64 59 47 35 24 21 23 26 31 36 40 39 37 35 32 30 29 28 26 25 24 22 22 21 21 21 27 28 30 32 35 37 39 40 40 39 37 34 30 27 24 22 19 19 19 20 21 23 24 25 29 28 26 23 21 20 19 19 19 20 21 22 22 21 19 18 18 17 17 17 17 18 19 20 17 18 18 19 19 18 18 17 18 18 17 16 15 14 13 12 11 11 11 11 11 11 11 11 14 14 14 14 15 15 15 15 14 14 14 13 13 13 12 12 10 10 9 8 8 8 8 8 6 6 6 5 5 4 4 4 6 5 4 3 3 3 3 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 11 13 15 15 14 14 16 18 18 20 21 22 21 21 23 25 24 25 25 24 23 22 21 20 22 22 22 22 23 23 23 23 29 32 34 36 36 38 40 43 44 47 50 52 52 52 53 54 59 61 62 64 65 64 63 63 61 59 57 55 53 52 52 52 54 56 59 62 64 68 73 76 85 87 90 96 102 108 112 114 115 122 127 131 140 154 165 170 183 187 192 196 200 201 201 200 196 194 192 191 194 198 204 208 212 215 220 225 229 232 233 233 222 216 208 200 194 189 184 181 187 184 179 175 171 164 155 149 136 134 133 134 136 139 139 138 137 129 116 102 90 80 72 67 68 72 80 89 99 109 117 121 125 127 124 115 105 97 86 77 69 67 66 66 68 69 69 69 66 65 65 67 71 73 73 73 62 56 47 40 38 42 49 53 64 67 71 75 76 72 67 62 63 68 78 93 108 116 117 114 100 91 80 73 73 76 78 78 74 69 63 59 60 63 66 68 71 70 69 66 63 59 55 52 51 51 49 45 41 40 42 45 45 45 45 45 46 48 49 50 51 49 46 43 41 39 37 37 33 30 26 24 26 30 37 41 47 48 48 48 47 46 45 45 46 46 43 39 34 31 30 31 34 34 33 30 25 22 21 22 23 28 35 40 42 42 43 44 41 42 42 42 40 37 34 32 32 29 27 28 31 33 34 33 43 44 45 44 41 35 29 26 29 33 39 45 48 45 38 33 30 30 30 30 31 31 31 31 35 37 40 43 44 43 41 39 43 48 54 61 64 64 62 61 56 53 47 40 33 28 24 22 24 27 33 38 42 43 43 42 36 33 28 23 21 22 23 25 28 30 31 31 29 27 27 28 29 32 37 46 57 68 77 81 80 74 64 53 44 38 36 35 36 41 44 45 48 50 47 40 39 36 31 28 27 25 23 21 25 31 41 51 58 62 62 61 60 59 58 60 62 58 50 43 40 41 47 58 68 72 67 61 47 35 25 23 26 29 35 40 42 40 36 32 29 26 25 25 23 22 22 21 21 22 23 23 29 31 34 37 39 41 41 41 41 38 35 31 27 24 22 22 20 20 20 21 22 24 25 26 27 26 24 22 20 18 17 17 18 19 20 21 22 21 19 19 18 18 17 16 16 16 16 17 16 17 17 18 18 17 17 16 17 16 16 14 13 12 11 11 11 11 11 11 11 11 11 11 14 14 14 15 15 16 16 16 15 15 14 14 14 13 13 13 11 10 9 8 8 8 8 9 6 6 6 5 5 4 4 4 6 5 4 3 3 3 3 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 11 12 14 14 14 14 15 17 18 19 21 21 21 21 22 24 23 24 23 23 22 21 19 18 20 20 21 22 22 23 23 23 31 34 37 39 40 42 45 48 48 51 55 56 56 56 57 58 60 61 62 64 64 63 62 61 59 58 57 55 54 53 53 53 57 59 61 62 64 67 72 75 85 86 90 96 104 110 114 116 118 124 129 133 143 160 174 181 194 196 198 199 199 198 197 196 193 192 190 190 191 195 199 202 203 206 212 218 223 227 229 229 221 214 204 194 186 181 176 173 176 170 165 165 168 166 157 148 137 137 138 139 142 145 149 151 146 137 122 107 93 81 71 66 67 70 76 85 97 106 112 115 116 117 114 104 95 88 79 71 70 69 68 70 74 76 77 77 73 73 74 77 80 82 82 80 67 61 51 44 42 46 53 58 64 67 70 74 74 70 63 58 61 65 75 92 108 116 116 113 100 91 80 74 75 79 83 84 84 79 71 67 66 68 70 71 73 74 73 72 68 64 59 56 53 54 53 49 45 44 46 50 49 48 48 47 47 48 49 49 55 53 51 48 46 44 42 42 39 35 30 26 26 29 34 38 43 44 45 46 47 48 48 48 51 50 48 44 38 33 31 30 33 34 34 31 27 23 22 22 22 27 35 40 41 41 40 40 37 39 42 44 44 43 40 38 33 29 25 27 33 37 37 34 40 40 39 37 33 29 25 23 29 32 37 43 45 42 35 30 30 30 30 30 30 30 30 30 33 35 37 39 39 38 36 34 43 49 58 67 72 73 72 70 61 57 50 42 34 27 23 21 22 26 31 36 39 41 41 40 33 30 26 23 21 21 22 23 26 29 31 30 28 26 26 26 25 28 33 43 55 67 75 79 77 71 60 48 40 35 33 33 34 38 41 42 44 46 42 36 40 38 35 33 32 30 27 24 24 31 41 53 60 64 64 63 63 60 59 61 63 60 52 45 43 44 50 61 71 74 69 63 47 36 26 25 29 32 37 43 44 41 36 30 26 24 23 22 21 21 21 21 21 23 24 24 30 33 36 40 42 43 42 41 41 38 33 28 24 22 22 22 21 21 21 22 23 24 26 27 25 23 21 19 17 16 15 15 17 18 19 21 21 20 19 18 18 17 16 14 14 13 14 14 16 16 17 18 18 17 16 16 16 15 15 13 12 11 10 10 11 11 11 11 11 11 11 11 14 14 14 15 15 16 16 16 15 15 15 14 14 14 13 13 11 10 9 8 8 8 8 9 6 6 6 5 5 4 4 4 6 5 4 3 3 3 3 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 12 12 13 14 14 15 16 16 20 20 19 19 19 19 19 19 21 21 21 20 20 20 19 19 19 21 23 23 23 24 27 29 30 34 40 45 47 49 51 52 56 58 60 62 63 63 62 62 61 61 60 60 59 58 58 57 54 53 52 51 51 55 60 65 60 61 64 68 68 68 74 82 91 95 102 111 119 124 126 125 120 127 136 144 153 168 189 204 206 208 211 213 212 210 206 204 198 199 201 203 206 208 209 210 208 211 216 220 224 225 225 226 218 209 200 193 184 172 166 166 160 159 160 162 162 157 149 142 139 138 137 137 141 147 153 158 152 145 132 117 102 88 79 74 72 75 81 88 94 100 104 106 113 110 105 98 91 85 81 79 69 73 76 76 81 87 89 87 86 82 80 82 87 88 85 80 69 59 50 46 45 47 56 65 68 70 71 69 65 60 57 56 55 64 77 90 105 117 118 114 97 88 80 79 80 82 88 94 94 92 87 80 74 71 73 76 77 82 84 79 76 75 72 69 65 63 58 55 53 53 55 56 61 60 56 51 46 45 47 49 50 51 52 51 50 49 50 51 49 47 41 34 28 27 29 32 39 41 45 48 51 52 51 51 52 51 48 40 32 27 28 30 35 39 43 41 34 26 22 20 26 33 40 43 40 36 35 34 32 41 49 53 61 66 59 45 43 33 27 32 38 41 42 43 44 42 37 32 27 24 24 25 26 28 32 35 36 35 34 32 31 32 32 31 29 28 28 30 31 35 38 38 34 31 32 34 44 51 62 72 79 80 78 76 67 61 51 41 34 28 23 20 26 29 34 36 37 36 35 35 31 29 26 24 23 24 25 26 27 28 29 30 29 26 24 22 23 26 32 42 53 64 73 79 73 67 57 47 38 34 32 32 33 34 36 35 34 34 35 36 37 42 44 42 40 38 32 25 27 30 38 50 61 66 65 62 59 57 55 57 61 60 54 49 47 49 54 63 71 72 66 60 45 37 30 29 34 40 43 44 43 38 32 26 23 21 18 16 20 19 19 19 21 23 26 27 31 35 40 44 44 42 37 34 31 27 23 21 22 22 20 17 22 22 22 24 26 26 24 22 21 20 17 15 13 13 13 13 16 16 17 18 19 19 18 18 17 17 18 19 19 18 17 17 17 17 18 19 20 20 20 19 16 15 15 13 12 11 10 10 9 9 9 9 9 11 12 12 15 16 16 15 14 13 15 17 18 17 16 15 13 12 11 11 12 12 11 11 10 9 8 8 7 7 7 6 6 5 5 5 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 12 12 13 14 14 15 16 16 19 18 18 18 18 18 18 18 20 20 20 19 19 19 19 19 20 22 24 25 25 26 28 31 34 39 45 49 52 53 56 57 61 62 64 65 66 66 65 65 62 62 60 59 57 55 54 53 49 50 50 50 51 56 62 67 69 69 71 74 73 72 78 86 99 104 112 121 129 134 135 134 133 139 147 156 168 185 204 217 226 225 223 221 218 215 213 212 218 220 223 226 227 226 224 223 218 216 217 221 227 229 226 222 218 208 197 188 176 164 156 155 149 148 148 149 149 146 140 135 133 133 134 136 140 146 151 155 151 145 133 118 103 90 81 76 76 79 83 89 95 100 103 105 107 105 100 94 89 84 80 78 74 78 81 83 89 96 98 96 91 86 83 84 88 90 86 82 68 59 49 46 46 49 58 67 69 69 68 65 59 54 52 51 55 64 75 87 100 111 112 107 97 89 81 79 80 82 89 96 102 101 98 92 85 82 82 84 87 93 96 92 87 84 80 75 76 74 70 67 64 63 64 64 66 64 59 53 47 45 46 48 49 51 52 52 51 51 53 55 57 54 48 41 34 31 32 34 39 41 45 48 50 50 50 49 49 48 44 37 29 26 28 31 38 42 46 43 36 28 23 22 26 33 41 43 40 35 32 31 31 44 57 67 79 87 79 65 48 37 29 32 39 43 45 48 45 43 37 31 26 24 24 24 25 26 29 31 32 32 32 31 32 33 33 31 28 26 27 28 31 35 38 37 33 30 30 32 42 50 61 72 78 79 77 74 65 60 52 44 38 33 28 25 26 28 30 32 32 32 31 31 28 27 25 24 24 26 27 28 29 29 30 30 28 26 24 22 21 25 33 42 53 63 71 76 70 65 55 45 37 32 30 30 28 29 30 29 28 29 32 34 42 48 53 52 50 47 39 31 29 32 38 49 59 64 64 61 57 55 53 55 58 58 53 48 49 50 55 63 70 70 64 57 44 38 32 31 35 40 42 42 40 35 29 24 21 20 18 17 18 18 19 20 22 25 28 30 32 35 39 42 42 38 34 31 28 24 21 20 22 24 23 22 26 25 25 26 27 26 24 21 18 17 15 14 13 13 14 15 16 17 17 18 18 18 18 18 17 17 18 19 19 18 17 17 18 18 19 20 21 21 20 20 17 16 15 14 13 12 11 10 9 9 9 9 9 10 11 12 14 15 16 15 13 13 15 17 17 16 16 14 13 12 11 10 12 12 11 10 9 9 8 8 7 7 6 6 6 5 5 5 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 12 12 13 14 14 15 16 16 17 17 17 17 17 17 17 17 18 18 18 18 18 19 19 19 22 24 27 28 28 29 31 33 38 42 48 52 55 57 59 61 64 65 66 67 67 66 66 65 63 62 60 57 53 51 48 47 43 44 47 49 53 59 66 72 77 77 79 82 82 82 88 96 106 113 123 133 141 145 145 145 147 152 160 174 191 210 227 236 251 248 243 238 235 234 235 235 241 243 247 249 248 245 242 239 233 227 222 225 231 232 225 217 211 200 187 176 165 152 144 142 136 134 132 132 132 130 128 125 125 126 129 134 138 143 147 149 149 142 131 117 103 91 83 78 80 82 86 90 94 98 100 101 101 99 96 93 88 85 82 80 79 84 89 93 101 109 111 108 98 92 87 86 90 91 87 83 68 58 50 47 48 53 63 73 71 69 66 59 53 48 46 47 54 63 73 83 93 102 103 99 97 89 82 80 80 82 90 98 110 112 112 108 101 97 96 97 104 110 113 108 102 97 90 84 88 87 83 80 76 74 72 72 71 69 63 55 48 45 46 48 50 51 53 54 54 55 58 61 65 63 58 50 42 36 34 34 40 42 45 47 48 48 47 46 44 43 39 32 26 25 29 34 43 47 50 47 39 31 25 24 26 34 42 45 41 34 28 26 31 48 68 86 103 111 100 83 56 42 31 32 40 47 51 55 49 45 38 32 27 25 25 25 25 25 25 26 27 29 30 31 35 35 33 30 26 25 26 27 32 35 37 36 31 27 27 28 39 47 58 69 75 76 72 69 61 58 52 48 44 40 35 32 27 27 27 26 26 26 27 27 24 24 25 26 27 30 32 33 32 32 31 30 28 26 23 22 21 26 34 44 54 62 68 71 66 61 52 42 35 30 29 28 25 26 25 24 25 27 32 36 48 57 64 65 63 58 48 38 33 34 38 47 56 61 60 58 53 51 49 51 54 54 51 48 50 52 56 63 68 67 61 55 44 40 36 35 38 41 41 40 37 32 26 22 20 20 19 19 18 18 19 20 23 27 30 32 33 35 37 39 37 33 29 26 22 21 20 21 25 29 31 31 34 32 30 29 29 27 23 21 15 14 14 14 15 16 17 18 19 19 19 19 19 18 18 18 18 19 19 20 20 19 19 18 19 19 20 21 21 21 21 20 18 17 16 15 14 13 12 11 10 9 9 9 9 10 11 11 13 14 14 13 12 12 13 15 16 15 14 13 12 11 10 10 11 11 10 10 9 8 7 7 7 6 6 6 5 5 5 5 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 12 12 13 14 14 15 16 16 15 15 16 16 16 16 17 17 17 17 17 18 18 19 19 20 25 27 30 31 32 33 35 37 40 43 48 52 54 56 59 61 63 63 64 64 63 63 62 62 62 61 58 54 50 46 43 42 39 41 45 50 56 64 73 79 83 83 86 90 91 93 100 110 117 125 138 149 157 160 162 162 162 167 178 196 217 235 246 251 255 255 254 251 251 252 254 255 253 254 255 255 255 254 252 250 247 241 235 233 234 230 221 213 199 186 172 161 151 140 132 131 125 122 118 115 114 114 115 115 117 121 126 132 136 139 140 141 142 136 125 113 100 89 82 78 81 83 85 88 91 93 94 95 97 96 95 93 91 88 86 85 82 88 94 101 112 122 124 121 105 97 89 85 87 88 86 82 69 59 51 49 51 58 69 80 76 73 66 58 50 45 45 46 55 63 73 80 89 96 97 93 95 88 81 79 79 82 91 101 114 119 123 122 116 112 112 114 125 130 131 125 116 109 101 94 94 93 90 87 83 79 76 75 75 72 65 56 49 45 46 48 54 55 57 58 58 60 64 67 71 69 64 57 47 40 36 34 41 42 45 46 46 45 43 42 38 37 34 28 23 24 30 36 49 52 55 51 43 33 28 26 28 36 46 49 44 35 27 23 32 52 79 102 121 128 112 92 62 46 32 33 43 52 58 62 55 49 40 33 29 28 28 28 26 25 24 23 25 27 31 33 38 37 34 30 26 24 26 28 34 37 39 36 30 26 24 25 34 42 53 63 68 68 64 61 55 54 52 51 50 46 41 38 31 28 24 22 22 23 24 24 21 23 25 29 32 36 38 39 37 36 34 31 28 25 24 23 23 28 36 46 54 60 63 65 59 55 48 40 34 30 29 29 27 27 26 25 26 30 37 42 54 64 74 77 75 69 57 45 38 37 38 44 51 56 56 55 49 47 45 46 48 49 48 46 48 51 56 63 67 66 61 56 46 44 41 41 42 43 41 39 35 31 26 23 22 23 22 22 20 20 20 21 24 27 30 31 33 34 35 35 32 28 24 21 19 20 22 27 32 38 42 44 44 41 38 35 32 29 25 22 15 16 17 19 20 22 24 25 25 24 23 22 21 20 20 20 21 21 22 22 22 22 21 21 20 21 21 22 22 22 21 21 18 18 17 16 15 13 13 12 10 9 9 8 8 9 10 10 11 12 13 12 10 10 12 14 14 14 13 12 11 10 10 9 10 10 10 9 8 7 7 6 6 6 6 5 5 5 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 12 12 13 14 14 15 16 16 14 15 15 15 16 16 17 17 17 17 18 19 20 21 22 22 27 30 34 36 36 37 39 40 42 45 48 51 53 55 58 60 61 60 60 60 59 59 59 60 59 58 55 52 48 44 41 40 39 43 48 55 63 72 81 87 93 92 95 99 100 102 111 120 133 143 157 169 177 182 185 187 188 193 205 223 240 252 255 255 253 253 254 254 255 255 255 255 255 255 254 254 254 255 255 255 255 253 249 243 236 227 218 212 191 176 160 148 139 128 120 118 114 110 105 100 98 100 103 107 115 119 125 130 134 134 133 132 131 126 116 105 94 84 77 74 78 79 81 84 86 87 88 88 91 91 92 92 91 90 89 88 83 89 97 108 122 134 136 131 113 103 89 81 81 82 81 79 70 61 53 51 54 62 74 86 82 78 71 61 52 48 48 50 57 66 75 80 87 93 94 91 90 84 79 77 77 81 92 104 118 125 132 132 128 125 128 131 147 151 151 142 132 122 112 104 95 93 91 88 84 81 78 76 76 73 66 57 50 47 49 51 60 61 62 61 61 63 67 70 75 73 69 62 53 45 40 38 42 43 45 45 44 42 39 37 33 33 30 26 23 25 32 38 52 55 57 54 45 36 30 28 31 40 49 52 46 36 27 23 32 55 85 112 134 139 120 96 65 48 33 35 47 57 64 68 59 52 42 35 32 32 33 33 29 28 25 24 25 29 33 36 39 37 34 29 26 26 29 32 39 42 43 39 32 26 24 25 30 36 45 53 57 57 54 51 48 49 51 54 55 52 47 42 35 30 24 21 21 22 23 23 21 23 28 34 39 43 45 47 43 41 37 33 29 26 25 24 26 31 38 46 53 56 57 58 52 49 43 38 34 32 32 32 31 31 30 29 30 35 43 48 62 72 82 86 84 78 66 54 44 40 38 40 46 51 52 51 46 44 42 41 42 43 43 43 45 49 55 62 66 65 61 57 49 48 46 45 45 43 41 39 35 32 28 26 26 27 26 25 23 23 22 22 23 25 27 28 32 32 32 31 28 24 21 19 20 24 30 37 44 50 55 58 56 52 47 42 38 34 29 25 21 22 24 27 29 31 32 33 31 30 28 26 24 23 23 23 24 24 25 25 25 25 24 24 21 21 22 22 22 21 21 20 18 18 17 16 15 13 13 12 10 9 9 8 8 8 9 9 10 11 11 10 9 8 10 12 12 12 11 11 10 9 9 9 10 9 9 8 7 6 6 6 6 6 5 5 5 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 12 12 13 14 14 15 16 16 14 14 15 16 16 17 18 18 18 19 20 21 23 24 25 26 29 33 37 40 40 41 42 44 44 46 49 50 51 52 55 57 57 56 56 55 55 56 57 58 54 53 52 49 47 44 43 42 44 48 55 63 71 80 90 96 105 105 107 110 111 114 122 133 147 157 172 185 194 200 206 210 223 226 234 245 254 255 255 253 254 255 255 255 255 255 255 253 255 254 252 252 252 254 255 255 255 255 255 251 241 229 218 213 191 174 155 141 131 119 111 108 103 100 96 91 89 93 99 104 118 122 127 130 131 129 126 123 120 115 107 96 86 78 72 69 72 73 76 78 80 82 83 83 85 87 88 90 90 90 89 88 85 92 101 115 132 146 148 142 122 108 89 76 73 75 76 75 70 61 52 51 55 63 76 88 88 84 77 67 59 55 56 58 64 72 80 82 85 90 91 88 84 79 75 73 74 79 92 106 123 130 136 136 132 132 137 143 162 167 169 160 148 134 119 108 91 90 87 84 81 80 78 78 76 72 66 58 53 52 55 59 67 67 66 64 62 63 66 69 75 74 70 63 55 49 45 44 43 44 45 44 42 39 35 33 30 31 30 27 24 27 34 40 52 56 58 55 46 37 31 29 34 42 51 53 47 37 28 24 33 56 88 117 140 144 124 98 63 46 33 37 51 62 68 70 62 53 42 35 34 35 37 37 32 30 27 26 27 31 35 38 39 37 34 29 27 29 34 38 46 48 48 43 35 28 26 26 27 31 38 44 46 46 43 41 44 47 52 57 60 58 52 46 37 31 24 21 22 24 23 22 22 26 33 40 46 51 53 54 49 46 41 35 30 27 26 26 29 33 38 44 48 50 50 49 44 42 40 37 36 37 38 39 37 36 36 35 36 41 49 54 68 78 87 90 89 83 72 62 49 43 38 37 41 46 48 47 43 42 39 36 35 36 38 39 43 48 55 62 65 64 61 58 50 49 48 46 44 41 39 37 35 33 31 31 31 30 28 26 24 23 22 22 22 23 25 26 30 30 29 27 25 23 21 20 25 32 43 52 59 65 69 72 67 62 56 50 45 40 34 31 30 31 33 36 38 39 40 40 37 35 32 29 27 25 25 25 25 26 26 27 27 26 26 25 20 21 21 21 21 20 19 19 18 17 16 15 14 13 12 11 10 9 9 8 7 8 8 8 8 9 10 9 7 7 9 11 10 10 10 9 9 9 8 8 9 9 8 7 6 6 5 5 5 5 5 5 4 4 4 3 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 12 12 13 14 14 15 16 16 14 15 15 16 17 18 19 19 20 21 22 24 25 27 28 29 31 35 40 43 44 44 45 46 43 44 46 46 46 46 49 51 50 49 49 49 49 51 52 53 49 49 48 48 47 46 45 45 50 55 62 70 79 88 97 103 112 112 115 121 125 130 141 152 163 175 190 203 212 221 229 235 248 249 251 254 255 255 255 254 255 255 255 255 255 255 255 255 255 254 254 253 254 255 255 255 255 255 255 254 248 237 223 213 191 173 152 139 129 118 110 107 97 96 93 90 91 96 105 112 124 126 129 131 129 125 119 116 111 107 99 90 81 73 68 66 67 69 71 74 77 79 80 81 84 85 88 90 91 91 90 89 89 96 107 123 143 157 159 153 131 113 89 72 67 69 72 73 68 59 50 49 53 61 75 87 92 88 82 73 66 62 63 65 71 79 85 84 84 85 85 83 77 73 70 69 70 77 92 107 124 130 134 132 127 128 136 144 163 173 179 173 159 140 118 102 84 82 79 76 75 75 76 77 75 72 67 61 57 59 64 68 72 71 68 63 60 59 61 63 68 67 64 58 52 47 45 46 44 45 45 43 40 36 32 30 29 30 31 29 27 29 35 41 51 55 58 54 46 37 32 30 34 42 50 52 46 36 28 25 38 59 89 116 138 140 117 89 58 43 32 39 55 66 70 71 61 51 39 33 33 36 38 38 33 31 29 28 29 32 36 39 38 36 33 30 29 32 39 44 52 54 53 48 39 32 28 28 28 30 34 37 38 38 36 35 42 47 54 62 65 63 56 50 37 31 23 21 23 25 23 21 25 30 37 46 53 57 59 59 54 50 44 37 32 29 28 28 31 33 36 39 41 42 41 41 38 38 37 38 39 42 45 46 45 45 45 45 46 50 57 61 69 77 85 86 85 81 72 63 53 46 38 35 38 42 44 45 42 40 37 33 31 31 33 35 44 49 57 62 64 61 58 56 49 49 47 44 40 37 35 34 33 33 33 34 34 32 28 24 22 21 20 20 21 23 25 27 28 27 26 25 23 22 22 22 32 42 55 67 74 78 80 82 76 71 63 56 51 45 40 37 37 39 41 43 44 44 44 44 39 37 33 30 27 26 26 26 24 25 26 26 26 26 25 24 20 20 21 21 20 19 18 18 17 16 15 14 13 12 11 10 10 9 8 8 7 7 7 8 7 8 9 7 6 6 8 9 9 9 9 9 8 8 8 7 8 8 7 7 6 5 4 4 5 5 5 4 4 4 3 3 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 12 12 13 14 14 15 16 16 15 15 16 17 18 18 19 20 21 22 24 25 27 29 31 31 32 36 41 44 45 46 47 48 39 41 42 41 40 40 42 45 43 42 42 42 43 45 47 48 46 46 46 47 47 47 48 48 55 60 67 75 83 92 101 107 112 113 119 127 135 143 157 170 183 194 209 222 232 242 252 255 255 255 254 254 253 254 255 255 254 254 254 254 254 255 255 255 254 254 255 255 255 254 253 252 255 254 252 253 253 244 228 214 189 171 150 138 130 122 115 112 96 96 95 94 96 103 114 123 128 130 132 131 128 122 116 112 107 103 96 87 78 71 66 64 64 66 69 73 76 78 80 81 85 87 90 93 94 94 93 92 92 99 111 128 149 165 166 160 136 117 90 70 64 66 70 72 67 57 48 47 50 59 73 86 93 90 84 76 70 66 67 69 77 84 88 86 82 82 81 78 73 70 67 67 68 76 92 108 122 127 130 125 119 120 130 140 159 171 181 178 163 140 113 93 77 75 71 69 68 70 72 74 76 73 68 63 61 63 69 74 74 72 68 62 57 55 56 58 61 60 57 51 46 43 43 44 45 45 45 43 40 35 31 28 28 30 32 31 29 31 36 41 50 54 57 54 46 37 32 30 34 41 48 50 44 35 28 25 43 63 89 114 132 132 106 77 55 40 31 40 57 68 71 70 59 49 37 30 32 36 38 38 32 31 29 29 30 33 36 39 38 36 33 30 30 34 42 48 56 58 57 51 42 34 30 30 29 30 32 34 34 34 33 32 42 47 56 65 69 66 59 53 36 30 23 21 23 25 23 20 27 32 40 49 56 60 62 63 57 53 46 38 33 30 29 29 31 32 34 36 36 36 36 35 35 35 36 38 41 45 49 51 53 54 54 54 55 58 64 68 66 73 79 80 79 76 69 61 55 47 38 34 36 40 43 43 42 40 36 31 28 28 31 33 46 51 58 62 62 59 56 53 48 48 46 42 37 34 32 32 32 32 34 35 35 32 27 23 19 19 19 19 21 24 26 28 26 25 24 23 23 23 23 23 37 48 63 75 82 85 87 88 81 75 68 60 54 49 44 40 42 43 45 46 47 47 46 45 40 38 33 29 26 25 25 25 23 24 24 25 25 24 24 23 19 20 20 20 19 18 17 17 16 15 15 13 12 11 10 10 10 10 8 7 7 7 7 7 6 7 8 7 5 5 7 9 9 8 8 8 8 8 7 7 8 8 7 6 5 5 4 4 5 5 5 4 4 3 3 3 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 13 13 14 15 15 16 17 17 16 16 17 18 20 21 22 23 22 23 24 27 29 31 33 34 37 38 40 42 44 45 46 46 38 38 37 36 35 35 35 36 36 37 38 37 38 39 43 46 43 45 46 47 47 48 51 53 58 61 71 82 89 94 104 114 111 125 139 144 149 161 177 187 203 217 235 249 254 254 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 248 251 255 248 238 225 207 191 181 164 147 133 124 118 115 115 109 107 110 112 113 121 132 139 144 143 134 126 122 115 107 105 101 94 88 82 76 69 65 68 67 67 69 72 77 82 85 93 95 99 102 103 103 102 100 99 105 118 138 165 182 181 172 151 122 88 68 62 63 67 71 66 60 51 43 42 50 62 71 84 84 84 82 79 78 79 81 86 88 90 91 88 82 75 70 63 63 63 66 73 85 99 108 125 124 122 116 107 105 115 128 154 168 180 178 163 139 110 90 69 61 56 59 65 68 71 75 74 70 66 63 62 65 69 71 71 69 64 58 52 47 44 42 43 42 41 39 39 40 42 42 44 45 45 43 38 33 31 30 31 32 33 32 32 32 35 37 45 48 50 48 41 35 32 32 30 36 43 44 38 32 30 30 38 61 91 112 118 109 88 70 43 39 38 46 61 70 71 67 53 44 34 29 31 34 34 33 33 31 28 27 28 33 38 41 35 33 31 31 35 42 49 54 65 63 58 51 42 35 32 31 31 33 33 33 32 32 34 36 37 46 57 65 72 73 64 52 45 33 23 22 24 24 25 26 28 32 40 50 59 64 65 65 57 51 43 37 33 31 30 29 28 28 29 29 28 28 27 26 29 34 41 47 50 53 56 58 56 57 59 60 61 62 62 62 64 65 66 66 65 63 61 59 52 48 43 38 35 36 39 41 34 33 30 26 24 25 29 32 43 49 57 63 64 59 52 47 42 40 37 34 32 30 30 30 26 27 29 31 30 27 24 22 19 19 19 20 22 24 26 27 28 30 31 27 23 22 27 32 42 51 66 81 89 91 89 86 82 77 69 61 55 50 45 41 41 43 47 49 49 47 44 42 36 34 30 26 23 22 22 22 21 22 23 24 24 23 21 20 17 17 16 16 16 15 15 15 13 13 13 13 12 11 10 9 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 8 7 7 6 6 7 7 8 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 12 13 14 14 16 16 17 18 16 16 17 18 20 21 22 22 22 23 25 27 30 32 34 35 36 37 39 41 43 44 44 45 37 36 35 33 33 33 33 33 31 32 34 34 34 36 40 43 43 45 47 48 49 50 54 57 66 70 79 90 96 102 111 121 121 134 146 153 163 181 200 211 229 237 248 254 254 253 253 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 251 254 255 245 234 222 205 190 180 165 151 140 134 129 127 123 119 118 122 125 128 135 144 142 145 143 134 127 123 117 110 112 108 101 94 88 80 73 69 66 65 64 66 71 78 85 90 99 102 107 110 111 110 107 105 106 112 124 145 170 188 188 180 154 126 92 71 63 62 65 69 64 58 49 41 39 44 55 63 73 75 77 78 79 81 84 87 91 93 95 94 90 83 75 70 60 60 62 66 75 89 102 111 121 118 113 105 94 90 100 113 141 155 168 167 154 132 105 85 65 58 53 57 62 65 69 73 72 69 65 61 60 62 65 68 69 65 59 52 46 41 38 37 39 38 37 36 36 38 40 41 46 47 46 43 39 34 32 32 32 33 33 31 30 31 34 36 43 46 48 46 40 34 30 29 27 33 39 40 35 31 31 32 44 64 88 103 107 98 78 61 40 36 36 45 59 68 67 63 50 42 32 28 29 32 32 31 31 29 27 26 28 32 37 40 36 35 33 33 38 45 53 58 64 62 58 50 42 35 33 32 32 33 34 33 31 30 32 33 38 48 60 70 78 78 68 56 45 33 23 23 26 27 27 29 28 32 39 48 56 61 62 60 53 48 42 37 35 34 33 32 29 29 28 27 27 27 27 27 30 35 42 47 51 54 57 59 58 58 59 59 58 58 57 56 55 55 55 55 54 54 53 53 50 47 42 38 35 35 36 37 32 31 28 25 23 25 30 34 43 49 57 62 62 56 48 42 37 36 33 31 29 28 27 27 25 26 27 28 27 25 23 22 23 24 25 26 28 29 30 31 29 31 32 29 25 26 31 36 47 56 69 82 89 90 87 84 76 71 64 57 52 47 43 39 40 42 46 48 48 46 43 40 35 33 29 26 23 22 21 21 19 20 21 22 21 20 19 18 17 17 17 16 16 16 15 15 13 13 14 13 13 11 10 9 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 6 6 6 6 7 7 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 11 12 13 14 16 17 18 19 16 16 17 18 19 20 21 21 23 24 26 28 31 33 35 36 34 35 37 39 40 41 42 42 35 34 33 31 30 30 30 30 29 31 33 34 35 37 40 43 43 46 49 51 53 56 61 64 71 75 83 94 100 106 115 126 136 147 160 172 188 210 230 240 252 255 255 255 253 251 253 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 252 255 252 236 224 214 199 182 174 162 152 145 141 139 138 132 130 131 137 142 145 150 156 147 146 141 133 127 125 122 118 120 115 108 101 93 84 76 71 66 64 63 65 72 81 91 97 107 111 116 121 122 119 115 112 112 118 130 149 175 193 195 188 159 132 98 75 65 62 63 67 64 59 50 41 36 39 47 53 62 65 69 72 76 80 86 90 95 97 98 97 91 82 73 67 57 57 61 68 80 94 107 115 119 113 104 92 79 73 81 93 121 136 150 151 141 122 97 79 62 54 50 53 59 62 66 70 70 67 62 58 57 58 60 62 63 59 52 45 39 35 33 33 36 35 34 33 34 37 40 42 49 49 48 45 40 36 35 35 36 37 36 34 32 32 35 37 42 44 46 44 39 32 27 25 24 28 32 33 31 30 32 35 52 67 84 93 92 83 65 50 35 33 34 43 56 63 62 58 44 38 30 26 26 28 29 28 26 25 25 25 28 32 35 38 38 36 35 36 41 49 57 62 63 61 56 49 41 35 33 33 35 36 36 34 31 29 29 30 38 49 62 74 83 83 73 60 46 34 25 25 29 30 30 32 28 31 37 44 51 55 55 54 47 44 41 39 39 40 40 39 32 30 28 27 26 27 28 29 31 36 42 46 50 52 55 58 56 56 56 55 53 51 49 48 44 43 43 42 43 44 45 46 47 45 42 38 35 33 31 31 29 28 26 23 22 26 32 36 44 49 56 61 59 52 42 36 31 30 28 27 25 25 25 25 25 25 25 25 24 24 24 24 27 28 31 33 35 35 35 35 33 34 34 32 30 31 36 42 51 58 69 78 83 82 79 76 66 61 55 50 46 42 39 36 38 40 43 45 45 43 40 38 33 32 29 27 24 23 22 22 19 19 19 19 19 18 16 16 18 18 17 17 17 16 16 16 14 14 14 14 13 11 10 9 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 6 6 5 5 6 6 7 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 11 12 13 14 16 17 18 19 16 16 17 18 19 20 20 21 24 25 26 29 31 33 35 36 32 33 35 37 38 39 39 39 35 34 33 31 30 30 30 30 32 35 38 40 41 43 47 49 47 50 54 58 61 65 71 75 79 82 90 100 107 112 123 133 148 162 180 198 217 237 251 255 255 255 255 254 252 251 254 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 253 252 254 246 224 211 202 187 171 164 155 146 142 140 138 138 135 136 141 148 154 158 160 161 150 145 137 130 127 127 128 128 127 122 114 105 96 86 77 71 68 66 65 67 74 85 96 103 111 115 121 126 127 125 121 118 114 120 131 149 173 192 196 191 165 138 105 82 69 64 64 67 67 62 54 44 38 37 42 46 55 58 63 67 71 77 83 87 97 99 100 97 91 80 69 63 55 56 61 71 85 99 111 117 119 110 97 83 68 61 68 79 103 118 133 136 129 113 93 77 62 54 49 52 57 60 63 67 66 63 58 54 52 52 54 55 55 51 45 39 36 35 36 37 38 37 36 35 37 40 44 46 52 51 50 46 41 38 38 39 42 43 43 41 39 38 38 40 40 42 43 41 37 31 25 22 23 25 26 27 27 29 33 37 55 67 80 85 82 72 56 41 32 31 33 41 52 58 56 51 39 34 27 24 24 25 25 25 21 22 23 25 28 32 34 36 38 37 36 37 42 50 58 63 61 59 54 47 39 35 34 34 38 39 39 37 33 30 30 30 37 48 63 76 85 86 75 62 48 37 28 28 31 31 31 31 28 30 34 40 46 48 48 46 41 40 39 41 44 46 46 46 37 35 31 27 27 28 30 32 33 36 40 43 44 46 48 50 50 49 49 48 46 44 42 40 37 36 34 33 35 38 41 43 43 42 40 38 34 30 27 25 26 25 24 23 23 28 34 39 47 51 57 59 56 47 37 31 26 26 25 25 25 25 25 25 27 26 25 24 24 25 27 28 31 33 36 39 40 40 39 38 39 40 39 37 35 36 41 45 51 56 63 68 70 68 64 61 54 50 45 41 38 36 33 31 35 37 39 41 42 40 38 37 34 33 32 31 29 27 25 25 21 20 20 19 18 17 16 16 19 18 18 18 17 17 17 17 15 15 15 14 13 12 10 9 7 7 7 7 7 7 7 7 8 8 8 8 8 8 8 8 6 6 5 5 5 5 6 6 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 12 12 13 14 16 17 18 18 16 16 17 17 18 19 19 20 22 23 25 27 30 32 34 35 31 32 34 35 36 37 37 37 36 35 34 33 33 33 33 34 36 39 43 46 48 51 54 57 55 58 63 68 72 78 84 88 93 95 103 113 121 127 138 149 161 180 204 224 241 253 255 255 253 254 254 254 253 253 254 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 254 254 240 215 201 192 176 162 155 146 138 134 131 130 129 134 138 145 154 162 167 165 162 150 141 131 125 126 130 135 139 138 131 121 109 99 88 79 73 70 69 69 72 80 90 100 106 113 116 120 123 124 123 120 118 114 119 129 145 168 187 193 190 167 143 111 88 74 67 67 70 69 65 58 48 41 38 39 41 48 52 57 62 67 74 80 85 97 99 101 99 92 81 70 63 56 57 63 73 88 101 110 114 113 103 88 73 60 53 60 71 92 105 119 123 118 107 91 78 65 56 51 52 56 58 60 63 60 58 54 50 47 47 47 48 46 44 41 38 39 41 45 48 47 45 43 42 43 46 50 52 53 52 50 46 42 40 42 43 46 49 52 52 50 46 44 43 40 40 40 38 36 31 26 23 23 23 23 23 24 29 34 38 53 64 75 79 76 66 51 37 30 30 32 39 47 51 49 45 34 31 26 23 23 23 23 23 19 21 24 28 32 34 36 37 39 37 35 36 40 47 55 60 57 55 51 44 37 33 33 34 40 42 42 40 37 34 32 32 39 51 65 78 87 87 76 63 50 39 30 29 31 30 29 29 27 28 31 36 40 42 41 40 36 36 39 44 49 52 52 51 43 39 34 30 28 29 31 33 32 35 37 37 36 36 37 39 40 40 40 39 38 37 35 34 31 30 28 27 29 33 37 40 39 39 39 37 33 29 24 22 24 25 25 25 27 31 37 42 50 53 56 56 51 43 33 27 23 24 25 26 27 28 28 28 30 29 28 27 28 30 32 33 38 39 42 44 45 44 42 41 45 45 44 42 41 42 44 46 51 53 56 59 58 54 50 47 43 39 35 32 30 29 27 26 31 32 35 37 38 38 36 36 36 37 37 36 35 33 31 29 25 24 23 21 20 19 18 18 19 19 19 19 18 18 18 17 16 16 15 15 13 12 10 9 7 7 7 7 7 7 7 7 8 8 8 8 8 8 8 8 7 6 6 5 5 6 6 7 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 13 13 14 15 15 16 17 17 16 16 17 17 18 18 18 19 20 21 23 25 27 30 31 32 31 32 33 35 35 36 36 36 36 36 36 35 36 37 38 38 39 43 47 51 54 57 60 63 66 69 75 80 85 91 98 103 105 107 115 126 134 142 154 165 179 200 226 244 254 255 255 251 253 254 255 255 255 255 254 253 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 253 235 208 195 184 166 153 147 137 129 124 121 118 116 126 134 145 156 167 174 170 163 147 134 122 119 123 131 141 150 149 141 127 114 101 91 82 77 73 75 78 83 91 100 108 113 117 116 116 115 114 113 112 111 111 116 125 139 160 179 187 185 165 142 113 90 76 69 69 73 72 69 63 54 46 41 40 41 42 46 52 58 64 71 78 83 94 96 99 99 93 83 72 65 58 59 63 74 87 98 104 105 99 89 76 63 52 48 55 65 85 97 109 112 109 101 89 79 70 60 53 53 55 55 55 58 54 52 49 45 43 42 43 43 39 39 39 41 45 51 56 60 57 55 51 49 49 51 54 57 53 51 49 45 42 42 45 48 51 57 65 68 66 59 52 48 42 40 37 36 35 33 30 27 25 24 22 22 24 29 34 38 48 58 67 70 67 60 47 36 30 29 29 34 39 42 40 37 31 29 27 24 23 22 22 22 20 24 29 35 39 41 42 42 40 38 35 35 37 43 50 55 54 52 47 40 34 31 32 34 40 42 44 43 40 37 36 36 43 54 67 78 86 86 75 62 48 37 29 29 31 30 28 28 27 27 29 32 36 38 37 36 33 35 40 47 54 56 56 54 46 43 37 32 29 28 30 31 29 31 31 30 29 28 29 30 32 33 33 33 32 31 30 30 26 25 23 23 25 28 32 35 37 37 37 36 33 28 24 21 23 25 28 30 32 36 40 44 52 53 53 50 45 37 29 25 22 24 26 28 30 31 32 32 33 32 32 32 33 35 37 38 45 46 47 47 47 46 44 43 46 46 47 47 47 48 48 48 51 52 53 52 49 44 40 37 34 31 27 24 24 23 22 21 26 27 30 33 35 36 36 36 38 40 41 42 41 38 35 33 30 28 26 24 22 21 20 20 20 20 20 19 19 19 18 18 17 17 16 15 14 12 10 9 7 7 7 7 7 7 7 7 9 9 9 9 9 9 9 9 8 7 7 6 6 7 7 8 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 15 15 15 15 15 15 15 15 16 16 17 17 17 18 18 18 17 18 20 22 25 27 29 30 31 32 33 34 35 35 35 35 36 36 36 37 38 39 41 42 43 47 52 57 60 63 66 69 77 80 86 91 97 103 110 115 117 120 128 139 148 156 170 182 200 220 242 253 255 255 255 253 255 255 255 255 255 255 255 253 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 248 227 200 187 175 153 143 137 127 119 113 109 106 103 112 123 138 153 168 177 173 163 143 127 114 113 121 133 147 158 156 146 130 113 100 90 82 78 81 85 92 101 111 119 125 128 123 119 112 106 102 100 100 101 105 110 117 129 148 168 176 176 159 137 111 90 76 70 71 75 78 76 72 65 57 51 48 48 44 47 52 57 61 67 73 77 85 89 93 94 90 81 71 64 59 59 63 72 84 92 94 93 85 75 65 56 49 47 55 65 81 91 100 102 99 95 86 78 74 64 55 53 53 51 50 52 49 47 44 42 40 39 39 40 35 36 40 45 51 58 65 68 65 62 57 53 51 53 55 58 51 50 47 44 42 43 48 52 60 70 82 89 87 78 66 59 44 40 36 34 35 35 34 32 29 26 24 23 25 30 34 36 45 52 58 57 55 51 43 35 29 27 26 28 31 33 32 30 30 29 28 26 24 22 22 23 25 30 36 43 48 50 50 49 43 40 37 34 36 40 46 50 51 48 44 37 32 30 31 33 37 40 43 43 41 39 38 38 43 52 63 73 79 79 68 56 42 32 25 27 31 31 29 30 26 26 27 30 34 35 35 33 32 35 42 50 57 59 58 55 47 44 38 32 28 26 26 26 24 25 26 25 24 24 25 27 31 31 31 30 30 28 27 26 25 24 23 23 25 28 31 33 36 36 36 34 32 28 25 22 24 27 32 35 38 40 43 45 52 51 48 43 38 31 25 22 21 23 26 30 33 34 35 36 34 34 34 35 37 38 40 41 47 46 45 44 43 42 41 40 42 44 47 50 53 54 52 51 51 50 49 46 41 36 32 29 29 25 22 19 19 19 18 16 21 23 26 30 33 35 36 36 39 41 43 45 44 41 38 36 33 31 28 26 23 22 22 22 21 21 20 20 20 19 19 19 17 17 17 16 14 12 10 9 7 7 7 7 7 7 7 7 9 9 9 9 9 9 9 9 9 9 8 8 8 8 9 9 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 16 16 16 15 15 14 14 14 16 16 17 17 17 17 18 18 15 16 18 20 23 25 27 28 31 32 33 34 35 35 35 35 35 35 35 37 38 41 42 44 47 51 57 62 65 68 72 74 83 87 92 98 104 110 117 122 130 133 141 153 162 172 185 198 215 233 250 255 254 254 255 255 253 253 253 254 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 250 242 219 192 180 166 143 135 129 119 111 105 100 97 94 100 113 131 148 166 177 173 162 140 123 109 109 120 133 149 163 157 146 128 111 97 87 80 76 89 95 105 117 128 135 140 142 128 121 111 101 94 91 92 93 98 103 109 120 139 158 167 167 154 133 108 88 76 69 71 76 85 84 81 74 66 60 57 56 49 52 55 57 59 62 66 70 76 80 85 88 85 77 67 61 59 59 61 70 80 87 87 85 76 68 59 53 48 48 56 66 78 87 95 95 93 90 84 77 76 65 55 52 51 47 46 47 46 45 42 40 38 37 38 38 33 36 41 47 55 62 68 71 69 65 59 54 52 52 55 57 50 49 46 43 42 44 49 54 69 81 96 106 104 93 79 70 45 40 35 33 35 37 37 36 31 28 25 24 26 30 33 35 44 49 50 48 46 44 40 34 28 25 23 23 25 27 26 25 29 30 29 27 25 23 23 23 30 34 42 49 54 56 56 55 46 42 38 35 35 39 44 47 49 46 42 35 30 28 30 33 34 37 41 42 41 39 39 39 40 48 58 66 72 72 61 49 37 28 22 25 30 31 31 32 25 25 26 29 32 34 34 32 32 36 43 51 58 60 58 55 47 44 38 32 27 24 22 22 20 22 23 23 22 23 25 28 31 31 31 30 29 27 25 24 26 26 26 26 27 29 32 33 35 35 35 34 31 28 26 24 24 29 34 39 41 42 44 46 51 49 44 39 33 27 22 20 21 23 26 30 34 36 37 37 33 34 35 37 38 40 41 41 44 43 41 39 37 36 35 35 39 41 46 52 57 58 56 54 49 47 45 40 35 30 26 23 26 23 19 17 17 16 15 14 19 21 24 28 31 34 36 37 39 41 44 46 45 42 39 36 34 32 29 26 24 22 22 22 21 21 21 20 20 20 19 19 18 18 17 16 14 12 10 9 7 7 7 7 7 7 7 7 9 9 9 9 9 9 9 9 10 10 9 8 8 9 10 10 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 15 15 15 15 15 15 15 15 15 15 16 16 16 17 17 17 18 18 18 18 19 21 24 25 27 28 29 30 31 32 33 33 34 36 38 39 40 42 45 48 53 57 63 68 72 76 80 84 86 91 99 105 111 118 127 134 138 143 152 161 171 184 199 210 234 244 253 254 254 255 255 254 255 255 255 255 255 255 255 255 254 254 254 254 254 254 254 254 255 254 252 252 253 255 255 255 253 255 255 255 255 251 246 243 231 229 217 199 183 171 156 142 128 122 115 108 96 85 81 83 89 105 127 149 166 173 166 155 133 109 97 102 112 132 150 152 154 138 118 101 87 78 78 83 95 108 123 136 147 156 156 153 141 126 108 95 86 80 79 83 93 95 102 114 129 140 146 148 132 121 102 84 72 70 76 82 86 91 91 82 72 67 64 62 57 54 53 57 58 58 60 65 67 72 76 75 74 73 68 62 60 62 66 72 76 77 75 72 61 55 48 43 45 52 62 69 80 82 84 85 84 82 80 78 71 65 57 51 48 46 45 45 43 43 42 41 41 40 39 39 35 37 41 48 57 64 68 69 70 64 57 51 48 47 46 45 46 44 42 39 39 43 50 55 70 88 105 113 117 113 93 70 53 40 30 32 36 39 42 47 46 40 33 28 27 29 31 32 37 38 40 41 39 36 32 29 23 23 22 21 22 23 25 26 32 32 31 29 26 25 27 29 34 39 47 56 61 62 61 60 52 46 39 35 34 36 38 39 40 40 38 34 29 27 28 29 38 38 39 40 41 40 37 34 36 40 47 54 56 53 45 39 30 26 23 26 32 35 34 32 31 29 27 27 30 32 33 32 37 39 44 51 57 58 54 49 44 39 32 25 20 20 21 23 18 20 21 21 21 23 27 30 36 38 40 39 35 30 27 25 29 28 28 29 32 33 32 31 36 36 35 33 30 28 26 24 25 28 33 38 41 43 44 44 44 42 38 34 29 24 21 19 19 20 23 26 28 29 29 29 33 33 34 35 37 38 39 40 38 38 36 32 29 29 31 33 38 43 48 52 58 63 62 57 51 46 39 33 29 26 24 21 22 21 20 18 18 17 17 17 20 21 23 26 29 33 36 38 40 41 42 42 41 39 36 34 32 31 29 26 24 23 22 22 23 22 20 19 18 17 17 17 17 17 16 15 13 12 11 10 11 10 9 8 8 8 8 9 12 12 11 11 11 10 10 10 10 10 9 9 9 8 8 8 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 14 14 14 14 14 14 14 14 15 15 15 15 16 16 16 17 18 17 17 17 19 21 23 24 26 27 28 29 30 31 32 32 33 35 38 39 41 43 47 50 54 58 64 69 73 77 81 85 87 92 100 107 112 120 129 136 144 150 159 169 179 192 207 217 238 247 254 255 254 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 252 255 255 254 244 229 217 212 211 196 194 184 169 156 146 133 121 119 113 107 100 89 77 73 74 82 98 122 145 162 168 160 148 126 103 93 99 109 129 146 149 149 134 114 98 85 78 79 85 99 113 129 144 157 168 170 167 146 129 107 91 80 75 78 83 92 93 98 106 116 123 126 126 112 105 92 79 72 74 82 89 94 99 99 89 79 73 70 67 63 59 57 58 58 56 57 61 63 69 72 72 72 72 69 63 66 66 68 70 71 69 65 61 54 50 44 42 45 54 64 71 79 80 81 81 80 77 73 71 66 61 55 51 49 49 48 47 48 48 47 45 43 41 39 38 37 38 42 49 57 63 67 68 65 60 53 47 45 44 43 43 43 43 43 42 42 46 51 56 73 90 108 117 122 118 98 76 51 38 29 30 36 41 46 52 52 45 37 31 29 30 32 33 33 34 34 34 33 30 27 25 23 22 21 21 22 23 25 27 33 33 33 31 28 28 29 31 38 43 51 59 65 66 66 64 54 47 39 33 32 34 36 37 40 39 37 33 29 27 28 29 35 36 38 41 43 43 40 37 37 39 44 48 50 46 40 34 30 27 25 28 34 37 35 32 30 28 26 27 30 32 33 33 36 38 43 49 54 54 50 45 39 35 29 24 21 21 22 24 22 23 24 24 25 28 32 35 41 43 46 45 41 36 33 31 34 33 34 36 39 40 40 39 39 38 36 33 30 27 25 23 25 28 33 38 41 43 43 42 40 38 34 30 26 22 19 17 18 19 21 23 25 26 26 26 28 29 31 34 36 37 38 38 36 35 33 29 26 25 27 29 35 42 48 54 60 65 63 58 53 48 40 33 30 27 25 24 24 23 21 20 18 18 17 17 19 20 23 26 29 32 35 36 38 39 40 40 38 36 34 32 31 30 29 27 25 23 23 22 22 21 20 19 18 18 18 18 18 17 16 15 14 12 11 11 11 11 10 9 8 8 9 9 13 12 12 12 11 11 11 10 11 10 10 10 9 9 9 8 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 14 14 14 14 14 14 14 14 14 14 14 15 15 16 16 16 17 16 17 17 18 20 21 22 25 25 26 27 29 30 31 31 32 34 37 40 42 45 50 53 57 61 66 71 74 78 82 85 87 93 101 108 115 123 132 139 152 158 168 178 188 201 215 225 242 250 255 255 254 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 254 252 255 254 241 219 194 178 172 172 163 161 153 142 133 125 115 105 108 103 98 92 82 70 65 66 76 94 119 143 160 164 154 141 116 96 88 96 107 125 142 144 142 127 108 94 83 78 81 87 105 118 135 149 164 175 178 176 152 132 106 87 75 71 75 82 87 88 91 95 100 103 103 101 91 87 80 74 73 78 88 95 104 108 107 97 86 80 76 72 70 65 60 59 57 53 54 58 59 65 69 69 71 74 72 68 70 70 69 68 66 61 55 50 45 43 40 40 46 55 65 71 77 78 78 77 73 68 63 60 58 55 53 52 54 55 55 55 57 57 55 53 49 44 40 38 39 40 43 50 57 62 65 65 59 54 48 44 42 41 40 40 42 43 45 46 46 49 52 55 70 87 105 116 122 118 99 79 49 38 28 29 38 47 55 60 61 54 44 36 32 32 33 33 32 32 31 30 28 26 24 23 23 22 21 21 22 24 26 27 33 33 34 33 31 31 33 35 40 45 53 61 66 69 68 67 57 49 39 31 28 30 33 35 38 38 36 32 29 27 28 29 32 34 38 43 48 48 46 43 40 40 41 42 42 39 34 29 30 29 29 33 37 39 37 33 29 27 26 27 30 33 34 34 35 37 41 46 49 48 43 40 32 30 27 24 23 24 25 27 27 28 28 28 29 32 36 40 46 50 53 54 51 47 45 43 43 43 44 47 49 50 49 47 44 42 38 34 29 26 23 22 24 27 33 38 41 42 41 39 35 33 30 26 22 19 17 16 18 18 19 20 21 21 22 22 22 24 28 31 34 36 37 37 33 33 30 26 22 21 22 24 32 40 49 56 64 68 66 59 56 50 41 34 30 28 28 27 27 26 24 21 19 18 17 17 18 20 23 26 29 32 34 35 36 36 35 35 34 32 30 29 29 28 27 26 24 23 22 22 20 19 19 18 18 18 19 19 18 17 16 15 14 13 12 12 12 11 10 10 9 9 10 10 14 13 13 13 12 12 12 11 12 11 11 11 10 10 10 9 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 13 13 13 13 13 13 13 13 14 14 14 14 15 15 16 16 16 16 16 17 18 19 20 21 23 24 25 26 28 29 30 31 30 33 37 40 43 47 52 56 59 62 67 72 75 78 82 85 88 94 103 110 117 125 135 143 158 165 175 185 195 207 220 229 243 252 255 255 254 255 255 255 255 255 255 255 255 255 255 255 254 254 254 254 254 254 254 254 255 254 251 250 252 254 255 255 247 236 216 191 169 154 148 147 144 140 134 126 119 112 104 97 98 94 91 87 78 68 64 65 79 96 122 145 161 164 153 139 111 93 88 97 107 123 138 139 134 119 102 89 80 76 81 88 105 117 133 146 158 169 171 169 152 132 107 87 75 70 73 80 81 82 83 85 86 87 85 84 77 76 75 75 77 84 93 100 111 114 112 102 92 86 81 76 75 68 62 59 55 52 52 57 59 65 69 71 75 80 80 76 74 72 69 66 63 58 51 46 40 39 38 41 46 55 63 69 74 74 74 72 68 61 55 51 51 50 51 55 61 66 68 69 68 67 65 61 55 49 43 40 41 42 45 50 56 60 61 60 54 50 45 42 41 41 40 39 43 46 49 50 50 50 50 51 61 75 93 105 112 108 92 75 48 39 30 32 43 55 65 70 70 62 51 41 36 35 35 35 36 35 33 32 30 28 27 26 23 23 22 22 23 24 26 28 31 32 33 33 32 32 34 36 39 44 51 59 65 68 68 68 60 52 39 30 26 28 30 32 36 36 34 31 28 27 28 30 31 34 40 47 53 55 54 51 47 44 42 40 38 36 32 30 31 31 33 36 39 40 37 34 28 27 26 28 31 35 37 37 35 37 39 42 42 40 37 34 29 28 28 28 29 30 30 31 31 31 31 30 29 32 37 40 49 54 60 63 63 62 60 60 59 59 60 61 62 60 56 53 47 44 39 33 28 24 22 21 23 27 32 38 41 41 39 38 33 31 28 24 21 19 18 17 19 19 18 18 19 19 20 20 19 22 26 30 34 36 36 36 34 33 30 26 21 20 21 23 31 40 51 59 67 72 68 61 57 50 41 33 30 30 30 30 30 29 26 23 21 19 18 17 18 20 24 28 31 33 33 33 33 33 31 30 28 27 26 26 26 25 25 24 23 22 21 20 17 17 17 16 16 17 18 19 18 18 17 16 15 14 14 13 13 13 12 11 10 10 11 11 14 14 14 13 13 13 12 12 12 12 12 11 11 11 10 10 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 13 13 13 13 13 13 13 13 14 14 14 15 15 16 16 16 16 16 17 18 19 19 19 19 22 23 24 26 28 29 30 31 30 33 37 41 44 49 54 58 60 64 69 73 75 78 82 84 89 95 104 113 120 129 140 147 166 173 183 193 201 211 222 229 241 250 255 255 254 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 254 254 255 255 255 254 251 228 211 188 168 156 147 140 134 132 126 120 113 106 98 90 86 89 85 83 81 75 67 65 68 84 101 124 144 158 161 149 135 110 94 93 102 109 121 133 133 125 111 94 83 76 75 82 91 101 112 126 136 147 155 157 154 142 125 104 89 78 71 71 75 76 76 75 74 72 70 69 69 68 70 74 78 84 93 102 109 116 119 116 106 98 93 87 82 78 70 62 58 54 50 52 57 60 67 73 77 82 88 89 86 81 77 70 64 59 53 47 43 39 39 40 43 48 55 60 64 71 71 72 70 65 58 51 46 47 48 51 58 68 76 80 82 78 76 73 67 61 53 48 44 43 44 47 51 56 58 58 56 52 49 45 43 43 43 43 42 46 49 53 54 52 49 47 46 52 62 76 88 96 94 81 68 49 43 37 40 52 67 76 79 77 68 55 44 39 37 37 37 40 39 38 35 33 31 30 29 25 24 23 22 23 24 26 27 28 30 32 32 31 31 33 34 38 43 50 58 64 67 68 68 62 53 40 30 26 26 28 30 32 33 32 30 28 28 30 32 34 37 43 51 58 61 61 59 55 51 46 41 39 38 36 34 33 34 35 37 39 38 35 33 28 27 27 29 33 37 40 40 38 38 39 38 35 33 31 30 30 32 34 36 37 36 35 34 32 32 30 29 28 30 35 39 51 57 66 73 76 76 77 77 81 80 79 79 77 71 64 59 49 45 39 32 26 23 21 21 23 26 32 37 40 41 40 39 36 34 30 26 23 22 21 21 21 21 22 22 22 22 22 22 20 22 26 30 33 35 36 37 36 35 32 28 23 22 23 25 32 41 52 61 68 72 68 60 54 48 39 32 30 31 31 32 31 30 27 24 21 19 18 17 20 23 27 31 34 35 34 34 32 31 28 26 24 23 23 23 22 23 23 23 23 22 20 19 16 16 16 15 16 16 17 18 18 18 17 17 16 15 15 15 14 14 13 12 12 12 12 12 14 14 14 13 13 13 12 12 12 12 12 11 11 11 10 10 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 14 14 14 14 14 14 14 14 15 15 16 16 16 17 17 17 16 17 18 19 20 20 19 19 22 23 24 26 28 30 31 32 33 36 40 44 47 52 57 61 63 67 71 75 77 80 83 85 92 98 108 117 125 135 146 153 173 181 190 199 205 213 221 227 234 244 253 254 254 255 255 254 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 255 251 254 255 255 255 249 237 229 205 188 166 152 148 144 135 127 127 120 112 106 98 88 80 78 78 75 74 74 71 67 68 73 90 103 122 138 150 152 141 129 112 97 97 105 109 117 126 124 113 100 85 77 73 76 85 96 101 110 121 128 134 140 139 135 123 110 96 85 77 69 67 70 71 70 67 62 58 55 56 57 64 68 74 81 90 100 110 117 119 120 118 110 104 100 95 88 79 71 62 57 52 49 51 56 60 69 77 83 89 95 95 92 88 81 70 59 52 46 41 38 40 41 43 47 51 55 58 60 67 69 70 69 65 59 52 47 46 47 51 58 69 78 85 88 84 81 76 69 62 55 51 48 48 48 51 54 58 59 57 54 52 49 46 45 46 47 46 46 48 51 55 55 52 48 45 43 46 51 60 71 79 79 72 64 51 49 47 51 64 79 86 85 80 71 57 46 40 38 39 39 43 42 42 40 37 35 32 31 27 26 24 23 23 23 24 25 27 29 31 32 31 30 31 32 38 42 49 56 63 66 68 69 61 52 40 30 25 24 25 26 28 29 29 28 28 29 32 35 38 40 45 52 59 64 65 65 60 56 49 44 42 42 41 40 36 36 37 37 36 34 32 30 29 28 28 31 36 41 43 44 43 42 39 34 30 27 28 29 35 37 41 44 44 42 38 36 31 30 29 28 28 31 37 42 56 63 74 83 88 90 91 91 99 98 97 94 89 81 71 64 48 43 36 29 24 22 22 23 24 27 31 36 40 42 43 43 42 39 35 31 28 26 26 26 25 26 28 29 29 28 27 26 24 25 27 29 31 33 35 36 36 35 32 28 24 23 25 27 32 41 51 59 65 68 64 56 48 43 36 31 30 31 32 32 31 30 27 24 22 20 18 18 22 26 31 36 39 38 37 35 33 30 27 23 21 21 22 23 22 23 24 25 24 23 22 21 19 18 17 17 17 17 17 18 18 18 18 17 17 16 16 16 16 15 14 13 13 13 13 14 14 13 13 13 12 12 12 11 12 11 11 11 10 10 10 9 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 14 14 14 14 14 14 14 14 16 16 17 17 18 18 18 18 17 18 20 21 21 21 20 19 22 23 25 27 29 31 32 33 38 41 45 49 52 56 61 65 68 71 75 78 80 83 86 88 96 103 113 122 131 141 152 160 177 184 193 200 204 209 215 220 226 238 249 253 254 255 255 253 255 255 255 255 255 255 255 255 254 254 254 254 254 254 254 254 250 250 249 245 236 222 207 196 179 166 151 143 142 139 132 125 127 118 109 104 96 84 76 75 72 69 68 69 69 69 74 81 95 106 120 132 141 143 134 122 112 99 99 106 106 111 116 113 101 89 77 71 72 78 91 103 109 116 121 122 122 121 117 110 103 93 82 76 70 64 62 64 64 63 59 54 49 49 52 56 66 70 76 83 91 100 109 116 116 117 115 109 105 103 98 91 82 73 62 55 50 46 48 53 58 68 79 86 93 98 97 93 85 76 63 51 43 39 37 36 40 42 46 50 54 57 59 60 65 67 70 71 68 62 56 52 48 47 49 55 64 74 81 84 85 81 74 67 60 55 52 50 54 54 56 59 62 61 58 55 51 49 47 47 48 50 49 48 47 50 54 55 52 48 45 43 43 43 47 56 63 66 63 61 54 56 58 63 76 90 93 89 80 71 57 46 40 39 40 41 46 47 47 46 43 40 36 34 30 28 26 24 23 22 23 23 27 30 32 32 31 30 30 31 34 38 45 53 59 63 65 66 57 49 38 28 23 21 21 21 24 25 27 27 28 30 35 38 40 41 45 51 58 63 66 66 61 56 50 45 44 44 44 44 38 38 37 35 32 29 28 28 30 29 29 33 38 43 46 47 48 45 40 32 25 24 27 30 40 43 47 50 49 44 38 34 28 29 29 29 31 37 44 50 64 72 83 92 97 99 100 100 105 104 103 100 94 84 72 64 45 41 33 27 22 22 23 24 25 27 30 35 39 43 46 47 47 44 39 34 31 29 29 30 28 31 34 37 38 36 33 31 28 28 27 26 28 30 32 34 33 32 30 26 23 22 24 26 32 40 48 54 59 62 57 49 42 38 33 30 30 31 32 32 30 29 26 24 21 20 19 18 25 29 35 40 43 42 39 37 34 31 26 22 20 20 22 23 23 25 26 28 28 27 25 24 23 22 21 20 19 19 19 20 19 18 18 18 18 17 17 17 17 16 15 14 14 14 14 14 13 12 12 12 11 11 11 10 11 10 10 10 9 9 9 8 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 15 15 15 15 15 15 15 15 17 17 18 18 18 19 19 19 18 19 20 22 22 21 20 19 23 23 25 27 29 31 33 34 42 45 49 52 55 59 65 68 71 74 78 81 83 85 88 90 100 107 117 126 135 146 157 165 176 182 191 197 201 204 209 213 221 234 247 252 254 255 255 253 255 255 255 255 255 255 255 255 250 250 250 250 250 250 250 250 252 245 233 220 206 193 180 173 158 151 143 139 137 135 130 126 125 114 105 101 92 79 72 71 71 68 67 69 70 73 80 88 100 109 119 129 137 139 131 120 112 99 99 105 104 106 109 105 92 81 71 68 71 81 96 109 119 123 124 119 112 106 97 89 90 81 71 67 63 59 58 61 57 57 54 50 48 50 57 63 72 75 79 84 89 96 104 109 111 113 110 105 103 102 97 90 85 74 63 55 48 43 45 50 56 66 78 87 94 98 97 92 78 69 55 44 38 37 37 38 40 42 47 52 57 59 60 60 64 66 70 72 70 65 60 56 49 48 48 52 60 69 75 79 84 79 72 64 57 53 51 51 58 58 60 63 65 64 60 57 51 49 47 48 49 51 50 50 45 49 53 54 52 48 46 45 40 37 39 45 53 57 57 57 56 61 64 70 83 96 97 90 79 70 57 46 40 40 41 43 50 51 52 52 49 45 40 37 31 29 27 24 23 22 22 22 28 31 33 33 32 30 30 30 30 34 40 48 54 58 61 62 53 46 35 27 21 19 18 17 22 23 25 27 28 31 36 39 42 42 44 49 56 62 65 66 60 55 49 45 44 45 45 45 39 39 37 33 29 26 26 26 31 30 30 34 40 45 48 49 51 48 40 31 23 22 26 31 42 46 50 53 51 45 37 32 27 27 28 30 34 42 51 57 71 78 89 98 103 104 105 105 103 103 101 98 92 81 69 61 43 38 31 25 21 22 24 26 26 27 30 34 39 44 48 50 50 47 42 36 33 31 31 31 31 34 39 42 43 41 38 35 31 29 26 25 25 27 30 32 30 29 27 24 21 21 23 25 31 38 45 50 55 57 52 44 37 34 30 29 30 31 31 31 29 28 25 23 21 20 19 19 27 31 38 43 45 44 41 39 35 31 27 22 20 20 22 23 25 27 29 31 31 30 28 27 27 26 25 23 22 22 21 22 19 19 18 18 18 18 18 17 17 16 15 15 14 14 15 15 12 12 11 11 11 10 10 10 10 10 9 9 9 8 8 8 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 13 13 14 14 15 16 17 17 17 18 20 21 22 21 20 19 20 20 21 22 22 23 23 24 26 27 29 31 35 38 41 43 44 47 51 54 57 60 65 68 73 77 81 83 85 89 96 101 106 113 124 133 141 150 160 167 173 175 181 189 192 194 200 208 214 220 231 242 250 253 253 252 253 254 255 253 247 241 236 234 230 227 223 221 221 221 220 219 213 209 200 188 175 163 153 147 135 132 128 126 124 123 120 118 112 108 102 95 86 79 73 70 67 67 68 70 75 81 87 91 94 104 113 118 122 127 124 117 105 101 99 99 101 99 92 86 78 70 64 67 76 91 111 127 136 146 147 136 122 109 92 76 73 66 62 64 65 61 58 57 57 55 51 49 50 54 59 62 71 74 78 81 84 89 94 98 102 106 108 106 104 103 98 92 85 77 64 51 42 41 44 48 54 63 77 89 96 94 88 83 74 60 46 39 36 33 34 37 42 47 54 58 58 57 58 60 59 64 71 74 74 71 68 67 50 47 43 44 49 57 64 67 73 67 61 57 52 49 53 60 60 62 65 68 69 66 62 58 53 50 48 48 50 50 47 44 45 47 50 51 48 46 45 44 36 38 40 42 44 48 54 58 62 66 73 80 85 88 89 90 74 64 52 45 40 37 40 46 46 48 51 52 50 46 40 37 31 27 23 19 19 22 26 29 35 35 35 34 33 30 27 26 26 29 35 43 50 54 55 54 46 40 32 25 22 22 21 21 20 21 22 25 29 34 39 41 41 44 48 50 51 52 54 56 52 48 43 42 44 46 47 46 43 40 35 30 28 27 27 28 27 29 31 34 37 42 48 53 50 48 42 33 25 22 26 30 41 50 58 58 50 40 34 32 31 32 35 42 48 53 59 64 85 90 97 104 106 104 99 96 96 92 88 85 81 72 58 47 37 32 25 22 22 24 24 23 24 26 29 35 42 49 55 59 56 52 47 41 36 33 32 31 36 38 42 47 49 47 42 37 29 26 23 22 23 25 26 26 25 24 22 21 20 21 22 22 26 33 41 44 47 49 46 40 34 30 26 25 27 30 33 34 29 27 24 21 19 19 20 21 29 33 40 45 48 47 44 42 38 34 29 23 20 19 21 22 25 27 30 33 35 35 35 34 33 32 31 28 26 24 22 21 23 22 21 20 20 20 20 20 18 18 17 16 14 13 12 12 12 12 11 10 10 9 8 8 8 8 8 8 8 8 8 8 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 13 14 14 15 16 17 17 17 17 18 20 21 21 21 20 20 20 21 21 22 23 23 24 24 27 28 29 32 35 39 42 43 46 49 53 57 59 63 67 70 73 77 82 85 87 92 99 105 113 120 130 137 144 152 161 167 172 173 178 185 187 188 193 200 201 207 217 227 234 236 236 236 235 234 232 229 224 219 213 210 202 198 194 192 191 191 190 188 183 179 172 162 150 140 131 127 119 116 112 109 108 107 105 103 99 97 93 87 80 74 69 67 65 66 69 73 78 84 89 92 95 103 110 112 115 119 116 110 103 99 96 95 95 91 84 77 70 63 60 66 79 98 121 139 155 164 165 151 133 116 94 76 70 63 59 62 63 59 56 56 58 57 55 54 55 58 61 64 67 69 71 73 75 79 84 88 97 102 105 104 102 100 95 88 80 74 64 53 46 45 47 50 54 62 74 85 91 89 83 78 67 55 42 37 36 35 37 41 46 51 56 59 60 60 61 63 62 65 71 76 78 76 72 69 53 47 41 38 40 46 52 55 62 57 53 51 48 46 50 56 63 65 68 71 71 68 63 59 54 51 48 48 50 51 49 47 46 48 49 49 47 45 45 46 39 40 41 42 43 47 53 57 61 65 71 77 82 83 83 82 67 58 47 41 37 35 38 45 47 48 51 51 49 45 40 37 32 28 23 20 20 24 29 33 38 39 40 39 37 34 30 27 23 25 29 36 43 46 46 45 39 33 26 21 19 19 19 18 19 19 21 25 30 35 40 43 43 45 47 47 46 46 47 49 45 42 39 40 44 48 50 51 48 45 39 33 29 27 27 27 28 29 31 32 34 38 45 49 47 44 39 30 23 22 26 31 42 49 56 55 47 38 33 32 33 36 43 52 60 66 73 77 88 92 97 100 99 95 88 84 80 76 72 70 67 59 48 39 34 29 24 22 22 24 24 23 23 25 29 35 42 49 55 58 56 53 47 41 36 32 30 29 35 37 42 47 49 46 40 35 26 23 20 20 21 22 23 22 25 23 21 19 18 18 19 20 24 31 38 41 43 45 42 36 31 28 25 25 28 31 33 33 31 28 25 22 21 21 21 22 29 34 40 45 48 47 44 42 38 35 30 25 22 21 22 23 27 29 32 34 36 36 36 35 38 37 36 34 32 29 28 27 25 24 23 22 22 21 21 21 18 18 17 16 14 13 12 12 12 12 11 10 10 9 8 8 8 8 8 8 8 8 8 8 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 14 14 15 16 16 17 18 18 18 18 19 20 21 21 20 20 21 21 22 23 24 25 25 26 28 29 30 33 36 40 43 44 49 52 56 59 62 65 69 72 72 77 83 87 91 97 105 112 121 127 135 141 146 151 158 163 167 167 170 175 177 176 180 185 190 195 203 211 216 218 218 217 215 210 204 200 197 193 186 181 171 168 164 161 159 158 156 155 152 148 142 134 125 116 110 106 99 96 92 89 89 88 87 85 83 82 80 77 73 68 65 63 62 64 69 75 81 87 90 93 94 99 103 103 105 108 106 103 102 98 93 90 87 82 74 68 65 60 60 68 83 105 132 152 175 185 185 169 148 125 99 77 67 60 56 58 60 57 55 55 60 60 59 59 60 61 63 64 63 63 63 63 64 68 75 79 92 98 102 101 99 97 90 83 72 69 63 58 54 53 54 55 57 62 70 79 83 82 76 71 59 48 38 36 38 40 43 48 53 57 61 63 64 65 66 67 66 67 71 77 83 83 79 74 59 52 42 35 34 37 40 43 50 46 45 45 44 42 46 53 64 67 71 73 73 70 65 62 56 54 51 51 52 53 53 53 49 50 50 48 45 44 45 46 43 43 42 41 42 45 50 54 57 61 67 72 74 74 71 69 56 48 40 36 33 32 36 42 46 47 49 49 47 43 38 35 31 28 24 22 24 30 37 42 47 48 50 49 46 40 33 29 21 22 25 30 34 37 37 36 31 27 22 18 18 18 19 18 17 18 20 24 30 37 43 46 47 47 46 43 40 37 37 38 37 36 36 39 46 52 57 59 57 53 46 39 33 29 28 27 30 30 29 28 28 32 38 43 43 41 36 28 23 23 29 35 43 48 53 50 42 35 33 34 39 46 56 65 72 78 82 84 88 90 92 92 88 80 71 65 59 56 53 51 50 45 38 32 30 27 24 22 23 24 24 23 23 26 30 37 44 50 55 58 57 54 48 41 35 30 27 26 32 36 42 47 49 45 37 31 22 20 19 19 21 22 22 21 25 23 20 17 16 16 16 17 21 28 34 36 38 39 36 30 28 26 25 27 30 32 33 33 32 30 27 24 22 22 23 24 30 34 40 45 47 47 44 42 39 36 31 27 24 23 24 25 29 31 33 36 37 38 37 37 41 41 40 39 37 34 32 31 28 27 27 26 25 24 23 23 18 18 17 16 14 13 12 12 12 12 11 10 10 9 8 8 8 8 8 8 8 8 8 8 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 14 15 15 16 17 18 18 18 18 18 19 19 20 20 20 20 22 22 23 24 25 26 27 27 29 30 31 34 37 41 44 46 51 53 57 60 63 65 69 72 72 77 84 89 94 102 111 118 125 130 137 142 144 147 152 156 159 157 159 164 165 164 166 171 178 182 188 193 197 198 197 196 194 186 177 172 170 166 159 153 146 143 138 134 133 131 129 127 126 123 118 111 103 97 92 90 84 81 78 76 75 75 74 73 71 70 69 67 64 62 59 58 58 62 68 75 82 86 88 89 91 92 94 95 97 99 101 101 105 101 95 89 83 76 68 63 67 64 65 73 88 110 138 159 186 196 198 183 160 134 105 81 65 58 54 57 59 57 56 56 63 63 63 63 62 61 59 58 55 55 55 55 57 63 72 78 91 97 101 100 97 93 85 77 66 65 65 65 67 67 66 65 64 66 69 74 78 76 70 65 53 43 36 37 43 47 53 58 62 64 67 69 70 71 72 72 70 69 71 78 85 88 83 78 68 60 49 40 36 36 38 39 44 42 41 43 42 41 44 50 60 64 69 73 73 71 69 68 62 60 58 56 56 58 59 59 56 55 53 48 44 42 43 44 44 44 43 40 39 41 45 48 51 55 59 63 64 61 57 54 45 38 32 31 30 29 34 40 44 45 45 44 42 38 35 33 28 26 25 26 31 39 48 54 61 62 63 61 55 46 37 31 23 23 23 26 29 30 29 28 26 23 20 19 20 21 22 22 17 17 20 24 30 38 45 49 51 50 47 41 35 32 31 32 32 33 36 42 50 57 64 67 66 61 54 45 38 33 31 30 32 31 28 25 24 26 31 35 38 37 33 28 24 25 32 39 44 47 48 44 36 32 34 37 50 60 71 76 77 78 78 75 79 80 81 79 72 63 53 47 42 40 38 38 39 37 34 31 27 26 25 24 25 25 25 25 26 29 35 41 47 52 56 58 56 53 47 41 34 29 25 24 31 34 41 46 48 43 34 27 20 19 20 22 26 28 28 28 29 26 22 18 16 15 16 17 19 26 31 32 33 34 31 25 26 26 27 29 33 35 35 33 33 31 28 25 23 23 24 25 30 33 38 43 45 45 43 41 38 36 32 28 26 25 26 27 31 32 34 36 37 38 38 38 40 41 41 40 39 36 34 33 31 31 30 29 27 26 24 24 18 18 17 16 14 13 12 12 12 12 11 10 10 9 8 8 9 9 8 8 8 8 7 7 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 14 14 15 16 16 17 18 18 18 18 18 18 19 19 20 20 22 23 24 25 26 28 29 29 30 31 33 35 38 42 45 47 51 53 57 60 62 65 68 71 73 78 85 91 96 104 113 121 127 133 139 143 143 144 147 151 152 149 150 155 157 156 157 160 163 165 168 171 172 172 171 170 167 159 149 144 142 139 132 127 122 118 113 110 108 106 103 102 102 99 94 88 82 77 74 72 73 71 69 68 68 68 66 64 61 60 58 56 54 53 52 51 56 60 67 74 79 81 82 81 83 83 84 88 92 96 100 104 109 105 99 92 85 77 70 65 70 68 71 79 93 113 140 161 191 202 204 189 166 139 107 82 64 57 53 56 59 58 58 59 64 64 64 63 60 56 52 50 45 46 47 49 55 64 76 83 96 102 104 101 96 90 80 71 62 64 68 74 80 83 81 79 75 73 71 72 74 73 67 61 51 43 38 42 49 56 62 68 70 72 74 76 78 79 78 77 73 70 70 75 83 86 84 80 73 66 57 49 45 44 43 43 43 40 40 41 40 38 42 48 54 59 65 69 71 72 74 76 71 70 68 66 64 64 65 65 64 62 57 50 44 40 40 41 43 43 42 40 38 37 40 42 44 47 50 52 52 49 44 41 37 31 27 28 29 29 34 40 42 42 41 39 37 34 31 29 26 26 27 32 40 50 60 67 75 75 75 72 64 52 40 33 25 23 21 21 23 24 23 22 22 20 19 19 22 24 24 24 18 19 20 24 30 37 45 49 53 51 46 40 33 30 31 32 35 38 42 47 54 61 68 72 72 67 59 50 43 38 36 35 34 33 30 25 22 23 26 29 33 33 31 27 25 27 34 40 45 46 44 38 31 31 36 43 61 73 83 83 78 75 69 62 64 64 65 63 57 48 40 34 29 29 30 31 33 35 34 34 29 29 28 28 27 27 28 29 33 36 41 47 51 54 56 56 53 50 46 40 34 29 25 23 30 33 39 45 45 40 31 24 19 21 24 30 36 40 41 40 35 32 27 22 18 17 18 19 19 25 30 30 31 33 29 24 27 27 28 31 35 36 36 34 33 31 27 24 23 23 24 24 28 31 36 40 42 41 39 38 36 34 31 28 26 26 26 27 30 31 32 34 35 35 36 36 39 40 41 41 40 38 36 34 32 32 32 31 29 27 24 23 18 18 17 16 14 13 12 12 12 12 11 10 10 9 8 8 9 9 9 8 8 7 7 7 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 13 13 14 14 15 16 17 17 18 18 17 17 18 19 20 20 23 23 25 26 28 29 30 31 31 32 34 36 40 43 46 48 51 53 57 60 61 64 67 70 74 79 86 91 96 104 113 120 128 133 140 143 143 143 145 148 148 144 143 148 150 149 148 150 150 151 152 152 152 150 149 148 142 136 129 124 121 117 112 108 104 101 96 92 90 88 86 84 84 82 77 72 68 65 64 63 65 65 64 65 66 64 61 58 55 53 50 47 46 46 48 49 58 61 67 72 75 75 74 72 75 73 76 83 89 95 101 108 112 109 103 95 87 80 75 72 72 72 75 83 94 111 136 157 187 198 202 187 164 136 104 79 64 56 52 56 59 60 60 62 63 63 62 60 57 52 47 44 38 40 44 50 59 71 84 93 106 109 109 102 94 85 74 64 59 62 70 81 92 97 96 93 87 80 74 72 73 71 65 60 54 46 42 47 56 63 70 75 77 78 81 84 87 86 83 80 74 71 69 70 75 79 80 79 75 71 66 61 58 54 50 48 43 40 39 39 38 37 41 48 52 56 62 65 68 71 78 83 82 83 82 79 74 71 70 70 68 66 61 53 46 41 40 40 42 43 44 42 39 37 37 37 39 41 42 43 42 40 37 35 33 28 26 29 30 31 36 42 42 41 39 36 33 31 29 28 26 28 32 40 49 60 69 75 83 83 82 77 68 56 44 37 26 23 19 18 18 18 18 17 18 17 18 20 23 25 25 25 22 21 22 24 29 36 43 48 50 48 44 38 33 33 35 38 43 46 50 53 57 61 66 70 72 67 60 52 45 41 39 39 38 38 35 31 27 25 26 28 29 31 31 30 28 30 36 41 46 45 40 33 27 30 40 49 69 83 92 86 77 70 61 51 47 48 50 49 45 38 31 27 22 24 27 31 34 37 38 39 34 34 34 32 30 30 33 35 40 43 48 52 54 55 53 52 48 47 43 39 34 29 26 24 30 33 38 42 42 37 29 22 21 23 29 37 45 50 51 51 42 38 31 25 21 20 20 21 21 27 31 31 32 34 31 27 28 28 28 31 34 36 35 34 31 29 26 23 21 21 22 23 25 28 32 35 37 37 35 34 32 31 29 26 25 25 25 25 28 28 29 30 30 31 32 32 38 39 41 42 41 39 37 35 33 33 33 32 29 26 23 21 18 18 17 16 14 13 12 12 12 12 11 10 10 9 8 8 10 10 9 8 8 7 6 6 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 12 12 12 13 14 15 15 16 18 18 17 17 17 18 20 21 23 24 25 27 29 30 31 32 32 33 35 37 40 44 47 49 52 54 58 60 62 64 68 70 75 80 86 91 95 102 111 117 124 130 137 140 140 140 141 144 143 137 135 138 140 137 135 136 137 137 136 134 132 130 129 127 118 116 112 107 102 98 95 94 91 87 82 79 78 76 74 73 70 68 65 62 60 59 60 60 62 63 65 67 68 65 60 56 54 51 47 44 44 47 51 54 63 65 69 71 72 70 67 65 67 65 69 79 88 93 101 109 111 108 104 97 89 83 79 77 77 77 81 86 92 104 125 143 169 182 187 175 154 129 99 75 62 55 51 54 59 59 60 63 59 59 59 57 54 50 46 44 40 43 50 58 69 83 97 106 115 116 113 102 90 80 68 57 57 61 70 85 99 106 106 103 95 86 76 71 71 69 64 58 57 49 46 51 60 67 73 79 82 83 86 91 94 92 87 82 75 72 68 65 66 70 75 78 79 78 77 75 72 66 59 54 46 42 40 41 40 40 46 54 53 57 61 63 65 70 80 87 93 94 94 91 84 77 74 73 69 67 63 56 49 44 42 42 42 44 46 46 42 39 36 36 37 37 38 38 37 36 34 33 32 29 28 31 33 34 38 44 43 42 39 35 32 30 29 29 30 33 39 47 57 66 73 77 83 83 82 77 69 58 48 41 29 26 21 18 18 18 18 18 19 19 20 23 27 29 29 28 26 24 23 24 28 35 41 45 45 43 40 36 34 36 41 45 52 55 57 58 57 58 61 64 67 63 57 50 45 42 41 41 44 44 43 39 34 31 30 31 33 36 39 39 37 38 42 46 46 43 37 29 25 31 44 56 75 90 96 86 71 61 49 37 36 37 39 40 37 33 27 24 22 25 31 36 40 43 45 47 41 41 39 36 33 33 37 41 46 48 52 55 55 53 49 47 44 43 40 38 34 31 28 26 31 33 36 39 39 35 27 21 23 26 33 42 50 55 56 55 46 42 35 27 23 21 21 22 24 29 33 34 35 37 35 31 29 27 27 28 31 33 32 31 29 27 23 21 19 19 20 20 22 24 28 31 32 32 31 30 29 28 26 25 24 23 23 23 25 25 25 25 26 27 28 29 34 35 38 39 39 37 34 32 32 32 32 31 29 25 21 19 18 18 17 16 14 13 12 12 12 12 11 10 10 9 8 8 10 10 9 8 8 7 6 6 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 11 11 12 12 13 14 15 15 19 18 17 16 17 18 20 21 24 24 26 27 29 31 32 33 33 33 35 38 41 45 48 49 53 56 59 61 63 65 68 71 76 80 86 90 94 100 109 115 119 125 132 136 136 135 137 139 138 131 128 130 131 127 123 123 123 122 120 118 115 113 111 110 98 97 96 91 86 81 79 79 78 75 70 68 66 65 63 62 57 55 53 52 51 53 55 56 62 64 67 71 72 68 62 57 57 53 49 46 47 52 58 63 67 69 70 71 70 67 64 62 64 61 66 77 86 91 100 109 109 107 103 96 89 84 81 80 84 83 85 88 89 96 113 129 150 164 171 162 145 123 96 73 61 54 50 53 58 59 60 63 57 57 56 55 53 50 47 46 45 50 57 67 79 94 108 117 120 121 114 101 88 76 63 53 55 59 70 86 102 111 111 108 99 89 77 71 70 68 63 57 58 51 48 53 61 68 74 79 84 85 89 95 98 96 89 82 75 72 67 62 60 64 71 76 84 84 85 86 83 75 66 59 50 46 44 44 44 46 53 62 57 60 62 63 64 70 80 89 99 101 102 98 89 81 76 75 67 66 63 58 51 47 45 45 42 46 49 49 45 41 37 36 36 36 36 36 35 35 35 35 33 29 29 33 36 36 40 46 45 43 40 36 33 31 30 30 33 37 44 52 61 68 74 76 81 81 80 76 68 59 50 44 34 30 25 21 21 21 21 21 22 23 24 28 32 34 33 32 28 26 25 25 28 33 40 44 40 39 36 34 33 37 44 49 58 60 61 60 57 55 57 59 62 59 53 48 44 42 42 42 48 49 48 45 40 36 34 34 39 43 47 48 47 47 50 53 46 43 36 27 24 31 47 59 79 94 98 83 64 51 37 23 31 33 35 36 34 30 26 23 25 30 36 42 47 50 52 54 45 45 43 38 35 35 40 45 48 51 54 56 54 51 46 43 41 40 39 37 34 32 29 28 31 33 35 37 37 33 26 21 24 28 35 44 52 56 57 55 48 44 36 28 23 21 21 22 25 31 35 35 37 40 38 34 28 27 25 26 28 30 30 29 27 25 22 19 17 17 18 19 20 22 25 28 30 30 29 28 27 26 25 23 22 22 22 22 22 22 22 22 23 24 25 26 28 30 33 35 35 33 30 28 32 32 32 31 28 24 20 17 18 18 17 16 14 13 12 12 12 12 11 10 10 9 8 8 10 10 9 8 8 7 6 6 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 12 12 11 12 13 14 15 16 16 16 16 16 16 17 19 19 24 25 27 30 32 33 34 34 37 37 37 39 42 45 49 51 55 57 59 60 61 64 68 72 74 78 83 89 94 99 105 109 118 119 123 126 128 129 130 130 128 123 117 116 118 118 115 111 110 107 103 99 96 95 95 95 86 83 78 75 74 74 72 70 68 68 68 66 63 59 55 52 51 52 52 50 48 50 55 60 61 65 71 76 77 73 66 61 54 53 51 50 54 61 69 74 83 86 88 85 76 67 61 58 59 60 63 71 80 89 94 96 101 101 99 95 89 84 82 82 85 88 88 85 83 90 104 116 131 143 152 148 132 110 86 69 56 56 56 58 62 64 65 64 63 62 60 58 56 55 54 54 57 60 66 77 90 101 109 113 115 111 104 94 83 71 61 56 51 55 66 82 98 107 108 106 98 88 76 68 66 64 61 58 51 51 51 50 52 57 65 70 78 82 88 92 94 92 89 86 70 66 59 55 54 58 64 68 76 86 96 98 95 86 72 59 49 44 40 44 54 65 71 72 74 71 64 60 60 67 78 86 98 106 110 103 92 83 75 69 65 62 58 55 54 53 52 50 51 51 51 50 48 44 40 37 37 37 36 35 35 35 36 36 33 33 33 34 36 39 41 43 44 42 39 37 35 34 34 34 37 42 48 54 59 63 67 69 69 70 70 67 61 53 45 40 35 33 29 26 23 21 21 20 23 25 28 31 32 32 32 31 28 24 21 22 26 32 37 40 42 38 33 30 32 41 54 63 66 68 66 60 52 45 42 43 47 48 48 45 41 39 42 46 49 53 56 54 49 45 44 45 47 51 55 58 59 59 59 60 52 42 32 25 24 31 48 65 83 90 92 79 57 37 28 27 27 32 38 40 38 33 30 28 30 36 44 50 53 54 55 56 51 47 41 36 35 37 40 43 51 54 57 54 47 40 37 36 32 34 36 36 34 32 31 32 35 37 38 39 37 33 28 25 24 26 31 40 48 50 48 45 38 35 30 25 23 23 25 26 33 34 37 42 44 44 41 37 32 31 28 26 24 23 23 24 22 20 18 16 15 16 17 19 19 21 23 26 28 28 28 28 26 25 24 23 21 20 19 18 19 19 19 19 20 21 22 22 28 29 30 31 31 30 29 28 27 27 28 27 25 21 18 15 15 15 15 14 14 14 13 13 11 11 11 10 10 9 9 9 12 11 10 9 7 6 5 4 7 7 7 6 6 5 5 5 6 6 6 5 5 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 12 12 12 12 13 14 15 16 16 16 16 16 17 18 19 20 25 26 28 31 33 34 35 35 37 37 38 39 42 45 49 51 55 56 58 59 60 63 67 70 72 76 82 87 91 96 102 106 112 114 117 120 122 123 123 123 122 117 111 109 110 110 106 102 102 100 96 92 89 87 86 86 80 77 73 71 70 70 68 67 66 66 65 63 59 55 51 49 46 47 48 47 46 49 55 60 67 71 76 80 80 75 68 63 56 56 56 59 65 75 85 92 101 103 103 97 85 73 64 59 60 60 62 68 76 82 86 87 94 94 93 90 85 82 81 81 86 89 89 85 82 86 96 106 117 128 136 131 118 101 81 66 57 57 58 62 66 69 69 68 69 68 66 64 62 61 60 59 64 66 71 80 91 101 107 109 107 104 97 89 78 68 60 55 52 54 62 76 90 99 101 99 91 81 69 60 57 56 53 51 47 47 46 45 46 50 56 61 72 77 84 90 91 89 84 81 67 63 56 51 49 52 56 59 71 82 92 95 92 84 70 57 48 44 43 49 61 73 81 83 86 80 70 60 56 60 69 76 90 100 105 100 89 79 70 63 60 58 55 54 54 55 55 54 58 57 56 54 50 46 42 40 37 37 36 36 36 36 36 36 34 33 33 33 34 37 39 40 40 39 37 35 34 34 34 35 40 44 49 52 54 55 57 59 57 58 58 56 52 46 40 36 35 33 30 27 25 23 22 22 23 25 27 30 31 31 30 30 27 24 21 21 26 31 36 38 41 38 33 30 32 41 54 63 69 69 66 58 47 38 35 35 39 42 44 42 40 39 42 45 49 53 56 55 50 47 47 48 51 54 58 60 60 60 61 62 53 44 33 27 25 32 50 66 79 85 85 73 51 34 27 28 32 37 43 45 41 35 31 29 30 36 44 50 53 53 53 54 50 46 41 36 35 37 40 43 50 52 53 48 39 33 30 30 32 34 37 38 36 35 34 34 35 37 38 39 36 32 28 25 24 25 29 36 42 44 41 38 32 30 26 24 22 23 24 26 34 36 40 46 50 51 48 45 37 35 32 28 25 23 22 22 20 19 18 16 16 17 18 18 20 22 24 26 26 26 26 25 25 24 23 22 21 20 20 19 19 19 19 19 19 20 21 22 26 27 28 29 29 28 27 26 25 26 26 25 23 20 16 14 15 15 14 14 13 13 13 13 11 11 11 10 10 9 9 9 11 11 10 9 7 6 5 5 7 7 7 6 6 5 5 5 6 6 6 5 5 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 12 12 12 12 13 14 16 16 17 17 17 17 18 19 21 21 26 28 30 32 34 36 36 37 38 38 39 40 42 45 48 50 54 56 58 59 59 61 65 68 71 74 79 84 87 92 97 100 103 104 107 110 112 112 112 112 112 107 102 100 99 98 95 91 91 90 87 84 81 77 75 74 72 69 67 66 66 66 65 64 64 63 61 58 54 50 46 44 44 44 45 46 49 53 60 65 72 75 79 80 78 73 67 62 59 61 65 70 79 91 103 111 120 121 119 112 99 84 71 65 63 62 62 65 70 74 75 75 83 84 85 83 81 79 79 80 87 89 90 86 82 81 87 93 106 115 121 117 108 96 81 69 58 59 62 68 73 76 77 76 79 78 76 74 72 70 68 68 71 72 74 80 88 94 98 100 94 91 87 80 72 65 59 55 52 53 57 66 77 85 89 89 83 74 61 52 48 46 45 43 45 44 43 41 40 43 48 53 65 71 79 86 87 83 77 73 63 59 53 48 45 45 48 50 64 75 86 89 87 80 66 54 45 45 47 56 71 86 95 99 97 88 74 60 52 53 59 65 79 89 96 94 85 75 64 55 53 51 50 51 54 58 59 59 63 61 58 54 49 45 41 40 37 38 38 38 37 36 35 34 33 33 32 31 31 33 34 35 35 34 33 32 32 33 35 36 43 45 48 48 46 44 43 44 42 43 43 43 42 39 37 35 35 34 31 29 26 25 24 23 23 24 26 28 29 29 29 28 26 24 21 22 27 32 37 39 41 38 34 31 34 43 56 65 73 72 66 55 41 30 26 25 30 34 39 40 38 37 40 42 46 49 53 52 50 48 50 52 54 56 59 60 60 60 61 63 53 44 34 28 27 34 50 66 74 77 75 62 43 30 27 30 40 45 51 51 45 38 33 31 31 37 45 50 52 51 49 49 47 43 39 35 34 36 39 41 48 48 46 39 30 24 22 23 32 35 39 41 40 39 38 38 36 37 39 39 37 33 29 26 23 24 26 30 33 33 30 28 24 23 23 23 23 24 25 26 33 35 41 49 55 58 56 54 46 43 38 32 27 23 21 20 18 18 18 19 19 20 20 20 23 24 25 26 25 24 23 22 23 23 22 22 21 21 20 20 19 19 18 18 19 19 20 21 24 24 25 26 26 25 24 24 23 23 23 22 20 17 15 13 14 14 13 13 13 12 12 12 10 10 10 10 9 9 9 9 11 10 10 9 7 6 6 5 7 7 7 6 6 5 5 5 6 6 6 5 5 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 13 12 12 13 13 15 16 17 17 17 17 18 19 21 22 23 28 29 31 34 36 37 38 38 39 39 39 40 42 45 47 49 53 55 58 59 59 60 63 65 69 72 76 79 82 85 90 93 92 94 96 99 100 100 100 100 99 96 92 91 90 89 86 84 83 82 80 78 74 70 67 65 65 64 62 63 65 66 65 64 64 62 59 55 50 47 44 42 45 46 48 51 56 62 68 73 73 75 76 75 71 65 60 58 62 67 74 81 90 102 114 123 132 132 131 124 112 97 83 74 68 66 65 65 66 67 67 66 72 74 76 76 76 76 78 79 85 88 90 88 83 80 81 84 96 104 110 108 102 93 81 69 62 64 68 74 81 85 86 86 89 88 87 84 81 78 76 74 73 73 73 75 79 83 84 85 80 78 75 71 67 62 59 57 53 51 51 55 62 70 74 76 77 68 56 47 42 40 39 38 44 44 43 42 41 42 46 50 60 66 75 81 82 77 70 64 58 55 50 46 44 43 44 45 57 67 78 82 81 74 62 50 42 44 50 62 78 93 104 110 100 91 76 60 49 48 52 58 67 78 87 86 80 71 59 49 46 45 45 48 54 59 62 63 64 61 56 50 45 41 39 38 39 40 40 40 39 37 34 33 31 30 28 27 27 28 29 30 30 29 29 30 31 33 36 37 43 44 45 43 38 34 32 32 32 32 33 34 35 36 37 37 34 33 31 29 27 26 25 24 23 24 26 27 28 27 27 27 24 22 21 24 30 37 42 44 45 42 37 35 37 47 60 70 79 76 68 54 38 26 20 20 26 31 37 39 37 35 36 37 39 42 45 46 44 45 48 52 53 55 56 55 54 53 55 57 50 42 34 29 28 33 48 63 68 69 65 52 37 28 29 34 47 53 59 57 49 40 35 34 33 39 46 50 50 47 44 42 41 38 34 31 30 32 35 38 43 42 39 32 23 19 20 23 33 37 43 46 45 43 41 41 38 39 40 40 38 34 30 28 23 23 23 23 23 22 21 19 19 21 23 26 28 29 30 30 31 34 40 49 57 62 62 61 56 52 46 39 32 26 23 21 19 20 21 23 24 25 25 25 27 27 28 27 26 24 21 20 22 22 21 21 21 21 21 21 19 18 18 18 18 18 19 20 21 21 21 22 22 21 21 21 20 20 20 19 17 15 13 11 13 13 12 12 11 11 11 11 10 9 9 9 9 9 9 9 10 10 9 8 8 7 6 6 7 7 7 6 6 5 5 5 6 6 6 5 5 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 13 13 13 13 14 15 16 17 18 18 18 19 20 22 24 25 29 30 32 34 36 38 39 39 40 39 39 39 41 43 45 47 52 55 57 58 58 58 60 62 65 68 71 73 75 77 81 83 82 83 86 87 88 88 88 87 86 85 83 83 83 83 81 79 77 76 74 72 68 65 61 60 61 60 60 62 65 67 67 66 65 62 58 53 49 46 44 43 47 48 52 57 64 70 75 78 75 75 73 68 62 57 55 55 63 71 82 92 101 111 122 131 139 139 138 133 122 107 91 81 73 70 67 65 65 64 62 60 63 65 68 70 71 72 75 77 81 85 89 88 84 80 79 79 85 93 99 100 96 89 76 64 66 68 72 79 87 92 94 94 97 96 94 91 87 82 78 76 72 70 69 69 71 72 72 71 67 67 65 64 62 61 60 59 53 50 47 46 50 56 61 65 68 62 52 44 38 35 34 34 41 43 45 46 46 47 50 52 61 66 72 77 76 70 62 57 48 47 45 43 41 41 41 42 50 60 69 73 72 67 56 46 38 42 50 62 77 92 103 109 98 90 76 60 48 43 45 48 57 67 76 78 75 68 57 48 43 42 43 47 53 58 62 63 62 58 52 46 42 40 39 39 43 44 45 44 42 38 33 31 26 25 24 23 23 24 26 27 28 28 28 29 31 34 36 38 40 41 41 38 33 29 26 25 24 25 26 28 31 34 36 37 32 32 31 30 29 27 26 25 25 25 26 26 26 26 26 26 22 22 22 27 34 42 48 50 49 46 41 38 41 50 63 73 83 79 69 54 37 25 21 20 28 33 38 39 35 31 30 31 29 32 35 36 36 38 43 48 50 50 49 46 43 42 43 45 43 38 32 29 28 31 44 56 62 61 55 43 32 27 33 39 52 58 63 60 50 41 38 38 38 42 47 49 46 42 38 36 33 31 28 26 25 27 30 33 37 36 33 28 22 21 24 29 37 42 48 51 50 47 44 42 40 40 41 40 38 35 31 29 23 22 21 19 17 16 16 16 20 23 29 33 36 37 36 35 33 35 41 49 57 64 66 67 63 59 52 44 36 30 26 24 21 22 25 27 29 31 31 32 32 33 32 31 29 26 23 21 21 21 21 21 21 21 20 20 19 18 17 17 17 17 18 18 19 19 18 18 18 18 19 19 18 18 17 16 15 13 11 10 11 11 11 11 10 10 9 9 8 9 9 9 9 9 9 9 10 10 9 8 8 7 6 6 7 7 7 6 6 5 5 5 6 6 6 5 5 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 13 13 13 13 14 15 17 17 19 19 19 20 22 24 25 27 29 30 32 34 37 38 39 39 39 39 38 38 39 41 43 44 49 52 54 55 55 54 56 57 59 61 64 65 66 67 70 72 72 73 75 76 77 76 76 75 74 75 75 76 75 75 74 73 69 68 65 63 60 57 56 55 56 56 57 61 65 68 68 67 66 62 57 52 48 46 45 46 49 51 57 64 72 77 79 79 78 76 71 62 54 51 53 57 64 75 90 101 108 115 124 130 137 138 137 134 124 109 92 81 73 70 66 64 62 61 58 56 56 58 61 64 65 67 70 73 78 82 86 87 84 80 77 76 80 87 92 94 93 88 77 66 68 69 72 79 87 94 97 98 101 100 97 93 87 81 76 73 68 66 63 62 63 63 62 60 57 56 56 56 57 58 60 61 54 50 45 41 42 46 52 56 60 56 49 42 37 33 31 31 36 40 47 52 55 56 58 60 66 68 70 70 67 61 55 51 39 39 39 39 39 38 38 37 44 52 59 61 60 57 49 40 34 39 47 58 70 82 91 96 93 87 76 62 49 41 38 38 48 57 65 67 68 65 57 49 43 42 42 45 51 56 58 59 58 53 47 42 39 40 42 44 48 49 50 49 45 39 33 29 22 22 21 21 22 24 26 28 30 30 30 30 32 34 37 38 39 40 40 36 31 26 23 22 19 20 22 25 28 31 33 34 32 32 32 32 31 30 28 27 27 26 26 26 26 26 25 25 22 22 24 29 37 45 51 53 50 47 42 38 40 49 62 71 79 75 65 51 36 26 23 24 31 35 39 37 32 27 25 25 22 25 28 28 29 32 39 45 47 46 43 38 33 31 32 33 37 33 31 30 29 30 39 50 55 53 47 37 28 27 35 43 54 60 64 59 49 41 40 43 44 47 48 47 42 36 32 29 27 26 23 22 22 24 27 29 31 32 31 27 23 24 30 35 42 47 53 56 54 49 44 41 39 39 39 38 36 33 31 29 23 22 20 17 14 14 16 18 24 29 36 43 46 45 42 40 37 37 40 46 54 62 66 68 64 60 54 46 39 34 30 28 24 25 27 29 32 35 37 38 39 39 38 36 34 30 27 25 22 22 21 21 20 20 19 19 18 18 17 16 16 16 16 17 17 17 16 16 16 16 17 17 17 16 15 14 13 12 11 10 10 10 10 9 9 9 8 8 8 8 8 8 9 9 9 9 9 9 9 8 8 7 7 7 7 7 7 6 6 5 5 5 6 6 6 5 5 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 14 13 13 14 14 16 17 18 19 19 20 21 23 25 27 28 28 30 32 34 36 38 38 39 39 38 37 37 37 39 41 42 45 47 50 51 50 49 50 51 52 54 56 56 56 57 59 60 63 64 65 66 67 66 65 64 65 67 68 68 67 65 64 64 58 57 54 51 49 48 48 48 49 50 53 58 63 66 67 66 65 61 56 51 47 46 47 47 55 58 64 73 82 85 84 81 79 76 67 56 46 45 51 58 70 82 97 106 108 108 111 115 121 122 123 123 117 104 88 77 68 65 62 59 58 57 54 52 50 53 56 58 59 61 64 66 76 79 83 84 82 77 73 71 75 80 83 84 86 86 78 69 68 68 69 75 83 91 96 99 102 100 97 92 85 78 71 67 60 57 54 53 54 54 52 51 48 48 49 50 53 56 58 60 55 51 45 39 38 41 46 51 56 55 51 46 40 36 33 32 33 41 52 62 67 70 71 72 71 70 67 64 58 53 48 45 36 37 38 39 39 37 36 35 38 45 49 49 49 47 40 33 31 35 43 51 60 68 75 79 80 78 72 62 51 43 38 36 41 48 54 57 60 62 58 51 46 44 43 45 49 52 54 54 49 45 40 35 34 38 43 46 53 54 54 53 47 40 32 27 20 20 21 22 24 27 30 32 34 33 32 32 33 35 37 38 39 40 40 36 30 25 22 21 19 20 23 26 28 30 31 32 34 35 35 35 35 33 32 31 29 28 27 26 26 26 26 26 24 24 25 30 38 45 49 51 48 44 39 34 36 44 56 65 71 67 58 45 33 25 25 27 32 35 38 35 29 23 22 22 20 22 24 25 25 30 38 44 47 45 40 32 26 23 23 25 32 31 31 33 31 31 37 45 49 46 40 31 25 27 36 44 53 59 62 57 46 40 42 47 50 51 50 45 38 31 27 25 24 23 21 20 20 23 25 27 28 30 30 27 25 27 33 39 47 52 58 60 57 50 43 40 37 36 36 35 32 30 28 26 22 22 20 16 14 15 20 24 29 35 43 50 53 51 46 43 37 35 35 38 46 54 60 63 61 58 52 46 40 35 32 31 25 25 27 29 33 37 41 43 44 44 43 42 39 35 32 29 23 22 22 21 20 19 18 17 18 18 17 16 15 15 16 16 17 16 15 14 14 15 16 17 17 16 15 13 12 11 11 11 9 9 9 9 8 8 7 7 7 7 7 8 8 9 9 9 9 9 8 8 8 8 7 7 7 7 7 6 6 5 5 5 6 6 6 5 5 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 14 14 14 14 15 16 17 18 19 20 20 21 23 25 27 28 28 29 31 34 36 37 38 38 38 37 36 36 36 38 40 41 41 44 47 48 46 45 46 46 46 48 50 50 49 50 51 53 57 58 59 60 60 60 58 57 61 62 63 63 60 58 57 56 51 49 45 42 41 40 41 42 45 46 49 54 60 64 64 64 64 60 55 50 47 46 47 48 61 64 71 81 90 92 89 85 78 74 63 50 40 40 48 57 76 88 101 107 103 98 96 96 101 103 108 111 109 99 85 74 64 61 57 55 54 53 51 49 47 49 52 54 55 57 60 62 75 78 81 81 79 75 70 67 66 69 70 71 75 78 74 67 67 66 67 71 80 88 95 98 101 100 97 91 83 75 67 63 51 49 46 46 46 46 45 43 43 43 44 46 49 53 57 59 55 51 45 39 36 38 44 48 57 57 55 51 45 40 37 36 34 44 58 71 78 81 82 82 74 71 65 59 52 47 43 41 39 40 41 42 41 39 36 35 34 40 43 42 41 40 35 29 29 33 40 46 52 58 63 67 67 68 67 62 54 46 41 39 37 43 48 51 55 59 57 52 48 46 45 45 47 50 51 50 42 38 32 29 29 34 41 45 56 57 57 55 49 40 31 26 20 20 21 23 26 30 33 35 36 35 34 33 34 35 37 38 41 42 41 37 31 25 21 20 21 23 26 29 31 32 32 32 36 37 38 38 38 36 35 33 30 29 28 27 26 26 26 26 26 25 26 30 37 43 47 48 45 41 35 31 31 39 51 60 64 61 52 41 30 24 26 29 32 34 36 32 26 21 20 21 20 22 24 24 25 30 38 45 49 46 39 31 23 20 20 21 30 30 32 35 33 31 36 43 44 42 35 28 23 26 35 44 52 57 60 54 44 39 43 49 54 53 50 44 35 28 24 22 23 22 21 20 21 23 25 27 27 29 30 28 26 28 34 39 50 55 61 63 58 50 43 38 34 34 33 32 29 27 25 24 22 22 20 17 14 16 23 28 32 38 47 55 57 54 48 44 34 31 29 30 37 45 52 56 58 55 50 44 39 35 33 32 25 25 26 28 32 37 42 45 47 47 47 45 42 38 35 33 24 23 22 21 19 18 17 16 18 17 16 15 15 15 15 15 16 16 14 13 13 14 16 16 16 16 14 13 12 11 11 11 9 9 8 8 8 7 7 7 7 7 7 8 8 9 9 9 9 9 8 8 8 8 7 7 7 7 7 6 6 5 5 5 6 6 6 5 5 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 17 16 16 16 16 17 18 19 21 21 23 24 26 27 29 29 30 31 32 33 35 36 37 38 37 37 37 37 37 38 38 38 40 40 40 40 41 41 41 41 43 43 43 43 43 44 44 44 45 46 47 48 50 51 52 52 54 54 54 53 52 49 47 45 42 40 36 33 33 34 37 40 41 44 48 53 57 60 62 63 61 58 54 51 50 51 54 56 62 68 77 85 90 91 89 88 80 67 52 41 35 36 47 60 80 90 102 104 97 86 78 74 82 88 97 101 97 86 73 64 54 54 55 56 55 52 47 43 42 44 47 49 50 52 55 58 64 67 72 77 78 73 66 60 62 62 64 70 75 75 71 66 59 59 60 66 75 85 93 97 97 96 93 86 76 67 60 57 51 48 45 43 42 41 39 38 39 39 40 42 46 51 56 58 58 53 47 41 38 39 41 44 49 53 56 54 49 43 40 39 38 44 57 74 88 94 92 88 77 69 59 50 44 42 40 39 41 42 44 43 40 38 38 39 32 34 36 36 33 31 30 30 31 33 35 39 43 46 49 50 54 57 60 60 57 50 43 38 32 35 40 45 50 54 56 57 50 48 47 47 47 47 46 44 37 35 31 30 31 36 42 46 57 58 58 55 49 41 33 28 22 22 22 23 26 30 35 37 43 41 38 37 38 38 37 35 42 40 38 34 30 27 25 23 23 25 27 28 28 28 29 30 34 37 40 43 44 42 39 37 35 32 28 26 26 26 26 26 24 25 26 29 32 36 39 41 36 32 26 22 24 31 40 46 51 47 41 34 28 26 28 30 35 35 35 32 28 25 25 25 29 29 28 26 27 32 39 44 55 53 46 36 27 22 24 27 32 34 37 37 35 34 34 34 34 34 32 27 24 28 38 46 56 56 52 45 38 38 44 50 53 52 48 41 34 28 26 25 25 26 25 24 21 21 22 24 24 26 27 25 25 28 36 42 52 57 62 63 57 48 39 33 27 26 25 26 28 29 28 26 21 21 20 17 15 18 24 30 38 47 55 59 60 60 53 46 34 30 27 26 29 34 38 41 43 44 43 39 35 32 31 32 26 25 24 24 26 30 35 37 43 46 49 50 49 45 40 37 33 31 27 22 19 17 17 17 17 18 19 19 20 19 19 19 17 16 16 15 15 16 16 17 15 15 14 13 13 12 11 11 9 9 9 8 8 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 17 17 16 16 17 17 18 19 21 21 23 24 26 27 29 29 31 31 32 33 35 36 37 38 37 37 37 36 36 36 36 36 37 37 37 37 38 38 38 39 40 40 40 40 41 41 41 41 42 42 43 45 46 47 48 49 46 47 46 46 44 42 39 38 38 36 35 34 34 36 39 40 43 45 47 51 53 55 56 57 56 54 51 49 49 51 54 56 66 71 79 86 91 93 91 90 79 67 52 41 35 37 48 60 79 88 98 99 90 78 68 65 66 72 80 84 80 70 58 51 49 50 53 55 55 52 46 42 40 43 48 51 52 53 55 57 61 64 68 73 74 70 62 56 55 55 57 62 67 69 66 62 59 57 58 63 72 82 90 94 95 94 89 81 72 64 60 58 54 53 50 47 44 40 37 34 35 36 38 41 45 49 53 55 57 53 48 43 40 39 40 41 47 52 56 57 53 48 45 43 43 49 61 77 90 97 95 91 74 66 55 45 41 40 41 42 44 45 46 44 41 39 39 40 35 36 37 36 33 30 30 31 32 34 36 38 41 43 44 45 52 54 57 58 55 50 43 39 33 35 39 43 47 52 55 56 57 55 52 48 46 43 40 38 35 33 31 30 32 37 42 45 54 55 54 52 46 39 32 28 21 21 22 24 27 31 35 37 40 38 36 36 38 39 39 38 42 40 37 33 29 26 24 22 22 25 27 28 27 28 29 31 35 38 43 46 47 46 43 41 37 33 29 26 25 25 24 23 23 24 24 26 28 30 33 34 31 28 23 20 22 28 35 40 44 41 36 29 24 23 26 29 34 35 35 34 32 31 32 34 38 37 35 32 32 36 43 48 55 54 50 41 32 28 28 31 36 38 40 39 37 35 34 35 33 34 32 28 25 29 38 47 53 52 48 42 36 35 41 47 51 49 44 37 31 27 27 28 31 31 29 26 23 21 22 23 24 25 26 25 24 28 35 41 50 55 60 60 54 44 35 30 24 23 23 26 29 30 29 28 24 23 21 17 15 18 24 29 37 46 54 57 59 58 52 45 35 31 26 24 25 29 32 33 37 38 39 37 34 31 30 31 26 25 23 23 24 27 30 32 37 39 43 45 45 43 39 37 33 31 27 22 19 18 18 18 18 19 20 21 21 21 21 20 18 18 16 16 15 15 15 16 15 15 14 13 12 12 11 11 9 9 9 8 8 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 17 17 16 16 17 18 19 19 21 21 23 24 26 27 29 29 32 32 33 34 35 36 37 37 37 36 36 35 35 34 34 33 33 33 34 34 35 35 35 36 37 37 37 37 37 37 37 37 37 37 38 39 40 41 42 42 40 40 39 38 37 35 33 32 32 33 34 36 38 39 41 42 45 45 46 46 47 47 47 47 47 47 47 47 49 51 54 56 67 70 76 83 87 89 89 88 78 66 52 42 36 38 48 60 76 84 92 90 80 67 57 54 58 63 70 72 67 58 49 44 42 46 52 56 57 53 47 43 39 44 50 54 55 55 55 55 58 61 66 70 72 68 61 55 49 48 49 54 60 62 60 57 56 55 55 60 70 81 89 94 94 91 84 75 66 61 60 61 61 61 59 55 49 41 35 31 30 32 36 40 44 47 50 51 55 53 49 45 42 39 38 37 44 49 55 58 57 54 51 49 48 53 63 76 89 95 93 90 71 61 48 39 35 38 42 45 50 50 49 46 43 40 41 42 39 39 39 36 32 30 30 31 35 36 37 39 41 42 42 42 50 51 54 54 52 47 42 39 35 35 37 39 43 49 53 56 62 59 55 49 44 39 36 35 33 32 31 32 34 37 41 44 49 49 48 46 41 35 30 27 21 22 23 25 28 31 33 35 34 33 32 34 37 40 41 40 42 40 36 31 26 23 21 21 22 24 26 27 26 27 29 31 36 40 45 50 52 51 49 47 40 36 30 26 24 23 22 20 22 22 21 21 22 24 26 27 26 24 21 20 22 26 30 34 37 35 31 26 22 23 27 31 35 36 38 38 39 42 46 49 51 48 43 39 36 39 45 50 56 57 55 49 41 36 35 36 42 43 44 42 39 36 35 35 33 33 32 29 27 31 40 47 48 47 43 37 32 32 38 43 46 43 38 31 26 26 29 33 40 39 36 31 25 22 21 22 23 24 25 23 23 26 33 40 48 52 56 56 49 40 31 27 20 21 23 27 32 34 34 32 28 26 22 18 16 18 24 28 35 44 52 55 57 57 51 44 37 32 25 21 20 22 24 24 28 31 33 34 32 31 31 31 27 26 24 23 22 23 24 25 29 32 36 40 41 41 39 37 33 30 27 23 20 19 19 19 20 21 22 23 23 23 23 23 20 19 18 16 15 14 14 14 15 14 14 13 12 11 11 11 9 9 9 8 8 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 18 17 17 17 17 18 19 20 21 21 23 24 26 27 29 29 32 32 33 33 34 35 35 35 36 35 35 34 33 32 31 30 30 31 31 32 33 33 34 34 35 35 35 35 34 34 34 34 31 32 32 33 34 35 36 36 37 37 36 35 34 33 32 32 30 32 36 40 43 44 45 45 46 45 43 40 39 38 37 37 39 40 43 46 49 52 54 56 62 64 68 72 75 78 80 80 73 62 50 42 37 37 47 58 71 78 83 81 70 59 52 49 58 63 67 66 59 50 44 41 39 46 55 61 61 56 50 46 42 48 56 60 61 59 56 55 56 60 66 72 74 71 64 58 47 46 45 49 55 58 58 56 53 52 54 60 71 83 93 97 96 90 81 70 62 60 63 67 69 70 70 65 56 46 37 32 30 32 37 41 45 47 48 48 52 51 50 47 44 39 36 33 37 43 50 56 59 58 55 53 48 51 59 70 81 86 86 83 66 56 42 33 31 37 44 48 54 53 51 47 43 41 42 43 43 43 41 37 32 30 31 33 37 39 41 44 46 47 47 47 51 51 51 50 48 44 41 39 37 36 35 36 40 46 53 57 61 59 55 48 42 37 35 35 32 32 33 35 37 39 41 42 44 43 42 39 36 32 29 27 24 25 25 27 28 29 29 30 28 27 27 31 35 40 41 42 41 38 32 27 22 20 19 18 21 23 24 25 25 26 29 31 38 42 48 54 56 56 53 51 43 39 32 27 24 22 20 18 21 20 19 19 20 22 24 26 26 26 25 25 26 28 30 32 34 32 29 26 24 26 31 35 37 39 42 45 49 54 60 65 64 59 52 43 38 38 43 47 56 59 60 57 50 44 41 41 46 47 47 44 40 37 36 36 33 33 32 30 30 34 40 46 45 43 38 33 29 30 36 40 42 38 32 25 23 26 33 39 49 47 42 35 27 22 21 21 22 24 24 22 22 25 32 38 47 50 53 52 46 37 29 25 20 22 26 32 37 40 40 39 33 29 24 19 17 19 24 28 34 43 50 54 56 56 51 44 37 32 25 19 18 19 19 20 21 25 29 32 33 33 34 35 31 30 28 26 24 23 22 21 24 27 30 34 36 37 37 37 32 29 26 22 20 19 20 20 21 22 23 25 25 25 25 25 22 21 19 17 15 14 13 13 14 14 13 13 12 11 10 10 9 9 9 8 8 7 7 7 7 7 7 7 7 7 7 7 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 18 18 17 17 18 18 19 20 21 21 23 24 26 27 29 29 32 32 32 32 33 33 33 33 34 33 32 31 30 29 29 28 29 29 30 31 32 33 34 34 35 34 34 34 33 33 32 32 28 28 28 29 30 31 31 31 35 35 34 34 34 34 34 34 33 36 40 45 47 48 47 46 45 42 38 34 31 30 30 30 34 36 41 46 50 53 54 55 56 56 58 60 62 66 69 71 67 58 49 43 38 38 45 54 64 69 73 70 62 54 51 52 58 61 63 58 49 41 37 37 42 50 62 68 67 62 56 52 50 56 63 67 66 62 57 54 52 58 66 75 79 77 69 63 49 46 43 45 50 54 54 53 50 51 55 63 76 89 98 103 97 90 78 66 59 59 65 70 75 78 79 74 64 52 43 38 34 37 41 44 47 47 46 45 47 48 49 47 44 39 34 30 31 35 43 50 56 57 55 53 48 49 54 63 72 77 77 74 60 51 39 30 30 37 45 50 55 54 50 45 41 40 41 43 45 45 42 38 34 32 32 34 39 41 46 50 54 57 58 58 56 54 50 46 43 42 41 41 41 39 36 36 39 45 52 56 59 58 54 46 38 33 32 33 33 35 37 40 42 42 42 41 40 38 36 33 31 29 28 28 29 29 30 30 29 28 26 25 23 23 24 28 34 39 41 42 39 35 29 23 18 17 17 18 21 23 24 24 25 26 30 33 40 45 51 57 60 58 55 52 45 40 34 29 25 23 21 19 21 20 19 20 22 25 29 31 32 32 33 34 34 35 35 35 34 32 29 26 24 26 32 36 39 42 47 52 57 64 71 76 76 69 59 47 39 37 41 45 55 60 63 61 55 49 45 44 47 47 46 43 39 36 36 37 34 33 32 32 32 36 40 44 42 40 35 30 28 30 35 39 38 34 28 22 21 27 37 44 56 53 46 37 28 23 21 21 22 24 24 22 21 24 31 37 47 49 51 50 43 35 29 26 23 25 31 38 45 48 47 45 37 32 25 20 18 21 25 28 35 43 50 53 56 56 52 46 38 32 25 20 18 19 19 19 18 22 27 31 34 36 39 41 39 38 37 34 31 28 26 24 23 24 26 28 30 31 31 31 30 28 24 21 19 19 20 21 21 22 23 25 26 26 26 26 23 22 20 17 15 14 13 13 14 14 13 12 11 11 10 10 9 9 9 8 8 7 7 7 7 7 7 7 7 7 7 7 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 18 18 18 18 18 19 20 20 21 21 23 24 26 27 29 29 31 31 31 31 31 30 30 30 31 30 30 29 29 28 28 27 28 28 29 30 31 32 33 34 34 34 33 33 32 31 31 30 26 27 27 27 28 28 29 29 33 33 33 33 34 35 37 38 39 41 45 48 49 48 47 45 41 38 33 29 26 25 26 27 32 36 42 48 52 54 54 54 52 50 49 49 52 56 60 63 62 56 50 46 42 40 44 51 56 59 61 58 51 48 51 55 60 63 62 56 45 38 37 39 49 58 70 75 73 67 61 57 59 64 70 72 69 62 56 52 48 56 69 81 88 86 78 71 54 49 44 43 46 49 50 49 49 52 58 68 81 93 102 105 95 87 74 61 53 55 62 69 76 80 83 79 70 58 50 47 42 43 46 47 47 46 44 43 43 44 46 46 43 38 32 29 27 30 35 43 50 53 53 51 48 48 50 57 65 69 69 67 56 48 38 32 33 39 46 50 54 52 47 42 37 37 40 43 46 46 44 41 37 34 34 35 39 42 49 55 61 65 67 68 60 55 48 42 40 41 45 47 49 46 41 39 39 43 49 52 58 56 52 43 33 27 27 28 36 39 43 47 47 46 43 40 37 35 32 29 28 28 30 31 33 34 35 35 34 31 27 25 23 23 24 28 34 39 41 42 38 34 27 21 17 17 18 20 24 25 27 27 27 29 33 37 45 50 56 62 63 60 56 53 45 41 35 30 28 26 24 22 24 23 22 22 25 29 34 37 39 40 41 42 42 41 41 40 36 34 31 26 24 25 30 34 39 44 50 57 63 69 75 79 80 73 60 47 38 36 40 44 54 59 63 62 56 49 45 44 44 44 43 40 37 35 36 37 35 35 34 33 34 37 40 41 40 37 32 28 27 30 34 37 36 32 26 21 21 29 40 49 58 55 48 38 28 23 21 21 23 24 25 23 21 24 31 37 45 48 49 47 41 35 30 27 27 31 37 45 51 54 52 49 40 34 25 20 20 23 27 29 37 44 51 54 57 58 55 49 39 34 26 21 19 19 19 19 18 22 26 31 34 39 44 48 49 49 48 46 43 39 36 34 27 27 27 26 26 26 25 25 27 25 22 20 18 18 19 20 20 21 22 24 25 26 26 26 23 22 20 18 16 15 14 14 13 13 13 12 11 10 10 9 9 9 9 8 8 7 7 7 7 7 7 7 7 7 7 7 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 19 18 18 18 18 19 20 21 21 21 23 24 26 27 29 29 30 30 30 29 29 28 28 27 28 28 28 28 28 27 27 27 26 27 27 29 30 31 32 33 33 32 32 31 30 29 29 28 27 27 27 27 28 28 28 28 33 33 33 35 37 40 42 44 44 45 47 49 48 46 44 42 38 34 29 25 23 23 25 27 33 37 44 50 54 55 54 52 47 44 41 40 41 46 52 56 59 55 53 51 48 43 45 49 48 50 49 45 40 41 48 55 60 63 62 54 44 39 41 46 55 65 76 81 77 69 64 61 66 70 74 74 68 60 53 49 49 59 76 92 101 100 91 83 62 56 48 45 47 49 50 49 51 54 61 73 85 95 101 103 91 82 68 54 46 48 56 63 73 79 83 81 72 62 57 55 49 49 49 48 47 44 42 40 39 41 43 43 41 37 32 28 25 26 30 37 45 50 50 49 47 46 46 51 57 62 62 61 53 47 39 35 37 41 46 49 50 48 43 37 34 34 38 41 44 45 45 43 39 36 35 35 38 42 49 57 64 69 71 72 62 56 46 39 38 43 51 57 59 55 49 43 40 41 43 45 51 50 47 38 29 24 26 29 40 44 49 52 52 49 44 40 36 34 30 27 27 29 32 34 37 38 40 41 40 37 34 31 26 26 27 30 36 41 43 43 40 35 28 22 19 19 22 25 29 30 31 31 32 34 39 42 52 56 62 67 67 63 57 53 45 41 35 32 30 29 27 26 28 26 25 25 27 32 37 40 45 45 46 46 46 45 45 44 43 41 36 30 26 26 30 33 37 43 51 58 64 68 73 76 73 66 53 40 32 32 37 42 52 57 61 60 54 47 43 42 39 39 38 36 34 34 35 37 37 36 35 35 36 38 39 39 38 33 28 25 25 29 33 35 36 32 26 22 23 31 43 52 59 55 47 37 28 22 21 22 24 25 25 23 22 24 31 37 43 45 46 44 39 33 30 28 31 35 41 49 55 56 53 50 42 35 25 20 21 25 29 31 39 46 53 56 59 60 57 52 42 36 27 21 18 18 17 17 19 21 25 29 34 40 47 52 58 59 59 58 56 52 48 45 40 38 35 32 29 27 26 25 25 23 20 18 17 17 18 19 18 19 20 22 23 24 24 24 22 21 20 18 16 15 15 15 13 13 12 12 11 10 9 9 9 9 9 8 8 7 7 7 7 7 7 7 7 7 7 7 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 19 18 18 18 18 19 20 21 21 21 23 24 26 27 29 29 30 29 29 28 27 27 26 26 26 26 26 27 27 27 27 27 24 25 26 27 29 30 31 31 31 31 30 29 28 27 27 26 27 27 28 28 28 28 29 29 35 35 36 38 41 44 48 50 47 48 48 48 47 44 41 39 35 32 27 23 21 23 26 28 34 38 45 52 56 55 53 51 42 39 35 33 34 39 46 50 58 56 55 55 52 46 46 50 43 44 41 36 32 35 44 53 55 58 57 50 41 37 41 47 60 69 80 83 78 70 65 63 70 73 76 74 67 58 50 46 53 64 84 102 113 111 102 94 70 63 54 50 50 52 53 52 52 56 64 75 87 95 99 100 86 77 63 49 41 43 51 58 70 76 81 80 72 64 60 59 53 53 51 49 45 42 40 38 37 39 41 41 40 36 31 29 25 25 28 34 42 48 49 48 44 42 42 45 51 56 56 55 51 46 41 38 39 43 47 48 48 45 40 35 31 32 36 40 43 45 46 45 41 38 36 36 37 41 49 57 64 69 71 72 62 55 44 37 38 46 56 64 67 62 54 46 41 38 38 39 42 43 41 35 28 25 29 33 43 47 52 56 55 51 44 40 36 33 29 26 26 29 33 36 38 40 43 46 46 43 40 37 29 29 30 33 38 42 44 45 41 36 29 23 20 22 25 28 33 34 35 35 36 38 43 47 57 61 66 70 69 65 58 54 44 41 36 32 31 31 30 29 31 29 27 27 29 33 37 41 47 47 48 48 47 47 46 45 50 47 42 35 30 29 32 35 35 41 50 58 63 67 70 72 64 56 44 32 25 27 33 39 51 56 60 59 52 46 42 41 35 35 35 34 32 33 35 37 39 37 36 36 37 38 38 37 36 31 26 23 24 27 31 33 36 32 27 23 25 33 45 54 58 54 46 36 27 22 21 22 25 26 26 24 22 25 31 37 41 42 43 42 37 32 29 28 33 37 43 51 57 57 53 49 43 35 25 20 22 26 30 32 40 48 54 57 60 62 59 54 44 37 28 21 17 16 15 14 19 21 24 27 32 40 48 54 64 65 66 66 64 60 55 53 52 49 45 39 35 31 29 29 24 22 19 17 16 16 18 19 16 17 19 21 22 23 23 23 22 21 19 18 17 16 16 16 13 13 12 11 11 10 9 9 9 9 9 8 8 7 7 7 7 7 7 7 7 7 7 7 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 19 18 18 18 18 19 20 21 21 21 22 23 24 24 25 26 26 26 25 25 24 23 22 22 24 24 25 25 25 26 26 26 26 27 28 30 30 29 28 28 30 29 28 27 27 27 27 27 26 28 30 31 30 31 33 35 35 35 36 37 39 42 44 45 50 50 50 49 46 42 38 36 31 30 28 27 27 30 33 35 42 44 48 52 56 56 53 50 42 38 33 30 31 36 42 47 55 57 59 61 60 57 53 50 45 42 37 34 34 37 42 46 52 52 51 45 39 38 43 49 65 71 77 77 72 66 64 65 64 67 73 72 60 47 42 45 54 72 98 119 133 134 120 105 87 72 57 53 55 55 55 56 62 64 69 78 88 92 91 88 74 65 52 41 37 39 45 49 61 64 68 70 68 65 62 61 54 50 46 42 41 39 37 35 38 39 41 41 39 35 31 28 26 27 31 36 40 42 42 41 36 36 36 38 42 46 51 54 49 50 49 47 44 42 43 44 43 40 35 30 26 27 32 36 39 41 44 45 44 41 37 34 34 36 42 53 64 72 74 73 62 53 42 36 41 54 67 76 74 71 63 50 37 31 33 37 36 36 35 31 27 27 31 35 47 49 51 53 51 48 43 40 34 31 28 25 25 27 30 32 39 42 47 51 52 50 47 44 40 37 35 36 40 42 42 40 34 31 27 25 25 28 32 35 36 37 37 35 35 38 44 50 58 61 66 69 68 62 55 51 45 41 38 35 35 35 33 32 35 32 29 27 29 33 38 41 42 42 41 40 41 45 50 55 58 57 53 47 40 36 34 35 40 44 50 56 60 60 59 57 51 44 33 25 23 28 36 42 50 55 55 48 44 43 38 30 32 31 29 28 29 32 35 37 37 37 37 36 36 36 36 35 31 27 22 20 24 32 38 42 42 39 34 31 33 37 44 48 52 47 39 32 27 26 27 29 33 30 27 25 25 28 31 34 37 41 44 40 33 28 28 30 36 41 48 53 54 51 46 42 33 30 25 21 22 26 32 36 40 48 56 60 63 65 61 55 45 38 29 22 18 18 18 18 20 21 22 27 33 41 48 53 61 63 65 68 68 66 63 62 59 58 54 50 45 39 35 33 31 27 22 18 16 16 14 13 13 13 14 15 17 20 22 23 20 19 18 17 15 14 13 13 14 13 12 10 9 8 8 8 8 8 8 8 8 8 8 8 6 6 6 6 6 6 6 6 6 6 6 5 5 4 4 4 5 5 5 5 5 5 5 5 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 19 18 18 18 18 19 20 21 20 21 21 22 23 24 25 25 26 25 25 24 23 22 22 22 23 24 24 24 25 25 25 26 25 26 27 29 29 29 28 27 28 27 27 26 26 27 27 28 29 31 33 34 33 33 34 36 35 35 36 37 39 41 43 44 47 48 48 47 44 41 37 35 33 32 31 31 32 35 38 41 47 48 50 53 56 55 51 48 38 35 30 27 28 33 39 44 56 59 63 66 66 63 59 57 48 45 40 36 35 36 40 43 47 48 46 41 37 38 44 50 65 70 75 75 69 63 60 61 59 61 65 64 54 44 42 47 62 82 109 131 144 143 128 112 88 73 58 53 54 55 56 57 60 62 68 76 84 86 83 78 64 56 46 39 37 40 45 48 54 56 59 61 61 61 60 60 55 50 44 40 38 38 38 37 41 42 42 41 39 37 35 34 35 36 38 40 41 40 37 35 33 34 34 37 40 45 49 52 50 50 50 47 44 42 43 44 43 41 37 32 28 27 30 33 38 41 45 47 47 43 39 36 33 35 40 51 63 71 73 72 60 52 43 40 46 58 71 79 82 78 69 53 38 30 29 31 30 31 31 30 29 31 36 41 46 47 47 48 47 44 42 40 34 32 28 25 24 26 28 30 37 40 45 49 50 50 47 46 42 40 37 38 40 42 41 39 33 32 30 29 30 32 35 37 37 38 37 36 36 40 46 52 58 61 65 67 65 60 53 48 42 39 36 35 35 36 35 34 36 34 31 29 29 31 35 37 38 37 36 34 36 41 50 56 66 66 63 58 51 45 41 40 41 44 49 53 55 54 52 50 40 35 27 22 22 29 38 44 51 55 53 46 41 39 34 27 27 26 24 24 25 28 31 33 35 35 35 35 35 35 35 35 30 26 21 21 27 35 43 48 50 46 40 35 34 36 40 43 47 43 37 31 28 28 31 33 35 32 28 25 24 26 29 31 34 37 39 36 31 27 28 30 36 40 46 50 51 47 42 39 30 27 24 22 22 26 30 34 39 47 56 60 63 65 62 56 46 40 31 24 20 19 19 19 19 20 23 27 32 39 44 48 55 56 59 61 63 62 62 61 60 60 58 56 52 47 43 40 34 30 24 20 18 17 15 13 11 12 12 13 15 17 19 20 19 19 18 17 15 14 13 13 14 13 11 9 8 7 7 7 8 8 8 8 8 8 8 8 6 6 6 6 6 6 6 6 6 6 6 5 5 5 4 4 5 5 5 5 5 5 5 5 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 18 18 18 18 18 19 20 20 20 21 21 22 23 23 24 24 25 25 24 23 22 22 21 21 22 22 23 23 24 24 24 24 24 25 26 27 27 27 26 26 26 25 25 26 26 28 29 30 35 36 38 38 36 35 36 37 35 35 35 36 38 39 41 42 44 44 44 44 42 40 37 36 35 35 36 37 40 43 46 48 53 53 53 53 53 51 47 43 35 32 28 26 28 32 38 42 55 59 65 69 71 69 65 63 54 50 44 39 36 36 37 38 41 41 40 37 35 39 46 53 64 68 72 70 64 58 54 53 52 52 53 52 45 40 43 50 69 91 119 142 152 148 131 113 88 73 58 53 53 53 55 58 60 62 68 75 80 79 72 66 50 45 40 38 40 44 48 50 48 48 50 52 55 57 59 61 56 50 42 37 37 39 42 43 49 47 44 42 40 40 40 40 42 43 44 45 43 39 35 32 30 31 32 34 38 42 46 49 51 51 50 47 44 43 44 46 45 44 42 37 32 29 29 30 36 40 46 50 51 47 42 39 32 33 39 49 61 69 71 71 58 51 44 43 50 63 76 83 88 83 72 57 41 31 29 30 27 28 28 28 29 33 38 42 43 42 40 39 39 39 40 40 35 33 29 25 24 24 26 27 34 36 40 44 47 47 47 46 45 42 40 39 40 40 39 38 32 33 34 35 37 38 40 40 38 38 37 36 37 42 49 54 59 61 63 64 61 55 48 44 38 36 35 35 37 38 38 38 40 38 35 32 30 30 30 30 31 30 27 26 30 39 51 59 75 77 77 74 66 57 50 47 45 46 49 50 49 46 42 40 29 25 22 21 24 32 41 47 52 53 50 42 36 33 28 22 23 22 21 21 22 25 28 30 33 33 33 33 33 34 34 34 28 25 22 24 31 42 51 56 56 52 46 40 36 36 38 39 40 37 34 31 31 33 36 39 38 34 29 25 23 24 27 29 31 33 34 32 28 27 29 33 37 40 44 46 45 42 37 34 26 25 24 23 24 26 29 31 38 46 54 59 63 66 63 58 48 42 33 26 23 22 21 21 19 21 24 27 32 36 39 40 45 46 48 50 52 54 56 56 56 57 58 58 57 53 49 47 38 34 28 24 21 18 15 13 10 10 10 11 12 14 16 17 18 18 17 16 15 14 13 13 13 12 10 9 8 7 7 7 8 8 8 8 8 8 8 8 6 6 6 6 6 6 6 6 6 6 6 6 5 5 5 4 5 5 5 5 5 5 5 5 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 18 18 17 17 18 18 19 20 20 20 21 21 22 22 23 23 24 23 23 22 21 20 20 20 21 21 21 22 22 22 23 23 23 23 24 24 25 25 25 25 24 25 25 26 28 30 31 33 38 40 42 41 39 37 36 37 34 34 34 34 35 37 38 39 40 41 41 41 41 40 38 37 38 39 41 44 47 50 53 55 56 54 52 51 49 46 41 38 34 32 30 29 31 35 40 44 51 56 63 69 71 70 66 64 58 55 49 43 39 36 35 36 36 36 35 34 35 41 50 57 64 66 68 65 59 52 47 45 45 43 42 41 38 38 45 54 74 95 123 143 150 142 123 105 83 69 56 51 50 50 53 56 61 63 67 73 76 72 62 54 40 38 37 41 47 52 54 54 48 46 45 46 51 56 60 62 56 50 42 38 40 46 52 56 61 57 50 43 40 39 41 43 43 45 47 46 43 38 35 33 28 28 30 32 36 40 43 45 51 51 49 47 44 44 46 49 50 51 50 46 40 34 30 29 34 39 46 52 53 51 45 42 33 34 39 49 61 69 72 72 58 51 43 41 48 63 77 86 86 81 71 58 45 37 34 35 30 29 28 27 27 30 34 37 37 35 32 31 31 34 38 40 38 35 31 27 25 24 25 25 29 31 34 37 40 42 44 44 44 43 41 40 39 39 38 38 33 35 39 41 43 43 42 42 38 37 35 36 38 44 51 55 60 60 60 58 54 49 43 40 36 35 35 37 41 43 44 44 43 42 39 36 32 29 26 25 24 22 20 20 27 40 55 66 82 86 89 86 78 67 58 52 50 50 50 48 45 40 36 33 24 23 23 25 31 39 47 52 53 51 46 38 32 27 23 20 23 22 21 21 23 25 27 29 30 30 31 31 32 32 33 33 28 26 24 28 37 49 59 65 61 56 49 42 38 36 37 38 33 33 32 32 34 38 42 45 42 38 31 25 23 23 26 28 30 31 32 31 29 30 33 37 39 40 42 42 40 37 33 30 24 24 25 26 27 29 30 31 36 44 52 56 61 64 62 57 48 42 34 28 25 24 23 22 21 23 26 29 31 33 34 34 36 36 36 37 39 41 44 45 45 48 51 54 55 53 50 47 41 37 31 26 23 20 16 13 10 10 10 10 11 13 14 15 18 17 17 16 15 14 13 13 13 12 10 8 7 7 6 6 8 8 8 8 8 8 8 8 7 7 7 7 7 7 7 7 7 7 6 6 6 5 5 5 5 5 5 5 5 5 5 5 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 18 17 17 17 17 18 19 20 20 20 20 20 21 21 21 21 22 22 22 21 20 19 19 18 19 19 20 20 20 21 21 21 21 21 21 21 22 22 23 23 24 24 25 27 29 31 33 35 38 41 42 42 39 36 35 34 32 32 31 32 32 33 34 35 36 37 38 39 39 39 39 39 40 42 45 48 51 54 56 57 55 52 48 45 43 40 36 33 33 32 31 31 33 37 42 44 51 55 61 66 68 67 64 62 59 56 51 46 41 37 35 34 34 33 33 34 38 45 54 60 63 64 63 60 53 46 41 38 40 36 34 35 35 37 47 57 78 98 122 137 140 130 111 95 75 63 52 47 46 46 49 53 57 59 63 68 70 64 53 44 36 36 39 47 56 62 63 60 49 46 42 43 49 56 61 63 58 53 47 46 51 59 67 72 74 67 56 45 39 37 39 41 44 46 47 44 39 34 32 31 28 28 30 32 35 38 40 42 48 48 48 46 45 47 51 54 59 60 60 56 48 40 34 31 32 37 45 52 54 52 47 43 36 37 41 51 62 71 75 75 61 52 41 37 44 58 73 83 82 77 69 58 48 42 39 39 33 31 28 26 26 28 30 32 31 29 27 26 28 33 38 42 42 39 36 32 29 27 27 27 26 26 28 30 33 36 38 40 40 40 40 39 38 39 39 40 38 41 45 48 48 46 43 41 36 35 34 36 41 47 52 55 59 58 56 53 48 43 38 36 35 35 37 41 46 49 50 50 47 46 43 38 34 29 25 23 20 19 18 20 28 43 60 71 86 91 95 93 85 74 63 56 54 53 50 47 43 38 35 32 27 29 31 35 41 47 53 56 53 48 41 35 28 23 20 20 23 22 22 22 23 24 26 27 28 28 29 30 31 32 32 33 29 28 29 35 45 56 65 69 66 60 51 42 36 33 33 33 31 32 33 35 39 44 48 51 46 41 34 27 24 25 28 30 34 34 34 34 34 35 38 41 41 41 41 39 36 33 30 28 23 25 27 29 31 32 33 33 35 43 50 53 56 59 57 52 45 40 33 27 25 24 23 23 23 24 27 29 30 30 29 28 29 28 27 26 26 28 29 31 34 37 42 46 48 48 46 44 41 37 32 28 25 21 17 14 11 11 11 11 12 13 14 14 17 16 16 15 14 14 13 13 13 12 10 9 8 7 7 7 8 8 8 8 8 8 8 8 7 7 7 7 7 7 7 7 7 7 7 6 6 6 5 5 5 5 5 5 5 5 5 5 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 17 17 16 16 17 18 19 19 20 20 20 20 20 20 20 20 21 21 20 20 19 18 17 17 18 18 18 18 19 19 20 20 20 20 19 19 19 20 21 22 23 24 25 26 28 31 33 34 35 37 40 39 36 33 31 31 30 29 29 28 29 29 30 31 32 32 33 35 36 38 39 40 41 43 47 50 53 54 54 54 51 48 43 40 38 36 34 31 31 30 30 31 34 38 42 44 52 55 59 62 63 61 59 57 55 53 49 45 40 37 34 33 32 32 32 35 40 48 55 59 62 61 59 55 50 43 37 33 36 32 30 32 34 37 46 56 78 95 114 124 123 114 99 86 65 56 48 45 44 43 45 50 52 53 57 62 63 57 46 38 36 37 41 52 63 69 68 64 49 45 40 42 49 57 63 65 64 61 58 60 66 75 83 87 84 75 61 47 37 34 35 37 45 46 45 39 31 26 26 27 30 30 32 33 35 37 38 39 44 44 45 45 47 51 57 61 68 69 69 64 55 45 37 34 31 36 43 49 52 50 47 44 38 39 43 52 64 73 77 77 64 55 43 36 40 52 65 74 76 71 64 56 50 45 43 43 38 34 30 27 27 28 29 29 26 26 26 28 32 38 43 46 46 44 41 37 34 32 32 31 26 26 25 25 27 30 33 36 36 37 39 40 40 41 44 47 48 50 53 55 53 49 43 40 34 34 35 39 45 51 55 56 58 56 52 47 42 38 35 33 35 35 38 43 49 53 54 54 51 49 45 40 35 31 27 25 21 20 21 24 32 45 60 70 84 88 92 90 83 72 62 56 51 50 47 44 40 37 35 33 32 35 40 45 51 55 58 59 53 46 38 32 27 21 20 23 24 23 23 22 22 23 23 24 26 27 28 29 30 32 33 33 32 33 35 42 52 61 67 70 68 61 50 39 31 28 28 29 33 34 37 40 45 49 53 55 48 44 36 30 28 29 33 36 39 39 39 39 40 41 42 43 42 40 38 35 32 29 27 26 23 25 27 30 32 33 34 35 35 41 47 49 51 53 50 45 39 35 29 25 23 23 22 22 23 24 25 27 27 26 25 24 24 23 21 19 18 18 19 20 25 28 33 37 40 41 40 39 37 34 30 27 25 22 18 15 13 13 12 12 12 12 13 14 16 15 15 15 14 14 13 13 14 13 12 10 9 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 7 7 7 6 6 6 6 5 5 5 5 5 5 5 5 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 17 17 16 16 17 17 18 19 19 19 19 19 19 19 19 19 20 20 20 19 18 17 17 16 16 17 17 17 18 18 18 19 19 18 17 17 17 19 20 21 22 22 23 24 26 28 30 32 30 33 35 36 33 29 27 27 28 27 26 26 25 26 26 27 26 27 28 30 32 35 37 38 42 44 47 50 52 51 50 49 47 44 39 37 36 35 34 33 31 32 33 35 38 41 45 47 52 53 54 55 54 52 50 48 46 45 43 41 38 35 32 31 30 30 32 36 42 48 53 56 61 59 56 52 47 41 35 31 32 28 27 30 33 37 44 52 67 81 95 100 98 93 83 73 57 51 46 45 44 43 44 48 51 52 55 60 62 57 47 39 37 37 42 53 66 72 69 64 50 45 42 45 54 64 70 72 73 72 71 74 81 88 94 96 87 78 62 47 36 32 33 34 39 40 38 32 24 21 23 27 33 33 34 35 36 37 37 37 39 41 42 44 48 54 62 68 75 75 74 68 58 48 39 35 31 35 41 46 48 48 45 43 40 40 43 52 64 73 78 78 66 58 47 40 41 48 56 61 64 61 57 53 51 51 51 51 50 44 37 31 29 28 26 24 24 26 29 34 40 45 50 53 51 49 46 43 40 38 37 37 30 28 25 23 24 27 30 33 32 35 39 41 43 46 51 56 60 61 63 62 58 51 44 40 34 35 38 44 51 57 58 57 56 53 49 43 38 35 32 31 34 35 38 44 50 54 55 55 53 51 46 41 37 33 30 29 24 25 26 29 35 44 56 63 74 77 79 77 70 60 52 48 45 43 41 38 36 35 34 34 34 38 45 52 57 60 60 60 52 43 35 31 26 21 23 28 28 27 26 26 25 24 24 24 25 26 27 29 31 32 34 34 36 37 42 49 57 64 67 68 61 54 43 33 27 27 30 33 37 39 42 45 49 53 55 57 50 46 39 33 31 34 39 42 44 43 44 44 45 45 44 43 40 38 34 30 27 25 24 23 22 23 26 28 31 33 35 35 35 41 45 45 45 46 43 37 33 29 24 21 21 21 21 20 21 22 22 22 22 21 21 20 20 19 18 17 16 15 15 15 18 20 23 27 30 32 32 32 32 30 28 26 25 23 19 16 13 13 12 11 11 11 12 12 15 15 15 14 14 14 13 13 15 14 13 11 10 9 9 9 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 7 7 7 6 6 6 5 5 5 5 5 5 5 5 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 17 16 16 16 16 17 18 19 19 19 19 19 19 19 19 19 20 20 19 18 17 17 16 16 16 16 16 17 17 17 18 18 18 18 17 16 16 18 19 20 20 20 21 22 24 26 28 29 26 29 32 33 30 27 25 24 26 26 25 24 24 24 24 25 22 23 24 26 29 32 35 37 42 44 47 50 50 49 47 46 45 41 37 35 35 36 36 35 34 35 37 39 42 46 49 51 50 50 49 48 46 43 41 40 40 40 39 37 35 33 31 29 29 29 31 36 42 48 51 53 60 58 55 51 46 40 34 30 29 26 26 30 33 36 42 49 53 65 76 79 77 74 68 62 53 48 45 46 45 43 44 48 53 54 57 62 64 61 52 45 37 37 42 53 65 71 68 62 52 48 45 50 61 72 79 80 80 80 80 84 90 96 99 100 88 78 63 47 36 32 32 33 31 32 31 26 20 20 25 31 35 36 36 37 37 37 36 36 37 38 41 44 49 56 65 72 78 78 76 70 59 48 40 36 31 34 39 44 46 46 44 43 39 39 43 51 63 73 78 78 67 60 51 44 44 46 50 52 53 51 49 50 53 56 59 60 62 54 44 36 30 26 21 18 24 27 32 39 46 52 56 57 53 52 49 46 44 42 41 40 33 30 26 23 23 26 29 32 30 34 40 43 46 50 57 62 68 69 69 66 61 53 45 40 35 36 40 48 56 60 60 59 55 52 46 41 36 33 31 31 33 34 38 44 50 54 55 55 54 52 47 42 37 34 32 32 28 29 31 33 36 43 51 57 63 65 66 63 57 49 42 39 39 37 35 34 33 33 33 34 33 38 46 54 59 61 61 61 52 42 34 31 27 22 25 31 33 32 31 30 29 28 27 26 25 26 27 29 31 33 34 35 38 40 45 53 61 65 67 66 51 45 35 28 26 30 36 41 40 42 45 49 52 55 56 57 51 47 40 35 34 37 43 46 46 46 46 47 48 47 44 42 38 36 31 27 24 22 22 22 21 22 24 26 29 32 34 35 35 40 43 42 42 42 38 33 29 25 21 19 19 20 20 19 20 19 19 19 18 18 18 18 18 18 17 17 16 16 15 15 12 13 16 19 22 24 25 26 29 27 25 25 24 23 20 17 13 12 11 10 10 10 11 11 15 15 14 14 14 14 13 13 16 15 14 12 11 10 10 10 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 7 7 6 6 6 5 5 5 5 5 5 5 5 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 14 14 15 16 17 17 18 18 18 18 18 17 17 17 16 16 19 19 19 19 18 16 15 14 13 13 14 14 14 15 15 15 14 14 15 16 17 17 18 18 22 21 21 21 22 23 24 25 25 25 24 24 24 24 24 24 24 23 23 22 22 21 21 20 19 20 21 23 27 31 35 38 41 44 48 51 52 51 49 47 42 42 42 41 41 41 40 40 45 44 43 44 46 47 46 44 47 46 43 40 37 35 34 33 37 36 36 34 32 29 27 26 25 26 29 34 40 46 52 55 57 55 52 47 41 35 31 28 24 25 27 31 34 38 40 42 48 50 54 57 59 58 56 55 53 53 53 52 50 47 44 42 48 52 57 63 66 64 58 53 42 41 42 49 57 60 58 53 46 45 47 55 66 78 85 88 93 90 88 90 95 97 94 90 81 70 55 45 41 39 36 33 35 29 25 27 26 25 30 39 43 44 45 43 40 37 34 34 36 38 41 44 47 55 64 72 79 79 75 67 55 43 34 30 29 31 36 41 44 44 41 39 38 40 45 51 58 65 70 73 65 58 48 41 38 38 39 40 38 36 39 46 53 57 63 70 67 61 51 42 34 30 29 28 29 33 40 47 53 57 59 59 52 47 42 41 44 44 40 36 33 31 27 25 24 26 28 30 28 32 38 44 50 57 64 69 77 77 75 70 63 55 48 44 41 44 49 56 61 63 62 60 56 52 45 38 32 29 27 27 29 31 35 39 43 46 47 48 45 41 35 32 32 32 32 32 34 34 33 34 37 41 45 47 50 48 46 42 38 34 31 30 28 28 29 30 31 30 30 30 37 39 44 50 55 56 54 51 45 41 37 32 31 33 36 39 38 39 39 36 31 28 26 26 28 29 30 32 33 33 34 33 40 43 49 56 61 61 58 55 44 38 30 26 27 33 38 41 45 44 45 48 52 54 53 52 46 41 35 33 35 40 45 48 50 49 47 45 43 42 41 41 38 34 29 24 20 19 19 20 18 19 22 25 27 29 30 31 33 33 34 36 37 36 33 30 22 20 17 15 14 16 19 21 18 18 18 18 17 16 14 13 16 17 19 20 21 20 19 18 16 16 17 18 18 19 19 20 22 22 21 21 20 19 19 19 15 14 12 11 10 10 11 12 12 12 13 14 15 16 16 17 13 13 13 12 12 11 11 10 11 11 11 10 10 9 9 9 8 8 8 9 9 10 10 10 8 8 8 7 7 6 6 6 7 6 5 4 4 4 4 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 14 14 15 15 16 17 18 18 18 18 17 17 17 16 16 16 18 18 18 18 17 15 14 13 12 12 13 13 14 14 14 14 13 14 14 15 16 17 17 18 21 20 20 20 20 21 21 22 21 21 21 22 22 23 23 23 24 23 23 22 21 21 20 20 18 19 20 23 27 31 35 38 42 44 48 51 51 50 48 46 44 45 46 48 49 50 51 51 52 50 49 49 50 50 48 47 44 42 39 36 34 33 33 33 35 35 35 33 31 28 25 23 23 25 28 33 38 45 50 53 54 53 50 45 40 35 30 28 25 27 30 33 36 38 39 40 40 42 45 48 50 51 51 51 53 53 53 52 49 45 42 40 47 51 58 66 70 68 63 58 46 43 42 45 51 54 52 49 47 48 53 62 75 87 94 97 96 92 88 88 90 90 85 81 71 62 52 46 45 46 44 41 43 37 33 34 35 35 41 49 53 52 50 47 43 39 38 37 38 40 43 46 50 57 67 74 78 76 71 62 50 39 31 28 29 31 36 40 44 44 42 40 38 39 42 47 53 59 64 67 64 58 50 44 41 40 39 39 35 33 35 43 50 56 64 72 73 68 60 51 43 38 35 34 35 39 44 50 53 55 55 54 48 43 39 39 41 42 38 35 32 30 27 25 25 26 28 30 30 34 40 46 52 59 66 71 76 76 73 68 60 53 47 44 45 48 54 60 64 64 61 59 53 50 44 38 32 28 26 26 25 28 32 36 39 40 41 41 35 32 30 30 33 36 38 38 38 37 35 33 34 36 39 41 40 39 37 33 29 26 23 21 25 26 27 28 28 28 28 27 32 34 38 43 48 49 47 45 42 39 36 34 34 36 39 41 41 41 40 36 31 28 27 28 30 31 33 34 35 35 34 34 39 41 46 53 57 57 54 51 41 36 30 28 31 37 43 46 50 48 47 48 50 51 51 50 43 39 33 31 34 39 44 46 46 45 43 41 39 39 39 39 33 30 26 21 19 17 18 18 18 19 21 24 26 28 30 30 31 31 32 34 35 35 32 29 22 20 17 14 14 15 18 19 19 20 20 19 18 17 16 15 17 18 20 21 22 21 20 19 16 16 16 17 17 18 18 19 20 20 20 19 19 19 19 19 16 15 13 11 10 10 11 11 11 11 12 13 14 15 15 16 14 13 13 13 12 12 11 11 11 11 11 10 10 10 9 9 8 8 8 9 9 10 10 10 8 8 8 7 7 6 6 6 7 6 5 4 4 4 4 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 13 13 14 15 16 16 17 17 17 17 17 16 16 16 15 15 16 16 16 16 15 14 13 12 11 11 12 12 12 13 13 13 12 13 13 14 15 16 16 17 19 19 18 17 17 17 18 18 16 17 18 19 20 21 22 23 24 24 23 22 21 20 20 19 17 18 19 22 27 32 36 39 45 46 48 50 50 49 46 45 45 47 50 53 56 58 60 61 58 55 53 52 51 50 48 45 39 36 33 30 29 30 32 33 33 33 34 33 30 26 22 20 21 23 26 31 37 42 47 50 50 49 46 43 38 34 30 27 27 29 33 37 39 40 40 40 36 37 38 40 42 44 46 47 54 54 54 53 50 45 41 39 43 49 58 68 74 74 70 65 52 47 42 41 44 46 46 45 48 52 59 71 85 96 103 106 99 94 87 83 80 76 71 66 56 53 50 51 55 58 58 56 55 50 46 47 48 50 56 63 64 61 56 50 45 42 40 39 38 40 42 45 51 59 68 74 75 72 65 54 43 34 28 27 30 33 37 41 44 44 43 42 39 40 41 44 48 53 57 59 61 57 53 49 46 43 39 36 31 28 30 38 47 54 64 73 78 75 69 62 54 47 42 39 43 45 49 51 52 51 49 47 42 39 36 36 38 39 36 33 31 30 27 26 25 26 28 30 32 36 42 47 53 60 67 71 74 73 70 64 56 49 45 44 51 56 62 67 68 65 60 56 50 47 43 37 32 28 25 24 21 24 28 31 33 33 32 30 26 26 26 30 35 40 42 43 43 40 36 32 31 31 34 35 33 32 30 27 23 20 16 15 21 22 23 24 24 24 24 24 25 26 29 33 38 39 38 36 37 36 36 36 38 41 43 45 45 44 41 36 31 29 29 31 34 35 36 37 37 36 35 34 37 38 42 47 51 51 48 45 37 34 31 32 37 44 50 53 55 52 48 46 46 47 46 46 39 35 31 30 32 37 41 44 41 39 36 34 33 34 35 36 30 28 25 22 20 19 19 19 18 19 20 23 25 27 29 30 28 28 29 31 33 34 32 29 24 21 18 15 14 15 17 18 21 21 22 21 21 19 18 17 19 20 22 23 24 23 22 21 16 17 17 17 17 17 18 18 17 18 18 18 18 18 19 19 17 16 14 12 11 10 10 10 10 10 11 11 12 13 13 14 14 14 14 13 13 13 12 12 11 11 11 11 10 10 10 9 8 8 9 9 9 9 10 10 8 8 8 7 7 6 6 6 7 6 5 4 4 4 4 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 12 13 13 14 15 16 16 16 16 16 16 16 15 15 15 14 14 14 14 14 14 13 12 11 10 10 10 11 11 12 12 12 12 12 13 13 14 15 16 16 18 17 16 15 14 14 14 15 14 15 17 19 21 23 24 25 25 25 24 23 22 21 20 19 18 19 20 24 28 33 38 40 47 48 49 49 48 47 45 44 44 47 50 54 57 60 61 62 57 54 51 49 47 45 42 39 33 30 27 24 24 26 30 32 32 33 33 33 30 26 22 20 21 23 26 30 35 40 44 46 46 45 43 40 37 33 30 28 28 31 36 41 44 45 45 44 40 39 37 37 38 41 44 46 54 54 54 53 50 46 41 39 40 46 56 67 75 77 74 71 57 51 44 40 41 43 45 46 50 55 65 78 90 99 104 106 98 91 82 74 67 61 55 51 47 49 54 62 70 75 76 75 71 67 63 63 65 69 74 77 73 67 58 50 45 43 41 41 38 38 40 44 50 58 67 72 72 68 59 47 37 30 28 28 32 36 41 45 46 46 45 45 43 43 43 43 45 47 50 51 56 55 54 53 50 45 38 33 28 25 26 34 44 52 64 74 79 78 75 69 62 54 46 42 46 47 48 49 48 46 43 41 38 36 34 35 36 36 34 32 30 29 27 26 26 27 29 30 33 37 42 47 52 58 64 69 70 69 65 58 49 44 44 45 57 63 70 74 71 65 57 53 47 45 42 38 34 29 25 23 19 21 25 28 29 28 25 23 25 25 28 33 39 43 44 44 47 43 37 32 29 30 33 35 35 34 32 30 26 22 18 16 18 19 20 21 21 21 21 20 20 20 22 25 29 31 30 29 31 32 34 37 40 43 45 46 47 45 40 35 30 29 31 34 38 39 40 40 40 38 35 34 34 35 37 40 43 43 40 38 33 32 33 37 44 51 57 59 58 53 47 42 40 40 40 40 34 31 28 28 31 35 38 40 37 34 31 28 28 29 32 33 31 30 29 27 26 24 24 24 20 20 21 22 24 26 28 29 27 27 28 30 32 33 32 30 26 24 20 17 15 16 17 19 23 23 23 23 23 22 21 20 21 22 24 25 25 25 24 23 19 19 19 19 19 18 18 18 15 16 16 17 17 18 18 19 18 17 15 13 12 10 9 8 9 9 10 10 11 11 11 12 14 14 14 13 13 13 13 13 12 12 11 11 11 10 10 10 9 9 9 9 9 9 9 9 8 8 8 7 7 6 6 6 7 6 5 4 4 4 4 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 12 12 12 13 14 15 15 16 16 15 15 15 14 14 14 14 12 13 13 13 13 12 11 11 10 10 10 10 11 11 12 12 12 12 13 13 14 15 16 16 17 16 15 14 13 13 13 13 15 16 18 21 23 25 27 28 27 26 25 24 23 22 21 20 20 20 22 25 29 34 39 41 47 47 47 46 45 45 44 44 45 47 50 54 56 57 57 57 53 50 47 44 42 39 36 33 28 26 23 21 21 24 28 31 32 33 33 33 30 27 24 22 23 24 27 31 35 38 40 42 43 42 41 39 37 35 32 31 30 33 39 44 48 50 50 49 45 42 39 36 35 37 40 42 48 50 51 51 49 45 41 38 39 44 54 65 74 77 76 73 61 56 49 44 43 45 48 49 54 61 71 81 90 95 99 101 91 84 74 64 56 49 44 41 45 51 62 75 86 92 93 92 88 85 81 80 83 88 90 89 77 70 59 51 47 46 45 44 40 40 40 44 51 59 66 71 68 63 54 43 34 30 31 33 38 44 50 53 53 51 49 49 46 46 45 45 44 44 44 44 50 51 53 55 54 48 39 32 28 24 26 33 42 51 62 71 77 77 77 74 68 60 52 47 44 44 43 42 41 39 37 36 36 35 35 35 36 35 33 31 29 28 27 27 27 28 29 30 33 36 40 44 48 53 58 62 64 63 59 50 42 39 42 46 62 69 76 77 72 62 54 49 44 44 43 41 37 31 26 23 19 21 24 27 27 26 24 23 26 28 32 39 46 49 50 49 46 42 36 31 29 32 36 39 41 40 39 36 32 27 23 20 17 18 19 20 20 20 19 19 19 18 19 21 25 27 27 26 28 29 32 35 38 41 43 44 43 41 37 32 28 29 32 35 40 41 42 42 41 37 34 32 30 30 31 34 36 36 34 32 31 31 35 41 49 56 60 61 56 51 43 38 35 35 35 34 31 29 26 27 29 33 35 35 34 31 27 25 25 28 32 35 37 37 36 35 33 31 29 28 24 24 24 24 25 26 28 29 28 27 27 29 32 33 32 31 28 26 22 18 17 18 19 21 24 24 25 25 25 24 23 22 22 23 25 26 27 26 25 24 23 23 22 22 21 20 20 20 15 15 16 16 17 18 18 18 18 17 16 14 13 11 9 8 9 9 9 9 10 10 10 10 13 13 13 13 13 13 13 13 12 12 12 11 11 11 10 10 9 9 9 9 9 9 9 9 8 8 8 7 7 6 6 6 7 6 5 4 4 4 4 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 11 11 12 12 13 14 15 15 15 15 14 14 14 13 13 13 12 12 13 13 13 13 12 11 10 10 10 11 11 12 12 12 12 13 13 14 15 16 16 17 16 15 14 14 13 14 14 14 18 19 21 23 26 28 30 31 29 29 28 26 24 23 22 21 21 22 23 25 29 33 37 40 44 43 42 41 40 40 41 41 45 47 50 53 54 54 53 52 48 45 42 39 38 35 32 29 24 23 21 20 21 23 26 29 32 31 31 30 29 27 26 25 27 28 30 33 36 37 38 39 41 41 41 40 39 37 35 34 32 35 40 45 48 50 51 51 44 41 37 33 32 33 35 37 42 44 47 49 49 46 42 40 42 46 53 63 71 75 75 74 65 61 55 50 48 48 50 52 56 63 72 79 84 87 89 90 81 75 66 56 48 43 40 40 49 57 71 86 96 102 103 102 98 98 95 93 95 99 97 92 76 68 57 51 49 49 48 47 44 42 41 45 51 59 66 69 64 60 52 43 36 35 38 42 49 56 64 67 65 60 57 56 50 51 51 50 48 46 43 41 46 49 54 58 57 51 42 35 31 27 29 35 43 49 58 67 73 74 75 75 71 64 57 53 42 40 37 34 32 32 32 33 35 35 36 36 35 33 31 30 28 28 27 27 27 28 29 30 32 35 38 41 43 47 51 55 57 56 51 42 35 34 41 48 65 71 78 77 69 58 50 45 44 45 46 44 41 34 28 24 21 22 24 26 27 28 27 27 29 32 39 47 55 58 57 55 44 40 33 29 29 34 40 44 46 46 45 42 37 31 25 22 18 19 20 20 21 21 20 20 21 19 19 20 23 25 26 26 26 27 29 31 33 35 37 38 34 33 31 28 26 28 32 36 41 42 43 43 40 36 31 28 27 26 26 28 30 31 30 28 29 32 36 44 52 57 59 58 51 46 39 35 33 33 32 32 30 28 26 26 29 31 32 31 29 27 24 23 26 31 38 43 48 48 47 46 43 39 36 34 31 30 28 27 27 27 29 30 29 28 27 28 30 32 31 30 27 25 21 19 17 18 20 22 24 25 25 26 26 25 24 24 23 24 25 27 27 27 25 25 26 25 24 24 22 21 21 20 16 16 17 17 17 17 17 18 16 16 16 15 14 12 10 9 9 9 9 9 9 9 10 10 11 11 11 12 12 12 13 13 13 12 12 12 11 11 11 11 10 10 9 9 9 9 8 8 8 8 8 7 7 6 6 6 7 6 5 4 4 4 4 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 10 10 11 12 13 13 14 14 14 14 14 13 13 13 12 12 12 12 13 14 14 13 13 12 11 11 11 11 12 12 12 13 13 14 14 15 16 17 17 18 15 15 15 14 15 15 16 17 20 21 23 25 27 29 31 32 31 31 30 28 26 25 23 23 21 21 22 24 27 30 34 36 38 37 35 34 34 35 36 37 42 44 47 50 51 50 48 47 41 38 35 34 33 31 28 26 23 22 21 21 22 23 25 27 30 29 28 26 26 26 27 28 31 32 34 36 37 37 37 36 40 41 41 41 41 40 39 38 36 37 40 42 45 46 47 48 41 38 34 31 30 31 33 35 42 45 49 53 54 53 50 48 48 50 55 62 69 73 74 74 68 66 62 57 52 50 50 51 51 57 65 70 72 73 75 76 72 68 60 51 45 42 43 44 53 63 77 91 100 104 105 104 98 99 97 94 96 98 92 82 67 59 50 45 46 47 46 45 43 40 38 41 48 55 60 62 61 58 52 45 41 41 46 50 61 69 79 83 78 71 66 64 60 62 63 63 60 55 49 46 46 49 55 61 62 56 47 40 35 32 33 39 44 48 54 61 64 66 69 70 68 64 58 55 43 40 34 28 26 26 28 30 33 35 36 36 33 30 28 27 27 27 27 27 28 29 29 29 33 35 38 39 40 43 46 49 50 49 45 36 29 30 40 49 66 72 77 75 65 54 46 43 44 46 48 48 45 38 31 26 22 22 24 25 27 30 31 32 39 42 49 56 62 63 60 57 41 37 31 26 27 33 41 46 51 51 49 45 40 32 26 22 20 21 22 22 23 23 22 22 23 21 19 20 22 25 26 26 26 26 26 26 27 28 30 31 25 25 25 24 24 27 32 36 41 42 43 42 39 34 28 25 24 23 22 24 26 28 28 27 30 32 38 46 53 56 55 54 47 43 37 34 33 33 33 33 30 28 26 27 28 29 29 28 24 22 21 23 29 38 48 55 63 63 62 60 56 51 46 43 37 35 33 30 29 29 29 30 29 27 26 26 28 29 28 27 24 22 19 17 16 17 20 21 24 25 25 26 26 25 25 24 23 24 25 27 27 26 25 25 26 26 25 24 22 21 20 19 18 18 18 18 17 17 17 17 15 15 16 16 15 13 11 10 10 10 10 10 10 10 10 10 9 10 10 10 11 11 12 12 13 13 12 12 12 11 11 11 10 10 10 9 9 8 8 8 8 8 8 7 7 6 6 6 7 6 5 4 4 4 4 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 10 10 11 11 12 13 14 14 14 14 13 13 13 12 12 12 12 12 13 14 14 14 13 13 11 11 12 12 12 13 13 13 14 14 15 16 17 17 18 18 15 15 15 15 16 17 18 19 21 22 23 25 27 29 31 32 33 32 31 29 27 26 24 24 20 20 21 22 24 28 31 33 33 32 30 29 29 30 32 34 37 39 43 46 47 46 44 43 34 32 29 28 28 27 24 22 22 22 22 22 23 24 25 25 28 27 25 23 23 25 27 29 34 35 37 38 38 37 36 35 41 41 42 42 42 42 41 40 39 39 39 40 41 42 43 43 39 37 34 31 31 32 34 36 45 49 54 59 62 61 58 56 52 53 56 62 68 73 74 74 70 69 66 61 55 51 48 48 43 49 56 60 61 62 64 66 67 63 57 49 44 44 46 49 56 65 80 92 100 103 103 102 92 94 92 89 90 91 83 71 58 50 42 38 41 43 42 40 39 36 34 36 43 50 54 56 60 57 52 46 44 46 51 56 69 78 89 93 88 79 72 70 70 72 74 75 71 65 58 53 46 50 57 63 65 60 51 44 38 35 36 41 45 47 52 58 56 59 62 64 64 60 56 53 46 40 33 26 22 23 26 28 32 34 36 35 32 28 26 25 27 27 27 28 28 29 29 29 34 36 38 39 39 40 44 46 46 46 41 32 25 28 39 50 66 72 76 73 63 51 44 41 45 47 50 50 47 40 32 27 22 22 23 24 27 31 34 36 49 52 57 63 66 64 59 54 40 35 29 24 26 32 40 46 55 54 52 48 42 34 27 23 21 22 23 24 24 24 24 24 24 22 20 20 22 25 26 27 26 25 24 23 23 24 25 26 18 19 21 21 23 26 31 35 41 42 42 42 38 32 27 23 23 21 20 22 24 26 27 26 30 33 39 47 53 55 53 50 44 41 37 34 34 35 35 34 30 28 27 27 28 29 27 26 19 18 19 23 32 44 56 64 76 76 75 72 68 62 56 52 41 39 35 32 30 29 30 31 28 26 24 24 26 27 26 25 22 20 17 15 15 16 19 21 24 24 25 26 26 26 25 25 22 23 25 26 27 26 25 24 26 25 24 23 21 20 19 18 20 19 19 18 18 17 17 16 14 15 16 16 15 14 12 11 10 10 10 10 10 10 10 10 8 9 9 10 10 11 11 11 13 13 13 12 12 11 11 11 10 10 10 9 9 8 8 8 8 8 8 7 7 6 6 6 7 6 5 4 4 4 4 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 10 10 11 12 13 13 14 14 14 13 13 12 12 13 13 14 12 12 11 12 13 14 15 16 12 12 12 13 13 13 13 13 17 17 17 18 18 19 19 19 19 18 17 16 16 16 16 17 21 21 22 23 26 29 32 34 33 33 32 32 30 28 27 26 20 20 20 21 22 23 25 26 27 25 23 21 23 26 30 33 36 40 44 46 45 42 40 39 35 32 28 25 23 23 24 25 24 25 25 25 25 24 23 23 26 26 27 28 30 33 35 36 37 38 38 38 39 39 39 39 41 42 44 46 46 44 42 41 38 37 36 35 34 34 34 34 32 32 31 29 28 30 35 38 51 55 61 66 68 66 63 60 60 60 60 62 64 67 71 72 71 68 65 61 58 54 49 45 43 43 42 43 45 49 53 55 57 57 55 54 53 53 53 54 63 69 77 84 88 88 85 82 81 82 83 82 77 70 62 56 42 39 36 35 38 41 43 44 39 35 32 32 37 44 50 53 52 51 49 46 46 50 59 66 79 88 98 101 95 87 81 79 79 81 85 91 91 82 67 54 53 52 55 61 66 65 56 48 38 37 38 41 46 50 51 50 53 50 49 50 54 57 56 55 45 41 35 29 26 26 27 29 28 30 31 29 26 25 27 30 31 31 30 28 26 25 27 30 29 33 37 39 38 39 43 47 53 51 44 34 27 28 37 46 60 71 77 70 57 47 40 35 40 43 46 47 45 38 31 26 23 24 24 24 26 31 37 43 51 59 66 68 67 64 56 48 32 29 25 24 27 34 42 47 50 49 47 43 38 32 27 24 22 23 26 29 30 30 29 28 29 25 21 21 24 27 27 26 28 27 25 23 21 20 19 19 16 16 16 17 20 24 28 31 36 36 35 34 31 28 24 22 17 19 21 22 21 22 24 26 32 39 45 47 50 53 51 47 39 37 36 36 37 37 35 33 31 29 27 26 26 25 23 21 17 17 20 26 38 52 65 73 84 84 83 80 74 66 59 54 48 44 38 35 34 33 32 31 28 27 26 24 22 20 19 18 16 16 16 16 17 18 20 20 26 25 24 23 22 22 22 22 20 21 23 25 26 27 26 25 25 24 23 22 21 19 18 18 16 16 16 15 15 15 14 14 15 15 15 14 14 14 13 13 12 12 11 10 10 9 8 8 7 7 7 8 9 10 11 12 13 13 13 13 13 13 13 13 9 9 9 8 8 7 7 7 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 10 10 11 11 12 13 14 14 14 13 13 12 12 13 13 14 12 12 11 12 13 14 15 16 14 14 14 15 15 15 15 16 17 17 17 18 18 19 19 19 18 18 17 16 16 17 17 17 21 21 22 24 26 29 32 34 34 33 33 32 30 28 26 25 20 20 20 20 21 22 23 24 25 23 22 21 23 27 31 34 37 40 44 45 43 39 37 36 31 30 27 25 24 25 26 27 27 27 27 28 27 27 26 26 28 28 29 31 33 35 37 38 41 41 41 41 41 41 40 40 42 43 43 43 43 41 39 37 37 36 34 32 31 30 29 29 27 28 29 29 30 34 39 43 53 57 63 68 70 69 66 64 60 60 60 61 62 64 67 68 68 66 63 61 59 55 49 45 39 38 36 36 38 41 45 47 52 52 52 53 53 53 53 53 58 61 67 71 73 73 70 69 66 68 69 68 64 57 50 45 35 34 33 36 40 45 47 47 40 37 32 31 35 40 45 48 49 49 49 47 47 52 59 65 76 85 96 99 95 87 82 79 83 86 93 100 101 92 76 63 55 55 58 64 70 68 59 51 40 39 39 42 47 50 51 50 47 44 41 42 45 49 50 49 47 44 40 35 31 30 29 29 26 27 27 26 24 25 29 32 34 34 32 29 26 25 27 29 32 35 37 38 38 41 47 53 61 60 54 44 35 34 42 49 60 70 75 68 55 45 37 32 36 38 42 44 42 37 31 26 23 24 24 24 26 31 39 44 54 61 65 64 60 55 46 37 29 27 24 24 27 33 40 45 46 45 42 38 34 29 25 23 23 25 30 33 35 35 34 33 31 27 22 21 23 26 27 27 28 27 25 23 21 19 18 18 18 17 17 17 20 24 27 30 34 34 34 33 30 27 24 22 19 20 21 22 22 24 27 30 35 42 48 49 51 53 51 46 40 38 36 36 36 36 34 32 30 28 26 25 25 24 22 20 19 20 23 31 42 56 69 77 88 88 87 83 77 70 63 59 50 46 41 38 36 35 33 32 27 26 25 23 21 20 19 18 17 17 17 18 19 20 22 22 26 25 24 22 21 21 21 21 19 21 23 24 25 25 25 24 23 22 21 20 19 18 17 16 15 15 15 14 14 14 13 13 14 14 14 14 14 14 14 14 12 12 11 10 10 9 8 8 7 7 7 8 9 10 11 12 13 13 13 13 13 13 13 13 9 9 9 8 8 7 7 7 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 9 9 10 11 12 12 13 13 13 13 12 12 12 12 13 13 12 12 11 12 13 14 15 16 16 16 16 17 17 18 18 18 17 17 18 18 18 19 19 19 18 17 17 17 17 17 18 19 22 22 23 25 27 30 32 34 34 34 33 31 29 26 24 23 20 19 19 18 19 19 20 20 22 21 21 22 24 28 32 34 39 41 43 42 39 35 33 32 26 26 26 26 27 28 30 31 31 31 31 31 32 32 32 32 33 34 35 37 39 41 42 43 46 46 46 46 46 45 43 43 46 45 44 43 41 39 37 37 37 36 33 30 28 26 25 24 22 24 27 29 32 38 44 49 54 58 64 69 71 70 67 65 59 58 58 58 59 60 61 62 62 62 61 61 60 57 51 47 38 36 33 31 32 35 39 41 47 48 50 52 53 53 52 52 51 51 52 53 53 53 52 51 49 50 51 51 48 42 36 33 26 28 32 38 45 50 52 52 43 38 33 30 31 35 37 39 43 44 46 47 49 53 58 61 70 78 88 93 91 85 80 77 83 90 100 110 111 102 86 73 59 60 64 71 77 75 66 57 45 42 40 42 48 52 53 51 42 39 35 34 36 41 44 46 50 50 48 45 41 37 33 31 25 25 24 23 23 26 32 36 40 39 37 33 29 27 27 29 36 37 37 37 39 46 57 65 74 73 68 57 47 42 46 51 60 69 73 65 53 43 34 28 29 32 36 38 38 34 29 26 24 24 25 25 28 33 40 46 54 59 61 57 51 45 36 26 23 23 23 24 28 33 37 40 41 39 36 32 28 25 23 22 24 28 34 40 43 43 41 39 34 30 24 21 22 25 27 28 28 27 26 24 22 20 18 18 20 19 18 18 20 23 26 28 32 32 33 32 30 28 25 24 22 23 23 23 23 27 32 36 42 48 53 53 53 54 50 44 40 38 36 35 35 35 32 30 27 25 23 23 23 23 21 19 20 21 25 33 45 58 71 78 89 88 86 82 77 70 64 60 52 48 44 41 39 37 34 32 26 25 23 21 20 19 18 18 18 19 19 21 22 24 25 25 26 25 23 21 20 19 19 19 19 20 22 23 24 24 23 22 19 19 18 17 16 15 14 14 13 13 13 12 12 12 11 11 11 12 12 13 14 14 15 15 12 12 11 10 10 9 8 8 8 7 7 7 8 9 11 11 12 12 12 12 12 12 12 12 9 9 9 8 8 7 7 7 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 8 9 9 10 11 12 12 12 13 13 12 11 11 12 13 13 12 12 11 12 13 14 15 16 16 16 17 18 18 19 19 20 19 19 19 19 19 19 19 19 18 17 17 17 17 18 19 19 21 22 23 25 27 30 31 32 34 34 32 30 28 25 22 21 19 18 17 17 17 17 17 18 19 20 21 23 26 29 32 34 40 41 41 39 35 31 29 28 23 25 27 30 32 34 35 36 36 36 36 36 36 37 38 39 41 41 43 45 47 48 49 50 52 52 53 53 52 50 49 48 49 48 45 42 40 40 40 40 41 39 36 32 28 26 24 23 22 24 27 31 34 40 46 51 53 56 60 63 64 63 60 57 53 54 54 55 55 56 57 58 58 58 60 62 62 59 54 49 42 40 36 33 32 35 38 41 45 46 49 51 51 50 48 47 43 41 40 38 37 37 37 38 37 38 39 39 37 33 29 26 23 27 34 43 51 55 56 54 45 40 33 29 29 30 31 31 36 38 41 45 48 51 53 54 59 66 76 81 81 77 73 71 77 86 100 112 115 106 91 79 67 68 73 81 87 84 74 64 48 44 41 43 49 55 56 54 44 40 34 31 32 36 42 46 54 55 57 57 54 48 41 37 28 26 24 23 25 30 37 41 48 47 44 39 34 31 31 32 39 39 39 39 43 54 69 81 89 89 84 72 59 50 49 52 62 70 72 64 53 43 34 27 25 27 31 33 33 31 28 26 24 25 26 27 29 35 43 48 52 56 56 50 44 39 30 22 18 20 22 25 28 31 34 35 36 34 31 28 25 24 24 24 26 30 38 44 48 49 48 46 39 34 28 23 22 24 27 30 31 30 29 27 25 22 20 19 21 20 19 19 20 22 25 27 31 32 33 34 34 32 31 30 29 28 27 26 27 31 38 43 50 56 59 57 56 54 49 43 39 37 34 33 33 32 29 27 23 22 20 20 21 21 20 18 18 20 25 33 44 56 67 74 82 81 78 74 69 63 58 56 51 48 45 42 40 37 33 30 24 23 21 19 18 18 18 19 20 21 22 24 25 27 27 28 26 25 23 21 19 18 18 18 19 20 21 23 23 22 21 20 16 16 15 14 13 12 12 11 12 11 11 11 10 10 10 9 9 10 10 12 13 14 15 16 12 12 11 10 10 9 8 8 8 7 7 7 8 9 10 10 11 11 11 11 11 11 11 11 9 9 9 8 8 7 7 7 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 8 8 8 9 10 11 11 12 13 12 11 11 11 11 12 13 12 12 11 12 13 14 15 16 16 16 17 18 19 19 20 21 21 21 21 21 21 21 20 20 19 18 18 17 17 18 19 19 20 21 23 25 27 29 30 30 32 32 30 28 26 23 20 18 18 17 16 16 15 16 16 17 18 19 22 24 28 31 33 35 39 39 38 35 30 27 26 26 24 27 31 36 39 41 41 41 40 40 40 40 41 43 44 45 49 50 52 54 55 55 55 55 55 56 58 59 59 58 56 55 51 48 44 40 38 39 40 42 45 43 40 36 32 29 27 26 25 28 31 33 36 40 45 49 48 50 53 55 54 52 48 46 46 47 49 50 52 53 54 54 54 55 57 60 62 60 55 52 47 44 40 37 36 37 40 42 42 43 45 46 46 44 41 39 35 33 31 28 27 28 28 29 31 31 32 32 30 28 25 23 25 30 38 47 55 58 56 54 45 40 34 29 28 27 27 27 30 32 36 41 45 46 46 45 47 52 59 64 66 65 63 62 70 80 96 109 113 106 94 84 76 78 83 92 97 93 81 71 51 45 40 43 52 59 61 60 49 45 38 32 30 33 39 44 55 59 65 68 67 61 53 48 37 33 29 28 31 36 42 46 54 53 50 45 40 37 36 37 40 41 41 42 49 63 80 93 104 104 99 87 71 59 55 56 65 71 72 65 54 45 36 28 24 25 28 30 31 30 28 26 25 26 27 28 31 38 45 51 55 57 55 47 39 34 26 18 16 18 22 25 28 30 30 30 32 30 28 26 25 25 26 27 27 31 37 43 48 50 51 51 43 39 33 27 24 25 28 31 34 34 33 31 29 25 23 21 22 21 20 19 20 23 25 27 32 33 36 38 40 40 40 39 38 37 35 33 33 37 44 49 56 60 62 59 56 53 47 40 35 33 31 30 29 28 26 24 21 19 18 18 20 20 19 17 19 21 26 33 43 53 62 67 72 70 67 63 59 55 52 50 48 46 44 42 40 37 32 28 23 22 20 18 17 18 19 20 22 23 25 27 28 29 29 28 25 24 22 21 19 19 18 18 20 20 22 22 22 21 20 18 14 13 13 12 12 11 10 10 10 10 10 9 9 9 8 8 8 8 9 11 12 14 15 16 12 12 11 10 10 9 8 8 8 7 7 7 7 8 9 9 11 11 11 11 11 11 11 11 9 9 9 8 8 7 7 7 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 7 7 8 8 9 10 11 11 12 12 11 11 11 11 12 12 12 12 11 12 13 14 15 16 16 17 18 19 20 21 22 22 24 24 23 23 23 22 22 22 21 20 19 18 18 18 18 18 19 20 22 24 26 27 28 28 29 28 27 26 23 21 18 17 16 16 15 15 15 16 16 17 19 21 24 27 30 32 34 34 36 36 34 31 27 25 25 26 29 32 38 44 48 48 47 46 44 43 43 43 45 47 49 51 56 57 59 60 60 59 58 57 57 59 62 65 66 66 65 64 54 50 44 39 36 37 39 41 46 45 42 38 35 32 30 30 30 32 34 36 37 39 42 45 44 45 47 48 47 44 41 39 41 42 44 47 48 49 50 50 51 51 53 56 58 58 55 52 47 45 42 40 39 39 40 41 40 40 41 41 40 38 37 35 33 32 30 28 27 26 26 25 28 28 27 26 25 24 22 21 28 33 41 50 56 58 55 52 44 40 34 30 28 28 28 27 29 30 33 38 41 41 39 36 36 38 42 47 50 52 52 52 63 73 89 102 108 104 96 90 83 85 91 99 104 98 85 74 51 44 39 43 54 64 67 66 55 50 42 34 29 30 35 40 54 61 70 77 79 74 67 61 50 45 40 38 40 44 48 50 57 56 54 49 44 41 41 43 42 43 44 47 53 67 84 97 111 111 107 95 79 67 62 63 67 72 72 65 55 47 38 30 27 28 29 30 30 29 28 27 25 26 28 29 33 40 48 54 61 62 56 45 36 29 21 14 16 19 22 26 28 28 28 27 27 27 27 26 27 27 28 29 28 30 33 37 42 47 51 53 47 44 39 32 27 27 29 32 37 36 36 34 31 28 24 22 22 21 20 20 21 23 26 28 32 34 38 42 46 48 50 50 49 48 45 42 41 43 49 53 56 60 62 58 53 50 43 35 30 28 25 25 25 24 22 20 19 17 16 17 19 20 19 18 21 23 28 34 42 50 56 60 61 59 56 53 50 47 46 45 44 43 42 41 40 37 31 27 23 21 19 17 17 19 21 22 24 25 27 29 30 29 28 28 24 23 22 21 20 20 20 20 21 22 23 23 22 21 19 18 13 13 12 12 11 11 11 10 10 10 9 9 9 8 8 8 7 8 9 10 12 13 14 14 12 12 11 10 10 9 8 8 8 8 7 7 7 7 8 8 10 10 10 10 10 10 10 10 9 9 9 8 8 7 7 7 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 6 6 7 8 9 9 10 10 12 11 11 10 10 11 11 12 12 12 11 12 13 14 15 16 18 18 19 21 22 23 24 25 26 26 26 25 25 24 24 24 23 22 20 19 17 17 17 17 17 19 21 23 25 26 26 25 25 25 24 23 21 19 17 16 15 15 15 15 15 16 18 18 21 23 26 30 32 34 34 34 33 32 31 28 24 23 25 27 35 39 46 52 55 55 52 50 46 45 45 45 47 50 53 55 60 61 62 62 61 59 57 55 57 60 64 69 72 72 72 71 64 59 50 42 37 37 39 41 44 42 40 37 35 33 32 31 33 35 37 37 37 38 41 43 40 42 44 46 46 44 42 40 40 41 43 44 45 45 45 44 47 47 48 50 53 53 51 49 46 45 44 43 42 41 40 40 41 41 41 41 41 41 41 41 40 40 40 38 36 33 30 28 28 27 26 25 24 23 22 22 29 33 40 49 55 56 53 49 42 38 34 31 30 31 30 30 31 31 32 36 39 38 34 30 29 29 30 33 37 41 43 45 56 65 80 93 99 99 95 92 86 89 95 103 106 100 85 73 50 42 37 43 56 68 73 73 63 58 50 39 31 30 34 38 53 61 73 83 87 85 79 74 63 58 52 48 49 52 53 53 56 56 54 50 46 44 45 46 44 46 48 50 55 66 81 91 104 105 102 92 78 68 65 66 66 71 70 63 55 48 40 32 32 32 31 31 30 29 28 27 26 27 28 30 34 41 50 56 62 61 55 43 34 28 21 15 18 20 23 26 27 27 26 25 23 24 25 27 28 29 29 29 28 28 27 29 34 41 49 53 49 48 44 37 31 28 30 33 37 37 37 35 32 28 24 22 22 21 20 20 21 24 27 29 31 34 39 45 50 54 57 58 59 57 54 50 48 48 52 55 53 57 58 53 48 44 37 29 24 22 20 20 20 20 18 16 18 16 16 17 19 20 19 18 22 23 27 32 37 43 47 50 49 48 45 42 40 39 39 40 41 41 41 42 42 38 33 28 23 22 19 18 18 20 22 24 26 27 29 30 30 29 27 26 24 23 22 22 22 22 23 23 22 23 24 24 23 21 19 18 13 13 13 13 12 12 12 12 10 10 9 9 9 8 8 8 8 8 9 10 11 12 12 13 12 12 11 10 10 9 8 8 8 8 7 6 6 7 7 8 9 9 9 9 9 9 9 9 9 9 9 8 8 7 7 7 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 6 6 7 7 8 9 10 10 12 11 11 10 10 11 11 12 12 12 11 12 13 14 15 16 20 20 21 22 24 25 26 27 28 28 27 27 26 26 25 25 24 23 21 19 17 16 16 16 16 18 20 23 24 25 24 24 22 22 22 21 20 18 16 15 14 14 14 15 16 17 19 19 22 24 28 31 34 35 34 34 30 30 28 26 23 23 25 28 39 44 51 57 60 58 55 52 47 46 46 46 48 51 55 57 61 62 62 62 61 58 55 53 57 60 66 71 75 76 76 76 74 68 57 47 41 40 41 43 40 39 37 35 33 32 32 31 34 36 38 38 38 38 40 42 39 41 44 46 48 47 46 45 40 41 42 43 43 42 41 40 44 44 44 46 48 50 49 47 46 46 46 46 45 43 42 41 45 45 45 45 46 47 48 49 49 50 50 49 46 41 36 32 31 30 28 26 25 24 24 24 27 31 39 47 53 54 51 48 41 38 33 31 32 33 33 32 33 33 33 36 38 37 32 28 26 24 23 25 30 35 39 41 49 59 72 84 91 93 92 90 87 90 96 104 107 99 84 71 49 41 36 42 57 71 77 76 69 65 56 44 35 31 34 39 52 60 74 86 92 91 86 82 72 66 59 55 55 56 56 55 54 54 53 49 46 45 46 48 46 48 50 51 55 64 76 85 94 96 94 85 74 65 64 66 65 69 69 62 55 49 40 32 35 34 33 32 31 29 28 27 26 27 29 31 35 42 51 57 57 57 51 41 33 29 25 19 20 22 24 26 27 26 25 24 20 22 24 27 29 29 29 29 29 26 24 24 28 37 47 53 51 50 47 41 34 30 31 33 36 37 37 35 32 28 24 21 21 20 20 20 21 24 28 30 30 33 39 46 52 58 61 62 64 63 60 56 52 51 53 56 50 54 54 49 44 40 32 24 20 18 17 17 18 18 16 15 17 16 16 17 19 20 20 19 19 21 24 28 32 37 40 41 41 39 36 34 32 33 34 35 40 41 42 43 43 40 34 29 23 22 19 18 18 20 23 25 27 28 30 31 30 29 26 25 23 23 22 22 23 23 24 25 23 24 24 24 23 21 19 18 14 14 13 13 13 13 13 12 10 10 10 9 9 8 8 8 8 8 9 10 10 11 12 12 12 12 11 10 10 9 8 8 8 8 7 6 6 6 7 7 9 9 9 9 9 9 9 9 9 9 9 8 8 7 7 7 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 7 7 7 8 8 9 9 9 10 10 9 9 9 10 11 11 11 12 12 13 15 17 19 20 21 22 24 26 27 28 28 28 30 30 31 31 30 28 26 24 24 23 21 19 17 16 16 16 15 15 16 18 19 20 21 22 21 21 20 20 18 17 15 14 16 17 17 16 16 17 20 22 28 31 35 38 39 38 35 33 30 29 26 25 26 30 34 37 44 48 53 58 59 57 53 50 48 44 41 42 46 51 53 53 59 59 59 57 56 53 51 50 57 61 66 71 75 80 86 90 83 76 67 60 54 48 42 37 40 36 32 30 32 35 37 37 36 38 40 38 36 36 38 41 45 47 50 54 56 56 53 49 48 43 39 39 38 34 35 39 37 40 43 44 43 41 41 41 38 39 41 43 46 48 49 50 50 47 48 52 55 56 59 65 69 71 70 64 59 53 44 34 35 33 30 28 28 28 28 27 32 36 41 44 50 54 50 43 42 33 26 29 35 38 40 42 40 41 39 36 36 37 32 24 23 22 21 22 25 30 36 40 45 55 69 79 83 84 85 85 82 86 92 98 97 87 72 61 44 41 42 48 60 70 74 74 70 62 52 45 38 32 34 39 46 54 67 82 92 96 93 90 82 76 68 63 60 57 54 51 48 48 48 46 44 43 44 45 43 43 44 47 52 58 63 66 75 75 74 71 68 64 60 57 57 56 53 50 46 43 40 38 37 39 39 38 34 30 28 28 26 27 29 33 38 44 49 52 56 53 46 39 32 27 24 22 21 22 24 26 27 27 26 25 22 18 18 23 28 30 34 39 32 32 28 23 26 36 46 49 51 51 49 44 37 32 30 30 31 33 35 34 30 26 23 22 20 21 22 23 24 25 26 26 32 34 39 44 49 54 56 58 64 63 62 59 56 53 51 49 49 48 46 42 37 31 26 23 16 16 15 15 15 17 19 20 20 20 20 20 20 20 21 21 24 24 26 27 30 32 35 36 36 35 34 33 33 33 33 34 39 41 45 46 45 41 37 33 23 22 20 20 20 20 22 22 26 27 28 28 28 26 24 23 23 22 22 21 21 22 23 23 26 26 26 25 24 23 21 20 20 19 17 15 13 12 11 11 11 11 11 11 10 9 8 7 8 8 8 9 9 10 10 11 9 9 9 8 8 7 7 7 7 7 7 8 8 9 9 9 10 10 10 10 10 10 10 10 9 9 9 8 8 7 7 7 8 8 7 6 6 5 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 7 7 7 8 8 8 9 9 10 10 9 9 9 10 11 12 13 13 13 14 16 18 20 21 23 24 25 27 28 29 29 29 31 31 32 32 31 29 26 25 24 23 21 19 17 16 16 15 14 14 15 17 18 19 20 21 19 19 19 18 17 16 15 14 16 17 18 18 18 20 23 26 31 33 37 40 41 39 37 35 32 31 28 27 29 32 36 39 44 48 52 56 56 54 50 47 43 39 36 36 40 44 46 47 54 54 55 54 53 52 50 49 50 54 61 67 75 83 90 96 96 90 81 72 63 54 44 38 38 35 31 30 33 36 38 39 38 39 40 38 36 37 41 44 49 51 56 61 65 64 59 56 51 45 40 38 36 32 33 38 37 40 42 42 40 38 37 36 36 38 41 44 48 51 53 55 58 56 57 61 64 67 73 80 89 91 88 79 71 62 50 39 36 33 30 29 29 30 31 32 37 43 48 51 56 58 53 45 42 32 26 29 35 39 43 47 46 46 42 38 37 38 34 27 25 25 24 25 29 34 39 42 46 54 64 72 75 76 76 76 72 75 79 83 82 74 62 53 45 44 46 54 65 72 74 72 65 57 49 44 38 32 33 38 44 50 62 75 86 90 89 86 81 75 67 60 57 53 49 46 45 46 46 44 41 40 41 42 41 41 42 44 46 50 53 54 57 58 58 58 56 54 51 50 51 50 47 44 42 39 38 37 37 39 40 38 34 31 29 29 28 29 31 34 38 42 46 48 51 48 43 37 31 27 24 23 24 25 26 28 28 28 27 26 23 18 16 21 26 32 39 46 48 48 43 35 34 39 43 44 50 49 46 40 34 29 28 28 30 32 34 33 29 25 22 22 19 20 23 25 27 28 29 29 31 33 36 40 44 48 52 53 58 58 57 56 54 51 48 47 45 45 43 41 36 31 26 24 20 19 18 17 17 18 19 20 20 20 20 20 20 20 19 19 22 23 24 26 29 32 34 36 35 34 33 32 32 33 33 34 38 41 44 47 47 44 40 37 27 25 23 20 19 19 20 21 23 24 25 25 25 24 23 22 23 22 21 21 21 21 21 22 25 25 25 25 24 23 22 21 21 19 18 16 14 13 12 12 12 12 12 12 11 10 9 8 7 8 8 8 9 9 10 10 9 9 8 8 8 7 7 7 7 7 7 8 8 8 9 9 10 10 10 10 10 10 10 10 9 9 9 8 8 7 7 7 8 8 7 6 6 5 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 7 7 7 7 8 8 8 9 10 10 9 9 10 11 12 12 14 15 15 16 18 20 22 23 25 26 27 29 30 31 31 31 32 33 33 33 31 29 27 25 23 22 20 18 17 15 15 15 13 13 14 15 16 17 18 19 17 17 17 16 16 15 15 15 16 17 20 21 22 24 28 31 34 36 40 42 43 42 40 38 35 34 32 31 32 35 39 41 43 45 49 51 50 47 43 41 37 34 31 31 33 37 39 40 46 47 49 50 50 49 48 47 46 50 56 64 72 83 93 99 104 101 94 86 75 62 49 41 36 34 32 32 36 40 42 43 42 41 40 37 36 38 43 46 53 56 63 70 74 72 67 62 53 45 39 35 32 29 32 37 39 41 42 41 37 34 32 32 35 37 42 47 53 57 60 62 68 65 65 70 74 79 90 100 113 115 110 98 84 70 55 43 36 34 31 30 30 33 37 39 44 51 57 60 62 62 55 46 41 32 26 29 36 42 49 55 56 55 50 42 39 40 37 31 30 30 30 31 34 39 43 46 47 52 58 62 63 63 63 63 60 61 62 63 62 57 51 45 44 46 52 62 70 74 71 67 57 50 44 41 37 32 32 36 40 44 53 64 74 79 80 79 76 71 63 56 51 47 43 41 42 42 42 39 37 35 36 37 37 38 38 39 39 39 39 39 37 38 40 42 43 43 42 42 42 41 38 36 35 35 35 36 37 38 39 37 34 31 30 30 31 32 33 36 38 40 42 43 43 41 37 33 29 27 26 25 28 28 29 30 30 30 29 29 25 19 15 19 25 34 48 59 66 67 63 53 45 44 43 40 48 46 42 35 29 25 24 25 28 31 32 31 28 24 22 21 19 21 25 30 33 34 34 34 33 33 33 34 36 39 42 44 47 48 49 50 49 46 44 42 40 41 40 39 36 32 28 25 25 24 23 22 21 20 20 21 21 21 20 20 19 18 18 17 19 20 21 24 27 30 33 34 33 33 32 32 32 33 33 34 37 40 44 46 47 45 42 39 31 28 24 20 18 18 19 20 20 20 21 22 22 22 21 21 23 22 21 20 19 19 20 20 23 23 24 24 24 24 23 22 21 20 19 17 15 14 14 14 13 13 13 13 12 11 9 9 7 7 7 8 8 8 9 9 9 8 8 8 7 7 7 7 7 7 7 7 8 8 8 9 10 10 10 10 10 10 10 10 9 9 8 8 8 8 7 7 8 8 7 6 6 5 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 6 6 7 7 7 8 8 8 10 10 9 10 10 11 13 13 16 16 17 18 20 22 23 25 27 28 30 31 32 32 32 32 33 34 34 34 32 30 27 26 22 21 19 17 16 15 14 14 12 12 13 14 15 16 16 17 15 15 15 15 15 15 15 16 16 19 22 24 26 29 33 36 37 39 42 44 44 43 41 40 37 36 34 33 34 36 39 41 39 40 42 43 41 38 35 33 32 30 28 27 28 31 34 36 40 42 44 46 48 47 46 46 46 49 54 60 68 79 91 98 105 104 101 94 84 70 57 48 38 37 37 40 44 47 49 49 48 45 40 36 35 37 41 45 52 57 64 71 76 74 67 62 49 41 34 30 28 27 31 37 42 44 44 42 38 34 32 32 37 41 46 53 60 65 68 70 73 70 69 73 78 87 102 116 130 131 126 111 92 74 56 43 37 35 33 32 32 37 43 47 50 58 66 68 68 65 57 47 41 33 26 29 37 45 56 65 69 67 60 50 44 43 40 36 36 36 37 38 41 44 47 49 49 50 52 52 52 51 51 51 50 48 47 46 45 44 43 42 43 49 58 68 74 72 66 60 47 41 38 38 36 33 32 34 35 37 42 50 59 65 68 69 67 63 56 50 45 41 39 37 37 38 37 35 32 31 32 33 33 34 35 36 35 33 30 29 27 29 31 34 36 36 36 36 33 32 31 29 30 31 33 34 35 36 37 35 33 31 31 32 32 33 35 37 38 38 38 38 35 33 31 29 27 27 27 27 29 29 30 32 32 33 34 34 29 22 16 18 26 39 58 73 81 84 81 70 59 52 46 41 44 42 37 30 24 21 21 23 27 29 31 30 27 23 21 20 20 24 30 36 40 42 42 42 38 36 33 31 30 30 31 32 34 36 39 41 41 39 37 35 37 38 39 39 38 35 31 29 30 30 28 26 24 22 21 21 21 21 20 19 18 17 16 16 16 17 19 21 24 28 31 33 33 32 32 32 32 33 34 34 36 38 41 43 43 41 39 36 30 27 23 19 17 17 18 20 18 18 19 20 20 21 21 21 23 22 21 19 19 18 19 19 21 22 23 24 25 25 24 24 22 21 20 18 17 16 16 16 15 15 15 15 13 12 10 10 7 7 7 8 8 8 8 8 8 8 8 7 7 7 6 6 6 6 7 7 7 8 8 8 9 9 9 9 9 9 9 9 8 8 8 8 8 8 8 8 8 8 7 6 6 5 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 6 6 6 7 7 7 8 8 10 10 10 10 11 12 14 14 17 18 18 19 21 23 25 26 29 30 31 32 33 33 33 33 34 34 34 34 32 29 27 25 22 20 19 17 15 14 13 13 12 12 12 13 14 14 15 15 14 14 13 13 14 15 17 18 19 22 25 28 30 32 35 38 39 40 42 43 44 43 41 40 38 36 34 33 33 34 35 36 32 33 33 33 32 30 27 26 26 25 24 22 23 26 30 33 38 40 43 46 47 47 46 45 45 46 50 55 63 75 88 96 104 105 104 99 89 75 63 56 46 47 50 54 58 59 58 56 53 48 41 36 34 36 39 41 49 52 58 64 67 66 60 55 42 34 27 25 25 26 32 39 46 47 47 45 41 39 38 38 44 48 54 60 66 71 73 74 75 71 69 71 76 88 108 125 138 140 135 119 97 76 57 43 36 36 35 34 35 39 47 53 59 68 75 76 74 70 60 51 43 34 27 29 37 48 63 75 82 82 75 63 54 50 45 40 41 42 43 44 46 48 50 50 50 48 46 44 43 42 42 41 39 37 35 33 33 35 38 40 48 55 65 74 77 71 62 54 39 33 31 34 35 34 33 35 32 32 34 39 46 52 56 58 55 53 48 42 38 35 34 35 33 33 33 31 29 28 29 31 31 32 34 35 34 32 29 27 26 28 30 32 33 33 32 32 28 28 27 27 28 30 31 32 33 34 35 34 33 32 33 35 34 36 38 39 39 38 36 35 30 29 27 26 26 27 28 29 28 29 30 32 34 36 37 38 32 25 19 20 28 43 65 84 97 102 100 87 71 59 48 41 40 37 33 27 21 19 20 22 26 28 30 30 27 23 21 21 24 28 34 41 46 49 50 50 46 43 37 32 27 24 23 23 24 26 29 31 32 32 31 30 36 37 40 42 41 39 36 33 34 33 31 29 26 24 22 20 20 20 19 18 17 16 15 15 15 16 17 20 23 26 29 30 32 32 31 31 31 32 32 33 34 35 37 38 37 35 32 30 26 23 20 18 17 18 20 21 19 19 19 19 20 21 21 22 22 21 20 19 19 19 19 19 22 22 24 25 25 26 26 25 23 23 21 20 18 18 18 18 17 17 17 16 15 13 12 11 8 8 8 8 8 8 8 8 8 8 7 7 7 6 6 6 6 6 6 7 7 7 8 8 9 9 9 9 9 9 9 9 8 8 8 8 8 8 8 8 8 8 7 6 6 5 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 5 6 6 6 7 7 7 7 10 9 10 10 11 13 14 15 18 18 19 20 21 23 25 26 30 31 32 33 33 33 33 33 34 34 34 33 31 28 26 24 21 20 18 16 14 13 13 12 12 12 13 13 14 14 14 15 13 13 12 13 14 16 19 20 22 25 29 31 32 33 35 37 38 39 40 41 41 40 39 38 36 35 33 30 29 28 29 29 26 26 26 26 25 24 24 23 21 22 21 20 20 23 28 32 40 43 46 49 50 49 46 45 39 40 42 47 55 69 83 93 104 105 105 99 89 77 67 62 58 61 66 72 75 74 69 64 56 50 43 38 36 38 40 41 46 46 49 52 54 53 49 45 35 29 23 23 24 26 33 41 48 49 50 49 47 46 46 48 53 56 61 66 70 73 73 74 74 69 65 65 69 83 107 127 142 146 142 124 100 77 56 42 35 36 37 37 37 41 49 55 66 75 83 83 79 73 65 57 45 36 29 30 37 50 68 83 96 97 93 81 69 61 53 46 46 47 48 49 50 50 49 49 47 43 40 37 37 37 36 35 30 29 28 27 28 31 37 42 55 62 72 78 77 69 58 51 33 27 24 29 34 35 35 37 32 31 30 33 38 44 48 49 46 45 41 36 31 29 29 31 29 30 30 29 28 28 29 31 32 33 35 35 35 33 31 29 29 30 31 32 32 31 29 28 28 29 29 30 31 31 31 32 32 33 35 35 35 36 39 41 41 43 44 45 43 39 35 32 28 28 26 26 26 28 29 30 29 29 30 31 33 35 37 39 33 26 21 22 29 44 68 88 109 114 113 98 78 61 47 39 35 34 31 26 21 19 20 22 26 28 30 30 27 24 22 21 26 30 36 43 48 52 54 55 53 49 43 36 30 24 21 19 20 21 22 24 26 27 27 28 35 38 41 44 44 42 39 36 34 34 32 30 27 24 21 20 19 18 18 17 16 16 15 15 16 16 17 19 22 24 27 28 31 31 30 29 28 28 29 29 30 31 32 32 31 29 26 24 22 21 20 19 20 20 22 23 20 20 19 19 19 20 21 22 21 21 20 20 20 20 21 22 23 24 25 26 27 27 27 26 24 24 22 21 20 20 20 20 19 19 19 18 16 14 13 12 10 10 10 9 9 9 8 8 7 7 7 7 6 6 6 5 5 6 6 6 7 7 7 7 8 8 8 8 8 8 8 8 7 7 8 8 8 8 9 9 8 8 7 6 6 5 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 5 5 6 6 6 7 7 7 9 9 10 10 12 13 15 16 18 18 18 20 21 23 25 26 31 31 32 33 33 33 33 32 33 33 33 32 30 27 24 23 20 19 17 15 14 13 12 12 13 13 13 14 14 14 14 15 13 12 12 12 14 17 20 22 25 28 31 33 33 33 34 35 36 36 37 38 38 37 36 35 34 33 30 27 24 22 21 21 21 21 21 22 22 23 23 24 22 24 24 24 24 27 33 38 45 48 51 53 53 51 47 45 37 37 37 39 46 59 73 83 95 96 96 92 84 75 70 68 70 75 82 90 92 87 79 72 57 51 44 41 41 43 44 44 45 43 41 41 41 41 39 37 34 28 23 24 26 28 34 42 48 49 51 51 51 52 55 57 60 62 66 69 71 71 70 69 68 62 56 54 57 72 98 121 143 148 144 126 100 75 53 39 33 36 39 40 39 42 49 56 67 76 83 82 77 72 64 57 47 38 30 30 38 52 72 88 108 112 110 99 84 72 61 52 49 50 51 52 51 50 48 46 41 38 34 32 33 34 33 31 26 28 29 29 31 35 43 48 59 65 73 76 73 63 52 45 30 23 20 26 33 36 37 40 36 33 31 32 36 40 43 44 41 41 37 32 25 22 23 26 26 28 29 28 28 28 31 33 35 36 36 36 35 34 32 31 34 34 35 35 34 33 31 29 31 32 34 35 35 34 32 31 33 34 36 37 39 41 45 49 52 53 54 52 48 41 34 30 29 28 27 27 27 28 30 31 31 31 30 30 31 32 34 35 31 26 22 23 29 43 66 86 106 113 112 97 75 57 44 35 31 31 30 27 23 21 22 23 26 28 31 30 28 25 23 22 28 30 35 41 47 52 55 57 55 53 48 42 35 29 24 22 20 20 20 21 23 25 27 29 35 37 42 45 45 43 40 37 33 33 32 30 27 24 21 19 17 17 16 16 16 16 16 16 17 18 18 19 21 23 25 26 29 28 26 25 23 23 23 23 25 26 28 28 28 26 24 22 22 23 23 23 24 23 23 23 21 20 19 18 18 18 19 20 20 20 20 20 21 22 23 24 26 26 27 28 28 28 27 27 25 24 23 22 21 21 21 21 21 21 20 19 17 15 14 12 12 11 11 11 10 10 9 9 7 7 7 6 6 6 5 5 5 5 6 6 6 7 7 7 8 8 8 8 8 8 8 8 7 7 7 8 8 9 9 9 8 8 7 6 6 5 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 5 5 5 6 6 7 7 7 9 9 10 11 12 14 15 16 18 18 18 19 21 23 25 26 31 31 32 33 33 33 32 32 33 33 33 32 29 26 23 22 20 19 17 15 13 12 12 12 13 14 14 14 14 14 15 15 13 13 12 13 15 18 22 24 27 30 33 34 33 33 33 34 34 35 35 35 35 35 34 33 33 31 28 24 21 18 17 16 19 19 19 20 21 23 25 25 27 28 30 29 29 33 40 45 49 51 54 56 55 52 48 46 39 37 35 34 39 49 63 72 82 85 86 83 78 74 73 74 78 84 93 100 102 95 84 76 56 51 45 43 45 48 49 49 46 42 37 34 34 34 33 32 35 29 25 26 28 29 35 41 47 49 51 52 53 56 59 62 64 66 69 71 71 69 66 64 61 54 47 44 46 61 89 113 143 148 144 125 98 71 49 34 32 36 40 41 40 42 49 55 64 73 80 78 73 68 61 55 48 39 31 30 38 52 73 91 116 121 121 110 95 80 66 56 51 52 53 53 52 49 46 45 37 33 30 29 31 32 31 29 28 30 33 35 37 42 49 55 58 64 70 72 66 56 45 38 28 21 18 24 32 36 39 41 39 36 34 33 36 40 42 42 40 40 36 29 22 18 19 21 25 27 28 28 28 29 32 34 38 38 38 37 35 34 32 31 38 38 39 39 38 36 34 33 33 35 37 39 39 36 33 31 34 36 38 40 42 45 50 54 61 62 61 58 51 42 34 28 30 30 28 27 28 29 30 31 34 33 31 30 29 29 30 31 29 24 21 23 28 41 63 83 95 103 104 90 70 53 41 33 28 29 29 28 25 23 23 24 26 29 31 31 28 25 23 23 28 30 34 39 45 50 55 57 56 54 51 46 40 33 29 26 22 21 20 20 22 25 28 30 34 37 41 45 45 43 39 37 32 32 31 30 27 24 20 18 15 15 16 16 16 16 16 16 19 19 19 20 21 22 24 25 26 25 23 21 20 19 18 18 22 23 25 26 26 26 24 23 24 25 26 27 27 25 24 23 21 20 18 17 16 16 17 18 20 20 20 21 22 24 25 26 28 28 29 29 29 28 28 27 26 25 24 23 22 22 22 22 22 22 21 20 18 16 14 13 13 12 12 11 11 10 10 10 7 7 7 6 6 5 5 5 5 5 5 6 6 7 7 7 8 8 8 8 8 8 8 8 7 7 7 8 8 9 9 9 8 8 7 6 6 5 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 7 7 7 8 8 9 9 9 10 10 11 12 14 15 16 17 19 19 21 22 24 26 27 28 27 28 29 30 30 30 30 30 30 29 28 26 24 21 19 17 17 16 14 13 12 12 13 14 16 15 14 13 13 13 14 14 14 14 14 15 17 20 23 25 30 31 32 32 32 30 29 27 26 27 29 30 30 29 28 27 28 27 24 21 18 16 14 14 16 17 20 22 25 26 27 28 31 31 30 31 35 40 45 48 58 59 61 62 59 53 48 44 35 32 29 29 33 42 51 57 65 69 73 71 67 66 69 73 84 94 103 105 103 97 84 73 62 55 50 52 59 63 62 59 54 46 36 28 26 28 30 32 29 29 29 29 31 33 36 38 41 44 48 51 54 57 62 65 66 67 66 63 59 56 56 56 49 45 40 35 35 49 80 108 135 143 142 123 95 68 47 34 35 40 44 44 41 40 45 50 56 61 67 68 63 57 53 52 40 37 35 33 35 47 73 96 121 129 131 121 104 86 69 56 53 51 50 50 49 47 43 39 36 31 26 25 28 31 33 33 32 34 37 42 46 51 54 56 60 56 52 52 52 49 41 35 28 24 22 24 31 39 44 46 46 46 46 45 43 44 46 49 46 41 34 27 21 18 18 18 23 25 27 28 29 32 35 38 38 39 39 38 35 33 33 34 38 41 42 40 35 31 30 31 35 39 44 47 47 43 38 34 35 34 36 42 47 53 63 73 77 76 71 63 51 39 31 27 26 26 26 25 25 26 30 34 36 35 32 28 25 25 28 31 25 22 20 19 25 37 51 62 79 81 79 69 54 40 32 30 29 32 33 32 29 27 27 29 26 27 27 27 27 26 25 24 29 31 33 35 37 41 45 49 53 53 52 50 46 41 36 33 28 27 26 25 25 26 27 28 38 40 42 44 43 39 35 32 31 31 31 30 27 24 21 19 17 17 16 15 15 16 16 17 20 20 20 20 20 20 20 20 20 20 18 17 17 19 20 21 21 23 25 25 25 25 27 28 30 34 36 34 34 34 31 26 24 22 19 16 15 15 16 17 16 15 16 17 19 22 25 26 29 30 32 33 32 31 28 27 26 26 24 23 22 21 21 21 21 20 19 19 18 17 16 16 17 16 15 13 12 11 10 10 9 9 9 8 8 7 7 7 7 7 7 6 6 5 5 5 7 7 7 6 6 5 5 5 8 8 8 8 8 8 8 8 8 8 8 7 7 6 6 6 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 7 7 7 8 8 8 9 9 9 10 11 12 13 15 16 16 18 19 20 22 23 25 26 27 26 27 28 29 29 29 29 29 28 27 26 25 23 20 18 17 17 16 14 13 13 14 15 15 16 16 14 13 13 13 13 13 14 14 15 16 18 21 24 26 30 31 31 30 29 27 25 24 23 25 26 28 28 28 27 26 26 25 22 19 17 15 14 14 18 20 22 25 27 29 30 31 34 34 35 37 40 44 48 51 59 60 62 61 58 52 46 42 33 30 27 26 30 37 45 50 53 57 61 61 59 60 65 69 82 92 101 103 101 94 82 70 58 55 54 60 69 75 75 71 57 49 36 27 24 25 28 30 31 32 32 33 34 35 36 36 37 40 44 47 50 55 61 65 65 65 64 61 56 54 54 55 49 45 39 33 33 47 76 103 130 138 138 121 94 69 49 37 40 44 49 47 43 41 44 48 54 59 63 63 57 50 46 45 38 35 33 32 33 45 69 92 117 127 131 124 108 91 73 60 50 48 46 45 44 42 39 36 35 31 27 26 29 31 32 32 35 37 41 45 49 52 54 55 54 49 45 44 45 44 40 35 31 27 24 25 32 39 45 48 51 51 51 48 46 45 47 49 45 41 34 27 22 20 19 20 24 26 28 29 31 33 37 40 41 41 39 36 32 30 31 32 37 40 43 41 36 32 30 31 36 40 45 49 49 45 40 36 36 34 36 42 49 56 68 79 86 84 79 69 55 42 32 28 24 25 24 23 23 25 29 32 37 36 34 30 27 25 26 28 24 22 20 18 22 31 43 51 67 69 68 61 48 37 31 30 32 35 36 34 30 27 26 27 25 25 26 26 26 26 26 25 28 30 31 32 33 36 40 43 47 48 49 49 47 44 40 37 33 32 30 28 27 28 29 30 36 38 40 42 41 39 35 32 31 31 31 30 27 24 22 20 19 18 17 16 15 15 16 16 19 20 20 21 21 21 20 19 20 19 18 17 17 18 20 21 23 25 28 29 30 32 34 37 39 44 46 43 41 41 36 30 25 23 20 17 15 15 16 16 16 15 16 17 18 21 23 25 27 29 30 32 32 31 29 28 27 26 24 23 21 20 20 20 20 20 19 18 17 16 16 15 17 16 14 13 11 11 10 10 9 9 9 8 8 8 7 7 7 7 7 6 6 6 5 5 7 7 7 6 6 5 5 5 8 8 8 8 8 8 8 8 8 8 7 7 7 6 6 6 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 7 7 7 7 8 8 8 9 9 10 11 12 13 14 15 15 17 18 19 20 22 23 24 25 25 25 26 27 28 27 27 27 25 25 24 23 21 19 16 15 16 16 15 15 15 16 17 17 17 16 15 13 12 12 12 12 14 14 15 17 20 23 25 27 30 29 29 27 25 23 20 19 19 20 23 24 26 26 25 25 24 22 20 17 16 15 15 15 21 23 25 28 31 32 33 34 37 38 40 43 46 49 52 53 59 59 60 59 55 48 42 38 30 28 24 23 25 31 37 42 42 45 49 50 51 55 61 66 78 88 96 98 95 89 77 65 56 56 61 70 81 87 85 81 65 54 40 28 23 24 27 30 33 35 37 38 38 36 34 33 33 34 37 40 44 51 58 64 63 63 61 57 53 51 52 53 51 46 39 33 32 44 71 96 123 131 133 118 94 71 53 42 47 52 56 53 47 43 44 46 53 57 59 57 50 42 38 37 35 32 30 30 31 41 63 83 108 119 127 122 109 92 73 60 49 46 43 41 40 38 36 34 33 31 28 28 29 31 31 30 36 39 43 48 51 52 53 52 46 41 35 34 36 39 39 38 37 33 29 29 34 41 48 52 58 57 56 53 48 46 46 47 43 39 33 28 24 22 22 22 26 27 29 31 32 35 40 43 45 43 39 34 28 26 27 29 37 41 44 43 38 33 31 31 37 41 47 51 51 47 42 38 37 34 35 42 49 59 73 86 95 93 87 75 59 43 31 26 22 22 21 20 20 23 27 31 39 39 38 35 29 25 23 23 23 22 20 18 18 24 31 37 51 53 54 50 43 36 33 33 38 39 39 37 32 27 25 24 23 23 24 24 25 26 26 27 28 29 30 29 29 29 32 34 38 40 44 47 47 45 42 40 37 35 33 30 29 29 31 32 34 36 39 40 40 38 35 33 31 32 32 31 29 26 23 22 21 20 18 16 15 15 15 16 18 20 22 23 23 21 19 18 19 18 17 16 17 19 20 21 25 28 32 36 38 42 46 49 50 55 57 54 50 47 41 34 27 25 21 18 15 14 15 15 15 15 15 16 17 19 21 22 25 26 28 30 31 30 30 29 27 26 24 22 20 19 18 18 19 19 18 18 17 16 16 15 16 15 14 12 11 11 10 11 9 9 9 9 8 8 8 7 7 7 7 7 6 6 6 5 7 7 7 6 6 5 5 5 8 8 8 8 8 8 8 8 8 7 7 7 6 6 6 6 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 6 6 7 7 7 8 8 8 9 9 10 11 12 13 13 14 16 16 17 18 20 21 22 22 23 24 24 25 25 25 24 24 22 21 21 20 19 17 15 14 16 16 16 16 17 18 18 19 17 16 15 13 12 11 11 11 14 15 16 19 21 24 26 27 28 27 25 23 21 18 16 15 15 17 19 21 23 23 23 23 21 19 17 15 15 16 17 18 25 26 28 31 33 35 35 36 38 40 43 46 49 51 51 52 54 55 55 53 48 42 36 32 29 27 24 22 23 27 32 36 38 40 43 46 48 53 59 64 72 80 88 89 86 81 70 59 57 60 67 78 88 91 87 82 70 60 44 32 27 27 30 32 34 36 39 40 39 36 33 30 30 31 32 34 38 46 55 61 62 62 59 55 51 50 51 52 54 49 42 36 34 44 68 90 114 123 126 113 93 74 60 51 58 62 65 61 52 46 45 47 54 57 58 54 46 38 33 32 32 29 28 28 30 38 56 74 95 107 116 113 101 85 68 56 50 46 42 38 37 36 34 32 30 29 28 28 29 29 29 29 34 37 42 46 49 50 49 48 40 35 29 27 31 37 43 46 46 43 38 36 39 45 52 57 62 61 59 54 48 44 42 42 39 36 32 28 25 24 25 25 28 29 31 31 33 36 41 45 48 45 39 31 25 23 25 28 37 41 45 44 38 33 30 30 36 41 47 51 52 49 44 41 37 34 34 39 48 59 74 88 99 96 89 76 59 42 29 22 19 20 19 18 19 22 28 32 42 43 43 39 33 26 21 19 21 21 20 19 18 20 25 28 39 42 45 45 43 40 39 39 43 43 41 38 32 27 23 21 21 21 22 22 24 25 27 27 29 30 30 29 27 25 26 28 31 34 39 43 44 43 40 38 35 34 32 30 30 31 32 34 34 35 38 40 40 39 36 35 32 33 33 33 31 29 27 25 22 20 17 15 14 14 15 16 20 22 24 25 25 22 19 17 18 17 16 16 17 19 21 23 27 31 37 42 46 51 57 60 60 64 65 61 56 52 44 36 30 27 23 19 16 14 14 15 14 14 15 15 16 17 18 18 22 23 25 27 28 29 29 29 27 26 24 21 19 17 16 16 18 18 17 17 16 16 15 15 15 15 13 12 11 11 11 11 10 10 9 9 9 8 8 8 8 8 7 7 7 6 6 6 7 7 7 6 6 5 5 5 7 7 7 7 7 7 7 7 7 7 7 6 6 6 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 6 6 6 7 7 7 8 8 9 9 10 10 11 12 12 12 14 15 15 16 18 19 19 20 21 22 22 23 23 22 21 21 19 19 19 18 17 16 15 14 15 16 17 17 18 18 19 19 16 15 14 12 11 11 11 11 15 16 17 19 22 23 24 25 25 23 21 19 17 15 13 12 14 15 17 20 21 22 21 21 19 18 16 15 16 18 20 22 28 29 31 33 35 35 36 36 37 38 41 44 46 47 46 46 46 47 46 44 40 35 30 27 28 27 25 24 25 28 31 34 39 40 43 45 48 52 56 59 65 72 78 78 76 72 63 54 58 63 71 82 90 91 86 81 68 58 45 35 30 31 33 34 35 36 38 39 39 36 33 31 31 31 31 32 35 41 50 56 61 61 59 55 51 49 50 51 56 51 45 40 37 45 64 83 104 113 117 108 92 79 70 65 73 76 76 68 57 48 46 47 54 58 59 56 47 38 33 31 30 27 27 28 29 35 50 64 84 95 102 99 88 76 63 52 49 46 41 37 35 33 31 29 28 28 28 28 28 28 30 31 31 34 38 42 44 44 43 42 37 32 28 27 31 40 49 54 55 52 48 45 46 50 57 61 63 62 59 53 46 39 36 35 35 33 30 28 26 26 27 28 30 30 31 31 32 35 40 44 47 44 38 30 24 23 26 28 39 43 45 43 37 31 29 29 33 38 45 50 52 51 47 43 38 34 32 37 44 54 70 83 96 94 88 76 59 42 28 21 18 18 18 18 19 24 31 37 47 48 48 44 36 28 21 18 20 21 21 21 20 21 23 26 34 39 44 48 49 49 48 47 47 44 40 36 31 26 22 19 20 20 20 20 22 24 26 27 32 33 33 31 28 25 25 26 28 30 34 37 37 36 33 31 30 30 29 30 31 33 34 35 35 36 38 39 39 38 37 36 33 34 34 34 33 31 29 28 21 19 16 14 14 15 17 18 24 26 27 28 27 23 19 17 17 17 17 17 18 21 23 25 29 33 39 45 50 56 62 66 66 70 70 65 60 55 47 40 31 28 24 20 16 15 15 15 15 15 15 16 16 16 15 15 19 20 22 23 25 26 27 27 26 25 22 20 17 16 15 14 16 16 16 16 15 15 15 15 14 14 12 11 11 10 11 11 10 10 10 9 9 9 8 8 8 8 8 7 7 7 6 6 7 7 7 6 6 5 5 5 7 7 7 7 7 7 7 7 7 7 6 6 6 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 5 6 6 6 7 7 7 7 9 9 9 10 10 11 11 11 13 13 14 15 16 16 17 17 19 20 20 20 20 19 18 18 17 17 17 17 17 16 15 14 16 16 17 18 18 18 17 17 14 13 13 12 11 12 12 12 15 16 18 20 21 22 22 22 20 19 17 16 14 13 13 13 14 16 18 20 21 21 20 20 19 18 17 16 18 21 25 28 33 34 35 36 37 37 36 36 35 36 38 39 40 39 38 38 37 37 37 36 33 29 26 23 27 26 26 26 28 30 33 35 40 42 44 47 49 52 54 55 60 65 69 68 66 65 60 53 57 62 70 79 85 85 81 77 59 52 44 38 36 36 37 37 36 37 37 37 37 37 36 36 36 35 34 33 34 38 45 50 58 59 58 56 51 48 48 48 53 49 44 41 39 44 59 74 91 101 107 101 92 86 85 84 93 93 88 76 61 49 45 45 52 56 60 57 49 39 33 30 30 27 27 29 30 34 46 57 74 82 86 81 73 66 59 53 49 46 41 38 35 33 29 27 28 28 29 28 28 30 33 36 34 36 38 39 40 39 37 36 33 30 28 29 34 43 53 59 60 59 56 53 51 54 59 63 61 60 57 51 42 34 30 28 30 29 27 26 26 27 28 29 31 31 31 30 30 33 38 42 44 42 37 30 26 25 28 32 42 44 45 41 34 28 26 27 30 36 43 50 54 53 50 48 41 36 33 35 40 48 61 74 88 87 83 74 59 43 31 25 18 18 18 19 22 29 37 44 52 53 52 48 40 30 23 19 21 22 23 23 22 22 25 27 36 41 48 55 58 57 55 53 48 43 37 31 28 24 21 19 19 19 18 19 20 23 25 26 34 35 36 34 30 28 27 27 28 29 31 31 31 29 27 25 27 28 31 33 35 36 37 37 35 36 37 38 37 36 35 34 32 32 33 34 33 32 30 29 20 19 17 15 16 19 22 25 31 31 31 30 27 24 20 17 18 17 17 18 20 23 25 27 31 34 40 45 50 55 61 65 68 71 69 63 58 55 48 42 31 29 25 20 17 16 16 16 18 18 19 19 18 17 16 15 17 17 18 20 21 22 23 24 24 23 21 18 16 15 14 14 15 15 15 15 15 15 15 15 13 13 12 11 10 10 11 11 11 10 10 10 9 9 9 9 9 8 8 8 7 7 7 7 7 7 7 6 6 5 5 5 6 6 6 6 6 6 6 6 6 6 6 6 5 5 5 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 5 5 6 6 6 7 7 7 8 9 9 9 9 10 10 10 12 12 13 13 14 15 15 16 18 18 19 19 18 17 16 16 16 16 17 17 17 16 15 14 16 16 17 18 18 17 15 14 12 12 11 11 11 12 13 14 16 17 18 20 20 20 19 18 16 15 14 13 13 14 14 15 16 18 19 21 21 21 20 19 20 19 18 18 20 25 29 33 39 40 40 40 39 38 37 37 34 34 34 34 33 32 31 31 30 30 31 31 29 27 24 23 25 25 26 27 30 33 36 38 42 44 47 51 54 56 56 55 58 62 63 61 61 62 60 56 57 60 65 69 72 70 66 62 51 49 46 45 45 46 45 43 39 38 36 35 36 39 42 44 42 41 39 36 34 36 41 44 54 56 57 55 51 47 44 44 46 43 40 39 38 40 51 63 77 88 96 95 92 95 101 104 113 110 100 83 62 47 41 40 47 52 58 57 49 39 32 28 30 28 28 30 32 34 43 53 61 66 67 61 56 56 56 55 53 50 47 44 41 37 33 29 30 31 31 30 30 33 39 44 43 43 42 40 38 35 32 31 28 28 28 30 36 44 54 60 62 62 61 58 55 55 58 62 59 59 56 49 39 31 25 23 26 25 25 25 26 27 29 30 32 31 30 28 27 29 34 38 39 38 35 31 28 29 32 36 45 46 44 38 30 25 24 25 29 35 43 52 56 57 55 53 45 40 36 36 38 42 53 64 75 76 74 67 56 42 32 26 18 19 20 22 26 34 44 51 56 57 56 51 42 33 26 22 23 24 25 24 23 23 25 27 39 44 53 61 64 63 58 53 47 40 32 26 24 23 21 20 20 19 18 18 19 21 23 25 34 36 37 36 33 30 29 29 30 30 29 28 27 25 24 23 30 33 37 40 42 41 39 38 34 34 35 35 34 33 31 30 28 29 30 31 31 29 28 27 21 20 18 18 21 25 30 33 38 37 35 32 28 24 20 18 18 18 18 20 22 25 28 29 31 35 40 44 47 52 56 60 62 64 61 55 50 48 44 38 31 29 25 21 18 17 17 17 23 24 24 24 23 21 19 18 15 15 16 16 17 19 20 21 22 21 19 17 16 15 15 15 14 14 14 14 14 14 14 14 13 12 11 10 10 10 11 11 11 11 10 10 10 9 9 9 9 9 8 8 8 7 7 7 7 7 7 6 6 5 5 5 6 6 6 6 6 6 6 6 6 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 5 5 5 6 6 7 7 7 8 8 9 9 9 9 9 10 11 11 12 12 13 14 14 15 17 18 18 18 17 16 15 15 15 16 16 17 17 16 15 15 16 17 17 18 17 16 14 13 11 11 11 11 12 13 14 15 17 17 19 19 19 18 17 16 14 13 12 12 13 14 16 17 18 19 21 22 22 21 20 19 21 20 19 19 22 27 32 36 43 43 43 43 42 40 39 38 33 33 32 31 29 28 27 27 26 27 28 28 28 26 25 23 23 24 25 28 31 34 37 39 45 47 51 56 60 61 60 58 58 61 61 58 58 61 61 58 58 59 60 60 58 54 49 46 49 49 50 52 54 55 53 50 41 39 36 34 36 40 46 49 46 45 42 39 36 35 38 41 51 53 55 54 50 45 42 40 40 37 37 37 35 36 45 56 68 80 89 91 93 101 112 118 126 121 108 87 62 45 37 36 42 48 55 56 48 38 30 26 31 29 29 32 33 35 42 51 50 53 52 46 43 48 53 56 58 56 53 51 48 43 38 34 32 33 33 32 32 36 43 49 52 50 47 42 37 33 30 28 24 25 27 31 36 44 53 59 62 63 63 60 56 55 57 60 59 58 55 48 38 29 24 21 23 23 23 24 26 27 29 30 32 31 29 26 25 27 32 36 36 36 34 32 30 31 35 38 47 47 44 37 28 22 22 24 29 35 44 53 58 60 58 57 49 43 38 37 37 39 48 57 64 65 65 61 51 39 30 25 19 20 21 23 28 37 48 55 58 59 57 52 43 34 28 24 25 26 26 24 22 22 24 26 40 46 55 64 68 65 58 52 46 38 29 23 21 22 22 21 20 19 18 17 18 20 23 24 33 35 37 36 34 31 30 30 31 30 28 26 25 24 24 24 34 38 42 46 47 45 41 39 33 33 33 32 31 30 28 27 25 26 28 28 28 27 26 25 22 21 20 21 24 30 35 39 42 40 37 33 28 24 21 19 19 19 19 20 23 26 29 31 31 35 39 42 45 49 53 56 54 55 52 46 41 40 38 33 31 28 25 21 18 18 18 18 27 28 28 28 26 24 22 21 14 14 14 14 15 16 18 18 20 19 18 17 16 15 15 15 14 14 14 14 14 14 14 14 12 12 11 10 10 10 11 11 11 11 11 10 10 9 9 9 9 9 9 8 8 7 7 7 7 7 7 6 6 5 5 5 6 6 6 6 6 6 6 6 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 5 5 5 6 6 7 7 7 8 8 8 8 8 8 8 8 9 9 9 10 10 11 11 11 15 15 16 16 16 15 14 14 14 15 16 17 17 17 17 16 15 16 16 16 16 15 14 13 9 9 10 11 11 12 13 13 16 17 18 18 18 16 14 13 11 11 12 13 15 17 19 20 21 22 24 24 23 20 17 15 20 20 20 23 28 34 41 44 47 46 46 46 46 43 39 35 31 28 24 22 23 24 24 24 26 26 26 27 27 29 30 31 26 27 29 32 36 39 41 42 51 50 51 54 57 58 58 56 59 56 53 54 57 59 58 56 57 56 53 49 43 40 40 41 42 52 63 69 71 69 61 52 43 35 30 32 36 42 49 57 57 59 57 49 40 35 35 38 46 49 51 49 44 38 33 31 33 31 28 25 26 30 38 44 56 65 77 88 99 113 129 141 147 141 125 99 69 45 31 27 35 43 52 54 49 42 38 36 34 35 35 34 34 35 38 41 43 42 39 36 34 39 48 56 65 65 64 59 52 44 39 37 35 35 35 36 39 45 53 59 63 60 55 48 41 35 30 27 27 26 26 27 32 40 47 52 58 59 59 58 56 54 55 56 54 57 56 49 43 39 34 28 28 21 18 22 26 27 28 30 31 30 27 26 25 26 27 28 30 33 35 35 34 36 41 45 44 45 43 35 25 20 20 23 33 39 48 57 61 61 59 56 51 46 40 35 34 38 43 47 55 55 55 52 47 40 32 28 24 22 21 24 32 42 51 55 60 61 60 54 44 34 27 25 27 27 26 26 26 27 28 28 39 45 54 63 67 64 56 49 38 34 28 24 23 23 22 22 25 23 21 19 19 20 23 25 31 32 33 34 34 33 31 30 27 27 27 25 24 25 29 32 35 45 55 57 56 53 47 40 36 32 26 23 21 21 21 21 21 22 25 27 28 28 28 28 23 23 24 27 32 37 43 46 48 45 41 36 29 24 19 17 19 20 22 23 25 25 26 26 31 34 37 40 42 41 39 38 37 36 36 34 33 32 31 31 29 27 23 21 19 20 22 23 25 27 30 32 31 27 23 20 18 17 15 13 14 15 17 19 18 18 17 17 17 16 16 15 13 13 12 11 11 12 12 13 13 13 13 12 12 11 11 11 9 9 9 9 9 9 9 9 8 9 9 10 10 9 9 8 7 7 7 6 6 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 5 5 5 6 6 6 7 7 8 8 8 8 8 8 8 8 9 9 9 10 10 10 11 11 14 15 15 16 16 15 14 14 14 15 16 16 17 17 16 16 15 15 16 15 15 14 13 12 9 9 10 11 12 12 13 13 16 16 17 17 16 15 13 12 12 12 13 14 16 19 20 21 23 23 23 23 22 21 19 18 21 22 23 26 31 36 41 44 45 44 44 44 44 41 37 33 28 25 21 20 21 23 24 23 26 26 27 28 29 30 31 32 27 28 30 33 35 38 41 42 48 48 49 52 56 58 57 56 58 55 53 53 55 56 56 54 52 51 47 42 38 36 38 40 47 58 71 77 80 77 68 58 46 38 32 35 40 47 55 63 63 63 61 53 43 37 36 39 43 46 47 45 40 34 30 28 29 28 27 25 26 29 35 40 50 59 72 86 100 118 138 152 153 147 131 104 73 47 32 27 34 42 50 53 49 43 40 39 38 38 37 35 34 34 37 40 38 38 36 33 32 38 48 57 67 67 65 60 53 46 42 41 40 41 41 42 45 52 61 67 72 68 61 52 43 34 27 23 25 24 23 25 29 35 42 46 53 54 55 54 52 51 52 53 57 62 64 60 56 51 45 38 32 24 19 21 25 27 28 31 32 31 29 27 26 26 27 27 29 31 33 33 34 36 41 45 44 44 41 33 24 19 20 23 34 39 47 55 58 57 54 51 46 43 38 34 34 37 41 45 49 50 50 48 44 38 32 28 25 23 22 25 33 42 50 54 58 59 57 51 42 33 28 26 27 27 27 27 28 29 29 30 37 42 50 58 62 59 52 46 38 34 29 25 24 25 24 24 26 24 22 20 20 21 23 24 29 30 32 33 33 32 31 30 28 27 26 24 23 25 30 34 39 50 59 62 60 56 48 40 32 28 23 20 19 20 20 20 22 23 25 27 28 28 28 27 25 25 27 29 34 40 45 48 49 46 41 35 28 23 19 16 19 20 22 24 25 26 27 27 28 30 33 36 37 36 34 32 31 30 30 30 29 29 28 28 28 26 23 20 19 20 22 23 27 29 31 33 32 29 25 22 19 17 15 14 14 15 18 19 18 18 18 17 17 16 15 15 13 13 12 11 11 11 12 12 13 13 12 12 12 11 11 11 8 8 8 8 8 8 8 8 8 9 9 10 10 9 9 8 7 7 7 6 6 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 5 5 5 5 6 6 6 7 8 8 8 8 8 8 8 8 9 9 9 9 10 10 10 11 13 14 14 15 15 15 14 14 14 14 15 16 17 17 16 16 15 15 15 14 13 12 11 10 9 10 10 11 12 13 13 13 16 16 16 15 15 13 12 11 13 14 15 17 19 21 23 24 25 24 23 22 22 21 21 21 24 25 27 31 34 38 41 42 42 42 41 41 40 38 33 29 23 21 18 17 19 22 23 23 27 27 28 29 31 32 33 34 30 30 31 33 35 37 39 40 44 44 45 49 54 56 57 56 57 54 51 50 51 52 52 51 47 45 41 35 32 32 36 40 52 65 79 87 89 85 73 62 46 38 33 36 43 51 61 70 70 70 66 58 48 40 38 39 40 41 42 39 35 30 27 27 26 27 28 28 28 30 33 36 42 51 64 78 95 117 140 157 166 160 144 117 84 56 39 33 33 40 48 51 49 45 43 43 44 43 40 36 33 33 36 38 35 35 33 31 31 37 47 56 68 67 64 59 53 48 46 46 46 47 47 48 52 58 67 73 77 73 65 55 44 34 26 22 22 21 21 21 25 29 34 38 45 47 48 48 47 46 48 49 58 66 73 74 73 68 59 49 38 28 21 21 25 26 29 33 34 33 32 31 29 28 27 27 27 29 31 32 34 37 42 46 44 43 38 30 23 20 22 25 36 40 46 50 52 50 46 43 39 37 34 32 32 35 38 40 40 41 42 42 40 36 31 28 27 25 24 27 34 42 48 51 55 54 51 45 37 31 28 27 26 26 27 28 29 31 32 32 35 39 45 51 54 53 47 42 38 34 30 27 27 28 27 27 27 26 24 22 22 22 23 24 27 28 29 30 31 31 31 31 29 28 26 23 23 26 31 36 44 55 64 66 63 57 48 39 26 23 19 17 18 20 22 22 25 26 28 29 29 29 28 27 28 28 29 32 36 42 47 50 49 46 40 33 26 21 17 16 18 19 21 23 25 26 27 27 25 26 28 30 30 28 26 25 22 22 22 23 23 24 24 24 26 24 21 19 18 19 21 22 28 29 31 33 32 29 26 24 20 18 16 15 15 16 18 19 19 20 20 19 18 17 16 15 14 13 12 11 11 11 11 11 13 12 12 12 11 11 11 11 8 8 8 8 8 8 8 8 8 8 9 9 9 9 8 8 7 7 7 6 6 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 5 5 5 6 6 6 7 7 7 7 7 7 7 7 8 8 9 9 9 10 10 10 12 12 13 14 14 14 14 13 13 14 15 16 16 16 16 15 14 14 14 13 12 11 9 8 10 10 11 11 12 13 14 14 15 15 14 14 13 12 11 11 15 16 18 20 22 24 25 25 26 25 23 21 21 22 24 25 26 28 31 34 37 38 39 39 39 38 37 37 37 34 29 26 21 19 16 17 19 22 24 25 27 28 30 32 33 35 36 36 32 32 32 32 33 34 36 37 38 38 40 45 50 54 54 54 53 51 48 46 45 46 47 47 45 43 38 34 31 33 38 42 57 70 84 91 92 86 72 60 44 36 32 36 44 52 63 72 76 75 70 62 52 44 40 39 38 39 38 35 31 28 27 27 28 31 34 35 35 33 33 34 37 45 56 69 85 107 132 150 170 165 151 125 92 63 45 37 34 39 46 49 49 47 47 47 48 46 42 37 33 32 35 38 38 38 36 32 31 35 45 52 63 63 60 56 52 50 51 53 51 52 51 52 54 60 68 73 73 69 62 53 43 34 28 24 21 20 20 20 22 25 29 31 38 40 42 42 42 42 44 45 57 68 79 86 88 83 71 59 44 33 23 21 24 26 30 35 37 37 37 36 35 32 29 28 27 28 30 32 36 40 44 47 45 42 37 30 24 23 26 29 36 38 42 45 45 42 38 35 31 31 30 29 30 31 32 33 33 34 36 37 37 34 32 30 28 26 26 28 34 41 45 47 47 45 41 36 31 28 26 25 23 24 26 28 30 32 33 34 36 37 40 44 47 46 43 39 38 34 31 29 30 30 30 29 28 28 26 25 24 23 23 23 25 25 27 28 29 30 31 31 31 29 26 23 22 26 33 38 47 57 66 67 63 56 45 36 22 20 17 17 20 24 26 27 30 31 32 32 32 30 28 27 29 29 29 32 36 41 46 49 47 43 37 30 23 19 16 15 17 18 20 22 23 24 25 25 23 23 24 25 24 22 20 19 15 16 17 18 19 20 21 22 22 21 19 18 18 19 20 21 26 28 30 31 30 28 25 24 21 19 17 15 15 16 18 19 21 22 22 22 22 20 18 17 16 15 13 12 11 10 10 11 12 12 12 11 11 11 10 10 7 7 7 7 7 7 7 7 7 8 9 9 9 9 8 7 7 7 7 6 6 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 4 5 5 5 6 6 7 7 7 7 7 7 7 7 8 8 8 9 9 9 10 10 10 11 12 13 14 14 13 13 13 14 15 15 16 16 15 15 13 13 13 13 12 11 9 8 10 10 11 12 13 13 14 14 14 14 13 13 12 12 12 12 17 18 20 22 24 25 25 25 25 24 22 20 20 22 25 27 27 29 32 34 36 36 35 35 34 33 33 34 34 31 27 23 21 18 17 17 21 24 26 27 27 29 31 34 36 38 38 39 33 32 30 29 29 30 32 33 32 32 35 40 45 49 50 50 47 46 43 40 39 39 41 43 45 44 41 38 36 38 42 46 61 73 85 91 90 82 68 55 43 37 34 39 47 55 64 73 76 74 70 63 54 47 42 40 39 38 36 33 29 27 28 30 34 38 43 44 43 39 36 35 33 40 49 59 74 96 121 138 159 156 145 122 92 65 47 39 35 39 43 46 47 47 48 48 49 47 42 36 32 33 37 41 46 46 43 38 34 35 40 46 54 54 54 53 52 54 59 62 62 61 58 56 56 59 65 70 67 64 58 50 41 33 27 24 23 23 23 23 24 26 27 28 35 37 39 39 39 39 41 43 57 69 83 93 98 94 81 67 47 35 24 22 24 26 31 36 40 41 42 43 41 37 33 30 28 29 30 33 37 42 46 48 45 42 37 31 27 27 30 33 34 36 39 40 40 37 34 32 29 29 28 28 28 27 27 27 28 30 32 34 34 33 32 31 27 26 26 28 33 37 40 41 39 36 32 28 25 24 23 23 20 22 25 28 31 33 35 35 37 37 37 38 40 41 39 37 38 35 32 31 32 32 32 31 30 30 29 28 27 25 23 23 23 23 24 26 28 30 32 33 33 31 28 24 23 26 32 37 46 55 63 63 58 50 40 30 21 19 18 20 25 31 35 36 39 39 39 38 36 32 30 28 27 27 27 29 32 36 40 43 41 39 34 28 23 19 16 15 16 17 19 20 21 22 22 22 22 23 23 23 21 19 17 16 13 14 15 16 17 18 19 20 19 18 17 17 17 18 19 20 23 24 26 27 27 25 23 22 21 19 17 15 14 15 17 18 23 24 25 26 25 24 22 21 18 17 15 13 12 11 11 11 12 12 11 11 11 10 10 10 7 7 7 7 7 7 7 7 7 7 8 9 9 8 7 7 7 7 7 6 6 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 4 4 4 5 5 5 5 6 6 6 6 6 6 6 6 7 8 8 8 9 9 9 9 9 10 11 12 13 13 13 13 13 13 14 15 15 15 15 15 12 12 13 13 13 12 11 10 11 11 11 12 13 14 14 15 13 12 12 12 12 13 14 15 19 20 22 24 25 25 24 23 23 22 21 20 20 22 25 27 28 29 30 32 32 32 31 30 30 29 30 31 32 30 26 23 21 19 17 18 21 25 27 28 27 29 33 36 39 41 41 41 33 31 28 25 24 25 26 27 26 27 29 34 40 44 45 45 41 40 38 35 32 33 36 40 45 45 45 44 43 43 45 47 61 71 81 85 83 76 64 52 44 39 37 43 51 57 64 71 70 68 65 60 54 48 43 40 40 39 35 31 28 27 30 33 41 45 50 51 48 42 37 34 30 35 42 50 62 82 105 122 141 140 134 117 91 67 50 43 36 37 39 40 42 43 44 44 47 44 39 34 31 34 40 45 53 53 51 45 38 35 36 39 45 47 50 53 57 63 70 75 76 74 69 63 58 58 61 64 64 61 55 48 41 34 28 25 29 29 29 30 30 31 31 31 35 37 39 39 39 39 41 43 56 68 83 94 101 98 84 69 48 36 25 22 24 27 32 37 39 42 45 47 45 41 35 32 29 28 29 32 37 42 45 46 44 41 37 32 30 31 33 34 34 36 38 39 39 38 36 35 33 32 31 29 28 26 25 24 26 27 29 31 31 31 31 30 26 25 24 27 30 33 34 34 31 28 24 23 23 23 22 21 19 21 25 30 34 36 37 38 39 36 33 33 34 36 36 36 38 36 33 32 33 33 32 30 31 32 32 31 29 26 24 22 22 22 23 25 28 31 33 35 35 33 30 26 24 26 31 35 43 52 58 56 50 43 34 25 21 20 20 24 31 38 44 46 49 49 47 44 40 35 31 29 26 25 25 25 27 30 33 35 36 35 32 29 26 22 20 18 18 18 19 20 21 21 20 20 23 23 22 21 20 19 17 16 15 15 15 16 16 17 17 17 16 16 15 16 16 17 18 19 21 21 23 24 23 22 21 20 20 18 16 14 13 14 15 16 22 23 26 27 28 27 25 23 21 20 18 15 14 12 12 11 11 11 11 11 10 10 10 9 8 8 8 8 8 8 8 8 7 7 8 8 8 8 7 7 7 7 7 6 6 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 4 4 4 5 5 5 6 6 6 6 6 6 6 6 7 7 8 8 8 9 9 9 8 9 10 12 13 13 13 13 12 13 14 15 15 15 15 14 11 12 12 13 14 13 13 13 11 11 12 12 13 14 15 15 12 12 11 12 13 15 17 18 21 22 24 25 25 24 22 21 21 20 20 20 21 22 24 25 27 27 28 28 27 27 26 25 26 26 27 29 31 30 27 24 22 19 17 18 21 24 26 27 28 30 34 38 41 43 43 43 32 29 25 22 20 20 21 22 22 23 25 30 36 39 40 40 35 34 33 29 27 28 33 37 42 45 48 49 47 45 44 44 54 63 71 73 72 68 59 49 43 39 39 45 51 55 60 66 62 61 59 56 53 48 44 41 40 38 34 29 26 27 31 35 45 49 53 54 49 42 36 32 28 32 36 40 47 62 82 96 115 117 115 103 83 62 48 42 35 34 33 34 35 37 38 38 43 40 35 31 30 35 43 49 56 58 57 51 42 36 33 34 39 43 50 57 66 75 84 90 89 85 77 67 59 54 55 56 58 57 53 49 44 40 36 35 34 35 36 37 38 37 37 36 38 40 41 41 40 40 42 43 51 62 75 87 94 93 79 65 47 35 25 22 24 27 32 37 37 40 45 48 47 42 36 32 28 27 26 29 35 40 42 43 42 39 35 33 32 33 33 34 35 37 39 41 42 43 43 43 41 39 37 33 30 27 25 24 24 25 26 28 28 28 28 27 23 23 23 24 27 29 29 27 26 23 21 21 23 24 23 21 20 23 27 33 37 40 41 42 39 35 30 27 28 31 33 34 38 36 34 33 33 32 31 29 32 33 34 33 31 28 24 21 21 22 23 25 28 32 35 37 36 35 33 29 26 26 29 32 41 48 53 50 44 38 30 22 21 20 21 26 35 44 50 53 58 57 55 50 44 38 33 30 26 24 23 22 23 25 27 29 32 32 33 33 31 28 26 24 22 22 22 22 22 21 20 19 22 22 21 20 19 18 17 16 17 17 16 16 15 15 14 14 13 14 14 15 16 17 18 18 19 20 21 22 22 21 20 20 19 18 15 13 12 12 14 15 18 20 24 27 28 27 26 24 23 22 20 17 15 14 13 12 11 11 11 10 10 10 9 9 8 8 8 8 8 8 8 8 6 7 7 8 8 7 7 6 7 7 7 6 6 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 4 4 5 5 5 6 6 6 6 6 6 6 6 7 7 7 8 8 9 9 9 8 8 10 11 12 13 13 13 12 13 14 15 15 15 15 14 10 11 12 14 14 15 14 14 11 11 12 13 13 14 15 15 11 11 11 12 13 16 19 20 22 23 25 26 25 23 21 19 19 19 19 20 21 22 24 24 27 26 26 25 24 23 23 23 24 24 26 28 30 30 27 25 21 19 17 17 20 23 25 26 28 30 35 39 42 44 44 44 31 28 24 19 17 17 18 19 20 21 23 27 33 37 37 37 31 31 30 27 24 26 31 36 40 44 49 51 49 46 43 41 46 54 60 62 62 61 54 46 40 37 37 44 49 52 55 59 57 56 54 53 51 48 44 41 40 38 33 28 25 26 31 36 47 50 54 53 48 40 33 29 29 31 32 32 35 45 61 73 89 93 94 85 68 50 38 32 33 31 30 29 30 32 32 32 40 37 33 30 30 36 45 52 57 59 59 53 44 36 32 31 36 42 51 61 72 83 94 100 94 89 80 68 57 50 49 49 52 52 51 50 48 47 46 46 38 39 41 42 43 42 41 40 40 42 43 43 42 41 43 44 45 55 67 78 86 85 72 58 46 35 24 23 25 27 32 37 34 38 44 48 47 42 36 31 27 25 24 27 33 38 40 40 39 37 34 32 33 33 33 32 36 38 40 43 46 47 48 49 47 45 41 37 32 29 27 26 23 24 25 25 26 26 25 25 22 21 21 23 25 26 25 24 24 22 20 21 24 26 24 21 21 24 29 35 40 43 44 45 39 34 27 24 25 28 30 32 38 36 34 33 33 32 30 28 33 34 35 35 32 28 24 21 21 22 23 25 28 32 36 38 37 36 34 30 27 26 28 30 39 46 50 46 40 35 28 21 21 20 22 28 37 47 54 57 64 62 59 54 47 40 34 30 26 24 22 21 21 22 24 26 30 32 34 36 35 33 30 28 25 25 25 24 23 22 21 20 21 21 20 20 19 18 17 17 18 18 17 16 14 13 12 12 12 12 13 14 15 16 17 18 19 20 21 21 22 21 21 20 19 17 14 12 11 11 13 14 15 18 22 25 27 27 25 24 25 24 21 19 16 14 13 13 11 11 11 10 10 9 9 9 9 9 9 9 9 9 9 9 6 7 7 8 8 7 7 6 7 7 7 6 6 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 4 4 4 4 4 4 5 5 5 6 6 7 7 7 6 6 6 7 7 8 8 8 9 9 9 10 10 11 11 11 8 9 10 11 12 13 12 12 12 12 12 12 12 12 12 12 16 16 15 14 14 14 15 15 14 13 13 13 15 17 19 21 23 23 24 23 22 20 18 16 17 19 21 22 23 23 22 22 21 21 21 22 22 23 23 23 26 27 29 30 30 29 27 25 20 19 18 18 19 22 25 27 29 33 38 43 45 44 42 40 30 27 22 18 16 17 19 21 21 23 26 29 31 32 33 32 31 29 26 22 21 24 30 35 45 49 54 55 50 43 36 32 38 43 48 53 54 51 46 42 35 34 33 36 41 44 44 42 46 47 47 45 42 40 40 41 40 37 33 27 24 25 30 34 46 49 52 49 41 33 28 27 27 29 30 29 30 34 42 49 66 68 69 62 50 38 30 27 25 27 27 26 24 23 24 25 30 31 31 31 33 37 43 48 58 58 55 48 38 31 29 30 37 48 59 68 78 92 102 107 100 93 80 66 53 46 44 44 47 51 57 60 61 59 57 56 50 48 47 48 51 51 47 43 44 43 42 44 46 45 40 36 42 45 51 60 66 66 60 54 39 33 27 24 26 28 28 26 32 32 34 38 42 42 38 33 25 23 22 24 28 32 34 34 34 32 31 32 34 37 38 37 40 41 44 46 50 53 55 56 57 54 49 43 37 33 31 29 26 27 27 27 27 26 25 24 22 23 24 25 26 26 26 26 21 21 22 23 24 25 25 26 21 24 30 37 43 46 45 43 39 34 27 21 20 24 30 34 39 39 38 34 31 28 29 30 31 33 35 35 32 28 26 26 21 23 25 26 27 30 34 38 37 36 33 29 27 27 31 34 43 44 46 46 42 36 29 25 23 24 26 31 37 45 51 55 60 61 61 59 53 45 38 33 26 24 21 19 18 20 22 24 30 33 37 40 41 38 35 32 31 28 24 22 23 24 24 24 22 22 21 20 18 17 16 16 17 17 16 15 14 12 10 9 11 11 11 12 13 14 15 16 19 20 23 24 24 23 21 20 19 18 17 15 13 12 10 10 15 17 20 24 26 26 26 25 27 26 24 22 20 18 16 16 14 13 12 11 11 11 11 12 11 10 9 8 7 6 7 7 7 7 7 6 6 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 4 4 4 4 4 4 5 5 5 6 6 6 7 7 6 6 6 7 7 7 8 8 9 9 9 10 10 10 11 11 8 9 10 11 12 13 12 12 13 13 13 13 13 13 13 13 16 15 15 14 14 14 15 16 15 15 14 15 16 18 20 21 22 23 23 23 21 19 17 16 17 18 20 21 22 22 21 20 19 19 19 20 21 23 24 25 28 29 30 30 29 28 26 24 19 19 18 19 20 23 26 28 31 34 39 42 44 42 39 37 28 26 22 19 18 19 21 23 23 24 26 27 28 29 29 28 28 27 24 22 21 23 29 33 44 48 52 53 48 41 34 30 31 35 41 46 47 44 40 37 34 32 31 33 36 38 37 35 42 43 44 42 39 37 36 37 36 35 31 27 24 25 28 32 42 45 47 44 37 31 28 28 33 35 36 34 31 30 33 37 46 50 51 48 40 32 28 27 28 29 31 29 26 23 22 22 25 27 29 30 32 37 42 46 52 52 49 43 35 30 30 32 40 52 64 74 84 95 103 105 94 86 73 58 47 41 40 40 49 54 61 67 68 67 64 63 55 52 50 50 51 50 46 42 42 41 42 46 50 49 45 40 37 38 41 47 53 54 50 46 37 33 28 27 28 29 28 25 28 28 30 35 40 40 36 32 24 23 22 23 27 31 33 33 34 33 32 33 37 40 41 41 44 45 46 48 51 54 56 58 60 57 53 47 42 38 36 35 33 33 33 33 31 28 25 24 23 23 24 25 26 26 26 26 23 24 26 27 28 28 28 28 23 25 29 36 42 45 44 43 36 32 26 21 21 26 32 37 41 41 40 36 32 30 29 30 31 33 35 34 31 28 27 27 25 26 27 27 27 28 32 34 35 34 32 30 28 30 34 37 44 45 46 44 41 34 28 24 22 23 25 29 35 42 48 51 58 59 59 58 53 46 39 34 28 26 23 20 19 20 22 24 31 34 40 44 45 42 38 35 32 29 25 23 24 25 25 24 23 22 22 21 20 19 18 18 17 17 17 16 15 13 11 10 12 12 12 12 13 14 15 16 19 21 23 25 25 25 23 22 21 20 19 17 15 13 11 10 14 16 18 21 23 24 25 25 25 25 23 22 20 19 18 17 15 14 13 12 12 11 12 12 11 10 9 8 7 7 7 7 7 7 7 6 6 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 4 4 4 4 4 4 5 5 5 5 6 6 6 7 6 6 6 6 7 7 7 8 9 9 9 9 10 10 10 11 8 9 10 11 12 13 12 12 13 13 13 13 13 13 13 13 15 15 14 14 14 14 15 16 16 16 16 17 18 20 21 22 22 22 22 21 20 18 17 16 17 17 18 19 19 19 18 18 17 17 17 18 20 23 26 28 31 31 31 30 28 26 24 23 19 19 19 21 23 26 29 31 34 36 39 41 41 38 34 32 25 23 21 19 19 21 24 26 26 26 26 25 25 25 24 24 24 24 23 22 22 24 28 31 42 46 49 49 44 37 31 27 25 29 34 39 40 38 35 32 32 30 28 28 29 30 29 28 37 39 40 38 35 32 30 30 31 31 29 27 24 24 25 28 35 38 40 37 32 28 28 30 37 41 44 42 36 30 27 26 29 32 35 33 29 26 27 29 34 36 38 37 32 26 21 19 21 23 26 29 31 35 39 43 44 45 43 38 33 31 33 37 45 57 70 79 88 96 99 97 84 75 61 47 38 34 35 36 42 48 57 65 70 69 66 63 58 54 50 49 49 48 44 40 38 39 43 50 56 57 53 48 36 33 32 34 38 41 40 38 35 32 30 31 33 33 29 25 25 24 26 31 36 38 35 32 25 23 21 22 26 30 32 33 36 35 35 38 42 46 48 49 50 49 48 48 50 52 55 57 60 58 55 51 48 45 44 43 42 43 43 42 38 33 28 25 24 24 25 25 25 25 25 25 27 29 32 34 35 34 32 31 26 27 29 34 39 43 43 43 33 30 25 23 25 30 37 42 46 46 45 41 37 33 32 32 33 34 35 33 31 29 29 30 31 32 31 29 27 26 27 29 31 31 31 31 31 33 38 42 45 46 45 43 39 33 27 23 21 21 23 26 31 36 42 45 54 55 56 56 52 46 40 37 31 29 26 23 21 21 22 23 31 35 42 47 49 46 42 39 32 29 26 24 25 25 24 23 23 23 22 22 21 20 20 20 18 18 18 18 17 15 14 13 13 13 12 13 13 15 16 16 20 21 23 25 26 26 26 25 23 23 22 21 19 16 14 13 14 15 16 17 19 21 23 24 23 23 22 21 20 20 19 19 17 16 15 14 13 12 12 12 11 11 9 8 7 7 7 7 7 7 7 6 6 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 4 4 4 4 4 4 4 4 5 5 5 6 6 6 5 5 6 6 6 7 7 7 8 8 9 9 9 10 10 10 8 9 10 11 12 13 12 12 14 14 14 14 14 14 14 14 14 14 13 13 14 14 15 16 18 18 18 19 20 21 22 22 21 21 21 20 18 17 16 15 16 16 16 17 17 17 17 16 16 16 17 18 21 26 30 32 35 34 32 29 26 24 22 21 20 20 21 23 26 29 32 34 36 37 39 39 38 34 30 27 21 20 18 18 19 22 25 27 26 25 24 24 23 23 23 23 21 23 24 23 23 24 27 29 39 42 44 43 39 32 27 24 22 26 32 36 38 36 33 30 28 26 25 24 24 25 25 25 34 36 38 37 33 29 26 25 25 27 28 26 24 23 23 24 30 32 34 32 29 28 30 33 42 47 53 52 45 35 28 24 25 28 30 29 26 26 30 34 43 46 49 47 41 32 25 21 20 22 26 28 29 31 34 37 38 40 39 37 33 34 38 43 48 59 72 79 85 88 85 80 70 61 47 35 29 29 31 32 35 40 50 59 65 66 63 59 54 49 44 43 43 43 40 36 35 37 44 55 64 67 65 61 44 38 31 29 31 33 34 34 32 32 33 37 40 39 33 27 24 23 24 29 34 37 36 33 27 25 23 23 27 31 34 35 39 39 41 46 51 55 57 57 54 52 48 44 44 45 48 50 53 53 52 51 51 50 50 50 50 51 52 51 47 41 35 31 27 27 26 26 26 26 26 26 31 34 38 41 42 39 36 33 30 29 29 32 37 41 42 42 32 30 28 28 32 38 45 50 54 54 53 49 43 39 36 36 35 36 36 34 33 33 35 37 40 40 38 34 29 25 24 24 26 28 30 32 34 37 41 45 47 47 45 42 37 32 27 23 20 20 20 23 26 31 36 39 50 51 52 52 50 46 41 38 34 32 28 25 23 21 21 21 28 33 40 47 49 47 42 39 31 28 25 24 24 24 23 22 22 22 21 21 20 20 20 19 19 19 19 19 18 17 16 15 14 14 13 14 14 15 16 17 20 21 23 25 27 27 27 27 27 27 27 26 24 22 20 18 15 15 14 14 15 18 21 23 20 20 20 20 20 20 20 20 19 18 16 15 14 13 13 13 12 11 10 8 8 7 7 8 7 7 7 6 6 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 4 4 4 4 4 4 4 4 4 5 5 5 6 6 5 5 5 6 6 6 7 7 8 8 8 9 9 9 10 10 8 9 10 11 12 13 12 12 14 14 14 14 14 14 14 14 13 13 13 13 13 14 15 16 18 19 20 21 21 22 22 22 21 20 19 18 16 15 15 15 15 15 15 15 15 16 16 16 17 18 19 22 26 30 34 36 38 36 32 28 25 22 21 21 22 23 24 26 29 32 34 36 36 37 38 37 35 31 27 24 18 17 16 16 17 20 23 24 23 23 24 24 24 24 24 24 21 22 24 24 23 24 26 28 34 37 39 37 33 28 24 22 22 25 30 34 35 34 31 29 24 23 23 22 22 24 26 28 34 37 39 39 34 29 25 23 22 24 27 27 25 23 23 24 27 30 32 31 30 30 35 39 50 57 64 64 55 42 32 26 26 28 30 30 29 31 37 42 53 56 59 58 50 40 31 26 23 25 27 27 27 28 29 31 34 36 37 36 34 35 40 45 50 59 67 72 74 73 66 58 50 43 33 26 24 26 28 29 33 36 43 52 60 62 59 56 44 39 34 33 35 36 35 33 33 37 46 60 72 79 79 76 58 49 38 31 29 31 31 30 31 33 37 44 48 47 40 33 28 26 25 29 34 38 37 35 30 27 25 26 30 35 39 40 45 47 51 57 63 66 65 64 56 52 45 38 35 35 38 40 44 46 47 50 52 54 55 56 56 57 58 58 54 49 43 39 32 31 30 28 28 28 28 29 34 37 42 45 46 43 39 36 32 31 30 32 35 39 40 40 34 33 33 35 41 48 55 59 63 63 62 57 51 45 41 40 38 38 37 36 36 38 43 47 49 49 46 40 32 26 23 22 23 26 29 33 35 39 43 46 48 47 44 40 36 31 26 24 19 19 19 20 24 28 32 35 45 46 48 48 47 44 40 38 35 33 30 27 24 22 21 21 24 29 36 42 44 42 39 36 28 26 24 24 24 24 23 22 21 21 20 20 19 18 18 17 18 19 19 19 19 19 18 17 15 15 15 14 15 15 16 17 20 21 22 24 25 26 27 27 29 30 31 31 30 28 25 24 18 16 14 13 14 16 19 21 17 17 18 18 19 19 19 19 19 18 16 15 14 14 14 14 12 11 10 9 8 8 8 8 7 7 7 6 6 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 4 4 4 4 4 4 3 4 4 4 5 5 5 5 4 5 5 5 6 6 6 6 7 8 8 8 9 9 9 9 8 9 10 11 12 13 12 12 13 13 13 13 13 13 13 13 12 12 12 12 13 14 15 16 19 19 20 21 22 22 21 21 20 19 18 16 15 14 14 14 13 13 13 13 14 16 17 18 20 21 24 28 33 36 39 40 40 37 32 27 24 22 21 21 25 26 27 29 32 34 35 36 35 35 35 35 32 29 25 23 17 16 16 16 16 18 20 21 21 23 25 27 27 27 26 25 21 22 23 22 21 21 23 25 29 31 33 32 28 24 22 21 21 24 28 31 31 30 27 25 22 23 23 22 22 24 28 32 36 39 42 41 37 30 25 22 21 24 27 27 26 25 24 25 28 31 35 35 35 36 41 45 61 68 74 73 62 48 37 31 26 29 32 32 33 36 43 49 58 62 65 63 55 45 36 30 26 27 28 27 26 26 28 30 32 36 38 38 37 37 41 45 49 55 59 60 60 58 49 40 34 29 24 23 27 30 31 31 31 31 33 39 46 50 49 47 37 31 26 25 28 31 31 30 33 37 48 64 80 90 93 92 75 64 50 39 34 31 29 27 32 35 42 50 57 56 48 42 34 31 29 30 34 37 37 35 32 29 27 28 33 39 44 46 53 56 63 71 76 76 73 69 56 50 41 32 28 29 32 35 43 45 48 52 55 58 60 61 61 62 62 62 59 54 49 46 38 36 34 32 31 31 32 32 36 39 43 46 46 43 39 36 33 32 31 32 35 37 38 37 36 36 38 42 48 56 63 67 70 70 68 63 56 49 44 43 39 39 37 37 38 43 50 56 59 58 54 47 37 29 23 21 20 24 29 33 36 39 42 45 45 44 40 36 32 28 25 23 19 18 18 20 23 27 31 33 41 42 44 44 43 41 38 37 35 33 31 27 24 22 21 20 20 24 29 34 36 36 33 32 26 25 24 24 26 26 25 24 22 22 21 19 18 17 16 15 17 18 19 19 20 19 19 18 17 16 16 15 15 16 17 17 19 20 20 21 22 23 24 25 29 30 32 33 33 32 30 28 21 20 17 15 15 16 17 18 15 15 15 16 16 17 17 17 17 16 15 14 14 14 15 15 12 12 10 9 8 8 8 8 7 7 7 6 6 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 4 4 4 4 4 4 3 3 4 4 4 5 5 5 4 4 5 5 5 6 6 6 7 7 8 8 8 9 9 9 8 9 10 11 12 13 12 12 13 13 13 13 13 13 13 13 12 12 12 12 13 14 15 16 18 19 20 21 22 21 20 20 20 19 17 15 13 13 13 14 12 12 12 13 14 16 19 20 23 26 30 35 40 42 43 44 41 37 32 26 23 21 22 22 27 28 30 32 34 35 36 36 32 33 33 32 31 28 25 23 19 19 18 17 17 17 18 19 22 25 28 30 31 29 26 24 21 21 20 18 17 17 19 21 25 27 28 27 24 22 21 21 23 25 28 30 30 28 25 23 22 23 23 22 21 23 28 32 37 40 44 44 38 31 25 22 22 25 27 28 27 26 27 28 31 35 39 41 41 43 47 51 65 72 78 77 67 55 45 40 33 35 37 37 36 37 43 48 58 61 64 62 55 45 37 32 28 29 28 27 25 27 30 33 37 41 45 46 43 42 44 47 47 51 52 50 50 48 40 31 29 27 27 32 40 44 44 41 32 28 26 28 35 40 41 39 35 29 23 22 25 28 29 29 33 38 50 67 85 98 104 105 92 81 65 51 43 36 31 27 33 37 45 55 63 63 57 51 39 35 31 31 34 36 35 33 32 29 27 29 34 41 47 50 60 65 74 82 87 85 78 72 54 48 38 30 26 28 33 37 50 52 55 59 62 64 65 65 67 67 66 64 60 56 52 50 43 41 38 36 34 34 35 36 37 39 42 45 45 42 39 37 34 33 32 33 35 36 35 34 37 38 42 47 53 61 68 72 73 73 72 66 58 50 45 43 38 37 36 35 38 46 55 62 66 65 61 53 42 32 25 22 20 24 29 33 36 37 40 42 41 39 35 31 27 24 22 21 19 18 18 20 23 27 31 33 38 39 40 41 40 38 36 34 34 32 30 27 25 22 20 20 18 20 24 28 29 30 29 28 26 25 25 26 29 30 29 27 25 24 23 21 19 17 16 15 16 17 18 19 19 19 19 19 18 17 17 16 16 16 17 17 18 18 18 18 19 20 21 21 25 27 30 33 34 33 31 30 25 23 21 18 17 16 16 16 13 13 14 14 14 14 15 15 14 14 14 13 14 15 15 16 13 12 11 9 9 8 8 9 7 7 7 6 6 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 4 4 4 4 4 4 3 3 3 4 4 5 5 5 4 4 4 5 5 6 6 6 7 7 7 8 8 9 9 9 8 9 10 11 12 13 12 12 12 12 12 12 12 12 12 12 11 11 11 12 13 14 15 16 18 19 20 21 22 21 20 19 20 18 16 14 13 12 13 13 12 11 11 12 14 17 20 22 25 29 34 40 44 46 46 45 41 37 31 26 22 21 22 23 29 30 32 33 35 36 36 36 30 31 31 31 30 28 25 24 22 21 20 18 18 18 18 18 24 27 31 33 33 30 26 23 20 20 18 15 13 13 16 18 22 24 25 25 22 21 20 21 26 28 30 32 31 29 26 24 24 24 24 22 20 21 27 31 37 41 45 44 39 31 25 21 24 26 28 28 27 27 28 30 33 38 43 46 46 47 51 55 63 69 76 77 70 61 53 50 42 44 44 41 38 37 39 43 56 59 62 60 53 44 36 32 29 29 28 26 26 28 33 36 44 49 53 54 51 49 49 50 46 48 47 45 45 44 37 28 30 31 34 43 53 58 56 53 40 34 27 28 33 39 41 41 37 30 24 21 24 27 28 28 34 39 51 68 88 103 110 112 105 93 77 62 51 42 35 29 34 38 47 58 67 68 62 56 42 37 32 31 33 34 33 31 31 28 26 28 35 42 49 52 65 71 80 90 93 89 80 73 53 46 37 29 27 30 37 42 57 59 62 65 67 68 69 68 71 70 68 64 60 56 52 50 46 44 41 38 36 36 37 38 37 39 41 43 43 41 38 36 34 33 33 34 36 36 34 32 37 39 43 48 55 63 69 73 74 74 73 67 59 50 45 42 36 35 34 34 38 46 57 65 71 69 65 56 45 34 27 24 19 24 29 33 35 36 38 39 37 35 31 27 23 21 20 19 19 19 19 20 23 27 32 34 37 38 38 39 38 36 34 33 32 31 30 27 25 22 20 19 18 19 22 24 26 26 26 26 26 26 26 29 31 33 32 31 27 26 25 22 20 18 16 15 15 16 17 18 19 19 19 19 18 18 17 16 16 17 17 18 18 18 17 17 17 18 18 19 22 24 28 31 33 32 31 30 27 26 24 21 18 16 15 15 12 12 13 13 13 13 13 13 13 13 12 13 13 15 16 17 13 12 11 10 9 9 9 9 7 7 7 6 6 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 6 6 6 7 7 8 8 8 10 10 10 11 11 12 12 13 13 12 12 12 11 10 10 10 12 11 11 12 13 16 18 20 18 19 20 21 20 19 18 17 16 16 16 16 15 14 13 12 14 15 15 16 17 21 27 32 36 41 44 45 47 51 50 47 42 38 32 26 22 21 21 22 30 32 35 37 38 37 36 35 31 29 28 29 31 32 32 31 26 24 24 23 19 15 17 23 27 32 37 39 37 33 29 27 20 17 17 18 19 19 20 23 23 24 25 25 24 24 25 26 28 27 26 26 26 25 23 21 22 22 23 23 24 26 28 29 37 41 44 44 40 35 30 28 24 25 26 28 29 30 30 30 36 40 46 50 51 51 52 52 60 64 70 73 72 66 58 52 47 44 41 37 34 33 32 32 44 45 46 46 44 40 35 33 31 28 27 26 25 25 33 43 55 61 67 68 62 54 49 47 44 43 42 41 39 36 34 33 33 37 45 58 70 75 72 66 55 44 32 29 33 39 40 39 35 30 26 26 30 33 31 28 34 39 50 67 85 101 112 117 114 106 92 75 58 46 37 33 30 38 49 61 73 79 73 64 51 45 37 31 29 29 29 29 27 26 26 29 34 41 48 52 67 72 81 89 93 88 76 67 53 38 27 31 35 36 44 56 61 67 74 79 80 78 76 74 73 66 61 58 54 49 49 53 50 54 53 48 45 44 39 34 36 37 37 36 34 32 32 33 31 32 34 35 36 36 35 34 37 40 44 48 51 56 61 65 65 64 62 59 54 49 44 41 35 34 32 33 38 46 54 59 69 69 66 59 47 35 26 21 21 24 27 31 34 35 34 34 31 29 26 23 21 20 21 22 23 23 22 23 25 28 31 34 38 38 39 39 37 34 31 28 30 29 29 28 26 24 22 20 18 19 20 22 23 25 26 27 25 27 31 34 37 39 40 40 40 37 33 28 23 19 16 15 14 15 16 19 21 23 25 25 25 24 22 20 19 20 20 21 22 21 19 18 17 17 17 17 21 23 25 27 29 29 29 28 27 26 25 23 21 18 15 14 12 11 10 9 9 9 9 10 11 12 13 14 15 16 16 16 12 13 13 13 13 12 11 10 8 8 7 6 5 5 4 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 6 6 6 7 7 8 8 8 10 10 10 11 11 11 12 12 11 11 11 10 10 10 9 9 11 11 11 12 14 16 19 20 19 20 20 21 20 19 17 16 15 16 16 16 16 15 14 14 15 16 17 17 19 23 29 34 37 42 45 45 47 50 50 46 40 36 31 26 23 22 23 24 30 31 34 36 37 36 35 34 32 31 30 31 33 34 33 32 30 27 26 25 22 19 22 29 34 38 42 43 40 35 32 30 24 24 25 27 28 29 30 32 29 29 28 26 25 25 27 28 31 30 29 28 27 26 24 23 26 26 26 26 25 25 26 28 32 36 40 41 38 33 28 26 25 26 28 29 31 32 32 32 37 41 46 49 49 49 49 49 54 59 65 69 68 63 56 51 46 43 39 35 31 29 29 29 35 37 39 40 39 37 34 32 31 28 26 26 26 29 39 50 66 72 78 77 69 58 50 47 43 43 43 42 40 38 36 35 40 44 52 66 78 84 82 77 62 52 41 36 40 45 46 44 40 35 30 29 31 33 30 27 30 35 46 63 82 99 111 117 113 106 92 76 61 48 40 36 32 40 51 63 75 82 77 68 59 53 44 36 32 31 30 29 26 26 26 28 32 39 45 49 63 68 76 85 87 82 71 62 50 36 28 32 38 41 50 61 68 72 79 83 85 83 80 78 70 63 57 54 52 49 51 56 56 59 59 55 50 47 41 35 34 34 33 32 30 29 30 31 30 31 33 35 36 35 34 33 32 35 38 41 43 47 52 55 57 57 57 55 52 48 44 41 35 34 32 32 35 41 48 53 63 63 61 54 44 33 25 21 21 23 27 31 34 34 34 34 30 28 25 22 20 20 21 22 25 24 24 24 26 28 30 32 34 35 36 36 35 33 31 29 30 30 29 28 26 24 23 21 19 20 21 22 24 25 27 27 30 32 35 39 42 45 46 46 43 41 37 31 26 21 17 16 15 16 17 20 22 25 27 28 28 27 25 23 22 22 23 23 23 22 21 20 19 19 19 19 20 22 24 25 27 27 26 26 25 25 24 22 20 18 16 15 12 11 10 9 9 9 9 10 11 12 13 14 15 15 15 15 12 12 13 13 12 12 11 10 8 8 7 7 6 5 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 6 6 6 7 7 8 8 8 9 9 10 10 10 11 11 11 10 9 9 9 9 8 8 8 9 10 10 12 14 17 19 21 20 20 20 20 19 18 16 15 15 16 17 17 18 17 17 17 17 18 19 20 22 26 32 36 40 45 47 45 46 49 48 44 36 34 30 26 24 25 26 28 30 31 33 35 36 36 35 34 35 34 34 35 37 38 37 35 36 31 28 27 25 24 28 35 42 45 47 47 43 39 36 35 31 33 37 40 42 44 44 43 38 36 32 29 27 29 31 32 37 36 33 30 28 27 27 27 33 34 33 31 27 25 25 26 29 33 38 40 38 34 29 27 26 27 29 31 33 34 35 35 39 43 46 47 46 45 44 44 46 51 58 64 64 60 54 49 45 41 36 31 27 25 25 25 27 28 31 33 34 34 32 31 32 27 25 25 27 33 47 61 79 85 89 87 75 61 50 44 41 42 43 43 42 40 38 37 44 48 58 71 84 90 90 87 70 60 49 45 46 49 49 48 45 40 34 32 32 32 29 26 27 32 42 58 77 94 106 112 112 105 92 77 62 50 41 37 34 43 54 66 79 87 85 78 69 62 51 42 35 31 29 27 26 25 25 26 30 35 41 44 55 60 68 76 77 72 62 54 45 34 29 35 41 45 55 66 71 74 80 85 87 86 83 81 68 60 53 50 49 50 56 63 66 70 71 65 60 54 45 37 31 30 28 26 26 26 27 27 28 29 32 34 35 35 33 32 28 30 33 34 35 37 41 43 47 48 49 50 49 47 44 42 37 35 32 30 32 36 41 44 53 54 52 47 39 30 24 22 21 23 27 31 33 34 34 33 28 26 23 21 20 21 22 23 27 27 27 27 27 28 28 28 29 30 31 32 32 31 31 30 31 30 30 29 28 26 24 23 20 21 22 24 25 27 28 29 34 36 39 42 46 48 50 51 48 46 41 36 30 24 20 18 16 17 19 21 24 28 30 32 33 32 31 29 27 26 26 26 25 25 23 22 21 21 21 21 20 20 22 22 23 23 22 22 22 22 21 21 20 18 16 15 12 11 10 9 9 9 9 10 11 11 12 14 14 15 14 14 12 12 13 13 12 11 10 10 8 8 7 7 6 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 6 6 6 7 7 8 8 8 9 9 9 9 9 10 10 10 8 8 7 7 7 7 7 7 8 9 10 12 15 17 19 20 21 21 20 19 18 17 16 15 15 16 17 19 19 20 20 20 19 20 22 24 26 30 35 39 43 47 47 44 44 46 44 41 32 30 28 26 26 27 29 30 31 32 34 35 36 36 36 36 39 39 39 41 43 43 41 39 39 33 28 27 27 27 33 40 46 48 50 49 46 43 41 41 42 48 53 56 59 61 58 54 47 42 35 30 30 33 37 39 45 43 39 35 31 29 31 32 41 42 42 38 31 26 25 26 28 33 40 43 42 38 34 32 29 30 32 34 36 38 38 39 42 44 46 46 43 40 39 39 41 46 54 61 63 60 54 50 42 38 32 26 23 22 23 24 26 28 30 32 33 33 32 32 33 28 24 24 27 36 53 69 88 93 96 91 77 61 47 40 38 39 41 42 42 41 39 38 42 47 56 69 81 88 89 88 72 64 54 49 48 49 48 47 46 42 36 32 30 28 25 23 26 31 40 55 73 88 99 104 108 101 88 73 58 46 38 34 34 44 57 71 85 95 95 90 79 71 58 47 38 32 28 25 26 25 24 25 27 31 35 38 46 51 58 64 65 60 53 47 41 35 33 38 43 47 54 62 65 68 73 80 85 86 84 82 70 61 53 50 51 55 64 73 82 86 86 79 71 62 50 39 30 28 25 24 24 25 26 26 26 28 31 33 34 33 32 31 27 29 30 30 30 31 33 36 37 40 43 46 48 48 46 45 42 39 35 31 30 32 34 37 43 44 43 39 33 27 24 23 22 24 28 31 33 33 32 32 25 24 22 20 20 22 24 25 29 30 30 30 29 28 26 24 25 25 26 27 28 29 30 30 31 31 30 30 28 27 25 24 23 24 25 26 28 30 31 31 34 36 39 42 45 48 50 51 51 49 45 39 33 27 22 20 18 18 20 22 26 30 33 35 37 37 35 34 32 31 30 30 28 27 26 25 24 24 24 24 20 20 20 20 19 19 18 18 18 18 19 19 18 18 17 16 12 11 10 9 9 9 9 10 10 11 12 13 13 14 13 13 11 12 12 12 12 11 10 9 8 8 8 7 7 6 6 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 6 6 6 7 7 8 8 8 9 9 9 9 9 8 8 8 6 6 6 6 6 7 7 7 8 9 11 13 15 17 18 19 20 20 19 18 17 16 16 16 16 17 19 20 21 22 22 22 20 22 25 27 29 33 38 42 45 47 46 42 40 41 39 35 28 27 26 25 26 28 30 32 33 34 35 36 37 37 37 37 41 42 44 46 48 48 44 41 38 31 25 25 26 28 34 41 46 47 49 49 48 48 49 51 60 69 76 78 79 79 73 64 52 44 34 29 31 38 44 48 55 52 47 40 34 33 36 39 49 51 51 45 36 29 27 28 30 36 43 47 47 43 39 37 34 35 37 39 40 42 42 42 45 46 47 45 40 37 35 35 39 44 53 60 62 59 54 50 38 35 29 24 22 23 26 29 35 36 36 37 37 36 35 34 35 29 24 24 28 39 58 76 96 99 99 91 76 58 45 39 34 36 39 41 41 40 38 36 39 43 52 62 72 79 82 82 72 65 56 50 48 47 46 44 42 39 34 30 27 24 22 21 24 29 39 54 72 87 96 100 101 93 80 64 50 39 32 29 34 46 62 76 91 102 104 100 89 80 66 53 43 36 31 28 27 26 25 24 25 27 30 31 38 42 48 52 52 49 45 43 40 39 40 44 46 47 50 54 55 58 64 73 81 85 85 83 75 65 57 55 58 64 76 88 101 104 102 93 81 69 54 42 32 29 26 26 28 29 29 27 27 28 29 30 30 30 30 29 26 27 28 28 26 27 29 31 34 37 43 48 51 52 52 51 49 45 40 34 31 30 31 32 34 35 34 31 27 24 24 24 24 26 28 31 32 31 30 29 23 22 21 20 21 23 26 28 32 33 35 35 33 29 25 23 22 22 22 22 24 26 28 29 30 30 30 30 28 27 25 25 25 26 27 29 30 32 33 34 35 36 38 40 43 46 48 50 50 48 45 41 35 30 25 22 19 19 20 22 25 30 34 36 39 38 38 37 35 34 33 32 30 29 28 27 26 26 26 26 22 21 20 18 17 16 16 15 15 16 16 17 17 17 16 15 12 11 10 9 9 9 9 10 10 11 12 12 13 12 12 12 11 11 12 12 11 11 10 9 8 8 8 7 7 7 7 6 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 6 6 6 7 7 8 8 8 9 9 8 8 8 7 7 7 6 6 6 6 7 7 7 7 9 10 12 14 16 17 17 17 19 19 18 17 16 17 17 17 18 19 20 22 23 23 23 23 20 23 26 29 32 35 40 43 45 47 44 38 35 35 33 29 24 24 24 24 25 28 30 32 33 33 34 35 35 36 37 37 41 42 45 48 50 49 45 41 35 27 22 23 26 29 34 40 44 46 48 50 53 57 62 66 81 93 100 99 97 94 84 71 52 43 31 27 32 43 52 58 64 62 55 45 38 36 41 46 55 58 59 53 42 34 32 33 35 41 49 54 54 50 46 43 42 43 44 46 47 48 48 48 48 48 47 44 39 35 33 33 37 42 51 57 59 56 51 47 34 31 26 22 23 28 34 38 45 45 44 43 42 40 39 38 36 30 26 26 31 44 65 83 103 103 99 88 71 54 42 37 33 35 38 40 41 39 37 35 38 42 48 56 63 68 71 72 68 62 55 49 46 44 42 40 35 33 30 26 23 22 21 21 21 27 40 57 74 88 96 99 90 81 67 52 40 31 27 26 36 50 68 83 96 106 107 103 95 86 72 59 49 41 36 33 28 27 25 24 24 25 26 26 31 34 38 40 40 40 41 42 44 47 52 54 53 50 48 48 49 51 57 67 78 84 85 83 76 68 61 62 67 77 92 105 121 122 117 105 90 75 58 45 37 34 32 33 36 37 35 32 30 29 28 27 26 27 27 28 25 26 27 27 26 26 28 30 36 41 47 54 58 59 59 58 54 51 44 38 33 30 29 28 28 29 28 26 24 23 24 26 26 28 30 31 31 29 27 25 22 22 21 21 23 26 29 31 37 39 41 42 40 34 28 24 23 22 20 19 20 23 25 27 29 29 29 29 28 27 25 24 25 26 27 29 30 32 33 34 35 36 36 38 40 42 45 46 45 44 43 40 36 31 27 24 19 19 19 20 24 28 32 35 37 37 37 37 36 35 34 33 31 31 29 28 27 27 27 27 25 23 21 18 16 15 14 14 14 14 15 15 16 15 15 14 12 11 10 9 9 9 9 10 10 10 11 12 12 11 11 10 11 11 11 11 11 10 9 9 8 8 8 8 8 7 7 7 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 6 6 6 7 7 8 8 8 8 8 8 7 7 7 6 6 6 6 6 6 7 7 8 8 10 11 13 15 16 16 15 15 18 17 16 16 16 17 18 19 20 21 22 23 24 24 24 23 20 23 27 30 33 36 41 44 44 45 42 35 31 30 28 23 21 21 22 23 25 27 29 30 31 31 31 32 33 34 35 35 38 40 43 47 49 47 42 38 32 24 20 22 26 29 33 38 44 46 50 54 60 68 77 84 97 109 116 113 107 101 87 70 50 39 27 24 32 47 59 66 72 69 61 50 41 39 45 51 59 63 65 59 47 39 37 38 45 51 60 65 65 61 56 53 51 52 53 54 55 55 54 54 49 49 48 44 38 34 32 32 34 39 47 53 54 51 45 41 31 28 24 22 26 33 42 48 51 50 49 48 46 44 42 41 36 31 27 29 37 51 74 93 108 105 96 80 61 44 35 31 33 36 39 42 42 40 37 35 36 40 45 50 54 57 60 61 59 55 49 44 40 37 34 33 29 28 26 24 22 21 22 23 27 33 46 62 76 86 91 91 78 69 55 41 31 27 27 28 41 56 75 89 100 106 105 100 93 85 72 59 49 42 37 35 29 28 26 25 23 23 23 23 27 29 31 32 32 34 39 43 49 57 65 67 63 57 51 47 44 45 50 61 73 80 81 79 74 67 63 67 77 90 108 122 137 137 129 113 96 78 61 47 43 40 39 42 46 46 42 37 33 31 27 24 22 23 25 27 27 29 30 30 29 30 33 35 42 47 54 61 65 67 66 65 58 54 47 40 33 29 27 26 25 25 25 23 22 22 25 27 29 30 31 31 30 27 24 22 22 21 21 22 24 28 31 34 42 45 48 50 47 41 34 29 25 23 20 18 18 20 23 25 28 28 28 28 27 26 25 24 23 24 25 26 28 29 31 31 32 32 32 32 33 35 37 39 39 39 39 38 35 31 28 26 19 19 18 19 21 25 30 33 34 35 36 36 36 35 34 33 32 31 30 29 28 27 28 28 28 26 23 19 17 15 14 14 13 13 14 14 14 14 13 12 12 11 10 9 9 9 9 10 10 10 11 11 11 10 10 9 10 11 11 11 11 10 9 8 8 8 8 8 8 8 8 8 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 6 6 6 7 7 8 8 8 8 8 8 7 7 6 6 5 6 6 6 7 7 8 8 8 11 12 14 15 16 15 14 14 17 16 15 15 16 17 19 21 21 22 23 24 24 24 24 23 20 23 27 31 33 37 41 44 44 44 40 33 28 27 24 20 20 20 21 22 24 26 28 29 29 29 29 30 30 32 33 34 35 37 41 45 47 45 40 35 31 23 19 22 27 30 33 37 44 47 52 58 66 77 88 95 103 116 123 117 109 102 84 66 47 36 24 22 32 49 63 71 77 73 65 53 43 41 48 55 61 65 68 62 50 42 40 42 54 61 70 75 74 70 65 62 58 59 59 60 60 59 59 58 50 50 48 44 38 34 32 32 32 37 44 49 50 46 40 35 29 26 23 23 28 37 48 54 53 52 51 49 47 45 44 43 35 30 28 32 41 57 80 100 109 104 91 72 51 35 27 24 35 37 41 43 43 41 38 35 35 37 41 44 47 49 51 53 51 48 43 37 33 30 27 26 25 25 24 23 21 22 24 26 36 42 53 66 77 83 83 82 70 62 48 35 27 26 28 31 45 61 79 93 101 105 102 96 89 80 68 56 47 40 36 33 30 29 27 25 23 22 21 21 26 27 28 27 28 32 39 45 53 63 73 76 71 63 55 48 40 41 45 56 67 75 75 73 70 65 63 70 82 98 117 133 146 145 136 118 99 80 62 48 47 45 44 48 53 52 47 41 35 32 26 22 20 21 24 26 31 33 34 35 35 36 39 42 47 51 59 66 70 72 71 70 59 55 48 40 33 29 26 25 24 24 24 22 21 22 25 28 31 31 32 31 29 26 22 20 22 21 21 22 25 29 33 35 46 49 53 55 53 46 38 33 27 24 20 17 17 18 21 23 27 27 27 27 26 25 24 23 21 21 22 24 26 27 28 29 28 27 26 26 27 28 30 31 34 35 36 36 34 31 28 26 19 18 17 17 20 24 28 31 31 32 34 35 36 35 34 33 32 31 30 29 28 28 28 28 30 27 24 20 17 15 14 14 13 13 14 14 14 13 12 11 12 11 10 9 9 9 9 10 9 10 10 11 11 10 9 9 10 11 11 11 11 10 9 8 8 8 8 8 8 8 8 8 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 7 7 8 8 8 7 7 7 6 6 5 5 5 4 5 6 6 7 8 9 9 10 12 13 14 15 14 13 13 14 15 16 17 19 20 21 22 23 24 24 24 24 23 22 21 22 24 27 31 35 38 40 40 41 38 33 28 24 22 21 21 18 18 19 20 22 23 24 24 28 27 27 27 27 28 29 30 31 32 33 37 39 38 35 32 23 20 18 17 20 27 35 40 44 49 58 65 72 82 93 100 111 115 116 111 102 90 71 56 39 29 23 26 35 48 63 76 79 73 60 46 36 34 41 48 60 64 64 57 46 43 48 56 67 77 86 88 85 81 73 64 60 60 60 63 64 62 56 51 46 45 42 39 36 33 30 29 33 34 36 38 40 37 32 28 23 23 26 29 35 42 48 52 56 53 49 47 46 45 43 41 31 30 30 32 42 61 83 99 108 97 81 63 43 28 25 29 36 45 52 50 47 45 42 39 42 42 43 43 44 44 45 45 46 44 40 35 30 26 23 21 20 22 22 22 21 22 25 27 32 44 58 68 77 82 79 74 65 52 36 26 21 21 29 38 54 68 84 91 94 94 91 86 72 63 53 47 45 43 39 36 31 30 28 26 25 24 25 25 28 30 30 27 25 28 36 43 55 68 79 80 77 72 62 51 43 44 48 56 65 70 70 68 63 62 63 70 84 104 124 136 146 142 132 115 94 74 60 52 45 47 50 54 55 52 46 42 34 30 24 19 18 21 25 29 34 37 40 41 41 42 44 46 54 58 64 69 72 72 70 68 61 56 48 41 36 32 29 26 20 18 18 21 21 21 25 31 35 40 40 34 28 26 22 17 18 19 22 26 30 35 39 41 50 52 57 60 61 56 48 42 29 26 22 18 16 17 19 21 24 25 26 26 25 24 22 20 22 22 22 23 23 24 24 24 22 21 20 20 21 23 25 26 29 31 32 33 33 31 28 26 20 19 17 16 17 19 21 23 28 29 30 32 33 33 33 33 29 29 28 28 27 26 26 25 24 23 22 19 17 15 13 12 12 12 12 11 11 10 10 10 10 10 10 9 9 8 8 8 9 9 9 9 9 9 9 9 10 10 10 9 9 8 8 8 8 8 8 7 7 6 6 6 5 5 5 5 5 5 5 5 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 7 7 7 8 8 7 7 7 6 6 5 5 5 5 5 6 7 8 8 9 9 10 11 13 14 14 14 13 12 13 14 15 17 19 21 22 23 24 24 24 24 23 23 22 21 23 25 27 31 34 36 37 38 38 35 31 26 23 20 20 20 18 18 19 20 21 22 23 23 24 25 26 27 28 29 29 29 29 29 31 33 35 34 31 28 22 20 17 17 21 27 35 40 45 51 60 67 73 82 91 98 103 106 106 99 90 79 62 48 36 28 23 27 36 47 61 72 71 66 55 41 31 30 36 43 53 57 59 54 46 46 55 63 81 91 98 97 92 84 74 65 62 61 61 62 62 59 53 48 42 41 39 37 34 31 29 27 28 28 29 31 33 31 28 25 23 24 27 31 37 43 48 51 51 49 46 44 43 41 39 36 29 29 28 32 43 61 83 98 103 91 74 56 38 25 25 32 45 55 62 60 55 51 45 40 42 42 43 43 43 43 43 43 43 41 38 34 29 25 22 21 20 22 23 24 24 24 27 29 36 47 60 68 74 77 73 67 56 44 31 24 21 24 33 44 60 73 86 90 89 86 80 74 61 53 45 41 41 41 38 35 34 32 29 26 25 25 26 27 31 32 32 29 26 28 35 42 54 66 76 78 75 70 60 50 45 45 48 54 60 62 61 58 53 54 57 65 81 101 120 131 137 132 120 103 83 64 51 45 44 46 49 53 54 51 44 39 30 26 22 18 19 22 27 31 39 42 44 45 44 44 45 47 55 59 65 70 73 72 69 66 59 54 47 40 35 31 28 25 22 19 19 21 21 21 27 34 37 42 43 38 33 30 25 20 20 21 23 27 31 36 39 42 50 52 56 60 60 56 48 42 32 29 24 19 17 17 18 20 24 25 26 26 26 24 22 21 21 21 21 21 21 22 22 22 20 19 18 18 18 20 22 23 28 29 31 32 31 29 27 25 20 19 17 16 16 18 21 22 27 27 29 30 31 31 31 31 28 28 27 27 26 25 24 24 23 22 21 19 17 15 13 12 12 12 11 11 11 10 10 10 10 10 10 9 9 8 8 8 9 9 9 9 9 9 9 9 10 10 9 9 9 8 8 8 8 8 7 7 7 6 6 6 5 5 5 5 5 5 5 5 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 6 7 7 7 8 7 7 6 6 6 6 5 5 6 6 6 7 8 8 9 9 10 11 12 13 13 13 13 12 12 13 15 17 19 21 23 24 24 24 23 23 23 22 22 22 24 25 27 29 31 33 33 34 33 30 27 23 20 18 18 18 19 18 18 18 19 20 21 22 21 23 26 29 30 30 30 29 27 27 27 28 30 29 26 23 20 18 17 17 21 28 34 39 45 52 61 68 73 79 87 92 91 94 92 85 78 68 54 42 34 27 23 28 36 45 55 64 62 57 49 37 28 27 32 38 45 49 52 50 48 53 65 76 95 103 108 105 97 88 77 67 64 62 61 60 57 53 47 43 37 36 36 34 32 30 28 26 24 23 23 25 26 26 25 23 24 25 29 33 38 43 47 49 45 43 41 40 39 37 34 31 27 26 26 30 42 61 82 96 96 83 65 47 32 24 28 37 57 68 75 73 65 56 46 38 40 41 41 41 41 40 40 39 39 38 36 33 29 25 22 20 20 22 25 26 27 28 31 33 41 51 62 68 71 72 66 59 45 35 25 21 22 28 40 51 66 78 88 87 81 73 64 56 45 40 35 34 36 38 37 36 37 34 31 28 26 27 29 30 35 35 34 30 27 28 33 39 51 60 69 71 68 63 55 47 47 48 50 53 55 54 50 47 43 45 50 59 74 91 107 117 123 117 104 87 68 52 42 38 41 43 47 50 51 46 39 34 24 22 20 19 21 26 32 36 47 49 50 49 47 46 47 48 54 59 66 71 73 71 67 63 57 52 45 39 35 31 27 24 23 20 18 20 21 22 28 36 39 45 48 45 40 35 29 23 22 23 25 28 32 36 40 42 49 51 53 56 57 52 46 40 32 29 25 20 17 17 17 18 24 24 26 26 26 25 23 22 20 20 20 20 20 19 19 19 18 17 16 15 15 16 17 18 25 26 28 29 29 27 25 23 19 18 16 15 15 17 19 21 24 25 26 27 28 28 28 28 26 26 25 25 24 23 22 22 22 21 19 18 16 14 13 12 12 11 11 11 10 10 10 10 10 10 10 9 9 8 8 8 9 9 9 9 9 9 9 9 10 9 9 9 8 8 8 8 8 7 7 7 6 6 6 6 5 5 5 5 5 5 5 5 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 7 7 7 6 6 6 6 6 6 6 6 6 7 7 8 8 9 9 9 10 10 11 12 12 12 12 12 12 13 15 17 19 21 23 24 23 23 22 22 21 21 21 21 24 25 26 28 29 29 29 29 27 25 23 20 18 17 17 16 19 18 18 17 18 19 20 21 20 23 28 32 35 34 33 31 28 27 25 25 26 25 22 20 18 17 16 18 21 27 33 37 43 49 58 64 67 71 77 81 80 82 82 77 72 66 55 45 35 29 25 29 35 40 47 54 54 51 45 36 29 27 31 36 39 44 48 49 52 62 77 89 102 109 112 106 97 87 76 66 63 61 59 55 51 46 41 38 34 34 34 34 33 31 29 28 26 24 23 23 25 26 26 25 26 28 31 35 39 42 44 45 41 40 39 39 38 36 32 29 25 24 24 29 41 59 78 90 89 76 58 42 29 26 35 47 68 78 86 82 71 58 45 35 36 37 38 38 37 36 34 33 35 35 35 34 31 28 24 22 20 23 26 28 30 32 36 38 46 55 64 68 70 69 62 53 39 30 22 21 24 31 44 56 69 79 85 81 71 61 49 40 33 31 29 31 35 38 39 39 39 36 32 29 28 29 31 33 38 37 35 31 28 28 32 35 44 50 57 59 57 52 47 43 48 50 51 52 51 47 43 39 37 40 45 53 65 79 91 98 108 101 89 73 56 43 36 33 35 37 41 44 45 41 34 28 22 22 21 23 27 33 39 43 54 54 54 51 48 46 46 48 54 58 65 70 72 69 64 61 55 51 45 39 35 31 27 24 24 20 18 19 19 21 28 37 40 47 52 50 45 41 34 27 24 25 27 29 32 36 39 41 45 46 48 50 50 46 40 35 28 26 22 19 17 16 17 18 22 23 25 26 26 26 24 23 21 21 20 20 20 20 19 19 18 17 15 14 13 14 15 16 22 23 25 26 26 25 23 21 19 17 15 14 14 16 18 19 21 22 23 24 24 24 24 24 24 23 23 22 21 20 20 19 19 19 18 16 15 14 13 12 11 11 11 10 10 10 9 9 10 10 10 9 9 8 8 8 9 9 9 9 9 9 9 9 9 9 9 8 8 8 7 7 7 7 7 6 6 6 5 5 5 5 5 5 5 5 5 5 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 6 6 6 7 7 6 6 6 6 6 6 6 6 7 8 8 8 8 9 9 9 10 10 10 10 10 11 12 12 13 13 15 17 19 21 23 23 22 22 20 19 19 19 20 20 23 24 25 25 26 25 25 25 22 22 20 19 18 17 17 16 19 18 17 17 17 19 21 23 23 27 32 37 40 39 37 36 32 29 26 24 24 23 21 19 17 17 17 18 22 26 31 34 37 43 50 54 56 58 63 66 67 71 74 74 73 70 62 53 41 33 28 29 32 34 39 45 47 46 43 37 31 29 32 36 40 44 49 53 59 70 86 97 108 113 112 103 91 81 70 61 59 58 55 51 45 41 37 36 36 37 38 39 38 36 34 32 30 28 26 26 27 29 29 28 29 31 33 36 38 40 40 41 39 39 39 41 41 39 35 31 25 23 22 27 38 54 70 79 80 68 52 39 30 31 43 56 77 87 92 86 73 59 44 32 31 32 33 34 33 31 29 28 32 33 35 35 34 31 27 25 21 23 26 28 31 35 41 45 50 59 67 70 71 69 61 52 39 31 23 22 26 33 45 57 66 74 78 72 61 50 39 31 28 28 29 32 37 40 42 42 39 36 33 30 29 29 31 32 37 36 33 30 28 28 30 32 36 39 42 44 43 40 39 40 46 49 51 51 48 43 38 35 33 36 41 48 58 68 77 82 89 84 75 62 48 38 32 30 30 32 35 39 40 38 32 28 27 27 28 31 36 42 47 51 58 57 55 52 47 45 45 46 52 56 63 68 69 67 63 59 55 52 46 42 38 34 30 27 25 20 18 18 18 20 27 35 39 47 53 52 47 43 36 28 25 26 27 29 31 34 37 38 40 39 40 41 41 38 32 28 21 20 18 16 15 16 17 19 20 22 23 25 26 25 24 24 22 22 22 22 22 22 22 21 21 19 17 15 14 14 14 15 19 21 23 24 24 23 21 20 18 17 15 13 13 14 16 18 19 19 20 21 21 21 21 20 21 20 20 19 18 17 17 16 17 17 16 15 14 13 12 12 11 11 10 10 10 9 9 9 10 10 10 9 9 8 8 8 9 9 9 9 9 9 9 9 9 9 8 8 8 7 7 7 7 7 6 6 6 5 5 5 5 5 5 5 5 5 5 5 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 4 5 5 5 6 6 6 6 5 5 6 6 6 6 7 7 8 8 8 9 9 9 9 9 10 9 9 9 9 10 11 12 14 15 16 17 19 20 21 22 21 20 18 17 16 17 18 19 22 22 23 23 23 23 22 22 20 19 19 19 19 18 18 18 19 18 17 16 18 20 23 25 28 31 36 41 43 43 41 39 35 32 27 24 22 21 20 18 17 17 18 19 22 25 28 30 31 36 41 43 43 44 48 52 55 63 71 75 78 77 70 60 46 37 28 27 28 30 36 42 43 45 45 41 36 34 36 39 46 49 53 58 64 75 89 98 110 112 107 94 81 71 62 54 55 55 52 48 43 39 39 39 43 45 46 47 46 44 41 40 36 34 32 31 32 33 32 31 34 34 34 35 35 35 36 36 38 39 41 45 46 45 40 36 28 24 22 25 34 47 59 66 68 59 46 37 32 34 48 62 82 90 93 84 70 55 41 30 27 28 30 31 31 29 27 25 29 31 34 36 36 33 29 26 21 23 25 27 31 37 45 51 56 65 72 75 74 71 62 53 41 32 25 23 26 32 43 54 61 68 70 62 51 42 34 27 27 29 32 35 38 40 41 42 36 35 33 31 29 29 29 30 34 32 29 27 26 27 28 29 32 30 31 32 32 32 36 42 47 50 53 53 48 42 37 34 34 36 40 46 53 61 67 71 69 67 63 55 45 36 31 29 30 31 33 37 40 40 38 35 37 38 40 43 47 52 56 58 60 59 56 51 46 43 43 44 50 54 59 63 65 64 61 59 58 54 50 46 43 39 35 31 26 22 20 21 20 20 26 33 37 45 51 49 46 42 35 28 25 25 26 27 29 31 33 34 34 33 33 33 32 30 26 22 17 16 15 14 15 16 17 18 18 19 21 23 24 24 24 23 22 22 23 23 24 24 24 25 24 22 20 17 15 14 15 15 17 19 21 23 23 22 20 19 17 16 14 12 12 13 15 16 17 18 19 19 19 19 18 18 18 18 17 16 15 15 14 14 15 14 14 14 13 12 12 12 10 10 10 10 9 9 9 8 10 10 10 9 9 8 8 8 9 9 9 9 9 9 9 9 8 8 8 8 7 7 7 6 6 6 6 6 5 5 5 4 5 5 5 5 5 5 5 5 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 4 4 5 5 5 6 6 6 5 5 5 6 6 7 7 7 9 9 9 9 9 9 9 9 10 9 8 8 8 9 11 12 16 16 17 18 18 19 20 20 19 18 16 14 14 15 16 17 20 20 21 22 22 21 20 20 18 19 19 20 20 20 20 20 18 17 16 16 18 22 26 28 32 35 38 42 44 44 43 41 38 33 27 23 21 20 18 17 18 18 19 20 22 23 25 26 27 30 33 33 32 33 37 41 51 61 73 81 86 86 77 66 49 38 27 24 25 28 36 44 47 50 52 50 46 44 45 48 52 55 58 62 67 76 87 94 99 99 93 80 69 62 57 52 53 53 52 48 43 42 43 46 52 53 55 56 55 53 49 47 45 43 42 41 42 41 39 37 38 37 35 33 32 31 32 32 37 39 43 48 51 50 45 41 31 26 22 23 30 41 49 54 56 48 40 34 31 35 48 62 79 85 85 75 60 46 34 25 25 26 29 31 31 30 28 26 24 27 32 35 36 33 29 26 22 23 23 25 29 38 48 55 64 72 79 79 77 72 62 53 41 32 24 23 25 30 41 51 58 63 63 54 43 36 30 25 27 30 33 36 37 37 38 38 33 32 32 31 30 28 27 26 29 27 25 24 25 26 27 28 33 27 25 26 27 29 38 48 56 60 63 62 55 48 42 39 45 45 45 46 49 52 54 56 56 57 58 55 48 41 35 32 33 34 35 40 44 48 48 48 49 50 52 54 57 61 63 65 61 60 56 51 45 43 43 44 48 51 55 59 61 62 61 60 61 58 54 51 48 44 39 36 30 26 24 25 23 22 26 32 35 42 47 45 42 39 33 27 24 24 24 25 26 28 30 31 31 30 28 28 27 25 21 18 17 17 16 15 15 16 16 17 16 17 19 22 23 23 23 23 21 21 22 23 24 25 26 26 26 24 21 18 16 14 14 14 16 18 20 22 23 22 20 19 17 15 13 11 11 12 13 15 17 17 18 18 18 18 17 16 16 16 15 14 13 13 12 12 13 13 13 12 12 12 12 12 10 10 10 9 9 9 8 8 10 10 10 9 9 8 8 8 9 9 9 9 9 9 9 9 8 8 8 7 7 7 6 6 6 6 6 5 5 5 4 4 5 5 5 5 5 5 5 5 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 4 4 4 5 5 6 6 6 5 5 5 6 6 7 7 7 9 9 9 9 9 9 9 9 9 9 8 7 8 9 10 12 17 17 17 18 18 19 19 19 18 17 14 12 12 13 15 16 19 19 20 20 21 20 20 19 18 18 20 21 21 21 21 21 18 17 16 17 19 23 28 31 34 36 39 42 44 44 43 42 38 34 27 22 20 19 17 16 18 19 19 20 21 22 23 24 25 27 29 28 26 27 31 36 52 64 78 88 94 93 83 71 50 37 25 21 23 28 38 48 53 57 60 59 56 54 54 56 56 58 61 64 68 75 84 90 83 84 79 68 60 57 56 53 52 53 52 49 45 44 47 51 58 59 61 62 61 58 54 52 54 52 51 50 50 49 46 43 41 38 35 31 29 29 29 30 36 38 43 49 53 52 48 44 33 28 22 22 28 37 43 47 47 41 35 32 30 34 47 60 73 78 76 64 49 37 26 18 24 26 29 32 32 31 29 27 21 25 30 34 35 32 28 25 23 22 22 23 28 38 50 58 70 78 83 83 79 73 62 52 39 31 23 22 24 29 39 49 56 60 59 49 38 32 28 24 28 30 34 36 35 34 34 34 30 31 31 31 30 28 25 24 25 24 22 22 24 26 27 27 35 27 23 24 26 30 41 54 67 71 74 71 64 55 49 46 58 56 52 48 46 44 43 43 51 54 58 58 53 47 41 38 38 37 39 43 49 54 57 57 57 58 59 61 64 66 67 68 62 60 57 51 46 43 43 45 47 49 52 56 59 60 61 61 63 60 57 54 51 47 43 39 32 29 28 28 26 24 26 32 33 40 44 42 39 37 32 26 22 22 23 23 24 26 27 28 30 28 26 26 25 23 19 17 20 19 18 16 16 15 15 16 14 16 18 21 22 23 22 22 19 20 21 22 24 25 27 27 26 24 21 18 15 14 13 13 16 18 20 22 23 22 20 19 17 15 13 11 10 11 13 14 16 17 17 18 18 17 16 16 15 14 14 13 12 12 11 11 12 12 12 12 12 12 12 12 10 10 10 9 9 8 8 8 10 10 10 9 9 8 8 8 9 9 9 9 9 9 9 9 8 8 8 7 7 6 6 6 6 6 6 5 5 4 4 4 5 5 5 5 5 5 5 5 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 6 6 6 6 6 6 6 6 8 8 8 8 8 8 8 8 7 7 7 8 9 10 12 13 16 16 17 18 18 18 17 17 13 13 12 11 11 12 12 13 14 14 15 16 17 17 18 18 18 18 19 20 20 20 19 19 18 18 18 19 22 27 32 36 41 42 42 42 41 40 38 36 31 29 26 23 20 19 18 18 16 16 17 18 18 19 20 20 20 23 24 23 21 23 30 37 55 69 84 93 94 88 74 61 42 35 25 21 26 36 47 53 64 65 66 66 64 60 56 54 54 55 58 61 65 68 70 72 71 67 60 54 51 52 54 57 58 55 51 47 46 47 49 51 59 62 65 66 63 60 58 57 58 58 58 58 57 55 51 48 44 36 30 31 31 26 26 30 37 40 45 51 54 52 47 42 35 31 26 25 27 32 35 37 35 32 27 25 29 36 45 51 66 65 61 52 41 30 23 20 21 30 37 39 40 40 34 26 26 26 27 29 32 32 30 28 23 21 20 22 29 41 53 60 72 76 81 83 80 72 62 56 38 32 25 21 24 31 39 43 51 50 48 42 36 30 28 28 27 30 33 33 30 28 29 32 32 36 38 36 34 34 31 25 26 23 20 21 25 31 35 37 34 33 29 26 28 39 54 65 78 86 87 76 66 61 58 55 59 66 68 58 45 39 37 36 42 50 60 66 65 58 50 44 41 41 43 48 54 60 63 64 66 64 63 64 66 68 68 68 62 60 56 52 49 47 47 46 49 49 51 52 54 56 58 58 60 60 59 58 54 50 45 43 36 35 34 33 31 29 28 27 30 31 32 33 32 30 27 25 18 18 19 20 21 23 24 24 21 23 24 24 23 22 23 24 22 21 21 20 19 18 17 17 14 15 17 18 19 20 20 20 21 20 20 20 21 23 26 27 27 26 24 21 19 16 14 13 15 16 17 19 19 20 20 19 16 15 13 11 10 10 10 11 14 15 15 16 16 15 15 14 12 12 12 11 11 10 10 10 13 13 12 11 10 10 10 10 11 11 10 9 8 8 7 6 7 7 7 8 8 9 9 9 10 10 10 10 10 10 10 10 7 7 7 7 7 7 7 7 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 6 6 6 6 6 6 6 6 8 8 8 8 8 8 8 8 7 7 7 8 9 10 12 13 16 16 17 17 17 17 16 16 13 12 12 11 11 11 12 12 13 14 14 15 16 17 17 18 18 18 19 19 19 19 19 18 19 18 18 20 24 29 34 37 42 42 42 42 40 38 35 34 31 29 25 22 20 18 18 18 16 16 17 18 18 19 20 20 18 21 22 21 20 22 29 35 53 66 80 87 88 82 68 56 39 33 26 24 30 40 50 56 66 67 67 65 62 57 52 48 47 48 49 52 55 57 59 60 58 56 52 50 50 52 55 57 58 55 50 45 43 44 46 48 56 58 61 61 58 56 55 55 57 57 58 58 57 55 52 50 48 40 36 37 37 33 32 35 37 39 44 49 53 52 48 44 37 33 28 26 27 30 32 33 33 30 27 25 29 35 43 48 57 55 51 44 35 27 22 20 25 33 41 43 44 42 35 27 25 25 26 29 32 34 32 31 26 25 23 25 31 41 51 58 68 72 77 79 76 69 60 54 38 32 25 22 25 31 38 42 49 49 46 40 34 29 28 28 29 32 35 35 32 31 34 37 40 45 47 46 44 43 38 32 29 26 23 24 28 33 36 38 36 34 31 28 31 43 59 71 84 91 91 80 70 66 65 63 69 76 75 64 49 40 35 32 41 49 60 67 67 60 52 46 45 45 46 50 57 62 66 67 68 65 63 62 63 63 62 61 58 56 53 50 48 47 46 46 48 49 50 51 52 54 54 55 57 57 56 55 52 47 43 41 37 36 35 34 32 31 30 29 29 30 31 32 31 29 27 25 20 19 19 20 21 22 24 25 23 24 25 25 24 24 25 27 26 26 26 24 22 20 18 17 16 17 18 19 19 19 19 19 19 19 18 19 20 22 25 26 26 25 23 21 18 16 14 13 14 15 17 18 19 19 19 19 16 15 13 12 11 11 12 13 14 15 15 16 16 15 15 14 12 12 12 11 11 11 10 10 12 12 11 10 10 10 11 11 11 11 10 10 9 8 7 7 7 7 7 8 8 9 9 9 10 10 10 10 10 10 10 10 7 7 7 7 7 7 7 7 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 7 7 7 8 9 10 12 13 15 15 16 16 16 16 15 14 12 11 11 10 10 11 12 12 12 13 13 14 15 16 16 17 18 18 18 18 18 18 18 17 19 19 20 22 25 31 35 38 43 42 41 40 37 34 32 30 29 27 24 21 19 17 17 17 16 16 17 18 18 19 20 20 16 18 20 20 20 22 28 34 50 61 73 78 77 71 59 48 34 31 27 29 36 45 54 58 66 66 64 60 55 48 42 39 37 38 40 42 44 45 47 48 43 44 45 47 50 53 57 58 58 54 48 43 40 40 41 43 50 51 52 52 50 49 50 51 53 54 55 56 55 54 52 51 50 45 43 45 45 42 40 41 38 40 43 47 50 50 47 44 40 36 31 28 28 29 30 30 30 28 27 27 29 34 40 44 45 44 40 34 27 23 21 22 30 38 46 49 48 45 37 28 24 24 26 29 34 36 36 35 32 30 28 29 33 41 49 54 61 65 69 71 69 63 56 51 38 33 26 24 26 32 38 42 48 46 43 37 31 28 28 29 32 35 38 37 35 35 39 43 49 55 59 58 56 54 47 40 35 32 29 30 33 37 40 41 38 36 33 30 34 46 63 75 87 91 90 80 70 67 68 69 78 84 84 73 58 46 37 31 39 46 57 66 67 61 51 44 40 39 40 43 50 56 61 62 67 64 60 58 56 55 53 51 51 50 48 47 46 46 46 46 48 48 48 48 49 49 49 49 51 51 51 49 47 43 40 38 37 37 36 35 34 34 33 32 30 31 32 32 31 30 28 26 23 22 21 20 20 22 25 26 25 26 27 26 25 25 27 29 31 31 32 31 28 25 21 19 20 20 20 20 20 19 18 17 16 16 16 16 18 21 23 25 25 24 22 20 18 16 14 13 13 14 15 17 17 18 18 17 15 14 13 12 11 12 14 14 15 15 16 16 16 16 15 15 12 12 12 12 11 11 11 10 11 10 10 10 10 11 11 12 11 11 10 10 9 8 8 8 7 7 7 8 8 9 9 9 10 10 10 10 10 10 10 10 7 7 7 7 7 7 7 7 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 7 7 7 8 9 10 12 13 14 14 15 15 14 14 13 12 10 10 10 9 10 10 11 12 12 12 13 13 14 15 16 16 18 17 17 16 16 16 16 16 19 19 21 23 27 31 36 38 42 41 39 36 33 30 28 26 27 25 22 19 17 16 16 16 16 16 17 18 18 19 20 20 17 18 20 20 21 23 28 32 45 54 63 65 64 59 49 39 30 29 29 33 40 48 54 57 60 59 56 51 45 37 31 28 29 30 32 34 36 39 40 41 38 40 45 50 55 58 60 61 58 53 46 39 35 34 36 37 41 42 42 40 39 39 41 43 46 48 50 51 50 49 49 50 50 49 49 52 54 52 50 48 44 43 43 44 46 45 43 41 39 36 32 30 30 30 30 29 29 29 28 29 31 35 38 41 40 38 34 28 23 21 22 24 35 43 51 53 52 48 38 29 23 23 25 30 35 39 41 40 38 37 35 34 36 40 45 49 53 56 59 61 60 56 51 48 40 35 29 27 30 35 40 42 47 45 41 35 30 29 31 34 38 41 43 42 40 41 45 49 57 63 68 68 66 62 54 45 41 38 36 36 39 43 45 46 42 40 36 32 33 44 60 71 81 82 80 71 62 60 63 67 79 87 89 81 68 56 45 37 37 43 52 59 61 55 45 37 30 29 29 33 40 47 52 54 59 56 51 48 47 45 42 40 42 42 42 43 43 44 44 45 46 46 45 45 44 43 43 43 44 44 44 43 41 38 36 34 37 37 37 36 36 36 36 35 33 33 34 35 34 33 32 32 29 26 23 20 20 23 26 28 26 27 28 27 25 25 26 28 32 33 35 35 34 30 26 24 23 23 23 22 20 19 17 16 13 13 13 14 16 19 22 23 23 22 21 19 17 16 14 14 12 13 14 15 16 17 16 16 13 13 11 11 11 12 13 15 15 15 16 17 17 16 15 15 13 13 12 12 12 11 11 11 9 9 9 9 10 11 12 13 11 11 11 10 10 9 9 8 7 7 7 8 8 9 9 9 9 9 9 9 9 9 9 9 7 7 7 7 7 7 7 7 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 7 7 7 8 9 10 12 13 13 13 13 13 13 12 11 10 9 9 8 9 9 10 11 12 12 12 13 13 14 15 16 16 18 17 16 14 14 14 15 15 19 19 21 23 26 30 33 35 37 36 34 31 28 26 24 23 25 23 20 18 16 15 15 15 16 16 17 18 18 19 20 20 19 20 21 22 23 25 28 31 38 46 52 52 51 48 40 32 29 28 30 34 41 47 50 51 48 47 44 40 34 28 23 20 22 24 26 29 32 36 38 39 42 45 52 58 62 64 64 64 56 50 42 34 30 29 30 32 34 34 33 31 29 29 32 35 37 40 42 43 41 41 43 45 50 52 56 61 64 65 61 57 51 48 44 42 41 40 38 36 36 34 31 31 32 32 32 31 30 30 30 32 33 36 38 39 39 37 34 28 24 23 26 28 38 46 53 54 52 48 39 30 23 23 25 30 37 42 44 45 43 42 40 39 39 40 42 43 45 46 49 51 51 50 47 45 42 38 33 31 33 38 41 43 46 43 39 33 30 32 36 41 49 51 54 52 50 49 52 56 63 70 75 74 72 67 58 49 44 42 40 41 44 47 49 49 46 43 38 32 31 37 50 60 70 70 67 60 52 49 54 61 78 87 93 88 78 66 53 42 37 40 45 49 50 45 36 29 24 24 24 28 35 42 46 48 46 43 39 37 36 35 33 31 34 35 37 38 40 41 42 42 43 43 42 40 39 38 37 36 38 38 37 36 35 33 32 31 35 36 36 36 36 37 37 37 36 37 38 39 39 40 40 40 35 31 26 22 21 24 28 31 30 32 32 30 27 25 25 25 28 30 33 35 36 34 31 30 26 26 25 24 21 19 17 15 12 12 12 13 14 17 19 21 21 21 20 18 17 16 15 14 12 13 14 15 16 16 16 16 12 12 10 10 10 11 13 14 15 16 17 17 17 17 16 15 13 13 13 12 12 12 11 11 9 9 9 9 9 10 11 12 11 11 11 10 10 10 10 9 7 7 7 8 8 9 9 9 9 9 9 9 9 9 9 9 7 7 7 7 7 7 7 7 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 6 6 6 6 6 6 6 6 5 5 5 5 5 5 5 5 7 7 7 8 9 10 12 13 12 12 12 12 11 10 9 8 8 8 7 8 8 10 11 11 12 13 13 14 15 16 16 17 18 17 15 13 12 12 13 14 18 19 20 22 24 27 29 31 31 30 28 26 24 23 22 22 23 21 18 16 14 13 14 14 16 16 17 18 18 19 20 20 21 21 22 22 23 25 27 28 31 37 41 40 40 39 35 28 30 30 31 34 38 41 41 41 36 35 33 31 28 25 23 21 20 22 24 28 31 35 38 39 48 52 58 63 66 67 66 64 53 47 38 30 25 24 26 28 29 30 29 26 24 23 25 27 29 33 35 35 33 32 35 39 48 55 62 68 74 76 72 66 56 51 44 39 36 35 34 33 33 32 31 32 34 34 33 32 31 31 31 32 34 35 37 38 39 37 35 31 27 27 30 32 40 47 52 52 50 47 39 31 24 24 26 31 38 44 47 48 46 45 44 42 41 39 39 39 37 39 41 43 44 44 44 44 42 39 35 34 36 39 41 42 43 40 35 31 29 34 41 47 59 62 65 63 59 57 58 60 65 71 76 75 72 67 58 49 43 42 41 42 45 49 50 50 48 45 39 32 28 30 39 46 60 58 56 51 44 41 46 55 74 84 93 92 84 73 58 46 40 38 38 39 40 38 31 25 22 21 22 25 30 34 36 36 34 32 29 27 27 27 25 24 28 29 32 34 37 38 39 39 40 39 38 36 35 33 32 31 33 32 32 31 30 30 29 29 32 33 34 34 35 36 37 37 38 39 40 42 44 46 47 48 42 37 29 24 22 26 31 35 39 41 42 39 34 29 25 24 24 26 29 32 34 34 34 33 28 28 27 25 22 20 17 16 13 12 12 12 13 15 17 19 19 19 18 17 16 15 15 14 12 13 14 15 16 16 16 16 14 13 11 10 10 11 12 13 16 16 17 17 17 17 16 16 14 13 13 13 12 12 12 12 10 9 9 8 9 9 10 11 11 11 11 11 11 10 10 10 7 7 7 8 8 9 9 9 8 8 8 8 8 8 8 8 7 7 7 7 7 7 7 7 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 7 7 7 8 9 10 12 13 11 11 11 11 10 9 7 6 7 7 7 7 8 9 10 11 13 14 14 15 16 17 17 18 18 16 14 12 11 11 12 13 17 18 19 20 22 24 25 26 25 24 22 21 20 20 21 21 21 20 17 15 13 13 13 13 16 16 17 18 18 19 20 20 22 21 21 21 23 23 23 23 24 29 32 32 32 34 32 27 33 32 31 32 33 33 32 30 26 27 27 28 28 28 28 28 26 27 30 32 36 38 41 42 50 54 59 63 66 65 64 62 51 45 35 27 22 21 24 26 29 29 29 26 23 21 22 23 24 28 31 30 26 26 30 34 42 52 62 69 77 81 77 69 58 52 43 36 34 33 34 34 33 32 32 33 35 35 33 31 31 31 30 31 32 33 35 36 35 35 34 31 30 30 33 36 39 45 49 48 47 45 39 32 25 25 27 32 39 45 49 50 47 47 46 44 42 39 36 35 32 33 35 37 39 40 42 43 41 38 34 33 35 38 40 40 39 36 31 27 28 34 44 52 63 67 70 68 62 57 55 56 60 66 69 67 64 60 51 43 39 38 37 39 43 47 48 48 47 45 40 32 26 26 31 37 51 48 46 44 38 33 39 49 63 76 88 93 90 81 66 53 43 38 33 32 34 35 33 30 27 27 27 28 30 30 28 26 28 26 23 22 22 21 20 18 23 25 28 31 34 36 36 36 36 36 35 33 32 30 29 28 29 29 28 28 27 28 28 28 29 30 31 32 34 35 36 37 39 39 41 44 47 50 52 54 47 41 33 26 24 27 33 38 51 53 54 52 45 36 29 25 21 22 25 27 30 32 32 33 29 29 27 26 23 21 18 17 14 14 13 12 13 14 16 17 18 18 17 17 16 15 15 15 13 13 15 16 17 17 17 17 17 16 14 13 12 12 13 14 16 17 17 18 18 17 17 16 14 14 13 13 13 12 12 12 11 10 9 8 8 8 9 9 11 11 11 11 11 11 11 11 7 7 7 8 8 9 9 9 8 8 8 8 8 8 8 8 7 7 7 7 7 7 7 7 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 5 5 5 6 6 6 6 6 6 6 6 4 4 4 4 4 4 4 4 7 7 7 8 9 10 12 13 10 11 11 10 9 8 6 6 6 6 6 7 8 9 10 11 14 14 15 16 17 17 18 18 18 16 13 11 10 10 12 13 17 17 18 19 20 21 22 22 21 20 19 18 18 19 20 21 20 19 16 14 12 12 12 13 16 16 17 18 18 19 20 20 22 21 20 20 21 22 21 20 21 25 28 27 28 31 31 27 35 33 31 30 30 28 25 23 22 23 25 27 30 32 34 35 34 35 37 39 41 43 44 45 49 52 57 61 63 63 61 59 49 43 33 25 20 20 22 25 30 30 30 28 24 21 21 22 22 26 29 27 23 23 27 31 35 46 58 66 75 80 76 67 57 51 41 35 32 33 34 35 34 33 33 34 35 34 32 29 30 30 29 29 30 31 34 35 30 31 32 31 31 32 35 37 39 44 47 46 44 43 38 32 26 26 27 32 39 46 50 51 48 48 47 45 42 39 35 33 30 30 32 33 36 39 41 42 39 36 33 32 34 37 38 38 36 33 28 25 26 34 45 53 61 65 69 67 60 53 50 49 53 59 61 59 55 51 43 35 35 34 34 37 41 45 46 46 46 45 40 33 26 24 28 33 44 41 40 39 33 27 33 44 52 67 83 92 93 87 74 62 46 39 31 29 33 36 37 35 39 39 38 38 37 35 30 26 26 24 21 19 19 19 17 15 21 23 26 30 32 34 35 35 34 34 33 31 30 28 27 27 27 27 26 26 26 26 27 28 27 28 29 31 33 34 35 36 38 39 41 44 48 52 55 57 50 44 34 27 25 28 35 40 59 62 64 61 52 42 33 28 20 21 22 24 27 29 30 31 29 29 28 26 24 21 19 17 16 15 13 12 12 13 15 16 17 17 17 16 16 15 15 15 13 14 15 16 17 18 18 17 20 19 17 15 14 14 15 15 16 17 17 18 18 17 17 16 14 14 14 13 13 12 12 12 11 11 10 8 8 8 8 8 11 11 11 11 11 11 11 11 7 7 7 8 8 9 9 9 8 8 8 8 8 8 8 8 7 7 7 7 7 7 7 7 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 4 4 4 5 5 6 6 6 6 7 8 9 10 11 11 11 8 8 8 7 7 6 6 6 8 8 9 10 10 11 12 12 13 13 13 14 14 15 15 15 14 13 12 11 11 11 11 12 14 14 15 15 15 14 14 13 12 14 16 19 20 21 21 20 21 19 16 13 12 12 13 14 15 17 19 19 18 18 19 20 21 21 20 20 20 21 21 22 20 22 25 28 30 31 31 31 30 29 28 26 25 24 23 23 23 25 30 35 39 42 44 45 45 45 44 43 42 40 40 39 41 44 48 52 54 55 55 55 49 43 33 25 20 20 23 25 33 34 34 30 24 20 21 23 23 26 28 28 26 25 24 25 31 39 51 62 68 69 66 63 48 44 38 34 33 32 32 31 35 35 36 38 40 39 36 33 31 30 28 27 27 28 29 30 26 28 29 30 30 31 33 36 38 39 40 41 39 36 34 32 24 27 32 38 42 44 45 45 44 43 40 38 35 32 30 29 26 28 31 33 35 36 36 36 34 32 29 29 32 34 36 36 33 28 23 20 23 30 39 46 57 60 61 57 50 43 40 40 41 46 49 47 45 43 38 31 26 27 28 31 34 38 41 42 45 43 39 33 28 25 25 26 35 40 45 43 37 31 30 31 50 59 74 87 91 85 73 63 51 41 32 31 34 40 49 58 55 56 56 53 47 38 30 25 21 20 18 17 16 16 17 18 17 19 23 27 30 31 30 30 29 30 30 30 30 29 28 27 27 26 25 24 24 24 26 27 29 29 30 31 33 34 35 35 37 37 39 41 44 48 50 52 48 43 35 27 24 28 35 42 58 67 73 71 64 55 43 33 21 19 18 18 20 23 24 23 27 27 27 27 26 24 22 20 19 17 15 12 11 11 12 13 15 15 16 17 17 17 16 16 18 17 17 17 18 20 22 24 22 22 21 19 18 16 15 15 15 15 16 17 17 16 16 15 14 13 13 12 12 13 14 14 11 11 11 10 10 9 9 9 10 10 10 10 10 10 10 10 10 11 11 11 11 10 9 8 7 7 7 7 7 7 7 7 7 8 8 9 9 8 8 7 5 6 6 6 6 5 4 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 4 4 4 5 5 6 6 6 6 7 8 9 10 10 10 10 8 8 8 7 7 6 6 6 8 8 9 10 10 11 12 12 13 13 13 14 14 14 15 15 14 13 12 11 11 11 11 12 13 13 14 14 14 13 13 13 12 14 17 19 21 22 22 22 21 19 16 13 12 12 13 14 17 18 20 20 19 18 19 20 20 21 21 21 22 22 23 23 22 23 25 27 28 29 29 29 29 28 26 25 24 24 25 25 31 33 37 41 45 48 50 51 49 48 46 44 41 39 37 36 37 39 43 48 51 53 53 53 49 43 33 25 21 22 26 29 37 39 39 35 29 24 24 25 25 28 31 32 30 27 25 25 30 37 47 56 61 61 57 54 45 41 37 35 35 36 36 35 39 38 39 41 42 41 38 35 30 29 27 26 26 27 29 30 26 27 28 27 26 27 30 32 35 36 38 38 37 35 33 31 25 28 32 36 39 42 42 43 40 39 37 34 32 32 31 31 30 31 34 36 36 36 35 34 31 29 28 29 32 35 37 37 34 29 23 20 21 28 36 42 51 53 55 51 44 38 36 37 37 43 47 47 45 43 37 29 26 26 27 28 30 33 36 38 43 42 40 35 30 28 28 29 37 42 47 46 40 34 32 32 39 49 64 79 87 85 76 68 55 45 37 36 41 48 59 68 73 72 69 62 53 41 31 24 21 20 18 17 17 17 18 18 17 20 24 28 30 31 31 30 29 29 30 30 29 28 27 27 26 26 25 24 24 25 27 28 28 28 29 31 33 34 36 37 38 38 38 39 41 44 46 48 47 43 35 28 24 27 34 40 57 67 75 74 68 59 47 37 25 22 19 18 19 20 20 20 23 24 26 27 27 26 24 23 21 19 16 14 12 12 13 13 16 16 17 18 18 17 17 16 17 16 16 16 18 20 23 24 24 24 24 23 21 19 17 16 16 16 17 17 17 16 15 15 13 13 12 12 12 13 13 14 11 11 11 10 10 9 9 9 10 10 10 10 10 10 10 10 10 10 11 11 10 10 9 8 7 7 7 7 7 7 7 7 7 8 8 9 9 8 8 7 5 6 6 6 6 5 4 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 4 4 4 5 5 6 6 6 6 7 8 9 10 10 10 10 8 8 7 7 7 7 6 6 8 8 9 10 10 11 12 12 13 13 13 13 14 14 14 15 13 13 12 11 11 11 11 11 11 12 12 12 12 12 12 12 13 14 17 20 23 24 24 24 20 18 16 13 12 12 14 15 18 19 20 20 18 17 18 19 20 21 22 24 25 25 26 26 25 25 26 26 26 26 26 26 26 25 24 24 25 26 28 29 39 40 42 46 49 52 54 55 52 50 47 43 39 35 32 31 29 32 37 42 47 51 53 54 51 44 35 26 23 25 30 34 42 44 44 39 32 27 25 26 28 31 35 37 34 29 26 24 28 33 41 48 51 50 46 44 41 39 38 39 41 43 43 42 44 43 43 44 45 44 41 39 30 29 26 25 25 27 29 31 31 31 30 28 26 25 27 29 31 32 33 34 34 33 32 31 27 28 31 33 36 37 38 38 35 33 31 29 30 32 34 36 37 39 40 40 39 37 34 33 28 27 27 30 34 37 39 39 36 31 24 19 19 24 31 36 42 45 46 43 37 32 32 33 34 42 48 50 49 46 38 29 28 27 25 25 26 28 31 33 38 39 39 37 33 31 31 32 38 44 50 51 46 39 35 33 32 40 55 69 79 80 74 69 56 47 40 42 48 57 69 80 88 85 79 70 57 44 32 25 21 20 19 18 18 18 18 19 19 21 25 28 31 32 31 31 28 28 29 29 29 28 27 26 25 24 24 24 25 26 27 28 27 27 28 30 32 35 37 39 39 38 36 35 35 37 39 41 44 41 34 28 24 26 31 35 52 63 74 76 72 65 53 43 33 28 23 19 17 17 17 16 18 20 23 27 28 29 28 27 24 22 20 17 15 14 15 15 17 17 18 18 18 18 17 17 15 15 15 16 17 20 23 24 27 28 28 28 27 24 21 19 17 17 17 17 17 16 14 14 13 13 12 11 11 12 12 13 11 11 10 10 10 10 9 9 10 10 10 10 10 10 10 10 10 10 11 11 10 9 8 8 7 7 7 7 7 7 7 7 7 7 8 8 8 8 7 7 5 6 6 6 6 5 4 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 6 7 8 9 9 9 9 9 7 7 7 7 7 7 7 7 8 8 9 10 10 11 12 12 12 12 13 13 13 14 14 14 13 12 11 11 10 10 11 11 10 10 10 10 10 10 11 12 13 15 18 21 24 25 25 25 20 18 15 13 12 13 14 15 18 19 19 18 16 15 17 18 21 23 25 28 29 30 29 29 28 27 26 24 23 23 23 23 21 21 22 24 27 31 34 36 41 42 42 44 47 50 52 54 52 50 46 41 35 30 26 24 22 25 31 38 46 52 56 58 55 48 38 29 26 28 34 38 44 46 45 40 32 26 25 25 30 35 40 41 37 31 25 22 25 29 35 40 42 42 39 37 40 40 41 45 49 52 52 51 49 48 47 47 48 47 44 42 32 30 27 25 26 29 34 36 39 39 37 33 29 26 27 28 26 27 29 30 31 31 31 30 28 29 29 30 31 32 33 34 31 29 27 26 29 34 39 43 48 48 49 47 44 40 35 32 28 28 29 33 38 42 43 42 38 33 25 19 18 21 27 31 36 38 39 37 32 29 31 33 38 47 55 58 57 53 43 33 30 29 26 24 24 26 28 29 33 35 36 36 33 32 32 32 40 46 53 55 51 45 38 35 33 39 50 61 69 70 66 62 55 46 41 44 52 62 74 84 90 86 79 68 56 42 32 25 20 20 20 19 19 19 19 20 20 23 26 30 32 33 32 31 28 28 29 29 28 27 26 26 22 22 23 23 24 25 25 26 25 25 26 28 31 35 38 40 41 38 35 32 30 31 32 33 38 36 32 26 23 23 26 29 42 54 67 72 71 67 59 50 41 35 28 22 19 17 16 15 14 16 21 26 29 31 32 32 28 26 24 21 19 17 17 17 17 17 18 18 18 17 16 16 14 14 14 15 17 20 22 24 29 30 32 33 31 28 24 22 20 19 19 19 17 16 14 13 13 12 11 11 10 11 11 11 10 10 10 10 10 10 10 10 9 9 9 9 9 9 9 9 9 10 10 10 10 9 8 7 6 6 6 6 6 6 6 6 6 7 8 8 8 8 7 6 5 6 6 6 6 5 4 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 6 7 8 8 9 9 8 8 7 7 7 7 7 7 7 7 8 8 9 10 10 11 12 12 12 12 12 13 13 13 14 14 13 12 11 10 10 10 10 11 9 9 8 8 9 10 11 12 14 16 19 22 24 25 25 25 19 18 15 13 12 13 15 16 16 17 17 16 14 14 16 18 24 27 30 33 35 34 33 32 30 28 25 22 20 20 20 21 18 20 23 27 32 37 41 43 41 40 40 40 42 44 47 49 48 46 42 37 31 26 22 19 17 21 28 37 46 54 60 63 59 52 42 34 30 32 37 40 47 48 46 40 32 27 26 28 34 39 43 44 40 32 26 22 23 26 30 35 37 38 38 37 42 43 47 52 57 60 59 57 53 51 49 49 49 48 45 43 34 32 29 27 29 34 40 44 48 47 45 40 33 28 26 26 24 25 26 28 29 30 30 31 30 29 28 27 27 28 30 31 29 27 26 27 32 39 47 51 59 59 59 56 52 45 39 35 32 32 35 39 44 47 47 46 39 34 27 21 19 21 26 29 34 36 37 34 31 31 34 38 47 56 65 68 66 61 49 39 32 31 28 27 26 27 28 29 29 31 33 32 31 29 30 30 39 45 53 57 55 49 42 38 37 40 46 53 59 61 59 56 53 46 41 45 53 62 72 81 85 80 73 62 49 38 28 23 20 20 20 21 21 21 21 20 22 24 28 31 33 33 33 32 28 29 29 29 29 28 27 26 20 21 21 22 23 23 23 23 23 23 24 26 29 33 37 39 41 39 35 31 28 26 26 26 30 29 28 24 21 20 22 24 30 42 54 61 64 64 59 53 46 41 33 27 23 20 17 16 12 14 19 24 28 32 35 36 32 31 29 26 23 21 19 19 17 17 18 18 17 16 15 14 14 14 13 14 16 18 21 23 29 30 33 34 33 31 27 25 23 23 22 21 19 16 14 13 13 12 11 10 10 9 10 10 10 10 10 10 10 10 10 10 9 9 9 9 9 9 9 9 9 9 10 10 9 9 8 7 6 6 6 6 6 6 6 6 6 6 7 8 8 7 6 6 5 6 6 6 6 5 4 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 5 5 6 6 6 6 7 8 8 8 8 7 7 6 6 7 7 7 7 8 8 8 8 9 10 10 11 12 12 11 12 12 12 13 13 13 13 12 12 11 10 9 9 10 10 9 8 8 7 8 10 12 13 15 17 19 22 23 24 24 23 19 17 15 13 12 13 15 16 16 16 16 15 14 15 18 20 28 31 36 39 40 39 36 34 32 29 24 20 18 17 19 20 20 23 28 34 39 42 44 45 40 39 36 35 36 38 42 44 43 41 38 33 28 24 20 19 18 21 28 36 45 54 60 64 59 54 46 39 36 37 41 44 52 51 48 41 33 29 30 33 40 44 48 48 42 35 28 24 23 25 28 32 35 37 38 38 45 47 52 58 63 64 62 59 54 52 49 48 48 46 44 42 35 33 30 29 32 39 47 53 56 56 54 49 40 32 27 25 24 25 26 27 28 30 31 31 31 29 27 25 25 26 28 29 29 29 29 32 38 46 55 60 70 70 69 66 60 52 44 39 37 38 40 45 49 51 49 47 40 35 29 23 21 23 27 30 34 36 37 35 33 34 39 44 55 64 72 73 70 63 51 40 32 31 31 30 29 30 30 30 28 29 30 29 27 26 27 28 38 43 50 56 56 52 46 41 38 39 41 46 51 54 54 53 52 45 42 46 52 58 65 72 75 71 63 52 41 31 23 19 19 20 21 22 22 22 22 21 24 26 29 32 34 34 33 33 29 30 30 30 30 29 28 27 21 21 22 23 23 22 21 21 22 22 22 23 26 30 35 37 42 40 36 32 28 24 22 21 23 24 25 24 21 20 20 21 22 32 42 47 51 55 55 52 47 43 36 31 27 24 20 17 13 15 17 21 26 32 36 39 36 35 33 30 27 24 22 20 19 19 19 19 18 17 16 15 14 14 13 14 15 17 19 20 27 28 30 32 32 31 29 28 27 26 25 23 20 17 15 13 12 12 11 9 9 8 9 9 9 9 10 10 10 10 11 11 8 8 8 8 8 8 8 8 9 9 9 9 9 8 7 7 5 5 5 5 5 5 5 5 6 6 7 7 7 7 6 6 5 6 6 6 6 5 4 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 5 5 6 6 6 6 7 8 8 8 7 7 6 6 6 6 7 7 8 8 8 8 8 9 10 10 11 12 12 11 11 12 12 12 13 13 13 12 11 10 10 9 9 10 10 10 9 8 7 8 10 13 14 16 18 20 22 22 22 22 21 18 17 14 13 12 13 15 17 16 17 17 16 16 18 21 24 33 36 41 44 45 42 38 36 32 29 23 18 16 16 18 19 25 29 35 41 44 45 44 42 37 34 31 28 28 31 35 37 38 37 34 31 28 25 22 21 22 25 30 36 44 51 57 60 56 52 47 42 41 43 46 49 52 51 46 37 30 28 31 35 48 51 53 52 46 38 31 28 26 27 28 30 33 35 36 37 47 50 55 61 65 65 61 57 53 51 48 46 45 44 42 40 35 32 29 29 34 43 52 59 67 68 67 61 52 41 33 29 26 26 27 27 28 30 31 32 32 29 26 24 23 25 28 29 31 32 34 38 45 54 62 67 79 79 78 74 67 58 49 44 41 42 45 49 52 52 49 46 40 36 30 26 24 26 30 33 35 37 37 36 35 38 44 50 58 66 73 73 68 60 47 36 29 30 31 32 33 32 31 31 30 30 29 27 24 23 25 26 36 41 47 53 56 54 48 44 40 39 38 39 43 46 48 48 48 42 40 43 47 49 52 56 57 54 47 39 32 25 21 18 19 20 22 23 23 23 22 22 25 27 30 33 35 35 34 33 31 31 31 31 31 30 29 28 24 24 25 25 24 23 21 20 21 20 20 21 23 28 32 35 41 40 38 34 29 24 20 17 19 21 24 25 23 22 21 21 21 28 34 35 38 44 47 47 44 41 37 33 30 27 22 19 16 16 17 19 24 30 37 40 39 38 36 33 30 26 23 22 21 22 22 21 20 19 18 17 16 15 14 13 14 15 17 18 24 25 27 28 30 30 30 30 30 29 28 25 22 19 16 14 12 11 10 9 8 8 8 8 9 9 9 10 10 11 11 11 8 8 8 8 8 8 8 8 8 9 9 9 9 8 7 6 5 5 5 5 5 5 5 5 5 6 6 7 7 6 6 5 5 6 6 6 6 5 4 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 5 5 6 6 6 7 7 8 8 8 7 6 6 6 6 6 7 7 8 8 8 8 8 9 10 10 11 12 12 11 11 11 12 12 13 13 13 12 11 10 9 9 9 9 10 10 9 8 7 8 10 13 15 17 18 20 21 22 21 20 19 18 17 14 13 12 14 15 17 17 18 18 18 18 20 24 28 35 39 44 47 47 44 40 36 32 28 22 17 15 15 18 19 31 35 40 45 47 45 42 39 32 29 25 22 22 25 28 31 36 35 33 31 29 26 25 24 26 28 31 36 42 48 53 56 52 50 46 44 44 47 50 53 50 48 42 33 26 24 29 34 53 55 57 54 48 40 34 31 28 28 29 30 31 33 35 36 48 51 56 62 65 64 58 54 53 50 46 44 44 42 40 38 33 31 28 28 34 44 55 61 77 78 78 72 62 50 40 35 28 27 27 28 29 30 31 32 32 30 26 23 23 25 28 30 33 34 37 42 49 58 66 71 83 83 82 78 71 62 52 47 43 44 47 50 53 52 48 44 40 37 31 27 26 29 33 36 36 37 38 37 36 40 47 53 58 66 71 70 64 56 42 31 26 28 31 33 34 34 32 31 33 32 30 26 23 22 24 26 35 39 45 51 55 54 50 46 44 41 37 36 37 40 41 41 43 37 35 39 41 40 41 43 39 37 33 29 25 22 21 20 19 20 22 23 24 24 23 22 26 28 31 34 35 35 34 33 31 32 32 32 32 31 30 29 27 27 28 27 26 24 22 20 21 20 19 19 22 26 30 33 41 41 39 36 31 25 19 16 17 21 25 26 25 24 22 22 23 28 30 29 31 37 42 43 40 38 36 34 32 28 23 19 19 17 17 18 22 29 37 41 41 40 38 35 31 28 24 22 24 24 24 24 23 21 20 19 16 16 14 13 13 14 16 17 22 23 24 26 28 29 31 32 32 31 29 27 23 20 17 15 12 11 10 9 8 7 7 7 9 9 9 10 10 11 11 11 8 8 8 8 8 8 8 8 8 9 9 9 9 8 7 6 5 5 5 5 5 5 5 5 5 6 6 7 7 6 6 5 5 6 6 6 6 5 4 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 4 5 6 6 7 8 5 5 5 5 5 5 5 5 6 6 6 7 7 8 8 8 8 8 8 8 8 8 8 8 9 10 12 13 14 14 13 12 12 12 12 11 11 10 10 10 7 7 7 8 10 12 14 15 17 18 20 22 21 20 18 16 15 15 15 15 15 15 15 15 20 19 18 18 20 24 29 31 40 43 47 50 50 46 41 37 29 25 19 15 14 17 22 26 37 42 48 52 52 48 42 38 27 23 18 16 19 24 28 31 35 35 35 34 33 32 31 30 30 31 32 35 38 42 45 47 48 47 45 47 50 53 54 54 52 43 33 27 23 24 33 43 53 60 64 58 50 44 38 33 33 33 32 31 31 31 32 32 42 47 53 57 57 55 53 52 49 45 42 40 40 39 35 32 27 26 24 24 30 41 55 64 82 83 83 77 66 52 41 35 30 29 29 30 31 32 33 34 30 26 22 18 18 22 26 29 37 39 42 45 50 57 65 70 78 80 80 76 67 58 50 46 40 43 46 49 49 45 41 38 32 30 29 30 33 36 37 38 37 37 37 37 39 41 44 45 60 62 64 63 57 48 38 31 25 24 26 31 36 39 38 36 38 39 39 34 28 24 25 27 32 35 40 46 50 50 47 45 44 43 41 40 38 37 37 36 39 38 37 37 37 35 31 28 28 27 26 25 23 22 21 20 23 22 21 20 20 21 23 24 28 30 33 36 37 38 37 36 33 33 34 35 36 36 35 35 34 34 33 31 29 26 22 20 21 21 21 22 24 27 30 31 34 36 38 38 35 28 21 17 17 18 20 22 24 26 27 28 29 28 27 26 26 28 29 30 32 32 31 29 27 25 23 22 18 18 18 18 20 25 32 37 40 40 39 38 35 32 29 27 25 25 25 25 24 23 22 21 19 18 17 16 14 14 14 14 17 18 21 25 28 30 32 33 32 32 31 29 26 22 19 16 11 11 10 8 8 8 8 8 10 10 10 11 11 12 12 13 10 10 10 9 9 8 8 8 9 9 9 8 8 7 7 7 7 7 7 6 6 5 5 5 6 6 6 6 6 6 6 6 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 4 4 5 6 7 7 5 5 5 5 5 5 5 5 6 6 6 7 7 7 8 8 8 8 8 8 8 8 8 8 9 10 12 13 13 13 12 12 12 12 12 11 11 10 10 10 7 7 8 9 10 12 14 15 18 19 21 21 21 19 17 15 14 14 15 15 16 16 16 17 22 21 21 22 25 29 34 36 42 44 47 49 48 43 38 35 27 23 18 15 15 19 25 29 40 45 51 54 54 48 41 36 26 22 17 16 19 23 28 30 34 34 35 35 35 33 31 29 29 30 31 32 34 37 39 40 43 43 44 47 52 55 56 56 50 41 31 25 23 25 36 47 58 65 68 62 54 47 41 35 35 34 33 32 31 31 31 31 38 42 47 50 50 49 49 49 46 43 39 37 37 35 32 29 27 25 23 23 28 38 51 61 78 80 79 74 63 51 41 35 29 29 29 29 30 32 33 34 30 26 21 18 18 22 27 31 39 40 42 44 47 53 60 65 70 71 70 66 58 50 43 40 37 39 43 45 44 41 37 34 29 29 29 31 34 37 37 36 34 33 32 32 34 37 40 42 54 56 58 57 52 44 35 29 24 24 26 30 36 39 40 38 43 45 45 41 35 30 29 30 33 36 39 44 46 47 45 43 43 43 42 41 40 39 38 37 39 38 36 35 35 32 28 25 23 23 23 23 23 23 23 24 24 23 21 20 20 21 22 23 27 29 32 35 36 37 36 35 33 34 35 37 38 38 38 38 37 37 35 33 30 26 23 21 21 22 23 24 26 27 28 29 33 35 37 37 35 29 23 20 18 19 21 23 25 27 29 30 30 29 27 25 25 25 26 27 28 28 27 26 25 23 22 21 17 18 18 17 19 23 29 34 38 38 38 37 35 32 29 27 26 26 26 26 25 24 23 23 21 20 18 17 15 14 14 14 14 15 18 22 25 28 29 30 33 32 32 29 26 22 19 16 12 11 10 9 8 8 8 8 9 9 10 10 11 11 11 12 10 10 9 9 9 8 8 8 9 9 8 8 8 7 7 7 7 7 6 6 6 5 5 5 6 6 6 6 6 6 6 6 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 4 4 5 6 6 6 5 5 5 5 5 5 5 5 6 6 6 6 7 7 7 8 8 8 8 8 8 8 8 8 9 10 11 12 12 12 12 11 11 11 11 11 10 10 10 10 7 8 8 9 11 13 15 16 20 20 21 21 20 18 16 14 13 13 14 15 16 17 18 19 22 22 22 24 28 33 37 40 44 45 47 47 44 39 33 30 23 20 17 15 17 23 29 33 45 49 55 58 55 48 38 32 24 20 17 16 19 23 26 28 32 34 36 37 36 34 31 29 28 28 28 28 29 31 32 33 37 39 43 49 55 58 59 58 46 37 27 22 22 27 41 53 65 72 74 68 58 51 44 38 37 36 34 32 31 30 29 29 34 37 40 41 42 42 43 45 43 40 36 34 32 30 28 25 26 24 22 21 25 34 46 54 70 72 72 67 58 48 39 35 27 27 28 28 30 31 33 34 29 26 21 18 18 23 29 33 39 40 41 41 42 46 51 55 59 59 57 53 46 40 36 35 33 35 37 38 37 34 30 28 26 26 29 32 36 38 36 34 29 28 26 25 27 31 35 38 46 48 50 50 46 38 31 26 24 24 25 29 35 39 42 42 48 52 53 50 43 36 33 33 35 36 38 39 40 41 41 41 43 44 45 46 46 44 42 40 42 40 37 35 33 30 25 22 19 19 20 21 23 25 27 28 26 25 23 22 21 21 22 23 26 28 30 33 34 35 35 34 32 34 36 39 41 43 43 44 43 42 39 35 31 27 24 22 22 24 26 28 29 29 28 27 31 33 35 35 34 31 27 24 20 21 23 25 28 30 32 33 33 31 27 24 22 22 23 24 24 23 23 22 21 20 19 19 16 17 17 16 16 20 25 29 35 36 37 37 36 34 31 29 27 27 27 27 26 26 26 25 24 22 20 18 16 15 14 14 11 12 15 18 21 24 26 27 33 33 32 30 26 22 19 16 13 12 11 9 9 8 8 8 8 8 9 9 9 10 10 10 10 9 9 9 8 8 8 8 9 8 8 8 7 7 7 7 7 6 6 6 5 5 5 5 6 6 6 6 6 6 6 6 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 4 4 5 5 6 5 5 5 5 5 5 5 5 5 5 6 6 6 7 7 7 7 7 8 8 8 8 9 9 10 10 10 11 11 11 11 10 11 10 10 10 10 10 10 10 8 8 9 10 12 14 15 17 21 21 21 20 19 17 15 13 12 13 14 16 17 19 20 21 19 20 21 24 28 33 38 41 44 45 44 42 39 33 28 24 18 17 15 15 19 25 32 37 48 52 57 59 55 46 35 28 22 19 16 16 19 23 25 26 31 33 36 38 37 35 31 28 26 26 26 26 27 28 30 30 37 40 45 53 59 61 59 57 42 33 24 20 22 30 45 60 72 78 80 73 63 55 47 41 39 38 36 33 31 29 28 28 31 33 34 35 35 37 40 43 42 40 36 32 29 27 25 24 26 25 23 22 24 31 40 47 59 61 61 58 50 42 36 33 26 26 26 27 28 30 32 33 29 26 21 19 20 25 31 36 39 39 39 38 36 37 40 43 48 48 45 41 35 32 31 32 30 31 31 31 29 27 23 22 22 24 28 34 38 38 35 32 26 24 21 20 22 27 32 36 40 41 43 43 40 34 28 24 23 23 24 28 33 39 44 47 54 58 61 59 51 42 36 34 36 37 37 36 35 35 37 38 45 48 52 55 55 53 49 47 47 44 40 36 33 29 24 21 19 19 20 21 24 27 30 31 31 30 27 25 23 23 23 23 25 26 28 30 32 33 33 33 32 34 37 41 44 47 49 50 49 47 42 36 31 27 24 23 25 28 32 34 35 32 29 27 29 30 31 32 33 32 30 29 24 25 27 29 31 34 35 36 36 34 29 25 22 21 22 22 21 20 19 18 17 17 17 16 15 16 15 14 14 16 20 24 32 34 36 38 38 37 35 33 29 29 28 27 27 27 27 27 26 24 22 19 17 15 14 14 10 11 13 15 18 21 24 25 32 32 31 29 26 22 19 16 14 13 12 10 9 9 9 9 8 8 8 8 8 8 8 8 9 9 9 8 8 8 7 7 8 8 8 7 7 7 6 6 6 6 6 5 5 5 4 4 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 4 4 4 4 5 5 5 5 5 5 5 5 5 5 5 5 6 6 6 7 7 7 7 7 8 8 9 9 9 10 10 10 9 9 9 9 10 9 10 10 10 10 10 10 10 9 9 10 11 12 14 16 17 21 21 20 19 18 16 14 14 12 13 15 16 18 20 22 22 19 20 22 25 29 34 38 40 42 41 40 37 33 27 23 20 15 14 13 15 20 27 34 38 48 51 55 56 52 43 32 25 21 19 17 18 20 23 25 25 29 32 35 37 37 34 30 28 24 24 25 26 28 30 32 34 41 44 50 56 61 61 57 54 39 31 23 21 23 33 49 64 75 81 83 75 64 56 48 42 39 38 36 33 31 30 29 29 31 31 32 32 33 36 40 44 43 41 37 32 28 25 24 24 26 27 27 26 26 30 35 39 47 48 49 47 42 36 33 31 26 26 26 26 27 28 29 30 28 26 23 22 24 29 34 38 37 38 37 34 32 31 32 34 38 37 35 31 27 26 27 29 30 30 29 27 25 22 19 18 21 23 28 34 38 37 33 29 25 22 20 19 21 26 32 36 37 38 39 39 37 33 28 25 22 23 24 26 32 39 47 52 63 67 71 68 59 49 41 38 37 38 37 34 31 31 35 38 49 54 60 66 67 64 59 56 53 49 44 39 35 31 26 22 23 22 22 23 25 28 31 33 37 35 32 28 26 24 24 24 23 24 26 28 29 31 31 32 33 35 38 43 47 51 53 55 53 49 43 36 30 26 24 23 28 32 36 40 40 37 32 29 27 27 28 29 30 31 32 33 29 30 31 33 35 37 38 39 39 36 31 26 23 22 23 24 22 21 19 17 15 14 14 14 14 14 14 13 12 14 17 20 29 32 36 40 41 40 39 37 32 31 29 28 27 27 27 28 26 25 22 20 17 16 15 14 12 12 13 14 17 19 22 24 29 29 29 27 25 22 19 17 16 15 13 11 10 9 9 9 8 8 8 8 8 7 7 7 9 9 8 8 8 7 7 7 8 8 7 7 7 6 6 6 6 6 5 5 5 4 4 4 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 4 4 4 5 5 5 5 5 5 5 5 4 5 5 5 6 6 6 6 6 6 7 8 8 9 10 10 11 10 9 8 8 8 8 9 9 9 9 9 10 10 10 10 10 10 10 12 13 15 17 18 20 20 19 18 17 16 15 15 14 14 16 17 19 21 22 23 23 23 25 27 30 34 37 38 38 36 34 31 27 22 19 17 13 12 12 15 19 26 33 37 45 48 51 51 46 38 29 23 20 19 18 19 22 24 25 24 28 30 33 34 34 32 30 28 24 24 25 27 30 33 36 37 45 47 52 58 61 59 54 50 38 31 24 23 26 35 51 66 74 81 82 74 64 55 47 41 37 36 35 33 32 32 32 32 31 32 33 33 34 37 42 45 45 43 39 33 27 24 24 25 28 30 32 33 32 31 32 34 37 38 40 38 35 32 31 31 27 27 26 25 25 26 27 27 27 26 25 26 29 33 37 40 37 37 37 34 30 28 28 30 30 30 28 26 23 24 26 29 32 31 29 26 23 20 18 17 21 24 29 34 37 36 31 27 23 22 20 20 22 27 32 35 36 37 37 37 35 32 28 26 22 22 23 25 30 39 50 57 71 76 79 75 65 54 46 43 38 39 38 35 31 30 34 38 53 59 68 76 78 74 68 63 58 53 47 41 37 32 28 24 25 24 23 24 26 29 33 35 40 38 34 30 27 25 24 23 22 23 24 25 27 28 30 30 33 35 39 44 49 53 56 57 54 50 43 35 29 25 23 23 30 33 38 42 42 39 34 31 25 24 24 25 27 30 33 34 34 35 36 37 38 39 40 40 39 35 30 25 23 23 25 26 27 25 21 18 15 13 12 12 12 13 13 12 12 13 16 18 26 29 34 39 42 42 41 40 34 33 30 28 26 26 26 26 25 23 21 19 17 16 15 15 14 14 13 13 15 17 19 21 25 25 25 25 24 21 19 18 17 16 14 12 11 10 9 9 9 9 8 8 8 7 7 7 8 8 8 8 7 7 7 6 7 7 7 7 6 6 6 5 5 5 5 5 4 4 4 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 5 5 5 5 5 5 5 5 4 4 5 5 5 6 6 6 6 6 7 8 8 9 10 10 11 10 8 7 7 7 8 8 8 8 8 9 9 10 10 10 10 11 11 12 14 16 18 19 19 19 18 17 16 16 16 16 15 16 17 18 19 21 22 22 24 24 25 27 29 31 32 33 32 31 28 25 22 19 17 16 12 12 12 14 18 24 30 34 41 43 45 44 41 34 27 22 20 19 19 21 24 26 25 24 28 29 30 31 32 31 29 28 25 26 27 29 31 34 37 38 46 47 51 56 58 56 51 47 39 32 26 26 29 37 52 66 71 78 80 72 62 53 45 39 34 34 33 33 33 34 35 35 31 33 34 34 35 38 43 46 46 44 40 33 26 23 23 25 30 34 38 40 38 34 31 30 31 33 34 34 32 31 31 32 28 27 26 25 24 24 24 24 26 27 28 31 34 37 40 41 38 39 38 36 32 30 30 30 29 30 30 28 27 28 31 34 36 34 30 27 23 20 19 18 23 25 29 33 36 34 29 25 22 21 21 22 24 28 32 34 37 37 36 35 33 30 28 26 21 22 22 24 29 39 52 61 74 78 80 76 65 53 45 42 37 40 40 37 32 31 35 39 55 62 73 82 85 81 74 68 59 55 48 42 38 33 29 26 23 23 22 23 25 30 34 37 41 39 34 30 26 23 21 21 21 21 22 23 25 27 28 29 33 36 40 45 50 54 57 59 54 49 41 33 26 23 22 23 29 33 37 41 42 39 35 32 24 23 21 22 24 28 32 35 39 39 39 40 40 41 41 41 36 33 28 23 22 23 26 28 33 30 25 20 15 13 11 11 11 12 13 12 12 13 15 18 21 25 31 38 41 42 41 40 37 34 31 27 25 24 24 24 23 22 20 18 17 16 16 16 16 14 13 12 12 14 16 17 20 21 22 23 22 21 19 18 18 17 15 13 11 10 9 9 10 10 9 9 8 8 8 7 8 8 8 7 7 7 6 6 7 7 7 6 6 6 5 5 5 5 5 4 4 4 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 5 5 5 5 5 5 5 5 4 4 4 5 5 6 6 6 6 6 7 8 8 9 10 10 11 10 8 7 6 6 7 8 8 8 8 9 9 10 10 10 11 11 11 12 14 16 18 19 18 18 17 16 16 16 17 17 16 17 17 18 20 21 22 22 22 22 23 24 25 26 27 27 29 28 25 22 19 17 16 15 12 12 12 14 17 23 29 32 39 40 41 40 37 31 26 22 20 20 20 22 25 27 26 24 28 28 29 29 30 29 29 28 27 27 28 30 31 34 36 37 44 46 49 53 56 54 50 46 39 33 28 28 31 38 52 65 69 76 77 70 60 52 44 38 32 32 32 33 34 35 37 37 31 33 34 35 36 39 43 47 46 44 40 33 25 21 23 25 32 36 42 44 41 36 31 28 29 30 32 32 31 31 33 34 29 28 26 25 23 23 22 22 25 27 30 33 37 39 41 42 40 41 40 38 34 32 32 32 33 34 35 34 34 35 38 41 38 36 32 28 24 21 20 19 24 26 29 33 35 33 28 24 20 20 21 22 25 28 31 33 37 36 36 34 32 29 27 26 21 21 22 24 28 39 53 63 72 76 77 72 61 50 42 39 37 40 41 38 33 32 36 40 55 63 75 85 88 84 77 71 60 55 48 42 37 33 29 26 21 20 20 21 25 30 35 38 41 38 34 29 24 21 19 19 20 21 21 22 24 26 28 29 34 36 40 45 50 55 57 59 53 48 39 31 25 22 22 22 28 31 36 39 40 38 35 33 23 22 20 20 22 26 31 34 42 42 42 41 41 41 41 41 33 30 25 22 21 23 26 28 37 34 28 22 16 13 11 10 10 11 12 12 12 13 15 18 17 22 29 36 40 41 40 39 38 35 31 27 24 23 23 23 21 20 19 18 17 16 16 16 16 14 12 11 10 12 13 15 17 18 20 21 22 21 20 19 18 17 15 13 11 10 10 9 11 10 10 9 9 8 8 8 8 8 8 7 7 6 6 6 7 7 7 6 6 5 5 5 5 5 5 4 4 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 6 6 6 7 7 8 8 8 9 9 9 9 9 9 9 9 8 8 9 9 9 9 10 10 13 13 13 14 14 15 15 15 15 15 15 15 15 15 15 15 17 18 19 20 21 22 22 22 21 21 22 23 24 25 25 26 21 21 21 20 18 15 12 10 10 10 11 14 17 21 25 27 33 33 33 32 30 27 24 23 20 21 23 25 26 27 28 28 23 24 26 27 28 28 28 28 27 27 28 29 30 32 34 35 39 41 43 45 46 46 44 43 38 34 29 27 29 36 45 50 62 64 65 65 60 51 42 37 32 32 32 32 34 35 37 38 35 34 34 35 38 42 46 48 47 43 36 28 22 22 26 29 37 42 46 45 43 41 35 29 28 27 25 26 29 32 33 33 35 32 29 26 23 23 23 24 26 28 32 35 39 40 41 41 42 42 41 41 40 39 39 38 40 39 37 36 37 38 39 40 41 39 34 29 25 22 20 19 23 25 28 31 31 30 28 26 22 22 23 24 27 31 35 37 37 37 37 37 34 31 27 25 24 22 21 23 31 41 52 59 73 73 71 64 53 43 38 36 38 42 43 40 34 31 33 36 48 56 68 79 84 82 76 72 58 55 48 41 35 30 28 27 23 22 23 24 27 31 35 38 42 37 31 24 20 19 21 22 21 23 24 25 25 27 30 33 33 37 42 47 52 54 56 56 51 46 38 30 25 24 25 27 28 30 32 34 34 33 31 30 23 21 19 18 20 24 29 32 43 43 44 44 43 41 38 37 32 29 24 19 16 19 24 29 33 33 33 30 26 20 14 10 12 10 9 9 11 13 13 12 14 18 23 30 35 38 40 40 37 36 33 29 25 22 19 17 17 17 17 17 17 17 17 17 15 14 13 13 12 11 10 10 14 15 16 18 19 19 19 19 16 17 17 17 16 14 12 11 9 10 10 11 11 10 9 8 8 8 7 7 7 7 7 6 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 6 6 6 7 7 8 8 8 8 8 8 8 8 8 8 8 8 8 9 9 9 10 10 10 13 13 14 14 15 15 15 15 15 15 15 15 15 15 15 15 17 17 19 20 21 21 21 21 20 21 21 22 22 23 23 23 21 21 20 19 17 14 12 10 11 11 12 14 17 21 24 26 30 30 29 29 27 24 22 20 21 22 25 27 28 28 27 26 22 23 23 24 25 26 26 26 26 26 26 27 28 30 32 33 36 38 40 42 42 42 41 40 36 34 30 28 30 36 43 47 57 58 60 60 55 48 40 35 31 32 33 34 35 36 36 37 33 33 33 34 38 42 47 50 49 45 38 30 24 23 27 30 40 46 49 47 45 42 35 28 28 26 25 26 29 33 34 34 34 32 29 26 24 24 24 25 27 28 31 34 36 38 38 38 40 41 42 42 42 41 39 39 40 39 38 37 38 39 40 41 42 39 35 30 26 23 22 21 25 27 29 32 32 31 29 27 23 24 24 26 30 33 37 39 40 41 41 41 38 34 29 27 25 24 23 25 31 40 50 56 65 64 61 53 44 38 35 35 39 42 44 41 35 32 33 36 41 48 58 68 73 72 68 65 55 52 46 39 34 30 28 28 24 24 24 25 27 31 35 37 37 33 26 21 18 20 22 25 26 27 29 29 28 29 30 32 33 36 41 46 50 53 54 54 49 44 37 29 24 23 23 24 27 28 30 32 32 31 29 28 22 20 19 18 20 23 28 31 38 39 40 40 39 38 37 36 32 30 25 19 16 17 22 26 31 32 33 32 28 22 16 12 12 10 8 9 11 12 13 12 12 15 19 25 29 33 36 37 35 34 31 28 24 21 19 17 17 17 17 17 17 17 17 17 14 14 13 12 11 11 10 10 13 14 15 16 17 18 18 18 16 16 17 17 16 14 12 11 11 12 12 12 11 10 9 9 8 7 7 7 7 6 6 6 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 6 6 6 7 7 8 8 8 8 8 8 8 8 8 8 8 8 8 9 9 10 10 10 11 14 14 14 14 15 15 15 15 14 14 14 14 14 14 14 14 16 17 18 19 20 20 20 20 19 19 19 20 20 20 20 20 20 20 20 18 16 14 12 10 12 12 13 15 18 21 23 25 25 25 25 24 22 21 19 18 21 24 27 30 31 29 26 24 20 20 20 20 21 22 23 24 23 23 23 24 25 27 28 29 33 33 35 36 37 37 37 37 34 32 31 30 32 36 41 44 50 52 53 52 49 44 38 34 31 32 34 35 36 36 35 34 31 31 31 33 37 43 49 52 51 47 40 33 27 26 29 32 44 49 52 50 46 43 35 27 26 24 23 25 29 33 35 35 33 31 29 26 25 25 25 25 28 28 30 31 32 33 33 33 36 38 41 43 43 42 39 38 38 38 38 38 38 39 40 41 41 39 35 31 28 26 25 24 27 29 31 33 33 32 30 29 26 26 27 30 33 37 41 43 46 47 48 48 45 39 34 30 27 26 25 26 30 37 45 50 54 52 47 41 35 33 35 37 42 45 46 42 36 32 31 32 33 38 46 54 58 60 59 58 50 47 42 36 32 30 28 28 27 26 26 27 28 31 33 35 30 27 21 18 18 21 27 31 34 36 37 36 33 32 31 32 33 35 40 44 48 51 52 53 47 43 36 29 24 22 22 22 25 26 28 28 28 27 26 25 21 19 18 17 19 22 26 29 32 33 34 35 35 35 35 34 33 30 25 20 15 15 19 22 29 31 34 35 32 26 20 16 13 10 8 8 10 12 12 12 11 12 14 18 22 26 30 32 32 31 29 26 23 20 18 17 17 17 17 17 17 16 16 16 13 13 13 12 11 11 10 10 12 12 14 15 15 16 16 15 15 15 15 15 15 14 12 12 14 14 14 14 13 11 10 9 8 7 7 7 6 6 5 5 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 6 6 6 7 7 8 8 8 7 7 7 7 7 7 7 7 8 8 9 9 10 11 11 12 14 14 14 15 15 15 15 15 13 13 13 13 14 14 14 14 15 16 17 18 19 19 18 18 18 18 18 18 18 18 18 18 21 20 19 18 16 14 13 12 13 14 15 16 18 20 22 23 21 21 21 21 20 19 18 18 23 26 30 33 32 29 24 21 18 17 17 17 18 19 21 22 20 20 20 21 22 24 25 26 30 30 31 31 32 33 34 34 31 32 32 34 36 38 40 42 46 47 47 46 44 40 36 34 31 33 35 36 36 35 33 31 28 29 30 33 38 45 51 55 52 49 43 36 30 29 32 35 46 52 55 52 48 43 34 25 23 22 21 23 28 32 34 34 32 31 29 27 26 25 25 26 28 28 28 28 28 28 28 28 32 35 39 42 43 40 37 34 34 34 35 35 36 38 39 39 40 38 35 31 29 27 27 27 29 30 32 33 34 32 31 30 28 29 30 33 37 41 45 48 53 55 56 55 51 45 38 34 27 26 25 26 28 33 37 40 43 40 35 31 30 33 38 43 48 49 47 43 36 30 27 27 29 32 37 42 46 49 51 51 44 41 37 33 30 28 28 28 28 28 28 28 29 30 32 33 26 23 19 18 20 27 35 40 45 46 46 44 39 35 33 33 33 35 39 43 46 49 50 51 45 42 36 30 25 23 22 22 24 24 25 25 24 23 22 21 19 18 17 16 18 21 24 26 27 27 29 30 32 33 34 34 33 31 26 20 16 14 16 19 25 29 34 37 36 31 25 21 15 12 9 8 10 12 12 12 10 10 11 13 16 21 25 27 28 27 25 23 21 19 18 17 17 17 17 16 16 16 16 15 13 12 12 11 11 10 10 10 10 11 12 13 14 14 13 13 14 14 14 14 14 13 13 13 17 17 16 15 14 12 10 9 8 8 7 7 6 5 5 5 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 6 6 6 7 7 8 8 8 7 7 7 7 7 7 7 7 8 8 9 10 11 12 12 13 14 14 14 14 14 14 13 13 11 11 12 12 13 13 14 14 15 15 16 17 17 17 17 16 17 17 17 17 18 18 18 18 21 21 19 18 16 15 14 14 15 15 16 18 19 20 21 21 20 20 20 19 19 19 20 20 24 27 32 34 33 28 22 18 15 15 15 16 17 18 19 20 17 18 18 19 21 23 25 26 29 29 28 28 29 30 32 33 30 32 35 38 40 42 43 43 46 46 45 43 40 38 35 34 32 33 35 35 35 32 30 28 26 27 30 34 40 47 53 56 52 49 44 38 33 32 35 38 47 53 56 54 50 44 35 26 22 21 20 22 27 31 33 33 33 32 30 29 27 26 25 25 26 26 26 25 25 25 25 26 30 33 37 40 39 36 31 28 28 29 30 32 33 34 35 35 37 35 33 30 28 28 28 28 30 31 32 32 32 31 30 29 29 30 31 34 39 44 48 51 59 59 59 57 53 47 40 36 26 26 25 25 26 28 30 31 32 29 25 24 29 36 44 49 56 54 49 42 35 28 25 23 27 28 30 32 36 39 41 43 38 36 32 29 27 26 27 27 28 28 28 28 29 29 30 30 25 24 22 22 27 35 44 49 55 55 53 49 42 37 34 33 33 35 37 40 43 46 48 49 43 41 36 32 28 25 24 23 23 22 22 21 20 19 18 17 17 17 16 16 17 19 21 23 24 24 26 27 30 32 34 35 33 31 27 22 17 14 15 16 22 26 32 37 38 35 30 26 19 16 11 9 10 11 12 11 11 11 10 11 13 17 21 24 23 22 21 20 19 18 17 17 17 17 17 16 16 15 15 14 12 11 11 11 11 10 10 10 10 10 11 12 12 12 12 11 12 12 12 12 12 13 13 13 17 17 17 16 15 13 11 10 10 9 9 8 7 6 5 5 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 6 6 6 7 7 8 8 8 8 8 8 8 8 8 8 8 8 8 9 10 11 12 13 13 13 13 13 12 12 12 12 11 10 10 11 11 12 13 13 14 14 15 15 16 16 16 15 15 16 17 17 18 19 20 20 21 23 22 20 18 17 16 16 16 16 17 18 19 20 20 20 19 19 19 19 19 19 20 21 22 26 29 32 33 31 26 20 15 14 15 16 17 18 18 18 18 15 16 17 19 21 24 26 28 28 27 25 24 25 28 30 32 31 33 37 41 44 46 47 48 49 47 44 40 37 35 33 33 33 33 33 33 32 29 27 26 25 27 32 38 44 50 54 56 50 48 44 39 36 35 38 41 47 53 58 56 53 48 39 30 24 23 22 24 28 31 33 34 34 33 32 30 28 26 24 23 24 24 23 23 23 24 25 26 31 33 36 38 36 31 26 23 22 24 26 28 30 31 32 32 32 31 29 28 27 27 28 28 29 30 30 30 30 29 28 28 28 29 31 35 40 45 50 53 60 59 58 54 49 43 38 34 26 26 26 26 26 26 26 26 23 21 21 25 33 44 52 57 63 58 51 43 35 30 27 26 29 28 27 27 28 30 32 34 34 32 29 26 24 24 25 25 27 27 27 28 28 28 29 29 27 26 27 29 35 44 52 57 61 60 56 49 41 35 33 32 31 32 34 36 39 41 43 44 40 38 36 32 29 27 25 25 22 22 20 19 18 16 15 15 16 15 15 15 16 17 19 21 22 22 23 25 27 30 33 34 32 32 29 24 18 15 15 16 19 23 30 36 38 37 34 32 25 20 15 11 11 11 11 11 12 11 10 10 12 15 18 20 18 18 18 18 17 17 17 17 17 17 16 16 15 14 14 14 11 11 11 10 10 10 10 10 10 10 11 12 12 11 11 10 11 11 11 11 11 12 14 14 17 17 17 16 15 13 12 11 12 11 10 9 8 7 6 6 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 6 6 6 7 7 8 8 8 8 8 8 8 8 8 8 8 8 8 9 10 12 13 14 14 12 12 11 11 11 10 10 10 9 9 10 11 12 13 13 14 14 14 15 15 15 15 14 13 16 17 18 19 21 22 23 24 25 23 21 19 18 18 18 19 17 18 19 20 20 20 19 18 18 18 18 18 19 21 22 24 28 29 31 32 29 24 18 14 12 14 17 20 21 20 18 17 14 15 16 19 22 26 29 31 26 24 22 21 22 25 28 30 32 35 39 44 48 51 52 53 51 48 43 38 34 31 30 30 33 33 32 30 28 26 25 24 24 28 35 42 48 52 54 55 47 46 44 40 37 37 41 44 47 55 60 60 58 53 44 35 29 27 26 27 31 34 35 36 35 35 33 31 28 25 23 21 21 21 21 21 22 24 26 28 36 37 38 37 34 28 23 19 19 21 24 26 29 30 30 30 28 27 26 25 25 25 27 28 28 28 28 28 27 27 26 26 27 28 31 34 39 45 50 53 58 56 52 47 42 36 32 29 27 27 28 29 28 26 25 23 22 22 24 33 45 57 65 68 67 61 52 44 38 36 35 35 34 33 30 28 27 28 29 30 31 29 26 23 22 22 22 23 25 25 26 27 27 28 28 27 29 29 31 36 42 49 56 60 63 60 54 45 36 31 30 30 27 27 29 31 33 35 37 39 35 35 33 32 30 28 26 25 22 21 20 18 16 15 14 13 15 14 14 14 15 16 18 18 20 20 21 22 25 28 30 32 32 32 30 25 20 17 16 16 17 21 27 33 37 38 38 37 30 25 18 13 11 11 11 10 11 11 10 10 11 13 15 16 15 15 15 16 16 16 16 16 17 17 16 16 15 14 13 13 10 10 10 10 10 10 10 10 10 11 11 12 12 11 10 10 10 10 9 9 10 12 14 15 15 15 15 15 15 14 13 12 14 13 12 11 10 8 7 7 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 6 6 6 7 7 8 8 8 9 9 9 9 9 9 9 9 8 8 9 10 12 13 14 15 11 11 11 10 9 9 9 8 8 9 10 10 11 12 13 13 13 14 14 15 15 14 13 13 16 17 18 20 22 24 26 26 26 24 22 20 19 19 20 20 18 19 20 21 21 20 18 17 17 17 17 17 18 20 23 24 29 30 31 30 27 22 17 13 12 15 19 22 23 21 18 16 13 14 16 19 23 27 31 33 25 23 20 18 19 22 26 29 33 36 40 46 50 54 56 57 53 49 43 36 31 29 28 28 34 33 30 28 26 24 24 23 24 29 36 44 50 54 54 54 46 45 43 40 38 39 42 45 48 56 62 63 61 57 49 40 33 31 29 30 33 36 37 37 36 36 34 31 28 25 22 20 20 19 19 20 22 25 28 29 39 40 39 37 33 27 22 18 18 20 23 26 28 30 30 30 26 25 24 23 23 24 26 27 27 27 27 26 25 25 24 24 26 27 30 34 39 45 50 53 55 52 47 41 35 31 27 25 28 29 30 31 30 28 25 23 25 26 31 42 56 68 76 78 69 62 53 45 41 41 42 43 41 39 36 32 30 29 29 30 30 28 25 22 20 20 21 22 23 24 25 26 27 27 27 27 29 31 34 39 45 52 58 61 62 58 51 41 32 27 27 28 24 24 25 27 29 31 33 35 32 32 31 30 29 27 26 25 23 21 19 17 15 14 13 13 14 14 14 14 14 15 17 17 19 18 19 20 22 25 28 30 32 32 30 27 22 18 17 17 16 20 26 32 36 39 39 39 33 28 20 15 12 11 10 10 10 10 10 10 11 12 13 13 13 13 14 14 15 16 16 16 17 17 16 15 14 14 13 12 10 10 10 10 10 10 10 10 11 11 12 12 12 11 10 10 10 9 9 9 10 12 14 15 14 14 15 15 15 14 13 13 15 14 13 12 11 9 8 8 6 6 6 5 5 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 6 6 6 6 6 6 6 6 7 7 7 8 8 9 9 9 9 9 9 10 10 11 11 11 10 9 9 8 8 9 9 10 10 10 10 11 11 12 12 12 13 12 12 12 12 13 14 15 15 17 20 22 24 25 25 25 23 22 20 19 18 19 20 21 19 18 17 17 16 16 17 17 18 17 16 17 19 22 25 27 29 30 31 29 24 19 16 15 14 18 24 29 30 27 22 18 16 16 18 23 29 33 32 31 26 23 19 16 17 20 26 29 33 34 38 44 50 53 53 52 54 48 40 32 27 27 29 31 32 33 32 28 22 20 22 25 28 37 47 52 55 57 53 47 46 39 34 35 38 39 42 47 53 57 64 68 67 61 54 49 38 34 31 30 33 38 41 43 40 39 37 34 30 26 22 20 20 21 22 23 24 29 35 40 42 45 47 44 38 30 24 21 17 19 24 27 29 29 28 27 23 22 20 19 19 20 22 24 23 23 22 22 22 21 21 21 24 26 30 35 38 40 40 40 41 37 32 27 25 26 28 30 32 35 37 38 36 34 32 32 31 36 45 59 72 82 86 87 73 64 52 43 42 46 52 57 48 47 43 38 33 31 31 33 38 36 33 29 25 22 20 19 22 22 23 24 26 27 28 28 33 34 37 40 44 48 51 52 48 44 37 30 24 22 21 22 22 22 22 22 21 21 21 20 24 25 27 29 29 28 26 24 22 21 20 18 16 15 13 13 12 12 11 11 12 14 16 17 18 19 19 21 22 23 24 24 27 28 28 28 26 22 19 16 16 19 24 30 34 37 38 38 34 30 24 18 13 11 10 11 9 10 12 13 14 13 12 11 11 12 13 14 15 16 17 17 17 17 17 16 15 13 12 11 12 12 11 9 9 9 9 9 10 10 10 10 10 10 10 10 10 9 9 8 9 10 12 13 12 12 13 14 15 15 16 16 18 17 15 13 11 9 7 6 6 5 4 3 3 3 3 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 6 6 6 6 6 6 6 6 7 7 7 8 8 8 9 9 9 9 9 10 10 11 11 11 10 9 9 8 8 9 9 10 10 10 10 11 11 11 12 12 12 12 12 12 13 14 16 16 18 19 21 23 25 25 25 25 22 21 20 19 18 19 19 20 18 17 16 16 16 16 17 17 18 17 16 17 18 21 24 26 29 29 29 26 22 18 16 15 17 21 26 30 30 27 22 19 17 18 20 25 31 33 32 30 24 22 18 16 17 20 25 28 31 32 36 42 47 51 51 50 47 42 34 27 23 22 25 27 31 32 31 27 23 21 24 27 34 43 52 57 60 60 55 47 46 39 34 35 38 39 42 47 53 57 63 67 66 61 55 50 39 36 33 32 35 38 41 42 39 38 35 32 29 27 25 24 27 28 30 31 32 36 41 45 46 48 50 47 41 32 26 22 19 21 24 26 28 28 27 26 26 24 22 20 19 19 20 21 23 23 23 23 22 22 21 21 23 26 31 35 38 39 38 38 35 31 26 22 21 24 28 31 41 44 46 46 45 42 41 41 42 46 56 68 79 86 89 88 74 65 53 46 45 49 55 59 56 55 50 45 40 38 39 42 42 40 37 33 29 26 23 22 22 22 22 23 24 26 28 29 33 35 37 40 43 45 46 46 40 36 30 24 19 17 16 17 19 19 19 19 19 19 18 18 19 21 23 24 24 23 22 21 20 19 18 17 16 15 14 13 13 12 11 11 12 14 16 17 18 19 19 20 21 21 22 22 25 26 26 26 24 22 19 17 16 19 23 28 32 34 36 37 33 30 25 20 15 12 11 10 10 11 12 13 14 13 12 12 11 11 12 13 14 15 16 16 17 17 17 16 15 14 13 12 13 12 11 10 9 9 9 9 10 10 10 10 10 10 10 10 10 9 9 8 9 10 11 12 12 12 12 13 14 15 15 16 17 17 15 13 11 9 7 6 6 5 4 4 3 3 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 6 6 6 6 6 6 6 6 7 7 7 7 8 8 8 9 9 9 9 9 10 10 10 10 9 9 8 8 8 8 9 9 10 10 10 10 11 11 11 12 11 11 11 12 14 16 18 19 22 23 24 24 25 25 24 24 21 20 19 18 18 18 19 19 16 16 15 15 15 15 16 17 17 17 16 17 18 21 23 25 28 27 26 22 18 15 16 17 21 24 28 31 30 27 22 19 19 20 23 28 32 33 31 29 23 22 19 18 19 22 25 27 28 29 32 37 41 44 44 43 39 35 28 22 20 21 24 26 31 32 31 28 24 24 28 33 42 52 62 66 68 66 58 50 47 40 35 36 38 38 41 46 52 55 61 64 64 60 54 50 41 38 34 33 36 39 41 41 39 37 34 31 29 29 29 30 33 36 38 40 41 43 46 49 51 53 54 52 44 36 29 25 24 25 26 28 29 29 29 29 28 27 24 21 19 18 19 19 24 24 24 24 23 23 23 23 24 27 32 36 38 38 36 34 29 26 22 20 23 28 35 40 53 55 57 56 53 51 50 50 51 56 65 75 84 88 88 86 73 65 55 49 49 53 58 62 62 60 55 49 45 45 48 52 51 49 46 42 37 32 28 25 22 22 21 21 23 26 29 31 34 36 38 40 41 40 39 37 31 28 23 18 15 13 12 13 15 15 16 17 17 17 16 16 16 17 19 20 21 20 19 18 17 16 16 16 15 15 15 15 13 13 12 11 12 14 16 17 19 19 19 19 19 19 19 19 21 22 23 23 22 20 18 17 17 19 21 24 28 31 33 34 32 30 27 22 18 14 11 9 10 11 12 13 13 13 13 12 11 11 12 12 13 13 14 14 16 16 17 17 16 15 14 13 14 13 12 10 10 9 9 9 10 10 10 10 10 10 10 10 10 9 9 9 9 10 11 11 11 11 12 12 13 14 15 15 16 16 14 13 11 9 8 7 6 6 5 4 3 3 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 7 7 7 8 8 8 9 9 9 9 9 9 9 10 9 9 8 7 7 8 9 9 9 9 10 10 10 11 11 11 10 10 11 13 15 17 20 21 25 25 25 25 24 23 22 22 20 19 19 18 18 18 18 18 14 14 14 14 14 15 16 17 17 17 17 18 19 21 23 24 26 25 22 18 15 14 17 20 27 28 30 31 30 26 22 19 19 22 26 30 33 32 30 29 25 24 23 22 23 24 26 27 26 26 27 30 33 35 34 32 31 28 23 20 20 23 28 31 33 34 33 29 26 28 34 39 51 61 71 75 76 73 64 55 51 43 38 37 38 37 40 44 48 52 56 60 60 57 52 49 40 37 34 33 35 37 39 39 38 36 33 30 30 32 34 37 39 42 45 46 46 46 47 48 54 56 58 55 48 39 33 29 29 29 30 31 31 32 33 33 29 28 25 23 21 19 19 18 25 25 25 25 25 26 26 26 27 30 34 38 39 37 34 32 28 26 24 25 31 40 50 56 64 65 65 62 57 53 51 50 53 57 66 75 82 84 82 78 69 63 54 50 50 54 58 61 58 56 52 48 46 48 54 59 62 60 57 52 45 38 32 28 23 22 21 21 23 27 32 34 36 38 40 40 39 36 32 29 25 23 20 17 15 13 12 12 13 14 16 17 18 17 17 16 16 17 18 19 19 19 19 18 14 14 14 15 15 15 16 16 14 13 12 12 12 14 16 17 19 18 18 18 17 17 16 16 18 18 19 20 20 19 18 18 18 19 20 22 24 27 29 31 30 29 27 25 21 16 12 10 11 11 12 12 13 13 13 13 11 11 12 12 12 12 12 12 15 15 16 17 17 16 16 15 15 14 13 11 10 10 10 10 9 9 9 9 9 9 9 9 9 9 9 9 9 9 10 10 10 10 10 11 12 13 13 14 15 14 13 12 10 9 8 8 7 6 5 4 4 4 4 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 7 7 7 8 8 9 9 9 9 9 9 9 8 9 8 7 7 7 7 8 9 9 9 9 10 10 10 11 11 10 11 12 13 16 18 21 22 26 26 24 23 22 21 20 20 18 18 18 18 18 17 17 16 13 13 13 14 15 16 17 18 18 18 18 19 20 22 23 24 24 23 20 16 14 16 21 25 32 32 32 32 29 25 21 18 19 22 26 29 30 30 29 29 28 28 28 28 28 28 27 27 25 24 23 24 26 26 25 23 22 20 18 18 21 26 31 35 35 35 34 30 28 31 38 45 57 67 77 82 83 81 72 63 58 49 42 40 39 36 37 40 43 45 49 52 53 51 48 46 38 35 33 32 34 36 37 37 39 36 33 31 32 35 40 43 45 48 51 51 49 47 47 47 54 56 58 56 50 42 36 33 30 31 32 33 35 36 37 38 32 31 29 27 24 22 21 21 26 26 27 28 29 30 31 31 32 34 38 40 40 37 34 32 29 28 29 33 41 52 63 69 72 72 69 64 57 51 48 47 48 53 60 69 76 77 73 70 61 56 50 46 47 50 53 54 48 47 45 43 44 49 56 62 69 68 65 60 52 43 35 30 25 24 23 23 26 30 35 38 39 40 41 40 37 33 28 25 22 21 20 18 16 14 13 13 14 16 18 21 22 21 21 20 17 17 18 18 18 17 17 17 13 13 14 14 15 16 17 17 15 14 13 12 13 14 16 17 18 18 17 17 16 15 15 15 15 16 17 17 18 18 18 18 19 19 19 20 22 24 26 27 27 27 26 25 22 18 14 11 11 11 11 11 12 12 13 13 12 12 12 12 12 12 11 11 13 14 15 17 17 18 17 17 17 16 14 12 11 10 10 10 9 9 9 9 9 9 9 9 9 9 9 9 9 9 8 8 8 9 9 10 11 12 12 12 13 13 12 11 10 9 9 8 7 6 5 5 4 4 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 6 6 6 7 7 7 7 9 9 9 9 8 8 8 8 8 8 7 7 7 7 8 8 8 9 9 9 10 10 10 10 11 12 13 14 16 19 21 23 25 24 22 20 18 17 17 17 17 17 18 18 18 17 16 15 13 13 13 14 15 17 19 20 19 20 20 21 22 23 24 24 22 21 19 16 16 19 26 30 35 35 34 31 27 23 19 17 17 20 24 26 26 27 28 29 31 32 33 33 31 29 27 25 24 22 21 21 22 23 22 20 17 16 15 16 20 26 32 35 36 36 33 29 27 31 40 47 59 69 80 86 88 88 81 73 67 57 48 44 39 35 34 36 35 38 41 44 45 44 42 41 35 33 31 32 34 36 36 36 39 38 35 34 36 39 44 47 53 54 55 54 50 47 45 45 49 52 55 55 50 44 39 37 31 32 35 38 41 43 45 45 41 40 37 34 31 28 25 24 26 27 28 31 33 35 37 37 40 41 42 42 41 38 35 34 32 32 34 38 46 56 66 71 74 73 69 62 53 47 43 42 44 47 53 61 66 67 64 60 51 47 42 40 40 42 43 44 39 39 39 39 41 47 55 60 68 68 66 62 55 45 37 31 26 26 26 28 31 35 39 42 42 42 42 40 37 32 28 25 22 22 22 21 19 17 15 14 17 19 22 25 26 26 25 24 18 18 17 17 16 15 15 14 13 14 14 15 16 17 17 18 16 15 14 13 13 14 15 16 18 18 17 17 16 16 15 15 15 15 15 16 16 17 17 17 19 19 20 21 22 22 23 23 24 24 24 23 21 18 16 14 12 11 11 11 11 12 13 14 14 14 13 13 12 12 11 11 12 13 15 17 18 19 19 19 18 17 15 13 12 11 10 10 8 8 8 8 8 8 8 8 8 9 9 9 9 8 7 7 7 7 8 9 10 10 11 11 12 12 11 11 10 10 9 9 7 7 6 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 6 6 6 7 7 7 9 9 9 8 8 7 7 7 8 7 7 6 6 7 7 8 8 8 9 9 9 10 10 10 13 13 14 15 17 19 21 22 23 21 19 17 15 15 15 15 16 17 17 18 17 16 15 14 13 13 14 15 17 19 21 22 21 21 22 23 24 25 25 25 19 19 19 18 19 24 30 35 38 37 34 30 26 21 17 15 15 18 21 22 22 23 27 30 33 34 35 35 33 29 25 22 22 20 19 21 23 25 25 24 20 19 18 19 22 27 32 35 35 34 31 26 24 29 38 46 59 69 80 86 91 93 89 82 75 65 54 47 40 33 30 32 29 30 33 36 37 37 36 35 34 33 31 32 35 37 38 38 40 39 38 38 40 43 47 49 55 56 55 51 46 41 39 39 43 47 51 52 50 45 41 39 35 38 43 49 53 56 57 58 53 52 48 44 38 33 29 26 26 27 30 33 36 40 42 43 47 46 45 44 42 40 38 37 38 39 40 44 49 56 62 66 66 65 61 54 46 39 36 36 39 41 45 50 54 54 51 48 42 38 34 32 32 33 33 32 31 32 33 34 36 41 47 52 60 61 61 59 54 46 38 33 28 28 30 33 36 40 43 45 44 44 42 40 37 33 30 28 27 28 28 27 26 23 20 19 19 21 25 28 30 30 29 28 23 22 21 19 17 16 15 15 15 15 15 16 17 17 18 18 17 16 14 13 13 14 15 16 17 17 17 17 17 16 16 16 16 16 15 15 16 16 17 17 19 20 21 22 23 22 21 20 21 21 21 21 20 19 18 17 12 12 11 10 11 12 13 14 16 16 15 14 13 12 11 11 11 13 15 17 19 20 21 21 19 18 16 14 12 11 10 10 8 8 8 8 8 8 8 8 8 9 9 10 9 8 7 6 6 7 7 8 9 10 10 10 11 11 11 10 10 10 10 9 8 7 6 5 5 5 5 6 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 6 6 7 7 7 9 9 9 8 8 7 7 7 8 7 7 6 6 7 7 8 8 8 8 9 9 10 10 10 14 14 14 15 17 19 21 22 21 19 17 15 13 13 13 13 15 16 17 18 17 16 14 13 13 13 14 15 17 20 22 23 22 22 24 25 25 25 25 25 18 18 19 19 21 26 33 39 39 37 34 29 25 20 16 14 14 16 19 19 19 21 26 31 33 34 36 36 33 28 23 19 20 19 19 21 25 28 30 29 26 24 23 23 25 29 33 36 34 32 29 24 22 26 36 44 58 68 79 86 92 96 93 88 80 69 57 49 41 32 28 29 24 26 28 31 32 33 33 32 34 33 32 34 37 39 40 39 41 40 40 40 42 45 48 50 54 54 51 46 40 35 33 33 39 43 48 50 49 45 42 41 41 45 52 59 64 67 69 69 63 61 56 50 43 36 31 27 26 28 30 34 39 42 45 47 52 50 48 45 42 41 40 39 45 45 46 48 52 56 59 62 57 56 52 46 38 33 30 30 34 35 38 41 44 44 41 38 36 33 29 27 27 27 26 25 25 26 28 29 30 34 39 43 51 53 56 56 53 46 39 35 28 30 32 36 39 43 45 47 46 45 42 40 37 34 32 31 33 34 35 34 32 29 26 24 19 22 26 30 32 32 30 29 29 27 25 23 21 19 18 18 16 16 16 17 17 18 18 18 17 16 15 13 13 14 15 16 17 17 17 17 17 17 17 17 16 16 16 15 15 16 17 17 19 20 22 24 23 22 19 18 19 19 19 19 19 19 19 19 13 12 11 10 11 12 14 15 17 17 16 15 14 13 12 11 11 12 14 17 19 20 21 22 19 18 16 14 12 11 11 10 8 8 8 8 8 8 8 8 8 9 9 10 9 8 6 5 6 6 7 7 8 9 10 10 10 10 10 10 10 10 10 10 8 7 6 5 5 5 5 6 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 7 7 7 7 7 7 7 7 7 7 7 8 8 9 9 9 10 10 9 9 9 10 11 11 11 12 14 16 18 19 19 20 21 18 15 11 10 11 12 14 17 17 18 18 17 15 13 12 13 15 16 17 20 24 24 22 26 27 28 29 29 28 27 26 16 16 16 20 27 34 38 40 44 39 30 23 19 17 16 14 17 17 16 17 19 22 26 28 33 34 36 36 33 28 23 19 17 19 23 28 31 34 35 36 33 32 31 32 33 34 33 31 35 32 27 22 20 24 31 37 50 59 72 82 87 88 88 87 79 73 64 52 41 33 27 24 21 23 26 27 27 28 30 32 32 37 40 39 39 44 46 46 45 43 40 40 42 45 46 46 51 48 44 39 33 29 26 25 32 36 41 44 45 44 44 44 42 51 59 65 72 78 79 76 72 68 62 56 49 41 33 27 22 24 27 32 39 46 51 55 57 55 52 49 47 47 48 49 52 51 49 49 50 50 49 48 45 42 39 35 32 31 31 32 31 32 33 34 34 33 31 30 30 29 28 25 22 22 24 26 25 26 27 27 26 27 29 32 40 43 46 48 47 42 36 32 28 31 35 40 43 45 45 45 41 40 39 38 37 37 37 37 39 40 41 41 39 35 31 28 24 24 26 30 34 36 35 33 32 30 28 25 23 23 23 23 22 22 22 22 22 22 22 22 16 16 16 16 16 16 16 16 17 16 15 15 16 17 19 20 21 21 20 20 20 19 19 19 24 24 24 24 24 23 22 21 17 18 19 20 20 20 20 19 16 15 13 12 11 11 12 13 15 16 16 16 15 13 11 10 9 10 13 15 17 17 17 17 15 14 13 13 12 11 10 10 10 9 9 8 8 9 9 10 10 10 10 9 9 8 8 8 7 7 7 7 7 7 7 7 8 8 9 9 9 10 10 10 7 7 7 7 7 7 7 7 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 7 7 7 7 7 7 7 7 7 7 7 8 8 8 9 9 10 10 9 9 9 10 11 12 12 13 15 17 18 19 19 19 19 17 14 11 11 12 13 15 17 17 18 18 17 15 14 12 16 18 20 22 25 28 28 26 28 29 31 32 32 30 28 26 18 18 18 22 29 35 39 40 41 36 28 22 18 16 15 14 16 15 15 16 18 22 25 28 33 34 34 34 31 27 23 21 23 26 30 35 40 43 45 46 42 40 38 37 37 36 34 33 31 28 24 19 18 21 28 33 44 53 66 77 85 89 90 91 80 74 63 51 40 32 27 24 23 25 27 28 27 28 31 33 35 41 44 43 44 48 50 49 47 44 40 39 40 42 43 42 45 43 39 35 30 27 24 23 31 35 40 43 43 43 44 44 49 58 67 73 79 84 84 80 74 70 65 58 51 42 33 27 21 22 26 31 39 46 53 57 59 57 54 51 49 49 50 51 55 53 49 46 44 42 39 38 39 38 37 35 33 32 32 32 30 30 30 30 30 30 29 29 28 28 26 24 22 23 27 30 29 30 31 29 27 25 25 26 32 35 40 43 43 40 35 31 28 31 35 40 43 44 44 43 39 38 37 36 35 36 37 37 39 41 43 43 41 37 32 28 24 24 26 29 33 35 34 33 33 32 29 27 26 25 26 26 24 23 23 23 22 22 22 21 17 17 17 17 17 17 17 17 17 17 16 15 16 17 19 20 22 22 21 21 21 20 20 19 23 23 24 24 23 22 21 21 17 18 18 19 19 20 19 19 16 15 14 12 11 11 12 13 15 15 16 16 15 13 11 10 9 10 12 14 15 15 15 15 14 14 13 12 11 10 10 9 10 9 9 8 8 9 9 10 10 10 9 9 9 8 8 8 7 7 7 7 7 7 7 7 8 8 8 9 9 9 10 10 7 7 7 7 7 7 7 7 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 7 7 7 7 7 7 7 7 7 7 7 7 8 8 8 9 10 9 9 9 9 10 11 12 15 16 17 18 18 18 18 17 16 15 13 11 11 13 15 17 17 17 17 17 17 15 14 13 16 17 20 24 26 28 29 30 32 34 37 38 36 33 28 26 20 20 21 25 31 36 38 39 36 31 24 19 17 15 14 13 14 14 13 14 17 21 25 27 32 32 32 31 29 27 25 23 28 31 37 43 48 52 54 56 51 48 44 40 38 36 33 31 26 24 20 16 15 17 23 28 37 45 57 68 76 82 86 89 81 74 62 49 38 31 27 25 27 28 29 29 29 30 32 34 39 46 50 50 51 55 56 54 49 46 41 38 38 38 37 36 36 34 32 28 25 23 22 21 29 33 37 40 41 42 44 45 54 63 73 79 84 88 86 81 75 72 66 59 52 42 33 26 19 20 24 30 39 48 56 61 61 59 56 53 52 51 52 53 54 52 47 42 37 33 31 30 33 35 36 37 37 35 34 32 30 29 27 26 25 26 27 27 26 26 26 25 25 28 33 37 38 39 38 35 29 24 21 20 24 28 33 38 39 37 33 30 27 30 35 40 43 43 41 40 36 35 33 32 32 34 36 38 39 42 45 47 45 39 33 29 25 25 25 27 31 33 33 32 34 33 31 29 28 28 29 30 27 26 25 24 23 22 21 20 19 19 19 19 19 19 19 19 18 17 16 15 15 17 18 19 23 23 23 23 23 22 21 21 22 23 23 23 23 22 21 21 17 17 18 18 18 19 19 19 17 16 14 13 12 12 12 12 13 14 15 15 14 13 11 10 9 10 11 12 12 12 12 12 13 13 12 12 11 10 10 9 9 9 8 8 8 8 9 9 10 9 9 9 8 8 8 8 7 7 7 7 7 7 7 7 7 7 8 8 8 9 9 9 7 7 7 7 7 7 7 7 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 6 6 7 7 7 8 8 8 9 9 9 9 10 11 12 13 18 18 18 18 18 17 16 16 14 13 12 12 12 14 17 18 17 17 17 17 16 15 15 14 19 18 20 24 27 28 33 38 38 40 42 43 40 35 29 25 21 21 22 26 31 34 36 35 30 26 21 17 16 15 15 14 13 13 12 13 16 20 23 26 30 30 29 27 27 26 26 26 30 34 39 46 51 56 59 60 56 52 46 41 37 33 29 26 22 21 18 15 13 16 21 25 33 39 48 57 64 71 76 80 80 72 60 47 36 30 27 26 30 31 32 32 31 32 35 37 43 51 57 57 58 60 59 56 51 47 41 37 35 33 32 30 28 26 25 23 21 20 20 19 27 30 34 37 38 40 43 45 54 63 73 79 83 85 81 75 72 69 63 57 49 40 30 24 18 20 24 31 40 50 58 63 62 60 57 54 52 52 53 54 50 48 43 38 32 30 30 31 33 36 40 43 43 40 36 34 30 28 25 23 23 24 26 28 27 28 29 29 31 35 40 45 48 49 48 42 34 26 21 18 21 25 30 35 36 34 31 28 26 30 35 39 41 41 38 36 33 32 30 30 31 33 36 38 39 42 47 49 47 41 35 30 26 24 23 25 28 30 31 31 33 32 30 29 29 29 30 31 30 30 28 26 24 22 21 20 21 21 21 21 21 21 21 21 19 18 17 15 15 16 17 18 23 24 25 25 25 24 22 21 21 21 22 22 22 22 21 20 17 17 17 17 17 18 18 19 17 16 15 14 13 12 12 11 11 12 13 14 14 13 11 10 9 10 10 10 10 9 9 9 12 12 11 11 10 10 9 9 9 9 8 7 7 8 9 9 9 9 9 8 8 8 7 7 6 6 6 6 6 6 6 6 6 7 7 7 8 8 8 8 7 7 7 7 7 7 7 7 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 6 6 6 7 7 7 8 8 8 8 8 9 10 11 12 13 18 18 19 18 17 16 15 14 12 12 12 12 13 15 17 19 17 17 16 16 16 15 16 16 24 21 23 27 29 31 38 47 43 45 46 45 41 35 28 23 20 20 22 25 29 31 31 30 25 22 18 16 16 17 17 16 14 13 13 13 15 19 22 24 28 27 26 25 25 26 27 28 32 36 41 47 53 57 60 61 58 53 46 40 35 30 26 24 21 20 19 16 14 16 20 23 29 34 42 50 57 64 71 75 74 67 56 44 35 30 28 28 33 34 34 34 33 35 38 41 47 55 62 64 63 64 61 57 51 46 40 35 32 30 27 25 22 21 20 20 19 19 20 20 27 29 32 34 35 38 42 45 52 61 70 75 78 79 74 68 65 61 55 49 42 35 27 21 20 23 28 35 43 51 58 61 60 58 55 52 50 50 51 52 48 47 43 36 31 29 31 34 39 43 48 51 50 45 39 34 30 27 24 22 22 24 27 30 32 33 35 36 38 41 46 50 57 57 54 48 39 30 23 20 23 27 32 36 37 34 30 27 27 30 34 37 39 38 35 34 32 31 30 30 31 33 36 38 39 42 46 49 47 42 35 31 26 23 21 21 24 27 28 29 29 28 27 26 27 28 30 31 33 32 30 28 26 23 21 20 23 23 23 23 23 23 23 23 20 19 17 16 15 15 16 17 24 25 26 27 26 25 23 22 19 20 21 21 21 21 21 20 17 16 16 15 16 17 18 19 17 17 16 15 14 12 11 10 9 10 12 13 13 13 11 11 9 9 9 8 8 8 8 8 10 10 10 10 9 9 9 9 9 8 7 7 7 7 8 9 9 9 8 8 8 7 7 7 6 6 6 6 6 6 6 6 6 6 6 6 7 7 7 8 7 7 7 7 7 7 7 7 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 6 6 6 7 7 7 7 8 8 8 9 10 11 13 14 17 17 18 17 16 15 14 13 11 11 12 13 14 16 17 18 17 17 16 15 15 16 16 17 20 18 21 29 30 29 37 48 48 48 48 45 40 33 26 22 19 19 22 25 28 29 27 24 22 19 17 17 18 19 20 19 16 15 14 14 15 18 21 23 24 24 24 24 25 26 27 28 36 39 43 49 53 57 59 60 57 52 44 38 33 29 26 24 20 20 19 17 16 17 20 22 25 30 38 47 54 62 69 73 66 60 51 41 34 30 29 29 35 36 36 36 36 38 43 46 51 60 68 70 68 67 62 56 49 44 38 33 29 27 25 23 21 20 20 20 20 21 21 22 27 28 30 31 32 35 39 43 50 58 66 69 71 72 67 61 57 52 45 39 34 29 24 21 25 28 33 40 46 51 55 57 56 53 50 47 46 46 46 47 48 47 43 36 30 29 34 39 50 53 57 58 55 47 39 33 27 26 23 22 23 26 29 31 36 39 42 44 44 46 48 50 58 57 55 48 39 31 26 24 28 31 36 39 40 36 32 28 29 30 33 35 35 35 33 32 32 32 32 32 33 35 36 37 38 40 44 46 45 40 35 31 25 22 18 17 20 23 25 26 25 24 23 23 24 26 28 30 35 34 32 30 27 25 23 22 24 24 24 24 24 24 24 24 21 20 18 16 15 15 15 16 23 24 26 27 27 25 23 21 18 19 20 20 21 21 20 20 16 16 15 14 14 16 17 19 18 18 17 16 15 13 11 10 8 9 11 12 13 12 12 11 9 8 8 7 7 7 8 8 9 9 9 9 9 9 9 9 8 8 7 7 7 7 8 8 8 8 8 8 7 7 7 6 5 5 5 5 5 5 5 5 5 5 5 6 6 6 7 7 7 7 7 7 7 7 7 7 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 6 6 6 7 7 7 8 8 8 9 10 12 13 14 16 16 16 16 15 14 13 12 11 12 12 13 14 15 17 17 17 16 15 15 15 16 17 18 16 17 26 38 39 34 38 48 52 51 48 44 38 31 24 20 19 20 22 26 28 28 24 21 20 19 17 18 20 22 23 22 19 18 16 15 15 17 19 21 20 21 22 24 25 27 28 28 37 39 43 48 51 53 55 55 51 46 38 32 29 26 24 22 19 20 19 18 16 17 19 21 22 28 35 43 49 55 61 65 57 53 46 39 34 31 30 30 36 37 37 37 38 41 46 50 56 66 74 75 73 70 63 56 46 42 35 31 28 26 24 22 22 22 22 22 22 23 24 25 28 28 29 29 29 32 37 41 46 53 59 61 62 63 59 53 50 44 37 31 28 26 24 22 30 33 39 45 50 52 52 52 50 48 45 42 40 40 41 42 43 43 41 35 31 33 40 47 62 64 65 64 57 47 36 30 23 22 22 22 24 26 30 32 40 43 47 49 48 47 47 47 53 52 49 43 36 30 26 25 29 33 38 42 42 39 35 32 31 31 31 32 32 32 32 32 32 33 35 36 37 36 36 35 37 39 41 43 42 38 34 31 24 20 16 14 16 19 22 23 22 22 21 22 23 25 28 29 35 35 33 31 28 26 24 24 24 24 24 24 24 24 24 24 22 21 18 16 15 14 15 15 22 24 26 27 27 25 22 20 17 18 19 20 20 20 20 20 16 15 14 13 13 15 17 18 18 18 18 17 15 13 11 9 6 8 10 11 12 12 12 11 9 8 7 6 7 8 9 10 8 8 8 8 8 8 8 8 8 7 7 6 6 7 7 8 8 8 8 7 7 7 6 6 5 5 5 5 5 5 5 5 4 4 5 5 5 6 6 6 7 7 7 7 7 7 7 7 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 6 6 7 7 7 7 7 8 8 10 12 13 14 14 15 15 15 14 13 12 12 12 12 13 13 14 15 16 16 17 16 15 14 14 16 17 18 21 24 37 53 54 45 46 55 53 52 48 43 36 29 23 19 19 21 23 27 29 28 24 20 20 18 18 19 22 24 25 24 21 19 17 16 16 17 19 20 18 19 22 24 26 27 27 28 36 38 41 45 47 49 50 50 44 39 32 26 24 22 20 19 18 19 19 18 16 16 18 20 22 27 33 39 43 47 50 53 51 48 43 38 34 32 31 31 36 37 37 37 39 43 48 53 60 70 78 79 76 72 64 57 44 40 34 29 27 26 24 22 24 23 23 23 24 25 26 27 28 28 28 27 28 31 36 40 42 48 53 54 54 55 52 47 46 40 32 26 24 24 24 24 33 37 43 49 52 52 50 48 47 45 42 39 37 37 38 39 35 36 36 33 32 37 47 56 68 69 69 66 58 46 34 27 20 20 20 21 24 26 29 31 41 45 50 51 50 47 44 43 48 47 44 38 32 27 25 26 29 33 38 43 44 41 37 35 32 31 31 30 30 30 31 32 33 34 37 39 39 38 36 35 36 38 40 40 39 36 33 31 23 19 14 12 14 17 20 21 21 21 21 21 23 25 28 30 36 35 33 31 29 27 26 25 24 24 24 24 24 24 24 24 23 21 19 16 15 14 14 15 22 23 26 27 27 25 22 20 17 17 18 19 20 20 20 20 16 15 13 12 13 14 17 18 18 18 18 18 16 13 11 9 5 7 9 11 12 12 12 11 8 8 7 6 7 8 10 11 8 8 8 8 8 8 8 8 8 7 7 6 6 7 7 8 8 8 8 7 7 6 6 6 5 5 5 5 5 5 5 5 4 4 4 5 5 5 6 6 7 7 7 7 7 7 7 7 5 5 5 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 4 4 5 5 5 6 6 6 6 6 6 6 6 6 7 8 10 12 12 13 13 15 15 14 13 12 12 12 12 11 11 12 13 14 14 14 14 14 15 16 15 14 14 16 18 22 24 27 31 37 44 49 53 57 53 47 39 32 25 20 18 19 21 24 26 26 25 22 20 16 18 20 22 24 25 26 26 23 22 21 19 19 18 18 18 17 19 23 24 25 26 28 30 32 37 41 42 45 49 48 45 40 36 29 23 19 18 18 19 21 20 19 18 18 19 20 21 23 25 27 31 34 38 41 42 42 40 37 34 32 32 33 34 33 35 37 38 38 42 50 56 68 76 82 82 78 71 60 49 42 38 33 29 28 27 25 24 21 22 24 27 31 33 32 30 30 28 26 26 28 32 37 40 43 45 47 48 48 47 45 43 38 33 27 22 20 22 26 29 41 46 51 54 53 50 46 45 38 36 33 30 29 30 32 33 30 31 32 33 36 43 52 58 70 70 68 61 51 39 31 26 23 25 25 23 22 24 30 35 43 49 55 55 50 43 38 37 36 35 33 31 29 27 26 26 31 35 42 47 48 46 42 38 35 35 34 31 30 30 33 36 39 40 42 42 40 37 33 30 34 34 34 36 36 35 31 28 20 18 14 11 11 13 16 18 17 18 18 18 19 22 27 30 31 33 36 35 32 28 26 26 24 24 25 25 25 24 23 23 21 20 17 15 13 13 13 13 18 19 21 23 23 21 19 18 17 18 18 19 19 20 20 20 16 15 13 12 12 13 15 16 19 19 19 19 17 14 12 10 9 9 9 9 9 9 9 9 8 8 8 7 7 6 6 6 7 7 7 7 7 7 7 7 7 7 7 6 6 5 5 5 6 6 6 6 6 6 6 6 7 7 7 6 6 5 5 5 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 4 4 5 5 5 6 6 6 6 6 6 6 6 6 7 8 10 11 12 12 12 15 14 13 12 12 12 12 12 12 12 13 14 14 14 13 13 14 15 15 15 13 14 16 18 21 23 26 32 38 44 49 52 56 52 45 37 30 24 19 17 20 22 24 26 27 25 22 20 17 18 21 23 25 26 27 27 23 22 21 20 19 19 20 20 19 21 23 24 24 25 26 28 31 36 40 41 43 46 45 41 35 32 27 22 19 19 20 22 23 22 21 20 21 22 23 24 23 23 25 27 30 32 34 35 37 36 34 32 31 31 31 31 31 33 35 36 37 42 51 58 69 77 82 82 77 70 59 48 42 38 34 31 29 29 27 26 25 25 27 31 35 36 35 34 31 29 27 26 28 32 36 39 41 42 43 44 43 42 40 38 33 29 23 19 18 22 28 32 43 48 53 54 52 47 42 40 33 31 28 26 25 27 29 30 29 30 31 32 35 42 50 56 62 62 60 53 43 34 27 24 25 26 27 25 22 24 29 34 43 49 56 56 50 42 36 33 30 29 28 26 25 25 24 24 31 35 41 46 48 46 42 39 36 36 35 32 30 30 33 35 41 42 43 43 41 37 33 31 31 31 31 33 34 33 29 26 20 18 14 11 10 12 15 17 16 17 18 18 18 21 26 29 32 34 36 35 32 29 27 26 24 24 25 25 25 24 24 23 21 20 18 16 14 14 14 14 18 19 21 22 21 20 18 16 17 17 18 19 20 21 21 22 18 16 14 12 12 13 14 15 17 18 18 18 17 15 13 11 9 9 9 9 9 9 9 9 8 8 7 7 7 6 6 6 7 7 7 7 7 7 7 7 7 7 6 6 6 5 5 5 6 6 6 6 6 6 6 6 7 7 6 6 6 5 5 5 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 4 4 5 5 5 6 6 6 6 6 6 6 6 6 7 8 10 11 12 12 12 14 13 12 12 11 11 12 12 13 14 14 15 14 14 13 12 13 14 15 14 13 14 16 18 21 23 27 33 39 45 50 52 53 49 42 34 27 22 18 17 21 23 25 27 27 25 22 20 18 19 21 24 26 27 28 29 23 23 22 21 21 21 22 22 22 23 24 23 22 22 24 26 28 34 39 40 42 44 42 37 30 28 23 20 19 20 23 25 24 24 24 24 24 25 26 27 23 23 22 23 23 24 25 26 30 30 30 30 30 29 28 27 29 30 32 33 35 42 53 62 72 79 84 82 77 70 58 48 42 39 36 34 33 32 31 29 30 31 32 36 39 40 39 38 32 30 28 27 28 30 34 36 37 38 38 38 37 35 33 31 26 23 18 15 17 23 31 36 46 50 54 54 49 42 36 33 27 25 23 21 21 22 24 26 27 28 30 31 34 39 46 51 55 54 50 44 36 29 25 24 28 30 30 27 24 24 28 32 43 49 56 57 50 40 32 29 24 24 24 24 25 25 25 26 32 36 40 44 46 45 43 41 37 37 36 34 31 30 32 34 41 42 43 43 41 37 33 30 27 27 27 28 30 29 26 23 20 17 14 11 10 11 13 15 16 17 17 17 17 20 24 28 32 34 36 35 32 28 26 26 23 24 24 25 25 25 24 24 21 20 19 17 16 16 16 16 18 19 20 20 20 18 16 15 15 16 17 18 20 21 22 23 19 18 15 13 12 12 13 13 15 16 17 17 17 15 13 12 9 9 9 9 9 8 8 8 8 7 7 7 6 6 6 6 7 7 7 7 7 7 7 7 7 6 6 6 5 5 5 5 6 6 6 6 6 6 6 6 7 6 6 6 5 5 5 5 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 4 4 5 5 5 6 6 6 6 6 6 6 6 6 7 8 10 11 11 11 11 13 12 11 11 11 11 11 12 14 15 15 15 14 13 12 11 12 13 14 14 13 14 16 18 22 25 30 36 42 47 50 52 49 44 37 29 23 19 18 17 23 25 27 28 28 25 22 20 17 19 21 24 26 28 29 29 25 24 24 23 23 24 24 25 25 25 24 22 19 19 21 24 25 32 38 40 42 44 41 36 27 25 21 19 19 21 24 26 26 26 26 27 28 28 29 30 25 24 22 20 19 19 19 19 25 26 28 29 29 28 27 25 26 28 29 30 34 43 56 65 77 83 87 84 79 71 60 49 43 41 39 38 39 38 36 34 35 35 36 39 42 43 41 39 32 31 29 27 28 30 32 34 34 34 34 33 31 29 27 26 21 19 15 15 19 27 35 41 48 51 53 51 44 36 29 26 22 21 20 19 19 20 22 23 26 27 29 30 32 37 42 46 48 47 43 38 32 28 27 28 33 34 34 30 26 25 28 31 42 48 55 56 48 38 29 25 24 25 27 29 30 31 31 31 34 36 39 42 43 43 42 41 38 38 37 35 32 30 31 33 39 40 42 42 40 36 31 29 24 23 23 24 25 24 22 20 19 17 14 11 10 11 12 14 16 16 17 16 16 19 23 27 32 34 36 35 31 28 25 25 22 23 24 24 25 25 24 24 21 21 20 19 19 18 18 18 18 19 19 19 18 16 14 13 14 15 16 18 20 21 23 23 20 19 17 15 13 12 12 12 13 14 15 16 16 15 14 13 9 9 9 8 8 8 8 7 7 7 7 6 6 6 5 5 6 6 6 6 6 6 6 6 6 6 6 5 5 5 4 4 5 5 5 5 5 5 5 5 6 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 4 4 5 5 5 6 6 6 6 6 6 6 6 6 7 8 9 10 10 10 10 11 11 10 10 10 10 11 12 14 14 14 14 13 12 11 10 11 12 13 13 13 13 16 18 23 27 32 38 44 47 49 50 43 39 31 24 19 17 18 19 25 26 28 29 28 25 22 19 16 18 20 23 26 28 29 30 28 27 26 25 25 25 26 26 26 25 23 20 17 18 21 23 25 32 39 42 44 45 41 35 26 24 21 19 19 21 25 27 29 29 30 30 31 31 31 31 28 26 23 20 17 16 16 17 23 25 27 29 30 28 26 24 24 26 28 30 35 44 57 67 81 87 90 86 81 73 62 52 44 43 43 44 45 45 42 40 39 39 39 41 42 42 40 37 32 30 29 28 28 29 31 32 33 32 31 30 28 26 24 23 20 18 16 17 22 30 39 44 48 49 49 45 38 30 25 22 21 21 20 19 19 20 21 22 24 26 29 30 32 34 38 42 42 41 38 33 29 29 31 33 39 40 40 35 29 26 28 30 40 46 51 51 43 34 27 25 26 29 33 37 39 38 37 35 36 37 38 39 39 40 40 39 37 38 37 35 32 30 31 32 36 37 38 39 37 34 30 27 23 22 20 20 21 21 19 16 19 17 15 12 11 12 13 14 16 17 17 16 16 19 23 26 31 33 35 34 30 26 24 23 20 21 22 23 24 24 23 23 21 21 21 21 21 21 20 20 20 20 19 18 16 15 13 12 13 14 15 17 18 20 22 22 21 20 18 16 14 12 11 11 11 12 14 15 15 15 14 13 9 9 9 8 8 7 7 6 7 7 6 6 6 5 5 5 6 6 6 6 6 6 6 6 6 6 5 5 5 4 4 4 5 5 5 5 5 5 5 5 6 6 5 5 5 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 4 4 5 5 5 6 6 6 6 6 6 6 6 6 7 8 9 9 9 9 9 10 9 9 9 9 10 11 11 11 11 12 12 12 11 10 10 10 12 13 13 12 13 16 18 23 27 33 39 43 45 45 45 37 33 26 19 16 16 19 21 27 28 30 30 29 25 22 19 17 19 21 25 27 29 31 31 31 30 29 28 27 26 26 27 25 24 21 18 16 17 21 25 29 37 44 46 47 47 41 34 25 23 20 19 20 23 28 30 33 34 35 35 35 34 34 33 30 28 24 20 18 17 17 18 23 24 27 28 28 27 25 24 22 25 28 31 36 46 59 68 82 87 90 87 81 74 64 54 46 46 48 50 52 52 49 46 43 42 42 42 42 40 37 34 30 30 28 28 28 29 31 32 31 30 29 27 25 24 23 22 20 19 19 21 26 32 39 43 45 44 42 37 31 25 22 22 23 22 21 21 21 21 21 22 24 26 29 31 32 33 36 38 36 35 34 31 29 31 35 38 46 47 45 40 33 28 28 30 38 42 45 43 37 31 28 27 30 35 42 47 49 46 42 38 38 37 36 35 35 35 36 36 34 35 36 34 32 30 30 31 32 33 36 37 36 33 30 28 24 22 20 19 19 18 16 14 18 17 15 14 13 14 15 16 17 18 18 17 17 19 23 26 30 32 34 32 28 24 21 20 18 19 20 21 22 22 22 22 21 21 22 23 23 23 22 22 22 21 20 18 16 14 13 12 12 13 14 15 16 18 19 19 20 19 18 17 15 13 12 11 11 12 13 14 15 14 13 12 9 9 8 8 7 6 6 6 6 6 6 6 5 5 5 4 5 5 5 5 5 5 5 5 5 5 5 5 4 4 4 3 4 4 4 4 4 4 4 4 5 5 5 5 4 4 4 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 4 4 5 5 5 6 6 6 6 6 6 6 6 6 7 8 9 9 9 9 8 9 9 8 8 9 10 11 11 8 9 10 10 11 10 10 10 9 11 12 12 12 13 16 18 22 26 32 37 40 41 40 38 32 28 21 15 13 16 20 23 28 29 31 31 29 26 22 19 20 21 24 27 30 32 34 35 34 33 31 29 28 27 26 26 23 22 19 16 15 17 23 28 38 45 51 52 50 47 39 31 22 20 19 19 22 27 32 35 40 40 41 41 40 39 37 36 31 28 24 20 18 18 18 19 23 24 25 26 26 25 23 22 21 25 30 34 39 48 59 68 80 86 88 85 80 74 64 54 48 49 52 55 58 57 54 51 47 46 44 43 42 39 35 32 29 28 28 28 28 30 31 32 29 28 26 25 23 22 21 21 20 20 22 24 28 32 36 38 41 39 36 30 25 22 22 23 24 24 23 22 22 21 21 21 24 27 30 32 32 33 34 36 35 35 35 34 34 36 41 45 51 52 50 44 36 31 29 31 36 38 39 35 30 28 29 32 39 45 54 61 62 57 49 43 40 38 35 32 31 31 32 33 31 33 34 33 31 30 30 31 30 32 34 36 36 34 32 30 27 24 21 19 18 16 14 12 17 16 15 15 15 16 17 18 19 19 19 18 18 20 24 27 29 31 32 30 26 22 19 18 16 17 18 19 20 20 20 20 21 22 23 25 25 25 24 24 24 23 21 18 16 14 13 13 11 12 12 13 14 15 16 16 19 19 18 17 16 14 13 12 11 12 13 14 14 13 11 10 9 9 8 8 7 6 5 5 6 6 6 5 5 5 4 4 5 5 5 5 5 5 5 5 5 5 5 4 4 4 3 3 4 4 4 4 4 4 4 4 5 5 5 4 4 4 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 4 4 5 5 5 6 6 6 6 6 6 6 6 7 7 8 9 9 9 8 8 8 8 8 8 8 9 10 11 6 7 8 9 10 10 10 10 9 11 12 12 12 13 16 18 20 24 30 35 38 37 35 33 29 25 18 13 12 15 21 25 29 30 31 31 29 26 22 19 22 23 26 30 33 35 36 37 36 35 33 30 28 27 26 26 22 20 17 15 14 18 24 29 45 52 57 56 52 47 37 27 19 18 18 19 23 29 36 40 44 44 45 45 44 42 39 38 31 28 24 20 18 18 19 20 23 24 24 24 23 23 22 21 21 25 31 35 41 49 60 68 78 84 86 83 78 73 63 54 49 51 54 58 61 61 57 54 50 49 46 45 43 39 34 30 28 27 27 28 29 30 31 32 27 26 24 23 21 21 21 21 20 21 23 26 29 31 33 34 38 36 32 26 21 20 22 25 25 25 24 23 22 21 20 20 24 27 31 33 33 32 33 35 37 38 39 39 40 43 47 51 54 55 53 47 38 32 30 31 35 36 35 30 26 26 30 34 47 54 64 72 72 65 55 48 41 38 34 31 29 29 30 31 29 31 33 32 31 29 30 31 29 31 34 37 37 36 34 32 29 25 22 19 18 16 13 11 16 16 16 16 17 18 19 20 20 20 20 19 18 20 24 28 28 30 31 29 25 21 18 17 14 15 17 18 19 19 20 19 21 22 24 25 26 26 25 24 25 24 21 19 16 14 13 13 11 11 12 12 13 14 14 14 18 18 18 17 16 15 13 12 11 12 13 14 13 12 10 9 9 9 8 7 6 6 5 4 6 6 6 5 5 4 4 4 5 5 5 5 5 5 5 5 5 5 5 4 4 3 3 3 4 4 4 4 4 4 4 4 5 5 5 4 4 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 Sigima-1.1.1/sigima/data/tests/image_formats/gaussian_spot_with_noise.ima000066400000000000000000010010001514013333200266460ustar00rootroot00000000000000 C Bruit impulsionnel de Tache gaussienne, Amp=10 lsb, lmh=128 pixels @Y@@@p@p@?p@?p@??@pix pix lsb K'=m.=V6===F=sN=m'W=%`==pi=-s=!|=H=׈=OF=ߓ=ʢ=A===,m=====E{= ===#=E=>zF> >O>0>>[>B#>D(>E->3>`8>=>\C>#H> N>GT>rZ>Mq`>@f>l>r>Ey>>>/\>>>Kg>Г>A>ù>|8>g> H>ר>ul>4>>A> >>/,>">+x>>>dd>P> >9>(>)]>0>h>z>OV>P> >v>?Ӏ?]?V?f9?1?_; ? ? ?؁?4?I/?w?b???3?G?P?M?C??$??,??<??{ ?!?!?!?W"?"?"?*#?T#?Hq#?q#?q#?Hq#?T#?*#?"?"?W"?!?!?!?{ ??<??,??$?C??M?P?G?3???b?w?I/?4?؁? ? ?_; ?1?f9?V?]?Ӏ??v> >P>OV>z>h>0>)]>(>9> >P>dd>>>+x>">/,>> >A>>4>ul>ר> H>g>|8>ù>A>Г>Kg>>>/\>>>Ey>r>l>@f>Mq`>rZ>GT> N>#H>\C>=>`8>3>E->D(>B#>[>>0>O> >zF>>E=#=== =E{=====,m===A=ʢ=ߓ=OF=׈=H=!|=-s==pi=%`=m'W=sN=F===V6=m.=K'=m.=6=>=>j7 >G>>#>(} >%>5*>0>h5>:>y@>(F>oK>Q>HW>]> d>Lj>p>w>!}>>&t>ֈ>B>>\7>޾>N>Q>c>h+>ר>X>@B>>A>=>rM>E>>S>J>YQ>>>a>>eF>>2>6{>+>>w>w>P?#???<? ?O ?) ??M?,?#P??.???(3?u????u ?!?"?&#?#?@$?%?X;&?&?'?J(?(?)?Bx)?r)?*?U*?[*?*?*?*?*?[*?U*?*?r)?Bx)?)?(?J(?'?&?X;&?%?@$?#?&#?"?!?u ????u?(3???.??#P?,?M??) ?O ? ?<???#?P?w>w>>+>6{>2>>eF>>a>>>YQ>J>S>>E>rM>=>A>>@B>X>ר>h+>c>Q>N>޾>\7>>B>ֈ>&t>>!}>w>p>Lj> d>]>HW>Q>oK>(F>y@>:>h5>0>5*>%>(} >#>>G>j7 >>2>=,=O=\==X&=n=KR=k2=FC=H==\=)b=]==ڎ=Z=x=}=ܰs=i=w`=W=N==6=m.=V6=>=>MF=N=¼W=\`=pcj=/t=N~=a=ʼn=V==h=4=^=3֭=}=iV=`==s =2====`F=>Bi> >>b^>B<>5>J">{'> ,>{.2>C7>EO=>ZC>QH>N>T>$Z>4a>xg>m>t>"{>>NT>Ƈ>D>̎>&_>t>>>P>>ZǤ>ώ>]>2>> >ֻ>>>>#>[>>u>z>s>k>2a>T>xC>.>>D>3>P?96??,? ?P ?f ?+???#P???-??C???)?ُ? ?:"?q#?@$?%?u'?J(?? )?*?+?Y+?Y,?Ny-?..?X.?l/?/?3o0?T0?\61?21?1?1? 2?A2?A2? 2?1?1?21?\61?T0?3o0?/?l/?X.?..?Ny-?Y,?Y+?+?*?? )?J(?u'?%?@$?q#?:"? ?ُ?)??C???-???#P???+?f ?P ? ?,??96?P?3>D>>.>xC>T>2a>k>s>z>u>>[>#>>>>ֻ> >>2>]>ώ>ZǤ>>P>>>t>&_>̎>D>Ƈ>NT>>"{>t>m>xg>4a>$Z>T>N>QH>ZC>EO=>C7>{.2> ,>{'>J">5>B<>b^>> >Bi>>`F====2=s ==`=iV=}=3֭=^=4=h==V=ʼn=a=N~=/t=pcj=\`=¼W=N=>MF=>=V6===u>- >>>>[>$>M)>ѷ.>f>4>9>Z?>}E>uK>UQ>W>d^>pmd>ej>q>|Bx>>> >1 >>/I>p>a>v>D>a>>6>zׯ>Nг>-з>ֻ>>> >r%>~C>dd>{>>{>>>g?>`>c>P>հ>???{??i ? ?D??w?EP?!??ȭ?g???_ ?!?q#?$?t&?'?=)?"*?u+?9-? =.?\/?3o0?s1?zj2?R3?,4?[4?5?db6?7?7?8?~8?8?.9?$o9?]9?9?9?9?9?]9?$o9?.9?8?~8?8?7?7?db6?5?[4?,4?R3?zj2?s1?3o0?\/? =.?9-?u+?"*?=)?'?t&?$?q#?!?_ ???g?ȭ??!?EP?w??D? ?i ??{????հ>P>c>`>g?>>>{>>{>dd>~C>r%> >>>ֻ>-з>Nг>zׯ>6>>a>D>v>a>p>/I>>1 > >>>|Bx>q>ej>pmd>d^>W>UQ>uK>}E>Z?>9>f>4>ѷ.>M)>$>[>>>>- >u>>9=ĝ=9=B = =wS==n=~J=DY=n=D ==섛=/====~=Zt=dj=Xa=sW=N=>O >,$>4>%>vS >%><+>0>46> ;>A>G>bM>H.T>nZ>`>xg>7n>!u>'{>5s>>Z>B>> >F>Z>=>[+>@#>%>40>OD>`>=>>>=>Z>ʝ>\>0>~>C>P!>6t>7>>j>A>?}&?-H?'g??P ? ?????,?ؾ???n?C ?"?#?ގ%?b?'?(?[*? ,?`-?/?}~0?1?33?{4?5?6?7?9?:?;?;??>?m????g@?.@?A?aA?A?A?`A?`A?A?A?aA?A?.@?g@???m??>?3>?~=?j>>7>6t>P!>C>~>0>\>ʝ>Z>=>>>=>`>OD>40>%>@#>[+>=>Z>F> >>B>Z>>5s>@@7n>xg>`>nZ>H.T>bM>G>A> ;>46>0><+>%>vS >%>4>,$>O >>>=C=z=m=/W=w="=q\= =2=%A==K/====lU=ӄ=7~=t=j=Xa=¼W=N=F=sN=W=\`=dj=t=P==ey=6=#=B=Ƒ=&=ʯ=9=ӽ=)=2=x=t=====>5>$\ >F>O>iw>7!>$'>,>^M2>8>=>{C>J>VP>V>/3]>Sc>j> bq>Wx>5k>M>>>i>9>s>>>~>>>>>`k>> >N,>}>>#7>ʝ>C >{> >k> >wh>>{k>>n>j?96?zs?? ? ?~P????c?T?_$?4?<?>!?8#?*%?'?O(?I*?n,?T[.?0?1?{b3?[4?6?7?$o9?:? '?B??@?A?B?C?D?E?AIF?WF?G?;H?H?H?BTI?I?I?|I?J?J?|I?I?I?BTI?H?H?;H?G?WF?AIF?E?D?C?B?A?@?B??>?.n=? '!?<?4?_$?T?c????~P? ? ??zs?96?j?n>>{k>>wh> >k> >{>C >ʝ>#7>>}>N,> >>`k>>>>>~>>>s>9>i>>>@@Wx> bq>j>Sc>/3]>V>VP>J>{C>=>8>^M2>,>$'>7!>iw>O>F>$\ >5>>====t=x=2=)=ӽ=9=ʯ=&=Ƒ=B=#=6=ey==P=t=dj=\`=W=sN=m'W=w`=pcj=Zt=7~==e=O=K=3x=Bآ="l=4=3=g==x=JV=m==M=O=>Ѱ>q >Q>Q>q>m>#>(>/.>a3>9>0?>kE>*8L>XR>Y>_>@f>im>lt>{>g>>ֈ>/>S>j>c>i>Y|>>Dɨ>>F>T>>tU>>W;>n>~C>>i>F>ߦ>'M>h>>T>> >??'g?1? ?f ?Է??EP??R??RO??!?#?e%? (?*? ,?.?0?f1?3?5?7?>9?M:?I????@A?B?zD?hjE?pF??G?I?&J?c-K?k$L? M?yM? N?dXO?QO?P?L Q?vQ?Q?R?JPR?tR?R?R?tR?JPR?R?Q?vQ?L Q?P?QO?dXO? N?yM? M?k$L?c-K?&J?I??G?pF?hjE?zD?B??@A???@@@>9?7?5?3?f1?0?.? ,?*? (?e%?#?!??RO??R??EP??Է?f ? ?1?'g??? >>T>>h>'M>ߦ>F>i>>~C>n>W;>>tU>>T>F>>Dɨ>>Y|>i>c>j>S>/>ֈ>>g>{>lt>im>@f>_>Y>XR>*8L>kE>0?>9>a3>/.>(>#>m>q>Q>Q>q >Ѱ>>O=M==m=JV=x==g=3=4="l=Bآ=3x=K=O=e==7~=Zt=pcj=w`=m'W=%`=i=/t=~=ӄ=ey=O= X=R==㦩=&=]={۾=n]==q=?A=_=Z=C=>Bi>< >0>D>z>[>G$>)>v/>w5>u;>A>G>;N>T>i[>M2b> i>")p>RVw>W~>q >І>>鎎>6>>>>>1>~>zׯ>~=>>->>@J> >[>?>(>a>>'M>O >Y>>>2> =?{?!? ?k ?u??#P?ȹ?[ ?f?o?<?!?#?,&?p(?*?C,?/?\61?R3?>f5?o7?$o9?c;?]M=?X+??Q@?B?{D?&F?G?BTI?qJ?GL?M?N?rBP?vQ?:R?S?T? U?{V?cHW?:X?X?OBY?;Y?7Z?+Z?Z?[?@[?S[?S[?@[?[?Z?+Z?7Z?;Y?OBY?X?:X?cHW?{V? U?T?S?:R?vQ?rBP?N?M?GL?qJ?BTI?G?@@@Q@?X+??]M=?c;?$o9?o7?>f5?R3?\61?/?C,?*?p(?,&?#?!?<?o?f?[ ?ȹ?#P??u?k ? ?!?{? =?2>>>Y>O >'M>>a>(>?>[> >@J>>->>~=>zׯ>~>1>@@>>6>鎎>>І>q >W~>RVw>")p> i>M2b>i[>T>;N>G>A>u;>w5>v/>@@[>z>D>0>< >Bi>>C=Z=_=?A=q==n]={۾=]=&=㦩==R= X=O=ey=ӄ=~=/t=i=%`==pi=ܰs=N~==lU=6=K=R==Kĩ= =ҷ=;.==D===w='?=`F=G>w > >>>0j>>e%>+>o0>6>T<>;C>I>v P>#V>]>uk>r>uz>fˀ>*>w>Og>Kg>w>> Ȝ>>\V>⳩>>ƙ>R!>>\W>> >J>Q>)> >g> >>z>>D>?"???f/ ?ۻ ?G?,?]?O?Dk??n? ?c#?%?E(?*?9-?l/?1? 4?R6?8?:?>z>> >g> >)>Q>J> >>\W>>R!>ƙ>>@@> Ȝ>>w>Kg>Og>w>*>fˀ>uz>r>uk>]>#V>v P>I>;C>T<>6>@@e%>>0j>>> >w >G>`F='?=w===D==;.=ҷ= =Kĩ==R=K=6=lU==N~=ܰs==pi=-s=}=a===#=3x==Kĩ=]==_= ===/v=;===v>> >>:>@> >@h&>1,> 2>08>f>>D> AK>/Q>X>˛_>6f>Dm>@u>|>l2>h>1 >>t,>V>>Rݞ>9>ǥ>!>F>G>>>l>>>>>>D> >P!>?>af>>>?â?BE??O ?5 ?4?z?Y+?[?v??W?W"?`$?'?*?c,?R//?[1?,4?6?9?t;?=?l$@?nB?D?F?I?c-K?.@M?nFO??Q?f+S?1 U?V?(X?wJZ?[?}]?^? o`? a?c?[Wd?݀e?f?4g?h?ki? 6j?j?k?l?l?m?Rm?}m?m?Dm?Dm?m?}m?Rm?m?l?l?k?j? 6j?ki?h?4g?f?݀e?[Wd?c? a? o`?^?}]?[?wJZ?(X?V?1 U?f+S??Q?nFO?.@M?c-K?I?F?D?nB?l$@?=?t;?9?@,4?[1?R//?c,?*?'?`$?W"?W??v?[?Y+?z?4?5 ?O ??BE?â??>>af>?>P!> >D>>>>>>l>>>G>@@ǥ>9>Rݞ>>V>t,>>1 >h>l2>|>@u>Dm>6f>˛_>X>/Q> AK>D>f>>@@1,>@h&> >@>:>> >>v>==;=/v==@ =_==]=Kĩ==3x=#===a=}=-s=!|=x=ʼn===B=Bآ=㦩= ==p=,=%=K^====Q='> > >T=>j>>2!>O'>/->53>`9>?>(F>L>S>rZ>1a>&h>Tp>w>>>>r>>>ݓ>!>v>ݠ>\V>>nz>A%>>>=>l>?c>g>y>D>n>>M7>>u>1>2>Ӏ?9?\?W ?8s ?4??ȹ?|?C??? ?q#?X;&?O(?Щ+?T[.?R1?A3?R6?8?L;?>?@?JC?E?G?ZJ?L?N??Q?tS? U?jW?;Y?[?D]?_?cla?Z/c?d?f?h?i?dk?\l?m?n?o? q?$r?=r?s?ot?!)u?u?=v?v?-v?h>w?Diw?~w?~w?Diw?h>w?-v?v?=v?u?!)u?ot?s?=r?$r? q?o?n?m?\l?dk?i?h?f?d?Z/c?cla?_?D]?[?;Y?jW? U?tS??Q?N?L?ZJ?G?E?JC?@?>?L;?8?R6?A3?R1?T[.?Щ+?O(?X;&?q#? ??C??|?ȹ??4?8s ?W ?\?9?Ӏ?2>1>u>>M7>>n>D>y>g>?c>l>=>>>A%>nz>>\V>ݠ>v>!>ݓ>>>r>>>>w>Tp>&h>1a>rZ>S>L>(F>?>`9>53>/->O'>2!>>j>T=> > >'>Q====K^=%=,=p== =㦩=Bآ=B===ʼn=x=!|=H=Z=V=/==Ƒ="l=&=ҷ=_=,=7==H===N=v>i>[ >a>)>>J">(>.>.4>r:>@>(pG>)N>U U>p\>SEc>j>r>y>fˀ>&DŽ>ֈ>>0>y>֙>2F>Ȣ>7]>>>>a>rM>uI>EU>gp>Y>>>k>%>6>.>G.> >}&??F?P ?8s ?M?)?????!?b$?b?'?*?>,?\/?2?>f5?.8?M:?߯=?g@?JC?E?`H?J?\M?W P?R?T? [W?]Y?([?=^? o`?b?d?f?h?Yj?\l? n?o?tq?Js?ot?u?h>w?x?y?z?{?;|?}?_~?.?? ?O?|??˳???˳??|?O? ??.?_~?}?;|?{?z?y?x?h>w?u?ot?Js?tq?o? n?\l?Yj?h?f?d?b? o`?=^?([?]Y? [W?T?R?W P?\M?J?`H?E?JC?g@?߯=?M:?.8?>f5?2?\/?>,?*?b?'?b$?!?????)?M?8s ?P ?F??}&? >G.>.>6>%>k>>>Y>gp>EU>uI>rM>a>>>>7]>Ȣ>2F>֙>y>0>>ֈ>&DŽ>fˀ>y>r>j>SEc>p\>U U>)N>(pG>@>r:>.4>.>(>J">>)>a>[ >i>v>N===H==7=,=_=ҷ=&="l=Ƒ==/=V=Z=H=׈=ڎ==섛=K/=&=4=]=;.= =%==$= =4==e>> > >+> (>">(>.> 5>e;>A>H>rlO>,kV>]>Od>^l>t>U{>>>(>5Q>>:>u>f>>M>>6>-з>H˼>$>W>r%>d>t>T>> >>U>P>n>8? v?\?ZG ?5 ?(???T?@?"?$?,'?*?-?0?3?"6?9?P>U>> >>T>t>d>r%>W>$>H˼>-з>6>>M>>f>u>:>>5Q>(>>>U{>t>^l>Od>]>,kV>rlO>H>A>e;> 5>.>(>"> (>+> > >>e>=4= =$==%= =;.=]=4=&=K/=섛==ڎ=׈=OF==h===ʯ=3={۾===K^=H= =I==b>-> >l>3>>d#>\)> }/>w5><9<>B>I>ČP>W>^>Q^f>m>wu>}>f>> >D>7>+>Ip>j>c>X>%>4>D>>>uI>>>?>v>9>T>6t>'>>A>??ø? ?ۻ ?H???? ?f!?:"?U%?p(?+?.?1?4?7?;?>?A?x&D?)G?&J?M?W P?R?U?X?y[?=^?R`?c? Hf?%h?Hgk?m?XPp? r?t?h>w?my?b{?}??@@z?c?0???Z?0??#?ѥ?i?}??:?????+?7?7?+?????:??}?i?ѥ?#??0?Z???0?c?z????}?b{?my?h>w?t? r?XPp?m?Hgk?%h? Hf?c?R`?=^?y[?X?U?R?W P?M?&J?)G?x&D?A?>?;?7?4?1?.?+?p(?U%?:"?f!? ????H?ۻ ? ?ø???A>>'>6t>T>9>v>?>>>uI>>>D>4>%>X>c>j>Ip>+>7>D>> >f>}>wu>m>Q^f>^>W>ČP>I>B><9<>w5> }/>\)>d#>>3>l> >->b>=I= =H=K^==={۾=3=ʯ===h==OF=ߓ=]=4=D =%A=9=g=n]=D====4==>>j7 >Y>/>@#>')>0>9d6><>C>J>UQ>X>#`>g>&no>RVw>5k>lփ> >&[>>9>2ə>[o>[+>>!>v>>>Q>9>> w>>>D>>v>.>P>2>???k ?"?E?l?)???,"?c%?(?u+?/?K2?5?8?(;?X+??]B?E?H?K?N?R?.U?g;X?@[?=^?1a? d?f?i?l?Vo?$r?Щt?h>w?Sy?:|?ȡ~?|?̞??Ƀ?Rф?@@?%?c?.??̣?M??~??!?k?S??k?3?e?e?s???s?e?e?3?k??S?k?!??~??M?̣??.?c?%??Æ?mυ?Rф?Ƀ??̞?|?ȡ~?:|?Sy?h>w?Щt?$r?Vo?l?i?f? d?1a?=^?@[?g;X?.U?R?N?K?H?E?]B?X+??(;?8?5?K2?/?u+?(?c%?,"???)?l?E?"?k ????2>P>.>v>>D>>> w>>9>Q>>>v>!>>[+>[o>2ə>9>>&[> >lփ>5k>RVw>&no>g>#`>X>UQ>J>C><>9d6>0>')>#>>/>Y>j7 >>>=4====D=n]=g=9=%A=D =4=]=ߓ=ʢ=)b=^=n=2=ӽ====/v====b>>C >ø>V>>$>**>p0>6>=>rJD> AK>dR>Y>4a>}h>p>x>a}>&>+>n[>ӑ>c>G >ǟ>>ˇ>>>ϸ>>l>O>^>>>`>2>>; >>->?{?? ?)D?z?5??C???!?*%?](?u+?R//?h2?%5?>9?I9?%5?h2?R//?u+?](?*%?!??C???5?z?)D? ??{??->>; >>2>`>>>^>O>l>>ϸ>>>ˇ>>ǟ>G >c>ӑ>n[>+>&>a}>x>p>}h>4a>Y>dR> AK>rJD>=>6>p0>**>$>>V>ø>C >>b>===/v====ӽ=2=n=^=)b=ʢ=A=\=3֭=DY= =)=x=q==;==N=e>->j7 >ø>c>H9>9$>e*>y0>A7>=>D>K>:S>nZ>b>]i>q>z>/>&t>qЉ>D>uђ>&v>2>>:>>u>G>'>y>fk>>ʝ>W>f&> >>N >+>>]>!?$?J(?+?/?y2?5?$o9?!??v??/?s?) ? ??z?]>+>N >> >f&>W>ʝ>>fk>y>'>G>u>>:>>2>&v>uђ>D>qЉ>&t>/>z>q>]i>b>nZ>:S>K>D>=>A7>y0>e*>9$>H9>c>ø>j7 >->e>N==;==q=x=)= =DY=3֭=\=A===}=~J=q\=2=JV=?A=w==Q=v>> >Y>V>H9>G$>*>o0>7>E>>9E>[L>S>0[>b>j>r>"{>́>">>> >Ip>|B>->1>N>>Ҷ>J8>>L> >˾>>>>>.>z>;*>>j?9?? ?/?,??Dk?o?_ ?#?j'?*?.?A2?5?O9??M??Ӛ?;? u?H3??9? ??e'???K?‘?ɡ???????ɡ?‘?K???e'?? ?9??H3? u?;?Ӛ??M?>???=Д?ب? w?#;?k?0?M?v?????X??f??P|?y?u?Fr?n?Hgk?g?$kd?`?LW]?;Y?P1V?:R?N?9bK?G?x&D?i@?;*>z>.>>>>>˾> >L>>J8>Ҷ>>N>1>->|B>Ip> >>>">́>"{>r>j>b>0[>S>[L>9E>E>>7>o0>*>G$>H9>V>Y> >>v>Q==w=?A=JV=2=q\=~J=}====H=iV=n="=x=m=_='?=='>@@@/>>9$>*>0>Y7>hw>>}E>*L>T>-[>mc> ~k>hs>|>HT>p>z8>wя>s>vQ>|8>9>oT>6>ײ>?>D>[>>>{>(>|> >g?>>>E?K?{?ZG ? ?"?s?[ ??<?"?t&?*?-?s1?k'5?8?I?B??Y?Fk?T?ש?#;?Ï?rC?&?+?h??1O?R?m?9?~?v{?w?Ut?p?m?ki?e?b?'Q^?+Z?V?S?dXO?K?G?zD?dV@?I>g?> >|>(>{>>>[>D>?>ײ>6>oT>9>|8>vQ>s>wя>z8>p>HT>|>hs> ~k>mc>-[>T>*L>}E>hw>>Y7>0>*>9$>>/>l> >i>'>='?=_=m=x="=n=iV=H==,m=FC=`==w=t==Z=`F=v> >@@@>$>e*>o0>Y7>>>E>fL>veT>p\>c> l>Wt>|>dł>:>ɋ>s>9>8>j>*>[>Χ>>8>N,>>S>ʝ>ڡ>3>y>HD>5>)>>???J ?y???(3??!?8%?O(?Y,?}~0?4L4?8?(;?B??C?G?sK?dXO?=S?#W?[?t^?b?f?Yj?^n?1r?u?Sy?}??t?G?? ݇?T?G[??꾎?e?? ?*?K?,???@@ ?(C?u??R?Ť?sǥ?T??~?aK?{ ??^?a?y?`?cZ???@)>5>HD>y>3>ڡ>ʝ>S>>N,>8>>Χ>[>*>j>8>9>s>ɋ>:>dł>|>Wt> l>c>p\>veT>fL>E>>>Y7>o0>e*>$>>3> >[ > >v>`F=Z==t=w==`=FC=,m==k2==wS=/W==M=C=G>> >@@@#>**>y0>7>hw>>E>(L>GT>M\>Ed>csl>t>3p}>( >>B>>}ԕ>+ǚ>՟>>*G>˩>T(>º>x>@J>#7>!?>a>_>>wh>e>T>S>#?? ? ?I/??|?2??%#?'?_+?>/?Z$3?7?;?>?B?WF?J?N?S?vW?[?m%_?Z/c?7g?>k?DBo?|Bs?h>w?D5{?I&?X?y??g?(P?-4???꾎?e?P?T?ƕ?t??4?hL? ם?W?>Π?@@?:?x?U?ϩ??a?`??RĮ?И?_??ܿ? Z?i?a?γ?,?/z?Ÿ??!???!??Ÿ?/z?,?γ?a?i? Z?ܿ??_?И?RĮ??`?a??ϩ?U?x?:???:?>Π?W? ם?hL?4??t?ƕ?T?P?e?꾎???-4?(P??g?y?X?I&?D5{?h>w?|Bs?DBo?>k?7g?Z/c?m%_?[?vW?S?N?J?WF?B?>?;?7?Z$3?>/?_+?'?%#??2?|??I/? ? ??#?S>T>e>wh>>_>a>!?>#7>@J>x>º>T(>˩>*G>>՟>+ǚ>}ԕ>>B>>( >3p}>t>csl>Ed>M\>GT>(L>E>hw>>7>y0>**>#>>+>a> >>G>C=M==/W=wS==k2===KR=s = =m==O=>w > >T=>)> (>d#>')>p0>A7>E>>}E>fL>GT>`\>pmd>l>+u>}>dd> >/>n>V>Z>Y|>>2>>$$>ֻ>ȥ>>4>>>\> >h>>>?_??8 ?"???M?H?!?%?)?x-?[1?5?9?=?A?F?&J?KN?tR?ƠV?Z?^?Z/c? `g?k?žo?Ss?x?:|?A.?e>h> >\>>>4>>ȥ>ֻ>$$>>2>>Y|>Z>V>n>/> >dd>}>+u>l>pmd>`\>GT>fL>}E>E>>A7>p0>')>d#> (>)>T=> >w >>O==m= =s =KR===n=2=B =z==>Bi> >>j>>">\)>0>6>=>9E>*L>veT>M\>pmd>cl>Vu> ~>>0>_>FǑ>޾>Hԛ>>X>oȫ>U>>H˼>>>>>z>g>>xC>t>:>?.?4 ?t ??]?-? ??#?'?Y+?/? 4?.8?Wt>xC>>g>z>>>>>H˼>>U>oȫ>X>>Hԛ>޾>FǑ>_>0>> ~>Vu>cl>pmd>M\>veT>*L>9E>=>6>0>\)>">>j>> >Bi>>=z=B =2=n===X&==9=C==Ѱ>< >>:>>J">(> }/>9d6>=>D>[L>T>p\>Ed>l>Vu>6~>è>iT>>>{>O >2>ew>ڦ>]>K>A>e>> >]>W>T>k>#>Y>B>^>#?ø?Ok ?+????׮?!?%?r)?-?A2?R6?7:?>?2(C?nG?K?rBP?T?Y?ܐ]?b?f?dk?|o?vt?x?|??? 9?Xs?A?W?-?T@?\j?ԏ?K?P˘?q?=?B??5?B?ʦ?U??L??zƯ?r???2?}???Ի?<?S?D}? ?գ?!?Č?i?!6?n?:?V9???7:?R6?A2?-?r)?%?!?׮????+?Ok ?ø?#?^>B>Y>#>k>T>W>]> >>e>A>K>]>ڦ>ew>2>O >{>>>iT>è>6~>Vu>l>Ed>p\>T>[L>D>=>9d6> }/>(>J">>:>>< >Ѱ>=C=9==X&==E{===ĝ==>q >0>>@>2!>(>.>w5><>rJD>K>S>-[>c>csl>+u> ~>è>9`>6>t,>A>v>kˡ>9@>'լ>M>_>tU>{k>ġ>=>n>F>>F>O>P>zf??F?O ?`?`C?3?1?<?T#?by'?Щ+?/?,4?~8?O>F>>F>n>=>ġ>{k>tU>_>M>'լ>9@>kˡ>v>A>t,>6>9`>è> ~>+u>csl>c>-[>S>K>rJD><>w5>.>(>2!>@>>0>q >>=ĝ===E{= =\==9=>5>Q>D>0j> >O'>.> 5><9<>C> AK>:S>0[>mc> l>t>}>>iT>6>9>[>P>>>/>>߸>>>?c>>a>8>>>> >:??1?K ??v?|??2 ?$?? )?Gj-?1?9#6?7:?; ??C?;H?L?QQ?U?Z?u__? d?%h?m?pr?h>w?H|?p?ڂ?D???<~? ?G?ب??a?4?q ?W?ß???R???RĮ?qٰ?i???͸???S??f?j????$v?l?d#?b????ڿ??k??O??}?B??4????Q:? M? M?Q:????@@@}??O??k??ڿ????b?d#?l?$v????j?f??S???͸???@qٰ?RĮ???R???ß?W?q ?4?a??ب?G? ?<~???D?ڂ?p?H|?h>w?pr?m?%h? d?u__?Z?U?QQ?L?;H?C?; ??7:?9#6?1?Gj-?? )?$?2 ??|?v??K ?1??:? >>>>8>a>>?c>>>߸>>/>>>P>[>9>6>iT>>}>t> l>mc>0[>:S> AK>C><9<> 5>.>O'> >0j>D>Q>5>>9==\= ==O=`F=>>$\ >Q>z>>@h&>/->.4>e;>B>J>dR>nZ>b> ~k>Wt>3p}>dd>0>>>t,>[>㬜>>N>'k>OD>?>^>>> >0>> >>]*>}>j?? ? ?r??ȭ??"?)X&?*?/?3?7?]*>> >>0> >>>^>?>OD>'k>N>>㬜>[>t,>>>0>dd>3p}>Wt> ~k>b>nZ>dR>J>B>e;>.4>/->@h&>>z>Q>$\ >>>`F=O===,=>u>O >F>q>[>e%>1,>53>r:>A>I>UQ>Y>b>j>hs>|>( > >_>{>A>P>>§>6>r>%>>>}>*>2>>>>?>հ>â?s~?@@@?d??T#?v'? ,?0?k'5?9?d>?JC?G?`L?vQ?qVV?@[?4`?a1e? 6j?DBo?Ut?my?~?ց?i?0?h?!)?꾎?PT??|? ??0)?c?7??5?׬?Y???LK???12?:m?v?f??n??x??ƻ?D?P???B??7A?? ?C?v?l?G???Ji?.??? ?Ƃ??6?r? ??? ?r?6??@@@?.?Ji???G?l?v?C? ??7A??@@@P?D?ƻ??x??n??f?v?:m?12???LK???Y?׬?5??7?c?0)?? ?|??PT?꾎?!)?h?0?i?ց?~?my?Ut?DBo? 6j?a1e?4`?@[?qVV?vQ?`L?G?JC?d>?9?k'5?0? ,?v'?T#??d??w?)i?Ok ?s~?â?հ>?>>>>2>*>}>>>%>r>6>§>>P>A>{>_> >( >|>hs>j>b>Y>UQ>I>A>r:>53>1,>e%>[>q>F>O >u>>,==#==Bi>- >,$>O>m>G$>+> 2>`9>@>H>ČP>X>4a>]i>r>|>dł>>/>FǑ>O >v>>N>6>z>L>>@J>>>z^>Y>z>>;*> >96?!? ?@@@?S ?4$?O(?Ny-? 2?w6?c;?l$@?D?I?N?S?X?D]?b?g?m?Fr?~w?;|??p?1O??̣?O?G?ب?U?M?;?QR???:?2֨?m??匰??????K?գ??@@??? ?4??K?M?^I? ??7??.???@@ d?_j?]?R=?{ ??$f?J?r??V,?j? ?̨?̨? ?j?V,??r?J?$f??{ ?R=?]?_j? d?J????.??7?@@@M?K??4? ????p?7??գ?K??????匰??m?2֨?:???QR?;?M?U?ب?G?O?̣??1O?p??;|?~w?Fr?m?g?b?D]?X?S?N?I?D?l$@?c;?w6? 2?Ny-?O(?4$?S ???#P?/? ?!?96? >;*>>z>Y>z^>>>@J>>L>z>6>N>>v>O >FǑ>/>>dł>|>r>]i>4a>X>ČP>H>@>`9> 2>+>G$>m>O>,$>- >Bi>=#=E=2> >>4>iw>#>)>o0>08>?>(pG>rlO>W>#`>}h>q>"{>HT>:>B>n>޾>2>kˡ>>'k>r>L>y>l> >`>(>C>>af>B>2>?? ?4?@@@!?ގ%?*?.?{b3?8?Ee?Yj?o?!)u?az??m??g?#???e? )??ذ?Rt?6??R?(t? .?{?떮?D??琶?-?bĻ?S??Y?$?Ee? `?Z?U?ѮP?K?pF?`A?B>af>>C>(>`> >l>y>L>r>'k>>kˡ>2>޾>n>B>:>HT>"{>q>}h>#`>W>rlO>(pG>?>08>o0>)>#>iw>4>> >2>E=>>>>%>7!>(>v/>6>f>>(F>)N>,kV>^>g>p>z>́>p>ɋ>>V>Hԛ>ew>9@>/>OD>%>>l>>> >>l>z>́>#?]?$?!B ?s?5?T?;x?!?k&?)$+?/?`4?$o9?T>?JC?EOH?cM?R?jW?@@4g?m?pr?w?m}?}?G???&?ő?\j?uD??I? ם?c?ʌ?e??$o9?`4?/?)$+?k&?!?;x?T?5?s?!B ?$?]?#?́>z>l>> >>>l>>%>OD>/>9@>ew>Hԛ>V>>ɋ>p>́>z>p>g>^>,kV>)N>(F>f>>6>v/>(>7!>%>>>>>zF>j7 >b^>>vS >$'>/.>w5>T<>D>L>U U>]>Q^f>&no>x>/>">z8>s>}ԕ>Z>>ڦ>'լ>>?>>@J> >> >D>l>7>>zf?j?? ?r?5E?ȭ?)?"?_\'? ,?T0?5?b:?m??D?I?N?>T?Y?t^?@@Wo?qt?@@m?mυ???!?m?`\?HM???H3?e'??S??a??Dϱ?Ÿ???\?4?i?$??O??ĭ?N??r??]i??.?}??'??w(?V,?????>??_??J2?|}?Z@@Aq@@]@k@-@m@/@@@@OR@]@]@OR@c;@@I@/@m@-@k@]@@Aq@@Z@|}?J2??_??>?????V,?w(??'??}?.??]i??r??N?ĭ??O??$?i?4?\???Ÿ?Dϱ??a??S??e'?H3???HM?`\?m?!???mυ?m? ?az?qt?Wo?i?[Wd?t^?Y?>T?N?I?D?m??b:?5?T0? ,?_\'?"?)?ȭ?5E?r? ??j?zf?>7>l>D> >> >@J>>?>>'լ>ڦ>>Z>}ԕ>s>z8>">/>x>&no>Q^f>]>U U>L>D>T<>w5>/.>$'>vS >>b^>j7 >zF> >G>B<>[>%>,>a3>u;>;C> AK>S>p\>Od>m>RVw>a}>&t>>wя>9>+ǚ>Y|>X>]>M>߸>^>>>`> >D>>`>G.>?? ? ? U?ȹ?(3??c#?J(?C,?1?w6?;?.@?mE?c-K?xP?U?@[?`? Hf?@@h>w?|?@@oD?:?I5?3?5?:?B?hL?W?Ed?[q?~?7?떮???}??뮽?Ш???$v?{X?n3?f???^I?b?l?.?5?6??{ ?w]?y??n?V?/?}???8@y @X@!@K@@*@,@@A7@@@r@@ @@@@@Ѽ@Ѽ@@K@u@F@ @@r@@@A7@@,@*@@K@!@X@y @8@??}?/?V?n??y?w]?{ ??6?5?.?l?b?^I???f?n3?{X?$v???Ш?뮽??}???떮?7?~?[q?Ed?W?hL?B?:?5?3?I5?:?oD?R?f?|?h>w?tq?k? Hf?`?@[?U?xP?c-K?mE?.@?;?w6?1?C,?J(?c#??(3?ȹ? U? ? ???G.>`>>D> >`>>>^>߸>M>]>X>Y|>+ǚ>9>wя>>&t>a}>RVw>m>Od>p\>S> AK>;C>u;>a3>,>%>[>B<>G> >O>>5>$><+>^M2>9>A>I>/Q>rZ>SEc>^l>wu>5k>&>qЉ>>s>8>՟>>oȫ>K>_>>>}>>(>>l>`>C>K?{?z?;B ???.?<?#?̹(?`-?@@@*A?G?7kL?Q?cHW?7\?jb?h?Dm?ٖs?my?R???ѥ?寋?꾎?qґ? ?>?#?D?g???9٪??&?LK?n?G?뮽?6??W?? ?K ???.??!?Ak?.??Ւ?e2??~I?ؿ?M'?L?E??%?ڜ@%@!@@>i@C@b@p@@F@<@̆ @ @ @5 @~ @ @4 @} @@@@X( @4 @4 @X( @ @? @q @} @4 @ @~ @5 @ @ @̆ @<@F@@p@b@C@>i@@!@%@ڜ@%??E?L?M'?ؿ?~I??e2?Ւ??.?Ak?!??.???K ? ??W??6?뮽?G?n?LK?&??9٪???g?D?#?>? ?qґ?꾎?寋?ѥ???R?my?ٖs?Dm?h?jb?7\?cHW?Q?7kL?G?*A?`>l>>(>>}>>>_>K>oȫ>>՟>8>s>@qЉ>&>5k>wu>^l>SEc>rZ>/Q>I>A>9>^M2><+>$>5>>O>0>#>J">M)>0>8>0?>G>v P>X>1a>j>t>}>lփ>+>D> >vQ>j>>@@@tU>@@*>z^>C>l>7>G.>K??9 ?f ?,?U???b$?=)?..?33?@@@;H?\M?S?(X?=^?c?~i?=o?'~u?v{??Ƀ?ۆ???3?)\?%?S?=?e'?Mb?r?Nީ?Y?_?ɟ??C?\? ???6?b?????>???M???w]???|?/??D?C@Aq@!@/@%@@@@@ @i @`6 @ @@ @LY @ @Œ@@ @+@e@˼@@F@`y@5@s@@@s@5@`y@F@@˼@e@+@ @@Œ@ @LY @@ @ @`6 @i @ @@@@@%@/@!@Aq@C@D??/?|???w]???M???>?????b?6??? ?\?C??ɟ?_?Y?Nީ?r?Mb?e'?=?S?%?)\?3???ۆ?Ƀ??v{?'~u?=o?~i?c?=^?(X?S?\M?;H?B?~=?N8?33?..?=)?b$???U?,?f ?9 ??K?G.>7>l>C>z^>*>>>tU>A>U>2>>j>vQ> >D>+>lփ>}>t>j>1a>X>v P>G>0?>8>0>M)>J">#>0>>(} >{'>ѷ.>46>=>kE>;N>#V>˛_>&h>r>U{>f> >n[>uђ>Ip>|8>*>*G>@@@{k>@@2>Y>>z>>?{?9 ?8s ?s?@@?@$?T)?.?ӿ3?8?@@@AN?T?;Y?-_?Ye?>k?5q?h>w?W}??܄?u?+?\?S?=Д?j?dY???`F??a?L?t??%^???j??y?b?ĭ??4?4o??9?`?? ?w(?%? ??y??Z^?@X@-@]@֔@@7@ @ @B @H @ @ @@@q@-@X@@@@@(@@@]@N@2@1 @;G@Ha@Pn@Pn@Ha@;G@1 @2@N@]@@@@(@@@@X@-@q@@@ @ @H @B @ @ @7@@֔@]@-@X@@Z^??y?? ?%?w(? ??`?9??4o?4??ĭ?b?y??j???%^??t?L?a??`F???dY?j?=Д?S?\?+?u?܄??W}?h>w?5q?>k?Ye?-_?;Y?T?AN?H?C?3>?8?ӿ3?.?T)?@$??_$?|?s?8s ?9 ?{??>z>>Y>2> >?c>{k>e>>>*G>*>|8>Ip>uђ>n[> >f>U{>r>&h>˛_>#V>;N>kE>=>46>ѷ.>{'>(} >>[>%> ,>f>4> ;>{C>*8L>T>]>6f>Tp>y>>> >&[>ӑ>&v>|B>9>[>˩>@@@ġ>>0>>z>af>́>zf??z?f ?s??@@`$?)?/?,4?$o9?>?w7D?I?dXO?1 U?Z?i`?f?l? r?x?.?m?ۅ??M?ő?ܒ?-???(C?#????c?ش?M?bĻ?:??%?? ?w??NG?? ?W?e?\?(?w]?=??ҽ?E?C?Z@@4@*@@C@u@\ @) @4 @LY @t@@@@Ov@k[@5@@@@Y{@6%@@S@@%O@@@g@@@@"@A0@A0@"@@@@g@@@%O@@S@@6%@Y{@@@@5@k[@Ov@@@@t@LY @4 @) @\ @u@C@@*@4@@Z@C?E?ҽ??=?w]?(?\?e?W? ??NG??w? ??%??:?bĻ?M?ش?c????#?(C???-?ܒ?ő?M??ۅ?m?.?x? r?l?@i`?Z?1 U?dXO?I?w7D?>?$o9?,4?/?)?`$?u ?C???s?f ?z??zf?́>af>z>>0>>ġ>>H˼>$$>˩>[>9>|B>&v>ӑ>&[>> >>y>Tp>6f>]>T>*8L>{C> ;>f>4> ,>%>[>B#>5*>{.2>9>A>J>XR>i[>Dm>w>fˀ>>D>>c>2>->oT>Χ>T(>ֻ>> >=>a>>>>B>#?j? ?;B ?,?|?C??S ? %?*?>/?{4?9?;??D?ZJ?W P?U?[?a?Fg?Dm?vt?LFz?O?/?*? %?S ?C??|?,?;B ? ?j?#?B>>>>a>=> >>ֻ>T(>Χ>oT>->2>c>>D>>fˀ>w>Dm>i[>XR>J>A>9>{.2>5*>B#>D(>0>C7>Z?>G>VP>Y>M2b>uk>@u>>>&DŽ>(>7>9>G >>1>6>>º>ȥ>>]>n>8> >>;*>2>]?? ??U?_$?u ? %?(*?\/?4?:?ӎ?? &E?qJ?P?{V?q\?x~b?h?n?!)u?b{??G???O?.?*??#??7?ʦ?b???E??V?D???O??k?]U???5D??/x?{ ? ? ???`l?/e@@/@wO@ @u@' @~ @u @g@K@-@@@@;G@s@@<@m@@@@l@a;@@ @X!@ !@"@"@o#@#@ ($@Lo$@S$@%$@$@$@$@$@%$@S$@Lo$@ ($@#@o#@"@"@ !@X!@@@a;@l@@@@m@<@@s@;G@@@@-@K@g@u @~ @' @u@ @wO@/@@/e@`l??? ? ?{ ?/x??5D???]U?k??O???@@@E???b?ʦ?7??#??*?.?O???G??b{?!)u?n?h?x~b?q\?{V?P?qJ? &E?ӎ??:?4?\/?(*? %?u ?_$?U?? ??]?2>;*>> >8>n>]>>ȥ>º>>6>1>>G >9>7>(>&DŽ>>>@u>uk>M2b>Y>VP>G>Z?>C7>0>D(>E->h5>EO=>}E>bM>V>_> i>r>|>>ֈ>5Q>+>2ə>ǟ>:>N>ײ>8>x>>>W>F>>>?> >?$? ? U????`$?*?\/?4?T0:???hjE?c-K?L Q?V? ]?Z/c?ki?žo?(v?V|?̞?? S??d.?ש?-?S?N???5?{?И? R??к??\?%?x?ƻ?,?Q??>?G?i?'?? ?CA???D?@!@OR@@&@c @) @ @h6@@F@@5@W@@S@@@}@@@>_@r@y @t!@tc"@-E#@$@m$@%@H&@&@w'@|'@o(@X(@4-)@v)@R)@s)@)@ *@ *@)@s)@R)@v)@4-)@X(@o(@|'@w'@&@H&@%@m$@$@-E#@tc"@t!@y @r@>_@@@}@@@S@@W@5@@F@@h6@ @) @c @&@@OR@!@@D???CA? ??'?i?G?>??Q?,?ƻ?x?@@@к?? R?И?{?5???N?S?-?ש?d.?? S??̞?V|?(v?žo?ki?Z/c? ]?V?L Q?c-K?hjE???T0:?4?\/?*?`$???? U? ?$?? >?>>>F>W>>>x>8>ײ>N>:>ǟ>2ə>+>5Q>ֈ>>|>r> i>_>V>bM>}E>EO=>h5>E->3>:>ZC>uK>H.T>/3]>@f>")p>uz>l2>r>>>Ip>[o>>>>?>N,>@J>4>>T>>>]*>հ>96??!B ?r?ȹ?.??@$?)?>/?4?T0:?B??E?9bK?QQ? [W?}]?Mc? j?zp?-v?}?%???r?k?|??4? `??sǥ??^K???н?V?v?~X?@o @"@(#@D$@S%@}V&@1L'@4(@)@s)@2*@N+@+@,@{-@-@-@yJ.@ .@.@ /@b/@-/@-/@b/@ /@.@ .@yJ.@-@-@{-@,@+@N+@2*@s)@)@4(@1L'@}V&@S%@D$@(#@"@o @>@C@s@|@@$@@O2@N@j@@o@:@Q @ @ @ZR@@@l@y @Z^?՛?&??V,?Q?r??̫????K ?@@@v?V?н???^K??sǥ?? `?4??|?k?r???%?}?-v?zp? j?Mc?}]? [W?QQ?9bK?E?B??T0:?4?>/?)?@$??.?ȹ?r?!B ??96?հ>]*>>>T>>4>@J>N,>?>>>>[o>Ip>>>r>l2>uz>")p>@f>/3]>H.T>uK>ZC>:>3>`8>y@>QH>UQ>nZ>Sc>im>RVw>fˀ>h>>0>:>j>[+>ˇ>u>Ҷ>D>>#7>>z>k>F>>}>â?!? ?s?5E?(3?<?b$?T)?/?{4?:???E?sK?vQ? W?z]? d?Yj? q?w?_~?ʖ?r ?}??s?B???W????떮? y?ya?O?C?;?7?6?8?=?B?^I?P?V?Z?]?w]?Y?Q? E?J2?y @@@@@ @1e @h6@+@@@6@@i@@$@@@@h@w4 @!@"@R$@%@d&@ (@4-)@D*@N+@K,@|;-@1.@.@]/@lm0@1@1@V:2@ 2@"3@3@3@ 4@:4@Z4@i4@i4@Z4@:4@ 4@3@3@"3@ 2@V:2@1@1@lm0@]/@.@1.@|;-@K,@N+@D*@4-)@ (@d&@%@R$@"@!@w4 @h@@@@@$@i@@6@@@+@h6@1e @@@@@@y @J2? E?Q?Y?w]?]?Z?V?P?^I?B?=?8?6?7?;?C?O?ya? y?떮????W???B?s??}?r ?ʖ?_~?w? q?Yj? d?z]? W?vQ?sK?E???:?{4?/?T)?b$?<?(3?5E?s? ?!?â?}>>F>k>z>>#7>>D>Ҷ>u>ˇ>[+>j>:>0>>h>fˀ>RVw>im>Sc>nZ>UQ>QH>y@>`8>=>(F>N>W>`>j>lt>W~>*>1 >>y>u>c>>>G>J8>[>S>!?>>g>#>O> >j?s~? ?4?5?ȭ??#?=)?.?,4?9?ӎ??hjE?9bK?vQ?W?]?[Wd?j?tq?{*x?~?m?r??K?#;? ??g?F5? ??ի?zƯ?쾳?h?bĻ?Kп????[/?O?r????W?w(?~I?g?.?N?@@)@p@@ @q @x@@i@A@/@@@X@ @@=P @!@o#@$@d&@'@4-)@*@+@},@H,.@K/@$^0@b1@:Y2@A3@4@4@S5@P6@6@}7@47@l8@8@9@6]9@k9@9@9@9@9@k9@6]9@9@8@l8@47@}7@6@P6@S5@4@4@A3@:Y2@b1@$^0@K/@H,.@},@+@*@4-)@'@d&@$@o#@!@=P @@ @X@@@/@A@i@@x@q @ @@p@)@@@N?.?g?~I?w(?W????r?O?[/????Kп?bĻ?h?쾳?zƯ?ի?? ?F5?g?? ?#;?K??r?m?~?{*x?tq?j?[Wd?]?W?vQ?9bK?hjE?ӎ??9?,4?.?=)?#??ȭ?5?4? ?s~?j? >O>#>g>>!?>S>[>J8>G>>>c>u>y>>1 >*>W~>lt>j>`>W>N>(F>=>\C>oK>T>d^>xg> bq>{>q >w>>ݓ>@@X>!>>'>>>ʝ>a>\>>Y>P>:??Ok ?/??T?)?c#?̹(?..?ӿ3?$o9?;?? &E?c-K?QQ? W?]?$kd?dk?Rq?x?h?5?Æ?^??.?9x?B? ??B?2֨?jӬ?qٰ???<?F??ji???f?B?"???J??W?a?@T?-?/e@@*@@Ѽ@ @ @@@>@@@@vt@K@@E@!@SS#@$@&@4(@)@@+@,@1.@y/@;0@ 2@A3@i4@܃5@6@7@|8@6]9@t.:@k:@;@E<@<@[=@=@1>@>@&>@@@l)?@l)?@?@>@&>@>@1>@=@[=@<@E<@;@k:@t.:@6]9@|8@7@6@܃5@i4@A3@ 2@;0@y/@1.@,@@+@)@4(@&@$@SS#@!@E@@K@vt@@@@>@@@ @ @Ѽ@@*@@/e@-?@T?a?W??J???"?B?f???ji?F??<???qٰ?jӬ?2֨?B?? ?B?9x?.??^?Æ?5?h?x?Rq?dk?$kd?]? W?QQ?c-K? &E?;??$o9?ӿ3?..?̹(?c#?)?T??/?Ok ??:?P>Y>>\>a>ʝ>>>'>>!>X>f>֙>ݓ>>w>q >{> bq>xg>d^>T>oK>\C>#H>Q>$Z>pmd>7n>Wx>g>І>Og>t,>!>@@%>v>ϸ>y>L>>ڡ>_> >xC>B>zf?? ?)i?#P?U?;x?"?J(?`-?33?8?>?D?qJ?L Q? [W?z]?[Wd?dk?Dq?x??c?0??\?R??Ǚ? ?ß?a?y?@@?C?S?E???Pi???p?9?:0?Ւ?J?Y?ż?>?|}?@@B@i@ @@ @@o@l@@ @ @@ @@o @ܩ"@}$@H&@ (@)@l+@{-@+.@R00@1@"3@4@Q5@m.7@l8@9@ۿ:@;@<@=@>@?@uT@@ A@A@JB@B@HC@C@D@FD@@@D@D@D@yD@FD@D@C@HC@B@JB@A@ A@uT@@?@>@=@<@;@ۿ:@9@l8@m.7@Q5@4@"3@1@R00@+.@{-@l+@)@ (@H&@}$@ܩ"@o @@ @@ @@@l@o@@@ @ @i@B@@@|}?>?ż?Y?J?Ւ?:0?9?p???Pi???E?S?C??Dϱ??y?a?ß? ?Ǚ??R?\??0?c??x?Dq?dk?[Wd?z]? [W?L Q?qJ?D?>?8?33?`-?J(?"?;x?U?#P?)i? ??zf?B>xC> >_>ڡ>>L>y>ϸ>v>%>>2F>!>t,>Og>І>g>Wx>7n>pmd>$Z>Q>@ N>HW>4a>ej>!u>5k>>>Kg>V>v>Ȣ>M>4>>>fk> >{>3>>h>t>^>?1? ?w???!?_\'?C,?h2?N8?3>?w7D?ZJ?P?V?}]? d?j?Rq?x?6?y?K!?֊?ԙ?\j?G?b2?0)?,?:?4T?x?@@!?l??9?{? ?Q?"?@@@-A@:B@$7C@$D@E@&E@F@V8G@G@^H@GH@@I@ I@I@@@GJ@GJ@|5J@uJ@I@ I@@I@GH@^H@G@V8G@F@&E@E@$D@$7C@:B@-A@@@8>@=@ef<@;@9@=8@v6@K55@3@1@N0@ .@,@+@4-)@1L'@1b%@o#@t!@r@i@X@A@6%@@@A@i@L @ @q@j@hb@"@C?]A?ɽ?Q:??6?;??N8?h2?C,?_\'?!???w? ?1??^>t>h>>3>{> >fk>>>4>M>Ȣ>v>V>Kg>>>5k>!u>ej>4a>HW>@GT>]>xg>q>'{>M>ֈ>鎎>w>>ݠ>7]>>D>>l>>˾>(>y>wh>>:>#?F?K ?r???!?k&? ,?1?7?~=?C?I?W P?{V? ]?Mc?Yj?tq?x??y?-??꾎?#?%??9??T??D?a?@@f??A?ƻ?=??R??}??x?Y???"@5t@%@@c @2 @ @?@@@@4@f@@@!@F#@&@ (@ *@j,@-@/@1@3@D5@6@8@N:@;@Fl=@8>@uT@@A@mC@FD@yE@:F@MG@|H@I@(J@-`K@]"L@L@}sM@N@-N@N@XDO@9O@2O@6O@:O@:O@6O@2O@9O@XDO@N@-N@N@}sM@L@]"L@-`K@(J@I@|H@MG@:F@yE@FD@mC@A@uT@@8>@Fl=@;@N:@8@6@D5@3@1@/@-@j,@ *@ (@&@F#@!@@@f@4@@@@?@ @2 @c @@%@5t@"@??Y?x??}??R??=?ƻ?A??f??}?a?D??T??9??%?#?꾎??-?y??x?tq?Yj?Mc? ]?{V?W P?I?C?~=?7?1? ,?k&?!???r?K ?F?#?:>>wh>y>(>˾>>l>>D>>7]>ݠ>>w>鎎>ֈ>M>'{>q>xg>]>@rZ> d>m>|Bx>5s>>/>6>>Rݞ>\V>>6>>Q>O>ʝ>>>|>HD>e>>?ø?O ???d?S ?ގ%?)$+?T0?w6?M@IN@XDO@O.P@1Q@Q@ބR@F)S@ջS@fM@]"L@J@I@oH@G@E@~5D@B@A@N|?@=@<@N:@|8@Ο6@ݷ4@2@;0@q.@,@2*@}(@}V&@ ($@ !@@v@A0@@n@A@@@4 @ @u@b@/@O@@?/?S? ???Ak???s??H??F??bɼ?]?B??^?!?5?͞?4?K??Iˎ??K!?c?h?{*x? q? j?Z/c?q\?U?dXO?H?B?e>HD>|>>>ʝ>O>Q>>6>>\V>Rݞ>>6>/>>5s>|Bx>m> d>rZ>Mq`>Lj>t>>>>S>> Ȝ>9>>>-з>>9>^>W>> >5>T>?.?Ok ?`?v?ȭ??4$?*?/?5?;?*A?;H?AN?1 U?[?x~b?ki?zp?w?~?5?0?֊?꾎??Y?Ӛ?B?)?j?ӷ??/z??:m???],????7A? ?? ?o?~I?M'?}?B?h@)@zO@l @4 @x@@@2@S@m@B@r@!@$@d&@|(@+*@z-@K/@r1@S3@S5@7@9@;@=@k?@M>A@mC@D@iF@H@ I@K@L@=M@XDO@@@$R@S@T@U@V@W@KX@X@wY@Z@Z@Z@+[@d[@[@[@[@[@d[@+[@Z@Z@Z@wY@X@KX@W@V@U@T@S@$R@Q@P@XDO@=M@L@K@ I@H@iF@D@mC@M>A@k?@=@;@9@7@S5@S3@r1@K/@z-@+*@|(@d&@$@!@r@B@m@S@@@@x@4 @l @zO@)@h@B?}?M'?~I?o? ?@@7A????],???:m??/z??ӷ?j?)?B?Ӛ?Y??꾎?֊?0?5?~?w?zp?ki?x~b?[?1 U?AN?;H?*A?;?5?/?*?4$??ȭ?v?`?Ok ?.??T>5> >>W>^>9>>-з>>>9> Ȝ>>S>>>>t>Lj>Mq`>@f>p>"{>>Z>i>j>>>ǥ>nz>>H˼>uI>>>f&>>g?>)>S>_?4 ?+?`C?|??T#?O(?.?`4?b:?.@?G?\M?T?Z?a?h?žo?-v?_~?m?Æ??ԙ?#?K?Ӛ? ?E??a?_?ش?%^??E?V9?\?ĭ?v?^I?N$? ?'???J??@m@@u@ @~ @+@@@@4@Dt@@X!@#@F+&@D(@+*@|;-@/@_1@ 4@@6@l8@W:@<@>@@@B@D@zF@AMH@uJ@K@}sM@O@P@R@ӄS@%T@@@X@-Y@۹Z@°[@\@@h]@h(^@^@p_@=_@l`@`@ a@Va@}a@2a@2a@}a@Va@ a@`@l`@=_@p_@^@h(^@@h]@\@°[@۹Z@-Y@X@kW@)/V@%T@ӄS@R@P@O@}sM@K@uJ@AMH@zF@D@B@@@>@<@W:@l8@@6@ 4@_1@/@|;-@+*@D(@F+&@#@X!@@Dt@4@@@@+@~ @ @u@@m@@?J???@@N$?^I?v?ĭ?\?V9?E??%^?ش?_?a??E? ?Ӛ?K?#?ԙ??Æ?m?_~?-v?žo?h?a?Z?T?\M?G?.@?b:?`4?.?O(?T#??|?`C?+?4 ?_?S>)>g?>>f&>>>uI>H˼>>nz>ǥ>>>j>i>Z>>"{>p>@f>l>w>> >B>9>c>>\V>!>A%>a>$>> w>> >.>>>#??t ??3??"?v'?Ny-?{b3?$o9?m??mE?7kL?S?;Y?i`?Fg?n?(v?}?ʖ?r?^?\?\j?%?4?B?E??/?匰???S?i???b?B?,?0 ?`? ?V,?>?V?dt?@]@@̆ @H @ձ@F@O@Pn@@|@@ @(#@%@+&(@2*@{-@y/@1@:4@6@8@ !;@[=@?@A@C@JE@?V,? ?`?0 ?,?B?b???i?S???匰?/??E?B?4?%?\j?\?^?r?ʖ?@@n?Fg?i`?;Y?S?7kL?mE?m??$o9?{b3?Ny-?v'?"??3??t ??#?>>.> >> w>>$>a>A%>!>\V>>c>9>B> >>w>l>r>!}>NT>1 >>s>i>>⳩>F>>rM>W>>>`>>z>>??8 ???1?2 ?)X&? ,? 2?8?T>?D?c-K?Q?(X?-_?f?Dm?!)u?V|?%?r ???R?G??͞?)??/?1?46?޹??Y?+? ?4? ??1? ?(?#O?|??B?!@`8@q@ @X( @K@Ov@@@g@ @@SG"@m$@w'@ *@,@b/@-1@4@6@8@a;@g=@@@[B@D@@@@V,M@c2O@m+Q@S@T@V@7X@\5Z@[@@h]@6^@XY`@Ka@c@GAd@je@f@Ѕg@wh@Ti@{j@Rj@Pyk@Kl@l@l@;m@ym@m@Fm@Fm@m@ym@;m@l@l@Kl@Pyk@Rj@{j@Ti@wh@Ѕg@f@je@GAd@c@Ka@XY`@6^@@h]@[@\5Z@7X@V@T@S@m+Q@c2O@V,M@K@H@F@D@[B@@@g=@a;@8@6@4@-1@b/@,@ *@w'@m$@SG"@@ @@@@Ov@K@X( @ @q@`8@!@B??|?#O?(? ?1?? ?4? ?+?Y??޹?46?1?/??)?͞??G?R???r ?@@!)u?Dm?f?-_?(X?Q?c-K?D?T>?8? 2? ,?)X&?2 ?1???8 ???>z>>`>>>W>rM>>F>⳩>>i>s>>1 >NT>!}>r>Ey>>Ƈ>> >>Y|>1>>G>>uI>r%>?>>2>N >;*>E?? ?"?]??<?$?*?0?w6?N >2>>?>r%>uI>>G>>1>Y|>> >>Ƈ>>Ey>>&t>D>/I>F>>>~>ƙ>>=>EU>d>v>D>>+>>K?? ??-?׮?T#?? )?/?k'5?c;?`A?EOH?N?U?7\?c?>k? r?LFz?????#;?9x?Ǚ?0)??!?ӷ?_??޹????#?k??b?.?r???v}??.@I@@n @4 @@@@Y@@$@s@@"@E%@ (@*@-@?0@2@S5@L8@k:@=@~"@@B@#5E@MG@#J@L@N@@@@XW@Z@#\@h(^@`@b@{c@Ve@]g@+i@Pj@l@m@n@9p@rq@r@s@Zt@u@fv@&w@ w@hx@x@Uy@-y@y@mz@.z@.z@mz@y@-y@Uy@x@hx@ w@&w@fv@u@Zt@s@r@rq@9p@n@m@l@Pj@+i@]g@Ve@{c@b@`@h(^@#\@Z@XW@U@ӄS@=Q@N@L@#J@MG@#5E@B@~"@@=@k:@L8@S5@2@?0@-@*@ (@E%@"@@s@@$@Y@@@@4 @n @@I@.@?v}???r?.?b??k?#????޹??_?ӷ?!??0)?Ǚ?9x?#;?????LFz? r?>k?c?7\?U?N?EOH?`A?c;?k'5?/?? )?T#?׮?-?? ??K?>+>>D>v>d>EU>=>>ƙ>~>>>F>/I>D>&t>>>ֈ>̎>p>Z>~>Dɨ>zׯ>R!>>l>gp>t>9>>; >>]>j?{?J ?I/?? ?!?by'?Gj-?3?9?l$@?pF?cM?>T?@[?jb?~i?5q?x?O?G? S?r?s? ?B? ?,?T?^??ش???Č????$?C??\?Q??>?C?`@t@C@ @? @@f@xw@S@A0@ @O @#@&@v)@K,@b/@11@ݷ4@}7@>:@<@?@[B@E@G@|5J@L@XDO@Q@*T@V@X@+[@@h]@L_@Ka@c@%e@g@i@Pyk@;m@n@kp@r@fs@3t@Pv@w@x@ty@z@D{@˥|@k}@~@I~@9@|@@!@8@/C@/C@8@!@@|@9@I~@~@k}@˥|@D{@z@ty@x@w@Pv@3t@fs@r@kp@n@;m@Pyk@i@g@%e@c@Ka@L_@@h]@+[@X@V@*T@Q@XDO@L@|5J@G@E@[B@?@<@>:@}7@ݷ4@11@b/@K,@v)@&@#@O @ @A0@S@xw@f@@? @ @C@t@`@C?>??Q?\??C?$????Č???ش??^?T?,? ?B? ?s?r? S?G?O?x?5q?~i?jb?@[?>T?cM?pF?l$@?9?3?Gj-?by'?!? ??I/?J ?{?j?>]>; >>9>t>gp>l>>R!>zׯ>Dɨ>~>Z>p>̎>ֈ>>/\>B>&_>a>=>>>~=>>l>?c>Y>T>T>v>>?D?K?R?Y?`?h?=o?h>w?.?@A@yD@V8G@tI@QL@XDO@Q@sT@V@xY@[@N^@&`@ b@/e@]g@l}i@k@m@~o@/]q@*s@t@ɐv@'x@-y@{@z|@}@~@ @@ @{@@;@)@΂@@?4@]V@"m@x@x@"m@]V@?4@@΂@)@;@@{@ @@ @~@}@z|@{@-y@'x@ɐv@t@*s@/]q@~o@m@k@l}i@]g@/e@ b@&`@N^@[@xY@V@sT@Q@XDO@QL@tI@V8G@yD@A@8>@<@=9@`6@3@N0@-@*@c'@$@"@@#@4@;G@k[@q@Q @ @@@@dt?y?CA?x?;??]i???#?p?Y?S?%^?/z???:?ß? ??B?k???w?=o?h?`?Y?R?K?D?d>?7?1?Щ+?%??M??y?ZG ?9?v>T>T>Y>?c>l>>~=>>>=>a>&_>B>/\>>>t>v>[+>>F>>\W>>>g>>>6t>.>->z?? ??|?H?#?r)?/?9#6?.>6t>>>g>>>\W>>F>>[+>v>t>>>>\7>>>D>@#>>>T>->>>y>> >'>P>?? ?"??2?!?'?-?,4?7:?A?G?N?U?~\?[Wd?k?ٖs?v{??ۅ? ?O?ש???F5?B?y?x?a?]?:m?E?? ?ua??C?? d? ?ؿ?.?:Q?!@D@@~ @i@@@@@@@o @#@O&@ *@z-@R00@A3@P6@6]9@ef<@k?@lB@lhE@^H@NK@7N@OQ@S@V@wY@=I\@^@a@GAd@f@Ti@k@2n@kp@r@nu@;w@Uy@H^{@&U}@9@텀@de@;@@Yȃ@@*,@΅@e@#@q@@Q@H@H@J@@̵@ى@@u@u@@ى@̵@@J@H@H@Q@@q@#@e@΅@*,@@Yȃ@@;@de@텀@@&U}@H^{@Uy@;w@nu@r@kp@2n@k@Ti@f@GAd@a@^@=I\@wY@V@S@OQ@7N@NK@^H@lhE@lB@k?@ef<@6]9@P6@A3@R00@z-@ *@O&@#@o @@@@@@@i@~ @@D@!@:Q?.?ؿ? ? d??C??ua? ??E?:m?]?a?x?y?B?F5???ש?O? ?ۅ??v{?ٖs?k?[Wd?~\?U?N?G?A?7:?,4?-?'?!?2??"? ???P>'> >>y>>>->T>>>@#>D>>>\7>>Kg>޾>P>a>%>`k>>> >>D>k>>>2>{? ?/?s?(3??%?Y+?A2?~8?; ??E?`L?S?Z?Cb?i?tq?my??܄??Z?.?-?4?W? ?2֨??t?}?bɼ??V9??4?l?b??;?J?ؿ?Η?|}?@@Ѽ@h @@@@@=@>_@!@S$@'@*@1.@C1@i4@7@:@=@@@D@G@#J@V,M@O.P@F)S@V@Y@[@^@2a@Ud@ g@$i@&Zl@n@rq@s@Pv@x@{z@D)}@O@@@@@@YZ@*@#@@{]@H@@P-@?@)@L@.@*L@,@ Ҍ@@'@@@WL@WL@@@'@@ Ҍ@,@*L@.@L@)@?@P-@@H@{]@@#@*@YZ@@@@@@@D)}@{z@x@Pv@s@rq@n@&Zl@$i@ g@Ud@2a@^@[@Y@V@F)S@O.P@V,M@#J@G@D@@@=@:@7@i4@C1@1.@*@'@S$@!@>_@=@@@@@h @Ѽ@@@|}?Η?ؿ?J?;??b?l?4??V9??bɼ?}?t??2֨? ?W?4?-?.?Z??܄??my?tq?i?Cb?Z?S?`L?E?; ??~8?A2?Y+?%??(3?s?/? ?{?2>>>k>D>> >>>`k>%>a>P>޾>Kg>Г>N>>>40>>tU>@J>J>>n>%>U>A>??) ?,?[ ??%#?)?/?R6?w?R?Ƀ?u?M??*?S? `???jӬ?Dϱ???F???\?b? ??.?\?x??.?|}?k@@`@ @@6@]@i@@@+"@S%@D(@+@ /@V:2@#t5@8@;@?@JB@yE@H@K@N@WR@U@&X@+[@h(^@ a@d@f@$i@l@?o@q@)t@&w@-y@"|@)~@o@D@@＃@zĄ@~…@@@@zV@X!@X@L@@@Tތ@q@#@Zs@@@@@%@W@k}@w@@@w@k}@W@%@@@E@@Zs@#@q@Tތ@@@L@X@X!@zV@@@@~…@@@@D@o@)~@"|@-y@&w@)t@q@?o@l@$i@f@d@ a@h(^@+[@&X@U@WR@N@K@H@yE@JB@?@;@8@#t5@V:2@ /@+@D(@S%@+"@@@i@]@6@@ @`@@k@|}?.??x?\?.?? ?b?\??F????Dϱ?jӬ??? `?S?*??M?u?Ƀ?R?h>w?Wo?4g? `?X?vQ?lJ?C?U>%>n>>J>@J>tU>>40>>>N>Г>A>Q>ZǤ>6>OD> >> >Q>D>>6>P>?? ?s???!?'?x-? 4?7:??@A?;H?"O?qVV?D]?>Ee?m?qt?|??ۆ?+?ő?T??N???ի?qٰ??!?f??],?ĭ?B???r?Q?CA?]A?:Q?@@<@% @:@i@W@@}@V@ś"@Y%@4-)@x,@/@3@`6@9@<@C@@ȋC@F@uJ@OM@P@ջS@ V@Z@.]@E`@rTc@Yf@Ti@El@"+o@r@t@w@Cz@|@3|@@;@"m@@綅@Ά@ۇ@߈@ى@JɊ@~@@X@@8֎@䃏@%@@CF@Wđ@.6@@@'A@@'@ړ@1@@@1@ړ@'@@@@@.6@Wđ@CF@@%@䃏@8֎@@X@@~@JɊ@ى@߈@@@@@"m@;@@3|@|@Cz@w@t@r@"+o@El@Ti@Yf@rTc@E`@.]@Z@ V@ջS@P@OM@uJ@F@ȋC@C@@<@9@`6@3@/@x,@4-)@Y%@ś"@V@}@@W@i@:@% @<@@@:Q?]A?CA?Q?r???B?ĭ?],??f?!??qٰ?ի???N??T?ő?+?ۆ??|?qt?m?>Ee?D]?qVV?"O?;H??@A?7:? 4?x-?'?!???s? ???P>6>>D>Q> >> >OD>6>ZǤ>Q>A>ù>c>ώ>zׯ>`>N,>W;>[>)> >M7>.>n>??)D?/?Dk?<?8%?_+?[1?.8?>?߮E?L?S?@[?b?Yj?pr?az?f???\?ܒ?t?#??sǥ??zƯ??C?l??@@v?,?1????y??!@@`@% @~F@@@@ @*Y@@"@}V&@R)@{-@lm0@3@m.7@W:@=@ OA@D@H@-`K@N@WR@PU@X@[@_@ZAb@je@(h@!k@n@q@Zt@w@)oz@4?}@@.Z@@ @7@p@@Lj@@k@O@@#@@@w@q_@@Β@9t@ @5@-@@@@@@\@>@X@e@e@X@>@\@@@@o@@-@5@ @9t@Β@@q_@w@@@#@@O@k@@Lj@@p@7@ @@.Z@@4?}@)oz@w@Zt@q@n@!k@(h@je@ZAb@_@[@X@PU@WR@N@-`K@H@D@ OA@=@W:@m.7@3@lm0@{-@R)@}V&@"@@*Y@ @@@@~F@% @`@@!@?y????1?,?v???H??l?C??zƯ??sǥ??#?t?ܒ?\???f?az?pr?Yj?b?@[?S?L?߮E?>?.8?[1?_+?8%?<?Dk?/?)D???n>.>M7> >)>[>W;>N,>`>zׯ>ώ>c>ù>|8>h+>]>Nг>=>}>n>?> >P!>>G.>8?ø?k ?z??o?"?O(?>/?5?W?dt?]@D@Ѽ@ @:@@:@Q'@ҁ@E@-E#@ &@\*@-@50@i4@U7@Q;@&>@:B@E@I@L@:O@0`S@V@u"Z@p{]@`@d@]g@Pj@m@p@&t@&w@.z@D)}@ @{@@.F@@#@:@1z@?@ދ@@@,@b2@-@@j@ړ@@i@o@Ȗ@e@@nz@@[@ȸ@@K@@?@Ě@wњ@wњ@Ě@?@@K@@ȸ@[@@nz@@e@Ȗ@o@i@@ړ@j@@-@b2@,@@@ދ@?@1z@:@#@@.F@@{@ @D)}@.z@&w@&t@p@m@Pj@]g@d@`@p{]@u"Z@V@0`S@:O@L@I@E@:B@&>@Q;@U7@i4@50@-@\*@ &@-E#@E@ҁ@Q'@:@@:@ @Ѽ@D@]@dt?>??{ ? ?0 ?^I??@A??S??쾳?떮????q?-?S??ѥ?R? ?w?o?g?4`?X?QQ?&J?2(C?W/?O(?"?o??z?k ?ø?8?G.>>P!> >?>n>}>=>Nг>]>h+>|8>g>ר>2>-з>>>~C>(>g>?>u> > v? ?"?5?v?_ ?t&?Y,?Z$3?9?i@?nG? N?U?}]?a1e?m?!)u?m}?m?oD?寋?3?=Д??QR?7?5?^K? y?h?<?E?9?ƻ?@@N$?`?(?~I?v}?C?@C@@h @@i@@@Q'@b@@o#@&@b*@-@b1@4@l8@D;@N|?@mC@F@uJ@M@OQ@kT@X@[@^@hb@%e@,i@l@"o@s@Pv@y@˥|@@de@@]@΅@[7@@@A@@ƍ@^@%@CF@4\@sg@g@\@zF@t$@@@>v@y#@Ě@W@ޛ@`X@Ĝ@$@u@ @@@M5@C@C@M5@@@ @u@$@Ĝ@`X@ޛ@W@Ě@y#@>v@@@t$@zF@\@g@sg@4\@CF@%@^@ƍ@@A@@@[7@΅@]@@de@@˥|@y@Pv@s@"o@l@,i@%e@hb@^@[@X@kT@OQ@M@uJ@F@mC@N|?@D;@l8@4@b1@-@b*@&@o#@@b@Q'@@@i@@h @@C@@C?v}?~I?(?`?N$?7A?s?ƻ?9?E?<?h? y?^K?5?7?QR??=Д?3?寋?oD?m?m}?!)u?m?a1e?}]?U? N?nG?i@?9?Z$3?Y,?t&?_ ?v?5?"? ? v? >u>?>g>(>~C>>>-з>2>ר>g> H>X>>ֻ>>#7>>a> >af>1>}&?\?ۻ ?E???#?*?}~0?7?=?D?K?f+S?Z?af> >a>>#7>>ֻ>>X> H>ר>@B> >>=>ʝ>i>>>>2>?ZG ?H?l?C??>!?j'?-?4L4?;?A?H?rBP?jW?u__?7g?DBo?~w??G??I5?qґ?%?dY?(C?`F?b?И??O?Kп?ji?? ????'?V,?|?Z?.@t@@C @i@@]@@*Y@E@o#@'@2*@`;.@1@܃5@-9@<@y@@~5D@!?C??l?H?ZG ??2>>>>i>ʝ>=>> >@B>ר>ul>>ֻ>>Z>C >F>'M>z>>Ӏ?F?5 ??)??$?*?s1?8?>?F?.@M?T?tK\? d?l?Ut?;|?m???3? ?S??#?Ǩ?@ R?н?C???Pi?Q?R?Ak? ??>??ڜ@I@C@ @v@@@i@}@@-E#@&@k*@`;.@11@S5@6]9@I=@@@D@^H@]"L@6O@~S@kW@+[@6^@sb@Yf@3 j@Fm@/]q@3t@x@"|@|@D@J@ @@Q@@4@h@@%@y@(@t@yѕ@t$@8m@w@ޚ@/@$@M5@:@3@M @E@XӢ@Q@Q@-@@p*@5@@^@ܧ@R%@_@k@@@@@@@k@_@R%@ܧ@^@@5@p*@@-@Q@Q@XӢ@E@M @3@:@M5@$@/@ޚ@w@8m@t$@yѕ@t@(@y@%@@h@4@@Q@@ @J@D@|@"|@x@3t@/]q@Fm@3 j@Yf@sb@6^@+[@kW@~S@6O@]"L@^H@D@@@I=@6]9@S5@11@`;.@k*@&@-E#@@}@i@@@v@ @C@I@ڜ@?>?? ?Ak?@@@??C?н? R??Ǩ?#??S? ?3???m?;|?Ut?l? d?tK\?T?.@M?F?>?8?s1?*?$??)??5 ?F?Ӏ?>z>'M>F>C >Z>>ֻ>>ul>4>A>> >ʝ>{>ߦ>O >>?9?P ?(???!?J(?.?k'5?(;?B?&J?@@`?@@my???g??!?5?>?=???L???V?;????"?@@o??V?B?K@@ @Q @@@@@V@"@ &@b*@1.@1@S5@Gm9@;=@ A@D@|H@L@sdP@f&@W@@\@9@@t@G-@3<@3<@G-@t@@9@\@@W@>&@š@ @9n@w@@8@\a@|@%@ތ@#@8k@aH@@@@@@[@o@@'@y@ @Zs@ Ҍ@)@1z@:ć@@.F@~@@}@mz@fv@r@n@'k@]g@c@_@[@X@f?5?!???g??my? q?%h?`?Y?9Q?&J?B?(;?k'5?.?J(?!???(?P ?9??>O >ߦ>{>ʝ> >>A>4>>=>>r%>\> >'M>Y>D>â?\?8s ????*%?+?A2?8?B??WF?KN?@@݀e?@@~?p?#?&?m?:?#?e'?`F??կ?E?к?v?7??f??Y>'M> >\>r%>>=>>A>rM>>~C>0>k>h>>?BE?W ?M?? ?,"?](?/?5?I_@+"@Y%@R)@-@b1@D5@-9@I=@ A@E@H@L@P@T@X@E\@`@d@h@l@p@t@x@˥|@/C@/@^@|@ۇ@̵@4@X@ @@@N@o@}@3@Ě@J@ǝ@:@ڢ@E@R@<@%ԥ@@R%@;@C@>?@G-@ @@J@?@C@;@R%@@%ԥ@<@R@@@:@ǝ@J@@@@o@N@@@ @X@4@̵@ۇ@|@^@/@/C@˥|@x@t@p@l@h@d@`@E\@X@T@P@L@H@E@ A@I=@-9@D5@b1@-@R)@Y%@+"@>_@@@k[@@4 @@`8@@?M'? ??;?p?B?[/?6?~X???a???Mb?D?B?`\?ő??1O?ց?z?pr?!j?b?$Z?tR?J?C?Ih>k>0>~C>>rM>A> >E>#>dd>~> >>>"??8s ?)?T?f!?c%?u+?y2?O9?dV@?G?N?ƠV?w^?f?n?h>w??i???\j?HM?hL?g?r?a?c??V?\?@@ٛ@K=@w՝@c@@b@ ң@e6@V@ܧ@@~R@z@ӕ@ͣ@J@ @{@gR@@Բ@~@@L@$@@)@ @@@@@`ζ@8޶@8޶@`ζ@@@@ @@)@@$@L@@~@Բ@@gR@{@ @J@ͣ@ӕ@z@~R@@ܧ@V@e6@ ң@b@@c@@@@@>@@@@%@XN@p@7@q@@zĄ@΂@Ӏ@}@-y@w?n?f?w^?ƠV?N?G?dV@?O9?y2?u+?c%?f!?T?)?8s ??"?>> >~>dd>#>E> >>>[>{>C>wh>T>2>?O ?4?? ?:"?(?R//?5?T>wh>C>{>[>>>/,>S>>>P!>>> =??5 ????U%?u+?h2?$o9?i@?G?dXO?vW?^?#g?|o?x?p??h?O? )??H3?Ed??Y?t?M???x?K ?B???Ւ?Q:??@?h@@̆ @X( @@@S@#@@#@'@+@/@3@U7@D;@@@~5D@^H@L@;P@T@N-Y@@h]@a@e@{j@D\n@r@v@9{@9@@Yȃ@م@@@.@#@@@@ړ@ĕ@@@W@$@@ڢ@T@@@_.@@@4@9@ @g@{@Q@*@>P!>>>S>/,>">J>u>{>6t>{k> >{?f/ ?4?ȹ??"?p(?/?%5?{k>6t>{>u>J>">+x>YQ>z>>7>>?!?ۻ ?z?|??$?+?K2?>9?g@?G?dXO?#W?m%_? `g?o?x?˳?D??꾎?ب?ذ? ם??~??ɟ?%^?:?!6?O?,??P???Y?]A?"@/@zO@ @ձ@Ov@;G@@$@ @"@&@ *@1.@V:2@`6@W:@&>@mC@@@@f&@ӫ@v@U@j@@k@@O@@۸@E @O0@D@J@$A@v(@>@E@X@G(@@G@@#@x@@@@#@#@@@@x@#@@G@@G(@X@E@>@v(@$A@J@D@O0@E @۸@@O@@k@@j@U@v@ӫ@>&@9n@5@@ @D.@aH@Z@Ke@h@e@\@M@9@ @@X@ @@h@;@ @t{@XQw@r@n@{j@=e@Va@E\@X@f@W:@`6@V:2@1.@ *@&@"@ @@$@;G@Ov@ձ@ @zO@/@"@]A?Y???P??,?O?!6?:?%^?ɟ??~?? ם?ذ?ب?꾎??D?˳?x?o? `g?m%_?#W?dXO?G?g@?>9?K2?+?$??|?z?ۻ ?!??>7>>z>YQ>+x>>>s>>>n>? ?G?Y+?C??!?,'?.?5?I>>s>>>>>k>g?>j>j?'g?k ?,?[??b$?*?1?8???\G?N?V?t^?7g?žo?x??[??k??M?6?ʌ??떮?LK?C??%?{X?k??̫?Z?w(?a?>?"@%@u@4 @+@O@@@@#@c'@j,@R00@i4@8@<@ OA@E@uJ@@@@[@l`@d@l}i@ n@r@&w@t{@!@@h@{@#@2@r@i@@@N@z@@Ě@@@d@ @z @@@ת@@ @M@# @@c@@@E @x@5@$A@@E@@X@#@#@@W@@V@X.@v@W@b@;@ @@@3@D@D@3@@@ @;@b@W@v@X.@V@@@@#@#@X@@E@@$A@5@x@E @@@c@@# @M@ @@ת@@@z @ @d@@@Ě@@z@N@@@i@r@2@#@{@@h@!@t{@&w@r@ n@l}i@d@l`@[@kW@jR@-N@uJ@E@ OA@<@8@i4@R00@j,@c'@#@@@@O@+@4 @u@%@"@>?a?w(?Z?̫??k?{X?%??C?LK?떮??ʌ?6?M??k??[??x?žo?7g?t^?V?N?\G???8?1?*?b$??[?,?k ?'g?j?j>g?>k>>>dd>a>2a>`>A>96?1?u?]?v? ?b?'?-?4?(;?JC?qJ?:R?+Z?b?>k?Ss?!|???<~?m?|?;??e?a??n?\?j??A?]U?>??]?~I?@T?|}?hb@@ @x@@Pn@g@l@@@*@ /@A3@7@;@C@@D@I@M@R@V@+[@_@Ud@h@m@.r@v@t{@ @\@{@@J@L@ߍ@%@h@@@H@`J@u@D@&@ ң@@@Q@@Э@{@揱@_@$@8޶@@-@»@J@0ž@,2@@@#@TV@y@@@@ i@;@@@N@]@^Z@@f@:g@*@'@(@(@'@*@:g@f@@^Z@]@N@@@@@@@@y@TV@#@@@,2@0ž@J@»@-@@8޶@$@_@揱@{@Э@@Q@@@ ң@&@D@u@`J@H@@@h@%@ߍ@L@J@@{@\@ @t{@v@.r@m@h@Ud@_@+[@V@R@M@I@D@C@@;@7@A3@ /@*@&@"@l@g@Pn@@x@ @@hb@|}?@T?~I?]??>?]U?A??j?\?n??a?e??;?|?m?<~???!|?Ss?>k?b?+Z?:R?qJ?JC?(;?4?-?b?'? ?v?]?u?1?96?A>`>2a>a>dd>P>>T>c>?zs? ??O??q#?*?0?7?X+??9F?KN?P1V?'Q^?f?DBo?x?\? 9?? ?? ?QR?R?v@(@@%@T@|@ŝ@@@Ȫ@Ѭ@Ѯ@XȰ@#@@qo@<@'@;@Z@@@@y@@5@l|@z@@@@@@ֳ@3y@C-@@`@@M@L@[@6(@L@_@_@L@6(@[@L@M@@`@@C-@3y@ֳ@]@@@@@z@l|@5@@y@@@@Z@;@'@<@qo@@#@XȰ@Ѯ@Ѭ@Ȫ@@@ŝ@|@T@%@@(@>v@1@@@aK@#@d@J@#@@;@@9{@Pv@q@l@:h@c@6^@DHZ@jU@OQ@L@H@ȋC@?@:@P6@1@-@v)@E%@!!@ @@@@4 @c @j@@-?g?w]?r?G??s? ?? ?G???T>>P> >eF>xC>P>}&??f ?#P?Dk?W?X;&?>,?3?;?]B?|I?Q?;Y?b?Yj?|Bs?:|??Xs?M?G? b???(t?/?Dϱ?}?뮽??y?w???i?Q?Y?.?/e@@q@2 @ @@@|@@#@@@N0@4@6]9@=@JB@F@-`K@:O@kT@ @Y@]@sb@]g@l@p@,?X;&?W?Dk?#P?f ??}&?P>xC>eF> >9>>.>հ>-H? ?Է?ȹ??W"?O(?\/?"6?>?E?.@M?.U?LW]?e?^n?h>w?A.?܄?A?ԙ?ب?ؘ?0)?? .??Ÿ??6??b??"?5D?'?V,?Q?N?@B@ @ @@2@4@@SG"@&@*@b/@3@D7@ef<@@@yE@uJ@N@0`S@X@\@2a@Yf@'k@o@t@-y@)~@@#@@H@r@ߍ@aK@@-@:@@K=@^@@66@~@w@ @G-@X@{@.@L@@@@@b@,2@@@TV@W@V@@p@@@@@@@@3@ԙ@e@@@]@@Q@@@C4@Z@m@m@Z@C4@@@Q@@]@@@e@ԙ@3@@@@@:g@$@@p@@V@W@TV@@@,2@b@@@@@L@.@{@X@G-@ @w@~@66@@^@K=@@:@-@@aK@ߍ@r@H@@#@@)~@-y@t@o@'k@Yf@2a@\@X@0`S@N@uJ@yE@@@ef<@D7@3@b/@*@&@SG"@@4@2@@ @ @B@@N?Q?V,?'?5D?"??b??6??Ÿ?? .??0)?ؘ?ب?ԙ?A?܄?A.?h>w?^n?e?LW]?.U?.@M?E?>?"6?\/?O(?W"??ȹ?Է? ?-H?հ>.>>9>(>2>>?'g? ??[ ?n?`$?Щ+?2?9?A?H?P?(X?`?ki?1r?D5{?e2>(>)]>6{>D>??~P?EP?f? ?'?T[.?>f5?f5?T[.?'? ?f?EP?~P???D>6{>)]>0>+>3>?P ???o?c#?*?R1?.8?ӎ??)G?N?vW?u__?g?p?Sy?X?1O?7?T@?Fk?4?e'??m?D?8??\????4? ??{ ?CA?՛?y @)@Ѽ@@ @A@@@B@X!@%@ *@w.@2@}7@<@@@lhE@#J@N@ջS@X@p{]@hb@]g@&Zl@/]q@fv@t{@/C@΂@YZ@@7u@@S@@@1@ȸ@K=@@;<@@p*@@@g@į@@h@@@ @J@j@X@͊@@l|@b@;@@@uu@|@m@*@@@Q@ޒ@@@@@Q@@h@@@?@ݵ@@g@@@@@@@g@@ݵ@?@@@h@@Q@@@@@ޒ@Q@@@*@m@|@uu@@@;@b@l|@@͊@X@j@J@ @@@h@@į@g@@@p*@@;<@@K=@ȸ@1@@@S@@7u@@YZ@΂@/C@t{@fv@/]q@&Zl@]g@hb@p{]@X@ջS@N@#J@lhE@@@<@}7@2@w.@ *@%@X!@B@@@A@@ @Ѽ@)@y @՛?CA?{ ?? ?4????\?8??D?m??e'?4?Fk?T@?7?1O?X?Sy?p?g?u__?vW?N?)G?ӎ??.8?R1?*?c#?o???P ??3>+>0>h>>P?{? ??R?<?%?c,?A3?M:?nB?&J?R?wJZ?_b?Hgk?Ut?}?y? S?M?\j?'?q ??5????4?? ??4o?W? d? ??Z^?@p@ @@@@A0@r@#@+&(@,@1@S5@>:@8>@C@^H@V,M@WR@ V@[@`@%e@Rj@o@3t@mz@9@/@zĄ@Z@@@ @@N@@>v@/@^@M @~@p*@@!@”@@g@ƴ@@Xl@;@@!@I@g@y@V@z@!h@~H@;@@@`=@Y@]@@=@@Z@@[1@A@7@@+@@@g}@@i@p @@@:@t9@M@M@t9@:@@@p @i@@g}@@@+@7@@A@[1@@Z@@=@@]@Y@`=@@@;@~H@!h@z@V@y@g@I@!@@;@Xl@@ƴ@g@@”@!@@p*@~@M @^@/@>v@@N@@ @@@Z@zĄ@/@9@mz@3t@o@Rj@%e@`@[@ V@WR@V,M@^H@C@8>@>:@S5@1@,@+&(@#@r@A0@@@@ @p@@Z^?? ? d?W?4o?? ??4????5??q ?'?\j?M? S?y?}?Ut?Hgk?_b?wJZ?R?&J?nB?M:?A3?c,?%?<?R?? ?{?P?>h>z>w>96?????!?E(?R//?R6?߯=?6HE?M?.U?}]?8 f?n?w???g?R? `?ԏ?N?W??׬?匰?琶??i?$v?K ???e?)? ??y @@@ @o@@4@v@!@F+&@2*@b/@s3@L8@<@A@zF@NK@O.P@U@Z@_@d@,i@Gn@4js@x@}@{@^@@zV@.@e@9@ړ@z@H@(@P@@|@ @@!@ͣ@, @.@N@m@̹@3$@r@@@#@H@b@p@ur@:g@N@6(@@"@]@@@N@Ut@Q@@S@z@I@J@t@\@V%@@?|@ @σ@}@:@!x@@]@]@@!x@:@}@σ@ @?|@@V%@\@t@J@I@z@S@@Q@Ut@N@@@]@"@@6(@N@:g@ur@p@b@H@#@@@r@3$@̹@m@N@.@, @ͣ@!@@ @|@@P@(@H@z@ړ@9@e@.@zV@@^@{@}@x@4js@Gn@,i@d@_@Z@U@O.P@NK@zF@A@<@L8@s3@b/@2*@F+&@!@v@4@@o@ @@@y @? ?)?e???K ?$v?i??琶?@@?W?N?ԏ? `?R??g??w?n?8 f?}]?.U?M?6HE?߯=?R6?R//?E(?!?????96?w>z>OV>w>?@@c?RO?#?*?[1?8?g@?;H?W P?g;X?i`?SWi?Fr?v{?t?(P?M?m?K?F?ß?M?Y??-?l?$?{X???9?\?V,??D?l@@ @@l@6%@f@@$@D(@{-@-1@@6@k:@?@yD@;RI@7N@F)S@&X@.]@ZAb@]g@l@q@Lv@"|@@]V@|@q@M@#@@M@o@@`J@@@66@%ԥ@9n@@”@, @@$@@E @u@վ@,@y@@@"@D@^Z@fc@W_@M@.@@@v@v@.@[1@@@S@J@e@@@8@v@!x@0@@c@I@kF@ @@@6@6@@@ @kF@I@c@@0@!x@v@8@@@e@J@S@@@[1@.@v@v@@@.@M@W_@fc@^Z@D@"@@@y@,@վ@u@E @@$@@, @”@@9n@%ԥ@66@@@`J@@o@M@@#@M@q@|@]V@@"|@Lv@q@l@]g@ZAb@.]@&X@F)S@7N@;RI@yD@?@k:@@6@-1@{-@D(@$@@f@6%@l@@ @@l@D??V,?\?9???{X?$?l?-?@@M?ß?F?K?m?M?(P?t?v{?Fr?SWi?i`?g;X?W P?;H?g@?8?[1?*?#?RO?c??i ??w>OV>P>P?,?@@T??,&?9-?,4?L;?JC?J?R?@[?c?l?u?~?G?-4?rC?u?P˘?D??y???bĻ?j??n3??>?`?(?ރ??@@@q @@@A@@ !@d&@+*@y/@4@8@=@[B@V8G@]"L@OQ@V@+[@E`@je@Pj@"o@nu@wYz@|@~@*,@ۇ@7@@@@]@\@@Ě@u@%@XӢ@~@R%@Ȫ@g@@.@$@@-@Ȧ@@X@@5@V@@@f@<@L@O@$E@6,@@@@[1@@MS@@0@@v@@5@@@@i@|@#@@*2@@@@@@ll@lW@q-@@@*2@@#@|@i@@@@5@@v@@0@@MS@@[1@@@@6,@$E@O@L@<@f@@@V@5@@X@@Ȧ@-@@$@.@@g@Ȫ@R%@~@XӢ@%@u@Ě@@\@]@@@@7@ۇ@*,@~@|@wYz@nu@"o@Pj@je@E`@+[@V@OQ@]"L@V8G@[B@=@8@4@y/@+*@d&@ !@@A@@@q @@@@?ރ?(?`?>??n3??j?bĻ?@@y??D?P˘?u?rC?-4?G?~?u?l?c?@[?R?J?JC?@,4?9-?,&??T?? ?,?P?P> >#? ?D??_$?!?p(?l/?6?>?E?M?U?=^?f?o?y?9???3?9x?q?l??a???S??O?f?.???w]? ?`l?!@@ @x@>@ @X@@ ($@|(@|;-@1@6@Q;@~"@@E@tI@N@S@Y@h(^@rTc@(h@m@s@hx@}@D@.F@@̵@p@,@@@@e@y#@@D@T@z @w@p@@į@g@N@@-@!@9@@#@@@;@B@'@@@.@$8@C4@!@@Q@@?@@|l@@S@v@@&@kF@cS@L@*2@~@~@h@@{@@:@@@@I@@sz@:@@{@@h@~@~@*2@L@cS@kF@&@@v@S@@|l@@?@@Q@@!@C4@$8@.@@@'@B@;@@@#@@9@!@-@@N@g@į@@p@w@z @T@D@@y#@e@@@@,@p@@@@D@}@hx@s@m@(h@rTc@h(^@Y@S@N@tI@E@~"@@Q;@6@1@|;-@|(@ ($@@X@ @>@x@ @@!@`l? ?w]???.?f?O??S???a??l?q?9x?3???9?y?o?f?=^?U?M?E?>?6?l/?p(?!?_$??D? ?#? >v>?P ??,?4?#?*?1?9?@?`H?fP?X?1a?Gi?Js?P|?m? ݇??R?t?=??R?@??f ?w?ؾ?<?e%?C,? 4?t;?JC?J?S?y[? d?m?(v??R?T?꾎??~j?B?'??}???Y?x?ĭ??!?M?w(??O?@@ @h6@i@@@r@F#@}(@z-@_1@6@a;@C@@#5E@|5J@XDO@0aT@wY@^@d@@@&t@y@~@;@ @:ć@7@X@%@@ĕ@ܔ@Ke@M5@d@ ң@ŝ@g@G-@@@h@@̹@u@@@E@@8Q@@6@@[@`=@}@@@@@@V@@@?@}@@@|@@q-@h@@@@j@Eg@C)@3@m@7@]@0@@R!@+7@+7@R!@@0@]@7@m@3@C)@Eg@j@@@@h@q-@@|@@@}@?@@@V@@@@@@}@`=@[@@6@@8Q@@E@@@u@̹@@h@@@G-@g@ŝ@ ң@d@M5@Ke@ܔ@ĕ@@%@@@@ @;@~@y@&t@n@Ti@d@^@wY@0aT@XDO@|5J@#5E@C@@a;@6@_1@z-@}(@F#@r@@@i@h6@ @@@O??w(?M?!??ĭ?x?Y???}??'?B?~j??꾎?T?R??(v?m? d?y[?S?J?JC?t;? 4?C,?e%?<?ؾ?w?f ???Ӏ?<?+?EP??>!? (?/?R6?=?E?\M?U?=^?f?o?By?f?1O?G[?e?ߕ?dY??T??ﶲ??K?$?{?N?^I?Ak??%?ҽ?|}?/@&@ @+@A@@ @t!@&@2*@K/@ 4@8@g=@B@MG@L@Q@LW@=I\@2a@f@@@&w@˥|@@1߃@@1z@*L@ @@Δ@@@Z@3@ @@@@}@X@V$@@@Xl@3$@վ@X@#@@8Q@@^Z@@:@ԙ@B@C4@Pn@@|@@@e@#@~o@0@I@|@b@n@@:@0z@ޥ@k@@@@M@#@@@@'@o"@N@d@d@N@o"@'@@@@#@M@@@@k@ޥ@0z@:@@n@b@|@I@0@~o@#@e@@@|@@Pn@C4@B@ԙ@:@@^Z@@8Q@@#@X@վ@3$@Xl@@@V$@X@}@@@@ @3@Z@@@Δ@@ @*L@1z@@1߃@@˥|@&w@q@El@f@2a@=I\@LW@Q@L@MG@B@g=@8@ 4@K/@2*@&@t!@ @@A@+@ @&@/@|}?ҽ?%??Ak?^I?N?{?$?K??ﶲ??T??dY?ߕ?e?G[?1O?f?By?o?f?=^?U?\M?E?=?R6?/? (?>!??EP?+?<?Ӏ?]? ??!??8#?*?\61?8?l$@?G?W P?`X?R`?i?=r?P|????P?K?@?5?Ǩ?RĮ??12?գ?<@@@@Q@@@d@ AXAARAA!A7A CA CA7A!AARAAXA Ad@@@Q@@@@><@@sz@@ll@@6@0O@!x@{@@J@z@vU@"@@ޒ@$8@`@_@@^Z@@X.@@@,@r@;@@z @f5?@0@$@@ @E@@@Ѯ@@L@ӌ@n@J@!@@@V@;@4@@:@`@]@@S@@@g@i@@@@6@b@@S@0z@&@@>G@j@@d@MA|AdAJAQAǶAAaAtAAC A.AEAPAPAEA.AC AAtAaAAǶAQAJAdA|AMAd@@j@>G@@&@0z@S@@b@6@@@@i@g@@@S@@]@`@:@@4@;@V@@@!@J@n@ӌ@L@@Ѯ@@@E@ @@$@0@>@N@q_@Zs@4@q@~…@@ @)oz@t@?o@$i@GAd@^@xY@*T@N@I@D@?@W:@S5@;0@j,@1L'@ܩ"@@@6@o@ @u@]@Z@y??Ւ?.????7?v?-?i?rĬ?ʦ??K?ƕ?e?+??~#?x?Vo? Hf?}]?T?L?D?f5?.?'?C ?ȭ?#P?) ?f9?1???g?"?O(?0?o7?; ??F?N? [W?~_?%h?$r?v{?ʖ??&??t?q ?Ƣ?U?.??jB?f?p?cE?B?]i?5?e2???@Z@' @h6@@@X@E@}$@4-)@-@2@7@@@@K@=Q@V@[@Va@f@&Zl@q@w@4?}@{@]@C@P-@h@ @j@o@@(@@5@@ܧ@ת@Э@XȰ@@@@@j@I@#@@@B@M?@[@ԙ@$8@@S@Q@7@@@f@?@!x@}@'@@e@@z@>@7@@@@&zA!AAQAAUAA.AXAAAYAAAAiAiAAAAYAAAXA.AAUAAQAA!A&zA@@@7@>@z@@e@@'@}@!x@?@f@@7@@Q@S@@$8@ԙ@[@M?@B@@@#@I@j@@@@@XȰ@Э@ת@ܧ@@5@@(@@o@j@ @h@P-@C@]@{@4?}@w@q@&Zl@f@Va@[@V@=Q@K@F@A@<@7@2@-@4-)@}$@E@X@@@h6@' @Z@@??e2?5?]i?B?cE?p?f?jB??.?U?Ƣ?q ?t??&??ʖ?v{?$r?%h?~_? [W?N?F?; ??o7?0?O(?"?g???1?_; ?M???#?I*?f1?$o9?A?I??Q?]Y?jb?Hgk?Щt?3~???rC? ??4???1??jL???,???6??|?Z^?4@zO@~ @@j@i@ @!@H&@+@/@ݷ4@9@@@@7N@ӄS@X@N^@c@Ti@n@)t@Cz@@@΅@ @~@@y@5@}@ٛ@͞@ڢ@~@5@x@@{@#@&@@@@X@g@H@"@@'@σ@`=@B@ޒ@-@@7@@@p @?|@@@7@lW@f@d@Q@,@@@N@oA,AJAA8(AEAEAA 7AAA+MAAgA'AAA6AeBAeBA6AAA'AgAA+MAAA 7AAEAEA8(AAJA,AoAN@@@,@Q@d@f@lW@7@@@?|@p @@7@@@-@ޒ@@@@'@@"@H@g@X@@@@&@#@{@@x@5@~@ڢ@͞@ٛ@}@5@y@@~@ @΅@@@Cz@)t@n@Ti@c@N^@X@ӄS@7N@H@C@>@9@ݷ4@/@+@H&@!@ @i@j@@~ @zO@4@Z^?|??6???,???jL??1???4?? ?rC???3~?Щt?Hgk?jb?]Y??Q?I?A?$o9?f1?I*?#???M?_; ? ?,?-??ގ%?n,?3?c;?2(C?c-K?tS?([?-d?m?h>w?p??g??Ï?*?4?l?H?L? y?͸?K?n????.??~I?/?@*@Ѽ@u @F@N@@$@@SS#@ (@,@1@Ο6@;@@@JE@K@sdP@U@+[@&`@1f@k@rq@&w@|@.Z@.F@[7@P-@'@%@'@r,@3@K=@aH@T@\a@9n@z@ @揱@@@@@0@͊@y@b@D@f@@3@}@C4@@͂@@@p @{@@kF@5@~@@s@@7@Q@@R,AAAA@AXAAAG*AAAeAȷAhA^9AhAAAAAAAhA^9AhAȷAeAAAG*AAAXAA>AAAAR,A@Q@7@@s@@~@5@kF@@{@p @@@͂@@@@@@f@D@b@y@͊@0@@@@@揱@ @z@9n@\a@T@aH@K=@3@r,@'@%@'@P-@[7@.F@.Z@|@&w@rq@k@1f@&`@+[@U@sdP@K@JE@@@;@Ο6@1@,@ (@SS#@@@$@N@F@u @Ѽ@*@@/?~I??.????n?K?͸? y?L?H?l?4?*?Ï???g?p?h>w?m?-d?([?tS?c-K?2(C?c;?3?n,?ގ%??-?,? ? ?#P??_ ?b?'?T[.?5?]M=? &E?.@M? U?=^?#g?XPp?Sy??Æ?v?#;?K?hL??T??LK??F??????}?{ ?ؿ??X@@ " @g@@O2@@=P @$@)@ .@3@|8@=@B@&@:@M@_@qo@i|@@@P@@V@p@^Z@<@@@@Pn@"@@g@f@?|@@[@@@:@e@@@@d@A+{AQAAAԕABAA{AALjAhAhAJAW Aa A@ A A A A A A A A A@ Aa AW AJAhAhALjAA{AABAԕAAAQA+{AAd@@@@e@:@@@[@@?|@f@g@@"@@@@@<@^Z@p@V@@P@@@i|@qo@_@M@:@>&@i@@@w՝@Ě@Ĵ@@y@e@L@@@@3|@-y@s@2n@(h@ b@@h]@XW@ބR@V,M@9?Q@?H??Q?;Y?b?k?t?ȡ~?G?c?0?T??W?8?@?r?Tη?S???4??Ak?'?y?L?C@]@u@ @-@W@@$@h@o#@4(@@@@<@M>A@zF@K@m+Q@V@#\@Ka@]g@m@r@x@)~@;@7@:@A@XN@q_@t@[@?@ǝ@@ @_.@~R@v@j@@8޶@'@U@,2@G@qW@b@!h@:g@W_@O@$8@@@|@z@0@@!x@@5@@/e@T@@+7@[@m7A7A&/AAAAApA*AABAW A- A, A A AUq A A AvK A| A A A8 A8 A A A| AvK A A AUq A A A, A- AW ABAA*ApAAAAA&/A7Am7A[@+7@@T@/e@@5@@!x@@0@z@|@@@$8@O@W_@:g@!h@b@qW@G@,2@U@'@8޶@@j@v@~R@_.@ @@ǝ@?@[@@q_@XN@A@:@7@;@)~@x@r@@@Ka@#\@V@m+Q@K@zF@M>A@<@6@1@{-@4(@o#@h@@$@W@-@ @u@]@C@L?y?'?Ak??4???S?Tη?r?@?8?W??T?0?c?G?ȡ~?t?k?b?;Y??Q?H?Q@?>9?1?[*?q#??.?4?I/??)?$? ,?{b3?M:?B?qJ?f+S?[?d?Dm?h>w?|?_~??k?Fk??>Π?T?jӬ??G~???ƻ???|???E?Aq@֔@\ @@@@|@w4 @$@)@@@@=@mC@AMH@M@S@X@h(^@c@l}i@?o@nu@{z@o@"m@p@1z@@Ĝ@@yѕ@@@:@b@^@@@@U@p9@c@@;@վ@@@)@;@~H@N@M@$E@C4@v@@@J@M@@}@7@~@:@ޥ@@M@@XAdAgAaAPA 7A AAAhAW A A\ A AUq AY AW A Ay AW A( AB A AAAAA AB A( AW Ay A AW AY AUq A A\ A AW AhAAA A 7APAaAgAdAXA@M@@ޥ@:@~@7@}@@M@J@@@v@C4@$E@M@N@~H@;@@@@վ@;@@c@p9@U@@@@^@b@:@@@yѕ@@Ĝ@@1z@p@"m@o@{z@nu@?o@l}i@c@h(^@X@S@M@AMH@mC@=@8@3@+.@)@$@w4 @|@@@@\ @֔@Aq@E???|???ƻ???G~??jӬ?T?>Π??Fk?k??_~?|?h>w?Dm?d?[?f+S?qJ?B?M:?{b3? ,?$?)??I/?w??ُ?t&?`-?[4?I?&F?{]N?V?_?h?-q?b{??@@@>???y?@@?j?H?P?M??r?V,?V?%?/@7@4 @1@@@C@"@'@,@1@v6@;@A@iF@K@=Q@V@S\\@b@g@m@4js@Uy@O@@綅@Lj@@@@B@8m@/@]̞@E@e6@9n@9@@@S@@»@@G(@TV@V@@@@@@@@@V@e@{@X@6@@f@s@@@[@XA+{AєAtAЬAAALjAhA= A A Aj} A' A8 AW A AYA!A;,A+AA2 A'>AcA|A6A6A|AcA'>A2 AA+A;,A!AYA AW A8 A' Aj} A A A= AhALjAAAЬAtAєA+{AXA[@@@s@f@@6@X@{@e@V@@@@@@@@@@TV@G(@@»@@S@@@9@9n@e6@E@]̞@/@8m@B@@^@ދ@Lj@綅@@O@Uy@4js@m@g@b@S\\@V@=Q@K@iF@A@;@v6@1@,@'@"@C@@@1@4 @7@/@%?V?V,?r??M?P?H?j??2?կ?y???>? w??[ч??b{?-q?h?_?V?{]N?&F?3>?6?/?'? ?(3?b??u?:"?=)?}~0?7???G?W P?(X?cla?Yj?Ss?}?Ƀ?@@@B? ???D?}?C??\??^I?n?&V??/?ڜ@%@ @LY @@;G@@>@R$@4-)@1.@"3@=8@Fl=@B@H@}sM@jR@7X@h(^@{c@i@~o@kfu@H^{@@＃@Ά@@@@M@z@@@@R@V@ͩ@ @M@k@`ζ@E @J@@@W@"@N@uu@@"@@@Q@@@#@!x@kF@b@e@d@@@@m7AdAAtAOAAAȷAAi A\ A( AY A AK A A~A A+A>A(WAͮAA8AOkA A\AAA\A AOkA8AAͮA(WA>A+A A~A AK A AY A( A\ Ai AAȷAAAOAtAAdAm7A@@@d@e@b@kF@!x@#@@@Q@@@"@@uu@N@"@W@@@J@E @`ζ@k@M@ @ͩ@V@R@@@w@z@M@%@@@Ά@＃@@H^{@kfu@~o@i@{c@h(^@7X@jR@}sM@H@B@Fl=@=8@"3@1.@4-)@R$@>@@;G@@LY @ @%@ڜ@/??&V?n?^I??\??C?}?D??? ?B?ب?7??Ƀ?}?Ss?Yj?cla?(X?W P?G???7?}~0?=)?:"?u????q#?"*?1?$o9??@A?BTI?Q?wJZ?Z/c?\l?Ju??Rф??S?=Д?@~5D@ I@O@kT@\5Z@_@Ve@Pyk@/]q@XQw@&U}@@zĄ@ۇ@k@@CF@t@@@@.X@<@ܧ@!@g@@@<@x@0ž@@@9@4@y/@*@%@o @}@s@@t@ @@%@}??(?|? ??S????t?[?:?(C?_@(#@ (@},@ 2@m.7@ef<@A@G@L@R@?W@@h]@-c@+i@n@t@{z@텀@@@ى@@b2@sg@@@$@8k@@@~R@ͣ@Q@{I@@{@$A@@@)@p@ֳ@@*@]@@.@@@@}@I@@G@0z@>@@@AJAAPA[|AAȷAJA A A A A| AMAnAA|AAABA A3AәAsAp@AA8AAAAAAA8AAp@A@@@ ABAAA|AAnAMA| A A A A AJAȷAA[|APAAJAA@@>@0z@G@@I@}@@@@.@@]@*@@ֳ@p@)@@@$A@{@@{I@Q@ͣ@~R@@@8k@$@@@sg@b2@@ى@@@텀@{z@t@n@+i@-c@@h]@?W@R@L@G@A@ef<@m.7@ 2@},@ (@(#@>_@<@@@H @@@??t??7???$v?E?Ի?E??U??㸜??m??Æ??my?o?f?}]?iT?GL?zD? '?aɝ?R?ϩ???<??l?4?7A?? d?Q:?>?8@>i@@ @@/@m@r@D$@4-)@H,.@A3@l8@=@mC@oH@=M@ӄS@N-Y@6^@d@Pj@kp@ɐv@˥|@de@@@JɊ@#@-@g@@N@M5@#@QҤ@@@@*@@۸@4@@@5@@@;@_@@@N@[1@MS@|l@?|@@|@ll@O@&@7@@R,A+{AAA 7ArdALjAA A A A֬ A( ArA EA2 AAwAAVAj@A6A3AuAA4BAAŶAAAAAAAŶAA4BA@@@6Aj@AVAAwAA2 A EArA( A֬ A A A AALjArdA 7AAA+{AR,A@7@&@O@ll@|@@?|@|l@MS@[1@N@@@_@;@@@5@@@4@۸@@*@Ѯ@z@R%@QҤ@#@M5@N@@g@-@#@JɊ@@@de@˥|@ɐv@kp@Pj@d@6^@N-Y@ӄS@=M@oH@mC@=@l8@A3@H,.@4-)@D$@r@m@/@@ @@>i@8@>?Q:? d??7A?4?l??<???ϩ?R?aɝ?>?\j?*??z?{?tq?h?^?P1V?M?hjE?.n=?5? =.?u'?u ?P?M?!?J(?\/?6?>?pF?N? W? o`?i?Js?;|?c?%??)\?M?͞?Ť??x5?}?S? %?d#?N??.?? ??y @C@ @ @Ov@ @@y @S%@D*@K/@i4@9@8>@FD@I@XDO@@@@1f@l@r@'x@ G~@;@YZ@@~@@@\@@(@:@ތ@@@@@@9@i4@K/@D*@S%@y @@ @Ov@ @ @C@y @? ??.??N?d#? %?S?}?x5??Ť?͞?M?)\??%?c?;|?Js?i? o`? W?N?pF?>?6?\/?J(?!?M?C??"?? )?3o0?7?B???G?rBP?EX? a?dk?ot?I~?0?c?꾎?B??aƟ?sǥ?a?J?͸?D}?pY?b?}? ??Q?CA?_?X@b@i @@k[@O@@t!@}V&@N+@$^0@܃5@ۿ:@@@yE@J@P@@@@g@m@fs@-y@@@*@zV@@@j@zF@ؐ@@3@%@@@@@h@{̷@@@@TV@z@@:g@@@Q@@Q@@0@S@qm@|@n@sz@Eg@>G@@oAAAgAAAA= A\ AUq A| A| ArA]A'>A8AAA,MAsAAmA֜AAyA4A#A9eAA&AuAAAuA&AA9eA#A4AyAA֜AmAAsA,MAAA8A'>A]ArA| A| AUq A\ A= AAAAgAAAoA@>G@Eg@sz@n@|@qm@S@0@@Q@@Q@@@:g@@z@TV@@@O0@{̷@h@@ͣ@C@@%@3@@ؐ@zF@j@@@zV@*@@@-y@fs@m@g@Ka@[@)/V@P@J@yE@@@ۿ:@܃5@$^0@N+@}V&@t!@@O@k[@@i @b@X@_?CA?Q?? ?}?b?pY?D}?͸?J?a?sǥ?aƟ??B?꾎?c?0?I~?ot?dk? a?EX?rBP??G?B??7?3o0?? )?"?C??$?&#?*?s1?9?@?I?vQ?$Z?c?\l?u?6??.?ő??Ӛ?c?T?`? R?޹? ?m~???C??N???!@p@`6 @@5@@@tc"@1L'@K,@b1@6@;@-A@:F@]"L@Q@@@@h@n@3t@{@Z@Yȃ@@@X@w@ړ@t$@s@ǝ@M @|@ܧ@>?@J@# @9s@۸@@@@y@@=@@@$E@ޒ@Z@@S@@v@@@@@3@j@@,AAA~+ApAAA A( AO? AK AMA EA1A8AAVA{sA&AAiAAyAYAXAAADA@@ŻAAAŻAPAyADAAAXAYAyAAiAA&A{sAVAA8A1A EAMAK AO? A( A AAApA~+AAA,A@j@3@@@@@v@@S@@Z@ޒ@$E@@@=@@y@X@#@D@۸@9s@# @J@>?@ܧ@|@M @ǝ@s@t$@ړ@w@X@X!@#@Yȃ@Z@{@3t@n@h@c@.]@kW@Q@]"L@:F@-A@;@6@b1@K,@1L'@tc"@@@5@@`6 @p@!@??N??C???m~? ?޹? R?`?T?c?Ӛ??ő?.??6?u?\l?c?$Z?vQ?I?@?9?s1?*?&#?$??#?+?zj2?:?A?&J?:R?S[?[Wd?m?h>w?\???UY??;?‘???LK?*?գ?????v??J??J2?K@@ @q@@<@l@-E#@4(@|;-@:Y2@7@<@:B@MG@>M@$R@X@.b^@GAd@3j@9p@Pv@z|@.Z@@@@@q_@@@_J@@E@\a@Ũ@G-@ @@qo@ܹ@@@@@@^Z@@o@^p@@@S@J@v@@6@q-@:@><@y1@@&zAJA>AԕAA*AhA@ A AY AA AAnA2 AAAVABAp@AA֜A8A#AJA&Az*AA?AA@@AaAaAAyuAMAA?AAz*A&AJA#A8A֜AAp@ABAVAAA2 AnAAA AY A A@ AhA*AAԕA>AJA&zA@y1@><@:@q-@6@@v@J@S@@@^p@o@@^Z@@@#@@J@ܹ@qo@@ @G-@Ũ@\a@E@@_J@@@q_@@X@@@.Z@z|@Pv@9p@3j@GAd@.b^@X@$R@>M@MG@:B@<@7@:Y2@|;-@4(@-E#@l@<@@q@ @@K@J2??J??v?????գ?*?LK???‘?;??UY???\?h>w?m?[Wd?S[?:R?&J?A?:?zj2?+?#??,?@$?Y+?R3?;?B?c-K?S?q\?݀e?n?x?9?Z?̣?h?K? u?Ed?~?@@Ի?!??ڿ??l?J?V,?*=?|}?@F@@ @-@@@vt@a;@$@)@1.@A3@|8@=@$7C@|H@IN@S@-Y@_@je@dk@rq@w@}@@*,@@@8֎@@i@@@q@XӢ@8@š@ @{@@$]@Ϻ@$A@@#@@@:g@@.@_@@[1@z@e@@&@L@h@0z@@x@d@!AAABAAAW AP Aj} A A A!AAAAA{sAp@AAŶA_AmAAAAAMAaAAXAj=A'XAeAeA'XAj=AXAAaAMAAAAAmA_AŶAAp@A{sAAAAA!A A Aj} AP AW AAABAAA!Ad@x@@0z@h@L@&@@e@z@[1@@_@.@@:g@@@#@@$A@Ϻ@$]@@{@ @š@8@XӢ@q@@@i@@8֎@L@{]@*,@@}@w@rq@dk@je@_@-Y@S@IN@|H@$7C@=@|8@A3@1.@)@$@a;@vt@@@-@@ @F@@|}?*=?V,?J?l??ڿ??!?Ի?46?RĮ?~?Ed? u?K?h?̣?Z?9?x?n?݀e?q\?S?c-K?B?;?R3?Y+?@$?,??%?Y,?,4?;?C?k$L?T?}]?f?o?y?ց?0?M?ő?g?H3?)?aK?@@?Č?-???G? d?#O?i?Z@*@<@LY @X@Y{@A0@@m$@s)@.@4@6]9@>@$D@I@XDO@T@۹Z@`@f@l@r@x@~@ʠ@΅@H@@@䃏@Β@o@>v@zҜ@3@Q@@p@@gR@ƴ@<@;@v(@,@@@@fc@@~2@ޒ@@A@I@@5@kF@p@@ޥ@@@MAA8(AXAA6ABA A A' AK AKfAvA|AwA&hA,MA&AAŶAlAAADAAS@AAA'XAAAAA@!A@!AAAAA'XAAAS@AADAAAlAŶAA&A,MA&hAwA|AvAKfAK A' A A ABA6AAXA8(AAMA@@ޥ@@p@kF@5@@I@A@@ޒ@~2@@fc@@@@,@v(@;@<@ƴ@gR@@p@@Q@3@zҜ@>v@o@Β@䃏@@@H@΅@ʠ@~@x@r@l@f@`@۹Z@T@XDO@I@$D@>@6]9@4@.@s)@m$@@A0@Y{@X@LY @<@*@Z@i?#O? d?G???-?Č???И?aK?)?H3?g?ő?M?0?ց?y?o?f?}]?T?k$L?C?;?,4?Y,?%??<?X;&?Ny-?[4?@y@W@ i@]@N@3@i%@@@7@@J@@@cS@n@@k@@@|AQAEAA{AOAW A\ A A8 A A AAAAj AsAA֜A_AA&A@_AAyuAQA'XAߵAaAIArAAA]A]AAArAIAaAߵA'XAQAyuAA@_A&AA_A֜AAsAj AAAA A A8 A A\ AW AOA{AAEAQA|A@@k@@@cS@@@J@7@@@@i%@3@N@]@ i@W@y@>@@ @@@J@h0@w@Q@@@y#@Ȗ@9t@%@Tތ@@e@?4@ @ty@s@m@Ѕg@2a@°[@U@O.P@(J@E@?@t.:@4@]/@2*@%@ @o@6%@@ @̆ @,@@.?f^?_j???k?r?i???_?{ ???j?\j???i?z? q?4g?w^? U? M?D??AIF? N?cHW?4`?ki?=r?;|?tn?ѥ??D?B? ?)?^?ܿ?M?E ?n? ?O??Ji?R=?CA?Tu?@A7@ @@@S@B@ !@&@+@1@P6@;@ A@F@]"L@Q@W@@h]@rTc@Ti@Tio@u@D{@ @:@q@?@#@CF@@@W@@f*@@ @@@~@@=~@@@X@@V@@3y@[@e@@@@@@\@v@@*2@f@j@@@cAJAUAAG*ALjAA, AUq A֬ A A A*%A8ABAj@A3AmAA#AADAAA"AxA@!AA_A<A?AAGAxAAAxAGAA?A<A_AA@!AxA"AAADAA#AAmA3Aj@ABA8A*%A A A֬ AUq A, AALjAG*AAUAJAcA@@j@f@*2@@v@\@@@@@@e@[@3y@@V@@X@@@=~@@~@@@ @@f*@@W@@5@CF@#@?@q@:@ @D{@u@Tio@@@@W@Q@]"L@F@ A@;@P6@1@+@&@ !@B@S@@@ @A7@@Tu?CA?R=?Ji??O? ?n?E ?M?ܿ?^?)? ?B?D??ѥ?tn?;|?=r?ki?4`?cHW? N?AIF?3>?db6?X.?'?{ ?!?J(?l/?7?>?WF?dXO?:X?R`? 6j?s?}??i?!?T?Ǚ???a? Z???:?ƻ???.?{ ?a?O?]@@5 @ @@(@@@"@w'@,@1@6@E<@A@V8G@L@ބR@KX@h(^@d@{j@9p@fv@˥|@{@{@@)@Zs@Wđ@@@ޛ@aH@#@p*@š@@j@@@ @%@G(@@X.@@C-@m@@ޒ@@h@@V%@!x@i@~@:@Eg@@@RAQAA 7AAhAU A AY A& AYA+ADAA A6A8A֜AyAJAAAyuAXAxA.AAArAAA>AlgAA[A[AAlgA>AAArAAA.AxAXAyuAAAJAyA֜A8A6A AADA+AYA& AY A AU AhAA 7AAQARA@@Eg@:@~@i@!x@V%@@h@@ޒ@@m@C-@@X.@@G(@%@ @@@j@@š@p*@#@aH@ޛ@nz@-@Wđ@Zs@)@@{@{@˥|@fv@9p@@@@KX@ބR@L@V8G@A@E<@6@1@,@w'@"@@@@(@ @5 @@]@O?a?{ ?.???ƻ?:??? Z?a???Ǚ?T?!?i??}?s? 6j?R`?:X?dXO?WF?>?7?l/?J(?!?!?(?/?7?m??G?QO?X?a?j?ot?_~?G?}?k????e'?:?y?i?G~?D?V9?q\?}?/?????k@@~ @+@@%O@@"@|'@{-@V:2@}7@<@JB@G@}sM@F)S@X@^@d@Rj@p@&w@k}@@@Q@L@@.6@@@`X@ğ@66@5@>&@ͣ@V$@L@ ,@;@9@@CF@v@N@@M@@=@.@@g}@@0@|@~@0@C)@M@d@7AǶA.AAAhA A AW A( A!A>A8A(A3A3AY(AAYA&AAS@AQAA@!AAr!AύAA>AAUAYAAh Ah AAYAUAA>AAύAr!AA@!AAQAS@AA&AYAAY(A3A3A(A8A>A!A( AW A A AhAAA.AǶA7Ad@M@C)@0@~@|@0@@g}@@.@=@@M@@N@v@CF@@9@;@ ,@L@V$@ͣ@>&@5@66@ğ@`X@@@.6@@L@Q@@@k}@&w@p@Rj@d@^@X@F)S@}sM@G@JB@<@}7@V:2@{-@|'@"@@%O@@+@~ @@k@????/?}?q\?V9?D?G~?i?y?:?e'????k?}?G?_~?ot?j?a?X?QO?G?m??7?/?(?!?!?)?3o0?8???;H?P?OBY?Cb?k?!)u?.?R??S? ?ͪ??⭦?`?a??6???B?]??$f?|?C?-@r@ @e@@@m@o#@o(@-@ 2@47@[=@B@^H@N@ջS@wY@p_@je@Pyk@q@ w@~@;@wq@H@.@E@@o@[@Ĝ@3@~@@W@Q@I@$@@4@@G@@W@]@`@@]@@H@@@?|@@#@h@@3@#@ AAAXAAeAJA AUq A Am A;,A(WAwA9AәAuAAyAXAz*AAA'XAAAAύAxAYAAA&AOA_kAyA@@@&AAAYAxAύAAAA'XAAAz*AXA@AuAәA9AwA(WA;,Am A AUq A AJAeAAXAAA A#@3@@h@#@@?|@@@H@@]@@`@]@W@@G@@4@@$@I@Q@W@@~@3@Ĝ@[@o@@E@.@H@wq@;@~@ w@q@Pyk@je@p_@wY@ջS@N@^H@B@[=@47@ 2@-@o(@o#@m@@@e@ @r@-@C?|?$f??]?B???6??a?`?⭦??ͪ? ?S??R?.?!)u?k?Cb?OBY?P?;H???8?3o0?)?!?W"?Bx)?T0?~8?g@?H?L Q?;Y?b?l?u???:??uD????cZ?γ?o?F??@C@@I@N@תT@Z@l`@mf@l@r@x@9@΂@@J@,@@'A@@@u@@:`@ܧ@\@@g@)@i|@@0@#@L@;@@M@`@Q@@D@ݵ@p @σ@I@*2@{@T@7@@A#AtAAAhAa A A AW AAAAA3Ap@A4BA8A#AA?AaA'XAaAA<AA>AAh A]APASAA2A+A@@@SAPA]Ah AA>AA<AAaA'XAaA?AA#A8A4BAp@A3AAAAAW A A Aa AhAAAtA#AA@7@T@{@*2@I@σ@p @ݵ@D@@Q@`@M@@;@L@#@0@@i|@)@g@@\@ܧ@:`@@u@@@'A@@,@J@@΂@9@x@r@l@mf@l`@Z@תT@N@@I@C@1>@8@3@yJ.@4-)@ ($@a;@g@N@@} @ @/@??r?Ƃ??4????գ?к?,??j?K?dY?!?k?? 9? ?=v?l? Cc?7Z?vQ?H?.@?8?\61?r)?"?"?*?21?.9?A?BTI?Q?+Z?c?m?v?O?r??3?ҕ??‘???/z?!???[/??N$????:Q?I@F@q @F@2@@k@Lo$@v)@ .@3@9@>@D@ I@XDO@ U@Z@`@f@l@s@Uy@|@@5B@@ Ҍ@%@@@K@ @D.@@R%@9@,@#@ @@̹@Z@@x@@ @f@L@.@@-@@@@}@kF@@@&@]@@RAL\AAYAgA^9A@ A AvK A( AA2 A8Aw[A{sAAAyA9eADAAAAIA_A?AAAAOAPAA2AGA0cAqA@@GA2AAPAOAAAA?A_AIAAAADA9eAyAAA{sAw[A8A2 AA( AvK A A@ A^9AgAYAAL\ARA@]@&@@@kF@}@@@@-@@.@L@f@ @@x@@Z@̹@ @@#@,@9@R%@@D.@ @K@@@%@ Ҍ@@5B@@|@Uy@s@l@f@`@Z@ U@XDO@ I@D@>@9@3@ .@v)@Lo$@k@@2@F@q @F@I@:Q????N$??[/???!?/z???‘??ҕ?3??r?O?v?m?c?+Z?Q?BTI?A?.9?21?*?"?*#?U*?1?$o9?aA?I?R?Z?c?Rm?-v?|???e??қ?ɡ??@@FD@I@9O@PU@+[@ a@!g@;m@4js@-y@@?4@p@̵@@W@'@\@@@)f@@_@@ni@@@@E @@,@@?L@@:g@[@\x@@Sz@@g@@:@ @@:@|@0@'@AAC AA'AhA A( A| AB A A'>AOkA9AA8AŶAAAyAMAXAArAr!AA>AUA&AՆASA2AaUA~AvAKA@@~AaUA2ASAՆA&AUA>AAr!ArAAXAMAyAAAŶA8AA9AOkA'>A AB A| A( A AhA'AAC AAA'@0@|@:@@ @:@@g@@Sz@@\x@[@:g@@?L@@,@@E @@@@ni@@_@@)f@@@\@'@W@@̵@p@?4@@-y@4js@;m@!g@ a@+[@PU@9O@I@FD@&>@6]9@ 4@.@R)@S$@@@1 @`y@? @u@@ũ?R?V,?6?q??w?A?;?b?Ÿ?@w??Å??e?-?@yD@uJ@2O@fU@@Va@]g@ym@s@y@!@]V@@ى@'@k}@ړ@>@?@@"@z @k@t@ @!@@=@ͽ@^@@V@@*@6(@"@C4@@m.@@:@!x@@q-@sz@k@@o"@!AtA.AAAAA AM A A A;,AcA AVAAAA4A&APAyuAj=AAA JAGAlgAYAOAAAGA~A@@AAAKA~AGAAAOAYAlgAGA JAAAj=AyuAPA&A4AAAAVA AcA;,A A AM A AAAAA.AtA!Ao"@@k@sz@q-@@!x@:@@m.@@C4@"@6(@*@@V@@^@ͽ@=@@!@ @t@k@z @"@@?@>@ړ@k}@'@ى@@]V@!@y@s@ym@]g@Va@d[@fU@2O@uJ@yD@>@k9@:4@ /@s)@%$@E@@;G@5@ @K@c;@B??j?r?̫??ĭ?$v?m???i?r??w?}m?/d?[?JPR?I?A?]9?1?[*?T#?Hq#?*? 2?9?A?|I?tR?@[?[Wd?m?Diw?˳?ۅ?+?s?G?F??5?ˇ?!??E???Q:?? ? ?ҽ?O @OR@@X( @s@Ha@"@@$@)@b/@Z4@9@?@D@|5J@6O@jU@[@}a@Ѕg@m@s@mz@8@"m@@@@@w@1@X@Ě@M5@$@(@@G-@{@@@`ζ@]@@X@@@3@'@L@Y@Z@Z@vU@@t9@@@lW@@@R!@N@7AAEAA6AA A@e A AA EA|A\AAAAAYAuAŻAA'XAAA#eAxAAA_kAA2A0cAvA@@AAAAvA0cA2AA_kAAAxA#eAAA'XAAŻAuAYAAAAA\A|A EAA A@e A AA6AAEAA7AN@R!@@@lW@@@t9@@vU@Z@Z@Y@L@'@3@@@X@@]@`ζ@@@{@G-@@(@$@M5@Ě@X@1@w@@@@@"m@8@mz@s@m@Ѕg@}a@[@jU@6O@|5J@D@?@9@Z4@b/@)@$@@"@Ha@s@X( @@OR@O @ҽ? ? ??Q:???E??!?ˇ?5??F?G?s?+?ۅ?˳?Diw?m?[Wd?@[?tR?|I?A?9? 2?*?Hq#?q#?*?A2?9?`A?J?R?S[?$kd?Dm?~w???7??U?#??)D?떮??bĻ?!?? ? M???̨?J?@]@Ѽ@4 @@Pn@A0@ @$@ *@-/@i4@9@l)?@D@GJ@:O@U@[@2a@g@Fm@s@.z@/C@x@@u@WL@@@e@wњ@C@&@e6@@@3<@į@w??Å??e?-?@yD@uJ@2O@fU@d[@Va@]g@ym@s@y@!@]V@@ى@'@k}@ړ@>@?@@"@z @k@t@ @!@@=@ͽ@^@@V@@*@6(@"@C4@@m.@@:@!x@@q-@sz@k@@o"@!AtA.AAAAA AM A A A;,AcA AVAAA@@&APAyuAj=AAA JAGAlgAYAOAAAGA~AKAAAAA@@GAAAOAYAlgAGA JAAAj=AyuAPA&A4AAAAVA AcA;,A A AM A AAAAA.AtA!Ao"@@k@sz@q-@@!x@:@@m.@@C4@"@6(@*@@V@@^@ͽ@=@@!@ @t@k@z @"@@?@>@ړ@k}@'@ى@@]V@!@y@s@ym@]g@Va@d[@fU@2O@uJ@yD@>@k9@:4@ /@s)@%$@E@@;G@5@ @K@c;@B??j?r?̫??ĭ?$v?m???i?r??w?}m?/d?[?JPR?I?A?]9?1?[*?T#?*#?U*?1?$o9?aA?I?R?Z?c?Rm?-v?|???e??қ?ɡ??@@FD@I@9O@PU@+[@ a@!g@;m@4js@-y@@?4@p@̵@@W@'@\@@@)f@@_@@ni@@@@E @@,@@?L@@:g@[@\x@@Sz@@g@@:@ @@:@@@'@AAC AA'AhA A( A| AB A A'>AOkA9AA8A@@AyAMAXAArAr!AA>AUA&AՆASA2AaUA~AvAKAKAvA@@2ASAՆA&AUA>AAr!ArAAXAMAyAAAŶA8AA9AOkA'>A AB A| A( A AhA'AAC AAA'@0@|@:@@ @:@@g@@Sz@@\x@[@:g@@?L@@,@@E @@@@ni@@_@@)f@@@\@'@W@@̵@p@?4@@-y@4js@;m@!g@ a@+[@PU@9O@I@FD@&>@6]9@ 4@.@R)@S$@@@1 @`y@? @u@@ũ?R?V,?6?q??w?A?;?b?Ÿ?@@D@ I@XDO@ U@Z@`@f@l@s@Uy@|@@5B@@ Ҍ@%@@@K@ @D.@@R%@9@,@#@ @@̹@Z@@x@@ @f@L@.@@-@@@@}@kF@@@@@@RAL\AAYAgA^9A@ A AvK A( AA2 A8Aw[A{sAA@@9eADAAAAIA_A?AAAAOAPAA2AGA0cAqAqA0cAGA2AAPAOAAAA?A_AIAAAADA9eAyAAA{sAw[A8A2 AA( AvK A A@ A^9AgAYAAL\ARA@]@&@@@@@@@@-@@.@L@f@ @@x@@Z@̹@ @@#@,@9@R%@@D.@ @K@@@%@ Ҍ@@5B@@|@Uy@s@l@f@`@Z@ U@XDO@ I@D@>@9@3@ .@v)@Lo$@k@@2@F@q @F@I@:Q????N$??[/???!?/z???‘??ҕ?3??r?O?v?m?c?+Z?Q?BTI?A?.9?21?*?"?"?r)?\61?8?.@?H?vQ?7Z? Cc?l?=v? ? 9??k?!?dY?K?j??,?к?գ????4??Ƃ?r???/@ @} @@N@g@a;@ ($@4-)@yJ.@3@8@1>@C@@I@N@תT@Z@l`@mf@l@r@x@9@΂@@J@,@@'A@@@u@@:`@ܧ@\@@g@)@i|@@0@#@L@;@@M@`@Q@@D@ݵ@p @σ@I@*2@{@T@7@@A#AtAAAhAa A A AW AAAAA3Ap@A4BA8A#AA?AaA'XAaAA<AA>AAh A]APASAA2A+A+A2AASAPA]Ah AA>AA<AAaA'XAaA?AA#A8A4BAp@A3AAAAAW A A Aa AhAAAtA#AA@7@T@{@@@@p @ݵ@D@@Q@`@M@@;@L@#@0@@i|@)@g@@\@ܧ@:`@@u@@@'A@@,@J@@΂@9@x@r@l@mf@l`@Z@תT@N@@I@C@1>@8@3@yJ.@4-)@ ($@a;@g@N@@} @ @/@??r?Ƃ??4????գ?к?,??j?K?dY?!?k?? 9? ?=v?l? Cc?7Z?vQ?H?.@?8?\61?r)?"?W"?Bx)?T0?~8?g@?H?L Q?;Y?b?l?u???:??uD????cZ?γ?o?F??&@ͣ@V$@L@ ,@;@9@@CF@v@N@@@@=@.@@g}@@0@|@~@0@C)@M@d@7AǶA.AAAhA A AW A( A!A>A8A(A3A3AY(AAYA&AAS@AQAA@!AAr!AύAA>AAUAYAAh Ah AAYAUAA>AAύAr!AA@!AAQAS@AA&AYAAY(A3A3A(A8A>A!A( AW A A AhAAA.AǶA7Ad@M@C)@0@~@|@0@@g}@@.@=@@M@@N@v@CF@@9@;@ ,@L@V$@ͣ@>&@5@66@ğ@`X@@@.6@@L@Q@@@k}@&w@p@Rj@d@^@@@}sM@G@JB@<@}7@V:2@{-@|'@"@@%O@@+@~ @@k@????/?}?q\?V9?D?G~?i?y?:?e'????k?}?G?_~?ot?j?a?X?QO?G?m??7?/?(?!?!?J(?l/?7?>?WF?dXO?:X?R`? 6j?s?}??i?!?T?Ǚ???a? Z???:?ƻ???.?{ ?a?O?]@@5 @ @@(@@@"@w'@,@1@6@E<@A@V8G@L@ބR@KX@h(^@d@{j@9p@fv@˥|@{@{@@)@Zs@Wđ@-@nz@ޛ@aH@#@p*@š@@j@@@ @%@G(@@X.@@C-@m@@ޒ@@h@@V%@!x@i@~@:@Eg@@@RAQAA 7AAhAU A AY A& AYA+ADAA A6A8A֜AyAJAAAyuAXAxA.AAArAAA>AlgAA[A[AAlgA>AAArAAA.AxAXAyuAAAJAyA֜A8A6A AADA+AYA& AY A AU AhAA 7AAQARA@@Eg@:@~@i@!x@@@@@ޒ@@m@C-@@X.@@G(@%@ @@@j@@š@p*@#@aH@ޛ@nz@-@Wđ@Zs@)@@{@{@˥|@fv@9p@{j@d@h(^@@@L@V8G@A@E<@6@1@,@w'@"@@@@(@ @5 @@]@O?a?{ ?.???ƻ?:??? Z?a???Ǚ?T?!?i??}?s? 6j?R`?:X?dXO?WF?>?7?l/?J(?!?{ ?'?X.?db6?3>?AIF? N?cHW?4`?ki?=r?;|?tn?ѥ??D?B? ?)?^?ܿ?M?E ?n? ?O??Ji?R=?CA?Tu?@A7@ @@@S@B@ !@&@+@1@P6@;@ A@F@]"L@Q@W@@h]@rTc@Ti@Tio@u@D{@ @:@q@?@#@CF@5@@W@@f*@@ @@@~@@=~@@@X@@V@@3y@[@e@@@@@@\@v@@*2@f@j@@@cAJAUAAG*ALjAA, AUq A֬ A A A*%A8ABAj@A3AmAA#AADAAA"AxA@!AA_A<A?AAGAxAAAxAGAA?A<A_AA@!AxA"AAADAA#AAmA3Aj@ABA8A*%A A A֬ AUq A, AALjAG*AAUAJAcA@@j@f@*2@@v@@@@@@@e@[@3y@@V@@X@@@=~@@~@@@ @@f*@@W@@5@CF@#@?@q@:@ @D{@u@Tio@Ti@rTc@@h]@@@]"L@F@ A@;@P6@1@+@&@ !@B@S@@@ @A7@@Tu?CA?R=?Ji??O? ?n?E ?M?ܿ?^?)? ?B?D??ѥ?tn?;|?=r?ki?4`?cHW? N?AIF?3>?db6?X.?'?{ ??&?..?5?~=?E?yM?{V?u__?h?$r?{?m?#?~??ذ?9?????S?!6?F????]?Y??Aq@@ @Œ@@@ҁ@X!@H&@N+@lm0@S5@k:@uT@@&E@-`K@1Q@V@\@1|b@wh@n@Zt@z@@＃@#@P-@q@@ @e@Ě@'@"@-@9n@@@y@W@ i@]@N@3@i%@@@7@@J@@@cS@n@@k@@@|AQAEAA{AOAW A\ A A8 A A AAAAj AsAA֜A_AA&A@_AAyuAQA'XAߵAaAIArAAA]A]AAArAIAaAߵA'XAQAyuAA@_A&AA_A֜AAsAj AAA@ A A8 A A\ AW AOA{AAEAQA|A@@k@@n@cS@@@J@7@@@@i%@3@N@]@ i@W@y@>@@ @@@J@h0@w@Q@@@y#@Ȗ@9t@%@Tތ@@e@?4@ @ty@s@m@Ѕg@2a@°[@U@O.P@(J@E@?@t.:@4@]/@2*@%@ @o@6%@@ @̆ @@@.?f^?_j???k?r?i???_?{ ???j?\j???i?z? q?@@ U? M?D?@$D@I@XDO@T@۹Z@`@f@l@r@x@~@ʠ@΅@H@@@䃏@Β@o@>v@zҜ@3@Q@@p@@gR@ƴ@<@;@v(@,@@@@fc@@~2@ޒ@@A@I@@5@kF@p@@ޥ@@@MAA8(AXAA6ABA A A' AK AKfAvA|AwA&hA,MA&AAŶAlAAADAAS@AAA'XAAAAA@!A@!AAAAA'XAAAS@AADAAAlAŶAA&A,MA&hAwA|AvAKfAK A' A A ABA6AAXA8(AAMA@@ޥ@@p@kF@5@@I@A@@ޒ@~2@@fc@@@@,@v(@;@<@ƴ@gR@@p@@Q@3@zҜ@>v@o@Β@䃏@@@H@΅@ʠ@~@x@r@l@f@`@۹Z@T@XDO@I@$D@>@6]9@4@.@s)@m$@@A0@Y{@X@LY @<@@@i?#O? d?G???-?Č???И?aK?)?H3?g?ő?M?0?ց?y?o?@@T?k$L?C?;?,4?Y,?%??,?@$?Y+?R3?;?B?c-K?S?q\?݀e?n?x?9?Z?̣?h?K? u?Ed?~?RĮ?46?Ի?!??ڿ??l?J?V,?*=?|}?@F@@ @-@@@vt@a;@$@)@1.@A3@|8@=@$7C@|H@IN@S@-Y@_@je@dk@rq@w@}@@*,@{]@L@8֎@@i@@@q@XӢ@8@š@ @{@@$]@Ϻ@$A@@#@@@:g@@.@_@@[1@z@e@@&@L@h@0z@@x@d@!AAABAAAW AP Aj} A A A!AAAAA{sAp@AAŶA_AmAAAAAMAaAAXAj=A'XAeAeA'XAj=AXAAaAMAAAAAmA_AŶAAp@A{sAAAAA!A A Aj} AP AW AAABAAA!Ad@x@@0z@h@L@&@@e@z@[1@@_@.@@:g@@@#@@$A@Ϻ@$]@@{@ @š@8@XӢ@q@@@i@@8֎@L@{]@*,@@}@w@rq@dk@je@_@-Y@S@IN@|H@$7C@=@|8@A3@1.@)@$@a;@vt@@@-@@ @F@@@*=?V,?J?l??ڿ??!?Ի?46?RĮ?~?Ed? u?K?h?̣?Z?9?x?n?݀e?q\?S?c-K?B?;?R3?Y+?@$?,??#?+?zj2?:?A?&J?:R?@@@h>w?\???UY??;?‘???LK?*?գ?????v??J??J2?K@@ @q@@<@l@-E#@4(@|;-@:Y2@7@<@:B@MG@>M@$R@X@.b^@GAd@3j@9p@Pv@z|@.Z@@@X@@q_@@@_J@@E@\a@Ũ@G-@ @@qo@ܹ@J@@#@@@^Z@@o@^p@@@S@J@v@@6@q-@:@><@y1@@&zAJA>AԕAA*AhA@ A AY AA AAnA2 AAAVABAp@AA֜A8A#AJA&Az*AA?AAMAyuAAaAaAAyuAMAA?AAz*A&AJA#A8A֜AAp@ABAVAAA2 AnAAA AY A A@ AhA*AAԕA>AJA&zA@y1@><@:@q-@6@@v@J@S@@@^p@o@@^Z@@@#@@J@ܹ@qo@@ @G-@Ũ@\a@E@@_J@@@q_@@X@@@.Z@z|@Pv@9p@3j@GAd@.b^@X@$R@>M@MG@:B@<@7@:Y2@|;-@4(@-E#@l@<@@q@ @@K@J2??J??v?????գ?*?LK???‘?;??UY???\?h>w?m?[Wd?S[?:R?&J?A?:?zj2?+?#??$?&#?*?s1?9?@?I?vQ?@@@u?6??.?ő??Ӛ?c?T?`? R?޹? ?m~???C??N???!@p@`6 @@5@@@tc"@1L'@K,@b1@6@;@-A@:F@]"L@Q@kW@.]@c@h@n@3t@{@Z@Yȃ@#@X!@X@w@ړ@t$@s@ǝ@M @|@ܧ@>?@J@# @9s@۸@D@#@X@y@@=@@@$E@ޒ@Z@@S@@v@@@@@3@j@@,AAA~+ApAAA A( AO? AK AMA EA1A8AAVA{sA&AAiAAyAYAXAAADAyAPAŻAAAŻAPAyADAAAXAYAyAAiAA&A{sAVAA8A1A EAMAK AO? A( A AAApA~+AAA,A@j@3@@@@@v@@S@@Z@ޒ@$E@@@=@@y@X@#@D@۸@9s@# @J@>?@ܧ@|@M @ǝ@s@t$@ړ@w@X@X!@#@Yȃ@Z@{@3t@n@h@c@.]@kW@Q@]"L@:F@-A@;@6@b1@K,@1L'@tc"@@@5@@`6 @p@!@??N??C???m~? ?޹? R?`?T?c?Ӛ??ő?.??6?u?\l?c?$Z?vQ?I?@?9?s1?*?&#?$?C??"?? )?3o0?7?B???G?rBP?@@@ot?I~?0?c?꾎?B??aƟ?sǥ?a?J?͸?D}?pY?b?}? ??Q?CA?_?X@b@i @@k[@O@@t!@}V&@N+@$^0@܃5@ۿ:@@@yE@J@P@)/V@[@Ka@g@m@fs@-y@@@*@zV@@@j@zF@ؐ@@3@%@@C@ͣ@@h@{̷@O0@@@TV@z@@:g@@@Q@@Q@@0@S@qm@|@n@sz@Eg@>G@@oA@AgAAAA= A\ AUq A| A| ArA]A'>A8AAA,MAsAAmA֜AAyA4A#A9eAA&AuAAAuA&AA9eA#A4AyAA֜AmAAsA,MAAA8A'>A]ArA| A| AUq A\ A= AAAAgAAAoA@>G@Eg@sz@n@|@qm@S@0@@Q@@Q@@@:g@@z@TV@@@O0@{̷@h@@ͣ@C@@%@3@@ؐ@zF@j@@@zV@*@@@-y@fs@m@g@Ka@[@)/V@P@J@yE@@@ۿ:@܃5@$^0@N+@}V&@t!@@O@k[@@i @b@X@_?CA?Q?? ?}?b?pY?D}?͸?J?a?sǥ?aƟ??B?꾎?c?0?I~?ot?dk? a?EX?rBP??G?B??7?3o0?? )?"?C??M?!?J(?\/?6?>?pF?N? W? o`?i?Js?;|?c?%??)\?M?͞?Ť??x5?}?S? %?d#?N??.?? ??y @C@ @ @Ov@ @@y @S%@D*@K/@i4@9@8>@FD@I@XDO@%T@Z@XY`@1f@l@r@'x@ G~@;@YZ@@~@@@\@@(@:@ތ@@;@ӕ@k@@9@i4@K/@D*@S%@y @@ @Ov@ @ @C@y @? ??.??N?d#? %?S?}?x5??Ť?͞?M?)\??%?c?;|?Js?i? o`? W?N?pF?>?6?\/?J(?!?M?P?u ?u'? =.?5?.n=?hjE?M?P1V?^?h?tq?{?z??*?\j?>?aɝ?R?ϩ???<??l?4?7A?? d?Q:?>?8@>i@@ @@/@m@r@D$@4-)@H,.@A3@l8@=@mC@oH@=M@ӄS@N-Y@6^@d@Pj@kp@ɐv@˥|@de@@@JɊ@#@-@g@@N@M5@#@QҤ@R%@z@Ѯ@*@@۸@4@@@5@@@;@_@@@N@[1@MS@|l@?|@@|@ll@O@&@7@@R,A+{AAA 7ArdALjAA A A A֬ A( ArA EA2 AAwAAVAj@A6A3AuAA4BAAŶAAAAAAAŶAA4BAAuA3A6Aj@AVAAwAA2 A EArA( A֬ A A A AALjArdA 7AAA+{AR,A@7@&@O@ll@|@@?|@|l@MS@[1@N@@@_@;@@@5@@@4@۸@@*@Ѯ@z@R%@QҤ@#@M5@N@@g@-@#@JɊ@@@de@˥|@ɐv@kp@Pj@d@6^@@@=M@oH@mC@=@l8@A3@H,.@4-)@D$@r@m@/@@ @@>i@8@>?Q:? d??7A?4?l??<???ϩ?R?aɝ?>?\j?*??z?{?tq?h?^?P1V?M?hjE?.n=?5? =.?u'?u ?P?G??%?9-?{4? '_@(#@ (@},@ 2@m.7@ef<@A@G@L@R@?W@@h]@-c@+i@n@t@{z@텀@@@ى@@b2@sg@@@$@8k@@@~R@ͣ@Q@{I@@{@$A@@@)@p@ֳ@@*@]@@.@@@@}@I@@G@0z@>@@@AJAAPA[|AAȷAJA A A A A| AMAnAA|AAABA A3AәAsAp@AA8A@@AAAA8AAp@AsAәA3A ABAAA|AAnAMA| A A A A AJAȷAA[|APAAJAA@@>@0z@G@@I@}@@@@.@@]@*@@ֳ@p@)@@@$A@{@@{I@Q@ͣ@~R@@@8k@$@@@sg@b2@@ى@@@텀@{z@t@n@+i@-c@@h]@@@L@G@A@ef<@m.7@ 2@},@ (@(#@>_@<@@@H @@@@?t??7???$v?E?Ի?E??U??㸜??m??Æ??my?o?f?}]?iT?GL?zD? '@~5D@ I@O@kT@\5Z@_@Ve@Pyk@/]q@XQw@&U}@@zĄ@ۇ@k@@CF@t@@ޚ@@.X@<@ܧ@!@g@@@<@x@0ž@@@9@4@y/@*@%@o @}@s@@t@ @@%@}??(?|? ??S????t?[?:?(C?@R$@4-)@1.@"3@=8@Fl=@B@H@}sM@jR@7X@h(^@{c@i@~o@kfu@H^{@@＃@Ά@@@%@M@z@w@@@R@V@ͩ@ @M@k@`ζ@E @J@@@W@"@N@uu@@"@@@Q@@@#@!x@kF@b@e@d@@@@@dAAtAOAAAȷAAi A\ A( AY A AK A A~A A+A>A(WAͮAA8AOkA A\AAA\A AOkA8AAͮA(WA>A+A A~A AK A AY A( A\ Ai AAȷAAAOAtAAdAm7A@@@@@b@kF@!x@#@@@Q@@@"@@uu@N@"@W@@@J@E @`ζ@k@M@ @ͩ@V@R@@@w@z@M@%@@@Ά@＃@@H^{@kfu@~o@i@{c@h(^@7X@jR@}sM@H@B@Fl=@=8@"3@1.@4-)@R$@>@@;G@@LY @ @%@ڜ@/??&V?n?^I??\??C?}?D??? ?B?ب?7??Ƀ?}?Ss?Yj?cla?(X?W P?G???7?}~0?=)?:"?u??b?(3? ?'?/?6?3>?&F?{]N?V?_?h?-q?b{??[ч?? w?>???y?կ?2??j?H?P?M??r?V,?V?%?/@7@4 @1@@@C@"@'@,@1@v6@;@A@iF@K@=Q@V@S\\@b@g@m@4js@Uy@O@@綅@Lj@ދ@^@@B@8m@/@]̞@E@e6@9n@9@@@S@@»@@G(@TV@V@@@@@@@@@V@e@{@X@6@@f@s@@@[@XA+{AєAtAЬAAALjAhA= A A Aj} A' A8 AW A AYA!A;,A+AA2 A'>AcA|A6A6A|AcA'>A2 AA+A;,A!AYA AW A8 A' Aj} A A A= AhALjAAAЬAtAєA+{AXA[@@@s@@@6@X@{@e@V@@@@@@@@@V@TV@G(@@»@@S@@@9@9n@e6@E@]̞@/@8m@B@@^@ދ@Lj@綅@@O@Uy@4js@m@g@b@S\\@V@=Q@K@iF@A@;@v6@1@,@'@"@C@@@1@4 @7@/@%?V?V,?r??M?P?H?j??2?կ?y???>? w??[ч??b{?-q?h?_?V?{]N?&F?3>?6?/?'? ?(3?b?w??ُ?t&?`-?[4?Iw?|?_~??k?Fk??>Π?T?jӬ??G~???ƻ???|???E?Aq@֔@\ @@@@|@w4 @@@+.@3@8@=@mC@AMH@M@S@X@h(^@c@l}i@?o@nu@{z@o@"m@p@1z@@Ĝ@@yѕ@@@:@b@^@@@@U@p9@c@@;@վ@@@)@;@~H@N@M@$E@C4@v@@@J@M@@}@7@~@:@ޥ@@M@@XAdAgAaAPA 7A AAAhAW A A\ A AUq AY AW A Ay AW A( AB A AAAAA AB A( AW Ay A AW AY AUq A A\ A AW AhAAA A 7APAaAgAdAXA@M@@ޥ@:@~@7@}@@M@J@@@v@C4@$E@M@N@~H@;@)@@@վ@;@@c@p9@U@@@@^@b@:@@@yѕ@@Ĝ@@1z@p@"m@o@{z@nu@?o@l}i@c@h(^@X@S@M@AMH@mC@=@8@3@+.@)@$@w4 @|@@@@\ @֔@Aq@E???|???ƻ???G~??jӬ?T?>Π??Fk?k??_~?|?h>w?Dm?d?[?f+S?qJ?B?M:?{b3? ,?$?)??I/?4?.??q#?[*?1?>9?Q@?H??Q?;Y?b?k?t?ȡ~?G?c?0?T??W?8?@?r?Tη?S???4??Ak?'?y?L?C@]@u@ @-@W@@$@h@@@{-@1@6@<@M>A@zF@K@m+Q@V@#\@Ka@]g@m@r@x@)~@;@7@:@A@XN@q_@t@[@?@ǝ@@ @_.@~R@v@j@@8޶@'@U@,2@G@qW@b@!h@:g@W_@O@$8@@@|@z@0@@!x@@5@@/e@T@@+7@[@m7A7A&/AAAAApA*AABAW A- A, A A AUq A A AvK A| A A A8 A8 A A A| AvK A A AUq A A A, A- AW ABAA*ApAAAAA&/A7Am7A[@+7@@T@/e@@5@@!x@@0@z@|@@@$8@O@W_@:g@!h@b@qW@G@,2@U@'@8޶@@j@v@~R@_.@ @@ǝ@?@[@t@q_@XN@A@:@7@;@)~@x@r@m@]g@Ka@#\@V@m+Q@K@zF@M>A@<@6@1@{-@4(@o#@h@@$@W@-@ @u@]@C@L?y?'?Ak??4???S?Tη?r?@?8?W??T?0?c?G?ȡ~?t?k?b?;Y??Q?H?Q@?>9?1?[*?q#??.?4?؁??C??!?(?0?7?X+??G?nFO?jW? o`?ki? r?:|???M?ש?,? ם?#?y?zƯ???7'?x? ?$?J??w]?M'?D?-@C@~ @K@5@@@@!@&@l+@N0@D5@N:@k?@D@I@c2O@kT@Z@L_@/e@Rj@kp@Pv@"|@@ @#@@@q@(@o@3@J@c@~@@@@ӫ@@# @$@<@P@b@o@x@l|@z@ur@fc@L@.@@@@vU@@i@?@@kF@@@/e@ޥ@3@@@@AJAA AgA~+AAA6AOA\AAU A A At A A A( AM A@e AUq AUq A@e AM A( A A At A A AU AA\AOA6AAA~+AgA AAJAA@@@3@ޥ@/e@@@kF@@?@i@@vU@@@@.@L@fc@ur@z@l|@x@o@b@P@<@$@# @@ӫ@@@@~@c@J@3@o@(@q@@@#@ @@"|@Pv@kp@Rj@/e@L_@Z@kT@c2O@I@D@k?@N:@D5@N0@l+@&@!@@@@5@K@~ @C@-@D?M'?w]??J?$? ?x?7'??@@y?#? ם?,?ש?M???:|? r?ki? o`?jW?nFO?G?X+??7?0?(?!?C???؁? ?#P??_ ?b?'?T[.?5?]M=? &E?.@M? U?=^?#g?XPp?Sy??Æ?v?#;?K?hL??T??LK??F??????}?{ ?ؿ??X@@ " @g@@O2@@=P @$@)@ .@3@|8@=@B@&@:@M@_@qo@i|@@@P@@V@p@^Z@<@@@@Pn@"@@g@f@?|@@[@@@:@e@@@@d@A+{AQAAAԕABAA{AALjAhAhAJAW Aa A@ A A A A A A A A A@ Aa AW AJAhAhALjAA{AABAԕAAAQA+{AAd@@@@e@:@@@[@@?|@f@g@@"@Pn@@@@<@^Z@p@V@@P@@@i|@qo@_@M@:@>&@i@@@w՝@Ě@Ĵ@@y@e@L@@@@3|@-y@s@2n@(h@ b@@h]@XW@ބR@V,M@w?p??g??Ï?*?4?l?H?L? y?͸?K?n????.??~I?/?@*@Ѽ@u @F@N@@$@@SS#@ (@,@1@Ο6@;@@@JE@K@sdP@U@+[@&`@1f@k@rq@&w@|@.Z@.F@[7@P-@'@%@'@r,@3@K=@aH@T@\a@9n@z@ @揱@@@@@0@͊@y@b@D@f@@3@}@C4@@͂@@@p @{@@kF@5@~@@s@@7@Q@@R,AAAA>AAXAAAG*AAAeAȷAhA^9AhAAAAAAAhA^9AhAȷAeAAAG*AAAXAA>AAAAR,A@Q@7@@s@@~@5@kF@@{@p @@@͂@@C4@}@3@@f@D@b@y@͊@0@@@@@揱@ @z@9n@\a@T@aH@K=@3@r,@'@%@'@P-@[7@.F@.Z@|@&w@rq@k@1f@&`@+[@U@sdP@K@JE@@@;@Ο6@1@,@ (@SS#@@@$@N@F@u @Ѽ@*@@/?~I??.????n?K?͸?@@H?l?4?*?Ï???g?p?h>w?m?-d?([?tS?c-K?2(C?c;?3?n,?ގ%??-?,? ?_; ?M???#?I*?f1?$o9?A?I??Q?]Y?jb?Hgk?Щt?3~???rC? ??4???1??jL???,???6??|?Z^?4@zO@~ @@j@i@ @!@H&@+@/@ݷ4@9@>@C@H@7N@ӄS@X@N^@c@Ti@n@)t@Cz@@@΅@ @~@@y@5@}@ٛ@͞@ڢ@~@5@x@@{@#@&@@@@X@g@H@"@@'@σ@`=@B@ޒ@-@@7@@@p @?|@@@7@lW@f@d@Q@,@@@N@oA,AJAA8(AEAEAA 7AAA+MAAgA'A@@eBAeBA6AAA'AgAA+MAAA 7AAEAEA8(AAJA,AoAN@@@,@Q@d@f@lW@7@@@?|@p @@7@@@-@ޒ@B@`=@σ@'@@"@H@g@X@@@@&@#@{@@x@5@~@ڢ@͞@ٛ@}@5@y@@~@ @΅@@@Cz@)t@n@Ti@c@N^@X@ӄS@7N@H@C@>@9@ݷ4@/@+@H&@!@ @i@j@@~ @@@Z^?|??6???,???jL??1???4?? ?rC???3~?Щt?Hgk?jb?]Y??Q?I?A?$o9?f1?I*?#???M?_; ?1???g?"?O(?0?o7?; ??F?N? [W?~_?%h?$r?v{?ʖ??&??t?q ?Ƣ?U?.??jB?f?p?cE?B?]i?5?e2???@Z@' @h6@@@X@E@}$@4-)@-@2@7@<@A@F@K@=Q@V@[@Va@f@&Zl@q@w@4?}@{@]@C@P-@h@ @j@o@@(@@5@@ܧ@ת@Э@XȰ@@@@@j@I@#@@@B@M?@[@ԙ@$8@@@@7@@@f@?@!x@}@'@@e@@z@>@7@@@@&zA!AAQAAUAA.AXAAAYAA@@iAiAAAAYAAAXA.AAUAAQAA!A&zA@@@7@>@z@@e@@'@}@!x@?@f@@7@@Q@S@@$8@ԙ@[@M?@@@@#@I@j@@@@@XȰ@Э@ת@ܧ@@5@@(@@o@j@ @h@P-@C@]@{@4?}@w@q@&Zl@f@Va@[@V@=Q@K@F@A@<@7@2@-@4-)@}$@E@X@@@h6@' @@@??e2?5?]i?B?cE?p?f?jB??.?U?Ƣ?q ?t??&??ʖ?v{?$r?%h?~_? [W?N?F?; ??o7?0?O(?"?g???1?f9?) ?#P?ȭ?C ?'?.?>f5?@0@$@@ @E@@@Ѯ@@L@ӌ@n@J@!@@@V@;@4@@:@`@]@@@@@g@i@@@@6@b@@S@0z@&@@>G@j@@d@MA|AdAJAQAǶAAaAtAAC A@@PAPAEA.AC AAtAaAAǶAQAJAdA|AMAd@@j@>G@@&@0z@S@@b@6@@@@i@g@@@S@@]@`@:@@4@@@@@!@J@n@ӌ@L@@Ѯ@@@E@ @@$@0@>@N@q_@Zs@4@q@~…@@ @)oz@t@?o@$i@GAd@^@xY@*T@N@I@D@?@W:@S5@;0@j,@1L'@ܩ"@@@6@o@ @u@]@Z@y??Ւ?.????7?v?-?i?rĬ?ʦ??K?ƕ?e?+??~#?x?Vo? Hf?}]?T?L?D?f5?.?'?C ?ȭ?#P?) ?f9?V?O ???n?*%? ,?R3?:?nB?ZJ?R?Z?c?l?Ju?R?X?h?꾎?T?? ?B?mʪ?qٰ??:m???u?r?l??w]??C?@ @) @:@@@K@o @1b%@ *@q.@S3@l8@[=@[B@%lG@L@Q@V@=I\@a@ g@l@r@w@D)}@de@:@:@@ Ҍ@@@@8m@W@C@D.@@@Q@Ѭ@{@.@9s@ L@ @@@y@5@@ @6@@_@@]@@-@͂@@@0@M@0[@X@kF@#@@G@O@@Eg@3@y1@x@@@@cARA7AAJA#AL\AAtAAoAoAAtAAL\A#AJAA7ARAcA@@@x@y1@3@Eg@@O@G@@#@kF@X@0[@M@0@@@͂@-@@]@@_@@6@ @@@@@@ @ L@9s@.@{@Ѭ@Q@@@D.@C@W@8m@@@@ Ҍ@@:@:@de@D)}@w@r@l@ g@a@=I\@V@Q@L@%lG@[B@[=@l8@S3@q.@ *@1b%@o @K@@@:@) @ @@C??w]??l?r?u???:m??qٰ?mʪ?B? ??T?꾎?h?X?R?Ju?l?c?Z?R?ZJ?nB?:?R3? ,?*%?n???O ?V?]? ??!??8#?*?\61?8?l$@?G?W P?`X?R`?i?=r?P|????P?K?@?5?Ǩ?RĮ??12?գ?<@@@@Q@@@d@ AXAARAA!A7A CA CA7A!AARAAXA Ad@@@Q@@@@><@@sz@@ll@@6@0O@!x@{@@J@z@vU@"@@ޒ@$8@`@_@@^Z@@X.@@@,@r@;@@z @!? (?/?R6?=?E?\M?U?=^?f?o?By?f?1O?G[?e?ߕ?dY??T??ﶲ??K?$?{?N?^I?Ak??%?ҽ?|}?/@&@ @+@A@@ @t!@&@2*@K/@ 4@8@g=@B@MG@L@Q@LW@=I\@2a@f@El@q@&w@˥|@@1߃@@1z@*L@ @@Δ@@@Z@3@ @@@@}@X@V$@@@Xl@3$@վ@X@#@@8Q@@^Z@@:@ԙ@B@C4@Pn@@|@@@e@#@~o@0@I@|@b@n@@:@0z@ޥ@k@@@@M@#@@@@'@o"@N@d@d@N@o"@'@@@@#@M@@@@k@ޥ@0z@:@@n@b@|@I@0@~o@#@e@@@|@@Pn@C4@B@ԙ@:@@^Z@@8Q@@#@X@վ@3$@Xl@@@V$@X@}@@@@ @3@Z@@@Δ@@ @*L@1z@@1߃@@˥|@&w@q@El@f@2a@=I\@LW@Q@L@MG@B@g=@8@ 4@K/@2*@&@t!@ @@A@+@ @&@/@|}?ҽ?%??Ak?^I?N?{?$?K??ﶲ??T??dY?ߕ?e?G[?1O?f?By?o?f?=^?U?\M?E?=?R6?/? (?>!??EP?+?<?Ӏ???f ?w?ؾ?<?e%?C,? 4?t;?JC?J?S?y[? d?m?(v??R?T?꾎??~j?B?'??}???Y?x?ĭ??!?M?w(??O?@@ @h6@i@@@r@F#@}(@z-@_1@6@a;@C@@#5E@|5J@XDO@0aT@wY@^@d@Ti@n@&t@y@~@;@ @:ć@7@X@%@@ĕ@ܔ@Ke@M5@d@ ң@ŝ@g@G-@@@h@@̹@u@@@E@@8Q@@6@@[@`=@}@@@@@@V@@@?@}@@@|@@q-@h@@@@j@Eg@C)@3@m@7@]@0@@R!@+7@+7@R!@@0@]@7@m@3@C)@Eg@j@@@@h@q-@@|@@@}@?@@@V@@@@@@}@`=@[@@6@@8Q@@E@@@u@̹@@h@@@G-@g@ŝ@ ң@d@M5@Ke@ܔ@ĕ@@%@X@7@:ć@ @;@~@y@&t@n@Ti@d@^@wY@0aT@XDO@|5J@#5E@C@@a;@6@_1@z-@}(@F#@r@@@i@h6@ @@@O??w(?M?!??ĭ?x?Y???}??'?B?~j??꾎?T?R??(v?m? d?y[?S?J?JC?t;? 4?@@@ؾ?w?f ???v>?P ??,?4?#?*?1?9?@?`H?fP?X?1a?Gi?Js?P|?m? ݇??R?t?=??R?@ >#? ?D??_$?!?p(?l/?6?>?E?M?U?=^?f?o?y?9???3?9x?q?l??a?@@S??O?f?.???w]? ?`l?!@@ @x@>@ @X@@ ($@|(@|;-@1@6@Q;@~"@@E@tI@N@S@Y@h(^@rTc@(h@m@s@hx@}@D@@@̵@p@,@@@@e@y#@@D@T@z @w@p@@į@g@N@@-@!@9@@#@@@;@B@'@@@.@$8@C4@!@@Q@@?@@|l@@S@v@@&@kF@cS@L@*2@~@~@h@@{@@:@sz@@I@I@@sz@:@@{@@h@~@~@*2@L@cS@kF@&@@v@S@@|l@@?@@Q@@!@C4@$8@.@@@'@B@;@@@#@@9@!@-@@N@g@į@@p@w@z @T@D@@y#@e@@@@,@p@̵@@.F@D@}@hx@s@m@(h@rTc@h(^@Y@S@N@tI@E@~"@@Q;@6@1@|;-@|(@ ($@@X@ @>@x@ @@!@`l? ?w]???.?f?O??S???a??l?q?9x?3???9?y?o?f?=^?U?M?E?>?6?l/?@@@?D? ?#? >P>P?,? ??T??,&?9-?,4?L;?JC?J?R?@[?c?l?u?~?G?-4?rC?u?P˘?D??y?@@bĻ?j??n3??>?`?(?ރ??@@@q @@@A@@ !@d&@+*@y/@4@8@=@[B@V8G@]"L@OQ@V@+[@E`@je@Pj@"o@nu@wYz@|@@@ۇ@7@@@@]@\@@Ě@u@%@XӢ@~@R%@Ȫ@g@@.@$@@-@Ȧ@@X@@5@V@@@f@<@L@O@$E@6,@@@@[1@@MS@@0@@v@@5@@@@i@|@#@@*2@@@q-@lW@ll@ll@lW@q-@@@*2@@#@|@i@@@@5@@v@@0@@MS@@[1@@@@6,@$E@O@L@<@f@@@V@5@@X@@Ȧ@-@@$@.@@g@Ȫ@R%@~@XӢ@%@u@Ě@@\@]@@@@7@ۇ@*,@~@|@wYz@nu@"o@Pj@je@E`@+[@V@OQ@]"L@V8G@[B@=@8@4@y/@+*@d&@ !@@A@@@q @@@@?ރ?(?`?>??n3??j?bĻ???y??D?P˘?u?rC?-4?G?~?u?l?c?@[?R?J?JC?L;?,4?9-?,&??T?? ?,?P?P>OV>w>?i ??c?RO?#?*?[1?8?g@?;H?W P?g;X?i`?SWi?Fr?v{?t?(P?M?m?K?F?ß?M?@@-?l?$?{X???9?\?V,??D?l@@ @@l@6%@f@@$@D(@{-@-1@@6@k:@?@yD@;RI@7N@F)S@&X@.]@ZAb@]g@l@q@Lv@"|@@]V@|@q@M@#@@M@o@@`J@@@66@%ԥ@9n@@”@, @@$@@E @u@վ@,@y@@@"@D@^Z@fc@W_@M@.@@@v@v@.@[1@@@S@J@e@@@8@v@!x@0@@c@I@kF@ @@@6@6@@@ @kF@I@c@@0@!x@v@8@@@e@J@S@@@[1@.@v@v@@@.@M@W_@fc@^Z@D@"@@@y@,@վ@u@E @@$@@, @”@@9n@%ԥ@66@@@`J@@o@M@@#@M@q@|@]V@@"|@Lv@q@l@]g@ZAb@.]@&X@F)S@7N@;RI@yD@?@k:@@6@-1@{-@D(@$@@f@6%@l@@ @@l@D??V,?\?9???{X?$?l?-??Y?M?ß?F?K?m?M?(P?t?v{?Fr?SWi?i`?g;X?W P?;H?g@?8?[1?*?#?RO?c??i ??w>OV>z>w>96?????!?E(?R//?R6?߯=?6HE?M?.U?}]?8 f?n?w???g?R? `?ԏ?N?W??׬?匰?琶??i?$v?K ???e?)? ??y @@@ @o@@4@v@!@F+&@2*@b/@s3@L8@<@A@zF@NK@O.P@U@Z@_@d@,i@Gn@4js@x@}@{@^@@zV@.@e@9@ړ@z@H@(@P@@|@ @@!@ͣ@, @.@N@m@̹@3$@r@@@#@H@b@p@ur@:g@N@6(@@"@]@@@N@Ut@Q@@S@z@I@J@t@\@V%@@?|@ @σ@}@:@!x@@]@]@@!x@:@}@σ@ @?|@@V%@\@t@J@I@z@S@@Q@Ut@N@@@]@"@@6(@N@:g@ur@p@b@H@#@@@r@3$@̹@m@N@.@, @ͣ@!@@ @|@@P@(@@@@9@e@.@zV@@^@{@}@x@4js@Gn@,i@d@_@Z@U@O.P@NK@zF@A@<@L8@s3@b/@2*@F+&@!@v@4@@o@ @@@y @? ?)?e???K ?$v?i??琶?匰?׬??W?N?ԏ? `?R??g??w?n?8 f?}]?.U?M?6HE?߯=?R6?R//?E(?!?????96?w>z>h>>P?{? ??R?<?%?c,?A3?M:?nB?&J?R?wJZ?_b?Hgk?Ut?}?y? S?M?\j?'?q ??5????4?? ??4o?W? d? ??Z^?@p@ @@@@A0@r@#@+&(@,@1@S5@>:@8>@C@^H@V,M@WR@ V@[@`@%e@Rj@o@3t@mz@9@/@zĄ@Z@@@ @@N@@>v@/@^@M @~@p*@@!@”@@g@ƴ@@Xl@;@@!@I@g@y@V@z@!h@~H@;@@@`=@Y@]@@=@@Z@@[1@A@7@@+@@@g}@@i@p @@@:@t9@M@M@t9@:@@@p @i@@g}@@@+@7@@A@[1@@Z@@=@@]@Y@`=@@@;@~H@!h@z@V@y@g@I@!@@;@Xl@@ƴ@g@@”@!@@p*@~@M @^@/@>v@@@@ @@@Z@zĄ@/@9@mz@3t@o@Rj@%e@`@[@ V@WR@V,M@^H@C@8>@>:@S5@1@,@+&(@#@r@A0@@@@ @p@@Z^?? ? d?W?4o?? ??4?@@@5??q ?'?\j?M? S?y?}?Ut?Hgk?_b?wJZ?R?&J?nB?M:?A3?c,?%?<?R?? ?{?P?>h>0>+>3>?P ???o?c#?*?R1?.8?ӎ??)G?N?vW?u__?g?p?Sy?X?1O?7?T@?Fk?4?e'??m?D?8??\????4? ??{ ?CA?՛?y @)@Ѽ@@ @A@@@B@X!@%@ *@w.@2@}7@<@@@lhE@#J@N@ջS@X@p{]@hb@]g@&Zl@/]q@fv@t{@/C@΂@YZ@@7u@@S@@@1@ȸ@K=@@;<@@p*@@@g@į@@h@@@ @J@j@X@͊@@l|@b@;@@@uu@|@m@*@@@Q@ޒ@@@@@Q@@h@@@?@ݵ@@g@@@@@@@g@@ݵ@?@@@h@@Q@@@@@ޒ@Q@@@*@m@|@uu@@@;@b@l|@@͊@X@j@J@ @@@h@@į@g@@@p*@@;<@@K=@ȸ@1@@@@@7u@@YZ@΂@/C@t{@fv@/]q@&Zl@]g@hb@p{]@X@ջS@N@#J@lhE@@@<@}7@2@w.@ *@%@X!@B@@@A@@ @Ѽ@)@y @՛?CA?{ ?? ?4????\?@@@?e'?4?Fk?T@?7?1O?X?Sy?p?g?u__?vW?N?)G?ӎ??.8?R1?*?c#?o???P ??3>+>0>)]>6{>D>??~P?EP?f? ?'?T[.?>f5?f5?T[.?'? ?f?EP?~P???D>6{>)]>(>2>>?'g? ??[ ?n?`$?Щ+?2?9?A?H?@@@ki?1r?D5{?e2>(>9>>.>հ>-H? ?Է?ȹ??W"?O(?\/?"6?>?E?@@@e?^n?h>w?A.?܄?A?ԙ?ب?ؘ?0)?? .??Ÿ??6??b??"?5D?'?V,?Q?N?@B@ @ @@2@4@@SG"@&@*@b/@3@D7@ef<@@@yE@uJ@N@0`S@X@\@2a@Yf@'k@o@t@-y@)~@@#@@H@r@ߍ@aK@@-@:@@K=@^@@@@w@ @G-@X@{@.@L@@@@@b@,2@@@TV@W@V@@p@@$@:g@@@@@3@ԙ@e@@@]@@Q@@@C4@Z@m@m@Z@C4@@@Q@@]@@@e@ԙ@3@@@@@:g@$@@p@@V@W@TV@@@,2@b@@@@@L@.@{@X@G-@ @w@~@66@@^@K=@@:@-@@aK@ߍ@r@H@@#@@)~@-y@t@o@'k@Yf@2a@\@X@0`S@N@uJ@yE@@@ef<@D7@3@b/@*@&@SG"@@4@2@@ @ @B@@N?Q?V,?'?5D?"??b??6??Ÿ?? .??0)?ؘ?ب?ԙ?A?܄?A.?h>w?^n?e?LW]?.U?.@M?E?>?"6?\/?O(?W"??ȹ?Է? ?-H?հ>.>>9> >eF>xC>P>}&??f ?#P?Dk?W?X;&?>,?3?;?]B?@@@b?Yj?|Bs?:|??Xs?M?G? b???(t?/?Dϱ?}?뮽??y?w???i?Q?Y?.?/e@@q@2 @ @@@|@@#@ (@K,@N0@4@6]9@=@JB@F@-`K@:O@kT@ @Y@]@sb@]g@l@p@,?X;&?W?Dk?#P?f ??}&?P>xC>eF> >P>>T>c>?zs? ??O??q#?*?0?7?X+??9F?KN?P1V?'Q^?f?DBo?x?\? 9?? ?? ?QR?R?v@(@@%@T@|@ŝ@@@Ȫ@Ѭ@Ѯ@XȰ@#@@qo@<@'@;@Z@@@@y@@5@l|@z@@@@@]@ֳ@3y@C-@@`@@M@L@[@6(@L@_@_@L@6(@[@L@M@@`@@C-@3y@ֳ@]@@@@@z@l|@5@@y@@@@Z@;@'@<@qo@@#@XȰ@Ѯ@Ѭ@Ȫ@@@ŝ@|@T@%@@(@>v@1@@@aK@#@d@J@#@@;@@9{@Pv@q@l@:h@c@6^@DHZ@jU@OQ@L@H@ȋC@?@:@P6@1@-@v)@E%@!!@ @@@@4 @c @j@@-?g?w]?r?G??s? ?? ?G???T>>P>dd>a>2a>`>A>96?1?u?]?v? ?b?'?-?4?(;?JC?qJ?:R?+Z?b?>k?Ss?!|???<~?m?|?;??e?a??n?\?j??A?]U?>??]?~I?@T?|}?hb@@ @x@@Pn@g@l@"@&@*@ /@A3@7@;@C@@D@I@M@R@V@+[@_@Ud@h@m@.r@v@t{@ @\@{@@J@L@ߍ@%@h@@@H@`J@u@D@&@ ң@@@Q@@Э@{@揱@_@$@8޶@@-@»@J@0ž@,2@@@#@TV@y@@@@ i@;@@@N@]@^Z@@f@:g@*@'@(@(@@*@:g@f@@^Z@]@N@@@;@ i@@@@y@TV@#@@@,2@0ž@J@»@-@@8޶@$@_@揱@{@Э@@Q@@@ ң@&@D@u@`J@H@@@h@%@ߍ@L@J@@{@\@ @t{@v@.r@m@h@Ud@_@+[@V@R@M@I@D@C@@;@7@A3@ /@*@&@"@l@g@Pn@@x@ @@hb@|}?@T?~I?]??>?]U?A??j?\?n??a?e??;?|?m?<~???!|?Ss?>k?b?+Z?:R?qJ?JC?(;?4?-?b?'? ?v?]?u?1?96?A>`>2a>a>dd>>>k>g?>j>j?'g?k ?,?[??b$?*?1?8???\G?N?V?t^?7g?žo?x??[??k??M?6?ʌ??떮?LK?C??%?{X?k??̫?Z?w(?a?>?"@%@u@4 @+@O@@@@#@c'@j,@R00@i4@8@<@ OA@E@uJ@-N@jR@kW@[@l`@d@l}i@ n@r@&w@t{@!@@h@@@@r@i@@@N@z@@Ě@@@d@ @z @@@ת@@ @M@# @@c@@@E @x@5@$A@@E@@X@#@#@@W@@V@X.@v@W@b@;@ @@@3@D@D@3@@@ @;@b@W@v@X.@V@@W@@#@#@X@@E@@$A@5@x@E @@@c@@# @M@ @@ת@@@z @ @d@@@Ě@@z@N@@@i@r@2@#@{@@h@!@t{@&w@r@ n@l}i@d@l`@[@kW@jR@-N@uJ@E@ OA@<@8@i4@R00@j,@c'@#@@@@O@+@4 @u@%@"@>?a?w(?Z?̫??k?{X?%??C?LK?떮??ʌ?6?M??k??[??x?žo?7g?t^?V?N?\G???8?1?*?b$??[?,?k ?'g?j?j>g?>k>>>>>s>>>n>? ?G?Y+?C??!?,'?.?5?I>>s>>>+x>YQ>z>>7>>?!?ۻ ?z?|??$?+?K2?>9?g@?G?dXO?#W?m%_? `g?o?x?˳?D??꾎?ب?ذ? ם??~??ɟ?%^?:?!6?O?,??P???Y?]A?"@/@zO@ @ձ@Ov@;G@@$@ @"@&@ *@1.@V:2@`6@W:@&>@mC@IG@K@6O@f&@ӫ@v@U@j@@k@@O@@۸@E @O0@D@J@$A@v(@>@E@X@G(@@G@@#@x@@@@#@#@@@@x@#@@G@@G(@X@E@>@v(@$A@J@D@O0@E @۸@@O@@k@@j@@@ӫ@>&@9n@5@@ @D.@aH@Z@Ke@h@e@\@M@9@ @@X@ @@h@;@ @t{@XQw@r@n@{j@=e@Va@E\@X@f@W:@`6@V:2@1.@ *@&@"@ @@$@;G@Ov@ձ@ @zO@/@"@]A?Y???P??,?O?!6?:?%^?ɟ??~?? ם?ذ?ب?꾎??D?˳?x?o? `g?m%_?#W?dXO?G?g@?>9?K2?+?$??|?z?ۻ ?!??>7>>z>YQ>+x>">J>u>{>6t>{k> >{?f/ ?4?ȹ??"?p(?/?%5?@@{>u>J>">/,>S>>>P!>>> =??5 ????U%?u+?h2?$o9?i@?G?dXO?vW?^?#g?|o?x?p??h?O? )??H3?Ed??Y?t?M???x?K ?B???Ւ?Q:??@?h@@̆ @X( @@@S@#@@#@'@+@/@3@U7@D;@@@~5D@^H@L@;P@T@N-Y@@h]@a@e@{j@D\n@r@v@9{@9@@Yȃ@م@@@.@#@@@@ړ@ĕ@@@W@$@@ڢ@T@@@_.@@@4@9@ @g@{@Q@*@@@>>S>/,>>>[>{>C>wh>T>2>?O ?4?? ?:"?(?R//?5?T>@@{>[>>> >E>#>dd>~> >>>"??8s ?)?T?f!?c%?u+?y2?O9?dV@?G?N?ƠV?w^?f?n?h>w??i???\j?HM?hL?g?r?@@?V?\?@@ٛ@K=@w՝@c@@b@ ң@e6@V@ܧ@@~R@z@ӕ@ͣ@J@ @{@gR@@Բ@~@@L@$@@)@ @@@@@`ζ@8޶@8޶@`ζ@@@@ @@)@@$@L@@~@Բ@@gR@{@ @J@ͣ@ӕ@z@~R@@ܧ@V@e6@ ң@b@@c@w՝@K=@ٛ@@>@@@@%@XN@p@7@q@@zĄ@΂@Ӏ@}@-y@w?n?f?w^?ƠV?N?G?dV@?O9?y2?u+?c%?f!?T?)?8s ??"?>> >~>dd>#>E> >A>rM>>~C>0>k>h>>?BE?W ?M?? ?,"?](?/?5?I_@+"@Y%@R)@-@b1@D5@-9@I=@ A@E@H@L@P@T@X@E\@`@d@h@l@p@t@x@˥|@/C@/@^@|@ۇ@̵@4@X@ @@@N@o@}@3@Ě@J@ǝ@:@ڢ@E@R@<@%ԥ@@R%@;@C@>?@G-@ @@J@?@C@;@R%@@%ԥ@<@R@E@ڢ@:@ǝ@J@Ě@3@}@o@N@@@ @X@4@̵@ۇ@|@^@/@/C@˥|@x@t@p@l@h@d@`@E\@X@T@P@L@H@E@ A@I=@-9@D5@b1@-@R)@Y%@+"@>_@@@k[@@4 @@`8@@?M'? ??;?p?B?[/?6?~X???a???Mb?D?B?`\?ő??1O?ց?z?pr?!j?b?$Z?tR?J?C?@@/?](?,"? ??M?W ?BE??>h>k>0>~C>>rM>A>>=>>r%>\> >'M>Y>D>â?\?8s ????*%?+?A2?8?B??WF?KN?U?ܐ]?݀e?m?u?~?p?#?&?m?:?#?e'?`F??կ?E?к?v?7??f??Y>'M> >\>r%>>=>>4>A>> >ʝ>{>ߦ>O >>?9?P ?(?@@@J(?.?k'5?(;?B?&J?9Q?Y?`?%h? q?my???g??!?5?>?=???L???V?;????"???o??V?B?K@@ @Q @@@@@V@"@ &@b*@1.@1@S5@Gm9@;=@ A@D@|H@L@sdP@f&@W@@\@9@@t@G-@3<@3<@G-@t@@9@\@@W@>&@š@ @9n@w@@8@\a@|@%@ތ@#@8k@aH@@@/@K@@[@o@@'@y@ @Zs@ Ҍ@)@1z@:ć@@@~@@}@mz@fv@r@n@'k@]g@c@_@[@X@f?5?!???g??my? q?%h?`?Y?9Q?&J?B?(;?@@J(?!???(?P ?9??>O >ߦ>{>ʝ> >>A>4>ul>>ֻ>>Z>C >F>'M>z>>Ӏ?F?5 ?@@@$?*?s1?8?>?F?.@M?T?tK\? d?l?Ut?;|?m???3? ?S??#?Ǩ?? R?н?C???Pi?Q?R?Ak? ??>??ڜ@I@C@ @v@@@i@}@@-E#@&@k*@`;.@11@S5@6]9@I=@@@D@^H@]"L@6O@~S@kW@+[@6^@sb@Yf@3 j@Fm@/]q@3t@x@"|@|@D@J@ @@Q@@4@h@@%@y@(@t@yѕ@t$@8m@w@ޚ@/@$@M5@:@3@M @E@XӢ@Q@Q@-@@p*@5@@^@ܧ@R%@_@k@@@@@@@k@_@R%@ܧ@^@@5@p*@@-@Q@Q@XӢ@E@M @3@:@M5@$@/@ޚ@w@8m@t$@yѕ@t@(@y@%@@h@4@@Q@@ @J@D@|@"|@x@3t@/]q@Fm@3 j@Yf@sb@6^@+[@kW@~S@6O@]"L@^H@D@@@I=@6]9@S5@11@`;.@k*@&@-E#@@}@i@@@v@ @C@I@ڜ@?>?? ?Ak?R?Q?Pi???C?н? R??Ǩ?#??S? ?3???m?;|?Ut?l? d?tK\?T?.@M?F?>?8?s1?*?$??)??5 ?F?Ӏ?>z>'M>F>C >Z>>ֻ>>ul>ר>@B> >>=>ʝ>i>>@@2>?ZG ?@@@>!?j'?-?4L4?;?A?H?rBP?jW?u__?7g?DBo?~w??G??I5?qґ?%?dY?(C?`F?b?И??O?Kп?ji?? ????'?V,?|?Z?.@t@@C @i@@]@@*Y@E@o#@'@2*@`;.@1@܃5@-9@<@y@@~5D@!?C??l?H?ZG ??2>>>>i>ʝ>=>> >@B>ר> H>X>>ֻ>>#7>>a>@@1>}&?\?ۻ ?E???#?*?}~0?7?=?D?K?f+S?Z?af> >a>>#7>>ֻ>>X> H>g>ר>2>-з>>>~C>(>@@u> > v? ?"?5?v?_ ?t&?Y,?Z$3?9?i@?nG? N?U?}]?a1e?m?!)u?m}?m?oD?寋?3?=Д??QR?7?5?^K? y?h?<?E?9?ƻ?s?7A?N$?`?(?~I?v}?C?@C@@h @@i@@@Q'@b@@o#@&@b*@-@b1@4@l8@D;@N|?@mC@F@uJ@M@OQ@kT@X@[@^@hb@%e@,i@l@"o@s@Pv@y@˥|@@de@@]@΅@[7@@@A@@ƍ@^@%@CF@4\@sg@g@\@zF@t$@@@>v@y#@Ě@W@ޛ@`X@Ĝ@$@u@ @@@M5@C@C@M5@@@ @u@$@Ĝ@`X@ޛ@W@Ě@y#@>v@@@t$@zF@\@g@sg@4\@CF@%@^@ƍ@@A@@@[7@΅@]@@de@@˥|@y@Pv@s@"o@l@,i@%e@hb@^@[@X@@@M@uJ@F@@N|?@D;@l8@4@b1@-@b*@&@o#@@b@@@@i@@h @@C@@C?v}?~I?(?`?N$?7A?s?ƻ?9?E?<?h? y?^K?5?7?QR??=Д?3?寋?oD?m?m}?!)u?m?a1e?}]?U? N?nG?i@?9?Z$3?Y,?t&?_ ?v?5?"? ? v? >u>?>g>(>~C>>>-з>2>ר>g>|8>h+>]>Nг>=>}>n>?> >P!>>G.>8?ø?k ?z??o?"?O(?>/?5?W?dt?]@D@Ѽ@ @:@@:@Q'@ҁ@E@-E#@ &@\*@-@50@i4@U7@Q;@&>@:B@E@I@L@:O@0`S@V@u"Z@p{]@`@d@]g@Pj@m@p@&t@&w@.z@D)}@ @{@@.F@@#@:@1z@?@ދ@@@,@b2@-@@j@ړ@@i@o@Ȗ@e@@nz@@[@ȸ@@K@@?@Ě@wњ@wњ@Ě@?@@K@@ȸ@[@@nz@@e@Ȗ@o@i@@ړ@j@@-@b2@,@@@ދ@?@1z@:@#@@.F@@{@ @D)}@.z@&w@&t@p@m@Pj@]g@d@`@p{]@@V@0`S@:O@L@I@E@:B@&>@Q;@U7@i4@50@-@\*@ &@-E#@E@ҁ@Q'@:@@:@ @Ѽ@D@]@dt?>??{ ? ?0 ?^I???A??S??쾳?떮????q?-?S??ѥ?R? ?w?o?g?4`?X?QQ?&J?2(C?W/?O(?"?o??z?k ?ø?8?G.>>P!> >?>n>}>=>Nг>]>h+>|8>ù>c>ώ>zׯ>`>N,>W;>[>)> >M7>.>n>??)D?/?Dk?<?8%?_+?[1?.8?>?߮E?L?S?@[?b?Yj?pr?az?f???\?ܒ?t?#??sǥ??zƯ??C?l??H???v?,?1????y??!@@`@% @~F@@@@ @*Y@@"@}V&@R)@{-@lm0@3@m.7@W:@=@ OA@D@H@-`K@N@WR@PU@X@[@_@ZAb@je@(h@!k@n@q@Zt@w@)oz@4?}@@.Z@@ @7@p@@Lj@@k@O@@#@@@w@q_@@Β@9t@ @5@-@@o@S@@@\@>@X@e@e@X@>@\@@@S@o@@-@5@ @9t@Β@@q_@w@@@#@@O@k@@Lj@@p@7@ @@.Z@@4?}@)oz@w@Zt@q@n@!k@(h@je@ZAb@_@[@X@PU@WR@N@-`K@H@D@ OA@=@W:@m.7@3@lm0@{-@R)@}V&@"@@*Y@ @@@@~F@% @`@@!@?y????1?,?v???H??l?C??zƯ??sǥ??#?t?ܒ?\???f?az?pr?Yj?b?@[?S?L?߮E?>?.8?[1?_+?8%?<?Dk?/?)D???n>.>M7> >)>[>W;>N,>`>zׯ>ώ>c>ù>A>Q>ZǤ>6>OD> >> >Q>D>>6>P>?? ?s???!?'?x-? 4?7:??@A?;H?"O?qVV?D]?>Ee?m?qt?|??ۆ?+?ő?T??N???ի?qٰ??!?f??],?ĭ?B???r?Q?CA?]A?:Q?@@<@% @:@i@W@@}@V@ś"@Y%@4-)@x,@/@3@`6@9@<@C@@ȋC@F@uJ@OM@P@ջS@ V@Z@.]@E`@rTc@Yf@Ti@El@"+o@r@t@w@Cz@|@3|@@;@"m@@綅@Ά@ۇ@߈@ى@JɊ@~@@X@@8֎@䃏@%@@CF@Wđ@.6@@@'A@@'@ړ@1@@@1@ړ@'@@'A@@@.6@Wđ@CF@@%@䃏@8֎@@X@@~@JɊ@ى@߈@ۇ@Ά@綅@@"m@;@@3|@|@Cz@w@t@r@"+o@El@Ti@Yf@rTc@E`@.]@Z@ V@ջS@P@OM@uJ@F@ȋC@C@@<@9@`6@3@/@x,@4-)@Y%@ś"@V@}@@W@i@:@% @<@@@:Q?]A?CA?Q?r???B?ĭ?],??f?!??qٰ?ի???N??T?ő?+?ۆ??|?qt?m?>Ee?D]?qVV?"O?;H??@A?7:? 4?x-?'?!???s? ???P>6>>D>Q> >> >OD>6>ZǤ>Q>A>Г>N>>>40>>tU>@J>J>>n>%>U>A>??) ?,?[ ??%#?)?/?R6?w?R?Ƀ?u?M??*?S? `???jӬ?Dϱ???F???\?b? ??.?\?x??.?|}?k@@`@ @@6@]@i@@@+"@S%@D(@+@ /@V:2@#t5@8@;@?@JB@yE@H@K@N@WR@U@&X@+[@h(^@ a@d@f@$i@l@?o@q@)t@&w@-y@"|@)~@o@D@@＃@zĄ@~…@@@@zV@X!@X@L@@@Tތ@q@#@Zs@@E@Ĝ@@%@W@k}@w@@@w@k}@W@%@@Ĝ@E@@Zs@#@q@Tތ@@@L@X@X!@zV@@@@~…@zĄ@＃@@D@o@)~@"|@-y@&w@)t@q@?o@l@$i@f@d@ a@h(^@+[@&X@U@WR@N@K@H@yE@JB@?@;@8@#t5@V:2@ /@+@D(@S%@+"@@@i@]@6@@ @`@@k@|}?.??x?\?.?? ?b?\??F????Dϱ?jӬ??? `?S?*??M?u?Ƀ?R?h>w?Wo?4g? `?X?vQ?lJ?C?U>%>n>>J>@J>tU>>40>>>N>Г>Kg>޾>P>a>%>`k>>> >>D>k>>>2>{? ?/?s?(3??%?Y+?A2?~8?; ??E?`L?S?Z?Cb?i?tq?my??܄??Z?.?-?4?W? ?2֨??t?}?bɼ??V9??4?l?b??;?J?ؿ?Η?|}?@@Ѽ@h @@@@@=@>_@!@S$@'@*@1.@C1@i4@7@:@=@@@D@G@#J@V,M@O.P@F)S@V@Y@[@^@2a@Ud@ g@$i@&Zl@n@rq@s@Pv@x@{z@D)}@O@@@@@@YZ@*@#@@{]@H@@P-@?@)@L@.@*L@,@ Ҍ@@'@@@WL@WL@@@'@@ Ҍ@,@*L@.@L@)@?@P-@@H@{]@@#@*@YZ@@@@@@O@D)}@{z@x@Pv@s@rq@n@&Zl@$i@ g@Ud@2a@^@[@Y@V@F)S@O.P@V,M@#J@G@D@@@=@:@7@i4@C1@1.@*@'@S$@!@>_@=@@@@@h @Ѽ@@@|}?Η?ؿ?J?;??b?l?4??V9??bɼ?}?t??2֨? ?W?4?-?.?Z??܄??my?tq?i?Cb?Z?S?`L?E?; ??~8?A2?Y+?%??(3?s?/? ?{?2>>>k>D>> >>>`k>%>a>P>޾>Kg>>@@D>@#>>>T>->>>y>> >'>P>?? ?"??2?!?'?-?,4?7:?A?G?N?U?~\?[Wd?k?ٖs?v{??ۅ? ?O?ש???F5?B?y?x?a?]?:m?E?? ?ua??C?? d? ?ؿ?.?:Q?!@D@@~ @i@@@@@@@o @#@O&@ *@z-@R00@A3@P6@6]9@ef<@k?@lB@lhE@^H@NK@7N@OQ@S@V@wY@=I\@^@a@GAd@f@Ti@k@2n@kp@r@nu@;w@Uy@H^{@&U}@9@텀@de@;@@Yȃ@@*,@΅@e@#@q@@Q@H@H@J@@̵@ى@@u@u@@ى@̵@@J@H@H@Q@@q@#@e@΅@*,@@Yȃ@@;@de@텀@9@&U}@H^{@Uy@;w@nu@r@kp@2n@k@Ti@f@GAd@a@^@=I\@wY@V@S@OQ@7N@NK@^H@lhE@lB@k?@ef<@6]9@P6@A3@R00@z-@ *@O&@#@o @@@@@@@i@~ @@D@!@:Q?.?ؿ? ? d??C??ua? ??E?:m?]?a?x?y?B?F5???ש?O? ?ۅ??v{?ٖs?k?[Wd?~\?U?N?G?A?7:?,4?-?'?!?2??@@??P>'> >>y>>>->T>>>@#>D>>>\7>>>@@v>[+>>F>>\W>>>g>>>6t>.>->z?? ??|?H?#?r)?/?9#6?.>6t>>>g>>>\W>>F>>[+>v>t>>>/\>B>&_>a>=>>>~=>>l>?c>Y>T>T>v>>?D?K?R?Y?`?h?=o?h>w?.?@A@yD@V8G@tI@QL@XDO@Q@sT@V@xY@[@N^@&`@ b@/e@]g@l}i@k@m@~o@/]q@*s@t@ɐv@'x@-y@{@z|@}@~@ @@ @{@@;@)@΂@@?4@]V@@@x@"m@]V@?4@@΂@)@;@@{@ @@ @~@}@z|@{@-y@'x@ɐv@t@*s@/]q@~o@m@k@l}i@]g@/e@ b@&`@N^@[@xY@V@sT@Q@XDO@QL@tI@V8G@yD@A@8>@<@=9@`6@3@N0@-@*@c'@$@"@@#@4@;G@k[@q@Q @ @@@@dt?y?CA?x?;??]i???#?p?Y?S?%^?/z???:?ß? ??B?k???w?=o?h?`?Y?R?K?D?d>?7?1?Щ+?%??M??y?ZG ?9?v>T>T>Y>?c>l>>~=>>>=>a>&_>B>/\>>ֈ>̎>p>Z>~>Dɨ>zׯ>R!>>l>gp>t>9>>; >>]>j?{?J ?I/?? ?!?by'?Gj-?3?9?l$@?pF?cM?>T?@[?jb?~i?5q?x?O?G? S?r?s? ?B? ?,?T?^??ش???Č????$?C??\?Q??>?C?`@t@C@ @? @@f@xw@S@A0@ @O @#@&@v)@K,@b/@11@ݷ4@}7@>:@<@?@[B@E@G@|5J@L@XDO@Q@*T@V@X@+[@@h]@L_@Ka@c@%e@g@i@Pyk@;m@n@kp@r@fs@3t@Pv@w@x@ty@z@D{@˥|@k}@~@I~@9@|@@!@@@/C@8@!@@|@9@I~@~@k}@˥|@D{@z@ty@x@w@Pv@3t@fs@r@kp@n@;m@Pyk@i@g@%e@c@Ka@L_@@h]@+[@X@V@*T@Q@XDO@L@|5J@G@E@[B@?@<@>:@}7@ݷ4@11@b/@K,@v)@&@#@O @ @A0@S@xw@f@@? @ @C@t@`@C?>??Q?\??C?$????Č???ش??^?T?,? ?B? ?s?r? S?G?O?x?5q?~i?jb?@[?>T?cM?pF?l$@?9?3?Gj-?by'?!? ??I/?J ?{?j?>]>; >>9>t>gp>l>>R!>zׯ>Dɨ>~>Z>p>̎>ֈ>>>&t>D>/I>F>>>~>ƙ>>=>EU>d>v>D>>+>>K?? ??-?׮?T#?? )?/?k'5?c;?`A?EOH?N?U?7\?c?>k? r?LFz?????#;?9x?Ǚ?0)??!?ӷ?_??޹????#?k??b?.?r???v}??.@I@@n @4 @@@@Y@@$@s@@"@E%@ (@*@-@?0@2@S5@L8@k:@=@~"@@B@#5E@MG@#J@L@N@=Q@ӄS@U@XW@Z@#\@h(^@`@b@{c@Ve@]g@+i@Pj@l@m@n@9p@rq@r@s@Zt@u@fv@&w@ w@hx@x@Uy@-y@y@mz@.z@.z@mz@y@-y@Uy@x@hx@ w@&w@fv@u@Zt@s@r@rq@9p@n@m@l@Pj@+i@]g@Ve@{c@b@`@h(^@#\@Z@XW@U@ӄS@=Q@N@L@#J@MG@#5E@B@~"@@=@k:@L8@S5@2@?0@-@*@ (@E%@"@@s@@$@Y@@@@4 @n @@I@.@?v}???r?.?b??k?#????޹??_?ӷ?!??0)?Ǚ?9x?#;?????LFz? r?>k?c?7\?U?N?EOH?`A?c;?k'5?/?? )?T#?׮?-?? ??K?>+>>D>v>d>EU>=>>ƙ>~>>>F>/I>D>&t>>Ey>>Ƈ>> >>Y|>1>>G>>uI>r%>?>>2>N >;*>E?? ?"?]??<?$?*?0?w6?N >2>>?>r%>uI>>G>>1>Y|>> >>Ƈ>>Ey>r>!}>NT>1 >>s>i>>⳩>F>>rM>W>>>`>>z>>??8 ???1?2 ?)X&? ,? 2?8?T>?D?c-K?Q?(X?-_?f?Dm?!)u?V|?%?@@?R?G??͞?)??/?1?46?޹??Y?+? ?4? ??1? ?(?#O?|?@@!@`8@q@ @X( @K@Ov@@@g@ @@SG"@m$@w'@ *@,@b/@-1@4@6@8@a;@g=@@@[B@D@F@H@K@V,M@c2O@m+Q@S@T@V@7X@\5Z@[@@h]@6^@XY`@Ka@c@GAd@je@f@Ѕg@wh@Ti@{j@Rj@Pyk@Kl@l@l@;m@ym@m@Fm@Fm@m@ym@;m@l@l@Kl@Pyk@Rj@{j@Ti@wh@Ѕg@f@je@GAd@c@Ka@XY`@6^@@h]@[@\5Z@7X@V@T@S@m+Q@c2O@V,M@K@H@F@D@[B@@@g=@a;@8@6@4@-1@b/@,@ *@w'@m$@SG"@@ @g@@@Ov@K@X( @ @q@`8@!@B??|?#O?(? ?1?? ?4? ?+?Y??޹?46?1?/??)?@@G?R???r ?%?V|?!)u?Dm?f?-_?(X?Q?c-K?D?T>?8? 2? ,?)X&?2 ?1??@@??>z>>`>>>W>rM>>F>⳩>>i>s>>1 >NT>!}>r>l>w>> >B>9>c>>\V>!>A%>a>$>> w>> >.>>>#??t ??3??"?v'?Ny-?{b3?$o9?m??mE?7kL?S?;Y?i`?Fg?n?(v?}?ʖ?r?^?\?\j?%?4?B?E??/?匰???S?i???b?B?,?0 ?`? ?V,?@@dt?@]@@̆ @H @ձ@F@O@Pn@@|@@ @(#@%@+&(@2*@{-@y/@1@:4@6@8@ !;@[=@?@A@C@JE@?V,? ?`?0 ?,?B?b???i?S???匰?/??E?B?@@\j?\?@@@}?(v?n?Fg?i`?;Y?S?7kL?mE?m??$o9?{b3?Ny-?v'?"??3??@@#?>>.> >> w>>$>a>A%>!>\V>>c>9>B> >>w>l>@f>p>"{>>Z>i>j>>>ǥ>nz>>H˼>uI>>>f&>>g?>)>S>_?4 ?+?`C?|??T#?O(?.?`4?b:?.@?G?\M?T?Z?a?h?žo?-v?_~?m?Æ??ԙ?#?K?Ӛ? ?E??a?_?ش?%^??E?V9?\?ĭ?v?^I?N$? ?'???J??@m@@u@ @~ @+@@@@4@Dt@@X!@#@F+&@D(@+*@|;-@/@_1@ 4@@6@l8@W:@<@>@@@B@D@zF@AMH@uJ@K@}sM@O@P@R@ӄS@%T@)/V@kW@X@-Y@۹Z@°[@\@@h]@h(^@^@p_@=_@l`@`@ a@Va@}a@2a@2a@}a@Va@ a@`@l`@=_@p_@^@h(^@@h]@\@°[@۹Z@-Y@X@kW@)/V@%T@ӄS@R@P@O@}sM@K@uJ@AMH@zF@D@B@@@>@<@W:@l8@@6@ 4@_1@/@|;-@+*@D(@F+&@#@X!@@Dt@4@@@@+@~ @ @u@@m@@?J???'? ?N$?^I?v?ĭ?\?V9?E??%^?ش?_?a??E? ?Ӛ?K?#?ԙ??@@@-v?žo?h?a?Z?T?\M?G?.@?b:?`4?.?O(?T#??|?`C?+?4 ?_?S>)>g?>>f&>>>uI>H˼>>nz>ǥ>>>j>i>Z>>"{>p>@f>Mq`>Lj>t>>>>S>> Ȝ>9>>>-з>>9>^>W>> >5>T>?.?Ok ?`?v?ȭ??4$?*?/?5?;?*A?;H?AN?1 U?[?x~b?ki?zp?w?~?5?0?֊?꾎??Y?Ӛ?B?)?j?ӷ??/z??:m???],????7A? ?? ?o?~I?M'?}?B?h@)@zO@l @4 @x@@@2@S@m@B@r@!@$@d&@|(@+*@z-@K/@r1@S3@S5@7@9@;@=@k?@M>A@mC@D@iF@H@ I@K@L@=M@XDO@P@Q@$R@S@T@U@V@W@KX@X@wY@Z@Z@Z@+[@d[@[@[@[@[@d[@+[@Z@Z@Z@wY@X@KX@W@V@U@T@S@$R@Q@P@XDO@=M@L@K@ I@H@iF@D@mC@M>A@k?@=@;@9@7@S5@S3@r1@K/@z-@+*@|(@d&@$@!@r@B@m@S@2@@@x@4 @l @zO@)@h@B?}?M'?~I?o? ?? ?7A????],???:m??/z??ӷ?j?)?B?Ӛ?Y??꾎?֊?0?@@@zp?ki?x~b?[?1 U?AN?;H?*A?;?5?/?*?4$??ȭ?v?`?Ok ?.??T>5> >>W>^>9>>-з>>>9> Ȝ>>S>>>>t>Lj>Mq`>rZ> d>m>|Bx>5s>>/>6>>Rݞ>\V>>6>>Q>O>ʝ>>>|>HD>e>>?ø?O ???d?S ?ގ%?)$+?T0?w6?M@IN@XDO@O.P@1Q@Q@ބR@F)S@ջS@fM@]"L@J@I@oH@G@E@~5D@B@A@N|?@=@<@N:@|8@Ο6@ݷ4@2@;0@q.@,@2*@}(@}V&@ ($@ !@@v@A0@@n@A@@ @4 @ @u@b@/@O@@?/?S? ???Ak???s??H??F??bɼ?]?B??^?!?5?͞?4?K??Iˎ?@@@h?{*x? q? j?Z/c?q\?U?dXO?H?B?e>HD>|>>>ʝ>O>Q>>6>>\V>Rݞ>>6>/>>5s>|Bx>m> d>rZ>GT>]>xg>q>'{>M>ֈ>鎎>w>>ݠ>7]>>D>>l>>˾>(>y>wh>>:>#?F?K ?r???!?k&? ,?1?7?~=?C?I?W P?{V? ]?Mc?Yj?tq?x??y?-??꾎?#?%??9??T??D?a?}??f??A?ƻ?=??R??}??x?Y???"@5t@%@@c @2 @ @?@@@@4@f@@@!@F#@&@ (@ *@j,@-@/@1@3@D5@6@8@N:@;@Fl=@8>@uT@@A@mC@FD@yE@:F@MG@|H@I@(J@-`K@]"L@L@}sM@N@-N@N@XDO@9O@2O@6O@:O@:O@6O@2O@9O@XDO@N@-N@N@}sM@L@]"L@-`K@(J@I@|H@MG@:F@yE@FD@mC@A@uT@@8>@Fl=@;@N:@8@6@D5@3@1@/@-@j,@ *@ (@&@F#@!@@@f@4@@@@?@ @2 @c @@%@5t@"@??Y?x??}??R??=?ƻ?A??f??}?a?D??T??9??%?#?꾎??@@@x?tq?Yj?Mc? ]?{V?W P?I?C?~=?7?1? ,?k&?!???r?K ?F?#?:>>wh>y>(>˾>>l>>D>>7]>ݠ>>w>鎎>ֈ>M>'{>q>xg>]>GT> N>HW>4a>ej>!u>5k>>>Kg>V>v>Ȣ>M>4>>>fk> >{>3>>h>t>^>?@ ?w???!?_\'?C,?h2?N8?3>?w7D?ZJ?P?V?}]? d?j?Rq?x?6?y?K!?֊?ԙ?\j?G?b2?0)?,?:?4T?x?t??!?l??9?{? ?Q?"?@@@@$7C@$D@E@&E@F@V8G@G@^H@GH@@I@ I@I@uJ@|5J@GJ@GJ@|5J@uJ@I@ I@@I@GH@^H@G@V8G@F@&E@E@$D@$7C@:B@-A@@@8>@=@ef<@;@9@=8@v6@K55@3@1@N0@ .@,@+@4-)@1L'@1b%@o#@t!@r@i@X@A@6%@@@A@i@L @ @q@j@hb@"@C?]A?ɽ?Q:??6?;??N8?h2?C,?_\'?!???w? ?1??^>t>h>>3>{> >fk>>>4>M>Ȣ>v>V>Kg>>>5k>!u>ej>4a>HW> N>#H>Q>$Z>pmd>7n>Wx>g>І>Og>t,>!>2F>>%>v>ϸ>y>L>>ڡ>_> >xC>B>zf?? ?)i?#P?U?;x?"?J(?`-?33?8?>?D?qJ?@@z]?[Wd?dk?Dq?x??c?0??\?R??Ǚ? ?ß?a?y??Dϱ??C?S?E???Pi???p?9?:0?Ւ?J?Y?ż?>?|}?@@B@i@ @@ @@o@l@@ @ @@ @@o @ܩ"@}$@H&@ (@)@l+@{-@+.@R00@1@"3@4@Q5@m.7@l8@9@@@@=@>@?@uT@@ A@A@JB@B@HC@C@D@FD@yD@D@D@D@D@yD@FD@D@C@HC@B@JB@A@ A@uT@@?@>@=@<@;@ۿ:@9@l8@m.7@Q5@4@"3@1@R00@+.@{-@l+@)@ (@H&@}$@ܩ"@o @@ @@ @ @@l@o@@@ @ @i@B@@@|}?>?ż?Y?J?Ւ?:0?9?p???Pi???E?S?C??Dϱ??y?a?ß? ?Ǚ??R?\??0?c??x?Dq?dk?[Wd?z]? [W?L Q?qJ?D?>?8?33?`-?J(?"?;x?U?#P?)i? ??zf?B>xC> >_>ڡ>>L>y>ϸ>v>%>>2F>!>t,>Og>І>g>Wx>7n>pmd>$Z>Q>#H>\C>oK>T>d^>xg> bq>{>q >w>>ݓ>֙>f>X>!>>'>>>ʝ>a>\>>Y>P>:??Ok ?/??T?)?c#?̹(?..?ӿ3?$o9?;?? &E?@@ W?]?$kd?dk?Rq?x?h?5?Æ?^??.?9x?B? ??B?2֨?jӬ?qٰ???<?F??ji???f?B?"???J??W?a?@T?-?/e@@*@@Ѽ@ @ @@@>@@@@vt@K@@E@!@SS#@$@&@4(@)@@+@,@1.@y/@;0@ 2@A3@i4@@@@|8@6]9@t.:@k:@;@E<@<@[=@=@1>@>@&>@>@?@l)?@l)?@?@>@&>@>@1>@=@[=@<@E<@;@k:@t.:@6]9@|8@7@6@܃5@i4@A3@ 2@;0@y/@1.@,@@+@)@4(@&@$@SS#@!@E@@K@vt@@@@>@@@ @ @Ѽ@@*@@/e@-?@T?a?W??J???"?B?f???ji?F??<???qٰ?jӬ?2֨?B?? ?B?9x?.??^?Æ?5?h?x?Rq?dk?$kd?]? W?QQ?c-K? &E?;??$o9?ӿ3?..?̹(?c#?)?T??/?Ok ??:?P>Y>>\>a>ʝ>>>'>>!>X>f>֙>ݓ>>w>q >{> bq>xg>d^>T>oK>\C>=>(F>N>W>`>j>lt>W~>*>1 >>y>u>c>>>G>J8>[>S>!?>>g>#>O> >j?s~? ?4?5?ȭ??#?=)?.?,4?9?ӎ??hjE?9bK?vQ?W?]?[Wd?j?tq?{*x?~?m?r??K?#;? ??g?F5? ??ի?zƯ?쾳?h?bĻ?Kп????[/?O?r????W?w(?~I?g?.?N?@@)@p@@ @q @x@@i@A@/@@@X@ @@=P @!@o#@$@d&@'@4-)@*@+@},@H,.@K/@$^0@b1@:Y2@A3@4@4@S5@P6@6@}7@47@l8@8@9@6]9@k9@9@9@9@9@k9@6]9@9@8@l8@47@}7@6@P6@S5@4@4@A3@:Y2@b1@$^0@K/@H,.@},@+@*@4-)@'@d&@$@o#@!@=P @@ @X@@@/@A@i@@x@q @ @@p@)@@@N?.?g?~I?w(?W????r?O?[/????Kп?bĻ?h?쾳?zƯ?ի?? ?F5?g?? ?#;?K??r?m?~?{*x?tq?j?[Wd?]?W?vQ?9bK?hjE?ӎ??9?,4?.?=)?#??ȭ?5?4? ?s~?j? >O>#>g>>!?>S>[>J8>G>>>c>u>y>>1 >*>W~>lt>j>`>W>N>(F>=>`8>y@>QH>UQ>nZ>Sc>im>RVw>fˀ>h>>0>:>j>[+>ˇ>u>Ҷ>D>>#7>>z>k>F>>}>â?!? ?s?5E?(3?<?b$?T)?/?{4?:???E?sK?vQ? W?z]? d?Yj? q?w?_~?ʖ?r ?}??s?B???W????떮? y?ya?O?C?;?7?6?8?=?B?^I?P?V?Z?]?w]?Y?Q? E?J2?y @@@@@ @1e @h6@+@@@6@@i@@$@@@@h@w4 @!@"@R$@%@d&@ (@4-)@D*@N+@K,@|;-@1.@.@]/@lm0@1@1@V:2@ 2@"3@3@3@ 4@:4@Z4@i4@i4@Z4@:4@ 4@3@3@"3@ 2@V:2@1@1@lm0@]/@.@1.@|;-@K,@N+@D*@4-)@ (@d&@%@R$@"@!@w4 @h@@@@@$@i@@6@@@+@h6@1e @ @@@@@y @J2? E?Q?Y?w]?]?Z?V?P?^I?B?=?8?6?7?;?C?O?ya? y?떮????W???B?s??}?r ?ʖ?_~?w? q?Yj? d?z]? W?vQ?sK?E???:?{4?/?T)?b$?<?(3?5E?s? ?!?â?}>>F>k>z>>#7>>D>Ҷ>u>ˇ>[+>j>:>0>>h>fˀ>RVw>im>Sc>nZ>UQ>QH>y@>`8>3>:>ZC>uK>H.T>/3]>@f>")p>uz>l2>r>>>Ip>[o>>>>?>N,>@J>4>>T>>>]*>հ>96??!B ?r?ȹ?.??@$?)?>/?4?T0:?B??E?9bK?QQ? [W?}]?Mc? j?zp?-v?}?%???r?k?|??4? `??sǥ??^K???н?V?v?~X?@o @"@(#@D$@S%@}V&@1L'@4(@)@s)@2*@N+@+@,@{-@-@-@yJ.@ .@.@ /@b/@-/@-/@b/@ /@.@ .@yJ.@-@-@{-@,@+@N+@2*@s)@)@4(@1L'@}V&@S%@D$@(#@"@o @>@C@s@|@@$@@O2@N@j@@o@:@Q @ @ @ZR@@@l@y @Z^?՛?&??V,?Q?r??̫????K ?d#?/?)?@$??.?ȹ?r?!B ??96?հ>]*>>>T>>4>@J>N,>?>>>>[o>Ip>>>r>l2>uz>")p>@f>/3]>H.T>uK>ZC>:>3>E->h5>EO=>}E>bM>V>_> i>r>|>>ֈ>5Q>+>2ə>ǟ>:>N>ײ>8>x>>>W>F>>>?> >?$? ? U????`$?*?\/?4?T0:???hjE?c-K?L Q?V? ]?Z/c?ki?žo?(v?V|?̞?? S??d.?ש?-?S?N???5?{?И? R??к??\?%?x?ƻ?,?Q??>?G?i?'?? ?CA???D?@!@OR@@&@c @) @ @h6@@F@@5@W@@S@@@}@@@>_@r@y @t!@tc"@-E#@$@m$@%@H&@&@w'@|'@o(@X(@4-)@v)@R)@s)@)@ *@ *@)@s)@R)@v)@4-)@X(@o(@|'@w'@&@H&@%@m$@$@-E#@tc"@t!@y @r@>_@@@}@@@S@@W@5@@F@@h6@ @) @c @&@@OR@!@@D???CA? ??'?i?G?>??Q?,?ƻ?x?%?\??к?? R?И?{?5???N?S?-?ש?d.?? S??̞?V|?(v?žo?ki?Z/c? ]?V?L Q?c-K?hjE???T0:?4?\/?*?`$???? U? ?$?? >?>>>F>W>>>x>8>ײ>N>:>ǟ>2ə>+>5Q>ֈ>>|>r> i>_>V>bM>}E>EO=>h5>E->D(>0>C7>Z?>G>VP>Y>M2b>uk>@u>>>&DŽ>(>7>9>G >>1>6>>º>ȥ>>]>n>8> >>;*>2>]?? ??U?_$?u ? %?(*?\/?4?:?ӎ?? &E?qJ?P?{V?q\?x~b?h?n?!)u?b{??G???O?.?*??#??7?ʦ?b???E??V?D???O??k?]U???5D??/x?{ ? ? ???`l?/e@@/@wO@ @u@' @~ @u @g@K@-@@@@;G@s@@<@m@@@@l@a;@@ @X!@ !@"@"@o#@#@ ($@Lo$@S$@%$@$@$@$@$@%$@S$@Lo$@ ($@#@o#@"@"@ !@X!@ @@a;@l@@@@m@<@@s@;G@@@@-@K@g@u @~ @' @u@ @wO@/@@/e@`l??? ? ?{ ?/x??5D???]U?k??O???D?V??E???b?ʦ?7??#??*?.?O???G??b{?!)u?n?h?x~b?q\?{V?P?qJ? &E?ӎ??:?4?\/?(*? %?u ?_$?U?? ??]?2>;*>> >8>n>]>>ȥ>º>>6>1>>G >9>7>(>&DŽ>>>@u>uk>M2b>Y>VP>G>Z?>C7>0>D(>B#>5*>{.2>9>A>J>XR>i[>Dm>w>fˀ>>D>>c>2>->oT>Χ>T(>ֻ>> >=>a>>>>B>#?j? ?;B ?,?|?C??S ? %?*?@@@;??D?ZJ?W P?U?[?a?Fg?Dm?vt?LFz?O?/?*? %?S ?C??|?,?;B ? ?j?#?B>>>>a>=> >>ֻ>T(>Χ>oT>->2>c>>D>>fˀ>w>Dm>i[>XR>J>A>9>{.2>5*>B#>[>%> ,>f>4> ;>{C>*8L>T>]>6f>Tp>y>>> >&[>ӑ>&v>|B>9>[>˩>$$>H˼>>ġ>>0>>z>af>́>zf??z?f ?s??C??u ?`$?@@@$o9?>?w7D?I?dXO?1 U?Z?i`?f?l? r?x?.?m?ۅ??M?ő?ܒ?-???(C?#????c?ش?M?bĻ?:??%?? ?w??NG?? ?W?e?\?(?w]?=??ҽ?E?C?Z@@4@*@@C@u@\ @) @4 @LY @t@@@@Ov@k[@5@@@@Y{@6%@@S@@%O@@@g@@@@"@A0@A0@"@@@@g@@@%O@@S@@6%@Y{@@@@5@k[@Ov@@@@t@LY @4 @) @\ @u@C@@@@@Z@C?E?ҽ??=?w]?(?\?e?W? ??NG??w? ??%??:?bĻ?M?ش?c????#?(C???-?ܒ?ő?M??ۅ?m?.?x? r?l?f?i`?Z?1 U?dXO?I?w7D?>?$o9?,4?/?)?`$?u ?C???s?f ?z??zf?́>af>z>>0>>ġ>>H˼>$$>˩>[>9>|B>&v>ӑ>&[>> >>y>Tp>6f>]>T>*8L>{C> ;>f>4> ,>%>[>>(} >{'>ѷ.>46>=>kE>;N>#V>˛_>&h>r>U{>f> >n[>uђ>Ip>|8>*>*G>>>e>{k>?c> >2>Y>>z>>?{?9 ?8s ?s?|?_$??@@@ӿ3?8?3>?C?H?AN?T?;Y?-_?Ye?>k?5q?h>w?W}??܄?u?+?\?S?=Д?j?dY???`F??a?L?t??%^???j??y?b?ĭ??4?4o??9?`?? ?w(?%? ??y??Z^?@X@-@]@֔@@7@ @ @B @H @ @ @@@q@-@X@@@@@(@@@]@N@2@1 @;G@Ha@Pn@Pn@Ha@;G@1 @2@N@]@@@@(@@@@X@-@q@@@ @ @H @B @ @ @7@@֔@]@-@X@@@?y?? ?%?w(? ??`?9??4o?4??ĭ?b?y??j???%^??t?L?a??`F???dY?j?=Д?S?\?+?u?܄??W}?h>w?5q?>k?Ye?-_?;Y?T?AN?H?C?3>?8?ӿ3?.?T)?@$??_$?|?s?8s ?9 ?{??>z>>Y>2> >?c>{k>e>>>*G>*>|8>Ip>uђ>n[> >f>U{>r>&h>˛_>#V>;N>kE>=>46>ѷ.>{'>(} >>0>#>J">M)>0>8>0?>G>v P>X>1a>j>t>}>lփ>+>D> >vQ>j>>2>U>A>tU>>>*>z^>C>l>7>G.>K??9 ?f ?,?U???b$?=)?..?33?N8?~=?B?;H?\M?S?(X?=^?c?~i?=o?'~u?v{??Ƀ?ۆ???3?)\?%?S?=?e'?Mb?r?Nީ?Y?_?ɟ??C?\? ???6?b?????>???M???w]???|?/??D?C@Aq@!@/@%@@@@@ @i @`6 @ @@ @LY @ @Œ@@ @+@e@˼@@F@`y@5@s@@@s@5@`y@F@@˼@e@+@ @@Œ@ @LY @@ @ @`6 @i @ @@@@@%@/@!@Aq@C@D??@@??w]???M???>?????b?6??? ?\?C??ɟ?_?Y?Nީ?r?Mb?e'?=?S?%?)\?3???ۆ?Ƀ??v{?'~u?=o?~i?c?=^?(X?S?\M?;H?B?~=?N8?33?..?=)?b$???U?,?f ?9 ??K?G.>7>l>C>z^>*>>>tU>A>U>2>>j>vQ> >D>+>lփ>}>t>j>1a>X>v P>G>0?>8>0>M)>J">#>0>O>>5>$><+>^M2>9>A>I>/Q>rZ>SEc>^l>wu>5k>&>qЉ>>s>8>՟>>oȫ>K>_>>>}>>(>>l>`>C>K?{?z?;B ???.?<?#?̹(?`-?h2?7??#?D?g???9٪??&?LK?n?G?뮽?6??W?? ?K ???.??!?Ak?.??Ւ?e2??~I?ؿ?M'?L?E??%?ڜ@%@!@@>i@C@b@p@@F@<@̆ @ @ @5 @~ @ @4 @} @q @? @ @X( @4 @4 @X( @ @? @q @} @4 @ @~ @5 @ @ @̆ @<@F@@p@b@C@>i@@!@%@ڜ@%??E?L?M'?ؿ?~I??e2?Ւ??.?Ak?!??.???K ? ??W??6?뮽?G?n?LK?&??9٪???g?D?#?>? ?qґ?꾎?寋?ѥ???R?my?ٖs?Dm?h?jb?7\?cHW?Q?7kL?G?*A?@@h2?`-?̹(?#?<?.???;B ?z?{?K?C>`>l>>(>>}>>>_>K>oȫ>>՟>8>s>>qЉ>&>5k>wu>^l>SEc>rZ>/Q>I>A>9>^M2><+>$>5>>O> >G>B<>[>%>,>a3>u;>;C> AK>S>p\>Od>m>RVw>a}>&t>>wя>9>+ǚ>Y|>X>]>M>߸>^>>>`> >D>>`>G.>?? ? ? U?ȹ?(3??c#?J(?C,?1?w6?;?.@?mE?c-K?xP?U?@[?`? Hf?k?tq?h>w?|?f?R?oD?:?I5?3?5?:?B?hL?W?Ed?[q?~?7?떮???}??뮽?Ш???$v?{X?n3?f???^I?b?l?.?5?6??{ ?w]?y??n?V?/?}???8@y @X@!@K@@*@,@@A7@@@r@@ @F@u@K@@Ѽ@Ѽ@@K@u@F@ @@r@@@A7@@,@*@@K@!@X@y @8@??}?/?V?n??y?w]?{ ??6?5?.?l?b?^I???f?n3?{X?$v???Ш?뮽??}???떮?7?~?[q?Ed?W?hL?B?:?5?3?I5?:?oD?R?f?|?h>w?tq?k? Hf?`?@[?U?xP?c-K?mE?.@?;?@@C,?J(?c#??(3?ȹ? U? ? ???G.>`>>D> >`>>>^>߸>M>]>X>Y|>+ǚ>9>wя>>&t>a}>RVw>m>Od>p\>S> AK>;C>u;>a3>,>%>[>B<>G> >zF>j7 >b^>>vS >$'>/.>w5>T<>D>L>U U>]>Q^f>&no>x>/>">z8>s>}ԕ>Z>>ڦ>'լ>>?>>@J> >> >D>l>7>>zf?j?? ?r?5E?ȭ?)?"?_\'? ,?T0?5?b:?m??D?I?N?>T?Y?t^?[Wd?i?Wo?qt?az? ?m?mυ???!?m?`\?HM???H3?e'??S??a??Dϱ?Ÿ???\?4?i?$??O??ĭ?N??r??]i??.?}??'??w(?V,?????>??_??J2?|}?Z@@Aq@@]@k@-@m@/@I@@c;@OR@]@]@OR@c;@@I@/@m@-@k@]@@Aq@@Z@|}?J2??_??>?????V,?w(??'??}?.??]i??r??N?ĭ??O??$?i?4?\???Ÿ?Dϱ??a??S??e'?H3???HM?`\?m?!???mυ?m? ?az?qt?Wo?i?[Wd?t^?Y?>T?N?I?D?m??b:?5?T0? ,?_\'?"?)?ȭ?5E?r? ??j?zf?>7>l>D> >> >@J>>?>>@@@Z>}ԕ>s>z8>">/>x>&no>Q^f>]>U U>L>D>T<>w5>/.>$'>vS >>b^>j7 >zF>>>>>%>7!>(>v/>6>f>>(F>)N>,kV>^>g>p>z>́>p>ɋ>>V>Hԛ>ew>9@>/>OD>%>>l>>> >>l>z>́>#?]?$?!B ?s?5?T?;x?!?k&?)$+?/?`4?$o9?T>?JC?EOH?cM?R?jW?~\?Cb?4g?m?pr?w?m}?}?G???&?ő?\j?uD??I? ם?c?ʌ?e??$o9?`4?/?)$+?k&?!?;x?T?5?s?!B ?$?]?#?́>z>l>> >>>l>>%>OD>/>@@@V>>ɋ>p>́>z>p>g>^>,kV>)N>(F>f>>6>v/>(>7!>%>>>>>E=2> >>4>iw>#>)>o0>08>@@rlO>W>#`>}h>q>"{>HT>:>B>n>޾>2>kˡ>>'k>r>L>y>l> >`>(>C>>af>B>2>?? ?4??U??!?ގ%?*?.?{b3?8?Ee?Yj?o?!)u?az??m??g?#???e? )??ذ?Rt?6??R?(t? .?{?떮?D??琶?-?bĻ?S??Y?$?Ee? `?Z?U?ѮP?K?pF?`A?B>af>>C>(>`> >l>y>L>r>'k>>@@@n>B>:>HT>"{>q>}h>#`>W>rlO>(pG>?>08>o0>)>#>iw>4>> >2>E=#==Bi>- >,$>O>m>G$>+> 2>@@H>ČP>X>4a>]i>r>|>dł>>/>FǑ>O >v>>N>6>z>L>>@J>>>z^>Y>z>>;*> >96?!? ?/?#P???S ?4$?O(?Ny-? 2?w6?c;?l$@?D?I?N?S?X?D]?b?g?m?Fr?~w?;|??p?1O??̣?O?G?ب?U?M?;?QR???:?2֨?m??匰??????K?գ??7?p???? ?4??K?M?^I? ??7??.????J? d?_j?]?R=?{ ??$f?J?r??V,?j? ?̨?̨? ?j?V,??r?J?$f??{ ?R=?]?_j? d?J????.??7?? ?^I?M?K??4? ????p?7??գ?K??????匰??m?2֨?:???QR?;?M?U?ب?G?O?̣??1O?p??;|?~w?Fr?m?g?b?D]?X?S?N?I?D?l$@?c;?w6? 2?Ny-?O(?4$?S ???#P?/? ?!?96? >;*>>z>Y>z^>>>@J>>L>z>6>N>>v>O >FǑ>/>>dł>|>r>]i>4a>X>ČP>H>@>`9> 2>+>G$>m>O>,$>- >Bi>=#==,=>u>O >F>q>[>e%>1,>@@A>I>UQ>Y>b>j>hs>|>( > >_>{>A>P>>§>6>r>%>>>}>*>2>>>>?>հ>â?s~?Ok ?)i?w??d??T#?v'? ,?0?k'5?9?d>?JC?G?`L?vQ?qVV?@[?4`?a1e? 6j?DBo?Ut?my?~?ց?i?0?h?!)?꾎?PT??|? ??0)?c?7??5?׬?Y???LK???12?:m?v?f??n??x??ƻ?D?P???B??7A?? ?C?v?l?G???Ji?.??? ?Ƃ??6?r? ??? ?r?6??Ƃ? ???.?Ji???G?l?v?C? ??7A??B???P?D?ƻ??x??n??f?v?:m?12???LK???Y?׬?5??7?c?0)?? ?|??PT?꾎?!)?h?0?i?ց?~?my?Ut?DBo? 6j?a1e?4`?@[?qVV?vQ?`L?G?JC?d>?9?k'5?0? ,?v'?T#??d??w?)i?Ok ?s~?â?հ>?>>>>2>*>}>>>%>r>6>§>>P>A>{>_> >( >|>hs>j>b>Y>UQ>I>A>r:>53>1,>e%>[>q>F>O >u>>,===O=`F=>>$\ >Q>z>>@h&>/->.4>e;>B>J>dR>nZ>b> ~k>Wt>3p}>dd>0>>>t,>[>㬜>>N>'k>OD>?>^>>> >0>> >>]*>}>j?? ? ?r??ȭ??"?)X&?*?/?3?7?]*>> >>0> >>>^>?>OD>'k>N>>㬜>[>t,>>>0>dd>3p}>Wt> ~k>b>nZ>dR>J>B>e;>.4>/->@h&>>z>Q>$\ >>>`F=O== =\==9=>5>Q>D>0j> >O'>.> 5><9<>C> AK>:S>0[>mc> l>t>}>>iT>6>9>[>P>>>/>>߸>>>?c>>a>8>>>> >:??1?K ??v?|??2 ?$?? )?Gj-?1?9#6?7:?; ??C?;H?L?QQ?U?Z?u__? d?%h?m?pr?h>w?H|?p?ڂ?D???<~? ?G?ب??a?4?q ?W?@@?R???RĮ?qٰ?i???͸???S??f?j????$v?l?d#?b????ڿ??k??O??}?B??4????Q:? M? M?Q:????4??B?}??O??k??ڿ????b?d#?l?$v????j?f??S???͸???i?qٰ?RĮ???R???ß?W?q ?4?a??ب?G? ?<~???D?@@H|?h>w?pr?m?%h? d?u__?Z?U?QQ?L?;H?C?; ??7:?9#6?1?Gj-?? )?$?2 ??|?v??K ?1??:? >>>>8>a>>?c>>>߸>>/>>>P>[>9>6>iT>>}>t> l>mc>0[>:S> AK>C><9<> 5>.>O'> >0j>D>Q>5>>9==\= =E{===ĝ==>q >0>>@>2!>(>.>w5><>rJD>K>S>-[>c>csl>+u> ~>è>9`>6>t,>A>v>kˡ>9@>'լ>M>_>tU>{k>ġ>=>n>F>>F>O>P>zf??F?O ?`?`C?3?1?<?T#?by'?Щ+?/?,4?~8?O>F>>F>n>=>ġ>{k>tU>_>M>'լ>9@>kˡ>v>A>t,>6>9`>è> ~>+u>csl>c>-[>S>K>rJD><>w5>.>(>2!>@>>0>q >>=ĝ===E{==X&==9=C==Ѱ>< >>:>>J">(> }/>9d6>=>D>[L>T>p\>Ed>l>Vu>6~>è>iT>>>{>O >2>ew>ڦ>]>K>A>e>> >]>W>T>k>#>Y>B>^>#?ø?Ok ?+????׮?!?%?r)?-?A2?R6?7:?>?2(C?nG?K?rBP?T?Y?ܐ]?b?f?dk?|o?vt?x?|??? 9?Xs?A?W?-?T@?\j?ԏ?K?P˘?q?=?B??5?B?ʦ?U??L??zƯ?r???2?}???Ի?<?S?@@գ?!?Č?i?!6?n?:?V9???7:?R6?A2?-?r)?%?!?׮????+?Ok ?ø?#?^>B>Y>#>k>T>W>]> >>e>A>K>]>ڦ>ew>2>O >{>>>iT>è>6~>Vu>l>Ed>p\>T>[L>D>=>9d6> }/>(>J">>:>>< >Ѱ>=C=9==X&===n=2=B =z==>Bi> >>j>>">\)>0>6>=>9E>*L>veT>M\>pmd>cl>Vu> ~>>0>_>FǑ>޾>Hԛ>>@oȫ>U>>H˼>>>>>z>g>>xC>t>:>?.?4 ?t ??]?-? ??#?'?@@ 4?.8?Wt>xC>>g>z>>>>>H˼>>U>oȫ>X>>Hԛ>޾>FǑ>_>0>> ~>Vu>cl>pmd>M\>veT>*L>9E>=>6>0>\)>">>j>> >Bi>>=z=B =2=n===KR=s = =m==O=>w > >T=>)> (>d#>')>p0>A7>E>>}E>fL>GT>`\>pmd>l>+u>}>dd> >/>n>V>Z>Y|>>2>>$$>ֻ>ȥ>>4>>>\> >h>>>?_??8 ?"???M?H?!?@@x-?[1?5?9?=?A?F?&J?KN?tR?ƠV?Z?^?Z/c? `g?k?žo?Ss?x?:|?A.?e>h> >\>>>4>>ȥ>ֻ>$$>>2>>Y|>Z>V>n>/> >dd>}>+u>l>pmd>`\>GT>fL>}E>E>>A7>p0>')>d#> (>)>T=> >w >>O==m= =s =KR===k2==wS=/W==M=C=G>> >a>+>>#>**>y0>7>hw>>E>(L>GT>M\>Ed>csl>t>3p}>( >>B>>}ԕ>+ǚ>՟>>*G>˩>T(>º>x>@J>#7>!?>a>_>>wh>e>T>S>#?? ? ?I/??|?2??%#?'?_+?>/?Z$3?7?;?>?B?WF?J?N?S?vW?[?m%_?Z/c?7g?>k?DBo?@@D5{?I&?X?y??g?(P?-4???꾎?e?P?T?ƕ?t??4?hL? ם?W?>Π?:???:?x?U?ϩ??a?`??RĮ?И?_??ܿ? Z?i?a?γ?,?/z?Ÿ??!???!??Ÿ?/z?,?γ?a?i? Z?ܿ??_?И?RĮ??`?a??ϩ?U?x?:???:?>Π?W? ם?hL?4??t?ƕ?T?P?e?꾎???-4?(P??g?y?X?I&?D5{?h>w?|Bs?DBo?>k?7g?Z/c?m%_?[?vW?S?N?J?WF?B?>?;?7?Z$3?>/?_+?'?%#??2?|??I/? ? ??#?S>T>e>wh>>_>a>!?>#7>@J>x>º>T(>˩>*G>>՟>+ǚ>}ԕ>>B>>( >3p}>t>csl>Ed>M\>GT>(L>E>hw>>7>y0>**>#>>@@@>G>C=M==/W=wS==k2==,m=FC=`==w=t==Z=`F=v> >[ > >3>>$>e*>o0>Y7>>>E>fL>veT>p\>c> l>Wt>|>dł>:>ɋ>s>9>8>j>*>[>Χ>>8>N,>>S>ʝ>ڡ>3>y>HD>5>)>>???J ?y???(3??!?8%?O(?Y,?}~0?4L4?8?(;?B??C?G?sK?dXO?=S?#W?[?t^?b?f?@@1r?u?Sy?}??t?G?? ݇?T?G[??꾎?e?? ?*?K?,???g?? ?(C?u??R?Ť?sǥ?T??~?aK?{ ??^?a?y?`?cZ???@)>5>HD>y>3>ڡ>ʝ>S>>N,>8>>Χ>[>*>j>8>9>s>ɋ>:>dł>|>Wt> l>c>p\>veT>fL>E>>>Y7>o0>e*>$>>3>@@@v>`F=Z==t=w==`=FC=,m==H=iV=n="=x=m=_='?=='>i> >l>/>>9$>*>0>Y7>hw>>}E>*L>T>-[>mc> ~k>hs>|>HT>p>z8>wя>s>vQ>|8>9>oT>6>ײ>?>D>[>>>{>(>|> >g?>>>E?K?{?ZG ? ?"?s?[ ??<?"?t&?*?-?s1?k'5?8?I?B??Y?Fk?T?ש?#;?Ï?rC?&?+?h??1O?R?m?9?~?v{?w?Ut?p?m?ki?e?b?'Q^?+Z?V?S?dXO?K?G?zD?dV@?I>g?> >|>(>{>>>[>D>?>ײ>6>oT>9>|8>vQ>s>wя>z8>p>HT>|>hs> ~k>mc>-[>T>*L>}E>hw>>Y7>0>*>9$>>/>l>@@@='?=_=m=x="=n=iV=H====}=~J=q\=2=JV=?A=w==Q=v>> >Y>V>H9>G$>*>o0>7>E>>9E>[L>S>0[>b>j>r>"{>́>">>> >Ip>|B>->1>N>>Ҷ>J8>>L> >˾>>>>>.>z>;*>>j?9?? ?/?,??Dk?o?_ ?#?j'?*?.?A2?5?O9??M??Ӛ?;? u?H3??9? ??e'???K?‘?ɡ???????ɡ?‘?K???e'?? ?9??H3? u?;?Ӛ??M?>???=Д?ب? w?#;?k?0?M?v?????X??f??P|?y?u?Fr?n?Hgk?g?$kd?`?LW]?;Y?P1V?:R?N?9bK?G?x&D?i@?;*>z>.>>>>>˾> >L>>J8>Ҷ>>N>@->|B>Ip> >>>">́>"{>r>j>b>0[>S>[L>9E>E>>7>o0>*>G$>H9>V>Y> >>v>Q==w=?A=JV=2=q\=~J=}===A=\=3֭=DY= =)=x=q==;==N=e>->j7 >ø>c>H9>9$>e*>y0>A7>=>D>K>:S>nZ>b>]i>q>z>/>&t>qЉ>D>uђ>&v>2>>:>>u>G>'>y>fk>>ʝ>W>f&> >>N >+>>]>!?$?J(?+?/?y2?5?$o9?!??v??/?s?) ? ??z?]>+>N >> >f&>W>ʝ>>fk>y>'>G>u>>:>>2>&v>uђ>D>qЉ>&t>/>z>q>]i>b>nZ>:S>K>D>=>A7>y0>e*>9$>H9>c>ø>j7 >->e>N==;==q=x=)= =DY=3֭=\=A=ʢ=)b=^=n=2=ӽ====/v====b>>C >ø>V>>$>**>p0>6>=>rJD> AK>dR>Y>4a>}h>p>x>a}>&>+>n[>ӑ>c>G >ǟ>>ˇ>>>ϸ>>l>O>^>>>`>2>>; >>->?{?? ?)D?z?5??C???!?*%?](?u+?R//?h2?%5?>9?I9?%5?h2?R//?u+?](?*%?!??C???5?z?)D? ??{??->>; >>2>`>>>^>O>l>>ϸ>>>ˇ>>ǟ>G >c>ӑ>n[>+>&>a}>x>p>}h>4a>Y>dR> AK>rJD>=>6>p0>**>$>>V>ø>C >>b>===/v====ӽ=2=n=^=)b=ʢ=ߓ=]=4=D =%A=9=g=n]=D====4==>>j7 >Y>/>>#>')>0>9d6><>C>J>UQ>X>#`>g>&no>RVw>5k>lփ> >&[>>9>2ə>[o>[+>>!>v>>>Q>9>> w>>>D>>v>.>P>2>???k ?"?E?l?)???,"?c%?(?u+?/?K2?5?8?(;?X+??]B?E?H?K?N?R?.U?g;X?@[?=^?@@f?i?l?Vo?$r?Щt?h>w?Sy?:|?ȡ~?|?̞??Ƀ?Rф?mυ?Æ??%?c?.??̣?M??~??!?k?S??k?3?e?e?s???s?e?e?3?k??S?k?!??~?@@@?.?c?%??Æ?mυ?Rф?Ƀ??̞?|?ȡ~?:|?Sy?h>w?Щt?$r?Vo?l?i?f? d?1a?=^?@[?g;X?.U?R?N?K?H?E?]B?X+??(;?8?5?K2?/?u+?(?c%?,"???)?l?E?"?k ????2>P>.>v>>D>>> w>>9>Q>>>v>!>>[+>[o>2ə>9>>&[> >lփ>5k>RVw>&no>g>#`>X>UQ>J>@@9d6>0>')>#>>/>Y>j7 >>>=4====D=n]=g=9=%A=D =4=]=ߓ=OF==h===ʯ=3={۾===K^=H= =I==b>-> >l>3>>d#>\)> }/>w5><9<>B>I>ČP>W>^>Q^f>m>wu>}>f>> >D>7>+>Ip>j>c>X>%>4>D>>>uI>>>?>v>9>T>6t>'>>A>??ø? ?ۻ ?H???? ?f!?:"?U%?p(?+?.?1?4?7?;?>?A?x&D?)G?&J?M?W P?R?U?X?y[?=^?R`?c? Hf?%h?Hgk?m?XPp? r?t?h>w?my?b{?}????z?c?0???Z?0??#?ѥ?i?}??:?????+?7?7?+?????:??}?i?ѥ?#?@@@??0?c?z????}?b{?my?h>w?t? r?XPp?m?Hgk?%h? Hf?c?R`?=^?y[?X?U?R?W P?M?&J?)G?x&D?A?>?;?7?4?1?.?+?p(?U%?:"?f!? ????H?ۻ ? ?ø???A>>'>6t>T>9>v>?>>>uI>>>D>4>%>X>c>j>Ip>+>7>D>> >f>}>wu>m>Q^f>^>W>ČP>I>B>@@ }/>\)>d#>>3>l> >->b>=I= =H=K^==={۾=3=ʯ===h==OF=׈=ڎ==섛=K/=&=4=]=;.= =%==$= =4==e>> > >+> (>">(>.> 5>e;>A>H>rlO>,kV>]>Od>^l>t>U{>>>(>5Q>>:>u>f>>M>>6>-з>H˼>$>W>r%>d>t>T>> >>U>P>n>8? v?\?ZG ?5 ?(???T? ??"?$?,'?*?-?0?3?"6?9?P>U>> >>T>t>d>r%>W>$>H˼>-з>6>>M>>f>u>:>>5Q>(>>>U{>t>^l>Od>]>,kV>rlO>H>A>e;> 5>.>(>"> (>+> > >>e>=4= =$==%= =;.=]=4=&=K/=섛==ڎ=׈=H=Z=V=/==Ƒ="l=&=ҷ=_=,=7==H===N=v>i>[ >a>)>>J">(>.>.4>r:>@>(pG>)N>U U>p\>SEc>j>r>y>fˀ>&DŽ>ֈ>>0>y>֙>2F>Ȣ>7]>>>>a>rM>uI>EU>gp>Y>>>k>%>6>.>G.> >}&??F?P ?8s ?M?)?????!?b$?b?'?*?>,?\/?2?>f5?.8?M:?߯=?g@?JC?E?`H?J?\M?W P?R?T? [W?]Y?([?=^? o`?b?d?f?h?Yj?\l? n?o?tq?Js?ot?u?h>w?x?y?z?{?;|?}?_~?.?? ?O?|??˳???˳??|?O? ??.?_~?}?;|?{?z?y?x?h>w?u?ot?Js?tq?o? n?\l?Yj?h?f?d?b? o`?=^?([?]Y? [W?T?R?W P?\M?J?`H?E?JC?g@?߯=?M:?.8?>f5?2?\/?>,?*?b?'?b$?!?????)?M?8s ?P ?F??}&? >G.>.>6>%>k>>>Y>gp>EU>uI>rM>a>>>>7]>Ȣ>2F>֙>y>0>>ֈ>&DŽ>fˀ>y>r>j>SEc>p\>U U>)N>(pG>@>r:>.4>.>(>J">>)>a>[ >i>v>N=@@H==7=,=_=ҷ=&="l=Ƒ==/=V=Z=H=!|=x=ʼn===B=Bآ=㦩= ==p=,=%=K^====Q='> > >T=>j>>2!>O'>/->@@?>(F>L>S>rZ>1a>&h>Tp>w>>>>r>>>ݓ>!>v>ݠ>\V>>nz>A%>>>=>l>?c>g>y>D>n>>M7>>u>1>2>Ӏ?9?\?W ?8s ?4??ȹ?|?C??? ?q#?X;&?O(?Щ+?T[.?R1?A3?R6?8?L;?>?@?JC?E?G?ZJ?L?N??Q?tS? U?jW?;Y?[?D]?_?cla?Z/c?d?f?h?i?dk?\l?m?n?o? q?$r?=r?s?ot?!)u?u?=v?v?-v?h>w?Diw?~w?~w?Diw?h>w?-v?v?=v?u?!)u?ot?s?=r?$r? q?o?n?m?\l?dk?i?h?f?d?Z/c?cla?_?D]?[?;Y?jW? U?tS??Q?N?L?ZJ?G?E?JC?@?>?L;?8?R6?A3?R1?T[.?Щ+?O(?X;&?q#? ??C??|?ȹ??4?8s ?W ?\?9?Ӏ?2>1>u>>M7>>n>D>y>g>?c>l>@>>A%>nz>>\V>ݠ>v>!>ݓ>>>r>>>>w>Tp>&h>1a>rZ>S>L>(F>?>@53>/->O'>2!>>j>T=> > >'>Q==@@K^=%=,=p== =㦩=Bآ=B===ʼn=x=!|=-s=}=a===#=3x==Kĩ=]==_= ===/v=;===v>> >>:>@> >@h&>@@08>f>>D> AK>/Q>X>˛_>6f>Dm>@u>|>l2>h>1 >>t,>V>>Rݞ>9>ǥ>!>F>G>>>l>>>>>>D> >P!>?>af>>>?â?BE??O ?5 ?4?z?Y+?[?v??W?W"?`$?'?*?c,?R//?[1?,4?6?9?t;?=?l$@?nB?D?F?I?c-K?.@M?nFO??Q?f+S?1 U?V?(X?wJZ?[?}]?^? o`? a?c?[Wd?݀e?f?4g?h?ki? 6j?j?k?l?l?m?Rm?}m?m?Dm?Dm?m?}m?Rm?m?l?l?k?j? 6j?ki?h?4g?f?݀e?[Wd?c? a? o`?^?}]?[?wJZ?(X?V?1 U?f+S??Q?nFO?.@M?c-K?I?F?D?nB?l$@?=?t;?9?6?,4?[1?R//?c,?*?'?`$?W"?W??v?[?Y+?z?4?5 ?O ??BE?â??>>af>?>P!> >D>>>>>>l>>>G>F>!>ǥ>9>Rݞ>>V>t,>>1 >h>l2>|>@u>Dm>6f>˛_>X>/Q> AK>D>f>>08> 2>1,>@h&> >@>:>> >>v>==;=/v=== =@=]=Kĩ==3x=#===a=}=-s==pi=ܰs=N~==lU=6=K=R==Kĩ= =ҷ=;.==D===w='?=`F=G>w > >>>0j>>e%>+>o0>6>T<>;C>I>v P>#V>]>uk>r>uz>fˀ>*>w>Og>Kg>w>> Ȝ>>\V>⳩>>ƙ>R!>>\W>> >J>Q>)> >g> >>z>>D>?"???f/ ?ۻ ?G?,?]?O?Dk??n? ?c#?%?E(?*?9-?l/?1? 4?R6?8?:?>z>> >g> >)>Q>J> >>\W>>R!>ƙ>>⳩>\V>> Ȝ>>w>Kg>Og>w>*>fˀ>uz>r>uk>]>#V>v P>I>;C>T<>6>o0>+>e%>>0j>>> >w >G>`F='?=w===D==;.=ҷ= =Kĩ==R=K=6=lU==N~=ܰs==pi=%`=i=/t=~=ӄ=ey=O= X=R==㦩=&=]={۾=n]==q=?A=_=Z=C=>Bi>< >0>D>z>[>G$>)>v/>w5>u;>A>G>;N>T>i[>M2b> i>@RVw>W~>q >І>>鎎>6>>>>>1>~>zׯ>~=>>->>@J> >[>?>(>a>>'M>O >Y>>>2> =?{?!? ?k ?u??#P?ȹ?[ ?f?o?<?!?#?,&?p(?*?C,?/?\61?R3?>f5?o7?$o9?c;?]M=?X+??Q@?B?{D?&F?G?BTI?qJ?GL?M?N?rBP?vQ?:R?S?T? U?{V?cHW?:X?X?OBY?;Y?7Z?+Z?Z?[?@[?S[?S[?@[?[?Z?+Z?7Z?;Y?OBY?X?:X?cHW?{V? U?T?S?:R?vQ?rBP?N?M?GL?qJ?BTI?G?&F?{D?B?Q@?X+??]M=?c;?$o9?o7?>f5?R3?\61?/?C,?*?p(?,&?#?!?<?o?f?[ ?ȹ?#P??u?k ? ?!?{? =?2>>>Y>O >'M>>a>(>?>[> >@J>>->>~=>zׯ>~>1>>>>>6>鎎>>І>q >W~>RVw>")p> i>M2b>i[>T>;N>G>A>u;>w5>v/>)>G$>[>z>D>0>< >Bi>>C=Z=_=?A=q==n]={۾=]=&=㦩==R= X=O=ey=ӄ=~=/t=i=%`=m'W=w`=pcj=Zt=7~==e=O=K=3x=Bآ="l=4=3=g==x=JV=m==M=O=>Ѱ>q >Q>Q>q>m>#>(>/.>a3>9>0?>kE>*8L>XR>Y>_>@f>im>lt>{>g>>ֈ>/>S>j>c>i>Y|>>Dɨ>>F>T>>tU>>W;>n>~C>>i>F>ߦ>'M>h>>T>> >??'g?1? ?f ?Է??EP??R??RO??!?#?e%? (?*? ,?.?0?f1?3?5?7?>9?M:?I????@A?B?zD?hjE?pF??G?I?&J?c-K?k$L? M?yM? N?dXO?QO?P?L Q?vQ?Q?R?JPR?tR?R?R?tR?JPR?R?Q?vQ?L Q?P?QO?dXO? N?yM? M?k$L?c-K?&J?I??G?pF?hjE?zD?B??@A???3>?I9?7?5?3?f1?0?.? ,?*? (?e%?#?!??RO??R??EP??Է?f ? ?1?'g??? >>T>>h>'M>ߦ>F>i>>~C>n>W;>>tU>>T>F>>Dɨ>>Y|>i>c>j>S>/>ֈ>>g>{>lt>im>@f>_>Y>XR>*8L>kE>0?>9>a3>/.>(>#>m>q>Q>Q>q >Ѱ>>O=M==m=JV=x==g=3=4="l=Bآ=3x=K=O=e==7~=Zt=pcj=w`=m'W=sN=W=\`=dj=t=P==ey=6=#=B=Ƒ=&=ʯ=9=ӽ=)=2=x=t=====>5>$\ >F>O>iw>7!>$'>,>^M2>8>=>{C>J>VP>V>/3]>Sc>j> bq>Wx>5k>M>>>i>9>s>>>~>>>>>`k>> >N,>}>>#7>ʝ>C >{> >k> >wh>>{k>>n>j?96?zs?? ? ?~P????c?T?_$?4?<?>!?8#?*%?'?O(?I*?n,?T[.?0?1?{b3?[4?6?7?$o9?:? '?B??@?A?B?C?D?E?@@@;H?H?H?BTI?I?I?|I?J?J?|I?I?I?BTI?H?H?;H?G?WF?AIF?E?D?C?B?A?@?B??>?.n=? '!?<?4?_$?T?c????~P? ? ??zs?96?j?n>>{k>>wh> >k> >{>C >ʝ>#7>>}>N,> >>`k>>>>>~>>>s>9>i>>>M>5k>Wx> bq>j>Sc>/3]>V>VP>J>{C>=>8>^M2>,>$'>7!>iw>O>F>$\ >5>@@===t=x=2=)=ӽ=9=ʯ=&=Ƒ=B=#=6=ey==P=t=dj=\`=W=sN=F=N=¼W=Xa=@@@ӄ=lU====K/==%A=2= =q\="=w=/W=m=z=C==>>O >,$>4>%>vS >%><+>0>46> ;>A>G>bM>H.T>nZ>`>xg>7n>!u>'{>5s>>Z>B>> >F>Z>=>[+>@#>%>40>OD>`>=>>>=>Z>ʝ>\>0>~>C>P!>6t>7>>j>A>?}&?-H?'g??P ? ?????,?ؾ???n?C ?"?#?ގ%?b?'?(?[*? ,?`-?/?}~0?1?33?@@@7?9?:?;?;??3>?~=?j>>7>6t>P!>C>~>0>\>ʝ>Z>=>>>=>`>OD>40>%>@#>[+>=>Z>F> >>B>Z>>5s>'{>@@@`>nZ>H.T>bM>G>A> ;>46>0><+>%>vS >%>4>,$>O >>>@@z=m=/W=w="=q\= =2=%A==K/====lU=ӄ=7~=t=j=Xa=¼W=N=F===u>- >>>>[>$>M)>ѷ.>f>4>9>Z?>}E>uK>UQ>W>d^>pmd>ej>q>|Bx>>> >1 >>/I>p>a>v>D>a>>6>zׯ>Nг>-з>ֻ>>> >r%>~C>dd>{>>{>>>g?>`>c>P>հ>???{??i ? ?D??w?EP?!??@@??_ ?!?q#?$?t&?'?=)?"*?u+?@@@3o0?s1?zj2?R3?,4?[4?5?@@@8?~8?8?.9?$o9?]9?9?9?9?9?]9?$o9?.9?8?~8?8?7?7?db6?5?[4?,4?R3?zj2?s1?3o0?\/? =.?9-?u+?"*?=)?'?t&?$?q#?!?_ ???g?ȭ??!?EP?w??D? ?i ??{????հ>P>c>`>g?>>>{>>{>dd>~C>r%> >>>ֻ>-з>Nг>zׯ>6>>a>D>v>a>p>/I>>1 > >>>|Bx>q>@@@W>UQ>uK>}E>Z?>9>f>4>ѷ.>M)>$>[>>>>- >u>>9=@@B = =wS==n=~J=DY=n=D ==섛=/====~=Zt=dj=Xa=sW=N==>MF=N=@@@/t=N~=a=ʼn=V==h=4=^=3֭=}=iV=`==s =2====`F=>Bi> >>b^>B<>5>J">{'> ,>{.2>C7>EO=>ZC>QH>N>T>$Z>4a>xg>m>t>"{>>NT>Ƈ>D>̎>&_>t>>>P>>ZǤ>ώ>]>2>> >ֻ>>>>#>[>>u>z>s>k>2a>T>xC>.>>D>3>P?96??,? ?P ?f ?+???@@?-??C???)?ُ? ?:"?q#?@$?@@@? )?*?+?Y+?Y,?Ny-?..?X.?l/?/?3o0?T0?\61?21?1?1? 2?A2?A2? 2?1?1?21?\61?T0?3o0?/?l/?X.?..?Ny-?Y,?Y+?+?*?? )?J(?u'?%?@$?q#?:"? ?ُ?)??C???-???#P???+?f ?P ? ?,??96?P?3>D>>.>xC>T>2a>k>s>z>u>>[>#>>>>ֻ> >>2>]>ώ>ZǤ>>P>>>t>&_>̎>D>Ƈ>NT>>"{>t>m>xg>@@@N>QH>ZC>EO=>C7>{.2> ,>{'>J">5>B<>b^>> >Bi>>`F====2=s ==`=iV=}=3֭=^=4=h==V=ʼn=a=N~=/t=pcj=\`=¼W=N=>MF=>=V6=m.=6=>=>j7 >G>>#>(} >%>5*>0>h5>:>y@>(F>oK>Q>HW>]> d>Lj>p>w>!}>>&t>ֈ>B>>\7>޾>N>Q>c>h+>ר>X>@B>>A>=>rM>E>>S>J>YQ>>>a>>eF>>2>6{>+>>w>w>P?#???<? ?O ?@@M?,?#P??.???(3?u????u ?!?"?&#?#?@$?%?X;&?&?'?J(?(?)?Bx)?r)?*?U*?[*?*?*?*?*?[*?U*?*?r)?Bx)?)?(?@@&?X;&?%?@$?#?&#?"?!?u ????u?(3???.??#P?,?M??) ?O ? ?<???#?P?w>w>>+>6{>2>>eF>>a>>>YQ>J>S>>E>rM>=>A>>@B>X>ר>h+>c>Q>N>޾>\7>>B>ֈ>&t>>!}>w>p>Lj> d>]>HW>Q>oK>(F>y@>:>h5>0>5*>%>(} >#>>G>j7 >>2>=,=O=\==X&=n=KR=k2=FC=H==\=)b=]==ڎ=Z=x=}=ܰs=i=w`=W=N==6=m.=K'=m.=V6===F=sN=m'W=%`==pi=-s=!|=H=׈=OF=ߓ=ʢ=A===,m=====E{= ===#=E=>zF> >O>0>>[>B#>D(>E->3>`8>=>\C>#H> N>GT>rZ>Mq`>@f>l>r>Ey>>>/\>>>Kg>Г>A>ù>|8>g> H>ר>ul>4>>A> >>/,>">+x>>>dd>P> >9>(>)]>0>h>z>OV>P> >v>?Ӏ?]?V?f9?1?_; ? ? ?؁?4?I/?w?b???3?G?P?M?C??$??,??<??{ ?!?!?!?W"?"?"?*#?T#?Hq#?q#?q#?Hq#?T#?*#?"?"?W"?!?!?@@?<??,??$?C??M?P?G?3???b?w?I/?4?؁? ? ?_; ?1?f9?V?]?Ӏ??v> >P>OV>z>h>0>)]>(>9> >P>dd>>>+x>">/,>> >A>>4>ul>ר> H>g>|8>ù>A>Г>Kg>>>/\>>>Ey>r>l>@f>Mq`>rZ>GT> N>#H>\C>=>`8>3>E->D(>B#>[>>0>O> >zF>>E=#=== =E{=====,m===A=ʢ=ߓ=OF=׈=H=!|=-s==pi=%`=m'W=sN=F===V6=m.=K'=Sigima-1.1.1/sigima/data/tests/image_formats/gaussian_spot_with_noise.npy000066400000000000000000010002001514013333200267070ustar00rootroot00000000000000NUMPYv{'descr': 'zF> >O>0>>[>B#>D(>E->3>`8>=>\C>#H> N>GT>rZ>Mq`>@f>l>r>Ey>>>/\>>>Kg>Г>A>ù>|8>g> H>ר>ul>4>>A> >>/,>">+x>>>dd>P> >9>(>)]>0>h>z>OV>P> >v>?Ӏ?]?V?f9?1?_; ? ? ?؁?4?I/?w?b???3?G?P?M?C??$??,??<??{ ?!?!?!?W"?"?"?*#?T#?Hq#?q#?q#?Hq#?T#?*#?"?"?W"?!?!?!?{ ??<??,??$?C??M?P?G?3???b?w?I/?4?؁? ? ?_; ?1?f9?V?]?Ӏ??v> >P>OV>z>h>0>)]>(>9> >P>dd>>>+x>">/,>> >A>>4>ul>ר> H>g>|8>ù>A>Г>Kg>>>/\>>>Ey>r>l>@f>Mq`>rZ>GT> N>#H>\C>=>`8>3>E->D(>B#>[>>0>O> >zF>>E=#=== =E{=====,m===A=ʢ=ߓ=OF=׈=H=!|=-s==pi=%`=m'W=sN=F===V6=m.=K'=m.=6=>=>j7 >G>>#>(} >%>5*>0>h5>:>y@>(F>oK>Q>HW>]> d>Lj>p>w>!}>>&t>ֈ>B>>\7>޾>N>Q>c>h+>ר>X>@B>>A>=>rM>E>>S>J>YQ>>>a>>eF>>2>6{>+>>w>w>P?#???<? ?O ?) ??M?,?#P??.???(3?u????u ?!?"?&#?#?@$?%?X;&?&?'?J(?(?)?Bx)?r)?*?U*?[*?*?*?*?*?[*?U*?*?r)?Bx)?)?(?J(?'?&?X;&?%?@$?#?&#?"?!?u ????u?(3???.??#P?,?M??) ?O ? ?<???#?P?w>w>>+>6{>2>>eF>>a>>>YQ>J>S>>E>rM>=>A>>@B>X>ר>h+>c>Q>N>޾>\7>>B>ֈ>&t>>!}>w>p>Lj> d>]>HW>Q>oK>(F>y@>:>h5>0>5*>%>(} >#>>G>j7 >>2>=,=O=\==X&=n=KR=k2=FC=H==\=)b=]==ڎ=Z=x=}=ܰs=i=w`=W=N==6=m.=V6=>=>MF=N=¼W=\`=pcj=/t=N~=a=ʼn=V==h=4=^=3֭=}=iV=`==s =2====`F=>Bi> >>b^>B<>5>J">{'> ,>{.2>C7>EO=>ZC>QH>N>T>$Z>4a>xg>m>t>"{>>NT>Ƈ>D>̎>&_>t>>>P>>ZǤ>ώ>]>2>> >ֻ>>>>#>[>>u>z>s>k>2a>T>xC>.>>D>3>P?96??,? ?P ?f ?+???#P???-??C???)?ُ? ?:"?q#?@$?%?u'?J(?? )?*?+?Y+?Y,?Ny-?..?X.?l/?/?3o0?T0?\61?21?1?1? 2?A2?A2? 2?1?1?21?\61?T0?3o0?/?l/?X.?..?Ny-?Y,?Y+?+?*?? )?J(?u'?%?@$?q#?:"? ?ُ?)??C???-???#P???+?f ?P ? ?,??96?P?3>D>>.>xC>T>2a>k>s>z>u>>[>#>>>>ֻ> >>2>]>ώ>ZǤ>>P>>>t>&_>̎>D>Ƈ>NT>>"{>t>m>xg>4a>$Z>T>N>QH>ZC>EO=>C7>{.2> ,>{'>J">5>B<>b^>> >Bi>>`F====2=s ==`=iV=}=3֭=^=4=h==V=ʼn=a=N~=/t=pcj=\`=¼W=N=>MF=>=V6===u>- >>>>[>$>M)>ѷ.>f>4>9>Z?>}E>uK>UQ>W>d^>pmd>ej>q>|Bx>>> >1 >>/I>p>a>v>D>a>>6>zׯ>Nг>-з>ֻ>>> >r%>~C>dd>{>>{>>>g?>`>c>P>հ>???{??i ? ?D??w?EP?!??ȭ?g???_ ?!?q#?$?t&?'?=)?"*?u+?9-? =.?\/?3o0?s1?zj2?R3?,4?[4?5?db6?7?7?8?~8?8?.9?$o9?]9?9?9?9?9?]9?$o9?.9?8?~8?8?7?7?db6?5?[4?,4?R3?zj2?s1?3o0?\/? =.?9-?u+?"*?=)?'?t&?$?q#?!?_ ???g?ȭ??!?EP?w??D? ?i ??{????հ>P>c>`>g?>>>{>>{>dd>~C>r%> >>>ֻ>-з>Nг>zׯ>6>>a>D>v>a>p>/I>>1 > >>>|Bx>q>ej>pmd>d^>W>UQ>uK>}E>Z?>9>f>4>ѷ.>M)>$>[>>>>- >u>>9=ĝ=9=B = =wS==n=~J=DY=n=D ==섛=/====~=Zt=dj=Xa=sW=N=>O >,$>4>%>vS >%><+>0>46> ;>A>G>bM>H.T>nZ>`>xg>7n>!u>'{>5s>>Z>B>> >F>Z>=>[+>@#>%>40>OD>`>=>>>=>Z>ʝ>\>0>~>C>P!>6t>7>>j>A>?}&?-H?'g??P ? ?????,?ؾ???n?C ?"?#?ގ%?b?'?(?[*? ,?`-?/?}~0?1?33?{4?5?6?7?9?:?;?;??>?m????g@?.@?A?aA?A?A?`A?`A?A?A?aA?A?.@?g@???m??>?3>?~=?j>>7>6t>P!>C>~>0>\>ʝ>Z>=>>>=>`>OD>40>%>@#>[+>=>Z>F> >>B>Z>>5s>@@7n>xg>`>nZ>H.T>bM>G>A> ;>46>0><+>%>vS >%>4>,$>O >>>=C=z=m=/W=w="=q\= =2=%A==K/====lU=ӄ=7~=t=j=Xa=¼W=N=F=sN=W=\`=dj=t=P==ey=6=#=B=Ƒ=&=ʯ=9=ӽ=)=2=x=t=====>5>$\ >F>O>iw>7!>$'>,>^M2>8>=>{C>J>VP>V>/3]>Sc>j> bq>Wx>5k>M>>>i>9>s>>>~>>>>>`k>> >N,>}>>#7>ʝ>C >{> >k> >wh>>{k>>n>j?96?zs?? ? ?~P????c?T?_$?4?<?>!?8#?*%?'?O(?I*?n,?T[.?0?1?{b3?[4?6?7?$o9?:? '?B??@?A?B?C?D?E?AIF?WF?G?;H?H?H?BTI?I?I?|I?J?J?|I?I?I?BTI?H?H?;H?G?WF?AIF?E?D?C?B?A?@?B??>?.n=? '!?<?4?_$?T?c????~P? ? ??zs?96?j?n>>{k>>wh> >k> >{>C >ʝ>#7>>}>N,> >>`k>>>>>~>>>s>9>i>>>@@Wx> bq>j>Sc>/3]>V>VP>J>{C>=>8>^M2>,>$'>7!>iw>O>F>$\ >5>>====t=x=2=)=ӽ=9=ʯ=&=Ƒ=B=#=6=ey==P=t=dj=\`=W=sN=m'W=w`=pcj=Zt=7~==e=O=K=3x=Bآ="l=4=3=g==x=JV=m==M=O=>Ѱ>q >Q>Q>q>m>#>(>/.>a3>9>0?>kE>*8L>XR>Y>_>@f>im>lt>{>g>>ֈ>/>S>j>c>i>Y|>>Dɨ>>F>T>>tU>>W;>n>~C>>i>F>ߦ>'M>h>>T>> >??'g?1? ?f ?Է??EP??R??RO??!?#?e%? (?*? ,?.?0?f1?3?5?7?>9?M:?I????@A?B?zD?hjE?pF??G?I?&J?c-K?k$L? M?yM? N?dXO?QO?P?L Q?vQ?Q?R?JPR?tR?R?R?tR?JPR?R?Q?vQ?L Q?P?QO?dXO? N?yM? M?k$L?c-K?&J?I??G?pF?hjE?zD?B??@A???@@@>9?7?5?3?f1?0?.? ,?*? (?e%?#?!??RO??R??EP??Է?f ? ?1?'g??? >>T>>h>'M>ߦ>F>i>>~C>n>W;>>tU>>T>F>>Dɨ>>Y|>i>c>j>S>/>ֈ>>g>{>lt>im>@f>_>Y>XR>*8L>kE>0?>9>a3>/.>(>#>m>q>Q>Q>q >Ѱ>>O=M==m=JV=x==g=3=4="l=Bآ=3x=K=O=e==7~=Zt=pcj=w`=m'W=%`=i=/t=~=ӄ=ey=O= X=R==㦩=&=]={۾=n]==q=?A=_=Z=C=>Bi>< >0>D>z>[>G$>)>v/>w5>u;>A>G>;N>T>i[>M2b> i>")p>RVw>W~>q >І>>鎎>6>>>>>1>~>zׯ>~=>>->>@J> >[>?>(>a>>'M>O >Y>>>2> =?{?!? ?k ?u??#P?ȹ?[ ?f?o?<?!?#?,&?p(?*?C,?/?\61?R3?>f5?o7?$o9?c;?]M=?X+??Q@?B?{D?&F?G?BTI?qJ?GL?M?N?rBP?vQ?:R?S?T? U?{V?cHW?:X?X?OBY?;Y?7Z?+Z?Z?[?@[?S[?S[?@[?[?Z?+Z?7Z?;Y?OBY?X?:X?cHW?{V? U?T?S?:R?vQ?rBP?N?M?GL?qJ?BTI?G?@@@Q@?X+??]M=?c;?$o9?o7?>f5?R3?\61?/?C,?*?p(?,&?#?!?<?o?f?[ ?ȹ?#P??u?k ? ?!?{? =?2>>>Y>O >'M>>a>(>?>[> >@J>>->>~=>zׯ>~>1>@@>>6>鎎>>І>q >W~>RVw>")p> i>M2b>i[>T>;N>G>A>u;>w5>v/>@@[>z>D>0>< >Bi>>C=Z=_=?A=q==n]={۾=]=&=㦩==R= X=O=ey=ӄ=~=/t=i=%`==pi=ܰs=N~==lU=6=K=R==Kĩ= =ҷ=;.==D===w='?=`F=G>w > >>>0j>>e%>+>o0>6>T<>;C>I>v P>#V>]>uk>r>uz>fˀ>*>w>Og>Kg>w>> Ȝ>>\V>⳩>>ƙ>R!>>\W>> >J>Q>)> >g> >>z>>D>?"???f/ ?ۻ ?G?,?]?O?Dk??n? ?c#?%?E(?*?9-?l/?1? 4?R6?8?:?>z>> >g> >)>Q>J> >>\W>>R!>ƙ>>@@> Ȝ>>w>Kg>Og>w>*>fˀ>uz>r>uk>]>#V>v P>I>;C>T<>6>@@e%>>0j>>> >w >G>`F='?=w===D==;.=ҷ= =Kĩ==R=K=6=lU==N~=ܰs==pi=-s=}=a===#=3x==Kĩ=]==_= ===/v=;===v>> >>:>@> >@h&>1,> 2>08>f>>D> AK>/Q>X>˛_>6f>Dm>@u>|>l2>h>1 >>t,>V>>Rݞ>9>ǥ>!>F>G>>>l>>>>>>D> >P!>?>af>>>?â?BE??O ?5 ?4?z?Y+?[?v??W?W"?`$?'?*?c,?R//?[1?,4?6?9?t;?=?l$@?nB?D?F?I?c-K?.@M?nFO??Q?f+S?1 U?V?(X?wJZ?[?}]?^? o`? a?c?[Wd?݀e?f?4g?h?ki? 6j?j?k?l?l?m?Rm?}m?m?Dm?Dm?m?}m?Rm?m?l?l?k?j? 6j?ki?h?4g?f?݀e?[Wd?c? a? o`?^?}]?[?wJZ?(X?V?1 U?f+S??Q?nFO?.@M?c-K?I?F?D?nB?l$@?=?t;?9?@,4?[1?R//?c,?*?'?`$?W"?W??v?[?Y+?z?4?5 ?O ??BE?â??>>af>?>P!> >D>>>>>>l>>>G>@@ǥ>9>Rݞ>>V>t,>>1 >h>l2>|>@u>Dm>6f>˛_>X>/Q> AK>D>f>>@@1,>@h&> >@>:>> >>v>==;=/v==@ =_==]=Kĩ==3x=#===a=}=-s=!|=x=ʼn===B=Bآ=㦩= ==p=,=%=K^====Q='> > >T=>j>>2!>O'>/->53>`9>?>(F>L>S>rZ>1a>&h>Tp>w>>>>r>>>ݓ>!>v>ݠ>\V>>nz>A%>>>=>l>?c>g>y>D>n>>M7>>u>1>2>Ӏ?9?\?W ?8s ?4??ȹ?|?C??? ?q#?X;&?O(?Щ+?T[.?R1?A3?R6?8?L;?>?@?JC?E?G?ZJ?L?N??Q?tS? U?jW?;Y?[?D]?_?cla?Z/c?d?f?h?i?dk?\l?m?n?o? q?$r?=r?s?ot?!)u?u?=v?v?-v?h>w?Diw?~w?~w?Diw?h>w?-v?v?=v?u?!)u?ot?s?=r?$r? q?o?n?m?\l?dk?i?h?f?d?Z/c?cla?_?D]?[?;Y?jW? U?tS??Q?N?L?ZJ?G?E?JC?@?>?L;?8?R6?A3?R1?T[.?Щ+?O(?X;&?q#? ??C??|?ȹ??4?8s ?W ?\?9?Ӏ?2>1>u>>M7>>n>D>y>g>?c>l>=>>>A%>nz>>\V>ݠ>v>!>ݓ>>>r>>>>w>Tp>&h>1a>rZ>S>L>(F>?>`9>53>/->O'>2!>>j>T=> > >'>Q====K^=%=,=p== =㦩=Bآ=B===ʼn=x=!|=H=Z=V=/==Ƒ="l=&=ҷ=_=,=7==H===N=v>i>[ >a>)>>J">(>.>.4>r:>@>(pG>)N>U U>p\>SEc>j>r>y>fˀ>&DŽ>ֈ>>0>y>֙>2F>Ȣ>7]>>>>a>rM>uI>EU>gp>Y>>>k>%>6>.>G.> >}&??F?P ?8s ?M?)?????!?b$?b?'?*?>,?\/?2?>f5?.8?M:?߯=?g@?JC?E?`H?J?\M?W P?R?T? [W?]Y?([?=^? o`?b?d?f?h?Yj?\l? n?o?tq?Js?ot?u?h>w?x?y?z?{?;|?}?_~?.?? ?O?|??˳???˳??|?O? ??.?_~?}?;|?{?z?y?x?h>w?u?ot?Js?tq?o? n?\l?Yj?h?f?d?b? o`?=^?([?]Y? [W?T?R?W P?\M?J?`H?E?JC?g@?߯=?M:?.8?>f5?2?\/?>,?*?b?'?b$?!?????)?M?8s ?P ?F??}&? >G.>.>6>%>k>>>Y>gp>EU>uI>rM>a>>>>7]>Ȣ>2F>֙>y>0>>ֈ>&DŽ>fˀ>y>r>j>SEc>p\>U U>)N>(pG>@>r:>.4>.>(>J">>)>a>[ >i>v>N===H==7=,=_=ҷ=&="l=Ƒ==/=V=Z=H=׈=ڎ==섛=K/=&=4=]=;.= =%==$= =4==e>> > >+> (>">(>.> 5>e;>A>H>rlO>,kV>]>Od>^l>t>U{>>>(>5Q>>:>u>f>>M>>6>-з>H˼>$>W>r%>d>t>T>> >>U>P>n>8? v?\?ZG ?5 ?(???T?@?"?$?,'?*?-?0?3?"6?9?P>U>> >>T>t>d>r%>W>$>H˼>-з>6>>M>>f>u>:>>5Q>(>>>U{>t>^l>Od>]>,kV>rlO>H>A>e;> 5>.>(>"> (>+> > >>e>=4= =$==%= =;.=]=4=&=K/=섛==ڎ=׈=OF==h===ʯ=3={۾===K^=H= =I==b>-> >l>3>>d#>\)> }/>w5><9<>B>I>ČP>W>^>Q^f>m>wu>}>f>> >D>7>+>Ip>j>c>X>%>4>D>>>uI>>>?>v>9>T>6t>'>>A>??ø? ?ۻ ?H???? ?f!?:"?U%?p(?+?.?1?4?7?;?>?A?x&D?)G?&J?M?W P?R?U?X?y[?=^?R`?c? Hf?%h?Hgk?m?XPp? r?t?h>w?my?b{?}??@@z?c?0???Z?0??#?ѥ?i?}??:?????+?7?7?+?????:??}?i?ѥ?#??0?Z???0?c?z????}?b{?my?h>w?t? r?XPp?m?Hgk?%h? Hf?c?R`?=^?y[?X?U?R?W P?M?&J?)G?x&D?A?>?;?7?4?1?.?+?p(?U%?:"?f!? ????H?ۻ ? ?ø???A>>'>6t>T>9>v>?>>>uI>>>D>4>%>X>c>j>Ip>+>7>D>> >f>}>wu>m>Q^f>^>W>ČP>I>B><9<>w5> }/>\)>d#>>3>l> >->b>=I= =H=K^==={۾=3=ʯ===h==OF=ߓ=]=4=D =%A=9=g=n]=D====4==>>j7 >Y>/>@#>')>0>9d6><>C>J>UQ>X>#`>g>&no>RVw>5k>lփ> >&[>>9>2ə>[o>[+>>!>v>>>Q>9>> w>>>D>>v>.>P>2>???k ?"?E?l?)???,"?c%?(?u+?/?K2?5?8?(;?X+??]B?E?H?K?N?R?.U?g;X?@[?=^?1a? d?f?i?l?Vo?$r?Щt?h>w?Sy?:|?ȡ~?|?̞??Ƀ?Rф?@@?%?c?.??̣?M??~??!?k?S??k?3?e?e?s???s?e?e?3?k??S?k?!??~??M?̣??.?c?%??Æ?mυ?Rф?Ƀ??̞?|?ȡ~?:|?Sy?h>w?Щt?$r?Vo?l?i?f? d?1a?=^?@[?g;X?.U?R?N?K?H?E?]B?X+??(;?8?5?K2?/?u+?(?c%?,"???)?l?E?"?k ????2>P>.>v>>D>>> w>>9>Q>>>v>!>>[+>[o>2ə>9>>&[> >lփ>5k>RVw>&no>g>#`>X>UQ>J>C><>9d6>0>')>#>>/>Y>j7 >>>=4====D=n]=g=9=%A=D =4=]=ߓ=ʢ=)b=^=n=2=ӽ====/v====b>>C >ø>V>>$>**>p0>6>=>rJD> AK>dR>Y>4a>}h>p>x>a}>&>+>n[>ӑ>c>G >ǟ>>ˇ>>>ϸ>>l>O>^>>>`>2>>; >>->?{?? ?)D?z?5??C???!?*%?](?u+?R//?h2?%5?>9?I9?%5?h2?R//?u+?](?*%?!??C???5?z?)D? ??{??->>; >>2>`>>>^>O>l>>ϸ>>>ˇ>>ǟ>G >c>ӑ>n[>+>&>a}>x>p>}h>4a>Y>dR> AK>rJD>=>6>p0>**>$>>V>ø>C >>b>===/v====ӽ=2=n=^=)b=ʢ=A=\=3֭=DY= =)=x=q==;==N=e>->j7 >ø>c>H9>9$>e*>y0>A7>=>D>K>:S>nZ>b>]i>q>z>/>&t>qЉ>D>uђ>&v>2>>:>>u>G>'>y>fk>>ʝ>W>f&> >>N >+>>]>!?$?J(?+?/?y2?5?$o9?!??v??/?s?) ? ??z?]>+>N >> >f&>W>ʝ>>fk>y>'>G>u>>:>>2>&v>uђ>D>qЉ>&t>/>z>q>]i>b>nZ>:S>K>D>=>A7>y0>e*>9$>H9>c>ø>j7 >->e>N==;==q=x=)= =DY=3֭=\=A===}=~J=q\=2=JV=?A=w==Q=v>> >Y>V>H9>G$>*>o0>7>E>>9E>[L>S>0[>b>j>r>"{>́>">>> >Ip>|B>->1>N>>Ҷ>J8>>L> >˾>>>>>.>z>;*>>j?9?? ?/?,??Dk?o?_ ?#?j'?*?.?A2?5?O9??M??Ӛ?;? u?H3??9? ??e'???K?‘?ɡ???????ɡ?‘?K???e'?? ?9??H3? u?;?Ӛ??M?>???=Д?ب? w?#;?k?0?M?v?????X??f??P|?y?u?Fr?n?Hgk?g?$kd?`?LW]?;Y?P1V?:R?N?9bK?G?x&D?i@?;*>z>.>>>>>˾> >L>>J8>Ҷ>>N>1>->|B>Ip> >>>">́>"{>r>j>b>0[>S>[L>9E>E>>7>o0>*>G$>H9>V>Y> >>v>Q==w=?A=JV=2=q\=~J=}====H=iV=n="=x=m=_='?=='>@@@/>>9$>*>0>Y7>hw>>}E>*L>T>-[>mc> ~k>hs>|>HT>p>z8>wя>s>vQ>|8>9>oT>6>ײ>?>D>[>>>{>(>|> >g?>>>E?K?{?ZG ? ?"?s?[ ??<?"?t&?*?-?s1?k'5?8?I?B??Y?Fk?T?ש?#;?Ï?rC?&?+?h??1O?R?m?9?~?v{?w?Ut?p?m?ki?e?b?'Q^?+Z?V?S?dXO?K?G?zD?dV@?I>g?> >|>(>{>>>[>D>?>ײ>6>oT>9>|8>vQ>s>wя>z8>p>HT>|>hs> ~k>mc>-[>T>*L>}E>hw>>Y7>0>*>9$>>/>l> >i>'>='?=_=m=x="=n=iV=H==,m=FC=`==w=t==Z=`F=v> >@@@>$>e*>o0>Y7>>>E>fL>veT>p\>c> l>Wt>|>dł>:>ɋ>s>9>8>j>*>[>Χ>>8>N,>>S>ʝ>ڡ>3>y>HD>5>)>>???J ?y???(3??!?8%?O(?Y,?}~0?4L4?8?(;?B??C?G?sK?dXO?=S?#W?[?t^?b?f?Yj?^n?1r?u?Sy?}??t?G?? ݇?T?G[??꾎?e?? ?*?K?,???@@ ?(C?u??R?Ť?sǥ?T??~?aK?{ ??^?a?y?`?cZ???@)>5>HD>y>3>ڡ>ʝ>S>>N,>8>>Χ>[>*>j>8>9>s>ɋ>:>dł>|>Wt> l>c>p\>veT>fL>E>>>Y7>o0>e*>$>>3> >[ > >v>`F=Z==t=w==`=FC=,m==k2==wS=/W==M=C=G>> >@@@#>**>y0>7>hw>>E>(L>GT>M\>Ed>csl>t>3p}>( >>B>>}ԕ>+ǚ>՟>>*G>˩>T(>º>x>@J>#7>!?>a>_>>wh>e>T>S>#?? ? ?I/??|?2??%#?'?_+?>/?Z$3?7?;?>?B?WF?J?N?S?vW?[?m%_?Z/c?7g?>k?DBo?|Bs?h>w?D5{?I&?X?y??g?(P?-4???꾎?e?P?T?ƕ?t??4?hL? ם?W?>Π?@@?:?x?U?ϩ??a?`??RĮ?И?_??ܿ? Z?i?a?γ?,?/z?Ÿ??!???!??Ÿ?/z?,?γ?a?i? Z?ܿ??_?И?RĮ??`?a??ϩ?U?x?:???:?>Π?W? ם?hL?4??t?ƕ?T?P?e?꾎???-4?(P??g?y?X?I&?D5{?h>w?|Bs?DBo?>k?7g?Z/c?m%_?[?vW?S?N?J?WF?B?>?;?7?Z$3?>/?_+?'?%#??2?|??I/? ? ??#?S>T>e>wh>>_>a>!?>#7>@J>x>º>T(>˩>*G>>՟>+ǚ>}ԕ>>B>>( >3p}>t>csl>Ed>M\>GT>(L>E>hw>>7>y0>**>#>>+>a> >>G>C=M==/W=wS==k2===KR=s = =m==O=>w > >T=>)> (>d#>')>p0>A7>E>>}E>fL>GT>`\>pmd>l>+u>}>dd> >/>n>V>Z>Y|>>2>>$$>ֻ>ȥ>>4>>>\> >h>>>?_??8 ?"???M?H?!?%?)?x-?[1?5?9?=?A?F?&J?KN?tR?ƠV?Z?^?Z/c? `g?k?žo?Ss?x?:|?A.?e>h> >\>>>4>>ȥ>ֻ>$$>>2>>Y|>Z>V>n>/> >dd>}>+u>l>pmd>`\>GT>fL>}E>E>>A7>p0>')>d#> (>)>T=> >w >>O==m= =s =KR===n=2=B =z==>Bi> >>j>>">\)>0>6>=>9E>*L>veT>M\>pmd>cl>Vu> ~>>0>_>FǑ>޾>Hԛ>>X>oȫ>U>>H˼>>>>>z>g>>xC>t>:>?.?4 ?t ??]?-? ??#?'?Y+?/? 4?.8?Wt>xC>>g>z>>>>>H˼>>U>oȫ>X>>Hԛ>޾>FǑ>_>0>> ~>Vu>cl>pmd>M\>veT>*L>9E>=>6>0>\)>">>j>> >Bi>>=z=B =2=n===X&==9=C==Ѱ>< >>:>>J">(> }/>9d6>=>D>[L>T>p\>Ed>l>Vu>6~>è>iT>>>{>O >2>ew>ڦ>]>K>A>e>> >]>W>T>k>#>Y>B>^>#?ø?Ok ?+????׮?!?%?r)?-?A2?R6?7:?>?2(C?nG?K?rBP?T?Y?ܐ]?b?f?dk?|o?vt?x?|??? 9?Xs?A?W?-?T@?\j?ԏ?K?P˘?q?=?B??5?B?ʦ?U??L??zƯ?r???2?}???Ի?<?S?D}? ?գ?!?Č?i?!6?n?:?V9???7:?R6?A2?-?r)?%?!?׮????+?Ok ?ø?#?^>B>Y>#>k>T>W>]> >>e>A>K>]>ڦ>ew>2>O >{>>>iT>è>6~>Vu>l>Ed>p\>T>[L>D>=>9d6> }/>(>J">>:>>< >Ѱ>=C=9==X&==E{===ĝ==>q >0>>@>2!>(>.>w5><>rJD>K>S>-[>c>csl>+u> ~>è>9`>6>t,>A>v>kˡ>9@>'լ>M>_>tU>{k>ġ>=>n>F>>F>O>P>zf??F?O ?`?`C?3?1?<?T#?by'?Щ+?/?,4?~8?O>F>>F>n>=>ġ>{k>tU>_>M>'լ>9@>kˡ>v>A>t,>6>9`>è> ~>+u>csl>c>-[>S>K>rJD><>w5>.>(>2!>@>>0>q >>=ĝ===E{= =\==9=>5>Q>D>0j> >O'>.> 5><9<>C> AK>:S>0[>mc> l>t>}>>iT>6>9>[>P>>>/>>߸>>>?c>>a>8>>>> >:??1?K ??v?|??2 ?$?? )?Gj-?1?9#6?7:?; ??C?;H?L?QQ?U?Z?u__? d?%h?m?pr?h>w?H|?p?ڂ?D???<~? ?G?ب??a?4?q ?W?ß???R???RĮ?qٰ?i???͸???S??f?j????$v?l?d#?b????ڿ??k??O??}?B??4????Q:? M? M?Q:????@@@}??O??k??ڿ????b?d#?l?$v????j?f??S???͸???@qٰ?RĮ???R???ß?W?q ?4?a??ب?G? ?<~???D?ڂ?p?H|?h>w?pr?m?%h? d?u__?Z?U?QQ?L?;H?C?; ??7:?9#6?1?Gj-?? )?$?2 ??|?v??K ?1??:? >>>>8>a>>?c>>>߸>>/>>>P>[>9>6>iT>>}>t> l>mc>0[>:S> AK>C><9<> 5>.>O'> >0j>D>Q>5>>9==\= ==O=`F=>>$\ >Q>z>>@h&>/->.4>e;>B>J>dR>nZ>b> ~k>Wt>3p}>dd>0>>>t,>[>㬜>>N>'k>OD>?>^>>> >0>> >>]*>}>j?? ? ?r??ȭ??"?)X&?*?/?3?7?]*>> >>0> >>>^>?>OD>'k>N>>㬜>[>t,>>>0>dd>3p}>Wt> ~k>b>nZ>dR>J>B>e;>.4>/->@h&>>z>Q>$\ >>>`F=O===,=>u>O >F>q>[>e%>1,>53>r:>A>I>UQ>Y>b>j>hs>|>( > >_>{>A>P>>§>6>r>%>>>}>*>2>>>>?>հ>â?s~?@@@?d??T#?v'? ,?0?k'5?9?d>?JC?G?`L?vQ?qVV?@[?4`?a1e? 6j?DBo?Ut?my?~?ց?i?0?h?!)?꾎?PT??|? ??0)?c?7??5?׬?Y???LK???12?:m?v?f??n??x??ƻ?D?P???B??7A?? ?C?v?l?G???Ji?.??? ?Ƃ??6?r? ??? ?r?6??@@@?.?Ji???G?l?v?C? ??7A??@@@P?D?ƻ??x??n??f?v?:m?12???LK???Y?׬?5??7?c?0)?? ?|??PT?꾎?!)?h?0?i?ց?~?my?Ut?DBo? 6j?a1e?4`?@[?qVV?vQ?`L?G?JC?d>?9?k'5?0? ,?v'?T#??d??w?)i?Ok ?s~?â?հ>?>>>>2>*>}>>>%>r>6>§>>P>A>{>_> >( >|>hs>j>b>Y>UQ>I>A>r:>53>1,>e%>[>q>F>O >u>>,==#==Bi>- >,$>O>m>G$>+> 2>`9>@>H>ČP>X>4a>]i>r>|>dł>>/>FǑ>O >v>>N>6>z>L>>@J>>>z^>Y>z>>;*> >96?!? ?@@@?S ?4$?O(?Ny-? 2?w6?c;?l$@?D?I?N?S?X?D]?b?g?m?Fr?~w?;|??p?1O??̣?O?G?ب?U?M?;?QR???:?2֨?m??匰??????K?գ??@@??? ?4??K?M?^I? ??7??.???@@ d?_j?]?R=?{ ??$f?J?r??V,?j? ?̨?̨? ?j?V,??r?J?$f??{ ?R=?]?_j? d?J????.??7?@@@M?K??4? ????p?7??գ?K??????匰??m?2֨?:???QR?;?M?U?ب?G?O?̣??1O?p??;|?~w?Fr?m?g?b?D]?X?S?N?I?D?l$@?c;?w6? 2?Ny-?O(?4$?S ???#P?/? ?!?96? >;*>>z>Y>z^>>>@J>>L>z>6>N>>v>O >FǑ>/>>dł>|>r>]i>4a>X>ČP>H>@>`9> 2>+>G$>m>O>,$>- >Bi>=#=E=2> >>4>iw>#>)>o0>08>?>(pG>rlO>W>#`>}h>q>"{>HT>:>B>n>޾>2>kˡ>>'k>r>L>y>l> >`>(>C>>af>B>2>?? ?4?@@@!?ގ%?*?.?{b3?8?Ee?Yj?o?!)u?az??m??g?#???e? )??ذ?Rt?6??R?(t? .?{?떮?D??琶?-?bĻ?S??Y?$?Ee? `?Z?U?ѮP?K?pF?`A?B>af>>C>(>`> >l>y>L>r>'k>>kˡ>2>޾>n>B>:>HT>"{>q>}h>#`>W>rlO>(pG>?>08>o0>)>#>iw>4>> >2>E=>>>>%>7!>(>v/>6>f>>(F>)N>,kV>^>g>p>z>́>p>ɋ>>V>Hԛ>ew>9@>/>OD>%>>l>>> >>l>z>́>#?]?$?!B ?s?5?T?;x?!?k&?)$+?/?`4?$o9?T>?JC?EOH?cM?R?jW?@@4g?m?pr?w?m}?}?G???&?ő?\j?uD??I? ם?c?ʌ?e??$o9?`4?/?)$+?k&?!?;x?T?5?s?!B ?$?]?#?́>z>l>> >>>l>>%>OD>/>9@>ew>Hԛ>V>>ɋ>p>́>z>p>g>^>,kV>)N>(F>f>>6>v/>(>7!>%>>>>>zF>j7 >b^>>vS >$'>/.>w5>T<>D>L>U U>]>Q^f>&no>x>/>">z8>s>}ԕ>Z>>ڦ>'լ>>?>>@J> >> >D>l>7>>zf?j?? ?r?5E?ȭ?)?"?_\'? ,?T0?5?b:?m??D?I?N?>T?Y?t^?@@Wo?qt?@@m?mυ???!?m?`\?HM???H3?e'??S??a??Dϱ?Ÿ???\?4?i?$??O??ĭ?N??r??]i??.?}??'??w(?V,?????>??_??J2?|}?Z@@Aq@@]@k@-@m@/@@@@OR@]@]@OR@c;@@I@/@m@-@k@]@@Aq@@Z@|}?J2??_??>?????V,?w(??'??}?.??]i??r??N?ĭ??O??$?i?4?\???Ÿ?Dϱ??a??S??e'?H3???HM?`\?m?!???mυ?m? ?az?qt?Wo?i?[Wd?t^?Y?>T?N?I?D?m??b:?5?T0? ,?_\'?"?)?ȭ?5E?r? ??j?zf?>7>l>D> >> >@J>>?>>'լ>ڦ>>Z>}ԕ>s>z8>">/>x>&no>Q^f>]>U U>L>D>T<>w5>/.>$'>vS >>b^>j7 >zF> >G>B<>[>%>,>a3>u;>;C> AK>S>p\>Od>m>RVw>a}>&t>>wя>9>+ǚ>Y|>X>]>M>߸>^>>>`> >D>>`>G.>?? ? ? U?ȹ?(3??c#?J(?C,?1?w6?;?.@?mE?c-K?xP?U?@[?`? Hf?@@h>w?|?@@oD?:?I5?3?5?:?B?hL?W?Ed?[q?~?7?떮???}??뮽?Ш???$v?{X?n3?f???^I?b?l?.?5?6??{ ?w]?y??n?V?/?}???8@y @X@!@K@@*@,@@A7@@@r@@ @@@@@Ѽ@Ѽ@@K@u@F@ @@r@@@A7@@,@*@@K@!@X@y @8@??}?/?V?n??y?w]?{ ??6?5?.?l?b?^I???f?n3?{X?$v???Ш?뮽??}???떮?7?~?[q?Ed?W?hL?B?:?5?3?I5?:?oD?R?f?|?h>w?tq?k? Hf?`?@[?U?xP?c-K?mE?.@?;?w6?1?C,?J(?c#??(3?ȹ? U? ? ???G.>`>>D> >`>>>^>߸>M>]>X>Y|>+ǚ>9>wя>>&t>a}>RVw>m>Od>p\>S> AK>;C>u;>a3>,>%>[>B<>G> >O>>5>$><+>^M2>9>A>I>/Q>rZ>SEc>^l>wu>5k>&>qЉ>>s>8>՟>>oȫ>K>_>>>}>>(>>l>`>C>K?{?z?;B ???.?<?#?̹(?`-?@@@*A?G?7kL?Q?cHW?7\?jb?h?Dm?ٖs?my?R???ѥ?寋?꾎?qґ? ?>?#?D?g???9٪??&?LK?n?G?뮽?6??W?? ?K ???.??!?Ak?.??Ւ?e2??~I?ؿ?M'?L?E??%?ڜ@%@!@@>i@C@b@p@@F@<@̆ @ @ @5 @~ @ @4 @} @@@@X( @4 @4 @X( @ @? @q @} @4 @ @~ @5 @ @ @̆ @<@F@@p@b@C@>i@@!@%@ڜ@%??E?L?M'?ؿ?~I??e2?Ւ??.?Ak?!??.???K ? ??W??6?뮽?G?n?LK?&??9٪???g?D?#?>? ?qґ?꾎?寋?ѥ???R?my?ٖs?Dm?h?jb?7\?cHW?Q?7kL?G?*A?`>l>>(>>}>>>_>K>oȫ>>՟>8>s>@qЉ>&>5k>wu>^l>SEc>rZ>/Q>I>A>9>^M2><+>$>5>>O>0>#>J">M)>0>8>0?>G>v P>X>1a>j>t>}>lփ>+>D> >vQ>j>>@@@tU>@@*>z^>C>l>7>G.>K??9 ?f ?,?U???b$?=)?..?33?@@@;H?\M?S?(X?=^?c?~i?=o?'~u?v{??Ƀ?ۆ???3?)\?%?S?=?e'?Mb?r?Nީ?Y?_?ɟ??C?\? ???6?b?????>???M???w]???|?/??D?C@Aq@!@/@%@@@@@ @i @`6 @ @@ @LY @ @Œ@@ @+@e@˼@@F@`y@5@s@@@s@5@`y@F@@˼@e@+@ @@Œ@ @LY @@ @ @`6 @i @ @@@@@%@/@!@Aq@C@D??/?|???w]???M???>?????b?6??? ?\?C??ɟ?_?Y?Nީ?r?Mb?e'?=?S?%?)\?3???ۆ?Ƀ??v{?'~u?=o?~i?c?=^?(X?S?\M?;H?B?~=?N8?33?..?=)?b$???U?,?f ?9 ??K?G.>7>l>C>z^>*>>>tU>A>U>2>>j>vQ> >D>+>lփ>}>t>j>1a>X>v P>G>0?>8>0>M)>J">#>0>>(} >{'>ѷ.>46>=>kE>;N>#V>˛_>&h>r>U{>f> >n[>uђ>Ip>|8>*>*G>@@@{k>@@2>Y>>z>>?{?9 ?8s ?s?@@?@$?T)?.?ӿ3?8?@@@AN?T?;Y?-_?Ye?>k?5q?h>w?W}??܄?u?+?\?S?=Д?j?dY???`F??a?L?t??%^???j??y?b?ĭ??4?4o??9?`?? ?w(?%? ??y??Z^?@X@-@]@֔@@7@ @ @B @H @ @ @@@q@-@X@@@@@(@@@]@N@2@1 @;G@Ha@Pn@Pn@Ha@;G@1 @2@N@]@@@@(@@@@X@-@q@@@ @ @H @B @ @ @7@@֔@]@-@X@@Z^??y?? ?%?w(? ??`?9??4o?4??ĭ?b?y??j???%^??t?L?a??`F???dY?j?=Д?S?\?+?u?܄??W}?h>w?5q?>k?Ye?-_?;Y?T?AN?H?C?3>?8?ӿ3?.?T)?@$??_$?|?s?8s ?9 ?{??>z>>Y>2> >?c>{k>e>>>*G>*>|8>Ip>uђ>n[> >f>U{>r>&h>˛_>#V>;N>kE>=>46>ѷ.>{'>(} >>[>%> ,>f>4> ;>{C>*8L>T>]>6f>Tp>y>>> >&[>ӑ>&v>|B>9>[>˩>@@@ġ>>0>>z>af>́>zf??z?f ?s??@@`$?)?/?,4?$o9?>?w7D?I?dXO?1 U?Z?i`?f?l? r?x?.?m?ۅ??M?ő?ܒ?-???(C?#????c?ش?M?bĻ?:??%?? ?w??NG?? ?W?e?\?(?w]?=??ҽ?E?C?Z@@4@*@@C@u@\ @) @4 @LY @t@@@@Ov@k[@5@@@@Y{@6%@@S@@%O@@@g@@@@"@A0@A0@"@@@@g@@@%O@@S@@6%@Y{@@@@5@k[@Ov@@@@t@LY @4 @) @\ @u@C@@*@4@@Z@C?E?ҽ??=?w]?(?\?e?W? ??NG??w? ??%??:?bĻ?M?ش?c????#?(C???-?ܒ?ő?M??ۅ?m?.?x? r?l?@i`?Z?1 U?dXO?I?w7D?>?$o9?,4?/?)?`$?u ?C???s?f ?z??zf?́>af>z>>0>>ġ>>H˼>$$>˩>[>9>|B>&v>ӑ>&[>> >>y>Tp>6f>]>T>*8L>{C> ;>f>4> ,>%>[>B#>5*>{.2>9>A>J>XR>i[>Dm>w>fˀ>>D>>c>2>->oT>Χ>T(>ֻ>> >=>a>>>>B>#?j? ?;B ?,?|?C??S ? %?*?>/?{4?9?;??D?ZJ?W P?U?[?a?Fg?Dm?vt?LFz?O?/?*? %?S ?C??|?,?;B ? ?j?#?B>>>>a>=> >>ֻ>T(>Χ>oT>->2>c>>D>>fˀ>w>Dm>i[>XR>J>A>9>{.2>5*>B#>D(>0>C7>Z?>G>VP>Y>M2b>uk>@u>>>&DŽ>(>7>9>G >>1>6>>º>ȥ>>]>n>8> >>;*>2>]?? ??U?_$?u ? %?(*?\/?4?:?ӎ?? &E?qJ?P?{V?q\?x~b?h?n?!)u?b{??G???O?.?*??#??7?ʦ?b???E??V?D???O??k?]U???5D??/x?{ ? ? ???`l?/e@@/@wO@ @u@' @~ @u @g@K@-@@@@;G@s@@<@m@@@@l@a;@@ @X!@ !@"@"@o#@#@ ($@Lo$@S$@%$@$@$@$@$@%$@S$@Lo$@ ($@#@o#@"@"@ !@X!@@@a;@l@@@@m@<@@s@;G@@@@-@K@g@u @~ @' @u@ @wO@/@@/e@`l??? ? ?{ ?/x??5D???]U?k??O???@@@E???b?ʦ?7??#??*?.?O???G??b{?!)u?n?h?x~b?q\?{V?P?qJ? &E?ӎ??:?4?\/?(*? %?u ?_$?U?? ??]?2>;*>> >8>n>]>>ȥ>º>>6>1>>G >9>7>(>&DŽ>>>@u>uk>M2b>Y>VP>G>Z?>C7>0>D(>E->h5>EO=>}E>bM>V>_> i>r>|>>ֈ>5Q>+>2ə>ǟ>:>N>ײ>8>x>>>W>F>>>?> >?$? ? U????`$?*?\/?4?T0:???hjE?c-K?L Q?V? ]?Z/c?ki?žo?(v?V|?̞?? S??d.?ש?-?S?N???5?{?И? R??к??\?%?x?ƻ?,?Q??>?G?i?'?? ?CA???D?@!@OR@@&@c @) @ @h6@@F@@5@W@@S@@@}@@@>_@r@y @t!@tc"@-E#@$@m$@%@H&@&@w'@|'@o(@X(@4-)@v)@R)@s)@)@ *@ *@)@s)@R)@v)@4-)@X(@o(@|'@w'@&@H&@%@m$@$@-E#@tc"@t!@y @r@>_@@@}@@@S@@W@5@@F@@h6@ @) @c @&@@OR@!@@D???CA? ??'?i?G?>??Q?,?ƻ?x?@@@к?? R?И?{?5???N?S?-?ש?d.?? S??̞?V|?(v?žo?ki?Z/c? ]?V?L Q?c-K?hjE???T0:?4?\/?*?`$???? U? ?$?? >?>>>F>W>>>x>8>ײ>N>:>ǟ>2ə>+>5Q>ֈ>>|>r> i>_>V>bM>}E>EO=>h5>E->3>:>ZC>uK>H.T>/3]>@f>")p>uz>l2>r>>>Ip>[o>>>>?>N,>@J>4>>T>>>]*>հ>96??!B ?r?ȹ?.??@$?)?>/?4?T0:?B??E?9bK?QQ? [W?}]?Mc? j?zp?-v?}?%???r?k?|??4? `??sǥ??^K???н?V?v?~X?@o @"@(#@D$@S%@}V&@1L'@4(@)@s)@2*@N+@+@,@{-@-@-@yJ.@ .@.@ /@b/@-/@-/@b/@ /@.@ .@yJ.@-@-@{-@,@+@N+@2*@s)@)@4(@1L'@}V&@S%@D$@(#@"@o @>@C@s@|@@$@@O2@N@j@@o@:@Q @ @ @ZR@@@l@y @Z^?՛?&??V,?Q?r??̫????K ?@@@v?V?н???^K??sǥ?? `?4??|?k?r???%?}?-v?zp? j?Mc?}]? [W?QQ?9bK?E?B??T0:?4?>/?)?@$??.?ȹ?r?!B ??96?հ>]*>>>T>>4>@J>N,>?>>>>[o>Ip>>>r>l2>uz>")p>@f>/3]>H.T>uK>ZC>:>3>`8>y@>QH>UQ>nZ>Sc>im>RVw>fˀ>h>>0>:>j>[+>ˇ>u>Ҷ>D>>#7>>z>k>F>>}>â?!? ?s?5E?(3?<?b$?T)?/?{4?:???E?sK?vQ? W?z]? d?Yj? q?w?_~?ʖ?r ?}??s?B???W????떮? y?ya?O?C?;?7?6?8?=?B?^I?P?V?Z?]?w]?Y?Q? E?J2?y @@@@@ @1e @h6@+@@@6@@i@@$@@@@h@w4 @!@"@R$@%@d&@ (@4-)@D*@N+@K,@|;-@1.@.@]/@lm0@1@1@V:2@ 2@"3@3@3@ 4@:4@Z4@i4@i4@Z4@:4@ 4@3@3@"3@ 2@V:2@1@1@lm0@]/@.@1.@|;-@K,@N+@D*@4-)@ (@d&@%@R$@"@!@w4 @h@@@@@$@i@@6@@@+@h6@1e @@@@@@y @J2? E?Q?Y?w]?]?Z?V?P?^I?B?=?8?6?7?;?C?O?ya? y?떮????W???B?s??}?r ?ʖ?_~?w? q?Yj? d?z]? W?vQ?sK?E???:?{4?/?T)?b$?<?(3?5E?s? ?!?â?}>>F>k>z>>#7>>D>Ҷ>u>ˇ>[+>j>:>0>>h>fˀ>RVw>im>Sc>nZ>UQ>QH>y@>`8>=>(F>N>W>`>j>lt>W~>*>1 >>y>u>c>>>G>J8>[>S>!?>>g>#>O> >j?s~? ?4?5?ȭ??#?=)?.?,4?9?ӎ??hjE?9bK?vQ?W?]?[Wd?j?tq?{*x?~?m?r??K?#;? ??g?F5? ??ի?zƯ?쾳?h?bĻ?Kп????[/?O?r????W?w(?~I?g?.?N?@@)@p@@ @q @x@@i@A@/@@@X@ @@=P @!@o#@$@d&@'@4-)@*@+@},@H,.@K/@$^0@b1@:Y2@A3@4@4@S5@P6@6@}7@47@l8@8@9@6]9@k9@9@9@9@9@k9@6]9@9@8@l8@47@}7@6@P6@S5@4@4@A3@:Y2@b1@$^0@K/@H,.@},@+@*@4-)@'@d&@$@o#@!@=P @@ @X@@@/@A@i@@x@q @ @@p@)@@@N?.?g?~I?w(?W????r?O?[/????Kп?bĻ?h?쾳?zƯ?ի?? ?F5?g?? ?#;?K??r?m?~?{*x?tq?j?[Wd?]?W?vQ?9bK?hjE?ӎ??9?,4?.?=)?#??ȭ?5?4? ?s~?j? >O>#>g>>!?>S>[>J8>G>>>c>u>y>>1 >*>W~>lt>j>`>W>N>(F>=>\C>oK>T>d^>xg> bq>{>q >w>>ݓ>@@X>!>>'>>>ʝ>a>\>>Y>P>:??Ok ?/??T?)?c#?̹(?..?ӿ3?$o9?;?? &E?c-K?QQ? W?]?$kd?dk?Rq?x?h?5?Æ?^??.?9x?B? ??B?2֨?jӬ?qٰ???<?F??ji???f?B?"???J??W?a?@T?-?/e@@*@@Ѽ@ @ @@@>@@@@vt@K@@E@!@SS#@$@&@4(@)@@+@,@1.@y/@;0@ 2@A3@i4@܃5@6@7@|8@6]9@t.:@k:@;@E<@<@[=@=@1>@>@&>@@@l)?@l)?@?@>@&>@>@1>@=@[=@<@E<@;@k:@t.:@6]9@|8@7@6@܃5@i4@A3@ 2@;0@y/@1.@,@@+@)@4(@&@$@SS#@!@E@@K@vt@@@@>@@@ @ @Ѽ@@*@@/e@-?@T?a?W??J???"?B?f???ji?F??<???qٰ?jӬ?2֨?B?? ?B?9x?.??^?Æ?5?h?x?Rq?dk?$kd?]? W?QQ?c-K? &E?;??$o9?ӿ3?..?̹(?c#?)?T??/?Ok ??:?P>Y>>\>a>ʝ>>>'>>!>X>f>֙>ݓ>>w>q >{> bq>xg>d^>T>oK>\C>#H>Q>$Z>pmd>7n>Wx>g>І>Og>t,>!>@@%>v>ϸ>y>L>>ڡ>_> >xC>B>zf?? ?)i?#P?U?;x?"?J(?`-?33?8?>?D?qJ?L Q? [W?z]?[Wd?dk?Dq?x??c?0??\?R??Ǚ? ?ß?a?y?@@?C?S?E???Pi???p?9?:0?Ւ?J?Y?ż?>?|}?@@B@i@ @@ @@o@l@@ @ @@ @@o @ܩ"@}$@H&@ (@)@l+@{-@+.@R00@1@"3@4@Q5@m.7@l8@9@ۿ:@;@<@=@>@?@uT@@ A@A@JB@B@HC@C@D@FD@@@D@D@D@yD@FD@D@C@HC@B@JB@A@ A@uT@@?@>@=@<@;@ۿ:@9@l8@m.7@Q5@4@"3@1@R00@+.@{-@l+@)@ (@H&@}$@ܩ"@o @@ @@ @@@l@o@@@ @ @i@B@@@|}?>?ż?Y?J?Ւ?:0?9?p???Pi???E?S?C??Dϱ??y?a?ß? ?Ǚ??R?\??0?c??x?Dq?dk?[Wd?z]? [W?L Q?qJ?D?>?8?33?`-?J(?"?;x?U?#P?)i? ??zf?B>xC> >_>ڡ>>L>y>ϸ>v>%>>2F>!>t,>Og>І>g>Wx>7n>pmd>$Z>Q>@ N>HW>4a>ej>!u>5k>>>Kg>V>v>Ȣ>M>4>>>fk> >{>3>>h>t>^>?1? ?w???!?_\'?C,?h2?N8?3>?w7D?ZJ?P?V?}]? d?j?Rq?x?6?y?K!?֊?ԙ?\j?G?b2?0)?,?:?4T?x?@@!?l??9?{? ?Q?"?@@@-A@:B@$7C@$D@E@&E@F@V8G@G@^H@GH@@I@ I@I@@@GJ@GJ@|5J@uJ@I@ I@@I@GH@^H@G@V8G@F@&E@E@$D@$7C@:B@-A@@@8>@=@ef<@;@9@=8@v6@K55@3@1@N0@ .@,@+@4-)@1L'@1b%@o#@t!@r@i@X@A@6%@@@A@i@L @ @q@j@hb@"@C?]A?ɽ?Q:??6?;??N8?h2?C,?_\'?!???w? ?1??^>t>h>>3>{> >fk>>>4>M>Ȣ>v>V>Kg>>>5k>!u>ej>4a>HW>@GT>]>xg>q>'{>M>ֈ>鎎>w>>ݠ>7]>>D>>l>>˾>(>y>wh>>:>#?F?K ?r???!?k&? ,?1?7?~=?C?I?W P?{V? ]?Mc?Yj?tq?x??y?-??꾎?#?%??9??T??D?a?@@f??A?ƻ?=??R??}??x?Y???"@5t@%@@c @2 @ @?@@@@4@f@@@!@F#@&@ (@ *@j,@-@/@1@3@D5@6@8@N:@;@Fl=@8>@uT@@A@mC@FD@yE@:F@MG@|H@I@(J@-`K@]"L@L@}sM@N@-N@N@XDO@9O@2O@6O@:O@:O@6O@2O@9O@XDO@N@-N@N@}sM@L@]"L@-`K@(J@I@|H@MG@:F@yE@FD@mC@A@uT@@8>@Fl=@;@N:@8@6@D5@3@1@/@-@j,@ *@ (@&@F#@!@@@f@4@@@@?@ @2 @c @@%@5t@"@??Y?x??}??R??=?ƻ?A??f??}?a?D??T??9??%?#?꾎??-?y??x?tq?Yj?Mc? ]?{V?W P?I?C?~=?7?1? ,?k&?!???r?K ?F?#?:>>wh>y>(>˾>>l>>D>>7]>ݠ>>w>鎎>ֈ>M>'{>q>xg>]>@rZ> d>m>|Bx>5s>>/>6>>Rݞ>\V>>6>>Q>O>ʝ>>>|>HD>e>>?ø?O ???d?S ?ގ%?)$+?T0?w6?M@IN@XDO@O.P@1Q@Q@ބR@F)S@ջS@fM@]"L@J@I@oH@G@E@~5D@B@A@N|?@=@<@N:@|8@Ο6@ݷ4@2@;0@q.@,@2*@}(@}V&@ ($@ !@@v@A0@@n@A@@@4 @ @u@b@/@O@@?/?S? ???Ak???s??H??F??bɼ?]?B??^?!?5?͞?4?K??Iˎ??K!?c?h?{*x? q? j?Z/c?q\?U?dXO?H?B?e>HD>|>>>ʝ>O>Q>>6>>\V>Rݞ>>6>/>>5s>|Bx>m> d>rZ>Mq`>Lj>t>>>>S>> Ȝ>9>>>-з>>9>^>W>> >5>T>?.?Ok ?`?v?ȭ??4$?*?/?5?;?*A?;H?AN?1 U?[?x~b?ki?zp?w?~?5?0?֊?꾎??Y?Ӛ?B?)?j?ӷ??/z??:m???],????7A? ?? ?o?~I?M'?}?B?h@)@zO@l @4 @x@@@2@S@m@B@r@!@$@d&@|(@+*@z-@K/@r1@S3@S5@7@9@;@=@k?@M>A@mC@D@iF@H@ I@K@L@=M@XDO@@@$R@S@T@U@V@W@KX@X@wY@Z@Z@Z@+[@d[@[@[@[@[@d[@+[@Z@Z@Z@wY@X@KX@W@V@U@T@S@$R@Q@P@XDO@=M@L@K@ I@H@iF@D@mC@M>A@k?@=@;@9@7@S5@S3@r1@K/@z-@+*@|(@d&@$@!@r@B@m@S@@@@x@4 @l @zO@)@h@B?}?M'?~I?o? ?@@7A????],???:m??/z??ӷ?j?)?B?Ӛ?Y??꾎?֊?0?5?~?w?zp?ki?x~b?[?1 U?AN?;H?*A?;?5?/?*?4$??ȭ?v?`?Ok ?.??T>5> >>W>^>9>>-з>>>9> Ȝ>>S>>>>t>Lj>Mq`>@f>p>"{>>Z>i>j>>>ǥ>nz>>H˼>uI>>>f&>>g?>)>S>_?4 ?+?`C?|??T#?O(?.?`4?b:?.@?G?\M?T?Z?a?h?žo?-v?_~?m?Æ??ԙ?#?K?Ӛ? ?E??a?_?ش?%^??E?V9?\?ĭ?v?^I?N$? ?'???J??@m@@u@ @~ @+@@@@4@Dt@@X!@#@F+&@D(@+*@|;-@/@_1@ 4@@6@l8@W:@<@>@@@B@D@zF@AMH@uJ@K@}sM@O@P@R@ӄS@%T@@@X@-Y@۹Z@°[@\@@h]@h(^@^@p_@=_@l`@`@ a@Va@}a@2a@2a@}a@Va@ a@`@l`@=_@p_@^@h(^@@h]@\@°[@۹Z@-Y@X@kW@)/V@%T@ӄS@R@P@O@}sM@K@uJ@AMH@zF@D@B@@@>@<@W:@l8@@6@ 4@_1@/@|;-@+*@D(@F+&@#@X!@@Dt@4@@@@+@~ @ @u@@m@@?J???@@N$?^I?v?ĭ?\?V9?E??%^?ش?_?a??E? ?Ӛ?K?#?ԙ??Æ?m?_~?-v?žo?h?a?Z?T?\M?G?.@?b:?`4?.?O(?T#??|?`C?+?4 ?_?S>)>g?>>f&>>>uI>H˼>>nz>ǥ>>>j>i>Z>>"{>p>@f>l>w>> >B>9>c>>\V>!>A%>a>$>> w>> >.>>>#??t ??3??"?v'?Ny-?{b3?$o9?m??mE?7kL?S?;Y?i`?Fg?n?(v?}?ʖ?r?^?\?\j?%?4?B?E??/?匰???S?i???b?B?,?0 ?`? ?V,?>?V?dt?@]@@̆ @H @ձ@F@O@Pn@@|@@ @(#@%@+&(@2*@{-@y/@1@:4@6@8@ !;@[=@?@A@C@JE@?V,? ?`?0 ?,?B?b???i?S???匰?/??E?B?4?%?\j?\?^?r?ʖ?@@n?Fg?i`?;Y?S?7kL?mE?m??$o9?{b3?Ny-?v'?"??3??t ??#?>>.> >> w>>$>a>A%>!>\V>>c>9>B> >>w>l>r>!}>NT>1 >>s>i>>⳩>F>>rM>W>>>`>>z>>??8 ???1?2 ?)X&? ,? 2?8?T>?D?c-K?Q?(X?-_?f?Dm?!)u?V|?%?r ???R?G??͞?)??/?1?46?޹??Y?+? ?4? ??1? ?(?#O?|??B?!@`8@q@ @X( @K@Ov@@@g@ @@SG"@m$@w'@ *@,@b/@-1@4@6@8@a;@g=@@@[B@D@@@@V,M@c2O@m+Q@S@T@V@7X@\5Z@[@@h]@6^@XY`@Ka@c@GAd@je@f@Ѕg@wh@Ti@{j@Rj@Pyk@Kl@l@l@;m@ym@m@Fm@Fm@m@ym@;m@l@l@Kl@Pyk@Rj@{j@Ti@wh@Ѕg@f@je@GAd@c@Ka@XY`@6^@@h]@[@\5Z@7X@V@T@S@m+Q@c2O@V,M@K@H@F@D@[B@@@g=@a;@8@6@4@-1@b/@,@ *@w'@m$@SG"@@ @@@@Ov@K@X( @ @q@`8@!@B??|?#O?(? ?1?? ?4? ?+?Y??޹?46?1?/??)?͞??G?R???r ?@@!)u?Dm?f?-_?(X?Q?c-K?D?T>?8? 2? ,?)X&?2 ?1???8 ???>z>>`>>>W>rM>>F>⳩>>i>s>>1 >NT>!}>r>Ey>>Ƈ>> >>Y|>1>>G>>uI>r%>?>>2>N >;*>E?? ?"?]??<?$?*?0?w6?N >2>>?>r%>uI>>G>>1>Y|>> >>Ƈ>>Ey>>&t>D>/I>F>>>~>ƙ>>=>EU>d>v>D>>+>>K?? ??-?׮?T#?? )?/?k'5?c;?`A?EOH?N?U?7\?c?>k? r?LFz?????#;?9x?Ǚ?0)??!?ӷ?_??޹????#?k??b?.?r???v}??.@I@@n @4 @@@@Y@@$@s@@"@E%@ (@*@-@?0@2@S5@L8@k:@=@~"@@B@#5E@MG@#J@L@N@@@@XW@Z@#\@h(^@`@b@{c@Ve@]g@+i@Pj@l@m@n@9p@rq@r@s@Zt@u@fv@&w@ w@hx@x@Uy@-y@y@mz@.z@.z@mz@y@-y@Uy@x@hx@ w@&w@fv@u@Zt@s@r@rq@9p@n@m@l@Pj@+i@]g@Ve@{c@b@`@h(^@#\@Z@XW@U@ӄS@=Q@N@L@#J@MG@#5E@B@~"@@=@k:@L8@S5@2@?0@-@*@ (@E%@"@@s@@$@Y@@@@4 @n @@I@.@?v}???r?.?b??k?#????޹??_?ӷ?!??0)?Ǚ?9x?#;?????LFz? r?>k?c?7\?U?N?EOH?`A?c;?k'5?/?? )?T#?׮?-?? ??K?>+>>D>v>d>EU>=>>ƙ>~>>>F>/I>D>&t>>>ֈ>̎>p>Z>~>Dɨ>zׯ>R!>>l>gp>t>9>>; >>]>j?{?J ?I/?? ?!?by'?Gj-?3?9?l$@?pF?cM?>T?@[?jb?~i?5q?x?O?G? S?r?s? ?B? ?,?T?^??ش???Č????$?C??\?Q??>?C?`@t@C@ @? @@f@xw@S@A0@ @O @#@&@v)@K,@b/@11@ݷ4@}7@>:@<@?@[B@E@G@|5J@L@XDO@Q@*T@V@X@+[@@h]@L_@Ka@c@%e@g@i@Pyk@;m@n@kp@r@fs@3t@Pv@w@x@ty@z@D{@˥|@k}@~@I~@9@|@@!@8@/C@/C@8@!@@|@9@I~@~@k}@˥|@D{@z@ty@x@w@Pv@3t@fs@r@kp@n@;m@Pyk@i@g@%e@c@Ka@L_@@h]@+[@X@V@*T@Q@XDO@L@|5J@G@E@[B@?@<@>:@}7@ݷ4@11@b/@K,@v)@&@#@O @ @A0@S@xw@f@@? @ @C@t@`@C?>??Q?\??C?$????Č???ش??^?T?,? ?B? ?s?r? S?G?O?x?5q?~i?jb?@[?>T?cM?pF?l$@?9?3?Gj-?by'?!? ??I/?J ?{?j?>]>; >>9>t>gp>l>>R!>zׯ>Dɨ>~>Z>p>̎>ֈ>>/\>B>&_>a>=>>>~=>>l>?c>Y>T>T>v>>?D?K?R?Y?`?h?=o?h>w?.?@A@yD@V8G@tI@QL@XDO@Q@sT@V@xY@[@N^@&`@ b@/e@]g@l}i@k@m@~o@/]q@*s@t@ɐv@'x@-y@{@z|@}@~@ @@ @{@@;@)@΂@@?4@]V@"m@x@x@"m@]V@?4@@΂@)@;@@{@ @@ @~@}@z|@{@-y@'x@ɐv@t@*s@/]q@~o@m@k@l}i@]g@/e@ b@&`@N^@[@xY@V@sT@Q@XDO@QL@tI@V8G@yD@A@8>@<@=9@`6@3@N0@-@*@c'@$@"@@#@4@;G@k[@q@Q @ @@@@dt?y?CA?x?;??]i???#?p?Y?S?%^?/z???:?ß? ??B?k???w?=o?h?`?Y?R?K?D?d>?7?1?Щ+?%??M??y?ZG ?9?v>T>T>Y>?c>l>>~=>>>=>a>&_>B>/\>>>t>v>[+>>F>>\W>>>g>>>6t>.>->z?? ??|?H?#?r)?/?9#6?.>6t>>>g>>>\W>>F>>[+>v>t>>>>\7>>>D>@#>>>T>->>>y>> >'>P>?? ?"??2?!?'?-?,4?7:?A?G?N?U?~\?[Wd?k?ٖs?v{??ۅ? ?O?ש???F5?B?y?x?a?]?:m?E?? ?ua??C?? d? ?ؿ?.?:Q?!@D@@~ @i@@@@@@@o @#@O&@ *@z-@R00@A3@P6@6]9@ef<@k?@lB@lhE@^H@NK@7N@OQ@S@V@wY@=I\@^@a@GAd@f@Ti@k@2n@kp@r@nu@;w@Uy@H^{@&U}@9@텀@de@;@@Yȃ@@*,@΅@e@#@q@@Q@H@H@J@@̵@ى@@u@u@@ى@̵@@J@H@H@Q@@q@#@e@΅@*,@@Yȃ@@;@de@텀@@&U}@H^{@Uy@;w@nu@r@kp@2n@k@Ti@f@GAd@a@^@=I\@wY@V@S@OQ@7N@NK@^H@lhE@lB@k?@ef<@6]9@P6@A3@R00@z-@ *@O&@#@o @@@@@@@i@~ @@D@!@:Q?.?ؿ? ? d??C??ua? ??E?:m?]?a?x?y?B?F5???ש?O? ?ۅ??v{?ٖs?k?[Wd?~\?U?N?G?A?7:?,4?-?'?!?2??"? ???P>'> >>y>>>->T>>>@#>D>>>\7>>Kg>޾>P>a>%>`k>>> >>D>k>>>2>{? ?/?s?(3??%?Y+?A2?~8?; ??E?`L?S?Z?Cb?i?tq?my??܄??Z?.?-?4?W? ?2֨??t?}?bɼ??V9??4?l?b??;?J?ؿ?Η?|}?@@Ѽ@h @@@@@=@>_@!@S$@'@*@1.@C1@i4@7@:@=@@@D@G@#J@V,M@O.P@F)S@V@Y@[@^@2a@Ud@ g@$i@&Zl@n@rq@s@Pv@x@{z@D)}@O@@@@@@YZ@*@#@@{]@H@@P-@?@)@L@.@*L@,@ Ҍ@@'@@@WL@WL@@@'@@ Ҍ@,@*L@.@L@)@?@P-@@H@{]@@#@*@YZ@@@@@@@D)}@{z@x@Pv@s@rq@n@&Zl@$i@ g@Ud@2a@^@[@Y@V@F)S@O.P@V,M@#J@G@D@@@=@:@7@i4@C1@1.@*@'@S$@!@>_@=@@@@@h @Ѽ@@@|}?Η?ؿ?J?;??b?l?4??V9??bɼ?}?t??2֨? ?W?4?-?.?Z??܄??my?tq?i?Cb?Z?S?`L?E?; ??~8?A2?Y+?%??(3?s?/? ?{?2>>>k>D>> >>>`k>%>a>P>޾>Kg>Г>N>>>40>>tU>@J>J>>n>%>U>A>??) ?,?[ ??%#?)?/?R6?w?R?Ƀ?u?M??*?S? `???jӬ?Dϱ???F???\?b? ??.?\?x??.?|}?k@@`@ @@6@]@i@@@+"@S%@D(@+@ /@V:2@#t5@8@;@?@JB@yE@H@K@N@WR@U@&X@+[@h(^@ a@d@f@$i@l@?o@q@)t@&w@-y@"|@)~@o@D@@＃@zĄ@~…@@@@zV@X!@X@L@@@Tތ@q@#@Zs@@@@@%@W@k}@w@@@w@k}@W@%@@@E@@Zs@#@q@Tތ@@@L@X@X!@zV@@@@~…@@@@D@o@)~@"|@-y@&w@)t@q@?o@l@$i@f@d@ a@h(^@+[@&X@U@WR@N@K@H@yE@JB@?@;@8@#t5@V:2@ /@+@D(@S%@+"@@@i@]@6@@ @`@@k@|}?.??x?\?.?? ?b?\??F????Dϱ?jӬ??? `?S?*??M?u?Ƀ?R?h>w?Wo?4g? `?X?vQ?lJ?C?U>%>n>>J>@J>tU>>40>>>N>Г>A>Q>ZǤ>6>OD> >> >Q>D>>6>P>?? ?s???!?'?x-? 4?7:??@A?;H?"O?qVV?D]?>Ee?m?qt?|??ۆ?+?ő?T??N???ի?qٰ??!?f??],?ĭ?B???r?Q?CA?]A?:Q?@@<@% @:@i@W@@}@V@ś"@Y%@4-)@x,@/@3@`6@9@<@C@@ȋC@F@uJ@OM@P@ջS@ V@Z@.]@E`@rTc@Yf@Ti@El@"+o@r@t@w@Cz@|@3|@@;@"m@@綅@Ά@ۇ@߈@ى@JɊ@~@@X@@8֎@䃏@%@@CF@Wđ@.6@@@'A@@'@ړ@1@@@1@ړ@'@@@@@.6@Wđ@CF@@%@䃏@8֎@@X@@~@JɊ@ى@߈@@@@@"m@;@@3|@|@Cz@w@t@r@"+o@El@Ti@Yf@rTc@E`@.]@Z@ V@ջS@P@OM@uJ@F@ȋC@C@@<@9@`6@3@/@x,@4-)@Y%@ś"@V@}@@W@i@:@% @<@@@:Q?]A?CA?Q?r???B?ĭ?],??f?!??qٰ?ի???N??T?ő?+?ۆ??|?qt?m?>Ee?D]?qVV?"O?;H??@A?7:? 4?x-?'?!???s? ???P>6>>D>Q> >> >OD>6>ZǤ>Q>A>ù>c>ώ>zׯ>`>N,>W;>[>)> >M7>.>n>??)D?/?Dk?<?8%?_+?[1?.8?>?߮E?L?S?@[?b?Yj?pr?az?f???\?ܒ?t?#??sǥ??zƯ??C?l??@@v?,?1????y??!@@`@% @~F@@@@ @*Y@@"@}V&@R)@{-@lm0@3@m.7@W:@=@ OA@D@H@-`K@N@WR@PU@X@[@_@ZAb@je@(h@!k@n@q@Zt@w@)oz@4?}@@.Z@@ @7@p@@Lj@@k@O@@#@@@w@q_@@Β@9t@ @5@-@@@@@@\@>@X@e@e@X@>@\@@@@o@@-@5@ @9t@Β@@q_@w@@@#@@O@k@@Lj@@p@7@ @@.Z@@4?}@)oz@w@Zt@q@n@!k@(h@je@ZAb@_@[@X@PU@WR@N@-`K@H@D@ OA@=@W:@m.7@3@lm0@{-@R)@}V&@"@@*Y@ @@@@~F@% @`@@!@?y????1?,?v???H??l?C??zƯ??sǥ??#?t?ܒ?\???f?az?pr?Yj?b?@[?S?L?߮E?>?.8?[1?_+?8%?<?Dk?/?)D???n>.>M7> >)>[>W;>N,>`>zׯ>ώ>c>ù>|8>h+>]>Nг>=>}>n>?> >P!>>G.>8?ø?k ?z??o?"?O(?>/?5?W?dt?]@D@Ѽ@ @:@@:@Q'@ҁ@E@-E#@ &@\*@-@50@i4@U7@Q;@&>@:B@E@I@L@:O@0`S@V@u"Z@p{]@`@d@]g@Pj@m@p@&t@&w@.z@D)}@ @{@@.F@@#@:@1z@?@ދ@@@,@b2@-@@j@ړ@@i@o@Ȗ@e@@nz@@[@ȸ@@K@@?@Ě@wњ@wњ@Ě@?@@K@@ȸ@[@@nz@@e@Ȗ@o@i@@ړ@j@@-@b2@,@@@ދ@?@1z@:@#@@.F@@{@ @D)}@.z@&w@&t@p@m@Pj@]g@d@`@p{]@u"Z@V@0`S@:O@L@I@E@:B@&>@Q;@U7@i4@50@-@\*@ &@-E#@E@ҁ@Q'@:@@:@ @Ѽ@D@]@dt?>??{ ? ?0 ?^I??@A??S??쾳?떮????q?-?S??ѥ?R? ?w?o?g?4`?X?QQ?&J?2(C?W/?O(?"?o??z?k ?ø?8?G.>>P!> >?>n>}>=>Nг>]>h+>|8>g>ר>2>-з>>>~C>(>g>?>u> > v? ?"?5?v?_ ?t&?Y,?Z$3?9?i@?nG? N?U?}]?a1e?m?!)u?m}?m?oD?寋?3?=Д??QR?7?5?^K? y?h?<?E?9?ƻ?@@N$?`?(?~I?v}?C?@C@@h @@i@@@Q'@b@@o#@&@b*@-@b1@4@l8@D;@N|?@mC@F@uJ@M@OQ@kT@X@[@^@hb@%e@,i@l@"o@s@Pv@y@˥|@@de@@]@΅@[7@@@A@@ƍ@^@%@CF@4\@sg@g@\@zF@t$@@@>v@y#@Ě@W@ޛ@`X@Ĝ@$@u@ @@@M5@C@C@M5@@@ @u@$@Ĝ@`X@ޛ@W@Ě@y#@>v@@@t$@zF@\@g@sg@4\@CF@%@^@ƍ@@A@@@[7@΅@]@@de@@˥|@y@Pv@s@"o@l@,i@%e@hb@^@[@X@kT@OQ@M@uJ@F@mC@N|?@D;@l8@4@b1@-@b*@&@o#@@b@Q'@@@i@@h @@C@@C?v}?~I?(?`?N$?7A?s?ƻ?9?E?<?h? y?^K?5?7?QR??=Д?3?寋?oD?m?m}?!)u?m?a1e?}]?U? N?nG?i@?9?Z$3?Y,?t&?_ ?v?5?"? ? v? >u>?>g>(>~C>>>-з>2>ר>g> H>X>>ֻ>>#7>>a> >af>1>}&?\?ۻ ?E???#?*?}~0?7?=?D?K?f+S?Z?af> >a>>#7>>ֻ>>X> H>ר>@B> >>=>ʝ>i>>>>2>?ZG ?H?l?C??>!?j'?-?4L4?;?A?H?rBP?jW?u__?7g?DBo?~w??G??I5?qґ?%?dY?(C?`F?b?И??O?Kп?ji?? ????'?V,?|?Z?.@t@@C @i@@]@@*Y@E@o#@'@2*@`;.@1@܃5@-9@<@y@@~5D@!?C??l?H?ZG ??2>>>>i>ʝ>=>> >@B>ר>ul>>ֻ>>Z>C >F>'M>z>>Ӏ?F?5 ??)??$?*?s1?8?>?F?.@M?T?tK\? d?l?Ut?;|?m???3? ?S??#?Ǩ?@ R?н?C???Pi?Q?R?Ak? ??>??ڜ@I@C@ @v@@@i@}@@-E#@&@k*@`;.@11@S5@6]9@I=@@@D@^H@]"L@6O@~S@kW@+[@6^@sb@Yf@3 j@Fm@/]q@3t@x@"|@|@D@J@ @@Q@@4@h@@%@y@(@t@yѕ@t$@8m@w@ޚ@/@$@M5@:@3@M @E@XӢ@Q@Q@-@@p*@5@@^@ܧ@R%@_@k@@@@@@@k@_@R%@ܧ@^@@5@p*@@-@Q@Q@XӢ@E@M @3@:@M5@$@/@ޚ@w@8m@t$@yѕ@t@(@y@%@@h@4@@Q@@ @J@D@|@"|@x@3t@/]q@Fm@3 j@Yf@sb@6^@+[@kW@~S@6O@]"L@^H@D@@@I=@6]9@S5@11@`;.@k*@&@-E#@@}@i@@@v@ @C@I@ڜ@?>?? ?Ak?@@@??C?н? R??Ǩ?#??S? ?3???m?;|?Ut?l? d?tK\?T?.@M?F?>?8?s1?*?$??)??5 ?F?Ӏ?>z>'M>F>C >Z>>ֻ>>ul>4>A>> >ʝ>{>ߦ>O >>?9?P ?(???!?J(?.?k'5?(;?B?&J?@@`?@@my???g??!?5?>?=???L???V?;????"?@@o??V?B?K@@ @Q @@@@@V@"@ &@b*@1.@1@S5@Gm9@;=@ A@D@|H@L@sdP@f&@W@@\@9@@t@G-@3<@3<@G-@t@@9@\@@W@>&@š@ @9n@w@@8@\a@|@%@ތ@#@8k@aH@@@@@@[@o@@'@y@ @Zs@ Ҍ@)@1z@:ć@@.F@~@@}@mz@fv@r@n@'k@]g@c@_@[@X@f?5?!???g??my? q?%h?`?Y?9Q?&J?B?(;?k'5?.?J(?!???(?P ?9??>O >ߦ>{>ʝ> >>A>4>>=>>r%>\> >'M>Y>D>â?\?8s ????*%?+?A2?8?B??WF?KN?@@݀e?@@~?p?#?&?m?:?#?e'?`F??կ?E?к?v?7??f??Y>'M> >\>r%>>=>>A>rM>>~C>0>k>h>>?BE?W ?M?? ?,"?](?/?5?I_@+"@Y%@R)@-@b1@D5@-9@I=@ A@E@H@L@P@T@X@E\@`@d@h@l@p@t@x@˥|@/C@/@^@|@ۇ@̵@4@X@ @@@N@o@}@3@Ě@J@ǝ@:@ڢ@E@R@<@%ԥ@@R%@;@C@>?@G-@ @@J@?@C@;@R%@@%ԥ@<@R@@@:@ǝ@J@@@@o@N@@@ @X@4@̵@ۇ@|@^@/@/C@˥|@x@t@p@l@h@d@`@E\@X@T@P@L@H@E@ A@I=@-9@D5@b1@-@R)@Y%@+"@>_@@@k[@@4 @@`8@@?M'? ??;?p?B?[/?6?~X???a???Mb?D?B?`\?ő??1O?ց?z?pr?!j?b?$Z?tR?J?C?Ih>k>0>~C>>rM>A> >E>#>dd>~> >>>"??8s ?)?T?f!?c%?u+?y2?O9?dV@?G?N?ƠV?w^?f?n?h>w??i???\j?HM?hL?g?r?a?c??V?\?@@ٛ@K=@w՝@c@@b@ ң@e6@V@ܧ@@~R@z@ӕ@ͣ@J@ @{@gR@@Բ@~@@L@$@@)@ @@@@@`ζ@8޶@8޶@`ζ@@@@ @@)@@$@L@@~@Բ@@gR@{@ @J@ͣ@ӕ@z@~R@@ܧ@V@e6@ ң@b@@c@@@@@>@@@@%@XN@p@7@q@@zĄ@΂@Ӏ@}@-y@w?n?f?w^?ƠV?N?G?dV@?O9?y2?u+?c%?f!?T?)?8s ??"?>> >~>dd>#>E> >>>[>{>C>wh>T>2>?O ?4?? ?:"?(?R//?5?T>wh>C>{>[>>>/,>S>>>P!>>> =??5 ????U%?u+?h2?$o9?i@?G?dXO?vW?^?#g?|o?x?p??h?O? )??H3?Ed??Y?t?M???x?K ?B???Ւ?Q:??@?h@@̆ @X( @@@S@#@@#@'@+@/@3@U7@D;@@@~5D@^H@L@;P@T@N-Y@@h]@a@e@{j@D\n@r@v@9{@9@@Yȃ@م@@@.@#@@@@ړ@ĕ@@@W@$@@ڢ@T@@@_.@@@4@9@ @g@{@Q@*@>P!>>>S>/,>">J>u>{>6t>{k> >{?f/ ?4?ȹ??"?p(?/?%5?{k>6t>{>u>J>">+x>YQ>z>>7>>?!?ۻ ?z?|??$?+?K2?>9?g@?G?dXO?#W?m%_? `g?o?x?˳?D??꾎?ب?ذ? ם??~??ɟ?%^?:?!6?O?,??P???Y?]A?"@/@zO@ @ձ@Ov@;G@@$@ @"@&@ *@1.@V:2@`6@W:@&>@mC@@@@f&@ӫ@v@U@j@@k@@O@@۸@E @O0@D@J@$A@v(@>@E@X@G(@@G@@#@x@@@@#@#@@@@x@#@@G@@G(@X@E@>@v(@$A@J@D@O0@E @۸@@O@@k@@j@U@v@ӫ@>&@9n@5@@ @D.@aH@Z@Ke@h@e@\@M@9@ @@X@ @@h@;@ @t{@XQw@r@n@{j@=e@Va@E\@X@f@W:@`6@V:2@1.@ *@&@"@ @@$@;G@Ov@ձ@ @zO@/@"@]A?Y???P??,?O?!6?:?%^?ɟ??~?? ם?ذ?ب?꾎??D?˳?x?o? `g?m%_?#W?dXO?G?g@?>9?K2?+?$??|?z?ۻ ?!??>7>>z>YQ>+x>>>s>>>n>? ?G?Y+?C??!?,'?.?5?I>>s>>>>>k>g?>j>j?'g?k ?,?[??b$?*?1?8???\G?N?V?t^?7g?žo?x??[??k??M?6?ʌ??떮?LK?C??%?{X?k??̫?Z?w(?a?>?"@%@u@4 @+@O@@@@#@c'@j,@R00@i4@8@<@ OA@E@uJ@@@@[@l`@d@l}i@ n@r@&w@t{@!@@h@{@#@2@r@i@@@N@z@@Ě@@@d@ @z @@@ת@@ @M@# @@c@@@E @x@5@$A@@E@@X@#@#@@W@@V@X.@v@W@b@;@ @@@3@D@D@3@@@ @;@b@W@v@X.@V@@@@#@#@X@@E@@$A@5@x@E @@@c@@# @M@ @@ת@@@z @ @d@@@Ě@@z@N@@@i@r@2@#@{@@h@!@t{@&w@r@ n@l}i@d@l`@[@kW@jR@-N@uJ@E@ OA@<@8@i4@R00@j,@c'@#@@@@O@+@4 @u@%@"@>?a?w(?Z?̫??k?{X?%??C?LK?떮??ʌ?6?M??k??[??x?žo?7g?t^?V?N?\G???8?1?*?b$??[?,?k ?'g?j?j>g?>k>>>dd>a>2a>`>A>96?1?u?]?v? ?b?'?-?4?(;?JC?qJ?:R?+Z?b?>k?Ss?!|???<~?m?|?;??e?a??n?\?j??A?]U?>??]?~I?@T?|}?hb@@ @x@@Pn@g@l@@@*@ /@A3@7@;@C@@D@I@M@R@V@+[@_@Ud@h@m@.r@v@t{@ @\@{@@J@L@ߍ@%@h@@@H@`J@u@D@&@ ң@@@Q@@Э@{@揱@_@$@8޶@@-@»@J@0ž@,2@@@#@TV@y@@@@ i@;@@@N@]@^Z@@f@:g@*@'@(@(@'@*@:g@f@@^Z@]@N@@@@@@@@y@TV@#@@@,2@0ž@J@»@-@@8޶@$@_@揱@{@Э@@Q@@@ ң@&@D@u@`J@H@@@h@%@ߍ@L@J@@{@\@ @t{@v@.r@m@h@Ud@_@+[@V@R@M@I@D@C@@;@7@A3@ /@*@&@"@l@g@Pn@@x@ @@hb@|}?@T?~I?]??>?]U?A??j?\?n??a?e??;?|?m?<~???!|?Ss?>k?b?+Z?:R?qJ?JC?(;?4?-?b?'? ?v?]?u?1?96?A>`>2a>a>dd>P>>T>c>?zs? ??O??q#?*?0?7?X+??9F?KN?P1V?'Q^?f?DBo?x?\? 9?? ?? ?QR?R?v@(@@%@T@|@ŝ@@@Ȫ@Ѭ@Ѯ@XȰ@#@@qo@<@'@;@Z@@@@y@@5@l|@z@@@@@@ֳ@3y@C-@@`@@M@L@[@6(@L@_@_@L@6(@[@L@M@@`@@C-@3y@ֳ@]@@@@@z@l|@5@@y@@@@Z@;@'@<@qo@@#@XȰ@Ѯ@Ѭ@Ȫ@@@ŝ@|@T@%@@(@>v@1@@@aK@#@d@J@#@@;@@9{@Pv@q@l@:h@c@6^@DHZ@jU@OQ@L@H@ȋC@?@:@P6@1@-@v)@E%@!!@ @@@@4 @c @j@@-?g?w]?r?G??s? ?? ?G???T>>P> >eF>xC>P>}&??f ?#P?Dk?W?X;&?>,?3?;?]B?|I?Q?;Y?b?Yj?|Bs?:|??Xs?M?G? b???(t?/?Dϱ?}?뮽??y?w???i?Q?Y?.?/e@@q@2 @ @@@|@@#@@@N0@4@6]9@=@JB@F@-`K@:O@kT@ @Y@]@sb@]g@l@p@,?X;&?W?Dk?#P?f ??}&?P>xC>eF> >9>>.>հ>-H? ?Է?ȹ??W"?O(?\/?"6?>?E?.@M?.U?LW]?e?^n?h>w?A.?܄?A?ԙ?ب?ؘ?0)?? .??Ÿ??6??b??"?5D?'?V,?Q?N?@B@ @ @@2@4@@SG"@&@*@b/@3@D7@ef<@@@yE@uJ@N@0`S@X@\@2a@Yf@'k@o@t@-y@)~@@#@@H@r@ߍ@aK@@-@:@@K=@^@@66@~@w@ @G-@X@{@.@L@@@@@b@,2@@@TV@W@V@@p@@@@@@@@3@ԙ@e@@@]@@Q@@@C4@Z@m@m@Z@C4@@@Q@@]@@@e@ԙ@3@@@@@:g@$@@p@@V@W@TV@@@,2@b@@@@@L@.@{@X@G-@ @w@~@66@@^@K=@@:@-@@aK@ߍ@r@H@@#@@)~@-y@t@o@'k@Yf@2a@\@X@0`S@N@uJ@yE@@@ef<@D7@3@b/@*@&@SG"@@4@2@@ @ @B@@N?Q?V,?'?5D?"??b??6??Ÿ?? .??0)?ؘ?ب?ԙ?A?܄?A.?h>w?^n?e?LW]?.U?.@M?E?>?"6?\/?O(?W"??ȹ?Է? ?-H?հ>.>>9>(>2>>?'g? ??[ ?n?`$?Щ+?2?9?A?H?P?(X?`?ki?1r?D5{?e2>(>)]>6{>D>??~P?EP?f? ?'?T[.?>f5?f5?T[.?'? ?f?EP?~P???D>6{>)]>0>+>3>?P ???o?c#?*?R1?.8?ӎ??)G?N?vW?u__?g?p?Sy?X?1O?7?T@?Fk?4?e'??m?D?8??\????4? ??{ ?CA?՛?y @)@Ѽ@@ @A@@@B@X!@%@ *@w.@2@}7@<@@@lhE@#J@N@ջS@X@p{]@hb@]g@&Zl@/]q@fv@t{@/C@΂@YZ@@7u@@S@@@1@ȸ@K=@@;<@@p*@@@g@į@@h@@@ @J@j@X@͊@@l|@b@;@@@uu@|@m@*@@@Q@ޒ@@@@@Q@@h@@@?@ݵ@@g@@@@@@@g@@ݵ@?@@@h@@Q@@@@@ޒ@Q@@@*@m@|@uu@@@;@b@l|@@͊@X@j@J@ @@@h@@į@g@@@p*@@;<@@K=@ȸ@1@@@S@@7u@@YZ@΂@/C@t{@fv@/]q@&Zl@]g@hb@p{]@X@ջS@N@#J@lhE@@@<@}7@2@w.@ *@%@X!@B@@@A@@ @Ѽ@)@y @՛?CA?{ ?? ?4????\?8??D?m??e'?4?Fk?T@?7?1O?X?Sy?p?g?u__?vW?N?)G?ӎ??.8?R1?*?c#?o???P ??3>+>0>h>>P?{? ??R?<?%?c,?A3?M:?nB?&J?R?wJZ?_b?Hgk?Ut?}?y? S?M?\j?'?q ??5????4?? ??4o?W? d? ??Z^?@p@ @@@@A0@r@#@+&(@,@1@S5@>:@8>@C@^H@V,M@WR@ V@[@`@%e@Rj@o@3t@mz@9@/@zĄ@Z@@@ @@N@@>v@/@^@M @~@p*@@!@”@@g@ƴ@@Xl@;@@!@I@g@y@V@z@!h@~H@;@@@`=@Y@]@@=@@Z@@[1@A@7@@+@@@g}@@i@p @@@:@t9@M@M@t9@:@@@p @i@@g}@@@+@7@@A@[1@@Z@@=@@]@Y@`=@@@;@~H@!h@z@V@y@g@I@!@@;@Xl@@ƴ@g@@”@!@@p*@~@M @^@/@>v@@N@@ @@@Z@zĄ@/@9@mz@3t@o@Rj@%e@`@[@ V@WR@V,M@^H@C@8>@>:@S5@1@,@+&(@#@r@A0@@@@ @p@@Z^?? ? d?W?4o?? ??4????5??q ?'?\j?M? S?y?}?Ut?Hgk?_b?wJZ?R?&J?nB?M:?A3?c,?%?<?R?? ?{?P?>h>z>w>96?????!?E(?R//?R6?߯=?6HE?M?.U?}]?8 f?n?w???g?R? `?ԏ?N?W??׬?匰?琶??i?$v?K ???e?)? ??y @@@ @o@@4@v@!@F+&@2*@b/@s3@L8@<@A@zF@NK@O.P@U@Z@_@d@,i@Gn@4js@x@}@{@^@@zV@.@e@9@ړ@z@H@(@P@@|@ @@!@ͣ@, @.@N@m@̹@3$@r@@@#@H@b@p@ur@:g@N@6(@@"@]@@@N@Ut@Q@@S@z@I@J@t@\@V%@@?|@ @σ@}@:@!x@@]@]@@!x@:@}@σ@ @?|@@V%@\@t@J@I@z@S@@Q@Ut@N@@@]@"@@6(@N@:g@ur@p@b@H@#@@@r@3$@̹@m@N@.@, @ͣ@!@@ @|@@P@(@H@z@ړ@9@e@.@zV@@^@{@}@x@4js@Gn@,i@d@_@Z@U@O.P@NK@zF@A@<@L8@s3@b/@2*@F+&@!@v@4@@o@ @@@y @? ?)?e???K ?$v?i??琶?@@?W?N?ԏ? `?R??g??w?n?8 f?}]?.U?M?6HE?߯=?R6?R//?E(?!?????96?w>z>OV>w>?@@c?RO?#?*?[1?8?g@?;H?W P?g;X?i`?SWi?Fr?v{?t?(P?M?m?K?F?ß?M?Y??-?l?$?{X???9?\?V,??D?l@@ @@l@6%@f@@$@D(@{-@-1@@6@k:@?@yD@;RI@7N@F)S@&X@.]@ZAb@]g@l@q@Lv@"|@@]V@|@q@M@#@@M@o@@`J@@@66@%ԥ@9n@@”@, @@$@@E @u@վ@,@y@@@"@D@^Z@fc@W_@M@.@@@v@v@.@[1@@@S@J@e@@@8@v@!x@0@@c@I@kF@ @@@6@6@@@ @kF@I@c@@0@!x@v@8@@@e@J@S@@@[1@.@v@v@@@.@M@W_@fc@^Z@D@"@@@y@,@վ@u@E @@$@@, @”@@9n@%ԥ@66@@@`J@@o@M@@#@M@q@|@]V@@"|@Lv@q@l@]g@ZAb@.]@&X@F)S@7N@;RI@yD@?@k:@@6@-1@{-@D(@$@@f@6%@l@@ @@l@D??V,?\?9???{X?$?l?-?@@M?ß?F?K?m?M?(P?t?v{?Fr?SWi?i`?g;X?W P?;H?g@?8?[1?*?#?RO?c??i ??w>OV>P>P?,?@@T??,&?9-?,4?L;?JC?J?R?@[?c?l?u?~?G?-4?rC?u?P˘?D??y???bĻ?j??n3??>?`?(?ރ??@@@q @@@A@@ !@d&@+*@y/@4@8@=@[B@V8G@]"L@OQ@V@+[@E`@je@Pj@"o@nu@wYz@|@~@*,@ۇ@7@@@@]@\@@Ě@u@%@XӢ@~@R%@Ȫ@g@@.@$@@-@Ȧ@@X@@5@V@@@f@<@L@O@$E@6,@@@@[1@@MS@@0@@v@@5@@@@i@|@#@@*2@@@@@@ll@lW@q-@@@*2@@#@|@i@@@@5@@v@@0@@MS@@[1@@@@6,@$E@O@L@<@f@@@V@5@@X@@Ȧ@-@@$@.@@g@Ȫ@R%@~@XӢ@%@u@Ě@@\@]@@@@7@ۇ@*,@~@|@wYz@nu@"o@Pj@je@E`@+[@V@OQ@]"L@V8G@[B@=@8@4@y/@+*@d&@ !@@A@@@q @@@@?ރ?(?`?>??n3??j?bĻ?@@y??D?P˘?u?rC?-4?G?~?u?l?c?@[?R?J?JC?@,4?9-?,&??T?? ?,?P?P> >#? ?D??_$?!?p(?l/?6?>?E?M?U?=^?f?o?y?9???3?9x?q?l??a???S??O?f?.???w]? ?`l?!@@ @x@>@ @X@@ ($@|(@|;-@1@6@Q;@~"@@E@tI@N@S@Y@h(^@rTc@(h@m@s@hx@}@D@.F@@̵@p@,@@@@e@y#@@D@T@z @w@p@@į@g@N@@-@!@9@@#@@@;@B@'@@@.@$8@C4@!@@Q@@?@@|l@@S@v@@&@kF@cS@L@*2@~@~@h@@{@@:@@@@I@@sz@:@@{@@h@~@~@*2@L@cS@kF@&@@v@S@@|l@@?@@Q@@!@C4@$8@.@@@'@B@;@@@#@@9@!@-@@N@g@į@@p@w@z @T@D@@y#@e@@@@,@p@@@@D@}@hx@s@m@(h@rTc@h(^@Y@S@N@tI@E@~"@@Q;@6@1@|;-@|(@ ($@@X@ @>@x@ @@!@`l? ?w]???.?f?O??S???a??l?q?9x?3???9?y?o?f?=^?U?M?E?>?6?l/?p(?!?_$??D? ?#? >v>?P ??,?4?#?*?1?9?@?`H?fP?X?1a?Gi?Js?P|?m? ݇??R?t?=??R?@??f ?w?ؾ?<?e%?C,? 4?t;?JC?J?S?y[? d?m?(v??R?T?꾎??~j?B?'??}???Y?x?ĭ??!?M?w(??O?@@ @h6@i@@@r@F#@}(@z-@_1@6@a;@C@@#5E@|5J@XDO@0aT@wY@^@d@@@&t@y@~@;@ @:ć@7@X@%@@ĕ@ܔ@Ke@M5@d@ ң@ŝ@g@G-@@@h@@̹@u@@@E@@8Q@@6@@[@`=@}@@@@@@V@@@?@}@@@|@@q-@h@@@@j@Eg@C)@3@m@7@]@0@@R!@+7@+7@R!@@0@]@7@m@3@C)@Eg@j@@@@h@q-@@|@@@}@?@@@V@@@@@@}@`=@[@@6@@8Q@@E@@@u@̹@@h@@@G-@g@ŝ@ ң@d@M5@Ke@ܔ@ĕ@@%@@@@ @;@~@y@&t@n@Ti@d@^@wY@0aT@XDO@|5J@#5E@C@@a;@6@_1@z-@}(@F#@r@@@i@h6@ @@@O??w(?M?!??ĭ?x?Y???}??'?B?~j??꾎?T?R??(v?m? d?y[?S?J?JC?t;? 4?C,?e%?<?ؾ?w?f ???Ӏ?<?+?EP??>!? (?/?R6?=?E?\M?U?=^?f?o?By?f?1O?G[?e?ߕ?dY??T??ﶲ??K?$?{?N?^I?Ak??%?ҽ?|}?/@&@ @+@A@@ @t!@&@2*@K/@ 4@8@g=@B@MG@L@Q@LW@=I\@2a@f@@@&w@˥|@@1߃@@1z@*L@ @@Δ@@@Z@3@ @@@@}@X@V$@@@Xl@3$@վ@X@#@@8Q@@^Z@@:@ԙ@B@C4@Pn@@|@@@e@#@~o@0@I@|@b@n@@:@0z@ޥ@k@@@@M@#@@@@'@o"@N@d@d@N@o"@'@@@@#@M@@@@k@ޥ@0z@:@@n@b@|@I@0@~o@#@e@@@|@@Pn@C4@B@ԙ@:@@^Z@@8Q@@#@X@վ@3$@Xl@@@V$@X@}@@@@ @3@Z@@@Δ@@ @*L@1z@@1߃@@˥|@&w@q@El@f@2a@=I\@LW@Q@L@MG@B@g=@8@ 4@K/@2*@&@t!@ @@A@+@ @&@/@|}?ҽ?%??Ak?^I?N?{?$?K??ﶲ??T??dY?ߕ?e?G[?1O?f?By?o?f?=^?U?\M?E?=?R6?/? (?>!??EP?+?<?Ӏ?]? ??!??8#?*?\61?8?l$@?G?W P?`X?R`?i?=r?P|????P?K?@?5?Ǩ?RĮ??12?գ?<@@@@Q@@@d@ AXAARAA!A7A CA CA7A!AARAAXA Ad@@@Q@@@@><@@sz@@ll@@6@0O@!x@{@@J@z@vU@"@@ޒ@$8@`@_@@^Z@@X.@@@,@r@;@@z @f5?@0@$@@ @E@@@Ѯ@@L@ӌ@n@J@!@@@V@;@4@@:@`@]@@S@@@g@i@@@@6@b@@S@0z@&@@>G@j@@d@MA|AdAJAQAǶAAaAtAAC A.AEAPAPAEA.AC AAtAaAAǶAQAJAdA|AMAd@@j@>G@@&@0z@S@@b@6@@@@i@g@@@S@@]@`@:@@4@;@V@@@!@J@n@ӌ@L@@Ѯ@@@E@ @@$@0@>@N@q_@Zs@4@q@~…@@ @)oz@t@?o@$i@GAd@^@xY@*T@N@I@D@?@W:@S5@;0@j,@1L'@ܩ"@@@6@o@ @u@]@Z@y??Ւ?.????7?v?-?i?rĬ?ʦ??K?ƕ?e?+??~#?x?Vo? Hf?}]?T?L?D?f5?.?'?C ?ȭ?#P?) ?f9?1???g?"?O(?0?o7?; ??F?N? [W?~_?%h?$r?v{?ʖ??&??t?q ?Ƣ?U?.??jB?f?p?cE?B?]i?5?e2???@Z@' @h6@@@X@E@}$@4-)@-@2@7@@@@K@=Q@V@[@Va@f@&Zl@q@w@4?}@{@]@C@P-@h@ @j@o@@(@@5@@ܧ@ת@Э@XȰ@@@@@j@I@#@@@B@M?@[@ԙ@$8@@S@Q@7@@@f@?@!x@}@'@@e@@z@>@7@@@@&zA!AAQAAUAA.AXAAAYAAAAiAiAAAAYAAAXA.AAUAAQAA!A&zA@@@7@>@z@@e@@'@}@!x@?@f@@7@@Q@S@@$8@ԙ@[@M?@B@@@#@I@j@@@@@XȰ@Э@ת@ܧ@@5@@(@@o@j@ @h@P-@C@]@{@4?}@w@q@&Zl@f@Va@[@V@=Q@K@F@A@<@7@2@-@4-)@}$@E@X@@@h6@' @Z@@??e2?5?]i?B?cE?p?f?jB??.?U?Ƣ?q ?t??&??ʖ?v{?$r?%h?~_? [W?N?F?; ??o7?0?O(?"?g???1?_; ?M???#?I*?f1?$o9?A?I??Q?]Y?jb?Hgk?Щt?3~???rC? ??4???1??jL???,???6??|?Z^?4@zO@~ @@j@i@ @!@H&@+@/@ݷ4@9@@@@7N@ӄS@X@N^@c@Ti@n@)t@Cz@@@΅@ @~@@y@5@}@ٛ@͞@ڢ@~@5@x@@{@#@&@@@@X@g@H@"@@'@σ@`=@B@ޒ@-@@7@@@p @?|@@@7@lW@f@d@Q@,@@@N@oA,AJAA8(AEAEAA 7AAA+MAAgA'AAA6AeBAeBA6AAA'AgAA+MAAA 7AAEAEA8(AAJA,AoAN@@@,@Q@d@f@lW@7@@@?|@p @@7@@@-@ޒ@@@@'@@"@H@g@X@@@@&@#@{@@x@5@~@ڢ@͞@ٛ@}@5@y@@~@ @΅@@@Cz@)t@n@Ti@c@N^@X@ӄS@7N@H@C@>@9@ݷ4@/@+@H&@!@ @i@j@@~ @zO@4@Z^?|??6???,???jL??1???4?? ?rC???3~?Щt?Hgk?jb?]Y??Q?I?A?$o9?f1?I*?#???M?_; ? ?,?-??ގ%?n,?3?c;?2(C?c-K?tS?([?-d?m?h>w?p??g??Ï?*?4?l?H?L? y?͸?K?n????.??~I?/?@*@Ѽ@u @F@N@@$@@SS#@ (@,@1@Ο6@;@@@JE@K@sdP@U@+[@&`@1f@k@rq@&w@|@.Z@.F@[7@P-@'@%@'@r,@3@K=@aH@T@\a@9n@z@ @揱@@@@@0@͊@y@b@D@f@@3@}@C4@@͂@@@p @{@@kF@5@~@@s@@7@Q@@R,AAAA@AXAAAG*AAAeAȷAhA^9AhAAAAAAAhA^9AhAȷAeAAAG*AAAXAA>AAAAR,A@Q@7@@s@@~@5@kF@@{@p @@@͂@@@@@@f@D@b@y@͊@0@@@@@揱@ @z@9n@\a@T@aH@K=@3@r,@'@%@'@P-@[7@.F@.Z@|@&w@rq@k@1f@&`@+[@U@sdP@K@JE@@@;@Ο6@1@,@ (@SS#@@@$@N@F@u @Ѽ@*@@/?~I??.????n?K?͸? y?L?H?l?4?*?Ï???g?p?h>w?m?-d?([?tS?c-K?2(C?c;?3?n,?ގ%??-?,? ? ?#P??_ ?b?'?T[.?5?]M=? &E?.@M? U?=^?#g?XPp?Sy??Æ?v?#;?K?hL??T??LK??F??????}?{ ?ؿ??X@@ " @g@@O2@@=P @$@)@ .@3@|8@=@B@&@:@M@_@qo@i|@@@P@@V@p@^Z@<@@@@Pn@"@@g@f@?|@@[@@@:@e@@@@d@A+{AQAAAԕABAA{AALjAhAhAJAW Aa A@ A A A A A A A A A@ Aa AW AJAhAhALjAA{AABAԕAAAQA+{AAd@@@@e@:@@@[@@?|@f@g@@"@@@@@<@^Z@p@V@@P@@@i|@qo@_@M@:@>&@i@@@w՝@Ě@Ĵ@@y@e@L@@@@3|@-y@s@2n@(h@ b@@h]@XW@ބR@V,M@9?Q@?H??Q?;Y?b?k?t?ȡ~?G?c?0?T??W?8?@?r?Tη?S???4??Ak?'?y?L?C@]@u@ @-@W@@$@h@o#@4(@@@@<@M>A@zF@K@m+Q@V@#\@Ka@]g@m@r@x@)~@;@7@:@A@XN@q_@t@[@?@ǝ@@ @_.@~R@v@j@@8޶@'@U@,2@G@qW@b@!h@:g@W_@O@$8@@@|@z@0@@!x@@5@@/e@T@@+7@[@m7A7A&/AAAAApA*AABAW A- A, A A AUq A A AvK A| A A A8 A8 A A A| AvK A A AUq A A A, A- AW ABAA*ApAAAAA&/A7Am7A[@+7@@T@/e@@5@@!x@@0@z@|@@@$8@O@W_@:g@!h@b@qW@G@,2@U@'@8޶@@j@v@~R@_.@ @@ǝ@?@[@@q_@XN@A@:@7@;@)~@x@r@@@Ka@#\@V@m+Q@K@zF@M>A@<@6@1@{-@4(@o#@h@@$@W@-@ @u@]@C@L?y?'?Ak??4???S?Tη?r?@?8?W??T?0?c?G?ȡ~?t?k?b?;Y??Q?H?Q@?>9?1?[*?q#??.?4?I/??)?$? ,?{b3?M:?B?qJ?f+S?[?d?Dm?h>w?|?_~??k?Fk??>Π?T?jӬ??G~???ƻ???|???E?Aq@֔@\ @@@@|@w4 @$@)@@@@=@mC@AMH@M@S@X@h(^@c@l}i@?o@nu@{z@o@"m@p@1z@@Ĝ@@yѕ@@@:@b@^@@@@U@p9@c@@;@վ@@@)@;@~H@N@M@$E@C4@v@@@J@M@@}@7@~@:@ޥ@@M@@XAdAgAaAPA 7A AAAhAW A A\ A AUq AY AW A Ay AW A( AB A AAAAA AB A( AW Ay A AW AY AUq A A\ A AW AhAAA A 7APAaAgAdAXA@M@@ޥ@:@~@7@}@@M@J@@@v@C4@$E@M@N@~H@;@@@@վ@;@@c@p9@U@@@@^@b@:@@@yѕ@@Ĝ@@1z@p@"m@o@{z@nu@?o@l}i@c@h(^@X@S@M@AMH@mC@=@8@3@+.@)@$@w4 @|@@@@\ @֔@Aq@E???|???ƻ???G~??jӬ?T?>Π??Fk?k??_~?|?h>w?Dm?d?[?f+S?qJ?B?M:?{b3? ,?$?)??I/?w??ُ?t&?`-?[4?I?&F?{]N?V?_?h?-q?b{??@@@>???y?@@?j?H?P?M??r?V,?V?%?/@7@4 @1@@@C@"@'@,@1@v6@;@A@iF@K@=Q@V@S\\@b@g@m@4js@Uy@O@@綅@Lj@@@@B@8m@/@]̞@E@e6@9n@9@@@S@@»@@G(@TV@V@@@@@@@@@V@e@{@X@6@@f@s@@@[@XA+{AєAtAЬAAALjAhA= A A Aj} A' A8 AW A AYA!A;,A+AA2 A'>AcA|A6A6A|AcA'>A2 AA+A;,A!AYA AW A8 A' Aj} A A A= AhALjAAAЬAtAєA+{AXA[@@@s@f@@6@X@{@e@V@@@@@@@@@@TV@G(@@»@@S@@@9@9n@e6@E@]̞@/@8m@B@@^@ދ@Lj@綅@@O@Uy@4js@m@g@b@S\\@V@=Q@K@iF@A@;@v6@1@,@'@"@C@@@1@4 @7@/@%?V?V,?r??M?P?H?j??2?կ?y???>? w??[ч??b{?-q?h?_?V?{]N?&F?3>?6?/?'? ?(3?b??u?:"?=)?}~0?7???G?W P?(X?cla?Yj?Ss?}?Ƀ?@@@B? ???D?}?C??\??^I?n?&V??/?ڜ@%@ @LY @@;G@@>@R$@4-)@1.@"3@=8@Fl=@B@H@}sM@jR@7X@h(^@{c@i@~o@kfu@H^{@@＃@Ά@@@@M@z@@@@R@V@ͩ@ @M@k@`ζ@E @J@@@W@"@N@uu@@"@@@Q@@@#@!x@kF@b@e@d@@@@m7AdAAtAOAAAȷAAi A\ A( AY A AK A A~A A+A>A(WAͮAA8AOkA A\AAA\A AOkA8AAͮA(WA>A+A A~A AK A AY A( A\ Ai AAȷAAAOAtAAdAm7A@@@d@e@b@kF@!x@#@@@Q@@@"@@uu@N@"@W@@@J@E @`ζ@k@M@ @ͩ@V@R@@@w@z@M@%@@@Ά@＃@@H^{@kfu@~o@i@{c@h(^@7X@jR@}sM@H@B@Fl=@=8@"3@1.@4-)@R$@>@@;G@@LY @ @%@ڜ@/??&V?n?^I??\??C?}?D??? ?B?ب?7??Ƀ?}?Ss?Yj?cla?(X?W P?G???7?}~0?=)?:"?u????q#?"*?1?$o9??@A?BTI?Q?wJZ?Z/c?\l?Ju??Rф??S?=Д?@~5D@ I@O@kT@\5Z@_@Ve@Pyk@/]q@XQw@&U}@@zĄ@ۇ@k@@CF@t@@@@.X@<@ܧ@!@g@@@<@x@0ž@@@9@4@y/@*@%@o @}@s@@t@ @@%@}??(?|? ??S????t?[?:?(C?_@(#@ (@},@ 2@m.7@ef<@A@G@L@R@?W@@h]@-c@+i@n@t@{z@텀@@@ى@@b2@sg@@@$@8k@@@~R@ͣ@Q@{I@@{@$A@@@)@p@ֳ@@*@]@@.@@@@}@I@@G@0z@>@@@AJAAPA[|AAȷAJA A A A A| AMAnAA|AAABA A3AәAsAp@AA8AAAAAAA8AAp@A@@@ ABAAA|AAnAMA| A A A A AJAȷAA[|APAAJAA@@>@0z@G@@I@}@@@@.@@]@*@@ֳ@p@)@@@$A@{@@{I@Q@ͣ@~R@@@8k@$@@@sg@b2@@ى@@@텀@{z@t@n@+i@-c@@h]@?W@R@L@G@A@ef<@m.7@ 2@},@ (@(#@>_@<@@@H @@@??t??7???$v?E?Ի?E??U??㸜??m??Æ??my?o?f?}]?iT?GL?zD? '?aɝ?R?ϩ???<??l?4?7A?? d?Q:?>?8@>i@@ @@/@m@r@D$@4-)@H,.@A3@l8@=@mC@oH@=M@ӄS@N-Y@6^@d@Pj@kp@ɐv@˥|@de@@@JɊ@#@-@g@@N@M5@#@QҤ@@@@*@@۸@4@@@5@@@;@_@@@N@[1@MS@|l@?|@@|@ll@O@&@7@@R,A+{AAA 7ArdALjAA A A A֬ A( ArA EA2 AAwAAVAj@A6A3AuAA4BAAŶAAAAAAAŶAA4BA@@@6Aj@AVAAwAA2 A EArA( A֬ A A A AALjArdA 7AAA+{AR,A@7@&@O@ll@|@@?|@|l@MS@[1@N@@@_@;@@@5@@@4@۸@@*@Ѯ@z@R%@QҤ@#@M5@N@@g@-@#@JɊ@@@de@˥|@ɐv@kp@Pj@d@6^@N-Y@ӄS@=M@oH@mC@=@l8@A3@H,.@4-)@D$@r@m@/@@ @@>i@8@>?Q:? d??7A?4?l??<???ϩ?R?aɝ?>?\j?*??z?{?tq?h?^?P1V?M?hjE?.n=?5? =.?u'?u ?P?M?!?J(?\/?6?>?pF?N? W? o`?i?Js?;|?c?%??)\?M?͞?Ť??x5?}?S? %?d#?N??.?? ??y @C@ @ @Ov@ @@y @S%@D*@K/@i4@9@8>@FD@I@XDO@@@@1f@l@r@'x@ G~@;@YZ@@~@@@\@@(@:@ތ@@@@@@9@i4@K/@D*@S%@y @@ @Ov@ @ @C@y @? ??.??N?d#? %?S?}?x5??Ť?͞?M?)\??%?c?;|?Js?i? o`? W?N?pF?>?6?\/?J(?!?M?C??"?? )?3o0?7?B???G?rBP?EX? a?dk?ot?I~?0?c?꾎?B??aƟ?sǥ?a?J?͸?D}?pY?b?}? ??Q?CA?_?X@b@i @@k[@O@@t!@}V&@N+@$^0@܃5@ۿ:@@@yE@J@P@@@@g@m@fs@-y@@@*@zV@@@j@zF@ؐ@@3@%@@@@@h@{̷@@@@TV@z@@:g@@@Q@@Q@@0@S@qm@|@n@sz@Eg@>G@@oAAAgAAAA= A\ AUq A| A| ArA]A'>A8AAA,MAsAAmA֜AAyA4A#A9eAA&AuAAAuA&AA9eA#A4AyAA֜AmAAsA,MAAA8A'>A]ArA| A| AUq A\ A= AAAAgAAAoA@>G@Eg@sz@n@|@qm@S@0@@Q@@Q@@@:g@@z@TV@@@O0@{̷@h@@ͣ@C@@%@3@@ؐ@zF@j@@@zV@*@@@-y@fs@m@g@Ka@[@)/V@P@J@yE@@@ۿ:@܃5@$^0@N+@}V&@t!@@O@k[@@i @b@X@_?CA?Q?? ?}?b?pY?D}?͸?J?a?sǥ?aƟ??B?꾎?c?0?I~?ot?dk? a?EX?rBP??G?B??7?3o0?? )?"?C??$?&#?*?s1?9?@?I?vQ?$Z?c?\l?u?6??.?ő??Ӛ?c?T?`? R?޹? ?m~???C??N???!@p@`6 @@5@@@tc"@1L'@K,@b1@6@;@-A@:F@]"L@Q@@@@h@n@3t@{@Z@Yȃ@@@X@w@ړ@t$@s@ǝ@M @|@ܧ@>?@J@# @9s@۸@@@@y@@=@@@$E@ޒ@Z@@S@@v@@@@@3@j@@,AAA~+ApAAA A( AO? AK AMA EA1A8AAVA{sA&AAiAAyAYAXAAADA@@ŻAAAŻAPAyADAAAXAYAyAAiAA&A{sAVAA8A1A EAMAK AO? A( A AAApA~+AAA,A@j@3@@@@@v@@S@@Z@ޒ@$E@@@=@@y@X@#@D@۸@9s@# @J@>?@ܧ@|@M @ǝ@s@t$@ړ@w@X@X!@#@Yȃ@Z@{@3t@n@h@c@.]@kW@Q@]"L@:F@-A@;@6@b1@K,@1L'@tc"@@@5@@`6 @p@!@??N??C???m~? ?޹? R?`?T?c?Ӛ??ő?.??6?u?\l?c?$Z?vQ?I?@?9?s1?*?&#?$??#?+?zj2?:?A?&J?:R?S[?[Wd?m?h>w?\???UY??;?‘???LK?*?գ?????v??J??J2?K@@ @q@@<@l@-E#@4(@|;-@:Y2@7@<@:B@MG@>M@$R@X@.b^@GAd@3j@9p@Pv@z|@.Z@@@@@q_@@@_J@@E@\a@Ũ@G-@ @@qo@ܹ@@@@@@^Z@@o@^p@@@S@J@v@@6@q-@:@><@y1@@&zAJA>AԕAA*AhA@ A AY AA AAnA2 AAAVABAp@AA֜A8A#AJA&Az*AA?AA@@AaAaAAyuAMAA?AAz*A&AJA#A8A֜AAp@ABAVAAA2 AnAAA AY A A@ AhA*AAԕA>AJA&zA@y1@><@:@q-@6@@v@J@S@@@^p@o@@^Z@@@#@@J@ܹ@qo@@ @G-@Ũ@\a@E@@_J@@@q_@@X@@@.Z@z|@Pv@9p@3j@GAd@.b^@X@$R@>M@MG@:B@<@7@:Y2@|;-@4(@-E#@l@<@@q@ @@K@J2??J??v?????գ?*?LK???‘?;??UY???\?h>w?m?[Wd?S[?:R?&J?A?:?zj2?+?#??,?@$?Y+?R3?;?B?c-K?S?q\?݀e?n?x?9?Z?̣?h?K? u?Ed?~?@@Ի?!??ڿ??l?J?V,?*=?|}?@F@@ @-@@@vt@a;@$@)@1.@A3@|8@=@$7C@|H@IN@S@-Y@_@je@dk@rq@w@}@@*,@@@8֎@@i@@@q@XӢ@8@š@ @{@@$]@Ϻ@$A@@#@@@:g@@.@_@@[1@z@e@@&@L@h@0z@@x@d@!AAABAAAW AP Aj} A A A!AAAAA{sAp@AAŶA_AmAAAAAMAaAAXAj=A'XAeAeA'XAj=AXAAaAMAAAAAmA_AŶAAp@A{sAAAAA!A A Aj} AP AW AAABAAA!Ad@x@@0z@h@L@&@@e@z@[1@@_@.@@:g@@@#@@$A@Ϻ@$]@@{@ @š@8@XӢ@q@@@i@@8֎@L@{]@*,@@}@w@rq@dk@je@_@-Y@S@IN@|H@$7C@=@|8@A3@1.@)@$@a;@vt@@@-@@ @F@@|}?*=?V,?J?l??ڿ??!?Ի?46?RĮ?~?Ed? u?K?h?̣?Z?9?x?n?݀e?q\?S?c-K?B?;?R3?Y+?@$?,??%?Y,?,4?;?C?k$L?T?}]?f?o?y?ց?0?M?ő?g?H3?)?aK?@@?Č?-???G? d?#O?i?Z@*@<@LY @X@Y{@A0@@m$@s)@.@4@6]9@>@$D@I@XDO@T@۹Z@`@f@l@r@x@~@ʠ@΅@H@@@䃏@Β@o@>v@zҜ@3@Q@@p@@gR@ƴ@<@;@v(@,@@@@fc@@~2@ޒ@@A@I@@5@kF@p@@ޥ@@@MAA8(AXAA6ABA A A' AK AKfAvA|AwA&hA,MA&AAŶAlAAADAAS@AAA'XAAAAA@!A@!AAAAA'XAAAS@AADAAAlAŶAA&A,MA&hAwA|AvAKfAK A' A A ABA6AAXA8(AAMA@@ޥ@@p@kF@5@@I@A@@ޒ@~2@@fc@@@@,@v(@;@<@ƴ@gR@@p@@Q@3@zҜ@>v@o@Β@䃏@@@H@΅@ʠ@~@x@r@l@f@`@۹Z@T@XDO@I@$D@>@6]9@4@.@s)@m$@@A0@Y{@X@LY @<@*@Z@i?#O? d?G???-?Č???И?aK?)?H3?g?ő?M?0?ց?y?o?f?}]?T?k$L?C?;?,4?Y,?%??<?X;&?Ny-?[4?@y@W@ i@]@N@3@i%@@@7@@J@@@cS@n@@k@@@|AQAEAA{AOAW A\ A A8 A A AAAAj AsAA֜A_AA&A@_AAyuAQA'XAߵAaAIArAAA]A]AAArAIAaAߵA'XAQAyuAA@_A&AA_A֜AAsAj AAAA A A8 A A\ AW AOA{AAEAQA|A@@k@@@cS@@@J@7@@@@i%@3@N@]@ i@W@y@>@@ @@@J@h0@w@Q@@@y#@Ȗ@9t@%@Tތ@@e@?4@ @ty@s@m@Ѕg@2a@°[@U@O.P@(J@E@?@t.:@4@]/@2*@%@ @o@6%@@ @̆ @,@@.?f^?_j???k?r?i???_?{ ???j?\j???i?z? q?4g?w^? U? M?D??AIF? N?cHW?4`?ki?=r?;|?tn?ѥ??D?B? ?)?^?ܿ?M?E ?n? ?O??Ji?R=?CA?Tu?@A7@ @@@S@B@ !@&@+@1@P6@;@ A@F@]"L@Q@W@@h]@rTc@Ti@Tio@u@D{@ @:@q@?@#@CF@@@W@@f*@@ @@@~@@=~@@@X@@V@@3y@[@e@@@@@@\@v@@*2@f@j@@@cAJAUAAG*ALjAA, AUq A֬ A A A*%A8ABAj@A3AmAA#AADAAA"AxA@!AA_A<A?AAGAxAAAxAGAA?A<A_AA@!AxA"AAADAA#AAmA3Aj@ABA8A*%A A A֬ AUq A, AALjAG*AAUAJAcA@@j@f@*2@@v@\@@@@@@e@[@3y@@V@@X@@@=~@@~@@@ @@f*@@W@@5@CF@#@?@q@:@ @D{@u@Tio@@@@W@Q@]"L@F@ A@;@P6@1@+@&@ !@B@S@@@ @A7@@Tu?CA?R=?Ji??O? ?n?E ?M?ܿ?^?)? ?B?D??ѥ?tn?;|?=r?ki?4`?cHW? N?AIF?3>?db6?X.?'?{ ?!?J(?l/?7?>?WF?dXO?:X?R`? 6j?s?}??i?!?T?Ǚ???a? Z???:?ƻ???.?{ ?a?O?]@@5 @ @@(@@@"@w'@,@1@6@E<@A@V8G@L@ބR@KX@h(^@d@{j@9p@fv@˥|@{@{@@)@Zs@Wđ@@@ޛ@aH@#@p*@š@@j@@@ @%@G(@@X.@@C-@m@@ޒ@@h@@V%@!x@i@~@:@Eg@@@RAQAA 7AAhAU A AY A& AYA+ADAA A6A8A֜AyAJAAAyuAXAxA.AAArAAA>AlgAA[A[AAlgA>AAArAAA.AxAXAyuAAAJAyA֜A8A6A AADA+AYA& AY A AU AhAA 7AAQARA@@Eg@:@~@i@!x@V%@@h@@ޒ@@m@C-@@X.@@G(@%@ @@@j@@š@p*@#@aH@ޛ@nz@-@Wđ@Zs@)@@{@{@˥|@fv@9p@@@@KX@ބR@L@V8G@A@E<@6@1@,@w'@"@@@@(@ @5 @@]@O?a?{ ?.???ƻ?:??? Z?a???Ǚ?T?!?i??}?s? 6j?R`?:X?dXO?WF?>?7?l/?J(?!?!?(?/?7?m??G?QO?X?a?j?ot?_~?G?}?k????e'?:?y?i?G~?D?V9?q\?}?/?????k@@~ @+@@%O@@"@|'@{-@V:2@}7@<@JB@G@}sM@F)S@X@^@d@Rj@p@&w@k}@@@Q@L@@.6@@@`X@ğ@66@5@>&@ͣ@V$@L@ ,@;@9@@CF@v@N@@M@@=@.@@g}@@0@|@~@0@C)@M@d@7AǶA.AAAhA A AW A( A!A>A8A(A3A3AY(AAYA&AAS@AQAA@!AAr!AύAA>AAUAYAAh Ah AAYAUAA>AAύAr!AA@!AAQAS@AA&AYAAY(A3A3A(A8A>A!A( AW A A AhAAA.AǶA7Ad@M@C)@0@~@|@0@@g}@@.@=@@M@@N@v@CF@@9@;@ ,@L@V$@ͣ@>&@5@66@ğ@`X@@@.6@@L@Q@@@k}@&w@p@Rj@d@^@X@F)S@}sM@G@JB@<@}7@V:2@{-@|'@"@@%O@@+@~ @@k@????/?}?q\?V9?D?G~?i?y?:?e'????k?}?G?_~?ot?j?a?X?QO?G?m??7?/?(?!?!?)?3o0?8???;H?P?OBY?Cb?k?!)u?.?R??S? ?ͪ??⭦?`?a??6???B?]??$f?|?C?-@r@ @e@@@m@o#@o(@-@ 2@47@[=@B@^H@N@ջS@wY@p_@je@Pyk@q@ w@~@;@wq@H@.@E@@o@[@Ĝ@3@~@@W@Q@I@$@@4@@G@@W@]@`@@]@@H@@@?|@@#@h@@3@#@ AAAXAAeAJA AUq A Am A;,A(WAwA9AәAuAAyAXAz*AAA'XAAAAύAxAYAAA&AOA_kAyA@@@&AAAYAxAύAAAA'XAAAz*AXA@AuAәA9AwA(WA;,Am A AUq A AJAeAAXAAA A#@3@@h@#@@?|@@@H@@]@@`@]@W@@G@@4@@$@I@Q@W@@~@3@Ĝ@[@o@@E@.@H@wq@;@~@ w@q@Pyk@je@p_@wY@ջS@N@^H@B@[=@47@ 2@-@o(@o#@m@@@e@ @r@-@C?|?$f??]?B???6??a?`?⭦??ͪ? ?S??R?.?!)u?k?Cb?OBY?P?;H???8?3o0?)?!?W"?Bx)?T0?~8?g@?H?L Q?;Y?b?l?u???:??uD????cZ?γ?o?F??@C@@I@N@תT@Z@l`@mf@l@r@x@9@΂@@J@,@@'A@@@u@@:`@ܧ@\@@g@)@i|@@0@#@L@;@@M@`@Q@@D@ݵ@p @σ@I@*2@{@T@7@@A#AtAAAhAa A A AW AAAAA3Ap@A4BA8A#AA?AaA'XAaAA<AA>AAh A]APASAA2A+A@@@SAPA]Ah AA>AA<AAaA'XAaA?AA#A8A4BAp@A3AAAAAW A A Aa AhAAAtA#AA@7@T@{@*2@I@σ@p @ݵ@D@@Q@`@M@@;@L@#@0@@i|@)@g@@\@ܧ@:`@@u@@@'A@@,@J@@΂@9@x@r@l@mf@l`@Z@תT@N@@I@C@1>@8@3@yJ.@4-)@ ($@a;@g@N@@} @ @/@??r?Ƃ??4????գ?к?,??j?K?dY?!?k?? 9? ?=v?l? Cc?7Z?vQ?H?.@?8?\61?r)?"?"?*?21?.9?A?BTI?Q?+Z?c?m?v?O?r??3?ҕ??‘???/z?!???[/??N$????:Q?I@F@q @F@2@@k@Lo$@v)@ .@3@9@>@D@ I@XDO@ U@Z@`@f@l@s@Uy@|@@5B@@ Ҍ@%@@@K@ @D.@@R%@9@,@#@ @@̹@Z@@x@@ @f@L@.@@-@@@@}@kF@@@&@]@@RAL\AAYAgA^9A@ A AvK A( AA2 A8Aw[A{sAAAyA9eADAAAAIA_A?AAAAOAPAA2AGA0cAqA@@GA2AAPAOAAAA?A_AIAAAADA9eAyAAA{sAw[A8A2 AA( AvK A A@ A^9AgAYAAL\ARA@]@&@@@kF@}@@@@-@@.@L@f@ @@x@@Z@̹@ @@#@,@9@R%@@D.@ @K@@@%@ Ҍ@@5B@@|@Uy@s@l@f@`@Z@ U@XDO@ I@D@>@9@3@ .@v)@Lo$@k@@2@F@q @F@I@:Q????N$??[/???!?/z???‘??ҕ?3??r?O?v?m?c?+Z?Q?BTI?A?.9?21?*?"?*#?U*?1?$o9?aA?I?R?Z?c?Rm?-v?|???e??қ?ɡ??@@FD@I@9O@PU@+[@ a@!g@;m@4js@-y@@?4@p@̵@@W@'@\@@@)f@@_@@ni@@@@E @@,@@?L@@:g@[@\x@@Sz@@g@@:@ @@:@|@0@'@AAC AA'AhA A( A| AB A A'>AOkA9AA8AŶAAAyAMAXAArAr!AA>AUA&AՆASA2AaUA~AvAKA@@~AaUA2ASAՆA&AUA>AAr!ArAAXAMAyAAAŶA8AA9AOkA'>A AB A| A( A AhA'AAC AAA'@0@|@:@@ @:@@g@@Sz@@\x@[@:g@@?L@@,@@E @@@@ni@@_@@)f@@@\@'@W@@̵@p@?4@@-y@4js@;m@!g@ a@+[@PU@9O@I@FD@&>@6]9@ 4@.@R)@S$@@@1 @`y@? @u@@ũ?R?V,?6?q??w?A?;?b?Ÿ?@w??Å??e?-?@yD@uJ@2O@fU@@Va@]g@ym@s@y@!@]V@@ى@'@k}@ړ@>@?@@"@z @k@t@ @!@@=@ͽ@^@@V@@*@6(@"@C4@@m.@@:@!x@@q-@sz@k@@o"@!AtA.AAAAA AM A A A;,AcA AVAAAA4A&APAyuAj=AAA JAGAlgAYAOAAAGA~A@@AAAKA~AGAAAOAYAlgAGA JAAAj=AyuAPA&A4AAAAVA AcA;,A A AM A AAAAA.AtA!Ao"@@k@sz@q-@@!x@:@@m.@@C4@"@6(@*@@V@@^@ͽ@=@@!@ @t@k@z @"@@?@>@ړ@k}@'@ى@@]V@!@y@s@ym@]g@Va@d[@fU@2O@uJ@yD@>@k9@:4@ /@s)@%$@E@@;G@5@ @K@c;@B??j?r?̫??ĭ?$v?m???i?r??w?}m?/d?[?JPR?I?A?]9?1?[*?T#?Hq#?*? 2?9?A?|I?tR?@[?[Wd?m?Diw?˳?ۅ?+?s?G?F??5?ˇ?!??E???Q:?? ? ?ҽ?O @OR@@X( @s@Ha@"@@$@)@b/@Z4@9@?@D@|5J@6O@jU@[@}a@Ѕg@m@s@mz@8@"m@@@@@w@1@X@Ě@M5@$@(@@G-@{@@@`ζ@]@@X@@@3@'@L@Y@Z@Z@vU@@t9@@@lW@@@R!@N@7AAEAA6AA A@e A AA EA|A\AAAAAYAuAŻAA'XAAA#eAxAAA_kAA2A0cAvA@@AAAAvA0cA2AA_kAAAxA#eAAA'XAAŻAuAYAAAAA\A|A EAA A@e A AA6AAEAA7AN@R!@@@lW@@@t9@@vU@Z@Z@Y@L@'@3@@@X@@]@`ζ@@@{@G-@@(@$@M5@Ě@X@1@w@@@@@"m@8@mz@s@m@Ѕg@}a@[@jU@6O@|5J@D@?@9@Z4@b/@)@$@@"@Ha@s@X( @@OR@O @ҽ? ? ??Q:???E??!?ˇ?5??F?G?s?+?ۅ?˳?Diw?m?[Wd?@[?tR?|I?A?9? 2?*?Hq#?q#?*?A2?9?`A?J?R?S[?$kd?Dm?~w???7??U?#??)D?떮??bĻ?!?? ? M???̨?J?@]@Ѽ@4 @@Pn@A0@ @$@ *@-/@i4@9@l)?@D@GJ@:O@U@[@2a@g@Fm@s@.z@/C@x@@u@WL@@@e@wњ@C@&@e6@@@3<@į@w??Å??e?-?@yD@uJ@2O@fU@d[@Va@]g@ym@s@y@!@]V@@ى@'@k}@ړ@>@?@@"@z @k@t@ @!@@=@ͽ@^@@V@@*@6(@"@C4@@m.@@:@!x@@q-@sz@k@@o"@!AtA.AAAAA AM A A A;,AcA AVAAA@@&APAyuAj=AAA JAGAlgAYAOAAAGA~AKAAAAA@@GAAAOAYAlgAGA JAAAj=AyuAPA&A4AAAAVA AcA;,A A AM A AAAAA.AtA!Ao"@@k@sz@q-@@!x@:@@m.@@C4@"@6(@*@@V@@^@ͽ@=@@!@ @t@k@z @"@@?@>@ړ@k}@'@ى@@]V@!@y@s@ym@]g@Va@d[@fU@2O@uJ@yD@>@k9@:4@ /@s)@%$@E@@;G@5@ @K@c;@B??j?r?̫??ĭ?$v?m???i?r??w?}m?/d?[?JPR?I?A?]9?1?[*?T#?*#?U*?1?$o9?aA?I?R?Z?c?Rm?-v?|???e??қ?ɡ??@@FD@I@9O@PU@+[@ a@!g@;m@4js@-y@@?4@p@̵@@W@'@\@@@)f@@_@@ni@@@@E @@,@@?L@@:g@[@\x@@Sz@@g@@:@ @@:@@@'@AAC AA'AhA A( A| AB A A'>AOkA9AA8A@@AyAMAXAArAr!AA>AUA&AՆASA2AaUA~AvAKAKAvA@@2ASAՆA&AUA>AAr!ArAAXAMAyAAAŶA8AA9AOkA'>A AB A| A( A AhA'AAC AAA'@0@|@:@@ @:@@g@@Sz@@\x@[@:g@@?L@@,@@E @@@@ni@@_@@)f@@@\@'@W@@̵@p@?4@@-y@4js@;m@!g@ a@+[@PU@9O@I@FD@&>@6]9@ 4@.@R)@S$@@@1 @`y@? @u@@ũ?R?V,?6?q??w?A?;?b?Ÿ?@@D@ I@XDO@ U@Z@`@f@l@s@Uy@|@@5B@@ Ҍ@%@@@K@ @D.@@R%@9@,@#@ @@̹@Z@@x@@ @f@L@.@@-@@@@}@kF@@@@@@RAL\AAYAgA^9A@ A AvK A( AA2 A8Aw[A{sAA@@9eADAAAAIA_A?AAAAOAPAA2AGA0cAqAqA0cAGA2AAPAOAAAA?A_AIAAAADA9eAyAAA{sAw[A8A2 AA( AvK A A@ A^9AgAYAAL\ARA@]@&@@@@@@@@-@@.@L@f@ @@x@@Z@̹@ @@#@,@9@R%@@D.@ @K@@@%@ Ҍ@@5B@@|@Uy@s@l@f@`@Z@ U@XDO@ I@D@>@9@3@ .@v)@Lo$@k@@2@F@q @F@I@:Q????N$??[/???!?/z???‘??ҕ?3??r?O?v?m?c?+Z?Q?BTI?A?.9?21?*?"?"?r)?\61?8?.@?H?vQ?7Z? Cc?l?=v? ? 9??k?!?dY?K?j??,?к?գ????4??Ƃ?r???/@ @} @@N@g@a;@ ($@4-)@yJ.@3@8@1>@C@@I@N@תT@Z@l`@mf@l@r@x@9@΂@@J@,@@'A@@@u@@:`@ܧ@\@@g@)@i|@@0@#@L@;@@M@`@Q@@D@ݵ@p @σ@I@*2@{@T@7@@A#AtAAAhAa A A AW AAAAA3Ap@A4BA8A#AA?AaA'XAaAA<AA>AAh A]APASAA2A+A+A2AASAPA]Ah AA>AA<AAaA'XAaA?AA#A8A4BAp@A3AAAAAW A A Aa AhAAAtA#AA@7@T@{@@@@p @ݵ@D@@Q@`@M@@;@L@#@0@@i|@)@g@@\@ܧ@:`@@u@@@'A@@,@J@@΂@9@x@r@l@mf@l`@Z@תT@N@@I@C@1>@8@3@yJ.@4-)@ ($@a;@g@N@@} @ @/@??r?Ƃ??4????գ?к?,??j?K?dY?!?k?? 9? ?=v?l? Cc?7Z?vQ?H?.@?8?\61?r)?"?W"?Bx)?T0?~8?g@?H?L Q?;Y?b?l?u???:??uD????cZ?γ?o?F??&@ͣ@V$@L@ ,@;@9@@CF@v@N@@@@=@.@@g}@@0@|@~@0@C)@M@d@7AǶA.AAAhA A AW A( A!A>A8A(A3A3AY(AAYA&AAS@AQAA@!AAr!AύAA>AAUAYAAh Ah AAYAUAA>AAύAr!AA@!AAQAS@AA&AYAAY(A3A3A(A8A>A!A( AW A A AhAAA.AǶA7Ad@M@C)@0@~@|@0@@g}@@.@=@@M@@N@v@CF@@9@;@ ,@L@V$@ͣ@>&@5@66@ğ@`X@@@.6@@L@Q@@@k}@&w@p@Rj@d@^@@@}sM@G@JB@<@}7@V:2@{-@|'@"@@%O@@+@~ @@k@????/?}?q\?V9?D?G~?i?y?:?e'????k?}?G?_~?ot?j?a?X?QO?G?m??7?/?(?!?!?J(?l/?7?>?WF?dXO?:X?R`? 6j?s?}??i?!?T?Ǚ???a? Z???:?ƻ???.?{ ?a?O?]@@5 @ @@(@@@"@w'@,@1@6@E<@A@V8G@L@ބR@KX@h(^@d@{j@9p@fv@˥|@{@{@@)@Zs@Wđ@-@nz@ޛ@aH@#@p*@š@@j@@@ @%@G(@@X.@@C-@m@@ޒ@@h@@V%@!x@i@~@:@Eg@@@RAQAA 7AAhAU A AY A& AYA+ADAA A6A8A֜AyAJAAAyuAXAxA.AAArAAA>AlgAA[A[AAlgA>AAArAAA.AxAXAyuAAAJAyA֜A8A6A AADA+AYA& AY A AU AhAA 7AAQARA@@Eg@:@~@i@!x@@@@@ޒ@@m@C-@@X.@@G(@%@ @@@j@@š@p*@#@aH@ޛ@nz@-@Wđ@Zs@)@@{@{@˥|@fv@9p@{j@d@h(^@@@L@V8G@A@E<@6@1@,@w'@"@@@@(@ @5 @@]@O?a?{ ?.???ƻ?:??? Z?a???Ǚ?T?!?i??}?s? 6j?R`?:X?dXO?WF?>?7?l/?J(?!?{ ?'?X.?db6?3>?AIF? N?cHW?4`?ki?=r?;|?tn?ѥ??D?B? ?)?^?ܿ?M?E ?n? ?O??Ji?R=?CA?Tu?@A7@ @@@S@B@ !@&@+@1@P6@;@ A@F@]"L@Q@W@@h]@rTc@Ti@Tio@u@D{@ @:@q@?@#@CF@5@@W@@f*@@ @@@~@@=~@@@X@@V@@3y@[@e@@@@@@\@v@@*2@f@j@@@cAJAUAAG*ALjAA, AUq A֬ A A A*%A8ABAj@A3AmAA#AADAAA"AxA@!AA_A<A?AAGAxAAAxAGAA?A<A_AA@!AxA"AAADAA#AAmA3Aj@ABA8A*%A A A֬ AUq A, AALjAG*AAUAJAcA@@j@f@*2@@v@@@@@@@e@[@3y@@V@@X@@@=~@@~@@@ @@f*@@W@@5@CF@#@?@q@:@ @D{@u@Tio@Ti@rTc@@h]@@@]"L@F@ A@;@P6@1@+@&@ !@B@S@@@ @A7@@Tu?CA?R=?Ji??O? ?n?E ?M?ܿ?^?)? ?B?D??ѥ?tn?;|?=r?ki?4`?cHW? N?AIF?3>?db6?X.?'?{ ??&?..?5?~=?E?yM?{V?u__?h?$r?{?m?#?~??ذ?9?????S?!6?F????]?Y??Aq@@ @Œ@@@ҁ@X!@H&@N+@lm0@S5@k:@uT@@&E@-`K@1Q@V@\@1|b@wh@n@Zt@z@@＃@#@P-@q@@ @e@Ě@'@"@-@9n@@@y@W@ i@]@N@3@i%@@@7@@J@@@cS@n@@k@@@|AQAEAA{AOAW A\ A A8 A A AAAAj AsAA֜A_AA&A@_AAyuAQA'XAߵAaAIArAAA]A]AAArAIAaAߵA'XAQAyuAA@_A&AA_A֜AAsAj AAA@ A A8 A A\ AW AOA{AAEAQA|A@@k@@n@cS@@@J@7@@@@i%@3@N@]@ i@W@y@>@@ @@@J@h0@w@Q@@@y#@Ȗ@9t@%@Tތ@@e@?4@ @ty@s@m@Ѕg@2a@°[@U@O.P@(J@E@?@t.:@4@]/@2*@%@ @o@6%@@ @̆ @@@.?f^?_j???k?r?i???_?{ ???j?\j???i?z? q?@@ U? M?D?@$D@I@XDO@T@۹Z@`@f@l@r@x@~@ʠ@΅@H@@@䃏@Β@o@>v@zҜ@3@Q@@p@@gR@ƴ@<@;@v(@,@@@@fc@@~2@ޒ@@A@I@@5@kF@p@@ޥ@@@MAA8(AXAA6ABA A A' AK AKfAvA|AwA&hA,MA&AAŶAlAAADAAS@AAA'XAAAAA@!A@!AAAAA'XAAAS@AADAAAlAŶAA&A,MA&hAwA|AvAKfAK A' A A ABA6AAXA8(AAMA@@ޥ@@p@kF@5@@I@A@@ޒ@~2@@fc@@@@,@v(@;@<@ƴ@gR@@p@@Q@3@zҜ@>v@o@Β@䃏@@@H@΅@ʠ@~@x@r@l@f@`@۹Z@T@XDO@I@$D@>@6]9@4@.@s)@m$@@A0@Y{@X@LY @<@@@i?#O? d?G???-?Č???И?aK?)?H3?g?ő?M?0?ց?y?o?@@T?k$L?C?;?,4?Y,?%??,?@$?Y+?R3?;?B?c-K?S?q\?݀e?n?x?9?Z?̣?h?K? u?Ed?~?RĮ?46?Ի?!??ڿ??l?J?V,?*=?|}?@F@@ @-@@@vt@a;@$@)@1.@A3@|8@=@$7C@|H@IN@S@-Y@_@je@dk@rq@w@}@@*,@{]@L@8֎@@i@@@q@XӢ@8@š@ @{@@$]@Ϻ@$A@@#@@@:g@@.@_@@[1@z@e@@&@L@h@0z@@x@d@!AAABAAAW AP Aj} A A A!AAAAA{sAp@AAŶA_AmAAAAAMAaAAXAj=A'XAeAeA'XAj=AXAAaAMAAAAAmA_AŶAAp@A{sAAAAA!A A Aj} AP AW AAABAAA!Ad@x@@0z@h@L@&@@e@z@[1@@_@.@@:g@@@#@@$A@Ϻ@$]@@{@ @š@8@XӢ@q@@@i@@8֎@L@{]@*,@@}@w@rq@dk@je@_@-Y@S@IN@|H@$7C@=@|8@A3@1.@)@$@a;@vt@@@-@@ @F@@@*=?V,?J?l??ڿ??!?Ի?46?RĮ?~?Ed? u?K?h?̣?Z?9?x?n?݀e?q\?S?c-K?B?;?R3?Y+?@$?,??#?+?zj2?:?A?&J?:R?@@@h>w?\???UY??;?‘???LK?*?գ?????v??J??J2?K@@ @q@@<@l@-E#@4(@|;-@:Y2@7@<@:B@MG@>M@$R@X@.b^@GAd@3j@9p@Pv@z|@.Z@@@X@@q_@@@_J@@E@\a@Ũ@G-@ @@qo@ܹ@J@@#@@@^Z@@o@^p@@@S@J@v@@6@q-@:@><@y1@@&zAJA>AԕAA*AhA@ A AY AA AAnA2 AAAVABAp@AA֜A8A#AJA&Az*AA?AAMAyuAAaAaAAyuAMAA?AAz*A&AJA#A8A֜AAp@ABAVAAA2 AnAAA AY A A@ AhA*AAԕA>AJA&zA@y1@><@:@q-@6@@v@J@S@@@^p@o@@^Z@@@#@@J@ܹ@qo@@ @G-@Ũ@\a@E@@_J@@@q_@@X@@@.Z@z|@Pv@9p@3j@GAd@.b^@X@$R@>M@MG@:B@<@7@:Y2@|;-@4(@-E#@l@<@@q@ @@K@J2??J??v?????գ?*?LK???‘?;??UY???\?h>w?m?[Wd?S[?:R?&J?A?:?zj2?+?#??$?&#?*?s1?9?@?I?vQ?@@@u?6??.?ő??Ӛ?c?T?`? R?޹? ?m~???C??N???!@p@`6 @@5@@@tc"@1L'@K,@b1@6@;@-A@:F@]"L@Q@kW@.]@c@h@n@3t@{@Z@Yȃ@#@X!@X@w@ړ@t$@s@ǝ@M @|@ܧ@>?@J@# @9s@۸@D@#@X@y@@=@@@$E@ޒ@Z@@S@@v@@@@@3@j@@,AAA~+ApAAA A( AO? AK AMA EA1A8AAVA{sA&AAiAAyAYAXAAADAyAPAŻAAAŻAPAyADAAAXAYAyAAiAA&A{sAVAA8A1A EAMAK AO? A( A AAApA~+AAA,A@j@3@@@@@v@@S@@Z@ޒ@$E@@@=@@y@X@#@D@۸@9s@# @J@>?@ܧ@|@M @ǝ@s@t$@ړ@w@X@X!@#@Yȃ@Z@{@3t@n@h@c@.]@kW@Q@]"L@:F@-A@;@6@b1@K,@1L'@tc"@@@5@@`6 @p@!@??N??C???m~? ?޹? R?`?T?c?Ӛ??ő?.??6?u?\l?c?$Z?vQ?I?@?9?s1?*?&#?$?C??"?? )?3o0?7?B???G?rBP?@@@ot?I~?0?c?꾎?B??aƟ?sǥ?a?J?͸?D}?pY?b?}? ??Q?CA?_?X@b@i @@k[@O@@t!@}V&@N+@$^0@܃5@ۿ:@@@yE@J@P@)/V@[@Ka@g@m@fs@-y@@@*@zV@@@j@zF@ؐ@@3@%@@C@ͣ@@h@{̷@O0@@@TV@z@@:g@@@Q@@Q@@0@S@qm@|@n@sz@Eg@>G@@oA@AgAAAA= A\ AUq A| A| ArA]A'>A8AAA,MAsAAmA֜AAyA4A#A9eAA&AuAAAuA&AA9eA#A4AyAA֜AmAAsA,MAAA8A'>A]ArA| A| AUq A\ A= AAAAgAAAoA@>G@Eg@sz@n@|@qm@S@0@@Q@@Q@@@:g@@z@TV@@@O0@{̷@h@@ͣ@C@@%@3@@ؐ@zF@j@@@zV@*@@@-y@fs@m@g@Ka@[@)/V@P@J@yE@@@ۿ:@܃5@$^0@N+@}V&@t!@@O@k[@@i @b@X@_?CA?Q?? ?}?b?pY?D}?͸?J?a?sǥ?aƟ??B?꾎?c?0?I~?ot?dk? a?EX?rBP??G?B??7?3o0?? )?"?C??M?!?J(?\/?6?>?pF?N? W? o`?i?Js?;|?c?%??)\?M?͞?Ť??x5?}?S? %?d#?N??.?? ??y @C@ @ @Ov@ @@y @S%@D*@K/@i4@9@8>@FD@I@XDO@%T@Z@XY`@1f@l@r@'x@ G~@;@YZ@@~@@@\@@(@:@ތ@@;@ӕ@k@@9@i4@K/@D*@S%@y @@ @Ov@ @ @C@y @? ??.??N?d#? %?S?}?x5??Ť?͞?M?)\??%?c?;|?Js?i? o`? W?N?pF?>?6?\/?J(?!?M?P?u ?u'? =.?5?.n=?hjE?M?P1V?^?h?tq?{?z??*?\j?>?aɝ?R?ϩ???<??l?4?7A?? d?Q:?>?8@>i@@ @@/@m@r@D$@4-)@H,.@A3@l8@=@mC@oH@=M@ӄS@N-Y@6^@d@Pj@kp@ɐv@˥|@de@@@JɊ@#@-@g@@N@M5@#@QҤ@R%@z@Ѯ@*@@۸@4@@@5@@@;@_@@@N@[1@MS@|l@?|@@|@ll@O@&@7@@R,A+{AAA 7ArdALjAA A A A֬ A( ArA EA2 AAwAAVAj@A6A3AuAA4BAAŶAAAAAAAŶAA4BAAuA3A6Aj@AVAAwAA2 A EArA( A֬ A A A AALjArdA 7AAA+{AR,A@7@&@O@ll@|@@?|@|l@MS@[1@N@@@_@;@@@5@@@4@۸@@*@Ѯ@z@R%@QҤ@#@M5@N@@g@-@#@JɊ@@@de@˥|@ɐv@kp@Pj@d@6^@@@=M@oH@mC@=@l8@A3@H,.@4-)@D$@r@m@/@@ @@>i@8@>?Q:? d??7A?4?l??<???ϩ?R?aɝ?>?\j?*??z?{?tq?h?^?P1V?M?hjE?.n=?5? =.?u'?u ?P?G??%?9-?{4? '_@(#@ (@},@ 2@m.7@ef<@A@G@L@R@?W@@h]@-c@+i@n@t@{z@텀@@@ى@@b2@sg@@@$@8k@@@~R@ͣ@Q@{I@@{@$A@@@)@p@ֳ@@*@]@@.@@@@}@I@@G@0z@>@@@AJAAPA[|AAȷAJA A A A A| AMAnAA|AAABA A3AәAsAp@AA8A@@AAAA8AAp@AsAәA3A ABAAA|AAnAMA| A A A A AJAȷAA[|APAAJAA@@>@0z@G@@I@}@@@@.@@]@*@@ֳ@p@)@@@$A@{@@{I@Q@ͣ@~R@@@8k@$@@@sg@b2@@ى@@@텀@{z@t@n@+i@-c@@h]@@@L@G@A@ef<@m.7@ 2@},@ (@(#@>_@<@@@H @@@@?t??7???$v?E?Ի?E??U??㸜??m??Æ??my?o?f?}]?iT?GL?zD? '@~5D@ I@O@kT@\5Z@_@Ve@Pyk@/]q@XQw@&U}@@zĄ@ۇ@k@@CF@t@@ޚ@@.X@<@ܧ@!@g@@@<@x@0ž@@@9@4@y/@*@%@o @}@s@@t@ @@%@}??(?|? ??S????t?[?:?(C?@R$@4-)@1.@"3@=8@Fl=@B@H@}sM@jR@7X@h(^@{c@i@~o@kfu@H^{@@＃@Ά@@@%@M@z@w@@@R@V@ͩ@ @M@k@`ζ@E @J@@@W@"@N@uu@@"@@@Q@@@#@!x@kF@b@e@d@@@@@dAAtAOAAAȷAAi A\ A( AY A AK A A~A A+A>A(WAͮAA8AOkA A\AAA\A AOkA8AAͮA(WA>A+A A~A AK A AY A( A\ Ai AAȷAAAOAtAAdAm7A@@@@@b@kF@!x@#@@@Q@@@"@@uu@N@"@W@@@J@E @`ζ@k@M@ @ͩ@V@R@@@w@z@M@%@@@Ά@＃@@H^{@kfu@~o@i@{c@h(^@7X@jR@}sM@H@B@Fl=@=8@"3@1.@4-)@R$@>@@;G@@LY @ @%@ڜ@/??&V?n?^I??\??C?}?D??? ?B?ب?7??Ƀ?}?Ss?Yj?cla?(X?W P?G???7?}~0?=)?:"?u??b?(3? ?'?/?6?3>?&F?{]N?V?_?h?-q?b{??[ч?? w?>???y?կ?2??j?H?P?M??r?V,?V?%?/@7@4 @1@@@C@"@'@,@1@v6@;@A@iF@K@=Q@V@S\\@b@g@m@4js@Uy@O@@綅@Lj@ދ@^@@B@8m@/@]̞@E@e6@9n@9@@@S@@»@@G(@TV@V@@@@@@@@@V@e@{@X@6@@f@s@@@[@XA+{AєAtAЬAAALjAhA= A A Aj} A' A8 AW A AYA!A;,A+AA2 A'>AcA|A6A6A|AcA'>A2 AA+A;,A!AYA AW A8 A' Aj} A A A= AhALjAAAЬAtAєA+{AXA[@@@s@@@6@X@{@e@V@@@@@@@@@V@TV@G(@@»@@S@@@9@9n@e6@E@]̞@/@8m@B@@^@ދ@Lj@綅@@O@Uy@4js@m@g@b@S\\@V@=Q@K@iF@A@;@v6@1@,@'@"@C@@@1@4 @7@/@%?V?V,?r??M?P?H?j??2?կ?y???>? w??[ч??b{?-q?h?_?V?{]N?&F?3>?6?/?'? ?(3?b?w??ُ?t&?`-?[4?Iw?|?_~??k?Fk??>Π?T?jӬ??G~???ƻ???|???E?Aq@֔@\ @@@@|@w4 @@@+.@3@8@=@mC@AMH@M@S@X@h(^@c@l}i@?o@nu@{z@o@"m@p@1z@@Ĝ@@yѕ@@@:@b@^@@@@U@p9@c@@;@վ@@@)@;@~H@N@M@$E@C4@v@@@J@M@@}@7@~@:@ޥ@@M@@XAdAgAaAPA 7A AAAhAW A A\ A AUq AY AW A Ay AW A( AB A AAAAA AB A( AW Ay A AW AY AUq A A\ A AW AhAAA A 7APAaAgAdAXA@M@@ޥ@:@~@7@}@@M@J@@@v@C4@$E@M@N@~H@;@)@@@վ@;@@c@p9@U@@@@^@b@:@@@yѕ@@Ĝ@@1z@p@"m@o@{z@nu@?o@l}i@c@h(^@X@S@M@AMH@mC@=@8@3@+.@)@$@w4 @|@@@@\ @֔@Aq@E???|???ƻ???G~??jӬ?T?>Π??Fk?k??_~?|?h>w?Dm?d?[?f+S?qJ?B?M:?{b3? ,?$?)??I/?4?.??q#?[*?1?>9?Q@?H??Q?;Y?b?k?t?ȡ~?G?c?0?T??W?8?@?r?Tη?S???4??Ak?'?y?L?C@]@u@ @-@W@@$@h@@@{-@1@6@<@M>A@zF@K@m+Q@V@#\@Ka@]g@m@r@x@)~@;@7@:@A@XN@q_@t@[@?@ǝ@@ @_.@~R@v@j@@8޶@'@U@,2@G@qW@b@!h@:g@W_@O@$8@@@|@z@0@@!x@@5@@/e@T@@+7@[@m7A7A&/AAAAApA*AABAW A- A, A A AUq A A AvK A| A A A8 A8 A A A| AvK A A AUq A A A, A- AW ABAA*ApAAAAA&/A7Am7A[@+7@@T@/e@@5@@!x@@0@z@|@@@$8@O@W_@:g@!h@b@qW@G@,2@U@'@8޶@@j@v@~R@_.@ @@ǝ@?@[@t@q_@XN@A@:@7@;@)~@x@r@m@]g@Ka@#\@V@m+Q@K@zF@M>A@<@6@1@{-@4(@o#@h@@$@W@-@ @u@]@C@L?y?'?Ak??4???S?Tη?r?@?8?W??T?0?c?G?ȡ~?t?k?b?;Y??Q?H?Q@?>9?1?[*?q#??.?4?؁??C??!?(?0?7?X+??G?nFO?jW? o`?ki? r?:|???M?ש?,? ם?#?y?zƯ???7'?x? ?$?J??w]?M'?D?-@C@~ @K@5@@@@!@&@l+@N0@D5@N:@k?@D@I@c2O@kT@Z@L_@/e@Rj@kp@Pv@"|@@ @#@@@q@(@o@3@J@c@~@@@@ӫ@@# @$@<@P@b@o@x@l|@z@ur@fc@L@.@@@@vU@@i@?@@kF@@@/e@ޥ@3@@@@AJAA AgA~+AAA6AOA\AAU A A At A A A( AM A@e AUq AUq A@e AM A( A A At A A AU AA\AOA6AAA~+AgA AAJAA@@@3@ޥ@/e@@@kF@@?@i@@vU@@@@.@L@fc@ur@z@l|@x@o@b@P@<@$@# @@ӫ@@@@~@c@J@3@o@(@q@@@#@ @@"|@Pv@kp@Rj@/e@L_@Z@kT@c2O@I@D@k?@N:@D5@N0@l+@&@!@@@@5@K@~ @C@-@D?M'?w]??J?$? ?x?7'??@@y?#? ם?,?ש?M???:|? r?ki? o`?jW?nFO?G?X+??7?0?(?!?C???؁? ?#P??_ ?b?'?T[.?5?]M=? &E?.@M? U?=^?#g?XPp?Sy??Æ?v?#;?K?hL??T??LK??F??????}?{ ?ؿ??X@@ " @g@@O2@@=P @$@)@ .@3@|8@=@B@&@:@M@_@qo@i|@@@P@@V@p@^Z@<@@@@Pn@"@@g@f@?|@@[@@@:@e@@@@d@A+{AQAAAԕABAA{AALjAhAhAJAW Aa A@ A A A A A A A A A@ Aa AW AJAhAhALjAA{AABAԕAAAQA+{AAd@@@@e@:@@@[@@?|@f@g@@"@Pn@@@@<@^Z@p@V@@P@@@i|@qo@_@M@:@>&@i@@@w՝@Ě@Ĵ@@y@e@L@@@@3|@-y@s@2n@(h@ b@@h]@XW@ބR@V,M@w?p??g??Ï?*?4?l?H?L? y?͸?K?n????.??~I?/?@*@Ѽ@u @F@N@@$@@SS#@ (@,@1@Ο6@;@@@JE@K@sdP@U@+[@&`@1f@k@rq@&w@|@.Z@.F@[7@P-@'@%@'@r,@3@K=@aH@T@\a@9n@z@ @揱@@@@@0@͊@y@b@D@f@@3@}@C4@@͂@@@p @{@@kF@5@~@@s@@7@Q@@R,AAAA>AAXAAAG*AAAeAȷAhA^9AhAAAAAAAhA^9AhAȷAeAAAG*AAAXAA>AAAAR,A@Q@7@@s@@~@5@kF@@{@p @@@͂@@C4@}@3@@f@D@b@y@͊@0@@@@@揱@ @z@9n@\a@T@aH@K=@3@r,@'@%@'@P-@[7@.F@.Z@|@&w@rq@k@1f@&`@+[@U@sdP@K@JE@@@;@Ο6@1@,@ (@SS#@@@$@N@F@u @Ѽ@*@@/?~I??.????n?K?͸?@@H?l?4?*?Ï???g?p?h>w?m?-d?([?tS?c-K?2(C?c;?3?n,?ގ%??-?,? ?_; ?M???#?I*?f1?$o9?A?I??Q?]Y?jb?Hgk?Щt?3~???rC? ??4???1??jL???,???6??|?Z^?4@zO@~ @@j@i@ @!@H&@+@/@ݷ4@9@>@C@H@7N@ӄS@X@N^@c@Ti@n@)t@Cz@@@΅@ @~@@y@5@}@ٛ@͞@ڢ@~@5@x@@{@#@&@@@@X@g@H@"@@'@σ@`=@B@ޒ@-@@7@@@p @?|@@@7@lW@f@d@Q@,@@@N@oA,AJAA8(AEAEAA 7AAA+MAAgA'A@@eBAeBA6AAA'AgAA+MAAA 7AAEAEA8(AAJA,AoAN@@@,@Q@d@f@lW@7@@@?|@p @@7@@@-@ޒ@B@`=@σ@'@@"@H@g@X@@@@&@#@{@@x@5@~@ڢ@͞@ٛ@}@5@y@@~@ @΅@@@Cz@)t@n@Ti@c@N^@X@ӄS@7N@H@C@>@9@ݷ4@/@+@H&@!@ @i@j@@~ @@@Z^?|??6???,???jL??1???4?? ?rC???3~?Щt?Hgk?jb?]Y??Q?I?A?$o9?f1?I*?#???M?_; ?1???g?"?O(?0?o7?; ??F?N? [W?~_?%h?$r?v{?ʖ??&??t?q ?Ƣ?U?.??jB?f?p?cE?B?]i?5?e2???@Z@' @h6@@@X@E@}$@4-)@-@2@7@<@A@F@K@=Q@V@[@Va@f@&Zl@q@w@4?}@{@]@C@P-@h@ @j@o@@(@@5@@ܧ@ת@Э@XȰ@@@@@j@I@#@@@B@M?@[@ԙ@$8@@@@7@@@f@?@!x@}@'@@e@@z@>@7@@@@&zA!AAQAAUAA.AXAAAYAA@@iAiAAAAYAAAXA.AAUAAQAA!A&zA@@@7@>@z@@e@@'@}@!x@?@f@@7@@Q@S@@$8@ԙ@[@M?@@@@#@I@j@@@@@XȰ@Э@ת@ܧ@@5@@(@@o@j@ @h@P-@C@]@{@4?}@w@q@&Zl@f@Va@[@V@=Q@K@F@A@<@7@2@-@4-)@}$@E@X@@@h6@' @@@??e2?5?]i?B?cE?p?f?jB??.?U?Ƣ?q ?t??&??ʖ?v{?$r?%h?~_? [W?N?F?; ??o7?0?O(?"?g???1?f9?) ?#P?ȭ?C ?'?.?>f5?@0@$@@ @E@@@Ѯ@@L@ӌ@n@J@!@@@V@;@4@@:@`@]@@@@@g@i@@@@6@b@@S@0z@&@@>G@j@@d@MA|AdAJAQAǶAAaAtAAC A@@PAPAEA.AC AAtAaAAǶAQAJAdA|AMAd@@j@>G@@&@0z@S@@b@6@@@@i@g@@@S@@]@`@:@@4@@@@@!@J@n@ӌ@L@@Ѯ@@@E@ @@$@0@>@N@q_@Zs@4@q@~…@@ @)oz@t@?o@$i@GAd@^@xY@*T@N@I@D@?@W:@S5@;0@j,@1L'@ܩ"@@@6@o@ @u@]@Z@y??Ւ?.????7?v?-?i?rĬ?ʦ??K?ƕ?e?+??~#?x?Vo? Hf?}]?T?L?D?f5?.?'?C ?ȭ?#P?) ?f9?V?O ???n?*%? ,?R3?:?nB?ZJ?R?Z?c?l?Ju?R?X?h?꾎?T?? ?B?mʪ?qٰ??:m???u?r?l??w]??C?@ @) @:@@@K@o @1b%@ *@q.@S3@l8@[=@[B@%lG@L@Q@V@=I\@a@ g@l@r@w@D)}@de@:@:@@ Ҍ@@@@8m@W@C@D.@@@Q@Ѭ@{@.@9s@ L@ @@@y@5@@ @6@@_@@]@@-@͂@@@0@M@0[@X@kF@#@@G@O@@Eg@3@y1@x@@@@cARA7AAJA#AL\AAtAAoAoAAtAAL\A#AJAA7ARAcA@@@x@y1@3@Eg@@O@G@@#@kF@X@0[@M@0@@@͂@-@@]@@_@@6@ @@@@@@ @ L@9s@.@{@Ѭ@Q@@@D.@C@W@8m@@@@ Ҍ@@:@:@de@D)}@w@r@l@ g@a@=I\@V@Q@L@%lG@[B@[=@l8@S3@q.@ *@1b%@o @K@@@:@) @ @@C??w]??l?r?u???:m??qٰ?mʪ?B? ??T?꾎?h?X?R?Ju?l?c?Z?R?ZJ?nB?:?R3? ,?*%?n???O ?V?]? ??!??8#?*?\61?8?l$@?G?W P?`X?R`?i?=r?P|????P?K?@?5?Ǩ?RĮ??12?գ?<@@@@Q@@@d@ AXAARAA!A7A CA CA7A!AARAAXA Ad@@@Q@@@@><@@sz@@ll@@6@0O@!x@{@@J@z@vU@"@@ޒ@$8@`@_@@^Z@@X.@@@,@r@;@@z @!? (?/?R6?=?E?\M?U?=^?f?o?By?f?1O?G[?e?ߕ?dY??T??ﶲ??K?$?{?N?^I?Ak??%?ҽ?|}?/@&@ @+@A@@ @t!@&@2*@K/@ 4@8@g=@B@MG@L@Q@LW@=I\@2a@f@El@q@&w@˥|@@1߃@@1z@*L@ @@Δ@@@Z@3@ @@@@}@X@V$@@@Xl@3$@վ@X@#@@8Q@@^Z@@:@ԙ@B@C4@Pn@@|@@@e@#@~o@0@I@|@b@n@@:@0z@ޥ@k@@@@M@#@@@@'@o"@N@d@d@N@o"@'@@@@#@M@@@@k@ޥ@0z@:@@n@b@|@I@0@~o@#@e@@@|@@Pn@C4@B@ԙ@:@@^Z@@8Q@@#@X@վ@3$@Xl@@@V$@X@}@@@@ @3@Z@@@Δ@@ @*L@1z@@1߃@@˥|@&w@q@El@f@2a@=I\@LW@Q@L@MG@B@g=@8@ 4@K/@2*@&@t!@ @@A@+@ @&@/@|}?ҽ?%??Ak?^I?N?{?$?K??ﶲ??T??dY?ߕ?e?G[?1O?f?By?o?f?=^?U?\M?E?=?R6?/? (?>!??EP?+?<?Ӏ???f ?w?ؾ?<?e%?C,? 4?t;?JC?J?S?y[? d?m?(v??R?T?꾎??~j?B?'??}???Y?x?ĭ??!?M?w(??O?@@ @h6@i@@@r@F#@}(@z-@_1@6@a;@C@@#5E@|5J@XDO@0aT@wY@^@d@Ti@n@&t@y@~@;@ @:ć@7@X@%@@ĕ@ܔ@Ke@M5@d@ ң@ŝ@g@G-@@@h@@̹@u@@@E@@8Q@@6@@[@`=@}@@@@@@V@@@?@}@@@|@@q-@h@@@@j@Eg@C)@3@m@7@]@0@@R!@+7@+7@R!@@0@]@7@m@3@C)@Eg@j@@@@h@q-@@|@@@}@?@@@V@@@@@@}@`=@[@@6@@8Q@@E@@@u@̹@@h@@@G-@g@ŝ@ ң@d@M5@Ke@ܔ@ĕ@@%@X@7@:ć@ @;@~@y@&t@n@Ti@d@^@wY@0aT@XDO@|5J@#5E@C@@a;@6@_1@z-@}(@F#@r@@@i@h6@ @@@O??w(?M?!??ĭ?x?Y???}??'?B?~j??꾎?T?R??(v?m? d?y[?S?J?JC?t;? 4?@@@ؾ?w?f ???v>?P ??,?4?#?*?1?9?@?`H?fP?X?1a?Gi?Js?P|?m? ݇??R?t?=??R?@ >#? ?D??_$?!?p(?l/?6?>?E?M?U?=^?f?o?y?9???3?9x?q?l??a?@@S??O?f?.???w]? ?`l?!@@ @x@>@ @X@@ ($@|(@|;-@1@6@Q;@~"@@E@tI@N@S@Y@h(^@rTc@(h@m@s@hx@}@D@@@̵@p@,@@@@e@y#@@D@T@z @w@p@@į@g@N@@-@!@9@@#@@@;@B@'@@@.@$8@C4@!@@Q@@?@@|l@@S@v@@&@kF@cS@L@*2@~@~@h@@{@@:@sz@@I@I@@sz@:@@{@@h@~@~@*2@L@cS@kF@&@@v@S@@|l@@?@@Q@@!@C4@$8@.@@@'@B@;@@@#@@9@!@-@@N@g@į@@p@w@z @T@D@@y#@e@@@@,@p@̵@@.F@D@}@hx@s@m@(h@rTc@h(^@Y@S@N@tI@E@~"@@Q;@6@1@|;-@|(@ ($@@X@ @>@x@ @@!@`l? ?w]???.?f?O??S???a??l?q?9x?3???9?y?o?f?=^?U?M?E?>?6?l/?@@@?D? ?#? >P>P?,? ??T??,&?9-?,4?L;?JC?J?R?@[?c?l?u?~?G?-4?rC?u?P˘?D??y?@@bĻ?j??n3??>?`?(?ރ??@@@q @@@A@@ !@d&@+*@y/@4@8@=@[B@V8G@]"L@OQ@V@+[@E`@je@Pj@"o@nu@wYz@|@@@ۇ@7@@@@]@\@@Ě@u@%@XӢ@~@R%@Ȫ@g@@.@$@@-@Ȧ@@X@@5@V@@@f@<@L@O@$E@6,@@@@[1@@MS@@0@@v@@5@@@@i@|@#@@*2@@@q-@lW@ll@ll@lW@q-@@@*2@@#@|@i@@@@5@@v@@0@@MS@@[1@@@@6,@$E@O@L@<@f@@@V@5@@X@@Ȧ@-@@$@.@@g@Ȫ@R%@~@XӢ@%@u@Ě@@\@]@@@@7@ۇ@*,@~@|@wYz@nu@"o@Pj@je@E`@+[@V@OQ@]"L@V8G@[B@=@8@4@y/@+*@d&@ !@@A@@@q @@@@?ރ?(?`?>??n3??j?bĻ???y??D?P˘?u?rC?-4?G?~?u?l?c?@[?R?J?JC?L;?,4?9-?,&??T?? ?,?P?P>OV>w>?i ??c?RO?#?*?[1?8?g@?;H?W P?g;X?i`?SWi?Fr?v{?t?(P?M?m?K?F?ß?M?@@-?l?$?{X???9?\?V,??D?l@@ @@l@6%@f@@$@D(@{-@-1@@6@k:@?@yD@;RI@7N@F)S@&X@.]@ZAb@]g@l@q@Lv@"|@@]V@|@q@M@#@@M@o@@`J@@@66@%ԥ@9n@@”@, @@$@@E @u@վ@,@y@@@"@D@^Z@fc@W_@M@.@@@v@v@.@[1@@@S@J@e@@@8@v@!x@0@@c@I@kF@ @@@6@6@@@ @kF@I@c@@0@!x@v@8@@@e@J@S@@@[1@.@v@v@@@.@M@W_@fc@^Z@D@"@@@y@,@վ@u@E @@$@@, @”@@9n@%ԥ@66@@@`J@@o@M@@#@M@q@|@]V@@"|@Lv@q@l@]g@ZAb@.]@&X@F)S@7N@;RI@yD@?@k:@@6@-1@{-@D(@$@@f@6%@l@@ @@l@D??V,?\?9???{X?$?l?-??Y?M?ß?F?K?m?M?(P?t?v{?Fr?SWi?i`?g;X?W P?;H?g@?8?[1?*?#?RO?c??i ??w>OV>z>w>96?????!?E(?R//?R6?߯=?6HE?M?.U?}]?8 f?n?w???g?R? `?ԏ?N?W??׬?匰?琶??i?$v?K ???e?)? ??y @@@ @o@@4@v@!@F+&@2*@b/@s3@L8@<@A@zF@NK@O.P@U@Z@_@d@,i@Gn@4js@x@}@{@^@@zV@.@e@9@ړ@z@H@(@P@@|@ @@!@ͣ@, @.@N@m@̹@3$@r@@@#@H@b@p@ur@:g@N@6(@@"@]@@@N@Ut@Q@@S@z@I@J@t@\@V%@@?|@ @σ@}@:@!x@@]@]@@!x@:@}@σ@ @?|@@V%@\@t@J@I@z@S@@Q@Ut@N@@@]@"@@6(@N@:g@ur@p@b@H@#@@@r@3$@̹@m@N@.@, @ͣ@!@@ @|@@P@(@@@@9@e@.@zV@@^@{@}@x@4js@Gn@,i@d@_@Z@U@O.P@NK@zF@A@<@L8@s3@b/@2*@F+&@!@v@4@@o@ @@@y @? ?)?e???K ?$v?i??琶?匰?׬??W?N?ԏ? `?R??g??w?n?8 f?}]?.U?M?6HE?߯=?R6?R//?E(?!?????96?w>z>h>>P?{? ??R?<?%?c,?A3?M:?nB?&J?R?wJZ?_b?Hgk?Ut?}?y? S?M?\j?'?q ??5????4?? ??4o?W? d? ??Z^?@p@ @@@@A0@r@#@+&(@,@1@S5@>:@8>@C@^H@V,M@WR@ V@[@`@%e@Rj@o@3t@mz@9@/@zĄ@Z@@@ @@N@@>v@/@^@M @~@p*@@!@”@@g@ƴ@@Xl@;@@!@I@g@y@V@z@!h@~H@;@@@`=@Y@]@@=@@Z@@[1@A@7@@+@@@g}@@i@p @@@:@t9@M@M@t9@:@@@p @i@@g}@@@+@7@@A@[1@@Z@@=@@]@Y@`=@@@;@~H@!h@z@V@y@g@I@!@@;@Xl@@ƴ@g@@”@!@@p*@~@M @^@/@>v@@@@ @@@Z@zĄ@/@9@mz@3t@o@Rj@%e@`@[@ V@WR@V,M@^H@C@8>@>:@S5@1@,@+&(@#@r@A0@@@@ @p@@Z^?? ? d?W?4o?? ??4?@@@5??q ?'?\j?M? S?y?}?Ut?Hgk?_b?wJZ?R?&J?nB?M:?A3?c,?%?<?R?? ?{?P?>h>0>+>3>?P ???o?c#?*?R1?.8?ӎ??)G?N?vW?u__?g?p?Sy?X?1O?7?T@?Fk?4?e'??m?D?8??\????4? ??{ ?CA?՛?y @)@Ѽ@@ @A@@@B@X!@%@ *@w.@2@}7@<@@@lhE@#J@N@ջS@X@p{]@hb@]g@&Zl@/]q@fv@t{@/C@΂@YZ@@7u@@S@@@1@ȸ@K=@@;<@@p*@@@g@į@@h@@@ @J@j@X@͊@@l|@b@;@@@uu@|@m@*@@@Q@ޒ@@@@@Q@@h@@@?@ݵ@@g@@@@@@@g@@ݵ@?@@@h@@Q@@@@@ޒ@Q@@@*@m@|@uu@@@;@b@l|@@͊@X@j@J@ @@@h@@į@g@@@p*@@;<@@K=@ȸ@1@@@@@7u@@YZ@΂@/C@t{@fv@/]q@&Zl@]g@hb@p{]@X@ջS@N@#J@lhE@@@<@}7@2@w.@ *@%@X!@B@@@A@@ @Ѽ@)@y @՛?CA?{ ?? ?4????\?@@@?e'?4?Fk?T@?7?1O?X?Sy?p?g?u__?vW?N?)G?ӎ??.8?R1?*?c#?o???P ??3>+>0>)]>6{>D>??~P?EP?f? ?'?T[.?>f5?f5?T[.?'? ?f?EP?~P???D>6{>)]>(>2>>?'g? ??[ ?n?`$?Щ+?2?9?A?H?@@@ki?1r?D5{?e2>(>9>>.>հ>-H? ?Է?ȹ??W"?O(?\/?"6?>?E?@@@e?^n?h>w?A.?܄?A?ԙ?ب?ؘ?0)?? .??Ÿ??6??b??"?5D?'?V,?Q?N?@B@ @ @@2@4@@SG"@&@*@b/@3@D7@ef<@@@yE@uJ@N@0`S@X@\@2a@Yf@'k@o@t@-y@)~@@#@@H@r@ߍ@aK@@-@:@@K=@^@@@@w@ @G-@X@{@.@L@@@@@b@,2@@@TV@W@V@@p@@$@:g@@@@@3@ԙ@e@@@]@@Q@@@C4@Z@m@m@Z@C4@@@Q@@]@@@e@ԙ@3@@@@@:g@$@@p@@V@W@TV@@@,2@b@@@@@L@.@{@X@G-@ @w@~@66@@^@K=@@:@-@@aK@ߍ@r@H@@#@@)~@-y@t@o@'k@Yf@2a@\@X@0`S@N@uJ@yE@@@ef<@D7@3@b/@*@&@SG"@@4@2@@ @ @B@@N?Q?V,?'?5D?"??b??6??Ÿ?? .??0)?ؘ?ب?ԙ?A?܄?A.?h>w?^n?e?LW]?.U?.@M?E?>?"6?\/?O(?W"??ȹ?Է? ?-H?հ>.>>9> >eF>xC>P>}&??f ?#P?Dk?W?X;&?>,?3?;?]B?@@@b?Yj?|Bs?:|??Xs?M?G? b???(t?/?Dϱ?}?뮽??y?w???i?Q?Y?.?/e@@q@2 @ @@@|@@#@ (@K,@N0@4@6]9@=@JB@F@-`K@:O@kT@ @Y@]@sb@]g@l@p@,?X;&?W?Dk?#P?f ??}&?P>xC>eF> >P>>T>c>?zs? ??O??q#?*?0?7?X+??9F?KN?P1V?'Q^?f?DBo?x?\? 9?? ?? ?QR?R?v@(@@%@T@|@ŝ@@@Ȫ@Ѭ@Ѯ@XȰ@#@@qo@<@'@;@Z@@@@y@@5@l|@z@@@@@]@ֳ@3y@C-@@`@@M@L@[@6(@L@_@_@L@6(@[@L@M@@`@@C-@3y@ֳ@]@@@@@z@l|@5@@y@@@@Z@;@'@<@qo@@#@XȰ@Ѯ@Ѭ@Ȫ@@@ŝ@|@T@%@@(@>v@1@@@aK@#@d@J@#@@;@@9{@Pv@q@l@:h@c@6^@DHZ@jU@OQ@L@H@ȋC@?@:@P6@1@-@v)@E%@!!@ @@@@4 @c @j@@-?g?w]?r?G??s? ?? ?G???T>>P>dd>a>2a>`>A>96?1?u?]?v? ?b?'?-?4?(;?JC?qJ?:R?+Z?b?>k?Ss?!|???<~?m?|?;??e?a??n?\?j??A?]U?>??]?~I?@T?|}?hb@@ @x@@Pn@g@l@"@&@*@ /@A3@7@;@C@@D@I@M@R@V@+[@_@Ud@h@m@.r@v@t{@ @\@{@@J@L@ߍ@%@h@@@H@`J@u@D@&@ ң@@@Q@@Э@{@揱@_@$@8޶@@-@»@J@0ž@,2@@@#@TV@y@@@@ i@;@@@N@]@^Z@@f@:g@*@'@(@(@@*@:g@f@@^Z@]@N@@@;@ i@@@@y@TV@#@@@,2@0ž@J@»@-@@8޶@$@_@揱@{@Э@@Q@@@ ң@&@D@u@`J@H@@@h@%@ߍ@L@J@@{@\@ @t{@v@.r@m@h@Ud@_@+[@V@R@M@I@D@C@@;@7@A3@ /@*@&@"@l@g@Pn@@x@ @@hb@|}?@T?~I?]??>?]U?A??j?\?n??a?e??;?|?m?<~???!|?Ss?>k?b?+Z?:R?qJ?JC?(;?4?-?b?'? ?v?]?u?1?96?A>`>2a>a>dd>>>k>g?>j>j?'g?k ?,?[??b$?*?1?8???\G?N?V?t^?7g?žo?x??[??k??M?6?ʌ??떮?LK?C??%?{X?k??̫?Z?w(?a?>?"@%@u@4 @+@O@@@@#@c'@j,@R00@i4@8@<@ OA@E@uJ@-N@jR@kW@[@l`@d@l}i@ n@r@&w@t{@!@@h@@@@r@i@@@N@z@@Ě@@@d@ @z @@@ת@@ @M@# @@c@@@E @x@5@$A@@E@@X@#@#@@W@@V@X.@v@W@b@;@ @@@3@D@D@3@@@ @;@b@W@v@X.@V@@W@@#@#@X@@E@@$A@5@x@E @@@c@@# @M@ @@ת@@@z @ @d@@@Ě@@z@N@@@i@r@2@#@{@@h@!@t{@&w@r@ n@l}i@d@l`@[@kW@jR@-N@uJ@E@ OA@<@8@i4@R00@j,@c'@#@@@@O@+@4 @u@%@"@>?a?w(?Z?̫??k?{X?%??C?LK?떮??ʌ?6?M??k??[??x?žo?7g?t^?V?N?\G???8?1?*?b$??[?,?k ?'g?j?j>g?>k>>>>>s>>>n>? ?G?Y+?C??!?,'?.?5?I>>s>>>+x>YQ>z>>7>>?!?ۻ ?z?|??$?+?K2?>9?g@?G?dXO?#W?m%_? `g?o?x?˳?D??꾎?ب?ذ? ם??~??ɟ?%^?:?!6?O?,??P???Y?]A?"@/@zO@ @ձ@Ov@;G@@$@ @"@&@ *@1.@V:2@`6@W:@&>@mC@IG@K@6O@f&@ӫ@v@U@j@@k@@O@@۸@E @O0@D@J@$A@v(@>@E@X@G(@@G@@#@x@@@@#@#@@@@x@#@@G@@G(@X@E@>@v(@$A@J@D@O0@E @۸@@O@@k@@j@@@ӫ@>&@9n@5@@ @D.@aH@Z@Ke@h@e@\@M@9@ @@X@ @@h@;@ @t{@XQw@r@n@{j@=e@Va@E\@X@f@W:@`6@V:2@1.@ *@&@"@ @@$@;G@Ov@ձ@ @zO@/@"@]A?Y???P??,?O?!6?:?%^?ɟ??~?? ם?ذ?ب?꾎??D?˳?x?o? `g?m%_?#W?dXO?G?g@?>9?K2?+?$??|?z?ۻ ?!??>7>>z>YQ>+x>">J>u>{>6t>{k> >{?f/ ?4?ȹ??"?p(?/?%5?@@{>u>J>">/,>S>>>P!>>> =??5 ????U%?u+?h2?$o9?i@?G?dXO?vW?^?#g?|o?x?p??h?O? )??H3?Ed??Y?t?M???x?K ?B???Ւ?Q:??@?h@@̆ @X( @@@S@#@@#@'@+@/@3@U7@D;@@@~5D@^H@L@;P@T@N-Y@@h]@a@e@{j@D\n@r@v@9{@9@@Yȃ@م@@@.@#@@@@ړ@ĕ@@@W@$@@ڢ@T@@@_.@@@4@9@ @g@{@Q@*@@@>>S>/,>>>[>{>C>wh>T>2>?O ?4?? ?:"?(?R//?5?T>@@{>[>>> >E>#>dd>~> >>>"??8s ?)?T?f!?c%?u+?y2?O9?dV@?G?N?ƠV?w^?f?n?h>w??i???\j?HM?hL?g?r?@@?V?\?@@ٛ@K=@w՝@c@@b@ ң@e6@V@ܧ@@~R@z@ӕ@ͣ@J@ @{@gR@@Բ@~@@L@$@@)@ @@@@@`ζ@8޶@8޶@`ζ@@@@ @@)@@$@L@@~@Բ@@gR@{@ @J@ͣ@ӕ@z@~R@@ܧ@V@e6@ ң@b@@c@w՝@K=@ٛ@@>@@@@%@XN@p@7@q@@zĄ@΂@Ӏ@}@-y@w?n?f?w^?ƠV?N?G?dV@?O9?y2?u+?c%?f!?T?)?8s ??"?>> >~>dd>#>E> >A>rM>>~C>0>k>h>>?BE?W ?M?? ?,"?](?/?5?I_@+"@Y%@R)@-@b1@D5@-9@I=@ A@E@H@L@P@T@X@E\@`@d@h@l@p@t@x@˥|@/C@/@^@|@ۇ@̵@4@X@ @@@N@o@}@3@Ě@J@ǝ@:@ڢ@E@R@<@%ԥ@@R%@;@C@>?@G-@ @@J@?@C@;@R%@@%ԥ@<@R@E@ڢ@:@ǝ@J@Ě@3@}@o@N@@@ @X@4@̵@ۇ@|@^@/@/C@˥|@x@t@p@l@h@d@`@E\@X@T@P@L@H@E@ A@I=@-9@D5@b1@-@R)@Y%@+"@>_@@@k[@@4 @@`8@@?M'? ??;?p?B?[/?6?~X???a???Mb?D?B?`\?ő??1O?ց?z?pr?!j?b?$Z?tR?J?C?@@/?](?,"? ??M?W ?BE??>h>k>0>~C>>rM>A>>=>>r%>\> >'M>Y>D>â?\?8s ????*%?+?A2?8?B??WF?KN?U?ܐ]?݀e?m?u?~?p?#?&?m?:?#?e'?`F??կ?E?к?v?7??f??Y>'M> >\>r%>>=>>4>A>> >ʝ>{>ߦ>O >>?9?P ?(?@@@J(?.?k'5?(;?B?&J?9Q?Y?`?%h? q?my???g??!?5?>?=???L???V?;????"???o??V?B?K@@ @Q @@@@@V@"@ &@b*@1.@1@S5@Gm9@;=@ A@D@|H@L@sdP@f&@W@@\@9@@t@G-@3<@3<@G-@t@@9@\@@W@>&@š@ @9n@w@@8@\a@|@%@ތ@#@8k@aH@@@/@K@@[@o@@'@y@ @Zs@ Ҍ@)@1z@:ć@@@~@@}@mz@fv@r@n@'k@]g@c@_@[@X@f?5?!???g??my? q?%h?`?Y?9Q?&J?B?(;?@@J(?!???(?P ?9??>O >ߦ>{>ʝ> >>A>4>ul>>ֻ>>Z>C >F>'M>z>>Ӏ?F?5 ?@@@$?*?s1?8?>?F?.@M?T?tK\? d?l?Ut?;|?m???3? ?S??#?Ǩ?? R?н?C???Pi?Q?R?Ak? ??>??ڜ@I@C@ @v@@@i@}@@-E#@&@k*@`;.@11@S5@6]9@I=@@@D@^H@]"L@6O@~S@kW@+[@6^@sb@Yf@3 j@Fm@/]q@3t@x@"|@|@D@J@ @@Q@@4@h@@%@y@(@t@yѕ@t$@8m@w@ޚ@/@$@M5@:@3@M @E@XӢ@Q@Q@-@@p*@5@@^@ܧ@R%@_@k@@@@@@@k@_@R%@ܧ@^@@5@p*@@-@Q@Q@XӢ@E@M @3@:@M5@$@/@ޚ@w@8m@t$@yѕ@t@(@y@%@@h@4@@Q@@ @J@D@|@"|@x@3t@/]q@Fm@3 j@Yf@sb@6^@+[@kW@~S@6O@]"L@^H@D@@@I=@6]9@S5@11@`;.@k*@&@-E#@@}@i@@@v@ @C@I@ڜ@?>?? ?Ak?R?Q?Pi???C?н? R??Ǩ?#??S? ?3???m?;|?Ut?l? d?tK\?T?.@M?F?>?8?s1?*?$??)??5 ?F?Ӏ?>z>'M>F>C >Z>>ֻ>>ul>ר>@B> >>=>ʝ>i>>@@2>?ZG ?@@@>!?j'?-?4L4?;?A?H?rBP?jW?u__?7g?DBo?~w??G??I5?qґ?%?dY?(C?`F?b?И??O?Kп?ji?? ????'?V,?|?Z?.@t@@C @i@@]@@*Y@E@o#@'@2*@`;.@1@܃5@-9@<@y@@~5D@!?C??l?H?ZG ??2>>>>i>ʝ>=>> >@B>ר> H>X>>ֻ>>#7>>a>@@1>}&?\?ۻ ?E???#?*?}~0?7?=?D?K?f+S?Z?af> >a>>#7>>ֻ>>X> H>g>ר>2>-з>>>~C>(>@@u> > v? ?"?5?v?_ ?t&?Y,?Z$3?9?i@?nG? N?U?}]?a1e?m?!)u?m}?m?oD?寋?3?=Д??QR?7?5?^K? y?h?<?E?9?ƻ?s?7A?N$?`?(?~I?v}?C?@C@@h @@i@@@Q'@b@@o#@&@b*@-@b1@4@l8@D;@N|?@mC@F@uJ@M@OQ@kT@X@[@^@hb@%e@,i@l@"o@s@Pv@y@˥|@@de@@]@΅@[7@@@A@@ƍ@^@%@CF@4\@sg@g@\@zF@t$@@@>v@y#@Ě@W@ޛ@`X@Ĝ@$@u@ @@@M5@C@C@M5@@@ @u@$@Ĝ@`X@ޛ@W@Ě@y#@>v@@@t$@zF@\@g@sg@4\@CF@%@^@ƍ@@A@@@[7@΅@]@@de@@˥|@y@Pv@s@"o@l@,i@%e@hb@^@[@X@@@M@uJ@F@@N|?@D;@l8@4@b1@-@b*@&@o#@@b@@@@i@@h @@C@@C?v}?~I?(?`?N$?7A?s?ƻ?9?E?<?h? y?^K?5?7?QR??=Д?3?寋?oD?m?m}?!)u?m?a1e?}]?U? N?nG?i@?9?Z$3?Y,?t&?_ ?v?5?"? ? v? >u>?>g>(>~C>>>-з>2>ר>g>|8>h+>]>Nг>=>}>n>?> >P!>>G.>8?ø?k ?z??o?"?O(?>/?5?W?dt?]@D@Ѽ@ @:@@:@Q'@ҁ@E@-E#@ &@\*@-@50@i4@U7@Q;@&>@:B@E@I@L@:O@0`S@V@u"Z@p{]@`@d@]g@Pj@m@p@&t@&w@.z@D)}@ @{@@.F@@#@:@1z@?@ދ@@@,@b2@-@@j@ړ@@i@o@Ȗ@e@@nz@@[@ȸ@@K@@?@Ě@wњ@wњ@Ě@?@@K@@ȸ@[@@nz@@e@Ȗ@o@i@@ړ@j@@-@b2@,@@@ދ@?@1z@:@#@@.F@@{@ @D)}@.z@&w@&t@p@m@Pj@]g@d@`@p{]@@V@0`S@:O@L@I@E@:B@&>@Q;@U7@i4@50@-@\*@ &@-E#@E@ҁ@Q'@:@@:@ @Ѽ@D@]@dt?>??{ ? ?0 ?^I???A??S??쾳?떮????q?-?S??ѥ?R? ?w?o?g?4`?X?QQ?&J?2(C?W/?O(?"?o??z?k ?ø?8?G.>>P!> >?>n>}>=>Nг>]>h+>|8>ù>c>ώ>zׯ>`>N,>W;>[>)> >M7>.>n>??)D?/?Dk?<?8%?_+?[1?.8?>?߮E?L?S?@[?b?Yj?pr?az?f???\?ܒ?t?#??sǥ??zƯ??C?l??H???v?,?1????y??!@@`@% @~F@@@@ @*Y@@"@}V&@R)@{-@lm0@3@m.7@W:@=@ OA@D@H@-`K@N@WR@PU@X@[@_@ZAb@je@(h@!k@n@q@Zt@w@)oz@4?}@@.Z@@ @7@p@@Lj@@k@O@@#@@@w@q_@@Β@9t@ @5@-@@o@S@@@\@>@X@e@e@X@>@\@@@S@o@@-@5@ @9t@Β@@q_@w@@@#@@O@k@@Lj@@p@7@ @@.Z@@4?}@)oz@w@Zt@q@n@!k@(h@je@ZAb@_@[@X@PU@WR@N@-`K@H@D@ OA@=@W:@m.7@3@lm0@{-@R)@}V&@"@@*Y@ @@@@~F@% @`@@!@?y????1?,?v???H??l?C??zƯ??sǥ??#?t?ܒ?\???f?az?pr?Yj?b?@[?S?L?߮E?>?.8?[1?_+?8%?<?Dk?/?)D???n>.>M7> >)>[>W;>N,>`>zׯ>ώ>c>ù>A>Q>ZǤ>6>OD> >> >Q>D>>6>P>?? ?s???!?'?x-? 4?7:??@A?;H?"O?qVV?D]?>Ee?m?qt?|??ۆ?+?ő?T??N???ի?qٰ??!?f??],?ĭ?B???r?Q?CA?]A?:Q?@@<@% @:@i@W@@}@V@ś"@Y%@4-)@x,@/@3@`6@9@<@C@@ȋC@F@uJ@OM@P@ջS@ V@Z@.]@E`@rTc@Yf@Ti@El@"+o@r@t@w@Cz@|@3|@@;@"m@@綅@Ά@ۇ@߈@ى@JɊ@~@@X@@8֎@䃏@%@@CF@Wđ@.6@@@'A@@'@ړ@1@@@1@ړ@'@@'A@@@.6@Wđ@CF@@%@䃏@8֎@@X@@~@JɊ@ى@߈@ۇ@Ά@綅@@"m@;@@3|@|@Cz@w@t@r@"+o@El@Ti@Yf@rTc@E`@.]@Z@ V@ջS@P@OM@uJ@F@ȋC@C@@<@9@`6@3@/@x,@4-)@Y%@ś"@V@}@@W@i@:@% @<@@@:Q?]A?CA?Q?r???B?ĭ?],??f?!??qٰ?ի???N??T?ő?+?ۆ??|?qt?m?>Ee?D]?qVV?"O?;H??@A?7:? 4?x-?'?!???s? ???P>6>>D>Q> >> >OD>6>ZǤ>Q>A>Г>N>>>40>>tU>@J>J>>n>%>U>A>??) ?,?[ ??%#?)?/?R6?w?R?Ƀ?u?M??*?S? `???jӬ?Dϱ???F???\?b? ??.?\?x??.?|}?k@@`@ @@6@]@i@@@+"@S%@D(@+@ /@V:2@#t5@8@;@?@JB@yE@H@K@N@WR@U@&X@+[@h(^@ a@d@f@$i@l@?o@q@)t@&w@-y@"|@)~@o@D@@＃@zĄ@~…@@@@zV@X!@X@L@@@Tތ@q@#@Zs@@E@Ĝ@@%@W@k}@w@@@w@k}@W@%@@Ĝ@E@@Zs@#@q@Tތ@@@L@X@X!@zV@@@@~…@zĄ@＃@@D@o@)~@"|@-y@&w@)t@q@?o@l@$i@f@d@ a@h(^@+[@&X@U@WR@N@K@H@yE@JB@?@;@8@#t5@V:2@ /@+@D(@S%@+"@@@i@]@6@@ @`@@k@|}?.??x?\?.?? ?b?\??F????Dϱ?jӬ??? `?S?*??M?u?Ƀ?R?h>w?Wo?4g? `?X?vQ?lJ?C?U>%>n>>J>@J>tU>>40>>>N>Г>Kg>޾>P>a>%>`k>>> >>D>k>>>2>{? ?/?s?(3??%?Y+?A2?~8?; ??E?`L?S?Z?Cb?i?tq?my??܄??Z?.?-?4?W? ?2֨??t?}?bɼ??V9??4?l?b??;?J?ؿ?Η?|}?@@Ѽ@h @@@@@=@>_@!@S$@'@*@1.@C1@i4@7@:@=@@@D@G@#J@V,M@O.P@F)S@V@Y@[@^@2a@Ud@ g@$i@&Zl@n@rq@s@Pv@x@{z@D)}@O@@@@@@YZ@*@#@@{]@H@@P-@?@)@L@.@*L@,@ Ҍ@@'@@@WL@WL@@@'@@ Ҍ@,@*L@.@L@)@?@P-@@H@{]@@#@*@YZ@@@@@@O@D)}@{z@x@Pv@s@rq@n@&Zl@$i@ g@Ud@2a@^@[@Y@V@F)S@O.P@V,M@#J@G@D@@@=@:@7@i4@C1@1.@*@'@S$@!@>_@=@@@@@h @Ѽ@@@|}?Η?ؿ?J?;??b?l?4??V9??bɼ?}?t??2֨? ?W?4?-?.?Z??܄??my?tq?i?Cb?Z?S?`L?E?; ??~8?A2?Y+?%??(3?s?/? ?{?2>>>k>D>> >>>`k>%>a>P>޾>Kg>>@@D>@#>>>T>->>>y>> >'>P>?? ?"??2?!?'?-?,4?7:?A?G?N?U?~\?[Wd?k?ٖs?v{??ۅ? ?O?ש???F5?B?y?x?a?]?:m?E?? ?ua??C?? d? ?ؿ?.?:Q?!@D@@~ @i@@@@@@@o @#@O&@ *@z-@R00@A3@P6@6]9@ef<@k?@lB@lhE@^H@NK@7N@OQ@S@V@wY@=I\@^@a@GAd@f@Ti@k@2n@kp@r@nu@;w@Uy@H^{@&U}@9@텀@de@;@@Yȃ@@*,@΅@e@#@q@@Q@H@H@J@@̵@ى@@u@u@@ى@̵@@J@H@H@Q@@q@#@e@΅@*,@@Yȃ@@;@de@텀@9@&U}@H^{@Uy@;w@nu@r@kp@2n@k@Ti@f@GAd@a@^@=I\@wY@V@S@OQ@7N@NK@^H@lhE@lB@k?@ef<@6]9@P6@A3@R00@z-@ *@O&@#@o @@@@@@@i@~ @@D@!@:Q?.?ؿ? ? d??C??ua? ??E?:m?]?a?x?y?B?F5???ש?O? ?ۅ??v{?ٖs?k?[Wd?~\?U?N?G?A?7:?,4?-?'?!?2??@@??P>'> >>y>>>->T>>>@#>D>>>\7>>>@@v>[+>>F>>\W>>>g>>>6t>.>->z?? ??|?H?#?r)?/?9#6?.>6t>>>g>>>\W>>F>>[+>v>t>>>/\>B>&_>a>=>>>~=>>l>?c>Y>T>T>v>>?D?K?R?Y?`?h?=o?h>w?.?@A@yD@V8G@tI@QL@XDO@Q@sT@V@xY@[@N^@&`@ b@/e@]g@l}i@k@m@~o@/]q@*s@t@ɐv@'x@-y@{@z|@}@~@ @@ @{@@;@)@΂@@?4@]V@@@x@"m@]V@?4@@΂@)@;@@{@ @@ @~@}@z|@{@-y@'x@ɐv@t@*s@/]q@~o@m@k@l}i@]g@/e@ b@&`@N^@[@xY@V@sT@Q@XDO@QL@tI@V8G@yD@A@8>@<@=9@`6@3@N0@-@*@c'@$@"@@#@4@;G@k[@q@Q @ @@@@dt?y?CA?x?;??]i???#?p?Y?S?%^?/z???:?ß? ??B?k???w?=o?h?`?Y?R?K?D?d>?7?1?Щ+?%??M??y?ZG ?9?v>T>T>Y>?c>l>>~=>>>=>a>&_>B>/\>>ֈ>̎>p>Z>~>Dɨ>zׯ>R!>>l>gp>t>9>>; >>]>j?{?J ?I/?? ?!?by'?Gj-?3?9?l$@?pF?cM?>T?@[?jb?~i?5q?x?O?G? S?r?s? ?B? ?,?T?^??ش???Č????$?C??\?Q??>?C?`@t@C@ @? @@f@xw@S@A0@ @O @#@&@v)@K,@b/@11@ݷ4@}7@>:@<@?@[B@E@G@|5J@L@XDO@Q@*T@V@X@+[@@h]@L_@Ka@c@%e@g@i@Pyk@;m@n@kp@r@fs@3t@Pv@w@x@ty@z@D{@˥|@k}@~@I~@9@|@@!@@@/C@8@!@@|@9@I~@~@k}@˥|@D{@z@ty@x@w@Pv@3t@fs@r@kp@n@;m@Pyk@i@g@%e@c@Ka@L_@@h]@+[@X@V@*T@Q@XDO@L@|5J@G@E@[B@?@<@>:@}7@ݷ4@11@b/@K,@v)@&@#@O @ @A0@S@xw@f@@? @ @C@t@`@C?>??Q?\??C?$????Č???ش??^?T?,? ?B? ?s?r? S?G?O?x?5q?~i?jb?@[?>T?cM?pF?l$@?9?3?Gj-?by'?!? ??I/?J ?{?j?>]>; >>9>t>gp>l>>R!>zׯ>Dɨ>~>Z>p>̎>ֈ>>>&t>D>/I>F>>>~>ƙ>>=>EU>d>v>D>>+>>K?? ??-?׮?T#?? )?/?k'5?c;?`A?EOH?N?U?7\?c?>k? r?LFz?????#;?9x?Ǚ?0)??!?ӷ?_??޹????#?k??b?.?r???v}??.@I@@n @4 @@@@Y@@$@s@@"@E%@ (@*@-@?0@2@S5@L8@k:@=@~"@@B@#5E@MG@#J@L@N@=Q@ӄS@U@XW@Z@#\@h(^@`@b@{c@Ve@]g@+i@Pj@l@m@n@9p@rq@r@s@Zt@u@fv@&w@ w@hx@x@Uy@-y@y@mz@.z@.z@mz@y@-y@Uy@x@hx@ w@&w@fv@u@Zt@s@r@rq@9p@n@m@l@Pj@+i@]g@Ve@{c@b@`@h(^@#\@Z@XW@U@ӄS@=Q@N@L@#J@MG@#5E@B@~"@@=@k:@L8@S5@2@?0@-@*@ (@E%@"@@s@@$@Y@@@@4 @n @@I@.@?v}???r?.?b??k?#????޹??_?ӷ?!??0)?Ǚ?9x?#;?????LFz? r?>k?c?7\?U?N?EOH?`A?c;?k'5?/?? )?T#?׮?-?? ??K?>+>>D>v>d>EU>=>>ƙ>~>>>F>/I>D>&t>>Ey>>Ƈ>> >>Y|>1>>G>>uI>r%>?>>2>N >;*>E?? ?"?]??<?$?*?0?w6?N >2>>?>r%>uI>>G>>1>Y|>> >>Ƈ>>Ey>r>!}>NT>1 >>s>i>>⳩>F>>rM>W>>>`>>z>>??8 ???1?2 ?)X&? ,? 2?8?T>?D?c-K?Q?(X?-_?f?Dm?!)u?V|?%?@@?R?G??͞?)??/?1?46?޹??Y?+? ?4? ??1? ?(?#O?|?@@!@`8@q@ @X( @K@Ov@@@g@ @@SG"@m$@w'@ *@,@b/@-1@4@6@8@a;@g=@@@[B@D@F@H@K@V,M@c2O@m+Q@S@T@V@7X@\5Z@[@@h]@6^@XY`@Ka@c@GAd@je@f@Ѕg@wh@Ti@{j@Rj@Pyk@Kl@l@l@;m@ym@m@Fm@Fm@m@ym@;m@l@l@Kl@Pyk@Rj@{j@Ti@wh@Ѕg@f@je@GAd@c@Ka@XY`@6^@@h]@[@\5Z@7X@V@T@S@m+Q@c2O@V,M@K@H@F@D@[B@@@g=@a;@8@6@4@-1@b/@,@ *@w'@m$@SG"@@ @g@@@Ov@K@X( @ @q@`8@!@B??|?#O?(? ?1?? ?4? ?+?Y??޹?46?1?/??)?@@G?R???r ?%?V|?!)u?Dm?f?-_?(X?Q?c-K?D?T>?8? 2? ,?)X&?2 ?1??@@??>z>>`>>>W>rM>>F>⳩>>i>s>>1 >NT>!}>r>l>w>> >B>9>c>>\V>!>A%>a>$>> w>> >.>>>#??t ??3??"?v'?Ny-?{b3?$o9?m??mE?7kL?S?;Y?i`?Fg?n?(v?}?ʖ?r?^?\?\j?%?4?B?E??/?匰???S?i???b?B?,?0 ?`? ?V,?@@dt?@]@@̆ @H @ձ@F@O@Pn@@|@@ @(#@%@+&(@2*@{-@y/@1@:4@6@8@ !;@[=@?@A@C@JE@?V,? ?`?0 ?,?B?b???i?S???匰?/??E?B?@@\j?\?@@@}?(v?n?Fg?i`?;Y?S?7kL?mE?m??$o9?{b3?Ny-?v'?"??3??@@#?>>.> >> w>>$>a>A%>!>\V>>c>9>B> >>w>l>@f>p>"{>>Z>i>j>>>ǥ>nz>>H˼>uI>>>f&>>g?>)>S>_?4 ?+?`C?|??T#?O(?.?`4?b:?.@?G?\M?T?Z?a?h?žo?-v?_~?m?Æ??ԙ?#?K?Ӛ? ?E??a?_?ش?%^??E?V9?\?ĭ?v?^I?N$? ?'???J??@m@@u@ @~ @+@@@@4@Dt@@X!@#@F+&@D(@+*@|;-@/@_1@ 4@@6@l8@W:@<@>@@@B@D@zF@AMH@uJ@K@}sM@O@P@R@ӄS@%T@)/V@kW@X@-Y@۹Z@°[@\@@h]@h(^@^@p_@=_@l`@`@ a@Va@}a@2a@2a@}a@Va@ a@`@l`@=_@p_@^@h(^@@h]@\@°[@۹Z@-Y@X@kW@)/V@%T@ӄS@R@P@O@}sM@K@uJ@AMH@zF@D@B@@@>@<@W:@l8@@6@ 4@_1@/@|;-@+*@D(@F+&@#@X!@@Dt@4@@@@+@~ @ @u@@m@@?J???'? ?N$?^I?v?ĭ?\?V9?E??%^?ش?_?a??E? ?Ӛ?K?#?ԙ??@@@-v?žo?h?a?Z?T?\M?G?.@?b:?`4?.?O(?T#??|?`C?+?4 ?_?S>)>g?>>f&>>>uI>H˼>>nz>ǥ>>>j>i>Z>>"{>p>@f>Mq`>Lj>t>>>>S>> Ȝ>9>>>-з>>9>^>W>> >5>T>?.?Ok ?`?v?ȭ??4$?*?/?5?;?*A?;H?AN?1 U?[?x~b?ki?zp?w?~?5?0?֊?꾎??Y?Ӛ?B?)?j?ӷ??/z??:m???],????7A? ?? ?o?~I?M'?}?B?h@)@zO@l @4 @x@@@2@S@m@B@r@!@$@d&@|(@+*@z-@K/@r1@S3@S5@7@9@;@=@k?@M>A@mC@D@iF@H@ I@K@L@=M@XDO@P@Q@$R@S@T@U@V@W@KX@X@wY@Z@Z@Z@+[@d[@[@[@[@[@d[@+[@Z@Z@Z@wY@X@KX@W@V@U@T@S@$R@Q@P@XDO@=M@L@K@ I@H@iF@D@mC@M>A@k?@=@;@9@7@S5@S3@r1@K/@z-@+*@|(@d&@$@!@r@B@m@S@2@@@x@4 @l @zO@)@h@B?}?M'?~I?o? ?? ?7A????],???:m??/z??ӷ?j?)?B?Ӛ?Y??꾎?֊?0?@@@zp?ki?x~b?[?1 U?AN?;H?*A?;?5?/?*?4$??ȭ?v?`?Ok ?.??T>5> >>W>^>9>>-з>>>9> Ȝ>>S>>>>t>Lj>Mq`>rZ> d>m>|Bx>5s>>/>6>>Rݞ>\V>>6>>Q>O>ʝ>>>|>HD>e>>?ø?O ???d?S ?ގ%?)$+?T0?w6?M@IN@XDO@O.P@1Q@Q@ބR@F)S@ջS@fM@]"L@J@I@oH@G@E@~5D@B@A@N|?@=@<@N:@|8@Ο6@ݷ4@2@;0@q.@,@2*@}(@}V&@ ($@ !@@v@A0@@n@A@@ @4 @ @u@b@/@O@@?/?S? ???Ak???s??H??F??bɼ?]?B??^?!?5?͞?4?K??Iˎ?@@@h?{*x? q? j?Z/c?q\?U?dXO?H?B?e>HD>|>>>ʝ>O>Q>>6>>\V>Rݞ>>6>/>>5s>|Bx>m> d>rZ>GT>]>xg>q>'{>M>ֈ>鎎>w>>ݠ>7]>>D>>l>>˾>(>y>wh>>:>#?F?K ?r???!?k&? ,?1?7?~=?C?I?W P?{V? ]?Mc?Yj?tq?x??y?-??꾎?#?%??9??T??D?a?}??f??A?ƻ?=??R??}??x?Y???"@5t@%@@c @2 @ @?@@@@4@f@@@!@F#@&@ (@ *@j,@-@/@1@3@D5@6@8@N:@;@Fl=@8>@uT@@A@mC@FD@yE@:F@MG@|H@I@(J@-`K@]"L@L@}sM@N@-N@N@XDO@9O@2O@6O@:O@:O@6O@2O@9O@XDO@N@-N@N@}sM@L@]"L@-`K@(J@I@|H@MG@:F@yE@FD@mC@A@uT@@8>@Fl=@;@N:@8@6@D5@3@1@/@-@j,@ *@ (@&@F#@!@@@f@4@@@@?@ @2 @c @@%@5t@"@??Y?x??}??R??=?ƻ?A??f??}?a?D??T??9??%?#?꾎??@@@x?tq?Yj?Mc? ]?{V?W P?I?C?~=?7?1? ,?k&?!???r?K ?F?#?:>>wh>y>(>˾>>l>>D>>7]>ݠ>>w>鎎>ֈ>M>'{>q>xg>]>GT> N>HW>4a>ej>!u>5k>>>Kg>V>v>Ȣ>M>4>>>fk> >{>3>>h>t>^>?@ ?w???!?_\'?C,?h2?N8?3>?w7D?ZJ?P?V?}]? d?j?Rq?x?6?y?K!?֊?ԙ?\j?G?b2?0)?,?:?4T?x?t??!?l??9?{? ?Q?"?@@@@$7C@$D@E@&E@F@V8G@G@^H@GH@@I@ I@I@uJ@|5J@GJ@GJ@|5J@uJ@I@ I@@I@GH@^H@G@V8G@F@&E@E@$D@$7C@:B@-A@@@8>@=@ef<@;@9@=8@v6@K55@3@1@N0@ .@,@+@4-)@1L'@1b%@o#@t!@r@i@X@A@6%@@@A@i@L @ @q@j@hb@"@C?]A?ɽ?Q:??6?;??N8?h2?C,?_\'?!???w? ?1??^>t>h>>3>{> >fk>>>4>M>Ȣ>v>V>Kg>>>5k>!u>ej>4a>HW> N>#H>Q>$Z>pmd>7n>Wx>g>І>Og>t,>!>2F>>%>v>ϸ>y>L>>ڡ>_> >xC>B>zf?? ?)i?#P?U?;x?"?J(?`-?33?8?>?D?qJ?@@z]?[Wd?dk?Dq?x??c?0??\?R??Ǚ? ?ß?a?y??Dϱ??C?S?E???Pi???p?9?:0?Ւ?J?Y?ż?>?|}?@@B@i@ @@ @@o@l@@ @ @@ @@o @ܩ"@}$@H&@ (@)@l+@{-@+.@R00@1@"3@4@Q5@m.7@l8@9@@@@=@>@?@uT@@ A@A@JB@B@HC@C@D@FD@yD@D@D@D@D@yD@FD@D@C@HC@B@JB@A@ A@uT@@?@>@=@<@;@ۿ:@9@l8@m.7@Q5@4@"3@1@R00@+.@{-@l+@)@ (@H&@}$@ܩ"@o @@ @@ @ @@l@o@@@ @ @i@B@@@|}?>?ż?Y?J?Ւ?:0?9?p???Pi???E?S?C??Dϱ??y?a?ß? ?Ǚ??R?\??0?c??x?Dq?dk?[Wd?z]? [W?L Q?qJ?D?>?8?33?`-?J(?"?;x?U?#P?)i? ??zf?B>xC> >_>ڡ>>L>y>ϸ>v>%>>2F>!>t,>Og>І>g>Wx>7n>pmd>$Z>Q>#H>\C>oK>T>d^>xg> bq>{>q >w>>ݓ>֙>f>X>!>>'>>>ʝ>a>\>>Y>P>:??Ok ?/??T?)?c#?̹(?..?ӿ3?$o9?;?? &E?@@ W?]?$kd?dk?Rq?x?h?5?Æ?^??.?9x?B? ??B?2֨?jӬ?qٰ???<?F??ji???f?B?"???J??W?a?@T?-?/e@@*@@Ѽ@ @ @@@>@@@@vt@K@@E@!@SS#@$@&@4(@)@@+@,@1.@y/@;0@ 2@A3@i4@@@@|8@6]9@t.:@k:@;@E<@<@[=@=@1>@>@&>@>@?@l)?@l)?@?@>@&>@>@1>@=@[=@<@E<@;@k:@t.:@6]9@|8@7@6@܃5@i4@A3@ 2@;0@y/@1.@,@@+@)@4(@&@$@SS#@!@E@@K@vt@@@@>@@@ @ @Ѽ@@*@@/e@-?@T?a?W??J???"?B?f???ji?F??<???qٰ?jӬ?2֨?B?? ?B?9x?.??^?Æ?5?h?x?Rq?dk?$kd?]? W?QQ?c-K? &E?;??$o9?ӿ3?..?̹(?c#?)?T??/?Ok ??:?P>Y>>\>a>ʝ>>>'>>!>X>f>֙>ݓ>>w>q >{> bq>xg>d^>T>oK>\C>=>(F>N>W>`>j>lt>W~>*>1 >>y>u>c>>>G>J8>[>S>!?>>g>#>O> >j?s~? ?4?5?ȭ??#?=)?.?,4?9?ӎ??hjE?9bK?vQ?W?]?[Wd?j?tq?{*x?~?m?r??K?#;? ??g?F5? ??ի?zƯ?쾳?h?bĻ?Kп????[/?O?r????W?w(?~I?g?.?N?@@)@p@@ @q @x@@i@A@/@@@X@ @@=P @!@o#@$@d&@'@4-)@*@+@},@H,.@K/@$^0@b1@:Y2@A3@4@4@S5@P6@6@}7@47@l8@8@9@6]9@k9@9@9@9@9@k9@6]9@9@8@l8@47@}7@6@P6@S5@4@4@A3@:Y2@b1@$^0@K/@H,.@},@+@*@4-)@'@d&@$@o#@!@=P @@ @X@@@/@A@i@@x@q @ @@p@)@@@N?.?g?~I?w(?W????r?O?[/????Kп?bĻ?h?쾳?zƯ?ի?? ?F5?g?? ?#;?K??r?m?~?{*x?tq?j?[Wd?]?W?vQ?9bK?hjE?ӎ??9?,4?.?=)?#??ȭ?5?4? ?s~?j? >O>#>g>>!?>S>[>J8>G>>>c>u>y>>1 >*>W~>lt>j>`>W>N>(F>=>`8>y@>QH>UQ>nZ>Sc>im>RVw>fˀ>h>>0>:>j>[+>ˇ>u>Ҷ>D>>#7>>z>k>F>>}>â?!? ?s?5E?(3?<?b$?T)?/?{4?:???E?sK?vQ? W?z]? d?Yj? q?w?_~?ʖ?r ?}??s?B???W????떮? y?ya?O?C?;?7?6?8?=?B?^I?P?V?Z?]?w]?Y?Q? E?J2?y @@@@@ @1e @h6@+@@@6@@i@@$@@@@h@w4 @!@"@R$@%@d&@ (@4-)@D*@N+@K,@|;-@1.@.@]/@lm0@1@1@V:2@ 2@"3@3@3@ 4@:4@Z4@i4@i4@Z4@:4@ 4@3@3@"3@ 2@V:2@1@1@lm0@]/@.@1.@|;-@K,@N+@D*@4-)@ (@d&@%@R$@"@!@w4 @h@@@@@$@i@@6@@@+@h6@1e @ @@@@@y @J2? E?Q?Y?w]?]?Z?V?P?^I?B?=?8?6?7?;?C?O?ya? y?떮????W???B?s??}?r ?ʖ?_~?w? q?Yj? d?z]? W?vQ?sK?E???:?{4?/?T)?b$?<?(3?5E?s? ?!?â?}>>F>k>z>>#7>>D>Ҷ>u>ˇ>[+>j>:>0>>h>fˀ>RVw>im>Sc>nZ>UQ>QH>y@>`8>3>:>ZC>uK>H.T>/3]>@f>")p>uz>l2>r>>>Ip>[o>>>>?>N,>@J>4>>T>>>]*>հ>96??!B ?r?ȹ?.??@$?)?>/?4?T0:?B??E?9bK?QQ? [W?}]?Mc? j?zp?-v?}?%???r?k?|??4? `??sǥ??^K???н?V?v?~X?@o @"@(#@D$@S%@}V&@1L'@4(@)@s)@2*@N+@+@,@{-@-@-@yJ.@ .@.@ /@b/@-/@-/@b/@ /@.@ .@yJ.@-@-@{-@,@+@N+@2*@s)@)@4(@1L'@}V&@S%@D$@(#@"@o @>@C@s@|@@$@@O2@N@j@@o@:@Q @ @ @ZR@@@l@y @Z^?՛?&??V,?Q?r??̫????K ?d#?/?)?@$??.?ȹ?r?!B ??96?հ>]*>>>T>>4>@J>N,>?>>>>[o>Ip>>>r>l2>uz>")p>@f>/3]>H.T>uK>ZC>:>3>E->h5>EO=>}E>bM>V>_> i>r>|>>ֈ>5Q>+>2ə>ǟ>:>N>ײ>8>x>>>W>F>>>?> >?$? ? U????`$?*?\/?4?T0:???hjE?c-K?L Q?V? ]?Z/c?ki?žo?(v?V|?̞?? S??d.?ש?-?S?N???5?{?И? R??к??\?%?x?ƻ?,?Q??>?G?i?'?? ?CA???D?@!@OR@@&@c @) @ @h6@@F@@5@W@@S@@@}@@@>_@r@y @t!@tc"@-E#@$@m$@%@H&@&@w'@|'@o(@X(@4-)@v)@R)@s)@)@ *@ *@)@s)@R)@v)@4-)@X(@o(@|'@w'@&@H&@%@m$@$@-E#@tc"@t!@y @r@>_@@@}@@@S@@W@5@@F@@h6@ @) @c @&@@OR@!@@D???CA? ??'?i?G?>??Q?,?ƻ?x?%?\??к?? R?И?{?5???N?S?-?ש?d.?? S??̞?V|?(v?žo?ki?Z/c? ]?V?L Q?c-K?hjE???T0:?4?\/?*?`$???? U? ?$?? >?>>>F>W>>>x>8>ײ>N>:>ǟ>2ə>+>5Q>ֈ>>|>r> i>_>V>bM>}E>EO=>h5>E->D(>0>C7>Z?>G>VP>Y>M2b>uk>@u>>>&DŽ>(>7>9>G >>1>6>>º>ȥ>>]>n>8> >>;*>2>]?? ??U?_$?u ? %?(*?\/?4?:?ӎ?? &E?qJ?P?{V?q\?x~b?h?n?!)u?b{??G???O?.?*??#??7?ʦ?b???E??V?D???O??k?]U???5D??/x?{ ? ? ???`l?/e@@/@wO@ @u@' @~ @u @g@K@-@@@@;G@s@@<@m@@@@l@a;@@ @X!@ !@"@"@o#@#@ ($@Lo$@S$@%$@$@$@$@$@%$@S$@Lo$@ ($@#@o#@"@"@ !@X!@ @@a;@l@@@@m@<@@s@;G@@@@-@K@g@u @~ @' @u@ @wO@/@@/e@`l??? ? ?{ ?/x??5D???]U?k??O???D?V??E???b?ʦ?7??#??*?.?O???G??b{?!)u?n?h?x~b?q\?{V?P?qJ? &E?ӎ??:?4?\/?(*? %?u ?_$?U?? ??]?2>;*>> >8>n>]>>ȥ>º>>6>1>>G >9>7>(>&DŽ>>>@u>uk>M2b>Y>VP>G>Z?>C7>0>D(>B#>5*>{.2>9>A>J>XR>i[>Dm>w>fˀ>>D>>c>2>->oT>Χ>T(>ֻ>> >=>a>>>>B>#?j? ?;B ?,?|?C??S ? %?*?@@@;??D?ZJ?W P?U?[?a?Fg?Dm?vt?LFz?O?/?*? %?S ?C??|?,?;B ? ?j?#?B>>>>a>=> >>ֻ>T(>Χ>oT>->2>c>>D>>fˀ>w>Dm>i[>XR>J>A>9>{.2>5*>B#>[>%> ,>f>4> ;>{C>*8L>T>]>6f>Tp>y>>> >&[>ӑ>&v>|B>9>[>˩>$$>H˼>>ġ>>0>>z>af>́>zf??z?f ?s??C??u ?`$?@@@$o9?>?w7D?I?dXO?1 U?Z?i`?f?l? r?x?.?m?ۅ??M?ő?ܒ?-???(C?#????c?ش?M?bĻ?:??%?? ?w??NG?? ?W?e?\?(?w]?=??ҽ?E?C?Z@@4@*@@C@u@\ @) @4 @LY @t@@@@Ov@k[@5@@@@Y{@6%@@S@@%O@@@g@@@@"@A0@A0@"@@@@g@@@%O@@S@@6%@Y{@@@@5@k[@Ov@@@@t@LY @4 @) @\ @u@C@@@@@Z@C?E?ҽ??=?w]?(?\?e?W? ??NG??w? ??%??:?bĻ?M?ش?c????#?(C???-?ܒ?ő?M??ۅ?m?.?x? r?l?f?i`?Z?1 U?dXO?I?w7D?>?$o9?,4?/?)?`$?u ?C???s?f ?z??zf?́>af>z>>0>>ġ>>H˼>$$>˩>[>9>|B>&v>ӑ>&[>> >>y>Tp>6f>]>T>*8L>{C> ;>f>4> ,>%>[>>(} >{'>ѷ.>46>=>kE>;N>#V>˛_>&h>r>U{>f> >n[>uђ>Ip>|8>*>*G>>>e>{k>?c> >2>Y>>z>>?{?9 ?8s ?s?|?_$??@@@ӿ3?8?3>?C?H?AN?T?;Y?-_?Ye?>k?5q?h>w?W}??܄?u?+?\?S?=Д?j?dY???`F??a?L?t??%^???j??y?b?ĭ??4?4o??9?`?? ?w(?%? ??y??Z^?@X@-@]@֔@@7@ @ @B @H @ @ @@@q@-@X@@@@@(@@@]@N@2@1 @;G@Ha@Pn@Pn@Ha@;G@1 @2@N@]@@@@(@@@@X@-@q@@@ @ @H @B @ @ @7@@֔@]@-@X@@@?y?? ?%?w(? ??`?9??4o?4??ĭ?b?y??j???%^??t?L?a??`F???dY?j?=Д?S?\?+?u?܄??W}?h>w?5q?>k?Ye?-_?;Y?T?AN?H?C?3>?8?ӿ3?.?T)?@$??_$?|?s?8s ?9 ?{??>z>>Y>2> >?c>{k>e>>>*G>*>|8>Ip>uђ>n[> >f>U{>r>&h>˛_>#V>;N>kE>=>46>ѷ.>{'>(} >>0>#>J">M)>0>8>0?>G>v P>X>1a>j>t>}>lփ>+>D> >vQ>j>>2>U>A>tU>>>*>z^>C>l>7>G.>K??9 ?f ?,?U???b$?=)?..?33?N8?~=?B?;H?\M?S?(X?=^?c?~i?=o?'~u?v{??Ƀ?ۆ???3?)\?%?S?=?e'?Mb?r?Nީ?Y?_?ɟ??C?\? ???6?b?????>???M???w]???|?/??D?C@Aq@!@/@%@@@@@ @i @`6 @ @@ @LY @ @Œ@@ @+@e@˼@@F@`y@5@s@@@s@5@`y@F@@˼@e@+@ @@Œ@ @LY @@ @ @`6 @i @ @@@@@%@/@!@Aq@C@D??@@??w]???M???>?????b?6??? ?\?C??ɟ?_?Y?Nީ?r?Mb?e'?=?S?%?)\?3???ۆ?Ƀ??v{?'~u?=o?~i?c?=^?(X?S?\M?;H?B?~=?N8?33?..?=)?b$???U?,?f ?9 ??K?G.>7>l>C>z^>*>>>tU>A>U>2>>j>vQ> >D>+>lփ>}>t>j>1a>X>v P>G>0?>8>0>M)>J">#>0>O>>5>$><+>^M2>9>A>I>/Q>rZ>SEc>^l>wu>5k>&>qЉ>>s>8>՟>>oȫ>K>_>>>}>>(>>l>`>C>K?{?z?;B ???.?<?#?̹(?`-?h2?7??#?D?g???9٪??&?LK?n?G?뮽?6??W?? ?K ???.??!?Ak?.??Ւ?e2??~I?ؿ?M'?L?E??%?ڜ@%@!@@>i@C@b@p@@F@<@̆ @ @ @5 @~ @ @4 @} @q @? @ @X( @4 @4 @X( @ @? @q @} @4 @ @~ @5 @ @ @̆ @<@F@@p@b@C@>i@@!@%@ڜ@%??E?L?M'?ؿ?~I??e2?Ւ??.?Ak?!??.???K ? ??W??6?뮽?G?n?LK?&??9٪???g?D?#?>? ?qґ?꾎?寋?ѥ???R?my?ٖs?Dm?h?jb?7\?cHW?Q?7kL?G?*A?@@h2?`-?̹(?#?<?.???;B ?z?{?K?C>`>l>>(>>}>>>_>K>oȫ>>՟>8>s>>qЉ>&>5k>wu>^l>SEc>rZ>/Q>I>A>9>^M2><+>$>5>>O> >G>B<>[>%>,>a3>u;>;C> AK>S>p\>Od>m>RVw>a}>&t>>wя>9>+ǚ>Y|>X>]>M>߸>^>>>`> >D>>`>G.>?? ? ? U?ȹ?(3??c#?J(?C,?1?w6?;?.@?mE?c-K?xP?U?@[?`? Hf?k?tq?h>w?|?f?R?oD?:?I5?3?5?:?B?hL?W?Ed?[q?~?7?떮???}??뮽?Ш???$v?{X?n3?f???^I?b?l?.?5?6??{ ?w]?y??n?V?/?}???8@y @X@!@K@@*@,@@A7@@@r@@ @F@u@K@@Ѽ@Ѽ@@K@u@F@ @@r@@@A7@@,@*@@K@!@X@y @8@??}?/?V?n??y?w]?{ ??6?5?.?l?b?^I???f?n3?{X?$v???Ш?뮽??}???떮?7?~?[q?Ed?W?hL?B?:?5?3?I5?:?oD?R?f?|?h>w?tq?k? Hf?`?@[?U?xP?c-K?mE?.@?;?@@C,?J(?c#??(3?ȹ? U? ? ???G.>`>>D> >`>>>^>߸>M>]>X>Y|>+ǚ>9>wя>>&t>a}>RVw>m>Od>p\>S> AK>;C>u;>a3>,>%>[>B<>G> >zF>j7 >b^>>vS >$'>/.>w5>T<>D>L>U U>]>Q^f>&no>x>/>">z8>s>}ԕ>Z>>ڦ>'լ>>?>>@J> >> >D>l>7>>zf?j?? ?r?5E?ȭ?)?"?_\'? ,?T0?5?b:?m??D?I?N?>T?Y?t^?[Wd?i?Wo?qt?az? ?m?mυ???!?m?`\?HM???H3?e'??S??a??Dϱ?Ÿ???\?4?i?$??O??ĭ?N??r??]i??.?}??'??w(?V,?????>??_??J2?|}?Z@@Aq@@]@k@-@m@/@I@@c;@OR@]@]@OR@c;@@I@/@m@-@k@]@@Aq@@Z@|}?J2??_??>?????V,?w(??'??}?.??]i??r??N?ĭ??O??$?i?4?\???Ÿ?Dϱ??a??S??e'?H3???HM?`\?m?!???mυ?m? ?az?qt?Wo?i?[Wd?t^?Y?>T?N?I?D?m??b:?5?T0? ,?_\'?"?)?ȭ?5E?r? ??j?zf?>7>l>D> >> >@J>>?>>@@@Z>}ԕ>s>z8>">/>x>&no>Q^f>]>U U>L>D>T<>w5>/.>$'>vS >>b^>j7 >zF>>>>>%>7!>(>v/>6>f>>(F>)N>,kV>^>g>p>z>́>p>ɋ>>V>Hԛ>ew>9@>/>OD>%>>l>>> >>l>z>́>#?]?$?!B ?s?5?T?;x?!?k&?)$+?/?`4?$o9?T>?JC?EOH?cM?R?jW?~\?Cb?4g?m?pr?w?m}?}?G???&?ő?\j?uD??I? ם?c?ʌ?e??$o9?`4?/?)$+?k&?!?;x?T?5?s?!B ?$?]?#?́>z>l>> >>>l>>%>OD>/>@@@V>>ɋ>p>́>z>p>g>^>,kV>)N>(F>f>>6>v/>(>7!>%>>>>>E=2> >>4>iw>#>)>o0>08>@@rlO>W>#`>}h>q>"{>HT>:>B>n>޾>2>kˡ>>'k>r>L>y>l> >`>(>C>>af>B>2>?? ?4??U??!?ގ%?*?.?{b3?8?Ee?Yj?o?!)u?az??m??g?#???e? )??ذ?Rt?6??R?(t? .?{?떮?D??琶?-?bĻ?S??Y?$?Ee? `?Z?U?ѮP?K?pF?`A?B>af>>C>(>`> >l>y>L>r>'k>>@@@n>B>:>HT>"{>q>}h>#`>W>rlO>(pG>?>08>o0>)>#>iw>4>> >2>E=#==Bi>- >,$>O>m>G$>+> 2>@@H>ČP>X>4a>]i>r>|>dł>>/>FǑ>O >v>>N>6>z>L>>@J>>>z^>Y>z>>;*> >96?!? ?/?#P???S ?4$?O(?Ny-? 2?w6?c;?l$@?D?I?N?S?X?D]?b?g?m?Fr?~w?;|??p?1O??̣?O?G?ب?U?M?;?QR???:?2֨?m??匰??????K?գ??7?p???? ?4??K?M?^I? ??7??.????J? d?_j?]?R=?{ ??$f?J?r??V,?j? ?̨?̨? ?j?V,??r?J?$f??{ ?R=?]?_j? d?J????.??7?? ?^I?M?K??4? ????p?7??գ?K??????匰??m?2֨?:???QR?;?M?U?ب?G?O?̣??1O?p??;|?~w?Fr?m?g?b?D]?X?S?N?I?D?l$@?c;?w6? 2?Ny-?O(?4$?S ???#P?/? ?!?96? >;*>>z>Y>z^>>>@J>>L>z>6>N>>v>O >FǑ>/>>dł>|>r>]i>4a>X>ČP>H>@>`9> 2>+>G$>m>O>,$>- >Bi>=#==,=>u>O >F>q>[>e%>1,>@@A>I>UQ>Y>b>j>hs>|>( > >_>{>A>P>>§>6>r>%>>>}>*>2>>>>?>հ>â?s~?Ok ?)i?w??d??T#?v'? ,?0?k'5?9?d>?JC?G?`L?vQ?qVV?@[?4`?a1e? 6j?DBo?Ut?my?~?ց?i?0?h?!)?꾎?PT??|? ??0)?c?7??5?׬?Y???LK???12?:m?v?f??n??x??ƻ?D?P???B??7A?? ?C?v?l?G???Ji?.??? ?Ƃ??6?r? ??? ?r?6??Ƃ? ???.?Ji???G?l?v?C? ??7A??B???P?D?ƻ??x??n??f?v?:m?12???LK???Y?׬?5??7?c?0)?? ?|??PT?꾎?!)?h?0?i?ց?~?my?Ut?DBo? 6j?a1e?4`?@[?qVV?vQ?`L?G?JC?d>?9?k'5?0? ,?v'?T#??d??w?)i?Ok ?s~?â?հ>?>>>>2>*>}>>>%>r>6>§>>P>A>{>_> >( >|>hs>j>b>Y>UQ>I>A>r:>53>1,>e%>[>q>F>O >u>>,===O=`F=>>$\ >Q>z>>@h&>/->.4>e;>B>J>dR>nZ>b> ~k>Wt>3p}>dd>0>>>t,>[>㬜>>N>'k>OD>?>^>>> >0>> >>]*>}>j?? ? ?r??ȭ??"?)X&?*?/?3?7?]*>> >>0> >>>^>?>OD>'k>N>>㬜>[>t,>>>0>dd>3p}>Wt> ~k>b>nZ>dR>J>B>e;>.4>/->@h&>>z>Q>$\ >>>`F=O== =\==9=>5>Q>D>0j> >O'>.> 5><9<>C> AK>:S>0[>mc> l>t>}>>iT>6>9>[>P>>>/>>߸>>>?c>>a>8>>>> >:??1?K ??v?|??2 ?$?? )?Gj-?1?9#6?7:?; ??C?;H?L?QQ?U?Z?u__? d?%h?m?pr?h>w?H|?p?ڂ?D???<~? ?G?ب??a?4?q ?W?@@?R???RĮ?qٰ?i???͸???S??f?j????$v?l?d#?b????ڿ??k??O??}?B??4????Q:? M? M?Q:????4??B?}??O??k??ڿ????b?d#?l?$v????j?f??S???͸???i?qٰ?RĮ???R???ß?W?q ?4?a??ب?G? ?<~???D?@@H|?h>w?pr?m?%h? d?u__?Z?U?QQ?L?;H?C?; ??7:?9#6?1?Gj-?? )?$?2 ??|?v??K ?1??:? >>>>8>a>>?c>>>߸>>/>>>P>[>9>6>iT>>}>t> l>mc>0[>:S> AK>C><9<> 5>.>O'> >0j>D>Q>5>>9==\= =E{===ĝ==>q >0>>@>2!>(>.>w5><>rJD>K>S>-[>c>csl>+u> ~>è>9`>6>t,>A>v>kˡ>9@>'լ>M>_>tU>{k>ġ>=>n>F>>F>O>P>zf??F?O ?`?`C?3?1?<?T#?by'?Щ+?/?,4?~8?O>F>>F>n>=>ġ>{k>tU>_>M>'լ>9@>kˡ>v>A>t,>6>9`>è> ~>+u>csl>c>-[>S>K>rJD><>w5>.>(>2!>@>>0>q >>=ĝ===E{==X&==9=C==Ѱ>< >>:>>J">(> }/>9d6>=>D>[L>T>p\>Ed>l>Vu>6~>è>iT>>>{>O >2>ew>ڦ>]>K>A>e>> >]>W>T>k>#>Y>B>^>#?ø?Ok ?+????׮?!?%?r)?-?A2?R6?7:?>?2(C?nG?K?rBP?T?Y?ܐ]?b?f?dk?|o?vt?x?|??? 9?Xs?A?W?-?T@?\j?ԏ?K?P˘?q?=?B??5?B?ʦ?U??L??zƯ?r???2?}???Ի?<?S?@@գ?!?Č?i?!6?n?:?V9???7:?R6?A2?-?r)?%?!?׮????+?Ok ?ø?#?^>B>Y>#>k>T>W>]> >>e>A>K>]>ڦ>ew>2>O >{>>>iT>è>6~>Vu>l>Ed>p\>T>[L>D>=>9d6> }/>(>J">>:>>< >Ѱ>=C=9==X&===n=2=B =z==>Bi> >>j>>">\)>0>6>=>9E>*L>veT>M\>pmd>cl>Vu> ~>>0>_>FǑ>޾>Hԛ>>@oȫ>U>>H˼>>>>>z>g>>xC>t>:>?.?4 ?t ??]?-? ??#?'?@@ 4?.8?Wt>xC>>g>z>>>>>H˼>>U>oȫ>X>>Hԛ>޾>FǑ>_>0>> ~>Vu>cl>pmd>M\>veT>*L>9E>=>6>0>\)>">>j>> >Bi>>=z=B =2=n===KR=s = =m==O=>w > >T=>)> (>d#>')>p0>A7>E>>}E>fL>GT>`\>pmd>l>+u>}>dd> >/>n>V>Z>Y|>>2>>$$>ֻ>ȥ>>4>>>\> >h>>>?_??8 ?"???M?H?!?@@x-?[1?5?9?=?A?F?&J?KN?tR?ƠV?Z?^?Z/c? `g?k?žo?Ss?x?:|?A.?e>h> >\>>>4>>ȥ>ֻ>$$>>2>>Y|>Z>V>n>/> >dd>}>+u>l>pmd>`\>GT>fL>}E>E>>A7>p0>')>d#> (>)>T=> >w >>O==m= =s =KR===k2==wS=/W==M=C=G>> >a>+>>#>**>y0>7>hw>>E>(L>GT>M\>Ed>csl>t>3p}>( >>B>>}ԕ>+ǚ>՟>>*G>˩>T(>º>x>@J>#7>!?>a>_>>wh>e>T>S>#?? ? ?I/??|?2??%#?'?_+?>/?Z$3?7?;?>?B?WF?J?N?S?vW?[?m%_?Z/c?7g?>k?DBo?@@D5{?I&?X?y??g?(P?-4???꾎?e?P?T?ƕ?t??4?hL? ם?W?>Π?:???:?x?U?ϩ??a?`??RĮ?И?_??ܿ? Z?i?a?γ?,?/z?Ÿ??!???!??Ÿ?/z?,?γ?a?i? Z?ܿ??_?И?RĮ??`?a??ϩ?U?x?:???:?>Π?W? ם?hL?4??t?ƕ?T?P?e?꾎???-4?(P??g?y?X?I&?D5{?h>w?|Bs?DBo?>k?7g?Z/c?m%_?[?vW?S?N?J?WF?B?>?;?7?Z$3?>/?_+?'?%#??2?|??I/? ? ??#?S>T>e>wh>>_>a>!?>#7>@J>x>º>T(>˩>*G>>՟>+ǚ>}ԕ>>B>>( >3p}>t>csl>Ed>M\>GT>(L>E>hw>>7>y0>**>#>>@@@>G>C=M==/W=wS==k2==,m=FC=`==w=t==Z=`F=v> >[ > >3>>$>e*>o0>Y7>>>E>fL>veT>p\>c> l>Wt>|>dł>:>ɋ>s>9>8>j>*>[>Χ>>8>N,>>S>ʝ>ڡ>3>y>HD>5>)>>???J ?y???(3??!?8%?O(?Y,?}~0?4L4?8?(;?B??C?G?sK?dXO?=S?#W?[?t^?b?f?@@1r?u?Sy?}??t?G?? ݇?T?G[??꾎?e?? ?*?K?,???g?? ?(C?u??R?Ť?sǥ?T??~?aK?{ ??^?a?y?`?cZ???@)>5>HD>y>3>ڡ>ʝ>S>>N,>8>>Χ>[>*>j>8>9>s>ɋ>:>dł>|>Wt> l>c>p\>veT>fL>E>>>Y7>o0>e*>$>>3>@@@v>`F=Z==t=w==`=FC=,m==H=iV=n="=x=m=_='?=='>i> >l>/>>9$>*>0>Y7>hw>>}E>*L>T>-[>mc> ~k>hs>|>HT>p>z8>wя>s>vQ>|8>9>oT>6>ײ>?>D>[>>>{>(>|> >g?>>>E?K?{?ZG ? ?"?s?[ ??<?"?t&?*?-?s1?k'5?8?I?B??Y?Fk?T?ש?#;?Ï?rC?&?+?h??1O?R?m?9?~?v{?w?Ut?p?m?ki?e?b?'Q^?+Z?V?S?dXO?K?G?zD?dV@?I>g?> >|>(>{>>>[>D>?>ײ>6>oT>9>|8>vQ>s>wя>z8>p>HT>|>hs> ~k>mc>-[>T>*L>}E>hw>>Y7>0>*>9$>>/>l>@@@='?=_=m=x="=n=iV=H====}=~J=q\=2=JV=?A=w==Q=v>> >Y>V>H9>G$>*>o0>7>E>>9E>[L>S>0[>b>j>r>"{>́>">>> >Ip>|B>->1>N>>Ҷ>J8>>L> >˾>>>>>.>z>;*>>j?9?? ?/?,??Dk?o?_ ?#?j'?*?.?A2?5?O9??M??Ӛ?;? u?H3??9? ??e'???K?‘?ɡ???????ɡ?‘?K???e'?? ?9??H3? u?;?Ӛ??M?>???=Д?ب? w?#;?k?0?M?v?????X??f??P|?y?u?Fr?n?Hgk?g?$kd?`?LW]?;Y?P1V?:R?N?9bK?G?x&D?i@?;*>z>.>>>>>˾> >L>>J8>Ҷ>>N>@->|B>Ip> >>>">́>"{>r>j>b>0[>S>[L>9E>E>>7>o0>*>G$>H9>V>Y> >>v>Q==w=?A=JV=2=q\=~J=}===A=\=3֭=DY= =)=x=q==;==N=e>->j7 >ø>c>H9>9$>e*>y0>A7>=>D>K>:S>nZ>b>]i>q>z>/>&t>qЉ>D>uђ>&v>2>>:>>u>G>'>y>fk>>ʝ>W>f&> >>N >+>>]>!?$?J(?+?/?y2?5?$o9?!??v??/?s?) ? ??z?]>+>N >> >f&>W>ʝ>>fk>y>'>G>u>>:>>2>&v>uђ>D>qЉ>&t>/>z>q>]i>b>nZ>:S>K>D>=>A7>y0>e*>9$>H9>c>ø>j7 >->e>N==;==q=x=)= =DY=3֭=\=A=ʢ=)b=^=n=2=ӽ====/v====b>>C >ø>V>>$>**>p0>6>=>rJD> AK>dR>Y>4a>}h>p>x>a}>&>+>n[>ӑ>c>G >ǟ>>ˇ>>>ϸ>>l>O>^>>>`>2>>; >>->?{?? ?)D?z?5??C???!?*%?](?u+?R//?h2?%5?>9?I9?%5?h2?R//?u+?](?*%?!??C???5?z?)D? ??{??->>; >>2>`>>>^>O>l>>ϸ>>>ˇ>>ǟ>G >c>ӑ>n[>+>&>a}>x>p>}h>4a>Y>dR> AK>rJD>=>6>p0>**>$>>V>ø>C >>b>===/v====ӽ=2=n=^=)b=ʢ=ߓ=]=4=D =%A=9=g=n]=D====4==>>j7 >Y>/>>#>')>0>9d6><>C>J>UQ>X>#`>g>&no>RVw>5k>lփ> >&[>>9>2ə>[o>[+>>!>v>>>Q>9>> w>>>D>>v>.>P>2>???k ?"?E?l?)???,"?c%?(?u+?/?K2?5?8?(;?X+??]B?E?H?K?N?R?.U?g;X?@[?=^?@@f?i?l?Vo?$r?Щt?h>w?Sy?:|?ȡ~?|?̞??Ƀ?Rф?mυ?Æ??%?c?.??̣?M??~??!?k?S??k?3?e?e?s???s?e?e?3?k??S?k?!??~?@@@?.?c?%??Æ?mυ?Rф?Ƀ??̞?|?ȡ~?:|?Sy?h>w?Щt?$r?Vo?l?i?f? d?1a?=^?@[?g;X?.U?R?N?K?H?E?]B?X+??(;?8?5?K2?/?u+?(?c%?,"???)?l?E?"?k ????2>P>.>v>>D>>> w>>9>Q>>>v>!>>[+>[o>2ə>9>>&[> >lփ>5k>RVw>&no>g>#`>X>UQ>J>@@9d6>0>')>#>>/>Y>j7 >>>=4====D=n]=g=9=%A=D =4=]=ߓ=OF==h===ʯ=3={۾===K^=H= =I==b>-> >l>3>>d#>\)> }/>w5><9<>B>I>ČP>W>^>Q^f>m>wu>}>f>> >D>7>+>Ip>j>c>X>%>4>D>>>uI>>>?>v>9>T>6t>'>>A>??ø? ?ۻ ?H???? ?f!?:"?U%?p(?+?.?1?4?7?;?>?A?x&D?)G?&J?M?W P?R?U?X?y[?=^?R`?c? Hf?%h?Hgk?m?XPp? r?t?h>w?my?b{?}????z?c?0???Z?0??#?ѥ?i?}??:?????+?7?7?+?????:??}?i?ѥ?#?@@@??0?c?z????}?b{?my?h>w?t? r?XPp?m?Hgk?%h? Hf?c?R`?=^?y[?X?U?R?W P?M?&J?)G?x&D?A?>?;?7?4?1?.?+?p(?U%?:"?f!? ????H?ۻ ? ?ø???A>>'>6t>T>9>v>?>>>uI>>>D>4>%>X>c>j>Ip>+>7>D>> >f>}>wu>m>Q^f>^>W>ČP>I>B>@@ }/>\)>d#>>3>l> >->b>=I= =H=K^==={۾=3=ʯ===h==OF=׈=ڎ==섛=K/=&=4=]=;.= =%==$= =4==e>> > >+> (>">(>.> 5>e;>A>H>rlO>,kV>]>Od>^l>t>U{>>>(>5Q>>:>u>f>>M>>6>-з>H˼>$>W>r%>d>t>T>> >>U>P>n>8? v?\?ZG ?5 ?(???T? ??"?$?,'?*?-?0?3?"6?9?P>U>> >>T>t>d>r%>W>$>H˼>-з>6>>M>>f>u>:>>5Q>(>>>U{>t>^l>Od>]>,kV>rlO>H>A>e;> 5>.>(>"> (>+> > >>e>=4= =$==%= =;.=]=4=&=K/=섛==ڎ=׈=H=Z=V=/==Ƒ="l=&=ҷ=_=,=7==H===N=v>i>[ >a>)>>J">(>.>.4>r:>@>(pG>)N>U U>p\>SEc>j>r>y>fˀ>&DŽ>ֈ>>0>y>֙>2F>Ȣ>7]>>>>a>rM>uI>EU>gp>Y>>>k>%>6>.>G.> >}&??F?P ?8s ?M?)?????!?b$?b?'?*?>,?\/?2?>f5?.8?M:?߯=?g@?JC?E?`H?J?\M?W P?R?T? [W?]Y?([?=^? o`?b?d?f?h?Yj?\l? n?o?tq?Js?ot?u?h>w?x?y?z?{?;|?}?_~?.?? ?O?|??˳???˳??|?O? ??.?_~?}?;|?{?z?y?x?h>w?u?ot?Js?tq?o? n?\l?Yj?h?f?d?b? o`?=^?([?]Y? [W?T?R?W P?\M?J?`H?E?JC?g@?߯=?M:?.8?>f5?2?\/?>,?*?b?'?b$?!?????)?M?8s ?P ?F??}&? >G.>.>6>%>k>>>Y>gp>EU>uI>rM>a>>>>7]>Ȣ>2F>֙>y>0>>ֈ>&DŽ>fˀ>y>r>j>SEc>p\>U U>)N>(pG>@>r:>.4>.>(>J">>)>a>[ >i>v>N=@@H==7=,=_=ҷ=&="l=Ƒ==/=V=Z=H=!|=x=ʼn===B=Bآ=㦩= ==p=,=%=K^====Q='> > >T=>j>>2!>O'>/->@@?>(F>L>S>rZ>1a>&h>Tp>w>>>>r>>>ݓ>!>v>ݠ>\V>>nz>A%>>>=>l>?c>g>y>D>n>>M7>>u>1>2>Ӏ?9?\?W ?8s ?4??ȹ?|?C??? ?q#?X;&?O(?Щ+?T[.?R1?A3?R6?8?L;?>?@?JC?E?G?ZJ?L?N??Q?tS? U?jW?;Y?[?D]?_?cla?Z/c?d?f?h?i?dk?\l?m?n?o? q?$r?=r?s?ot?!)u?u?=v?v?-v?h>w?Diw?~w?~w?Diw?h>w?-v?v?=v?u?!)u?ot?s?=r?$r? q?o?n?m?\l?dk?i?h?f?d?Z/c?cla?_?D]?[?;Y?jW? U?tS??Q?N?L?ZJ?G?E?JC?@?>?L;?8?R6?A3?R1?T[.?Щ+?O(?X;&?q#? ??C??|?ȹ??4?8s ?W ?\?9?Ӏ?2>1>u>>M7>>n>D>y>g>?c>l>@>>A%>nz>>\V>ݠ>v>!>ݓ>>>r>>>>w>Tp>&h>1a>rZ>S>L>(F>?>@53>/->O'>2!>>j>T=> > >'>Q==@@K^=%=,=p== =㦩=Bآ=B===ʼn=x=!|=-s=}=a===#=3x==Kĩ=]==_= ===/v=;===v>> >>:>@> >@h&>@@08>f>>D> AK>/Q>X>˛_>6f>Dm>@u>|>l2>h>1 >>t,>V>>Rݞ>9>ǥ>!>F>G>>>l>>>>>>D> >P!>?>af>>>?â?BE??O ?5 ?4?z?Y+?[?v??W?W"?`$?'?*?c,?R//?[1?,4?6?9?t;?=?l$@?nB?D?F?I?c-K?.@M?nFO??Q?f+S?1 U?V?(X?wJZ?[?}]?^? o`? a?c?[Wd?݀e?f?4g?h?ki? 6j?j?k?l?l?m?Rm?}m?m?Dm?Dm?m?}m?Rm?m?l?l?k?j? 6j?ki?h?4g?f?݀e?[Wd?c? a? o`?^?}]?[?wJZ?(X?V?1 U?f+S??Q?nFO?.@M?c-K?I?F?D?nB?l$@?=?t;?9?6?,4?[1?R//?c,?*?'?`$?W"?W??v?[?Y+?z?4?5 ?O ??BE?â??>>af>?>P!> >D>>>>>>l>>>G>F>!>ǥ>9>Rݞ>>V>t,>>1 >h>l2>|>@u>Dm>6f>˛_>X>/Q> AK>D>f>>08> 2>1,>@h&> >@>:>> >>v>==;=/v=== =@=]=Kĩ==3x=#===a=}=-s==pi=ܰs=N~==lU=6=K=R==Kĩ= =ҷ=;.==D===w='?=`F=G>w > >>>0j>>e%>+>o0>6>T<>;C>I>v P>#V>]>uk>r>uz>fˀ>*>w>Og>Kg>w>> Ȝ>>\V>⳩>>ƙ>R!>>\W>> >J>Q>)> >g> >>z>>D>?"???f/ ?ۻ ?G?,?]?O?Dk??n? ?c#?%?E(?*?9-?l/?1? 4?R6?8?:?>z>> >g> >)>Q>J> >>\W>>R!>ƙ>>⳩>\V>> Ȝ>>w>Kg>Og>w>*>fˀ>uz>r>uk>]>#V>v P>I>;C>T<>6>o0>+>e%>>0j>>> >w >G>`F='?=w===D==;.=ҷ= =Kĩ==R=K=6=lU==N~=ܰs==pi=%`=i=/t=~=ӄ=ey=O= X=R==㦩=&=]={۾=n]==q=?A=_=Z=C=>Bi>< >0>D>z>[>G$>)>v/>w5>u;>A>G>;N>T>i[>M2b> i>@RVw>W~>q >І>>鎎>6>>>>>1>~>zׯ>~=>>->>@J> >[>?>(>a>>'M>O >Y>>>2> =?{?!? ?k ?u??#P?ȹ?[ ?f?o?<?!?#?,&?p(?*?C,?/?\61?R3?>f5?o7?$o9?c;?]M=?X+??Q@?B?{D?&F?G?BTI?qJ?GL?M?N?rBP?vQ?:R?S?T? U?{V?cHW?:X?X?OBY?;Y?7Z?+Z?Z?[?@[?S[?S[?@[?[?Z?+Z?7Z?;Y?OBY?X?:X?cHW?{V? U?T?S?:R?vQ?rBP?N?M?GL?qJ?BTI?G?&F?{D?B?Q@?X+??]M=?c;?$o9?o7?>f5?R3?\61?/?C,?*?p(?,&?#?!?<?o?f?[ ?ȹ?#P??u?k ? ?!?{? =?2>>>Y>O >'M>>a>(>?>[> >@J>>->>~=>zׯ>~>1>>>>>6>鎎>>І>q >W~>RVw>")p> i>M2b>i[>T>;N>G>A>u;>w5>v/>)>G$>[>z>D>0>< >Bi>>C=Z=_=?A=q==n]={۾=]=&=㦩==R= X=O=ey=ӄ=~=/t=i=%`=m'W=w`=pcj=Zt=7~==e=O=K=3x=Bآ="l=4=3=g==x=JV=m==M=O=>Ѱ>q >Q>Q>q>m>#>(>/.>a3>9>0?>kE>*8L>XR>Y>_>@f>im>lt>{>g>>ֈ>/>S>j>c>i>Y|>>Dɨ>>F>T>>tU>>W;>n>~C>>i>F>ߦ>'M>h>>T>> >??'g?1? ?f ?Է??EP??R??RO??!?#?e%? (?*? ,?.?0?f1?3?5?7?>9?M:?I????@A?B?zD?hjE?pF??G?I?&J?c-K?k$L? M?yM? N?dXO?QO?P?L Q?vQ?Q?R?JPR?tR?R?R?tR?JPR?R?Q?vQ?L Q?P?QO?dXO? N?yM? M?k$L?c-K?&J?I??G?pF?hjE?zD?B??@A???3>?I9?7?5?3?f1?0?.? ,?*? (?e%?#?!??RO??R??EP??Է?f ? ?1?'g??? >>T>>h>'M>ߦ>F>i>>~C>n>W;>>tU>>T>F>>Dɨ>>Y|>i>c>j>S>/>ֈ>>g>{>lt>im>@f>_>Y>XR>*8L>kE>0?>9>a3>/.>(>#>m>q>Q>Q>q >Ѱ>>O=M==m=JV=x==g=3=4="l=Bآ=3x=K=O=e==7~=Zt=pcj=w`=m'W=sN=W=\`=dj=t=P==ey=6=#=B=Ƒ=&=ʯ=9=ӽ=)=2=x=t=====>5>$\ >F>O>iw>7!>$'>,>^M2>8>=>{C>J>VP>V>/3]>Sc>j> bq>Wx>5k>M>>>i>9>s>>>~>>>>>`k>> >N,>}>>#7>ʝ>C >{> >k> >wh>>{k>>n>j?96?zs?? ? ?~P????c?T?_$?4?<?>!?8#?*%?'?O(?I*?n,?T[.?0?1?{b3?[4?6?7?$o9?:? '?B??@?A?B?C?D?E?@@@;H?H?H?BTI?I?I?|I?J?J?|I?I?I?BTI?H?H?;H?G?WF?AIF?E?D?C?B?A?@?B??>?.n=? '!?<?4?_$?T?c????~P? ? ??zs?96?j?n>>{k>>wh> >k> >{>C >ʝ>#7>>}>N,> >>`k>>>>>~>>>s>9>i>>>M>5k>Wx> bq>j>Sc>/3]>V>VP>J>{C>=>8>^M2>,>$'>7!>iw>O>F>$\ >5>@@===t=x=2=)=ӽ=9=ʯ=&=Ƒ=B=#=6=ey==P=t=dj=\`=W=sN=F=N=¼W=Xa=@@@ӄ=lU====K/==%A=2= =q\="=w=/W=m=z=C==>>O >,$>4>%>vS >%><+>0>46> ;>A>G>bM>H.T>nZ>`>xg>7n>!u>'{>5s>>Z>B>> >F>Z>=>[+>@#>%>40>OD>`>=>>>=>Z>ʝ>\>0>~>C>P!>6t>7>>j>A>?}&?-H?'g??P ? ?????,?ؾ???n?C ?"?#?ގ%?b?'?(?[*? ,?`-?/?}~0?1?33?@@@7?9?:?;?;??3>?~=?j>>7>6t>P!>C>~>0>\>ʝ>Z>=>>>=>`>OD>40>%>@#>[+>=>Z>F> >>B>Z>>5s>'{>@@@`>nZ>H.T>bM>G>A> ;>46>0><+>%>vS >%>4>,$>O >>>@@z=m=/W=w="=q\= =2=%A==K/====lU=ӄ=7~=t=j=Xa=¼W=N=F===u>- >>>>[>$>M)>ѷ.>f>4>9>Z?>}E>uK>UQ>W>d^>pmd>ej>q>|Bx>>> >1 >>/I>p>a>v>D>a>>6>zׯ>Nг>-з>ֻ>>> >r%>~C>dd>{>>{>>>g?>`>c>P>հ>???{??i ? ?D??w?EP?!??@@??_ ?!?q#?$?t&?'?=)?"*?u+?@@@3o0?s1?zj2?R3?,4?[4?5?@@@8?~8?8?.9?$o9?]9?9?9?9?9?]9?$o9?.9?8?~8?8?7?7?db6?5?[4?,4?R3?zj2?s1?3o0?\/? =.?9-?u+?"*?=)?'?t&?$?q#?!?_ ???g?ȭ??!?EP?w??D? ?i ??{????հ>P>c>`>g?>>>{>>{>dd>~C>r%> >>>ֻ>-з>Nг>zׯ>6>>a>D>v>a>p>/I>>1 > >>>|Bx>q>@@@W>UQ>uK>}E>Z?>9>f>4>ѷ.>M)>$>[>>>>- >u>>9=@@B = =wS==n=~J=DY=n=D ==섛=/====~=Zt=dj=Xa=sW=N==>MF=N=@@@/t=N~=a=ʼn=V==h=4=^=3֭=}=iV=`==s =2====`F=>Bi> >>b^>B<>5>J">{'> ,>{.2>C7>EO=>ZC>QH>N>T>$Z>4a>xg>m>t>"{>>NT>Ƈ>D>̎>&_>t>>>P>>ZǤ>ώ>]>2>> >ֻ>>>>#>[>>u>z>s>k>2a>T>xC>.>>D>3>P?96??,? ?P ?f ?+???@@?-??C???)?ُ? ?:"?q#?@$?@@@? )?*?+?Y+?Y,?Ny-?..?X.?l/?/?3o0?T0?\61?21?1?1? 2?A2?A2? 2?1?1?21?\61?T0?3o0?/?l/?X.?..?Ny-?Y,?Y+?+?*?? )?J(?u'?%?@$?q#?:"? ?ُ?)??C???-???#P???+?f ?P ? ?,??96?P?3>D>>.>xC>T>2a>k>s>z>u>>[>#>>>>ֻ> >>2>]>ώ>ZǤ>>P>>>t>&_>̎>D>Ƈ>NT>>"{>t>m>xg>@@@N>QH>ZC>EO=>C7>{.2> ,>{'>J">5>B<>b^>> >Bi>>`F====2=s ==`=iV=}=3֭=^=4=h==V=ʼn=a=N~=/t=pcj=\`=¼W=N=>MF=>=V6=m.=6=>=>j7 >G>>#>(} >%>5*>0>h5>:>y@>(F>oK>Q>HW>]> d>Lj>p>w>!}>>&t>ֈ>B>>\7>޾>N>Q>c>h+>ר>X>@B>>A>=>rM>E>>S>J>YQ>>>a>>eF>>2>6{>+>>w>w>P?#???<? ?O ?@@M?,?#P??.???(3?u????u ?!?"?&#?#?@$?%?X;&?&?'?J(?(?)?Bx)?r)?*?U*?[*?*?*?*?*?[*?U*?*?r)?Bx)?)?(?@@&?X;&?%?@$?#?&#?"?!?u ????u?(3???.??#P?,?M??) ?O ? ?<???#?P?w>w>>+>6{>2>>eF>>a>>>YQ>J>S>>E>rM>=>A>>@B>X>ר>h+>c>Q>N>޾>\7>>B>ֈ>&t>>!}>w>p>Lj> d>]>HW>Q>oK>(F>y@>:>h5>0>5*>%>(} >#>>G>j7 >>2>=,=O=\==X&=n=KR=k2=FC=H==\=)b=]==ڎ=Z=x=}=ܰs=i=w`=W=N==6=m.=K'=m.=V6===F=sN=m'W=%`==pi=-s=!|=H=׈=OF=ߓ=ʢ=A===,m=====E{= ===#=E=>zF> >O>0>>[>B#>D(>E->3>`8>=>\C>#H> N>GT>rZ>Mq`>@f>l>r>Ey>>>/\>>>Kg>Г>A>ù>|8>g> H>ר>ul>4>>A> >>/,>">+x>>>dd>P> >9>(>)]>0>h>z>OV>P> >v>?Ӏ?]?V?f9?1?_; ? ? ?؁?4?I/?w?b???3?G?P?M?C??$??,??<??{ ?!?!?!?W"?"?"?*#?T#?Hq#?q#?q#?Hq#?T#?*#?"?"?W"?!?!?@@?<??,??$?C??M?P?G?3???b?w?I/?4?؁? ? ?_; ?1?f9?V?]?Ӏ??v> >P>OV>z>h>0>)]>(>9> >P>dd>>>+x>">/,>> >A>>4>ul>ר> H>g>|8>ù>A>Г>Kg>>>/\>>>Ey>r>l>@f>Mq`>rZ>GT> N>#H>\C>=>`8>3>E->D(>B#>[>>0>O> >zF>>E=#=== =E{=====,m===A=ʢ=ߓ=OF=׈=H=!|=-s==pi=%`=m'W=sN=F===V6=m.=K'=Sigima-1.1.1/sigima/data/tests/image_formats/laser_spot_array.png000066400000000000000000001712561514013333200251520ustar00rootroot00000000000000PNG  IHDRnuIDATx H- Byd^ 7+0fUzH"WYzX+Vz_z_}VBh3r&o4=t^zCtkOeΞVzSC,nKY{crYzY"jޙIN'hc0HgB׏d\C[d$oq3dEws?_;0a1Olw4q4x n #xuc|z'iʓ&AQF*c ޚ7_OL/w] i`p(d)Cdsqw7;61t FPW9anNj|cG<}>;#t0K/_M(mq~"c0{\uwCӞgHPL H$*na]LaߦIu "H[J'ew{l *&!Т`r0{E~6H=PuUB.5}G.1~{W{XDV19? \w:b0l6QҚ"~c 6ݗG wL}q2jM')sD*o>Xcyg=6w҈/^L]4O_<=YDǤb9~&./^ʒ>4??ћׄ1𑳴` 7k12qzwEbЍ!Y(?=Qta ҿW`M37J?OLHgSJXӽ^{NL;]z<`3i9j>ShWmوqf: < _&FV +7X1~dſy^U+618qIH#ʛ^`݅;1/clQ'w{Nc{uR8)}u =M(v3O7?A`:j>DQ=i  pg'i Ow9!T=RN2=ϓ3Bk=H rÓP?|i'ZláF鐦?zoZ NC#mRɥ".K–ubbgR& *Uh8rXsֈ.1`%ĔD[ 'Lx]bƼ82.tiVj'vUb1iNS &h5Z̀[McAbwx)lK\R[ťl W(<1'̤`zS!S6t!%0V@bOS,e)"#؏Q4>jsm~^15[)GkKɵ2A,$p91-Sa%T < )jb mK Ā0X5JuKLqM쥶VIXP15d2=XAz|1 ndp#szO'XZPN_X靡+]%-s{lַ{oW"z5Xd>Hs29na}>5Eų8H4Xds{[V5S9 71q{7xK K]L'_=7P[Y׵RRˏe;Y&(oqC ͔S޶CEM,}e\zĝ|ދs c,"v*?i.җA2䄀md5 u{<~lqzX2Hx!te&빅{Z/`~={.c̏GUuX7SK@T7T$JW|s͏_^6SeF,f0>(o+o5n'[Lvs|-&)cbK\ ||}咗=|ܤuMG\Wka,d_zXI5#?a"ayu^_dd*-5da쬬)tDxEܤR)ƵR6 Ȗ~4`5F@5g1p !q?O TNTx+p90B=mi5/7XuDx|c^PҖOFKF:c׸߭r"GLKDTI/ЧS|ĔvGQnD1ǚczc%*2: {ExC$(!_Gy;vCh|#aCBQ!zts3! :GL (^57~kٖ{s|Jy] N=Buz fiil` d׸.p0iG ͎aX7 +*ܷWJ KQK=ZXVI5/ "MHlg:"Y)>_k.4ow/g *<mPgr vYsw_ݤG\% :䧪Wd4F:eŽĸmt|ӝ63E8ҋ"5-`>i]s  Hw̉ QR3F4k=cv%;V]+}!!CLA%V%4ș,$Z_hk>!9fl*ףR#:|΄ʨZ`wɕa@V-Z*LR{('#9vQE A7% V>OlYXFX"Ny{hi%/?(KaQ\9D+;x=>`0eJ>|d8; dHl >?zc~}0t=E:戍aVVJ-}GB1<0@x0D$1jK[!Oʾ<ӻˆkNe0y[RrCN.X#QX#ʏjrtk`]Qq/E(HUVSsזǾ`aEfer k)u)v'/YVy=4n,&}ql{^ez ߿kn+;3GG. bTy)S2TF4(^Mk}WX̿#E(4i]3Jx~ Z9*ccD` ,y Qb8~yDZ{%2ohM|H$[l+F>!>i'oikx~9Žs3OG8wA.o7x4ܵz,8M@1gaBakm߿0aovx?`m)=wL„ ~2(A Y}۶"`q^wIF+ lAҾsSO?G0x?9çO #Sߝ8:DlsrFK97n69D#G 0s$r`#3jee_?DqAZ+4;w Wsa!5 1h1=d4QKK%J]BbSj"$ n<5I7`BHӰ?VT=Aqe5XĶ(SJ*i$!2!>0|7M4^㙮"dojaKc bmiC3=D=GY=ﶿr ٹjQh-`I=ò0 UdT0<^|-5^ ?0DbO>$OM0P 5|rU>̃!*&V((XgLxc^ z2ZOKS[+H~ PSHd.vE˞a BXZV@~BZ,G ,-2c8Bxh5}궦@^K= RP7ż|7 &{W{JKoGOh"4'[d;Rz>v sp F4+=xAEpݸ"ێnϰ{>W#i%-=jVщ?%0k3cHvž?swS&UhM΅cx$cFq X΢II@db!ʧ7֨&4j_7 hlƨr%E/,IIr12sY4ɰZ+O.RU j#;ꗿku?Y2_&H ֭c+hcW\'b(Z\gJ1S&<7DZXo%ݜ e {z%G5 ΊM3ER2Ѡ2CWW+>w9!ylbKWTvrxS@ZLtϫp6֋mrC͚Ezh:;"/v\EғĂ4pђnb s=35y6<<O 9v`.b2x.< 8ft[tvT'\,.E.ɖ wWmfBkE4$^zQ>zL-QxgoӭT^P<ayC7? e7Q' K-cjPtdEP&Qt288b0ծuٌYrl|uL1{eTPЫyG|pAKߏ-2rOt9j\M%AS}f+KfpZ?k\ah?iFpl* ̓γt2VZdz'荐=鸗@ \1sbGcs\y#R_8rs~x`05ڕ7\E7ŀrb^_j{;VnGg2Lu{zo>Psk<| N_eikƉI_p=ˠ_Qc|ܾD 4#>}gݱD~ǩ;2kFJ44+!>OpkU?椳¸;| qhń?$]u٭g8P<@^<ƺ殝,X0P*ك_V_I tQoAѝKڅQa,hVF0,^2Qy57d941['*^x/4@ jt ƥ7_lSeŌn|-Ɔ㍳Tf)icB*U'`!ʦ? {uOCQ~Zް~pQ0jW3dWgtK˓/}J6haRdžj8/S0p @svȺa9)(w׹TجS n\K p83 Q7EM? Vyo˵l~7P6>_?2]! :Cg:WȿuV2O[!~Zɐ7D{mL{{mysSǙ$rp*wZJG7~ NbGE-7LX D|L[IK&ϑy;{{nb-%bO'MP59 =P8fw }KO|.;fA1U %<$S Y_XbrC\ 2օ<"oJZF}`.0GvkI~ϻ+.ViʉHϢe޺:4L„0bBy5dnk%X?|AV5f4uϕ~G'Ej1a9m6q'3t 9ݨ*8L~_|^U9x0A-61gxNNK-nym`!a=Y̓nqO?ϷΕ)Pw<݋O(Hψd KoCŨ^;CV_?J `Xu2JB˿¹f~Ay*s&cl6]ltco p^j`?`3 es]7C ΅>b\Mu[ggo"!DWqki8wgtZN'Dz/d,4?*uHܒI.5 ynH]O :/2rTv,9+s_Fi@l9~Y,#יI+eD`w?I#ח:t6J0qV= HU˞@!$˛qQM|sQV:FڄI KG?9, }.**z)C'&u#!uRBzԚjcDK2Q.=, FɊZ Ԧ'ŗ>Edžk4%pPc@;hkf]%~q^ ԠlhSoRSߺY95 #妻9^ǤR^aqQ[]͞Z(GlSć[+\T}ΘO&WciS` gϟ{Ik3:¦ ϺǙlCcX=FUDP战՜TtoW=b+Eh!xlc&:fY!CB %3ڝNC/[c0Je6Nb ( USa( F-7t.о8>0$#s. 0{@Y4륗ꉈB!lۆR+V|O\x9m? )o9onA*'@wj!d`R|fEImRh洱9 k(0Q%-ŴVxDiVXUz88$ -@m1`#t\@򶆄hӨ̑w وS5Nuu ׆:!*Pi ˘`ӊ;v0R7 K Y|؄CZ-#/If i=22PcEpBBǖO2rpl/ćVG3|9Oz[rzvKhU}r(wcO ,%)PeR, џ"i}+Dz,G~}'8eq#vȱ*Հ%:fР\[uZs[Ssg#}G"7K9 B5ПQ:n>,9kk1K}x ww$|h9W1d >dI#?|\ck[  D գїk>)XY>^yVSlD!/y}Uq=C;jS'7r1b}-%-iZz/Ş *u]Bl]H( EA(zqȉּz}V48ޟYMARDqVdͼp¦1c+lǾՌE5V'z+F671 ⅏u{=WL7;2Iy =QacK̏__k]%S^ >qMYMq=mH h}IJOXGq,Һ^m]K!(Cv#8Ts{5q\f2.l"ڞ3.u롦7[GsFJ0i{0VZچ6?j`$‰U kN#f ՝{+ cxƺLj-jÆu[$CsuEsфЫ4obXPjFbRA3yϊ׶=Қz ԨQCL>c541|+mXΥȐ5 XtC+׺;XZOG)#E5.!m{>u--FŤND'@[-=)]\Dj;aQmyPkPA~S凳+o[{Ywh 57t%IG3f8U!X[Oۺ>[mGV. Es^` ~ȳm]poa<.+Իnq)HTc; trgeW#<Ɯ2Ts|7+ HIfQyz=r++&/$djʂVhxVHug_8)v>(6K-T84&"7~1ZaZΏs}\{P&a`i3ډMCZ d_ԏ5jBkjζM摺 !y%@"䈱WC5. HT~Xla󥺚pLC#R i{帬-唹v>gk\nw+LC7yyG!5H< ÚEqc9Vt 뽄[Br`R0C<e,8վ|M'Orp;>V$?7N3;iZf#nm W9Ў*U016;0uS ;7Ba0B`-ecDe )ˆ0S*p{1LZjs1D@05vˣj:=a%ŚfFΈcYPj) 5S ?sN:+2洽K@c |rG:ku|Z7,.$\]O>Uz_tjl}'.x"(͌٢>WGLh|Zבs{1r^żυA0# W[4MZW(5d!K O68 AEF_!tcZ[X[ .b8 |#VfDcW8*c1-{2zP\-ʈyRRȶ\{ɕP[K EU#.:cܱ%ڛv M*bKN}ܐ,u<4x ` rZ5bC'Gv XӓJ}ɻW*~ñbt7s^VQ6'Jk;Ls6(Hn< yA9fh%D. &6;Û/f KtKNwهh`U-S7c:ÒRi$yISС $."W=ٿ./AKT`zzk ޵|VgN5ML ,{8}ft_~W؉ A5tB;c$v[I^YY  P#dϜl;n rIXG)"az_B|ݔm*A3I=vI,cD !& WNpJ^HL V+ԥyB0583i-ʋ F/it2B78MTչb8ɆzmG.z`r+UڋF*W8Q̙#_ >Z Ghkh78*6w K:t>6g lzS虬tPR]^Kxu Fs;Mϭ"R~Z+cD\g"nۑK92ls֝Ȟ'%~:EgQpV9Z5j*/Ƒ!78~Ă\&b 怙Y~{z^K| v9)cřˬ~T Pi9 XR`,Gk,jB܆;Y|"aʑ^TCamRo w :3*=K]{9Z,z1?Yr* k{ ρ!wTSjr9|7Q I^aw%ߟeB4fPϛ:Lǻoaot\pp&ѯlҘl{5sz{ΐ֝aZ AP[ɼI+}@b;fk Kh{Xa)|?I%TzbSS=Ϻ~ح¼3FBWt&QׅJuq@Prx#,;RR #徴@w'4%Sr|~;ڍ؄xD%&/a++{/4P@%.+L=(壟IRVIˏb 3VR~LJǼJ")`ſZ%]f?Da&=_wvv4Ӳ;XߩA쩦GbQڒZ[j޷=]vB̛>fn;2Fu)z|6X";h" t - A>g: a' ^wzLm> סdzuLS9boxAr'^C1j kǁ8ƣq7Olu7TЗu[RY*x?~*^~Bt~wiYeȢia$,B^SF0[$얹&4b"Z'+EE$3srS%qZR{!j+RSU ' jZȐڴB%mW;CJ0%PR{;BH)3Ia%'2-zxʱ#¯~>-|k(R##JwkJ2+1 ƀ )R֐m`sM}fE~CK<Bug3MjZ>WX:~סc !uUVWm{y-%i5zߙ|ȄגY pvM 䚄z.b$`ZǴiװd丰DM=bpTn 5^W0R Q* vL)"/ UVo0i֊'|;y9Jj{]ycgcG ,䩺znQaz8 EK= '=FGZ ћhCCĪ.7c$؂{\>pRJT8T0Ԅ*C]UYa!"=¡LHbmIQ v$/N|Uw G$& "Q)G–T>ʹ,p9ص&*`cV\ G<8 yꏋ M#X񧘽{_@WeV1y"2)zLJLt?XQJ;_  0 nU#؇< ԵQVx(mp5e dJTZ ȹfT6lxw'*+u؟ؠo$+)t3tH8CN?ZZ4p_jlN,L*%$;iy2r)ĉͿOEj}8E1 ߳D'Rr w k{ cP0k \H+X46TT :"ʌ80da$5Q,2EibDP^cr\i19~bt0ۊ2n!qnLx.5O4}g$_OqJ-;_Rʣȯ՘_w|s [Q\ =,*nx9˿_$R!] uLѲe)8N2u%~j!;j ={"9=ٓuq#Y+迾Ob[qyd ^Q\Լa^nH4 Q:\VOP`#Bmr9thK5J©.qqʗ~PSp4 ĆV ,U:0ϵϋ}qrLF,xw&{OO[C5TsyXK~"`Q7[Ld"WO=r_yYIF*Eڣ4cQ̝Dr|G|Sڥ=BrT0yRgCO}3Rz< nstLǨîfT3CT̐ VJމw:ÍO?mO/Wf4y\Ҩ[q憂!m?F1I\0+pWavjp1*|?&# ӔK+ut>w 7Г} \Mv1\IRQbޣҵQa4kYޕVEI#I`(QZ$ |=M)W]jH-Saf"Qpim/kdI)Frugg7mqqiy"B4D3z\FT =y7EH*i()=j,mϠ1&RT^}9%hߑ5dM*x)'F').8qp_vk`>.Qsy<=o9ps]HXw\..{⯔1u>i}:/HG5t:e+ a99IڊPk Mʑb0*и?G3*$y&Y8?{ov@՛K}@J@:K\Zg/sT׭qEhf?wXw9vDWJ\똅gŧYX?$fP&NkfG*'!;CM 3zf>QcHټHꙻY,Hz=6bsN{?0\"5Ƅ.JvC#XI/}yK5O 7Qa@l@fjW hb*:=_I]M gx_'bw<ӮWv՞s[X"M7:c:HM,F!Oj%o}$ӧ5 ~$!:ΆMwAOcsWf'8\Uۢ?hkRs[5b]d]*;֗ q~_22,jc;!8G m^9l(WZ>oi~Medy?qҲT$ygPj{n2 xbMj0 !9vRdJ$ʜcF>8Mu砀r)#/z c q u>#4,V,eO)%ʕmK9RϬY9n7e|);ELL#\"řfa|fJ,\hW:&$NNN\%X*:<ʓKŶ+S: i|X#ATr8}Ӥ0DxΠ w<*E83/6W_W~zEiQ]ȳe#S-PJS!<a^vȢg\H-w,5-K#i+e4)U"8 Plj@NM#G<z Qe Mذʼ}^슺Q|35ЄaRgj<noXhuu^BBh)FӘ* r 3O #zī{WqbY#zP{l8u׋F^Vr'Un8`:?9L؅bk?$W8I&Ҕ~}|ܾ ^g&UP)~x96MQÔyg˓]Pëiyhz?σ3Z,Ʒ׬^)ԟԥ34Ae4SV5햪ʀwAhN-pƵBLa5F$Z">*nYr\AGcź-ؖIX$`pֈkǑW@uX2 &\"Cg6go ,`;'.-wi`>=a )@_ . }MH)A=yU@e-QdBF&&>$a#,u0C4p(-Qn8s A_'((uo #1QWݟOМFbhS|b7D;̚낀 _ sit-)%ńNjMo^PAU0heHT 'z AP#NY ]MU8ntx Hd:cgbɼ/83xRF@%9!uTcF&tBJ,@.G3sgVsZ]e#4ZiNjۮ3;<7h?FL31MQ)s(UsWҴx~C]3 ]i*L/P(]BÎm8r`QI0̅ ;]J»cҶcbQ -K"Ra!W04]xF-}lj1ds,uS(WӔr]Y8նDwvM9l4fD;oB(K1RIAF"Ig)암A!)%zJ@ѼM+}`N܏kQaܽ %fj3Xr1Z ČPQ{׈])^TXO~ur'=MzW[-t,a4Kj앎0ŵq‚+\\+cJ1p9<ݩ.+7v]r)wP`EJ_aF/>;P>J-nΐa`&H:a@RWj9!ȱ<V="i1{KKԄ(UfFމP3`1"DktǮp(j)u ~lF*-u +I]˓+d2_^csp9_x˞ĹS TfSDL4;hc5l>`Z¢Q츮V<ˆMd0鰮0#VP|q1֝;5WB aEOjo U"WQM~ ŢncLH hVpQ-X. C8x"`cSe@|em6^^$7wG5G2_p-*RF FQ@"΃ޠ)Ǻm:JX WqR?|SW[@ӃVRj_℔# yy]A9?.`zTE@s4RAj[H+[d{PR./\i?&`@D:_Wl~Vg,8 7909Ɛּ>Ҷ&4&aAVΉFң]=4ju[ hSMwK`(Zǘ׺zJ v$ong{A VqH iMm'Z4DO< EIG-RRΏC%ظ.oMulG 9nXӞ2PS"t#Rr V]N3T*]Mgc+$ȼȡ磊CS!\p!ƈ){.i)1Ф̆!d)E=_-9Ċ<(bBчS޶ǯ_5v{Y?nm]U5Q)|؅~=m ECnArYC^ Hp00_Z#btbN=sBTC;ZPi_bgӝ9k^j h^?GXYl=>c!z>R\zM݇ _]`RR&q)mc> 'N5-?]2ZBV^+ [J >ݺz\|&{# *7bmrXۊR05-<0HIs)k9}ß ꐎ>RBb(-cA"':yy>__),m]/Ā,Dt%D(\ʺ)=ᶳ$r]RAMSJy9XڎP)=m;c[?Dч%!-).)c[3Zc=5q+TLRţY@OmM+ƒQ-;Mۦ5xvZ CvzN1.Uۑ>f[Dpx#>>MV] ^p8Aip, 97;.%[(!~9^~aL4GN떱e])E\ry E~А5ߡ@t6XCnq!_&+úhĞ=׼]AE{^_>Ƴ Ш攡LN3_a2Wx ڜypSF}30ؿHԙ?W?9Gr܏$m'CohnMi{&LA)U]F*Quvnϯ-' "9g G & !@-K;V]C%%E_SJǙ²#5S i[5'uE j7n=4qUӏDW5õArU'E* O-9?<7mX݉&rx\J Ԕ8i:ġn}Ns1[N}K5wJIJߜT!Q"ICikZrGY7e#L/)Ckz>=ҒRwnGmRw@"ai$9c  ިhb.r 1ۘ 9byk :$2yOY2nXpij&6nI<0H@eavXY9(cY,`% @߰?92w2'),JA0 ⻳I|dAjO Rd#Y%.Se{"Wуs@5wW(Y . AB,^׾4dP瘓ǑYayݞW}l9QDJӉr*(n5]˻ӟгs_t 9ź|'( ]at3pWp-j"Z|NJ*I_쎾 #kʔyn[}T0Ai50 oѭ).{ v^FMl_/+[eWRw"'5`*%T ld;pFl:qr%\e\s|g J@i^VKn_ KWID.4oӋv?* 5lɆ3pȌ2yz"ͮx\CNs(mZw6' BW5~hwNW#ORkZJE{RqKc^ICIoliԒʞ>Rke+|"IxEXܱ xܦ7& z6nho}]E,HVknF-*ܡF'D>j=IR{d9V]Ĵ|Az4E^,(f2u Eܫ-m'KCނ~@SGRzP3!1F2꟎=?U_kG}?gp#eU&z;y7422+thUYF?l,y3pA;쿷z)P:7tj q@wH]~ɱNqJ]K9>zPvc;a dJFO^Pk`rMsK'~ ZmqF+U[J$})^`V{5;0n aL ǝ2[fz=-"8|};U SUxR՟a9$i0#l^zԞzflIs}u~ro}?>G:e3dV:V)"~/qz;~VY9|U&~.ࡕJ{8Jw0[bcFWse8~CDA }HkI?!}qGTRu=.=YO8(Rwdiw:JP>Sy(6?W˿{{:Io|؂T K(~>5ɛGVuSwK;X5:Ob0~e;c05h6\nЩ*?OBhq2XOGJ,K(yZjf/npn1[0dzDqJi?mlK tXPg,x-4H71֖z$|>޿1- Ixk_K|ha3SY72JEٿV@}V5˸(TV}K9U%0#9W {nKE!"CiQw\ť,G540(9թϹؤcn{]㲆ρ~cY uOqYzGei<ϾȆL6ERd k}P d?~| j{+KXr?dhz z({H[?Zw9 mګy8++񃶚{?6X%2 V4\kR p~ۼN>kkk_R7!m%2:BC(x/ hM@ Ω3ge1J_>Ў +,N;*:eIX"فEQ6@FC[ r87~-H에{ 1-kAIlmJFj_Z+TA /&ޠXBGξԒW&uVh!H,$v#kvn-v !B-R8,m}Z`kp ulBF~hAۉ:XNZ {j)j=lyd)w&'TD@ʼn N%vl"k);vBG-nlXnƶPU;jlȾ &&n,t>M6c sٝj_Z~/@a1 *8 +" D]2Sf8AE!&b~`Dgenxj9};HG0iPӪ3"}E6264OgAc|kh1P` 0\gH^ηHC1",-8l+{SLs]-4>ڔ8 i1/kteP`[.?6E{dwcY\f+Ik:`E DQrmH u.&Xϗ-6=)x3UoEDL\I#]}sq f,>vŤ66ӻ -x8&v0G6MMo7G#¯6${Ƚ 59()hX2{AT *b-X?c:0\wDؠ;py^t@k~S;!< D#(D'Xam:(@̔ 4C8;uJsF$P\5U>3)^% 1fv 2Y.)"`{~ACFO4/0EP`MKi:!-:'-&Ka:όoƬpmE//\Y yл9Z@W2 L˾)Ebț;( 6+:BH(ѫ*ÂPJS^*FCr[3;JP6f[ k:HQ9Z.ڸ8H sC0 V s2\>PWyJ0H c+)2OƵNzLctYgC?Ij"x"H/1)}PE)o{rΘTx{aN/L& w!KJy$ΠrcRtm0Xݞ(",\.JNkhQxBZ;X-70| ;1RSBG.+LG ޾QY2k!nIQ[F̍)'w?؄ `ϏJ3e\q9A%5O%"Fw^0m%zjd3%BǥD)zu'kG) Y l1<,6HS&ҁІi;C9ywcK)qs?pcq*tFZB N8J,&ӃFau^7o{ >IpI7<e0 dݽ4c03Kk*TgtntqOuu);{LG+%lܸ UŔE>C,g:sP! #RnS !^yHۉ79D? zW;}! sAϳb?Zq(: fTX kD7ȕ58RPkȚwhuח I7hX]#0G>=O`s>/N9}>ɭ˩݊a-آ_NGvn5`s}10^r;w-$ˠ08tǦWS5GBbRqO욧܆"<[i֟Q! w8ġ>w߾ l@a`l(mGz³{[LNsq;g|O S$7V Q!&PEBzPqYJzIBfY_Rt2rdD儓EfZNB€ 3m vل*^+XsWnɜ?tCwǟGsJ|}C^Lu"L󯣒f~C8I7P~NVv޲3WAwT-$Vg{!fefr'c RUx lvmơ{ؔ*vlx}2b%u]fLKeBz!GrC[fiDIȝث⃯G\?zW7Q6y1etkG2\I=ץP;猩4Yvɏgvn9+;^oQi|ķp,DէkP_hM:}~1*n|HjnFȁ0c܁_ $Y]C~f8: sU !꧗@%TspfMy@!oN3fpi5#MhI50ə I^=QAM59ĠU]؟Ko 9pڋ t:.鎛,נЋYaO =$:-kI$ﺲ+Sh`YZ$_j8+SH]!\ohiv0o:(c1kЖ+K|S4~u;-vښMNxgǃH,etNNi2=Bk|uG M(W9jYR>A*q.+0|L;HgkwqL²tsq.m﷨Puv/ۡ\p+G©2#o'DW5~t fDװP5?Q̼c.8əjN+?"x҇8Mo7f c܏[9Sؠ{rT4}pBE.؟nچ8ĩPnZճxFz@GZ*Ph츗puz\@uG&z xuJ[[xVD0OA 4p蕧0|>%qw/7˦{̙&*otX4.﷤ t[0';"^=y'u&AbreȬ,`ⴿʆdXx]q'y7GKQEPәe 1Wbe1Tz§\n. 0%Wh`QψiCcb {c3ԼHr unkUmTEȄu ,k+pĴMntHƙw3OnwkJ 1&8[l*@U^\ tf0ylXgxMZx"HHWg ٍRn˭ѹv'w&<)ޡRͬV?2zg>4>C%۴{k: ,-yjxQkHʘo+T&M\mChxeBO4>)bk;lM,z0axKPL~4dxWd)Y/Nx16-U3Y jp5ą Y.R;斾hZ,VSD2dAϘfJ5 r$BJw ߴڅA(۳5/ FfL(g]5&ҫг՝lHx|^Dt /D'.6Bx<coXgϥԏ]^SN3SE9+e;>'1~ްXp,P~)lZSB>bl%Y0!QgR̡m9>Kǝ#t32K_u?#sD6{0g=x=k@3ߡ/ew}7,g:xAm.[vQf|_kLذu{n4 fR Yo1=^ך[{+ޯD×8fjCc{<y@A'\>#fS#5.L, ȰVǾ-hFe>F tvy?Ӷn3]rеGN|1 $r}nԭv:ϊ%ZрCeKH iE9u{ǚR탭 = '1 BB>^_-TLdҕ46@k+ÞrPx:C!FCYk]_Zcgf g icTn۶5GV9.aF1nm]eEou9RfIL#YzSWN_Ȑ[R%qΗBzuu)0hbw^lQ $r2A)Ҷ=ݗD{Y2 2 t/+n?`%XhzόQ]a6ۯ]joźX1Cb!ԕ2k9E)%mk~|}zaN &^5*J79ȶ{z<Nd=Xz'aM"G n}OzWJ5m[ { DmS^W,9-9!FTk_? $X+۾R)f#άPf]aaI|kqcV&#'a%*9 ż|5sK'0Fpo8 \uٞ9Dc.=to\Ed]K %G1aDg yT& Z%’-o zEepLK @~4D;PZLHт&ĎTݲ-:@9Op.7&St: *⺭\>|ojrԻ8zu~e s:ײj5@%0Cz@$׃3&Ő: D&b92yc [uJX mZ6R kqYԅJpT&hZth V%(ZO Cyd$$m*e: aDKw0Q>CXpP%]'E!h9V]90ºr0p(̵YFh.v-b{s33Kj̍2D+$7-zw%W^H#2:l THpz5S|p,<8$pLd67{8NaDwX}h5'A%k itemhT; 65 h*{hf0"Υ4E`!RCۢLK"d H܏Ҏ?Onb'[|4UuKlZ+ou$g,C(\;~yui`NWfB0#QsDcV 9fzVkɰIɠNsX~ r5콮UE%BR;%~8{" QStjXDcN5k4vc&8Ui=p#x؈w6܃ƼX?CMm%gT/j(a- 寽}ˁ;#xH7d]-GL{Ϻ#;'k#K(pGuAd^mxH( Xn=>.>ʱ#2{_ۥFQ!Ijj+o:,ӿӍ=#v Y(3P bH>7(r ۦc`H9ہߟv׈陼 ӰLAZ*6Lg|vpW K9p|KIvsjI^ؖ MD#}b[N0cNzOT.7Q}0aQ9NWx$0C T[ _c#م-T=J -a[ w8ϛP E;*.l FU7zKyyS)DJd,Kj==Ok8VH>qGpO2[#"TwI?G 4tzq Wh}H}ϯ4@"'^V{,}!VŐs [- #bX8 hd2[׍ %RX+a*{=|7q݊2P/;ݡC?X`$kץi_Xۨk|[opWBc4 7wh%5e 'V4.=ap xZ ϱ3 O}Ԍ)Z#+ΈﺮI܌eb0)oV&MpyJZ|Tmٹ ̾+ySs^>̚V39gFZe9I7DWp7- y4%1eCb 4v42y4i$ 1e`M}-gJqW9>0 lYu90Zb cjK- L( #stZ9#h-SraZmԽ2y%"hϧTu h) +MuedG2 |dY4j$l=B2d,#{Y\p^(oH]`ӏu3bZy4,! cd  ~%$[D4"jiZ&ahl 'U=FiQa\2WЫnQ| XV!*=~Nf|8DM(mX 'Zwc,R2Npw~ĸ-Fۜ#n!`[6ܜv^xx_81 n XPcLRiG\e:Z5 ):g1*3@%[Go_}$׈2yXwhPMpp.΁H&BA^3#=19pP&"k8uA9 :u【Zd\UXVY,;3ڐ]~|:–iJ,[BEW zMDzxSfRL <w_<܁:bidvH!&1$呧ZoH֤iLP뾀 NJybmF^s >erSH;qʕ]@7!Rģ/$M/$Gx~SK|hBlt R#U&`cCf҄)H+P&!t!іz\IevhVEt%h5_`ƚCp\a^fv!Lgx(>s E>dc怯n$zB 1psQovY<iQ@4V ]iUcD ո+p7yqrDK';Yz&A+(⪜]&"ѬLst bwgGqxr}A1 Npq\䪧xr=NNglUTlFOᎱ1``+P[0zSushIf~ $kQz:& rPf/2~؅IX, o)ʼnnyil, Ǘ#~x1QatG.x >ލ1UDG_y8-}hCz ߪy{V1{K7\NJZu̓n5U//UIJmSauV5xYX\h*UY˄ؘ+Bc/rŦ6U8!`iBB'ES]Wc? 7}h~CKCu|3㌢̬iR85e`Gu,ұ B`wc7Brʕ=i@/LQ8vYfpA3.:%SLAHS:% hh!{,Kq?6uk @q#bkݟ5orϞMTf-j':q_=j50c4_qy.fG[ϔ>eJLkSP^AiFCSw#Q'09MMn{1kǡyB0wiV'_vKa!l}= ~|& qڏ92Rx E!4]@eiA uʏȄLD29k-N|1g=GL)R{7Ս$GfgRn^N%}s욪 bA 9%~g>9$FqV>4彖œxUv71x-#:npo&VdA&%Yl-s]KTrߙ  :Z/nUZ4QwY*(tJ131gv9+f!5H4lwد }N2 Z`@T ɖ샫ܵg3"VEKfh^?8OzzXǞҐ69U/BHW1O|yoԲ34p #N'=(dSqpq9o#>h|6Y?}]jMtuEkZJ!1;_*mEx)Fnܔ -xB^ܮ(3PEL=}4ϨN*72UF_NyYv^,e9Avy}r#t+9"02Ls,~ gt79v#Ut4Cw# xW:L_Snp']O4'cu@9i0q/A4Y#TkgGn 0lP%3i(wT7 '>%OT8RvdkW$!,[M'qͤγ!m7F.GN@w4b[B 0MvGa3||a89T9Mp9sf{zf1ϡ3_5}Lb2_3kƢ-LTgׄjkuszHP٥ ms?aa=x]zQ6&y23 “0 Pz&x ik| {БWpge0'%H!sD\@Mէ7$j!}yt{wStrW.u)dF{lsahg}Oh]/0jH19龸8f5~c8V;nDn.AAθJ+$'%׽dV&+g? jϝ<2.&6vUCOp7AZYn}aLgYҊ*Ux̎ɩ*eO!{oFc{Y_+-ooZ4>mtYOlԼ![&@n=Ajcl 4O xoL}#b ֳ0\nA<|6_uLZ2M?]Q%+8H9<.,\('դNAwR6"y ͿeyyXkj씌uI0ӇcYJB65j^$?%fG&MOI\cW.ZTIڑH1q'l}ׄT5’A%|[?m>V"}/""$m?dj[(M2lu[q%z44E*:zj=ZU;UBYV9̪cK[C'c/ h.VYKz \@ h**I9k|[.hR*@)QIϵҚWZb=r- WH@""` 眷{v]TIp!Y -{HIk{mdJNX]ʹxjC ݠ9sۿ[hڸ!4C>-me;|CHX[ᬗv*dY+j[>Vs]__J?Ｂ& N@rB\px<Kkr, -Si$?rL[bb1xRSzA(>>5W~Dv.WPTi ļJ'F楗{{, P pOu9OJC 5fbƴc+K*y`d)_a L-t~\wz )5ׯem_຤9xAW zmy[_0~pZJVt޲)L.kҖR(n8(rT Ѡp5u{m~mkli/.%v~ȪTVׯ ݶ+Įsޞ8C=^sCs#Ÿ#T明3l1_kZ/!9 [hhX-^Z"$Z(.W@8-!zmyCG(M=߻mm 0\P1o`9c=BXꊭ"MICd4xT)x> 뵶:uSdՏ  e2u]z-k%C˖1lc=~2~^ C{1щL`HG}ז{?OM%]ԯ1͑?E0{>#H8Avd%3"Xܶ^wb&7 j)3)bϭ Zנ׌^6%10@ԂrupvA\)c`ITH ah,@@1mK)Yjި5zHGNe ᱭǶǶ_d,0X e~:BX=gc'ѹҩhbѤBbr)~Mb̵.P+-KK"XK'Prsvb2q~zfqB[gZ{}G`VtGӑ:n´ ׳Q2670/dq0ì믿%͝[hp,ʌBZ5X-u,M->LrisCu a]bg8;+T;  ?p9BzwMi+!PrhfFsCN)]ۣNYp0`|<-#9R &0‡/ͮ6__{h]W>%Tx1#/M6+ k^h [&܅;\C<%a6L_pĈU8/y]1zf2G+)v`qw\ %UKBf3E5yIQrIR@vi]PBl꺼Wa~S/l%aƁ=m–UU$;2$,mqPjdC^~ )dz-q]{[ysyLp# &6Gxrm H"Et 9@+v4MTU>[E1 \ZeQly'ѿM }]ؘ;6e U""n Xca>h]͗:YK369䍓DlUZbJMngTtඖ=|~bD k%YJ%՗[2s䯝\'4ӌ|`V#J= 㻆UN:;zgN_ffIOp7gFzv%rIv*Ft;r{\)[ IbH VFRtE ӣMvWfIrd0ԝ>`j;R0IԌΩGfrG0I$X1ܬcxp|:Ҥ6 #2̢g?_%̍Z*.==U1OBDIZm$9Ot!!"HWRcmlSbhh{Z|+Vd $ ?@;wZ} N 2"̒-@ɣM/{>RGK5^!בZ,]I ]Wa-u_SOmy-z;SP]|Z*-})BA@:ԯlkuȉtz^[j!KqDR0F 'aAkd:_ukLVyz1Ķqo"6?4Yרj;JsXwIJ%rU^3- ҬN5P^{)IsErPB$V{:#CzWC%)jjFg ?Ko߿8c[6:5f1J]oz|ޭJ T&Tf|tQ#Hub\>MgqZ$FelY?|ߟnK|cy}.=b;>Q;ԑy_Lw^Tw{myc.YilY_Ӌar{|c*!dUƲn$.BzHq?gXF& @3@TKa cG@3I@G'Q4,lscLi-| z}ǦQz )1 vϿIAB&d&y08z]O|8PH`LAk=փ@h?e'.M NrdMUKAton  vY!C`KDJCsKH5ë'od%=H#L`9 Kbz-60)IJRPҞ 1[b?ޣ{95^wQB)PΣ@y/y z_'j@S}wOߟkܜ蕝{ GD@Y[~/[oi~;ǤeUK*uzϾo0xϧ NsaԀGU.@-K({k iv*J?ԾKTaq#;.^@AB:jt:\Z(}|1KO E]zz";C$#4\r Uߏ{$~kՖab{;vDPz*k>ȉN 2G^5Jl[^RGc4~u90{X>#NxI87vN$(-ֽs]YEqQDu̒G>Z? R#wy5[Z~|4 %Q-آ5Jk8X:jf6dJ:}=GɊG&"1]SXqکYX"L&ew/FB$,56{SCH cgI% ƺ$*nPzpc5`u̍*P 4M δ6PYM2a i$K4(c\ ؆쩭s#}0\PPKOk%-˧M =*򂆻Sܠ#.| ^t, 1QaFl51pzҘˆI0k@mÒC@"^|`,=l)sV  TD^D)Ï18mi=M7='Vix*:[ qiY:]앞( @u?p~^u"(3X tf[BnO82pBXjY96t|Pi78--TaQEN;A܈{@hnaSd]"tĽ7lyV[ i: "Az+s`vRz1@Y-r LI;G+@}GW ~Za8w"VUst?|H&t}q|`IbVkR#FBdlB޹L%$,e댜eFf9ơ|֮RddHR"X̤$KJL eOHn2U@e/)k όВ"<: q0L0 Bj=9*fuqㆽ۶cv í4ORqdaxKYV`8'HcSC`wf nxm!($c*2΄*ahHa$}#Yzn]ߺF $ 5QiXt̿2 Ь_Ps+NdIGEz>i{qf ԕZ1="}㟡k>q9 ٚ^ iA'dW y"wMu>A`g{631Asd_q#ŸU/ޫC2 n8ژ gLwтV>lidz3N1ܵ@oc"}5{7eP: *,.2q$ 1>tbk}2qOT't.;9Ѭ]_#jxYR.2؜7sXpSHR51p3tTGQ,Q{r/Y~ BSVA?7xY% B="d=H3obbrQ8O|-.Upp!@ƇȚn/ym1yyZ? ;N0Zu@L)zrK˞0ظI0*}KrDSQysՙ ~ Gy:$Gd 4ܐr>_9?ªGf"6Oݲz֔c>y c˄Os7Oet$.4D0 .:rꙎtez$ZvFqo4ZT|uW$~)`Rj*Q|Mk` C |H%i*`ClZZHw} aB1x~v !7w$%|u-z+p{L8;e v^qiu\>=lLskFFԵk)ʑ$H7EBb)n ;KZtn. !ݚ_hD8)pıt~ET.A U{M2$r)aul|K0ϖE}x~)FE *O:\OclpC8KO{qHCɣ8g^m}K4v4`]&Cl4tqCE,x{HTk[JcFh< ;R9⽪vsP599DDۿ3w79m[uj˦q/0?*s[htjLy~5O8?Иu36j߻ }RrLvj?c%2_g wZc{TYxҀ ,iKKYlKA'%@'Whd'" _?bcN$s%Ezd[|Ԟâf=pq] tg>Fe"y<9:Ly!.L6bq [3iý;5HI} fles T y Ɋ{E&L\pL'H5KLp <o8A}ȋF=p։;=-u_?vqǢl=|?lOk+H" !4>xP3+;dj w<glm04j;3n ƿ=i#`5uK'GZ\Xn~}&8m#47sd{Vx.A*4#6[8~o %;,NehSa=<#geiMƄF\?Ǽ+ϳ[4A' {Tzd >W%xqNJJD aܞ=jL| 2~em4vҬ g.nR{s`\R0}ƿC;|6L(ŝr kcwOn6qEX߂⛚f'FFJΪo&rՔp9QOmT7-DJq<5JsCq4ӜMH:;GzT ԚO%/CR+\7 ̸X^Gy2+ :J{ 9É:+'q|"H37VMʧgRoX> B5b<&۰4q#RG޼Y_U>mi=a7;*9ˑ˙D7 fVWp`̍Y*?iP<;vyuNUf\<@qV( _NVfJ%>4}'ج.P5m+[2vw9 ~=Fun?vC};ZdoՃ2%pn:9ب9Rq\΁EzRS.2cGl4#-L,,4J^,l #r+-@Vs">NHRzHׄ"x~Bq|敡NV8:eI3897˾9BArNWȆo8H߇cs z{N¤ ͸H;W\ThπG_> o)Pa3_6Mq7r>;1==Rcn+khTM'?&ZI+5 1b%΄}}*@UߍhvW1e_6N׀&$m8l^\@,?x;*7yTj-3R>;,l(>~-\L=;~鹁줦>2GXP-&LLARxxjCl]rE P(SS)6zU錸V=zwl kmSUyw3 ?^R04;x£hfy3F% WQ1p>5Wja89fKye-εlǽ4*Gi~\]qFui/y{QIWKylԽPh_h И؝]I4LӯX346y+#Y5qRIJ:n]ZET1{Ku|wk%癆;lVx7ߨz?SƨT75A~gBqTBC iʎz\0g18"&j"hD=6v9-Ќ6]dUqGqz=y>tjs;qr~&Bb9j#Z9Ԗ<>\,&.r$1.7P#áS ƐKuN/h,Wy5,{X\=Զv܇bs-z|8ϣ:RDFY"⼇-e4"XQ0_sF S4Q!5!MC `rOUE(:0BHnF>NJpִ5b(=zd7eQuD|NxTZ90N>b JAOCFSeQK9b_cy犘- EH5Svh /Hv-"Ja)W! +C{d䒤1ȑc\m`;-&&tLĴ`0lz3 DzUpS(,q PBc&YmQqr?qd'六 %3 /\OzaJ: wվϒd=H*djc1L7;CSt2GRԥٹNvhhP3C3.Vo3A:*}#)A3cM!VoG戞(Tp6Ѽ=R(FL@wdyW¦-H)С-((}8@֐;$^j&^lL=)#z[vA)dX1ej t=Th%ul}ϩdJ RSh )+YCB uIr |E}-^S`$<:c'q@*e\RZ#Jb-LzK;A+IN)@ÌujIdW{hhP rHg6; c]\,>Эbj2ǔkS@5J "6@lc+TLHN$E+kιR,XŐzwBrw`Hc(zΒ?+e4j5agL.GDFxw23oaۚ⊆T/6XU <&ƒ^2׉fk˸ u}ffWsʛ;w)u{} *TL)>#qWͧ-Eۘ2l#΁Q Ƙ\3PK &$ZEՔվ\(W hN{M՝ Ҡ?L`iր& QGN!502m߭|PO:5&ЋuPDT꒒kcR3&pԢ[s KC;46iw'us-OK:MNRF=mQZ*j[QU{?}l]yDhtvQ`$~zbp@*3VVzI8RX1v|^?+mX;O.U 1EL@Ϟ)5BDKna4WшУ`ǯ/r @Jq,N(=qZVBT ^.k{-$J[ MI4~qNP:(rxZt-0pw 9׊4s,YEr _)북@ -6DZ8Yρz!ҖS~kK;3 lx aH<k}<_W^9罿0ѓFk{mE7[,wbx'eJASC;v8 &U͉I_kY>oj^.qǂ!gmJeK+׿^e{-]z| E帠Jmz lb|K*Oq/-8\} iu%躥!nv0> `]v%ʑ8V<$ٮΞ*k JJwf̴]LhZkGKۆ͖7IC[}]t-g<\!ڸ('LJc`ˠ%@d0 Vdɥ@ƈ>\iԘQI^@>>۶QzŕbL%'ݽta۶=[O1oyS' oP,>tvhF-XɌTX "d:6 m|)/~glD7+ aJ-}"aY,K~7#h}ܶk-W-%VVV)aЇׯ>o\()z(٠-BՉ_kJ\KK+|Dq[cDWp}j)M6{k<(;1']M/ΧTe:]@Ţf ۺkŖC!+.v2954?1m,u֛h2  As!w迹"F Yx5o kl ܿ\񁺔O"p*9 Ot`篯}-.x$Zxn0x;lra_/G+s Dћ K^&qBZcmwB<:-L/['cX׽,0t&EpP(`!'_M2Pq˰ykK4vIN8aZc\ׯϵŀTh _IxRHԉGk1na[Zs 7! CWhv$5εEPu ڶ *n(9bPL >:}[\uOr-3poR`,nkҘЦdNV`${eJ`9;\Ci4>] $sPiWU4lD: (n喳?O Cey"R-3h3|$pUys!L_bj; }l7(h\|s."$0{2+ąIkɽȮg*}}7UC&wGpH%\(.Z|k]iW_3o|y >[?~J1)Œs/UB#`19ܝZ>L&(f~um @P\Ǜ:.,gmH !Bd낆tjTPP|dxC0i$*RhS:DAaݚS)IZ67EeiCpӥ#IϟqV}IJB7-f 2R9s KsZOY);$~,IJ.rkB>!+Dc쩒8FRZ^ u FBX =ϭ_F$Cs?˅|)YPCOԞ~Md+] 5r۹HD'6R1FD`snn, 5+53-יq3G\l5 z%r2z Fu^6΀mgO}:_WjK>Hə_qP3Rrh-QZ9a,BW %" גS8_5/K>)'1U;T`K+E5%"z+A6rR3hz.A|Δ@'n$mڍƓb}S%,Ayag5mL Ji ꫥqCΩflwɱND?S֡lu`ɲD0BN)B4';쓩|5U[+ ~ #>~ڎ@0Wb늘"R%s4J~%h 289SyFOqșTþkAS\m )-? k:A%g֖*(2"ڒaw.HB ?|IObW?r:] EHL7+cѲlV -K/5O9|MtDc-Pz gނwy!1q nogܜ[5rm)'aߏ;)7r 屠ť5\o &" 8gtk$]X9=}z#FOQ<)Ҷ=T (op^W5Y4?*86›hb]̡=C!DƾHܖv!A^moOq%?aGT--M%`VZr-rihr-pGH03|#:4g%-˾(<€%FH9֔} fz2Ry\R crZU)siՔǨ`ܾ]qWΓLx uF:sxo'r5Ux́fDFQv?*euK̙ k n!(޻}VV3]lI j ;4(K_pW}Gzd¹a kC*t|a]!\#Mħ+i'r#:ġ^h%МAOc< 3{wX%':95z2C~_Z?wvϼr-^R怸ZibfF/ՇpigHP0sU4*TB'ƻ>4fkƤP):68LZ\Ҿi))Fsm=Pw. ]L$ vS90թbI Pk<6| ̾}?]+Sy/30Z*IJօ֥@'Z-C(gZQvtB LyY}15UpN6%CxwPM j(+*I-,0M.l p@byR;&Q>oPJE)["c24Wj|L-v2'ǰ4p ʥ]N3̸HDJ~: )Aٙ"K+5-$D3鋹fcb SuHtTӘ0m(1*0wNjuj tz#L^lUkN^gRI^Rs\.(5:3f"埴48ahR^‹KIi^~+χ\)(9w! Lv?P5"Q?&epʒ-$y[Zx/烜ƞHJ6[o#U3챁6K_&Y;r\w = DѥD,sŊLqkٵ}f vʙ1r,&-鶚K6U~aJ\'iwa>MvyzQǼ]PS- y[꛷{Qcnp(3r@ws4QhcҍTQ{99]]7d Sf:0[[?+DNq bLXԌ\g_mQqs[д K=zF 6髲pk/ЭR[gɍ%F貉Kv;MxU=j4pTxoa3F94 Gyk}ϲ$L=_ ItF4޾f-' 6*ÄsY)|MWK7wr6 0Uhqظz~3pr7?yc}:9pF􌯍`B'ߕ݇DTfK 2R>OLkFUXL&ɓ~i6RMvO"Q 2޾/Ͻ1>kjeVP܁iW:`/{&,xZn$]ST靖oM1ORŊ\UR[o`>ÊƽQ,PꣂMk)ETqٕCq,XUxP!={tKS,dhcXջZiI(h?M YOWTjO6Kg{ҕS5i{Y^#qZ ᑮ~-?7/ LQZ"b' tB?b_HV)i\ u.5F'dDW<:=?ajѥ\tc%E:1bY] Or2fϱ"]=<+S[x=u=XmXbKZq866?k|Ku""p=U} c7U=|2Ի39ԛGw2McqeL/4+vwXmx:=`HLs3;vy̧Z?T6tַ|}? #0+.ͷ3}#"G }!c^0tv-|b]H~ 8V*wp8GB8LJra%ݦUIO^I߹=x ã>:AOףQ' L1_X?&9ӨpPxFҤvƉ7`lɝ;XbDu7Egc!ђIENDB`Sigima-1.1.1/sigima/data/tests/image_formats/mr-brain.dcm000066400000000000000000020025101514013333200232530ustar00rootroot00000000000000 ISO_IR 100ORIGINAL\PRIMARY\OTHER\R\IR 199602161144591.3.46.670589.11.0.51.2.840.10008.5.1.4.1.1.4&1.3.46.670589.11.0.4.1996021610440014 19950330!199503300 150829.0000 1 155614.6300 P`MRpPhilips Medical Systems  OTM4 R4.5 0BRAIN > Gyroscan NT MR/BRAIN/GRASE/1024  7 019010101@M 090 IR!OTHER "#2DP6.000000 4414.826172  64.000000  140.0000002  42.593601 1H1 1.0000007.5000000  75.000000  75.000000 0  RTNC1 0 0 102 0 60PH QB ROW  90.000000 QHFS &1.3.46.670589.11.0.1.1996021610440014 &1.3.46.670589.11.0.2.1996021610440014  191 1 13 1 2"-125.000992\-122.842384\32.496708 781.000000\-0.000005\-0.000000\0.000005\0.959915\-0.280292 R&1.3.46.670589.11.0.3.1996021610440014 @ @(( MONOCHROME2 (((00.488281\0.488281 ((((((f(P-927(Q2265(R-19595.000000 (S9.570207(TUS8Z7                                                                                                       /XE9Y4                                                                                                    /YBAR-                                                                                                                        2Y=!CR-                                                                                                                                  2W?$!BV0                                                                                  ,XG#?[1                                                                                                         .TH%C^)                                                                                                  6UC##FY'                                                                                                    5XC!$DR+                                                                                                 8UC$&FQ*                                                                                                          7YA" $BQ+                                                                                       /ZA &BP+                                                                                                                      ,TE! (>Q.                                                                                                         /UC"#"@U.                                                                                  3[<"&"?V.                                                                                      3[>#%#?X.                                                                                 /]A!(DM1                                                                                                        3W:#!,EK5                                                                                                 5T8( +BT7                                                                                         /XA""-AR6                                                                                  /UB$+EQ1                                                                                                         -[D !*DN0                                                                                                *ZD$'DQ+                                                                                               'W@!%%DT)                                                                                                   '\A #"CX-                                                                                                -X<"# >]5                                                                                                        +S?!#";Y;                                                                                              .W?!$:R;                                                                                         2V< !>S1                                                                                                           ,T=! AW,                                                                                              ,W??]/                                                                                                      0V@ ;[3                                                                                                       .RD 8[4                                                                                                      -SE 6^3                                                                                                      %UG#5[4                                                                                                       UI  5V:                                                                                                          $RK"5W6                                                                                +UG!$5J4                                                                                                     0XD%9F4                                                                                    6X?;V/                                                                                                     2Z=#=S3                                                                                           +SA$>P4                                                                            *S> !=S0                                                                                             #OD";O2                                                                              %LB! ";P.                                                                                                  ,V>  ":S)                                                                                                 .U>##?R%                                                                                                   )Q@&"@U%                                                                                                !QF'! !;T*                                                                                                                 'PE( ! 9U+                                                                                               -SB%!"!5T2                                                                                                     )UF#"!8P-                                                                                                        .VD# =N,                                                                                                 8\=!!">K-                                                                                9Z<!?S+                                                                                       6X:#?R,                                                                                                                    6S: %?P.                                                                                          6O:"#;R5                                                                            1S8!! #=S3                                                                               /Q5"!!8Y6                                                                                         -O::Z5                                                                                            (T<AV*                                                                                              *T:"?R+                                                                                                 ,Q9'?O3                                                                                          .R<!&@P/                                                                                          +SC!#@S'                                                                                 (UE ES%                                                                            -S>%DS!                                                                                    +T>$! AS'                                                                                &VC!$@P+                                                                                   *QD$ =T,                                                                   .W@ ":U0                                      ~                          +`D!"6T5                                    }x                              1\B" 4W6                                      tq                              2\@ 9T5                                     jm                          -W?"  >O3                                 ^t                                     3T;#!?U/                                    |^w                                    0S9#&%<\)                                was                                  -^;'!<W)                          v^}                               0_?#=U,                             }g                     1TA#!DV&                     vjjssnmkny    t~  |mhZKOTNOW_t                         0R@%C[&                  ~vk\[cig_WX_gs  xiYGDJGA>;AMYn                      +RC%"!=U$                    vmdk|zjgnpjebabr paVZce_XZc^RNNSi                              0P@!"CS                    ~vtor}~{rgnvhgnz{iWWgz                          5S9  "!AW                                   tsz |ldphak|                    4T:! &BM"                               wwyt}xlaWW_qi_k                    0P>$'CL&                      |pjuvxvomefq dRHCFNXk}q\h                        *PA')BL)                  xgV]kfk{{bZWVdzwrUDCCGOZ\aiyjYc{                        %UE" (<N-                       xk\LP]cbegs{qma]ZNIUg{uzaK<:>@AJRLLWfyrmf[U\q                   #WE$#9T1                         mZNHKOU^TV^[au|umbaffb[PJKS]u o{}eR@9<;6;HOTQNTXb~~pcZVQRXn                +U;"">V+               z\MLHA@KVLAAIMW`cjsvoili[XVPQNB?83;EQg mqi\D8>=41<@CEGKNKITftworfQPNDGITs                   -U6 %":Y(                     ~\GKMECFLFEF@<:=A@@EIPVTLLNNRNAAA579=G[m hk g\L57<324676459EKFBEKR[ff`cc\\^IC;9==?Sq                     *[:!#:S-              ~bLKMG@?CLB99>B?69C@:>GKIDIONE?EJ=03<>:Ieu}chdXD9;97=A<30476;EC<CHEGIGNPIGIMNC42:;8BYs                         )SA#?S+                      oWJJIB?JMA=BDA=BC>BLLECDDHI>8?B:67424>B;Lp  |dvt^I;735=?=?<621333:=9<B@;@A?DB:9A@956;>CQb                                      -T?BS(                     zaLGKONCGMJEEHI?9BFDFIHDDGB:>D=1187593.>E@_pnkR?>:9DC66?<54735>====@A;9;<98843>;5689=IWn                            1X<  ?R)                         lULNPNH@@FC=AGC<=FI>9BF?97<B?;7873//16608@Rss~vpdJAB9>H=5:;:957<=;65889BD:1/17845;7/6;::@Nd                 -RA!<R*                   hTONMD=GOGACD?78=CEE@;<BE@BI@686/+*07:A<27Lbxt|vr]IB?9;;8=1'<B26A<;?;:76;EFB=83-,4>7,2769<@Vx                  .Q?!>T%                      bPOLGBGPJADCAGB<GI>;GE>88A?9=<7:;2-5859>85DYlzyhYJ??><99=<:;<71.:A74;:66968=83983;8*/>86=>Ig                           2V;!"?T!                     |]QOEBGKKD>?FIC=CIB?A@A<8AC:;?9:?8378447<;;ANh|}saRIA@<8>B=:98;8389/-7:558873354331460/7<:9>H[~                                 1U> "!=R%                 v^QHDEGLKCDD@EC<GHB>=@DCCA9:>3.8:6:<9736=;:>Hd{dRIGA=?94:919>40=<5::69:79<:45<6/54286/5@=8DXp                 *[B =Z(                 r\MIHBDOLAB?:CE@>>9:=GICFD;<?=A@97/0;5/:@<;;C^}hQJF?>>>@<745A=1;B59A7;?@?:46766/0971367<?:>Ph                  #\F?],                     jWQKFBDOL?>DC=:@G@?EDAC>9:>;6;?705715;64==9>HUuzhOLF=?@935>;49;7:3'0B@<;<<;3-022562./17AC>=BG^                 $UH!B[,                    jSRMEDFML@;>96?FA?B@<>EE?<<939B7-7=56?82=B::GVwjSMB;@C:159>@93:<9846>;7924>4/9747/.:83=>5<DGZ                       ([EFU)                   jVOKFGIJG?7:?<>GB7CPF<AFB<<;;CA20@=259:88=?;E[w~nXOB:>B?967>B=7=?<:8:<32>:6@<7<4*01/4/*5:5<EGT|                 *XDCU-                fWPFEMD@D?6;><@CFK>9B@<FI>88858626@?63788=D?C^~zvyXOI<5=D<37AE>:::<:8:61;B9375132494/8@:349=AHVr                 /WA>X3                  pTLFCLJ?A@99;;@DFF>;><>DCDE84@@2199=?429:=GBDdv}aOIB76=B<7<?7567<@<:1)03/;A66<54;619:1-3=?>IZp                    4YB CV+                  VIIAEHBA?77<7<HI?=GB:AF82==6753=?9=B51:;@HCJko kXI?9::7>C829=726;97:759;=7//42..16813<@?>=FZv                     3XD!CS(                 aGIIEKE:58::<;BHB?BB?>?><9>>77==;CG>559>BDFTr  ~mr} r`OB=89=<<FB67;89957439>7010/6801<?6.5;89=>H]|               /\B#@P'                lNAJLHB:<>:<BCEHC><9?>9AB<@EB>;:>FF<48>@CGN\|myzbUEA>7679A:4AK>48>8499..87374//496230.;A;?L^                   3W=! !@L#               tXGEHFDD96;>?FIHA>B@;@HB;@@68@<=BCC>6?FBBIRldp}i fYIA?>=74;=>==?A<628>933378--2((3.0;5,4::APg              5T=#$ @M                      dKGD@>52:<;;<FKB@IIABC93=C<854=A>DD:=?;?L` {W] y\NGA;>>5:B@@?=A:07?:633179/19557027549??@Ty             /W@"$@M"                     yXEJF47@=AH=:HJ?>?>><AG?6>>;EE;>EG?7;>>FZuel]  iRHBA?:58?AA@>>85;=;7328:1)0<92468:65:>>Gf          /SA'# >M)                    mM@JG@@?EKB=HKA>GD8<E@97:<<@@?FF?>@ABBQpjg aLB=>;339=BC=9;97=>73442/3:94:7,0=53;ACRt                1PC,!;S)                hK>BB?DE??DIGCEH@@G<2731>;3@E?:>?;>ESl~|XE??>:66;DH@;=;==;:4398984:?615886;BDLh                  6TD("?N"                  eL?=CMM?BPI<DJCCB:8<<6.4;:BA<BEADOWdvvUBDCA>52?GDB>;=::A=1/8936<:36944:?DNa~                 2YD'""CJ!                  {]NF?FUTKKLFGJC<99<;9;63>FCBABDJPV^ooPFB=B?27DCBD@<?@=<;;747604:6458?ELZo              2^@"%#>Q-             wWKE?BNRNLKLMDBFC;;==?FFEIHBDKMUdtgSH<;A;4:CGID=<:68;75=?78946>=>FMWn                     8Y>#"AY+          aQLECGIMOLGGHCAEFFEA@BDE@@JRYfvsaNB;778:AKQNDDC?<:>>55<<=A<7<I[t                  /SC%AY,                oZSQRNHIIJNKILJB<?DCAA>?N]hv `NKF@<89CQMCB:58?B@@DC@?87BOc                 #WI"!=U/              kWTZSKNNKLNNOQRUZWKBIU^hzoTKHEA?;@NRJHJIIE>?<568<N]l            (YJ#!:[3            redbab]VVZ]bhcQHVjmoiVLB?@84BQSOJB=>=<CGK\lx                (XH#<^3              {qppqwvpoojfk{{{iPEHBBR[VTSNINVW[l                 ,RF% @[.                    wnl_PUclprtvw                 /U?#!%@T.                wuz                   )X? ""%?V/                                &QG$"">Y2                 r               +SB#!%<[4                p                  .W?!"@\0             x              2U= "!AZ3         x            ,Z? $BV7                y           (XB !BZ8                p~           .P=%B[6           |}z               /O;%AW/          zz             ,Q<"# AY*             y~          /T8"'BZ)         y        -S>! =[(                      ~         (VC>W0                          (Y@!&=Q7                      -U@!'=R1                    -WB DT,                   (WC!FV,                   'SC!$HO,                  "QC&KS(                     )S<&$!DV+                       -Q@'#FW'                   4T>%!HZ                    ;Z: #AU*                   2[C  $<V.                  +\E"?X+                .XB!$:W.                 0U=""#8X2                 -TA"&;R0                   +WF!'>P'                  +\E$BP'                         +\F'>M-                         2[C #?S'        qmv     /YE#CR(        d          /WC$>P,       go      3X?DW%             y                  2X?EU&          v           2Y? BV'                  -TA!@V(                   (UC#7T5         x             #UD!$8R3          ~mlrv~            #WB #  <P/          nt^?BSX^r|z             %WE >V,         _eteQ^ifotlrsds  xjjy              )XF#;T-          kzzw}x{T]wzslXCHa{          (^E "8W6           r]Nhss      -UE%! =Z,          u~fVUf~         3MB)!FX%       le_`m  zrkv         ,OD)"BY*         ui`ely|tuz             -RB(##=R1         ~rblor    zt|        4U@# ">R2       {ko{y  {~      1SB% =W,           {}wp           1WE ;Y.          z~             1WG!!@Y*                    /NE%@Y&                            ,SC@W(                         1_>">Q'                               8[;";Q*     ~            2Y;"=S)        r               (U<"$AO.              {n            -O=%'>O3       ~qm                      1R="!=U3    lr|                  6Z6DU)       hyvzx{x                8W8 @V*       &^jrw|zp`          x           4Y;%:\1            ny~r`f          pr             2]<")!7[3           quzd[h    |f          +ZC $$=Y2            rkse\s     jw             0Y>! $EU,            wn{_      kq        2[; # D]+          }|yk        uq|         /a@ !?^.          s        x          7^< !&>X2      y              8W=!#";Z7             z    |        9X>! "#<W5            t            8[> !"@U0       q    ~|z            2Y?!!%C\(        o    ws        *\>&!I\!       uv  wvqr           2W7 &!D])       zp }{s\V             4P8$#$ =]0             fpg           1T<"%;\3       _z       -X>"$;^3    by            (W?!=`5     %oo          *L?$@]5                !my              *K<& F[1           lxy~m}         +O9&! FZ1             rlqxzfgs|         *R> %CS4        vsgtvo|yXcf|           -Y;)FM4      }vnsmrufZ\[        .V:"%CS6        prru\VQc        ,R?$CY4       kMLTp          +X9! !AV2     qtEN`        '[8$#;Z4       rb@To          (X;##<Y/        pRCXuy            +[:$#@L-       yKE[n        ,Z< %DJ,           ~ CMpyzb        1[:  &ER+         k>`u[             4Y8!"!'EW*       XG|{b           4\=!$I[%      U^i    1^A #JZ%    |}\n~      2]@ $GV'        wfy|                5[>"$EQ-       zl     :^8##FT.     |p            @^5"'JV)      wu        9U?#&DX-       pr~       5VB$!BZ0      |`oy         6W?(CZ1     y}sVsy        .\D" @`0          |z]T{~       .[@"& @a0            }|qSZt        1Y>$%B[,     xp{}yd[_|m       0^>  "BT-            xnqzwuc_em          3W>#%AS.            x|}mewtq_grp        -SD$#!BX.       xv}gSlkcuwuw             *ZA!$"CV3             stkaz|mlzu}e         1Y@$!!AW/           plw}sr{{e        .VC#D[*   {m}u{z|u           +\BCZ(  xyu~              ,[B=^-   {~y{y||~}zzz        -T><Z4        zt}{}wl_WTT\fwtlrod`bjv{        &L?$>T,   |pt~k\YZ[amx||}~}na[XUZiyx           $JA!?T" tq~tcXZbhjmrwyj^\UNQZfvr        $P?AN xoga\_cdbekrut~{nmfXTX]gxx      $S==J z|ga_\Z\cglwzuyyiijdbbcdfm       #U>8I& se_WTPQakgksv~gXY``bmd^w   %N>6M$  wlrkaea]iidu}ymTTal^OXy|{     "NB :U,  xyyxm_hwvty~a_swntrid\^XXtu      )SA#@X,  zxpefdZ[_^jw~rdwwil}vm^[YZow            3W=#"(?_+}}wlYVl{nYURLOXan~vw~jfec]Wh|      1_?(,@b+  ~xttZVnxwvl^SRUW`qsj^QW^TVpz      2a?,"G`(  rp{ytw|yzYSo{ibffkpoosuspy{xsjbZ\UGTtu    /YA!&I\.       rv}tmjszp_Wp}fT^p|}}txqlnrw|~zwxcL[l      (QD&C^1      ywncdjqb[v}xrpov~wtxkeuvvv]cxb        &SA&! !DY,       ~cimd`g~|~wonqsx}i`o~vpp]         &SA#!"&BR.      rjtkZd[YumW|          &N?" #)BT.    quv`^y^iwp\i             0P8 ! +FQ-        y}oa}gcvyrse^     4V7 +EL,   {kshcv{{u}xVx   2Q:!#*AN-   {rd^szj[-R? #(@R1       y_W~z^    ,T<"%AX/      xVck      +U<'"=Z-       het   +X=%$BY*     vnp      -Z= $FV)      nwx        *X>$ET+    pn       /Z9 @X/     y{      -[<!?[,   w          )V@%A])     t      *T< #'@^,     {y|          %TA$%@\(    {w}           )T?#"@W)        .W<" #?Y,    y      +WB#&AW'    ~x   -S@$*?Q)      |~t    ,RB%&<Q.    |s         .SA!">U-  {v        6[9$BW-   ~y      4_<""CU-  wy|~         3Z@ DW*   uv       3]D?Y'    vy|      /`D"8T/  ~|x}|y    4^@9U/   }~ztx~td}|s|       5b@;T,     z}~wlp{lWxol      2YE?P,      ~skbls\upjt       3UC#! <S,      pl`Xkz~gqugouz      -VA  #9S/     n}xqeTZmumpuhhpwx     .W? !#<Q-    zzytiWQY`tmklljsz      -Z@"#"<M,   ysynUOVQemqmskbm     +ZD "!8O.     {z{^GRJQuvvtpc_s     /TC!7O1    spnQUE9upzyeaz       3R=" ;N0     zngxsQ\V8a~upsih~      6S:"<R-   bbXTXC^yctuns      4R:!:S/   v\xmTVIZ|feywx    1X>$:M/     tronyzdm~YWRUo^os{    2X@!@N,   ohuy}rtj\TS~`Zw}p          .V@DT,     ||~pf[WtpQe~tw        ,Q>"=S2{{ynprf[l[\o{s{           3T8 !=T2   ~jfosiksYboy{o    0Z;" #=U5     ~mfktsq||`Sel{rn}    *T@#%>X8     ymYc{vivkynmeMZfg~sot      -N@"#AY7   y~eTdkdmplw|h_vhWZ^^gkfy    .Q?'@V9  |dZ_ULd||en|zwuwrabr^YZ^^Ubicz    -R@%@Y5    |ncaR>Lm|uagyzllx~r`rykb]]__XPai`u     0W@!%<V5    o{pbkgMHbqobejkolbgh_csmeYW[XMISfx^`{         2X=""8Y5 bfr[Wdam~zvrdUX_YY^`_b]ieb_SRXSMVH@VuyUV     /Q? ?d/ WXnwjWbjbg|{sodbcXX\_gpf_fkjbd]X[UJKSWRfrsNR  ,PA"@[0tHQz|kgWN]m|wbdeY[bhhehg\W`cioncVUSIFGCEM[zzbM[x        -ZD!@U.e;O|jPO^TVaYTTLFJQUUW^e`_bWJLTRU[U]p_J^   .[D>[,\7Nz~sTSgeVKEEMSQMIJUcrfY_YQ[]`mfo|_Mb 3YD #?R+  X.Myz|r]aXQPYgkowwvywuugcd`fnnz}pt\Sn    <\@$=N+  K1Qu{zwaFOdqz{k_n}pvt`^t}z   8^>$ :T. B:Vzz~}}zZZ{w}{gdse  1VC !;U3qBJaqr}zp}~lex|cb1RD#"?R3   lGS[mzisnhq] 8UB$!@R-   jHW`~gi~ptr4UC!8U1   mM`m|xtnz}{u} 1PB 9T3  xZixtp{xvmr}  1K?"!8Q9 go|xq}}y~{    0O=# 5]>  tpsry~-U?9f;  spt~x     *[E>^8  zmsrxy~  4[?B[1 }tr}~jts     4_?!!=[4    {pyqoun  1]@%&8R9kllvvy   1Z= &>P4 {dswt      3V=$@R6 kf{|{~  4U;%$9Q9 hk~v    0\;#'=N1  |xgpi    ._<(AN. xvg}ept   1Z?"&<S/ |uuuwh_}ro       -VD!##=V,  }~oxtQls`     &XG'?L2}uV]ch     0TA#%@N-     {y`VsZx    3T?&! AS$        z~cVye_     2V>%## ;S,      }nWu{at         .T?"">W-    y}akoc       -T<! &EO&      }sy||d}ih     /P=(&DO'      nrz}y}nr|by     *Q>"!GX$     kvyvsmjrlkxzzjp]     /W; EY)        odr{a~_]^acn~xtsen       ,V= #BU,           f_ekfXdhBIaqvr~z|d     &WB!EY(          tid^W_}IDdv|ywthpf     -XA#DX,        zogZTh]AWq|zp|pgvu{     1Y@&FV,     qf\Sgj@T~zppw{uuxy}        1X@%IY,      lYNZ{v^dukoxypsut{m     )\B"$F^5         eQYfktpxtmjsv}rrmn~tf    #VD$Ac8  dar{~ss{ynicgw{k     )V> #?_:      otywzk\W`lwk{         +Z>  B[4     lSU^ftqh}      ,Y?!A^+        }`UZYdwqn}  *_?! AZ*           ~|dTQOQbrsfy       /^> !<\1          |n`SHKVaur`j       -XB  !9\5      }qcZIDNQ]yf[             *SB!D`,        ~vxgYOHMROYrvZg        +RC# EY/       {qmxkXQJHQSQWle_~       'RF!!AW5           ~qomlh\QMMLKSSRdo_i        (XA@]1              wpuo^NIPRHGOQSaqrZ\{          '_C!@Y2          zpkdRHJLMJHLSWUarPPvox         *]I BZ.             }wo^MNOJJJEEPSLa{\Npko       1_E $#@W,       to\MLOKDFIHKMOf~zsiRXjk      2bC $'AR.        ~xrncQJRREBJJLOJNVV[SIqhj        0TC%"%*?O1      ywrmjcVLNRIDHNUSNHNLFkg\t           3T?&$&'@O/        }{ztigeWOOO]q]MS]XSwi\sox         2T@'&#$CR)       ufycaopigjgXSYV]ibz}eX|       2V>'%&ER+                  y}k]jqeOMPW^rjk}{fSc     1XA%$AR+           zhjpdfiwvneo          .VD!%8X0    ywwrt            /^C#:]1            nw           0^D#<_+             }p|           .YD !>Y0          yr            /Y@!DV/         nw               5Z; B\-       un         4]<=]2             z              0^C$?T5                      3^G*CM2                     ;\A$'DN*                        7U@& !AT(                    3RA%!#>W%                       .ZC"!$>Q%                                ,YF&@P&                          .VD# #>Q(                          ._A !<Q-                               *[C =W-                       .Y? "! <V0                      5Y; $!!;U6                  }             3W> "" =W7               y                2`=$  BW0              zz            /\?"!!EX%                      h|            'XB" 'DO+              `wu               $XA (FK(         \qtyz                )R?$  ?V*                  wyYndm~}vqx                )V> !@U-          zfajZe|k_gy             )V>!"@T(           ZrkYc`Sc               *T<"%:[,                 \vZNc}             -T=#";Q4               inl                 +WB <O0            vy                   -[?@S)           r                  .^;$<P/                             .];&8S1                             ,VB"!#;M5                                  /QD%;T9          {                   -RD&@X2             vq                     &VD$ ;U4             yup           'PE' 7W4                mojz                     +NE&!9W2           quhgu                   1Y;$?V,              v|uxWwk                  -X=  !CS&                   oz\k               /\=#BQ/         rw~eZmz              1_<$CS2                   viwSid               .]CCY-         pt}~|Idypjjly                    %_F =Z/                sgkQxpxkdenx                          "]I! :[3                hkZbh|mfsyu                    /]A !:Y5                    nwKg~uww{j               3Y?%"6X6             zkGwv}ukj                   .T?!   =W3                    ~R^ovorjx                    *S?$"AU1                              s}Bpxkkp                        1S8($%CP+                  xq|_x=V{iby                   1P;("'BR*                         ~bsQikTGjtZk                  +RB%!$=T,                  ma|SN}wei                     .Q>#  #>R-                     }}s]cb:\ryjh~                          1T;""DW)                    rryn]ScE7dqxfaj~                                  -X<#!?V,                          njfRMdqD:i|vn}                          +N='! >Y-                          ^`YH\~kC?f                       ,O;#%!AR&                            ~T[``d}fJCXj~                       -Q6!(CQ#                   z{`{|iVFI^k|                ,T=  $@P(                    ZpzpbYXq                       +TC!">R,                  t]yl{                        .X? @T2                          ~                              0[:AW3                                            0S;$CW.                          b                        3O=&!DU.                                |l                7T9!"FW-                                                   3V;!$GT1                         ry                          3R=$#DV0                       mu                      6T:"#>X2                          tmt                          6Y<""<V3                             pop~s                         6Z=(!:Y1                           ruakdV                          6Y;%$ =X/                        lmrzbKs                                 4V;$"AT+                           prjbXj                                 5X=" #?X*                                {t~`Eq!                                 0VD$!BW(                                     sj_Upy}jd                             +XF" #>P-                        t\Kn{kr                        .YB!##;P3                       L^~cz                             0Y@ "#!>T3                    jL{j|rv                                 1_=%!AS0                         wnc]w                         3\<!# !>T/                        zqk~                                   3Z;"#@Y.                             eqob`h                                        .X=#!%AP.                                     zpdR[                          0T?&'9O5                                                         ,RD$""8R7                                                    -WA <T4                                                       8X8!!AU/                                                         8X8 !?V.                                                                          4Z< !!!=Y0                                                                         3W="!"<T4                                                                     4W>!$;R7                                                            /YA=Z.                                                           *]AA_*                                                                                *\?"=Y0                                                               *XA  <W3                                                                    +Y?!@X1                                                            .Y> AW/                                                       +TC& >V.                                                                /S?%=W-                                                                3N;'"  @W+                                                                    1P;#$!BW(                                                                      -S=#"=X0                                                                   ,Q?  ;X3                                                                     +S= ?W0                                                                                 .U9AU.                                                                                               /Z:<X4                                                                                                     .\= =U3                                                                          .Z@<T2                                                                                                      'XC  ;S1                                                                                                                       %VD!?V)                                                                                  "TD !B\$                                                                                                   &QB"!!CT)                                                                                                           *QA%!@Q)                                                                                                          'QA& #@P$                                                                                           *TB!!!?R'                                                                                 (XC =Y0                                                                                                           '[C<Z5                                                                                                )[C <Y5                                                                                                 -WB#>S1                                                                                                             .W>!?S.                                                                                                              0U= ?V-                                                                                                 (TC!BX+                                                                                  )VA"!B^*                                                                                                .S@!@^1                                                                                                .U? E`.                                                                                         4R:""Cb/                                                                                          5T9#Bb2                                                                                                         0X:!=_6                                                                                             *Z?;]8                                                                                         /\B?W3                                                                                 :`<>X1                                                                                                          7`=B]0                                                                                              3Y@ Ba1                                                                                          1T@"@`/                                                                                                   3U?A].                                                                                             5\?C_0                                                                                                 2[C D\/                                                                                                          0YB"#?^3                                                                                       /TC$"$"=Y3                                                                                          .TC&"#$?U0                                                                                                     +]C "!#>W2                                                                                                      -[A AY.                                                                                               3V:#"?W/                                                                                                      6U8!"!";W4                                                                                                   7S:! :\4                                                                                                    4S< :Y8                                                                                                  3S> ">V1                                                                                          4V: (>P0                                                                                                      3Z='=Q3                                                                                                  0VCSigima-1.1.1/sigima/data/tests/image_formats/noised_gaussian.mat000066400000000000000000000435401514013333200247430ustar00rootroot00000000000000MATLAB 5.0 MAT-file Platform: nt, Created on: Tue May 7 15:26:11 2024IMF LwimgF.'g 8!n  Rs Vz  ce `\NPOcXTqn. S X5  ~{  0,  ,Ly_ZN("  Zl+xuZ> FLB) B 0_  Sw.h  SyVIwWOOh4 qUoyS abq  t  vFQ>  W u\ ,v s T6 j?$ j Vh ' q], . |Nq[  ;40 C}2{g  - iS u <7tw NJ   P>(7 e 3 ' pl1w<#`r ) $ mq %6>%< W~m } m? -q _ W`9HG> B Z'0 Ej|% V )rm h9zp"  b \& &wQN W6deo  7F q/ ;W  7W d  ]x O{ &  v@ X 6yy%v I m S7X q ` ||s a$raUV GoI S/y  w\8 9nPxv2` {y D_? rluUA {C ;J5 [ P  9\ )w ) p qs y!|9X  n    dF)P] ~:@{ = |X M> ~>  t5n 6; y k; g2,yr Z2 m-W@  qNL V>^vWAT1 L  _  g Q 0 o3 V  c ;L M[ &!S ( [. Er  @K7 !nj  _   "d ]4 SG  c .3 >l u Ga G * /v  i ._ L{ "   u oR  N  >U V~,@t q _vOC #m p(t26?H h u Q GAz )w ds*0dN r L 0L 7 5y  _BY % @ )  w)^ Z/J>hkt ) d UHu 8e7QWL kZ0z .> ?  <c ~ 5  vd Y  >hR  7}#5. 9 a0 KMH Zz8x D v>j ?Zq  3 h M r 4  sq>  c ) { ` G  / 2vi WS  .' xw U/  I i - #o2 Ia  I Oi .  ZVV9L#$Fng F*R)n'W; # < 0iM =#) A GE  > z   :g%L` ] P 4 xX5 _EMr 6 &  BA`|5  >^ `; y#  9HZ )'iUx " l  $ ] o v TS z3 ^ ;E\' N m lw  { |. y 2*a ,`v 6 k5 00 (^(< J ` 0: = <n hC fo ;  9Pb d  A8_(k} aQYnb(R p JZ~&*.TeI Cu . =&R h VM> GN<L bC. V6ppIsMP  {  ,  slY>6Y/ {| <G 3u!h U p e u3p #   w6a Ku r ]F3n0w,D5 .d/  em CP 2 `I L 8e} oaj7? YY  R ? P@ =m [Ex + >y0_zn k \u lA > J '  N   "*r 2 q kB 0 & W J r2  h g F ny B] r .gG 3 8a ~   YX6o! ;xI  bD = 0 (Q&'h  wG1- ;  Q v  P0%_UL ' (E[ =G;$X p51% D3 JAQ=  z_ 2u WH xm D e i; UMBKQ 8 O N& s 2N| 2D; T *Ot  kg^  k-    fkM@ >p@ X3h m | :( Nq[ ;)- m.  2  "+ F KveJ$u,Kj h i I; j lIOs < ~  M/ l c "  <  fylh U0 7 ]n8( ,,\1}    ;61 7  z p{/h Q A{. -cN~Q n  *|A5R (1S.{ }zcrc3px G* ] E GcU }:  A#F ~,\ > [} H>Eg {cU(em-c Z Zy Fk  dUW h q i @ G    +,a  rF=.   ~% ?g $R _+ s ~PaE `u('!6{R f O m /  ;   a ch6<1&!C "e 90` Nf=dL FR1>Y  i - 0 #2 V   ap3K_ 3   -  ^ b} $s  B eH ^  VHhtr5, $~#L" h >ng g g B K   ,CM Y co+M 5r,Mn  8D nA w  d}V Z: q,) oe\ av  >m ~6 U L: R" U$kw I [xw ,, " K X8zbY,r);m   c9c?  #4Y EFcl|P O5VB ^Qs . 3 >n:P @ L  X & X) \/T   ]$'- 8 #  2  - Ysr-?  'r 2'l 9/:    B + H  A5 _P !\ q 1/ EK.  ,wf)j X  8  ? yg^u v/m 6 [H @ E  L$}r A $ Jd ",mDly(K%bZ&RA doBH}jHW =  w G ! e[ " Y_ ` +4C `  !bd l "\6V \ q 1vjR ID   1 H Z 0_?  %2 v T,eWv d1 2^o X Y ( O <L{} u \oo; g ?  8r(MtAh G K J  _lvO7 L x +( 6 +4- JV0l W! o\`mI ` ni p  aV :W S b - H `p TJK ae mPnj q_ "K uy]   w * 7b-|   _ uT< u9" 7 & tua d  (-JjV dl F +@i2!  .i!OP U m:\j ' ;2 <J I 74  a$t1x 8F W!8 !; z   !ErH R Zf.07vk u[Qd eb 9v,Q!U~1 QM ![$ V!u " R ?bm *N  `Vj0 ,B9  pQbc3[#f I  = (*ea ni #v" - 8# ,!$r kq Pw < N }:  W0 bS R|! Mo'K"~ C$ ]," #7Y^> v N9   ;oQ 8~Up / K3dwg?c)$ "j !%$9 $|  ?H2n ! /6+I cd{ `BR>z C#! $I$  Z p#6"(K!!}m B8 fZ 0,R +  s/Q=t t f   B %h%8F%@2k"PoI T~@%pf)P);-+Q C d \zl !.0 w  /@" S Eo m[#p'tBpq$A% X * e{   %uw E\6 I F pn > A?: Nu U%3C%&~8$!%*"#J!4(B!((=& ;j'  Sh$ h  (CAQb! R"0%r"C!%~q&o)$'Y"'!e')*&'   CC?h*JQ  ^`  /p!'!| #N"k!'"''+T$ "!$;)%'"2&14B#Ig G"? A s 0 | RS }0B$$ "?8&k!.%$b, %)#fa Nz(W(`%*Z! #*& L k"t ] 1;@fGd h9$J]VP5 - '?$#wR$rb'V!5 (*). #B#V$,*!00s.s.-D  _7 i blb 5 !t "GuX"'Ua #'",H/!6$-("O$")V)*s(o .'*-"&O0-"y Z ~q w@ cl e}1 XL  U>lVFF0*)R #g$uJ!%L*[0g*"5'2&-/2..+#+ 3+*.)*'~ 3 qGE[* [) 8 E ]~ y!\+c2z" #-S!'\&&- #02@394%[O" {3-0$105%Fl*32-#Y8 0(  H vuo{n 0 eiC% s#$I&(i"%,+S">&y#,b#11E",+7,=*5.t+01,)v5"6k66.;/ zQ   . u> k {  >y&w&i ) "k#r&2g.d3#+7H$c2,&'x(8/*Y4$-/%.d%0C&'3Y)T>g -}i  2*5v% !<!Z T, #.0&* #'!#1'!-4"=!7"3=/7<:@,1*' :591&::1N ~ 05t%=  @{ms %& m e!%Gm'Tq)**%le&*0,L"!5#00,B9|6.#8.3;y&(S='O:-~4&31-)'$%(Qz +Ik:- %T5$X$,',T.;%% 1"t$J+$+]71,94J%p'J-B,14=6=n=601=5 (2@<49Lk!] ' / U PE MvEf!=# !oR#="C%#K%01\'%'$'4,%0)<8G?18>]+6*&>7u,+T=3,.:2b> t gt Yiy , &~$o+ \, ($5$2+;:'38y*/.)t8>5'A`C0>2-4>>1,AF5i87,AnC TlM)Ob j oz  =  u7j&s(S!1+^-)2/$$ *f'904-]3W'?2.b:38=//80?:28;@wF Bap>9BBF;<,?%B@GeDJ;%LoP7OD>7AE@(LFB c G p m  u "+ Dv+,u#**3$67'15d7B7v-c0r@30:l0<@SC:D5 F?bB?P>qGgOGNDGaBA;:<]Dh0?V=3?JEHN7BLA)CKIH'NeQHpBWGMFCF*M;5+hvA#1$-"'(.&%C/5;>6-1EnQ $ ", T!(<&Q$A &~$(L.&9+@(_$s4(=q*4:aDi7F<@Ab8XCICP;PHIbPyERCUK1MWXZAHKM\_PxZ^QmM^O`HZcx >W 0 ]"!3#q%"xc!JR',2[060*+'7/w7 :8@B48HNH;GIGWV[PUF(RNPKaRYcKMnaU]6V$YgSaP^LVbXX+ Dh IFo@)_D%?+G-!-[,3/2)b:V&+@2?s?4B>9(MN+JP[UsKRVGH;^\^VzZ`a ] hPZP9UWVPHXPWYLd"t Ah#qx _ HD#E% ,qh+v/&/04**6/;?4*3[?xAG09,5P5BMZ=SQAOSZE[ma]\Ob\1[W`Xad.Z[GRTedtiT\Vpge 0>G C 5h$&<( .""/)2'0&*g9.5<1.DF4J AF;lPNWsZkW}Z`N[`MrQdOblXitT_gU^XnuY^4`7VIZUV]_af[9Z=7eE +!G|!Y h"[$&v%327%167^1-6AE6FI8E;L; DD=JQt]aP6^XTTSiPX,Xhfj+Z(`Z~q|cit^bl_AqehXXlP 3 =V h 8!A 4#+(&%$'$ 3_#/(<o)N W!>! %z%I"os$!%2%Y5K48%:k?7*EE6>/:;HSINK5RcR`cIOQ ]fktc~jtqpa`vf?mhk}ovqMsG{|x1r|ejrv p Y" k$$D'm'T*'%".) "-!B3%8%59@+-:hG4G9KMEMGGToR[\eYa`arctbstpyz_qԀw-qq|yj5~tz}zJk 6& "[(|A,e+u23 1,:72>L>W>-m+337;K ABH@qXL3K~Q7aTbTke\jtomEx mr|ntmuuށσ} 8ynk)wxkIvXK9 L !H a(#$<,%~".Ff24N"1O..=6JC;*:LA7Q0JIUH-^`'\U'Y;fk\mpn2sv.h]gljxIw9v0;uts9|:v^{oottp  p 2&B|!\knj!*lD!12/x5+!&- 'g1 ,.:*9?JG\AOUbVBILNVRPRVfd,gX`cdrjxEe*tKy|px{s~?{x2p|Izv%wIe{Nn߂V )h s]p(b)"% (s#o,*X35I5G54@356;;OQ@CY"(4(*)7/AQDGEHB;DDFVSUMYbeh`1aVjkr~wr퀹ov7~3w~W\Sg{~|xKz`{ > p  Q! J!$!$(U)?*%1+*X+72(g<8+u6:23I>OQZDVER ^/Z!S^k``aeSow(kmt.{vt~~.6}юA2{dxG b3  K$^k$ ,N'<)6rX805j2;/C?E>CHTX^JWK_diWh lWtqzrlvstz~ΎaRَ,mvZz  lo!(a"#U#Bq--@-I3d,40/#2:+?-;F2G PGI"L\NjVWO]5[f\Fp%i1yPg~x|7zr(|4E|yL}v}Zܐ CxuG!z.an$*e&$x*3E(7,- ,$81K@O9*:>gE`glp`q|{g}y̅[JFh!t vT?6 " np > !}#"+&V y1_2*Q*$Q9},)53b7H1mEL}B1AbBfCOJJ ainjVkd6kwpbn_k{r~cox ~/8ݗ wmYO_ƌ󍣇T*B!fB! %6!3s)#0"/)13-!:=+>&:5D26BABIPI[[HJNSjaPb_g6gEumofs{pt1~PsR8Xkeo.Ì{ U - }"o!8%k)S_*(D/'+4H._-.3Y&-)3981FlL`P:BJHITI9Ua:\jZ`*ihwrtYpL:j47}M=Ւ s1q::ǔЀZ  # HT.c0%@062I%07JAv74;F`?Z;;mPO_LOY)ekcThqgcfxerzXxĈR\}~7 ;bx #}1(  _"g >$8)h ,._4e&$!!8 -37,@T59::EHBaR{HRR"cXlnn]2mh;tljmkɀ"uXӁ"`LJ锷KM{ޒWp ~ UT #'!!(X!0}09n(>=#6*1,43@HDNoHFOEz_MQeh\qLesqqNhX}Lp|t}{u̅Ғ͑׎NĐ:s} ۃbSigima-1.1.1/sigima/data/tests/image_formats/sif_reader/000077500000000000000000000000001514013333200231625ustar00rootroot00000000000000Sigima-1.1.1/sigima/data/tests/image_formats/sif_reader/nd_lum_image_no_glue.sif000066400000000000000000411403771514013333200300360ustar00rootroot00000000000000Andor Technology Multi-Channel File 65538 1 65567 0 0 1 1502999015 -50  0 0.1 0.119854 0.119854 10 1.19854 3.33333e-08 0 1 0 0 0 1e-08 0 0  1 0 4 1 0 0 0 0 0 0 0 0 4.33e-06 0 2 10386 0 1 -999 1 0 1 0 0 -1 4 30 30013 0 0 1 500 1 0 5.50173 550 0 0 0 0 0 0 0 0 0 1 1 8 DU888_BV 1024 101 71 D:\FV10-ASW\Users\Petro\exp_data\2017_08_17_ND\nd_lum_image_no_glue.sif 65538 2048 Calibration data for frame 1 : 425.36, 0.0483309, -3.41973e-07, -1.1823e-10 Calibration data for frame 2 : 464.883, 0.0476565, -3.89446e-07, -1.17364e-10 Calibration data for frame 3 : 503.828, 0.0469567, -4.36332e-07, -1.1643e-10 Calibration data for frame 4 : 542.174, 0.0462325, -4.82603e-07, -1.1543e-10 Calibration data for frame 5 : 579.902, 0.0454853, -5.28234e-07, -1.14367e-10 Calibration data for frame 6 : 616.991, 0.044716, -5.73198e-07, -1.13242e-10 Calibration data for frame 7 : 653.424, 0.043926, -6.17471e-07, -1.12058e-10 Calibration data for frame 8 : 689.185, 0.0431164, -6.61031e-07, -1.10817e-10 Calibration data for frame 9 : 724.257, 0.0422884, -7.03855e-07, -1.09522e-10 Calibration data for frame 10 : 758.625, 0.0414431, -7.45922e-07, -1.08176e-10 :\FV10-ASW\Users\Petro\exp_data\2017_08_17_ND\nd_lum_im04o"2sif14o"2"20P#"201/(2p#1/(2#K 20#472<1,A#00 #CBpBtABBA @A@AABCA_@,,BAB(B`A C\ABC7CCBBB@@\|BCAACX B`BA4BCPBlBCBVCAB@A BC#CABHL6CtPAA0(BC0CTAAABBB8CHBBB2BBtBBB^CB$BXBBBB0 BBDlB@BCACA@A0B`PBc)B8A8BLnBB`B1CAABB@0B B<I$ ABBL0B`AB~CpAAMCD-CBPl,B$|B CBC@@A? BA3BBBB$ /CA`BBBpB\CpACBCXHBPAB 0CBHBC HBpBBB`ACpB2.?BA`>AA B`B^CAPALlB#ABPAB@@BpBBCBtB,BBCB0BlBC@ABCBBhBYCXC/C0PAeCPABLBB'CPdB(BCBBBBBA"ClA &CLBCA',@#@@ABBBBUCB;BB0BB@TCB AC.&C*CBBLC_BB'A (CBtuCBB BBBC@A|\,B C@@HB@@ ! BC8@ ) 'CB@8TBBBBBxBPB)CB A@ABXA(BCC)CBtBJCTBC`BV#B BpC?CB CAp!XB+BB!BgCB]#B<LpBH\PA,hBtBC BA B)CBeA(BXC4BdBCB@BACBp.CCAB\CC`B@BiPAXA@+BBBCBCCAd`C`(B\BhBA@B@BPB0ABAx BO'C 0AB4ADBB[C#CCpBGA4 CB0ACB0CBBBBB'CB=@ B%BPC BAAB@Y|BPC`BCB@BC,B,A.|:BC tDB?C?@@CB AA]C@APA>CHBGCCC@BA0h BBB B0CFC\Cp `BBHBAC0BBCC@hB|$`B7ECA0BpB*8pACUBACB@ B1C< XPAB0B< zC@ BACPAtKC(B?8BBCCC@BtB BPA@(B AAB8BCChBPLpB?hAdB \CBlBBABHrA|BBiBCaC,?4B >|BCPAZC(CB`AA @ B|AkhBPC0AB$BCBCcBP C@ BC0C",BCBB BB|B4B@B|9,BCBB, BB+CBBTB0B BBCB4CB.CP1BCBpBBCBB,B CB)CB0B@ABBCPBB BP CBtDAXB`C8BB B`B4BXB ARCTB@AAABYC*CBBB Bw@@A* CB0BpDB$PAx@HBCBiABB"CBA<P-`A4BBA$ CB@`,BB $BBAABC0BBqC@BB > A0BBOC$BBBPBB4A B<BL@@C B BB@C DBB8BBBdBBPB\BBaCxxBBBhB xA(BBA,BBBBA@BAABBBLCCBXCB`BB@$BPABBCABKCBABBABCAlBUCBp$BPBBB&CB4BBBBBBpApACBB -CBPABBCnCACB0AP, BBBBBC= B,BtBCAeCB@`BA CC0hBdB BBpPoCC BBC@TB BCC B ApBAB{C$B`BBB$CCTB 7$<C`$C@AB4C=CBAjB@p/CB`dBBB BB AAqCB4BCBBC0BBTB@B @B@@d.$ CB1AB(LBA$CAZAB A CpALB-CPA`C(BpBBBMC4C(BxBB|BAdBD@B AB,CBxCPB1A\ CCAOAPCABBLBB8lApBC B`CB\BBAhABA40BA?BBC}@CA CLCC4B@BCpBABB&C B,CBB@$BBAA,B|@ABCpxB@BF`CBBCptBB B0B A@@BBpB P`L>CCA/BB%C>C>C%C[C CxB$BCBAtpBp!C4$BCCB C$@A8BeABCA@,B CCBBABCDB BB$B0CD0BaCC@BXBCgC0CAf`ABkBBCBCBA BAB\PB A"CBBBpACCAk>BBBBBA@rBDA`A@ts}&CBJBB,BAB BBQCBBlB@PAACXCP|BAB BBC`ABB+CXDBBBEB-CBB4BCBB@BCMCBB<C4Bl%@A@BBx@A@CTBALBxCB@~ACA(BA@B,C9<BA BBBBApAhBAXPBBCBtBhBBBB)CBq CDB4BXCDABBBHB1C\BAPCA-CBCCQBBXBlBCBA BBBL@B0A,`3BBB4A@AB`BBBAqC0CBBDB`A4CBZCB CA:CCC(BBB cCBB(AxB C4`4p0BeCBBABACAxACAAABpCBAABB@PBhBLB]CBhCCABxBB|,OCABCT@@$B5CBAB46$BB@dBvCBB(B0yCBL`A!CAB@X0=@BTBqCB$B(BB#CC@A\\BBXBBZCh@Bz2CBBxB@Ah'BBGC@@pAyCA#CdB_BBT0BAC CtBACdBCB'fCA@pBAABUBC@BPACBB BCBB@LBTHBB 8xClB0Bt\BZC|C#CBAN,@C,C+C8B`BpBBx(ABB2CBB0|BLB CBC@@X`AA?BBB.CBBBtA\B4B(BC|BAAABBAB<BCAA|BCYBXBA 8Bt@C4B TBBHoCBPBBC487CBBBB|BLCDEC BBcCC]C<BdB@BB`` [C`ABC8BBB$BCtCBBB?BBx*AB@@tBBBCAACWC KBBpBBpCBOBB\BQCAQCAXCA\B0ABAAABBql|CC1C@AzP,BBB (BpBC?BL8B B BBlCB%CA@ACCx<BBB xPAB @XBx0A0CpBC T~B(B8BBpBBu @`pA4BB-hdBBBBCA8BdBA `BCi BBhC C<PACTB4CCldBp@$0BBpABlA!DBBBBACBTApB$C8B`BBA1CC@ BBCBA#`8$8ABCABB7C{BBCBB C&CC0BAAQ/CFCB5BtBzCBCtBxB( @ CpANBBBrCBL$B8BH@C0ClC@@0ACB4<CBBCBCVBqLBJCBATphBABlA<@A0C"CBCBBBBBB BBBAB@B_CLBA A8AC@BAxB%A`D$BBBBh@?B@ B$AuCDBX4B@PB`BBC8B,@@-#&B2CA6CB\|BB#CBDCBp tBPCB,CbBC1CCB>lBBlC8B(`?@]CdB`B0BxBBB8CBB0C0A@BACMCA$BBBB[CA B>B@ BBD@BtBBBBxB@@B<"BdBAgP@@B%CBBBll$BBC4BABXB4W^C CCBAB'CAB?B CCB;CC0HhBB 5C)C@B@B#TBBpADNC2@BA` B0BACA=CB@ -CB@@B@BB AEC)CPB4B(BACPBBCjClBB M<@BWQC@AB,A+Cm CBB?B@CC-CB$B\|BACWBBCB8C A4C?ABB!LB%C|B`p CBLhSCCB8ABTBPBCB?mBmBCB,BA@ B2CBA(`BdABHBBtBGCB<"C0ABBdB;HB\B4BBB C\BP3(CBBBdCBAB4BJC A0BB/PA@BC| AO(D&CBBpBAheGCB4 CAPBBhB@BJCB`BDCPABABA(!C0@tBtB? BB$AhBBApXBABBXBBAB0C A0AhB B8B@A$BBT@BB@A6CACBAh8#BBC@BBD<ACdB@'CCCHB8,!CSCRCBd`BB1C7hBCBBpABB C4!CCC?C@$BbCB\B$@A@@A@;CABB0BpBBBGC8C LBhBBBL-CBBQC TB,`AD@BdXBBlBB@B4TBCBXBA0C(ACABBBDC|BBB 4D CBBPAxBBB$APB?@6CBgCB BBPB!bCCB@@CBBB|7ACBB,78CBA2BABBBtB| ABA8BhBB8m C6C0%B@ C CxBl@X5C0{BXCVC0Bh`APAp C@BBBBT-4CAC4Bl\BWpBBCBtCCBpxBB}BpB BlBBAABBA0BjC BtCB@hBAt@@CdB%CXBA ]C8BQCtB)C(B@ACBJC @AXB BBApCBA@AkCBB BX6BA0A3Cb BC0B!$CBB$CW|CxBHBBBB;CBAB$BAd@@PAyC4BdB@BA&C@A A\B5C@ACBJ2CBBBBBKCA`ATB#CBABC0C'C?@3MCWC LBBACB0B$BB@9CC@0AXBABxAAwPBC@8ABBC*])B+C@@CB@@A\BAdB@B4BB8BTBC4CB CBVBh AB CA$CA0Bm0A?CB@A3CBAB?BBB(A BBBC0|BBC CX BB %BBB(B@BdxBBCBAMCA2CpECB>BC(BB8PtCBDB0BA@CBB/BCC{BCBdBBBC B0T,B9CBALBBBB A,WCCCCCCAB)CB<C C@XABdCXBB@ABP@CBAA|BdAB)C1xBCPAA,pAHA B@,|BCA*BYC@80BBCCBBQPBdBB(<BBTC4B@4AB@APAA@#B7CCBBBBAhBpB3CBA&C)CA\B6CBp BBB#BA CBPABCA$B LBBBB$CC/CB%CC1;KC!CBBB4B`ABBd\DBBC,BBB8B@$CBBBBB0BCB$P4`BBBBB@OC0ABCAPBTC>PPCB,TBBA@6{B3CCC)CXy%>BCB5CpT`A@B1C'ATBCLBpATBBpBBC_dB B&CBBCBA6C1CB@ `tBCBTCCB@BB$Bl,B BA@ABB@`A*BlC$BA`00CpAB @B CdBA@@hB(xB BxCAPLB @A BC`CBB#CBARCB1`0XBB0BBBpA@BpBBpB()CMCBk ACqCB?CBBPPA\d C@BMC(B>CP<XBBpCA'|B C B@B AP@A(B$BpxBB\^CjC(BBECCBXBB| BZCA0 C+CcCBC@BCDB@0 BCC@lBCBB<ClB9CBHlC(BaCAPBBBB<ABTBLB(B B3CxBtB\C8B%tBBd5GC8BcClBlPB C`BBhBTC(BXBU4CICBANBBuCMC$BBBBBvB|tBzC@BACA@PB`B9,BBB2AdB"ClBAB BPH C3Bt(CBLB4B`BJ0ACAA| CB3|B@BCpAhTBBAB0)CAlKABx@B00BP3CBAABBB A(CBBB@ABWCB@ BG`C@@BC)CBFpAB8BB)B,B@A Bt@B|A1C BMC3CCABXC4@BnCC@"QC C\BCB`BAB -CC|H CCBB0AdBPAT\B BLBBFCBPBACB@HB\DA AC+C8CAC5 CBhAAB 1B0ACB>BxCBBDCB6CpBpCBCBCCB BC CBAB`BA|XBC/BBB?CA$BCB =CABPABB ChB@B*C&CBpAB`B C'CB 0BDCBAxBB`BACtB`A B ACBCB;CC$BC'CB4BCCWC@BA-C0B@UB ASC`BB!CA2CA(8BLBO6CCBBBCAA8GB C}C'C@JAsC\BpBCCBABAB+CAABB@A5BTBTBPBBbCBBB\B0AClBA@ACAB 8BC C CBBCMC|b|pAB0B`B@B_CBCLBBP$xBB-CxP@A(BB CBB@BCNC%4B$C@BxC(BB8B9BBTBCB\BBPBpC@ LBBCSBBdBB\BAB`$B-C\B@APAB@CtB ABAB!CB@AoAD$CAhBBPBB B@AA$A`AB@TClC@@dB ACB|p 0A@CXBTBB]C,BH8tXCB\pAB@BB=CB C`A(B@CRCB@B dBC A@CB$'@B^C A0|B&pACC,AQBCAB$ClCBBBBJ,C4B@@!C H.CpAAtBa4BB0B`BBxB0ARC7CAB<?c7CB CBAQ pABCB Y PABC`B CBAABtDBB\BBATLBA`CBC@C|<#C@HCBAHC C0B|B)CzABKCBl@CLBB$PA0BA@ACCCBFXC0'BC`PCBA&CtlBB%&CdC4,BB@\BBBCBB0@BCHPACBB CCB4B[4CRC8B B0Ax`P"CBCBBAdBTBAABXBB`ACBC*C@Dh!CCB CPA(B&A|`BBA AB CCC. BB)C,CBhB0B C\CB0ddBCP CBlBPA0C`BCABB@<@A|B|B@oACA?`B@`BAB\CB=BCB,tBP@YC5CxB)B8APBBCBNCXx CCAB@HBrCgCA PC B,BBP|B$((BxBBC40AC$ChCB|xBXBB`A ABB5CBABB)CLC4C@BB(B||X@C B4BC4 AB? AdBBWCA@'@@PBPB\B(BA@.,BCBBBCBB@BXBAB&CB@xB0B0A@ pCXB`P%xADCVCBB@HB8BwCBPABHBiCBCA BB BAB\CBAB!|B:C(oBBvClBK@hDB\CB|NCCBBTBB0B#s0BC>CBBt`A?BAXB`ABCB\BPAppAhBtBBB8CA2B(B>C/C< CAtPAL<@A|?CB`ApBBBB(BBT.C\BE(BB BBBZ8BB0At@lB\BB0B8BCVCBPBC ClCB1CBPB CA0BACXPC,BMC BxB CpBQ`ACBBA*t@PBfBCBAABBBAPTBAT(BBzCBB@BP0BtB(BACxBCB0BlGA@BCBAlGB0H\BOCBAWC(B@BAtBA%C`A,XC<BhB0B$WCC2'C)C@AA#C9CABABBBBCCBKC CB *ADBB0B@HB`B4ABCAABPB0C'C>A7CD8BC$BCAxBBC)CAB?HA%C!d@B5CvCB@EC@BBBBBAC,BBBLBABBB0CB A@]C&CB0RdBBC\BpAACBmCCpdBCC lBABBBABWCADC C`A 0HBBPA d0CC|Bl@+AC|@BBiCCBiCB@@$BPCDBA|BBPBB A@BlBE#ABBD-BBBABB.BB@B--CCN|B@CBl8B BpCdA|CB0CBBBAB`sBQC,tBB(Bl CLBBCp(BB@"C<T(CBBBBhBB+C<BOCBB?BACH<BB,BBhBzCC@@BBCOCBBO B0A*%C(>,JBBB`AhB@APBB AAJCB ABBW 4B< BBtB|\\ByCCPB4B0BB$ C& %C9C@@A`ABB@0-TCBB`-B@BB@A DCCA 0BB A*C`B8C)`dZCC`AB@WC@3C'C BCB8?C&BB$CBABlAO CBB0CBPBLRLB$B|`BCpBAC0XCDB BATB?BAALBBBhB&ACpxBOC CAABBBCAB|bPPBxB,C CB ?CBPABBBSCCdABCA CBCLAd@ADBB@@ABPBAUCBTBP4N\BACpAC@B8`ABBBBB<7CCBD|W YCHBB?@hBABhCBBCBxBLAzC BB\CB`BBBCPTYdWCC`B4CAB`+(B B|`ACXCHBBBB!@APBCCB 4B@CBLBANCBEliCBp@@CBB8CpICnCPB@ACp"lBC @C\BBHBBC:xBxBA?B@B&CBB&C%CBBxBA?lBBBC,tBBB!C %C?CBdB0BBB"CCE0CB5C8B\BAH&`A0BC CA HCpPAXLBABCC$B>CB B0B @BLBBPAABB45A4BAlB>XATpBAD;CBlpCpAB`ALBB6XBTB@ALC!CBABPB@B;BiC`B@@,BA\BA(CCB\BC Co pA*C6CDCBWCC0B"BP2CDBLCfC C\ @A\@BpCCBX`PBAB BC CB=ACAB84BB0$@ACB8BCC CBBC@tGCB|<@CPC `B3CC9(BABC>CCpAA C]CBCC@~HBNC!CP@B`AlPChBL9C0CB\BAOCBBBxAaCWCPA$CBBB|BBADC@BC(CCHBA*PCAA|BX ,BABA@ lB+CBpB <:"CCx*A@lC CB6@BAXB<BC AWC;C0AC7CC$B@ABCAA@A@BABBCAC<GA?BLBB<HBB`A3 B C C-C@B B5CxBH`BDB.CHB B B7C#CB4BGC@uCtBfC`LB1p8BBBArB*C'CNC B8@B.ClBBC2CTPC@ABBB@BtDCCBClBD`BB Cl`[CB0AHg CpBBLB0T<AB4BB$0BtBApC+C?@TBAACCBA`BBB BBHB$BBACBBLBTBCBTB@LB B AHPABhB 0C,*@<P,BCC@BBB`BBBABC#CCC ACPlB<AGC<,BCTABC,VCCpPBAB@|p8BA=@ABPACB|B,C_0AABBABCBBB B5CBBB(BB )C @B BAlBB8BB;|,BtB2j`ABBaC5A,CH9C'CBCAa@BBBApp:C8B"CpAvC?4BABCB;AB|BBB"CA4BB BB0C\TBDB@B3CA CCB,@Bj0HC CBtBBCA$BLLpAAGB8Bl=BBTBAppABC C C9CBAB4BCB@BCAB3C"BABBBp\BBCBB@AIC`CS_pABJCBBMBB`AC@dBBBBCP"CB0F AXtBCt&@BHB,BBBAA`AAB0BlB$CCBB0AA<BC|B/CBB(OA7NBC< BXBACA=CkCAd?B[CB% BmCEC@BB0C A|B?@|BCLBAABDBXCB @ B2C4A\BKCAABBAAABABHCBABPA1C,C 8B4XBABBABBB!BCB!D(B0B\B%ChB/XBBCd ABA H B C0tWCC@AHBBt4AABB B.CxB BBBAB`B BBCBBCABB@@@BppC|BBCAFCB|B8BPbCDB@C BBB`,$CBB`BL | PBBh ABQCB; ACB`BCB$BJCwCB8ACLB)C@d BBcCBB0QCCB@DC_C@AACBBAA*CCB-.BpACBB`CB@BB(A?BCt)C-ABZCtB,CA$BdB@BA,CfCBACBlB4BBKC0BB|BBC C ACUC BA,B|BplB0AAGCDCBBB >CC|PBdBCgCB,IC.CAH(L@BCCBCPAC|BIC'C<BBBtBpATBBABA BB?HB*CBA@B0BBA`A &$BICBpA@@C@@XC,CtQCDCB AXBCDB4#7CxB@0A@B B<BB B@dB'@ 0AB8f+LBsC=4 @AB.BCB)xBCBBB@0BSAp@BBABBB!(C@A6$B@pBdJCABBB00B@AXBBC%C|h0DClBABCCPBB6ClECBBA<`BA`ARC]Cp?(@dBBBPAA@B4ABpAB C CA00dB AICdBCBBpABB'CvTB`AAPBB@A4C@B BBA B\CBB{C?0DCBYBBB CCB|  B8B,BBC_CABBCCDC,BBBCA ZCBpAV@BPACpBA@A A-BCA$B@B@AC!DTBBCBC5@@B K BXB4C$BB8B,BlB.CTB4DBACBBBAA@B`ABCPABB|B BPAACBC CA(@B$BBBBBCB@BBC]CBe@PCCC_7CAHPABBP@BC`AP0A%CCLBUCCLhxBB]CB`LlXBAC@fC|BA8BAbCArCBB<?ZCB BCB\@@0PBBCAB*$BBBCA?B.CB_tpAABTCBhB`ABAqC C@C4BBA-C@8BBA,CBTAcAB0\BBBBBA3CBA@B\B@@BC\$BAB$BC3CBCB,B@B@xCB BCLCdBIBCB8BTBB1CC$B CBAHCBA8BA;WABB$B\BB@BB? FC%CPpAB@Q:CB8CDBJCAtTBCpBCAB4BBHBAB4BBBBC@A?<PCBBCA#CBB3C0BBB8CjCACpA+d B`B@BB`BxpAAC'XBBAPB$0`C'<CICl4` AABBHBCB`BA{ABBHBlB0 CC@A6CC tB(tAhC@CACWC@&CBtBp@ABBPA:XB2CB(CBLBC\B9@AB.CBABABXBBBB@BhB@A@C@?`BdBC?HB,CBC]CBBCBBBB4B,CB@ABB-C+ACB CB?C/-?C%CxBPBdCdB2C B41CCABXBC8CAb=C BXCB.CC@YbC|B0B,`BLCAC04BBAPB@C4HBCCAD#C4C\BBjC@TBACBBC Cp|B?CB$BpATBAATBCXBBC]B8CXBtBxBm8BBA5CBap\BBsCP@AC ?ASCBBBBdBDBBu(BeCABddBCA# B,B\B@@AABhBB`BABBBpABB`AC 3AB%CBB@BBBAkHBB@/CBPA<HB0pBBXB<BB8TC'C@@\BfC yCTCC`AB,$@A?THBBCC$ P`B7C@|OAB|BBBBCBBdCLBABB"CPABBA@t[C|@FCB02C4lBQC@XCBBCABx4BBCdBB} C B BB4BT`APABBTC!dBJC B@BB@CBBBABCCPB`ABBBKC(BW=C:C? AR BlBBB!}1CAACAd'CB BC,BBBBCBAABPPAAA0PB PAeCBTB/CCl;C8CCA08`A`pC#CBlBpA@?C0C+CB@B$%C0BBBC@A\A BFCBA|B`*CB7BCBUB/CHBmCBAB#@|@@pBlB,AAi4ACPA@@BCB _Ct4APABDCB*CFCAi`BCABBBCBPB#$BTCBBpFC@A%CBBMICC,C,B5@ ABA@BB BB$AB B-LBBCAB4A\BC|C0C|pB#CB(tB+C@AT | ABCWC0B@@CBwVBBBAACB-CBBB2CxCAHB,>BhBCC`ABhB(hB@P B4H CBABHCiCCB1'CBCC(C @@ACB@HB8BA BA,BCC> CBp A5CABBBpBB B DBJCBBxBBC 8CABBCBpABCBBBdB@ +dBBLCA(BBC )CABBB+CCuH"CRCB,@A CBA>C1CAB4 CECBA'BA0BBPA#CBBpB'CCBC A B!8@B0B%CC@TBBBBA`ABBB<P@CB*nCBBAAB CIOR8BTBA(B8BA@`PBBBDBh$CPt `"CCB$BlBSABC`A"C A B4`CC*C9C3CBhB6%$CBBBBAB<|BCB7CCt@A0BXB4B@QC4B XBCAdBB0BpAA8BBB`BTB~ @PBB pB@CCBB?@lBB@BBLp@DpA'CBB@XADBtGCCA@BAA&CttBIChpABHB0BB"CB?A &4BWCCBB,BABBdBnCB'AB#CA]6B CFC@ABBXB B@BAt ACC PA CQd !C$C$C`C\v$BBP@TBXBBABA!C CBBA=CBBdB B CC*BBGCACsC@tBdBCPBBP0A@\BC=CC3/LB\CAh*CBAAOC #%C!CAPA=$BCB8BBDBeCB A(<BB4`A$CALBLBBApAB\PC5C(BBB4BCABVC,B@p?CBLBpCBxBA/CBXBLBHB5CBC BAsCC!B*CAB CLBIB``B@@8B6ACBTBCBI:AB@% ABB0B`BBJZ5HBLBB*C$BGA8pBA:$B BChC8BB8tC5CX,ABpBCl98BXB~CB_X@ CBB@ 4BCBA BBpB B @@nC C ?AA ACB$C~CCtC\B(B B BBABBdBphBBBx>C@A BBBBP1BTpBBTB6ClBPB`ACdBtp@BCXCBF4B C3C$BTBBH@BCAAh BB CAAl`HCl BBDB pBBBPBC@"C]C6CBBBpAB@AB% BB?tn=C CK COC.CSBTB`5CB CpABAB\ABYCBC@PAB8BkCAB=CPChBBLBlB8BBAC|8hBBBDOCdBCA)BCFCCAB0$BBAB)CBB8BA@CXBPh BtB8BCAlBAPAZCBA`PC!aCCBBp`BCBC`BBXxBC5C@ A4BB="C?ABhBHC|@B(BhCzC|BpABAB@B@CABhdBSC8BB@ CAlp@@AlBB-C~C$BA x@8dXt@lvBCpBApB`,02C@CC*@@BB!CBxBBBACBWCBBFC@ABtBlHBOCB BJC(BB|``AC2CC CBBB BChBBBB:CBBBADCBa`ABBlB@APBB0A.C B(B@BB C@ABABpCB?5B2C?CBBBBBxBA8CC8,:$BxC"CA?&A?sC\C$AFB;CBCBB?\BC, tBBBBDB#@BCC,B+C=CQC;|zCA?BAA D CDXBBXCA0ALBBBBCBB@@DBBBBBAX BdB(BxB]C,B0AA?BC!B5CA$BhBA;C AXBphBBBYCAA< HBPPB<@)BCBA#A.CC0A^C?|B AB!CI,BSCBBBB8CWC BCABBBABBBX<GBBAA4CA CBACBBPA(Bg?CB`AhADCLF1 CABBT@1CPABB4BACBCB:CDCBL@6C $ CBBCCBC DB@0AxBBB%C%C`0A@dBXCBkCB@ CBApB@tBBCtB4iCB0@@]CBBA BCBA-ABH@CCtpAp|BpPB*ChB B\`BBBA\BBCB CA? $BBcC"CtJCBIACB`BA `B D+BB0@`CBBApC|@@B@BCBB`ALBB`5CBTBPBB@BBDCABuBLB`BA$BCPBXBI(@DBl@pB`B)CP(BPB@@BB@6BTC (BBAXBB BBCX` B[CACBPAB!ACJCB@@@BD`CBlB-l0CA?xBBDBLBCBBBB@BBB0BPA@`BA@0BoCB@B)B$CA?B@ CaCABPAb@ CmCnC9B8|BBQC0BA@ABB`B)B,CCBMCCA AB@AxBECD`A@ABXpADBDBCBB\ CqC`CyAlB\0B@C CA5BTBX@ BBH?CCCNBpACB@ CAOCC\BABB#CAmC>C04CC$ CA0pAB CBBAp@@B=C>C2BC!C\B89,BBlBHB6l(\ AB0BC B<.@?`A@ DB\BBx(B`MBBPBA8ptBLC,B@AC CB0A`CcC?CC"?@BPBB&C0BB{TBB\C0C4+B@@wC C@BBHBBBCAB BKC@@B,BBPBCBapAXB0A+lABuBBAKCB<B,B3( A 8)B6CB-CT@#CD@hABBBB@dBABp ?4BB+CAA0A`B}CBpBL$BCHB C|BAABPLxBBBT B`B\BBBBC0B@xBHBBBAHBpBCCA(TdBAA]C_CBBBhBdB+BCAAdBABBBC@A$B+CB@B CBB BCP(0BC@BTB0AA@@C C2CCBpBpPCBXBBABBCxPB CbC0BB@0B@A``AB(BCAA,BAA,dBBCBCBB@ HB(ACC;HhB"BBMxBB BHBABBB@tBA@pBBh CxB8BB$BB BmDd%CAAPApBBBPA_lB,BBBDBHBBBCtB+@\CwC5IhBBHBCBBABXB[dBBvC*CApB%CAhBBBU@@P%C0BB7CA@BNCvBBCFCJd>CCB4BB@}C BBt|4BBBxB'CpCBC>BBBdB#C<AlCpAAECpBB$BBtC_C?ACAAC$BlBBBACB0BTC 7CCC C|@B@ABL $B0C AB@LBBC]B%CPAC4BA\BB&C+pBA ABBC C(BdBdB C1CBCCBBB%GPBABB@CAB CTBB\B(CCd?BB0C`BLBBAABtBB(A4"CBBBTA CbC$CAdXBAAC$CBB0B`vCAC tB(APH CC3CA0B5BDBB3xB+C At# B|BBX^?BBs,B8BPAAXKCBMC BdCBhB0ABxACACdAC-CC0B@RCBAXB BB.CB,BB BBh@B"\.CA B@CA2C FpApBTBpBBB$CBChB4B/BDBABA@ABB CXBC @A(lBBB(BAB?BBB>C ATBC@,0A`BB`pBBBBBoCCc0AABCBBTCCd AB0@A@: AAA3C?`ABHtBBA@FC(BBBA0B*C C`Ct@AAL B|PACBCA8BB@BOCBBAC$CDB|BBBA`BBBBC6DB4CXBBPBxBB CxBAAhBBd4B%BPBy0AlB+CBBj4BCd CCBDB\BBCB BBBCBBAB@/AA4BPBA0B@$ 0ABB%CBC A@2C@B0C(CxBB <4BAXABA\hB CeCBB$C@B CBB@ AElBC0B8-AACtB ?EC8B$B)CB$CBB`A4"ABBL0lA B`BCBBB@AlB\BB!CB@0B8pAB@,PBhBt$,CA`[@AUCBpB,B,BC CB%B B@,B@@.CCB;(B|A8BsCB<(AB,d4B@BB8@AF|!CsC!CpB0Au\IC?C[CB+wpB]PB`A@,BpBaAP`ABBHB$B*ABCBE_@AApAlBBX*BLC PBA,BtB)BhBCABACdB8CBB$B'CB`BCABBB"B"@@CBBBBBBEA@ACBHCBtAA ACCGA@BAT0CpAC`B`CB_CB ABaCJC|BBB7CBB,ABBB A0ABA CAC`AECAA$t+CB`B APB0 C(BhB B<hHH(B@@D%CBHB0BBB8B(CBCdB,BB0ABB`A ,R;CBB8$AtCBCBB1`BCB%,F8BCBB3ACA\BClBDppBB'@BBBp|BpB<BB8xBBBB|BCB C_CBBAPAhBABB 0BBBJ GCCB oC5CB0B CB,BB8B@A(B A2CB@@BgCDBd%C+C0BtU XCCBbA0CBABpAA ABB!C0@@2BBA4BBDB@A:CCpCPB x0ABBB4CLCPB AtBCCHBBhC\B TB@@ B tBDBBkCCAAB|`A@PABB`C0A@XCBXBA0B0@A`B$BpABPBBpAt^`AB$BAC?ClB2A7C4BA.`BA@@@hBAC$CB,BPB7CBAA?CBBCB0BrLBlBB^CBBdB@BB`B %CCp@BBCB BCMlBB@PA0B0B!BCBBB@AlBBBB pBDBBB`A`l0BB|B*CVCBABA$BBACAHBBCB` AtBBD@T@#C0 B C[CBhB`(AB'C`A@p@AClBBpA +B`BA@ALBB(pBA*CBB$B BBLBUABApAB{C(BBB0AABABC`ABCBBTBBPBpCB`B`AAA BXBBCPBBA(CBCB%C@B|BiC.CB4AC@BAACxB(B@BBpaCBALB B`B AoCBLBB<CB ABABB`B|BBBBA @@lCpA0BAC\CX\@C/BC AB(B|`CAA CBBD sAzCCCBAdB|BCLBBpBpAB*C,(ABBLB,D@FdB BxB)C A B(BBBA@MC]CC@@,B`A B0BBB^CCB6BCABB`BpCCBB5B BBAB AB0A`BKC<A0APBABTBBhB\B@@@BABC@wAB$BB0BD@BtBCHB:CBABCBZBDC;CAxBB)C\BPAC?BB(BBABBApAAfCB CxB?B8@VC|B0C@BABA@A0B CB@ABhB!DBt(B BDB@BC BFBBCDCBBB8 0Bx@3C(C" CCHBBA@BCB@BBCACApABHBBB`CAABXB C}CBA/# BABAALCCB,B@CB0AB:CCX@BApA`B BAA}C](B@@5\BCBC&CB4BB"C\BABB CPAHB`ABBA>BBA@B(BBBBXBBoC @A)BB B?0BtB@BB Apl4BhBCBBd(0AA|BB C&0ABbCBB@6CLBHBd\DB4pACB6C8B9B8BDBBBxBBB CBCC^C`AABPCA BBBB3ACCCAB CLBBA>Y/B/CB CA0A@@qCBrCXBdBB #CB B(C CBB CBI4B`BBBJC|AHB 8*CBpB`AAABBB4zCCBOCXCB9CC@&CCABBCTB00BLBACBBB||BABBB0pCC,BCABAB`B@AACUCA8BB?CP:C\TCBB0A,\B\BBACA@ACPCeC`BpBpBCBpBdAVC C@BBBD4BCHB\BCBBGCA4C?BCTB BXABCAtB\%CA"DBC/CPI0AhBBCPCBoS`BBCABBB0ABdBCB$BBBAaC2CABA'$BHBHAjBB0BA\0Cl!CCAl@0 CB@BBB B@A AB\#CABB@BCC`ABPA AA|CC8Bx_@BTBB4 BCB\BBtBB@AdBBCFCALBBB`BAxcC CZCpBA,A<d PACBA$BA0BdBlBqCA`ABqCC[K\BBHB.CA<LB}CC\BTCBCPA$XBC@BB,B'BCABB'CBt\ACA UC-CALCBDCB$CPCBBB C BpClB?HB4BT (B4CB?BB@\0C#B<&BPBtB3CPBACB1CBBB@AB?AC\B_x8CBBBB*B2aCCB4BB BApBBBH C@BACdBCAFACB@BCxBhBBC@)C,C@G>A <BxBB BCA`BTCBRBCBCCCdBEBB BCXCB*CBBBpA@AJB>CAL`BBBC?A`AABAC`AhCB@XBB^CXCABA@BDCA@CBBDH`ABLB?CB-A CB CB %BACBBpA BB(B@AB ABrCCCtB@@B@ BB CiCCd(BBDPBB\B?ABA|B?C@AB,TBdBCtBBABpB8B@BB|YH0A4BC@C@B#CB 'CB0A$CBBCXBBA<tBDC@C Cx\B ABQCpAy@AlB@B ACBCA8B*CBBdB8C`BgCLB0B0BP A@tBB$B6CBB-C<BBCC;C'C4BC,B4B4BBC8BBB lC%CB4BTBpABB` B?B0C A4BpCB8BDBDBJBC@dBdBBA!C0ABCA@BOBB3CPA$CBLBCBw@#dCB`CCBtC|BT ,BOCB BABBB>CBBB@CCA$C8B`AA%CBABACAlBB CB]CpABDBBBCWC`BPBACAAAB BBB?BhRCA(CCA#C6CBLCxBABhCB%/C@BCC3 BCBChC-tBB CCPBB&C ABZC|CAAAD`AB@C0A?|BB@B BCB.CCCBpA\BBlCcCBBPIC9CBBUC BHB!CBCmCBBsCrCPCB3C BAB=C\CApAABBphCdCBPAB*CCBBBB@0cCBWBBB\9CvCB@ABB)CCdC OCBBACCSCBBB@CCB\dB+CB AAAAB`TB'CC @CLBBCC0\CBhB -C tABBABpBAPBB CABBBiC`B@uCCBBPR2CA<B@H0BBB`0B4BBBBLBBBCuCBB@ B,BHBCC B0AC'CBABB0A'CAC_|B@BCABC:CA@@,C`AC@`BlA8|BA8B|`BBB aC:CUDBAB AB0` bC-CB,AA@B@AD CBB BB BCA5CCB(CSCBABB DC.CB CBBCBBTB0AB^CACC3`WCBB<BB(B@@A0BpBBCCBALBCAxBA!CWCBC4B BALBlA|BBCC4B`B|B|B 4 BjCYC6C$CCBCPBx CBBB@AhBAhBDC@BkCBB@`ABB CCWD Af@eCCXBB7ABA: B+CCB3CBBBAB%%AB\ $AlBtC BBlB@BMCB;CvCA@1CRC6>CCBBBCBLBpB*0BDCCB0,ABlBPABC1CBBA7C@BA^ChBtB2@BAqCAApABC$B=B@BABOCA4t]4xBACCB\PB.CBBB*BBX,B{BBBRxCqCUCL :JC%CBdBB+ B`ABpBBB@AB]CCUCbCAX@BA(CBC(B@BABP.VCBC;BB8Cx`BBpD`B^CClABB0AwCAB@ABB@BBBC3CRCBAPAC`3CQCBXBBPA@A.CBBCBBBdBB CcCCBCBB ABBuCBBBddCCDBB@CCBXBC AB-CxLsCCB$*C(BBBFBBBC)BPAKCCBpCxBCABCBWCtBBB*TBCABCB.CB8lBHB/CBTB5CBB BB^CBABBC`AB,BCdCB3CAC" BX0PAA,BB@B@PAB,B,C)CB?CtBABCBxkCBBCCB CC`ALB@CP!CAPA(BCZCCAAICBACBA(BaCIC;CCC0&BTC@(BBRC C0AA4CBCB\7BpBBdBl@PB@BB0AD@.CB0 CCAB8BBtAC*TBBA{C75BCTB$BB3EBB5CBMBBtBA/CBCBoCBBACB@ABAABF@B@B(BB,@BOXB0BHB@ACB@CBB4CBBAWCGCBBABBA@B\BjC`BBB@@ A@CA\(B lB$CBCBB?lA0CqCt@wB CZZBB^CBvC0BC6CABHBBBCeBB`ABLBVCB@@C\BBBB$C@MAx-CBVC KBB@ CA,CCCCAhdB1C2CBBBBBBB6B0pBBCTBBXDCCBB`BAeCTBBBAA CPBC BoCCS4@BBBC.CtBB,BB(B4BBCCPCjCAApAADBHrC8CCBATB B@BCCBBB7CpBiABARCBCBB`5CBLCC HppBBhBBCdDB4BAp0(CABBC,pB,BA\BC BpB8BABBQCBB A CBBdBCB`Bp\B#ACCB CB`(BCDBB`C+CiCPC\QC@DB8B B B;CB@B BBKCD&CB8AbLB6C|B2CBB}CPBpB|AxCCDBlBBtBB ABxB8BtBBA/@AAhBBCCBUw0AACBCG:C\C:CCA B@BC?B&C$B'ACA `AdlDBB4BpB!CBB0B@A4BpBBA@BBC%CBCB@BB>ABx4BBC A@BBCC$B CAB4CECBDBpAtBAdCHBDCB6C/CEC,CBAHBBp,CBBBABCB[tB4BTBjC$CCLBC0ATB AA4BXABICCBAB4BCFCB BtB6CA4CjCBBB\ BABBCpB\B6CB+CB$BBKC PCC`8CB@6CA@BLCU8BBBB4BPBC|B^CYC|B!CBBB dACECBBBA@@tBHB0BOC 0jCCA(ClCqC@C CBCABBBBBA@@A`BXBB`B CC4 $A@A CpAA?CB(BdBBC ChBB BACCTBCWCB*CBAO4BCpCC*CXt OC8CPCB*A|BSCCCABB(XCAxBZC@B@B'C4B`lB.R0@CAjCB@BBA AA CP@B0B/CCBC4|BAB(BBgCBlB?CA3P"BB0ABHBLhBB@|X@A8BCPB|BAC'ChA*<BB BTBCLBAbCLBhCC 8BA(BBCX BB<CC fCBB/`BABACB B@\DBBA(B`AB=B,B_C\CABABBB0BCdCPB(4BCC CXtBBBT C"C B@B@AA\BC7CU`BgPB C@@@$BABBABB AA/CBABBpA\AdB4BPA8B`C4BBhBCtxB CBCC-C3CBp (BBOCBp@BPBBPA A8BB C),CXB1CmCAADC,BBBA@A\BBBBA BBBdCBACB AX?C B@@AATBsCB7CBx`BCBC$BLBCCGDA<ABAB,BuCPAhCBBAB0BDBl84CB,BZCH@BCB3C"C@BCB@6h^CB@@ABBD |BB AdBBtBBATBA0A$BBTC`BCB,B AB BB@@BB0ABBBBAPBAeC8CATBOC|CCxBBRCBlCpAHBtB;lBB@C C4BBBBAB.ChB @,B4B BD/C ABABBBC@V CC?8BB$BBPA;d`B;CpABBpA@BpBGA_CCCCBPAB@CB`BBB0ACXCCCTB@xBCdBCC|B@B*CB0A(BPBBSBJC5C`C@5C&CAB7C@C)C4BABAA B CC $BB@TBC=BBAALBHBICAApB,sCApBCA0C3DBdB AxBA@BBHB0CjC@7A C(@C/C B|\B(!tBB@BB@@ CBpA0AC~CB?C=C C BBABB@$CP`ABBPA0B$%CB,CCtBB@CACM@BHCCABBBtB4B CABBBCABBx A4BCPA2C<`B@^ABBBBBdBJC8BA`ABBB0ACpB B`B@@(B84ABCA@XBBTBCABBtBCBtBBC1CBAttBtB~BB`BB#CB8B|C,B CBB$B-CA8BA< BCDCBBBC$Bh`A9C0B*CW0pA$BB BBBLC@PBBBB PBCC0ABBBBT2C0BBt@B@%CP"CC,@4BT BBBBBkBBECCBc40BQpA|9@B8BBAB2CBABHBBBABBACOC C)C)BB BBDICT@AAB t`CBBhCAB@BBB0AZ(*CBHAKCCTC B?BBBBCCCBLCyC(ABCCDCC| Cp=CBAt `BICC0ABBDB CBB:C[CAB$Cl,BP BxmCCB8B CB BCBxXBCUC@PB pAGCBC.C(B B@BA$BA@B@ HBBBlC@AB$B `B3CCC:BDCBHB@@BBBB C? C+CBB@B5ICX@@ B0B\BB8Bp@@BBBp|B`4CCBC0AS XBB/xB0B=C%4ABhB DBtB@CBB!PB@(BB8A<A,CCTBBABxBC Bx#CBHC&Cx` BBB%pBA@BLBqC,CGC A-LB0AB_CPBt6CBeCAchB@PAlB\AHBFtBB BB|QCBBAnCABCBPAB\ B@CA npAC@BWC@B<@ABBBHBBBABBBT_AaCBBHBAPCBC@BBC=CABPALBCB!C2C`#C`0p0BB !CpBC\@BB`CB B^BDB CAB`C;C#8BB6BB`4BT(BNC@BCBFC8B"ChB BCBB\hBAB%CB\BABBXB@BB<APB`ABl\BBAB@ C ABBnCBAtCDBACDB@ CBB0AB`ABXB@tBXCCBCCBBpABAB0A B@!C4C,AB`d9CB0CCBB@@BBGCC\1BBBBA`B`l BBBB0@+C @dBBB0Bz,BCCB2BBM8BB@AB(BXBAA|`BB6C?C`PBBBtBAXBABBYC00BhB;CFCB\BBtBBBBtBBCCADBBHBpBApBBthBpBBA"BjC|A@CBpBDB,CCBB\B CBx?BB B0B?BDBCBA Cp?A C'CA3CTBuC@B@tC'BBABA@A&BBtBLBYCuC@ABA&BUC$CA,BCBC`BBChBCBCXsLBACB@ CdCWTBB DCPB ABlOpCBBBBB|B0ABhHCH ALC8BAGCBpB0 CBl!PAA(CC C\BaC AKADBCBpBBVCB<B&`pBqC(BZCCC,[CCBC PAJBBB&C4BdB BB B\BxC=CBC BA3BB.ABCABJpA3CBC , CCTB&BB4BBBB,C`8BC><B`BICChDICA\BB(BCC@#CDCXCBpABABABC>CBBBP C@ CTBB0DBDBBiC@B`@ @@ ABxXC BB|CehZB8CBB@BCxBhABAC0ABCABACSCJ(B CBB@@bCzCBPA'CBB@BCC4CBB@@pBA0BCCBCB@@KCAB/@ABClpBB0BCAB@?tCABXBBBB+B8B#CB:ACBAPBDBBCAC'B CTBBlXB APB!tUC3CA0MCC(B@A BBABB0AxB@BPBAB2BBBA!ClBC@@ CJB?CBBAXB+C3tBBAAABBCB`ALBTBB9@BCALBCX1CCe`ABB`B'CbC`APBBBwC6DB(B(&C@fCCD<CC,@AB ACAABCAB\BA7CDB@B8BB0BAC CvCIo\BBpBL A( 5CBECBC@ B@`ABBAB BCBLPABBB @|BpB`BABBBATpAB{CBtBB@BBBAB0AK@A$C C 55B@ACC,BACGtBQCBBAC6BTBBAC`Ac@B0BCCBB@ CtACCBBBA|BAhC@(B BppBLBCxB CLBC^DBBCGC`A0BBP\CBp7ABCP5?ADBBCLBPBlBCBAB|@@BAACB'BCABHBH@BB(C~CAX@47C CB BCBPCL\BBBOBB0CB8)BhBhBd`ABBDHAlCC@@DBBB<BLBRCCB@B:B@BBHBPABBBCC\BdCCC@ lCGCB/CAB\vCBB`BIdBBAABLtBLCqAAxB %CAfCB' A`AC@@ABB@ABpBC CdBB C\BtBBC8A>C\BB BhCA(JCB BCB0LB(BC,B"CtBCBBB\'CBCBCB`BHB@eCB@ABAAB|'CBA?AB$BB@BB2C C @@0C|BBBBFCB B;C1CAB$hHh5CpBTBABt#@BBCB\DBPB( C,CBBB0BpAdBBB7C3CPBBAABCCdBAwCB- B!CBAVCgC:/CBB?CAAB'CA'C4BBBC`B2CCBz@CBXB C~BA1C2BBAB@CdBT\BB|` AChXB0CBBCBCABCB$CTA8PA0BHBBBPCBBB B]CBCBhBtBBAB8tBXACpBBBBCA`B'B)C AbCCC0pXBBCmB@TCBpB BBB38A9CHB]CB$0B_@t&CLBpBhBTAAAACABCB$ApB-CCPB@A@`CBBBAB4CBBBB @BCCB CB\BMCAB$CBB@BCCH0ABABtBB dBHBBCABhBB@@BTACBBBB 8CTB dAB?d BBBBBACA<BBB`B|BpC@BdBC%CBX@B B CTBBA<PA\BtBtB(\BdBA1BP4JCBPZ,$ECBBB`AB AB@CB8BAB0C*ABB&AUCB@@ CCCDBC?`EB0ABAh A0BBBDB@A%`3CBy8C*CBA\ABHBCC CJCRAPAA@BB2@B`AXBBCSCCCC$BHC0B4B@S.CUCA=p<ABCB@BCBCBC$CBB%BA8B:C/ BBJBB0B BABLBB0@AB-C&C@.$hB`AaClChB`B`BCpAlBhBXC`BAABB BFC.ChBPAP(B@@\PxB,pBACB A8BBB$BBB@hBHB CBxHBBA+BB`AGCBA@0>tBBB>C@B}BEC!CBbChC=CB0[|BxlB C@@`BCBBABCBB4B0B$C CDCBALCpABB`BBXBB@<BYC<?B'C CB.C,BBBByCB8ZBBA C\P&CD`B C1PtBApBAPBBA@BNCBB`ABABAB4C<!C0AplA$xB|BpoCBBB8BBDC.BP4ICA4ABLBB&8CWCB\B0(8C B#BAC@)<BBCA\BBEC CJtBC`AlB B5AB9CA B@AC|4BBCBBP(BPpxBABPB BCB$BB9|Bh B$`@BpBB0BBBBBA,` *0BALA?aBlBBA C@BB0BLCxB AYB@B(C> CBC BBPCB|BBB0pA8B*C+C^C` CBBHA AA TBxpBCDBBBBAPBBBC\BBBDC B:X%CBB(Bh`8BL0CBBB@ADhC-LBABx0AjC|BtLBB>C(A{CB+CdLB7ClBCAPA0BhCCBLB\BBPB@AB5C BCB:A$`CBACF$BBHB]CPC+F CBpB6`ABBBp@C@B@BB$B C@ABCAAB B BdBrCBB(DBBlBBB@aCBABDBB`BEB0BxC=CLBBFCaCBBBCBCPjCBcPABBBKBUCCC8<B?BbBCPA8BPBA<aCB(@m0BHTBZBB)C`AB;CC9LBhC&C.C A@@@$pABlBB0tB8BTPC@B`BqCCBe\BA0BBBACB$BlBB pB>B tBAl!CBBABABC,BA-CB\\nA"CCBq0hBC0ChBABhBHPB`C4BP\B C/C=C0<BBB"C@AB&CQCAC@f BlBB|@CBABA"CABAOwCCB@MB DXBBC xACB`CBC B`BpA[AB BB{ A0@HM$@pAxB;CBAC@BCBB CCoCB@@AA@AxCChB>CCB5|BBBBCB8d;CBBB4BBAKA3BYC|0A |J@8B 0 CB LCCB1CB@XBB@ABABLB @9C<LBB CB|CCBp+CQC `BBBC^AcCA<pAC:C=BBtCBBB A}BB|DCCB?PpApB4BqC<BB BLBdB4C BBF DB@@HB|BCdBBA>@BBBBBx+CC`CBBABTDA7CB^CB`AB2CBBBBtB4CCxAbB\AiCBgC@AB 8B$@BCCBA<CCAB BC<dBzC((AB1B$CB%CBB=C'CAC@PAA BeptBUCA7BA`B@A B,@B BBA%CBAlPACB(BCBPBhBpB$rCBBBBBBpB@C?&?0(B`BCdB@A(B@TB$PCBnBB@zd`A@?hBBC$BBC$BBxB0B3CLC/`BB(BBBPlBBKCdBlBA:A0DBC$B BdBk8BC?BA?CBBB!CBqC2ClB,BC\ABB7CBBBBDBBB8hBBBB@AAOCC#C(B@dCC@A`CBBB0CZCB&8CNCkCCBCBB,B6TC5CA\BdB AUC|t|BCtB@BABTBdBABBcCBB0Bp,B(,CB3MCpAACAxB@@CBBB`6|BMCBAB\AC B@BABlBAB(B`A0BBGC|BfBiCC B@FCCo(ACBB$BPCCBBh 4BzCB?BBCBDXBB@C(BX A$]CBiCCv{/CBpBA=@BBCBB@@@AB}CLBB8PBBBBB" @`BPBB%,B A{CHBfA\TBwC CPApB0ABBA`A4AA6C;CUCBBBAB C\BBCClBC!CBBpACBKCBB BCA$B@PB@BAB CBvC%CBP`BSCBBAB=DC9CAAJCBDA$BdBBBC#BBOC$BC Bd4BEC@@AJC4BADXBLBBrBBxjCB\A0`AB BABBXC9CBtBBB@ABA AxBBBdB@@@CA`A- \fLBC`C-CTpBX"CpCBdBAIBlCA<AAC/CBBxBBBxCpAA@B!CxBPA?,B@CB BCB*CB@\|0C#C@B#BB,BA&CBBCB@lzCB@CB `$BB!CCTd`DB0A%CB%PCDBhBOCCBBPBB\BpBCBUB?AXB8B@A(["CC@ l(v\8BP$A]A+0BABBhCB6n:BCpA'C A:CECX@BB=B@@XXBEC-CBB0C@AAECBB6CB\TBDB) C0lBPeCCBQA0AB,BB BCC'CBFCpBB!C BOC50A@ASBKBPBB AC C,B AB`B>C@lB|X07CBB@ABAxCCl C0BA;@ CBB\BB$B@B GBqCB<AB>CB0BXB+ClBE?lJCzCC>C9BB\VC?BACC9C@t4BM@pBB8BAA,BBA(C[CB 0B*CBBBA(CBAB8CYChBDB@A,cC(1CB$C4BBBACPCB A`@BTB`BPB@CCB07X@C 0ApZABBABBBBATB@B`AB1C/C8C`ArC C$B2CBBJCCBA?1hBCABCBBB$ PBd@C$CB%A}Cp`@/C:CC:CBACB@^AB*CiCB C@ACpA$BBQCCgC!4PABLC6%CBBB0Bl<BB*CBNBPBCAtC$BA BBBBAB@ACABBhBtB`CBAB@BBACBhB@,C BD@$BB@B`B B@BByCB,A0A/CxB`A@BB3CCBBBAAApBBBPAOChBAAAd-C.A$,BBAlXBB@@PABDBAt@]B@B`?rCCAAPBBBAL4B ChwABBBB`x0TBACCCPB@B*CC CB<0B C@C.a6CBBzAB|XBB@BABAABBB KChB|DB ABAC pB4C@#4CB0ABB@`0A!CC@@@A5CCAp<BpC^C0AAB:@B5pKC(BB@@BB@@B@=PCB+CB@A B CAt(BCB @BBxBBABCCAx0BLC:B?x B,CwCdB\BBP@NCL,AA-BsC B4pPBB@lBPBl!CHC,CBBB 8IBXBhB0DC4 CCBCW"B`PBB B$\BdB\PBC(BBBB4B HBpB,>C C PA\BBB&HCAPB2B|BBiCp$CBc@XBA 4B:BGCBBBB$B\CXABMBBBaC.C`@|Ah@lBBPA2CCtCpA(A xBTBSC@BCxBBAxVCB `BC|BppBB`+ TB B@dHBCA@DBCB,Bx0B@BAB@@AAdB@Bd6pAxB`AHBdB\C@+PBAA%CB0AHBB+CA8A pBBCBPA@B|CDB BdBB@BPBBCB A0|B%BBtB`BYH C AC&OBBBBB@CPBBPB0A\ABB$BCBCB<ALBB B?BC4BA@@A2 CB*C)CpAPtBC CCqAB\BB@\BBB,B@' B%CDBBhxA=A@EBfClBC BBA@CBHBxBBBXPxBBBCIBB@BB_CBCnCBLB/CB'ktBHBCC$B8C0CCBcCB`6CUCCCBq(BlB9CC@x9CDBhCCPTX0*CC4BPBAAh\PxB4BBlBDB!CGC,BABCBABBB4CxB0BC(BB@lBB*B0A8B0ABLBxCCBTB B*C<BpB@ CBCCtBBHB@\B$B4CX/B`BBBC1B4BAlCpCdB@A?CATBBDABBBC9pCBZCA QCBBLl:BCAAXpBACB3C2CBAAB`B;ClCBMBBCCC6|AVC/C@0BAlTB@pBLC@TB4B%CBBTCCCBBBBBCB@A AALBBBB\B 8BBBDB8B&CT CCBCB#CpB=BBBCBBB$CA0B@B @XBB@B*XBCA"[ABAABB Ch0 AaC CBBBABBAA CBBA A`BALB@&BBAqx B@DBB4BhBC 4C-P\C"CA@B BCBADB&ApC/CBB CBHCCBCtBCBBCXBBlBu CtAC\CA3PA6CBCB]C@pBC*CCABBBB%BB{CdBBCxABAC@`BA8$@0B|dBYC (@ACWCBBICATB@ TxBBCBPBBBDB@0;CB@BBAlP:CGC,C?PA<BL5CBBCCBBxB|@ @ABBMBwC AAAB%XB.CSCC.C)^%BCxCA(dX(BBAB|x4A@BHB04D%B=CBNC4B AAB@ABHCpBB`BCCBCBBBABB050BB@ ABBBB8BBC<A$@BBh9C2CL`BBCCBCABB DCFCdBB#,BLBA AB"C ApAB B)CBBA \BBJApBA\B`BJAA CB@BA|BA C6ClBBCCSCG@*A$BABB4:BBPBlB\BHCAl@hlC>C>JABB\BB4ACABX AzB$XB C=CtBA (BpKCB8BB$BBkC@BC-C@4PADlBGCBBBTBFCBBPC$CRBBAC B A4 ApQC0t `gCACtB2\DB|BCNC<CB B0BhCCAB<B|`B&CLBA'CBBC B|HBCp3C@A@^C`4BBBAC0BBXA-CB5AtCB4")CC5CAB@BBBA)@ABAPA8BGB$CBBLxAB(C@B?CSCCBBBB7CA?B@@BBB HD CB?R@@lBBBB8C `BBAB?C, CCC\B0 CACBB@%C<^60BBBB `A CCBTBA@BPBBdBB@BBB%BA<ABCxB@@B_CBA@(QCBbCTBA BCtBBBXB@@Bp C4BPBCBpB4BB(BtBBsCpCCp@@BA<BAA CBPA'4BEC7CBBBX|B@xB CBB!CC@"CBB.C4pC@B0BPB(ACBBL\BBApBC CA,2z~CPC&CA3B@BhB%C@BBH0AFCB BAtB$ABA BxLoCB@BA DBHBC@BBBABB AhBB`BACABBCCdECB, .BB BBBB B$BB'B(Cl@?TBB`ChB'B;C@ABpA*C B BA0AA@@@B@C`LBB0B BBB|B;CpAB`A4CBBBhB;Ct`BUB@B(B`XB!SJ `AA BBBBB|B$C BArTXBBH C@XDBB8@B:ADPAP,B@?C2B& ATBAB XB\BBBB-BCCBL@@BBB@A@@ABAC`C(B?:A,BhaC HB\0,=C,AB@ BBQCJA CBB+BtBB?BB@@BBLB@BABBB|CBBpBBABlBB0AC C9CBB5CB@@AACB'CB`7CXBCBPpBDBBBXBR`_CBpBBB}hB,CDBBC?C$tATCAAACpCA TBCA BHBBDBe CBBXBBBA BhB@5C3BATB4BBT(B\A4Bl ,BB\BBB8B0AC0B)C'C=CL$B+CpCP`BCBBBC|BTBTB B_C,B0B0ABA BBCAB/CBBA4B/CBBlB|CB@A$BAgC-C@`PABeBBBC BB 8BCB\BBC2C*)C`CBvBDB<0B,B3C C;C|B{@BB@1CPB+CAP@B]BB|BBAC7C$$HDCB@AAB$BB`C0B> BFCB8B7`C4C@B B8B|BBBLBFC4;A@BBA`B8CGC1bCC,@A0BBtB$CBBP@-6BBBB BAtBXBB3B0BBB$cB.CPAXCECB@@EC/CXBlB C0C C7BpBN4JCB A,A(@B@P ABXB7pB0BHB+ CB|ACh?d" B4B8BB BBBpBBBB=CiCHBBd<%C CB B CCCBC COB:CBC@Ah BB#CSCB[x@4BBBB+CB} CBAAClPBA ZCCBB0A RCCp#T9CCBBY@*HB0ACBIDBBlBBABHCCB8B$BBB B\A0AvCiA`BBBBBBAB-BBHBBMCp`AB@xBC0AB#hB8AbC.B`ABhABDCPBXBClh0B8BBAEC#CCBB@ABAC@@B>CBAAl 3`CA4CTB5CXB(BPABOCB0A@A$CPA@@C$/hBCBCB A$0BGPA C0BB hB4CBA0BgA$CBCthCBA`AAABABdAA\BB0A)CBCCBB:CBrCBABBBhB=CCBB@`ABB<B\BSCpBA8|BdPABAABB`B\BA@BLB :BB[ACHBBp,BCC_C BhBhA,B4BB`BB<`B?4BBCAxB BB B1KCPBCL'?@@@dBtBBC C(BB0B BDB6CB@BAC@@CUCA @BBX2CDBBH, xACCBBUC8A@ C)C,B3CBBBBLBKABBTBPABB@@BBB +B\=(CBAA@HBBXCaCBABTBNB9C A1ClBBB0[BCBpzABBBTB$CICp4B@@BxBBA?hXCCBALAxBCgCB1@A`CUC?x 0B `A`AB C@BB@,BBpB @DBALCB$@ ABACpA,BCGC[,BB%C4 PBlBBBA1CBBAC<p(BRC,BBP@@lAB8BCC\8XBgCtCBBTABRC Cl@`TCBw4>dBBdBCBA@CABBBA4B?'CB@BCKC.CACB CBxxBB@B)CBdCB0ABBt(BBdBBBR0@BB$B@BC@B 8yB(BACCBB=)CBB0ABBAB`A@BBBd@d,BB4BPB` CB`XCBBxBA CCxBB?CC`BpBAC08?C,BBhBBB(C9B=CXB@PXBBB@pB` AABHBPB0CB@ABBBCTDB7BBtBABBBUCBBHB\BTBB.CB*9BCP @@LB(B0BnCA CBAAmC8B CC8B?DBCKC#mC!CL@$BC`B`BAC*CBAC@ABBCCA@tC9CBBBHBB PB(CBC|BXB\BB xBBlBA(BC@$B}eC CBl@tlBCBBp BA|BBAdB:BB?AAAXB CBPA<8 BYC+C40@p ABBY0B,B=CLC?@8CaC {BSC@BLBBDC`pQBpCBA@$B`BBpdBPAPC@ABBPB+CBhBB`hBABBB'A$phC BPACdB,Bl@@AB B|BC,BDB@CA(Cd1BiCAJCM BBC@BBCCBtBBB`A8Q8\B8AxDBB HBBX$`BBB tB8BdICB`B$BBBBB'C$CB|BB?DACLBC`BB(C$8B`A?TBCCp@CB)C,CpBBBB C0BBBA@BB@&C?A#CAWBBB8B,BAPBPABuC.AALB0ABA j+<0B A3CTBBBCBABpBPC$@ABg`ACjCB0A@A@BTCB/CB BAxB3!CBD@AB|BBDB.A(BB@BxBC!CPABAB \B?CBBBB@B@AAAA@AA HCB@B7CdB,BFCtAABC@CC|(BAApCB@@0AxtBAB@$BBCC CXBA}0 BBxBYCH#BC@CEB1AB2C"CByICB8BABB A$PB}CBABtBB@0BBABdBB$,ACA ?|B/C,CB8hB@CXA?0C0AA0AB\<ABB`AA8BlBB-Ch8tB<AA BBB;C@C0A$BtBCt\ CAB#BAptpBBP$C`B!P8BBt-B C@BkCB|/xB$BBBBQ ABBCBBAp0ACB-BB@`B*CBBH`ABBADABB$B`A \BCxX8BCB@ @AB`C0C BICBPA!@ABlBAB C@`HBPBTBBBd?CAB/B1C+C8`,BC0`AlBAB|B%CAB`B(ABC8Bx0AB/C` AABBBBBB0CCAlXCtCBuC CBHC7CT\B@C C\89CB\B/HBA@nCGC B C`BBA@ACAB(C2BBC8BBBDBA#CAB`H@AtBBhBB$CBC&^BCX@H??l:CAA@'8BB)CBCABBB B@B`ABCCC$A@ABB!CBC?!\ CdB BCBB@ABlLBBBC@C BB0ABB8(dCBA B &A`AXBpA=CpA!CB@BVC@B`B4B,/CP6B@B0AxBCD,B $@ABBABBxB?BPBL@H B@BB,B4CB^7sCBHDyCBB@AxxBB@CCA@nS@@1CpBhB(E,@BCBB CeC7CC@B[CA0lBlBB@@@XBACBBBdABBDhBA#dB4CKC(hBlBBBn>CPBpBBABBBqBClB4BDBBBBA CdBA@S65@A1C@A@A8`@B C|BBAA sC=XBtB`CBABBABBB AdB*-B CB&CB\?4BB,BPAl0BAA3CBBACBB@BTBBBBAA.CBBB.CAB,B@A0B )BB0AADC>C$CBBCC8@@BBAKBB]hBB C@B8BB<0BBpAB lCPCB0AAB@BOC@C1CAAtC @HBCBP`ABHB A$BB CBAXBB7CA`BhAB\C7CAB4B2C CCB(BBBCBC@@BDBPAA@@LB,B4CB@@Bp AC8CCA@8BBBBB @pABC(#CaB`BC@BUCB`A@BABB BBB@BB@6BBB(0 BB(B%C\CC`A BhB@B0APBABBg+CB8C@ BPBBB@,(B$AAAC ApABBABB0BA?PC4BC APP BABpCHB,B4ACBB<l@BlBdBT@LC@BBtBBBXBAA CB BkCC&@n@ AC 8BABB\B1dA(BlCC`A<YC0BxAABBBCIC+CHB$AYCC5CUB@@LB\C@@@ACC(A AB@B|B!CBABBBB?|BBBPB BXB.ClB@B@ACSCp@BB BB+CBBBA?BB@LBB8C CB`BpAA@B@BAHpaCA0CBCAlBACBpACBp$`A0( ABCB$@APBBB@P $PA CBlB@`BAB ClBB? CB` B BBBVCBPB0BAC9`B`AAAxB @&KC6AB`BBB%BBB,BhBBBMB@AB0ABBPAB%CC`BSB@A@Ad$B,BBA$B?:xBBpBtBgB]CBpACBXxB@BdTlhBCpBxBdDCBBBCB\@AcBABBBC@\ DCjC0ABBBA CBBAAACBd6A8 B3C<B(BBB ATBPBB`ABBBB)C <o@C BBB@ABB BBABBB8(BAB`BBC@@IHEC( CBU@A!CA4@ CB-tBC(BBPL4BCCf/CBBCA AKCD\CPB@ BBCBB0Ap- C&C AB|>`CpABABBBBTBXHCsCB2BBp4B AFCB B`CA|BBBP}@BPBBICCB\B`AABC,CtCB8@ BBHCB@B<BBPBB8#CBC>CBBBOCBB@pABBC DB$CAADBpHBhBB C\AhB@9@BABBBLBApBpB BLCCD(BBCAX@A CBpACnCL`3tB$B BCCv/BBXCHDB(BBPA`:BBBlBA@0A@@|BABBPACC`B/CB,AA@BHBATB`AAB@ATBB.C4,A1CDC0B`ABBBB!BC@C CB@B2CBC B<C4Bx`B}CBxB@`BC`BCXB`\C7CA@ ABA90C?ABABBT?BNCB1xB0(CBXBCiC0U!A?@@pBC B AAHBXBXx CtBB@B,Cp$C@B@@ C +C.BABgP,BACBPABBBCB-pBBRCC`lBCB?CtBBBCAB B |@@`@ BB@A@BB@LA!CBB]CA0Ad8-CEC`B BAP HCBABCBOLBHC0BBA! AAPA!C@B CQCs]BKCACBBXCA8ACC4ClBBBwCB@H>DMCCWCPBLB?CBA(9ABB@ABBBCBBBC CrCBhBBACBBA$BA,B4B0B@B BCKC|,BB AB@ C0CABXBBBBdCB,?CKC$BCCpBBB.BBAAACpAtB ABBB0CB"C8C0C8BBC#ABBC4B0C$0LAC0AA@@`AB0CACBTtBBA4C@A PC4BB`BDB@BAtBAxBCxB pGC8@ACPBB CdCrC C9A$AYC`ABB1CCBCBAC@&)ZC>CBsCB$B(CCBBBC,B\ACB0C=CB0BBBB<B(AA BCBCpA@@@BB4BBLC@B6MaCC"CCB@8B(CB B CdVCtB1CBA`ACB*DBSC{CKCHB<CDB@@0A$C CBA.BPA@ $8lBBLB;C[CB0-A B(BBBA`B=C CCB\B0 @ CBBAA&CyCB`l,Bp1DABB<`BA30CABACBBTB4BB|BLC@AlAH@AB|BRC C|BPD"CBCJC`%B0B)C0A@CB@CC(C0A@BXBB=B)C0CCB:C A`BBB2C`B,CBDB@BB8CB@$BBCC<B@CLB8BBdHBCpBB&CBT xAABBBBCAp'UCBAABC8C B*BBGC C,B>C0A@BACB CpA8 0p BABBAX)2dBCC^CBT8CwCNCUC0BAA8CBBACBPBB%CA@AC4BB$BB C9E\? AD0 ChBA TpACBA5$BwClB3CBCBA BBB$BBCXCA&CBA`BB pB@`A$BB*CBBAP,@A@ABgCB4BB\C`AAA0BB0BA<<tBB(B4BCCB0BpABB CBCuC CECBAB dB@8,BB AB,AHBAA`Ak8BLABB0B$Bg402AlBAHHB(B, BB@BB @TB0BPBB t BAABBA ABBBC4BBBt`AB6CxX`sCC+CO $CC\PAd5C0BdBDB0CCBC@0T`CBC@ BhBB4BTB"C$PQCC ACBHACBBB$$lB!C)CBCB@CBCC?$B CCAdB@@ABB#C`B1U|lQCCA@CUA@B7CBh @ CCpBxBlB+C@AB$!|BdBPA@0CTC0@|BBAPC@O,BABBBB;A`BpBiCH(CBC0Axp0C6CB(B@AAB0ALBxBBB8@@A!ZCCC4\B<AHBBBxBA$B,BCYC(0@B%A8[CCB6C BxB |B.CX(@BCBA@BBBTB CxAAAyPBA0B@0BPATB@A AtdBBB B\BHB!BBBBC7CpBB,QBC@ACB0BBAAP@0DBBCBBpB8BdBpBCA;CC@BBAAC9qBCBAAPBBB C|8BB BABC`B@BC ChBDBC`BACB,B8BB B BSHA,B$BPCBBB@:C@@@@BFC CICBB\B(B0B BB$CBBp)CCHBCB0BpBAdC6Cd,B"C?A B`B?dBB@@`A95C@CmCABA0B=ATA|B\4ZC[CBB CC@AfC' C?$BtBPAC`BA0AAC?VCB\BDBBXBB5C#CCB 3CGCCl B/CBBB8ACBtBlBB&@JCBPB2C @B!CpBBCBBCCC$BXXC0AB@@BD/AC)CBSBACjCpHpABCBAFCCHBW8B'C BBLBB`B CAd8BHlB8CB"8BHC.@BLBBBB@PABA.C CBP(BBBDBBpBNdDBC BPBPCIBIC4BH~C[CCBCCAB'ChBBYCApBB`A@0pAOCBAxeCACB@HC @BBpLBB4BCBCTB$B/CA>CC`B0pC`\5CB@BPBHBA BPApAA@BBBpBB(PA9CAAXBBBA<BC@lBBB B>@HC@ABBB?BBBCBBXB+CCBBC BTBB BTB@BBBBCaBAEC@@0 ABCA,BLBCBBC`B C0@AB,BB@B2C,AWC0>CBAAAATBBB`AB B)\BBP$CCj!&CRC0B @.C CAdP~CAPBlBAAHBBBBA|HBBBHB B$B[CB)CC CBPAhBdB@%@BAxB&CCXA(CC:C(B@PBB`B@BvCpA0DCA0B,BXB4@@@AtBPB@XBCBBBBBBHCB\0B@@|B PAB(B(AC@B?A] CCBABClB(CA$BBB0CCaCBdBBBpTCC\BpB0 C@,B8aC;CB\oBC0BH- BZCBCBwiCA`AAZCQC A0BPBTBB)C<AB`4BBAABXBBBCdBC;(BB#pzC@A@4BBC_ACB-CBA@Bl@"7CBA8`AB``LpA4BBlxBBC C?0AB0 C CC8B5VCB`AB C8BCPABUCBB0BAOCB BBBB,C%C]C@C@ BPAB@ ABBhAhB=CaCQC$B ,BB^CSCCBSC#CC@@hi@sC C2CxBC0BBBBpLHd*C%C'CABA.4BHCA0AA",DBBBABAB`AP0 AxB"CBtAABRC@B ABBB0HA B8B BApBT|8BBCB\;CLBDCBB 0ApLBB CABA@BBPB\BCpABfCCA1CCBPB(BBuCBzACBmCBBCECBBp@B Bh.CFC$M@@B`BADBTB4BA A B, PCBECtCCp`AATBiCC|B?CB0?AXB0BBBB0hBB<pACP4 dBT4C$B@CdB,CBB Ae/C`ATBBBB-CB@hBBBBBCA BBC;C0BA8BB 1CCBBC<2C0'CB`A@B BHBBBCC|B0BECBtBCPBAAdBBAC0A=!C@BB@,BCA@BHBB)CCB$C@@C`8\CVCAB4 C(B8BBBBBABBtCn 6,BC@A CC|BBWCBdBB(BBBB$BR CdB@oCABL(BAAAC)`BAB8BB\uAC4BACACB0B8BDCCCBCC ACBBIB XBCB-C \BAPBB(C>C`BBH$CBvCA@\pAB=CCAx)BB\qBl8BCBBA BBCdB@BCpBhB~|BBdBT\BBCBBBCCWCpBCCBB B0B`BB XCBCtBB$gSXBC,JCdB@5hBB0LB0BBBc CBBPHBB`BB8B\TB B CA(xkCBC2C$TCB.tBBAB(PBAloACiCABBXBBC%C(CTBBATBAB BfC$B-CBAz A 4ClB@AC AA'CCB D dB B0BvCB`BBBA@BA8CBbL*4"C BBBAANC`B`A`LBtB BBpB A#GC1CBBB0BBBB@BBTTA`L.PBAA(BBx *A6C0AgBB@B,?BtBpBBNCB |@tB@C B(CrCBALBC|@@@$BgCBJ8@CBA@BB(B?,BB,B|MBB,B BpAAB?B@AZ A:CBChBB BlVCBg\HCCBPA<PATRCYClBLB0 ABdDBCPAChBdB C40:B@BXBuCPBP;C>C.C@PABBBBBAA,CB&C[kCxBABBBLB|B \CCBC,BB8BXCA?`BB8@CBB!B@HB`BhB@B)CBBCB80AAPABBtB8BBBBtB`A8BBAA?BABPABBAC`ADBBBDBXB#CBAA ACB0A@BC!CACCBLA<BBB B@^C@dByCBBB8B:C@e?BBB]CB@BB BLCCBAB ,B\CLBBBABDBA,l@DBTBBB]AB@T AB.CC(A(BA AC`A AAABBCXAB|BdB ABl4BBABCPABAA\BC8B@@C.BC,BCZCB CB@lBBECB.ABBB(BBABC_B BB@HBBC6CBBCB@A ,BXBC0ABABBBB/CC,hdB CCKC@B\;CCBB3p$BBCBAHAvBHB hCBLBpB@@BBC@.BBAHBBTBHBC$,BBBCAH AABDB@ALBB@BB`B %B7CBe6 BB +C ApBTBB0A`AVBBABDB0uCAAZCBBDBB(BAXBBPB,BBdBAABECB pBB|BB A4lC"CB3CDB$VCxBBzC@ pp7CB1CA B/ AHBABCC2CBdBACBBBBCB28ACECPB ATBCABwCAABACB/C C@2C CA,BpBB[CB,BPBTB"BB ,B|BCBpBB~CB(r@tB4XCCB1CB9<dBCBABBBBBACCB(0BABCB*CBA(BC'C?;C[Ch AA<`BhBAABhBDB AxBA<BBABL<ABCAFBBBBBBA(B+4CC}CHBBBB@pBCC@B\CBA5 0BBBhPBBmCC?0BB$C@LBy`B@A0CC tBBB@@B@A/xBC BH>BBBBBBCBC!CBuCC`AwCBA|BApA;BB0BXB$B AClBC|B8*BAB,BBBAAX@@BlB Cb BTBB90BBBAAAB hB9C; BBCBh4BSCB =CBPPB%APBPCCBAChB@@A(C(Bd@@B5Bp|tB8BBB0%BHBBBCt(C BA@A< CBAB7CH0B`CB CB BCl0BtC3CB@AABC3CAC!CBB0B@ A ABX@PBBCCvCBdBBBC4BBhB`B"C4A`ABTOCB A@@@APBBjCB BHCBLBAC BkHTAB CpABA|AA+B@B)CBB@B'CPDBICB C$C=B@APBBB C@ALBRC#C`BLB BA0BBLBjCBpyXPBBCACBDBjLx@7CCmCCx CCBA X?PBCVC A0BpB7CBCBB9@ C`AlBzC0BHBhB CAhB CABBHCB@A`BB@BC@@@@$BA0B>lB !C,BB(BB(ApA@A A A ApMCLA@ABABHBAB pBBBBCB@dBBA4B@ABDBB@BBACC(B@lACCBBB(BB`ABBY,BB#COCB ABCC@wABCB CEHBABACB|B`xRC CC0ACB`B*CB>DBCBCC7CuBL BBBC@ECICAB`BB@ pBA@ CABl\ A@4(<BB CBpBCB CxB@tM@DCB C B CBBC`PACAA`BBBBCB@\C5CBtZB+CCBBB|BbCCp??D4C AlB|BABhtB0A@BAB @BLB(tBAABCC5BBT@B?ABB$BBB$BB4BB\BBA\BC ABBCA8pBeCCAxLBAB@7*CB@ABBB Cx@A|BBpBhBBTBB(LL4BBCA|PAC hCCHC<BrCBAA;CB BC xpBBBAh4BAAxB`BAXlBAABADBPHBABBBB<BnABDCAA C3CtC AXCC*CBW)CAB0CdBA@xBCP8BAPA \@@@|BBCB+B0pAXBBBBBdBABBACBBLABBB?BCBBLB{BBB4'!CB@A`CBA,BB,B(B@tAA vBJCC@BB0A4B BBx,B>CBAATB8BBCLXBBB`AHA0ALBCClB C>CB0@BPABA $BBB+`0ABBCBBAAA`BB,AACiCB5BBBA XBBAAXB BHcCPC@A ^CB0BCTBCPBTBB ABCBB8BBBC"C0ACxB@D?|BABAA`@@`ABB BB@IhB0CA BBBBBBPTB CBdBdPApB?C$B'X|B@@.B\B4B-C`ACC1CAC`BB(BAPBBA,BADBCC"CpAtmC`AA`BTB |BtBC&CBpAT\BBB! C!CdBBB@CB@/=A7CKCC R0BWCBBBBDBTl CBBB@@CC3CdB8$pBB7TBGCAB LBBBCAAhBBC0, C CPBBB#BB 4 CdB "0ABB!C+DBTBBPACCBMP,BBB<B@0B BCA,B@JC BBBA&BqCBBl BAB A($B ABAAC`H@WCBBATBBBB,Bl`CBB0ABCBA@BB_C A,AC C AAnC\BBCBABA B\$|BBdC|[B0BpAHB AB0l(LCA$/BB4BB+C@B PBBp'BB2DEBABBPABp&BBChBBB VABPB@BCCJC B0AHB(BBlB2AhBPCEBLBBBBB C-CA\B?A5CBP|IC C  BlCBA5XX BBtBBBCCBDCTBpAttB Am,BC8C>C@@`T p@BA AB1ClBB:C)C3BBByC,BB[CB C-@CUCABC&C BBBPBB@@BXB@`B:HBBBBq$CBB ClB@BBCHBA2C@ApBCPA@ABBC$B4BB@ChBpATAABA\BJCB?|BB<BTPAlB@@ C(BBB,lC_C5 BB@BB`ABBBBP BAC(ChB BxB`lBBBPBB<HA4CB0A%BAB1xPA1CBFCB!BAABB}CCBAI\xBxCBhBdBBBA2B-CBBdB@@tBCd@BPA[C|BDAA0A,BBBCP\BX,BB)CCBBDAhCH$CAA< B0xBBtBhB`A<CBBD@@B\A4t$BAHLBABPBBC0ABBSCB@BB@@AAkCTCBBRCAB B@`AB@BBB@8B0A@A BdCC@@lFSClBADCBX@8B"CAAL`BCCBTB,eCz@ABB0BuC0 BAxBlBPABC8B@ BNC`A@B6,,BCAdA@@L$.C$BB|BldB BC PBLBABBAB@@|BBB07,B B`ACBBXBBBC@,8BB/?CpBCHBHB@<BBB(RBqC*CpBB2 B`A$C`B`?C#CjC`CABBB,BABA{C@x,BC@AB| BCCBBC@%BAB0BTB BB,BCB*C B@@pB<|,BPCBB?CB0AA\tBBRhBBA(AB0A$4xBBBBB`F|BB@dB@%COCM:0A@BBC8BB/|BCB(CBBBC0BGhCBB $C BlCBACPBBBBBC@ CCA4<T8BBAHCB BB@@HCA(B41CA@wCBAxB BA@BBTBBCdB@ChP@BBdBC BBCCB)ALB@A`AABPABBBtBBR$C\ Bp@|BCB000BA4BtBBBdBA`BBBBB #CAB8C|XhBdBCpA<A`ABBA0`BCB[C BH"C7CBBpBBBBCCGCB7CBCBBCJCBBA#Cl@BXBBBBCxBpACBCBBBBCnC`AL8CBBB?BBB A8CABA?B` BBBQCAAB>,B C?CCBpBCCZCXABB@ACA@@@BCCABlBBzTAC#CBCHBAxB<CCXBB+CBLA@CB0AB!C,C B@BBBC A&C $,BAB@PA BAB@ABBACBlPA`ACLCC,$A[CAHBAC C<PC0B0B@BBA0B DBCBABBBB6C0AXBA CBB CBBB@%CBVCNCC\PAB CTBBA BCCBAAlBABTPAB,BATB|BMCtBB\BBCBHBB\BHBBBClTB]A$CHCCd*CB"CADBDBAB(BC0|h`DB7 B@C@-JCBbwDC CAB BBHB@XBHBppA@BB\BC*+CCCJCBqBCjC6 A?CCBBAAhBALBBNaCCBB\ `P\BCB>C B0"C,3VtB\BdB, CHAC C. @AB BBETB$BBCh<@TBABZ0@B`BCtBBx B CBB8B<ABBp0BAABAA`ATDBBtQC 0BB1C C:C80 AC8`B3PAHBCCBBBBA@BCBBCBBBBB^CxBAAB CBC>C AACB1CBdB@C,@AABtBB3T:CxBB|hB?CBA0BfB3C3C`@BI`@BBB BAAShBC0AAPCABBH@@LA,BmC+CTBh`CDBBSCp(B CBBABLA0BBBBB BCh\B`BBBBBC, C%C|BlB`BBC<BB@B,<@@HC0A@AA$B[CB\BBBCBpBB(B8B@B\CBCCC!CBBB:CBB_CCdBBAC"CyC1CCC$BABBB[CBB]CB\CBABBCCBBBCB@B@pBPCCCLBBBCSC/CA:C(BB C\BhBLBB[CBHB\BB,CBBpBCBCB6CBABBAC4CB1CIC CBCCBxBBBB[CABhBBBBB@BB?@0BCBC@BBAuCBB|)CCBAaCB CBpBPB0CCB BCC C0AB@CB*CDB C@ CBkCCCBC,BbC1CxBB@ B BICCBC |CVCBPW1CCCMC0C`BHCBB CjCACBABXB48CSC,0CCCBBCCTBfC0BUC'CBBBPCFCB`BBCB A4BABChB@BQC@@ByC C6CACxCBC8BB`AC|BCCBB}CB BBhtCC`B"C CCJCBBAB B%CHBBBBRCB?BWCBBCCC3C\BCB/CChCBBM jCCLCBAC_CTCBBPBCp ABB\BBBBBQCCCA5CCTCVCA:B$CCB8BBCBC@@DBBCABC0CABB CdCBBBICCBCSCB[CBBB$C-C8BZC0BBBCdBCmC-C(CCC)CXCCdB"C=CFC)CCACiCTBBwCxCC3CBABCQC_CC#C@@CBCBCBB4BTBBCfCB8BBCCCC1CBCgC CAB BBC6CCBLBTClCCbCBCCB;CBFCpBCC~CB!CAcC,CCCCBC>C-CCABCCC1CBBBCCCBB,CAC,C4CACCCBBDC@JCBtC{C_CBCCBTCBB CyCCKC0CCCCCcCBB*CCCC A CCZC C3CCSCHCJCCCCCXCQCBB$CCCCCCFCC=CFCCCCCBBBCOCCjCC"CjC:C.CCCCBC:CCCCBCBCCCCdCCeCUCLBCCCCOCBAC4C(C$CtCCCBC]CC\B{CYCC0CBHCCBCCvCBRCBBOCCMCzCCCCAC~CC+CYCLCCvCsCwCCCtCC=C CCCCBB\B(C CNCCACBCB BBABBlBICBBB\Bx4C@@2CBBBPB dBCLC>CBABBBtC?C:CPB&:@BBCCBBB *pA@BBAB84BPA,pB0A8BBlBA BAxB AABBBBCBCPBABBC\CB1CFCB?%ABClB!CABxBBB CA@(BCCB BiA>CB4]@BB<BB0B0AhCBAA @B@@BC8BA@CB$CB^7CCFBBl CxBACBC@B@4TBABB|BBHBBBBBABCBLBOC2CBBAALBBBCC8CC`CC$CCBBCCC CZC CB BBCBAICCBBABCC C.CC9C4CCHBMCCB*CBBB@dBmCtC8CKCXBBCBPCBB C@,CABC4ChCCCBpC CCBBC`CCyChBPCCB>CT C2ClBjC*CCBvCCCTBCC7C%CCCPC|BwC?CrCCLBBBCCeCsCBBB3CHCB9CClBB C6CCCB$CBlBtBCC(C CHCBC\BBHCKCBC0C BBMCMC%CC%CPAB|BBC CtCCCC~C:CCCCC{CCC#CCCJCCCCCCBMCCCBB@0>CB CTB@B$Bt@|B@BBBBBJ( CB4BB@BBABCB@P`BPA2CB CCBBB>C C xBtCB$BXBBCBMCCB0B/CtBClBMCHBBLBB`BCA@BBxCBXCBpBB3mC\aCxClC A@dBC(lB@CB4BtBB0A BB6CCBABBABCxBBCCCCCC)CC.C$CtCvCvCC CFCC-CeCCCVCCBCC1CLCCCC^CB BCuCCuCCC*CCbCjCCtCCCCyCBpCEC_CCCCIC?ClBwCCCC CXCC CBECCCCCCUCWC4BCCKCCCNCBkCCCGCYCC;C CCCB/CBBSCA|BB+CtBLCB9C>CBBBICB@BTBBhCCC,xBBA CB(CC CBBAB\CnCB B^CBCBBxB,AB@PB\B5CCBB CBBAABQC>CBABBCCqC@CCC|9CCCB CcC'C3CBBBBLC4B?FCCABCCBC)CBC[CCCC9C-CJCBCyChBAjC:CC&C(hCCC@BqC;CCBUCCC=CABCBBhCCYCBCBhBCpCBB4BBC)CB%CCC BDCB1CcCd`C+CBCB"CA%CBBCBUC#CdBB.CVCpCB2CYCAl}CCBPCCWCCC4CCBB,BCB2Cp%0BC`ABpAICCAA PdBYCGCBC?@PBBB @TB,@B@pBTB8B9C&CpB8l@UC@CBpA1^CBBB@@#CC@@C `@CBBp4B-CCCC@pDB4CTCB@AP9CBBWC&CHBC/CC ?BBBACCBA0AICFCCBPA2CBABtBlB,BABA|0ACBBC A@CBCABKCCB`ABBBB)CBCACCBTBBABB BB@A3CBBB8B@FC?C\BC|C BBBCDCC(BABB8B@CXCAxBC|`BBBBC4BhBhCDCT$B7CBC0CCB=C@CPBIBBAAPA$ACAPBCAABBHBBBCA BABBdB6@ABA`BrC$CB$`ACBB/C,BDBB$BCX)C%CC4BB(BiC,B0BCCuCBB_CCBKCBqCBCC@BC`AlBChBpB|CB4CmC8BBCCBBBPA@COC4CBvCBhB00BC ACWCBABABBpAABCCUCECBA CC+C$BB CB C"CCCB"C)C@AALBABA$COCBBxB: BB/CCC(BhABCBuCBB$C0C@ CB8CBC4BBpB BCCC@CBICKCtADCBCAp`BYCCBBB CBHBBAAC#CAgCBCYCA ,B,BB CMC@BHCCxCkCBBAB4CBACBDBBBBBhBLCCCBlCyCVCB@A CCiC+C0CBACBPCdBB{CiCpB@ACBECChCC?@BCBC CBIC"CBfCCWCBBCCCBBCBBWCRCBdB CNCBCrC4BC@hBUC3C%CBPCBWC@BCC-C`BGCJC]CCBBVCMCB.CdBBHBOCB1C2CCBLCCCBxB7CCXCCC4BBCCCCA`KCmCCC,CDCBBCB|B%CCB$BgC3ClCWC@CYCB/CCoCGC;CnC*C`B'CBCTCqCCBBC]CCBCCCCnCBsCCCCCTCCpCCBCaC CpACCCC+CCCDCCC!CPCCGCClCCB\BCCbCPBFCC4BClB@BDC%CBBtCBACC0B%C,BBAPB-C5ClBdBA B)C@B%CB9oC`BB0A,B0B<BYCBBBCdCB2CBB2C@RCAhBxBBCC9C5CBBA4CB`AC`ABB"CB C=CC'CCCC%CDCCmCyCCC@BCQCaCC C`BC CWCCC:CCCC^CCCBCCCC-CBkCCCBCCDCCCxC BZCCCC C{CBCCC\C?C$CC/CC\C|C8CCCC~CCxCCeCCCC\BIC\BpBBA@ %CB BBBBC?@AA(BCHBBBtBbCB5CBhBTB8CB*CBh`BPB;CCB=CACC A:ClA< CB;CBxCC BCAAt4BCABCBWC@ABCpA$B!C3CCCsCCtBCACP@@@@ABCBBCBAAB8C]C,B@ACC:CQC%CCCWCICBC{CCC+CCCYCKCBCBBBPBHCCCB8CACBC`BCPjC.CCBCB\BBdCBBCCC8CXCCC6CuCeCXB\BHBwCCCCBA%C(CCCPABB)CC-C@B2CC&CBC+CC\BBCCCCbC9CCBCCC@:CCCCPC`BBAZCBCbCCYCBCCpCCBC"CCLBCB)CKC@VCCiCBCBCCWCCBCVCB@.AClCCPBA0BHCCBCAhAPAB)CBBVClBCBBXBBCsCbCBBB!CBdBHBCPACBBFC{C(BBC(CBBBTCCBA$C6CCXB0@AApBCC(B"CBB CABBCBB|BB AAB CBPB0x'CCBABCBCBNCBBCCB.CqC!CCBC$C C*ACNClBBZCCCBBpBBAB.C|BB4CICBB1CB3CCB+CB`ABCCB*CBTBBCBClCBBBCB"CCCACC%CXBXBPCCB@BC-CPB`C~CBBClCnCCBBBxCC?BBBuC C0B=CPxgC$CBBC9CBQCC C C;CC?!CCB(C BBtBAtBCCPCC~CmCCGCBB AlCCCBC(BxCCC#CB$CC:CC$C0BDBCCjC CB7CBCBhB CCBTB'CCCCKC?CjCLBC@AICCCmCCaC_CB,CC"CfCRCBABCiC!CBZCTCrC CCCCLCCBBCC?CQCBBCC2C(BCCnC;CKCBlOCCCCOC7CA BuCC CDSCACCCLB C|B9CCsCB0AeCBECBBBBBA A-CB_CB@A BpABBBBBA`ApCBA(C8B"C\(B4CTBCBB(XBBxB|CCB|BBBACCbCABPB ABC?C@@*CBBCCBAAtCCRC3CBBB0ABBABB\B\CBCBABC\CBA!CBLBB| C||BCCB`BB1CABB.CB(BlB@CCBABCCB@AhBCBB.CCBBHBC`ABBB (B$CCBC@BAB[C@, B\BpCCMCC@BA|BB}CBBCBBB@B@tpCVCA!CpA ATBBBCACBBlB|B8A CCB@X,B BBxBpA@@{C@@ABBDB&C B B|BBC`BhCBMCB4CBB@8BuC4B1C0(lCCCABCBBBlB8BBBBB C9CCOCBDCFC0 BBA,BBBB*CBhCBpB+C1CBHBBA0B`BBC0BBAC?BSCA CB%C$\]CC[CB`hBBCBBBC@.ABCOC4C CpDBABCCB0BBCBBLBBLCBh-CBBBC0BA~C BC/CPLBNCJCBBABp+C@BC@?$BBB0AACCCCB'hB? C!CC\BAGCDBBDBNCBCHBDCBBBBC8 CLCBCBGCC6ChBBB BBBBCB*CA0 BBBB0CBB?pAFCBABAC?C,BBC]@AlCBC A-CBCGCCLB*CBGCBAjCtBCB@`B^C,CBp<BBCCBABBBLB$C[CCBC`ADCBBACBLBBC0CCC@BBCCB<B0BCB,ClBBBBBC|CTB?BBCB BACBB&C0xCCBCCB$jCCC&CBTBCCaCABCCBBA@AzC7CB C BlBBuC B/CPAB BC$CXBCCCYCCAtB(BCCCBCC@B|BECtBB7CBCAC*C{CC,CA`ACDzCC4BACCBVCBBC\B,CB#CC C,BCACCBBL CCCCCBpABC@BBBNB2CB`ABB A8B\B@@BBBBC,BTBhCCXBBCABC?C.CCCCBC$BB@CBACvCCX(BBtB8B1CECtCsC> vC(B$BpA,BC0ABCBXBAOCCCBlCCCB&ABCh0BBLCBBBA\BBTBBBB\BB?A8BlB^CB0BB80B@CACBGC(B CBBC(B!C8BCB7B`BC CCBlBKBCKC@BBC7CBB0BXBdBC*CXC|BACBC,CB_CBCB 45CBBBB?BBDC[CCCCBBB1C(CfCFCCC B$pA4CCBC"CC@ABkCxBBB5C+C^C0BBB-CB8CCCHBBJCPB5CCCHB@B CAeCCMCB CCBBBB@C)CBC/C+CBBB CQCHBBC C0BLCCA9CCB;CDBCBC1CWCBCDB BCBB;CbCCcCBBBBBECBA=CBpB(CQC3CBB@PBRC(BBBACQCpBlBB@BCWCUCBCBB`B(CCA!C;CB CLCBCB3C C+CCCC)CC,CB \CBBBBBGCCCFCBdBBAAnCBCBAHBB-C3CABFCXBAOC-CBCCCApICBBB4bCCCB`CBBMC0xBBV B@@8CLB,BB,B8'C@@BBPBBHBPACBCC*CCxBB>C@4?@BAB*C'ChBACB BpA\BBC<pBCBpBCB`BlB0AP0BAATCC(0BCBBCB9C>CC+CA,BBCBpABCBBBpB BACB@@BBBgC@gCCB&C@0CAB CAAPB 4BB6CCXBAABBB|BBBABABC0(PBC9CC6BBB"CBA<AC BB$BBBd CQCBBB` B`A C\B0BBBQBB?BhC^CAB0@BxB;CB8@@ C`AHC C%CDB@DCKCdBA@B@BB C@AC&C4BxTCBYCLCBBA8CCBPB`BBAA|BABCB#C@lBArC1CA(BB\CC APBC8B@ACA@ABdBTB!C@CPB+CAlBmCBBABAB4ABCBBBlB0CCZC`AABBTAGHCACB? BPPA`B(BCBBB@8tBBAx|BCDCB0 CCdBLClCBBA&CpA$B%CQCC9CBAB:CCBPB0BCCBCAzCBCCC A CB3CBBCpBB@BhBBBUCBBBTCLBBBB BPCB1C\CCCpBxCBlC0B(BBCGCBBBBCCBBtBACC`BABCdB1CCBCuC,B@BmCBCCCP BCBhB<uCA@CCDCAC$CXBxBBhBtC_C@@$ByCB(XD&CCBC)CpSC 8BCB\BBCBBLBeCA@BBLAUCCBDCCBCC`CB8ChBBBCgCABBBxCBXB Ax CBOCMC(*ACCCBBBKCBB|hBCC8BABA$B B1CBdPAC BBCCACCtB@BJCB AqC.CBB+CB B%CCPC,BB@BBB)CBAB Bd(B@hCBA$lB?CdBCAtAB?A?C5CC7CClPACoCBBAA@BABHBtBBB CB}C0X BBBt(hB@BB;CAC$B,A-CCBBK(BB@C`BBACCBBBBB@AAxB@C@AdB$x#BvCMCxBBL@BRCBd($BC!7dBBBkC@@B@ALB@pABB_BACLB0AAB[C=C/C@B?BB;TxBB\BLC`AlBy@BAB@BCpB@@ BBBBBBC(CxB0AAHB&CP@BA1CiCWBBB(CBCBttBB ATB"BBBBBBCB0AXBBhBBNC"C0CAB*CPB,B@#>CCt*,CBpXBBBC CBBxBpBCHB BAlA C0BB;CNC A@pACAB CBTBB$B\0CPCBC0(BBCAB@@1CBPl-C0C`ABAABBB,B0CBBBLB%CCC<(BCB@,2CBBCCAAACB8BxdC(CCPB|BBA BBBA,CBCB5CB`BBBApABBCbCC!CA:CAB8B!CBACABBBL`BB CCB}CCB0A8B8 C-CAT@$BiCBx4`Ad"A8B|LBB'CCB8C/CDBBABlCtBhCBA3CDbCCBBBBCCLBB@@;CCACBAAhBCPATBB@ B$BABACB BBpC$BtBdB0ATBLCCBDBtBBBAACx@BBsCBBLlCBxB@BCCXBAABB4BB8 A,CB*CTB=CJCd,dCBA4CC4B@B0AABtB:CACC?CBCBABlA>CGC  C@p.BACB0HTAppAXB1xCdB9CPB8xBBAdBBXPAB`6CBB@BlC\B( CB0BPA+?CBBBCA(C\B`BBB@@ACCBBBCB0B,B`B0BHBpCCB`CAB*CBBBBBBpABABCC|BB@84B@@DCCBdB^CAB4BA$BTA#CCBBp0B0ABB,P@@AB A B<`AhUCC0BC-CBB+CCDB'C3CTBB!C]CBACBBB4#CAB`B|BAAASC CD1C@A"CCC0@OC7CBhBFC`BCCABBiC+CBAXt }CCtBABCBD@ CBhBA@C{CC/'BdBCCRC XBBCBG/^CSC:C(C4CBVAB<TBABC0B@8BABCBAB~@CB4B BBB0A AOC^CAxBCWCRCBCB8B1CPAApB|B `BBBBBABdPBLABCBA0ICVCCA$BCA8C CGCxBB0 @ AA(BBBCdB4BB,BxB&C4BBlB0ABYCA CPB4bCBH|BBBBBBdBCCB#T B CBBB`BB?B@@CB\@CC-CA4C|BhB CB%CBB0AhBB%CC @@B@BB C@CM|BA@AB CBB`CCpA\ @'CB@H%CBCBBB0tB(CB CB@dBAm,BBBBC0CBCA8BBCBBPBhB?CABBLACZCPBBBBCBH\BBCCBC$BBlC$BBBICBBCB@@4C&CCdBP@kCA>BBCBL!BBBCXCCRlBNCHBBCHB`BBBPABAC CHAXBC\A=C?B*C,B`BiCAtBCHCB`BACC@B CABB@@ABCB BpAA@BBICBCAAZCP|BD`B_CXBAXB @ ALBh|BCBB h8`JCtB@B\AB@XBBB\BC@@DBB AhBC,C BOCAhBA0B`BhBABBBLBHBp1C BA(S`BBBAB*HCCBx@@CAAH\B0BBBAAQB`,J<9CCBpBD$B` ABC.C8BTBBCA09CB8BBAAABB @LPB CB`$ChBC\BBA@`LB@6H%CTBAHB BABlX@0ABBCATCBB t !CBACx $CAA8BB6CBdM`BBBAA CA B$CjCBAB`AD BBBH$ApAVCBBBAB?BPBB6BB@A8DC8B BBBDBPAAB BBBA<ABBYlBCP'CcBA+C(BOAB0B(*pBBB0AA=hC_C@ AABh@8CCBACZC(CBA&A&C'8BBCB C0AB BdBCAB?CBB@ BB@B4,$B-CB:CACBAxBC|B<.C4B?C5CB@ABPxCDBB4C CCjC@@@BBeCBB`CBBABBsCB:CBPBBC0BB0AB&CCBBtBB@@pBB4ABdBOCCXAABBpCB@A?B4CB C$ABBA" AB_C@B@B0BB@ 0B(C0ChBp,CB@B*C,C0B\B2BCBhCCB8BdBBlB`AA.C@APB7CHBCBCHC@A@BpA>AB ATBBBC Cq?CCBB`ACpBBBB &$AFCBA#AlBBCB`8BCBHBCdCC@BCtBCB`BBTBAABB1C\CtBDBABBBpCBL0VPC@B@A@A*CCBPC@EC)C0AB tBX!CB BXBGCC(C@ABjC\#BB 0PB!C(CBB1CCBAACCB B.B@@A%C]CBATBABB0A$BB@LBAxB(CBB8BPABBA B&CCB A7AB8BB C0AGCtB@B.CD BB CA2@@MCPB@` AABB@BCA@XBBB@LBABB`CA$BBBpAhB`BA|BABB0BB,4CBBACBCBBBBC(BphBB`CB\B8BBsCBCACACAhA4BPAlBBABBB B0BH^LB0AB4B[CLCBB,B`CLBCA4C8B?C,B0BBBABBCdBB'CPBPB6CBB(BFCBBBA$BGCA4BCB BBB AAB@ABB@xBdCQCC?lj GCCBA(.,ABfCB@A 0ACpBB^QA.C$BB@$ CBAC AAPA( t<BAtBBBB B@AB$xCBPB|$CAB A BB0BBABB@BBB@BB BC@C4BtBBA? ,@A)ABBhCBHpAlABBC CBB0A|BBB CA BBB@@BBAHhB8CTB@BCBdBqCB?CB?BAAXBgCC`BA.C?$dB,DB`B(BBBBBd0A ABBDBhBB\C / B@BAPBYCCx&AC]CBA@BX$C`AB4B`ABA%C3CAdB0AB$tACCCCCBgBBWCBa]C@A@ACAp"B CBBBA@PAtB4tP' BB2< tCB`B|BC]CABKABB|BB`ABBAC/CBDBw XBtB#C0ABCA|<d$CBDB\$xB,BB.C CABBB(B:2B@BBdBdBBAPBC?C`BBAA CBBAdC `BAABBtB|BApBPAARCB@B`BA`At`A?CAB@?BA`(APCBC.CB`BpBA(BBPB<B|<BBPBTxBPBdABB@%C_CPB BhB,XBBBAB(B,C\CAvCB@B$x:CBBA!@B8 BCKCB(BBlBB/,BB4CYCC+CLBABtBBp]C/C0CC$BdBCwBC$BAXB|B4BB%NCCB@B,BB0PBB/BBA!BB`0BB8B0CvCXPB@PC B4B8BA=B@APBCBBHCAA|BpBPBC8B A?B<ABPBABABx@V?CBhB$BQtpABHB @CACB-B@A BB B'CA"PAE/CBX@,B0CTBCHBABAxA@@XBA AADCBrCxBBp0APACABA\B& LBBFC@BpB0BW,CB@BBhBPBCC0@@ `A1C.CQCBlB(B$DtB$BB AB CDdBBTB$BB(BB8BBCCTXBBBBOCBX(BBECAB@AB ,B@A|B"CCCCBBB$BAVCCB\`A5CCHB8BA\BBp,4B%CCB`CC4AHB,BC BB\BiC0LBAAABC0A$,@0ABB|BB0B,XCBB@8A@ACFCA8SCCBBc4B3CB$ABATBCCBBAh<PBtBKCB^CB(B BkCCpAB@B0BJ?C-CMCBBuCB2CBpBXBBPBBBAB Cp A-CCCBABpPCABBOC`BHB:BWC`B0A ?(BBB}CBCB(C#@HBtBhCB$B9CCAhB@0B,.BCLBXB@pB)BABC@@B B4{CC$ClCB-C(H%CxpBlDB DBJC0A@B`BB$0A8BA,B\BB2CBP ADB\@AxCB| CBCl0@CY|B@BA@D`AxA BECpBBCB CAB/C|CBBlCCBh#CC BB(CCBBaC(CsC#CU80CBB(CB8B C\BBCAA@B0BBBA!CBBAPApBBB;C@4CC( ;$CBBxB(BABtBBBABAB,B+ A (B@C-CLB CxCPBB`B `0J0BAB BTB CBXB A!CBq CmCPAeAA B@HAABHB BNCdB@`AxtB(BBLBB,BA$@ABB:(BCBBABB\B$BHBBCCAB CAB@ ABBACBBLxBpBpA%CCBpAPpABJC8`BB+CBAA CTCBBpBxBxCBBBBC CDCFCCBxM|CCB6CCSCBB7ACdBDCB@e?<\BP,08B A`CBBdCCCdCCAC@HBcCBZ%BPC@CBBB*C?CBBLB C%CBB 'CPA1CCB@TB@C;CBPB9CAB(B{C C`BAHB`BB98<B@C@AA7CjCB@AB APA CPA5CABB(pC8(pBBPtBBB4 B F@ CBBB@ClBACCB@B\BBHACBCA08B6CCB(xBCBA@A@HBtBAB<pBB1CB0PlBCB`AL)B@APA8P)CBEAA?@BBA0BSCA@CAA.h@@B)CB@BB@BBBB8C BBBAABB|EC`B8B,B@B+C!CB >B@@DDA'C 0B(BA(B?\PdlBA@B@BCBgX3CB(CB9@AADdCB5pC0a@8C A8B6C%CB CB.`B`BB0BlBB@80BAC BB\BCCBB CA0AB@ABLBABC8CB 0BABtBBV=C@0BB BBpBB,AXBCBBTCBA7TDBAC@CC`AhBCB\BD@ABADBABAA4C(4<B@AA@1CxBCCCp4BBBBtB4@AB,BXBTBHBpBBBBBBC*CBBB0BC8TPACCCBBCABlCC+C BCBLBBC8BApABDB@PBBB0C#A0B.CBApB@A~NC(C`BtBBABCB C@HBBAC8CXXB7PBCDOBA<CA VB CBBBBZHBABLB -CBlA@CCmC/CHC?CCB0pABCBB(C,8HBxCC'C<tBB0AB3C`BB0BpA|lBeCB CJ@0ABBC@ABBBBB`ACTHB;CB4B i B0pBHBBC0BA ABBBB@AdBBABBA TBAB@TBPBB C,ACCB|B'BB?`BC .CBBdBC@LC1CBB`@C@BBBHBtCA0BK$BBB,BBlABC[CB6BBC7CAB BAlBQCIBPC C1 A4BBZCABLB@@p@AeHBpBBBXB|BCCPA@B(BBdCB6h9CBBPwCB@XBHTB0A;CNC+CHBC@BLpA4BCC]CB0BxBt<CoC"C@I BB?CCAT8BBPCChB\BB8|BC(`B CBCCC@QBBBdBeC%C`BBBB\B?pBB CBBBB SA,BB?8B`(BBBpBBB`<pWB$B@bB`A5A,`A@BA!TBA5C4`4BBB`ABBxByC2CXB8BX`A`BB%C[ B C@WCB|BB0lBC#ABB`ABACBBB\/CTBBPTBBBB<@A BBPAB$BBBBB0 B$CBB$C0BA,Bl@XBtBCpBBtBC&C@B!C@B IxCBF! )CBrC@BBCABA BAABTC`BCPAAB@BBCB(BdB4B\B4B@X@BdB0ABD1BBBB8BACAACpAB@@2C AABApCC&CBB:CdB@AC%C@BApAB4C0BsCpB`A^CpA8HB@0BPBABABA*C0A^CBB$7CLB@ABB?89`B NB#C,BBC<B@@HBAB4BDhBCBdB5BB% LBCC@BA`:CjCp= BdC CB"C A$A@C C`BABBBBBAfCPAVCClB,hB|BBC-CtKC`AA(B0A(BB=CtBC@B0P`$dBC-CICBBCCA@BBCBPBBBpABTB(BB|C|9@@CCTB\B LNBBBAABBlB BPpB0BBB,C8BBY$^CjC A>CdBAB0ACBXBtBA@lCBA(BACABB@BAAtBAB ABBAPBB0lBBBB`A9BBC@#C BBqCABDPjCBBBiCCApALCPBlB@ABClBPB[CC >CB,!] CJ PpAABB|B0BTB4BxAW@BdB B C@AD@UCFCTBCBLBxB@APBB0ATBXB(CBAA0A B%CPBBA4CpABTB3CC B6BBBB BBBCtB|/0(LBCLPCtACTBB.$BB\BC CBB$BALRC"CCAYCBOPCBBBCSLBBDCB CBBCpAp@8A8B@@4BhBDXBAhCxB@@B0BPCBB<BAdD@DpBC0ABBKCBCB H!BAA`4B CCA@0CADBNBBdB|L0BBCdBAtBBBBhBBLB CBBB CdC B5CC BKl@@JCCB?B CB)C@@!CB@BBAdBAPB7CBxBC`AdE`ACBBBApBPABdADC@BTCDB|BP9AxBBBCA@RCABCBBBC/BCAApPDABHBABTB`A(B@=_CpAC?BBBA`P4BAAA{CBBBClBAPA4B@wB(B7C$C B$CKCBB BB&B CBB BB@BCB |BCC`B?AA@4BC!CA,BBCHBBhB &:$BBBlB@(B4CxA2C5xbA CB(CB< CP@BB\ BP B@ECBV0ApBBB,CCCDBTB @}CA`CdBCCpA$Bd`A$BBAPBBP,%ABAp`AA?)CHXB4BBABCBBX@A#4<BPBCC BABB CC8`A8BlCXBhB)AP`AB&CB@C(BBeA(BAB8B v(BBpBBTB<BBBtBxtBC%CBB(BF$HAAACp$BCB@BCB@4BATdBCBABB?<P\dB'C3C<+CBB? PhC BB@C`@AApBBkCPACB=BC|BAsCBBPABBBB(|BDBP|BCBA@@XBBPBpB BpASCBB@dP@ClC8B@BCA%BC`,B CxB@ MCB4ATBB<`0AdB CC,AAC( CpA H AAAx@hBCB4C C3CC?HB@B<@B BCBCBA0BBC@BhBA ACp@BBAA@ ABBABPBCBPBCAABBPApAPB84B|`BBD)BAB8B4@A HB^CB |BBBAABB0B \,BBBBAABB@pBCEC4BBAC:CB4BALBtBB@$B0A4BBCtA#ACB2,CBhLBBA@BBBBB@ADCC"\4C7CpAPACB9CpE qCB@C`BB>CBCT B5C@C@AB0BB.CA|BA@B+@AB(ChCdT`A<B@AB CB C&Cd C\B,BCB=C@@CB0CB:CC5C RCCDBA,C4CD(@B-C0BB8B\BA:BCC!CBB B\B4CAA@@TlpCB A'xB\BP"PB BA B@AB BBBtB`0BC@A@B LCC@<,,B@BBBB`ABCAABC B B*CA BB@@@C@x"XBBP# B@Xh)C@BdBFC`BpACC)CAA\BBCCBtB6ABCB C@PtBA,B2CdBA*CBBCBB CAAs BAPADCBB%CTB@BP ABAiCBC`A[CC7C 2 0B@`B B\4BARC @ A>CA@@T4B5C CBA<BTCaCB|BB CBPBC%CA8BAB @pBABgqTX,BB0ACCBlBBPB-C4B@C@ACBBLB? Tp`BCdBACLBDB@4B<LB6CA^C@IBCTlBB1CBBBB4BC|BAB\CBB BBBB3C?tBAABlB"CD`BBYCA CB BBC $BAPACTCgCgC|B BCCA`BxBBAYC1CXCABBB CdB0BCPABCpCdBABBLB!C8BJC ABGCBBBAABABABXBB@tBAC BBBpABB-C@,A,BDBB8BBBAdr`:CLBtBA@B4Bx(B@`ABB0ABAhBB0B\B8B C%CBB@ABB}CCVC0Bt`BTC?C)DC <tBFxPAB@=CBC{ CCC@AXRBB`BCCB BBB\ADB ABBDBAxBBBB!CCAzCBpd0BBC2BC C8|B3ABBXPBABXCX4CBBABaBBBxCA B BBBB|C$CBCAB EpHBBACB\!LC>CB$BxBAB&BA BBA:CUCA!CBC0CDBBDBC0,AB DBgC C\C(B@`B0C BT@C`B8B&A ChB@BB'CAfCAL C` 0B,B@A2BLB|B@BXBsCApAWC<BpB 1CCxB C/CCBB` |BCPpAB@@l CtAB qBBB6,BA C!CT@pBCB@@@CAC4B8BPABA8LdBB8BBB$C CPC*BABTAxdBpBBBA@dBPA CA`BB@1CB@AXBBl<B$BCA)*`BCApAA{CB@`CB%C0AB@C@0BBC@A0ABAT@C(4PBACUCBBhClBC?nB4CCC`B CBABAB,BDCC@#XBClB@AB@?@C BB1C@BBEpdBtBBBB:CBBTBBCBDB@,C/C@B(CB@ APA,BB4C CL@5CBpB7C,AHBBPBBAPC1C@ApCCZC@@ABAt|BXCB B`LtBy(BBB0AAC8B$@h5C@+CBL3C"CCpA@pBB@(B_CACB8BkCB ABPBPAmC]C@BsC)C@bCB\BABDP$BBACuC(BpACXBPXCB(!XB+?B$CBB\"C,ACMCABuCB 0BBB)CA4BBBpC`Aa,&CDC A(BCB#C\B+ pABC@B@B|C$CAphBHCBBHCBA+1CBAABXB`BtBCB0B#@BBBB*@B7.7B4BBB BBB ABpB@yCXCCA?B&CHBX$pBB AtBhB A*lCCB@LRpBCCpC0tBBLBB\:&2CBdBpBPBLB?AECBBHBALBFCBBDCB+ XBBdCHB@TBB`B@<xL@CCcCB&xB?,CxBHCPBBi0AA B@BB 4Ap`@\B@0BB3CB8BCBS 8BC CbBCB, BC|B<BCDBAhBB`@B C@B$B0AxpA@lpC`BA BB@,BB0B0AxF@BBjCVCBMB8$B@@CCAL`BBBpA'BMC4BB CLB0ABC$`B0ABB:<!CuCC ABA@BlBBTdBTBTBIC(BXBBqCDC&CB&;0CAACAB`P)}CBDBDBB|B@C#CPAB.JABBApA\BBCCDGAdCBPBBC_CB@BBlBA`ABp@PBCA06BxCABB(B2CAAACO"CtBBBXBBLC4B*CCC(BP(BA7CB 0(BCDBXBN\BBBB@ACBxBlABx<LB AxB@A2C$B0BB BXBC\ C7C BBBAB4XB4C-CBBCC$-A?CBpCB0C0CBCUCA dCB1CBAdB$BBBBBB@BA\BBCt|B @C/C@[BBBB\BB=C@@HBB #C,@ABB$BBBBx-CCdBpHCBCpBpA\BABB4BpAPAB($B\BBB C;C/C8HBUBB@C@@BhBB9WDHCCA CACCRC BASChCBB CpBACCBB@ AADAAhA4BTB,BfCBHBC$C8BDB L C8CB?B0CCA7RCDC CCXAA>CBBC,qA(BB*CBVLNC$BlA BAABCB`ABCA@@vCC`BBaCCB8BPB@7CBTdAENBBB(BMA@A@A\@BC6CX`@BAAxCCGC/C0AtB4B@B@BBB4BBHB@BCt@/CCBDBC`B`@?CaCBNB BJCC(LB`ACBB@BB-C\BCBxBB`Y`AAB7CABBC`BB@SCcCBAICBBB8ATBBBBPApBCCDBCCBBBCCXBBCTB CAHBAB>C?Bp APAXCBBx BBB>C CtBBp >BCB9C40B5CCB#CBAABC-CCABBBBACACBFA C#CBB `AB BACBCAJC((BA4BBBCPA CBAB4CBBBCA@BBBpBAxBCTBA|BVC0ABCCAsPB2C|A%CB@<A5CBABB0BBACBDBABCB<PBgCB@@A`|BBPBA<@CCBlB+CHBB@?AACBB BHB CBB`CCB BB BAGCHB$CPB CB`A#hWC4B#nLDpAA4BCAC@AFCI@C CPB0|B@tC CBB%CBBYCPAxC BCBLL@BX CBBB@B@(3CfC7,B'CBBC/BCAA|BCBCCBB`TD@BABB0B0BBBBA|B<A@?pBBBTPBpBCQCA,CCB@ZC#`BBBB\BBtB@ AB4BA`B@C@@A D@CC|7A0NC A:LBJCCBB$ `%ACBBBCLABAGCB,BB0B A~BBqBOC+CC|P@@AD 8BP B@@B0sB(BApA$B5CBA AtB` BfCaC0:C ACA@BLB@AzCB@BhtB0(CPC@`B[CBBABBLB@BApBoAA?)BhBCC2ChCApB3`BPBABVC8C'ChRCB"CpBBPB$BCt BPA@ABCxBgBAM>CL C$BBpCB8BCBtB?B@PTB@AECTBxB@@B@@`B C t$PhBC,,PB8CBAF(,Ah@@B(ABGCBB\BBBBTCD@A0AAX5CCB`CAACCBpAC`C@BDCpBACAABPA8BA0BBBBB AxBBBt@BABBFCiB$BB(BHB#@A,CBHBCrB9CA<D5CVCCt B CBBBhB(BB@DBBCC N`BBCApB| CPBBB5BC00ABB^@tC@A AB'CBC[CCBh,BC\pBB8CBUCCC@B0A8XBCB,CBA@AB,BB%CdBACCC0BBDBB0ApBaCB B%CAC+C3CBC@A{BCB AAPB(C B8-0BCBA@AiC|ABB@BA$A A@PABRC|BA`@pB@0| CAB'ChTC@BBBBZC 3\8B@C C@0B)B,BBAAB @AC(BEBB @PB@BBBBB2C,CA(C`B(A B@A CxBFePBA,BAAMBB,_CAABCB@BLBABjCBB4 A2`BaC@BC@BBC`8BB`ABB\AACAB CB<3B&CABACl<4tBBBBEPABBA BA C@B$cCB(BCBHB,A=CCB,B'LCLB,A<@LBBBPA!@(BBRC,|T0ABA0B ABBTBAABHBBBBB@@0ABB[CCC@BAABBB@BV,BACB&XCA"J`BABB`A$B C`BIC>BC C`C-s@C%C,$BrCAPBABAABBpB CBhB(BdBBAB`BBxBdCB!Cd,BCPBB@p\B0A B(pAXB4B$BBA8BmCBBBCC -(B(xC0CA50zCB@4BB@ABAAB BB\CB\BVCCABtBBCeCBAAhB4BTB@@BB$C AB4CB`TB$ABB@BB8B)CCABHxLB+CBBhBABCBBA@ABKC C@BBP,@BBCAA.@PABC4B@B@B(BA`DA\C1C&CBBB AICBRCqCBBAA4B8BBACBCBQCCBLBAB3CxBhC=CBB$BtBBAt( BCBA|B@BC0 FCBNBCCA0,BCABC|BB'C@ [BC@B3CiBBBA $BCBC$CAAChB? ~CyCp ,BBLB#BB`A` BTB\B\ItB8C>CHChBCBtBC@ABZCBADA-8(BMCxBB4CBDB%CSHBB CaCBB|k@BBB B$A@,BPBwCBCC8BC6~D`ACBCAC\BCB BXBBAABBTBPCPBC4C$B0BsC`B9CBABCvC`ALCETBB9CBC,B4AB C$P@xBBAA@@@ABPC,AB\'8BBABBA$@B AZCCBmB$BLBABACP*8BCPBx6C8?xBBMCLBBQ`gCBB@@;CHBNCB 0x08ACTB B@B$BBp@ CC^ CpCddAB*CB@AXB@PB3BXBC@lBCBB$BBA&C9CCZ+CA B0A-CBBXHBp04BB08 B(BBApBA@&C@BC*C$B\tB@BCHB B@@AA`B#C0AC3CtBlp]CAl`ABBPBCXCA\BBBCBBdBA CGC%Cp|BB@BNC'C|BCXBCB@` ICCBvCK@BBuC/,|lB;CAA_CA `DB`BCApAPAlAA@A,B^CAA\BLBl0ACB$CBBBB0CBA@tBBASC@:C BlA0JB CA"CB`C@C BCBB{CA?B/CPA=ChBB:CB@@pLBCA\BtBB8$VCB8CA,B4BPBeC>CT&B F 4CCB0CA`CBBBBBB8C CBCCTBBCBZ83,BBBdBBATClBBHCB,-|WC`BCxB$BB,@BAB%CB@eB.C0(CBBBPChACCBC$BPBCBBABA,BD\CC 26CICyCABCB AABBC<CA@BhC,BACBA<BxDB BBcCBBlBABB8BH<>@AB@CBLB@xB! @BABCsA$"CB8?`CA<B<`|BH(B CB@0dB`CB t A@ACA0A8@LWCCGCA0BBDB4AB8B|B CB?=CTBCFCABB A@B@A8CABBZCB@@AplAdBBhBL0C8Bs@ABCB@xC BBpBH0A4dB@CB@PAAC$BABBB\Bp<AHCB A`ABB0BLPB#CB;CB@AxB`LBPA CAA!CB@`BICBBdB 4B0CBtBB1CAhBBC,B 0AXCB BAB|B0pA^CC0AAB$CCgCpAB@<@C;CC $B@A`AABB1BBBCBBCtB .5BCB>hBBBB:xB CxBBB00%CBBBBhBBfC8CBCTBHAUCB!BB4CPACAABS,CBBB0Cl,BBA@BB%CBLBCHCBBdB@@CC,CCBB@$BBAC@@&0BAB@vB(BBBB\BB CCBCABBpBACLtAxB@@CBCNAABBC4LABPBB\*0AB.ABA'<hBCpAB#0B$Bl`A$C0PABC@@ AC+xB C\B8tB$ ,B&C$0BPhB C@AAB$BBBm BCBCDB@B(0 CCFC"LBBBtB9BB @DB@`BBC CBPBAApACCBCBBBHB,C\B? B@ABPAPA ,AGCDCCBBTBA8C/CTBBA@9.C Bx CBAB|BCBB`BACBhBApA(BBBCB%C$DpB4BBAPBPA0A!B@A5C7CDBVAABB):0AHAB\B,BLx&CDBC#CC8CBJtpACCBB0B(C@(QBCBBAxBAxBAA0BtBBBBpB< (VCeCB`A+CChB@0AA0#C@ABBB- @ CCBA BB@pLBCBB@B!CpB@@hBABACA(BB C@A`BBB@pBPlA@@B,CLCBA0(CBC0CA0A,CSCA@AA)CB@ %AXBMBH8BP AB?'B?CBBBV+0B^C(0ABBBB@$ LB:C@0@CABB`A;VTC$BABB8DC0B CAA CCD@S@B\BKC@BCo`CB@@4Bx BA?CB A@pBC@C/CBDBZBBBA@CQC`<BBh\BGC(!PBB C@$BBHC0BB\AB0ABxA!CBpA B|B`BldCfCAABC C\LC8B BCA$BBbFCBpAlB8HB4CBABA<`n +CB,> ACA@BM0B BBB5CABAA@C BB&BALBxQMC4B\BBB`BL CCBXB CBBB0CBPcB|CC|BA}Cd8lBA@BBVC ABCB X0A@CB(BiXBBBRIBBwC^CHAQ@@B'ALB@C0HBABtB C=C@ABBAL CCBA?C%4B@BBCMC!1CAsCB<B(ABB|hBB)A7CBL@@@B@XB C8B\BBAB(B@B6CBFBC8TB`BBB@A|BAx@\BAdB`A4CB\BtB B@;CBCB@A@@BtBBBCrBB4lBF BhABC CDB!CECpBlBCCB-CBbCPAABBBbzB4BvCC kBBDCB@AC C`C+B CB0@BBC$C`BXB`<C`UCBPAC@8`BBBBBCPAABA0BB4BB4l|DBpB:CBBTB ABXBV BB@BABB@P$CBBNC,BGBB@CBlBC`ABXBCVC3Cp BCB PBACCAPB0A%CTB&A$>{CCBAAB$CC6CBFCB0,B@BTBlB@BBtBCXpK9CBBB R CBxBJl*C BB,B CB`BB4 CB*C` AABACC} C)CBB+xdLBBBBH pCBADC]CBCBBBASXBCBBA"C(BA@BBPAtA"C 4CBB8BBA4C (CB;CBpABB C ,ABCBCABC<AAB0ABYCAALADBdB?C@@ACB@AACXCPAXB@BACC C`BBBNCCC@XA0`BBLBPABXBtL0BB;ABA1C*CBA CpBh|BlBB B`CfCCBp|C_C0B\gCBdCB@AhBBhxBBBdBgT,B`B.@ABAC$AA%CCCBBkCCAhBABPB2Cd4BAB%CBBCgCB,C CB@DACBBB CxBXBB\BBB( BB0HB@BABFCBCBS<BAcCCC: B B*@CCj4$BBAHC,CBPCB`LBCBB*,@ BBrCBBBlB$$BB_C BC, BABtB\CB-CB\@?@BCB$0B`B<B@BxB]CjCB]CBBBdB@(BhBBBB`|BA@BBBBB@pB$BBCXtBBBB@`lL!CL8C2CCP@BDBB7lBBA B2pB\CBBHBC`0BY6CBBBhBPACB/C8CC@BBC|B@A B C4BCDBC@D@CA B|B`BAhB8B*CdBoCA| A\C@p-CC`A.CB&CB,@x4@@BB CBOCCB@CBcCBAPAB$@A,CC )1CBCBBB C0ABCB00AABDB|BB BCBBpA8BCBp B@R@ABACCC4(BCBDC$BB BB0B<AZC4C`AXBBHBI@BBNCBBAB@d`BBC@@ C(",0BBB@A C C B0ABHBB@^pCHCB*C|BB .BBBC@AA$ACB@B5CAB\B0AC@@BXPAB BBCBB\($BX?BPA#B\lB BBC8BxB8BB0C B@B-CABt@BCBB PB@(C4BQC B-AACCBBPA A0B+CHC+CBB jCHBMCBPC0BABB&CPAICB @@8CChBB6CBB@CAB8BB'CABB CCB lCB BC=CBxC CBxBBCCCoBCBBL`BTB@A }CBABB`AB*Cp #CBBBI9PBB@HB|BBAABC9CB5CBC@B\CClA`BdBAA@CCxCQCXBCECB$)&C`ABBBA@`xhBABA@TBB"C0B@A@DLBuC BBBLCKCC]BBBAB!$THBLClBBCBB>CB0\B+|BtBHBAB C30B CA)BLBBtB/0C,B,BwCBDCHBpBB`@$=ABtlB PAAB`)CXBpAHBBBBLCA0BAAgClBAA@BBBBat?hBBB0 `CABBBA@ALCBBBC\CB?B9C ABDBdlBC@DBCACC@jCIC CtBBB80B;Cp BB9C0ACP$BCBbCC@BBACBt A0ABCXBC(XBBBB(EB @B4BC$CCB0BCBqCB&XLB'C"C$LBBB tAXDBtBACBdBB @BACgCPB@0ACAABLA`B\BBpBB/CVCD`ABKC@B6CBp[ABPBA@hAXGCB_CBdBB(CCBpBB$BBAB xAA(BBT <&C@Ad8B BXBCdBABB*C`AB0BA8B0ABHBBpBB@BA,BA CB4ALBLAC1CBPCBCBB+CBlBCB4%CA$DBCBA@BB CBBA8B B;C8B0C3C(CCBA$Ah?pBBCBEpA>CB2C\AB= A CB,B8l 0BBBCh X!lCBHB_C|A CBA$$BB C,BAB@ABAB8 ,CLC0HBB)0ACBC4dBBFC@&\BTBlBBBBCR5B:BBBhCCAL0BnCC$xBB?1C`H CBI A@CABBBCpB,BBCBACB CxhAHDpA3CBp CB LTC"CAPA>`@ABAhBdBTBlB CB,BDB#CBC@AC<B( A CB\ CFC`BBlB( C]CB"CBB B|@BHBBBQC h&CBBB0C@86BBBBBBABA_CBBBA@BKCdB TBB0C[CCPBpdB|B @@zC?BxBCABBC`ABAp%C 8 B+BVCA\lC!BCDC4dB`BA$BBACBhBCCBCAB8AAhBp  BBB BB0BB4dBoCCt%LBB +CUCB0AC AB|AB @AA@|A&BBABCB#*CB$-CAB`BAAB|BBC CKC0AEBB5CPAADBBBA3(BBBBP0BFC`BC<A8B CA9CA AAAC(BCtB@@CB?A`L\BCBnCCBC0AplBDB6CB$BBBA BBT@@$XB0APACjCB:Gp8B|CB@(AABB`ABpBd B(CMBPCBNC0A@@CTC"CB CBCB?BCCB4+9A2 CB`BB@@pA(BBAA&tB5CBB$B?BACBAdBC(C4CB@@ TBABBB@ BB vCAACB^C B CC%C0A A@@hBC4CABGBBAPABA@BLCBBlAd`BB0$T6CBBB:BBA8DB@E@BBMV!dB8C AA\B0AB$C ApB0pBCd\BBB@AC6C0BtBBABCTCATCB5CBPA`BBBAB$@AB(B kCBXpBClB <WCXBA BCB8BhBBA`CAB@pC:C4<4BBBAB<A0@B\`ABCBABpBCCP'BCB ABACBA,B@A9CBB;CA+@BBFCA B/CPABB80BACABB$`d(BAB%CA B@AADBC@AQBh>hC+CxLpBCBpHB BpBC@ B?XBDBBABCcCBHB&CB "ChB@<,BB!B4B`ALLBAA@B CBACAB@ ABAxBBABCCB'C&C@ BpACABBBLB@BB`BTC? $B.CC%9?5BTtBECPA@BBBBBXpAA\BlBBhBhBBMCCCC)<BCC5HBBC C$BBCBL,@BAB@DCCCBL8 C0BC0C B CVBBBlBA;DBBB8CAlBBBB CAHC ABhBCVCBBBB`CBCBBBE)C@dB]3C ?~C CBABBBALGCCBB0C AxBAp CdB3BPBB0B@BBACCJCBABBcCB?GBCCBBA .?PBPC$;ABC!C!<p hAB B4BC@@0LBCBBCTB(CBB8BBBHBp0CB@B6CB`A0TBC C xBAC@B`ABjCA,BC8BPBtB0!C@PCB0*hA2CBBBB$C@0A*vC+HBpAB(tCCBBBdC+CAECBAB BBA`AD A@BBXBA:pCB5CBIBB@@CB'LB@@B `BpBA7A8CCPgBBBBAAC"CAA0CB<4BHBBSCB@`A`BBPT:BBp? ApC B 0:C`BCVC B0ACB,H ABBrCB|B@:@B@ C`BBB@AXBB?CB @AB@ABhBCACXB`AB)CBBBBB<0A,CCGC BCBHB0ACC@pAClBBBCbCXCJC@hB!BB BlLB@ABDCBABC07@(`BBB@ABgC!CBABtBB@]CBCltABABBBCB AgCBA88C($BBCACV BB8@@/CB`BCBBQLBDB,BBCA BBCd8BBABByC8CB%CABC@AB[C hXAzCmCAA`pBCZC`ABB!BdPC,B4BB|pBUCLBA|B@CC@@BAlCNB@@BBCB'B ABCCBdCBCAB8B;CABDB`-CBX0A" CBICxBBBB%CCCBBA|B\B%BzCB83BAA?_CC!PBB`BlBBTBB,CC`BCpBtBBB0A@xBHBC@BBBX<@`BAXCBCH, ]CBAB@AAC@CAlBA6CCSC"BBBBBLA+CB BABC`BBTBBB0BBB>CDCPAA B@BAB\BBB`AhpABCBLBBh0ACC A|BZC\Bd`BAB@pBpT*CC*4BBBHBBBC@@dBTCWCLB`8BBPAP<BICAXBBXBBHB @BCB B;CAlBZCC%@BXBBBApClB B BC\B@CB4B8B ABqCBBB@ChC%CAAB\BCB@0L@BABB,BClCCtBNCC(BB8`AB0BLCBxBVC@BAC0BXBBBCBB\BB=B&C@PAGCtB@@!A?4ChBB A<XBC CB=CX@0AABpCBkHBBd+BC0A0BBA@0CBcCABAHB NCCBBBBCPATB@ABA0G`ABwC`B @ApBB CTP CA\,@CB dBBCXABBBHBBdHBLBCpB8lBBCAPBpBT'C8BAABCB{B0PBDBBBB0B(@J`BlB8@tBLCB++CTC@BCB0BdB%B0A@BNCBB CjCBAICAzA%ClBTAA$BB(t 0BB@:XBXBC^CIBBICBBB PABPhBX CP\BAoC5CB@BBBClPA AABBB7C x(B(P B4B3(BZ6DBCCABBl\CBBAjCBB0BC0A?@ BBO$VC7C B@h 4C`CBBTB.C4BB$CHBB`B0-JAA$6C ,B|AHBBlBB%`B`A,BCCBCA)CCB3C|B@<2C@BBPA)CT<^CTBPCABxBBBBBCABBBCCp;CpBB$B,BB0BBB BBTBBBB$)5CC3CAHBBBA*G@ BIC@Bl CCBCB ACuC0@^C>A0XBBCBCC&CBHB"CBB%B CA@@BCBDCDBUBBCBB AB4BA( CQCCAbCC@ABBB`dBACABBDB@dACpABlBCBCBhxBB@BTBUC$CBLB`BHClBAC8 C|CBB CBA B[C<BSCBlBC0B BAB4CA @KC@ABBpP0AdRChBBBBBXNB@DC0CBo8 AC`ApBBAhB$LDBD0BACk(B4BdCBLB\BB(CBB<C:CBC@BB@BKCtCA@@(BCdC@\0AtBABHBCBPAZB( C3@TB BBB@@A`BBCApAACBt bC"CCTBBBB1C5CBDB0BpB`ACCHBAA@PACBHCCBC CBAKBBHB@BpBBjCCCAPA@B@@`(BB8BCAAACC@\BBB!C$ TBlCHBBPA dB:CC@B.C`B@BB-CA B@A\CPABC&UBBAdCB$D0UCBUBAB#CA8@~CBC /C[CB:C<DBCB0CBB@pAhBBB0pB @CCB@AAC$BB&CAoCApB=CpABBd$@|B@@AvCA ACBdBtpCBBB<LCBB A0AhAB\B$BACBAABABCBBB<;C@cCBAUCBxCA,BtB$BBBBBBB0B0AHB@8BA6CzCB4B\BBABBp`BB&CABBBdB8B@CBCBCAAB|BB4XC9CCX;@@BXAC@8BA@CwC@@B'CBB>CCBCTCXBBB,BAPA-CBxB~CNCrClB`CA<d AHBo05ApB?`B+C|AAQ`<@AP8C]CA@A@CAxBACBBB0B@PABBCPA?pA0A7CBAxBBA`BA`B%gB|B^CCB@C@PBCLBMACXCiCCB0ACA=CB?pAxB(CB CApA(BB`D?H0BBCXBBB,BCBpB@ A4CBhBBB2CAXBB,BBBABCCpAA0BABBBBBTBBpB`CALBIC|BBhBCAAA1CBdBBBCCBHXBBnLBB B``B:C Cx`B+CPB$CDCB A  ApABBB+C 0ALBlBC (BBA\$BhBBC4A B BBCrBTBBA9CRC CCB`BH8BCA8BBUC8BCBBB@BAB?BABB(BlCB ABB Bt8DBAL@@CABBBBBBB BdBrC:CBTBVC"C/B6CCtABBC=pABBB1CBB- CBt4BABABC4C!LBA CA=CB%4B(BxXBCBBBBBDxBTC_CBBA\TBApB9CBBB`ABC B2CXC6@BLCB CBA0BACA@,BBLB(BACCB}(BCPBTBdCB@B B CBC?BCA$ABBHCBA>CD CCA*CBCtB % ChC`[CTB?`AB&C 0B0ABWCChB?;A0ALBBB@0ABAC+CA=pABABAdB`A(CBB;CCBCCtBBBBB@@BTC8CBBLCBD$$BC,BA|BBA`BA@CTB@A8APpXBAABB`A$BCA4B`BB CB,CBCBC@A.xBBDABXB$B C/tB A@B@HC4BAdC@XT AlBBBBBB@`AB$B0ABpB0@BB ABAA C@@ABB B`CA@BCAB{CBTP@hBkCAXBpCBBBBBBA dB$CABBABA CAAAXCBBAA`BBB1BBCBBLAiCAB@B@B@B?B56CHBBCLBCx,BB0BBBMCCAB:BC(HB@DB0ACCCB@ppAB@|BPC}C)CC0ABvCC$uAABCC9C`AB)CAPAdBBCC`PB4BB6CCBBAlBB@B(BB B0ACBCBC"C C B C@AC$CBB$B|B,BACCC@AhC"CC`A1CA8B"C&CB(BBPBBl@@CBChB|BAtbC<B3C9CBCBBB0A@CCBBICRC4BdBAABBiCBTB% BBA%CBdBYCUCBA@A<CLBACCl`A>C-C0C5CAAxB\BBB+CXB B-C;C4BB%CZCBBBBLCBCAAAC|C@B@@B1C0BB CB0B(CAA`BB CBxB:CD0dCBBB4BAlCvCB]CA@C+C CC@AA48BC:C#CCBC`BlA0ABCLCABXBA\;CqCB4BJC1CCpA "ABC0APC BCppBC_CBBB@CCyCCAAACCBCACABB7CBLB3C`BCC;CECBBxCBC?CA(B,CB8C2CCCB CCCCBBZCB?C,CB\CBmCC CxBBTtCBmC|CpCBXCBB2C2C3CC5CB;C/CC?CBBBADBCCBUC'CSCCB|B@ CBBCCSCBzCBCCBB*CCnCBCCCGCHC'CCiCBCBXB CBBBHB1C`BxB|pAC CB`A3C(AC9CACDCCC`TB{CCpAABApBB*C$BA/CBA$B0BCECCpBBBqCB pKC\CpBA.CAp0AWC0C2CDB`BB;*CTCC,B ?BBCACB0BBBCBC&CBPAC CBcCCLB6CBVCBlA,BBCBxBBCA B\C|CeCBB BLBHBcCBnCCCPA\HQCAPABCgCCxBABCCBBbC@BJC|LBCtBB|BBBB CCBCB=CBPCCB BB@CC7CCCB`B CBpACCBAUC?B@BBhCBBvCBB;C.C'CBA#CBCB@tBBCBBC4CBBOC C$B#CCB@BHC(C(CCBABBBiC-CCgCPBCCC(C!CCmCC'CA?B@1CCjCIC A B0HCZC_CCCfCjCAPBACBBXB BB$BCCCB`BRCCCB BZCKC7CBBBBBCChCt@aC8ABBUCB(BBCECCCBTBL(+ChB@BCBBB@CABBB4CWCCB|`@CBBBBBB`BCCALCB)CCB8C[CCB,C$BC0CB`A\B@PBPBCCNCBC)CCBB|B/CBC2CC-CCBC B%CCB]CCPhBBrCB@dBBCUCCC CC6CBBCBCCPCXB\BC1CB CAPBC/CLCC\BBCCvCCBCCxC4CCC CA@4BCCUC`ABCBCABVCBCB@eCPABTB BBECCC}CCB(CB@bChCPAB*CCnCBCB/C3CCEC&CP,BBBACC3CBP@A A-CCCB\B+CCBC)CCBBCC{CCHB>CBiCCCSCBBBA*CWCCCCCBBPC?.CzCBOCCCC.CC-CACSCCB=CCbCBBCECCCB1CZCCCCCJCBxB,CCC_CHCBC=CB>C;CC>CCC\BCCCCBAqC=C?CC0CCCuC;CCCCjCJCoCBCC@DCChCBtCCPCOCCBCCpCCCMCB CCDCBOCcCCCCCC$C C CCCGC@DCtCCCCCBCChCBCC6CeCCCCCTC C|BC aCCCAP,BCBCACBBpA@hB@HBCBhBpABpCA$C7CCB,C<4C@BQCdB@BCkCCBJCCCCCECOC8BA~CBoCCKCFC:C]CBCACBBACCrC;C3CdBA9C5CCB,CBBQCCBCOC-C5CxCCC.C-C,CPBB(B`CAAp BOC7CCC"CBB-CBBCBBBfC3CABCKCBYC2CBCBAB@CYCCACBB3CBA@AhCHCGCCAUC3CYC`CdCBBBaC+CCBrC8BmCCNCvCCB>BAMC-CCxB CABCVCxB8B8CsCxBLB(CCCCCBBB+CB%CzCtB|ChChBB{C-CBBCuCBCB|CPBBBBC*CGCPC BB;ClC0CfCBBBC(CBAC.CBB C`CCJC-CCBVCBCC BCYCCBBC^CCtC;C@DCB BB C CACBBBBMCBBCC1CBBCB@BSCWC9C`BLB@1CCICBBBDC:CB$CBBCHCACkCBBBXCPBCCdC!C+CCBCC)CGCdCC`A{CVC@C*C@BCTB`BC2CBHCC0BCCBmCC1CBCBCHBA(@CXCZC}CHBDCBCACCLB@A"CCCCCB?CICACCBABC(CA9C}CvCsC-C BCB4BCABCBCpA`AC;CBpBCCCCAC?CCuCqC CBCxBB,CClCCC C CpA`ABCCMCCCC#CBBBBeC%CBBBCvCJCCB ACcCgC?C2CBCCSC~C5CTCBBVC6CCPBC\C@CCCGCCBBBPCCCC(CB`BFCCClC7C CC)CBC CC)CBC7C C3CB*C8C1CiCICSCB@BTdBhCC|CCB3CCBBdCRCCC3C@CC>CFCBCCC C?C4BB?CBCCCCCBICBBCC C@CC$gCC BBCC$CCCCCB C C&CACBCCBoCCMC|BTCBCCCCC CCC0CCCC9CBCCICB0CCCC CpBBCCCRC!CCB|CHCJC&CCrCC[CABC3ClCpCgCC^CCZCCZCCDFCCzC'CCBCACCCCCCCC_CdCqCCCCBCPCCCBBCCCC?CCCCdBCGCCCC2CCBCDCCwCCBBCJCbCCDCCCwC1C;CBDCCCDkCBCUC`CCCBpCCTCCyCCwCCC8CkCCCCCCCCCCCCC*C"CCCCCCACCCCCTCCCC-CCECCCCCCCdCCCClC:CCDCCqCCCCCC4CCCC5CACdCC5CBACCCCgCB=C[CCyCCSCC.CBABCBCyCfC;CCBAwCJCCCAB CA CC!C#CBCmCC!CSCCCtC!CIC4BCBCBHBC[CCCC BuC7C CXBBC2C?BB C9CmCCCBCC;CBICCPCtBBdBSCC5CCdCCC;C]CCCWC\C CC|C_C CCCBiCCC:CC.CCCFCYC$C/C(CCC@C0CnCBBCCC:CCBCKC/C;CCC3CC-CbCCB]CC0CCCCCCCCBBCCBCCTCBCCCCOCCgC CCDCC\CiCdCkCcCCCdC*CCVCC;C[C~CCCCBC)C;CC@C#CCRCCB_C?C[C=CCKCCCCCcCC{CCChCsCCCCCCC~CtCCCCCCCCCCGCBCCCC3CpCCwCBCCCCCBCC?C0BCCSCCCCbCCCCqC|CCtCCChCCBCCCCCC[C^CCCCCrCaCCCCvC_CBCTCBCCCCCsCsCCCCC$CC D~CBB)CCCCCCCCCGCCCCCCCVCCCCCC2CCCCCCqCCCCCCC(CC-CBCCCCCqC%CC9CCBBCCCBbCCCCcCpCSCCCCtC#CCC`CVCBCCCcCBCC+CpCCC`CCCCC]CBCqCCCCCCCBrCmCC@D DCmCC;C@ DCUCbCCCCCCCFCACCCCCCCCCCxCCCCCmCCCCCCXCC%CCCC_CzCCCCC#CCCCCCCCCB;CDCACCCCC{CVCC6CCCmCCCCC CCCC]CCCCCCCCWCC=ClCCCCyCCC5CCCCCCCCCCCCCC{CCCSCCCDCC#CZCCCDCCBCCxCCCBCDCCCiCCCCCCCCDCC@DCCCDCCCCC@DCC`CCCCCCClCCCC@DCCDCCCDCCCCDCC?CCCCCCC[C3CCCCCCCCCCCCCCCWCCJCCCCCCC CCCpCCCCDCCDECCCCCCCCCCC?DCCDCCDCCDCCDDC DC+CDCCCCCCC@DCCDCC@DDCCCCCCCCDCDCCCCCCCKC D D DDCCCCCCCCCDDCCCCCCC@D DCCCCCCCCD7DDD DDDCCCC@D@ D DCCCDDCCDCDD@0D D@ DDCD@ D@DCC@*DCD DDCCwCCC)DDCDDDD@#D D1DCC@DDC@D@!DCC@*D&D@"DD@DD@DD@DD D@DCDD D3D@D@.DCDCC%D#D DDDC!D D@ DDDD9D:D@DDC@D!D@-D!D@DCDCC!D DVD"D@&DDC^D@$DDD@D@&D@DC@$DKDCDCDCD*D'D&D DCDKD@DD@(D@D#D+D/D%DGD>D@6DWD-DD&D)DD[DHD@DD:D(D7D@ DPD@-D%DOD@ED@%D?D@3D%D@6D@ADQD(D.DBD#DBDCABBB&CCCxCCTCCBBCA(BECCCCCCA!CBHBbCCCCxB2CB:CBCC9CCC]CYCCdCCCCCUC0BB'C0`C@DCXCB:C?C3CCCZCCCNCCAWCHC`CCC%CCC'C/C@HCABCBCC CEC,CCCACBvCB4C{CC@CC-CCCBCCBCCdCBBB+CCCCCiCC^CCBCCCCB>CMCCCDCqCBOCHCBCCCRCCFC!CB<CCxCCB0CCCCgCCCC]CC CCCHC}C>C\BCC]CCCJC AC|BaCZCC^CC_CCCRCoCB?!CCCCB$BDCCC{CCCNCCHCBCBCCBBoCCCCC]CCCCCDCC|CUCCCCClCLCCC#CBCCCCvCCCCCbC/C4CC`CCwCCCB CaCBCoCACSCCCCnCBCCCCC!CiCCDCCC9C;CCBCCYCCCDmCtCB]CDCCCCCCCC{CCCvCC~C\CCCDCC@vChCCCBHCCBCLCC@CgCYCCdCDCWCCCC"C.CBFCCCCCjCPCCBhCCCCC!CrCCCCGCCCC)CuCXCC[CBCCCCCCCCCCCCCCCCCC DCCCICCCCCCCCCCCC[CBCGCCCCCCCbCCC*CHCCCDC\BKCUCCCCCCC8CCCCCYCcCCCCCCCCCCCCCCCCCCCCCCC1CCCCCCCBRCCCCCCcC>CC DCCbC CCCCCDC_C%CCDCCCCCCCBC@DCCCxCCCCC@ DCCC@DCCCDCCCCC@DCDCCCCCCCDCCCCCDCCDChBCCCCCCCCCCCCCCCCChCCCC:CCCCCCwCCCCCCCCCCCCCUCsC*DDpCCCuC@D}CCCDCCDC DCsCCCCCCCiCCCCCCCCCCCCDCqCCCCCCDCCCCCsCCCCD@DPCCCCCCCCCCCCCDCDDCCC DCD DCDDCCCCDCCCDCCCC(DC DCCCCCCCCwCCC@DDCC@DCDCCDD DCCyCD@ADCCCCCCDCCCCCDDCCCCCCD DCCDCCCCC DDDCCC DCD@DDCDDCCCD.DD@+DCCCCC4DDCCCDCCCDCDCCCCCC*DCCC2DDCC@D'DDCDCC+DD@D!DCDCC DDC)DDCC@$D@"DDD@DCCCDND2D*DCCCD.D@D@DCC7DCC@DD+D1D@DD3D!D@D@7D D@DCCCDDD)DC D'DDDCD:DGDCDDDCDDGD&DDCD=D+D1DDC@DC#D'DCDDHD?DDCD/DD,DD_CD@D%D0D@DCDD*D@?D:DDCDDD4D:DVDcDDC,D@DDDD@D3DDD2D@.DFD@(D>D;D D/DDFD!DDDD@9D:D@_DKDCD@DD@IDeDJD$D@-D=DZD@{DUD/D0DHDIDCDWDFD@1DKDeD%DD+DED@aDDFDyDRD@>DRD@RD#DC5CLCBCCCxC|C}CCCCBA'C$CBbCC"CCClCNCBBCfCC)CSC0CCC~C5CgCC`CcCCCCCoCBACC~CCICCCCCCBxBCBCCC@ABCCD]C9CC(CJCCCJCCCCCAC&C:CCCDCBChCCCuCCCCTCCBXC0CCDCCCuCYCpBCVCDCCCCBBCgCCCoCC(CBCCAJCCCC(CyCCbCjCBCC?CCCCB6CCCC CCCCCCBuCCCB{CB,BCC%CCCCCC>CChCDD*DDD.D@DC:D D!DIDD DDDD*D&D%D@4D@DCC?DD:DDD(D)D D@DCD D@)DC4DD1D4DDDDD D)D D@D@DC-D;DDD7D@DDCCC8D@8D+D@PDUDC DDD@#D D@*D8DCCDbD*D.D:D)D DD5D9DC@DD:DD[D1DDD D@CDAD>D1DFD7D&D4DBDHD@#DDFD:D@D]D\D@$DD$D2D9D4D@ D@$D-DFD-D@UD.D=D@ DDD@$D@2DVD3D5DOD'D@CD?D@D@9D[D1D@OD@DEDC7DD>D>DD4DOD$D@?D9D@EDJD@=D4D=DaD@D.DFD&D&D@KDNDMDID*D@6D>D-DaD=DID@D>DDD`D@AD@gDZDPD(D@ DDZD@mD@^D@FD\D5D'D`DDLD`D@EDRD,DDD@DC@$DCCDC@ D@D!DD@/DDC DCCDCD DCCCDDDDDD0D@DD6D.D@/D=D@NDDRD@D(DD@(D@WDKD&DpD'D@4DMD"D@D:D@1DC@BDYD[DgD7D+D.D8DLDaD"D$DGD,D@GDSD:D]DDdD@D?D@BD.D,D@+DWDsD@xDCDD@(D1DND1D3DND@eDVD>D@GD'DCCBjCCWCCpCCB;CCCCHCCCwCnCpBCCTCCCCCCCYCCtCCCJCCCCCCCCCC~ChCBtCCC\CCC~C}CCCCCkC!ChCCCCBBCTCCCCCCB5C=CpCCxCCDC#CNCCCCCCCC~CCCCDCMCrC{CCCCCCCCCC=CBCCCCCCCgCCCECBCCCB|CDDCCsC`CCCCCCCCCCCCCCCCCCECC0CCCC@DCCC DCCCBCDCCCCCCCCCCCDCCCCCCCCDCC@ DCCCCCDCCCCCCDDeCCD-DCCCCDC`CCCCCCCCDCdCCCCCC@DCCBCDDCCCCCCCCCCCCCCCCC DCDCCCCCCC$DCCCCCCqCCC;CC DCC~CC DCCDCHCC$DCCCCCDCCCCCCCCCCC,CCCDC$D@ DCBCCcCCCCCCCCCCCDC{CCCDCCCC@DC DCC@DCCC@DCCC,DCCCCCPCC DD@:D@DCCCCCCCCCCCDDCCCDCC#D@D@DCCCCCDCCCDCCCC@DCC@CC@)D DDCC DC@DCCDDCCCDC@ DDCCCCCC@6DCCCDC DD@DD DCCCC@DDCCD@DCCC@"DCCC@DCC@D2CCCCCCCCCCCCCCCCCCCDCDCCCCCnCC3D DDCDcCCCDDDC@DCC8D@DCDCD@DCCDCWC@DC@DCCC@!D@DCDCCC D DCCCDCC@*DDCCCCDCCDCCNCCDDDDDC,DC@DDD|CC DCD@0DDDCC@D DCCD@+DCCC@DDDC@D@DC@DCDDCCCC@#D DCC*DD@9D DCCCCC8DDDCCDCCD@.DCC@DCCDD(D@/D1DDCCCD$DCC!DCCC2DDCCC D@DDD@ DDCCDCCDDCCDD@#D@DD DCDDDCCCD@5DCCD#D@ DCD!DCDDC!DD0D@DCCCD@ DDDD@D?DDCCDDDCCC@(D@D@&D$DCCCCD@D@DC D@:D@ DDCC@DDD2DDCC@D@DDDCCC5D@DDCC@DCD@'DDCCD-D9DDDCC@DD@ DCADD@*DDCCDCDD@ DDC@DCCDC D@DD@kD@>DCCCCCC@DD DC@/DD@,DDDCD4CDD=DCDD5D@DGD@D@)DD@ D@#D D!D D@ D@D/D DC3DDDC9DC@ D3D DDDC*D@EDDD6DDD DDDGD1D!DCCC)DDD@DDC%D>D+D@DC-DDDDDCDDC%D=D@2DCDDDDDDgDC DCD@D5DDCDD'DC@D)D2D%DDCD@1D@DDD!D DC D@D@DC3D@D@D DDUD DDDDD_D.D@D@0DDD@D@DD!DDD2D*D@>D%DD@D8D@,DDeDhD>D@/D.D?DRD0D[DcD@DD@DDDD&DD DD@BDED-D@ DD D@/DDLD@ADDDD:D5D@DHD[D@ND"DD(DD@ D-D@>D@ZD@JD0DD,D@:D6DWDPD8D)DDDD"DCD@!DDD DC D9D@D@D@D2D@D@DCCDC@ D@4DJDC!DCC%D%D@D"DD$DD@ D@DKD DCDCD@CCCCCCCCCCCCCCQCBCCCCpCCsCC:CCCCCDCCCCCCCCCC}CCCCZCCCZCCCCxBCCCCC8CICiCCCCcCzCCCDCwCCCCCCCCCCCCCCCTCCCCCCCC%C3CCCCCCC~C5CCCJC0CCCCDBCCCCCCCCCkCCGCCCCCCCCCCCCCCDC|CCLCC DC{CCCvCCCCDCCCCCCBCCCCCCCC CCCCCCvCCCCCoCCTCCCCCCCCCWCCoCeCCCCCBC DCCC}CBCCCCCCCCCCDC1CCD@D@DCBoCCCCCCDCCCCSCCCCCCCCCPCCCtCCCCDCCCC|CCCCC9CCCCCCCDCC6CCCC@DCCCCSCCCC DCCNCCCCCCDCMC=CC=CCCCCCECCCCCCCCCC@DCCCBCCCCbCCC@DCSCCCCCCCCCCCCCCCCCCCC DC_C(CCC@DDDC`CCCCCDCCCTBCC@DCCCCCCCC{C D"DCCC+CCC%CCCCCcCCCCCCCCCCCCC[CCCCCCCCCCYCCCCCCCCC"CCCwCCC>CCCCjC,CCDCCC8CCCCnCCCCXCCCXCCCCBCeC@DCCCPCCCCCCCBbC.CCCCCCCCCCCCCECCCCCCC C!C]CCCC'CCCCCZCjC DCC=C CCCCC~CtCCCCC_CTCCCCCCCCCC3CCCCCCCCCICCCbCCYC=CrCNCCCCCCyCLCCC DC|BgCCCCCCCCCKClCCCCCC_CCCCCCC/C/CCCC`CCCCBCSCBJC:C CCC8CCCCsCCjCCCCC.CCCQCC;CCCCCCCC}CCB7CCDCBBrCCDCgC CDCCCCsCCCCCCCCCCCCCeCCCCCCkC$CCXCCCCCCCCCgCdBqCCCBBCCCCCC/C@DCCCxB~CCCCCCyCCzCCCCBC+CCC;CCnCCCCCCeCCCCKCCCBCCCCCC4CCCCCC@DDC^CCCCDCCCKCCCCCCCC^CKCoCCCCCCCCCCCCCC7CCCPBvCCCrCCCCCDCCBCCCvC=CCCCCCCCCCCCCC;ChCC'CCC CCCCVCC@CC$$BCCCCC CCCCCCB@CzCC&CC~CWC7CBzC&CCCCCCCBCCCCC@CCCCCCCCC~CrCCCCfCCC{CvCMCCCCCCCCC%CCCCtCfCCCCCCvCvCCCrCCCCC8CCCCCCC\CCCCCCCCGCpCKCCCCCYCCeCCCCCCeCBCB`CCNC7CBBHCCCACCCCICDCC|CCB-CHCCCCCXCOCBCOCCCCfCCClCiCrCyCCCCCCCCCCCCPCCCCCCCB|ChCCCCCC)CCCVCCCCuCBCC|CCCBSCCCmCECCCCCC[C,C\CCC`CCCCCB9CCCnCC8CBCXCLCCCClC5CCCCCBxBCCCCCBBCCCHCCICCCpCCC^CCCCCC:CCHCHCCCC=CCBrCB@=CCBCCCB|>CCC$CCCCCZCsCCCCBCCDCCB/CWCCbCCCCuCC}C-CCCCCCCCCCCCCB+CLC`CCCCC1CCCCCCCC CWC CC:CCCCCJCVCcCCCCZC]CCYCCBpCBPCBCCjCCCCCBC5CB`CCCCQCOCCC!CYC{CCCBCgCpCCBCBCCC~ChC_CCCCCCCCCCCCCCCCCC5CCC;CCCACbCaCpCCYCCCCCCCCCC9CUCC"DCTCCCBB:CC DCvC=CACTC|CCCCrC=C)CCCCB,CBCCCCC7CCCQCNC!CLCCCWCCCvCPCCCCCCbC~CCCJCCCCxCCNCCCCTCCCCC CCCCXCCyCBCCCrCCCC_CYCCCCCC$CsCCCwCCCCCCTChCB#CCCCCCsCCCCCCCCCBCCCCBCCCClCCCCCWC:CC]ClB+CJCCCCCC1C(CBPBCCwC}CCB;CBCCC]CCCCCCXCCCjC7C`CZCCC2CCCCCLCCYCCCC CB7CQCOCCCC}CBCCCCCAVCCBCCaCCCC+CDCHCCC5CCC4CCCCCYClCCCCBA@ECCCCCCCCCCCCC5CGCCCCCBBOCCvCCB-CBbCCCCCCCCBCCC0C4CACCCCOCoC@CBCCCCCnCCCCC#CB%CYCC@-DCCCXBBBCCCBCCCC0CTBC]C^CzCCsCnCCCCCnCC)CC#CCCOCCCCCCLCCLCCtCCCCC{CrCUC1CCfC8CCCABBcCC&CCCBrCCCCC0CHBB|CC*CCCBECCCaCsC3C?C&C]CCC(C4CCCC,CCCBBCC[CCBPB+CMCfC[CICPBCCC'C1CBAfCBCC#CBArCCCCBCRC>CoCCZCCCCC!C]CBdCCCA\ByCCC CBBIC,CCLCCCACoCABCCCBCC_C[CCCCBDCCBBCCqCCJCWCVC:C~CCC+CB@UCoCC;CChCC CBBBCCChB CCCcCB C%CBoCClB=CGCCC0A CBC6CvC@CkCCC(BrCpCCCBvCCBCCC,C>CJC4CACKCgCCC3CCfCCCCCC C_CBCBCBC^CCCC)CCCNC0BkCCCCuC%CJCC)C$CCaCCC^CCyCDCCCSCCPBB(CBCCYCBCB`C1CCCCAC C,CBCCBBBCCCCCClCCCC@DCBBCCCyCxCCCBCC=CCC9CCJCcCCCB/CB-CChCCB'CwCCCBBC]CBCCCC5C*CBCCCvCCCCC=CCCC@CCeCC@D C#CfC|CCC]C@CUCCCCCBxBCCCCPB,BCCICC#C0RCCsCC8CCCCCPB`ClCB$BAvCCOCkCCjCCC#C@UCbC;CACdC@C{CBTCCaCACDCBCOCCBCCCCCC CuC+C0C_CBBBCCCxCC'C{CC$BBBC BCBnCTCBfC"C ACC{CC0CA@BBCwC"CBFCCB.C@BB)CClC$C1CCC'CC)CBB\xBuCCCvCCC|C+CTCdCCCC4CCA,BCCHC6CDBCCCFCFC4CCBUCCB.CBCCCC2CwCBTB#CBBCBB.CALCBqC*C$B,CVC~CCBCCClB.CBCVCBBpCCPCWCC CCFCCCBBgCB3CC(CBCACCB CBCwCGCBCCXCCBA`CCJCmCABBWCCB`ACBBCBBB3CnCBChBC%C{CCC=CTCCBCACNCB@fCCCC(BACB&CBvCCCACBECBCBnC CC2CVCsCBOCzC BSC*CB4CBSCCCBCKC&C9CCCEC`CC~C5C-CCCCBCLBCCCAAvCBnC1CCCGC dBWC B/CaCCCC>CBBCBhCqC[C_CCBCBCICBCB$C9CC]CDCC ChBdCWCCB+CC\B-CB&C7CjCPBCiCBVCB0AAB?CaCnCmCB@YCCVCCBCCBCsC4B?CCHCBBjCCCCCPCC!CC1CBCB;CClBCCC0BPCBBBUCCCCC)COCCCCC+CBnCsCCHCBHCmCNCC#C2CCCPBBC4CABCBfCCB(CWCDCmCoCBBaC'CmC C CByC]C|BBqCCCCC]CBxCCC.CBCC*CCC@B_CTCCiCBBC8CCCCOCBC@BBCCuCzC%CBiCCmC5C,CCB0@CBCCC?CC2C?CAC5CBmCBdBB\CB(BCCCBSCUCBCB CBC(CC$BACCCABCBCCB0A|BCC`CA6CqCoCCCC1CCB7CC_CcC3CBvCCCCCB0eCCC%CC7C CB@@CBmCCCLCVCBCBC CuCC4BHBCTCBCCBCVCCBBBA_CECCxBgCCCCvCCC2C@@CyCBAcCC-CBC0A@4BfCC6CB BB CCC'CNCBJCxBhhBNCBRCYCCC{CECB"CCCCBBBBCCZCBL$BBxC"CCCB!CC0BBBB1CAC4CBpCJCCBCCB C|CBBBBGCsCPABBCBBHC-CC5CB4BC>CB CBBBICaC@jCBICBBPB C\CBAC(BBCLBBBB*CCBB@CBHCDBBB;CXBCCsCBGCCCCcCCBBBBBCxCB5@CCZC CpABCBCBB`BnCICLCB(C.CCpBhC\C"CB.CABZC|BBC C_CCJCCVCBCClBpB7CBCC@@)CB/CBBCB@BCB[CfCBC0ADBBHCBCJCB$xCBBBvCCCABCCCCBhBCRC-C4BBB2CCTBA`ACiC_CvCBCLBiCEC\CAB4C/CCBtBCuCeCCCBBwCB0A+CTBBHCBBB3CB4CBBB`CBBBBB`ABCCC/CABBBqCCBCBABBBCBUCCBC0ATBBBBlBQCBjC>CC/C8CX0CHC-CCUCB*ChBBBBCBBCJCCuCA$B*ACCA}CBpB@A,BPACBC!CCBBCBBB B C2C7CMCBwCCBCBBbC7CSCBaCBtBB-CBBUCC@A4@4C BdpBTBBXC3CCB(CB@C9CACCBqCB08CCB$ B$CVCB3CBC8CB=CBB\ CjC0CB$BBBBCBAA\BBB:CmC8BBA2CClBCB&CB`CCB@CCB?C'CJC CAD0A!CoCA'C@ABCCAB`A_C!C2CBp#C ChB,BC+CT C\CBB^C B+CPB`BBA$$BAACoCCB@?B%CLBBAB!CBBBXB|BCB4+CxBgCB`CB:C+CC#C0KC@0CC4BCCBHB@CB5C_CdBBAA3CXCCBCBCBABBCCBBBBC|@A ChCCF5CCGCWCB?ppBB6C@BxC#CA+CB@BPBBB`BBBxA-CBBBA7CC2CB CXB(B"C"CCCBB$B CB CFCBBpCCPBBBC;C=C@BCAC CBGCBC=CLC C8BB C CBBYCBBnC@ABC@qCBXC=CBBjCBBvCpBB;CBB(HCPC;CxBCB<B@SCH\CB>C@@BhBQCCCB|B@=CCBpBBiCC>CBLBBBCC(CBA8!CCAlBlBPBDBPAlBB$CC ABCCBBB(ABTCXBBTBBB$BB`C TCBLCCpCCA,bCeCTBpCB`BB^CBCCCTBCLACB!ChBCBtBBBGCLBBCBCB@BBB:CAxB GCCCBCCCICBB@ BBmC\dBAC&C?CCB|BABBBCLB@@B@BBBCBCzCfCBBB`BB0BBxBCCBBZC$CCC$CBB@2CCWCBA, BCsCB`B&CBH"C0BAAACC[CA1CBBBBBCC CBC;CBTBBBBBB BC@AvCJCCCC0ABAAC\CCC/CBBBBB!CB8C\BBCC=CBaCBBBB`NCCCCB(BCBBpBCACUCC@ABBBB8PABBAXBCACCB`CBABBBB`ACCCB*C\BA$CBB C(CACABCNCBpBBBBCBBBCECABlBC]C1CB0<(BPBCCB|B$CPAECECBLBACBBIC"CpABBCBB0lBBCBBB@8BCBpBBACABFCP@CpApCB\BC AB%C3CBCBB;CCB4CBB{C CoCCBBPAQCBBCBCBB C C`A0BBB|B`A7CCCBCCpAYCCC`B`BD@ CMBBoC%CCBXBC4CC"CTB`CCBlCpCB,BB\B@Ap@BGC\BCBB CXPBBCpC CtBBB0BB8BBBBCBrCBC0B<B C0BC=ClBB Cp BBBBBABB[CAxBpA^CBBp`B?CBBAADAABCA C6CB4BP\CCCN)CB?B0CBBCBAABCBB@ADBB CAB`AhBBC7CyC pACIC@DBWCCACCV@BLBCBB0AXBBAXBB/CBABBCBBB(Bs-CCB:CtB^CPBACBBGC AA@AAcCCBBBtBTC4CsC ABABDB BABACBPB(B?CDDB B `AAAB}CB BTB)CB0A6C*CABAB C$CBXBC4B\B|B=CBAClB( CCBB B LBBBB\BACB? $BBECBxPsCC!C\BRCB@At^CCBBC\C(BBBd2CJCBC@@p7C@B`ACBCB BBpB4BBHBB0B BAB4CCBdBHBBP C@BB`@\CBB+\CCC2CAhBKBBB?C9CBB0CBC`CPB@`BBhCB\CCAhBpBBBBABBBBABBBCBpBxBC,BBA5C(CB,bCpBAB$CBCBlB"CB0NBAC@CB`lBqCC0BSCC`AA$ABCB?BC BBAB<WBC0CC@A8B|B+AP@BBB BBDBB|BBBBx`B%CBpPB4BBBB%CBC B`BABB0aCBA,BB?` C2C\CBB48CBBBA@$C$C(B`)CC5CPA5CCBBBFCAB+CABBTBAB\CoCDBAiC+CTBBNC0BBGCpBCB0BtBBAX|BCSC@B ABBACBDBBB0B\BHY@BBCC$AA<BClAtBC0BBBC`BBA5CBBB6H9CaC0TBLB8BBB]CB0BBBBLBASpABCA0AXBBCDB BBB BPACB A7CB CB/C:\BMC\B#CAABpCCBTCC CCpAB4BA0:CBB@lB0B`BBVCBpCBAB1CCDBEACB*ABICtBBBALCBCChBCDB[CCGLBBBCBPBAC6C\CB@,|B`ABHBAB ABBBlBA@BTB@CBCCPB&CC>C$AApABABBxBp C0ACCB8B@BB@,BPBCBBACBBA`BdBCCBAB$CXBBCgCBACBPBBB`CC~BCC CCCC|B C ABBEB@B4CABCABA B CDB%@ ABB@hB4XBBCB@LCCCBkB.CDBBBCCB86C@AAP@BBHB|BO6tBaCABpCCC@@uAB+CC`BDx4B8KCdBBBBCBB@Ad9BC BA CB(CCCPB'C!@B<BCB"tB@BCD@ 5|B(BB CB@BBUCABDB@CC}C0 CtB B`BpATBBVC(C$CP0?BBB5C*CSCaCC,xk8EC`BBCCCADBBA@CBB |BBCB@hBBlBBCCCBHB_C,CAA@CBCBP$Cx\#CCBCl B4BA>0A B9CB@@(BAB@AhB AA!CBAABJCCACCBC2CBBBCxBA80BB@@AA2C.CHBAA BBAu,BBApB$XB!CkB`ABECBXBBBBA&CA@pANCBBXBACB@|BfCCNCABTBBB4`/C9C CBpA6`4BC CB@@BB(BABXB$CBB4C<HBB BCB@DBCTBAwBCB4B@PC?BA0BBBB BB.CSCUCBC`BA CBBC CCH$BBLBAB@;CXB"C@QC"0A@dBB$BpCCACA\BBBBBQBCBC-?CLB@DB C-BdC?dCVC C@AB8BXxC@( XBCB8 AAB$BPB`BBBBC@$BAA`Bp0PC,B#CApBDBBBC4B>AA\BpBBBBbA\hBCB`A4\B{C@BOAB0BCIC X1CAtBB1ABB CKLXBBCC B@@BB0BBBDBABP(B@B&CB B$CBBxB0BhB CCABBBBCCACBx,CBBB`A@@B BAPABAAAC-C}*CALCABBBALCHX3CC0B"CBBBxBBBDBDC`BrB CC@ABBBCLBBBABBC BCHBC\CTA2\BBB,B2CbCpB BCBPB8CPAB0BCCZC4BAXBXBBPBB@@BB<A|BBAHBhBC8CBBXBB?CB<zC C ABBCdBBpBBMHAACXB BCA@L@ABB,5CPBBBA@BBBPBTAPB,B0BBpAAC9CA0B BlC`|BBVC`BBxBB@bBACCPAABA?PBBB B3PA@@@B0CB0AB?@0`BCH BBCBB-CBBP@ 8BA6CC<BA;CB$BDBBBBCABBB,1CB|CHBBCCBLpA@ C5CB CBA6C@CB4(BBBC,p@eAAB 2C+CC/BBBBBB BCBB\qC0BACC C`BlC9ABBCBABC@0CB`APXC CpAB(X `C@BBt HBCC 0(BhBC@ $/BB=CPABpAl@B.CBTBC-CB!CBB9CJCABA@`BCXCALB@BCB@BBL)AxB2C!CC/BC0BBAPA"CBBTBlBsCBpB5 CBPBB"CBHBBpCXB0A;HAAlBBB( BTC)C<@@BBB@C0B BYCBCBA`< BBB?CI@BA+CbCHtBDBCC@ ?xBB|BCB|@AB1ChB>C$BqCABBCBB\BB;B`BA`ACC_CTB C@ABBBBCUCLCB`B3CdBBBB@C@$ C C8BABB|BBBBlBCdBh0BBBA$BPBB?BC0BB0ABBB CCLBCTBBzCC\BBBDB{CPBx@@BCB=HABCBB 4[CeCXCR)CBBAAMCBlB|B<A&C4CBLB <{BC8ABBAL)CB#CBp%LB3CdBdBvCBCBBBBClB)CBAB@@@\BpAAB@BBBB`B#CBCBBfCBB\ BBdCCABt@B*A0CB_ BPBC#: B`A CdBBADC 2CB rC,BBAB@cC0AB4C4CB\BxBcCBBABPAA$BCC@AtBBBH4TC@`BAtB,B CABpAH9+B CDBHBB$BACB8B]PA"CpBBBBBC-C@@`4BCBBCAB@BF B\CBAAB-Cxt AC BCA4D,B4C"C-CABBLBB?B#CB@BBBC@@B&UCBBpB=PBBCA,AB|Bd6L@ CA8BBlCClBB\B(xPB|BdB ACHBxBA.CCBA(B@A 2CB:C:A6PA\BB`ABBxBB`APBABhB(, CC8BBBTBFCB`B<@@BB@0BAA`AC@AAB^C0BTBBB`B'C(DBABBhCC@8$(B42CCCtBAA@pAPAtB-4CB`CB,BBlB7@@p`AA>C$BABBBB`BBBCB B CDBBAB AVBBbC6B CpCBB$BBCCAABB A\PAxB_CBBPBBB0|CdBx@A;CBBB@BBA<BB`BB*C>?&CB@C\BUCCBB0HB@CCB@@B8LC6CChBP,B`BAB$0APA@A/BBBhBBCBA0pICBAABCC?CB,B(BB'CBCB@01CC$ChhBxBAMC4C B C@tB0DYCBDPBAA1CA|B CAetBBBBA@ABBPB`AA+$6C@APAP#B0WCBltdB BbCBpCCzClBBCLBFBxBB BB(CBQCAJpPB+CCC(CBBAB BCBBABxB BBCB_`BC_C)C KBAA(C(CB`BB@h@TB`BA@B?CRp@9ChBAFPA@CB HCABBAP CBABBBBAACC=C0B8BLBACABC@B'C?@PCB*C`B0ABdBCRC#?B0|BB\ Cd&CpABB $AB C3CLC0BBBA.CABBBA B CA:BBzCACCC(xB CBBASCB0HtBABACABEABpH.`BB`L@PcC0CBA6CBBB%B@@`+BBCBB|BB#C@BB#\A+C)CL4LB?Bl*CB%CAAllB"B8h(6C%CBAlCAxBBeDpACCpBBAARC8Ci(C CBC8BB CB3BBBBA ALT6BCBbRCECBBB0ACB,C0AB B9CB,AP5CBABC$ BC%CBKCBBDB>PC BA2CCBBABCTCBdNCCBBBHBB5CB C1CBCBB4CH?lBBAPBBTAC\5BBXCB  BQCpATd0CSCA?CBBBACBp"CB 7'CtBlBABBBB)BRCBAtlCSC BdB`pBHBCBAuCH@@BXCBC B^CBAgCB0AfC`PPBCDBBlB`ChB0C0BPABCAB+CBHCBE4P@@ CB A CB@ A^B BSCuC(BTB|C@&BBCA(@@BAB4BB=CBpABXB|BB@LB,BB&BpBACBpBABBBB BpBHC@eCCDBpCC0 CKC+C(B?BJCAAA`BBCBCAT$$B$B)BBA4B8,CB@A$ABpA@0hDBiCCBAB>C(BBgBBp<ICBBBB@lpB_CA&CBBCBB|B0C(BDHB2CpAPQC$BC,BCp4B CCBAP`C AAB C0CZC``C[C@@\ CBBCH9ptBnCC-CB\ABB BCL,B|B@BBBBD?;CC|ABy`D@0CP4WB:C@tB@PtBP!C@@@BBBE|B hClC8B2CBahBB CB8BBCBx1CCBBBBBc64B4BBB)/ BA=CpBCBAB4B(CB&dBBA\B@ ?C@B`(CA\BB,$BCBD C0,pA BBA?ABBCXZBBBHCSCB@@@ CB@BCHCCAG8BBABBBBB@?xBHBCA"02C,A@B$B8BBB+BABB B,B< C`BC4BlPAxBC%AxB&CDBBNCA@=CD`BA0BBA3@@BCfCX PBB@ABDB6C@d4$BCCxBBB,B0A0CCCf`\|BBtBICAtB@(BCpA%C`B4CC`BBC:CJ AB A@@L@DBAtBBC0B GCNC1CBe,BAxB C(B|B8BPGB A$B CUCB+C?92B@BBACCdfCCABA@BB@C@C@ BA@AA@BpALB CA/CB"HB`BACB`AB\BBB$BC@@AB@BBLB80B|CcCLBXBBTB3C@A@?x QCL@BB4FCpB0$PBJCB*Cpi C!CBhCBB$C\BB@TCBd`ABBCdA8BBPAB AdXBPBA.CBAjC@@pB|BA(AA`MCJC4B@0B@`PBBmCp@AB4C=XhB4B0ABACB4%`BTBFCtCHB$BACC C C BBt TBCTBuCLCZ`00ACDBB\ABB-CB4 B#CBT BBZCBBPxBBBBAEABB|BC@B@]CC0hC@ ?C@BCCC ^A8BB ArC .C3CCnCCBAH@ CCAC0CABNHBCBBBDB@BLB4B@A@BtB:A*CBA BB`BCCBBA2B@=CCBA BdCH@@CBxB0AdA8B,B@@AB4@B? CCB\B\B@`BuC$BBdwC BHdB 4CBaCZCHC$MsBLBA CpABB AB8CALlBObO0A C<4C(CAj4B tBBBB8CXO.CtC3CPBDBB4AB0ApCCBB4BB1BABdCB(BB3CDBB`ABB|XBBA@AWBB@pB@B0LC ABAB\BBBB BBDCBBBBBBB/CAXCC\B|BBB+CB\CHBB(B/CC TB,BpApp|B`@8P@BpBB40BCAB$BX@4BhCBB A BBApB0ALB@`A$BCBBPABOCA#yBVCCCBBCICX`B/CyCB*0A0\BBAHBBBttAAKCMV?QCA?ACBB$rCAA'B|B@ C B_CCB A( CAD@hBBBc`0BB,CC Bw0BdCD @BBBCAC&@@hp8BBB=CNACB(BBF!ABjCBChB.X\GCBBDB\ 5CHBBpnChBCBAAPABC AB@B\CCB(yCC+NpBC2HSCBBpC|AAB%CCBBABABp(BBBA@@pBBB"C(ABCB@ CA8BBCB8B-CBBB rC<4ACB@@ 0AB!BTBC CRCB rCA2D CBXBBB4BBBBBB 5CBAB C"BPtB"CB$BBBdB(B BBPAB Q(BPAhB9X/CC6C"@CBAA@|BB`AB"C]CXBB?0|B$@\BBB)RC"CBBBlBhBB@'!BBC@@AAB\BDB@A C$CxBlBC CBC@CCBTBBPBBB@XB3$BB1CB`BxHBB/B$BBB CB0BBBC(A@BA,BHBA@`ACAxBB@ <)C(CT0BBA|C(CCP~dBBC$@A7CBdBBBn20B)CTBLBhPB+BvCHBCB|\B@BC,B LB`dBtBLA\BACB@02C C PB,PB$A$BBATB@AS8 B$B%CdB0B0B(LB|XBBCBBB C@8B0*Ct!C$BB#BBHCBGV@ CCCH0A AHBPACTBBB(ABB@ABCCIDBBLBB4BBC&@BABAC(Bl\BBB0ABhB@]C@'C CBBAt$BCBBC@tA<;CB+BBADICBA"`ABCpA(&C C8WtACCAOC0BP8BtBB@B6`B@B CBA@AACCB CHBBHBBBBvC"CCB8CBtABACB:0B*C\BAt BBCBABcCBAB$BB BB$BpdBHB"BA8BARB\BBh`ABBAB,BX0BBCBB AB@BRBBCBCBC$BHBBHBpA@0EC4CFC=B@ A AC@B?BB@0CC] <3@BB@B@ C(B C"CTCBAC CA`AC@@ICB@\B,CB` BBBB0AAphBTBdB8CAC%C4?j`B1C@B,BBBBB`B8AxBPAAAB0AAHBAB|BABB`BCB CLB8B@Ad1 C@@BG B BC/BB!C@C DBCXCABAgCBBkCBBdABHBCCCClpCPAiBB3C N B0AtC-@B4BBP!LdBAAA CBBB4o@BPBLB\BdBPBABxB3C-/C`B\CB`CdBJ C@B7CnCLBBABBhJBBB@dtAnBCCTBC0BWC(BBpDBBBC8BB&C@B(CBBpBPdLB@BB&LBCBCXBCC`A@@%] A@LlBBBxAF]rBBC(BBHBBB CA(BBZg CB0CPB@A@APB4C!(BPB9CLC@A=_CCRCBB,BPA@ CBBDCC,B$;C]CpBBCBoCABB BCB`|BCB~CDBCB4C BACCThBCA(FCBxpC*CBAA C@Bj B0B8BBB8B@CdBpBABChB3R{CPCBABt`B-C0ABZCB\B`8BhBA BBCTBBBCxBBAAXBhBxA6CB^C6CAGCCB7B4BABBlc@B@9@B C C C BdB=CC$CABBAA,B \BGCBBXBCB*8BBAPBB@@@@@%B A@@TtBA)CC0BLBB0A0rBpBBBC(BBp@B\BBBC\BAAA|tpAB`AXld;CCrC`BBpBB=CBAJCCB$@HBhC C tBBBA@ABXBA P.CB A`AAAtBBBCBB0B BA1C8BBPAHPAB8BB$C@B B,BB]CBBBX @LB CABB\PAB@#BZCBIBpTBB$C2CCltB@@BPABCA C0DACCBI8B @BBRBBBaL$B`ABBpAJ lBtTBALB 0ACXB LhB$BBB!C8BAB.CTBCC@&|!CxB$A,B0BAABC`=C-0aC @AuBBxCBx)@`BCCtB@8BC|@B0BFBCB\XBDBACB"CC@PCBtBAACXBxCB@AGCABwP CB\B,XB)CBHB$BB0CBCD^ACQ B` CA,B1C0BXB=XdBB`@LAB @ /AB @0,\DBBBABpB7BABA`B`BB,B$BC<6C6CBACXB BL.B`@@@0BZ9CbCsCB-BBBABCDBQC-BLBpBB>BBB`ABCAPCC@x\BBCBDBXpBdLB(CdBA4BCB TCtAB\B `BBB0BB VBAB(BClB@hBHBABxB,(B C3CPAB@@<BPC@84B+C9CpBATBAC@B\LA1CBA@C$CA\ BB4@@B7,B0C6BCA\ABDC C0P`ABA`C|BHB@ACBB@4BLCBBBB`C@pBBBXBBB?hBBABaC$IBB BBClB)HBCAACBxBpBBA@ABB@CB$C0BABOCBlBBBDCHBCAB0;hBpAxBTtBCCA@BBAATlBIC=CCB84?CpB CBA(eCXBvCBABBpACHA8BP@ABB@ABCrCh4B ACC`C@BBhBCALBp:ChBpBB9BHC|BB>C|C@C0B CPB,CABBHxBABCCT6:C$LAB|BBBp\ABBDBBABhBCBPABBCAHAhC0Ajh BABBCB,pp C@B7XCBAC B8B0ALAlBC?GCB.C7C%hBByC`C$CBdBx\BBA,B@ABB0CClBt<ABCBHBT rhCgCCdBLfC?CtB0BABBB_C0ChB4$ A(B@@(AptCfCJCXCA@C%CBDAQCC0`A\BBBCAHBABB,|BmCB3CB1C\BB CdB CCVXdBBA WCpB0BCAtBALBB8BCC@BHCgWtCCCzC`ABDBDBBBBBBACCBBvBPCB CBB(xBBXhBB@C@=CCTBPCBDB4CABBB!CB BBCAC B+CB BCLBBB)C`CB@tBC5CTC@8BBBBCCCB@CC@B@@BBAACBBBdB`BAB@B@BC4BBBlBB@B4\BHB<CB\B0bCBB@ACAPB CA C04B$CDB?ACtB@AxBBAA@@BCC@BB@CCxZC'C@CjBCC ABAXB,ECCd\B)ICA0cC@BBPBCB BBBAC'CP CCTBBA#Cp BLBAh?ABB*CC4t0A=CBBBAgBCAPCBA<YCC?@8B]CBDBNC@OCCCp@@ CC CtBHCC`AB-C8BAB,/CB4A,CpA$BCXBBC,CB5CBBBBB9CCB|B'CiC+CCB\BCBB BP0UBCDCB]lBPYBBBB/ BA$AB CAABBB:C0LCgCA@BA|A@PBH LCB@BGiC`B`A*C?BP@ACd BBA0ZCB+CCACBlBLBP8LBGCLBB`A B8B"BlBBBLBB\CB BCBCCtB|B`ABB@BBB"CBL=|B-C@@ :CB)BECAICHB\IB L4CB1CeC@@BLCCBBABCB=ICBBP6TBABhBAC2C@@tCA/CBB|B8BABB?4ACmCC`BBsCB`ACBABACBCB?BBXBBGCBpAMCA Cxl XB,CBB|BpACB?@B CCCB?CRCp@CBPAXpJC,BBWCAHBBpICuCBABB<hCB Bt0B3@BYCTCBDOH C \BpABASAB0\&50A8BBCC (xBB@ABl CBxh?$@(CABA6CB(BPAB ABB@C@@BAx0B\B0BACABpBBA CA0t BB0BAC`B0CAC3CCBBBLB$B CB`0B@BACLCP4B (AB BB4CBBB`X.CDaCBA|B?CdCBLBBCBC C@BdB$BC@8BCB `wVCBCBBCilB BPA)CATBlC;CB[C#CBCBB@ACAAnC(5DC`AB<BB(B]C@p.CACxBB@AB<@ B`A*@BB BpP:C C0CBC.C@XBC0A"TCBBBBpA)CTBCBCAB8A}C BBBBPA$X@BBP%CbCB1AdB^CP`B B(%!CCBCPB$B]CBBt$ C1CA4BX `B/CA(C@CXC@BBABCBB CC,8BBCBC,C6C7CCB'xCB\BLBdB@BCxCBBBB@C@C0A`d A?CHABBCBA CB\AB2CBBBBB@CxBA@B;CBBD@@B\CBHBPB@AUCBABCB9HBABCA|@ B 8CCABABACABB^$@xpBXABA"CCCBB$BpAsCB0`yCBB7CX[BCClB:CPACXC0BBpBhBBLCBCdBXBBAACB[CCAB B$BB CTBCBBBA1Cp `BUC.CCBBCtB0BBLBTABBCA ALBXCCBAB@(B'@BBBA@BPA' AP$BHBBCTBBB B5C7hBBA0ACC(dTCBA@0uCTB0BBtBBDBBCAABQCCBBdd0(BCCC>B CBBPAd=CCLBBCCBB_hBC1BCXB C@lBB6CBtBAB(Bx-CBBBAC,C BBCBC0 CBB B4HBBB%CBABCCBA5C0Bt5lBCBB]CXXB80C$C@BFC-C\CSBABlBC@BBBB;B=C`BTBBBC5BpA+CBBBBLBAP0ACA`BtCBB'CC@BAB= CBb CAB/C0PA!$BCB'C3C\CPBB'C9AlBABZCC?BBAlBC0BGCBGCBBB BCB0A BB8B$BLCB(@BlCB4BPBDCBBC<B$BXD|BCld8BmC`ABAlBCCB$ABCBBBCALC\BDC(BLp\BACB@BB&`BBdBB`BBB>4PAdBBBCB@BLC!BB\BB@CtBtBCAE@ A BCB8BC@@ BABAABBACCABAUBB%C(BKChBStABBpBBBBBB@&CABlBBATCB$BBB8CCA8CGBCBBbpBBBBACBwBBXC@CBAAHB A_COCCBC'\BdCXBBBAUVC0A,BA d3 BpA6@BXB@BC@pABBA\B\B@`BwCBHb,}CBC|A+CB?HCtAALBCiC|BNBPpB@`)CXDCB5=CpB)CBXBA,vCB CB0B{ BKC`CABB pC\B,B@@B,CBBT Cx@"B sCA|BCACABCLB`BBB,BXB7CHBBDCB=ABB0BCC0CACBBCB<.CBABB0C<$BBtBBtBHBB@^CBzdB;CBOCCAXBBA@B\t8CC BdA"CB BB@>CBS,7B ,$C.C@AJC@P`BpBTBB BGCB\AVC@CAMPBBCCB `PAhBCw8BB7CPCABPFC1CBBWC@BDBKC < CBBvClBAaCBBBBACC,B@CZCBBLlBC$BDBBpAACB)BPC CB,BC C*CBABtBX BABAB BAK@TBB@PAB4B4\P\BABC!xC%C@BBBDB6B}CC/ BhBBCAA(#C,CoCqCBBBC`(C@hBCBx#CCC0`CAABAAA[$C;C\BB$BC0@VCBA < ^C/CBBTBYCBB,B5CB4BBTB@BJCBA!CB\B4CDBC;CT0PABBB0A@PBCBpCC&AApA$C7CB C,xBA|B0XdABpB0B[CA BCBxBT ABtBtABCCAAIpB(BCTCpBCA0B tB|BB8KQBB:CC0C 8AAAFC[C|B aSCChLBB@ABqCCCBAAPBCBCBKCB5BBBBoC@C2Cl.BpBBAC]CBB \8C{CASCHBK'C0CTBSCBA0BACMCR%@@BBhCBB\B@BB dB`A$CCHpB! C`B)CXBABBCBB,B@PBBB BA =LB&C@BBJCCCHCD"C BXC BSCXB BHdB8CX$\APBBCBXB)CB0AB'PCB[BBBBl8BB\CB4@C(B C@AhlbCA1CCp|ARBZC!0BBQChCABBl4BACCdC@C"<A|B[CXhB B? CABWCB=BB)CAO9ECTBXCA\/CB*DC4B}CApBPA:CXBAxB=\A8BCuChCABBpB A0AC,BCBPCBA@A(gP-C@B@@ALB8BAB@C7CBABABC@ICB[+CCpByCxBCpBAJCdBPABlCTB?CABBBB@AA7C$B|BCB AMCBBCBLBBC CA2CXTBBABBCBBA@CB@*CC#AACdChPA%CCApBBB|B@@xCBBPBBAlBBCABCPC`B{CoCAiC4< CpBBCAbC|B@TB'CCBCAu@BlB0ABHCPBiCB2C}C(B,CCB@A&CPBBBBBBAs 0ABCCBC@LBB$CB`AB%khBCB1C0A*BC|BBdBC$B)CWCLBB\B@CtBpBpBMCBBB"CBpAB6C=CtCBC@B0ACCBTABtB'CB,BB@AC ABBB[CB4xBBB1CCA0ACxBB0`BA$CB,A0B\BB0hBBCCA5C$BDB00B|BABjC|CABB0A=CBLBCp@BAEC0@A\B$B,pB!C4BBBUAl& BBJACBAAAA BBCBAB,AB0<AC$ABlBCpBBCBBpAC0AB|BB|B3CB%CMvC\BHBACBACmBBAB;C >CB$ATCTC4BhApB4BBB`BB@zC(0B<BCB BB CB(BB C1CBB#C1C0BAC C?TCBC CCBB,C@@pB"AA"CBCC0C'CB)CBBBPBACB@=CBB?@B8A'CBKCPC A ABBBB0A.CBBC3CA?PC`ABlB<5CBPBBtBBB)CDB4BBC<`BBCCBUCABCHB =\BAPABBBCICABcBB ABAB#BhBBCC+ CC,GB$BvCRACBBB6CA lABAC|X@@BBB@@BB@AA?1TCDCAAAB(BCApUCeCA4lBpB@AxBBACBwxB@BAB B B1iCpAx>CdCB(xCA@AVC@AB^@BLB?CB/BBA $CClBAB!CPAABC(BdBB@BBpBlB'CLB@B4C7CABABBBABCBbC%%CCA AtBBAABBBBDB$B^CB@ABB (BAI$B`ACB0BtBB P`BBpAxBB<HB A CB@ CADBCBBACBBABA4B!BBtBB@@BBtBB+CBBHBB=CChCA0CAPBLB+CXtA@BB0vCCBAp@B?"$CBXB@BB@8B0AMCCB(COC4%CB-C5CCBCABMC4C)CAhBBB4B?l1CC@hPBBBBl\CBSCAC@)BCpBBA8uC8OCB ,BpARBBTB@pBB@BACCpAB=BBB@tBACg CFCBjCAAA@HBC CB`rC2C`A` /CBa C@@+/pBAB8(C(BBBlBB8 CBdBBC4aCB(A0AlB ABMCTBBAB4BB?\BxCA4(B|0CBH4B7CtB@\BvCB CTBBBABCoCAACAA@BBAhBA@B6CB?CB`<C~C`TBBB@ABCCCC,BHB CBBCBC|BBA+BC`CpBAP=CA4B@ABBhBBBr (BBC`T\BBLB CBHBt|CABBC@BB2CAB4BBAB C@-CBH+C|B\BBECABACB BXB,<AC ADB@B@BBCBB(CtBBhBBcC@@l5C@ B8CHtCAlB"C]CBAB#CC4C4B AC,BkCC4A?C?CCBBBBB@CBB1CDBLBC/CxAHCCp%B,C0@ BBC@@BBYVCsCAHB@5C`AC dpB?CBgCB@CCBBBB>`ACC|BAT`YCCBB4SCC C,C`uB6CC@PBB@"B@B@CBCPBtBABB@tBBbCCBCBH`BB(BPBACTxCC 8@BFCBBRB4AB \B@@BxBdB$BdA|@BCBA1CxxBHC0BBCT(C`C\B@BB@c#CB@AB CC CBDBfuCCCDB0ACCBB C4C,C CDC C\`AB@dBPACBDB0B(BC CBPClB%B@@BBA@\B|BBBxBC(B`AA ChC CB2&B4B%BBBC C< DACDC`@8B@BBCCAA0BBAgC C/PAAHBCdB@dBBB\B 4C@ABB(Ct@BBlBB@AWCBBhACBBDC@d@ BCAL1CCDB0ABBLB8C(CpBBA$BB`( BBp>A8B@&C@ABBB$@$BmCABDB0APp0CiC;CB-CCB9`B B'CeCB0AADBBFCRC.C@BBB BBzCBA$BBBB3C@pTC BB B C BBBA,BCBPAC B CB*CB;BC64CyC1CCB$B B@@dBBBCXB"C BqtB(CCCTBZ`@@BB ABBCCBTBP<BB@BMCCACECA4BeC`BpABB1CBBAB0\C"BlBC6B@Bhh|BPBBAp0AC;CXBBA<BBBH|dCPCOCB@@AtBCACl!CBdC@@B(BBCCC(B2CLC\Bl@@BBBPWC!CC(LA8BAYChB`CHCAAnCkCBACCh@(B`ABpCA/CCBACKCChBBBpA'CBVBB+C/CC C'CC ABC0A CBP CBBBB\BPP?lB8B4CBB$C|T`B(C(CdC C$B-CCBCCAHBC$`AAB@CL@HC@BdBABTBBA%WCOCZCN`Ax@ CBpCC(A?CC@AB@@B@AXBhC]COCB tB(BdB0ABABB,8BpBA!LAOCCC@`aC6C_CC@ BBRTB C-CAxBBMCBC%BBCPCB dBHCBBA BABCA0A\BHB CL0B?CC/CB CPBFC5CCCCBBBBFB0BBBPACBAA AhBhBABLB\BB`@@"CpACAXC2CPBC@gCpBdBCA A"CAB BXB9CB?CAOC.BLBCCpABP` AB*CBq )CBDB,B@AACGCB+$CBCAC@@@UCOCB&0pAC B0BB4BC0BPBBC@uC,BB \hBBCBCBPBB$CBdB4B'CBBBC*ABCSC`C8UC'BB+ACC %CA[CBB@ABB$BB7CApA@@:CB`B@B%CBLBBCCU4BTBADCBJ@Df8C0ABBXB8CTC`ABCPB TRCAHBX4CBBA#CB@B\BB BCC(CBhB0B,CDACC`BA+CABpCCCC$ #CBBBB6CBxBHB!C2C.C CPAA CB B CB0BAACBBcCA A CBBBBBtBBRC'C8BtBdBA3Lp|BB,8BPCCB\BTB$ BC0ALB(B@B8A`A@A CA,tCC@@4BBC B\BBB1 A BMCCBAyChB;CHBlB<BBhCB(BA,C`BuC$B]lBCp;C ABAP5CP !CBBAC@=C@ACBA0BBCBBBDC`ACLlBBCAB';CMC CBlB)CBBBDCCBICAB0ADBCWCBBPAAApBXBBCBBC ChBBpCCCLC0AA@8ABC C A%CpBB@SBCBB#C,CJB4 CBzCCA8A7,gCB!CBd4+BC EC-CBBfCBB@A C CB(CCpAXBB7CB BlBBSC8$CB5C'CPB3C&ChCdCBBdC BL_0xBB\BCAA2<@ BB AAA BCx+B%CxBBCHB |ABA|BB)CLBEC\B@BkCDBNCxB@BBC CCCFCBvBACqCA<qCBBBBA1CBdCABA(lCPBCCAt$BCB?BKCBaCHBABB@p@ACKC ACA\C CaPltCC\BpBABAeA;CCB BXPBBB[C>C .@@B B2CCaC(BC0BB|CB@0BBPA0B@A CBBvCBA SJBgC@C*CAB@@CpsCtBCBC`A4 }CCBBo?4BCB^CBB-BB@B%C(B@AB8BBB9CA |BHC,BBECB(B3BB'C @BCA BBB`BBH.C*CBHB=CBABlBhpABAABBBCA`BB@BBB$BSBQC0B)CBBBBA8BCCA@oBWCBH|BABgCBBAB`B-CBfCBBB0BhBCBCWCB4|BByC BRCCBBB|CXBAXBu:CBHVCAC CKC0CCDCDBBA@B(B0BBBCBAB ABA@lB@?CPBBB4BB@CP`BGhBAPAAY#BRCAlBHCBHC)CDLBC$ BBABAABHBnABA TB8@BBB0f(C ABTBABAxB,C0BB@408CB|B@pA+CB C`ABt0A$CBBlBBeC4C BCA BBBBBBU+CCBCACt~0B CwBB7CBDC;BCdB3chC4BXBpBiCCB@HACDBBACBBC|(`GCCLB8B@BB@BXB@@PBB@AB C$B BCBA@"BBBFC;vCBCCSCP0<BdBTCPB>tB,C1C8BpBB4BBCZCB$A CABBp!(eCC$BHBBjCB0BAtB,BA`?C8CBA8BCXB0o7CFCACB@llBAH@BC"B@qC5C,BHCB&CCABxBqCAPAVCtBrHCB0AB@,C8BBB0B@B`BCB \@CBBB(;C BCBCBBBBB48BBhBBVC ?PCBCY#CBdBlC:C BBtBBBIC@ACDB,BpCABCB B pkCC CBCC4CCCHBAnPAqCBB,AC4BBBB BTMA BEAPA@0BAC.C0_CDlBC@BB?!CCtpA6C CBCBBAC[BBXCB4 CCAB@PBB(B%C A-CBE.CBpAC=BAACB`ABB BCCAABBB/CAoC$BBBB6A!C BXB:CCB?@ BGCxBBAABBB`=C@BBBC CBCAW]{CCAB| CCXCNCCE\BBABtBwCCAB0CBPA@BC AB,BLB A|dBA~C~CBBaC*CB8BBPAA@BBBBABBAB,B CB,@BBA BBBBBCA$BB8C@@C8BB CB7CABBHBBB?, CI>CBB#@A|BPAA CB:B.CBBCB C<0CBBA^C @A=CAtBB BA0 BBABB/@BB( CBXBxC:ChBA CBBhhBACB B'B ? =CNC@BU@@CBBZC-lB%CBCBB3CAHAlC=C(8B"CBLBB+CBCPCB@0xrCCtBA1BBBCpBB C@BAC C7hB8B_CpBCBBLC B@A*CAnCPA4@B BBABBBBAjCdBBBUC,CnCA'pBB@pC@pCACA@@7CXBNCXBC$C 2B BxCBG!B CRCT[ECC(rCLC2CzCB B BBBCCxC @A@B4$CCC`B:C&C@BCMC?LCBklB|BwBAoC: BWCB CBB`A,`AB@AxXBQC@|BBCACBBBB-@CBHCG@B0C$BxB$BsCB8LBBCBHBxApBCCABAABICUVC`BBBB 'mCAC4BCYCBBASC"C*CpAvC@_GC?CBHBA$BbCp0ACtB BtCB@BBpABAxBYCB`ACCAALC@AAB`BBBLB@L?C,@BCBCxBB@$BCBB:PACB@@C BOCCC@BB4CAAC CBB CB CPB@AB0BA(C@CB$CAC#CtBAT?C-C08BB@$BB@C3CB B[CBADC`B(BA@BLBGCAWBABWCGC CBBC@BBB>CBBCOCB38`CYCBCAB@FCBAB@P<0AtBTg@@WB$B9CCd@BB~C9ClBCB:TCC(CB*@CBBBBC6C@0,>C B4BBBATBM0 C BmChBAB'B`4BBdBB@A1CBDCCA|BC4C@A@@CxBBBAA A%C4CBVCCCABjC8BBB7CtBh{CiC$BCBBBpAyCBA?BBCCACBP@]$B0AxA@BA$PBBAB0B 0BAC`B<@CCBYCBBA CUCxCC0ArGdBCC0B6C`CBdA?CRCC4B B~CB6ClBA3CB BpBAdB0@8BPCLpAX,BBA}CBCBCB0BjC\BRCAUBdBCDC?BCBBBdABAB&C@ABPtBB@AZCsC1B$BBC>C`B*CC$ABB.CABBdBBB@BBBVCA BB)CdB' CB CCC4BA?C4xBBCA*CBJ&CBX@BB4C(BCC?B`BB0_C_CBPA/CC0A4BBBxBA,C@0CPBXB8ApCB<+C[CB CdBACAB;$BAAhC B.C"C@xpBCCBCA|BAOC CA5CBBxBABZC BG@(dC BCABB:CXBB:CBB;BBBCBAbCBlB0CBBB0aBB STBC'C|`CCBBB$B(CCChB$CAB4B@BZA@CUC+CBB BBACCEDBCCpXBC|B$BB AB0BB@@C0AAAbC*CfBA|B=CBBBZCCA!CBGCB?BBDC C,BAPAA4BBAB(BnCBCX7CA7tB@,CBBC4CiCBBxBECD AC0A|B8BBB8BB,BB>AB\dBAdB,BBCBB@hB(B)C BLBpAC BdB BCTB:CBPtCBB`BPBLCTXBCAC A CB@A8BBBC@BpA3C!ABBBCBlCCdBBAlBCBBpACC@BlBAQCBDCPAbALC@Ap@CBXCuCBB'B&CnBB&CAB C#CCBBB$CBCBBBBBCADBHBBBB BCBBCBBBCADCAC(BB5CBHB CBA BAB&C CT0BC0HC0A&Cp`oCBBBBBC\BHB BAB>CA.C@B CBABCB>ABB@CPB$Bp7BDBACHCCBCACB|BdBC@B B-CBPBBCCBBC/CB\BB0BCBB\D`B`B%@ABA6C5ChBd ABCACC C(BdCC`AA d@ CTBC2CCDBCB5C$AATBBBtB?pBCBAB)CBYCB&B CAdBACBABAxBCB(t\C?CBBp B C@]CWCB0BZCdB@2CHCB0AxB2CX`AA\BB@AICBAC@BlCABMCCPA +CCBCBAdBCB@C`ACBDB)CBLBC!CC:C@CC)C"CBCBCChBUChCvAAp\C@ByC9C@@ABCBBHBB&CABDCBTBCBBBAC0ACpA\BBaCC CBABcCCC=C|CACTCBCTBCBBDB CB@0ABCsC`C/C`ABpBBBAB$C /CdB"CdB`BCC{CgCCqCLHAC3C'CoCBB$GtCBBpABCBlBhBcCXBCAPA_CBDC8CTBmCBYCC,C@AtC#CA#Ct>PCiC#CCBFB?bC(CA4BCpBmCBC|C BCAJYCCwCA@nCB@BACB1C\BA@BBBB?ABAAB(BC BtBBCBCBxBdC*CAABABB@pB~CCx@BCBlB"CAAHBtCB<B?CBAp@JACB@ABBAdACBCoCB?B8CBTTBAlBBBJC?0A#C\BXBB\BB BHBB(BsCAUBACX C BBCB$BBCB#CABTC&CAB C/C0Bp@3BCaCB$CAB$BCBBYCAECAAbCBGCLCBNCB|C@BBBECAd3CBBAB=wCC0BCh@]CC'C\BAlB B#C@,$CBLBjTCBBB/CBuC`ABBBBBLXB,CBCCBBCBBBCPBh CBBzCCBBtB|CPWCsCB C0B/CCJCB1CC CWCCCCHBB`ACCC CC6CRCB8C@AB;CYCTBB`AB:C0AICAdBA=CnCA(0BBABtBA_BB#C,B@lCAC CLB B#CACBpB0A!C8BCC0AH/CCC@ABCHC6C7CdRCX7C"C6C\B@@-C!CB@ABB$BB@B(C4B8BBA{C`ABBCTBA,0B$CCBACPCBBCLCB~C8tBCnC*C4BCCBCACHCC_C cCBCACECBB CBXBpB8BCC8CA`BACC$BBCCTC@BCACCBBBC(CCB7CABuCA^CC@BBB}CvCBB.C\BECIC.C|B`A)C$TBCQCBB[CcCwCAC"CDCxCCBDCBBCBBFCB@BtBBLC9CRCCBKCC>CJCBBChBCC:CiCtBBBPp@B,BICC^ClCBBCBChCBCBaCLB CC0CB|BBlBC BPCSCPB\BCBBBCBB@ B@@B BA(BBBBC|ECAC<@$BBAB_BVCBCBA@DC`B?B"CPAc@R`ARCVCBBBABPpCB@CCB|4BXBBWC|B8BBwCl@ICBB BCBCHB B BAOC@TB*CC4C0B\8BC@B?CCBB@ B0CiCB}CC@B)C@B)tB>C$X@PCBS CBBX^CCC@ACC?BLpXBC+ BlCCpAACB!e`CCB1C8CZCC)T@4BC"BB,B lBCB`0CpBCjCCpB@B EC[C@B>CC^C(CHB CBsQC|BChC@@PXBCCB@ABA/ 8CBC7CLLXCtPCABA"CoCB<BB,BC C,PsCBCB APA6C"CCBCB9CtBBiCBBLB/ChCC{CB0BBBXBCBB\B$BB CABCA8CDBBgCB9$BC4CA*C`ABDBhB CChBA _CdBdCBTCABHBCCCxBBBiCC|B?CBALCpBoCTBj!Ch@.CBBDBwCBBBB@@\%CDCGC\C0BC%C!CtBBLCC(B;CAXBBBC"C$BBHBUC CB.CB@CSCYC CBA$CCCBCBBEC"CC~C C8BCCC CCBCCByCC8BhBBBXCXBqC C>CwCkClBBCGCC CCCB;CCBfC+ClCCtjCZCHCCNC`CClBCCAByCtCUCoCABoCBCCC@C BB=C|CDCYCIC@@CiCCC*C@;CCDBKCCBCfCdCCB3CCAACBCjCSCmCB3CBBA ClCCACB)CBClBBkCB&CCBpBYCBDBo$BCLB$BB (x*CHBBCB A #C BlBPB-C' A,BBBLBAAPB@$DBB@BBBB@TBJpAC@pBB BBC$BB CBPAB6C`BApCCCBCC,B1CTB1C0^CpCBBBA|BA7CB@ALCCxBnA|BXC-CtBAbCfCNBPA,BCB@$WCB`BtBBB@dBBLBB Bt@^CwCBBA B!CXBC0AjBBB!CPC|p`8ZCB@AHB B@BBBBBUCBA` A\B@B2BnC CA|BxBC>C0 B B4CCBhACBF BC BzCxBBC' BC@B0BC ?GCABC CCBCnC+CB/CMCAxCCAaC(BBsCCBBC9C$C0B0CDB CCCgCC_C7CCCCCBCCBCB@CDC4CCBABCCCFC@CCCnCBA1CCCCtCB1CBdB"C4CLBCQCUCCC[CZC|C*ChCC]C5C@^CCCBCRC`BCB0CCaCCFC&CCCB`CBBCCBmCtCCC CBCC;CjCJCsCCCCBGCCCC(CCC]CC5CCCCCCFCCC[C}CNCBCCCC CDBECCcCCCgCCBBCCCCCCCBdCC0BBB CBBB'C@BBCB^LB!CPBXCB|0BCBBBB BB@C0C<TB<C7AABBCACCdP#CCBBACABC@ CAPB$rCC@AB@9CKCA*CKCB| C=CBBB@BBCLBXBCABpBCBZ@CCC$0CCBCB(BBBCCC A C+CBCANCcCxBBDB CBaC,lBxTCB4B(BCAPBdC-C2CC5C CBaCC4B0B(CpB2CdBCB'CBClC+CB$CwC9C4BBBeC{CC<&C5C CCCXBB1CBB@ABBBC0AB4BA%C*CxBABBBPB@BBB CCBBB-C`BpBTBDCjC CB BBBBBC$B<BRCHCC!CfCB+CwC PBCBCJCABDA BXBC>CPB(CB?qCBBZCtC?CBBC#C2CNCCJC CTBBdCVCBLCCB,COCBBBCyC`,B@QCSCB7C*ChBBgC{CBC}C|B#CC/CBC,CBCCCB CBB.CHBPCqCBBCCBBBC8C&C@@BCFCC?\BCA?CCYCCLCBABCsCfCQCBCCCGC9CCCNCBRCCCB'CCABBCBdCCBhCpBC~C*CAC0P|CB.CCICrCCC+CCBCNCBB CBCxCBBACoCC@2CCECBHBB7C -CBDBCxP CC)CBBADC2CBBClB%CPCCCCHDjCCKCC:C|CCBAD+C6CBA AASCcC C?CB lBBCCACCMCBOCTB5CChBB?CNCCCTBCCBCBC"CCCBBCBCYCPAB0BB.C~CJCCBTCCCUCqCC*CB$BCC0CCB(BjCBCCBC|BBXB@3C(C CCTC@{CB0CCC`CB4B#CrC:CyC\CBCvCACCC[CCCAHBA\BCCC8CCCANCC}CCCBQCBAC7CBdC/CSCCCBCkCdBCACCCCBC{CB{CyCCCC.CB`CGCdCCBCCJCCCBCfCaCCCoCC|COC9CCRCCDCCBBCCCDCtCCCCCCCCCCCCCCDCCCCCCCCCCCbCC@"D DgCBC.CCDB-CC?C@ D|CCCCCCSC-CCCBCCC DCCCCnCCZCCCCCBOCCCC$C CCCCCCCCuCCCpCCCCCCCCCCCCVCCCCCCCCDC\CCDtCCC4CCCCCCBCCCCnCCCC%CCCaCCCCCCC@DCAbCDCCBBCCHCCCCCDCCCCCCRCCDCCCCCC~CCCnCDCCCCCCCyCCCuCCCjCCCC DCCCCCCCNCCCCCCCCCCCCCCCC7DDCCCCCDCCCC@DDCDCCCCCDCNCCCCCCCDCCCCCCDC@ D@-DCCCCC@DDDDyCCD@ DD$D@DCC D*DCC@DDC@ DCCC@!DCCCC D DCCCCD D@D@,DDCCCBCACBClm BBBA@[BCBAB4uC6C#BBBCABAAC\CCBBpACBB lBBBCC6tB}CRCdB,BBBCcCkC.AtDB0C C2CBC7C ABB.CCKCxBB@CBHBC`BLC iCB)CXBPBB0AdACBB CBCCBlBBCB$CC3CC$BBYCCCC%uC2CBB!CC@AB(CACMCBCCABC[C@?CCCBBC(BBBLC CCCHB$BBLC CBBuC0CtCVCApCvCCC`CCFCNCACxCBCRC-CCACCB&CBCCBCvCBCABCCA@CC=CC5C/CC,C C*C|C#CCC`CuCCCC=CB8CkCSCeCQCCC!CBCwCwCxCBC_CBCmCTCCPCCC{C BOCC;CCCKCCCKCCCBCBC(CCCCbC'CP|BC]CCC{CCCBCCZC\CB CCC!CSCCCCCCCCICCCCCCCCBCCCCC8CCFCCC+C CCCCDCCCC/CCDCCCBuCCCDCCDCCCDhCCCCC$DCCCC@DDCDCC7DCCCCCCyCpC@+DDC DCCCCeCC@DCDDCCCCCCC@ DCCC2DCCCCCCCCCC#DCCCCCCD|CDDD DC;CCCaCcCCzCCCCCCBCCCCDCCCCC@DCDCCCCCCCCC@DCDC`CCCC@D@DCCCCC@,DCCCLCCCC&DDpCCCCCC}CCC*CCD DDCCDCCCCCDCC DCNCCCCDCCC@D@D5DCC@ DDC,DDCCCCC@#D6C:DDwC%DCCCCCD D@ DDCCC DC#DCCCCC(D'DC.DCCCCCC@DCCDC D@DCRD*DC DD@D1D@DCC DC@DDD(DCDD@5DCDDCD@DCD@DCD6DC$D'DCDDDDC@D@@DADCCDDPDZD@DCDC@ND@TD@(DDD,DCCD,DAD&D D@6D=D@%D7D@D DFDDD@DDC@ DC@D:C+C/BCBCBBClB_BCBXCBxCCBBBLCxC ACA BACdB+CPAtTCC B# CxBBA8cBtCHBC C@CPCBCCCwCB NC0@@C CGCChBCC0BtCBBC C.CC@B:CCC@DB2CPC>CZC}CWCCCCoCBLBCeCCB~CCCQC`C5C0CBVCCCA$CCCBCCCCpCBCNCC&CxC\CC|CAeC C@CICHBCC BCCBCCAC4CSCCICBCBCCCXBCtCC5CRC9C=CCCBTCC@CSCCCB@CC CCVCBCCCCCYCCCjCiCBCCCCCoC@CCxCCCCB@CCCCSCDCCDCLCCDCCC]CCCCCCCCCXCDCCCCCCCCCCCC@!DCCC]CICCzC DDCCClC@ DDCDD[CDCC7DDCDCC@DCCC@DCCCC.DDCDDCDDD@4DDCCCCD@;DD DDC#D@D DDDC9DCCDDC@DDCC@:D@D@-DDDCCCDDDD%D9DDBDC*DDC'DDCDC@DCDC@ DDD#DCC@D@ DCC@ DCD DC+D@)DCCDCD DDC DCCCCD DCC@DCCDC@D)DD@?D@DCD@ DDD3DDDC@D@%D@BDC"DDCCDC@$D DCD,DDDDC@DCCDFD-D@DCCDIDDCC DFD D@DDD DD"DC/DCCD=D@DD@DCDDDCD/D D@*D@DD@ D5DC@)D@ D DKD@DC@D"DCTD@DC@D+D2D=D@D D0DD$D@DD/D@D@DC0D@ID5D@ADDCD1D)DcDoD@DDCC@VD@'D@D@MD@SD@D"D-DCDUD@DCLD@LD@,D`D>D"DYD1DC@3DXDDJD@D@D9DDD>DWD(D'D@ DCD%D@TD@JD9D6D;D3DND@KDC=DKD@ID/D5DDCdBICCiCC!CB|C\CCCCCCCCC CCpBCCCCLCaCBSCZCICGCBLC[CSCDdCaCCBCCCCCCVC@DBBOCCBCCCCCBCCCCjC{CCCCCPC@BwCCC6CCCCC$DCNCCECCDCCC}CCCCCCCDCBCCCDCBCCVCD@DCCC CDCCaC?CCCCCCCqCC@ DCDCCDCCCCCCD@CDDCCCCCCCDCyC@DCCCCDC DCDDCC@#DDCDDCCCC$DCC D@DC@ D2DCD@.DDKDDQC DCDDCC(D@D4D@D-DDND!DCD@EDC/D@&DD@0D"DCOD>DDD7DCTDFD@"DPDBD@D D3D@DHD[D9DD@/D@DND^D3DD=DC3DXD@"DD@(D7D@\D:D@ D*D@HDDD/DDC@DD:DTDDD@MDDD!DD@*D6D6D@;DD@DxD@nD.D"DCC@WDSDFD@DDCJD&DD@6D2D2DD/DD>D@D@D1D7D6DD@!D@D@aD@DDCDMD@>D*DC@DCxBBC>CBVCBBCCCCxNCBACBCBwCB ]CC-CB CjCPB CCtBAC\BICBB?L4BB@ACQCCtB$ClBCC CBB00ABB\C CB.CCCBCC|BCBCBCB?CDCC?CECBKCBB=CkCdCBeCCCBCCBBrC@@TC#CBCC)CCCoCBCbCBCCCCCFCCBCC CC CgCCfC@CnCCCCCCfCCQC CCCBCCCCCDCCCBBCBCCBC.C0C4CC&CCCSC}CRCBCBxCCCCzCCCC)C&CCCCCC.CC_CACaC4BYCxCCC:CCCCCCCBrCCCCCLCCC^CCC-CCCCCCBCRCCCCCCCeCCC;CCCC+CCCCBC[CCCCC[CCCCDCCCCCCCCCCCCCCCCCCCWCDCCoCCCCC+CuCCCCCCCDCCCCDCCCCCCCCCC\C@DDCCCCD DCCDCCCC@ DCCC@DCCC@D DCC@DCCCCCD@DCD(DCCD@D$D/DCCCCD@2DC$D@6DC DLD@DDDC!DEDC*D@SDD D@DD@SD1D DED9DDIDDD3D"D5D@GD+D@CDBDCDDDaDaDDaD@4DD1D@-DLDVDDZD@MDD@HDWDD@hD@RDfDcDMDGD@ZD@\DNDVD6D`D@RDD]DiDD8DmDJD@?DmDpDcD DDCDOD@iDrD DgD@HDDpDZD[D@GD;D`DSDtDDvD@SDwD@LD@DjDVD_D@uDD@xD@hDoD+D[DwD]D@ID@}DLDvD@sDKD@DDQDBD@D6D@iDZD_D@fDfDuDRDYDCD_DaD@#D{DPD@aD@hDtD@dDD@DD)DiD DDdD@D^DIDSDpDEDFD@RD@pDIDeDjDiD@D D@RD@zDFD[DDDrDlDMD9DDD@[D`DTD@HD_DtDqDyDXD@VDDWD>DmDVDdD@sD@jDCDVDXDGD@DaD3D3DvD[D@ODxDUD|D@aDIDwDnDpD|DD=DLDLDCD@sDD@MDwDsD=DD`D9DD`DnDDDiD@yD@D@{D`D DDDcDxDD`D$D@D@wDoDDDiD D_DoD DD DkDqDxDD@tD@DvDDeDD@D@lDnDDjDvDDeDDDDDDDDD|D|D@D D@DD@D DDtD DD@DD DuDpDDD DDRD DDD DD~DD DDDDbD D@DDDDD DD DDD|DDDDDD DDDD@DDDDDD D D DD`DD@DD@uDDDDDD`DDrD8D`C$CC2CVC CBoCCA;CB@ACCBBCCBBBtBCBCBQC@,BCCB CPCCBB_C(xBCCC BEC"CABB|BCpCBB8NCoCBACBBB:CCSCBCCCBBoCB`AfC C@@,BB,BNCDCCC<BCAAp;CC|CB#CnCApB]CACCB%CBBCBB]CjCKCdB(BJC}CC@@BDC^CBTCpAA CB2CDC2CC@'CCB&C0BCAoCCBtBCJCCCHClBB`BB~C'CA@@wC)CBBBCC@CBCBC@,B*CBC.CBBBTBCCt7CB@BoC"CBCCC(C,CBCCBBC@BCC\AC$CCCABBjC!CCCC|BCbC/C CBBCCCCC\B=C$BCQCbCC=C4C>CCCC8CB C_C"C4BOCCB4CCBC8CCCCCBBCCUC{CkCMCiCmCCC%CC*CBpCCyC:CUCBgCCCCCAC7CC CBCtCBLCuCCChCBCpCdCCC CbCCBjCCCCCBCCCCeCBCBBCC>CCpCCCCZC[CnCCCC`CBCCCC*CCCiCqCCBXCGC\CC0CBXCC?CDCC'CCBCCC6CCuCCCCCzCUCCCCCCBCCCCCCCCC.CCCCC0CBCCCCCsCCC*CCCCCCBCCCCC1C@D%CxBCDsCCCbCD~C!CCCCCCBCC@CCCCCWC\CC@DCCCNCCCCCCCC$DC DCCDDCCCiCCCCCCCCCCDCaCCCCCCCCCCD DCDCCCCCCCCDCkCCCCDCpCCDCCCC@ DCC1DCCCCC@D#DC'DCCCCCD@$D D@ DCCC@DCD DC D DCCCCCCCHDDC.DCCCDDCCC@*D D D@,D@DC D@#DC1D@DCDKD+DDCC@D7DD6DDCD3D@D5DD#D=DCDD@;DCDHD;D@4DD.D?D7DDD@%DDcDnDMD0D&DDMD*DDiD[D@?D@jDJD1DHDADSDWDkD@=DYDWD&DcDrD@DED4D5DD`D3D_DkDRDlD7D D@\DeDUD@DD@=DDJDOD D D@aD`D@iDRD`DD@xD@{D DyD D@DqDDDkDDD`DD@pDDD`DYDD@DD D`DDD@DD@D@DjDD@DD`DD~D DD@nDDDDDD`DD@DvDDDxDD D DD D`DDDDDDDDD@DDDDDDDDDD`D DD@D DxDDDDD@DD DD`D@DD@hDD`D@DDD|DD`DD`DDD`D DDDD|D DD D`D`DDD@DDD DrDDDD D@DD DDD`D`DD`D DDDD D D@D|DDD`DDDDDD DDDDDDDD`D@D@DDD`D`D D@D@DD@DDD@DD DDD DDD@DD DDDDDDD@DD@D DD`DDD@DDD`DD`DDD`D@D`DDD`D D`DDDDDD`D`D DDD`DD DDD`DD@DDDDDDDD@DD DD D D DDD`DDDD`D`DD DDDD@DD@D`DDDDD@DDD@D`DD@DDDDD DDDD`D`DD DD D@DDDDDDDDDDD`D@DD`D`D`D@DDDDD@D`DD:DCC\B?C2CAC$BB=ChBBCBBDC\CCA$BABB(CWC0C$BB$CCCTCCB CCfCCAgC@BACCC-CC@A3C\C>CCBAC{C#CCCCB CCCC-CBBCsClCB C"CCCXBBpBNCPC6CB1CCBZC/CCC4CA@CRCrC_C,BCCZCCCBCBCBCB]C%CBBBBCCFC~CTBzCvCBCTBBCC*CCCmCCKCB=CwCBB^CBChBBeC,CCpCdCC-CCrCACCsCB CCCC`BQCCBVCKCKCCWCC%C1CCCBiCtCCjCC2C2C1CtB4CCCC@CxKCB BCC@dCCCQCB;CCCrCCB:CCtCCzChBCyC&C.C&CC&CCCCuCCBWC CpB@ BCCBCB4BCVC B"CCCeCCCC#CBCC"C8CCBBCCCCCsCBHCCCoC5CCCDCsCCBuCCBCC/CC'CCCCBUCCPC C CCgCCC$CC~CCCCNCdBCCC)CC#C)CCCfCCICBCCCClCC"DCOCQCCCCCCCCCCCaCCCCCYCpCDwCC8CECCCCCC8CCCDBJCCBCCGC1CCCCDiCCxCCCDCCCCCDCCC)C DCCCCSCCCCD@DCCCCDC{CCC]C@DCCCCC=CCCCC CCCCDCCCC8CC DCDCCCCDDCCDCCD DCDCC(DDCC}CCCC@DD DCDDCDDC@DCCDDC@DCCD@&DC$DCCDCC@D%DCCCC6DCCC@+DD@,DD D)DCCCCC@DCCCCCD@(DDDCC'D@$DDCC@DD0D@DC)DDD0DCDCCD?D@"D@4DDD@'DDC"D]DDGD@DC8DD D1DDC,D!D@'D@BDDC'DODC7DD@D@)D@DD=DHDBDD@/DDTDdDCVDDD4D@VD_D9D@D0D@DD=D@DZD>D#DRDcDSDD:D@7D@*DCBCCC7C2CdCrCB|BwCCdCCnC0]CCCC,CtBDCeC7CCCBC+C5CCCCCBAqCCCCCCCCCCCVCC0CBCLCCC=CBCxCBCBBCCCC(CBCC$BCVCACWCCCCCCCCBnCB5CCCMCCCBCCCCC)C%CCCCCBpCCCC|CICCCyC@DCBCC CCCCCC8BCCCCCCCC4CCCvCCC%CCCCCBBDCBCCfCCCCDCCCCD%D1DFD DTC DDDDDD%D DD DCC!D"D#DCD/D?D@DCCC@ DD@+DD@3D@DC>DDC@D#DCrD@6D@D/DDD=D8D@D@(DDC8D_DCDDC@&DWDCDSD3D=D&D D@DHDD@.D@CD=D@SDgDNDDDCDDDDDWD7D:D@gDdDJD2D[D D@[D+D@ DDD@^D@_D@ZDtDFD@pDDZD@cD@fDADUD DD;DaD3D@]DXD@ND DED(D5D:DCDD DD,DUDGDhDSD@D]D@tDIDPDdDIDsDaD@5DTD`DaDDlDZD@tD^D@*D-D DcD@pDJDDDrD{DD@{DhD@1DMD~DdDD~DQDD DXDD@_DOD@iDDbDbD~DlDqDDnDD@DeDD@DDD`DD`D`DDD`DDDDyDD@D~D DzDDDDD@DD`DD D{D DDDDDDDD`D`DD D@DD DDDD`D`DDD`DDDD D DDDD@DDDD DD@D D@D@DDD DD`DDDDD`DD@DDDDDDDDDD`DDDDD`DDD DDDDDD`DDDDDDDD D`DDDD@DE ED`DD DDDDpEEDPEpED`DD D E E E@EED DEEE EDEEDEEEE`EEEEE EE E@E EEEEEE0E E0E`EE@EE@E0 EEEEPE EE` E@E EEEE!E`EEEEE EE EE E@E0EEEED EEP EE E@E@E E EE`E E0 EE@EpEE EE` ED E E EEEE@EEPE EEP E E E`EEp EpEE@ED@ EPEE0 EEDPEEEE EpEpE E E@EEDp EEE EEEE E EE EEPEE0EEEEEE0EE0EE EEEEE0 EpEEPEE@E EEEE0EE E0E EE0EE`EEEEEE EE"EE E E@ EP E`EEEEEE0E`E)E"E EE E`E0 E"EEE E`E.E`EEEpE@E0%E0&E`EpEE0Ep$EpEEEEEE@EpE0!E3EpE'EPE E#EP%E!E"E0'E EpE$E@ E@(Ep!EpE)E0 E E E0#EEP&E@0E`Ep"E!EE#EE@"E#EEE)E$E (E)E`%EE!E@5E*E!EP"E@E3EEEE$E!E(E+EE`%E+E E0.E`$EE@&E@)E`E'E$EEPE@ED1D|CCWCCCCCBCCC)CC3CRCC9C^CCvCCCCBCCRCWCZCBCCgCCC7CCD\CCfCCCCVC>CBCyCCB@DC&CdCCCCCCCCCCCCCCCCCTCCC.CCCCvCC CC{CBCDCCCCCCC`CDC5CCCCCC2CDCCCCCKC4CtCCCCC=CCCdCCxCCDD#CBCCCCBCCCCC CCCCCC?C|CCCCCCCDpCC]CCCDkCCCqCCCCCCC#DCCCDKCCCCDCCCDCCCDVDCD@AD@DCDD D&DCC@DCCD)D4D DD+D8DCCCC+D:DDCCC@ DCD@kD%DC@DCC@DD@'DDCC.D@DCD&DC'DDCD@ DD@DUD@D$D(D(D,D?DD@DD@D@2D3DD@D@D D9DDD@!D@IDED3D{D@PDD\D@GD@PDqD7D@D@XDfD_DeDKD.D@iD@BD@DMD@kDzDD@D@D6D^D@QDfDQD@^DD7D DsDuD`D@aD@DYDeD@0DBDDqD4D`D~DIDzDwDXDDD DDfDFDgDD`D D D@2D@sD`DvD D@\D@XDDtDuDDD@|DjDeD@ZDD@DD DuDADDD}D D@oDiD DDiDDpDoDuDDDDDrDD D@fDDDbD@DDxDD@DDDDDD D@zDD`D DDD@tDDD`D`D`D@D@DD`DD D D`D D@D DDD D@DDD@DDDDDD`DDD@DD D DDD D`D`D`D`D@D`D`DDDD D DDDDDDDD DDDDD@DD`D`D DD`DD`DDDD`DDD@D DDD@D DDD`DD@DDDDDDDDDDDD@D`D D D D`DD DD@DDDDD DD`D`DD`DDDDDD DD`DD@DDD DD@D@DDD`DDEDDD DDDDDD DD D`E@E DD@DD`DD`DDE`DE0 EEDpEE`D@E EEEEpEP E EEE@EE EEEEEE E`E@E0EpE0EEEPEEEEE EPEP EEpEEE`E!E)EE'E@"E`E@)EP9E#E&E@2E`Ep2E&E%E@1E.EP$E/E3E9Ep?E3EP%E*EP9E@5E>E@2E6E@E2E@1EMEDE`;EFEKE=EHEDE=E`JE9EEPEPFEBE QE MEAEPQEOE FE?EQEBEMEpLE`IE@ME0DEDEpREGEP5E ?EpKE0MEWELEpCE`PE WE?E@E`>EJEUEpKEFE`LE@IEEEP=EKE:EpHEFE?E0FECE 2EPEKE@>E>EAEFENE`CEP9EP@E0FEEEBE@E0IEVEp=E5E?EBEp)EE:E:E?E:E0E ;E0AE`E9E?E0,E(E(EP7E BE/E0E,E03E@E2E*E3E`8Ep5E0@E.E%E`8E4E-EAE@E9E ;Ep;E@1E4Ep?E!E/E ?E3E`KE@E;E BE`?E@>EP8E?E`,E2Ep/Ep)E`>E;E>EpEP4E5EP>EP3E3E =E5E0/EP>E05EE5E7E3EBE0E ;E0EP6E;E3EFE:EEp0E`6E3E D@DCCD@DCCCCCCCCCCC DCCCCCCCCC{CCCC@DCCCC{CCCCC@DCCCC@+D@ DCCCC@ DCCCCCCD@$D!DCFCCCCCC@DCCCCCC6D DCC DCCDDD DCCCCDCCD$DCCCCC@DC DCCCCC9DDCCDCD DCCCC@ DCD@DDCCCC@+D@DDDCCC@ DCXD/DCDDCD@DCDD@*D DDCCCDDDCDDCD@/D D@D5DCD,DD?DBDDC@DC@*D@DDD@6DDDDCD@'D@ D@#DDD DBDNDD@PDhD3D%DDC8DPDD*D@0DND"DCCCD2D D@5DDD6D4DD*DDDD1DoD1D,DPD@5D@XD@TDKD4DRDdD@-D\D[D/DPD@cDYD^D@aD2D@D4D.D@pDcDLD[D@DE7E-E(E5E5EE:E7ECEJEE LEAE;EFEMEGEGEEEP'E@SEPPE CEPLE=E0AE FE BE0EE0LEDE4E:EpAE4E`DE0?EDEDEGE3E`:E ;E`>E:E5Ep:E=E`=EP8E0@E@;E8EJE0AE@?EFEJE>E@9E5EP2E05E:E?EPGE@E`-E@7E0E:E7E@:E8E`;E 6EpE`:E8EGEP:E2E7E=E*E`/EP=E5E@=E6E-Ep6E9E3E?EP7E-E 7E5E@0EP=EE>E3E9E9E5E=E@EE :E.E4E@/Ep9E5E0E>E06E3EP8E1E,E=E5Ep=EFEDE@E9E)E3E7Ep,E:E5E+E;EP:E/EE EDCDCWCCCCCCC@DD DCCDC@D DC@D2DCCCzCCCC DDC DDCC@D@DD@ DCCCC$D@DCD!D#D%DDCD@DC@DD@DCDDDCC%D@ D!D(DCCC D@ D D DDDD@DDCC@D@DCC,DDD@D@D$D.DC@D.DhC@DDC@OD@6DCDDCDDDD!D@'D@WD@DC%DDCJDD5D@GD@DDD;DBDFD"DCD%D+D7DCCD@MDD;D7DD0D DCOD'DDC?D4DD4DC4D;DDMDD6D\DzDFD#DC@D@GD@aD D@D&D@DaDIDD@aD7D@D@MDMD D@FDDD[D[D@AD@@DSD(DCDC@D3DBDwDDAD DDD D@"D5D@bDHDxDtD@$D;D@FDDD#D@D@aDQD@aDWDVDDmDVDSD_DiDYD~DGD*D^D@uD'DjD@]DOD@cDfDmD@bDaDaD@WD@pD@hD@D@^D@gDD@WD9DXD@KD@NDDDUDD~DDDQDMDVDD`DXDfDqD@D`D@D:DrD@xDuD D]DODvDDvD DD9DcD@DhD}DD@XD@}DDD@DDiD@D@D@TDDD@iDDtD@[DDvDxD`DrD{DDD@DDD@aD`D`DD`DDDDDD@DDvDDD@D@DqDDDD D@DDDDDDDD@D`DDDDDuDD D@DDDD DD D@DDDDDDD D D@D D DDD`D`DD`DD DD`DD`DDDD@DD DD@D@DD D`DDD@D@D@DDD@DDDDDD@DDDDDD@DD DDDDDDD`DD DD`DDD D DDDDDDD`D@DD`DD@D D`D`D DDD D DDDDDD D D`D@DD DDD DDDD@DD DDD@DD@D@DDDDD DD DD`DDDD@DE D@DDD@DD0EDDD@DEDDDDDDDD D@DE`E@D@Dp E D`D`D@DD`EDD EE`DDDD`DEDEDDDDDD E`D@DD`D`EEDEEED`DEED`D EE EEEDEDD E EE`D`DDE E@EE ED EED@EEE0E0EpE EPE0EPEE0E EPEpEE EP E EPEEEPEPEPEpE0EE EEpEE EE!EpEE@EEE*EEpE@EE`E` EE(EPEp E!E E@E@EE!E'E!EEEP"EE E#E E%E(E%EE E EP!Ep)E (E`5Ep7E@#E&E`E`*E3E;E -E!E(E-E1EE.E7E.E1E=ECE`3E0=EFE0>EPGE /E3E AEPHEBE?E`1E08E0CEFE;EIERE@?E0LE@BE`AELEDE=Ep[EPOEAEJEPE`BE`[EYE0JEOEFEPAE0TEPEIESELE`OEWEOE PEpaETEFEJEPEKE@OESEMEZEPEREeE]EREUEWEPMEZEZENE0XE^EXE0VE0]E@UEWEPSE@_EP]EWE@OE ]E0^EQEPXE[EVEHEJEPMEQE0KEPNEWEKEpFEREXEKEPNE HE BEIEHE0;EQE KEHEUENE`=ETEDEPEKEDE5E0FECE=EAE@EE>E`CENE06E AEIE5E0AE7E01EE0?E>E@E5E@9E 9E2E04E0E 9E &E 3E2E*E4E'E$E9E6E,EP-E 0E@-E@:ED D@D@DDCC DCC@DDD@DCDCD@DCC D@(D@D'D DCCDCD@+D DKDDCCC#D@PD@'DC@DD&D'D%DC D@DCDBDDCDD@PDWDDDDD@$DD D!D@'DDmD0DC@D5D&D6DIDD)DQD@(D.D3DC@3D{DD4DCC@/DD@D@!D@FD?DOD4DDDD8DCADD5D$D@>D@GD,D6DODAD?D$D@D9D>D-D!D2D@DCDD@tD@PDD=D,D2D;D.D9DdD>DD0D\D@)D>D1DD@QDTDTDTD6D#DgDOD D=D@>D5DvD@VDCNDD@[DDoDFDrD:D@D9DyD@]DADUDgDnD`DLDoDEPE@ME?EGE?Ep5E@BEFE :ECEIE@FEpQECEBEDEJE?ELEGE;EGE0IE9E@PE0DEDEFEBE0FEGEIE=EOE?E ?EBE9E6Ep7EP@E0GEFEFE AEJEDE7EEE 9E02E:EpEE4E8EAE?E=E:E1E`8EBEp8E=EDE3E+E6Ep(E6EAEp.E8E1E`(EAE9E'E 1E.E1E0E7EP"E`1E`0E0+E@8E,E"E3E%E'E+E06E/E2E$E-E*E01EP*E@2E(E#E`+E"EpE@+E0E%E#E/E(E (EEE@E(E(E-E,E'E0*E,E E0.E/EpE*E@)EEEE0E0E(EE@3EEE2E +EE0)E E`"E&EP&E@E*Ep,E@$E5E&E0"E !EP#EpE*E0!EEp%E#E`E0,EP-E EEE#E"EEE#E@E@E@(E0EE@ EEE'E@E0E(E'EE0E0'E@E&E*E@Ep(EP(E Ep.E 'Ep'E %EEEE#E0!E #E *E "E E"EE E.EE&E0!EE*E'EE!E(EE-E(E@E EEEP0E@$EE!Ep*E E*E%EE(E`'EPEE#EEEEE$EEE E "E%E!E#E Ep%E`#E@EE@#EEE,E`#EP%EEE`"EpEE*E%EPEEP$EpE E`(E,E$E EE'E!EE"Ep$E`EEEEpEDDBD@2D DD.DBDCD@DDC2DD%DEDC DBD5D@UDDC3DDCDD!DD%DDCD-DC,D@!DDQD@6DCCD D2D@@D@ADGD8DCD%D:DkD@>DCDPD@)D@ DCC@(D@D@GD9D)D+DnD-DCC@%D@.D@ODDC3D4D DBDBDC@BDBDD@5D@5DDDDD@eD[D{D D`DnDQD D@D@tDpD@kD`DDDwDDDVDmDpD@uDD@D`DD`DD@D@DnD`D_DSD`DD@sD`D@DbDD DzDDNDND@DD DDD@mDDDjD`DDoDDD@DD DD`DDjDD DD D DDDjDrDDD DD DDDD D@DDDDD[D@DDDD@D DvDD@DDDDDD D`DDDD@D`D@DD@DDD DD D@D`DDDDDD D DD`D`D`DDDDDDDDD DDD@D`D`DDD DDDDDDD DD`DDDD DDDDD D`D`DDDDD`D DDD@DD`DDDD@DDDDDDD`DDDDDD`D`DD@D DDDDDDDD@DD`DD@D@DDDDDD D@DDD@DD D@D DDD DDDD@DDDD`DD`DD DD`DD@D@DDDDDDDD@D DD DD D`D D@D@D@D@D DDDD@DDD DDDD D@DD@DDD@DD DDD DD D@DDDDDDDDDDDD`DDDDD`DDD`D@DD@D`DD@DD D@D@DDDDD@DDD`DD DD DD@D@DDDD D`D DD@DD DD@DDD@D@D DDDDDDDDDD@DD DD`DDDDEDDD DDDDDE`EDE D D D@D@DED`DE@DD DDDDD@DDE DD`D D D`ED@D DDE`E@DEEED EEE`DDD`DEE@ EE0E@D DED DE E EE EE EEDE0E EE0EE EE EE EP E E@EE`EPE EPEPE E EEE0!EEEE0$EEP EE E@E!EPE EpE@EPE%EE0E$EE`EE EP'E0 E-E.E3E E-EE`E0E$E`E1E-E+E*E+E E'E`0E &E+E`'EP"Ep5E,E"EP&Ep'E`#EP7E6E+E3E0E%EE+E&E ,E/E*E/E*E'Ep"E(E`E@*E,E/E8E@.EEEEE,EP-E&E%E 'EEP#EEE@+E,EE#E+EP#Ep*E&E0EEE&EpE0!EEE@E EE"EPEp#EEEEE0E0%E2E EEEE)EE EEE EE E@EEpEE EE EE` EEEE EEEEEE Ep E0 E EEEEEEPEEEp E`E0EE E E@D@ EEEE E@EEE0E0 EE EpE@E0EEpEEEEEE@E@E`EE@E`EEE E EE@EE E E@EE EEpE0EPEEEpEEE EEEEEpE EPEEp E EE E0E E Ep EE E`DEE@D`E E@EEEE`EP EDEEDE EEEEpE`EEEEpEpEEEDE Ep EE0EEEPEpE0E EE EEEPEEEEE E` E E E`E E`E`EE EEE EEEEE E`EPE EPEEE@E0EEPE EEEpEpE@ EEE`D0EE`D@EE EEpED DDDD7D7DD.DCC+D>D D'DD@DBD1D@ D@DDC3DMD'D@D@6D-DDDCDDD/D%D DD@D_D@=DCGD@CD D2DTD@D.D DC@ D@5DC1DCD@D@/D-D`D;D@ DCDQD2DJDCDOD@"D@HDED=D5D%DD@#D%D#DED@FD5DPD?DDD@0DD4DDDHDMD DDDDDC@JDaD@SDDDD@-DDcD^D-DGD,D@3DeD6DGDtDtDPD7DDD@BD@-DLDoDJD D+D_D@pD>D-D!D@SD:D;DaDwD+DMD`D@=D[DAD+DuDRDBDID\DcD?D@CDDyDmD3DpD>DDED}D@CD@VD^D@DDDADZD@QD0DRDkD?D@OD@.DODuD@XD1DtDD?D[DOD@BD@gD}D[D>D]D]D D^D@RD@|D@_D(D@HDPD`DD@DeDyD^DUD@DDVDoDuD`D@DjDLDD}DPDPD@\D@:DRD D@[DDcD@\DrDvDCD@wD`DPD@LDhDWD@D DeD`DvDKDD@DD DsD2DfD D@yDxDD@hDD@D@tD~DD]DD D@gDDZD@]DaD@iDpDjDD@[D@aDD@ED@kDqDDDD@fDDDuDcDD@D@{D@lD D DDdDDDpDDD@D`D`DIDDDwD`DDDDD DYD^D@kDDD@wDDD`D D[D[D@vD`DDuDD@qD`D`D`DD@yDD@D D@~D DD`D@D DD DDDDDDD`D`DD DDD`DDD@{DkDDD DD D DDuDDD`DDDDwDD DDDDDDD@}DD@DD DDDD D@nDDD`DDDDDD`DDDDDDDD`DDDD`D@DDDD`D`DDDDD`DDDD@DDDD@D@D@DDD@D@DD`DDD@DD@DD DD`DDDDDD`DD`DDDDD`DDD DDDDD@DD`DDDD@DDDD DDDDD@DD@DDDD D@DDDD`DDD DD@DD`DDD D DDDD DDDD D@D D DD@DDD DD@DDDD@DDD DDDDD D@DDD`DDD DDDD`DDD D DDD D`DDDD DDD@DDD`D@DD@D@DDDDDD D`DDDDD`DDDD DDDDD D D D@DDD DD D@DD DD DD`DDD@DDDD@D@DDD@D@DD@D`DD DD@DDDDDD DDD D`DDDDDDDD DDDD DDD D`DD DDDDD@DDD`DDD`DDD DDD@D`D DD@DDpED DDD@D`E0EPEDD`D`DDp EED@D`DD@EDDEPEEE@D DEEEE`DE E`EE0 EpED@ E@ EE` E EEEEEEEEEEEEE EE0 E Ep EE EEEE0EE` E@ E EE` E0E` E@E`E EE EE`DE EEEE E`DD E@EPEED`D Ep EEDED EE EEED`E@DpE EE@E EEEPEE D@DED`EDD@DDDED@D DEDED@DEDD D`D@DDE`D DDDEDDDD@DE@E@DD0EDDDD DD D DDDDE`DEDD@DD`DDDD DD D@D D`DDD DD@DD@D`DDDD DDDDD`D D`D`D DD`DDEDD`DD`DDDDDDD`DDD`D@DD`E`D@D`DD DDDD`DD`DDE D@D DD D@DD@DDD@D@D`DDDD@DDD D`DDD ED D@DD`D@DDDDDDED@ ED@DDD`D D`DD@DDDDD@D`DEDDDDD@DD DD`DDDDD`D`DD@D`DED`DD D@D`D D D DD D`D`D D`ED@DDDDDD@DD D@SDDCCDVD+DCCD@%D(DDD@ D0DCCCCC#DDDDC%D7DDCCC*D,DC@*D*DD3D DD@:DUDDCCDADD@0D[D7D@FD.D!DC"D-DD?D@DD@D@3D@!D!DDD4D@4D@6DODC@ D;D)D@]D/D@$D"D>DAD@*DTD@D@UD/DC@HD@>DD2DOD@7DRDDC_D@8D0D7DD D5D(D DnDpD DD#DEDKDKD+DXDcD@DYDADD@gD@D*D(D@JD D(DID@D`D[DCDND@HD@`DcD>D@gD@&D"D@+DWDDkDHDD@@D@|DzD2D9DDID`D@D[D=DD@RD@HDPDD@D/DRDWD@%D>DmD7D@ODiD>DKD@CD@0DcD7DwD`DhD?DQDAD9DvD)DD6DYD@YDQD`DCD3D4D@[D@XDhD3DrDLD(D@D@wD@kD?DZD;D[D@,D@FD@iDVD'DjD@SD"D@PD}D@ZD DcDqD8DsD@IDlDLD)D@D@D)DGD@QD]DuD@wD-D@`DkDQDKDoDVDDaD'D`DOD@&D@D@OD@gDDaD@dDRD@ZD$DiDRDZDwDUD6D@{D D\DqD@hD1DODoDCD{DUDMDD`DQDnD@FD@DDCCCC@ DD@)DDD/DDCC@DC0D@ DCCCCD5DCDCC!DDCAD DC/DDCCD@DD@DC&D(DDDDCD DC!D D@D DCC6D"D D@2D@DC@D D@DDCCD@AD@8DBDCCD+D@D.DDC@D@ D@D@"DDD@ D@ D@&D1D@%DCDCCD@ADD@DDDD4D@FD!DCC@D5D@D@D(DC@9D@ DCC"DD=D6D D@D*DCD@DCD)DD@DDC@%D@HD&D@D%DC>DCD7D/D/DyD@3DCC@DDC;DDDID DDDDC@.D/D@ DKD@*DC4DD@D@-DMDD;D3DC2D DC=D6DC5DD D)DD DBD@DC@ D D@DaDID$DD DC-D-DC>DDCDDD-D%DC&D0D@/D@2D@EDCDD!D=D7DC&DDnDSDqD@aD:D*DDZD=D@AD&D@-DlDD DDGD@DD@7DNDD@KDDDDDDCCCDD@OD@8DCDDC?DD DDDD@D@DD@D@(DC&D@DCDXDC D DDD@D'DJD$D D-DD0D%DDC@&D#DD@1D>DDED"DD!D@D6DIDFD+D.D@#DC D9D9DFD'DDCDDMD5D DCD@!D@D@D@DCFD>D DZD@ DCD)D@5D*D^D?D1D@D@D5D2D@DYDDCC$DED`DDD@DDD.D@4D@RD$DD/DD@D)D@DGDTDC+D,DD@D@ED\D-DBD%D)D@D#D@kD@&DD@9D>D@1D8D5DC6DeDED@BD@DDbDSD2D@&DCCDDC@'D\D;DZD3D DD9D>DHD!DD)DHD@6D@8DFDC@DbD@GD[DKDHD?DeD@-D@[D.D DaD_D-DXDvDDDD?D]D[DVD@DQDhDLDwDCDHDDDND0DKD@nD@^D@rDRD@8D9D@fDFDDaD'DAD@_DiD\D;DDND@aD DDnD@"D@CD@D]D D@{D@=DD@%DlDD@{DD9DgDgDsD}DlDvDD@yDQD DiDCD@pDADFDkD@PD@[DhDyDDuDhDBD:D1D`DnD^DVD D{D@>DgD@5D@+D^DD@WDXDkD@DhD~D@ID@ZD@mDLDDDED8DQD@[DzDbDJD\DMDDD/D-DDDED`DTDDDBDPD4D~DcD?DYDMD%D^DoD?D[D6DMDkDhD@XD`DjD@4DnDuDID@sDlD0D DgDBDD-D@;DD^D@aDPDDLD!D_DZDD?DCD@YDDnDoDcD@GDXDXDRDDeD@HDFDzDED@cD@D@DiDDDJDD_D;DCSD*D3D@eD@kDKDVD=DCnDYD@D@CDcD1DgDkD@ED}D@7D*D D@xDODyDeDGDDxDKDiDaD?DQDRD@ND]DZD6D>D,D@YDD D^DLD@D8DjD`D@D\DCADDC3DD%DD$D$DJD>DD@BD@DDDAD@D'DC!D,DDC@5DKDKD]D6DD@7DJD.D@?D@D+D@DCCD@_DLD@DCCD@D7D@[DTDD@.D2DD;DC D,DNDC@VD@?D@D@D@DD\D4DD@DD@D(DCC@ZD@DD"DRD,D@DDHDDJDDGD"DC:DPDC(DD@DD@(D4D*DFD2D@DC5D@BD[D@mDFD@8DDC?D8D=DTD@3DCD@=D@;D@QD@ DDFD@DC@5DiDDRD@7DDCCDsCtCC@C4CCCCCNCC*CnCCSC/CCVCCHCB@DCCCcCB2CdCC@DCCCCyCBxCCCCCCCGCCbC,BDCCCCCC!CCCCC1CCCCCCBqCCCCCCCCBCCCCCtCC(C&CCC3C\CCCCmCBCCCCCCCMCCCCCCCVCCjCCCCCCBBD@DCCCBTCTCKCCCBCCCCCWCCCQCwC2CbCCCCCyC)CCCCDCzCCC-CCCeCC@ DCCCdCCCmCCCCDC,CCCGCCCCCCCCCCDCCCCCCCxCCCCCCCDCCCC:C@DCpCCDCCCCCCACBfCCCCCCAC!CfCCCCCCCC~CCCCCC~CCCeCCCC DCBCCCCCBCCACCC DCC DCCCC|BCCCCCECCCCCCCDCFCCgCmCCCCDCC@ DDClCCNCCCCCCCCCCCC@CCCCCCCCCCCCCCCCCCCDCCCBCCCCbC4CCCCCCCCCC@ DCCCC4CC@DjCCCCDDC@DC|CCKCC@DDC@DDCoCCLBCCCCCCCCCCCCCCCCCCCCuCCCCCCCCCCCCBCCC}CCCuCCChCCCCCCCC^C CCCCCCCHCC[CDCCDCyCC@DCCCCCCOC DDCDC-CCCD2DCC DCCCKC\CCCC@ DCHCCC@DD@D}CCCC5DDCC@DC@DDCCCCCC!D@DDCCC[C@DCCCCCCCBC@DDCDCDCCCCC@ DCCDCC DCB@DDCCCCD DCCCCDDCDCCCCC@DCCCCC DCCDCCDCCCDC@DCCDC@DDDC)DDDDDCDCC+DCCD@#DC@+DDC2DDC DD D!DDCD D DDCD3D'DCD@ DD%DDC)DDC@4DCC$D:D>D0DCCWD@:DGDBD,DC@4D@D@DBDODDGD7DD@\D/D@D@D0D3D@DD@$DC@9D@#DC@8D D&DHD@9D D@DDC.D-D!DD"D@D@IDDCDDD@BD&DCD@BD5D!DDC@&D#D&D6D@1D@D@)DCCD;DCD D8DD:DD D@1DCD%DD@DDCC@#DD@$D DCDC D2DDCCCCD@7D@D DDCCC@DYD+DCCDD@VDDC@DCCDCCD$DCDDC9D DCDDCDCCCCCC4CCCCJC?CCC CCCBdCBC DC*CBICC&CCBCsC|CCCC{CFCCC_C[CCCaCJC;C CCCCCB CCCCCCBCCLCqCACCFC~CCCCVCBCCCvCC2CHCCCaCCCBCCCCCChC`CBC]C=CfCC;CCCCjCCC^C?CCCC$CB0CMCC|CCC CCCcCIC^CCC%CCCCzCMCCCCyCCC(CDCWCCCBCC,>CCCCCFCCCC8CgCCCBCCC'DCABzCCCCCeCCNCBGC!C@DCRCTC=CLCBbCCCCCBCBCDCCRCCD`C%C CiC|CCKCRCCCBCCCCBCCICCCxB%CCCCClCCYCBCC5CCCCCCCCCC~CZCCCCCECFCCCCCCCCC ClCCsCCCBCCfCCCB;CCdBCCMCC]CCCCCCCBWCCCCQC#C@DCB@VCQCCC@CCCCCCCCBCCCCCCCCCCCCCCC?CCBBCCCCC'CSCCCCCCCCAB4CYC D@DCC~CB CtC3CCB5CDCCCCC)C CrCCDC7C?C[C5CCCCCC5C/CCWC=CCCCCCrCCCCCCC CAC&C>CCCCCC7CCSCCDCCCC0CVCCCCCCCCCCCCCCTCoCCfCCCCqCKCjCCDCCCCCCCCcC^CCCCCC5CCCC@DCC@DCCCC}CC$C CC@ DCCCCCC*CrCXBCCDCCC CCCCC@D DCyCkCCC(CCDCCCCCCCCCCDCCCCCDCCCC!C'D DCCCCCCCCCC*DCCCCCC DCp C"CTCCCVC}CBCCCC@CCHC BCC8CCMCBCCBCC@yCCXBnCCJCCCA'CC6CC$CBCCC^CCtCC@"CoCBCCKCCbC9CCCCC`CCCqCBCBCCC8CCCRCUCCCCC}CACCC+CCCGCCCRCCCCC=CCBBwCrC@BCBCBCCCRC`B ACC"CBpCC~C0CCC,CCCVCC#C CC@CCCCC>C CCbChCTCCSCCCCrC=CBCCCCCCCCBCC\CCLCoCCXBCLCCwCcCC7CC7CCC[CCC'CCCGCCCCCtCCCCC{CCCCCCyCeCCBvCCC@BECCC0CCCCC5CkCC#CCCCCeCDBCvCCCCBCCCSCCCCCBCbCtBpC~CICD[CBCCCCCCChC/CCtCCCC9CCCCCCCCCCCCzCCCCCCCCCCuCC{CCiCCC@CCDCCDCBCCC@DC>CCCCCCCCDCCZCPCDCC!DCCCCCDDCjCCCCCCCCCCCC@DDCC0CCCC&CCCCC@DCCDCCDC@ DDCCCBCDPBCCDDCCCsCCCRC DCCCCCCCBCCCCC9CDCmCCtCCDCCCCCCCCCCBFCCCC@CBCDCCCCCCCCCC!DC5CC}CCDDCCC,BCC6CCCVCC DC?CAC!CCC7CCC CCCCCCCCBCCC_C}CC)CCCCCCCCwCCfCACnCCC3CC;CCCDC]CzCBCCCCCPBCCCxCCBCC]CCCBCCCCpC[CDCcCCCCCCCDCCCCCC CCDCCCCGCBCCCgCQCCCBCCCCCYCCCCCCrCCYCECCC}CCCzCiC'CCCC/CCCCCtCCCOCCCCiCC~C$CC^CCCC CCCCDC_CDCsCoCCD|CC*CDC:C0C9CC(CCIC(CBCCCCC0BNCBCCBnCBCCUCJC0C\C8C4CACLClC5CBYC\CBBCBBBABbC2C0B[CkCBBCC>CBqECCCBBtCiC+CCCxBeCCACCB(BiClBBuCB CuCHBnCVCBC:C HCBDCBXCVC2CCCBqCBC6CAC.CB8CUCBXBBBJCCBCkCBCCCC>CCwCqCBB$CBCC`AxCCC.CCBB C#CMCCoCB8CpBB CBCC CBBBCGCBC?C`BCC"CClCACA(CCC CCBC}CCBCABC\C ACCBCBCB`B`C-CCC0CZCBBCCC CBC8CFCBBBB.CmCABCBCB9CgCC7CACCC+C[CxB4rCVCBCXC.C(CICDBFCPC CvCRCB BC@CoCHBPCBCaCCOCCBBKCCBC?CBCCBCC?CCCBB4C BC/CBAHCCCCoC CEC+CC CBC CBC(BBCCPC4BCCCdCBcC.C CSCNC C\C_CCPCC4CCC;CCCACCBBUCBCCBBACCBCJC@lBBBCC:CACCBdCCCBBLBTBCC@?CC,CB@A BCC%C C2ClxBsCMCAC_CBA/CBCC4BnCBBCACCC>C0CAkCCrCBCCCeCCCBCFC4CBBCBBCBCB\CCCABPCvCCpCA`BCCACCB.CCBdCCCC}C(CC CCCBCC/CJCXC0CCCBBBCC4BC3C;CCCBBCCCC$CCB0B`CCC$BCCsCBCBkCA)CCBP:CCB BBAeCB@C(CC}CNCPA!CBBNCC.CgCBCCSCCYC/CCBCECBCC4CB'CBCCCgCClB@7CBC}CB]CoCMCBFCCCfCPB&CCCCaCCC@BACCCChCC.C^C4CCCNCCCCUC(BcCBhCCICLBCC^CBhC@ACCCCDCCCJC>CCBtCCCBCC0BwC}CBCCcCCCJC8CCCCCFCCChCxBZCCCCCBC]C B&CC`BCCCCUCBCCBTCBhCCCBBCCCfCBCCBCPC=CCCFCCCCDfCCCCBCCBCC9CCCB0C~CACCCCCFCC-C`qCB`ABCCDCBCBDCCCCBBC\CCB}CCBC1CBYCBBiC@DCCnC0BBtC/CCCECRCC3C9CCBCCCBCCCTCBCCCCCuCCB?CCCC:CCCC!CBCCCC+CBCBBzCCCCCC[CCCCCCC#C~CBCC1CCCCCC9CCCCCCC;CZClCmCCCCCCCCCCCCbCPCCLCCCBBCCCCC^CCCCCCBCBB@CCECB CCAtBqCDBCCZC*CBBLBBvCBp@9CBCCB?BVCCB4B%CC~CBCB CBCBoCC|B+CaCBAkCCC AC@C@6CCB;CBBC>C C.C)CpBRCCBCA ACB@B`B/CB@VCBB9CC8BPB@AXC C#CC"CHBBCBC BB~CJCBBpC$CKCCCA{C0 B,Ch.CB\CC+CCB@ACBBA'CCC,CBHB BTBCC`CCBBCEC$B3CC@@CC*C5CBC*CACA`C C@ABBCwCXCBlB CCCBCPABBJCBCC`WCCCB:CfCC@CC8CBBC&CBCBBQCCC1CCCB7CCCCA0CCCCCCaCBPA\B$BCkCBCnCrCC)CBCACCDBBCCB CUCCCBB@BBCOCBCB\BCZC0CCVCBBCBCBPAHCCBBXBC'C CCCCB\BcC&CCA:CCBlBXBAAHBxC"CAB<C>C&CBiCBBBHBAlBACCBD|CBBlBCxOCBlBl$BBC/CpA\B?CBBBCCCBB"CB$aCCBgCUC@BCXBCB CjC{CCB;C,BqCC(CiC$CBCBACQC 8B$BBBB@ABAAB8BpAAAxBCA)C4B@BA`BtBBBBB`ABBkBC@B$C CBCiCL`PCCC C@\CChA`@BBBB`B$LA$CB)CCCzCBBAC1CBBLBCVCA"BBCCXBCBBA CC%C3CAB"B`B`p0B BCAHBBYCCA CC`A@eCpCCBB8CCrCB@CA;CBlBC;C8CBBj BBCC0B 3Cp+CCHClBiC@@dBB$BBlCBCBB.C$C&CCB@JCBdBCBACDCBBC`B8CCCCBBXC8BBBBxCCC,B B[CLC/CABoCNC/CBBCCBqC\CuCCBB@CB CCCCC,BCBCCCvCA}CCBAC.CCLCC.CCCC.CC8BCCOCBCCBTB/CCBBBCBCBCfCBDBBaC!CBABACB[CCCC0AB(BACgCnCSCA)CB*CB|pCBBQCBBCCBPB@ABCAACCAC.CB`AAeC CCCRCCBB$B]CBCCBCgC BBBtBChCCoCCCC BBCB(CLCB$BCXCNCC CHBBCBtBBBB BBCB8B8BCtBMC0A9BCBC;CBuCCpB8B*CCACBCBXBqC,C)CBCBABBLAC CBpAFCCB+CCCCA CC C7CBBCCCBBhBPBA@AMCC@C;CCwCaCB CCLBnCACA-CCxBCBBCCC C(BCPBCBLBBpA'CuCBA0B BCKC8\GCBPA(CRCBB^C]CdBBNChBABCBBBCPBCC|BBBCdBAXCA<BOC ACBLBB0CCBC C-ACBBBpAA=CCZCC&C<CHCXCBB@8C3CCAAHBXB -CB hBCCApAA<4C?UCdCAAZC.C^C C@SCCyCBB'CCHCCCCB@ACbCBBXC[C C(}C?CAdC|BT CCABCCBB^C@BCBBB-CXCABC@C CCNC@BAB|C1C CCCxBBBBtBPB ABBdVCBACB`AB|BCCCB4BBB CAVCBBBBBBC?CBC:CDBCCjCC@rCBC C`BB`ALBCB(|BC9C#CPBCHBBDC.CC\`ACB%LB CgCCB)CBTBBWCA'@CBBCPA@BB84BC CCCtBB Bx8BB'CBCTBCCBA CB%CABA BBBBCt#ClBBB$CCCBC0B3C0B`BtxBBICC,`BACCBtCHCCBB3CBCCBTWC!CcDECBADBCCBCBB,BBCBB|BBBB0BB@CCCABzCBB BB)CA&CHBBBB|B@BB ABBLBTBBCBBpABB-0DB,BCVCBAB AACpBBgCBBBNC 'C'CB@CCBA2CDBBCHCB4CADB9CBB0B B CMCBBKPBChCB,BAB}CA0=CBBHB BA!CC0A(BB0ABBxC AB0-`ACB0CNCdBBhBCB'CBBBpABpBYCAB@BCC- BBAhCBBAB3CtB@ BH37CCABBBlBBC@dBB\C8CHBbC.CBB#C9ChCPBCBpA BBtBDB@ AP CTB:C@P`AuCBT`CBB@AA0wCCC<LBICBBCVC*CCP BB0@ECB~CNCBBB,BA FCBBDCBABiBAdB BHCCB/C_C@@BH,CPrCVC@A C0BBzCCBB0BCBB( BCBBCTB0BBCPhCBI BB(B4 CAA,CABBB0A|BB,BD1CMCAC|]?PB\ABBBP CKCBBCBFBTCB"C8CpCABfC@@kCBDBABA)C CBgB B2CBABP4CJCBAHBCBSC(C[C B*CBCC(C0CpBBcCxBABCaC\BDAt4BBB!CCBBBHFC ClBCB2CPBCBBtCACBXCCBBCBBDBB0CABBBCdBB CtCBABBBCCDB`CB.CBB0BBB CBBC BC CCBCB2CCBBCHBBB'CBtB\B CQB`A\BKCBAAB@@CBB0ACBACpADBCCB C2CBBBB b,B]CLCCCB@@BBVChBPAC4BB2BBCA.CXBABsLTCBBB@ByCAp4BC*CBBUC-C6CBCBBCAC@4CB,BxCBBB2@BAB<@@DB#CjCB*B$B@#C`Bp? BB-C(B(\AB2CB8BBPCC'C(BBCQC1C[C2CCcCpBCB,CBCC4B,@PdB`ACBCCB B=CApApBB+CA A ABBtCC@PBCCBB\BCBhB3CPAPCPB`BCBQ,C@CxABBPBA C{C B*BBCC 5B`BBC4B;CC@CBACBBCXBBBB(CC>CXBBBtB0ChA CTCCnABC$C0BBB:CpWCDBB AB,BBB@CA C!C`BBA;CcC-C B\CC?CH CA BCACAC@5C CAC_BABCC0BC$CCCtCAxB0B CCAB@ABpA)CBCBCBEB:CABBB#CA}C@AtBAZCBBB@BB@AABzCABB"CCh(,:CB>B6CBCPA BBBAPBCBLBCBBhRC%CBBAAC:CJCBBB)BBhB5CtB%CB,BCfTBhCDBlC#C@B$CCB_C:C0BBB{CB9C%|CB`@$uCB*CC,B@$BCBCBxC`BBBCYC|CAXC4B!CCBCClBClBdBB?C&.VCC;dB? CABCB,B]CB:2?;CB(lBBB@BCBBCUpACACGCB)CC [BC7CCH/CAC(BdBDlBWCTBBCBACB8BBCC0p@A CAHBCB`A:CBC0PA@hBB BBB4BCCBCBxACA0CBpA5@BhOCCHC AWCCCB BhCABtC@C6CC`BBB4BB4C CBABCBBB0B`BBiCBBCBlB@CB C.C8\BPAKCtCt#CBKCBA"C@A@BHBCC C@A3CBi(BBACBBFCtBdBBB-CHCMCABlB&BBxBBAA2C5C8BcBlC0B BATBTBHBlB0 :CCYBxBCC-A@BA6CBBCC6CB0B,CCaCBBZC|BppACCBB@ECB3AA\BdQCBCBpB`A CCCCL CB@BICyCAB4 CBBB4!CWB@BBvGxB%CL/fCBmCCACICB\B\C DB&C7C C}C0YCDCABBCBCbBBBABCBMCCA B CABB@ CBBBBBB(BgC A@ABlBB(CB CAB@B,B(C C\BC\CuCC`B\BgCBFC)CB]ALCBNCPC\BBCnC*CXBA>C&CBBBAB9CxB'CBA CTlCCCCBC CBABAB8BCA@HC0ABABBBB C%CBB7CBB2C\LfCBC@7CCBC ACD=CGCBCBACACoB CBP @Cx CBZPA?C\BBCpABBYpBHiBpLB0BA?AA`fCB\XBYBCKBB A6CpHBBDB@ABxCABABPABBBBKCBDBBBB,CcCAA`CkC,FMCABBALBBB4B ABCBD0CGC*CB,A@AB`AC$BBtBCB dB`xB`HBBBBB AAB=C!@$BB2CTCBCBAL CBdCBB5ClBBBCACBBpCA&CfCd@B,BApBBlBAC@B4CHA?BAHB|BBBBB@|BBCI|B0BlBJCBABBABKB0BCAC|B@@A`@BB0CCCBBB$BBrCBACRClBB,C5C0B |B CC@LCCpBBdBCAHBBABB8A@XCCAC2DBA"CCBB@BXBOCB B CAkCBBDBCB@@CBBXCACBBBoCBBCBbCBXB'C,C CBxDCIC4B|BCABACpA$BHBCBBX@WCB1CC,BBBBCC4BBCTBBBCB\BBMC*C4BkCB_CAB@P`BAXB0BlBBBA0B\BCWC(BALBBB8hB@B:C#CBCCZC@A`AtCB`B$BTBCBBgCCUC)H$2CBB*C#C@KCOC>C@@(BABBpB$@BXBBCBDB`DB'CBUC 2BC@BwCC@(BdBCANC@B@$BCBBBCAABCB;ChB@zCBPA2C@ACBPAA8B$B@B8C@AABH_C*CA^CTC,C|BAC`APSCpCBBABy CB@A`h7CChhpjCCC C AP`ABTBBxBBA8BB@@#`CBCCTCGC0B4B4TBA BBV,BBAPBB#B,DCpA@&`DB0B B$ACBtBBHB\t.{CLBCl0-CB@BhXBB CSC(BBA (BHCAArN7CC4BC)AB#CdB8BB=CBApB@ CDCBBBAtBBBCBBCTpBpBxCB A|BB0B"CL *CB.CB|%CAB$ CKC@xB9CB C$BpBB`CLB@-CB8PLCCtBB@A\C_CCB@B'CBBABBAB@B0tBBB`BBlCBA,B$C`ApdBBB?B B$B0$B@@;C9B,CBpBBwC@BCDB@B%CACpBB8BBB ECBB@B$IB|$CBLB?C C31CBCB0AAhB,CBCC C0<BC8CBCX(H\BBdABB$ CA@BB0B*hCCBB!CCB"B.C$BB BB0B B4B`BBBP. ACPBCHBB8BCCAPBBB BBlB BBBBBLB`APBHB+ABxC}CA4TB!^CBBB 9CpBtBBDCBxBBAC?BBBB]C?CA$BP CCkCCBB@ABlBB@QC 0BC`BBBe@bClBdA(l?>CXB.C@S`XB@xCxB@F@?CBtC8BLBBBM AA2CCBABRCA CgCAAdBhCAhBB=CB$B?CaCABBBB%xBA(B6PA@ADlBP6CCRBCHC@h#CBcC+`BBAB8Bt(4CXACABCXB!CBpBCPA5CCBBB\BpAQ@BACB@B`BRC0APBCX-CA5B>CPBHCBC\C4BHBHBBB(CC!8BBTBBmC/C |B0 ADBBBB(`A?B'C[C0B0A CHB|BAAdBB BB C@ABBjAB CCBACHBMC6CICCCUCXBDBHB8BCHB4C@BCBBUC`BBhBBAC0BB0AA"CBXB'CBBhLB @BXC6CAABCCPx8B`@@AB CBAEA4CB8>C@pBA$CC|B&ChBBCCABeB@@BCBBA@dCA,BBB0@vC'C@xB,C CBp%CCABCCXB1CCAXBB/BC6CYCBBCXB`B0 CD,BBuB(BNCACXD@BPEC;C@8B@ABBtCB,BBBxBBA@@cCBBC7CAB,BBCBB|BB%CnCATB\BBdA@Bd CB,(C@@BLBABB@ABBHNCB0C+BBBB BBCh B-C -C@@oCBB.CBxBTBCBBPCABBU B*CCgOC!C?BABACB-A>BBBBA@CBABX,Cl0BA,BtBVC\BcCBCB/B;C $PBCCB8B< D CABC@@@|BABHC&CAABLBC`sCBBACtAPBBBACC5C@@ABB3CCTC0BJAB,*CCBA\BBpBBL`B`ApBBClBC CALB@@3BPA0*CBCB`W B0AA@BBBCPBnCAjCBCBBdBAB0A9C7C0 CB1CCB B@AB(C B@$BXaCB@@CCBDBPB@@A@@ @BB&C@B#BlC\BLkCB"B@uCyCBBYtBB0B?AC ABQBB\`A9CClB`B@-C(BAVCABlBxB%CpBA@CXCApApB`&C2CBB40AD CBCC@BBB 0CCBBAB'CB:C0BBB1CxBB`BBBRC$CBwCA/CB@@\BP@*C@@AxCB&C LCCBA AB.CB0]CB@B@@ACAB\BdBChBBBD&CCAXA$BBXCTBBBAC?BxBPBB4'CCx%@CHLLCBC? 8B@BB @BCBBC0A BC@AB( BCC`B CbC9@ABBBCB0BC\CPB1CT(Ct4B@@BT0CBCCAABHCHC8B NB{CA0CZC(BABB"CCCABAXBC@?HBHXCBABCB@Ax B0AWC (XB3HBNCCBP B`/CBXB-@CB@A@B8BBC@BB[CJ0BXBxBF,B|CBB4B.CBBCh A A(BBdB `DCB, BCX0C `BhBBB&dB$VCCC`A#CC3CB5.ABxBA BCB&CBDB CAx0B$B CBiCB C B#CtBBAJCC CBClBB#CBBB1CBo CWC0AQCCCB20CTBApB@(CB BlCNCECBBBhBCBHBCB%C8BK5CP@+CBHPC@BNCBOCBB#C $Bx=BABCCBzCBB (lBFB CBBdBLBB@BC'BpCpBCBB+C?C]CB`BXCAB4B CBB C0A$CBA`CCXBA BAC!?0CB BK0%CB1?$8hCAHB0H@ICuC]BECCGC), B)CB@@0 CCBPA!C\BA BBrCCdCBApB(BKCXMXBBBCaC&BBC'CBt BXBTBBCB0BBC`CBCx+BlB$B4B!C+CB8BRCBBBBB ACBBpABB AC@BmC0CC`Bh CCpBDBTBBTBBCBFC=C A@xBYC@BDCBBAClC`GC@mBTB[C|B^C^C A,BbCtBBB/CB3CTl0:CHBB@\CB`$B/BpdB9C#CCAtAtBpCA5C@ABBqC&CCB-0C)CC(BNCATC%ChBB\BB C CCYCB,cC`BCATB@ALB`t8CB !CB8 B@FBxBB`4 CBkCpAB@CpA,BOBCCCMCTAB$CCpCB%KChCC%C7CB+?HC`BBZC/CABPDB CJCC>CdABABACPB $ UCCg\B CC`A,B-CCBB CtBC@$BBC CCoC?|FC@B4B@B]CABa0(8BCBtBAB_CC84CFClB(NCBB[A,BB5CAC.CdB\BCd7CxCXBLBCBTCBB`@AfCx)C*CABTC BBdB aCpCeC8\CCBBQCABC:A@%C"CCNB@0{CT3BBBC7CC`BQBBB4B4BAXBUCB BH0ABCaBC?C@;C$BASCC.CC 0@BCC A0CB`B0B BBBBBA*XC1Ce@BABLBC@C` x@<BeCvvPCB]CpA6CBBBBAdBPAACCC&AA+ AAPB@07%CBD?*Cp A C(BCJC,B2CDB4BA*BBBDBTBABC(BXCdBCVCB.0BCCtB BPBCBCBBAdTB)CAAAHACBzCBCqCvBhB:\BuCLB#CC4`BCB`CB`AB`YBB)%CCBcCA ACB,CBCTBB0A|lABBBBB?BBBdBt/CcC`B\B B4BB&CCgCC;pBBWCC@ABBHBC(LDBNCALADCBH0 ABC CDHBBABECABNCBpA C,BDC.C8KC$B,BB7`` \CCCABC6C@BMCBtBBhB@SCdBBBpABB8CBBBAH0,CB/B<BB@BBCDBBCCaCC2pBXBpAhC+C?4LCCBCb|BPBBBANBC}pAB\CC5 ApAB@BB8B>CABpBCB :1LCWCC$CXBQC=CCBHBBCB@BrCPT BtBBBCBB3C4BBC@A%C0A4CRC:C>C(]KC4CB0CmCC#CAuC)C C$=AICHpAC`ACBpWCBBCB`BCBCAB9&CBBB@A(ACCBlBCBAQCA@BBdBBpA9CABJCBCBHQC[CB%B V?ABBPDC@lBBABBB@D,CBlBwCBABqLBAB\ BIC^C0(B .CCBB@@rAfC$>CPBhBABCD+C`<P(BdxHCBlB@<BATCB=(BC#A@CC CqACC.#CB BHB@BBBpCCHBC;>BC0CaCW+pBCABC:CBoCB@#C+CIpAB`C(CLA@B(AaCx@ChB<pA4BC.CCAAMCBBSBABXBC5B9CB0CxB@< AICTB\XBBB!CpApA`A0C0,B@:CB\BBCCAlBB|BBdCCABBB,dtC~CpA@@BBB@@BfVCjCB@o|@CdB$BpB,C(CB0B!BB/CIPBpABBpB0C CXBACBpdCCE>C C pBBBBP@@C B0|BCKCCB`AoCC@BB~CCBB5CBsCCB BBECCA(? C/CBnXBBB^C$BBBBB?CABpB@8CvCACb\@@iC(C@AhBB1BT$CTBBHB?|SABgCB@CBACB4C!C B TB`BCBACBCBA@#CBCBAB)BBgC8B@tDCxC@KC81CBB@gA"CB_C\C LB1CpCdzCbCB|BdBHDBBX~C@CA|C@/8DBABlB4B@ABC\B@BaC@B?BBC2CAC0AXC)CDB,4CB AJCBBYCBXB8CpTB4 C@A\8A C()CCA0AB@0B&@BBtB+CB$CICeCBBB`ABBV@CBCpAB&CBX@A~ CKCBBBCAU B\B CBA?XPBBCBb@CC20C,@DBBAACCB APBBA@Bb8ABTXBBB6=B`CBBA@C,BBA+C8BB@ A>CC AXA@`B@C6CAHB0CCA4'CAA@@{BBh BdCB C8BB8-BBBHBBACBpBpA!-Cp$BB%CAcBBB$BC`B B(BBWpB`A|CBBABBB`BQCtBBBB9CACPA0$BBTBCP`BAlCkCBDBAoHXB7CpBC\LBPx*CBABLB ,CB|BC |BBeCBB CCB[BBB!C !CBYC@ASCi8B@B@B?CBBA3C`BB8DHB'CAdCHBBC@_CCABACp@7CT4C A'CTC)BBpCCAB3CBHB@AV$BB5CC`C|BBBC%CBhBBBAB)C\BTHBpBB>C?B(B-BD0BAB? BCBFBuCTBBB$BdCBPABCD#C>BB A9CCB)CB BCA'C C@,BICBBSC B4C XBACB@h"CA-BBBRC )BBABHBDCC ABCCA@B4AP0A&C@P;C\PBB]CC tBBBBAxPBAB'8C0AA CBC CC\B1CB$@@LBCA"LBBL1CAlIB A,B B{C,BBdjFCC ,BCB4BBB\CB|AB|CEC4 ABC@At'CMCPBA` C(CBdBC CBBA;BrCBXBIB6CR|B(BCXB4 DBxBCA=BC%CC@ABdBC CxQhBBAPBA8;CBB@)@BlBBBBB,BBBCCAM0ABADBBBCB:HBAB,pBB?CvCBBB(@BPBBB4BB@AxBCuCB|1C BB\BTBB8B$4Bp6#CCACB%C@BLBBHC CB8B`BC\+@BCBBx@BB.C0A CCDBY\C0ACA,BBB`BABAPBpB`AABBPBCB4CpCBAC@CxB.B8C%CBC@SCD0AACMCC@lBBCABAA$BB8B`BCBAB$0CxBB8BC-C MC@BBqC(`TBTBBATBCBP,CPA BtACB,.CBBBhBBDBB\BTBBBB=CC@C@B!CAB)CBB@@@BCCBP$BBBN0CB(B1C|0AABB5CB@CBBBCB@TCB>@`H CBBA<cC;C@@BBAAhB~CBBBAB*C|3CCBA2BCB~( A8C\@ <BC@@B+CB@`@@BPCB1AACC@BB6CCBAHCLBBB@AXB$< B@B4Cx6\C\B%C7'B,BA\WB^Cp.CPBC;`pA@HBABB6CBABB@AC,BP BBC BCBD|BABpBvB@AA4PABABB$A<qC4CB,0BClBrC@ATtBpA@LCDB`A@4CKP(CBA>C!CC?LBB BA_C0CTBLBBBA< ClBCLB0AB A8BB @xBBCBB^ClC,B2;CGCC4BUCCBA`A@`*CBLB(xB8CAB@AAB BC)C 3CBBB@A1BB0B`gKC\C*CbA0BB$C&C#?A?X APrCBt@ C<B@VC@(xBB^CHBQB@(A+CB@}C7C`A BBCBBABB(BBABBB(A`BCB A'CBCC0CC& C,CBCBBpBB0|CBBB!SC ABhBE BBC!C(BMCB=CmCLB#CICBBBCpLBABZCB9BBBCpD|C.CB8CCC BCBB,C BB*C`AC? C@BBABpABB@AADCBBcCC8C C0CBpAC@@PBCBC=CB`BYC@ABBCAB<HBCBCTBS&BAA0B?.CBB0BBCBBBBKCBBBtB5pAACB\PABHB)C ABCLBB@BAA BhCA CB(AB8BKT(A)BnCA`BBCBPLA|B$BAB@@ACB<BBx8B@<CnC2C4BBCB A CB"tB@4`XBFCAJ1CB3CPCB CB/@? CBA CPCtBCBBA C@0$CBBAA C/AD.iC;C@AABBCQAXBDCBAXBBABBBxBBLBA@C A@BCBB4B>CBHBxCCB(B@HBABMCB0B`,BBA BPBOCPtCCBBCBN BCpCBN,$CBCBBhBCC@B8,0C@@@BB`CB@0ABACC6Z@BChB`ACC5C Bhlf-CBAB@AB@B6CCBAB B@@ CBxBiCB8B|@@C8C4CBBBCC( BBXBxBAC C`BC BBCXCC@AB8B@BBBAC4BABtB C,CCA7hBXALCB4BHC<8B ABCBAgB4BBC(CHBC BDAh CC!ChB8B-C@'C B C=CAABB0A!CC-CBKCMC BCBBXC`A@AB@@ABtB/C$DDBBhC0C@BHC AJCpBtABB]1BCAACHB,BpB4B *CTBAhDBHBKTBB(CBBA@:CB)CB@BhBAhBE`BB|BAT\A0ACLCBAdA;C ABBAC@BpACBB@ABBB@BC1CVC@HCBt;CBXGCBBCBB.BBBB ]CB4,CB$BBB]CBCBd^BB5!CB AGCvC@ABPeCB!Cl@B]CBBBVS(C@A0B`BBBC>CHBB.C`8oCkA@lBC @C\CBBCCB PClBB"CCBzCB`B9CCCA{CCBHB@|COCCBBBBBdBBBB,BBB3CCC7 C_CB0AA45CBCDBD4BJCB-C?BtJC CC.CT@C`T@1C7C(@ @@pB8BTBAB{BOCBFCl (APBGC@pBpABDCB(B:CACC\B0A0CB.C0xB!0BCBBdFC Bd /BBCLBBICA3ABA PBdBaW(_C0B BBHB[BB\Ae0BCBAv BBBBAPi$CBbBBCBpAAA(BCBB(BDB9BC|$BCA,BBBBALBBBB3C A C C CBXBCvCBnCA?C*C.xEC\@C@B+CCkdC[CCB>CCAC1BC>C B OCBB0BBLC BBB@A$B BuCCBB,BABB@%C CZCBT{CBCABPA@CCpC C FCpBB\CB BtC6CTCBB28lCvCCB CBHC CB F@@A$B"C 3C@AB@nECB@BAXCCBLBhBBBB)C(BBPAB6C@AABYCC;ClPB8@ ABBhBABC BPA:A BBBCCBTB&BCBBB|BpA+CBPBACCDYCBB5 ltBCxCB$BlC@BBC`'0LBBDBCCyx@A-C`B C CByCd Cp0B(C<MPBBBBB@BBB@lBiC@ZCtBBtBdBCLBRC0B CClCBARCBdBNCB8,BCAABBBPCO:C@CBCAB BQC2CBTA`AB0B"C0AA+CAHBAB4BB@ CClBB`BBBACCA BA CBBBCBB@BPBBB$@CvCCBSCdBdBB X|BPABGC4(BA_CB C4BLTB=CBB(B!CgCCBTBB CCB\`BBXCBtBBBBAA@CBLBxBB%CAB B@+CC 0ABX2CllCCB"CBXBAXB2CxBBpBpABrCRpC.CAABD CAAB?+tB1C"CxBHBABzCfC$B 4BCLCACBBBBBABkC@BA(A A BBhB$LBBBB?@0BBP|BCBGClBCCCB|bCBBA3CBCHCBABB\A ApApASC@C<@@PALBD@@@RCBdBpB?ABsBABCAPA0\tBB5CCh<B@lBC B? CBBPBAtBBXBB?BaCBA5C@ ZC@5CB-BPA CB0BpLAhB B CACMC C@BBNCBBB'C28BLCB@0`ABTB@ABB8BBC?pB/CBP`BB'BC`BBBhBBB@xB|BgC7CABBBpTC`CA BBCBHBgCCA@zLB BBTBCBtBA @lBBABB"B C@A@4ACBBBA4BBA`BB C@C@BABC\B8]CCBAP5 CBC B2ABABBBPBB"CtB08B$CB"A>CBpB@@C$HBpA$TBBlBBCjCC BBPB,BCACdCp?BALC@AAB\CB8BAKC CpBTB0lCBPB$BLCBBB#pACpBBBAhBCBB"C$0AYC\TB@B,@@BoWC.BBF'CB4B@8C:CCA@AAB@BBBBBCBCRC? B CB(x@$`ABCBXBpCBCBBp(@]CTB*C*(BCC CPT#CYC"C7CB1C<PA C@BB:BxA@APA8B=1C@B!CB8B@CXlCChC|BpwCB A*BBBA*CAAdBBAB9CBBABC A BtCC8lC ABB0ABBsCBBCB~CB`ABB A ABBBx`BBhBB@BABVC CsCPBCACPBB1CCBZPBAB oCNC< |B`BlBAA.C@C,ZCB B]C wC@@BLBCBK(BBC;C`ApAB0B3CBBBA8CtPB*CBBHB?C`LBHCCA"C %C7CCBCC`AECBB0AtBA@AABy0\ BB8C,0@CCB5Cl CLCBCCC>@B$BBAP|:CAB,CBB@AGCXB/BC,B0BB,P|B41@B%pBBB^CBHB@PB0BBBB@BdBBAC BCC0C6C@CR-CB@@HB?1%CBAICBCB@!B4BBACjPB(B"CC@BBCABC:CAP~BBHC9CPACB ABlB@B(C7C;C@ECBBA(B)CHBACBpbPBBpBBhPBBBtBCCBA$B<oPpCC'BCBBBB CPAA,BDBB@CBODBDBC@@@tB@DBD BDBCBBA CBAHB@C(B2CClP-TC@BPABABAlC@CB>CB@@TAXBBLBA CC(BB PABSAp(CCXsC3CB,BB CABC;@ACB(CCA@BBCBA CBBAAB-CB,BBA@BBB(pB-YCBBBC@BBAPAB9CCpBBPBDB|BB&BCC,BL ABP ;CCC>CBp4BB8BAAVCApA@ZBdB;C05BBHB+CCB4@@@BpBCBBB_CB.8B@@0AB\B}PBNCC ,@ }CBB BB^4CB4BBh D4B`@BB%ChB7`B8BB\Bp@0BBBBdBC BBC-CB@HFBABA C|BBBTlB,4BApA\BB2B(BBBB0? BPBBTC,B<]BDTBCCCCB|>CRC6C4`4B`ABPCBBC,C`?8B5C@PtBCC0BBAxXBBBA C`ACCBAABCB B@B?,0BBYCB5B2CBBCd@C$B&CB  'C8B(B"0B,dABA<B7C'CC$TB6BYCPB/C BCC`BBCAzCC%ZACB=C CC@C|BBBB6CCB@2,BCBBpBC-C B3BgC:CxBCeC(@,p$BhCPBdBPAUBPA| CB0CBZPABC,B[CsC0B0CAB B*ACCCA@BBCBA<.C@PABB`BCBA$B@a$CCPA8C4CB CBBdC\B0CBECA?pABB BBPBB~ABBBAXBAGC BBBBZBB.CBC,CCCA0XBAA|HClB&CAp5A$BBtBLCB%CCpB0? BppCzCKBAMCA BACBCpBBB&CC8BPBCABB@B@'CACB@<pB ChBCABCB(BP08BB/CBrBxB$CBBVCcCBC AC0A,CB?YBp-C4BdBpBBtB@PAtP)dC s8FCp{C2C AtC`A$4B B pCTC|CABB0@B|BTBBC+C3ChBClCQ@rCBA $C,BCT8BBC`@@ACPACBX(BCLBvBBPBC=CB ABB CFCdBBC@CCBECBBB C CBB?BB`BCCB,F|BtCm7B/CUCCB$pACsCBAtlB@8B/C8CBJA0|B4C0\CC CBC4AB+BDBP`B?BC$ BBBCDBB0BpBC/0BC0BB0AC^CBBpBCA@CABC8B@CCH\B@@CCB'CHBBDBdBLBAlB$B9CB$+C #BCCC%BBBBxB BBB$BC@ABABCdCQC CLB1PBMC1CBl\B CPDBpLC{C(XxB0BB3CB(BB0BC*CA4BBC$BBCBd;CBeC$B$6CBAB?lBCB-BlC0 B\B,$(IBC0A8BtBPAC tBBBT?CBBECAPBB`BACCCFC@BBBAA|BCC(BABBBBp=hCC`2CdBC;CCClBC$C CCx@0B ABcpBBCBBC0H$BhB`CB$)C@A`BBXAgpC!CB,BB?lBBHBhBBBB*LBBBA|B$BCBCA4BBBB Bx C7C#"C8CB,AC BA B@@@&B(BBIC/C RLB%CAB"C`BDBBB@YBB*CBBBBBB($BBB CHCPBB(\BCBBBpde;CGC2BNCAbCAB@c CHCTBTB BBACrC#C,BC@B|BCCWCixBgCCDBB`CCBAPBB%CCBBB(CABHHCdBMCbCB,BBxB|BBCBBA CC@CBCB@C@PApB4CB@B;@@<PBtB0CtBLPA7 B4CtBCcC!C4B:CN0Bx`BBHBBT8B#@BBBBACADBBBA%HB4 BBBxBBApxCBABPLICB@DB0B`AnCB|B`ABB0BhBB_CAhBBB AA ABnClBBAA B4 AwC6@B&CaCBJC'C6)BCdBGA`B5ARC8C.CAAB*CBl0B8CBg,BB)CCYACBAHBBAp ?0CA@ptBBBB8BCB4Bh%C.C=CBXBBBpA ABdCA CARlBBB,*CC%CBB@ALhBB *CCCB@TB$CH3CqCOCBB\B CBB#HDBMC@BA`DB,B4BB|BB&CB@BBBCABBCBBBHA`BCPABC@BSxB?&C$BAC@Bt@BAABBBB4B@ABLB&dBrCA,BICB C@@#CAC0CB@C'CBdBR~lB>CBBBC,BCAPAAABhB4xBB(C`C4B BBCB|BCDBBB BBBAA\BB<ABB=CCABC?C,BCNCCABp`@\@%CAApBCCIC4BBxB`B!C3CBtBC4C? BhBBBFyAB B@ABBP;\ BCA;CABBC@Cp@@cChCCA|BBCB>BBCCB(.CB CP.HBeCA&(BpBxBB<HXBKCCtB CIC$CBBCB(BC|BBBCACE AOC>ChBBpA6C CCB1C`@(C@BCCAC0AB`ABC`BxBBBC0@hBjCLBAtB:|C@ABBB@,B CBBBAAXBAABHBB/CB\&/CBBZ@CTBCAR@AhBB<@B`CB:CB cCBCA@CBCCB4C C@@@C]C@hBBO|BbCBBL*BDBACC|BXCBAB@`B"BBBIC{CBBB CpBPABBD@0APgC ABB9h"C!CHBBCAAB@BBTC)C,BBxB `BTBCABKCBBBJACAC9CBxBB4dAtB"CP6pPBpBB@C BHXB@BAA@ C`A|KCA,BdB BB?`@@hp) CBAB6ACB BC&4tBBB@,;C7C ,C0pB@&BBB+BCBaC BBC A C)C]CnCBB CA@BBBBX@CCXdB08UCB\BCBBXBBLBLBAB`AtBB A8B@ B,8`hBBP|@ACXB?C?BuCpBXABpPCGCCAhCRC`BB4C`B^C\BtBhB1C.CBBhTBGCCB=BFCBBBBB dABBL!@BJ`BzCCsDBBHBBB4CBxBCdB| BBBMCLCBACBBBAACpPA2CB C0C 8B$BXACPAx BBH^ChBCB\B8BAB`AAB4XB,CT r UCC0B4B(BBB0AC@@4CAgCBB@ CCBBA@BhBABLCL8BCBA(BCC@B8xB'C$BdBDBhBBc$UChB8_PCICC@ACC<>@VCAB*C`BBBAx CtBC C(BPABABBPCDBBCBA4BB'CFC B[ CdCBp8BBC)CQB`aCBBgCBA<<CH@B\B<BA@tB BBBCdBBC@@(B CAAB.*ACpl0BXCCACBBdBB A2CBtKC5C $BB|B@d5C@B B]CAB8@lBB0PCC&@BpBBB@B,C3CX)C cCOCA 8B\BBHCCBBA'CA BPAAB<BB|\BC'CC#BCCGClhBBB`ACDBCDC= C4B>CBABBp8B;CB0BCBVTBBtB@ABLB@@BxBCfCBBBDBBBA\8BPA@0AB#B@@`B`BA CVC C+CCB@B<BCCHBCCxBBmC,BC@B@AXBBA CCGCBtBBTBB4C4BBBB ClBDBA(C0@@AbC $BAcCC`AB0ABEC0ApBB=CZC;CBB C.C CAA4CB0BAB4BbCC@@@`B&CB0dABBBASC0BABB CBB4>C`lB8C4>CCACBBDB/AABcC(CBBPB@mC}CCB@(AlB BB|$/CB$BxA\BAB BCB(CAA3C,HB@@@BCA C#CCBBdCALB CZCALBBA$BBPABBWCAAJCXBB?dBnCBLB4C,@BBxBA;B BvCBABBHBBBBB0BBCBDB(BBLBPC0BCPBrBB$$CB)0ATB@A@`DHpA@ABH2XdBCB CBA4 CBIC(?sC)Co,CLCBBSAB>CBCpA!$BRCJCB CGCC BB|(C@@BAh4ChlBBPB@CHBBBB8Cp.p BB8BtBBp0AB ABB`(BJB(B@ArBTBB C@B"C BTBAtBpBkCBXA@QCCB@eCB8B8BB@A@:,BBCBAB @4B@APBB1B@ ACHBCBPA0BB"C BA pAB`BB8CC,BBICBB@`ABB@ BAA)CB+t4C\B9CB6CAB0BlBBBB?dBB88BpA\BHCBlBABBdBAB@MC?C`ALCS($B`ABBhC@@8B BCpAB"BBA ABB!,B@B~C@B,CH8BB\B`BDBC"CB`AC`ALBnC`Bl4CB B4/0BBAPA B 0BBxB,BBB Bd %CPBtBBBBBP'B@A C8CC!hCB&CABXBpAPCxB7CAFJCCBBAB^CB CC@B@B[CCRAB8TCC`B@B$A`LB@B4AB@@lpABCd`BAICp@BCWCBC$hBPAAC&@C@AC CBMChB\BBBCAhBBCCBPB B/C@PBXB6C@BXB@B+CpCXB`B CCBCC C$AChBB0 hBPXBA LB0AABBAFBCB0ABdBBABTBqCsB"CCBAPAA0A=Cx%CA@!CBCBCAcC=CCB@hBBANCBLBAA@6CC0B\B@@AC@pbC0ACB(CBB A!CB|BBCvC@CBACCpB,BLBC&B BC B0B4BC@BACBhBBYC)CBL0C(B%CDBC4B|CC|CPBBBCBAB@C4C BBBA|$BBlCB@A@9C,8ECBC@AABC1CHBBABB@@BA@@B]CpB@C, AAp|BCBBj@AB8B@@BDB(CBdCBBCB0A@C CeCGC ApABCA BBBC .CC6C$CA?CC CBCAC@rpBB~"CQCBZC@HBBBBL*CB|'CCBClB$C|BB4CBB]BUC"CBtBP@@AoCBHC)AB6CBB: BABBB B4BB4BlBBHBdBBGC *ACCCB@BZCCAlBBCBCBXBAC ACBCB`A0yC(CBBFChABBCB^C`ABBB BLBBH?BCCC$BACtBA0DBwC#CB@BDCBC$:CB3C C,2LBBBBC~CBH@BBXB(CBpXBpABBB0x\llBC BlB*CC0CTB8BACBhBBxBB@@3CBB$xBABHB.BBC_CA4B@ABeC8BCxB(BSAB CBBAAB BABC`ABCApB,CCC0B? B(BB|BCBAC@1CB"A`tAB6BABBPC&CBB8AdDB%CfC@ECCB$ClBxBC0ACBB@HC`B+\@BBLCAlBBBBBB.CBA AL@@,BB@BB BBCBCYC BhBuCBPACA.CAAC(BBFCBBB CBB|BO|BC BhBTCB88DB\B)CAB@A`A4B BA'ChBBB`BQ%CCB\BBBBCBA,B4CLB`Ld\B8B\BMC?CBpoC4,0BXXB#CPXB8BpB|BBzCXhBBCCBXhBPC9C ABh5PAAC@A|@BCCFClBALCBAAB0k)CCDBB]CCPBfCHBP|B$ACLCBBBBB CALBCBBABB@@`BBA<BAClBA#C-CCBBA{BB#CBBCBBBB0B&C%CPABCp@qBBCCBRC BBC@@ FCC"A'B6CCB_CB?BA<ABBACp#BBCABB0ABBBA "CC!@@ACAB$B,BBB0A A -C@ ABcC^CABA$AtB(CAABCA CvC_C#ChBBCB40AC CC:C"BCClBBBlBVCBBBB4BB?CCBB`BAC8CCBBAC lBBBX`A!CKCdYBHC4B-BRCCDBCBBARVtA.CCAB(BDLBBBA1B#C CuCHbB BBC8BABNCB>FC@ABDBBDB BBQCpAAhBBBBBBB CBtB7CBBB:C0BBCAjLBC,C\BRCTBCBB@BdB CBCBLBpB1CBB,BAABBCt0\p4BCCB'C PBCB1,CLBtH`C,BCA:CpAB C CBPBBd( C|CC(BBBA@@AA`ABCBAWC@C8BPBCCBBC@BkCTBLB B;BB4B!wC3CiLBBCBpQCA*CACCC CBCBB C@SC CA4CB CBBBBCLB A`BCB C ClTBBB`BCABBFC%pBCBVCB0BBABBCBBBBAABPCB BB@B'CDBBp}ChCdBBB?<ABXAABA@ABNCBALCPCBCBPBCBxB B/CiC]BBAAChC\@B A`BBB0BBBBB'C@aBBBABLBA(BTBBCAALBPApAC@A?BCBICCBB`CB)CBC4 ABA ChCCBPB BBB |B@@@ CCCA(BB@A7CCB2CBBCBLxLBBCHB AB@CCB `gC8BBCBB7C.?CCB P,BJB@lBB@X@pBACDCxBDC@A\LByC|A@7CCCCAAXBCBBBB4+CB$BB0@84BBBBC C}C7sB BB@GCBB"AC?CABA0BB|BCCBLBC,RC B AwC$CBBCCXBp<0AtC 8AB2BICBCBA@AC@LBBB$AC-CBB0ACJC CB C,C-C@C(BB`BCBBBB CB@ABCAA@BBRCBBCB,4CPBCGCCB$BBB@hBCBeC4B!DCCBBPAABBBBB4BABC$BBBBBd P&C0ACCBDC$BBCC0A)C@BB CLBPPArBCpAC BB{CB<CBACBBBCUCPABERBdBB ABBHC??CCBA BB@$BBlBAC=C@$CRCB C@BB CxABCAB@ x+C@?BBBBBPABBDBCBUCBCBhBBA-C!CA\`C4BBA2?pA@=CABB\(BB'CC3CnCBB@CB\BBGCB%CBABB$B`nC$C%CAWB uCChBBB C@@ BABBB"CCUC `BAB@BCApB CCB<'B@5B&C5LBBB44RCBpBCACCCMCCBHBpATBBlB|BC8B`B8CC}CB CBB|TPCBLBBBC/CBB|BBBBHC\PBBC9thBCBAA8BB\ CCPBB-C(xBBABB\CWCCNCC; BFCBA0KCBC&CBBBBCBABlAB1B,CB~CB6BBuCBCBALBBQC0CxBBBB@@BB7CBRB+CCBBBBPCBCtBRCpBPBlCZCCB+C-CABCtCB" C.CBBCBh?`CH\B!C9CHHB$+CA(AA1C0:C|CpBBBlB AB CB@AdC BCCpBAC C 9C(BkCCJxB,CXBCAA0ABA@AhB/CBC?CB@BHCBAACCpBB1TBA AB.C4BCClBB CB C8BxB`BC(BlBCCTBAC\A(LCBB"CBqC@BAC8C A(BADCBKCC?ABB@BAC@ xBxB@Cox CBBB|@DABCBBB*CC0ACmCCdB CBBBPC@A CBA CAx@BCC$BDB C\CBD4BBDBB B"C8B9CWC.B CBBhBB (BBA@%C`KABlBBB\BBUB LP@@p2dC C?ClBB0cC BB`BUCAC8ABWCBBCBABCBBCBNCECBBCA@@DBCxBLBBB`BXBLB%BtCBHCBCB$BBdBECB CpHCCB8BpA ACC0BPBaChBBA@A PBABAB$B6BB CABXCC APBB@(AAHB!dB\"@@BB%C?(BpBTACVCUCCAB@BABPACCCuC BqC.C`BBaC9C BHBBlCB@qCCCCC\%CFCXB8CABB lB$CB*CBP@`AABB1C#C|?@CATCBOCgCABB8BBBXBCBHBAB ZCABBC6HBBB=CAdB$Bh@BaC!CPACAC-@@C@AP,BBB@C/CCDBY>BDCB` B0A7C2C( B`Bt\BCAxBX\CB8BCpBB,`@(BAxPB@KCB4B)CdBHBdBCB2CNC4BtB$CdB PBC1C CA@ BhCBBBtB8CB[<C(C(ALB_CwC-CTB2Ct@BWC>CC@p|CDBB,BBdCBB@A(CpBCBC ,BBKCFC XB@C(C BBAB8BABC,B}CPBB@BpwC$|ATCABCB@B8B|BPB"@CCC7CB|B8CCxBB@#CBBBC( B>DB$C6C?AdB@@CPA?ACBOCkCQCBB@CCBABBpBBBAA6@BBmCB[CDBB`B$B`BB`BB CB/CB@B()RC!CCB?CAAA8C4CPCAC3B C,BCCB50B0BBPCBBCvCACBC CCAABAB, BB"CACABBBBBChBA\BBCB BBp0BXr$B CCBA0ZCBB@BB=C@B(BAB,BABP4C4CB B4ABDBBxBApBCB$BBB)CCCpBCCBXB<@B`BBB4CDBdB@KCAl$CLBB@pBCBB@AB^CBACB}CB$CBAAABCBCBACYCBA@BBlBAA,TBBBB@@@CATdB'CUCBTB8BTB CCBlCACCCCBDB-CtBjCBC@BB0C CT BTBC\BC@BBA8BBxBAA8C@0B>C48CCCBKC+CB C)C]C4CB'C@BB7CC *$CBwCB|<BCCB@+C:@CBCB BCC[CBBB'CABBCB{CC CxBB CqCHBBCBBBBABA0BpBBC0B(ByCBABBP CA$@ABCB4@B@ABBBCBB@C`BtB@@0BpACA`C8]C\ChCCAB%@BB C< CBBB`BB,B;@BCC0BB>@+C"CC(BBCCBBBxXCC@@AB0ABB@CBlBB C C1CCCLABlBCBBBL`B:C$ B CBXBXB%CBB=BpPAXBCB,C0Bh|AdBAC-C@&CAkCBBB C4BOCR0BBBB+CBBACB-CACPBT-CkC C PABB,@CqCBBBfC%C?CBB@<vCPBCoCLB@C,CCABCCAHBAp CwChCC8CA4B+C5C4CB@ACBB6C3C7CB0Bl@I&CBCBdpCB BB@BPA|BAABC:CC A4CBCB$BXCBCpBAPAACBC\C_C0BCtBB<BB 3A4CtBBsAoCCBC8BB/CBBPBAB CBPAA8C@BBC7C'CCDBiC>CB4BBFClCB@BC@tH`B`CQCB$CCAhBB"CB?CBABABBBCA`@@AlBBBwCD0ABAA8BBBA@C&C6CpB@PKB>CCB ACBBBBB4*CCCB]BCC>C7CBB*BCB@4BDB@CCBA0C>OCB@ABCCC}CBCBBBrCBBCTBfCCABPCBC&CBBjCC_CC BT`AAB A@AB`ARC`ACA,B@#Cd2CBBABCB@FCCBCC@AAyCBhB@BABBAB(C5CBmCBPBB BBB$Bh\BAB CKCCBABBB4BBBBHBXBCBBECBlBBBACCCCtCTBB%C>CBxTBl>CBUCCdB@>CBBBD BPAB-CWC`mCB C@0AXC CBBB ANCB/CBBlBPA,BBTBvCxB3CBB[CBCB .C:ClBB AC$CAC`]CB`A-CBBGC<B5CCC@]CBA%pA`BJCACTBC C=A@@BC`0AB|BBBA5CC,CA6CACB@TB CJCBTBC|BBC\B@CWCtClB.CBBB|BCPBCAB-ClBCBA*`BB@`B>CHCBCCqC&XxBA8CCBCpBBEC@A@ CzCB B5CC?CC@AABBBBA(BBBCBBB0BFC10CrCCPAC CBBBCBBBPABBTB8C1CBBSCBCCBCCXB%D 8B4CBAC ACBCB ABrCBBC B+CCpA@BBC@CCBCvCC4BGCBClB CBBBBhBBBBACB1C@B@ByC A ApB|CiCAlhBrC(BPBC@CA:CCPBC8B`lBBClCCBAB7CCBBABCBBCBBpATByC%CChB8CKCtBVC(B'CBB*CBC+CBC<A4BB&CVCBBBBCB6CCd|B7CHBPBLBABAAAB0$CdCACCB_BDB>CBCA$%CoCCCACCDC1CA,B%CAB@BCnCC0BjCB)C`CB8ACBBlC`CukCCUCCCB CDh{CBA`CCCvC\BB-CBcCCBCCB`BpBBCBCBBpCRClCC@@AATtBB$CBOC@PABH)CA0BbCBxB\CjC0ACCC BCBCB5@CPCeCCAAhBpAC+CChBABeC[CBoCAC`APB(B$BCC B?LBxBBBCA`sCCBBB CC BtCB@NCBpCCKCABpACCB C`A C_CtCC^C'C0AgCJCBCHBpC`CBCC*ClC C`CCBCCB0B0B*CCBC)CXBBCC ]C%CtBBUC8BCC/CBCA@BB'C~C[CcC=CTBDBbCCB XABwCCC^CtAKC3CCCkCCBtBaCBBBtBCCJC,BBB`ChBBBCCECCCCCBACPBBgCgCDCB CDCCBBtBxBBCCfCB CTBEC@ABJCBCB@BCCCtBCAdBB$B/CCBC+C-CtCDTCFCAYCVCBBCBBCCC CB@|ClCAC+CBCCpAC,CC5CCCCpBA\C(BkCC9CBBB BC'CCC,B;CJC(C0BA CGCC@CBBCC@AaCAdCC,BCCfCBBBCCABcC_C CEC|B]CCBCMCBPABBC&CBCCBDBbC.C>ClCA,BBBBCKCCBpA`AkCdBC$BCBCCBhCCB*CB BBLCNCC CC>C(BSCCBB|B4CLC@CB4BCBCC`CBiCCA*C`C:CBC CACB0BKCAACBCBCC\BB#C AOC1C C CC(BwC;CBWCgCBBCBaCB~C?CBgCBBBrC`CCCPBC;CmC|CCCCBBCC]CCvCCUCBBCACBICCCBTC?C BgCBFCCCCCBBtC XBC5C BCkCBBMCCCNCHBCC)BC8CCCBCC]`CBC`C6CADBCQCCB<88C]CCCB4CWCC8CAdCC2C@@A@vCCCB4BCCCBA%CCFCXCbCCB[CC CVCBB$BBC\CpCC`ABRCCB@0BCtBBCASCA.CB4BB&CA`SC@AALBBCA+C#CBHBACCBBBC/CqCAB?CACtCC~C$BBCBPBCCXBB8BBBrC.CBBCA$B#CTCCCCQCB CBC CBhCBCBCbC(C4lBCCfC4CLBTBBBZCCB8BLBB @)CpCAB`C}CCBCXCICTCyC(CB_C;CBCBCCAC CA(CCCCuC0BCB:CGCCCACBBCCC`C$CDCBB>CCCCC?C`CGCQC>C}CtBCBBAB`CRCBCuCBCBC C8C?CC CCWCCB$BCByCkCCC?CABCC!CC C+CJCBBBXB-CCBDCCMCBdAVCCBC?CC A8BBBBClCBB1CBAOCxCBBDBCCCBBB=CCCCBB%C'C&CCCBeC!CCXCBOCCABCCiCCCB8BCB?C BBpC BnC}CABCBB[C CCC CB AiChC]CHCCBbCCyCBCBXBCCBBBCCCBCBeC!CBBBXBCeC,C CMCC$CBBBBCBC(C.CCC'CCBCCCrCCB@CCfCZC9CCCFClCJCC%C>CCvCHB|8C{CCCBC/CP|CiC)ChCCBB~CBArCCuC%C@@NCBCC@`CGCCCB@B2CCCCiCCB4C C)CCCCCCTBRCsCjCCD`BBCBCCB0B2CCCCMC>CCCcCYCKCC,CCCOCqCC,CB CCCC B@BDCCCLCCtBBCBfCwCBBCCACB5CCDCCC CCC&CzCC,CCC@CCBPACCCCACjCBCHC&CtCBBCCCC\CBdBNCBBCC%CBB%C;C{CABAPBByCX CCtBJC4CC`BBB2C3CTBA@CC1C0BTBC CBHCCX`A CBB AICBXBBlHfCB? C)C-C@#CC,BBC&/CBAzCBCBdCC=C:CCCABABCCC@@,8CBpACCtCB4BRCXC:C@ CDCCCC@oC0B CICBCBhCB(C0BPACC9CB,BCDtB XBLC^CCBICCBHC`C"CCCCiCB@CBACC8BBCCwCC)CCB:CCCCECCCyCCBCBVC,C1C,CBBC*CBECBCB2CCBCCC:C1CBCBCCC.CBPCwCsC CC3CjC CCBNCCBCDCCCC~CeCCCCCBB+CBCC;CwCC~CCGCBCACC>CBCC!CDCB, C&CCECABLC A$BCCBBBBCtBBpBBBBBBCCrCCC-CC|BCBVCGCCBBB\B@WCBC;CB$BCB7CCB8CBCCl?CcC@@(BBlBlB*CdB4C@AfCCCBAICCCbCDCC(ChC0BmCBBC CFCB BDCB"CBABPCBBbCB BBSCxC@+CC*CB2CCCBB9CCtC^CCBVCB5CBBCBBBCACCCBZCAXCC}CCAA8CCBC.CACCCBCBBBCBC CCC%ClBjCACC C CB@`CCBCCLCCCC C?AB0CCwCFCBCCBB@CNCCmCBA@CCBCXBBB@EC\CB$BOCCCCC?CC CBKCpBPCC_CZCB-C<BwCC fCCACC\BBBCCA>CCBC6C6CCCC,BVCC;CBC{C]CBBB>CCBCCCqCBBB8BCdCjCBC2CBIC|B CCBHCCdBCBBCC7C&CBHBABqC/CqCCBTC4CZCCBC6C2CC@@ CCvCCwC@CCCC`C_CCC@BBCCdCBCCCCOClC}CBlCCBCWCCCC.C?CyCCCCBCC,C CCB[CCCC9C0C-CCC;CBBBuCCCyCCCCCdCBCCC,CdB[CCCCXXBBCkCCUC?CfCC|ClC CACcCCCaCCCB/CzCCCWCICCCCCXCCC5CCC/C"C@D~CCCbCBAC^CCBCiCCCCJCBBCCC%CCCCCB$CCBCCCCCCDCCAFCCCCB>CCCDCCC4CCCCCaCCrCBICCCCCCBC0CCC0CCCCCCCCCVCKCCCCCBACCCCCCCBBC4CCCACC^CCC}CB2CBCCCCCCCCCCC@DCCCfCdCBCCWCCVCiC3CCZCCCIC'CCCCCCCCCCCCCxCXBCCCCkCbCzCCCCBBfCCCCCCCCCBC!CCCC?COCYCTBCBCB'CUCQCwCBBKC(BqCdCB|B"CBjCB|CCFCA(C`A/CSC0BBxBBCClB7CBBC|CBXpCCC|CCAlB@CnCbCCCCBECZCC3C,B +CCGC0ACBAC(BC CC0C$CCBWCB CCChCAAZCfCCCxBCCOCGCLBBB@CCCC-CQCwCCCCCBCBBCLBPCTC C0CmCCCCA@"CACCCQCC5CBABBC@BBCCB@ACCCBBCCCC0BCCCCLCPCC.CCC7C6CVCDBCRCCqCBmCCBClCCC?CBBkCSCCKCgCCCAxCC BCCCC CC\CCBBCoC1CCXBAC2CBsCBCC-CRCCCwCCRC.C_CCCCC6CCCCB CCCBuCCCC|CCCB?CCBCCHCdCC4BQCCCCBCRCCBqCCB@@BCCCBBbCBC%CTCQCYCsCCCC@CCCCsCDCaCxB CCCCC C@C\CsCCCBCmC CBFCpCCCtCyCCChCBBCCBC6CCmCBRCCCCJCBfCCB[CC1CCCCQCBCBdB`ByCB@DbCCC>CCCCC]CCCuCCCrC+C.CiCCCCBCCCCBCCSCCCC?ChChCCeCBBCCDCCC3CBCCCCCCCCCCDCC_CCC DCCCC9CCCCCC(CCC@ DCCCCgCCDCeCtCECC,CBBpBCCC{CACQCCCKC@hC7CBCBC`CB*CBCCCCC`AA#CBBCC C8BBCBA&C@CjCuCBC4C0C}CC=CgCD;C)C]CxB9CMC7CCCBCCCC#CmChCzCPCC9CC]CC.CC'CCBCCCsC'CHBWCCTCqCDCxCACGC3C(CB.CBB$ChCBBnC4CjCCC@pCArCbCECzCB4CfCCCyC,CBCBCBbCPCaC CgCCCfCBdCChCuC{CBlCCBBCwCCGC@@CC~CC~CBCCwCNCpCBDCCWCC_C CB:CCCOCB?BmC CCB+CCCVChCCyCClC CC C%CCCCDECICC(CCaCCCCCCCBCCCCC DCB1C$CCCCCCCNCjCJCCVC'CCCCCC9CGCC_CCCoCCCCBCACwCqCDCCGCCDCCCCCCsCPCCCCCCCCeCCCC=CCCqCCCCCCChCCCCCBCC:CsCCCDCCfCCCC`CUCCCCCDCCC@CCCtCCC CCCJCCCCCCC@ DCC]CC}CCCjCCC!CwCCDCCBCCCCCCDCCCCJCC"CCxCCCCCCCCCwCCCCCCCnCClC DDCCzCCCCCCCCCCCD/DC@DCCCCCDCCDCCCCCCCDD}CBCC DCC^CCC(CC~CCCCDCCCCC}CCCxC{CCD@ DCCCCCCCCCdCCCCCCCDCCCCCCCCCCCDCCCCCCCCCDCC DCC'DCCCvCCCCCCCCCCCDCDCCCDD@&DCCCCCCCDCCCC'DCC@DCD@DCCC DCDCCCCC@DCCCCCCC-DCCCCCD@DCCCCCC\CCC@DCDDCCCDDCCCCfCCCCCCCDqCCDCCCCDCCCDD@$DDCC@DCCDCCDCD*DCCDDDCC@ DCCC$DCC!D0D@DDCCCCC@DCCDCD@DCD1DDCCCCD@.DDDC D2DCCCCC@!DAD1DBDCC@DCCD D@'DCDCC D.D@?DCCCC D-DDCDC D'DCCCCC@]DD+D@DCCDCDBDCC@DD/DDC%DCD DCCDDD)DDCC@D@D@D DC@@D>DDCDCDCCC@>DDDDDD!DD1DC@-D DDD@"DD DDUDD4D*DCC@!DD8DBD@ DCCCDDCD!D"DDDD.DD@D0D@ DD@DC#D6D6DC D9DDMDkD1D DCCD@2D@*D5DCD@?D9D@)D@D@DC@D@DD@D@9DCC@DD%D D@DGD@lD*DDD%DDD.DDD@FD@&D;D.DD@ D(D*D@D@BDDC&DD.DLDlD@RD2DLD@HD@2DGD=DD9D@'DWDFDlD@$D@#DCCXCCnCCTCBB/CA^CCC8CC-CaCCCLB4CnCCC"CCC[CoCCCCCCAB CoCC9CCCCBCC[CCBC DkC9C6CCCCsC}CCCBvC]CCCCBCDC_CoCBBC`C}CCCyCC5C^CCCC5CBCCCCCCCCCCCCDC[CC?C8CCCC7CCFCICCCBCCLCC"CCCCCCCBCqCCDCCCC]C DC"CCCCCCCCCCCC0CD+C%CCCCCxCCC*CCCCCdCyCCCCDCCC`CCCCCDC DCCDD@D@-DC@DHDDCDC-D'DD@"D/DD@D0DDDDC@DDDD@4DD5D$D@DCDCDD D D-DDEDTD@9DCCD@CD-D)D1D.D@&D>D5D@!DCD@FD$DDFDDDD/D?D0D DD@ D@>D@\DCDDCDD9DDDC@D6D$D!D@#D@D@)D$DD@.DD@,D@D9D7D@9DD@7D@D@!DD-DCD%DD#DD&DDDDCDED@ODD@D8D@=DLD^DgDPDaD0D)DIDGDRDEDIDBDODD%DYDOD{D@hD@2DLDSD@:DWD`DXD@"DYDQDND@D[DUDsD2DSDjD>D-D@@D@HDD@eD@]DWDNDD D@D-DjD@_DKDKDcDNDIDRD@"DbD@eD`DOD@@D(DtDdDLD@+D@SD4DADgDJD>DyD@D@NDOD@XDdD>D=D3DDODoDzD{DID6DD*DDcDyD`DkD@)D@_D?DcD`DCD^DD^DJDcD@MDwDDTD@RD@rD@bD@YDDdDtDeD@5D@-DpD}DDfDDD DtDbDlDD@tDkD@qD@NDhD|D@SD@LDDD DTDdD]DgDD`D@D@MDJDmD@RDbDnDDD DNDqDxD@bDDcD@}DyD`D@sD@TDDDD`DRD@~DD@eD@WDbDuD DeDDDDTDND@]DDDRDDDDD@DDgD DD@wDqDD@nDnD DpDbD`DeDD@D`DDDD|DzD~D`DDtDDfD`DDD@DDlDzDDDnD`DD DDDVDJD{DD`D DDwDD`D@vD`DDDDDD D`DDDvDoD D@D`DD{D`DD`D D@DDD@DD@D@D@D`DD`DD DDD DzD D@D@D DDDD@DDDD DDDD@bD`DDDDDD@D~D`DDD@DD@xDDDDD D`DDD`DD DDDSD DC0CCCD-DC@DCeCCCdCCDCC!DC D DCCCC@ DCC@DCCCCCDCCCCCCCCCCCCCCCCCC DDCCCCC[CCDDCCCCDDC D@DCTCC DDCCCCCCCDCCD`CCCCCCDCCCCCDCDCCDD@DCDDD@ D]CCCDD/DCC@DCCDC@DDCC@DCDDCCDCCDC@D6DCC#DCC DCC)DCCC@ DCC DDDCDCCCDCC9DC@DDCCC DCC@DCCDD+D@DC@DDC'CCCCCCDDC DCDDCC@DCCDCD.DCD(D DDDCCDCCD5D3D!D%D@DDDD+DC D,DCC@DD#DD*D@D@>DDD1D@DCD DND-D1D+D6D+DD)D@SD"DD(D DD+D7DMDjDDD'DD@PD!D"DBD@;D7DbD@ZD4DiD3DC@HDDDD*D_DlD@2D@6D@8D D@FD1D4D}DD1D@KDCD@D#D@?DODND6DNDD@6D@VDYDBD2DDD@]D@qD@5D3D@LDiD@4D@4D@]D1D\DD@CDLD[DOD@YDoDXD@_D-D~DuDXDWD4DdD@bDCDCD8D@jD.D3DmD^D:DmD`DlDgDGD>DDDED@eD>DdDWDbD@\DCDhD@vDD1D?DZDD@wDRD2DiD:DIDUD@8D?DPD/D DDND@_DGD@#D@KD`D@D@ODxD`DXD2D1DrDD?D@RD?D%D@tDmD`D`DDoD@HDpDpDVDcDeDxD@mDfDD@kD@pDXDDRDmD@zD@lDDnD@^DLDDD`DzD@DD`D@ZD@\D^DoDbDYDDgDtD@dDXDhD@xDDwD DsD_DzD4D@qD@DqD@=D@nDiD@iDD}DDDbD@}DD`DSD@DyDD@~DCDD`DXDSD@DDDD9D`DD@D`D`DvD@D\D@tDD`DzD@D{D|D`D DD D D_DDDDD@D~D@zD DDD|DgD`DD[D D@DDDdDdDyDDD`D DD@D|D`DuD`DDDDDDDoD`DDDzD DD DDD~D@DD DDDDDD@DDDDDD DD@DDDD@D@DoD DDDD@DD@DD`DD@D DD`D`D D`DDD DDD@DD@DDDD`DD DDDD DDDD@D DD`DDD D D@DDD`DDD`D@DD`D DDD`DDDDDDD DDDDDD DD D@DDDD DDDDD DDD D@DD@DDDDD`D@D@D@DDD DDDDDDD@D DD DD`DD DDDDDD@D`D DDD`DDD D@D`D DDDDDDDDDD@DD`D`DDDD D@D@D@DD`DDDDDDDD DD DDDDD DD`DDDD`DDDD DD DD`DDDDDDDDDDD`DDD@DDDDDD`DDDDDDDDD+DC+DCD DDCDCCCDCCD#D4DDCDCCC@)DC#D"DCCCDC(D@ DC@DCC*DC@D DCC9DCC3DCCD DDGDCC.DCCD DD D DC@DDD@ DCDDCD D@DCCCD@6D@-DD-D@DD@DD!D%DD@DD@DHDCD@ DCCC#DLDDDC D@DiDCD.DDC%D D@/D7DQD D@0DBDDDDDC@-DD#D@DD8D9D;D.D"D"DYD-D1DD@HD D@DD!DbDwDDDCCDfDIDFD.DCDSD@GD@DCCC-D@EDD8DED$D]D@D@D5DDD#D(D;D%DDCDlD.D2D@D$D D2D9D@?D@GD DJD@&D@DPDPD2D D@RDDD@(D4D.D#D@#D@D_D>D@+D1D(D?D@DD#DaDhDD@D2D@PDRDEDND#D/D2DPDDD=DCDDDCDODKDKDOD9D@"D@D@7D*D7D@EDCD?D@BDID@aD$DD@6D/D@8D D@/D@?D@JDSDFD@D'DD@;DZD,D;DD2D@D@hD@ODKDD@FD_DdDD@3D3DIDDED DcDVDBDfD2DID[DD8DLD>DQDZDDD@KDMDD;D8D%D+DCD@MDRDbD7D8DbD/DkDID@1DSDCDfDVDpD$DD@CD=D^D`D.D$D~DpD@YDQD5D@PDHD"DED@SD8DoDXD`DpD;DBDLD@?D@:DSDkDDlDZDMD1D?DVD@{DvDNDED\D@fDwDAD_DDDRD5DND@bD@mDtDID=DxDWDsDdDSDRDXDD`D]D6D@7D@KD@D0D5DZD@MD7DD*D@DD>D7D1DGDIDDUDUD2D@RD9D'D(D@ZDVDvD@PDD)D@dDnD@gDWD6D@1DRDrD;DD D:D@7D@BD9D@mD(D7DQDTD@=D@]DIDHDLDHDgDYD:D2DND@AD@GD@TD1D4DLD4D,DIDIDVD@D3D6DeD>DAD@LDD+D`DrDYD@XD>D@CD_DED(D@HD7DiDiD_DCD@=DgD@DPDMD3D@YD@CDDvDKDZD@PDTD@IDYD8DqDxD@TD@WD@wDmD^DcDSD$D@DCD@;DRD D@bD6DFD:DhDND2D@`DvDHDVD@LD@VDpDPDRDFDWD@8D@hDlDLD@D@cD@^D^DD{DhDID/DSD@GDQD^DPDjD^DPDGDIDDDD@aDD^DJDYDTDjDuD@eDDD0DiDD@JDYD]DYDbD`DNDD~DdD`D~D?D9DuDDcDxD@qD DnDXDaDD D D@zDPD@DDtDLDhDmD@yDDtD[DDDDhD@QD\DD}DDnDpD@|DDD@DaD@OD@wDiD@VDqDD[DD@DeD~DD`DMD@EP:E0-Ep)E0E`7E7E7E-E5E01E.Ep4Ep.E2E(E=E0:E2E4E0E@1E6E.E8EP6E7EP5E1Ep1E@=E`7E`1EP;E8E@+E:EP0E@/E)E0E`4EE6E@5E'E`0E;EE;Ep6E%E@E:E`-E-E>EAE;EFE0E@0E@>E6EPAE@8E=E6E@7E`:E9E0=E;E4E0:E0;E@7E6E@+E7E ?E6EP0EPE@7E0E)E%E(E%E`6E:E@1E6E.E.EP8E :E6E5E%E)E/E >Ep8EP.E&E2E4E.E1E9E3E`BEP-E2E)E8E8E=E05E/E:E`CE AE;E8EEP>E@1E=EpEEE`CEDE@IEKEJEPBEEE@JEHEWEGEP=E9EHE=E NEEJELEJEKEDEAEpFEJEOEQEQE`JE`HE0CE@5E`EEP>EJE NEJECEJERE JEIE =E@KEPVEKE`HENEIEEEPE0JEFECE@>EPLE`]EOEEE0EE NE@FEREUEHE`WEJEMENEGEIEPQE`ME@LEPEpUEIEPZEQERE0LEKE@LE GE0EEQEYEYE0YEKEME0OEZEGEOE OEKEHENEMENEQEPEMEMEEEVE@PEPREJE`VEMEMEpGEPKEPEWEOE@NELEIEIE_E SEHEJEPBEPEPEUE?E0QEIEHELEAEEEpVERETEWEHEDEREPOERE\EpVE@=EQEVEOEPELEOETEPLE0IEPKEIEpJEREFE@QE`YELEPFELEJEKE@VEIEJE`TEPTE`PEDEEEPPE\ELECEBEQESEWESEPEPUEBEKENEEE0:E@NEKEJE0HEGEOERE`@EHE NEEJE ;E=EEE`>EEE`FE`?E8EDE`5E@JEFECE`EE0@EP>E@EPFEGELEGE`7E;E`?E :E08E@E7EpEEJEp7E?EFE`5EAEE5EAE>EE@E*EE@:E@9E-E(E#E+E@6Ep3E-E'E&E*EP6E+E*E5E)E0E/E4E'E#EPE`.E4E +EP0E,E"E'E,E0E*EP/E05E!E0E1E.E/E&E/E-Ep*E *E%E%E+EP&E2E0*E@.EE*Ep0E3Ep&E/E E-EE&E,Ep,E`"EP*E.E*E!E"E@!EEP$E)E(E-EPE0EEEEED"DEEDEpEEEEEEEE0EEE D@E EE E0 E EEPE@ E0 E E`DEDEE`EEE EpEE@DEE`EpE@E ED EE EEEE0EE E` E EE`EEEE E@E E EpE E EE E E0EE E EEpEEEEPE E E E E`EEEEEpEE E0EE@EE@EPEPE@EE0E@E0E`EEEP%EEEE`EE@%EE@EEPE $E(EE EEP#EE0(EEE0E%E 'E@*E@Ep(E#EE"EPEp!EE&E E)Ep%EE`E0,E#E`(E%E$E E&E EE1E@-Ep-Ep+EE`E,E)E'E0-E E)E3E$E!E$E*EP/E0E%E3E6E E%E'E'E2Ep+E,E%E0EE`!E`E06E)E-E-E02E8E,E3EpBE0E$E(E5E3E :E4EE`/E1E9E>E 5EP;E8E@5EHE5EAE6E09E/E5E4E9EP>E7E7EE.E DE@E>EP?EEE:EP3E8E 7E:EHEp5E?ECEP>EIEEE EEp;EEEFE`:E:E=EIEPCEPAE7E?E`DE SEYE`DEBECE@=E`AE;E3EMEHEKE:E@NE =E9EEEKEEEGEJEAELE=E`HE BEEEDEAECE=E@EQE@UE`HE>EJEHE HEJEHEBEQENEIEGEAEPBEJE0QEMELE@LEAEMEVEQE NEPSEJEOEFEIEPEbEMETETEQEMEUESE RE0VEPEUENE`QEQEp\EOE@YE0ZEOEVEYEZE RE\EWE[E@^ERE@PEVEYE@REP[ESESE^EcETEREWE`VEYEpLE^E bE`TE@VEPE XE_E\EpLEeEaE`E[E SEWEbE_EZEP^EUETEYE`hE\E0^E \EZE bEbEaE`WEeEcE\E\ENEYEaEVE`_EfEpbEpXE@lEPYEgE TEREpdE`EWEUEhE_E`^EPbEWE0`E0XEPWE@WEdE[EPcEeE^EeE_EpUEaEaEgEgEiE0VEZE_EbE@aEkE fEaEdEWE `EpbEhEhEhE`Ep^EqEdEXEphE`hEcEgE]EpnEfEpWEpXE]EeEqEoE^EUEdEnElEgEPVE\EcE@fE`mE dEPXEWEbEnEcEkE\EPoEcE@]Ep[E _E[EgE@mEpbEfEfE@hEZEcE`EgE0jE ^EeEjEZE[EmE bEiE`EfEptE`iEZEVE@fEeEdEaE XE`ElEhEfE[EXEYEeEfE@]E@bEZE^E`[E\E \EcEXE0_EgE]E_EXE_EfEXEgE`dEaEOEYEnE`fEkEdEPEpXEPmE _EVEgE\EoE0YEWE`EbEbEeE XE@TEUEbE_E@ZE@lE_EaE@TE0WEZEbE@gEaE UEbEcE[ERE`E`E[EeE]ERE@PE`WEMEXE@ZE CEVE_E^EPZEaE`XE[E@WE`\E MEWE@ZEgEiEPE0TE`UE`cEcENEREMEP`E0]E]E]EWELEXEPHEHEQEMESEpNEREPZE@OE0JEPXEbEZEPE0QENEZEgE\EHESE`IE0HEXEPEPMEUEPE`TEYE OELE`QESEJEZE]ETEOEQETEWE`^EEERETE@LE SEPUE`QE`LEPEMEPREQEPKEME`LEpSE@VEMEREPKEOEQESEJEJEPQEDE?EIELEPYENEQE@E0FEPLEDEPUEMEQE0JEBEFE>EMEPIEPTEIEEEGE`HEAEGEEEGEKE@=E`JE`AE@>E@JEME6E0?EPEE0DEOE@LEp8EFE PEIE0HE`FEpIE0SESEHE07E;E0@E9EFEHEIEIEAEGEPDE`8EPIEPOEP>E`7E IEEE@EE GE?EJEEE>E09EIEPIE@IEDE3E=E UEPBE?EDE`EEp?EAE DE`?EFE?EEEE@1EDE:E E EE>E9E5EP6E@AE@IE6E;E?E4E9E`>EP5Ep6EEE1E EE;E,E8E`BE?E9E.EP.E8E@MEp6E3E02E@/EHE@IEE9E6E05EP@E-E4EE;E`ZEPMEOEPE@BEEESE@NEBETEJE`GEHEAE@EEIEJENESEIE VEQE0UEXE WEpMEKE0VECEIESEPPE@XEPUESE0GE JEGEZEhE`YEUEME0VE YEPTEpWEpLEPE\EPEcEZEYEKEPMEREgEpSE`TEpSE`MESE^EXEYEZEREYEWEXE[EWEHE NE`REPQE@XESEWE`ZEQETE]E VE@UEPYE]E[EXEp_EHEQEpZEPEWE kE YE0^EbEYE YE`dEVE`QEYE`XE [E@[E ]ERE]EdEP[EXEVE_E@bEPWE`EnEpaEpYE^ESETEUEZEiE_EREpaE^E\EpYESE^EaEeEiE[EcEZEeEcE@QEeE0gEcEiEphE \EaE[E ^EPiEsE_EZEfE kEPtE hEgEp\EfEVEP`EgE`E0hE`pEaEfEkE@jEfE^EPE_EPnEpiEkErEcE]EZEVE`]EnEPsErE0lE0UEfEfEPfEnEfE`qEaEcEeElE mE`fEoEsEmEcEPdE nE`cExE dE fEcEp`E`rEoEmE mEqEpcEkE@iE0qEnEsEcEpfErEeE kEnEmE`EgEcE0sEpsEpvE mE@iE0cE@hE@mEgEpEoEpvEuEwE0cElE@uEhErEmE iE@rEmEeEpErEmEiEwEiEsEvEhE0kEkEhEsEPwEPdEsEPtE`hEVEfE`qEPwE`sE0kEpkEoEkE@rE`rE0gEeEfEsEnEhEnE0mE0vEiEiEiEppE iErE tE@pEeEpcEnEuEcEiErEnEPhEyEmEiElE iE0dE sE sE tEuE hEiE`nEbE0nEpiE0`EpdEPrE]EkE@}EpE^EaE]EmEmEiEcEfE0]E`lEfEcEhEfEZEPbEjE`uElE0hE`aE@\E aEp`E^E^E`EpEmE aEeEqEbEcEfE]EeEaEiEiE0hE0[EUEdE^EqEuEkE^EPZEPcEPjEdEPeE`EcEcE0XE@`EfE^EiEiE]EiEgEaEVEZE`EgE\EiE WE WEXElEP`EcEaEPZE0eE@]EYEVE`EPE\EgEjEiElE`EZEhEjE0bEdEdEZE`EZEaE^E`E`aE bE_E^E]E`YEpTEpTEYEP]E^E^E`]E0_EYE [E`ZEYE aE@XERE0GEYE`eE0\EpVE^E^EVE`QE [E]EQEXE\E ^E ]EPIE@UE\EaELEPWE^E@cEPE]ENE0NEPVEREPREZE0XEp\EhEREGEKE0>EOEZESE0TETE DEPRE_ETEJELEKE0WE[E0KETENE DEKEOEVE_EPE?E`FEOELETEPWE`AESE`VEpPESE@UE`LECERE0OEPEHECEIEDEGE@GEOEKEIE@E0?E HEEEEEJEIEBEKEpDECE@EPEEEYEFE`=E>EOEPFEJEPECEDEDE0AE0NEEE.E8ELEP>E0MEIEE4E`BEGEHE>EBE`E7E.E@E@:E/E:Ep8E3E:E8Ep+E4EBE`E0-E/E>E`.E5E09E4E8EBE9Ep3EP5E@4E'E4E7E`7EPCEP.E;Ep5EP5E>EDE02E06E=E6E4EPFE=E=E0EHE`EE`GEBEDE@?ECEEEBE>E?EGE`NEPJEHEpPEIEKEQEGEBELE0OE IEJE@EEEQEREFENEMEHEWE0EEOEPTENEKELE0CE_EPYEPQEJEIE`LEJEUE]EOEPRE@RE`VEUEp]ETE@_EYEPEMEKE0NE^EaE`EPaE \EKEUEpQE kE@`EpTE UEPEQE@[EhEZE_EdEP_E0XEYE QEWE_E0OE``E]E`NEUEfEXEVE@_EbE^ElEPRE`E`\E ]EcEfE\E_EP]E@ZEZEZE[E@\E XEeEbE@hE@ZEXEYEcEpdEoEaEiEfE[EpiEoE`jEnEmEWEPhEoEjE fE`hEiE@VEXEbEPsEdEPlEcEPdE hE@pEpaE fEeEP`E_Ep_E0ElE^EdEpaEfE ]Ep`ElE0bE[EkEfEbEmEkEeEiEgEPfElEnEP[EhEPhE@lE XEpkE^EaEpE0lE`iEPmEp_E`EpgEPsE nEuEgEhEbEeEPbEqEjEeEdEdEnErEbE`lEpEpkEiE0dElEfE nEpmEfEiEZE[EdEkEpEnEkEYEbE@]EpEpE nElEoEeEiE0eEpjEdEdE^E\E@sEfEnE{EdEP^EsE iEPkEjEgEZEpEPlElEuEphE@hEgEfE\EqEsEqEiE0[EpjE`tEeElEhEhEpoEkE^EmEvE@lEbEpE`iE0fEpEeEeEmEoE`eE0fE hEPmEuE_EbE zE@lE0lEPlEdElEkEbEnEPmEmE fEwEpgEPpEcEiEpnE`tE@vEbEiEnEbEcE@qEPdEpEiEPmE|EiE`qEpEhEPfEpoEPiEpE`rEjE`]E^EiEfEPwElElEppE\EfE`vE nElEPpE hE jElEcEfE0kEiEgEmE`fEkErE`bEjEpdEPpEkEpaE nEjEZElE gEaEdE`bErE`aE gErElEeEfE`ZEYE`bE`E fE nEpnE0eE`EbE`TE0cE0hEbEZEUEpeEpEjEfEZEP]EbE_EPfE`E pEPgE_E^E ]EiEhE[EaE`eEPYE@gEmEP`E`jEp`E0`EcE@kEgE`E@cE[E`fElEbEYE\EbE`EfEPhEaE`E^EbEbEPWEPREaEPXE]EPbEeEZEcEYE\EdEPZETE[E0aEP]EYE^Ep`E\EpbE]E`aE^E]E`dE`E ^EWEXE\E^EUEOEUE ZEZEaE^EPbEp]EPEWE [EPEWE ]E\E]EYE^E`RETEQEJE@VE LEp[E^EQENE0_EYEcE\EPJEMEOERE0]E ZEPQEVEUEZERE[EWEVERE@DEJENEZEREUEPREpTEPUEMEFEpREDEMEQE0UEYE`[EDEQEPEPEQEWEHENEPSEKELEHERETE\E?EDENEDEPETE OEMEDECEOEME@ENE NEE@CE@=E`EE?EFE`?EpFEAEp3Ep=E1E7E8E8E6E:E6E;EEEDE`=EPEE0EEAEHEGE`AEHE;E2E`?E IEME0ME=E7E E JEDE6EEEKE0@E:E@E0CE 8E`7E@9EpRE=E:EP3E;EBE CE9E0=E@?E.E?EJEP@E`8E5E4EAE0BE0E 7E8E0=E6EFE>E05E:E:EP5E@Ep,E(E0EEE8E=E5E@/E6EE9EDE`PEpAEIE=EEE ?EKEE0>E@>E IE?E?EGE@E0=EDE`DEAE3EFEPGE0FEAEHECE`GE NE ;ECE`AE0REJEp>ECEHE0EEpOE OEMEAE 9EpEEBEQELE@GE@5EDEIEOEME1EDEGEpCE>E`LEGENEHEEEHEEE@PE@GEPEIE0ME`^EEE@CE@ME`JE@RE`HE:E @EPJE@JEIEpNE`FEIEpCEFEFE@MENE`MEIE?ETEUE`PE`KEpEE`DEIE@UE`TEPBEOESEOETE`CEBEYEVECEHE ME`QEFEGE@QEPEPECE GEIEKEIE0EEHE`PEFEIEIELEEENEJEEEOE=E@QE REJE[E0KE@DEpQE KE0?EPEKEGEOETEPNE@NEOEEEpNE`GEE IEUE`DE;E>E@E DE0PE`FECE@CEGE@E7E9EpBE`WE=E@E@E5E IEBE@9E Ep;EE(E0E=E-E@;E2E2E5Ep6E/E4EP3E*E/E>E5E3E1EE`)E9E8E9E=E .E/E8E=E.E-Ep(E/E1E/E`;E7E 4E2E :E#Ep,E0;E0E.EP(E!E@/EPCE,E)E/E1E4E4E@4E+E3E0E@0E.E7E`1E@E/E ,EP7E,E`.EP/E0'E1E`8E2E-EpBE4EP4EP-E,E01E2E@&E/E 0E1E9E07E`-E.E@3E,E4E@,E*E1E`?E0.E2E@,E00E6E@9E2E&E9E5E*E*E$E`,EP8E+E/E @E 7E.E.EP%E/E3E1EP2E`8E,EP0E4E+E4EME-E3Ep,E)E,E*E.E08EP9E@*E$E-E)E@*Ep-E`(E0(E 7EP2E0E 2E*E E-E+E3E4E%E%E"E-E/E0-E&E@4E2E)E!E)E"E ,E@'E0)E&E1EP)E/E`0E%E`%E@4E/E#EE E7Ep6E*EpE0-E4E .E 2E@!E`)E(E%E!E@.E +E$E4E&E,E 3EP/E0*E E@ E E*E)E)E%E!E@ E+EpE`$EPEE 'E+EE(E(E0%E EP%EE E EE"E&E"E)E"EEE"EPE%E&EE0EEEE@E$EEPEE"E-EEEEE&EEE"E0!EE$E EEPE EEPEEE*EEP EEEEPE0E EE`EEEE0E E EEEEEEp E@EEE EEEEE#EEE0EEEPEEE`EEEE@E EEEE,EPEPEDDE0$E EEEpEEE EEE`E`EEEE@EE EEEEE`E EEE EEE`EEE` E`EE EEEE EE EEEEE EEp EEE0 E E E0E` E E EPEEEPE@E@EEE Ep EEEE EpE EE E` E EEP E`E`EpEEp E`DPE EPEEDEE EDEED0E E0EE@EEEpE@ E E0E`DE0ED` E0E`EEEPEPE E@E@DpEDEE`D@ EEEE E@EE@ EDD EDD D`EEEDEPED@EE DE` EE EE`D`EE ED EEDPEDEEPE E`EDDDDEEDDDEEEDpE@EEEEDPEpE`DDD`D0E`EDEEDEE@DDD`EDDD@DED DDDD DpED@D@DD@D`D`DDDEDDDD@DDD@DDEDD`DD`DD DDDDD ED@DDD@D@DDDDDDDD@D DDDDDD`D`DDD DDD DDD`DDDDD EDDD`DD`DDDDDDDDDD@DD`DD DDDDDDD@D DD`DD@DDDDEDD D@DDD`D`DDDD@D@D`DDDD DDDD`DDD`DD@D`DDD`DD DDDDD@DDDD`DD`DD DDDDD`DD`DDDDDD@DDD`D`DDDD`DD@DDD`DDDDDD@DDDDDDDD@D D@D@DDD`DDDDDDDDD`DD DDDDD D@D`D D`DDDD DD`DD@D`D@DDDD`DDDD`DDDD@D@D@D@DDD D D DDDD DDDDD`D@D`D D@D`DDD`DDD@D`DD D DDDD D`D DDDDDD DD D@D D D@DDDDDDD`D@DD`DD@D@DDDDD`D DDDDD D@D@DDDDD@D D@DD DD D`D`DD`D`D DDD`DD DDD D@DDDDDDDDDDD D`D@DD`D@D DDD@D`D`D`DDD DDD DDD DD`DDDDDDD`DD`D`DDDDD@DDD DDD@DD`DDDD@D`DD@DDDD`DD@DD`D D D`DD D`D`DDDD DDDDD DDD`DD DDD`DDDDD@DD{D DC`EE0E E@EEEEpE`%E$EEPEEEEPEEEE0E0EE`EE@EE@EE E0EpEE EEE EP&EEEE0EE E E` EE0EE@E E EEE&E"EpE`Ep Ep EEEPE`E@E`EE0E E@EEEEEEEEEEEE0EPEEpE E0EpEEE@EE EE E`EE@EE0EEpEEEEEE EEE EE@EE`EE@EP E EEEE@EPEEp EE EE EE0EEP EPEEEEEE EEEE E EpE EEEEE E` EEPE E E EPE E EE'E E EEE EE E@EE0EPEE EP EEEPE E EE E0E Ep EE E E EpEE@DEE EE0EP EP EE0EpEEpEEEEEEEEE`EEP EPED EPE E` EEEE@EpEEEDD D@E EDEDDPE E@E EP EEDP EEEEpE EE@DD`DD`D DD EED@DDD`DPEDDPE`E`DDD@DEEDpED@D DED@D@DDDDE`E DDD@DDEDDDD DDDPEDEDD`D`DDE@DEDDD D@DDD`DE@D`EED`DD`D@D@D D`D`DDDD`DD@DD0ED DDDD`DDE@DDDDD@DD@DDD@DD@DD DDD`D`DpE@D DD DD@D D DDD`E DDD`D@D DD`DDD@DDD`DDD`DDD@D@DD@D@D`D`DD`DD DDD@D@DD@DDD`DDDDD@DD`DDD`DDDD DDDDD@DDDDDDDDDDD`D`DDDDD D DD DDDD@D@DDD D`D`DDDDDDD DD`DDD@DD@DDDD DD`DD`D@DD@DD@DDD D D@DD@DDDD`DD`DDDD@DD`DDD@DDDDD@DD DD DDD D`D DDDDD@DD@D D`DDD@DDD DD@D DDD DDD`DDDDD@DD D D D@DDDD@D D`DDD`DDDDDDD@D`D DDDDDDD@DDDDDD@DDDDDDDDD`DDDDDD D`DD D@D@DDDDDDDDD@D DDDD`DDD@D D`D`D D DDDDDD@DDDD D`DDDDDDD DDD DD@D@D@DDD`D`D@D@D D DD`DDDDD`DDDDDD@DDDDDDDD`DDD@DDD@D D`DDDD DDD`D`DDD DD@D D DDDD@D@DDDDD@DDD`D@DDDD@DD@DDDDD@DDDD DD`D D`DDD@D D DDDDDDDDD`D@DD`D D`DDD DDDD@DDDDDDDDD`D~DD DD`D@DD@DD`D D DDD D@DD@D`DD@DD`DDD@D DDD D@DD@DDDDDD`DDD@DD@DDD D`D`D D D`D@DDDD DDDDDoDD`DDDDDDD@D`D@DD`D DDDD@DDDDD`D`D DD`DvDD@D DDDD`DD DlD@^D@DDD@DDDD`DD D D@DDlDDDD`DD@~D@D@DDD@D`D DDDD}DDD@DDDD`DD@DDD@DDDD`DD D`DDDD@D DD DDwDzD`D`DDDDDDD DDDDDzD D D`DD@DqD@cDD`DDD|DdD`D@D D D`DD`D DDDDDDD D`D_D@D DDDDDDDeD D D@DDDSDDyDuDDDsDD`DD{DD{DtDrDDoCDD@DE0E D@D`D DE@DD@DPEDDDD DD DD@DD`DpE@DDDD@DDD`DPE@D`DDEDD@D`DED D DDD DDD`DDDD`DDDD DEDDDDD`DDDDDDEDD@D`D`DEEDDDDDD DD Dp E@DD@DDD DD DD@DDDDDDDDD@DD@DD`DD`D DD@DD DD@D@D`DDD D D`DD DD`DD`D@D D`DDD`D@DDD@EEEDD DDDD DD DDDDDD`D DDDDDDD@DD@DDD DD@DD@D`DD DDDDDDD`D@DD`DDDDDD D D`D`DDDDDD DD@DD@DDDDDDDDDD@D`D DDD D`D`DD`DDDD@DDDD D`DDDDDDD D`DDDDD D DD@D`DD DDDDDDD DD DDDD D DDDD`DD@DD@DD D D@D@DD@DDDDD`DDDD@D`DDDDDDDDD DDD D D DDD DD@DD`DD`DD D@D@DD D@DD@DDD@DD D D@D@D`DDD`DDDDDDDDD`D`DDDDDD@D`D`DDDDDDDD DDDDD@DDDD D`DDD`DDD D`DD DDD@D`DD@D D`D`D DD`DDD D@DDD`D`D D D`DDD DDDDDDD`DDDDDD`DDDDDD D D`DD`D DDDD DDD`DDDDDDDD`D`DDDD D@DDDDDD`DDD@DDDDDD DD@D`DD D`D`D@DDDDDD D`D@DD@DD@DDDDD DDDD D D@D DDDDDDDDD`DDD@DDDDDD`DD`DD@D DD DD@DDD@D DDD`DDDDjDD@DD@DDDDDDD@DD D@D D DDDDDD}D D@DDD DDDDDDtDD@DD`DD D`D@DD@DDD@DD D DD DDDDDD`D`DDDDDDDD`D@DDD`DDdDsDDDDD@DD`DyD DD@DD@DDDDD DD`DDoDvD`DD DDDDnDuDDD DmD}DDD@DD DrDxDDDDDDDqDDD@[DDDxD D D@~DD@D DDDD@:D|D|DD@D^D@nDDkD DD`DxD@DDEDDPD@rD@{DD@D`DD@{D@dD@zDD`DD@rDDWDD DhDDRDDDDgDDDkDqDD`DD@nDrDwDD\D_DDDjDiDD D@rD@UDDD|D@jDD@tD D@DbD9DD@JDiD DDDvD@{DDDqDaDDZDqD`D`DDD@bD,DYD@`DoDDjDDDrDbDHD@DD`D`DDgDHDlDrDNDlDwDD@oDqD@ZD D`D[D@iDDeDrD@WD@@DvD@DGD@vD~DfDD@jDuDtDtD^DD`DHD@xDpDQDmDvDVD@iD~DUD`DD@ADeD@|DfD`D|D@oDDDiDgDDeDsD_DdDhDDcD`DDDD@sD7D@ND@eDD DDsDDXD{DDDND@/DXDUDrDDDlDYDcDpD@DhDDSD@?DD`DgDD DLD@sDpDDDDqD@lDD_D`D@eD}D@xDxDD^DrDDD@cD2D@QDDyDDxDgD@GDxDPD_DDnDDD|D D@~D=DDD@:D~D@tD|D@zD\DRD1DD@^D@1D5DqD@>D@xD@oDcD\DYD D@-DTD@QD[DDCBD D D`DD`DD D`DD D`DD D@DDDDDDD`D D@DDD@DDDD@DDD@D DDDD`DD@DDDDD D@DDD DDDDDDDD@DD`D`DDDDDD`D`DDD`DD`D D@DD`DDD D D DDD`D DD DDDDDD@D D DD DD`DD D@D@DD`DDD DDDDDD@D DDDD DDDDDDDD D@DDD@DD DD`DD DDD`DDD`DDD@DDDDDDD@DDD`DDDDD`D@D DD@DDDDDD DDDD DDDDDDD DD@DD D DD`DDD D D DDDD@DD@DDDD@DDDDDDDDDD@DD`D`DDDDD D@DDDDD@D DDD D@DDD`DDDD@DDDD@DDD`DDDDDDD`D`D D@DDD`DDD@DDDDDD@D`DDD DDDD`DDDDD DD DDDDD`DDDD`DDDDDD@D`DD`DDDD@DDDD@DfD`DDDDDDD D@D`DD@dD@mD`D@DD DD@DD DD DDDD DDDD DDDDD`DDDwD@DDDDDD`D~DDDkDSD`DDD`DDrDDD DDlDpDD@D DD@D@DcD@D`DDDsDD DDD@DDnDvDDDD DDwDdDDD@DD@D DDD`D@zDDDD D DDDmD`DDDD@DjDvDtD@DDDD`DmD@YDwDDiDtDuD@oDDDD D`DzDfDDDqDoDD~DD D|D@XD@|DwDDD~DDaD@FDsD@mDpD}DwDEDGD@DDD`DcDDDDfDDvDTD@D@^DkDpDDD@aDkDD`D@DDKD@iDiD{D@IDxDQDDsD`DDTDdDXD@D D@DDQDrDD{DuD`DD(D^DDlD|DcDnDXDYDeD`DDQDlD@SDHD@pDOD;DnD@[DODkDDDD@gDZDeDcD:D@fD@QDQD@D]D@iDDDDuDoDRD@HDdD@iDODZDOD@KDPD]D@ZDtDXD@dD D,DPDeDfD]DD_D4D@0D2D@DZDvDmDD@TD/DdDaDcD@dD@4DED@DDMDnD=D@PDZDXDDQD@qDLDZD@ID@FDZDvD;D@:DbD\DDmDRD@aDdDxD@ZDvD@/DvDHD6D@yD@pD9DkD@_DtDDED@tDrD?D@QDMD@DeDlDQDD@KD9D]DD@~D0DgD@KDYD@8D@2DKDfDqDnD@4D,D6DODSD@JD`D@bDD`D@FDKD*DD.D_D@tD[DlDDAD[DaDjDZD;DAD@>D-D@PDhD@BD@_DWD@7D@YD@|D@LDDNDHD`DzDjDVD@1D&DD@@DBDKDDbD`D,D@+DCDWD,DFDD@-D-D@2DCDDjDND'D7DBD@=DBD@SD@7D@BD-DNDZD:D@DJD@3DaD@ D@DADNDjDWD>D@>D?DGDCDHDND[DID>DEDFDmD@JD@^DRD:DSD@{D5DPDQD@0D>DiD@D@-D'D=DDiD@D.D[DCDQD@DC4DNDLD+DXDbD@7DLDDCDVDND@LDVD[DBD@EDeDD/D1D?DwD@8DFD]D D@D@?D1D@1DWD!DD@MDD&D@GD:D%DJDID^D@ZDDSD?DMDD@VD@DMDVD D!D@:D)D)DqDpD7D&D D?D@JDdDQDD8D4D6DMD?DyD+D@2DtD@8D@OD2D1D@>D+D&D D@YD@DD:D=D@LD;D D@JDBD@D@+D@^DD.DKD@D5DBD@=D@D"D/D@)DJD@DD#D@RDDQD DD9D>DMD@JD DBDYD@%D9DWD@2DD@GD@.DXD@DFDODHDDD-D@SD3DC1D8DIDZDBD:D@@D+DD!D?DD!DCD*D=D D@DID~DXD1D DD:DaD"D@D D7D8D D%DD@/D(D DD@DD?DDD@DDSD@WD3DD@DD@ADD@"D5DID D@>D6D@D*D:D@;D@eD:DC(DOD:DDD@GD?D@*DDC6D&DDD6D D@D@DC%C@DD D DDDDDDD DDDDD`DD@DDDDDD DDD DDDuDDDD`DDDD`DD`DDDDD@DDDDDD@D`DDDDDDDDDDD|D`D@DDD`D~DD D@DD@DD@|D@DzDDD@DyD@DD`DD@`D D`DD@DD@DDD@D D@DDD D|DD@DDDDDDDD@rDDD DD@DD D`D@mDDD`DDD`DD@zDD`DDD@DDrD`DDDDDvDDDDDDzD@DDD D|D{D@xDD`DD D{DzD DkD@D@D@D@DD`DD D`D DDoDD@oD@D D`D@DD@YDRDD@nDDDD^DD@jDrD@mDDDD@D^D DtDD DtD@DvDDD`D@DDD^DiD`DD?D@:DpDD DpDuDeDtD@hDMD~DDeDDDDfDaD|DDiDwD@kD@rD@}D,DD@{DDwD@sD@D"D{D[D[DrD1DDMD[D]D/D@4D@LD|DFDRD2DPDfDaD+D@DND;DMD6D/D@!DEDDD?DGD,D@8DC@ DADDDCDD7DD0D7DBDD$DCD@;D+DHD DCD-D%D@,DDDC@:D@DCD4DD7D#D1D'D,DD@DC@DD@HDD'D@D@5D.DCC5D@D@0DDDC"DDEDVDMD DDD@D3D-D DCD4D@CD)D DDCC1D@7DCD'D@D@&D@D@D@D"DDDBD`DD_D_D'DNDYD2DADDqD{DED/D@D@D@gD+DUD+DTD#D=D1D?D8D5DVD]DGD,D0DDQDmDFDcD>D@ DCZD:D@8D.D@5D>DRD@2D.DLDD@ DDDLDD%DTD4DDD@FDDD;D8D@d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zCCCC DCC@DCCCcCCDDCCCCCCCDCCCCCDC@DCxCCDCC D"DC@DCDDCCDCC,DCDCCC%D@DCCCCDCCCpCCCCCDCCChCC4D&D@DCBCCDDCD@ DCCxCC@D$DCC_CDCDCDCCCCCCC@D$DCCDDCC@DCC@ DCCCC,CCtCC@+DCC@DCeCCDDCCCCCC(DCCCDC0DCCCC@D@DCCCCC-D@.D@ DCCCCCCCCC DDCDCCCCDCACCDCCDCCCCCMCCC!DCC'DCCCB$B D:DHD@OD@ED#D@:DIDD@*D@mD'DJDDDDvD@XD@^DDC'D[DAD@KDDDD@ DAD1D@TDZD:DgD\D/D@?D=DD/DND.DD@4D@DDeDDD DBD@D$D@ZD@D@ADDDD*D9DRD-D@D@DjD@1D D=D@DD-D:D!D-D@D D#DUD@DCCC/DDD@D@DC+D@+D!DCC D!D DCC*D2D@DD DD@D@DCCD D&DCC@ DC2DDD@DCC@!D1D@*DCDDCCDC@:DDCDD@D5DD@D@DD5D/DD@DDCCDD*DDCD@D#DCCC@,D@?DCCDC@ D@-DCCDC@/DDDDDCC!DDD@D@ D6D@,DCCCC D/DDCCDDDCC3DCC(DC@DCCCDC@%D@!DChCCCCCC"DBDCDD?CCDCCDCDD@ DCDCC@DC@D@D$DC@DC@DDC@ DDC DID@%DD@)DCCDCC@DCD@EDCCCCCDCCCDC)DCCD D DCCC"DCCDD D.D DDDDCCCCCCD)DCCC DC DCCDCCDCCCWCC@3DDCDCCDC*D@DCCC@D@ DDCCCCCC DCDDCCCCDD@DCCCDCCCCCCCDC{CC-DDCCCCCCCCCC@DDDDDCCCCCCCDCDCKCC@DC@D@-DDvCCCCD(DCCCC DDD DCyCGCCDCC DCLCCCCC DCCDCC DCCC DDDCCCCCCCCCmCC@ DCC~CCCCCCCCCCCCCCDDCCD@DCCCC DCCCCC@DCC"DxC@ D DC3CC@DCC CCDDCCCCCCCCCCCCCCNCCCcClCDDCC7CCDCC@DaCCCCCCCCDCCbCCCCCCCCCDCCCCCCC1CCCC DCCCkCCCCCCCCCCCCCC DCC~CxCCCCCLCTB5CCCCDDCCCCCwC{CCCCCC^CCCCCCCCCCC4BWCCCC3CCCDCCCCCCC'CCD&D@DC~CCCCbCCDCsCCCCCCCCCjCCCCDCCCCCCCCCCC>CCCCCDC@DCCC'CCCCCCYC@DCCCCCCJCCCCC@DCCCCCCCCCCCCCCCCfCCCCCCCCCyC_CiCCCCCCzCPBCCCCDC@DCCCCCCCCvCCCDCCCDCCClCCCCCCsCCCCC DCCCzCCCTCnCCCVCCCD DCCCCCCCCCtCCCCCCCCCCCCCCCCBC@DCkCCCCCPCCD@CCCDCDCCbCCC$DCCCGC\C5C CCCCCCCCxC@CCCCCCjCCCJCCCCCC\CCDCCC CCCC{CCgCBC%CRCCCCCCCCsCCCCCC3CCCCCCCACCCCcCBCCBCCECCCC CTCCCzCCDCCCrC CC'CCCCBCCCCYCCC3CCCpCCCxCCCCCCC\CtCoCCCCCCBCCxCCBC.CCCCCCCqCCCCCCCCCCCCCCCC~CWCCBpAChCCCdCCnCtCCCHCCC@DCwCC@CCCCCC@D DgCBCC]CCClCNCBCCCC`CMCCCC|BCCCChCCCPCUCCCCCBQCCBC&DC DCCC DCCCCDDDC@DCCCCC@DCCDDCC DCCuC D DDCCC DCDCCCC8DDCCCCCC@D@!DDCCCCCC D,DCBBCCD@DCCCCCCCCC8CC DC@DCCD$DCCCCCCCCCCCCCCCCCCACCCDDCBGCCCDCCCCC!DDCCB*CDCCCCCDC@DC@DCCCCDCCCCDDdCCCCCCCD@ DDCCCCCC DCCCCCC@DCCCCCDCCCCCDCCCC@D@ DCCCCCC{CCCCCCCCCCCCBCCCCCCCCCCCCCDCCCCCCCCCCCCCCCCCCC]CCCDDCC*CQCCCCDCCCCCC}CCCCCCCCCCCsCC@DCCC$CCCCCCCCCCyCCDCCICCCC@DCCCCCCCCCCCCCCCCCCCBCCC CLCBD'D@DCB(BCDCCCGC@D@DFCBCCCCCC DCCCC@DDC*CCfCWCD@DCCpBCCCCCCCCCCDRCCCCBCKCC@ DCCC;C\CCFCCC DCCBBCCCDD3CkCLCCDCCC@ DCSCCBCCCCCJCCCB5CCBVCC'CCCCrCCyCCCCBCCCC|CxBBCCC D9CCCCCCC\CSCACCCxCCCrCC[CCC[CBCCCC`ECCJCrCCCCCuCCCC>CCBCCCCCCDC^CBxCC@ DC8CVC(CCCbCCCWC7CCQCCCACDCCCCCCCCLCBCCC DCCCB"CC{CCCCCBCCCCCCCkC)CCC&CCC.CCCuCCACCCiCqCCCNCC^CCBC@CCCZCQCCCCCCCCCCCCBICCCCCWC,CCCCtCpCCCzCzCCVCgCCBCCCZCCTBkC;CCuCC@CaCCCCCBwCCCCDCBCCCCCHCWCCBtBCCCCCCCcCCCCUCCCCBCeC CCC2CCC#CBCSC8CjCCOCyCZCCCCCC9CpCCCB;CCBCC}CCCCC CC2CFC`CCBC%CUC)CCyCdCCC6CBNCMCRCHCCC`CCgCBBKCCC=CBCC6C&C7CBpBCCCC#C:CBCECNCC3CoCCC@CC~CCCBqCCC,C CB$!CCCCCC@DCCD@D@DCCCCCCsCC@ DpCCCCC DCCCCCCtCCC@DCCCCCCCCCCCCCqCCC DCCCCCCICDC@DCCrCCCCD"DCWCCICCTCpCCDCCCKCC@DCCCCCCCCdCCCC"C'CCCD DCCCCCCCCCCCCC\CCfCCCxCCCCCCCcCCCCC~CBCkCCCBCCCCCCqCCCCCZCCCC=CwCCpCCgCCCvCCC.CCCzCCC3C CCCCCCC9CC{CCTC~CCCCC9CCCCCCC!CCCCCCCCC2CCCCC6CC DCC8CBCBBC CGCC$CBCCCCPBCCCCBCCCCCcCB0CCB=CAC CTCC*CB$CACC'CCCBVC}CCC>/@BCNCC`CCB6CCCVCCC CoC:CC_CAICCB@{CCrC\CCPCCCCCC4C&CACCCeCB@CCC CHBC8CB-CtCCCCB_C\BCCCBBCuC'CdCCBkCDCB"C3CCyCCCBCCC"C CBPCCCCCCwCCCCCCBCUCCCCBpBCC$C=CPA`ABDC"CCBdB+CACCBA,CBBCQCKCB&ClCICBBC3CECACBCCOCCCCBLBAjCsC.CCCvCCCCCxCCCBBBCCCCCZCqCDCTCBCCPCCB@3CB7CoCCCCFC8B CC?CCC`A|CCALCCCmCB|xCCCCCCCBCC1CCCOCC B/CC\C/C@ABC2CrCC BBYCJCiCOC*C#CCtBCCCCnCBCCCCJCCCCB+CC,CCCCBuCCC~CCCCC+CCCCCPCCC\CCMCCCyCCCC:CCCCCCCoC0CCCCDCCCCCCCCvCCkCBiCCCBCCCZCCC0CgC6C CCCCCcCABHBHBjCCCCMCbCCC~CWCB.C=CB)CdCCCC$C[C^CfC~CCVCC#C*CCC@CC|CC!CC=CCCCC}CC_CCCCCKCCC*CCaCCCzC[CCCCCC8BwCCCCCGCCVCC4CCpBCCA7CCCCC@DCCDCpCC9CCCCCCBCCC4CCCCCCChCHBUCCNCC0CC0CC|BB=CCCCiCCCCCCCxC5C,CCCBCC0AgCCCCBC{CBiCCCCCaCTChCCCCCClCtCCC CCCCCCCBCOCCCCBBBCCCCBBTBC\C8CCCCCCCMCBCCBCC CCBICCBCsCCC`C??CCCCCC`C$CCBCJCCCTC2C"CB@CBjCBmC(C$CwC>CCgCACBCmCC>CCCC@C}CCBBCCCCC:CACC^CZC@ClBCCBCCCBCgCCECiCKCxBlB[C`CBCCCCmCCCBCC(CB+CCeCCCC CCCCCCCBBCdC,CC*CCdCdB'CRCCCBMCHCCfCCBCC,CB%CC/CCCBCCACCBGCBCCCB CPCCCBClCCCKCgC/CCCCCC@D}CCCAsCC+C,CCBCCCBCBCCCCC?CBCBB=C CCCFCHB`C@BCB(BlBBCCCoCHCCBmC@*C-CmCCaCB@0BBgCC?B,C`CqCC,CDCDCkCCC4CRC$BBBC9CRCgC{CBBA\BCCnCCCAChBBCBBCCCCC8CCCTCzCBCCCC9CCkC4CCUCBCBBBBCC1C,C CTCBAC`CCBBCBCCCB CBCC8CBBA;CQCCCNCC=CBBCCCCBBCA6CxCBB$CC CB8CCBPBCBCBQCBCfC\CBhCBBTC ABuC]CCBBBBMCBAOCC CB2CC CC@ABB3CBB`CABCA1CCC`AACCCB:CCBCh$CChB#CC&XCCCB2B:C CBBB 8C1CBB lBB BCCBUCBPCBCB(CBA B>CBqC/CA $BB$CCYCCCA?EC+CHBXCCBBB]C1CC6CLBfCBdBBBLBCCpAC4CcC!C C4CB:CBACC||\BbCCyC9CPBBBCCB@CBHBCCCC$BQC[C@C=C?B$CBB?C>C?CBAJCpxC CCICp+CCCC@`pBtBCCB\BCBCOC B4B0CCCA%CC80BCB"CCCB,C@@BpA`CBC@@@0CCC$CCCC-CA@P4BpBGCCBC$BCCBABBBCBBC)CBBB,BBCJC@CBB3Cp9CCBpCXCBABBBB~CaC2CCHBB BBIC~CB(B&C@BQCPBCBpABCCB>CLBBCCCCB@BB9CACBB(CPA CHCBq`DC:CBmCBlBCAYCTBPA"CA`BCqCBcCB@RC1BBuCWC)CC*CBCCCDBBC8BBBBLC@RC$CBBCACBxBPBACCB(BB6CC C@ArCBpA4BPBCFC@B0ABB<CCC\BDCB@CBCPB;CCA$CCdC CCBHCBBt-CBPBAPACB4LBBGCBCCALB#CA$BC?CB5CBPC-CZCB0ABRC?CAABBBCB ABHBQCA0AB;CB8B@BOCBABtCBBBBCBxB@B0CACC_CtBB$@}CCCC<AdC@BjCB@C@CZAJC CCBVC&CBB@ABB@BRCCCB(WC`CfCChBBB-CBiCBABC8BCA|CwC\)C`tBrC+CBA4CpCC?CCB4:CC@+CC@DCA(@@>CCCGCBGCCBBCCBACB$BBHBBBdPA}CB`ABCCC@dCBaC8"BB]CC}CC,CP4CCBLBBpBBCCB"CDBPHCLBB BABBBPACP|CTBBBTCpBABIC6CBbA@C CBBBFCCPCBAWCpBBCTCGcC,CCsCDB'CTBBBCBBCRCCHBBB?"CC C3CC hB(B*CBCAOCAPDBCC`?CBpBCX3CB#C`BHBPBB@8A0BCCB BCxB6BBB]CBABAAXBwCBBBC;C3CB CC1CBBBBTBCCCB(BD/CBB AUCBB$BCCA@@CBB@B&CpB0B@eCpA,CkC`BPBB CBBBCHh.CpAACCCB@@@3CCCA9C6CMCCB6CClBB$BBTtB0LB\C#C,(CfC CTBABCA(CACvCQCCB.&CD;CCBA5CBgBA6CtBABlCBA@C C PBCCA@CMCB`ACC C@ABCPABrBAC:CBBAFBBTBJCBBBpA,C(BApABhBBOCBBlBB(B CBBpBh AjB|BB(BC,C@fCAB/C/CABB7C,CB0CBLBBB\CB@A+C CBBX`A,B@HCBBCA|BCBBBBQCCB$BCTCCBC&CCBBBHB0AB|C$BACKBB4BOCAPBBECBxC(CBAAx@ACHBdC0BDBAC0BKC%C ACC_CCBBCBCBBBBPBBhBBBC BBCtBWCXCBAB@$CACCAABTCBCB C CNCCB`AB&CCB CBBA3ACBA5C4CC0C4DBCB"Cd`CC4BCdBC\CLA C`B`ABACBCKC|BCCBBxBB+C(BCMCvCB,BtB8TBXB #CB^CBPB@BCBBB]ChpAAATCCBABAB?TC!ABLB_CCB68BlMCCCBBC@ABtBCB@C:C@P/BBACTC@@BBBBB%CBBdCB$B$C*CCBBAB=CC C B@@0CZCA@,BJCBABB@BAlBBABAPB*C@AhB5CBBABHAfCt#CCtBZC@BB}CBABBLB@CQC@CcC,BtB`BYCA8@]ABBB5CB(BBC0AB@BBC/B@BABAGC>CBB(pAB`BABB%CACBC CB7C@AC`BBC0BDC C CAB<BzCB%CP-CC CCBABB`BCABWCTBBlB @P B BBC AAsCC BBtBPABB CQBBPA@BjLBqCVC CB0ABBB}C|BlBA;C*CBGCAsCC| CCB"C\BBBAC:CCBpC0B8EC `A\B@hBBVC@BAWBB C%CABBB,C C%C0BVChBB.@BBSCBB#CB\BdBBhB"CxBxp)C,BBCC4?ABABDCBBA@8BB(BAA#CBB`CB0B)BPABBCdCB"CB ` BAFC8C CABHCClAACBBBC \BB8BBCAAA A@@B0AAWCTHBBCCB@fCCB8BBB(C C1 BUC\08BdBB!CBBTKCpADCBBBBBMC C9CCBC CB)CABTC4C CCC-CHHBCABAEBFC8BBBBC$ 1tB0BCBC 88B CCkCB8BBA>CBBlBBBA@A{CPA"CtBC`\B@`CUCB`B,=BwCBdC Cc<$B:CBBBBsp@?BCA'C!C hBCABBCBAP"?XBrtBCtB@AC(BCBCCBCBB@TBC0AAABSC:CAPACC@lB&CBBNN(CCCCSCABBB4C((DdBCAXBOCpAH`ABB C(BRCB?CBBBB @Ah|BHBBBPBC+CAA$BBAS C CHBBB@.C(BCBAC_CBBCBBB\BLCXCBaCBB\[hBA< C CC\B@ABOC(B(B (XBhBACmCB(CCBCB,B BC\BBC C4BBBC@B!CCA0BwCBB`ABB>CLC-CBBcChBBlBC`ABCCBBC4B)C@CC0BBA@`CBBBC CBBBB?CBC@ CBC@B0PFCBABAB8BCC CH@@CDBTBBAB(CCKCBPBCdBB CAgC BA C{C@h AxBB`BDBC BBBABCd/CB p*CBlB@xBDB BBtBB8CAA(ByCB6pPCXC8O BBB|BBBeCBpl2C+CHBtBDA|CC[CCBBAABB7]@BB|.CBXBAA#CP CJCCBBBx A=CCB]CaCABC BCPBBd/ A[C CABB)CACBCDABA;CC0B CXBABB0@B AB%C<9CBICBBPB8BCCBBABBXBA@A@@B+C,BBB'CB,CB!C-ChBxB AABBB1CpBBT'CCCmCP A3CACBhB>CBA3C C4BPBBB+B[CCC BAPABBgC?BACA5ACADBBA3CBB#C`@C&CpB$C8BhBzCA^CBB%8BBCB BB<1CBAB CECCAPCBB\'@B!C`@CA$tB Bh@C CB ECCAABCClCBCBBA"8B@BCLBl@ABBB4*B`:CCBBHCBUCABBBBBBBAx@RC0B`ACBBAABBB BAB@YA0CA:CB B`A$BB C A@%CBBBAg0CCRCACBhBB~@C B*C$BCBRCDB`B@@AB06CBBBBXCCCBVAAl CBBiAB"CB$BNAAC;CdBl ABACB-CB@BpBAECq:CBABx%BBCB-CC BB4B(BBC\B7CB0B!C`BBBC$BB*C?BBBBBCP@B CBCA|BA|@%BDBBBBABMBC4:CBAT0B$BC]CCCBB`CAC`CCBLCBBC|C$ TB,BBAB C@ B CCtBB\BBCC8,C@CB@t(B`BC BppBAB BABAClBBD85CwC$BB C B ICaC@@$YC@'C0BALB,BB5CAdBB8@Ap&ABABBB CC xBBp$BBlCB4CB4C0BB@AA3CC8BBCS @CUC@-CB>CBA?CCKC@ A%@C BB CB BBCBHBTXBXWCCASCBBB`AAKCABHBAA8BAA*B ACB0A[CC1CCB'CBBB4BB\IRCB`AB \BCA4CXB`A%CB$CLAxcC.CBB@BFCCdB 7CCCA PA*CBBPC(C.B#CBxBd|^C\BpCC@BBlB`@@AB$CBB:C@B$B CPB( B@,C BXCBCCBBeCCtB@,BB?LABB$CBB@B/bCCLCB2 BPB4B`,BBBBC|B-0BB wP3CBCip\BBABCClBXB/CABBBB|C,B AC<@@BBxBBHCbCBB<)C@B&C`AC `B@CCPBOCBCBBCB$CAB@@tBA@6.BA@ pABBB4BxCL:CBA@?B(CP*8vCPBFdfCC_xBPCxBBBB{BBLBAB0hBBBBB@@S CA CC@BlB C1CHBB0A<0@B CB@\C(B81ABAC0APBADBBAB"C@CABAB BACPAB;C BBBBhB0B-CCTBAB8BBC?CC3CBBABCC@BTBBBUBBB^?(B.CABBB0BpB$>C BB$BXB@BACCXB@tLBBBBXtB`B@lBCABmC`4BC4DBPAxB0BBmC?C$CBBCXC\Bh@B0@@BB^CCbBC Cd'CBCOCB`ABPCB%?CpCBB,B(CC BeCB)VCB CCC$BBCC+BBC_CAA@C0(B B B@FCEC@BAB $C2CBCuBBBBA(B|BCEBXC^CBA|CTHB@ALBB%C=CB C@HBTC BBABpB C(BCB(CBBABhBlBClC)C2C#CHBCT@`B`BVCBBhB3CeCVC<86C@B BBBBC(BBAPpACTBtC T ABBuCB`AApB?B0BC_C!CBBLB@ABBA#CACbCKBBBT$B(?@BBBBBCB!EBPBBpoCZB=C0C@AAB%CUC$C`BB,#CAA@0BpCABC@BlC?A0ABBBX$BBB`BPAC,BBC BnABAXBA%C@(CTB'CCXBH CAC8BVBBBCd@C@BC @AC4BB$CBBCCAB#C`B$BC0BBB)B>CBtBCCAA.B3CBPATBB,BBB@@AxBoC1ClB AnCBAhCABBCABPPAGCBjCB PqCB(C$ABCB8BD@@dBBd BC0BC BBDBDBApBBdBBhB PB C@@OpBtBBAB[@0ChBTBB0AoCB(CB"C@@BB<BB4BB @TBBZCBh@B@LB4CdlB2CClBGBp CHBBBB@C0AcCB@$CACAB0BB@A<LCA-PA+C( B4BB? BAB7\B@BCA,AB d`A@ CLCBIC(CBC\BCC0| BB8BPCLCB BB-kCCBA8 BECJC+CBBE@BBCBB8 CCABC;C@ B BB CBCbC AkdBBBGCBAC@(BB ABpABB`Z B CABYCATB`A0AA CbCDB@hBBHBBBtBA D\OCsCBBAC@VPxBBACK\CB'XB@ C]C7CDBEC3CBBBB9CBB ABA0ABCgC@`A@CBxBAB M|BYCCA BPBBA CpAhB CB,CBB@ECCjCPABBpBAALB8BCBCAA-C4Bd.CfCxBX`B HB CB`BB0BHBB0AA@@BB:C8CCBBbCA<AA CB>C8@hCBOC1C@KCC6BCC|BA#CB)@BCB0CBABA4`AtpaC@8BA<CBFC CCACU (CBpBBAC)CzChA BApBB@B0C @C A0AdCBBAAhBBBCBDB C.CHB AABABCPBBhCA@BC CB CBBBdB>CBKCTBG CBCB`B?ACABh<DB,BYC7CA@BhBBHBCB@BBpBB CpAABA!C@C`BBCC0C$xB0BACpABBBALBBCTABB4CBPC2CLBB"CXC BPBApZ4CBBPAP0BT1C,PBCBBpBCuCBTBdA,BCtTB<@@CBTCxdBAClBT?CBBADLBBpABCB@xBPB8xC@CjCA(ApCDBBA?CAlBCA iB@(BAC7CpB B%CBABBBpBBC@B4B+CC$B@`A ACBlApC(@BACC'BABB%BC\B:CgnBC@@BACdBpAB"CBBBPBBOBCC8BBBBP@6CDBBBtAphB C@@#CACBpTB3BBXB@B\B`B B CBBABrBACB CYCR)<B}CB@@\BPB@BdBLBTCB LB@A xBB!CBpABPBCu,B\B@@ CX@|B,B@xhBALBABkCBX@@ACB\BBtBBBBBB@DB6C;C@@ACBBBBBCKCCLBCdBBtBMCBspBBBEB1CCC0B BBARC$BBBCBA0ACBCB\BBB/CB,C|AAB)CBBBJCBB CBAfBB4,$KCVCtBPCBBHB0BCCtApBBB BC=C@PB@(BNCCBP CPB@BCPB@@BzCA BB(BA(CPBtB,CBC`BBXLB0 BAtBBHBB C{hBfCPACAMCBBB? BB:CB4B@B4BBB4ABB AB"CBBBB?IC BABxB|=ChBBBEBBBBB CqCC`AABTBpABCBBPB8BB`A9CCA|BB`A |Bl0$@A4BC!CBKCBCyC 8ABC8L"CCABA?$BUCBCUC CBnCA7pAPPBCAAB@B BABbCBCB,BCBBBoCB B`BC BCB@B`BPBACqC~CACB*CCB B(BD@l<AB8B)CBB BBPp(C-CB@ABBCCh@BB8B?=\pCC@AxhBC"CCA8QCACBABtBBB0AB-xBBABA\C CBBA(BPBBtBpB<@CCCLCB\A( CLB@B C@BAOBB@BBXBPA[ApB` Bd BBCxBLBPBBBCB,BB@ @APABB BA@C@BBBBBA|BUCpADC@BdBB@@B\&CBBBA)C-CC,B PA0BlB!CA0BLB0A! B.C/BB`BBhLB 0A BA B@@BB:CPB@AB CoCB BBC$TBIC )C'C\BXB?C@ BlBC0BAACBALACBA$PBX)pVBPA5CBAA8LBB,@B AA,C<CBCAAB1C CB1CAByCCB~CA_CB0C\'#BCC(gpC A?ACB0A`BNC$CCoB CBdB AAT`BDB=CAABVC0CICBC@CCBTB$BC(@AB-CiCC(B`zC0X'CCBBpB!6CB`AA C$BB|NAhBBBBX@`lBHARBLBB|B$BpBlBA|BA(PBAB4BC,C@ABA hBBA5@XB0AB8BxBhBBBBp%CAC@AXBAQp`A0CBuCBAA(BLCC$FCCBB`CHB@AB@@`BACcCCpB(B4?B(BAB@CBdBUCCtA$BCxBB;B CBB#CB\C:.CBBB0 CPhBHCAL`Bt(BB C`ABBD\X''@BBHBBBBBBeCBPBB(C)CL@CBBD |HB0BCCBB\C C\B0@ACB@@$C(B4BBBBBBTCBBBtB C(CB.C AB@tBB-B#CdB,B\BDBBBBC@@0AB(B#C9|BB0BBCBAB XLBBB ?X|BxBCXCBBA&CD,BC@CC#C BPBCBBB8CB@LC@BXtCBBCABBCCVCB8CACdB9$C%CB0CCAHpB\BB7]B+CBNCCBC&CB(B2C ClBBDBBp CBA BBB%ClBBBB +CCt`CCP*C\(B B9CABA))B`BT$B4B.C B@B+C4BBrCC\B@ASCABABGCB,uHCPB`BCBoC@B 0B5Cx<C BBBC9CzCBP CCB|B7ChAhB9BxBBPCCB@B CCBA PpAAB(GCB,BB0C,BBBB_CBBBC*CBCBA@C@BLB\C@lB'C`pdB'CYCABA?BBTtBhBBB`\BBBCBBASC,BBpBCBABB|B Ax|B7CBBB BBXBBB@BBhBC !CB`t$A+ B`BC@CB\CB1C 8ApABJC4BBAxCB ABBPA\BABA0B|BCSA8dCABpBDBBd\ABAHpBB[CC`APAABB-CDBhB/CB,BOC1BPhBB C ^CBSCB pJC,C@BB@@BBBAFBbCBi@`BBCCC,D4BB@`AAC@@BXBBH@)CBBA;CQC@@AAPCBAABBBTCzCCLlBBCABpLCB CBCBCPB(B(BhB@4B CBBB CBB?CA CCAA A` CmC0rABOCBp@BBCTBZCB B'CLBB4B8BA`B#CCSCCBdB(BBACABUC@BA(BB8BBAA`tBBB(8BB4KC@B6CBpBBABB@Bd ?C&CC!BBHBBBC0AB_CB BABLBBpBgC;CB0ABd*BAABBA;CBBB@A@LtCBC@4BBB BBDB`ABC pB$BBBC$ BABBBCC@JB Bh@CBPBC^]8 A,BXCC,C"IC$CBlBCAB0ADBxBBBB,Al8BpA%CLP@A0BBDCApA (BBA5B`A B C@B CBBBACA8B@BBBpACzC`0Blp?BlBB!CX@CnCx<@^C BBBcc++EC|BACDBiC+dB#C B@B?AB(BBBCBaC ApA@ A CwCB 4BpCBC ABdBB C\BCpABACCT@BB BBBB C BB`B0C`B\GAYC\BBICBABB\LBHP CC@&B&CCxBB CpB/C#C B8BG@AB@B@B$BBC.CpAG4CBABACBEC@BABB A@C+CBB ABB8_CB`BCCLB!lBB oCBPAlB @A%CA4BB2CAB<P@B@ABCHB;CT`BxBBCBLBl8C0CHJA:CB0C\BC7CldB|ABuCCB?BB`ABm$VCKCpAB8BB!0+CB B C@C@@ANCVCBBBPPAt*CBh0B\C B@pC4BVBA4CA AiBAxB C`FCCAxCLBPBB CBH,B&YC6CA%?AAB AB`AB BA``XC,BBAdBBBJC`BAAdtBB BCBAABZCB<8CB BBBpB&CB>CB!(BpA%CrC:AL(CdB@\BTB0LC\PXBpBBBALKC[CmCBB @@dBBuC$BAB`BABBdBHBdBD,C(B'C<0AaCC+CBBABPC=BA5CBAhCJC/CABBBC-08ACA0PC`A BBlBA^CBPB`ABBt?BAHBACDABBA0C,CB0@B0CxC0oCDCBB<C$fCPB@A%C( COB'C@C(CBBB@A`CB$>CBA4 BC@@DB4CCCBlBl`BEC ,`A(BClB4CrCpBBYCAClB C@0ABBCOX||C#Cn@LCAhCBBpB@BA@"CBLKCBCAABBBT@BTB@B5C A@B PBA@ABBB|BBCBAPABBBBBB:CCABBB@B4B`A(CB0B8BB FxBBCAuCB*CBxBB'CB,BX C@@C@p"zC8CBB@BCC*BhCBYCKBPAB C@BBtBiCA`B4BlB@ 04BlBA`AB6CB,)$ CBBCHGBRCBAC2/C`BA&(BAXBC0t``BdLBBCCBB(?CBB`C{C CB C\CBBxB%BBdBAX0.CpBCBBBB$B$CB@Bx|`DBH1CCBA AlCxB B4B@LB*C.XcCACBBB<:hBBOBB#CBHBdBBABC0 B BBABCIB@BBB;CF AB|0+C CB45C@C,BBl4CA ABBB ACBCXBB nCBGCCABAYCCXB@@ B`ABAp8BpBpB-CdCAPB2CABAX CBBBBC`B@B#C[CpBB@@,ABBB(BM(B$B$BC>C(\CBBlBdBAACAGCA NC!CBHBhB CB)CC CdBB= B1CHB88BBBD+CB?`4`BBH*C??DBBA?KBCpB!CBABCB?'C CLB$?PBBB$A4C$CCBCpBC'BCTC1C;?=C-C4CBBBbt$BB@B0AI8ACHBBB6 B ?CB BBC@\B AB8l*C5CAh$BBB@@`AB0BB0|x8BB,F<B C\B` @pBBUC4CBBB` XBCCBxBXC$C@@AACPBBdCBpBBAB?CpB4B)C|BC.CBDBATBCBACBBsZA@BBBB-C*C<B C4pBBBAHCBB`\BC58BxBBPCBBBB] B0CB<$KBC|B BCCB]p@A>CBAA<-BBBABBtBCC HBBABpCAdBBAABCB0PBBBCBACHApBAX`;$BB@C@AABtuApBBTABBCBwA8B?C8SCB0CCUC\B`A8B3CB 1C@"C,C+CAAB(B\BB$B\HB}CB@,B@BC2TBBBAdCuCABN BDCABBpBBdBBABByCpBBBlBBhCB\CCB@ACB HBACBiPJC)C CBfCB@BB@`BBbCB$<,CPA.B@,`BB AB.A\BCLBA0AY(WCCCB^BAAC3CCGAB8 CVCBCB@'CBACBAB%B?xBHBCBl$BxB;TCCBCaCEBBBBAB CBDB<(Ci%C C=CTBkCBBtCLCB@B(BBLBBB@ABBBB@BHBCCByCxC,BC(=DB@DBTBD!@LCBBBABBHB8`BCGLC$(A8BpABBCpA,PA| BCABBAX |B@:B(CCG,$CBBBC A(BqCtPA@BB CCp B\BCBOC08B BhBBLXCBXbBACABAB0BBBC8BB5ClBC|B0AL,BA$BpBtBC2CBNBtB5CBCXAB?BBt kCBC8BBB@BC@8XB|B0pCBBtABABBBCBBCBB AGBPAHC B C"CC;CBB04BAB@8B RqBCBDACVXBA@B0BB@$lBAB\7CBP14BB]@C"C@@ABLTCB4BB@4CpAUCBBAB.C C$BB@CCB6AB:C,Cp`BDCt@APACPBBB1CB0]|ABdYCBBBBB@@C?@(@CApC3C@@AotCBBBLB_CpBxCBBCB|A@CCA8@BC@AA0AhB+CPB@]CC?B BX@BA@@BPBBBtB4VD0BBBBACC$PA BBC BBC,`HB`BBB C\B`BKAAB@0C`ABBxBBaCCACBBHB`B BAC4B8DxB(C\B(@HCCBA<GACCCBXxB@AB0@B(BBB(`BC@B`BPBBB?0AAPBB C`BB$BB BCBAC@@BBBAB7B`BbCdCt$BBB CBBB1C0tBvCACB=$BCDBACB|BBABX`AB BC@`PABHBxBC\B!CB+BXBBB@0A!C@@BBbC@A2BBBdB<0BPABBBDBB0BpB,C CLB-A<B@ACCUCACCBB@BB:C`BABeBB ABB@HB8B$ AXB)B@@A\B*CB CB@@FChBC<B4BC CB@(lHBBB$BSC>BBBB/CpCBKBBmCBBBxBBBHC@@4BYBCBBl%CBh$@0B A0ACBB CCCC CC?@BAXBBBCAdBBPbC|Bx,\BBdC|BAxB B|BB@B6xBRCDA@AB@BBBBBBA4B1\FC^'CB4CC CCB04BC`?BCBB.CBPAB@A,CB{CB BBA8BCA C0PBBBPAB@CB$`LB xBC\C |l?BCBBBC BA8CBp(DBPAtBNC:C@@pALB`,BB@BTBjCCABB/ $!AAC4BBzPBACy [CBBB7CBHAC|BBBA BC,CBBvC!CAC$4BABPCC`$BCdCPBCA80A,BB@BAFCKCB,BAB;B@CuCB BcCB`BtBBTA$B?aCC\B(BABCCBAsCB(DCB$CJCBBACBHBpBP0BCBBB`BAlCpA:C@BLBCCB;CBATB C#CBBBLBA(BTC hhC\B8CBA"CBBBB(CBA@BABB0C &CDAB@ABB]CB4B1C@CC^CYCpA,B?CgCBC &+CBBuC0BA\ CB\BPCyCCB#C$BBAWC CpBBPCC C@@TB\BB\A4BpC5C B AA&CCiCBX d@BBDCBlL@dBABBAA @BBLB!CC,CBB`8BIC C^CtBCAC8B+C@BB\Bl=CCB CAPA$BBCAB3C*B AABICB|p5CBBBT,BCC\LAC A@B C,B$@C5B@AjCHBhpABBX3CDdB@8CAh,BB;CCB`ABBB@@CB B`AHB!CBWCBXB\Bd/CBB8B/BbCBoCABTB(B C7C%XA CBlB$GTCCTBB$B CBBCqCCAB CT`pA@A?d.CB'ALBB^AB<CL,BBNBC8C@Tc,BC>CLBBB@!CABB &]CC0TAAYCABAQC# CBhBB4CLBLCpBBpAA@@CCA0AAL(BBBKCCB@B CCBA |CCAtB7B+CP\BBp84BCDq$B CB`AP\ABCA<BBBAA@SB^CtxTBBh@B B(CBCBBBBo0?!CBBA `B@BABC\A0@BP@hBBBpBZCC8CM4C0TbCBPtBC^C A>CBB$6CCBBA0p\B0A@BBtBBA8B ABA^TB@LBB`4B o?BBA[CCBB#C4B$BAUCB'C0CBBTB\CBBC'CAB@BB0*C`CBB(PB@@CBBPA BBB C BHBBCHkCxBpBA lBB@BB@$BB,H0B CiCA2CBWCbCBlB*CBBvCBXACCBABBCCABBCC C8BLB B^CB'CZC@B@ BBB BpCB B`A 2C"CApBBB`A B8CBAB)C8BbpABNCC0B0A}BBPBp4BqUCCANC0BBBBmCBABBCBC8BBh(BBCDCBBABBBAA4BPB&C;C@@=A CC@ C |B CAB CC]C\BX `TB8BA$B CBBCmDBChB0BRCBCZCCBA BWC@@CtBBBBBBXAC#CALBB!BB`BCCBBCBbC8BB@A'CCB=CBB xlB@9C ABAAX(B$0AtBCB"BdBBAC:C#BB18?|BCTBB`C4AC CBBAeB@B CB#CAB?B@HCCB0A@~HBBB|gCxB%BBC BB#C4tABCBB bBtB5ClB CxB(BABDCCpHB%CMCB8B CANC $B CBpB4B ABBE"C|BdBBPABCCAAB#dB|B@@B8CBAA@B'CpdBt@=C|\PABBPBBPBBC#CA$BCCP'C|B5CC,B4CB{CHBBB(,BBd_AB`A@@BXB8AClAT7CB ABBB C-C8LtXB1CCHCC<AdBhBBh3MPA;CBBPApC\CAABB@TB@BCApA0@@xBABB@A|BCB B$B=BC BCBCAX0XBsCBBxBB`BB=C8BCLBA6C`A$BB`B`B`AkCCBChBB_@BBdtB B@ACFC"@BBABABCCA)8BDBqC 5CCCB? CHBlB+C'L+C4CDBC'C0B)CB]C=CB ltCBBBAB@@<PCABB 7/CdBBB\DlB0B @ B CCCxBtBB,XCB'C/ CB(APBBpAdBBCBBB8BpAC ClBBB&C=CBxBQPAC @DB.CBp@AfC CxBC@ B BB`BBB,BBFBAPBtBABBA(CBB< A |C*C8B|B@@%C0BBA@BBB9CfCB`ACCBDBBBA0A0C/CBT@@P1CBBcC0CHCa2C`cCBBxbB=CCBp@AcCCBA@AQ*(C=C1C{vBBCA;CAB|8BAAA(X+CCvC<ADhC>CC`xFCAB|B BBB(BTBACALCB8plCPB CKCB( ABlBBBpABBAABBPBBBPAWC CpA0 CC0(BA0`"CtBCBACCAo$BB8tB:CBABBC0A@B#CCAB@BA/BBB APCABBAABBAA8@fCBpAB,BAA`LBpBCBBBtBA$TB=A BB C`Aw4 C)C@AlCCBBBB BB(BB.B5CBCBB)TC5CCBCBDTxB@ABBPABBDBB BBt0OCBB1BABCD CdBBCAAB6XC BBPAB@BLC CL A?B(BJCB B0TB-C@@CC-$8@ABP@.BA4DC@Ax4A4B/CBBACBCBABpBB7BCCMCClABC\CApAA@BxB?0CBA< CBx CBBBCpABCAPA(4BB\BBH@CpA CBPtANC LG0CAG$B4Bt@AB0B CB BBBdBt'A@7CBuC@CB`CbC@@PAXBBBAdBPBECBtECA A`lB(cCB AKpBBB$CB@BB\BHBCABABlBxABp8CB8B|BBPdCB,ABBBPAdBB@PB$BDB B@0CC:CDNC@AnC@AWCBB@@BPCB;CPB$BHAxBAqC?)CBBl"CBBBCB0LBA=BCB`ACDBBh@TCBBgCBWC%CB@@BXJCHBICBB CCABBBA@B08|B B2CCClCBCB P@B0CBABB@CxB@BABCACBF@BbCxBxBC:BcCBhAJuC0CB,B$BoCBBC#C<B;CB`ABB@BxBB^C B\B)CECBABBAICdB,BBICMCDBBCkCOCB`ABPCBAXB)C5CB$BCpAxBAJCBCB_C@$lBhB BBC)CB<BA BPBBDBBlXAACpA BBABDBBBhBBBCBAA{CBCB?4? B8BIC BB[CC-CPB@AAAlBCpCBCAB`APABLBuCAApl CB@A0\BACB CYC!6)CPdB XBAC(B(BlB C CBBB@+CCPC[BCBA@B;CB0BBABWCB C C@C@BBACBlBlAB#CBCTC4ACBBB?DB\VCC,BBBBpAACB` BlB:C C`BBBBTBCABB CCBH ACBhCiC$$B@AxBBB1CCBOCBC2B}CABBDBABBDB/CB4AAlBB"CC$UGC$CCBABTCB$BPC0C-C@CACBA CA`ADC2CqC # ABCCChBICBCBDBABCCBBBC@hB6CBAH@aC<BBAhBBBB|B(BBA|BBBLBH8CBC6CXB.CCBCLC0CPBPCSC B\oC(CL4C0CBCT AHB(ABTBCFBB@CBB9C0@?A CBBATTB@BPBAAA#B&CpBBB@_C0AB8xXB'CBBBCBC,@B@@@@BB`0B ACABCTBB B@ABBBB0BBACdBBBBFCBBJC@ABA BpAJC.CC4B0?CB`B@BpB@A B`C BCIC@BkCAXB5CCBpBBCtBBB@lBT@@CB%B+TBC@dBCC`BB@@CRC5CACC CB2CC@ABBByCBA1CC<BB0B-C[CB|4B5C,AA=BlBfCBBXBA2C0A+CAA"CALBCVC CxB2BBBgCAB$BBB0BDBPC?BBAC BACBJCB8CC?B@BBBfCB`BABABCBABBP|BB4Bp#BBC|C?CBBBAA'CABB CCXB$CpCmCTBC8BpAB,BBABpBB`@BBhLBDppA,B7CBhC4BB8'C@BBfC7ChCBCBBDB2CCCBPBBBA#BBABB<DE CBBBlAPBB0CCHB[C\BB0CAAT CkC CBA$BBxB@ B2ABB\CCBC|IC-CC|@XBA@@B`C@B'CB/C`AMCHBBC8B&.CZC|BB@@$B?|(BBaCBBBB BBHCBC"BBAA@DB ACAlPtB/ClBBBO$$AC`@4BDBCQC0AC@=BIBCE<.C,BCABBdBC$C<BkCxX@B /C B+CdB`CCC@K8(lB?hCtBgCB B\BhBHBC= CHBCA BB0A C\BBBBBB|BBB  C*ClB`BFBBCB B C(CpBBBBBLB$@*CLB@@ CAAHAC,BBAh,B C CABAC)C1CdBB$CABBBLBCB?$B@AAABPABCBdBA CA@XBpABCBCBBB$CCA@@2CeC$BB0ADBB1CBxBBt`B`ApAhBBWA,B$CBPA4CBA"C@ATBBAMPA#C CB B -pA6CB?dBBPDBxB?$@APA$pA@TC`A B9CCB&@CBBCBB@B{CECp BCBCBBBBC C(B@DBGC$BCA2CAB@%CDCCB<0ABDCCB$JCCBBBBCCCT|BCpC@8BBBALsB@ABiC$BB,BC`CB\C7CDCX\CP<B CCB<2BoCcCPB@BBlBPB?PB@5CCtABBBzBBCCAACC0ABBPB{CCCBBB`8CxBXxB@0BBBBpBATBpBpCBAACBBB|CBABhCAC[CBBDCA\BBBCeC@B*CCBdB0C8B AUC0A&CD5CCBMCL B C B(BDBpB BBBBBBCAlBCB4l@CCBBCJCC,+CCBCBAPAxBl@0BB A(BBFCBBDBB=C(PA0|B"CBB,;CATBB`ABoC\CPAA7CPB>C{C@AB BBBmCICCBhBBCCB TB@@ACBA7CmC BtBBX/C BC4B@BdBBOCCDB@BCB`\AT`ACC@@BB BlC/CAA6BABACPAlB8CBBBCBuCBCBCAlxzC.CB,&B0ABPAABC CP2C C@A lBxB?BB(CWC CPCApABCBCB\B CxCB/CLBBBCA@CTBB BECCA8B:C 6BbCtBB@@3\B BBC@BBC CPC{ChB@AABCBA|BB ABCBZCBBBCCB?CBCBBBBAAw@@$CMCBA0BLC;CBBPA4nCP hBjCCBCCCB 1CCCBBACAABBAABAA`BPCaC/CBgCADC B CS+pBCCA@A`MCCXB@BDBBC`<@BPBC$h#B$CCB`$\hCB$B)CiCBCBADCpBUCCL\BBCCpABBABB~CBBKCChBABBAABCBXxBA4C!CX`BCBBB C @BICTCBA40CtC@@BABB CBB%CBA%C'CqAB=C, ABAXBGC CCCBC*CBLB,ABA|BB&C[CA`BB8~C,C AXBB@B,CB$B AXBC+Cn0B|BCBCBDBB2ChCCBC&BMCBBBXBB`ABB BBBCBBCB@@CpP0ABB8BC BA CBxBBBBB/CBAB4BBBB?B%CBBB3C@B`B@ CBlB,BBpBACB(CpB2C}CAQAB@@BACUC$BBB3CC@B~CC@@@B.CBBDBCCA0ZB|BhCC%`ABCtCBACTC@AB,B4B9C B@h?PBB`BBP 0C!C PBB@DBChBACAkBA`AABBBA A8BXB"CBBBBiC@xB9CC BCBBA0AB5CpAPCtBC(C8ClBC@BCBADB@@C)CPBAABC@`<0BJCC-BBB)CBHC CBXBBA|BCA4XBB;CC4!CC6C CBH|B$,BC#C1`AB(CAB CBBB,BDBB@BCBABBBBBB0BBBlC\BBGCCBB0APBl3ClC,TBBB CBBB,`BBBAB@PBA8C$C0ABCBtBCC@@=CAB0CCC@@` BQCgCBB=CBkCCBB0BBNC,BB`AB>ClBlBBBBCBJ#CB0BCOCBB#BBBA2CBB;C"CBBDB@BBBCC/CAp@ B CBBlCBCXBCBBpBBBCBBBCCA[CvC7CBZC`AAB(BBBQCACCB@@CBC B$CB"C?CCKC NC0C$|BCBCHC8 CAdBBtB^C@6CBCBCABBB/C CC B CDB&C,C(CCBBwC@@P2lBPB{CBBBBCBCtCABBBB4CBCB`B@LBBBPABCCBB4BC^C,BB_CACCBB8CCdBCC@BCBpB@C?CCX|AtBC0 CB@AB{CP@A3C#BA CC>CBAAdBDCBCA$BCBBBA6CBCBQB*CYCBCJCBCCB(B`ALB%CCABuC`dBC'C BpCB|B CBIC+CCCB BBBBBB`AECCCsCANCXB4B@CACCCBtCBf?CBB*CYCBBBCBBNC(BdC0B8BB`AB@)CB@C CBBB}CBCJCB@BdBTZCBCBP@@dBBCCPA ABCCAB^CBB\BDBBBB4BC'C3C.CCCPFCABBABBA+C@BBAB BBpBBBCTAA;CBBAdCBHB:CBBB-BB+CCC:[LB:CwCBSCABlBCCBBC5C}CTCB0B5C BBCB.CBBACB01#C CB"CBA#CCpA,@ BChB@?BQCBACvCB4B@ABuCDBoChBBBA CBBKC@C ABBdCA9CC'C6BCBB@BB`@AC,C?XB|BB@A4CZ?CABCACC@C@ABBB@@dBBpABBC$B| B(CCBACBBA`4CAC@BBPB CBBDBBHdBBCBBB;CDOCpBBBBBBB C?CC B#CpVC@BDACB`AAB=CB BXBCC C:ClBB0CC9CBbCCXBBLCB(B CB'CCACA`CABBCCBACTCeCB[C*CB C@@hBBPB6CBECA>CCB@BBCBBBBBbCCCBhiCBDB|BCCBCPLBGCKC/C?B BBeCBC$tACMC BBZBHBCBB:CCSCNCAC$CBFCCB,ChCB`BBABC%CCqCBBBPBA'CBB4CBdBBBPBPCBB C4B@XB BBBBC6C(B$CCCHB`ACBBC{CBJCpAB%CCB((BCHBHB"CACBrCBBApABCAtCCBBCDC@,BCBBuC:CCBAECBNAXBCfC@BBCBBBBA&XCChCCXB$CB(B,CBBCBC<Q/C@A CCBBBB;C4@5C@4BB AC C\BC3CB@ADBICeCBB@C@VCBCBLBC'CBBBA!BC@BBA8BQC,BpBPhCdABVCABSCABBBB0AAACBBBB@ABB3CCBBCTBACC0A|CCBABhB A4BdBB]C@AKBoCC@8aC C8ABBC~CB|B1CCC ClBC80pBgC| CB0AC8CBCBAB.CA=CB4B@@BCALB`CBBBBBC'CGCABBAACCDBBBA BCCTP0t CECB8Cx@BDBcCBCAoCBBD3C2CBA C\B`XBAABB BBPABPB A0BBGC^C@pC#CTBBhBZCChBB CCnC>CBCGCdCRC@B8CBCBA9CCdBB(CB{CAdBHBwCOC`AfCCtVCB0AB{CgC=C6C(?CD B#B CB,BACAp0BpBB4C{CrC ,BBQCCBCB@tBCA0C6CABDgCCABBBABACgBCTC1C0AB CBBB+CBBABCC1?BAP[ChB@CB[CAC@AC%CB;CBMC@@BAACB\C`A BCB8C\C|@4BpC7CAPBCABBCC BCCAC2CTBBCAABACBCBLBAC+CCC<TBBCpAC:CABC C/CBCBACABC`B0BBB@B@BB@ASCCB ACChBBpAC0AlBBLB-CCACBPAUCOCCWC@CdCCCCA@B CBCBBB|BBbC0C BbCCxBCBAA\BMC0CBBCBCBBA8@ C'CB3C0A@@ABBCBP,CCCCUCBCBCBBC_C@@CBBB(BB/CB8BBB'C LB4B\JC^COCC_C`B A,CCBnCPC@CBBABCBeC0BBNCNCNC)C|BC5CdCLB=C|B C(BBB8ABBBtB5C2CBCBxBCBBA$B8CA CBB!C)HBBBCWCBvCCA@CBPCCCA6CBBBBB@OCBC#C9CBB!CKC@CBC1CaCA8BCGC2CBBPABCCCCBCB9C CBBWCCCTDCXBBB7CBTBBBzCC>C,BBBpB>CBZCB\C"CBGCDB}BBC+CCMCC6CBJCVCCRCBBB@@CCBA@dCxCCCB8(CBC`B>CCCBACBCA|BCC BxBCCAxBABCOCBB?ClCxB#C@@5CAAABCBB,Bx-C*CACBCCBC CCpACCECTHBCdBAAC&C!CBCAlBABbCLC`CCCBBXBBXCCkCBCB ABCNC AChBBPCB*CBBBsCFCCVC(BBCCAAPBPCuCBPA B+CBLBbChCB%CC C_CYCB8BAdBB{CaChBBA%CC$A$B,BCBB.CjCBC8BBCsC&ClB@DCtCBUCCAADBB1C-CvCB CB@B(CAtBBBC`BTCCC`ABGCBBBCBBPiCZC@B CA,BBCCBBBC5CBXBBHC8BBBCdB;CBCsCXDBCiCCBB2CCCCABB$BCBxB C$CB1CdCABYCCBCCBBB0CC3C"C C@BBABC+CBC@BC-CBBdB\B`CIC$B C C(CC|9C6CBAdBoCaCBSCB AACBICB>CvCB'CCCh,BC+CHCC CBdBABfCCABBBtC 4BBBxCBAB BBoCBBJCBC{CBIB@CBB@@BBCCB-C:CBCA\CBhCyCt0BpAA^C@CB)ChBBBBBFC@BnCCBC@@BBA@@QCCBC BCAVCMCAB`BACCB=CB`pCCTC,CPAB@@CCC CBL ABCCACXB0AB*CBBxBCjCCABB|B CBBACBC/C7CdCBBxBL@PACSC@-C@@@.CBl&C&C_CBBCC#C@PCCB3CBx=C?AgC4CBBBBXB`ABBBB@A&C@BUCCC"CCpA)CCFC{CBBBCnCeCXBKC|CBBAOCCC"CVCB0C/CC`B CABCB-C\CC?CTB4B?CBtCCBA@CCCC CpAC@5C|BCC8B8CyCMC8BdCCBCOC`BCBCBCdBC_CcCBD CCCCACACC,CCBABp7C B(BXBECCCCBB CBWCCBCBhBBBBCCB,CA0BC1CIC/CCBCBQCCBB&CABC:C"CBC(C+C=CC9C6C,B*CQCBBCNCXBCC8CC,BCCBPCtBBOCC*CBCCB"CBBCCXBC*CCjCAjCtCWC1C0CBB7CC@CCCC1C-CBCCC C(CBBCCBCBBB(CBxBBLAB9CCBECBBlBB2CCBtCB9BB@C/CJC:CP,C,CCVC@@B@BHC'CC CgCCqC1CACyCBBCBB|B\CMCCCCBCCwCBB(CBCxBBCCpBACLBC CBdBBBP BCCB%C\BCTBCpA BCBC$C=C\CB"CC`AAACjCBB,B@@A^CCBJCCCCC4BCKCBCBBxB@BCCCBBC{C&BXCCBHB@BvC3CiC5C,BBCCBAB|C9C1CBA=CbC@C+CcC`A0C|ChBB#CBPBAB?CBCBB|B`ABCBCBBCB C7CBBCBCCAQCVCCC B8C;CC BCBBBBBB@BBmCBACA@ BBaCBCCC?CTBB0B,BCBB C7CACCMC8ClCBhC#CACCYCB;C2CBBB,CABpBBCCBeCA C.CnCCBBBC3CB4`,B,BCCHBBXC#C}CC$C1C SCBCBB8B`BYCIC`BBCAHCC CXBCCCdBBPCBuC\C-CVCCBCMCCBaCCC8BCKCCZCACKCjC!CCCC!C+CTC|pB}CC;CBBwCCYCCCBTC4CUCCTBLBCCCHCBB$BBCtBC7CC}CBCBCCBClBdBC|CxBB^CuCC*CC{ChC@C>CCCPCBECSC@DC,CaCWCBCCCvCqCC9C'CC&CDCCCCC,CpA BGCC2CBBC CB%CCCZCCtC@@tBBCCC8CCCCMCABBCXCCC;CA|/CBCJCgCBACRC"CCdBaCCQCDCC(B@@dCBCCC9CCB|CChBBC\BUCCCCB(B|BBwCC`CCCBcCjCC'C|BBTCqCCB@APAlCCbCCCC~CCC"CBSCLBCBCHBACACqC BBGCCCAACB B0CBTCCbCA`_C7CgCAA@BLBC{CeCCAC/CBCA;CBACCCCC4BB.CAB#CAaC>CC[CCHCB4C-C-CKCBBB$CBB C$BCgCBCBBBCBCC@CBB$CCHCC7CtBC C!CCB0 CCCCC@ACBA1CCCCCB CB\0BCCCC BLB\[CCCBCJC8B[CCCfCBB#CC@CCCLBCCBB BC,CCCGCB ACC@BnCQCjC#CCLCBCCBCBBiCCCB,CvCC*CDC@CCCBJCCBJC BA0BqCmCBBLBBC CCsC@BBxCrCCCCBBACCCCCsCCCCBlCBBBCSC9C+C`ACBCCBB]CB.CC3CC CB"C|C`C(C)C@C_CzCBCkC $B`BC|CBtB,CCCCCCCiC@CbCBCBC]CXBXBXCC[CCCABCC CBBCCLCCOCBCC"C CoCBC B+CBBTCBC_CCCCBBC(CCSCABCCCBCC@CC$BB?CC CCCBC`CBCCoCCCB\CCBVCC`C{C@CCCCBnC]CCCC BCC@@BBCCBCCCQC5CGCDBC]CdBB BC\BCCBB0CBBjCCUC8BfCCCCmC\BC3CCPBCC/CB@)CPCCCCtCCCC2C"CCCLC CCC;C:CC\CCBCC:CCCNCCvCFCBCFCCCCBBCCC4BByCyCCC C/CCACCC=CBXC;CA4BNCCC#CB!CCCCCCCCCClBCxCCCCBBC`CCCCCFCCC9C2CC4RCC>CXCpCBCbCCCCCKCvCCCCCCC@CCCCcCqCCCCJCBfCCXCzCCC CCC$CTCCCYCCACCCC DNC-C1CACbCCBCCCCCCrCCPCCC7CZCCCCCCCQCBC%CCCCC CC%CCCCCC,ByCCCCCCDCCCC:CCkCCzChCBCCACCCCCCCCC]CCCCCdCDCCC/C)CCjCCCaCCCCCCC6CCCCCCCCCCNCCCCCCC CCCCC8CCCCqCtCCCCCCCC,CCCCCC)CBCCDCACCCCCCCC]C@DCC{CCiCCCClCPCBDCCBpCC)CDCCCCBDCjCC}CDDCCCCCCCCC$CUCCCCCCCCCCCC2CCCCCCC~CCCDfCCC2CsCCC_CCCCCCCPCC DCCCCCCCCC)CPCCCjCCCCCGCBB^C-C C(CCkC_CCBCrCLCGCCBCCXBB?(CCC CA CB=CCCnCCWCCCCCCCkCLCCBBCCCCBTCBBCCjCTCB&CC\C C{CJC1C&CCBC.CJCFCCBmCBBCC/CxCCPCKCCC;CC|CWC$C:C1zCCCCC'CzCCC1C5CCCCNCCCCCzCCC?CICC]CCCCCCCCCDCCmC CCCCCyC+CCCCMCCCCBCCbCCCCCC0CeCBCCCCBB{CCTCC9CLCCiCECCCCCuCCcC1CCxCgCpCCBBC}CCpCBCCCCCCCOCBCCCCPCCCCCC3CCCB$CCCBpCCCnCCtBBClBkCC#CCJC+CACVCCCCCCBiCCCCCC>CCBCCCCC?CCCYCCtC+C"CUCCXCCJCiCCBCCDCzCCCCCCSCCCCCCCCCCCvCCCrClCCCCCCCCCCCCeC DDCCeCCCDCC+CCCCCCDCCCC@DCCD@ DCCCCCCCCCCYCCMCCCCCCCCCYCiCCCCCCC DDCCCCDDCDC(CCCCC$DCCCC>CCCCCCCCCpCCCCCCCCCACCC@DCCCCC@DCCCCC DCCCCC)DCCCC{CCD_CCCCCCCCCC@0DCCCCCCCCCDCCCCCDCCCCDCCCCCCCUCDCDCCXCJCCCCCCCDCCCCCCTCCCDCCCCCCCCC DCCCDCCCCCCCC DCCCCCCC:D@ DtCCCC DC D@DCCCCC D@DCCDCCCC@DCC DCCCCC.DDCD@ DCCCD/DCCCCCCCCCCyCCDCCCC&DCCCQCC@DDCDD@ DD@DDDCgCCCD D@DCDCCCCCD@DC@D DCCCC"DDDCDCD@DCC*DCC@ DC@DPD DCCCDCCC6D D"DCCDCCC4DCCCCDCDCCD=D@DMDCCC$DD@D DCID@KDDD DD1DMD?D3DDC@DDD#D@DC;D'DDD@6D7DD@=D,D@D/DDFD)DCD#D D-D@7DD5DGD9D"D=D@DD-DC@2DIDC"D@ DDCDID@&DD@D@4D@.D"DC2D&D@&DSD6DD"D@NDDC@DDLD@\D,DCDD#D1DD@DID@JDDC@D DQDaD6D%D@2DDD@DDD,D@ DCD7DCC'D"D(D DD7DD!DD@'D@*DD:D D,D;DC@5D;D DC,D>DOD@[D@1DD@D@$D@DD,D@/DUDD)D@0D@D@DDD%D7D@DC(DD D@DDDDDDD0D7DDDD@ D@D@&D@2D]D8D4D@GD#DD D@9DDD@D,D DDD@D(DDD?D D;D>D+D6DDDD@DMD,D,D@]DHDD2DKD1DPD+D-D@;D?D>D4D#D@LDuD@DD@2DVDTD@nD@qD\DFDPD4DGD6D:DVD@ID1DID@^DID4D@DDUD@dD@D$D8D$DhDbD3D8DbDmD4D8DLDRDAD;D,DcD@8D@/DZDUDQDBD/DCDNDsD@#DZDGD*DpDSD(D@KDbD@:DD@cDD@D@@DIDWD@FD)DCBCCSCCCVCCDCCCCCC:DCtCCC DCC@DCD@DC DCCCCCDCCDCCCCCCCCCDCCCCDDCCCDCDCCCCCCCCDCCCDCCC6DDC@DCC@DCCCCCDCCCCC DCvCCDCCCCvCCC&DCCCCCD@DCC@!DCCDCD@&DCCCCCCC@ DCCCDC@ D.DCDC@D-DDCDCCDDCCC"DCCCCCCC@DCCDC8D/DC D.DCDCGC@"DCCCCCDDRCCDD@.D.DCD@DCCCD$DDC@DCCCCCCDD@5DDC DCeCC@DD@D5DNCDDC+D,DCCC DDCCD D@ D@D@ DC DCC@D DCDCCD%DC D@#DCD@DDD$DCCCCCCC@"D@JD&DCCCC@DCDDC,DDCCD@DD DC@DDDD@DD@DD@DDCCDDC DCCCDC D DCDCzC%D&D@ DDCC#D$DCCCCD&DC4DDC;DDD@DDC DD@DDDCCD DD@2DD-D8DCCCCD@DCD(DC@ DCCD;D!D^DPDD!D@(DDC@DDDD DD,DD@BD'DCCCC%DDC DCC DDC!D@#DCCDDD@%DDD@DD=D=DD D+D@0DD@LD DC/D@DCCC@DD DD%D(DDD D;D@.DFD'DXDDD9D*DID@ DD@D:D"D*DYD]DDCD:D:D@D DDDEDCD6D4DLDD*D"D%D3D@DD.DDWDDD@)D;D@!D(DTDCD4DD@D3DSD=D@'D4D@ED*D>DcDLDDDUD@DRDLD,DHD!D3DnD@)DCCD.DID@WDtD@DPDHDSDDDtD D\DSD@D@hD`DjDRD DlDD@[D`DjDQD[DD@KD`D@`DSD=D@IDaDD@D2D)DIDwDD@wDHD_DVD4DrD3DnDRD+DZDVD\D@@D@PDgDJDDDZD@QDBDCDKD@OD@4DmDMDiDDDoDDKD@ID@D_DYDaD@ZD'D\DDSD?DJD@lD@D`D@DD@/D@-DDD@D@@DD@DDVDD;DD0D DLD D@D5D@NDPD@TD%DC@1DQD'D@.DD@)D@D@7D9DCD+D-DC@:DbDDD)D.D7D9D;D@*D@D@DDHD9D DED@ID@DD@]D9D@#D@#DC_DQD)D%DKD/DND-DD(D@;D*DfD@BD D@D7DBD>D*DD,DD6D,DuD4DD&DD-D5D%D@!D"D#DaD@&D1D@$D5D@D@D$DBD@D_DD9D@ZD]D&D0D@DeDTD@GD@AD3DC8DD/D@5DED!D:DD\D*DZD:D?DKD}DgD@D@D@HDlD@iDQD@PD@~DQDXDD@9DcD^DuD@CD@$DTDUDjDKDqD_D@DZD@}D@8D@.DBD-DvDZDUDXDeDRDXDeD@vDSD@7DDHDOD.D/D6D3DjD@PD@D#DUD@D{D@=D@,DsD@lD@dDjDjD&D)D@iD7DTD@JD'D@D@}D@KDlD@HD,DgD@|DAD@vDD@1D@)D@9D@DEDEDRDcDFD@+DJD@XD@rD@XD@HD@QD:D@YD[D@[DaD^DsD@hD4DMDaD@4DD}D@=DD*D@MDFD.D_D@qD@:DgD^D|D^D`D6DqDjDD\DjDUDmD~D@VD@KDaD[D|DnD:DBDwD\D D[D\DbDGD@KD}D@ED7DsD@hDoDDcDADRD[DDDyDuD@vDrDbD@\D@aDTD@DuDkDgD_D@gDDDcDvDgD\DDgDsDDD[DNDcD_DrD`DIDwDeDEDzD@zD4D:D@D@6D~DDD@DMD[DfD~DWD@VD@vDtD@DnD_D@DvDDD}D@mDlDXDeD~DDhD}DyDDD DTDD{DdD@kDDD DD{DDD@gDDhD_DD D|DRDhDHDpDDHD}D`DwDD@yDZDWDDDDDD`D@DaD DDpDD`D_D@DD`DD@jD@rDD]DmD@eD{DDDDgD@5DDD@DsDSD D`DoDD|DcDDDfDDpDwDDDnDDDuD}D D DkDDDDrDD D@D`DDDxDDDfD DDgD@DDDDD`DDxDXDDDDDDDDD@}DD`DrDfDDDD`D{DDD@D@DD`D|D@D@D`DDDDD]DD@D D`DDDDDXDYD@DDDDDDD DDD DD@DsD@D@DD@DDDDD D DDD DD@~DD@DDDvDDDDDDD@D~DDgDD`DDDD`DD`D DDDD@DDzD DDDsD@DD`DD@DD@DDD@D D`DD@DD@DgD`DDD`DD`DnDD@DDDD@DD DD DD DDD@DDDDD^D DDDDD`DDDDxD@DD@DzD DD DyD@DDDDD`D@|D`D"DC$D%DC D'DDCDC>DaD@DKD@JD$D7D DC0D@@DD D"D-D'D@DDHD2DD D9D@4D@1D6D D@0D;D+DDD@9DD1D)D]DWDDC)D]D4D@DD&DPD7D0DADUD D@DD@SDRD(D=D'DJD3DRDND!DDCDDsD@DD)D:D"DC@\DTDPDAD,D3D(D@D,D;DCD@XD@FD@DSDXD5D1D DLDGD@2DD@SD4D@)DD!DD@KDCDDWDD!D>D@>D1DrD4D3DZD@iDND9D3D@$DZDjD'D:DID%D@WD@:DD?DD3DcD8D#D@JD@UDUD@ND@4D7D@JDPD=D@nDeD%D.D1D@4D@MD#DD\DSDMD~D@6D@D@)DJD7DID@NDD@/D*DDD@BD=DLD+D\D@iD@/D@HD@=D@-D-DnD0D@HDPDLD@LD@"D@ED$D@DZD]D!DBD@TD@HD=D@>D*DkD(D@#D6D@D&D@dDoDD?D$D1D@GD*D(D2D8DND@fDDNDDD6D@WDRDD@%DRDgD@?DRDZD@`D@KD@CDUD'D@WD@DVDTD>DD@DD6D@SD@2D@?D@D@`DhDeDPD8DPDMDDNDVDKDfD_D6DKD@RDMDjD[D@RD@vDvDQD`DpD@.DPDaD;D_D@NDDDKD@UD9D@PD^D%DFDrDBD@mDaD6D@rDWDAD@PDDdDJD@7D@D7DuD@cD~D[D`DMDWD(DRD|DCD@|D@DD_DmDPDODD@D@MD_DCDgDDvDoDLD@uDnDbDED:D@rD@DYD@cD DwDDLDeD@nD@;D?D@jDjD@DnDLDOD@hDrDD@aDD@tD@fD@D@D@yDfDD`DUDDfD@HD@\DDdDDD D@mD@jDXDUD@DyDD D@D@]DDnDDmDMDDD_D@D@{DwDyDDNDnDxDdDDlD@gDD@CD_D@DD>D@MD~DFDvD`DaDD`DuD@DjDhDD@D{DD@DuD@nDjDjDDuDfDvD@DjDDDD\DcDDD@D`DD`DD`DtDCDhDD`DDD@DD D|DmD@pD@^DmDDkDD~DDDOD@oD D@DpD DDD`D`DDUDcDSDgDdDHD/D@oD_DfDqDBD'DkDFDPDDvDbD-D@qD@UD@mDZDGDoD@\DRDdD@D=DbDDWD DzDDD@jD@JD@DDD@-D@dDGDjDiDqDfDwDD@7DGDDVD`D@vDDnD|DEDnDD@PDbDQDDiD@D@DsDOD4D@_D_D@BDyDnDqD@QDGDUD@TDqDIDtD~D@QDtD`D-D DDiD@fD@xDKDnD_DD\D~D@|DuD DnDzD{D^D~D@zDDDrDCD~DD`DD_DDnD[DVDDpDjD@qDD]D@D@DmDD@D DD DDDDqD@~DDDD@DYDD DPDvDhDD@DeD}DDDtD@DD{D@DkD/DD DD@DD@DDjDlDD@D@D`D DDDbDgDyD DDDDXDuD`DsDDD@8D DDDD@tD~DDsDkDyDDnD@DnD@zD@sD]DiD`DDDDDDnDDrD`D D`DDwDeDD@DD@DDfDsDlD@D@vDDgD DvDD|D`DDD`DtDDDyDD@|D`DD@DDDD DDDDDDDD{D}DtDDD`DxDD`DDD`DDgDDDD`DDDDxDvDDDdDrD D DD D@DD DDDDvDDDD`D DkDD`DDDDDD D@|D`D DDDD@DDDDD@DlDDDDDD`DD D@D@DDDD D@DDDDDDD D`DD`D@D`DDDD`D`DDDDDDDDDD|DDDD D@D@D@D@DDDD`DD`DDD@D@DD@DD@D DD@DDDD DDDD`DDDDDDD@DDD@DDDDD`D DD`DDDDD`DDDDDDDDDDD`DDD@DD DD D`D@DDDDDD DDD`DDDD@DDDD DDDD@DDDDD DD`DDD@D@DD@DDDDD@DD D@DDDD DDD`D@DD@D@D@DD`D DD@DDDDD`DDDDD`DDDDD@D@DD@DDDDD@DDDDDDD`DDD`DDDDDD`DD@D`D`DDDD DDD DD`DD D DDDDDDDD`DDDD@D D`DD`DDDDDD`DDD@D`DD D DDDD@D`D DD DD@D`DDD`DD`DDDD`DD DDDDD DDDDDDDDDDDDDDDD@DDD D D`DD DDDDDD@DD`D D DDDDDDDD`D DD D@DDD DDD`DDD`D@D@DDDDDDDDDD DDDDDDDDD`DD D@D D`D@DD@D`DDD@D DDDD`D`D@D DD`DD@DDDDDDDDDDDDDDDD D`D`DDDD`DD@DD@DD`DDDDDD DDDDDD@DD@DD`D@D@D@D`DD@D`DD D`DDDD D DDDD`D`D@DDDD@DDD@D@D`DDD`D@D DDDDD`DDDDDD@D@DDDDDDDDD`D DD DDDDDD DDDD`DD D DDD DDD`D`D DDD`D DD DDDDDD@DDDD`D DD`DDD`D`D@DDDDD@DDD D D DD DDDDDDDDD@DD@D@D@DDD`D D@D@DDD@DDD DD`DD D D@DDDD>DC`DD DDD@qD`D@yDDD DD@bD@DDDDvDDsDDDD^D D~DUDD@D~D DDD D@DDDDDD@D@ZDD@DD{DiD`DD`D@aDZDDRDD`D}DlD@D{D`DDD@DD@D D D D DDzDD@DvD`D@DDDDD DD@DDD`D`D@DD`D@DDD`D@SD`DDD DDDDDDD`D DDD`DD DDD_DbD D`D`D`DD`D@DD@D`DD@DD`DD`DDDD@DnDDD`DDDDDD`DD@DD D@DD@DDDDD`DD D~DDD~DD`DDeDDDD DTD D`D@D DlDD DD@DDDDDD}D`D@DDDDDDDnDDDDDDDD@D@DDDDDDDD@DD`D DDDDD@DDuD@D DDDDvD`DDDD@DDDD@DD`DDDDDD`DD@DDD`D`DDDDD@DD D DD@D`DDDDD`DDDDD@DDDDDDDD`DD DD@D@DDD D`D DDDD`D`DD DDD`DDD D@D`D@D DD@DDDDDDDD`D`D DDDDDD@D`DD`DD@DDDD@DDD`D`DD`DDD`DDDDDD@D`D`D`DD@DDD D@DDDDDDDDD`DDDDD`D@DDDDDDDDD`DDDDDDD`D`DD@DD@DDDDDDDDDDD@DD@D@DD@DDD DDDDD@DDD`D`DDDD@DD D DDD D D`DDDDD@DDD@D@DDDD`DDDD@DD`D@DD@D@DD@D DD`D`DDDDDDDD D`D DDDDDD D`D@DDDDD DDD`DDDD@DD`D DDDDD`DDDDDDD`DDDD DDDDDDD`D@DDD DDDDDDD`DDDDDDD`DDDD@D DDDDDDDD@D`DD`DD`DDD D D`D`DD@DD`D`DD@DD@DDDD@D@DDDDDDDDDDD@D@D`D`DD@DD DDD@DDD D DDDDDDDDDDDDDDDDD DDD DD@D D`D D DDDDDD DDD@D DDD DDD D`D`DDDD D D@DDDDDDDDDD`DD@D`DDDD`D`DD D@DDD`DDDDD D@DDDDDDD D`DD`DD DDDD@D`DDD@DDDDDDD`D`DDDDDDDDDD`D`D@D DD D`DDDD`D D D`D DDE`DDDD@DD DD`D`D`DDD DD`DDDDDDDDD DDDD@D`DD@DDD`D DDD@DD D D`DD DDD@D`DD D@D`DD@D`D D`D`D`D`D DDDDDDDD@D@D DD DED DD DDDD D@D DD D`DD D DD`D@DDDDD@DDD DD DD@DDDDD@D DDDD@DDDDDDD DDD D DD@DD@DDDDD`DD`DDDD@DDDDDD@DDDDDDD@DDDDD DDD D@DDDD DDD@DDD`DD@DDDDD`DDDD`DD@DDDD`DD D@DDDDD`DDD`DDDDDDDD DD`DDDDD@D DD DDD DD@DD`DD@D`DDDDDDDDD DDDD`D`DDD@D D@D`D@D D@DDD`D`DDDDDD@DDDDD@DDDD@DD@DD`DD DD`DDDDDD@_DC`DDDDD@DD`DDDDDDDD@D D DDDD@D@D@DDDD DD DDD`D`D@DD`DD DD@DD`DD`D@DDD DDDDDDDDDDD@DD`DD@DD`D`DD@DD`DDDD@D@D@D@DDDDDD`D`D`DDDD`DD D DDD`DDDD`D DD@DDD@D`DDDDD@D@D`DDD D`DDDDDD DD`D@D@DDDDD`D@DDD@D@DDDD DD@DDDDDDD`D DD DD@DDDDDD D DDDDD`DDD`DDDDD DDDDDDD@D DDDDD@DDDDDD`D`DDD`D`D`D@DDDDD@DDDD@D D@D`DDDDDDD`DD D DD@D D@DD`D@D`DDD DDDD D@D@DDDDDD DD`D@DDD@D`D D`DDDDDD DDDDDD D`DDDDDDD D`DDDD DDD@DDD@DDD@DDDD D`D DDD DDDDDDD@DDDD`DDDDD DD@D DD@D@DD DDD DDD@DDDDD DD`DD@D`DDD`DDPEDD D@DD`DDDDDDDDDD@D@DDD DDDDDDDD`DD`DD DD DDD`DDDDDD@DD DDDD`DDDD@DDDDD@DD EDD DDDD`DD DDD DDD`DD DDDD D@DDD`D`D@DDDE`D@DD@D EDDDDD`E@D D`DD`DD DD@DD@DEDD DE`D@DEDD DDDD D0EEDE`EDDDDPEEDEDDEDD`DD`D`D@D D@DDD D DDDDD`DDEDDDEEDD@D DDDEPE0ED D`EE EE0E DEpE0E ED`E DEDEDEDE@EDDD0ED@D EEE`D`DDDEDE@D@DDE`DDD@ EEEE DDEEE`DEEEEDDD DP EE`DEPEE D0 ED DEDDEEEEEEDE0E EDD@DEEDE E E D DE` EEEE@DEEPE EpE@DEEEDD E E ED@DD@ EEEDEDE EpEEEDE0ED E ED@EED@ E ED@EPE`DEEDE EE E EDEEE DDDE` ED@E DDDPE`E@E EEE E@DDP EEDEDE`ED`D E@E0EPEDE EDEEEEDEEEEE@E@DDDDEED EEPED0EEDE0E@EE D@D`DDDDEP EEpEDDDEDE D E@D E`EDEE DEPEEEED`EEDDD@DEPEE EE@EDDD`EDD@DD`DDD`D EDD@DE`DD`D`DD DD@DD@DDDDDD0E EE@DEDD@D`DDEDD DD@DDD`DDD0ED E@D DD`DEDDDDD`D@D DEDDDD`D D`DD@D@DEDDDDDDDDDD@E@DD D@D@DDDD@DDD@DDD@DD D@DD@D@DD@DDD`D D`D`D D`DDD D`DDDDDDD`DDDD`DDD`DDD@DDDDDDD DDD DDDDDDDDDDDDDD@D`DDDDD DD DDDD@DDDDDDD`DDD`DDDD@D@DD`D@D@DDD`D@DDD@D`D DD@DD DDD`D DDDD`D DD`D@DD`DDD@D D`DD@DDDC DD D DD@DD@DDDD DDDDDD@DDDDDDDDDDDD@DDDD@DD DDD`DD`DD`DDD@DDDDDDDDD DDDDD@DDDDDDDDDDD@D D`DDDD@DD`D@DDEDDD@DD DDD DD DDD D`D EDD@D@D@D`D@DDD`D@DE D@D DDD`E@DDE`D DDD`D@D D@DDDDE DDDD@D DDPEDDDDDDE`DDDD DD`D DDD`D@DD`D`DD0EED DDDpE@E@DDD@DDD@D@D@D D`D DE@DDDDEDE D`D ED@D DEDEEDDDDEPE`DDD D E`ED`ED`D`D@DD EEDDDDEDDD0 EE Ep E@DD DDEDDEpED@DDDEPEpE@ E`ED E0 EEDDDPEE0EEP E@D EE DEDD E`EDDEDPEE@DD0 EE@E`EPE E EEED`D0EEDDE@D0EEDEP E EEDD0E EE EED DE@ E E0E`DEDEpE EE EEE@E@E EE`EEPEE EEpE@DEEDPEEE EEE E`EPE E E E EEP EE@EE@ EpE0 E E EEEEEE EE@E EEp E E` EPE EPE@EE EEEEEP EEpE E E !E0EE E EEpEE EEE EEEE0E EP E` EE E Ep E` EEEEEEEEPE E E@ EEE EE EEEPE@E EEEEEE EEEEPEP EE E&EEpE EE@ EEEE@EEp EEp EE0EEEPE EP EEE0E0EEEEEpEP$EEEE EEEE0%EEEpE EEE0E@EE0EEEEEE0EEpEPEEEEE E"EPEE`E0EEE EE@EE@!EpEEEEEEEp EE E EEEEE0E@EPEEEEE EpE EPEpEEpEEEpEEE@EPEEpEE`E EEEE(E!E0E EpE E EEpE`EEEEPEE0EEE E EEE`EEEEEEEEE`EE`EEEPEEEEpEEE`E EEEpE"EEEE@E EEEE EEpEPEEEEE@EEEP E E`EEE0 EEpEpEEpEE0E@EPEEpE`E@ E@EEE EEPEEEEEE EE E0EEE0EEEPEE@EE EpEP EPEEEE EEE`EEpE0E EpEEEpEE EE EE`E@E`EE EEE0 EE E E EEE E E@EE EpEE0EEEE EE E0EpE0E EDE E@ EE EPEE0E0E`EEE EPE EEE EPEE@DE E EE0EEpE0 E`E EEE E0E EEE0EEE EEEEEEPEEE0E EEE@DEE0EEEEEDDE@DDEDpEDD@E E E0EED DDDE@DEEEDEDDD E` EpE`D`D EED@DD`DD E EDD@DEEDE0ED`DD@DD EEDD`DEPEDDDDE0ED D`DD`D D D D`DDD D`DDDDDD@DDDDEDDD@DDD D DD@DDDD`D E@D`DDDD`DDD@DDDDDDDEDD@DDDDD@DDD`D@D@DDDDDD DDD@D`DDD`D@DD`DDD`D DDD DDDD D`D@D`DD`DDDD`DD@DDD DDD D D`D@D`D`D@DDDDDD DDD`DD D@D`DD D@DDD@DDDDD`D@D@DDDDDD`DD DDD@MDCEEPEEPE EE@EDE@E EE DD0 E0 E EEP E@E@DEEE0EEEEDp EEPEEEp Ep E0E0EE0 EpEE EE`EEEE`E`EpE@EEPEEE`E0 EE0E EE0E ED E0 EEEEEpEE@E`E@EDEE EE E EEEEEPEEEE@ EPEE0E E EEEPEEE` EEEE@EEE0 EPEEEE E@E@E`E EE EEEpEE0EpE0EEPEP E0$EEEEEEpEEE E$EEEEE E`EE0E!EEEpEpE EEEpEEEEEE E0E EEEE EEE`#EE`EE "E E E EEEP EEP)EpE@E@Ep!EEEEEEEEEpEEP E EE0E@E EEE"E(EEEEP"EPE &EE!E!EEE-E&EE@Ep!E0EEpEE@EE@E0E"E$E"EpEE EEEE%E"EPEEE@ EP*EE@EE`EPEEEEE'E'EP)E` E`EE@EE@EE EpEE!E!E"E&E'EE,E%Ep E%E`'Ep#E"E%E%E`)E%E E0E#EE'E@#EE0#E0.EE0#EE"Ep0E0,E$E)E %E$E#EEE(E0!EPE4E4E`+E +E0E &E`+E0(E E&E.E $E E)E+E!E0%E`&E'E-EEE`(E@%E0E$E%EP)E+E+E4E!E#E*EP/E+E`2E%EPE` E0,E,E0E 2EE'E&E0)E1E'EEp&E@4EE0EP(E$E@)Ep-E'Ep4EP+EE-E-E E$E+E'EP)E(E'E-E9E`;E0-E0/EP'Ep,E&E&E2E FE0E@3E%E0/E`0E0/E'E5E`+E*E.E5E/E 2E/E#E0E1E@*E8EP+E!Ep$E@+E2E4E#EEP.E04E%E@3E.E (E2E)Ep(E$E'E'E-E)EE E,E`*EP)E$E`E@0E3E"E5EP/E*E4EP%E"E%EP0E+E6E$E)E1E2E&E 6E9EE 1E-E,E+E-E$E`)E0E`E(E@2E.E;E6E0*E*E@-EE+Ep&E-E`3E'E EP1E)E#E%E+E E2E-E(E)E.E0E1E&E(E-E 1E&E+E'E!E+E*E+E-E2E(E0/E3EP'EP5E*EE`E"E,E5E.E$E"EE(E0E@*E@!E`-E%EEp3E*E 1Ep/E$E0E$E!EEE2E/E0+EP(EEPE#EPE%E0E #E$E'E0'EEp%EE E-E*E/E@"E E,E9E ,E E%EE$Ep.EE0E#EP$E(EE`E(E!E` E!E`!E'E E/E(E`*E@#E E-E /E%Ep#EE#E@,E2E!E%EEEE E E/E1EE`EE"E3EEPE(E(EE0'E`E0EEE)E*EP!EEEEE#E`EEEpEE E "E E EEEE0E E!E@5E$EEE@EEEE &E(EEPE@%EE $EEE'E$EP EEEEE!E0 EEEpEE"EEE@$EEEE0 EE0"E@EEpE@ E`EE`EP!EEEEPEpEpE EEp#E E@ E EEEEEEEPE EEE0 E E0E@EEED0EEE`E EEPE@EE@EPE0E EEE E0EEEEE@E EE`EEP E E EEpE0E EE EDEEE E EPEE EEpEE0EEPEE EEE E E E@E0 EE EEDE@E@EEpE D EE@E@DEE@ EpE D`D`E EEEDEEEPEE@DDE DEDDD E`E` EED DP EDE@DDpEEDDD0EEE@EPEE`D@E`DE@EDDDDDE EDD`D@DD@D DD`D@DDE@DDDD@D D`DPE`DD@DDDD`D`D`DDDD`DDD`D@DD DDD@DD`DPEDDDD DDDD`D DD DDDD DD D@DD@DD`D DE D@DDD D`DDDD@DD DDDDD DDDDD@D D`D`D D@DD`DD`DDD`D`DDDDDDDDDDDD D DDDDDDD`D`DDD@DD`D@DDDD@DDD@D@D`DDD`DDD@DDDDDDDDD`DDD`DXDCEP'EE0&E@+E%E $E"EEpE0%E0E.E*E%E*EP'E E (Ep)E)E`'E*EP+E2E*E E$E E'E.E`/EE,E2Ep+E!E/E0%E +E&E$E@9E0E@&E/E+EP+E.E.Ep#E%E/E/E.E)E,E1E'E(EP*E,E&E01E*E`(E0E-EEP+E`-E0,E0E *E0.EGE CE0E,EE %E0AEp3E%E.E0'E .E0.Ep7E/E@E@4E*E0E09E6E 2E-EE6E:E1E&E*E'E+E8E :EE4E:E06E.E/EFEE6E?Ep6E0(E*EDE>EJEBE@0E9E 5E7E8Ep@E1E@EAE 4E0=E /E6E5E@E@9EJELEBE;E4E5E@@E2E`2E:E:E8E?E>E;E4E/E`5EBEGE8E/E4E0EPDE7E1E7E;EP3E@DE;E9E08E02Ep(EJE0KE5E.E>E1EHE`CE@CE@FE 6E6E@EP;E0BEDE`?EEE@EEE>EFE9E@9EFECE`DECE6E 0EDECE@EPHE`CE4E4E?EDECECE=Ep.E`EBE`IEPDEGEp9E`2EEE@=EAEHEP;E7E;E EEHE=Ep?EDEKEEE0FEP:E9EE3E@E9EpFEEE:E`=EJEp:ECEBEP@E>E?E@FE LEp4E2E;EGE LELEp@E@1E1E@EGEIE@EEENEAEP3E>EpIE AEFEAEAE0GEpEAE5EPDE0CE0;EHEBE09E;E?E;E>E0CEEEOEPE`EBEE8E0KE7E0>E@EE(E=E`0E7E@LEE;E0EP>E?E4E:E3E0-EP.E`5E8E9E9E/E6E`5EP8EP2Ep9E@3E?EP8E6EBEpHE&E8E@=E1E>E3E`7E4Ep;E00E0(E@E`6E%E,E*E,E3E`,E08E4E/E"E@-E(E/E,E/EP!E,E .E`-E1E@4E0EP5E6E*EPE(Ep)E3E1E$E0EP(E`"E%E#EE9E*E'Ep,E0E@'E%E03E.E'E$E"E.E(E%E&E1E4E04EP+EE$E"E`$E(E0*Ep#E`'E$E` E E#EE"E!E#EP.E %E#E E&E E"E(EE` EpE EEP E 1E/E(EE E EEE&EE`#EE%E@$E'E#E%E!EEPEEEPEE %E`E@#E EPEEE@$E"EE`"E&EEEPEpE(E$EEPEE@EE$E@%E EE`EPE!E`!E#EEpE#E`E@E`E!EEEEEpE"EEP'E E E0EEEEPE@EEEE EEEEE E0EEEE0EE EEp EP"EEEE`E@E`E@E E EEEE`Ep EE@ E EEEEPE EEEE E EE E@EEDEEpEPEEE EE EEE`D@ EEE EEDE E EP EEEE ED0EDE0E E`DEEE@EPEEDEEDD DpE`E`DD E EpE@DDEEEEED0E@DD DDDD E`EDDD EE D E`E`DDDDDDDDEEEDDD0E`D@EPEDD EEE@D DD ED D@E EDDDDDD@DD`DE DDD@DDDDDDDDD`DDD@DDDDDDDD D@D@DDDDEDDDD`D DD DD DDDDDED DDD`D@DDDD DDDDDD`D DDDDDD DDDD DDDDDDD D@D`D@DD DDD DDD`D@DD DD@DD`DDD@DDDDDD D@DDDD DDDD`DD`D`DDD D@D D`DDD`DDDDDDDDD`D@D`D DDD`DD@DDDDmD@NDCCEKE`BEHEAE0:EME0CECEIEKE`BEFE`@EBECEHE>EBEAE?ENEJE5EOEFE0GEMEDEDEIEOEOELEPE@EGEME PE`REFELEFEYEPEJE@9E@EGE LE`HETEJEDENEKENELEpTEFEpJEOEpCEDEFEKESE UEKEpIEHESEWE@FEFEHE@UE NE[E@DE?ECELE0XEZEHE >E CE`RE`KEpME@QEDE@TE OECEPVEME0OENEIEPMEQEPREpJEpQEREPE0WEUEPE UEYEWEZEJEPHEOEPQE `EWENE`SE PEUE0KEpQEpHE@IEME`OEQE0OE GEpNEOELE HESEIESEREPSE`JE LE@KEWEQE[EIEQEDE LE0UEVEKEPMENEOE TEYENEpYE`OEHELEUE0MEpSE UE IEPEUEIEPUEZEFEFELEQEbEREAE`TEpWENEUE YE`EE]EPPEIE@PE PEGEMEFEOEQE0WEKE`SESEPMEOEAEBEXE@\EVE@\EOEBEHEOE`KE^E^ETE`JEOEQE ]E UE MEPME0SENEUENEXEPXEpQEpCEREVEpREXE0XEQEREMEPCELE JETEUE^EPE`XE[E QERE`ME@KEUEMEME `ESEOEPEUEHEKE VE[E^ESE0AENE SEIEKE@NE`AEWEXEPFE BEFE@GE JEZEIE`NEJECEOE`LEJEMENETEp^EJE0ME PE _EOE HEFE`IEUEJE0JEFEGEQE YE[EOELE?EGE KE`OE9EpDEPERESEPZEIE0UEHE`JESENENEQELE`LE`KELEGEOEQEKEJEIEDEDE JE0LEUELEFE0@ENE JE0NE AE >E0JEpLEME_E QEE@ME0QE8Ep9EDE@LEMECE?EDE@MEJEPJEMEME0AE>E:EGEIEJEGE@IE@EEpFE@EpHEHEPNECEIE0DEGEPJECE?E DEGE8E>EDEOE NE0LE?E0>E`IE@EME?E@EP@E0LE@EJE@BE@AE=E2E0?E@EGEEP=E@@EEEp?EPQE`9EP9E ?EDE=ECEPE>E>E7E`:E`9E:E@E>E=E?E/E@-E-Ep&E0EEP;E1E8E@;Ep1E>E`EIEPHEIEPUEpUE@EE`AE>EPBEJE`BE>ELEKE;E CE0;ECEJE?EpEEFEJE 8EGEPNEpBEBE=Ep5E0OEFE09EGE@QE`CEDEPCE9E:EBE @EEE@PE=ECE`:E0;ECEGE/EGE GE0=EEECE`>E >E AE@>E RE0CE8E=ECE9Ep;E>E 5E@1E1Ep?E@E0TEVEBE`ZEHEGEPMEPEIEETE WEPE@ECEpAEPCE@MEDEAEE?EPKE>EDEPCE:EPEpGEpECE@E`E`CE0GE0=EBE=E`?EAE5EBE`8ECE;E9EP>EPCE>E:E0@E0FE:EP:E0LE*E7E6E0:EEEBE*E>E1E 2E7Ep4EHE7E:E5E 6E`;E;E:E9E@%E06E8E>ECE08E4E@E@E@0E;EpCE6E7E2E0EP>E8ECE:E@/EEP+E/E@5E9E`1E .E05E>E@8E8E*Ep$Ep(E07E;E3E05E&E'E!E"E00E:E1E=E/E!E 3E5EP7E 5E@#E*E&E)E0"E5E2E(Ep2E3E/E*E'Ep!Ep+E5E`'Ep'E/EE-E.E0)E %E *EP)E3EP&E@%EPE(E`'E(E,E&E#E)E00E+E E@EP+E+E!E'EP!EEEE E@/E.Ep#E'E&E0!EP(E#EE`!EEE(E*E E+EEEPE"E!E0+E+E`EEEE.EP+EE0 E&EE@EEEEP#EE"E"EE"EEEEEE0EE@E!EEEEEE!EEEp"EPE@EEEp EE0EEPE@E EpEPEE@EE0EE0EE EEEEE EEEE`EpEE EEE E EEEEp EEE0 E E ED EEEEEDE EEEpE EpE0EE EE E E EEEP Ep EE EE`E@E`E EPE E EpEE E0EEEE` E`EPEE`DEPEpEEE` EE E E@E`DEpEE EE@DDEE0ED@DDEDPE E E EE@D`E EDDD E EEDD@D EDDDED D@E`D`DDEEED DEEDD`DD`DpEDD@DDDDD@DDDDD@DD`DDE EDD@DDPEEDD D@D`D`DD DDD`DD`DDD`DD DDDED DDDD DD@D D@DD DDDDDD DD@D DDEDDDDD@DDDDDD`DD@DDDD@DDDD D DDDDDDD@DD@DD D DDDDDD D@DDDDDDDD DD`D@DD@DD D@DDDDD D@D@DDD`D`D`DDDDD D`D D`D@D DD@DDD`D DDD D`DD@DDD@D@DDD@DD DDDD DDD`DD`DDD DD@D@DDDDDD@DDD@DDDDDDDD D`D DDDDD`D D D`DDD`DD@DDDD@DD@DDD@DDD@DDD`DDDDD DDDDD@DDDDDDDDDDDD`DDD DD DDD@D D@DDD@D DD`D@D D DDD@DDDD DDD`D DDDDD@DD@DD@D DD@D`DD DDDD@D`D@DDDDDD`D`DDDD@DDDDD DDD@D DDD`DDD D@DDDDDDDDDD@D@DDDDDDD@D@DDDD`D D@D DD@DD`D`DD@DDDD D@DD`DD`DDDDDwD@DCkE XENEQETETEREp_EQEXE`E RE TEUESENE0\EPWEWELE NEpTENEPE@UEcEMEpWEPEFEOE0WELEYEOE^EpOEp[EKEUEQE0QEpKESEWEeEREGEOEpXEVE@WENEIERE@VEPWEpNE UELELEMEYE QE`QEGE@NEUE0PE@JEIE0JE@SEVE@XE`]ELEPFE0CEJEPEPSE`PE@QETE[EEENEHEIEVE0FEE:E`CEKE0NEEE0DE`KEKE@Ep>EpBEGEpGEHE>E>EQE@PEEE`BEAE0DE=EpAEP;ELEGE 6E3EpBE9E0BE7E@2EP9E HE@EEP;E?E:E=E BE5E2E1EP3E8E0JE7E :E@9E0AE@EE0AE6E>E?E-EEp@E04E7E;E.EP9E 4E0(E 5ECEE=E`=E@0E%E)E=E0(E +E=E5E.EP7E0-E !E)E@0E(E.E ;E`,E +E3E )E`0E!EPE 1E3E&E'E,Ep"Ep0E2E)E.E&E E5E0(E%EP$E#E,E'E`'E Ep&E0E0E/E5E!E@&E'E`,E$Ep-E%E+E)EE0%E&E!E *EE Ep$E2Ep!EP(EP+EE&E"E!E-Ep!E(EEP EE0!E,EEEEpE"E$EE)E$EE +EPE@!E#EE0 EEp%E0EpEEpE*E)E`EEEE`&E@!EEEEE"EE0E"EEEEpE E"EEEE0"E`E EEpEE EEE`"EEEEpEPEEP E`EEEpEEp E0E E0Ep EEP EEpEp EEPEEPE EpE EE@ EEE@EEEpEEEEEE E0E EEPEE EEE EEE`E0E`EE@EE0 EE@E@E EP EEE@EPE@ E E E E0ED E EE EE0EP E`EE`E DE EE EEEEEEDEE E E@EEE@E@DE0 E D`D EE0E D`DEDE@ EEDEEPE@EDDD@DE@D@ E DE D DpE` EDPE@DDE0ED EDD`D0E DEDDEEEDDDD EEED@D@DDD DD`DE`DDE DDDDD D`D`EDDD DD@DD DD@DD`DDDDDEDDDDD`D@DDDDDD D DDDDDDDDDDDDDDDD D DDD DDD`DDDDDDD D DD@D DDD D@D`DD@DDD DDDD D`DD`DDDDDDD D D`D@DDD`DD@D@D D`DDD@D DD@D@D`D@DD`DD D@D D@DDDD DD@DDDDD@D DDD`DDDD`D`DDDD D@DDDDDD@DD`D DD DDDD D DDDDDD@D`DDDDDDD`DD DDDD@DD@D`D@D@D@DDD@D@DDDD DD DD`D`DDD@DDD DDDDD`DD`DDDDDDDD`D`D DDDDD D`DD`DD`DDDDDDDDD D`DDDDDDD@D@DDD@DDDD`D@DDDD DD DDDD@D DDDDDD DDDDD`DDDDD DDDD@DDDDD`DD`DD D`DDD@D DD DDD@D`D D`D DD D D@D@D@DDD@D`DD`DDDDDDD DDD@D@DD@D`DDDD@D D D@DDDDD`DDDsD`DDD DDDDDD DD D@D`DDDDDD`DD DD`D@D`D@D DDD@D`DDYD@D`DD@DDDD D DDDDDD@DDDDD@D DD`DD`DD{DDDDDDqDDDD@D`DD`DDDD@DD DoD@vDDD@PD`D@DDD{D@eDDDgDD DD DD@DtDD@pDDDD@D`DD@DD`DD`D`D@DD@D DDDDDuDD D`DDDDD}DvD DD@{DDDbDQDaD@DC=EPEAE/E 6EEE/E>Ep>E`;EDE @E0-E.E7E-E+E8E@E8E`9E`-E=E0/Ep2E0+E6E5E6EIE6E`2E 9E,E9E6E8E`;Ep5E9E`9E3E`)E07E6E/E@5EP;E7E:E3E4E04E.EP3E?E6E4E;E`'E"E(E`6E1E02E4E5E0(E@7E,E7E(EE@+E`$E-Ep.E04E6E0.E`)EP'E(E0E6Ep2E 'EE$E(E@'EP.E(E&E+E'EP!E`&E&E E7E *EpEp'E$E #E)E*E`E(E@1E(E2E0'E"E%E1E$E&E0&EE&E'E ,E4E@$E E0!E@ EE EP$E`"E E E@%EPE@EEE`%E`E0!EE0 EP#E`%EE`EEEp*E&E0EEE@ EEEE@EEE)E0'E EE E@EEPEpE@EEE%EpEEE #EPEEE0 EEEE!EE EEEE EE@ E E%E EEEpEEEEE E E0EE E0 EE EpEE E E EP E EpE EEEpE E@EE EEEEEE E0EEEE`DEDE EEE EPEDEP E EEEEPEEPE EPE E EE`EEE`ED E0E EpE D D EEpE@ EE EDpEDED@DEDEED E D D ED@EE@DDDpED@E`D@DD0EDEEDD@DDD@D@DEEDD`DD DDDPE`DD D D`D`D`DDDDDDD`DPE`DD@DDDEDDD D@EE@D@DDEDD D`DDD@DD DD`DDD DDDDD@DD DDD`DD@D@DD`DDDDDDDDDDD D D`D`D@D`DDDDDDD`D D@DDDD D@D D D`DDDDD@D@DDDDD`D`DD`D`D`DD@DDD`DD`DDD`DD@D`DD`D D@DDDDD@D`D@DD`D@DD@DD D DDD`D@DDDD@DDDDDDD DDD`DDDD@D`D DD`D`D`D`DDD@DDD D`DDDD@DDD DDD`DD`DD@DD@D DD D DD@DDD`DDDDD DDDDD@D D`D`DDDDDDDDD@DDD D DD@D`DDD DD`DDDD@DD@D`D@D DD@DDD D@D D D`DDD D`DDDDDD`D`D`D@DD`DD DDDD@D DDDDD`D DDD D DDD`D DDDDDD@D`D`DDDDD D D D@DDDDD DDD D`D@D`DDDDD`DDDDD@D D`D`D@DDD`DD`DD`D DDD`DD DD`D D DDD@DD@D D@DD@D`DD DD@D@D D@wDD@DDDD@D`D DDDD DDDD`DD`D D`D`D`D@D D@D`D D@DDzDDDD`DDDD`DD`D`DDDDDDD D`DD`D@DDDD`DDDD DDDD`DDD D@DD@D@DDDDDDDDD@DD DsDDDD D@DD@D@DD@D`D D@rD@DD@D@DDDDD@mDD`DD DD@FD|D DDDD|DYDDD@DDDDD@sDDD@DD]D@xDD@DD@DD`DdDmDjDDD`D DD`D`DD`D@xDDyD D`DDZD@]DnDDDD`DkDIDnDuDgDD D@bDDD@mD@_D|D@aDDDgD@iDD@wDDpD}D@DGDSD`DDgD@vD@DqD_D`DXDD@tD@xDsDmDGDwDDRD@rD DeD@sD@DsDD~DiDtD@mD]DtDuD@DD@tDoDSDDDDDyDnDyD D@DDfD@XDcD`D@wDDD@kD@ZD@PDDD@~D{DD@DbDlD^D@DjD@tD]DDcD@dDDD D@ND@iD|DnD[DrD@eDTDeDDQDZDDDvD@DhDwDlDdD@fD`DDEDcDuD=D@>D"D@kD`DHDtDUD.DNDBDgD@IDCDyDD+D@:DCDDD@xD|DXDuD;D;DDHDDaDgD@QDkD D@-D@bD@]D;DUDND)DVDfD@]D_DgDAD@=DGD D@iD@}D@6DD"DJDKDuD@RD[DoD@6DRDrD@&D)D-D D@D@]D>DbD@iDUDlD&D=D[D|DWDVD"D"DQD@xDNDlD9D8DDDIDqDQD/DLD9DD"DJDuD@5DuD@BD'D@^DQDD@RDKD6DSD`D@9D$D7DDYDDD@]D]D6D1DNDODCDpD!D,DYD6DDCD#DSDLDVDCD@LDRDDD@PD@GDFD7D-DC@DsD6D:DDDQD@&D4D@HDDD@CD:D^D6DeDsD@cDD;DC(D(D@DfDFD5DVDdD@DDCCCxCDDDE@EDD`DDDE DDPE DDEDED DEE DDDE`DDDDDD@E D`DDD`D D D@DDE`D`DD D`DD`D@DD@DD@DDDD`D DD`D`D@D`D EDD@D DD`DDDDD`DDD@DDDDDD D`D DD@DD@D`DDDD D D@D@DDDDD DDD`D DDDDDD@DD D D@D DDD`D`DD@D`D@D@D@D@D@D`D D`DD@DDDD`DDDD@DDDD D D DDDDDDD DD`D D`D`DD@D DDDD`DDD D@DD`D@DDDDD@D`D`DDDDDDD@DDD D`DD DD`D@D@DDDDDDD DDDD@DD DD`DD`DDDDD`DD DD@DDDD`DDDDD`DDDDDDDDD D`D`DDDDDD DD@DDDDD`D DDDDD`DDDDD@DDD@DDDD D@D@D D DD D@DDDD DD`D@DD`DDDDDDDDDD`D@D D`DD D`DDDD DD DDDD`DDD@DD DDD DD DD@D`D`D`D D@DD@DDDD`D@D@DDwD}D D@~DD@DDDD@ID`DDZD DD DDDDDD`DDDDyDD@~D@D`DD DD`DD DDtD DDD DeDD@D`D@DDDDD`DD@DDDxD@DyD`D`DD`DiDD`D@QD@qD@rDRDDD`DD@DvDD DDmD{DsD DDD`D`DD@DD@sD`DD D`DD@GDiD DDvDQDD@D|DlDDD@\DkDD@D{DDD DgDD@DDDDoD@HDD`DADWDD@dDD@{D@tDDyD@.DD@{D@cD~D@DDxDDHD@pDkD@xD@zDjDSDDqDsDdDmDYD@hDvD@`D@lDjDD@tD D_D@uD[DDLD@wDhD[DND@\DXDMDTDGDRDUDZD@DDzDGD]D6DDFDIDgD@DXDADcDgDLDJD,DRDD@DVDQDoDKDPD@DDODNDrD@_D@aDDWDCD@SD`D@{DWDLDSD@sDkDiD@qD?D@hD@uD9D^DbD"D_DeD$D@NDWDKD@gDLD3D@HDHD@5DOD@;D@IDeDvD0D@WD@BDID@QDXDD@MD@BD@*DuD@CD"D@D;D@CD7D@dDD`D@,D?D7D1DQDDJD@+D6D#D_D@VD@MD3D?DC*D.DTDjD@YD.DED@DD@-D>DcD+D=D1D@DFDD DFDD@GD`DD@GD-D!D,D7D@;DVD@ED=DC@#DCZD?D+D@NDND6D@ DD7DcDjDDCD1DSDED:D@,D@DD@D*DClDkD@@D@0D@&DCDD@@D D@ DCCOD@]DDD>D5D@*DDC4DWD@)D6D@D D D@.DDDaDDC@DCCGD@*DD(DCKD5DCCD&D@D@+D$D@FD(DCCDC@"D;D DDDCCD/D$DCDD@D@D%D@D@.DCDCD@:D*DC#DDCD6D@D%DDDD@7D@'DCC@D@DDIDDDC*DDDD@DUD@1DDCD9D@DCD:D@DD3DDDCC@4DVD@UD@%D,DDCCC@D?D!D@DDDDCCqC@D@DD DDD`D D D`DD`D DDDDD`DDD@D@DDDDDDDD@DDDDDDDD D`DDDD DDDD`DD@DDD`DDDDD@DD`DDDDD@D@D DDDDDD`DD D D`DD D`DD D`DDDD@DDDDDDD`DD`D DD`DDDDD DDDD`D`D`DDDD@D DD`DDD DD`DD DD@DD`DD@DDD DD DDD`D`DD@DDDDD DD DDDD@D D DD DDD@DjDDDD@D`DDDDDDDDD@D`D@D`DDDD`DDDDD DDD`D`DDD DDDrDDDD`DDDD DwD DDDDD DDDyD@D@D@DD DD@D@D`D@DD D`DD@D@uDDDDD{DDD@|DxDPDDD DDDaD@MDyDDD DDDD`DcD|D`D@oD@DgDgDDDmD@HD[DUDDDdDDD`DeD@8DgDDDpD@D@D_DhD DDEDaDDD@DJDxDDlDxD@D@DfDeD@4DcD\DnDqD_D\DDxDoDTD@7DaDzDiD@JDdDD@RDiD@uDCD@eDD@iD@4D`DdD@iD@pDjD@kD\DqDhDqDSDcDD@yD DDHD_D@}D@kD@D[DUDSD\D%DHDUDKD@tD`D@NDPD,D,D>DfDADlD@MD@SDfDDDcD`D}DDDZDjD?DhDwD|DyD@JD@8DfD@lD]D`DaD@YDiDrDQD@nDWDFDqD=D@"DcDLDDD[D0D]DjD@9D@dD@aDUDuD[DKDWDXDwDgDdD@iD:D`D>DFD@$D4DDND/DhDsD*DODqDPDSDFD#D@VD@RD=DfDgD@@D9DTD@]D@.DPD@;DSD@=DQD@zD@ED%DKDqD"DgDWD,DVD.D-DAD]D@"D}D@aDGD@1DD8DhD|D2DSDJDPD@DFDEDD!DDD,D@D/D>DD%DDDD@2DDD@[D/DQD D DC@JD@D@DDCDDC@DC8D DDD3DJDCC2DCC@DDC@DD@D"DCCCC@DD@-DD@-D!DCDDCCD"D+D@"DD=DC"DD?DDD9D@DD.DC-D DC DDDC@DCCCCCCCCD:D(D@DCCDCD)D@.DD&D@2DC9D(DDCCC@D DC@D DD$DCCC@DDC-D DDDDDDC DD"DD@ DC@3D@DC DCCD@3DD@ DDCD:DCCD DCCCC$D@4DKD#DCCCD-DDC DCCC DC$D DCC@D8DDD DDCC D@DC@'DCC@D&DCCCC&DC[CCCCC!DDDCCCCCCCC DC@D@DDCDCC@DCCC@:D@D@D DCD@DCDCC DDDODDCCC/DDCCC&DCC@DCCD"DDCCD DC@:D@1DCD!DCDDCC@DD'DCCC@DCCCDCCC-D'D%DD@)DChCCCCCDDCCCCCDCCC@DpCCCC@D@DCDCCDCCCCBC`D D`DDDD`D DDDDD@D`DDDD@D`D DDDDDD@DDDDDDD@[DD`D@DD`DDDDvDwD DDD`DD DwD[DD`DDD DDDeDuD D D@DDDD@D{D DDD@XDDD@DDDyD DD`D DD@DD@D`D DDDDD`D|D@~DkDyD@DzDDD`D`DDDDDDiD`DvDD@DTD DDuD D|DvD~DDD@DD@MDlD@aD@\DDDDhD D@~DPD`D@BDDDfDyD}D@]DyDDDD@]D4DD@xDDoD@ZDUDsDsDND{D`DuDiD_D@ADID@VD@uDDD[D@eD]DjD@{DoDVD`DTDUDDD%D`DkD]DHDsD@)DDDoDuDSDDD~DgD1D|D DMDJD@IDJD2D@JDMD DkD.DXDeD@cDcDQD3D@iD D@eD`DKDKD6DwDGD@JDbDJD[D]D4D[DYD DmD@D@FD@=D7D?DtD>D@9D5D@HD5D=DxD_D@qDUD@4DFDMD+DSDCD2DhDNDMDYD@UDSDKD@4D@2DVD@VD=D@D@:D@:D@ DfD@=D~DSDADJD@UDGDnD`DDDfD+D=D!DGDgD@DDLD=DD@,D(D@KD;D@2D1DRD D@MD0D(D8DaDCCCDCC=CC D@DCCCCCCCCCCCCCCCCCCDCCCCC@D@7DCDCCCCC@DCBCCCCC1CZCCCCCCCDCBCCCCC2CDDCCCCCCWCCCCCCC DDCCCCCCCCCCC@(DCCCCzCCCCCXCCCCCCCCDCCDCCCC@DCCCCC"CCCCCCCCDDCCCCCCCCCCwCCDCCCCxCCCCC@CCCCCCC@DCBCCCCuCBD DZDsD@OD@jD@dDD^DyD]D@hD]D@eDdD@DwD@xDDDlD>D@VDXDDDYD@tD[DnD@DHDFD?DkDzD@xDXDTDDDfDWDnDbDJDXD@sD@?DND@BD@lD D`D[D@nDD`DoDLDDKD@tD^DPDD@iDcDFD'DsDiD)D@RDkD@KDeD@LDD;D@vD@nDD@ZD@>D@hD@DD@GD@RDD@DCDDD[D,DC@BD@{DbD8D]D@dDUDPD!D@FD@IDFDED`DTDiDOD*D@D D@#DKDrD@6DJD5D@WD@7DwDWD@FD2DPDADzDBDaD>DPD[D7DFD@WDZD@XD@xDiD-D@PD@nD(DGD@MD@D DD@?D@YD>D7DHD>D!DADiDD?DDDjD@CDPDoDgD@D6D@:DC`D@NDD;D@D$D.DD%DXD@HD!D?DJD@D@0D*D@DGD@EDD@TD-D D@D@4D DtDoD D7D9D@D@!D DD8D)D>D,D@+DDED,D@8D:DDD/D@DC6D@DCD;DD5D@D@D9D@UD,D(DDC D DDED*DCDDD#D6D@D7D1DC@*D$D.DDD DPD3D!D@4D,D.DDCDBD7DD@ DDC9D,D D:D%DDC@D2D#D%DCD D;DDDD@CD0DC$DCD2D+DD@RD@*D"DGD@LDD(DD@D@#DD(DKD@6DCD!D$D@,D$DCDCCDD DMD@DDD>DDD"DD@%DDCCCCCD D@GDDDC@7DCCC-D@ DDCD$DCC(D@DDDDC D DC@DDC.D"DCDCCD/D*D@"DCCD&DDD DCCDD%DCDD@DCC@DCDCD*D@2D DDDCD D@D*DCCDDC!D@/D@DDCC?D@DDDCCC DeCCCC@&DDC DDCC@DCCCCCCCCCCDDCC@DCjC@DDDDDCCC@D@[DDDCCDCCCCC@-DD6CC@ D@DCCC#D@DCCRCCCCCCDCD@DCCCCC@DCCCCCCCCCCCDCCDD@DCCCCCC DCCCCCCCD DDCCCCCCC@ DDCCCCCCCCCCCCCCCCDDCDDCCCDDDCCCQCCCDDDCCCCCCZCDCCCCCCCCCCCCCCCDCCPCmCCCCCuCC DCCCCCCCCCCC D(DCCCCDCC DCCDCC$D#DCC DCDrCCCC@DCCCCCCCDCD@ DCCCGCCCCCDCCzCCCCC DCCDCvCCCC@'DDCCCCCCDDC?CBCCCDCCzCBCCCD@5DCCC'CCCCCCCC^CCCCCCDCCCCCCCCCCCCCCiCCCCCC2CCCCCCCCCCCCC@CCDpCCCCCCCCCCCCBCCCCCCCCbCCCCCCCCCCCnCwCCCCCCBXCCCCCCCCCCCCCCCDCCuC"CBC'D@DDCBCCCC@DCCD@DCCC CeCC~CCCCCCCBCRCCC@DCCxCBCCC DDlCCCBCpCCCC@DCCCCNC5CCCCkCCbCC DC_CCCCCCMCCDCCDCCCCDCC@DCCCC\CCXC$BmCCCCCCCCCC DCBwCCCCCC DCCCCOCCC|CCCCCCCVCCCvCC BBCCxCC8BCCCCCCC+C)CCCCCCpCC_CICCCBCCCCCCCaCC CCC@DCCCChB@ADBD3DCD;DVDDD@DDD DDC@DD@ D+DcD+DD@D@D-DDC@.DBDC.D@D-D@ DCCDDD=DCCHD!DCCCC#D"D9DD@%DCCCCDDDCCCDCCDDD@ D@ DCDC D2D DC@DCC D@'DD'D(DC@D;DD@ZDDDCCC@D)DCC@D D#D:DDDDC@BD@#DC#DCCD@6D@$D DDCtCC:DDCCC8DD3D@DCCCD@ DCCCDCCC@"DD#DCDDC@DCCC@ DDDCCC@DC@ADCCCCCDDCCC D D@"DDC@D@DCCCCCCCCCC@DD@DDCCCCCCC@ DC'DCC#CCCCDCC DDCCC DCCCCC)CCC D@DCCCC D)DCCCCCCCC@#D DCCCCCDCCCC=DCCC@DC@,DDCCCCCCCCvCCC DCC(CCD/DCCCuC@ D@ DCCCCCCCCCC D1DCCCCCCCyCCCCDCCDC@DuCSCCCCCCCD@DCfC_CCD!DCCCC DCCCCCCC{CCCnCCCCD@D@D DCCCCCDCDCDCCCCCCCnCCCCCCDCCCC8CCCC DCCCCCCDCCCfCCCCCCCeCCCC@ DqCCPCCCDCsCCACCCCCCBC DuCBdCCCCxCCCZCCC.CCC{C-CCCCCCChCCCCcCCB#CBtCJCCC{CDCbCCCCCCaCCCCwCCCCCCCCDCCCCCBCC8CCC CCCCCCCC}CCDCCCCCCC AYCCCCC@CCDCCCCCCCCCCCC/C&CCCCCBCBSCCCCfCCwCCCCC[CCDClC{CD'DCCWCrCWCCCfCCCCC^CCCCCChCLCCCBCCCCCECCCCClC^CCCCVCwCCCCB'CCCCCCCCCCrCCCYCC9CCCCCJCCCCCCCCCCCC@DCC4CWCCChCCCCCCmC@ABCCCCLCBCCCDCWCC(CuCBCCCCQCeChCCCCCCCCBB,CCCCCHCfCmCCCDBCICCC^CCCCCCCB CCCCC'CBrCC"CCCCCCCCtCaCCCC@D;CCCCCaCCCCCCCCCeCCWCC=CCCCCC(BCCVCCbCC CC ABCCCCPCCwCCDlCCBHBCC*CC_C!C>CBBCdCCCQCCTCCsCCCDBCC!CCCCCOCCCB6CCCCCCCCCCCTCBCCCCCECYCCCC%CCCCCeCBCBCCCBCCBA@!D@,DD4D#D3D@DDCDC"D-DDD@DCD#DD@D.D D D@DDfCDLDDDDDD@%DDC@ DD@DAD@DC#DDDCC;D@D#D0DDCD(D@DDCCD@7DDDCD@ DCCD8DDDDC@DDCCC#D@4DDCDCC/D9D"DCCC!D@ DC DCC(D@DCCCCCC DCDC#DCCCDC;DCCCDDDDDD"DC@2DCCCDCCC@D!D!DCCDDCCCCCDDCCCCHCCCCD(DC'DCCCCC DDCiC@CFCD@DCCCHCCzCC@D4DCCCC@DC DDCSCCCmCCACpCC.DCCCCCC.CDCCD+DCCCCCCCCCCCCCCCCD@DCCCCCDCCCCCCCCCC DCzCCCC DCCCCxCC|CC@ DCCCCCC@DCCC~CuC@DCCCjCCCCMCCdCsCCKCCCKCDCC%CC]CCCC@DC(CCCCD DnCCCC}CC{CCCCDCUCCCCC#DCCCC@D"D$CCCFCmCCCCCBtCCDCC.CCCCCCBCCCC@ DCCCCCCBCCCDCCyCCCCCCCqCCC@DCCCBCCBCCCCCCCCC@%DpC_CCCXCfCCCCC@CCCCC@DCCCWC@"DC7CLCNCCCC}C[CBCCCC_C-CCCCCC@jCCCCCCCCpBCC2CCCCCCBCgCCCC CCCCCCCCCtBCCCCBJCCCCCPCCCCGCCDC@eCBC4CCXCCCCvCBdCCCCCoCCCCCCCCCCCCCCCCBB_CC-CyCCCrCCBCCCdCBCCBCCB]CCC]CCBCCCCCCKCCCCC[CBCCCCCC]CBBCCCC"CCzCACCCCCC BC(CC?C CCCCCCC@CCBECCCCCtCCCBjCCPCCFCCSCCBCC`CCC@CCCCCBCCC\CnCCBWC@ DuCCC?CCCBC&CCCCBBCCCCCC"CCCRCCCCCCCqCCCtBCCCCC-CCCCCAC!CCC`CCCBCChCCCCC4CBC7CBCCBMCCCkCBC;CCGCCWCCCCCC2CBC:CCCC;C[C-COCCCCC@ABCCC?C%CBBkCFCpC CtBBTCCC^CCCCSCCBYCABCCAFC@CCC,CCACC)CCCCpCCCCDCCrCC?CCCCCCCMCCBCCCCC@CCCCxCCC{C^CC DCCCCDCCxCICCCBCC5CCCsCCQCCCCCCCCkCCCClB0CCCCCCCcCCCCwCtCCCsCCC5CcCC0CZCjCkCCjCCCC;CCCCC/CCCbCCCBCC\CCCgCCC>C C,C`B\CBCC3C0CCCCCC8BCC[CCCtCCCB8CCCC@ DCCC)CBeCeCC_CCCTCC@DC8B5CBLCCCBHCCECpC3CAC$CBOCCBQC6CpC~CCC,CRCCCC@cCC[CCCCkCDCBCCCCBLBsCCC C0CLClB8CCCBCPCCrC@dCB@(CCCZC=C6C}CCLCCCApABACCBCC*CCCBCCqCCCBB4BBCBC\C>CC CCCBCC*CyCnCBC4CCC/CkCCCB,C|B:C>CB9CB]CCC7CBCBEChBBCBCC"CBBAC:CC.CCB\BCCCBBHBCACBCBBCC"COC-CC}C=CCSCCCl8BWC$CTCC CCCCKCC AC2C.CCCBCC+CB4CCCBBCC@CBC`C`AC4C@@dCCBMCeCCB BB%CaCBCUC\BCCBCrCCCcCBCiCTCjCMCCCC CCC CCC_CrCBBCCECcCC5CB*CCCMCOCA BCiCCCCCCBBB2CCB CC+CCCnCC|BBC7CBC8BBCwCCCB:CCfC^CCC? CcCBCCpATCxB CtCC0CBBA\BC?C[CCBC CBCCACfCC/CC BC CCCCaCxCBBB]CCCC?CjClCCCPCBBCLCCCFCCWCBCCBBhB7CCCBCCBCCBClCCA}C;CkCBB CCXBCCbCC6CCB^CBC&C0CB#C!CxCCCBBCCsC5CC$C1CrCBCCBBlCCCCBoCCdAACA]CCcCEC9C8BXBCBCBC%CC1CCTCCB'CD|BCCBBCuCBC CqCBCBBBeCtCBBBCCBCCBCaCB CCB:CCRC:CYCACUC\BC&CACBBBC@ABBBClCCCVCCAB HBBCBCCCCCBVCBCBBBtCCB'CTCCOCCCPB'CBB CpCoCCCCB@CCBlBA'ClBXBCCFCbCJC$CGCBDBSCCB CABICBBCCMCBB~CClCCJCCCCCCCCCMCCCDCmCBCBCCCCCdCCCCCCBCCC'CDCCCCCOCCzCCCCCC:CCCBCCDCCCCHC~CCCCBCBCCC4C$CCC+C#CsCcC4CSCBCCPCjC0C{CCCCCCYCCCCB{CTCB@CCB~CBhCJCCC@CCBFCnCCCrCpBBBBCC9CChBC\CCCMC)CBZCBCCBBTCKCCB)C CCVCCCBHCB-CCCCCCC7C.CCCXC[CCC(B3C CBCCCCCBC)CBPC[C(CCMC/CCCCuC!CCC|ChCuC3C8BxCCCC:C1CCTCCCCCCLCXBvCCA$B4CBCCeCC\B`XBCTC>CyC&CCBMCCdCBC BBBBCBCChBCBCCApC$BICC{C BBBBNCA@AB5CzChBBLCBB0C[CBBCCCC=C&CeC BBBMCCB/CCPAC8CBC~CCACTCBC@DbCSC8C0iCB@CCbCOCCBBjCB1CCCCC8CCCoCCCWCBBxBCpCCCB CfCCC@APC&CZC{CzCVCBoC0CCHBCHCBCXBBC9C$C,CRCBB CBCHC`CACCCLCBtC0C=CpCCBGC&CCCCBC:C BCECB|CCPC$CBA$CB9&CKCBCCBCCC)CC_CBCCCBmCBACLCCBBC@CAAkhCBCC@GCA CBBB8 lCCABSCBCC`CTC^CB(CA-C00CCC_CB9C@CjCC@CBvCxBDBCBBSCBBACB`ACoCSCuC9CTBNC@BCC(B5CBCCB&CC%C/CC`B`C?CB`BC%CzCzCBAB*CBAHC!CBCHBSC+CBBBxBCCBBBCCC CBCCB2CBB_CCjCTB@B@CCCB*CCBBXB#CBpA+CCCLCuCBB4CB8BB8BCCJCBCBACCC\B0gCbC CBB$BmC^C@+C`ABBAB@`BCsCPBB-CA2CB @TCCBAABvC#C-CBBBRCCtBB/CCBCC CCBXBBB~CACpBYC0CCrCbCpA@BB$CBSCCxWC{C BB.CVC`0@@CBSCMCC/CiUCC5C C0CCBBA?CBB*CCBB8BoC9CCCB@@ BChBWCA0C @BfCCPBAKCCxBBQCCCWCC CBAB{CCCpB/CbCLCHCBpABB0C@@BC0C CCBAAhBCBlBBCACBBCCgC@xWCHBBA]CBBBBBC B<!CCSCB$BC0C4A CBBP0CcCCBABCB@@AB CB>C@ CBBC,BCSC9CB@BB@BBYCqC(BBCCCCXCfCCCVCBCHCCBB,BBCfC$C*CCpCyCA.CAACpCBABRCBECB'C`BBCBCCCTCX@zCCpCB0BCB1CBH@C'CUCxCBBCHBBB,CC@BA,B1CbCCCdB=CBHmCBCABBZC/C\B@ACABpB$BBUCCmCUCC'CA8CB0BvC@BCBACBC CNCfCB`C C8B8BBUC?pACpBBACBB !CCC(VCCdB(CfCBrCBBB@@)CBCBtCJCCGCA@@BCC0CBC$BBBC}C CSCC?pA:CzCYCtBBEC/C8CCBBB@JCBCABP_CC&CB,BB\BpCC CBPCCBDBC)CB4B7CCDBB*CCCCBADCCBP@CCBCCBBB|BC+CBCT9AwC$CATB ClBACPBBCPACCCCBB AACBpB BEC@B8C0BBBCBB$B AsCC>CCxBBBB)CqC BCBCp<CC(CCBkC C@@BBBCBA CCCCmC&C8CBLBPAB(CCBiC`CCBCCA(B`ABCVCB:CCCNCBC BBCCNCBBcC2CACCgCB BBA<CyCBBBB*CBABCBCBjC|BBf9C"CBCsCBCBBiC CPXB@BB$BCdC?,$UCChCB0CBCBB,CCAB+C-CCdB4B QCCBBBB CB,CbC@AB HBpABC CC5CCCC CBtCB(CB$C@CBCBdB<1C CBB!CBpCdBXBCyCB0A:C"C4BCCPBBCACB`BC]CB CCBKC C$BB@@ABB@@AC|~CBB*ClBCACBBhB,CpABChB$BZCBB|BBxBCBC1CB|BPBBBBA'CBBPB BABBBzCBBBB]CDBCpC8BA@@#CCCBBDBBBMC/CBCBCBCBB]CpBBAhC5CB8CC=CFCdB`AB4BBC*C B CBC CBBB?/CUCB\BBtpPCB4BXBBLBC,XBhAPACCCpBRC`BLBBBBJCICCB4pBBB#CZCBBBEpA4B B CBC`AUC0B8BB2CCBBBpBeCHB^CB AECjC$BLC`BBBBCCBtCBABFCYCB@AA,BTBA?CChBBAC4BCCBC>CB*;CvCXBBCBBBBCl8CCpAAAOCCBFCbCvsCACBA`BVCAtC!CBBCnC CC@@BBHB(BCBCC@@BBdBABCBBC CCB`B`C B4BC8BA@CIC`A=C,BA BB7CBlCpA=C0AClB4ACBBAAxBBCBPBkC4CBC?AAClBBBC@B>C,tBB=CB`Ax8BB@B@BBBB BLBBCCC7C|BBBA` RCBBfC CAXBB<BPBXBC?HACC@TBBHBdBPB CBKBB CBC@BDAB]|CBC ACB CBCBaCgCB? BBCBB`BBBUCAABC/CBABA"ChB BABBNCDB TAC@@BB2CUC%CmCB#@AfCBPCHB]CTC CAAP?BXBoCB#CJC@LBB@nClBlBB C,CBB@C@=CA<@AtBB@A@@BB0BpAB@B$B"CA&C0/CvCB`0BFCOCpAC@u`CB*CXCBC@HBCCPB4`AB^CC@C B,BAA0CBBBAAvC|C@DBDCCBB@CBhB,BBA@`CRCBPB(BCAB@C2CC;C4B:CD0iCLBCYCBBwCBC CAA&CCpB\CC@&CBDCB`ABBLC,BBB BB7C(BCCAB$TCChB0B B%/CPB B,ABB0@#CB(pB2C@B#CBAC\B|BgC,BtBBB*CpCA CBCCB CWCBGCBBP& C$C4<A#CC`-BAAB0C`B C@B@C @BBBBBXBlBlB>CBB@CB#CC'C C50AABXCBA BpAB\BC)CBCAABBTBB,BC-CB`@tBBBBBA ABCxB@B0TBApA%C:pCBpBsCB:C+CBA"ABBB@ CHBBBBAB CBBOCBBhCDCB%CwC@AHBC@0BWC@ CBAuCB2CDHBAC2CCAABnCtBB(BBBABXBXBBB|BC4BpA@lBECBCBECBB4CPC0BuCBAtB@ACB\BB,5CBB CABABBDBBSCBAhcCCBCB8@CB?BAlB CBCChBA B&CVC$BA@BAB\l{C[CB CUCABTtB@AlC C*BPA`BC BxBBBAC(B%BxBABCBBPB^C[CABBCCBB(BBBIC_CBPABBAB:CBA%C BpC6C1`BB ABB*CxC2C$@A0BABDCBCBCB"@BBCBBCBCJCoC ALPBKCCCAClCdBBC*CBB hCCABNC\B(CXLBCp`ABCrC=B0ACBdB1CC9ChBCBBA3CBTA*C DCBhBBB@C CPBCAdsC0CB|C8BChB CB)CB9C*CBBBDBBCcCBCl`ClBjCBlB PB`BRCB&BBdC=C0GA8BBxBBB$BBB,Bj#C|BuC?C C*C(BB@B BPBB,CB@ABB5BaC CB iBBBBxB)C0ABhBC(BBBBBBBCPCBTB BlB@AB CA@(BB@A BlBDBBCICB,BCBBDBB.CBCB0BtBBCC` ABCB$^CMCBPBC BpA,|BA8B<<(B]CBAB\3CPBCBA@BH?C:C-CC\(\CCACCDC\B|OCBC`HCB@BMCBTB$3C0CwBBGCB[C4BBCCJCCABBBAB0@BBBAB50xB\B@@BRCB@A3CBACB,AABBIBBByC'B\CBB?hCLBBBC!CBDBBBAPACB4CBB?(BCADBBC4BBxBpA;CCCB @B C0AAB ZCBB&C|BBXCB@$/CNCB CBXBAXMCC>CL>C{CBLBBdBCFCDBxBABPB"CpA,"CB1CBC8BpBC[C@CB\ABBBJCBIC@rCkC`B jCC`ABB4B,BB B@|BACB B3,BXBBAA4B ABhB<`BABCBBBBC@CB CBBC8B @LtBABB C$tBB4C A\BX@yC CH\BAlBC C@CyCBBA8BB!`CCCh|B @(CBBC$CABB0DBABBB0BACA,CY@@!C(-CCCCMCAC?C00BCAdCbC @BBlBBlBABBBBDBC=CC0CA`ABBABCBxBt+CCA~C C C BtBlB@(C|BBtBBxBArC@ABPB`CBACBB0AC}C)CBBPBTBBPpC B B0\B$BACsC@BtBBBBB@XBxBCBBBB=C.`BBBBBB,ICBBApAB`pBPA0C8,ABC@A2CCC4 AC CtBBAlCB\B<|RC5?`0LB0AB8TBBBBCB7<A BC`C CBAFC A$CCBBB?CCAABpA AA0BB)CBCB3C\C"C@@BBB,BCBBBA3CBHxt ACB,B@B\BA06SCBCA@@AjB,B@BA PCABACBDBAp)$BDC3BNCCHC4BpA0B9@ B CD'CBABBAC@?@AVC, CCB CpB1PpBC|B CBAA B@@B `CCXBA@BA BC@(CBhC;C/)C C,B CCCpC lBBxBB@@BB`ABBjCCQC0B'BBB}CBAB@/C C*C,BkCC0BByCBB BCXBB?@@@B CBCBBHAFC BB$B0C &CBPBTB$B)C AAA&CB`CBBA BBB,BB,#CCDBBBBAC=CA)LBpCCHBCB CApABHB(BB Q-B BCC8BHpBAP \B4B=BB<@;CAB.C0ALB@BAQCTB CCPB A@BBKCBABA:CBPPK0C CA\`BA\BB/C C$+BaC>CpBhCA<CBCCB6CvC AxC BCABBhBBApC,BBCXB0PBB8?|B,B ,AB-CPB^CHCA4B$CUCBBBABABCB4CBnA@ABBCBQB(BCB,B *CtBBhBBBB@BC0CCiC@pAACB(BBBBC2CkCjCABBCB@C8AC`AtBBBBC(BBhBqCA\BBABC0BqC BBCBB@BB8B,lBpC B\B!C@BA\B@C2CBDB,BB`QB)CA|B&C CB?BBBHCB?AAB8C ^$BiCXBLBBJCCB hB@BzC(B8BA@AHC;C CCdBBBB`_CPC?BPBBCAp@A BCLB@DBDBBBV CBB2 AB9CCCAB5>CCA0AJ AQCCAHBBCCA$BBlBBbCADB QLBLBBBCB`APNCBXBBpALAB,BhCBtBx0BBBpB| BQLB@P( BJACPApAP4 CB@ ABpB8CClNCHC CBDcCC`BDB@BCHBB8BB?CABBBB,CL,B4BlBBBLBCCBpTp|BdA|B7CAlC CBLBA B8BB8 CRC ABB@KCBh}C#C4BBjB@A@@M"C@4C@BBBBB PBCAECA@BTBClC CLBl B C4BBCtC8TCCBTC@BpADCPABB` ApAlBBB\(BBB} >C!CXB CLA5CBpB4BCTnC7CCAxH@BJCACBB BGCBB|B9CtB<BCBx`TBBuCLB$XC@@ BCAAACB<CBBAPC CB;CCxoCBPB4 CBBBB4Bd CA!BBC CAXB@tCBC CB@,BBCAXBdBaCB@A0B C)CBCHBBBPBSC CABA4ALC B`BBh5wCCLBCB@,BB'C@?CB(B!C@B ABB*C@RC`B2B`BhB` BBClCB.lBCCBBCBZ"@SCBXC$BBDBpPBA@A@oCATBHBCB4B BBAlACCBB@A`B`AA?C BABBDCeCECB1C`ACAp4At2C`B0ACAxA\PBx,CA!|B?LB'ChBECCABLB C$BBlAtB1CAl ABCDCBC-CBBB+@xB BtBBBA\)@0A8CLBBBBCB@ C CH@BBBCAWC@\B:CBAA BCC0AB4BCBBAtBCC}C/C5ClBCBcC CBH@BCB,xpACBBCBBr7C CB(B0BBPC:CB`CBA4B@4BB@BL0BBBABC`tBB@@0 CB:CBBC"C0ABiC4BC(CC!C%UB`BC$BpA@AhHBB @@BxCA9BCA,CC,CC DBA8A B{CBB`@0BB<rC C00CPBTBBBBB|BxB+ClBBlB,bAHCBG$BAZCBtB8C|B@AB BBTC`0`A04A;C;CA@AdAL4Bp]CCBN(CAB B4+C4ACPBBCxBB`BBBlDBAy?NCBC(B`pLC4tBBBPACB?0B CPuC@BB@DBBBAB<BB@BB CB@AB CC C+BCB,BBB(CBAlBCABDB(09CBXB@4kCCA BBlBECCAmCK BA%CH0AC@plBCBBBBCuC AB`C%P BBBXCCAxPBA<@dCtBBCCA?CB`HtB@@CB BCEC)CB+,-CBCB\B8BBIB8BpBAlBBBxBB0ABBCEBB6mBACBBAA+$dBhCC@7AA)CBB0AAA B`AB AB@BC2CBCB A@xtBBpBBA!C`BCB8BPHPAVCC0ABB(B CCA+C@@dBtC7CBB?@iAB @rCANMC`AC@ACABAHBCABB$BB CC&C@B$(BAC BCCC4B\B^C,Bp4BAB( BpmC@ CB3C` =|CB)Cl4BBSCPtBCA%ABBhCBA@ChCBC$B$CCBVHCB@B?CBAA|0BBlCBAB|B@(B6C@BCA;CCABA CBB ^LBA CBCBBxCBpC@@BHBBBBBCAhBJCuC+C BBC`BBPB`BB@ *C?CBBB@@@BDdB$B@BBCx\CC6CBBtBB0C AdBCDB3BBBBBLBdBBBBCOC>03CCBA1\BtBBBPBCBB[@BBBA>CC8B]ChB\tBB"CrCDBtBBB@AABCBCPABB@ABCC H@CCC`8BLBX B BPAA8@BBB|BC6@AcCB|BMfB@BBBBABPACBACxBBtB@BBACTB CHBA~ CXBAl4AC@@BdB,BIB5CA,lBpADB C CBC(^CPABPABBABABECB9CA"CCjCBACVCABT dBBC AABECKCVCBLBCBlBh=CnCB C(Bd7CHB +CC<04$C@@C@BBDB@BBb-C >CBC02Bt@AsC&CA@ AAOCBB4=C(BBQ*<BvCBBACO@BBpABLBHBdBB8B!C@LAd CBBTB<BP4nCCpBxBC`AB+A0ABNC`BACBBB,BPlBAACB$HBB$BECB@1C0Bp"CBdBDC3cCxBB@BB3BBZHB@#CA#A BBC@@XB,DBB^CB3CACC(BVCkCBC,B0ABfCB&CP4C0(BxCXBBCAXCBBCPBBBpBABBAoCFCABCAC' C<BBCCt`BBBB !CBC,BA@ CHC&BNC(CCP0ABCDCBR@PECB^CBBATB CCB(B`B0B-BC.C|BUBBBB1CdBpCBpA/C"CBBA8B:PB BBBBBdBdCBlCBB@APAdBIBB\gC@@CCB@B@oA C[CA\BpT2CB@0lBCCB,@8`ADCBC,,CAAB#CBZ(BlBBBC9CB,A|B0B A B B$BA$BFABB2?@8)C0ABBPB8BABB["C2CHBTV1CxB@B A,BB@@tBBABtBCBB7t(PABdBAXPBBABABTBp@BPBTd\!`BXBIBC*0 BBCABB@@ACACP'CCBB89CCB@B2C8CCABdBCCVCACBB<'CAKCVCAD `BB0ABCB=jCC XBCA BjdC= dCB,pCB+@B8BB AF1BCp`|B@)AB\AA\C&C1CBB$P0fCCPyCCMCB@0BA@@3CBCXBXBBC.CBBCOCCBCB/QCBBDAeC @BCB@B$'XBB@HB1CLB6pdBB/C9C8B`B\BB@0ACCBCA;BhBBBBBBBCB(BbCB\BP ABCD7CzC BBDB$BtBB@@(BB@B'C,8\B CTBiiCCTx(hBBB"ClC@/CAA<X8BC6CBB0B7BBZCBCxBBPpdBCC$4BB@H0ABBA@A @@BBBB A(C>=CCLC0pBB Bx %C(BBtBt$BlBkCCp`B,PBC4B|B C:CDBBCC@AB0TBLBB<BXCxC#CB,CdB4BAxBtBB@@LB B\BBABQC@BA4B*CBB0A0PB CCpLBPA=BABdB B'CXC?C/CB(PBBpB0HWChB(L<EBCBlB0HX`BC&@BtB CSCB"CB\BTBBCACAA2C*C@C&C`BBC/C0B`ABBGCBB8B BtC0PCB@@;CICO@APBCCBX@kCB@TBECB@BYCC?A BBABXBB@BBABBDBC$Bd)CB@ACBdBACA@AABBCBtBC@AXB CC0BdB$CACB0B:A`!BtBAB@AC$@0AC CBLCCBpBCdHBATBBAB@BBB08BBC8BDBPBA~@CTBC BABA "CBXBB?;C C3A(ASCB B4BBCCBAdBPC)CBBXC ABCCtBAB xB B<ApB|BBpBXB`XB2CACkBB(B0BB8,pBLBCB\AAT" htCaCBBBBAJ@BXcCDB CAB`P6ChBBB0|@B@A0BC*CBBPPBXBCA`'CBBBM CBB BZ6BB@lB(BB?tBCCAVrABABB;C, BBAB@ BNC@dB+C0ABBHBB@7CApA?LBACdCB@C0B@?TB)CBcCA:BA@@C'A CCBBB@B8BIxBB7BB@@DB( @AACC@B<BABAHB\B*A:4BB CCpACdBT BBAAA\CL0A`BBB@BBA`BBAB>A)CB0AA0-CBIBBOC,B/CB0B(B0ACBB AAhBACHB8BBBUCB,8,CABBBBADLBzC|A@*CDCBBtBQCBA| CC4ABBhBAXBAB<CBXBB@BBBCBBABC BBBAA ApBCC(BATB$C"C(BB8BACCBBB\CB C CBC8BA B\0BA@BCLBBC"C@ BbC $CA BBss0CpA A@APBACBT`@BB BxB0C`BCxABsCPB!BtBBBB8B'A@A(ABB`A$BC6B0hBh@ABAAC$BAdBCBC@@BBCCFBBBlBB+CB A AGC1CtBA4ATBB(BlC(B,A$B@BBA-C|A?ABwCChAB@B?CJC BBHB'CPA@CCBoApAnCABfC@BHA@CChB|#CBBB@ @BB[lBdB@CPBAABBTC,CFC+AHBB<;4B7CBC )CB59CBBBB:CBWBpCA8B@@dP(C B@B ABAA UCBdaKCCCB B@AXBBBB`BCBBB0AdBBPBBBBBAl,*CpBBAC `BB,B@@B$ BB8BBB(BHBdB8B, CBp CYCCAPA8B CBB@XBCcC C@AX dBG@,B8uCC[<@@BBCLBdBAhC@BBABpABBlBBB@CB4BBAC`hBBjCBAC,B2CBBBBBBx0 CDBB,BB BBBAA$lBDTBB(BBB%CB B ,BBBBHtABBAAB(ABOAABlBBhpA|P CCCBBBB@AB;@BBB&`Bp4BPtAA C"CBB3CB*CB0@A&CB}BCBABk0CBAZ\CCB? Ah` pA`B(BBCB,BB&CB@tBB@@@tBBBpB$B@PBBG@AB BBC`YCBdCCAwB>CxBA9hBBA@CHtBBTBBBtBHpB@A0A`BlBD|0AA4BBCBPBXBBB=CAC*,T,B^-CAAC(BCB/B`BA$AB,BBBBBBRB)CB4dCB C8C@B0ACxBHBB AYCKCBAPACB A+B9CxA3CHBCB 0A PAC A(B BABBB@ABCBA3ABBC$xBBvCCDJd@|BB @ABpBlBDB\AAC C,B0AB`A@ C,BC(BBBChRBBB(BdBBABZCCA(&BB>CEC ACBA/C$C9CXCTCA @B.C5COCB9Cph@@BB4`BA`ABABB$BBBhZ$,CBHBBC@D\<CBX Ct@B[C>CPBBHBA@ABB<ABCCCAA(Al X BC(CBBBdB$BDB!CBA@A@`h|B,=pl@@@ APAA?(BPA'CXBPACC?< BxB`AAp`A2CBC#CDC5?A"C BH4B(C@BApB(pACB CpCpAJC@BC0Yp$wCVCBgBBBS|C&CBABtA@CA"HB$BB@@@AxBAB\B,CLBBBBAC ^BBBC cC)C-pA BAhB|XBB4BCPA`BA,BB!B |B2B,0B5b BxB@C XB PABPBYp#CB BC A+@B'Ch<BCBBBADHBBPABXB4CABBB C`BACAB C8D@@RBBIC,xB AB CBlBA,B|B$BC0AHC@|.`B\CAAB@AB@\BBBPB$BCB@ ABCp@B|BvBBBr8BB@@A4BBPAC@[@CAA@B@dB@2P,B8C?{-CBBdCBLA;BBpAC8CyC CvB 'C CXB(ABCUCAC@@CBB<BJC0CAA0CCBBl3CDBdDB`BB CpBBBBC4BC *@@C3CB/M BXBBhBAB @+jC;CPCBBB#CCBgCABBBWCC*@@4BB(C%`ABAC@@0ABDBBCXB0BABB#4BABAA0B-GCx|A4C|CC,XBA+hC-C dxhB A@BtBbCBTBpBCBCL!CFCp@HBBABBBACBMCxBACAB B@|PA C\ C BBpCB9l\BLBWCA-ChBCC PAA+C0 KBC(CBL|BG\B CBAAA'pB A0A`A`C@HBB@lBCCB@A CBB%CBOCCxBA0ADBABPAA@A#CB` ApB"CTBCCB p8.XBTCJCBBBcCrC0PAAB+CB$B,0BkCBB8BCD@H&BAAB4BBBCA~yC8BCBA"CCAA CAB C\BCAlB@CB'BChElB AnBB?3C.=@\BB0AB@ BBBB0ACB ACpABDBB4C`XBhB@BBC@CA@ABgC0`DB9C4BCxBAHBEBtB4BBhCAC-CPBChBBAAMCBJA8BCB;HBCCCBBAB'C$(B0AB*C@D$CC@ 8CB!CCFCCB@LBDBB 1CQCBBCCBXBA0C@B@ C<DBB BC|B CB4BTBCB'C-C0B"CBAtB8 tB C`A!C@'BBC BC8UBACHCdBBAL@*CBB@ CB`AhAA,BA%LB'CAB,C@ pBA@@@B.ABPB`A BBB@BCCBkk<BB`@@hBBCCTC@@1C`BC0B@ BxBBB!C@8B| HBBBBCC`jBBA\BPAlBBBA@BBBBBpCAC@A@AB ,C@@CTCBA5CBCCBBQCABBLB@T BCBhB@(lBBCLBAB2A$BCLC<$B0B$B@BpB=CHBpB0AB|BBBB4BBBB@B4B@BC@@BAB1B,BBCA0C A&B$BB$BYCxB 4C7C3CB(\CBI4BCA=,BA\B0ABA)'BBCTBdBClBCBBD|BB,C$BA8BACABXB"BzCzCBB AC\BC CAB9CA BBB@B@A@(BB A@BtBLpBAC CA0A8TABxB]8HBC$B CABBCBB@$(ACPBB@CBAB@A<BB CVC B@BhBB`?BpA|B?CL\CBA |B8XCBxABB@ B|B9CdBBBBCBB hBACNCC0/PpBxA@C@CBABH\B`BBB@C4@6CCBDBABATA0AtB@?1C@@BB \BBCCxBBBBBCABBXBBHBkB0 CBAlBCBBB,B]C`@CBBBhBA@BBy?!CBB+C`CALAB CB0B0A CBCB AyCBAApBBH0B(CBDB$`BCBBBBCPBBpBB8(B@B$ICB# B]CCTBAB@BPC|B4BAAB8BBL ABBCFCBB}@0A0B xBlA`B-BBlB CxAXC,B%CaC@(BCkC B BBBx0B B+pBaCB:(Be`BLBBBAABBBABBB/CBBLBeCB3B`Bh|@@A5CAT eC,CB+@A BACB|CA4BCC8(BCC&CA|TB CBCBBA,ABdCBCBBB`A@C@A@0B AlBKC,CLBBBBBChBB`BABChCxcBxBDA|5=CBB2=`AB0CBBC@4C1CApXB3CBA<B{A@BBAB`@B8CCdB`BPAxVCBX@BC B(B@BA(CBDB8@ABLBB1%BCC0BB@BABDBBX-"C(B\BBCBB@B8BVA{C[C C@`AtC0@A;C B-BBjCC@n@B`,CAPBBBTB`AB CABBsCBCT ABB1H*CB8BA`AjC(BBAhBC0CBBABBB$BBB_CBC(C~@ ACpB0BBB!BBtBA WCl:?bC4B BAB@CCxBBCB@CBBACDB@BC&CBB`98BbC,C4B@0ABCCLBA3CBA@CpBBB@8B|B@pAATBC>CLBBBA%?\@BBB`B'C$XBP,CAp<XKCBA!Cx@VCBLh`BCB$C'C>CXB,BCH|C&CBC@ ]C8CBBBlB,LABBhAAd-CC@AB0C@LCBpBBBBBB.C B@BC BC C@@@BPB-@pBB@ABB@j^CB A@0TB8BBA@A$BB7C C.CC!88BCC|Bhx AGCBBCB@A#C0B"C(BCJCPDBC,BCp<xC@@BBB(BCBBAAA@@'CjCi/ dCBB ` B(PBBBVC ABdB% (CCICBBP@ABDBBB@AA APBCATBBBB4B`CC BBBCC,B)BBBBtAACBBLBAC`@@2CBAA@BhBAB@`ALBA!CC@TCC\BPAA'8C:CgCxBB(BBAA0BB`BBXBBBKCB&@`CHBBAWC B(B@BB @BOCCpBC=C S(BBBBCBB@#B:C0C/`HB0CH@@_AB 3CBCAPB@@8B(BAA@@BBpClBA@XCBB`BYCCBB$B4`A A0A?DBC@CB-CC$BtBX=CCpBBHOBBBD,B B CxBBAlBAhBAQ@BBB0BICCB(B@CBB ACiCgCB@PAB BC  CRC@@B0ALANBB@BpBBtB(BB CB<@@YLBCB$BBBCBHBBPBBtBICB&CAAlBhCpB0B@@B"CB8B`CBBA841CBB0ABB/CLCA-dBB(CBBAABPNCp=CCBBA,BTBBpBB"C|BC C0BUCBBFBXBxBxB@#C4BECCxAB AC]CB@ABlBBBB"C B$XA0BCBCCBxBCBB\$BCpBBBgCB@BSC|tpB CPA@ ACBpYA?C C,CnC\BLBOBOCB5@yCBtBB-AOC?BBBBBBCBB0CgC@BBBB=CJCBpALBB+C CBB2CBBABBBHBB0C`B|BT7`BB@C CBBDC<B|BBpA|\L/C8CBu`BLBBAPB|CAX"CLA1CB$tBCJCBMCoCC,BP@CC%CCAc"C%CPBLB CA0dBCABBBABDBBBBBCBBJBAP*CBB BlB,CBp?%C(B4HBC BpB@BXIC CpClB ABXBB,BBCAC\B@'AAB@CBx #CBBB$3C%AlC8C+dBB+CL@CBPB BCpDCLBCB8B@@B.xLB(B`B A=BBAB BXCBXC8BG@PCICBHB CmBoCtC?C0L0ApBBBBBCBF=C6DBAEC(B,B CB@'BAAC|CBB@BPC@CBtBBBB`BBCBC`ALBXBB@/C CAAB"CAB02C[C-B AtBAHCxBBB BC'BB4TBBB`B`BBBTBBCAH@@C7CCxB<DBBBCC8AB@B$BBlBAPABXCBAB(BCBA<$C A@B A0BBPBphBhBBBC+CBBBA B4CC2C AAPCA#C BBCB"p0ATTBBPC?CB7CdB$8CPB BAC CBCBXBB|0tB-CBBC CB$B B`B8CCE(HBCBBAAB8C=CdB8B.CXBA\DB0CtBtBTBBPBABBCB8 CpBB?^C_C0ABB mC0CAX0AABBBCkB@CB$BAhBB@@@CA(B(B?B(BBLBB \BBBKCA8BB9TnC(BB,B BC@CBDBPxB,BLBBSC C<TBTLBDBAB6@BCTDBoCBAUBABLBBBDBPABC\BBCA<<BB@CALBB8CpCCB B55@@BBTA$4 xBCpBBB0AT@AB@BBBAChBBB ,8B`B;ClBCBBC@BXB[CB@PAB@BXB'CB#5CC C|BpCLCCClBBHCBBtB\$BkC?C0l\HC C`'C%CB@9CBBB,ABA@=CBBPACmCAPBB@ BBBBBlB)@A A0AXXBjC@BABBtBpPAcCZChBA Cl A8COCBPBY@@BABACBC) B&CCSCCB BB ClBBBCBB@4BAA81CB CBABdCBdBAABA!CApCBpA@CA@ C-CBB,BB.BBBpBBBBBB @@BXCBpB[C0CB@ktB!C AB`xB-LBBC$C`ALB@@BCC$BBCCBC"CBC<8 ,BBYC BB8CBBBAD APBD@B BACCB@A=C\tBBBBCBCC\@xBBB`A-CCABOPAABM'CICCBBABCxBAwCHCCAA$hB` C@CABBBABC `CCTDBBDBTBBBT`AA8<8B>CC?C|BCDCBBBBx0CJ ABpBACdBBBBDBkC@@AOCBBBABBNCBCXBA@BACBBB PABC`B@A"CBBByC C\%BBPBBAHB+C4CCA@C`A-BB@C\BB B`BtB C"?CHC:CCABRCfCBD@0BCBAB(A6CCx BC`BdBBxM0ABdBCB'CChB@@pxB4BBB\@A BB#pABBACCHBpAA`BaCCLC CC6@A)@Bp,CBBB?BBPBpC@PBAAtBdCCBd,TBPA@BBZBB5CCB@pABBPBCHBxBBBCCCB\3BBVCC\PBCPBdBCCCB< BBPBC(`A?ABB!CPB@[@A,B,BtCBBBC4BA`A|AlBB@A@@B KCB$BSC#CICB C@BBhDB'C0=CBCBp%BBCA=.CICTBB CBC< @BCB3CCBBCVCBLHBAA Bx dBJCBCA`ApCBB8B*B,pCiC7ABB@A,BBB AC@@AB>CCC8BBDB7CBA BBBBB0ABB(CXB=HXC+CAHBA CCB,`B\BCbCXB\B@ACBBCpAgBCCB1=OCAlBBBB|BCB BB9 8C BBCBxD ClBCC B@BABPB@CCBlBB[CBBB@$XB8BdLBCBBBBBBCUC7tCA'CB&AXBBB8A$XPByCB'CB ABBB0BxBBtBAB@AECBBB AB0B@@C@@ 4$B:C&CB1CF@CCCCBBBCB@B-CACB!CB0 CBtBBEC@"CBK8B B]CC`BA `LBA5CBABBBAlBBCCLCBBBlBTCApWC<BAoCBB]CB8 B*CB4BT,,BB7CPxBAB@$ABBA@B%C3BBBTCBAZCMC%CBA@TB"BBHABBCBBB|P(BCC@ACdBXCWCdBBBABB(BcCpAt!PBBB`0A<NC<pACwCAHBdBB,B CCClBpA ABB@gC@@BmC2CBB>CBpAAC:C@lBCCB?XB B@B1CCtBtCCpBBBlB#C*CBCApBBCC:C@B B@ABB#pBC,C,BtBAtB@BBB C`BBxBBBCLBPBUCCBB1C0BB jCC#CBCBBRCApA C@AAPBFC(SC,hBB CHBB@ (CC@CeC.CC@BTBBBCBlB BBECC0hATBBAAAC@7CC0 CATlx$BCCB4MCCoCBlB7BCApAdBBRCBBPBBBB,BCqCBBACCCBB@@ ABB\BGC CB?CCA4B<AAeCCtX.BBjC$C (BB@,CCBv@BlB~CTB)CC8DB4CBB BBBACBCxxlBlBBB^B BBdB@B&CAC0,BBB4BBx*CAB@kCB@tB`ABBDBCCCCCB BCC[C C*CBB` 0C`PBBwCBBPA C?C`BCCB(PDBCBAAC=CBBHCiC:CAHBBB6CB BBAxBhBB BCB BB@BB@|BDECBB0AP1IBA(BAAB9Cl,BdCBBC0C0BBB B@@@@AABBB<hBLBBABNCCC+BBpB>CBB[CA@BBCC C0(BCzCB:C$BAB\BAp5CCBBCPAA AB#dBB@FC0AABCC`A\BAHBpBA0AA"CjX(CCHBB0BBCC$ChB8B qClCCLB%PB.CxBPCBC A@:CB\BBhBi1?BA2CBAA*CBA@BoBBPBC|BCTBWCB(BlBB8BdC$\ZCp@BAAB,BCABBABAB1C CB@AB@C C`B[C`BCCBpAByC`BBB@@B-CB B'CA4BAABCBBdBBCxBBB0APA4BAC$'A|BC$CCCBB@BBBBtA9CCB'[CC$0.CCA,CB8CA$hBBBEC0AtBBBPCB0eCBHBdBB`B,B0A$BBBBPAXACBB BBAC@B\C@BA(HBCBBBBBBhBpB@AB$CBBBBC CC$@B CPRAB=CBA/CCPB,CkCB@@@6CBrCB\pAAC?C CBAdCBBAA@BnC4CPABBAACSCBBBB;C CCptBA^CCACBB B BBCB(BLBBC]CBUCBtB0@BAADBBA@AB C`BACPCB C]CDBBB!lpKC5CB\BCBA4B,B`AA AACC/CC4BCAAA@@@hBBBB@C/CLPBhBdBBtBB3CB@B!CCCBBTB:CCBqCCBBBBBABB,BBBp@@@AC\C`AB@BHBBBLhBrCBB AHClB@hBC@C`?BBB\CB\BBaC@CA`CQCJC(BBBB`CA8B4cCB?BMCBl C4BB=CB BPuC BpDCBA@BCCBC@BABBBgCgCAJBwC6CHBBBBBCBB@1CXCCBA CpBPA`B@C!ChABB#CBB0pBBMC@B A0CBC0CBBC$ BcCCCB5BBB$DC CB\B< CNCBL)6CBBQA0ATBBB|8AJCBhBBCQCA:CYCLB@BDB BB$BxBHCBB BBB,BB7C0BBB?>CCxBB C0B\C@BB#CB@BB(B8CB@COCB2C@A|CpB`CCBx,@@XxBCBABBBB)BBBxpCCB AAxlBxBA&AC2CABR0B@ pADC.CBABC5CCCUC`BCBBZBdBxCBB BB|BBCB|@H]CvCCCBBXBBlBCA6CAUC$BBCCCL'5(BC7C(BAPB PABABBlB(BdB B#ClBBC$BB%CCp0dxBBCCBlBA;CBB C@AyB`ABB@CAxCAcCSCBYcC"C,BHB B0BAB@0ABhC2C4B hBCABBPAABCCWCBp8B BRCBBIC@B[C@A @BPB@$BC 1C CBBC8BB03CCB/CBAB CLdBfCC@B@AB$ByCoCCPCB6CABBBtAA C+C B$B6C,BXBJCnCBBBBBADBB"CBB h^ CCABA,ANCCC=CA5C7CmC$BBXA@ABB@B \ CBKCBAACBBCBBB3C`rC`ABBBCBB(BMC8C-ACCCDBCDCB0B@C4CBCB0A CCC?BCBABB"CBCC0BBBBB?CPrCB`A(C5C\BBCABB(CBBBCBBBBBB>CFC\B@CA[CAAC+C0AB`BB|? ?B=C@JCC\CA+CC CBBCHB@BBC@ CBC1CBABBBCC (CB|@<CdC\BCABB=CCB_CCB|BPCC$B,B BDH:C(C`BBBLBB^CpABACHCBB C'CBBBBBA;CCCC0BCBCBB TBCA0BHB ChBQCBBxBAB(CpBBnC1CB@BdBA(C4CBBCB@PCCChCB&CCyClCKCAPCMCCC`ACBB4BBC*CBC}CdCp`C@SCBBC{C(C,BC0B1ACCdBA@XC,BCBBBnCBB`CBC BBBBBBlBABCCBXCC CCBBBBABCA&CABA B BABCXB>CX$BBB%CdBCCAtBBPXB0CBC@BBCAB CCCB`BAB=CBABPBCtCCABJC5C@C'ChCECBBBCCBBA[CAPB$CmCBBBArCCBk@CCCPTAC7CBB|B CB B`BBBABA 4 CAXBBlBB/CAB4CxBAP CC#CAtB`ICBABBBBCB"C<+CCLB*B4BCBCLBB~CC(C@ C4ChCBABBCBBZC.CCCCB8BABBCC\CBBBAC;TwC(BDCAPAB@CB4CPCBB CBACBCACC\BB\BtB%C0CdBB0B@BC[CBB4B CCBB$CBA|BAABP@PXBBCB0CCB CCBBX`ACxBB2CBAtBpXCAC@(CDCHAC"CGChBxCC BBbCABCA@#CB`A|BBCBKCoC4C2CABCTCB4BB AMCBBB BCBBABCLBXCCBBChC B@ B\BCCBPBB?C8CXCBBdB0B7CBBPBB0BCCCBCCPBtCAB02CC0CC<BABCByC8@@2C8CB CBTC C@B>ClBTBmCWC=C}CAPABB@`ABC)CBBlBgC CmCCBHCBBBBCB@@ACB1CXCdDBBUCB$CBpBBVCCB:CBCBCxB)CXC`_CtBB9CC}CCHB]CpCCB,PABCABCCBHBCBBBB CA CCBCB`Y9CCCTCAC AAC|CACCBDB%;CCRCB@ADBhB`BA C CBB?B BBBCAB*CB0AB C\$$C#C AB'CBA7BCLC A?/CCtCCBBdBBCBX0C7CCxCC0C$hCdB C$B`$BDC B CBAB8BCBBB@AXCC7CBlCBBB"CBC^CC8$CB2CBP AUCxBBGC CHB(BBAACqCB@BC4BCCCBdFCBgCBCACCBAHBABBCCB@?BXB*C~CCCA,BdBB"ChhBTCCBBBCC-CBCBC C0AB3C/CA@CCBhBBMCB$CCCBBTB@ACB"C'CBBBCB C BAACxCB4B5C`CpA CCCB B C@BCCBB;CCCBB#C8C?0ABBhCCCTBA5C CtBBBkCMCBBCTB2C<$C%C`B(CB3CmC B!CCWC(CBCCCC'C CQC\CC\CC7CACDBCCBCBCBCqCC[C C C@4BpABBBECB|C#CBC[C@BC%CBC)C7CC4BBBECC'C[CAMCB8CC C&C9C[C@@@AABCBAPCnCCcCMCpBC@ABBTCCNCBBA|CB,BCAB(CAB%CCCB0A6CSCCCCCNCB"CCXBBCCCp7CFCBBCA BBBBBBBCCBCB BHCBCC CBCAB-C!CCwCB@CBBpBAkCfCCCBCACCmCCB CCB$BCCACzCBBC:CBBC-CBB)CCCBCBCRCBB/hBaCCCTCRCCABhBBC!CBBBBPCBBBKCB`CCCA4B CCpEC;CMCC BBBC&CCCB@CCPBCC=CXBBB@B`CA$B9C3CWCCCBBCxCC@@AB'CuCoCC-CCBBChChBcCCCCCB&CBtBCCCBLB3CABBCA%C_CBB,CfC+CB@B8:C)CBBBC0BB B^C CBA~CCABBCZCCB#CCTtBCB]CBCBBhBJCwC*CABC'C7CCCC4B$B}C1CCnC[CHBoCB4CuCB|B|B\BzCBVCBaCpACCTBeCPCBBA/C CB CC?CCB9COC@B)C5CCFCCCB!CC9CB B1CB%CCABA|CC&CBC2CCBBC9CC CCtLBC`BCCAB(C)CiCAC4CBBCrCACCB#CC(BCZCXC8BBlBCPB.C"CCBmC&CACB(BBpABC>C@BeCC2CoCC9C C,CA4BC;CBCVCCBCTBCB\BbCCBBBCC\BBCCCjC.C9CACChCC7CCCC\C1C'CBDC BfC4C.CCC-CSCCRCBCC4BDCCCCBCjCCCCAClC CCCCWCBBB|CaCxCBBCEC.CCHBXBQCC=CBBCCnC\BCCCCCCCCBBC~CC_CCXCCCC}CuCHCiCBCCCAtC.CFCCCCCCC1CCCjCfCB>CCCNCCBBCCB0 CB BoCBCCBC/CmCACCCCCCA}C~C$BCsCCBC^CqCCBB4B\-CICCBB$CLBBpCtBC^C'CBBCBbCC(BBCBBHBRC{CC\BmCcCBABCuCCiCClCCCrC.CBCCC0CpCC-CHC0AmCAC8CCCCcCaCVCB[CC-CBmCC,C5C9CoC*C.C"CdCC(BCbCeCCCC`C CCFC]CCCCCVCCBYCCCCCpC%C~CCC4CCHCLCoCCTC@ C CPCCC@CCCCCiCSCLCBsCKCC!CC8BBCCCC0C\BCC`BBB(C@BCBCCB(CC#CBCCBrCeC"CCCCCC9CACpCCjCCCwCLCCCCCCCCLC]CC&C%CCC$CCDBCCSCfCvCC CKCC}C4CBZCpfCCCCrCQCCBuCCCCCCB CCC&CCCCCCBDCuCC]CCC1CBCCwCC"CCCBAGCBBCCACCCCCIC0ICCBBCBWCCCCdC8BCCCCB|CbC\C7C]CBCCCCuC\CCCCCCBCvCFCCdBCwC,CECCpBCCCCCAXBCCUCAQCBC[C!CBBCYCB CCCCB:CbC1CCC AB1CB CNC@CCHB\CeC?C8C2CCDCCoCFCCBCnCpBeC=CFC CCCrCVCCC'CACC8C2CAC"CCCrCBBB CCCBBABwCBZCCCCACRCqCCBDCpC4BYCCCCC4B,BCBCCCBABCICbCC0C{CCCCCBCGCCCaCBBBDCDCC*CBB[CCCCpB C#CCCB6CCpBCCCCCaCGCAQCCClCCCChBCCCCCB&CrCC8BBCCCMC6CmCCCCnCBCBBeCCuCCCBCCC.CCbC[CCCB B3C CCCC`CCpB8C@CCWCRCCkCCBCJCCB-CBC$C_C`CBoCCCsCBvC$C@CBCCCkChCBrCBwCCCWCC7CBCrCCaC@CCCRCCCCDCCCC-CCBCCCCCBCC*CgCCCCCC>CCgCCCCBCCBC9CC#CpCTCDCtCCCCNC[C@BbCCC@DACCC"CBC CBCCCDCCCC(CFCBCCBCCC*CA-CCCCC7CBCCC\CC6CCSCCBCCCqCpB@C\CCC9CCC}C CCCCCBiCC#CCCCCCB+COCXCFCCCCCB]CChCuC-CACCCmCCALCCCCCC`CCC CCCCCwCCCCCCC&DhCJCCCCDsC4CCCCC)CBCDCCxCCCCCCCC@,DCCYCCCDC`CpCCCC-CCCzCCCCCCrC?CCC#CC_CCCCCCCCCwCjCCBHCDCCCDC{CCCCCfCCCCCCCC6CCzCCCCCCCCOCCCCcC[CCCCHXB]CsCCCBnCC CYC@CB(BCCCCKCC CzCBC7CCCBTCDCCCdCCC0BB)C!C_CCC=CCCCBKCALCCNCC@CiCCCQC CwClBfCCCCCB5C6CzCMCCOCCnCBCCBrCBICCACCCC0CC@=CCBCCCCCBBCCCCCCQCCCBUC6C6CCCCZCBCBCLCC.CCbCBC_CPCCBsCBC7CCCyC$C)C A#CBoCCBCCAbCCCCNCCbCBBgCQC"ChCxBCCC3CChB CCrCrC3CB4CCCC0CBCC~CCCCCBB4CC-CCC(CC4CB ClCCCCAWCCDCCC`CClCCCCBCiCCCCCvCBbCuCCQCVCC3CNCC`CBBCCCCCCnCvCCC_C BCCRCCCCBCCCCCBcCCCCkCACCCWCBBCCCCCBEC0CCfCC CCuC~CICCACLCzC^CCCCBCCCCCCOCCCC CCCC?C&CrCBCC%CCCC^CkCbCCCCCCCCC+CrCCqCC CCCoCmCCBCCCC`CBCC^CSCCCC3CBCCCACCCCCC#CCCPCCBA,CCCC2CC{CBCCCCBBCCCCBTCCCCpCgCCCCCCCCCCCCCCCCCCCCC\CCCCCCCCeCCCBCCCCCCC0CCdCCCCMCfCBFCCCjCCzCCDCpBjCDCCmCCCCsCCCCCCC#ChBCCoC CCCACDCCCCCWCpCCCCCCCCCC`CCCECvCCCBC,CCCCCCCCCCCCCCMCBCCqCCCrCCYC\BcCCCCCCuCC@DCCC|CCCCCCCCvC|CCCCwCzC`CC[CCCC CCC8CuCC@DCCBCCCC9CuCCC DC%CC|BCCCMCBCCCCCCCCCCCCVCC'CCCCIC%CC$CCCCCgCCCCD%CCBCCDCCCCC2CBCCD D-CCCCCCCC?CCC DCCCVCC@DC&CCCCCCCACBCCpCCCsCCCCCECB~CCCC@:CCCDCC-CCCCC1C1CCCCCCCmCCCCCCCCfCCCCCCCCCCCOCCCCCCCCCCC@DCCCCCCC|CCDDCCCCCCCCCCCBvCCCCyCCCCiCCCCBC D@DCCCCCCCCCCCCBBCCD1DCBCCCCCCCCCCCCCmCCC@ DCCRCCCCCCCCCnCCCOCCCCCCACCCCCfCCC%CCCC%CCCCCCyC[C`CCDCCCwCfCCCCCCCCCzCCCCCCCCCCCCCCCCCC@DDC@DC_CCDDCCCYCCCCDC~CCCCC*CD DCCCCCCNCCDDCCCCCDCCCCCCCCCCCtC@DCDCjCmCC@D DCCCCCCCCCDCCCCC@DCCZCCCDCBCCCCCCCCCCCCCCCCCCCCeCDCC(D@DCCCCCD@ DCCCCCCDCCCCCCCCDDCCCCC@DZCCCC@ DDCC@DCCCCDCC9C DCCDCCCsCCDCDC@DCCCCCCCCCCDDCCCtCCCCCCCDCCCDD*DDC CoCCD@"DD DCCCC@DDCDCDCCCCCCCCCC1DCCCCD@$D6DDCCCCCCCCCCCCCC D DCCCCD DCCCCCCCCCC@7DDDCCDCDCCCCC D DC]CC@DC D;CCpCCCCCCCGCCCCCCCCCCC DPCCCCCCCCCC7CCCC|C>C CC1CCCCCCCCCCCCCBCCCC|BaCCCCCCCDCCC_CCCoC\CCGCCTCC CCCfCCCCCCCCCCCBfCCmCCCCCCC2CCCC CBCCkCCCCCC5CC_CCCCCCCCCC|CCBCCCCCBwCCCCCCC DCCCCBCCCCCCC^CBCCCyCC`CBCCCkCCCCCCCCCCCcCC3CCC@DCCCCHCCCCCCCBC/CCDDCCCCCCCDCCC;CfCCCCCQCCCC D@DXCxCCCCCC@DCsCOCCCeCCJCCCCCCCCCCUCCCCCCCpCCCCDgCCCCCCCC`CCCCCCCCCCCGClCCCYCCCCCCCBCCCCHB]CCCBCCCqCCC DSCCpCVCC@DDBCCCCCCCCCCCCnCCVCCCCBCCC DCCCCXCkCCCCCCCCCXCCkCCjCCCDCCDsCCCdC_CCChC D DCCRC9CCCCCD@!DCCDC#DDDD@ DCC@DCC@D D"DD@D!DDCCCCD@D DD D@"DCCD@DDCCCC@1D DDC DCD=D@DCCC6CCCCCvCmCPCCDCCCuCCCCCCdBCC DC{CCCCCSCCCC=CCCCCCCCCCCCCCCCCCCCCCCCCCICjCCC{CCCCCCCCCC5CClCCCCD@DeCAjCC@DDCCCCjCCC@/D DCCCCCCCCCCdC DCCD@ DCCCvCD DC@ DCCCCCCCCDCBCCC@DCCCCC@DCCCCCCDCCCICCC DCCCCCCCCCCCDCCCCCC DCCCCCCCCCC@DDCCCCCCCCCCD DCCCCCCCCC@DCCCCDDCQCCCCCCCCCCCDCCCCC@D@1DCXCCCDDCCDCCCCCCCCCC@DDCC@DC@CCDDCDC DCCCCDDDMCC}CC@DDCCCCCCD"DCCCCWCCCDDCCCCC$DCCCCDDDCCCDDC[CCCCCC@DC DCCCCCCDCCCCCCCCCDCCCCCDCCCCCD DKDCCCCCgCCkCCCDCCCC DDCCCCDD@ D'D@BDCCCC@DCCDCDCCXCCCCCCC@ DCCCCCCCC@D@D@DCCCCC@D@DCC DkCCCCnCCCCDD@DCCCCCCCC@D*DDCCCCDDCC@DCD#DCCCCC@'DCCDCCCCD/DCCCCCDDCCCCCCCCCCCCCDCC@*DDCCCC@DDCCCCDCC$DC DCC D@D@DDCCCCCCDC,D@DCCCCCCD DCCCC DCCCCCCCDDCCCCCDDCCC@$D DCCCCCC@DCCC@-DDCCCCCCC DCCCCC@:DC@DCCCCDCCCCCDC@D@DCC DCDCCDD DCCCDDDD DDCCC(DCD@)DDC@ DCDDCCCCD@ADD8DDCC$D@DCC@D%D&D@D D1DCCDC$DYDD@D2DCDD D@D@DCCDCDDCCC@D DD@ D@ DD@DD@+D D D/DCCC@DD0D D"DCCCD!DD*DDC@DCC D@ DC$D#DDC@DCDDDDCCCCD9DDCD@D@,D;DCCCDCDC-DD*D'DD*D@ DD@ DD DDD@#DDC D@+D/D@DCCCC@D:DSD@-DCDC D@ D"DDD7D2DDD0D&D@D1DCCCC+D(D3D@DD DD6D@%DCD,D'DD D@9D@%D;DDCCD@D(D@#D1DDDDD DDCC0DDC1D DC3DD/DD@XDCCCCD@0D@ED_DDCC!DDBD@2D D>DPDD@1DDDD@+DD'D4D@!D=DD*D@"DDDC@,D@D@9D%DADND@DCCDDDD@bD@ D@DDCQDCD3D#D5D@:D$D#DD@FDD D@(D D'D9D@ND?DDC@DAD*DD'DD D D@DD#DD@ D!DLD DCC`CC@DDCCCCDCD@DCCCDC DCCDCCCCCDCC D DCCC%D@DCC"DCCCDD@DCCC>CCCCCCCCCCCC@DC@ DCCCCCDCC DCCCCCCCC@DCCDD@ D@DCJCCD D DD@DCCD|CDC DCDDCDC@ DD@DCCCCD@D@DDDCCDCCCC*D@6DCCCCCCCC DCCCC@DCCC@ D@DDD@DCDCC DCCCCCC@DDCCCCCDDCCCCCDDCCCD@DCD DCC!D DCCDCDCC@ DCCC DCCCCCC DDD-D DCCC@ DDCC@ D@DCCCCD&DCCDCD/DCC@ DCCDD DCCCCCCD@DDCCCC DC4D DC DCCD DC@DCC)DDDCCCCD D DC DCD DD%DCDCCDCD*DC@D@DCC@3DDDDCCCC@D@'DCC@#DDCDCCDDDDDCCC DDCCD!DCCCC DCC6DC DCDD(DBDD,DCCDDDCCD DCCDC@ D+DCD1D DCD+DDC DC@&DDC*DHD@0D@3DCC@D8D DaC5CD`DD D DCD/DDCCDDDCCDDC/D DD D@D D!DC$DDCCC@DDDCC8DC5D D@ DCCC@D@ DCDDCCCDD@;DDC@3DDCDD"DD DC D@ DDD@DCC DD@D@DD@,D.D!DSD4DDDD@ DD D8DDCDCD DD D$DD D9D.D*D@DD@D6DD!DDDDDC@D&D@NDD4D DD DDDD8D;D@#D@:D@D@HDSDC@D@DD@8D@DD@D@"D-D9DCD!DD@DD7D D-D"DDBD0DC@D@D:DNDDC/D@DAD,D;D@*DDDCDC>D%D DDCDNDC@(DDCD D.D-D(D(D@ZDD D@!D@#D)D7D@D@D;DDD@D0D*D@GD"D DD@"DBD@3D@SDD1D3D5D2D D@4DD)DHD"DCC1D@DD1DCDFD7D&D*DDCD3DC2D@D@D@,DC*D DDDD@UD?DDCAD8D@!D"D@4DD@DDD2D@D/DDiD@6D,D@DDD@TDCC5D@-D D'DC@D4DCDCC$D@1D@>DHDYD@)D'D@@D2D5D6D!D2D/DD@D@BD9DNDWDD D+DCCDHD D D@QDCD%D!D@DQDDBD$D1DCDD D9D@%DD@GDDgDwDD3DD@>DBD@`DDD@=DDDuDDZD@EDgD7D@CDnDDDiD@FD3DED@(D/D_DfDdD@DD@8DhDgDjDmD0DRDNDBDpDLD.D?DODiD\DD-DDDRD@YDBDOD@fDQDiD@vD DqDJDWD@jD@IDND@bDaD@nDTDkDeDfDDD DdD@ED5DYD@dDIDLDD#DWD@2D@RDD}DJDOD@vD?D>DkDQD@RDeD@9D@QD]D@ZDADWD@5DGD@pD@(D#D+D_D,D_DED@ID+DDDpDqDD@D@QD@[DpD@/DD@2DBDHD%D0DgD`DeDIDLD@MDDJD!D2D@aD&DfDRDYD@DGD@FD3D.D@-D3DODJD9D2DIDDD D%DD@{D\D@D@DDcD@=D+D@6D5D\D@kD[D@'DGD@vD}DnD0DDDOD@VD@CD]D@MDLDSDaDsDD#D\D@LD2D@4DADDD@iDFDD:D_D=D.D@hDD|D@@D+DEDQD@DDD`D-DJD@`DYD6DNDlD8DPD@PDPDDeDbD@kDOD@*DHDrDBD@2DtD@D@lD@VDJDjD$DQD`DhDgDcDJDJD@zD@nD@7D@YDVD{DlDDDADIDDDLD@nD@LD;DUD@jD6D@mD@D@fDGDED@dDD`D:DYDDvD`DlD@DeDADBDqDDD@?DMD8DaD@dDqDvDdDODyD>DYDPD D DhDD@UD/DEDfD@@DD@WD-DIDjDxDPD@ODcD~D^D;DGDbDDD1D@IDvDDtD~DD@|DdDJDSD@iD@D@rD@OD@>D^D@iDeD@dD`DnDgD@nDZD0D@%DoDaD^D@YD@lDVDDeDkDsDuDdD~D>D@RDgDBD'D9D2D`D@lDFDHDrDlDD\D]D^DrDDwDiDkD@GD@PD0D@vDeDyDlDDnD@aD]DzDID@cDYD DDXDD2D@qDiD@D@vDDgDEDuDpD@vDXD`D`DdDaD@DDD@{DD@6DCDgDD@rDD`DjDQDeD~DODrD^DgD@kD\DD`DjD\DD|D{DDDyDyDtD@VDDvDZD@D@D}DDkD[D{DDDDkDgDDxDaDfDrD`DD@hDD DlD@nDD`D DD@^DkDxDfDDqDwDrDpDDDD@PDkDDoDsDDtDhDD@SDD`DOD4D@4D@tD@D`D^D@(DoDDND`D@]D@yD`D@DuD@vDVDHDlD7DD{DD~D\D`D>DDzDDDlDhDhDtDUD~DyDDtDfD@NDXDvDDsD@DDvDYDxD DeDNDXDDwD]DDdDDD@zDwD@ZDaD{D@YD@}DoDoDcDmDdD@lDD`DnDpDcD@_D DtDlDDpDRD|DlDDxD`DtDkD}D@xD|D@gD@bD@DhDyDuDDD^D@zDjDEDTDVDD@mDD8DDD}D@yDZDjD@uDeDwDaD^DuDDFDlD\D@sD^DVDWD`DDjDfD@DBDkD DDnDOD@aD}DD@oD]D~DgDDDpD@MD@aD^D6D@hDDvDxDVD5D@:D>D\DD^DWD@aD@gD@7DQDeDD|D@D+D@DwD@LD@$DXDDqD]D@OD@D^DdDD`D@DpD@rDD[DBDiDDzDtDgDqD@|DvDlD&DJD@UDkD{DvD@zD[DVDGD}D:DfDqDSDYDnD@WDZDDaD_DuDxDqDTD@YDXD@AD+DjDDSD@pDDD-D@DyD_D^DYD=D8DDIDDTDjD#D@OD_DGDgD@UD@zD@DcDRDwD;D|D DJD5D%DIDTDXDTDZDvD2D@RDbD@LD@QDKD9D9DEDDOD@HD@KDSDPD@[D|DHDD@9D1DdDTDeDBD^DfD:DADSD\DpD!D@D^D@lDrD@DfDID@_D0DVDeD@DnD\D@nD@yD@]D@GDeD`DBD7DaD@oDZDD DDdDD/D@aD D@nDUD@CD@FD`D|DZD@jDPDXDfDaD@cDwD@6D8DkD@wDlDD`DaDbD@gDmDpD@`D DlD@D@~DrD@DDDTDiDXDPDID@UD DD|DED@uDdDDDnD@5D D@vD@mDeDoD_DmDaDiDzDgD)D\D@wD`D@iD`DOD`DaDKDED@wDADDbD@/DJD@uDD@XDnDMDZDFD7DsDgDNDQDEDD@$D@DXDmDgDqD D DCzC`DDDDD`DDD@D`D`D DD DD DDD D D D`DD D@DDD@DDDDD D D@D DD@DDDDD D@DDD D DD DDDDDDDD`DDDD@DDD@DDDD`DDD`D D DDD`D DD D`D`D@D D@D`DDDD`DD`DD`DDDDD D`DDDD`DD`DDDEDDD@DD D@D DDD@DD@DD D D@DD`DD DDD D D D DDDDDDDD@DD@DDDD@D DDD`DD DDDDD DDDD D@DD@D@DD`DDD`DDDD`D DD DDDDpEDD DD`DDD D D DED`D DDDDDD DDDDDD D DDDD@DDDD D@DDDD DDD@DDD`DDDDDE@DD@DDEDDD`D@D@DDDDDDD DEDE`D`D@DD`DD@D DDD@D@DD@D D`DD DD`DDD`DD@DDDD@DDDDDD@DDDDDDD DD@DE`D D D@D`D0EEDD@D DD`D`DDD DD DD D D@DD@D`DDDD@D@DDDD@DDDDD`D`DD D D D DDD@DDDDD`DD@D`DDDDDD`DDDDDDDD`DEDD D DDDDDDDDDDDDD DDD DD DDDDDDD DDDDDDDDDD DDDD@D@D`D DDDDD DDDDDD DDD DDD@DDD@DD`D@DDD@DDDDDDD`DD D@DDDD@D@DD D@D@DDD`D`DDDDDDDD`DD@DDD DD DD D`D DDDD`DDDDD`DD D`DD@DDDDD`D DDD@D DDD`DDDDDDDD@D`D DD DDDD`DDDD@DD`DDDD@DDDD DDD@D@D`D@D@DDD`D@D@D DD`DD DDDD@DD`DDDDD D`DDDD`D`DDDD@DDD D`DDDDDD`DDDDDDDD@D@D DDDD@DDDD`D@DDDD@D`DDDDD`DDDDD D DDDD DDDDDDDD`DD@DDD DDDDDDDDDD@DDDDDD`DDDDDDD@D`DDDD`D`DD`DDD@DDDDD D@DDDDD@DDDDD DD DDDDDDDD@DDDD DD DD@DDD`DDD DDDD DD`DD@DDDD@zD@DDDD`DD@DDDD DDDDDD DDDD D D@DD@DD@DD@D`D`D@DDDDD DD DDD`DD DDDDD DDDDDDDDDD@}DDD DD@DD DDzDDD DuDDiD@DDrD`D@DD@DD`DDeDODDD`D DDD DD DmDiD`DD D@D~DtD`DDDD}DD@jDDDDD@xDDsDnD@D DfDrDDrDmDD@DD@DDiDuDvDDDDnD|D`DD D D`DD@vD@nDZD@[D`DDD`DwDxD@rDlD@]DwDDVDdDD@D DD@rD DD D@^DXD`DDD}DxDeDjDWD`DDD@WDiD@DgDyDFDDDDhDD[D_DJDfDD{DaDaDXD@oD|D.DUDDDD`DpDhDDnDYDxD{DDDrDaDUD@LDRDRDsDvDDDSD^D@_D\DyD@]DtDsDD@NDfD]DkDzD@yD@wDD/DZD`DVD8DeDkD@JDhDXDwD`DOD@OD@qDODHDRDaD@RD@dD`D@ZDD|D:DdD=DxD9DPDfDTDgDxDqD@D'D/D@DWD*DD3D@&DD5CE0EE EEDED D EE EpEE D`DE EDEp EEE@ED@EDDp E0EPEE EDEE@ E E`E@EE@DE E`E E EDEEE EEE@Ep E E0ED E EE@EDEpEE E EE E@DDEEE@EE`EE@D E`E EEE@DEEE@DEEDE EE@ E` EE0E@E@EDpEPEEEE@EPE DEEPEE EE E`EEE0EE0Ep E E EEE E EE`EDDDEEE0EEED0EP E ED`DE`E`EEE EE@ E EEpEEEE`E D`E@E D Ep EEE ED`E EP E0 E E@D`DE@E D@E0E0Ep E@E E E EE@EDDP EE EE EE` EEEP ED EED` EEE E EE EpEEEEEEEp EpEEDDPE EE0EE DEED E0 EEEDpEDEE E0EE EpEEEED@D EEPED@D EEEE EE D`DEE DE0EDDEEDE@D`DEEEE`DED`D DDDD`DDDEDDP E D@DDD@DEDDDEE DPEE E`D`DDPE E EpEDD@E0EpEEDD`DD@E@DDDDDED`DDDDE@DD@DDD`D`DEDD`DEDD D@DDDDDDE DDDDD D DD DDD D EDD`DDDD DDDDDEEDD`DDDDD@DD`D@DD`D DDDD`D`DD@DDDD`D`D D`DDD DDD DD`DD@D`DDD DD D@DDD DD DDD DDDDD@DD DD D DD@DDD@DDDD@DDDD`D DD`DDDD`DD`DD`DD@DD`D`DD@DDDD DD@DD`D DD DDD`DD D D@DD@D DDDD`DDDDD@D@DDD@DDDD`D`D DDD@DDD@DDDDDDD DDDDD D`DDDDD`D`D D@DDDDDD DDDD@DDD`D@DDD D D DD`DDD@DD`DDD@D`DD D D D@D@D`DDDDD@DD@D D DDDD DD@DDDD`D DD`DDDD@DD DD DDDDDD DD@DD DD DDD@D D@DDD`DDD`DD@DDDD@DDDDDDD@DDDD D@D@DDDDD DDDD DD@D`DD DDD@DDDD@DDDD@DDDDDDDDDDDD DDDDD`D@D DDDD@D D`DDD@DDD`D`DD DDDD DD DDDDDDD DD`DDDD@D DD D`DD D D DD`DDDDDD DD`DD@D DDvD D`D`DDD DD@D DDDD`D`D`DD@DDDD DDD`DD@nDDD`D DDDDD`DbD D`DD`D DD DDD`DD@D@DDDD@gD DD@D`D@D D`DvDTD@rDD DDpDoDDDD^D@KD@[D|D@DDMD~D@D DD@~D{DzD@nD@pD^DgDpD@D DcDRD@cD@D@D@D@}DSDPDD@D}DvDDDwDDDD}D@vD`DDD@qDxD@iDD@oDD DDsDDDWDwD\D_D@D@yDDkDD_DDDbDsDDDDDDnDeDqDeD`D@AD@oDcDnD@fD@DDDDiDhD@6D1DPDJD@[D D}D[DtD@GD6DaDpDD@DIDZDhDwDDDDD@hD+DD{D}DyDpDQD^DbDUDUDD[DDyDODbD4D@]DRDD@eD@iDgDzD`DeDmDSDkDhDbDD3D{D]D@DDKDTDZDqDwD@]DtDaDD#DTDOD@@DD8D@%D_DMDsDbDxD@7DTD6D@+D@GDWD@SDUD@4DIDC@-D,D@>DCBEEEE`EPEE@EpEE EEEpE`EEEEp EpEE EE EE !EEE@E E EEE E E EPE EEEEEE EEEEpEPE`E@EEEE EE E0EE@EEE`E#EEEE EEPE E $E@ EEEp EEPE0 E@E Ep EE EEE E0 EEEEE0EpEEEE@E"EEEE`#EPE E0Ep E!E EE`EEEpEp EpEPEEPE EEEEEEP EEE EEEpE0EEEEE@EpEpEpE@ E!E@EEEEEEEEE0E EEPE0EE EPEE0EPE0E E0EE E EEEEEPEEPEE0EEpEE E EEP!E@E@E0EE EP EEE E E EEEPEE E E`EPE EE`EEE0EPEEEp EEEEEE0EE E EP E E EpEEEE E0E E E0E0EpE Ep E E EEPED EEE E EEEEEE EDEEEE`EPE EE E@EEE DpEEEDDE EDp E`D`EE EDE@E@EDE E@DDDpEEE@E0EEE E DDD E E`ED0EDDDD`DD`EEE0E@ED0EpEED@DPE E D DDDDDE ED@DD@D0EEEDDDEDEDEEpEDDDDD`D@ED@D@D@D DDD DD DDD DDE`E DDDDDDD E`DD DD`DD D@DE`DD D@DD EDDDDD@DDDDDDD`D`DD DDDDDDDDDD`DD`D DD D`D@DDDDD@DD`DD DD`DD DD`DD D DDDD DDD@DD`D D@DD DD D@D`DDDD@DDD@D@DDDDD`DDD`DD`DDDD DDD@DD`DD@DD@DD@DDD@D@D DD`DDDDDDD`DDDDDD DDDDDDDDD`DDDD`DDD`DDDD@DDDDDDDD DDDDD`DD DDDD DDD DDD DDDDD DDDDDDDD@DD D`D DD@D`D`DDDD DDDD@DDDDDD D@D`DDDDDD`DDDDDDD DDD`D@DDDDD`DDDDDDD DDDDDDDD@D@DDDDD`DDDD@DD DDDD DDD DDD DDD D@DD`D@DDD D D@DDDD`DD`D D D`DD DDD`DDD@DDD DD`DDDDD`D}D@DD`D`DDDD`D DD DDDD DD@D@DDD`DDD`DD`DD`D@D`D DD D D DD DDDDD@D DuD@|DDD`DDDfDD DD DDDDD`D`DDD@D@D D@DDDD@DDD D`DDmDDDDDDDD DDDD{DyD@DD DD`DD@DSD`DDDsD@D DtD DmD@DDlD@qDDDyDDD`D@DD`DDDhD}D@uDD DbDVDD`D@pDoD@0DbDD`D@lD@kDfD DD|D`D@D|DuDTD@^DD@DD@D`DlDiD@xD@DtD~DsDDDD@%DQD`DZD^D}D@rDoDXDODD@eD{DiDlDDDOD@rD@ZDMDQDDaD`DDDyDaDuDfDnDiD@DODJD@xD~DQD@KDLDRD~D^D@DD7D@GD`D@qD@PDDKDYDzDPD@MDWDGD)D/D;DXD@YDpDDZD6D@KD?DMDLDDDDCCmCpE#EE )E'E`E"EE$Ep2E0/E&E E%E%E0E#E`E!E&E$E&E0&E@%E#EPEp'E0(E`&E`E"Ep(EEEEPE`E`&E+E&EE@E@E)E#EP&EEEEE`E $E E0"EEE"EE$EE@E"EEE@EE0#E (E#EP"EEpEE E@"EEEEEEE#EEE E@E@E@EEE EpEEEEE EEE EEEp&EPE EEEE@EE EEPEEE0E EpE EEE`E`EE`EEEEEE`EE0EEE`EE`EpEEPEE0EE EE@E@ EE EEPE EPEEPE EE E EEE EE EpEEPE@EpEE`DE`EEEEE EP E`E EEEEPEP EED E`EEPEEEEE0Ep EE`D`EEEEEDEPE E EPE@DDDE`E`E EDDE` EEPEEEEDEDD`E@DEEPED`D`DEE DE@D0ED@D@D`DDEPE@DD DD D ED@EDEDDDD`ED`DDD@DDDD DDDD@D DEED`D`DDDD`DDDDD`DD@DD`DD@D DD DD@DDDDDDDD`D`DDDDD`D@D D`D@D`DD@DDD`D D`DDDDD DDDDD`D`D D@DD@D DDDDDD@DD@DD@DDD DD@DD DDDDD@D@DDDDDDD`D@DD@D`DD D DDDDD@D DD`DDDDD D`D@D`DD DD DDD@DDD DDDDD`DDDDDD DDDDD@D DD`DDDDDD DDD`D`DDD@DDD`DDD DD`DDDDD@DD DD@D@D`D DD`D DDDD DDDDD DDD DD`DDDDDDDD D`DD`DD DD DDDDDDDDDDDDD D@DDDD DDD`DDD D@D@D@DDDD`D D D DDD`D D`DDDDD@DD`DDD@DDDD@DD@DDD DDD`DDDD@DDDDDD`D@DD D DDDD@DD DD@DDD DDDDDDDDD@DDD@{DD@DD`DDD`DDDD DDD@DDDD D@D@DDDDhDDD DDDD DDD`DDDyD@D`D`DDoDjD`DDD`D@D@xDwDDDD~D DDDDDDDD@D`D@DD^DDD{D@D`DDDDqDD@DDDD@`DDDDD@pD`DDCD@D@DDD@aD=D}DDhDoD@lD@}DyDD@D@D D@sD@VDoDkD]DDD{DDoDD D]DKD`D@GDDDDDD^D@6DvDDmD\DXDcDyDDDDjDaD@mD\DDwD@TDTDD{D@gD|DD@DDhD@}D@DpDSD@eDuD`DoDcDdD|DmDeD DdDDDJD;DkDDDDaDuD@DcDyD_DSD@8DDDD@D|D@nDDkDmDVDBDaD@D@|D@eDDuDbDjD@7D@GDuD@KDcD|DFDDsD:D8DIDgDUDlD@[DCDuD6D@DD}DD#D*D*D@JD@gD{DD0D@@DaDJDSDdD@7DhDxD^D\D^DCD@BDZDlD^D@~D@5D\D|DVD@DVD@/D[DODNDeDcDD`DXDD^DqD^D@`DeD5DXDWD8DSDZD@]DQDbDLD@tDgD DGDPD@3DfD[D@GD@LD@SDID@KD,D9D)DSDJD6D@YDeD-DKDQDQDLD[DKD@$DEDDD@UD@,D@FDHDEDhD?D?D(D@,D@*D@8DOD@:D@ DD&DLD2D;DD9D5D@D4D7DPD3DD5DOD@D@DC@D@1D@RD0D@'DFD'D@0DCDED;D@DD0DDD>D@$D#D@MDGD@(DED7D:D@D@4D*DDDD@D@2D@3D.DCLE E0E!E E0E0EEEE E0EEEE@EEE0E!E%EE E`EE EE E EE`EE0EE`EE EEPE`EE EEEPE E EE EE EE@EE E`EE`EE` EEEEPE0E ED@ EE E`EEEPEE E E EEEE` E E EEE EPEEPEEE EEE E EDPE EEEEE E`E EEPEPEE E@EEDEEE EEE@ED@DD`ED EDDEED ED`Ep Ep EED@D@DpE`D@DDED0EE D@DDEEPEDE D@D E DDDE D@DDDEDDE DDDD0E EDDDD`DD`D DD DDDD DD@DDD D`DDDD@DDDDDDD`DEDDD D DDDDD`DD DD@D DDDD DD DDD@DDD DD DD@DD`DD DD@DDDDD`DDD D DDDD D`D@D@DDD@D DD`DD`D@DDDDD DDD DDD DDD DDDDDDD`D@D@DD@DDDDDDDDDDD`DDDDDDDDDD`DD DDDDDDD`DD`DDDD@DDD DDD`D DD DDD D`DDDDDDD@D`D`DDDDDD`D@DDD D DDDDD DD`DDD`DDD D`D`DD`DDD@D@DDD@DDDD@DDDDD`DD@DDDD`D DD`DD@DDDDD`DD`D@D`D`DDDD`DD@DDDDD@D`DD`DD@DDDD@D@D`DDDDDDDDD@D D@DDDD`DD`DDDDD DD@DD`D D@DDDDDDDD`DDD@D`D D`DD@D`D DDDDDDDDD@|DD D D`D DD D`DeDDDD@D`D D DDDxDwDDDDDaDDDDD@D@DD}DDD`D@DDDDD@vDDD{DDDDzD@DkDD@DDD DD D D@D@[DxD@|DD@DDDDDDDD^D`DD|D@DDDD D DD D`DD D@lD`DD@_DDDDD@qD`D@D[D@wDgDDDDDWD]D?D@eDD DD D_DDDdD9DrDD@DqDYD{D DDvDmDUDD DzD@TD`D`DDDUDCD@|D D@zDaDYDiDDlDtDD|DcDD@UD@@D@tDaDjD@kDDDkD`DDWD`D@]DfDgD~D6DD]DDrD@\DjDUDYDIDVDbDND^D@_DsDfD`DADnD@CDXD|DTDnD@8D]D@pDsDfD@FD@XDrD>D@aDBDYDDDdD@XD]D@4DTD[D@=D|DTDfD@}DZDWDZD|D@ADfDIDED\D^DDzDVD0DgD?D)DTDmDDGDRD@BD@UDnD6D@]D@gD{DzD`D@DODvD@mDD-D>D@^DCD@CDlD8D@qDRD@lDlDWD=D@+DqD@lD@HDPD,D:D@=D@}D\D@qD9D@WD DZDDDGDZD@DgD@BD@$D'D@0DND[D:DJDvDLDDNDC@$D|DtDeD5DQDfD@~D@LDDD*DD@GD@zD@lDiD@gDDfDD)DC@DPD5D)D D3D-DDGDD%DDD@DDCiD;DC#DD DDC@.D@xDD)DDDD&D@"D9D*D(D+D D@#DDCC CEPE DDEEEE DEEDPE E@E D E EDD`D D@EDDE`D`DEpE EEEDD DD`E DDEDpE`D@D0ED0EpE0EDD@D@EDDDDDDDDDDDD DPED DDDPED@D@D@DEDDDDD@D`DDDD@DDDDDD`D D`D@D`DDDDDD`D D`DD`DDDD`DDDDD@DDDD@DDD@DD D@DDDD@DDDD`D DDDD DDD D`DD@DDDDD@DDD`DDDDDDD`D`DDD@DDD DD D`DDDDD`D D DD DD@DDD`DDDDD`DDDDDDDDDDD D`DDDD`D`DD`DDDDDDD`DDDDD@DDDDD`DD@D@D D@DD`DDDD DD DDD DD DD D@DD@D`DDDDD@DD`D D@D`DDDD@D D DDD D@DDDDD DDDDDD D@D D@D`DD`DD`DD`DDDD`DDD@DyDDDDDDD`DDDD`DDDD D@DDDD`DD D`D@DDDDD@D@DD D DqDDDD@DD`DDqDD`D@D`DDDzD DDDDVDDDDDDD`DyDnD~DD`DDD@~DD D D`DD DD@D_DD DnDyD DDzD@DD@D`D DsD`D@|D@D@D DDDDDqDD DD|DkDD DDDDjDDxD DDD@uD`D@}DDDDD`DD@lDDcD`DD@DDjDQD`DD`DD@{DqD@NDDDD`DiDJDDID`D`DDD@nDbD2DWDlDDD`DeD{D@D`D@DwDQDUDDaD`DD`DDDDLDuDDD D@wDtDlDzD}D@aDDwDiDPDD_D@qDmDDVDDDyDDDJD_D^D`DbD@_DYDyDXDnD`DrDIDVDD`D@jD&DFD@tD@VDODaD@?D@KD@aDEDFD=DJD\D@1D5DmDJD@eD@SDGD@7D/D7DLDbDnD@ZDQD@YD@cD@lDiD]D[D@DSD@nDeDsDqDRD`DkD@iDcDdDyDiD/D[D@wD@fDHD|D@LD@D@rD@ZDgD@bD@cD@ADnDjD@ZDxD@OD\DPDeDzDDDDfDDD@DC3D@.DC*D@XD@ADMD@(D DD>DND@3D?D@7DDDCCCODDDC@DCDDDUDCC#D5DD@ DCCD)D@7DDCC:DDD DCC'D@ D0D%DCCD D"DDC'D@DCCDCCCCC DCCCDC@DC;DDBD,DCCCCC@D@DCC=DDCDCC@DDC DD@DCCCDCCC@!DD@!DD DD@DCCCD@ DC DDCC DCCC@D@DDD(D&D@'D@DDCD DC@DD0D3D DCCCCC@DC DD@D@DCDC@ DCCCDCCCCCCCCCD@ DCCDCD@D]CC D DDCCCCCC@$DCCCCCCCC@DCC5DDCCeCCCDDD&CeCCCC@D DCDCCDCCD@D D DCDDCCCCCCCCDCC@DCCCbCCC DC@D@DCCCCCCCDDCC@ DCCkCCCCCCCCCCCCCC@DCCCB@BDD@D`DDD DD DDDDDDDDDD DDDD DD DD`DD@DDD D`D D@DD D@DD@DDD D D`D`DD DDDD DDnDDDD DDDD@}DDD DD`DDDDDD@DDD@DD DDeDdD DD@DpDDDD@DDDDD@DD^DD@DDDDD`DD`D@|DDDDD@DDD@DD`DDD`DDDDDDD`DDwDDjDDDDjDDWDD{D`D~D`D`D DyD}D@lDhDlDD DDDDD@cD`DD@DD]D D`DD D[DDTDDDD D@|D@|D{D@QDDD`D_DzD{DsDyD@~DqDtDDD DD@D@QD@oD~DD D}D@gD@TD}D@nD@rDPD@D@]DDDFD4D^D-D{DDRDdDCD@tDKDD\DIDMD@D@\D@pD@GD@gDTD@WDtD`DrD@lDnDHD@JDnDDDWDID`DD}D@VDEDD@fDlD_DcDXD@cD\D DTD@cD]DHDFDLDHD[DMD@RDTDbD_D@~DLDQDED@TD@fD^D@-DD'DCAD5D@6D"D?DHDFD1D@DADD#DKD6DFD.DDCD@ D@DNDFDDDCDDDDD0DDCCD@3DDD@3D@"D@D@/DD@DDCDDDCCCDC%DMDFD$DCD@DDD)DDDCCC3D@3DTDDCCD&DCDD&D DCCC D%D,DC DDFDKDC DCCCOD@DCDDD[DCCD2DCC@$DCC DCDDC'DDCCC:D DCCCCC DC@DC@DD*DDDCD1D@DCCCCCD3DCDDCDCC DCC DDCCnCC DD)D@CDDC@DCCZD+DCCCC@7DCCD@ DDCCC D D@DDDDCCCCDCCDC&DCCCCC$DDCCCD@DCCC=CCDD@3D@]DKDFDOD@YDKD@SD+DXD@XDD@D1DHDpD@UD2D@5D;D%D@DLDlD@D'DkD:DRD.DD2DDD@D@/DD@/DC\DD@DDND@!D@QD$DD4DLD"D)D@#D@=DKD;D@DDHD-D@YDDD@1DD@D@4DDZDAD0D-D.D.D DCCAD>D@MD?D DD@3D(D.DDD7D@ DDD@&D-D/D@uDZD&DC DFD@0DDC+D.D DC@DD?DDCaD1DD)DD DDDC-DD D@DC D'D#DC@GD:D"D=D0D'D DD@D=D@!DD@%D DC;DDD@DCD@ DD@D@EDD@DDD@DDLDDCDCDCCDD.D-DDCSDDDDCC@DC D@6D DC-D@DDD#DDDD DD@D'DDC@DDD@DRDDCCCnCDCD@/DDCCCC'D@DCDDD DC D@ DCCCC@D@DCCDCC DC D@DCCCCC DCC#DCCCCC@DCCC)D DCC@DCCD*D%DCDC@DCC@+DDD DCCDCDDADCC@#DCC@$DCCCCCCC@DCD@DDCC@DCDCCC@ DDCDWCCDCDC DCCCC DCCCCC DCCCCCCDCCCCC@DCCC D@DDCCKCCC@ DCCCCCCCCDCCDCDCCCCCDCCCCCCCDDCCCCC@D DDCCDDCCYCCCCCCCCCCCC"DCCCCCCCzCCCCCCCCCCDCCCQCCCCC@#DDCxCCCCCCCCCCCCCCCCCCCCCC\BCCCCCJCCDC]CC@DkC^CCC[CCCCSCdCCCCC@D DCCQCCCcCCCCfCCCCC@CCVCC^CfC@BZCC|CC CHCCCCqCDCCC|C@CFCXCCCCCCCCCBCrCCCCCC2CUCCnCCCCCCCmCCCCCB]CC@DCWCPCCCCCDCCCCyC(CCCCCCdCBCBhCCCwCCCCCC}CCCCCkCZCCXCzCCC8CCCNCCCCCCCCuCRC0B CBCC7CCCCCC;CtBCCCC'CCoCyCCCCCCrCCdCC\CPCBCBCC\CBCCCCsCCBBWCCcCCCCCCZCCLBvCCCECBtBxBCCCZCCBCC3C(BCCC+C?C@.CCB-CRCCBCCCJChCCC;CeCBHC(BCCxCC\CCCxBpAChCCC.CCqC CBCCBCBCCCsCCCCBBB4BCCC'CCCCrCC BMCYCCBCZCpCCSCCCC0ACBKCC3CBqC=CCC)CBBBCGCC CB{CCCtCBB@AlCCCnCEC6CCCBBKCBCZCCCC;CCCBBCA jCCC[COC;CBwCVCCbCBA@CHCBgC0CB_CCqCBBBTB\BBC@DCWDDCCCCD@DC DCCC@ DCCCCCDDCCDCDCDCJCC@D@ DDCDC@:DCCCCD*DDDDCCDCDDCCCCC&DCCC DDCCCCCC@ D@"DCCC DCCCDCC@ DDbCCCDDCCCCCCCDDCCCCDDDCCCCCCC@DCCCC~CCDD@D2CCCCCDCCCCCCCCDCCCCC"D$D@ DC/CDCCCiCCCCCD'DCCpCCCCCCDCCCCCCCCCCCCCCC4CCDCCCCCCCCCyCCCCCDC6CCC@DCBCCbCCCCCCCpCCCCCCCCC[CCXCCCCCCCCCCCCCCCCCCCZCCCCCCCCCCCCCCCCCCCCtBCCCCCCCCCCDCCC1CCCNCCCCCC'CCCCC(CCCCCC5CBCoCCCxCC4CCCC5CCCCC|CCCBCCCCB@C3CdCdCCBtCCsCCA{CC C(CCCC|B AHBCCwCCCCCCCCBCCCwCBCCCCBNCCCCBCCCCCC$CBvCCCCCCCB.CCCCcCUCC+CcCCsCCZC)C?CCCBzCBvCCC3CCzCCC6CCECCCCCCACkCaCCkCCBBCCCCCCBXCCCCCC?CZC%CCeCSC+CC CCwCCC9CCCBQCC CCCCCBCqC4CICCCLCBaCCC"CCCCCCBTC,CCCC\BC&C:C5CCB$CcCCCBBACCsCC8CBCQCCCCCCCCC@ CkCCCC`C,CC5C0C(CSCCCVCCC,)C%CACCuCC_CaCbC1CYCCCCACIC=C2CCChCCCBCBmC&C2CAC?CFCBaCdCCBXC{C)CBCeCHCBPABdCCzCXCCCCCCBCvCJCCdB#CCBHBBKC;CCECCrCBCBPA@BC*CBCHCCBBCoCCCCBCCwC#CCCMCACBBsCCA\BLCC1C,C{CCCB6CBhCyCCCCpA@?CCCBCCoCECAFCC A!CCxC9C"CC|BCC,C CB BLXBCCChCgCBB CBCOCOCCjCBmCCBC@ BBhBBBhBBSCqCcCB_C6CB BBB]C*CCtCB"C CBB/C(CBCCBBCCBCC_CCYCCC{CClCCDCClCoCCC>CCDNCeCCJCCCCCC~ChCC9CCCC{CCCCCCBCC6CCCCCBhCCCbCCB[CsCjCBCBCNCC CC\CCC`CC7CBCCCCACCqC CC CB4CBCB"CBCCCClBxCC}CCXCACB1CC BCCCLCiCBdBBCCCWCBCHCwCBCC,CTCBpCCwCCVCCcCCuCBCB8B?C}C@DgChBC>CCuC CBoCCC1CACtBRCCMCDBCB`CCkCB.CvCCCBBB BBCCCzCCCCCBATCzCCCBCKCBC5CBHC+C`CZCBBBBPBCBiCC]CACCBBkC)CCB`BZCCCCgCBCBOCVCBCCCBBAByCBXBM0AA`C7CCBB 4BBCdB#CBB7C@BBCBB(BBMC CCBACC}CXCBtwCBSCBCBABCBCBC:C CBB#CBIC(BBCoCBCBpB@BmCzCCRCABBVCxCXBB@@CCwChBCXBBCYCB rCBCBCABCBCCCCCCCCBCkCBCTCClCBBCCCeC}CCCoCBBCCCACCQC6CCCCCCPC:C CCZC CCCCCCC{CTBCCCBCCC}CCCQCCC-C>CPADDCCCCsC"CBCCYC"CBCFCJCCCCBkCCCOC'CCCCCCCBBCCCC CwCBBACBCCCCBA~CCCCCVCCCCCB8CCRC_CP]CCCCCBCzCBPC8C4CCVC"C8CC/CCB&C BBCCCCrCACBTCChCQCPBBBCCBABC2CCCC`pBBCgC[CCIC:CCC"CCBVCCChBBC C@BClBCC`BBYCBBCCBCCfCZC?CBjC]CCC CCCCCCCCCBA8CCOCA C"CCCCVC_CB CnCB7C8B^C[CBCxBaCxCCCCBICC$CQCBBxBOC!CCB-C CB*CCBG CBBBBCCAC}CA#CCCCB\BCCC\C$BAB1CCABBCCsC/CBC CB'CCC\CBBCaCXBBCLC@CB CB$CBBCCCBACgCBuCBUC:CC@A C.CSCBCATCCA9CCCCgCBdBpCCBYCB,CBC*CCCBBBB CeCC$C8BMCCCB7CCwCBBCCCpCBCCCBCLB4BBBgCgCCCB_CSC>CBT\LTCC!CDCCeCCtCC`BB CCFCECBBCtBA+CBpB7C/C4CyCICBBPAC"CCYCnC-C?CCLB(B%CBBCMCcCBCC3C(BBBcC'CBHBCB4BABBCJC@BCBHCCCB CAB CC^CaCLCB`ABB B,B8B3CBBB CClCSCBBBCCACBC3CBCCCCtBBCBBBpA8BCBAB CB^CAeCCpCdCBBhB AB/CCCC?*CoC;CBhB8BA`B?< 9CBBCC@eCBAlBBTBBvCMCA@B BChC\BCB4C,BDB< B>CiCHCBBTC9CbC}CB|BB2C]CCbC@CCBC@BCACA$BCBBBBBBBCB2CP BtBBAABtC)CCC"C?HBqCCBYC/CBpABPCeCcCtBp@@9CBB~CBBBCSCClBCCBAC CB9CpBB$BABCCBC_C CB A CBBp!C[CBBCH{C$BACCBBBBCCCCTCB,C CBCCKCXCCbC@'pCB:C9C4BBB7CB CACCJCBC4BCBBPBZCBBbCCOC,CC CCCBCC0CC4C^CCrCCCIC"CBABCCB;C%CBCC,CrCBBByC5CMC#C4C0BBBmCCCfCDCCCLBB%C6CCBB{CBCCAdCVCVC0CCC?CpCB@ClC[CBCCC)CBBCCtBC0B@CBMCBC2CCRC-CrCBC C@ACdC'CCCC-CCCCCLCBC`CBXBC6CC8C5CfC3C\CC(B!CCCB B ACCCCCCBBCwC0C C@BcCECBCB*CABvCOCBBBB=C\BpCB ACyCC;C'C0CDCBgCBBBCpB`BBPACB"C#CBBTB@B@BACCBC@hClB]CBLB(BB)CCBBCCyCRCHABBBCB$BBCICA ]CBA C ChC>CB0A?BtB?BB@@PADBBCC@WCDCCxBBPBB C C C0BAA CBdCCXBB@BBGC>CrCC4BB=CAlB$ CpCBxBBZCCpCBHCBt<BBFCB BCB8BC CB`BBBB0AlC`CCC(C@%CCMCFCCBBBC)C/CCCBBCOCC8CBC B:CCCC-CBB,CxBBB#CCDCABICCZC0C?C"CCCBCiCAACBA@CCCCCC]CBBBB0BA+CATBBCBC|BB`BBoCACB!CCNCCBDC\BTBBNCxC C CIC5CCA_C?CPC@BBBB-CCBBVCtBUCxC0BC_CAB)CCBA$BB,ACcC@CAC@@BWCBBBCCC B0CBBCCMC4CDBBBBxCXCB4B8B(CCBBCbCBCOC(CBBACCB8C,BC=CB$LCcC/CBBBBBA CBBpB$CBAJCICBBCiCCCBC(CXACCcCCAPBBDBBCB4CCdCCC;C&CTCC1CBBUCBB C(BB CCBCBBBBX(BdBBMC$fCCJCB0kCBB+C@CMC,CB)CBB5C(B`BPCBD$B_CCC8BKCCCA| CBCCSCXB BtBC,@@CBdCACCBXC(CBC+CB#CA>C$CcC8CpBBCCBC'C,BDB:KCCeCBBwCxB?CBCCBJCBxBBBXC-C@@C8CBUCC#C CxBB8C CBCB@\TaCrC\BHzCBBCDBACC+CB[CB.CNCBBCACC B $BC\CA9XBA]CCC-PBXCC(BAB2CCBBxBABB BB8BC1CB8B(BA$CB7CBTCCcCA -CCCCkCxAJCYCBBNCCC`BCBABBBECCCC#CpB JCB%CpdpB;CBPBC0AC8C.CBB$CLBBBBBHCBAA@pBC$CBCBB?\BHBC4B :BxB|BCCTBXBrCx@BD)CBTCCCdBpBC1CB!CB@@BB4B/CB2CB|C C,@B>CXB`BB@BCCC@B BCRC}C4CB7CDBAB?XBCBBACAXABPCB$B B B0BBBBC@gC CCBtBBPABBBBAC/CABBNCBCCBCCBBBABCC8C&,CCHC>CBCzCAABBCCCBBA9CCCE/CBB<NC??BCBBBBBBBB\BC!C CB`C|BA CB@B $CA7ClBpAB)CLBiC@AECBpAAHBCx `PCHCCBCAB4BXB`C(BABCBBbCBEC,:CA$CCBCBpxCA0BCCwCB|BnCC!CtBBCCBBCBCBDCBBBpCC4C0ARCDB0ABMC;CCBBAC`CaCCrC@CBCtBB `CCCCBCBB+BCB$B @BB?7C7C,BdB%CBPABBBB=CH(BCBBBC CB@BB$BA$BuCBB$B!CC~CYCBd@ACCOC`BDBx@XCBxB|C;CxB@CTCBl%%CBABAA`BB!CBBCCQCBC-C@BBHCdC8CtB`ACB@C|BJC2CBCLBABCCC5CB-C,CBHBABCLB&CXBBBBB0BoCuCXBBB0BxBCBBCCC&CmCpCC C!C$C8BB0AB@ CB`ABPC9CBTB$BCpBB/C8B4BCBxBBBCBC>C @CBBBABpBBCABB8\BC\4BCBBHCBBBLB BB?5CVCcCBCBBB,AgC@CCB<'BpCC C`AABdAB(@BXCBB @@3ClBCBB@B@@B@CB`0BAP|B<C'CBBCBAS BB CC}CCABtC2CX`5CC"C@@ABBC`B4BBBBoC(BA@AlBB:CBP7BBC@C$BBBBCBABCCBdBBBB@BBABrCBJC.CAB~CB$BBCBCCB0ACCACBCLC0C@BB\BpB BYCBxCDApBACXBPBBB$CAB@@ /C?CBAB B AB%C4BCB@BdgCpBZCCB=CCBBaCLCABC[CPABEC]CBB`ACBAaCBBBQC CCB@A8C`BBCBTAB#CBUC(BCB C@B`A@0B|BBCjC5C^CBB CPAC CiC&CABCAH#CB4CB@ABC0CBAdB@@yCECB|BB@B CCBCCABBBB(B CB:ClBB`AB'CCB,xBhBCBSCB.CB CBBABB8CCBBtB C@B@A8BBA CB ]C5CJCC`BBRCBBAHCAC?@PB B{LB@B+CB/CB+C]CC,B?$B0L4BBCAABjCBAA@ (CeC$CA@B0AcCB`ACBBfC@PAC`ANC>C0A4BC%TBCCHBCBCA@@hB4BBBB'CBtBLB$BAABAfCA@TB`ACBCC0@P CKCCCA`ABBBBOCC$C[CpAIC CIzCBBBB+CBCC% AhTBBCHB`BCBABA4C"CC|BtBMCC C7CCCL@BBAW.C$C7C$CCC`AB5C?[CCB4BBlBpABDCALCApA4BB(BBCABhC,BBdBBC C^ChB;CCCBB-CCB",AtB C8B@PBBB6C$BB@CBxMCVCB<8BB<XpBC\BCLBp B(CBCBB@TB'CAICBBTB%CB`AC PCA@Bh8CAB Bp BBCNCB#C4C`BB CB(BB@AABCBlCSCxBBBBB,BBPBBx0AlAD,BbCBlHBPC4BpA0ACAB0@BB"CB>B$B2CCB PAB!CA7C4?##CA<BCB>0CdBBtBBWChBtC=CABt0CBPBtAPC@BBC7CB[C CTB$/BoCCA?TBpBQCA/BC@ BABBALBPjCC?B|BCCCCBAPBPCB@'BCCC@BBXB@BPBBBBDCBC CBBBA?,ABCLC+CBB,BBQCBCCABBTBC@A@`BC@CCTCB@D9C`ADB,BBTBdB$B9.C8CBCBP=B;xB|BC1 OCB.CEBBHCCBABC@0HpB-ChBB BtAABcC$?@hB2CTB CB@B`ABBB@BXBBHC CBBC#CTBA@LBC(B8 CnCABBpABBPA CBmCA@BBB@NCA BC6CCPB@%C BpABB&Ch`ABABf@BB&xBd BtBB BDtCFCBHC CEKA?cCA2BBBAPBp8BBA0WPBBpBBgBDBLPB@BLBPBCBpACB`B CB<@CA$BPBB6dSCPABBdBFCBBBABHC"CBBCPBBB.`AhBC hBtCB>CCCh,BBLBABB`B@ABA@BBpAATCBACBB$BFCA$ ABCBBB@HBBAB=CBBXCFCDBBp|BB@BB]CB&C1CAh(B)CfC\BB,BCCXBABBlBtBlBDB"ChBBBxBCBc?AABAHC[CB,BB@BB? BpAJB$BPAC_CT@CBCBdlBpAB$CPABKCAdB2CBBABBAAAXCCAI&CBCBBB= BBBBABBBCBA@C`XBBBCAB&C(@AA0ABBhBBBB CBCBB4 BBHBxCB`BBAB``Bt CB>NCCDB-CCBBYCBB1C`A,BDBCB^CPBB BmC@BBB@4BBABCB C1CB|BPABAAAC9Cp@\BBCBABB!LBCCxBCBC~CECB@B\BOCaCVCABBHAc`ABC BBBBAtBVB|BC|B:CBICBB%BtXBBBDB lXBBBBBBPLiCNC BjC@ABPCABpC`B?CC@YA@B@6AA7CBB<B$B0AB@8BBBBA(BBCx BB BXBB!C,BBC@B@ C$BBBHBBTBBBACDCBZ @A?@@BCAB\BALBBBAB0ADhkC C`B.pCBwC0B BA@ pBABCBp?8LBOCFC$BlBCAC1`($BPBtB@AHB@@BxdBBCdB@ABBC@@'CCTBBA0A BB0A@BCBBPA@B0CAd+ABCA$BAD`CBBB"B AtC,{CSC0CBB0AAhCA@)(}CA(BBPAAPA AB'CBB@CC0BA:@BCHBBB C0B!C@BBBBjCKCB)pB+CB8AcCwC`A0BPC@@BCCBpABA8B"BB0B@@A BBBBBB`AB@;CKCXB]C:CBB@B $ B BBA 0A-CBxBt1C&C0 BB(CC0ABCBBBABxAB@BDBdBpBBBAA`vCCBB\B8L ACBABLC(BABCC-E PABCB1?CCBAB@BB7xB3CA@ BCB@FCCdBXpB\AA@\B CBP HC? BCBBB0B B@@JCCBAhBhCCBYCAHB|BCBBABppAOCB\4BBBlBBBB A4BB(A`ALBCB|c#CBAxBB$lAB3ABtCBBAB@BB@@`BBB CAAAC BpAB@(BhBSCBBA'BB8BAAByCBCB Bl!C-(B BB@@@AC4 BBLBpBBB5CTBB8 A CMCcCBBADBBBCBBBBdCHBBIC:CB6P BCTB C@@A$'CGCBB0GC<BCxBCB$dBB'CECCBBBxBB:CBBBC|B2B`BBDBBA$B CD)CaCCCBCPAB<BQCBT,BxB|BCBpDBB5ACAB#CAABAC C0T(0 BBB;CBg CCA C(B BBBNABABx+BB*CB@@BO4BA(C`BA|B CB@A&CpAB &TB\BB CBCBBA`BRCLB.CLBB5CB5CaCpBA@ApAB@`BCB+@FABPACBCCxB&CCB@ABB0CBBiCAC0 ;A_CDC BB? @CxC7C0BBBAZC$CCBP#CBB B'ACxBB ABBC$A,BBBABB CClC0PB-C4B4@pBBC@CA= AA#=B\BBC(BBBBBVCCS;CxBB%CpA$3BX$B BBGCBB$CB@@`<B7CB`AAAABL0BB C[CBTBxLB@BBB(BBxBA\BYBBBDBBBBB| B C0BA$wA`BAB BC$CBB&`MCBBhCBBBB8C BX$CTBUC<C\BLCC=CB$oCQp@@ A0A6CABBBxBBAPBBA BVCXBB(BB@P,B@FBPC`BXBYCXBB@B nBBADB!CnCBCB@ ABP8BA$BAPB@CBB-,BABClBB|B@hB0AlBhHBBQC@YdBB@4C\B C;@@" BBC\BCBBBAHCCAt ABCB C(BBP0HBABPBLB#AChCBBC/B!C$lBSCLB]BLlBC@CBBpA|B0AAAB0ABBB0ABBAA@BtBBB@@5CB6C@BCBAABHBC,B8 $4CBBB ABpB8CA0B`8@@AC~C@* AB3C CAB(BCBGBDhBAAdB8BUCXBpBAHCCB8BA@@B|AxBB CBBCCAA0A C&CBxBABHB$BLAAA0"CB8BApBLBdBB@AClBA2CBB`BBC C CcCBBABtBCAMCAphB`BeCAATBixBABB,BBtpB@0B(C,CCA$B A4BAB@ABB,A8BpA AFCB@'CAmC?C@B0BAABBB4MBA$AB0CpA@BhDBCBBCPC`B1OClB BJCBCB C B @AA.CB@"ACAxPBLABKCC@BB CDC CBBAYCC ECAzClB0BLCPAB0ACBB$BXdp,CBh @BB5 CNC@BPH@ABtBC80BFCB C!\C ABBA@0BBC,BBAhCBHB3C 1CCbCt BdB@B,CCB@hB(TCCB@BtA(BBBLtBC@ACA0BBBxCC/(BSC C0o @CBB0AtBICBCCACABAC#CBCBdB DBBB,BCBB`BxGC Ah$BBBB?(CBBPAP.CDPAB:C(BBtB*CG|B0CBXB@h B"ChB4BBhB@@AB@HBAAB]C@BB-C0 CBB)0B$B CBBB BBABBA$BpBHCLChBBlBB@d-\BB`@B CBBPeB`BpBA@ C B(BBA@=C@@BAC C^CBLBACBBBhB@5CfC@B@BCA`AB0B`ABBVCBApBBOCBBB4B1C"CBBCBALBC$B{CBB8YCQCB?C&BBCBACCdB$BBB#C BCC.2BUC@8ptBCXAbCB?DC|C ABBl|AAC CABxCX A@AA7ChBx CWC@,BlACBAA8ClCB @PB CBDBA0B1d\B@CBDBA@ACB\BEC@@GCBAHC@C)CB DBAC@A)CHBhB\C<A`A CCVCBAB7c@ABB@-BUCB|C@A$B H80@CCX,C BHBCpBpAB6CB o<BCCfC%CAAXBCB6CB B1CpBB$BACSBA/CuliCA5$0AC`<B%0BXBBBB#QCBBBPACJCBBOCd"BpB`C#LB@XC`A0B CB0LBCCk@BhBCBxBAA,BB*BLBBBlBBCCTBTBBC2CBBB *CBABAp*CC(@@BCBBz0$C0B@@BBBBBlBAC(@@BBpBHAB,BAABC AA$BBBBB`ABECABB0CAkABBBCBZCTBBdBBBCABBCA CAAHB.CvCAAC@fC B@ABCMC4CQBpA(BHBBBACCBB tCABBABA| CB $lBB-CC<$)CB CPA C+CC8BB7C BBTC0ABPB,BTBBAB`BCBA@ABB@ C*CBB@B@ABdCHdBBAC%B{C4BT|B\hBzCCC BBtBTC\ATCCBBBB`B@k@BBBBC@BB|EC8B CC8BT B@A?CBBAB8PpABBCAAdKCACBCxCB~3CCB8BAbCBT$BCAKFCCCC4C@BXA BCPBBCAB` B=CA"C4CmCBB/C:A@@B``+CAC1CABBBXCECCBAB;ZCB ABLC$BA C cABkC}CBE*<Bl@9#BBBpBBB BBPB?B0@BXCdB\BC| B0CLB8BB"CB;CBB0BpBBAA^B0B(BBBBB@$BABAB@A`BBAC@A$C-C0\B,LBHBhBCAB1CBB A A PBCBTEC!B.C0BBBCBBBhB B8$wCTBtBBB AA Bh CXB4BBH8KCBBA4CB C AC`BBC|BBlBB BB8BLBpB(BXBxBBCA4BCBBBBA@ABh,BBA@B+C`B0BBA0DBBBB<B0AA4B@CDB`BOB0BBDCAAB4C4B8BBBBAB|BBB\B AXBGCC@HA@@B`BtBBPC0B4AC*CDBnCB0BBBALABC&C-$BB`C CH$B [CTB@ BBiCAB@@CCBtBCB,BoCBpADACBCdBCAlBBB@ CCBBXC+6 CVCCB@BwCBP4\BBXB@& BCB@<#%CBtC@PACBABBBCC8CB#C`BBBPB@B,B(5CxCCA?ATBI CUCXB,BTB@/CA$tBBC4V@,TC_CApAAZCBPBBBB`BBHAB0AB`C'ChBBCCA4BACC\C CwCQ0BHBCCBA1CdB`BCBA|CLC`B4@dC$B|BBhBWCF@BCt BBBCHAA@A@CBP CBBBC _(CBpABAy4BPA@@BABC8BBBACBB!CB C(BC|B@B8BBBBAC2BBB8BB@@ABpBPA BBBB`ABABB.CBCC@CJCA@C(BXCBt/CBBB;CBBBBhBX0AABCBBPT#,BBBBAB@,B\pBBBB#C CA4"C@ACBXBLB@CfC BBBBC p@oCB0BBB AB$fB_CBCdB@(C@BKCB BB@PBCGCBDBB<CYCkC4hBBB(BCB@LC CBB4BB2C5C HBBBBB ApBLBCBfAhB AB,BBC0B@xBCAFDBB,BBzdBACCBHB" C|PA BC0AB,CB\AB`B`DBB CBBnBVxBdBAAXBCBO@TC8B ApHBBA\CB@4BTAHBXBAAC0CB' ,BBBAAPBB,ZCB BACAC@ByCCA`ACCCB`ppBPPpC C CBx p\,BBMCP`ABB(BDCB3=BCaC CAHACBC'C0BCB(TBCB/C,B(BpBrC48BACBBB!CpA :$? xBRCcCBPB$BDCBB$B(CAlBxBCB(tTBBQC@`BtB3C4CB@@0BCB|BdBBBB A@BCChHPACABCLCBLBCA"CpA? PA'C(B]C CBABB(BC`B#ClBhAPBkCBTBC:C4BB*CxBA8B0Bl`B0B@@,B,4AICC8BBdBA0BBWB BCCCBA@BB@BDC@@@B<LB@@B5C@C?ChBABBBBBCA CTB4BA8?CzC@AGCdLdzC)C(BC0BABAxh0C0BC@C|CDC\BJBA@ CBFA8 BtBA@6CB@ @AB@B\B)CBTHByCCYCCA B?C CH0BTB BA7AB$BgC@BAC!C(Cp&CBCdB BCxBBBp CTB pBBCB@AB@BB\BBH8B@BBAHACC@ABpBALB @@BBBH0BA,CBA@BCABPATB0BpABRCABB;CLBB pBB1C@@BBTB|B0AB8BCB<BKCzC(CS BxBB1C\CLPABBAC BB)CBPABAUC CBB@lBIB(B4BB BBBBCBoA-C$CBBKC @FCC B`AA$B0B|B;BCB0ABxBCAB,AACBBOCLPAAPBB@@@BCBT BhCC4CptB0AxB?'BABBC ADB CP BBBBBBB (B@CBBA(BBB4CCTBB P@ C@BBLBCICB BHBBTABTBBBdBB\SAB4B\ATADB0VBX|@Ap @A$RC<BBCBBB@AA?C CBBBiA0pBBABBBlCCBChCC2C(A`ABBLBABBp,BVCB (lC@(AABBACfCBP,BBCBCHB. BBpC#CXBpA@tBBBB@,PBA-C0B@ApAwC.CXBPA9CBCUCB HBCC'C,B CC Ae B$$BA(BA0C BfBBBBHB UCBBACC4BBFBtCBJ CPBBBHC C(BBB 8CBBTBBBA$B@@kB\C AB<A%CBBdB CBBH CPA(XBBAQCyGBXBtBABBA0BAjC-CBC(BB BBp+BB`BCCLBL@lB%C?BxBAlBhB0(4BBBAA,LBBCpA@BCCT0B`AR@TCHBB@XCCBLB,C@B8BB(B$B@BB APB BB9CABBB@@EhCCB^-LBBHCAp8BB @B8B C0CBApATBBB;C`,pBVCpBDB(\5CBxBBBBBBTBBgC'jC@@xBABABB@C9CoC B@@tBB$BBBCJCPB$B`CCECCAB#@ACC,@PB(C!CKCAAAPAABLBPpAh BRCB-CB0?BTBBABtCC@AB8BCBXBB`BC|Cl%AyCCBBT`ApB@BBzCd0A'CC0BB@8BBE(@ WCB=CC)CB@B HB0B C\BBRC AAA4B\PB2CBACxBA@BPCBj?lB_CBCABltBfCB&C\B CBABB@B BB:CA'0BCB0C=C]C0AQC\B AtCP B\BB@PACABlBABA0BBBB@ABkCB ?BBDBB|BPAA C/B@$B4BBA\B%B C*8BICB C`AABBBPBBPA@BCqC]C[BB(CC64B:B,< CA BBXB-<,B`ABaBB0CB@ABCC BN4 CCCBAXBBABBCX ABB@BAB4BCA9CB$Cl ApB*CB@A@BhC`ACBlBBtBC@dC[CC@ @ CCZChB\BFBCAAB C|BBBCBBAB0B A"ACd@@0BLB`A@A!CB:CBBBdBaBC@@BCBCCCCBLtBCCHx dtCCCBBq@` B CUC4BCLxBPB?CC2CBlBBXBB%CBCAB0A@?C}C@AAB C|B|B3CWC(C@PtBBSCTCA B<BC!CxpAB0CB>CBtBBlB3CAACAB`CC@BB CBCPB 0CB`CA@@lBBlCHB8@@BB@COCBB@@B C AD#CmCLBBA*CA@l0 &C\BBABBhBXB@BB B7C@AC*CBB_C$BB$CdCBB-AA` \BxB!C'CBBBTBBBHBC BbCB8bBBBPBEC?CBCCTbAC[CCB<A|BB4BBBmCB`ABA BBBlBCB|@0CB>CBTBABpCCA\B@ BBBCBBT AhBPBBAPA(CUC@1(BBHB$CBB*C@:CABBBhB ACC CBCB BA AB CA CdBCCl@$CCCB`BpAP8BDBBpBp CBhBC,6@|BB@B`BBC<lHBEC0C ABB|B$0AP#< BBCCB@A*C@lBBBvCx@BABtB(BCMCBBB,BBB5CD B C>C!CBl8ACCLB`BCB|BBpAdAAhB<BB1BCA]CdBhBBC0ABhCtBBA ABBBB,BABhBYCIC>BpBTAAHBABlBTBAC@BBBC-C@PABTBBCBD@B`ACBCAA A0CBBBAA4CWC"CBBBaCIBB ACTBAl<CJCCAB CpABVCBBPBC50@BBLCB A? BXB$BpA;A+AB8B!CBTB?;\BC"[CB C4BA0BD1C@@@B CBBB~dB=CB8CBpRC3CB\B0BBBB@@BB`AABCVCDB9C\yC?B|BBPBTBWDB@(C(0B8BtD AA CBB-CB8CTBA|BBBBC0A B$ATB(BC]C0AB8B$C@ CBBP8BCxTb*B$B$/ BBCC?LBPAABBb BtBBBPB %CC@0B$B'C@$lA<CB(B@A@BBpAC44PA BBG<BAC CCBhAB BCAb8C BCCLAAB Ap@@ AB@tBCC0AB3~B#C6B4B8BPB dB@ jECTBB@AAB !CBCBB@BQAAABCAjBABBBlBJC@ B@CBBBCyB|pBBDB ClBMCBARBHC+CB BC BBB!CCBB@TBB@BA$XBCC ANLBDA{CB0ABqCB@0B@@B,Cp*AMC C9CCY|B_ICB0ABPBBBBC`7\(CBCA@DB@oC8B BtBAB@B<BY40BAAC$BAB"CA@BBBK$BBBP`AC@@(dCBBC B@|B CA?C\AB AA8CAd@B CkCTACCtPAJC8}BA8Bl.CLBhBBALB&CBPBBdBCBCB0BABAC?CC CBqBBPBBBEC3C4B#C>C`ABB dBAS,>CBCOC@ B70'CCXBCAIC;a9CBCEBCCC01?B_BAB5pBCAC&C@:BAAACE`BCCB@CaCA[C!@pACB4BCA@PA4BCxB@BB`ABBAB CA\HBBBLBC!CBDB~CACCBZ!|BBtB_CAB+CBABPAL\HBRB@BCCB`TB*BAAB0AABA4BBgCBtBA4BApLBC,CtB:CCAICBACBC RCCB0A@A@@BB@1@@BO B ABOCpBCC A -CBC@@A5C3CCBH@B@4CBCZCBFCB A< AB,AjCBBA6CCH B!CCAAB,BBPCBFC B3C0`AChB3C>8B2ClBBB?BBB8_+B&C`BzBCAB C NClBBAxB@>CB@A/CL4BdBBhBXB@C08BC@CpAEBBBB$0AB4B@C BCBA^@`B?CQChCBA CTBBAB`ABqA C3CCCBB@lBCB( P,C$CZBB+JCHCH CpCABB\BBBBt@A`AAB CA(CBB@fABBPAA\>BB@BBB@C-,BCCpABA?BBACBA?BHBA8%CC@(=CBABG\BBABxMCBCeBB$BBLBoCB @0B$CGC0&ICBAMX<CSCxB@B:$p7CRCB|B`ABAeCB\?DB.C~C0BTAA@(AABBBB@40ABBB @B`B $BSBBNCzCAB%CBx\BjBBAzABBBB`A0AC|p`CBBtB CC CBxCuC? C(LyD,CUC(C@DBBpCB@4BCBB9C BA4BBLB!PA@APB C@|AAB0CB CBE B0CtB8B LBDBCBB'CABBBB4BhhCB3C(Dp=BPBC%0AtlC\Cf B@BCCBCBA\BCBBBB4CBAB\B:C@B CBC@oh;t`lA?C/CBCICB BBBPB2CCFdCTgCyCB#CCBB B)B7CCCo CBB@BB0B@BBB,CIC0BC8BpA|C)C0LBBBlB|B"CA0@@lCB4BC5C7CBBB0CC=B@@AAPxB$BC5CI$CCBdA>4XBB BBsB<KA8pBB;B0BO#hB\dBOB@LAAAPBB`PC@80BTBP CXPBB BCABEAB<,@CA@ CZC(B C@BB`AABW-B,BCBB_0|BbBBB%qCB@BvCpAABCA?CKB@pATB BBBYAB$CjBBZBBBBB@`CBhBCMCBXB CHA"CT\4B9CBH8BBB`C|B`Bh C@B{BCECA(`BCBA`A@@A$BAAhB(BhB7CB8BB'BpBCB=h`A@BhB`CA%'CB?BB 'C`BABC@TBkCCBBTBxBFddCBB AC @Bq4BABC0Ap@BB%B(BB%CB,BBBCpZC(B d`BkB`MRCB$B1BT]CvC`"CBLBBB7?8BT..CBBB@AHDCBB&C@@B[CB"CBBC;CD@BBA@BB8C`BPAB C C7B+CP)CPA A$ BCH@A BCACrCtTC<BPA&CB8CA B;CAB$BBPB`B@LBBA@BpAAPBA0BBBBBB2B3`BBBBhB>%BCdBBCyAB@A|B?LBCB@CUC@BCALC,B@nCB8CQC BBB CDBKCB\dBP,BBCB0BAABB+C,BtCCBAC$CBBCB@BppBBBB `A?XC@LBBB|`J8BBD@ABAmCtBA0+CpB@@8BVC80B<2ChB`-C"C %CB@BA(B pBC3Cz|AA@8CB (B`B|BABH`BDBDBBBApABB$BBXBHBA5CCC?BBX0{SC0A@]CBBAB,BB#@CCACBLBBJCBBBpPABpBBt0BCBppABuCA@hB\C0CANpB0lBCBBLBBp TB0`B\BBDCHBRB B=CBtBBBA&C$CBCtCGB4B`BBBC|C`Bd/ pABCB+"@@BDBq B$BBB@AB@B,Cx]B8BBT @BBBBCCTB/pBCB@CB@@@(p4A!-CBB@XB&BTBYAEAAAC5CFAC7#CB@BBDBC C0BBXB`BB*CBA^CBBHBTB@@CCBqTAdKCB@B)(BB A@BBBB!CBBBAdBB:@LBBtB CBB@=CBXBCECCBAFBBBwCB@(lxB,4ClBB@@BB@CBX BABlBBCB@H,B|BBB CCB4B4CAxBC ABXCB BBBdC<AHAlBBAA2P DB4xBBCB|0BB BBC= ACD0@LICAeCBACC,BCtBB0B<#CCDB4BBC`CCA(BBBCX,CC|BRCBAB6BCABLBhpBB @ARCGC$BA C@0B(BDB`ABl8CPA`C(CAB@@<D9CCBB#@A$ B@HBBABA|BBBB(BA`CBCCBBBBAA@AB!C A&BA4C(B7C\BB B@@BgCB_CB@A@ B@C|BBA8GCB<CBCBACZCBB\BBB!4BpCC$@BdLAAp8C@C,BBCC(BICAb?CCTBBBC@|BBB@@@ C)C4B[CBB L\jA8BCHBBBACAB C@*4BCBC@@0BA*CB`BAtA;BC\B@A0LpBBA@BpAA B@CBBBp@BsCBLBzCB@ABXNDBbCB BB@|BB\BB \\ BAAC`IBBBBBBCl|BBJPBBCxBBB,BAXyCTTC!C@A0AAdWCB?B@@&AB%C%CBBB(BABBtCCA BBC?BAB hCCSBAB$BB8CC0BkLBC>TB,BCTBpBBB$BB | HBCB)C\B<TCBHxClBCB0/CmCTChiBBBBB56CBBBppA$C)CPJ,BB BPACxB0AB7C\BCCBb@BC2@BBBB(B4BBCCB$B/CCB1CBs AvC@BBTECpAAC@@BB.B8pBAkB CA@PABB B` CB(BCxlATAlBpBHAuAB0&CA C?CBACB BpBBXCB)C0Bd "CBAB BABC@CAB'Cd`DBDBATBBBVABAJC2CB`A@B8B`BCCPB0BBB8BB0ABBBL CLBAtqCB@=CBXC0ABBCB!pB H,pBB)B,CBpBpA+pB2C,BsABB A.EhBBNCB'Pp@A\>BuCBBpA g ClBB,B|PAAOBB,hDC 7CABpA BBB|]CuCAlBACCs>CBPBBA<BAx4@BBBCAPBB AAA*C"ApBXB0TBB8dB(HB@@BC,UCBPhZ@CzCAB|CC CBBcCABB"'C ClBC CBAB]CBBBABpAp0CBC4CBCA HBAPA(xBxBKBlC\C<$BVCl;@AOCt2DBOCLxBTB C\BBAA/sCA&CBByptBQCCBA BA6CB B \BA@@C$CBB CALCBAB C&B\B ABUC"CBC4B&CB@BBC$B BqC7CDCA /CBB BBTA_lCACA`PA'CfC0C$BBBB CP<LBCB pB)ASCB<4B C%CBC`8C(`CCABC'CAQ$O7=CCBDByCB` CB`@ALLBhA@B0B<PABkC`B PLCABB CB]CBB0ABBBdB\BBC|fCA?BAB'BB%CPdBBBRC#C8 TBSCABTB<B`BA`AAC<hB`ABC7C@XBAC@AB0CH BA/CA,dABJCACPB-CB%C@A+CdB0Bp|BB* B0AB$B+CB,BBltBPCRB0CBBRP| C AlB?,GCBaB`BAB(1CApHBBBP&CT(CDB' CBPBC`pB PBB, bCCBDLBACCA@BpBCBBBAB BBP@ABpBBB BB8BCBB.CBTCC!B,BB0`'CCBHBB C BBBBBCCBBBBBBtp/BBC@@`B@CCl44C 0B BhtB AgC(BAXBxBB\BPBB%00B(BBB-CBbCDB@3A@CX ClB{pA<<@BDB DxBC7B@BBC?BBHBLBBAA8CCACeCBDBEB@BCplBCd@AP(C(p,CZKCC.C@@B@TBC@BC BC48BBB|BB)CB0A!8B>CB?C8C8'C 0 C;C|B!CBBC7;BpB@BAB>CIC)C`A-QC.CBABC,NCHB`A;C2CHEX$B8CC#BXBACA8$B 4CC5CBB CCCCVCBA(B/DBB4<CCOC|,BNCxB,AAsCBLB|B`CC<@@ CA8BBH1C;C \BB^pBB CCDA C@CA1BBACBBATC`B|;CPC(BBlBA"CA@CaC,B lB !CXBBhBA! BBA}$A|BB CCDmCBA@APAPCaC@@'|BB5C C$BBBXBBClpdB,BCB5CDBBo\cCCB/C-lC2C)hBBA,BC BZBQC$BBB %C C@BBB$BBn BHB=C-C|B CAB;tBBCAAB(BQC?CC2UAC]CXBB CBg6CB,BBBB|LBBNCrPB B,BB B|BC5C^!B!CpAB QCAB=CBCCHBAB CBBACA(B@@3"C@ECDBC'=A(BAB1@B CBLBBCSxBCBAOpxBC"CXBy~C2CCA~BAPB\Bx0AC,CB@@BBBB0< @CCA!C)CxBB,BBPAB|BB8*C CAfBCCh^`BNC(,!CACB'@@@0ABC%BB@ (!CB'CBWiBB CCBA`L C1CBABA@CZBBBACBtB0ABCgC C pBBBBeC8B Bh=C:C?LBB4B0BZTB,AplCtBKU$BBCUCB CBCBBLCC+ B0BBBXBsdBCMCA CpB@0ABB0BBBC CAC!C dABBCBAPB%)CB9C3pB\B-C|lB6C A 4BBBBBPCBBPABh ,BA@CBLB,BAB@BBBXBCBXBhBB|BB6C$B(ACC_<B C@BBHhBBCBBxB?CBBA@P0A\BB@C`A A4B(@A_u@@ClBCB BQCBABCBB&CZBQPYCXCjC1C0BtCpBATB`AtBECDCdBAQCC@ClBWC@C4`0A@B C0A(B@@XB CCBBpA@fCB&BBpDB AABBBAAB@XCB AC|BBB@`?B!BBzB AmC08BB@I&3CB@1BB0AB?AADB4BlB\CBC|BDI-CBMCB,B BABBAB@ACB!C@|BB>C@BCB@ AC`AAB1CCB&J BCp0AB BBBADCA\CA~?pBB!B CDABBB@BC0B@, +ClBXCA2CBC( CBA BC@;CBDBCPBPA<BBB| 8C,BB,fm@$BBDB2C0BCBCABxB/CCACCBaYCBtpPAp`C/CDBCBcNCBC@&iCBBArCBXB=C?BC#C.CdC CA"C|B$B(B`AAhC BA4BB<#nC(BlBBPBH(BBAB2C0C$C|B#tB>C'CCA4BBCBH@^C@ACB%CTBB`A@C`BB1CcBAFHCXBHBCB@hPC9C@AC`EBBBpBB{@B C?P/A`CBAhBB CB)C6CWBABLICC\B`AC)CTB(H?CoC8BA`ACB4BCBTCB!C;C CBA0Bt|BBABBPCB A`AB@@ C#CpAB{C92BNCBB8BtCBB:LBF+*CVCAB0BCB A,@?ClB B@CB BtABCB+$ CC7C BBA PCCBP\B;C#CBBPA B B(DBB`A@@DBBtBB@tBBBBAC+CACCB(BJpB`ABdBaCBdBB$jCBPBCPCB@?'B"C$CBCBA0B ABB\`CCPAAdT'CC80BC@@CCxBB\CPA BxBC C(BCBECBBBB@BCCBCB,|BMCB*A;ABAC A;BC@BB XC(BBhBBdB-BB,BCCBB rC^C@@8CPACBd`ABBC EAlB2ABBBBBB4C&CBBXBBBC(C*CF&CS4BCBTBlhBBBBBB0ABC YB^CpArCB/C#CBC C##CC tBB2C_BAAC(CLCpA$BC?C`B`ABpA$CBBA$B"gC[C `AB`ANCBAC!C2C(BhB(B?ATB#^CBFCT CBB@C,B0B[C#CC5B9C,B4@xBBBB !CxB\(BCBCB|HB8AEC CBpBG"CA$@BBX9C|BfCBY<CBOC@BB`B@@BC,CBCB0BpAB0AACXCBAS;CNCBB AB|BBXxPBH`CBBTBBBAxACAB@PA\CB*CB$AFCCBA CABB4BPAC<ABkCuC~CA#C|BWCPC?DCACCAZCCBZABCBA0AA!CXBCB B 8CBB@Au0B:CCBB%C|B ACA AlBdCi,BIC CBCAB@@=CACBC"C;C$CBB0CBPBQA8BCC00BB&C7CA2CC\BA4e BBxBB B\B$B/`B,B_pBuBlB(B\B?BBB\CB@ PzCA@PBAPB B2CA \BHC+CtC(pABB@@AB@B CC B BaC C`'CBB,BC"pAB8CB, C(ABPABXBCA0APBXCBB/@@BApAB!CC,BBBBBhB+CtBK-`B@AAABC``AA0CBBABXBBBCHC8B CAAD0B8BC/Cl\ pB!C CC PADB8BCTBCB@ B,BBBC8BC@@$BxBA:CBh9CBBMC2BC CCB/=0CBpBC BCChBFCBB CtC~ABBCB$=B CBBBA= <CDCzC@C/B CBpLBBC^C@@BXBBA CBB CBB%B CBdCCABp@BBd-HBbC/C ABB0A@,CBBLB,|BPA@2@CBA?BWC0A0A CH A!CsCC@BNCBA@pBBBOhBCBrCB0Bh BBaCXBAB>CC -CpA8BhBlC%CABLBB0lBp,C]C4APBCAH@B$ACBBAGCPBlBFC 0BB`A?CB BA7CBAD!CBxBBB2A4BBBECACC BRCBCA@@CoB CBC@=BCo0BBuCBxBB`4B ABBBABBBpBLBBtB@C@WCABA` B|BBlBBBAXAB8C CBA CBB B&PBBB$CCB8 BC CAACB CBkC0B; CDHDB4CC C?C"CBD,CALBPCBBLLBPA4=CB@@$BxB/CuCBPB0BB4CB@BBPAC B4CAdBHB-`ACCC@C)CBDC'CDBlDCB B_CB<HBPBmCXC)dBtBBQC( CSCBBJCBvC,BBBABCA CnCAdC!CB CB]$ACCwC A(CBBBCA(A@CLBBBChBABXBAA[CCCX'!CA @CA8B(BGCABeCB BhBBXBB`&0AC0CA8BBAA BBhCLB4BBCBBPA,NBcC<BPAYCBACBA@BAB5CNC*4CB$B*C?B@BB@lBBBHBBHBtCCCB B[CBCAPBBAP&C@BBDBBABC6CAPA|BKCBxBBVBB tXB|BAC@ :CB C4CC0BB`4@TB@<CHB @BB4BAB[`hC$BBCBCBBBAoCRCA$BtBB9CXBACB BHOCBpCBBBBCABBCnCpAe$CBPLB?AAXBCBB@BDBCCLBCCBBdCBBCPpA\BRC C|B4B\C4BCB*?B<AA,BB@@BC BCC|BB@ICBA@tWLC0@@BBA`B8CpBABBB&CCBBABCYCB CDBBADBsC>C0C*C8CB[BjCeCBX@L9C CBdBADCXB;CCAp@/CC8BBhB00BBBBAB CB|BCPBB`AXBtBCCA0BABC;C,BC^CAxCBBA0Ct5CBp3CCDBXB LBAB'CBBBBPAB,C@@ CICATBBB@BiCBBXB@A CCBBB@CxB-CBABPBCA\@BDBBBHBB8CB?TFCDBCCCB C1CBBBCBCBRHCB?BBf,0 ,0\B #BAaCC ABHBOCxBt,BBBBCCDBA,C(BL@LCH`B;CB CA@xBCBB4BxBROCC0BCBBBCBBB AICCC.CB|BHCC B0.CJCBBAKCQCClB?pA/BXCB@"C`BC?tBLAPCBBrCBBaCB FCABCcCdBAlBlCBtBkCC BYC@nCBBCuCPB.CC(BBB=CxCC CBL}CHBeC&CB)CB2BBCh CB&TBBB;C[C'CchBC,C`B B9AB CCBW@@BxBlCADlC,BChB%ClBCBbC!CHBBpB CBABxAAPD@@XBBPBxBTBBBCC`BTCC@TBPB`AA9CB@BBA%BBB&CB8CxBCYC@=CA@CHBBBBBBBCBBhBB)CB, (BhB$B@CBpB CBBCB$BBCCBL^BA@BBAyBHDBA@ACBC3CdBCCJCLBBCCpABHBB$eCTBBB4C$cCCAA@CDC5CBBA ClB0xD.CbCBdB-AHBBCvC$C CSC TBB@ CBACCX4B$B0BB*CB7CSCpB.0KCB$B|{CC CB ABECCB8B/CT@C C BACB@BABlCB`B0ACCC$BXB1ClC(BBmBA CB CB*C_CMC,[CpBC CBWC( CBCBBCBCACBBBBB!C|B@B?CCA@B8PBHCA`ACC(@B\CB BBABBCBPNCBC#CBAC0C4ABBBx&XCBBpABPA C-CBB@@B!CBBBAAABBCBC@#CB(BBCxBBBd(B04B A=C:C~C(BBbd)CCBBKC8:CCAC@C4C@CB0lBBBBCC9CBBxDB0BA@KClC5CC@B B%CB@BFCCBB7CTBDC3CBCBC`ACBBBB@@BCLCC(aCBBBCB3BBCB CCAABXC C@@BMBBQCMCT`AxdBB`BXBCMC,\B| xCA_CA BCCdBdpA(BlBtB#CC/C@BpBBCCAADBABCC?BC C`BdBbCCAACBPBhDBnCBCC@t6BBACC)C&CHB=C9C B7CAAC06C4B$B4C0xBCCB@@ZC!C|B4CTBBC`BDC:BB0ACBB@BAB~CC (BAB8'ACp@B CBCxCBCPB CdB@B Au<HBBBABxBB8VC(BBP4ABBBCAB(CPABCC4BBC@BBdBA|B]C``B8BB,CB@BBBBCCA@BBCCBB C'CLCKCBCC8"CB(BBlC#CSC\A`B BBBSC0B =CBCvC C#BHB `BfCBAdBC`BBAHBBB`AB)C/C*CB@ ABDC0C*C 0BBBBXBBC@BHBA9@TC COCGCBB8BB!CBABBBCBlBP`CMCAp@A1CuChBCCABChBB3@BBB C4oC CBBBZABBhB@ACC0ABJCBB\CB CBCB0CC\BCCBIBCBCaCBB CB4B@CC`CB[/C CA[CBpCB)BjC'CB+CC\BCB0A0B>C@CB\/CBoC C@CmC<B)CcCDBTBhBWCUCBB\BB*CBCBqCBA`@BA4B)CBDBP|BCYCbC.CLBJCCACBBAP@@BBBCB0BABC CBbCB`At| C C88BCBACP|BjBBBB$B tB2C BB=ACB'CAC C A4BC\B<BBBACC`ABB8C`dBCC ?BBC4BBC^CBAEC CLCBBB(B&CBdBBvCC4C0ACBPTBB?ChBCC B|pBBBcC(BCMC&C< A@B5CBh?CC\7C.B5C"hBCB CB(=@iC@@BB6C(BdAWCBECB,BC(CBCBBB0A*C0AABOUC!BCPAZCB8CBBB AC%CBBCXC C89CCBpABbTBCA BC:C@BCAABLB@CBQC%CTCfCvCAC(C?BB,BAB,CBLB@A,BXB`ByC!CBBAhCT CB ?BBOCBCPCBDB5CB4ChCBB\CC`CBC2C}CC@C@@BBnBHCB$CBA@BB?C2C<lSCC0BoC CBB@ BCC, AB4CBAACBKCP4AC8BXBC;C?AB \CC @AAiCjCC6CCCtBAB(BCICLBdBBBXCBBHB BCBA BtBBCpACCBp\BBBC\C-CCCBBC8BCB B@B5CXCBB>C8\ABBCcCAB=CCBA?@@A-CB$B4BUCXBBBB CCA?CCBB=DB CAC(8BCC0@CkC_CBCC5CB5CdCCBCBLBB<BB C-C\tBpAnCLHCBCCKABWCpB(_CB@B4BB@ BBBCBABB CC@@hBHlC'`CMCBBA0B C4CBAC!CBBB C,B`$B@BCPADB0^C>CCAB\C&CBBA*CCB*C @@C4BBQCtB(AiCBDBBJCCA4BBTBCBCBCB0BXACBCC C@@BwCMCCA=pBBCBGCChBC"CTUCRC@ BlBCB0BBC0A4ZC4BBBABCBBB'CBBBCACHBCBBC{CB4C{CBCB|BKCAC#C=B@CBCBB/CbCCAkCkChBUC0CvC0AC=CAC%CLBBjCCB4CBLBABB8BXB7C_CBsCB@PB'CC7C0 ACB\BDCAC(CBBBACB@CBhCIC(CB@ACBCDCLBACCBAxBBCzC'CCHCC05CBB-C`BCCBXB@}BCCCCcAC^CBDCBCC{CpAB CBBCCCCpBB,CBiCCA7C0ALCxCCBCCABBA2CCBCSC BPABiCTCbCBBdB"CXBA$CqCBBBA;CBA@A@CCBxC ACCCBDxBBaCBBB,CQCCUCCBBA(BCCCBXB ICCCxCBCCBBCCMCtCBDB*CoCPCBCqCtBBC$CBHB0A$CBCCBAp CCBBlBCB@ABCCABAACBDCB,CdBC`CBACJC`AB\BBBCBCC]CBkCBCh8CqCNC1CCpBD;CChC^C@BmCCbC1CCB#CB~CCB8CABzC~C CCACDCCBCCB@?CC0CC BACCBCCB8CRCACB)CCHC0CACCWCCCBNCCABBBrC@CCAhnCFCBC[CBTB8pJCGC-CChB<MCBABC,CBsCvC|CB&CBBCC1CBB`BCIC CZCBCCBBCCBB9CtCCCB`BBCWCYCC CCClCAA@BLCCXBBCAB,CmCKCB1CACCXCC$C<=CCBsC,BCC C2C7CBBXCCCB%CX$0C9CCCB/JCCFCCEChBrC8CBACCC6CCBUC|BlC}C)CCCWCZC(@B2CvCBCQC BkCCBBCCCCB@CCB>C\B0jCCBC,BClCBACLBpCBYCCCCCBCCCBcC~CB@}C'C`B|CZCBuCCBCCC+CbCB#C4CCBdBB*CCCSCBCB!CBB^CeCC'CBCOCCaCBDBsCBqC=CYCBB:CC.CBgC ABCBBBCCC@C,CANCuCB?CC#CCBBBJC*CBC1CABCB@BCqC%CBECCCBC@CClB@CLC@BBPCCEC @CCBC7CCCCLCCB=CCBPCALCVCABBCB CC0CCBsCCCXBBBBfCC+CB?CB)CjCCCC_CB(BCCC\CCB4CCCB+CxBCCuCsCsCCXC8PC_CCCCCCwCB\CC,B/CCBC`CDC-CC?C.CCuC@CC,BCBBCBCC CCCxC CBBBCC@3C@@BC1CB4CBCCICwCCACYCCACBCBCwCpB&CCB_CCwCCBB0CCpCBCA6CCCgCCC}CTCBfCuCCB`BBCrC*C@@B CC CBBCtC!CBBCCBlCCBBCC=CB`ACsC@\BBCCBCCBCCBSCC(CCCKC1CBBCCGC+CBCBCCpCCBCQCAA0CBCCCCICB}CdCCCC1CC%C6CCCkCC`BC-CCB7C4BC&C@CBBGCCbCpC`C\B}CCC`C CACJCAjCBBCCCeCCABABACCB CiC>CC1CC CC(\BCCCCC`BBBmCCBC BCCCCBMCcCBFC9C%CCCQCBCBCBC)CBC4CB@CC4CCBCC[CCCCCCvCC\oCCD|CBClCABCB C3CCCCBCCBBCCCCBCBDB;C.CCSCCC4C3C`CBtBC@CB,CCBCCOCB,CBB.C}CC6CPC\BXCCBBCeCB3CC`CVCBBfCCCCC8CBBCCrCZC=CCCCBNCCC+CCC.CCCC}C=CCC5CPA B1CBYCC,C CBCCBBCCB4C;CHBCC;CCCdC[CBLCECBCACCBBBCBBBCCCBBCBBdCCtCCeC"CCBtBCmCCC CBACdBB\CPBCDWCB^C@CB@CCeCwCBCCBCCAsC C{CCBCCCCCC-CCCCCCCCCcC%C[CCNCCCCCBpCCCCCCCCCCCCC>CPdCICSCCmCBCCCCCC|CB4CCCBB CCCCfCC9CCCCxCCCByCCCCCxBCCB7CkCCCCCtBuCC$CCCCCZCGCCCCCCCBBCCCnCbCZCDRC%CCCBJCC'CCCCCCC)C CCC%CtCBCCrChCCCCCCDCCC CCC7CCCGCCCCCCCCCC CC^CCBCC]CCBBCCCCCiCCCCCC CCaC*CWCC(CCC/C[CCYCCCB~CC.CCCCCCCC"CCC(BBvCBCCBuCCCCCCZCC!CCCCcCCCCC-CCCYCCCC:CChCCC&CCCCCCNCCCBdCCC@DCBuCCCCCTCCLCCCaCCSCCCrCCCCCwCCClBCCCCCBCCC*C#CaCFCCCCdCCBCCC|C(CCCCC|CBVCKCC@DCXBBrCRCCCCCCaCCCyCPBCCwCCCfCBBDDB)C/C\CCCCCCCgC[CCBCCCCCCBCCBCCDBCC$C2CCHBnCCCCCbCCCCCCBCyCCCC0CCC*CTCC0CCCBCvCBCCC|CCAqCCCCC$CCCCCC9CCGC]CCC'CCCCCCCCCB\BC5CC2CCBCIC+CgCCnCCCXBChCCCC>CCCCB*CCCCCCCmCCCvCCCBCCCCCB+CKCCCCDCPCCCiCCpACCCC`CNCCCBCC`CCCBCZC2CCC$CCCWCC,ChCCCRCKC'CZCCCCCCCCCBCBGCCCCCCCCCCC4C+CCB~CCC^CGCSCBCCUCbCC C\BCC DDCC3CBCiCC?CpB=CCC]CCC1CCvC@uCCICCCCCCCCGCCCGCaCCCCCKCCqCBaCiCCBBCCCDCxCCCPBCCvCCCCBCBCCClCCCCCCC D7C\B]CCLCCCCCCmCSCCCCCCCCCCCCCXBBCDC`BECClCBxCCCC'CC CCCDtCCCCCCCCCBlCCCCC CCCCCCBCCxBCCXCCCqCCCCnCCCCCCCCCCCAmChCBDCCICCCCCCCCnC~CCCCCCCCCCCCCCCCCxCCCCCCECCCCCC2CCChC@DCCCCCCCCDCwCCCCCC`CtCpCCCCCCCCCCwCCCBYCC{CCCAC?CCCCCCCpCCCCCCVCCkCtCCCDCC?CCC6CCCACCCCCClCCCCCCwCCCWCCDCC>CPCCCC@ D\C0CCCCCCCCCCCCCCCCCCCuCBCCCDCCC3CCCCCDCBhCCCCWCCCCpCCCJCCCCxCCnCCCeCCC8C@ DCBCCmCCtC0CCCCICCZCCCCCCCCCCCCCCC`CC DCCCBpCCCCCCD@ DCCCC DCcCCC|CDCzCCCCCCCCCVCCCCCOCCCCcCCCCCCGCCwCNC@DCCC[C^CCCnCCC@CqCCCCCCCCCCCBCC!CCCCCCC}CCCCCSCCC$CCC9CCCCCCCCC#CCCVCCC4CCCzCCCCC@D8CCCMCCCCCCCC@DBCCCCCCCCCiCCC@D@D:CECCBCCBCCCCCpCCCDCCvCCCC DCCCCCMCCCC?CC DCCCCCCCCC~CCCCCCCCDCCC#CCCCC@DCCCCC@DBpCCCCCCCCfCCbC4CCCCCC/CDCCCCBCC(C DCCCaCbCKCCCCCCCD>CCCCCCPCCCCDCCC@DCCCCCCCDCCCCCCC/CCC~CCCCCC0CCC5CCCCCCCD D^CCCYC@D DzCCCCCC2CCsCCCCCDCCCCBCC/CC1CCDC:CCDCC DCCDCCCCCCC@ DDpBC DCCCCCCCCCCDCC DCCCDCCDCCCCCC'CCC@DC-CrCCdCCCICDCCCCCCCC DCCCC$CCCCCCCCCCCCBJCVCuCCCCCCCCQC;CCCCDCCCC|CDCCCDCCC:CCCCCC#CCCCCCCCCB CCC DCBCCClCDCCCfC#DCCCCCCCCRCC"CCCCCCCCkCCCC.CC;CnCBCqCCCCDCBCCCCCCoCC2CCCACCCCCcCDCCDC2CCCSCDDCCMCC]C#CCCCCD&CC$CCaCCCCCCBCCCiCCClCCCDCDCbCCCDCCCCCCCC@ DDC DC.CCCCDC@CCCCCCC@DD`CCCDCCCCCbCCCCDC CCC*CCCCC DC@DCCCCCDCC.DCTCCCCDCCCCCCC DDC{CCCCD@ DCCCCC.DgCCDC@ DCCCCCC@ DCCCCDCCCDCCCiCCDCCC_C@DCQCyCC@DCCCCCCC@DbCDCCCCCCCCClCCCCCDCC@D DCCCC@ DDCCCCCCCCCCCCCCCtC DC/CCCHCD DCCCCDDCCCCDCCC0CCCCC5DC CCCCDCCDCCCCaCCCCCDCCCCDCCCCLCD@DCCDCCCCDCCC@DCCCZC DDCCuCCCC@ DDDCCCC@DDCCCCCCC:D@DCCCC@DCCCCC D@ DDCFCC DDCDCCDCVCCC D DC)CCCCCCDDCCC CD>DCCCPCC@*DCCCCCCCCD)C DCC DDCCCJCC@DCCCCCCCCCC@*DCCDCCCCCCCB{CCtCCCCCCBCCCCCBCCCCCCCCCCnC}CC@ DCkCCCsCCzCCCCCCCCCCCCBCCCCDBBC9CCCBCCC DD-CPCCjCC*CCC@D@ DCCCCD@DC%DDCCDC DDCDDC@D)DCCCC D@DD@DCC@)DDCC DCCCC?DIDCCCC DCC@DCC%DC@DCCDDCC@%D@DCCCCCDCDDC*DCVC DDC@DCCD DfCDDCD$DCDCC DCCCCC!DDC DCCDDC@DCCD D@ D@,DDDD.DCC@ DC1D@DCCCCCDCD@"DCDDCLD!DCDD{C D#DDDCC@ D(DCC`CCAD@DD DCCCCCD DCDCCC@ DD@'D@ DCDCC%DDDCDCDDCDDC@DCC:D@DCCCCDCCDDC D)DC D@DC@DCC@@DDCD DD2DAD@DCDoC D@>DC)DDCCCD@3DDCCDDC@DCDDC@DD D@ DD@DD@+DCDDD2D7DC/DCCDCDD@4DDC@ DD!D@DC"DC1D.DDD DD'D D@ DDD@.D@8D-DDDCDOD:D2D D DDDCD1DJDiD:DD@D*DD1D#DFDcDDCC.D9DADCC"D2D-D7DDCDCDcDSD$DCCCD@,DDC@DC0D@DC4DDCD0D@DD6DD@D@D@ DTDSDD,DCCWDPD DQDCD@9D6D&D#DED@D:D+D@0DVD9D@ D@MDDDDD$DCCD@.D@8DC@D?D;DD'D"D D@HD0D#DcD(D D@DC?D DC/D+DDD DD;D=DD#D!D1D@pDmDC@D DFDMDD@D*D&DC D"DD6D#DC@3D7DD6D&D'D8D@EDCCC)D]DDDC2DDC=DFD@DD@,D@'DOD@DC0DKDD@>D%DC DCCD@!D@D$D?DBDCZDDDD@DCD@1DCWD$D?D0D D1DD(D@(D7DD+D;DDCD@BD%D/DDCD@GD%DXDDC3DD@ D@DDFDD@D$DDDD4D@DpD@D@!DC D@$DLDD D?DDC@GD@>D DD@3DDD@DBDD7DD%D/D"DC@DDCC DDDD@ DDDD@DDCCDDHDCCCCD@-DDCCD@D*DDDDDC+DDvCCCC D)DC"DDCDDCDDC$DDCDCC^D?DCD@!DCD DC@DD@DDDC3D8DDD4DDDC@D6D@DC@DDCD@DCD DCCCDDC@DD@DC7D@%D@DD DDC DC@+DCC@DDCD@(DCCC9CCCC*D DCDCCCCC@"DC DDDCC@DmCCCCDDD+DDCCCCCCCC=DCC DCCCCCDCC-DC!DCCDCCDCC@ DC DCCCC@%DCDCCCDDCCCDDCCCCDDDDCD DCCCCCD@DC@D DCCCC@ DCCDDCCCCCCC@DDC@DCUCDCCDCCCCCCCCCCC@DDCCCxBCCCCCCCCCCC.CCC[CCCCCCCCCCDCCCCCDCCCDCDCCDCCCCCC DCCCCCCCCCCCCPCCCCCCCCCBCC@DCCCCCCDDCCCBwCCCDDCCCECCCCCCFCCCCJCCFCCCKCC@DGCC|BCCDCCCKCC`CCDCCVCCCCCCCCBCCCCCBC@@D@gDXD_DDC+D@BDDdD@6D@^D@QDDVD>D@PDYD?DCDMDQD=DC@0D@QDNDLD@9DBDDDiD@D@RDCD1D@CDgDSDzDRDD@2DMDbDjDID_DqDFD@D1D@FD1DdD>D1D@@D@`D-D@TDKD@D7DgD5D@8D@WD@DDDSDBDD@3D@9D@D^DZD@lDYD4D@5D@DD1DaD@UDvDDDDFD@FD@LDqDrDmDVDLD@/DhDWD?DfDLD1DrD@HD@WD*D@[D@9DHD^D"D\D*D)DED@jD/D7DtDD@^DGD'D@D?DXD;DGD:D@jD[DDhD@?DLDVD@YDD4DWD;DSD@UD@7D@QDVD=DND@(DD%D@0D-DcDRD@BDEDRDDdDhD)DFD'DDVD_D:D.DVD@DDAD&DpDDDVDDTD@VDDLDCDLDzD\DhDeD,D@\D5D@#D.DND@5D^D@UD!DBD4DOD@UDBD/D@RDDCDKD@nDAD@_DOD(D@5D%D@D>D1D/DJD=DAD7D@D?D@8DAD,D@GD@7DD'DVDWD-DED@%DvD[D!D&D@.DCfDrDD7D&D"D@FDIDDADeD@ DD@DZD D4DDgDGD,D]DAD@D^D@0D%DZDLDC@D\D;D@?D,D(D3DBD@ZD.D@$D/DD@]DDVDD@DAD@+D DGD)D@$D5D@RDDBD-DC>DZD@?DMD:DDGDHDC@D D)DD@;D7DVD=D@D&DD DD@DEDLD@DD@;D2D$D@WD@)DD,DDD^DSDCC-DD@(D@DCCDDEDD@D!D@'D@D@'DEDFDDDC DDD1D@(DC/DBD DDDDDDDD-D5D'DDC DDCD@ D@D@D@D'D@6D(DDD@DC'DDCD+DDDCC@D@#DCC@D@,D3D@ D@&D'D#DCD DC+D@DCC@DD@D DCDDC@_D6DCC@DC@;D'D D;DCCC@DCC@1DDD@ DCDDC"DCCDD@ D@D"DCDC%D$DCYC@DDCC@DC(DCC@DCC@D DD"DCCDCC&D0DCDCC@!DCCCC@DDDCCCC@ D"D@D6DDCCCCCCCD@DDCCCCC@DCCD%DDCDCCDDCCD4CCDCDDCDDC D@DCDDC.DD@DD%DCCDC@ DC DDCCCCCCDCCCC D(DCCCCCCC@DCPCCDCCCC@D@DCCDCCCCDCC@DCCCCC DDCCCCCC@CCCC)DCCCC`CCCCCCCD DCCCCCCCCCC DCCDCaCCCQCCCCCCCDCCCCCCCCCC9CCCC+DCCqCCC@D@DCCCCCCCCCCCC@CCCCCD0CCtCCCCCCCZCCCCCCmCCCCCqCpCDeCCCCCCCByC!CSCCCCCCCCCDCRCB[C@QC@cDD@`D@kDD@yD@uDpDODbDDeDDD@}D@wDvDJDD}DTD\D^D@iDMDBD@ODDDXDbD@yD@~DeD@ZDLDkDrDkD@tD@nDBD@DpDnDDsDXDCD[DeDpDDOD@`DDD D@gD'DnDqD DzDD\D@DDDDjD@>D\DuD~DD@|D@D@WDuD@VD D@}D|DDxDdDtD6DNDDD@MD@lDjD`DDmD@BD]DhD@mDDDOD DDnD@DmD9D D DD@zDZDKDqDoD@QD@rDD`D@}DWD3D@fDsDJD@WD@WDnDDD;DmDkD@jD`D@kD@GDsDDqDDWDXDZDyDeD|D DID@DhD@^DD@{D@3D@DmD@{D@DlDLDyD DyDbD|DcDDDJD D@D@4D_DlDMD@DD@TD DbDWDrD~DoDD DVDxDnD_DDDCDhDDwD`DwD{DDYD8D@|D`DYD@sDDD@DDDD|DXDD D@NDpDD@rDDLD]DD`DcDD]D@TD{DrDWD{D`D'D{D@kDcD7D@lD6DbD@DEDjD~D{D@uDbDOD@BD@JDLD\D`DZD@\DD@oD@D@D9DzD@bD^DD@D*D@pDDDxDrDjD@fDFDnDDuDcDDvDpDwDdD@8DUDDODD}D@LDPDDlDsD~D^DJD@jDUDhDD^DWDPD:D@lDDPDDDBD=DAD@7DWD@mDzDcD@pD0DSD1D@ DGDYD^DsDWD@ DkD@kDYD@SDODdDpD\D@6D{DyDUD@gDZD8D^D^DWD]D=D@;DfDeD7D@NDZDgDvD@}DQDdDED@4DCDZDODxD@BD4DMD DlD D\DlD^DpDD@bD@\DDoD@DDbD:DD=DDD@0DkD D@LDrDfDgDDD@HDsDADD^DYD!D@YD@-DFDDD`DLDwD@?DD>D@UDKD@|DrDD@DUD@RD{DhDDBDHD3D DnD@DeDND/D@eD-D5DRD{D@%DlD@ZD DZDHD,D@DD@MDCD@iDzD"D@GD*D`DuD@JD0DCDGDID@vDZDqD-D@JD@D@ED>D1DUDlDGDPD@ED=DWDJD@ D>DFD(D@HD`D@D2D5D@?D\DD"DGD@JDHD_DD@3DD'D@PDZDiDOD@6D=D D6D2D!D@PDD@4DDDC D@:D@DDD)D5DJD@,D@DD1DD@D@DC+D7DD(D6DCDCCD DC!D%D@D DCC,D2DCD@'D@ D@D@DCD@DC0DDC!D#DD!D DC+DDC@%DEDCCDCC*D@D@D*DC@DCC9DCC4D@DCCDCCCC@AD)DCD@DCDCCD@DC0DDCCCD DCC@%D@DCCDCCCC DCCDDC DCCCD~CC'DDC@DCC@DCCD:CC DCCCC@DDC DD@DCDCCCCCC@D3DCCD@DCCCC D@DDDCICCC'DDDDC@DCCC@$DCCCCCCCCCCDCDDCCCC]CCD DDCC&DCC[CCCDC DDCBCCC-DHCCCCCDCCCCCCCCCCCCCC@D@DC@DCCCCCCCCCCCCCCCChCD DCCCC@$DC^CCCDC@DCCDCC@ DC#DCCCDCCC6CCCCDCCCCCC@DCCCCCC|CC@DCCCCCCkCCC@CCC@DCC'C^CCCCCCCCCCCC@DCBCCSCCCCCCCCCBCCCCC CCC\B4tD DDDD`DDDD@DD@D@D@DD@D`D@kDD D`DD DDDDD@DoDzDDDDDD@vDDDD@DDnDDDD D@DoDDDDDDDDDDDDqDD@DD DDDD`DDDDD`DD`DD`DD D@D@DDwDkDDDD D`DDD@DZD@DDDD`DsD@D@DDDD@DDDD`D DzD D@D`D`D@D D@D`DhD D@DwDDDDDD DmDuD`DDD@rDDDVD@DDD`DDQD DD`DDDD D@DDDfDDDUDDDDzD`DDDDD@D`D@D DDD@jDD D D`D@D DD DDD D`D DD{DD@JDlDD~DHD@yDDDD@DQDDsD]D DDDDDDDDD D@}DnD`D@DD@DD@yD DDD`D DDDLD@zD@DD@vDDD@D`D@DyD`D D DDD DDDD`D@yD~DD D@XD DyDxDpDzDkD`DD`DD@rD@DDDDDDND DDuDDDDD_DDDDpD@sDD@D D DsD`DUD@mDD`D@MDDDcDDD@>DD@DDDzDDDdD DzDbDZDDDVD@DiD@oDD|D[D{D`DxDkD@GD4DrDD DD DjDQDD@oDgDwDgDDWD@D]D`DMD_D@qD@_DuDDDDeDPD]DqDwDD@rDCD DD DhDoDDDDkD@~D^DTDDtD\DlD@vD>D@D@D`DsDnDIDQDxDDD@lDiD@kDyDUD@DiDD@qD DD-DTD@GDPD@D{DfDsDaD@`D@_DYD]D^DTD@?D`DjD)DSDdD@(DDdD6DID1DDmD@lD:DPDaDRD@\DgD2D@sDJD@QDgD DPDZDSD@:D@TD@XD?D\DDaDQD^D"D2D@hDXD]DCD\DuDCDDuD@{D@8DRDDLD6DSDMD@]D DD@rD}D,D`D@CDDeDiD@iDGD+D@"DUDyDGD`DoD@D?D@LDUDD@>D;DiD@ED@D@@DjDHD D@DD@DD.D^D@D@GDD@MDD@3DD@DDLDAD'DRD:DC@MD@9DD5D=DD8DDC@PDLDFDcD.DCD@.DD:DED D@#DKD@D@DD@SDeDfDDDvD]DD@D@dDJDVDoDDuD@WD}D{D9DcDWD@*DD@]DDDPDD@pDDsDDAD5DGD@>DRD@dDVDcDDxD@&DSDjDFD@hD0D@%DYD`DUD@D\DCVDqD@D@TDID@.DED@BD)DPDaD"D@-D@GD>DTD0DAD.D%D@DRDDD/DhDFDTDDDOD@ DD8DID+DBD;DC@#D>D4DPDWDC(D@D@.DED&D@DfDD@#D.D/DXD@%D@DCmD)DDRD@LDDD;DPDDD@-DD[D)DD.DD/D5DOD+D@.DLDDDC@D^D@RD"D D"D!D9DYD@(D,D0D7D@CD@HDD@&D@DC@:DADD@2D*D3DUD.DCCMD4D@TDDCDCC0D@@D=D0DDD9D0D$D@D@6D@D4D-D@D*DADC@=D@(D@D@#D?D)D@ADD@DCDC@DGDD!DiD@0D@"DDC DCDD DC5DDC@D,DC D@-D@4D;DCC8D@DD@6D@+D D%DDCD@DD@9DJDCD;DD@*D@"DC(DCC DDD9D DC"DD'D@ D3D0D@ DDC DD~CD0DDDCC6DDDC@ DCDDD5DDCCCCD@QDCDDC DC D@DCC@"D4D DDCCC@ DDC DCCCCDDC@#DCdCDCqCCDCCC DCCC@DCCCDCCCC@D DDCClCDDC@%DDC@DCCC%DCCC C-D=DCCvCCDCCCCCCCCCCCCCCCCCCCCCCCCJCC1D@ DCCCD@D@ DCCC^CC#DCCCCDCCCCCDDC DCCDCCCCCDChCCCCCCCCCuCC~CCCCCCCwC@DCCC_CCCChCDCCCCCCCCDCCCCiCCCCCCCDCCCCD@]DdD\D{D@D@jD\D@DSD@kDnD@8DMD@dDhDwD>DJDD?DZDnD@\D@}D@DnD,DmDqD5D~DqD]DhD`DHDxDXD"DWDkDPD@WDXDkD@JDVD@6DrD D@D@hD@ADbDD@fD)D,DaD@]DYDhD@.DADpDPD@gDVDD\DuD;DoDgD(DlD@ID@DDtDGD@OD@2D@!D@QDDfD@jD@SD@4D@eD`D@ DgDwD1D@pDXDDGDXDLDrDQD:D@mD@`D@rDUD1DFDqDPD@,D@OD!D@DZD@ZD"D>D@bD@*DHD@KDWDXD@@DDVD`D'DCD@]DC@)DLD@MD[D@dD D@@D@KD@6D%DODC@0D DD@VD@@DCD.D@,D@GD@LD3D;D@5DC@DnD!D@&D?D?D9DdD!D@>DDD@UD(DC D2DD3D3DFDHD@$DD5DDvDMDaDhD@^DhDDD@DLD@D'D?D@#D[D@GD\DuD?D[D@TDID!DFD[DPDOD%D DgD_DhD_DD@D@=D@oD@#DVDTD@GDSD^DD@hDCD@D?D@>DHD@rD@D D@&DDIDPD%DDTD(DCD@`D@UDDDDSDDC@@@D DD@DDDD DD DD@DD DDDD`D@DDD`DD@DDDDDD`DDDDDD@DDDDD@D DDD@DD`DDD@DD`DD DD`DDD`DD`DDDDDDD DD`DD`DDDDDD@D`D`DDD@DD`DDD`D@DD`D DD`D DD@D`DD@DDDD`DD@DDDDD`D@DDDDDDD@DDDDDDDDDDDDDDD D DDD D@D`DD`DDD`DDD@DDdDDDDDD@sD DDdDD@DhDD DD DD@iD@DD@DD{D D D`D DDDaDDvDgDDD DD D}D@DD@rDDDDDDD D@DgD`D@DDDyD@GDwDDD@DD@SDDDuDDrDDDDD D@TDQDpDDDD@pDdD`D@`DDvDVDrDDqDRD@|DDDHDtDvD@{D@UD?DDDZDeDSDMD@MD@FDPD\DD|DDlDdD@^DKD=D@lDD@bDmD@iD@6D@qD@XDxDDDRDDnD\DcD`D|D`DTDPD@lDUD@xD@vDpD@8D`D^D+DeD D@oDoDfD{DsD@YDCD@RDD_DXD@D D@LD@DD@UDD@|DNDYD,D@DzDuDD'D@VD@HDpDUDGD#DKDzDXDeDjD?D;DDGDoD;D DMD@UD^D@TD@TDDADjDyDD@iD#DD4D@D,DID4DVD@YD@&DD@ZDBD@D@DlD*D@D@$DDgDFDDDD@+DMDMDD&D.DC7D3D@ D2D)D D D1DDD2D#D@KDUD%DDD@5DDGD*D)DD@!DC@:DRD@!D=D2DDEDDDD#D DDDCD@DCD@DC`DDCD3DCID!D DADHDD9D#DDD@D&D@:DDC@D%DC8DDC@pD DD@5D DCPD@%DCMDDCDDCDDC&D/DC5DCCDD D'DCDDCCCTCCC6CfCCCCCOCCC|CCCBB$BBCCCC[CBCJCCCC[CCC CCCCCCNCCCBLCCCbCCCCCBCCCCCCCCCCCCCqCCCtCiCC/CBC6C1CCCC@DCBPBfCCCCBC_C;C`CCCCCCCTC[CCyC CCC?C@C[CGCCC;CCCECC,C?CCC`CCCCjCCjCC~CPBC0C&CCzCCCCCCCCC}C)CCCpBiCCC1CCBCDWCBCBDWDHDD@D@'D@6DADCDCCDODD@D@ DDD%DC@ D@7DCDCC;D@BDD/DDCD-DC D.D@DD D@D=D8D4DD D DD*DCD DD2D@DDDDC,D DC D5DC D@D0D@'DCC@D@'DCDDCD DCDCCDDCCDDDCCC@DCCDDCCC@!DCCCC@D:DDCDCC@2DDC@ DCC@ D-DDCCCD@ DC DDCCCC D@DCC D DDC@D3D9DCCgC'C DDCDDCCDCDC:CC DCDDCC@DCD5DCnCCCCCTCD@DCCCBCCCC@(DCCCCCCC@DCCCCCCCCCCCDCCCCPCCCCCCCDCCDCCCC@DCCCCCCCCCC@DCCCC@DCCCCCCDCCCCCCCCDCCCCCCCCCCDDCC DCDC~CCCCDCCC8CGCCCCCCCCCCCCCCCCCCzCCC@CCCCCCBC9CzCCCCCC!CACCGCCCCBCCCCCCCCCCCCC]CDCCCC>CCC9CC@ DCD CCCDFCC'CYCCCC@ DCCCCCC DeCCCWCDCBCeCBCDCDCB CVCCCC3CCC}CCCB@CCCCCBwCC^CCCCCCwCCCCCCC{CC}CCCCCCBCC&CBCfCCC7CCC8CCC;CVCCCDCCCCCCDCCCDCClCC~CC#CCCcCCCYCCCBCCMCCCCCCGC@DCSCC@ClB~CCtCCCBCCpCB2CCCC6CHC.C(BYCCCCCdBCiCACCCCCCXCCC#C CC2CCCCCCBCkC CCCCCCoCCCCCC?CCBCCCCCCB2C3CCCCCmC:CCrCCCCC CACCCiCCC/CCCmCCC CfCCCCC4CCCkCCBDCCB C$CCBB1ChCBmCC(BCaCCCACC`C@BCBACCWC"C%CAC;C`BCCYCUCC+CCKCBMCCACCCBBBCvCCECCCBBC]CCBBEC6CBCC@RCLCBCCCCBoCA'CCCCAtDD@aD@|DD@MDfD@MD}D_D`D,DtD@ED@PDpDCDLDvDZD`D@qDpD*DDD@lD@ID@oD@iD>DkDZDQDxDyD@CD@0DD@D@[DD-DBD*D:D@ED@DJD8D.D;DAD+DFD@bDD&D@7D@QDPD@_DCDDZDXDSD@D`D8D/D@BD5D@3D DADDMD,DD@D@WD3D@8DD@ DbDWDD2DIDD?DZDD@D&D4D`D)DC@:D@kDC3D#D@D@ZDTD@D@DXDD6D@,DC@*D5D@4D.D@'DC@*D@HD@#D@*DCC@#D@DDDCDzD7DD@D@DD#D@ D@7DiD4D4D@DC D@2D@DD@UD>DDCC@ D;D@DC@DDC@DDC@DND:D@&DCDD9DC@KDD@D DCC@D@DDD@DC&D@1DDDC@DC@DC@&DCCDCC(DDCCCC@CDCCD DCDC@D DDC&DCC@D(DDDDCCCC8DDCC,DDVDDCDD DDCC@"DCCC@DCC5DCCCCDDCDCCCCtCCCD@oD.DCCCCCCDDDCC8CcCCCCDDCCDCCCCD@ DCCJD DD@DCDCCCDCCCCCCC DCCD$DCCC`CD@DCDDCCCCCCDCCCDCC@D@ DACCChCCDB@DCCCvCxCDCCCCCCCCCCYCCCCCCTCCC[CCCCC@DCCCCCCCCCCDCCCCQCDC3CCCC DCCCCCCCCCCCCCoCCCCCCBCDCCCCCCBCCCCCCDCCCCCC@DCCC@ D@DDCCC@CCCHCCCCCDCCCBCC/CC CWCDCCCCGCCCCCCBC@DCCCCCCCCCCCCCCCCCDCCCC8CCpCCCCCC"CCCXCCCuCCDeCnC CCCCCCC)CCC CBCC DCCCwCCCCBCCCCC CCC7CCCDCCCCC]CDDCJCCCCCBCHCCCCCC|CCCBdBCC DCA;C(CLCCCCwCCCC|C7CCCB-CCBCCCC8C CCCCCCCC DCCC?C0CCBhCCCDCBCCC|CSC7CCCCCCCCC C|CCCCtCKCC\CtCBCCCCBvCC(ClCCCCCPAPCC_CCCCACBCC+C@mC1C@CiCMCWC}CC!CC]CuCCCMCCCBCC\BaCyCACCBC5CCCCCRCCCCCKCBCBCCCC CBdCCjC|CCCCOCC CCACCB"CHC,CCC~C>C[C CACDBCCCCCBC,CNC@DCBCCCCcCCCCMCCCCCCtBCCkCDDCCCCCC.CDCCCCCCC%CCcCKCCDCCCBCC:CCC0BCCBuCCCDCBCCCCCBBCiCC#CfCCCCC>CBCnCCqCCC2CC^CCCSCCCBCCaC^C;CwCCWCC CACCCCCBC,C2CCCWCCCBCCB)CcCACCOCClCBCCCCkCBCCCC4C2CCCCCC~CACCCCCCCjCaC=CABBCCCCC>CBnCCCCCC`BBiC+CCCBCCCCCB-CC8CCjCCCCRCCCTCCC1CBACCCCC,B[CA@DrCBB BCC4CBCCBC#CjCCC\BC\CoCC^CDCCBp#CpChBCCCB`ACCBBBBCCBLB C0B%CB- CCCBCWC\CC B:C@CCC+C$C>C hBCBAsCBBzCBBB`ABXBBCxCCBLBBB BBCB8CPCUC&CxBCBp.C!CCWC$C@BB C8CPCCbCCDCDCCCCCC*DCCCCCDCCCCCDCCC9CCCCC@DC@DDCCC7CCCD@0DCC DCCCCBC/DCCCCCCC DCC@ DCCpCCCCCCCDCCClCCCCCCkCCCCCCCCCCCCCCCCCCCCHCCDCCCSCkCCCCCC@DCCCDCCCYCCCCCCCCCCCCCCECCCClCmCCmCCCaCCCCCCjCDDCCCBCCCCBCCCC DCB3CCWCC+C3CCCCCCCCCCCCCCvCcCxC'CC7CCCCCB[CCBCCCCgCCCCBCFCC1CCFCCCCCCCCCCMCCCCC#CCDCCCCCDCBCkCCCC@CCCVC)CCCCCBCCGCC\C0CCCCsC CCC{CDlC, CCCCCNCCCCCC$CkCCkCCCCCB8CC|CCBBBACCCXBCLCCZC~CYCCCCCKClCBkCzCBBPBCHCCcCByCCBBBOCCLCCCCBCqCCCCMCYCCCdBBCCC\C4BCChBhCCCC)CCCCCCCB+CCCCvCBCCBCCCCCCCuCsCXCCClCCCBAWCdCCCBYCC CDC}CtBCCCCCECB@}CCqCBCB-CACCC@QCCB2CCCtC}CpBnCCCBBBCCBxCCBCCBCBACC@CUCB'CC CaCCCJCBCrCXCBPB$CjCdB`CBC+CdB9CCCZCCCCB%CMCCBC8B` CCB]CCBBCCBCCBCBCC@BpNCBCGC-CBC#CACFC0BBCC8C BBCdBBCC#C8C BDBB:CB?C`XB \C C,BZCACCCCCBCCCCC}CCCCzCCCxCC&CWCC_CCVCCCCAChCTCCB BCCCCCCBCCCCeCBJCCXBCBCCCCC CCFCBCwCCCCBCB CCCCCzCCCCCCCCCCCCCCCBBCCC"CACCC/CCCC{CfCCCCCCCwC`CACCCeCCC0BBBCCVCB9ClC;CBCBCNCRCCCB CBB)DCCvC/CCcCBCC_CCCBBCBCBC2CCB|CCkCCICBCVCBCCCzCBBpACCBSCCDC>CCBBCvCCd|CBPACCCCCBC=CCB`CCBBWCCB$CCBCBCCLBBCqC;CCFCACCB C@%C(CCxC^CCB|CTBBCHCBUCC?C\BACB_CBRl|CRCCB-CYCwCBCC CC,CA CAB1CJCA7CFC9CCCABC9CCAdC$CCBCBCCCCCCfCBAjCUCCXCDCACCCfCCB CC CCDBTBCBB|BCCC B{CDC AAwCCpCBBBeC0BCCSCCA?C\C>CCWCBBfCUC^CCC4CBBBCB\BCCLBBBBBxC C[CCABHBBC3CxCBCmC$C'CBACYCAAB?CBB@B-C~CiCChC@B)CCCpACzC>CTClCrCCBBrC`ABBADCC4CB8BCCC'CB8CBTB A`BBABCB CCGCXC;CA?<PCCBCBA ABTUCCBhC#CBOC&CABBCB'CCBAB^CBCCCCBABPChB,CCC-C6CBBC CJCBAXCB4BXCCBC\BB;CmCB8 C@A;CZCdB@ACBXB0BCCC{CEC0ALCpXCwC2C0AJCBC)CC hBoCkCC4BB,B,CB8BOCCAAhBMCBECACCAB0AACCB&CC ABLBAzCC CCBCCBZCLCPBBA SCpAT$C CxBBhBICC B8CAC<@CC+ BTBEC B0Bl>C@dBCBBCABCCCBB`CCB CTB(C`B+pB%CBCB.OC C<CB/CB,C`.=C@C4C CjCqCBBBBqCCUCCBBCHCBJCyCDBC"CBCCC6CBKCCnCCC"C?CCdCTC@BACC7CCCCuCZC CCbC@CCC.C]CCCKCBCCB{C7CCCTBCPB1C.CCCC7CB8CCCCBAACCCCQCCBsCC8B|C,BsC0CABAuCCBrCC/C7C BACCCBCXBCRCCCC>CCCACCBBBBC CPCpABuC*CCBCC,AB@C!CXBBBC CBBCB0AH`BBB-CBPBBBAsC CBBCCBdB|B@B@?CB5C^C@.LCBA@C8 `B^GCCIC|BB@ACC-CyCC@@AC C@8B'C<CB8CCAXCeC=CVC CB|C.CCBB1CpB*CfCBBCCSCAzCC@AB=CB]C%CmBpBECAXBBBCBB@PB -BB@BB'C6CBMC1CBA4BBeCiC`BBBBdBB0BC=C@C CBB CC@BBB5lB(CQ(BCBCBt`A AB"C`BdOCABNCCBCCL1CWC>C |CpB|BYC|BCDB B`ALCBA(B@@~CB3CB<BCCB5CBBGC0ABBBSCC7BCBdBBB?pAB/CCA"CxAdCHC`AB?ACBWBBCB`N}CaCA@AtOCTNCBA?@BCBCB\BQCB :CB@BBPAC(B:CC0BABB`CB`ACBKCB`PA,C_CC(ABSCKCUCtBCjC CB@BB CZCpRCCA\B'C C B/%CB A?BHB$@\BB CdBB=CCDBFCtBBB C@lBhBBC4CzC0ACCbCPBABC?CBBBBLBAC`A1CVCBnCB3CBoBChB CpCsCAAhBB;BB(#CBCdC0(B BBB9Cp,BBAtBB$B@0BBA9C>CBP4BBG'C@4B|BxBvCC@BBBBCaCCBBNC:CBsC4CBCCB@B C\CBACB\CEC8B?BwCCCCCBCBCC#C)CBBCABCCVC$CPBCCMCMCACTCC BPCB0BnC4BCCsC0C-CnCCCHBC@A@,B C0ALBCCCxC (CCB)C}CACB0AACECCDBCCCxBxBCB CB!CBBBcCAB>CCBCtC CCCB8C(CC|B{C@CVCChCBAgCBAjC&CBTBzC C4CCCCPABBBCECCBCBA7CtC)CCClBQC CJCBdBBpCNCsCCAB ]CXB@BBBDBeC`CBC&C@TCC,C@>CpA0AB?CB CCXCA`CCTBCBCCLCBBBoCpB@PACCB<(C]CGCBCB%B.CZCBCBBC CYCABBtB'CcCBCQCKCACuC@BhBCA0pB5CCCCC`A"CBB C\CCCsCBxB,8B CBB'BCABgC CC0AmCOCBBdBBB1C(BCCDAC8CCCACMCB$CLCQC$BPC,CNCBC"CB.CB@BmCAABAAbCCBBBA4CCBBCCCCC@2CCACBBC4B!C CA0BpADC`B$pCBBBCBPBJCB CBCCBMhBBTBCB&BBpBBlBPAB8BCCCCBC#C{CxB:C CdBPC&BCC+BBC@@BBxCx@B@6CnCB/C XB^CCBA~C(BCCdBBBC BCCLBCCCCpBCX(BACBC4B=B BCCCCLBB(C=CACCB=CBcCBB&C|CCOC hC C+yC C8CCQCBATC@ASCCC9CCCtBA)CLCCB@hBCCABBqC,CB;CDC:CC CTA0AAC*CLC7C2CCC\CrCBBB TB[ClBCBBB+CBJCCBA@lC,CCCA@A BbCA#CBCC|CBPeCBLC4B}CjCCB@@BCWCCCC5AABBB0BBA_C4BC A@B CRCA CB<(BC0CBC BQCBAACpABB8RC9CA@BB:C1CBLCA$BLGC{CBAB<BB<B` 0ABC4BCCBCA/B B ~C1C7C@d@CACC3Cl9CA $B%CBBpBC CB(C,B CSCx*CBHB.C CC`CBCaC(BTC1CCC(ChBBACB@@*C C@BSCBB3CABBpBtC@ BCB|B|B`C8CBBCB?(BBCC7CPBBC"CBCBBBCaCBB0B@;CB4B\C4BCB-^CCCB$|C-BC0ATBBC6LBJCCLCBTCB^CBHBPBBBC|BBBXBBpBrBCAC0CrCXBP\lBACVC|xBLB!BB0`BTBBBB ADBB CBB@x4BCB&C$CGxB(BLBcC#C5BCBtB`ACCdB,BCBpAABBC|BTB`AB4C>CBBCCPBBL4CBLB4BTBCBBBB CCAD<@CBBlBPA>CXBACB?CCB`@3CBC BB@AkC,B BB0`8 CHCA@AlBB` C;CHCC@$BBB( CBAC|B/CBBkCpBPC\CC&C4B B_C^CTBBXBBB+?BhB\C&CBBBpCtB@@BtBtBBBCTBoAB?@B?(BA@CBC\ddBsCBPKCA8BBEC`BAABABaCLB A#{CBKC3CBu[C_B@BBhBB$ABBKCA@C ACABDBCBdswCABpBB0A.C&B`BBXB<7C0AtABBBAB@P@BCBBA\0B(BBABA4CCBC;CC C$BAXBB]AC@A\B BCB0[C,B3AWCBCBBApAdB)`CBBN? CECBB~CB@BwBBBCAhBA C(pHB B!@iCPBBB4BBCBAEBABHBBBBCABfCBKCB AxCCCCtvC(CBTBH@tCCBB CBBCBA BA`CA$BACp4B8BBABBPBBBBAhBpABB\B(CC%C0ApA B BUC A;C(CB8BABBBCT%AB(#C|BBAd*C9C0BA)C>C&"BuC@5CLBAdCC4fCCDC#CADBBB!BYCAKC* pAABBAAwCDpAC@DBB A@4Br0CA@B+MCCpAB4A\A4BgCD2LC|C\4CC ApAB@B$BKB4BAAp' B?CB`CABBPAYC\B.CDC@@\@C%CpC Bl0XBBHBB`B8@0BBL@@aBXB&CDB@B@B8C@@BCC@B?[CCB CPB%`A BqC C@ BBBCCABPC`ASCLBC@> A5:CBB2CEC/ABTC44BACCA4BmCCt9C`ACBCMC@@8BC-C` dBB0$B F$B@/CB;BBCAp6CACB0Ah8BCCACRC PAB%C@@)>CB,CCACBBBBRCPABABSC'Bp`A|BAbA1C:CCB?h A CC CCgC?0CBCBBGC * BCC@AD@HBBHB 0AKCCBBCBlBCBtBA.C 5C0C|BPx CA `B@dBC,BBBBC>CpBBACBXBB B@A\B1C"C1CBJHCECAB@@5ABpABACB8CCAiCBBP0BPBBBB0CHCC<BBACB/+CB&A@{CC>AABBACCBrCGCB(TBC CCC@CB?T@@CCACllBCBC4CCB@@BeV@CBPB @BB@BAC`AB CBB CJCA A" AAC(B CPAPBDCBCB8ABBBLBB,B$Cj)ABjCC(BC C@CBBC@B;CBC+CLBwIB C BBlB bCCA$PBBBtCC==C@ABlBAtCBB6CAlBCxBC CCB6 ABHBBC|BXCCPA(@AABCBB HCBC BlDBBBC B8BNCB8BB '<BBB@A7C(BA BlL4BCZCC1C BABd8B|BBC$BBMCB|TB B<LBuCBCBBbCBABhB BC?B"C@BABBBCC\BB|CCBB C7C@B1CDPBBdhPACABpAYB.CBBBBHB/CA6C-CCBCB2 CA@C9CA[C#CC CBCxBPLBBABBpBBA(`C0CA A8C\B`BPBTB@@$BXdCBAB5TB C@B`lB0B.CBVCB@4B@lB_CBBAMC%C8BBCBJC0BBB CB?TJCjC xBdBAB PACCCBBpBABAlDBCCOCB4B0BAAxBABaB]CBBA7*BA(BBB CA~CB ABBcB BA0@4C:C"CpABBAB`(BBBAdB,HBTBCBXB B BA|BBB4BB\BC(CBBBXdCABAABA lB BB AADB-0ACB B@ABCBCA@p8BDBB@FCBClBwBACBB'C" BBCXB&CBBBBH@@'yBNCACCBxCB`BBApBY@B0BBG?AAACB.$BpB3C`A\BHA.CBAHB BBCPB@BCBpANCBB! ATB0C,C@p`BTB\)C B,TB0PApB\BBCAFPA+CWC Cp%CBdPAABBBBABBA`A BVC(4B@@BCgCnBCBhCB.CBACBBB#C CBAv\BC,CxC.TPB C.dBB tC3C@A@AA4B/CuCB C*C0BHBBB'CBxB88B &CC4A<8B!CCjC CyCCT<Bp4CB;CVC<C\B.C8B+C>CCtCC`Ca'CBCB*CB-CB PBB,BCCBB|CBCC@@/CBRCBBC6C,*CBB?CJCE:C8!BOCBBjCYC@LBHCBtBFCWC`C,BA?BBTBC@@BoCA5,BBCCCHCBBB@BCQBCCBCB@BwBbCB4BCH @8B+BxB=C\CHB;0ACB'CheBACB6CB3CBBB@pA4BBGC8B0ABB"C CA>CAA A(TBqC3C+CBCA5BBB CCBB%CCC`A@B B(BB@CBBpA@BBBA0C B`CBLBB^BoCBB`BvCA`A@BBC&B*C,BGCB`bCA@QC@ 0B@BBB!CKCGpB@ CC@@ B BB@@ABTBB CP5B%CB$C)CAhBBt7BB>C `B5@/CECB,CBBABBZBCVCBCCBBKCpCABB"L{Cd$Bw@A A.C&CHC DC$C|BCDzCCBDBBLC,C `A C8CDBBlB@A|CB(A!CnCAMAkCB;CBA`A,B3CCBBAB BC`AC6$xC: ABLCA4{OCBAB:BCCB CC|BBABB+CeCCB4BA\BCABj|B+C AABB8B BCLB04B@@C0AW\BCBpB0G@0APBBPBA@pB@B` CAB@A A4BtBC'C@ACB!XB@ApBBB0D BnCA B5B 7PBBClB~,B CBB[0ABdB B48BCPBBCpBAABdCCB6BCD\BBB1BC<hABjCC`B`CCJC\B@B`A`BC9CAABB0jCCP%C CBB0XpBBECBBdBl C\BABBDB`BC@0AAkCCBpBiBBdCAOCx$ sC`C1>CLC(B^CCAABCA/At$!CA\BdBA@lB5bChB@CSCnCHBG$(NCBB#CATCC7C tB?CBB,BPB aABB C=CB(BCA@0A0BC@B!CB!CAB`A CjCBB]CCB"CBB`BdB/C@ pBC#CB&CXBCB/C8B/@B(dApAD?=CCBB-CC@BB`CC8B7,BB0B^C C\BB@B&BCC`A0CCpBpBBCBGBC|BPA"A@tB BCBBBC BHB`BA8B0BAA B5 BBgCBBCop` AhB`AB4B]UCBA(\BCMCPA!CBBA]xBB4BhBC HPBxBbC@%|B0BBBBHBB@A BtiCKC<PCJC0,BB?C@ BBpC C mCBB@jBBBCBCA B1CB&CCCB\`BIABlBCA AB?CAATC!C.CC% ChB` CCYVCBB ABBAC@@BVCB DB*C0Bp,BBC@B*CC AB\CTB 8CBBCBdBBBCECB4BBWCA A@B?C1C:PAB pNC<RC@B CBA<0BPBpABBBpABBB+CPC@B4BCpAAB B|$CxCA CBC`BtBB@CChB C$BBp\BB%CBB BB LBCBB dBmBgCBA@AAA$ABACB`ABBB`AB@?CAdB0A{B8AWX8B(B@LBXBdBCx0BBBCxBBC\CuC@BBC,ABwBBBCBBbCCACFCA.B=CB~nABB@BIC4BCBCTbCCT4PBB0 CrCABC@TC@pBA1 B$A0A0B8B'A(CApLCBCAPBB4BB8ABBChB BHB@B4C#CAX(BvC`@B!CtBbACUCLCAB8BPAA]C@tgCnCAB\CLC B\BNC`-0C`BbBxB4@C H@FCCBC0AA3BNC}CAAA~C7CP"Cm$BAPCBBCCCBB BSAB9CC@BFCC`BC(BTBPA|BX"B$AC@kBACCC(O.CC0B?@BA CBB-BBpBCCOCCBA(|BA(BPxlHBBCBP@pB8B- BtBBBTB9CB5CBCB0\C0APPBB,BXBA{CP5A BDBCB@BfCpPATPA CAB %C CBZCpB(B[|B0A_CA#CBBC @BC~CB@pB CB`A@A)BB`BB@C?@,HAB.CLB C~C C}CC) AABCB:xBX8B(C%C`TWC.CA)CHDB`JCrNCBChBBA0C|BNCBABA((BBAcC @7C4BCC BCIC"C CBXB@,B`BC  ,I ApC`CpA(VCBBBACBxPAoC CBCCCA B`ABIC_CHB@AB CBA0BBCAB`AB`A#BC$&A<HCAYBOCBBB)hBC`BAB\BB@u0BBPB`A\B#CCB B.&xBzCB=pA@pdBBBdB CH@pBABvCHB`AB=C BBDBCAPCP B4B#BB8B.C0Bb`AB$lBC" ABTB\B1CoBB dBAdBBXB2CABCC4BB PCC+CLBB@B(BBCCPBCB\\@C0`D CxBC@<B B BLCB9CBBC$CBC0B4B@:BB3@ CCA$CB@VB)JCBA%BC]8BXBBB,BBB2CBBA&C(BB8B CoCB<BC CBjABCB$BBB C|B@BB44B+&CB$BB AAB0CB AlB BB(0dBB{BB@OCXBBBAB#CB@W\B`C-c$BBBB7CBBA[C$BABB %TAPB/oCC@A\<-CTBhBBoCBBBBAxBCBBBA4CxB@A BBB@BB BB@ph B0\CBBC&BAPACTCABTB`A30B,B\B0B|CCB(B<C UC8BB!dBABAB\BBC4B7` A^A'C BWABB` [CAB @CBBCABpBO AAB2C^CB: CzCB|A<BBC\BAC B4p$)CBBB >MCBHBHB0AABBBjICBB@AB$C`BB`CXBB\PCC0B`ABA;C9C C8C\B$BPABBCtB~CCdBBABB8BBLBRB&CAdCCB0B(hBPCCHPA4B}CBBBBB BB@C|BB8B\ABB(OA*C@BBB CPBtBHBhB|B4B4BCPC/CBBBCH6C0A BNCBB -CBB<ZC< CB?B PA`A`0BVCC*B?CB\A\CD%CBXACB@$B BDBCBBCAKC@ =B0Bu$CCdB>CBCAC0BACaPBBBBBBAWBBrCp7C'dBABB CCBBAD8BXBB0TwCC_C\B,?B4B$BB9C"CCCC AB CDBdA4BtCBDB2CDB!CPBBC@ABxPCDB4BNCBBBCBrPXBB0BB{AHLBBBxCACBB\BPBACBlCBCZCthB9CpAlBC9C"CBTBBRB>AB AdB BAKCBLBBBpBBBpAdBDBACUC`ABLBpBC BC CBCB"CBBCo`@B,BbCBQa?B ]CBa)B0AB$BM B]CB BBrC)A8BCB+C8BABjCAQCpBBAfCBpABBBBC7C$BpA@B.BBB2CLB0@AB@@<f,P CdBBNCBBpACCAhB|BABtByA8B0B1PB!CB0BATBPqCC?4B0BBBBBA`AC$tCBAjC(Br @BxBB@@kCAeB`RCLB@@A@A AlCBBACC CB/CB0LPABLACB C,BB|B0ABBdBAB07LlBBBApCBCAP0CBBBA@aC(0\BhBcC4pVC@ ?4$C,CdBGdCTCx@B0BBxBpACDHC0B:pBA@D>9C1CCdBCBBxCt @A C%CBACBpABPBBCCBAp`PBBmCACBpCBBBCmB$A(,B+CBABAC B{pB C<BBhC@B B#CLB/BABdB?!C@BlB BBB;@<BIBBtBYC3C^BgCBBBBL$CB@)CA_BCABBdA CTB CBBAAAuAA@"CBTB+C@$BABAApA6`BBACXB 9pC BCC CCPCBAKC&0AC@,PABBCCLB@ BB4BCBRlB@A(B8BBhBB`%HMCBACA XBdBABBECtAhBMCpBBBp`B$B0BUBpBpCBB|B,C x?lBB@ABBA@pWCBBLBMC\BS@B`BpAlBH"CB\$BGBcCBAUA@@BC@A8BB|BB|DBCALB@CABBCA C"B>lBA@;CCB B`pAB@CC[Ip<XBBB~04BBBCBNCBT+CB9F@L CCCCAcBB\B,C<=4CB@XBA8<B0ABB@#CDB):(8BBB$ CBCAAfCBB@B0BABCB CXB%(C,_XBBBp@BCBpABBBBAAC@ |BALTCd`BB& @CPB BADBCCCvCT|^CdBABABBXB+BBBBBPPoCKCxCB8%CB'AB B,B\xB,BBA$ BBBBB2CB8BB,BB BBXB0A=CBBB B CB@@B@BCCPAAdBJC,B8BBZDBpBSCBUT#C4B@ `AFCB9CBC|B2BpTCSCA @CA7CBACBBP$xHlCCp@ @BB1C`cEC,BBTBhBBB6CXA;CBBB BBABKA`@nC7CBLBC@ BCH BmCxB.CBB}]CAC COC`B`B`B4(&CBBABP@AABBU @@5OBHCB AtB\BBCB,BBLBBBB@1$pACBtB,0AhB7LBRCuTBB,|B@A BBEBHB7CpBS|PC.BACB@ACGT^BBA?BpBAL0BA`BA(BPB9C=C0DBC.0(BCB BB`BdBCCVB@A-BA 0\BACB#CCB C@DBADA ClB%|BBCPBBBoAABd%CVCAAH0ABBxBBl@B B(C.DBPpB@B< BBCB.C@.CICAXCbB$BBCC+&C*CBCCCmABB+CB([CLB|B~AP( BBB BBBCBABBC'CBCAB4@tABCPASCB$B BA?BhBP{C ClDA$CB@@BB QBBB DlBB@@CBABB@BCD\BB``CHBBB/CB$HBBpBBBP,B@BllCB ?BCBAB:CB?_CB8BtBtBC@ACB4aBBXBBA(BXhBHChBBiC?CC@@ABCBChBBCBM ,B.C4B@LBCBVCB@ACB(C?7C@@CBB0C A C@(BBgCA*C5p$LB8 BCBBC,CBBCaBB 0BHCBBUCA BBL>C8BhBABPBC0B5BCLBDBtBhKCCAdBB@@< B'C@BGCC/DCCMCpA@HBhBXBB@ABBLC@AB CpBB0AAlB8C@@BC CCp>CKC!C6C@8B|B>C @HC8BB?p,CWClCB$BCBHd ACCdBBCDBlB20CbClBB-BACqC@]6C$C.,B@@C1C9CAABNC@LB?PA0BABB BtBHB4BXCBlBBAAC4AA. B)C?<BPA$BB`BBBOC8BPAA@\C4 XBlBAB A,BD`>?C ClBPA0AB CBAXBACdB,BB`AA(C%BdB0APB@C0HBLBVCBB`aDBBABAB^CAhB?TpBA7CB 0@ CCTBB@@C80`B BBB9CABB BABtPBABCBBBA\BtB3 BxC C(B@A@TLBBBLBBB+CAdBClCPBdB`B`XBABBAA`BpBAB0BAB@ACACLCpBBBBpHLBB CAA`B\0CB C5&CBT(AhBp-+CB @BA$CA CBpAB&CABBLC CA B bCBBBRC@BIC C@sCB;C4CJ3BCAB&C@AJ ABBLCBBB<C@@@ADCBeeCB3p XAABA,CA@BpB3CBG|BBxBBBACh CBBCB BC&CClCBDBCBABBBB"CB3l'CBBBlBB+ClBTB4CB@@?CR04B@ BBBBCCBB0B0CBrCBABBdBBAABCWCp|B-ChBC@pBBhB7ACA\BA0@B0AxBtB]C"VC CCB@A?CBBp9A"C@AAAdBAp KCC@BBl$CBA@BABA<CBB@ \DBB@BC&CDBBCBBlBC@BCZB `CA C<XCBBpABlB@HHB|CA"BChB\hBXAB(BC@BBA8B_CkCC4B-<ABTC0ABDC ABDBCC@yB,.BCsCBBdBB@TC C)CA#A`CCPA\B@hCBBBx@A4B9bCTCFAlBTB@CAYCKC`B,\B@9C@@]CB pBdC`AAhBPDBAQCPB{A.CD)WCBdBB@@ABCCA<7CC A@@,BPA CCABBCCCB,%C@BB. CBB?,B@BdICB`CA"+CBBCt@@@A4CDClBBU&@@,B#CCBsC"C @KCCAFCC%C`A BhBCBAB@CB4h`VC_CAA40C@AdA\CBA`A@%CA@B%CBA1CVCL#BlBAApB^CBlBB\BCXB4@ACB@@C&B*CBHBm(hBACC CB AAdB4DC A(|BABoC@@ABC` P@@@B@CA@B\BBA'CBBdBAB`SCBCB8BIC<1c C\B=C`AB` |B;CXB8APAABq0BFC5(B1CA/BB|+NC\CB$BCQxB||P@eCBLBB!C*P@B3BHBA{CB5@BBCpA?B(cCtB]xBABABBBBHBBAPWC {CC4LB0B$XXBA BB.C.CcB gBB|CC@ABQ$BBB!CAdBB,B-BB0AOCB@lBBABACBPB0CBB ABCg,+FCCBtBBBBtBABB%44B@,CYCXB@@BB|BCACB&PBXCpsBECBBPB0C A'B&ABBBAAxBLBCAC$BEBNCA(BB,BC@;C9C%x:7C C\`lB`B.CC7\,B1C)P4BxCC7C(C/CtBpBUtB[CXCC(B&B=CIC4CBA@L_CCB|@BA(ABKC | C@AB0CB#BCABpAA% BBBAAb1CB /u_CdB@BBBCB2C\ABCCBC@@A@BBXBBlB/(B,%%,CBABPA0BAB@CBBBBB@B1C$B BAxBBrB@AEXBB C4CBBBAPTCCBALB@B AB@Al@@B8B@BB8A8B`AB0AX0A,CwC4B=hB@BXBZB.C0B>C<:C@FC0B`0B*$CDBxB A0 $pC$CBB'B(BHBBCBBBBCB B"CCtB C84BBB@A(B?#fYCBB\BBMBBBBXBBHBAbCC`BPBBACxA`CBB?$7A6C05AC4BA@d4\BBACC`BBBiCdB|BpT(B$BTB BxCB@CBDBB/CCCpBB@ANA!C8B* CA? JCCQ\B`@CBTAP@@HB@DCB C7CBBBPB A+CBCBTBBAVCA,mBCBIMpNCCHBBB5tCBBAAB`BPB(BB1A`SClBBB@B`BB`CBbPA$xBRCCdC CB(CBCCHB0AB|`B| CDBB@pLB$AA`ApBCBHBf@BHCBHB$`HCBCR@|BA+CBA\BCCAFC`ABBtBBCB$zL B@@qCTB(/@ABD\8@0xB@BFBpACJCLBBBB\B0A:C`\B@\BA<`CCBtBACBCBDBKCB`%8B$C0B)=`BRCBAgBABBBP BB@BBOCBACB CeC@PBJCC7CB$CpAHB BBB`DCCBJ CCCBBACBC"2CB]C4BBBdPA BCpA(BCBBB{|B B$ClBBxBPdBA,BBtpABBB`BWCWBH C@BB@A!CBB@B@?BBEClBhBCAPBBB BBBX`ABA?!ASC@CN4CBBC;CC+AA BB0AA\B\BAdB`&C?A0A,8BBBXB@hC`CL`@3CB.ABPB,CBPA+D BEAlLBCJpCB@@BA0BB@_ `A\Cta XBPp\BBABLBA@|BCBA ACCBd@@B A&0AB4C`B^ClBiCBTB \BC CA>CCVC BVCB(By@ABA`A\AB BBBCCB0AC@@BBLCA0BAA BB;CB(BAPAB!BBBB@@ C?CxBBhAC#C ABAB,CrLB0Bx>$@BBBA lB6C<BTB`B-CBCBzC>CA6C`BqCPAA0^0AtBdBrCB0@`BPBCBGCBCCOC6CBCC\|BBdB,BB$CBLCAC`BBBdC,\DBB4ABBATC<0B8BB@@B?.BSABAA($uBB2C3C@BBAACBlBtPAPACC@4B`hB!C%CBBCBBC_C% %C8+@DB B<BABXBBBB A,B*CBBBB!A4CBDC8BBBAABBBtCBB*CHA@@CpCBoCBl7CtBdCAdB@B>CBB:CBBBB CtA`C&CB@@ CTC@PB|%ABB'BBPBB?lBBDBCC(BBtBBPBPAl`ACC|pBBABC A|[CADB1C@CB@AB&BA C BnAB0BB@@C#8BHBDB&1CCCC(LBC@@mCABPBB*C(BpC0BYhBBBABB`A BABlBB`B2xBBB@TB(pBHBlBB B C <AA:C?CCCB" BC6AA}C(JPA0 B%C CB,DBC4C0EC,C 0PBtpBC/CBBDBQCAM0BBCP@CBBFA|CAP=B;BC?A(pABB@!C4BDBALBAxB@ C\Bl@@BABBdBpBlCB'CBBABAB,n|BABCBTAABA`CBC sBBB4DBBB,BA/BBBPA YCTB@hCA|B`BB CBTCoBA@@ B6C@BH:BB+CDBCOC|$BBB3CBBB\xBAlBSCCATCTCdBMBxjC BB<Bh@C@AdBH\BABTAAdBpBB\BAA2BB*0/C T CCA`AD8BAC@@PBABB*C<BMCW9C0BPBX@0L`AB$BB`C?CAPA tCBeCCdBpA`ABB0BA8>BUCp#CCB6C@B?AdC BBFC@$AABTBpBSAA0A08BABBBBD1CBCB45ABTBB?C$CBtB&C*,C CB#BC4QCdBC,!C|@B p$A(B(BBA8@Bl|@BpAB#CBC&CC$BBCB!"CAM$C'CCC0BBBBBB2CC h A@ACDBCXBA2B`B$B1C dCCx ?CPB;@ABA,BT"CB0 CCPAB]`AX,BXCBB.\,B@B-BB/CBB|BCBBhC8BB@A(C1LpARCAAABZCA Xi`@BmCC@BuPAxB8CB`A5CpBBP@BB@BB|B`ABB`9C4CC$BB@9BAOCJC ,PA{ClBtBB4/CB0 `C(CPcBCCPBlBPC#CLB@AhH0BCXCkBBXBABTCBA@lBBABL BA0pA`B_CAoB B@ABBBCLBBC>4CCB30Bp7C|8?|C\B?0CB`BB@ACBA'CA"CAABCtBTCBB$B@ABA C0BBAAPBB 8BBB,+CBB*CVAhBP,HB8BBAAhBCAlBJ,B <BnCTC@A@CCBP=BBBBBbTABBLBLBBB8B$BjCC|B$L6#A CBB0AC~BAAABB5B`ABzC C'PBwCDCBC @4hB4B|B]CoC BlC4C&B(BbC@,BBA%CC @A@ "CvtBCABBBMC,Bk uBB +tdB B 0ADB@@B:hBxB B$$CA C `A-CB@pABBB.C,CC1'BC:A$B@=CCB|6;C BOCBACA)CZCCB)At@@LB BPAHBACBC0@C)C>C ~CCAC@&C0APB`BBBXB BTBJBBCP,CBBvCCBmBUC`BjCBBC@C\BGCB C4HBB`8BDB.CA|B(B@B0BB`"C#CBe8^C@BBBB>pB_C0B|PCBB<&CHB B\BA BCB`C?AB(@ PBBC/BB A\BBdBzCpB8\Bp$XA(BB1pBBB@BBQFC<B`ABk?TBBBdBh`LC\A4TB`@C_CB4BPBCBB\A@ECBABBC CBB`BCB`BpCDB zC?<@BBAxBaC/CABBBBBCC 8<@hBBWCBA,>dBBPACC`VBBBkBRPBiCA1pAxB`BBBAJC C4@BBAB$BPBVCBBB"TA@B C @BBB|*B CA@ABNC`BBB C&A4BtBPB\BvCpH5CCAdBDB-C@A,CBBBB,TCp$0ABB6C/C'CBa@xOC_CPBBy5CA6CC BC0A(B,kA CBClBAQCB|p8dB@2CBDBFPAx0BBBA>CjB1BBBB,B|C>CRB7C\BBBCCC0CBABTB@B]CB@@CPBA@CBXB(BBpBC2CACx1CC"CB3PAB AA@BCPB B@B@AP(CBBBC`HBXBB@@IChAB@BB B@BL9CB8B d0AA<ABHB:CA(BDB4CCC,B7'B2C<BBg0BBA<P.ChBAChBAC0CABB(B@B?CrCBAA=HBBC*C8aB@@ BCpBAXBR-@BCBBBl AtB&`BCBB@@BBT@@ A,@B>6CCACC4TBBC)C@@b\@CB B@,ABPB@@AC@@pBBBBBTdB#C*C(BAl C0BB |BA>ClCBABB+B`BC`ABlB#CxmCBBcC|B,CACC:CABC$|B3BABB@AlB8B@@U !CBp BCAp BC@A`AlBiCBpBhBBlB@`ABBPBB CBBBC BTHC8KCBCBAtB@|BBLBA,BCCNdBBBB@ABBB`BBBXBp\BBCB@$BABB BCBF`@L4B eAArC@A@B CCHCC$A@laCCA\C C@PBPICCB BT0BBC `AFCBB4BB`AB$B BAABPA`BBC@TlBABK,CTB.CA"CB@ BCBHBBBPBBPB?PBB\B@BmBA AilB CBTBB C(@ACXB$CLCoC2BACHBAxBBCABBlBCBCCAA*CAD&CABD@B BD`B<8B8BBB|i C@@BA0hBAC pPBBBHB` B BBdBxBA?(CBBCBZ@lBC4B BB:\CBCBnC1Cp`AA08pAB*C\XChBA @ABBdBf CBJC'C`ABd&CtB@4CA$B%C'C @CLCQCIA+CB,BHBBPA|@BBLBpBC@,B@ xBCBABECBCBAxBC8AAPB:CBBBBB=ABBBBB@A`ABlCA|OCB4 B BPCd!CBB0ABCS@BC>BBBpQC1C@PB@BhB,CBlBBPBBAB4IYU<BOC@(B @X`Al BCBB%C`A`tBA0ABBBABBA@AAABB4BPC#C,B`ABBBA B5CB@?C40@ACCCHB@ABTBlB`B0ABBCt+CHBQCPAHB`AB,BCBCZC0CB0ATqhBB$BAAB@ABCcB`LB`C5CAvC-DBBAB0A@W B.CTBB@BOZC\BXpACDBdB\BpB ACKCpLAMCTCCCBQB7CBBJBPBA@B@CPA *{CHBBBBBBCXAAxBECA0CC0 BBNC6BSCBB{C8PA?`C8BCAPe(BA0D$BAB CL<ABBhB@A"B/CBAC B#CBB+CBCATBB0`B0ABrBcC@AS C0$AA,@ BCC@A$BBCBpBB B`AHB`AtB B@@BBPBCBCBBBTC|B+AC-CAAA(C C0C@PA?lBBBAdBBB,BdB0A0B7CDBHC60JCPBB(@'C$CBICA BBABxBsCCpAB`AB?BAA tBDC@XBCBBB(BT A C`CBB@B0@@B2C@BLttBBpPA)CBH0A0dBJCCPB]CCBBCBX,B`CC*CA%BxCl t `&C,BaOBACB CBFCCBBcB:CNCB \B{CBACBBB@BpBBBB1\B)CBABBBICCJC3CA@B$CCLBBdtB3#CBHBCBBHB B$tABApB@A,CBB,Bb?AAAB<`B`QC,BABBhAVCCl@xBB`6C, xpA6CBB@`B@A#CCdBhBCB $B8ApB CACBjPB`B B lB#8;CqCBdACP|BBCB?BBCBFC0C%CBjC<BwCBA%CCCPABBlBX CCBnXB(CHBBBxBCAlB|C3CBp@BB!C8BAAA@A BB0B8 BAdB CB(B'C 8CB CBT$BA PgCBBBABpA&CHC$P0A@BCAlL<XCBB BB CBC ZBBBABPBpA?ChBB0BBHB4LBlBB,CCC`B,BDB$BBA BLBADBAB BABBB3CBA#B WCBpAB4BCXCBtBBBCXB?ABAl|B,&CBCBA0ABCABBAC|BPBC|B"CBSABF AB@BBB0BBB$C@dxBB@BA@ B1ClBHB BA4BoCB`BB C@B4BB@B B`#CBBABBC<20C A C8tBBB6CBIC|BAHDCphCCCQChBABBLGCTBp0B|B0ABC ACnBCTB AC*C`C5CBCBB8BXB,BB?C@B`BLB CBCA7 C(CBBZCCpBCC+C+Cd8BPBA0ChB,CCCC9CBC A`AB2BC$CA@HBBBBBB\B$PBPABBB=CH0AAATBt@@AABMCmBCCdB@BXCtBBBCAP0 BpAG AB0BCBBBBA@$BVC@@ABCBPBPA@AC)CBdBBBAXB^C8CC3( B>CB CkCB\B0A@BCQC@@`BB0B-CACABCmC4AU4B@ABABA A@BCCBCC0AC@PABB @DC4@)C CBBAACA'CBXBB@B`BBB0BBBB8B!CAwCCA=4BBBPA7CC0BCAF A=CB@<QC|BACK7CBNC$CMCrCAB@BCBA7CPBLBAAA@BABBBCLC0B$&J4?PBC/pBtB pBBhBBBABLBCKCCGB@XBA|0B@|pBB CHBlBKCBA CC!CBpBA`xfCtBA'CB9CX@B`CpBB@ CBABOCCG$BL CA0BsCtBDBAlABCFC;Cp ADBPBBpB=CBLB`AC$BAXBBBBW CCBBBdBsCBBBAhB,CBAB,$BA0Cp|BBBB pAC@Ai3CBBC8BAB_B<BBB)C Bl@BCWCBnBBBB%TB@@ABBX@BACHBBC1CACBBB@BCBBXBAB4BBB ChBApBCCAPAAB)C.C`B8BB3AA!CbCBAHBTBzy,BvCQC5C B @lCBBpAC@AP<A\BAC Bp@BB$CABB0C0A%*BBAxBA#BBBB(@%\(t?lBBBCB=C`B CBC BB\x@AhXA&CBBlB9AB?C KC$BCB (?,BBpCBdBCC@BCB`BB; BB|B CB/C`BA0A2(CB_CpA@tBC\PABBB0B^CBpBB uB@CaC_4C5`@BClBBBfCC4C$?$C A.CC CCB C(pAmCBBACBCTBJCBB(BCABB,BBBBBCBBB@AB\BICP BB6CA[CB|BBAxB@?0BBZCBtPBCxB&3B`@@xB@DB@`B ,B\Bd-C@HB<CBRxC-CWB)C#+tBCBB$BA\B@@@EC@BC,BsCBeCBCBBKCDBdBC@pBCB}C#CV$B C$Bl8BBC0ABl@BBpdB\B0BBBBC0@Bp$BHB,PC;CBAB BBAW0BBB@B`AC@@B`AyCABCB3`B+C!CLB"B;CCB`AAAAA\ 0`AC@BpB@A0AC AC%CACpB`BP ACAB,"CBpA`vCC4BC@<p@BBCpA CBABBd]@CC$BHBCB(BA:@BBBC0BA*B#CBC Bx`EwCC'CBCprCxA"CCAA CAECpBA`ECBBBAXCB$BB({C XA0BPACBCBnC<CBCTCHBCCLB\BBC@ABXBTCBCBBCBBHB AB@BB CC|B2BB'CLBBABhH`B<cCB,BA)C.BBZC`BXBLBBDCCkCpAUBwC&C` C4BBBC@B@BACBBtlB@C'CBrCBCA<B4C_CK(BCgC`AgC@D0A:CFCCM@BtBCBCBCXBtBBBB]CCCBCALCEC4B$BAPACHAABBB3CA4BBB C@0BAPBJC?dBBA A@pA4BB`B,CdTABBBBhC@B@BB+CB|SC?CB`/CVC B0BBAB$BCCACB0A @Ld<CCYC4BBC|BB@ A(B~CCBGpAZCCBgCA$CAA CHPACA|ABQCB0ClB@BB0BiCLBP8BCA8B@0ACABAB CCB SBBB@B@,B'C@|CB'PBHBBBiC\ABqCCBBBpA@hBA0A"C(B?B@ALp0B0BCC ,B@B@B(h B#CLBB@@AdC+CCABpBBBABLCC@@DB@ACABCC@B$sCZCPA= "C4DBHAB XCCBBBAA@4BCCBACATB'B(BBAADTBBMCB|A8B+CTC0AB@BCB%CCt7CBBAChBPBhBAA"CC\B/CCAB0BBBBBB@CBCBBBA-4CCB8BA#mCALB`BABPBBPA@ BNCDBjdBC8B@BAAABC^CBBCC8KXBPCTBBB@BDBB8BB-CBDB@TBBBBBL0KCC0BC1C?CA C B D8CBCBB*C`BCC]AdBC`CBLABBQCPBBBBr":C C0ABBEC4BBC @ CB+CBD TBB2l#C@B CrCxApBCCvCBB\CB@CBBA!CBLiCwC4`ABIC+*pABApAC]XBC B(1C$Bx-BB2CALB\CBRCtB(BCBB\BBBdBB*C@C(C0BBXBA]C 4CB C+C@CB0A0BC,B(CB`B|BBBBB'2B@A@CBLBBB`,0Apx,BZCl$BBBBBXBlBGCpBC n3CCBpB?CBBBA@ABACCB[CA!pBABCICPA.C@BBBABvC$A`BB%`BT4B C@CBC@9C8AB B!C5C@A@@CBBB%CCBPBB0ALCBBBUCPBBBkChC<UC4CB.BB"C8CC CBAA@BBBCCB:C4tBBB'CB@B@BB<A(T%CA0BBBVC ALB@@?C'8CBBBBBBBXBAB@BBYCmCAKB7CY0BCB B0BB CB`AtBBBBBBJCYXBB-C)C3CCPA;CpBhB|C CBABBBBBABTo)AICC A\@4BBCpC, $4CB$CCxB@A*CPBB$B(BACBAA$ CBBB@@pBoC@BA@@dC`BC8`pC[C$C C=@AxB CB+B@BBpAL4B BBLCC0BBBAhBB BBBD0%ChC CDB@B=C>,C}CC_C:BBVCCzC@TBBABdB0ABB /Cx0B`B(BB)C0ABCBdpLA CBBdCX?BBCBlB2CCLBBB0BBA!CCB [@@VCBvCCP8BBBwCCBTBh?.CBCBCC ABlCCB CCDACABBBBACnCAHBBB|@BABCBBCBA$B$CBAA;CABB)CCQ/CXABHAC BHBQKClIC0CBBAAdbCPB*CBBB0 CBBAC BBBCB\BZCQCBPA`A4`CeC8$@CCBBA|BCATCbC`^CA#CBlB!CCB CRB)C BC9CWC (BDBLBBpBxBH@0B#T(CBC*BCBBBB7CCCCECAAB(CBA,BBBBABB\A|LB%Ct4B@ ClBC\BBB C`\BACHBhBA(CABBXB HCA(CkCCBB@XBBhB- `\B0B?4B@CC`(BLBBCBDBA1BBABBA@$Cl@<|WCYBhC@A`BC8B!,BB'CBBmC CBApBB$BN@C A5CB,CR*BB!CBB-CBBEClBB[CgCkC<CjCBtB 8LCCLBACABB\BBBBANACiC?BCBCB)l)CpABBLBKCC YCAC@B`AA-CACBPB4C4BC5C`BABC0BLBP@BDApA"C0B\C$B C@@8BA? BGC@B@A4BCCCCBB!B CBB0AA@ !C(CCB^PBBBBBC@8fC @BB A CBBb@@`A$CBBAAI CAABAB6CGT,AxB CC ,9C*C PC B0A%CABLBpBCABQChBBA@BA4A!CAB`B@@BAB$`AlBAQCKCW4 CCCA?CCCCBAA0A4BBBC,BLALBBBBSC9C@BB\B$f%xBAAX.pABB4B@@d;CBB$C$BBBA@CBCB@xBB||B0B CB B4BC A`BB C:B(C@tBPA)B^C@B+CHOpBBHCpPBqCC^C,B)BCCC0$tBBBAtCAABBAh@ABB0AB?B@CBB C,BPwCiCA4B BBHl@@%@H0B B#CB=BCBC@@?lBACAPPBCTBABkCA\|C@0BA B`$CBCAB(C($BBAt,BBBHCA D:C_C;CNCB B:CpCCB C BBC@IBBNCBBT D0,CXBBC@B`@Ci@jCA8BBF,BBBC2C@@BBCCBC<SCB`AB@#CYAB)BR CBB#CB\CB&ACB@CXLNCBACsCBCPC+C,B@B5CAAfC;CA@B:ABCCt@BiCB,BB,CB9CCBC7CB@$BA6CB@C0xBBBBB;CLB BAAABAC0CCA lBCPADPPBClBB0C%CBAOCB`ABB8B%CGC@pAB1C ,C BBBABt(BBBBdB!C C7CB8BBHCChB%CCCCAAB'CC)C`WC4BBCBBCC6C,Bt?PCChB@BTBBZCpBB(BBBCBxC8BCTDBCBBBCB0BdBDBBXB$B @BB2CBBB`BB7CC/C)CcClBBbCAClBBC$B(eC|BCtBGCB4B|BB0BBCBApACC C~C0C@B@BC$ C#CXB BPBBdCCCC0dBB CXBAC\C`0B C@B>C-CdPBCABCHh CCBsCA3CiC AB`ABJC\CBBATCBCAxCBC]CpBC$B CBBzCCBBBCBBABB@B0B,BC C(B4`CBICBB=CACzCBB@B $B@CBBpBBBA @@BCC~CBNC#CWCzCB CLBB$BBH`BBBCBBCpAAB`AYCC@CdBA-CBDBBC%C{C@AC%CBBBCK NC C^CB=CC8B9C4B@CYCACPBlB`BNC4BBBBC5CBBB*7CCeC$BBZCCBCECXACCBA~CBBT@A8CB@C_CC|BBB0CBCHC8DCC BACB!CB"C)CCCBBBBtBGCtB%B@@LCyCB CCBB`BBBBBBBA\BhBBBBB4CB/C'CB$BzCB%CpBABrCACBPClBAQCCABBBlB$B@CC4C8BBB`BC4BA`CpC)CFCCB@B0C?C'C0ABB8CtBBB3CBBCCBHCTCC_CABH@BOCCBBBICBPAB0B dBB`ABB$C[CB*C@-C6CJCLBB@B`B|BuCB CBB'CPCCCBuC0ATCCBC-CB BBBoC$B9CABC0BB|BBB8C\CBBB&CBCBHl3CBACBmCBBBBCC|BB<%CBBd&C;CxBBBAB$CCBADB@ChB!CBAMC&ChCCC+C@?BBkCC!CBABBBUCAACBCWCBECCApBB Cp)CDCBA@4&CGCB"CBtC@BBeCABBBB(BpCOCAHB!CBAUCTBBCCCC)CBCBB+CAB4CB8C BBCwCBB0AC$C CLCB`C ADCkCBAByCBgCECCBCABC@eC B@CCB CC|BBCTBhCB^C:C@[CPB&CBC CCBADCBB9C!CABCA@W0 CCCB` CAxBxWCx@B\BTBB$CBBBB4CABBBCBBCB"C* ACBBhCBHGC(pBCPBBhBCBA5hB~CBBvC0#CB CCbCvCTCpCC#CBbCCBACBACCCBBCBeCpBtBBqCQCBCTB BC CpBBDCtC0BBCAB4B/CCqC~CLCCdBBACC0C`CBBB CBACACC$C`C)C2C7CcCCBOCxBB BAlBJCBBC BB$CBBpABBCC[C ACC%C0BAB=ClBBCBCHCABdC`BBbCAC6CXBApB!CnCCICCBhB@BvC^CBC6CPA CbCBiCA3C@C8B CYC<BrC)CBxCC.C$BDCCBB@CBBMC(BYCC;CCQC`BB[CNCAB]CBBBBACCBBlBBC@AB*ChBCCC$CHBCCCB!Ch CCBhBCpCLCBBBBBC[CCC\CACBBBCCsCeC CCBBBBHCCUCAHBBC5CCtCBCC4CBCBBpBIC^CC`CC,ClCCaC=CBLBCP3CB0APCCBBGCpAGCC CBBBCuCBC~CCBxCB`CKCC@CyCB@WC CCCABCBB AlBC\CBCB C?C^C CVCC3CC.C@%CBBBA;CBCACCCPAAC`BB_CCC5CACBOCC@@C CB|CCAGCC|CBACBB#CTBCBAPBBCCBBB CCB C(CBABhGCB4BBdBBACpBL@PBC+CUCABBBCBKCC]CBCCCCBvCRCCCB]CB B C?CCCCRCBCCCmCC8C?:CCBBtCtB:C*CBACmCBCACCCC+CB@ A?XBCCCCBCCPBBlBCgCC;CCABC0CCCCCBCAC|CjC6C4CnCB5C9C`?C1CeCBBA[CCzClCXBBB_CUCC`BdCB0CCBCcCB<xCCCdCBCB\CHCBVCCwCDC`C C,CCCABCCsCpBBA@CdCJC|CC>C>CCCQC BC_C\CCB5CC|CBBCCCBB CLBB`CCBB CC3CrCCCCXBECDCB>CXC5CBChB:CB6CCCC2CCBCB$CC]ClBBBCCOC-C CBrCCABB!\BBCCCB AACCZC>CCeCCCCdBBC]ChChCH8CC5CCCC8CCBCdCYCBCCCKCHCLCCB`ACCJCC"CBCC!C~CCCC*CBCCCCCPC_CBBHCBCCCCBCC C C~CdBB%C1CCvCBBCWCC,CCCCC C*CCABBBCCdBAUC>CCCCCBBCZCCBBnCCCCC\CuC8BBC8CwCCBBzCCCwCCCCCACBCCJCCCC;CABC,BCsCRCnCBCCBBtCCCCBBCCB@CfCBCCCECBAsCZCBaC[CBC+CB0CCBCBCCBKCC(BpBACC:C@B AB:CC+CkCCCB CBCBCCCCsCBB7CJCC7CCh@@BC#C\B+CBC4C%CCCA{C CCCB\BBCCrCxCCC:CBHBVCCC%C C.C=CB`B"C)C>CC+CZCCtCCUCCA$B*CC5CCDCPBJC3CC8CBdBBB?CCBBCCC!CBBPCACCpBBBBJC;CBBCBcCA CBATCcCCCmC^CCBCSCC8BB$BGCxBBCCBCCCBsC@APCCUCTCBA?CBAuCBBICCCMCBCCB$C@@0ACCC#CCB?CLCCB(3CCCCBB CC CC C7CCB5CbCBmC$B CBBClCBCdBmCB$CBBDCClB@B(B `CCMCCCKCCNCBC7C@CTCCUCWCCAdBCCtCECA@wC,C?C`CCBCFCCCCC@C'CCBCNCiCCBBCCCC+CBCB}CCB(CsC;CCCBBACCBCA|C C'CeCCCB BCCdC5CJC~CCCBDC7CCCCBCUCC8CKCClCC,CC>CCC1C^C(CCCSCBCBCCBTBC_CCClCCCCICC8BCCCCB{CBCCCCrCCBPCCoCCCBCClCBCiCaCCCCCMC.CBCC\BCCvCCClCCfC!CCCqCCCBCCCLCvCCdCBBCCBrCCBCCCfCCCCC]CCCCQCDCBCDCBCCC CC[CClCCUCCuCBC~CjCCBC1CDCCCCLC1C.COCnCCCCACCGCCCC CbCyCCCBBCCACCCBHCCCCCiCCCClChCCCBBCC[CCCBCCC}CCBCCvCXCCVCCChCCCCC}CCCCACCBCCBCCtCmCBeCC5CBCCBCC@CCCABBCCCBCC=CfC}CSCCCB!CCCCCCCCCJC`CB[CCBfCCCICCCCCBCCBBCCOCC&CB>CHCCCNCyC)CC0CCCC*CSCDBBCCCCC~CCC^CpB8C[CCPBCCCCC@@|CC\CBA C{CCeCCYCCCBCLC,CZCbCCIC|CUCBXB{C CCC{C:C"CBCC@BC;CCCRCeCC CCCyCCCBCCpB#CfCxBICCCGCmCeCCCBBCBBBCCC'C(CC=C8BCCCB0C-CCCCACCCPAJCCCD3C*CCBCDCCC"C C%CBCCACTCBCC|BlBkCCC=CBClC"CPCCBB%CBChCBCC/CPrCBB;CXCBCBlC/CCWCBCB/C2CCCC+CPGCuCCCBCmCBB1C6CBCCCpCBCBBCCCCC6CCC\CCCCC@DC:CZCCCCCCCCCCDCBCXBCCCYC{CCCCC[CCCCCC DDCCChCCCCpCCD-CdCC]CCCC4CCCCCOCBCCgCCCCCCCCCCCCsCCCCIC2CCCiCCC(BCCCCCCCCP CCCCCxCCCCCCCCC+C?ICfCCCDCkCAiCCDBC CCCCCCCCCCQCCCCC@ DCCCbCGCCCCPCBCDCCCBCCCCCCCCCCCCBCCCCCCQCCC}CCCCCCCCBBtCCCyC(CCCCCC,BWC|C]ClC\CCbCC ACtCCCCCC+CCBBC9CCDHCCeCB9CCCCC8CCCBCCC]CCCCCnCLBCNCCCCCCCCCUCCCCCuCCCCCCCCCZCCfCfCCCCCCCCCCACCCCC=CCXC{C CCCfCCGCTCCCOC4BCCCCC/C?CpC}CBhBxCCC]CcC9C:CCC CBBCvC6CBCB;CCBBCBCCB^CxCCCCCCrCCCCCCQCC'C+CDBXBqCCoCC5CCCCCC(C7CCCCfCQCCCoCC@CCCC~C&C'CCVC_CC~CBwCCA"CsCIC{CCCCCCiC&CBCwCCDBeCC@CCC@CTC8CBCCBCBBtCCCCBCCCYClBCyCCC{CBfCCHC]CCVC1CvCA8CRCCDCCCUC9CCBC]CCPBCCtCCoCCCCCC0CBvCCC DCBCCZCC@DCCCCdBYC1CCCCpCCCCCnCCCEC>CCxCCC7CBCCUCCTCCCCCgCCCCiCLCCC7CCCCCB1CCUC=CCCFCZCTC8CCC4C^CCC8CC}CCC%CACCCMCJCBCCCC@3CCCCC.CCC9CCBC"CCPCCvCBCCCCC^CCCCCBBkCCCCoCCC42CCCCCCC0CCiCD4CCC0CvCgCBCClCCCBbCCBCCCBB0CBTCCCCCCCAACWCeCCC_CCLCCC,C^CkC*CCBBB"C`BCCCACBdBBCCC3CvCC;CCBCCCCBACCB2CCPCCC^CBBArCC!CBBBC DB@CHCqCCCBC|CBBCtB:CC CBCCCdCCCCCCCCDCCCFCCC@ DCCCCCCC~C?CCCCCCCpC#CCCyCCCDMC4CCCQCCCCCnCCCBCBCCCC~CDnCECCCzCCCCCCCCCBCC{CCCCCDrCpCCBCCCCC:CC:CCCB.CCCBCACC{CCCCCCCsCCC1C(CCCC_CCCCCCCC5CfCCCC'CCCCCC*CiC+CCtCCCqCCCCeCCCCCCBCCBCDCCCC}CCCCCFCBBaChCCCCC]CCC;CCCCD/CCgCwC6CCCCCCCCCCCCCC9CCCCCCCJCCBCUCCICCXC&CCCCC'CVCC_CCCfC1C??CBBCCyC@CBB CCmCC8BBCxBhCBHC!C@CCC&CCCTBpACwCC@ CBwCBBrCVC`B4BABCCNClBhCRCCBCCBC>CBBBBGC7C?CB BppC@CCCA-CFC.CCBCBCCC&ChB:C BA:CBCC=C,B1CCB9C~C4CB!CDCkCB CBCACCCCBC;CgCBCCaCWCCB`CbCrC>CCdCoC0CB[CCCCC'C<CCCWCCCLCB{CCYCBClCBCCCC1CCC`ACCtCCCECABCCSCBFCBCCCCOCLCCcCCCKC CB@ACC3C/CPCCCCCCCBC}CnCBC^C\CBCCCB!C\C CCCCZCC C`CB[ CCCfCuCCCC`C~CC\CCCCCC6C_CA`CC=CBCCBAACCNCvCBTBCCCBBB\CCCCBCB7ChBACC"CCACCQCrC^C CBCC1CB@CBC|C5CBCCBBCTCC1CCC"C#C(CCCC@C0CB$CsCCCABbCB]CCCB CCCCgCB:CCHCwCUC1CCBlC4C#CdClC(B3C0C6C@BB%CQCCVCB1CuCCClB7CCCwCVCCpCCBBCBBBBCCC$BCBeCECCCBCCCgCC CBCB~CBBCCkC1C BCCDCfCiC&CaCCTCCLCBDBB$CCfC4BpCA^CC7C8ChB`C(CBFCmC@B*CCBCCMCC#C^CB!CpBCC)C)ChC CBCCDCCMCBCBCoCBBCZCCCBCRC%CCC CBCFCHCC@ACC}CD3DC$D@ED@C:CCCC7CCBC`CsC:CCCfCCCCC CBCC5C3C[CBCCuCCvC/C&C"C ACcCBBnCtCCCBABBDCCB6CCBaCCUC4C CeCC B-CCC^CCB|CCB9C~CC]CCBC`CIC-C\CBCTCBCC,CMCpCCCRCCCCBCCCCXCCCCOCC,BCVCCCCBsCfCCBCPCCCOCCCPCC%CCC1CBC3ClB'C_C_C:CC @ACB\B9C CBCPC2CCC8BBpuC6CmCzCdBB8CCABBA$CXCCzCCMCCBB@GC;CC!CBCqCBCB.CCClB@,CB^CCCC[CBAA,lCBC CB~C(CCCB5C:CBBBCWC\CyC8A8CTCB$B`B8C2CCAB`B BRCBxCB`BB0BTBABmCBCB*C0ABaC5CBABBCBC JCBBC>C`BB`C2CA_C1CEC CXB C(BCCCC"CxCHB|BdCC C@LBCcC\B LCBGCBA,CB D DDCD2DDDCUD(DD)DCCCD DD=DCDJDDD@D$DD@ DC@D D D DDCC@$D D'D@7D@DCDDSD$DCC@DD@D.D*D*D@DCCCC D@DDDD D!DDCDDD^CCC@D'DC@DDCCDCCCCC%DDC9DC DHD.D DCCD0D$DCCD"DDC@EDCCCECCCCBzCCCCCCCCCC>COCCgCBNC$C{CDC2CCoCCCCCCCCCCCCC(CICBBCC{CC0BlC C"CCKCCTC C CCCCCECCC-C3CNCBCCCC%CBCCC(CrCCCCCCBChCoCCC!CC%C]CCCxCCCVCCCiCC3CC;CrCCCkC?CCCCzCBjCCcCwCCB*CCCCCdBECiCCCC BeCxCCCCCYC B?CCCCC"C5CC5C'CyC\CC,CCCCBECPB CBCCdB)CC0BC+CCCCCrCC)CC4CB@CCCCCEC)C!CCC'CXCWCXC CC=CCCRCDB+CUCBCCLC:CBjCCBBCCaCCBC(CCEC3CB CCCjCNC!CC|C}CPC#CCCCjCBCCqC)CNCWC0BnCGC CCXC@B1CCqCCBBzCOCCCCcC>CBzC CFCBCCBCtC/C5CNC CCCCBB`CKCFCCCCqCCBBYCBC%CCCC8BXBwCCCC B.C CBCgCCCCLCCCC\BCCLC BFCBABtCCC1C$B BJCBMCpBCL"CCCqCCpBBCBC^CABCCyCC,CCC8BkCBBpBBCBxB C+CLCC B BCACCPBCCACoC0CB?C`BCCBWCBCvCBCBACCC`!CBA !CCB{CC|CCC(DCB CwCjCCpCAnCBC6CBBCCCC@CBiCC1CC{CBACCQC)C4cCCECCBXBWCCBBC\BXCC`CCCBBdCCCCACCChCKCCsCCxCmC-CYCC4BCCnCB)C8C]CjCCCBBCxC@CCBB6CCCCCBGC`CBCBCCCCCCB2CCoCB CFCB}CDBCCpBCCgCBACCCC9C@B@ CBFCCB0BB4CCBCBBCBhCCWCCCA,BzCvCCZC#CC0CBAtBBC/CBC8B(BkCBCBBCLBBCC\CuCkC\BCgCXBBCYC3CXBCBBtCCA CBBBABFC6CC8BxBCA0CB*CC+B\BYCtCsC CDBBAbC(BTBBBpABA B1CCJCBBB2C&C BBBBGCB<@8C@`CBBxAAPBSCXBC\tCCB1CC0BUCC"CxC"C CBhB4CHBBBBBBClBtBCB1C BBBCmCBCCBtTBFC0jCBDBPALCCBBpBBCBCB,`A\B^C2CCBB)CB@CCZCC-CBC@B4CBB,C|BACBB@CCCDCCCB]CCCDCCCCaCCCCC@DCCCFCiCCCCDCCCCvCC:CCCC@DDCCDzCCCCCDCCJCBCCCCCCCC~CCCCoCCCCFCMCC@&DCB0BOCCCCCCCxCCxCOCCCCCCCCCCCCdBdCCCCCC2CCCxCuCCCwCC\CC CCCCCBCCCeCCCCChBDBCBCCjCC7CBCDCC9CAXCDCRC"CBCCCCCBCCCxC#CHB~CCCCC0CCgCCCxCwCCjCCCCCkCNCCCCAjCCCC0CUCZCCCBCmCCmC9CBCCCyCCCnCPCCSC CCBdCCCCCCCCFCoCCB9CCwCC*C BdC\CB^CCBxCC*CsCCBBeCCCCCCBCCFC,CxCCCCoCCC(CCCCCHCBpCCoCCC2CYC6CCCCmC,CCXCCFCBfCBBlCCCCrC C]CCCvCBCwCCC(CBCCC?CB#CCBAOCBCC0BCtCX]CCBBtCCCCBCCCCjCC`CCC|CCOCBCIC3CCB@C`BIC|CBCCAPB\BBuCCCCBAC1CCBBC BCCCCBBBaC9CBCBCC9CB+CBCCCCVCB-CC}C:CCbCCJCCpCCBCOCB*CFCBCCBCCBBCXBBCGCCC'C9CBECCVCCjCBCDCCBBCCCClCCCCGCCCCCHBBtCrCCCC CBCByCsCB CKC CCCCCCBXCCUC&CkC\BCCCCC@ChC8C-CdCCCBZCBCCCCCBtBCCWCCChBBC)CC!CBCCCAC/CCCCC0ACkC_CCCB(BBCCCCCJC'CCB(CC~CCCC@@BC@@RCCCCCCvCBCiC7CA?C7C'CBC3CICCBlJCCjCCCCCDCCBB.CCCCQCBRCBC C'C@CC$BBB{CfCCB|CCBBYCBCC C BCA!CCCB@^CC)C@C%CSCBCKCCBB6CBZC CB-CCChCiCXCBjCB=C\BCC7CUCCBaCACbC[C~CCqCBBCB$CC7CC>C|BBiCCCBBqCBBpBA~CC\CBA?BCBCC7AjCCC.CBB:C C{CBpBCKCCBChCCBYCB\C5C A CC`CCKCAhCDCA-CCCkCB0C\BCGCBC}ChBBVCqCC\BBBBPTCA,ByCC4BCBC(CCBCCBC CACbC3CBC4BBAC5CBAB,CCB(CCAA=C0@BRCBPA#CCT`CB:CuCtBHCnCC@@CkC4CBA(7CC@ACBeCCB1CCCBBBBzCQCCvCLBCCCBB@B CC\CB/CBCGCBBpCdCBB8CB!ChCA/CVC ACAB'C%CP CCBB7CCBB@oCBBkCCBCC;CLBBB\BxBBCB:CC4B@`ABC(B(C CC#CB-CtB(C/C,C C0BBd BCB@@A1CaCBCCBPACB\CB ABBB BCC,ACBdC1CAiCBpxCCnCCCOCCBCC\*CRCB:CCNCCTCBBCCC(CBCBC^CBkCCCCcCBBBCBMCAUCCBCBUCTBCB$CCC8BCCBC'CTBjCCBBC\>CC|CLCBBECACCCDBbCBCtC=CCCB;CUCpCECB`A\CC@bCB+CMCCpBBXBBC%C1CCBCCBCCB[CVCJCBBwC4CeCJCBxB.CCcCiCB$BC:ChB[CBCGC>CC[CBcCRCBCCCd3CUCJCBC~C+CCHxCfC*CCA1C BAXBB CBBbCC C CCCBBCB0BAA8BPWCC4CCBB:CMCMC5CBCAKCBC[CBBtBWC@BACC^C(CPB@[CB CBCCpB ABBCCBBCC@BYCtBCB%B;CBBCBA5CYCCBBACB`CCA B@PBC2CACBBC\BTBBBAACBP@#C*CC@CBBsCCyCOCB\B?ChCB CB C BA%CCCXBABBC ByC+C#CtCBDCC|BHCB>CCAbCCXB#CCCCCA4BDBCCCB8CAACGCB$PBCBpjCCCBBYCA`ASCB&CCBClBB=CBBBDBBNCBpAC@A B]CB"CCCBB`xBBXC4LBpBBBBCSCB0BB@BZCB CBB(BBCABCKCTBhABC(ACCCC`eCCCNCCCBBBMxB-CTBnC|AB.CmCpB@tBB7CCBCB$0CC(CHB\BB DBPC7CCXCBBB,BBJCcCB6CBBYC@@tBBB CCBCCCZCCBcRCCBABcC(BB`SCBAAbC@BC$BBB8BmC,B@BCBAABECC84CB@xDhBBB0B/CjCBBAhB5CCB0BBB|B%CB5CVC ABCCCC CBAOCDBC?CDCzCBBqC@B@BbCLC'C0B CBBBC/CBB3C%CPCB,CLCCCTCACC6CBBpCC(BBXBBwCHC\CCBCCBBaCCB BAB CC,ByCChBBBxBBd*CB1C9CTAxBlBB CB AB@CCB!CAPB1C.P(BB@B7C%CBAA`BuC CTBBDCB@:CABpA@B}CBtCDBBBABhBBTBCAMCpC`"C@@"#CBlBWCAHBBBCBBBBLB0CC@ACB,CJC CDCB@sCBpBOCCBPCC(BBKCBXBdBB/CBPBBTBBdBpCAA@@BCB C8BBCiC@>0AB|CCBh@ BClBLBUCmCdBCB+C(tBKC B@ACHCBeCCC$CB`AAB)CBqCBCHBAC:CGC`BLC|BCZCBBPA @BBCBpAJCBMC$B2CgCB@CCBBB=A|BCB PABBtBCCAdB@-CDBBCwCB@C?C7CC@A|VCCB<"ClBCBBB$@BBMCTBACBSC}CB`ABAB%C<xCC/CCBB8BAC@@;B|BAAA`CCABB BCBHBB`BBT CC?0 C,CB(CD(@4C@B|BBCPBBBBCB~C|C CC!BCpCDCBBBC+CBBeC|B@C!C@@tBB(BXCBBPcCB/CPCMhBCCCC(BxCOCdCTBtC1CA*C,C:CC4BCC8CF CC@BBABBCAB+C(BBABBB_CSC.CC(BBBA+C4BQCBB$B"CBBpCpABCBA BBCPAdBACB)C@DB!CC08BB?BBAB?CVC4CApAA&CBWCC$BCAP?BdB|B.CCBAtB@BC9CBL(BBhB\BHBB8BBtBA CB@AT`CB0B CB UCC\BEC)CeC/CRC0B@EC#C@@BC0C+C`AAAlC3C\C CuCBB C`AD$BKCJCLBCA@CGC C<B*CLBBCBBH0ALBBHBBPB8CBB@DCLCB6Ch2C<LBxC C(@BB<BC4CMCBCYCBB@BBABB @ C@B@;C BB@lB8C1CCCA%CSCBB BCBB@B@BBCCB@L4B0C$C#CC3C?H4CCBBoChB*ChBBBCCKC,CB C~B,AALB\,0BBB>CxBCB0BCJC|vA6VCC!C3 C-CDCAtBB CBC0BABC@@BBBXBBBABCPGBRCA\XB B^CxA\QAyC ?54\B,:C C'C@AdBBABA@C$PA@B5CB&C%C,ACBB,TBB@AB5CBpU"C@CGCBA@BCClUALCdB}C CABy!ChBDBABBBBB"CC4CL(BB C?CAaCBBBBBAEv4CC0C CBBpBC{CAB(BDC,zC\B@BBBTA$CBxBABZAh"CBB-AhBB 0A ChBT4BLBCCB|A0B|BFCA@pB+CB$BCBCBAhBCCdB2BA CBCAACB@@ABBC C(CHBHB@@B(.?C]CBdhB@A2CB@CPB|BBhBA"CBPPAC>C7AB0B`B\B5C4CB ACkCTBpADB0ABBpAxAA BA&CPBBMCBBC;CBPCPACCBC$`CTCBBCBBAABQCOCBA4B*CCBBABPXBxB`B,B$BCCDBJBBCdBBB:C CBUCBBPAcCVCFCCB_CB4BB0 ASCdBCjC@MCB(BBATBBBC+CB6CDBDBaChCBgCCB47CRC CC@@BB@CCxBBOCZC;CBBCCLBFC2CxBC8BCBCBPdBC@BBB2CBBBBBCPA0ABCB BBBhBBCBBB`FC?C@ACBCWCBABBBB BC0BABBBBCABBBBCBvCB@@@B%CHBBB@BBBBBB-C Cz|BClCX@BDBBBANC%C[C0XACBBhCA BDB0'CAB@BCrCCBB@A4BIC`YC>CB"C9CDRCC'CA@@C}CABPBBBCCCdB=C0C9C BP0C`BCBAB$ByCBBsCTCPClBB@B.CCBB*CAABA pBBQCB0ABBBC AB0BBBBB CjCB@Bd$C B@C0CCB@AB@CBkC(CPAICABAB,CBCBAdBAB@xB{CB0p1CGCB A@@BpBBBCB@B@4A\B^CABCC@CpACBBABB$CLCDCCBCfCB CB|5HBtB$BB8B BB\BC@BBCCBB`A@B)BC(BCgClBlsB]CC@0ABC&CAB4])CiCPAA@BBBCCBBBHhBCsCB$BBB0 CHh BBA`A@CAB@C@BBB C=BhBB@BUCBCYCpAS,BBB@A@@|BC2CBBABCpAWCDCB4BABB C3MBCCFCLBBLBD CDBA@B B ,BxBCBA@BB`B C *CPBC C1KBBAB,B!CdC`CpBB0A`0L0B4B$CNCAl4CXB\BB4CB,BAxBB BPBAB0A\B?pBCBBBB B(BkABAlBA(CXB CCpBBBCwCBB(CBAPPBA0BBBtBBBAxBALBAB`AB%B8BkCBA5CB[C$CB BACB|BBBBB@BBB$B CBBCPXB!'$CB@B8B`BPC8BBB\BTBB`B&C{CABCmCB@CBB(?dA_CfC8BBC|cC CA@BNC`BPpACABABB`BfBCC(CBx@@@BC,AB`A CA4CBB@B0BB~C`B6BACCCB@WABBC4BBBCCpA'C:C<f(BA B=\BBABBpBIC>B@BBB@HB@|BDB@BA BMCBdB)CA`C?tCRTBCCCA p@ACBABBAX(8B@BCApBBABBKC BC~CAg02CC*CBB$ BBQC BJCNC?B'CgCBBLB,BBCBCAC@ABCBpB(CHBB[CB*C$BHB-CdB\B&CCB`AB+CABA`BBB`AABB,BB3C>CjCTCCBBPBBA[CBB?@B@JCB7CpAhB*CBBsCBBBlBBBGC CCA/0CBBA@ACRCBABCBlB@CBB1CQC0BDB$PABBAB|A@7CBCLBAAdB'BB@ BCACABABXCSC+CC%CXB*@CCpBp(BCBA\BBBTAB@hBKCCtCBItCBA|CBB*CB BCA BCBLBCCABCC(B`UCBPLB|pAB$CHB&CCB0ABC!C`AB<9C\BxBECCBiBBBBP@B`CC$lBBBtBCBC BCBACCB($BPAHBCL0AhBA$BCC BBKCB4BB7CCBB@B%<BCClBJXBBAABBTdBBDBB$B0ABBB@ClBBlBBPXB,WCCBxBBBCBhBA8BOCBABBZPBA@B CB!C)B0BXBdACCCBACBTBPC CBBlBC#C9CoDCPC@C-CB9C(CABBAB DDCBCB"ATBPBBC(DBBB CBPBCDBBrpA@ B#CB`AJ A\BCCC@C CTBB` CB`ACC@BBCzCxpBABj@BABLB@AB8C*C/C@@dBQB&CBCBBB BPAPB,BC`CBBLAC EC`04BBlBB0BApAXCXCBB(BBpBBBBZ(BlBC CLBBBlBA $@ACCnCA,BArTC|BdCBB<BT$CBLBB@?CCBB%`ABBDDB CBy3CCBBBBC0BBBBCBn BB&CB @@xCCBPB$B#C0C+CBABBBBxB BB@@?CBBCBl$B0AABPXB'C@AABxB`B`CBC0A`T(Bp tBB_C5CBP@QC[CB @(+CXCFCCA@B`8XRCBC _CdBAC BALB@ *C@' BC)CB@CBCB7CBBAB$BBPAB0 BB BXB2Co(C pBA0ABAACpBLBBBhB,HBBx(pBmClp0B CAlB(B@AB@tCCBB\BB@x8dBCBBH8BCB@@BACp`BCdCA0A\BCB#AA>CGCBBxB,F@@08B&.CPBDD+ABBXB8B CBKTB@dB#CVCdB C#4BBBA8CBBp5BA BkC^CxCABDBCgCCB(VBmCB@0A #C$CBB<BB.C@7HCCCALBBBBxAB BUCB4BC`BC;C|Bp CCBBP,B`BBPCdBC|dCCvC\B@B'CCBtB`A CBBBBCoCCBC6ChBIACB ACCVC4BB@CPB DBAAtBA.AhBCBBBB C3C4CxB,BB|C#CBCP+CCDCB fCB+C\'CyCBCBC>C B?0AABXBBpAALB)CLBtBABC B-CpB(P\AHBBLCB(BBB> C;C B8BAB-C[C`BdB#C,\BB$BB8@C`A AB>CBBPA CA,=C?BABBACLBC@B@)C@A|BHxBBBt$ClB@XCABBBhtDB3CtBC@(B@tB($CCFC C@MAHC4@BA@ CC@`BICB1CAB-AAEC@AB@BPABBCB:CCBXBBpBBtBABBPA#CAAlBpApB`BKCAB`BjCBd4BBCCBAHBCBB@AHBG)CA`GCP$CBBB.C`CCBXB` C/C:CAACBO/C$BDPB BCAHBCC@0|BfxBCC BC9,Q0ApBCB(B@B' CC@mC_CLBBBEB8BA%CC (B4CyCCB,ACHB_BCbCBFCBABA0BC@A@F(BBBCBXBBBBBpAABAdBBCBBCdBA>CdBBAAhB<@A>CBBBBwCLB CLBCGkB&CB6CACBCCBPqCBl0CBClBmCBB|BA@@hhBB,Ch,*CBBABaCFC|B@PBBBLBBBpA+CBB8BBB'LC|<BB.CSC <@ABC0lDB<@ABCBAB A LA@@B|BBBCB_Cp!BBABBBBBN3C@@CB@@@0A)BACBB0BpABBA%CjBA0ABA$BBC@'C4C8h<(B|ACCAC@@B@@B8BpA*BBsC,CCBCA45B=C'CB:AC$p6B BBBCC@CBBxAIB B8CHC%CeC$ChBBBB CBBABBCC0@DBCPBtBABxCK$ABBBB BPA0iC%CpCPBCH CB@@A?C/CX=x@CCBLBC:C"CCxB|BCA*CIC|C@ApBDBxPBAB,?BGCDBh(C BPBlBdBCHC@ ]CVCB`B_CB(BBBPA@@xBBBBp-CDBPC>CBPC-C<(tFB[@B+ALB AB7CPA+CB CBppBPB0B+BCCRACC;CBCB`AB<C8@xCCBAAP@xBB,B0A4BB4BBC|A0CBT CBfC:CC@AA$C,OBtCCB.pABtBA|BBBBBBHABC0p CCBPAB@@B BpBB C(BBA B(C'CA$B#CA@AB`ABDCACHAB-CCBP+CABB<C@pBPA CBBBBBCBBBB@,BC|BBBRCTB\-C)CBYCB@TCDBBpC90CBpAPBBCT4BBB'CB3C#,BCCBFYClBpAB@BB'CXBTBBBPB4BABpB$AB@B4BBpLB DBACt$BA@tB08C \BB\B0BC0A dBBB@@BBCzC"C@AX@ABBBHBABBVC"CBCB@@pBCBC-BBBB`LBB$C8BHCC B=CCBtBBAACB8A-0A@R BBLBB@$BABBA CHBlBB,@@`CgCC`1AC8B(PAAC}CB @CB9CX@ABB@pABBA@CB0ADCABTC{CA&C@(C)CBCtB@CCXB;pBB;Cp@\CBAAA9BC C(BB`0#CCB<\$CBBBLBBCtBPaC0BC HAA]C!CA@BpBA8BBLC@CB`ADAC4BB7ABKCBCpPBB8CBpBxBPAB(BpBB C,CpAB@@A B(B(CKCBAB\B9B,C AB CBCaClB\B/CABCDB8BA BCBA`AcC Ad2CLABOBnCCpB$BBB CB@B AGCdC@AC8BABBDC t] B#CBW(B'CBBAB CA\(BxB00APAdA|B`BBBtB`ABACBA `C|BBACABBCApPAAA BBB0C0B|BAB@AA;TCBBB,BBBT: B CBCTB,BBB,C@@0@C(AC@BABCAB$B_itBApABCBBBLBA$`AZDB$B@BABOCdB@ABB@pA|8B0CAECABB"0BCxBCAB(C!CA>HLBHBBA@BBpABtCA`BC<AC@BC#C BWpBB,BABABBHBsCB@A*A`AtBC@\B@T BKCB%CA]EC@lBBCXX|4BB @A@BBB AAA?hBPBBBL`A'CBBAL`BPAC lBC!CBA<*C CB B,BC$BB@C BB]CBCTCDBXBB(BBBABB0AB8BB>C`Cx@0A\C9CBBB(%CABXBTBBC@XBxC8CBC,5B@BB%C\BBBmC0BXBQCTBBBBvCBABB^CDBBHCCBB9,,BCBU @@@@BBBBB@BHB.C>CBBBD@CA.$?C@AdBC;C`?P@BC0lBC|ClBACaC@AB+Bw$9CKCBB?\B#CABBDLWC0CA!$BBBBBB$B@A8BCB0CB<BABBlBBBBtB ?B CCBA3@[CClBS`BnCA0CBBBPdCpAA@dB9CLBBA BBLPXBBBBtB@@@4NABB$B CA(|BB8Bt xg@ACBHB@B4B@A ;PBBBbC C@@`6 B AD CAp PBiC4BCCBB CA BCCAC< BCBhTC.CC0B`ACCB?CCxBPCCABA`lBmCC.3ACCBTBBBBlW@BBPA BBBA'DBBCBKPBCBTCC0AA$ABYC PAPBCLCB*B4CxBsC'B@ABB%CxBAC,BBACCBpACBCBBBNCCyCCpAXSC+CAA)C@@CBDCA/CCBCBHC@@BB0AhBXBd?BgCB0$loATBC|C0BAAOC pBfC@BLACLCB0ABeBl,BBB8BCC@`SCBV@PB'CPNC+C0BB&CDC\B B`A8BBB@AB\BLBf]CBDB|B`BPB(CAHBB@WA&C@pCCB|`A C,CdpLB/CB,B0A0\C@A@BBBpBClC$BAXB`$BICB$BCBCC@8BBwCeCABAB 2C8B=CABx;CPBlBeC0AA\B5C&C0C"C?BPA`BT]BBCAgBABJ0B@CHABhC(B@Bd B4BBCBCC4BBJC(B@@$B@LBBBBABnA@B C pA8BCBPAxBCCSACCxBB`BedABBXB,B4BxBJABBrCBB CABhB @BBCBBBwCApACBFCBBBB@ABBCBBAB@C_CBB |CB3C<CB=CBd@A`BlBYCAB C9C ,BBCAY\|BA<5CC tBTXCABBp+C0BB(BB#C(BBCC AP BB(BB0ABATC/C1C CPBBC2CdB2C3CECvCC`8B-BBBBiCtB`A`CBwCCBB|BB,BCBBzCxCTB<`BB^L CBCL(BpA@A@`BAQCCB,B,B<BkCABdWBDBC C B$,BH@B=C$A BB 9CAPGB&CBBB%C\BPA CxB`BABD CBBBcCsCC@AxCfC@ BBB(BABBCB{CCB, AB A`BAC ADBADCBABdCAC,pBAD$ BBLBPA0B7@HB@AAABC7C,T4XB\BCB`xBA&CBBB8C`AB4pABCBABB0A C@@BCp `B\?|pAB`CaC@`,CpC\CBCBB BBBxCBxBBB)CBL8B>C@AB`@BB C ,CA9CHBMCCxBm BCCB@hBBBBd<0ACICHBB+B)CT@BBBCB A`4BAB@xBLBBBECBB&jBAB 6a0B?CBBB A(1@BBpB'C CBB+CBC@@@BIC0C$BDdBPBAMCA `A?CCLBCCCB(CEC@B CA@TB2C `|BB'CBA1)CBB$BB8CdC(BDCB0AB?}CB0,CGBBXCdB)CABA0BBPBlBBBCwC ,@BBECA2AwCHBBV@B-CCBBpB<BdB(B@AHBB BBfCB@CBcBACyCBPLBCmCxX0CBC C8B(BA@BB3CCB8?B0BB FBB@BB8B(|B C@pAoCBLaPB@B]CPA B\BxBBB4BBBBdBB >$BBCCV`BHhBTB3!CBAB6C|BCBL%fCBCBBCCA0]BB@Bw#CCoCB BLBB@AAUCCC@B *BBB"CBDBLBACB BBp0?CCCXCA ABDBdACBA7BCB%CC ABBBC C6C B@CAhVCBYd|B@B@BBCA1CB8NCBBABC BBP CCH0B*C@0AB0BCBB@V`BB8AACp@@B@ZACCBpB/CBBBB@@TBHB$B`BBLBCBBD\BB`AC\BfCBCCGCCSCL8BBCB(C B"Cd]CLBC=XB3BBA CP$BBBpAxBA|BOC&(Bh_CBlVCC=C)BBPBBCpBB@GBxB@ C*BBTBCA'ClBB,BBCB`A B@XABDBBBpA BWCBBBBBKC$B B@@A{CB;C4B'B3CB"C@ABBuC BA$B2CApA $CBClB\BACpA8h}B'hB8pABAB AMBBPBBdB>@C`CBBPABCAA$C!CB\KC0B,ACBPB4B@ABBAB AG+I PA`ABC"0BhBB@BBBATA "C"C AB@:AP0cC0AB8BBCsCCBCBhBA!CAKBB@pAC&CB/CCB$BA0IBA@ABBDB C(.C(CAC|B,B14CXBCBPB/A)C0B@tB HB@`BBBB BBCBXC0CpBBB@DtBB@BAB`C7CC A@BCBcCA@BB BxB@BHB0BBABB5BhBBB4ABB@BAPB0ABBAP$CBBDC`A`lB`AECCBCC CBC`BA_CaBA8BBBB@Aj{BCPABBACBTB8B CBDB@B,CAxB CAALBAA AdBAAC@`AABBAtB`B@AB@C@A>BCBBBUCAB`At@`ABBBBYCB(B BBAxB@@BAAB CA B.C B6ClBB@`BBBB?PZCC`CcB BBB$C\BUABB B$B BB-dBB BPPA7CTCHBTBBBBCBLBC CPBBB@APCCX4AXBBB0CBX"BBpA`ACBXBg,BCxB@P8 C3CBxBrC)BB@AB:CC BABCBCK HBtBBD!|C/CBBBBABP"C0CC(BBLFCBB!CBLBKCBBBBPL6CBBxB@BEBCC)C1CB:C*XBB@ABB,B C1CBB3C@ABCBWCXABB@BBpA@ B7PCBAPBABB@B|B (CC%CBBB0BBXB7BC$B B4BBBB@#RBBCBBCHB`pLBxBCDCaC@`BBAlC8AAA4C4C@ChBPBGCAl.CPAX|=C@CCAAAPA0ACCcC<HBCB? CCNpABB&CATB@B{CB`WC0BA CAAA@B$8B@pBlB`A @@qBAC(AC@BBC4BBBlBCGT$B"C^B8A*C8BBABB.>CCB|B)BAlABtB3B;CCPPBgCBB@ 0ABA|CClBBBAClBABCB B,BB@@ C,BhB CCBLBr)LBC@B@BBCCPC|B,B7C@BBLCBBT0AnBAB(B@xC@B A9CC$xBBSCA`B$4AAkBCC@ABA\, 'CPCA0BBHBBCB"CCl|BACTB C`A4B? ABB4B BC3BB`BD@TFCBB3YAClBp@@BAB@@BAB C CBB0A BpCABTPBBLB BDBBB@plBB@BBC@BC@AAB@>C C$B8C@BdBpA4BBBB@ C`BBB4B@B`CC$B(:CBB9C`B@@BeCpBGCBBaCB9C44B B`xxBBBpBB,B@CB!C@CRCQC|T7`_C8lBB8|CFCxCA0B,B*C+#CC@BDBB(BAA@B|BAICPRCNC(&CA}C@|BBCBPBCAtBA@CLTBCBTBBpBPACB|AB)CBBPACAl )CyCB0B>C.C0ABC8BTBd@lBAPAACC@ @DCCoC!CBCpBAAPBABBC2C,BB$BB@A3CC@BA;CAPBAC PBBBB5CBBB`ABBBCCCB-AB ABBB0B`@pB|BCBAABFCA@BC,|B0Bh5|B0AA|ABWC@ABp7CA'CACB@`BlT\TCpCDB`,BBGBtBA<BAxBfC BAAB@At?CBHHB?CBABABBA$AgAbC BBLAC,B2C*3C_CPAB|CA30h@@CB@B*C@B>AChPB\CBB`TCP@ .CBCC8BBhA|CB0A O/C AA4B7C`CBAA8H A'C8BBpB:oC CB PBxBBBKYBBAKBBAB4BACC+BV@B hCKBBABlBABXPCBIC@BBB"CBB;B\BB`A@@B`AB(BC8B"AA(BpB CBAABTABB CCCACB)CHDBYCxLpABCBJC;CPB`PApAACRC%?CDCBBB(BB@C5UBCCC@A=- AC"CB?CP{BCPAhB! A CdB$BYC BB ChTBBh*C@A:CB B(C@BoCCBPBCOCB5C@BhqC@B BXB)C)C@CB0B%C(CBB CRCBBpB B ACUAX(C5CW@APBCBB@GjBBBBBBA@'C'C=CBTCpBA`C.CBBBAhBAXBHPBAAPBB"CaCC,BPABCB BBABl`ACCBxBCC CBdBDBB@ SC C?DB(B\BC&C AMCCCCBpA,RDBCB8ABB@C`<C>CCCB`BTBBBB0LBcBCtBBBCC`BBA8A\BYCBBBBB@CLCBBABPBAXCBCBpABBCBABB0APCCCBwBAeCB (BBB< BHBABuC+CVCC W4BzCBC((C(TBBLBtdBdBWClBp@ @BB"CPLTCC,`DBC4C`BDCB,BBBBB BCB@CB `AxB0hBtCBCBBBBEBBBtCBMCnCBAtAHABB C,CXB,B,CCBB|TBCCABBCB%@BCCA$B#CAB ABtBBp(AC4B@CBBBJ8B( A B0AMCAPpBABP$B0ABA$ ACC?@ABC@ABC C UCtBxBX\3BB0CBr=AXCBBA$BPATC0AB?BBBlBCQC CBdBBCBE5CABBB A(T)C B' CBB02C1C.C@B,vCAB)hB"CUA0;C@CBBA@BBpCLBBAACLBBBBBBB0`BB0A BDCA?BBAhBABhBt2C4BABHCAB|B ICaBACB>CD@wB0|@B6C@@mC8PABB$BA@BLHA)CB?CBBHP@ AAHl B)CBBBTC)CBB5CBBJCABBB(B&CdBABB0@LA`oCCB,pApBp CB@@BCBBCCCBBCBPAX@?@C?BBApCXBBAAA|BAB]BBCBBkCX`ABBG0`||BB`B2AgCB-ABAB$B8@BC'CBDBBBAA0CCp)4BlC(HBBA$BB`B4BC1CBC@0BCADpCC0@B #BBCA AB`CBBC BBEPCCCA?,C @B@BCL\B.A"CCC@ 1KCCAlBBBJB BBxphW|CAXB:CB,C2LCpCX@tB,BABB$B`A#lBACCC#ACBA1+CCB& AAP"C8AC;CCCB@BCC@BBBBCAX(BB$BCHBpBB`BPB%CABtBB)KCBXBChBBBABDBPBCBB(BB=@CCLCCCXBB@BB`BB&C B@`BCBBB@A@~ABLBBwCB@CB?AB|h"C|C^A@VCBCBpBABBB$@BAlCCABB@C B CBxBlBBB$B0B@AB[C@ABB`4BBBBBCxBBpB&AB)4B *(C(9B02C CUC}C@BBBBB6C2 A\BxBT7CBBpXlB.C`AXBBBpB(BPB ,lB`C@BBB3 BBA WCB@B0BBBB;CuCtB)(p BQCBBPAAP`CBB)CA}C pAGBC4CBA`(/LCA@BBC,BA\BCCPBBpB|B 7CBBBBPBA$BBBC4x,B_CAB4T/C@0CD$@@@B;CA|OC ECABCB$B? CA8CBBh"$(BBBBBLpBC AB@fPAAB@AkCCB R@?0BBB@BipCpABBA@DBAAC%CAABBA@AXBAB,C C|.ChBAGC@tADBDBB`4lBA:CPA`CApCxB@p@@BCCBAAPA@@BBzCd/ABAC CC`BLAB/CCl5ZCBCAA@ABB0*@*CAA(|B?,B@@ABh)CC AhLRC CBC Ap$B\BBBCD+CCC@!\C`AP$PB\BBPCAz27CB`AB4ABBCCAH0A@9lBWClLCCXCBSB C+CB CB;C@A$B|}CCBC|BB@B(CTBBBB CB0VCBD@9-C0AHBd(C6CB`@@AAB(B$|BB,[$BKCP4BBB@B^CBAlB0C%C0BPBA`ABACCBBKCB A@BCC`(0BOCBCAA@DBCEB4BBB@B|?2CA`A_CpBB C DB8XC@H@C4B CDAL0A$B9C@BBdBBAC4A(BXB2CAABtB@PApBCBB?C5C BC`ABCAB`A`A(BB"C2C,C B@@1BBBB,BCBB Cj,BB|/@<tBD$B8B0B1CGCCC-,BC:C,B CCBBBCBCB0AtCCBVCBBLB#Ch JCBBBB8BB0B@BA%nC@BCClDC A(WCBABTBAB A\AgC CTBB+CABBB`D\CCB0ABBB\B"C0AB?BAc@@AC`AB@,?LBB`?< ]ABC0XtBAxBB,BB,;C@B CBB@BB0AB,AB0BPB.CBCA`BBBHB@AC@BAC`A@B@BB BPA:CdBB=CCP 0C CBBCBBCAPBA`ALA$CCPBBBBPBBB@0BPAhAB8,BBRCCDABB CC0B?BBC\CAPA@B(B,BRABV,BhCA?/BBBBdBC@C@CBA-(G tBAAABtV!Ct PA\B$BDBBCBCB'C@BC AABBBtA'XBB$BCt YCB BBBCBCA? ABA1CLBTB C@BC>A;CB BCBDBBA@BBBAPA-CR*BCB4AALXBB+CBBCAABCgBBBLB B{C,CCAAhBBCC AB A4CA0CCACANCBA B)BxB CA `AHC`CAClBB5CBBBpBxBpBlBB BB Ca@sCBB CHBC`BAd.CBA B@`dBA(B AAC:C`BBXICB,BPA B@\BDBAPKCBAx@`B<BBpAL0CBBBBB4BAB\B0ABBC(BDBX\CCCB@@ B) CAlBxARBB/BpBB#@B0BPdBAB>BtpBAB7CxB8C4BBTBCBBBBxBCB'CCCkC;CB5C`A`B1CB C@B@>B C@@ABd$A,A|BBCd A5BBB|(BA-:CuC@hB7C HBT(B ZC B@@C PB@A9CBXBBOC BtBA@@BB CBBxwCBBBTC 0BB\BBB\CBPA'@dBBBL B0%B@Bl4!CoCC`B$BF)CBB@@CBlBPCCBBMBBDB XB@ BB$CACB`ABAB<pBA `0BCAJCBBBAAPC>`BBA?1C0< OC@@B}CCB"C*CtBRA?BB@$CBCTATPA\C A4`TBB&4BCA<dBCCP| BL0A C|BlBB@x:CBHBBB@`BB`\BCBAB BBC@BBAB<HByCBPBCA,CP$,HBCCB?BBxB&AC@#C2CB4B$B BbCBCBPAC0C0tB BBBB|BpA CB@(*ACxBX?BB3$tBB(B0BlBC B,BBPBBC\HBBBBBAA`BBBCC2C@(\C |BBAQCT@B8CB CIHCBBBBBBT@C $B@ BABBVCDC!ALBABCBB4BBWCB'\BBB@ C&BCB,B)C4ABCBB CA@ZCCBC,BBCPC8C@@A<C8BBCB C`*LBCXBpBuCB$Ac BlBCpACpCCBAC@AHBCCB,BxB.CPBBBBB8BhBBBlBAAALB8|B APA4B0B?C C#BAC=TBBBAB| BBUC?@BVCBC#9B`CBBDH$JCB <B@TCApBACBBCBCB@@)CC"C8BBKBBBB@'BB|^C RBl$/|BC2CB=<CC|`A=CCCBAB@BPBP!B:CMChDABBB00CB A@pBB@<CPd4CBC@0CGCA B4BXBMCBBAB+C`tBCC8B4BAC ABA@ M,,B`AC@M\BBkCB @B@ADBA0B,BBB C1CA@?DCxBB@?CABB?=CBC0 CCPB,A2C,CA@B CxBXB@yAB\BA@BB@ ABBCBB(BB4C$hBDDB BChBA4BBB BAPBB_C\(@@0pAB@AA`ABBhB8BA?CAhB AB`BxB`A|BAAKC@B@ABfBBCC@BC`AEC{;CLC!JC ,B*CB(<:)CBBXBdBBPA+CBBB.CAB0CCDB8xBBBABCBBBC@ABC CCAHBBH<\B<CB CpA @pAACC@AAYCBB`AABBe#CBB>C|B,B$BXdBDpBC.C@BMC,NC;Cp$BiA@@,(0ABB8BCBBBDCBhABDB.CBB|PBCBA@@0CRC`APBCPB\\CLB`B@ @BCBTApATB!CB@lB dAB<DB4BTBLBTB,BTBBC'CBBCBtBA ABCBBBBBABBLB`PBx CApAAYCBBBDBBB,B`B`B@CDB>C@0 CABB0AlB\BB0A.C3CCBC@C4BtBBBBJBpABBB AhBhXB@BBAACABqDBBBBUd(B0A@%C C`2ChBB0C(BBC@(A(B5BPB@.CBpoBCBBB@  CBxBCpBh BBBBX%CAB.CBB0BABBBBB*$C4C(XBT( ddB,CBCZ\BBB,B\A2C@AAB$A[ClBAACKC A BCC0A\B AACB@BBNLBBB)C@BB`BCC&C B CABLB?iABBhCB0`ACCBUC@$ABuCCBB;C8BLB$C`BCAB`B5CVd@BBLXTPA AAA.7CdBAACp8[CAB`LBlB$BB\@CICa/ClBB CB Bx0ACAHBO\BBB@CABPCB BlBfCCA|C0CtBTB|A BC` C@CBBB CBC1CBCBBBCB|B<@BBB BAB@C@P ACC6C C(A@B@BB |BCA(B`BBC~CBPBBLAB'C,A/CC4BCmCBB B,BAtAB!C BdB'CdBBdBA4B3PdB0B2BTB&CPA|D CpABBDHBJCB@B-C)C,MC4B*CHBB2C4ABBB,CA@DB+CC8ACD*CHBBBBA4BBXB?A@BP @C C@B`A CCCPBuCP?C`(B]XB@AA,BBp40BLBB,< (xd,BB`PB$BDBCB;vCH%C B`AXBCB8pAB$`@ B`CB400B\BCCDpBBBXCC$A@ AxCBBA@AdB@A@BCDBCBBB$WCB4BA(PB8$CB p,BB4BeCBBBB@BTCCCBBy@BBC7C,$@BCBBB#8BSCBBA,C0C@B4BB@PA dTBCBCBCaB_CBd BBBB@@AbCBa,B|BCAB8A|X`A?BB@CjCB( CBTBBA7DBB((BB Ap@$BBXBSCBA0rPC@BCBBCDCqPTB,CCC/BCBTBBBCB$BCCB8BB!B?ABJCCXC BABAZCB0BBABPBTYCB0AB BA4BBCdCB 3B,BXB?A7BBBCAA-C`BBBAOCLB T`BBpBBB(C< C0C@B8ABlB@(A CBAUCPB^CC5C|BA(<C CA B,BECBBAARC0BA8CPiCB\BCAcpAB]CBx$CC,tBC]pBBP%BBA1C CC,BMChClBhR<B4BvCxCB:CACK8PAC,CAH@B< CPBHBCB|BBB(C B|BDBP9C BAABCpC$BBA0A4BdBA C8CT@BC:BASC BI.xB-CCCBACCB@$CBAxBBCBBtB;CA%@C`AXAC CB4$CXB5CAAB@$~CBB0B0BBd# ACB$B$B\ABC4F,C&CBDB24C"C`B CC@BJCCBCA`CBBC@(BB2 C7CBrCmCCBTBBB\BACFCXBA[PCBB(SCBABA`@ CCAB A@ABE CxCB#RCPAC/CB|BPBBA?BB<hBXBBBChBCB XACpKCB BTBAx\BAiCTBX@@BA,CCbCALBBB`B$CXBAlB,B-CB`BLBBCB*C BB(BB0NBkC@ADBACBPA`AB@BC0A8\B4B&C A8 B@BdBBWC@B4BBBBABB3CB`DB ABBBB0A0BT&C CdBTB|`AB`BpBBhBADB@AdBB9CATBAB0ABCtCBACB_`BB^CBBC4BBC4B?@BBCdB4BlABBB C1CPAA@B 4BA#CBC9B=CBBB@,BBl@(BDB@B(tBCBA@@PBBB@B5@xC8pB B8BBB A8AOCB`BTBA5BFC@A CdBCABBB!C HB8A@A?ABFCDB( B0DB@ACBB!l CA CCB`AA#hACC.pBCBpB C8 ABECCB/8C_C|CBDB 0UCyCA8A4B CAACB CB%tCBtA8BU$B@BLB)C,BB@B@BAA@B@A4BkC0.BCBCA$A#-CCCxBPBCu BCBLA0BCB CBBBBL B<tBB@ACS@0LcCA:CAdBMAABpBB ABC|BBxBCB:B0xB`\B@PC@BPA$BBfCBBCB%CB FPCAkCBPA\0CC>CBPAC:BC(B`AB#CCBdB"B@A)CBCBuCAdBB@0C@EC hB@CC -C#C@*CB@A,CBCC*C1CxBBC0AB<5CBxB@BAtB``BB0BB\p0`BBCBLBA;CB!C` CtB AA C`C@CdB@CBBB~C,!YCCTBBA@BHCBpABBC\EC3CBBB@ABB$BpBBBdA`BBBCBT`ABTBBPAuCpBBCLBX 7B{B'CCB`BpAA`p`B?xB@BpCBo?CXCBdNCBBA@@B)C!BBCB0ABX CB|8CBBBDCBB\BB BAtlBBBmCB`BC,CBA A]CB(CH@kdB@BA\BB@AHBLCCA,xBBC*CHpA0B ABABBPAsCCBBPB@CBCCDBAICxB"C\xBBCBCC[C BfC?0BSCB`AA8B$B4CqCZ,B^C@HBCCCBBBLBBCC;CBBHPBApAABHB@@YaB@BtB@BBBTBAA AHAXABl<XBACBBBB?CBCBlB\B4Ct|C)CB4@(BPBDBB@A0\-CC)CBPHB B@B@\B`BRCBxBBBA0ADBCB,B CBBB$BD$BZCACA@B`BPABCfpABBHBLBB@BBX1CC BABBB) `"0BxBBpHB0BCB+CD BC BBBQ$C@A CBXB@A`BCB`ApBC0Ap|BB@BXBHBB$BTB3C .*,8B@BB`A?<BB@B2CCA$BB)C@lB@BDBAABBTdB CXC<B{CZCB@Ap5@ B]CBj4CC $B?C8BBl6CHABBAChBlBBPBBtB$0B(B2C0CBBPAABB;CXCBL@p<A:C7CB7,B@BlCB0;CABt `B<4BZC;C]BpB(B AH?'CCBBBCp@ xB)CBBBA|BTDACBPAP@TCQCB`B@ABBBBB B$BBBpBA B XBC4kCC+C BOC'CXBjC{CAHB C BC=CBA8BBBDB`?BCChBB+`@CBB CCBBBYABHBCBBLB`A"C8B<C(BAtB|B`B BXBBBCAB`1CAC CALB=ChBB@C0BBCBBzCB"C@B$JCBBC@dCDCDB@BxAB@OC8BAtB@:CzC B@CB]BPBpAACA1'NC0AA<`hABECBB?@DBPA8l@A&C(BxBBC\<BCB^CBxBB C{CHCBA`AC|BBAZBBABB,BCApA8@AB`DBB@CABBBDB0BC@BBAB`B$CpBBBCC\LBpACBBBBCCBBBA0AB C`A@B`ApBBBBxCBBPB A9$B ABB#tdBBB\BBAzCBBB?CPC0BBCDCBMpABACA0LABBAC AB8CCBBB$BAB@C9CtBB(B\BBBBB CB~COCA,BWCBB\B CCCLh8BCTBC?BBtXxB@B8B`APAB(BBB@@B4BHBoC`BB0XBBAABMCBHB<DBfA#C1C@NCB0zXLBBBxBdB2CBPAABBhBB CBBtBOCBCCAB@AB&CBCD,BGCB  B2CBLBCBB@@ $B dBA AB?CB.CB3BBXBAxBPABpA(BBmCB(C`AAxBP8AClBBB CBACBBBA|@ACCNCABd@ZC B@TB B)CAA(B`BBB0BA AB-dhBBx,BB(`A(C,Cl\B'ChCBAAC4CCB=CpBABxBAAPB@@@WC@ C:C0BBBA@B0\BA@A@A?BBBBPBBBABB@BCBA?A*CBBB@BC CC@?B\BB@C?C0BCkC(BAB BBB`DBCCCB"D@B BH?BBBPBABC FBBAAh4CCBAw6C%C ABBBAAABBpAKC6C\B` BBC{C@A@ABBC&PBxC|AB>CB4BA$PABB@ADBBApBB hABBBCPB4@BBdBBBlACCB04 CPA0B/CB|BAH0C'CB0[CB`8BB C-AABB B4HACAB8CB8CB,BT@BB&CPBpB$@C CT|\BBBB@PAB xB(BmB0CBBPBAB>$CUCBTCBLBBABFCCBl 0(BCABB CBXBtICBpB4BBA A@`%CB&CB?hBpABBpB8B:C5C$E1`AB4B$BACCLP^CBAPb,CBC`AB|BB@ABBC(BBAUCCCFC1xBBBACABCB`BhBBA@BUCPA(ChBpB.CBB CxBB(@BBA88BB (t8BLB(BCBPBBBTB3CB<SC5CA6`BH@PACB BdBBABAhBC CpCB)KBC CB0C@@CBWCBBHBClB@-CCBBB"BCCpA CLBB<lBB@B-C!CPBABBBBA`AB\BB0AB@TBBXHCBBB(B CBA@@dpBdBClBA@7CmCCBBB@DiCB0C5CB@A`B(BCPBBCCCBBDBCpB8BB=BBBBABBBBBCBCP@Bh(BBBB6CBBDCGC C@0BABBBB/CAxAhX|BCBApA @9C@@BC`ABBCBBBBC pBB`BB\CB@ACACB0B~$BB\BBA8+DBAB A(ABACABC|BhB(CBpA@ AHB@BABtBq(CdCBB`*A-CBAACBA&B"CB.BB@@BtB[gCpBpA ABBBCC,B`BA{CCB0ABCB8,A7|B"CBC@@CBBB C,B ACCpxB,BBC@xBBBA*AB4C,PAB@B`B@CBBPAB(BxC/CC C04BTBD$@BCA@ 4XBBA0AABC$BhB@CBTBAAA@BqC|8BP1C@XBBP0BB@@ApDB`C5BB1C$+CB!CAAX\BBA)CCBDB`ABYCCHAADBxBpBBB$CCCB C3CtA`ABBB4BAhB$BCPBBA@PA9CABB!APAHCB#CABDCBBBJC$B2CCpAX$B*CBF0@BB BP4pB^C@@0AB(CB0 ABBJC\BBtBD@CCB0|C|BBhD(CBBOCBCW_ CAl+PBTCBB/CBgCB\BBLB]CB C@C@XWC CBCP8`AB8B{CCBApC0cxB)CA@BAXlBA@@@xeCC1CBBPEB`BBB CHBBCBxCBHBBBABhB@`BC BhBCACCBAB0\B5CBHAB hBPADBBB2C0@ C!9C-CCBACCC+A!CBBCpAC_CBBBHBCBl(?BBT@BPC:Ch`HCTCBBPCAB@BTBBA`BB0BBCCB$ByC BLBgBXB00AB B@ BBB3C/CCCBx\B@FCBCB|BBiCDCDCPABDBABB<ApBB$BBCBPA+C0Q4C@BAB`BCBB8TBBC\BBXCCB0@B$BCBpBBTBCBClB C@ECC@0ABBBpBTBAW0ApC CBBBBO?BA(BF@DCxCHCACABB0A4BB*CB@CHtB@ <hBB)xBBCH,BBBBBABXBBAABBBA@BdBBBB\BAL@BsC A?C`ABAB`BILBpCPAdC/CBA`B8 @`ABCC@CXA(CBCHhB6CBBt BBhB@@? BlBBAlC d8@AA8BBBXBA@yC0B"@BCCBABBBB$B;CA B"CBHAC!C@uC0DCC4DBBAC1CAQACB(TdBCCB(B8FpA$CpB(CL@AC&CB C.B0CXBCdBAa@/C^C`B$BBCBB@8CB|B$&CTCBlBCBB ` BBCTCA B@8hdBBBBBaBCCA`,ThBF&C'C'ACB$BsA B@BsCA`AbC;CB AB@CpB;CB\BAH@@TBlBA@@BaCpAC:D/CBBA@B(BDBBxBBC"C C C~CB~pP@iCCH`BxCB(BBAB(B\B|BBC0CtBHBCCBBCABBl`4.C0pLTCBCB A,BXHoC BC4CACB0CBBAB^CC$BAB AHBHBA C C|D CBBNC`A5CABtBBlB4BOBMC:C8BhB(BdB BRCB4CC pBBCB BB^CBhAlCCBBPlBB#C@TApAHBBHBPtBA HBLB,B]CBC@@`BABABAABBBBAA@BxBpAPBCBAB4BA CBB8/B@5CBxBXBA CBHCAA0@CXCBC C A(,B'CB2C,BCAL4B@BXCCB'BCBAAmCBCBA1 CP1AT|MpB CB@@CC9BAxCB0A`BB(C&CBB$BB@B@@ACCB)X$BdBA,BCXBLBA04CApA6CCDB CB,C,BC0C BBBLBB CHBBBPAB C,CBB`B-C1CCBBpAdBC|BCoChCA(CABB A CdBCABhB(C@BBCC$BBBABfCBBAYCCB(B8$AC6ClBaVCBBB'BB+CB`BB2CBFC@|B5C B|BB ABBABCcCtBA@CA| BX4B>C@BBBPBABBxB/CA@)CLB88BBC@Bt"CBBBBA|BKB B@BTBBA>=CKCBd@C}C,B1C@@ABBBXCBBFC0p\CmC@@XCC@B<j`BGC@pA9CC`$Bx@HB`C BBBBBHBBeCBBpAAAABBA&CZCBBLAABAC B0HC0BBCpA\BB|A@`@(PB1CBT|BBBB8tB8]CTBJC|:PBB`BBdBBB BB`B@XCCECBBJCBBBB@BC@ChB@AL CDBBA\BABlB*CB8BC9C(C`BBdBC@AP88BCB4BDB)0BCB\8@@BBCBBBdB@B\BP/CAGCB_CCPB`B%C_CCB@@8SCCBD=|B?0C4BABBBA ,4<B!CQCAACB(B,LAPB-CBABBBABABTCBBCBBBxCpAA\BpCB#CApA`ACB_CCB.BA&BC^CBdAArCCABB0ACA A4BCCBB@nCC8C@BCPBBCPB|pB C@BhCCBBxC BBB@)8B4C8CXBh`BBBBDB|BB.CMC|(ACBBC@(\BHC0B@\BjCB]pLBBYCBCB@Bp4BACA0 C)CCLCB5tdBB@BtBB-C CJC'BB@C @B8B C8B`A B`ABXBBB `ABB,5"BABp BBdCA0@BCLABBB8BAB<B:C`BdBPB,B CACA((ByCPBB B@B@CCACBBCBA@BBC BBC,B=%BBC|BB\A'CB0BB8JBCCBBB0ACDBA,BA4 0AB0ABBBt7B4BBADB7CICB`B!C$A8ABC4BXBDBCBC B@@ UC0AhBBB B !CpA@A*CaCRC}CBBBrCC4B AECL0BFC@CBx B-C`B)CBHBOAlBBBJC BBB0A0BBCkCHBHBB`B CtBA5)C'CB`B\B@B@B@hXBCP4CP/C@x@BAjPACCH\B C(C0BBB;C|BBBB4Bh@PC B$BBBB4BBBXCBA@ATC`BwCB%tBAyC?@@B@AACA@@PA`ACWC[B5C$B BBxBBBAB8CCB`AX4CBpAXX(BB CC<BB4BB@ AVCBBCBpBMCC!CpA@BAB(CB@xC@A A+4BB@B@BBBBB0AFB(CBBAAB0C C xBBA CCBXBCCBAA[CCjCpBB\BBoC@4BAIBbxBLB`BBBA(B@$B@BBACgCCxl 'CDCLBBB@ALBKA_C$CAA\BB`LB#CCwCPA`?B BtBBLCCC|@H?CBB\NC BBPBPCMPA$C%C=C B@@$C$0B? A/CHC BBC4(BtBAB4BA8BmCAA CECABOCtBCB(8BBC0B0B ATCCXCBBBBp&CCTBxCCPBHBBA A:C9CBB"C*CBtCHARBbCCBCYCUCCCB|BACB@ABABBB BBBXB,BBB40AC@ ~C3C@AhB+ClBC8B\ BCB@3CxpA1CBTBBBEC@9CAA@BUCA@]CB0AtBB0(B0B0A`-CC8BBBBBBBC/CHCB8B |BPAB8CAA$CCB0BBCL@f CCCBAKA:CBmC@AcCBhP BBtB B B%CCCACA@"CCpABTBdBhXBB$ CRBB $BCC\BC@O4gCBPA$B`BB`ABBCB\A C0ABB|8BBLBLBA@B@BXBLBB;CC`BBKCCCBB@BABBBWCCC],B@lBtBtBClBBB,AM"CB>AdBBBBABBCBCB@@&zC8B|BB$BBACBA@BBCBBCCABBCC Bh|BEC C,BBBLB@A0DBBA\B0B#CBB@BADBABBB0ABNCPBAA CBBAACBAB BB2ChBxBB CbCCA,B-CpP,BKCB0xuClB|B_1BkC!C8BdBhABBCPB4BHa9C*CCTABL2C*CBBAB A@^CC3CBB_CaC AhCBBApA`ABB C\ D C CeCC0ABt(B9C$BCBC CCBA\BxCtBa[CAB BBAABTBBBFC A(B `aCBBBcB7CA\BB0BhCBBB/NCFC0CPABCBABB$B-C@*ChBW$C0CPCBBPBCCP$BB4C@BA$TBsCC#C@d tIC,ClB BBLBpPBC#CB7X4C2C>C\BX>AGC,CBBC CBACtBBCBCCxBBC@AB BBCCA BlB B0BB$BBdB0?BBAA$B?0BBBBB7BB.C CP@@@$BLBBBBPCdBBBA<BB B ,CB@\BBACAyC+BCeCtB8B BBAZCpBDBfBhCC`ABCCBPB B0BCB;CTABBAB<BhBWCvCBBAA<gCCCABeB;CBBBBBBBB B4B@CMChB(tBCBTBpHBAC SBC$p\B!CBBBBQ@CpA`CABtBxB8BLBBCA# BBBBBC,B tB(CHBBtB B0B4CCACCBBCC(C@B``B,BBBBhB$BABB$CBCB8CBHBpAPBB@@VCxDBCBBB BAC CAB/CHpA$BA$PBC0BCBABi`A@AACCBBBCDtBABBAB0AC A C!CCC^C\BB @CBAOChBABBBlB4B\BBCAC0AB$BC !CBBA@BC3CC@A\C B^CB@?pBB.CB?CxB<p( BPABYC,BWC1CC CCpBBpB8BBC`ABBBPB:CTB@ACCC6CDB@KCCBBBHLBC@AApABBBBAA APBCB9CtBABCAAL0@BbC@A B;CpA&@ CCB0B?BTBB@MC C0ABB&CrC p B@ACAB,BBCB0BBCMCA0BBCABBPAATBBBCBBTBCB8BXBABPC CC@? BCPBCBCC@B CBB|BBBC@BBB4`ABp@ BBB*CCABHB9CPXB@C C)CBA#CBC|BA@B,C0ACCB+C-CB@JCTBCdBBCBB@A.CB@CAxB C\CABAllBCAXBAB`@BECCALB)C.C@HC XBABB+CP@mC'C>CBBBBA@BBB A) A[C A @BBBC@BBB A`BXBBPA CzC0ABBBBBB@B BC CHBBA`BUCBBC B ~C>CBB<<AAABB AB@B@ABCA CBBBBBBBB@BBAB1CC@8BCBCBCCC4BB9CA @!C AAtBpBpCBBHB:C@BcCBBB6C4BBABC>C=CB;BC`BBBBBx2CCCB CBCC\CBpBPB[BBC:TCcCbC%C8B@BHB`?CYCBPA,BCBHBC B7C@GB@BBbCB@Al$CBBB%CCCC;C8BBCBxBcCBB BP6CBECBClBLC C.hBCBBZCpAChBCB-CHCBBBxBCAB|CAB%CBwCBCBBHCBBB.CB@ B8BBBpA0BC@BjCE`AP CBXB0 B%CB@CPA ACCHBGCBB CP`B0ABBCBoAPBCC CBCCLC,B0AABBBCTBB\ A&CB$BBCAxKCCBB4C$BpB TBC8BADBBAB%CCBPC6CCBBBBBP-PAAB#C$B0BB+CBACp@ C BAC`B, A4BC0C"CA@AHBHCCBBA0BBB:C'CB44dBCdBA}CC@B@@AB4CCBBCBBBBBBCC@BBB9COCB$BFCBA BBCA@B4CB?BBCCBNCCCBdBBCBBC#C`CC@ACAoCCB BAAABBDBBB CXBt@BC`B ChA$B?HCCC0CBC\C4BKB?|BBBNCKC7CB$B@@@B9CCBABBBBBChBBB4L8BCBC ABCCC,BBB"CCTBA]CJCA\CPBBACBCB*BHCCB B|BCCBCB,`BBB9CBBBPABC;C BA%C@BxBBA<0CBDBABBBBPB0C4B(BdLB@XBCBx$B$rCABA0BB$BlBCCCB(B6C?\@ABpABABB|BA CBB0AB$t BP\B`ApHBBCtBApACBBCAXBiCCBBXB7C<BBdC]CBQC1C\ ClA@`tBB`C,B@B C@@B 8CBBALB3CCBZCB(CBC C(BLB?BC@AMB.CB#BAAPBBHBAB"CBB C`AABlCCpAB(Cp CBBCBA)ChBjCTBCC"CCALbCJC@,BBABVAiCCB@A ABBBHBCA B CWCBb4@YC B:CC'C@4B(BB}CCBBABBdC\CBBPBCBTBBBDBNC C(C@RB`B,BBB`CAB)CBCC3C$C(BTB/CBC0BBBaCDBABAB B'C BBB$TBPBCB4BGCPA!CCC?WCBB,ABTAPA@@PCCCH@BABATBABABCClBCYCBBB)C@@$B|BCCB BBBB1CBxBBdBCgCBdBABBA:CBB(B(ChBCHBt CB CCCBB|BCBC CAM0BBB7C@AdBA0CBADBtB#C6CB8B BBBXACB*A=C-C?CtLC`B BC pTBdBBBPA@BZC C`B(BBBLBCBBBVCB'C3C8BB0C0C@BC CB&C1C B@B)CTBAiC"C LBCxDBB*C@A BECFC@BBC BTB@ABBCBC C@BHCC< A!CNCB@BB @@BCBBd`BCFCB\A(B?lBAC?C8BM!0C CIC.C6C`Ct A]CBDBCA6CCB0BXBHBAAAA@@BBABAClAC"C4BBB<|BCCABC@CB(BGC@BBCCsC CAC@BPBGC7CD<BX8CCCCBCPCBCBBBCCCABCBdC BB@A(CB8dC BMC9@BBCBPBAPC<$BBCrCBBBB C`<LB@BXBtBjCB4CaCBBAC5CCAB"C$C@BbCAB@BCBBvC@@BB@B_CCBB A@CJC@B C@8BAC0BBCB>CBCB A( C0B:CYCBBCXBpQCC\B BBBA,dBCCB2CpNC0BBAHBhBC^CB#C?8B@TBBBTB AABCBhBPCqC BBBHCpBAB6CBBA A1C$BXCBCpXB@A BBB\CABBAB $BBBBiCXB1C4BCABlBCAB"C=CC3CBCC3CB`@@PCB CB@ACBABBTB:CB$C(B'CBBp$BBABBAlBAFC"C`4BDB<AIC@CB,@BtBAAC C"C,B$C@`B:CB9C|B<' ACBCCC4BaAAxBB|B2CB@tBBPCBBBBJCBC<pB0BBBAB ClB0BABABAfCB@CRC@p4CC`BCQC CBBC4OC\CAdBBBCABxBNCbC0AA8BBBBB7CBA4B CBCBA@`AA{CSCCBBBC$CB2CCBBLB0BBiCCB(4B8CBP@ACBBBA2CB ClB CB0BBABECBAdCB@ CCCBBCABPACMCC9C`A3ChBCBABC C@?BDC|B0B BEC~CBX-CCiC$C4BBpACC(B%CBA B`HBBBBzCBBC0A_C 4 kCoCDC\C CpABB CBB{CABCBFCBACxCBAgCYC0A AC@BBBHBDB CBRCCRC`C ABBBA@@BCBB'CB+CCtBP00B CBpA\tBPA;CCBBBB@CBBBCBCYCpBBBCCCACBBBCBC`B BBCB`AlB@APPBC|B4BBC|C(BEC!CB#CC0BBpBC/CAKCBoCCDBABBBBBBCpBBLBBCBCBCBB`AHPAB CC.C0A|BHB\C@AACPB#CB1@@CC6CB)C?CABC.CDAPB$BJC CBpBpB@CBB8B%Cx@ApBHCPBBBCCBCBB@BBCtB`B@@BBB DB CXBCBDB9ClBA>CpCgC4B`DBPACBBBA(B CBABxBTBC8C`CC hC C@ B81CBABAC!C=C C0AB`ACABBCC0CCCC,@BA C2CACCBBBXBwCC(B@B2C@CrCYCeC0Bx BWCCCBBBCKC CBB8BACHCBPBCACCBCC5CABB CB? B(CCBACBBCBXBBClB@pBBBCBA?BC\C#CTBCBtBBBBB#CgC/CHBCBCHC:C CBChBAhBBmC*CBCC@@ABBRCBCBABBCRC C|B@CB BBBKCCuCBWCJCB8 BB4BCXBCMCACcC|pCB BB'CB@AB`CACC=CBAC]C CxBBXACBC,BH]CBBB CBBeC (BCBBABBBB9CB,TBLCBCBzCBCCBBBpBAAoCC4BCB0BQCBCLBBsCHBCB'CBBCBCCqC4CY,BCCBApBBCBBBCBC0CBBBBBCB0BBBBCBBABB8BBTBByC,C CXCP%CppA6CBBBC@@eCBCBCB0BzCBBCAPBWCB|C8BBBxB@ BbCBCBBAdCNCBBC!CB CB1CCBBBBBBCBDBAtABCB(A/CxBACC4CBBBABB#C2C%CBCCBADCCC0BCCDCC\B@BpACB}CXBBB`BB2CCYC3C B8C_C C@BABBA@nCRCpBXB B"CPCB@BBBHbCCC@@BBB7C4ABA>BdBBC BABlB BBC,BA.CFC@9CBB.`B@ACBCPA0CA&CsCA#C"CKCB@pB$xBpC%CBC@B CCBC\CAA BP(CHBB LBpBC@ NC* CH|BBBA8CdBAB`ChWCBBBCC@lB9CBtBBTBSC\BBA BTCBdBBA@@dB8CCClBdBB@iCBChC,BSCBBB BqC7CgC+CBIC@AC&C@@CBBABACC+C BHBB%CCDC?DBAwCBBBCBChBBCB^CCP9C]C4CBhBBqC*CCCBICRC@CBBB`CUCCCBPBACBBC^CXCC>C BpCCC;CCCCqCAPC,CCBBCCABBC4CCC3CB CUCBBCABCCBBZC0AUCBB0A)CBCBBCBNC`CBB@CxCCBC`CBEC:C=C C BC@CBtB&C0C|B@ABlL,BPCC3CQCABdBBCBC CBBA\BBCC[C CBBBxB9CCCZCAA`BCCCHB(B(BSCBCcCC4B`BYBCB%CECADC| B(BCCTCCBBA)CB_CBBBBCvCPB8CBH$BBBLB@PAC9CCkCBB@)ClBAB0CCBBBCTCBBBCd\B0BCADB#CBABCB`ACCA`B>C4BB8@BCBCB+CB@B ?CCKCrCBBCCABA CAnC(CBaClfC@@pB@CC1C,TC0AAhBCoCBC"C5CB@ABHpBAB AC< A`4BBCBBBxBB1C8BCBBCC=CCB@CC@BzCCMCBBBBBgCpBRCYCCB[CBZCBGC C\BGCBpACMCBMC;CBPAC@BB CgCVClBBBBB@BCCBBXBBmC`CChC^C-C`C C ABCBBBbCBJCC4BABB$CC_CCPBABCCC*CB B hCCB+C5CBHB(CC9C$CBjCBCCBB@BBuCC8BA CCgCBSCB`CCAACB|BCCB@BS@B BC,C&CPCkC@C C/CAC0ALBBhCOCBB CBBAC ABC1C0BC CA@A@BCiCB-CBC?ppANCB?BTC@ pA@CBBC CC2CICCCCDBBACBB CC &C%CBCXBCB=CB CC@CBBBRCbCAlBBC3CCA CdBBT@BBC BkCCBCpBBBABXB`ABBHCDCBA-B~CrChBB1CBpBACBBBAA$ BBA/CBlBTB,B0B\BCBCeCCC#CBCCCCBCBCpC*CCBCCCCBAPB|BC7CBBUCtB@ABBBCB0BBGCC$"CDB@CA-CCCACBpCSCC3C?PCBCB@AA@@AADCCXCC$B`AB7CCB@AC"C CBGCC`AB!C@C0ABBC C;C(XB+CAB04CCxBC4B vCiClBC>CB?`/C9CAB3CC:CpBBBB@CC`AACBsCBBB@|BCdBHB#CzC C\B2CBC CClBTB@BOCCUC4C !CBB C CRC BPmCBCmCABtB`C:CpTBBABB>CjCCC,BBCBBBpBA!C#C CBH`BWCBBACBC/CCB|BBCB\`@BCCB (AACCBA@XBACWC`B@BB>CCABABCBCC @$B@C C(CBPpBCB`ABBBLBSCC@@BBChB zCCB%C&C`AAlBAA$ @@B{CCCBBA:CWCBB3CBBxBBBB0CBBHC@CBBxBBBBAiCBBAB1CB|BB$BBBB \BCBXB@B=C]CBBBCBBCBB"CC@BCt.CLCtCBC3COCBBBBCBB CTCeCBCBABAECBCBBCBBBBCC 0A BoC3CB,BBhCYC PC?C CBB"CH@`B@BxCCBBB A C$CZCAB0BB/C-CHCCBBBBBB.C5CpDBB:CAPBB"CBBOCTCBTBA&C-C%CBBCBC8CB0BC@@B_C CB(HBCBCCBCtCBPBDCCCBBATB3CCAB,BBB(B@BAA4BB*CCBACCC@PBBB,BAXC7C@`AABXC&CB1C<BPBHCCBHBKCBBBDCA BBC0CB`B`C@A&ACCB,BBBBABCBCCC0BB|BBCBcC(B@9CBBC $B7CRCC`AByC\CdCBTCBQC CB$C4B CCcC1CDBCCALBBBB{C,C5CnCplBPAACC>CCB8CC0ApA0AOC'C`AzCBdCBBBAB@4FC`CABBA@4D$CCC,CBP PBAB7CCBBSCC|B!CBC4@CCC4BBBBBCBCCB0AtCB C/BkC@@LBCBBCICBdBBA (C@CDCBCBp!C B$CCCRCBCBsCCCCCBB CCBA]C@BBCBCCBC(C@>CBCCwCFCBBlCNCC^CCeC CKCCuCClCCCCC`BCCCCCCCC2CB@CDCsCBcCvCBC)CCCC9CBBdCCCCCC$CBBlCCoCC9CBABCCBBACwCPCBC4CCHB`ABC\CCCSC#CCBCCGCC'C CCkCCCBC CCBCCTCPCClCZCCCB3CBJCCBoCLCBBCMCBCCCJCB1CCCBCLBFCCdCBBBCCCC ChBCICBCB@C)C C=CXCC CCCCCCBaC:CCBJCBBRCBRCCB0BSCCBCBXCSCCC1CB6CFCAC]CCCCUCCCC&C@CkCBBBCB CCaC|SCCCCCC&C]CuCBCCxB^CBBBCBALB@CCBBBBC.C BBC*CoCABCKCCBDB$ C C0CB(BKCCCbC&CBTB0ABCCCCCCuC*CB-CB'CBBB+CCB:CCTC CCC`ABdBC/CCSCCVCB dBCaCw@CCCtC$CCBBPCCC*CBABBCCBCBCkC3C@TCB@pHCBCBB BVCCBBBiCB&CB-CBC@AB6CBBB)C@B[CBrCCCB{CC,BBB6ChBC$CA0CBLC-C{CBBB0CBABCC]C,CBBC9C;C#C CpBJCTCB(BCCBMCBBpBpBB9CC C@@BTC%lBCCCCBCFC C:CB.CBBC{CC|BBCpC8CA CBC?pA:C`CdCBBBBB{CQC? CB6CB@BKCC_C B@BBBDCh4BB@CCC5CCBX BBBBB@@BB@ A*CC(CBCB[A|0CCCBB@4BBlCB8BmC'Ch B BTlCGCBCPdBB?BBBBCBBBBA@4BpBABCC-CBCx*CCCBB CCkC.C4BBBAClC;CBC CB,C%C[CBBA $C CB?BBQCCB4BB@CCBLBpB4BBsC A@CBBCBA:CBBCAACXABB7CBC BCLBBBB CDCCCC CHBAB5CB2CB2CC(BDB4BCCCVCBHBpAACCCXB BpBABCYCAyCB,C>C`PBA,B@ADBB`BB(BB BAtB:CB[CBCCBC)CCBABBAB`AdAC BBBC CBBnCCCB1C CCkCB@BB)'CBZChBLBB?CC@ A C CBBACBCB@BTBBAhLBBBDBB,B*CBBLLBBA0ACCC3CCCCWCCHCCCCC^CCCCCKCC[C(BBCvCB)CGCC CCCBCxCBBCBBBzCJC+CCVC#CCUCCVCBFCCCCCBfC]C)CCCCCyCECECCCC1CTBhCC^CzCC,BBECCCC A`CFC{C*C}CCB|CCCCACCCCACWC/CACBbC'CCCB>C@CCCCCCYCCzCBCCCCCBBCC CfCCCCCC CCABBC]CCMCC,BCCECBB`CCB[CtCNCZC C1CDB`@A-CCCBCBBfC0ABCC C|CCCC4CFC@BlB2C!CsCCC}CNCB7CCB/CCBCBC1CDQCC|CBbC!CCBCB#CCB?C^CrCtCC`BBXBHCC!CCLCCCCB2CCTC]C'CCB BB>C{CBC?CZC1CfCVC$CxBAWC-C4C1C"CqC\B2CjCBlBB CCB CC< BB(+CHBSCCCBxB4BBBdCBSCB6CvC*CpBCnCB@1C,C CC\CMC\ZCABCBCBHBaCTCBBBBTBB(BBCBA4C CAB CMCBCCCdC5CCBBB(CCCCABmCCC_CBCABB=CBBABBCBBVCfC=CHB AA"C$`AABuCBBCP9CBB`AtBCB ACBICBdBBC0BC@LCCTC&C4C"CACBCCBCCC|CCC4CBABCXCA@TCBB(BB9CDCBBCCC@ CPB?CCB9CBBjCCVC0B;CMCBC@BBCB(B@pB+CACC'CpBUCp 4B=CCC C+B(CB,BTCCB CBBsCBGCLCCCEC+CGCAB>CCBBC@BBB"CX@@CB<lBtPAB8BwClCB8B(CC BxBB%BCC00HxBC CBtAQCBBCUCB"CABBB#C0CAB~CmCCCBCBC/C@A CACBB@&CBB5CBB'CCAC;CBCB"CBBQCC*CLBBB COCxC;CBB@CFCA`A\BBCBBC;CpBA@CC$CCBBCB=C BBCD\CCBtB@ABBBB8CCBB@ C C+CBCB-CBA&CCB$BBB?iCBCBB@@UCCOCPBAC@CCC|BtBApBVCCBBCBCB@SCCIC$B BB CUCKCC@ BAHBB@@ CB@C`CTCACCC CBp@BBCBBCC!$B]CWCBBPjCBBA[C C CBA@$BB C\C C<@CB(C?CB@=CRCBBCBC;CCBBUC0BBAAC!C<BABCC@C8CA(*C(C"CpB4BBXBBBBBTB CCBCAaCBBBBC5C@/CC\B,BCABAnCqCCB/\dBBC1C,BdBSCBBC$C~C%CSCBBBBBAdC p1dB.C0AB A@BACBpA|BB CAPBB7CA/ B@BBCBApBCB#CCCC0C0CCCCkCsCBqC[CCPCCBBmCB#C$CCC*CHBCCDCPC5CsCCC[CECCCCCC/CBCCCCCRCYCCCCPCA'C`BoCCTCQClCFCCBGCOCB C0CCC@BrCCCCBBBCCCC5C.C CBBLCCCC CCCBACVC(CCZCCCBBCCCC\8CCGCnCuCqC%C0A|BC/CBxB\CCCBC>CBCC3CCCACC*CCsCGCChCsCCCCCC3CCCCeCByC2CC5CCC?CmCCCCCBxBCCBCICBCCaCCWCB<HCuCBC2CBQCB+CCzCC`BCC7CC$CC8CCCCCCHCCBCCA@CBBAtC$CBBCaC-C\B`CB|C'CBB[CBTB\BXBC?CBCCCLBBTCAdBCCBBBCoCjCPChBBCBBBCmCdBBBABB CCiCC`CCgC#C-CdCC@`BBBBCBBB|BA B!CCzCOC&CBhB`CHCAB0CdB@CBCBCBBC CB@ABB8CTBBCA*C@BEC&CBBLB'C+C@@uCCBB A0BCpB9C@BB BBA0CCBtBBhBhCBPB)CC^C@CBBA;CBCBB A)AA)CBAB5CLCBqCDBAB5C|BCpBvCBB$BpABC/CvCPB@BB3CZACrCBICCCCB?CaCBBXA!ChBBBBB#C(1CBPBBAAP@CpA4B@BCBPCQCCB B@XAC4BXB A<[CB(BlBPBXBwCB`BB CBBPB,xpB]CYCC=C(B$CBB7CCBBB(CCB@BC C\BB|(CtAZCHtCtB80BTCCA CCaC0@B3CBC9CCBpBDBLB9C@BC0B\BC>A CABuCCC|BC\UCHBBCBC(BBC C CBCPCCCA>C{C,CBBCBBCBDHC9CC\@WCBCMCB,BC>CCAB APBB:CeCkC0AxBB CB0CAACCBB`BACC'C$B,;CCDCuCtBCBBBH @CBLBC)CBABB CC ?C@ HBCBBpBAtBBBBB CCCBDBl+CA8BXCiCBCCC8@2CC C C,BABAA CB-BA/CBBCDBuC"CBBBDCBpCBC;C9CBBCAAC8CCpA|BBhB@.CCbCfCC@BCCBLCCpB'CCBBBBAp\BBLCCBBABPC*CBBB@C?C~CwCBCTC(BBCB$B@B@BC&CCBBBBCBBA CCABCCBlB4CB(BBBCBB|xABBCB\B!CC|B@@4BA4OCCBgCDB0BCBBBFCBBCpAVC0CpA BB3CBA BBJCL@@AB CBBBVCBADBzC@2C CC@CBCUCBBBpBCC*CA 8B$ByCBhBA@DBBBC(CHBC[C`B|B4B0BhBBDCCBCBCBBCCBBsCB0A@@CCCgCTCB@'CBPB CC+CB CBBCoC0A.CCB@BAB$ CBBICCpA`BAB@pBBWCxCCC@BACCaCXCTC^CHB$CBB^CHCCPwCEC`CBlBABcC/CPBB A`A@BBCA2CCCBCBC,BBA`BCABxB.CBB"CBBPh"CC5CLACB8BBCBBpCCCBBC4~CBB BB ClCCB CCB^CBBB`AbCLCABBHhB8BACCCC@A@A5CCBpB@vC_CB|B7C'CB?HBCBLC/CLB>CBBCB CKCbCP0BBA|MCBBACtCCBBB84BBB?BXBLBBB%CdCA pBC|BpACBA=C.CKCBXBSCBNCBtB0pATCCHCBhBBBBAvCBCBBC C!C4BBCCBBCB6CWCDBBHC[CCBhlBA@A@ACCNC@CyC8BABBAAAB2CBBBCC(BC&A CCBBCBB(BAB]CCPABB0BBxBCsCBB@CCC@BDBBC>CA 7CBC@A#CBFCC$CBXC$XC|C3CCBC`A@ADCBCNCABAC CBLBlC:CkCBBA@BACCBCYCmCXB8CLCC!ChBBABBB8BpBxBTBBBBMC4BCBB@ CBAABpABBBdBBBBC2CBCBdBBNCTPB"CBCBB-C'CACCcCAB\BB8B CBCClBCC@ABC CgCB$AB+CCB;CXACBCBBCFC`|B'CB\BPB8BTBBBC$BCCAB2CCBC!CB CBBB,BCBCMCBB0B CBBBBCBBB@B@2C!CBABBAYCUCBBABBBB@`CC@BB1CCiCPCCe4UCB CBC9CtB@CLBA CBABPBBCCiCFCAB!CCCT'C @$CCB<BnC`ABB\CBC_CBBBB=C%CBBB0ABCCB$@AaCCBABC(cCBBhB0ALB`t_CC9CABCVCB(BBBB@BhCB(BDB0ABB DB BBCDBB\BHB@BC0AAtB*CAZCABGCiC0CCAB[ChBABCC CJC$BdCC]CE# BBCBBABC\CPxBB@BOCB@(B8CH@(BB@TB BBCB,BBB09CBA C@pPATCHB+PBBtBBBHB,BB B&C@-C@LB(LCCPBD\TBC@B4PA ByCCPA$CB:CC0A0BB96CB0`AB CBFC`BBB0BVBBBdC CxBCAdBBL3CB@@$B`C0A8B@AT@@0B0TBAC@@dBB(BFdBLB$CC*CB,BBBpB0AAAAxBBCC@@HACBCp@@(BCBHBC0ABB`BBp<A$BgC BB C m BBCB4C@PBBABCBBPA@B&CBBC&C3C*CBC CBB ABC$CpBATBA:C0AB&CC@CB@bCpACB:BBCCABB ABCCC\BBAC,VCCHCBDBCBC!C`AhBVC@ECqCBA CB@@BBuCCLCB-CCAC$IC,BC`BBBxBCB2CBBBCB B CBCBBBBBCnCB@XBCTApBl-C2C CC A pBBkCPB#CBB$BCCBBABDCBB8BTBBBBtBB<AB$B4BBBBPACA`ABBCC4ClCB#CHCABBBC\C CBB2CXCC?,HCB\BA\B8CACNCBB4BDB?CBpA0B CCB4B>C CpCCBBPCBpBC:CCBBBBC@A@>CBBHBBAUCCBHB$A$@BBC&BpLBdBB8CBB-CAABBECB CBBB8PBxB&CBCCB,`ACBqCA0"CBQCPBB`B`ABCBB$BBC?`Bl@CC BA@BA$BCPCB+@1CC7CAP C/C0BADdBApA\BBADC`@0BCB(B,@BB@A0AB CcCBCCB@BKCCBBPHB,tBBCAAqCpB tCBBBABTBA8CDCAApBBB3CCB0BxBBCB`Bt1CB\0AdBpBOCB|@2CBlB^CgC CdECBCB|BBBC BBXBBBCAhBp%CCBzC@@B,B,A$Cx8 CBAC@DB=C@BCBC@BBB A`CB@`A@B,BB9CP%;0ACBBPlBA4CBpdLCC|BPCBC+CBFC(CADBBPAP,CBBpAdBBCCA`BSCDC8BAAAPAXCBNCB l3CBXB@@BA#C0ADB-CCLC[COC Ct(BB8lBBAp$CCp#$CBCBBTBB@A AJCCB?ABbCB@0B@rC0B `PATA CC$BBCHBBJjCPBAAH`CC + BBAAAACa6CBBBPBBB>CPAB(B`AB3`B!CgC CCBC AA8BCB&CB0BBBBB P BABBB@ C A B9CpBC0C@@BB C,B@BB@BC\BBBB4BB#CXCACA@BhBC@AtBBBBfC`pABBBBBBBhBBC BBLCB\BhBA\B'C(@ECdBB)CECC\ BCBe ABABALBCDB(@C CmCAh`CBBB4B-CBB@BB^CCTB.CBBBB@BCACBpABCCAPAABB0B\BPBB| BBACCAC@CC@BABCCB |\B XCBBBACBBBBDBOA`CCA8BAA9BCB BpCB\BPAxCB4@ @@PdBBBBBB|BCC^C`PBBCB4BBBtBCC@@DlBB CB PAB@@BB*CPABB>ClBB!CB@BCCCB0B$BQCB@BANC@@*ABxBCBB30B@A@h>CCB A BB(BPABA C)XBAd C$CCC@BB8B@AKCBBGJ6pAHpBBBlBApA08xOBXBCB TB@,HB CPB@tBBC&C@0ABMCBBB0A0B B@A`BaCAP0AB`B0hC@@@<xB^C$CDB`B@B|ABBB@0BBcC\BBBBCBXBT @uCBB A0@CB@@@A0CBPB_BCBAC^CB@BAdBlB0ABCnC0BBAlBBBDBB`BB(@8B!C AB .CPAXB@@PA0B:CAA\BB]C$BA0BC(BB CCjCB@@B`@BdBCC0B tBgCfCB BCBBCBHBBBBBBA4A#C@pABBNCNC<h BB BlBBB B`B@}CtBCBBC8pB ?(BdBHB4BBDBC"C2B Cd0ACB`ABBPBCCPBtCB@CBBAXBA pCB=CLB CApA0CB CCPCB@B@@4CBLBH`BFCCCDB\0BLCBB,B`AoCB A+CBB<B'CBd@ACBA8B?ABCLB)BSC+C AB%C(B!CCBAhBBPBBBDBBBA/CA(PB AB@CwCTBlB"C`ABDB(A CATB0C6CBB BBPA AB(BB`CB'C`AB0$C`BB@BBBBBB|BB@LCA@xBBBA@B(B!CtA pA@ CB JC BCC@AC CBACBI$?B@@B@BBCTBmC`C(B`[BABBCB#C$0dBTB0AAHBBBdBCC8APBBBCABhBBxB0B0AvB8BBABChlBvCABB|A$CXA C5CbCBTB AB!CAlBA/CCBtBB\B!CHABA0-CC BpABBA@BBAL B]CB0CC\BABXpABBB\B@ ABBBLBXABBBLBBB$BBDXBBBBA8BC4C CxB$BBCHBB&CCl%CPCCCBAABBXBABB CXB,ECCTC|B\BXBB3C BC CA@BBXB@(C CBlB8BBC BBC@ ?,B(BCA<|BACjC'C@(C$1BPBCCpB+CtBCHC B CLB`^CCB(BB@CABAB0BBC]CBApA!C"C0ABB4BCBA0BCBAMhCBB.C0ABBB B@DBBADBAA(BBlBB*A C`AXBB?tBcdBPBBBBC@A@`A&CpdBLBBLBB C:PCC@AXDBACTB0B@BBB1CxjCnCB>vCCB0CtCsC|BB ChB?B4CCB/CBBB$BC;CPAB5C/C8C d@CCFCBBCA BBC|C Bp@C'CC@AB CA@CrC\BBBHBvCCBBA?HBB BB0BBBDBCBABx CA@A@tBZC\BpBB%CB!CBBdBVC0AB$CBCB%CB8BA@@CABQBCA A@K@ BB-C`hTAD7CdA(C(ftB;CCB@ 0)4BCLCABBCAB@BBBBAAB@@AAmC?C(CBTC_CBxpBC+C@@C~CHCCBEwCBxBBB`A CABAB\AB B9C|CL7BBlBBA\BCBPABC!CxBCBDdBB%CB+-BACpBBBqC[CCKBEC<B7C`B 4BBBA|BBBB[CBBAB`tCCPApAB BBAB CBCBBJpA BBHABA BPALBBC7CC\BBC+C5HBAGC2C,pBBAlChBC?4BRCCB CA8CBJCCB?BBBAA CCA+CBAxBXC!CB,BeC8$CBpBBlA(BBLC"C CCdB@@BC3CB@B AXBBB|C$A BB (B0B,BhCB2B \BBxTAhCVCC?@pBECDB@CBB@)B\BB A?pBBA&C0ZAA=C0BBtB(BABCGBBHC@B,oC CB C!CBBP0Al C$B'BPA_C8C(CALBtBB@B@@@@`A;CxBhB@BBxBB3CA(B@@BA<CBBB<|BtBGCBB$L`ABCGC@B$BC?@5@dACBAQCBBCBBCBBiC1C_CQ"CBpAxxBBCPBABPB3B'BXBB(B|BBCB)BB\B,BB5CC@ LBBBBCC B5C8BBCAAB@/CHBBBPBBB\lB CC(@@CBBB BBBaCC CBuLppB5CCAXXCSCdBB3CBpA0xCYCBBA;B CSCBMCBB CBBHAxBBBB`B@`BBCC$B C`BA|BA<BVCA| CB,`BAA(BpOCB BPBlCABCB$-;C(BABBBBBkB6CBB CBX0HBCB0BBBAB)u?%CC1C CD\0ABBB0ClC BPATCpBA\TB8 CBdB BlYCXBOCBAB?CxB|BBOC BBrCBBAB*S4BBAATBBB'tBBC BCB BBBJBB(BBAA(BLB< C`AXACTBAAECBMLCCBKCgCB@\BBALCDCAzAC%CBBTBPBBBA CCABP=C@BLBB@BB$BCTC%CBCBB\BuC CxBhBHhBBB$AB@BKCACpABZ#pCLC~CBuCBxCBCCMC@BXBB@@DBTB(B@CBP@?CBKCB@A$BA%CpA*CPC@&CBCBtUC|BMCB B(BL5XBA@AACB@! PC8CBBB( BA(B @AA(BBBBB@&CB0BXBCBBhBCCBBBBZCCd|BCB\A=CC p@wCCTBP@BXB1CAdBBBBBCB@B?AAB7CpA`@C$ C#CdBB`$`ACBB AAATBCABAB@A\BBB@BA C@BhB@|BBlBCB(PB BP2$ C3ClC3C``BB=,pA#$BCACACd'HBB0BABBpC2CB@ CB@ BdB2CB@@A/CdBlBxBB CBB,B_C@2CCAB$TBCC(BHBBA4BCBAhBB$BC@A\BB` B @PAC`|`BhBB 4ABABBBAB@ `$BAjCBH FBBeBBBDBA C,CBPBBBBB.C8@ABLBC@A08BBDCB@BC BpA`dB@B(\5CBB4BBBBBdBB0BHB`BPCB B C2CB#0BCC||B,@B\B CABBB(BB A0ABB0C$BB@BB|tBDB|C@#PAABBBB8BDBC$BX%CB`B``9CAABTBBB\+C B0B@pBQCB`BpA2ABB$B$?BCA@ABDBUCBC*CBAALBBSCB@0ARC C<BBHtBpCpCBBCAAC@AB@CJCCt BBhBBBBCA Cp5B BA,BAhB%CDBBDBdBEB4$BBC$B.CyCB0C<0xAOVCBLBCCBB`AB,nCCTBCAT?BB@A$B80BBCTBPPBBBBtBACB $C\BBBDB8CB0B CBBBpA@A B0AC(CCCBTBA<OCXCCB ABsC `|AB`ABBAxBBABBB`C|BA CACBpjCCC @BBLCCCABDBCABCBB?ppA?G%CBHBdB@CB8dC?C$BEBBCBB BLBBBkBC{CB0APB@@BBBB/CBECBA`BCBPABpBBCBBB|BC@BB(DBB&CxBC@BBSCJCC`B0 CDB-@NCZCBHB@BA C-CB B0BCB$BAAB fBlC BC CCBTT(BBWCLBANB"CBlC@0CA@AHB CBAtB@@5BCxCAB@UpAC CBXBB8B@ApiCB%CC4B`B<@ABBCCClAA0`BABpB,BBBBAACAB?AA5CBATBBBxBKCCBW CCB@BB)C?A@BXB,@BBAAC\BCpB`BTBBPABsCp@B$BBCABBB'CBAA'CCB@HECABBBNCDBlCBXB@@@B0BAdBABBB\BPA C0B]C?sCCBBB0,BBABBC|BTB@BL0B@C4B B@B`BBlBBPBC@BxfC0BHBLBAA@ CBxB0TBAB1C|B49CBT@BBB8`BB@ BB\B 0ApA2CC`@_CC`ATBBtCJCXABBBBSC C0x $CwCB@BCbClB4BB?@BBB06C4BABHBC@A?HB,CBBA`At\CC`ABtBBBBpBLCCCRCA|OBCSCGCB A C>C@ABhPBKCC@pBcCBA CCCABC,CBB0YC'CB<<LCBpABB\BB JdK@CBtB BAJCB BB@B<BBBPCC@Bp5C B22C CAC o0BQCBlBCBsCBA(?<B@BPBAXBCMPBL,dB.C:BB)C@ppA4BxABBBBBBCB ABB0@\CA@A|BBC@@BTB_C(C\BBABBLBpBhBBB BB`B`BB>CC CABXC@BPBB@ ABhBLB CB@kC8BXBB~CTBPABB B@BC CALBCB( BuCBBBBA0BPBxBB$BrCAC%CA pC*pZCALBL0B(B oCP@(BGCpC8B@6CjCB@B1C4,BPABBCBdBh,ABABCHI hB.CB`?CB A\ \BPB47BxBC*CB@@XBA@BAA?PB8B@BPB|B4BCBB0lBbCBBQCA0ChBACBBB0C BCA0ABBA@@BBBxCBC4$BCAtB7CB(BA+lB(BBHB@DB4B.CBBB[C@BBCB0ABJCBBACXBABCAPBBA$NCpB4BBtBBpLACLBBfClP`B C\BBBBBBCTKCuC&CPBABCB@BABPAP@@3{CBC A@`BABBB`+CA%CB@BBChCA B.H4B-C"CC0B BpALBBDBAxB(BBA~CCBPBC`BpALBBSC+CB@@BA(C.CCXBlBB,QCBpB@BCGC(CAA0TB9CBBXBB0B:CECh@C@pATB,C!5TBBBBD@pBABBBBpBBABP`ACB3CP?|C4BpB BpBAB,BBBVCBB[CtB"`B C CB@)C4AB@,C CCABBpCCBB`AHCCATCC C CBBA$C_CABABB8CxYCCB)ClBBCB|BxB(A`BCACBBnC8BCB@hBA CB C@L `A ?CAAd@@9@ A$Bz;B?BtB@`BAABCC CBB%CACUCXC.)CBBUC CB$BBB8BAt BB$BB C ADBEBOC4 B3C+0At @HBB0CIy_BLBACB,BECBBCRC@A4BCCB5CBKCBtBBBABBB<4B~CCB BBAhBBBl@TBApApA@BABB<3C@}CBPABBHCC3CB,Bh @CB 'CPB@]CCBPBAPBBBCCBBA$C CBPBBHBBB1xCgC5C CBABDCB dBB|$tBB4A@CC@CBBA@BBB5Cp)A(CBCBCABBB@`B ALB,BCBpABBhBB0ACCxsClBCBtBBBBBB$,oCB@B@lBC0 CA9CCiC B@ABBBpABBCCBHB\fCB0A A@TBxB\BBBlB C,BPB8B@4CC0BBCPC<'BA? ?@C`CBBp@ ABXCCA@\@HCP@BLBCA,B'CwCB 0BBz BBlB@ TBCB@FCBcCCB`.BCCCCABCTBBBBBCB@(0BB\BCx@BBP,B4BABBPPBBBUCBC ,CB+CpBBpA,B-CB BB)CC @BjCVCBBB C0LBBCCPBBCABChBBBCtBCBBBCABBpC|BBCABC,CAj#CCBBPA.PBBCBtC"C BxBBBADB&BB A0BBBpB@DUCB;3`?C6CBA#BBB@A0B$C'CxBB@0LBCZCB BBCBB BBBA`B@BBAC,?B%CTBSC BBBAG|BCB@nC6CBEC8H0BR?CCBx@AAX@CCBfC?!C`B|B`CAAECBTB -BCABBA+Ak`B`C)C$BHBCBBCC+CBB| ( @BPBB@rCBBLC%TB'CZCBB4BCB@@\A9CBL AB`ABB4B@CC3C%CQ0FC@@BA0B8C@C$B@AHBtBB XB BCB@B CBABBCB`ABtBCH@BlBCPAhB SCBBpABB C B(BBlBBBAA#GDBBA#CB BApB CPBBPCCOCJCHLBBuA?C?xA!CBAA BB-C C8 @@MCB]BTBCCTCBhB Ch BCBdB,C1AH1CBTBC,|BBUCBA1ABB&CBB( BHBC:CBXBPBPA<BC`AB@@dBCBBBB@@@CBxB$B4BBCB@ ACC00BLCAB@CBB@4B@@BBlB2dBCL,C C0@\BBBBC WCBC8DB.C B?CBB*BCtB"+B0AgtBABBB "!nCCA4B@hB2CABB `\BCAQC&CCB BA0ABABZ CpCCB/6hB0AB$B6CCA$B?CCCBBLBBBCCB.CBCB$4BLTBC*CD BClBBB|By@ CABp$BCBB@CByCBApANC@BBCCCC,ACiCABBpBhBXB`CB<BB\BBA@CC^CBB9%B|BA0$1CBABYIB|BBib@CLC CB*AC @CBBNC `BA$BCB`C$BBpA$B A+C@ALMC`CB@B@BBB|BB@@BA_CtB7C?CAB,BB4BBBpA4CBBCBBB@DBBCD;CB CBN`B&ClBCBLBBB CCBOBBB"C0BBA@BA_BBB B@BAJ9B`BBBCBAtB>CCDB BCB BBTBBAJcCFC@ACB%CC@ BCBnA,AB4tlBpBBAB?PBaCB0LBBB!CGCAeCCyC|B BB!CBBBBWCCB%CXhAABBCABXCCtBd@@B@BC0B@BQC`8B CBB0AB BA~CBB,BxABbCCB@@BBBB&CMCBAhBBCBBB?_C ABMC?C@ ABBB@D@ !CB,AA lBCgCAAL ABB@BApBBA!IA B$BBABpB@BBBC@C@ABBAT\B CC0CTBpBBABCAB8TBBClB AdBB@A#CaCB zCC@AbCB@A.C8 X,C CSCC`BBBBCBA;CBB!CChp$BCPCDBCB@AC@BA@ BCCCZC[C@BP~CCxBABBLAPB(CsC$BBBAtAA CBBCBCl$B@B@BPA`T CA$J@BC@CB`@+CBTCBAA lBBAtBB0UCBBBC\@BAP@A$BAB@A,BB$2 BCrC(CBAWC BCB.CBB)CBB4B TBAC BBtBA(B$B@@B,@ 0 BdB.CBBDC AC0@BB0BDA AACA B$C C BDCC,BBC@A 4BABXB(hBpB/CBCzMAC@@$C8PB3B CtBDlB\B=CBA3CLBA`BAHABBC|8BBXBCACBCB$BB0BABaC4CxP?CTpBTB BXdCAhCA@.C`\APB'PC(C\B|BBBHBPAB8C pABCC@ KC0LB(B$C,CCOCD$CCpApB`AA@MCTCABBB.%CBBB CBHBB5Ch"C(BC@L,BCB@@A AA0 AA0A B|BLBB CBBH?(BDBPA BRCBBB^BC)CXB@ BBpBC@0BCLCACCBC3TPNC5CApABB@A@BTBCBCB@@hB8B$B@ABBB,BB)FC4BAxBT @ A>C*CpB7BBtC,CA B@CeCA,BBCBlA`BB:AB#B0B"CBCC:CB0ACC4`|<B@Ac\CBt`BChlB$B`p@BBh,B\B CBABBpBBB BC@-CA@BBpCA@B A`BplBA(AlBjCBhB?CTBApApB0AAB|4BHBtBB|4@PBBBBB(B$B @@BB`ABB @`#CBBA iC LGCB@A$BBACAB BAPCthB B@"CB8B`A5 BACBkC7 B|BBDBtBB9C<iC<A%B-CBtCBPBP@A@A"0BB0sCBAB;CB:C`AB@BBCsCaC;BAPCPB04tC$CCCD$BPC"C@@ A| ABiCBBA6 AWLpA(B(ALABB@2ABBB BQC B@MCDBCUCBBB@0@B|BTBB)B CBB,CCACXA CgCLBAlBABCBBCBA@@:CBB$&dBRCCC0ABSCCB C@B\BCADBlAABDlC?CPAABBQCBC|PBB}C,CB8BXBCCB4LBL6C CACA0BAB`ABICB`AfCBOB{CABCA tBBC<BBPABC\BBxBq`A C|C&CA CBCBYC@BSCBgC\BBDB C\CA$CC BBB)CCABCCBBxBhBBBB tB()ABB CB`A B(CCABCBBABBA,B4BBCAHBCATCDBpAA@@BP@:C@{CCA@AAh.C AdA&C@CXpBBC\BBlB8B CXBBBHB0A!CACAABbC*CdCHBXvCBxZD`B@C`pAZCBB-CCBB2ABB A CBC BADC#CBBB|BB^BBBBAHBA@CQCCBBBCBC`LCBB xDB0ACB$B`A,B@BHB0BTBpBLtBBlHABC@B B8CCptB@B C@@%C*CC`AB BBlBB8CxB CB\BB|(@L@AC@AB(CBBBB`BBCC BTCCTBHB(BTBBBBA C@CAC`ABB`TBC@ABBTB@@B BBB@BPdB@BBBxBLBlCBUCABpBBBBA+C@A CqCB`BA@@BIC8CBB@=BABAChBBACA8dBBBLB<LBbCwCBCA,BAB@BCCB x@A`BxBA7BxCHC;C/DBA A SCCAhBPC BHBNCAPBBEPACCiCC|BBsBABBC0AdBB\BDBPBHBBAdB/CC0LABBB4C,tBBB)C@B;CCBBAC|BB"CBCCBULBBBpBA<` BCCBB BB`B AB'CCpBB,BB2CXBB"@ pABBBdxBCB0BAAhB C8BBAB:CBA B C~C lpB4CCAC@A`APBBA@LCCDABCCxBC4Bt7CC<B,BB CBpPBpBCBBB<@A;C@B\CBtBCCAC(@A4BZCHC@B,BCBB)CAX CpBBBlBB@@HBCB C0BABXCB@B@BBA0ABBCB`A8BAgCBB%pBB AhBCpACBCxXhBCC BdB/C*C/ C/C4AB@@BBTCB(2C(C$C4BPBYCBLC#CA\BBCCA CDB At@CBTCBpBBC`BBB@BBAp`BC B@AB@B @gC+CB@[C=CLpBBA`BBBB,@"7CCBB ABBCAD@&BB+BhB4BC]C/CA`BB@)CLBBCDxBB B CBA4BCBBABBBpAB&pBXBB@@ BBpB BBBKCX@;CP A{CBBBTC4 PBT8DBBCC@@b(=CuCB+@AtBB)C7CC5B(PAxKCDB@Z\B{C=C AB lBhB$CB B`BAoCBCAC)CKCl`AC@CBYCC CCB3 B$OCCBJ($BCABCpB CAASCxBpAB@|,BBB8BCCBCBB}BCCB@BBBlNCBBCACA C(BCAC9CBP BCAL(BDB8B@CAB C(fCB%hBuCBB, <pB4CBB B?B0CpBBACA CBECC*NBB8t:hBB@B\ ICB$BAADBBB?0B6h0B|B@A`BACB LB$0B`AAB=C$|BB,Bh8CB8A,BA` |BBA(BAC\BAxBCB@ BALBBBB CCB3C@ABBXBDpBp!CB,ByTBBBB C44d_C`BB?BBBh\CCBC4BTBBCDB`BB AKCBAA`BC3C`P AB!CAB@ C2C!C$X.CB@B C`BBxBlpLCCrAdBBh B0CBB`BBPAHA1pC4CCA00ABCB&BA@@B 4h-CC BNCACBH=BBATBBBBB@@ABqCDCBBBp\CBBBCB BBAB=CtdB2SC8BBZCCTBB C/C@#B(. pB@\C]BL,CB`ABTBCCCApA0B$B$BcC6pBHB0AABSBBCBBCBF'CB<'B-Cx AATB9,BBCB4CBXCC@A`B CPA!PAB~ChBXBFX(BCCB = CMC\BB0A=BAtBCdBPBC=@BtBBDB B?MLCBKCB@8B@ABBBBCBkIVCPB A CAA@BBBB07BBATXBCA0B@C#CBBClBTCBAA@BBHBAaCB BOPAkCAhBBCBBBB6CB@BB<{BCDB2@`BpAHBAB@BP B0ABAPDHCCdBABBCCB AACBHBxBCpB`>C0BmC8BBpBB\BBC$BACBh@<AAB CC`ACp CB4C AlB8xBB'CFChBBBBP?AC CPCCC0AB CxB*BfCA$BB0BABCAB@C,@*CBC($lBB-CBhBBB@ACC%CBBLB(BAHB|BH.C\B3C0B3B@@HBBCBplBCL$ABBB B(CPBB@0A@@A3C"CB\BDB"C`BAB/BCT|BBBA'0B ATBU\BA<CA CCtxB@BLBpCB@TBDB0B/CBB0pA\BAC?CB@`BCBB# lC4Cd@A C|B(B@B8BBBUB&ACCx?@KCBBABLCB\C$B BABB(B8k@A+CC^Ch0BAB CC@@@AAPB@AAPAC2C@LB<B*BA|B `C0fBACChB+CBA`8BhBPB/CpABABCB\CCBApAVB`ABBC WC CHBB C2CB\B\Bx`BBHB,B@hBCB@B ABCBAB*Cp BB CBYBBBBB BBBBHB6CBC0$BB`tHAC#CBC@A@aCtBA A/C4BABP08B,B`BCA@@LBdB BCCBxB"CB C@BC0JBXCXCB#C!CBPd8B`BC4hB CB`C d|BtBBBCCC A$0BB&CB2CGCX =CcC[TC\BBB@@CCABB4OCBiBCGC'C4BBBBAD@A@BBBB@BCApAxBB BBBdBHCBD$BABBBBBTBBhBBA@ABPA|<BBHPBB8B @ACZCA@8AABCCnCTCsMBBABB0C|B"ACtBC4BB"CABABCP8CpAB@B`B\BaCdBQCBB@ PBABiCBBB@0C|BBBDB S'BBuCCCC?CHB|uBBBB$BBBA@@Ah`CBtBBDBBMBBXBCBBYCpA@CGC<BB|B$CBpCBBA1BAB BBB`CNCBHBAC,BB`BB,BBBC /<zCCC8BXBCA|B"CXC?CAA<xBBBB BCGCXBC HBBCBB B@BBhBBHxBqC`BDBBB0A@@CBaCAB$BBABAB@%CPB0AA@CBBBABB@B@\BTBBCD@AHB.CBBC8BBBcCDBBBB`A1:CNCXCABBA@ACpATBBB BBW$BC BB@BXA8B$B2BA(BA`ACPB,B@0BP@@@CA9lCpACdC\B_2C8B4B C,PA4B|B |BADBBB8B HBAB_C4B,BA@BpB,BBlB`APB0B-CpB%CBTB@BBB CfC@@Q,BC(C0A@ABXCBB`BB:C CB@AA?dBCCXB|BB,BClBC@BCBB`AA@CCTAACCBH:P@BBAdBC @BBAACAC0CB@@BBACLABAABBBXB.CXC@ApAB\CB:C,BpABB$CABC5,C3CBP.j CATBAnBBXBhCBAA@ BAA-B+CDBdBCA`B B`ABB00ApAB0BBB CB@&oC$4B BAHCCBABDBA\B@xBB$CxB`$BBBBABhBA8CC;CB?ACpBBCB$CdBlBFAB(BpBAB@@<`ACBBHBB B@B)CBHB$BLdBBBCB.ADBPpA AB`BAAB=CBpBAdpBL@AmtBBxBHB@BBXBCBBhB^ sCC@CDtB BBHB6CDBBBP W\B0CPPBB@dB B<XBSLCCCB0AC&CB CC A1CAC0BpCBABCpA CBLB B,HBPBBABBTBBBlBCHBAB$CT CBxBBECBB@03BCBCB@lBB:C3C|CCLB4BAB` CWCPBB"CB:C A$C`A2C`AB`BBCxB$BA4BB| BhB`CCAAAB"CBB@ \BBBCpAAB4BUC`BLB@-!BC1CBAFBB+CPB-CBTBB`BBA,"BBBA4B CBABL@0BA\BBBB@B BCSCA `B CCPP/(BBBhBBCDBVBB B=BBCB BB[CPBPgAIC^C\=CC`BPB@@BBBCBB$SBBBAAC C#BB,BBA(XBBBC@BBABC?CB-TBBxBB;CB<\BpBpB,BdBdBBB@@ACHB0BBBBB@0B|CB|BC484BP CaC*CBB@B ALB BC.CBtB0ABDCAxBBC BAAB CBBCCCA@@ABB0pB6C0BUBCBACB(BAABd@B C @*C?4C?@@BB@@ @CB\BEABB(CBlB B0AdACZC%CA`AABAB CCBKC&CMCnC<)B6CtC ? CADBfCBB@BCB@A@BzCC`BCAHBgCHB?C@XBB4CmAZCDCBBtB*CBB4BzCB`BLx@$CC@?BCBA ABCBB@& CBB.BBCXB0 BCBB$,C+C}CBLB/%BAlBBtB C8CBCBPB CApBg@A?BnC@CBL$4BB\B@ p8BaCBBBB`@@ `5COBPABBB)CBP#0BdBB@B`A0CACCB/PB(BDBC 0B#AB@C BC oClB^BA/CHBAAB(0BCChBAA`@@CpBCC3CoCBp Bh`BBB@UCA[@B@(BCBtB@01B;CC"CTBDB`BpAB|B B(BlBCAAC9C8x/CAB A|xB@A @DB.C@BwCAC@xBSCB@BC%CBABBLBBBALBBCpACABBC@BQCAC1CBBPXBp CCCA@OAXB@Cl+CBHBBABBCtBABAB<CBBCBlOBtBAH?A A CHB CB/4B BBAB0AB@BBBBABB0TXB%CC5CTBBBBPBBBBE[C CLB|`ATBA0A-C:C7CB\lC@5PCWCAAB5CCTBBBB-hB C BABpBCCCBJBBB(@DBCzCC@ ACBBkCB 8B'CABXB@27C@CpBA CxAALB)CxBBBCHB`AZ1\BCPBAABBoCCBABuCB8BBB@BCsCB$0K"CCq@@xC6CBG,BA@CB B/CCdLpAHBFC\B,CAB@$AA`BLBBAT<BB8!CBBT0BBCOCBA/BABlA BBBLBBBBB-@A0A(B BH@BC!CACBP$<BAB(BqCbCLC_ChB tB,AA&CBB@A\BBBBBBpBC~CB\BBBB AB@PBGC 4BBAAB4%CC@C8BBBBB B\B@CBBBB@PA4CC!C%CL|B@4B&CaC<B KCpCBBdlBAAPBB ~HB BPA+CPCdBBxLBCHB B8BAA#CABC@sTB CCMCdBApA0BBB@A B@xB4BD0 CPAKCBlKCCAT<CCTB0BxPAlBBBAB)CB|-BBB`BB0B<BCBBPCBB|B`7CBABLCCLAAC@B`CB4=,BDC#B@`A$XBBB@CCBBA\BB`WC0B'ABPA6CBABAC@C1 B BdB`$FCMCCB0CB`'C B#4BB0BCBAB0BBB@6CA A,B@@BBB$B=CC(BA ACPAA4B :CCAC7CB|B CBC9CC4BBB[A,CB(BBxBAB%CCBCB BB BhCBBBCpAADB@A8ABBBBBA@BDB@BC0BAAABB$BPBpt"ClBA@(BC=CB PBRClBBiCB@.C`ABPB2CP0AA4dB|BABABBIC0B4BABB`A@ BBClBPBCCKClBByCCCdH0AADB@4BPABBBA@LB2CTppBZCPABBECB@B0B`B BCBxBDBABB2CCCBLBB;COCAQ ABBAhBABB80.BC,BXBABBEBdB0CBA3CCCBVd;5C CCBB A@A@pABB`@ApBB C^CB`A0B?4CPAABMLCCB@B4B`BTCBCBA `BA` ABATBCpACBB+CBB|@pC)ChBB BC@B(BPABbC#CB|TC8BP@ABPAAC|BBBCXBpA@BC B/CBDB>C (B CCt\CpBYC#hBC@BHBBAB?tBqC\BrAvCBBBBBtBB B pB@0ABhBAAdC,CPXBCBAX|BB`BB@B<@BCACBAHB4\C8B?pA4BpBxCVCB`A,B:COCAnB6C BP`CA-!&C3CALBBBBB&C\B0CX SR-2469 626 0 0 -1 0 0 0 0 -1 0 -1 10 0 0 Gain 2 SR-2469 132 0 0 -1 0 0 0 0 -1 0 -1 10 0 0 SR-2469 403 0 0 -1 0 0 0 0 -1 0 -1 10 0 0 SIFXSigima-1.1.1/sigima/data/tests/image_formats/sif_reader/raman1.sif000066400000000000000000000203061514013333200250450ustar00rootroot00000000000000Andor Technology Multi-Channel File 65538 1 65567 0 0 1 1504875832 -50  0 0.1 0.117276 0.117276 500 58.6378 3.33333e-08 0 1 20 0 0 0 0 0  256 0 4 1 0 0 0 0 0 0 0 0 4.33e-06 0 1 10386 0 1 -999 1 0 1 0 0 -1 4 30 30013 0 0 1 500 1 0 17.7345 550 0 0 0 0 0 0 0 0 0 1 1 8 DU888_BV 1024 1024 66 D:\FV10-ASW\Users\Petro\exp_data\2017_09_08_Michal_Mona\raman1.sif 65538 2048 #2@#2`N`Np##x2gQG## #i 2#2a#q## ##-086624375832##i 2#P2P2h#B8#15538t##B#?P2#`#Mm 2#7`#uvP#B#Bd2wB `l##Btates.437 @u>wD:\FV10-ASW\Users\Petro\exp_data\2017_09_08_Michal_Mona\04o"264o"2"20#"206/(2#6/(20#K 28`#472G6-A#00#I?IP^BI`DIIGIPuII LINIpaPIQSItUIWI0pZI]I0`I bIfIPgIkI~mIpppIJsIvI XxIP!{I~I_IIMI`hII(Ih$I0IXIIxjIHIII IGIIWI0I I̔I IxI\I0ʖI}IHI0II8IDI0ۙI(I`ISIhMI֚II IٛI :IIĜI5IIIޞIII([III$I轡I I8IpI8IţI[ITII{II@I æIPmIħI(ISI(*I8rIZIZI@ڪIHjII@I(I8I8bIIIPI舮IٯIȯIHXI8I@IhI@bIPII`IײI #IhCIIIII I@ I IrIIIIHOII I I"II80IpI{I4IuIXaIp$IܽIIIhI8I8*I0IHÿII0uIIpII(IIIhI`II^I9I(I+I(#IIIIXOIIȄI`IIxIhmI8I IIxBIpIPIwII#IIIKI0IIPIIII/I IIhPIpITIX4IhIАII>II0I IIIIpqI`I\III@IH3II0IxIHIPIXI@mI(IIXI0IIlII FIPI{II0IXIIXII(vI3I IЛIIII0IIISIhI@I:I)IpISI`BIEII;I@(IxIIP#I\IJ JJ|0JJtJJ4J`J|J:J@II`II IIIpI;I #IXdIIPIx>IHI;IxI`IPIIIhbI'I(jIIH>I?IpIx@I IKI,IgIII IVIIxIHIIhI[IxITJ(I4J@8J@JJLJJįJJ nJpeJ(JJJJJ$HJ4JJiJJJJ-JJJQJl]JD.JJyJJ JĖ J\J JJJ8J VJJ Jx JH Jp J4 JK Jp Ji J Jl2 J`n J JP J J(% J( Jd J # J2 J< JS Jl J J Ji J Jt JT J< J(Z J J J J JT: J J JԞ J@ J J JĊ J J J J,J J5JTJJXbJJJJJXEJJ0fJ=Jl}JXJ'JJpJ0JlJ JJ|=J Jx4JYJtJ0JJ(JJ{J5J7J8JJFJPJJl?JpJ`,J`QJJ4JrJ4Jp"J0EJ JJ JJ\FJ@JJJ@JJ JJnJXJhJJHJJJ_JyJPJlJTJJJJlJT_JJȀJxJ@JJJX/JfJJJJJJ`wJdaJ JJJHJ~JxJHGJ(JJJ`J@J J^JJJ(JJJJ,gJ0J4JLJJJP7JNJJ JhrJJx J̊JpVJTJJ8|JXJJMJpJ3JtKJJlJJJ< JJJTJX5J`J@^Jl5JJJ Jp &JH#J< JаJJWJJxyJ9 JJTzJJ$- J41 J t Jp J!J!"J J`B!Jx!J:!Jb!J Gain 1 SR-2469 73 0 0 -1 0 0 0 0 -1 0 -1 10 0 0 7SIFXSigima-1.1.1/sigima/data/tests/image_formats/sif_reader/sif_reader-LICENSE000066400000000000000000000032501514013333200262700ustar00rootroot00000000000000SIF Data samples within this directory are redistributed from "sif_reader" project ==================================================================================================== Project website: License: 3-Clause BSD License Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. Sigima-1.1.1/sigima/data/tests/image_formats/tiling.txt000066400000000000000000000032201514013333200231030ustar00rootroot000000000000001,0000000e+000 2,0000000e+000 3,0000000e+000 4,0000000e+000 5,0000000e+000 6,0000000e+000 7,0000000e+000 8,0000000e+000 9,0000000e+000 1,0000000e+001 2,0000000e+000 4,0000000e+000 6,0000000e+000 8,0000000e+000 1,0000000e+001 1,2000000e+001 1,4000000e+001 1,6000000e+001 1,8000000e+001 2,0000000e+001 3,0000000e+000 6,0000000e+000 9,0000000e+000 1,2000000e+001 1,5000000e+001 1,8000000e+001 2,1000000e+001 2,4000000e+001 2,7000000e+001 3,0000000e+001 4,0000000e+000 8,0000000e+000 1,2000000e+001 1,6000000e+001 2,0000000e+001 2,4000000e+001 2,8000000e+001 3,2000000e+001 3,6000000e+001 4,0000000e+001 5,0000000e+000 1,0000000e+001 1,5000000e+001 2,0000000e+001 2,5000000e+001 3,0000000e+001 3,5000000e+001 4,0000000e+001 4,5000000e+001 5,0000000e+001 6,0000000e+000 1,2000000e+001 1,8000000e+001 2,4000000e+001 3,0000000e+001 3,6000000e+001 4,2000000e+001 4,8000000e+001 5,4000000e+001 6,0000000e+001 7,0000000e+000 1,4000000e+001 2,1000000e+001 2,8000000e+001 3,5000000e+001 4,2000000e+001 4,9000000e+001 5,6000000e+001 6,3000000e+001 7,0000000e+001 8,0000000e+000 1,6000000e+001 2,4000000e+001 3,2000000e+001 4,0000000e+001 4,8000000e+001 5,6000000e+001 6,4000000e+001 7,2000000e+001 8,0000000e+001 9,0000000e+000 1,8000000e+001 2,7000000e+001 3,6000000e+001 4,5000000e+001 5,4000000e+001 6,3000000e+001 7,2000000e+001 8,1000000e+001 9,0000000e+001 1,0000000e+001 2,0000000e+001 3,0000000e+001 4,0000000e+001 5,0000000e+001 6,0000000e+001 7,0000000e+001 8,0000000e+001 9,0000000e+001 1,0000000e+002 Sigima-1.1.1/sigima/data/tests/image_formats/uint16.tiff000066400000000000000000020004001514013333200230530ustar00rootroot00000000000000II*(1 {"shape": [512, 512]}tifffile.py8Z7                                                                                                       /XE9Y4                                                                                                    /YBAR-                                                                                                                        2Y=!CR-                                                                                                                                  2W?$!BV0                                                                                  ,XG#?[1                                                                                                         .TH%C^)                                                                                                  6UC##FY'                                                                                                    5XC!$DR+                                                                                                 8UC$&FQ*                                                                                                          7YA" $BQ+                                                                                       /ZA &BP+                                                                                                                      ,TE! (>Q.                                                                                                         /UC"#"@U.                                                                                  3[<"&"?V.                                                                                      3[>#%#?X.                                                                                 /]A!(DM1                                                                                                        3W:#!,EK5                                                                                                 5T8( +BT7                                                                                         /XA""-AR6                                                                                  /UB$+EQ1                                                                                                         -[D !*DN0                                                                                                *ZD$'DQ+                                                                                               'W@!%%DT)                                                                                                   '\A #"CX-                                                                                                -X<"# >]5                                                                                                        +S?!#";Y;                                                                                              .W?!$:R;                                                                                         2V< !>S1                                                                                                           ,T=! AW,                                                                                              ,W??]/                                                                                                      0V@ ;[3                                                                                                       .RD 8[4                                                                                                      -SE 6^3                                                                                                      %UG#5[4                                                                                                       UI  5V:                                                                                                          $RK"5W6                                                                                +UG!$5J4                                                                                                     0XD%9F4                                                                                    6X?;V/                                                                                                     2Z=#=S3                                                                                           +SA$>P4                                                                            *S> !=S0                                                                                             #OD";O2                                                                              %LB! ";P.                                                                                                  ,V>  ":S)                                                                                                 .U>##?R%                                                                                                   )Q@&"@U%                                                                                                !QF'! !;T*                                                                                                                 'PE( ! 9U+                                                                                               -SB%!"!5T2                                                                                                     )UF#"!8P-                                                                                                        .VD# =N,                                                                                                 8\=!!">K-                                                                                9Z<!?S+                                                                                       6X:#?R,                                                                                                                    6S: %?P.                                                                                          6O:"#;R5                                                                            1S8!! #=S3                                                                               /Q5"!!8Y6                                                                                         -O::Z5                                                                                            (T<AV*                                                                                              *T:"?R+                                                                                                 ,Q9'?O3                                                                                          .R<!&@P/                                                                                          +SC!#@S'                                                                                 (UE ES%                                                                            -S>%DS!                                                                                    +T>$! AS'                                                                                &VC!$@P+                                                                                   *QD$ =T,                                                                   .W@ ":U0                                      ~                          +`D!"6T5                                    }x                              1\B" 4W6                                      tq                              2\@ 9T5                                     jm                          -W?"  >O3                                 ^t                                     3T;#!?U/                                    |^w                                    0S9#&%<\)                                was                                  -^;'!<W)                          v^}                               0_?#=U,                             }g                     1TA#!DV&                     vjjssnmkny    t~  |mhZKOTNOW_t                         0R@%C[&                  ~vk\[cig_WX_gs  xiYGDJGA>;AMYn                      +RC%"!=U$                    vmdk|zjgnpjebabr paVZce_XZc^RNNSi                              0P@!"CS                    ~vtor}~{rgnvhgnz{iWWgz                          5S9  "!AW                                   tsz |ldphak|                    4T:! &BM"                               wwyt}xlaWW_qi_k                    0P>$'CL&                      |pjuvxvomefq dRHCFNXk}q\h                        *PA')BL)                  xgV]kfk{{bZWVdzwrUDCCGOZ\aiyjYc{                        %UE" (<N-                       xk\LP]cbegs{qma]ZNIUg{uzaK<:>@AJRLLWfyrmf[U\q                   #WE$#9T1                         mZNHKOU^TV^[au|umbaffb[PJKS]u o{}eR@9<;6;HOTQNTXb~~pcZVQRXn                +U;"">V+               z\MLHA@KVLAAIMW`cjsvoili[XVPQNB?83;EQg mqi\D8>=41<@CEGKNKITftworfQPNDGITs                   -U6 %":Y(                     ~\GKMECFLFEF@<:=A@@EIPVTLLNNRNAAA579=G[m hk g\L57<324676459EKFBEKR[ff`cc\\^IC;9==?Sq                     *[:!#:S-              ~bLKMG@?CLB99>B?69C@:>GKIDIONE?EJ=03<>:Ieu}chdXD9;97=A<30476;EC<CHEGIGNPIGIMNC42:;8BYs                         )SA#?S+                      oWJJIB?JMA=BDA=BC>BLLECDDHI>8?B:67424>B;Lp  |dvt^I;735=?=?<621333:=9<B@;@A?DB:9A@956;>CQb                                      -T?BS(                     zaLGKONCGMJEEHI?9BFDFIHDDGB:>D=1187593.>E@_pnkR?>:9DC66?<54735>====@A;9;<98843>;5689=IWn                            1X<  ?R)                         lULNPNH@@FC=AGC<=FI>9BF?97<B?;7873//16608@Rss~vpdJAB9>H=5:;:957<=;65889BD:1/17845;7/6;::@Nd                 -RA!<R*                   hTONMD=GOGACD?78=CEE@;<BE@BI@686/+*07:A<27Lbxt|vr]IB?9;;8=1'<B26A<;?;:76;EFB=83-,4>7,2769<@Vx                  .Q?!>T%                      bPOLGBGPJADCAGB<GI>;GE>88A?9=<7:;2-5859>85DYlzyhYJ??><99=<:;<71.:A74;:66968=83983;8*/>86=>Ig                           2V;!"?T!                     |]QOEBGKKD>?FIC=CIB?A@A<8AC:;?9:?8378447<;;ANh|}saRIA@<8>B=:98;8389/-7:558873354331460/7<:9>H[~                                 1U> "!=R%                 v^QHDEGLKCDD@EC<GHB>=@DCCA9:>3.8:6:<9736=;:>Hd{dRIGA=?94:919>40=<5::69:79<:45<6/54286/5@=8DXp                 *[B =Z(                 r\MIHBDOLAB?:CE@>>9:=GICFD;<?=A@97/0;5/:@<;;C^}hQJF?>>>@<745A=1;B59A7;?@?:46766/0971367<?:>Ph                  #\F?],                     jWQKFBDOL?>DC=:@G@?EDAC>9:>;6;?705715;64==9>HUuzhOLF=?@935>;49;7:3'0B@<;<<;3-022562./17AC>=BG^                 $UH!B[,                    jSRMEDFML@;>96?FA?B@<>EE?<<939B7-7=56?82=B::GVwjSMB;@C:159>@93:<9846>;7924>4/9747/.:83=>5<DGZ                       ([EFU)                   jVOKFGIJG?7:?<>GB7CPF<AFB<<;;CA20@=259:88=?;E[w~nXOB:>B?967>B=7=?<:8:<32>:6@<7<4*01/4/*5:5<EGT|                 *XDCU-                fWPFEMD@D?6;><@CFK>9B@<FI>88858626@?63788=D?C^~zvyXOI<5=D<37AE>:::<:8:61;B9375132494/8@:349=AHVr                 /WA>X3                  pTLFCLJ?A@99;;@DFF>;><>DCDE84@@2199=?429:=GBDdv}aOIB76=B<7<?7567<@<:1)03/;A66<54;619:1-3=?>IZp                    4YB CV+                  VIIAEHBA?77<7<HI?=GB:AF82==6753=?9=B51:;@HCJko kXI?9::7>C829=726;97:759;=7//42..16813<@?>=FZv                     3XD!CS(                 aGIIEKE:58::<;BHB?BB?>?><9>>77==;CG>559>BDFTr  ~mr} r`OB=89=<<FB67;89957439>7010/6801<?6.5;89=>H]|               /\B#@P'                lNAJLHB:<>:<BCEHC><9?>9AB<@EB>;:>FF<48>@CGN\|myzbUEA>7679A:4AK>48>8499..87374//496230.;A;?L^                   3W=! !@L#               tXGEHFDD96;>?FIHA>B@;@HB;@@68@<=BCC>6?FBBIRldp}i fYIA?>=74;=>==?A<628>933378--2((3.0;5,4::APg              5T=#$ @M                      dKGD@>52:<;;<FKB@IIABC93=C<854=A>DD:=?;?L` {W] y\NGA;>>5:B@@?=A:07?:633179/19557027549??@Ty             /W@"$@M"                     yXEJF47@=AH=:HJ?>?>><AG?6>>;EE;>EG?7;>>FZuel]  iRHBA?:58?AA@>>85;=;7328:1)0<92468:65:>>Gf          /SA'# >M)                    mM@JG@@?EKB=HKA>GD8<E@97:<<@@?FF?>@ABBQpjg aLB=>;339=BC=9;97=>73442/3:94:7,0=53;ACRt                1PC,!;S)                hK>BB?DE??DIGCEH@@G<2731>;3@E?:>?;>ESl~|XE??>:66;DH@;=;==;:4398984:?615886;BDLh                  6TD("?N"                  eL?=CMM?BPI<DJCCB:8<<6.4;:BA<BEADOWdvvUBDCA>52?GDB>;=::A=1/8936<:36944:?DNa~                 2YD'""CJ!                  {]NF?FUTKKLFGJC<99<;9;63>FCBABDJPV^ooPFB=B?27DCBD@<?@=<;;747604:6458?ELZo              2^@"%#>Q-             wWKE?BNRNLKLMDBFC;;==?FFEIHBDKMUdtgSH<;A;4:CGID=<:68;75=?78946>=>FMWn                     8Y>#"AY+          aQLECGIMOLGGHCAEFFEA@BDE@@JRYfvsaNB;778:AKQNDDC?<:>>55<<=A<7<I[t                  /SC%AY,                oZSQRNHIIJNKILJB<?DCAA>?N]hv `NKF@<89CQMCB:58?B@@DC@?87BOc                 #WI"!=U/              kWTZSKNNKLNNOQRUZWKBIU^hzoTKHEA?;@NRJHJIIE>?<568<N]l            (YJ#!:[3            redbab]VVZ]bhcQHVjmoiVLB?@84BQSOJB=>=<CGK\lx                (XH#<^3              {qppqwvpoojfk{{{iPEHBBR[VTSNINVW[l                 ,RF% @[.                    wnl_PUclprtvw                 /U?#!%@T.                wuz                   )X? ""%?V/                                &QG$"">Y2                 r               +SB#!%<[4                p                  .W?!"@\0             x              2U= "!AZ3         x            ,Z? $BV7                y           (XB !BZ8                p~           .P=%B[6           |}z               /O;%AW/          zz             ,Q<"# AY*             y~          /T8"'BZ)         y        -S>! =[(                      ~         (VC>W0                          (Y@!&=Q7                      -U@!'=R1                    -WB DT,                   (WC!FV,                   'SC!$HO,                  "QC&KS(                     )S<&$!DV+                       -Q@'#FW'                   4T>%!HZ                    ;Z: #AU*                   2[C  $<V.                  +\E"?X+                .XB!$:W.                 0U=""#8X2                 -TA"&;R0                   +WF!'>P'                  +\E$BP'                         +\F'>M-                         2[C #?S'        qmv     /YE#CR(        d          /WC$>P,       go      3X?DW%             y                  2X?EU&          v           2Y? BV'                  -TA!@V(                   (UC#7T5         x             #UD!$8R3          ~mlrv~            #WB #  <P/          nt^?BSX^r|z             %WE >V,         _eteQ^ifotlrsds  xjjy              )XF#;T-          kzzw}x{T]wzslXCHa{          (^E "8W6           r]Nhss      -UE%! =Z,          u~fVUf~         3MB)!FX%       le_`m  zrkv         ,OD)"BY*         ui`ely|tuz             -RB(##=R1         ~rblor    zt|        4U@# ">R2       {ko{y  {~      1SB% =W,           {}wp           1WE ;Y.          z~             1WG!!@Y*                    /NE%@Y&                            ,SC@W(                         1_>">Q'                               8[;";Q*     ~            2Y;"=S)        r               (U<"$AO.              {n            -O=%'>O3       ~qm                      1R="!=U3    lr|                  6Z6DU)       hyvzx{x                8W8 @V*       &^jrw|zp`          x           4Y;%:\1            ny~r`f          pr             2]<")!7[3           quzd[h    |f          +ZC $$=Y2            rkse\s     jw             0Y>! $EU,            wn{_      kq        2[; # D]+          }|yk        uq|         /a@ !?^.          s        x          7^< !&>X2      y              8W=!#";Z7             z    |        9X>! "#<W5            t            8[> !"@U0       q    ~|z            2Y?!!%C\(        o    ws        *\>&!I\!       uv  wvqr           2W7 &!D])       zp }{s\V             4P8$#$ =]0             fpg           1T<"%;\3       _z       -X>"$;^3    by            (W?!=`5     %oo          *L?$@]5                !my              *K<& F[1           lxy~m}         +O9&! FZ1             rlqxzfgs|         *R> %CS4        vsgtvo|yXcf|           -Y;)FM4      }vnsmrufZ\[        .V:"%CS6        prru\VQc        ,R?$CY4       kMLTp          +X9! !AV2     qtEN`        '[8$#;Z4       rb@To          (X;##<Y/        pRCXuy            +[:$#@L-       yKE[n        ,Z< %DJ,           ~ CMpyzb        1[:  &ER+         k>`u[             4Y8!"!'EW*       XG|{b           4\=!$I[%      U^i    1^A #JZ%    |}\n~      2]@ $GV'        wfy|                5[>"$EQ-       zl     :^8##FT.     |p            @^5"'JV)      wu        9U?#&DX-       pr~       5VB$!BZ0      |`oy         6W?(CZ1     y}sVsy        .\D" @`0          |z]T{~       .[@"& @a0            }|qSZt        1Y>$%B[,     xp{}yd[_|m       0^>  "BT-            xnqzwuc_em          3W>#%AS.            x|}mewtq_grp        -SD$#!BX.       xv}gSlkcuwuw             *ZA!$"CV3             stkaz|mlzu}e         1Y@$!!AW/           plw}sr{{e        .VC#D[*   {m}u{z|u           +\BCZ(  xyu~              ,[B=^-   {~y{y||~}zzz        -T><Z4        zt}{}wl_WTT\fwtlrod`bjv{        &L?$>T,   |pt~k\YZ[amx||}~}na[XUZiyx           $JA!?T" tq~tcXZbhjmrwyj^\UNQZfvr        $P?AN xoga\_cdbekrut~{nmfXTX]gxx      $S==J z|ga_\Z\cglwzuyyiijdbbcdfm       #U>8I& se_WTPQakgksv~gXY``bmd^w   %N>6M$  wlrkaea]iidu}ymTTal^OXy|{     "NB :U,  xyyxm_hwvty~a_swntrid\^XXtu      )SA#@X,  zxpefdZ[_^jw~rdwwil}vm^[YZow            3W=#"(?_+}}wlYVl{nYURLOXan~vw~jfec]Wh|      1_?(,@b+  ~xttZVnxwvl^SRUW`qsj^QW^TVpz      2a?,"G`(  rp{ytw|yzYSo{ibffkpoosuspy{xsjbZ\UGTtu    /YA!&I\.       rv}tmjszp_Wp}fT^p|}}txqlnrw|~zwxcL[l      (QD&C^1      ywncdjqb[v}xrpov~wtxkeuvvv]cxb        &SA&! !DY,       ~cimd`g~|~wonqsx}i`o~vpp]         &SA#!"&BR.      rjtkZd[YumW|          &N?" #)BT.    quv`^y^iwp\i             0P8 ! +FQ-        y}oa}gcvyrse^     4V7 +EL,   {kshcv{{u}xVx   2Q:!#*AN-   {rd^szj[-R? #(@R1       y_W~z^    ,T<"%AX/      xVck      +U<'"=Z-       het   +X=%$BY*     vnp      -Z= $FV)      nwx        *X>$ET+    pn       /Z9 @X/     y{      -[<!?[,   w          )V@%A])     t      *T< #'@^,     {y|          %TA$%@\(    {w}           )T?#"@W)        .W<" #?Y,    y      +WB#&AW'    ~x   -S@$*?Q)      |~t    ,RB%&<Q.    |s         .SA!">U-  {v        6[9$BW-   ~y      4_<""CU-  wy|~         3Z@ DW*   uv       3]D?Y'    vy|      /`D"8T/  ~|x}|y    4^@9U/   }~ztx~td}|s|       5b@;T,     z}~wlp{lWxol      2YE?P,      ~skbls\upjt       3UC#! <S,      pl`Xkz~gqugouz      -VA  #9S/     n}xqeTZmumpuhhpwx     .W? !#<Q-    zzytiWQY`tmklljsz      -Z@"#"<M,   ysynUOVQemqmskbm     +ZD "!8O.     {z{^GRJQuvvtpc_s     /TC!7O1    spnQUE9upzyeaz       3R=" ;N0     zngxsQ\V8a~upsih~      6S:"<R-   bbXTXC^yctuns      4R:!:S/   v\xmTVIZ|feywx    1X>$:M/     tronyzdm~YWRUo^os{    2X@!@N,   ohuy}rtj\TS~`Zw}p          .V@DT,     ||~pf[WtpQe~tw        ,Q>"=S2{{ynprf[l[\o{s{           3T8 !=T2   ~jfosiksYboy{o    0Z;" #=U5     ~mfktsq||`Sel{rn}    *T@#%>X8     ymYc{vivkynmeMZfg~sot      -N@"#AY7   y~eTdkdmplw|h_vhWZ^^gkfy    .Q?'@V9  |dZ_ULd||en|zwuwrabr^YZ^^Ubicz    -R@%@Y5    |ncaR>Lm|uagyzllx~r`rykb]]__XPai`u     0W@!%<V5    o{pbkgMHbqobejkolbgh_csmeYW[XMISfx^`{         2X=""8Y5 bfr[Wdam~zvrdUX_YY^`_b]ieb_SRXSMVH@VuyUV     /Q? ?d/ WXnwjWbjbg|{sodbcXX\_gpf_fkjbd]X[UJKSWRfrsNR  ,PA"@[0tHQz|kgWN]m|wbdeY[bhhehg\W`cioncVUSIFGCEM[zzbM[x        -ZD!@U.e;O|jPO^TVaYTTLFJQUUW^e`_bWJLTRU[U]p_J^   .[D>[,\7Nz~sTSgeVKEEMSQMIJUcrfY_YQ[]`mfo|_Mb 3YD #?R+  X.Myz|r]aXQPYgkowwvywuugcd`fnnz}pt\Sn    <\@$=N+  K1Qu{zwaFOdqz{k_n}pvt`^t}z   8^>$ :T. B:Vzz~}}zZZ{w}{gdse  1VC !;U3qBJaqr}zp}~lex|cb1RD#"?R3   lGS[mzisnhq] 8UB$!@R-   jHW`~gi~ptr4UC!8U1   mM`m|xtnz}{u} 1PB 9T3  xZixtp{xvmr}  1K?"!8Q9 go|xq}}y~{    0O=# 5]>  tpsry~-U?9f;  spt~x     *[E>^8  zmsrxy~  4[?B[1 }tr}~jts     4_?!!=[4    {pyqoun  1]@%&8R9kllvvy   1Z= &>P4 {dswt      3V=$@R6 kf{|{~  4U;%$9Q9 hk~v    0\;#'=N1  |xgpi    ._<(AN. xvg}ept   1Z?"&<S/ |uuuwh_}ro       -VD!##=V,  }~oxtQls`     &XG'?L2}uV]ch     0TA#%@N-     {y`VsZx    3T?&! AS$        z~cVye_     2V>%## ;S,      }nWu{at         .T?"">W-    y}akoc       -T<! &EO&      }sy||d}ih     /P=(&DO'      nrz}y}nr|by     *Q>"!GX$     kvyvsmjrlkxzzjp]     /W; EY)        odr{a~_]^acn~xtsen       ,V= #BU,           f_ekfXdhBIaqvr~z|d     &WB!EY(          tid^W_}IDdv|ywthpf     -XA#DX,        zogZTh]AWq|zp|pgvu{     1Y@&FV,     qf\Sgj@T~zppw{uuxy}        1X@%IY,      lYNZ{v^dukoxypsut{m     )\B"$F^5         eQYfktpxtmjsv}rrmn~tf    #VD$Ac8  dar{~ss{ynicgw{k     )V> #?_:      otywzk\W`lwk{         +Z>  B[4     lSU^ftqh}      ,Y?!A^+        }`UZYdwqn}  *_?! AZ*           ~|dTQOQbrsfy       /^> !<\1          |n`SHKVaur`j       -XB  !9\5      }qcZIDNQ]yf[             *SB!D`,        ~vxgYOHMROYrvZg        +RC# EY/       {qmxkXQJHQSQWle_~       'RF!!AW5           ~qomlh\QMMLKSSRdo_i        (XA@]1              wpuo^NIPRHGOQSaqrZ\{          '_C!@Y2          zpkdRHJLMJHLSWUarPPvox         *]I BZ.             }wo^MNOJJJEEPSLa{\Npko       1_E $#@W,       to\MLOKDFIHKMOf~zsiRXjk      2bC $'AR.        ~xrncQJRREBJJLOJNVV[SIqhj        0TC%"%*?O1      ywrmjcVLNRIDHNUSNHNLFkg\t           3T?&$&'@O/        }{ztigeWOOO]q]MS]XSwi\sox         2T@'&#$CR)       ufycaopigjgXSYV]ibz}eX|       2V>'%&ER+                  y}k]jqeOMPW^rjk}{fSc     1XA%$AR+           zhjpdfiwvneo          .VD!%8X0    ywwrt            /^C#:]1            nw           0^D#<_+             }p|           .YD !>Y0          yr            /Y@!DV/         nw               5Z; B\-       un         4]<=]2             z              0^C$?T5                      3^G*CM2                     ;\A$'DN*                        7U@& !AT(                    3RA%!#>W%                       .ZC"!$>Q%                                ,YF&@P&                          .VD# #>Q(                          ._A !<Q-                               *[C =W-                       .Y? "! <V0                      5Y; $!!;U6                  }             3W> "" =W7               y                2`=$  BW0              zz            /\?"!!EX%                      h|            'XB" 'DO+              `wu               $XA (FK(         \qtyz                )R?$  ?V*                  wyYndm~}vqx                )V> !@U-          zfajZe|k_gy             )V>!"@T(           ZrkYc`Sc               *T<"%:[,                 \vZNc}             -T=#";Q4               inl                 +WB <O0            vy                   -[?@S)           r                  .^;$<P/                             .];&8S1                             ,VB"!#;M5                                  /QD%;T9          {                   -RD&@X2             vq                     &VD$ ;U4             yup           'PE' 7W4                mojz                     +NE&!9W2           quhgu                   1Y;$?V,              v|uxWwk                  -X=  !CS&                   oz\k               /\=#BQ/         rw~eZmz              1_<$CS2                   viwSid               .]CCY-         pt}~|Idypjjly                    %_F =Z/                sgkQxpxkdenx                          "]I! :[3                hkZbh|mfsyu                    /]A !:Y5                    nwKg~uww{j               3Y?%"6X6             zkGwv}ukj                   .T?!   =W3                    ~R^ovorjx                    *S?$"AU1                              s}Bpxkkp                        1S8($%CP+                  xq|_x=V{iby                   1P;("'BR*                         ~bsQikTGjtZk                  +RB%!$=T,                  ma|SN}wei                     .Q>#  #>R-                     }}s]cb:\ryjh~                          1T;""DW)                    rryn]ScE7dqxfaj~                                  -X<#!?V,                          njfRMdqD:i|vn}                          +N='! >Y-                          ^`YH\~kC?f                       ,O;#%!AR&                            ~T[``d}fJCXj~                       -Q6!(CQ#                   z{`{|iVFI^k|                ,T=  $@P(                    ZpzpbYXq                       +TC!">R,                  t]yl{                        .X? @T2                          ~                              0[:AW3                                            0S;$CW.                          b                        3O=&!DU.                                |l                7T9!"FW-                                                   3V;!$GT1                         ry                          3R=$#DV0                       mu                      6T:"#>X2                          tmt                          6Y<""<V3                             pop~s                         6Z=(!:Y1                           ruakdV                          6Y;%$ =X/                        lmrzbKs                                 4V;$"AT+                           prjbXj                                 5X=" #?X*                                {t~`Eq!                                 0VD$!BW(                                     sj_Upy}jd                             +XF" #>P-                        t\Kn{kr                        .YB!##;P3                       L^~cz                             0Y@ "#!>T3                    jL{j|rv                                 1_=%!AS0                         wnc]w                         3\<!# !>T/                        zqk~                                   3Z;"#@Y.                             eqob`h                                        .X=#!%AP.                                     zpdR[                          0T?&'9O5                                                         ,RD$""8R7                                                    -WA <T4                                                       8X8!!AU/                                                         8X8 !?V.                                                                          4Z< !!!=Y0                                                                         3W="!"<T4                                                                     4W>!$;R7                                                            /YA=Z.                                                           *]AA_*                                                                                *\?"=Y0                                                               *XA  <W3                                                                    +Y?!@X1                                                            .Y> AW/                                                       +TC& >V.                                                                /S?%=W-                                                                3N;'"  @W+                                                                    1P;#$!BW(                                                                      -S=#"=X0                                                                   ,Q?  ;X3                                                                     +S= ?W0                                                                                 .U9AU.                                                                                               /Z:<X4                                                                                                     .\= =U3                                                                          .Z@<T2                                                                                                      'XC  ;S1                                                                                                                       %VD!?V)                                                                                  "TD !B\$                                                                                                   &QB"!!CT)                                                                                                           *QA%!@Q)                                                                                                          'QA& #@P$                                                                                           *TB!!!?R'                                                                                 (XC =Y0                                                                                                           '[C<Z5                                                                                                )[C <Y5                                                                                                 -WB#>S1                                                                                                             .W>!?S.                                                                                                              0U= ?V-                                                                                                 (TC!BX+                                                                                  )VA"!B^*                                                                                                .S@!@^1                                                                                                .U? E`.                                                                                         4R:""Cb/                                                                                          5T9#Bb2                                                                                                         0X:!=_6                                                                                             *Z?;]8                                                                                         /\B?W3                                                                                 :`<>X1                                                                                                          7`=B]0                                                                                              3Y@ Ba1                                                                                          1T@"@`/                                                                                                   3U?A].                                                                                             5\?C_0                                                                                                 2[C D\/                                                                                                          0YB"#?^3                                                                                       /TC$"$"=Y3                                                                                          .TC&"#$?U0                                                                                                     +]C "!#>W2                                                                                                      -[A AY.                                                                                               3V:#"?W/                                                                                                      6U8!"!";W4                                                                                                   7S:! :\4                                                                                                    4S< :Y8                                                                                                  3S> ">V1                                                                                          4V: (>P0                                                                                                      3Z='=Q3                                                                                                  0VCSigima-1.1.1/sigima/data/tests/image_formats/uint8.tiff000066400000000000000000011304001514013333200227770ustar00rootroot00000000000000II*(1 {"shape": [480, 640]}tifffile.py                                                                                                                                                                                                                                                                                                                                                                      "                     #!!                   ""##                 #$#               !$$""               !"#%"                 ##%""!!              !"! $%# ##%&$             ""%"   "! #'))(&"           !#$%#  !&)*-,+'"             "%%$  ! !)*+.0-($  """""   "#              $#%# "$#  ").0/,($ #&()'%#! $'%!            """! #''$ #(,0.+(%  !"'*+,+(&# $&(&#"         $#"  '*+)# #%+-/.)%!"'+,,.,*&% !%'*("!        ! !" "+/21*" !&),,+)%#! !"'*-...+&# %((*&"          !$"" !$.2870'!&),,+'%#!!"$!"!$(*.//-+)# "(+('%"        $&%$  (49=@:0%!$*-++*'&""$%$#"%(+.--.,)$  $(*)&#        #&&&% !)5@GGB8-"$*,,-.+(&'&&'&#"%((+*++.+'$ #&)*'%!        ! &(''&!!.8DKMHB5(!%(-/--*)*))(&$!"&&+*+*,+**%"  &,-)$        !!!"%'*)'#!!,:HNQND9*!%'.0//-*+**)&$#")**-+*,*((%! %*-,*$         !"$&$! %(*++&&  *8EMNMF7+! !#(,-//-)+,*)()%! &)-0-,**&$&"  #)//.*#        "$%%$$ #(+-.*%# &3=CJHB9+  !! $*-,--*)**+**&##(+01-+*&%"" (+12.(!       $%'&%$"(+,.-(%"!" # "*7<@?<6,!!"#!!#" ! !"!"(+*)*)*(+-,*'#"(+-.,)%#7 "*242/'!          #&)(%# "'+++-*&#! "#%##"  $*15872-$!$" ##$'%&"!$#"  $&&$&&%'-+,)'$!!&(,,)($! '.453.'         !#  "&'''%"!"%)**)&% #&)***(('%%#""  $(-010-% ##!"#"#$%(+)*&"$" !"##$"#$&)*.+(%!"&'(%$"%.4694+%        !   "%'&&#! "$%&(%"!"&*,/0231//-**''%$"  $'*..+&##&%!$%$&'&'+-*,*&#!""! !$&)+-)% "#!!%.49:61)"        !'&'&"  """!! #%+26::;><9610/,*+)&$#  "#(*+'#$((#!%(&'(),.0.-)$!!#  "$(+()$'/6=?95.&        "$&$"!! !&-4:=BDHHD??;9512.*&$$ "%%$""! &,,(  %''(**-1212-(" ! "$((&&$ '19ACD<6-"     !!! &%$#   "(/7@DKPQPRNIDA=954/*'%" "#$ !"$&%)02,#!$#%&')-45740," !" "'''$#$0:BIJHA5,           ! "%%#! " !$(/8@LRY\\_XQNJ@<:41-*%!!"!#%',)#!+472(#$#"$'+3<<:7-& $$!!&'&" #-9BLQQNB3$      "%#  #%%"""#*0B>9/(!&%% "$$#"! $'*5DKS[ZQC5'    "$'&&#$'$#"" "+18CNZgjljkg`WOE>71*'#$# "#%(/341* ".:=9.#!(2:BHB;2( $'&'! ##!!""%('*,3;JV^c_VF5$    $'()(" !%$" !#"##'/6@N\hlorpic]SIA62*'(&%!"!!$$',/654-#",7?:0$ )4>GJH>2&"$')%  %)(,.0129AM[ee`VD2!       &*+)(# #$""$$"!#$%*3:KZdntvumh_UJ>6.+)(+(('%" "$%'(,0465,%,7;91%'5BJLI@2( %')%!!',/2464:AGS_hjdTA2"         "')-..(# !$$ $"! #%&()-7DUalruvqn]VO@70-++++**'##$#%&(*+.554/%)264-"!"(6ALLI@3'$&%$ $'-25=;;@BLX`fiaT@-    !"" !"%*.//-)" !$"#%! #(,,,*.5@MYdmqrqkbXM@61-,-+-/++'&$'((((,.1441%%.42*!"&&#'3CMOK@5&"##"!$*/38:<@BCNV_df\L9'      !$#&# "#%(.110.'"   !$# "!#)1332.+07DP^fmnkhaVJ@72/--,-0+)(''()&%'&*154.' !*.-+$ ")-,'"$2CNRNG:+!! !"!$$'.4679=>BHR\`^TD5$        $(((*'&%'*-1130(" "%!!" !'.5==95205=COYadfeYOI;72/.-,-+((((''))%$%)0582+$%+,*&&&+151-%'4BLRQG=2($!! ! !#%*/3646;.""   %+.-,.*))).3310+&!#""%$ !""!!$+4:AFB=7437;CLRXYUPHA92.,+,*''(%%''*'&%$$'.8:73*$(*,*+.48961)! '3?MPOLB60)! #%&'%# #&+-.0149?EKIH?5%!%&%#$      &+-121-++*-.120,%! "&&$!!$$# !#"#"%*4?GIJD:71049=CFLEB@82.**''&%&%$''&(($#"$(.8=>;0&&*,-039<=<5*$"(1>JQRPD<5,'! !'*-.+)% !%&'*,.49=B>;3+ !%)++)&#      %*03530+((),/41-)" !)*,($#$&%#$!!!##)2?INNI@<2/.-0558961-+(%%! $"%)'')($!"$*2GMPMF>7/)#"(,1640/+'  ""#%'+-18852+##)-/1.+(!         $*03761,'%&)+/20+$#*.10-*((%$ !"""#!%03)"!&*08=AAC>:1)%'/;DLMJHB81+#$.7:=?:30+)%$##!!!#)+-/.,("!&,15650&!        '.4662+$# $),0/-(#$,46441*)&%  "&%#!!"*7EQVTMF@5.)& !#(----+(%"#&+3;92(           %/5771)"! &)-//,%!!###-6=:83/,(%"!#)'&! &2BKRVSLE;1+# $+/471/-&!"$(1:5/-)&'-5<@DED>81)%0>ENPMIA<76652/(" !$$" !"#$%$&# !%&'+/8?AA;3(      !#+5750)"!(*00+($!!$''%"#07?A>:6.*&!#(,-)"".=IQXWTLD80(#'/46:61-&" $(.7>DHKG=2)" $)/6532+)&%()16:=A?<6.(!)6BKSVRID?;=:<82)" #('$! "$#"   $'+-27>BEC>2&!!      !$#! +2460(!$(//*)'$&(*,*%!"/7>?>>72/+# &*/0+$" #,9FS[[WRK@60&! !$#" "*29=A=6,($!"&,2;DFJLD;0& "&,-/.,)$ "%+048=<<5-(""-:GOTUSLC@>>?A:2*""$((%" "#"#" "(+04:BIHKF<1&!!    !! "!"  $&'$! +2:82+ !(++())(),.//*%$-6>91' &'&#   !##"'/47AEHNMLF:.$         #$%&%&&$# "'*+)%-4:83+ &())((()-11/,)$ $,26=@=9730*("$%*1441-'#)00%!!$##! !$&*.0430.)&%&(+07>FKMJEA;99993+$$'%# !$#! %,3=DJOUTOJC8,#         !'++-.,*(&# !%)--,)+6;=6*  $*$%('&(-0/-,)%"!$)/25687752-+''*,/562,)&+2=JS]dec\SJ@=<3)#! ""!  $%'(*/.+,**))*,-17=ABA?:65542/( $($!$$#"$+3;FQY\][TI>4(       !##"! #(,.2000.+'%" "&+.121.$)4;=6, %%P> (%&,+,.+(%$"%%'*,20123501-+*,/1460,*+06@LX_egcaYJC>?FKPSMD8-# "(.7<<=6.%#*291% "%)17972.$!'08>CIHMLHE;3,% !  #%&&)'&##$$'(--,,%###(*+0//-+*%""$#"  "###!  $'(-9DNZhjkg]M@3'!     "$'*+*+(&%!%+147677640.,'%"!!$%'(+.28>C>4-%&.9:6.#$+0'')%#"%((&%&%'&')()%&%%&),./0/01/230/,*.48BP[cgghaSHB@BHU\_XOA1)#!&*0230'"&.:@DGJKJHD>92+'"!" "#)++**'##!"'-..+$!"%***-)%""'%"!!  !$%$! $'(&'*/3=HXemomgYH9+"     #').-//,,)&$ $)-/37;:77642,+&$!!!#%'*-269>BFF?4(!.476-&'..1/)#!!"$$#$&&&)'*+&%#  %(.02332340.-,-3:CLU_eie_TE@<@GT``\SC6*"#%+//,(!&09@FJLKIGD?;50)&#""#',///-+%! %(.1/*""%))*)'$"#''###! ! "%##&(-..-/08BN^ipqqiVC2$     !$)-.10/.+*%!!&)0259<:<<:731-'$$! "%(),048GIMLLHECA;93.-*%&"!(048872.("#(/240*% !%)+,++'! $%&%"!$$#! !"!$'-./21221;FS^ioql[K;-      "&*.01200,("  #(,249>@>>=<741,'#"!$&(+.26:@JNRSKA5&%,00,%$+3553/)"! !#$&*.-//-'% &+127611-)*)*05CEB<5+' !).6:871,($%)+.02/)#!&((%#"$# ! !!&*,04332/249EO\ejjbRB4&!          %)011321-+%"$',158>@A@?<740+($"!$'+-19=BMUVROF8*!',,+%!'069:71*%  !&'*-.01.+(#!%,047631,('$&)/7>HTYXYUIA5/2HRXXSNGDB>?>?;850**'$ !*4?JPPLH?5*# )19CDEB:2.+,12494-' !%**'$!#%! !!! !&''+.0123//..16>HT_b]RF8)          !(-/1241/*($! #%*/4;?;0+$ $),-02300+($"#).15541.)%$#"')09CIQVTOG;.+.9M^klcU@0%"$-132139CM\a_[SIB>;=A@@>:63/*%#!  &.:IU^_\TJ=2(!!")2;IPQOH@:5599;<:2+$ "$)*+(" !""!!#"!""  "'++-231221/*,)+37@JSRMD;.$       #&+11220++'#!"$-17;=@BA=:521+$#$#%*-36=DMQTVPE:.!$&#!!$-4;B@=6,%!!%*./231230-,(&(./16643-+)$  !#(19AINOJA6-*/9Lbjqm\E5)"'.4889>DMYefbXLA88:70+0=McpzpdQ=0+-28=BFIOU`d_ZM?4016?CFFC=4/)#!+7GXgs}wjYL@3,)'*05BQ[dee[PHEDGEFA7."$)-/-*&# !!!!!!%&&'(*%#"!!$+.38:7861-+'$" %*14684.)!         $&),00/,(&"#&+149467231-+++(%()+/58>CHKLKC8,#!! !'1;BGJD=4*"$).-//0.03348:9;<=;:62.(&%"!"&,49?>;<6-,3@R`pyshYF:45:@AGLNRZ[]XN<.''-5?GJID92,% #,7HZm||p_OB6/+*+06DTbkmjbZPIGHHG?6+"#).1.+($" #%)**()($#!#(/38=<:951+&# !%)---*$!         "')+,.,)&!"'*02123110.-+*)'((),/39?AFHDC:2&!" %1;DKLHB6+&$*,,-++*+/27<>?A?@<<84.*(%$" "$(/157755207CTaszvl`PC=>CGIMPTVYZVL@2% '3?FHF@4.&!$+7I\iw{{naO>41*,24;FVertpg\RKIHCE<2( "'-//-($  "%*+,*'$$#!  !%*17;?=;84,'"!$%%#!         !$(()'$$!!$*,...+-0-.--+*(&'*--2:>ABEA:5* """%12.,.48>JYfptrk]SLEA?=7.%!'-1-+' #'**)'% !#!! !"$(-49@A?:72(#           ! ##!#((*++,,+-.-,+(%&'*)-35?:774354100.((''(()+.,-/359AHQZbiic`YYY[[\ZUPKKKJH?0')4;BB<2,%"$%*2=HYgnnaQA7-++,27@IVgqxsl\OF<985.( $(/2.(&!!#()&%"!!!""$%+/9=ABA<6.$      %'''*'()+++*(%##"%%),/6=?A>:2*&%$%(("$.8CNSPNE91&! &)(%# %)/8:98842534866452/,,+.,+,++*-16KWdqurjZK>4/,)&#"),/,*'"#&&%  #$%+29?FC?92,"       #%'))'''(''&$! !#%)/8=>A>84,)+++(& "+4@JRWPG>6*" %))'"  $,3453//./0696:66332248630,+)*05;>EFGKLONPS\epnmh\RHD>>><<52-*.25662.& !&,/.-+*07@LSTOD7+$$%).5=GT_nrneWG6*$$""!!!"$*/00.*&!"$%"! "&,4;?EB=6/&          #(**)'&$$##"  $+4=ABA=93,..-+*&""*4?IQVQIA:0&  $&)+)$$-223.+*(-/5<<<;86358=@B?82,*+/389==?><>@DLZdqvvqcTIB;=?=>?;3117442-(# !%,3451-)).6@HJF>2+$#"&*07FS^imj]M<-! !#(*,255740*&# "!! $+3:@A@:2*"       "&**,+(%"  !'29>DFB><40001,*$"#(2>ENUSMH>1*# ##+/-*& %)131-''&)/3;==;965672+&'-4=??:0(#" $)-4@M\bgdWG6&"'049=@A?>90+&###&('%'#! #(/6<=;5,&          #'+.0-('# ""%-6?GOLGA<72233/*(((.9ALTSPLA2-(#'+/24/)"#-251.'%$(/49=<:713;BLSWXPC;1*)(,/20/*)&)0;FWhoule[I=8<<>FIEDA=9951-)&!%-5>DC=5.)&&+2651.)##""&)4=HS_e_R@/"")3>DHKMGD>9/)%$&),-/,*&!  %+2563,%         "(.252/*$! #%&.8BLQUNF?:72453/))).6>HORPJC8-+))/4793-" *1142)%!#-39>953029BN[a_YOC7-(%(+,,+&'#$+2>L\hljcXK@<:8?CEGGEC@>>960*$!)1;EKID<4-%#&)--,+'$%##&)0;GRZ_XJ9)+9GNSWVTKF>7/%%$&00363.'# '+.,*%!     #)28555/'" ""%)+4>FPY]VOE:625761-,*/4;EJONKC:0,-/4;?@;1$&0461+$!#)089841-07EPYcc`XMA2-)%()))&$$$)/6DPY`_^UKC>989>CFGIIJIHE?6.'"%,7AHPQID9.&!!$%%(%$#"$&*.8EQWWOC2% '5CU[`d[UKA91)%!#(.5895/& "%$"!     !(186750,'!"%',0;AJU\a[QH=4245663/,-3:AHNMKC:4/.4:@GF@6+$-761*$!"'.3430-,+1>IUagf]UK>1*&%'()'%('*05CHLRTTTPH=4.)''0;DNUVOJ>5-#!!#$"""$&,1:CJRNI@."#.>N\ggb]PD80*#!#)-5884.%       '179:72.)$  &+03>FP[`d[SJ>612369732/19AFKJHB:6027/!!*220*"%,0333-**-4?MXbd`[RF92.+()(')+,/247=CGLNOIE<30/38@KS[\]aYQF;3--19AJRVVWQE<4)! !#%%&'*-3=DINHB9+$!&6FQ`ie]UF;.%"#(-3862,$ !! !###      !"!! "'-38;:6-*&" %+28?IV_ed`TI>6/.489:62319?DGGIA:5018>EOTOF5'&./0' #*3545.,-.0:FNVY^[SLF>741/+*+-366865:@EHIJG:5/-/6?IUbfcd_WJ@:46:?EMSVUUTLC9.'$""#$'(((+,/6>=73.((.5@GOOK@0#"')($! &.6;=A?971.-19;GKQV[WVWOF@510458>:640.29>@?61/+/7CLWbcea[QGA>=@AFGMOPNQOMLF@73121122245687><=81.(%#(09DKMLE:*"',-.-,,++)#%)/200-($ "! $%(+,+++-*(("          %'+/253430*$!#'+//2/21,($!$+4=GPWWXUMB4*$',3::;:76447756.*($#&09CNNI@5'!$'(%#"&-3;DFHHD@820/039CLT[^cd_TH?827:=@;6.**-5;=:42106FD@;/" +49:60,*'&#$"!"$*05652,'! $&&&%!!"$%(***++($$!!!!!   "&*-0379:63.'#  "%&)-./.1-*($$+1;AISWTSI<3+&%*07::;775210.+(% *3=GIJB6+"!&)%''&,19CJOPQOIA92-*.39CNXdiof_RH>9<@BA>6/((*/8:78548<<:;:<<>>=<:71,($"$))/5;>=:2')5CGE>6/(#$!"##(,077771+% $(./.+&! $&()('##! !" "# "'%#      "%*-/379:833*#!"##$&$$"##&*./.10.-' !*17?GLRQNF>2)%%(/5::<:721.,)&! $-8=DGA5-&!!#&*()+-06>FLQTSTOHB81+),19HXelqmeVLC@BGIB<5+#&*/466568=BKRTURME?<62336998:768:>AFGHD@@>=;998<94/("! $'+059;95.$$3ALPMF:.%! !#&,.159753,&'-4654-$!&%%%" "#&##"! ''&#          "%)-03786731+'! "&&),-/+*'#$$&-22121+% "(17=DHLLLH>3+&$(.49<<;952.-'$" "$.6<@A=60'#$(*,0--265*$&,7FWfpqkbVNIGFNLA;/%!"'025556=BJTVTTJD=81-,,.2262221347=ABBBB@;:42245;?@=<70)#!#)+.49<;6/%(:KSZRI9,!!&+1488963/) $+5>?;3+# #%#" &&%#" #')'#     $&),,1232340+&" #'+/046530-'##%-/1531+'!#,18?CINKIF?50*(+/4:>>=<:4.-((&$$%%),08=BA<50*''+/00/2:;>CIOMPSSSOH?7+$$(3CRcomd[VJFILPNF8+!#(,23444:CORSPMD?71,*)*+-../,**,/47>A?@<862,++.16<==;5,&  "%),.5:>??5+ !,=LX]RF4)#+-37;>853*$ "+48>=:2'#$$ ""$$ !#&'%"      #%(+++--.10.,(!#%+239;<><7.*%&(,/5953.)""+27>CJIHHA?<61.+169?A@@=;851/./0//236<=C@:61,*+-03458;>@@DFEFIJLKEA9-'#(0?P]b^ZOHAFLPQKB5,"#(1355/016AFLOIE>71.,*(+**))+%&%%(.28?B@<:3-'%%(-26:<73+&#"#%()-25;@AC8/& !(:HQTJ>1%&,378;962-(#&06:<:6.# %(($"""!$')&$!     !'((,)**)+//.+& $'.7;AACEC=4+%&'+099;71)#&.29?EGIHFB??::7358=>DGGHD?<9===>>=<<>@?A?:94./014689:9>??@;;;=>BEG?70'$(2=KUVSI@;780//2:>AA?;9630-*(((&%%#""!#$*166/(#!#'-1675.+)&%)*+,,.4:CGF>5)!"'5@GH?5)!(.47:761,)##&/58983* '.0,&!!  %((&"     "%*+)((&&(+,++%#(18@<99<@BILMPLIFGHKKMJHFCAA@@A@=:6578:<9;::=<9852016:>B@:3+(+4>EMNF93.05?GGB;539HQYUK@4.,/23575333450/*&#!$$!!!!&+3:?DDB;4-&"!"&-120--*)+-0/,-.09CIJD:*"!#18?<7+!#).68763-(#  "#&+123.)#!'/30/) ! " "$'&#      $'**,+'&&'*+)(##(/8?GMLKHA7-(&)07@EB?7.%!*5?BDC@?==CHMOUSTRQSVWWXWRLEDD?EDBBB@?A@?A<;=98860-*''-3:?@<61.07?CHA70&#*28=<977@Nbrzr`OA5..-+-*+-03851.)%##!!" !#+07CGHIB;5-&" $*-/00//03510,*(+6@HJF?BDADA@AFNSUVYYUZa_cc^XMGB@>EFEKOIHIEEF@=<8761/($ "%,7=@C>:96:@CC=2' !'.56323=Ql~dPC93/*(#"(/39:4/&##"!##$#"+/8BJMOIC:0($!!$)..1557;;73.)$(0;EJF;1(#(-455." *1330/*%"  !#$##)043-&  !#')(%!! $&%" !!!     !%*.1/.,)&&&('&#*07=AED@:0'"!'-7CDHB:/%!!(0;IRWUNG?7479>BABBABDLSWY[ZY^cdec]WMB=;=DKOQWURTNHD@>832/,*&"#*5@FMKFEBADC@;0'#&.473/+3EciXMD=4+##).5796-'$$&')&$%#"!$)/6@HNSOI@5,% "',/68:;@@<5-(%&.6AE?91,,/9<<>2$!)-0./+%#! &,.,)  #$%%$$())++&""#"!$&$"!!!! !!!!       $).221/+')('%# $,27;@A>7/& $)4=>?=5,'!"&-7COY]\PE<2-,28??@=>@EHNRSYYZ]^egaZME@96=ENU]a`]YRJG>:321-,)&!#*9FPWXUSNGGGA:1**-5;:4+)5OvѶrc\OA4*),17960,((),-/-)&'%'')/6?FPRPJA7,#"'+28;@BBC=5.'"$*48;;81049FILK<*$'+/+,)%#! !#%$"$()*+))*+,+)%" !"&# #$%" "##!! ""#$"  "#" !  "!!      "(,1220-)''&%! %,248;60," )17::5/+&%%*4=HW\abWH:1&&+/8:><9=CCFJOPRSX\`c\VH=6//:COW_ggb\RJA=;430-.,%!#-;KW`bc]YOLKC;3017@C?9/*8XĭucSC6104852,*.0589731,*+*),17>DINNKB9," &/69?BBA>;5-( #(.3784117EUZ^VG6'!&*..)&#"  !&),.0..,+,)&" !#&"!##!$%$!!"$%'$"#"!! "!$$ !"""!     "&,1343.,)&&#"")0030+'$+/22.'%%((08CR[cieYL:."!%.379948>>@DHJKINVXVQLA8-+.5@M[ckie]SH>93/-,-.+)%"$,;M^kmphbWQIE;44;CJPH?4/9W̷ziUD;7531.*)05AHHB<5/.-0//269AFKLG?6)!!)/4;>??@<74-%""'-2531/3=M^jmeT>-'-,/*#" !! "#')01/0-++'%""%$"!! !"#" "%'()'('&&$" #""#!! "!!     &(0230-,(&$"" &*.+)%! %('(&!"#',3=ITalnkcQ>.$!'/54667::9;=@CDEGMMG?51)$(1:HV_ig`ZQD:1+*++,00.)&"#,;L_ltvriYRJA;7:@JSYUH;3AB<7-($"#+4@MZaa`ZJ=3,'&((*020-'#&+:L_oxysiYOI>88:COYa]P@7?MjyeRE=70("#,:KY\]UE<6778764059=AB=6/&$/1787531,'#!!%*.21-+*.9Meruo^F2"%.122,& !"" !"# #(*.+)(&#  !&)-0/0/./.,)'$ ""$%" !    $*,,,))%%$%$ &''*+'&%#$!!"'/9AKXfpwsiXF4&#!$)014538746411146765/(#%-8CNYX[OF;-($ &)-2321+%%*8H]kqsncVNC>98;BP[bcZM=;CVotcSF;7-$!!+<6-$#)-200/-)&#  $).54-+%)5HZfjgXD0##)2763+$ "&*--+%" &)*&%# #*/0461/21,+*%%" ! #$&'%#!      #(&&$$$%&$#$!  "#(,,/-+)&#!&.7ALZeosqkZG8(" "*+03456530/,)+**,-+'""&.9AMRRMG;," #)/3574.'&+3CVaimg[QG@:989BN^hg^SC8:EUdr}kXHC:5+#->O[]WMB:988971+)+/1;<86-' #)-/0.)(# "+276.'#"*8JS]ZN?-"!%.3995+#$*28995/&"$$" !',2566400,)+*'&$" #%('%     ## "!#&%&&# #),.331/*$  &-4=GQ_gmleWD5)#"(--/035762,'$#"#%%$" '.8DNNNG;/' $)-7995/($'.>OYabXPI?:7789BO^jkdUE734AN_jts]MB:70*% "+;KSROF>788761*%!&*17=;60(!")-4443-% ",3786,$ "-:BKI@2*""&/6<95-#%.29?A?=6*$  &,135640,)&''%&%!""""'((%!      "#%)(('# !'-25542,&!$+0:CLZ]bd\MB1($#%&+)-/46:94-&#!!!#*197778878751)$"'19=@82,& "*2:?A=8-%$-4<=<5*#!$+3761*$#$)17784-$#'-5:?BCC=4*# #%#!(.4436/*($! !#"!#!!$$%'%# !"!      #(,,+*($ &+35462,& "'-3:EKSXVLB7,&""##&'',05;960)"!   !%-:CJMOJ=3/++0399<6.'"#)2=EMLE<6565789BKYegdXF6,(/@O^pp]F2,+**)$#',5=@B?933541+$#,4<8751*$"(,-&!$).1/.(" !# "  #%'$!    &+05674/*'# &,/21-' !$,0367:92)$ !#! $*2;=>:2,'%(+,/,+*&'%&&#%-6BJVZ[XQHC@=<9951,&!$+4;?<62..06789;CMV\YQC6..3?L[kr{q`L9+!!#(+37:=:97774.''4=FKKJF@:4-'$#,9GU`fc]RD;6347>GOOMH@7,'!#%%()&&'()(($"%-5;=;950)$%+..& !$&,-)'"!    !  !"%(%#    '-3:<=;82,%!!(+./,,% #&(*.0/-'# "!! (29?A?;51/4699631-+'()(*/6BKX]bfbXRKC=964.)%"#'-39<72.,-/38767>HQUTPE;414?HR[dmqoj[J7+""&*47<@:<><<4)!&2@INQROJF?:4*%',8IVchebUGA:7::<>@BC@:50/,**),/9@IWdlqoiaUF=42,*'%&&,/4:;82.,,/453227@INKKE=758:2("/@LSZWWRLKE=7-)(*3CQ]dd]TGA<<==@ENQRTQJ@3(! "# !$&(+/+(##*27850)"!$()(# !'-,'#  #%$!  !   "###$%)*&#"   $)1;BFGC<4+'$""%&')*-023/,&! "!!!""#"! ! !%+09>?AEBBBDFILGAA:3/-*+*-26;60,)*.01/.03:DHgZDC>:;;:879>DIJHC;3*$  $+08>DIFHB<4'!,9HRX]WUNLKHA92)#'/;JTYZUNF?====?BDKOPQMC9," #&&$!!#&*++*%! %(.10*& !#'+02/+% #! !(,+&! "$&#   ""#&&&'(&"!    ")0FA@A@@ABFIMKJDB<4.,*)-269>ES_nwwsgV@2'&').47;=?A@?71,((+...+-06?Cq_EHAA>=6/+,.5:=?>;5/*&!!##).6>AGLLF>4("$0@KRYYSOLKJID>3)$!(3?KPNNGA;:::99:=AHMLJG=/#"',..*%$""$'+,'" !')''$!%')''*.59863*$#'%$# $(('" "   "$$#"   #$$(*')%#   "(.9AGIF?8-)#',.36699;<<96.*%"#$&%&"!###%%%!&2?HQSKE?:;=BEEFDD?=93.,*).359=CLZfprk^M9' !$-7@DFHHHE@90)&%&*))((*18?@DKLHED?9/+)(,1259854.+(%##'/58?ILLG?4'!!(3@IPSOKHFDIKHA6+&!%.:DIIGA:666445348;EMJG=0$%+2562*)&%&')*'" """  ',./0.-.09@@>81(!"'*,,(# $(&%!!"#"" "#$"#$%%$! !%%****#"    "&/9ACEB;4*&$&,26;>>CB@@<83.*%&'('(# $&*,*&(9LXa_TG:1139=?>>:67840-++058:;AHS_gicTA/! *9GQTVSPLG?7/)$'%''###&/7=EIIKKJHD=3/)(**--/4462/,)%$%)07=FJJD=0(!#)2;BHCB?;?=;7.&"#%*39=ACEDDDA941+))+,*($   "&,251*"*@Xirn\I5'',16552001540/,-07<@?BFNW]]VH6%%5FU_dc^SLD=4.'%&$"!  $+17>CHJKNNLD=81+)&')+-34431,&%$&,4A<72,***)'#"*39=>81-*,3:AJHD9,&"*,))% "!  $$#%"!"#$!!" $)-.*''%),*'# "$&))'#"    #%')(%!"&+39;960'!$+3;ADDFFED?:71+)*+*+&$%%$&"! !&0:<<2%+F_s}sbF.! &-310*(+/342/./38?BDBEJOQPJ;,!.BTeiokaSKE=5.'%$$! ").259@EJNRPJF=93,&%%(+16861-($#$)08<82.-..+*$ $,482%$6L`osuk^QF>82-)&$"  &)+.266/)#!#,5>AB<3) !$'$%((&!$&+,+,*)&% %,03/+(%%**++)# #$%&&#!       $*/23/0*#"%+1420*" )28?DEB>:972/,(&&$%'''+,22.( '6FPPK;)#.A^s|u_D.#$+5=82,(.7>A@:4/2;AIKKHFHE>7- (40.**)%"!!%&'*--4:BFGE@=50)# #(/5:;71,$!#(-246530+)&%&'# !#,69AC@;/# ")8EJML@5/)((+/138AFKKE>2+$"#).2232469996.'#')+-049971-+(%$"###$(-2674+#")8IV_TC3*.=VgkhU>/(-7BIC:405AHIJ>7138CJMMNIFC?3(+>OcolaUH=4.**+)))$#&&&%##'+29>?>930*$ !%,5:>@91)#!$',02330-,('%$  %-3EKMMJD7.'##$')+,/6:>CA;1'!&)+/147;=<82*$#*,.,(%!!')*&! &,.-( %06;==:50,'" !(.//+&" "%(%$  !! !   !'-1521,(&! !(,,-*&#*29?@<;74/*(%$$#! "'.7=:60'#)9L\g_N;.,7IY_\M;01:FNSMD:9AKRVRF;42:CKNNKGGC>5*" +9IX]]UH:/*&#&+,*)%# #(+,,)%%&(.48962+'#" #'/:CDD=2,$  #&+-010/-,)%#  $).7?A<2&%1=EHC83+')*.48BFNQNLE;/,(&#$$&'+4;DHGC8)"$)-./1478:;4/(#"$('%"!%).00,(#!&-00.'"-:CIIG@:5/)" #%)((#! !       $*-.1.*(#  !"')++($")/;==;940.)&#!#! #(08@A<6+'+6I\hbT@2.3>JQND948FRY\TKA@EOX_WJ@748?FKNIEFB@91)"!)4@JRND7+$ !$'+*)%#"%(.241-(%%(.243-)$!!$+3:DIHA91)#!!%)-/02/.,'" #',39BDB9-!)4>BA60)'&(-3=EKQSNIC;5/*(&%$$%,4;GJLD8-#!'*--/0024431-(%$"#%$$#  )-28:94.(%&*,151+$"+8DOVTNG@80*% !!!"$%$!!!#      &)+,+'%!!""&()'*(%")/589:850*)&#!#!!!!'.5@DD<2..8H[b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bc^RG<3*&# "" #"%$%$$"!    "#""!!$%#""$$&'''$" "%(-01300//-+)&$%&%%"#!%.7CJPLA::9BNUYWJC=96564327?JSWUICBBGOUVOGA78:89869;?DLNKE<1.)'(&&""#! #)2C@;4/+**+.11.-281' #+--.)# #*2>IJLKE>4-)(*--,)&%(-5>A?;2(""%+)('$"$$#&*,036954.(#  %/8CMQOIC91.--.0,$ '6EVade\M@5-(#  !#!!"$%')('%#     !#$" " "$(*()&! !$(,.220-,)))((('&'*&$$$'.8EKPOHA>=BMTVVPMF@:74/-/4CCCB@AFMMHC:2-.458:6.*+/3:>@?>;9:642/+(%$"%('&"".;ELPSV[\^XSG9.%""()***&"#$*2;EKGD?9-%#"(+//+'%%'/6;83.%#'((''"!!"!#&+/37:73-(# "#)3:CNNNH@81.*,-)% !-:KY`^YQ?5-(%" !"#" !$&')-,+)&"     !  !!!  #$')*,'# %)-034.)(%%&''*)(()*(&%)/:EMTSNGAABHOSVWUOG@95.-/4;@FEB<6489>BC?9776540-/3:GU`dd]TD5-%##!!!  !!!"$)0:?CCCDDHRXUQF;0-/4=?>8/*%&)3689:=>=?>@;3-($"#$%%"#/;IPTRQQ\]YTJ@5*'$%**)'$"#'.3=BEC>:-&  %)/1.+%"#%),.*&!"&&&&&$$""!$%'.46650-)$#"%%)17?FHHF<61*))'%!%1>MWYTK>4-(%"#""! !#%*+./.+("     "$(*)*'%"$(/321-(" "$%'')**(*)&(-29DLQVPIBACEKPSWXTLF<3-,/26=>>=84363777745542//.08BP_kpldUH9-%$$$&&'#"!!!$%$%&)142)" #*.2577DIHE@6.)('()'((+-/24530+&" '.574/(  #%&)((*)'&""%(,.//,(&$&))*--/36<9631.+*)'#" "'.9CEE>7.)&'+29:84.*%!!&-/00-*&       !"$'*&&!(0874.$$%&%&'''&(+07AEIJE@>=6.**+-26656321.0,,/,00.+)*.4>Maq{xjXE4'#'*089760,+)+++227>DHJFFCDIT_jkdQ?,"!+8CDB:-# %&(,3;AJNLGA9524:>>8/"'4@EFD<222:ABEE=4.*('*))-.02010+'%! $,48;61)" #$%)*)--+'&# $%(**(&'((*+*+,./233210/,+*'%"#'+18=>81+&&)-6@HJFA93,&  !" (-/0/,(#      %&))'"$/785-$!###!##$#%).6;>A@>;5557:?EHIG?62+()*,.///104541-,,..,,*()19I\ozvdSA0##)/9?CDA<4/.-+/55:BIKLJFCCFT_kldV?*%0>DB:1&"#%+19@FHFA<<=:72-)&(+,+,),/399:7430--,+'%*4DTe{t_N;*##(4AIPQID:30.+/24??@@FPX_]UJ:* '09>94-%)3=IONF>4.+++--.-0-+)*%#"#').36;>?=94,#"&(*,)+,/+(&!!# "#$$&(*,+,()+..0224410*%$%).154.*&#(/:GTZ\]WNE92)#!%&$##(++)&&"         %-/-)$(-1/*% "%'-0/1/002111121330,+*'(((')'*1:CFEC<730/,+)+1:M`sxlXE4)$%/>LU\]VJ?71+)*,399AQ`ecZG4" +5<=:3)#! !!$)-038;>DLV`hidXE1$!)5<<3*&(2>IRQKD:1-,.////-,,+)(&'(-48FSWZTJ=72;JV_b[I7(! &.5;7/*&!""$$$''*./38?DQZdonjcO<)&1983-))1>NTVSG>5/,/0//-*+,,+**,05:>DHECC>84+&%'()%! */021-+**)&#"!!$$%##%%%%&%%(,15<<:80+& "&))'%"$&/9FQXYVQJD91,$"%&)'%#!#"$"       #+00/*#!&(%$ "$)+.278>A?;60(%$$'''+*)*'&$(2?KY^_ZN@7/)').6@O]mtwusi^SF<1)(,:IZglh]M@5-&#"'040.0351+)+)+.0.36;@EGGGE?=841//1340," )26881++)&%$ "#$$#"#"!" #&*07;>=93*$!#%&# !#(/BDHECA<:76759??D>4)!",4<>=6.)%""!  "#"$#!%+2::4," "$#$#" !$)08====84/+'" $$&(&&%!         $%&&#!  &(*.1233*""$##!$',-4;>HTZVK>3)"!#'-000-*&#$(5BQ^ee_RA0(%&+5AMY\]^ZSNFA941+')2>O_ec]QB7*$##&*3?LYahdYJ;559AIKH@3& #)+/1/--))-26=FQW[[ZVQIFIHKS_egcXF6,%'-343*#$+9JVYTJB@B?=;8678<>DMPNH;-##/7?E>82(#" !$%&&" $)/6:@=:0-(%&('(%#$$&)-0230,*'%! !#$&$#!   !$%)*('%$! "%(**..144.("""!%#! #%)..19BKV]XPB4'"!").142-+'##%/-##$-6GNUXUPIE>861,,(%+1?Q[^`VJ;/(&&)*.6?IUage]TF=99>CEA9/$"',.4442.,,29CPanqvqjdVOE@AEQ\aa]QD4-,0672(" &5COTN?4,*+3=8865658@GOTZWN@1$!.8AGC:3)"#%%((# &+2697611/--//*((%%')*-+%#! !! !      !$'+,,,++)'$! "%&'#!"&'*+./0021,'$"   "!#%" $&*+,/6=EPRRK?/(#"&/4641.(%""!*1>HMNIA9+! %-8AJNNHB<63..*&&#%,5@Q]^VMB4-)(*,/39?IU_cda[QD?@@@?94,$ #(.389940-+/9GUlzrcWE;79CP]`\VK=634651( #/5+%#'*2:852*&$"!"#'/58<>60("!#*49@GA=:30/)))&"!&-9BPXXSK>1+*),/027:EPZbc`XSJFA@@<71*'$#$(-3;===80,),7CXmy|lZK>/09CQZ\ZPD@<:864)"!)09;8.%!*8DINMA4.%$#&+16973.*((.57@IOUVOG<-#"-8?D?81% !"&(*,)($ !"&(*/048<@?=94.,*)*&!        "&-033633.*'!$-44)"!#$#"#%(*)*''$#" #'*+)'%(+.330*'#%+48??:/*'#"$%#%*+.00/-%#"$&-59==941.,-*'$#$,5@OVXWQG<2.*,/33238?GQZ[XRMFECAB=91,+,+-038?@B?74,%&/;Obu{p_N>3,/:DOXWRJB@:983,'!$'..+%!",=LPWRJ=5*" $(1254/+)$$)-34)"-8=>:3-#!#',...+'"#&.79BHE@;50-*)'%  ! "!    "&*-335564/-'!&1:HQTNF9*  !$%)''#"! $')*'$! $%')%$&+5>DIC=5+%$'+.//,,-++*'$"!"#(068;<9540,*%$%)28222/58:?ACE@90*"%,7FXhrz}xlcPA6.*2LV\VPJ:.%!"$*1330)$! "',5:>A<;5,$ "&.5:960*!%*0121-)% #" #"#+7?FIGD>7/-)&%# !#$$%$%%%# "     #').1643310*$")5?N[b_TF7("'&$"!!!"%&).,(&!"'&(.5=FMMI=4*'&-4=@B<;61/-*%! #)/6EIJIC>::6:;?>?CAA?:7/*% ##+6=DFIQTY]XRE8*&#&2;BDA>41.*,,)&#! "#'.4=DJTUZXMA4(! %,//.) %'*,)(&&%$&&*.00/+)%%,38=;6.# #$(+,..,'$"!'.7?CB;5-&$!"!! #$%#!"&'-1235342.*'  !!   !#&')(+,)($ '3AO`jmnbP@2&!!!  "$&'## #%),014;:?<50-+*,/068;BLSWZRF9,%+5GZfmkf^OA9.'# ")2;IQX^YQH;.%$)3CUbkngaVIB<7401-)'%%),.1-)%"%.=GSWVRPGBC???=;:54/)%!""%*.3779;BJOSOB9-%!+17:960+(%())(&# !#',08:?@CHLQOLD4(*020) !#!!#"$'(()*,**('%!%,5>@>6*""%*-37871*'"%+/6<962)#! ! !#%'%$" !',048<;<<:73/)" !""   """ !!!" " !"""%%#!"*7JZhmng[K;0*)(('&%#$%&('%""!#&+-+)$" !&*07<>FHHKFB>9467<=@>=BLTXWTF8+$)6I[owxvk[LA3*&&)2>HV`ehcZK8,$")7O_grnh^OE=951/-+%$'+-01/,$ #.=LY^]WPHA=:89522.+)%!!!!(++.0-..5>FMIB5("%+1240,'#""#%&&$$%)06<>?;:94)!#%+3O^jopdUI<21013/0.-//00,,.-./12/+)"!#)39AHNSVYYSNFD>=AD@B?==DMRTUE:.%$0ARhswtj\MA7.+.4;KYblqmdZJ:-$$-@S`msnaRE@843/.*(&'*-1562,% '4AQ_c`YME<541/.-*'$%"!!$&*+,*&&(.9@DC<2*# !$).//,'%" "$$(-08;>>>921269;?9/$'02,'&)+)&$"$##"%/:AA;2(""%*6?KLNF:.&! ")+,+)'%#"!! $*-.,+&" "(,26;@CDHIHD<50(" " !    "$('')*+))'###$$')))&$"" #1BP`hnh\SG<88::6756699==>??><:51*%!"!%-9CJQZ]bca\WQJCBCAAA9659AKQRG=1&"'2BTekhdVKA8327@IU`kmlj`XG;/(+2BUclmcWJ>841/-+(#%(+2;<:7/*')4>KZ_d\RG;3/,)*'&&$#!"" "')**&%#%)1;=;71+%#&(+-,,+(%#"""$)07=@@>94,''*0573,"&-1.'%*(&%! ".8;<92'!""$&+7AIQQK>3)!!%'(((&&($  $! '-030+&!"""""  &+36;?BFIKJIC?5/&  !!!       !$'))*+++.+&&&'(*+--,*(&'"$2DV^fe_WNFB==<:98:;?DGKOPPNJC81(!$*5@HSX_gfhe_XOIEEDBC>6/0-5>EJG@6)" &0?NUVXNIC=:=DKSZcgfc`XQG?737=GXag`XL;60-++)&#$&*17>>?:6215ALV_b^UE=1+)'%&%%&&&&###"%)+*)&$ #'-3685.+)*./1/-*)'*'(# #,4<@B@94*% "$-20/*!'-/.&!'(%$  #"*4;970($!""$&&%%,3AIQRH@6)$#"%'(()))*(#!  ##!$.2652-($!%&'&%"#&.39=?BEIKIIC;2+" !"     "%()++-0/,,*'),,-134/---)($)6ET_``[RKE@?;<:88>AKQY`a`]VJ;0$&/@@><60++/4>DCC:.# !#*:?EKEFDEDEMPV]][WTOMKHHCBDGPWZ[UL>2/+*+,&!"#&/9<9;=ERY]b\SF9/)$$&&((),.-.+)''(),-+'# %*-242/,/23671+*)+010+&%-6>@A=7-%!!&,/1/(!$)./-% !""#&#!"$"!  &/6731+(%%()))%$*2=JONE>6/+('*,*)+---+($"!"$$" )179652+$!$(**(&"$(-289:>?@EC@=4.'      !$%')+,10.,++*+-14575332/,("!+:JS\\YSNGC>98556=EKXbhjhd[I<.# *5@JSWZZY[ZRNJC;79:=?>73-,.28?EC=7.'" "+39;AIT`gg`RE7-&#$#'+,02567741-+-.21.*%! #'+1100/17:?;3+().4:<81'! #,5=B?7/(#! #(,-.,$'*--(#'()$ #$%&&(&$!"*04421+++-,)(&$(1;DHHF?95353330,,++-+(%!"#"!"'('$#,29<851*#  $&*++)%#)+-01588:=983.)$      "#&(+,-00,,+,,-253863551/*&! "0>HRVUPMD=:30.-28BJT_clf`UH;/&""(2:BMPPTSPMFE@841158=BC>850,269@BCC=6.((.8?HNVWSNNKIJGD;966?GMX\\\[XUND?5,&$'))&"#$+3>EHH@95:CP[gkgZI:-#""$'+/36:>B??<53125962/*#"%%(//00249@?;4+%'0;EHE=1%!$-5>B<5-$ $*,/-'#"(,,+)""++-)! "&'++,)%'-03431./+*(&#$&,48=?==<:=?@>:60-))-,(&!! #""! $)+,%#)27;840*% "%)+*&" #%&'(,..23320,(#        "%),./.,.,*+..04442222.*(" "$#"  *1>HKJJF>82/('(,4;::40+-3INSQ?727DQaik`R?0# %*-125>AFHFC<64369==;6/&"#%*-0-,159AA;4+%(0APTTK=/&&-7??:4)!!%+.-*##%**('!%,02/&  %*../*&")/3433..*''#"#$',2586:?BHHIHA;2.)))(&'# #&),*$#(.3421,'# #%))#   "#$)*'('$       $',-/.*)(''++,,./-,..))%!#&&&& "*1=B@>=81-+'%%(/8AFMQNHGEA?857:<>AEEDD>;82*$" #)09CIKLGB=72006;CNRQRPRS\cjmlfTI>5/,,,,*-2:IR\^`\ULE?6.)#"#$''%%)1:NV[ZSB804BS_ddVF6&!&-55678=CFIFC<6247;=B?81("!&*+,+,.39>@<4*$'3CU_`WF5+).6>>:1$$)*'#"'*('%!!'-452,%%)+--+$#-33230*($$! "#(,.46:>CKONMF>4-)&&#" !"'*,(!!$*,,,)%# !&%"         %(*+-,)%%$$%''%'&''&&&$"! "$)*(# &*04222-*&##!"',369??>;:>AFFGDEACBA?@@;82,%#,5;BJLLHC>71-+.6ALV[\afjv|~ufR@3)&&(+-/16@GOWZYTME>83-(&#!$%%$$,7E[fnhYE6.0=OX^[L9)!!'08=:9778>CB@=70,027>BB;3'##%),,+,+,49<:1+#%0BUdm`SD4-17>>90&!##"!%()(($"!&*154/(!#',)'!#)0111+'#" $(-176/'#! %('' #$$#!#"     %'*-,*'$""  !"   $&'($!"#'))%#$! "'*.002.,.28AKQTROG@:8768896/*!!%/6>AEEBA=92,)&)1>HT_cjq||eM:)"#&-48:=BCCJNPNGC<840-*)&#$$#$'.:Ocqsp_I6/0;HTUNA0#!&/6346<983*'&(.5Pekg]J<119:=:1)"(*))(%!! '-200*# #&&"!'-/-*'""(,35EFDA?@ACBB>96422/.,**(&$$*0=QfuwsbL;/.6AKMF9,#"-;ITVOC93101/.(#! $-/4;<5.$#)/32,(&',12.'!'8M^jmaSA758;=>7,!$)/.--+("!"(-.-,$$'))&!%)-249;;<:772--&  "!!$#$$#')+'$!     %'),..-*%"!  #%(*'"#%''&$!!%.:GOZ]UMB4+%&*1;?C@=3,**.47563/+)()'$!!"'/7@GR`lyvaG7/+4>EMPNFC>9666433111353100*&&&)0:0&"*/221/+(& "&*-*#!"$%# !$)+-../0/05431,%  #'&'**-..,)%         "'*-..-+'% "&&'%$" !#'*(&! $#%&$%&*1=INSTOF7+" $09DIFE=7321242/+'""!!" !#).24:BJZgw|p\F:88AKSXVPG@81.-/,///25445752.**(*01/5<@A:.%#(9IZfaZJ;2+'%"! ")./460*"%.:AA;1'##%'($ ,>QagfZK?87;?>:2*"!&,48:60.*(!"$)*("  $%$%$$#&'-49:81.'  !%'(+.111.)'#!      #&*,100/))%!! ! " ""$),,,+'%%#&)**'! #'&(,.17?BGIHF:.%%/9CKLHB<6220/.)($"""##!!#$(././4?CISXXUKA91,*),++-.2346;<:961.-.07ER`daVG90-28?>6/((-=L[g`XL>4.(&!!"%*04753-)  (4?FE?4*" "&'# )7I]ggZM@778<<:3-(!! "(09>?<83.)#! $'*+*%"  !!$+39<=:4.$ $""  #$&&),.0/,)'$$"        $&*,.21/,+)%$#%%&&'('$%'*-0673/,(&&(()%" &),/2658=AA=<5/)!#+6AHKGB=840-,,*)),,.+'$#&(*/0-)*08FT\d_XMEBDHOUUQH?80,(()++-.///46;;=<9732127@ELVSK>2+*/5;=60,+1;KY[ZRKA91*)""$&-388882-& !+8AHIE7." "#$#"#'6IZeeZOA866::93/(&$%#"!)4>CCA<4/*'&&),051-&#$!!""# !##" !&18=DA:3*%" #(((&! #$&'*,,+)&%'%$#"       "#&,.0101/,,*++*,.-,,((*.38>?<83+'$'*)'%  "#%%&# %-048=<:=;642-(# #*2;?CB>;61.-*+.048::91*'')-220+'(,6@IPOMEAACJNNJC;2/-+++-../,,,./18;?==:962359?EHG@60*).3:<93./4;FMPPKC?:21-(%(*06:<994.' *4BHIF9.!!')(%'-8HXdc_QF:545740,('&''$)2@FHE@6.+*+16>@=<2(# $((&&$""!$&&&#!%',,'%  &+5;CA?8.'%$&)**%#!!$'&&'&'&''&%%     "$%(--13202212142332/,,,07@BDD=4.($#&(%% ! #(*,-)%# '.49<<;:81-,)&&##$!"(+/5557751.,,(*/5?HMJD8-(&(07;93*%#)16::979:>ACA:3-*))-/1222+)+)*-078=>?;;:61245<><72,)'*27887536:86550,*'+/47;862*' &0:CEA5+!"'+,--2:JWcc]TF;4/00++*''))'!'3CIKJD91--19DLMMH:-$!'-0-+*'(&%"!(++)""(.552/,& #$"#""!$)08<@?60)&&))+**% !! ##""#%%&)(%"      !"$&)+.031456678:<982.,+/7AFIH?72'#!"%'&%$  !$*-/0/-'" %)06;>?<61-*'%$'&''&+*),+*,++**)*)*-2?HTYVR@/&%*5=FC>3'#$&)-./,-/2751.+'().24999532.*,.16;@@C@?;750/06873/)%')-27:<976677544532640.*)*-244110(%""+38:7/' $*/3312=IU^a\QH<1--+)'''(+*'"%1?JLJC82.08@O\b^TE7+$#&,132/.-++'"$*./-$!%-4:<=;60+##('(&&#!&,37;94.)'%&++,*% "#  "&%(+*(&"        "%"&+.1346;>@?BA?;5-))+5?HKKE<1'! "'()(&$##$&,/0/.,&""%*/6;?>=85.)'()*.,**)))')&$" "$%%'*.5BO]c`VB/&$*8GONH<.& #$%%$&*,.-*'&'*.49;?A==<964659=?DECCB<630.11132.(#$%(.268774210*),*-0.20,))''(*++***$ $+10/)!%,14545=HR\_ZNC91.*((&&$&('&#$/942-,/11//-+(((&#!$'(-8DP^ebUD1$!+:ITUOA4(""""#""&(')))+/17;?CCFGHHGJIHJJHGJIJHD>:4/.-.033.,% #%*037752/,+($$$')),.+&&#!""#%&'&# !%(*)$!&,123339BMVWPLA6/)'%&$$"$%&%!$1@A;1( %,020.-)$#&+./20+'$%'.4;FHJJFA>9678720.)'')'% $%)/7AQ\bcUD1$#-=LWWRG9,%&&))('&$$'+-.59==AAGHNVW_bdcbc`[ZVRMNIC>70..-0330+$! "&,13331-))'$$$"!%&()%#!!$(%$"$))'#"',11.,039DKMKF<0*'$##! #$$%$##-6=E@:-&"#,=N`otrj]MC=89:7<;AA@=70&!(--*&$-8>FHC@=6.($" "')+)(% #','%" $)+.+(%""$''&($!!''*($!$&*,,)'$!!!%&'*)%#       !"'-08>EJMSTQLE:/$! #(28870(" %,27540*%%%'+02/-(&&%+2=FQWZWQKGGEB>93.**)+..(#!$(.8BQ``\R@/&#,=MUUQD80+,04761-)(*.2:?CECDAEJUakw|qkd^VUUPF?62.-/01.*& !$),21-,,++,,))$"##$%#! $*+'"!&*-.,(! "'+--*''(08>CA92*$" !!##"!!"!")39;74-"(4FYfstrdWKF>;=:>@DFHD:2)" (+)&"#*2;=><:30+$ ! ##$'))((# #%'$ &(./,)%" $&((&$!"',//+(%##$(,/0/-'" "&'''%         "%(/3:ADOQUWRMA7+" &.02/'#!"!'.6;;:5.+&&(+/011-('')1>IWcgle\WQJFA;60*+.2874-' "&,6BNWYXN>0)'.=JTSJ>8229?GHE@60,*08BIJIE?=BGXj|zoiba\]TM@5...02/+&!"&+//./)*,.47662*$!"! !!&)('""&,25551)#!##)+*'" !&+1541+#"$%# "&-554-%.>P_lruk[RKE?=@AGINPIB9.%! "')'$$+/111/+)#! #%$&+)&%#"$&%#%,./.)%!#$$'%" "(068630+&''+-010-&!$((%&"      !%%)-3;@DJPWVPI?3&#),+(&$#&+/6:<;851+*)*0231/*()*1=O^jtxtkcWRJC=70-,4:>CC=2)!#'.6>GNRNH>1)*1:FHHB952:BLVYWL>5.,/:DOOFC:5:EZwtnhigg_YK?5//.02-&##$*/02/+)),2;CFG@5+%#" ! !%'('%" $)1:@?=8/*$$!$&$#!&*)(!!#%''# %(/0/*"(8HXekkf\RKD??BDLNTTRI=4+#"$()&# #$')('&$#" !"$&'%'&$"#!#%&'*'"$+/1/)$!!"#" #*/8>=>81.,&'),.,)$ $))(&          !!"&(*29=ELPSPLF<2'!&))**()*026==>==:422013522--*)0>N_s~vg[SKD=71/06AKQRO?5* "(.5;CGHE?8.,-0:AA>9105=IW`d^QC4++0:FOTOB6-2D^zĻulklqonfVH90//./.,'))04582+').7ERUWQE8-(" ""####$('%#$,6AGID>6,'#"%%%%  %**'&#!"$')'&#&5ER]be`ZPJD?ACIPT[XWMB4+&%')(&"#&&*+('%#""$%'&''%#!$#%(,/-+&#+/0/+% !'1:ADGE?61,)((()$!!(+.+&        ! ""%)/39@GGKNLD>5,)((+,/.,,-049;B?BDDB@>85744351-*+09I\p~wg[MA?:72.19ES^`YM>/% !'-1:=>B=:5,*+-5<<95215>MZedaVF8*'/9JTVQA5,/>Yw~qfeluzyrbN?3,,.--...27>=;4-)*1>N^ejeVF6+%!#%&&$#"%#!#+6@GKIE:-%!#%&''#'---+$ !%'&'&$$,9FO\``ZUKHC@ADLRY\_ZLB5/+**++'"!',04540+)%%%&%#$"#$$&(*0650+"").1/,'"%,6@HMOI@8/)*%#$!$+/1,)$       !%(-128@FHJKHA=95666241/25:=?A@FIJJHHB@:4012/.+,-4CUiv~|p_QB:7530./7ETbj`WH7+'&(,/489;730()+-25776548CLY_a`VF8,(-:LY]UH9*,8Qp~ma\]hw~{ugV@1)'+.//24;>@B?81.,3AT`oulbP>0'#$&&(#!! '2?DHH?5-$!"$)++)$&-02/*" #''%&$"!"!)4=GQXYVRMGDCBADLPVUWUL@6//..10/(#  '28?EE@<5/*(&&$$""!"$&*16;=8/& (.1.,(  '1>JQRRKA8/'&!#*034/+&!####"     !%'),*.59@EJIJJHFEB@<:3446<:4)"!"%+/2.+'  $,243-%!#%'&$" "%-;DMSWTOKHEAAADHJNPPQNF=500144450)%! '1=HPUQMG<1-((&#"  &-5:?C>5*!&+2/+& ")5BLUUQI?5+$!&-47:83-& #&$#"       %')('#&*-6:AIOPRUTQKE?7316=?FHHHKPQRQOE=8/)&'('%&'.=KW\\UB5-))*,(''/9JYad\LD81//-./21/0/-(&%%(.6ACA=8538@CBDIIH@:9200559=860-&!##'08HT]]\UK>1*'& #!$.5.&%+22,'! %,9FQSUQF9/% """$!#')06:<>:1,& !""#$"!         !#" ! "$%*,*%! !#*08AHOTUXXSKA9306;AEHNNOQOTUPIA8-%!#''%'&)6?KROF:1)&'*,)'$*5@LZ[WMG=6533//.-/10/+'$#%*1<=CO\fniZG4(*7M`lyvofXLD:7;CP[ek`VH8,#"%+169<=>==:766;>FS_gie`QB4,###&$!$)((&'(()-//)%"!#&,267441.)&""&/5551'""$%$#! "+6=FNSOHC><;:630216:73+"!!"##"#"      !$$$#"!!#',01/("&-4;DJNUVPIB:2/39@IMNOMJGKONIA7,%!""'()*+2>FLLC;2,+.1/*(%'.9GPTPNJEC<:40,+,-3521*$!"(/:GT[[UPC<68>CACCDNZghf[G1$&0F^ovto`PD>57:BLQ]\UK?4($#'/579:;>=98689;2+&"#,5AQZ`d[OC5+%# $1=ITQH;+ !'00,&#&%$ !(.6BFIG>4)#!$(-4664679:<<=;60)#"!"%%$" !          #&"$!  !!#',3695.'!#)09AIJHD?5+(.8@GPSOJGB>EFGD7/'#"#),/227@HLPJG?:::860)%&*4>FJJLLHGG?51*()-38972(#!#+6FS[^WM?4.07AHFBCHMZ_]P?+ "2E`v}~qcTG<678?EIQOH@4+''',16;:;;<976279=BFEHKLJE>7,(%&')*(!!%/:>A@5*%!!#(('&#!"%).26<=<<74,#"(0365/*% "#" !)27<;:32//0340/+'##'(&)()+,17;?>:70(" !)2>KSYXPG;-'"$.;JTSL?/"%--,'#),+**&!"'-39<>:4-#!(/4;=98898797761,'!""$%$#             #%%#! ""#)06<<:4+##(.48;:6.(%(09HTVTLC:98;A@=7-)))-57=BHKUZ]ZVNPMIB=2("#&06;CEFKMMID<1($',0:?<7/'"!%2AMUVQG:.++3>EDC@A@IMOD5&$6Qll\H?:59<@BBA;4.())-36779:86434349;<>?@@?<:851.,-.1-,'"%/;DJOH<0$ $(++)%%$$'+/6;A<401/4:BINU[fnnlhd_XSJ@3'# #*169BHKRXQK?1'""(3:=<92+&#),4@KMGA6+'*1:AB?8658:;6,""+@\{v_LD:8;99:852-)*-259==:9767521/01579977455653412686.-+.5@LUUK>,#$*/.*&&#"%)*16=7.&!'*064.,$#()(%"%*,,(# $'(,.,(# &-6>C?;4-(! !  +5CPVRC3&!()*%%-355-' "$(+/.,'$ &,168740.))),,++)%      $%#!""# ##$&&%&%#'(.6;@@:1'" #$! (5FRY_TD9*&)/;><8667<@GR\ajuz|zwqjbXJ:0% "&+./8FMU]XP>1$$/77;82.)%2++3<>>:0*'+09AC=80++.,*'#&4Lhw_ND<;6340..))*-5=DHGE?:533310,,,-221210379<8><>?>=72129FRUTL>+"#',33/+'#!#$'-14:>;6.%!(,/0,)&$&%$!(++("!#'$ "(/56420*'&$#"!&1=HQLD9'$*(&!!&/152,$#(,-.,("%*001.,'$!!"$)(*'%        !#! ! !#$(*()'%$&,2;AA>6,&%#%()($#2AO^d\M<-#%)29=>>=<>EKTbirz{vm`SB2'!!%%%+2?MX^^UD4( (-34320,($'(-1263-*)+4>EFC91*)')(&&+>Trs]L@:74..+)+(+,3=FPUTNB91.-.0/,+))*,./.369?ABEGFEGC?958>KSTTJ;(",4983-'" !"%(+04872-$ #'*++(% #%''! !%)*'!!&)+---+))%'(%!",8CLPF9- ")*($"(.13/)#")-364-)""%)+**&# %))'%!          !%'*,,*'$""&07BD@92.**-37841)"#0?O`fdXC2'#%,4:@@?==GJQWcls}{wgXH9, #$" #.:IWc_UF4)  %'**-,,+()*(*,.0/*,.1;FIKF>5.*)'((*2AVs}jWE<7/.+**+..37=IV^`^UG:.'),-/.,('')-/06:@GHNKKJHIJE=:;AHSYUF8'%/:==6.%! #%&-1443.(!"%&''&#$),/++($"%&((%!!!#%%'&')(*()&%/<=?BBFKXahnopph[M<.!"&'$!'6GVa_UG:+#!!#%#%'%)+-,++,/..-.18=GLNJE;3/,,-,.7DWl}~n^N?73.,++,249?GMWaklbZJ8+'(+040.,*),135:@EJMMMKNKJJECB>FLQTMB5$ )4=C@7.%  !$(-1253+'"!#%&% &-7::73-('((&# !"%')*(%  -9CFI@3& &+)%!#$#$"!%',39CEFA90% $'**%!"%&(&#          !%).1.-' '4BJMMH?<9=CKSTPH=-$! "$$#)4BQahe]N?5,(,1387:??;=?CMRY__]UK>/$"(.2+%!3EU_]QH:,&!#""!!#"')./0//101027;@GLMLE=84101015AN[kslj]ND=52.++.2:AHLT\dkrpi]K;0*+18::6200248:?FFJKKJGHHIHFDDBGNRVKC3%!#+8CDA6-$ #*.4883/'!!"#"!+3=DFD@60+'%!  !#%$" !#''%$  '5@EG?3'"()('#! !%(*-.7>FMOOH:/%&+./,% "%''#"! "%*),,*&"      "'+/.*$%3EOXYSPI@AHOWYXRC6*!"'&(().9HWad`XL>5-+*-159;:95138=CJMLF=3%"+4;=3)!.?NYUKD6+&#%####! #&*.2444312569>BFJKHC;6200./018BKS[\WKD?973-,-2;EOX\cfhqrqm_NA649?DJHC=8789;>BEDIHDCD@?@ECCBBDMPOKA3'%'0=DA?8+"!&-4;=;5-% !!$-9FMNLH=4+"!$%%'%%#$')++*&"!#%$#%/:CF>6( %%('"!"%+.36:@IMSTLE9*!%-2650(!"#  !"(.58:;50+$!   !! !&(+,&"#3ER^c_ZSLIIMRUWOB6+" $*+,,(*2?4+!)6BKF=0$"+9DLJA:2*%%&'%&%&$$$(.2677754689??@BCCB?;9976-)+3>DA=4(!#,2;A@:1*# !$!#.:GMSRJ@5+ #',.+,,((*+.0.+'# !"# #,7>?>3)!'((##'+28:0% #,5=>92*""+0<@DGE>90*&"    "# !''%# !1DUafkh`SMJHLOKG=1'! #)/0.,+/5?LYdebXJ;0'$&/7>?:5*$!!(-4961(!".>LQQF5*""*3;B=72.&%&%(***,*(((,27887678:=@EFB?:2-+'(*,+)+---2878><9224>:400056;;9;;80.045*"+4>FD>6-$!*2MQSG8,"!'.562.,'&&%''*.15311/.13344249?BHLIE@:.(&!#&&(*')'%((+29>?A>8323=KT^defa__^YUQLMT]hoqpcVH?8678<<:;963.**).22451247=@?940136782(!!+29=97-$!$')*)))((&# (4?IQNH>2(#,2451-)((((,-)% "'+-0,*'" !&.452-% #')& "$).39>CFGFEB;1'!!(2>FJGB6+"!'1;HQYYXPH=3.)$($"    " !#"# -3)!&/7CQY\YWK@6/'&'&$%$"!     "##!  '5CR^cd^TJ?2-((&#  '-2741002=IWbjoeXF3**/A<70+/9CJNSOKCDFFEF@>@IQZdig_TG8,(&)//25210.*&%$)(-,)(%$*049641-*)'&##(*+)'$!'()*.23652,&"$)37<>;6,&""&*/23-($ ! $$%(*/9>??=4-%!"#$''$$&'%##&+-,//358::1,(#""&08BIJF@7-$"  "*4=GUYXVOB81(##$%%&%""    "%$# ! &08BOVWWLB8/($#"!%-3576567;JU`jql^P;1-3APVZVI;/'$(2:AA;/% #'.22.'$!!""# !$).1/+)-6AJLNI@81+'#%*6DUbkpmdZSI?72.)(%%(&###"(07:@9/*(-9ELLJB:557>A@><DIFA7>4&%## %+16::8<=>HQ_krleS?608BM\a\Q@2($)2;AED9+%#'&$""##''"#,254..2:DKOROGA81+$%/;K^owxvqd\WMF=60*%&(&('&*-39;;6+&(.:EMMA4+',4@CCD>:;>BEEB<4-#!',.,,*'(&$#!&(*./+)(+157971*#"#(*-46:96/) #',,,-++*&&&&%')'$ '*-.+&'*/5GJLI@5,#"%%$#"      !!! "!#$%""!" !$&-0354301+)**(& !$*07==?@>BGT_homfVC948BQ^fbWH9+&)2>IOMH8* !!"!$(*.+'#!+255325:DJPUOOF?90-,6DUkx~te^ZXQG=5+&$&)*,*/26:3)! $$$!       "!#$"!##%%$!!!! #&('()))/242/-("! #*/4=BAABDFNZeklgYI>8:HTbgiaPC0),5CR[XRC7)! $(,455,$%.45636KOK<-##-AP\^YRH>73/)&$""#%%'-100/,'('$""!"(049;:53368860+%# !! !    !#'*/233,$ """"""#####"!"*124,&%!&**.+&" !!%"!!"!",5<>:4(!"&.6?CB>5-$$,.02.)!"(-4551,$         "$$"  !"!"#"!!!  "!$-39=>;4-'$!"$).4;?@BBADJR\fkgZJA::EVepsgZG921=Q^lkeTA3*!! !%*08<;5-$").266:>BGMLORSQNHA>DRdvyg]TSUVSG<0+))048;<>?CE@8.,+1@IOI=1*+:O`lmg`QD:3,&" #%&*,,05652-*')%#$""%/6=?=9734342/)'%%((&%$!"#$#!  ##! !'+.0-)"! !"  '.241,%  "%$""$&#  $%#'19AF@8* $+28==<7,%)021/)$ &(*-*&!     #%$$$"!#"$#" '.7ACFC>5-&!"%(.5;CFDBBADKV`ebYI@==FUcpvneSE>=J]kw|seP?1($#%'-43+# !#)-/489<@BFMTUYXTNIMZkwq`QHHMORG?4///59@?=??EIG>71/3=FLJ<5.3F\o{~vjWI?7.)&$&'(,./368661.,*))'$$%-4<=<:31///--)'),./-*'$"&'''$ ')+($ #)+-+&  !)03660*% %(()&# !"!" %*(%"#*2>GHC;, !'+/4441,#&,12/*#!$%%"        #$%#!  !#$$"! '0:AJOME90*$!$(-3=EHDEC@?FOW\ZVK@:;BOcmttj`OJHRex}oZF6,($'(,5;CDB;4-'$$%)+0458:;>FPXaedXUU\it~wjVI@=BHLGB;5333029AEG=66@Qg}ym\LA:3-,**,,+1359;>93111.1.+)+.2:;<6/***),)**.05872-&#('*)%#"").21-'!&,,*# &+178860*$!  %*-,*&""#!%'('&#  !%+)&# %+3?JID:-"$((+,,*&!!'-020+"!"      #""!!#$""!&0:BNRPL>6.(%#'-4;EHHID?<@FNUUSK>98@J]gkoj_UPQ[kt]I91+'&&(/9@DDDA:2,)&&)*.11013;JYcmlda[]jpw{pfSB97=@DEC>;:;@BC@<68>FHFA7016;?=;6;EVo{hXI?942//.0,-/06;@B>;55786640.-0243+'%#%%%(),/5>@?:2'!%(**(%" #(09972)  '+.)#!(06;<<81,'   !&,/00,%!""%*,.-)% !!$'*-+$ "#%,3FLMJF<898CNVafdZSQTbtr`K<4,))&'*2:AFLOIB91(#$'(,*(),2@SclppecbfhnngbUD=77:ABBA=@@A?@;413:BHHA90--475538EYo~s_OA<9575250,..28?FGEA=;:???>82/..,)& "&((+/4:AED@4) "%*((&"#"'1:>@=4( $(-.'"$*"%&)0HQVXPKKO\lzn[H;52-+('(,4@HOWUMC9.&%$)+)&!#*8I\lomgb[[\bfd_TI?:9:;::=>:72-/7AFHA7.)*/13117ARdsuq`OA4322266640./4>GMOJG@?@BHHIA93.*%"!!#',/-/47@GHI@9- !$'(&$#%""+7=BA=4'$+-.("""  '),-**.2GTXZSH<2,')-.-(#$0CVgjlf\TPPUYYVRJB;9<<=<;84588850.2:?FEC5.)(-141.29IYef_RC4+*+1379786448@JRQJC=;96237CMQPF?4) "+4?EGDA6.&%(,02/+( &,.1-&"! " %)-20+%"&&#%+02//'! !  ! !"#%&%#"      "###" $.;DJMJEA8436;DLTVSH@6.,.4:9<<:30//0567667=JYbeg]RE=8889:51.-2;EQW[WJ>2--47784*$&.BS^ed]QJFFJLONNKE?=<<<<85//2286579AIMHC7+().6873/3?IRTOD9/+)+-5::=<<9:>DKPRKE;76;ELMPH=6*"#-9BHJIDCCHLMNH=2)!!$%''&%%%%'%$$-5;=93)"!'*,&!"$'&%! "#$'%""*9DMKF@88DMPOLF<5,++,058<:42/,()**),/5BOXYVPC8339=AB>72027@IQRMB:2/3=GJHA6..6@P[aYOF<77;?CEEFF?>=<@920-+.353,%%(++))&$$'),-)$"*/460,$"%'%#!''()'##&')*(%+:IW`]PC<79BKNJ?2$"(4@KTVUI<0("$(+,*& #*/..(#"(('%!  $),*%# $')*& !!%&)+-...,)&#         %+1540*#*5=FIKKIDBBBHIKJF>6.)'(+-279985/*%$$$&(-4>ISTMB6.(.6=BDA:3116=?EE?61.2;GSXWPG?:AFPWWQJ=4.*.27;8;=<>AC@<51,),3:BJPU[\\TC7,)1;EKJE?60156733666876;>?B?B@?@CEE>4,&',5?HNJE80%"'3CT_ii^VRMIMPMHA7.)*,-.-*(%$&,11.+# %,..)$"##"!$(***'%%&*-.-(!!0I[ilgVF735?FGC5( "" "'.90&$-7@GKMMKKHJKFGC<50-(%'*.15:<:60*$"!!%(/9EOXSJ>.($(2:AC@;200158884,)+1?MYbc]WNJMSWYSJD6,&$%*--0338>BHEB>6/./6?ENW]`fdXH:-+4APXWTH;5.-,/29.+09@D:-!!&-.+*+.3=FQX]XN?0#!&**("!%(*)&"%'&"$#"!  $)*,)!$''# %(+./2220/.*'#       #*08CKLKG:.'# !)/7BGIMOMNNJG>60+))'()+/249:952*$! "%,5?KY[ZN>/#"#.9=B@71-,.0221)(&*3@P\efc`YYY_`[RF<1(%""!#$&+/4?FLMKG<753:AHPV_bjh_K;109ESae_SE91+*+2:@IMKIB=77877500032/+%" "(19@A?:0+*1>O_lnjbVNIFGE@<71../3684/,'(,15:61)"!#'*)&# !#!"'*(*)&&'-1683-$#)8O`joaL5(&)7>;4'#.6>>:6317=FPYYUL=.! './,& "&&%#"&''"  %)+,(  %*.-*#$(,0335323.-+$!     $+6?GRTQOE;.'"!&-3;DFKNTRNHA90(!"#&(,-0267574-&#!!"'0:LUad`UE3%"#)29<81-((+,011,+,,6>KW\aa^^ccec]TG=2,)$$#!"!%/6BLSSSOG@=;<@DJQZaeibSD73;HT`jf]SD:0++.6BNTSLF=520-0.*))-.,++$$')-2<<;71,+0=OXbh`YMEA<=?:52,*-13;;84-)(+17;61+#"&)--'$#!""! !'-,+%##"(199:4+'*7J[`_UA-! (4<;4& 0>DMMH?868;@GOQRH;,!(00/+$""$!!&)&$" $&*+$$-253/( !"%+/14755310,)$        %,7AIRWTQH@3(#$%*1:?BINQQMHB6+% '*.0345532.($ "&.:Kcmrk]L:,#&,2764-(%&)/24652358=GNPTWZadgif]TKC<60.*%$"#&.7ALUXWWQLHDCB=?FJV_e`VH=9:HT^ee`XOB70+/5ANSUQJ>4/))'('&&(,*/0-+)'+/4653.*-0A>6-)++/7982+&$&(.241,(%  """!!(/,,&" &09BB;6,-3@NSQE4#!.:A;1( "-=NY\ZRG>858:?GIID7,!!*366/(!"&%%&%#!!!!!! ""$&'$! #+16;83,'"$'*035577230+*%     "+2;DKNOKD:1,'$#(-18=BGLLJHA6*"")0155420-(# +9J`nrqhQA2(%-2440+&%(*06:AA?>><;??CFMTX]_`_[VQMID>:3,(%&*1:DLTWYXXSTRKD<775+ !+5961+"#'()+)*'&&$#"%(&!  #$#""!(.49:870+# "&').4646420.+'#    !!!&,27/)%$$&).38<@DHHGA7.%"(/46653/+# &5F[jsphZE3.-/4670*)()/6=EKLNNG@9855;AIPVWUUWVVWVQLE;2.,+/6;CIMQSWW[\^UJ@5/1:FR[\RNFCFILQSUWYWPE:239AKPRQF=0'$&((*--0356542.*(*)*+*'&,17<><9.&&$''('#!!'16CIGA9.(##)/10.+'*,3;>>82*" $&&#"%-241-!&8HOPI>611430(#!%0@MPLA3,3@Sfjg`SG9.)&(-28883+#!,2750(!"')0../-,(')*,-*'# $## !&+058;:54,(" $%()+.1131//*'#     "$%%# !! %+258:953-'$&%%)+-/5:@CCB>92(!#).578760)!!.?TenphXD;3147:;3/.,47JPXTPNKFGGGGKTX[\TG;56:BJPQKA5-)))*-012568653-+'%%'&%#"'+1440)! #&&%!"$*4?IMKC:.# !$+.,,*'),5?@>81' $''()$" "(28<8.%#5HUVSG=5,,+)$ $-=<4-%" !).39<960(!")9KZegaTG=8;=@B>=766;>GNRWZXSKC7/,4<<6/--01565885552/*%%$&'&"!!#&(*&!"')''')/8?JMI@4* "(+*(&%(-5;B@80&!%'())&&&$&(.6=A=5- "5HY[YO?7,'$""#)4FWde\QE>?IVae`RD2*#!&+244/)"!"(-0+)&!!'-02551,++,05983*#"! $(+-14455..(! !#%'(()())')+('&"     !"%,122,)#! !"  "%+.0151/..**)'&%(),279=;:3.*(&'*3;>A?7/(# "#!!#)2DT\^YPI@>CGKIGE?=?CFLOTWXVPI?82/9DPXZRI?;=DS[b_\TF?787:<>=:4136@O]dje[OB;59=@@CEGKLJF=AD>4," '3CW\ZUG90(%!!%-;L_ikcWJDEIT[[TD:."#)0331+#!#'++()%#"  "#&(%%$"!$',2522.+'(,2;=>:2(!"!%&)+..131/-("#%&()(&'%$&$"!!!!      !$).2484,&"! "#%&'##! !$&,/4:<:9973.($"#'*,/368864.,,)05:CFHC;1(" "%&)(%&*1>JTURKEEHLNSTNKHEEJLOQUSOOKD=768AM\ef^O@86@GOTVRH@;79<>BA<64../6DO[dedXNF>:74366>FINJD@CJVdkok_K90.3?@<81/0//+.2120-)" "%*0476355:=BFDA8,"#'+(&%(/5=@>81*$""#',))+01365435;AED>4,(*0@RWYWI91+$##'/EEA9."! $%'((,-./.*$  %()(((&&"         !#)05695/)% #&(,+,)&%$%*07?GGFDB>73.($&')-0335330-./07=DKQMD;/'#!%+-0.*+.6>BLPOLIKRX]a\TQKGLQSQNMJHECB@:8?LXdklbRC847=BFKE=;89=BEFGC>;0*+-4@OX^a_RJD=6-)',4GHF>0%! !#"#"&))+,'$ !%+('($"!        !$(/48961+%"'+.01.+('(.8@HORTRLG?93.))*,/36542++,.371'!!&,0231/39@DFKLIOT\ilke^TMINPRSLHB@=;;;;JSVZWPJD8.$")4DLUVPMJMXdnneWB4+&)3=BC?<:74.,-19>BDCC>5+$#)/379:::754464663,%&+/10,+-5;@AC?:2+(%%%#&(-59?>;2-+.7DLNMA4,-2=FMOH>4,(%$%+9?NX[[UMGC?<=:2*% !$).320)" '+-.+(&!!"'+149??=81-'##%)'&&"&2:FKIA5)  "!$$%'$$ "$'&%#        !  "'*1775/)$!$)-133-)&%)1;FOUZ[WSQHA92/.3359;62.*'(,27CJQ[YSJ;1'#%)/479647:@DHHJJT^ktvpleTJFHLONHA;6477:>AJP]kkkbWG70-**+-/049>CKQV^a\TI?1)&*3==<=CINLF<0*(,4=FILMKB=1'%,17:99953010..//-'" !'-264//04;BDEC=3,'#" !#$.3:?>8.%!&2ALTPD5+&*3>GMF>4+'%$&*19AJRRQIB=8631+'# $)020.&#(*,-+%" #"!"%&).39>ABA>6-'" "%%$"#,7@HF?9,# $%#%$! ! !%&$" "$#!      !!! "!%).4531,$!""$)/00.)&"!*3>:92,)&'*17BKQTTOG8-'$(/5;?><<;1'#&-49=<<<5)!&-046411/-,*)(()*(&" !*13764426;ACC?:3+$"!%049<<3) />LVRG7) #*7AEC>5.'$%%(,17=EIE?<5/-+))(" !!!%)+10-+%"%(+('"!!!"$&'''((-04<@CED=5,% !#"!!)2;?A;7.%!!#&*+*)(&&$  "$'"" !         ! !  #)+/23.,*%#"$(,,)(#!&2=IT\_`[ZXUSLFB??>A?<92+('''.4;AIKNHA6.)+/6>FIDCB?@<=@AFLXit~{k]RF><@FD?;2,*.6<>GNRUSSQLE;3,)&((+07;?BDMW`nxxrhWG;3.-2128AHKNNK@:0*.6CMSXQIC@BFMOQMC8-$#)/58=::>AFIIA3' "*5ERUURKE<2)!!&-01-,)'%"$!!##$&&&# #'.26765349;>A=52*% %/47;6.#)4,($$$%&)067<<85/*%%%%&%#$$$%(*-,/.*(#!#&(&# " #%+----,-126<=AB?;4,$ ""#!!#*37:95,'#"#%)-12022.*% "%%$""     !#%$$# "$(--.1+*(%''()(&"&1:ISS\\WXXXXRLHDCB@><61,'%'(*/6;?EF@;62/3;CMWXUQKC>:879>HUap{{qbXH:7:CO]mz|xk]PG@?:82.15;EOTUOH>4059EMNNG>967?FJLH=3*#&*13688;@BD?8-!!*8GTWSRIB80(""&,.,*&! "$""$%#!$',268632.15::75-)$")/5861)*8EKJ?. $0=CE<4-'#"$%&'+-00/-+(%"!!#%&&&%())+,-+,("  "###" !$',1455222566:;<=;71+$  #'(&# #)+111,(('(,.37;<=962,%!!$$$&%%#     $'*)'&" !$'(,/.,+*,*)*(##!)2;DKSSVTTW[\YSLIF?=:73/*%#"$)(057;<;87259FP[ghg_WJB9513;DNZekkdZOB9569<>:61-,.49CIMMJHE<62..)(+.69>@@<76:EWeqxuj\URNLID90,-7ANZ_[PF81048BHIC:40.2;DIF@7/&&&-15666::;93) #-=MVYXND<4-)#" $(*+'#  %('&$$# "(,16551.,+/0451-'"#*/120)#*3>C@6*#1;CG>6.'" "#%&''('(%# #%&)**,,--+,+&$  #"""!%+-679;8:;87847897840+% !&*-,($#%&(++)((,029>@DDD>94+#!"%')**($!       $()*,(%#!$&*,.,-----+'$!!'+7CO^kqrqjbTG82/05EIKIHC>821,,+.269@AB@61-09JYglg^VRSWYZRE90-6ANZddXL?0+,09BBA:5,')29BE@;2)%&*.301/1342.&"$)7HU^]]QD72,)&#%%)**(%" $)..--'"! !"%)-2761/+'()+/31-(""(+-+)#(/695.%%4=FE>5,&!!""%&%##"""! %)+.0220,*''$!  ##%'/3:;>@>?=:762344332/)$!!!$+/33/+$ "&')'()-36=AFHGHE@90)! %*-//,)#      #'))'((# "%'++*,.1211,'%&&'+-17=@DDBDGJQW\[YQLE>841-*&#$##$&),5;?CCCDDJWanyzo`M@6004:;=AEFHGGC=9432102381)#(2>LVZVNKMU`fjaSD:97.&&*2;@@;6,''*-1.-,+/../+)/5DT_fdZQE9/+,*+*--,,)$!$(.38993,"!&,158=;3-(#"#'..0-(" $%(('# $,/.,(!(3;CE@7/$ "$%&'$#" #'*/343/-(&"! !!&((/6:?BFF@?=8521/01./.+$"#%(-39;83+&  !$'((*.37=BHHLLGA;1)"%).011)#     $%&%$%! "%%(,-023220/..10246688:9:;=@IPVYUPKC=:61/,)&%$$%%(/;FKOQSNMQVco|wiXLC<9:=A@>BFHLJFE>889;>BCFGCGIHJIGFA?<<::8776:>@EB<4(#&.;IJIHA?ERamnmcUNPR\gmni_M>2)"&/:BFD91*#%+0:=94/)()*..+*)()-1158BMZeljaTH91+-./1121,*'#"$)/9>AFA8-%(06;ADB@8/%!!&.00.&"#%(&!!#%%$"!!(07>C?9.' !##%$$" !',.263/*$" "%)+.5:>CGHEB<93..-,00/.,(((++28:2("  $&%'),37:?DGHGB<8/*$ &'-0.,($       "!!!!##%')./27647876665453333468:@GOPPKEB=9:533/*('##&*4BNWb``ZQOT`lx{rcVMJFFC@>>@FKSUWRKD>;@@DKNPNONNOJDD@A@?BBDA><<>ADC?82,/4O_ortqjeiqu{|ysaR@3+$'-7CEE@4+$$%*3874/)*)*,.+)*)*/36:>ITbhlofXI>5./247772.*&$#(/6>GLKE<.%%/:AGRSMH>2& "&-32.) !#%$! "(.57.%"!!$%%&(-25;>@>;853.(#%&*.*&#      """# ""$'(-2589;=?<9740/./--,/13;=FGHCBA==:;<<63.*(%'.8GVcnolbXTSUcpx|~vj`\XTUNFC=BIVahoh_SFBBCHOUW[[XSQKEB?@AAFLMKE??<>CFEB?>@CIJG@6/0:I[lwwyy|vdTB6+'+18@EG@8/(#&)+131-(()*,0.-**,.35BGGA=4/1179;<:;541/0489@DD@93,%"!!!"#!"&(+-1562320+)&#!#$%$!       " "#$$#"! !&+/27;?=>;761*))**--*..16=>?@?ACC@<72.()/8K[kvurjaWMMT`ksxwulhdb`ZRLDBJVhwr`SHGEGMRY]_][VLEB=<>BIMQMIB==<@DLNPUWXZZMA9./9HUesw|eRD82+-2:=BE@:4.)''*-/,-()+-.101-,,+057=EMU]_b]XNB702277855+($"%+19BHLKC7,#"/72.16:<;=;72-,+++,+++*-/13440.,*,/35:CIPRVURLB82014754-+$ #)/7?EIFD8.%#.?TdusYA, %-7<:4- %--.,$ " %*-/,(#&((&!  #&)+-,*% %,5?EEB>99>GMU\[XMD>94221488962-)%&##"!! !!$&')+,,-)&%#    !!"%&'''&"!!$(0356761,)%&(+/4446422356756868=AEJLMJEA:56;FUcqywk]RHAEJQ]imnputrjbXOIN\qgTJDCFMQ]bcc^VMD;::>DKONIC947:CLWbovzwndUC768>M^jt|jZNF>:521.034788424/*,*().-,2578630-)((+-.380)%&'-322-%!#%$$$""!"(*)'  "%&%""$%&(()**'$  (5?FIEBBDMV`hpjcZHB:1/.,+.01/.)&&%$&%"!"$',02540-+&!   "#%'()(##!$(.12640,($$'-359::=:568788644366:=BILNNKF?;>EO[irrj[QGAADLZajnqtrpd\RLHQc{nZOIDGJNW\_cb[QD>88:@FKJF@721554=GVdsueXPGA?<720-*+/26;==83-('(+.124675431.+('%$'+/5;=A@<82.+...1,( $(.27;=;6/*$ "*8MjnN4$#(3>DEA70*+089:70)!#(+./,+(&"##&%!!#'%#  $&)***()'&'# *5AFLMKLOZfpsvsd]M?6/)&##%$%&$!##%())&$" &)1699863/)#        $&&''$!!%(-2434/+))+17:?BCBB=<;;=<:8451.-04:GLNSVPIFDFLX`gha[QFA?HQ]dmuuush`YMEFSf~~n^RJFEFKRZ`cc]SKF=9=@DEFB<94127?GQ^irvxq`PB95<<:60-)&)29?FF@9/)('-379775201221.,('&('+.45532/,,,+..*$!&.1478883-(" &4IeoR5''+8GLJF>7238;>=71*#'-04551+)$ %## !"$%$! #&+..0,,*((%$"!"" )6?JQSTT]es{}uiVK<2)" !%*,,++'  $,37:9;51-'" "%$#"     !#$$"$'+003330.//49>FGFFBB???ADDD@><3-+**1>DKSVWSPJJPY]bd[VQGBDKT`luw{|uj]TKEHTg}ueYTKFDFHMY``b`ZSLEC@BBDDC?<7745;?EOXcmrndXI<7:@Ses~sdWJB;;7:;:;:40.,/8=ENNE=1&$'-4851))'&&)**.,,,,,+,*&#(.12556893*##.A\{kM6))1>IPOKB;98=>?=71*%&,2:;:7-'&!$%#  !""##'+2456/,)'%##" "$# )5ANUZ]`gkwpbSB7+##)+.0/+%!!%,1475510)$"#(*))%        !&*.234311249=AGKFGE=>==?BHILKIE=7/('-2=IPWWXXSSZZ_`]XTOH@DKWam}~vl_SLKNXj}re\TMKHGJLPU\bba`[WPLKKHLJGGCCDB@?>ACJS^ike[O?7;?Par{paQI?:889:;<=<967:>HNUUJ>2($&0??<50)" '.4;>?81,%##&&%#  " "&(,08:97/,)%" !!$&#)7CPZ^`dhmswvphXH;+#"$,/123/($$).111-,+&#"&)*))'#!      #%),1/241456;?DHKJD@;66574,$(5Kcvt`E3(,9EMOJGEA>>>><73/*%%,69;=761'#! #%''&&$ "&+/59;;50+%"  "%$$! )6EPZ```eghhd\SG:2*%!#-4742/+&!"!$*))&%%$ !$&(*+&"     #)+.2011.159>EEEFD=4/,**04;CJTZ^[TJ@3,')08CHQWZ]_acbb\VMGA<>FP[kvwnd^YYalv{~ymcVOMLJJKMLRTZ^bfhfjkijf_XVVVX^ckmoi_UI?AHJY\WOD;:=HZly}sjf^VPF@AAEHPVX\Z]`dd[R@2'%.6FSVK<- *?TdppdWE7-&$"$'-4:@?;51,##'*-20259;BGNOH>6+)3DYkssbQ?/(,8BGJGCA=>><<930-)$ !)18<=95/+('&$#"""%)')(&$"%+/58851*$!"%%$  (7DNW\a`\[YVQI?:3-*''$# %+25540*&!  !! ! #$$%$       &-/13/0.//1:=ADC?;2+%""&,5=CNWa^WOD8/**-3:BJOWY[bc__[VNFA;;BJS^ntsupje^abjt}{pe]UPILLLMQUUZ]_ehknqolid`a\[aivxhUFC?CLSSMD878=Nalt}}~zxuqk^THAAENW`fjjiiee\Q>0(%.8IUXN=+)>WktukWI9,'$'+07=EIJD<2*$!"%*-011379@HKTYTI>3/2@O^fcUB3*).7=?@?<::==:852-'$"$,468631.-+,''&&&'(+,*$!"&+-054.(#!"$#!)3=KVXXUOJGD?:20,--*+*)%# %+1453-'#"!"#$#!       '-/344/-+,,069=>=82*##,2=HRZ\WPF<2-*+.3ADHMJ@946;BRZdknv{~~xk`QEAEMZenqtrmfcXL@4,+1;JVVO@-(HOPOJA8.+(*.286+('*..-*+-/4<>;5.(" #%'*+)**,-.,+)&$&''*+($!!#%'+**&!  $$#!!%.7@FJGA:3-%$#$%,16:872,$ !$(,/-,(#!"%((('%    !! !"""#"#((,25551.,**+.134310+&%"! #&+5<@DE=81+,-,16589;>CHILOQRROJMKHHKKJKKOPR[`kttig^\`]Z[YZTTUYZXYY\^^_djskUE=8<><=86412477>CM]n~o`PHCFQXehfh^TNID>=858=GPOL=."$6K^g`S@0$#'2?HPX[_^ZQD7.$#'+1330-+/58DNX``_VE:0-/59=>70+)*()'%""&.3:<;4+$ #$%#"#&),,,*('#$)')*('"!!"$$%%'('$#"##%"  %*+)&%%)/7CFA:2,'!%,5<<=70,$  "$(+--*'$"&))))%        !  "##&%&&*,044943/+()+.0/1200.,,0.*)(&(*.569;:52,,.1569679698<966243/.13?NbuxjYMC@EMW][TQIC@AB?>><>AGIG:/""1CUXTE6% )7DLS[[^ZVOB5)#%).334/)(-5;CMX^^ZPD6+%(-2464-,**'%!"/5:<:1)"!$#" "%)+,+($ "&+++,)%$%$$&')')(&%"!&&((#"$##$#&-261*&%&,4::86.'"&+5:<;7.(#  #'*,+-+'"!#&'()%"     ! "%$&(+*.246752/+((+,./2421457:<;985364897751/-.249<<;7644148;DGINT]dkqsrhcYTPRU[`ks|}{{uog_XPLHCBDIPW`elquth\PDA@=?=9;:99743/08EXjzyo`QFA@CJMMHEA;;=DFDC@>?AB@:/$".;JMJ<+!+7DLORRSQNF;.'#$*/771,)),4>ELTX[UJ<.$ %+235/+,*(##-6>>80' !#%%"#(+..+%"!%(//.-,**)**++))'## "&(++%#%&$%#$-7?=61+#%).233.)% !'+15871.%"%(*,-,+($"%$%%$!""!"        "%&)*-./15843/-+))+-/14659;?CDFJEHFCE@?@<9432359?BCA<;850./3:>=AGP^nzwla]XZ]^hltzlbXPGA;>BIR\ajlu{}~vok]QPKGEEDB@?@CACC><;>GTfu}|{shWJC>?CAA@:755:CIJHC@9;995-% )4>DB5( +:AGFGCEGD?5*#!#*2570+*).8@HPPOSOE6*  )11.0-+,'##1;?=:3&#%'&%"!$)-010-&! %*01321...+--*+)(%#"! #*)**'&%'(&%!$,7>EFB:/($%'+-.)%!!!#&)-00/-(! "#&,/--*%&!"! """"#())+)%"       #&(+/0/02342/-,)'((,/017:>AEJOQSWSUVRKIGCA<<8:?>EHGFA<73/-/4778BGNU^gknsupkf^WNJJKMMKKIIEEJLQQONKLPUbnu|{qi_RHC=<=:853028@GILG>8442/+$ (05<:0(!!%/8>=>836763,'!"*4763.)+2:EKQUROHA4' &,../.++'$#0;@?91*$#%'*+++*/9;==6.(""+04677750/,-++-+)+)&#!" ''()((&(*+)%!"*4CKRSMA5-$!%&&&#"$#$'),,-*($ !#&)*+-($" !$'&$!!',.123.*&#!       "&)-024222130.,(%%&(*-225:?DJMSXY^]\^ZTQNIIEBDGKGJMKIF@9320367879>IZrxpljhfcedgmqw}lbVLHEHKLTZbfhhf^WME?@DKPSSSQLHGIRZ\_]\WUZahmqqpgc\PFA?>:762015@HMOLC81-++($!!$*1551*&&+38;72-(),..)$ $*/784.,.7=IQTUXQG=3( ',/-+*+)'#$/;BB<6-)'$ #%+-/35:@HMJF>2+$!"&+03:<>;841.,,-.--.,($!!#%((%()+..*%$.;JSZZVJ:,'""!""!" #$'*()+)''#!" $&'''&&" !$&(*(%$!'.367763-('%"!    "%(-369975430,)(&%%$$(-026;GQVQH=2('&$%!!"&,021,*.059:4-'" ')*(" (-492.,/8BLTX[VRL?3*#$+.,*+&&('#"09>D=<4-+'!" !',/6>DMV]`ZPD6-)%&*.36=>>?<70-,*+/001.+&#!""&'%,.12,)$"'/>=9420,*(""$#%&(*.16:88=I_}ymikjih^YUQNTW\cktzk^RFA?=@GJRXXOE;2.0:GS\_aWRLIHMV]`d`]WUSTY]cgnnjdYQID@?;94341*#!$&$""%(-131/458??80'! %)+)&%/340..16CQY]_\XOE8)" "'*+)'$##$%#!-77/-))+/2554/)%""$&*-/10+'# &/:CQYZTK=5+)&#%&'%)+.363/)$ ! ##%)*)+*%! #%'#%'$&)-056763/-+)'&%%#!  "!"#%&%&"     !#*.39=>BA?:41/)&&!##$#%%'(,059FOXZP?/&$'(""#'-246259?BB?7,&%(-/+(!#*.//),.4AS\__d_RE9-%""%++($ #"'4=BA??8/+&""(2>IZlw~~q`QA6//1469>CEGF?:1+&',/7::81+$"%*-0/,&"$*6?FNQMF;3/..-.--)+/26740)"  !!""%&')'%""#(+-+)((((*-1443/+,,)'()()%"  ###$&'(&'%#"       ""#$!""&+069@B@CDEJNWZbfe]WUYWWXUPGDAGQZejg_TPQT\adb]WLECDBDFMV\iqrpmnu{xrfVIA945;AHJJDA<-!$((&"%)156568CDFC<4+*.22/+%!%+.+'%)2@KXdfhe\J>0' $'*+' "#!&1:?A@>82-'""%-=K`r|eVF91/459<GGEE;454798653446763/&  !#&%'%"%*./-+(''$%')*-,+**(()+.+-+(#!! #&%')'%&$!     "! $'*+*)'%!$',/369=<=;73.(&#"#$$&)''%&&-/2667654578:<=><>?=<>@EKUbgqqmjfda_a\VSLGJOUY[VLF@EN\eig_UNHECDBBGJQ[ababafmw{riaUNF><<@FJMOMKNX]ejjheZSOLGGGKHIGGFJNRZao}q`PDABFF@<63=LRTL<-!!),+'" !(266877@HJGA;2/279:3+%#'*'&"%-:ESahkj_PA1'!$&+*&%'&$!!(/9>??:51,%"$-:H]snWH;6596:=>DGKIE=2(&'-6;?C>62*$!&)'# &.29=>==889;ADDA<;42121.)"!%%''" "()-0/+&"!!! "$&$%&)(*.225452,& "#$%'&&&#!    "#$&)--.//+*'$! !$),/3655231,)%#""&(+.-..*++-28:;95313/36::9>?>;89<@JUelx}xrrnhde]TNNPRQPLFAAGP_ekncYRKHGIEDFEINRRPRTY_jt}{x{zyzvvpkga[TSLGHLOSXY]fjrtvsl]XPKIGLMKGHGDGKSZfsyvaRC@@EHA:637?IKE5( %-0,("#,4;;8659BIIC<735;??;3+" "''%#! %1=M\knlbRC2&#%(*+%!*01.+('*179=983/($ #)5DXo{oXF946797:>CKNLI>0'$%-6=AA>92)$ !"" "&+/469888;<@FHLH>;5.0,)'#!!""!""$'(*+'##(),+&#!! #%(*.59==?;81&!"#$$$"!   ##'(+..34300,('%#! !"&(),+,-,*(&$! "$)*057644345=9:898<90&!#+141(!"/:@@:425?EDA;644:ACC:/(#$%&'#!#,6DTannhUD5)#"(+)%%06;:530/157975.)'%!$/>OdtylVC8124558<>HLKH:-% #+3:AA>:3+$#(),13334568=DHLMIC:1*%$ $&*+*+)(*.00,)#"%$%" "&*19@BGHGA8.%      !"&&*-0224220-,)'##!!$$$%$$#""# !%).57=<?BHJMQPGA;688:;>CA@?<:=:;;EOXcie_\Z[acdgedhggigd`[^_airw~{maSIHLOWX\YUQLJPS\fmunZI<7;EGD>6/+.020+%%+3983' (5CKF?5.37?A<70-06?FH@6-&%$&(&" !'0:KZff^TF3($#&*(% !+5=<73-% #)/2542313438:CGGGD>4+$ "%).35745333661/&  &+2:@HLMKF>5'"   #&(+-..1//10-,*&$"#!!  !%*05;@CDEHMOUY^\\QJE@<@AGHIIHEBACCCLVbm{tlffefghfhgdggjmpy~ukb`_gou|wukeVMH?<@GNYchc[YYY]_df`]]`fimlgefbemps~xp_TLMT[`ec`ZUOLNR\ckuz{}yqdVH<5;@FFB91)'&(&%(+33(!#/@QWMF81/17=93+(+3=HIC:-&$%'((%# !(5DS]a\TF5+$$$%'&#! ".7@EFD@941.+,++)'&" #+9HU`gb[L?50-*-.-/69=<80%%07::740*& ).4:85321//038;AA>>8/&! #""$%%'+09=>A@?=<<9:83+%"(/71-08962)&'1>DIE=0&#%()+)%##'0>LW^[QC6,%#'')(&$$'19?HGE@91/+*+*)(''#   #&-9FPWSPG;2+**('))02450)"$-1353/+(# #&/59=851/,**+-.27785/*"$)*+*'! "$')(*.7ADJJJGECC>@=85.%"$*/6:BED>8.& #$$"     ###%%%%%'*))**(&%""!!"&'+-25:BEHNU[cjrqrmf^TRQWacghb]YTQW[_elqv{}vnhb]bglqsv{{~xmgejv~m_XUV[^efcbb`ejolcaZWRV\_`b]Z[Y\b``cljkooqy{~ug^RHEEIS[__`^\XVVRI@659;BJE@60*'&))/8@IIA5,(.@YlrjXE6129961(#%.8CE@8-% '*,*)(&'.9COUVL@4+&$%),,+*(+07;@BA<41-(++-.,*%"" !"$###"'/8@GJFA93+'&%"#"%)-+($ #)/0-.,(&! !!" !(18;:62-)%&%&&'*--/,,' !'-3673.($!"%&)*,-3:CFNONJHFFEEA=96-&#  "%-14763.( ! #$$"   !$%&&(&''##! #$*-,/248=AHKS^fnqxwmgc\\[elsvxrid^^djsx{}~~~~z|umfa^dkpsv|}ujaeov~tjigiliiecffkpqvneXVQSW\YXSQPOQPNQTW_hs|k]ODADIR[_c^XPKGGGD?:67=AJIF>8/*)*,2:BIJC7//7Kdr{o]L<539?;5+%%+5==:3)"#(,,-('*.6@JNMH>4*%$#',.,--./478::50-+)*,01/+&%# !$&%$$!!#+39?=940+% "$%# !$&+++(%%$!! #)-342.*%"  !#&&''%#!'.6>BA;4+(#"%&)+.14CLPYdjotplh^^`boyvpfeou}}{srmjhknry~{sqjegnw}utuwqmigdglrwvqg_YWY[[ZTKFECBBCCFITcrr^PH@EKU`eg_XLA@CDC@:48>AFHHC:51---29BGE@835?Ulw}p_L>68@A>6/)&(1254+"!',./,)*/3ABA@:71-(# "%&&$! "   #$#"#      #$&'&%$!  "%&*,1147436=@GLT^gnnkfc\]_gt~xrsvzz{xrqtrvz|~wpkmijs}ulhdbeinsrmieecggd`XNC<99:<<9?IYoͽu`TICHS]ipnj[MA<=?@?<889=CGGG?91.++/4;AC@;;?GYkwvnYG<66@A@:3-))*--*%  )+./.,),18>B?=4+'$"#(-/21210.-,)**),,.15684.)$""#)+,,)'"!$)2564/(!#""#"!"!  ### !!"!!"!%-5>IPRRJ@5,&!"&()+../18;<:;>;:=<>;74/($! #(,)(#!%$%#!!#&$$"!    #%%$$$"!!  "$&*/0245358:>BJS\cdec^\[[[es}~{xrsw~|}}zuqolrznieb_dijoljilswwuj^RB75677959>NhνtdTKJLVblwwl`RB;=B@?=:75:BDHE>80,(((.5:=>?@DM]jtqaTB735941(%#%$',.03200,*'&&&'*.147:84-($"#$&,..,)&&),2543/& "!"!! !!  !"#"$%%*/7@IQUQL?3+$ %(')()++05768978867431($ !%(+*'$ !&+,,)#" "%(($!     #$$$#"!  !$)-01245678<=BHPWW[]\XTSRX`ks{{rnlmrz~}{|xsos{zjgb_bcbbcbgpy~xhVC9357:9756CUrƳo^UMLRWblywmcUF=?EED?:77:?BD@94.(%"#%06;@BFJNZadaSC7/-49>@=9/+'$$#%*/022.++,04410-'$$$$&(+-011-+)#!#$$'-248962.*% $'+./.-,/469981+"!!! ! !  !! !#$$%)-4@AFKOUWVRONMMSZagjlrsmgfbeilpvssqptx{wtztlga]^[YZ]anzpYI7546?>;639E]wr`UNNKNU]hppi^QHCCGJGC=88:@A@?80)$"! #*1:@FJHLRTRNC7-)*18?>;93*&# $)-/00,,)).-1/-+'%%#$%$(*-,-+'&""%*028640*'$"!#$&*-.147=@@>;5(#%%&#!  !$# ! ! $$$" !! "$$$%)-3;@FJGC:2*" %$$"!"$',2477532.,,&# "&'&$#! "&+18895.($ !%'*'%#     !"##$!"!!!#$'',./0248=?@<5-)'""'+.--+,''()),()*'&&#" #"'*,+&&! "(/0210,(&$%##$%().3:BFIJC;0$$)*+)%!!!$#!  $$##  $(,,)($ #"$%&'#%$)-16;?@930'# !"#"! "'.257870,)(%! "%#$$#"#%%%'+/49<96.'%! #())%"        !$&%'''''&&**-//./36JPPLB858GYioneZPKHGEEFJLNPQQQOOUUTWQF@<;?EHE@5-&!!%*08BGIJFD@;730*%'(.5>AA>61-)# "$((*(%%##''(*,--*)'" #'(*&##',./-++))'&&#!"&-4@IMPPF;,#$*001+%!"!"%"!!"#%&&&$!!#'+2442.' "%'&*())%#$%(-.11/-("  !##"# #$'/5:685/+'" !"!#'()(+--/469:40+$ &('(&"      ! &(*+.1/-/,.1343116:=CHKHFGDDIHIMLPT\_bc^VPGDBBGLRXUVTSRTST[iz̼~zvrrlmmjvvmcXJEB>BNXenrul\K=36@LVZZQC<;@JRXWTLE@CFGJFGEDDGKORW\]\UMC::>@KMGE9,&$$&,.5?CFJGC=930-)%"&,39BEEB:3/+%! !"#" !&(,/231.)$ !"%'+'$ "%+,..++,*)*+%%$%,6@JRUOD8.#$*.23/*#  !#""####$# "'')((('%&(,17685-'" "%)+---,(%$$%%'&''# !$$%%%!!"%*.59771/)$! #%'*..126669851,&  "$((('#"     $)-0599;9759878834;=?IQQQJHGFEGGNUZ`jrw{og^PJGGMQZ^bd`\Z[YYbo{Ƴwtojhfktuj`VJA?;=EMXcmqi]O?45?O]fiaTLDDHHKLHDA?CFHJHGFDCDGMW]ac^UJ?79?FQUPI>0*').16:>CDEDB;30+)('),08BGJJF@81,%! $).46896/'$""%&(*)&" !$(,,+,,*./0/.*&$&*3@JQRKB7+  %,112-(!"#&'''&$%#"#! %((+++)(&'*/26861,&" "%(-.///-+(%" !!"$%'&##! #)-/488520*&"   %&),/489:;976/*% "#&)*'%#      !#&-49?BEHDD?@>:97669BJSZ^[RMJFFHIPZcq~xi_[WXdmuxz|xrsnos}ȸvkebbmy~odVKGA>42;Lbpqpf[PJGFCDCAADFEIQLLMIJFIR[dccWLA848DNVZZL>1,*.478:<@@A@<82.,)**-17>DJOMFD=3,&!$&&#""&*39=@A:30+%&')++('$ !!!$'*,+,+0.03652.+'(+4=HNOG<2'! $(+01.(# !%(*-**('&#$!#$(+,+)&'(),02320-'&""#'(-0/0-)*$"&((()(&#"!"&,057895/+'%##! !#! !$'+068=?><:72,& !#$&''&$         "$&+29BIMPQPMHDA=8767>HS\dih_XRMLJPZeq~srwrc]]dm~ygZMC@=>@ACKSY^ca]O?63:E\mtyqgYPHFBADDDDFHKQRPPNNLORY_\[OA703;61-,*)-04:CFLMKD>91+$  %*041,&!$*08?FFGA>:3-+,+,*(&%#$&&))*-+--,-279;:71*'(0=EJJD:/($ !(*+-,($ %)-1/0,'$$ " #$+,,+)''')+-,-.+($$$$&&(-,+++)& #''*+,+)(&$# !"$*0389752.*'$"!"!""" !'(*/46;@=@>942+$ !""#%&$"       " %%(-7=ELW\[YRMHE?655:BMZdkqpia[SOTXcnøĿŽ~l\[]fzuaPD<7:=BEINTY]a^ZP>426?Pdquuk]TLE@CDGIHJIMRTURRRPQTVWVMC;1/7CVhon`QA50/58<<86558:631-(()-2:@DGHFC>;3-("!(0:A@:2& #'*27=DKLMJE;840.+,)'%&''+-,+--)('(*16;@>:2(&&.7@CD?90+(&%(,,*'#")/122/+%#"" !"!#(+*(&'''+))()(&$$&'((&''&%#$# %(-2210.*&$$!""!!#(-468;983/(#! !#!"! #$(-,/2669<>=<84.( !!#"!        !""#%&,/7CLR^_a^ZRJC?6447@O[kwy{tjg`ZZ]ftêucYZar~~k\K@638>DINPRVZXXUK@4/19KYhnph^VIBBDGFKLLNLMRRTSNNLNONKE>616ERfuuqcRA4//6;:985367773-)%(+.6=BGFC>:62-*& !+6CMNH<1'!!&'-39AENSRRPJB=5/-*&%$#%),/0//.+(&$%$,4:A@;1)$&(1;60)#"#$&%'(*/011457;;;8630*%   !##%()03=DLV[bea[WND=6569AO_jy~~~wokebfr¢o_Z]iy}iZL=778BFIOQRRUSSOH@71/9EO]jhbZQF@A@GKKLKJIHLLNJGHCBEC@;;7:EUfusaN:0.168<=85435660*&%'-1;BDIE>31-(()'#*9LSUQD:0&&)+.7==<><=88;FWdtznYD3-+1;???9;=6654.)$"%-9BIKMB8/%!%'+)'! )7GUYSG;2*(-23:AEHNTRSRMD>83,%"  #+-232.*&"#-7:<3+&"$+2;BA?<5377;:71(#!&.3540+% !"$''(&!!#"#$#%((+,+)''(+26;=:3,%!(059974-& $""#!"(,5:@C@:1,"!$'*,./1443411/.-,+(%"     !$%(,-27=EJSZ_]]YQHD??>@HWanx~üض|obdju}l^SMC?BEGJNOGDBAADHGDECCIOV^c`[VPKIIKOQOJE?=;==<;86567:JSTLC4& *.1.'"!'3APTRJ<3+,/27:@FHLONPKFA<2/*#&+-22/.*&"!+2770(%"'.7>DB>9547;@=:3*"!'.3451,'!"%(+,(%!!$#""%&+.001,)+-29AGFC<3*""',2341+"#%$""!$*/4:A?<7/%!&',--035310-*)'$#!  !#%*,.127>DJSWZXYTLLGEDGQXdmxŽյpihoyznbXRLJIHIHMH@=<8;AENRQRSX]_eieeaVNOTQRRNHC<;:7783113488?IQZfpy|ugUB1'$*1=CJMKGE@<<4.&#%,:HTZUOA0",7=9.&"".;GMKE;0++,/38=@BGEDHC>;6/*%#! &&*/1/-,)$#*145.*&&.36+#$*0250*(&%&,.-)%#'%#%')-354520/29CKQRJD80*$"#$#$#!%'+,'% #'(&"#&)/4;>;70*"%)+,.0000.*'&#     !%))++,.179764300/248>DLS]dgkj`UG5(%%+7AJMRQMJGA;4.+'(1@PY_ZN?,#1?B@6,%#)3;951.*(%# #&(,-1.-*$!!%-1461-*/7?FIJD;5137HQUVSJ@70/-,..+'" !"$$ "&)*&$$$+17;;:3*#!#&'+.-,)('%"        #%)***(--.361'#&-4883.*(&%)('('(.0355622/+*('%%$&)./.,)&"!  #+03546328>HPOKC73./7?DC>7-#!&.2350+*+,-00+$#'--+)(+06:>=;8567?IUYWUPF>9664660+'$ !&*+*&%%(-27;950'!%%&('%%$       "$&(*)(*('),/39;FMQ[\_dfffiu{zuswx}|zvmb_VQKLMKIEB@:52./5?MZdfhmnnry}}wpgb^ZXUVQIC:330/.-02338DE=5,$!#,0321,,,+.1-*%&,21-*().4:=@>8448ABC?9330-.2249>CHOUUVQOIC;833452'#+9?A>7-&""%*,.-*&%'%#"%*/47::952/)'()+-22+*% $$(+/599><=BGOTUVM@8103:@@C;4,&!")1411-*)',/+(# '/34/+)&+4:?A?83358BKUXVNH@<<;=;840*(%!! !##%$$"!$%),//,)%"$'+47752+%!$$!!        !$'(**)*($%#$$%).9AMS_ihmporzξurty~{tneZOIBA?<9:8553/-)'+/7BJNQY^^bcfhfjgb_^^VXTPGA93+((+02268487:;<52,,,/469==@AFJQSONIA@;631169?GJF?5.#",4974.)$"#$()*))''&(#")08<>?<:4.*&'(-033,& !&(+,/39;=AACIOSSTLC9314:==;70*%%" "(.232*&%'**(&""(/33/***,4<@@=94105>HMQNKE=:88:752-*&''&%%)*+++**,,0241.,&##&*.244.)&!!""     "%)-.,-+'&%$$#")+5AKU\akloou|{˾|shmox|tod[UIB=9823300//-(&(')09=AGLJLRTU[ZZ^[Z_]XUSLGB90*'').36997778950,**.2:?@@??>BBGLHF?<822--+15:>=?92*! #)-0.*'$"" &'%'&%%'('# !&,39>B@?:6,&#$)0333-'#(*,/1359:=>@FLOSOKC;643<:753,)'&%" #*-0.,)%!"%'&$!#+034.+(*05<>?=91-,09BGMNH?85/000--**)+,)-/.213212100245.+&"!#')-00-($!        "'+-.0.++,*'%&'),2=DPZ^gimpnu|~ɹ}wrifjqw}~{zy}yleWNF>743/-,++-,+&%%#&,046;?CEHILKNRV[^aa]XSLFA6/)%%(07:>=:::8632.-.16>@A@A<8:==AA>:4/.+'('*.35776/'$"#&'%&%#!!!#$#! ##&%$#!" #')-27<62+#!#+15990% &-/./-13658:<@CINJGA<866871/,(%%&%$!!$*11-)%!#$$""*/353.+-3:?@@;7.+,.2;DHID<5.)((''('),200345898:710005661-&#"%)+*)(###! #      !!#)+/34320./.,+*(/17@ITZadeiilqsxȴ|zpkfhkoqusoomqzwl\NHA=540-+)))+/,&&""#',,.39;>@BFCELS[eedc\UQH@90*'&+27?C>>?;:752/,/16=??=:5229:<:71-+)&##%%&+0145.*&$$#$$%!!" "#$%%&))+,./.258892-&!!%+17;:3'#+241-*--.21356975442.*&$$%%##!%)-02-'! $#" $',021237=BCEA94/)).1:@ED?6/(" !#$&(,267:9;=>?;62/./4;<52)! $())'&$##"#!       "#%().24466667411-/-17=DNTZ`_acghnruyĶ{yvnkihhdedb^_inu{|ohXMF?;741/.,*../.,)#!#$().78;=ABA?AJR^hljc]UNHC<5/+),3BA<72210-*'%%%&$!#+-021-& "#" !#&*.036;AEGIGB:3.((-2:>DA82*##)/3:<;=>BA?<5.*+,1:?=6-!#&)(&#!$!!####       ! $&()*.27:8;>:==:8523127:BHLQXZ\\_bdknv|ĵ~}~vqpjca]XPNV_aho{wg]RIB?;98332.047853-(##$)/3:?AED@>?AMXgnroe[UMHB@=7/029?EIGD@>:8741/-++,,..,+,,.1010,(&" "(-1231.*'(('$"!"" #%(+.112,($"!#%'&#!*/694,"")1640'"!#%$&&')-389873100/.,))*)%%! %+/111,$""!! #)(.28BFINMH?5/*&(-/49<<4.'!!(27;:<;<@A@<5,'&+4>@?9. #''&$$"!  #%'&&$     !"$&')---/27<>>>@??>:98542175>CEMRPWX\_cirquy~~z}vlbZOKHIRYbju}xl`WKDA?==?<;79;<@C>82+$&(-1:@FGJHGC@DN[nvwqdZSKJHHE?<968;?IIEC?<:830.*)&(**,,*+.0.232-)&%!!#).241/-,))++'#! !$!"$),./0/*'" #(/44-'!")250.$!"#"!$)-2210,-/1573///.+% $)/1/,("! $&+0A:3)%&-8CFA;.!#%()&$" !$')(&%"     $%&((+,/0333677<=>?A@??=987524877>@CLMQW\ahiprqu}ſ}of[PIBDJPZbosx}tf`YOIBDAADDDB@ADEIJF>3-'(+/6@EHLJKD@?CM_msxwg\QJILOLFGB;=>ADFDEA>:7620.)&&&*--,,-10232/-''%"!%+.10/0.-/.-,&""!!#%*,++**+)%! !!$(*-,(!")-.-(!! !')--+()+/69=@>953/'!#(+,,+$!(/:CMSPI@5-(#"$(,/121+(%")3;=?>>===>85*'*0.#$()*'!"#%()))'%     #%()+,-06888:99:=?>@@><=97775679:;>ABHMUY[aksquu{Ŀ¿{mYPIBCINV`hqrvssj`YPHCEEGJOKKKJMLNVTLC:2,+-0:DFGIJE=;=@M\iuuqeWOLLPRWSNJCCCCGHKLIC>=;985.*,.13330/022461/-+)*(" !'+,032/0330.)# !$#"')))'%')-.-'# !$%%(('%"%)*&#  $')'&$%)1:BHJFD@82*""#(*('"!-9BKMMI<2)#!"%&)*)))(&&$%!(4=??@>;;=<:6.++3?EIH>/"&,*(#"$((+*'&#   !&)+/2346:<==?>;?>;<=:::863648<<<=?CCDIOY`cnv{||}ǽtcXOJELSYadilrmf`YVOMGIKMRUWXUSTSTZXQF:4-+18>EFGCC?988?N[isun`XQMOSX[\]TLKJGMNPQONIFEA?=95568;;94/-.135200/011,'! #'+.1111353,' #&('! %))'%!"(/:>?:0' $(*,+'$ $#" #%&# ")2>HLOPGD<3+# !%%#! *5@JKJD90'""##"#""#&)+,)$ (3?B?BBA>==::753110/38=?CFGHGGNV_knxɷ{f\QNLNTX]beikge]XTRNLLQT[aa`\VUTY[ZRH:3//3LUcmomcYQOQT[aggb^XTRTVZ]\WSONJIFBB?>?B?=60,,-2443446785/*" $+./241230)$'+/,$!(,*$*:HRXOA2#%-11/,$!"$%#!!(2>IOOOHC:4-'"(5@HHF@5,%!!$(2542/(!!(3:@>>;56:8651018?FGD:,% $(+*&" $'()'$      #&,/468<>@?@@ABBA@>;8450.*,1/6;AKKOOQORV_hrȺ}~yh^UNRRSX^aaedce^ZWVQPPV_dkmje\VVXYYRE:1/26?HJE@;50.04>GS^fdd`YPOOR\eoqpkfa`dinqme_[TUUONKIGFHD?5/,-/1677779>@?:2'" "&*.01100.+'!"*13.( %+0-% -AXhlaN;) !'3874-% ""! $&" %.=CJMLE?84/+'#  " "+7?CFB:3*  $-:A@A:1(#"(27<=;63367421239=DEA7,'$%(*+(%! "$%'&"     !"#%(.146:<<>AA@BAA<=>9610*))*.28?HQRWUXZ[`ku~˹}}wsrsrsux{raZTOPTTV][\``^\[][VUUV^gov{xj`ZSRTVRF=4/29ELKHC91.+/7@HTZab`^YQNOQZdqwzztsnr}}wmj`_[YWTPLLLD@8/,+059;::?@BGEC7-($$),.0/+-,'%"$.452* &.1.% /Mhy~u\A* #+4;=:0'!"$#!$''$ "*5>CD?:95333.+&!#$(&$#%/4=?B=5.&! #,6BHLME:0&#&-3897200/010./47>BA>5/+))**)(% "$# !$)*(''"     #$&&*,,0358;=;;>>>>==;:71.+''*,09ADMY\`abghqyп|tqlecafhkrzz}wl\QJJKOPQWVWZ[[[\\[[VWZ`kvrfZPNSROF;326@LTTNE=61.3;BKQV\\\ZTNKMR[fw~|}pga]\XVQNLJF@84005:>?><>@EIKG=5.)&+,..,)(#!!&27:6-!&14/% 4To{aC-"#08>C=1)# !$&$ !&,+)"%,588632247730*#"'+-.*)%"%/37;840)%#! #*3@HPXTNE7,&$(.3741-+,+**-.26>@@=82,*+,+)&"  '.479940*'!      &'(-+,+,/34678855898:98440.+*++.5?JQX_egjnqryؿwrmjd_\^bekw}~~zxtkbWMGEFFKNSTSTVZY\\ZZXT\fs{j[OLOMJF<447BLYYTLA;67;>GNSUYXXUPLGGO[jvti]XTUTNLOLGA:46:;@@@A?<@GIGE?6/,+,--,*'$  )28;90$#+36/$#9Vu~^D,"%1AGD>2+$$#$"!$'&% &,0.,&',./+,./49<:4-%(.1530.)# '-1241-)%$$&&(%$'&%+19FNTZZUJ>2)&'+011.*(%$%&%+07=?C?63./-,*'#  (4>CFGA@90+&"!%'((%#         #(),./.,,+/0014301113443420.,./04=EMSahmqrv{«}vqk^\^YZ_hrz}|{wqmcWPKC?BDHLOMPRUXWY[\WYZ`myjVKDDHFB<514>LY[XRJC>?AEORTVWTSNKGEFMZjywcZRNKLLLLKHC<9<>DFFE>=<>?CC@<20+-.--*)%!*2896/%$+340"#@A:61//-)'$"!  '6BHPQTMF@72)'%$()*,,,+($    "&))-/-0,)+)()+*+.)(,,/2-0-,../06YqkO7%"+:DIF:1' $%'#  $(($"#*27:93," ##!#(/9ADC>3& (/8>@<93-&! "#$$###%)-.2366557:=BDKMPPKD=4-'%%&*,('$#+29@>=830.+''# !! %0@LSXXYSLE?9/-(),/001/)(#    ##%)+-//,*&&&&$%%$&&%%%*-.),..1449AGQZdhpswѾ~zpplmknrxvslkc_YQICCAACFGPSW\^deggdbahtyZG?@DHC83./3=JRRTRLKNQTW][UQMIB?BBDSbnwyqmjroXH?=@EHGE>;20-*,-+*(&)**/.+($   !),15.*" &+,(!*>Wnxn]E/#&,:HIA6+#$#$# %'%#" "(07<>:3+%! !! !&0:CJF>4) )39@B?:1*' "(.159:9:9:><<@?AABCB=95-*'&%'($#!"+2:?@;7/*('#!!)7DOX^[WSJF=93+++-/2//0)&#   "!##%'),,,*(#" !! !!"%%(+,,,0226:=HNW_emyzİ}}vxz|zvqoifcUPIFBABDINS[`glmonnijn{}]F>:?CA80+'*6@GJOMPQSUXa`^ZPIC><;?BDGB94-)''%%##$$'*,/.+'$"!!""  #&*-0-'!#%'# .AUei`M;(!&04'!!"$%""$(.5;>?;2*&# "! !$.=@CB>3*%'-6>;6.($""#" !#%(-102.&&#!%%$$" "$),,,& ! %3BU`_TA2#%.;@@9-$!#%$%%+07?@>82+$!#""#!!$0=JSPI<."!',4984/+)&&'(&!%*-256987865530,+)(),-0.0*&#! #-59>84+# !##$"!!  #*2;CMSROLC<84-)(&'+--,*)%!  !## "#$&&'&$#! !!#$'(*-/005<>@IMMTYflt}ιzpidWNIC@BGLUdhkty|}||vqyļiQCBBCF@5,'%'-4:=DFMR[aage[QG=:8:4456861,)&%&((%$"%(+0350.-*&'),+**'&'((*)%  '5AQVTK;+ #*3982*"#%&&#$)07?@;5/)$#$'((%"  '0>LVVM?1% !(-10/*'(*,./+&#! "&(+,.//000.0-))%$! "#(,,,)%"!'/59:7/' "%&'(&'('%$$%)-3:BCFCB>61.(%$ !"%(*'''" '!  !!"""###%$$$""! "$%,-13688>=BJRSTX_esz{~wneZPJFFDGRZ`lstv{|zyrrxpWIB@@CB92(&&).39=CJPW_ehb\QJ?87=HUcoqpeYH97;GXiwzth]N@9437;=A=852-010-*)'(+.00.+)*-23451/+)),-0533/,*))'&% !)4AJNLB3'!(-01*#"&''%$%)/6;;64-&"!")**''#"(5CLWVP?2& #())('%),1561*%#! "%%&&&&''&&'%$##&()&$$,04872+"!%'*,,,*(-*+)**-.27:;<94.,)#! #%$'%$#$"%$!   "$#$$#$#$%#$$&)+0368:ABDGNT\_eksux{xyuz{x}|sbWRKHNPP\hkruttupqrlotzpZKBFJJF@90*)*+17:BDJR[bca]SI?98>IVahieXI?5/6CR_mroeYLD<96577:820-**+)((')/48<963/2366741/*)*/51$  %&$$#%+,48862)%!  !!" #&&%#!"',2542+&!""!"""!$&*-,.--,),-..-/0015550.)%#"&%%&&()'%#"  "$""!#%$%%&')+./37;@FFINT]_ejss{;}wsliis}vp}qcWPLPW\amw}}wtnkgfdhmktsZJCFINLFA:20/.048>AGOTZ^`[OF?9:AGS\``YMC9206AOZdff_XMI@9630340-,)'&'$#&(+29?EC=:44588430+)+.4=JPTVND:.'$""" !&.4:=93+" ")-120,'$#&+1331,%"#'*++)'%%)4@JQPH9,!  !" %(07;984)%" !!#%$"#%(,-352.&! #%%##$%'&'*,.-,*(((+-14256421/-*$!$$%(*-+*+)%"  !!!"#""#&%')*-248?BGKKQW]ailvy~Ų~vrgc\^gsxlmyk`TOOWbisvmd]ZX^bdl}oWIFILTVOIC=753457;?@HOQTVRLB<:=CFNVWRKD<3.2;ANV\]\TTNJA:510.-,++'&((#"$(.7?CHEC<6535520+(*,/9CS^dg`PC3)! #&%#" %)/.1.*%&*04;850)%##(+/0-'#"&**)('%)1:CGD=1% !!!!$*3;=:70&#""  #%$" %(*-01/-'" !"$$$%%'(&)***)&$#&)+058:863.+)$!!&))-.,,'$"     "!!!#&&)+./38CHKMKE@71,0260)""$$&)'&&$%"    ! "%(),04:=BFGMSXW`fls{ڿ{ullg`ZRF@AMcwsa[^jm^QLOXfvlXKIIPVY\abgie]WPKIOV`jjhbXQLGD@=:7758=@BEGHFGFDBCC=81.'))07?EMONLIC?=:8744799<96410+'')*2:>A?;70+))))(+,-..19FWfvypcM4$%1:=95,%! !!"!!!  #(/5Kezn_Z^k~wgXMNOZhqkXLHGKQTVWSTTSNNKKNU^hpqoi`URNJC=96458:31'%'+08?CIKKGB>855346;BFHFDB=83+*(*-17:<;71-*&))*,.341113>LZkmlYH3#!+8AHD;2(!!!#"$#!!! "#'.6??><;;;=>>:84/,&!!&&))'# $$%"*471(# "$!     "%(-17;>CDINPRTYahqyνwtga\WZSPOKBBEQeyn^[am{~o`PKNS[fo{jWMGGKKLKKHFDCCGIOT[eqxvsic\VRKFA;5228;CIMQXXSOMF?93/+'))-/8>BFHHD@;30.048AJNQMMIC=60,,-/4599841.++,+-/155321/4=KY^`SA4'#+6BKOLA6-%#$$&'%"! #'+38BEEE=3)  !  "&*3?8<;610)&%$"##$%$%# "$'''&'%%""  $$%$##"#,3EHC=4.&" ""%#!      "$(+048=BFIKOOTWZamwɺ|xph_ZSMQMJHFBBLXcyne`fmw}tdXLINU]hrx{k_SKDGFFDB>;87?BGGE?:5/,-4;EMUWTSKE>631/2357:9930.///-/0465401,+2?FNOHA3-.5ANTUOE9/)&&)+,*(%"  $+1:=EFD?2( !$)/5<@D@>92.+((%$$$$!"!#(,.+*'" !%)*,)&" $,8BLTYZYZbca]ZPH>3+$%&+,,*#! "%#"" !*3;CD?90+%! "%''%"      !"&'+.47A@?=:7223:BHLS^cluutrnge`YQH@51.-23,)&&&,037:830,++)$##  !&-/00,& $+.00,' "(3=HV^bdefghie[RJ>1'!%)--1/*'#  "$&$# "# &28=?:3,'!"&()(%"    $&(+037;?EFHKQTYZ\dlt·zqkeYQJDEDCEGJQWamwymeghlkhh[KFGHU`ny~|yrke]XOHCC<;<:731217=DKNTZchkosokkga[TJ>60),38BPZb`a\OD:-&%%%(-2677;>@AEFHD=72-.1C?=<842//1121/36662.('&'.37::;CJ[lyk]SLFC??<9:964445:@EJMSVY]bfjjjmgb\RG>4,)*06CNY`c^VJ=0($!#&+157;;;<>BFKKJE?2.*,49@FEC<83468>?AFE@<:52011000+14222.)'%&*.368>CGOXZ[XN@5,%%(.04551-)%!"##$"%)37761( "%),,,1347741,+-/-0-'"#&*052.)"*3672+$ #(/5ABGJKOTX]fjrzĿ¾zysmlkkhedbZYOJEDACFJNUX[_gmpqurmfa__\WTNE=;AO_yq^OC??=;;:887576;=BDDFHKNTY_chghf`XPI>6/,/16>JSZ[TL@4(###$(.46;=>=@>AGLONKE90)&)/37:8650138;979;:=;<>>@?==@DIQZ`deb_XRKE?;5655:@GLTTMEBEFEDB@:63445545220,.-,,,**)-.58@FHLJHB9/'# "%+000/-+("%*/332/'  &%#$+/01-+&'%$#""&-4:<<5-)#"&)+("#*350+%!!&0:@GKPRVX[ZWSJ@;8852-'#',3:895/*"#+00+%"%(("##"!#)-/1/)%$#$&((''')'&#   !%*,/357;>ADHKNUZ]gnu}¹|}|tje_ZYUQNLKKHFIGDC@?;9:?EKQVTY\\\\cfeehd_[UJE@?>AJVoƹfQC:79;7;@?<><77644:>ESYaddc_UNEA@BBEA@BCGHMNJ@6,'&*07:<@BFGIHEFDHMTTSOD;.)$$'(,+**(),3:@DFHEDD@=:<979::841/+,,+,*(',+/58>A@=;5.(" $)-.-+*(#!&/8<@@<7-%%,131.($"!" !#*18>ED<5-'"! "&% $+21+&""&3=GKPONMOQRLIB51*'))&%" #+.49843.)"#(--*#!## "#%#"#),-..)&" "$%%'')*+'''"!  "#')+/458>=CCEJMV\_jrz}wqniimggd`WSRJHIFDFE?A>=:6686448?CINRRRSSSU[aelmfa\OJGEFFFL]r˾mSA9899;;=?>?<9:41.,.08CKX`hjcbZPG@>BFOUTPJGFHKFC=1,'*28>CGJJKMNMKKFFJSWUOIA81++*)++*&&')/5;ADGKKJIHBAC@?A@<:3-)*)+,*)(%(*.0344/.*%  $&**+'$#!'1:BIJKF>5,!&-220-'" #$)05:BIFB;4*&$" !"  '--.( $,:ITSNKFCAA@=72' !$%#! %(-368830-(!"(**' #'+)&  !#$#%! $')*&%$" !## $%'*+('&$#!!      !%)+,0459;=@BGIMUZ`howvrsmgd^\\WUVUSOIGCBAAA??B?>86200//246>CEKIGKKKNRY]dlnmh`UOKHIILU]nȼhPC7368=;>><=<860.*),5;GS^jlnf\PHA;=GNY^`[UMKJIIE;2-,07@FJMOPSWVTSLGGFMPPQOHEA:43/.*('&'*/6:@CCIOPQVRLLJHHEA?6.)())+,+'$%'()++))'%! %),+*%#!!(1;FLRUQKD:/#&,010+'" #%*-269?CCFD=6.(&'%&" ! !!%)+.(!&4CSZWOF:22152+&! "&(&""!"'*05676410+&%()$%,244.&! "!!$$#! $%$$! !%'*+(%%" "      $&(*.135:;@>BIKMS[_dmt|~wnnmhb^Z\YQNOMFFEB==<8:==?AABA>962//,-36:?CFHDDACDHOW]fkomi`ZQNLKOTW\j~dL>337;<;=;;9742-**+/GVbhkgaUMHHH@:5/039DLNPUWY\[XRKGB@DHKOPQMJH?:61,''(*-457<>BFOXZ^`XSQKHEC?91,**)--,((&$&('%%$#! $'*,+(%!#&/8@JQWURNF=1(#)/-,'$"#'.37:;<=BCD@;4,'(*,+)#"$%&'(*--,$*;=>DKSYennjh_YVSPPRSUVaq{_G:556;==><:8740.-/38CQbmtxvpcZM?67;HXcmrkeZLGDC?<6225;AGNQWZ[]][SJIA==@EKOTWTUJC<1,*+,/5<<<>>@FO\`ehcYTKEAA?:4/,,./0.,*'#$##$##"!"&*,,*)& "(-6;BJLQPOLC=3*# ! #'+))% "%-59>A<8778::62,)+,11/0)%$&)-/011431,$",=Q^[SB1"!%#$(.4331-'&%#%,158740+))((%"!"%(& $.48:61(# #'''%!!###$      ""#$$&*.04588;=?EIKMTY`dipry}|uuvsrrplgfc_c^YSNKJJIFFDBC=<94111/1369>BGIKFD?82223>CNSVVSJC><9<731116;?FNTY[`^XRIA=989?ELU[`]TI<2,).4?EHIFB==BLXekke[TKCB?=9533362320,(%###$$##$ !!$%)-))'$" #&*/6;?AEFFFC>5/'$ !$')&!!(1=CDD=3/++-12,+*)-14670,+-0158;:<<5,!!/@RZ[K9)%&$"!+/27861-)(%$(-2873.)$!#$&%%# !%''$")/340*$"&**+*%     !"#$$$')+-03679;?A?FIMSYZ^fhnqttzx{|wqpnkmgcab_[ZVRSNKHCEEBAA?B>9740---0047=@GKOOHE?;8::AMS^dhhaUJB<:?@CLPUUZ^^]YPPTXWYTRV]jvwdTB:8:ADGFGGEC@?=>;=AJR\fmlkh`VNC;736>JYchd\PE=98622/.//38>GNUXYYTME<95326IRUXOF=9;EN[cgb\PD>:9587888<:763.*'$$$%#$$$"!"!"$(((&%"!!!%)-15667:9;953/+&" !!%&($"(6DHHE:-$ "&(+*()*.148720/256:=?>>=5-"!2AOWPD2!'+,(##,266762-)%#&(-321-&  "%$&$"##&$'$%**)&!#'-321,("   $%$&&$&'+-/3779;<>?AGLOTY\`efiomnrqokjfcdcb^][WRTRNJGFCBDA?BBA=994.,+,-037=CFINPMIA=<@CEO[epxvtmcTHA=AACEJKLRRTSQOMQWWWTRRT_kqwup_QE==@EINNNOMLIGHEEFJLPXaab^[UNJB;5448DNU[ZTJ>400.-0-,))+16@HOUUTOJ>:70.//5@KUZ[QF6,+,:GU^bdVI=64:CP[^^WK@733268;=??=882-*&''&'%$""! """"!!!#&+-00/-,-+++)*)'&$! "%(*&! "+:DGJE7) #')'%)*-053212689==<=?;3,%"2BKPJ:+%.22.&! &-04422/+&!"#&+/.-& "*+))%$%''&'" ! #)079:50,$   $%%)'&&&)+/1268;<<=?DIKNUYX^\[cfbfddbb][[XUURROJKIECBCAABB??@A=850,*+/039=CHKKMJFA>:=85428@GKKJD;/*''(*++))).34/19BNTTQG=1-,/18:=AA=:5.)*''**('%#!!$%)-.+'%!!"#$%""!%+..)$$&.=GJNH4$"%'&#$'&+--..02477557652* $.>FIA4$$-6873)$$$'/122.+(%!#')*'&*..-((''))'!"%+39=>?:2+%   !"%%&)()'&'+-025789;=?ABFILMQQQQVXWYXTVVTQSSQPNKJGG?>=;?>>ADCDB><52..,-039AIJJOKIDA;77>DP\gp}xh[OHD@A?=>L]hkc[O=2++08BJKJD<3,+,/3;>IRPC3&"%&$"  #$#%(*.242/-)+,+&! +9=>6,  '2=?=0)&&'*0.-+&$##$&!$)1220++'(()&" #"$""%)06?AB@:4+% !""     $&&(')'&('&+.045647779;:7539;>CDDDB?:41-*-05:?GNQOOHF@8139BMXckryzk\RJC@A==:899:=999698<<60,)+059;82,% #)147:9;BDEHB<6/)))('(&&,4:>>9/(#&.9DS`d^UI<4)'*07@EFA83.**.47<:85/)'&(,/11/*%!!$&()($!"!#!&-353/)%)3930..07=BGOUURNJA61/0:GS_hkmqsy~}}wi[PGA@<;8332468<>>DJQTTSLHGLNQVURMJCCEKWX_efe`^WNIC=7546533230167;>81-(').3891.(# "%+3=ADGHEGEA<4/,)&'*('#"'*/10.*# #*4>EQPOOF=4-&&)-6<=>81/+*.33760,(#"#'-2775-("!! "%'))(#"""%%" !&.252-&"'/8CHC;0# #%"%+.-(   ',/-'#.5=<50)(,263.("&.8:;93-,$#%!!#,361-)$!#'/6=>==60)$!%++,.-*%#    !#%')(%%%&&')*.././-.1.01126576:<;;:;;=?=;9762/-+(*)),-27GKNQQHECCEHKNMGEBABHOW]dda^ZRLE>7/00--,+,,..06;;83.(#$*05774,'#"$.8EQSQRKF@94.*'&()'(&#"#$()(&""(,48?CADB<6/'&$'026::62..01241+%!!#'.69960(""#%#$""#%&*('#"#%%&%%#! %*00,'" !(08=;4) !$$ &-00* !! !$(,'"".5;81,**.351)$"+38;<;5,%#!)26872*$!$,14872,'$ $*+,/0.*'&!  !#&&%'%$&$$&'(+*))+*+-+,,,,,../023436569523/+,)$$#$&((,17:>=;<:633368969@GQZ__]XPI><;7440,(# !#%(.267774-(&()159;63/+,3=LZ_`]MA7-%$'*-,-+*(&%$%#!"!%(()+.579963-&$$'*03577530.+)(%!$)/3884.'! #&('&&%%'))'$"#'*00..*'"! "','"#%#"" #%&'# #*0681*"$(*(&####!  '.33.)$#)/41-#!,29;;5,$&.6;=95-$ "$%$%$!  %(-.,-,&"  !"$$%#$$!##"""!!"%%"#%&&%##%%##&&((()))(''"!  !#&)),,-+-//0.//00244LV]ZME;8;@FIB:2**-4895/,(+055878:=CHHD>51029;?>;768;DR[^_ZTMB><==<=70(" %&+/54641.+&%'-07:984..3=KU_aYI=/%"%',022.+('((&$#  #$%'(),./46540+(%#%',05;;;72-($$#! #$(.030,)#"$"#""%&'()($$*-21//-*##$" $'&%&).242,%$%+59;70*&#$)*+)'%"#$ !(,./)# &-/.(#'(%!(/6880(! #! #+489:4,&!!"! !"%'())("   !!"####"!!   " !""#%%##$#"! !! !!##%%$## " "%'*),-.-)()'%%)),0238AB<1)'(/8<<:2--17:<;:77:CIJG@90-.16996338>HV[aa[NF===@EEF@6.$ ! $+-/02232.*&""&*389<5214=GQXWOC6(!%(0552/,*)*+)(% "%(+,..133632//*'&$"&)15:>;71+%"! !!#&()+*+*'&"#&(+(&!%*043440*$! # !&(+-26=?@;5+(&*28;=92+,*,..*('$""!"',-+%! %))'"(.1,$&.352-'%'(&!"*15885-'! !!##" #&$$"   ! !!  ###!!!!!$#!""%%)*/0-.-)%"!'(.3578899<@BFFA=2+&',8@EJE<6559>@<3)$&*4>FB<9309=AC=:75:CJRLE=3.+.2543205?JY_a`XLC:;=CJMNH<6*$%&'-00/0000.+(" $,17:87217?KQPH=/%$,2740.*)(..-+&"!"%+0268;:941.+***()%&)-38;85/%  $')++()(%$" ")*)'""'-59::91,&"!!"!"$$$"$'+.39?FJKE9/'#(/7<<<72/-.0/))'%#"##%',+(""&&#$.53.%%,041+%'-1/,&$-14785.& $&')(%#   !!""""  ###%$&(*,/./.,*$ #*.4447432238<>>;4.*+-36;;92/27=>=71)%(.;FMHA:9;?FIF@7548GPXUNE80--114014:CO\debVI>95;GMPVMD<4+),//10-,,,.,*$#+26642/38AFGC:,&" $-492.+&'(+,/+)$! "&*38=@BA=8.*)*.01/+'+-/8761*""(,//,+)&"!"! "(,)("!&,4:?>>92.(""&((*)*)'(""(*18@HLONH8,%"&-5<>;730..,+)%%%"%##!%&+*&  %# )496/&$,120+!&.4952("$,17:981' "&+/211/,($!   ! !  !"#&(*,-.11/..(&"$*256651,*(*158<951.-.020.+)-16=?;5-(%,5@JQMFB?AGKKF>611JV_ge_RE6216>IPTOH?950144/.+)*()*)$$/232.//47??:6/'"$*0331,%$!%+-.0+%"$#&+08?DFD<80''*19:62+((+030,%%-0362.)%""%&)*'$"$)+.*# ""%*2:@BC?:4.(" #(-//.---,*)# &+09CFMNHA4'$+3<>;53.*)'&$"!#&&&%""%&('" $# +5<8.%&)00+'! *36982+ $-49<;71*"!(069:<973/+($!     "$#'*+/1/10.-)%"")036763,'# "'-38986621/.+(%$',4:;72+&&031145768BKTadaWH=/*,/9EKOLGB>;5420.)''%'+)($")0//,*)+19:73.*&&+-//,& !)-./,)%$#$(06>GIH?6.&(09BC@8.'$%),+' #*05671.*&  $&)-0-*&"!&*,,("$""#'*/7>CEC@<5.($  !!&*/0.../0/1/)$$+/9@CFH?6+!"+29;92.*&%" "'&%#$%$%%#!$%!"-384.%%)*,*$ "&/6:870* !&189==93-$"(/7@ABC@>855/+)%"      !#%%'+-/100/.+(!#(/268860)$  "(/5;=<;974/*%%##)-453,)%)3=GPNGF?>?EHF>0,.9KatviVF;43888:>ENX[^XM>0*&(+5:BFED@>;63.,*$$%$(+''$ #(-+)%%%&*15620/+))+--("#*+-.+*&"!%-4>FJJ@2*&*5ALMF=1' %&%#&,15334,'% !'.0020.)%""$)++)$ "$#%%&.28@DEB<93,($"""" #&(++(*)+05775.&$!!'-18==>;2)!*1784/*&!!$%$$$#%$#" &)*'"#+03/(# !$)*&!"*/4771*$"'08@AABAA=>943.)&   "$!"%###$&(++-.//,,($"  !)+/246871.(# '.6<>@CA>82+&"""%+.-,*(&,5@HKIEB<9:>?<4,).;TlqXI=647:7<>FNSXRI>6+$%(,128:;;;=:50,'%"$'))))($###$&(*(&" "#'-03420,,++,+)$!%+///,&$!#(3=FIH?2+',9IQSNC7'  #(,01.-.*&" %)-/232-+&'&'*)%#!%&%&$#&),3;?CBB=40*&$#$$%"&" !#%$##$*3:@C@:2,*').26644.&%,466/)' !#$#####!"*23,($"$),-+$ $" !%$! #'.221+% "&/7;BB>90'!&+25;;<@@?>=<9731*&!  #$'%$$%$%###&()++,,,+'%%$!"&(+.2854562/+'" %.4;AEGGC=92*&$##(()'%$&.5@DHE@:657555.))2D\yoXD=85779<>CJNOI?4.)')-/0//246:;;5/(##&)-21.+($%(*,,.,(% "&,.3411.-+,-,,)% #).11/*%!"(/=CFF<0+(0>JVXPG7)" !%*,+))'(*(#  !'+020/-+*)&(%$#!%&('&%""'+/4<=??;70+'%#"$%&')&  (4>JOLHB93--0210-,%"*.342,# !##!#! %29740)%#&'''# #%()"!"  %),.+)% !&-7=?A@80' !$',/12554677989;61-'!    !$))*(&&$##"!$&'()')**(&%'')0024666431.+&! &-4;ACGEC@=71+'%%%#"""%*/8=BB?94.,,*++''*6Ke}jUC:315669?AIIG<3,%%(06641-,.49;<5/*&'-38<92*(%%*,.1.)%"!%&-0221/.,.1231.'#")/454-'##)/>FJG:1+)0>LTVRI8-'#"$&&$"!!$(&'%#$+-,,,+)&(&%%#$&')**)&#"$(*259?=:82.($#$$&*+++)'&"(4DRY[WMB:63222/+% (/334/' !! #/7@=:4*&#$#"!!!#',-+&  ! !"#&)))(% !%,3:?A=6.(!"#%%&((&'*-.156743.)%   "&*+*('$" ! "#"#$&&''&()*-1357752/-+&%"  #(,3:=ACCBA>72/)%%#"! !(-3;?B@:6/)'%%#"$%+8Nc{s_N>60/0346:>CD@5-&"'09>@;3,)+08<;:41-4:BIGC:.($%)-/0+$!"#'++-.0-.046==:7/'!!'03420($%+4=HKH<3)',:JPONF91+($" !#&)+(##$%(((%%&&$''(,.,.-(%##&*.29::952-(%"#$),1410.,&!*8HU[^]QLB943/.+(##(06850*" #-8?FB<2)$! !"!$)-22/(! "###"%%&'))$$"!##+179:74,% #&*.//.-(%       #$')'&#  "$%%()-/0543640)&&! !%*/48:?@=9:72/.*%"!!!#).69<@=61)## "$-9K_qz{rcSB70-..0237;>?90'#"*5@GE<6-(-1;AAA:9;DLQXTM>/% $%),*' !""&(')+,-.2:><94.($$%*28;:851,'$# !#'.368973.)#",8BLNQMG=62.,+&$!!"!&,39=>;5.%" #%+08@DD>4+!!$')-37894,& "&(++++,,++*&"  """&&+./.+&" "       $&*../300.,*&%%%%$$#'))+.1112..,)*)()&$! #(078;=85-( !$(08BJOPKD=850--+--06;>?;6,'&-5?FE=2..0;FNQSQRVZ_deYI=/& !!#'''$$#$%%),09AFMPLD:0% "&+11.+'%+2=GKLD8/+*-14531248=<;5+# (.58881.,,))'  #&+138=DEEB=6/(#%*18=;;83.*% "(.067652,)$!"%-27=A@>80*'%###! !!#'/69==:2*$ ""! "$'*04=BBA6-$ &)),158885-'$!%*././.-.,,($"""#%')()&"     !$+.10101+*++*())+.,-.,-/00/++%%#"#$$#!"(.268:50-%!"'+059:=;9645443.+,.38@CA;2*'+3:=;52..6DNVWYZY\]_b]SB7/&""!"&++**&$##$$(+0:@HMOLA7+#%(-,*)&&+1:CIFC:/,((*))()-2=>BC=4+"!(,49993.,+++*&" #&,29?DKLJD>5/)')/8???<;1,'"#)-02/,*%#"!!!#$""&*+.110-'##'*259830($" #&&&&#!""$'+04:?@9/( %(--.148852*%""',000/-,,+*&! !!$%$%#     #&,+/3312+,-.0/13443243120,)'#  #! !%,/5560-)!"$&((**+/023246643-+),27AGH@80++-0432.04=MW_bb]\Y[XUPD=4/,++,+%! $*1432-)'$##&)-29DKNKG<1'$*+-*'&$*/2;BDA;30))&"!"#).9@HJC>5+%!"$(-27::51-)('*)$!#)-3=CHNOLD<5...08>CC>:70+' #&()'$  #&'&&$"#%&)(%%!!%*/1/,*%$""&)*,+)$ !!!##$&*.58971*#&+13/005431+&! #&+//.+((&&&#"""!       $(*02300/,./149899865531/,)$  "!"#*,122.+'!#%')+)'$&')-.237742-+(+07CLHF@7,*+,-./.54-'&)-17554.,)%&&&%"%*04>EGLMF@80-,1:@BE?=94.*&!!" "()*,'##!""##!"%((%&""%'*+0/-*%"!#%%$$##&&+/011+%  %/36631///0-(#!"'(,('&"!"#"! !        !&+.10/12,,-0479;<;8644/-)'#!!""#((-..+(&! %(-.-+($%&()*/45631-*&*.7BKKKF;2-)+*--1:COY_djd[RIB>84/25=GKLJHB>=AGKNID:5/-,)('*,2=EGHC;/$ %*-.-+***)),.0459863-& #,4?HMMKB=63,*-.0/.+(&$#$$$"#*-3;@DEFA81,-09BFHF@94/-*&$&+./-)%! !"##"  #%'*-0.-*# $&))'%"! "&()+(%" #,59884.*()(&$$'&$"!!!!"         %,..,--+**./25788963/-)(#! "!"#&(,,*)($#" !"'-0210+&&$$&'*.2310,*')/6=IPNG@82,-+-16=FRYaec\VK?90+**3=JVZ\]WRTRQVXYNE=40.,,)&(+29AGE>6-$"&-335420.,-+,+,.167:60*""*440.,*(&(%"""#&#" $'*07:>A?92.))1HMMKB=92//038><>;52.,2;=;:2& !&-15>6-'#)0433/'#"'++*'" &158952*#!#!!!%-4<>=;85/+&#        !"  !$*,-/..*$!!#%#%$$#%(*,+))(&&&%(+,++'$! '-17<=>::779=DGIIIB@<6410.057;>>BA=930,-38CO[dffc_]]_[ZTH90)(),++)&$(*18:872-,.2;FQZ\WRMGFHKMIC92027>@>4+$!"&-0378:;?@<93.&!#!!$&&$),/1-'!$2?JMH@1+*)/11.'  !'.6;?CA<4*"!(05640'"#')(&$ "(/2561/(""####!-9BHLKEF?91,&"         """!#%)+-,)(&$"#&&&&&$%''-.,*))&$$#"#### $(08=CEF@=<<;=AFHFGDA?:4/.)'),/13767544137=DMUVYXURTTRKKC9/&#$')-+(&"#',36631/.27AMX_b]VPQMPX[ZPB8327=B>7/'#$(.24333146861,)!  $$%&'*/42+""2ACBBBA?:62+(#""#')-247545679>DGGEEAACC@>;2)! $*.--)# ""'*./01/17:CMW_c^YRNPWaff\M@76=@CE?3*%',/451-*)+-134//+$!!#"! "$$&(19=<4+#!%/?@>:3.(#! $&*.02733344345443113122-&  &,451*%!&&),/0359?FOW\ZUMMPZfpnfVF>=AIJJC8.(&,2540,'#"%)-1112-)$" $((&!#%%$)/:CKKD9-(*2:DHB6)!!&(&"$(/6:>:4,$"%&()##(*-+(#!! %,046841,(%$#%$"".;FRYXXRJD?:4/+'&&           #()(&" "%$""%&$$&&)+*.1012445524310/+)(&''''&" $&,279=??=:9:868:99<;;??=:30*%%""#$(,/0020/-*)'&&$&'%(''$!!*1694,&  $&)-/266=AKOPMHGNYdmpm^MFFJTXUL=/((,4:96.'" $(-47897.+#$*0/,&" $'''.8BP][SG;316=FHB7+#!!# $)/5:83-%"##" !&*/10,&   " !  $+049<962,(&#"""$-7CNQTPJE?;73/+*(%         #$'''" %&(+)('))**-.0354556669;=;<;831)(&$&)*))%"&+,//3678630/02226745898:854.)*'#%%)*,-,--+&#"  '269<7.(!#')-/.-/49?B<=?DQalokaVOMS\`\TE6+)/5AED<60%  &+0562,($#$'**,4AN\fibWG95FLOIC;2,(&(.04::4/**)+,--/7ASekqk]PB>?DIFC8.% "*/6<;6-$ $*0450)& "%%! "&,-0220.+++,15:BIIIG?80*%$(*,-*&#" !%&'()+**,-++)''(++/.+-../446500.-*+)((*+*()''%&%$$" !(18881*&!  "%'&""')+,5AP]cc^ZYY`hjhXG5(&,8DLJA:.&""'6@JSVTPJ@9300139;630+,++-.147BN^kkg]PHA@CHF@71( $+28:=5-"%*1440+$!#$%##).38:9:882.2699:;82+'#)/211,*)(&%()**'%"         !%$!!%,4:=:870.,,0379;>?>;9659>BHJNOMJB82,*()*)%#"# "#$&'%&')').////,)((*+,)'**,.110./,+****+--,/.-112431-)&! !'1665/+$  ##"!"$#$# !&+3:HVZ\\WX[aiheWA1('-7EKLF@4+& '0=JVZ][TLC<:967:7842/.-.-.037?IQ[^[RJE@>AAA?50($#!!" !&,29;:2*"  %/554/'##"$%$ %*-4:<<@@=965665662-'!"%'*+''%!"$#&),+)'#        #$&$!%)16;:9730-*(,0469<=:86427:?ILPWWVME<60*'&&! "#&%%&%$(+*-169853.*''%'%&)(**,-)'())*+./2312458<@DHD@;4-&"!%)/463/)  !$)('(&""$ $)0:DNTSTTTWYbcZN:/)(0;FJKE<9.&! &-9EQ[`^VSLC?:852331/-,,,.+-.28=FJLOH@=<;9;:50))&#'%$ "%,2693.(! #$$!#-3541)#  "%$  "(+/7:;@@<;954222/*'! !"&&#$! #$&),,-*%!      !!   "$(('&" &)-4778620+%&&&*-/4784430115:CKRY]_XQH?6.($! #$')''%%'(*27;=A@=83+'$!"#%$((((&##$%'-246889::>BJTZ\YTH?2)# !$+04881/) #)/2/-(&$% "%,07>FKLJKLOQNPH?3**.6@FJJC94-'""#+5>GSZZWQKD=851,..+)'&()))),///4679766431/..+''(%&'%#!%*//0.)%"*/0.*##&*.22/)! !!! "%'*.27898874/-+,+'#!"!!"!!!!"'+*---)#     !!"!  "%'+,*&## $'(-1231/+'$!! "%%(,01210./15;?HT\bfa]UK>3+% "(*++''&%%(-3:ADHGA<5,&" !#%))'%#! #&)159==BABFHO[dopoeSC8,# !$(-26;=;5/'$-39:40,(%$  "'*0158?ABAB==@@=84/,-4=DJHC;3,)#""#%+4@LPSPIH@82//**+('%$$$$%''((%''&(+*+,+)'%$#$#$%%'&$ "&)*++&$!#/MQRLB71,+(*+-/0/01/.--,*('$"!!#%*2:DKPH>5)# ##"! #(.48873/)%"!!!!"! "%$#  !" !"!!#"!""#$'('&%!!!$$$,@TbhfYF;0*'$" !(,/32/+&! "$$'*'&$#! ""  !"%''$"        "#"!!!!!    !###%%)+*)(&%"" "'*,/020,)(+/6DQ[hlhcXOH>;=AGLLHB80+%$''*//25651-'!(/253./-/4:=@EIHIHDCAFUi~|cM8*"#$$&*09CKOQNKB8-#'4CV``\PG<2.,../3611/+'&%%%!  $-7@HJPH=.! $%$ !%*.11.(#  "$$%! "! "%"!$%(().-*'$ "$%/E\jrobL;0%# "*158861*& $%*-**'$#""        !!!#!! !!!     "$$$%&&''(%#! '+/26620.(%%(/:IUZbc\SMGEGJPXZYPF<2-)(++.-++,,*(& #,/4434548AAEFCB?A?5-*.?XszcH0%"%(()+.6?GNMHC;6/&$4G]rywn_NB76225530+&! !%+06=?DEA91&$)*'&"!%&*.+)# $%&(%##""%('&&# !%%((%"""""&*/59>@@90)" !! (;QaidWF4& #'-0588540)$#'*-*)%#        !! !$'*16=<;;81*&  )2;DFFEEBEIQ^ejd_XH:313:>><3*# !#%(/216;<@AAAA=;;:3-&!&5Qow_C.%#$**(),39?FE?;41*$" %2F]vzeUG;63312.,(#!!!&(.565;89953-#%)./-**+--1.)# #&'''%"!"!%*+(&$ #(,.-*&$""$(-5>FJJH<4+!!"! $1COUUG9,  !$(*,13331.($!$(*+*)#!!"#"#          """#&)-17;5/'##)168;9971/-(% #/B]r|k\G950//.*'"!!$&*.289851/,)*'$ '-25233./11.("#%))'%"#'*,)%" $+232.+%"$$)29FRWWNA7,!%%$'2>E@:2'  ##" ! #&+-131.-)$# !&)*(&# #'*,,+*)$    !""%&(,.048;<=961+% $)../348??<622353/($#-A\q}|p\I;6<@A<6/*-3:94/(!!"(6J_ntpdUE:3-*'%" "'),023.)"!',--*'#(-3961,(&!!!&')+.,(" )0465.,.14;4,*&"! !!%),-,& &-,*% !',251/,'#"%,5DS\aZL<) (112+$"(-32/0./+&$!!!#"&&#! !!#$'&(%$#$#"!!!(,472+'%%#%#$%$&%"%$! !"&,3;><7401131,'&,8L]ggd\TSV\]UJ>0*,37;70("-;74559@??92)#!$&*,($  (/.)#$+33331*'#!'1>JTWQI9*%-4782&"*08:986/*$  !#"!!!! "#$$# %&&&%""!#!! ")+28?DCFE><3.(      !'&'(($$#$####"!  !#'**027988;;=>?=888=@FIHB<40-,-,.+(&$$%')+*(%$$"(/6;:83/-,,,)&%)1AOY``_^aemlaQ>0&'.5971'"*5AB=86:;?==7/(!"&(&"$*.,' %,37862.+&"&-5BKMJC5)!+27;:3) $.4;6.(!!$#$%! $)*((%$"#"""  ! "%# %(+/8;@??=660*&        &*-+)-(&$# !#'*-/56;=<9:;6::<<9;<;;:6110026776/)&""%'-010,($!%*04761+('&'% "%,7CNW\`gpy{nW=,""(2760& #%(.535000479;63/&#$##!!#$,2441-("%,4:?A>;9::==98/' #""!!#'-.+%&-7;<<72,%#&(-7?BA92(&/68<;3*#&.6@C@;4,$ #%&# ',//-,%"! %(((%""')-252342-+)&"!          !&)+//-*)%#  $%(,03559;=988768988:552,*().2;CFA=5,%!#$)17:95-&$"&.340-'$ &/7COVbp{_D,%+441*$#!###"$'*,*(&$(18>C@91,'&''#%+.3;><60)##).5;=:875889;92.'  !!!!#&*,-' (07<><74,($#%*04784.'!(17;=<4)#!&-6?B>:3)""#! $,3885.)(%*-.,)# $&)+*()&$$#" !             $),0..,*)%  "#(-,00079;;79686886941-)$##&09DLQOF8.% "%-8?CB=5+$#%*./,)$ '/;HSawlL1  *221,()'&&$#$%&'&"! %/8CGD:5.*)))*+-4<;4-&  "&)+,+' +0889540*'%#&(-..0.)$ "+37;960*! $+3;?<6/& !"! !(1<><90)$"&.12.'  !$#" !         !&+*,,+))&"  !!!#"%)+,-025999742235211-*%"!!*6BNWZUH=/% !)4>DHF@91'$%')*($$+4>L_suT7& "*/12.*,**'$!!"&&"!&.8ACA:60./--//29CHKHB9,"'--/-.--3:=EHHE>-$""##%'+/.)%!*04650-*&!""#$'()**($ #*05651)%$*.3741*#  #-6AC>91'$*010,'! !         !"&)(%''$$# "!"$  !#%&(*-254531/.-,...+)$!#-9ET[\VI5+ !'())**+0:DOXWTL9,"&#'&$" %(-/-(% '*-/,)%"! !""$%'$"&+//-+% !$&*,/0+&#! %/8AC>6/"  #(,/.+%       !####$"""!! !&'&&#  !#*,//11-+('(*++,+('%'08/*('&$!#'*+(%"#%'/:Hbw{aE0)'&*-//-/0.(# $+-/+&&$*/3884579?@>:782(!#&'('&(-9DQ_b]Q@0! #&*++(&! &*-/,(%  #%'*'(#!#"# %()$$" !"$#%$())'%%" !!  !%/7>@:2*!#'&&'%$!#'(''"         !!$')((# %),.-*(%$!#&()-/-)**-:FPUTK?4+&&)09AEDCC?60.*)&$!'.22.)%#!#)1><7.*" "&)''&'-6DT`ebUC3# %(+,.+)% &*-.,(&"!#%('('"""!#! $$%&%"!!"#&%%$##! "%"!#,59:4+$#,0010,)#!$%$!        !$)+-+##(+(&"! %+/11.-..5AFHKC:/)%&*28>AA><840,*(%#$-4860*%  #&1?PcpxvhR?.%!!$$"$((++% #+38:92)&#$'-07@IRYXUMC=6789951,%"##"#%'%%%&'(**)),4?NZ^^SB." %&)./.+' #(**)&% """"$'',*()'%" !%(**'" "%&"   #%$%!")244.%$+25:880*%"           "&*,-*! $%# %*.241,)).7:==;4+&%&(055:96651--((&!#.576/)# &/:IY_\UC3(!%'# #+39?:2*#".3><80)$!"$$        $),,)& !!!#)0530*%#'+1651,(%#$%*,,00//-,*'((%!#-230+$#)1=FF=2( &,39;81' $/;EQZfld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hh]PA5+"'06BBACEA?82.*'%#!!""&&+/--(#!! !"$""%&*17>EIKLIB:4/*%%#%&.6>CC?6+ "%&(**&# #'()&'%%#!!!"!    !$',10.)&""#%%#" !! &)--&"))/1007ADKJD=4/))(&&%',59:;4/& &+36852/./20-,*##,4:94(!!(*'!!(3CXdmqi\L@2*$ (0;CC?9-&# !!#)06?IQVZXQF8+! "-7;ABEFGEFCA?9641.-+*%$$%''(,+(%# ""$$"$$).18>EGLIDC;3.)%"!!&/8?EEC8,"%&'&$# $&(((%"#" !! "!       "(*+0221+& !##%$#" !&%%"%)-+'! #)-11016=@GHE?82-,*&$" %,-00-*$ #.6?BA=63-,,+*&%  &/8BHI@5)!!'*)#! &3AUiotqiVF:0'##(2AIHGA4+%##(.6BKSY\VPC2&  %/7>CKOLPOIEC?832302230,+'#$%$%&"!! "#%$$#$'+/2:=@B@?<73+)%"!&.7>DCA8."#$#$ "%&&%$! #$$((%#     !'*/1032/)"##"""#" !!"!! #'+*(# "&))&##%)/120/14;ACC?91/*'$ #''%"!)5@JNMF;3+*+))&%%#%*6EOSVNA1*&'(-,)##.@Qbrutk\O>2)##)4@JROG=3+$  &-2;FOTTPI@;4, !"!! !"#"! #&(+0.-*%        %)+01/10+&! ######""#%#''$%#"(+./,&$ !$'*-,*'#!%$!! #'))$ !"#$'*.00-+*-4:>?>:2-)# "  !!-2+)*)*('&%)/;ISYZTJ=2--.1/.'$ !+:O_jqph\K>0' ")7CNWXQG<2*$!!).3>EJJG?4+!!'-6?ELPRWTTNG=71015?DDGC<6,%! !###  !$&*+,./111/+& ")/354/&!"!  !"'),1333.)$ !         #(,.-,,+*'#!##$&#$$%')+*+('%"!',01/-+))*/69<>=5/'! %),,'# &,+& #'*+&!!!"$%&*,.-,(%$)16?<5.' &*06;@EHQUYURJ<6347@LSVVQH;1' #&(+0220,*&# !%*-+&" ! ! !!$(+,1641.*&"!$$%$!!       "&*..,*((%" ""$#%%%'))+../+*% "*.010//16;ELNRNIB5)"$+065/(!#(035.& %-//-(&$$$&'***,0/-'$""$+28?<60' $%%$$$#!*:Obfa]K;/'%')*)(%$'.4@GPTQI@:300..-'! )6EW`ceZNA2'".?PZcebYNA4-%! %*/441.,(%(-.1568=AJQVUPKA879?MZdke^SB4* #(,02542/+'! #$!  !#$$! #$%'',001//-&#"%(&#%!      !#')-/,'#" !#!##"&%&))/012-'"#(-02238>EOXadc\SF7)!*3=@=8,%%'/9:84+"")4676/+*(*-3/0001.+&$" $+28:83,$#&),-*))'%"!.BTglgYG5($""&*'&#$%).562,+)'%" )9JT_dZPD5)$3CS`ilf_TI<2)#"$())(),/146430/27AMSTRKD<>CM]juxsgZM:-%!#%%&"$+/48<<<7/,$!%'+*%!  !###&%(++.--+'# #%%$&%$$$"    #&*+-.)#! !""$%(*-111-&$),047:AMS\lsqmfWH5& -:DHD=0*)+5=DC;1'"%*5>@@>942156676420-+(" !!%/555/(  (.3320./,($!%6J[fldS=-!!)*'&$$$)+059:<971+'##"#/>JSZ\OD9+"*7IYhmkc^SE=1)&! #&*3:=B?74-+-21.-.2450(#"$%#%&)029BGIHC=5/($!" !%*36661*#"#### !#$$#$"!       "&)*(%! !#%&'$"&,29@JR[entuqiWF7("1BKOG<.%$(1<@=50*.4BMUVUPHB?;==>>:40+*&#"#%''%!"+148531.+)'!->QbibT?)&-132+(%%))),---,+&#!,9DMRPI>4&(5FU]^^^YK@70*'%# #+8DMONG<3,+09AEFDA=>DThxq^K;2/025960*#!%)))**.39ADHJHF?5/)# "$&$  %)068=;60) !!"!      !%&&$" ! !(+3;ALS]dhiff[M>0#&1>HHC8(!#,6:641/6AMZ``[TKDA??;=;3.+'&%" "$*1531/,)(%" -?Sde]M5$ -8>?<2+)'+),,+)+*&$!&0:BIMH@7+ .>9557@PeuygSB4-,/3554/(  %)-..-.14=DHJIGC>4.) "&+,)$$'+068<;51+!       !"#',2:CIPX^]aZVNE7,!$.9?@;2$ ',13316>K^hjg_UIB?==<91/*&$!"!',-0.,*(&$$,=S_`SB/ '7EKHA7-&'(+*(&&''$% "+2=EGGB:/"'5BMUWUK?4,'###%'$$$ !"$!'2=DEA=6/0025544.+,2;J^jt}rhYH5+'&).12.)! &,11010027?BGJGD@94-'##)-0,)$!%),.37665.(!     #" "&+08>@FKNOOPOJA7.$!(3663,$%+-036=GYeoplbUIC?::92-*&###! #(*+.((&%&&",EFC?5*  ,8EOSQH?2)#!$&(((%! %&"#+37872/,-04220*'%%,5AN]ejgZK8-# #&',,)%"'.45520./16;ADGGA>70+'%!$)042.'!$(+,/120.)"     $''$# $&,059<>ACFLKID>5)"$)/0.)$%*,142' $')+'"! !%&"$(,***().022/-&"!#(1:BNWYSJ?0&!%''%$  #*0478630++/8;?ADD>:94-*'!#(055.($!"%&&)&)(%!       !$&,+('$ !$**-/038CGLPPH;0& &),,**%$').25:?IZdkoi]SD=8764/,)''+--./-('#! !#! # "!"#$$#&&*+,,(#"0;AA:.%"-AOY\TG6& "$$ $*2:@FKJE<3( )6BBD?3)! "&''('#  ! #'-6650*&#$$(/5;?DGD>6.%$%')%$$%&(/39=?=72/++/279>A@?=:91/)&#!&-52,+$ !"#"#"!         %').-+*%  " !"%)4@ISWVNA1'$*-331/.00279@ENY]cc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igima-1.1.1/sigima/data/tests/laser_beam/000077500000000000000000000000001514013333200203345ustar00rootroot00000000000000Sigima-1.1.1/sigima/data/tests/laser_beam/TEM00_z_13.jpg000066400000000000000000001572071514013333200224730ustar00rootroot00000000000000JFIFC    $.' ",#(7),01444'9=82<.342 @ }!1AQa"q2#BR$3br %&'()*456789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz?IEvRw1PhҊCɠERRGt43E裥-{њN(H84QE-'z(hQ;QIKI`xGQ@GzZOE)Q!E/AIGJ\zti)sIGfA;QFhRPiEQEJ:(KRpizQEP:GJ(-%QA-'gSM%(*(F9ތRRRG44(KGQQԝE%(b@b(4 ^zA(JwIۥ/Iӵ-8uQEvFsڊ;ў((ך3IJ);Ki? Z(4Q1EhPE%-QZ(Eh::~41=84{Q;4GJ3)- QFqGz:QJ9QgOŽOŽi3@KڌQ(z;Rwځgڔ`R ))x8R)AҌsғIޗv N8RQr)((њ)(>ԣhARwE<hъ4 ZCG%-'zZ;RuRt:@ZNE/J(QKF(Rc=ǽQ4QIKEr :֔Rw:P~u'z0hvPh4Q:P:Jx4P(d:(F){RQGJ(4H3ޗ(Rb`Ps@I^)p3E'4Q(J=1&)h9u94w%ii ~4QF(QEPh=)i)yJJ1i;Q}(E ;ގE4Q\sIAF( ԼސyG&I(4(EZ PhRAu4(i({ 1J=i){}h8bIE/&h&8Q(uRRrE/8Z;yH3KG'J1(KhzQA9KA֒qF8E =hZJ\fQޓ4KF(Q1G9Q:1ZN(f;Q@J9QցI@QIEJ8z9fւ QQ;E'zSғEu4Rw*Z=1F(KEFhGցEEGA@EPEQG/wARE'@(SAR`PhK;P:zQGRcSG^h4QZ:ci-\RQ҃ץu#^;Q֌sGnG4 LIޗQփғh)s^ԟZp A⏥/Z)3AŒ (<Ҟi(QGnԝGzZJ1A֗#H:ќh4vq@4 ZNҊ uޗAGj(⒔P=i斊J\ҐS/z(QGtJ)Ev8 4R JQGQGJ(G)Hs(ӊ? Z&yɣ84vvu/jJZ3/I@⓽(E &It4RJ^zQҊ;g?QF9F);tLޗ4b֗4/SIޏ(Ji)M 4PyQ:tԇ)i8Q}h%.9/AIڊ^`P)qG4 :);:RF=)q7F8>)("'z\v)4QJ)94tv{tGjhNi@(4b84qKޒ P> fJ1I)q֖}EQGz?(@sҊ^&i})vE~4~4bǚ(H 4QڎhKڒ'zERIҚ;Rt/SFhF(҃Ҋ;KIGnPM-%GjN4i1)tKHNI& j_bQ(F(i(iIZ^◵ԇPfKIGZ1Gz:wϭQ;/@ 4cP)(FyRsKҎw@E'z^u֗ҌR`◵%NphKRfIޔQGj;QIJ4QE(h4{Rf hԔ=<ҜvKGzJ3Fsڌ{REj3E.yғQҌMgj3Iߚ1Ew))sFqE%: >RvQJQҊ3E('.i? \QI> (΁GZ;QGҗ(hh4 ?))siJ(>ihҊ:s@(E .h4sQIEO4t bih4Q(A9Goz3_ƐP(h)=s%)IFE/'N(P:Q֊Aҏ(4sIޗJ^fI'z\t8QJ1LQd֓/9uցIKހh=)J(=)9/j4`zRfu8ǽS '4Q:E 3)H⒖uQIQF9:Q@:Rh(IGE/Gz)iZCEJ)OJ@{@ގhh>`RvF(Ҋ:QKޓҀ(ǥQGEKҌ m; bq֓4AQ֐QP(G=(Qފ: ) /QGz1JE'J_ƓKEb!JzRRG);wJZ3IKH2sF)hrh<Z:);vJ:Rғ.(QJ8QGj;;ERu(G_'zZ1KZ(RR(J(4wE'/j>Q(vGzQ֒ӥ /z&OJ(9ǵ/l(4E΃E;QR;4RQqKFi3){Rt4hIށZ)2(=8@%(4Q%-%QҀ 製ڊ((ҁGj1E~ ZNf:Ҏ~fOJ^GjNGZRyRQKރ(E; 3I-b4Gj}^fʌQړ(})KhEPz@E4RF))hRR撗Q(Q)P84cҞ);ўxsI^c'rii9ڌqE3@=GjCE:t/jJ=Aj (4Fhg=)I=Ҏh撁FrzRGj?4нiMJOҔ()(NԽ{Pz;IE-%.y4(ϭ(J/8Qڒ3KފJPhE'ZB)M'CKEJOz) 1'CN({P4GJ:Ҋ(ҏz>v4bhh4h@GFqGZ(i9h4P:hRs@RJNԼ4R`E(RsԹ9QA\qIKHGZ(:sGZ %(!4sڃ(@4Q:xHhERނ9=:7/Q&){fRuqGjAfjQ׵LfPx 9hFi9QG"F8PzbP(F(!ihssER :F(@>sF8IE'GzQh<ғ֎iqALJ8Rbފ1F8{֎褥4RRh=)1.: :vQM)GzZ8q%/zJ;QEZ(JNbP((KCGc4Z)OJފNRF(!u#Ҋ(4Q(/Is@>tKhQ@uh))Gj0)1ފ1KQP:F8h=h(`KI)(QɠⓊZCJRR 8hH9P)i;EQ@A84:QzJ=sA RځӭQފ)8)48(EΎ'4Z_&h]fGJ((- 9 OƌKAi3Kތ4 u-4KQj)3J\QE J (ӺI֔Rw$b3J4RJ9Rq\Fh4@Gz: E4sEfG֎g3ږ9c֌␞iA89(P=@P4FE QGJ(f4fLtRg;QGZCF}t"fHO->v%gJZ(E;Q(FhG{ѓJO4Q&h;RLsF}4g(21HO.sIޖ9"4FhGNR=hR ъZJQM4ii){҃()(񢎇oN{Ҍh(ϭuvKAގ}(GҎRi){ސQ9%/PE PAQҎ3E :4b1E#ڏz;Q8H(Pi'JS(((:Rcڃc֗ 7-fGt%Pz@F0x(QE'ҖE裷Z &: QGҊ(sA1IE/JJ֊J)NqIڔ ZN F9PGz(QڏEE3LdCZNJZ?;яzKڀ8Ғ^ԂsF9Ԡz(F(QKIKޒ N( QE'KEњ;RZZAKړ񥤢-c1E QKJJ^d 3A4~ROΗ(KA@4QGGz1IKڊ Pz=i:ю(Z9%;C֊=H){ޓ{QHiiGjLҎփGn}iO'J:sA4QIKړڌA x{QFi3ER4;R{qFzCJ(hi u4QzCK(r  w4sFh(izRi){g((G&isINϵ'CҖfJ\QRRQqKF(4MsKIQ@}K;ҐZN(.yA'QIޗK(GsF9RRQLҗ@ȢL-%Z^4z掴;EOZ?'h'R):j ۥ(@AKRb=:ӥ.i(PZNԤI@b9ғ>Rh֓ފZNhPhuGz(Q֊J(4gAGcIJ:sGZ;thE'ҔhNrEf};RQsKZOj:ҚJZ(Ҋ;Q(=8RwE"'AK(F(€94F8J;qFht4s(4 z=hi;R3ARR{sE@4( J^P)hԘ/=/zJZLޔSA斊1GQE/bsF}QҊb9撊;Q(ϵ(֗JA֔u׊ `;bAG4whuPF(QGjj(-hQڒ(tvQւ1F8Q1E=xEM((Iҗ!)hZ^wJhAKRRK=Qފ0qKRw);Q@;GcEE;ZN 1ڗRQߚ4ԝ~((!{~w%Z^pE((EvGj:ޗ!R}h<яZ^(Ҋ)GZ1&: ;ގsG!F(ǭ%9掴J1Ӛ3Kڒi)zI@PGjN :Ҋ8Gz(i(;QJP:z(bN P)i;RF=Gj;ъ)hE 1QEQF(KHQK!@F(ǥ R(h C֎ԽsN(E.9QF3G@h<>cQ8#CAF3Gz1F( ("\FP(zQhQJ6PG4bq)ȥ&)qIh# ^ԞQ}1֔(g QGz;w斃Iڎuc('z1KڌQ4c))hsF(ԘIRj/4QKI(Q\hvbsKIZB(s;ڀ>Z@)q))ԝhH:Җ:uz>RccJ;K֒RƒҀhGGj\ў(sKGu=i}(cP)}GdIL׭E}iG֐x4~4h֏lRFE'KސR(h=hCA4QAϵ;&h掔v4 vNvqFy(HhPh&}izQ֐}hh(=); 3)ⓠgM&h(i2{QH(Q&0h(RfҒZ(E&h=4R((—'z1'zZBO=(PMQڊ 8IRR>v\fRR)1{b8=裸AƊZ3GQKP(cɠ{ti{QKF3IKފ:zRq@44/j)i1Px83^i֊Z) {:њ;iLi(ǽRR~ -@Qڗ)sIGjJR2:RI^t4Rڊ(GҖIڀ=i:-%4%EhRQ=hP(3EsIޖRPzP(F(E4}h4J:E'Z_jN4bfF;(&)(ZLRE~&}ih%:RR⎔usIފZ?Z:ҊNwQ)h'(ȣ4u4ffbAQEQFh4vqA(⎢f{Rc4%/Z8JQޒ^1ҐfSE%)қޗGlL}(ɠҜb4}(IE>:(挌P(pR{fҏz9ѓNQQ@gۚ33ސQF1AQGz)hhQ\A۵yPFi{RQF;vz1A/j(b)>3A(EZ;HF(ҖMQ׵R9:R:jBi{Q:P Jh4J;1FiZ:RF}4QҐih4 C@EE(4ҌKj)zњ)RR\tIց?/zLҌJ\sK@i;QzR4QGqKޒ)i▌~4fRF(ht-QqH3KIJ0E0h#ΌQ(4g)zF);hQt (?Z:юiO(ӭ/jJ8:CҖbsGLI8rOZR9ts@hҞyK;QGz^ wG4Z;)zQF("GjZ))xG4PyQRwOZ3F /jLP(H}i{94 13A()i;яJ(8~4GnsI߯Q߭@wqIJE%(I@=h){RQ@xh%-%/zh9=ERqZ(=hE-QKIҞgEj94QޔLҎAP(t;tGJ;E-%hKڎb g=i:QISZ( ڐQ(!(K6Ex"sGzSE%-E.'4tNHzӽ)(4-RR f)OZ11Gj(G|Qޔh-$R9:(h=(wIҔzh<ъ(4qߊ%(hzR)1/jZ)(9QF %(EP:i(旵E&1E) Lg֝Qii14u1AsKRbf;`4QGjZC֗R:4R(Z11E(hȠu08R)(Gb(==(Q֓h4^ԇK֏%(R 1J1%/ZNg4\ڌP:PGhph J^;CFh()i1Iڊ^(4uQڔRcJLdRE.xcNiiIvj? ((hs)zPyF('1GSGIR)zHG84.9~(Rъ1Q((J1Ҋ(4Ph9◥:RKGj(QF GJ=&y/A@@H4u4 ({QE(QLsGJJQH((E&3ɠhKQF9=x@JJP(h4 :Q1A!KQ;Rc1@AIKHh-'ZQGIE%)M;QKހ2h֌P(>f ){T1wKI@hӥ/8(/Z=(Z⏥$Q⓿4vKGZ:Q:ANI( :QQ(t)@H3K9hKQgҌqI\Lwh=z㸣9=(&(48'4KI)1ޗOE g7`qGA@cAցGZZNd֏Ž◵'j9;QR _“{uuv`IڔR'^)p)OQޗǥRGjZq@Q- IzPi%(usHM/4sGZ:ڊ?(KځEtgSJ\fƎ}hG8szEҒƌI=q@RZNg(i4{Qۊ;ўxJ:s_ŒGbFizPhwf())z>()94Fy: @ti?fցGCA$QiO%h4vg&hGjAK)9$ 2E$PhZPyi3Z3EڃI(QG֌Pi=Fi;(4GjJ;zEsj;RgQ֎FhRE!ii9gҔQb;ѓڗ=i;▐{K?1ERRsE91.=( NiE J0Mv-&)1K(E{((ǭɥǥv@RE'zR3KҐ RwiLQ=?ʔ~cҌbԧHhAbԽZ(iri1Ki;LsKZMsI\qIF{Q~hRQȥ4'&3GJ=F(IG'zwjNҏ))p@QE'zZN3Ip 袊1IK{R&F(E)ZJCK(qKGzB){ӱM(9^F)G'z^QKsI@= \fEh:(F;EhF}hAi:wF=1K@Ph/z)1J94iyRsP8JP;h49ъ>GzZ;RPsSGA֒(Q@tQKH:Fx)zRt@8斎gҎ⃜Gj)zLs. '-&:*J(u.xs&isϱ(EwHzъ^J;=s@qIJz)1-& )zuyqڌqI.y);LE/&Ni@}):GQ@tRIE-'J g\Q:ҎR(4gLsF (ȣ8N)1ȥ8w;1֏G^hF3@s9⓵(JB=HRsQH94NMuM/lP &9EzRg(4fQh9FO}izQQ֐h旞ԜўzvsQ4'~)sI(KIў(/>;g=sE4 ?q֔QqJZ=h#4t49AZZL=(4CҀhM)=44sIҎi'4挓FiE) fz9#"t9u4M9Fh='~M%>֗NiqAH:Qގi:()sE'zPyz:=hH3Fy' 4(J>%ҔRQڏƌRg=h4@99ҁFh:OE4uA1I֖/Ewj);E4i4:@襣ZLўhzQҐџh)iJQ@|gEњ)AQGqGC3ⓩ⑽(Ҏ(>RAHhړ'v8*3EIJ}Ag44(ۃL⌎ZR1ޓonԼJH:ҰSq1hSGz]i攟AIG֌u qE (ځE&M %-(gRz(֌GQH)OE!Gj:{ў(hϽ%<j(/&}(sޔ{P8t<ѓIJZ3E9=褠q.(E:(R'F)y)s ^ii84h\RtE- RQ@ɠp((hiphhJ_Zo"?::RtGZ1J9iE<ў(/z;Pнx1GR);׊0q@($RFޗm ^4ғtyF87$Q31QA8ZNsQh3K(gdӾ:ׯZ&9AҏjZp=;v(֜ ݓpϭ.)lb?4 HzRJ C` T1)2});("q@nRAA4g:Rd֒Z *z] .3<⟰ӭ&ܜRcJn.ڐO4¿Za ކPí3iXsN+3 M VSHqPbّ8#4.@^i.)3Jy4I;u4!2{DH0S:g|{F('4)z:QA֊@pzsF0sA'E&=#sIړ(4 Nsڔt()qAP袁Fy8GzڌQGRuJZ1ERNqExǥj(H){z) 4QhJ=i1S%Qi{RqIޖќF{њ3G\RLҞ9hQ(ȤiqE K֓1K2sGJJZJPhO4\(4t4KR{Qڔq@Kڎ(8@)>f4R`)9)NJi<Ҋw'zz\8zҨ^&pE&*Utri>GR894JkBw{Ll{R*yPm3QK8 5& P)elI!!zR 3ޣt♒Oڽi) 5:f(>@'zv)Ғ&y擽&03Gj4 jN((A9g4f4RvFp(RtQIE/JJ^sIҎތ:sKڎvZ>s;Hh(3Gl@4RfRt4Mfsڊ3(4'^QKEԽ1Gz^R`өqNPq@hNUR3 TzUUlqQ$#E1~4ebќrj>niΠPi!4F1F3ڂ8 Pq֐9Q/j;RfRc4QQ8G4gQi)i){RQE4`Pj^Ԕp1I֊03G4QF1Gz(GQGAE(zJSH(^)(4qڊ-!ҁE/ғE-:qEERGZ01f?旵'(GGz(Z(G?Fh4Qڗfwsҗ!𢏥探Q֜) G c8dRz^KQuh841T`R94GSM=h Jh ڌ֐Ɨ@4%);&)Zh(wg\ERRQis-!=A&Lњ=)GZ%J^vc)h;@@uQz1.(ޓhQގ(> ;? 1F)yJJ1KҎM.0(%IKE'iݩ;ҁF=i(J8K: QARiGGv@ڤ^j@) 57LӒ>sVq֐ǎAɭ`y =V*ROv2Hnvv)1Cyt𤣨QNRt4QI҂(ǥQRP>9M9(})h(y'J((RQE/jNF@ 3H3KIޓ{Q;RRqޖ=Ewu4gҊ:4h(I#@8;~vgw⌚ZL/J))hҎ⓽/8Q_zOE.yFzRcGJNKڎ(=(8):Rޗ ~)98\Ny~*tx'sRLIVcUbv4cXDZ>jQWcbTRy@v`R`tQK Jb9cJUd^2ֳ~*qU#c0Ȧ4A޲eRӊT4l)VO4dT@c&N:Qм 8LPi҃֓hhGJCJ84tE'Zb;rhwnqK\G|})((N(vA!QAEth/jAZ1@8ɠъ=hvڎt4w ZLQӽ (Tt/E%-IKG"%u Nt4i{Q֓;Pz@=@=h8xbRv4fRuޗ'E)Ggh})GriOhN֐=@J;7qTVT>i#" USn8F;ք1 ե W֧DiyLǵ.J(UjUsGM@ qQuyZ`qP]Gb= ˼F LT.SURcY*=*_L7jMSMMbwCҊJ\sQ3IJ9F(z(?J?3H8t-Q(i)sFhAJ &y惓ҌڌKE8F}(fG=hI\FizIFy 斃׊P):RRiGdR S^~ Zo| ^߽HG$槉pj\⧍9(J>=jtjd\fA5^H*eNjEqSHԫNjd?)J"W94z?jeɓSsϽ3]r*2j p+.U`rGZϹEn1f@ԁw֬S.qPRنQ 82Uq &:1J9HO^Gj3ҏ'^QAJxڊ\њNE) /i{gwQIKfҐZ) R8Rs(A(8t&h(Fh@Hx4($Ph\QFhKI(z4bSҒqGE.!{QӚ=REGJ:v1;>4QfzӺQKH~R14 qIKڗ8)⛎jAAZZziRsSӚTjcoSR Ocq;՘Ԓ8hC֮ĽJх09*XEVS*a_/NIzSZ PR{G< w&m'Y`ơHZrZ&sU5c^@ѹ;|Ae7zmMrУC He;f {r;QI4sK׭'A4(?'҃I(((Ai1R4w(4*:s&8=ihъNQE'/ҁҌP ԔPPi;ѓ1IEh)h4tP){R})i){zEZ=@QJS8Ph.)(AF=F(izq)Et>J)hqGzOŽq{QڔiM4{sK:Rv4 )i (ROQJS=*R&F \֟@rOW9Wޯ5r^A =jiTҬƙڬjeR*UUҔF ?^`ɦI4"xq֘b"| *Av}J k6c>Y\U9cTnQ}j¡83dRcޣcc4֣A!#/QI4\š}(QGAIڔdAF=}J3H)OOj);)p!QȤGZ;sFih4 GRRI: 'jZ=Iޓ9jZ>&9vJ);Kڒ/CA /`4fFJLsJ8NR)KڔipqOQPFMH*ejh<҂sUp u(֭D=+NҎcyԝhqJ=(=(I.0hJ;f֓u8ڊ;P(:QF(8)E&9hcqF)h8F;Q84w斓z\qE}hcRJi(ޔHG4b{Qڒ4◁GRvn)G>ts֌R4ր94UzԊ8掽)b5V#_njni@ɫV|Uq{tt'*&ӥY>v8ڧ*t(8a-:tՈR-4!sPN}'P&ǭ1xOڡ2MЂjQB%:y&Π ޱn~W$*Kqri:iyRSGjJ Q(;}hr(▐ S֊▓Z3IQ8:RRbQE-%/J94i{R)z:Q4gNu4 SҁҔ{vqjU^;@3ڧX'"ա zVyl1JՌ=j]8iW U\bՈqS 榍yYE>xb*AOPO&LuJ8A_֨LI~,'' U)`UlO=jU&><'~}9kL+1K$C'zM=h'&'4^ԝR Rd\搞?)sHsARu4G֎g.ri QIJsGJ hGg^%րNhGj(h');RAZ8R(R-Z(hQKGAIqI){Ph<џZ(A撁Ҋ2zbZ?)94i{ J^ZNbhz)qނh(Gq@t斁AQ)Á&y):priI"q07P5N|9=*f|ƣLvnAu cxz)i:R>uAQAzPiOz:PA)zu'&hI/JL;gR}(GnuH){PzQ'zh(uQڀ(((G4w%!/Ҁ((.):;bў();QGjZQߥ/ZLR(ޖFxi/zZhhKIҏz)%%.3EQHy⏥}:Q@>M(?-'9KNiG&wzRޔ}isi.r1N8)Fjt9ҧNM=YJ҈ j[>pkjbbFոޯB<Qf1V8ČcޞO 9$d'>xQ3v48x19ˇFfj $j5EYusU.#+6u ˑAcTnl# _zA隅8DGT,pO( RsA`Ri)=sJ) 8⌌( )=(R(yOZvr1Zc+Z.FZ zUrG^=j2{\񚴌28qS9f6ZRR5.Gj =ꤣP|jL䊧*u㚣2yUI,I5p1dK;7jIU7 U0TrPm1ޘ~ZaZBOJi3.sIךCv/jOZ;ҚLPh<5sF=hh1IҎ %E&)sA4QގbhE&)?SҐp)GғZZL@i(ǽ&9b(ր(斌{c(1KIGKEQZvI^>dQGZ(–j_z QIގZZ;ъ)HQQ{QKI)@=hE'qNF;E?r(▊LN٣R^5 ԊFzÁ&gpyYNNEigJ |յl(`)#&DH8xf6z&MXY5*9ɫ/2L}XYN2jCqZF)(ќ ۚ3֎g(gԝZSFh4AҐRwEEh} E'֗K;Rڔhǥ4s&KރҌ`R}4#dU*x5iFHsS*qKFq!< 9P*ғީOz$jDT~MSy1<񬋖=+cҞԜRhEtI;RKڌ/NR wQF):q6 4Q<K@N JzQSiv6*dTa+rB YSմ+VPjZI!90y5~ =WY\V280SJƠvNsQj9J'ҫN85.sU֘R䑆k>yzj1֩K&9%j彪%fY*dDh&2sHO4ZN3h=}(p J*?Z(4 IG\IK;Syڊ9)&8Pzњ;(4t旌RR~T(RQ^QGwQE.) R RGJ=hF3Fh-'~( ┊8ӭ 1GzZAGj-u4t旭(\qIҏƖ zwjR1Gb>s\pi3ƗJ8hIK09/׊ 9NMGZPsOZ052դncnAUj z}+R´gZA T \CUԗ81I\I1OGNqS-zвSy8j[QL}jT%*a U$^sUXg5ZOU)` jFUPz'=jAPrj2=iA tsMtb)擡^IQ4sRwތRw(=(4ޔQғq׽RGSE4&EhG@4 ;c /j';8E)=Qii:iRvZN~bҌQGRR(4'4P> ( Ҋ1IZ(@h/jSқڔg((44zOcK~9*t?LW`c[z֍kI`wO"d欤du52J_<B=jUsQ1*"pM3ޣaQz:iIMGSNT;E{RsF;ғ7ZPHɣH4c'Kߵ҃IރhH(4RQڏzNQ@)=ybR~4bH(AKړg\qIҔJwzJ=i1;Q(R&h4PO4qFh4RJ);ъQ֓I(b^ԙ 84RZJ^3KIޗ;ߊ^bKqJOjZ8NhG󢓏Ɲڐ㹥 IJ=i=x"R4g'.3IЊOҔӔTy;٩ZW^qI>W`(nF=sVV^aZzq֦Yddӄ'%AO򧬄iKZWSlPq֩xP7T.JϘ RwZVFIE$\frNi8)7 '4ub!9u=8h8 ii;QҌK{3M( :(֏@ A֎3KӡM.(8/GZJ^h^);QQ֓sҏ!g(vE9gC֊ QE'QKz)3Z(׊1Qږ3{O.xqNY1ߚy5^KM5 ɁUj:{ULɪRqU\Z(})I\`fM"}zR 4Rf4њ:QߚhI1OŽأ.9E'@QߑK'lP#p5j2pGz6Wa~+R fwjPå=N*E RHG9S@;yM3i;=i nM!9co'4ǜyuIuUžMPwCI2YULG#=*xsyR`Ґ M4ڛG$IJ1ފi J\bqIAtcރh@3F fNԝzތfzLzQKIKGJ:LGQڎP(i xQ9g41IZAKG(AHE&(Fh3=qҊJB jSF) 8d'ni LR 'CE{u&}{QJJQGJ)Z\M!/9G@8RI-⎴:R{Qɠu=(Gj: 4zRڎԧ6?22)~ץR$h'(ҎsGNuy֎OzR=;N1JI*6g5:>8O@bbB񚴧jn٭m1H3W5f;Oanԫp30#w?y ?TU,<'5 1Ҩ)UK{PpqlTOy桐JxR3ړ)) (9Ҏ;R)qsIqҊP;w.8vQRsJ8<#}zRIt:74`JԀSR j`})0Wc=5Y~8ޥYAe8KVR=MhRxGJ>YLfӔLcU4/LAL雉Խ4qFxǭ K(R/liG=M<4lTqpP4ܐ§LjBucޜ>VXNmXd *O\PQM;%M2i<f ˻@4FzY{1Lg8^BLf*0MDzR( DF3Kݩ:S[@sGJ=1h'z qI(F2)N)G)iOM9 }iNJLcҗw8i:J\q1&8Hh&);٢Rj1(sAIG4⓵( (3Hi{RcғSIEc4tQK֓b;(4ϵtsEQޖdE'zZ)3^gAǭR(I(ihhQA8Ecь})M KJG'NAϭ*qKIޔu)HJiH[Nɩ@qC=bYxz%=e;h4 RdbRv(H)xE.x>ԠE' ~3K p'N E&hݓޕIGҬFTz9H>#0"XifzTdgGy+Ҵæj"C#JGҫ4I *6snw1" 4hzpiI)0 BFyO”JNgN P:QIGQQ֗҃EAR~4QҎ(GzAK%CҊPqړPH"ϭhzQI њLq@hJ(EQ(E'(=hdR )h)3N:QGEv;Ҋ^J^uڗJ'AKIޖ(tKڎq׽(RS{Qߥ ڊ_JJ^Rww( ZJj9(Qz1-/_7:4!ŽbOԁRO(4w Zr@ < z`sO vygxJ_'iAM]=i9UJzisN,2j=(zKb[&8(3ON)sړ?7ў()ŒRRKIӥA4zt3IךJ_ƃ&3F>փvh :QړJ_Žt!&wQKhIގE}htގ(EqH)ix 8u(ڌH)~w(QAKIޗv)iOZJP}IGZ3'zZJQF(\QKۥJ=;zњ3FMv֊3KۚLK4Qڒ)24ғڊ\GPqGEiZ:(4Ӹ8:P;v8QځɢږZ^Ԕt3FhIAKڊ(GʓQ(h%r(w/ZJ3F3Fi{P1E=((8)x4J)h)@GJ '֊P^(@E(, Sړ#4p"!<('Rv4B{QӥQ\hގR1&yRK{qJ1q\ 3MGJQzzIߚN)F();փ@)(@))xG^ԝGZ(փA GcGj1P4AH /zN)33KFhIҎRIE/j1Gz;QE'-ΐFix'z -=;Z_%;RSQ: /zQGzZJ^ԔcQڐsKފ8&iEfIKh;юzwG8tu Q׿494utN\rE.ysKR:NbtQN83ӳӚi4u0ƂN)AjPMKo4p( сIs\B3ގgw#t=h4/4PzRwiҊOjS@"OKHM(LS Z C֗ޓi)h@RP -&h4J\qEQڎQIh4);J;QEiF)(JhtJ:c4v(G֏J9wR-P(Gӥ#ҌsKF(F(Kڌ9\QFi)@F'z^4Ғi=sFqF{҂ .A8IZ43KAZvq֚OJ8zRt.iSҐw惊Nuޓ-IPii/JozZJ)?!ќRii(h4zRQw=9zQHyԸysKMԝGZ=iiҁB9EE dRQɥ/CGEpE(ɣE/Qi~Rc u%@KFM;QCKFHKLK4`”S!"֎1JT9KvG)~VIފP1ZNzR}izzќ^())AHHQڀ1Fh> 1GqAE&2hi:QE'4zNRJ^Qآ1Ҍ QIE;Kڐ()OjNR/jJZG~qLqF(ќvtRbb9RⓡQߥAA :ցԚ3PydG=(J;QG4Qii("җ@@֔zFE\~4ԴQIv@f4tތhizQ@;Ҏ=hGz 4s$tҎ)CB8惚(z=3J)'9-Ǝԝ1NMJ8掦CI(G'zQGZC@֌bJ?&3KߥR@㨤=^Z4~wq@FxIRwF3IQA<(Gz)M6\sGQ(Iځ֐旵3KH::tQIڔ='4c"RPi -' ihA:RI֖IK'=i~RHhKIKފ;hZP'.3I4)(KIjvF);w4JJQH:sKKړqE/4bQ4v (RQhH:c&@hIJGRwJ:ў1A)9- =s pRtJ:Qh=)(ix'&H4QuA4(iyJJ(>tu3K~QJ;R`ъNԹ(4IRzf_Ǝ8ŒҁGz)) ;fqGz;#'jJQEQJ:;Q8vgҗ@Kގvw)ϵ/zNi{Ph4fZ^ԔtR›ih{\ҐfKb.1ғJxȥ \QhuҊ\hԢQҒ9fI4w"AKG9b1J)1G=yڃҌvF9њ?G;4gr=(Z?Zv81@#Ki0ysGS@&=ҏƌg_Œ N{Qh/N=)=h1E C9Gj1 Q}(F;@Qi;J>R-qEzQLRLڊZ:QjCץLb KIKIKi: ^Ԝg49 bbEMQEғRӭ/zLsREQf1E/cފ1/Ҋ;4d(hQE%-Rgwj1)Z(=3J:RQJii;^=(AҎb!{AGCK3FqփRA"(w=iB>QA>#ғR w3M?{vqF(du:zQAKj@hI4 = JERP 9h (IhhG)Ig4AfԞ{x֌P(E%)֓;;G)GI֎{ցғ1cځA(E4 ;A>/4أ4c%(Ji:QGG=sKъ>1E.((%-~T.(4tF(;RuddZPy;Q;#=)z JQGJ((4i8P{QZ;H =izLR(':Ҟ &sJG攑ښ{ƔQ֊;4qI߭.'84A4P~RsR4w%.xiHzRғH:P1ڊ9֊4Qp(=):QFxJN8҂i9>PzGnh4 %C@ix(4QE&hGz(h4u3(>d~4RsQ() (E%/z:Ph4w֓Z:F("h u& ;RZ;1Kz:h J)}:=Jh^RR/'ցJ((3G@4t=r1I@j:RQ=)G=8u/j((4Rnhi{z"PN:RuFFh4=i1xqJh?:&1Jzڏj8q@sJy^QGut_sH)MsҐjJp8tgw9zN(4phǽsAGz;{IҌ⎴!Q4w4ww㩠yI(K'ҌGzڒqKhb`Rw=(ރ'az8KP ȤiEi}3Fhi)hiZ .^JhQQFh҃/zLKRRFM֓EE9ړ)Ei{Syϵ(<ўԴ :fQG@ZLџќZJ9j -Rw:уQ.i99 ;4fq(&{33I{RϽ/z:uESJz CF}i{sLsvw=1KӚ ɣ&isaIޔtwGzhN~sAG4ғI(h9@Qގ u'SEN '~i{QRGz3EP(E&ph'4vvPOfrhHzE%R瑊Nޗ9:њ>u斎Gz:ڎI@=KZ):P -&ii){ցA RuK(ϭRu4r~ԢFzK4KNwzZ3֏j1/jo8J~Qҟ֓փ%җ.xu!ץ&0iz aF)lRNzi;iݲi(hz:vG4b/GGZ33(ҎEZ_ǥ&iE})zRj3IFyqFr=49Z3Z(>u/8)A{PsԔϥE%:QFp)){RMhQjFhsG4h9IPqMQN \ў(߽('4Fh}h:Rzs@z'4QQߌъ)hF)ZZсE"Rc Ըbh(GCI1/jNȠtڗt9z:QbԼfR}(4 sڊ)};h1yvAҗ}qi "zqR@Iޖ?Z1I4qьP1S40)=qHG4F98hZQғ<Ͼh4R%!(Q&McAF9#@RzRvhQF揥Z(h(F(RqH/nP1:(=(g(ғjQIޗ'SO袎҃A4P ZJ^Ҕh4d;Q֗探@9g0r9E);K ҁޗhsMR8JN{RSJC:SOZ\Qړ(QRvhQIE/IE/jNvFy(IE-&h<4Iih>.;O9ғG4wE{GguIKIK@Q);ϥxcF94c1FMF)iRg#4.r(wғځ4Q@ϵ/zRb('/9PhiOJA֖3QI4@"IqќPhg4NNh \sIގ҂sF(i:J^~v3ExNJ&h:ZNv>vd} )((NRKҊ:%/M:Nw֌ގ(<:sHxE AG4M'z;R9J2sKKHF ZSIhGj3Fh^z Z:IKA4d)M%-M'| 4Ƞ24Qih4uQњZ}hcҗғ/jN{PGzNqKEhǽ. }qA(4bQGlM4Z:M-駭;'@u'n3}) qў=h4Լzw)9(IKE 9dqAG%/ni;(G43ځގ{QZ(Iڗ2rhFi h(GZ:}(4Q@GZ(49H(1h4sFhsK& -i9E0h:^R: (4zP(ԴFhKE'zQGj: Gz)EQFhG搜IsKEEf֗4:RwG))FAA&ҁҎh◵)9Z^gAތtzь^Gs &Qw4<ҌRi2sFrh4RzR:RG(KSN)3ޔg4iGr(?ZLK擿&bc sAEvhOZQI9IP:QRfLJ^t斃IJ)44c4P J)=y⏥zKړcJ)i(>ԙ;:ތIւ(hvޓړ.qAii=hE-^h:QF;E(控\qHi~/F %-)R4c-hu=hQ1INE/j(M֌g.=鴽i){QQ0)i1FNqڗz1E'4 @(&1J($)3@cJ\R~4q@Þ 8GZNs)M(K:掦KI^sցIqEQz@K1F%/z;qGzLF=(Qށ(R}(@'z1Z(֎hRQi{ӽ1cރIEKڌQ(i:SE7ih4vi3J:GJ(h4c{RtqKڐ QGZ(EޖzQEJ8hԽ{RQZJZ;QuQKGj;R 1h>h4QZAJON(.}hiqGɣ:RҎt>sc&(3K>RRuEZ03E)1F9A48'QJhi KQRfQҌ #R@tGz:@>q )i;zRu=(: -% ;袎Ph 'KHzGz))hK&h/%擭 KIKZ))zRZ:)iqGIPhڃڊ4(E/J:ZJZ(RwEGnhǿv^4I-GqR;fP(3(4vbGJ:i{Qڌ Z@(ך\QQւ8ZLRt=)1(=h"A LsJiEҒ:ҜR~/NhcN)8)~Ni{QIGG9AbۚAڏZ){R֔`}h4qu(Aj='|RsIEp(<ҏʖJ\IRGsHzPqNGj38Gn(IA⌜QAP:E})ZS֏N)3K1Hh(EwPhIފ^R u@hEvqGJLzQK%.1J RRw(4uG֖();h1vR1Gj4Q(=E2MJZLڐZZ֓c&ږ(qGӥ-.1Hh(IJq@IJ0(KHG>1K𦞴Gtg2(bRb{Q /&Aɢ€9FiM4QZQ)hQKh't(N3K4cҊLR<яzO %KI@$cg`PzAG~whi:RI\с֊J9f%('|QI@ڗSIFxGRԙCA(AJ}h(GRi;@G"ZNq@hZ\RfwEz@hQ1-!;Qߨ\94/M/b K(J3(tsI81J_Ži !-.i=i)zq-qIAfGҔQߊ \QIތQJZ;Q(IiOZ):Rc!tIޔ`:)3E)=)(IJޗIJJ:sJ@G4Q҂}(Z14i{QEqA)wԝsIQ₣4s@&J:QF8(Gj%/8{Rc3F1֊0("(.);3Ҋ(((E%QzN~(4P(RtNuh qQڐJ(hiҏqEAK1I\whA)? Z;ъ:zҒ(E(/J RڔR~4Ph(Ph@!>g4IA4qE){њCf^QށޖԂފ)i-ZNc^QE旷&zR3ZAsA֏ƊQiOҒ}hA#֓8.yr} R &iÊC 8PO./j:1H~iN3IQqFyt4s()i{R{E'|Rǵ(1Ih))i=hR^qF8IҌJ֎ގz(IF1A>i}sM(t)J(4qF=iZ(hIEEEfq(QzRQEy 9JSH:RT裥IK{QQҖF=h~ub(QKRt ZJ;_j=4Ҏ=iMGJ)җsGҏJNiyt揠<q(E1 :Q`c1Q֗.iJ1ڊ1bsIh -Iޗw:v ҎOQj?*C֎q@QJ2;Q֊8}(4P=i>i=hi~w(ڃF))@9"(Q:P)i9&ҏ’g/9#Q;rhJ8%-!RIE'=qF8qIތQ\qE%.('z(Gz:(H斊^)1Qފ:RIGJ(QEJ3/jNR4 Rڊ(ցҐ@94vF/NfBqFE.2(t⏧G`g(EQގ)z4g.i)}qA4fZ3KI(GjQA?ZLџZ.}hKގwڃ'S.)03G:GZ8vQފ8'j;q^g֓GzL^xcPz@t((G8ɣ4r(u'9!S(4i@Q֎ԔER4sցF(4R1IE){bGz1GNQGhGPzP)x4{RfZ@i}hIQȤJ{Q)z O~: f4(wZN ^g4QIށKҊZ:B=9֒v'z\ c"sIvA4wIKb=(9h>ԝix>Ǝ{wIގ(4g '4;Ҟy&){RQEQ@G>ԞŠ(Hh3@GJ:Riq 1GlQ( 'Z\RwQɣF84!){RbP>v!1ړ/z;ފ;tL@9:GJ;ގ3IKڊ)(@旭b9c4ZZLsKFh#_z(@Ni{RRsHzKފ:RN)rixhhQG&Cҗ`sIHh(&)A-'jNs@KG4hQh?Z;Q.9I) iҏj(ih4 ^ԝuE⏩֊;Rd- ((4(4ғwRRڒfg4w3GzSGGJ3Hzt(4u=A(=AKLTsK@GqEGEA8/zJ Q&})z@<Bh'Kғ9x@PH4t?J;Ph?'jZ)A3(G~ P0is7ԜzRFi'j^hi;R8M(HE'AE-Rc=hQERs(4F3GLQGw);R@99h@'jZOZZ)xfZJ3/~Pxu}i()riII'/'i3M("(4K:ۯ4df%R4sAvfQ)=hTQQFh'8Q)~RsA>ԇGQ@1FNi{QtҒRҒE(AN4ŒIۊ9=h4whړ'3v'Z;ޏZ8EfP1OJ8q('3IGJ4*3Ph'Aҗ9Aҗڎ)(j(sF=GJ^p)(F)GNJZJ)xvhH _jJ;RN(KGnM'Z^sF9((hhP(RRJz(>ԟ.?&?TfQHhKPEvE4({:R撔}8֗{P~w(A:GKғ𢗌j;O9j^}((Gz9;bJZCKGz:b\f(␚:ރF}{PIKEJC(h^(sKߥu&h(cQsEtnh&g31E(֗4Fh4z33E.x"hGH)h@4掴g &rsFxE(4gzc4fA&('4Q\3Ag3KGN&)G&h4KG=i:њ)sHzQ(&ihfsGi}i3J P8A<ў &}KF~isRQ3w4Q@(94QI֗=8hGҁGciG'H={O%4('"z3@ۚC{QGz?ތEQ(-!QG^ZCGj=i .8QQE/AIEt4-֓ ^(ɢQ;P:?&p(ރGG>dc1!Gz9)h4qEZZNԀbZ)1@(GZ;i1KIE.)1KځANbZZNf(׭i)iJ\q֊?;w4Q1bQъJ\F);REh'җ&REyc(?vu/dJZ;Q֊J)hҊ3GSERQKF}84J) ;CE R :ӊN3QAǭɥi֒)i(4ds@KQAQ Gz:GFxjNbAZQIi%QތRJ;4Q4G4sIZ('Z):Pi)i>4ڒ>Q^⓽f^Et!RNQGj)hwJ (GlF2)hϵ`P(RGjn94ҊN/^h1KzRQ'zZ1ERb3ER⒎w4R)3撔thǽ-(AtRc4 ?qڔԘiyF=(QF)i ѓKIQG9~4ǭ(SHhQ@QF=)i)ydQh)1q%}hGZ^ԝhM(w旌R`њ;ҏzJ0hF=(sHzPE'>)z ɤQiiҊZ >ub'z(揭hҎt1Gz֎Qx&P:-%-%-4QE9;QE4RGz(RR;ъii;юhz8E-PsG8Kފ !s:Rw ' iyqF3F)94Rw/z:R{RRR5!-!Kʓ\QG&fh Z('~gizQIE-4fQG4g p}z4&{RRFhhJ8J(4QF  ԔRRIF3GlPhɠtZ^ԔsE RPs@Rw%/j0hi1ޔQihG4RwQhG %-'j)hsI;AKF))i9u(.8:1Gz(RvKG֓(IKA⒔uޓ斒;PyQҀ}(GJJ^s@){Q@RRgފZ(4RRgs/zJSIKCԴQHh.i;RFh<ќQGz;ғځ1Fh)9/$QRsI(;qF{P(hE.);QFii1JAP)xP}R=hѻy◵hAz;{ڊ;QE(AtZ^g֌'4hON)^hQIҔRRhўƊ3FrzQzRv'z(Q~J4֖bMOZhF)!&E(#ڊ(Aҗv<}(JNgRSN fCI13ڌQE֊:J^R QIE)JwҞ{R~bPh94bO/jJ(SE'j1^i){RP(KE)}(J?Z9'J\qH)i9" Ɗ\uIJ!wsj^Z9ihϵ&(E 4SIڗ.z(>w)zK;P(ɤϽ-dGCEJ\G~ii ֎ŽQQҎi;4bڔ Q֐R3IQKG'Aގ>dE&(ԴPsJ;GJ(EzJJփh"f.zC֌>w'Z)i 'z^-%F(;P:Qފ(ގԜPhwRP>R)=hE&y |Qڒ;ڊ:(SIKQ@h.hh()G%){QEqJi0h ;Q;ьIGR(i=ԄbhQҎxM%4ޓ裎~4wIG4ԴGzZCFrh=QE%)Gnb(ϭwFN(hcރzPzIE(яz(Q('ZSEi \Qhwq!v֛ޗ^s@&i{f9(4wGGz(Iږ1KI旡4uQތRg4QKEhIh4Q4Qz_z:Q旵%F3AGQE-Δb R`i-^(Q((<ў(TsIޗ8uJ:џ'z_z3EtR`(RQKH;E4Qht⓹/KqAEJZA\ g(qF() bJLRь(%M!ւqE-QEg=(QڌE:Fh^qIFp(Kx$P(IERq?RRz(<Z)hi)s3A"1GJC/j -'Ҏ@4⒌=Hs4GFz`Ag{HO4C@'җ44M/F8 G8;H(4R4g?J\d`tu`H=y`4uq1F)}01GsbfMR%.ъA/zB c@H{юE's1E.8~T (ivMZ\qIRt&(#J1@sGKN%{Zv4JLzP~F)~tO/9H8)j;旨'ց^Z?:OZ^4bc4qG4}v }QG~EAi9J\v(hG(:bdfԹN)8OƗ!ȤɥZA֜3Cך@F}ONRq׵z3P ⓽-Ru4p>t9𣡢4bu))G=x){Qނi8 8й4 :P9=4=Q&c&iLӳ)3Kڎg"H擓җ恜Ƞ}h>(9^Ԡ@$)qǵ9 Q׊?N4s@擩P?*;RPF;qH&ڌ_jLfg:v◂'cGK٤< \'NbLQJx9 R1< =P0s@j;c4i((nR):3FAQQu(hGz控hv )A44gNӱIKQӓEAA3sK(hJzRcҗ;t4 i q@g?:;qF=9SM;ϡ#4R{I1AcҐZq)ݩ/1H8Bi{zю)PNMCJx>vRrsL8qKi?~guA(=M'"~4Ԣiq(4ޓߊ\3ڌtdt>G~PFh}h@(qNRPsF(; 攞vgt=րz {Oҗdg9j>w<#ғҗS(~?*FIJ\ ^? 8Ӛ;bhA8ƎJpz)~c:QK׊AG׊8)4({8=iZ1GAG|R#=h=qJA֓\ѓG#ގPi@4;RS4G~(uIKI4cސpqޗsGNc9>"SI={h>J1Z@Nii1J8GQ@NqZCҏKIKHqG==1H:4\`{gҊQA9riO^)3`x=)zcLqH)GA>Qzу>zRw/cFqF1ސڝsړf@{PzҊ8fs旌Ҏ٣RhK^`w'){tt4R4AAZQipwRR)x'N(hϭu={RhIzt4h>Qߥ/4=(=h#4tGK1GQȤ'AEZ\sIsG'hǽ9=p8qӚ;N(FqFIzqF2(AKsIQGZCK84ƎKRgړv\wg&%/Z;ڐ(zRsQ֌zR)Q"Ґrh=(֊? :ь ў:w'z^܊Q֓<փ҅G4RN}i{Qߊ) /_sGsI-~;ҁǡ֗QhsKێc&zҎ֛fOZ8>Q^gN)3(LuҀISdRFM%)qIGqA<:QךZN HxZR9 ץ~4JA֔Pz~hs;LsJ88֎3֓/ltɤ=(=sK7آhN:}(Iz\fF)?:v2}1IQg9-'GI(IK@4{Q֎~h=h=Fi1 gz0:I{i{Hpivⓚ;Rߊ@h){ctu3@Ɨ֐Uq@N(=zqJ~J 无#!(q j(@y8Ґ R4wJ3P4Qi{RQRj1IQsGQҞRIR".1ގRr;@ޓ)Fi}:ҜzS{/J:P9A(/I_z@qK:P84@=( t84g*s^yj4s SHzcގZ֊=(g4QqF?::F2zҞG=:RsK>c'48Z;ԃzINPzqGƒ)?Z;փsIJQ4g't$ti4=sQ8ڌKh=hzN:џZ)44uF׭wRshhE'A4c>Ԕ>Q1GZ@ /~{P:.=)xϵ((<8I;ю3GCKZCu҃F1AN&=q'nh=JhKI/AI@뎔u&84F(Hrxv4~4u?֖@)GJ3G^c:v))qAR44KړҗZN/'liqhb/ҏ4uA=(ךJx c4cAKIRZ;P (;@})O?Q@vhh47j~)zg=/B R::P}'Ju=Mϵ.i3G^ti;юh֗҃ɤGJ^t=h:GE֐th4=(GAށȣ>Rg=A91Iځ)^ؤ Qڗ 84.?IɣT)ڊ94w"!<4cIZLI:RM.?:AsG@M& pj8ҏޓFrhԙ9/ZL~39A>(ҌcOjځ)LQҌsAiqI/ғSA&<Ҏؠ;юy1Ij_Q9bR)0r(hz\8HiG4\R"9Kz9}h◠s)p3I^i3ciGJ:Rqځފ JOڐE;ҐiC@4p(^hK=Q4PsځJw !%IixjJ;PNhۃ׊Lw44'AK@h8Q1ߵ2 2)>q@6hǽސȥ8'F?:N1E t#4qGq߽Z=hG^i4cڗ)J)OJ)KRu=((*; R?J0h8Ͻ'`QΏ⎔'oJ^)9=iZ\A/lR@ҐIގ4wzZ(ӊOj֔ /&qڎi;`ғ(Z^PyNsKGzRi$}h=◶h8(thEg)rwv 1KRh qځQ@أhI)G@IRiz- ph<Ny.h@zȣGNvqIGlNԠRQIN)ޔQ׿4vGAQG9f4 9֌3EKzRhEc=1ڌT(曒x ;qIKNh#4@ځF9zC֗zQҐGq/^IҗӚCGҗQӽQf@uhjL֎GJ\ZBF1sv;Ҏh4)ZF1IjQG4F)(4w4<@Rc^tA')h~48c.1Iߥ.3IKI4ځKIE(uGNQGF^ԇ /jJQNKH2E."1Iv@Z)J&GJ34Gփ(}iy ^C֎3AG&O.G8h1KiRcLڔcu#4v=)3)ORcZo){۶i:G9qGN)9:sGz>i@FrxG_'z\8(?JOQڎqQ֎h4<KސtȣuҎ)3ߥ@Ng)4(} w>tRw/CHE(?/P(4 џhꦎ߅&9):qF)}PRtKu9t9$dZQ@4wѓKRv:hIG'ړ=h>=)ݩ=J0(>ƒ^{Rp?!v((4M:2;hhKQGz:ҏLRޛzw9!}QGn(AѓR:Pq@擿((94OZ` u)h >IKzQ(J:Qhiڔ>ӜҞ1AhQڒgi9##"gLёA랔ti{bKڐ >&y~(R9hi{юMt?I(x֏~fFM&G)RQJsIӭGғRh{g 1Gj3֓֌qE/z1F3FxF{◎g=RLqKIKi;R(9&(8sK{֌PRwGAGAJ@4 Sȣ:iqhj@9;wiOGJQ~.h4wJx4tP@AF=gҔ(ZR8M)zJ(c?=uɠr8K)1h=qE@F)OR~fFs@sG҃@?'|QN)O J= 8 f@)z=ncҗ4{sIGSӊ1^ԝ:Q@RzCgqڎF(;P:})>uK֏z;RqG_zZNތw 4F@8%:})zRf"w`:;'@j(@i3֐u)h=iO'FG!)1NA8H9(=)9҃!P@vbzNO4RZ 4AiLb\PG4`\EQJ94wJ1(wFE(8vڎԃKsKH4fqڎr984u4Q@Q J{wȣz1.xA=hPyNҜRғ\҃K!P4 OjQ/={R\3:P3G|Rrjp}q@ #cG4NݨG@9j\H)?_Aj jSGzLړҁɥ9@b3zbsGnM(o֓Kj@2sA('9R*C@p3J947L`@9&Oy=hh wF}h#ϭAiI֐fA␊֌|<AҌv)JNҐ`\uq֌sF:(?Z:v@c@Ҝ8+H:Q &)ri=F=@QM/ojh9Ah0<}qLsK^g{qGJ3.QLQ(zCJ&ƀh'(8Œ;PqOf 8G҃Nh(RӚ0zAJ( N3G9/:RcRғތg(9){Rb~4Kښ3J:h<84}M 01J1&3F0)ϵ/rh#<#ARю(GjBri)=nzғ(4J3Q3I4h◶E&~_ʓތP~)9;b u? hiE&))Ը:ҞM4t'o3ȢG_Š#(QH)FZC)rOPy4Q&)zbA:9=h8}?Z^ F{v}zN.8.E&;x8G~(֗4ךCZ_z;~4sҎi>&~n.i{;ҊNKGCך1Z1cZ8J:A\яzJN3Kq9bz ў-Ƞ◌FqMfr1H ;=i^h@>olK>I ;h}h"#ךQI3ږ<{ьf?/ZLIG/H"(ގ⓿Z:ёPE)֓H 2:QJ(֊94v`KJ; 3$RGRqQFp( ^POoH1/A@A<>c"t:4ziAȢ)3ڗxq;cю:ړҗsIJ^)HqҐb)zGh#@1֔@94KtݹzR{I(8H} ip1J=y֓s֜:qHFOK('~Q4㠠 ㎝ix!ހFzQڗRqGP9hz@8ZJAފR(ړqAF 'Oj_ZNϭ/dq43ҁ9CFsKZh cN? 84J3ޔ}1N9FZ=GL@i? 1Ii84Lby⃚(h44`R4g((3M'ޝIh4hs39i:=yu@usGK4uQj;Rڀ@4vϥiGKނ))OQ@PI=)qz9J^ LgZLspK9Kޓ;j1F9RQҔgsK@MrqIP=h<A)ҎhGjLPs9lRǥ >~t@1=3H.94u;PF;Ri1b4cF=hGz?:(HO CҜpE!LҚBTuJORg \qN3Z3AsIF("Rґ!{R8/4:(PqJ_|Rhi{sNIIF=(KޓԸ<1Qށc'49)xIQF(uIQzE\p(J>'&ihҌs (#hi1@R``'G"FzsFyGҁޗqIg4~8F1A{fqJsړ'=)SG~ގأڐ4c=@ ZChZޗE ȠP3F;ю8֏ƔqIԹ֒׊ .sIڎ=8hiأ`Qv$LRsGN&9E-IGi1iF}i1KE'ҔzJy#NaMi{c84~hԘ>c\wi =Oh`4bRҐ/֗ь}:M'G4~TPyQzQޓQߊK:ړ^'" )9)soS\`1斓4u(=h=hh$dPp9;Rёus&ZZ9@=h{PxA4CF8G'j3Z3ԠHr;R(8u֔ڎғHF[=# ^LӸHx掴g#cNҏK1҃{[:Rnh ( !=H)r(48vҔ{߮i޽Zwii;P}88~JNI֌z^Ԝ>Qhhhh8 j1Z:P0 Q}:F3^N9u'Sց9ϵ%sF}G:Q@'/Nh@QyK4{Qv#&;StR8. s֗!ḣZJ:h.9}9A _jLRtҊ\⎦юsJ=zPsԙzъQA<ۊ:R4'җ(G >P8@99b֐QQKhGL҂JJA=zu^i147J_“4p)8ZB3B~4MzQҌ)M7۵)p1Ac@:@'֗<֗48:POZ^;Z.2~9gNh#wz1҃!RE/QIIߑEc4⏥.2i:ړ9⎣; 3(wʓQKҚ0(sGҌdsڎ'| !JyGAA!(F9$N:f֗H@94ڐgӚ_“RRhQZL^􆓵/'h=h;fqix9(Z4&h1G^; 1Ɣ)1Gך 1 ^ 1(9Jwⓓǥ)4$P<֏`h9~giN(y4A)ړ֗A3GzLJ_G9q@28QJ9qA4~z.1I@h=3KG~>ښ:R"nhIZ@zzҁ^887`g|~ޓҐ.=ԃHzR;uԘR4c)I>F h4 'IހqKCގ($8t'3q RAҊ: 3𣞴uG88Gz JzqG^L{E/AғuZ8t;rh=IfG=E&qJzP:R!QJ{ђEJSH8/zC֗<(h(1ցԹhxg4utz\R{w>ԔOJ\fNH8G~4izRg\E8qG4@'!#H J(cIA-'J)9iOlPI}isFx)NzqG#MHIOoΔH;qAh\qGj2i1O(>sI>vF:1-:9ǽ^ԜuiqiHNgKޏKR14O4&}rsG=FO=Z13K~;RFsqJ0HҏJQsI8J:(tNi}1ڐZ .0h#.i(# }hȤ /b҂qGc4v=)֏ΗP8j(=s:944 RԿZC֌֗'z3ڌjڣpx 0zS4HJ\v:oJ\(9~s@t撁K^hPPpN('ҎZBxu hhwIhE/ PG1IGiqFR8u֊;QGz(G('ޝNF9KFh␞ 8-'j\bsG#!/ipzHZ8sKH{G~)z{4Oҁ1KHA>w<(ZNs)hړZP}h qF8=)s(C@('9j֖dPN):EQwuH}- !NF (MJ6b';q:掝=hizh1i;ր1ҐҮ}9ah/NzE(ӻsMNR4sF:jLu99i(49҂8} 擊4Q)1G()=) LQLR1қ4c'&h'=)Fsғw-'SJ3GQғ)qGnv4QZ1@KGjP(#"@RzQJQhiqOJvQ'ցR(:QQF=)h$ ^c?F8(9-&=hFx^0HhTzюP{3 ^G'y◌q:ю9|)fyڎj@$(h"&x7Q88sJ9oJ:—Ng&3NcQ'/(ȣ8J\v# ɥG8xq)3ڔghҚNԞ.zh94p)9z: @4vz;Q!H>nf37RQ{gz^JPqNOF:Q׭/yLqAךSP>fRnJ\ qA4–(ϭp)4=M4sOJ4g4w(9z N9 L.ORzKҔr);RshJ)IIӨttCt89(iz'lsFFh8&Q֎ǭ9E)zsHiyGjLsQށ^M 9&cb{ҟҏK@/1M=xi F2i{v&{Q9׎(.}21LKZG^8)pqҎi;ތtEi3ZN~@4zP1((8)>M- >cR RqIM.>p8F9擧ZwJi}h=>chA8==i23@( 3Ev9#gގ($dQKGj;sG#&2(dnN❃4ӊB})94NϽ=qAA 9u9ьJA@t>sPF Rݰ(=.Fhx8/C\Ru< ^9ئޟxFOJLק*Lя^`cړ?*ZA4gϭKAt_҃qc8FrGc=ϵ1_j;uiz1IQ)8{ )8A1G(8G4Gi8(IctR.y @98h4◭Ms'4x1^M!3J^!P=iOj_&y"/玴z\ nRuzRjC.89 Q(#ގ=@:RqK۶h)xxE(#9(Pz{ҏz: :wf9JPyPzw :юi1G⒗4RsKGozs9vN;P3Pz֚2OΜ; LPsj\3E/(+ѴG(q֐E3F:;㌚O#gwZ\w(4`4v40MsG~J_LCj!jPh& v:t"vu9v?Z'ӊ0~ʊNy#uIsw~lbPzK~4g֓L9KlҏjL{֌F}y.:CFx/N((KIЊ=gz{K:Rf(=<ҁZ\@h8br(J\I߽ތќ㞴mSҚ)sAJ^riE!9cҗ4)}ȠA'JA)wQCKځ`q;R=@4}M&2;zS dKNz;Q88ޛ3җ '94pq@zѻ#(Pz@i9●J>v&GJ^'^3K'4@iGC@'SҊ1@9 fzRg4g gz0{R4{{Q}E/J:Rw9֌J^:A)j@zK)2Ej9PE'J: ޓ<}iGzLqJLA' ޖGցG'"3F9biO'ސ::RJ3EgH)R (4qޓ9=:QSoj=)G&9G~Ը!<4tPi()3J>&zќc4< 2@J44恏ZIQ44⓭8⎂)ԧHOH:P84{J9K߁hGҗER(FF8t,tu=( ~Ow4KqڀNhHNE/4x=)s)/$P=GLPxihj\c4h.N~r):^ujO\z ^i)qIKڌs@GF=3NI$ #ޗ9 u@iO=)i})3RGNisGOzL㩤ڗ4i=RysAZP0 Lۚ\R F}i9(sAQ@cvZ\R``R)OlRt)v/ni09=9o4I3ځ4Ҁpi  сF9I>&y擞NGh (4csJz}qIɣs&*;R R(QG҆''zQ84trycG"R :)P:fAKJLQ1!ޔt=x>Ԥ.hZ:;t89zvJc.=Kޓ)Eh?Δ{ccьzRG >gڎ)>)u ;zQΏJ0rh8t(1KyHE.2((J9'FϯZ;FhPiO4Is0G.1ސAQK/lAOZ1@zQ&QۜaNh/!)2zRHsj}(Iha@@ϥ'9h&(h.8!(=8t Ct/JhRMRb|Ҍސ L^ԝ/^{R)sz=hҁK^wu)ZosG'4cvGjAԴ3qzApޔSi)=dqKޗ_Ɛ{LIߚ8ȠRv8J  GIڜ8xsKzQΎ:LKhϵG)?A9~zRq bKH:M9 .; NsR1Kh8qI@44A@8& )z ьd(LP2^(#w=zAޜ)=z8(j:('8 .94c11zw0{;ҁQIl Rv;{} cޔ94i84gz hǧJ:p(Gl1M=0{SLN1KE!{<1@hQ֓_CGlRc(< Rvx'Q:vc?ΎpA:AzЌOcKAJ?JI;4tjC֊FGGzR1{R})G>cފJ1IZ:Q׭ڎޔҔg?&lQvǥ.M'֎< Ԧsӭ&1@Gz=(ΗގsNi3F~j8/@?֎3Kq@/C҃1/z/^?Z>E!ҁG"u?/l֗=4iBsQ׊ ڗJ\Tsyr /zLюhF1)@)OZ)FI1N5&/)1yǭ< RnivzR)y);/b=19)c1zLI##oo@4f1E&Ai3hsKIA'zi}ѷ=izn):sAIZO{yF)zJJ8AJ^zPy4~0 4cƌ (?*ҏlQҎP>ݳA''jAGLuǵuIF(FG~g/8LӾ(<~s(():J9g(~4tGJ ㎝O j\ғ?7LӳJC“8Jvp)O&3G)4zR:9uiAO'|uIRHN(M/CԿJA)O4cƓ(zP;f4 ~4==3KP1NE8M)@QG/QҜ@ c 9< ҁ1ҝG֞qO JxN2)S8)7Ni. 9PsߊUҗi ))SHlS6sFvi*==Ggғ7 8;ڌ) J1HOI҃i3\Z;>=E}iclޔҒ֌HqGAZLJ1HZOjLs!y(hB{Gҗ'~h(('/ZoJRxsќuJ!)8\i;KsIҎ/N3H1^3HphG(9 hQ(t= G&GsKR~TG8QQ-s֌g4&HzKրq.;w4hhF)GIթqAvtPO/j:9ޗ{qK(ǽRE')x җFhP4rE&;RJGLt8Gz1Kc4”_z;҃Z3!ϭ/8j^(9sK(Ru99cǟjLJv01v8c bts*UK*Af"!_(ԞO#C"HМ8EژbTAN}\cQ*2◪)g$Sd9'Ky76o^P:RASO׽/֓#S>ԞҎF8HF)2A89$R f=z'ZOj1InIҏaKJA(qHsF1AG yԄ9PxfJ=8\Rv<})x# _lP)3E)=hxz=(n'A(ȥFqڐ zўhgLڗ4JnOZx& R*\EF3H uKJ u/Nҏ(uhfך^4z;q3ڜ9sNH(=tQ*.W֥T AJ#sJ:S'AojvsOP3;Oh;=:=j!H#>2F}8UlJ9#ÏZ4$GMxz~4ғh)L n3ޚPzM *#T^^r*)">'&ܭWdHT4й4RtM,u4c"z:Mw4ҾK'!pE-'A9)z~8'~hRp\=)N(>Ԙ . 7Rb—RdzQ#qGR(N{I\q=?j03Hx=h;P:s@v䌁I:Rғ~1FFhsHzt\R (i=)s)֏9΁֔Q4{RZy 3s-'=i?'z:uM8( sJz掸t@"Qڌ`yK&{P:KJ9=ZN9GZ\fuZ^1AJ\P=sF3ڗ K4)}ȣG@ NLvGZSGQ^Լ&?*^# w8rN'Jg֤)OlJ}G@ !Ԃ Մ'O[|&9 P-}h{\mPݜPГ* Xi9D53UZiJn8zk Rq4i4uZwoz!m=)90z)=9r=Hr zB2sF0q&2z ^ I(\{Iޔ:;S{RtvLF(OZ4OZOh4Oq = tۥ-R:=iy3MҞjAZ1{r(=zQ(ZR94AE'Ґ20}(}E/R;Rx{R^t`RvN hأqi('"ϱ\RZZ1 F3J:ցGd~48('Z9 Py@fx/Z1׭җ8I4`g)OҀx=Zsp8lvIA@&wQxfu?ӥ<ڔEJ}?:5稫Q1TRM6WU{\Z+檛`ʒK|@G5CȪ0)qPɨRFED@*4c43qyG|R`gtmAt_jC(%4.{RqH('ڊ9⃎i1F9擵LzCFr@~(hQ֎vj0x(i:8{vtɣFrqG QH:chzPq{ړK֓>-H}{Tzڐ{1ɥjAI&Ƥ֤*SyV"U&N*u*!9e#8a =GJ!5DjizUVdHAR U0H*qUofqPy_!(ux>o_ZUjfIȦ0#|hu4ޣaHNM!9w4ߥޏJ $9M'Qzb`w/n~?n;\`R)9ȤpFGRp 'CKRRq4Ҏ'CFzKNu4cQj8'Q@SEE%!>J1G4:9ǽp qzsKhz3HczьџƎ(ϭ;QRdzQڗ)>4KԘbGRttn)q҃Qޔd3ڎ QGj^1IҗKڂzP>q;)x40)z7ZNRsK4rsKG_/nԄsJ84g4:PF~)@9< \dP>P PGJ_F(4cҗ/!\ϵ(sF3Gjzj@S‘S(@J>ed`U9U欤=UG<[gamEN"i:T_Rچ ޚT;vxjpsQ0JUiB@ɜ)U@8R["ST:qCB3Ƞ(QBzvAȤ4AKzi9h=h'&qHyG'\bڀ(4c= Z@{PZ8{ߥ}E&9%Z@ L A$R4gP~g(jڏJ8"x%$h&hJ1ZNi{{9–8҃4=lc 4vCKڃ4zN(FZ:w4~4c3K(яCE)xKփsGQJ4&2i@QG~)@=ךGh4RzBpyAlv:dRh})N.84c"J^ځ>t.x(⁌qކȠr)F(11ȠQj֎ RqR}<jD6sS9UXNzUj(3W0\.xv(p9Qǀ*eN8EAONفB8CҚЀi. Db<\*«5Zus+RN* A9⩺PȸBy9"~faÚ:aS1~i={ϥ!(zAӞRczRg4sAw4g#ҎqLc)>qhPOqG8I\f:c=iG_Z;ggבAp4c&?ʎZ)3ϭҎQ@ރC@^%⁜Qt}14`sޓ={Q9z{'sE/c4鞔(h?ʓ4f(h<юis8::3` Q3G^m=)IxRKG8(Z;NJ^(4u@4hGj8@8FxGhsJzץ/Z2sGNhPF(ޗ@$dP9r{Ӡ]*ۚGj (8 zSAO)(AM*3(0j&񍿅W1{t/s\Az qsPԴwAҌzQGl)K&\qޏJ=s@ރ֗'8Z\qH"FM:=izPsKFyARHVtɂIP8x2aʢ>?ªPHp:RG=sQ߮)#qޙ'Ҏⓜ4E&{*98z>^)(4z; :)'@KH'(I$QHsGԤ?:22) PG;P '/^Rv4g)sF2}(J=hZ:zPOKJ8&QGA4v CP((4g4iO= zR8"Q(i:v▀h$Iҁ 0(旷ZQR)zLю/cGPIiqG)p:R:=I=7Rn ^G@FM"q1Ԃ#қ߽)FN)1}$l)0sFhZL:sK&1ӭ'֏;ъLьEA9ΎAci9iRxx(PzџҎԣ֌vZ;P?)p)@>R%(Rx4ԾO\RHJqV#Q =UڮCt(85`ZX=jaӎ0QR"٩dqR"d_\yx3ޡxy<Ҙ@-LtjNy%^URj\T9PHi zu7| Vc7vV:C"=q' zsHqgL֐{@=iJCxh=)@RzQN$hҗ(4uR QޏJ3RJN0((}irցA){dLdgF(iM(hKhsJNxM9JdRNs~4s(cK(=>PFG/=)98)hFy /"I~ui"1KރF@t9TvsAqIAҌj9'}(v挜@&(i;ӳԄSGj;HzӔ4g H4w4v4=)qHydқ֔Qۭz8p94bsޔ NRhy{B裊\cC(qJNJ1w{c'җZ\zRw.1M(h#sԼbҎQOZ=ZC?(0)Fhɧ 杜z}iz(=iG=h{\c4g@G/҂sGAGz6s@Ӈh'sp"JS*^qV\cVF3ڮ@hBLVPsVOZt5eEXNztaY^}xչJp:h#'G03L)"銯*=*Z* */Z"U""ΨDBgUA 'j 09W=PHO'sM=qIɤ 4◌JL֚zR9$ h2h&)ZCP8֌ғ(LsG4IRsڗ(GZAށGz:Gh4sJi3փ3I4LU!KqIFqIڗE.pM R;fGOƃH:# gGjJCG4vR 8c)sڏҗJ={u3FhJZ1A4c }hh '{J8iAZ_ƒ0is8' ӽz1ʔr)1p1ӱR*@x ZQҗuJ1M$*:F8h uxJMS:Ԫ( ՈjCjcUք1V?Z`zU\VNz~n$JS H:8c#q&8rA'p)95y@_'$?UUY[$U i21P?CT'^qYYoj*TUW\r:TsңD㿽FqLڙOjNzRt494I;R`֔yPO4w Ӏ9$ϵ9i9J:i1Jp qғ` _z:ir))@s9=qKr')s)ϠMފ^F2?8p)8(q_s䌏JL:Ԫ6J8ҷdV'֯ b2>r3VNV=f;^N*T.휎VSUٹYsUۧ NqSzbn3Mxǽ qK}EI4});u)A.:fF?Z:Q tw9)c Rc; Pz)3֔(i 9qHG4czQGzqERQE)I=h ROK);tK`w})Fsғw9hJ2O4dhԾؤK(A4 1KG8GP;Py1AP1ⓨ◎)GAKvt2izj\p3K11@$у{ҚQҁ/a@~ԹA֓"”8t4Ґ&1Fr8ir)pqԼ⏠sACG~:R=~qF3i;ӱIփqKۭ((fVLL 5f>qV@Ӏ V#ӯZPOQSZAVf XAȩGL:ɞ*\bҔN}i p:6I:sU@y<75RSjU%U߁T%j2= QqҪL橺c5VU5 blx?j3%4I?ƌa 9ϵv;Gс8JN)sM J:QⓟLRQn2sޗߊN)=;h=(=LR`&)2sK Z;RMg#8 .3ޓ4gKvz :h qKs4ZwlqH 80I41M'=;Qiqq1A8:R/Jzu&(ixNirq@h攌P)r1ғޝ҃i@)OƦNTOQȪjEBqPL'Q`yM}i֐vzi9=i{u4~i('g}(&NiOךOqFriqA8?.H [Px@9.M&{QJGZZCE:QGgzǥ8ZNKڃ(=9 LMP2zuRM{Phޔ=hZ:s@ B9֗$ Nӳ&FqNb,ǭ/N\~PR(vF)H<84uR;(Z1/j\qP9>iRN^8WJy RaOU´`kNZ1UUXN?§C*t$V9*TzwCqS,{QzZR^3g&fTRK\V|UlUXUi9jfʹSY/=*Z"Lb&OzUw$a'=j=ؤIyi0!<F )Ih4Ӏ)Z1R='Ni:^}(<g79N)&sJRw4s;ьG @<KӚCB{ߎgjN &p@@4MJzRv@9F9g֎i3K)1K@Z>xIKZ\g#ҁ֎(&8A8Iߦ(ZPsFhKؚ(/ϽuP(1Jh⎹9{_JF4Qtҏj_z:tZ0=hIցcNbqHrIzc4?Z^A)yb{t)xގzSZC֗)zZ)~{SU9@S+st>,kFqVDҬ*ʜ f!aH52r8~u*8략 H=99Jc2)#ޣ2QF8)~}M9@JL~4g(@Jtߥ"`guKږ>Ը$)@jP4Qs֗Qxiأ/'9h3J:{Qߏ֗)4$R:cu/zSR@ɠuv=#3=H"SަRzRf398&fG'jJ1VNEYI{vVAT/&GUqԠ?{4SA0q֠'~U*`Uw']ץB ֣fQ[ k`L L84y>~I|Rd'4ƗtJ3h>wzHR}8 !ԘӺzc ~tQRG'2JP=.y)4w惚:@>إh=GҏΝ?ZP94t8GNݽ*;”~)NST50S/AMF3ޮEsZ+F"HVTF" TJ%sOLIb *A08R48iP jnjsUH7JϘc&HjV@MWVccL-ژ=O5rz7q֌)M'SQ%/֓摈稣?zn)1Jr@IR`Q A@hu{$Q4}h旜QL⒗3ށך):N({tx$6qGh4q{JCǭ*AfQߥRqKFj^hi3׽* Ҍ`is׭!ǽ)u">R($PO44g&GZQ랴q9⎠`csq(h92)G>J9掴("3vQڗ9)2sK('Q4pOh==)AqG(?xP4)1463N-(^8{z⦍:Gjd󊲆FGqҭtqH +J*S`O {wJ:uBqp 7b3Ӽ9G@'s֚f9cMQ?|5c*CUdpETvWҫHFMU\5SOQF?Zn5x~jQg/^:qҏExQ'=ri=`җpO^ړz8ZNIFrɣw84A֐qAFsb?'oz:QHE׵zR R)(֌vF0:GJOz1H3$d =ǥR4tGzc9 @'4dgڔs֏J23FI<ng&iq4QKf(IFiIj;KRtzf/&p܊\duE/wF(usK@h9'KR ўzQN>ggY-7=)$UN9֫gMMlQ#)8q7IҚF 'j(B9M!go&F1FOQJ3i98RQדQE'Nht)3cAdҜsKzLqFsGj:zfŒvI<{vޏ—SO3A'j){qQHsGnRtP9' .sMME():&zhJP?ɠ(sHN /_j9ɠJ):(}h8KߊCӚw&994usEގ`֓R((J1AQ":wzwrh&>:Қ4`ԜcUPiy)@w3KbhGJQz_zO>;ӆKqH2֧CxҧG= ZSZNGV|G'5*R zԉ/5 J$=iLԂAkH3֙"i;TdycFNI*ǃTd=:)U5?7Sc2*n:T 3)Ia88O~GRh'RwjF4Γ&1Hޙ ~4@df& @M4=i1^84c4Mq\(!ړh.:Ԟ٣'~)HqI"s֐4RtGSIԽG!Gj"ёbs֌_ƚ8^cڔ2 /JoG/zN3GJjSFsMFsJ984t>#?FqG^EQIԚj\ JF(8^i dAPOs\Qqj\҃ތ~t(v/_3ڀ}JZ;QqAp)G<'A.r:R98(GZQj -)qN"PiGގiz`短;!u/7M9})3P9>ԣړ(IiҎ3GSI(Gގ):{2NH⍸4{тGҏzCӯ"NhsIRc-Kޓ'q?:^xK"RQGzSZRFhj9Z^3.9>!8斂hizs@zF9)GHN)ʓRsbQE9Gz\M)^qQ4`hڗ8J33ހO8iiqI/;уKϯJ@9֎;R߭җ~2:fB:iNNj/04qQ<qNA@UW9=j9MsDdA5 ITL49)MunrrzSM ⓏƓy=qFO' ϥⓏjC҃hRZOҊ)KҐTy?S{88)9iE!49Ic:Q֌GCA RbCAؠ1Gnhhh>)3(HzqEp(AC-џlqIh#ӭ'?{f;J:S9)Z\Rwv>4w1ڀ9AރsIiF(48 _G$ ޗzҎh^8 旱R);zPs֊SQG^HqސuN);~4zuuR$4uOz>8=isyB8㨥)h{Sɢ=)FsK(4^*Dnq¤FR+=_9r*tS$ڧ_~j)V0 8'952 }]`[H.}#L:fNqk0zdzK1Q3`5 GNZF䊬W}$;TdȨXܑ֣,j2<qzSs&ƍp=i9i>4Üy4:Q9i1FE7PRw(R.xzNp0h>> J^G"z3MiFqIZ9:zw)>Ȥ4wI^Ԕq2 Q@9擎ԼGzN4G掽zsғsIwNFi:(=sG8@=zP:tIޔQj:1K߽Rǿ.xZN1 `:(99=(ڗP Q9&xE r 8֗z0h(Jj^)dd 1Z(p<{R)ONҗ@Gz9z3Kh8E(jNs'8tӉ'"Hr:Sng4ԁOV5269"+zf[2ǽJ#7bjxJ_J_0Mg 3'zS~юǜkMSL `̘${T.ڠ/)3@cHHS45qƌO= Z3j^HN֐9 qGqAuhy(X׭0i(4G8})? SI98/=qMniH >qAG^htܚ:{Ґx>c4) }Il:): ?AbQ'(8RdQA2h<0zugփ@#'4N(":^}i ((8s@M;Q3Gz)8R4ΏZJAqԠzq:ўqғŒJPi:fpސ`sKߵ'-4٧u/S֌zQ/AIך;Z_Ž8Z;^{sGozAjpzNPM-1Nz3K;9~4cw=( ;ގ)GNO4u#4g)91I_JRr:8JN=8֜ #i.iNR+sj?OZp8<1QHZd'R8 & x=h I֢fM.3dRgJSL'#34ȡ)M74RzzMsHx)1G&svR8H\RgNAh֓(>1H:sHzR t8'ZCQAր{RcF:s)91G3Iڎ)M瞞d9Iۚ:u4q){4uKRj3&Nh'J\ڐҏ֓>(Q)@)FM(SqJFGf΁#QҎ1I(=(#?JQHzRjNҚQך^i: LR sҎ@KAKRp4J1 (>dfzL稧uFE <⒌KsGyiFrҔNKҍK)3E.Nq@=EFy<яZSR1z :tqNȥ &F(=Jx8^*c40M/nx/LԁlԊpy(,qHXgޓZ<ÎsQrM1ѻ h<n~4O) ui==s!pHcޛx9=hv'8ݚ3'j)р掃IOJ;Ҏ1GQMMFyHii▓8h4ڐUQ3L8IJzq;R "\zR:;IRzsA֓—G8&;b4Rt= 9iå9nSCN'N8=Awsx杻A4C.٤q#du&Qn)Fy掣'4ӜI{FM`sL(9Hz4d!<@i1j4Z=hϽ7ғ"!(=)(jNu9)OK 3GNqAIҎ=h=3Fxړj^ JzR:Q8}iOZ٣( 8'MA<]hⓜf)9=iz A()h4dG(=)zLޔ ^)Nq&y)L Qj?J=Z_ŒP{R0~{8h\ciGe(7sKiFG):{փҔH=}i\֎hK'9jP8Iڗ4G@=1RcG;83G_JN3֔pd@=sN(nhqJ2Opx@?ӹ&'ڌJxO4) &pO4ԽJs``O>ޔ~$ڀqڂpx41n9@1 =8!iJQڃM'c= ?'~ޗ?&ON01M99=)?u!=Tx'4RguK)3xIsJs7t3G&7jL01$ iCƓqGnQQ(A3KSsGQʂ}A4J@xiӲ<RtQ.F~lQIQF()ڎNx9pOz=(4{hj F{Psڔuۚ\b/qH٣ }=(4◚Cڐڎކ)sIPF'?:^qȦKמQGlRc^Q@xFqF2t/)O&0>QiZR)zL;ϭ!K((@{9I#g)g:Rv:sI/hڎhjQA9{twJ:s֐qڗN(>Q֗Z;qI|P)NvsGNwJ\G|1F21ڗ B}4zށ֌=Lfʗ=4wt4Z Fh(9g"4i'A8q/Ku݌ \ⓡy ^4gRcdԧ4POLzr}E/& y)`('b:q zB= 'c9p()'3֗<J:AփZ3Frix9)s@AьRt9*LRL|)zqIs\QA()?RcҎNxQޗLizZ=zP9斐ޔ99i=F)q 9Iޗ/JBxKߚAK֗i:^=)Glt#cڌQc4=)Gԇ'^Q&}(>nsIۊ^(9Mz1G8sP:掾wg9)K'1G7Q>ԧH?Z;0Gr)1ߊ@(hg#ގG=zsڀ}ixqIӨwȤ'2):IzSHyizRwtsB:SȤ1R})uwhI:4vt8F}u=i g93J8=iZ:R/jJ\i1ѓߥ%SO=ǚ9E8=i1S;q֔QߓFZ:^{zP94{1hu"qH~zBqڝ֌Q3K9ҎG~(cOj2hn):zҎGj1zw)xhȥю=iqҐizu/QN(q֌ ҎҗG\qAG  4 ├(K֓<}hN@' юqH=.0sI'җ?-'Q@@OzL/GIJ !/|P::HO?J:)'{icIG9n)(#ҌsE)0}y֎Rvth484J11ǵ/~oCKFE'zB(QIQҔQǭ.}i;POJ3J^ý~pH}4qZJM"}F)2?]٥wG$dg=)@="` 14(t=(8$~4{ Lu#&Hxh G4$ޛ-% 4t4c"/4ސ 1A=xIZ^QPqMSrF)z}M!vF=i@)yfrI(8iLP&9i:  у)H4G=)(>gR֔Iiz #4w^):RQ((#җ}Z ⌃G@(ьi~c:~4zQڂ;揨i -;d iZwg)Fqף“>w.}q@hN1@.Oz^ gȥ4uHj^1H:&dwJGR8hǠ !J# >tsFz`u9'ȥF@g4sJ8 J"g\s֌:Rqך2GJNph#PHϭ)OoJ^wtKh={QL( Ay旷#I~(83F7ۜRG )&q)ސRcGzQRt4c)8Z3GQG#N94=@:ъ9ґIڂ(`b:(uڊ02x┎)8 Ehh=1搀i旽dP:OŽuJB1ӭ8@xRu8/j98&O#(4j\t日h:(F)h( > /QH8◓A<P:J0xwⓦi@)xǥHϵKFyi2AM/A'ҌgF;u^Q;=h89:y8sAi8J &xIINh((ڎMڐJ;tN}h=8vh4`j旽'b9s@ 3Fi8g){ s4GZ y׽/=/Iޔ}hG^ɣ9FqG/)1G (4.~nQ4(9JzrhG zќ1F}(g^sFsFx=Q((Ͼ)sր{1xހ8#j9f'4&@ɥќ'sJ=(~tI E'~;SIӚ\sփJ rhOh=8v}xZ:(J(34wcIRhK҃GZ3N=)=K!Oz8z3@$s@>ԹsJ(h'Rx(ڃ ҃i{ьF1@qKL4x.xQA8'(h֌qGt^3Kbh#3GQG֌Ɨ4OLp)2=xRKԜ C\IʏlP@t@sސKҐ =JOA@NxJ4:擯ZQ(Z) .p=:QFi@<ю;f"PO?ҐE֎R;}iO&}(&2h8ȤϧJQNNԆw@}iF=)()ԟÊ3(J8=(i3AAzRJ_qE'Kڐ(TJ1A:vz0:sG(J:)Kh^ӜzѓG֔GzA)zu#ir(3Fy3P9ҎsG=<\qIz◧pyhxQ}(h( '9N"q; JzgM;tKIМi)>g(ߥ!K@4{Q!㷽/=Gz9Ҍ(I){Q(8h934R"}ǽ/{юzړx)4GvP:t$uKZ^qGnh <(A(Ҍj(8)4uhǽ J8iZC?w9'P8 C3Fp(#"wphgcA/h"iy4g4ёEQ:JAZ(4ڌьf/LQhG~(i1Iy)H2it=h<RJR9NK'QJ:ў1@G94g4?ZCqKj^ E'OK.g){QzL GQF@gۭR;.2)1J:HN:ҞV*#(8 giqr8.}3:QzySϰ1Gx8@(/b8AZLRAG#OZ$g4t/^MP=OJO—HzP3փ9>ԝNi~9ɥ)qގ٤'CG֗'^?⌁F{Ii~)KާIqIJ(hɣ4dg9JLG&4wc֓n){QyhGSH9gZ^9p~ ԀRu=xT ȥA#8'.p(@`ޔIގ/j:8##IQ߮}sHN4hM⁜uOjL/:{9uh4`u@`㞴c%)bקf=(֎:fizsMh8cRu:{g#ҏJh҃&rzx=#=:GA֐u/j;%^(֏ƏZ;z@G`x984fԜH}^F8g!=9Ԝ=ZN)x֌)MR֗4Gҝ%u3JywQRg'ޗN)x=hqGN (G fǚ3E.:0z1ZN;`֎Ҟ`Qi9P{QZ=/j={PhRǵgbAcj()?(/zRdw gh9/')z1h$vzPG^wI4B2)y)u=h!h{QIq@ziF?L{юJ:QtҔt8RGzZ1iqސbLQ:{P#)!9)'lFqAI>P=h 1GJ?Gj)yҞM=i{` pi;R> bҎwE=2hQy4&'N J8^'J1:g )9K^qҌ|`zsG }Gh:R:(s;>'(dph# >4AsH@3jwn*Iq;qHxuhȣu~(tIK9sJ~gcь1GlQz8i;tҞ)= qJGR\ќM'^iN 'AF9)9gӵ(>f>=))qJ>p1Fy⎜Oz(4c΃Ҏ4ސ=)4 Q!dct=yQF84vғҗIߚ3SH)}3A^hIh\P=i1GOj\R`G(Z9qF1F;撀=i1.@84uf1FZ'@i_F4ьy<@>Η&'j(=;99 Jv=? 1I)i:whzg)QhqFyS(iMf(=~G׭(c/j=q@c9M.z:)=KҏzPi{Q߿4^x#4=(4N(ꦗ1֗8рhF)^iGN('QM4 9?K\zRsR@PEbƓJ@ht) N A8s4FqIӨ=E;ƖdQf /NQ/jB0(R{PON()JQ@!4s9@ނ{RgEph9zp(1ڎJNԘ)q֌?Z:tFx:@揭/Ny=zQ84zLs֔i- h4EM Goz ^c&0Iޓ├)=◌(;?&33KތAp0)E&phMzsE/9{J(ސ\xȤ:qޔԄ~tv(8ցƗރHO4E'CN:Rv():掼fRpz֓<юh&zQw'zRh) ;(@BMhI4ރ֊? ⓓii1(u(N1H:R{Q (Kך?*8J0{=1F{f ȣ ;qK֌Ez@KZN)r1@=sH;zN3Q8&wJN(iq֓8|ۏց9Ί)(hϷ4sHq^&&FqG94g"Rށ4vQpҌJ"tKRt4g98yKڐ9=i6G4w4tFE ֗Qښd>ԙ8} 8EwQAAIҏOցqGR):Rnjw g4g" gRtBrh8G֔ʌsc֖#\iGۚ&x4w4RwGE4^uQIAךhZ\gGcҐ014ǥi0)GsEJ;ތs!u:Rf4Gў(ߚ?` N ^٤/sGz3GzJ:яr)ifA8_9qG֏aF(@=^RѓG٤G3P}HzR@4JNp)zh{ dQtK{֗ўsAIp)@c({'w^R#4 RH9F1PG3^=h͊1G^);)IRƎ(GqAZ:(3Ji

ڂ9GzNuRGRv.{cL|Ԃ1G){sM#:s'ҔtؤA#(dwI@֌}=)OOjNhnhG|gh4 3&NyA)^(.8IQ߭ԙ}hIjNqI3@#1@@R3I4Rdf{gH884)i{fP={RzRtFGz(>ԝO4x@i1J{Q 9gzZ:?Z^AA"٧Rs@F4yiIx'G8ZJ攎:R`)h?(G1@u}(~i}:qA4uZ^ԝAINJSGZu/=hIzcr)A)ɥ~4gRtiO&Px>ݨ#ތ4*JSG9=h҂(җh);AJA=h֌c/;;N8 RuR3IyG^ qF(9p1A'(  (<ъ9qF3ښ1ޗ}i$9G9xz{O"znhi{g1E H:RNgQсړ4IbiA)3NQt^Rc# ;QԘ"LR@(@4ӥ=9Ӛ3&?:Z:):R)H"/AH94&OJ?ZQ֎p) ;(җNi4M.9sGGisP1hR4޴#P:}(ڝFGHqRKGҏN8Rvt#R94OcFx4qI^4R}z҃.yɠuh2hK@@\n㎔GZ3')JHZN\A8i9yN)O^qI#o9/^?ZQAFx{){{Rdth =iGLw<1GQG@ԃ:@:u4.0i\zhRcOj1IԽ3Kڀ;9KR;}J3Iގ)^4v%g#:NFzRڒ٤Gj\RH:GҀi;㜚Ⓦ=x(⓽Ҍ/|{4E'Ҏ@y9E)=($g(ފZRh=ڗ#J09J:bcNAZ\ <@ ◌sH}4:c֎җhG44p(qH~t=8) KzRJwGR@ sӚ(:RMAJ;PGcץҌK:3&yҗ yJ{()Z3JqIIÊRx恌fS"R:N1Kڏ:QփN3'%)s1ғך88'>qJL/&٤4QR/Fhz@?:SHE)ڗFh#"Ȥ=8" NhyP:P}GRJ0;s@)G4fR}i1)=py<ўiGJ3Ic&ȤfK^1ޓ#8bfJ:Qڎ٥iFHs4@4ddRsJNp)1Q֎G)z)0wv}J8IdgK9nO\RǡQ3K}=33Gh(JZ;O Q)(03KJNiq&ҌPp3(4Rq@4f=)8ɣFxs@=is߽4sQ&)Hr3֐xGP)xIڎ3Ҏ(&FF:SZLQfGZ$R{^3G'G'b3Ҕ@sEΌOj;PO旚Cȣz8"qGl:Q!>Gj:P1hi=#8x)?Nt^ڃҎhɣރ֎1:h`/o 9▀9Gz9c֐S;Ҋ^qIGw◜rGG89旷jNP=֗jsA8H=)OpMRh"׊ZAJN)4~4v(1A($g^OZ:ǥ ?J^3i3&㎴tȣ(Rg8Ͻ/jC֎s۵ ;^)JhGZj3 j3&.G֓縥ڌ= &J4/RKK):ҏJo4z@Z: GAHx}(s(h'(#SG;@'4w8<ўԀF)9IޖFrh&㷭/NG&AaNsG~uA?J9QJN޴ggQz(qIK@Rh=sJ}1J=sKړgԽ3ǥ}{R4KG44FyJhIQ&}F3Aފ:}Mi:izv;RA&):cҗKL ӏ^M/|f@8Z:QތGz9"NZo4P~g(<gڎZOҁ(=}{QLўx'| qG`f ^vz:O9qGH(ѓ3c4v)u9߭z\)OiA((9c=xl94hp;搞إgJ;FiqIҎ3B= F}KڏJ>(h=z4h 14v#KڏzAGV9Fh'G&IA& LQ)3G\PwIIJ})AsIJyCғzRM<6=ipsQJ8 C\t=yE8Gc?JS4AisG4Hpy F(F)1=gt4ZH'Ji:ҁGsIxR*^:GZS'|Qu!(ϧ4}s3@:U4u^9<){u4{ъAҗ GR38Iӡg\R? RiH %(掜vqjZOz\q'j(<;f{u=)}KQ猊?*(-۽)w GAB;ix4qQRRg}hǽ.hR(F擦8I(hj1Nh}h摨Py4dJ?Oj1^'2:IsK:vSI 'N (j@1Kz(JM: (Q⒏Iiz}(#=ZOj1@ ֔thh'z^R{Kހ?9E%/i(q@ҌFxAӭ/_ƌvG9=i{SOJSҒJ;O4EKFp8=/S\uF?*R});QR)ȧtRs@IK=(#41Qގ})Gjqy`m/J:4b;QAZP8i~}LQJ:JSHI)F{QI8s ExPO>JCA)G4֌EP8zRH:ڐ斗4gIޔhtZ?h'֐{ҟjJ?Z3=^(CA-'QIP84ւ3HqҗRfғ֎޴ތs)4h v/~i9RuR9R;4ҏw擿J\֏֐)3^q֔q~vJQ: Lp8sRIPsޖ^(h^w@< QIKIizvQAԣQE&FNhҜ}At.qҗ1IPzuNiGJByg9<p)H1G4NR(׭)׊;r(#4vg&'8G#{z3GjZ(8RgZPsځ 9ZLt(zњ 'A(9׊Oj3J1?AOJZ? L$)8i?9gG4dAu&ȣ?J84:A i/LGGҌIQ8=h@I(sJzQ)Q\ޓF:QRuh=E #RzR4g=('h!<;84G4JLJ_8ɣޖ4g I1)s!Fh"cKޓZLzj(wr9)h{RsK}(tϽ)4g(ҌKڀ}h84Fxڗ֏z\ JJ1@1G/R)JAN(iA}h4u{F8SGCҎM'_—!is_J^RQ)qw4Qь(<0;JN;f9AKJ1Gz(hӥzџNRF((H4ғ4Py⎞yc4A#(/4~4 c4g(<4&bg=;旷JAJ98I@/M&iqB((g8&Fh(ǥsKQz(ZCQ֐I4ҌRQ(أԼt&(i:ۚ1җh48}; 4fdz!(;9 擯J0EҁIJ9==M&8#PM7jPhHzu! &◿JA4)G(\);qEt4uqGNh{sKғsҌKIǽ时hzPGnޓ>ԽR)21Kў ;ށPO4qގtgi3Fy}(i?.0? Ps23IG{=R3Kh4FGJ=i9Q(<@4O=(!: ^qIGAjOAR9(1KڐuQE'4vA?Q((bFy"y擌Gnӵ/ZJҗތ@r(:qMT4L^fA4Nh4S@4w(zAGcFxғ<(riAvL\P:ޔ@4wFq3ihA)8ўi):&(4(Ic4ۊ@)xi3/(OZJ(=yϭ'NiytQ֗\qzьR=揭F 4瞔qAAFx ޗ8h9GlQ)=< NNzCޓ{Si֗Z'Z:ڊ^fQKRJ1h'4ގ4vqځ֌w4v_!yIsKۊO4SHϭ/ӥ'~4J:L{Ғ 'NvZC@48uNZ;攚A@~ 9Px@Ri=94ci }?OGZ\ǽ0i<ސ 'RjA<- Q۵ Q׎}(h)y'S׊^)cKIQ Q߭})OJNأ`P:P}'czL ('Py=)%Iӽ)ϧ⎄uKƐ8'9FN}sNsS@{d99Kq'/A@{ 4TJ1(G;RJ/:x4RgZ9~t4>ߝ.}hg()=H(h)G ?&9ފ hN){rp(ϵwgvԧ 擯CIG80iG4vG$֎Ԁ{iyғ9&qtӀQPFGRҗ Rw& =qKRsKi?\QޓhqLFyMx֗҃4( ܞ€1J84K@9`u)?NҒG\QJ #)z})qQi1G4r RsGnizcsF1IGRBpiGzZoB}ii v=4 ڌA<;F)1ޗ=AA/{b"sJxt&FH<)y&h-'4c=3F9bIsAJ:Rt4N(kSigima-1.1.1/sigima/data/tests/laser_beam/TEM00_z_23.jpg000066400000000000000000002345461514013333200224760ustar00rootroot00000000000000JFIFC    $.' ",#(7),01444'9=82<.342 @ }!1AQa"q2#BR$3br %&'()*456789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz?1 14GqIJNi Ǿh)G=8#QIޗ=8Γh=~O=rc4Ŋ^h('gJ){RJ1ךN^{R~4sր2)GLqG~13Iޝۚ)?REfOƔQۚOz)qHp?\Qޔc4ޗGLf)wJ:RR)g(s/~~tzR iy;ъQFGj8 LzOP{Qގ4nh @#=(jSQI@iAsA?'9Kގi3J9O48ZN)~c)23@9ŒQڌzP884}hM/G4(t ޓc4phAyGj.1HO4:\Q(>ԇh'COZ)ǎE <9R#J@R(=8{RSG4v挂F)ziR(yP=:\P4vz h=zGI܊\h~4g>u9&&/CIJH4c/aF8FG攜ѶFGGJ:g.y<tzSOԝ:8sPO|KZM/P0;\JLQԹiJMGJ:E&sGM.F}(=33AR )8K⃀GA8w9ҔCQ֓h)٣?J4{ۭ(N(R҃ "— AiyR P;9c“4w/LQr{H=(֎ PsȠphM$u94tǚ^&;PzAL-!=ҏjOuҎi1փF9F)(z^IzRc旿4vEZ@8(ZP}i4wG#Rg9ȠdRb4vI(֗'Ҁ fg*HZJ1? NvRxRf:8qAך(ց\яҏƊ^? ɣQ(PN(hh48挏”RsR (OZP)=h⏭!}hҜg (җҀ:c\zю):QyQ (EA(84QzR8G"Q@zP.xc dzь=)IzNx-Ad(>c4t}hJhIZS%.sG't㿵 :GQQHGj0 ? 3Ҏ(POGEj@(8/Ҁ9ⓁGJO^>c⃌H{bG<('{QuJ=ZG^w┐&F3GZ_Ru&zQIJ>P0(zQA=is:RwԚ>IKڌsGJB"duR籣IJ Nyzz:J1ڎIEgRN3N#ޒP}zR@E⁃҃RƔPz; ;)qH N=3H?ɥ&AQӞ4ɥ)8 sIڗ'Nq֊ փGn(}4QEyȥ1ތs.xb =:RIŽϽ/cctӥ'^1J=(&!JhGC;4SփL(K֏zQI=R '|-sG|z'iNp;O1HF9}){vhKA#F{bsKIsK@0:(gޗ9?Η}isKۥ1h4M(G~hg'oJq;RsFqځ\RERҎJGAI@84L}(ъ/9>Rht);ph ɤ R '!ȥtNZLR)i2h u4c&qғ@cAߚQ֐sZSIG4EցhqGSAFE.)>4cӊ\zg=94ry.=g9{NAtP8y9}(/ZJ:R(%ԧi;t84q@h#/AɤJi1F;h)Fiq߸Gl AӚv8iy=(>ԸNQ8֌JFp(jhpM/J;r(#Z1Z=ր1GCKښ4I4`Q_Ɗ)"RQ8)8Q@hFiz{qɠhҌ֎fOAG~{QzbOn~Kh=i94v9 q@/M7!݃"挌h8tt Gj4{P2h}ISrsA/SOKJKQߵҙQKIJ;~^=9GxѓP0)~.H4=ݩ1M*?>()@iNxHl/ҌP=x@4 ԇNi=GҏƔ *(G^gP:R0(&;֓J}4gڐizǥP1x9&rz&ri{Rc=){R:v4R(Z\RQgP:9=iHzQIьJ^q s֌wF=8ɣ==9x=sG4ciEgJ> O=(GP9ϭGl{P .;IF=G4qwjh9'4wItqG;zQޒL<ޗ҃g>c&xZ:P(Br{ҁ:J8#.hZLcx'$P(?B(8K1ړ)})Gփ֒sKڛޗޏJ@sAJZ Jyёj:H:ړ9҃@KzNԹ#)8GcA^(L)wg)9sFG/ȥE42JLQs@Q}(v)4q(QF=0(8RA<>FGAAs3ҔuA)AsGz8` Z\qEg'.(GQH@.1!\ԼI4F=i:u4vG׵'~y/G9h=)==GLQhPGhKp֔)01Gz^G4HRtKv LGQA<J:CdsF9pM/^ 'AKӑ u@փ4gچ9@fGz^)i C4;P4zҁFhH:ғ8xbR:b揭/lsGJ)S斌Q^3/^hx<Ҟ掼GQG~qA랔uQ z}=:sG4J1:QК1?J3Gnh'GIGsKG'CQ֗JCҗ<ޔbޔJ1Z1ךC~u=3H}3GNԣHҐKSRRmǭ&94Eq)\g\Qhw'4sޔ!KZAяj(w3F{0hN)Ht Qڗ׽&xsӚ_cFhzIߊ^)xҊCQAJ;):1z81IAΓR4vIIڌR`ӑQAGZP}'|P})z AzPq֗=Zni^(}(>⁒=)@sQsF)OG^)@iZ9SҐ2)G^(R uJ9GqHx4ǥ& qA&O4F1Fszޜ=)Kۊ8ցҌciqAlRRihցqG҃RGz^{RSҎ"G'hgۊ:9==(Ȥ>wҔqIK$ A{)3M(qIތRQ()rsJCGLߚ2Oj3֔r0)(h(aߊ1-&}h(hNIJ~H=h<uGE .h搎(i/Cg=(=rzQc&0sE/^)9KQIG?'jF)sސRt>ԾԝzQK֓wҎԇs@zҏJS֓=hGg?!&g(){%ъ\qIRqi{OJCAh(;=ќQ:Ҏ3F4t()uKF0(h֎ԧ;cCӥ/jLfbs(ZZ1!h  QӨh#4R8(iAtZ&:bANi}FOONg9QFi:g1J4Qڎ~z:RC~=Fizvx4u4QGNF3:Zh#4`-!ug&Q}'9.)q77:fȠ:qZ:RC){q֓ڀsGix&1Gz("P:Q=h((y`A:zQ:}Q< =>94ɢhbi8'vJhPy<AI旯4=hJG⎔}Ez4zh'@3K94G==hqAQ);Q'J_i14s)17Q(P@Z2:POJ3@.{b㞴ԝiz{яJc^y})HZ;Pz8ғ=x"cJ:JC_Z1@ސ=.p)1ZPF1qQHx@J'4tFxGўcGi1NMOʁQb1Gc:sQǽ4ޖfi{RQڃ@1ސ!7)(9<9L sJhFq֊2dE-/QIF\ftu==(:wg'GZASӞii1_΁|QڏNJ^IgEG~h=x'h(wQRH8(}JGcbv=(`s}F1@{RN))“JryF9xt=8=(E PG#($ߚ;){R RgR'gZ1<==P(PxڐP@G2z 'AJ@)0iON});f):){9Kh<((/^dRcjQM'ҏj EsA:ڗ()441'h44`cތujh#(F84"h֚GqKۭt/NJ:Q(Gҗ8cڏZAzGj\dcZOJAPsցҎ֌\c84'/JCڔ=E'^xJ^E'G$sH4)x/z QH}}iz4(<@sKM8;R`&=hRJj#gQGJ3?&}izw)hϭ }(ҌsKIh4#hZ=ɣ4b z4 /JNc89(4 z擾h/zC;RFzR(F0r(4g'=F(Ҏ=('=1(81׽ގ;R;u@'m4sڌsGҗ{t J\qN◃INQڗzB=np(@AJ\4Q܊1ir=(>>qG8:GҔ҆8Ҟqw҂):旐z8ю94\sKKLsG_4){QGjON999`b;:@ށҎP} =8`RE73P3@' ނqF^NO4z)z NΊ3Fyd3H>Zu% !'Ԡd~4 Ҋ=x KH8&Fq4 NR3^~ҁJ}փߚi;N#ޏK)=w3 ;vAcKс֓ҀyA1@ȠiO~g3hNhgQJCK84_Au=(ytu)s1Ip}hҏp1AhF2~KRz;Hz֎ԝ ==hG84R~0h<׵;掀P9 (KqGZZAAb848Ȥ 5/(ց֊@`NJ^zOn3Nj@y惌֎J^vQG4cP~q\G@3G|S78/ցPiqzQi{Ry84G(>cj3◞R)HGSךEB);㩥ڐ1Q׎iJJP1GQ@׭F(ր9N)sڎZ=i>\P &rI擠т(ɥE FqGriWw?tuҗv֓㹣ތAE玔pr2(/wӽ'sG~EH)@#Kh==ց(&ۊ:u4{sI>`iIlGjNZ\H}Ah QЊ8H4PO|R҂y{R (c);Ct? 1ϵ/JC߭EQQ@<тzR})z}h~)"֛ڔҎԀqGJ\Ύc;ڃ֓4nh'C@QZ;t&8֖}(HN>)84sڎ(@⃚8!ⓑތg^(=iցZ1Np(֗='KIK8sAAIN R>``FZ4Qf}('&1qA4(94lގ(i{c3(8uҗGCӚS҂8);Ru9}}NsKؤӧj;Aj\dbҔ dQZ\Q⓿IKj)s4RҐ9њ^)h9$N) ;9֊3)@ 'NzR/Z8Qǥ!qG>\{Rg)zRf9)=(֓QߑA<sv4{ # b( L.q3GzNqK֏֐ǥ&x4JJ1i>hсh9'4qK h&0(:JA֎M&7ⓜҔ{R);zQhQ9gLw}984֎4|z`RsJN("8斐uE2(ɤdN1h4t4"Rd1KzNJ?Z #gM- hZ_NJCu=)GZqI0c֌qKHE.s~h<ڌc(^яZ;w=iy(&(=hZ8s'Q4ZN4 zPy0/4wIQ'ڌqK84}zu=hZSւ9ށA$vZ;fҎzҊ)ҌsKz;Ru~€)OJ@3ߊ\wt=hҌQj:'Z^i8qG\`uҌs4:P()gۚj0(9>G\qGAH8di'48т(GڎZLc.8HqMI;4qRRF)3AZ1hxҏzLcގ:b`}E&yftQ֏oz:''q1&:ҐN .;h^u#PGH8ҎO&1JQz~4uvqKLd`ёCݨ 1ciOZ=&=/HA=(LPi:{њZZSށ@p()QQϥ'Z^EuN3ri)z:=(ڎ:bgG9”ւsIQRnvH>cJ:is1H@G="}( ASni/9RaJj)M%ib٤riI98'\P{f/AI@$tjL9i}⌜<8h<;ף|QKT@('hE֎JBiGLR8iN19(Gnrh~3J Rg-ҞhCG|:N(z n3N='dgh&}8w馌hsHzii?(pq␞Oz^E7SG=iy'Q(=֐his. F@ړ$J>p'Zg<: )Z;Խ裸GҎ_A4j).=8Tޣ^إ'A֎? FNhH;qJ(Ad' K֊1A)/Nԙ8Z8?QE sR8- =hԹ4Fq7KGP)zQچ֓ғSKG9Q3=;?*QF};S)A@RR(<z :Qi;F:RRRsRbQ"IM&0=944d(?})4M.OzZ1tۃ.}9ќ944sڌQў:K=h4^sIJ:qGQKG9 4@zhF(8KӧjN8}y2:2zӚ;u~JG'GC=1J1ϭQzK3I@JsB0x◧AHFEbgҗhd(hۭ((փE;;R R2hj1ۚ:R4tu.3F8PqF;SysJyuђ)H= ך^h(;bZ3OƌqI^f>1@p.1Q4J}i{qI\񞴇JoSJ2N)zhz'.i8 =q;>tbғʌ zPx G&҃^AH)~):ԧJ?9R^n9iǵ LuP1@w'z?J;GhI`/lRc=FFy(4Q@w@3HO<)0=)G҂pJ @IR .i8ޏSGҀ=)G&1tEp(8&B(@(֗#FiIށIQJ:{Kғ{G/~q  9*3c.xG8&<ю8E=)GzqJ^icPO'84{fqF1I׭(z:Q Q\qgiz=OjAh<.qIF}@>gvޖIE.(ɤh=qIN=h#AIZ^ڎ>ph#gQIFi:{ h<0ɤNZ\ i(cފ)8KLph<OjJP1FyJN=(qG ui:Q@'=)3GzRqM'jSA=g?v⁐i;t(9֐ZLzw!.qH;KQzLbK^j?&0iGh9H;'AGhHq(4.{@f;84giA>&ys@j9h4P8~w!)IF@>`h'4/R3Ҏ(댌RcӚ\R֐RN)A֌}h9c\ѻN;gKڀx Lq8LsJs@G&Fiz{ R)1擯M&sPi^)4ӚC ;QP=㠡G|Rg7u4s(&:QӞ8u`/rOPsFh8< :fԝӁ@9{ьўƐtix/8sKړgҎ#ގZNsKy<׌h4Z=:3ގh'9AqFhE'cKZ01K(RRdqGz.=)=֛Kh據3K))O3';1šzg=)ئ4'=)ǥ'~pqb=(4Rr 4N>: Rw/QΎ2}OҎ{ъC^ԔzZQ֐ztgchqx.;dfZ;9.)1M/Z)qN(1F'J^^4Ԣs@/jNSFcKڎQ擟Z\:K}h{utF=M(='SGSGAE/җyޓowq4R8CGQ@Pzw3M>t%EqCJzQ`5{PzZ\ȤJ((4⏥J)qi/=sNց(=M&>g^!c=wngb”h<JC(ɣz>4sAIp:ր){`ь ۥ{^;Rppi}HvxG&g('hn(#֍ڂ{fbIn(I)t4t/qM)Q@}/lQ8< 8M>4qJBAONi@/z:(w֌ {Rhݞ)F;Fi1ҌsFs;(v(GR}4uv^=#4J3I4)OOj1:t :q@A4E//0(qSr? S1G\wJ@4v P02(84g/h`Qq((QG8FzQSȤ֌tJ1J3uKGӯz\Q)O~Tgh8jy!iz㎴zKԝ3F:;Py:fRv֔R1s(v!ס=i:f49R~4т: o;N8L҆IP1A=i@tbhIЊS{sKGN(y'~j^h(GjCMj;JLiⓜy< R'i}<:QN(JA'J;=zQg;~g< Q<)'J\.yR qIKNP:RsF;yI?q@cK߯G|1}ǽ'j^֓R`r=3R"'=)#Jp4qCޏLҊNs=)^ޝzByG4FI=h9n(/H =zP !?*A1ޔFy␚\1ւ{h84gGҌI@/s=1@=y Iizw43A⌜֓$ ^@zRIΔ98Z G?'^ԼbǥSI#{SIiNJOƐӊ\8Od)9ϭ!<{}iFh=4qQ&imu#)zPzf8tǨ{9Ki9?J^Iޔ`u=\~~ќޕp0iyu9K_sIIޗzJQA RQH:zҎ /~{QEgh8cq bx9i@C@iGQhqFZusJ9(lR1H1ڃJQҀFzsC)rr1AM⁜Oj=(i{я/HO8ހxi8(^J;RwdSGzF֓EgE3 :}(Rzҏz\qHNh8@֜F( &99hJ_֗F9uHr(fj֎RsvGb 0zPz֐zP;fs1GzZ\qhԿJ^(Nh'N`zьQ׵/B(%-: 9t}{ ;=)i03ڌds@u2(4 {j;o4)zF9;qIKڎzPz-A4hGNhz hcGc)#4h0ܚ8=})JWzց\|yqig1ZOz^)G9F)'|uJq#iޓJP2hhϽM4tA4ڎ1Ҁ(#9)qIܚ9j1Jr1Lt4$*M ސzQZZ==(ǽ֏ILRHs94ʐh#/CNh$z3ɣ9JQ֗qIfi3Z\z(ȣhޗ9ъ:-@(<ьh#h^hZ_H> .}=hm@qIy4ؠAds'z:t9(힔Gl4=)G)JLhҎ=(RRR}E < Z1G~FE qьP>Z4qI^Ԁ#4Rhi:H PҔGz19h> RtҗH){Lrhގ?K֛(Rh zۃ&~uɥ&N1қހ0)Iғޏz9>v4%;4 4Gz@<㸣Q A(#s)$C`lP;RF1ڀ;w=qG֎܊\94SP4QQ99#4cGZ:ށ4z?*h)EGS֓攊=揭֕N?Ɠis1 sAE7%qJ14:QG8 Q>֎G')p(tҗIKM'LNHs(<ҏɢFsj:RL^iM%G:ў9֓ 8A8JIE4H3Iȥ'K}3Nǽvipy9F8t~4qތgiRs֜: R? 9Nrsҗ(F3҂xC'S)i2 RgqGR)1Kz}i"@(MoJ\8iGZ3G&=KN(8.pqF 49&1Ki<(Lg4p)u&z挜RLtyMў ? (8ހM8@OqFq($4=~i9M(<(i:iy4G'\KI-hzR`c<JH#i}=h'ztPz'u4 SҐ~A):ҁڊ;bڗ&9K &ywgw۽(j=r(@⎃M.xƎRC0ihRQߚ^P8^i{cpz:'qKZSAFzQGZ\Rw{QR:H}@"'<ҟ\Q)E<(Jh=&rMvOF)@F3֌)/ր1B?*: ='8KNs)9Gj)8#p8#i@:^ؤȠEh4qFxQ#h=8){dO⣹ӻsH=qIzь=LE!#ڎP4N;Qҙg9&1ҔtGz1Q)֔ǽ/h%S}lt3B8Nx={R֗(QNiJSJqHG(:014ގ HϡKiM"ZRfAS<A搃I(I~3i;RqF1@8֐Ɣb x緥\:IⓒiN')O1Rgj^s֓ny44#&9ߍRh3I3F1G'֓QKA4})=JLKF=(t@zn 4ԄzQ֓)@:f~KQIz\qGc9J~fIy%JNR֎ԣsHxZgJ\`f0(rM'w(H$Ku4ih#ގ9E>iG=i}=&OJ^E#t ?(4H@GJ\֌zi@8J91()c'ȥt)G&{旧isӥ`P:udz94g$>vҗ֎٤4vRFsӚ1K֓FNx/^M)K(QʏJ1y8i.3MFўh硣1H9>sIJO?@RuA8@tu ўE!#"r(=9:֏cH-ץP0 qK4џj3&yN1I y&\w8ARwɣ>~~4Rރ֏zQsIۥ/I@f<x=i=hQi8G^t4rhJ@4sAM8I78Qz@rzR/zҔuKv'4 RvZ1)M.=i$g(zQ)@=ZLgޏh@Ϡ!8z~41F1҃K GQAj3;sF;Iߎ㠣޴4ړixph뜊Nvm@zюiGғ4's(`>H>w֗<.9u'`@qA=G4}z 8IJO^)v1{RF=iGHQׯJB0N(M~>.ri{P1A :Q㎴uߞ@i1(G$2;RRQр}h`i1^ܚ;c4cqIޗ9擾rhgЊ&42(q7֗$P}MzPA RC@⎂)i;zґAA>.x4GN(F=8fr9=Kב׽94Qۥ`P:R)RG^)r@((F9OZBxu~RvLҎ{Qށz4tPGQڔ @fך0(h'4^֎c>Ԋ{v)3K:QKG^QLsKѐM.H9FGGJ:# E.)?P;R8◧Rc>)3ZvsI.29u4ќ wG\sKI"6 JQ!9vR'сiF;qG=bF)qHz^PrE)sӯ/jSցK8)d;8S99ڜ)ʸ84lj]=i gL2)HR:&54xJFP'3曷#4(zPG4w搊NH@FIGz8siOJE^8ԴSH9h4J;4(?Jy' g'zQϠg4q:юA$8:84qGQF0(~4gҗrE:;4v@K0Fh)QIJJ\uF88=9;P1R(#ϯJ))p:q0:9=@KMxJzҀ3JA$q8tȧx\Hȩ@OTR1G1=Rdԋ{x➨{PƟS< #1!'IQ/haAL*N(QޘԴw{׭&@uZNLqKKѓGz:3):wM b=iIjBG@N;oCKRsɥJ):K΃GaAEGb#}4ץ&xROa()=ގԸȣ4QA4"{G8 ?*FL8\J97 n yhbqQG G,x9QGCQ:`vqOZv2)r3A晌 (OzP QIqGz0 G~sH1ўNhA4cޓ5'p .zԘiq ׊N):Rt4h1IҜPO/ozNQ1IqF{RB1@qG< c{t@4cIQA8(R4E)# ך;RwQJ;Q)CE֗=:=:ցZC׏֝=i2t;Pz(Fh)ARF:h)}QސRsFzJii0h/&)swqތ4NݩqH;K1C`cҎK0zpG&Si֗'dZ\ΗZCFih+x`Ӈ&0O$S TxJ<cާHENS,\bJ"57>bbg>RR`ғH /I0a@fz# sKcGj#4dsKp)@ޔڀ23N۸SHHr*.x2YHxMYXTp=jGV<:*ASGaҥ:RyJO#8F9iP# [l `9p܎ƃ)ҩ4N5TGcC2z`dbqңJ QQ78'Jg'ƌg>M44rz<4;3(#hqHyR:=)Qvi◌( L@ #4}'sG43GERJ^ :'&RQJ?7Rj:i:qG4r:Q)0ҐfRu:ҁ:RwJhǭ9tz!46Z0CPqz1FzNc494^RNԸ4q@4q3ΌP:џjSցJ1ϵ)}izt4gbK4"'J(@p 'F1qKΎ){␎Q?qK'lb ^ҎJ=?toh3;҂{Qz>.2ix(;Ґҝ{z`u9ڔ.9<=iH#x2/=dSb4I10qS98Q*xY[~sZTV52;gTP?ZR 8ÞjMjXBRu :U_/h TNJjmyS]O΢E٣q@Ah(G/GAHF\sH)z}h=֓J\F{{Qڗގ4ғiI&uҗ({ڎ19A4/jJ:8h8r:bsF2sG_jR:Qϵ((4ޗ{Up n8S$xSTW"P#҃i?:F㞴2S i9LdsU]*ɃTeVJ]u8Ү}TODJ7qQNxq`@?#5Aw@QIϥ.8J()( =M<' c<?Z^h9R=)8)9 1 LdR4c 3F>l#\qҁ֎hGҁ&99 QӚ\K:=F){P0>G~:QbqGnzR:(ڌg9=@=zP1/Kh& t)=8c4ҁNHTʼW*h95iT1lVNjj=h3Wc;USLz5*Lr*@)6`Ӽ).zPS2HM9#Ə#Wj \T $9W1lVu$p*֡`qP3g*69c#4g2Mh4/jAKg <ځFI'$R{O4g<>4QOƗs39;R{Rc֗(4zg9v4:c4񎧚V^t" j0@*i3VLqڮƼr9V#NyZe:=jdSSl*E\qRm㚐 zЫNeԅ2=6ҘxTe2:T T@'NsT>}$wj*ب dn08Py)›֚y9x4֓ސ8֌4GqA?/I9~IރGR"dJHIڐiH4无H8oAPH3K^#p{RHZQPqҐzh=)Aj3ڛ/ҌF{P>Qisx!Rޓ棜փF}i=ўy}ǽ4')4r>gPy_’CKLH~^(sFsҕ SvF\ 11Q0/5Q"0q֣~5Y8^\nEShB֨\>j2sD g^HUFxv"#98=i3EZ=JAhғJAݨ:Ps)⓯QQ߽"C;h !K(>~QI{P}q;QךOj(G(0~`9(>Rs)OFphhǥ!Rph֊:ƓR ^;ޓמ)gA4AJNM/QA9z^i;@J:1G@?J3?uΎzށ;=Q qKjSIޗ%((H-4Cɣsiq= <P9=@gږ()ON qNAd)9fڌ{RRu4zӇJxTT`tAV#Z-ȫh#ք+*I8&0qW"P1VQxVQsVQF1V2*qS\`҈jCI|4`qL6H88B2BE7;j&2@{Ub>nj98V Zb\:f'ϥScSp fqJNUV4QGzN恜ҞiN "3@9&\ nr3Gj\/L ;(tz<=xJj8֎ޗ)A3( "{: N3ޗڗ>ԃ.(>Q֔t:мtjNsǹKߟҌޔ`F2hhF}~qZ:bq'^)GG~g=h.AǿJNG9(JSҎøi0G8W5"cF;ULjaH=x'5~zЊ1/JUstG'͌TCT8v҅C})N)t4N{fqP A\g\S 7z˖P*. WJ1RqӚcUnA2|LA 8zt#< IG4*a0df4j1VV#T{TU>nN9"!U䋞TMT/HMiUYIZ*&0?P$1r:U''5^F;zsUUUbI50Lbzf>M4Q&ގ)i4t4`h#);攷&4t=hH:qGJ:)"Qtޗ'M<8@'|ҁAFO~gҎi4ڌN)qғj^3&NizQJ(΀yR'8GQ@4c1!H:G988ϥb:zPzKI{'ڌf`P=)&)z3 RI8ڌfRF(^)0 >iGZqM94ӭ&?C(#HZ>qNZu~u*RZr-ޔzќ\JV0yd*3U@sU8(U>9Sœ*a2sUOGj0>Y '\cTDq֢n 4 {SZB:cIdv޼Z^'($v#)ɤ4g֎G#?&xF}i;QG֎qA`3(Rp)1ќs^4Ҁzя6#==(4c40E4Ǧ(#/CRbTzҎG8 SL{(=);zR@F3GŃрp9Ҵ"&1VҮDUӵ]j/~j(Vy*TjE1*jsC) ֘ d`qP9j2h=껾Idaګ3dUy5Q9Uxwi52*ZAsUMC"{tB{TN͵aL )cAh )1oz:Q`cZ1Iߚ_oLfg=ԝh)9vj8P )Mюh N:I>P2Gi@sIt4z=ޘIRFONn;JO4GzQudҜR31Fzf:QHOt8/JZ9u_'/z:u4t8.0 !_Ɠ<8ȠdԽ /&;r=&=)3FpisU;N(Z\Rqۭ/oZ==F:P9QJ8"^h8=)@\zS05"AzgN8Q_p*8hB+B%YEڭ9q *]Gq: bF+qR)J fwqPIڡpzUW\0sT2jTuNTe̤*Z̑rڪM⨓y[v8jl~̌䚍jaTD隌|SқރM'ҁׂ8f3ii}3I{qAF㞴!Ҍ{փ@8j@uGniqPE;QjKG Q!\qF=K p_K8hN(NR3Fy◽/^t4֗sW#nv2\[fG1ڦB: N2)ؤ=**=zTREPqU O V~*  Uw=괏5Yf$J$)˓Ueps㏭VzF׵C2j6Fqc"<iRg8'7ΝFhϵ'Z(Q9Oޤ)C(j_oIu֗FFqGSҐRQ4f cހ=vGy4 ^sP:sFK\>v֌ 1Kьu83@ҁ(1/n;Rcn3WkBFcьVv9[cZ[H: Ք=Մ9 rN^jA!)|HqJyޝM5eiCi8$t8Q5]֫ +UȪҜIU&#QJaLW*ZOT0}*g㊯('QsQ7fS vh78=i~c!ɣ gތ(4҃@}(?'\=)s)9QL)IH}((AG~)}){QߑқF)GNzfcKɤ8t;gҐ3ޗ#3RbI)sFxⓎ3ڗhP:sIKy>LsMsFxhO@`bN2)#^v&qǽ{`sn(RK҂}M{RBiiG4zҚ14` S@zRgM(_zLqJ1֗ tGQ֌z{RyϥAԞ٣J3Ssڒ/ dG/$bҌRw/JiRzt.3INhޔuIߵ/:c4cޏlQڔFM9(4c4▀89)GG4t&H9Kj:t'=8h’R’旽'z0:⌐(J(ϥ&ryHIKupqKJ?JC_sA: 1I߽w& /qA#>=h:fdP9N(=)GQҤtW#2TIոfDzc&B@jOZojb92jr皷VcjK5:=*e=dԂE8w$ct0~j3: ZFsU\c=* jq/CUUyXjpy#"I/~UWB 5 QHP@J*7<9OJq4sPi#=1H:sփ&(T4J:hғhRڀ=(=JL`Qړ&8M=M 944t4gqIʎw/CHi31F{p1M#?J\Pg O~G4:p3֗9z4Kޓ>{Rv4҂})1G{Q~Q:RIޏZhђ{RҎwQIN" R4Խ`G05Y*9UFe}+2pw`9WRz;櫶GP1䊉M0)|l*BGxP:S{餎I=i?qF(&yl2( z~4ќR8RsڌyQ~:LPsP{ў(4CSGq ֌JN9=(GI99]QJ1J瞔FJ{PxP)9J"#1t(<!ZTwȥM# Rtt=NڛȥF0hȥ'4;G{ўiFs׊)i6\ufui1iRQ/v.):4hudA'RzRqtuiyᏠ"x!){Rrx#֏sڌc)^hO<):sg9iG4uR1r ryN=*t>eoU8Sq6O5z7Wbn^_*tl(ݱXG8Fy*eSϵHԃ)Aki09=/)a!C1皌4Ƹ8ZO?y(栒^=ɑUe`IeHT`GҪϵWjcҠ~3@F3qL 54izIiF?Tuր01HqK ?C'jQ)׊9/4ؤg&F#dt擧j=E8搌QQyQm/J:( }9;/qAI׷4dԠIGCzPqLQȣ=8Cq`4Ro΁4 #iܚ2A⎦:tR 1ji!(8@ӎph>p2hiL@8 :wN 4x^wi{ǭ4vozL$P=@(ҁMM.4r1F2(hubhry84h(=i1֎wAwN=içv~ lqR TzՄ|犰jrjr!L15n9{f+*852R'J Ȥ)Jfj"yjc?C$GWs $9_ƪwT>G_Ƣ3~LIl:v~jnj2Fqa?&3ڏ^h9Qy<斀!JLN'AԤ*B2 b)G8H8gh(Fp>zv/jOʎvAGjɣjRg(cGt(ҎJN) =1A@sFi;RCC78~L.s qKA֗P:F}(;Қ@s@>NR֗ԔS@& Zz\RizQ3I/lRPM⎠@Ҍr()zj3<{fiݳIN)OQ:Lg^֐qsQG#F2NhR@hϥ.3@b(KNN}sN3R!T4oǯ5:9<՘V㓧?Yc5j9Z~=jW{U>X`0nAV@{Ԣ\tx@)7OҚ_?Ja|S5ZVVGQϿ5^F9{PǦF*'ץ@IYG44ܒ1H=M-4 R=i^ !HxъLZ;~8#qb9Fz})KO\PMt}M I;M4Q֗8$Q}4sA(4:LuqG :sGl'GR&h=hu(?ʎH)yhցsץ'Q;FZN);sK֌wQ׽7 =:R`sJ=h4s/Z)8Z9K^#Kރ Gz\9N-}G=H}Jȥ-'?J#4;JN{{(){p);iNsiGH:/_ŒF8 _K)ހxM 4 qddPiѐF})Ҕz xZvh1A=iSIhR{L͚9&3y{~*\ ?JQ<\M>{FQpz,56I$AQJi<֚y4ƚ@) &Fi9&硦h zc98<)AJ:wN֜=T H[<Ԫ⧍񞂦ZS=jefR yR"͓Ks_4R8n9Yn:DXϵBXQ*=sL.NOL.}j'0@4;OJhoQ֐M&#!<)9)t旨4z@=O4g&Ҟ׊)qi})6Rc{RޏcҌ|—׎ԃgiqN8r{QIӭ)GIG#ўM֔ҎԼpiҟx<>qzO|Ru4dPzudc"zQvځ(@=43Iz2z(#p1ڗ oj\L`Q^;Р o<u7"JsR cR,S~G".zӅ=h@4}*6gFuAzEzlFBXL$j,j6nxlz{ 'IiJNqM' ~TڔM479=KRg E)ZL8; 2zюi8GQIӞip(M NhRQJS{vzOaҗRQM&iHi1Q8 c Rf挊_1)8qKFqךLb=p);J=4b֔Nq8Fpi;E/֌{?ƃ“.xzLȣJIj.xHE)>((gsNE Fy4b)q`>JpHs֗Z\Q(=(Ҕ(ێsN((Nhѓ(JRy4cZ;@ph4Ґq֝:JREȣ'u(>iE~TތG4R;w^iN)j@izbSR+sT7^;T@N<>IyN` ]8qJf!i&eL3dO0N30:epiaqaq#&)HOziy&xF(t4JA \c(#4_z3龀Ӻ*3)?JHAǽ)/lfŽs׊NJj>!Ƞ?@qKMQQƎQ? \x?J8Ru ZNցߚ Fx'oZRhz~9yu#wM$=hRg44})9KP(qI4;4Pގ{яʁӥ.=)(4惚(gJ('ozuHQvfiEZS4'.z: NE'^ .GLdR}FqGN( 7$4 ֓qJZC>GJ=N {RI掽hNN~`ޝA&=IpsޞjE~:1ĀIE8>yڜPFiwךBRno97@RoFi:sZ]SI}iz:RbG\44␒N01Iׯ:t4viǽt4;gF 4{RzрZ>ZQuI>`z{QM(QJ8ǥ$cn3r(iHAIǭ'NE҃IZSӑ ٣(=;1IZ iy#zLE5.2=RNƓJ3@#^УbHN){h'#)=ތr)I*;yQ^Ծ>ÀiG F{P:POE&IޗKPA\PZPxiy ֗9ўqKƐSwSR` q֍yFz SJ:RP)9=(4c';ҊZp8<pF)&i8>$ԛ8Hzd zɁ֜z7ڗi\_3҂p<"q~p(#@!8=iG'z H8#M&3KHI(i{w8!<Ǝ)sMڃARG<= Z)>M';Hi&}$"۞ih)1 N /J3{ў:{sJvp)E'/n):E(擟Ɨ4g1iGJiJ^;:FyA&   }3G|RFi@bғQ/8): vxZLR'^Ɠ(9tz\@E8c4=H&y#ўixbzy9J^qAG.=sъ8)4 )ArOxӃ`Ғ23Pbr)۩})rFy'89(,r};҇Lv@}GƔ>L, Ji39I2AA3S ғ߽@$R44 B*F֐Iӊ2LbM>8w4@)KLʐNԙi~ўqޏI9GrzR=i)֌^c:i FsGZQsIM!j\sҐQLsҎ9>'׭&3K{ь;(OR{R ;xh8'cFI▌R}(ތQRdSri{zRc\3IsKҁ=("ϵ.M sߥc9&F 4c9f`9&ҀqJO\RZQ(掜R֐4friiy"4Jx9>uqC3;RZB>^:үsu9?J1 ց`_QJGhjCJ>f`F 1IRi;;Aץ!:RȤ4@Kzn GҎ{Q9֔zQxE'4Q(z1(p AKGpis=R} `тEzsK;t89iRڎGn(IށR\wF8/JJPhZtiԠ֌ޝ@9$j3(=;=:PpHJBy4Ⓜ0hԙKy(i>Igr(:vw'=3A<A ~TǠl4cۊN٥"H8ւp4isNh'(gJNh:Ry'>wHÎ 4穥_z\py=)F);R4PqA>i? 9):)s(9I4#QEڒZ9Fxv)'4{SJ3IM4?:ZJNi})y=:POJ_ޖ֎E'<֗8H:.8ZҖKH}(=3N;rMS(.}Eh_j:~IKI0sK;QG/4/|Q:dK('sKE})W֐KہIqEhyހr8}zZ\qI1F1Kғ Ž_z9ɥ@#9掝 iAS(ZPOZ^3F P-4_.x4~Rg;Pi1Gj9R❜`qҐ#gbAǿ4IqIzRI=j_^) Cx&3L`M9i@( Q(<)9$Lz;ў'ڐq֎FC(Q4r(s@z1Khɠg׽/pi{Aϭ'BhL \\@$ԠќK2p3JH#Fzs J;qI}hiqG4v>2 zv?F2})O'Sֆi1i)< vGc'R8֒g"`t'U=)3LJ ߭QSOIG_j9;Q擯Ҕh=i9(M(Isސsz#4wRM'=;> zPsFhޏƗ R֐.) p9:@A)=&iGFqG8$v⎢921H:r1KAZN)FqIih:@>QsFiIFyQP((J2NiA{bҗxځ=z4h▀19Gl:P9=fq_|{QҌRR(d 3^iy"/^1@8F:Cҗ^ gqG;irz4g< P{R*NڐzךrO4ϥ#ޗ$~#/QMKӚ3ޓ(NisA'4zP8)'ғ P{=(M'J&yQɠ{'9 ғFxǦi֌稥dwFNM K 39r)2h=RqJ9RtN{ܜq@49'SJ:R:QץH[EG4Rq4 &?\LRf3FqFz挎Ps֐((zPpNqJ4ci 9(HɥfJL)A8JZ '9=1K:zQR"R / QzCQ(J2qKrh#J^v֌siO^hɠǹ<(qPўqA4cZo\RG9SMJOn3s=HA(8LGaGN{PH)01KÊB#8"4#(֐qڏNyIRc4FiON:4R:bhсIQG~hA(ϭ#14)sP@A# LzZhvyAt8 Ndvvh{S֛JFGJ2 ֗;f׽yԠ撎.h=)2zRJ3@'/C)sHy#)sڐ\(qPh=(&æiIH~w4_F;ԓ@=zPOJw~3fԹ&i :E;&Iis23FsCнI9L߽; )sKRdNsҗS{RJz3Iʀyp9*3P(Fs:4~9"L/ Q)=$4'ӟZOƐppix<'4Kސў8@Gt)>Ԁ\ҏz^ ҁA)ZS֎);bAJ94sh҂y#CHE!F:RҀ(ך:(>9i~h.=KPrh<1҃{qGC@z?K4Ž)MKڌ.8 gڎztKzފ~4wJ^~yuJ3OLwQ8g'uGGJJA(iAh8zfڐ*9Z);R)sH}1֗(GoJ1:^d~tv8u9"ixHN{QZ;3פg9x\RgRj;4z^—8H' )Z9"N9PO4cJN֓<)A֎)z3!`q;9:zSsNisFHҗOB)z@qF8(Ͻ;Mޜ0Eh=p:3@94Qڊ2R ;ўhG^ 7sFii14q?;8q@"J):ii=Jwhi1/lS{.;(8&wJE'ZAӊw-&)9ܜKڒKqhR:Pr)r ?Z^zQ稥8⒗Z^'ʔtqKIq֎;ڐd($Ҍ ?{u9>IAڔ NA랾ԝMA(G|bg4@<ށғ !ic)1t#/j^P&y 'z擿֗#4vGSK0(֎{vPy"=h=3;ZO^h<b8Lޔuf䞴tޔiHRc:ځ@R`vF9'4z\h'=iIށ:R=M(J) = rAցҔcgIߩ^hz #I(9$dGwɠs3GI4zPr(# !ғ<)r3I("FE $~d掴P /ϥ 4v<ޓ>g=8>bfF?:CCGC@(G(=1GzNvu^Ɛg4L}hs@=ti{p{4g#/wǵ&Mh&y◿z_qGNi܊CRޛ;*3Q9gR㩣#:Ҟ Qߊ)sM Q)? 9ӳMh;SZ>٤RR3IN z~i:`}(R)3ޔQHFGZLb3Gt<^ Lv`t^izG;xbIKIAg>ғ'<sMd1AIRH9A)i;ѷH4f@{N)zvz?F0y4}iOi1)i:p(ڊF9⏭-sIJRhEIѷ# '2Z3@QJh<\P0~v֌cz=i@4FhiON)($Ӈ'B)r &H=y$A׭/&sA#9֓J\})8 =qKIGSK:4g&(zqGj3Hzc'visڌ֎=):})xv@')3F9KޓFHc4sɤc"H ?&y)q.=&OfsIj^Ԁ1G23H}M.i3xӊ\IGJ94׭zP;uPE`c;^);z`.rx=h=}q ӊ^ \p(ғ8iz_78=)R֐Px>~g9E((GZL? RF:QJxGgڃ@9ёGj\RԹIzZ44ё:4:њJP:^?tt擩(րOJ^( n^3ғJ_LQ{ҒsRwG'4}x5Oz2)I@>s@8(ϥ/C=ў4t>4sҔd :9w掿OjwSҐqJđP .i CRx)z Rg<\qIQhS;I()3GQGnhy ќ)2iz(Z3FsۊB}(zR8"Nr3FHhA?QGZOnhG=M'S)Ԁ擒h4h摏OZSFNE'SGoz?Ij\IqF:VԜfQw{Kt =1JzR SJi1JIإ;:Qў 1'7):J\Ru"ғpisQbu9=-Ҕhҗh3ցӞh/֎(%/uړi:s@;J?(@4ԧIQ8zGڗ 9@ 8zѓG\玴E!j^woJA4;F8i{qJ;HH}(#4u(=84N2hԄ=#"sgL`ҞTRf %M&:3I֗!ёA@CЁޕOoJ&أJJ=1F8<ZL^ԃ?(Qړ<)c4cގ47y pi8=zC֗ ;O.)09Qړ74q1z:vҎ:bp=yQ҃KF3Jc}(9A9fQM.xL(N1)=iN^~qڎ{R( }?h (9dtZNE.h=(4J<ю4i=}Q@U~(#sҗ 'H\P3KӨ}'9R2 @颔qFFi3ڃA8;Qڔ N.p);R$Q8ɣP)z~4q֊;Rv8(׊;iOZ(RQڏÚ3J9ƁќGaJ:sG8<n)q?J;utJ9KB}9)r1A;:Si8$JہIޔqւ:Jh? K.F)4NzR9GOZicӁHHNԽ~Ҕ{bj3(P1qJqH)y'Q{ђq֐})Iȣ9p1֗8C KR(8#>z=< =4'zJL`⁂8/NE=?n/Izu@)FxKR)~C<\~tP?KۊC◰$斎 x{j:P ?AGJ:Rs@gڏLьwcgG qq֗sցFF8z\cw4b~}ii=){u<(ǿ7J{& `KӮ)N(J;(.rؤ8)GlCz*N3I4}3†#sCs4ɤ# (9h<;uQisIiE!=)rzbc;PG9z^{@KA(POzQނyɣ>ҌF8hڂ>bhC@}8IixϽOZC@#49&Ґ)3>pí֓ qGI9=Kސ(ҁhh8(9GnhƓ-&4Rg"Όr=)Or(qGS3G=iZN~JH3@s^h~pzRg\gfP}h> 1s@9`QzR##K;RwAAh#9 <}O֎ ( S֓Qߊ\ޗJOsNސ◜GZ\QQ{sKCJzqK!gRfR׊{OZ9<Ҏ) \wrZ6Ͼ)rh~u?җ#()G"ޗ 9/֐PzAjQ(ǿ4ғԔGzR):1bx@dQ'&QB uJ3HI{Qɠ)G#H~h*2?$G/|KM`Gs֔旧Ҏ'C֎q!ޗG&xIޜ!>^(ZL{xG~FNi9'җb=v}(斒3E 8R@}Ҏ84@fҔғ39RiqJ14t(qH94HsKB}?(SQ94A92hq4M'^)Frh<>ԘQ߭'ZLiPG"JOۧ{ޒy=/jBsҁIZ;?'Lځԝ /I<Ҋ9G$u4~Rrx9ڝHh=>)tɧqMzm/~MO4c?“:ҏC@^)3qNsқӥ)} ?)'=EҌFv)OIG4g#(8G)xǭɥ84Ahw(jAɥ>ȣ4KI%;ɤ{t@⎝psHrO^)ߏ4F(tZLRE)'4uJ =G҃Gj0{Lc=qi~'tG4J^֗H84yQӽ5OvZ dzv :v.2}6穠c@h?J3ڎz=Fh=)3E'N;юh NFhҔԝNhI]gڐJ)zS׌RZ\掣GJ1߽#4i?3L ȣ=( Pii-0u>/S҃ڐ(isj^ 8J9RԸ=;8(4d4}h>GZ=!(E.I@ŒN:sNzc3IG(@ҐҟzNQ8۞i@AJx >qNڗ擓c◭%p:)})2)2;PO~QE/(EKhisAn9{KߊLRސ\qI)FhGP}@4Z@yJHhh)֗4(}{ѓP8IӳJ:t▐9{R9Խ:P:QҌ/nQFp;үJB9R8?Z1^(&G&iF)Nh"Qy>PMOJQɤyњ34.zzP@);zRQCZ^:cR֐@I4h ڌGNINiz:1H3zR?* 8t򣜟J\{vIsEc-)3@bۚNw3I8''$Kԝ{v ?j^֚:GN҃E3Qߥ4&j;PO($Q8Qi0R!9֗Ɛ\FqIN!>f҃ɣvt3Z^(3qGSZ;dQ:Rh㞴(i:^(Q:Gz=3)A=Oz;R擽)>4riA3)\B3ҌҞFhIޖdKFphL< A֔J&ƒJ: ׽JO'❏JB81P= v^x4Ͻ I=iG1An'_ϭ-!E׊ZB Q?&pqF:ҒzNHR):qJIg#N=gz{pxqAg(ZC4PF(Hy#z3ۚiO搎iA^ԝѓ(L;rO4w=hG#ҌZLJ;yiyȥI9'4Q3F}旿G$ўqޓ:_ >’`RjNKӓ ڗ"$GQH}GNzўsFy=(hK8@<@Ԅ<Ҏ}iKK:>})?1Җ J=GR Rϭ/jo^RQaFyRZQjC֎挜Qڌ<{ю')41H2(=~'| Px֗ sKwqG=)OhGZBsAGۚ^xI۵.z /)=hPr)OΔdH)94{$9HzZA- F9 ph ;Rc'Gh9r(Ӂ@Cץ.ri$Q׽L`is~\Q\QI$R9(ފ> ӿ4cs:G(`Q .hR@<Դњ_GZ:hяڌh=sZO4b3ӊQh(Z:8zP)i Kך9(h hwR3j@=~c8GLx=GJ?_^s֗(N)Hf@y';#֎)>)p8)ތG&Oz^h"שxg={P1֗h$&yK֔u'~i7QK)} ^( ~]i03J1җ펴K#1'<}iJ^3HNHz zzRb94 fБIԎ((QƓ&th(fiy擐ihRgcLQ@hғ'@0O~(z;i:PNJ^4r~#8=hKސKi3=2{LKl!0(zg*`_SJE'#F:)#4vڏz\{{N9H)sIQ^4Ǝ8J\@#&)yR}){t# qJOZ9@GGIҊ\3sIJ1Z>}hf$)sҐQQZJNqGH8&E'1ړGJ8hi;>4)=QbK׊^sӊ !zJL񎴾g֓)u#)(R P:ڔtރjLv(Bis84n8'n9#(=(94 AsG~sFxwEFiI;RZ3Ҏ}zQޔ{~Q&ry~'4~tGZB:x(yuHO4dRP8GOj4'w={P9(/l9=hFx":: R9=1ҏg99}i =;{Ry;I}h9bsFNOΌPOzL(8I)I'ғf3ގ=8iJ3) cq9h3A֐׌P~iޗ78r39t~4Gђ)H`(h?JbhRQvQd{:bGzzRsj>^)3q@)3G֏H~1ڀAɣ3ށJ^@A:vNR8F{RwKH);c(K֐dG9Q:12=G0HgqFE)8҃J /KF{;vz:!qG89.{bHA<J}%)h"xG'Ҍғ)z'94(&y92{ўh'Jgh(9ґMt/_cF}zRfz=h掼~d^␎(KG4J\t&3R@ 3J=HzQF9cF:@掔gƎ=x>#y>gw*htށփފ: Z0A~~t +(39"=h=h? LQNԹ4d &J uQGCړ4w(ԧ v{R=h9<{PzZJ;ii2OisHhHGϵ'aA撎QJM (s;{ёh4u=iIsK1J0~Qғ93b)1-j\ѻ N8cGb#(/z8/2Twt=9<;*^icJ^i"bqSA3ځGn ◩gQcސR(FN)9sKNEKKG_jO~u){ɣKi)=) R4<ќҏŽ#4uP8g֗9FqG~hhʗ)ьJ\IJ}瞟Z^'Ҕ)1KIhG9tcJ8G^i=y)cg梃oŽhҌ֎qN)Z1Rcڌ`gQh'C@~Q;F;ZL ^M9J?IJNԼ&sKt4)94c4QsF;P8w=iGZH)@<ьPFJ9P:gQRQ9#ޔGH:c2ip1I:9@=37p ZL zLGҊ:'Ҕ)9Fzhhs:нGCF N8iz{;g4LߊSA4 &y &^( =iHcޔҖ<҂(i:{׵ϥf?.GZLQϭ)4 OKxȠwdRN8Fx&FF1G{Pxtzќz(w!>zуi}) iҊ3J?\OPq@;=G|)9Ͻ旎ԜNԼggҎ}(yF4GQ)3sFp)ArhIڔbP0i~TQ@Ԡ/){^ Lcw\QJ:R~tKځ߶ib qF E)A\Q3(#8挑֗(9擿jN)8gwJ(ڎRr:w4P[489t(J:GzC4RRQ@zRt=(()huvz?<O()::ޗJLGasJy>ԝi){N1Jy3&@(9րiNsIEz8hsKۥ/n9Kh4ni{ )(E擊QaIi{Ev~vJ=h#{Qғz:)g8QG!=i9F9{uҗN=ht'Z8b9Lъ(ǽ/=QG^(ϵ'^Ҁ;i(/|Q'^h(K4v G^`1IJzQjNI ~OQL۵1@ۥ۾i}(>j$h')sHGJ(4p RjAu@z E4Sc֌֗z3Ӛ;zsQ91t4IhiOjF8#A4qA;QIJ;LONi3){tގ_(E&p}GL)3ќKցZ\)0qhqG pi1NOZ@8JzSiI8Ը~bؚ>q/AF9qw&ޔf8Iz^&x/C!G˚3֏hHփ"(qF:RMYvG~({ќ`qE@=hdQH;Qߚ(84wt??֗@֗&;GlJ?NԀF8)}I/lq(ڎFyM =(<4F@uGҗ'hLSzgvRKNuiqF1פ9ȥwP:ߥ/!SiyFAҏjRGj14RҎ( ֎(P1gP&sA1Kۭ4HsZ>{p(qAڗP8ɠTSRsM/<юyhj1K~4P(KbP81GlP=((G~rq)IRt3c)qERu<@%.h&~j=H84v8t9;KʂxizwҨ4JQ}(q7Rⓥ=h @Fx94ъ z;g4f=ϵ.)F{\gғQڃsH 3ړўqw⎔1ޏҔqc֊"G1F94H>(FhPG4qAKcZQEZ:P9FMc3{Q{h(@ ɥ$H2:2yK)GN7hg9^=yQIjRz`c׵&:sKHxQ֗4dڐ 9 ^أ%)/nF)4w早掜Q2sGNPF(QG&sK\g'?cC^u>(Z4}i .(4qE{:Ҟ{PI&EރF(G'0('#4tJ1\RZ1֎hJ_'b("JyGc4t .s֐QގMњ4f#$sKJusAIњSҐ*1GlRcޓ'vA$} Ҕt֓:J=(!h<;҃EG4/luJ^z)x8`J^zO(G9?ǮhjҊ:=N('(Iޗ=>v3@"49֛b KN):R}iy4$Ґq.y~ (H~0sF9jP1ҐsI((h`'z>z n8Rv/N)3bu{P)9fJ;ߊ8֊99Fy8#:֎sAh=h'Lg`◵.qRuj9.8ғGj\9J 擥.xxtduu=F)3uihϥ(&RjQI3c8Qғusӥ)A-q'Z?QKr)2:Pg#!JOJ\)1E(F;)sHzRu4wRh#=sj^@{ќ/4 KoJ^4c4cނ09I_ƃHbx49 N( :֓QތcNu@2(('i}9ќ L?J;Hȣ&1sёE#z^;߃F)=@@M4PP(h't3PF(4;RAQ1ȣ&h)1/Ph@iiq4(?&+Sigima-1.1.1/sigima/data/tests/laser_beam/TEM00_z_30.jpg000066400000000000000000002402451514013333200224650ustar00rootroot00000000000000JFIFC    $.' ",#(7),01444'9=82<.342 @ }!1AQa"q2#BR$3br %&'()*456789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz?1I(cAiW~M?zKғhbFzRu{RQgj8x%/^3;z=)@⒎3KҏqIh>c.8#";~w4Z9rhzRM'/j8Lu`bz;q@玔8H3J:FG4sC)GJ(ޒԚAA{RjOJP(=Turhs21:0qZ&qGz39Z #4u}sG|"fh#izqIKɤ(){Qɤt(ggz 4zǭ%.84ڃJLJE%3G$c8pEbO^)@)y֐ɣQ;RtJ):QږIIғ4JGsE'CGnqg2O ڌJJ: ьF{u4{ҟHIz㎔sJi9Z9Ȥ#dԸ"LFxԣNތњ?'|ғQKE&iM(4{R; h#4d!(>tMHqҌt.i4 MIKu PH0hj_jF ȣ4 S4dPM 483G|QKj Hi $)9N)sϭqJ:RzbKGjNRZih(=y(z($@/֎J:QE 8/SAT9"˚Rx=/KAGցr(EIE(Q !J;4PA4Oz^chqAE/Ni^hҐ8ڌw bOF=3@ wގޏQ@n:R M⒐9R;RRKڌb2q@yҐhQAGNg=('1:Rp:SIRu'JP1H~<#$Qw{QΐdjNsɥ4 z;ΐ!wQt'&њ:'7K4w.(֎(Qfis`u8_ŽzQҏʌ{ҌڏbiJ3!4IpiOIڃ֗0rh)ތG4t'=)3h=0~4 ڗ8`сҗzP@`cczQG<(u Z^!n”ގR8)⎂֗Jz3i}hZCz\:zBq4A QALуRg\Gl ў1@)Np94HcusG'hݓ^t8<({8u 4Goz^xGn(s3;Py4ޔ(Z01G<)x~ri{t=)h&IQOc/QcGa)r((Mǵ/zB8.@>iG((⎼ny/98uRJNG^MtRR3G'?c ֎4t OZL|?wj:(,ur(׭.8sAȣ@4vcI*_ϵ/AF:sGPGz3qFpy:N ^:Q)8#>c)?^hJ RttI ($P2i@9=(484RQ@ȥF4҅'"9KQh`GQLF9i=)I-'zSIh=xJp} AҔ:җ4ڔrE'9<;ZLc')4Oj_nqȠGnڃׁHqg^"Kǭ/JN(RQi3(P:Rg.qA4 &s֔PEqj)3۽;oJ4ސ\ӷsI(ۥ/'~g.G LQڃ׊Q\)=hJ^zN3@)~փ@~tJzRJ^iz( g4b G|G|sIiE qK(=8JF?LsJ;8ғ.}A}P}c׭Av=(hj=h=x44ғ<:ZN;zNy9H1ڗJ'c4tGjP>J;hT}({u~T@G 8G?1GCڌP?*1sKBqGhq|Rg׽Ҝ֛׊;4x QP I}x⊌c4Z0sGZ3IS4RRGz?S)穥hPy4{(v3Ҕ< IցsKZ^g`J ^34g=)(9:1KP"y?xfhI߽(G~M!M(ړ֗>v<v1ҁHxP1Kϥ|P}M `(ڊ9# c:t? NgizZN .0s֎hbfҔg_zHysJE3G掦81?J=}RcރғCJGI9;ъ(ҞG'oZQF44vFzQ`Rޔu}ړ8dvK␜;ރQ Px=(<җ 4 &=:8@4ripsIAAGl CaK:E'NO/lRdqAJz9L )GwjA/& (J'AgZ%)4 }(ޗB3Җ4ɤCKjBq4#tIE)@9JtKۭ Fh4qAG!#4z?Z@rbґ0isA@(NأrzzQ9J3Hz;ցAIڌJ\qIQɣuQp(\RwERу1JQǽތwi ڏ0s'#?҃q@ɥ$qJ{ctJ?:Qڂ RIڗZ?;qG<Z_Ɛ1J>Rsc9<ґ{ўqI)sF?* ^1Ȥ攓hɥ4t?Z\{@!4Q:;*\zR8'j3I9ތsF /׵q94 ARQ))H"\яj◯p8&8N3Ru4~J;d^94ؤyzҎy=Gz1bQtGz1Ӛ\F(HG("]A4~p:Qʏ⣷4(?1=IySy搎E掽(##ΎNr))::0G4q(GKК)1sNF;Aӥ(F 4`JGG'CyFzzQɤ?49掦sH8JShA8f83H1P}hA!G(:\F9F} )R4)=~42h1=hhҁ/n)3KGAҐ{E-(Ɗ=x  Qۚ1Fh (3KRqGғs)84s=9)MX=xh':}iz ;sKqI惞=)yz(RzQr)p:Lp((I8Q@MON)O@9J9zR})}dQT 1?w JG/!I(>cq40iOQI;QGAҐwKtqFN(9r)qRgziq:J1RR搊RqKHx84w74^z:RR)H=ڌGzQsZ;zҁ4nK9AAqI@ۊOQ֔{RM{Q:Qړ;) QS@8}q@03czxގ@ޓJ?:C c)sI֐tZ\Rj@2= )F3ɤhۊ1F14p} Ґy5^ sF9JQIZQE`HA){恓G(@RRwizsKޓ(GA֊:QہA9Fqiz@۱(Rqހ0sCZ^qւp(SA⓹4(4! A98Rwt9aGZN'9;&qK/^G sG?"qȣ)z{/~ Qx<bt( @ւIf'z^أ=(KH};Gj1A$s=h&9PJ01Kӥ'\Qu((= (b{R㎔s׃KN8c: ?z׊>CIP|qAr \`{gvJ֗jOʗ߱J9F)1^:9I\R4Fp0(G})1qw)qғJ\qo@8)sh=*=>Gz1~4=(4E)Qw#ޅq('4`IR=ih'SJ24t=>u⃜Q1 y搜FiE440NI:R`iOZ3J1B);JwF)s֓qH}zRcZP9Q;ڏj1\ёz01@G^wRҐ.qGA֎ Ґ i:J;Fp)$ޔg1MqKϭc4J^sI8df=h'"HqQю1@1J{Ӯ)9#(iOs(q\y8'H9sRz3(Ͻ(u#4vhϡF9P>dfuytRsJ<ґIޔ=(qIR@>4G(4Γ4IN8)#4ZOcJzRƁ׭<z\ӚsGBi;RO@)AN:RvuJi34qG@@hi9K);:Py>=? Aڔ{hߓF;Rh(=7Qץ/ @ vPG88n8sҎG4'n((iW &Fy8=}x4a(JN>ၜRzy@3ɥ?J3FҐcPE'=iGwQtɥ#R'~uRcۜ88(8h8AZ9zR@'J(zӊ4sJiփ4)(9H?ZN:Py=h'P ֎4Gz;N`PGzOR:GNh(P9)0z\zt8#RdԃjR #?J:tإϭ&311E(H:QN֗HNiI֓RCdQڌSGU-&(ߚ{c;z 'AKz{::uu4џΗGSKuHs}(9@Ȥ"RcҎ֊N){4GJ\cҎ=)F9)3A8@m}i zqZCzс_aI1׽vQzc=8g<ҚC)x83t4t&#RzRQAhqGJ3yށڗ)GFuI"T@8F=i24qGj^OZN~tw/^zP) R@zzvqSP(sh:Q@4KzNt8)y"A);QKs(=9 gj@("94sKړ/HNI{h>vF)(j=^dA9=)sHyOԣi: \֓'"ڗҎi=^SWK?Nx)`{ҏ֐ RJr(9iy>S;'_jZ^sH;/ni0zF~"9u=G8h=h#r&rԧ{RvIiyH?\RZjZ^N(ȣu3J{`R`ҏzR:zzRGQA8֐(4LBx4rE&889)(=zwQ&zR.=?:;R);RߵF 3M'ZS}z҃ޖi3Js Rg{/#988&{Cҗuw[Ri;gQa@ :4rii2sCu9J3QIcJy>Լi >Qi?:3ASC@R(E4ZҌ/掜g?_j^9< LF:3h.xH:`23Jp)֓?ΗGӵ&OJN(:ߚMtE.NG7$u.y$QM!=8qǽ=iAⓡ(8>#z:P94LdQ(&3ցp) =){Q֐g4i:GCJzNxG4sҔf攜&JG^)3GCރ4uLh@AJ=3ތi8="ZN}(xhǭ8G҂ 4{RsIF;u>LQG'NϿ捴bJNK Rc`ft⓵tQ:PG< t41;g"dA9擁KϭZ= h֎Iޔ)҃Q@8G.sҎ ){c4` :~T48֔tL9=@QN>ԧړ'8hcҁJ='\cyўc.8(H03KRcM}(/H~4wFxwޗiN:R ^ ԽHO4.H;P0 h⒗H9$!'< / 㞴ӜiAzKxh9hzRF(>!$RS{񞔽HAR>i: 3NҎqz@r1iGLsAG@ZLcKqI)ZSZ9>gh<RqG|sj\c!RgdRghQ:P88ȥsJ RJJB}zнz}: 3&EGSJ\(ItΌҗ=:OJ)&3ށҌGnh(G>Ԅqz1Egږh$K(J1^zFy^P{bxSKރA(E/ZN`֗Aҗ4 Pxih99N(M 8&ҞhϧQHyvA4r 4q@ =q(<2;у4w8S S8dp:P\dǽ fQ :6piI$I@J;сu8SAH:J=Z A֗dq4QJ?9'&dR|Zs1Kh;: 9ь 9Pf֗yϵct!4^4OzCҁ cҗ sF3ސuAsK)Ni}RZ^i;AdF 4h^sJsR 4`Pz`bsQޓ99zPFhOc4bʐ1^(Z^(j2F ڃFG\R⎝9( _ΐc Sޓz:sGP}GAG>t9'4Hq{>q^)QAtxz1FF0 KzB=('^4 By`CJ'ړ94*O_ZP=&1߭)GzNwti8)s<^4<4w擁ך=1HM.N/^(ӊ8'Qx1FxQhAH{Q8SH:88=)8sړ})5Gzw);`RIҞ RhݜqN=i9) :(g=iOzQӊ7v@8R搚NԸ9Gni0y(9R⒁4})G!:u:тi1GRI@<уARy9◀:PFH::F8Ͻ'"ANJsJG44`>csF Rv4J1I /#:֌Q֓( @1A9==p)@#9FMQހi9Gh} ϭ:hKHzRv'4(??Ž#(h):9$qK}h)qZCA旞iAq8ɣ/' KQfdRc@sA1Gz:{uZA< @I4JQߞhj)11KӊCJ3s֏j:tFpF)ry4:SJRJ3?'B(ԇsߥtEb>/qGZLR4ug3IiqhF1?sGJ^3Hz{RQ8GAg&Ks}h14q;G=:sIIiz)8K׊:{Qޏƣ9(E(ޓށӯZQdfGZN{b PGh~gb(Z^RKRn'1NITsփ(4iGAKA旨'4:1-zʐ(/QKH}E/aLf0E F) )iip:gJp;w.z)OR1AғIڐ◌RzoSHipG&A# csҀ)O4ڎ}^ZAf}h=(.s4oz=i9GJN)@RzQ'"=Q8ȥ}(GR^vF0M&OJZ)3@q^AӧZ)sړ8ϭ/qZ^)3JN)M%R`yړ8gڏCޗғ<sJhzќq_֓4sAMj1JFEvgwڎ(0q:FqFxތ{Pz9'qG(y5֗8>c8R"E-'^.x@(Tu҃Hzc4Ҏ{w(sGJC(#=@:fړ(hiH(=8# R֌Gn(֏GZLbXvPx4C(>J4掴~ O4SJp{QތzёI(:(^F3HVR;qE.hFz ҂p(RRcQO?jq<pzӳM';\('i? SvcRM!845@ힴxu=h nsIQ=irz);џJ9)1;bґ4vNy`t<уQzSŽ1N vҊ(( 0N):u>h'#HzPxQRGS֎I;m6q@FOR(9.hoƃzP;C9d R ȤNbQ 1wA(~ҞE'j3GniqGҔtⓡ@=Z(vɣjLq@⓷v$zRgڗ)#={tP}wSA>vߊ:KJ@8ɠ{;zB1J=GҀ—PpG4jc9G8ⓐiN=)zzsNZANǵ&xi>phؚLQJ9qAIPN0::R;H֓ZA4c=xG4cu /~g=i;wK;4}hQx#\qG Z\R H=MΌzььu4JS`` R`QjLs:cҌhI`\pzP6u򣡤J:Rt'(◿&A֜:RqA}hǽZ4c'ރӊ1$(i9J).iQ AA?8 S4)  旭&1)8qIZZ(z\qI:}i{ 19bRTd})sLqJ=Gc=)sQ1>quGs^:RsKi8#4qGiޔ9QL}pOJ\jL/&? ARQR/H}9t搏z_ƒNhsK>G8y1AJ^܊N'#y9Ƞ֒LR(1H>9cG^)4&(8"p('3A9FyHy&3@((z=N(9&u&PZNh2) .y9L bZOcJ8=iqьqI@`sF{zq;}i9bpqNMQߦh4'_ڂ;JӚNȣj8{)xLӥG#~ܞ3ixZGփ. Fx94qGbPq 8OZxZCZ8(҂{~tznqH8<ӹ4tN fd;Jxd֏jLw&OJ AbR4~4qJ1p81 K@0=}IE('ӧ4E)4P=y4Rd='j:FyiE'AӚN3N&A4~cPiÊCJG8A8Gz\88h3AI:"u~ sc4R@I.0xii;┊ KқKAGQhKARu'P{PZP9Hzh KCۚS;dR F9AJ ъҌGirI9Rr 4LɣP9#<Рg>`fzP4i0 (ގOz(J9Gt('4M@uNIphҎbc<tj?N(4zRF!)i9GO{Q斃ڏj1GN.Ax4ʓҁ)vI:A>s@=AŠx<sQ< 1KPhRc^Ԙ)Œd␏ΗP;GOΏ=F=(惑Ҁ{RR)GJA=!P8)84Ivh=R}{g2sҗ"tpiv-!G4qF)GSG9␎ޔJNуtQMh !;G? 8iA8挌duރ)޴H}Fiz֓<(s@)ڎRx␌ڂ(4΁IZ9"ތP=(8iGN00Ny>bƒGCHy9J?Ri=iZ\qIҜ{`J1֔ LqMzR=(`3L.Fyi1Fh4v (N6Gz0(xcryی8K(㞽(8 Rs3@ɣG^9(tnNEGZ3r($bztg !_Ǝ(Ͻ(:udFiyG^)9J:fRr4r /Z@.8(~ ^);KbqKPz B ǥ;ގhǽ8$R(P:)s8'c.9ȣIj; ^s34Ax:R4ځKGCGNԜ~>Ԥ:sI`h8iN(#HJ_^)1h䞃S֔J:Hsz;RHs-'NQGj:qEw9ph>ԹIQA" @9=)OҐz{pq@NhPzgQGSF8 SCA=i1ry"'  p(Koƒ3JNJ}:hJQZLqM9'JH'+8}LRIN#ғ<ZN :pҌzQuA'#/'FqGAIRsFF3J(hfӭ'Z^)z1(hPEAF(?JOz;hRIF9J^p:Rv(җ4=hҁȠ}y((ϭ/9JB~cA"JuKH:`ƌz`ҁ(IXA" (8(P)x֐qւzRu1ƔpqAKyHG\ZN4v&h=)y=I8=sGn4y4sPyE(u\uis{ьEv4#@GqZ03@/ix?Zhi~xǥ(ȣ9  ry?J\CQ֐u)z1R=9`ѝ3Kɤ㠣ԧ? LqJ8ȤhRڐK Cڐj BFO@)y9hRg'J8鎴$ގ۽'L ^1OЊ\gA)Gj0zcy4rCF"3Ij^@֒iǠ4 /򢓚ex4Q K֖ 4[zR Pr( QҔPxZCsKP<_KړZ^QץirCF@G=)gQQFpsG(h?ZCqKJLqޔg4sJ%dҀh$ .i&J}ijZ@AҔ)1gq:}h9Ki:});ORf1/M=K:QM9F}(Q֔I׏Mi9fہH3#)JI@})j Iz2sƒԇf>3iH掃"(j3Q^1L}sHM((<ނhҊ4\ўP1ӊLThN Pz4uhz^c'nR{ڎ((4.Fz*^3@S4҂q wҎxuԹ" {ўsG99^hzҁMzR94P8IAj֗\QL4 RpxGlJ@қҎ}9Jp=(8={sF@Q94F3IP'$җ<)zйGn(v8#@yny)}1SsA98hIv'ޗ1G8QރԝJy8E֎4gi2@{B):rh^c=z<ѓ@'ΐPNGKM)sM.:dJ4g<縤91A<ҞM(#8qAdq֌s9qAQh8#փ^JzP?3K=.(qяz: R)~c43@Kuiҗc(=1ҎؤKߊgRqQǽ'ӭ;})>0 ֓9ǭzRg'җqJOaczN=hyP~(i;(=8#ZL3QIސʗ9J1K)1֔~B=h:ьP3/=i3sF1G3Iڗ>dv9;Z^tqKq^Rڐhy(#+GҎgvi8iM4v)G"=M. ɠizz9(zuA;:QJ2?:Z3K4#!J:QҔ?A;}IxSHx PyA>4#{bZzϽ/^):(<JJ"_ʌ:t4Z=F:Rc ;TJG|`}){sF~mSvZ;#GZLdr? 0 rsGAӊ⎧ڃюzc(v㎔sAގM֌ qh'G9F9=h=8G:Nأ=^:NJ & v=:PsE(?Zcp)z84moF+ޔtLzґ@9aqJR{8h8ⓨ'SHsw)<'zCN(iy֑_j9 ޗ}(w 9QIۊ^٠6&y @4Q:Rd2/jNir1Oz\H =sAϯ4cǵփ):J:O4tc֌ucgZCך^t(( 6tқyqGQI)t~g'֙'94u4;R)yQHFNizzK(<?3FhqPs4:@/izF8@/CHzF2){Pz #@q(擕4g/cH8 Q!(){{&xdў9j L JB;Ҏ)E4p1@!QRQ}wZ\f{r:94'JAG4F)GLҊ\fZ\dўx84$J<)ir( OjC&S#lǕЦ'cHE XqHFh\R0Hzbx'#Fx@9ʌ`I 3I 4wF8i;R}2iscޖ4#ցG~giZSڐ9w!QҎ{{ztɣut4\Rq֗APy4w򢌏Ɨ'8ԋRqG$)@8=p/Z1@N=>Qhiq(=p(P:PhϽ/L旱=#wHN4ғ=.{P(> sR |ѓ !9Ӳ09g=8ȤFy& )GL8j t( ZLs;(=:R)H@ih AiO28pqJO=83G^iIf(tI4JN;ؚQ=G42)N i'9WO 0)W;a5 @JQ8)R.SzP"=Zy99)Ȧm884udLh3JAR4ZPsNcQ׊=)旽-!Sޔ C/_ʐdzSc=i{R Ga/N(=@&cF .8%/wPyQF1KMOR@^{RIfQךLzR4i{*~u1&iOLǵ.0:`3K}i::\:1ϭ*qKy?RORG?o~ޞ=HU}T\1O ԡs֜#D6慏-Sakϵ cڑzTrE)r:T.[)1玕21L*)GnҸy֌|49gzQӵ ER4zѓ߭ )qxȢqK .)<┞yzR@4)1ҊLF;JNǽE۵u1ց=QCsJsG4Z@HKނ 3 &d n(h)O(<G~qGZ_Z=i;߭)ъ?*()'4Ӝf񎆌Qޖ@yփҙ'Z\ɤN(zQ@J9.:џN4'Qd:99)=4nqӭViANG"G)8| Cz~!$v'GԿAFy@O9(dsJ={P:PsKM)sA?LP8=I IipqB(G4OR0)Z8tA@(=xK(HHR{tK})y4iN){Ҏ*OԊJ1x_zWڦTHJ.zT RUSy9|qzwE@s=zӊbW5=*3<9>qPC"cҫ2`5)3MQs)0Mi1'y&9A'RqG~hۓڗcinrE )}IshE'C#Z'4wb4KړޗRqRON1M94a掣րsI旨E/QFq?98){S['N1@(=G!KJ\MQ}ϥך0s֌wu)4>ui;}H"i)zh4Ԡs(:ӅHž&PI .xX`sҡd4µo3o*?1y`_J;b88G&~܌⓷!1;旷4 B9&JBQ@94PAғ@pi*@'^<(@rG~c8{th4At@<sKsCɣ1Z\qy84ȥǵ(=x(Rߵ.8JGQRt>~XzsI4w&jN4G> Q8Ґ.}yJ=(.(=(sK);SJ^Ec1)CҔ1(R4^)9?JQЎ(=(#֏(sI(J\M!9;gڔzQfǥNJn)xRE89i3Kc;4 ұz;hsPK0Jx)@>qڤ۞{T{r+njPȸ>aXEE8ij=* X:R`NhbЂz _(cBm<UV-3!*jŕ|2qQHFq@Pp=j)Zac})0}M3J0(ϱ֗IԜp9إ8 f!FZ^R{QMwJ^惀c 1A#dg(` IQ0h'z>ASO֗4t4v曟ޗFGZNG)3BKLZ\ :RqGj^=0 7=iGȠt})F3֓h#\J^OE g^=h|RwJi)A=;QҎ(*;ьv掴fj\QQҔ擿J;xiG4G(3RA'J:Q('<сڗP4sJqSH8Rqz^6 9G~wF3Kӭ01F?*3t<4~4{ьwq3Z2xu= Rq@ӚҌz~i*FOΤEϵL8*TA,@b(F*BAX{f2¬$R?8wIdu6R杴ԡ}i1ҕJn)1JL0W#8A4#Ux9=ҩ`Q QIߒ){sҐA4c<>٣A#J !֎dQR) L;9ǥ'4`sF2}<zf2(bLQӿQGIJi$GH< ~irqI84H)zv)yNA4v''Q֖ubҊJ>j=ɦufZ? ]nԧG/oj)1OK)xHqڐqt>c&w&җ(upsINAF2hxH)vi>)MQڊN$ǥ֗J^Qߨ4g&JqNu{Ӻ ⁎s@x遊:T` _n1F:qN8u(c&8*dROJK|ՕR;T*jM\yѨ%[P`TȼTPTT2i1 csҏ+"1ǎ)QoU'3T^#ќҩ e#9֠=H_ }i<)SXF8'Q (:QGjSi2(ǭ("'9PqzcF2}iqI@ޗQK48:?OFqZZSHx/j:zѻ=iz掽(u)zR@4`} )ғ$Jx8?Z?*FzR֓i3sK89sN3BOа=EA<_'5L8V r8켓S õB㚈cққޓ8c>cړ)"}(HFq0:p83:\4yJ;ҌRgڂyx9=(#"dFLGLS'4ny2'R]9Dy)LTV;S,6ڗ P>q5,Xr=*6 n#ZuU(ۜ Oҹ*ZaG={RqG9&y)>QIFJR`h/>c&?Jz bs8=JN})}M4 ޔ擽:HM:hqA\ڐZNiE:uڐrq@qF3G'4)s0pqRғJ83G9)FN=YjIXH/DXHB9P权63HMBqc8?ZNpMA(砨HUsn0G5Ufܠ)Ȭ׏TnP٪f0G5NhYx{S$c*.t4Z{oy489{#iǥ)4E@M94Mg'jwOZJ\sGHx㠥);tڔfLF;w4w"F8&dc}ސTg.8ihzQIhJ3I/4ԃ#4֐9J:QzRR{RcGbsG֐撗4~E4zvgڃCH* duJ]GqAI!R:`rM)(49u=zg_j2?L֗QK}RQڗAK=@(iqZ:~4z:J^vIԼv ZZ1ϭ%)R>ԽKրy'S֝ǭ'psGSKݩqA@xh(=iGz98ǧ;bQ< tAK@=*uP*tPGk*kr Wڴ OZ@1=Vq5n>jpYj 5i84y?ʗg 8`/5U5XJ4GP8U9]89*D@&9 gȧwz8lU%Uvuk0j7Lvn1);I8)>aץ1N@#)M.s&px<^ԝ'I3AE!ތzQAȤZ8i:h>)yiqJ '"FsH9x4ԇdZO(F1FZO”Gxҏ'~iApvw.@u)4qG4^R.wKf{R`-L \gLzѓ:tC֊\zO”sv8SƌRRHOJHjLfZCփ(rE.޴qɥ@Z1֌Rqz9r1K K941 ӱIӇ8oJQ@cތzQ{SF=zьQF{ җʗNJNiGqN ԀۊsS&zӎ* tfZ=(?Zm/h<}G&RGN{qK(8xH:Py87hRg.}zP8h`S(?:QABɓ)GMA,\UdqU挃U;ȧ_UE'⪳`2#"\1IRNMVrH5Ujc Jr*?\\?NILBqwSzi ^“3 @0y&Qړ#8G=4{Q4 PiɠFF8OZS("_*CQKN As>FhփEA4JGN(>zz84{QjOŽ)A$iq@1E.8\cLxIRq;ttE(HG(aQJ{&x֎sKJAy4xh=(4 H8KKړ83G8N{RdEqF;ў2E$Gz^{RpZh=hg9m0FE"3h)}'ғ>Թў= hNg8wQ(b4@#4:RgSE=H=ELuTj3V\zqWQִ 7jЎnԧ> (I@?;\fyJ 4 ch#?Jn3JQzS- OAz? ;/@q@bKӽ/&9KGSNG;9v)"TSNa =*}U؎1W8HZUqzU^Zr=jYA*iVV>:S0H8Hr3I9zߎz o!f/I3PgWaT C!㊨UU$=+>ASLUW\fXpx? cj7?Jh zalR׽!搑iZ^)֌`sG^}) \ⓒ3N Ah=;2~QHOj2@ vKH\P)@9z\qA4Rc\j s9u  ғ&sޏz8ҐR3H:sҌbuH (ڂsIMqK({P8(ut/CGI)ȣt}%.J?G(uI#ڜ0hzёۓF2s4zfRJ: 3@8gz\dRG_Ҕ8ұAGgJ9^)xIןҔc=.py~4AFEjB j;f2 1A/qKz21J);iqޜ)ǥ?ҤAR=t^8f0A[ƯByXZQ}jgjnq9']*O9q[{ՈiH)&(#.M!^*\w䏌*!ɨeV+U8TOCP!9皪EDUA#*3Iۊ+dw>Uێ#FEg9Lc ASxlz>Ru#F):R@3HhҐ)I(qI "`/s QւMh9JqJgzOLu}i旓'^~r)>KԁGr){F)GPO8RqK֌g=iy?Z9Pyt8Ǩ⁌qA "CcA#JQ{BzsGnhNz◨v8=jT"USp8 cVPxq.5z g~5"F9(;UxH:ոZrb'jISڥ R(g.*#w=5~UZb05ZQګU^OWp1U]0sU{UFUy~P<3MqTd'ך#Vn1T$Td*"@aH'0xIߥ0J~3M&!):z89=(<} Z`QގQjngҏŽRqF=u4gdJP9&~lb&)N)9փcH:QRZO|q@$:S4c={R`(:њ\QsI PO~Թi;QAxO&{Q~GJN>ڗjhӚ^Nvɥ:\֎֐j;QҎ3.F>`ьRq$'.rr(d/Z1 N4JQwo;i@֜JpsS/ V;*L2sZ0Zc ՘ GZj1S(8S$:6JGz9ޘ$`q=8N^j6F0Bd!הơ2sP;9 gVMB#U|f@SU:U 3r5AJnaU_G'?C3ޘIT`GjM'㯩'MR#$RAhz-RŒI5/&y(ӠqKښGiqK(9(G iy^PM/|I<ϸaڨ&NSsP185XsZT|$b`{b<Ȥ8!) b?!4dюsIyKCwl4:H8iq@ җI{⎇GqA'):zR(ϥ IކqGqG`yFN1J?4{RwRdjZF8ؤ:N 94уCMgZn=yۥ8 $zR&yZ^{TdtɤZ^}hcZb :Խ4Ґ c^֝HM9(E(Q^ӆq9?R HTˑfN٩wXNjtqVjxUG5~uVVc~*H@ϭY^*KV0YYxH=EIzSċzH=6jDg$gҡaU'ץBcI皯#u튩pYҾ'P( ui@Rg/'ڊ_oJCҝMKRG֓'4zҗiN /'~4dgLr)sϽ(9z=Ҏf8t‘I.y@ӱE(8R/Nd¦\ԓӥL:1ڬDݳՔ|u<_<_QZ}*0犲:TVLzS)GɥqwJ=)6Po=JJ9ғ^AA4 ){}џΗ~N(Qx4 (=9wQi. :R?8piF9;G5YN}jaT,{SX5t+L9rsڐXMF(4Lz控&xKCcL{PpN{ёҐ3ҏz1IR֓QA砠>iy9F}ڃ؊:8@ڂRulsF1^ޗ#8&hZCڗ#R6JzSOZp9)1ڃד@Q(_&E(4}(ҌsKtRҗp3I/$QH:?h4zќQn'98gR=84uzњ8'szBFzSQG(j1?J:R&)s4 Q1A9^yQf3$Qҁ8);R\^J^zFFh<LKE4q?h =ݜP?O)aXD d#J'R,)mTaߊ<឴yy4֐u3}F`s֢c =99\{va*ǃgJI5JSU78>Z^ğqQ>O9siZ?:k7M|qښԦF@RN)RI44۹QG\QE43;sڌHJ;qGz3۽&);={GF}3Ҏ(J1I*0)1Rt=$Fќ zSȢh9=h(F{c23F>j3/֎)i3&s:jhG֎4}h=ɤF9&.FqIёywݩ{{RPzRۭ◜c4iF8u(hK('ך^3֎R~t֎v8t掾zNH|ɣ=JqAޓ< P}ю(ץiqЃK搐8sPqOZp.0r:RN8OS׀*EaS{TS֬G. ZR}S` <㹫i*5:8=eq*x5 aԀ:vi7dFyg4pQ`f[Q1P9KUyU$8=*Hh@<׵FHRpiIjPrw4 R)r1֌qGM8FsR 8=OH:tS) N*T9jAV#b:QNzոG1'n90O5a&ԢNxH$74^3KsI掔G<L5OF瞵 0U%#֪Hj;UIUW<ҠrO~ ӊFڢ'ץ4)4OsxN4 y掇cH8OZN@q 8Ruj^zs@8p(hQךJN`LPAP~sސpiXQҌRu҂[@$Q#9#JJ^!Fzb)O((t=h֎:H}:(փ8"KIId\{x4g3Rԃc.?:>R03GOqH~(юKzIi}.3GhG494Fڌc>c8gQ g:wSpAc?ZB9F:R='')4HO^Ƞ1JjPybFG @_ZQsIӚ^c4#i/qK;8G@gzx=0*@Z7jen2LXFD#zUcҬ!YFަSZH@9<9'R)|1֐|dwyLij6 zsP4&*\dQړzQZ:!=zьJhjN)sRsH;▌Ri}~b LqJ9ޗ ⃒yF=(}hth>R)s QhڎA;)Ҍڎq8uuKJyҗ H[Ԋ?Z[TƦI8$uV@=rzgդG5adH=x)r(FQzk53iNMF*8JG'@s׭A$y&VyN9LZCCQ7q9♐O^h1Fh#Ӡtӥ.FzQ'AC=iA۽.{b)2iOR):RzPOZ1})9◧Ҏ ;R QE(' xIFӓzKގs29xKNAuqJ00()֗J ⎜PZ:QJ9֓sGKץ'J3ޗŽG(kz犈3byҠi528 rI5n84ӃӊcsMN⛏zfNizSGQI}p3INIw8M 8=81HxNi sA94NK Nԣ8~NIbOj1R6(4mu(isIޔ`E.8Mx>:w)JN4(ڗ߮)qҌgޔ;Qi1N8ϠҀ1SKZN4Gn()AGl "N)8ZvAF9=1@!ΝIh4 Zv?:;bLvFE/z(斓GE֐t旊:g FEQǸ(phx ֔u'\sJOj\RNh=y3Ҏ֔srzR&t?6?\sE-. —\P=GҎ'Lu=(ii; ^4Hs(NFh''8(A9=i{R~SJG43GG9qJ:~4ZA{y4J3GbwH^{R)8()sZ;u8sGz4җix֐wKۀE4w&OzP~`R֗Z=2(ޗ4['ty==hFxunsZQG)=q֏L8J&b֔I)QzZ)҂8ߵ;IKH:班SJ)1QAvڎ14gjQȤ$/R:b8y(ZASJ:fKh'sA:(;EŒc{0OJ^ {N)y"wRޔqr4鎴4=jAԊf{g89)&^"=ih;ӼڔM)3zqޓ$S zS7Qٽ6~)ZilM gÃFr9sMݑȤ$␞)!}1IۊAKސOJLsI4O4iAΐ9M 0y8◞jcr ~(h9t@RJ~>j20E/)8)3=w4})91h4qGJ4)N{;b#Qi;G/Iތip: n4*C'-&h=2(!w{1sE sI-SK=*#֗'z^gގ(J3gRRczZ: ;dsE.xߥ t:zqK#8GAQ=qI@\R=Q@_Q&KҌ^Ԃ֎3(=h&9(/j;dQhy9)qbҎh^ix(Tjq  wi ǽ)3ڔv LNќtg3N);p֝c=zu+񞔠q8[Q֓=O3g L3֐jo=):f8&}zIMBi1M< N)9#F~^iZ\*2@#C94r):z4{G={R4b1Hph=y_ʗo!xz`iZ=猚3߭zu=8#aG98i; 1EB8ɥE!KLZ\'( NGA)xw()A3 f8IM'z<wni3S=(v#5zQF(cs׊#`s@<)i7sZ4g֎@^){RuJ:#ғF)z})Z\&{O`;8vRPz}9Ah< 1M>`uяt繠zҀvOl4{QM@^vA4p{P ;ҞhhqG3ҎNQ׎8f|Ӂ=xɩbnzӷiU)'Ҕ8}vw47ւ}|E0BsMis4&[i7gSr3Z7qHN)3␞!7Oc9F=OG! :wAK4tKIy4yvG4u Lci{'gۥJzP1 HH4dtqNqRKHA)9GӚ:c8ƃMA(4pE ((NgRѓC'b=Qws@4w "s@J=Eqڌ擵4sғҞ);u{Rc ((qKiNE/Qh4֎RҐc8=sA擧Z zP8G sN⎝hϭ78K߁G󢗭&E/JNhiqҌ`;g8ւ2irH3cQ4F tJsA_zpM)qԀE)88) ^ 8 Q҃Jwr *;œ)#&8878gހO|SސI;Ri09w)jC⛕'!JhqH~!!MIH֔3Fr0A84 u֌g<CqޓIg/;fqIRLԊ3F1A֗Iڌri8hǽs_zRqJAcK;SsڔS"g:ъJ^&4'8Lhϧz(Gt(=( QߚNRGJCiA~4qP;w4hG iOO/JNJQ84ʗފL?2:fT֒hqAq?:JZAf.;&=8_Nԇ9 .}qH8Խ(4ǽ;֑rO/! (籥J1w8t J1Z^cA8u.0)>c#sGlgCƗҐHsڗ8&izQ@~t\RZ\s(>җ4gP(shGJ:ьc4u.p;h(hրh84tG=4G~izaF2sH0)GNi:thѐ /Rp~FxA"@g/oz: R?㏭A!Q=hKcAɣK1NLp GCK{J}zQ)Kt'ލ$Rz٥hJN4 8P{}zQ:sHrƒGL֌ds֓(NgGQ(Iߚ;9I8J1ҐIs>Q RdR(';R3ӭ'C֎IҎv6䜚3Ґ_&yIJG4HE 4P9949.;gB—3GjA3)gNZhQN('JZ:KԘ=h)zqAhMgZC4cSIz;RT ьt6ɥ<ɥu9o )F08qހy}hҎ}ihF?T}($zH=)=R/J3iz(9.=M⎝ڎP1c&@&Sɣ98)r hy҂sҎIJ߽Þg Rn&<'88 tnr1IP1҂9旌z>(xCGE&'S׊\cZn9)tcޏ)1O4@=yϵ.:qK޴GlgJ@h=x֊1s&=}J Q@`fCM'zRM>hCI94c҃I<ѓG4duiIJ23G8Ҍ=8'4HyGlQ8:уG_ŽKƓ7<ޗ'4g :у@>uqi'KGjLK(I֖ZLg(挚:sG҃x=:Ҍ◚ 'hFy^)8^2hhM&8J2)sIӟʗOlQzhғғtAG('4“4y> c=hv둊oҎ 'gRƎGZNqCr83֐@b@P:\R֌gzqF=.}hq@< њE᳚S^1@@8hǹ)GE(Q)=h=GN(@<ڌ{Rz3(*\: gS'/:P8ҎGz?SAKց}MyKғ旨(g4riri JIF3Fq4AA#)(F0y9JM284P0\gFi;Ҏ4pwgw3sH9'sF@٤.3'A#8jEAIQҀh'ۊ3E>t9j =z\q(擽('>`Rt '#ԹJ@O4uZhq)ǯ4(O4Rց^iOAҎ1A4wȢҀyRq^⏩Ҟ&(=ʊ9J_Me.9zL`یA4)i;KN; V b֐^hK Php{2qւI4PN)sHh@g4r(m.y@>ԹQ)3ޗ8)sI}xHO/\@}Kӵۭq֔ 9sGCIs_z2ONsJ1Qɣ(&h)8::&=hgsތ\cs@==)x'֔=1@2)yH;bz^OQIFx(cҁR!sGzCJ: NOSFq<OɥiGj(秭:PO4RvGNcރ*?R)/~i:sHs?z^vcҗjN=h uH3RH9=(< 挚\c֜:Rc&K&9qAsKKARb:JqsGA)H9< P0(>u\R׽s{S{vA){ў}((^u'K҃8s:sKjO/J3ؠ{4R?A2qIcKsI֎HyiۨN1I84g4{(jN8zRw◐xg4xރi?RƂ ގ'dt"\J3IBN{RRs{HG=);bҎicSڌ(IA84v=(Z_jOZN/ah;ъ19⎆#җԄfRg^ƀOPq&G J@/>T|4 (;Q3)x#)QJ:iGh=OȤp8t擓Sp{qFph\1׽z}isHxz@Qwux}'9␀KAMgqGsKGj1Fr=>"Ύg&x◸`qޔGoF8#:Rj);Ӳ3LjLduvH84E:Pz v 瞔g$sK<(G)3uzRi1O1A8t( ^8cI2N9օ ))ndf=iy3i:ъ1:QNE֊^g榓3ZRr)3RF('89rG.=i)1(x3Kқhޔ>np=hɣ?7) 84—؊N;QIKדIJ=h tOJNȣ4v(?jL`=h GAI߭-w%/@i=Z(qLvJ\QRbJg){QF841G":LS(4hH0(>J0h◵GC&)z)HcPi3s@@=4~})zHiEc]9ސԴchq@ޗ}iq@8848! 4IPZ;ўg)$QG"ޗ4׎tQh֎P:&҃M!4sGh'9RQJQ9=.rsړwۊڗ@Z34^hgFhK>()G_j HOAڔQ'Z\q@GzCKQKA\cbG4:~/J)^E; 7{Ri:)i3^w/IKҎ( Qɠz:т=(z3I< ^旯R{-:qڗ֓ɥ QItjNBUԔsc8I)qAM)>`c@ JCӁր1zQcA)zF=J:{ QҌ {R 5<P8z^ZLgPiZP=sҀ8hRcR'=qA4gi}r)GҐK=i8攜 ⌊oo—FzNFhcӊhQ(ɥ9-!c/b)2p)x94sE(`gyu֓4 rNihs֝4SJ)J0(\M.xQF8)3JMOҊZNsJ2E';4d҂{Q—ъAQ? ;R&'CKA=ǽP=p(4}h^sHAgq@P:iI&1^Q#qF~qM}iϵ"9IJ$QҎ~G\GQZ9ҀNiy?j8OZ BǃAK(tFxGHq(sҗ&( PI?ZNf4;sK3h'?JzzѓBr?Δ{Rc?QFr=(1A=)Z3GQzS<((ԿOZSғM@q@Ky4{QӧJZhRNsKZZ48EzRfRd\c(9J1Hx?/hAAxH#!_ƀp3AzRt) )J:f8⓱?΁֏Z8 B~?PxړRg *ZNԹz\HsZ0E3ڑfM#ހE(Onh#K(.;⎴c J3!)7:wKʂGғ8MRZ_šx;v8zRu#KG4)9):})xǩ~w>ԠsҊ>wrhhj3A<=җ =szr0h׽/i:ipqIAϥ-& /֐qz^qҗqGz1RGJLNh4;Ҋ3ހAb(G c֓8); 9&(:4 ړJ3hf4}iFt= %&:bƗғ8Ru4izsGN h@(.;ьRv c&(@HE#^Z>֌qA.i1^ԔҎ_|Hrzu* ɥhOQ4u9.zsGIE(^zs:hFJ8ڌ:ӇJ sIfJP) Lz :Z1.8G#ނ=(49Z4A=1Z^zOt(( H) =hH:џRci瓚;K֌PscQ4tȤz/4uH}sF0hFq@}h#=}hQr9#w(#I) 4`3})Ϯ(@ьHh'Qrh@})1/NM.}?Z^t:c?ZCEO^)Ói F{Pzߥ!@@ޓ'EE&8GZҁQ9'l:ih"3֝ғzvJ0sڌRp8M=2)G?z1J8zRKsG /4QӞt&֌Q(փ=ghzJ{RM/z:ZBryۭ(IKZⓥOZ;J(/_jZE 4Rdw8瞔ўRt4J(=ZOPizZQ:P:ⓑҏ(qK:21IKz󢓽-F1h4zь14qFN8P:s@RFh=qGҁGozN('~/$zQh8&sJ8أ?5/Z2:w3G4y44=);+t(QQ4 &:Q9h#;҃u'ҁ:KҏhtEtQ1hR ! rx7zRq23G4w2x{R@hC׭-!I9">tcE!F8◵&(bRO|qG G!"2! AFzRQ4zwp):8t94x:Q/81GFFzRXJz^=;Z:}h g4~Tg֚:zQڎ3L4ގ:ҞN;9擭旧ғ>)sAڎ1NzSOZSui^=i9~4w A=)y=is@Hnt4҃@uc"({>dҗGaGG8ZNOҗ/&CA֎Ҏ#SM&}K3IKRZnH<ӻzRwƖ? sK 9<sKsQNԹh=zb 8RqIwGJ^:LtIQi@>P>3ރF2)9Ҝ8'J )GIF84cJCAtZ=QFGNd==((;юhKjL=;OhQJ:LA(#ڌ 3ɣ9h4{R~jSGZCNi1J8u 1G&pzRғ>f}>cOҐ{Py4g sHzQ(K֐^qFsJLsKHOAJM&i€Š)()⏭8& R҃Z: 1i֗j:N.Nx!@ JyH#ޛZ\}1GjNփҗԜt)OJAj^Q4%tFHS(ϨHHuC@K)23JzRtJ:(iO*i(4w(qPS:9 ##c'=h?J2E s>и8JA4u")ޔ(u?җ=s84wyw8dF=&Fh΂:8G:Pzpy1׊LuK=;t҃CF9EOj1'\qGMqEHɣ>dP3֎ A@'$RJtI{f~4tiHt;R}҂ E(#&u=)z4;} 5~(:QKNj^ :F@oZ=> t9&9'?Ғ>c1@Q\ȤJ^(}hgK\Ri;Ҍ4Aɣ(~41KKь);tǯZN((f @GZOΗhcq@K4piGA4J9ќ \9JN14 >'cA>ԠOGZ\ ǥ&y'p(isړ=iGq@98Pzq֓:t)QzP2zj\JCR:z@>g4GC҃z3G3@i=h>4 =3KNyF{POj=gus֎Rfփ4uҌwޓ=2)҂M/jC@>إM4Q߭?&~jq LgP94N&tRFE4vR($G&QF}ހy#=zGM=ztH'Ҟw?֎xfz=hS(փGQBZ^9PM.zP(ݞ~IGa8Z(E)Ibbi ⃒)sJ=i2PzuZ34霚Aǥ?_í`zCJP~sK@=sE ӜPJ21IzZ>^P3Iۭ|u(=x!z@HaE(掟J(Az;QKZ=Q}(i{QS 'ץ8bp.9AtIFG~dfHF;ҌIH@Rޗރ(S&G;Rc֎w挟ZC׭/lRuҌ֌RvRiw`P hMbҗN3F8J !?\qx@xP3/zNc4tJz/jN;g.N(Kz^Ú@N(<JzR ҏj^қKs !29=1GKc_@֎s҅hQҏE!)M&>\/LsG9G_=qJZNiH@}=3@#Kuӵ#`RAϵ-l4ў(P999:z_H"Eh#4`3JFx4}h4tRJL|isv!Z0:LHǯ!A/zn8iCGzNi@I׎ԜQKޓ(f"J9qHsF;>Qh\t @hޏ~M(NQM- c<q;(IMQH3@;RZ^u()4J3LKgzQ!^ݨ֓F8KނI€G)#%ffG_s@Gd`ќQГKRԀZ|)GAG|GH /q'~fh4“(8#)x?J:ZLsRc֎y:x΁Kӵ'> S9?:\F(1AsK!qF8F0(=i1^޴s/I9G旨ѷQ҃'^r)iOZx4 K ◟4g9t=&1ҁɤ(Q&bj34u4ހrO ގ/Q֓#8/Gt4qv&:Qۚ3ӵZ\擒z~qt֐cޏ"'z=xbGɣ4i3_\Rth.zb'niGGQqIZ=AE&0iq)r;dc΃t(rxKғZNQI4 q@M8^iOJBxKv?x3@ԟCK4֐t$;RF)cZLsF8>GGSH:Q}hF0sGZ9tڏcIFiIjsMCANi &j3ǥ1JNxzP?”RcSCK֗р(=)#=G&h"t/j9P)qޓFEF?T}zR)ӊ:fdihsthA&/qEҎf'4J9Z_IzRz\G%)(8'җv9ќzQ3ZMҌҎz9Z:})HJ8ZihRg=E/ji=)GJN?:4sH /l4qGj4(⒎RPhqJzRJch3AуR31@0z&=6:/\vryJ?:O8=PqJ3RR N:(hhMQ@4<ҞhHhjQA/o€GQGhQԀsN4v4 ^ނ8s@烌Ӻc4pE1z1P8tFs)E 攎uc~3G=O"ME.(4v P9@{Pq;u=h+'^hҔg!G֝qF4G|w{J0 K֐u`;})G&8ց'$^I=)hP@4NsGz9h“=hpy94z“F)OcR3߱z; )H}ix\Q:RƗ8 4Q Z: :$qڎZ'QF1Ҏ8~C(&PhAЁ>`fCKތR4/8Ҏ;QҌ24@>cўwzQchGj;rqA8I?={x9x88(Q4Izӿd)1zR)1BҏcI֎GAG~g8ۚ:M)rMڎg@Q:#4wayF'֌ќbbHG4gJ3)qғxGQ9掣jA::<94ڗu4wKޏҎ;Ҟ&q@9U- }( / -4sN)ԇ/Ґ)G< =L_Z;{RgiI$(S LsKiq'is;ь"F3H9_AGOZLw<1R ׽Z4֎4sFri*ARc@&t=Ozz13 >t<\Z=h(Oz8@8=iGF?Z2Rhf1N. 7thSIQRJ94{R.yޓ'>{c/ZNhh֌dqHy;v9f?(< n1Gz9֔ N3GOƁwQKi2sM.=)Z\:ʗҞȤҒԙ>x8^ܚ9d@9K(lqHizRP:#AҊQғKۃF9@$]qF8.yqK'׊2q<`4Q4g4CIJ{ :qJ;>d&hsA=1KGAF}Oxt88h{N ?:u/A֔) 8x '~sGaE.rp(#ސIi}F1A;QAu3KސS4=(RfFzR(ExJ(#&rA/GKB);QۚZ^:frh'җBx4 CJpMIFAvPzȣ֊0 @ftQڎ(s֏JNg=ԣIѳK #GJNь}(3M.2h!<g E3G恌bhZ2HGQAsI֎◊CF=)8hg!=xwNz_@ȣ4f ɥ;Iq(4Kd;;ސ)8Ni@(=E&23K(hjJn9ƌzQڌ)J;R'LќtNփQȥICKŽޔzсG8>r)1\cJCJ~4o旭R ◵4{斃{Q);C^(0h&B9J'Nz_)sڎyILz Qi$dRJr1K׎qޓQ<3L>GҒh(N3F:KG~~v}h>(ɢ>ޗZJNr;gipOJ;QR Z03ʐZSj3iҊ1ӽ.>I/oZAFvi:i}GzNڌ{J1@K4ΌqA<(4qKғI1K:ќqEҌc8 QPzQAJP}Fi3@挟Zq@JZ@23Kޚy}(PO4s=( ^Nt43@3uF;wFhF;J4 Q>ԧtq֎9ў“qKӚg/ҏʐƒ(sKNqZ18Ͻu&yMd@3M ך1IxM⓮h})O=G֊\Q4qh4M9ix4qڐZ@2}O]qG_“8ǭJ^JHKҁӓG֌Qߚ^`g=3J}(ǡ$ Q?“<\zwLR~1R}hR擊4sPьP{ ?'^v3ԿΒQF8j?1G~Œw&qҐ :h ҎzLQGJ(:>Ɨ#)3J^hhL4qE&?*=hH4sIԚ=i2: LR:qG=ޗʐqj?){4` :F(GHR~8'4A斎 t9F}A#>t9)z:Q)9KRu׽.{fGZSҊ)?R1gI{vьcʗqI?ҎHڎj;RcZLiyJZ_Ǝ)3֔j\4)i=8H=ihfhZZNh@4*_U7#?֏֎4dϵ.i֗'qI8"A9ӵ&h\0ifu{s(8v⓮2)1ii8}(=x KѸ(x֌{Q(&2jQiւsF;FG@Eb֔Rgɥjn){KjN{QR)3ҁ44{z3Fh㧵-&=zR4?^q>M/=sȤ$wGN(RtjQA<GJ0=iN(!>uQP@ Qc#1E)3ړR80(4LQ(H:u#Nhh84t)Irh#4zqGQIi}b)d@q֗3FsGJ=hZRg"ޗ'^c4gQҞ(9@uғ\wGj3֓$SځҒrhGќ1;?S#ғI/Z1A>gڌQ@i0s>bh[ր}=xN);:GJ;vu+g8GSGLwQ␌A8)h8ǽ 9Hy=3.pyš:S)>@4֎pGQޓ.1FȢ@"Ҋ@/lQ-Ҏtw4:3*9J 'AG bԝ84(ǽ&h 4yG^QLu{R{QI9@!Ҍ(9&(8vu擜pN=)Oҗ┌=Kh Kj8J0qGnG~Q(ޅKI1i JA4g4(xGH/^ &py'"~(Mfi@ⓒpixA֔t492(<u4gGJAڗ'J;P9)O4=)1MڃRF Py(t9ڐhƔ(7$RgP8ޗސtCA$4t<{QƌSHry=(/_cGl:{}izAdc@@TIґ9F<ƌΫFxҚ@җz='${Qړ=yqKŒ0z)hAzBiGJ1Z3Iǭ.N33h4@4)? ^ގ3@4u< 1z1F}JS> ^ގ4i{htp(;PM/A-'|R=zRsJ:P8sI ҞCӽ@4}):{LRwQ;fqi sJ(=i;Ҏixh&()zI'ԝ(('KGQǭ֐sN9IAG/SI /94fڗc(4g/ғ'EFyjLKAҝ~)4ۚ_qKJ3g4Q1\ws)>i8┏JLsK@zߚ1Z:Q߭'h/JE R瞜 8@ԝ)i(4^}N(^0O~(44 ^N#sHIҊ\ci~zLc_ʓ8'=I3Kߞh(ϵ&}(;GGSG:(ӊ:(I/zNsFIN4(=)E/niyP}(4zQڎ`ǁI@=!җ8@>R /|PwS F)JFi4$G)8 @;ހOIiIIۥE' u9 g)sIzu'CJzui3\cLҞ(NpzRv(4'0rqF9zO|P~Խ=(ϥ.OLRRȥt4^1IޏJ_ FA4S@9'<tQAPҌb: @J=y?z^RJ^4'ZR()3I8Qړ<杓Ah@(h((HQG|R(}i? yG}h9'zJAJ4Z^# 3/SIޏ/'n:f$RPy?'lǽڎdG()1A=-P:{Ⓩ#zH13ҎsGKu:R`").y␎sxǽiLqҔP:9 ) ɤ=yJ\QJhihQb@QތJMGyN GP(8R=3)Nh#SZCh`Q{ciq:RxގJFtwdfz;ޗқ=ii撝HxiÚL :h{1ւF{PFE (GCHJ_zt׊8(ju/AsPh#/ScIJ)3тh>)GLzRgQ 1iz9<>r9.xKn  ~4h3ސ/zP:I!#O4ޘqH1h 9=)E!zu&(RqҌ"ݱG/n:P8<۽>humqތb0(94NN(=xǥ) sGi&)3G4t3 ɥ c! {RH'4撌zy^擌<)?.x7Ԝt4g=y4~43G⎘ҞIq֗q1ךN}hRZCF99wFsJ=Rs RF8tɥAGj13ϥ/ьRu4ޓގM-}is:挞ԣZB;f'Q/JNv`LR?,ю9R NhO=I=~c= ҂0GZ:x")֓HG4cg'zz:SJO!ݩ{QIStC.}i8Rc<ҎA֗b(4dcށקғKQҌ{PIӚ>`(FbFvǥ0(֌{R _Z ޓǥ'ZLssFA:R`}hC4JLs@hE擠9R"H8"IZ=)sG%)4QA7 GLҏzC\ךNƊ(/nzO9aPO4sG 8Z4)22jvsL 8#(KۧJN|惃9ԧ4pEȥHxpM'9<)r CקZQQޓZ\Rx.9oJ\dsJ8~yҁA'\RJ3?hs:QzPFzRzQ3K搟J\t(9&;3PO4b=E&O\)2 ;ZAdq@8ڔ:^g=h(vgJL`fr(8H:tB;џj3;xIОz҃֓9\ џJ)ڃ1GB)ϵP=i8?Rz@GnM(FphjP@ Q))3KGQG|NuqNzGSGwHs֏ƌך:z3J~RIK9piOLQ1Koz^֔AKӜRbq8K@ތs'A:RڌcK֐84ғюHu t)8"tҌzӚ4t(`vɥhJ='Jj9)_ΐR:u wǧZ8)y?C@qKМRPFy{Fh()zqG~(9? @OKۊL?AM8&3Kۥ'sKۚL}h9FԹIK=_v4`ZOtlb3JFFsH28@Z? )I/Q@<4i@)1ڎu c8j}h\J(z'E("w4gqG&3AKN)zL4"qL֑}~Tg֌c$i@^ B3KsJ(ϵ&hǭ/>(u!Z#4ZZCGQ ◡4u4vf1E.GF8<44u4⃐h'3g4F*;u8 9ׁG4f4vӚ94q 4g(urh'(Uƃ9iqI֔{R R Ij(4F}zR;NhuRJLR$QNr9<Խ=(94$Rc.xRL⎀xKRKӧ4-"L:~~u4.8(◎ilQKzRHLQPxьu4^A@׃KAF}'#('I8(; `hLv49Z~)I8HI'$Q)sqA>+ғ&3 '@{P>zsH Cg4v#(9G#4zP9~ZCҎ}hJG4:Qў=ҎuNJG4sFA>ߚ;P=#8֔(M.1A(dc3ȤisFHq@RGa'KgGj1ϵ4gAR:Qю)H' J9<<֌(M/{R /ZCtgRqHxM/~vFO4G(s@ 旐:1GiqAⓧ>gjLsҎhNis^i@M9y@KJyi20(Z0yI\q"z(=9@:=\Iɥ_Bi٧xF9-&< J\(cPF:u&q`4c4Or '?)(IK׭ ҁHFOJ\ҁ@A擐(HAhJIG'J;iÚ EGJ^4uRQ(O(P9w:~)8(ќqFyyF(wE&vtތRb(M(IMޣ9{A(>iqAރh/|b/Q&={⓿.1ӽh&~= RI{PyHzuHF{PE/CK֓8Qӊ3J?:@zKLzQw@#9掇3/8PG2zP8֗&hJ?9fg>cQ}Rxɧ&(K'4<ѷt.1&;RPFsIi@np{џʗcҞ)QyH>JwnzSg>`q9Rv~h=x<A'=:IJ֎{c&3`&qR9t4u4=c'ڔړh|G84PFh4dTu?ރ'nihP0 K'M#:j\gF8G~JNsKG$~4Z\{wgJ0G4Խ:Rf(291G> 3zQF=zPF:\u;g9=q(dc.@OJ94%fAN}1;RfwQ_J@}E)CךsAʓriy NH9)@jNNr)::PFE h;9t ?/QҊ1}h}(}I=(jo;iOOj'nrhh1HjS蠞\bcQA$4hGҞxҎAhwHG~)'/֓RIz^Jj1&yA=J94`}=2wK@掇4HKNJsS@izf:A&u<:p(G?0i{cހ3s=iJAAs@L=)8ϵJE&8Z)zRg?!@.J" \Qߊ(8'ϭ(PxGzJB~Aiis=):KޛJ͊RM ң<#ތIQȣ恓֏ƌsA.=1Gc Qߌs@C.0)(GC4Gԃ4zK((fRs@u1J=8 \{q3c(AKғGϥqɤy'n=h`ip{xQϠPG^zJzPAyh֔Z9ҐZ_’df=cPGC^g)ȣj@ ;~擜4( h\Rڃ֐t{Q;Qގz{_409KsO%'.ɣ4cuZoM.0@.hN2i;4rzzg֌tڐN{Qq׵ڎ8ʁւ=:Nz34ԝ;8aF:s9KZ>R}J3~t掼ғ֎4h/84^i22:u1E%'4&T 9Ґ QvɣPs*L g5*2qIdhϥ(Rw֌gԜғhgKۥ 9gsiy4t'йA"R8Fy>d(w&N9vs֗?ϥG^2)ndJ =(1J$L@A')})=p)F9Qh@sFH8

=h83AaIߵ)=8җNi4t@dJc#'KMKG9Խ3ڎZ\RIZ3aG'J:ϥ$Ki> `Fi>tRqA=E'9ށ@J^1ɡFlPx B9uA*I߁@⁃F(Ҟ ZS1I϶(lu.=Gz;IIzv~ޟz1K= #B…(=(' P=):◌RqCKސ~4ph ㎴KhzB~`y4sIj^zcPzh(?2vM4v9iizgs:( 4};4cjAJ9=zP:ўi{w~h$/c7<=3^@I4ԙ&֐ԦN룜 r:SIqOZ9#ҔpzF'"q֖ץ4xfNqFhKs@K4tJ<i#9i:)HނQ׊\):zsڅ㌚3iO?Z:h=(!i@1Iގ){Ru4f4jNҗuGNs@z^{RqK1@I&}8F~{{RsF'RxJ1KǭRcӥ8:{Rf!=(zRڗƊ:QRg.ph4@4qFx9A'B?-I҂zQGSI=zc{g-Kj${P&4׃J8CA!<cGK۵ ӽ)8ǽGl>`;џJ;zR ^6z zR)GZZR2=hQ)x29/SHz/=(yI{Z4MM:QEJx"3GZLz攌 ~gގ f9#("Ҍ`J=hK׭&I=1@RiG9w8v򣿶iĎϯJ_a֓.q !<Ҏi::Q/'SQJ\FqZ8ϭځ^s֎2MI^{zҀGҐO7Ҝ Qь44zA@F@҃Z('Hr:Ғ1ӟjJNAGz1gr8/Rg(Glq'.xG?Z;jJ\Q1&1P;R(NFZ`PxRgzGN  8 K֎E)?6?Z zEc< ǥځ"JqN~(={<&=hiGIQՇ)SxoќҐ)3Q֓G^wK1IތQڗQE.x4?SӊN){ta@hw^)9wzJBsҌ砣 gғdQSJ}=y>R:zv.;RƒE(GJ3֎@:z;)iKsڌ}3F;=zю9G><89Iޗ&N8J=(g'dsF3;RR{QۓMpҎ?#Gz? 1&9&;r0hTF(N(ޝ9ȣMR RN(׊1KE4.1w'4iG)(֌sKސ34 g=RhEOz ڔg2){Iǵ&8օ9=(&ր:i1h=isR}M.qAq@旎ӈ҃Ƞd)A@Kvy/N(=G>ܜ\ڃA? ^s(tvFH/S8IɤN;RM3٠gҌ~TFxҕ =9Hqi{bRqF1֍ߍ.OZLڔ >J3phq@'8FA=);t=⎣4t>Ԙ4 4lP ڌҁ>89{q'j;Ҏ?B (4֐ QӨ4{ќRs׵(sv;{Rtg g4188\QԚQhzR6֌nPNCJ0'` K1֌PzI:Ҍ?6;Qޗ(4rFMҁAzRc^HԃQ})p@4bGCGSӟjChcG#8QK AƁڃK۵'@c=(JΡr~g8@ғ٣y@r(h8G?CAɥ'NԾNh>wiL(^h9Ku @ҏ㱥3Is()rhy zt掿ZLwK{Fp~g#;RsAK84`x#/Z3Q44iǥ'AԹi:}iN;zA=}!< : ? ڏA#=E(ғsKG֓))zRt4A:hRwJ9GG4qF/|s@֒s֌hiOq &pqN< qր=i:/jPGaHqь\{cK@ N18Өzu?ʌd/i挌R:o8ɥt^i(s4c=r1ȢnzZJ);(ir3Gtq'hZ03IyJ =ipM(=9GgNGqA zSAZ֌>ԝizt'"iAh>wuEzQ.)?(cށRzqG}i{SHJPrN)(Ru:sGNKIs_ҕz4sI׊:KA9`׵&Fh4{QGls:j8?Z:iAv@4RG4zzzP1K:#'^zJ9)2Jf4g~wtzsKϽ!4)>Ԥs@h<c2hv4M8ڔt4(=8O4qJ}z ><sKIZQ1K߁IօF3'K4vRG4zRg4b&(ǽ'4J9ZP8r)Ӈj9?JP)1KMwGLр&RNiz0G'(9x7qj( FQɠniyI9яIތсu:bdP=}Qi{4x=()O֎3ލI^iH(;PI⓷=h1 OZ:w:Ғ{P<}Ƿ4'|Rg$qKM(J=iJ89N)}(ȠP2yIz֐g8z\c GL֗=ycj='lqzg#"`fth'SAю188G֔nJNOnz94%(FhfҐ@◚J@ =iy)NxG?Z)jQF9ؠJ44vsۭ. %hڎ G|ޔsA/^!g'gƁ>ԝsFzbG4֌qZҔcbAg<\fpxh#:\/==Jyb4)vс;c4т:P=qΗ&ƁzLzҞ~cNs9#ڊ\LhIx=)Hށz1sHG|@{Q1AF=*P};ZShZLQJF~!Pi@ RJ8@OaGj jR(ҁڃ=(=ғzf4=A4?_E/ ^s|t@JIqK4wROwR{gP:8<$^G4zR ޔi9v9(=lRt8QzQ@(KsGGCҌړ4wEixIJ}GOJCF=Fyu'P? =qGHNp=hCJҗQڎԝ:Rގsڗ!R)^hu&G#IAϩJ:bCh$Q(9ӁHr~c=iqg>ؤPq֗ސA.8ONJQޔh>`47~(ю=)y4cLsIߥ/֎Z@1ڂzbu擜vyPz QJ9Pz R:(=8t:ڐhn{Q3F3g u*A֎Iht`vsF2zJGjCқޝGcނ;=!Z^ztgfAi:c;!JgAM8{SFxG\fяƏJ:E&x(qJxrz^9$J:-#dҞzQҁFh&SAKHF;:9ץ(HNM/9'JCҌ 8sH=9 ju&35>qF:)G&}(:Qߎ(Ҟ4&>Z08I4qҁj84g]RRRr(@9GZ_t(=  z21=sK9'=H/n:PGQ֐hTQ"= =){uϮizz; {h4~TKpi3J3u旷8p}i;ьwNfϽ&HҗbӑJ 4I8Kқ1Q@hq֓## Qۊ:h#=h3ڌ4>3_(g֐`/)Ҕ`Rtw(cN{Ҏyu)HzGz1HNx:Qrx#('/^֌qG8!4)Gnv9=hq^):g41V/OqGj8y"h'.8ғ')p9x&F1G9dsF3RG\ \fPrpizg=A $ Lt;փ=:7h=ix#?f cqJ: Nz@&J=8 #Lf9惌dJ !9׊^I'(sւwQE): w8v8JP8'ZAJpGZPh;R0qQ;R:(/jCҎt&'Rzu3KڌqJN:s3iJ3)<Ѻi=ޗuG~g֏j^E'qi֗$zRc9)䎔;%#hK =( L3SQ=(z9i}4}擧z_zQG~vF)p}i8K{R89.p:jLu49ϭ)E.&xR1IO7◥w(=hg=p)ztѓbZ:ґi9@ڗ#bt{ъ2@RG_7:ғNi{cI@J'iq"F48c4#^z=F4vvr1AsGs(A` _JONJ Q\ 498⒜N8('S֔Z2)9PGjL3ڃ4J3NԀqƗoh=4f)zsځ)Fyсڗ֓4z9 SSO(==J )hF;ьs.sE!?ҖHNi84֓/lQz\Ir8xⓡ`(>ߚ;ь{Qߎhނ9pq;P=hIʔd:Rrp(Ґ1I_aMtZSRHznpO4`cI$J1ߥ!zt/OƐKΚ@OzH9c#(t#p8҅gx,s@n;RB)xǽ&3ސuh'Rg-c3(g4``8@i8/QM:KN)8ރi;/`D>dc/ё<3C`ړ(>s)AP=)Aӥ$4cڔt'IǥK /sdcZS@ތҜʔ~t@4)1iAA֌Qҗ֎PO&1/z;ri??HdPG4֎(x!4i^yiE&1Izq(3G4{ѻfu׭&=8ۚNNzfԸSIn(RFA@^A#x?Z#sGoJCp^y=)[ #qӚ9@S⓶sւ:`i@ZNiҎ(Ҏcj\sI:h<:Qۥ&0(.3OǚI{RG>{s)GJCJ'(֓}i~TK7;RP.1Ni{udu@"J4c03H*^?Iڂ1Ґp.zJi:@#K2J8F3jAJO4t\ Ozp&y<R):RZ93\A=Qh(zZ}:'ҔcR zSZoAKEz^FrhG׽'*yA4ipq4cޗց4"9{h=hݚ^RsFOʗhzQAp4u ZFZwzCzPzu4֑G/a\d M.)2qF;ю8<ґIڗьzg/=h=@cގ֗N;R*\g^sI҂1<ړ'g:^(KڛK(ځsF("PyA9'J^sA;K '4$RsBs9d{z擶(9#AƝIJPJ8GIPp}i< ^ "4`'ցgR@J2}ڌNI)\ހy}hۓqG_җ$tz@&=8Sv@Kޏ‚}hE'Siނ3(M8HO('R(Rc8Fʅנ{ўE.E֐Q(>P>}3KGn8(!ph8"P[EE ml P3:R ґ\b ((9ǽ.88y{Ru/jAGNhzAבSi? ҂y$d=F?9G8^ 4 j\b 894d=i0sN'$ qAf=iҏSڎ7ޗ$q^is@x= yEj9ԧ' Prj;u'қi{RlG2(9H9iy&OaA)3'ZSH8AJ1ך1J1j:Nh":9◿J4qA4 '~z{RdqO'E4r3L~QOj4KڐsFx"R(/AxϽ 9h43)p3Oƃ@QMF?ɤߍ|b iph(t BHP3g)|RfQ8JN3QNsKQzZ1ONqhKL (ɤg@/J1E8R`uGqGuSNzRHx((ON0{t8'ZLrh=)yhG{Q;t QA4\`uc'=x⁎QE'&iN})9ځK҃ CHx^c"&Rw4)^ri+E(AAP=]R;Rz@3+)JA9 I:(isQR{3QQ8t֗4sRr`Ҏgzځ #=/#$ ~INc? 4uM *zJSG)0Ni9/J{:zA ;RڛKAh(8փ׭r)q 'C.F?JzzҒ:b:;P=GP:z瞟ȠMҌRΗ&O~ўR1H8gz\RGu4((:Jc==(ihR\{Q)G4sJ=h>杷N F)j1OJ011h'^Ԅ`ь`) ҌRizhךOF8f~vGqh&GHxF1?J^Ly=({Rf$0sgғ8G`IzQh'iGK=O!a;Hhɤ=zQQ␒y4`fF8Ps{ў0hTg8h+Iq.82i88hў((`q\sϽƓ B_z\9Ԁs=i:PqKL*"p{Ҍ44ԾR'AEjSIG|wZB2yK )\wlR&q3Jy4iqKۚOaJ?'Cޗri}ss@FqրEzR_ғ{RsKi)@))1~01H>pO4bB90x&4)J:E.1&~'ҐucZ(ZLsF?T=;R>y Q~4~cPr;:gh'zғi148" f(E' q@/J D2{tqGj18"RZ9qGAKשj>JN )@KxZ\cgvu8w9ǵMҞ :bacFr)sޓ wQqKh"=M.8 r8HG9sך9挌q@ݩNq/J^(nc\~4v#tgӚ^hJtvSs\9棡⟀iB2) .)xJ#;e*=:6S4':QJBtdϯ(#HZ6M+G&0i1zRzSO_ji2;Ru4Rb=84t'A By4 c֗1IҗL4v(q1(s TIF{G|Pzu@){ Ⓦ4E'f48t=(ړ8qI4Ҏ3֔SHRHqڃڌc޴^hrsE'sJ:4Au4)N@zhHx$ƏA@Ҋ~i8hzQEAF(@Fxⓥ:q 3G9٣#("sҔw◩i8sK ҜuR-7R~ЌQ@# Q8z{t '4ӥ {Ҏiʎ֎M8GJ9L_jC֗=`wLQ\Qzd^ZZC@&)Nx掴v4):hǥ;4}{)zsGQ}ix{@҃cⓡR sZ\P94zPF>cR8T {3qQG֐:Q:A!㸥)=sN; ҜSy<GJr>&юQ9p(OӼzuU zUsԥ8ր)J`ێԅr9TcqҢ+h`ңLlFS]pr)6QȦzgIB=zPF(>› ; sMh84ړڗgjZ^(9QNgJA_&3GN($3ǵ!iAr) 9NqOj9$"@8Z;ғLP{RtϥzRz@84tsJ4x<`vތ9QR)ɥ/$R=qIzisGO=y>٠w izAȣ8'$9m<Nю4=<&u'${J: 4^ԀGS@Jx}hZzTVR"S4I1@+yg␦3n@87SsL)rr8֙i69$`0Ozh!b}J;4sF #u4(⒀sF0i.)#ߚR9GҐpy{R) '`b2yz2;NԹy$I4vyKIܜQڃ9 t LcPGCIR>)0sJ1ړ4ʀNh#=h٨(=q@&N}hݞ1zsJh ^J)sځӊN-JݨZ;G_Gz^1ސr=((9AE/=9(<@F2yt34֏Z^M8\Qޗ&}KtirsG'8Nϥ.G=>g4t▗qL 9ALRP{QF(sJO .rFix'ڔg8)qP;o9UzRtTgx8 SRޜI6jhzӊ=jEZ|Ԇ1dqDLX䇚QPy`z$Uq)D:QHH{8?Z:I>## 8=M4g:?f&zQў:Rdpi38Jy@ўŒH94 :z~f9 984N3=AKߥ RsR z1j7sF:Nڔu&yKPy)9b94}j.h84)c^iI3I/^`ќRc^1Rih @(ߦiå'Cԧ7$)Gz")HȤ=8 88ȡGi{S@iI3GךQAwǽ-Q|>/KNǜR^)9Fp(tqAb9␌:c4cP)< S@/=Qތv=(E)րqQ恃֗x旮N{QiH ӎ:RcP8QGFrqG֔M#R)}(cGzF=3K4w);tww&GZ\p3J-)Rc&ҝ'Srj@*I5jUSSNVdw#_VJ ; qV#`ZS-Y0B3ҤxrjB=({p@z-ӏJ> ;UF4/Ub1QMşA*LdNj)DFG=*R0Px֣HM zRjc.MN3I/"#փC)3i{}h')qM旌sGcLch)pzF=)OB3(*h u4E~&03@;)8G8P{zG#<揥48(s : 9⎘1z] ~TZ攊1%=b(HFs=h QhF:ZNNi~dJZo4ciOn@iHڐJ4 v)F9A?JpR/#*@94*qc1Sr{*DYUZ(ng u54qEXs*h@<.HR*!h^)sLtth2HUAPJ"Oly+Q^*FUrMFѐ*"Td?Dõ4ZiSH!n i1GZ: nIGn)9 x{ 1Kǭ%8?ŚNhTdIy4iI~4`:qRzRނ{ҏGcΓ=J8z=)Z}O=H8hSJ9$P(8f}ҎhzR>Q2x44'94)h=(֗#i0(ɥ.;S QҞ5 뚝z{ѓ\Հ:jCN[ WڥqbM <_gr:T6=z dڂ=g޴@?:4=iGҐ}Ry"Ru籥(z@֐=<}3Hrx4F0F:R44 is)A$SAIߊL u<9KMKqH qI{R`SH=/ԌRj;J:ސ}iqE y>掆8chOZ Խ1yގ{Eҗ9 CA ҚP}CP?*N1Q0oҫJc| T[GfP U}< 2 $+Qdf@ET)PJҫjy89ȦM'aAJpM94J`uqc"8MRB^994u/SHF 01Is /J2 :j: LRqGQ3@Kޓ(d10(=hN( { o5mc*{TVV,4qzTY>KUB;o$4()MNRI48桐rs06˃LuUb< QJ#֡? UIcU9UixmVu5]]ޡ#ޢa084=) {S1kK4pގFy)~)N(Kۭ&s8(h1Ii(#h:RŽ=hhP1u44֗8u$Qj4j29挌 iF)z1zRb_ʎjB1ӭ; q)OJ^P0?.ⓥsE 3ގsIcG3Q=((qM4S}J4:Qӵ>Q1J8ŒbcGJ9җR~h'ӽ(^:CA)٠c zB28qɦw'CG9/ր0qF1R G4G8Kc&@)HgH:KqGz?ΗNр_‚hx4cޗ˞=i@ 8yP2 9Tsȫ *C'ޮ銻^thیjҎjh1׊5'4KYjxȩDX>:E8sRM4Cԣ$tGZgZ9dfdsjҁǥ'8Ϯ)A9n4I.G&110I4Afґh4dJ)zJzH3)) u4r(H1Jp ⎇g"'~Թ8# ߍ.>Z1 4cigRqڐs֗g9IE(;Ҕu PIhI .0hϥ((qF}hG4"sC׃GQI֔!擊Qv{cNҀ33ץ9I#ސu Sޙ׎œqH4KHz>J=JLxNb(c9E_ZLRQi8JGi P8)x֎)1ғFAPy"`uhcސH)Hȣғw@OG_—Qђ(i{Q9ryu4g'.8:{y4s@G>{4isOHGJZRxi݀g#4 8/֓=)z(=h/zLc:nNzR;rGOzSԃJqSҧN*\Uz5[Z1Z tU1'5iSӥX?j#=)\ Қi8~v4)<уPrqAvp)A.zSEQ8H83h֗f4`+RA/Nh֎)9)@h')O&1J92Z)ޛRցҎ'^qhcғFI9Q9qڜނz3isy$"tqIv>tj0s֗j 4})q֎4N(Kӭ/iA9 < fUSKpMLbDKj5玝@UvЏZUnE[V"#=jmXb25>сVQF1ssSynEڡX5PylWD gQ=zLC.FsPzC5 *=y5JL׊>NyTXUf9x4R/|{QӑHO):R(?14Nj<҃@4OӃGIjJLN?&1G~)ۭ4zSރKHsޗh''ށ#jPsG~q֣/J2$gx('jsA }hF(=c^Ì{sKR(- #җ:)IZfv{ 9pj9Xcs&UȨH9BcJ*ž}*.}; *@ÞMB?F{S 0jF^9j:SON҃>㠠 iW'^s@)q^GRRbp)HڎMx4KҚ{ ^bi G֌ʃF((ޜb6q@ރQ@5=_—)3ґ@J&rh)GB@K֛ޜ9cj1K:SqR1JF{Rxɠq֎ҏz/JNsKQց9R2)A<~Hp;G_j80 Vf9SPJFjvBXBޢsT~zU+:N{G U0jבL2*6M9u4sNq֛OZFK4HzMRM)>hjM)'>)8:^h4ތCsގv"/L4ҐRIi~JsIߚC(8bw1ޏz:挏OΎ1F3H:sKڌq=Γ&A394gҔ` =?j.zPFƏz?iARϯG8F@Px8҃( x4Ζ4$RIך:izt(@Kփ=ցJzQLc/|Q߸-(?GA4Z\>zRsRh4p98J:Q}(T:bu#+zTJ&|DҪȣ#E㊮TjUr T/Q7]8C!;HJFTooN*Sgr:g9j6:sQ7 Li=# sMy>(=HHA>擭/NuT0Ru( Z^{RgҎrx4>4җ=J )zuI>^)>HI@Ҏ{4qF)1@4GlQ=8ph@z^@҂}GԠrx,QF;vAis!J>JH(g>r(F?*:Q &is4s)Gi3O(=r)OL۞1@4()sJL{т~c4)}g&8$Fpi'Kgc!'曎4Aw(:Z GGҌh'/~ё(&:LsSҐQ@94gsqIH9ь8s(H RGQVc=OAqn'քN@օqWCZj`[R0*}ҭ.:ՈzGL81ϵJߍ)\7Z{-5r4y,sڣ=j2o5 i!UOo/ Y9MWvڢfz!@j<}*U}?*֣?tgϽ'MZNE1#'qGҚsGHO4ϭN)1{RJ:.3/n'sJyMӹ`IJ;tEҌPIgq8)@J3onONsNҐ>cuaJ0;fd:sڗFxqF)z@'Czץ/$NZ\IE/AI J:qDݨhKQ4vG׭#'4/J3AGAFj3G#GZwHF9z=h);Pxt"i@ȠrOzR9󞸥ǵR)GLJ:(ϥ'hKǧ>vI^4cO&Rzci1i÷z3dcQ0 Pzbh)G^iyJ39Ny➸@:Ғ:Rt4y9r;z:\}i:}(?:1K{SӔzԋOԪAJ6AQZ`֮@^IڦPjuѶ3VN1Shc I52͜z4LINyC&ZkD_ٸQ>1UQI_:UyZpFyg֪N*x眜Gnz,ƫ`QrxjBZo|c'M'KM<4 HyьvvjS8989ё҂yd(4/8hOZ8I SvsGG48hF޴d8E(74"8=)çOA){ڎ2ARnȦI9JA=i:u N\ⓌGGEg4b3EԘLiO{Ғ3J94G@'8"} riAɩMc?`VW#qǭ]Z?e갧VutS58/GdI֎Z:sA/Zh)xRKtzR3ւ)q)7~`3J:RcO/JxaJ)w8oZctQ֢=}j7'PLǩQFGҢ,yDO(5JIsyrVWMSw1PHG֫9N*'P^ÞsI:sM8q=E!9NGn:QI}89sp{PFh F=84qIx{9ȤZS֎r(=F)h?ΌZ =4tnQqF0OLyJ3HqQ9"xZ;q(>){R`fփҁy)JO?9i{fh{QK);ӽ&Nbǽ')GҖ5ޔZi?Zpݩ랹RjT=;Մ9fCM,\TmvQZ/֢$.:!FsT-ӵVZ#U$ I:1둚\Qp="s?4gBxzԄq!4>9&N&0x9.GP)9ryю:ҌHI'K)sA=F?Ƃ~Q>g=)GB(:hџΎ ׯZCn(JOi8Q׵&rzPz{R)fMT@ɠj?'$v- Z=F /֎(( Nu \hxP A Q=(A8Esր=)F@sҎcށΌc1KG&ܞzRTɠ{P1PHzGS14GS~iqN@=(=zpiAg#8Qǥ/ҁ֔u>G"8Ҏt=xTߝ=HTõL3y֬Î?:*njL֮*g=qVWOL{THTcޥSqO Aߍ)ryϽփG\RS\i0 (4 xҎ(S&3jxr1*3'4Q9Bc-qUd*j$޿U^85Y뚮(Ri1KӓI(Ԅr(01Mb>\QhNh}1Ahhih9ZL} /=JAI㩥'i3QȥI>Z1CPsCp3F8HO΂)}(OaҗNI:bj4֓) hԆLddo3sQ}1PjUgpGUfUY檻qUDǜ,NI5Q4M#4bZi9h$:ni} 4I8#SdRqP_jOK#zNphtG48Pq(֓٣9Rz=:{zbPG '҃(22(#'~ CKރzъBzQ֐z>JxIъCj1ʌgx(djL`⓽/Cրg=I~t>J^ب:rii:{QǽzO/~xGJ\PGh(G>iwt<#FN2)z@y(ނqG^3H(4J`QFqF3GzwIHG4gF߽1N`b}hȣ4sR}(!<ҁgF8Sv i((hj4֔qH9uތqKHFqQFi@'ڐL)xhR< PGE(#Ґx7\;֌1׭ڗ:SrqzK)Vփތ~R`zK 8t9)G9Q'N4Qړ/>_ZNJ!֗F;Gn< NQ>iG@>旧jCzF11FNGqFIHzP=IK \sIK(JL{P3KhfiNzRgFH})~g8sEJzv@hphJO83G~:LsڌKQ( tsKOƎNԼӽ҃NH4njP*0jEn٩UjtldT:Ԫx0a44sE<1Jp';=Ly8H``~M1MFgyLi8Z_ۊ֢y20*"aQsQ&cCSqH4JBRzހzrF(FiBhiz.i=!uBI43֗'IPz)? \s<wRKA9G4J9ǭ4u9IzsJ0sڀ?I.xgӱړ4Jsv=h8A$;Piz&s֌'4}h(4ڀOjn9.Z!Q3H1GғqFqFsGisHz3J &GS d ;sFy}@qF{G9G8ތ`zӇ)3ɤ䎴w8@>Ԁ҃3 .}@ޣ&N1!HH&9$n>sIJ G pyH0zG|#׊CsK&FhF9Kh ;i9x_ΌgQQ:ўGZ3ǵcpir4wf$b84 Nw?@yԽ;(E#9'o(sS4Iњ9?SI)si;M48>2փ(QLh#*8b(>~4w/.1z98qGZSIc9SGqJzQ@\ ^~4֎ w(#>ip )qH(.2)g/jsFNh<ѻ'◧J=;8@&I}1NRm旚:lzRSqJ ;P9=Ӂjp#ӳp riڞE=M=[ԡ985"˃֞<Ԃ^zԂa7Ӽ Ӽ=D?/yM> 1~*&aS3Qzi֢bAȦyJi'm4ޛRg9t9!擧ҎI4q dF=9 _'AP=zҚ&4sEƓP0)}8.r '^^)@i[ҎFy搊;GASHOt1ARGlf(8Mh8FOjRu_֎; oK1F9?63G&Nis/Q'zLҜ LNisHzGcZ\`h҂jLҏGGZ){RdtۭϥpMZLqޗ))AhQQ4Ophn:Sץ'H?; {иih^h#ȥqF;掔wHJw@}&yS4r}ÓNRA&֗߃T~ߕ4y'0~t<`8)ҚI49Ƞg.ti,}(g&Qۚn1H ~4 9(4FO(<)w82IztJ23ҐsqNstj'jElw~)9GhMqN=BqHOG@&4@4`'j( FOj=҃!<CJ:`<: SȤJ3(=xҐ{J:RGGZ(ڌ~GZ^ߍ c4g&tHrM/ZByqFpqSրsAtq=&}R(8<曟JQ@<ҌcQP;g Rh=OJNzRg4҃֌4vQ;I^hzFQǵ.}sIJ?ZC.xiH; .iS!;>`Fh(8ri)zP9{RKJzӸR`1ʞ:qK)A8JP)ygҀiQ83֔7z~^:R3w&N)L\S4i7fi >):q@HuA=iTFGzNi1&4֓4H(QR~ M'SZS=i?}9I"f8R)i3F:bR`JI8);R .3`٠sGCKiE-'JQzP8<ѓڂNzA&tOJnM݃ڗ?h֐?!>fx擎sIKMK): 1FOL R}dԔgsE&''<{Ldg^sHz"P}i:ZAK;i2E8ҔZ=A's֓(Ϯh=hsA9F1ޓz1 qځgҔu<QxcבKZ?hz3FOJE/@xJ(Ҍ~t/<({:QŒ<=hJ^1IƅJqKׯj3▌G/|*Q7gp8җp))riwsJO(o|RJw?J7q֓q֔1QȤ1i8ɤb>yjCӽ)84֌Hz}( HFFi:/OqIϵ:ZBGZ:\t9AE&h9GAHp@IKJ qHҔO٣' QҎ8E( !@>dG|IJQRqd=H/ACIx(aGNџJ18h=)2{ ^~cAKRc4r2h<g4ރ)&3F1IfA8H*1sGSQ3JzьGj\bh(84sR—!9&9u=z{bґތw94 RJO\GJ )}zRuwi~—Row{Q&qKҌRAߊS֓RRg@^PzPRFr=)qގFgJ0sF?:P(ۥj3Nb֎;9R@$⁞sNc3:PēJPzsAnx}(݁FFGJN)8~Hw`i#ΌzP}=/Q })OJ1FyFp=hR``RIJ:!z PIIӌiRQIIG>أuRz4QhK:g4f֔tO_ŒrMv␊;z:t4sތH39:R4M(ARSӓMO4df8t ғ҃ץ/JA`~Tz\ ;91M)4qZ _A=)0=NiHdP)NA{RtҎtZӺ1FK.yyARҐiq.@M$KhT~sJ=(4׊]߅E;uz^җ~t(ȥ;Z_掾=馜<⌃99iAQғh@y)lwEgڌ׿JLqɤvFyLRy 84擱ⓑz:r:P;RJ8&3ZQs֝'jS/~rx=Gq֎bߕ(- n:w<()#JN uF3NqKΌzx)\Ӊ Gj>qN4(gzQ \3M.p:qFhqI◊23I>Ғ֗tJ٠()q J0E'hi{P(rGZw {CAڎ23KA(Qڐ8F1E/RR3GA_zZ 9 JF:R wjNzRtڌ_ƔgQ@9Fy"u)\<xhԤMϠi{uל}ΔNtzRqR@nqҐOhJ;=;P}):KߚFqFy4?&iFqM KRj0;RsL}hGn0@ڎsG?Ɛ{tҗ4u=i9#>ha=(sۭ'JSi14ڜ ut9ZZOjNI>(ьR=sGZNKGSulI~dg'pzQF);R㱥bxK>wI֔8ڗRqS :sB}I?(RG/ џ΃ɠuNix&IF8ZB}){g^hъ1p ) O^Z8/lwz:NqAKΓɣ<2zq.?0>dgF2y)HP~Z' 4w旽֗JC=:sF}ڐbŒRќ@84iAbҔ3q3JO;)r3Hp=.1ޓKސ4~sǥIҁ;ZAxx<(n :@Qx8'֐)֐=.2:8#g"Ӛ1<c}h43֐Gnڂ{PsF9ϽqGdI9◀:zAbqqF1%)>bp)=(!#'j: :tvz:х88)@M&qKΒKO4ӌӇlx:qڎz_7}hRigbxi>tRt=x<8>ސњ^Qސ8`#w.1ғG#;Q4;Lҏ/N(J^>9K~q;Nh9I QwN:S`IK9֗"(R=h wJG)'\`R:R}iq&qZޥr8diG9QZNz>9⁜sG?Z_Γ1'oz^(qF܊L`zuJ(z>^)9j;Rc^&;g:py94r9H8"c9}xhс'8ERʎ)h=E'$LKhzR#&!('IК^:PN(1I=zbgގ^FFqG\);<њ\)9rpu!=?J:QFx$9▏“җ4(bj:risғ8J:ni3ߥ/`Jy@GNh4bi(ȣ^u斌Q)~>g<IKi<Ҋ\G(c@sFy>s^6ONciOZL`Ҟ})IO.9(9r1Jx @#H/z 'vN/sށsޔӆ:KRr(8=:vd23~& ?JNqJ3h=h==1sG!O֓o=iq`RPQ9Ⓜ:Pj3;Px8Bu8G9I=:s)Ai NgROjn q(曜JqsG8pI94:=ю):9K4zӊQ"=Oz88(9FiqH:Ҋ^SqAsڀF(OI4{Pi});)zAAH8KiAJ>c(>)hH3M/AZ3%/4t(ߊV֌S(474s9#h A:,wJ _ʁ(qhriyKI)qIhqHHO1K)^((FGF)zJ9xz_OZNI@>޴A4'G(ʎ?Lv(Ǿ)x)iW9"Iփȥ\zo9 GSGOJ9N=h=})JZOzL@'hԽzQG֗֊;|zgK)1(AqRhh::uZG8tǭ`┌LZ=x8aGR)pzO/Ҍq@ǵ)җLsJh4iq=(8L~tSF{. &y)9@#=)OLfցh4cG $q);sJ284 J;$f :^?*:=Rgh$RQ: ^(:GԇzSқxGCKR9ځRLҊZB掝zPOg*A:uhɤ#Gj\f81!0);<ʐzPsϮ(3ȤQۥ?ڂ;7 J{Fr(=(hw)2}֐:uHHǽ/{q@4(GozZ 8c'!ݩF1G~qRr1P2>z֏&;bq.2hu'Ž` "yϵ3Š 1I.;уj8F9wsKE&JzRԣIi@)sԇJ;t𢖂h( &=){RSzi 84w◷JoV-.>ZA9qFz(9 =\R Q&0iGhڀ=<9<^4yҎ'C֌4}h0ȠGJ^*Qu C(1G旁ڎ2z :Rbuiz=qGU◜Rg)18?$ Ҏ挒:Qޓ<ҏSEF1h早i: qF}0('uI׽/ɤ )ғȥj2):ў^=QסbH}1FhJsE&pizԜ◌ ;>g֌ Q19A#3JSM֗4Z@yg4ځ E)4gg)psINiZ^Aړ4Qϥ.:sG=)zgސdZ\ցwc4 b)?QizNG^hȠd@i3Zp!wlRi:Z^i.xSG=Z^ZA(4g#Ia!v?&iNqA8)84${P=}h^:Oj;u4ƓbQJ0y4`9FNhi=GҊ^)ǽFGzARIإz^vu'\ R4tڏj8=(CRQ: =9"uv8G/nci@>ړKڔ`s:rzPAրh;J>oRtK ۚ)x);җzQ(>J8zњ2qGA:(zR;RvcE-=JZN3x=yfހ1A@ԋC{;h9bp(ϥF1h4Qq04z3ҌP~QyR;҃tqGr;K-&}(ǽ(QuQJ:QsA Qhq*3; 8&?.xt4ϥ0h'/֐s(JqfУ;sQ)qK=cu;t=)LRJN8Ni iF&I) =OjNԧRgH :J2{Ri? \#4:QbԹ֓94j,ZPxcށJz`1Aڗvuhޔ{QǸ/ؤhE@h4֗Rs@ZP(砤 P8 ?qGF  Rv挒irsAZR~hhQ4(8 GУKъ@yԇۥ Ji1N?`PA}z<Ҏ '9J 'AI\f299"4gRbRz:4cڗ֏ 1A4fR( {Qi1$R`J33JqjNʔR ҏ(֔)9/9I{Q)qNMޔ Qߵ:Kۊ;qG4v( ё4?.8!R֓4R搌R@IJ:VI;.)JiO" c4RҔvRg'SKRc;㎴p;t$qB1GR#N`uڗ4M;(< g4@9K )s)yKvi9IךqR{(EIJQ-&Ҕr)Ҕ`R۽'N9#ޔp?(=q!&G֗zt cMҎ9J9P}@=qJ(Q QNsK)x#ړzQJSӎRI֗h= NzQҚ>}(()L84ޗ/(>LQJZJCRGzA֔ t2=8^(ZV3-Z  wsv:RH3KҎxM/J@(hJ9#4gRS=(){ڎ&F}hFxI:\cGnh?B=( vAt~ =Q֐ZR;rzRsQzqKufI֓u=ii?Z18)Oh9J3Kғ-q@8v⒗Kڏ4w( ќ%朽) h)y84j1\RQ(9#u4u=('z^hҐw(҃w4tRr:t :Z֔ c#֔`&GdI;i2OnhO֗uG_u<z2sOZSɣQRuzґZNHKSG$g(ⓌfgR!==&9f4t=q@4RqJM02\gH};Ҟt^qA$cLNb1 x4)3A8րA4J:SRdg4A> : 8:RR@4q֓uGRR4g)0?G4KG ;g9;:jh= 0hM7J\4P3(hqF(9KQ#4f (ZOjCK):j 'S8j1Ӛ>q@(қsS8~G^أNbLsH /49'^EZE(4isz=HzҀ940isZ)O\94q@ȠgҖ.3IAKKӽ'zQӭ'\ft(qIӌҊ^H= )9QqF8sAJ ;sF=(ޓ3hE Ҏإ@4'4i@9H}Q҃RsFOKNxKIq=M'jQК::֏lP:R:R?QҐA4 zъ\LPpFh(/Z?.iOZpǡ'sK)qRҞE=hM1c:Q ^4~4ϭ/x4=iO@t#HOaJ0>Q@(J8z@;>ؤFr0M'Cɣ(s(Q:QғKw4hM/z4( w.E!4Qނs)9q(4)xhMǷ4s.1)PqF? : /LQhqځI4) )M!J:1F0:ӞԀd4pN)q)=v2HqZ3 &3h@ zȣw&3J1L:Ҟ)RьRt4t 4Rz&/L{PA!JM#&Ú ==yJRxfl@sӵKۥ(ɤ8 z8یQ9JNҊ:(FM)(J RN }@=4uhH3Q֗Kގ֎=i=);QJ* E/{f})s h'z(R'piIIyKGgJɤ8RGb;izwCҊ2(֐qKzLN(( qHGzQiKRc (9F9N(8?j? _Nhwi^MKAH:f4 H>j)}&iG#)=Mqץ 4 ){w&rN9qڌҎ=hzގ'CZ\`挃9gzo~dɤ4F3hG Rthn֎gғ/jh^izg4t")3ё@8ޗ gIR8}y4g41IK}h'4gڎ3FsHzҞzP1ӽ'p)84zPޙRzz{Nzړ/JL^ݩ1^}юEfi;tGu4J?QyIJpZ(3(?PzҞ3q88`R3IB}~g:tGNr}8psGqFq!<38=Rp: /oJNʌ<сAH q-g4zR`{u.yHyJ(旯֓4~1Z1R :(i;юOJ3h~J^c֐Q ֎ԃޔJJ?L ; gh4*PyTg/ZL{sI8R*^җIOցPz(J):GKQގv.Fi#TzRt=iGAh9F8KKޟ4c9/~*7v}iO`F)}isJ9ZړiyR K( GF(◓iZ^@'$ 9R2sAF{@ƂfqHI(ќҟRE'z\K~4g4=zJOjhZ^ԜC4J=)9F?/J9PO͎P#ю)#3)tuɤ'$vi^I֐^ԜRc4uZyIi 9(oz;P8I18g4OZAR{Rbb3&shbMQҎGғE;# N٣>b{rOJy4cz:^c֎c)('>u: \zc)z@2h>׽)A4 ;Fh4c'^)O!ғuGJ^JIޔtiA撗H&.{bRsH9/{Ԟi{sIޗ9'ҜR~\{Rw#֗4fӚ#OƎiAדJ (#03֚E;< C֗RGNiɥg;dfF:Qۥ7c_AAfpi;i2q@4~(>s֏z^t)v4phw2i&iӻ!RQNzQӚnc棊=*(#J^Ԙ{8ǥڏa F:G tv#i:gځւxKv('/\f&isA# ?AISxҞg4ɥ49t"2qAR( &q@wHx@F6H(=(HzGAɠt<;Rt.s֓⎽猊^z t .yϰ ?{IZ\v(8Ij3B{b4Z3J9i3K;RqRM4=(<~nI ԽE!JG4~(J1HG(ipiN)NhƐf4q.x&M.x=EҌIwQKi:?ƂRyNs;RGҎ J^P:Qƀ;:NƎ)sJ3ю9J2sFhx`dw=w&qڗ𣱤ZQA#Aȥuiހ}LsތڗޓFsFryv4cqA< =iOG_“qK@p)3:E&9''ޓ4})sFoZ3Q4qJ^1 8(LҒ;P;ю(IP8Gr1z8bp)>R3iz N1GNi:ix1KzSO΁`I:qGʊQI R.8HGARy>qK? O4t4 r(zPxIRMJquGQF= Qץ/3Iߊ^KߥgEIG?.AfGi1F{PFz Z1GlR w=:P~sߊ}i&u=()9t4`w3K4(ᾔc AR{cF)3z}h4&0.i3-u8'=)Fq)1J;qF{PGbyc=i=isF2~)MҎczQߊ\qH?Z3HM(fZ: )ORF(=h7y1 2)G4RhG^cӞQQx{Rc掦M)AHpzQzSbԆ3z&׭֎PJ^Qސn()sK0isA=hT|Q4;QҏƌJ1KџwuR.qGwKϵ-}h?{Q~4NGJ:MN{R wQ(3KzqNi9401&(@4^vQ@ځӎgdޗ7'm;j;RzL=;RuRtHOPp 4gތќZAրGB((Խh:bGJBHGzZ:(Z(4g#^fԸh t?'"HP1ړpihKM֗ZO(ҊLKN.3F9?(9A~TsCFi} =J21ךB:R89:R3IK(=hI Q&𣅤?(8)PN qKJ_Κ9N"x:GJ^^iK)4}qAJ) Qڎvh4 8IփKPO?JR҂(4u4}.Fph>ԙF8ގRRӀ"4v@P:F{T4J0)3\ԝ3/h)0;Qҗ=MK#P;t4Ҍқ)))1Kߥ&xKGJ\P;擯C@ih:Q׵&1KQiMq!Fs (w(=)@4u(=)Z=zRS:b \t9^i=GSEsGZ(JPsɤip((84}hlNLҁގ)@&=:ҏsK֓>7PMGwh8ʗQ@&(KQQӭv3ގ⎇1ړSJAAROJ^Q'piszOj;R^)Ocp8I׭i3Rr=4QE/w<) z4`1u8ɠt>{F8=(=8c=($RF2yIR(ǧ҃hGAH>ьzPrh9m4~):{9ɥH&j(jsAR\ Z;dfqAJ_zN@}(JC(瞴fu9?Ҏ玔4fRގԹMN(9M >J;Qך (JzR4*Lr=}szKϥ'9zRhz1Z9>t 9(=覎9J4 IΝi)~^wiq1@4v㯽~RGAi14(sғ$J(!f@3F;dRiiiM 3Lp(ڐ)zPqE!^ (QIԎ(ϥqG׵/~zR΀=zQځN)qɤcȣLuq'=ip3GsLHhQ҃((Gj\RbQ4Fq:sG^“ޔQ{␏z9Ҍ)MJ^~t3E44gzLR)3Z^JS'- .8Cҗv(944hAќ ^ԟisF{Rbj;⓿#zP1֌RM)y1G@hʃ׊A/控;{Q 0}EdP lьRcE/!?/jNp /Q!>zuh1IzbtKQz;Rペ^b:A4|sJ3HG4u)q␎}QޗM S<4)ZZLsփh'$tFr:Qwip &KGj=i;Ҏ{Rp(hr3K?*zCJ:pE.i{RbPh.p('4bwuhޝjLZ1Azю;KZB3zcg>()IƐ\{w Ґ^JB2Ԡb&O"cZZ;b{QQGz64ΔzԸ4E/'^(j3җR(Ls֗ڐ)y'ڎ3F3H:)O=(#::Qӑ֎Ǝ)AF)?:Oj(<sF=iɤz1Q׾h4c=ON)4ⓩT{NPxw/Z;qh:ґZ=zQsd44KސZfÜRwpG8~gw!旨=:QI ⍽)Pj^}((@JzR`FAϭ t8G>ԧz0Ny9'4^R8۽8t(z —H9lPgw⎢I▍fJcAr=~=I94ZL=i{R3@PO=h݃ӭ8"iOPNi h)ACv)Ȥ^y)yG~PPy1FhOjZ}i)G^s@P8'"w據\=)3)H4z;zQ8_ƎQGj:sGQG֔QN4G/QIߊ\=ߚ4`9wi (掽)sIiyJLrzAZړo~uIR:RO4&2h=0 8~(>h֐yԽ &Mߊ H3By8QKi()ȣRtf&qK G {QGCҁw 'ZRz@4t&z^&dԧIqGҎRJ ⏭j;J=h/d={R=iNi=y=);P}03N0)3/J3EўGjN8J3G?!ҝڐڃ8?} j Qނ(/I;(pyA/AGjCgw=yPyE(I{Q(p1@4(8җhA=84s@GhQO.:⎆瞔qIRڎOhj^&h/IP{RJ\APy#җ3@:))q\'֎R^ԽN):Sϱisғ<QGqIK i ȥTF2zь~f^w'\wq@s֎i1\))8h#O.}8Q'ug@R >ԤP1(K3փhAȣxMz;RXJ})G.sIG|⎿Z^1Ǯ(f┞Iؤ'< \dg)$h=zP}n):j@3ޗ֔:qA8@杌}4֗E旷QRw;ь~48◯Q'~gڃQҞ;JL JzRj\fcFy֏|R4L)r=(?*PH␏J1iGJLqA4vу\gF(9c(<zwKߥ!4)j^ R 3y9"4Ix M$Q&sғ܁K֎wKސHE)Icg>tPӭ-!@֓(RZ_Z3Hx)AhZZLQ֎q֔u'~hEJJJG"Whi3NE'~u\)3S@8)sCPi3FH9QPZsJ ZG=~P8'Z? Z0Eڗ?CIN^g=NȤSHNihLr){bL1A>=0iK4{QGj3F)1Jy("(b1ҌgJ^֌zu9/{ўԃ NҗwHsڗ^hNq֝4`c3^qQFq҃ӭ.;QHxQ"I#KڐqGziqIG< \Bf RPn}hhAA#ޗ)i:Q 0s(҃h( /Z?h"FxPhPzb=)xsH?:R(NMg2{izuh IɢyrixH8KҎZ^p{Qzѐ){RR!^H⏭'NԽE!(N'qKߊj^(;Rw>QRzR R{P?Z1Glќ{sJ:qȥ1H~1@Ac/z4QIۧ4g⎼A94{~&IƗJ3(A>tKӊ cQRN*oNJJ@pqGn{hv@s9(4CGj?ZOj3@=zzs@fҌsҏz<<ғRgڗ'ץ.:bH)s4wJ"(/Ҕoz):f~sPiz⓵Fh< w:O֎qJ:wfiI1Kڎ ~u=(8I=Arx.2i95.@xJ1Ύ3֓1ޣM4j\Fs9)3K׽=hJqFƓ&xʃ&px @:9'ڗJ;ftKړ){b/O'9)q@4яZ(EgPN0yތbz990q/^(ړ>i2@p4t#8\ ֗(J34cM/xԜ Z8tt4g#)13.GnԝisGAIҟjAz3OΑHg4=)1GbsGOiqϵG&GZw|g(HE.tdbsGn(g^r(~4tdw9(9=hAI@Ec4iqIޔtq'/n zނ(9JN3Gr1Kߥ!Oj\qH9◽/Qқj}.xPyF \( zw9j\|f.= &h<)Ҍti;vcLOҔ@ރҊ:t)p{RQJ:y=p:bPF ѐq@OS@:I(Ri= BMԼ:Rcޔoz=q1KzQ4RNGjQҌK8sI&J1L 8${hϧZڌP?ZNҌgt=(yRucAF9I/FxF"/ץ&3ޔAQphtQ֎;IHzRGCF: Kړ 4t?/q1ⓜQts@/h(i8KJ1IoƏj(zqG_aKf;wIxhQx(:QJ:>ю1G;r8ހ0iyJ81RڛKP9Z(i=iyGO4KRQQ8֓4u9=sG^cP= !yGj=( /j;wF4tG8"R4zRъOʔrhsGS qڎj3KړZ(JGAf.{PxG=A(:Edڗu揯JJ Z@y^M&w稥yv>g2(98:#CKd iKZ1 Q9(9֔t88ǵE/cS/lR*PFhRt=4P8'CI4qKuAJ2;Qi3J:A9҃ӃHFAqA9qKJ9ҌsRw)20qI(0O9җҗo|zGZ9b~4sG~h*SIN(49Q(hߥzO4sN=8ʎ3/Ih=iJQAɤHsޔN9n'j;Tgv>wQ.8>߃EԴuIPqMg/R~4t=h1MԘƆhǵ(@J40qɣߞbghϵ/ld{ќ01A;R=JZ^)zQ'8vMҗRu4ގCӽ(Q֐ ;'lsGG|QɣR㎴8Ҏ`ހ{ZOJ:4{ .})'gPN)xH302=zrW3J1QzjjR{u(qR=(x 'Cqiniz8GAHn(׭)tSqz\(s֏z((EJQ(ɤ4uOhAgMڊLcLvKP8(4'ҎqHzނ('K{PxKG4}sI3KIJI8bR=Fst'?Ҕ`u4A99⓶hJRyh֣)?(z=sHOqGRIڔc%)Gޣڒ=yhXhߥ4Jqޓ4 :J4sI4Qڎzu)(P94ci=8qHF @OKҎNhQh=(9KJ?Ni}Q;qK AɥM \I(ӊ=)zI׵%Zy>d iyz)Inq(ϵi{JLJp$b(cg)zށFqFy8J=^;u<GzLJQҐP:t4=':@:w=)qqG@(})OJ@; SblRqHE(=ip:Rc=h#(8MGdzzg"3N@iG?ZN`{Rz3H9 fs(PGs@Ƞxv{Rry◁z97s@{4J_zNZ^4s@Qɠc/A4cځZ09g8Rhӿt'Z^֎{~tǵtrwcK(z?::QhǶ(> 1((>aFsIޔsGnu@H:zKЁi;vlR:O—J? NҌ探LяS.=) &=@iG>3IqZZ8IA8Qя^{zڎqMyB(zzgh)1:Q׏J3I@vJ1Z0(47Lڗ44K N){qIך:R掜f$KӎM#f9=q#֔vIcu@&9?(.Z4 .1 8;c /w'PsKۃ'41уIqKH3^ќҎF);AG(tR#4dc;{PFh< C38x'4S@9Iu?.p1NfJ^ f֗<);n94az2h@z;zRc^N)bhizRqFzQ\JfsNwAGZ1Z}FyGCߚ3s֓I(K9<ɤҎJ95()1ut<ю8-'R;PGcu 'G=(џz.87LJ\Ҍ^ԙZQr*LҊSޒqF1RJ3E'iF3GZh 'LR)qHy?JwZAy"FsFNhPpGMjL4Rw)GMj Qdf1@j4zsփfsKӠ⏭&8=(4ԣP8<o\F0)I4zќQK(9 3/>y4G?));ڗ'=(Gn:у=1ғZC֗ؠsڌs@r;QڃҒh.x>(ޖ?:(֢r&yGց֏Ž=h(4v4 RbRP=}):=(8#ǥIv8Hiz㞔w~}(J}O8 Q4zצi(F=:RS}{hRьKRFsI/^ғ#A}4CQގxڗZw)A K#:@2iǩ8'qF3G"?:\{QX/|P!$R.) .;JOւ8Rcd֗wGM(h#i1ڗQۭ'zw8):Z^ցsK֐⎴ ;HyI}yڎ RxJQ֎RsK@)3׊:d4c(ϵғ9;=i h֓Q\vJ{bQ}8)=)yiG>qEG4R:PqLdg4zc4n"٠QۊC֔b\Cڃtv(N4rh9'9PpphiG^{ qڗ=iu(/n4!ir1Kb/A8:A8Phqҗӊ?3Qށ\NM4vآׯ4 :'ݩqҏ&2y4O&⓿4փیhȠ=ҔGA@Q(ԝh^>gcRcҢ8G'KIڗq~T{QF9IE)94c֗z=()O4B=)pEhgPFhs::wڀ9@x8?I9iX(Ԥwޔvq(F;xu4уALqG8'jw^Rw&G:q9$ #4J1h:ZB3KH'OR)z4 J;M(⑺RdJ9R֎mʎ~hc֌)$i9<_掝:H7J=zp'j8=hGAJzLs^“jq@j:i0*\`M ڔst:⃊>R@4qxs7j1C֌P9>Ԥ`44PqJ@=I@=i@wzR`{◥ J9#1@;1HzKb8=1F1A3F1ց-J}{QQEv}y\RcGB/@"QP=t!A4ciGJ;P(IP=`AQQI9.3ۊAO1GzR3J^i"?:4QQzhqKc OZ\ 3Z=4 A1A/@j8=龼ӱI@is@(< 2€1֔!B$A=M/"H8Ji8KړҔqh:Qh=1C)NAINE/=h9{yƓԃRd2A#wf 1Hy=b9!FxQJ8#'Rдw\CHzR2s$ aGqFy…<qҀ3KӽޏHWzQ=)AiZSҎ8?ʌ`u@@8jvi:sGi>ڃE)^8?4U}:z3\6{f8ȥo=};hj1(!dR44Թ!#Hqz\q;Q0q<8#)GJONu=$zIڃqJ1qM<^z(@q擱9ON 0)3GEtwAQh &Ew=zcQӽ/QAB{\)zZBTւ}E&)qRzZJQFG4 :R擷`h<(JjC44JR9ɤ R4 =&sR=(chǽc'Bi@sF}9ԣg&/=i0=9{P:zAԊ0hFqF(zq4sɥڎ / QԄԸ\Q Ns֗ƃA&{RRuց9ґI (ǵ'.⎣p^w P94z02yӊ9FyG}QGE=)}<ҕsN)0r1֔h)hG8IH.:=@{PzFOj^Ph4ƎF}i0O40CJ{PZ\⎣=!Ҏ}"f(.8tL4{'N};ғԤN(j0␟z:QAiq 4(8Kގj);sڔ u>j\cy47Z3ߥ=izFE'ozSڒ4t~Z9 /=P94qh''^Qޅu֒Z;SSx?Zqq@ҁgQߊJ?/Cך_n}c9v('֎'\ 14gqw9wh=x4wOw<9P9=)vJzuԞF):})=i:?/ъN⓯x4)IRgAiqFdgӡ*?*QB98LP=hϵ%)1F8 4F9@y攎{`QҊ:Pˎ8F9<?QgO/zMҔHxҌvQȠzɣwG&ғ'84c9 3ҔSyNI8Jx)I9n;RzNޓLG␁Kh~(?JQ&=isHH 1z^R>jސ \RwKQ"1E.xzҵ&8 ^hs@4g=:)Ԝu&}c4HqGfsJ&(!ǥ(8{QG{R⁚@{ў⎜b<('R /s:v}9IxڗJ:EPx>j@y3GIG^TvGlG4R)ruAM)4h:ގFy/G^Ԅ~tUPzc҂s3֓<&99$P2F)1hh*1ҏj_jNqA) R0ZFŽh0)I擡ցќv4wh=uh(ǵQqI1KۊLԠyRc9⎔g'J q֎PRRc03Q:^أF1G҂pN):w48旜A9GRؠty()N?*0(֔IP:8恏JA^C3i:QG.1I(KBs(A4pNqIޔcj;GzL.:N4z^v⎢c?֐Z~4Ҍp(qF;h/ZN;=;)i zK ">RN{RdG^:rHj ގʁJ9"8J3H3487n)qJRh 9K$R ?8ރڐv)RRAAӺbLrGjLҞO\!҅< Z qJ{zr/jOjPG49GqގzQ)3/9G"9(Iiޔphހ Ȥ{>)3KB08Q=M(֔g<GwIӭ%KӚCIҎ;ށǭ_SiܓF;u"Z ޗ u#K4R.H4)I1AךNJ8&8JERtF{KnhJ=hbsGLz1GLɣ<{18vsH #":^Խ~sޓ9旜QɣJ(}i14cޔ8ʃsFxPO!=E)8((GZL) ]ԙɥO99~jNcߊ^y4;uGC4g'Pz sFOA@Rz:@ȣKM4Ќ҃旵!ϷJ8JylSy){Z;q@u搎IGt֏sҀ@'=:x()=zqIN9Ⓨw)G$4sKHGz 4@i 98^x!)~n(4qA4Q_F3Rt4QF(G8@4P9i1<ҚJ1ڌP1QI#b/ni{{\~b)sNҐȠށד)qZ1' 4t44c=Gz\Z=Its8K֓u9s@Tqڀ2}c>u=h4 4.81KznM;ZZ?dh(zd)2(” zC׃Kz\sHqc 8iF{iI\g( ֎1F9z1i:i*3j=IN( &S&(8Z0IIKގ4c׽ -'zMq94 !Rփ9Gz2S.F(YTv7=@u4PN;R(j6h q)/l8`g&Nփ)qG_}(QIҗv/oz1I׌R:=;\ތq_3ړ>4`wcrh:Qߚ^;R\t4zGؠch>4bRg4p;'~.1ߚAӊSuA9 `fƐR);Rh<}8'LP1GӊLq(9''|fqIҗhZ^٠=0n;Pqړނ8F9'9.0:ёڐ=:PHOlv7=(G| q4zсրsI@\jL簤<ӭ(hP9􆁓=i`d҃@AFz4gQF;Z# ڎsFhHix) y=OJ<߭d8攜ь _KONiyɤ9 Z C’v]GJ:'Z^q<<ҎO^E1JF9zLQQץ/=14gw4G@ҌgGHyJG҂9OJN&Η F1zL;@F?IڗROc (zރG88ԄwdbA֗4GA@ҁɣ8b҃Ϧ(hǠvPF?ŽFxAGZ8Iޟ9sJ qFF8dqIR4s:}hRH/z FќJ >u=iqKhJJ1!3Kӊ=t9c4`&4uK)1CM@Ҏ Lu"h)1@A4Rt8ǧҌLvh9)3pM/⃟z\GzҐZjR?Z@2(8ԣ4}:1룵ރQF((sNϵZ^ԂsKړ 6zRJLQv PM'Z^>Rc){g&} .p:P3Q=9)@M88Jq&y=<>QtGlsޗh$F3H})@4KڐE49i9=ht/?P=9⁜ҟCGQȦu(?FqPjR{bzIE/j3G^h4u9sCFNh2hHp>zўy@u@9'Ҋ94ө/LqGu&p:P2)=NZQvxh8(phpizQ@h;3\ȣ9ԟҜ:Laϥ*LsPsK8=(4q(zѻ4f֓w3@#hF /' s3zr=i1)8'h\{EKFȤ8">GzzJ_֓)3''Px8's:QE.qғft/Z^R◜E (4}izI88#4P}wjQIzGQQw{wj1:9Ҍϭ(8GJ38b8|ff4wNIJQϥ'nyx4ub:s)ސ)1h(c)L ^K:RQ1);M֗F@I@IJ)qǭ'җ'R#(!:uzҟփzNG'jLP@qA#4u4s1:tGnqGH9⌁-ҷoZCJG=4N?ԟΗRp1֗h7z9t!(R)qIЀiGZ9hHP)xJCbv)p3@'4I΂sIz\fJh#J3;zZ&yh=zK҂I((H=xi?T1@94vtϭ:O&(P8)=3GaF9ۥA  p){fZR;dg/SH2y8R QKۊN1P{zЊ^CG|R{^@Iќ掄d^q֓/z^4dpyzSNJN4buSN) zz C׽((a@h&/ h(4zHM-'Sґ(::8N)zsh RT@Ni>dp hz &ƔFzfhKi 8{Qz{QiN{sH\1Lg8׭%=I; N;QK3F>ZSҐQ۞q(hJ1ރh? ҏn)1^aZ^p(=)(攜P(=21@sFhQJy'|RhIiKHqڌAJ8HQGv◩␎/nwΊ: iZR1IF){掦4)ⓧ9GjC)z>Ӻ(=h(Iޔ7{џΗڔRLJyM ړ8>sz1(R')(w)p::R֓֗QЊCu989'=x:Q4t#(Q֓9KMҐ1ȣq3!.Ei\JqusIԊ;d׵ҎZ i 4g? LҌ=8:w(M!F=3Fx((Q@ɥ >~T:^:\Rt !=h})qg4ҔlP2((h4 2@֗o#ڗtGZ#hG4czQ(i8( 3N ' H<ґZO/zQxI8 QxZZLsKN(4g0isӎړn}(4ޙy#88 Rsx0 t^/E&1ȣ94zQ׵  “:N4gzRzip?3i:䓚p(#46 :NuA#Ҏ ɠI/Gԇdtӡ`qGz6sGp EQ^z#J(hiON zs&N'т::sKF(?Z:Q:~TRuKIJ09fqހGNu^ARg:Q۞ Rr=)Ӻ NiFiCKȠE-)!wn@I֌g='iMGFGH>{ǵ/)TsFx ƓJwNm?J\R`(zizHsHIsM9_ƐG4F֏3I 'g4>{PsH:tH$iu(sCi1E=␃/FE @9FOzRxR8I.qP3F(!>K&<:wZ1(9=3v4<QyKd O4uI8QK#A(( LsJ}@>t44FSI8J:(1ސ(u;f{`3\OQJOJ=(GRJ}x( gގJ;Phcw)y?4h#Ӛ^GAG Fh#I8H (luJZ:ڗ֓3G{;Ssɥ(Rў9z:ўGz?9^iF)z7ԼJCGRx1hhOZ֔IRюh#IFi{u;Khr1H޴Kv)@sF8 (3h8#!IKsڃ@#c)@ q9Gjǵb9֎GQA@;u(ڌgQj\ "1h=iHғcӚ8}hh8@4 )y9M4ch3KR{Q}۞g)Q(\tғ{Rt'"G#IPy=)1qKi=:Sp>c)3J8J94{{RsҔ?xсG ђ(=zRLhь&4J#Z9^hw^bqȠsIN8".sA;'sK#i0sK{RzԴfsO-!j>~AZ!bis@sH;ӱǭ AI8Kwt_Ni;?_֓8'Sњvi1߽8x(<)9fAF2?:R>4i /GE@G 2hGjR1Ҏ;ҁ)J8ϭ&})u F(h 8<'.x)W4ʂ:N9  iyAhɥ#dGjwjEhR(094F2i@;i;(qF2:b@u47Agi)Ǧ)s֔jCZ_֓#KQG&}(ߚ:ds;c4zNQցғ<{R?:N j4rOZN ciG'QKEG8M94(9=QS'QHAp:Ҏvb=Z0FhAڐu)Ji8NLR^4s < QQA2)(ɡzQ:Ӏ"JT8~4;sB)}9'.)1A4[KN^i~4()1^?*L{R_j0sҁJ3R擯Ls\c 8.xҎJ9I'򠌜R=(>֓9uR@8$dRt>c=)HH(PxQۭgK o'z3Z^?:A֗$}hxO~ QHFzs@p#:ъLK)1;qF8 i>(94ڗ)tczR#\Iޗ?uړA^*pxI^P(Ҁrir3tiI>Ԕ=sҗu?G`sA$Ru/lQFGjSKHt' ^FjNҌQus@{R1N(}Ҏ.( KxaZRGnw9NirizwAMɥ9( J^܌P \d^:M'~z RIQ@:L1K\0iqJ1~4.84m>ߑ@&9jҀ:s})=i♏ҔSy/֓v(i^J>wFh⃜b>sg9ɣ Nzc4gqKӯ4A$4riy&Fz~֌4y⓿Z qh@J@ҁ'{=KKh=G=h#>Ə@6M! QPr)3KNWf4c^GғȠRsIJ}1ޓrh h<8=))O"=R4Gz1K=)ӁI9vb)Oj:vh.i0:\gԙ^O{QI{SF894vȥ:q;{Sp(8ZQH=)GZ?֔o~4: : LJq—(ϭ;t?; \g(~j8vۓҀю}}q \Q=h# `0(cюi>z1.)RN ҜFuڂy1AGAGlPLQԚOΗw4v9"wwt= (KߊL '4gvi@Hs1^)q^js\sG@4hr:R z(Tg:z=h">S(4gғΗ= ⌌`f(/jpB3߭(ڔ:F8/j3JlQ=iShhۮ(qAzތcԸ.hhҝRF;~tb{)mځwc4Jv1J)1R.2h+ cP?&:zS6҆) rh#M0u>)AF0IܞcʃFq׭'sA i;Ii;OG<\яSQR1GCG8:~NOƌd8C҂xzRF1J:RaIߚqړ߿(iq)8(JL)M4ずQA'jNE4g (O@xMA94x01GjLqAqrz掟Ҏ=18s9ƌ bdi@ȥhGIȤ;4hތK߭~#KF>jS@Rv{u 3Nڎ@iO\ 1 \wzLiOK&RQ֏J>P RKPzRёdqJqA@bqך9#4#RhN)Tw/&z\ _N4$SNF޴m4=hU?; M&ޘN MÚUiGAF0iJB2) `RZ6f搊B8M=h#(Jiw`}(ǽ)I}: Py4@hA(|PzcG}9gj\ziF;g9Hs(9EZ3FZ8$Qihh#KړNGnH:c4qRwԇҗ2($cH8tM.MރCiAFrpi;Rhh){Qڌ(Gj#ځGz^(֓(ɠʌKsJFqK\ihuh#tR't.G4/'F:`~1(I攑ғ4i1Bsv9;*Ҁ8ȧS(SޔƜ1R2Þ)ا1ڜڗonhlJES@bP4ҜJW5z(+:h0R/8MLL`L {N?5SAx oIZ;tzPrx&iO^iz^P@.zɣɤH ?J 4ގrOz d4Q ҁsږ@RzNhsJ'4 Rt4yIߑGns֔GQQp)4QRhqE@#O>?{Qތ@J^L֎g<ѐis1Kjh8RI“i_!>vIf>}i{=>挎zdsK8QsHzt0)9 PO3)I Bh*JRiZ;`a@i:)ågJ4c=;R ֓ t遚3~4Q/n?4 wpi9;SLRӗRƤB)qҝqN_JP9Se(ivz {ڍ'f?LsC))A怽MFAJɕ>>c#ޓc\`A сڊZL84ڐ);84s@sAQh3H@ Pp>SJ3'O@94 @q֗ p*zv:{OLR\Rv:R8=)ʄG4*ا?CNU>R#q\ƐqK99ғ`W4'u`^yZ@ZaO=cx7!bšN{Rc<Ҝ&0hB2;Pp;Rg 4d{PRCC0)1ގJR()_Z(CH{擜@?;'Қ{t`JIbI'RF\P=hyRiҔ BqA"q@I<ҟAHxIIFt׵(/N< 瞴bi֐wKv}(㩥'&IۭEǵ%)4}izGҏj<)1H FqG&iy u)3җ =h}nwt.29(4cҎh ? њSRiy?4qKftiҗ>g4JsF84)dǥ@;֗ѻZRGZ_Hsj_'FAPOzSҌ'$);S$riGޣ4ӊp=< S{SSxx\8-;gCiS}Y"G 8{S?SHb@~3aLy*5< qMZc)A.qQɤe8`La4)E0)g)^*1=h'Ҁv֕L3ց8PcR)ti;Ӈ\HsIz^(.yCAڃ׽'CK)}i{P:?&IqGHs:REj^H49SJ{hR(ь{R~i=.pyE'9H ɠ QۥQCGN3F}Z\J(4G$u<)!h=1GI>Թ=:zѓR4/!8N< pԀqZp^BN ɩ8✫T${SssSSFqޥ02*H?QO+ti?*P4,yXIwF*#)Q=+cULxld`gHGj3A9IϥQzE(FscvȠh9@ڌw`(㑚8Z\ch8R#GKRdpsI@&hZB1ڌt Ӈ \ӇjxNf*P2)=UH8RTHJ2G<ǂ L)SyX<I٧\h\q4g $lAǥ~^ 8@'j@ǞPjNr)^֡ӧF~*=Tn43sAw3C:Sx!␏Z搎I/&)x-&;(494s@}h4;SZABQF*B3/QAA&OҔq)84 )4(IׯJf)NE Q18qzRRt8Ojny(4^;N0h#B1N6ԢIZN=h4RO4uZRE*Nu@u9H{8)s049)1ҔҎh=)2JP{c֖<): C1A)~j1Aʚiy;POl=;P>^Ԫ-1Kȥ3isOsNO"[𩇵HcG9TӚ{zʾT1 !Sy#SSNi֒KcNQqsҒX8>5ѐzS|j.GRV#>j >^D

F=h'9Pq@HhIޖRd ?gǥ7=A1Iyz杏ZJ<}*EqR*RӟzAEަTqS$g*Ő==*h;T\ sVԋ#"^$Qm)Ԉ4NyJUqAiuQ¢*'NRH>?ªx9Ux'*S=q]ۊc _ r*w'|(=33zL()N(Gqփ֓9K9?3H4rGZǹ8{b3 @9 Q~})0@掽&0hyKG'@>~Tc(Q׊OqH)x@Z)qG&qJ8aG~Mw4f擵.1H:Ҏg#:.xIp;(z:usҁ>Kۭҗ?!tRy.sF:掘֐t (xG$Fs@'8F;1R‚pzPI4(Rzv`visڃNs.s sK;ZSFy4fpxh\vE֗F=h#: :q(8`RQ84ޔ@:ASjqS3ɫ1U^Ʈć*h=Vp"/J*@1R*vb';h;T^]#JGQI4͟)5VX~adxT|15|Pz@=j 8W9Q6՘ڭ=*PjD8*帩RgISN:~t`I֝p aQ0xmq֢up*?74NY4(֗'CӚ^S@ǧ4.1@hHFiqҏ^`cH3_/~iryHOZ^ސKڊN֖bnz(N)Mގ@t9>R4cۜӀS){Nvr?IjtTpjt?֭Ơո8㊶\M&y4}E/SF8x- qAA9Q9> җ' Eu9)F7}iݩ@IHU^jTD늳UcJn {tq^յ*tje#*tPqS&ELzԉpi0HOX9LxYZ-WWQ5T2GL):gR8'P{UaV sPbJĜTL8CTOڣ~9p*6j-0Sh=)=qx'Ij84N'Sҗ4u{Q^9ҀHP1}i{qIޕ'isqH1Px=J3ʎAIGF{R81Gzi)F 3IҎF}(84tRt(=)GJNrzbp:T=JzgbAG(}yh'ʓ^ʒ(jQG~N”chߜߊ^u('Q=zOjQ~(ގzRv=h4v/SJ=sAsGq &j_j8!)s7RqJݱҊv0)="~T)cps8*@8UxS"|zU^xjiڬr(QUq[.Vu2'NbEԨҬl{TNJz柎 x^wL |" ֣8=9|u PUAG5G=*&L2sSS PJ@۱rr5Tj:{G=D>8?֣ߵFh8~dRAIޗI})җzҎtAch/@iʔI{Q0zhh?ʗzҞ/$J01@4 Ͻ!bzRҐ;ҞhҐ P:c@р3b8t}1F>n)u"qMg94g<=䎼4gjqA Fq8QEq/P(JA֗gZQFxA=aKQ8@t`1ME/Fpy);bF}4j;z\R`Rgz\Nq֐uAAԸ4isҌ掋֐t')sɥb89SzǦ*EZ=ju==jpAV#[g5n5Nj ȫc*xןjb8NjGJ#zf.Fj_/T 5HOQ L`z**3Zj6o\yZ1G֌zђ{bOZC s}h(=g֌Q֏nԜtKzR z9c"j;f86;?LiXgGoz^Z3M94iq֣֎GJSJJ^tpU5Uz8PAqj'Hק"QH2 &9J?G@7{AHhGNE&xF=h>R 料tHqצ(z\Ҟi:hZL€.qڐ(҃ @{PC9sA)>b-qHO4ⓦ)ܒh4ߵҏ֚G4QK1IҎ;Q1)8j9Q;:N}Jy8h'&Ij14cqF 4~/Z1u=(sK@<ҁHE/&)&hc< {PGz:R!r1J8'=E(1M=1i܎Rzv 㯽h)wzJy'G֎ަc8JFqr[Ҟ8KN@8S(MSVbLVR8JR< D<U;Q9Q$'1NfcEniؒ3QSr)O4t97c擦xڌ џcI(8#zbpsR=idPc;di0;v2i1)=3}ihHR Bs\`fi:Ҏ33@h=37R\u$҃)"ғ#E(<ў84ځRsJ^H{R R(9ތA<{^x!S҃H:J2z'(/&p}EgJOnt'lzbEy9ǭ'8tGl8ўؤڃڗA׭)q֐ gM\|}(x8SqK@y'':CsKhҗtѷ<Ӏ/f0jJ29B~$U\S**¦jiqS,y9ZH=jdT2*h56ÂMI d/SrCu6qnsMw=2Q^jz|Ur*'/JC"t1QJ㚯#s>U;8PRg' A&܊6P9< TNjt UG5j%kv%V\ө(aPըJm#3W#b*g犲b6_JqN qOc5֔ڡ)TR+Ҡ* X+銧,_7 GTt!C*dUb9fG)x4` &M@Z0 &Iө9Fh=3MFxƓqiM'iMǭ#:F(84`bg֎ғR▃Gn4gF3/Z9Iߊ;QۭOZQJyN֗.=0)IGAq$hZ ( >Ԕs@H(@Hpq^sF(?/h=zNE/=OO_\ޥ_ʬ(LVd3V*`qޯDUbyT`cL*FU<ը֧Ezե\ \$^*"NBx>ZD1Y) xUiT`ysUK8YwP3)ޚ>cu4!i8PN;Sy>q2rF!zw=}ܑ<SxƒzOjhN3M9E/E'zOy)GCF}hph'z^CڔsցF=yqފ#hzPON`g<њN*NA)=裡4 _4dRg=9("$PN1/LcCJNy4'9)r@Zq@QFqKށ}qJ94KttqGJSE9A=)jB9)擓KQQhݑG^ԸC4J0{R ($'N(iߍ zQNiG4){w9OH89}eVr=*x~i8Z*KWa\W"@p{^*t\e5aVyH*t*gȫ V"~)aՄq=^}AGza+)6Fz\_J N-TqҠAX8PHɪF=꼊s*6Np{ )8gNMVMR,Gjwr1I\у# 0h׌рO(qF3ށ&q$z=i{fdu79#ގ}*LR4~hB93Lf(784tuaA44\4 'SK>4HO4Q@֎Ը)#QKzJ:RւsEzсނ0( P~\ѓg}E/Aр@lrsIJH(ƀ9hҔi@8ӚL~tSϭSJsڌA49؊^3֌;Sڜ:ҁ;Sׁ*TǭJѪx۶*6pJaOX{U#*02jʌ/j1(UQqUTvNi(l֞ Lg9⑤bQ4$$s֢N;2KQ4J~UɑU| Wfj}*}3QKWj0Ttg̿1&ʝMQuZP@U'Ҡ|Qzx8$jUdP}j_2PȾUfC("> frq֨M#9Ulɪ9rjTi= Wxܞj zMڢ4ޚzIIבҐI)NORccvi0:dp(#׵Aϭ.<ݽ(f94Lch9?J:u4(AQϭ g(ޏ\:Q4җ@=i)14A'-4rN)qF'j;u)A/Z{}h4 t'zPr8Iץ'${g91Hh&CFI)GOJN=(G`qFN)8NE/zL'z9Pz;RHr(^9Fi3^{9j:)OA= ($'ԴiH84@4Qފ_ÊCJZ@ )Z?Zp=(A4:SH:֎'ۥ&}h4GZ\֐F1Kԙɤ9i=(r)߅ F{◒FzFr9FxL1N@&8'N(\ҁ}98ɥjx)9 LjE@TǷZjf+;Uz9W|OZ~aYSV#&F(ջ^yޥCsO·sOcHG?җ/ZךGqQ * 犍\wdZgDzO PQ;sPU95VFQRjj٪V D^ ~B=)I3(i:QjAIނFqHN)@ȣҀ=qG_‚1H:攎i1zў(9׭ sF?9hM !#FSUVIH^ SV7jsj֫ ~tiG9g4 2K(Q{QғiIh: Bxw)3Aցpi=Hgcs^4z):;buJ2 hh#=O4gӭ.8MΏ IqKR)1ޔO4Qq֔{NFq@!&ғ:sJ99.s;bp11L(4t> QE&0:x:F:RI:78JO4SA1'oZAZ]ZNgzQ3Py&H4ni23ޗ4KFx{P?J;t?uAgzZHzґ"RvsJ_|Qzbp9G^ixQi8烚;RMO֗=}hҁȤGSi{t?"Jj1'Kdњ;zQK)i01^i-ޔ1Nց;vyҞ:TjE;@2N UrըMj2pj?=juaJ[52KV` SԂqS;ԋڔzS(ϥ)$.)44?i!FiZ9΁bnyqAZ3ZAP:QڔsHIsQHM-%)K֌tKsFMdw=E)sQ>FOJ_Q~}8QdGSG^E)99@Rt=i;)qATu4g;ޚih9=8x.r{сH'(Qz3Px(RtK߁NStjEJtsOPy=jT yMA1=*lNjn@ئE5*7<~UGDA#Ңcz= 5 9A,43Vn qLOjIsߥUiy]gD5oQpj3֘x<i&sNMi2Ah&=N(Ґ(G=hA8E'NNGj^z4Fr'^)Ã):ր0>w ()8F8@O fHiOJ=?'z^)3Nv'4sOJs֌RyI3Fp(uZ:M擶M.:Q@,cQHAiZd`}M!?7/Iъ;tҔ})p)U({׵ 4rs1A/n)?9Eriz5^R֏KQuc>$Ҋ3G94<94)I@4QғހN=sJxqGP .iGQ@Ҝ)x9S)T֥R1֥V2>⧌}t'81Vc9f.⭨jg{Ԡ=jUl*¤OR&8}i?ZqfKIM/1iLjF5|Lvxu=Jcp:-֠#9ɪHT֪OTs#Ww>Y*lP*2Iܓ֐ўRrqHqҐcN2: ItvhN}9)FOc7`F9h~Z:LJ$9j1=iy#> 901/GUH:{FxH}J^ڐ9pӊ:qN)31GSu(K~d`Nzx)?)9Oۭ$sISӑA4{ҌSq/֎֌JAJqɠ4)3ۥd@ځx OZ^(c7(F2hKQԝO4('~4K~K(HGGch(Ӛ_J>=i9QZ\qGz^Kj01Z3uGZ;PI=Hsހ1@(h=88(.`׭&ix#ޒM'ӏ֓=h=~hAut9sDzgg4gҌZ:ќ\\POA#.qۚ2֎ގ^sAQҁփ((J^M> P3ҏJ]c挞84c֌Cg8 89u?zRpp:\h?Ǝ;Q1(>u{J(rG^)W3QNǽ8x=@qOS{ԪҥVL'X27SF#uN򩕸Ҭ+Z_$ԢN➲r 8❿+/iDˁizю}i9sJN)~(ޓ41Gzw֐qQzcGсHGsx=*@xsO8RqR3S,R֬$ulRxq(ԫ8隐\c5'7=E)4£fTl fvBzu N*#cFg8Q3Tl/&gFңqL~ʓ8)!'h{}i8 !AҌs֌q֚zQŽSG&{~~8 0P~F4RHx4/CI{KܚAlF03h9⃞(٠q RtMp>A/Q!JݣGncގz@2i{O΀I4 ZLҞ98>GA=hǡqGQך1 I\:E.?J:Q׽y3&;R4`cG!KM~(R8<4'N`4׽HsE.8y{R9j9:4)8J=9N&3ޏj^RqҞG4t^:P9-'ӭ'88z(ގ/AIG})x9ϭb1SpEO_zvpijE$zTqROxl{Ԡwp:LRG|ԁjO0Tbž&sKN%z)~ӑ(F֓=yes֘eJ:O =) &gD`j=QHsPP~xA񊌱`qL- zLNqA49sG֐O? ^=9Q94_—#ǭ:c't8р:9'zҌg&9j3i9Q ]h1裣Qh&y=I^g4 J:bKރP /cRҎi{:f 4ҌRr)hA$w/֌Q֗ҞM)H?:^(4 P;:&p}M⎃='Nsސ}ʜ:fdt:ނh;RQӎԄtTb{װ Qi{RK(4v4y?3◷jAҔR{RtcZ> $ќiH~w&QޓsGoZQ֌s'|Rg<28(}(◓Rgҗ'4u ZwO ;1ǽ<\ȧcӁ8c4s)c~nqN )O<9 ozp~0zMĴ. ;ɥOZQ'hLMfnx0ϭ3ޘ'ޘ[a<~riH@Lc)曊^8ҎqHzqҐ~4T8'ӥisMKקi zRcQi31Kʓc׊)Fx;R֢ڗi:v׊^:ьw/Iirhhp)qbx/S@8g>ԿJ0@@{R(t9M;K;J33G 1G9֗'49=((R: R2)9(b8GN1׌84>t(xɣ1F1jPp)݉3h )F zjPH=*Un7O2;Z~pqKN:p=hKA/h~^O4yIsS!9nɦdRg$v=HGK4"#JZGN(R &9J?:(jLf8Q^fh(4<sZBv֓PF@HisG844tӽ {ӌ#Gz2{QڔFI4 ғF(ǡSN4/Fs'JZRh=)OZP=HzQ ӎqHH@:ҊNIF1RqF}y)8(hP:)I$QFr08v^)=yh SGօEǡQQHy֎ݩ1G""GM(;0:uZ^Ԝz攨#ޔdS^hڌ旌҃9Jpn:ՇA9N杸mNF2?*xq҆p~yz2 (l2qH8>gB߭4Jk) qc'alw?J@w>qLf8?4y搟^&dez3ҐZ3AȠ֎޽Rw4qԇڏ({Qۭ'|R' /)=GR^џZNztww QۭQӚ:h?<9ΗQF3hю)9ZSdPy?^( H4F3GJz(#ڎh#&b Lj14)ؠрy4Ec4ґARA:Ҋ\Is\c)3(uR :)O~:h9 Qz׾'A"ӥ'n:u4H:KxL 0Դc:R`Q18#Iޗg)r0}i/JAҜ~gF0x@4dюsG4x9G'◧h(=zJ0(t>AwZC惜ڌ)r?' 8M!ҟuFz9vwcH88@h=(N1Fhǽ'N(vc<~tt4O/l nI44 qJpM'|Qs҃E#4Fy7 ^G4M8 ~4? 8/ZNJpOJHxPqKHFri3KJQht>gsϥ!ґR1"jM(@89bh'''Z=A8GLAj a}(iq3KQ\OZ\qKק#'>ԙ^M'j0zPshE&9N>ӞsIGnԹP.};qGS֊= I#;zQ0M4gqG<8}EFz1q(֗$@Ky4sF:ьF(h&{◟Z=3KF)9v8֐r)Rcޖ{b8xiy'ڗ }hgځZ\:P@ǭ(Ss/j֗&1ގ8v1IG~i{4t.xzLcG~@FF(>JNudh#֓Pyiz Lg\R—&M~`qⓡsA hځi{g4Rp)P;f'֗ Hz?)9(8'=(<^޴}3ZGZNqRt掼r(94.Ag#}ii1(<{IJ@ށғi}ߊBA8(h3Hz4nzzQړs9:g4 1'A彨P@gGh4.3ޓ8rhҎt֐z)z"jBhzQ=? #3I'9fQgfP94iӎCM3Ku'>P'wp &sGZR8ɦvAQIP;';NJiAQ}i1)qT3ցHF*wJZm($JLc֗bKEj:}hȣQߊ^E'Z)~SךNGOjJ34 Gj13@JG&<=i{b֗788Z?/8E'>Qސcg?u#xƌޓ8)s' 9(!=G)("RJ_=):QG'ތcAi>N{Q(c^xR']c4֔ np= /Ai;hGI(th$҃ڃך\tN -)r9hFqڊZ?L(vA&OJ_~ R=iJ1OCF;x(ڊ\tM&ys&xZL`Ru9hGJ.{Rxg"ޗ1N{р)J?*BFOJ8JrzRL{R?Z4vF0(RhrMǭ4dKqH$uAKi=Ni\tG ⌞h#)XH9is! :~TR`p)z 8J20h$џZ9QsAA9xQIҌɠFs'|SE8ivK`QzRR`qI֗pqKQ4~cb&11sGOZ1GJZ=)1GҌh'3HN0(<Ҏ !4c"P(Rt(iH␃LtyQGF 4P{1Sy'8'^ZQy$;E7)JN(4t9 g4'4(~'Kߎhh8'آ֐q֎AMu(=iy?Z;::~tތy#F(JM/IcQQZsHO<>j;}i3ۚRA'j_'8`}h ;E/lP=EJNg%GJ:RfAњQ88z /8⃜v9zr98{џjRzRd-(:f(1IA4sEw#/SFc@P/|ў掣^)x >9c>Թ稤c'bsI:PM'zZ\JA"тj\'SJ:cў)(sGi:Rgڐr=)x(dџʔqI*vxRR ґH844#׃)sA;iL 'I:ќvqޗёQdF8ȣ:Ը'p:zsNϡFyP\hҀr(9c= %/ʓ iO=(=z:qF1Ҏ!<tgO=i{JzLzzi2@p9K4sG.s1s>vi9@>qƒ POJCQ@cPsN /֐юx◯4{b89&z2(M/4qRNJ;g=hA=>i 88)vyIށIѓJy9wqIގ=i3h3H4hԝOOzCڝ'j;Ҏҗ7tgL@s@擌j3/ցҐ ^܊Nq(s֎q۽-z:P}hϵ/z3Խh=?'8ÊS҃^zRPzP;RwcAs@dKLiҐ҃coZ3J={zt=}h'i ⌊N ^q&G9GO!擯/z3MXѴLf9iq"uRMlqA/j@NJz}(9)~R Ҕ(JA҃M&hKqME/QIqG~c*E!G斓JLN1FxK@"< >&IRg֗L{zRh4뚌(fKߥQ(J1Z1Q斔)zPE!4viHڗ9􇧥dx=iH4 (ޗM 41ڐҗ);ryh^P:fz L|SysޗQc4POjwjCNhրM4&qK׿{c4>ZNE/QA4u4wKҎiG&s^;QbޔRcGj^gBNq)`ۭ-})GN1sKz )E:piFqK)M#Ꮄw'A4Z‘F8zL9#(PA?*1sFqr('8߭/AI.G'$₿J=(֓~sRdMzcGH4`RbqF(=EZR c◑Ґ84zs@⎣ANn9Gh4h#&=QFzP=ю1EZL{ҊB9sJzќt{G(~4g=(h4`zb {h֗g4zNx@ך^޴tj3(h vb=s/zLqցAEO\R;fqA'/P=( P/9>㨥(i$:2i4:FxiO֎F)348ԙ4pi8qGFFGA&r3HQ3IRP89{ҁ^Rd*ю(qGSQюc^M&O}($(یqF9K;Jv@?,RgsHxJs@F=8ϥP

ўyh<1Fq)}M/89>zמ1֒9A@Q{tQ@)Hɤ{Ӂh.in`.=(:R^Gri2O֜OIIj\{Rri{Ҕ}qR4z Pyt}Ehڔ@=(9=)I9<9JzN&)z@Ij b=x.x193`@\iz 94 ԇ3G$r(M旯z;p(<0iq"1IG(RJ:d4;R@i~gri23֎qH{iOg}i{R`~(I(

gڃ4uQh=8ށKI׊1Ͻ.)= LќQ@y/9. җ4~vwǽ Aւ3ހ(ڌҞ~;Rv|LudKwsGzPy>҃GgAKRԢ< Q{{bџaN"ߞ)=MP~ 2Iڃɣ4zc4sy@֔G.01IPG? H9ナ\83t99Fh({G4ti9◨擯~(RRnMJ;>QdP0;p4PRQ(NZ;P^p):4?(ғz/|g)FMisqڔ LAsI4=iR>Rڌ}1ZR:Qhǭg9>q f&AQHz1GluB3ZA=J8`z4z F$(J14z3⓷#\p(J\Px&3FrqK8ǡr)8)sK=EtRsڎGqK u:P9hQߎqFyAR1 ;|Q#h*i3Jx=ix#Qy擁HG{u@Z_7KFiڗu=(hzA:)^)x$zzRcB)p dqKhT.(F9QzR`QA/8'ZZC֗8&q֗֓(N1@R 'oJzCIԣu4 JKGHGNiA(/$bԇoj\fKǥ'Z8Ԃm qE\QH"jҊ8?gޗӊ1'ZLsւ0iG⑺R$wɤޔgҜc&@49 SI:R:ގi;P3 8@:Qސc֌9掆s4b:@w)OjȤ=)IIqGK֓փ)Z_1q'9@3GJ_ZAj;~t3HJF;qI(3@ZPi=h=1E/Q8xqSGCրyjC?JKގ֐Q\p1I׽4t>(: N4t$C?J1 GZ~4 F:ќhs(~Rޓ/KAE!<?.p(i(>sN:}(hz1ڌdR&3ރ 9P= /jJZA-)?/j(s҂=h/CIA(i=M.s@@<֒4Iޗ@A})>Ԟ@4I=(( 3Kc=(uiH:fzq>ޓJ)u&{u(}Gq׊woIfs&8'ڎi})1AF@"h;`w@`KjGJ3/lzw gJ8=isEI=1I旊AgZ3GSIq8}i01ԊwAZ@9Ґ) J u&Mڗ9q@aix⛜R&c))jC@{zRF(zHI?Δ{zgpx%.y(E%(JCҐw9Ӈj03'QҐ'!(fzQIK{T](Ҁ8tq`4QQzZڌџ΀G"ҏ&iHK!8"@u/jLvbizcNsGNM(tzя—1I_zJrsRўuQ94q&~ZI{Ҟ?:v{zґAގƁ/ZLcF0)HIK0i3Z^HJN)1@vo~tg QZ'4ҐqIti?/JBr}uޗ'<ґNcA׵LR=ztlfH:P~`Iz6hQ֎iA49{Q{ќc4bycZ:cLc1QƎizLG֗=i)GҚNh4v8c4(H4r3Ҏ'AJ(֐Qޓ83@92qҀ8@R=xJ\wii8Z_ⓚ gqE* =MO.{bd`Q4 /zR9M$'zP);c4)@ZLGj8Ҏ\LҚ)O\RqޔӚ\dњ>Ͻ+@4sH4_uipi? :J֎ 8@j ({4xbR4&:ю:KAzz:JBy4LҔB;cJ}({RuK_ZNM!ғ>BFFh?*;۵(ԼF)?ZPO4Zv9@/Lz ;tRFx91ށh'ތ4vҌьP<ҊC.21KsA)(<'4Gz1R;QG旞cތzEJh fJL ޔwɤ(H;Ҟ(*;d4/n=i=x1ǥ'SZ=xR(u4QjPzF3Kc ސr1;J9'E.Gh){PPx)IP? f:pFh.F)^&/z^s'@tQҎ9g4~)3Kޓ^(sAvJ(RfGQ}hF)s4zҞ;R33i==I4NiE/n(&A8 4I҃L9qIK߷҆i@M(i)KN3AH(3iG4>рH>ԽM!< -tM'02)x8>~iN{Rdg/jNq g:QsE()1KPq@4qPzsEs@?J '4vEP~g׊q) 斓ޏZ1z;Q9h;cؚ^JGzj^h=x})hsڌ`gi`RKu(Z?1E&{Rc`҃Kۊ)fJ;sIތzG#K1Q&){F.A{Kۯ4}h(Iiqc w9ӑIE)!ɣs3!דK&9)(ȤOƗ>Q.(GU/J(#OJ0ZL1 IP &sJi3ڗqSFnc3Rt?/E=i@?'~ix?ZZN1GA b()11@9束7.yKGCҎtb1F;Z: T—QEcڎ3A8uu=zO&yuxHy})z@tQARf~{с:ќ{Gnh"c^Z@qG>N=i?Fx.3E'zRgڎFp;zRu'ҁA'>z҃H>Nx{zS:^hN&9~Ҕu(')'^x884dRvZ^x:^أ4P?J? 1J9)_QEtM/lfu94擡v$w#8H:?v y\F(bQzPzG6izE! PO.xx(>zv2);POzP @db'z:/ozLҌ@FI4Q4O~h힂(xҌRuqI揯ZSI~4phJV(Kg4)sE/G8"`P?\硠uT挂irzN'zP:0)x׵&hGJ^$=1Ku:P;׽'E)I߭/zN杞1oy<)sp)Ni1KގP0Fh2ޓ9 "QȤ@$_å&{ќ4zQӭ)($F}NOJ\wP)9)s& 4t4Z;qRt@994g&:t'&qJ(PM.i8&|旂i:Q:N \qQhё@Q(cIޗFhh&RZ3@>޴v8zQғ3Iw'4 ;ێRw4(>)7cR٣mȣZ_ A)QFy97RҁrҁuIҎџ”8u4 f҃@1GZA֝:RtE.~}(%^!(9GOJtwriGcI`G(GiG:Z:zQQҎI h$(#{Q=i:ӳI7v>db G=J^LӀ2))~RTz֌u㱠uPGz_\RgQގF3A8i3(#փ@9"''JzNǜQ֌Qҏ@hqzQҐPOrhϥ斊8)3(Ҏ9zPJ^NԔ"FPi0)O^:R}F)y"sH= .zRqߚ^)t=MsG^;cuA=NQ8sԧF()J1яZ\Szvyci Z^qARvKA@JF(ތԢړJP:ќQZ=Qz3K׷4qNA G_Z_j^sAG8)4KށQ=(zь_Ɛ#<;tv (j:^c^Qҁ@uJ:Fi4AsIأ6bE'n<h=:тFhG~?'&x:)q@FM/ZLphNh8d=龴ڃ"ɥZhKq@qҗdўQ()O)2:KקRsҎ;9Γ\ҏ)G Kb98Gz8hNi;R4wEʓzzў(i: 3A4uG4sҎCF(QFiE(<~i;QƔQ1hGz>“Ҏ 9旷!>mJ>&pisGsҌG}9#Z1h$ڐt֜/&i1KgI\RrG\RwsGN)A4I2hҌJ) )G!z\ӊSցƗ挓iS~֌9 zq\P:j@(8N1@֓;@(J>g= P&F{;擑Ҕ*s8)zJA}h=sGAF1 !J9=)<QPhx82t#@8g4f};()ph=iqȤ=hzP:P:юhP8?6)OuH(FM'Z)GqZ?<ѓFIA18)iSAq!i9#Kۥ'#JF~/4{ъ^I\Rt(ў t(4wNtcG ъ3Kӊ@O)aGL4wvM֎ci3Ҕd{RڐсHE(9(h?zCQ)qA&3ץ/oҐczq@8Z1Ԋ14֓SKߎNOJ\h4=;ރEތq= oJL`sFN=qRg('aAt@ғ9{KANc4E AA9▓Q0qh/IhɠzRisF}h/A'Fy"qEJ2v斏ʐҎZ\J9ƃ@8.yQ֔(_SHI(S03NƎsHyڔԃ9E(Z;dQގ{f(ьh>Ԡq'z=j`Mu8((#up &0z8#'&` 81(Q:tsu1AQPy9iyҞsI^F?*27QG@MKPpiOQ9v)z1zLNϵ&s@$GJ:{w?7?;ʃfr;bG/#@GRr)@ QGP t.=駮()OLAގ /n~4t|ҎF)1'NQfAAG=/%ZҏZR`ў9)9vpF;Ҟ~4w#&. /(&K(@98r9Hq֓\ &z\sB{wv=h䞴wv9F0hQrhGRԜҎ# JOjnNi{4q;:AiGR~4h 4QJ:)G~(cނ9=A< QJ9cSǽ4zRu ȣ9t4GϭF)qhڏLQy94sFMLs—'=@{R֌sE1Kښ 4I qIi{RrZ@;P)Hj9hBp 1(){@rhqhJqIh)s۵zQGҐғA@<8'<3KhޓƔguh"Ҁ8=:RiG^(t@Pi9j3җ .)ȤK99c9<Җq@'4'.;Qi3ӊ_/AF(G8SJy Q:P/OJLqK Gj^ԙ i@)QҐc4֎Q(^RuJ88 L`gzuizRRz^ @9dSigima-1.1.1/sigima/data/tests/laser_beam/TEM00_z_45.jpg000066400000000000000000002606671514013333200225050ustar00rootroot00000000000000JFIFC    $.' ",#(7),01444'9=82<.342 @ }!1AQa"q2#BR$3br %&'()*456789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz?F( `4gփҎڔ@HIyhZ8j^ړ##ޔg8i:izZZ?/ҐG4}(Խ~iGjh⃃I3K{Q!#O-)s\q֎Ny!8wGQ֗@{>ԅsӵ(4tz:IގPך3AA Ҍ;bE{QcFrHچi98>`z89Ah^i 8:Pqz;q֎:Avo~)ƎP~4z҂}9GLs@'=8rsi:ޔ֊Qz A(siAqNEwjLsKAPGGi8Oʔi>O4{Ҟ)zIbhǨ搞sKcg\H84 @sHyJxaG^tv Z?})9(4ҎRutx4'G^◮>zRw*9ԴRRzRFi;2h=E҃;{z3@##d ^Zi=sgsڏ␞3/9vxHIʎ2)9Kg4/zoZ9ڗ ZS֒8JQ4H'R1ځAA(FO#fw9 R44Km֐uch=)1q.: RJOҎԼP)ўߕ/aJ):c9\zQ@G&4th9&bKrEINFyGގp;h9 E/lL4{(=xpiq9ZN'R;8H2:vi8(8xKA9GNhE/l;1v'PEDszQ9=hp(hwIҔ?(7OjȠzޏN#8 !ZHSK(JHE 4 K9zS7#p9`zQh=(.08)3ރywbsN3Җ4 8/'i;s)yK'rz{QP:Rތ'iG'Fz1@砧S@=iOj1=i: .1!Z1ҎJ_ʐs@8@@ZB94cS\z(@(q c3gi{dHz(zQJRsAғGȤ:-'9ҕz@@MJQNc&)1ZR)2{@9'<⁀3ޗu49 q)ϥ&}{P@4>tIiAricKKnsAROlQdZp4~c##B(jwzOQH iG=h';cR"s'n(#:^A#&qAޔHSށ2i @?ʗ=pF R)3Gn(iOz14Hy4ZP8449qJzQqяʌȠ~4E(JL\u8AI==?JQȣ ^(G=){zRC)A&f{q@4tw cE.yJ/lI)ss@t>IG4LqGqFhs 9掹Q{y)yc@ .qޓ'=Þi:\J2E{R ^sgM/Jh李#Ը;Qޓ<҃J|qH'Խ:hhl\sҌg<юx)2sGn{bc{0A #\"p:q @r:&RiZ3IޗJ:Rs:Q)q֎إ֓sI߭.:d=R?JLs$w{uh=zR:м4Z3E4t4/Ru旭3C4ҎNJ;s/Q~4惃(qAG4i d&}Pz{R~h8Cu8)3 8ޔցszԽ) 관qAJ8hxu֔“ތҌ J u sKϭ@ha{cKGHy֎:^ܜӸa@.:Ф҃uqr .0i{@/zCɥ1֎)})=i{ 3ךLJ: s@ȥSRg J{ Cӭ.s@=zR:iA4JG='CG!8 LGғ9Q#'R3vўpi?}i6/&4zA'?8t#ތё%iON8J0G&AG=(z}7qӟj\bh4^JNxi KA`\AqHxwzތ&HSҐ(=x)GjiҊ3Kӽ)֕A5P3ڐ`u:i}G \G>cPyhԽFJw!1Fy֎ G⎃h~c Fqץ/SI#)'QGE'>R@::31ր8 iHdbxK4F@4Jhǽhh'#֏LqGO/(g >hJ?* ◾;PM3G(=( ;r;Ҟz {bA$tG4c$Qc&21KqI}hiz:s@=(:HI)NJ@qA(ӊ88i9dv#N zPzsڗqM;4QAt4`uڗ_'4`4Ez8o(zqCсz1EqڏszLqG8qHy9iKӉ#1օZP9?J:h=1HrhQ3^(=(HGh/)q4c$Rq"SA94fAjPE'zPr?Ɛ=h+ZZAޖԘ=:=ӁK9'ҊQ{ќPG4g2xz3؊;Rg+c4ZiG)أ=iJ3ރ~)8){=(Glց֐.xȠ`яJ8VN8ȣj^`מ(4ޝр)ONJ zт{RP8{zPE瞔(r=)}~isKޝiqK\{xs@Nڗh>qփA@) zA!ԇRz=lRޗ8z !@9ڎ=(rpx=zP?JP);MzP1K^cH1K4c=zvE!DZuޗ91GZ@>cR8(iqH )OZA:wN#堌QGO})?ڃC8`FsJAU0#td1hj9'GGCޔ{BITF9':\qIzS҃ғzPAJ?.i ) Қ8qHFAf9ǥ)HsEKN)O_!=)qZUA'>q`1IrQ҂{Qϭ.>@ArhGzL)ҁMܞԘ9GQGS"v1GRcRIRdgځFBh1G?A{~>t>iGZqGpM.F2($fqNs֝A)sK h"P}֗4>h4v=i1KFx&xFEdiq֐ {QсiGJ@2zGr(gEP2(G擜ўsPs◧4${ґRt _F9NK&8ђsF:1@ҁFq4tLT4:RdQi'=Ґp( .IP03i:iA s3@='K)zCҀIҗ@i;S4ʗZ: Plc J94)q4(1ړJp;Qhj!ҁ֌f~hG恞2xI@4J_@iǭ71JiLbAGSKHyon 4ڌ)y 9J}}8Hs(9")9(:q /N(!}i?J:RҐ/GEP(9E/aIK}IcGZ3:Ҏ}hɨzs@sFܚ1ϵ/);}EҐ0} ')8NMJO?JBNzMOu{RzfNN( ԿZ;Qu9>`PA23G~ )qzRG($4w4 ўpNh89QsNҐ(G#ARZ:2=QԚNE{FsҎ9ߊ1KH ;҃hȤ J@җzRg=7 9hh=x&CJ c`GIN)@IGaތu'P8"78N(^9(&IޜjL(:Rⓧ/CړӞh >lQ/Sܜ ┎s;?Jtr;QGN)0sޗQӵ'94M}(JS8Nis'( Hw4^tHp>ў88ZLsSK:A}'x揼)O1H( CiqIiGLRzyȧt' u┏\Rr CzRqK448=i0pbwg<4)1)}((֎u'NJ}F(֐Ҏ` QK)03t)9⁑֎'J1G(9&K8)GHs)4R(#L—1mPqhKN1F2 /NdycގqGo :j^cԤdsHsۊ^΁ӊ*;Qۿ֓RAA.}qHOqJy-ӱIqGcsGj\dsJ Pq i>o—:w8җ4g4 Z)1(ؠw=JOJN 4c/CGAҐڔ٢iFyF0(Z3Zv88!ь(㨤OB)ցҔwuiHtR@G99"qIxrqPG8ځ9?ZQNҐph9($ z\ F} !.9N)Aw掝Ҟ}(2M.Q֌H9@1ӇNM&xtϥJyߊ0}hoNvGqGC (?ʗӵ'NRtϽR ;zǦhc/=M Jy=zLg4&`i8q@JqCyiޗcgJ:)@zCiO֐RH SItz4nFsҔJC^i3Z19(ڎz.1vQJ{zQ88ўi{R{A')z^;PsAqJ J^8fցzRBqF9zQ9((9;8F:^ғ>Խi34P3Z=}h );җ=y1@ZJ &x3@@y$)ppzRA旿J ))GEhϧJ:hH@4(4J}i`PR4~T ~(<GN} (=8g: 0h\ xF{ړ9Quz ؠ9qHx4)H@-Ԫ~RE/8g9 \qKϨsJ8f{Ҍs;؃H@&:zNzqGޠG)IG|P8 RJN/j'=9җ9q:c#3҃΃<x~){R:h($4dTu /~ڀ;ʎwIREցz1t==)h<`uʐAJ>E&HA=^4 zQŠNO"ڗM/jh84{01=:ߚ@0hihԧ R)SHzҞP:d(@1Ab8HGqҔtގsҎsGFyAQ ӧZ3ߎ(ZN{h1ғzPjKޓ:bZLJ4v4 ^)QRZ\ޗ$'y'=sIQC QڌߊC:tRd PO^(8F20sJhϵ'=h QGO/B M S3mK玴sJ3jB~b8.9R08h8җ#d:yy}sG%ybwciq;@z^y4&Oj ҎzF<)Gҗ4{ў=i#4 "uހ?J_ŽOJBp)F 揥 h<=E/Ǝs3Oh1Jr8ނ8 qi9J3A<:jSMKj8@zҎrHscZ^s@ڐ8J1E9qI֔ғz 3IJ3QQH Jv}0qG~v@9֗SHj1(M)8@#tNi1hEIߚR:bsKIN:g`֔psڏŽ=ygڗHrGڂ>sK4\^Ҁ9ҁFZZC('1NiG6P8&Ҏ4 )ь2cߚQ׭ZN88)GN8nh=1_zOJ;h4g'^GN!uGri3QRAtOjLs\F)A3J9hhApA#Rtq@#49:zIAN!OF.;94K4c&2yzfRJ)O)81ϽGGR"N')H4E;ƔuCsHy旞cp N1ZS׊uNqF3@).Ni ֐c:wN&NqKޗgxƃ QSF8ǽ{ Q4;'@##9/搌F8Iq419'/)1ցdџ\P<3 (?HsҀ֐ izIѴv4q:R);{9MQ9= /j@Aӹҗi0}E`P1A<@Ct"NqKh wL~83G98(&4`}(GSGB{=}z1E'h9I?֗G=)/$r)N{SpsKc2gJPpE;RqK 39(<ڐ}(49R~4CA8#=({i3J\׊?tu Q9OJqfvsisKP=isNhu4gJN4>84fz^Nh\Aϵ"qҎ3crEJp{PsGcѷ#֐dd1;у;Rc={I9zIp:Qʎ;I4r@A8:AKL{R4`ԝ? 3@JA9I{sQЊ2 R{Gzi֜3C֌Ԋ9"֓;G)֐Ki9֔֗9RdԿ49j^zSz4ӊ@ ɠ PxJy푚:bGBd?PirA&3@Ng Hr1})}=(F(=GO)1h Bh>})y֐:SH\z9H4}iGӊ:p9&sGўrGJAJzGoz1?Z?2h1J~qKjAR8OzRhс@cIcNH3Z\g=hƎ)s&0xh4w>fPx4pPG=))}=iOJSE8'i@i8?Px~Tcgɧr)9=@H֗Ȥ<QPFh 44cyJ)1GJ_AKҐR zץ=(b3u^xƂ҂8$AG۟֔r3CE)^ H:#(!A>`u)[?OZ:g{R`8 AsGpN(GJ89Ȥ9@㎴ɤs@'҃(h1JNwJqIwҜx8j\tKߜQRwG~x# {QqA<Z^Q)sI=ƒH@$q=)@=Q~Z^8( K23ӥ;ځni飌ǯZQǥ4(wHA\ӁZBy"z^#'8)Gh\psKMOON(OZqp2)0G49Rc|P:qGjNA◯JQR ^uN1F}i{ъ\Rfrr)vF14Iz4{QpAK(=sE!Phth9)yZ8s҂zF88Q۽)S{{:39 ( qڗA9GN~zGoZ@qsԛz#s/qK8$&J~g}ii(<"">@QތRhdd~JGу֝zPΐK֎=JyHqގKzsqi֐wҚ8N)ܓGtH {R  zRJOGB1N4PNZ9v8!r94QKQ׎ԃ=S杞0{SJE'zFS/#qSy'4NE449(\fSG4c9)~9.OZ1ڃ⎽(9AB9/Z\psBFIJ^ 4@?ZQi}Q$C֜0I@Q:ҁ$gIϭ(Fx/^MxюP?Q֓\CR眞RqK }hPN?JJCԑJb`ƂqQ?(R0)i/4`w~u4g҂x) Rhi9#Kۭ&0 팊3J=is&qޗcw=G!h&y'cv8H n:RO—'' `c'i Z=;buN70M:ތs-'>$ &1NJNsΐRQJ9)z89sZ:QhҗC(KQԊ@Iǥ[ޔ>P:QZ^sN=4ѓ3J^h#;``t#qjJ? zRvcށ֗&KڌssHyH38GJ^OQIփzR` (>ŽJNv/\H@(OjE 'GGQIv:3KH3N(qޓޗ94< CJ"Hz ~\bG'F>jSg֓=qA8A&Q{Hp^1:'i>QԚH~8GQhgzzњ^&6 ~Z1NE)?.i+KҎ΂:= !M49r=)I)SqKҏn2qRjҍ÷Z Ƞzc\`tu'Q4GzR&sJGzzRRGSI”`h^=iHќRFqL4jG=:w RqITQKzݩz}(43ъN4{QJ2>uH3J848#/Z\7t9A8=3F)zf~RH~hOcK{;Et;b◿4F8\83җJJ(#җ(<0;P=Z?)pQ8F=zьɠgZdh 3; _֗JL F@;y֐ZQ9P}jh84u8i:{QNh)RR8Z^POAAsރsGA֌ރ}Qڐ_Z3{4i0q@KΓZ# Jwc@qMҎFMGьb:;9ϵ'Nx4qA8}4J:ߥ}u⁌Rv/z;Q~4co4848'\q =($ui()H9sP{sKLQE)FiݨJCg1BuԙK44Rf=yɤ<)'Nh< !qۭ x JQ \bvizRdZ*vsLҝgޑGҐq@Pz4wϰNh')pzRϵ cўGchzQR~Z_z1LzGcGjN9@IԒ îh< ^4 !9Ґ`5h C:ס9I?\gR~=s@# Niqh@G#cq1֓nJ4ԠK AZA(#P1; 4SH~P:tK\:Z=qJ1:G^z֗'oZ\h>(ӊB3jP848Gc8E)r1&r:ti1G&uG|QP>.9'.;>tKJsM})x8sG◶(G< (Oz)@9&2}z(@={؊pz\Rc`: '*3Fp3Kԇɣi S!1AZ6#*Lc/MQhoRm);@2=s!RIрG48(<{тyEIJzdqG^}h9=(h<ϭ!ޔt QL^1F1@zN:P= )qEѷ+KL!""tG4"R :@~ƔMeʓH:Jъ@OJSF)9G){P8"3I^):Kc I)T~<џcH9gE u0E)ӵ'/&Nz~4HpiGM&s(9#vF@((@ӚJOb\R玴}h')aI{bNvxuuwJ4q3ɥbtqp )s֌~TAG|RҎԀsS֏Γ=NIzSdGJ)2sJA9#)I/zB9`ui)OaG84 2RRQԥ}@Siq iiqϽ#{S>sG^PqL"si^1@=l.r9Eh49JQ&֚sJx44(<8jB{R;RuJQȤLGҎpOJL{P1dRphON(Gn ގ6Gjh gIڔu8 nq7 ;`҃2(4}8sFIZC1Kz8(=(< NKӂz;@'-ziSKȣi}xiw1G3␚\cHڃHOsKȣttg4ڔyA 0sKYƃiA/sG'\Ls KR^IZLR`Fi=ÊB8P{FPOԸv ^;R~{R:A')8sR`g/N(Nh=);1jsA QۚHSKp)1ǽ;IN:Qמdf;`.=l~4//.~z^F} j9jSIGlvޗ8⌚\^izR4w)sNsAҁg3F;ށ4ړ=E)sK<Ԙ}(hZ3 )pq@R҂IQ@ցg^s 4cj\Q4cHOZA89ъ@;砠4gKg҂y #01K:br(#4E/׭'S4q/AJ\`ґiTqK{x`:1Ӆ.ӏjx\( N)sҝP{gCqҝ\R"sn'`zP֛Ɯ)|R2M}81߱rO4c)<{P8iZPACti8'y⏭Q8jLPyo9P1i8=hiqRA@C)8IK')qRѓAi:Qւ~ZIRr>(jNQ(sHx93i3JG8hޏCKCbh?R`u([$ý'oz^4g#u?Z^zLQѨN /&r(9AQ҃= KoSA(=>M/SF8ӊ'.(FNydF2};qN:u^@摲F-(hւyg8_{RftcJ4RN8? m;}yϥ) 9>ԍ:sEA'&SҔ:'x<Gniiz@h3M9JZ:w=y(4ҞtdgҜLERF)٥i9pzQJpG1^I\d;)AA^*uM")FqGKގA>ԀT):c4wGZpqA1@ҌbyA Nj^4pxb CK۹:с֐ riAzҖI#/8ޜhsI9 +a,Q9+)J.{SX1Lǩ9S1E''`@9 MpG5_I i3=GI9JGri:ӭ! 2CI1H3J3 4=/>R(Iu{(Sӵ9hz9 f$cҐ9Ƞ1AҐsJ^Rd OnKjKӎڃƓ)ONi28EFh)3sNi>;RM){E)hH1jQAi9Q~@ړuޡǵ&;~td8^}izڌt4hߎ M/HFG|P8P1Z8c/Q:sJ4>ԣ} `ӂޝS;zSx&P@*Ԡ8T{TgL WN8ʣ*ecv*UOlԫN/ H44,>׷Q)*@CS8<'nH>9A40#Y#9W*G_Z6;A;Ң )*0zSzSGmT,0NE㞦u28zO=h֎nH:F9RJNF2(=(z3@EP:C揥!j^3ԙAQ^QzRfyz;9E@s4s4zRssڍ_–ނ~_Q{=(')O8@>(Gx硠{g$Qڔsߊ A3Ni:w9T!s@P (:ѓ@=ђ(}M3G^uiGzCczsA4G^ȥF9ⓜu .{⓭h<Qp8KiN@wxZ5(OXR *aGKg:AS"gڥX܊#*H1K߭zOš4Qҗ>Z\RiZ9)qN>n })@N)F=iI>g#);'4IHN;ҁ^(F@(Q֛}iOAJ1v4Կ֎w'):^~QhN @J zzґRqh/z3AKA8F1ڎ/AA/nhIi`sIJQ)3ۑGZ_4c((F(=@yzSLx4QQ"L i5WPA§n{i>L$WpO~ZFOUMG0* z2M+bbGW61銈/? 3rIG Lq@Aёסԇ9QF3ҀqI;&@i#4(_JS'Nwځ=hҌ㨣?.99GAIZ1֗=M9"KPy4c}i=Mz S{рWE(#i0("hQA#H=ipr )RpO4T9sQRc(1#Si:J@?1p1҂qvpSrM.r1I@h$b93F=.#P`Qg C)s94MьG֝Zm4riF199L Hxc(1i'=/)(p8G>'Ҍը9`Rdv3L'=)@$Qi2{Ӏ&ړqތԘAӧJGRz<(&>ʄ✠SKjCۊv)~1Q05QQHHBHyeyxP_-U<w^EcP$8J8q@zC3M4~(ϵG'JNi4LS揯4gҔgsAwQ)2zvw4by)nhPyҎq)0x9JoCJ}}sQzA@2{t{ڂM(qHzҒ}?n:2i@9!~M/88s3(Bю3Fsނ{8j2zb9zBzqJ81_)OӚ9( bqy'$)qQPq@Ng&2zSԃ4ך^<ϭ'$QQ4r}O 39/| CisK(=3GךQRO'N@5 ^=G=*@*TJIaTV  [{~uj5UPڮ"bETz S*GJN`Ԃ,NX9(ѐi|)2:c;rj0֑8m$ofydwuAh!҂;QqKjON)1ZByztZ0zcddKJ"HNyI׌bt4>Խh3QN3A֏_jNҒ/lNPAqI)y F8gM!ah)9s(xւGҐRhj^޸ޔ49Fh)?z60yF:@9N{48h `J^Oڀ)N=A)9uʎyTq֞1Ipjxjt\ZDeڭ[/®E@ȫLJ#v*!1RjeSzT&9T)Oi}ib@]F*"MaT[>*-fgZ#MJ8sA8(<NqKӚ'< ӽhQ֝g;ʜ֞1OR("~a*"F1Ҡp3FW&JUncjcT0sU~c2Eyp?6EFF7Қ:SIO{g'4gӥ Jy4rZ$P͎~擧KH/JAҗ8֎iq=)c t8:RwGCF1ֆ99)=E.:tLdsJ:zQ׎{t4Z;:=:_7"K߯Hzʍ~4>@9?@Rgh@xFr9ns@88'4zRgsFOj=G 4gs/Qښpi${1G ғvPN4֗ќ:R sIj::P94{P( );dQ#;GOS@''zP}:JNyK$ҟѴQ֔w^^)CPO()Oi8;N)—4cKqNHJ}0jP0zuQxq*.:&HV^qҬƤW^ݪ#* 3SV{TqS:B*uRTFi)#iD\sH dcmD`;4d1Py\4b,T9QJjNwUyӚ|l1sQ5j3pETfNqwVNr1Ȩҩȿ7)tMҠ&iLaO4 g'=ǯQI֐)FON}R@4vr0zi1O/Lq֔ G4I(;sǭ ɤJ= 6{izi9hi GPҔu(cʎgL(uwtڗ<9iyhp:R 斚G9旞j:(ⓩ#3G^:Q;9s74J;qM gwP)sN4ҏQ.@pM'ьwҔ&ܜztPz{Ri3KrF Go@>9GQI?;SA知; 8)8JJyҗ(=s'jwI==i{IׯJ3bh1\tu4H8J9h4g{R—3H2_U|c5 _zNzc ZNM\zҞi<s !9(A4ސ`6Iw>`R''K'(=Jx=xsJ1A (~jAG߽.3Ҍ`R})H@JFqɠt=\up3@!p8<9'(48 Oz^):dR&hg9&)~SGoP=h&oh׃R;fINI?^vp:tԼ0){PF2j@;NsR=MJ}je\֦A(:qW"ڮD:qWjtV&ǁVTVL$*HX'zF1JaX!ZDC{Q"|ZE8CɨfبjWf55\r>c5ޜTsTSs{F1TlbeMStMG"J8H8{TN6GL9jBs؜cI֓irhz~4ݼZ\PyQ֏uqNtHA8Si@fL‚@8g4 )A}J9''4 f @Nix-$zR&: R3@By=ȥ)N=2;d<҂ 1RHy'A('SNI^qKJx/'.8 Ӕ`sNQx uԊ3R:sR54`U^޵a:t18!ļ:U׊W?ZWVSڦPs>ԃl\b~4qAځbuqh=9>Q}iNRJ3ARЊ2ON@控qOGIގT{F=GKMRrEIM=is4ޤS83Q(#=R IP !ǭ/^g<*L0x<҂;j:Oa')qGɤ i/E!1Ҍ~r9q?(hOty4t{SO)8JPsFFi )cA'}(II{㡥<ьp AIӚ03@A C\ރ֔8&f2=}i3uh94('3Ƞr ?wgzLw1FH'qQyA 9GJ=i9J>()(AAPM'^iZ3Ϯh'=(8zv@tiA8ޓޗJ1ס@fw>٧v(Ԍ zv8 :Ԩ5f>3\Uquv"?z$ ⬯XӥX\`gXNj5e<2 ʣGZANHNӄgn=NzӶ4KTr1T&f֫*"]sQ3Pg"~j {TO p*83(P8\c5I-j$*\u5  mczv=0t'F21֓N 8'Q LJ=?Z) (9;wϵ)99&yr& $N9(ӊ1Igc4s(<'HR(FGj:QAI(cQA`i9ݨs y(ϥ&qJwlݎ(ۭNRqڌ`iO@OcqBz#&FyF l9Ҏg \`f#) ɠ4=sNqF0G4gҔu9y:x885(OySLQ(8uj5ը Uמ*Ke:q֬'=*xǭXCVP՘5ipEN`6qҬ!>R:Ɍf@4ࣰPTm Giqj8稪.Iɨ0_jNnJT.H*':UY=:v"ɂI5]sި*ǟF֪#jrj&M= Q֐Q7sJ<h9J:N80M&n(1rqFA~jMpMJxi jP}8&:u4< $Q J1ގ s)G8&1iJh;Q JLG4`)qMޓS3KӦqI(})GNi_ǩZ\{T `H'3Pzi;Nh3H&.>q3.y2)H NJLҁ%/L֌{Ҋ1:r9';R3( !FyqAdh=i3ɥ> g"HqڔqRgR u/j9pqȥ8Q9)F3NғG=J1?;QRQK .p:Q ^hi@1ҝRN9J{fLf^VcZTR.EV+TR TE.Zwc5rsPUc U׵A!TMӞ qM覣=)1ғN2 !Q &H#"R1^أ;ў{Sx&ҏj>< \O4ӊ\ BMGuƏ€E=3M8RgPx1J1'|`g4(;9N3ҀZnpqڔⓠɠHI3:Z4`c())Fry9Ԅ`ҁR@ @z 8wz^qTeAP88S#j8\TtOsQsL8LM'ZLu9=E!}1Iߥ!iڎq҆1<($h({!N:Q 82){tRs(< h8Ixg#җ>G^;I'GR i;TZ^ԝZBKI)WzKH{փ)8J:Ru4F0i: ڂsn9AqFx J1(Ix1ރJGjH{ґFp}ڃI=9\ҁZLK@#Ⓜ>un)O< nyG#3GN恞ym4isvgPs(;*ޙ %jAP:YHH5lUwcDp*~Fz9݁Ȩw vj"U9Uه5NB2jSo:TOUX|ZAP߁P~i8늏4v#9)3G4i; Oz:jLRzRӚ@p0iH{}@(!֔;ސ;Ҁ3 Aך^~Rvh(@I\s֓<J:Q3Ez1hZO_Oz3J)rF1G8)HGN)3?(tu&QKޓ㯭J9Z0( AF3J&w<2M*1G|bbҀ`O4 w4gZ3ǭh}(.p()y4uh p{c4}iҗҞR)'5"zqS Vc3PyWa^Ձ2 A?j:`ՅF21YWpr*tsS52Hqnԫ.OԂysbI4z)AڗhM}3 /N9QzRʌlL4vK׊Z_iN89&A9;K?&h'#R?QcҐgus :J}!b/CGCZNSCGÚi#){s֌Ziђ(8ǽ&ysR$t=(#HNiZLz\sH(ϥ.FEhϵ>nN(SP)})9␚:Kڌ`R1NAK`'h"g":0ZAr(40:QRFq)#xPxi~`gi3\ Z 9b P;Ҏ6qފ1h.B3Ͻ!q@sIҟh9)ZCNhI3NyJOҞ3ҟcH5"֦N* *x5e;V6q@?Nj?LF(G֧VUaSJךzcxڥO A^L`I Q`iN3܁BsQ59@d0)o^*b=f>qW#cV9T}*e8*tn*dj|.jdzަS,R皑\Aȧni۳LCfϽ1֢p9OCsPP7D'j3P֪! P;Z$Y-֡w=곶* F @OjNTeFzi88i?RsI_ZL~(M'"wRc> q~4u ?J19}?(f:RpO^cqI/nԃڌqAAR) =9E&2G4<.1=(4gpA4G$Qrnj3M84c?=E(N(rEGqh 2q\:@?(Ȥ^)1ZGҔKמCAx֝ʍ#sAR㎙$fsR(9!x"(^i?1Z9FiO u;R#)q4ߑIKӽKQRA<4ZpR}i8ZA^iN"Z#eD\GEJSvZHZXbO5 ^:Ӽ&z'1 & ƙOMw5Gңi:Kj'P?Қϑ֢gQ3drqQnsQRgUQS8Ϋ?$Ug> ȨMD cQ^s)?\ьv(:QjCzC9ⓌqAZ#'L~4;R3Qzi=)ݩ1EZLqKqIގ{3JHN(ZNu9iI8룷u "=sփԑ?39cN(qiN(@ۥ Z3ߚ^H q9A9~TwoqPAҊ: < R9>4< H=Z H2xtNxSr*zՔ$r6sV ZF3S#fWNǵJ LLjPק'*@/(`:RZi#=y#Zn9?Jo9ct9IqDjPS\E3P/J$P4;穨Z#9 r}*8DTLr9>FFGzC䞜QG3cҎsHz4dtiLQ1ނ9ϵ>&pqH[=)qG;xۚr('~4?Z2OqF0ԙ=uP '3KIQӽ/IzPri{Rri:~&q JpƌQi8ҍr)9tKғJ^:tRoB~q@h9JAA;RzBHP.@)? c@'4'#KܟZ\c49Ҏ?Z9ݞ1KCN JVRR:Rw F9R@chF=i\;&Fz@揭vZ04ڗ=ƃ<:ҁސ~XRGj;E;ހy▃Ž0sG֎cv)@GsI99=idґ(rO4c4ӎ?JOZH\u52LT#qU>j93VedަV?z8je~OVjEl})I9MNϵ7)lNx}6cLg5~Ɠzyj5T 'zy*j5 6j&#> 1$Q5œS #9tIsړ4O4dz inA ('$s(">٤F 4yz^})㠥(ғR"GO/vM9;{R:LfƂqӥ&J^AR{RRsgIK:3v(8أ!J:QvhQGqCw4qFp(Мp9>hC5*9QhG~:qsR >~h>w!R`Iǽ`֝& RNh'wdך_R48pE!lP;Ҝ1h i}i84qhfqޔ {{ JQҗ}}Ê39i=Aڌƌ/8UbiOFEΗ)zRM ӹ'<'IzzzzdԋS#` jec5"6MYBjx5"n=iK)Dd4fOzC/LoLdژX2rAFd`5XPMB:g@ǎ^CP_*8Zj5gL'i?/ZMW7ץ4oCFsրzIJN1@ 2> Rn ގ;ԹPh$@hg֗4тsNIւ1'Oz;0(9ۊ>@@4ZN3h:}h3GbzH9hhF(oΗ ?61KzUhݑҔ0(PpZ@?qc4w3ގ:zQ@8:vPy<@r)r3Z1qގZQFG^$bZ9"j~F8F:fsNK<y"&b ɩU(|c5*=juqZ$S"Yp}I 5:JzZ\Ԍug87֌֐ғ֘ϊoj׃ڣyLvMFT/)AOSQ>~IQ<=j&p~ ;LdflfXv<ӭ5TmM ۭ!&2zG=i1p:zq4q@ZLF{ft"4 RxhR`3S)&qH=H}z^{GߍrOz8>c(ь^֌:3qIRh @ϥ>33H:Gn(9 J4hQ'OKB9!ь=N('K g'Zp?Z\挜tc4Jixh}~4M(ҐQހ{ \)'JA׽/j:Z@bؠ4}E*:Rz^OE\g)Aށϵ;4:Kڔu㚐R֜R9OJ fBzujeLԨ2HҦIK֧I9VlqT0c3F1IϽ㨤')x8ڌ408{vG#A8яZ;sHr[:(Q F(JyJ i:vF3ץԼ CF=M.qޔ(z@A zRIҎҐxIJLsFr9:ph&0:RG/(qPgsIs.;dIל 'RhH$Rtގ)@挀Hq;3A'4v89F(4gQfzc&Qތ@O^h?)8Hy`&qJ} yGA(~e A9gӖv v~?Fgq4Ƙn854*2 >l'9 TD"~'Ds^ߥN7ޠuA4)20)s8F ԇ?*L`uҔ 03Eg҃g}('ȤJ -J)>)F){Q`gуJ&c҃(䑊u;<iAOM<05"HԁjE|wUԊp92:Ԋ=@*0#zv:]zR#_0zP_7瞴-0HN:Ҝc81yMFҌL a& &:g&`I'4S 0ߵ4i;R)"{Rgg<)A 9MǧJCJ?JNIӚ@I#RsHc=scA8GIړ翵;Zo#(b{Gz=48zQюXv44MҔ{F=8gR1M$>`ڃ:`Rړ9 ;dPN8Jz\4~4cOZ^31;旽!GJCz:ZSx⓶MBi=sG:3qޓ ~"S8GzLg9uc))Hyh玔@Ns/E34c:QE R sR8>ԣA⃑KFqIGNh3F{bɧsG@ (Lwi)ݩ&JF/jCJZQFhyKڜ/8qޝ׌M; x9OWjUINy?=dH3xKqҞ҇uIi*`cBQze<ُ~FL8Q Tlcޚ_ޣgL,93P:QP?*CQhގ1GzCJAFNzv1ޗssFs)8Ith(9M҃CE/^ zрGhh'iN0y{Rgޖ;gA掼֔ J^3ށ:Rh g= =};F:z;8sϭ(Jz}i2q)H2:׷NA&j#8FsڌQZ\A? (E)#\G.})=IN掼fҌhځgqގݩ Ӆ& ;)bGnhڗ۽!^~t␞("сGSJs'ƔjQi#ޗ)z ^pp}(>cy4c>N<$OS{g*E4vqx#9X9Ӂޤ J^iɧP[49.E/Fz<ϗMu/M2d~:M/ԃ5؎iJfi޿Ni^r3H[Ȩzs&qGzi8PIzO֔iOCM^d03@q&EfO4SFzH~n(O'KIьz2sڗ'ZXS}CiCHX =!4ܑ֓xvF{Rf0')x/yw>3~)K ڛ''3:v4igҙצH4^n$=hqAҝZL`s&yJ? ҚB ZLq4`Hǽ^):z dI1Ӛ:w=z\ZC9@8riq c'94Qr3ڗȤ4QJ# xA.9' hqGZhtGp)_Z)I `b8HҞ<ƒ=z4R ֗9J^8q҃;Qh<3ӧgzQQIޗFzd c4zuր8Lfp3G4Z>b(E/;O&OJ@s֞NE-c:ʝ\SRJu ֗><ѿ';~L9G>*7֓G4 I_Swv'NG&xIi<SKdS};BONq zҐhH0(:Rݨ>FG4g4x旯4I)Rr{vQ)Ox4HTciF⛓HLRt{up9◮)n>1LRN;RpE/AI~44g8^tdc)sJ9h'#8:Ҏ8/lqK('J}8RGn?:;guRt/|Gn(=Jqޔ֐c=bsь(#җQ֌c9h֔u4z`PA8$zSǹQǽrq^)r1h/nG4(RcSQI\Ӻ L砥s4v<sH\Pz{N9F0)sA1JN4c)r)0Nԣ!9)0֗vގs҂RtiF1ހMqJ^Q{QϧZ^:snRq@u iIIizu4ɥsSH3 RipG.?:3Gx0zR֎(McS؊u.}h^)2ԿZ==hisҐJ^q@8◃G8ޔ@QӾh1xT1җ^h QӞdS4u?J}hȠ}J^pirxP4N݃K'@aޔ6G.qRѸԄўqHX4j oCzf''OZ;Rp1AI=;R (zP:N.s);7g.;&qHM;yG֐Jxzs1ǽn3J0(⎇M.1֌s@K)1ZQR(iGך:{Ҋp/&sӵ;8֓ҀIX#z'֍qڐF) # {IGCҐ@4GSh8=:?;ZLdtr):4~wȠP=9#ۑAOFO=) ;xGvۊ:t֎;@AIzRw@i:/q@94{xHzRsKGR L'C=i{h <р;?N94f@IA.)qNs\r:Q(ltv)t;h u4qQKߚ hIG'i8wp)GgIԣ);!>@R JNtG#:gSzLq(QHHϭ)GZ1@G4QҌў(z^:@i{Rc/o8?Ɛg#Fxg)z۽ " =2;{с qKPxKߊ;@4F PyFA^h Z8MFxGw4 PqN(玔JQڌusښc*ќ}(qG&$ti94㩤ѓџʐEPqH iR gJJzSzs9恜|fR#49<IZ@:`iߖi1撌FZS8⁌c44w=8KۊL?8Stϵ O=)iGNh=(hƌrz֓bsϥFr84)A8i@9AN1Js@=1Jph#֔gցӭ4qHO4bpqj3ޜzbRqRAӭ/SK٤c#!P:zR1ךLr3K;cEЊ^RsGNi\~}9zy4xH8i;94bEZ\ސ9{?z ʝ_ʐTt8J:zsڔR#Izg)'J^M&N{R sL/9Gn:=qIKߥ?ZS)zQ4F{RIS hJssF})yϵ/l'ђOQK($֗h9SƓߥ'nsPsRb3.14`p:f҃RqI.JiJO@LJzQQ&s89`&Gq@9PX9┌qJFI.(ny30A})sh"hǵczBx4P1^>ҎOI.{Hx @(擜N qA?x;sGph4uRczN֗={(攒z(J=3G֑4zvu)z( 4`jLqɨ14@0ixghzPx4{J3R0 Ҝ֓$zbt \3Jx0H'=Rw.:8'Ҍ KސҒQ =~E8q '`P=z !ў:ў1(Frp;Q֗8IGҔ@4>? \ HI1GSx>uR֚XnҖ9&{G.@}FEi{Qi@掼gS4gҝ21BG8tKf8$qIRsK?&sP:G|8=h4ԃ4c:R3 sEMFEq@19 .=4?<Њ#(<.8I>ԣI44z ΖE)ItJ}'Nԣ9==)z9/OJ8F@B)8?NP9084Ԅv R(#Z#KKZA&>1q:Rǭ.94ގxG\Qϥ44c4~Rڐw#4u4`qx"@<g4vI8E+pҔx}}'y#4Ɛtu_Sy9x=9 NM1FO&1ڒHG|4pNE &9无K=}P@>`(GntZLc$s:ѐ޴i:T i=֏cHG>`3Jp{sZ3tNtZFSFi{`QZzCH.y=?p֓J;RR'R`'Am?擵ht4\H1/lZ;:iRcOƎqך M*^iC Qzgj9 Jy4c>b:{Gnx'uR`Z@})(㓚AG\qFh9 (8h29p)yiTRlQ =GsGRzюxs.*K!K+)uI◾}(ZL^icҔ擠@qގqNf')sڎ?*_ƚ3RޗIQNw!Q M9G^iFq8p3&9Hh:R/8QRS7;ޛ[ dzRg'.8{)Ҏ})g9ڐb>h})9ȠQRHFz8䞴gic;p=98&I% "Hi9Ȥڗz1I/4gq84psJh@֌lRRi?h#n?*֔Pz2iҌzsKz$\Ҝ4sU){sKC)}Q(ӜPi3R=ǽ/|>3FC@(-!zRF8 r8.)MR4sP2}:zQӑ@9@.qIn@qFyi8tFM*c&ތך_)y=(zv};RR(4f 斏)ȥ'iGJ@Ҁ{Q)>c}08 ` LrqKb}ݹӳzQsG'$) u$;JR8M0M)?^ړ N<&F)\E.02)3Fri=H/=;RM Ҏ=h'4x)J\~tIF.}?JQ Z3Ҏ{ޏ ^LQhƎQi3iFqҁ3J ɣ4gb@niOPq@$ўK4up!8(#v!R`Q1A#҂qFjSq: '8dϨ94@֐KI֔(9?7)Aތ)=qK“IA>( s׶i?'C┚;u(ҎQutޔA84gJ1qz1F8Ts:ByJsN(&)9'ixғ?4PGJ^Fh9:Kh'Nh@ӹIҀFxKFp1:P=(?:1җg(E=җғӜҊF;yPzёIN)z /j:bu#\q4cI 3ҔH}qKJgi9n٥#Z8䎴iFjL{y'n?J;< ߚϵ8/Rьⓧ(2O#.Fh7ΗJL sA?Z3P84zR`Izch˚Lfq1i@v^␎iq s;H&}M.OQGc4HzNf:sNhhҎP8i:sFi{JHI9QtRJK}(#)@I@Gix9L:9AZQҐxKs;~cNi@#hR&O9J)G)xi#Np1֔F@99$JrWZ8tFpixG~i1K 3{4gސzRJ:0<ޓiGސQp9{Rӊ\P}3J'NJhҐKQH8JxPs;R(I&ҏZP;POFF}8j1ޔ889"8GN:Foʎ'S4~tv:in2(ǭAAצ)sO~qKLgQրOJ9(ch ;Sqяƃϵ&2hvy 1ROz:uM!<ҒgQdjCbr &9旡=3i>  ;iHi=ޗ&3ڂy"f^8<ҁIyH4q/Nw ;dqI8NsF3izcJPp(98.SFsJ814A g\dQisp znrO9(Qӵ;ӺR^hߥ)8掝F)sqғ"z@1җE ڗOH{>qzP3=ix'"v4ޜьK !A=ҔdjȥTךN)G'LqJ>֎?^ϯ{qIRA84tF(日ZA\RRsG>sSzӹBN"c;^c4$gJw^9<ќQF}cғ@<MF8.8玴"i){u'sGJ.rxARi /\zd3FOi)"G|z`t#:ߍ'ӊ\H84qBiGaA1(#h=3֐4ⓞ)GK׽ 8G"`Q:P8Qyڗ~ԝJ2W ;{ P4(A4 IߧxwFփ].23c'֔ќ@n4J3I.9mIz'ށ)).==3/<( @$z\zgJ9'PQI(44{q Qw~?)#1:AN:Q('('i2yRz:~sJ>g#<J6Go=iszfc'7?^)A#Bpx旜}hia ^Z;bzA<8Q=ўʔǩⓩ)0Np8=MjRzRgE(1i8s@=9!●ʀpy=h4ZSsғiO&iH#&y#4d( b9JsOvIA<⎽8 (3oE֔)JNi93^=q1Iq0p &I) :P?Z;w4hU(ZJOރނ(8i>(<ҌtJ;qFph(KHZ9c;ьysJ1\pEҝiKGPON);p8<4IJJ1$Si8'&JC\΀0sKo#=)i3FzPx4gڗ4x8i0WNOJvsH:hq#8&sE&j^xix8 8)8)3R4}^)18$9j^ށ=(2E/^hp(y' .  q@ 1qܚ(4q֌zL\q@z1uҌN?Rx擭.0zRKqP}{;ui')HNuchA>4}\{j$u9<9\3;} Z\`{Ri )ER`>c'ގ{/joP9t8Qy(q.1IP$&)N w_74}iOҎqFh>qIhiOp);i}3֗!Ȥќӻ{c䯽EFH.qA.F4.=sMsp(ϭ8{xiޛ}Ԅҁ /A4:ҁ—$tIv惌bi}IH>)p(89ޔw 4=)=rh#!yAF8P89ϵ'8^KL~iF1@Fy/GNhQ8!'Ӳ3&yRPNJ8$pIxWhlnP8'Bqގҏ֌ьz3NhqR8sFH}iNzےi@sMJ dbRԄgץҗ ʓ$zPsϥ'(sځ=3KA>` N(֝>i^b0i})zR֎3ӚoNhx=9w'?=3zriO):åsҝ7^)GN!Sь#ԃg'ތB9z\c&΁ǥ(8q4LdQ҃_)Gc4g?*L~{Qz=x9?=r?AH3JN;u9?{/~H=C{ʗM&:>eEF)G׽;b`*^ 4(>`(=h'ր{SNOyJ;PHeϥG4/Z=MRcz?\Ч9(ΗhMIJy4c''QP擷Qir3׊=(#?RAu"hdvǽ/l4:waHzq@4dړM.x<ў)i)s.Ȥ`f3/\QFqJ@44M?J3/68FqҌ' w;E/N)SJ4xh94:ӭ'Rf)N1RRF{$Ґ$Gϥ8s4HyR9J; LsJx\go^Px&8({}O4Q@"#"J1!P(^4ZG_JQfs)0 ь4!Kz{Q9>g1@LsHOZAz}h)H{p}>Ԙ9_z3J=;Q֎ sKCȤzќ}hE(JړKsڌz3֠i=)x){w8'GVn1Ԋzi{h{QKԘJsH:uw}('֐\qך'K >cEF9Fx{2}@4}8zf;4biHRJbғC^H84zf^(qގ1A=:\SIhsG99fi2@;u4d894coz3яΏƓ~r8K'F{RgґZNqF{4=:s)O=> Ns׵:o4s>'`ZLgb(yhPGc@^89I({bIh)z!(<{vK3HI(>j/4hǯC}i3 89Z\r9Rgmri@ҎONzlQȥ =9NI掔c'j1GqKLQ$))y)sh_sAiz旃Z ҁJ^s҂9h=84v`;PNr)H9'K::\zuҌvRcPx_ʂ? 2qK߭i1N)1sK'_j@1ޔcK C@4)2sG^1KG4@'=isFZvއҐF=@)(Rxh'}A pht {PRA)H4Ҕs&9qFy((ךSMsփ׭ (&)3FjL>Px 4Z3ⓚ;sP:gƁh~==$M (9:^M&{ ^ic:Ary;9Z`u'm`PyaI֗{w9)?/4g=8т=@>ғt<4gigKzN8H;RIɣCZ0 z2h)1RŒgAOqA>c}hKڐ{vHQq{z);Qߚ? Lԧ3FZ1j1i8NҎ~t\s^n)߅P=E')Ǝ٣tȥ7P_zRpxFr(OCH))2zQRzQZQ87?.=sGh9'~JN{;RҁI4gnzRtcKt8bIiy b'SJ(_J0Fp(^iI8Pzbx Ez~4NE/j^4hS@Ҏ:Z\zRJ(29Ҍc"A 3K)F8isAcуIR掹 tE)@Ҏғ8)si ix P8h8IҌq;E/^$J8y=)q&“4쎹曂^F:IaK=Rsڎc`RrM&}^ԟ΁җ4cALP@Ҏv<֗})=(cҏŽ8gE{)1)IM֓M)9Ҏ8N)NZn3Qpzu?JNsԽz9h4mCG`Iӊi f3A==(Ezh#F=Oz@((Rz3b8qKQJBpOҌ('GqE- z2j擨Qǥ OOZ3ZOz2:^sGs&x4JO#4cN}{R 4 c (PF(<(E/nԃ~w R;ylRt1!FF(g.FA=h<ƒ;Q;c4ѓJ1A>)1=(QA@Oi9^(R@h(joA@͎px>t4wiMP:bG|40@)?ڗ#ҏ hEbsvN}A$#4dqGQQ)p@s҂zKi;QJ\4qGQG?JQzIy4:14Rq ӊ^;P34I48s֔t擡F=F=irsKuy@9tsF{cJqM֗ӥs@P p:Rێ)zQМ=?h>ƎъϵiGAhj O48;')x?)8H3=! ^4#H2xh=<:)tnsZ@ySъ1_›gҌqA<)s֌g((=i;R}&ԸハjQqK(@)9ҔcGdR_ғJ;&t!zZNFsR'NRnQ߮i}}3 \sA<;gh{iy&'сG^ !9KӜ48ރ3i g&qG $1I&⑁wnO ө94ȣ=1KIAFFh&p)x=qIҎ&tdcJ{Qt"=i?{sA֎G{P3ǵ8N98Gnh'Aך7{t$G~*I;=0q@=E}h=P8^yRF}_Ғ z~4r(#2NiAR{Q @ ^i14(PE(&02h>ʀqǽ&1)@8g{RvF(z)z}sGqJA dڃf3փӓK9@:4.sF3ɣ:R>i)TG?9AJ}q@vȥQ!ZNu4tQ'8QJQ):qAxus2ph=FZQi;iM'^t4~@{ґj21sJ8 i4c #'4GFy~g?KH1ۥ)< P1G^:qI~u8HHZ\4g)G!=x_j61JE ޜr!8H\qH29ih3@AڀIcRsI:)iΏj#s@{Rc sJsMrh ZA4MɥhIHҐth8*;R׽A֐jLu(Ai}'Az4Ҏ>EB?]phc4ߚQ޴r=)It(@h4@ w4ތ 䎔!b)1ZQ>w!.='A;RtK϶)O#׽~Tj;T)0OqF4ARE=qA>┌QמŽP !9zQsqK{cw^ԽHO?J=S"8rx8H ({ S#&1Kނ 3`zf8i0xqI>ԝx>$1A'fxg}iOjNh9Tch##Ҍ.xxqizQ< QsIJ4c^Ԙ&)i:)x=i?H8ojpF3ސt) \ R R'! p(qA=Ҝ8<~4oZ=KB@'8#v'Ni߭ RR4v 'hG4cNלRR`sH9Kh9&qjg8#ERcE)}wdsIڗb4׽.x%1ǭ.;ѻLd=8` 4c#F}hzsFyأ8t1HstGSF)9Ey&r2)pOmZ= ;QځOZ^4sGt4}(◿9v=h1A֖JbM|=h3ސp(ZG^`dցxԽsHsgU)@4x*\I{}iG#ރ׾h#A !J:th94v@TniqHy1Cj r=3G-sIޓڔLgJN;Q?Ƃ23ME&I@=IRߚ;\Rv8Z ' ޏƌ("8(>޴{Rc=)@~T/jB8/R;ΓJ\q)3F}J;{P9ӵ O.qAQ9ɧcH8IԐGJ:8IJ1q@)I h~93 *(Ix4&1Jx4_j8!KLA9"iiAɥnF1;t 94qHx)1h>JLw#4yTnqGJ_֎;u Guw)h<^i3K;R3u=1ftc9'gOf`:Q(u=))r: 9R{ўsڃ99HOZ0O揭&s׌Rgџ^wќ'sGaGAzP:qFHi1J:сҎG_Jiq!4Q9G9Ҕ'jN(^)GizwL9h'#81уё(9=:R.}9KE.~aqLP|PFxJ>/A'^fRt RGhԇ)I/'r{QA⎋i1w_ < 9S:Rp8qA<(& :y ӊ^}iI8jsH1ҜZnisN=(ҔuHx)x'SJF@4b(4wGA:ttyvx>Ԟb`‚0 :N(^uހi~:4J2'jiG9nKz68s֌ Nzu'Fhs@r3tj0A9 \vQސPϭzv)9dgL惑B?ȥg4iN1H=sGZ:}(Rq#Ҕq:rGP=sIQ۽.q@i-'r;QKv^힔ipLqEތc^&{ⓚwM;њ7R)1PMqI鎔c^Rv@tg ^{@J~Nh9G_Ag3KP }v(IHpxsF2{Qޔ`ќ@#h8jAjv} T=sI1Gցux'~~gt /44R1ȣ&1zRs߭E=)NԧړրxiG4<`Qg?guhv)[zA2)F Cڜ9&vǭ Ҏzғ9OnG4v(39.xKhqARcqGt4OZ^O8ⓧ~t('9#);qKzCG^ Aɥ$뎔Zތ^hNOIPO C@RI擧5^=iI1MN Giu=(9qJ0I(ގhzg((J:ZL>c;x4`@fi:q:f@攁i^i{уvzR 3HOϭɣ;@҃֐ҞQw"K֚z֔=hzR1A?&A8H?\!Z_J01NJ9iNq@p0hԄc8p98GOsP?*\i3ϵ-!Z")F1ҎP^ 3&9GqK=yR4'g941J94qFhi Q9i=J^Ԙ.xA<Aɣg&Ԡ֓izrZ;R``ҎюzC@?:y</AARNԼIڗ Lgޔ⓹Zv)<#Qq R:Px@JzbtiF0}qF0:sIRҌqQߧ4cґOl>ugJ\cQs@!4b)INyz=?;ryyO(M40)1Fjj\v>v& (G(##҃4mN):8oJ>01An) 99G=)OQuFN>Fhڎwɤ iG\PG) 㟭xr(ݓI(4O=);R($w(=sSiO#}iOO\Rizu{ѓF2h@'(<8KG4sH2}3GֆۃFz={Og =i;i;9=x=i{x֌ihiy4g=(R?J=#h{Pz\qLA惎(&9(QԼtu/_3SF{P}Qь)23JxG!ZS֎xK޴d}i N &ҏS4:Py4'M/_”Hx4g!яKIFy:ӊ:zPr9ⓚQ@Mu)sJM }((>1J;tCy PHQR RhZAE9ڌ)ONQ7.00hcޗ <⃓RdG\)y#Ґ1G\ւqHrzbPHsFzFrqKIJ8c$P@#Ը <8):I7Rw"җ3HO.i::c9Ai:`”ZQqGnhcP84K@=AϵRw~T`2/Rҗ'?PErhێ(uzLt!9ޗ!iMԚ80FhɠSG"ZNOZQM4Hΐzu994Δh`ut/AHM4(S7֝ށvf(':c0(@uH.hF qG| &sҗڎi=K“Azр/L=:RPN:Plbԇ=^(=z'<ќv8hPJByJ3JI1^{Ґ_JNԣ(E(vK ixɥJ;!8QZ22M8tJ @ )(hH8qG|gI44>sF(=(;R ɤ Kގԙ)=Kc#A:QzR1qIJ@ /P8(yp`fqhCphc(4)9F1\t{t֗c;t(4qғ=JyjB@4(8掦ҁI"isJ^(ۥHzQ( ;Rjh篥x N(ւ9ȥ#=9:PG(4=izџ@>c4`҃:RGOʔAu֎h>zNs@>Լq`nzGJ?J0(H}3/SIcx恞r:O8JLvZ_jh9Rペ8"?)I_aFOMN>j^֐)Nx4>IF@(z1h=hqJNhI9wlI4z\b9E(㨤cP&Hz L◠@4LdnZ849-bsHywϥƃb֓Jz{Qx٧s 44iE/n)'Ҍu3I4sRB4z 4n4F0N{ҎJJ z4zoz^)}GNyO/)4҃Kz9RZQGu'81H9J\'AzRG4G!h4(ZLzRg@S\Ҕ)2zF}iA9bJ:{')䏥wuzF? b)3KQ0:98ch=)yu⎢P:&3GKi0Kӊ\sH?J\MqHhRj(4uQHE.=v⌒x(hG<^q~TP3KRRN㎴y)r2)q9)z;PFG"zOGSԧ;L RRw#4cF8 dюM/B1ސJ 2>G^O_j49gP~z^6(I8}:R҃=p=(ߕ旷%.擶hR){ 'RA<њ^hRȣQuPGQǥɣ҃@NiG.{dfqF::҃j 3wAA23HO<҃HA8IA#4hz;>ڐsȠcץ 恞1I8ڔj;<{=ގI;R@ A@⁓FNqKR֌0(94`RbG=Qށi{f9)x'S G4whqg(4dԹ֓RdڕO^sؤ#tu)HJ )IRG9⎂ҐQAKZ^AϷ֏ʀqzLA.wsϥc&u2E.x>zbQ4\<;}9gp<4OZP8=.0(I\hS4p(8HOZ^844ғ.ŒqH8Rأ4A zP=E'|x4u8\ry|RӲ)=#n`_zLu B ^q擞=(w4AJ:I:84 3(Q: SҚN:Rh!9h֓ޗ9{ўzis)P94sGj2K <OZ3GFrF(BHZ\tAsI=@(sK@FyOJ11IʗJ{QJNd ▛Qޗq֢4s@ \g8$ fqKӵ 4?)QH: ю&;RAAF3׭!(4zb}hA@$=iN3K3H2 /|F3H@֓9A&zKE>FN:Rd`ҌsAP(zҊ:7gz 99'ҀR“֗9'I(T⎣ލ{wKAA'.zR{K4vG8ŽQztw~R8z;R Z=#ޏ‚::}(<=ގq(҃ӭ!?/NRuփvshFquypG ^J](!?(8z3hyNiO\ہ!Ty┒1IHϱ/J =h=?:RIޗ9|~TuG֗y4(=isڌA= '(HpxF})y#NPqzARqԃ(=K 44ŽGJ\`N K C(=x133JNqM.p:f{1E/.GzCRJRy:u=3 p=:h=y<.xGJ^tҔr84@NE'u&x8"ARjLQg%8.@N9?J:֗H}K93GGzG} M(yiy)KQJlRwqi4i@{擽.y9яJ>vq(p)8K#;;R{ ґړƌ=?:PN@ԇqGA8sҌ s23HyKi?j_J@>j\{QH2 jA)Ip9nzviy8Ix4G^@4;RcҌQE!'Kj=1FK8J^ (8=hj҂=su"dQ}i3Niy=i343J0 'piNi:ތr1F(FE qKR9!t9Fy1viO"ԝ){t'GLR@q@҃@'h4{@4 x.8ɥA&&3JyRҏlQ79j_qA88֎zG94R@> RA:xzf "8R&{ґ3H4AH<^iZ=1G8)8<tҌ=(9zRg2:@r) ⌊&r1Jx:Ҟ);@jSڐhARyc'=(@H}{QHR4׊NszRr-4FF9ԠwGNiGLZ;h<@y9)2{Q҃bjN){`0;Q\R~K:h4J8hGANx=)Oj9}iޔQh'=)})(;RcM/j#Q׽/Nx(iiǹ "c@8! ?R2zюŠZO|Qzɣu@@pi49Z1(ך:}~tKNA9S n(QuR)^b9'i}zT{PqQ99(=>uF2shhKRn4)P(9&^)6M/ly~4g4)88Qץ)8ȣ֔!#qI߭(4Nh<{uhZPyLs@4R8O4c.xFHONdH2 &Q/&qIi;qӿ Rh{Ҟp;R: )1KQz3J:gKۊi֜Ӳ1J8t=s@qҐ3wӭ9 юE_B:Qq4G48IӞiǽ/cI?*:JAh'<N4gqJ:P~ҌqڌtPp}&?:0^R~21i{:9'qGojSHx8 ;֗=(~Ij\{(=xɥ8~ .y (ⓧj=r=(<$F(:ޗSyN 4gzpG4/ZG :A=)GGj^8ۃF1ސR@Z_ʌ}s"1@#4p)> b9\SQڊNIJ\ gMSڐǯZ1P:u9IKϭCRg^֓,qK/&=2r.KqI~lRqI߭/nh;Ȥ$KsP:ҌfcQ҃@ҌqryHs 02(ќRK)9dx日MۑKS4pFr) 繣qף) 9iGh(& :ol:t;Q1vP= iO8F֓<(ރ@4^i9&P1t7j3Gn)(=#֐RC׊Q98Kc$hI(Rw◁Ҍ 88&q@sHGSۧZ:(⌁Fph9lQ4fir3Fh#zԣ(ւ8:wwJ;g/QH)s`f}(fF1Bu?J=4v>GojQ(zQu4dQqC@Gj8~(1AKΎ?ZQN;zi3/PhGQKAS8'j82Gy.y1)G4uƁQj1⃞h9KA8LpiztH: }Q{ь'r1IqKǦh)(җԇ8p{QPhǥzҎisR3ӊ3r)z@LsGAGnf3(:&i{ 8I0hx9sH{ѓQfi~Qޔp{b(=M9JzQ0M=OH3ރԃɥӊ;Py'q#4G8bRr2)N}( !~jZBOΗ'|gqE.A;PN:>ޔtA4gh=1\ fr(-@u┌cQ84ސaҕs!J3ϵzj٤s)BғI@JzRciG=}|Q4$z1@FGZ2:Rv1I;qI)Ǧi;ҟLE&(834q҃֎A~PFFN)4`ZsGnҞE '(QRCF{H~cN4E'JQ:h9zsI~)q42A c&p:P4>F3K'Nc^IF(^E/Oz3IDAFGҐsA>zK4xIȠur;4RqRBsK@tzHK Ncts^zRQۥ8HM?R`HO4uN)zoj):QsK(鞴R?:QAip)擜RsuQ:уJ:Iۥ/؊ 9g4r> v4>zZtc'/NcFGZ8 $NQ<ў~)ڀrsGJ_΁d()qi@ hQzA>OҞ4p(qހ}3Ax@ǥ(GAGsH8━Ґc)O4=1KRGLg4v4):K֌PhA֌j8f1F;QJhҎg4A$ցb/ځL{Tc b}i3ҁRv&p=h?CK R`huRzҎzJQj84xuRs:MRR9u^sJE&F88pqKZiރ4yHrh4rzgc qGoy>w֔9>yAGAFN(w)3FOF}O&9 cAHO.2Aցh'Z\s֓-RҌz1Q^GAIQ@FyfnI2:qNi@>JCu`KRGA=h?Ҏiq)3: 4ڌ1֗s@>J;fG4qJ{s!?P1@4cF{8At/JBv^(G=I}h^A" )4w?/)۵(ɠA'(8KڛҌdR{h֎ ;RHOj9)1ZRzKڛ))MxH=TwQ Psʗړcޓ8=E'ޏRw'9zZGQJP49H~z} _M瞢4=ZA=t8svp)G4s=0GzL^)p}hizё4Ґ.=wGz8IE u3K=M4v⎴ߝҗP\ph hi;Q#`b"h9J1(c4>zulzd4GO.yd 03A@u(KRzҊ8t'4ޔ~g&0=GlьvF3ȣhOK>4uQQFiMsc4gtқJH(֎9F2rhtS1P3׵-@zt>tSƀI fJ@BZs@/4jPz/^3Hh1KM8P9&r8!#j^gNi RsQwc8ZNOZ\8Ssi@)y=qI\rh GJN<xKRg&2iqIҎ 玔A3AڗItM'8ߊ3xPN(4v.i3KM!;Ҍ⓷=ip:h((!Oy ҅9<:PO!dT;RbLJ'ihtz擌ߚɠI>JRáqE/~“B:sGu(&~niO4Ҍ}(>4QQץFx҂94ӊ\tZ)F3 >AQF?Jq(gJy A/j;4g#4:x$JB)?KҐP'8֗֓8=xNj^ƁƐ)qricA'GO. CJ0q@z9)@"=h9iz4t>ɤLRKsGH[87˚LђH8qcFy(AA()H19)s^Rt׽#4r1qڏCP(s֌ttI<ʝ8IڌzJGaڐg8rrM.83F9x1)OLr931@njS8Q):8'S҂c=i1ɣǭRtf '$K׃ڂnt9A)qh{Rp840sJ(4):NtzQqڃ(sF?*\Hhړis:QCv(9 \ߊ^4cƀIUZ0GA_z_LPzttZ$QpAҔ v'AGs3& 'O)ځ4(vIi GJ\J/`M?Z1RAwޓ9ҁs.)ցZs\JZ_=G&9K^RB=E!㱧cJCցQIrzP9;O ڔGzF3ZJ@9@'҃(GsARڌy\f֗y;SOZ\zRQARzRmӊO)0})HQbSAlv.x" -'OƂ( :8hqF0sҔsw4ғߜRdJpG(^1LяzNڃ0:ў ߞiIR h9pb@u4cQR/~TcGZ3GNcҗҐF(Ґ9KtޗҌҎҚo;AIP0W0 i#)G?;›P84NG.}:yҌ\sH:AcIȥ(c ֌tv_қ ~4dQ@f>{Qiz w4cގ{R)@4\urh# <ڐɥh? 8(8(sA;upqG>8+hϽ3G)G9:sPOG'A)IQuZ=h'ސ 旵%/ rE!ɣ)yH=1KyJO8GCAF{Ph=G.2zz(O4qHt#);┎)ڗ~1hLKR;J0{sI܃@9 A{wMr3F9'z84i 8<i;8;r)zz(8ތg\f3*| ғzўduҐiiqqG뎴1@pJ3Hqz8qIґ)sIF9BO簣/A@1HXg|f)ؠ0i)F)8Rڌp(9=?Z6R'(ۜǥR \1Mz3֗9){`3H9ԍڗ('փ4gj8 2(zN/$b1Capz1OJ21)0Ɛ~ 7(F.;L\L)ݰy\8ҔvqJH4P9 Q\sRqq@8tҏs<K8Ҝ3҃֌s@ך1g4Qړ_ʗGNKMF)9ǶzR4gך>t4 N1ɣ߭=(jNRqA9'KcSNsw󥦂{Rh>ԽHzjCɧB(#''c4t@PA?)֐u/|qZ9&8dphE)A)TI})x' ~@8å1KގqHG٥=O4dw&ސH9jv8i{KC/oj3GqKMKGJ1F QӚ1֌QޗN=3FI׷J1Kh99 3A;旰8`֐=QQԚnhq֗}ltH8=h1K)Ncޗ)h=h< NRzQԝzRRsH=)qf')ݨ3G8ԆJAȣ4MzsփQץ4AP{P~8G9)sӟ‚Fz@{4>񦁎)rC@44m=h#ފB@FG#=GNGK>ԄF8я9q=hNǽ&3J Z9Gn9IIJq4T.;b)GKN1K h?>JOG\z13P})zfF('l握)Nh=FM.=ߚOΗ=>q@sJA#QqGюGP8Fy/'`G9.1ƌN^84! ьbʗj;QKjnN8٤<4无z8}(ʌ&94d_j=y&N=')O=i8=GJ3Iߚ8iHpisLw=zRF1֎揺E(?֓'ғ A8ǵA`hKiyN"^iǽ.F z Cϥ8h=x1ތs^PqKREB@?J\i})}98G R~A\iO1Cj^=Qp)xN21HrN)Z\h#ڂ1)OOz0=i0&擏Ɣ@<1E.z ўHKw4 AJA4qۭHyI q/sI>iGoKמdm}POJOƗb>h#/s@~`fJl&q):K"4hKRgRd瑊;R掿'Sҁg ;RsF=zQfc֐ԃӻs@9iON?:=CH@~xܚ^ހF9ȥHVSH4;fxgҞE1F3c(ǭ 0=izڌsE:qI(<Z\QgԣRt4 OǚN .p)O$`w4wIKӎ==Ki9P3^@9SNPpixzCK翥!9Bzt4PzJCA(9ⓟŽ~4sl;pqJy9zRRi0G~ qHr8 ZA\sFq#=x>iZo9sJ:cLg4փA{RF?:@@hh'i?JI$b@ 843gZ28ޔڃQ(@4c"?68'ғKrFhzwN?A{“dь8hȥ<~sڃҎǥ)M'zS#>=1N)zPzԝƃ)Rs=y#( )IKߧ4wGsڔhzRR#^RQhHIj^'1Ҋ_aFy&RcQh 0AjSҁϦi13@4u#ʓJx4('hr;c\HM\dRzR)z#) 8zKzRjN{S򞔜g9);q@K=i.1M=;u9߭I3ȣ =O\b M~=ӱ@4{N٣<8NM'C׵ x.2h"1t|( &R BO@rE&'=)zt# hF\R9_x4ԤIhsJr '^h=(@<ўsu1KInc=)3ty 4)@3Gnp(=8cG_@u4;gpzRHPps R3RvKRR HG Aϭ'@擜RNsP{֎Rǥh=E/91Aɤ ^N)qM#RJ8G4b> )s}8\KwdQ}lKg1֌qyZ0:OqҌ9/lL<^Q 8sGj;ގڌ⎇0rHǸ9.O($w|RR)ǭ&g4nZ\ځ4f҂9&3I3Kۧ<旊1ړK}HI9JtFF8qK擁ۥ'Ph-&shJ ǽ'h8g c="`z98isրK!֎Gn)1h!$ghץHҎ2(zQ4pM&iʗg3F1,P1ȣғ3AGc@(=M'9Iցקq@y8)@9g; B98A):qHzґސ)zsڏz@=zsؚ@ 3w(F(I׊8&(둊LsKӭ&?Tw 9jLdQh4s@y'={sɤ9Nb:q9Ҏ٥ ۞i;JiQ)cJAFz⌜ y@њOj\:r>u4;RAuA> Gz#RGOΐr1ҔҌz}(^ԟ4G'ʀ:R@ 9;Hz8!pGzp@ҎOaH:IGZZA@.3FG ^`8qR98($ ==}#&9q*>`"n(Fsf9'(;tPNFqA$tGLP9#Brs\f~wzR/:QGw7<ӁHj\LdGQh(ފ1ϵK}(=h'"RQIž)A8h4W9掤JN)8ǽ&y@KjLsG/9zSA2>c4N)Gi>qIsKڌ fQj*p8 dh@r( y P ␜vⓜҎGUў:u?Z\zG ю>@(EFyF}:ѐs҃Ҁ;R`= R'G48lAA4ڔZO֌~t/jFbƁZ\g44'Np9c9ӆ<ғv:RqIǥ.yRizQHz= (0{t▀=i^)1h4)qA&}?S=h RCޗgߵ!A◯G|fJC=qG$zzF (i:sKuqGlOLP9>t)8( g!8J0488Ah QЏJR)2AjP8ɠGnh1=h41A8)[4<:;ION֐M/= A3KQ48N?ʛNySn:?.J2~J99䞴sLQדK>G/('c<:P8hKރ s@NN=1Hh#sPG4dNr4c~$(izўcޗcҔ cޓs@Qh ׭.=qF8%JF@zcҔE'(Ezр)8<`d҃F:Rv44=9Kހh<җ`{Qg<5)>cQ֐J&0i~ bƗpO'#֗Z@p129Kc&1@/MP}uRc$)ǡ Rzr(KjA׭/9JA8==:~4Z3RGҟN(sF:"9Iԟ/jNz$E(?ZIJ'|RM'(zۊOni~hz^qKF 9b'hzRp(ޗi9N8Z;#`AJ Nhҁך\s+zi})J@89cNZ)aZ8zQ4#qM/F2(/""$4`1sj8`RK1֔vB(

lQqIQ4g842=hF9"'4Ҍ`Z3Ҕ)zSqIz9J/i88ɤ8 Gr>cށz^1E8.;Sx` uҀ?Z;8j:sN ֐h8:RpqAGzQz1^d{:RvKޗց ֎=)hڌ~xzgޖ=)H!҂3֓FA# 8(GaK֗n}_jRGJ11F Zv8(sJ 3P˞)@ 84y@#.;SH)6}6Rm#F0(Mӊ攎 &Rtspx#M)ԔuzAE JZ0}p(i1)qǽ!9_ZR8h^Gh׭&p)? 1ixqޏ @=$QөM/ZObiFpqI1ނ?:BisQG>8.{(gP84E&7zP=.8Rw#`zN)3c<ރPxc֎ qΎݨ^}h#{SvR㎴sB=ǽ&M P9E#< Ҏ Ґi: Aɠ֔JB={I4) ;nizьu&ޜ8=i=})qH9`dh.|v'OG84=!F9);qiN)h9@'RxA M>($J1@48K N=QhzciqIۚ\gd{ N}:ǥF9yvGz<^: C\93@14|ތ܊SԊ@Oi{&@K7j4P3ExQ9Z8'4 8iJL:NQҐth4H:24c=iN'QG_4c8Z_CK84R€8@"1AGKNg&81F=F9yKғMsOz^):RڎOZw1J9cϵ;s(ϥ/Py(0ӀN(4/ N+mZ]@L nyF"sSp3F=89qJW#›qڌ 022iqF8ICHqG#ZL;tvJE!K)=h3 3Fr}$ztoj_'”)FqG$P>sqFqJއ`sFFqIɤ9N=) $s2@G!B sK߭ ҏz9HG<1n(43$uFҏ($H8?Ҏ?Q@LJ( :Ad :Qړ#4 P2h>փIPNizRF)F!cHTPlXN#<҂)G!4{t4izwN~4M<`iq:Rr=iqGzCт4ޗZaI}KK֎z~]hz~T#Z3Rx<j1ߥ)"q֗p)4?&8j3FI'w){c*ȥz*S◜;m*qNJv3QZv)@RUȤ?vMMqڂ)*t#'9 k/481)h+M#ڃšy4t@h( wH1׵ N٣Խ@=z:w C)q8HNON(u9=1@99z?LQǽ)Rwڗz8SNsIӞԇ'֏p("iqGԚ2K΃ތ>tz:;PNxš3N':P:IJ43qF&1$yR?F:gNs4M ֓4xIO4Frq.i8=`wGz1Z9)A=4=' \=z*^hC0p(+NhQ3ތgI_ҔwK(i '8J3qց@׊^{ΌѓKۧ"jQڊw=@"v2(8~4z\ pq@LSxKP"Filѷ4=)1iJLSY984Ҹzv<): c.:sKcM` ]=igO|Qih8 N)9Sӊ^44s֐iRu&E(n< 9x9^鼌 ^pM&~qGZ:fzRNԀR!#Ըւ3I@t'4qq37Q&q@=hH~x4p#iG'$v/#(AF~QȤ,MaCzHHx42ڎAK 4cU|\yҎqڀ;QGFA␐1J=*ZLds@|h<Ғ0i{3I7c=ipz});vxQQF(<1G'KFz1ڔGJ@}s@擯?x堎:ӳ֛GJPJSt=𢁎z@#tȣuwA4 Թ@9dӲOZB2{҂hӵ?(G^9N)sӥ()N K֞r)sZPqK<ӂdPc(?Jj'#11ҚP{ i? kIS Ґǭ7pԄc'qLM# a\!L>atR>f`fтސ(qzPsw9рNII{R=Fg8NsA$/Rg;2:PqҁA'9f Qi zR4cҎ9(#'=JG w(E4sK؞uE)ɥ 'oz?=hZ^Œuh=s@JF:N٠\0GR* zҌ4dތRzS14SORcP:0zzҐ1HqjSsRqJ9(x=:ۧғihȣ)RQ(Tt9't4 ^)3})F}izqGr8@簥8JHwu4 gGJ? Lb9?֚3NHF)SGOIG.}hF)qsJ:h=x)ʗqõ8 Rӑ8.riʼc4֞~:] ԁӂ❳M Q߭ ?QEZ})◵޴cH3GzC֗1IJqdu84~hݓJđM@<g8A&\sIp:<*:K(I1F1J:qG^i9.N)>gO샊1҂q&F3Kʃ׊\x8A}sN& (8PxIt4{Rc)K1җAzA qGq֐{/ށr1F:bRu(4 掸ziN3F\J֓֗NhwAz1QF8ɥd/zQޔg(HG9F1K֌`R3җr(ހy?N^8Ԙpi=@ pNj@wH4ǵ¼)<ў4O֛: S֎w!db3HO@ G~RdRh>rRg=(P0W 'n84gu/⓶zLR󞴸#Hyccc㯽K3K>ގGLQ=h;v?Zv4KqI)(ϭ'NA4r~Z?:{qHGKc@9(c03֎:Qt7)Jdh1?^qK(f9.i]zӇZx\"5 Q>֤ ȧf H( K|&<#$t84W9ʎ) G4 d g4 c L8L֛ 4DT\Z/ӥ0I360)iJL)ԇ^R);Ⅰ(()1^PgiG/nzs2Mp4SKۑGlRҎўq(рph#ފ֗xQ4(N>P}ȧcӺzjz5 TҤ 5":~ǃ4Őj-QL?4zaM#"cM#0idg·N1SG#i1'4:N3FOZ8JIHx?/qւ:sf! p1I ҁ^i:ў;v('(<$ (ǥF3Η(.2084?8 (vhhRzsIך;ғvsF}hRwRt9iz)>nqG\PxJ9sH:Rނ?:җ)83) &sqJzJ(dgu@# RpN) /=q!RR/?{PN;Px8ztI4r:R~4#8L●ʎ<ҩIRN=Ҕi})x)9Z3hӚ^֐h9 dR=) N֐)幣bhJ;S3E:~4Azu qLsKS&P8!`NF=(=h#>Rc `R)穥H1FKvz;)N3Rb1K qz{Z94Ҍp)1gKʌ~zRs:RZ=EGN94tJ9)2yK8^iҞ8=i}()>9?&p)z PFEҌь҃H}JsLr2izr?Z sF9fH #J*En8L b8'9a'sOOlZ6Qq֙gx>ͽ#JhIj=* bUd0,@R'jf1PIznӎWQM+a A4i P9zI.9LqJ1htJp!4zQjCތHs R3Z3G&Fh1I39֗IZ;{=x Rg3@4Hqt'Cקӭ&yfSs<A#=9dw(>t控9@ǥz֎2htJLah#4z u=*)q?:NqGN}#'QKJ &pp(>$RJFF94r1IPGLRAGb;3Qϡp(ZL /^M'RN)q:Q9QGNq:RRw"x>`J()sӊL9 ֎z~֖8&f֔4 sJ9=iݺR?Zxǥ;zqOU8Ԫ9qO *PHN?_JWXP=3S"1S$~7 T Sy@*Nhڜv1KdS 5.).:S^.=0*)iDTQ\,@4GҐ.-5rGN֛fH=~4sIsM4٣g(#?ZN9r)GJNh)(ۃ;(_@ fxH)i9(^8d`Syip8o<;QZ\LIQAcFGz/(HqbhAJH1HN;b<ғGB=zT=yw'8>r;RAhɥ)=.9\'VJyZGQ4'^=(z\AzҀzGJNO4y9J1ړ:P>8ך9gI> iq֊LNh48zv:sG 3FqJi?PI=)03K:h●'!i:>.t.:֜OҟޞyZs֥E=*US"sST3jhNu*tCb4VR<ޜ#rTgڔ@Z ݝxt$p)8Fy4YTrCULxyQIcCRߵFAT'sQ5֣=zT^MJsJzQ9/ 9曁zQR<}GZ^9"~sKy.;wZҔG9@㨤 旊0ڐ(( Ҟ))v\hJR;qi0sJzh4z1ҀL@KM&9?jqԧ(13h/ZC Nc9g֐sGsF=)GNhLqJ1zq@Q8izQx v8*ޜT<4NTL؃S"STșlUTcAAS$^"ϵ?a8-;g4y;iqL.GZhZk⛎1Q czB1W c5^xpy\DBU }j"^'8FM0JaҚǏjigI!=(?wiޔ}ӑMRsL @.8#4#.)8 .98{^ԇڌ1KL`Q !Rc;QtzCJ1)y4Gw)OjN;utsҐzQI^iN}\sԝ);O~*2ަQjdǽH"P1Ҝ#( PF)9ShsKe}*2SWGSd2*-ǎS#Bri )qI=:g"j^1FLRGg"fҗ)Fs!tQ׊LsKGCAP8uRtc{Ӷ)qҗGNUR{ԀbQߵKj!Nsҭ"g[<㏞u!U ;T~Oza5"'r*@)j@RcۚU? i_.ѷޙn|Bg9Lx͝*4` Ȩ<.j^Rx9ZqU9b$1Pd/Z"QCQǵDI1Q7iN}6=΂hS1ҔSp`Iz(<ъCA8 $zюPb\K: сH8P?*Cڀ'V<{Rt?/;;zN? (9d~($cޅi)yҏƐFz7i:\IތQɣI :czNAtE'sF~ѻ@)ރOjN:4z'\`F9=zPz` zSR`sFp:R3A O`iFH4挌8֜}{f{th3Jc2sGl擁@Qތ(h8Ƞ;K ;H8ۊ?.3()z48FSE!?Z杜vNfuN85*H#JJFNVPqҬƙ#V}iLդ^G\*T^TʿHSJJpҦX刞+,}N1@bNƝɦ'8Jn2i af05"ێUcU'*$D*"xQjnEB{Tmn:yOZcvⓠSsRcOA#vKF{IMFiOi~4`RwIApiڂF~Px4ɣҎCQӵ'l\qNv>v8◭'"}izQ4c}:4(Q֌\.sߚL FphǽA^h&3KڃӮhH==3K9Iߎ$f;Rmv8ǭ%4OJ^=.8gޜ8A#v=zS\_LL@jusVb\դJ jGWcBNSR"?J֧UB8HzG󩱐0E9:<@e0xdGj!iF6 GݨTMVh<F t까t*IqPʦU%\ګ8{t}BW$GwrEDj'a֙=0݊NSH擯)Q}?'z hM(AA>wAANi=AJzF=:w?Fx4Si{j3F9ȣK Chzx9ғ8 џR)G^QG(#+{PJ:JZAAh/>i: ByJQɤ֏4$fsHs(K>? oKytÁFqPO@2)zv}.zRgs@b҂8=x&yҁK=;Q֓8iO@)0 8z*(:<ғ$~g)P19ϥ'@<)R1JQւ@qAhԘ׊^ hz P38I{PidQSHOKڎix֓n3ȥϭ84 q3SRxK~zݩå;&r}jAsRU*uS =XEjnj \NNeG_Ʀ\US zT㊚0;TsUH')Ԧ:tqdNhy,9Tm JЍ[GiN1E=0i֙֫3llޙP?FPfgT'E jcF2*msUv 5 W+ޡ`T,XsޘAi'9ϵ;zqFqEJ99wK4jOŽh$z~4gKx4~))gڌ sI:QygR֓ҎO֏Hzj^(+ӥ (|QE8}i3ցd tIM/rh=A)g(h/Z9hfu!Z>Qޗ8'QQJ:4gOQތvVAZ^:探ьf2ʦZ>j`cU`9/dV@3S*dT辢SFT 5e#8=cہKҞ$}EcFG4/5~x*1 ljPLZY A^GAEG$cXڡ9 ^HlT/Q2*qU5 9cz,zdQ7\g4cQJz9pANxsvgր;Gh 3M/Lu@)8'QqSAO4JxT@:jjsVVcE]z"5a2׊:Ո#^aTXU➨3P#9c!tp})Z;QI֗ۊ8֔c!c(&9ҁ(y`ǵ&x? ^|bA4z P8Ϸ>܎.Gw1N֜O>wn@#iz 4czJB3ҁ_Ҋڠ<҃NҌiHNE8~4zҐg;E4g<ӺRs?JE'8 Kȥw'C?,Ppf9F3֌@.9 Q⓶xׁAqGrO\R(*^Gn(>I=RgPzKڜ:c4ޤR@z@=sK"7RA9J34 i:S{`TTc5a@21jմAVQ隻ո XJ::jœG`tW9my>Pڜ0r)<6qN1 1A|ԒC'=eP\jbe5]8pҫsSzDs֢qPTljwA#{U&ME+#桗U&B@qɨq:Q"F;Rr3MJ;qH8RqIɣߊ3I{Z'@)^GZCҎHNpq@C@ސRB*iF=i?/j\H}A{Gz ')0x"I NOhv44H2hSޝkuMM)L84ߊN◚O:#-֔dsPu$Rqh$p3QzJ^;Q“u#9E$(FF;b`I=8t֔㰤|RH0:4Ooj\HFzuz:1hKҁⓂ:. qJy$QỌwJWQ;'֪yjX8\A"`zB\qT'$ !15 Nyy<26x5|Pb'Ңv8{{Sr;Td4wRpII:IhcޔrxJ҂1ȣ:RzN'^֔?o\r)zQZ3֓dьџZN:҃KM,:K!KHA=(<4/zi4;AH} :P2O~3I\zќzF&0(R>z9:P(?'gR{SORu4x)40zR`cڝR'zQh#gF1ץ/JQ)Nt@ ёz3FNi8'h(lqRZ;RԽ}(&=2zzRQGҌ)@});Rw"c4s֎QڎgI4wKMޝGsOJ\qIN(F)zI0^qHF=3N#@sNJ3NpTn"uN: Ne UCU1WPs[NqR `TYCZ VUVQu{TaNE>>H>A(e;`ӜR{3Lۭ(ތu)" h֌x ^:u,(;qރ7#qz֒ӧZ^>rO?8&9i)#ޟN^Fj`1ҥZ3Sy次(5r&q2: 5eWjd*uQSƟ50P L*/=7Lq4{Pyƒ z>ܒpi[<ydx&9HzҒ@韭'_J^{Qуn 0iO餞`KRg$ } MOŽzQrhz3ސrO8p3K2z8QCN0zg/֓8K(9bryR⁝qF)₧њ;ь1FH{tqJ:K`u9P}Kp")21Fp2)rqJ:uOJ8~8&s=hjCvA⏠hvI4djFz3sI}$gA'Qh(G|v€xgF?t;Qu=)x&Q!8'O֌h^ހ9K)pniKeG\ҩt=y=yH0x4RLՅ CVcҮBU}hFMt< w({sG=i3K/I3Nr{ {S_j Jp@'

ܚ^hn(Z>i\㱥`HVXӜJP94㸥ȦԹLpJ9iG)gQ=ACgQހNip[ړ M ;TN~*Q"P1Kޓ>тqK={r:@Թ朼 E#@3@'9 /&}3z^P}qIҎH:.sKߎ}y8(7Lt?J(#"'ڗA@8I\1#>ԽG_zC–qAP8R4v'z\њN=)x旷RsJsF 'Ӝzӆqtzpќƞ8rM.5"֤J8:\T}*tctZW!Z֮DVUntqѰ+rjd֦P jPNDNe_nh`GSQ99c QfoaH\~iLl֣`sQ<'a"i~~*'#I:%PMD[8_F+Td_ȼtn5^TXuZLH8@Q$zSޘNy61Hܑ('4擡Rii:т1Hzۭcԇӵ;44.;&pxΔ>uHx.NsIS^F01ڃJ89>9)q֌`4~\s@lg4v)jғ9ϵa.2Ԅiå7isJQ‚OOZ@vqN< ۶i/#f)3iOK:ҁ^TNE8uy=霜ԃcUxS Ӄ*tNaYM[yq6qz27"+9r:fY1ץXQS,YIx*Ep{Uadg=D|TQzӔ@ԧ) :FAPMetBS=R3PqdD=j'isPFQLqTnO'Q3ޠj7cU'5P=F A6LSOx|Ssi}8)3ғ8I})6i{phE!})8F8QޓAzQE6GI@9?ZP0h8@8ǽ-&z_4*^1A擷/AiK}i:R$bsh1@LQ;Qց9{b3Ghbq})i`PN9zPIsڔ4GZLZ9SӁI&8~J^fcߊ q)Ls֌c(83JqFIϥ!f^{Ѹc{t4{wҗ"^GjњLKyʗ׵ ϵ/QAҌPy /JN҃F@.i{G'ҊɧRA}iy4֞8RպKOn:d}*`f `uQɫIUJjUxPTqR =TS) qS=sS+ͣHpjW)@5 *HRyZ*٨# *`1UD@WA TL*'u5 wMWw`*C#j?Dr85 g=j&cF["'95yɦSO\q$яQGlv {gE9O&1sIJ83h &')?za:G38>md3!zPr:RO\Rڐpy4A À;SIҌ ^4G=A8jN)Pr0(8JCҀyGc@BhcF}@F ьR(9?OzR{Q?t #ގԹ99(~4qKۊAc4ؤ*3q\p(4qǥ.yOƗqJy'b(㩡q^=iJ^E;ЏʔdO_ZP2=R.#x=*O2LjeqXsSqV'ڭFNާ5aJOTwR,JjUja0R 5"LRG4&{y8xPnTl23jSqQpjj&j#֣`}yHWqP#$P+c#5]$5ǽ@|nqP3"wL$gBϵ1>idb:sפ?Z:PyIҌ1qA8 iZLҐǀi}0}h84cS%!$)sphG@#ZAz9( 80G9q8vjAIGPi@M"ӧJp$T{J JjU?J2Z$jʰsV_zVG/a$*R皐R+it8>w&){Q)RdӊfA|֐~aSM2iCcI^)L)h~O^* %ZUOr11F?*NaQJgךa9M'dH@IQt48F&zqK3Iފ1IKۊNOZq4rii1qځt -4 c.}:QHNF)9)y<ޓ4qIJ\gAҔ)?JBy)8:qJݟZ;Iu8:QzQ4L֛Ngir1H:ҞG^҃[ڣg5 >1Q1^܎niz6{Rv&Ґc$}zQc)Az\b{w4u:9y`ⓚNc4M7擩Kh :MJ E攎h(#֐旜R 4qւxARtɥ:QG#ZvsӚLʌ BF=i{Q3#Zt4qfq⁂x5җғ(+KԜu+hPO?J>>J^A=9Nix8ɥ4dhޗۓGFsOLu=iF֐Rǧ)RuGs_nCQҐ68 J?*>9@#(Ҏx=zRw RG_j(=F8qA{CqKA)x)9=h=cFp9'84i2qZ_I(<(|F89I;Ӆ6qLҌ@F8Iɣh=3IP3qAqH1g)GO'sE i1)z/I#qM N(N(8}}isP?Z:SzQs?Z\ S$w~AF8P(A݌v )=?:\Fr8(8i JQ4zQASڌOKۓGCKIyޢ8;N}OZ0)GQI֔>gP? :})Oi E(0hF}E'9<=GN=y׭/JHOSRcNn<3@Axb1OI0pjd}J>1z?52?XY=jtqVyS֧VaHRn9wv U4sӁQ3QZn4M2ޚz|eqZGLSp3P<MPpjoz BPB=_tu?1'1y9ov{GCc4sRJZҎ(?4Ҁ;RAsK/"c{'4^)^3Nu<с~T#J\AJGqFpq^rxHNh!ȥ#=4fT$>I= (41Hxiq(R97=ӳ9c4ziF@RN ֏hҗJ2F8ɧԜJ3׵~^tZ;RR4/HH/_\ZphsGdRޔqQI}=K`RsGSGJ\):i{sG~;Qh{K1AKK(׊_J(#Ҕ?88 S5"R+*ޥ 5 gLEN(8c@&(ZE8=}'FA`}iryhA8Ԁs֔N=(A4 1IQܚ3=(#!4 !iFphGNi-A$ t83G&z\co\S NA@9h4qI.H簤@FARqKJSqEJN\ю('= 8z =SG|0Gh遊\N)NzRr;҃ )GpҌ Q?֐^gcN=z1uJ'Z^JQ)G{PA"p);}h(ϯ@R!KKh ֔H9=!GJ2);dӇ"sN)s&=q?4{KZ@Fi͂ 4qJ8JK(^1JxoZvy4(i٥ 29:SiA9N;Rzѻ'nQ=) 8iLa?*ii9i\ iڣ2FeC)z0zc?5 Oy4z waLb;*6<1nMN/AFxv#4d⎿Zbc=i:=8ǧ4g4.9!Fryp٥t`dN)i2?t=֗)/4 ʖjCq0y?(4 ׊ZLds@JNzSW#A('8ŽԟP{vq҂Oqǵ;sG_.>9׵9)Oڜ21O?=N)ҝp> S| 8>9?s~1/A<ӄZqޗ$vS/bx{&qSKdTlEFjuRd8'I@1Ҍh@GL9'9SRH<sȣIFsڀ9$cF'm41)J֔1H9g:)xu;vH94&h(OF2i9J;J3NIzROGz=9G;:})qJMiOg=yhsғiA94~c9#'Zic3IlJpi2JsPx=!8=(:Rg8q)H9sQإ'ց@#8P3ނqhQ;;qRRh#h'ގ9)<:c4[Ns׊\zQ”{44}{RL◶i=ю8w};ѓ^;1Qpiz94K 9OnݩڜKvq(ni➭sR+c<҆=[p>w8ni Msi8ޘ< ii.N!~:LM2 })`úךfc֚ZkOFtoLSH=FxMϱJq8ҏZE"/JAsޗC8d`tRɣ<+ c'4K8f眊QHivУOOLjQAҏq'^ԄsKQHOJ\N:8t;Sџ``' /GjO(gi#hǵ֊: t4=p1N}i98dԙ9)zz^q ;uq.qjPN9҃R֜8֜A4'`})۹SӃЊ~b0&Ќ[9JLi7 ҘHRq7>O=i7OH?LbIi=~>o#'4ixǭ'N:si8" *H҃ӭ!I۟֔\P:bw7֏(IMRt>ԘKi;{ߵ3I#ԃ=){{^Ij? 1ߞiAȣ =(SJ;8 8\P ɣbN .?:AQzRd>);q_Rc4?:NsA{ҎzL◠⃒(h'4G4—= 3ґN=h4،RQ`ڏPsO@ǽ֗?h=(٤=sZBp)sgI߽();S3iqi9ipt'4O^)2qN1KysNsSNsJ)gzFNi})y)8v* x%G֜s(#gx)DӚ{ѿץr  q♚ 7x4p>njn}M'3S{M8wzPO{Qi1旿_Œ)F;F{SJn}9?jB~oJR>Jzu .GZU4d׭'@1KN 7=p)Gbx4FsA4 Jy{ҁg>أޗ'iޓF}x4w/lg<Ӻi:uiG&A~4^ǭG=);AbaGlRv.sҎJN{z^Z;ϧJ;ڠ`Ώ31Z:$}iqҁGSȠюqў8(g =x^Pzu=h$wJG\~LтP;KGץp):AP/JC1Kx4c4r(v bJNJ\d1ȥFH==x?R&CH@sKN1^:f@㌚QLQ8isZ\ёM=&q:Ҕ2*q83@R4sޗ4x.sS|4_zP"9.g҆9x!h &''҂yBxAlT4"'44M'On-ϭ4޼'LI`ޓɣqKIN)AKsPA?!zQ1h9޿AGB3K(ނ288R{Q׀i^hM.3Rgo})GE(~u=E.=)'|?ZGҐp)yӜQJ2=9<Ғ: AQ~i26P}ڗ=/>}i&sךRG&@@ɠx wIiy ;Q߭&y#z0 o9ɧMj1(4K@ lL.^ւ\A֌bqIץPAIր(.擨oN?hs@g'1Nց&Fy& Qu'zP9(4`u(dzQ_'oJ98sҔzP:Sr})h;/zQG8@M.qr)}RAG~ .~Ҍ=/$Sq@cPM\RFNրzsA<ݞz7 fNhIizSsI׷4֐ u4F8i0sAs '8 S!=xd֎gIAHr:R֔p:Ph94gRcfh=@Kxϥ'=O^ 94)2rGANhF8i3g^1E'J$sJz\CFxc(48A9yF2)q'|Ju' u(s)hԽi:.8FF=J0(IK) fr{RgJ9Gj^hǦ1Kہ 4sJ0AG@q88^($KH~E&>j\ΌdbO)?Z\whɥ=:Q)G44ddsJH^gȠR1w{~4Ν:Fzg\21GsHxK$('3IqMfi֛.3#Cs@ LdRA^)3)gۭJLqK8QN)s3Kf):F0zQc4phԼtuq֎)㖣z `R$PzP30Ӛ3F1f G|Q9u/Ngr:b q'ړj\`}4y!?ZP q9gAAʗϭ.)ҊA;Pp9!PFh0sQ@Ҏ(jNgi9b9r3Q#֗9u2('ځ=AJA!9SK@Ay rhPqN8<SRiy3H)K=(Z\c>g )=/SJ8~TcSL9A>z8Ip94t݊3ڀpq=h i3ғGZIb7iNq֓#9qjQ׵'&إ=(9#Nϭ&sJ1Ӛ8;@~lɤJxcRCA?;=)GҗzZ1'F(9'΁I:Qߊ^(E9GJNG 4Q){b>''@:(INc~Nh4c?I4 sAIҔ`G|R`=ixG`t!KҌqNƁ}<;9IҔiJ}sA#j;Q8qFp=5qP8旽& 944}4:sGRN3J__JC֗'L┌GN(T{zRR4c'u4 =:\AΔH9`RRcKni?Zsǥ:&yS1 9z\􆓷risQǦ)@&Fh)NR(֓c#>t:u'y19)W)I1ތȠt=sJ:gQ֗x9"mRuQ^h=hizJN)NE @)ǧAGsҐt擡/):ў#z?)z/C1)34ր~J Ҕ'ץ(_7z8zf8PzP9w!J23.tZBғ0(($t!(_zL:Rwǽ1G^=cGQy=iAP}{9NEQtzQx.Qڌ(ǵh1I$Ri>9`Qzhizwc֔!{ѓߊ Խ99#jS⃌ug gh97~R{HFhK(=)3HqA$R㞴wA3J͑֓=M8p9IyGhQE4dP84vm&i{z}E4=@A`iAғ$JCN0NhC:9hc<н('iÊCiZ^IKz^z cJ\}~֎h݊  2(?J]ߍ}($:`));zR)⒁4Դc3њQj_Ɣzۭʗ#E8#Ҁy&ڃG_81Ґ`ciA&)H4{@@sj@}(:QɥQu4R֔7JQ(~4zP@=izfҁt~c;c}M&v]٠df&y=({S8R :(׊CўQҐ($sH~yqK3L0:RG?FxFx8vAA(֐("&h'ގ{ќRtޗ=:t玔^)1hg7vr()3E(I8֗`PxG?K08Z3 OޑNO&~gڌ QG&9Kۭ!=iq gzQjfROJv8897#ސvi=r):sڗڂ8⏧z8 ;Qۭ3J:hގK $=)x4PZ9RNh/zOŽ \Q8GJ nNH9rO iqi3J8E&gKL@PsԪ~^hGF:ЧsJOL94wZ1i~g?J21G4(7uȥ"gSfIѷ(@"CKۚ4`⃀:s:cK֓8 o!֌硠u Ii2_”uz0y1J) =$4:_7iG4g/>/q!ѓAqLsKaHGRh=s1KJ:7#'.恁H2y!鑊UyM4gғx4c>GQ@u? _jS dnh(^&3JOьiGNh8!ȥz:Lփ@z?'ZR014==2EsF1ߊ:qڐvh=y.N9G#zP0y?'NM914QғR(@9=AiҁR[u4J=(qפ sROi1J1h @B3R(SJy4c&юzK4c/^(E.ph>I4iI9p84s.@PzF=:=`u.qIK={cjSzQ߮h {4Pz8\{K>/—'&MJ;3Iь'GK>47i^ g0 }O%sށhG@hx~Y}i3Krh" 8(3G=y4ҌAt==iq=(#)?Q4֎Ruӏ{RA44v8h$8{bzю=>g? ^PO4'HF=G LLSJI'w搞E;4={KsHy>czJ^sN AnRAnqA8@;dJ=)1Ib qGn>Œgi~ҔPpE@sR9#zw(9sފPOJLR[82y;gR:3G Qg=z \ctZLأb# ZRF1NJ\g{ўzFѓKf9KӞgtJN1F@F9GsNHE;R'bzsRQi:rzRuҐ`ӻހ=8iz#J FqHI֔g4~*Aޔzހ3:bA>'cGQJ8 A=/jOΔJ64ǽ ǡ>< '(:Pz\N^= ўyR}i):Q/҂xRw{1 ý?M)#=hڂH)8{Q(QqHpqޝ=O^)sisRgҐS^sAqI:s@R`i[:gҐ1FxќGjNv8=gӵ'/QIGzSFG !z`RE/P:dҏjB9&Œv(=>FiJPh='9Zw'< &J;{ޜN@<JwiHiB)sJ\IsK0Mڎp9:dR|RhGn~ x搌.24/4H{SJiRLqIN#=)H㎴\>fgxJwZBz:wjJN;֛hiw)2sKQs@=GNԠ{ќIA));fɥu8iqGp t 3) (9_lRp#ҐC@w4J9K@9QHx A/=}=i3ȧt)FxA>vHq /!I

@v4cAQ'fAA lOʂ?v搓c9=))@GcސќqFiFOAHx旟JA=<(ޓ'o$Ruj^)K:x44▌Ko<8})q4O4⁊0:ў($zQЌ QIqIޗiҁǽ $uy8xc4g-!'s8c G\czQs&1K( :;Py4J\Rgny7j3R4cvhfF(= tGN^?4`旐xI(ZZASFjS֚)“j14(>z:Rx4J=hPN0)qIy =}s4҃PxELw)N ='NfhOg\qҏ΂@n(sKI~t)A?8ڐ<K@3/J3GNx`!;R֛ߥ)^`҃Q >h<0})A"{N;PHQNMiGJ)^z3(Ҍ"h8I)^ԄP>ҚOޗ߽x}(8^9>`փg!iEM\Zg3KZnp('h'&y4w84h#3FyT<юzzQӭ)8fѐhv⁐s;`s94wJ2iO&=i=xHzH1Ӿ(sIdKi00hx.;3GNh(' ɧdI⎣{zPyߥړ#4: ȥ8xp94408zQg֎ B:5Gބ-t KrM;RqA'\r2?JZ:p3 R`v(9CoƓڔsўR^ޔ<2:qAl@w4`4uJ}=J4@sPN: 3C(AA.su84KxCi1;ރьiiG׊OK)qڌc:BFh˚:){Rn4 9ɣ4t84RO(4{RttҎxw94s8q> ɣ f8j4c4w}guI4v'4vI)s@'9#oj^1G8i;ё.xO4}h8N!J99sFp(>^zRu"z riXqI=#F@nirzϷ4i!E.x~tE4F( S2?J3JL}i@h)O f 4~)NJN1AqGQ(sFILnQKߧM9'U3Rz\?9O8擷_Žq)zup0{(1ҏH cH=)4{Rc'R惌w 8&ӌғIސ(4soJ:΀N1ގg8=3Pvi}h4ZLfM}E)ȢƀNI⏮8"Rq@zNvr0h Hqh8$c/K֓=KHxԧcdn4p{QF{: bc4Q `SԊLi9(;Rݨ?*>!Ɨފ@OfN3/QF1ڏփv=ґ֌ƐpiGq@8u4Ps8ǽ(<{RڌלR<=RZOJ Rs{RFh4gڂ=i:R"^N)zvzR$n@qN>n(v"AZ(?SK Pzt3RzQv()1Z_L(M8(^ih3JRuKgo⃎sF0GA/NsAJO .p(:Py: 3)Ni=y(<Ғi=zP;P34#4uu?;ьu2{Q&49oJ_n&ќQ@=)?*Lz}) Q8)@qKǭ&y)yA)ON)1qJ}iցGjO Ryh9(~t׊=I8ZAzpNh}8ޖyR)1ҊsFy)8 8iG֏J0:Tc?ENP9'4“AGjJzp3GN (Q=(9@? NdQh($FG^)~I*KۃIFpypqKurzH1KޜHi64wFAA cvAniMZ=Nh4u4:wu)r8N3ޗړ549@h=(>g4t9jP=(IJL~TcA O4:vdёKҎ Q($zN)^dt(cQQN:3ϵLɤ@Ꮷ.sAԃS A4 ttvc9Kޅ9қRzwqӥ/zL{рn(nҁHZ0h<Qh#48qGҚOS-%.8#$:qFNiqȠQ})69t riGGZhiq888iO!Jdړ)9"=is)#Nv}4uuR N旧^)3?:^ԝ>)F( Ɛ`sGC@Ҍ4QGB)O@P9ڗԀ߭ޗg\LdzRh(#PF;:LsKyړ@3Hq:tvz(sAw=iHL11;1ILKsNRc)ץ)1Q~(FGZ1/'IJ 4sJ 󞔙J:G4 PjOSRxGJ;旷=SR((=qEȤl6RFi(izbi)}GChis=)N)1Ҍ9hhAh?ҁޓ9:Ҏu4@4Fxb>FzQN(=zqF94 Ҟx搊P94 ҀN})N.88Phc"֗=9i{P2iOJAӚ^ON("03(Ry" =)s(IQӚLF84I4oLKӞ=ތsǭ?JLJS׊Aå }(sF=xd~4)q^)(AjAv?I4v 3A4gwҎ:c;R;#g4_j8qH@"N(&Ҏ 88zpzQiOJLqjR3sK23FqdG|{Q ֔}i=0ixݑ֎sIS9Fq`uM/^Ԙ#((})⏼= 4Ҕp~t=84Z;u⎇E&Ҏ9.yI$P0Gz\~)wj;ACs@B)ALR:w֗zwQP9A$S=)zHH(Ҁ F}(pi@RgB*_Ɨ8('z CK׵ӵ&NGPr)9=Zn)qx(4Mxzu<◵'z^Ɠ'8c$c=h '4q֗{Q)OJP3G?'AURrS8<p(<sGQqHM&@8€) ;`g:Z\dwɣEKG! .8 ^٤8dchz:Sh=h94iSiOjS8ڃh*NvGsAюqGz04ӊSi:?4 KޓhwhA [4}(8'|@ҏJ_y⎔zhqAnqE)8GR9{S[zRzrp ғ84ԝ{sJI;R`g >֜QGn)z) 8d8FAIqKE'K=('I$SRJ1@dtƔzSsJ1u'0xRgPO)I)ph٤<w< h'C=FFyAւŒzQh=hm\= '=}:4sHFE`R`}('SJ9&=})x _Ɛڀ;?/!$N.xFF`9rZ(ݜA'QQԹqҍ3Fr~KHsҀ)3N IzPjuҗIh GnGF i1Z cw<4$Fx稥֎1zv9A'SJ8dJ:r99>ȥL랴9*sK)2N@g8.r@NisҏnhOjzќJ3J} vJLKiGaKzѻ4guZLӳJJ@iGL99hޔ91(=h$c8ɣ(ybqAސcNs)14ZFix҃GCzv@'҃<hҎh&$Px<${QF(Ry@G)9@/F3Iێڎ sHG4cht3%◵=H/=ipq1IydwIҌguH4RM-'4֏N8w&sIKק֎0hޓ=1z_d4j38@掃Q:Qz{Rw@Ӹ'֎psI84O4?JA8E!@98}sF9KOJSIG\ Rz?wҁqFrdzR&}Ocӽ(Aڃ@40hN'J:Rs)&0M֌gAKZ !4f-)O;4NtS֓nF3ցӻb{рyp(czR2})?/QF9Iށ1:fҗqG8>!<ҔRc@izSGQE~4i 'E)}ip:ri:SiO8xAGQ R8A9jh{ISqȨpqH֎=hҁAwR?J94J~qґy{ъ?iyAi2 t.(4wȤ'=ARG|uw'zo~zќvxA)1h ~tz @s\>wh8Fi *F)G#gG\R9H9Zh'FI҂OjU=ZN=h;I;^ɣ~:!4t4JLsQ:)G|LcR IӊЃJAP9KLs׊=1A?.@=x#(~Ȥ'u@h!P8GcP8Kރ4i8F}EQނy?J1@8<^i9'Et旯Rr:^hqA<{w 94:P1 )c4h=8i8ϭN;R{)4㨥()r4h bKь8i4g)2N~GE/n)1f֎GޓҌE.0i֎i8y!w\IQ3M=)4i;R?T}( R t3(SNJx@۷ڂ@q۽8CrhIґأ8w4}h'K&sGSAv()@N(җ!nqA9Iڔu4Jx:R ֎:g4Q(.;dNi9h /hizqG_/J:L9 H9Nbz1Q#hZQ{2qG {sJ/Z2?iGJ3ϵץ#4gJ\qMGjw)3xRh^h'g"Q▁Њ1. ~T1H3KH9掂374ɤzڔ}zLn;:s8h>z PxI89hNi>pG^ϵO>vr8ڃ"QJh^iJ8Iz31KȠ=h8ӥFiMȣ:>4EtG9=( OjQߌRzzPp'"J_)~T(=zќfuqH>S <  4QRҎPM`ddb}h3ޓ?/ih9擿=Td{{I98◜P8jAҔqڀFId҃iF t: ]dHz3J:K9z`RJOAI/NE!lv9F3֌g֏Z: (c"sN7E~'|R:Q:(cю(:Z0MJ}i1Py JyR&})H⛞€sHy#篵Jj\&*j@)Gp3юiH @@4`zS4y=h q@Ҏ搁{RL:ӇL`)@zQ(>{FZM>dRc#Z^z=OisJyO4$sK1ϵs zAu 9i}@`g==T`{ъ03II┃<1J8AIZ? LR(ÊL('=h>QLR.;cޔ4PFx : 힔) J1 (yv~tghɧuF9'q4`(}( \uA(>wGoA@FFMק4===)3ԧqFGҎi83FhGnZN—9 Ip4~?%g֓Jp:N(9KR~4qjNQ”zQb)@ǡKӥ8(<.)9RKߊLsJ8IhQ@sGLW>掴=9<()O\LcQw"A)?RAOJ;(ǵҗ)9;i?^=:bqGJ2):ӭu6 hvxqPzPF{S1F)曒2 8ut8s: 4)OқߏƗ'i{zRI4~tڎ f{R`n`JR*P}h9揯4czbs/)J:tcإq4`;Pz)h'49G'/4I4G(N(9"9.xz8#=ihڗ&qGo۞(=)9=:Rr4g)s);( A:R)psLsKF8恜b)A#cEFi0=z{qKօp(ݑ4qHG>P:zޓڃ:~`4vqA9Խ~qP){cюis3q (xzsF@4ix<րF 4ǽڗ'^gHGjvi('^(Ij;FihKIԚ;Qg'NKqsڗbQ׽{bOntf|)R:Sǽ!'J3ғ})^pM&:b Z1&1AP/Ґu3pqڗ4QzQ)4`R8w9sh23cJ9GIsG|u8?ZNsj^3AJG"KOJhsAE.9GAA84w?Z9'Z(qG҂9'.@2{) {ۧ7@QzA)w>v ׭.4Orizis@(J 4f!IC֗gփJ1i0(#z^MQg=h=h;QA`/ך3׵(IG^hyJ8g4t4('' ڗgP:sJI4=sKہRZhn93`tc>Ҏ(@ dQ׵=4(^F(JCҎŒsIӂy/=G}Ҍ p{㞼X"}9)3\h&Fhϭg%ɣ=Rv9(:R;t'>'~19sFy`{fhփӊ13K:rylt=h<҃iJj" R֔@ 5Sigima-1.1.1/sigima/data/tests/laser_beam/TEM00_z_55.jpg000066400000000000000000002407711514013333200225000ustar00rootroot00000000000000JFIFC    $.' ",#(7),01444'9=82<.342 @ }!1AQa"q2#BR$3br %&'()*456789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz?ғivj\AQIv: -c(>)JA4 AFsA?JQғ4wȤ4:Ki;}is'=OGJLrhth$֗1F(4z`FIu-'֎ ;H:EȠ N2N)pqAOj &}if;FQx8ԴiG"Ri:QӚ3Q׊ 4sIΗ4gg3Pq@|Qz4vRҌIQQFxA3@E=(OcA;R ;@);:b}(ǽ9@ 'zFS֝ڐ\v)=iE Sӎ3H)O4J=i1:R :PA'(4:swGNhh8ɥi1F?JCR(hLRf&zGҁJ}ih"Rt8𣧭#z1ӚBqww`Ҟ=3Gw4{i/QFjQփAҗJ8jR2)QKE')FzPzRc")9'Q:sFyޗ(җ4F9#f▓.=F3A8((ii1=GQތ֌cތ::KE&1JFHcCzRqJ{;u&y=iF(n(4v>OLqIڎ=():ҁ'j\sE!'\`b:`8iq.2sA(9(ڎ(9ҝIiBi1@A'4{^uҎ}(#c֊A无b€=':ӥ JA^h恎h! /Z1riJ\Ȥ⃊):RьnuR1hKA<⎝F~^isA4`Qӭ'4qwdIg" 9Hp(^3HzKG~)ZQLzғGZ(U):hpiZSi{PyZSҚ/ך;1ڌq/lSih33@'RqGC\Q:pO'sJSށ֏\R}iF2IF (=hF:ўiAڐ 8c^ؤ8(=8tsFHPGsPT`4ԄtgzRRws֔ PHz}hwɣw4`fCJ8G_jB;RB8F=h8֏ӚV`ўh?9"⓶sAzQ3@;E֊8 2Gތ4i ɤ )HHCKF1 q3Kڊ:uRFGZ)9&sKRG<hiAj)}x{t4thi94qA(sI})hphfqF2}4`JғMOx##ҌGlZNARRyR Kۮ(c)듏(GNvR)xP;yQʔdRv#/ACKځN(=1/jNJ=cރaG" &GAfx;"1LR(N{A֜}#" 9җ⓿/ȨҀ2(h4wџj\9h<-ҏȣRfIRъ8ޓ8s)@^z? 1:Z^A֌d`QשKNhHsE)\RuQ=4ӱFrqKI; (J\IwH9NFRg^QE&)21ABNO/j84td^4tR)>4Fhi@<'NhMK4h>E1(=)2Oʗ߭i|ҌPzP( q֗8>(_ŒsPyh^u4sF(ϩߵ!ԿΌcރG!ds@iz>tΏnw @}E.(IKOJ0I7=9G$gR A(nh=hǭ(<=j:9҃֌GF“/NE΂()@#ғi::p Q߭(G5<(Ɛt8掴 9;_jLZ3/HyA$qKGbRSvH1A/P:PGKړ=E.@('ފC8/z^RR9)F=iyJ1GKɣӚ ֐"G8h( G4RF}H(8j8擡M=A4M8G€3ߵ/JɠrsFy!@iG94pv1FOsff&=)CQIi}hRS֎┎҂i9h' {AMGNqA=ȣbdph?:@@>A{g48HhKz(9IǥKZLsGҎކzvŒ`9&'< Lc.0IE&:sA4zP9} )qց:) 2iq4M(@xpE!IB֌!jZ3wjNsڃnc&uɤJsցI}iy8"f(0(=)ގP=FG\R#4q/AH9'=s ;I֜2:SOOzǽ>8Ecz(GҔJj;cF(yԟ/B2:A֑ hi;;@288'@҂1 Lg-&)qj9&JAP=zxqA?ҁE'>rsKxF)xJ@AȣN'9&Hc4vK)8)xځ=LizQ4di1)9Lc8=:sFqҎ1@4t<Z:ߊ8I9i9){P1\=(ϵj^Q1hR;P:Oʗ=#qAQHh8:i)Z\qRE1ގ#4uhh>wtuJ84p:QINnv4sԔ٤ގԽE=sG/Z1ր=qA(J1ihǭ'րsGh֗ڐp:sA{Q߭Gњ\zҞ)9z@4g'hh߽s/4gޓi{RgP{N?Pw LsFE/GCFh)J3&>sԚ7E`A<4sGR@Z:PGsA^(^i *Ȥ(GF2zR揠4d{)?GsցAڔtyF)>(EcǭMhG(8`sHK@4\QirOҐޖ3F((x<џ 3{Q׿4vsIQ֔dަ1֌֎襤4z:RƖL4c4;84;og(<ݱCKF3F9K@Ǡ^84xd 3/Ґ{Ҟ:cR(sЊ9T)1< 4(>i'GFs(t)撏j1'ҏU&)G#ރӥbC"◵-!J;QמԝNipqJN):Q#z;P){~{f=)Nx4(2iOj@0:RⓑҔ ".OZ 4_Zzc=iNp8 :s\8Kx{ތT8G9GPA$zRc?Z:}}(@8sA9zҎ4h# A)Gr)ғ!时7RyRc1JE'isPG9! JpⓜK)3҃KRntF{Q߭.}zRcG4SIAPOJ({h(uސNɠAg&P_J=i: Nhd4MR8g(/NiGzN3GJL)x4/Z: gP:{Pqځӥ/ғN)qGҊCJ#ސwȠQQ:SGz3@w9ȥϮ(=x@(8ւsQޓ<9s33٥(is(<֔Sx;4g\RrEКE}OҌ֊Q!Q:PH&qI}(nhsJzgCJN(FZ1IJ1E&yJ:Rg):}h4v'Όt.)sIFzF8G@=h^A 4; 3KJ3 1)=z ҃4}hRhjZRy}(;(=i3Fx8u֎uƓ)8ۚNNP)GJGёۭ )s).h}i h1IQҌIE/ i -hx4Pshސӳ'48:F{3E.hhɠuJ]`P)sIK!ȠMi{RdhMBKށFE}h<ёH:R=zQ(h qE/sIy/֌Hs;qKڎii2zbPzRg9҃Z ph'G?ZOzRȣj_֗4ޔvN:RtGZ@;{ҜwtG 9tFhh)3Ah:s@34 \G;PiOz^;׵/R:Sx&ph(⓶qE.x3G\Rސ⎀P:Ri{Ғq@&E@h ɤhwxd)NsiM3'hx3A&NRI)A)y(Iߊ"⌜F1KRҌR%.F:ьd`cҌQɣQsI܁֎w:R(E!(*;ڗ"旽?vQގu<{J恚( 1ƃZ9(zӥQ:}ix#9Iڗr)^EZv@F&8i>QJ3F1KQQAdҟր9(i21K(I@h/>8 ~{H8'4z:GzSϵ'JSڐrhLsI)z:s׽/~itvG8<ҌuJi;P1.9Jy()QAFsF8E"PjLґ'8I{Ҏ(ғҌz1G^IޗGjcGO8ff:GJ:c4c"Kʏڀ!rh(z:vQƗIڌpxjwPAHzSiޔc@QQ;@9K׭^ZN{у1;SHqF(ڃQ8u?;Fiy4w/SӊL 1AJZOÊȥGbAA1Gt 40 h\/|ך{RKۊ1֌@⃖E1F0(~^O'zF=GZ88GL_Aڃ֐ʎPzIE G֌QQqE/$oCF3KPFEQ4t5-/$RJQRuAx _ ^GjO.(:^5JGhE'4IךQCF{uqڂyȥfq'@\3ڎAPO;AusF;R}iGz7r3Jq@9fs Z_JSځќRCA1G\sQށ֏_Z1LQ֓KM'sN(Qސ==qIҗ()=n=Gc@SҐuh_zLf7J)ORz1R(}h4P@J=(<ўأ)M'^t#}h)N)s{ӇғZP94N ( PyRs֗JZ:J:})IZLA'|Ҟy#G gQhFhcփϵQMsKNiNA玔}hiz hJz^3R@isϨ'qFA=)x#'9(i@1F1/GJB\Үq N=i~)8b*L(#)C(vz3ҊN :\ʀF)Q8}MJjLRn8#u4hy K bKP# xb2{SRg ^"MIPx4gQhKIɣPx@'xr:RI)8K=>cz0sF0}3KOj39ARcQғ<GNq1Aj\)3FsG~hy4E78 w~ҟʌ@ >"~Q1G Q=3Rt;ڀ(=(8H~pxsQ4G"@ӊ9y 8G^JG8{SI1Qւ9Gց׭I/QFPhZ;r(hKNzQ){hEF}iqɥsz=(ZBN9҂:⎔1J:J\pyR)i:vGAԘ4dQ(E7 /$tۏqzR`Ǝ(>( R4Q)yMւ0 Fyp=zu=i9\ڗ(ǭ{R <`L \R`QJ)Ҏ1J:ghJ(> 4 KfP}}hҁ&=: Rb_ΓG^h1ցGҔRAGJ =#94sIʃJsF1rp(=zQ2xKA^ǥ:@=h)s'QҏCARi>QL;⃌i@4qJpE' ނ8(Ryi{r)9<KRQqKv<uz1ڗ(4^4mך^rqi}h<=4ڏSK(>|dzR4=hAs>"RRg/CGV1R9ȣNhM/|9v)3AzQސI“=Hgz;ihGj9Z;}(9ȣ5'/ZJo';{QѱHGP*>E)#mfIҗ!= .yqGJ"GM9)qIJ33Iۥ(\QRqGzSIJOQtph(=fڌ)x=:F wMRpG9}AzbRgPE)AjCڌN}E)FqI(GZ_JSN'ozph>4 ;Q( ъLr=iZ4hzRhaKbg \sIGhzLgu4t};P3@}wq@Ҏu94}s/#Z3Fp1Ҏ4O&Q׭IҊ;Q;R8␞(/@) KQP3P4@ސg>cu<#A@s(=@iG\Pph@(KގԔAE w4d҃A$Q44K4tj^AR.zQփA>h4ҁ'iڛҩ484c:Qރ>qփE{LRRszPs֓$RJqSʓԽiAIҀ3JQ4.H{:?Z=h($p? $AA9GAғc> )q4֗=pizuzGj0Ah$'zCSJ?:=sFh֌{pGRԴv4v$RPRGQH3}NzL){'^)sIހqr~q7s~Efn)q(qA8(Lzv'SKӶh@ts~ wozNNJ@r3JsG4KҌ)F1qH @84:\ Pzh4ۊnp(=1h8iɥNM4cGGQџJNiMGN )=8#@A~4fi:A#{џZ\t9HIfh=949'ۚ>s q8I(R%qGj\Iޗ1֗#4$(=( Ny<;RSL^14sKAҀq׽1M=qNINMhqH3NI9"9(4=N`I;ќ #cKCG{PzzRSqN :ƀyQ)3{R@ (Ȥ8)O?Z1H3$us =iy$I%)IF}/nކ>tI(G=$R;ю/$d9 \ғ&hph izR84QgG={Rs3.riz1 g4 z34db9qHI(#=<њ3IJ:Qю('qG'clҁ4bsIޏ.zP9h ֌PqM4L4R9Jy:ьIׁҔuG֎ÚRx >iH0)O=iH sM Qނ3Gj(9Ȥ>=t.?:=(8fKPy){}hK)Hg;R4`Rg;֐c4{@M{`cKAMԊ\юGJJQu9t4sP:֌sIQALQRKڃNc9M(9юs֎gZ:{P84tRJNOQIÓKizPMN@旯ni4m|RsI4֐qKE }(0}'ڗ(u=AȠi:RJNi}Hzi:KK۵ GAug;Gtǭ7KHzq.h=h=yRҎqJLu⎼@ߵ/qI8ǽ/SFxE9xFqҗқ}iOZȤ{Q (#?ў3L)z Lxhhސ֗vxM8MʐҁqGL9(I)WNxOJJzy< :(yn'FM=M%; =qdP!Kgրqg(cGqGt<3\Hxj^3@#=)q&RgIArhcvH 'Phg.Ny%Iҏz;⎴d :;GNgQރ^٤tc'nM(x8#04gh( њLFqG|֊;Ru1JiE!<ӳ=E z\(j sJN G4vQQӵ/C);x~֗ =֌◭!<@掟ѓZ:NCt)ynRz@@h֔{RvAh⃊7t)quftJyE RFp('ҁG9[qKx4ւyZOJ>v9v 'z9(9tv'|ӳ1I#<QցisFr8Gs@(u.E79=/^w/QIhaJN)NhE=F9iAi=h<8>i{⏯JOKFGJPF)3FzR4P94t=⃜fg>qJzR~4'ӭ/j:tJ3zOΔ9:QGN4RuKGFNytҔ:uZLM}h N3N=R"jPK>1֎ܚP=)zP|Fi}:G 4CG#'GA@9>g\'~&y旡qKH2h'=ڂ)9){sG~h{:ъAs^PZ@NrqKF!h=1E 9KsFri9Cғ$Rgڐc'sH}y&Qph''CK"}( 2qFr(=^gҏz3Rc'`Q'PɥҀ(=hh#Ҕ t2E p@q/3֗яQGj@y()hJWdc4`tRtx4L )z {y1F(98/84cҏ“R\{֎p9<ъC◵dt8RjL{y#CFۚ=xZ^3F0M'Ggӥg?QGNHO#"hfi^ɥGlR{F02hw⎃ނ8`48h`==z( RSMcE'ҔPztH@4uJG4^7nx8c3ҁIQA4vK=:RqKӽ&spE/^/Z)'ZLPy!>&sQւ4ށQiN=h>JOz1Juy&@z(z1hfZA4cvfy(.3K=hך#ރ&\ctm瞴|PҔd}(ARJLw'9.8Nz Lj^1ғ8tw"dp);I:R@HEcQ~4'N)~֗ސғ(Cq@>t҃h4֌e})O 擜RuN3ךq)1֓փK(G4})֗^z8<ތ|擩џZ ҃'9~h hzP1Auڔu`r)zVB秽9UsO1M4zЀҰ if)h :ю9/CM@Ҙ&4Fh##:ӈ_H@R8i34rsGOJBMA'_”擧Nxސ#t?4cj0qFpEFx'=(G~4vJq)x49'tJn<289㱠ь{^Iz7sڌh9Qh:qAp(;A>pM4qM/n(IiGZj(<(zQ֓>3K '4}(I)EtR}iGoj33'F/|Cӭ/4qQ);qKڎŽrKgH9K('ځ\Nԣړc#>gȥR ׊:(=qK(;{R})Tb98Pzu5'iڜ߽*:zT8G4g48eEU4`ip)vFSFr(*3I4Mg&@h#!9!:Rn)8d)#Ҝ{S}(O3ގXڌ"soJwR='vGA(F3J1=iPrhG@ϥF3hKhsޖ@0zm/iA7cCu@9sL{vԘqG(HGAG:QqJqIpiAIߥ/Gj&OJ^qIR) ^8E4v^ciHIJ999ԝiyv)N{R8zu< p;@֌b~/j9h;#>>ǵ4 woJH3\w=)~SXcgJA׽֑@@&*\'N4gw:RsGsF3׃A @9R:OZL}iri=H@f۵'Gn1F2=OH3FwȤ8OEAҐ;R{Q;9F/z9Ͻ&܎H=}() 8y#QZ\~4g(/J;QGnh܊:P:zPq} QG(RG#4cKIRu/Rg0 (Ph=8z:CJ^s@y)8$֔1:GqGNƎ:Qs֌zCA"Rh<@AAސGN'Z;ґ!Q:G>`s>ԙ4zHqK10 wv8tuׅx+/8\:*`zSU~~+/"E9"Fi~n*mLtcg#&(X}h)3ҰzT{piYx(` H49$LSE#v#)(8ɤ>^h8) d)HrsH8Rv;&qץRrh (<:gcҁ 0xh)s۵&y/֐d (:9fy&H)O ғ=@4!88(3@@ϠIA>sIFj1)G=Z8QƎ?*1NiG\J1O_J;T<(n֦T7c9OScNsR|(H :S*C͊! Q51cLU*ǁK c~ޕ5HwDgSq Q+0 H“q&F3IF;Lh8POz{)3tizH8zQh#(#=G.i3ڐtAzLt挎ƓwHGւ{ ҏzLtw4vBތZ3IK}(=QG`/\f@GN J=izRd=94Q1Gj◨dcDJ^F94bsKڌ3F8@QsN)8<^(FEiN(K٣}({QGRhQi &{P94r ʝ8z JZLT})@ :Rj9#Ҁ}h Ps(;`KJH'AJ^ڎIJ}{PZQF:sKўA>ԫqJxҨSu@R1H:z r?HˑNZ|&P@VvAۊd =;UTmRD⦎v(i3@j3gEJ8JL48gByPh`(ю;hqGZ)sIz^OzN33ҁHN?ғGJ8^:QF:hINh(/ji'<Ҕ~4fs^NAw-&z@ɥ#ю)KޏAҀj.>KHQԚ8iM/$ISIGNh&^qJ1A#=)3JqFyc>c:wΌf~48c3֓8Q{R \b^FM:xюqCԹҕA#==#LRt&CF1ɣA)g?N'|f@Z42)8 gJ#4c,J 5)^)ѥ8r9֦D0X қtXuȥS i|u=K2qHPL9ɧn^*ONds*$gY>#Za^MdI*6\c|T{~c\ғ)Қ{qL"3M=( w;Rc'R4Aghߚ0s)h9<ў1ғ8/@jSh<:{_jC׊::PH" =?\d Lf#KҎ QQPzҗ(ϭp~tuGϥ22)ri:GJJSQ1IR(HOAtqFh ' RE/Iގi7Q(K߮hǽ(M&y/@;sڗ9ҔڃڐQ'1ghi{QP1^ 8h֔iy*sW }jd? >V C׵L2xL+&b8CE/3V#q6(rTGSڥ,'zc!-ՀoN}j$LHjY6!̤>^*~MH*xW :S@@5'Pc4qHPC'5-E$6gJa_Zia^֓)ԇ;SBRN{I֎SH#4n$j1Liq^IJpޗh8ڐzPy3֚A8J;z㹠R֗Z;{sGA:ޔfyIQʎp/Z:A:gCG4v2(E)Ai ~4(ȠhۃG"{RizQӧ4gފ3Iɣ9=)Gh8P94f8!.x&h8&xF}zRw.rh&ސJsIA攓=qҀsGf23GH9RC9& &::19(>xxIԠѓQLzi{P:s@g4Q@c;'c@8(4ۑ(&x4G^*?Z=HPGqGZP}1LRA(qړdR'Aȥؚ0JCҗAr(3)=y :i; Q΃0)sH(hzGⓧJ?:RsvA= !=)ztKjN҃J?\ԭ0sGsG^)x);sJj3ARb~4N0)qJ1IO28"x(N[ޞF;S{R1IcaX;SHF:Ԑ!ڤt;p8⛂dj3qqޭ2=IhrA \GP \x9.!hGJhF3N[p#^*ARXA bJ$aAګ`;8 S\dfD TDb0)ZF\{SGOsM#48Av*CGF81NyF ;%'J;R1Eɤ'^z03):sA w{ўx􃎔q&yQw'֐g=:PO4`b Nyb@9┮cR<:Fh##ޓP}i:t8? <ҚN=dJ.i:zQ)3җI>׽- >h!/Z3fRwi2i;Ӻwڎt֧? ޴8jHxQI^d{Rӌդ\EZ)#'JsNx~a\G|㚵@ő4tyҖhn'T{q)? 6J>^@;gPNqR^1U9]3EUDifmP횂XlTf8Ui"3LxvUsv~u}1Uge֢sQ?4zl9FN)# J8licQ)SrEJW3SJD7Zl[p=*IMu+T,%1c1R_-FsK$ siޣx| DwҔ!sP(OqQ3MSA8Q95V7OZdv g p?:"Q2ҫ G"q9Uj7N*"ul8#LlgڛښFs!0yɠ{Rcz(>1I׎(1J0;tKuJpZ4'~CFhǥ'4'4gOÊ_޼/Gc@:Ax;H\wv~b{GQ3sIlv!hҝq۵Qc}h)E&)@Q)}N@qI:IPqރץ4w㎴t44Q1i@q֗chhjP8恏J3:p(#wQҁj:N#8Ҏ(J?J^3Iץ3hF8ɣ>RClQ׾)O p9ZUSsӊpҝީqR@NjfP=3ڜc^ icy\Ԗ6V;իH&qR48<դS|u5gtB>oRT- ÊrN5;8ZtKr*7o4/ _1Ҡ 6H~⡒3ҙ '35PwZU$*qQM5X9NqQ3|}isȨ1Aۡ5tj3ӥ'08)221KJ_΂8j '֔) 4 p(I\P G'sKۥ@9ȥ(TqJzp)鞾Դ=((\I GCB9.I-ʁbTNƔPx)ץ r(8#=:R1M9injQ=i>iG<Ni{ :zR@84ΔsN4$JLPiz*N├qE4lbJ=ϵKQ)p3Fq֌ڊ){RsFi;R=Q#H:/>`($gRӭ!s(4joQKbڀ?*Lh_—0)Ï˽M;vxҜNbsRJ)W;rjK~<W-ZӏWҖCOִdOVeqVam`.89*. "EXhE>H1REqC!*ph!*cbAsRx6B3Oup9PȜ4UvBO4OY=*)T5ZX*`vFwUr犮 #T$0*&#q7S4L=qM4) xG4`Rtx@=sG4=(8J;掣ҎAjBxQ֌ c23Ih8gKP(P2yc=i8JpqHO4x擽39u< oRэRgRڌץ(>(&GqKhڔ!/lf&:v;޹8gʓFxKh=wp{Rc&ց<>br:4uNixhsFFqJ})3ږ)=vQf(ICNր1SciBv&@)+N)Qrd0E,Xe869jCv5L8zRI9J8ڏ'A`gڔu4c83Hrx QRߚB} zҌRu/:P#h' 1h 3E#(qF{4}(I=izt}Խ@Ӄ. wJN)G u .9=R~4}EjP1H qPH ;玴8/<4yӨƌc/SIX4wKU8gsJzqQy֜ @9>|c` >Q֖07Ւ(Kn'֦uҮ[Õ\q޴bt@Lբѐ5%dz&B2WH\s[95bސ վ< 7ެHAM2i& rD6Uy":ҘڇgG$d T-#URxa=E@T iCi,3U#[wߞjy8bmQHҠaJENMDFj&^sQ߽3sMMޔfghzhQߥ&1=i{u)}h|G'/c֓|Q׽R㏭Gi3ϥ/ZN} ;RQ\qIӌSJ8Q'izڌCt KڒG4g cߵ.x9#3I`LFxEZ_֎qwFGFGz()x@sڎ~4摍(uJ:(p{њQ^ԀF3A`FHJO4wE;4NqA<P1F:QsҔg=sH{R4 g/ \zb sN(?QMK:Q@H1ȣڂzsFNsFKIQiOKߊNI4Ҁh=JxzRv9JzPZ\qNESI"8XUzsJCUes U9WO/֌*ՇkALzCs4E-V8O#p⦎ /Ƈ#c!@Q'w$9L٧TV&f*%a֨elsUjlm*'TRj5xx5BX0ju9W15X$N*&\*"1n9DښLnȦ Ni9擶1Gӥ/8&sQΏǚQQ֓G=( SҚyzxϽ&3Jxq4GAGS(=88ўipHh )As zK=);юjN$ft=>A):ҏCHs4g8 OlRd{H3i@8?nԃ4c⃃F;9IIiOz^tqHFO(L:ҏG8(qF1֌=}Ҏ'lRK)4WGQҔԝ99N0}:QG/8R4RiH8IҗۊZNu(yJip>1օw䎣zdyQ\eҨ4V|5]Չ"W-;3O|ZqyXN\I+A**h85+upGjP8))1-V#hMjxjIjnѸfA K,Y^zbc4٠)zKr[Aێ_dT2OJdQ`桔?-@ǚk6GZH E' Y9]0n>*j(鞵* JE׽Dba" Ȩʞj2)siwݹ}zMۓJ=):'CAz1sIip:򴠞=)Nإƀ8r}(qJZoc4( 9^h9 )G=i1F(~vh#8gҏ^nR#cNi8<恀1ɥ84.{R`.:RJQMJi($~b q@<}i3hɠt:`qJNݩ旂13J:A=is ځҚOJzt' ֮eEXaVhZ0ON*D|KN>Yny*͸#xq dJ<ʸmKY9UajH"4#;h!xMhyՓ)vji M4[)ѹqRyC/J`{T(8j9?Q.ڂR 8QΣ5ہVd `UrC"1Tj21T1$^̵yɨ DT-DTmL0iM'Z'SIKqCǽ')>w֐qɠ>()sIf^hӚ ȣ֎&h:u>—Q4ӎ)y䎔c)0i~<?4GSJ9Rd(tQ=~.{ N>(⒌K$ VqS۶ELٚzM]>݁nq~-5+ĀZgy@֣H'8$2(?Zd ҠhlR-W .q;~XҢPH4C'"#*lEG#T9Pjjæ:UyTsUU7]UST:"jQ=*&㊌u4QHr:GA)3794{r??~QޗސAI{{p8N)O^RuOK=((J:>gJC/F?J3GNc#hǹM7o4 ?Fr8(⓷Ҕ}M!4–8ɠ{ c@OEw j)I}hK;҂sI@JIj3ڏH:QG9KL bsڃGJh1&yJ1ך>r;SN{RLR~gڔr)KךN1hzRM4JzR(/^h(8S K?ZCz;ynTL 1r* D䑎$p*99:i_T~ @1TczUw9cT$EBt5Z=jm5qM:ьydPJ39@~h{x֚G(#RJ: RqM~㏥ {t9F1I488Qr);^:c4:}h)┏ZNSy֖֓?ZwaF?&xPO/l=IA~4 󞔹AI(-4sG`{P&.:LJ 'sE qҐzZ7w' M8 AK֓E!K)󣎔s@hx@'4\g(44({Niy'^3K;r*;ўhH9>>Oڟsh­3a;f<*6*H欜*x89 Z\ U/";9a=K dS0lb-!곸jy=JYd=OSB*i]wSڠۜUiWT/MUhdQT2'BSjZ"U'n2*pj w`U.׽DU4?P`zTGMFy4ÁL'M=)GnqI<0} ;{fh?{h4:cf1N3c@F)A'9֓>Gj1hށ֎<њN{Q9gI3(J}cPNJ3iyҚN('4H(o^R1GsI8);{sGZ @ uڎF~^g4g;Ɨ>{HRw^O^Tue>ZmXhozTEh*Np*;԰8SɫP1iIWÏ/:'b\'@`^yc7{Ԓ;R";Sd_J/81HA4Y?QI@#"yA! Qqޫ NUrj7%&|dpEWNFUgaUnw|sUʌA"U 9P0CQOƢ?J:XTdPNs4>gҁדGLќA4u'#P '"׽QGz=P3h8Ȥgڔgڂvҏ~(|R|QhKہHxgQ}h4FiwqGZ1@FE)ў;Q FxE&M)G4EN6@hiH8/l LQj\8=1NxIJ>I(֎Լ֎zGz:RrӺ) _Ҏi94szR)֗94Iڗ8:RFh4/F?j9}iAҗ9z8*H܎"8jh S{U'aVnف5o hSG21OdՂR~5jT*O ֬⥷$#ҭB' jؗ ʗ;bxhFizi֗GCzL^٠@>d sIޗ(j\g'. 恃ȥj3@L⎔sKڗG=(Z3A)I8Ps(h<ю/ZҌ}sKn(u=(&2'#Z3?J;s@Ijczz8I xz՛tɩp@ L9ARE٫ ҬB6RC/Ɨ&xN;Q}iqZNFqhj:QךN4h)s4v89b.8tG G-p)zvU$fIj8C/*hlnc8i@nEJ]ԑ,*vZ%<1&wsVi 3V]ߊj'&g=)c9$ uD'98P1FWPO,A,u1ڪȜj&^9U]y5 tA< HdoPRIFj $=ɃA$<jI۵W*aT}_j*DN)iސcIΌh4hҎu=)1ށOZ1@sRvǵHAj◐8&9i恜ъ(Z6q@с1AgE(csAu/jLQ8<УތrxяJ14d1="Iȥh9ghI1Psz;zҟn)2{Ӏ'CKj1E4{~ARhIQ:Hy&Z)O1@'84pNh#ߊj;Py׭&}GFi:)huQHzⓡE8^҃ڗ89E-(ƞFG^iSi~bG4?[zzY v6_ƭVmUaZPIjx-WqةclS?*50=j qfmiѧ͑Sg&1) |TA.s"I4,AS<%1Y~^j#0݌ӌ_j$p'T2IQ]{Ui5f1⠐gGPT 3 "ޫHuH*&֡v$ 8Pu74G3)c4pp}(aIр:'&\Rs:ޓ^qIh(GbQ=i;{R팚^֓fE-&9ҁK:uC3GsK{P84J2(3i{}( u4!4C(ҁ4 ;fi2}hǽ/p(=i;r)z{qފ=qϵ&qKA)?9#sKց֊RPGK(>c4i~N){br(>3B?t8f)IiyG~hQi{Ҏ)GJZpx)÷=~<H4u]3VNt#Z [*$ж$ǽi zɫ;OS'K7\eqS@~e":f-jt_M Qڤh~\'-Ox϶i<nh\,h9 [0c4)F)?jR83K:AF{Qߦ(4bQhRp3GPsюg9qFy(@94}h HiI9LsJGJ4)EzQԙҔ{:RAғ.N)94u4cJzdPxdRgJ 94=i{Q 8i”z98~"8(<cOSՁ.H9xX@80]2*h}SbSS榏#yF~\cjǵK<`S)jC?=jsYrcPK0i)i qPC&EWeҢ?ʫ9Ȩ^0*AP>sQ795Q3cE2IP<UG B{GjGʜ[P99>*ǭB=*&Q018#񦓁Ii:Q)4g4dg8fN(=3gQQNa@2irќ 4`LqF;⌜bӵc8$wN9sIҏQK4QK9a.8c҂4t)Җc4Q9)0{R ={QӵZN:P:`Ri1=h98'qڂƀrh;QcA3C(u ~u4sRw=)3K(=8@s@ E(iiqu)1ޗ4g=J9)sGg4((d \qҎhcLiF*'b1Q的8Q<= vr/'*]9͞A[u&cҢ<|TmDsSsJkuF8HI8' VD>9V ,R!nSJUpHLXMVJ1S@)F*&SWOcJ3 .=j6r9F_j6*#!'*7MDҎ*e q֫I&sUUvlPnj$jQ: 5"nH~43֘ɤ&ŒqMϵJSrhIhҔoZsJsڛsڔwRs=>yZLv(gn)Lr(94)B;8J[&:KךO`hi1:RF3A4vl@\S2 N3;RJx2HGJwS,-9%R ?9L١g/xFy`W #=iޣ8'9d*21Wsڣaҡa*7D3U?ʫ!ҫg5]5 Hzv'"2w^L{6l''dLsi~ÍOړh94vOOZCӓF}GZBi388):){g4=QH &HizZNQӌQsMǭ\4'0J:R)i`K׵784L>=(==Q֎~Gc֓#ʌQ׷4Rҁ (I)F4<ӆ(4P<493KHzҀ13֏^hQ^R1E4g:Qg旑ڔsJJp)yv9NRKT,mT۹O`㚵o#`֮mYnQ5b68).sGj@G.8u=)Rz 0:sK9Pq=(=:sJrxQ:L{wh=iE&pHz;Rwdf٥A4uihzy4,;f␎#h>8Occ8px(aQg/8Qj{u8piN֐Z:^)J'4I֔QqGF28{Rv(F9w(vz_z1z_j=v=9(sG4z)Nq)ϥ/LQA'9$cޏN/:RSJ1NR`ƜdJ=Fy֥Lj2*1jx8i_fB\qV㚰&ՅuN) SoRz=iA~P)IJh1TL}3ڣ]Li=E4ɊҀ:(yxUZPOWEBޫHx@́@sҡ~jQQ?F֣c88jCq h<4rM/CZB1KNJZ;Bq(w4v "hv4qސF`A:dғsN4t( =sKF99r(4.{w ^tRqQۑGzZ;}qG@\r}hǭ(֜:R~4qC44^r <ў)> ёΎsRFi2(\AOz^揥/!&ȥ(֎qGJ!旌bԀ^vږtSI9\MwJ@:(L|g4iԘ/<ҏsG8vHKx_Z Vg8=j9N jDC`w=<|F*T8KSS,.8OSRxB3Ry zѿހQ;DJ5g(?\Nh$bۥ&p? ?ZvAzg<@9qޗtzOZ\gޓ8ץ`jP=>88A}ixwcG#i;ьKbڎs҃ӭ(R{ѓ1^QMH(=izbOjB: 8iHw=)p8z:Qۥ'ҀAGjSҐG8G'R@(Rh P2E/;h \)=hyQQy i{iWҗK+N:R HJWϽJ⦍*&`TI튴֦*qj`{SNJ*Zr❒ 9X.qxs@r ; r)VZ 4`4˃֗Jg׊C £5sM1Q3 lrJ%8#Wp*G@5T,OQP1{Tlp*,j'7j"y1FNOSA{T@tRc9HzғOqAR`ҀOwb\ҌgI׵7o8RqzӺRGz'(n4h -hGQh3A=zsF{v#c;&pE;ђ=)F2h)c)5 a֜ SoZNI> =PsOOVI>)nM8=:Մ֤cҭoZ9}jǚ:枒Ƥs)_zP#P,3֍IsL&zà79xC!8I?Jg=s@^3P#M.3QI/*"d);?"HF1ԆST7֕eɩ<(Ni|AFi|MAqL.3iM D*@뚆L5 7TD18z 4ZaK4.pEڎOj?J8hJ1wiOJU_Ɲ})اJOWQ*dT˓S4rYyYAlޝjaOҥV.,҂r)H?ΞqM"@4.9/piyHg4pFy7n{~y<֘g9iFgD '9N]}*2r*#מ{ڣcD[MFN)?'Ln4HNsڂE!)=y4i}h)=gF3֎7')1֔p2(GLsKȦdcj>GCKM<:RQFph(8IfAќ^ԟ.'֗N)84P JRM4LQ)'9(9&xqKc$j^(J:}hqQ04O#M>`Mwj@y~TMNNix1Fr9:Ҟ)8&h({f(:RByԇ<ZnN)s@RwF})rh{S;fߚ;AKZ:ZZMރ8'#igMFhqPOJ24/QFh8FsEQKh)8Px(RR)q84zh4 :QJ1h- q֔FI')҂IƤƕxgNQ;;ғ/JN.9'(ɤ3^^Rc(4vӳv/i: N@=G=h G@4E/_JCK}(9ϵ/'c.p('z<^"O=h)=:Rh4(t4P4u"4w'旡}(J_K}E'ng4u(ɥ(ɤy9<' z ZL`{ӇRd:җiIQڗ=hyu;wq)8hS7<7~j@a n `M8jeaE<WiḧsN]q~)wt8>G4吊 >v=Oc4q@JGJAhzQގ瞔u#{RKޔqޓG$bҏG^ \ZS_Ύ۽KڐP1zSIH=ri8'ڗ }gQzQ!ɥ"KIۊKҀ/zRP:rh:isJPp2?^P:{Tb8n9ҥW ʞ>2')&{Tf:sNz}@ICNۭ80 Nݜq(8R94) S8K10\ g@8yM#HGқ=*ɃJiiߚiZ5n)x3)'903F4ΧA4wtIJ^hI^֌KQǧ4J3ߥc21)(:Ӹ=Oȥ8fNSiÃӃOsOVJpcSĸLz\8H S#ҔJwcj)x?> uA.)=8)撔``IϮ)zOZ\q@K(cьZ:u4g)R:Rg)ݨ=sHy1JAqOZLӻcbZP0ƀx٠ӇqN44r ;?O1OSZq9E<Rw{SisS98GqNN8h2摜c7dfѽM1L$0''G܃M'SYa44E4i#i!!ҐzH8恏LѐOJOQKq@~tt"$("i} L`Gcր84I9x88A9 P=!(8┎hB9qGqIޗQQ1ތ)#c4;(w<J:Z\`PxsPq4bAL 1qP9qG֗֐s֘9>KE/n )ҐGsKZ;P;ړhK/Q?z P{cޗz://s)4;sь/zm:ҁҁRcҔLSO\ьbGRu"҂)1:ъ;s g}?Z>jnpzRHsҗ8Ҕ{IKIAҎ`g9GzMҖ3^IG={4O4HyқJ0{9PHQ_S@``Q( ) PO> )O4旽=Hhߞ`Qbs'KGnh9ZZCK׊A׭/(qFGj\qHO֗ 8hzSK)qN :p֜Ji۱Jz杻z|+d*vx4u&pZ2L4F@֎>R9ws\sFsF(}GZ3qH)܎֎ ȥ&tRv=@N~4"&9?ќ ^ wdю@ ֒)@'ԽoZLR:ߚ DGirhx(tI9PAAc94 (hƐZ^(z?dMJH&y44Ss&x=}i'4ҒiqCh{{R돭/ށ֎E.s҃ӊJ=:uޗj6֓KǵFq@4t9G9?Z: =h)(M/N3KΗ=jvxJOz)TOKpb8';90hV@ozytp=h'i4"ic4>9FiFM7<`SO'Ni{PiqHH:Rng4F( ǭԙϭ A `%{zJNOz"}i3֔)34~t'KAisA hA'4q) 1\P:Rd)i3&z)sSpOZ H:R9KhH旁ɠ\ސRzGzƓIϥ3``Ҏ1)i=3K>gރҗ2y=)( C{f$`Q>(֎JN{zZ\u4phgZ94vhRJzu>FNzF};zRƌ}(<}(@挟JP?:C^szLgP){QqLgڗ|sK@AJE&xJOhr:z}xtt@KsIni{Hx# M4@Rh=h'dNp)y$QCҐOaJ:Qz!4u":S4}?*8< LcK9sF)p qA!=(4ZBʗ'1HxpizPxQ81(girs&xG~;Oz1c'Ҕt0 &x<{Fzސb)IގZ21G`Gqڊq!yӥ.})>Pr{84ɠ1H1K֊Z94}h/zOq@sG:QK(hR ԴF1K)hzj.H֎3 Kރz ֎旞i1Kߐ):\1ҏ43QQ4֏zPx8g.N) 2h$xǡNsHrNEҗ{ 1{c MΊ p(#r1C穣=Q8:zhdFsKH2ixNsFxwqM'c}^hc!gZByu?惓ҌB^RsӜQӥyG={QӊCu҂9ɣ =@>()0"zAOҐzQ{ .9>oʎR.}qGNqь:)3_ J&3x4~sJx'!sFr=(xPIA(Z;uQ)=(&){R@g/QHqP>8}iJ>r 8Rizwi='qwRN htRsM.y4QLRbi?€h}i@9Rc(i{b99I(i{s^i9=)}£瞔drh)4Kztu(d^=E/J^1 ь)GJC)sFM.ssKA4ҟjS=ix^ԙi=JA8`JO=)3NP1Qi ~ܞҎ@4;ғn{ _P4uq`ⓜbڔf(01Ґw ;֌F:t KR:3FhMRRt@PO&q֊01K?ZNGz9\?QHFqFF11C@GJ>:Q;zPHFM;dRgwLRRZL N41⌊2(sGQ@F@N8ɥ'Aڃ֗.xϵ2:Lu4qhJ(z:R@>9  ɠ=zqZhM/ZLRGz^1IG^hG&rh擟]4Pq@:Lw旚GLQ@'Ɲh .hF(<Z3€hގ(<}iEғ94sAփzGq֗#&1)G9(z |sKƎ&8.=ix?Z3GK:P{g\udg(n.hZ QҐ:Cގ{Fi 9)sfri:4g48I QߥG4fsG 1JGh)9'@&I9gџ4/Z ܊Q zsց探9Ҏ:R ހ} P:GJL~Tn9Z\84y(=4Q$}($`њ8=E)9"4Ai'Ҏ)xfRRE)=(''ҌFhIiOΊ?/S֐u/~4j7shO44dzQ֗r)J):=)Gi;pz҃(9Iⓚ3uKQۊ;RsM/=J3GC'/A3'cKQRsE҃G?Z'**Cc4R|PF(杁I/HsځKڀh>'0ʌE(P:d4掴pG_RGz:gd~4N4(ғ(J\bfњ?g~4i Rڗ?jAA<ў>Qږ\cy4qz_&8ޓۭǠ4>ulPx)0 qQێ)s3IקZ1"QZ(?֗CF==FxZCӊn)IAғz3jӁ@'iAތ&q(?iIސwE'N <\xRrx`KIg $fLIiAZN3 ~4E(={ўԦ~Q1Q߭3('@)yFFyA4I^܊NgQJ1ڌE'GAviO4w=)3J8HH (qKIizRw:QإRw4C Q:Q)֗)G^\8gh$4`uqF~ PsA4f ɣ!hZ"ti◭&0;RN8='hցzў)}gK:nh֗J SFxZNyGn)3 .8(JL))hh3A┎i1HHEQۊZCix擠(I(:ZC23IJ:f=1FFh(N)1֗tqE/sHO8@@G4A8=Rh$JJSҐsҎ8zE6$Ni4E/|v=h:zN (Nh>) JLќ\4Z:\i<=G=(SHN?;ތ9փt^(zђ(;Qɤj,PxxҜ4shgJJ:GiSxi2)siq ڎHG=(9L"@84/|q /43Oz1⓭K裚(s1-&(8K'z)##Ґ R bQ@4f wG$hJ֎ /h KHNzR4~J2sAz::RfZ1){ӱiA)g.})8'hi w4zPh砠3KG^NqG8'>gizQhcҐhړ>d("g1OzS2  u֍8.=)=h=}(uuE&iGOE3 zюxIG#Sz_AG(tփ҂) ◵IJSGOJZ1wI 'w*Qߊ3A4c֗Q):ZNs֗њ)iOCKAzϥ(1=.(H&9ǽ ǭ8Ҏx4sGnhj:3I҃E.8=(Np') qGz_~1Qڌ "ގ'9QNciHRb{}(Qj֒>J@)p3GI(~(Mt;RJ1ǥ)dR4c=84bQځRgޓKh(F=i?z}h>gG4/jNԧ8(#擥JZ0qAH9'_C@ɣfȣ9=ii=q@&0)G8Fi1A9#R8(E&(iq郎Ԙ)&14QGl&9c=(1K֓=~4c<瞔>H?)(#<~4biqLqjSv)u4iOLюR.(Z1G|׭}h&8j1Ȥ ◵!\RS~)'ǥf'-Nh>ԟJ;R^(owƂ"QbΓ9ю4M<㞝iqr zRczNE(4QNQAoZ1Z:4c֎qiA҅qѷ$RcJ\w\c7 Ki1.4sJ;ڐ4c4);J89'ڎ ҊF Ґ4OzB9yJzRbR֐:jP9ZL;ъ9ϽgI֗ѶIxA3KC׽9 6sH)~M(hҗ;aGI@1P:tLS}x 44}({sH>H3KғGN'=掴vJ:pzv03JGZ6-ьGJh<^i9iOҌsHFzRIRqI^PF(Z1(4QEJiRԘ":F2xZBҜ Q)q4`8:RAK9R9v9 xbڛzs&p(#>Ɛ•M 0)@4`ƒbҌ@M/j? @Ls֖ʏtf$F9ڎƔⓧ~ . dьڌQLGz\qGZZ@j^hh(4bzAI>R)y$tQsN4d(`ޗJ9ipp;P1R#.qCGzB(9j_dd 09s2i}(#yfGnG<H Jxh҃җh08;JR?*Q%ԸQP9B~>q޴v◜sIڗ恐sڊ֎ w28v掾Ԅ{.qGzBy&`i9Mړ0=)q6:Q'9{Rc){qяZPHsP=ALsfR҂9A#ڊ'Ҟ>q3Ҏ):~TiG<1ڎ'4 9- Ҍ$iO G=GR;у4{R:8HE(i)sߚNs(;88J^qJ}hF(#/)=P<().2)4@h=x⃚^1Iҗp(F .:sIKAGQNҐ{Rc?1z1.3H3JA4GK#Ǝ?__Žޔ >M9/ \x4!tw 0 1&2((4מgҎ!RؤGGJAzRP3IZ {vT ;dF4PsBRz^1@ IQu):}(0qIߞri3G<ގ _z3G4OzAKjCyp=i{=)iq4:⃜{Qڌ{"<4d}(Q&9A8(9{`Ҏ*1@qҌPi~1ށҐqA'h^(4h)zj^i:pIRRrNiGCIޓ#)_|Rb@8c=iqQ4v}iG(i3^F0}QH~)3Ҕs@J0i;Pz 84zRGNcdHzR(8b =y>z)rhv-&ZP9Hx4=M'IG gA`h֏zC1J9t4SHusZOz=I :q:A(Rvy/&y! ;qIQFqҌq׎t ;ftwz(MKys@Kǭ!M%;Rg^*!܊3G&Q@G9!J\(֗s;H1K4zQi9 P@Ҏg=hȠuhJ3I\ⓥ(9Q!4{K94c';9@hjQF}:rydڃQtzJ(ɣGҜt('&hF}җ ;bP~sGnhǭOZRO^1H:fjnzuiqғriOQHs48@M砠ҌJHh1Z1;(#8G9Fx}ޝh/zBH4\(# 硤go&sFxh =i9Ӟt'>&OaKZ ?OPrF):A9?J9uh (4~4F?*7R ց!IۓGa/Az?:A='@{G8ړ9ǭJOz:rht@)FsGz:POJAҎM'AA)IE.sHh g1I;RR=s=M>cQ A(Fx`Pi9Kg"?4g^3;Q 3G~g= i҂qz:AFh"u▎:Qۚ3q@G~P:u' NzQRJ3R}h.;ќHss@Py4;Kސ}(Ji"ZCs֓z2FGG J94(8N/^vԠ~TcL GKLu8>(AE/Z:RPqN @Ong^(C@/"4jQӵh@GSғJ^ԝ:1hM.{3Hz;QԄwdӲiGK8IJpyu jv1ғE ?(3KZ)Oz\q -%hс֏KRRquI֗4u 4KNOJ\NQiq:Q߭J_'J}i{RRҎZ:wZL ;Q\֊SH1;ߚ\ gތt4 R):8'/"֎{(tߎqKq 4h|ќu( qFpyqyF{:bIۭ(Fq֔>SJq1H{i{Q{@9S)Q: ZRd^;yA>}(vyF1EQ>A9#GSKғ)3Kz;▛{J(=(J8>QۥR-&y4fџZ(g1ڌcёҎiO" ^( tJx_zzӚ3Lg^P;c=M( (t >ci{c&8<:u @9&I܊Z03ϥ}J;q''N9⓭hJ2(<(ގ4;Fy0R{SH#ݨc{RcҗM?L;ddRփ{P:f 7#i{QIF??Z^zR/Aj4J8&{LwKJh8ϧҐzJHA8(ii>H )Iރځǽcz=qFy(=3@ 4$Pc@xK>KGךiPO4gڎqIqKsK;h's(>Z0=hRE&8\Pӥ&ќi=1ҔFi{fOZݤ)q@Rc= ;ޔE&9sKؚ$fM!4:ю '4٣?h c{}SNGC /N(j1G=h9Q2~t:z;Rc?6)NwF18ȣPaFzzJSN:IiqGZ3R曌RHh-&H2isIGC;zqG99qJxi9qG&}qHrfҎ?.9zCGJ (u 4i2G◌P>3=”qKIގ=sI43KzRCFp(GQ@=sJ 884&#GPh(Cri%8`QJ0hFxZN)x֓Z_z;Ri;u(4wtZLNhz^zz^xeJ3h99.F2iO=)2;=(^9c)r1OJ^(HO;ҁO8Tҗ8=E'إ9NOJS{i٣' =8K8(i3ϵ/'( H9<f@GcAFx(#Q٣9{Ph/PiG=Gri:c1GKAs@=3N3A}>)44h҃4{JN)!QdcފS'):PF:Rp2sRӚNEAiIR Ax撏&֛yAKFyN'HOJq֎)sH2OA2h9=E ) N֓#4qG>Rs ($qGlGGK4J>4u 4g LiF:bbIڎz1QFhu'zZ@◌ь'8掝9y('4wړS3ړb):z^v48N=qKIj;jZ_J=8J^GJLKց4&P:tށ9iA&9=QfQiEc1֓Gph}h=zPy==  #4r}(=hɣ4t9"jLdH}sKEQ{ќQړ)G|gҗbIRF{uGё掼Rc4`G{O4Ҍ4wdR4qA M@44:8"ҁފB)z3֌֓ԙ挊3GJ\ތԠi3ϵ/’4ҌRR}hF(A{8P⌌{8#'z2sA搎y҂E?.qӚNi}3E.(''w4g4)8Pr>ݨAFѓ@qKuLq0(#ގŽsG"(94AvQRz0h)stI=(2Eg9(4gQ3@ޔK#h4wR;MKiJ9$ҊJ(}) 挞j8~~i:RRNgE'j:({Rc4{ zRFy')&۽.)1zP3Ni3: Iߚ^ԇ4~4cOf<▓5)@qZSH(isR Hr) A@4)psAуzN3J9qF8(g#"(#4c=(>QKIQւ(Gz$8&i:~4sK=1Es4=iO#((⎆iqRQzS{;⏥ i}(փ֌ _7db{Hh)“Δ'izr(}(Ih/Ziޗ8J@sN&J9֗◜u4яz8Ldq/҃J3֗ޒh>@=zMcڔAc4t{ZRIFhtu(ޝM>j:ڊJ\zR4Ҋ;uKH}ipzARy4i')I{QGL?vKHZȢq@^@K;uKbI#GOƆ(!&=y/Rg)G4Hh(֗rhzqGӭցsGs@FyduJ840><)<\x4cA4sIM;g@IQ;P:搎(w)R4zO^Cڎ:ҊLϵёG("j_փt~p1\v(1ޓ~iyNMzR0@zQ1Q:ҁԃAR`R^ғs?Jb i@4vE'Z\h#"ڔ=h9oN'Z84}))xNzGnyJ= 7Z0Gi3qLN}@ӵ)⎟Z1<)x'Pm?ڀ;"Q)=i{qF3At:4sAqG? (G'4J0qIu94=ր8⏭'z8F&  )ϥ.r)(wGJ(4{\u" L`RAc8=!~4zPzڊLt4ѓP(Ҕ~4ǧ~P>;zP'Lbg9)?8:Q&=M4@.zd\qH)xphŒRw㱠utZOlQ(J;Q֐bNu4Aקj\RԙF;RMz8Gx@GNi8=x4-!IހqVR{POAu&zA4փ.Ni9ih4cN()X{R`яJ0}iG^bޔs'\R tAI_Ό/8)4GsEP:qFH4g.8\:84g"ǽځPG4c֌3( ր8"֓; fgJ^h?8(@Fh4v8R9qAIh(=ցF(RR@sGJEGzLc)qIQ9E.;(GAE`qJE'CG={tGQJ~Rc4qut/ @s֎wQށA=(4MҀ84g ~v(IAzwE(@=)i8JiqhIǥ.q@uI׽/M((=G~Iڊw<Ⓚ?zQHN:JA)撎zҁ~Qh4)O8Qރ4rƀFsHiEҌF;z ^@OK)?J_ZLGUMŽ)zRf{Rj=zQiG9<(ԟsF){tONJZ;йɠ#bv)}3JG'B(z?`zҜG;x8AHJs@E.9tR4$pisM҃(1A!8})G֓=G\c.{qIϥ掄R:zQדFO8ii==z3(qIʌ~TLgJ}hj:RHMRҎ/J=sIJ3ڂ&}ii:q !jPGJA )Z1 &=)zzL0)܁H 9Lҟ ~Tpҁx\RrsKފ_jo|sJzt=@IFyfhG`:ߦh}(ϧJ\{i2xvp)Z=(ϮhҌg^sӊNI$R@AQ׽dQ< i8r=ҜJjLsGC\(ړsKJ #'$ws)~@Gn3w֛RIZ;RJ;җJ1֓h@>9z_j8'aJH4Q4 zbiŠ:c(Qgph #=)r3H3ۥ/OZ9ڃɣ8gE(` 1GQ4Z֓GNc'1KHr9`Q0=Mu=("9翥&2r)ݱIߵ"sڔ4gRp; 3E(Gc4g֌i:ZJZ1!)ⓩ&0Z;NzN?TRc4g)O—9Q^1JOƔr1IiO @֔{Rt`t4O9!(ގt>ќ߽&zbJ:b84tޓ9&&~u)zGjNsGw}(恊tKҎh ph# b/'שRgGcҁi3ZLg^/JnNxuGQ:AA21KGCI)z`O4Frzyu9: sҎE/Z='!?QE.qA掴ΔSGzLG 3ތzqG9I֌҃J p)ZZz;QsM֗9ϨQJ^qhJLcԃOtcGJ:zdsH4HFG_z_z@*S tq;P}1GAҌN=iZROIAIڗsF}/nHisjCӦ)p1@'R){&{QA>)FF8g'AFiq─)gNsKғNi(#J3ҊA9(揥GA)GR)8b΃\'!^hҌSI⁚^Ը&@sh< C֌~(9? z $fRs::g"( :惒h=)9ڔQޓ/z@pqޗ= sK֐Iޗ<1G9# ctP@byc=(8cryRh#ҐsKPA.:R'I}Ah4`g3A44R?C8g wRRJSigima-1.1.1/sigima/data/tests/laser_beam/TEM00_z_60.jpg000066400000000000000000002541071514013333200224720ustar00rootroot00000000000000JFIFC    $.' ",#(7),01444'9=82<.342 @ }!1AQa"q2#BR$3br %&'()*456789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz?*LqF=x>QԚRp=ך 3A~TqGץ.F)=hG={Q qJN?8ў23BzR)sjOzQ;QߚN9❐G43\Aixaץvt?cޖ4w4`Qs!9@ץ8t ;3@rFiǓԘ9?(3ڐu=J=(^ԃ4~T)=G4vdƎ(ўhGlf_ag})zx4qA( ߯g=I8ϥ'A)$i3K<1\0@8G>sAjp~R)1J>GQӊ8J@CցҁHGAq@ PGsJzhP0Z^ƛ2)xf{Iߥ.G4u8Gyd瞔gPJ03֏9 GK۽'EJ;Q{Q (J?)F3Hx_ .r=NsJAF2zx8AօH1 //AI`?ZڀGG9Qi847;sMҎhZ;RB?ƔCҌZ1cҔgQJBE.v>r9pM F>Z)@惞tzF2₣9@'=.31 ACK=(4u@ր(,Go@F=ZNsG4G&2yK΀zsI:QRIR1MKߊNy=)1dKc#1;RўGJLK@>Ixҗ80is<ю@8< LgԸHG48z4 ҌqMǮiH{RGnM .yh&8#LZCE/~h hQ֔g>ԝ\sKڛ`?:zM 21qьRO@}s@tA(&ތ{H: A&y)ۜc4fu)zOZ1(4ӭ&;h g2(ސF8Ӱ1zCvFriI9ޔ L&sHsG<⎙)?ƗQ =(jFp)qȣ#{A}hr(wM'!x4I(4`~4!Gl 0OnzG `Rz 4v'=f >cQ@h9q֌gi8hJ\ Rm=&1ڗ{ҁOj08` ޓ 4A:KGZ3OJEQhrM!Դ Px=GZ^cK1G/qʓ0޴ҔciNьRK(=)>izҝcց``{RixHF8g1:=MbGb Rތq'Ci9)GjAE/HzNip: ^384G^){Rc)4PpAZN)x >pOqAIɥ֏zARM >cڎH<}O4uipA{N`i'NiH4c){tp(i~TxM)i?ތ?ZC;uPhzҞiFyG((AN94g#(9٥<֝})z}hIҁ-!;RF1GqIуqG^=(1GF1֌cJg/"NԤzShxGHpzJ1'lL֔Ǝ:sH ڗP*C4 Rvt=h#A)=)3)zqHxJLӭchqQZLdFq; \zZ\RqFph'RH~uёf$4=(>ҁ_LGjOCQQސ0(n9G#c .9RAM0x;~4׊:TG=(zPx4w8Z\h(^'#ގG&}E%)⃎f{~4ggjӎ1A(ڊ2)Rc9Oҗ}M4?H:ќ9CKsIxގPp@".z4`hrhJH 4cJO9у4Ps ⓾1)J1POsրj^yN >u9hhM/aL^H}A9r8#ҁ4{џAFNr(=h4'_QIҗ!=KR r3KH J=qI4g )J=M&? \֐=hA< P1jSR}irz^v<4)03h8w#'NGZA֗ZJ8Q) cOzn2)I@2iM'j^1۞)F=iz LqIޗ;i('Olҁ&zKRdf`P}(MɥMZC98viNOZNQGQCb4~xM!98Q=(u/zGI֗@8NjZLs4dgJ{cO>LҞ#&&=!tw4)}9擜)zhF28F3#(N>h{=i)q'NcR}sHiqsEtQh$Rў٠A@@1ZNiFFhǯ&4s)qNZ\Gg#Ґ⏭)>$RZ1s 4:d 3F})ZocJ?Z;sK(Rc1(>֗ޗI@vZ)1h(909 Nz\Ru<=);^g F8KcZ4 ѓ҂=<SF{сG9h:4ϵ>cJ^r94vA'iG<(8JxKъ9HzQ^)2qJ\Z;`Ҕ穤=”r3IK3҃;B:`I4Ҏ)&8J3^r=<09QZR@&I2hw&1҃ӊ3Ҏ;:):z1ҁڏZH9ޗ>c=h:Rb;P2xG'i;qJ#R#ҁ;R}:Q ; p::sN{R֓ў(4c'z0q֌PzQ 0OҏjL҃KhɠvGJ3ґ 8i31)RsQ{N? 9"ҁsHy(=y8=zҏcA)W'K 'N(R=)94jipp(\zsJNԴ&>glRcќRw(>=>ؤ<K1 ipqGQQɥǩZQȠN)ZRsHzR֓/8j9h?9R8Q? N4:Q1ҌS'|QZRq(h[ 3Jy::RgӊqjLc(v&q֗4 恟֗hԝhg.}3N~ ^G9|~lR:>zAqO/"{bpiZ:Aɠ{ҚOi{A'4<2:ܜs^IQs&9`IIߚ_lwz  vu@3izi:ހ9@ӱGqGӥ.cpڕ Ay=){Ҏ9(׭Ng4d_ c@y#E!֗z{_“c14w*B3@sϽ)z2r;QIvuiz{LuJS(#H=(1\ROqGZQ֌h(Sړ4 sGjAF1A hgK;qHG"9/cnzQތs֗""փf(=9qҌsKIڗ&M(ځҍcށc2/&:RI(9h)H&x@⎝is@Qԇ(ȣ۵'Jy9ځ:ќg4Q8{RQ ^0(1&N){MjQ֗QErh4PhG8P)qF9⒌Q׶((ފ@IKZ1׎iGh(ǭRs(Fsj^cRu)Oo҂?9F9϶): \QяZ@=(~t4`RuK0s@8G~J^qIAڗⓟJ:Py4z r)@^(ϨqKґ 23HNHҐs: :RzSj;ь ךSRc1)zPqH:Rϥ4qރF=1<4֓2i^);IIўhM/$Q֎֓SCH"GAKǭ ׭/jN@ъS(|1^(8mtڏ֗4?1ѝxhO/i3Kq֓#Ȥ4z vO47#(&H &ri~֗4QQϾ)x/AG֗'JR(#<:ҁ/Rw>cqJ2OJx.zI)@ 1Kqg zSҌR4Gj^:Q׃F0@h~Ԝ⎽bM{Rtzqt8@=iq9( ғxJp{j1(qڐ QȤ(8)O#I8)xF8(jSړPAϵc\dR`v1ҎF1ސAEҗ#J^P:yR=MРQKIpiH$9擦:8(4gBюi1֔F́Ҏ4lS)1:Q984w4&2Gj0(*I4Sɨ^h}h:Ri@i9ARi9'/!⎂M(4hK8F~j3.zNJ8gvIFiz)I8P#J:tړ񠃎{GNuΐr9iߥ(QGI=@()qڐwґ4d׭.q b٥ǭzۥ'SENhzbIsF84 )hh8G:F2~c4`t4gNzqNiiy+sAqL{קJ?ZғGS李h(Fx)OZ:M.84tޗ旿4~Fj\N}hZN4ZN@⁐~tץ'(wsߥ/jLcz:R)@⎙ m.@h#hF;u uzRdJSFޓJA@I={PGQێg'CџJ1hZ_LR}irJL) #-HsK);RqFERINz:()?4P) >qK8J~PGsAԜQzPcq Q>OsPH3(h=h4R=(Q3Ҍ;PM'jP8I ԿΌy QrsI҂@IiHN'Oj )@HqNs@Zw\7u8ZLd:0:Q?t (FE֌tc39'9с:zj ('@4shсhތdTޗi惓)ޛ.( AIZ8qI)EIh4uR9 8*0⁌p) jS@2}ޗKNGZ1@84cRc('uh'hc4= ֔ F3Ei1/OIߚP8P}F <4/08K1֌tFyI+~4pqFxt$AA\t47&y:Kۭ&9w4`cI4uڎԸ`8Q=֔9\gj6֎)(֌pxqGj:ARcҗy4C{Piz L|G43)4ɣR##RzQbF1@F1ށ=H#sKEҎc4g^:@1t#Onv8J;H}z_J9'&wу&`ьJ^j^cQ@"ӳߵ!@ qI4@ӭ h9x4ch=t.8ɤQiqJCӭH2G=E KIKR8)) )"Z=ENw#4`sGҔr(>ܚ>)cҗhMǵ$PN(;OzSRҚNҗ9:Qރ⌍֗N99}/I~tzRR\4׽'n`KNO4t(=yfҌhGbxb;qH=*!JE!ɥ 1hGZ\p3K铊Bi;u=(8:K@qJp/l~Tޔ@⛏OҎ/J0M'~is(p>q׽&34ތKғq=E{N֗8q&ӥΌG~1N9;P4sx(})xwOJOOJSNzPcJC"t`ZLqF@R֐z җMhux@(CAN<GAJ1IS9M4qRN:S֐Q 9JN`zt3'9tҐ{ \ސg$f\җ{ҏNi{␓ӎc(}ǓH?B3KjP01AKy9֌;q(ў:`dn)9MP)O_zLO4A׌ьtzLPO֏~iGiiGLRsց0i;/H ɥMLz \3AyK<h&xZLvp)FH擷n48c!0)qKRuQޔ֛◑ǽތɠzߞq߭'zqJz@{PFGZP=3O{zR&x PqI @8isFICڃ.9q^xcAFp}>rzPy9'qJ:Fy'R Ӻu<(uR3I-&)rONԝy RI('ץx99ғHiҗ擽.sړ=2xsK=i}A8w4M UHI4tKRqќ"O(AH8@旨pyAQGF('m"F) ?)8j3Iz?QCRt3֊db9JPEJQM!i= .A8ɣi>P3Ύ*3'i Gօ$zғgq{Rgސu9:Q֌GCLt4OjLӳ)3EⓧFh:I(zCh('҃Ƞ&xNzC@p?ƌHZqJ{gL{44'ғ?(h9g(z2GqFx2)A"Z^8H2jwփgi{)zRFr:RBsގ1ށLґwGBi3ڌ9U9ў4RRQp34 JNqH(9447rh.yAP{Q֌`@/Z>pGZ9'Kg=zv&<K(֌4N4gGZP@yz8:iI!hQF@RΓZ3J9'(r9A<⏽) :сQiiz'C֐wPs'lR\>('z?::sK~JN{Px>u<^(3@9fqK}iG1ސzy@t@Iۚ:y3ϰJ2qGrzFB{K&>Ɠh=?*QAў)1G“wڗ֗?%/\u4M'{Rj3Z=ސRҌb{ LB9Ҏ(sFƐ9>'h3ځqA>db֓ьרc"qڛ1ӵ(`wRP8sFsփBzRґҗ8uю(N;њ g(iCɣ/:u?N(3Kҁ֓(h(FGq4iGKsIFh9G4 4_! Q֓iǶ({)HA ҎRt'\!qKA8hlw)?*ь=Iޔ}i:t &FE/zNԿ''> hF}K}4(s.y;G$(?:P8@8<z\҂xQ_N<ь N=(ޗnMiyx4( 3=){P𣎔Rp4P{13G9#IޔuHisFx=F}E{Ni8ϭ.Ocsր9zc-旵%(<(ޗbJ^ԃ\qF=(HsQތ@JZLs@G֌t4dsHs /ҐT:<ѓړ~ʌ)O?J84{R⓯zSbqG̀h9$Qӱ{Rt斐gڀ1ӭ.r:i:w٥vGqsIߚ?_zJ1/JiL`c;ǭ'N)A4qGQ@w<((1@ .{RO! F <Sڎ/IϭK 4ԝ1E!F:Fh9sA(s@AJ zѓҁ0OG=hҀ{Px8'^)A@94g`>֗~40OGBy擣dёJ:Ԅpp(\RKtF8dpiq)1h=/^u3F9tw(9@(/S@> Aךu #)T`d`P==qG\Լ N:G4Hi?JSPq))GRߊN?*S=(90=(4 RZ◊AԀdJ\4}h =F;sGQH:4Rxd*1P:惟ʔ~hh#FrE(/ndgE {QGqAƗюƓ>g)@=>`A'ړP/s4F1ސ)H4;4!zRIדKӞ 9FOFxFM&N (^q@z9/ьKFNqF?*(!(2x^fuƒsA8ڔgzR)֓'4 3v^ԧ'z_ LҝcsKސ /4sQG^QړJ}hqR(At=sIь}:Q҆ѓ)y4z^F(zRx?*1QI}h=~IM/QH '^3s֐)M'9( Jր\ўI'@N)M&4zQКA)H4g9N$NzЧE'GAɤcN٥҃I߁JM4R3){ 8ڌqH>FEc9&)@"ޗҗx=?qN7 \ ֓=GNz(큊BM&0bi8sK @Nqڃd:Rr=)ƓրEztu9 ܊3$H4w(i:M&=ONj;Cv GuR4cڊ1(@z\9р!8=ޔw#)pihKӊL :u)AHG=)ByKF9펴Hy^Rz vGAsi#&'Ҍrh:ۮ(ށ8ԙҌG^EьvIc/!4)@ALrNsu=(hړ҂q9>`RJ\qM#i_ړci3Z^6w)O9qA('ހ1ǭ/ bQ>ԸȤ⃏Nh ֗MyKނ1B=zP:guK֎wsI:\bJ8ȥ4:}SF8{Z^iXr1F9{Q{v 48⎦dqJA#Ҏw/^/^ipq@4bPzRwyJwaIjSғRtǥ/nh@/dhqbހ84`tAsIz擓җF=9m"qH=iz9nqA>q4g@J=9㞔F Ӻz?Z^Z1ߵ42)x<=(9q֐`ҎށҁG98N"}Qh=2(`9;◽'z_GO.>ޓ1IKZwӭ&gҎjQޓqG$p(h8 8txqҐzp?*8#zяJ=9擜SցΌ94\v4RbJ3@"3ҙ)JQr0iz9ցt#IҀ}? ()1 N4}:Q9F{wbOjRsրsA4c4PG{ڎC`џ΀q1!ǭgԫAx^&9<`GNj:3߽'ZniOá)F=ihQ@K)J^b@J~:Rc :fTcF8=!'4s:PFhҎ`֎fiz@nPziJ1֌qך1:Q8xt`j1G vPxhKڎq@g4wҁyCF2}(c֌vӐqH2yҗG<<xsKi(G1H4iyjLwRRrNZ@qKA@Ə^hfޗԸq8Rץ⎣G󠎞6G9.}4{fCGQ_#`сj H.91^'ҁ}(<('H~zvJAqCRcNh4@8"Q8A8c=( ҏZ7JB(:Rz})G; ;=(={QGaKIqJ1Z\c֐t& s/^i11Sڎ)(yғ~Tuڗ A#8 8))1G|R 0 .>(&1( ъQތ{={1@!-fJv:{R@h縤zR@ \t֗1Fri8:QփN^ǥ <ڔw'izOZ:%/lA; >'QFy׵/\sG|ߥ( FzSs8JOGSQx}H84QӞj_&9篵/&~lR&iyyR}(4J\RҌdN8'4٠旦;ю9zRwz^(֗ϭ/J@}G\g Rw&2ih94 \ڍA943KIsiZBx4t;8LE.zcS4ђsڗސ!”q;RizRb8u4;Px4F}{9ZV1N)Ӕ|>=):Jy.3H9=iJP"HPzh)hn9 h=zҎ;S#o#Aӯ4^\Pz}i9!֗ڝ`~7GjA(&K֏֓:P8'ғ֓94uKsIq:PqgKLdzBIA\Ǝi9=);c9=1G^(ԃz\GJ)s)8sF~n:Ph/_jSzM9(J9Rz׭ ќ3u&hj3:Rc')1\NsKQ(?5(Ϧ(?{ڗ'Z8(ғH3_Jpҁ3AҀvHs t暣zӑxa;NӞjsGҸ.1֘qqn:ʐz40ړRq|Rw)^ynGZ3!ȠR GA&A4fzRȣhE€rh{sNޏå(nN;= (iy4ޗ '('\`ӌGjA@'֐8SIҎh$'CKPzќRgj@sA~7Gt=i:҃(<9"89hFy2z#ړ;(ڗx LҒtZ;)Z\) rBӆqқiqbuqQ*cg)e}|1ڑg҅!Ac4MA N:)=OZ(9(sM'A(G$IKgڌփ4>ӥ搓j\QI/SG4@ROns^ԇs4ރg7qAў(r(J^s֓9@0{Qir:sIKғM&x&@G_q@֎OzLFp8h)x8=iGZCF}8(QQڗ })z␌ZRy@GRg18KCIh 3ۚ: NsQ֓M;wIZ^?9Ҁ9I֔)A)zӳw S4gڊ^)4)14ǎcA挑J2Fh"sҌ' t{PG?.=;(8P=4A)W$11NsJsgR+piyT=iD|@T8⛴柌^y=ǥ5Si1HF9S RLsJHVsP8Rcfq(?/ZPxM#ړ Q}=i^QEzђ?dҜR'('|RɤM1KҐghr {QqGOphҜC}JG4q҂JNz ~4я34hdRɥ<}i ތ4w&pqF(FE&Nc huh/NR~ސ`Ҏzь)FNi94tp(Rg=zK)(9t9SxozPNh8KG!2)zE:֗&p?Ɨ&))&q2F(>tR\qH=/CG_Z x>_AGd)zR`h)1_K:=('cK:):6)wQ1J2=|җJqZO>)?iG<c"u=1<:q)G"Jqҷ=0:piFRLa)#^9ӣ i8R%x'u844_S Ta2ǭ.ޘOJuU(xEԄsG#aoN)GgҐ &8OzM/JNG=A(>Ҍt)'Aȣ9QF{P0Mg4g4玞s2hSZ\HENJg{ڊ8($/J3fIyRRiM qP9ڎqiG1@= o|$ SȠ()?q&Idgz0iq@4ߥqI&1/"t4=!cHAސ>)1ڂsIӷ␍Jf}ьz:@t(zCҔ < 9<#QB}RE"'c(GjLH~Ru LҚ1GG? N3F=(Gy:wأ4G|f )r IJJ;9)}iq9qAGZ^OjLҗ 'cgg&4qIקj\:Z37RҔg\vA9Fhhfi8@h#Q=#җ>K֎ϥ!)4gڀF:Ri)I)K3hF:P:bz\u(^OJǥ.GG4ۊ\R@sK:RsFiA㠥>ԃ8!={рy4;Qڗuq@ASS/曂NGSc^p}jG4Ln":sFӚ~ͫ`{?li,$_.iӱ=F+s)u?:Y0{R($c (=F(aE0 FyI0ތg!^zE'<ѷ^c<ԇIZ^ z!$4c99>g8:9$у׊ZBH1K R A.F8ґ4MF;RqA!@(t_jCGP8P:҃|P1=948v@z~1I3ցޗ@ɠZ^q4Q:Rv@N:RҁJB=*!izG&y4;Qђ{ }1z;wjh旷)g=4jp#Gԝh9=/&2=-'4ugڗ'S(vϵZ~"PzҞ 4JN{P9=hR!c )@ڐh9A㹥?!cŒ~NiCc֜1HcSqgJs֖1HW 8Ɯdu`=*HЅǹTA)*g_(>qN:dT)c!*}N*jyTRA#a* DF_OezTIb\rE5S$:c84p3Њ6zT{yHpIك4=)q 4q^'^1ڎi;tFzw9!2r2i:s)@=(=M PZ3ǭҚN:ҜZ֐cG=}=1֏M`ю8Iy4I1GZXs0 &:T`ba]q|^3R[ >*.be:ځKi斓4#ޔzRb|1ъB0i{PG4vz֎g/j;Z;Q#cր)4`)(#9t`JNZQ#Қs((9hO)#1Gq@qE (#^QFF8BR(x 3HFiMށޔqLz@/zP/ڂ=(#ޔsHzA鑜S09?*#15SU\Q2#R/&E2D|aPm bH}<O£p3Mjw43ץVe,*CPg'5ГLي Sq6NE0i1M#4}靰i1NOQ҂8&A'==h'<ьS{юqKLRu4=z҅ךqJLsj)sQGnzN8i0/H)HvQt8fh8iq8H—.3<:RgAQ)q@P{ =GZii{:Rft?ZJҔQ;={g&8>t=)O 81/z\Q“zRzbANG9ZQ3IьG4(m'N)G+ Rhv z(ph=h$K(4;<{R{~>fJ?@yuj1.xP>`g4tGzP3ZP}:R{Ҏԛrx1 ڜ84GtȔU\gQnqյL 8HhDŽI9#I)@:,+O ǁP?{歘wTljycE%ڙ:sSFjˉ*i1Uxڝ2qG9Q݂(d“Uo,.i3Ԋ$1QT.ÎE50xIёL?C~M!ҚHLv G"99ўiz!8481\QځڛOLNriLRwG&  :w<`PIюyhZJPshG}1PGў>.I4ڗpizPu&x gZ:G\R (9ʐ@Q׊;FO9#H(=1QGZ֒'JugA@iG&=i:( cցGC@R[)qA 1ތs׊_Ahh8@'AAh9R!^?Ύ(<4֔)xg8&.M F9G(z>tǥ=hq҃u֞c'=*@rTsSFB)OW |eҧ_\Iȫ1~@y犿*EROo)V,G <50zN LqI׊\Fx$P9/SqiFG{uA t;~4ړPrF@=(PsK}2(z8ۊ:`b䟥i2{ZB91ߊQdq&֚x4P=qG$p('?Z\(91:80h}{*Lg4w4^})iG`㡣4–&y֗HzqNǾi/^uPhZ=is)=<{hhj}AɠgԼf Fy =h*^ғ8\Z3۽(Q0(gq)#Ά qG)sF:KR\*:Nwt})OZ94Q@8E8z_nF)EJz4RM4p3KRM.1FzPM ڛQFhیQ41P}Q2)@ȣv)4?8\r߽z?(硣GP)~pz;RqGL(h|A{Q)xIځ&F1AJGi /i=iF “sKufjjP2h1K4Aނ?:җ4].(#-ޗ&=HSJ:Q)rzfd( 枠HS)a5>UM%x ]Uy椶\*ijݼ%+GZ"@ WLXMR[CM ɻax8~QLpM>Aǭ,w5ir8N`qF3ӊlHmef c5U5jłHO+sP4X0߅BcPȘ?L)sҠe$0=3n)p3&G?JCڙi;NsHz:fHE&("wJ^(搏ƌ1OIR\сKBw#'Lfts {PsFޔcF4~Tc)q@ZNGh>ؤ("CKF^ 9M}@ 84*N/~)i(4ќPF9(>)s\KIKTcއ)F8F^qށGzSR)'.F=)0qGCGj^Aҏ~qI#4>`(=h=N(</ϷJ^1LdP)1F.J1^=ӸLJs?:sڌGO=){*1cZ@99<o?Sc,*Cu_N)]pҭ¹2/=)C/:ڭZ =b\Xu̸'گ: 3R:R~La/=j r*AtǏ I3Q:ڢ)~t:Fï8inM'1H8dR 'C"Gji{Rt'C\>JR;߭擜=89tc#}=80ȣFMZ:oZ=M ҊQ4 7žG=ަmґs>V!AR~n5ڜ(1U("VsVl!9)dⴢ_Q@gZ.S[lT9SD>Nqtbq.’D,@Y9\i\_Nj 1F˓*6^ب#4On0)OZCHyGjPs֓Q^~dCcgt$Nz`SⓂ1GҔ=QQ=i=Tg (F0=i}4#JzR~4c/"O&uNf(`4h?CA<1GS\sIQG^4p81/z6hRi{qHIc)0AR.jSM (4Qө#&sփy۞ԝZ3R@x)(9rG4R2ҨZ9Nv;Y#奃TjJҁNjs԰.1W0'5fTUhd Dy .(=*I#|(vGjuJbjwnzat"aԅ~_¢UZs&3QglЃ*'OMN&M18UfQKUGUB:*UiWڢe8Ȫ? cLa5=F}ҘyݪƔ恜P3ހ9 qHy'4>c'4 $(3@tjj4rx=)qPHҔH93MqF}hzqN>P1'T@~t81) R/J@7dg4`cj_Ȩ UvӧU?ڠh5VHnŎr~YDUrGF*"Q㊍zkʙޙIǥ4i=i0;`fOZAhsM_DMpqiQ:j:C+ڪJ5B='́T!5 B5Q֙rj&Pǥ0HFޚßJa㨦>ӜRgh4&ۃ/z\fIө4dh֌'HIMɥ4FO⎔u' ACށG~{Rh):I@88=(9N((FiLhKޓ'Q84zzh$'4ALF#⡕l*[F2(Fv^u UTObryo5\qP N\ |d`Tm׿Q8=׹18ozCNzIK8$)=ɥ}E hҁ9 &9$QN:QzhHipq&0E\lўԜiOoj;{N88.xN)I='ڐt)9ݑҀќ(4KqH:֗4Qקg:)7wN@Ҕ~IPx8KNi3KEiI4Z qJ3BM.q&G4w)yuOJO|P/SH@1B {)?q_Ng0ՙˀ*Ke榕NE]ϗ(^%sKfٗҘm\Zjfȫ1ɚ8aFޔZd |=Ӟ4Q1i.1֧5!Di"B9,ɒ)яdp*&>*`2@NSd4pr*0*>Z£uv桕V`G֡gAqQ"0j})ϡ'Ml֣#֑M>ShI)=' 4u>gƌRG4)w9MݓF:7sS֐SI?yրO4tQIzZAGZCG;R9K=)sg”Aӭ1M{qqIN$R(B"KzyFsҎ Kc4ӚOz^J ^nyH0))q<*9)S 4`NuX_Q{ն'cOLGҭ'ҝ~cֵӵ63{fO݊zyJI⓵&43N v<L҃I=GJ:AaGZ:O4Z8#rh8dֆŽ8ޗRCJ: ^1H(>ԇҗ(JQGOJ:sHOgpG8 RqF8Jy=ii\g4uҌzLKۧ4R:sޝ!sQGsG$#ܚRyF3ޔLR3'q 旵cAJ:s;ҏ&s.GQz8Ͻ/~Mӈ ;Sa@\b=$ ֝[U~R@|U3S9!F>Nic]լ@sRZ*vSR[jrzP 5o` (?|/J|>u4QƓ$vuyc&OAKhj?4ZA|cPT29VA*y=$uYמ1P8|=j6^*ZM<ZNI›ގ擓 4GZN٣R֗?nI({ќv 0p})21ڂ3֗m&0q M iFyF2(9Z;R'ҌR})3RFsڕx}8Z^4b5?ZB3'}z=M ◽'Aɥh(4d(3@z1RwR'?:r('ڊ=Fp)Gu ⁒yiݳG֌?i&qG'^ƐM 玔w/^ҐKGl;sn U/Czԃ<(=ϽX|҄񊷰l"e=3ެڮ1R1%ig>"Vz1ԐNNJlr*Ln3tk~R@jyO Ӛ,>f4jʰbdS#5,qIbTM=GˎjjK)dHxF7vFj?Xjxaڠqz T ;n5U>Uձҫ895 ,j65  mӚp7#ޚL=h!ڃHǑGnhw<7$S}zPsHJ?L1@4ҌA=s@K3@CMӸ:P8׵cޏP:r=:J1is;cPlA?~)rcA)9)Fz36LsRsAރҌF(G#җN(s^8:Ҝߍ9sRzߵ9=95"ΞyaHq-&8vdsV׭I2pt_hj[+NvO"SA4wZ"1WBv3R9"n nԊ~LT[~nH:M?B=?JdDq3PVlup0* ɨd^; ?ZL~5 P'@OZ*UlY#&$Կ9z;qHzQۚPhǭ'ڗAc4c/<@{i9) ֔`1;Qޗ{Qӵ.})ps 9;F@=Ď)x=AiW5!i/R2֬F0ҪJnwzի?ާb|Z6"NZzԶO;0<\TsV|o5o.*HSjf@GJZR7Jcf1 NьSbE8ȥ1H-Ҟ ?FwHJ;T)&(=%av`fXi)< M7/֌ŒBHxqF;(⎴M/8v9 ;!gޗ"z9Q@g@hۊA}>ԽGHV=Qv)0OLRh=hdRjq4*NH)zN:bx)F9sюwҐ{^xNG>sIpiΓ4(H)zQץ RQ8QKjBO3Kׯ.>O<(rsAGsR)P幩zjH^&f06fU\8WY8bN}v2t+u?dutD7N*zJz|9m3֬AZq񚶃*=hP7jrnZj! r&)FzbIjWȤ9@"L#c. dOZ"qϸY8Oz>^UꬫT֫H9j P:㊁Z>zqQ>j#דLnFzch4zCy N9Hy@y3Iy4QQG9 RItNi?JQ9'AIAO:C(O!sN}3ڔczt(1F09тE'z8KFGF9⎙q֚1SI֔w)s8{t=i2h=)I2(S۽bG=ui9N8&sIҔv QAbR=)zhzRt:)?ɥ&n3KqH3-/4AiN:R8:}(ўhf?AF2 H09ϭ=M/c'C֗ v#P8u):stc"߭=y^sRBƦ?J#9mS=~Z*3Ү[vY2Vyt?"NSՆ\!L8ոB w>sY81=)]G=N)\N@I֤f9E#M8t$₣mDқ*} ^DFW:b`EV\Ur9]Psޣfϵ@֣b1z+sW?7J#69W3UsȨXJGBɨD}9TD0S=Ni(3M#<ޚNyNhzҜL`u h':N K)!'8Ӛ>֓x# 9@8␚JQ0iN␜ڌAsK4`bsJCB4w<qJFE!F1u'!w0{PzсKRgS!3ڔ{uғ\gp(('Ҁ}KgҗAJ1^uIޗӊZLcJM'4JQތj /QҐb'~vGR){qH9/C03&3('.(pyA=i@P}1I>qAjiOSG@E)=) qȥn1B R8ԥ:Au]㚒َlqڮ8SZpbԱ6_$ M&$*#V})2 B9*v\TЮ8&" !*d艆pRHHtnqnD57^i TJnO6V8sPzݪTN85Y> 櫰Uߎ1P0PH3*P7=9qҪJx7=8pzTj'<'EDTL2s6 iӞÁf SzLqNJ89'uIix8'.OQ;Rv:R#J9.9Rg)Rc;ҌF9Eޏ֐zf!H)x&FҞ1KJJN)rq@ x 4RLx8RjQsҎg8KΒqr:)IQǽ&0iN >RhznqI^Z 8i;֐x>mjLdhn~ʗ=Z1sGAR>)Gc=h&)r:wZ8ʎsҎhwgiN3ixiJہRRC ҥF3֟}_s|dyqS9 j>Zhf޴`SR*8XpiNWTpSUJ3VKeyS[͌c,7մar>p_V = $hs#8ArƞMoR&*d@ dPc9'5H,}* KqߧZ֣bYB̓P9U%=MWlzIWp>^J=*5F5wQQsқ)RyN1INԙKړǭ6?.1֚'qA8r81&N:sKQڌ4}E7Qӵ 4΁Ǝ:S{E.yR <&z1sւSGA4G?'Nv(KRpxt;"F(ϭ&{ׁߵqP(׊9K(49c4GPaKGSGSF='|fAgZFI(t Qs@ϭ;'j:iqc\iǥ(9֔iR |CjB9ԙs\c>ԽzvqڐOLiqwsҖA#ю(/Ҏ'94ӲqRR`u H擿)4cJH@Ҕs):F;(P3FqIǵ(cFr٧p1ސHۚPx)|ӭ?<оR'\y*H) A b䚵9 #5iUrJ sZQ1 4j?/\зSV"#zԁzմaZtdnk9RF}r{wbWypQS;@%N@tCM|+asTel\Gc4 C#Z NT,<95^Lg֡aT/JPH#?Tu#&ɐzy8\V\qUz$cj'9*6lq4~ȦhM'qt}hϭRtqў(NzRt3N I#RG튔uѾ^NC[ R֭õY{g0_|RD1-^ԑsS7@zT=LՕrT{TZ-ҥsS3V`oʾ>+dE=g4H>Ԩ3)vQɤ~= G%Gud'5<ޠcDy ?Zܑ{R78{UvlcDH!ҪT;V|GjT P78ۿ@TmTg1L&)RRƛԧ;QsIKj3۽RZRxcG?Ϛ3^i} C@/$Ry)HLRc&Z^KzRt9#4wIP8NQF{֓3Im(Bz3FqG|n1N Py?.h i21.F'(JCJG9?GPjL9uI($j:\IڌjZq'ڧCIsV65, 3ޭn90XV_\T[I3SpMMyNiуrE>jF$*Mӄ5e\n?2icN)Ao?E- t3LA'\Q]Uw$=~rMBXDcP;9N Ty֫HP3UܟQ܃b bc֠f5 z5E4񦓟“u)8&cwzL2KsxQSM.hI109&񎔹' n=2s\3GC֗0irH8 P'RO=y'l "E&r})sA#4#v1Vp*H-VX[sTaگE'jx$5*3R2jm?OqO&)ƒOC_OR*\`ԑvT(nj^6B7JM=sґ&L2إix`ciH8f?*-Q;sQ;qP1QHj .yf~2sQ VVs9pjU'Q9f56:T.Ğc1Qۦ Dzynxyt7=JL`uPz:RdPN?€}(Kс۵&8Iigzuh:fCސΗE"ig?Zo~sIx1M){dbϥ/#Gz^8J3)3F)@ Ci~0rsK&J}xjE'9F2yt4wu4iBzK"M-')G\b(=:i1K׽ϮE玔 '3ɣ֏z\R {R>g4#4:h=h4gMhKCSځӷs@旷=)A84_ZN{wSx=1~*D> zN0Gz!VOPY"?|F޵,,C㊿sަ=X'5" */Z|o!^MIK5L(9a5!'oFpiX=)c8ipy)j2}f5I'қ#bifSnwjn{EZߒj2TNjn:TVCjUg#=x`wUd⡐n*<PqTlMFN;ږGzsE ֗!qړ\ўGJ\t^٣4h$3H /GJ3J:Q!F3֗)r)Mc&y)AhяZ:sKߵ%);@ :Rԟ)yӉ N^ ?'&ju?.i=zՀy4MO#ZLjgi݊$ حT0x"sSǽOf$(&OKXޞcJrH0i K"3C6jfy9^jL'#~ 8Ps֡n0Dz.UI$9$z\fv5YDϑ!cB_{TLrFiLSi@7Lsޏ_ZNq֎ԝx##pqI~4ssCg<3K&sR478=)O:u3(= )R؊U⎤擑@94~4G<("4}.{8RQ1.p=i⏡'Fqȣ#9>Q(NԠ~u8%ӭ/QށJ@Oz>@PMdMzҗ=:Gz)G=)9<^}hx#OҐfJ?ZGR玔 ^hqF)Z3J1i{Rg;@ގsJ;h9J^ wPjTb.մ?("U!*gա $j>HϭN6=nq׊$Mp}3/^(94=41GJ3'R1J8=MF^:޴u@(&RM=Iu(`F*h󁊞#*P )IlT𞆬XASǽ81T?LK 'sRڕ_s@6GzBԥ9$fc:g68IdޣffQQ3ST/'8C$I*#3djq6OZ¡sM@O\\늍J0izG'Ґri#C؊BA'9N4( MҐOGq:~hߥ7g9 )Ӹ#4(9J~3M$ғ)W)\QAh4(K(vK\R`ڏj@r8NN{ bxsގQI4M/ғKx)>}h(izzLg4vz Pxu Kޓ^tK!44qIzҎN1F3G{0qG8Gj^Rw(8})@/ڗ#sKi2q\qցi:\Լ`c NO\JOz;挚NG_ΌߚQQ*:^(w۵(tKF9ȣ99I{&%h{};iz=BJ:sI}iG?&0({R(s@<4@RGS֌gA=2R7z; 8ҏ=s `!RR:On~q(Fqގii0qEg;Qq)}xATeQP]jwafcP'*> ڢcQ9'?ti2G~gޣ= 'n}h=i"R8@4i84Zz@p(.GMsHiA4dqG4iR4ZJJ84`c4K@fxG(QJoLӸ?JCA3wAHZ;u89pF1Kz=AIuZю()1=(?ZZA`q.zIzRqKIߊ?Nc4usގRA!>ԧc(9J8KRgRp>`2 :9/QҀ8r}( &694=x(F9xKڃj8O.0{PAڃA u18J)OOZrOӔȧpMHr)¥-H9R=zLCN8b Nb6IAVRW*H;X>" 87֥F|SsON 9ySҀJ&6 !o΍SKf@McfE013 LP wj#'j˜,b2n&w9FsPDܚj6=H4'ӊl!<`1ғ>Ԙޚ)=FsښzQ(h9-iG"s◞(r9:3(-G+HO<*A?/cG4zZNE!u`I3Nϵ&zמƌ`R82Fx4QҊO4qZ>dFxZN{}h &)OJ>cހ{GJ:>`Ҏ 9@"E/ju(G6 B_G5 Pdfg# 0bG5oZQڣ'L'4izyp9Mnyi14qӚ 4ƃ֎y9RgJwn 8 @J$iҏC֐:P9LR'h:u8hiH֎1JQ])(88'(HzK9uQA4v'CE4ӁM(1GZ^0qG~i2;QԾўy4hh4cҎh~4vQ=>=))8#1F8сKEҒtQz҂ri1^q<3ޔgh ҁJ^sNϥN;qKqO] p))IxDzT%3QBTngM4Dscrr FGlny<NI>ך:7'\:v/4}h<lRь`(QGJBF})H'& Q⌁4 n^ CHyڐJ9=3I֔ A#Ўhɣyތ`ct1i1KA@IJ)8A#.9#=:g֢vP=;(9# ;QKNwZC!ޜ:qHsӵh?J1@^/^zRsvK K֓ޝs1hN(Kt:b F0xhǯs\c/\f҂)1N)1@nhNڗryQҌɥZ~x:U T84pޞR'8uL֞ jE'8R=OFjtlt5"~EH*M>9R9''ޟÚOzϚJfeHZъ\P});8G9.9GZ^ؤ^hIqIi:c@qAulsP);tR3E'LuN(#'jR K9Rc /NQ1Av4R@;<ҌbsGhg('o4Q޴zwNs֖}p(QzQ稥E(ө{8/fORj@G4HSwR枭֥W5"ԡҦGSC"ԅ>Zz>8}hH$tgHzJ)7sނ00);Gҗ.zc'J4;K Aɥ R^HF8u‚?F? Aj1) ޴ҎE9JsLg֗ NҚ@;Ҍޓ$sފ9)OoJLsGCKGj9=hiO'9Hsڔp3'z^ƓA)q4$qJZCKHAϹ N p)N}(3JF~4M&3K~$NԼK&4;Rh4sڃF?*:qGJN /\q/zAӲis֌sKڔsҔs.NZv0x4ҔPqz4gAQړ&9ȣ#='3zV3IQ2zT`r;Iӊ:\)RpzӻRgc= K84p)q4 qc0? A SsOR!iةwsr1IY8s֤f$#R qޕ$$ҝ惞i@1.s*qSL7^(ȦʂSwץ1=)S*2yLS֣.NLf9;z YiߠqɦfB<4ry4cS3_“< '֗sC }hyӡ=N)z3J:u1 Rfr !isހ:搎(Rs .x&pzQގsG(g'8Ӹ4H3ϵ.{H`=i{sH9= 0CsFsKqQB0 9Z^CJ2hy\q(OJ4RrGuRzsxsHO>)GC)90 \ pirEM#NZ^iMԝ){~4z8;Q=(o9)1ǥ(@4sA@')h K`vJ^( Rth'M)֓=huj3:G/B;s r{Qg8 tў8A$N@RR?#M?v)bsNRiԛ1NF"b[?Zplu#F}iCB;vzqIt/҇8MP_uɎ i2:35d*2x9qؚfSsM, 3sϵ'_joM71ME#:zQǭ&1R{zCPI84!E= c#s9:F; oӽ=i;r(◂qIi3Jqڎ03Ҍ1E'@ҁIP9Z_Ú;4(P0?^E&r8$ѓG$8Zo#8ϵS֓4.ri:Lv7Z&N3\/jB:bhP3y9gQs#}'R2)dڗ=OHr:wF= jvy U\ȠwiA杞>g#\RJq֜;c/4)xvOH˚Uldӷ dozvSN*.i@2 Ni `94=iJF[Ԝt`R;qG׊ ڂzqFI48IŽ4Lc8f(F9)'8ёirzIh'PO擯QK9F)H{Oj0=q@1҃Ҁ1G"4*^=hi 84'ڎ3KwC~;\gJ;c֐{٥>RuNi^(==J\搚A>q@QRg>PN;QGn8);ҖB}M/J s@NHz~GJ^z('Z]Ҏ.yӃt^ӃsJX>)t+g'gZ9bC?ʝQ xmïJPFN&8J\v曻ߚ<2h=h.H$R4nҘX`HN7;j0=AO4/lbҀA搃OGCFrztFH8#8ϭ)\9F}{P-Fs@Oph=1Oޔ);{P~Z21Z3OFp94 2s⌌t FsڀsҗQ:3hy4q =)p=i:v4)z(O)ގIJ\(Oz9N)ؤl:dP=;FFh#8((:sE{ҔtEGj;R:uixތIGKюqKzLFisITg"FiN(uJ8'^(#?Z)q9攌HFFGz1ԚPx!?:I^w'ڔ&)z3.Hf}/iA4Jvsҗ&7'v=i۹ozSsڗvpsFw>+r47MRgw$Rbp4ISCgHN8&8#Iڐ8iuOR⛞HzH9=hG} Mғt4d1R) KӚBy-s1A4qRq׽dii 'J#4zzRʃI֗POl␌ 9){RsHG4(8Iץ'SxA(I)Ns֚ɣ })rr1ڃӵނqM'=)qQ@<i{b֎9?_֗{яʌdzR( '!O=h(ց >qޜ@^)1&4dt=(<0)N1֒hG~~9Թ<сҌ◀=(Ei3K4q'!9# &:^ޔq(\ w<\|Թ zNEM1J~ԣ=hG O_Z2KR4Q:wzq:0y֜:qJ;>)ϭ◁Fݕ Ӛ]1Frz҇{Җx4 Ԁ`R&/j ⛒?*LO9 S3@=i}xtZBzKIHxMFE&;Թr;Sr bhGNyg<::8JAEIװ#O4i)H&q֐z1Eϭ.=颗I1KȠџJ2i K:JQF{Q83K׽8i8 M#HsNޗ>Pphbɥ^Ê2:I4 u4 2y?Jvs4 Hz)MSۚ\nSM\Ґ($c>n'PzQ84):/SGnyKy(>Ԟ۽Z@p9&G9GޜR9ɤғGn!?j\G489sx@g#ni:ZNZ\uŽ(hǿ4QI"RyR4␐E'җ(E3搏C:ҜGA&@@qޔtHNzR ґIIz=hNzRg#vA c(}(uBF){{NPsA<qIQݨA#q.x犌`IץpJSɣG4Nh4 3 &@Rޓ>(RQA'<SFF(4hFqN(p(ϩ~Tw^u'C@=@Nr94{RwJC@'&Hiq)H=iF;fI=iG9p)AFԸwJZ)sOjC`RixJ>;RjCQׯJ\pN)sFjL`{J x(cяJm.ށތ|٤'v 8@Aɣ9Q֐q֊R>^=hԾԀRg=M(!@ޔ4u Q &9HH*hSQO4sJA@9g+Ƞrh4zRR#ґR)Ph ֊P1N1I=HNҌ&rJQ ^hQޓڎQt vG &8uё (Iގs(( q;uThR)=#<ў)z)(Kڏltނ()iI!Z;ҁ4Kz294diԝ֔1NhhKϵ/F9Gs.r3Mz\)O#4R 2qLR҂N:Qڔt!'ҎE/Gj#y=((>ځHߥ8s@'"b=(AbJ_nh)3GJ1ɥ3usQ4ɣ=)@=}dP>QFZ^OAI4>)!G>u'ۚBF}<)sށ:dt4Lh-'^~zC)qF('I1HOlJ014)4SGz0($Ԥg uJ *_:q@NvcFN9<1K8Ґc)jA8g"ggM'\SpsF(lQhz08q)*C&p39IѾSA>PF;vޔs)1H>u۟j8^ ҃n)8=(1ޗ91ǭ.sR`PJ;P@ҌPN}9(рs;Rӵ!hןj(R⎦w4's@KփIIO.hP(_“i9iqߵ'B)yIxd@恚ph=)wf<KO@8}h$8ʎIɤR=9PRu8rsQQIhF1: LR g:G;p(HG 8zj>Q(ɣQKގIރ){qғK3C}#ڀ=E@^ygP9>{QGz)GGhQ4wh0(G:L u!t:PxaAj^ wiݺRczўԸ@)1gQҞ1 <(8';cʔdz\RS"ϭqJF9!=?“ȤqKZ:Q}18㩤8R޴RҐ` R<8RtFJps֌OQK!ϭ!$ _j 斌I)8)sǥsޓ:P94gNJ8&Ӟ4hH8G=9($Ahiqi=(hJ?y47$GIS Rts@F9@Kz*#INMx4{g=(j^sG^ttp}ix'LQswK);R4@#8'iGZ0:Qc1Ȥ&yJ})K߽b#Rq׽!@@A'QJ:Q'^K>Z_Ɨ#ҏƔ:hR:1Hʂ2EOH9j0A<=(@=hmwv8fPp}8ڎڀ3HFӚQҚGz<Ҏh=hH~tFph8fjA \3ޗ'`?* s4ю0;Q׎PS)䞴u$u)zj\M, v s4wQHs/jn=F(r;N4ڌu1R!ǥRGP@JLwZ3Qj884sLw"c!G.3'KN@(tgiOMҗ8Gu8/l~ʓwhG4)1Z9uJ0q=87$sN`}iJ8vTzQӑڌhۦMGN)? zz('(Ϡ( QҐ@BM(9J3/$3AR8)=.8ќQ9g!P 4ސs@ f8h'($';sQɥzNztqK(ϥz;穣Qb: ^Lh sGSA(454 @ڔ(* 494wiy'}i{RR49GM ߟj=)Fx挞v◟ƀy9ڎԘKڌsJNzL`Rzӱi2sKj;u◠sOJ=y4`ђ֌{Ru 'N /)s'Kj98wA)/_JQzL@M<*@14~zRM/8nOJRJKIҎ٠׽Jߍ'8Q1NZ^zCqȣ=I.xjLc.(<:isF?*(7<^Rq@M ◠K=):KמhhhҎ(==h8&'<ѓ:zu'nyK@sҗҌ1jN:4qIRzf 3GA֍ĚZڌxE'-ғ&:ўqJy:dў;2 /Z3JO&}(Gnc.Nؤ4d99)1wgI2h294( ?~tQj(GGQGz;1ޗ83A@94uZ4Q(#ҁץ/s@qFGjZNsJҀH<ѓI( H)A'^_\n8R3FpI9ws.(8z3hSIjBqNH}qAE&yr(QO)%9/J8y4) /lRwJ9GQʎhڔȣƌQFphϵ(n:R (.{R.9jZ14Jތ"ޔ3IQFN=r攓3: Nh.i1ZAS3M1K>dsFHgiy'ڎ(4N&Oj]ǽ'CKr 4 f֌FhތQ.~^hh(\ԁ;<@i8hqSPxsNzi<sڗ>t4Ҕc3ϵ!<Z2{Q 1A9RFAN1Fq/nsv$ 4g.8yϨI~CJJRM'N} (9K=4A8HzJpGZB{ s1H (<`Prh49&ph:Q@ǥ8FH AҁלgڔA9($h h=KڑN2j>&8AA#')fJ3cwFy'J;RwF@vғJxJA;9A34 -!zQ;8K /zZLd b񎔀~TRfh@ԇ^OzZPsFG4JzRbi3c4RGNqG.;`J{Rg cKhRqёc)t擯?'Q4g1j7sގZ^ؤF;Z8>€s@qr{z_~I)8FI)qIӨzM/n84ri3 (ui; J3JOZi&'@9QjP{Lw)qKɤv4visA< O^r9'^@LtZ iGbi IRGZ88r3P G|fyc:Q8΂H㯽C('ҏŽ){wPAxw01FygץE?)fإ?JCJ^sA֓g0u;NR`1c :zҚ:Qsց(A旷Rs4wNsIr3FNqKM!(c(RR@>dޏ”ߊ=u>p;R J;R bƁAA/|f}i{Hq)AޔQ;AGFq\qIɥw~4Ҕ9?Z=-)HIHy0zќ/N1IbsҌ~F)2{R~揯Z8H;P8gZZLףZBy|sgފL01i9Ȥ'ױy=)ERrNsG&Ө!擵N3@^3HI3'1Ahtu<zRڎݨyz =Rf۽.yh/?zqG#An3@ 8uwJ8Puh*wqKӿ4 }iNHGc=)y<cϽ&H=iy<<sA);JA4ҞуAsҐ t$3AC4IϿzQq⓾sK&g)Iw=2)R<@֌ 7c<89<{;Rqz ^fJ('1A#z&z8Ҏ~T8Si{ AIPiOI9~i 1KGNAь/|R"R(18ԿQsHGJZ)1?/i;J^E{fNGNR~{SȤ?&y֓$fP )vяʁQqGn)E 'җ_Žҁъ: ;^zQoʔ` oK= s@Ϧ3K@L^ԤgLcьCAIR8P{ўqG$px)LtAj8ךLdSu4zsF3ɣR"vfzfRdR}( &9I=yJ:J^7.8 }})qր=ЊLQ54gI8?J\ ^ sG4`)h'4?8p9g&Q0sފ?bzbғw~RcEI:揭AFxxh,1ъ8=㠤9AJ4w4sǥ gҎHqG)GZ;y9:R;P:t IR)JZc4qGҌg1.zLzj9hhҌr1Gi_ZQ)1\AZ֗>&: 1{R)}(ށ惌IRA(4^QғNhhiFAzt9".&01K:*.qұIځ֎ROʎi Rc攊CP1KJAӭ.{Qi1AK)=/Cq@ht(i{ѓғq:4sG'.8P4EEҔ(>ԤP(4vg(Z0siq3AhyҌr=zi>8KPq uϽph4)shSE=RJ^4cރJ9Rh=^܎h$QҎ3AڎRfq֗zLuCK)8 н(JLJ\ztюA@{߭(צ(ьRzQG4{fҐ_ʎAQ 8#֗\bgtqF8iA=h'~M(JLK;g'9ךS p:KGM=OzR9&AJ;sF;4$ғK!ќi1yx9((=iF1I{g#)(i:Q .p9'KȠޔ O€qZAq?Q=LK@Q G|џ]⎀8z⎧:1QQ~4qKǭ!;Ɗ'ޔ9Ҋ^R}(#=(AGj=ip;NE(QөN1/tct:4G1I&ր84bN(2i@J K>mh'ڗi i0(ף81hh8&җ۵ 9@J:sI\Ǯ(9Z;'J\79Zw4^h' ~tF){3I}/4dbJ /aFA֐`EZ_J )/)=:&=9?(4őA90:TюP8fN)ݠqʗb bijLy99֓ b&izu铞)JQF(nc)~O=9=i>K&8?3ڔ'ZJ3JGqN4atc#AizQg4|i 4Ҋ3֡QFy8Q''J1GNsFs֐}SF0{Ruh>Դc;=G=&(y8"; 1h'#:w44SGQIϭ)uJ;QG~Tf@HFM(Pi:j_R)ڌqJ>g)9iAQH8'ڎQ:RL4w.qy(  =N{ѻZ3֗9ӚC׮(tx)h!ϭ-@9'ҁ掦hg)9J>'=;SA7/~#83Rup(E9gҗ? iO )'9 cA31F8#(KG))=iAnwPJ3ۚ^M.ZLIQڔўqތcJrzRfNHvG\9/Z:ғ8R~4R֔ԭr8ӊ;8ZvO\Rw'!$c4 .qz^)QCz^ҌF(@"IFsKǽHr9J$<}(ր})3NR H:f 3QGQU.zRg&HNM(&*= &R玝iڏz4~_AI8G#K:Ғ@&qI)F{g?:2vJ?'`Qޗ4 =sJ}(֔CҞi44 8ѻNѓ.x%/ riKq@=1M#ӥ;isJGQQ/֌(=;fFxg4Q؀(^hhTp(($Ȥ:hH{Ҟ&I&N) .h2);g4 ^yRg֎((=I9(43ϨKԊ^;rqA'4ڗ$vH Qך\JAE(iyhsMϷGQQF2h.I FNy'4zqo{:Qb.yhd8K'AQsߵ.MGj֓J 'ڎw=h=94Pxz9qғQҗwE!' 8*)4~BFwb9Ԡ= GJ8'֊SӌQ^ȣ8ȥNi4fKJ9i 4ڌ\v֓u=i~֌r 4pO4fQތ(Z3M94gr9v('4q{P3K?d8gE'z^0O'1ގE/AQ&I44ҝ 1֌'t1H>p8'IQ~d>ڀMqץ)u' 3A(9JNZ\G44dRqK֓I<9<K4(/9HNxtqހyF3@:RqjNt8`w~T)1Ri3J9Zvr:q&hƃڌ4dfҜց~)_jQIFN'>M' :)=}iGrhJ3!<}h SGJS Iߧ4nӻI9NH)s o=4h19.qړ$_(IRht$ѓ01K}@4:){QӥTzGЊ@h' 1@K}Gn b ?'(LFp94KތsMϯ4RQA CQZPyGS9G|Fpiy"/hKߵyQ@RHFZ\h'"?)O')sAqO4sڎqGϭ;H0G4gR'8G<:Rd4{RRs1A? ֗Ҋ;P=:R{IђƗ<:x) LqKFy$QNi{␐t٣JLw`QipinqK9FJQH(#җ(^i 4t>:{PG>ԇiqǽqF{P=h\x9o&qOҗ M/"tJ\Ҝ hqȠqh@PGI1SӚ=1J4c>gE8iRK4=i34pN;Q QhG׵;qփȤ4ZM4dQӌ94g\dsڔ})^h8 ֐A9RoRG)#/ZLq8 b4sFzPG4A.8h_Sigima-1.1.1/sigima/data/tests/laser_beam/TEM00_z_65.jpg000066400000000000000000002323671514013333200225030ustar00rootroot00000000000000JFIFC    $.' ",#(7),01444'9=82<.342 @ }!1AQa"q2#BR$3br %&'()*456789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz?юj? ?EKARR(dQҎ)\~Qڃgr;fzz?*=ijGJ_擾)zqF8&hi iQҗbGA(9<߯Z^)9F?:98N◜R`RҌQۚ8ϥw`AsKT1NPI֔bQ; _ʓR)})=9LhԹ'{01Ob@h{REyxn4J)I֏AFizwhhH/H8ѐ- (?AA(4RfiIG4fI4R{349җ#R{R;ѐ(-zt(I>Ԥ%)s34~4gRKA('=֗c4 cKSKL PqGZN b}EA#>):Rj&x4R~(hvcɥ@>h@ǭ ?%wJZJ:v$Q@zLݩN}(;K? L(փҔCG^hh)GZoz\QF(h)i杁I.sMN4qԣ&GZLҗizg/ju}'sQҌwNu@)zusKڎRis(ZB斊N:E.=i2sqFp=zЊ FIi:Rg\Jy@!Fpz{ޗg3:QtGj1h(8=<h|Qր ׊ZNisJ(!񠑟zNiA= LqG4>;Q^q'N`{>p~SK֎hh#4}h - iy&8<(J: 3QלюF=4(h4R#Cގ1@Fxy(3ѓϥ/ JOgёA9>g8A13fR#ItZ s@"3HOl^);P9Ki8E(ɥ'rFhqE8GNg>qNq֌ғ'C֌@9849G⒁ph4ޛߚ\ќ)xўi}3Kס()&}8= h(Qғ<ќP98)GfqڃHzs>gIڃF(ϵf(Rӽ ֔'4)H8 }i(ۥZv}iSZCJKqM'ө ")L4J\&Z3EQ\A'&}h֔u!z\F}) Z^Ú ǭA'zwQv'z3ڔIh.sEZhgӭs8֌G\Qi3Ɨz掸( A^_zLѓKH:bގNt=h=(FqE!Fhփҗ&xQތG\3g }sGJ3@%.{3(џZ2(4g)QRgҌgRv:(ѐGNwQHzH:ߥ-% R\QE'^):u4 FsANIތGNGzԜis=iAb8&{҃4i}M&iw'ZvsHOg\sisރɠc}h()F(TڔN1IGJh ?& GzJ\dRci{ќtphKړ84G\zPx&0>tGҎ{("=3GlQʁJ3^&:ёҌҊNM.xZAփZ\uh&(3KRtʃGҐ}(O4R(wp3Eԝ{Qڌ4Gnh8u){qA4Q(c:Qҁڃ-QGZ94cށ֌⏭Ru׽ 8<סc)@' :Q);$R9Ni3ɥ(8J3GJAހȣQGj}iGJB9zҊ)}E G4: IKIҜނgԃ)ɠzzQ^SA;G|dRwsF;Qԙzvg)3t҃=<֌c)#4ўԽ4Γ֎zc'9qQҗpi ◊>GRvKLzfғ/?bG9`A8}x`ڊ1(۵R}>4HNإǭzb8`Q߁G?u)9IQHz\sI–N; :j\RvcN.ytJ:Ph#~T)zbޔR4JO^((A>߮((#H={Qh>)3G^=){zcb1KJ;I _1J1GJ1QށGzFhҁGj))H"gHyiOG F}tGRw4})~ 1hځր8>:qG'8/QG3F2):F9/P3۵#::c֗N)~'Ҍw>t(?J^j1GCڌPzS{◧}E?B1G⎣I984 Q֛J^.1Iz.1ɣc0r9Z:u/zޓ94ނ9`̜AGQKA'J?#KzNԿ4Z}))sۏƓ)zҀ(@=z4ԜtzK9NԽG^i1Kۯ4ޝIҁށ׭蠌P~{ב@xIޓJ9J4 sI@)~44NsFh'h(4)sK'N=)#JJ\gZ1ȣH(҂;84QH;ў:RҐizw94c=hg'z\QcG&Q`sAq;Qv(Q~4t:v$}hQ߭ Kڎך^ю)9 ):@<^ށϵIu◧"Z;u'K=G( }9Q( ㎴ZL`G'b@#&Cڌފ^cJNFE'=hM^GjN$RhxFi;sI–&}h#?Z)=KޚsL RRNƔRpO=)HCF= ގ(籣})qڎ8 R)(?h#׊C4@})Z^(44cIΌjB2E8ʃCҎ~(h#=1EQ;◃Ah/z(O~*1F1K4掂KsGSQ=H7 J(I Q߽:8&(4LrxE ԸE!9o9RZ@>Լc"dQC@@@?LzRi>'(#=i.0zqF8/IycҎ~JE'z^Gz P;JLcRc֗ځɣcP3ޗRc яz1=F)▀?ƌdt 03KLxh&)M'RhGN`RϽ.(Az\dtMF;:Qhaϭ)(#4AQGҏ 1NʘqE-'ҁփ%)⓸)?^i}y4RQҌ{}i;F(ցL1FG@(?JQjCKH}GJ(H}J3H:zR֌1=9A^RIhKzCӥ( K?Žg@<?JQzPzQ:CށҌRJNRbNHKhihi{Rh4s֤ъ1җRc1K@qI^J_Z)^31ޗ"9⍤zю9ю}h}h 4)zQ)GQF >ҌzuԹ@9qHx<G>qփ֎Η'@ޏZi@ 494~qiz旁JSA8=wGр:fH=<@'Ny(3FpHt>“KdtRb/Z1F0E/Ҏ0h4Qh4tF=hҁlR~4rh4QڌRgJH> 1Ҍb(P:fGRqFqA硥ьtc<ҁcSGZ>~fFxM8i Γ@i:RbvI89`CsҐNqJ=1Gq^:RL .G(")p6P:RH=sEuqF(8'{qFjKߜތc<@4c棂h=i1 hK`@<\p9)H?J\ޓ◿IzN)0iOZ<}!߭(FKӊCϥ!t)GGj;1F QK:sL4ڌ};Ҏ}(?J)qIߎs4u QށڗqIӾiH4!K:(x(IG(ғ/JRz8h>Nh) \҃.y4zP{ߥzZ_ J=h4ߚOuq/#(A CҔ}ysKSFqGjLҎ4G4OZ ߌRbJ:4wQGJ\qFqځюztր=(MCȣF)MښN=i{ZN)z~)?/^tK&(G~J:>gڎ4gE/lZ◷v8xw}(ɣP};QG.9ɣԠs֓Q@43G|␊(>hRth{i(IFhE'Lғړ֗y)&4;р94cHy/j;Q8 AR4dSNqCAьbg}i;h/'qڔ9HG4~4Q)y{Qx_(=EƏƎ<Ҏ#4(=(h>(xR:1G? @ix z84t4R(㸣p((G84Psi:GbsGj>QK'CKȥ?.Ai9'^ߍ&9Aft43JFSȤ= `wގ 4zP挌uޗZc4A sIփڎqz2=)AHhgg4ғz^Iu掔frhG֖sڊQhE!}0(4J(ҁړ~9(QK(sGSIzCځڗJ1JNzRz׭F:N`g0((#?*3ڌdR)si&4Q^Ԙ{QZN&)yQG'(=(q:PM'ץ.9u'0)zQAKHyNqH9?QۭⓦGz\(Ɛ{QSփ8ڎsJ(ҁN;Ru)I/j=h3@K擧=CӑK֗ǥ/ZhȨ\Py4i&{S*hzh>v:sփތG#h8Q/AHIF}hC—4h8җ(ʁFhҐۚRH!FZ3֎Ɠ=iÎgi3⌏Z17{RZLKLtcJ\p(=)=) 9JM'NixϽIZ^g壯zL8FE'.GҌIiá')@IuKu'sHaNs9!84(I:f9j2sHKfё3LR4dw)34}h϶h҂:3zC.F3IiG֍RqKړ8J9J8 \֎zӁ@Fy"FqF@4zAGA@L=(9.xzF;\A'3J2HTKgi(K3SIԢ>hhrh'њZ@ir=)Z^48j3HdQFz8ZLcQ?xRP=()(&zҚ:sGRiǥ%s;RϽ'KwAGݎg/jCJ0)23K zRQ I8 (i2;(.y"EhȠ~tg=({wsKFx8iWތRc{R)3-8џz\qKIw@7ugJsNfё@4gR})9E#AHXfKh=))sAKGҗwusQҀqڎz҃E&{Qc}(?{ڔLHݩs&8q4A'4EqGSFx2hGIA׊Z3?PsRt&y#֎}GA\ҏ“< =y挜yszJ\`ў(#)s;Qi:K4R)jL=( QM&nGRs@@<$Gp(ɠH4uc&A ~t3GzQ֓9ɠ\f1INIZ2 'J(J;Hr(P:`qGS~43ޕzf#c?zIҗurzHqQE'4c旁^KNG_\Qԃ9I/H:uPqz3ץMqH{&AbgӧZ^x;dR%K Nf:R@4is Aך8<8&{ьw̚ҒwQQG_j^Fy'i9К\bZ3A<Ҁ:=(;ޖ?ŽZ Z:cҎ)2sڎRzJh&dqK٣8Qӌc&HZKHzfQJLQ=hIP杊=h^i;; 3օ)8=sG|Q=h&BqFi{{4c!ڐdь{KNsҔv I◞RQNi@>N88IҌpNh \s@x)z ^Pxg)/|R`3)O^h(u&xKfq֎ }ER1G=sIRh ){P>ihu>/EڃQ)@44яJ:QA3:vAFx|Լ4ri2})}GGIF(- _'J3$88ќNq@ڐp(\bz0qGc\њ)ri'^h< .p:QI1s׊;Q&=R);R&yQւi9Ah< i9#4`s@yޏ~z^qH3Jz0=;cF QIGzSGJ3(1s0h9 bQEQ> ֎)~ =zR;R9'A0FzQJI=Q(===3KӚ9ǽq4^){Rޗ'&8 sҎ89ڗ'<юG4`4c4@=h9sڃFipO.xcNIzSO?)4 ;~sE=zўGcKԟZ0hQbpipq֏LN@ҊsJ:H9֓;)()1J:v=xw PqF2($◜RcAIc=?*S 9֎sF( gAR"3Ij^)j  ;RR1ޓ(<\Q^٣9SF}J?*旵'AF{Ҏ􇯭(4) )r(ӵ⓿/~g֎)qIߥZ)M& gQ֊^1Fx;QRtLKGjO|Rڐb _IЊR{9i~'4uъLRPz)N0y_!y4zb)0{QQޒ?.E'Ar0(#ނ)xzNS'9ގPI ?ڌ▒ZCҝIHGaKQLzǯJ^ZP}=#RR␟)Q{◶3@㠥M/ (>ҏ%gR4csK'#ڏhh?JN{ZAG"g:)0z◨'ҔsGAǽQJ1KIȤ'sJ3KI\M9v/?L֗J^M0 Hh-QQۭEKA )q'zSȣqwd֗׊0AA4:uuGQJs(IGiG4s@isJj34t@:@dA4'U4{GsKH>`Ri=h4 Pɣc1ڔqH{ROjB=(J^Rc=1GQLz;ۯ4w_r((F94wy旵 =dzRtKGғy֐zRwRqGj^@u҃wu): 0i{r? 3AGl⎘zR wbg4Z28ڌcJ1Qs?*h9E=iG=E 3Gz9G"(Nh<9惊6q@c4ctQG=E/&֎@<⓿J9Ԙ(99Z3Ҕ`c4zGցJQZ{P= sHsQ:uqHG R4Gn(I/QJ(8Ru◥&;=Kړg4t#''ڗ)IqF2zRwGG(4zC}s@Q}9;p):Su4 ␃Jhi旞(=F)NiMJ?Z^;R=fqGJOh)Ivgx4Z1֓ґpyw'_J\qh4dfw)qhZ^Q~<2O4'Hzj:z0:P0(=(@(t֔iOMSjLfsK)8>JIvF9&z^ sA GҗhG\g8@):ch(4u4tJzQ֐uA@8#” b( 08 hF;撗`?Z'4t{ ^oF h(NhR?J1KGzNJȠzvj\fqhQQ{Q{j0Iϵg\dP)1.8)1AQ(1Jx@KRQF8@QA?ZP)1J9ڎHzQbɣI֗ɤ4)JiJ^ԘK֔ w'9яz(>c)qIӑ@z9hG>c#4ǭ9IҁJ:9Hr3iE!{}QQKc'NGji`c${i4qߊP(qҙoʂ)OMKތf1J:u)qOA'֗OҒ"rh4QzRzRwҊ JL zJ>I; R~4b>qKNi@ uIۃF)@sJ^t}c=q>q'oj::P89?)tr(j;tҁA'4tF;( 9&sG~hJyW/4h9)KHF}rN(#֔qJi(J>Qhqi}ǥ)bsGlw9QB:zlqGP:ю(Ҍ9JZ?bRt:Q(8ZNG@9;QE))3ڐP31\R`OGɥA=9=i)GփGz^vwv9u (tcSғvN;Pi1AG_Z^q@ h4hxLRڗ=OH}3K~cbzQ4gjLc^A Qbc{QF0)s~4&-.!JBP@hKI(hǽ.=:`GsKސFGihbu(J3Ki:\sHG8 P9RŒ 1RczSHG9IF1ס#$ҌQI4cJ\c9bR{P=iqZn>jwsF1zB;1A:ь 9*s@4qҎ hjiZ;(JP?*LP9G4CGnz8ǭ7^tǿP4GBi3GN'q):/SAsҗJLR#ޓ:H:sKށGsiqKF2O"1Hx4&:w }/n~4z;vށA1IJ9#޴b8w)GҎ4*R:SG.zPzh=)GJ:c=(F9Ryi)ߊ:Q֌z8'cC)APxҍ08jt .Iځ@ȣh):h҂3҂8HA J0Mǽ"QhA^Jpix=?Z; ^ !>t^I=zPGjJ/QvJ3ӵ֏ƐsH)yۃ 4)g4h4x/M wJLd҃ӌSziF)0A<8gQ֌zQZNM.P8=)< NqFj\4}1F1Gz=iIR/LR~4Kנ?Z1ǭ3ni9ޔzRsޗp(sGzOΌ~QRJA AA&xQyր9Ύ)ON zP3ph14uюc$Qi3;ҊBcG=) F(h48@Kǡ4bcJ:})1Jh zsJ2j IgҗiM!JE(iO֌RۭcC4R1IgҔ:uҊ<($ ׊\QJ_jR=):Qތ@9KGN(ޔΎ;d~t4cdj( =(QwϨQӥ&ss@Rփ(ϯ4@)HF9rhipsQG_/4c?֓"`KF}( җi?(#I Ϲixh4ݹ9AQ'S֓{i8#i= vQKc9cݩ/JA֊QGZ(ԝH\`Rԣtwq.= /(҃4s^0IA$t<'(4t>{ґGJ3=(#&IK($Gv@4g)<JAғ)zQA3FQGU (ރJ0E!K4Hn1֛4=Pr{Rvny4QǭސzQ@&t9FqGQA>G^Rߥ )'SF{Rc/AFh9ɥ3L`'Ҏ1GZ;Qr(()x4Px/~(4u(4R}@&ɤQ4Q֐P{Rg1R)(#'3K4dR !)G'zQ9Kۭ =}('QڊLJRh< LӺsGIGj2=(-(4(4 S1J(zQNM-sҎ4^'(:RwAzP) %w)q=)8ҎށތQKi )=)FGҌ1G~3Iփpi^v&3Ks֎4ɠ:PzRzRIǭ4Nh=8Iz^>ԾѺR IiszrZ\hϭ';FhKړ?}(z#֚}){hǯ4C(P8K2x4~1GA=`bOj3)(h4tiG(GGwRK4(8@3@& Qz}i3Թ}h?{tQFF{f('ފt/Pht G~fiOn—׊1A>3@"qJ(+&Ѷ2zRdS}GixϽ ֖Ӟ(J=}i>JN9 qI'PzA܀}4i0)M'NQiEc<яJ)RHΌџʗ'b)֔p:QQZChJ^4u4r '}O@@<Ҝg): 3Kӥ 5=x'CFx/E!&8RzZ31ԝҀs =?J\GZi8Fy{3֗ZB}(\:R_aK֓t{t(.((/^{Ҁ##H $ґҚG84$s7) Gn);'N?Z3A'u'QG9RsAE KFyzҞ)h(>t=@<=H P3֔33F ZL\ѐ84gg4g4gҗi2ih=3Gj)^1FsK@z4'.y94>qќLx4uPh'R.iKG''O/j3::HI?J3A4(4)Z(%((:=/_GJq֜ QqJ)zZ\d}(+h yxA R“֗B::I@ȣq1(943IF3;MdzRq()>89>ƀ}gFx撗vў(3qJ)1Py=(44uh?JNZ\⓱{ӳFpsM=;:Rufg4uփ!4G4җ =ONԜsGԹSO4(:v9GS\GN;ќQؚ2=)94:R 杚JN/lQtF=h9=E(zB2( 4zp4sҊ\'KI3ўhҎHr1)i ֔cޓ){R RhFh4`<ҌbtcJ/= (0:ph7֔dj\dҁ@qJ֍8RJB9r)R P403ޓiJ1HE7PAzQ֐sAIHi8٣iqA4Z3F3AA?JQG~1F9 }hA>i1ϵ/҂P 'tޓ::{ѓяz\p)1ϥ^Ծ{(w@қ}ӆ3&E=&بɥhc(lP)hHRi;RASAށ4uj^)1IM~&t揯Jc<94(ǧZ13ҁ94vubF( uG>AF9AH:PzqFNhRJ\uuq9t=(^()zEhRsKӗ/-lғi0GZCAI zRqiqM#ڐqc4FxzkrGʓfҌzPO9J:ҁ74AIڗ'җQNԹ⓯'Np0)֗(ъ21EJGsȤ@\fqHqҘTsAr)搌M?Κx$9NzHGhR}HzG!xRJ3hM/Q@#89(=;Q@/jLezRփFzڂ29()GJ:Q@x#RStKGJ8&Ihցӊ֌fq@pzh^Nq$QK֐h=h'>:Ru!R H.?*(#`>⎧):R҃G8Qڏj^ZN49bjN}>GjNԣG@985jJS⓯֗8u9Sҗ1J1NԄzRzQsMw;oΎ掂^(:Q9 PzR`gڗ1(qz1~?.=hJGLNsKf@/4;$tڜ)yS Ӏ0r9*giL|"^^)1NhڕP<5?fE0)<VP?t&9)JL8E3Mru򡗎0sMx1HQsISqF\vHi{}(4i3Ai h'z4 b1ZNږ8\Fh&KQH=)G4{Gz1N)1RHiiZ;QFE穠Q('Gz);SJiAJ>(Iip1H^wuKۊonzPiG'ڎ);3vтMP;Q&yz4g8f*1)z8}h9J^u@zPhEփޗғ4r1Gz^ԙRqR҂y&p:Qu{Դ{E{QP~3J4w (.x掘"O)zR3J:2EZOz^cJZiJ=Ը⓮)}(F~liqJ((@(7i? oz:x֏j:p/^h=;ZOCƖ@#4J:c^C\N:v杚Cץ sG8/NqKzRuҎzRpOqN8)d8 riBzӑH8Rljr.N1Oێ*@ Rmw(5&rz)qB jv̜p:sHS'';gLVsI$Y9 gޜj,*%^OSHW+$L0yc4ÂiSG|{SqIZiM+4n9#z1٠M1Ғ8t(E'Q; Q ?O^49=3F3@4njPE&iG46}q{i0)xJZ3Z( b4gwZ^xc :QގF)(ޗ"jp=8cO_<{Ԋ:u(Pr8JF8G=fH9&JGDNsR<$,i4ǭ9.XqM fJj &)8SzuA曊=4QZn1ތfҌvG'C`11֏&9ǵ&00h~QZCN)qތJ? _^)^q)qG֓ۥ'`vޓAH҃B;ڐӊZ\cғ68ϭITd#_jy@zbX,7Jy$cwCRI?,qgҚjO')Ң|8<1#$RIS@LQTJ940޽irOWMG10izF\86r()T!N!L})`Jc PW#FG4ST2: pJGOD'TYz4O*e\✣$S=iʹ ަ3iʪ;f(>('C jDL1GaT S"tЌ ңXr=9 ҬYR*ޝ$_/⫬|$<⣑y0"`riژpzTmw};7Lz1FFri6ITHT1J B4Rc gqF8!)z@z>qhip1 /Iގ)qG9(w : :Z_'(N/֛=)qIqG; 'SGL9Iޔ&4\{Ppϭ(␎Z^{RJ^ MQzRt4 i֗{Ҟh(枃JgJr,MXTr)>7jH=u3J"T"qڄ1RdivS"fIMJ.1S se`y4Iaґcp*|84@UhrtcL G?rlR2XS[zxIiȦ1!oBiⓌf 8ϥ''biAJE'zLsGJ:F94QփJBsNRc3'>䓊\t &0(i}'\uQAF(RbzgGj(A >/J;R)@zCϵҐ)1F0Mz(8N`jQRy`WMS8EeFjO$ˢ bGZY-3 *N8*7k8LKy=;sңH')^*) ql2}*"PHTj#hL6v1ʃPlx4¡ CQiBFsQ(+Dqwa3oZCצ)r)14tRglQۊo8h*Uޕ4JG9 1Vb_J~3UҪ`#4tQHȥcfsŕ$X4EIx"zwVh4K ӊ'8G"梐j<:sQI~nzT?JcqIx5 A'znߗP2Iڙw߯~th> :)qQz0z⓽ȥv4t(hw9Q1GGJ^>tzrs)߅qڌqҏ֗/=1֝Rjq-H8ǭ=Fy Hj|*h'&SVc+9cE[xȧE͏֬N:Tq<Æ ۞PqVDd.})H4=:qc4=zsښ:!4E8Hԁx:Mi^ S,52Ut֫Cҙ8U!:UYri)sQ0"#ڢnVۚij[i9i搏ʓ:qi94sڏ irx9A=1KhёS{Kt< )Iө(<4h\ZNzAG=zu)99ќ B})MF)1Psh\LRi;Q)yv9QӚCdQ:ZJ=3J=i{Rtg^(ɤǥ֊9ϵ/? :c4)9'iIKRfNh8 ZBp3JAA$R03IMz^4gNi{tE/Iހ}Igږsޖҁ4~4gߚ9KfhюH8)֔tvӰ)OZ}@#=@qJj`28<*eɫQsRqV>_Z5t01SA>+C*tǵ /JENO!)Qr(hȧ*qI杳йl)01ޚWB R4N{P@s3I"Q*+*RxN|_7LTrF6>p:TSF}:!8"px=s֗њ\q sޔ:Sw(48`R(#?Jӊx^}sR*XӜR{rjxԕT9VcB*hmwҦsrjxN5?SRc<Ӏ qS^@d54珞:z'4 R-?*s5G懏Տc)(840Gi`Bq)_zCڛ֐Iғ>}i~"{ќh<Nhڃۚ3JO iI4G/qM47gtd})i⎔`QJ3JN 2@Ng^hp—ғh?/>QIE/|b1G4zzQSHztRdހx(Ixq'|Ӂ=FF޽)3KQ)psi;w4fwQ=F)s@G474;}PI4⌟JSȤ\/IJNFsOJ:jN:ўr=)A&{ɤ==)1iߍ'4`s֓wjPxɥKM.yr{ԃ?S &QVx5$i=*a$f8Hy\\⥂,X⧉9T`SԠqSA0$} 5*Pvmi/n4J DOjHI卹J|ԏ5ҙ,^iT2)3'LuUNQJ*)G֡9dG*`c5M5DWN)0F9 } Gޛ֐Rc'3Fy<)Itdu4'ALj)FO@ QKӽ;PNqHzt4)3JI=Q=(ӵJCO֔u'7u(zRgOJP}:ڌGHisLQڐ)GҐ):vsG\J:fQ:=2h8sKZ\NhqAS'G*rsL0}*Ќ*9!8Sfa9桙㊀)J FzjqLlL<cu^j?›~Ӝoғ>ۃIփ֌w\I4fi3AN cތhzѐ1Gӭ&M:HlO(R撌ޗBq9ϭ=99ќhJ8)A4 3Hz@?J8is(?LTy&QޓH8qi E)OΌFzPzIӥ( f{Kj2Qj_G/(r)) ӇJx枣R*SsTgc\ՠ(VbazsWa$/5ѶJ3KY⇏ RQyR^*14#Th# *qQ1Q3J#@SȤ?5[L`ix5QG,yL`f61AQMFN= 4SO֚zM=8Hi3i4g&Rcޏ—8&8=xJOzQGJO&i:JdRz3J8C׵9ւ@ў)K 3JN:xIx4Swd)sڍhtc\֔n~j\g"ZA=)A:i"J /aGJNz_LڎvqIKE/Nc!/z((4QqGJ\&h|SE/џzN)3^:SNh~gҊ;њ>hyԙI\Hzub)i=>`\sGCKRS4)îi9z&TRޤ*Rƃ5` J$ XXέCa*e U*h85l c_AKTE<zG9~5dtX[3tsK KM)Tڄ'O0W2$iEBG%Kej<|dqF*9TQ**'>P)v/ךC*vsW`*rEWp*U1r̟5E"nj2*"0*23zu9Jiɤ4c{Z88LG^)E&qFy{gS'SA9'/sG>gR'&z;w/lQR3KR{qA4qF0IKz@֌`ҁG84<҂ wRdQRqz◮9#N޴H4zIӱ}sG}(Gj;Ҍ994Tc֌ ^u=3R֎zGj; ^='Q@\I)N{RK)i4uEJ_Iך^h<'AiH(du֌J/z=<@/j;:JU1(柌{TJ*qV=EO'ҬOJ#\_X t"TZ|IHcbc$b%( ?BRƼԎ8S!| HN9E4t梕rO4]C6*\7N)&N3c㚊h6|]MtʜSQ·nGJqI\ZC'UL$cU؂1Qr=ixi)dNhi8 hƔuќsH9G4'z;ю)3Gnzv~4Դg1%~4^qҌdOPr&M7'j3:QނxRJNԦJyө1֗!4w nqNUtPqKI8ۥI9OiT{Th2$Qi/9('$@K1U _U9", X*6|9R:}9:t 98U8Uf>j#pFjlUwuB1JȨdfQQFF{ a5za⛁h?JNJN3EP3jQjJ1F0h4bG^@A揯4w>4iiG^h(sN)sO =A)2sS*HJrqjx@1V]SWZ8HV9"jGzqNy+JJb'֤x)Dԭʄ&sQwT|L椐qM=qI)iRZw{Ur>cDUTT*j=ZEdSZ>2:SG"}ZxjȪ&J e'͞sڢ=@2}*70ץDG$1SJiQM'SI+c5~;T2&UF)pX$U|zTrXW2q8%7L.9T#j9Q?J5 {SOL'ښOMiS@&9HzqH)F3H~vQ:B=M/&:}(4iOlR{QŽh)@GNu49ގ/C)0y1hh>C8E8t9K 4 Žǭ>j?/$sE'J 4wҎZ:r1Fyi3KGLsizw0i1^أI/ZLzsKL(:Rc'֔R{BzbvzF3ғzt(=h(GAF9E.=ǿv)1xRaG'ޏ‚>ZJw@G8?Ls@rh^`1z\wF21@8攜Q1It `{R;PhRFj֔g=4җ`h'jw>)sK:xv*P5"*`8ެ'9\jD*@vȫV aq<$,H=*b ˃)?,_/ SxQN3RtO+ L9Svd)!u)ݏ։"C&7J9R*\?JITm"*׊# v̜)U>lb=)T*0RpCrj/5NBKMКZC@NO^j)2cP?\*2*lGndFjd9eWtiLUZ!!{ԛDN:#V\nF=*XXOj<R2P,nEj)c!U!ŅSLW fޠڠS2@7Mr6U4jj9?Z8Uf  >qPMRqj"mPj qPQ\5QzczSNOM׊C@QJ:{Rghh>ԝ.h9Hr;QqGz;QҎǜKAIh] 15_T98*P1z#]㊪E#*j);n'baQ:awJisI4>g4)p})r?NcJ^xⓟjR)=9>(g9G_J9;tr:Ӱqh")J;Rt ҊL@QH8ڃG^z _'vs=(4Ɨ$(ޔьhGn);q{sҏZFM'4 }M&1K3Bp> (=HJZ(LwғRxgzdM ~8~}L$qW"F85s~WN>aǵ>/VPz WL7TcS "s'4ЄsU]NҕeWO5GZ\`P8|UnajTE) cVU0j8d.ld;xUHɨd^xT?FF:Q7Zc9Mc1L< n)RwHx9h&r}Ry/z:R}Br(OIގҎJ?:FzRq:Qߚ;{Jڂ)H3@g:RRQI)siIRxJpE)31ԘZ\btҌR.sڌ~t}(Ϯ(݁֎h4Tw1IR!50&{Vc81 \VzV{Tg9T|iT >4*rjh*R"F&,;U\S8AV;O542TI&zUSAoMK@~jVǭ2P3H+U_+'!6TZ9E:w8튫*5RVpsG&@?G!@MG#qɨKqUfi:H~lTH0WVfT2GZqQI G~ D=*&jߍ J\߃I(ތ1GCڂqJNKhgPM&zө:ѓzg4=:(={Q/Žqɣ4g#Rrs@Ҍ掝MQ)OJQ4RqڎRފ8KIu($ NNiMis;ќ(^i1Gj_L@\L^)å8:T2?8} JELLUV#r68cVcXX Թ5iOB7p9\SEנjyˁޭ"|ϊcXR4{zr{ԑ7z"mf`}8)b4Đ9Oip=Ll c&m*N.UIe$6Ur )8ǵWJ^qUdwCyTR:U|2,NۊPF*n}jl {R7ayvDǟjޙc֚pE0tMn:u!#qISE9#jR1NJ;^? v')h>)>))s(Z8RgRI8R{gzNuRw=hc)◥thjAHO4 K߭'- y&FsJ9=hGEF1Kߊ:sIzPxhMŽԹқixZ3G4uA>h@'~zRc@RN2)4(< #ڃ(ڎu((^Ht4sSғKڏj2} .OZ\H3ќtzRSi{ /Zpzz8}{1N^OLgNV#_Sl@皲ث1);N0}* sVx'ޥRs֬zTZONjN6D}]G 9F?5k#o> 3tH(egHgOdj4LKFzL)!y⫾K$CUپlLd@? 3q*"x5#4# nr3HO4ӊF qM'p 3h<!E-'Q):i{R>◊%/^ԙ4 Qړ<ڌczҞAGz q֓ӳGlJ;vgD()wQbIQ֔&xҎhϥ)'jSZBE/cIiFJ(E&izr(#?j4hё@9FpOI֓wZ\/oZ3ϥDNh$Rvt4"ւN9EN<Cn/=j9:TC.j=j]sUޕ9皪d='JX5PEDNsQ)Qjn{S3S;M!4&{w(IO4Q׭KGjLҞi:O QcJ:dRc:u4fE @4phgJ~AFph8J7ȥϨKނyJLёKnqzPrizA8O-b9qFs(Gz(sE{掴?8ƀz \c&=hip3ڌsKRwS׭&{RcJ==hh<&^ӺNF(ҏ`RRsQӚQ^h9KsJ2qN֜jbjzA98SS">*XDCS iFJzjZ 9欣*UoՕ`GZ9j|sS 'S֬BM{UAOjt{*}cڥu(ۚFL \GL`H,B lj$!*74I`֣OLbW5 ޕ2Cf9nj)*T.F*>^Ju=};Ug\*Q0Q Aq֠,NjGDQ#5 u4c~{ N1@4c ^P(*;⌌RwIGAH"v֌9*: KjN:IMqbgފ)!u持is@#4Gzp)z?c'qi:`RI^?0( 9(֎q(&NN})@Ҕt(TnԠ3RTSxVcSZE*#jVaLzU*E7"\:IќT*nq֥sI/3R$zU/>)FyrjXdpxgUL2sҤlɨeO4GxT:U7gޫH=#)V`Iޫwo_ʢ߅dcQ#uMvoj#vN:TR&@T?7ϥE ʜTC j.~lQ61Dz߃ӌTLln; 'ґ'ozZi@GƏ:E}iNixiyE.}i84ZQ)>(py4w/jL`ъSI=(Q&M/|Ҝ-'CFx"utF*lg5ZgҫoOUjIޫH֡w9&y_FϹyO_j{~U9ߚa:To"pF8s&'L sGvI@@F{R}8G(A@T'Ҏ(F9F)1J<(w/Z@AP{ҏEs@#wj "}hҌbZ\1sG^(88ǭ/PsH8S;GQ(G^;\ sj(ގQQ1Eij;Qҁ.M'J^Q֌ G4~4{:fҗ&2(R4uȠxzQH:/zLs֗)A)0}(GqKڗ.yɥx?8r:4:zc>9=):fT8 u:jt3VUPOj皶=*/>b;War˞2YGR<'gSŌdqV@P3*mޝ)dc>4B |ԥO֣W=i"$I $dzPA>$"2dr8QnZBQ=jl\jŒ`uNazTMT5⪱#a֠/1Q`DqQsQ֘ǑM)}锄9Mh) ^4Ph Rc=;zzRtу {у4ҐtsJ=1GzOj\b4=OJQ}ރ(֎HQKZ3GIQ/N@FNi3ZNjzQt@ZB3ޚF:Pr%3Fyϭ֐8R Ҍғ4Egҗ>dJPi)zQ8j;Ph4z;)3KZ=84"4ځҎGjNGJ0zҁ8KhJQKȠw8ǧ4SyOSҥSR)TLxTdՔ*eGBU>j&F*QENHC{U1ɫKǭJsV\H ?&ZzT3R 4)XqLQ>Rj5\{$qT/ׯ87})/5ZܜQo"y9&djza~87S$aޠ/ҫFb*?UYXsPJUq{'-2`j* )jcg4)&4ӊm#Q(qړriGB(ѓڎ:0:qA/S'ޔxy8)Jw#Oí (!@4#&t<ѐE^9Ph)tqGC8ގA/^ؤ #4GAHE 3O8<htqFSF}9}:ҜP0M.2yQR;Rр;wi4Cюh~gQ4qRqKH1)}(})@9Jz:QҎԧCA(g tgiN:R Ns('/JNԸ:Q;z1h=)3׭8cRcޞ;iӁ&N@Jqz8RJQ=*e^zfz3jd<#5b#ך 9Vc䎿=\dfTa犔H :)=izc8-NGni", W)߆Q3C#?yw&sEu4[2 DMgP3jdyU*WUVg=*0Ojmڢj2HxJii)>JNiE-'\Qg4R`R44`v):Q@#zs9|Rq(f(( gbw9:BIGK1@&;R&9◊N(=(Kߨ攎x)HR(88Fi(=(?Z1P/_joJ/AG~{R` : RJL thҚO|QZ]RM.0iG ◽^z18QKӻӇ>=GHjzT֦G^jeaSH5eP:LsR 2sR:OIqޥF)/N2} I|Ci\L#M~i*''4-BE1Q?ZfsQQ8wzcIU^\d2ːjhW\Urj"U݁~ D9$vcFqQ7CQigF™zoJn=yCc&)1=hI_F)8ʃҁc4b擿-&s1@# !z 1ސsN0iqxJ:Q{F9 F3FRc4zR恚ZOz^3I(F`Qr(i1`֌QZ;QKJo~)qHF)yKI(<{@Ͻ{ ;Kb юi9)4җN( ?'.oƃJ;`QJ?CҖKzqM4)ph=Qpi@҃ϯS8`;ҁNQ3O^S:ԫ4jtlTG⧍@edߵXOz [AV#o5icJԣT֟G*\`Tq4=jLҩOf84o)sNY8> OHe%.GŔ+IM< 8yɨuL TMȨpz2sU7$?=*rFA8NsUns튀9Ȩ]55*&rDDA1Mc*31B*o!4PE!Ҁ;֎sG_i1.HH2zӊS(4Z@oz:J}h%sKi})~:uIRcCRh9i:F(JLiH4⃜f=h1G~QL=hF(qK߽'Z1/_A<1M%)#J1Rq44wZ]F9qF(g<0hph*@ -&yK;R`㎴v9@Rc)pzьQphy)}F?:1֗QzSQRO8RR/'xtRqR(HFFrjURGLV *HjRqךSrzJxiq4 0ڢhir2i' 0Bz #U$tpp*c5P?CP8Zj.T|O\lHgIIڙތ“tAI΂9qK)K8AIqG!wCJ%%rOJrRdҫ;nœ#)#97 bǭ4`s4="y5Nx4njP8UQ &IPs*'wjg5 ֢,1Pza5LhhIR)HCI.qH}ڂM()րx/CJy4Z9b4(◵K4{(ނz`sAi=xN'N()G&1Ҍ:P8<8qG@bO9:f})qE<iAw?jp$tEHRTƤY9IRn*mL0jXǯzTV .ހ{ԫS"WJUݜTN~i)NzR xh47# sJdSF858֣-ښبHLfJN^ScsKu4(')F)hEQ(Rx4 yRd}iASN4?>5֣''1MnO&OiTݸ7wғޓ ΊOlR/:Q(hފCގ4gR)}) Z8RzC(ғKjJ;R'8c =JxҌ ⒔擿"!t;Fx qڔ=hQ(gzw)ցJ^4O|RL_ʀ1HO4ȣҎn@)zOsGj^~4ҏzQ9u'lKߚN)iO@鎔9.xdӆpHjr?ZI=OjzB8 [֞J֥^Z`*E*e>"g<RjP*ZLr9|M>9{Ծh*ˑN/iaq߯4R43qҍ4J7QgC)㊃v:nۇ?W' O5sz,`e{,݁zƐ E^ˀ Fϒi{-ڣ'$⛞&i;=颔c &p QbP(F;v;K:=i/֎֎i3RF~w4fORt=3GNiG?ZN}iG4v4H:J:Q҃֓$Җdr3&z)hE!qԋ90֦IsR$\Ę5/=柼~t84gN@ݓFG^zT{=g=j`cHu:4)3QvHf)cڢy0sޙsQj6Tm.HQ̃>>{lG׵1(J^:B2}hځ֌GN(=)Z3(I@#3(@8z3@9GjAҌ Ҏ/ZC)Agץ!&q֔(>;gZQr)q4KnG?n4Ӄęӕ:ԋ'8֞HqR  p|w+g-h;{RRsCHzd7Jd8ˑi*4N3ғy7=g/C95rI\Hdژ3ޚ_׭F01L 3LcL{7sҐnJiLԄT瞔hI<)(OqF;р qG.7h44g\ I849֔&Fxc1I(OZ^1GN挌GqGE'HFO_—=ҏ/Hz QASP9Ji);P9)hM)í `ޔoL'LR*91dAQ&QOz\ qF1;GP88Ͻ⓿z=EJi M/'!zRќR村hNLQiO@pF)@M.rA/ǽ9OOV^iYlSws(fu ֌iPRis&y4Tr4nx4ܜS iKiIژO'i9?JLS:fGZBqHIHzw4G'4Qڃ4y4iHj;{QR NJzRc):\ 94;P(=M'-!(Gnh= 9&J3'tcN9٥Z\ӹ)s"]"ޔ85&))NڞN'ӥ.Ꮵ(4(l”Nd҃ϥy a<$'Goh27$is˓ژdz47@vibOa<M'zO4Hy4Hr1M'ݩrxG9#'>R(jSJ=OjhKHx(:QGZ9- '=(=#N)𣰣P)O_IGAGQhJ;R N23Abd Q!piq(qڌ2Q}zPh"u~z^sF3IG(@=(ciHqi3i$qIN3Mi=␜班4Ii >Ԃhғ9擩ҎG'zQyKRsKL◮(GR֗ts@AQ':'^)i>F?:\G9vIJI('qҞ(уoKQR/nhQގ8"9qJ1ޓ4AҙȠP(KGJ>}(9/Ju7җ('99?iM㎴~4SA. LRGSFzQh҃@G'nc<h8sGJ(#hځF9惌);RQ)1iO'AKpz(h`1Gg^;AxR㞘8G}(=)=/4R 1H=htȣ 1Kړ}(R@QK֌AQҌqGz9GҊ斓4ƎqG|rHJ(<=i3Cg4=֌bw4JizRv8-&>v ޗ8/:bqH:攒FhEF@i)Ž@JRGj9)=4isR^h)y!89<\tO9N49p'9b)ڌFi(cZJ;zh' NAIߊyQݨrxh'PqM9ԜEڎأzCL2s\t)F :qIFqGz^{R时:ڎ(tCތZ;P9!9=(>{RNԇցZ1&(簠N)s@ۧ4tޒG4tFh"LwKf(Iޗv>ԾxAqJ (T^N9cҎ{NOJ"Rwz\N7qqIJ"J^y"4擷4ۥh; ~TfsG(IK=):S'I֔h'L4uJ:hA(Ix'z1:SF;f6ڗ&)8ґGsGaGґ{.1K֓4vKPxcL9$Aޗ4QӚ3Ͻ.p) H"1GJ\H})}_z8ɢ}ixvG=( ;9Iҝ 4E(Z=(" sHh/upqE)9QZ<~(aJ 8; \P>^sIz\{4N9" ?-=h)J3AJ3㞴g"ӊ IAQ(*1KӁIɣ4y"'^cތюi;ҟf4dHO4hu4Nbސc'48?:PzJPh'Ԟ{RG"9Ҕsړ$A4ϧZ1NG^PzFI'8F9uɥhҎցFi=i(IF(94?AFh'◥ }ҊBy<8J:Rs掽 NhE.sI4)yP9(h84`3ǥ(NsFM&r9&ր9As.MJ&risGQA<:G#&8:ўiZS 4J;Ph(=i;斀xFqGp&"&'Z88R)33 ќ )AIs=r(֓8@Ȥ/\ ?'<4ItsޔPF)3dzKIGw֎g'Qҗ)Py惎1Gc@\uGlfQGR(9Fih"@;ug4ށEZ24v'ڂhǽP .2h;ӸJLB;џʔrsA E.{LHx_LQ҂zJdf3RR֓—<fJMќgTuis%L3p=>!;84Z9{RACKGj@A'ߊ:P~@GzNEޓ<}((ނqKH8@RךhiZ^(J2 ޗg4G^iџ^@G(oZ=yA8Rz  H~1@g8zfN34H9&vQHiEJtH~w(IJ&sIf;ьsJzRc?rqJxRڗ%('4t.s֗IJI4qѓIZ3I^({ϵ~wP ߚ3QE h^3֐9G8u>6(1GAG9@9K@'A@џ)sڒ=xh'IIE3AP gQҀh*ڏŒ(?ʁӧ4Kj3A3ڎMgh4wRhi;g&׭&}SL"<џj\dP49(4G=}TvlRzhM4;Rh4F~uKI&sJ(94`H8ёJ('R{"@@GփӎԀK׭&i:4QҌJ:sG'L4u<ҞxޒE.}sFr)9dҐtwF}3FM⃌p1@ϭSsړ@48җ&~'QRJi{c&ywqEi 8G$t9⌟J2=(3E&yRQځAh4cރ֎vGz qJ)_J^RdRך=(ǵSȤPxϽ!qRvҌQzLR&G9.?Ԟh#^1HG~( )?ZJ^2(sZ^Qޗ44EGAF=:.=p(z|߱*::QbҀ3Rc_jGюh;㎴q@JLg/דAқQ( %ǽE){q֓Q8H4Aɣ11K@2J\?hҌ}):GCJ(A/H)1K3F;N4PxF9QN;֗\Cւ0i1Jy{f==hL—IEQҗpO\Q(4vQKA4h~T\R~`sREP:{QP8AюqF9Gi@y8HG(9ZLKh#8r(=xRw▊;PG(1ށȣ$E&0>g&)yyCt(#8d=ڎAf;Z3AKށjNA⎧4R#))\zLъ1A`1ރ@isғFx (ƃ@<^ڑzR &;юA ֌{RS{БHQG'Q@IsG~c;PG'brqJE=}hzR4OSM=J.9cZoI^sց\)z_zCR֎wA'4`ގv(w◿҃ڌ uMF=:zҏ&8zpR hKi84NڎGfGQҌt c R׭.(?g:Q@ƒҌRcۚE%(Qg;'{JFGGJ8j;RGF2{QҊ;ZiRi=xwuAQ Gc:;"QR3GZ1IЊP? ڃIQ_ʌ`t tJL` %.=i1֌bF;Q0)"\vyc1RRc0) .i:J dJ:{P1GJChQ4vs@E&)q@0(P{zRpxGҌv=iy4Fю:vK/M4cZAך:zRw^)i8^dW)1KE=Ei;~KRv4)8ɧ`Rڔgh'R:@sҀh}iha@ AJqK֓PxcփqKRpM/NqFx'M-n2x)1K Ҏ1җցq֐b1ic/ZN3Kϥ==EqGqF=h{Rcg)?/JP3I4i Ӛ(Rbc"8R4GSzz);P(qEi03Q={Q!◂( N? ^i^@Ǡt~q1IsJ93y3ފN0(K@=IAt;Rb4cAKd?tf(4G яN(`1Gj\ޗ)1QHy9Qht:1J8MJ;Py@2}(ь֓R~c4twgJL \PZ134/ց@<с>x(Iޗ1Ih#=4vsZ)1F:J;vR<сKH?*h&Oz_ŒfږsNQ4~uP8I@Qc ɥ٣h?ҎviR Av"R)1Ki3=){A8ZJ01J:R{w}x9bsF0h4 K'Z3҃u)R^N)Hf84zQQI)}}h&4wzsh)M/AG4/^Egށj;Ii{ьNP:RLڌcJ>Ԕ)3KE.xSsK> IۥҌќg4wH4{wސя'/^xP:CFpsKך?1GA擯zR)-%(sM>JNғKF;)){▙ɥHxE揥ifq@2OJzt);f€}h=)r(=?'J?^qFxQzrEʓ<3KH^}h|RqK߃IKHFxg4{fzb֔Q֖<◁gڀy4@h''K斃Z֔ 恌{P:z>OR( 旽 Fi3Gݠ)h/lg?Z9s9='8?<Z(:Qװ4'((j^z18h(Q=ht@4֌P;RPr:RF)hތAQڎ8C.p9ƐpisZJ3tƊ>w41KA@F8@G4g'AG|4{P*\OAG\v惎gsKqIqEK8tugځրhgIK2i3\`I<(ȥ^i214f1GFZi3Q֌_Aޗ#ϥDN0}izJ6(4擩`{=F{b2qۚ:zQiZ34`)H1F>cKOi}ϥ'|Pq(>ԹOJ\LўyR})H P>u<E8w2)zcQKj4IFI4{RE=zFh҃)GJNsAhAFGZ\AK1F1@qZJ9#{Qi{t:'Pj;A4PM84gFxtv(i3Ky4dQI8S{ix9NCFGQNh֓48xҌ9:KsG|֓>(ޗ'(}(~4i3FNzsKNQތbߊSGɣތ*u #wg=qHO# -&yuG ){ё@< Pz挂8793FEQ;sI֔RJBisPhΏzN2(4q@F3.8cdfP 4v4;QގI)IקJ_j":QP9Խ(4fr4H=ߵ/!i{i?3Gt4f\ނM4)!R $zPMudрy@;Ґ_!u}NsHsR(KI94tzd;zъ^֎Nf֗^v(Q4wgRcJ^F #Q Lc4$ ^sbG4{F){i;P(E(֎(8JQJOOKךC(tJQuɣS@J^hAJOwJQIFsKIsRɠsA4tQуۥ.1IM/AFx(i {R:;P=>Aӊ\|sRԣ4~4d@qFhGJ^9RNh"GCސ( yqғ)FzLQh@ɣ(<4g4E)j;ҚI )ý'z_&qK@AIhi3iMsKjN8z1\4RќbhIGNhucKG &EhE:>ڏj1dQҁ}(~g8nzRLQQF~Jc<{$A㡤;<Kޓ4f_s@'4gS֓h#?*LRf#ߊ:d;'(~tPhi{Fy){RdAFGqG>ԜFE/h9֌Z(ɠ}hH~c'J^ ڎ3I/j xGNh($QךRh4Sӵ'Kڌ3ړh Qh=))hրF)>{sG~hF8 ^Ԅq֗'9{MF)r(R(g(=)zg9iz Nzѐz3Fqz2}(R=bҌ֗9iފJcL&qIs6(hhzR~K%})}8R◧Ը1AIRP~Q4 裵F}i{gҌRy$GQGN=)qGnwt%Pz9=)1jIqKׯZ3~4◂:RrizRt`Ph(ϵ'9Q&J)qΊ:zQF8F(b=GH}8KA'SF8uKGNߝ!.}9A;sF(QKzQJ2xF;ӭ/78H8<4zQ4zc.99Pzu3G|Pg( 3Ki?ڎ(Ƞsڏz3~qN IHix(F('ҎցSARd<~4j;sMޝ@(zPF@qGz1N3K4GJQFp24Fh҂{ :  ~x򤣞i3&/1P@A9Q=ht4SqKR(zR(4qFyяҀ1Fi:8uCKۥqF4H=hJL 9 tJzEIx))4֗AHz⎘POc4z^Fsڎ3JizfڃK@ xSigima-1.1.1/sigima/data/tests/laser_beam/TEM00_z_70.jpg000066400000000000000000002332301514013333200224650ustar00rootroot00000000000000JFIFC    $.' ",#(7),01444'9=82<.342 @ }!1AQa"q2#BR$3br %&'()*456789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz?IZ?PsP(:Qp9(&py&G^RqAԢcvzRZN^ԣRJ >h޴dR#L◌RqޗZ8^hI:)E!bdFx;xf֔sҗƁ?RJ^chM.84r>rqKhZ3@(FZ?ɣQ]tsAIҗhҌg'sFs:QEI4t$qKҒ9<֗ZJNҌRI)zwʎ);NGZ3K׽c<(F ("28ޗ"R (h?ڔsJq tiq):CIGz84Kޗ})(ɣ4G^#A=1F@@9<ҜdQHO9J2:&AF쑊8IiAj01GqFx4g fҞIqGGC4gJ3Qގў@t=ir:RPz{vQ:$q@isG|!=h|JE'N@OJ(9>c҃8'sAN֗'֐\'QZ2i/ncgҎM/Iz^s֗=#(hwqGќ@sFx4~4sh$@)4(.i3Iҗ)i3ޓZPsHN)ў@揥:sE◵ZS&yE?h9QތE!=)L(8ghx4F=i=I A'>tqJOGIGN8xNi3)ғ=Iڎ<: FqGz2) (qANIآLR8JKM=)E (88G `JC֗=(2(9IzLQۊJ\:PHtޗgwQԏZ E(=(cu'CK' zQRғ8㹣AczёFh9tqZ:#usJ&{PM<{ҏΏҗRw)GCG҃P(hǽ-&i@y{~T41ӚN(Ҁri3Gq=<ޓ$$vQ֗4dzg u(;QIڗ~{ 3Fi8(;NO44NuE#(9z'z 4g4qz@G-'"!Rdf٥ڐ:h.ғ.qH(2q)z4=rO"nRJ(E!$ )IƓQQ3JO?ZK@ngfjgڂNhϨ wzQA>hzў3(QP3(xr(Fp(8hɢO'~ @ Qj9$H4M(E⌚ )4Η&Nۚ^qK9A4gtޗ =~3'$O8hJ  GM4z\&}"@<`PzQ҃8CGjAN9E"GzR}=KtOzQӞ 1ҎgGvHPz֓u4Z9'Q(4w#\ҎƎwAɠ84'׭(Iz?tϽ/jOz8h)}hzzL֏KR(i;A8c QӃG4`Rp:Q׽ԠbZ03֐/U!@9Z4ӜGsQx@(GZ:RC@hހ8h#ތbx42M!zQȤъ^(9&{Ҏ})0zv(z: ҁ1Gl4:GA4GAG=pN'){P )1J;rh(Opi{?'=Rh?rhۊq@ȥ(9&93J=i; 11AJ^&i?*S9znNi%F0i{g4q@ќ? zQG֓d旜Gni3Җ{QzNh=)"֎s/z&>rO8RgK3Iuޔ1I@(jQҗ4c=(LҎŽdf?.;{Q8A'$Rhp(wF9(9ǽ7 яZ(qJ)J(ҖH/nhCRH8gi9J^ԝEԇ&)Lwt~fMqb9?{i֎‚sK);9~t擞G;qA4ڔzIۧJN{(тOZP{wڊ0h}(z1F2hMH?Z4c&F*9(qKғNzRhp9Kۥ&tHI旞h ֌w44GҎ4`@IҗPZ:QڎZL}}Hy: =:Aϥ)ޗ&z*\ڐ{R(N{QxRg8RQ;( =:Qڀ)}) j(ҎGSIh=ҒEI߭/9t@(8'\c⃒sG`(ҏ֎f9GB)ΓG j8!ޔh3Gʓ=84ގhx%/KӚ0 c):KG"R{1K4flR{Rs^ /Z? 2q@#ҐiOҗP3ךQzqAbN(.A4i1HN4qH(ր){F=?J1G!@QiE&3i‚sKړ.=(Gz: ֓=4斐-i0i1i 8=9R R&9Azizt={ҏғގ(4IփK8Go@A֗=6)?Z(=:P9ךfʒ:qIR P94Zo^HIތbt9<ipsIhsHyȣt`GEQpi~izdҐӊ9J\!iq>Q@SqwfsR)qӭ/jLzQ9OZ: :=hqI\s#rzbz8hԸ둊1AcԝT z;zҁސQ=901J(G|i$Ҁ14c# O—c!G94:R␊0{1Q2M◷JN1Pqҗ}(hڔG&/&>s֎{R#ҎGzNqKފ~8h1F9%/R)4 1@旿ZCh4LzF8@b:Hp)G \Ҝ@)93J=i1KSIޗsI֗`Iz\gtsъ:RGqIA:у->sGSF)iM&1AҐ ֝@;QqQږ~3K)sJ=hzgvh A'Ȥgci~viqۚL3F9PGq@(Q=hǽ &sF3Kq@Pqɤ:E'~(clF1Gi(9(sF{QsKs@I3@9FM;P2zHG/NhhF:F=(t4 c_~ԂiqF=qHG/8xғ֊ ixIA83Gj+J6(" _ŒzK(s:c8HJ\(H==wQ^( ֗&֗~i~v)9K׵`G~ԹiqQsGҌQsIyF)qJp;sH}A `t)@s:uRfS3/|R R)(RҎc^'$ M!{vd/^ip z_'H:RyK94mҗZ!'ҁҌbAzьZOl׊;Rh=)1N'⁞=i9/Nޣ9ў).s0(8#ь @/(F(Niqt9d1@㡥8)1SJ(Z;RA}i~T'!׊^qI֌h4dv 84◨c`c4sI@!bz@2=J}4^4()x֔HHi£uL \3ڌPhAҌb?ւ=ehZ O48A;.(PO8cF{ (EG֗ - wRz8Idf&Hcތs/Fhcj/QH~shA^g$R;FqsJ@H `R8j:J8BirJ;QvZ:Lz' G=3ւrx<1KNGjHzQE/'J8dfzQ3K4=hh4ggdJ &`њ(FyG|QҎ(RLuѓI~})sM8g ҊNO4ƁҊ) v=3H0Oz?.F4qKޓ>c#/8'~wZ;bKf4ڗ4g4"yb1{K=G~(4=RzQr)i )M ={ۭRwKJOChz_Hng;4J GZ_Ɛ^h=ҁKEfQiǭ^Mt79N'&c)zH ɠ3@ry.x4އ]H 43@8ގ(8Kހq4O ֗ P3Q߃RC;z PqǯJ3AH@=OJ)#4"sJO9^4JJ2:bJ2s@4gg_zJLJE%.y=8g4g&s/ Թ掼Rz֗?ΗJLGN g(h?(;842(E9'U$u/9Z\Rwtړ#Mh(gG9#8NKҁȠqJ;uFy@Gj;f9%@s/PF(J;40))h#?c&hRHҁҗ'\QҎg4~gF)xGw )I׵(J2})x{by◥AGZ)3)xhs^߯J3J?Z2zbGAL=)hҎ{Q(E揥(4fvF)8&ҞأEi::i{p(R3G=q.q@Kȣ=.9=)hI8bGzZ:}hJ::sqI~4(z Z3g4 hҁiOJN4ph?7$u4".y&piE7(3@#4:RtGzn);:Ҋ:fgQ{Rd~4FhE:Q߭!GQ@4t&⓽(4IsGjSڐt4c֔pz \bOzQN{FR&(4}E'N}iqEԘfGAK(E&>Py JLg4=h(hE(>ҒtR4): }Gt9@ҏN8ڌsɠZAޏK@81֗hA瞔<юzҁF93AZ1I4ށҁ掴GҎQGJN3@ȥ=xtڌzP=);tJNPϥiʌRP3ҁ@ (@Qޓ4`SqJzb=?Z\PZ?/O&yP:ӽJF 4ch4)0=zEuH2FiOZ\bsRv(qIRz('ӹPs֎٣<r /9K4)Q8!4g)Fs֌R Ehz:hsA8?Z1A{Qyw!R4iA8$t ҁ9ϽqIiNqRi?җ!iq1Hyҗi)s`Pz ҁKۊCz\I4QGNc_I{Q23@?^h=IqKތfsFI1F;fv><ҞM z\zs)(4sG֓^(P3ҎҎO?:4% 9)FsԘ4q< qKRtF=?*wft֎.})sAKҎh=xh4I!qKҎ:R 9=i MF;:}{QIR3KiZ~tsAF)i~3ҌRRI=)1A)~ڔZ&—qGQ1)GJMZAAȧvJ.8)A)tڃׁ1@Z(&>ʗдJr4c#ފL◐):9/LAFysGZ^QI(ҏZ '?\{Qy".zqAQ1J:1JyH}s!G>GcRqhzߥ(s)0{4gҌQcҗҗGAKFQAGz? =(w4ݩ1—JNh"ipsIK)ZqGSF{Qӭi1sFQہH89GK &:A)tw("zR!@b(h4R J1 ^q1sIv0;RbtRQҁf{QCF8t֗ъ^ړ8yQzF=0qF9族Z8{Efh#p(dQ~(#i{Qi1/vpiqN KQG')p1i4`Rʓ4Rh⎧8A8ۑIךB=)h~b掆RcbE!h\`PF(Q֐\KIsߥ1ޗFZ(qt-h4E.)8(ʓ=l;R?C۵(J1ZQH@=(NhNh4c@P88>QF31C bdc)pIޗQH (<IH=A_( aHO.0(Fh:R&FhFq?sTqGz9dhJxi;)q)N/9◽>c4;Qj^tr(HG9=h){sH8JڗvAAJ=u _z:SGJ4v(8(#vґF1IZ;Q(FZ(Ji0z/^zQ1Kӽ!֊^9iEhiv⓭(#8ސ8(=iHtZ(4z"c#QڌZ;(0ip~`ct#pE>hq@RrpqKߚ1\Rp2(I;'49杞(Q~4(h%RiO8h )0iP)4҂3Gz@P1A\鎴֏ŽRsKIF2)q)?JQӎH:REǥ.)Nc4F i:Qփ׭/nccю)&/@i=Qy(>(>qǽ'~h# p99`QGbҟCGQ1(h4RJzPi )c1IP1KZLp}h.8LsFhhZ1.1F9cސ/򢓎 #Rch^I3J&>qj"dQRR(xGj;`4$R֏)Ԡg4GGQNzR@#ZL`0zRQhғ RɤȥGz(H}Ebc#KE'4:3@c"sF8)p)>0h(җRF)ZCޗ=)qJ=hq҃ҏF=h@QKJ;M#4sR QŽtF;)zhuG9F;(瑊1EZj?i=#(sA掜jOޏ֓(}(F=#9&ݨ4#P4v4(=hSZSҌRE(sF?ZJGp NsF8.8!ۜRc h9w4qR֗擭z)q֓ҔQhJ? P穣9QތN=)4v9 =uZZ1rhOCKКLsK;PFxF3ǥ/C<{KʓgSZ;fJR';F9dяCKڏjAcގvӊ1Z4F)8Kf1:SF>JF:t(i1J}(?ғ@K)hHr)ԝڊ1֔ o4с\`ri:ɠz;QIގP2F3{Q4M qߵFh)9#4q֌s֗sGcHF(,R:#ޓiGCG|FO.8H}iqi:GR:_j;Qz;FQ-&=4&;v8ɤ#(sފC/lRP=i&zp:яʌF8!iM'SKF8ғFM(ǽ('юzё^?IR!i}(G^hHzRdQzK!4(J9'zќvNzP(ɣҌQG ^ܑIۃG$Q<=((/^s:(M)!84tҁIҎ(֌ 3G;яShΐIu(ގp(֓l=OA4u/GފLgiqޓKAG^ {Rџʎԇ$ZQמ !94Iyh/Ph RgZ\JCy F9R{RIA@Z0}hc;( RcG^;Rp8g)s(R\bsJq4 M(4 ɣ~tJw==Kv:pG4bG^*3Fhdu8#J8#&vȥ~{g4brh}(K)z{('K4zphAw&;#փNvGZ:;{ќj3ϵzZh ӜP 8uǭGj^ؤ nKNsKڎbLqJ:P2isQץIz҃FE/jN:RwҔu'O)w`PsGhHx)N;hfg8&0E!:NsIyzFNhn(A(LqךB9w<&yqGwix'Z\qA9u43M=h;408J:Q( :iqzRczPxF)G\PM K~=繣8Pi;bPF0isҏ\u3RgԿw@>)qқ(=g&J? 8";N(=!J=)<ۊJ8?Z: J3 )3Gn:R3G4Q{c9QM7&4(ǽ:3^I&(M.}MS{b4ZCJ ~#p>i iyf8#Fr{Ҟ;Z3M'Z^LҞK)E&qGKHJMH/n?ZOƗގ&z ┑M挜AHI4֓}hSA4n \sIIۚQZ QFI4G:P i.Oj :Ri;4qyF9IԴ (/◭'jS1E日RH:Qڗ'zQ֎sJ(8Q` RL 4Qy~T >}ix#)3@ ɣ֐4tޓ8擥h'QS:L`Qtj;dii3\sMޖA<("{bh>'HzҁPz9iZS֌)A}i;A*S)3֎3)EQHix);QRR")~(IFxFE&E.GyNM\bi34v4J3-&@(4A984J:Gc:9> Eh(RRiֆ(')ӥ4u>ԤbڏƁץ.8fZBH=Ai7c Q֌IFh3K@z*1A*N(IFyҎsjLKތE1@֐>wɣJ(<:Iގw=8Z? NqG֎ǡ((ttiqu4u<(;i4y rMz\c4h.=hs=(4wqF=h:SׁHGҎܚLzPAJ0ii94 @i{1Oj1uy !qG4g=yoZ3HisIhg)2;Rގs(9ǽ99&8P8Z^I(&:Lw(/jCҌKSZ=NhCF9HOQKތPzQFrxGF!G Q9 zS?N{QP?JCGZ_H>xۭ(3I4g掔Jh:J'N0)hғsڎ=GA4(#)zz1hihvGQGj|sKۥN4}GOzp&}#4G4sGsIȥ&rihց4sG&O.iz;ь}hF K9׭!:@#4c>dg֎Rc?JҊ^Q\q=EhJ^u `3IK(>gsGZ?7<((=:P:bxJ;֌s@GLQ(;r(G')1"E'jUԃ<3E)p(i=R瞔c"3R1Ih4p{;QtE#J\~Qh ҎKfx)p3GwF=;sށK3ǭҀ1֐٥:ьsZniz4fϭg4P*iG_(9tGhKސcގ(֖zڔ.)zQH}iHۧ4'9.3GJB;v٤G=1Lp(I4J1i0I@>FxJ3IiyF^ZN)F(I1GG8z(Kӭ!/g'Z9=iqIɣJFi: 9c֖i{Ⓝ4@riJ3M@jSJ=)4pzCӯJ\ZNgRM<#uJ1ю Hs@◡F3ތTZ_F&qҗu4`g֗&N;8҃H;ҞRd瞔8Q2h IK!#4G^QⅣ {ўhzQ K҃pFi:\{R3EKր)?Ɨ~;8◚LcSRmZ:ugތ`ҏΌw p":t 1?.3R1p= h+4RK(#"1< B}ǭh<1ӚN9Ҏ)=׽`Rii;Qh!)OqGAޔH}(phhTqڎt4n;Kޓ>c#"vAF(=(I\Qߊ /Qi4zJBȥMn.}i;hhvwȣڗ) !ԃv ъ^):GQҗ(穣&q/("n:QRS~R4`3Fh~?J:QקZ\wuzQGJSHF2hi~ҎQiqAJ)}qcNҔ3 b4c ]N#" 9 fwGZB1HˎE$c4Hd}@:ҚF:SM(# RcoQiF+c#sBiqGQIGӭ/);{bfi@&; ;Kъ)Lu3H8w4LzR"GI3@.=&8F3Ii@/jNhiyϵ&(cLRւ):j(4 3A8E4vIHzSڌ M$P8 ZLQҏ֎9硥%/L 2GcG^)Nri1x!fR4t<ΌPMGrsA<.=)M.12hxwJFaGьwސf:~4sK@sh)q9Gz:v)p1K.◡;o+JE&>j\1<ѷ@4m=})sNy>_MM 0E&R`zP\c 014AqHA׊B N01IӑHGz1I֓'4uh#b>pI):ҚNOҗ8;IIcIсG|яZZփҏ'~GzBOaKPs_)GJ>=iz3A(w sAf0{P3HxҐ(4g.)3/&;ڎ'F/AqKLh# q֗#4;pI)OAg%8 JLs/sGl8x&G)zўis8RA9ԤG~w⁎(8h/LsN4qP=Bp)v)=(>zӀ ]sJ ⍣9UPTJ`Lc93f0ԥr}Bn9F?Jo@iq)“P@#4bzRZ8i'ɤ 29nH֓czNct'j1N8I9>QсJyi?J3J 8i33R9> 1LQKt֎RHh8ތ):QZj1zb}ixqKIҏ 9ތg&8Q(^hqG&y/8Rb(ǽZ(K@@q1(#c{Iix9oKIg}hҀ9/Ri1R֓'\dh(8A(.8&(F:&dG\~4~^)qM<jLRc׊n9iIHԇ>{1F h攏zCu:Q Q)6 R)h4)?\RwF?:\`Sq߽.3F1):R={tǽ.)K'Z'ӥ(֌sii@KҊo4\F(QRc@m9Q Fh4ZqF8A"F9Z){ NpGNi;f):1^h p( R8Ȥ.8A@`u掿ΎsARҗM8 b{~4LԟIҗQ۽)`  -LsF)}@GzK^F(t81RzS8Δ.NH*sӊ1J=*qN `*USN1Щ}h })8#NH*iroݹ4^=:i)141HуN) HSjB4֛B;cBqh)1c#k84${֓O!H1JGyQڎ~PGsҌ(4QQjB(8J4!03K)_—usJE&:P{ҁRvAqA4wuqK#ߊCǹQ)'󢗃F0h0 с@41FfQHoj\sGQB)qRx9(<)A8ց8攁qA޼SqA>h>Š旵&控){RiN(ړ4Q–z:i #K4}(\qGz;zw'- N3R0=KҐ{zfJO"hZAڔC}(43@{٣hsKbb u?J):Pϵ)499Q;HR>SqJ18G;N< ϵ.LS}@sN j@tx.' ҅N)9HS#;xhNNzs@@˜S␂zgf3MÐ{1kRʚFH9H@Zn;RmqF3M#<B;L~tJ9(g h'=Pq~ M9Ki)99F;Rh/^si#cގhAi/ғv})FqF 9d')y(4ur(?Z;ffJ:qM=:( -!ǭ-!'jLҎ(hQ4b^(EKIKIF8zAF8tKRztLJ1AA^qAwsJxIjJNzR.sEE&qҎR/J &1Ҕr99@A(ڃ(=8w9⓱uJ_J1g /z>(Gz^8'zM"(8┚L@-''ҝi P?J_jCҎCךSxtV PH< P 8x9=)D| aCQV5>nؤ?/vsӊn7rzt#&;4ӂx9m;8F@Tdd]-F0)F)ޒO)iF 4sIOz\w4'4ӺC Qhc(Z;ю(֏4vg;р(h(P= 9cސwph4u"84ⓌsH)~P3GSGZ1Gng"<@#\w4Zgf3ڊ2Fy9'Z^ yjJq.F)~)c>QzpA!9⁞=}()=hހhyuP{zRv4v.G~pGZNGџjOz\gPq@RcۊwzCFE/8KI43F8⒗?iE.QQiR;RZv=j@Ⅷ>;iR*ԀbA#qI\ڃΎcq8hIN()I)GA ◩H=J8<⎣KȣփڝjC֓;'~:Q\RG$EwJ@҃Ҁ1K{g.^QqG~tv2)Gw4uzJ1GOz(ҖPIc9 PzҎ:~Twqg/J;R f٦R{Ғ)9J^AZL:tJ;E4^\➃F*E.2}D^sR2zc)g")Cu<;LHy1@=?U`S'֠K5GL2)qT,6 .JR?ʤ$gpO5zXt='ǭ3}'; B2E{ F_j:pqښ0w'_›qi4IQ LRqxGCKڌ@=){Bh=4 3=hMR挊J?^7'4=y@Rs#3QiA4u׊3ȠH}Ag)A(4ڐ}(Qhh(rhGҗ97r)yjQIۥ(" )M}(RҜ w4qڃҀxL_zsAրyǵ-ۚ98QhZ^:utG-'8֐()3ۓKץiF;=1JhQ=GJ1t=J:探w⒗/9c3NqNHHKdtBqiǓ'7w3GS,y)蜜tdg?IgRLd:Rj\m✫MHFGj~oZVPOLRb ҈\T^OsK$9O\UuZIm E=A АsSWxvkvt5qQEFz ӊiS:*Hz`} Ȩ' 9dSyM!1Sқ7Mq'N~=i cҗ8ґҏ@i9dGfz2sGj:R SE4ihJJ^QӠsi(J !?4P}(Ҍb_FN(=(F~QFpzqGzRqM.*Oz3ӊ:Rfw4u /jN~tu4LqHM(:JI8zPOc=~搎(b94gg3ڐq\wFM.{fQw8@e#} $_5X^ҥh=*H0zUOsވӮ)ΜRqC/#֜=駯N}i͹R FZlIEt xj "qHɕ,?4ɣʑTJ/jcS/ *qMu9Ȧ`cf략ySXzqڛ׽Zo$`Ni4I:tM#4()&1FrxzAFH=(89?(3\揧J(})2qJIސzf? 3x4cހ}4'o@z2OZ|gAdQ 8OŒ҃GIތuP:Fyt4zPrsZ01ނyM'qFNzМH(CGZ\ ?ۑ֚q94c&җюwhq(&A(:Q^Rt$QGPzg֊? ^IRbfiFs@ Qx%.O)I? ^IJ=()3ڗ^t(cQq֗KK)Fzҁ)ˀijU}*UsR('Ws=d>k{TF1g"™xU+NЂ=OhzF.ЫӁO+٥Q)H4t zf8"GFhey Q0,x !?$/sT101U#^xqGUxcMh:qUc`i3P֣=iFizCMN:SN4 uc1 B9IG֎g ;tތcғތьhƓ8t@^A'Ҏh8'/4J^RtGnh4syԘ:҃掃uԂPpG.hi;8J3ڗ{R4F1֊Z)=OGz1@y(=J((ϭy֗{Pz!98K>f4n3ޏj1F2zJzNzRaKbnԼw/jv)xOQ;=W9W(Pq5*QONQ U9b sVXvY zUTqHȩ*/HWz'dɩ' >5#QޚO%qH=i(@Lw4riir{Ru&8^H94)O1I@{Q@cIh)r:fw4~TK4 7w tPx&i: ^IJQH3ҏ)4Ru4޴RQxGJ=2iO^(A(8RсJ0=hw4(< Z@1.0;ў9ǭ/|hr(q;QH)ݸFp:Qރ׎qց&;Z\f掣!"8:т擾s'R'\s@PGzp旎 p03OӀjEtSRvåMpRr@XX54QjΜb>aPI򃊙<յi3RTQR/QhۖB(NxOs8F b1+cx>ċiG"Wpq U)j%Trҡ5OUMBhҫ%Q+VuϹہ$\Ge*2)aژWoHðS0piFx4t&3IBiON3E KI4u=)}yMΓ#?ZEGs19K@$! Px8#ؠt/sGz^ 4gbqF))yhM(RwЊ0y )h\ Q(=.(8ތqKQE3u`RSKpHTc<2HS'*V`qSt)Sĸ8yyb9##[!z3N:TihiG4&LҊ 4ZLJ\F)Hт(14R⓾ (M?J1m&NzqJs1E'z\qG!sGzRHgqc==i:sJG'j_Ɛ)QI-&(F8IJs`Z1EG^{P8dQG֌RрE'N(A|R=Ҏ1Gj\zR` J}h!)2zӻZJ)qJ=F9:R9{H:R42qKQڎ{R &qNqץ\ ^3J18 Gzz0jPqN jeLjDO֥zzUӏSR}y(ہV.bVBqVUt)9jpjX=x=T_zv=LT)BGJDnxcE1;xrJŇ/D)i=7R xNsF\Q=:?.():KH9= CI4 F9ږ.=i1#QҚs(:ь3t:qG}3Aݎ)1K8J(SJ8KF0sHpNi{{ьJ&9/r)4dRgQʗ{F8 4P?Z^(ғ(h4KI"y=iH_IE;uc)A(Ӆ;V"_zG5j4H}*ڬCV(R}8 56̮;ӕ0j]@MIEJ J5:yМx4GC)8r\bHHn*9cV1$1a?c8EGEG'_£#"puoTLUR)皆Eɤ+]Fj_4cB~u ~5N=ꔱ)Dv*Q=1u+xA/sϥFx#Wa1F?}*6<ښxi0)F4wsA␎ &8&(h=(By(RsIp)h9RNh<J^Ԝ(/Rqь~Lю?'ր<яƊ8ϭubRhRN(xpqF99>{GG9M!SK\ @(>(·Ҍ NzqޗNF=)sIޗQӵcc(F38(cގgi1GZJ@8i@iO=JOj\PhF(qKҌw`Rj K(sKNޗ3OҞ?iJpjeP@jTL*s TLZHO}ULUW{늙2;T:{T֬=579bjSR1vϛN#pEFjgm>F)R!?F)2S$T[ o+B*B=%R3\h*9< BH&9j!=,u]Fd:qYp;r *WIYS={T{8VvOZa\f#c 09t&zg>8:qZJAӥ'(J7Z^#'bޜz`Rp84K:Rq/jB>u)p1ғ PhJR;bԸ@4pi)HF}h 4&q㎔旌s!)RI1I!F@ތrhIڌz(4 LqN'֐(zQp)GR'SK"?J\P y~tc=qJ='8P2 4wuJG&0zո)qߊ2ip3GCG Rcz\RG# =(/z\dH84'A/AK?(8{Ӡ f}*AJgޥLVgRx?VAOWDX\>2'Ȟ8j`{A\vɣiJ^()4SqJHޔiOM=Wޞ*TDj4}zՀp*GYN*ddqVPr8ʼS ަ €rO| @Nj/'jSjX㧴x5"GJPHQ*SR*{S)aQRqQ)j(&2ӭ4(UAPZgIҀ):^4RJ: ^F{0;QF1JF=i2sҎQڏj:h@G^)9)4 >Q9h;Ru uGJNqJ8;Afh+fҚNإ'N('# !sE\J8ސjvsHhր*8h}'ڔ()ɣqG\v/OzsIHjQA!JGCE"ԣAh(ҌϽh4ڔ)N; gi841&riG^zt}JQ(>SҟO#֞jMS Qj`*dZ VM[qZs]V#n85*sۥLNjdT#+=>" JJ4h18MXcL Q$dv,Y.*O,+}*%pi$8ǥ1)MVj*qC5YH ǭ2S֢"sQ@&f<6qPFsCW2*Vtj"=6j#ӃQsL&'SGAMfM3pr)nyϠ=:RHFxLQOQߧ4RԽ9@hўiN4߭R<HN) 3QڌRgڔug1GCGn{P{PHt@lq j\i RdJ=(yA9<Ӛ/JB})93G^hO.=&hNJNڗ i-ǽ'@4w (E/'Ҋ\FNxќqKۥOjPsvpx쑌SNzS펕*{ԋS'J:OcXxը#W2F*q*j;qRv.1RԊՄRHy xMw S{Ӳ +)g:RBzSPM:87{ C3"S?#IzT)G*`q*)HrVg4 )zX`j'nNi9Xj֣P8u?JUi?A"H8g֓҃cLTwc BAќ9#(j29()s) u(͎֒dzRQK֊֔E/CҗԽO; Rzf/5 :U`'}jve`*p)goҪ9yeoTZw|rA#j &9Τ&8484 =) Zo^i}(!4($(AH(&I߽Z#ҌP=i4i3F3 ?/lwAQQރfQm%⌎vii24dȥA9PHbFh"}iIuQC҃hjSΌH}iEgixʃQ&I>}i=iF3H:Aހ:bހrh4)>)s߅'h9)NEM'< /~)ǥ4}(ҏ~gҌ\Z2(NG9N1G^JzZxN<qR)2je4cVf}jŽUsVUv&#VbcV`bzOsҦ*g J{/# sBEcm'|sD;ӕr3M$S qQn,=)/|z$)&~i8RdsJ sL[VPԑۓQ g82ɌFrv8HA<|C5RDSZ"T)ۊRdTd񚁏4}nqg8⩙05TIɨ&nE@XbQr*Q#8Q5LnE0dⓠ1(l4ӊC3ǽRd⌞~n(4dz(&A4A8is4 Bs@@8␚NqKz3L◿J)JPqץ*Lw@py'98A? F9N(f?\zM(4dt9!>uGg'oƗ4tH O4FqFIE$ux{PN2B5皑9A"%䚊RuUe3UXr8J)5T-E:(ۊ*Qm;zUg\7_6~j9ٜTy$i\?5c*f8ȨLf`TS#dbnޝ)@7Hx=i 'z@{t@fRh(H}Gz3K&M/H:&}GH Ҍztb4g.zRN)O4]gjeAf@r*[G=J#֫8C:n-5^3@T~CUuez2ƨsLcn=6=01LbqJBxi48g&9J:f:RPG''(Ig&PZNhA>M:"=d'&+Jc?mAӥ [4ٓDX>ÃUOX)&JkUrj9N*,ihh9&9'vqI ur(G`֗"(iA{RM.8"3ސc{LH=x*N H0;ґH3GFF(@NƎޔu}h8Kړzv=zQ@ix&QL~G(99) qA&}(cR)}L(){Qc4>s'J?/ZRxGC҃JJp⎧)8/;9b)OR@2x K9⧌Z g5v&YFWlЌSEO3SF*PՄPE9T` RE LSKd{ӂ|܊`:Q$S"M9O_SZQ#ĠzT&Q9PPcv)zgqUe7F*PX^*j 5Μy Q1UN}> Fj SWb0 WQƢ/}EWv?FWf9r5ϥ1*`J0uoJi))8'J:%-3IZLsP9sjLKގQ:QIp78< ^qIҎюiQHAz>c8LvҔ`ьJ? QFy'4c$_vXJV#A(Q0A9ҢuUgP9'O Uk"Ue\*"351 TjygZ*=iq0i◜N);Ru{IךGJ!tfIJ4f9 Δ43H8}NcLS!88qJ:RKFsGAր9=sF)OJ? 4NiOlbǽ!(4uKҎ"P8ӻA9ӊOz:u8i0H?ZsGri}J); sN&?*R22)z 8jh'5,`SF|J#{sSyc8Zr3uMwiH|)Cpr~$8F;T>M4U)p_R}j$553Dr jS 5^qU"MTLz{WI5 Jc6EBFO^*3Q 曞sL8&E6SHsz(#ǿ~(=h"/A@N 3F){fF;Q(sGCFhh3IR:wҜch84vbGю9utx旷ҁJ=яzO(4`Rtr:G)h@bZOc }h4ccڌCKҎ4QJ:RGg4/P9ڛjS@R03F1Z'H/CGsғz?sA:Rdw >cZ3:~(A(F8z^3^iG(9Ҟ)OVz{`TxP3VS P X{ʸ5e*`p}x=U ;2sS#Cr1VU5"͟VDqԱZ*h6ڦGӷsSLgʥlm4:iU2*7_Ӽc8 |Ԯ-W#\E!=7yyLSj#'ڔr))p:RcR3It34IKҀ1Ҏނ8Gj>cޔQEI')g^ǭ!84uMvNsKhQQM K)~{f=x'nh3J)?hiq;QƎwKNpsҌgڌdQ Nfz&;ѷH=ZQj 9%>`{R(H /JH)M/lbJNr1H3җB0hc.2i1()}iqFzCJ;Rڊ1F(q~T{phǵ)289GCIKғҎQ)N{ 3G&֌qGڒюh"ހ}pM!Sq4}):@ڔR \JqKތzR 1ϽzGLh◿c_&9\ZBqKFp=i::R1F)1KGz1Qi:q@M/jNq旌w=)E!AK)E ?֔Rc4uҗhh(4`)ԝpϥ=zӁ=*E;ElRH6jj[ߩғZBs)1F)Avi I<()xҊLRJNsF)hiN4sG@#v(Ls=h挚23KނyGNu9ڌQv qHyF0M*3֎{RtGRc|QSƓ4ug֒Kz8P:P~)h#"/AqI=sqF08RcN{Rg'ցG^IюsPs%/8(яSK8wҁN">S"3J8S!z:6*՘ߊtqO֮q֧G*\ԪsޟS(ߵnz\|FߊP*TUv$ ⡕ϭB_<ڢQ~*~zHP3sɨCM1)i&1ҐI/^Ԙ4wA?:>Z8&QA Ph4cƓEҌqތ{z)Hh G4R/n(zN;~4w攁M( R~( уhcQK} sQ/~xRsG9g'IR@@4FhҎإJ=Gj&1ӊ1ޝؤph'ڎ;P2(zNԃ4cEHsڏRq\t(jwn)&9A;%8c=)}GJrU >)G j@zTE<JxW8GL TU~:՘9I7qKXWTSc"8^j`/>l05!`Ҝg"‘W98$Jkp)@8'4'֔Zf㞴܊H F4՗JgO.H1Ңi~n֓#ޡ/csQJrjFqڎݨHx>ƎZ s\4 NsԹ⎽() ":HzTrG5:q֥^jxJF*t(J T) OZS$ (sޞ4RdT'Jx ׭I#J8$_7ЯRu["i1F4cj09t0 T[NsL|bTNy'rUL=}9<;:dsF#DynzTLzdQ٦0{O&i2s1A?&{R8 izQI"9AIߊ3Z>'֌G|:wLPEJ^=hbz'^Ԡ Q(}4PphdzQ𥣯ZC_(QތbF1zzQ֔s9S;v3XdcRzjDcS+gpjp*t 5b26хXVj2168E隔s ҄ R(ڧӁҞ2(JU1Ӄ4g4哞*O3f;9fc!ޞ$}@M)`j=$ZG8Ȩq֢cMG7=i5?O5w56zb34ӂx=i 4(ޒ^iȠti3֝{SON)O֣h֓ߵ/(=sڏ9ɥ=GҐt=(>~{JOjCy>wҗ4BshhcFxH;PF(~4dќfP=iOZLs9Iڗ4utGRQЊ\挌{Ӂ:S ^;::P}=:RfKIzzҌw8#QߥGz3(4ZSj4*9GҌRۚ3Aޗԣ&y9(8<Ҋh<:\@KM'9y.y*Q*@OLzTEJ:ǥMF޽*X8.x ͚@Ԝ9wUsR OrjA&;BRy_YsJd35E)})ӓfAQ`*74*'?J^2j]AjG~HAWS3Qri*&Q3ޙ$9iݺ TlĞ;SzKSTd\Iqӽ'zBOIO“zu < u7w.OZ@r9I4<3FO4gL=GPO9#'ցh4sF(ϵ'9ɣ֐њ3G84ZJ@Oj^ϥ7'&Rvi:QR58}Z^3Q 斃}(4ggj3G`h= Q9Ji~㎴>AH(ݎgJzIҗ&Nh,{Qϵ&z;3KڌFh϶hA縠vʌ84hќzҎiz Q:QJx QOȧ)[5&sO xoJ[5 r1S+sR0IXYF1S(ĠXjenLr )Ɣf4 g4+߭;qZPRJO00NM)n4jq3do3 ӭWrSTڣPKӥByPKPPg&&{yFfQ'acL߃Jksi7})AcZi9cIQFiGJ(Rr (7K(\Rg_zti2yZp<})3:QFx4J'J1N=K֓uiz)I€}Eќќg/uqA&sK}ix!)<'AqQރC@GjZLR8ړ4qKF(ϭRr{)qIҎ?^ё@9'ڌFp9u⎜Rs\Iz^n(^)3KzRt9.hj@~j1M/QGj^ԝ4-/J1F9<`QNM($1Ny~4EH:Zzyю?Z$`2L3LyUߔm Upj)#8j$Q<@u'Ft"y=)[Gܓړ4iNJ: RZh?ҌQ2(ސg(-ӊ^ii:RtGOZL 8g=3K)Ӛ(>=hGQIsGhK>zOqKqG qG^G֑Q鞴v41IM.z*8F@hҊ@@LqE'I@$_/S֐hڎ:RIK)=zwGQZ ގ uIHhZ_֎ :{K⒔~(2&{S(KҊ)sL8Kޖҗ }iwvisO\O 8?<HJ@ǭ?3R9&[JTRVYL{TҝTBOz9 9oDϜL21ʢkIٱ1M3L&}qM#iL9Hi 'JC'~b=zH;R<}hix&^))i?/Z2(z3'LZ?8J);;9h@htwcvzMZ1z^({ўc99QP1Jic:gޓsE|QyF({Pz9F3A"ML*`ST5(<צzԊ'40n1ҜgQJJPjO89gɥyNxs;i uhsqIj^dA) PzzR~h Q84t^ԇ).):Ҟ A>vx8IK׊0GZLd/IN(}ZQHyG~zbwRqIҔd)5Ni?'䃃F<(BO>fi)ׯ5aDǞ9qQ>֡`97JCڙƘi>I7>{􆐑I xV|HXzk@4nS4MD.i+Ą2Bp~`bNsM2PiSx9IϽ!#l6Aϭ0b0qMGB3H\ڢ&v^p*sDšB?-1N0*694FĆji93{S]S7gȤ< qM-IMbڔRcۊ掤=M&qAzN}Eqϵp)0@Jxu:NgځR)8S'CG3K8 8RJ3)::ӆ1A⒗zފ#4(B8/AH=M/~4qK!#>8hv(җL{Q҃۞h4c\G$z_RNqS9!L:x'*A +ڜO !$,k8 fd883rO= u09z4iig<}iM(9.s/JAqRƀ{P w& zU9)Ҕ8(E81ɧqɧ+֝ӕȧyi)i!N,ڜ&ӄ㸠OJq<ܓ'AC0SCzi*x f 07pQ=_Za4nS[SKgތL$SCGzi9&,3H#4i8Nv&(9j:4-P9FAQv֌QbvQ^>$u gڐsE9 (:^v)q!9ҜIJi@4E.0=(Iۚ^^RIE LsKށ^ԝhF;bs@A4b4F3Gpi1;'Oz>Rwh#ړ8Fs(攌IP);dqN=(@ !KAG8Z\R`Rcґ\qR4AҐP;ǭ Jv)>ь1FRҊP8ǥ49N8|җqҜv4SR=y}O ;SbwNSZPx4c&u Kn &q(uҎ38L=)49zZ=h4wJ0hǵA旧zB8N4t&QRh!3@sQgE&3ьRtȧt4*4qH 3QA;IsAxz1G֖ьG=:RF0hFEhG81@Rbf)ZLS=iGS֌ӀzRIA9[ 8>{R?8N8''9֔99N)w| (.1FG^n77v:R!F9744M֚I{NGJ֚M7u4s†=R9}EhF1hGlуz1;Ph N; ȠI&8#hn` g4ө;QҐJ0hi (?ZSۦ)/QHyJy R28Q4KOƀq4{ӭ/qHzP)O'G֗gޗzByKPqJޔA&}hF@(g3ϵ(cFy@GNgڏj 4u4fGni2=Ғ1F~E/_J)4>EqG3ԙ◐(<(H9vx/jN3Fi{g#H0f)H94◽"2(=zsA5$Rd҃GLⓁӺIך_!KE'j4f1֌ތ{ތi2}sKڏG)h=(I\A>Ӛޏ\Kڊ13JؤIސ:sJ[Ȧ8fq B;s>ɤ'NҌdCqA98HMA-֓4h('Lh9恊Qi?J3ڗg/jLA Qތ )Qޗ'\Ij1JxG fў9뎔hq@Go(g擨'ȣNɥǽ1J:Rq֗`Q(ۊ=/֎▓/A4J;Pyii;PF(F)IAG44)qϥZ4LJ0xG4ҌRޓu8z1Gj9Ԋ@G/jLqF )8Lc(r GӥMIǭ)iH4('9ϵR ⃒h;ю=N=z(ɤ4RR@Azw& t34 h4R;yi3)s/(ғڎ1ҎERۥ JOFw^F ґҊ)84t)sN2)=hz1I}8 ^;vZ3izё@o\R⓵/j9)Iҗ)0( fGQSR*8'Ȥxi{R3JOZN .A(E)P9㨠uyh8)x/lƃ@Hxߑ)ҁҔ擿zRini{J:{Rh~4֐f8Nx&G))EJ>Q$hRE(rs^:R{w҂@⒗4hi9<ъ;4!I4:G(QEƒ@KF8JP))=xzRd“-8/O/4◎h=G֓џZ:hE!O#&8- q@Nv=EPx>AK؁@{PAIj1ѓ@ih &>nqhRсGHzR┏^i8>vRdg 9GcH/A (H8z҂)1ɣH8ހ0zR㞔(i@掔uEKNQJ:њC/> RqGZ0E)x"i:94SzqAJ9Ii;ҊO֔tEtH:RC`/jAҁKzs@9AftIPG|Kԃ/&8h4PzQI#ғaF:z4hP9):RA 9zrhv!4 S1@-&E')sҔڛwsGK֎isC@9qAҗߥ'qK@<{(G4jSE)r;}&}"gt>׊QJNzv4iZ8JxjNisLw=RJQ9fҎi9JZN'&^qGZފ3{;NQJCAJ_zC@$u84d{ARsҎ3G@E!F{NJqIǽ۞E/`Hz?ڔړ.1y(@RQhF QGN(84Rz}");zHz┎:R zҞF=i@Nc^Rw֓S4F?OQҔvG}(@ьuFrMPE&;@Gj:߽f4ӻ{s^)1J?Z8h)0j^ԃ@iH'@1;ъQP8QhQG^Q4w94c:dQ)8#KӭK)P !Ҟix$ѐqFFqILҐ1@rEP\ 01Hyу\N4Q~p?8)c'A`fŽE( @ 0cIh.h#'4cIQN4`ю)q!w)10&3NIQ8Lz(:PҊ;I\t(QIuK+\wIJ^٤)h@ 9z'?Z:qG|bnvi94c G8_hgGGg)@u d1GQHWҎ.8F=h4PzRJ3Irh u⍽94S׎i1K#.{H /9{QsK֓4M`u;bG_ƒր4P@h(J:Rs@0M/z(F8}h=s@P:IE&1Ah(vz1Z\ :RHbOҗހh=E;2=hQގ bu=(}9JZ;x(RsNڃJ;sKoN?\Q(GjJ3Gh(d1izj3J:pE/{}iG'~⎝hсFyKڎ^ԝ ZB2:QږPsB={t#4r)q4sހr(K&}p3HHt.3AI/z;hcEtj\f"qGjSG4掙=8 ?1㎾4w旌Hz^O"Iy8w 3/qH});RցҁӚ:2q1I֗WNi1('ۊN3JGlv'4c֎ҊNzRI3@s@c0h=8R>)}8R[ނ1J3)xMPzhڗ>ԜJIqK@@@Z?Ƞv4vqҐqތғ4faGA)GqHE9KސJ0F)3PG)h9KړhR4 8yKI:('/4QGFS ќ:E.qLzZ: Q2Eh>RvFp}) OjN2i{џZ\R^G9)N !J3 QғJ4dg;E'LGz ⏭ER)=sANʔux#?/Oi'hƂqK)2 Px揥ޓg7iQ֐@<RG4g4vҎsKRN攟jCE֗R*Qd(;u);Rc:ϵj1) 9'.)zuZ:v㹣|{M)>wccG4t9Gn(9zy8 R:gRŽi1)pF0:ތFGq␞i(G4u R}<)yu1KޓܚSӚN)iR(=)x"Z3hNHygNMҔ Biz NsGSKq֗{ў8G'N{ۚ;Q -FqRz^J:9bFh/i1(4dLQF}@i3h#4PIdE'#ތ_AJO>nGgEGQ4gQZ(iM&hGCG4ixK:QZ"ޔZJNA@Nh=1AwQzLrzqKGZ^{S=i8ɣJ#>tR!1G$RgؠzSA?=jQ4g<ҁ=&3KA{QF 3.s4J3fTq^7=iii;QF>lrNhHi}>ԙu49R=Ȥ=:ߓEqI;uG~Etyy$ќ%y.x>i 8N4Қ?ɣ!<◿J2=(JxqFx=i3҃is'z^1ILҗ4qރ \F{ % ]ߍ'Cz ^ԙ zPi94ȣ┞i3G)sIrh֎(4ځ.E&qhR:CFxZ:j\L0@{viiA94rA=hzF97sҗ9IK{fF{n(?Z;u3(PhN1F{Q(8(sA.G'# Əz \`Q!/$PxIZ9c>u}(@='J;4d1@ҎPOsA<:s;t@Hs4q))GJOj◵fnʏ.H@zKNh8hM pZ:3!K) .yg&ѓ@Ҍ?G@4sf~4j▐Q4}iGL}(AGB{zRF}(4I(}yFq&x)GLhǵ4xQ/4R Rf4#@h"sKQ49\:4zPrx@4v"E4uڀhK@r(4w5{494bt &x9v 9ǽ.hC3K(҃Rd89旵H:ў֎Q3G|Q(wGjR):tRsK Rg'2h4{QR':(PzqAp)zgFqK֓T'Qߥ'Kڎ{i9g=89JLsvOLRu :\qғяz3ȥ=(Q);H:Қ:zҎ/OJO/=tb9֎gǽ- ӵ)i3=i)O ֗h4Q:惟j@;f('8<iGJ;p)3ZR=@Z9r3Sړc߭.8h'қӇԹQGZ($qH:{Pz^tt>F p/=Q4tI(gJ2{џ΃ȣ4QQӊ94N`Rw#=t ҊJ9ci ֓<֓<sGL@(h8'hh4~4:{RjQ'J_7=iq cƎњ0sINأt8hǡ)=JxF{sjZG8Ȥ4ԝ-~(<cQt9%.('R:;h)OMhRqI9Rg4cނ9/\Rc`t(r9E h=&1JO 11IGJ:F>jN3A8y()G֓ޔbcGCIhhqTcJ掭KR(~rxc@ǥ&;֎cך^4*89z֌{Q9Q@(ȣNhM/~i^AE)O4g^M'cKh&FRvhQI4u8EQIi}=)3J14tFqi21@旨PhzNNxQhh4nh+(=@җGJ @hJxi;QҌi=hhϥiݹF4I4thȣRMg@('qK'z;('cA4ΗI⌜QϽ(<MGLQ84B0r(E'~hz\sq@h hH;vw=s@sG84A8\S)z}(0sFkSigima-1.1.1/sigima/data/tests/laser_beam/TEM00_z_75.jpg000066400000000000000000002367401514013333200225030ustar00rootroot00000000000000JFIFC    $.' ",#(7),01444'9=82<.342 @ }!1AQa"q2#BR$3br %&'()*456789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz?I{h֌}h#'\⎔iA}h/\I@:!ǥ)(QHxb:ڃp8i1(8h􇑁4}(rM09^v(x4w- ӭQ4 0)p=zP4>Ըz;ҏz3A&֝H= (֎1GNvڔ L u#:/ZCt& :G9◷!GCQޏOJ1t9֊\qIz:sF9R΁EqAȥ 擷t4(ZSi(^y4c'њ1д hFixH0sF9zۊ=hGS@G\␌㞴q @3F(LR1Iޏ)ȥǽI)qQۚAJC@4iO4Qސ=4q.Gǥ()3/QGCނFhq8=8tq֐r}?:2A=( z^s@F:PG c\q֎i1Rhz< h9J)(J:RGqGj;恜v掃OJ^(sG4uZNsK)>t9I0iGZ\PM&8 4zR98sGҊq=G40 (=hu1@Gz hhZN@vރsKE&)G|Est֔Q֓8z? ^)9(ցqAZ)G~#ҌPqh!sKE@<(}O=7/aIP8FARg ;AGA74c?:;sځ֌wqvu*\bw-KځG^&q!h4E/jN~&1ߚ:t'z&;яZL֜3AIip);޴QzҎ=? Ioj 1ϵ.;}hۚ1FO'/Jv4Q=I҃ҖF84c'J=);❏JNŽucF(qKIt(ORiz?J.3IJwjCEzu.2sHy9⎴u(qހxsRJ:юqI}9ю:RJLh @8=9p1ޓ4` ZCғj^٤4RQw)u"9cFhuGZ=)F(PFh/Z:Rw8 1(hI2sJ=MyяzKI1z3ڌfrz IޏƎъLRc4pEڔڐ`hcJ\ QIG4R4bE&:9GҊ:dB9})qzNZPE!(whGGP=hh1K1 Q~ʔz(4c`QҌff(=1K(is;A׭;);ނ0=@&8Ҝi: (`p>b LQE.884b@Rw5/)x#QA"Ii{t4c^`u QڏŒ`z1Ҕu:擸ь z =xIz\|c& (4/Ni}9Rw-&9@Q)Hh#ގԠqғ:butǥ'GNΐsA#җ'Q֔})/A4Fici9FA):F(8E'z8sIԒE({\bh4&2iy1AG9)14iԿ^h{fqJ@&=ut#Kg#(bu揨t8GbQޗEqAHE.)ъ_-%'s:w-!jQHG'QLŽv9Iڂ=(@J;sEaAތg搜;sE>w4`whϵ'<њQIځ/8Qh4PEJ(.qқzQsRj9Ri8z1G^wd38K) Q){sM攞8q('wJ\c(ޏ.9'S(7􃠣A(GJP)=y4cF(Rs^:Q}(t u>uq:vQKh#@1JzRR4s㎴&r9izjOizGI֔ c4p:LRsRNsK۠b)p)4S F2-&iGzL掽8)IL\23I|\u4QvR8g.3H84њҁQ!(iri44#dR4QQ~>wR{ьQvKIQKLK@<{H\Gniɤ4} ▐dzQzQIAzIތ'ixh'(.4E&M/N\c'9/j>ђNh@Gj2GzP2yI$g{vQh=(ڎ(Gғ> =ӱIQE>{yi{L()z})23Kޒj\%xց@AIR#'4\控&tr8Fzi“&ך; ^1HE/jLs.;P:ёCҌuzPzPOr(>E`yҔcғ'/Cӽz">zJ^)8J94I֗gץ!AK/}h@GZ\⒗8F9IҎ4qIQߊ^M3Ҕ揥?Z_:4cQJ31&Ԟ (&ր2isH:EKE~qKHzP0E/NzB:INRI\Q81GҗM֗<ҀqIK;R~wڎG^QK)0O?Η҃ r&3KhϽ&h'ޗfҐ) /QA/ RvŽ⓯AFM.yԽ)3֎HqF1ӭ)iNGz3Ҍf/Z8z (9(Gj_JIԘsFrzґC3K:FiG_jLuΌqԘN֎N)Z)y'j=x&)GaLcғ'w)qgJ9{Nh1J: b &2}zN/\R8.hgi"4wnn}(dZ jcJ:QAzP1ǭ!=iG;Q@=i::i3 KތA'֗ўqF8N&RH)sFM'z_Fy&Fr(s izڐ3ӵ744QK:^dAAFx4Qȣ>w dғJ(:PZ=H J?/A4⌏Ɣz}sIsڏZ@F)~hGQ@ނMK3I}@IG|{P1bM-IҖ&xvu&&N}G4b4gA#4u4֐y#8pxKN)Z34.IH=(=At}h4h 9IҏCGKLќE&s/JLN4wAg9^)sڎRsFsA8ڎtFysHc)<ў; R8ifZy#&h (g.M&zI2iG>Z3(PjLO)<(3FhsG֌R'ҁv9'LҟbӥȤ&iO#E.h42})&'GNy'ږԠOƂsޏJ8ќќTdR?ZQ׊ 9>(~dIKFx((@FsGni1gLQj8(ތ\RFqAt=isM!Fp8$cRgZ;)Z@{QڔޛK j3Gj(GJ\Ih(s998Z挊J2sEj)sJ3'nh,tfލ((֗4gրAsރh"(=(h/v֎(QރFAARN1KIF~Rh4GZNg)sI}-R”R3A)GgQ.8GJ2)3.8ڔ4ph硣Z9Թ'(hޓ4q֌=i2=is;Q3GJL ; @N֊ 3GAG֗4~tw4(hFy8429֎c򢗿8yh#ގQ}xR}(sJ~QߚLsGS;PMԿJCKڐ@$ڔsۥփHF@)zsK94KLJy^i!R)xQ)(i)q&{ 9Ƞ4ǽ (;Ҝ3ӽ-'4{ўq\f^fރJ)qK4w#4R(ϵ)֐(4 ^(P8ȣ?A<ъB1N)x}h9zGAzOKӭPFE(J:QڛJsgRⓜIKӥ=ix&xg&I.)8ހyBI{QQ@&xGP8@/3G4 w8I}4>&1ҐKzQzwOK#򥣰Aj9M/j):vzޓzPF()2qJ=i(4(#ҌQ&;Rޚ)~t`@ԧ&RGS\RpE!1jN\ftPx4cLdRQIR!_ŽE.}(qH}4i9):KZ8@9JO $ڀ:E4c3@(isJ1!tgڃP1fsG9RԄwG=hJE&;Ҏj^PsG;ь =(NF1NsF8}(sZdRGQG^ sGjZ;q@zQh?O%/zCF2x:(w"(Z3ڊLbGlhޒ)@J1 &rzQZ(IF8c֌fsH:?ZL:ޓ((={Q4ڌRhQP?J$␁Aڌt掇(E/I4IKsJ:At1qځvg!5.)H#hǽqi3j\dzAPx(@sGzB3Iڗ ӀMz C':t>E Kj1 SNC@ҎhҌ 8<֌})qr)9J4ch'Nۥ&1N!Gj=){PFi1K8c4riqŒcq'.3uKތ(RJ:4 p3R`z@Pr((v#)*3֐)q1h=x4t(!4bc:g4uh}޴d('`0AGCHIߥΎK@Ҁ4uz֌旓H:J3ڎsҔfh8RI:gQQ҂8G"{яJN?^ui?/QF=# =xϸcqޓZ^E'hS{'ړ=控 OJ?旌r)(ZNNiqI<~ts(t@f {9֔zґIR sRSH.8RqGbi:t)hm~4M=⎔RcQӚҌd>蠁JNcҀ:CKK:P"=)hHJ^h) ^``t4Lw? 1F()iڗAip)2Fi}0i@`Rc)u)8K)1/f:R4})8A/zLzڊB)HJjp:zRtzH Ծ)}覟ZQ KޗiH'AGCAƎJoz\ 1g(@b8⎴c1Mq|AFyMsɠP:P{Q4uG@=h1҃)s(dzOP9@Ҕ)3 zPz1I8qF8ƏŒvҁZAK}23Ag(=xHM('8F8F~cңhJ1פ< Rh _  '֖:Qb=8hӽc=p;P>ZP1ҔZN C׊PɤAJ}%;H8n84 _zCҌc9:8.p}h9E(zc-4g4@<4RiKGj#G@=)H1Ih'/ZC=(#8bw4Rg=)sI\qQ{N}(@ 4 }iFy;ӏGlZ:{Rc(&2sKInHy(bsFrHG^)\QAG^)ҌJ2z⃁AN):.O=J_Q@jO8)xE!RdytiG&oZ\twނ(ϵ=OZBry{Qӎ)3r `(s_v{Ҟ})3Q}MNsF02h> @ץ!fցڌ֎iE4w=M/ҎM i:QsҌdqH1KFOqGnQ/R{IKQhGA J(#vAIR<zP:bRi/j^{Pp[){b8&Fix4wӏjoj8=Ҏ8◯88r:`/CKIQ(^b8<#1_74wt)>Ɨ&8⓽;#qiG/jAEff I)x/Ch8)8.A ?(ڗH?J\Rfi 惊Q~4u@^ԝ4`r /Jn>fԧH(Qȥ=F4—&8ntG}/z)0{jisq@hqGPz 3 &9ҎyuAyph(8/F3IE/tI1(&KRQ !4gn0x4v?*4;P&pM&O:4ASj({yTG_.O~y/\Q;!S3IG~h4h)zo֌z/^h<(zu9G>xd^(=(>h:iiⓊvx!=Pp04gfɤg8Gӥ=iQRyInQiq^)3ڊ(J)}ڗ!v( SF(F9(=A\bQJNAAq@t4P{o^ * ^i03AGh=h9=hiIH:\3֓=ԼFh}EGR4z^'K;sKڐP){Lq3KI^GҊ;t9RRFsGKNc< &84gQIߥ/.F(=hyKIZ\ӭc(?Όc(֗&8:T zuҗZ);ޔ}hϽ(GԌъS)33ڔNqҐ4M&0r(Nǥ&}=Qӥv@iG<@f\v9nڌzsA@⎽>Ɠp{qGlGLJs(GZOc7֗NzJ;9rhEzOcGJ;i3K֓8vM.y'cJ4Fhf4{g 9P3Jr{i:G9~4 x=Ec>PGz0s֐IߞE }(sHxi39<3E(984u<LZ3@=i#KM*?ƒ9'n ێ)=Fh=(KuO^iG&8'Q@>Qڀx#4{G4bg4h4`@>Ҍќ:c4Fhx!gF(4sK1ך_2}hAG_ǵ!8?J]&#"Ҏg4zQ).yq֗'"8xQ(8R(-.x(<ҞsK>~s(.=@Q^;Q׭@4Rg/lP birqIӜQdfpqGZZ7 \RRϵ)>JZ8"w8RFqJ|Ru9M/#҂qڏ($z\=)2I(^gBA88&1IN8!i3ށ׊^M!88#'#4dG4◊NZ_ZOJC֗ux=ɠs֝_ʌ3($ 'Q挃Z2s 84;P ;(vqFy4&yzޗ=\h"u<*^) <~cJғ<GғIisHzcSA):ӏjOŠ31F1K8!h(;ъZ1hH>t)qM4('4&) (ҁF;94vڗ8I_JJ_: G~h'tv9Jzw^)=/N/N'F)Ԋ3(ӱbg>b8#?*1AiZp0uhԼbSXp:1IKj@(>ԀsKOjAގRu1Hz=F4ch&})F3HzҨzҞ=9wHGsF8旽'1RsK@{яJ6ގqZB2zRҌ֓-JBrz◯x SJC֔y?J1Ph :0 2xȤ4(R| ( tך;u4c<(EqKFjNRc<ъ1}izqGCҎ1'J:QsGCAҎ:)0RTc#U u4Ҏ€84'z#'—v`с4bupFhǽblRzAKj);c4R1N\wKEJy"Z\qHM/ZP8u \s((=i{I Q`ґiNh8:ʚcK`izz\dRr3Jzn1F=xa(iюi_jR8J: L i? 4c4q⓭dQ=iJ1G'S1F8QZ1{:q֓# 1P8{R֎PG8s"Q4 Jj\ sMڗPG?֔/9!fhp3ښ&JLdE7o4:n֗iNqښ1j:i1ǥ ghH=zҚi4h)xQ҃{P8 ^4ьҎ.1i=yuqGLQۧJAҁG/JOz1K4}>փҔt4~F9zsQҀ}{d~TjNRci_Lzњ3JLR}xcIJgJRNyN9QzQIЌJ^ƒӞ 4PsGE"1v⁜=}&3F0qޓ.9F9cG@z&<KJy^(#h?))@ԴAҔ(>dZ? :A Ri:c4zъv9ҎGNҁ4x(b;Rr 4uR҆SBPG*t2(\iz Ѷ04и<q9 @ 7c3ucZjMc҅Hg;R`Qu\sHSR8Aqh=)3F2}){ҐQϭdE}(bbQ3Ӛ;Qҗ4OR&N(K;`4=8AQN>ȤMPs@i@q֎'tduNP= )ݺK(:r Hx#4;ךsW9h#4_jPݹ4.;jAHTd"CMar R8@=)`q(96iz+&FzR1M^8>߭!C@֓G&1;*niĒG;RqG)8ޏG|c>G{ғKڛތu8J^sHi~ƐQP8;r(3F83KS'{R/8Ԝڌ:֐ Q֎c1Iɣ4)@Ⓨy4 mU(Q&N)AJR6w`6Q0i2GډW>^>8Q<R>Z`^=OijQӁM<{Ҏg`qIJ}9M&r=8vh(@yP4vsڐ{zt> ((4ڐsKϭ'Z)xG'N((z\(Ƞ7ZZCJZJ==)z(!:PsJWIIiG\fZґF1@F)=;RIҝ*Ol==(z\45"zr .{t*A\v4&:ӊgM N1 ₼fP֘ޟ3L ңSRqԉh>ZO# XqLP :Vi8/9 aP8Jg^h ~4w(HփK{uF1Jsڂ;xPNqF9/غRI֕1}0\ / Xҁ8ր)hTxt i^j"vE9T[pZs;jp;Ѓ $峊x wN29):3HEH(#4h=)? 3zьjxz"#cҔh<ғvh=iHⓐ=^iGQQi:F:Qz' р[!斐@xK sG^(4;P:IߏΗ&('sGF8֎`RԝN'-'Nт(֌sE9i;b:8sҒqw߭.8JZ=s֌׽%҃JQQ3KAJO)z_^ L=4\ΎأuZ=Gs4{Z;x⁜9KRxsɠƜ:ҌqNtNN/R3O9:cӞ*@*>Ɵ&W9)?QKCyxnE5Ht")%S @>=*YTqQGt*b9L6iȿ-@yO5_֜QQ"☫\SpOzxMtPN\ҞAg=aL4N(Hõ $~TK'CAGZ9=)q'g#/ގixGN'j0A=y=1}( }(=iZQI}pE!9)O#ҏqG^>N`c_ƓGRs)Gs^}zRtNG& Q^ PhG@җڌ`fsP@sG$Q=:џZZLfӊ\2:GZn8{ѓK@RsKߓI)ڐh9? _N(Fx \⒝ךAך94Q@)qJ9GNq@Fp9A~4u";b۵(QIӯJ\q`S֗.8ӱ/qNSڕT.)UyEHyJҔxB89'۵I)3JVOO&qRM "hbFsY"Ixϵ 8DŽYw jwqK:1ޙ ,g娜aOgUR>6Nbe#4"ӂMBGq֔LCjOZ)8P02)&Mb}pҚ:^:bsAIA~R ^ bގAKԃ}߭/aA8@Aރ:сR`:}hǽ(IZ(NhT=ip)JQ@=}GJ;I^ؤw&=y:4J85\QF@}gҁ9斀i"Riz('4t4⓾G=z֎ 2;ގ٤z_z;P8ix9(NzRR8{S8qJHsNۜOU4Xޤaey>ZdGڙ7jXTO9S){ړwJy\ўƌ: 4dP?R揥tIӵ Qȥސuw|ўԇ۵Z^ @QJOaAtg'?I28(KҁWޗhQӹ98 R;SNONEH)S TNyQFG"ȩNqڥ1j?ڥ1}(Xz Vzh# L5265;J8.G皖>Vajb?w@enjI dDبgP[S!哌*ڞW̝;ԒGsU>~Nڊ4LR Ȩ8"^ 14xMS$sڀxcցt?tc& zy>Ԕcހ{QfqE- ֌{яjLQ(3GQ_zCIץ.h3K4NqGZ\ R ?%(nԘ─(=):C1GS K֓(==h8w v9ցҗSA4Rғ$^3օgގt⎔FF(đҊ3ҔpfҊ\֌wisI3/oZ9#Ԙi={{cގʗ"dQ/֊ HyQSKh8q֌Qh1ԅ@)裮3JS8Tt1<4Մ/qXGB9 棞#!1H|!UeStS.ޟt>^GEs zUZ3S<*榘|9҉9Q3LpsM ǵC"帧jz\NS\_#SW҆}ߥ48sL=xԙhy4}(@/ZLр:Q߭&Hњ>:R֗4wA|~pA~cKWozUR7 Q'-#ҘFǭ5Bj>zGN=8KI@lB4qGgџ֗"q4J3@:RғR"g9њA׵)9dRP!K=( '|\ўzQJBpiAhAbJLFh'QIA8dQߊ9⌜њ;z2E(#( (8#"Pi3ҖҊ\JL⁎h#0E=>֏i9'QuQҎqFs׊3=irM揥)n*^'RIAZ ?4cҎhh$f4RHx4Eߚp▜>S)ˌt3)T8R"}*lr*E\ ^d]ة7\Ԣ<"9TPGH{tp+tSGxQn>^h"|M=)ztjd*c϶js 5;ġӚN^604ؓ8Qi, Q2όjVl U/+qO6⩢)+⠉pzTw Nӊ0A*+oBCNӮSPi֜>1L09cAlBEIөHztLQޗ Cփך;ҏJ:gzBy.r(ȣ)G֓aG~Hiiz&OҎ9P1җ$HT0*PT=Œzu=*vUI`8OH sǖ*Tַf/gwSKfE:x>^8C 5Gp"?UaFǑ/*kW_C;[qӚsĤTd8/qOe;8櫨ĄTtP i$5lS_jWNqUm;R]qLj35>W<՟.0*sYO-Y,hQ⠹J|c1`<©b*87#StU$IAJcrh OQާTc98^*24㍿Dt" "uW2*6GZXcNBx?{sS4_֋R!s֨2t⋴;*+Cv9ޖ-_Z(ΥR#4銫;&qI)M'G'ZpTL2O:b֛Ssғќ $g4{gMu?tv(ғ/F 8{F8u4`Lphȣ4ggҁK“9ޣ)TRd(8I&&9AJZZ1Q^sSEt=izhj8)Oy փF84cNqJIKzRi~pP}h>u(3F>Ҋ(#ғu1K=JR:qIяZ1Ґ)bqrsAqKցP~cZJ^hҎ1.8zRx;g4\db&c֤UfQҥPz Aأz^h0J^:RNyKғ=(g ;ޔ*L#?J;f0)y)P2i:R;4r){P;S׎qR9`fxZSJF 4<$hAy⦎2*Pv29Tm#=Ҏ1RyV:Ss4=~N)@|)ԛsTNh~ԏҼxHe1< O1 ϥ,˕J%#m|i LtS8*̸9f|j{YFۖp: ^ U_֖$L1̆>B*2֡E2QizTrЊJ=)Nv>ʘ:`tw"{RyjP9HHIqJ>9: ޓiy)ғ=11'KHqG'z$@th擭.2)=iFi?SfZCJ39Jڏj6'QӞ@(e'8q֗4q=R^1KIJ3Nc/nz<Kϥ.;;&2=1tڃzQqZ8@JR;ь(#"Ǝ;wqKڌRJozT8LDڞqDcIF8+QRjGzTQ:ӦQ98cI.N)pRHI9?g< TQ~ yDqVwױIdFA5Btuf9541Zć!k8|yI*f3TcOuUNzr9D?C*ǚTi &ӊbuAЊi'йsG~Q(>R`iA=<v9=h>h9Ǝh)9ҎޔyHy8(IxzQњE.i3F9"(?7҂E/~Rg篭&})Rw;sK)@Zxɣ=)it}(PޗJJ\K֐pzqKԃ4dt(zqAQ)pi{s֏J:Q۽1A<ҏւ(@ip3G h4qK/;Z\ޔ zR/4"1ޤQSjtSTx2e#",cnv*&,u/N.:qJTx$`ӎJ98?()bp$c-R?)$qND*'@OR":~uHэUthP$YȦN/iDŽ$5(P2*W'5J0|z+BȦߞsP1e^SReaS}+7?֦b>F5Kp\PB(qG֐?'9:u'֓JZғ03Z^i})zhg4/J^hEΊ^HIZ^)3)<4ߕ.9z;/RbGv撁Ӛ3۽(9Kh)z~44dqJIAH}qEւhHq9 1JxIG\҃ڗ.ri( NsG~;P}=(ZN_J;z5 S !)}(Gz1IK4ړ/QF8GZ9֏j3(ɤ旽sARp@ǥZQH:Qڗ:Qڔg“RsG4tfzьh4JNIKQҔёG.G|RJ=iF惁N=A?}=:Ԁ~T*MR* RTeO*ULsVcLX0j #J R=E銜R'5!"-IT"qH"WbhrqQG$䄑M1I,g#:8^ MUCS8"2j4 A6v81%|T]TlґNp;qT*D1PƞɎ=qzrLrDDj{tGB3ǭF͓ȩN UpzA{7Ṛn*ҙp9c*ԭ v{hoJ~J|UCϑӵdJH,s3ԗ'Rޛt~\b֣^)954 0i3@)旜fJQr*)::Q@)s);P3As8⎞CRҎ 3FhCA9)9=s@9I֗Z;>`Gz? :ўzQތҁ:}iKGzP{wO\RF9 }j3%{g\AEKҌ}GQӶix&sE{RsAFhOz;gR=1H4}Mw⎔(4d OcJ(4Ê4u<ӑHN)*LKx=)gRҫc;Ӈ?# ;@8}*U_U52)PjuZǽNf#V@ZXS'5(#(F꘮i&PvӯW=*O+M}jcSFwt$gJHeC֟;*&Tǔ/5,@-K3qL G9FSUNjܹ"uzUhדQ&WMT7C ʹ R9JlԳVtIKx Uk_ң?6i!9NV^$3UX3R8UaÚs*5883) ~惎i?:^i9^ԝhq'z\bq֐Ӳ:GZSׯgҗ!Zf(<(Gz;Rzߡpyi)sތ2Fh!(8S'\c3N)Oj?IAxgd R9ϵ(;d@❃ ;N;PyڌdPOj9A߅fi@iFNhIx3ڀ}=xR搜R})E >ȣtO Zp4;)IޔsQPx/4dz13;AKI)y2sKрs⓶iA'Z^{Q$AGzS)M'ӥ(#ҔQ(=)@ (sN=j@3tOJZx?Ҧ<ёju=j`vHy"5mVQN*UQx_j`Ԋ)ȜԢ3)1Sڟ*;ԜT'509Tof)b`O^)0ӣ# Ȩrԁq?Zb̞$UU҉qQvGsL>NxpO|RH%RUR9!q)]Ib,ǹb.Z$ǵf'>1T 9]*^FYh֫>lR?xy~n9F"iցR(MlcҔ:Rc: R4rzғ=y848@vpS{8&(9ZCߚ^ԄQ(@hx#tFx>:}x(eFi;c.9(@4wwRj3{PNh1Hx◧JPy=qE(9hsFis&~j^ZN;RrI/qKҗ<إhqA惒2h1)ELSzRNi٧/_jwsNwHJ/AJZ֥Eg5"AS(AR"^=ّڟy9Ha3OH1GM}jgCivKt<;Se$ 娙TwPi&*&#*O4޵ZeKR i)΃H ߜQ> zUx񨮗 p.zz:$&. qoޤϖ}*Do%jI.ڈ~᪲gi /ZbQJNϽ'GJ(4 搞(A9>~^h~q3J(ϭ?ΌqGZ;ѐ):tc4PNzfri<9=(vF~_j3)Oj^)Y8z31F(IJ4xނ}qFs@(h^I&Ԙ@j1Ic49aD2hlCo5]!m1J|OZ Kqj8n#ZG̙???'nP:S8J|NN*c&LAV]Ƅ\&3ʹ5!_ܐGjdOOؓIx%U' ҝȁjJj#rj>Jl?ZDHsh'5Ҏ8-KqF2iZqF:PzQZZOj\P}i2Iw{ f-Q^(ہF{bF};=:P: S!&Q Frh8Q9=(yQ3ӽ'4Ry94j3@)F⎇.{(>"J^sJ'8}Ry(4tR/=Tt8JӚ S$d*ts֧j6QNn7WQבS'RMLWN֤H3ODJ t08jTLJ@6jphҦbBv4sB dD$jb«RS݀ޡL&9*(g43U&O8GUyҺ/Kg҉䪱'GttȪw<4Fa+*n.R}>-Oʨ@yTB!=z⣌?ƫLyNٌVzs`/U\Ӥ b\6:RM=yqҚM4@)3M.yFh GJ>{tJNh)sJ0 ʒ}ƏJ:g'{b? @yPg.zH"QIGR=)Aڊ@;:Z)3Ҕ14f#M'FxAqhGSG^;J^HdI{у1֗dP(Qޏ|4N:ўMzR'~ƃӊ3R~4:: 2qr3vi:zRPJ\p=1Ӹ4HxCjX^68SBW5 d#=jVwmvXGPIQ5i?N|M/~Z͞K1:棹{zp" q˹|'5#? hr$9rV2<[_|UW$I=^:|+*%{RH@/sHRLl(H}x!sGQ֓z^xZLgҗ4gt4sAϥ))(<KҐhϽ)IQPzZ?:'z8(EIހ=4vi3i@Z A8T;:UU =i@:R} iz g<=)} wA@.hpE4}K;߽.=1J1ssKdcJ/zQ҃v1RtQOLy*TSHVUj2HD܏Zdոe{sJT׽LuD QNp{zr}j`g|jR$j@Q})TSdqT~jfl.Iǵ,O4Ztrd FqT|.3Q3Ny*K:Ɲj@FGNOT'ZIpj;> T'R1Y'5,+,7ﱚu>Wgu6PD&?5G6*ǽ.@?|U J篭BhQg49>Ԙ߭/jNu1KIޓ'JQQ֓Qڌ 8zj~tRt4xC- FF(4ڃړ/ybpizy(&&QF{csFI(qH1!=iq)hϷ4zL(IF2sFqך9 qG4c>HO~G4 #Ҏ)qM) JF(1Kw.qIQJE'J\GZ:֗ڎҖJ:Rqс֥jҁKRE(=)^;Ԋ3R {ԸxԉjU^OLzW<*;eTUZ# jvT5:(na0z*DҬp*DBjTNHPn"œJ#T2b32cjj K2M@Bf'ީS;951zىN;T"C~T$88cD Tq 桕 96A#n*SgT32jҫ\c:\LQcfK1GqK׊2})iG'4 r3Nz`b3Ӛ{Pns֤xrz# )( ’4qL3vU#)?vM:QdS88PrzIُZ+;0jsK# UW Lc0~* N[AV}̔$沈ZY1bSItgST\vQ]/Dz*p0Z|ZA:qN`*0xJG=(FR0SXsc 4qڝt4(RcڃR ^98J9E%KNiqIg9G^EG(j;fRbҔ \z)9*;;qBy)zwch#ށۊ1(/SQQRIR)2sF1GQ#)R2i\zQc֊S4i{H:tdZ !>ҝޓj8Ej^Q@=ha^h@SJq2}ǥ;Q/t@=))I=*DR 㚕F*DަC?Jڬ#gU wYPOZ}xqέnjڬ/@1R.I@xPB8NjUBEI֦ z1RFMIS#N N4Ɋs•$㟭9ѶFi=Jm;}P_։+T 'LoZ4n#昉ҪNoƂ>J縷||#GE=1 U @s+:iE= >#Qs9MaV#5rbM>Oª>lR`*zR;zT `ևQLP˜S@?ȣSNA ( GZޥvbьP掦qȣ -.}1HJN`v)WqI^/Ng"OJ=?(EvIގڀ8 ^:v֗}iK)~Zv=I9)sMKZQzS!@4( I^Ըuyi>iO8 wZLZ=x#Z?4c)J=!ɠ8< =:1ҏj)ƐA'zZ?00EqF1GZB8-!Z23~=hJG'Ҍz1HGԼntt1@9@Eؤ~HJ^`Q4c<юs٣֌dg"Gj 8RPGvuM#Gnc#;&jGZP)8( #4҂x '=JGv*x ՜DNjCr>yUijQY;?.* An6㚌@~r)<~4}!=>=қ֗A?“`QڎE/ғ:wԜu =isIQ(3;ѶKCւ03@4g@-ӊLяR=(ԜQ-'#\48.81K]:Ө֓Aϥ&sN}q4t$>ƎgSjB?:Qu=(QAΗRփڔ=9)AF{?^ךN?Z;ɢ)ǯ4w(EJ\});sA֔Q֗Q掦9ZwK?)t4ӭ9zTzӳTJTyjt9:qU>aOUaV#ZEޕ$S֒T U>sM>Z.OT9ȦU6cf_UAlρ[9`ޫN4JΙɔҳ3J$y7p{U?1Zm@UQ\@U@I(aGRtsIԎ(sKZ?L@sIi =(JO!h1F1ߚ\cF3F;Qӊ^NR ӚQI/lQ֓/=h@ɠhM#.>)i3uI?QQdJ}=i1GփaIR(i9ہN{4/NM_Hr)~h~~T izwzsGG|q֎u 4EGaFzKf '&קZzZQʁsJ98g(iܨO"W)R5(sR2gj1:1VQNJ UsJ1R:TTS)J`zT6{TSڤQP~\gz*Byg9,ΘdN.1׊xJ uy^(ߏ b}h@JxGh(IE?/F&?).=:sޗ>/JNqҗ0Fr)?֝h4wr(ڂ99ޒ). @xJx#4:1@c&(p)y4J9N)إI {RҖJQK(?$Zr8zc4Ԣ^sRa(T0ju^SU*c)XF=ErL׽JsSULRT2R"`O dT.ߛK6^: UBޘp׊AP!i˜{ԊI✤ 6GHRjE2׭JJ:*daUlUnaV|v1͌VvzwR(jPjU֤_H9)9ΦR(jE㞼Ԁԙ!G49%敤>֐jpM2|4 0 .xA/9Fs J(ڪUeqP.wTs9PZt$'5rWJ+~4˪,FE| $dstaQ5S9 u/HӥGiza$tPzhi  i9#gק4czQ(9c?7sAKӚ^1MK):p9<{R)TsҎϯҀ{9}ރlQڔ u4ݤvN(<9'=){R /^i Q)ҌKރG4Pzu<KJ; Z:i: c4?J%8RnsN{ў= /~h}h@݊){F R^iA8wRR:SǠR(.GҥR=3R zsR(Rڥ@ON\TV'Nڭ!zQ3ڗG)IqE(Z?ZNpF AGPOdAG8h4PjGҌ李h48hhI^qIڔ~t/ғ\{bKGҔ _Ԥ^4{oZv@j\twt5"*EN2j@szI)SJ3)RSjRA\^qC1Pgޛ& ֢QQJ9<Jqҫ9=iT{ [Cp_?Tr|ɪrC'ɏΪ5[x5*?x& ҔpiF1JHд@S5E(NisC^3{{yNɌM2||C ׊k#@)9'W 9Ӟj.s1Uaaj{RI-@8D2M2N4x5i %ܜR;UbwE4\TIQO/5 ? ,5\i|bwU2OZl1֡$950xTLqI:ߧjC֚:}M'!>fր}) SZAQJ\_ғ)I'gz;掣sHXPy@O< 94ޓ| ^⎂ԇځӚLFsގs= !֗fP0掄&ih$tgE- wM/JCA(RrM/Ps'4Z JOE?J;R ʗgQh{Rtɥ@Kۥ'z;Gҗ8#җRy'<ЦKiFԀNێ"Fr3NOJzTIjpǥLF*¾*XߎzՄV#VNEYNޕ<9qSSwqRS.sdjTS+zTđVCsSL|jHN7T(L#,> ~1HN<?,G4GҌヂ(R3N'vxsJ[`4Mg84㰨/֠3ץ5ɪaȨI99u+j dy@'u8h` :z1M{ "Ӛ8#\{S~dOj J1)qJP1҃S:wӥ(ҝS"i O RGH=Th&OjF<ޑg=5L cjnp4}*9ׯ6GU7%֫>l:iD}* Zyd|S3IXX8<* d?˜:SM}ziM9hl9'JNO>sڐu94.)9zњ:GGlR}(>֌q;ZQGSI:qZ;RҁG=hzP2q^s!4j9#ތs9G=q'=REZ1cK)3(ǩ>v(4lҞ֗qiq(RE. !_AȣQzH9Ζ<㡥R(A=h(8g<▐j`(px&zԠL}xZ(ƌz8@9)—Ӛ<i9sO^ԃSS9H3js<ԫ֤SyYJOzd#S 8S*uSJqSyRON\OqJs\ R*) QnyjRo0Rޔ4zO3MF*zfv}i"T|rr_ E)Pv£fw-&AQG44/L)IqGjnhh3H:4uԀ^Oj3w-A9n(EA4w ccڔG g=iqPS@ Ɨ9M<p$N2 H < 9J@I"QKI\bR3A<}i;Gz9r=0hGQJ)(ڗ.4`1qQޓ({Q@b3ӵgc9QK ю9qFs&9qތRH1G)t4`guPAK(I@K(4`uF=hcKӞvg/A=hnh&9(~`m—ސ㡣J1)qҌ`w`R44@s(R~8}iG&qӥ.Ozd҂OzzXԡ:Tr}qS!9gRaFzTA8CxV^qRȧZI$ԨnjT%Ojzpv?J})'=d44N4oJZ]w441sH21PҚqPj58 *&bEWf;ISJcx<%˜Q;&&H3spxc3#8=i @0i1I#10:`4tQG$Q:QQJ !)@?B;:=\ 1A&9&QfqҎ'/))N 14h'\duc(< }i?R)q&?QjLc4MiO:u◷Z:@rh~T4fy~x3Lx<)qK;wќ)Hɣ'Jz00h#ҌџΌzE.9AzQ>㡠c(~yT,LfRgAގiz= P=3N<)A4z^(HO>3(H8 R` CփҎأQ:.@FM'h-!zJ:p{҂1~tF(GzoCdi csH@^r )N9F:A_ja)=/?F?*8Sp8AF֛)P?Jasޢ/֑ޢz sMs֣v4j6nɦ)gBG4qH i$ئN?g7E4hKN)\qEizR fqށJ8xbN=){fڅ4Z~{S?qSjEo|SRJS| a1OS<04)`村֞N4I Q'BM+HhHhiDEC AN鳭5$[M3ƐƐsґFsF]E4{Tg58 gLp F)Ȩg8)޽֝3Fq)ޕyRKQޝ;SN㊑[ xa+1G5 oC=\ÐjEx| pjA 5 )C4d׊~@l})ލ'=y"n9f6ުi0'uiCjk?lfLi4qQu3`QyHXcITN93@zfJMǡ49M4qIh941挜Rg}h'HN9& rzQA=);xs@(G?JNgLӿ:A@(4uҔr !z>cvҊCF)x⎴h'ӊL=G@ !J4Idh֎sF}h3G R~Tm/ҁҎ@GQ3Q!>Ծ=ȥ(Nh)wjI4)Mwdў:R9h=qH:QJ=z^I4xӥ9u!FhR(LQ-!KxȢ9AK)W2zvh֗9iۏzpn)ws94zS^ZpRzG|Ӳ39>q4O88=piiL=iDqNSNfO3w)1J@sQ:PqڎO9 sH3iAcy8=i:88i Gdu~4g(Iފ0)yfxhZFtNzRhiIޗޔPZP޽UM)|{҆#)҉=4H$&ғie4CI fm曻1M-ZB&zu4xNs(#o<ҍu旷@PQ@@h>zA{Qޗ҃'8tEj0Q@)2=is֓FyG<^٣4g43Ҕ`=hg.M8&N3Nx)A^޽)A҃KNӁ0)&w=)v~)OWzR뎴9ui(/J$ȧ߃ւQzi 7qH[ݳF晻RjfڕsQ#HE7'i $u-qMqiojMJi4I~ǽz i<ⓌqA'7JLގ|HJ:(ڀN2h<8H8gixGiSF8GPx(gMFph'sP:P1i\RgA$y4RZP2(qJ &iqI\cQZO.ASE/^QJ3ih(=9&ҔdR~4j>JQR~4v nsG"(i;QӯJQ:j:J3 }){^g4g4gByy: &E&=3KfE 7KޔdRg v(=A;?.his֔ir=.ir{t7iKtu~hg,iw{ ޗ9)'!l u;ǽ4҃&E޿Z vgh l{ёiA4yIZZ?*9{uis֓94f㎴g"^ԃ!"9u)&vNh&vFA&pMȦ}h;Rn?Z ڙ)r1֓i #:RuZL␚;i:wKR{Q$PrzPzFތzR?=@~FyuJNE恎Z@zҊQޔR֐csK׭.sJOjg92=r( g=F4g~s@>(d{g4A=')II!#.N:wiI=iRi3Z3%!ni9=}0);qJzsM'w=N '?J3Ƞ:8qKփӨGqG=(''gz^ZAy=i:ZZB;=i 8hI4QM ? QIqGqF>g:i:jR:9Fq'.hP=3I2)GLQh'Q8ҖII8$⎣'Z\PZN0h3GR/O hGSҌ`Px.8JN(G_!QGOƀ(#G#4h( (hadqB (9)x3@ 3jZ;⏭/z\֓^QKFy8t4rzҒH(HP@=xJPi)ҔH<<du9sINCJGJiQړԝ)x)ZoC:)#҂rph ?AqGUȠu"hRfKۚJLR)>IJ8z=1GQӚsFp8旯4QzQRu4(>ԙ/zQAQNxihϵ&8\M K;IږN9LfҀ둊^NqL^JJ9R ;4t'z@sKގ:֌s(h(>g#tn(#֌shڌG8KޓRcޔ})M'^RJ1J:(4ސuA(8NҌsH=hAhIj;RIRs)qKiFJ/^')8{R\FIRz( 4Ԫ)ssKӟZg$H@◚Lu4~4ўԸ"sJG9ӎ(͊9&s#iⓊ\ R`tsGs=h#ߥ/Nhԃ.ƚN;qJi9)8h4JqA7Z^qHyAiݨcNwqJFic/ni;Ҏ:Oƌ}ih霊OZZOƁ.3GQǥzҌRf~G4KE 3G(AtIɥ)&:R` ZJ:Ҏ)9)/'j\RRgz 1IqIx'4wAF#'җh#gRJNRǯJJgn{ץ&8F3ڂ(9F:f!8< 4sA(ҁ&I.sGRNPx)@hC@ǵM4sc4"Z@LR) QQGz3u֚E)R@Kj1 bG~sG(t=zh҂1GҐҗZ1&(Ҍ{=h>Œ`}h#ގRb(#LbqGQF is0q@҃ />=iNh⁊1:QihdڌPEi:SsGQKc# 4R8`i)݅%ғ4vGҗ}((Z^)=s`f?J)sG^ )JCZ\g 4G\QNiI%)sGJAKQ҃I8cR3@;1@qF:) G)ғ)S􃯵. >f.6=1sg:3@hGzhi ZSҌdsIޓiMŒb.Nh&ҚNq)8j_.:ANGsP3GN H=9"QF(\b8Z8P9b:ۥ'/S~);Q=(g9#c8GF)N0(E֌(Z:^3֌w4t8u9(#_⎦)Oҁ` LQ}h)s});{ҎF3F9=)s8֏Ɗ;u'QK==:QFޔtI? ZN"%4cZZi֊3A9gw(<_~P1z9tvu9J_JJ:(=qցFGHx>h iJ)E.p(<c4F8ZN:юsQ׃IGNh.(zOF=)HrphhM``'nh(')FsA<>cSIqKޢizIH=}RHFG/ZLfdPF(@}(Q=ZL{уJ4}hssG^3KIhKFx!\(4A9&;Q׽'zp&iGF9@>”(j:vҎ1G~h=@KރA}x:GNR98hJRzR:P(4⎽֓E7s҃z=h {}zRdG9z9▂39A<4p1GQAHsK'=Z_lI4sҔIȥM.hF)9)jJ01EH8sFxHxKڐ});\gLPx47J29FyQAJ2h~4gNJOƁƌIҁ9yh4Lu=i;c4>ޔ{gz0sE!8ԣԠ;gx4 Nh@֔֎&y4 ԣ=0;_΅x8p3H}I4v~c\RzR"ǥ⒊4#'QGj=9◌{֔cM SN)(G4d{J>4s@s֎0}( \P 4 LGjA\cGN)){RIށZf7j84gސҔ=Gz3IqG$Q␏j.ry ƌ f Oҗ>/3J9isHqFzP:c4u׭)&;zQFOjN :c\A8"ʗcގڐ֎(tG#29);4cQzR}h(z'gqF1)IJ9CK#v4Z;uw'~:Ғ=i (>Ԃ:Pq΀(J\c4JiךPhhZ(E&34wdRI)/⓿^h#P9H=9;'ڎy;K&{ @(Gz{ў(is@#>g>'SKqF;Fpz;QF9Ij\qNq֗J9(G=:@A ;^4z=sGs8PyAG֌4gi{PG ?(4 ^1@'^* ?'4Ii9&h֗=ZJQ@(<н})OZLP{H:9=:Piqhi3/z\P}!h(8ǭ&qKy8d}(sH3M)G4qցA=sA&sڃڗ88Ԙ:@Ͻ4ցH#!RO_Z1Ih4u#p(9日&xM(py(awwGNq֐җi3J21Z2AޜzQߟ(Qޔi(((ӥ.0'4җbqpsJMF):R@O9Fix(9(&J;}E.qHO֎}c?D=?Z>ԧ9=i{J@iFM}:RcfP 'j\;qG8:R'n(=:QQF=y(<ўd҃HhGj1ihA=(4P3G=(J IKzL{S'֎qI/Z==(zx" /G8 `w9ER9RN(Fx&N)GJ:E NjLh&9)A>}MSAڏZ?^:Q!QރSIڎPzsBQqFxh<}iGQގsI\c/x4<8M/N(ۭ(#Lqiq҃RM;/8&qQNG~ԝtKI׵/Sғ QE i N):ȣ'?&}:Z>;փAL2 2z҃Fi:v9Gl-z `:H:u=RgP){M#v)3G=F4(ϭ(} / S8'/(ց@9Ҁ}(4}sKCҌ/^sE E9GQ֗zqIރix;Q{8>҂ryZ\њPr(2{HIڜ:PhϦ(R~4fh{Qړ>fZ8wK҂xE!ڜ9x#I撁)Gi3G֔p)>):<Z"g'uI9⎃K499ӽ(u)KsGqOJPM!h3Frh-'nMJ:wFGZۭ/8h=:q@⎔M)sȤ.1GNx#JL?MFi?QZ@q&iG=qH)M((9? J\i9Jڌ{8QQ('" 4 :K`Pz gsN'>c5(ȣsҌH=֐ڔgQނ):҃j3ގ܎h)A8uKڏLvgҁ֎)LRQh=Eh);:8+4qP9d@hM掴R:> :QGz8PiA(E} J^~wץ@GJ>g3A<ցȣhB ~g" h R~Tg֐MJ;Ri zLGLcސA(B߅sFphϥw:L}:^4 RF)IG(=NsGݎ<њ '< 8ϽiA'R:R^- ѐ9Bү֗Ssڗ#dg9g"21Fp=(!)A}PZ^ԄtnyIփU(qKIzR1FqGZJ;fFhgqAFqFy֓9=)E&h'ހH=E=JGsҔbx4{bҐ)4ZZN 1KEց֌G_Q'x=(ZQڔQQߥ!;P1FN1ڏƎzRA֓<z:ԔRu=4=:Rs49GJLpiO43Fj;P8iqϭ=8^8!Ԡޓ=zQ;(t)Iɣ9(IKރ׊n(4:њvO  =.q֊3Œ=h_Z#ΓR'4D-'|ҜIFiF֎i88G"IڝIGhw<3zRwGojN;Rހx$ѐzR4ަ\{ӜGZށ掾ugi}$)Lў{Rw4t`;Q/H};RGJA֗=3@N}IdQh)sQ4$19EΎu<ޗړ<ך)9.=h4vdiA8q֓)ҎhO.xhZ^) (G8>ғs4vǭږҊ>ڐKӵ&;RhAQގ4)3p:}@gPiz)ϵ{9=xΔ{4z_z\RIE!׭)NRyQރ@8POFqG> vr=)GސQ׵x?'vt \~t'@sIR'z^ސg?z1ւ(N:掝zҎ' g/~h&H}ihf.qIтRsނ8sIN&GҐ_ƃQ␓^- =hEM9){P@i=zqNg掃(P:h#LqJzt<(4Q֌hƗҐxlҁ^h揥.8IJ@)vF9K\ Nu E.) (>)'NuiqI߁A'ҏƎ(cu=)?Rh>:3J1KߑF8֔~t=:g=A;fьZi:RQ)3ڗ=(8擒ii?/"i=ZQҊR8v旞=)9Pr}8cGZS֏G=hIފ\GzNqF3ޏoJSQnh 9)G=O?-J9tr:Qގc"hKۊo^iN@jAK@z:1GRⓌ c&@"Rc(? &(#E.)184.>i6v9v>K&){PyhgwzQ֛J;\sG(E(<ZNG:Qx`F3F)=i{hȣ=sP84`y4>Z=)I{Q~4ڗ$g^:QAJ:ю>Z;擭Ni{bF8Q?J^)>:ripA&2=FxR4ъ1F 8w=F?*CҁGSZ39s4^Ir(8!ɥj0:QaJ}(4(瑚@=P ֌QE@sAvfj qK֐Z1Ej" ds.8hhbRPx>“rh:PA&9qG|QIsGR֔tMzpzQӊ1)pzRE/'3JOJ1ސɣG4Fq@'bERci~J9(JNԼt4Qތ ^v4gsKRc9:R9t\Z"zRyڂ8 LQB14 ;sKN$ҒJC׊\{ӊO_J;Q4Z\sџ^zPIȥIΔP:Ҟr)LG=hlRb=4ugҎ-;Hyqh3I89RQi~ygjN?u%'l(=:ӺRFq@F(4\`f/Mp)M&=)qъL143ړZqcr))E}#j4c#^})1h<ҜIҊ0O΂{I)))y);Nv9'^qJzxHiquuǥzusI])sG\?z;#4Ru<)ў)0z*R?O—jriqG1Ҍ=r=i#4gRR=h;(<#t4Kۭ҃&)h8P=0zKhy)\@ʌ4c.aJIGj:wQӊCǭ@ҏJp9E(<4QR'4Kځϥ'/j=9gqIɥ RcRd:s@r9@Gz2M&=ANF=iqs@}h'_”N@>wGLu4cџj){FҐG֊=tONQR M SLRځ&ERAAמc=\})=9ڌQځӒ({1/jZ3Z<Ⓛ(p =hgix4RdK):)h494/=(LsKH8=sI׊\ 8GKG~qK{QPGz\SrzKڏz&ւ999 f(PpM'җJNsGAKLJ:v8w/~)F;0:sHOdP4uuўxu:wIt;){c@F@8w(KڌJ::{:QҌM8-(HGsK AGAI׌SHzʗN??4FzQ֌q@;P:QۥGz03֎izRt4<(#=GCҊN(2i3G^~I;qJyh"Qt)'lҞȤ=iyN{Ҟ;\Q8qI1ɥc)ZR(zLKRc'^Ԝ. F8pE\ cҐRzJ0hh/^h9982qGz(9ڌtyG~c#Qi9"MgQiN:vizH(ތRрNh _ri:ь^Q]GaGCGKړ!"NzG/f)3KsG~q\QсR'~\sIGzfZ3B>Q4)sAKF8GpqAIKGQϨҌft@up(0(ix >`$8M/ǥ={(1Qu)E&G#F;{QF3֔;1;){g=qGCE&AڔE'NbʌJp4g.x9)<yJF9MJNEz@ /~/Nh<E 8lc; 0IsJ9ⓀqK:uџʗҎ`x֏Ǝ(F:QlP)F2hӨR)23 _n(:@~Z (E ?1BZRyF)@4Q=i: QG^zP=1.8'ғޖQJ8=hh);KsFIG~ r}issMA4IpFzP0sNZv) юhI2(҂j0q_Sigima-1.1.1/sigima/data/tests/laser_beam/TEM00_z_80.jpg000066400000000000000000002351201514013333200224660ustar00rootroot00000000000000JFIFC    $.' ",#(7),01444'9=82<.342 @ }!1AQa"q2#BR$3br %&'()*456789:CDEFGHIJSTUVWXYZcdefghijstuvwxyz? ҁIӿ>ԤZAKG~sH[j`֊CgҎz@xZQJM LdzԠK:rh)238yZOK((4u4)zuP99uJ:QCKN4Q&_JNZ^b篵qFɥwq@=M <҃ތic4Qޔ}QSE!<`h:ڎ8'Z\ OzɥLќu'.x<($gL4@4g/nx4w GSj;uE"=('Hx:8J\~4vA#җ=-(=zQZJizqbKތ֏u\vvqڔ $@)84J8{qFy}&{PN)G&)ix23RO4{=K=({сKz1֎sFh?ZQIA9>bJAHwAI?BhSJG=h(zQ"ӵJRxoM/Q31H}J1Ҋ:QI{iNhb=i8gSӊAK3Gȥt@#q wў(qGёրyQON/j^AuJAK׵%{t94Z:{PyڎZ^ڐjPr1F*94r9K4Aӿ&yIPO)On(EI jZSc4RҏqKւ:H8(⎿Z: 3j3`>ch@o_F t=(wp(j? (Qړޒ.yKHG`(' Kh(=(ђ"ڐp)n)sEN)}M&{RҔvO?JJ 4g: ;Ov(=MAEzL FE~MiO^i3(▐x'.r):1@4OjJ3ڔ٦Rc֔r(zSIӊSҐR:QΌ⎃M)4bGP:c4}gLv'NԽZ4Z3'J^ړfAu. xA&A<ɠ PM&hHz 34Izȣ?-.x<^shQh94c4i3;@4Z94gFq!piA<84 >b&}iEd1R3 Γq@zNOZ\֎hg4RK֓y\v~:^xsF9L$uiG?z(F(JxhP:ѓ2h< Z搞hi\ӽh'IƎg)I@ȣZLџZ\I'K(>gғM)ǑךAA84(Q(>L@KIz֌GzZ;IJ_ŒKۭ3HO=(.EEdPzKځғ9FyRn4M}iA#)zf)sQ8 @Թ=h揥7Qރ.iځGZ(8G8P Ppttƌ=蠞((hɤ:q)@4 Zo_jSځZ .xǭ&@cfFqN9@&QҌRRtuњ3H94v=收)<bqFh:QLFq/J3KIҊ3Fh)3J)8Rg43K1֐ўi{P&!8@&yFhPp .p9GcH:R'4Q=(֎v=(h8c>(s(Z^w.h:v^y4ΗCvѓz(IRdiw H;Qҗޓn)x!@=h<<K(ǽhǭfzRIi&x(:gA8qA):ӻR 8=AqڂZ_jN?t;KC .s@<fKIR~4)p1'N 4w'~dփH:Ҟzў(ڊ4`Q(84QJ;ўhfS8ԽҌN٥GJ:LvRIzQڗ4Ύ`:ҌzPO@=LR;P4c tjL;=)xz028=(RץG_}h=i4>Rސu/JP:&8%!/u8)18(AF9>c4lQ 3Fy=Zh;fcZ;qIG@n1AzZLwy4tRڃ({@ҚA⎴~tŽ(=Gz_Ɠ4g!h4MQ@h i8c:уKq@'4gR:1I(j0?y4c<8&zяzR8&3ڌvu'>ԸG^w~T dюԤg)q􇧥zPr(>H=)Iix4AF)hJhzbQלPG QQG~AGCEr1F8Gh(v 4Z8 b(&)OJ@J:QJ9/c=4\ю):RS{Q?ƃz14I яJ1(98)tii1K}h=(sK :B{sF=MQF9 @0I&)OJNh`wqKs&; GQ:c4~"{F:QK;PxFi旞41(M9(֗3A9KJ1E%.)iqGzNiWIJGz1ǵsHG4:QKIߚ:Gz1GQF_&4tP? 0;ސrih?J::SKH:1F9u(搎(h"sK:Ҁ=(;F1j(h4oz1‚)h`Qؤj1K@1GAGCF:t9cރzR:9QF):)q۵|s'Qӽ(&2pi@4 6Gz14{RIނ;4Qւb)yqҌ`EuHH{P4(\ۥ!Qփtǥ7P}ю<ъ.8@4}iycҔqGj;b֊;Rszөր3J(4ך: Q(?;QKRwz_ÚCӎ ZC/zQO4҂1Gҁ((F1ґ)1@4b1E(1ғ6i)4shǶs@b8<Jqސ(fzxRF;@9(=8AJ91)y!);M/ZLbxP4c4HFsAǽ&01֔QxKE󣿵)0s֔uϵQJ);sK'J:c4`RJP:R1ϵɤsɣs(RcӥEq'|PzFy((S⎦ۜc m(ihҌNn0O4 IcҌ((9ԟʗz*?Z_zf{QG\{z=;PGwtyzGl(QNhRsRR " ^i`Qo"8'ҌMҗړ4sҐR4 )h4ҞGޔ 9H" /& 'NFEs;4qhi9=1GsإF:LqK4wRtJqqAƎԃތR ԘރғLz`cfMh֌d@@J3IA֌t&0=h)1GJ_QށJ9S&yR7/KGz#4i2r2:ҞO4p2zۧ4tR(I@ttq(Qރڊ^i8/(})x4R/nM 攎h'cA< 3Ehx)G\q:i9/:?Z;ڔ);Sҟ~r}(z? CzQ? >Jq֓#9֔M=zQFhh>;N;0M/z.Ni0(瞔g'QIJE!?g”u8Z^ŒsNhbs0 z NR)9p1Gր0sAɣ4Pzu'QKڐRsI׽E ǥ8 :;Pi3E7v /NcڃRc֗砥ޓ/j19攏ZNqG&sG|QKڌԀ` /lLqG@)~sJN{\`qIh#is)2=iq}p1F=*9F(ƏF:Q=qъ: 0hvZ=(z3xsG R'(;R/&sǥ!9KFxhz (Py`4cgF0:tIb`(׵%.9RZ^=IKӌRLPBdRh8)vSF!K(p(QPE RzڎssAǵ!s4g/^r9'f=Ԙ^cڐugsAZ)zKHhu9){RR$G4}(?_z^٤!Q=)zsڎzN)zP1G4u}) /Fxzj94)9ҎG4q@q) >IJr:P=(4ަAF8');ޔ:сIJ^ʎFNxzўg)i;Qۭ(PE8RL~TtE fA()Cqғ8(<ҟi4J;Q:(Z=RqH8)='EJ8:=E'\QA=h)=N;RgR8pF{ьf.TJ1x'n(A:Py>$sGqGќRQHzӳ3HZQz҂NyRRP84NQQ~Ɗ(|QרcG4h=Eގh9R): \qHN(ڏJLQ4sv 'P:ڃփqڗR`G)⛃ڗ1^:RZR})>f<GF=^:wҗ!{SGƓKO.y◵4iy(֌v=h'wIt"{юh)AH)H>4Ԕvh=h#j\qAZ?):w@#9&xKsNzN3Ҏ (Qhsցz'.8CG9A?CKփ@'Hi@zA4wJNJ;RcKR R qG&uRu0R `{1HH=p=9})? ^Qڎ(NMGҊ:h@P1֓” N(@KG.SGQhȤ!4uZG^ii8ڌ}iN)pzwԹ$JzҐ@ƀ})1֌zҎ}i(_lQJ1֎آ}hKސʂrzGN)ڂy3֌QўqGlQ0(Pyc3Q9t#'oz^i2x&J 4wu=2h4uRъLRC4Z3((4uKJA84ҀGJ\R Ҋ(8:Rޗڗ&y'(IΔLdҁI߭.yR):֓N8#8␊3Ҏ)xuJRpA &1J=$uT=Z 4vP HI()sOʓt LgKI@/sF@ގ qE/ZCڊ='*;zup:qAGJ8=1FE.qNv;JL旂9JLQҌ Prgi iAJ4ޏ^)s4.qLc^bԜ:zQSi(p(cBғޒF9&ZSRJN1K(Z旵'n^~yi9;RIj^~4q)I}yԘ?;r)3;ۭp8PK E(4Q"M)4U>gC(֌N{tyhϹZ:4}iJ4rAΎGn (P(9g@4g3G8IhQd~w@)2ihڎx=3ў)x$҃ǥ'֔`tK8֌BzP*^RƌsړZZN2)O\fSL L^)y4fԼ(ݎԹx'RvN MiGOj3GqHIڐ)EⓩN}iqޔs)sHz\QQך?.xis҃׊AyN4y()OZN .9I=i3N#H}(43G&xcRh4K8⁜sIRb}&I=(#ҀqJ>c@ؠ)Eh4<ǭztȣn(jSx}x'!\=hѓJ !ITzb)1JzQIȥ#^9QHhAK3G"Ҏ(1GOz9&1sH=isZ>`QҔӭ'4qHRd8JS)3(QځhZ:Qڎ{P92iqIzRҎߍc(ޏ\Pqg'?ǥ (9ϥ&x>{R*^Kɤ4PiN4h^ 4w&h=)hҊ8ϸGJ2hs)IEў4?>gJq@HzRNJ\QJy$P9cӽbyhi)x& S-8IKK%AzғZ@N({ўM)8QfLiII(4;8shGFx)8bK֓isI)GLPhI)@s(h /jNQO(挊LJ.zQG֎ҎhgJ>'4ɥH}:QI)@$p)1\P)s4JQ'Nq@g<њ0;RsJMM(h^Nriz?N&F(J3KE&q((G@sG(ȥt2ph;Rg@#ўz 4"u (qGZ:QisH{g_I( /zў(A&~rhZq@ pGZLc8R{R{9hJ:挊 L4dtޗi9FsI;v@hZ3GZLR㑊0 'җCqE.)9qEJ3ރQh? JȤǥ( BQC@4R9/F;P3ޏނ88IޏŒ`qGJ=0(G4i;RKޛ4#_n(PN)/Z1J=ߕ=:QFi9;RbAޖӭ=i iG4 1A:Pѱ'N;P(9=) ^@iyLzҌ`GOƔJLߊ_xGJ:!?7t.h"E4g;xRq/nP){fzRKG~hOJHzRwǵ4@sQȢ;⓵.ig$QHz4EGJ4g4sAhM})O?ZN`sGQG_.)4gQɤ'ڌq%.9F9<RR~zQފ2sғ.;QڌP8uIKۥ9zbR=xϥ)?Γ8ғ4Qڀ?ZJ^b/A))NA4R;QGZ(iqi)GRڌS9c;ubSA' i1pqKSx 9=4:ړ"RzR==hGM)q4ci[&8'zu&8Kӥ(H84Z3)9EF(.=(ǭ/lc1J:R`c&qJG)^iOzOKގCށ)9.1JzsHAEHF)};rh< QȠhr(=hQރZ=(=1F3ip3!4`PM(AfP(E֖{sR=iAr(9(cJ1uq=2(sJ(h9jN{PAcZPNih֏ƌd惚1ڐz9Q()1A~TҌr)H Ebb@GC):v4b&1GN=hG4sF0rhϭ7#8s`Fy1H)Nr(}3FwF0zPqzNڎ Rɣ#`\Rz\Q~vMJ1@Ji^M(ё98u/擽h';})Ebw=iN?Z时)!ǥ(RsjAKZ;sҀA(?QAZL~T843jZLv< 1@Q1@sj14cERsPsIzw%94cQɠ u%ǵC⎴1F;Lwۭ-4cNizRvhfӀ)zqIޔ89v"(|ь"QvRSzQׁGGn(ǭP3\40) -i:tJ9F;֔(8Q@@84QҐтEQߥ)RŽg_ZiI30z<u R9F1L{ҁAҗ9擜ӱIڊ( E—'jJG4IڌqF9JonuR{bQi{RG~4ERE!izz;t:tjA(ZSF1֓ ڊ\ 'CGOzFiqpiؤ &)Oj;早(4`gނ(j:R=jR0>@JCڗ8'n:@t\cAQZ;M{wi} fhJ0I)PzR'z Lڗ :L~Tj^A`Rz1J}i(QKRR8(Rc#3`RqIhڂy)J9ҎF1֓4{Rx KG1EZ1ڎғ8xGzCKu8NfM4~h_—HIޗf*1sF I4h9KqA ht4qь4K:Q)1Ҍzc4RzsN!B ^ŒQߵzRZ\g&|;wG4w񥢗>#bǽɥjLgvJ=h y1HGZ9H9{֣t("P89fQJ4(f#i/旨HZ:uڙӵchI^Np(HM&:ӏNi0(:c旂)9֗-'NإjC;KI^zdqGҌQǭ 4~h R;zR?7Aގ(ޏOZɠph#(v'3G4?)qF=(⓽.rHsAF}:QR=&=:j;)h )sH:Rރ4}h9'^bnh dsG~4p )xc#/! K7NE.QIzӻIޓ<ғ:Lڗ6RsPxQF})1G8@R^=(=(P(iN'^ؠ`f) A~(>3IQE)):sA4xǽQҗJ2M  h9G&=G={P)?_AMb294G)'@4.GqP dviGɣQސsJ}{sK(.H qE9>ǚN֔ސ4*Psғ$)G!'=)xKIУQӊ;41ހy ڗQ^ʒFqGZ;(Q3KRw JҎ~t uGj1Ec:bbw ^`c&3F0h<`QރK AӊޗސqKI1J\J2(ʌH::u3q1AKQ4ZK4 .; EGAAz)š dc&3HN:t49!A=ǯZLwg3H}AF(fi*;ތqGNPzzQKH?ɠ(IKhg?ZP3(#lfJ=F? 9J3/lRzzREҞ)(Ҏ:┊:QP}0iAҔb:~4`u)&NsE(O)Z\zqHzƗ4{@F2:Q(#^QHO((^Z3Gnh});N;?┌p(9FsG)1G >ԽG&Sh}iGJJ)q#RIך_nJ\ZLsւ8bx4 cQN8( {&gM#{f)NOJ^ғ'i{}iAZCzsh=(A\b;JzGNhK3'^i1JsK!z4Δ= /$fvr(4`sIt9qH:G8┌b3HE(HzQKޏZLcތ fR4惞sGhqA1gޗ1FlQggK=)"擜֗ZR =(ъPx(qE'NisȠ9惏ҌspisA揭qJ89QҊ3K4Iҗzќ;RҎI@buJҎif&0sp@%;)$ҜQPҐ/&R3HzRHyq#/NԇZJJ;?*3N1I 4qzC4qJ9)OsA1I4Gp>F/4iQ)Z==h}i@yH0)ߥ ;?Z!9;8ϭ.1ސsh uCKאhzv9gy:Z@Niz:t4c';qQ4ӿ֏Ɠ#8qJOLR`Pi3NL=8>{Py?Җ gҎ3RIOjS&)}JAɥEΗwhAA?izJtdRnR(hϵ.i89\A@ԹiZ3/ndh=:Q4J(iAI(=y@4dGNsKsA=z({@4f>ԴKr}FqFp(:RgRFN3KHq$=}iA^(ɣRwџZL^uqAhhGj8G|i(ɣ&O=)zQhhϥ8ғ.hsRpO"}ŽH;ҁP(y4q;AFpzsIҌQ(&h9ށ g&yE&{b=hR)Z?!'/^FF}y⁃Ivvڐ?֌.xɣތN)1(ǭ 89A4gqj\N(束ʚiAQg4-(IFs/L⏭)^isA4T(.iH2;QҌ-G/;3;40 pisBphzP8K)qc<(#g=i})4tJ1֚G)@>ޔ RcL}hIrEz Ҍ`fӚB;)( =($>)=Ғ})4h&y'|3ހyڌA旊3j^sHx@)3J94z4`R4g4} tQIiIhPO/ &I)3\H3׿/l;R.#Ҍwis{'44})Og/揥c/aIz9Z3ޔ!=ցIJM)cI.y~"4uhN(:ZP3N(J=)@)ޔ`NUF(AK~"&y( AGϭ 883={ҜM43ӵS{9q)c2( &31S~=)Fi`ќd4 u?ΐΎ4c3F=i Q)ihhGA@s/4)hGj_jCȠg߭ #ҖI?:R)Z : 2{Mt4xt9i:~&F){RA4֎cړF0xi~h')z)O#'N̎iOR}E1KIIߑ)H(QKiGQHs`Q׊LQZ^=hrsJ &=GRwJP=hZLq99})qw=(4tP(=җ`ڊ{!Kۡ GJ( 4z t)O+QI1)qޗ{QGғ)> :zy8I(֐;:tGCI@4pi{R}(=}֗'~hdv ӭ掴I>(=isGF3Ew=)i0=(h4qŒ`f&9z^1H/^*QJ(K=)qJ8j\gҜ8=z p_j)p)@Jp]3AS;Bv ( R8ހ0zQ8i6JSnhe⛳"xbMqH)94¼}MǵRu))IN7I(ӊSG03ך2MOҎsQR`zQ1J3ސsQގ*AG|֐ސ1hA>Խ) E%(=K);Rsږi ;sHO3@iM1;={(:R PG9IOJ>hǡsIN3F8RI=ҔiACK!F)49&r:RuJ~R`)_z(F3ށӓKcJ>Z0(x#Q7z \ Qh(>gwixsIإtIT>c;^p0E.)Ì \sx1J:S{ӂE*i;hi);f}xZ]P#Ҕ@R@#4fN`jjCuH{J#cT7JSFG8*2sLe␎9x*iB0)if4cwZB(SEqHz\qZLqA:h##ʓgu=AIߚSQcjLWⓒ?c;юhJ6M3֎3IR3HNcz1IAF(lR( Z1&1ך0?84wޗ}{Qz\QRc1AF(OCޗ'~)“G֓> &qJG4cg<ѝ)(=^x/JG(g~`^hҀ:Ҏ9ڎ(sK҃RƎRH:RsAg JJ RZ/@QB9J1K .8^h:ґNucҜ&t)ycO׭(O\\s~3RvlqҝN 6!LJS"JBH1Qnͼ w4ݾ/ cqҔ}gzx)҂4 \iRZ6ʙO+yaF ޔ@ czP):sA 4zJ4t!RPzр:Rb==h9GN(GjS֐Q))8◌QP0E4<:h QP1(ip1I):R)q4K:Ѵt:ьxRB3F(8J_!8bo|=h# \dw}{Qi@.E!"H4G9u6Gz1KF;Rb(^E(ROJ9ڌb NZ:KLP-i:掝Fb=(=)1J1I'-iF10E(Rw4ǩ(./'.pӀoΝ*bOjpZvÜOH'Rl4@"x\Rޜ"))Bl 2(曳"#hh:SgFT~P(d=7f 5ӟ.1cIja0P=E9Jh^sMaduqI=iE c4y qI :v(4;qH8ҍZ:q@ i0E))4s\9J\RE'z^;RRb\{QҀ)8)HGcF:R'j1Ki=('ڀ8Rv.(=("u 9qE!QRcH߽`Ҍ')N(TE)ps1!cKNԿM49t Ru84{ 1) (j^z3җdfF9x`◷'~izF0i;rF)zc) 119(@.= \w Z@9c#IAQށK1APz1QP";jv9DZsNۓi ֞zx\z=b8篩펴+$gvÃҞ#=zѳ9S4=zR iN8/"S)T;z8=)?˓fߚ#FzR:z}i')8ǑQ#4"LSvz9ȠHWZh# p{P>4`y4`Cڛ9hƚ:Gv1L'8;uG|fgqH)9<㹥y&8(9FzROю)hi}i~Rr{tb;ҜRZ9b{я^~TdҌ(ǵN 8( (4 Rg#=(~JQ #8h4Ԙ\P:2?:\wF)i;ԓMhR*Z8@◩!I:Q~4xIKӥ4QIzRMp:1uȥO4sFM!< \ .sKi(4h< B9cbߥ))G(ґhK-/|SZU1ҟSo8ޔ8 ^}{R}*Epy }jMl r5 Ly6EXPc`S 8FWqJ#8)9Уu5@MsQF2qQA\31LqL֚ٓWZa\A ^E4aȦjkjCIi0ACޛx'Hx<ڎJ8uH=h#'4>=(>h@s֗n&M.iqRu84dG\ќu=J:I^3փRQhc);.1) =1KZ #4}((Gt4wIsK 犏\t P8IGJ9zN/zL:{IJNi?\ۭ&8ȣ34dRZ:y(KfIׯZ_^h'hR;Q(ix f84Rdtr;}@ނ8rhC^d 旌{:Ӱ:1֝֔)p=)ÜS81O8SSzryT3xN9'"!֜?o=Hu#(H)T`末;o=hX(1ցIz i'#ڑ  ޚќb4Z`Lk9q*28a59L8i3HG7N33HFi 4ҌpE7 GϽ;֔8=)dF /zC?*zN:QH)4IP;hGҎFhQǽh uJJPE⎸P9laN3pph:^t/z4 xE'guf3Gn>F9ڌi{dt?'JQI߭1Cv*1K 8\u'wҊ1A>cޗ421҃Rdڗ&qۓKӚ\Rs R)J}vF1F==hGz&:AiE'zNz3KсGZ^i(RM&*1G@4QӟNԘւx?-KGn.њ}8iqJ1N)Bҁ;nO_< p"x\Ԫ;ujMRp3RȩzjEJ8iAB S\ x#'O zwy?_zw0hg4#J"8)=*3rSJ)JGtJGcMXm8ɣlcHc8-Q֘񝹨gc=j*6\zL1"W#i SsMac֛73oJ^07c4"JGR٤֚zғJ=MP;QN{Q8ǭJf= J1Ǹ9'L p):cp9zR}F);'#8&1ށڐ`xO=()H1z ;4Z^ICKތ{?:Z\}(ʁҎJ1iN/SHFi{Qڔ Lt?J\{QI_CAhړJqQȤ(@h'JxK(⎴cPzQۜb8; A- Z\q\)x;fҔ)◽ԽGփRuҞh)1QF8&:sN)G4QGjLdbHxt<(lQށIzg83֐g91I^Rd>4z4bIQQ@E< ps(A .r9RI^r>sq(9(qH:֗:~4`)t4oǽ(;Ҏ֤^Hϵ=@vJ:(FhKh=){RRs ֐()x:RiH1{ҎZLt4 1i{PQ iiqZN{RQG_4>yLd 4=h^h9i:RTrzҌdu'%g?Z1Ӻv Nh?߃GFsGjf(i3G=PIJ49zQғ=)x(/q@4qIg\TRf}9h'\J94qKҔ`w)zҟ084|^}UNRJ8R*U#*)#Ԫ NALT8ewArE ^zS389;#:Tc4Ҁ8HޔGPh3AKѩ\qHzRdP(ϵQJ^~3#/Ҍ3AhR~iE!4uQ0GzRgw曑\GZ u 3MG^4RO=ixϥ&~Z c .hƖ9@c8 RKzs <iQTj@#HIRS* T=je@:ՄJvd(8xe@t T2'^ L5F♎j7zi3i 旷'FgzL:sHI8(֗Iޗ9(tv)┟AFqHzRgMh@"@ӭ&x/j u'sIQ׃ /zzGZ3IӂE99ڛ籣'ǭA:ӱIڗFi:{R((sRcM/ڏ΂~1֗ڌ<(rhO|ފҗ9SO_nizvtizh94җ4硥(ssA4((t‼4x3N})å8 sxN^84zH}E3R3S(H& N1S( S~u*2&?V,zTaSgdPcH@RԹ h4g:Qu :HH(4Z\h,{MsF^܊AK֎ԙGzNԽis⁜ ;q@=3A@KڌBjSHNhtrGlQ/=$zsJ>(qKҖۥ88sN(Nǥ8i1i ٧9#ڤjUjeAMN2.Nje81*p*kV#Nj'Joz-8.}j@O}:R NN qJS~1^zR\b1MzwUg!I )9viw G֦1~M<5YgAf\=*:8j**'@*l6*2)a4 i3z_Τ@OƧQ3S35:qVPdgb1V2X@3VU@1R5 \x\usRZxN21R'ԊӂZ9WqN^ߊxGJx ҚJWTo?ƘSr*-!c?4:F4NHzьsG֐)3JM4j\zP<\RvGCAG&8R}x&}(H Ct=(#N)ъ\sҌڌQ({Qlьctނj0hPc}G4QAIzR0iy)@^hzp</QP:=I"S{ԀdiRGRjUgJs'NUuǑҧHՄBy*㊝Z y@IR(U#ԪH:ԃ1O;ni^JvN ӥ!Z_(y}MHb$S6L+L )Ҙ~qktFM19Ff#1sQ9ecΫ5QԂpTҪ{Oj#5XH:T8 ګ#SXd:cqڣ#=iyiTdwAP)3HAⓐqAcڀ2)jL`gcQ@bqcۃIۥ(>_“{bfG ҜG8h EJqF1ғGɥGGAҏu֌{RdԴ(t⒊\PyGқH@ K(AZ@ў)z=3AG֓RAN )=iFi9Kxt=/sG Gz\f3;QQsE(▓RPsڌz(2:iOJ\qޓZ\i@Z@9ӱ^( @┌P41N R}j\p ^=A¥U=s֧^LN=zU5ib5*ij4P*P0\S~\ԡ8O ޤۑOU=JҤQH3Ԋ2iO N$r:Nb{ѷ=:Rm1Mǵ4Y<]FbFpF*32:Q'Qc/ j#ڣcM'Q#UVP#㸨ܜgP E" V ZD?C ™Lc.G YI}i4I) &h){dP{N8=izWO*@ JvO5(/Nԡ JTȾ0^LU^=XN1/Z*gb< T㿥JJ&jT*U_JWzxOjF1ӚGڞԁ=i0{R>Zvi)JAi@{RSڗq"5IqH޽)2GsH@Q7֣`1FPTNTE2*6N1Q(Ğj">LuQqޡe?Ur~UY W>_rjaT%&gzcEA; `r*&9=) zTDs4}sӥGڐFi ␊LzSqIA҃RFri6Ҏzu@┞i1۵)OO Ruߊ(/^(4w()9sA1ъ9ȠphŠ(%-9`1JiSQq44gQi(gA:3G~9Z^p(&)wZSHc4G=h zQ8KIPOJ~/;IK9=j&3UcDTqPTl8Eڣc銈8g֘uj7) g ɠJCԄRqw)h#4c BOR)F1@8*t8(ɥ4wQ҃IFh=(<RRFii4ޗך\s1K8GlQۚ8## >4f}(CQ/~tE&9);:uABԝZwIG(}h;R8?J\zQ4`F8GJ3ӟΌP:RP{Rъ&qG?( /'4=izhpE/K)W9N(+(ǧZpJp\^:S9*ARnjU'8ר{_N'l*¨뚴9⬪FaP~5"5.T1R*` qOqRU(Sȧ xZ z8zV"#ҤH0@=zSAPJB48Hbiu4;ToZ&C1ҡad{ 6>بg4,93Tl}6 TeUdeNҧITR(= ̿6e@sUPJ5SS qtHb鑟J<.qQ=hi'RI׃֘@Fz{R`1IiNqI::QA>րy!֗gxҁf}M/zCpGjKړ>h?{sN)Nh(i穣M@P:'$Rњ^wA8 4w9>)GK03@Kۥ&s)-qւ(8E(93GQ@}8G>Ê= ѻ(<.sIץ&qތw^w(Q֜$ =)~SNP1Ӛ^SHFH֦US($vN)U" jdgYV@TTqU*@ԋ`Sy'P8ECOjp7L z9=M)lud '#Þ)qH};SH0~1Q /nZ(2}j6jL0}^zqQelD{qQ8g*q*U95^F]Z u$٦KsPgMC&4̀8J4ޢqi~8yh֎Z/Q58zPh d8ǭsA'~)i({f=ȣ֓cQsސK3);v@4t4tϭ!'v'M/X<}(:SD)|:ѰrG47N*@4>zwSKHM4Te/ZӚf iEB\UTnYqҠu*R89.=%/9#ށѓ0yGz1F3x>zA=)O"u@AZ? 8;P{Q4g-:搁0$9=E; Kڐ 3RdRrOG⎴FzPME/'){\T{ѐ (?Oʗ"p1FyZ;tFr{8FAK/ҎRbϭG84hh(hh44჊wAOSOZxT~`jt9SL#]I搒OJisf^Rg^4w;s@⛜qK.x/u49c#)v=:GjN* 8D9YOCN>l-jFsQ151c@vu^G#8FNG=*#׽E/NqP m$^y7#>nW+摔5ip'gӭ5=M4y!Ӛ?A4K}({QIӏƎ~&E'O4 N⎜Rw19hx փGJLRQցRu4=i;=)zGoz 4bx&<&{}1Fr .GJN1GgSAG#(8zQ:QE&qރ=G8LӚ:KH4sG^3GJC߭(I-/(Aڔ}Q:JwҀ9R@8<xnyjLҞ'JgR@Z2x9F}jt5:(UQ*I1XTVbL UՄZ-J=R ¥^2wP}X:J>EJj`x*e#֤-ץHMR*u2HO,q7"OƏqIҢ(NOqLe9Ҭ~ۇZ3d`$Lg#Jڣw^vz D[j7 w8C #ޫH=*P`tjX0:Bw#Ze 90OJQzeDMGL=sH_Td!9Ҙxқ@@㡦$PFy(E&xc>i}( bM>I#ҏ~hhi4ZRc( K@FMZ>3Kގ9hz)ix4#>($OƔQF{)1(>}M@4ch==h"q;GӭF}h8ϵ(TKjԊ3 z;sGj^)?җ'ӥAڂ})y4gҎ9J]܎"/=R;4KޟpzjNirH$4gҗQM&ҌFy)sIӭ/֌<ўhQPǁIJwQޔP:R@'~})ENxc<zSq֟Ԫ*T1Rl*UoʥVLx!CLZ{zԪjdQөԪ*=c#9OԣnZ BGz^s@Z[>2gL2*e|֧TEJaG@yLxyRjߚ@T 2EC2b1PHpiIIޚ;*1QHiHN7?!g&sӵ 3Hy@=(8=i=zvqKRsCKQ\N)%.h<(:F;78"NMџʌ֐zSI: jQG4tⓧ4` L) h҃'QGJ^)-/S Hy'Fiz AJy{Ҝq82A8)sQ=z\h=ғ;J>gրp0h~ʎy'Կ.x$RS^3JZp vi0jUsަCu*1sVҬuQyZJI5mHԪ@TáS(ZVQS(TG~ELR>"9sO\qHAOZd g9{ўMiOJL Q@֌њOZLqA)A;Rdf=i 4 \f#F{wgQ:ތ9 I=(1K旵'E(F '^qJ:sG њ =)9^)~*1@)HOt旭'JQAғ/j> :ҜI׵zQ=zzQ8(Q4`u惌QJ9 g .)@◱dbr)ÓOS۵8tR/jGPTڥAZ+Rr*®01S*1Vr NQ`Օc#J2*e$dsLN3SFԫpiH=iAj`9)vQNsӊ6#`P[!sޑ M M2p9'CQ)`5:QuFH=lbnsQ8P`~ Q5jL9S&cPJ21ګ6sE!;~`j C#wJC3<`TL<qP)*38j ~j3ӊ֐sM4ii#@}{RGJ^):( H}iy(3H>`GZ_qIɣ"v;Qҏ⢓Jҗ&xh9QތAюsG:Rsih{}S^9Z1@hKߚ3'9zQtqI֔ҎzP14ʃߩ=('Fs֌K֎ J |ӵ/QGis@@}A<`43H3gyў.8c"C돭NcڦCNVP}H5f1֬"208 TꝪ@:T*D$L*O*?L L5(IxS,5*ԪR<0HfOzF)~TҙsLh:DWң*qQ>A51GDNyiy<2sQ;T[qQ;j2bUI0A$#oR$E"*e8ey֫GNjQ@BS;2:/'sQ4SQ)R1H '_ƓqF{Rzh'N)zރH3ڎ(Kۯ4'G>sj94h𣿽fdRg g=_HztgM)>O^Ըi#ڝ֏ΎZCP:ќޗғ=)~jZi{RcQ1Iڏƀ:Rz8'v◵ P:юsA&ތ1})zi;J48 zڎ4g&3Ը)qGRE Jy4c-.)Aڒۊ^qN;ȧc)JsҜsR*N*Tcjj?Ne$Vc~s~5n7ZBfҥ\T5H,1VǵHqOUǽJH SR"(9nyM玢Y8Cܑ{ԋ>Zڜ&<ӌdP3.񞹥߽FXE5Zڡ*1QBA ?Z@֣(j5F*=j)385TdQK&:uLUY%䚅ߌRWRzcҩ3~;UԂI5Fj @MD1 F z| dS:R@}:~ZCZ@(R8qtG84tKhҁ sQJ(Iw)qإRIߎvJ8@sAOך '4I@Gj1F(QA#E`f}EqGn~Qi{p)>(h>ؠ ^)瞴'ӭ/q֓J^1R89{fޔbuc-!_J9qԸ^&z\ph(RA۽8b9ch`S8tJx9#ޞSNyQR RH WҦ@qSa8(pF*nn)ZY?*[J520jd`:*UpMLVt(\T<(는(<%9Pg1c6*2|gޣ85Qu rMD&e$qQq*T$ &O&b@5Rf;FqU'<RGZ8J-D ܂9 6Aڢ~taAt֢?Ji f9ҐQZ1F= :G?J)8sH:R=qI)@;4c'J23@=юh:uґ:h4=1s֗<֗LQڌQ(I=hf⣽~c!?JP{RsQGJ(gR~4c'9h84ޏKE'wQڎz^\Qӊ\擨xޔtԤ4Z1SFqJO^)bS{ҚA>GJJR<)4d֓>xvڎii(i{֌) 8#v((#?Ҏ-h4uAPA旜pE.@t9M<LRtRʝ8NӔJ[?ZN1R{TY1jIVRLVRA Yގ:P}4J>i)q /|4FsG|H~>dcv@"=i_|R44g%9qF}i@ړz:R 瞔@9Nx`&qGa $)}(֓⏭'Ҕ J:4sJ3I88B~l;Aj8 s33Iv {{֓3Ȥ֌ QA&Nc984v4Rh=iONy)i1K'iF:qIޔw RAhOJ1)z ))ht>'Rg)pzG v4J:b 9]@H'-'Q(=h4s4gt'K}iOi9@Ҟg8x@9\~TL⌎ 玔Q 3ց֓?74`QHM/G4уڔҁKKҕOZ:ӁqN=zRǥ<)i׊zi=EH:`Tm*ޤڥ^*EjQ522LH:HA S Hv sԁ>~=AEI(1GךB P3!>ޝǎM4 BOz#IL2kIKbc7uu5qUj9dj#ZpA)Bzsɨzf`7sQ~j' Toc=5u)) 'L43MN9'^&RguN3Ah'4Q=(9GzNJ\K Aю:RdNsJFsE&Niq֌>QKy4'ҐM.yj1h'9/zRE )3(4is!G)/lth)3׌tҏJJQH:׊3KL2֗b@8Z_IKM984 Z?@)h9({"b Qޔt;QQK( j_'ҧVsZRz`S1RLTˁޥL*1ޤ\TUMwF9'nsG^ix)1(tg:P=n(@zQ3 /FxFsJ 8$>)?Qրy'@.zQg&FhN@' zP;无⃃ץ'Q)Ì4c҃ZNw);F@8(hlP:LPh֐{R9ۡ &u()sHsM)H>)G!Gҏ΁Kړ/L Ƞ@t.M'8fJ3ޔ{ߊp; (aT^)N(jASq*P>\(5 OԪTߥJDS,XI*Ozn5agl*YAx1֜&)sKR8HpzRt9&9Z2}i!'aw4(ޑ㊏SZȦ4}EB^j3(5~O5 0G98ϷE&@xi$ SO+P7)9Qm7Қ)HNM!Z7Gn94u8g)I@qFsEQCAZ3G~h >RvZ4R3F0E.8qA^Խ NOQҎu4sH)sGjBsҗ=8K$?Nb=yȨAE'lE'4J\GS@hFsQӚ=*i;qANE.yϵ/3ڃARh.xhi;M/^ }(>zc)9fҎؠwzNhg3JS;֗?8sO)sJ8{SZplSRqԡjE=}NޤQO^{b\Rx*U`TMH21Hj@:!5"ˌR5:\6pjE9(ZpHSr?:Mޣt)1HzS&xY?^bҡf ֢w<'֣Cfz 'Ҙ5dP3ށA4)0zE&}㹠t>df9izR8:惀:Rg9P>&~(݃ҔPsq^֜1)?>#Ҟ9\ӻ ӹIϥ9y=NN*@a> sJƤ׊Mp<~2MR R,ӄ֟q׊rc[֐OZ9t'SI# 9Zc܃ޙLǓ֘Ԫ1R)s8~NwQ֜'&uy4u=['&qx+pAi14jLzu) ʞœ{׎))Lӄ=F)^r3NzN֔9x-4M-H:vDL^j&♃{`'8463(?CLNF:R&:Qӵ!K3Iڎw=h9R}(zRZ_zOJ\P3F(?ƒ.)(h@b!(!QE)IGҗ.2i=AqG=c'ގ1y /)Jgn{Qsڂ(ڎQ=h9Ri0h^ 9@4z( :RtJ2}ێsH)H 9K=82xցԸ4g8/jNqQɤKF){4R=(֔ڗ;h/ҔdqJ"9{qOϽHޞG^9RSqO sRtHTgp$ <@yt$88֗LJn82mi4SHe JҗsҐR@uNMz:@Rc&:RdPFx7F(K8=>(9g\QAKۿ4C@IiE.9c8;&1@GJ)p3/j\`߃OZ2Agޝ*iˌzӳ880dSp=yOҒ1)y{ӳ=ۈ9OiNqR iD s~E;Ӽ14c 9|Mo&4nFO4ҙSi#}QH}j6JCpj3qHX⛻Mf?inM#1alqM{&7jB{SrjkciӊBHzczZLq4-&s@#F9p(GZ^sIqHFM/_ZA fRcctI/F8ޗJGJLR⓵`fq &փȣt=8u N9sJqJoaK\Q߽Ԙ)st9LRc1Z8ȧ}iFF}h8_ZQHy/=8FxsځGJ4{g^`FEMQړ(f?Ɨ'J_3;Hx q E72SK4n8nP(8&q@h@KKHHpzqKo_+qsAqF>_ƎiR旯4|1Jisc'AjCz:w2pt h=i1K4sҗ4cnM(?F1ށ֔dKgNcJ:QҔzRR(KHRӁJ'S Zx~ݩ'4ʔ7sON)C❸pap#(, JHi擡4 ӎy4Q{P} )qޓ I\t{Nޔ43A􀜑K֓n; ^0(J=1Gh~){Q)0sKHWFJh fc4g34cҔfӊ(<(J9ךu掃FG'Oz_ƃK?\Q֗ހ &Kjq4g9Q}i@!:#N>)A(ϭ8ZQӳ'3Ni7dѻ4fh'@9M8A!ҖCK1I׽){Z PN1Fܚ9=Rs8ҁGZN/4I4⓯isJ'p֛EG'JQzLzRr)O'A ^))9A@9'ҐG Rb}(1@NE'p)i:G)GҐiAɠQF(4w)q'֗)sIΗzRg?Z\RqG^i{;8RJN Ҟ1@iwd4(4zRhG~MҌ~Tg&Ҏg^LF}GԣP9iA8~)A.h'#&8ҩ4( =O'4݁IiĂ,7SȦJOJXv=EށLAӚ^qM!nO<qMsH )7g 9?NIq Nh'!8&2qI9z:zz^4 ==)2GRNh"zM&}izP874sޓ' 4 ZNڗ=)r3Ґ"zRgF>qy "iAQޓww sE^)1FyxH0.(ޏAF? ڙғ=)y0iN{ۊNhJ\J))OqG^{џΗ'N 4CR"/IiEI)qsF}iqzAbwqEG=(sIK$ь:)1ti}('SJ)i99Gz֗&? 0AK48sցސQ]wK9wjHN !#p?)2(zR&LHG9B}(^dc'qKIގLg:8Pzu=.OGQ֓9ғ#bޓ R48ԔMѻ=zҔsLGwhH/&:=ǹ9^sHj{;u'$\ўԜ(8((O'E<џ^zTYȤ&=88$JBxK&y9:RړJ:сIɥҏLP9&);PzFF1QIK}h&Qڌ;Ҏ?!鞔Rg^ԃ4JCǾ(#?FEf`Kڂx4F;@ 9uxG_”'NF3֔t{Ru.JL\A2svt7P=sA#@zR) _J M$gsޓvx( h8HF{Pr!8Lќh$4I)z L4)('<f8' JNP &yOZ9JRyh'SgGrh4(E/s@8A9KH1KGz!#րs֓izt4ȥNAKq9J^4Rs—Fh4i(AG ҃GF:QD4;Qޓ(ǥZ1ޏʃP:Rڗ&:vKZ3Iڗ擽)>v'g'hiz߯u KGC@<{>@8qJ)I^ @x&JxE3FrisQۊڂh)AQPxvPh'A ^1HNzQQ旭'$RIPOJ298\dgJ0GcIAFh'ߚ3J:RzR f4<{I@?J3@ ўg?v(4~g9JL҃҃yR tfQގ܊1'hJ1GF9t4s\fz@ARsڌPsK1֎Q)=Rf@hϷH@Nҁ@<ⓡF){sҎhhKVp8sA~@"R}}E^()GNzRgJ}EP=@Pp(g(9=)A8)84~(=hc(h<ԜwqIKZzZZ9tv=?{H9.)qbQtJ})1)oaIҎSАhKڊ1h<ьRxut9IQ@{QhȥPzP旚Nԣ4fGlI~:lIi>) cvzAJzRvR8փҎ4x)8t֎sx4cJ8A84h9 /&=( dJLr(~& F9"dG)A94ʗj)){ў5ȥx>uziJ=yhFi1J4Ғ(#=)OJڔwt>N3KyP2'=O#NΓE֌b4AAFip1AhH8&48A).2=(GJ@{~i{RRuQ9v8f}q.E'A@'9Kڃ9z\qG@A NiH=q? :N/4tIӞhsFh4~1\RsFEJi ڔlQG=1F ޏqH)qҎhZ;q3Ӛ1ϽPAJ1. B1ڀ?:Lǧ4HF8K)S_c0(PGG4{4r(Pyc֔q׊1ɠgcz1Ap(ϭ=sGcR\QڐsA9AF){tG'AюqF4&=iy@bq֔ F3J8ȣԂi;4c4v8"Q^=3A F=֌Qъ8' NihOʔJ\(R>F)1ґHE/C'j\`Pzdv4F2}惞擽)4b0sGҎ(4~qR"tP;F9(t8{;RҎ Z@1KO4fsZLr -&1zGQm&9KsM<⁌)8^bGLRp3/l(=(94qF? ?J@0xf҆c'z:ӱޒsGCOj=}cޔ`A#8J0iq:@0iz(h?'9i@RcqIZ1E/AIG9Q\R'Z\Rc#J\ q4H?:( xc(xsF(sF2hŒvF(#Z\Rb>K1RcJI\q@qARmԝ^jLfbi:Mc LM /J?JLތg=Tr3KJL{/j?b=sK!G#^)A#LAڎhϧ4ubj(Rg4@zNhǵg/RR3j:PIҗjC^G֗CI=8Rw'ށ4g(.hIj0zR!p(#=M}hGz'&t\@Z23Gz;RtMH9(RfxޓN"~tRJc4ҏb?3Gz3A#cZ旌OlR&x4wQfI=izPN1S7iy$PyP;ϭ!:R`Qj:KL`@RwFg iOj3@sEZ)p( Rf}{y/lQڗjҎ ;uJ3H9iOIޗZLSҌbgHx8GNԧץ/'rh?-&:QF(G?Z@(>z_h=(u4{PF)@G G(#ތ(ZLdsKr)(ǭqKIA1\Nq c&EhQ׭j;rO((ҁ^ǽ֎qhԞqF1E&1^!Mi KۥHHR*:z=QzR%tɣbfA@֎KRORv.hNvQяΔHf Px;f g'OPh3Js)P8GniG׊CGAEy4:Qތs@vh;Z 9j9^('x?Z;s@H=xҎ'dQ]iqҐQށJFhQAQKzCzP1RIsJz:)Nsޓ^'aK))z=)r3'9&M&yizRcќ~4> Qȣ(1@4gP1/' AAGQIM:Q֎h(ϵ&yGJw$qMZ;Z3sALccj2 \E'/n)3\w<u7bQj8ړޗ'Q2J:GGj(   (G8$g89Ҟ:w);84gFx" QԊSN wzRhiG\t R4.3*=(4g4u旎%is A;t.9>Ӟ44(Ki1E:FE'R){GQJ:cG~E/4bj\!8ڐ4z\8r}=փ⏭ʁ('c(Phc3Gj_ӵќR⎇zPG/ZBiM?*QӵvwJ:?*G\f(#'41'/}E A"ȣJ3 s֎=F:zPG4/z)3v; P(Ҕ='Rht8⃐i{bh@}8ގŒQh{hlh.=ih'3w.qރG֓@C֗(j\RsKHO8@$P}Mǥ&9R4vKhҌ 1GCޔ3I (J;Rt3K\ցKޓ{P{KI^'4IPFO=hEҎdP3Az?N:Q {RwI)}齩{u$)ҌsQ4gNԤ}y␞tތg1f{Rtfq4 Twc4i?8x/:R;Tg?/l84t@=ю(9z9'N /84sQۃAfP3zуKۭ1-sK8Rc){uӃKױ?PzL!J:sA>s() R(hRsKۊ^E'~sQPKA4vZ3ZOΓR@ڔҜIJ IҌh=iyJњ34ќSsK}T֠;ށ3G^^#ތ{qZLTԝЧ() 擩;=FF3@9zG8ɣ擜K—4h=8HP:&`GAJy4~4 \ 9(ǽ)}})4iy(=hsG#IKގ ZFNh4LfHM֔Q׊=hg4) qjStQFs@99A^h'3GjKI('gZCJ)(zC28&1җGAsG~JSץ&;g4{ 88@⎦qF4Fx惜Q@ M(JAuG^ߝ(gt9'ё)='&rx4h?dvڏ'8((8!sޝNup֎wGJ3KLsJzSHh=(IK$sK:҃ԅhis4Rb(s4qќQ۠'ўޔt9Ahϭ)3zq֔tG4qڏ=z}(9Ҏ(z9htJ;wsKځɣvvE.pqGRW(= ?zFM/=9ǩFqHzGz_lEhRъ3Fqɣ8>=E/j@izG&xSNqy5N1ڗ'nsF(=Ig@QNM/9-'cHNN1J9ڌ{I\4ր}P giACsH~R€zQMތ48Gj\J-4_@ҞҌќEJ1Fx/掔Z;fu`Z2s@;dL_ʁ҃I88>f裑҃Ƞ{qAHjSϵhLA΂{ NRA?^vC.9)`PzR׵7'G( b@rh$~4FMg=(=h;Rhi;w)֗98~4c&q44?RzQQӭcP=(</ZȢ09}3GSKRbQ҃SRpx`fIQFph}(G|PzsGj1KJ8) :R/JRM9֓$z)I"N8@9hQQŒJ2 iIZN\bwњN:RINM;&Au ixgdsE/jCޏƂp98Iӵ@zڊ:b8ѐ:早'Pp(x4ZLFxdK;sHN>E(MZ^G8- izRhJyE;Ҏ'LR旜i ((JQ@&9)4Z(98斎Ii:;Q׿4NhIA4@J}<:}(hy掞uz3sMKڎ}(KގԄ玴 ;Qy4i)yx)`c@Fx4g֗QڔR} wɠz>c$g.(ON}):Ri3Z8q@⎜җޒcTQRR8hdZL ~T$ozP)zҎy4pGCJO I)sv&qFr((j;'sڃ;tGQڗ}z(Mix?!Ȣ֊;E!z8KۭE&:9&Hyn)GJ⃎){Q&x>g3E(R`M(uQK֓җgۊ\JOL9 3@֊OZ:}ix֣^:Qǥ/RRG=izi1AN1G9)}))xuzGQEzR`QPFE㠥Ǿi1Kڒ KG^I)MF8qIiy:ߊ\&;ҁG|P~qK(<`P=EJLgQzbv8G@jZAҗ4c=)h=(KF)1ߵK1GSҎs&3ҔcGz94mRi}: Lf( ъJ14){I(IsSғq^Ը&28KE ^`ь? NځARwN 惎KCFF)1KQʃF3HEށ94ȤKQQ)$ғN>J;IP3_jL :wIEQ~{ 8=MG=(htʌP94=ip"1 NxFw'4\qFEt\P9PG4bq(Q*> )6ڌm &r2)~ ? 9 @=zRQ4;Qp(&Z0GւF>j:cIqN1P1yւ)'Ҏw;4ccԤv֓?*0)p >>JZ()4wQRpGJ_OJ9^)J\{ъ\By)z-юh=9#/p(ڃ:KK):PGzAvsy3vhRғ np.ndarray: \"\"\"Read data and return it Args: filename (str): path to MyImageFormat file Returns: np.ndarray: image data \"\"\" # Implement reading logic here pass """ from __future__ import annotations from sigima.io.common.objmeta import ( read_annotations, read_metadata, read_roi, read_roi_grid, write_annotations, write_metadata, write_roi, write_roi_grid, ) from sigima.io.convenience import ( read_image, read_images, read_signal, read_signals, write_image, write_images, write_signal, write_signals, ) from sigima.io.image.base import ImageIORegistry from sigima.io.signal.base import SignalIORegistry __all__ = [ "IMAGE_FORMAT_INFO", "SIGNAL_FORMAT_INFO", "ImageIORegistry", "SignalIORegistry", "read_annotations", "read_image", "read_images", "read_metadata", "read_roi", "read_roi_grid", "read_signal", "read_signals", "write_annotations", "write_image", "write_images", "write_metadata", "write_roi", "write_roi_grid", "write_signal", "write_signals", ] SIGNAL_FORMAT_INFO = SignalIORegistry.get_format_info(mode="rst") IMAGE_FORMAT_INFO = ImageIORegistry.get_format_info(mode="rst") Sigima-1.1.1/sigima/io/base.py000066400000000000000000000234321514013333200160660ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Sigima Common tools for signal and image io support """ # pylint: disable=invalid-name # Allows short reference names like x, y, ... from __future__ import annotations import dataclasses import enum import os import os.path as osp import re from typing import Generic, Literal, Sequence from sigima.config import _ from sigima.objects.base import BaseObj, TypeObj from sigima.worker import CallbackWorkerProtocol class IOAction(enum.Enum): """I/O action type""" LOAD = enum.auto() SAVE = enum.auto() @dataclasses.dataclass class FormatInfo: """Format info""" name: str = None # e.g. "Foobar camera image files" extensions: str = None # e.g. "*.foobar *.fb" readable: bool = False # True if format can be read writeable: bool = False # True if format can be written requires: list[str] = None # e.g. ["foobar"] if format requires foobar package def __str__(self) -> str: """Return string representation of format info""" return f"""{self.name}: Extensions: {self.extensions} Readable: {"Yes" if self.readable else "No"} Writeable: {"Yes" if self.writeable else "No"} Requires: {", ".join(self.requires) if self.requires else "None"}""" def to_rst_table_row(self) -> str: """Return reStructuredText table row for format info (table `.. list-table::` format, with 5 columns)""" return f""" * - {self.name} - {self.extensions} - {"•" if self.readable else ""} - {"•" if self.writeable else ""} - {", ".join(self.requires) if self.requires else "-"}""" class FormatBase(Generic[TypeObj]): """Object representing a data file io""" FORMAT_INFO: FormatInfo = None def __init__(self): self.info = self.FORMAT_INFO if self.info is None: raise ValueError(f"Format info not set for {self.__class__.__name__}") if self.info.name is None: raise ValueError(f"Format name not set for {self.__class__.__name__}") if self.info.extensions is None: raise ValueError(f"Format extensions not set for {self.__class__.__name__}") if not self.info.readable and not self.info.writeable: raise ValueError(f"Format {self.info.name} is not readable nor writeable") self.extlist = get_file_extensions(self.info.extensions) if not self.extlist: raise ValueError(f"Invalid format extensions for {self.__class__.__name__}") if self.info.requires: for package in self.info.requires: try: __import__(package) except ImportError as exc: raise ImportError( f"Format {self.info.name} requires {package} package" ) from exc def get_filter(self, action: IOAction) -> str | None: """Return file filter for Qt file dialog Args: action: I/O action type Returns: File filter string """ assert action in (IOAction.LOAD, IOAction.SAVE) if action == IOAction.LOAD and not self.info.readable: return None if action == IOAction.SAVE and not self.info.writeable: return None return f"{self.info.name} ({self.info.extensions})" def read( self, filename: str, worker: CallbackWorkerProtocol | None = None ) -> Sequence[TypeObj]: """Read list of native objects (signal or image) from file. For single object, return a list with one object. Args: filename: file name worker: Callback worker object Raises: NotImplementedError: if format is not supported Returns: List of native objects (signal or image) """ raise NotImplementedError(f"Reading from {self.info.name} is not supported") def write(self, filename: str, obj: BaseObj) -> None: """Write data to file Args: filename: file name obj: native object (signal or image) Raises: NotImplementedError: if format is not supported """ raise NotImplementedError(f"Writing to {self.info.name} is not supported") # pylint: disable=bad-mcs-classmethod-argument class BaseIORegistry(Generic[TypeObj], type): """Metaclass for registering I/O handler classes""" REGISTRY_INFO: str = "" # Registry info, override in subclasses _io_format_instances: list[FormatBase] = [] def __init__(cls, name, bases, attrs): super().__init__(name, bases, attrs) if not name.endswith("FormatBase"): try: # pylint: disable=no-value-for-parameter cls._io_format_instances.append(cls()) except ImportError: # This format is not supported pass @classmethod def get_formats(cls) -> list[FormatBase]: """Return I/O format handlers Returns: List of I/O format handlers """ return cls._io_format_instances @classmethod def get_format_info(cls, mode: Literal["rst", "text"] = "rst") -> str: """Return I/O format info Args: mode: Output format, either 'rst' (reStructuredText) or 'text' Returns: Text description for all I/O formats """ if mode == "rst": txt = f"{cls.REGISTRY_INFO}:\n\n.. list-table::\n :header-rows: 1\n\n" txt += " * - Name\n - Extensions\n " txt += "- Readable\n - Writeable\n - Requires\n" txt += "\n".join([fmt.info.to_rst_table_row() for fmt in cls.get_formats()]) else: txt = f"{cls.REGISTRY_INFO}:{os.linesep}" indent = " " * 4 finfo = "\n".join([str(fmt.info) for fmt in cls.get_formats()]) txt += "\n".join([indent + line for line in finfo.splitlines()]) return txt @classmethod def __get_all_supported_filter(cls, action: IOAction) -> str: """Return all supported file filter for Qt file dialog Args: action: I/O action type Returns: File filter """ extlist = [] # file extension list for fmt in cls.get_formats(): fmt: FormatBase if not fmt.info.readable and action == IOAction.LOAD: continue if not fmt.info.writeable and action == IOAction.SAVE: continue extlist.extend(fmt.extlist) allsupported = _("All supported files") return f"{allsupported} ({'*.' + ' *.'.join(extlist)})" @classmethod def get_filters(cls, action: IOAction) -> str: """Return file filters for Qt file dialog Args: action: I/O action type Returns: File filters """ flist = [] # file filter list flist.append(cls.__get_all_supported_filter(action)) for fmt in cls.get_formats(): fmt: FormatBase flt = fmt.get_filter(action) if flt is not None: flist.append(flt) return "\n".join(flist) @classmethod def get_read_filters(cls) -> str: """Return file filters for Qt open file dialog Returns: File filters """ return cls.get_filters(IOAction.LOAD) @classmethod def get_write_filters(cls) -> str: """Return file filters for Qt save file dialog Returns: File filters """ return cls.get_filters(IOAction.SAVE) @classmethod def get_format(cls, filename: str, action: IOAction) -> FormatBase: """Return format handler for filename Args: filename: file name action: I/O action type Raises: NotImplementedError: if file data type is not supported Returns: Format handler """ for fmt in cls.get_formats(): fmt: FormatBase if osp.splitext(filename)[1][1:].lower() in fmt.extlist: if not fmt.info.readable and action == IOAction.LOAD: continue if not fmt.info.writeable and action == IOAction.SAVE: continue return fmt raise NotImplementedError( f"{filename} is not supported for {action.name.lower()}" ) @classmethod def read( cls, filename: str, worker: CallbackWorkerProtocol | None = None ) -> Sequence[TypeObj]: """Read data from file, return native object (signal or image) list. For single object, return a list with one object. Args: filename: file name worker: Callback worker object Raises: NotImplementedError: if file data type is not supported Returns: List of native objects (signal or image) """ fmt = cls.get_format(filename, IOAction.LOAD) return fmt.read(filename, worker) @classmethod def write(cls, filename: str, obj: BaseObj) -> None: """Write data to file from native object (signal or image). Args: filename: file name obj: native object (signal or image) Raises: NotImplementedError: if file data type is not supported """ fmt = cls.get_format(filename, IOAction.SAVE) fmt.write(filename, obj) def get_file_extensions(string: str) -> list[str]: """Return a sorted list of unique file extensions contained in `string`. Args: string: String containing file extensions. Returns: List of file extensions. """ pattern = r"\S+\.[\w-]+" matches = re.findall(pattern, string) return sorted({match.split(".")[-1].lower() for match in matches}) Sigima-1.1.1/sigima/io/common/000077500000000000000000000000001514013333200160665ustar00rootroot00000000000000Sigima-1.1.1/sigima/io/common/__init__.py000066400000000000000000000001621514013333200201760ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Common I/O features """ Sigima-1.1.1/sigima/io/common/basename.py000066400000000000000000000134271514013333200202220ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """Common functions for file name handling.""" from __future__ import annotations import re import string import sys import unicodedata from typing import Any, Iterable from sigima.objects.image import ImageObj from sigima.objects.signal import SignalObj class CustomFormatter(string.Formatter): """Custom string formatter to handle uppercase and lowercase strings.""" def format_field(self, value, format_spec): """Format the given `value` according to the specified `format_spec`. If the value is a string and the format_spec ends with 'upper' or 'lower', convert the value to uppercase or lowercase, respectively, and remove the suffix from `format_spec` before formatting. Args: value: Value to format. format_spec: Format specification, may end with 'upper' or 'lower'. Returns: The formatted value. Raises: ValueError: If `format_spec` is invalid. """ # Ignore dict objects silently (metadata should only be accessed via keys) if isinstance(value, dict): return "" if isinstance(value, str): if format_spec.endswith("upper"): value = value.upper() format_spec = format_spec[:-5] elif format_spec.endswith("lower"): value = value.lower() format_spec = format_spec[:-5] return super().format_field(value, format_spec) def format_basenames( objects: Iterable[SignalObj | ImageObj], fmt: str, replacement: str = "_", ) -> list[str]: """Generate sanitized filenames for SignalObj or ImageObj instances. Format each object's name using the provided Python format string, then sanitize the result for safe use as a filename. The format string may reference any of: - {title}: object title - {index}: 1-based index - {count}: total number of objects - {xlabel}, {xunit}, {ylabel}, {yunit}: axis labels/units (if present) - {metadata[key]}: specific metadata value (direct {metadata} use is silently ignored) Args: objects: Objects to name. fmt: Python format string for naming. replacement: Replacement for invalid filename characters. Returns: Sanitized filenames for each object. Raises: KeyError: If the format string references an unknown placeholder. """ result: list[str] = [] formatter = CustomFormatter() for i, obj in enumerate(objects): # Note: We provide metadata dict only for {metadata[key]} access, # not for direct {metadata} use (which would create overly long filenames) metadata = getattr(obj, "metadata", {}) context: dict[str, Any] = { "title": getattr(obj, "title", ""), "index": i + 1, "count": len(list(objects)), # Attributes may not exist on all objects. "xlabel": getattr(obj, "xlabel", ""), "xunit": getattr(obj, "xunit", ""), "ylabel": getattr(obj, "ylabel", ""), "yunit": getattr(obj, "yunit", ""), "metadata": metadata, } try: formatted = formatter.format(fmt, **context) except KeyError as exc: missing = str(exc.args[0]) if exc.args else str(exc) raise KeyError(f"Unknown format key in fmt: {missing!r}") from exc except ValueError as exc: # Re-raise with more context about which object failed raise ValueError( f"Invalid format string '{fmt}' for object '{context['title']}': {exc}" ) from exc # Sanitize final result to ensure it's a safe basename. result.append(sanitize_basename(formatted, replacement=replacement)) return result def sanitize_basename(basename: str, replacement: str = "_") -> str: """Sanitize a string to create a valid basename for the current operating system. This function removes or replaces characters that are invalid in basenames, depending on the underlying OS (Windows, macOS, Linux). It also strips trailing dots and spaces on Windows and normalizes unicode characters. Args: basename: Input string. replacement: Replacement string for invalid characters (default: "_"). Returns: A sanitized string that can safely be used as a basename. """ # Normalize unicode characters (NFKD form for decomposing accents and the like). basename = unicodedata.normalize("NFKD", basename) basename = basename.encode("ascii", "ignore").decode("ascii") # Characters not allowed in filenames (platform-dependent). if sys.platform.startswith("win"): # Reserved characters on Windows. invalid_chars = r'[<>:"/\\|?*\x00-\x1F]' reserved_names = { "CON", "PRN", "AUX", "NUL", *(f"COM{i}" for i in range(1, 10)), *(f"LPT{i}" for i in range(1, 10)), } else: # Only '/' is disallowed on Unix-based systems. invalid_chars = r"/" reserved_names = set() # Replace invalid characters. sanitized = re.sub(invalid_chars, replacement, basename) # Strip leading/trailing whitespace. sanitized = sanitized.strip() # On Windows, also strip trailing dots and spaces. if sys.platform.startswith("win"): sanitized = sanitized.rstrip(" .") # Truncate to a reasonable length to avoid OS path issues. sanitized = sanitized[:255] # Avoid reserved basenames. if sanitized.upper() in reserved_names: sanitized += "_" # If result is empty, fallback to a default name. if not sanitized: sanitized = "unnamed" return sanitized Sigima-1.1.1/sigima/io/common/converters.py000066400000000000000000000136741514013333200206450ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ I/O conversion functions """ # pylint: disable=invalid-name # Allows short reference names like x, y, ... from __future__ import annotations from typing import Any, Sequence import numpy as np import skimage def dtypes_to_sorted_short_codes( dtypes: Sequence[Any], kind_filter: str | None = None ) -> list[str]: """Return sorted short dtype codes for numeric dtypes. Convert each input to a numpy dtype and ignore non-numeric types. Order: - Integer types first, unsigned (and boolean) before signed, sorted by itemsize ascending. - floats numeric types, sorted by itemsize ascending. - complex numeric types, sorted by itemsize ascending. Short codes use numpy kind letter plus itemsize in bytes, e.g. "u1", "i2", "f8". Args: dtypes: Sequence of objects acceptable by numpy.dtype (dtype, str, etc.) kind_filter: String of dtype kind letters to keep, e.g. "iu" for unsigned/signed integers. If empty or None, keep all numeric types Returns: List of unique short dtype codes in the requested order. """ dtypes = [np.dtype(d).str[1:] for d in dtypes] ordered: list[np.dtype] = [] if kind_filter is None: kind_filter = "iubfc" # all numeric types assert kind_filter != "", "kind_filter cannot be empty string" # Standard dtype codes in desired order bool_codes = ("b1",) int_codes = ("u1", "i1", "u2", "i2", "u4", "i4", "u8", "i8") float_codes = ("f2", "f4", "f8") complex_codes = ("c8", "c16") ordered = [ code for code in bool_codes + int_codes + float_codes + complex_codes if code in dtypes and code[0] in kind_filter ] return ordered def _convert_bool_array(array: np.ndarray) -> np.ndarray: """Convert boolean array to uint8.""" return skimage.util.img_as_ubyte(array) def _convert_int_array( array: np.ndarray, supported_data_types: tuple[np.dtype] ) -> np.ndarray: """Convert an integer array to a standard type. Select the smallest supported integer dtype that can represent all values in the array. If no suitable integer dtype is found, convert the array to a supported float type. Args: array: Input numpy array of integer type. supported_data_types: Tuple of supported numpy dtypes for destination object. Returns: Converted numpy array with the selected dtype. Raises: ValueError: If no supported dtype can represent the data. """ ordered_codes = dtypes_to_sorted_short_codes(supported_data_types, kind_filter="iu") amin = np.min(array) if array.size > 0 else 0 amax = np.max(array) if array.size > 0 else 0 for code in ordered_codes: info = np.iinfo(code) if amin >= info.min and amax <= info.max: new_type = np.dtype(code).newbyteorder("=") break else: new_type = _convert_float_array(array, supported_data_types).dtype return array.astype(new_type, copy=False) def _convert_float_array( array: np.ndarray, supported_data_types: tuple[np.dtype] ) -> np.ndarray: """Convert float/complex array to smallest allowed type at least large as current. Choose the smallest supported dtype of the same kind ("f" for floats, "c" for complex) whose itemsize is greater than or equal to the array's itemsize. If no such type exists, fall back to the largest supported dtype for that kind. Args: array: Array to convert. supported_data_types: Sequence of allowed dtypes for the destination object type. Returns: Converted array with the selected dtype. If no supported dtype of the same kind exists, return the original array. """ kind = array.dtype.kind if kind in ["i", "u", "b"]: kind = "f" # convert integers to floats itemsize = array.dtype.itemsize ordered_codes = dtypes_to_sorted_short_codes(supported_data_types, kind_filter=kind) # Filter out any codes that don't match the requested kind (defensive). valid_codes: list[str] = [] for code in ordered_codes: try: dt = np.dtype(code) except TypeError: continue if dt.kind == kind: valid_codes.append(code) if not valid_codes: # No supported dtype for this kind, return original array. raise ValueError("Unsupported data type") # Find smallest supported type with itemsize >= current itemsize. selected_code: str | None = None for code in valid_codes: dt = np.dtype(code) if dt.itemsize >= itemsize: selected_code = code break else: # Fallback to the largest supported type for this kind. selected_code = valid_codes[-1] new_type = np.dtype(selected_code).newbyteorder("=") return array.astype(new_type, copy=False) def convert_array_to_valid_dtype( array: np.ndarray, valid_dtypes: tuple[np.dtype, ...] ) -> np.ndarray: """Convert array to the most appropriate valid dtype. Converts arrays to one of the valid dtypes, choosing the most appropriate type based on the input array's characteristics. Args: array: array to convert valid_dtypes: tuple of valid dtypes Returns: Converted array with the most appropriate valid dtype. Raises: TypeError: if input is not a numpy ndarray ValueError: if array dtype cannot be converted to any valid type """ if not isinstance(array, np.ndarray): raise TypeError("Input must be a numpy ndarray.") if array.dtype in valid_dtypes: return array kind: str = array.dtype.kind if kind in ["f", "c"]: return _convert_float_array(array, valid_dtypes) if kind == "b": return _convert_bool_array(array) if kind in ["i", "u"]: return _convert_int_array(array, valid_dtypes) raise ValueError("Unsupported data type") Sigima-1.1.1/sigima/io/common/objmeta.py000066400000000000000000000137761514013333200200770ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """Sigima I/O module for handling object metadata and ROIs.""" from __future__ import annotations from typing import TYPE_CHECKING, Any, Literal from guidata.io import JSONHandler, JSONReader, JSONWriter from sigima.objects import ImageROI, SignalROI if TYPE_CHECKING: from sigima.params import ROIGridParam FORMAT_TAG = "sigima" FORMAT_VERSION = "1.0" ROI_TYPE_FIELD = "roi_type" def _check_tag(data: dict, expected_format: str) -> None: """Validate the presence and type of sigima tag. Args: data: The data dictionary to check. expected_format: The expected format string for the tag. Raises: ValueError: If the tag is missing or does not match the expected format. """ tag: dict = data.get(FORMAT_TAG, {}) if tag.get("format") != expected_format: raise ValueError(f"Unexpected or missing format: {tag}") def write_dict(filepath: str, data: dict) -> None: """Write a dictionary to a file in JSON format. Args: filepath: The file path to write the data to. data: The dictionary to serialize. Raises: ValueError: If the data is not a dictionary. """ if not isinstance(data, dict): raise ValueError(f"Expected a dictionary, got {type(data)}") handler = JSONHandler(filepath) handler.set_json_dict(data) handler.save() def read_dict(filepath: str) -> dict: """Read a dictionary from a file and return it. Args: filepath: The file path to read the data from. Returns: The dictionary read from the file. """ handler = JSONHandler(filepath) handler.load() data = handler.get_json_dict() return data def write_roi(filepath: str, roi: SignalROI | ImageROI) -> None: """Write a signal or image ROI to a file in JSON format. Args: filepath: The file path to write the ROI data to. roi: The signal or image ROI object to serialize. Raises: ValueError: If the ROI object is not of type SignalROI or ImageROI. """ if isinstance(roi, SignalROI): roi_type: Literal["signal", "image"] = "signal" elif isinstance(roi, ImageROI): roi_type = "image" else: raise ValueError( f"Unsupported ROI type: {type(roi)}. Expected SignalROI or ImageROI." ) roi_dict = roi.to_dict() roi_dict[ROI_TYPE_FIELD] = roi_type data = { FORMAT_TAG: {"format": "roi", "version": FORMAT_VERSION}, "roi": roi_dict, } write_dict(filepath, data) def read_roi(filepath: str) -> SignalROI | ImageROI: """Read ROI data from a file and return the corresponding ROI object. Args: filepath: The file path to read the ROI data from. Returns: The corresponding ROI object (SignalROI or ImageROI). Raises: ValueError: If the file does not contain the expected format. """ json_dict = read_dict(filepath) _check_tag(json_dict, expected_format="roi") roi_dict = json_dict["roi"] assert isinstance(roi_dict, dict), "ROI data must be a dictionary" roi_type = roi_dict.pop(ROI_TYPE_FIELD, None) if roi_type == "signal": return SignalROI.from_dict(roi_dict) if roi_type == "image": return ImageROI.from_dict(roi_dict) raise ValueError(f"Unsupported or missing ROI type: {roi_type}") def write_roi_grid(filepath: str, param: ROIGridParam) -> None: """Write ROI grid parameters to a file in JSON format. Args: filepath: The file path to write the ROI grid parameters to. param: The ROI grid parameters to serialize. """ writer = JSONWriter(filepath) param.serialize(writer) print(writer.jsondata) writer.save() def read_roi_grid(filepath: str) -> ROIGridParam: """Read ROI grid parameters from a file in JSON format. Args: filepath: The file path to read the ROI grid parameters from. Returns: The ROI grid parameters read from the file. """ from sigima.params import ROIGridParam # pylint: disable=import-outside-toplevel handler = JSONReader(filepath) handler.load() param = ROIGridParam() param.deserialize(handler) return param def write_metadata(filepath: str, metadata: dict[str, Any]) -> None: """Write metadata to a file in JSON format. Args: filepath: The file path to write the metadata to. metadata: The metadata dictionary to serialize. Raises: ValueError: If the object does not have a metadata attribute. """ data = { FORMAT_TAG: {"format": "metadata", "version": FORMAT_VERSION}, "metadata": metadata.copy(), } write_dict(filepath, data) def read_metadata(filepath: str) -> dict[str, Any]: """Read metadata from a file and return the metadata dictionary. Args: filepath: The file path to read the metadata from. Returns: The metadata dictionary. Raises: ValueError: If the file does not contain the expected format. """ json_dict = read_dict(filepath) _check_tag(json_dict, expected_format="metadata") return json_dict["metadata"] def write_annotations(filepath: str, annotations: list[dict[str, Any]]) -> None: """Write annotations to a file in JSON format. Args: filepath: The file path to write the annotations to. annotations: The annotations list to serialize. """ data = { FORMAT_TAG: {"format": "annotations", "version": FORMAT_VERSION}, "annotations": annotations.copy(), } write_dict(filepath, data) def read_annotations(filepath: str) -> list[dict[str, Any]]: """Read annotations from a file and return the annotations list. Args: filepath: The file path to read the annotations from. Returns: The annotations list. Raises: ValueError: If the file does not contain the expected format. """ json_dict = read_dict(filepath) _check_tag(json_dict, expected_format="annotations") return json_dict["annotations"] Sigima-1.1.1/sigima/io/common/textreader.py000066400000000000000000000030031514013333200206030ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """I/O utility functions.""" # pylint: disable=invalid-name # Allows short reference names like x, y... from __future__ import annotations import os from itertools import islice from sigima.io.enums import FileEncoding def count_lines(filename: str | os.PathLike[str]) -> int: """Count the number of lines in a file. Args: filename: File name or path. Returns: The number of lines in the file. Raises: IOError: If the file cannot be read. """ for encoding in FileEncoding: try: with open(filename, "r", encoding=encoding) as file: line_count = sum(1 for _ in file) return line_count except UnicodeDecodeError: # Try next encoding. pass raise IOError(f"Cannot read file {filename}.") def read_first_n_lines(filename: str | os.PathLike[str], n: int = 100000) -> str: """Read the first `n` lines of a file. Args: filename: File name or path. n: Number of lines to read. Returns: The first `n` lines of the file. Raises: IOError: If the file cannot be read. """ for encoding in FileEncoding: try: with open(filename, "r", encoding=encoding) as file: return "".join(islice(file, n)) except UnicodeDecodeError: # Try next encoding. pass raise IOError(f"Cannot read file {filename}.") Sigima-1.1.1/sigima/io/convenience.py000066400000000000000000000105051514013333200174450ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """Convenience I/O functions This module provides convenient wrapper functions for input/output operations with signals and images. These functions offer a simplified interface to the underlying I/O system, making common tasks easier to perform. """ from __future__ import annotations import os.path as osp from typing import Generator, Sequence import guidata.dataset as gds from sigima.config import _ from sigima.io.common.basename import format_basenames from sigima.io.image.base import ImageIORegistry from sigima.io.signal.base import SignalIORegistry from sigima.objects import ImageObj, SignalObj, TypeObj class SaveToDirectoryParam(gds.DataSet): """Save to directory parameters.""" def build_filenames(self, objs: list[TypeObj]) -> list[str]: """Build filenames according to current parameters.""" filenames = format_basenames(objs, self.basename + self.extension) used: set[str] = set() # Ensure all filenames are unique. for i, filename in enumerate(filenames): root, ext = osp.splitext(filename) filepath = osp.join(self.directory, filename) k = 1 while (filename in used) or (not self.overwrite and osp.exists(filepath)): filename = f"{root}_{k}{ext}" filepath = osp.join(self.directory, filename) k += 1 used.add(filename) filenames[i] = filename return filenames def generate_filepath_obj_pairs( self, objs: list[TypeObj] ) -> Generator[tuple[str, TypeObj], None, None]: """Iterate over (filepath, object) pairs to be saved.""" for filename, obj in zip(self.build_filenames(objs), objs): yield osp.join(self.directory, filename), obj directory = gds.DirectoryItem(_("Directory")) basename = gds.StringItem( _("Basename pattern"), default="{title}", help=_("""Pattern accepts a Python format string. Standard Python formatting fields may be used, including: {title}, {index}, {count}, {xlabel}, {xunit}, {ylabel}, {yunit}, {metadata}, {metadata[key]}"""), ) extension = gds.StringItem( _("Extension"), help=_("File extension with leading dot (e.g. .txt or .csv)"), regexp=r"^\.\w+$", ) overwrite = gds.BoolItem( _("Overwrite"), default=False, help=_("Overwrite existing files") ) def read_signals(filename: str) -> Sequence[SignalObj]: """Read a list of signals from a file. Args: filename: File name. Returns: List of signals. """ return SignalIORegistry.read(filename) def read_signal(filename: str) -> SignalObj: """Read a signal from a file. Args: filename: File name. Returns: Signal. """ return read_signals(filename)[0] def write_signal(filename: str, signal: SignalObj) -> None: """Write a signal to a file. Args: filename: File name. signal: Signal. """ SignalIORegistry.write(filename, signal) def write_signals(p: SaveToDirectoryParam, signals: list[SignalObj]) -> None: """Write a list of signals to a file. Args: p: Save to directory parameters. signals: List of signals. """ for filepath, signal in p.generate_filepath_obj_pairs(signals): SignalIORegistry.write(filepath, signal) def read_images(filename: str) -> Sequence[ImageObj]: """Read a list of images from a file. Args: filename: File name. Returns: List of images. """ return ImageIORegistry.read(filename) def read_image(filename: str) -> ImageObj: """Read an image from a file. Args: filename: File name. Returns: Image. """ return read_images(filename)[0] def write_image(filename: str, image: ImageObj) -> None: """Write an image to a file. Args: filename: File name. image: Image. """ ImageIORegistry.write(filename, image) def write_images(p: SaveToDirectoryParam, images: list[ImageObj]) -> None: """Write a list of images to files in a directory. Args: p: Save to directory parameters. images: List of images. """ for filepath, image in p.generate_filepath_obj_pairs(images): ImageIORegistry.write(filepath, image) Sigima-1.1.1/sigima/io/enums.py000066400000000000000000000006251514013333200163020ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """Common enum definitions for Sigima I/O support.""" # pylint: disable=invalid-name # Allows short reference names like x, y... from __future__ import annotations from enum import Enum class FileEncoding(str, Enum): """File encodings.""" UTF8 = "utf-8" UTF8_SIG = "utf-8-sig" LATIN1 = "latin-1" Sigima-1.1.1/sigima/io/ftlab.py000066400000000000000000000326131514013333200162450ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """FT-Lab I/O common functions.""" from __future__ import annotations import struct import typing from enum import Enum import numpy as np def check_file_header(fileobj: typing.BinaryIO) -> None: """Read and validate the file header. Args: fileobj: Opened file object in binary mode. Raises: ValueError: If the header is invalid or incomplete. """ nb_bytes_to_read = 6 read_bytes = fileobj.read(nb_bytes_to_read) if len(read_bytes) != nb_bytes_to_read: raise ValueError(f"Header is incomplete (expected {nb_bytes_to_read} bytes).") # Unpack the first six bytes to check the header. # The first six bytes are expected to be in the format of three little-endian 16-bit # signed integers. i1, _, i3 = struct.unpack("<3h", read_bytes) i1_possible_values = (-31609, -30844) i3_expected_value = 8224 remanining_header_length = 250 if (i1 in i1_possible_values) and (i3 == i3_expected_value): # Skip the rest of the header. read_bytes = fileobj.read(remanining_header_length) if len(read_bytes) != remanining_header_length: raise ValueError( f"Header is incomplete (expected {remanining_header_length} bytes)." ) else: raise ValueError("Unexpected values in header.") def read_length_prefixed_string( fileobj: typing.BinaryIO, encoding: str = "latin-1" ) -> str: """Read a length-prefixed string. Args: fileobj: Opened file object in binary mode. encoding: Encoding to decode the string. Defaults to "latin-1". Returns: The decoded string. Raises: ValueError: If the string length is invalid or file is too short. """ nb_bytes_to_read = 4 read_bytes = fileobj.read(nb_bytes_to_read) if len(read_bytes) != nb_bytes_to_read: raise ValueError("Failed to read string length.") length_to_read = struct.unpack(" None: """Initialize an FTLabSignalFile object. Args: file_path: Path to the FT-Lab signal file (.sig). """ self.file_path: str = file_path self.x: np.ndarray self.y: np.ndarray self.xu: str self.yu: str def __repr__(self) -> str: """Return a string representation of the object.""" return ( f"FTLabSignalFile(" f"file_path={self.file_path!r}, " f"x_shape={None if self.x is None else self.x.shape}, " f"y_shape={None if self.y is None else self.y.shape}, " f"xu={self.xu!r}, " f"yu={self.yu!r})" ) def _check_header(self, fid: typing.BinaryIO) -> None: """Check the file header. Args: fid: Opened file object in binary mode. """ check_file_header(fid) def _read_real_with_x_range( self, fid: typing.BinaryIO, n: int, start: float, step: float ) -> None: """Read real data with a given x range. Args: fid: Opened file object in binary mode. n: Number of data points to read. start: Start of the x range. step: Step size for the x range. """ self.x = np.linspace(start, start + (n - 1) * step, n) self.y = np.fromfile(fid, dtype=" None: """Read real data with given x values. Args: fid: Opened file object in binary mode. n: Number of data points to read. """ data = np.fromfile(fid, dtype=" None: """Read complex data with a given x range. Args: fid: Opened file object in binary mode. n: Number of data points to read. start: Start of the x range. step: Step size for the x range. """ self.x = np.linspace(start, start + (n - 1) * step, n) data = np.fromfile(fid, dtype=" None: """Read complex data with given x values. Args: fid: Opened file object in binary mode. n: Number of data points to read. """ data = np.fromfile(fid, dtype=" np.ndarray: """Read the FT-Lab signal file, populate data and metadata. This method reads the signal data from the file, checking the header and determining the signal type. It supports various signal formats. Returns: XY data. Raises: ValueError: If the file cannot be opened or the format is not recognized. NotImplementedError: If the signal type is not supported. """ try: with open(self.file_path, "rb") as fid: self._check_header(fid) # Skip signal title _ = read_length_prefixed_string(fid, encoding="latin-1") # The following image header is expected to contain 20 double values. nb_values = 20 header = np.fromfile(fid, dtype=" None: """Initialize an FTLabImageFile object. Args: file_path: path to an FT-Lab image file (.ima). """ self.file_path: str = file_path self.image_type: ImageType self.dtype: np.dtype self.nb_columns: int self.nb_lines: int self.data: np.ndarray def __repr__(self) -> str: """Return a string representation of the object.""" return ( f"FTLabImageFile(" f"file_path={self.file_path!r}, " f"image_type={getattr(self, 'image_type', None)}, " f"dtype={getattr(self, 'dtype', None)}, " f"nb_columns={getattr(self, 'nb_columns', None)}, " f"nb_lines={getattr(self, 'nb_lines', None)})" ) def _check_header(self, fid: typing.BinaryIO) -> None: """Check the file header. Args: fid: Opened file object in binary mode. """ check_file_header(fid) def _read_image_data(self, fid): """Read image data from the file. Args: fid: Opened file object in binary mode. image_type: Type of the image (real or complex). dtype: Data type of the image data. nb_lines: Number of lines (rows) in the image. nb_columns: Number of columns in the image. """ size = self.nb_lines * self.nb_columns if self.image_type == ImageType.REAL: data = np.fromfile(fid, dtype=self.dtype, count=size) if data.size != size: raise ValueError("Unexpected end of file while reading image data.") return data.reshape((self.nb_columns, self.nb_lines)).T if self.image_type == ImageType.COMPLEX: real = np.fromfile(fid, dtype=self.dtype, count=size) imag = np.fromfile(fid, dtype=self.dtype, count=size) if real.size != size or imag.size != size: raise ValueError( "Unexpected end of file while reading complex image data." ) return ( real.reshape((self.nb_columns, self.nb_lines)).T + 1j * imag.reshape((self.nb_columns, self.nb_lines)).T ) raise NotImplementedError(f"Image type {self.image_type} is not supported.") def read(self) -> np.ndarray: """Read an image file and return its data. Returns: Image data. Raises: ValueError: If the file cannot be opened or the format is not recognized. NotImplementedError: If the image type or version is not supported. """ try: with open(self.file_path, "rb") as fid: self._check_header(fid) # Skip image title. _ = read_length_prefixed_string(fid, encoding="latin-1") # The following image header is expected to contain 20 double values. nb_values = 20 header = np.fromfile(fid, dtype=" np.ndarray: """Open an FT-Lab image file. Args: filename: path to FT-Lab image file. Returns: Image data. """ ftlab_file = FTLabImageFile(filename) return ftlab_file.read() Sigima-1.1.1/sigima/io/image/000077500000000000000000000000001514013333200156605ustar00rootroot00000000000000Sigima-1.1.1/sigima/io/image/__init__.py000066400000000000000000000003761514013333200177770ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Image I/O features """ # pylint: disable=unused-import import sigima.io.image.formats # noqa: F401 from sigima.io.image.base import ImageIORegistry # noqa: F401 Sigima-1.1.1/sigima/io/image/base.py000066400000000000000000000115261514013333200171510ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Image I/O registry """ from __future__ import annotations import abc import os.path as osp from typing import Sequence import numpy as np from sigima.config import _ from sigima.io.base import BaseIORegistry, FormatBase from sigima.objects.image import ImageObj, create_image from sigima.worker import CallbackWorkerProtocol class ImageIORegistry(BaseIORegistry): """Metaclass for registering image I/O handler classes""" REGISTRY_INFO: str = _("Image I/O formats") _io_format_instances: list[ImageFormatBase] = [] class ImageFormatBaseMeta(ImageIORegistry, abc.ABCMeta): """Mixed metaclass to avoid conflicts""" class ImageFormatBase(abc.ABC, FormatBase, metaclass=ImageFormatBaseMeta): """Base image format object. This class is used to define the interface for image I/O formats. It is an abstract base class that defines the methods that must be implemented by any image format class. """ @abc.abstractmethod def read( self, filename: str, worker: CallbackWorkerProtocol | None = None ) -> Sequence[ImageObj]: """Read list of image objects from file Args: filename: File name worker: Callback worker object Returns: List of image objects """ @abc.abstractmethod def write(self, filename: str, obj: ImageObj) -> None: """Write data to file Args: filename: file name obj: native object (signal or image) Raises: NotImplementedError: if format is not supported """ class SingleImageFormatBase(ImageFormatBase): """Base image format object for single image (e.g., TIFF, PNG, etc.).""" @staticmethod def create_object(filename: str, index: int | None = None) -> ImageObj: """Create empty object Args: filename: File name index: Index of object in file Returns: Image object """ name = osp.basename(filename) if index is not None: name += f" {index:02d}" return create_image(name, metadata={"source": filename}) def read( self, filename: str, worker: CallbackWorkerProtocol | None = None ) -> list[ImageObj]: """Read list of image objects from file Args: filename: File name worker: Callback worker object Returns: List of image objects """ # Default implementation covers the case of a single image: obj = self.create_object(filename) obj.data = self.read_data(filename) unique_values = np.unique(obj.data) if len(unique_values) == 2: # Binary image: set LUT range to unique values obj.zscalemin, obj.zscalemax = unique_values.tolist() return [obj] @staticmethod @abc.abstractmethod def read_data(filename: str) -> np.ndarray: """Read data and return it Args: filename: File name Returns: Image array data """ def write(self, filename: str, obj: ImageObj) -> None: """Write data to file Args: filename: file name obj: native object (signal or image) Raises: NotImplementedError: if format is not supported """ data = obj.data self.write_data(filename, data) @staticmethod def write_data(filename: str, data: np.ndarray) -> None: """Write data to file Args: filename: File name data: Image array data """ raise NotImplementedError(f"Writing to {filename} is not supported") class MultipleImagesFormatBase(SingleImageFormatBase): """Base image format object for multiple images (e.g., SIF or SPE). Works with read function that returns a NumPy array of 3 dimensions, where the first dimension is the number of images. """ def read( self, filename: str, worker: CallbackWorkerProtocol | None = None ) -> list[ImageObj]: """Read list of image objects from file Args: filename: File name worker: Callback worker object Returns: List of image objects """ data = self.read_data(filename) if len(data.shape) == 3: objlist = [] for idx in range(data.shape[0]): obj = self.create_object(filename, index=idx) obj.data = data[idx, ::] objlist.append(obj) if worker is not None: worker.set_progress((idx + 1) / data.shape[0]) if worker.was_canceled(): break return objlist obj = self.create_object(filename) obj.data = data return [obj] Sigima-1.1.1/sigima/io/image/formats.py000066400000000000000000000777311514013333200177240ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Sigima I/O image formats """ # pylint: disable=invalid-name # Allows short reference names like x, y, ... from __future__ import annotations import datetime import os.path as osp import re import imageio.v3 as iio import numpy as np import pandas as pd import scipy.io as sio import skimage.io from guidata.io import HDF5Reader, HDF5Writer import sigima from sigima.config import _, options from sigima.io import ftlab from sigima.io.base import FormatInfo from sigima.io.common.converters import convert_array_to_valid_dtype from sigima.io.enums import FileEncoding from sigima.io.image import funcs from sigima.io.image.base import ( ImageFormatBase, MultipleImagesFormatBase, SingleImageFormatBase, ) from sigima.objects.image import ImageObj, create_image from sigima.worker import CallbackWorkerProtocol class HDF5ImageFormat(ImageFormatBase): """Object representing HDF5 image file type""" FORMAT_INFO = FormatInfo( name="HDF5", extensions="*.h5ima", readable=True, writeable=True, ) GROUP_NAME = "image" # pylint: disable=unused-argument def read( self, filename: str, worker: CallbackWorkerProtocol | None = None ) -> list[ImageObj]: """Read list of image objects from file Args: filename: File name worker: Callback worker object Returns: List of image objects """ reader = HDF5Reader(filename) try: with reader.group(self.GROUP_NAME): obj = ImageObj() obj.deserialize(reader) except ValueError as exc: raise ValueError("No valid image data found") from exc except Exception as exc: # pylint: disable=broad-except raise RuntimeError( f"Unexpected error reading HDF5 image from {filename}" ) from exc finally: reader.close() return [obj] def write(self, filename: str, obj: ImageObj) -> None: """Write data to file Args: filename: file name obj: native object (signal or image) Raises: NotImplementedError: if format is not supported """ assert isinstance(obj, ImageObj), "Object is not an image" writer = HDF5Writer(filename) with writer.group(self.GROUP_NAME): obj.serialize(writer) writer.close() class ClassicsImageFormat(SingleImageFormatBase): """Object representing classic image file types""" FORMAT_INFO = FormatInfo( name="BMP, JPEG, PNG, TIFF, JPEG2000", extensions="*.bmp *.jpg *.jpeg *.png *.tif *.tiff *.jp2", readable=True, writeable=True, ) @staticmethod def read_data(filename: str) -> np.ndarray: """Read data and return it Args: filename: File name Returns: Image array data """ return skimage.io.imread(filename, as_gray=True) @staticmethod def write_data(filename: str, data: np.ndarray) -> None: """Write data to file Args: filename: File name data: Image array data """ ext = osp.splitext(filename)[1].lower() if ext in (".bmp", ".jpg", ".jpeg", ".png"): if data.dtype is not np.uint8: data = data.astype(np.uint8) if ext in (".jp2",): if data.dtype not in (np.uint8, np.uint16): data = data.astype(np.uint16) skimage.io.imsave(filename, data, check_contrast=False) class NumPyImageFormat(SingleImageFormatBase): """Object representing NumPy image file type""" FORMAT_INFO = FormatInfo( name="NumPy", extensions="*.npy", readable=True, writeable=True, ) # pylint: disable=duplicate-code @staticmethod def read_data(filename: str) -> np.ndarray: """Read data and return it Args: filename: File name Returns: Image array data """ return convert_array_to_valid_dtype(np.load(filename), ImageObj.VALID_DTYPES) @staticmethod def write_data(filename: str, data: np.ndarray) -> None: """Write data to file Args: filename: File name data: Image array data """ np.save(filename, data) class NotCoordinatedTextFileError(Exception): """Exception raised when a file is not a coordinated text file""" class CoordinatedTextFileReader: """Utility class for reading text files with metadata and coordinates""" @staticmethod def read_images(filename: str) -> list[ImageObj]: """Read list of image objects from coordinated text file. Args: filename: File name Returns: List of image objects """ file_metadata = CoordinatedTextFileReader.read_metadata(filename) # Validate metadata and raise on inconsistent or missing keys CoordinatedTextFileReader.verify_metadata(filename, file_metadata) dict_keys = file_metadata.keys() allowed_column_header = { "X", "Y", "Z", "Zre", "Zim", "Z Error", "Zre Error", "Zim Error", } columns_header = [k for k in dict_keys if k in allowed_column_header] # Remove keys that are in columns_header and construct metadata dictionary metadata = { key: value[0] for key, value in file_metadata.items() if key not in columns_header } metadata["source"] = filename df = CoordinatedTextFileReader.read_data(filename, columns_header) name = osp.basename(filename) try: # Check if coordinates are uniform or non-uniform x_coords = np.sort(df["X"].unique()) y_coords = np.sort(df["Y"].unique()) # Check if we have a regular grid structure expected_points = len(x_coords) * len(y_coords) actual_points = len(df) # Extract coordinate and data information (zlabel, zunit) = file_metadata.get("Z", file_metadata.get("Zre", ("", ""))) (xlabel, xunit) = file_metadata.get("X", ("X", "")) (ylabel, yunit) = file_metadata.get("Y", ("Y", "")) if xlabel is None: xlabel = "X" if ylabel is None: ylabel = "Y" if zlabel is None: zlabel = "Z" xunit = "" if xunit is None else str(xunit) yunit = "" if yunit is None else str(yunit) zunit = "" if zunit is None else str(zunit) if expected_points == actual_points: # Regular grid - can use pivot to create 2D array data = df.pivot(index="Y", columns="X", values="Z").values data = convert_array_to_valid_dtype(data, ImageObj.VALID_DTYPES) # Check if coordinates are truly uniform (evenly spaced) x_uniform = len(x_coords) >= 2 and np.allclose( np.diff(x_coords), x_coords[1] - x_coords[0], rtol=1e-10 ) y_uniform = len(y_coords) >= 2 and np.allclose( np.diff(y_coords), y_coords[1] - y_coords[0], rtol=1e-10 ) image = create_image( name, metadata=metadata, data=data, units=(xunit, yunit, zunit), labels=(xlabel, ylabel, zlabel), ) if x_uniform and y_uniform: # Set uniform coordinates dx = float(x_coords[1] - x_coords[0]) if len(x_coords) > 1 else 1.0 dy = float(y_coords[1] - y_coords[0]) if len(y_coords) > 1 else 1.0 x0 = float(x_coords[0]) if len(x_coords) > 0 else 0.0 y0 = float(y_coords[0]) if len(y_coords) > 0 else 0.0 image.set_uniform_coords(dx, dy, x0, y0) else: # Set non-uniform coordinates image.set_coords(x_coords.astype(float), y_coords.astype(float)) else: # Non-regular grid - cannot create proper 2D array from this data raise ValueError( f"File {filename} contains {actual_points} data points " f"but expected {expected_points} for a regular grid " f"({len(x_coords)}×{len(y_coords)}). " "Coordinated text files must contain data on a complete " "rectangular grid." ) images_list = [image] except ValueError as exc: raise ValueError(f"File {filename} wrong format.\n{exc}") from exc if "Z Error" in df.columns: # For error data, use the same coordinate structure as the main image error_data = df.pivot(index="Y", columns="X", values="Z Error").values image_error = create_image( name + " error", metadata={"source": filename}, data=error_data, units=( file_metadata["X"][1], file_metadata["Y"][1], file_metadata.get( "Z Error", file_metadata.get( "Zre Error", file_metadata.get("Z", file_metadata.get("Zre", ("", ""))), ), )[1], ), labels=( file_metadata["X"][0], file_metadata["Y"][0], file_metadata.get("Z", file_metadata.get("Zre", ("", "")))[0] + " error", ), ) # Apply the same coordinate system as the main image if image.is_uniform_coords: image_error.set_uniform_coords(image.dx, image.dy, image.x0, image.y0) else: image_error.set_coords(image.xcoords.copy(), image.ycoords.copy()) images_list.append(image_error) return images_list @staticmethod def read_metadata(filename: str) -> dict[str, tuple | None]: """Read metadata from file Args: filename: File name Returns: Metadata dictionary structured as {key: (value, unit)} Available keys can be are: - nx (value is int) - ny (value is int) - X (value represents axis label) - Y (value represents axis label) - Z (value represents axis label) - Zre (value represents axis label) - Zim (value represents axis label) - Z Error (value is none) - Zre Error (value is none) - Zim Error (value is none) """ metadata = {} try: with open(filename, encoding="utf-8") as f: for line in f: line = line.strip() if not line.startswith("#"): break # Remove leading '#' and strip whitespace content = line[1:].strip() # Parse specific patterns parsed = CoordinatedTextFileReader._parse_metadata_line(content) if parsed: key, value_unit = parsed metadata[key] = value_unit except (ValueError, IOError) as exc: raise ValueError(f"Could not read metadata from file {filename}") from exc return metadata @staticmethod def _parse_metadata_line(line: str) -> tuple[str, tuple] | None: """Parse a single metadata line into key-value-unit tuple. Args: line: Line to parse (without # prefix) Returns: Tuple of (key, (value, unit)) or None if not parseable """ # Handle special patterns first if match := re.match(r"Created by (.*)", line): return "author", (match.group(1).strip(), None) if match := re.match( r"Created on (\d{4}-\d{2}-\d{2}) (\d{2}:\d{2}:\d{2}\.\d+)", line ): date_str, _time_str = match.groups() return "creation_date", (date_str, None) # Note: creation_time is lost in this simplified version if match := re.match(r"Using matrislib ([\d\.a-zA-Z-]+)", line): return "software_version", (f"matrislib {match.group(1)}", None) # Handle error columns without colons if line.startswith(("Z Error", "Zre Error", "Zim Error")): if ":" not in line: line = line.replace("Error", "Error :", 1) # Must contain colon for key-value pairs if ":" not in line: return None # Remove Real(...) or Imaginary(...) wrappers line = re.sub(r"(?:Real|Imaginary)\(([^\)]*)\)", r"\1", line) # Split on first colon key, rest = line.split(":", 1) key = key.strip() rest = rest.strip() # Parse value and unit value, unit = CoordinatedTextFileReader._parse_value_and_unit(rest) return key, (value, unit) @staticmethod def _parse_value_and_unit( text: str, ) -> tuple[int | float | bool | str | None, str | None]: """Parse value and unit from text like 'value (unit)' or just 'value'. Intelligently converts values to appropriate types: - Booleans: "true"/"false" (case-insensitive) → bool - Integers: "123", "-456" → int - Floats: "1.23", "-4.56", "1.2e-3" → float - None: empty string → None - Strings: everything else → str Args: text: Text to parse Returns: Tuple of (value, unit) where value can be int, float, bool, str, or None """ text = text.strip() # Extract unit in parentheses if present unit = None if text.endswith(")"): if "(" in text: parts = text.rsplit("(", 1) text = parts[0].strip() unit = parts[1].rstrip(")").strip() if not unit: unit = None # Parse value with intelligent type detection if not text: value = None elif text.lower() in ("true", "false"): # Boolean values value = text.lower() == "true" else: # Try to parse as number try: # Check if it looks like an integer (no decimal point or exponent) if "." not in text and "e" not in text.lower(): value = int(text) else: # Parse as float value = float(text) except ValueError: # Not a number, keep as string value = text return value, unit @staticmethod def verify_metadata(filename: str, metadata: dict[str, tuple | None]) -> None: """Verify metadata keys consistency. Perform a set of sanity checks on the parsed metadata and raise an appropriate exception on failure. Args: filename: Parsed filename used for error messages. metadata: Metadata dictionary parsed from file header. Raises: NotCoordinatedTextFileError: When file is not a valid format. ValueError: When required fields are missing or inconsistent. """ # Check if this is a coordinated text file by looking for key indicators has_format_indicators = "software_version" in metadata or ( "creation_date" in metadata and any(col in metadata for col in ["X", "Y", "Z", "Zre", "Zim"]) ) if not has_format_indicators: raise NotCoordinatedTextFileError( f"File {filename} does not appear to be a coordinated text format file " "(missing expected metadata structure)" ) columns_header = [k for k in metadata.keys() if k not in ("nx", "ny")] # Required columns check if "X" not in columns_header or "Y" not in columns_header: raise ValueError( f"File {filename}: Missing required X, Y columns in header" ) # Z column validation has_z = "Z" in columns_header has_complex = "Zre" in columns_header or "Zim" in columns_header if not (has_z or has_complex): raise ValueError( f"File {filename}: Must contain either Z column or Zre/Zim columns" ) if has_z and has_complex: raise ValueError( f"File {filename}: Cannot contain both Z and Zre/Zim columns" ) # Complex Z validation if has_complex: if ("Zre" in columns_header) ^ ("Zim" in columns_header): raise ValueError( f"File {filename}: Both Zre and Zim columns " f"must be present together" ) # Error column validation has_z_error = "Z Error" in columns_header has_complex_error = ( "Zre Error" in columns_header or "Zim Error" in columns_header ) if has_z_error and has_complex_error: raise ValueError( f"File {filename}: Cannot contain both Z Error and " f"Zre Error/Zim Error columns" ) if has_complex_error: if ("Zre Error" in columns_header) ^ ("Zim Error" in columns_header): raise ValueError( f"File {filename}: Both Zre Error and Zim Error columns " f"must be present together" ) @staticmethod def _try_df_reading(filename: str, columns_header: list[str]) -> pd.DataFrame: """Try to read the data file with various parsing options. Args: filename: File name columns_header: List of column headers to use when reading the data. Returns: DataFrame containing the image data. Raises: ValueError: If the file cannot be read with any of the tried options. """ # Define parsing configurations to try in order of preference parsing_configs = [ (encoding, decimal, delimiter) for encoding in FileEncoding for decimal in (".", ",") for delimiter in (r"\s+", ",", ";") ] last_error = None for encoding, decimal, delimiter in parsing_configs: try: df = pd.read_csv( filename, decimal=decimal, comment="#", delimiter=delimiter, encoding=encoding, names=columns_header, ) # Drop entirely empty columns introduced by trailing delimiters df = df.dropna(axis=1, how="all") return df except (ValueError, UnicodeDecodeError) as exc: last_error = exc continue # If we get here, all parsing attempts failed raise ValueError( f"Could not read image data from file {filename}. Last error: {last_error}" ) from last_error @staticmethod def read_data(filename: str, columns_header: list[str]) -> pd.DataFrame: """Read data and return it. Args: filename: File name Returns: Image array data """ # Try several parsing variants (encoding, decimal and delimiter). df: pd.DataFrame | None = None df = CoordinatedTextFileReader._try_df_reading(filename, columns_header) # if Z is present, the image is Real if "Zre" in df.columns: df["Z"] = df["Zre"] + 1j * df["Zim"] df = df.drop(columns=["Zre", "Zim"]) if "Zre Error" in df.columns: df["Z Error"] = df["Zre Error"] + 1j * df["Zim Error"] df = df.drop(columns=["Zre Error", "Zim Error"]) return df class CoordinatedTextFileWriter: """Utility class for writing text files with metadata and coordinates""" @staticmethod def write_image(filename: str, obj: ImageObj) -> None: """Write image object to coordinated text file. Args: filename: File name to write to obj: Image object to write Raises: ValueError: If image has invalid coordinate system """ # Validate that we can write this image if obj.data is None: raise ValueError( "Cannot write image with no data to coordinated text format" ) # Get coordinate information if obj.is_uniform_coords: # Generate coordinate arrays for uniform coordinates ny, nx = obj.data.shape x_coords = obj.x0 + np.arange(nx) * obj.dx y_coords = obj.y0 + np.arange(ny) * obj.dy else: # Use non-uniform coordinates directly x_coords = obj.xcoords y_coords = obj.ycoords if x_coords is None or y_coords is None: raise ValueError("Cannot write image with missing coordinate arrays") # Create meshgrid for the data X, Y = np.meshgrid(x_coords, y_coords) # Flatten arrays for CSV output x_flat = X.flatten() y_flat = Y.flatten() z_flat = obj.data.flatten() # Write file with open(filename, "w", encoding="utf-8") as f: # Write metadata header f.write(f"# Created by Sigima {sigima.__version__}\n") timestamp = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S.%f") f.write(f"# Created on {timestamp}\n") f.write(f"# nx: {obj.data.shape[1]}\n") f.write(f"# ny: {obj.data.shape[0]}\n") # Write axis information f.write(f"# X: {obj.xlabel}") if obj.xunit: f.write(f" ({obj.xunit})") f.write("\n") f.write(f"# Y: {obj.ylabel}") if obj.yunit: f.write(f" ({obj.yunit})") f.write("\n") f.write(f"# Z: {obj.zlabel}") if obj.zunit: f.write(f" ({obj.zunit})") f.write("\n") # Write additional metadata if present if obj.metadata: for key, value in obj.metadata.items(): if key not in ("source",): # Skip internal metadata f.write(f"# {key}: {value}\n") # Write data columns for x, y, z in zip(x_flat, y_flat, z_flat): f.write(f"{x}\t{y}\t{z}\n") class TextImageFormat(SingleImageFormatBase): """Object representing text image file type""" FORMAT_INFO = FormatInfo( name=_("Text files"), extensions="*.txt *.csv *.asc", readable=True, writeable=True, ) def read( self, filename: str, worker: CallbackWorkerProtocol | None = None ) -> list[ImageObj]: """Read list of image objects from file Args: filename: File name worker: Callback worker object Returns: List of image objects """ # Try to read as coordinated text format first # (for .txt/.csv files with metadata and coordinates) if filename.lower().endswith((".txt", ".csv")): try: return CoordinatedTextFileReader.read_images(filename) except NotCoordinatedTextFileError: # Not a coordinated text file, continue with regular text processing pass # Read as generic text file obj = self.create_object(filename) obj.data = self.read_data(filename) unique_values = np.unique(obj.data) if len(unique_values) == 2: # Binary image: set LUT range to unique values obj.zscalemin, obj.zscalemax = unique_values.tolist() return [obj] @staticmethod def read_data(filename: str) -> np.ndarray: """Read data and return it Args: filename: File name Returns: Image array data """ for encoding in FileEncoding: for decimal in (".", ","): for delimiter in (",", ";", r"\s+"): try: df = pd.read_csv( filename, decimal=decimal, delimiter=delimiter, encoding=encoding, header=None, ) # Handle the extra column created with trailing delimiters. df = df.dropna(axis=1, how="all") data = df.to_numpy() return convert_array_to_valid_dtype(data, ImageObj.VALID_DTYPES) except ValueError: continue raise ValueError(f"Could not read image data from file {filename}.") @staticmethod def write_data(filename: str, data: np.ndarray) -> None: """Write data to file. Args: filename: File name. data: Image array data. """ if np.issubdtype(data.dtype, np.integer): fmt = "%d" elif np.issubdtype(data.dtype, np.floating) or np.issubdtype( data.dtype, np.complexfloating ): fmt = "%.18e" else: raise NotImplementedError( f"Writing data of type {data.dtype} to text file is not supported." ) ext = osp.splitext(filename)[1] if ext.lower() in (".txt", ".asc", ""): np.savetxt(filename, data, fmt=fmt) elif ext.lower() == ".csv": np.savetxt(filename, data, fmt=fmt, delimiter=",") else: raise ValueError(f"Unknown text file extension {ext}") def write(self, filename: str, obj: ImageObj) -> None: """Write data to file Args: filename: file name obj: image object """ if not isinstance(obj, ImageObj): raise ValueError("Object is not an image") # Check if object has non-uniform coordinates and filename is TXT or CSV # If so, use coordinated text format ext = osp.splitext(filename)[1].lower() if ext in (".txt", ".csv") and not obj.is_uniform_coords: try: CoordinatedTextFileWriter.write_image(filename, obj) return except Exception: # pylint: disable=broad-except # Fall back to regular text format if writing fails pass # Use default text format super().write(filename, obj) class MatImageFormat(SingleImageFormatBase): """Object representing MAT-File image file type""" FORMAT_INFO = FormatInfo( name=_("MAT-Files"), extensions="*.mat", readable=True, writeable=True, ) # pylint: disable=duplicate-code def read( self, filename: str, worker: CallbackWorkerProtocol | None = None ) -> list[ImageObj]: """Read list of image objects from file Args: filename: File name worker: Callback worker object Returns: List of image objects """ mat = sio.loadmat(filename) allimg: list[ImageObj] = [] for dname, data in mat.items(): if dname.startswith("__") or not isinstance(data, np.ndarray): continue if len(data.shape) != 2: continue obj = self.create_object(filename) obj.data = data if dname != "img": obj.title += f" ({dname})" allimg.append(obj) return allimg @staticmethod def read_data(filename: str) -> np.ndarray: """Read data and return it Args: filename: File name Returns: Image array data """ # This method is not used, as read() is overridden @staticmethod def write_data(filename: str, data: np.ndarray) -> None: """Write data to file Args: filename: File name data: Image array data """ sio.savemat(filename, {"img": data}) class DICOMImageFormat(SingleImageFormatBase): """Object representing DICOM image file type""" FORMAT_INFO = FormatInfo( name="DICOM", extensions="*.dcm *.dicom", readable=True, writeable=False, requires=["pydicom"], ) @staticmethod def read_data(filename: str) -> np.ndarray: """Read data and return it Args: filename: File name Returns: Image array data """ return funcs.imread_dicom(filename) class AndorSIFImageFormat(MultipleImagesFormatBase): """Object representing an Andor SIF image file type""" FORMAT_INFO = FormatInfo( name="Andor SIF", extensions="*.sif", readable=True, writeable=False, ) @staticmethod def read_data(filename: str) -> np.ndarray: """Read data and return it Args: filename: File name Returns: Image array data """ return funcs.imread_sif(filename) # Generate classes based on the information above: def generate_imageio_format_classes( imageio_formats: list[list[str, str]] | list[tuple[str, str]] | tuple[tuple[str, str]] | tuple[list[str, str]] | None = None, ) -> None: """Generate classes based on the information above""" if imageio_formats is None: imageio_formats = options.imageio_formats.get() for extensions, name in imageio_formats: class_dict = { "FORMAT_INFO": FormatInfo( name=name, extensions=extensions, readable=True, writeable=False ), "read_data": staticmethod( lambda filename: iio.imread(filename, index=None) ), } class_name = extensions.split()[0].split(".")[1].upper() + "ImageFormat" globals()[class_name] = type( class_name, (MultipleImagesFormatBase,), class_dict ) generate_imageio_format_classes() class SpiriconImageFormat(SingleImageFormatBase): """Object representing Spiricon image file type""" FORMAT_INFO = FormatInfo( name="Spiricon", extensions="*.scor-data", readable=True, writeable=False, ) @staticmethod def read_data(filename: str) -> np.ndarray: """Read data and return it Args: filename: File name Returns: Image array data """ return funcs.imread_scor(filename) class XYZImageFormat(SingleImageFormatBase): """Object representing Dürr NDT XYZ image file type""" FORMAT_INFO = FormatInfo( name="Dürr NDT", extensions="*.xyz", readable=True, writeable=False, ) @staticmethod def read_data(filename: str) -> np.ndarray: """Read data and return it Args: filename: File name Returns: Image array data """ with open(filename, "rb") as fdesc: cols = int(np.fromfile(fdesc, dtype=np.uint16, count=1)[0]) rows = int(np.fromfile(fdesc, dtype=np.uint16, count=1)[0]) arr = np.fromfile(fdesc, dtype=np.uint16, count=cols * rows) arr = arr.reshape((rows, cols)) return np.fliplr(arr) class FTLabImageFormat(SingleImageFormatBase): """FT-Lab image file.""" FORMAT_INFO = FormatInfo( name="FT-Lab", extensions="*.ima", readable=True, writeable=False, ) @staticmethod def read_data(filename: str) -> np.ndarray: """Read and return data. Args: filename: Path to FT-Lab file. Returns: Image data. """ return ftlab.imread_ftlabima(filename) Sigima-1.1.1/sigima/io/image/funcs.py000066400000000000000000000364371514013333200173650ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Sigima I/O image functions """ # pylint: disable=invalid-name # Allows short reference names like x, y, ... from __future__ import annotations import os import re import sys import time import numpy as np from guidata.utils.misc import to_string # MARK: SIF I/O functions # ============================================================================== # Original code: # -------------- # Zhenpeng Zhou # Copyright 2017 Zhenpeng Zhou # Licensed under MIT License Terms # # Changes: # ------- # * Calculating header length using the line beginning with "Counts" # * Calculating wavelenght info line number using line starting with "65538 " # * Handling wavelenght info line ending with "NM" # * Calculating data offset by detecting the first line containing NUL character after # header # class SIFFile: """ A class that reads the contents and metadata of an Andor .sif file. Compatible with images as well as spectra. Exports data as numpy array or xarray.DataArray. Example: SIFFile('my_spectrum.sif').read_all() In addition to the raw data, SIFFile objects provide a number of meta data variables: :ivar x_axis: the horizontal axis (can be pixel numbers or wvlgth in nm) :ivar original_filename: the original file name of the .sif file :ivar date: the date the file was recorded :ivar model: camera model :ivar temperature: sensor temperature in degrees Celsius :ivar exposuretime: exposure time in seconds :ivar cycletime: cycle time in seconds :ivar accumulations: number of accumulations :ivar readout: pixel readout rate in MHz :ivar xres: horizontal resolution :ivar yres: vertical resolution :ivar width: image width :ivar height: image height :ivar xbin: horizontal binning :ivar ybin: vertical binning :ivar gain: EM gain level :ivar vertical_shift_speed: vertical shift speed :ivar pre_amp_gain: pre-amplifier gain :ivar stacksize: number of frames :ivar filesize: size of the file in bytes :ivar m_offset: offset in the .sif file to the actual data """ # pylint: disable=too-many-instance-attributes # pylint: disable=too-many-statements def __init__(self, filepath: str) -> None: self.filepath = filepath self.original_filename = None self.filesize = None self.left = None self.right = None self.top = None self.bottom = None self.width = None self.height = None self.grating = None self.stacksize = None self.datasize = None self.xres = None self.yres = None self.xbin = None self.ybin = None self.cycletime = None self.pre_amp_gain = None self.temperature = None self.center_wavelength = None self.readout = None self.gain = None self.date = None self.exposuretime = None self.m_offset = None self.accumulations = None self.vertical_shift_speed = None self.model = None self.grating_blaze = None self._read_header(filepath) def __repr__(self) -> str: """Return a string representation of the SIFFile object""" info = ( ("Original Filename", self.original_filename), ("Date", self.date), ("Camera Model", self.model), ("Temperature (deg.C)", f"{self.temperature:f}"), ("Exposure Time", f"{self.exposuretime:f}"), ("Cycle Time", f"{self.cycletime:f}"), ("Number of accumulations", f"{self.accumulations:d}"), ("Pixel Readout Rate (MHz)", f"{self.readout:f}"), ("Horizontal Camera Resolution", f"{self.xres:d}"), ("Vertical Camera Resolution", f"{self.yres:d}"), ("Image width", f"{self.width:d}"), ("Image Height", f"{self.height:d}"), ("Horizontal Binning", f"{self.xbin:d}"), ("Vertical Binning", f"{self.ybin:d}"), ("EM Gain level", f"{self.gain:f}"), ("Vertical Shift Speed", f"{self.vertical_shift_speed:f}"), ("Pre-Amplifier Gain", f"{self.pre_amp_gain:f}"), ("Stacksize", f"{self.stacksize:d}"), ("Filesize", f"{self.filesize:d}"), ("Offset to Image Data", f"{self.m_offset:f}"), ) desc_len = max(len(d) for d in list(zip(*info))[0]) + 3 res = "" for description, value in info: res += ("{:" + str(desc_len) + "}{}\n").format(description + ": ", value) res = object.__repr__(self) + "\n" + res return res def _read_header(self, filepath: str) -> None: """Read SIF file header Args: filepath: path to SIF file """ with open(filepath, "rb") as sif_file: i_wavelength_info = None headerlen = None i = 0 self.m_offset = 0 while True: raw_line = sif_file.readline() line = raw_line.strip() if i == 0: if line != b"Andor Technology Multi-Channel File": sif_file.close() raise ValueError(f"{filepath} is not an Andor SIF file") elif i == 2: tokens = line.split() self.temperature = float(tokens[5]) self.date = time.strftime("%c", time.localtime(float(tokens[4]))) self.exposuretime = float(tokens[12]) self.cycletime = float(tokens[13]) self.accumulations = int(tokens[15]) self.readout = 1 / float(tokens[18]) / 1e6 self.gain = float(tokens[21]) self.vertical_shift_speed = float(tokens[41]) self.pre_amp_gain = float(tokens[43]) elif i == 3: self.model = to_string(line) elif i == 5: self.original_filename = to_string(line) if i_wavelength_info is None and i > 7: if line.startswith(b"65538 ") and len(line) == 17: i_wavelength_info = i + 1 if i_wavelength_info is not None and i == i_wavelength_info: wavelength_info = line.split() self.center_wavelength = float(wavelength_info[3]) self.grating = float(wavelength_info[6]) blaze = wavelength_info[7] if blaze.endswith(b"NM"): blaze = blaze[:-2] self.grating_blaze = float(blaze) if headerlen is None: if line.startswith(b"Counts"): headerlen = i + 3 else: if i == headerlen - 2: if line[:12] == b"Pixel number": line = line[12:] tokens = line.split() if len(tokens) < 6: raise ValueError("Not able to read stacksize.") self.yres = int(tokens[2]) self.xres = int(tokens[3]) self.stacksize = int(tokens[5]) elif i == headerlen - 1: tokens = line.split() if len(tokens) < 7: raise ValueError("Not able to read Image dimensions.") self.left = int(tokens[1]) self.top = int(tokens[2]) self.right = int(tokens[3]) self.bottom = int(tokens[4]) self.xbin = int(tokens[5]) self.ybin = int(tokens[6]) elif i >= headerlen: if b"\x00" in line: break i += 1 self.m_offset += len(raw_line) width = self.right - self.left + 1 mod = width % self.xbin self.width = int((width - mod) / self.ybin) height = self.top - self.bottom + 1 mod = height % self.ybin self.height = int((height - mod) / self.xbin) self.filesize = os.path.getsize(filepath) self.datasize = self.width * self.height * 4 * self.stacksize def read(self) -> np.ndarray: """Read the data from the SIF file Returns: The image data. The shape of the array is (stacksize, height, width) """ with open(self.filepath, "rb") as sif_file: sif_file.seek(self.m_offset) block = sif_file.read(self.width * self.height * self.stacksize * 4) data = np.frombuffer(block, dtype=np.float32) # If there is a background image, it will be stored just after the signal # data. The background image is the same size as the signal data. # To read the background image, we need to search for the next line starting # with "Counts" and read the data from there. while True: line = sif_file.readline() if not line: break if line.startswith(b"Counts"): # Data starts 4 lines after the "Counts" line for _ in range(4): line = sif_file.readline() # Read the background image data background_data = sif_file.read(self.width * self.height * 4) background = np.frombuffer(background_data, dtype=np.float32) # Check if the background data is the same size as the signal data if background.size != data.size: # This is not a background image: not supported format break # Add the background data to the signal data, as an additional frame data = np.concatenate((data, background)) # Update the stack size to include the background image self.stacksize += 1 break return data.reshape(self.stacksize, self.height, self.width) def imread_sif(filename: str) -> np.ndarray: """Open a SIF image Args: filename: path to SIF file Returns: Image data """ sif_file = SIFFile(filename) return sif_file.read() # MARK: SPIRICON I/O functions # ============================================================================== class SCORFile: """Object representing a SPIRICON .scor-data file Args: filepath: path to .scor-data file """ def __init__(self, filepath: str) -> None: self.filepath = filepath self.metadata = None self.width = None self.height = None self.m_offset = None self.filesize = None self.datasize = None self._read_header() def __repr__(self) -> str: """Return a string representation of the object""" info = ( ("Image width", f"{self.width:d}"), ("Image Height", f"{self.height:d}"), ("Filesize", f"{self.filesize:d}"), ("Datasize", f"{self.datasize:d}"), ("Offset to Image Data", f"{self.m_offset:f}"), ) desc_len = max(len(d) for d in list(zip(*info))[0]) + 3 res = "" for description, value in info: res += ("{:" + str(desc_len) + "}{}\n").format(description + ": ", value) res = object.__repr__(self) + "\n" + res return res def _read_header(self) -> None: """Read file header""" with open(self.filepath, "rb") as data_file: metadata = {} key1 = None while True: bline = data_file.readline().strip() key1_match = re.match(b"\\[(\\S*)\\]", bline) if key1_match is not None: key1 = key1_match.groups()[0].decode() metadata[key1] = {} elif b"=" in bline: key2, value = bline.decode().split("=") metadata[key1][key2] = value else: break capture_size = metadata["Capture"]["CaptureSize"] self.width, self.height = [int(val) for val in capture_size.split(",")] self.filesize = os.path.getsize(self.filepath) self.datasize = self.width * self.height * 2 self.m_offset = self.filesize - self.datasize - 8 def read(self) -> np.ndarray: """Read the data from the SPIRICON file Returns: The image data as a NumPy array with shape (height, width) """ with open(self.filepath, "rb") as data_file: data_file.seek(self.m_offset) block = data_file.read(self.datasize) data = np.frombuffer(block, dtype=np.int16) return data.reshape(self.height, self.width) def imread_scor(filename: str) -> np.ndarray: """Open a SPIRICON image Args: filename: path to SPIRICON file Returns: Image data """ scor_file = SCORFile(filename) return scor_file.read() # MARK: DICOM I/O functions # ============================================================================== # Original code: see PlotPy package (BSD 3-Clause license) def imread_dicom(filename: str) -> np.ndarray: """Open DICOM image with pydicom and return a NumPy array Args: filename: path to DICOM file Returns: Image data as a NumPy array """ # pylint: disable=import-outside-toplevel # pylint: disable=import-error from pydicom import dcmread # type:ignore dcm = dcmread(filename, force=True) # ********************************************************************** # The following is necessary until pydicom numpy support is improved: # (after that, a simple: 'arr = dcm.PixelArray' will work the same) format_str = f"{'u' if dcm.PixelRepresentation == 0 else ''}int{dcm.BitsAllocated}" try: dtype = np.dtype(format_str) except TypeError as exc: raise TypeError( f"Data type not understood by NumPy: " f"PixelRepresentation={dcm.PixelRepresentation}, " f"BitsAllocated={dcm.BitsAllocated}" ) from exc arr = np.frombuffer(dcm.PixelData, dtype) try: # pydicom 0.9.3: dcm_is_little_endian = dcm.isLittleEndian except AttributeError: # pydicom 0.9.4: dcm_is_little_endian = dcm.is_little_endian if dcm_is_little_endian != (sys.byteorder == "little"): arr.byteswap(True) spp = getattr(dcm, "SamplesperPixel", 1) if hasattr(dcm, "NumberOfFrames") and dcm.NumberOfFrames > 1: if spp > 1: arr = arr.reshape(spp, dcm.NumberofFrames, dcm.Rows, dcm.Columns) else: arr = arr.reshape(dcm.NumberOfFrames, dcm.Rows, dcm.Columns) else: if spp > 1: if dcm.BitsAllocated == 8: arr = arr.reshape(spp, dcm.Rows, dcm.Columns) else: raise NotImplementedError( "This code only handles SamplesPerPixel > 1 if Bits Allocated = 8" ) else: arr = arr.reshape(dcm.Rows, dcm.Columns) # ********************************************************************** return arr Sigima-1.1.1/sigima/io/signal/000077500000000000000000000000001514013333200160535ustar00rootroot00000000000000Sigima-1.1.1/sigima/io/signal/__init__.py000066400000000000000000000003731514013333200201670ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ I/O features """ # pylint: disable=unused-import import sigima.io.signal.formats # noqa: F401 from sigima.io.signal.base import SignalIORegistry # noqa: F401 Sigima-1.1.1/sigima/io/signal/base.py000066400000000000000000000073251514013333200173460ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Base I/O registry """ # pylint: disable=invalid-name # Allows short reference names like x, y, ... from __future__ import annotations import abc import os.path as osp from typing import Sequence import numpy as np from sigima.config import _ from sigima.io.base import BaseIORegistry, FormatBase from sigima.objects.signal import SignalObj, create_signal from sigima.worker import CallbackWorkerProtocol class SignalIORegistry(BaseIORegistry): """Metaclass for registering signal I/O handler classes""" REGISTRY_INFO: str = _("Signal I/O formats") _io_format_instances: list[SignalFormatBase] = [] class SignalFormatBaseMeta(SignalIORegistry, abc.ABCMeta): """Mixed metaclass to avoid conflicts""" class SignalFormatBase(abc.ABC, FormatBase, metaclass=SignalFormatBaseMeta): """Class representing a signal file type""" HEADER_KEY = "header" @staticmethod def create_object(filename: str, index: int | None = None) -> SignalObj: """Create empty object Args: filename: File name index: Index of object in file Returns: Signal object """ name = osp.basename(filename) if index is not None: name += f" {index:02d}" return create_signal(name, metadata={"source": filename}) def create_signal( self, xydata: np.ndarray, filename: str, index: int | None = None ) -> SignalObj: """Create signal object from xydata and filename. Args: xydata: XY data filename: File name index: Index of object in file Returns: Signal object """ obj = self.create_object(filename, index=index) obj.set_xydata(xydata[:, 0], xydata[:, index or 1]) return obj def create_signals_from(self, xydata: np.ndarray, filename: str) -> list[SignalObj]: """Create signal objects from xydata and filename Args: xydata: XY data filename: File name Returns: List of signal objects """ assert isinstance(xydata, np.ndarray), "Data type not supported" assert len(xydata.shape) in (1, 2), "Data not supported" if len(xydata.shape) == 1: # 1D data obj = self.create_object(filename) obj.set_xydata(np.arange(xydata.size), xydata) return [obj] # 2D data: x, y1, y2, ... # Eventually transpose data: if xydata.shape[1] > xydata.shape[0]: xydata = xydata.T # If only data contains one x and y columns, return single object without index # in title if xydata.shape[1] == 2: return [self.create_signal(xydata, filename)] objs = [] # Create objects for each y column for i in range(1, xydata.shape[1]): objs.append(self.create_signal(xydata, filename, i)) return objs def read( self, filename: str, worker: CallbackWorkerProtocol | None = None ) -> Sequence[SignalObj]: """Read list of signal objects from file Args: filename: File name worker: Callback worker object Returns: List of signal objects """ xydata = self.read_xydata(filename) return self.create_signals_from(xydata, filename) def read_xydata(self, filename: str) -> np.ndarray: """Read data and metadata from file, write metadata to object, return xydata Args: filename: File name Returns: XY data """ raise NotImplementedError(f"Reading from {self.info.name} is not supported") Sigima-1.1.1/sigima/io/signal/formats.py000066400000000000000000000217401514013333200201040ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ I/O signal formats """ from __future__ import annotations import numpy as np import pandas as pd import scipy.io as sio from guidata.io import HDF5Reader, HDF5Writer from sigima.config import _ from sigima.io import ftlab from sigima.io.base import FormatInfo from sigima.io.common.converters import convert_array_to_valid_dtype from sigima.io.signal import funcs from sigima.io.signal.base import SignalFormatBase from sigima.objects.signal import SignalObj from sigima.objects.signal.constants import ( DATETIME_X_FORMAT_KEY, DEFAULT_DATETIME_FORMAT, ) from sigima.worker import CallbackWorkerProtocol class HDF5SignalFormat(SignalFormatBase): """Object representing a HDF5 signal file type""" FORMAT_INFO = FormatInfo( name=_("HDF5 files"), extensions="*.h5sig", readable=True, writeable=True, ) GROUP_NAME = "signal" def read( self, filename: str, worker: CallbackWorkerProtocol | None = None ) -> list[SignalObj]: """Read list of signal objects from file Args: filename: File name worker: Callback worker object Returns: List of signal objects """ reader = HDF5Reader(filename) try: with reader.group(self.GROUP_NAME): obj = SignalObj() obj.deserialize(reader) except ValueError as exc: raise ValueError("No valid signal data found") from exc except Exception as exc: # pylint: disable=broad-except raise RuntimeError( f"Unexpected error reading HDF5 signal from {filename}" ) from exc finally: reader.close() return [obj] def write(self, filename: str, obj: SignalObj) -> None: """Write data to file Args: filename: Name of file to write obj: Signal object to read data from """ assert isinstance(obj, SignalObj), "Object is not a signal" writer = HDF5Writer(filename) with writer.group(self.GROUP_NAME): obj.serialize(writer) writer.close() class CSVSignalFormat(SignalFormatBase): """Object representing a CSV signal file type""" FORMAT_INFO = FormatInfo( name=_("CSV files"), extensions="*.csv *.txt", readable=True, writeable=True, ) def read( self, filename: str, worker: CallbackWorkerProtocol | None = None ) -> list[SignalObj]: """Read list of signal objects from file Args: filename: File name worker: Callback worker object Returns: List of signal objects """ csv_data = funcs.read_csv(filename, worker) if csv_data.ylabels: # If y labels are present, we are sure that the data contains at least # two columns (x and y) objs = [] for i, (ylabel, yunit) in enumerate(zip(csv_data.ylabels, csv_data.yunits)): obj = self.create_object( filename, i if len(csv_data.ylabels) > 1 else None ) obj.set_xydata(csv_data.xydata[:, 0], csv_data.xydata[:, i + 1]) obj.xlabel = csv_data.xlabel or "" # Set xunit, defaulting to 's' if datetime signal and no unit specified if csv_data.datetime_metadata and not csv_data.xunit: obj.xunit = "s" # Default unit for datetime signals else: obj.xunit = csv_data.xunit or "" obj.ylabel = ylabel or "" obj.yunit = yunit or "" if csv_data.header: obj.metadata[self.HEADER_KEY] = csv_data.header # Add datetime metadata if detected if csv_data.datetime_metadata: obj.metadata.update(csv_data.datetime_metadata) # Add column metadata (constant-value columns like serial numbers) if csv_data.column_metadata: obj.metadata.update(csv_data.column_metadata) objs.append(obj) return objs return self.create_signals_from(csv_data.xydata, filename) def write(self, filename: str, obj: SignalObj) -> None: """Write data to file Args: filename: Name of file to write obj: Signal object to read data from """ # If X is datetime, convert back to datetime strings for CSV if obj.is_x_datetime(): datetime_values = obj.get_x_as_datetime() # Convert to strings with appropriate format datetime_format = obj.metadata.get( DATETIME_X_FORMAT_KEY, DEFAULT_DATETIME_FORMAT ) x_data = pd.to_datetime(datetime_values).strftime(datetime_format).values # Create modified xydata with datetime strings in X column # We'll write manually with pandas to preserve datetime strings data_dict = {obj.xlabel or "Time": x_data, obj.ylabel or "Y": obj.y} df = pd.DataFrame(data_dict) df.to_csv(filename, index=False) else: funcs.write_csv( filename, obj.xydata, obj.xlabel, obj.xunit, [obj.ylabel], [obj.yunit], obj.metadata.get(self.HEADER_KEY, ""), ) class NumPySignalFormat(SignalFormatBase): """Object representing a NumPy signal file type""" FORMAT_INFO = FormatInfo( name=_("NumPy binary files"), extensions="*.npy", readable=True, writeable=True, ) # pylint: disable=duplicate-code def read_xydata(self, filename: str) -> np.ndarray: """Read data and metadata from file, write metadata to object, return xydata Args: filename: Name of file to read Returns: NumPy array xydata """ return convert_array_to_valid_dtype(np.load(filename), SignalObj.VALID_DTYPES) def write(self, filename: str, obj: SignalObj) -> None: """Write data to file Args: filename: Name of file to write obj: Signal object to read data from """ np.save(filename, obj.xydata.T) class MatSignalFormat(SignalFormatBase): """Object representing a MAT-File .mat signal file type""" FORMAT_INFO = FormatInfo( name=_("MAT-Files"), extensions="*.mat", readable=True, writeable=True, ) # pylint: disable=duplicate-code def read( self, filename: str, worker: CallbackWorkerProtocol | None = None ) -> list[SignalObj]: """Read data and metadata from file, write metadata to object, return xydata Args: filename: Name of file to read Returns: NumPy array xydata """ mat = sio.loadmat(filename) allsig: list[SignalObj] = [] for dname, data in mat.items(): if dname.startswith("__") or not isinstance(data, np.ndarray): continue for sig in self.create_signals_from(data.squeeze(), filename): if dname != "sig": sig.title += f" ({dname})" allsig.append(sig) return allsig def write(self, filename: str, obj: SignalObj) -> None: """Write data to file Args: filename: Name of file to write obj: Signal object to read data from """ # metadata cannot be saved as such as their type will be lost and # cause problems when reading the file back sio.savemat(filename, {"sig": obj.xydata.T}) class FTLabSignalFormat(SignalFormatBase): """FT-Lab signal file.""" FORMAT_INFO = FormatInfo( name=_("FT-Lab"), extensions="*.sig", readable=True, writeable=False, ) def read_xydata(self, filename: str) -> np.ndarray: """Read data and metadata from file, populate metadata, return xydata. Args: filename: Path to FT-Lab file. Returns: Signal data. """ return ftlab.sigread_ftlabsig(filename) class MCASignalFormat(SignalFormatBase): """Object representing a MCA signal file type""" FORMAT_INFO = FormatInfo( name=_("MCA files"), extensions="*.mca", readable=True, writeable=False, ) def read( self, filename: str, worker: CallbackWorkerProtocol | None = None ) -> list[SignalObj]: """Read list of signal objects from file Args: filename: File name worker: Callback worker object Returns: List of signal objects """ mca = funcs.MCAFile(filename) mca.read() obj = self.create_object(filename) obj.set_xydata(mca.x, mca.y) obj.xlabel = mca.xlabel or "" obj.metadata = mca.metadata return [obj] Sigima-1.1.1/sigima/io/signal/funcs.py000066400000000000000000000647551514013333200175640ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ I/O signal functions """ # pylint: disable=invalid-name # Allows short reference names like x, y, ... from __future__ import annotations import datetime import re import warnings from dataclasses import dataclass from typing import TextIO import numpy as np import pandas as pd import scipy.interpolate from sigima.io.common.textreader import count_lines, read_first_n_lines from sigima.objects.signal.constants import ( DATETIME_X_FORMAT_KEY, DATETIME_X_KEY, DEFAULT_DATETIME_FORMAT, ) from sigima.worker import CallbackWorkerProtocol def get_labels_units_from_dataframe( df: pd.DataFrame, ) -> tuple[str, list[str], str, list[str]]: """Get labels and units from a DataFrame. Args: df: DataFrame Returns: Tuple (xlabel, ylabels, xunit, yunits) """ # Reading X,Y labels xlabel = str(df.columns[0]) ylabels = [str(col) for col in df.columns[1:]] # Retrieving units from labels xunit = "" yunits = [""] * len(ylabels) pattern = r"([\S ]*) \(([\S]*)\)" match = re.match(pattern, xlabel) if match is not None: xlabel, xunit = match.groups() for i, ylabel in enumerate(ylabels): match = re.match(pattern, ylabel) if match is not None: ylabels[i], yunits[i] = match.groups() return xlabel, ylabels, xunit, yunits def read_csv_by_chunks( fname_or_fileobj: str | TextIO, nlines: int | None = None, worker: CallbackWorkerProtocol | None = None, decimal: str = ".", delimiter: str | None = None, header: int | None = "infer", skiprows: int | None = None, nrows: int | None = None, comment: str | None = None, chunksize: int = 1000, ) -> pd.DataFrame: """Read CSV data with primitive options, using pandas read_csv function defaults, and reading data in chunks, using the iterator interface. Args: fname_or_fileobj: CSV file name or text stream object nlines: Number of lines contained in file (this argument is mandatory if `fname_or_fileobj` is a text stream object: counting line numbers from a text stream is not efficient, especially if one already has access to the initial text content from which the text stream was made) worker: Callback worker object decimal: Decimal character delimiter: Delimiter header: Header line skiprows: Skip rows nrows: Number of rows to read comment: Comment character chunksize: Chunk size Returns: DataFrame """ if isinstance(fname_or_fileobj, str): nlines = count_lines(fname_or_fileobj) elif nlines is None: raise ValueError("Argument `nlines` must be passed for text streams") # Read data in chunks, and concatenate them at the end, thus allowing to call the # progress callback function at each chunk read and to return an intermediate result # if the operation is canceled. chunks = [] for chunk in pd.read_csv( fname_or_fileobj, decimal=decimal, delimiter=delimiter, header=header, skiprows=skiprows, nrows=nrows, comment=comment, chunksize=chunksize, encoding_errors="ignore", ): chunks.append(chunk) # Compute the progression based on the number of lines read so far if worker is not None: worker.set_progress(sum(len(chunk) for chunk in chunks) / nlines) if worker.was_canceled(): break return pd.concat(chunks) DATA_HEADERS = [ "#DATA", # Generic "START_OF_DATA", # Various logging devices ">>>>>Begin Spectral Data<<<<<", # Ocean Optics ">>>Begin Data<<<", # Ocean Optics (alternative) ">>>Begin Spectrum Data<<<", # Avantes "# Data Start", # Andor, Horiba, Mass Spectrometry (Agilent, Thermo Fisher, ...) ">DATA START<", # Mass Spectrometry, Chromatography "BEGIN DATA", # Mass Spectrometry, Chromatography "", # Mass Spectrometry (XML-based) "##Start Data", # Bruker (X-ray, Raman, FTIR) "[DataStart]", # PerkinElmer (FTIR, UV-Vis) "BEGIN SPECTRUM", # PerkinElmer "%% Data Start %%", # LabVIEW, MATLAB "---Begin Data---", # General scientific instruments "===DATA START===", # Industrial/scientific devices ] def _read_df_without_header( filename: str, skiprows: int | None = None ) -> tuple[pd.DataFrame | None, str, str]: """Try to read a CSV file without header, testing various delimiters and decimal. Args: filename: CSV file name skiprows: Number of rows to skip at the beginning of the file Returns: A tuple (DataFrame if successful, None otherwise, decimal used, delimiter used) """ for decimal in (".", ","): for delimiter in (",", ";", r"\s+"): try: df = pd.read_csv( filename, decimal=decimal, delimiter=delimiter, header=None, comment="#", nrows=1000, # Read only the first 1000 lines encoding_errors="ignore", skiprows=skiprows, dtype=float, # Keep dtype to validate delimiter detection ) break except (pd.errors.ParserError, ValueError): df = None if df is not None: break return df, decimal, delimiter def _read_df_with_header(filename: str) -> tuple[pd.DataFrame | None, str, str]: """Try to read a CSV file with header, testing various delimiters and decimal. Args: filename: CSV file name Returns: A tuple (DataFrame if successful, None otherwise, decimal used, delimiter used) """ for decimal in (".", ","): for delimiter in (",", ";", r"\s+"): # Headers are generally in the first 10 lines, so we try to skip the # minimum number of lines before reading the data: for skiprows in range(20): try: df = pd.read_csv( filename, decimal=decimal, delimiter=delimiter, skiprows=skiprows, comment="#", nrows=1000, # Read only the first 1000 lines encoding_errors="ignore", ) # Validate: CSV should have at least 2 columns (x and y) # If only 1 column, likely wrong delimiter if df.shape[1] >= 2: break # Good delimiter found df = None # Try next delimiter except (pd.errors.ParserError, ValueError): df = None if df is not None: break if df is not None: break return df, decimal, delimiter def _detect_metadata_cols(df: pd.DataFrame) -> tuple[pd.DataFrame, dict]: """Detect columns containing constant/single-value metadata. Columns with a single unique value (excluding NaN) across all rows are treated as metadata rather than data columns. These are typically instrument serial numbers, experiment IDs, or other constant identifiers. Args: df: Input DataFrame Returns: A tuple (DataFrame with metadata columns removed, dict of metadata key-value pairs) """ metadata = {} cols_to_drop = [] # Start from column 1 (skip X column) and check for constant-value columns for col_idx in range(1, df.shape[1]): col_data = df.iloc[:, col_idx] col_name = df.columns[col_idx] # Get unique non-NaN values unique_values = col_data.dropna().unique() # If column has exactly one unique value (excluding NaN), it's metadata if len(unique_values) == 1: # Store the metadata value = unique_values[0] # Try to convert to appropriate type (keep as string if necessary) try: # Try int first if float(value).is_integer(): value = int(float(value)) else: value = float(value) except (ValueError, TypeError): # Keep as string value = str(value) metadata[str(col_name)] = value cols_to_drop.append(col_name) # Store column name, not index # Drop metadata columns from DataFrame if cols_to_drop: df = df.drop(columns=cols_to_drop) return df, metadata def _detect_datetime_col(df: pd.DataFrame) -> tuple[pd.DataFrame, dict | None]: """Try to detect the presence of a datetime column in a DataFrame. Detect if the first or second column contains datetime values, and convert it to float timestamps if so. Args: df: Input DataFrame Returns: A tuple (DataFrame with datetime column converted, datetime metadata dict) """ datetime_col_idx = None for col_idx in [0, 1]: # Check first two columns col_data = df.iloc[:, col_idx] # Skip numeric columns - datetime columns in CSV are loaded as object (string) # dtype, not as float/int. Numeric values (like frequencies in Hz) would be # wrongly interpreted as nanoseconds since Unix epoch by pd.to_datetime. if pd.api.types.is_numeric_dtype(col_data): continue # Try to convert to datetime try: # Attempt to parse as datetime # Note: format="mixed" was causing failures in some pandas versions, # so we use warnings filter to suppress the UserWarning instead with warnings.catch_warnings(): warnings.filterwarnings( "ignore", message="Could not infer format", category=UserWarning, ) datetime_series = pd.to_datetime(col_data, errors="coerce") # Check if most values were successfully converted (>90%) valid_ratio = datetime_series.notna().sum() / len(datetime_series) # Skip if conversion ratio is too low if valid_ratio <= 0.9: continue # Check if values have reasonable variation and are actual dates unique_dates = datetime_series.dropna().nunique() if unique_dates <= 1: continue # Check date range - should be reasonable dates, not epoch times min_date = datetime_series.min() max_date = datetime_series.max() # Dates should be after 1900 and the range should be > 1 sec valid_datetime = ( min_date.year >= 1900 and (max_date - min_date).total_seconds() > 1.0 ) if valid_datetime: # This is a datetime column! datetime_col_idx = col_idx break except (ValueError, TypeError, pd.errors.OutOfBoundsDatetime): # Not a datetime column, continue checking pass datetime_metadata = None if datetime_col_idx is not None: # Convert datetime column to float timestamps col_data = df.iloc[:, datetime_col_idx] with warnings.catch_warnings(): warnings.filterwarnings( "ignore", message="Could not infer format", category=UserWarning ) datetime_series = pd.to_datetime(col_data, errors="coerce") x_float = datetime_series.astype(np.int64) / 1e9 # Store datetime metadata (unit will be stored in xunit attribute) datetime_metadata = { DATETIME_X_KEY: True, DATETIME_X_FORMAT_KEY: DEFAULT_DATETIME_FORMAT, } # If datetime is in column 1 and column 0 looks like an index, drop column 0 if datetime_col_idx == 1: try: # Try to convert first column to int - if sequential, # it's likely an index column first_col = pd.to_numeric(df.iloc[:, 0], errors="coerce") if first_col.notna().all(): # Check if it's a sequential index (1, 2, 3, ...) diffs = first_col.diff().dropna() if (diffs == 1).sum() / len(diffs) > 0.9: # Drop the index column df = df.iloc[:, 1:].copy() datetime_col_idx = 0 # Now datetime is in position 0 except (ValueError, TypeError): pass # Replace datetime column with float timestamps df.iloc[:, datetime_col_idx] = x_float return df, datetime_metadata @dataclass class CSVData: """Data structure for CSV file contents. This dataclass encapsulates all the data extracted from a CSV file, including the actual XY data, labels, units, and metadata. Attributes: xydata: Numpy array containing X and Y data columns xlabel: Label for the X axis xunit: Unit for the X axis ylabels: List of labels for Y columns yunits: List of units for Y columns header: Optional header text from the CSV file datetime_metadata: Optional dict with datetime conversion info column_metadata: Optional dict with constant-value column metadata """ xydata: np.ndarray xlabel: str | None = None xunit: str | None = None ylabels: list[str] | None = None yunits: list[str] | None = None header: str | None = None datetime_metadata: dict | None = None column_metadata: dict | None = None def read_csv( filename: str, worker: CallbackWorkerProtocol | None = None, ) -> CSVData: """Read CSV data and return parsed components including datetime metadata. Args: filename: CSV file name worker: Callback worker object Returns: CSVData object containing all parsed CSV components """ xydata, xlabel, xunit, ylabels, yunits = None, None, None, None, None header, datetime_metadata, column_metadata = None, None, {} # The first attempt is to read the CSV file assuming it has no header because it # won't raise an error if the first line is data. If it fails, we try to read it # with a header, and if it fails again, we try to skip some lines before reading # the data. skiprows = None # Begin by reading the first 100 lines to search for a line that could mark the # beginning of the data after it (e.g., a line '#DATA' or other). first_100_lines = read_first_n_lines(filename, n=100).splitlines() for data_header in DATA_HEADERS: if data_header in first_100_lines: # Skip the lines before the data header skiprows = first_100_lines.index(data_header) + 1 break # First attempt: no header (try to read with different delimiters) read_without_header = True df, decimal, delimiter = _read_df_without_header(filename, skiprows=skiprows) # Second attempt: with header if df is None: df, decimal, delimiter = _read_df_with_header(filename) if df is None: raise ValueError("Unable to read CSV file (format not supported)") # At this stage, we have a DataFrame with column names, but we don't know # if the first line is a header or data. We try to read the first line as # a header, and if it fails, we read it as data. try: # Try to convert columns to float - if first column is datetime, this will # fail and we know we have a header first_col_numeric = pd.to_numeric(df.columns[0], errors="coerce") if pd.notna(first_col_numeric): # First column name is numeric, might be data df.columns.astype(float) # This means the first line is data, so we re-read it, but # without the header: read_without_header = True except (ValueError, TypeError): # TypeError can occur with pandas >= 2.2 read_without_header = False # This means that the first line is a header, so we already have the data # without missing values. # However, it also means that there could be text information preceding # the header. Let's try to read it and put it in `header` variable. # 1. We read only the first 1000 lines to avoid reading the whole file # 2. We keep only the lines beginning with a comment character # 3. We join the lines to create a single string header = "" with open(filename, "r", encoding="utf-8") as file: for _ in range(1000): line = file.readline() if line.startswith("#"): header += line else: break # Remove the last line if it contains the column names: last_line = header.splitlines()[-1] if header.splitlines() else "" if str(df.columns[0]) in last_line: header = "\n".join(header.splitlines()[:-1]) # Now we read the whole file with the correct options try: df = read_csv_by_chunks( filename, worker=worker, decimal=decimal, delimiter=delimiter, header=None if read_without_header else "infer", skiprows=skiprows, comment="#", ) except pd.errors.ParserError: # If chunked reading fails (e.g., ragged CSV), try different approaches df = None # Try with python engine (more flexible) for skip in [skiprows, 0, 9, 10, 15, 20]: # Try different skiprows values if df is not None: break try: df = pd.read_csv( filename, decimal=decimal, delimiter=delimiter, header=None if read_without_header else "infer", skiprows=skip, comment="#", engine="python", encoding_errors="ignore", ) break # Success! except (pd.errors.ParserError, ValueError): continue # If still failing, try auto-detect if df is None: try: df = pd.read_csv( filename, engine="python", encoding_errors="ignore", comment="#", ) except (pd.errors.ParserError, ValueError) as e: raise ValueError(f"Unable to parse CSV file: {e}") from e # Remove rows and columns where all values are NaN in the DataFrame: df = df.dropna(axis=0, how="all").dropna(axis=1, how="all") # Check if first row contains header strings (non-numeric values in all columns) # This happens when header="infer" fails to detect the header if not df.empty and isinstance(df.columns[0], (int, np.integer)): # Columns are integers, not strings - header wasn't properly parsed first_row = df.iloc[0] # Count how many values in first row are non-numeric strings non_numeric_count = 0 for val in first_row: try: float(val) except (ValueError, TypeError): if isinstance(val, str): non_numeric_count += 1 # If most of first row is non-numeric strings, it's likely a header row if non_numeric_count / len(first_row) > 0.5: # Use first row as column names df.columns = first_row.values # Drop the first row (header) df = df.iloc[1:].reset_index(drop=True) # Try to detect datetime columns - check first two columns # Often CSV files have an index column, then a datetime column if not df.empty and df.shape[1] >= 2: df, datetime_metadata = _detect_datetime_col(df) # Try to detect metadata columns (constant-value columns like serial numbers) # This must be done after datetime detection but before converting to numpy if not df.empty and df.shape[1] >= 2: df, column_metadata = _detect_metadata_cols(df) # Converting to NumPy array try: xydata = df.to_numpy(float) except (ValueError, TypeError): # If conversion fails, try converting each column individually # and dropping columns that can't be converted for col in df.columns: df[col] = pd.to_numeric(df[col], errors="coerce") df = df.dropna(axis=1, how="all") xydata = df.to_numpy(float) if xydata.size == 0: raise ValueError( f"Unable to read CSV file (no supported data after cleaning): {filename}" ) xlabel, ylabels, xunit, yunits = get_labels_units_from_dataframe(df) return CSVData( xydata=xydata, xlabel=xlabel, xunit=xunit, ylabels=ylabels, yunits=yunits, header=header, datetime_metadata=datetime_metadata, column_metadata=column_metadata, ) def write_csv( filename: str, xydata: np.ndarray, xlabel: str | None, xunit: str | None, ylabels: list[str] | None, yunits: list[str] | None, header: str | None, ) -> None: """Write CSV data. Args: filename: CSV file name xydata: XY data xlabel: X label xunit: X unit ylabels: Y labels yunits: Y units header: Header """ labels = "" delimiter = "," if len(ylabels) == 1: ylabels = ["Y"] if not ylabels[0] else ylabels elif ylabels: ylabels = [ f"Y{i + 1}" if not label else label for i, label in enumerate(ylabels) ] if yunits: ylabels = [ f"{label} ({unit})" if unit else label for label, unit in zip(ylabels, yunits) ] if ylabels: xlabel = xlabel or "X" if xunit: xlabel += f" ({xunit})" labels = delimiter.join([xlabel] + ylabels) df = pd.DataFrame(xydata.T, columns=[xlabel] + ylabels) df.to_csv(filename, index=False, header=labels, sep=delimiter) # Add header if present if header: with open(filename, "r+", encoding="utf-8") as file: content = file.read() file.seek(0, 0) file.write(header + "\n" + content) class MCAFile: """Class to handle MCA files.""" def __init__(self, filename: str) -> None: self.filename = filename self.raw_data: str = "" self.xlabel: str | None = None self.x: np.ndarray | None = None self.y: np.ndarray | None = None self.metadata: dict[str, str] = {} def __try_decode(self, raw_bytes: bytes) -> str: """Try to decode raw bytes with the specified encoding.""" encodings_to_try = ["utf-8", "utf-8-sig", "latin-1", "cp1252"] for enc in encodings_to_try: try: return raw_bytes.decode(enc) except UnicodeDecodeError: continue # If all attempts fail, use 'utf-8' with replacement warnings.warn("All decoding attempts failed. Used 'utf-8' with replacement.") return raw_bytes.decode("utf-8", errors="replace") def _read_raw_data(self) -> str: """Read the raw data from the MCA file, trying multiple encodings.""" with open(self.filename, "rb") as file: raw_bytes = file.read() raw_data = self.__try_decode(raw_bytes) self.raw_data = raw_data.replace("\r\n", "\n").replace("\r", "\n") def _read_section(self, section: str) -> str | None: """Read a section from the raw data.""" pattern = f"(?:.*)(^<<{section}>>$)(.*?)(?:<<.*>>)" match = re.search(pattern, self.raw_data, re.DOTALL + re.MULTILINE) if match: return match.group(2).strip() return None @staticmethod def _infer_string_value(value_str: str) -> str | float | int | datetime.datetime: """Infer the type of a string value and convert it accordingly.""" # Try to convert the value to a number or datetime try: if value_str.isdigit(): value = int(value_str) else: try: value = float(value_str) except ValueError: # Try to parse as datetime try: value = datetime.datetime.strptime( value_str, "%m/%d/%Y %H:%M:%S" ) except ValueError: value = value_str # Keep as string except ValueError: value = value_str return value def _extract_metadata_from_section( self, section: str ) -> dict[str, str | float | int | datetime.datetime]: """Extract metadata from a specific section.""" section_contents = self._read_section(section) if section_contents is None: return {} metadata = {} patterns = (r"(.*?) - (.*?)$", r"(.*?)\s*: \s*(.*)$", r"(.*?)\s*=\s*(.*);") for line in section_contents.splitlines(): for pattern in patterns: match = re.match(pattern, line) if match: key, value_str = match.groups() metadata[key.strip()] = self._infer_string_value(value_str.strip()) break return metadata def read(self) -> None: """Read the MCA file and extract data and metadata.""" self._read_raw_data() self.metadata = self._extract_metadata_from_section("PMCA SPECTRUM") additional_metadata = self._extract_metadata_from_section("DPP STATUS") self.metadata.update(additional_metadata) data_section = self._read_section("DATA") self.y = np.fromstring(data_section, sep=" ") if data_section else None if self.y is not None: self.x = np.arange(len(self.y)) cal_section = self._read_section("CALIBRATION") if cal_section: cal_metadata = self._extract_metadata_from_section(cal_section) self.xlabel = cal_metadata.get("LABEL") cal_data = np.array( [ [float(v) for v in val.split(" ")] for val in cal_section.splitlines()[1:] ] ) self.x = scipy.interpolate.interp1d( cal_data[:, 0], cal_data[:, 1], bounds_error=False, fill_value="extrapolate", )(self.x) Sigima-1.1.1/sigima/locale/000077500000000000000000000000001514013333200154265ustar00rootroot00000000000000Sigima-1.1.1/sigima/locale/fr/000077500000000000000000000000001514013333200160355ustar00rootroot00000000000000Sigima-1.1.1/sigima/locale/fr/LC_MESSAGES/000077500000000000000000000000001514013333200176225ustar00rootroot00000000000000Sigima-1.1.1/sigima/locale/fr/LC_MESSAGES/sigima.po000066400000000000000000001242041514013333200214360ustar00rootroot00000000000000# French translations for sigima. # Copyright (C) 2026 DataLab Platform Developers # This file is distributed under the same license as the sigima project. # msgid "" msgstr "" "Project-Id-Version: sigima\n" "Report-Msgid-Bugs-To: p.raybaut@codra.fr\n" "PO-Revision-Date: 2025-05-22 15:46+0200\n" "Language: fr\n" "Language-Team: DataLab Platform Developers 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.17.0\n" msgid "If True, the FFT operations will apply a shift to the zero frequency component to the center of the spectrum. This is useful for visualizing frequency components in a more intuitive way." msgstr "Si vrai, les opérations FFT appliqueront un décalage de la composante de fréquence nulle au centre du spectre. Cela est utile pour visualiser les composantes de fréquence de manière plus intuitive." msgid "If True, convolution kernels will be automatically normalized to sum to 1.0 before convolution. This ensures that the output signal or image has the same overall magnitude as the input when using smoothing kernels. Set to False to preserve the mathematical properties of the original kernel." msgstr "Si vrai, les noyaux de convolution seront automatiquement normalisés pour que leur somme soit égale à 1.0 avant la convolution. Cela garantit que le signal ou l'image de sortie a la même magnitude globale que l'entrée lors de l'utilisation de noyaux de lissage. Réglez sur Faux pour préserver les propriétés mathématiques du noyau original." msgid "" "List of supported image I/O formats. Each format is a tuple of\n" "``(file_extension, description)``.\n" "\n" "The ``sigima`` library supports any image format that can be read by the ``imageio``\n" "library, provided that the associated plugin(s) are installed (see `imageio\n" "documentation `_)\n" "and that the output NumPy array data type and shape are supported by ``sigima``.\n" "\n" "To add a new file format, you may use the ``imageio_formats`` option to specify\n" "additional formats. Each entry should be a tuple of (file extension, description).\n" msgstr "" "Liste des formats d'entrée/sortie d'images pris en charge. Chaque format est un tuple de\n" "(extension de fichier, description).\n" "\n" "La bibliothèque ``sigima`` prend en charge tout format d'image qui peut être lu par la bibliothèque ``imageio``\n" "à condition que le(s) plugin(s) associé(s) soient installés (voir la documentation ``imageio\n" "``)\n" "et que le type de données et la forme du tableau NumPy de sortie soient pris en charge par ``sigima``.\n" "\n" "Pour ajouter un nouveau format de fichier, vous pouvez utiliser l'option ``imageio_formats`` pour spécifier\n" "des formats supplémentaires. Chaque entrée doit être un tuple de (extension de fichier, description).\n" msgid "" "Backend library for visualization (sigima.viz module).\n" "\n" "Valid values: ``\"auto\"``, ``\"plotpy\"``, ``\"matplotlib\"``.\n" "\n" "- ``\"auto\"`` (default): Automatically select PlotPy if available, otherwise Matplotlib\n" "- ``\"plotpy\"``: Use PlotPy for interactive visualizations (requires PlotPy and Qt)\n" "- ``\"matplotlib\"``: Use Matplotlib for visualizations (simpler, view-only)\n" "\n" "This setting can also be overridden using the ``SIGIMA_VIZ_BACKEND`` environment\n" "variable. Note that Matplotlib backend does not support all features of PlotPy\n" "(e.g., ``create_segment()``, ``create_cursor()``, etc. will raise NotImplementedError).\n" msgstr "" "Bibliothèque backend pour la visualisation des tests (tests interactifs uniquement).\n" "\n" "Valeurs valides : ``\"auto\"``, ``\"plotpy\"``, ``\"matplotlib\"``.\n" "\n" "- ``\"auto\"`` (par défaut) : Sélectionner automatiquement PlotPy si disponible, sinon Matplotlib\n" "- ``\"plotpy\"`` : Utiliser PlotPy pour les visualisations interactives (nécessite PlotPy et Qt)\n" "- ``\"matplotlib\"`` : Utiliser Matplotlib pour les visualisations (plus simple, statique)\n" "\n" "Ce paramètre peut également être remplacé en utilisant la variable d'environnement ``SIGIMA_VIZ_BACKEND``.\n" "Notez que le backend Matplotlib ne prend pas en charge toutes les fonctionnalités de PlotPy\n" "(par exemple, ``create_segment()``, ``create_cursor()``, etc. lèveront NotImplementedError).\n" msgid "Ellipse" msgstr "Ellipse" msgid "Circle" msgstr "Cercle" msgid "Polygon" msgstr "Polygone" msgid "Bottom-right" msgstr "En bas à droite" msgid "Around" msgstr "Autour" msgid "Cosine" msgstr "Cosinus" msgid "Exponential" msgstr "Exponentielle" msgid "Flat Top" msgstr "Flat Top" msgid "Gaussian" msgstr "Gaussienne" msgid "Linear" msgstr "Linéaire" msgid "Spline" msgstr "Spline" msgid "Quadratic" msgstr "Quadratique" msgid "Cubic" msgstr "Cubique" msgid "Barycentric" msgstr "Barycentrique" msgid "PCHIP" msgstr "PCHIP" msgid "Nearest" msgstr "Plus proche voisin" msgid "Maximum" msgstr "Maximum" msgid "Amplitude" msgstr "Amplitude" msgid "Area" msgstr "Aire" msgid "Energy" msgstr "Energie" msgid "RMS" msgstr "RMS" msgid "Brickwall" msgstr "Filtre idéal" msgid "Elliptic" msgstr "Elliptique" msgid "Each signal becomes a row" msgstr "Chaque signal devient une ligne" msgid "Each signal becomes a column" msgstr "Chaque signal devient une colonne" msgid "Rectangle" msgstr "Rectangle" msgid "All supported files" msgstr "Tous les fichiers pris en charge" msgid "Directory" msgstr "Répertoire" msgid "Basename pattern" msgstr "Modèle de nom de base" #, python-brace-format msgid "" "Pattern accepts a Python format string.\n" "\n" "Standard Python formatting fields may be used, including:\n" "{title}, {index}, {count}, {xlabel}, {xunit}, {ylabel}, {yunit},\n" "{metadata}, {metadata[key]}" msgstr "" "Le modèle accepte une chaîne de format Python.\n" "\n" "Les champs de formatage Python standard peuvent être utilisés, y compris :\n" "{title}, {index}, {count}, {xlabel}, {xunit}, {ylabel}, {yunit},\n" "{metadata}, {metadata[key]}" msgid "Extension" msgstr "Extension" msgid "File extension with leading dot (e.g. .txt or .csv)" msgstr "Extension de fichier avec un point de tête (par exemple .txt ou .csv)" msgid "Overwrite" msgstr "Écraser" msgid "Overwrite existing files" msgstr "Écraser les fichiers existants" msgid "Image I/O formats" msgstr "Formats d'entrée/sortie d'images" msgid "Text files" msgstr "Fichiers texte" msgid "MAT-Files" msgstr "Fichiers MAT" msgid "Signal I/O formats" msgstr "Formats d'entrée/sortie de signaux" msgid "HDF5 files" msgstr "Fichiers HDF5" msgid "CSV files" msgstr "Fichiers CSV" msgid "NumPy binary files" msgstr "Fichiers binaires NumPy" msgid "FT-Lab" msgstr "FT-Lab" msgid "MCA files" msgstr "Fichiers MCA" msgid "Seed" msgstr "Graine" msgid "Uniform distribution lower bound" msgstr "Borne inférieure de la distribution uniforme" msgid "Uniform distribution higher bound" msgstr "Borne supérieure de la distribution uniforme" msgid "Normal distribution mean" msgstr "Moyenne de la distribution normale" msgid "Normal distribution standard deviation" msgstr "Ecart-type de la distribution normale" msgid "Poisson distribution mean" msgstr "Moyenne de la distribution de Poisson" msgid "Zero" msgstr "Zéro" msgid "Normal distribution" msgstr "Distribution normale" msgid "Poisson distribution" msgstr "Distribution de Poisson" msgid "Uniform distribution" msgstr "Distribution uniforme" msgid "2D ramp" msgstr "Rampe 2D" msgid "Checkerboard" msgstr "Damier" msgid "Sinusoidal grating" msgstr "Réseau sinusoïdal" msgid "Ring pattern" msgstr "Motif en anneaux" msgid "Siemens star" msgstr "Étoile de Siemens" msgid "2D sinc" msgstr "Sinc 2D" msgid "Untitled image" msgstr "Image sans titre" msgid "Title" msgstr "Titre" msgid "Image height: number of rows" msgstr "Hauteur de l'image : nombre de lignes" msgid "Height" msgstr "Hauteur" msgid "Image width: number of columns" msgstr "Largeur de l'image : nombre de colonnes" msgid "Width" msgstr "Largeur" msgid "Type" msgstr "Type" msgid "Image data type" msgstr "Type de données de l'image" msgid "X label" msgstr "Titre X" msgid "X unit" msgstr "Unité X" msgid "Y label" msgstr "Titre Y" msgid "Y unit" msgstr "Unité Y" msgid "Z label" msgstr "Titre Z" msgid "Z unit" msgstr "Unité Z" msgid "Coefficients" msgstr "Coefficients" msgid "Domain" msgstr "Domaine" msgid "Checkerboard pattern with alternating squares" msgstr "Motif en damier avec des carrés alternés" msgid "Square size" msgstr "Taille des carrés" msgid "Size of each square in pixels" msgstr "Taille de chaque carré en pixels" msgid "X offset" msgstr "Décalage X" msgid "Y offset" msgstr "Décalage Y" msgid "Value for dark squares" msgstr "Valeur des carrés foncés" msgid "Minimum value" msgstr "Minimum" msgid "Value for light squares" msgstr "Valeur des carrés clairs" msgid "Maximum value" msgstr "Maximum" msgid "Amplitude and offset" msgstr "Amplitude et décalage" msgid "DC offset" msgstr "Décalage DC" msgid "Frequency and phase" msgstr "Fréquence et phase" msgid "Spatial frequency in X direction" msgstr "Fréquence spatiale selon X" msgid "Spatial frequency in Y direction" msgstr "Fréquence spatiale selon Y" msgid "Phase" msgstr "Phase" msgid "Concentric ring pattern" msgstr "Motif en anneaux concentriques" msgid "Center X coordinate" msgstr "Coordonnées du centre X" msgid "Center Y coordinate" msgstr "Coordonnées du centre Y" msgid "Ring parameters" msgstr "Paramètres des anneaux" msgid "Period" msgstr "Période" msgid "Distance between ring centers" msgstr "Distance entre les centres des anneaux" msgid "Ring width" msgstr "Largeur des anneaux" msgid "Width of each ring" msgstr "Largeur de chaque anneau" msgid "Siemens star pattern for resolution testing" msgstr "Motif étoile de Siemens pour les tests de résolution" msgid "Number of spokes" msgstr "Nombre de rayons" msgid "Number of spoke pairs" msgstr "Nombre de paires de rayons" msgid "Radial limits" msgstr "Limites radiales" msgid "Inner radius" msgstr "Rayon intérieur" msgid "Inner radius (hole in center)" msgstr "Rayon intérieur (trou au centre)" msgid "Outer radius" msgstr "Rayon extérieur" msgid "Outer radius (edge of pattern)" msgstr "Rayon extérieur (bord du motif)" msgid "Center and scale" msgstr "Centre et échelle" msgid "Scale factor" msgstr "Facteur d'échelle" msgid "Data" msgstr "Données" msgid "Metadata" msgstr "Métadonnées" msgid "Annotations" msgstr "Annotations" msgid "Uniform coordinates" msgstr "Coordonnées uniformes" msgid "Origin" msgstr "Origine" msgid "Pixel spacing" msgstr "Taille des pixels" msgid "Extent" msgstr "Bornes" msgid "Coordinates" msgstr "Coordonnées" msgid "X coordinates" msgstr "Coordonnées X" msgid "Y coordinates" msgstr "Coordonnées Y" msgid "Titles / Units" msgstr "Titres / Unités" msgid "Image title" msgstr "Titre de l'image" msgid "Untitled" msgstr "Sans titre" msgid "X-axis" msgstr "Axe des X" msgid "Unit" msgstr "Unité" msgid "Y-axis" msgstr "Axe des Y" msgid "Z-axis" msgstr "Axe des Z" msgid "Scales" msgstr "Echelles" msgid "Auto scale" msgstr "Echelle automatique" msgid "Logarithmic scale" msgstr "Echelle logarithmique" msgid "Lower bound" msgstr "Borne inférieure" msgid "Upper bound" msgstr "Borne supérieure" msgid "LUT range" msgstr "Plage de LUT" msgid "This is a set of parameters defining a Region of Interest (ROI) in an image. The parameters can be used to create a ROI object or to extract data from an image using the ROI.

All values are expressed in physical coordinates (floats). The conversion to pixel coordinates is done by taking into account the image pixel size and origin.
" msgstr "Ceci est un ensemble de paramètres définissant une Région d'Intérêt (ROI) dans une image. Les paramètres peuvent être utilisés pour créer un objet ROI ou pour extraire des données d'une image en utilisant la ROI.

Toutes les valeurs sont exprimées en coordonnées physiques (flottantes). La conversion en coordonnées de pixels est effectuée en tenant compte de la taille des pixels et de l'origine de l'image.
" msgid "ROI title" msgstr "Titre de la ROI" msgid "Geometry" msgstr "Géométrie" msgid "Top left corner" msgstr "Coin supérieur gauche" msgid "Center coordinates" msgstr "Coordonnées du centre" msgid "Radius" msgstr "Rayon" msgid "Inverse ROI logic" msgstr "Inverser la logique de la ROI" msgid "" "When disabled (default), the ROI defines an area inside the shape on which to focus (masking data outside).\n" "When enabled, the ROI logic is inverted to focus on data outside the shape (masking data inside)." msgstr "" "Lorsque le réglage est désactivé (par défaut), la ROI définit une zone à l'intérieur de la forme sur laquelle se concentrer (masquant les données à l'extérieur).\n" "Lorsque le réglage est activé, la logique de la ROI est inversée pour se concentrer sur les données à l'extérieur de la forme (masquant les données à l'intérieur)." msgid "Lorentzian" msgstr "Lorentzienne" msgid "Voigt" msgstr "Voigt" msgid "Blackbody (Planck)" msgstr "Corps noir (Planck)" msgid "Sine" msgstr "Sinus" msgid "Sawtooth" msgstr "Dent de scie" msgid "Triangle" msgstr "Triangle" msgid "Square" msgstr "Carré" msgid "Cardinal sine" msgstr "Sinus cardinal" msgid "Linear chirp" msgstr "Modulation linéaire de fréquence" msgid "Step" msgstr "Echelon" msgid "Logistic" msgstr "Logistique" msgid "Pulse" msgstr "Impulsion" msgid "Step pulse" msgstr "Impulsion échelon" msgid "Square pulse" msgstr "Impulsion carrée" msgid "Polynomial" msgstr "Polynomial" msgid "Custom" msgstr "Personnalisé" msgid "Untitled signal" msgstr "Signal sans titre" msgid "Npoints" msgstr "Npoints" msgid "Total number of points in the signal" msgstr "Nombre total de points dans le signal" msgid "Temperature" msgstr "Température" msgid "Initial phase" msgstr "Phase initiale" msgid "Chirp rate (f-2)" msgstr "Taux de modulation de fréquence" msgid "Vertical offset" msgstr "Décalage vertical" msgid "Initial frequency (Hz)" msgstr "Fréquence intiale (Hz)" msgid "Horizontal offset" msgstr "Décalage horizontal" msgid "Growth or decay rate" msgstr "Taux de croissance ou de décroissance" msgid "Start" msgstr "Démarrer" msgid "Offset" msgstr "Décalage" msgid "End" msgstr "Fin" msgid "Start time" msgstr "Instant de début" msgid "End time" msgstr "Instant de fin" msgid "Number of points" msgstr "Nombre de points" msgid "Initial value" msgstr "Valeur initiale" msgid "Noise amplitude" msgstr "Amplitude du bruit" msgid "Rise start time" msgstr "Instant de début de montée" msgid "Total rise time" msgstr "Temps de montée total" msgid "Step pulse with noise" msgstr "Impulsion échelon avec bruit" msgid "Square pulse with noise" msgstr "Impulsion carrée avec bruit" msgid "Full Width at Half Maximum" msgstr "Largeur à mi-hauteur" msgid "Total fall time" msgstr "Temps de descente total" msgid "Custom signal" msgstr "Signal personnalisé" msgid "Data and metadata" msgstr "Données et métadonnées" msgid "Signal title" msgstr "Titre du signal" msgid "First point coordinate" msgstr "Coordonnée du premier point" msgid "Last point coordinate" msgstr "Coordonnée du dernier point" msgid "Arithmetic" msgstr "Arithmétique" msgid "Operator" msgstr "Opérateur" msgid "Factor" msgstr "Facteur" msgid "Constant" msgstr "Constante" msgid "Operation" msgstr "Opération" msgid "Convert to `obj1` data type" msgstr "Convertir vers le type de données de `obj1`" msgid "Result" msgstr "Résultat" msgid "Gaussian filter" msgstr "Filtre gaussien" msgid "Standard deviation of the Gaussian filter" msgstr "Ecart-type du filtre gaussien" msgid "" "Mode of the filter:\n" "- 'reflect': Reflect the data at the boundary\n" "- 'constant': Pad with a constant value\n" "- 'nearest': Pad with the nearest value\n" "- 'mirror': Reflect the data at the boundary with the data itself\n" "- 'wrap': Circular boundary" msgstr "" "Mode du filtre :\n" "- 'reflect' : Réfléchir les données à la frontière\n" "- 'constant' : Remplir avec une valeur constante\n" "- 'nearest' : Remplir avec la valeur la plus proche\n" "- 'mirror' : Réfléchir les données à la frontière avec les données elles-mêmes\n" "- 'wrap' : Frontière circulaire" msgid "Moving average" msgstr "Moyenne mobile" msgid "Size of the moving window" msgstr "Taille de la fenêtre glissante" msgid "Mode" msgstr "Mode" msgid "Moving median" msgstr "Médiane mobile" msgid "Clip" msgstr "Ecrêtage" msgid "Lower clipping value" msgstr "Borne inférieure d'écrêtage" msgid "Upper clipping value" msgstr "Borne supérieure d'écrêtage" msgid "Normalize" msgstr "Normaliser" msgid "Normalize with respect to" msgstr "Normaliser par rapport à" msgid "Histogram" msgstr "Histogramme" msgid "Number of bins" msgstr "Nombre de classes" msgid "Lower limit" msgstr "Limite inférieure" msgid "Upper limit" msgstr "Limite supérieure" msgid "FFT" msgstr "FFT" msgid "Shift" msgstr "Décalage" msgid "Shift zero frequency to center" msgstr "Décaler la fréquence nulle au centre" msgid "Spectrum" msgstr "Spectre" msgid "Output in decibel (dB)" msgstr "Sortie en décibels (dB)" msgid "Constant value" msgstr "Constante" msgid "Angle unit" msgstr "Unité de l'angle" msgid "Unit of angle measurement" msgstr "Unité de mesure de l'angle" msgid "Unwrapping removes discontinuities in phase" msgstr "Déplier supprime les discontinuités de phase" msgid "Signals to image" msgstr "Signaux vers image" msgid "Orientation" msgstr "Orientation" msgid "Stack signals as rows or columns in the output image" msgstr "Empiler les signaux en tant que lignes ou colonnes dans une nouvelle image" msgid "Normalize each signal before combining" msgstr "Normaliser chaque signal avant de combiner" msgid "Normalization method" msgstr "Méthode de normalisation" msgid "Method used for normalization" msgstr "Méthode utilisée pour la normalisation" msgid "columns" msgstr "colonnes" msgid "rows" msgstr "lignes" msgid "Distribute over" msgstr "Distribuer selon les" msgid "Columns" msgstr "Colonnes" msgid "Rows" msgstr "Lignes" msgid "Column spacing" msgstr "Espace entre chaque colonne" msgid "Row spacing" msgstr "Espace entre chaque ligne" msgid "Regions of interest" msgstr "Régions d'intérêt" msgid "Create regions of interest" msgstr "Créer des régions d'intérêt" msgid "" "Regions of interest will be created around detected features, if at least two features are detected.\n" "ROI size is optimized based on feature spacing." msgstr "" "Des régions d'intérêt seront créées autour des caractéristiques détectées, si au moins deux caractéristiques sont détectées.\n" "La taille de la ROI est optimisée en fonction de l'espacement des caractéristiques." msgid "ROI geometry" msgstr "Géométrie de la ROI" msgid "Relative threshold" msgstr "Seuil relatif" msgid "Detection threshold, relative to difference between data maximum and minimum" msgstr "Seuil de détection, relatif à la différence entre le maximum et le minimum des données de l'image" msgid "Neighborhoods size" msgstr "Taille du voisinage" msgid "Size of the sliding window used in maximum/minimum filtering algorithm (if no value is provided, the algorithm will use a default size based on the image size). " msgstr "Taille de la fenêtre glissante utilisée dans l'algorithme de filtrage par maximum/minimum (si aucune valeur n'est fournie, l'algorithme utilisera une taille par défaut basée sur la taille de l'image)." msgid "Shape" msgstr "Forme" msgid "The minimum standard deviation for Gaussian Kernel. Keep this low to detect smaller blobs." msgstr "L'écart-type minimal pour le noyau gaussien. Cette valeur doit être faible pour détecter de petites taches." msgid "The maximum standard deviation for Gaussian Kernel. Keep this high to detect larger blobs." msgstr "L'écart-type maximal pour le noyau gaussien. Cette valeur doit être élevée pour détecter de grandes taches." msgid "Minimum intensity of blobs." msgstr "Intensité minimale des taches." msgid "Overlap" msgstr "Recouvrement" msgid "If two blobs overlap by a fraction greater than this value, the smaller blob is eliminated." msgstr "Si deux taches ont un taux de recouvrement supérieur à ce seuil, alors la plus petite tache est éliminée." msgid "Exclude border" msgstr "Exclure la bordure" msgid "If True, exclude blobs from the border of the image." msgstr "Si le réglage est actif, exclure les taches de la bordure de l'image." msgid "Log scale" msgstr "Echelle logarithmique" msgid "If set intermediate values of standard deviations are interpolated using a logarithmic scale to the base 10. If not, linear interpolation is used." msgstr "Les valeurs intermédiaires d'écart-type peuvent être interpolées selon une échelle linéaire ou logarithmique." msgid "Min. threshold" msgstr "Seuil min." msgid "The minimum threshold between local maxima and minima. This parameter does not affect the quality of the blobs, only the quantity. Lower thresholds result in larger numbers of blobs." msgstr "Le seuil minimum entre les maxima et minima locaux. Ce paramètre n'affecte pas la qualité des taches, mais seulement leur nombre. Un seuil bas donne un nombre plus important de taches." msgid "Max. threshold" msgstr "Seuil max." msgid "The maximum threshold between local maxima and minima. This parameter does not affect the quality of the blobs, only the quantity. Lower thresholds result in larger numbers of blobs." msgstr "Le seuil maximum entre les maxima et minima locaux. Ce paramètre n'affecte pas la qualité des taches, mais seulement leur nombre. Un seuil bas donne un nombre plus important de taches." msgid "Min. repeatability" msgstr "Répétabilité min." msgid "The minimum number of times a blob needs to be detected in a sequence of images to be considered valid." msgstr "Le nombre minimum de fois qu'une tache doit être détectée dans une séquence d'images pour être considérée valide." msgid "Min. distance between blobs" msgstr "Distance min. entre taches" msgid "The minimum distance between two blobs. If blobs are found closer together than this distance, the smaller blob is removed." msgstr "La distance minimale entre deux taches. Si deux taches sont détectées à une distance inférieure à celle-ci, alors la plus petite tache est éliminée." msgid "Filter by color" msgstr "Filtrer par couleur" msgid "If true, the image is filtered by color instead of intensity." msgstr "Si vrai, l'image est filtrée par couleur au lieu d'intensité." msgid "Blob color" msgstr "Couleur de la tache" msgid "The color of the blobs to detect (0 for dark blobs, 255 for light blobs)." msgstr "La couleur des taches à détecter (0 pour les taches foncées, 255 pour les taches claires)." msgid "Filter by area" msgstr "Filtrer par aire" msgid "If true, the image is filtered by blob area." msgstr "Si vrai, l'image est filtrée par l'aire des taches." msgid "Min. area" msgstr "Aire min." msgid "The minimum blob area." msgstr "L'aire minimale des taches." msgid "Max. area" msgstr "Aire max." msgid "The maximum blob area." msgstr "L'aire maximale des taches." msgid "Filter by circularity" msgstr "Filtrer par circularité" msgid "If true, the image is filtered by blob circularity." msgstr "Si vrai, l'image est filtrée par la circularité des taches." msgid "Min. circularity" msgstr "Circularité min." msgid "The minimum circularity of the blobs." msgstr "La circularité minimale des taches." msgid "Max. circularity" msgstr "Circularité max." msgid "The maximum circularity of the blobs." msgstr "La circularité maximale des taches." msgid "Filter by inertia" msgstr "Filtrer par inertie" msgid "If true, the image is filtered by blob inertia." msgstr "Si vrai, l'image est filtrée par l'inertie des taches." msgid "Min. inertia ratio" msgstr "Ratio d'inertie min." msgid "The minimum inertia ratio of the blobs." msgstr "Le ratio d'inertie minimal des taches." msgid "Max. inertia ratio" msgstr "Ratio d'inertie max." msgid "The maximum inertia ratio of the blobs." msgstr "Le ratio d'inertie maximal des taches." msgid "Filter by convexity" msgstr "Filtrer par convexité" msgid "If true, the image is filtered by blob convexity." msgstr "Si vrai, l'image est filtrée par la convexité des taches." msgid "Min. convexity" msgstr "Convexité min." msgid "The minimum convexity of the blobs." msgstr "La convexité minimale des taches." msgid "Max. convexity" msgstr "Convexité max." msgid "The maximum convexity of the blobs." msgstr "La convexité maximale des taches." msgid "Radiusmin" msgstr "Rayonmin" msgid "Radiusmax" msgstr "Rayonmax" msgid "Minimal distance" msgstr "Distance minimale" msgid "Standard deviation of the Gaussian filter." msgstr "Ecart-type du filtrage gaussien" msgid "Low threshold" msgstr "Seuil bas" msgid "Lower bound for hysteresis thresholding (linking edges)." msgstr "Borne inférieure pour le seuillage par hystérésis (liaison des contours)." msgid "High threshold" msgstr "Seuil haut" msgid "Upper bound for hysteresis thresholding (linking edges)." msgstr "Borne supérieure pour le seuillage par hystérésis (liaison des contours)." msgid "Use quantiles" msgstr "Utiliser les quantiles" msgid "If True then treat low_threshold and high_threshold as quantiles of the edge magnitude image, rather than absolute edge magnitude values. If True then the thresholds must be in the range [0, 1]." msgstr "Interprète les seuils bas et haut en tant que quantiles des niveaux des contours, au lieu de valeurs absolues des contours. Si le réglage est actif, alors les seuils doivent être compris entre 0 et 1." msgid "Value to fill past edges of input if mode is constant." msgstr "Valeur de remplissage si le mode est constant." msgid "Gamma" msgstr "Gamma" msgid "Gamma correction factor (higher values give more contrast)." msgstr "Facteur de correction gamma (plus la valeur est élevée, plus le contraste est important)." msgid "Gain" msgstr "Gain" msgid "Gain factor (higher values give more contrast)." msgstr "Facteur de gain (plus la valeur est élevée, plus le contraste est important)." msgid "Inverse" msgstr "Inverse" msgid "If True, apply inverse logarithmic transformation." msgstr "Si vrai, appliquer une transformation logarithmique inverse." msgid "Cutoff" msgstr "Cutoff" msgid "Cutoff value (higher values give more contrast)." msgstr "Valeur de coupure (plus la valeur est élevée, plus le contraste est important)." msgid "If True, apply inverse sigmoid transformation." msgstr "Si vrai, appliquer une transformation sigmoïde inverse." msgid "Input range" msgstr "Echelle de niveaux en entrée" msgid "Min and max intensity values of input image ('image' refers to input image min/max levels, 'dtype' refers to input image data type range)." msgstr "Valeurs min/max d'intensité de l'image en entrée ('image' correspond aux niveaux min/max de l'image en entrée, 'dtype' correspond aux valeurs min/max du type de données de l'image)." msgid "Output range" msgstr "Echelle de niveaux en sortie" msgid "Min and max intensity values of output image ('image' refers to input image min/max levels, 'dtype' refers to input image data type range).." msgstr "Valeurs min/max d'intensité de l'image en sortie ('image' correspond aux niveaux min/max de l'image en entrée, 'dtype' correspond aux valeurs min/max du type de données de l'image)." msgid "Number of bins for image histogram." msgstr "Nombre de classes de l'histogramme des niveaux de l'image." msgid "Clipping limit" msgstr "Écrêtage limite" msgid "Clipping limit (higher values give more contrast)." msgstr "Valeur d'écrêtage (plus la valeur est élevée, plus le contraste est important)." msgid "Threshold" msgstr "Seuil" msgid "Counts" msgstr "Coups" msgid "increasing" msgstr "croissant" msgid "decreasing" msgstr "décroissant" msgid "X translation" msgstr "Translation en X" msgid "Y translation" msgstr "Translation en Y" msgid "Horizontal spacing between ROI centers, as a percentage of the automatically computed cell width (100% = evenly distributed grid)" msgstr "Espacement horizontal entre les centres des ROI, en pourcentage de la largeur de cellule automatiquement calculée (100% = grille uniformément distribuée)" msgid "Vertical spacing between ROI centers, as a percentage of the automatically computed cell height (100% = evenly distributed grid)" msgstr "Espacement vertical entre les centres des ROI, en pourcentage de la hauteur de cellule automatiquement calculée (100% = grille uniformément distribuée)" msgid "ROI titles" msgstr "Titres des ROI" msgid "Base name" msgstr "Nom de base" msgid "Name pattern" msgstr "Modèle de nom" msgid "X direction" msgstr "Direction X" msgid "Y direction" msgstr "Direction Y" msgid "horizontal" msgstr "horizontal" msgid "vertical" msgstr "vertical" msgid "Direction" msgstr "Direction" msgid "Row" msgstr "Ligne" msgid "Column" msgstr "Colonne" msgid "Start row" msgstr "Ligne (début)" msgid "Start column" msgstr "Colonne (début)" msgid "End row" msgstr "Ligne (fin)" msgid "End column" msgstr "Colonne (fin)" msgid "Profile rectangular area" msgstr "Zone rectangulaire du profil" msgid "Row 1" msgstr "Ligne 1" msgid "Row 2" msgstr "Ligne 2" msgid "Column 1" msgstr "Colonne 1" msgid "Column 2" msgstr "Colonne 2" msgid "Center position" msgstr "Position du centre" msgid "Image centroid" msgstr "Barycentre de l'image" msgid "Image center" msgstr "Centre de l'image" msgid "User-defined" msgstr "Défini par l'utilisateur" msgid "Center" msgstr "Centre" msgid "Cut-off frequency ratio" msgstr "Fréquence de coupure relative" msgid "High-pass filter" msgstr "Filtre passe-haut" msgid "If True, apply high-pass filter instead of low-pass" msgstr "Si vrai, appliquer un filtre passe-haut au lieu d'un filtre passe-bas" msgid "Order" msgstr "Ordre" msgid "Order of the Butterworth filter" msgstr "Ordre du filtre de Butterworth" msgid "Center frequency" msgstr "Fréquence centrale" msgid "Center frequency of the Gaussian filter" msgstr "Fréquence centrale du filtre gaussien" msgid "Inverse FFT result" msgstr "Résultat de la FFT inverse" msgid "Real part" msgstr "Partie réelle" msgid "Absolute value" msgstr "Valeur absolue" msgid "How to return the inverse FFT result" msgstr "Comment retourner le résultat de la FFT inverse" msgid "Frequency" msgstr "Fréquence" msgid "cval" msgstr "cval" msgid "Value used for points outside the boundaries of the input if mode is 'constant'" msgstr "Valeur utilisée pour les points situés en dehors des frontières de l'image d'origine (si le mode est 'constant')" msgid "Reshape the output array" msgstr "Redimensionner l'image de destination" msgid "Reshape the output array so that the input array is contained completely in the output" msgstr "Redimensionner l'image de destination de sorte qu'elle puisse contenir la totalité de l'image source" msgid "Prefilter the input image" msgstr "Prétraitement de l'image d'origine (spline)" msgid "Spline interpolation order" msgstr "Ordre de l'interpolation de type spline" msgid "Zoom" msgstr "Zoom" msgid "Minimum X-coordinate of the output image" msgstr "Coordonnée X minimale de l'image de sortie" msgid "Maximum X-coordinate of the output image" msgstr "Coordonnée X maximale de l'image de sortie" msgid "Minimum Y-coordinate of the output image" msgstr "Coordonnée Y minimale de l'image de sortie" msgid "Maximum Y-coordinate of the output image" msgstr "Coordonnée Y maximale de l'image de sortie" msgid "Pixel size" msgstr "Taille de pixel" msgid "Output shape" msgstr "Taille de l'image de sortie" msgid "Pixel size in X direction" msgstr "Taille du pixel selon X" msgid "Pixel size in Y direction" msgstr "Taille du pixel selon Y" msgid "Output image width in pixels" msgstr "Largeur de l'image de sortie en pixels" msgid "Output image height in pixels" msgstr "Hauteur de l'image de sortie en pixels." msgid "Interpolation method" msgstr "Méthode d'interpolation" msgid "Fill value" msgstr "Valeur de remplissage" msgid "Value to use for points outside the input image domain. If None, uses NaN for extrapolation." msgstr "Valeur à utiliser pour les points en dehors du domaine de l'image d'origine. Si aucune valeur n'est fournie, alors NaN est utilisé pour l'extrapolation." msgid "Origin X-axis coordinate" msgstr "Abscisse de l'origine" msgid "Origin Y-axis coordinate" msgstr "Ordonnée de l'origine" msgid "Pixel size along X-axis" msgstr "Taille du pixel selon X" msgid "Pixel size along Y-axis" msgstr "Taille du pixel selon Y" msgid "Calibrate" msgstr "Étalonner" msgid "Constant term" msgstr "Terme constant" msgid "Linear term" msgstr "Terme linéaire" msgid "Quadratic term" msgstr "Terme quadratique" msgid "Cubic term" msgstr "Terme cubique" msgid "Destination data type" msgstr "Type de données de destination" msgid "Output image data type." msgstr "Type de données de l'image générée." msgid "Image statistics" msgstr "Statistiques de l'image" msgid "Footprint (disk) radius." msgstr "Rayon de l'ouverture circulaire (disque)." msgid "Cluster size (X)" msgstr "Nombre de pixels (X)" msgid "Number of adjacent pixels to be combined together along X-axis." msgstr "Nombre de pixels adjacents à regrouper le long de l'axe des X." msgid "Cluster size (Y)" msgstr "Nombre de pixels (Y)" msgid "Number of adjacent pixels to be combined together along Y-axis." msgstr "Nombre de pixels adjacents à regrouper le long de l'axe des Y." msgid "Data type" msgstr "Type de données" msgid "Change pixel size" msgstr "Modifier la taille des pixels" msgid "If checked, pixel size is updated according to binning factors. Users who prefer to work with pixel coordinates may want to uncheck this." msgstr "Si coché, la taille des pixels est mise à jour en fonction de la taille des agrégats. Les utilisateurs qui préfèrent travailler avec les coordonnées de pixels peuvent vouloir décocher cette option." msgid "Padding strategy" msgstr "Stratégie de complément de zéros" msgid "Rows to add" msgstr "Lignes à ajouter" msgid "Columns to add" msgstr "Colonnes à ajouter" msgid "Padding position" msgstr "Position du complément de zéros" msgid "Denoising weight" msgstr "Poids de débruitage" msgid "The greater weight, the more denoising (at the expense of fidelity to input)." msgstr "Plus le poids est élevé, plus le débruitage est fort (aux dépens de la fidélité des données)." msgid "Relative difference of the value of the cost function that determines the stop criterion. The algorithm stops when: (E_(n-1) - E_n) < eps * E_0" msgstr "Différence relative de la valeur de la fonction de coût qui détermine le critère d'arrêt de l'algorithme. Ce dernier s'arrête lorsque : (E_(n-1) - E_n) < eps * E_0" msgid "Max. iterations" msgstr "Nb. max. d'itérations" msgid "Maximal number of iterations used for the optimization" msgstr "Nombre maximal d'itérations utilisé pour l'optimisation" msgid "Standard deviation for range distance. A larger value results in averaging of pixels with larger spatial differences." msgstr "Ecart-type dans le domaine spatial. Une valeur élevée a pour effet de moyenner des pixels séparés par de grandes distances." msgid "Used in conjunction with mode 'constant', the value outside the image boundaries." msgstr "Valeur de remplissage en dehors des bornes de l'image (en mode constant)." msgid "Wavelet" msgstr "Ondelette" msgid "Method" msgstr "Méthode" msgid "Manual" msgstr "Manuel" msgid "Mean" msgstr "Moyenne" msgid "Minimum" msgstr "Minimum" msgid "Threshold method" msgstr "Méthode de seuillage" msgid "Threshold value" msgstr "Valeur de seuil" msgid "Greater than" msgstr "Supérieur à" msgid "Less than" msgstr "Inférieur à" msgid "Pulse features" msgstr "Caractéristiques" msgid "Signal shape" msgstr "Forme du signal" msgid "Auto" msgstr "Auto" msgid "Signal type: auto-detect, step, or square." msgstr "Type de signal : auto-détection, échelon ou carré." msgid "Start baseline min" msgstr "X min. de la ligne de base de départ" msgid "Lower X boundary for the start baseline" msgstr "Borne X inférieure pour la ligne de base de départ" msgid "Start baseline max" msgstr "X max. de la ligne de base de départ" msgid "Upper X boundary for the start baseline" msgstr "Borne X supérieure pour la ligne de base de départ" msgid "End baseline min" msgstr "X min. de la ligne de base de fin" msgid "Lower X boundary for the end baseline" msgstr "Borne X inférieure pour la ligne de base de fin" msgid "End baseline max" msgstr "X max. de la ligne de base de fin" msgid "Upper X boundary for the end baseline" msgstr "Borne X supérieure pour la ligne de base de fin" msgid "Rise/Fall time" msgstr "Temps de montée/descente" msgid "5% - 95% (High precision)" msgstr "5% - 95% (haute précision)" msgid "10% - 90% (IEEE standard)" msgstr "10% - 90% (norme IEEE)" msgid "20% - 80% (Noisy signals)" msgstr "20% - 80% (signaux bruités)" msgid "25% - 75% (Alternative)" msgstr "25% - 75% (alternative)" #, python-format msgid "Reference levels for rise/fall time measurement. 10%-90% is the IEEE standard for digital signal analysis." msgstr "Niveaux de référence pour la mesure du temps de montée/descente. 10%-90% est la norme IEEE pour l'analyse des signaux numériques." msgid "Sampling rate and period" msgstr "Taux d'échantillonnage et période" msgid "Contrast" msgstr "Contraste" msgid "X at min/max" msgstr "X à min/max" msgid "Peak detection" msgstr "Détection de pics" msgid "Minimum distance" msgstr "Distance minimale" msgid "FWHM" msgstr "FWHM" msgid "Methods and trade-offs:

• Zero-crossing: Fast, sensitive to noise
• Gaussian fit: Good for symmetric peaks, assumes Gaussian shape
• Lorentzian fit: Suitable for peaks with long tails, dominated by collisional or lifetime broadening
• Voigt fit: Most accurate for spectroscopic data, or laser lines broadened by both Doppler and collisional effects
" msgstr "Méthodes et compromis :

• Passage par zéro : Rapide, sensible au bruit
• Ajustement gaussien : Bon pour les pics symétriques, suppose une forme gaussienne
• Ajustement lorentzien : Adapté aux pics avec de longues queues, dominés par un élargissement collisionnel ou de durée de vie
• Ajustement Voigt : Le plus précis pour les données spectroscopiques, ou les raies laser élargies à la fois par des effets Doppler et collisionnels
" msgid "Zero-crossing" msgstr "Passage par zéro" msgid "Gaussian fit" msgstr "Ajustement gaussien" msgid "Lorentzian fit" msgstr "Ajustement lorentzien" msgid "Voigt fit" msgstr "Ajustement Voigt" msgid "Lower X boundary (empty for no limit, i.e. start of the signal)" msgstr "Borne X inférieure (vide pour aucune limite, c'est-à-dire le début du signal)" msgid "Upper X boundary (empty for no limit, i.e. end of the signal)" msgstr "Borne X supérieure (vide pour aucune limite, c'est-à-dire la fin du signal)" msgid "Signal statistics" msgstr "Statistiques du signal" msgid "Dynamic parameters" msgstr "Paramètres dynamiques" msgid "Full scale" msgstr "Pleine échelle" msgid "Unit for SINAD" msgstr "Unité pour SINAD" msgid "Number of harmonics" msgstr "Nombre d'harmoniques" msgid "Number of harmonics to consider for THD" msgstr "Nombre d'harmoniques à considérer pour le THD" msgid "Filter" msgstr "Filtre" msgid "Filter method" msgstr "Méthode de filtrage" msgid "Filter order" msgstr "Ordre du filtre" msgid "Low cutoff frequency" msgstr "Fréquence de coupure basse" msgid "High cutoff frequency" msgstr "Fréquence de coupure haute" msgid "Passband ripple" msgstr "Ondulation de la bande passante" msgid "Stopband attenuation" msgstr "Atténuation de la bande d'arrêt" msgid "Zero padding" msgstr "Complément de zéros" msgid "Minimum FFT points number" msgstr "Nombre minimum de points FFT" msgid "Cutoff frequency" msgstr "Fréquence de coupure" msgid "Polynomial fit" msgstr "Ajustement polynomial" msgid "Degree" msgstr "Degré" msgid "Strategy" msgstr "Stratégie" msgid "Location" msgstr "Emplacement" msgid "Where to add the padding" msgstr "Où ajouter le complément de zéros" msgid "Number of points to add" msgstr "Nombre de points à ajouter" msgid "Convert data type" msgstr "Convertir le type de données" msgid "Power" msgstr "Puissance" msgid "Angle" msgstr "Angle" msgid "x" msgstr "x" msgid "y" msgstr "y" msgid "Interpolation" msgstr "Interpolation" msgid "Value to use for points outside the interpolation domain (used only with linear, cubic and pchip methods)." msgstr "Valeur à utiliser pour les points en dehors du domaine d'interpolation (utilisé uniquement avec les méthodes linéaire, cubique et pchip)." msgid "Xmin" msgstr "Xmin" msgid "Xmax" msgstr "Xmax" msgid "Calibration" msgstr "Étalonnage" msgid "Detrending" msgstr "Élimination de tendance" msgid "Detrending method" msgstr "Méthode d'élimination de tendance" msgid "Windowing" msgstr "Fenêtrage" msgid "Shape parameter of the Tukey windowing function" msgstr "Paramètre de forme de la fonction de fenêtrage de Tukey" msgid "Shape parameter of the Kaiser windowing function" msgstr "Paramètre de forme de la fonction de fenêtrage de Kaiser" msgid "Shape parameter of the Gaussian windowing function" msgstr "Paramètre de forme de la fonction de fenêtrage gaussienne" msgid "Allan variance" msgstr "Variance d'Allan" msgid "Image with peaks" msgstr "Image avec pics" msgid "Size" msgstr "Taille" msgid "Number of peaks to generate" msgstr "Nombre de pics à générer" msgid "Sigma of the 2D Gaussian" msgstr "Sigma de la gaussienne 2D" msgid "Amplitude of the 2D Gaussian" msgstr "Amplitude de la gaussienne 2D" msgid "Mean of the Gaussian distribution" msgstr "Moyenne de la distribution gaussienne" msgid "Standard deviation of the Gaussian distribution" msgstr "Ecart-type de la distribution gaussienne" msgid "Attenuation" msgstr "Atténuation" msgid "Ring image" msgstr "Image en anneau" msgid "Intensity" msgstr "Intensité" msgid "Xcenter" msgstr "Xcentre" msgid "Ycenter" msgstr "Ycentre" msgid "Thickness" msgstr "Epaisseur" msgid "Grid of Gaussian images" msgstr "Grille d'images gaussiennes" msgid "Number of rows" msgstr "Nombre de lignes" msgid "Number of columns" msgstr "Nombre de colonnes" msgid "Centroid" msgstr "Barycentre" Sigima-1.1.1/sigima/objects/000077500000000000000000000000001514013333200156205ustar00rootroot00000000000000Sigima-1.1.1/sigima/objects/__init__.py000066400000000000000000000170611514013333200177360ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Model classes for signals and images (:mod:`sigima.objects`) ------------------------------------------------------------ The :mod:`sigima.objects` module aims at providing all the necessary classes and functions to create and manipulate Sigima scalar, signal and image objects. Those classes and functions are defined in submodules: - :mod:`sigima.objects.base` - :mod:`sigima.objects.scalar` - :mod:`sigima.objects.image` - :mod:`sigima.objects.signal` .. code-block:: python # Full import statement from sigima.objects.scalar import GeometryResult, TableResult from sigima.objects.signal import SignalObj from sigima.objects.image import ImageObj # Short import statement from sigima.objects import SignalObj, ImageObj, GeometryResult, TableResult In Sigima, computation functions take signal or image objects as input and produce signal, image or scalar objects as output. Scalar objects are represented by the `GeometryResult` and `TableResult` classes. .. note:: The scalar results are not rigorously scalar as they can also represent vector of coordinates for example, but the name 'scalar' is retained for simplicity and by opposition to the more general 'signal' and 'image' terms). Scalar results ^^^^^^^^^^^^^^ .. autoclass:: sigima.objects.GeometryResult .. autoclass:: sigima.objects.TableResult Common features of signals and images ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ .. autoclass:: sigima.objects.TypeObj .. autoclass:: sigima.objects.TypeROI .. autoclass:: sigima.objects.TypeROIParam .. autoclass:: sigima.objects.TypeSingleROI .. autodataset:: sigima.objects.NormalDistributionParam .. autodataset:: sigima.objects.PoissonDistributionParam .. autodataset:: sigima.objects.UniformDistributionParam Signals ^^^^^^^ .. autodataset:: sigima.objects.SignalObj :members: :inherited-members: .. autofunction:: sigima.objects.create_signal_roi .. autofunction:: sigima.objects.create_signal .. autofunction:: sigima.objects.create_signal_parameters .. autofunction:: sigima.objects.create_signal_from_param .. autoclass:: sigima.objects.SignalTypes .. autoclass:: sigima.objects.NewSignalParam .. autodataset:: sigima.objects.ZeroParam .. autodataset:: sigima.objects.UniformDistribution1DParam .. autodataset:: sigima.objects.NormalDistribution1DParam .. autodataset:: sigima.objects.PoissonDistribution1DParam .. autodataset:: sigima.objects.GaussParam .. autodataset:: sigima.objects.LorentzParam .. autodataset:: sigima.objects.VoigtParam .. autodataset:: sigima.objects.SineParam .. autodataset:: sigima.objects.CosineParam .. autodataset:: sigima.objects.SawtoothParam .. autodataset:: sigima.objects.TriangleParam .. autodataset:: sigima.objects.SquareParam .. autodataset:: sigima.objects.SincParam .. autodataset:: sigima.objects.StepParam .. autodataset:: sigima.objects.ExponentialParam .. autodataset:: sigima.objects.PulseParam .. autodataset:: sigima.objects.PolyParam .. autodataset:: sigima.objects.CustomSignalParam .. autodataset:: sigima.objects.ROI1DParam .. autoclass:: sigima.objects.SignalROI Images ^^^^^^ .. autodataset:: sigima.objects.ImageObj :members: :inherited-members: .. autofunction:: sigima.objects.create_image_roi .. autofunction:: sigima.objects.create_image .. autofunction:: sigima.objects.create_image_parameters .. autofunction:: sigima.objects.create_image_from_param .. autoclass:: sigima.objects.ImageTypes .. autoclass:: sigima.objects.NewImageParam .. autodataset:: sigima.objects.Zero2DParam .. autodataset:: sigima.objects.UniformDistribution2DParam .. autodataset:: sigima.objects.NormalDistribution2DParam .. autodataset:: sigima.objects.PoissonDistribution2DParam .. autodataset:: sigima.objects.Gauss2DParam .. autodataset:: sigima.objects.Ramp2DParam .. autodataset:: sigima.objects.Checkerboard2DParam .. autodataset:: sigima.objects.SinusoidalGrating2DParam .. autodataset:: sigima.objects.Ring2DParam .. autodataset:: sigima.objects.SiemensStar2DParam .. autodataset:: sigima.objects.Sinc2DParam .. autodataset:: sigima.objects.ROI2DParam .. autoclass:: sigima.objects.ImageROI .. autoclass:: sigima.objects.ImageDatatypes """ __all__ = [ "NO_ROI", "Checkerboard2DParam", "CircularROI", "CosineParam", "CustomSignalParam", "ExponentialParam", "Gauss2DParam", "GaussParam", "GeometryResult", "ImageDatatypes", "ImageObj", "ImageROI", "ImageTypes", "KindShape", "LinearChirpParam", "LogisticParam", "LorentzParam", "NewImageParam", "NewSignalParam", "NormalDistribution1DParam", "NormalDistribution2DParam", "NormalDistributionParam", "PlanckParam", "PoissonDistribution1DParam", "PoissonDistribution2DParam", "PoissonDistributionParam", "PolyParam", "PolygonalROI", "PulseParam", "ROI1DParam", "ROI2DParam", "Ramp2DParam", "RectangularROI", "Ring2DParam", "SawtoothParam", "SegmentROI", "SiemensStar2DParam", "SignalObj", "SignalROI", "SignalTypes", "Sinc2DParam", "SincParam", "SineParam", "SinusoidalGrating2DParam", "SquareParam", "SquarePulseParam", "StepParam", "StepPulseParam", "TableKind", "TableResult", "TableResultBuilder", "TriangleParam", "TypeObj", "TypeROI", "TypeROIParam", "TypeSingleROI", "UniformDistribution1DParam", "UniformDistribution2DParam", "UniformDistributionParam", "VoigtParam", "Zero2DParam", "ZeroParam", "calc_table_from_data", "concat_geometries", "concat_tables", "create_image", "create_image_from_param", "create_image_parameters", "create_image_roi", "create_image_roi_around_points", "create_signal", "create_signal_from_param", "create_signal_parameters", "create_signal_roi", "filter_geometry_by_roi", "filter_table_by_roi", ] from sigima.objects.base import ( NormalDistributionParam, PoissonDistributionParam, TypeObj, TypeROI, TypeROIParam, TypeSingleROI, UniformDistributionParam, ) from sigima.objects.image import ( Checkerboard2DParam, CircularROI, Gauss2DParam, ImageDatatypes, ImageObj, ImageROI, ImageTypes, NewImageParam, NormalDistribution2DParam, PoissonDistribution2DParam, PolygonalROI, Ramp2DParam, RectangularROI, Ring2DParam, ROI2DParam, SiemensStar2DParam, Sinc2DParam, SinusoidalGrating2DParam, UniformDistribution2DParam, Zero2DParam, create_image, create_image_from_param, create_image_parameters, create_image_roi, create_image_roi_around_points, ) from sigima.objects.scalar import ( NO_ROI, GeometryResult, KindShape, TableKind, TableResult, TableResultBuilder, calc_table_from_data, concat_geometries, concat_tables, filter_geometry_by_roi, filter_table_by_roi, ) from sigima.objects.signal import ( CosineParam, CustomSignalParam, ExponentialParam, GaussParam, LinearChirpParam, LogisticParam, LorentzParam, NewSignalParam, NormalDistribution1DParam, PlanckParam, PoissonDistribution1DParam, PolyParam, PulseParam, ROI1DParam, SawtoothParam, SegmentROI, SignalObj, SignalROI, SignalTypes, SincParam, SineParam, SquareParam, SquarePulseParam, StepParam, StepPulseParam, TriangleParam, UniformDistribution1DParam, VoigtParam, ZeroParam, create_signal, create_signal_from_param, create_signal_parameters, create_signal_roi, ) Sigima-1.1.1/sigima/objects/base.py000066400000000000000000001106321514013333200171070ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Base model classes for signals and images. """ # pylint: disable=invalid-name # Allows short reference names like x, y, ... from __future__ import annotations import abc import json import re import sys from collections.abc import Generator from copy import deepcopy from typing import Any, Generic, Iterator, Type, TypeVar import guidata.dataset as gds import numpy as np from numpy import ma from sigima.config import _ if sys.version_info >= (3, 11): # Use Self from typing module in Python 3.11+ from typing import Self else: # Use Self from typing_extensions module in Python < 3.11 from typing_extensions import Self # CSS styling for HTML tables in Jupyter notebooks HTML_TABLE_CSS = """ """ ROI_KEY = "_roi_" def deepcopy_metadata( metadata: dict[str, Any], special_keys: set[str] | None = None, all_metadata: bool = False, ) -> dict[str, Any]: """Deepcopy metadata, except keys starting with "_" (private keys) with the exception of "_roi_" and "_ann_" keys. Args: metadata: Metadata dictionary to deepcopy. special_keys: Set of keys that should not be removed even if they start with "_". all_metadata: if True, copy all metadata, including private keys Returns: A new dictionary with deepcopied metadata, excluding private keys except those in `special_keys`. """ if special_keys is None: special_keys = set([ROI_KEY]) mdcopy = {} for key, value in metadata.items(): if not key.startswith("_") or key in special_keys or all_metadata: mdcopy[key] = deepcopy(value) return mdcopy class BaseProcParam(gds.DataSet): """Base class for processing parameters.""" def apply_integer_range(self, vmin, vmax): # pylint: disable=unused-argument """Do something in case of integer min-max range.""" def apply_float_range(self, vmin, vmax): # pylint: disable=unused-argument """Do something in case of float min-max range.""" def set_from_datatype(self, dtype): """Set min/max range from NumPy datatype.""" if np.issubdtype(dtype, np.integer): info = np.iinfo(dtype) self.apply_integer_range(info.min, info.max) else: info = np.finfo(dtype) self.apply_float_range(info.min, info.max) class BaseRandomParam(BaseProcParam): """Random signal/image parameters.""" seed = gds.IntItem(_("Seed"), default=1) class UniformDistributionParam(BaseRandomParam): """Uniform-distribution signal/image parameters.""" def apply_integer_range(self, vmin, vmax): """Do something in case of integer min-max range.""" self.vmin, self.vmax = float(vmin), float(vmax) vmin = gds.FloatItem( "Vmin", default=-0.5, help=_("Uniform distribution lower bound") ) vmax = gds.FloatItem( "Vmax", default=0.5, help=_("Uniform distribution higher bound") ).set_pos(col=1) def generate_title(self) -> str: """Generate a title based on current parameters.""" return f"UniformRandom(vmin={self.vmin:g},vmax={self.vmax:g},seed={self.seed})" class NormalDistributionParam(BaseRandomParam): """Normal-distribution signal/image parameters.""" DEFAULT_RELATIVE_MU = 0.1 DEFAULT_RELATIVE_SIGMA = 0.02 def apply_integer_range(self, vmin, vmax): """Do something in case of integer min-max range.""" delta = vmax - vmin self.mu = float(vmin + self.DEFAULT_RELATIVE_MU * delta) self.sigma = float(self.DEFAULT_RELATIVE_SIGMA * delta) mu = gds.FloatItem( "μ", default=DEFAULT_RELATIVE_MU, help=_("Normal distribution mean") ) sigma = gds.FloatItem( "σ", default=DEFAULT_RELATIVE_SIGMA, min=0.0, help=_("Normal distribution standard deviation"), ).set_pos(col=1) def generate_title(self) -> str: """Generate a title based on current parameters.""" return f"NormalRandom(μ={self.mu:g},σ={self.sigma:g},seed={self.seed})" class PoissonDistributionParam(BaseRandomParam): """Base Poisson-distribution signal/image parameters.""" DEFAULT_RELATIVE_LAMBDA = 0.1 def apply_integer_range(self, vmin, vmax): """Adjust default λ based on integer min-max range.""" positive_span = max(0.0, float(vmax) - max(0.0, float(vmin))) self.lam = float(max(self.DEFAULT_RELATIVE_LAMBDA * positive_span, 1.0)) lam = gds.FloatItem( "λ", default=DEFAULT_RELATIVE_LAMBDA, min=0.0, help=_("Poisson distribution mean"), ) def generate_title(self) -> str: """Generate a title based on current parameters.""" return f"PoissonRandom(λ={self.lam:g},seed={self.seed})" TypeObj = TypeVar("TypeObj", bound="BaseObj") TypeROIParam = TypeVar("TypeROIParam", bound="BaseROIParam") TypeSingleROI = TypeVar("TypeSingleROI", bound="BaseSingleROI") TypeROI = TypeVar("TypeROI", bound="BaseROI") class BaseObjMeta(abc.ABCMeta, gds.DataSetMeta): """Mixed metaclass to avoid conflicts""" class NoDefaultOption: """Marker class for metadata option without default value""" class BaseObj(Generic[TypeROI], metaclass=BaseObjMeta): """Object (signal/image) interface""" #: Class attribute that defines a string prefix used to uniquely identify instances #: of this class in metadata serialization. Each subclass should override this with #: a unique identifier (e.g., "s" for signals, "i" for images). #: This prefix is used as part of the key for storing and retrieving object-specific #: metadata, supporting type-based serialization and deserialization. PREFIX = "" # This is overriden in children classes # This is overriden in children classes with a gds.DictItem instance: metadata: dict[str, Any] = {} annotations: str = "" #: Class attribute that defines a tuple of valid NumPy data types supported by this #: class. This is used to validate the data type of the object when it is set or #: modified and to ensure that the object can handle the data correctly. #: Subclasses should override this with a specific set of valid data types. VALID_DTYPES = (np.float64,) # To be overriden in children classes def __init__(self): self.__roi_changed: bool | None = None self._maskdata_cache: np.ndarray | None = None self.__metadata_options_defaults: dict[str, Any] = {} self.__roi_cache: TypeROI | None = None @staticmethod @abc.abstractmethod def get_roi_class() -> Type[TypeROI]: """Return ROI class""" @property @abc.abstractmethod def data(self) -> np.ndarray | None: """Data""" @classmethod def get_valid_dtypenames(cls) -> list[str]: """Get valid data type names Returns: Valid data type names supported by this class """ return [ dtname for dtname in np.sctypeDict if isinstance(dtname, str) and dtname in (dtype.__name__ for dtype in cls.VALID_DTYPES) ] def check_data(self): """Check if data is valid, raise an exception if that's not the case Raises: TypeError: if data type is not supported """ if self.data is not None: if self.data.dtype not in self.VALID_DTYPES: raise TypeError(f"Unsupported data type: {self.data.dtype}") def iterate_roi_indices(self) -> Generator[int | None, None, None]: """Iterate over object ROI indices (if there is no ROI, yield None)""" if self.roi is None: yield None else: yield from range(len(self.roi)) @abc.abstractmethod def get_data(self, roi_index: int | None = None) -> np.ndarray: """ Return original data (if ROI is not defined or `roi_index` is None), or ROI data (if both ROI and `roi_index` are defined). Args: roi_index: ROI index Returns: Data """ @abc.abstractmethod def copy( self, title: str | None = None, dtype: np.dtype | None = None, all_metadata: bool = False, ) -> Self: """Copy object. Args: title: title dtype: data type all_metadata: if True, copy all metadata, otherwise only basic metadata Returns: Copied object """ @abc.abstractmethod def set_data_type(self, dtype): """Change data type. Args: dtype: data type """ @abc.abstractmethod def physical_to_indices(self, coords: list[float]) -> list[int]: """Convert coordinates from physical (real world) to indices Args: coords: coordinates Returns: Indices """ @abc.abstractmethod def indices_to_physical(self, indices: list[int]) -> list[float]: """Convert coordinates from indices to physical (real world) Args: indices: indices Returns: Coordinates """ def __roi_has_changed(self) -> bool: """Return True if ROI has changed since last call to this method. The first call to this method will return True if ROI has not yet been set, or if ROI has been set and has changed since the last call to this method. The next call to this method will always return False if ROI has not changed in the meantime. Returns: True if ROI has changed """ if self.__roi_changed is None: self.__roi_changed = True returned_value = self.__roi_changed self.__roi_changed = False return returned_value @property def roi(self) -> TypeROI | None: """Return object regions of interest object. Returns: Regions of interest object """ # If we have a cached ROI, return it if self.__roi_cache is not None: return self.__roi_cache # Otherwise, try to load from metadata roidata = self.metadata.get(ROI_KEY) if roidata is None: return None if not isinstance(roidata, dict): # Old or unsupported format: remove it self.metadata.pop(ROI_KEY) return None # Create ROI from metadata and cache it self.__roi_cache = self.get_roi_class().from_dict(roidata) return self.__roi_cache @roi.setter def roi(self, roi: TypeROI | None) -> None: """Set object regions of interest. Args: roi: regions of interest object """ # Cache the ROI object self.__roi_cache = roi # Update metadata if roi is None: if ROI_KEY in self.metadata: self.metadata.pop(ROI_KEY) else: self.metadata[ROI_KEY] = roi.to_dict() self.__roi_changed = True @property def maskdata(self) -> np.ndarray | None: """Return masked data (areas outside defined regions of interest) Returns: Masked data """ roi_changed = self.__roi_has_changed() if self.roi is None: if roi_changed: self._maskdata_cache = None elif roi_changed or self._maskdata_cache is None: self._maskdata_cache = self.roi.to_mask(self) return self._maskdata_cache def get_masked_view(self) -> ma.MaskedArray: """Return masked view for data Returns: Masked view """ assert isinstance(self.data, np.ndarray) view = self.data.view(ma.MaskedArray) if self.maskdata is None: view.mask = np.isnan(self.data) else: view.mask = self.maskdata | np.isnan(self.data) return view def invalidate_maskdata_cache(self) -> None: """Invalidate mask data cache: force to rebuild it""" self._maskdata_cache = None def invalidate_roi_cache(self) -> None: """Invalidate ROI cache: force to reload it from metadata""" self.__roi_cache = None # Also invalidate mask data cache since ROI data might have changed self.invalidate_maskdata_cache() def sync_roi_to_metadata(self) -> None: """Synchronize the current ROI cache to metadata. This should be called after modifying the ROI object directly to ensure the changes are persisted in metadata. """ if self.__roi_cache is not None: self.metadata[ROI_KEY] = self.__roi_cache.to_dict() self.__roi_changed = True # Also invalidate mask data cache since ROI has changed self.invalidate_maskdata_cache() def mark_roi_as_changed(self) -> None: """Mark the ROI as changed and invalidate dependent caches. This should be called after modifying the ROI object directly to ensure all dependent data (like mask cache) is properly invalidated. """ self.__roi_changed = True self.invalidate_maskdata_cache() # Optionally sync to metadata immediately self.sync_roi_to_metadata() def update_metadata_from(self, other_metadata: dict[str, Any]) -> None: """Update metadata from another object's metadata (merge result shapes and annotations, and update the rest of the metadata). Args: other_metadata: other object metadata """ self.metadata.update(other_metadata) # Invalidate ROI cache since metadata might have changed ROI data self.invalidate_roi_cache() # Method to set the default values of metadata options: def set_metadata_options_defaults( self, defaults: dict[str, Any], overwrite: bool = False ) -> None: """Set default values for metadata options A metadata option is a metadata entry starting with a double underscore. It is a way to store application-specific options in object metadata. .. note:: This will not overwrite existing metadata options (unless `overwrite` is True). It will only set the default values for options that are not already set.* Use `reset_metadata_to_defaults` method to reset all metadata options to their default values. Args: defaults: dictionary of default values for metadata options overwrite: whether to overwrite existing metadata options (default: False) """ self.__metadata_options_defaults.update(defaults) for key, value in defaults.items(): self.set_metadata_option(key, value, overwrite) def get_metadata_options_defaults(self) -> dict[str, Any]: """Return default values for metadata options A metadata option is a metadata entry starting with a double underscore. It is a way to store application-specific options in object metadata. Returns: Dictionary of default values for metadata options """ return self.__metadata_options_defaults def get_metadata_option(self, name: str, default: Any = NoDefaultOption) -> Any: """Return metadata option value A metadata option is a metadata entry starting with a double underscore. It is a way to store application-specific options in object metadata. Args: name: option name default: default value if option is not set (optional) Returns: Option value Raises: ValueError: if option name is invalid """ if ( default is not NoDefaultOption and name not in self.__metadata_options_defaults ): # If default is provided, store it in defaults # and set it as the option value self.__metadata_options_defaults[name] = default self.set_metadata_option(name, default, overwrite=False) try: value = self.metadata[f"__{name}"] except KeyError as exc: defaults = self.get_metadata_options_defaults() if name in defaults: value = defaults[name] else: raise ValueError( f"Invalid metadata option name `{name}` " f"(valid names: {', '.join(defaults.keys())})" ) from exc return value def set_metadata_option( self, name: str, value: Any, overwrite: bool = True ) -> None: """Set metadata option value A metadata option is a metadata entry starting with a double underscore. It is a way to store application-specific options in object metadata. Args: name: option name value: option value overwrite: whether to overwrite existing metadata options (default: True) Raises: ValueError: if option name is invalid """ if overwrite or f"__{name}" not in self.metadata: self.metadata[f"__{name}"] = value def get_metadata_options(self) -> dict[str, Any]: """Return metadata options A metadata option is a metadata entry starting with a double underscore. Returns: Dictionary of metadata options (name: value) """ options = {} for name, value in self.metadata.items(): if name.startswith("__"): options[name[2:]] = value return options def reset_metadata_to_defaults(self) -> None: """Reset metadata to default values""" self.metadata = {} self.invalidate_roi_cache() defaults = self.get_metadata_options_defaults() for name, value in defaults.items(): self.set_metadata_option(name, value) def save_attr_to_metadata(self, attrname: str, new_value: Any) -> None: """Save attribute to metadata Args: attrname: attribute name new_value: new value """ value = getattr(self, attrname) if value: self.metadata[f"orig_{attrname}"] = value setattr(self, attrname, new_value) def restore_attr_from_metadata(self, attrname: str, default: Any) -> None: """Restore attribute from metadata Args: attrname: attribute name default: default value """ value = self.metadata.pop(f"orig_{attrname}", default) setattr(self, attrname, value) # ------Annotation management methods def get_annotations(self) -> list[dict[str, Any]]: """Get annotations as a list of dictionaries. Returns: List of annotation dictionaries. Each dict contains application-specific annotation data. Returns empty list if no annotations exist. Notes: The annotation format is defined by the application layer. Sigima only provides storage and basic validation (valid JSON structure). Example: >>> obj.set_annotations([ ... {"type": "label", "x": 10, "y": 20, "text": "Peak"}, ... {"type": "rectangle", "x0": 0, "y0": 0, "x1": 100, "y1": 100} ... ]) >>> annotations = obj.get_annotations() >>> len(annotations) 2 """ if not self.annotations: return [] try: data = json.loads(self.annotations) if isinstance(data, dict) and "annotations" in data: return data["annotations"] return [] except (json.JSONDecodeError, TypeError): # Invalid JSON - return empty list return [] def set_annotations(self, annotations: list[dict[str, Any]]) -> None: """Set annotations from a list of dictionaries. Args: annotations: List of annotation dictionaries Raises: TypeError: If annotations is not a list ValueError: If annotation items are not JSON-serializable Notes: Each annotation dictionary should be JSON-serializable. The internal storage format includes a version field for future migration. Example: >>> obj.set_annotations([{"type": "label", "text": "Test"}]) """ if not isinstance(annotations, list): raise TypeError(f"Annotations must be a list, got {type(annotations)}") # Validate JSON serializability try: # Store with version for future-proofing data = {"version": "1.0", "annotations": annotations} self.annotations = json.dumps(data, indent=2) except (TypeError, ValueError) as exc: raise ValueError(f"Annotations must be JSON-serializable: {exc}") from exc def add_annotation(self, annotation: dict[str, Any]) -> None: """Add a single annotation. Args: annotation: Annotation dictionary to add Example: >>> obj.add_annotation({"type": "circle", "x": 50, "y": 50, "r": 10}) """ current = self.get_annotations() current.append(annotation) self.set_annotations(current) def clear_annotations(self) -> None: """Remove all annotations. Example: >>> obj.clear_annotations() >>> obj.get_annotations() [] """ self.annotations = "" def has_annotations(self) -> bool: """Check if object has any annotations. Returns: True if annotations exist, False otherwise Example: >>> obj.has_annotations() False >>> obj.add_annotation({"type": "label"}) >>> obj.has_annotations() True """ return bool(self.get_annotations()) class BaseROIParamMeta(abc.ABCMeta, gds.DataSetMeta): """Mixed metaclass to avoid conflicts""" class BaseROIParam( gds.DataSet, Generic[TypeObj, TypeSingleROI], # type: ignore metaclass=BaseROIParamMeta, ): """Base class for ROI parameters""" @abc.abstractmethod def to_single_roi(self, obj: TypeObj) -> TypeSingleROI: """Convert parameters to single ROI Args: obj: object (signal/image) Returns: Single ROI """ class BaseSingleROI(Generic[TypeObj, TypeROIParam], abc.ABC): # type: ignore """Base class for single ROI Args: coords: ROI edge (physical or pixel coordinates) indices: if True, coords are indices (pixels) instead of physical coordinates title: ROI title """ def __init__( self, coords: np.ndarray | list[int] | list[float], indices: bool, title: str = "ROI", ) -> None: self.coords = np.array(coords, int if indices else float) self.indices = indices self.title = title self.check_coords() def __eq__(self, other: BaseSingleROI | None) -> bool: """Test equality with another single ROI""" if other is None: return False if not isinstance(other, BaseSingleROI): raise TypeError(f"Cannot compare {type(self)} with {type(other)}") return ( np.array_equal(self.coords, other.coords) and self.indices == other.indices ) def get_physical_coords(self, obj: TypeObj) -> list[float]: """Return physical coords Args: obj: object (signal/image) Returns: Physical coords """ if self.indices: return obj.indices_to_physical(self.coords.tolist()) return self.coords.tolist() def set_physical_coords(self, obj: TypeObj, coords: np.ndarray) -> None: """Set physical coords Args: obj: object (signal/image) coords: physical coords """ if self.indices: self.coords = np.array(obj.physical_to_indices(coords.tolist())) else: self.coords = np.array(coords, float) def get_indices_coords(self, obj: TypeObj) -> list[int]: """Return indices coords Args: obj: object (signal/image) Returns: Indices coords """ if self.indices: return self.coords.tolist() return obj.physical_to_indices(self.coords.tolist()) def set_indices_coords(self, obj: TypeObj, coords: np.ndarray) -> None: """Set indices coords Args: obj: object (signal/image) coords: indices coords """ if self.indices: self.coords = coords else: self.coords = np.array(obj.indices_to_physical(coords.tolist())) @abc.abstractmethod def check_coords(self) -> None: """Check if coords are valid Raises: ValueError: invalid coords """ @abc.abstractmethod def to_mask(self, obj: TypeObj) -> np.ndarray: """Create mask from ROI Args: obj: signal or image object Returns: Mask (boolean array where True values are inside the ROI) """ @abc.abstractmethod def to_param(self, obj: TypeObj, index: int) -> TypeROIParam: """Convert ROI to parameters Args: obj: object (signal/image), for physical-indices coordinates conversion index: ROI index """ def to_dict(self) -> dict: """Convert ROI to dictionary Returns: Dictionary """ return { "coords": self.coords, "indices": self.indices, "title": self.title, "type": type(self).__name__, } @classmethod def from_dict(cls: Type[TypeSingleROI], dictdata: dict) -> TypeSingleROI: """Convert dictionary to ROI Args: dictdata: dictionary Returns: ROI """ return cls(dictdata["coords"], dictdata["indices"], dictdata["title"]) def get_coords_html_rows(self) -> list[tuple[str, str]]: """Return HTML table rows describing the ROI coordinates. Override this method in subclasses to provide more detailed coordinate descriptions (e.g., "Center", "Radius" for circular ROIs). Returns: List of (label, value) tuples for HTML table rows. """ coord_type = "indices" if self.indices else "physical" coords_str = ", ".join(f"{c:.4g}" for c in self.coords) return [(f"Coordinates ({coord_type})", f"[{coords_str}]")] def get_coords_summary(self) -> str: """Return a short summary of the ROI coordinates for table display. Override this method in subclasses to provide a more meaningful summary. Returns: Short string summarizing the ROI coordinates. """ coords_str = ", ".join(f"{c:.4g}" for c in self.coords) return f"[{coords_str}]" def _repr_html_(self) -> str: """Return HTML representation for Jupyter notebook display. This method is automatically called by Jupyter when displaying the object as a cell output, providing a rich HTML rendering of the ROI. Returns: HTML representation of the ROI with coordinates. """ roi_type = type(self).__name__ html = f'{roi_type}:' if self.title: html += f" {self.title}" html += '' for label, value in self.get_coords_html_rows(): html += ( f"" f"" ) html += "
{label}:{value}
" return html class BaseROI(Generic[TypeObj, TypeSingleROI, TypeROIParam], abc.ABC): # type: ignore """Abstract base class for ROIs (Regions of Interest) Args: inverse: if True, ROI is outside the region of interest """ #: Class attribute that defines a string prefix used for identifying ROI types #: in object metadata. This prefix is used when serializing and deserializing ROIs, #: allowing the system to determine the appropriate ROI class for reconstruction. #: Each ROI subclass should override this with a unique string identifier. PREFIX = "" # This is overriden in children classes def __init__(self) -> None: self.single_rois: list[TypeSingleROI] = [] @staticmethod @abc.abstractmethod def get_compatible_single_roi_classes() -> list[Type[BaseSingleROI]]: """Return compatible single ROI classes""" def __len__(self) -> int: """Return number of ROIs""" return len(self.single_rois) def __iter__(self) -> Iterator[TypeSingleROI]: """Iterate over single ROIs""" return iter(self.single_rois) def __eq__(self, other: BaseROI | None) -> bool: """Test equality with another ROI""" if other is None: return False if not isinstance(other, BaseROI): raise TypeError(f"Cannot compare {type(self)} with {type(other)}") return self.single_rois == other.single_rois def __getitem__(self, index: int) -> TypeSingleROI: """Return single ROI at index (subscript access) Args: index: ROI index Returns: Single ROI at index """ return self.single_rois[index] def __setitem__(self, index: int, roi: TypeSingleROI) -> None: """Set single ROI at index (subscript assignment) Args: index: ROI index roi: ROI to set """ self.single_rois[index] = roi def get_single_roi(self, index: int) -> TypeSingleROI: """Return single ROI at index Args: index: ROI index """ return self.single_rois[index] def set_single_roi(self, index: int, roi: TypeSingleROI) -> None: """Set single ROI at index Args: index: ROI index roi: ROI to set """ self.single_rois[index] = roi def get_single_roi_title(self, index: int) -> str: """Generate title for single ROI, based on its index, using either the ROI title or a default generic title as fallback. Args: index: ROI index """ single_roi = self.get_single_roi(index) title = single_roi.title or get_generic_roi_title(index) return title def is_empty(self) -> bool: """Return True if no ROI is defined""" return len(self) == 0 @classmethod def create( cls: Type[BaseROI], single_roi: TypeSingleROI ) -> BaseROI[TypeObj, TypeSingleROI, TypeROIParam]: """Create Regions of Interest object from a single ROI. Args: single_roi: single ROI Returns: Regions of Interest object """ roi = cls() roi.add_roi(single_roi) return roi def copy(self) -> BaseROI[TypeObj, TypeSingleROI, TypeROIParam]: """Return a copy of ROIs""" return deepcopy(self) def empty(self) -> None: """Empty ROIs""" self.single_rois.clear() def combine_with( self, other: BaseROI[TypeObj, TypeSingleROI, TypeROIParam] ) -> BaseROI[TypeObj, TypeSingleROI, TypeROIParam]: """Combine ROIs with another ROI object, by merging single ROIs (and ignoring duplicate single ROIs) and returning a new combined ROI object. Args: other: other ROI object Returns: Combined ROIs object """ if not isinstance(other, type(self)): raise TypeError(f"Cannot combine {type(self)} with {type(other)}") combined_roi = self.copy() for roi in other.single_rois: if all(s_roi != roi for s_roi in self.single_rois): combined_roi.single_rois.append(roi) return combined_roi def add_roi( self, roi: TypeSingleROI | BaseROI[TypeObj, TypeSingleROI, TypeROIParam] ) -> None: """Add ROI. Args: roi: ROI Raises: TypeError: if roi type is not supported (not a single ROI or a ROI) ValueError: if `inverse` values are incompatible """ if isinstance(roi, BaseSingleROI): self.single_rois.append(roi) elif isinstance(roi, BaseROI): self.single_rois.extend(roi.single_rois) else: raise TypeError(f"Unsupported ROI type: {type(roi)}") @abc.abstractmethod def to_mask(self, obj: TypeObj) -> np.ndarray: """Create mask from ROI Args: obj: signal or image object Returns: Mask (boolean array where True values are inside the ROI) """ def to_params(self, obj: TypeObj) -> list[TypeROIParam]: """Convert ROIs to a list of parameters Args: obj: object (signal/image), for physical to pixel conversion Returns: ROI parameters """ return [iroi.to_param(obj, index=idx) for idx, iroi in enumerate(self)] @classmethod def from_params( cls: Type[BaseROI], obj: TypeObj, params: list[TypeROIParam], ) -> BaseROI[TypeObj, TypeSingleROI, TypeROIParam]: """Create ROIs from parameters Args: obj: object (signal/image) params: ROI parameters Returns: ROIs """ roi = cls() for param in params: assert isinstance(param, BaseROIParam), "Invalid ROI parameter type" roi.add_roi(param.to_single_roi(obj)) return roi def _repr_html_(self) -> str: """Return HTML representation for Jupyter notebooks.""" roi_type = type(self).__name__ count = len(self.single_rois) rows = [] for idx, single_roi in enumerate(self.single_rois): title = single_roi.title or get_generic_roi_title(idx) stype = type(single_roi).__name__ coords_summary = single_roi.get_coords_summary() rows.append( f"{idx}{title}{stype}" f"{coords_summary}" ) table_rows = ( "\n".join(rows) if rows else "No ROIs" ) html = f""" {HTML_TABLE_CSS}

{roi_type}
{table_rows}
IndexTitleTypeCoordinates
{count} ROI(s)
""" return html def to_dict(self) -> dict: """Convert ROIs to dictionary Returns: Dictionary """ return { "single_rois": [roi.to_dict() for roi in self.single_rois], } @classmethod def from_dict(cls: Type[TypeROI], dictdata: dict) -> TypeROI: """Convert dictionary to ROIs Args: dictdata: dictionary Returns: ROIs """ instance = cls() if not all(key in dictdata for key in ["single_rois"]): raise ValueError("Invalid ROI: dictionary must contain 'single_rois' key") instance.single_rois = [] for single_roi in dictdata["single_rois"]: for single_roi_class in instance.get_compatible_single_roi_classes(): if single_roi["type"] == single_roi_class.__name__: instance.single_rois.append(single_roi_class.from_dict(single_roi)) break else: raise ValueError(f"Unsupported single ROI type: {single_roi['type']}") return instance GENERIC_ROI_TITLE_REGEXP = r"ROI(\d+)" def get_generic_roi_title(index: int) -> None: """Return a generic title for the ROI""" title = f"ROI{index:02d}" assert re.match(GENERIC_ROI_TITLE_REGEXP, title) return title Sigima-1.1.1/sigima/objects/image/000077500000000000000000000000001514013333200167025ustar00rootroot00000000000000Sigima-1.1.1/sigima/objects/image/__init__.py000066400000000000000000000046671514013333200210300ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Image objects subpackage ======================== This subpackage provides image data structures and utilities. The subpackage is organized into the following modules: - `roi`: Region of Interest (ROI) classes and parameters - `object`: Main ImageObj class for handling 2D image data - `creation`: Image creation utilities and parameter classes All classes and functions are re-exported at the subpackage level for backward compatibility. Existing imports like `from sigima.objects.image import ImageObj` will continue to work. """ # Import all public classes and functions from submodules from .creation import ( # Constants DEFAULT_TITLE, Checkerboard2DParam, Gauss2DParam, # Enums ImageDatatypes, ImageTypes, # Base parameter classes NewImageParam, NormalDistribution2DParam, PoissonDistribution2DParam, Ramp2DParam, Ring2DParam, SiemensStar2DParam, Sinc2DParam, SinusoidalGrating2DParam, UniformDistribution2DParam, # Specific parameter classes Zero2DParam, check_all_image_parameters_classes, # Factory and utility functions create_image, create_image_from_param, create_image_parameters, get_next_image_number, # Registration functions register_image_parameters_class, ) from .object import ( ImageObj, ) from .roi import ( # ROI classes BaseSingleImageROI, CircularROI, # Specific ROI types ImageROI, PolygonalROI, RectangularROI, ROI2DParam, # ROI utility function create_image_roi, create_image_roi_around_points, ) # Define __all__ for explicit public API __all__ = [ "DEFAULT_TITLE", "BaseSingleImageROI", "Checkerboard2DParam", "CircularROI", "Gauss2DParam", "ImageDatatypes", "ImageObj", "ImageROI", "ImageTypes", "NewImageParam", "NormalDistribution2DParam", "PoissonDistribution2DParam", "PolygonalROI", "ROI2DParam", "Ramp2DParam", "RectangularROI", "Ring2DParam", "SiemensStar2DParam", "Sinc2DParam", "SinusoidalGrating2DParam", "UniformDistribution2DParam", "Zero2DParam", "check_all_image_parameters_classes", "create_image", "create_image_from_param", "create_image_parameters", "create_image_roi", "create_image_roi_around_points", "get_next_image_number", "register_image_parameters_class", ] Sigima-1.1.1/sigima/objects/image/creation.py000066400000000000000000000715541514013333200210740ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Image creation utilities ======================== This module provides functions and parameter classes for creating new images. The module includes: - `create_image`: Factory function for creating ImageObj instances - `ImageDatatypes`: Enumeration of supported image data types - `ImageTypes`: Enumeration of supported image generation types - `NewImageParam` and subclasses: Parameter classes for image generation - Factory functions and registration utilities These utilities support creating images from various sources: - Raw NumPy arrays - Synthetic data (zeros, random distributions, analytical functions) - Parameterized image generation """ # pylint: disable=invalid-name # Allows short reference names like x, y, ... # pylint: disable=duplicate-code from __future__ import annotations from typing import Type import guidata.dataset as gds import numpy as np from sigima.config import _ from sigima.objects import base from sigima.objects.image.object import ImageObj from sigima.tools.image import scale_data_to_min_max def create_image( title: str, data: np.ndarray | None = None, metadata: dict | None = None, units: tuple | None = None, labels: tuple | None = None, ) -> ImageObj: """Create a new Image object Args: title: image title data: image data metadata: image metadata units: X, Y, Z units (tuple of strings) labels: X, Y, Z labels (tuple of strings) Returns: Image object """ assert isinstance(title, str) assert data is None or isinstance(data, np.ndarray) image = ImageObj(title=title) image.title = title image.data = data if units is not None: image.xunit, image.yunit, image.zunit = units if labels is not None: image.xlabel, image.ylabel, image.zlabel = labels if metadata is not None: image.metadata.update(metadata) return image class ImageDatatypes(gds.LabeledEnum): """Image data types""" @classmethod def from_numpy_dtype(cls: type[ImageDatatypes], dtype: np.dtype) -> ImageDatatypes: """Return ImageDatatypes member from NumPy dtype Args: dtype: NumPy dtype object Returns: Corresponding ImageDatatypes member """ dtype_str = str(dtype) for member in cls: if member.value == dtype_str: return member return cls.UINT8 # Default fallback def to_numpy_dtype(self) -> np.dtype: """Return the corresponding NumPy dtype object. This is the symmetrical counterpart to from_numpy_dtype(). Returns: NumPy dtype object that can be used directly with numpy functions. """ return np.dtype(self.value) @classmethod def check(cls: type[ImageDatatypes]) -> None: """Check if data types are valid""" for member in cls: assert hasattr(np, member.value) #: Unsigned integer number stored with 8 bits UINT8 = "uint8" #: Unsigned integer number stored with 16 bits UINT16 = "uint16" #: Signed integer number stored with 16 bits INT16 = "int16" #: Float number stored with 32 bits FLOAT32 = "float32" #: Float number stored with 64 bits FLOAT64 = "float64" ImageDatatypes.check() class ImageTypes(gds.LabeledEnum): """Image types.""" #: Image filled with zero ZEROS = "zero", _("Zero") #: Image filled with random data (normal distribution) NORMAL_DISTRIBUTION = "normal_distribution", _("Normal distribution") #: Image filled with random data (Poisson distribution) POISSON_DISTRIBUTION = "poisson_distribution", _("Poisson distribution") #: Image filled with random data (uniform distribution) UNIFORM_DISTRIBUTION = "uniform_distribution", _("Uniform distribution") #: 2D Gaussian image GAUSS = "gauss", _("Gaussian") #: Bilinear form image RAMP = "ramp", _("2D ramp") #: Checkerboard pattern CHECKERBOARD = "checkerboard", _("Checkerboard") #: Sinusoidal grating pattern SINUSOIDAL_GRATING = "sinusoidal_grating", _("Sinusoidal grating") #: Ring/circular pattern RING = "ring", _("Ring pattern") #: Siemens star pattern SIEMENS_STAR = "siemens_star", _("Siemens star") #: 2D sinc function SINC = "sinc", _("2D sinc") DEFAULT_TITLE = _("Untitled image") class NewImageParam(gds.DataSet): """New image dataset. Subclasses can optionally implement a ``generate_title()`` method to provide automatic title generation based on their parameters. This method should return a string containing the generated title, or an empty string if no title can be generated. Example:: def generate_title(self) -> str: '''Generate a title based on current parameters.''' return f"MyImage(param1={self.param1},param2={self.param2})" """ hide_height = False hide_width = False hide_dtype = False hide_type = False title = gds.StringItem(_("Title"), default=DEFAULT_TITLE) height = gds.IntItem( _("Height"), default=1024, help=_("Image height: number of rows"), min=1 ).set_prop("display", hide=gds.GetAttrProp("hide_height")) width = gds.IntItem( _("Width"), default=1024, help=_("Image width: number of columns"), min=1 ).set_prop("display", col=1, hide=gds.GetAttrProp("hide_width")) dtype = gds.ChoiceItem( _("Type"), ImageDatatypes, default=ImageDatatypes.FLOAT64, help=_("Image data type"), ).set_prop("display", hide=gds.GetAttrProp("hide_dtype")) xlabel = gds.StringItem(_("X label"), default="") xunit = gds.StringItem(_("X unit"), default="").set_prop("display", col=1) ylabel = gds.StringItem(_("Y label"), default="") yunit = gds.StringItem(_("Y unit"), default="").set_prop("display", col=1) zlabel = gds.StringItem(_("Z label"), default="") zunit = gds.StringItem(_("Z unit"), default="").set_prop("display", col=1) def generate_2d_data(self, shape: tuple[int, int]) -> np.ndarray: """Generate 2D data based on current parameters. Args: shape: Tuple (height, width) for the output array. Returns: 2D data array """ return np.zeros(shape, dtype=self.dtype.to_numpy_dtype()) IMAGE_TYPE_PARAM_CLASSES = {} def register_image_parameters_class(itype: ImageTypes, param_class) -> None: """Register a parameters class for a given image type. Args: itype: image type param_class: parameters class """ IMAGE_TYPE_PARAM_CLASSES[itype] = param_class def __get_image_parameters_class(itype: ImageTypes) -> Type[NewImageParam]: """Get parameters class for a given image type. Args: itype: image type Returns: Parameters class Raises: ValueError: if no parameters class is registered for the given image type """ try: return IMAGE_TYPE_PARAM_CLASSES[itype] except KeyError as exc: raise ValueError( f"Image type {itype} has no parameters class registered" ) from exc def check_all_image_parameters_classes() -> None: """Check all registered parameters classes.""" for itype, param_class in IMAGE_TYPE_PARAM_CLASSES.items(): assert __get_image_parameters_class(itype) is param_class def create_image_parameters( itype: ImageTypes, title: str | None = None, height: int | None = None, width: int | None = None, idtype: ImageDatatypes | None = None, xlabel: str | None = None, ylabel: str | None = None, zlabel: str | None = None, xunit: str | None = None, yunit: str | None = None, zunit: str | None = None, **kwargs: dict, ) -> NewImageParam: """Create parameters for a given image type. Args: itype: image type title: image title height: image height (number of rows) width: image width (number of columns) idtype: image data type (`ImageDatatypes` member) xlabel: X axis label ylabel: Y axis label zlabel: Z axis label xunit: X axis unit yunit: Y axis unit zunit: Z axis unit **kwargs: additional parameters (specific to the image type) Returns: Parameters object for the given image type """ pclass = __get_image_parameters_class(itype) p = pclass.create(**kwargs) if title is not None: p.title = title if height is not None: p.height = height if width is not None: p.width = width if idtype is not None: assert isinstance(idtype, ImageDatatypes) p.dtype = idtype if xlabel is not None: p.xlabel = xlabel if ylabel is not None: p.ylabel = ylabel if zlabel is not None: p.zlabel = zlabel if xunit is not None: p.xunit = xunit if yunit is not None: p.yunit = yunit if zunit is not None: p.zunit = zunit return p class Zero2DParam(NewImageParam, title=_("Zero")): """Image parameters for a 2D image filled with zero.""" def generate_2d_data(self, shape: tuple[int, int]) -> np.ndarray: """Generate 2D data based on current parameters. Args: shape: Tuple (height, width) for the output array. Returns: 2D data array """ return np.zeros(shape, dtype=self.dtype.to_numpy_dtype()) register_image_parameters_class(ImageTypes.ZEROS, Zero2DParam) class UniformDistribution2DParam( NewImageParam, base.UniformDistributionParam, title=_("Uniform distribution") ): """Uniform-distribution image parameters.""" def generate_2d_data(self, shape: tuple[int, int]) -> np.ndarray: """Generate 2D data based on current parameters. Args: shape: Tuple (height, width) for the output array. Returns: 2D data array """ rng = np.random.default_rng(self.seed) assert self.vmin is not None assert self.vmax is not None data = scale_data_to_min_max(rng.random(shape), self.vmin, self.vmax) return data.astype(self.dtype.to_numpy_dtype()) register_image_parameters_class( ImageTypes.UNIFORM_DISTRIBUTION, UniformDistribution2DParam ) class NormalDistribution2DParam( NewImageParam, base.NormalDistributionParam, title=_("Normal distribution") ): """Normal-distribution image parameters.""" def generate_2d_data(self, shape: tuple[int, int]) -> np.ndarray: """Generate 2D data based on current parameters. Args: shape: Tuple (height, width) for the output array. Returns: 2D data array. """ rng = np.random.default_rng(self.seed) assert self.mu is not None assert self.sigma is not None data: np.ndarray = rng.normal(self.mu, self.sigma, shape) return data.astype(self.dtype.to_numpy_dtype()) register_image_parameters_class( ImageTypes.NORMAL_DISTRIBUTION, NormalDistribution2DParam ) class PoissonDistribution2DParam( NewImageParam, base.PoissonDistributionParam, title=_("Poisson distribution") ): """Poisson-distribution image parameters.""" def generate_2d_data(self, shape: tuple[int, int]) -> np.ndarray: """Generate 2D data based on current parameters. Args: shape: Tuple (height, width) for the output array. Returns: 2D data array. """ rng = np.random.default_rng(self.seed) assert self.lam is not None data: np.ndarray = rng.poisson(lam=self.lam, size=shape) return data.astype(self.dtype.to_numpy_dtype()) register_image_parameters_class( ImageTypes.POISSON_DISTRIBUTION, PoissonDistribution2DParam ) class Gauss2DParam( NewImageParam, title=_("Gaussian"), comment="z = A exp(-((√((x - x0)2 + " "(y - y0)2) - μ)2) / (2 σ2))", ): """2D Gaussian parameters.""" a = gds.FloatItem("A", default=None, check=False) xmin = gds.FloatItem("xmin", default=-10.0).set_pos(col=1) sigma = gds.FloatItem("σ", default=1.0) xmax = gds.FloatItem("xmax", default=10.0).set_pos(col=1) mu = gds.FloatItem("μ", default=0.0) ymin = gds.FloatItem("ymin", default=-10.0).set_pos(col=1) x0 = gds.FloatItem("x0", default=0.0) ymax = gds.FloatItem("ymax", default=10.0).set_pos(col=1) y0 = gds.FloatItem("y0", default=0.0).set_pos(col=0, colspan=1) def generate_title(self) -> str: """Generate a title based on current parameters.""" return ( f"Gauss(a={self.a:g},μ={self.mu:g}," f"σ={self.sigma:g}),x0={self.x0:g},y0={self.y0:g})" ) def generate_2d_data(self, shape: tuple[int, int]) -> np.ndarray: """Generate 2D data based on current parameters. Args: shape: Tuple (height, width) for the output array. Returns: 2D data array """ if self.a is None: try: self.a = np.iinfo(self.dtype.to_numpy_dtype()).max / 2.0 except ValueError: self.a = 10.0 x, y = np.meshgrid( np.linspace(self.xmin, self.xmax, shape[1]), np.linspace(self.ymin, self.ymax, shape[0]), ) data = self.a * np.exp( -((np.sqrt((x - self.x0) ** 2 + (y - self.y0) ** 2) - self.mu) ** 2) / (2.0 * self.sigma**2) ) return np.array(data, dtype=self.dtype.to_numpy_dtype()) register_image_parameters_class(ImageTypes.GAUSS, Gauss2DParam) class Ramp2DParam( NewImageParam, title=_("2D ramp"), comment="z = A (x - x0) + B (y - y0) + C", ): """Define the parameters of a 2D ramp (planar ramp).""" _g0_begin = gds.BeginGroup(_("Coefficients")) a = gds.FloatItem("A", default=1.0).set_pos(col=0) b = gds.FloatItem("B", default=1.0).set_pos(col=1) c = gds.FloatItem("C", default=0.0).set_pos(colspan=1) x0 = gds.FloatItem("x0", default=0.0).set_pos(col=0) y0 = gds.FloatItem("y0", default=0.0).set_pos(col=1) _g0_end = gds.EndGroup("") _g1_begin = gds.BeginGroup(_("Domain")) xmin = gds.FloatItem("xmin", default=-1.0).set_pos(col=0) xmax = gds.FloatItem("xmax", default=1.0).set_pos(col=1) ymin = gds.FloatItem("ymin", default=-1.0).set_pos(col=0) ymax = gds.FloatItem("ymax", default=1.0).set_pos(col=1) _g1_end = gds.EndGroup("") def generate_title(self) -> str: """Generate a title based on current parameters.""" terms = [] # Build terms list for non-zero coefficients if self.a != 0.0: if self.x0 == 0.0: x_part = f"{self.a:g} x" else: x_part = f"{self.a:g} (x - {self.x0:g})" terms.append(x_part) if self.b != 0.0: if self.y0 == 0.0: y_part = f"{self.b:g} y" else: y_part = f"{self.b:g} (y - {self.y0:g})" terms.append(y_part) if self.c != 0.0 or not terms: # Include c if it's the only term terms.append(f"{self.c:g}") return f"z = {' + '.join(terms)}" def generate_2d_data(self, shape: tuple[int, int]) -> np.ndarray: """Generate 2D data based on current parameters. Args: shape: Tuple (height, width) for the output array. Returns: 2D data array """ x = np.linspace(self.xmin, self.xmax, shape[1]) y = np.linspace(self.ymin, self.ymax, shape[0]) xx, yy = np.meshgrid(x, y) data = self.a * (xx - self.x0) + self.b * (yy - self.y0) + self.c return np.array(data, dtype=self.dtype.to_numpy_dtype()) register_image_parameters_class(ImageTypes.RAMP, Ramp2DParam) class Checkerboard2DParam( NewImageParam, title=_("Checkerboard"), comment=_("Checkerboard pattern with alternating squares"), ): """Checkerboard pattern parameters.""" square_size = gds.IntItem( _("Square size"), default=64, min=1, help=_("Size of each square in pixels") ) x0 = gds.FloatItem("x0", default=0.0, help=_("X offset")) y0 = gds.FloatItem("y0", default=0.0, help=_("Y offset")).set_pos(col=1) vmin = gds.FloatItem( _("Minimum value"), default=0.0, help=_("Value for dark squares") ) vmax = gds.FloatItem( _("Maximum value"), default=255.0, help=_("Value for light squares") ).set_pos(col=1) def generate_title(self) -> str: """Generate a title based on current parameters.""" return f"Checkerboard(size={self.square_size})" def generate_2d_data(self, shape: tuple[int, int]) -> np.ndarray: """Generate 2D data based on current parameters. Args: shape: Tuple (height, width) for the output array. Returns: 2D data array """ # Create coordinate arrays y = np.arange(shape[0]) - self.y0 x = np.arange(shape[1]) - self.x0 xx, yy = np.meshgrid(x, y) # Create checkerboard pattern using floor division pattern = ((xx // self.square_size) + (yy // self.square_size)) % 2 # Scale to desired range data = np.where(pattern == 0, self.vmin, self.vmax) return data.astype(self.dtype.to_numpy_dtype()) register_image_parameters_class(ImageTypes.CHECKERBOARD, Checkerboard2DParam) class SinusoidalGrating2DParam( NewImageParam, title=_("Sinusoidal grating"), comment="z = A sin(2π(fx·x + fy·y) + φ) + C", ): """Sinusoidal grating parameters.""" _g0_begin = gds.BeginGroup(_("Amplitude and offset")) a = gds.FloatItem("A", default=100.0, help=_("Amplitude")).set_pos(col=0) c = gds.FloatItem("C", default=128.0, help=_("DC offset")).set_pos(col=1) _g0_end = gds.EndGroup("") _g1_begin = gds.BeginGroup(_("Frequency and phase")) fx = gds.FloatItem( "fx", default=0.1, help=_("Spatial frequency in X direction") ).set_pos(col=0) fy = gds.FloatItem( "fy", default=0.0, help=_("Spatial frequency in Y direction") ).set_pos(col=1) phase = gds.FloatItem("φ", default=0.0, help=_("Phase"), unit="rad").set_pos( colspan=1 ) _g1_end = gds.EndGroup("") _g2_begin = gds.BeginGroup(_("Domain")) xmin = gds.FloatItem("xmin", default=0.0).set_pos(col=0) xmax = gds.FloatItem("xmax", default=100.0).set_pos(col=1) ymin = gds.FloatItem("ymin", default=0.0).set_pos(col=0) ymax = gds.FloatItem("ymax", default=100.0).set_pos(col=1) _g2_end = gds.EndGroup("") def generate_title(self) -> str: """Generate a title based on current parameters.""" return f"Grating(fx={self.fx:g},fy={self.fy:g},φ={self.phase:g})" def generate_2d_data(self, shape: tuple[int, int]) -> np.ndarray: """Generate 2D data based on current parameters. Args: shape: Tuple (height, width) for the output array. Returns: 2D data array """ x = np.linspace(self.xmin, self.xmax, shape[1]) y = np.linspace(self.ymin, self.ymax, shape[0]) xx, yy = np.meshgrid(x, y) data = self.a * np.sin(2 * np.pi * (self.fx * xx + self.fy * yy) + self.phase) data = data + self.c return data.astype(self.dtype.to_numpy_dtype()) register_image_parameters_class(ImageTypes.SINUSOIDAL_GRATING, SinusoidalGrating2DParam) class Ring2DParam( NewImageParam, title=_("Ring pattern"), comment=_("Concentric ring pattern"), ): """Ring pattern parameters.""" x0 = gds.FloatItem("x0", default=0.0, help=_("Center X coordinate")) y0 = gds.FloatItem( "y0", default=0.0, help=_("Center Y coordinate") ).set_pos(col=1) _g0_begin = gds.BeginGroup(_("Ring parameters")) period = gds.FloatItem( _("Period"), default=50.0, min=0.1, help=_("Distance between ring centers") ) ring_width = gds.FloatItem( _("Ring width"), default=10.0, min=0.1, help=_("Width of each ring") ).set_pos(col=1) _g0_end = gds.EndGroup("") _g1_begin = gds.BeginGroup(_("Amplitude")) vmin = gds.FloatItem(_("Minimum value"), default=0.0) vmax = gds.FloatItem(_("Maximum value"), default=255.0).set_pos(col=1) _g1_end = gds.EndGroup("") _g2_begin = gds.BeginGroup(_("Domain")) xmin = gds.FloatItem("xmin", default=-100.0).set_pos(col=0) xmax = gds.FloatItem("xmax", default=100.0).set_pos(col=1) ymin = gds.FloatItem("ymin", default=-100.0).set_pos(col=0) ymax = gds.FloatItem("ymax", default=100.0).set_pos(col=1) _g2_end = gds.EndGroup("") def generate_title(self) -> str: """Generate a title based on current parameters.""" return f"Ring(period={self.period:g},width={self.ring_width:g})" def generate_2d_data(self, shape: tuple[int, int]) -> np.ndarray: """Generate 2D data based on current parameters. Args: shape: Tuple (height, width) for the output array. Returns: 2D data array """ x = np.linspace(self.xmin, self.xmax, shape[1]) y = np.linspace(self.ymin, self.ymax, shape[0]) xx, yy = np.meshgrid(x, y) # Calculate distance from center r = np.sqrt((xx - self.x0) ** 2 + (yy - self.y0) ** 2) # Create ring pattern: modulo creates repeating pattern ring_phase = (r % self.period) / self.period # Create rings: value is high when ring_phase is within the ring width ring_width_fraction = self.ring_width / self.period rings = np.where(ring_phase < ring_width_fraction, 1.0, 0.0) # Scale to desired range data = self.vmin + rings * (self.vmax - self.vmin) return data.astype(self.dtype.to_numpy_dtype()) register_image_parameters_class(ImageTypes.RING, Ring2DParam) class SiemensStar2DParam( NewImageParam, title=_("Siemens star"), comment=_("Siemens star pattern for resolution testing"), ): """Siemens star pattern parameters.""" x0 = gds.FloatItem("x0", default=0.0, help=_("Center X coordinate")) y0 = gds.FloatItem( "y0", default=0.0, help=_("Center Y coordinate") ).set_pos(col=1) n_spokes = gds.IntItem( _("Number of spokes"), default=36, min=2, help=_("Number of spoke pairs") ) _g0_begin = gds.BeginGroup(_("Radial limits")) inner_radius = gds.FloatItem( _("Inner radius"), default=0.0, min=0.0, help=_("Inner radius (hole in center)") ) outer_radius = gds.FloatItem( _("Outer radius"), default=100.0, min=0.1, help=_("Outer radius (edge of pattern)"), ).set_pos(col=1) _g0_end = gds.EndGroup("") _g1_begin = gds.BeginGroup(_("Amplitude")) vmin = gds.FloatItem(_("Minimum value"), default=0.0) vmax = gds.FloatItem(_("Maximum value"), default=255.0).set_pos(col=1) _g1_end = gds.EndGroup("") _g2_begin = gds.BeginGroup(_("Domain")) xmin = gds.FloatItem("xmin", default=-100.0).set_pos(col=0) xmax = gds.FloatItem("xmax", default=100.0).set_pos(col=1) ymin = gds.FloatItem("ymin", default=-100.0).set_pos(col=0) ymax = gds.FloatItem("ymax", default=100.0).set_pos(col=1) _g2_end = gds.EndGroup("") def generate_title(self) -> str: """Generate a title based on current parameters.""" return f"Siemens(n={self.n_spokes})" def generate_2d_data(self, shape: tuple[int, int]) -> np.ndarray: """Generate 2D data based on current parameters. Args: shape: Tuple (height, width) for the output array. Returns: 2D data array """ x = np.linspace(self.xmin, self.xmax, shape[1]) y = np.linspace(self.ymin, self.ymax, shape[0]) xx, yy = np.meshgrid(x, y) # Calculate polar coordinates r = np.sqrt((xx - self.x0) ** 2 + (yy - self.y0) ** 2) theta = np.arctan2(yy - self.y0, xx - self.x0) # Create spoke pattern: alternating black and white spokes # Normalize angle to [0, 2π] and create pattern theta_normalized = (theta + np.pi) / (2 * np.pi) # Now in [0, 1] spoke_pattern = np.floor(theta_normalized * self.n_spokes * 2) % 2 # Apply radial mask radial_mask = (r >= self.inner_radius) & (r <= self.outer_radius) # Combine pattern with mask data = np.where(radial_mask, spoke_pattern, 0.5) # 0.5 for outside region # Scale to desired range data = self.vmin + data * (self.vmax - self.vmin) return data.astype(self.dtype.to_numpy_dtype()) register_image_parameters_class(ImageTypes.SIEMENS_STAR, SiemensStar2DParam) class Sinc2DParam( NewImageParam, title=_("2D sinc"), comment="z = A sinc(√((x - x0)2 + " "(y - y0)2) / σ) + C", ): """2D sinc function parameters.""" _g0_begin = gds.BeginGroup(_("Amplitude and offset")) a = gds.FloatItem("A", default=100.0, help=_("Amplitude")).set_pos(col=0) c = gds.FloatItem("C", default=0.0, help=_("DC offset")).set_pos(col=1) _g0_end = gds.EndGroup("") _g1_begin = gds.BeginGroup(_("Center and scale")) x0 = gds.FloatItem("x0", default=0.0, help=_("Center X coordinate")) y0 = gds.FloatItem( "y0", default=0.0, help=_("Center Y coordinate") ).set_pos(col=1) sigma = gds.FloatItem("σ", default=10.0, min=0.1, help=_("Scale factor")).set_pos( colspan=1 ) _g1_end = gds.EndGroup("") _g2_begin = gds.BeginGroup(_("Domain")) xmin = gds.FloatItem("xmin", default=-50.0).set_pos(col=0) xmax = gds.FloatItem("xmax", default=50.0).set_pos(col=1) ymin = gds.FloatItem("ymin", default=-50.0).set_pos(col=0) ymax = gds.FloatItem("ymax", default=50.0).set_pos(col=1) _g2_end = gds.EndGroup("") def generate_title(self) -> str: """Generate a title based on current parameters.""" return f"Sinc(σ={self.sigma:g},x0={self.x0:g},y0={self.y0:g})" def generate_2d_data(self, shape: tuple[int, int]) -> np.ndarray: """Generate 2D data based on current parameters. Args: shape: Tuple (height, width) for the output array. Returns: 2D data array """ x = np.linspace(self.xmin, self.xmax, shape[1]) y = np.linspace(self.ymin, self.ymax, shape[0]) xx, yy = np.meshgrid(x, y) # Calculate radial distance from center r = np.sqrt((xx - self.x0) ** 2 + (yy - self.y0) ** 2) # Calculate sinc function: sinc(x) = sin(x)/x, with special case for x=0 # Scale by sigma r_scaled = r / self.sigma # Use numpy's sinc which is defined as sin(pi*x)/(pi*x) # We want sin(x)/x, so we divide by pi data = np.where(r_scaled == 0, 1.0, np.sin(r_scaled) / r_scaled) # Apply amplitude and offset data = self.a * data + self.c return data.astype(self.dtype.to_numpy_dtype()) register_image_parameters_class(ImageTypes.SINC, Sinc2DParam) check_all_image_parameters_classes() IMG_NB = 0 def get_next_image_number(): """Get the next image number. This function is used to keep track of the number of signals created. It is typically used to generate unique titles for new signals. Returns: int: new image number """ global IMG_NB # pylint: disable=global-statement IMG_NB += 1 return IMG_NB def create_image_from_param(param: NewImageParam) -> ImageObj: """Create a new Image object from parameters. Args: param: new image parameters Returns: Image object Raises: NotImplementedError: if the image type is not supported """ if param.height is None: param.height = 1024 if param.width is None: param.width = 1024 if param.dtype is None: param.dtype = ImageDatatypes.UINT16 # Generate data first, as some `generate_title()` methods may depend on it: shape = (param.height, param.width) data = param.generate_2d_data(shape) # Check if user has customized the title or left it as default/empty use_generated_title = not param.title or param.title == DEFAULT_TITLE if use_generated_title: # Try to generate a descriptive title gen_title = getattr(param, "generate_title", lambda: "")() if gen_title: title = gen_title else: # No generated title available, use default with number title = f"{DEFAULT_TITLE} {get_next_image_number()}" else: # User has set a custom title, use it as-is title = param.title image = create_image( title, data, units=(param.xunit, param.yunit, param.zunit), labels=(param.xlabel, param.ylabel, param.zlabel), ) return image Sigima-1.1.1/sigima/objects/image/object.py000066400000000000000000000570131514013333200205300ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Image object definition ======================= This module defines the main `ImageObj` class for representing 2D image data. The `ImageObj` class provides: - Data storage for 2D arrays with associated metadata - Physical coordinate system with origin and pixel spacing - Axis labeling and units - Scale management (linear/logarithmic) - DICOM template support - ROI (Region of Interest) integration - Coordinate conversion utilities (physical ↔ pixel) This is the core class for image processing operations in Sigima. """ # pylint: disable=invalid-name # Allows short reference names like x, y, ... # pylint: disable=duplicate-code from __future__ import annotations import re from collections.abc import Mapping from typing import Any, Literal, Type import guidata.dataset as gds import numpy as np from numpy import ma from sigima.config import _ from sigima.objects import base from sigima.objects.image.roi import ImageROI from sigima.tools.datatypes import clip_astype def to_builtin(obj) -> str | int | float | list | dict | np.ndarray | None: """Convert an object implementing a numeric value or collection into the corresponding builtin/NumPy type. Return None if conversion fails.""" try: return int(obj) if int(obj) == float(obj) else float(obj) except (TypeError, ValueError): pass if isinstance(obj, str): return obj if hasattr(obj, "__iter__"): try: return list(obj) except (TypeError, ValueError): pass if hasattr(obj, "__dict__"): try: return dict(obj.__dict__) except (TypeError, ValueError): pass if isinstance(obj, np.ndarray): return obj return None class ImageObj(gds.DataSet, base.BaseObj[ImageROI]): """Image object""" PREFIX = "i" VALID_DTYPES = ( np.uint8, np.uint16, np.int16, np.int32, np.float32, np.float64, np.complex128, ) def __init__(self, title=None, comment=None, icon=""): """Constructor Args: title: title comment: comment icon: icon """ gds.DataSet.__init__(self, title, comment, icon) base.BaseObj.__init__(self) self._dicom_template = None @staticmethod def get_roi_class() -> Type[ImageROI]: """Return ROI class""" # Import here to avoid circular imports return ImageROI def __add_metadata(self, key: str, value: Any) -> None: """Add value to metadata if value can be converted into builtin/NumPy type Args: key: key value: value """ stored_val = to_builtin(value) if stored_val is not None: self.metadata[key] = stored_val def __set_metadata_from(self, obj: Mapping | dict) -> None: """Set metadata from object: dict-like (only string keys are considered) or any other object (iterating over supported attributes) Args: obj: object """ self.reset_metadata_to_defaults() ptn = r"__[\S_]*__$" if isinstance(obj, Mapping): for key, value in obj.items(): if isinstance(key, str) and not re.match(ptn, key): self.__add_metadata(key, value) else: for attrname in dir(obj): if attrname != "GroupLength" and not re.match(ptn, attrname): try: attr = getattr(obj, attrname) if not callable(attr) and attr: self.__add_metadata(attrname, attr) except AttributeError: pass @property def dicom_template(self): """Get DICOM template""" return self._dicom_template @dicom_template.setter def dicom_template(self, template): """Set DICOM template""" if template is not None: ipp = getattr(template, "ImagePositionPatient", None) x0, y0 = 0.0, 0.0 if ipp is None else (float(ipp[0]), float(ipp[1])) pxs = getattr(template, "PixelSpacing", None) dx, dy = 1.0, 1.0 if pxs is None else (float(pxs[0]), float(pxs[1])) self.set_uniform_coords(dx, dy, x0, y0) self.__set_metadata_from(template) self._dicom_template = template _tabs = gds.BeginTabGroup("all") _datag = gds.BeginGroup(_("Data")) data = gds.FloatArrayItem(_("Data")) # type: ignore[assignment] metadata = gds.DictItem(_("Metadata"), default={}) # type: ignore[assignment] annotations = gds.StringItem(_("Annotations"), default="").set_prop( "display", hide=True, ) # Annotations (JSON). Use get/set_annotations() API # type: ignore[assignment] _e_datag = gds.EndGroup(_("Data")) def _compute_xmin(self) -> float: """Compute Xmin""" if self.data is None or self.data.size == 0: return 0.0 if self.is_uniform_coords: return self.x0 if self.xcoords is None or self.xcoords.size == 0: return np.nan return self.xcoords[0] def _compute_xmax(self) -> float: """Compute Xmax""" if self.data is None or self.data.size == 0: return 0.0 if self.is_uniform_coords: return self.x0 + self.width - self.dx if self.xcoords is None or self.xcoords.size == 0: return np.nan return self.xcoords[-1] def _compute_ymin(self) -> float: """Compute Ymin""" if self.data is None or self.data.size == 0: return 0.0 if self.is_uniform_coords: return self.y0 if self.ycoords is None or self.ycoords.size == 0: return np.nan return self.ycoords[0] def _compute_ymax(self) -> float: """Compute Ymax""" if self.data is None or self.data.size == 0: return 0.0 if self.is_uniform_coords: return self.y0 + self.height - self.dy if self.ycoords is None or self.ycoords.size == 0: return np.nan return self.ycoords[-1] _dxdyg = gds.BeginGroup(f"{_('Origin')} / {_('Pixel spacing')}") _prop_uniform = gds.GetAttrProp("is_uniform_coords") is_uniform_coords = gds.BoolItem(_("Uniform coordinates"), default=True).set_prop( "display", store=_prop_uniform, active=False ) _origin = gds.BeginGroup(_("Origin")) x0 = gds.FloatItem("X0", default=0.0).set_prop( "display", active=_prop_uniform ) y0 = ( gds.FloatItem("Y0", default=0.0) .set_prop("display", active=_prop_uniform) .set_pos(col=1) ) _e_origin = gds.EndGroup(_("Origin")) _pixel_spacing = gds.BeginGroup(_("Pixel spacing")) dx = gds.FloatItem("Δx", default=1.0).set_prop("display", active=_prop_uniform) dy = ( gds.FloatItem("Δy", default=1.0) .set_prop("display", active=_prop_uniform) .set_pos(col=1) ) _e_pixel_spacing = gds.EndGroup(_("Pixel spacing")) _boundaries = gds.BeginGroup(_("Extent")) xmin = gds.FloatItem("XMIN").set_computed(_compute_xmin) xmax = gds.FloatItem("XMAX").set_pos(col=1).set_computed(_compute_xmax) ymin = gds.FloatItem("YMIN").set_computed(_compute_ymin) ymax = gds.FloatItem("YMAX").set_pos(col=1).set_computed(_compute_ymax) _e_boundaries = gds.EndGroup(_("Extent")) _e_dxdyg = gds.EndGroup(f"{_('Origin')} / {_('Pixel spacing')}") _coordsg = gds.BeginGroup(_("Coordinates")) xcoords = gds.FloatArrayItem( _("X coordinates"), default=np.array([], dtype=float), ).set_prop("display", active=gds.NotProp(_prop_uniform)) # type: ignore[assignment] ycoords = ( gds.FloatArrayItem(_("Y coordinates"), default=np.array([], dtype=float)) .set_prop("display", active=gds.NotProp(_prop_uniform)) .set_pos(col=1) ) # type: ignore[assignment] _e_coordsg = gds.EndGroup(_("Coordinates")) def set_uniform_coords( self, dx: float, dy: float, x0: float = 0.0, y0: float = 0.0 ) -> None: """Set uniform coordinates and clear non-uniform arrays. Args: dx: pixel size along X-axis dy: pixel size along Y-axis x0: origin X-axis coordinate y0: origin Y-axis coordinate """ self.is_uniform_coords = True self.xcoords = np.array([], dtype=float) self.ycoords = np.array([], dtype=float) self.dx, self.dy, self.x0, self.y0 = dx, dy, x0, y0 def set_coords(self, xcoords: np.ndarray, ycoords: np.ndarray) -> None: """Set non-uniform coordinates. Args: xcoords: X coordinates ycoords: Y coordinates """ self.is_uniform_coords = False self.xcoords = xcoords self.ycoords = ycoords def switch_coords_to(self, coords_type: Literal["uniform", "non-uniform"]) -> None: """Switch coordinates to uniform or non-uniform representation. If switching to uniform, the image pixel size and origin are computed from the current non-uniform coordinates. If switching to non-uniform, the corresponding coordinate arrays are generated from the current pixel size and origin. If the current coordinates are already of the requested type, no action is performed. Args: coords_type: 'uniform' or 'non-uniform' Raises: ValueError: If switching to uniform coordinates fails due to insufficient non-uniform coordinates defined """ if coords_type == "uniform" and not self.is_uniform_coords: if self.xcoords.size >= 2 and self.ycoords.size >= 2: x0, y0 = float(self.xcoords[0]), float(self.ycoords[0]) dx = float(self.xcoords[-1] - self.xcoords[0]) / (self.xcoords.size - 1) dy = float(self.ycoords[-1] - self.ycoords[0]) / (self.ycoords.size - 1) self.set_uniform_coords(dx, dy, x0, y0) else: raise ValueError( "Cannot switch to uniform coordinates: " "not enough non-uniform coordinates defined" ) elif coords_type == "non-uniform" and self.is_uniform_coords: shape = self.data.shape xcoords = np.linspace(self.x0, self.x0 + self.dx * (shape[1] - 1), shape[1]) ycoords = np.linspace(self.y0, self.y0 + self.dy * (shape[0] - 1), shape[0]) self.set_coords(xcoords, ycoords) _unitsg = gds.BeginGroup(_("Titles / Units")) title = gds.StringItem(_("Image title"), default=_("Untitled")) _tabs_u = gds.BeginTabGroup("units") _unitsx = gds.BeginGroup(_("X-axis")) xlabel = gds.StringItem(_("Title"), default="") xunit = gds.StringItem(_("Unit"), default="") _e_unitsx = gds.EndGroup(_("X-axis")) _unitsy = gds.BeginGroup(_("Y-axis")) ylabel = gds.StringItem(_("Title"), default="") yunit = gds.StringItem(_("Unit"), default="") _e_unitsy = gds.EndGroup(_("Y-axis")) _unitsz = gds.BeginGroup(_("Z-axis")) zlabel = gds.StringItem(_("Title"), default="") zunit = gds.StringItem(_("Unit"), default="") _e_unitsz = gds.EndGroup(_("Z-axis")) _e_tabs_u = gds.EndTabGroup("units") _e_unitsg = gds.EndGroup(_("Titles / Units")) _scalesg = gds.BeginGroup(_("Scales")) _prop_autoscale = gds.GetAttrProp("autoscale") autoscale = gds.BoolItem(_("Auto scale"), default=True).set_prop( "display", store=_prop_autoscale ) _tabs_b = gds.BeginTabGroup("bounds") _boundsx = gds.BeginGroup(_("X-axis")) xscalelog = gds.BoolItem(_("Logarithmic scale"), default=False) xscalemin = gds.FloatItem(_("Lower bound"), check=False).set_prop( "display", active=gds.NotProp(_prop_autoscale) ) xscalemax = gds.FloatItem(_("Upper bound"), check=False).set_prop( "display", active=gds.NotProp(_prop_autoscale) ) _e_boundsx = gds.EndGroup(_("X-axis")) _boundsy = gds.BeginGroup(_("Y-axis")) yscalelog = gds.BoolItem(_("Logarithmic scale"), default=False) yscalemin = gds.FloatItem(_("Lower bound"), check=False).set_prop( "display", active=gds.NotProp(_prop_autoscale) ) yscalemax = gds.FloatItem(_("Upper bound"), check=False).set_prop( "display", active=gds.NotProp(_prop_autoscale) ) _e_boundsy = gds.EndGroup(_("Y-axis")) _boundsz = gds.BeginGroup(_("LUT range")) zscalemin = gds.FloatItem(_("Lower bound"), check=False) zscalemax = gds.FloatItem(_("Upper bound"), check=False) _e_boundsz = gds.EndGroup(_("LUT range")) _e_tabs_b = gds.EndTabGroup("bounds") _e_scalesg = gds.EndGroup(_("Scales")) _e_tabs = gds.EndTabGroup("all") @property def width(self) -> float: """Return image width, i.e. number of columns multiplied by pixel size""" return self.data.shape[1] * self.dx @property def height(self) -> float: """Return image height, i.e. number of rows multiplied by pixel size""" return self.data.shape[0] * self.dy @property def xc(self) -> float: """Return image center X-axis coordinate""" return self.x0 + 0.5 * self.width @property def yc(self) -> float: """Return image center Y-axis coordinate""" return self.y0 + 0.5 * self.height def _repr_html_(self) -> str: """Return HTML representation for Jupyter notebook display. This method is automatically called by Jupyter when displaying the object as a cell output, providing a rich HTML rendering of the image object. Returns: HTML representation of the image with summary statistics. """ shape = self.data.shape if self.data is not None else (0, 0) dtype_str = str(self.data.dtype) if self.data is not None else "N/A" z_min = f"{self.data.min():.4g}" if self.data is not None else "N/A" z_max = f"{self.data.max():.4g}" if self.data is not None else "N/A" # Build axis labels with optional title x_label = "X" if self.xlabel: x_label = f"X ({self.xlabel})" y_label = "Y" if self.ylabel: y_label = f"Y ({self.ylabel})" z_label = "Z" if self.zlabel: z_label = f"Z ({self.zlabel})" html = f'ImageObj: {self.title}:' html += '' html += ( f"" f"" ) html += ( f"" ) html += ( f"" f"" # Origin and pixel spacing (for uniform coordinates) if self.is_uniform_coords: html += ( f"" f"" html += ( f"" f"" else: # Non-uniform coordinates: show coordinate array info x_coords_info = "N/A" y_coords_info = "N/A" if self.xcoords is not None and self.xcoords.size > 0: x_coords_info = f"[{self.xcoords[0]:.4g}, {self.xcoords[-1]:.4g}]" if self.ycoords is not None and self.ycoords.size > 0: y_coords_info = f"[{self.ycoords[0]:.4g}, {self.ycoords[-1]:.4g}]" html += ( f"" f"" html += ( f"" f"" # Extent (physical bounds) html += ( f"" f"" html += ( f"" f"" # Physical size html += ( f"" f"" if self.roi is not None: html += ( f"" f"" ) html += "
Shape:{shape[1]} × {shape[0]} (W×H)
Data type:{dtype_str}
{z_label} range:[{z_min}, {z_max}]" ) if self.zunit: html += f" {self.zunit}" html += "
Origin ({x_label}, {y_label}):({self.x0:.4g}, {self.y0:.4g})" ) if self.xunit: html += f" {self.xunit}" html += "
Pixel spacing (Δx, Δy):({self.dx:.4g}, {self.dy:.4g})" ) if self.xunit: html += f" {self.xunit}" html += "
{x_label} coords:{x_coords_info}" ) if self.xunit: html += f" {self.xunit}" html += "
{y_label} coords:{y_coords_info}" ) if self.yunit: html += f" {self.yunit}" html += "
Extent ({x_label}):[{self._compute_xmin():.4g}, {self._compute_xmax():.4g}]" ) if self.xunit: html += f" {self.xunit}" html += "
Extent ({y_label}):[{self._compute_ymin():.4g}, {self._compute_ymax():.4g}]" ) if self.yunit: html += f" {self.yunit}" html += "
Physical size:{self.width:.4g} × {self.height:.4g}" ) if self.xunit: html += f" {self.xunit}" html += "
ROIs:{len(self.roi)}
" return html def get_data(self, roi_index: int | None = None) -> np.ndarray: """ Return original data (if ROI is not defined or `roi_index` is None), or ROI data (if both ROI and `roi_index` are defined). Args: roi_index: ROI index Returns: Masked data """ if self.roi is None or roi_index is None: view = self.data.view(ma.MaskedArray) view.mask = np.isnan(self.data) return view single_roi = self.roi.get_single_roi(roi_index) # pylint: disable=unbalanced-tuple-unpacking x0, y0, x1, y1 = self.physical_to_indices(single_roi.get_bounding_box(self)) # Clip coordinates to image boundaries to handle ROIs extending beyond canvas x0 = max(0, x0) y0 = max(0, y0) x1 = min(self.data.shape[1], x1) y1 = min(self.data.shape[0], y1) # If ROI is completely outside the image, return a fully masked array # with a single element to avoid zero-size array errors in statistics if x0 >= x1 or y0 >= y1: empty_array = ma.masked_array([[np.nan]], dtype=self.data.dtype, mask=True) return empty_array return self.get_masked_view()[y0:y1, x0:x1] def copy( self, title: str | None = None, dtype: np.dtype | None = None, all_metadata: bool = False, ) -> ImageObj: """Copy object. Args: title: title dtype: data type all_metadata: if True, copy all metadata, otherwise only basic metadata Returns: Copied object """ title = self.title if title is None else title obj = ImageObj(title=title) obj.title = title obj.xlabel = self.xlabel obj.ylabel = self.ylabel obj.zlabel = self.zlabel obj.xunit = self.xunit obj.yunit = self.yunit obj.zunit = self.zunit obj.metadata = base.deepcopy_metadata(self.metadata, all_metadata=all_metadata) obj.annotations = self.annotations if self.data is not None: obj.data = np.array(self.data, copy=True, dtype=dtype) obj.is_uniform_coords = self.is_uniform_coords if self.is_uniform_coords: obj.dx = self.dx obj.dy = self.dy obj.x0 = self.x0 obj.y0 = self.y0 else: obj.xcoords = np.array(self.xcoords, copy=True) obj.ycoords = np.array(self.ycoords, copy=True) obj.autoscale = self.autoscale obj.xscalelog = self.xscalelog obj.xscalemin = self.xscalemin obj.xscalemax = self.xscalemax obj.yscalelog = self.yscalelog obj.yscalemin = self.yscalemin obj.yscalemax = self.yscalemax obj.zscalemin = self.zscalemin obj.zscalemax = self.zscalemax obj.dicom_template = self.dicom_template return obj def set_data_type(self, dtype: np.dtype) -> None: """Change data type. If data type is integer, clip values to the new data type's range, thus avoiding overflow or underflow. Args: Data type """ self.data = clip_astype(self.data, dtype) def physical_to_indices( self, coords: list[float], clip: bool = False, as_float: bool = False ) -> list[int] | list[float]: """Convert coordinates from physical (real world) to indices (pixel) Args: coords: flat list of physical coordinates [x0, y0, x1, y1, ...] clip: if True, clip values to image boundaries as_float: if True, return float indices (i.e. without rounding) Returns: Indices Raises: ValueError: if coords does not contain an even number of elements """ if len(coords) % 2 != 0: raise ValueError( "coords must contain an even number of elements (x, y pairs)." ) indices = np.array(coords, float) if indices.size > 0: if self.is_uniform_coords: # Use existing uniform conversion indices[::2] = (indices[::2] - self.x0) / self.dx indices[1::2] = (indices[1::2] - self.y0) / self.dy else: # Use interpolation for non-uniform coordinates x_indices = np.arange(len(self.xcoords)) y_indices = np.arange(len(self.ycoords)) indices[::2] = np.interp(indices[::2], self.xcoords, x_indices) indices[1::2] = np.interp(indices[1::2], self.ycoords, y_indices) if clip: indices[::2] = np.clip(indices[::2], 0, self.data.shape[1] - 1) indices[1::2] = np.clip(indices[1::2], 0, self.data.shape[0] - 1) if as_float: return indices.tolist() return np.floor(indices + 0.5).astype(int).tolist() def indices_to_physical(self, indices: list[float]) -> list[float]: """Convert coordinates from indices to physical (real world) Args: indices: flat list of indices [x0, y0, x1, y1, ...] Returns: Coordinates Raises: ValueError: if indices does not contain an even number of elements """ if len(indices) % 2 != 0: raise ValueError( "indices must contain an even number of elements (x, y pairs)." ) coords = np.array(indices, float) if coords.size > 0: if self.is_uniform_coords: # Use existing uniform conversion coords[::2] = coords[::2] * self.dx + self.x0 coords[1::2] = coords[1::2] * self.dy + self.y0 else: # Use interpolation for non-uniform coordinates x_indices = np.arange(len(self.xcoords)) y_indices = np.arange(len(self.ycoords)) coords[::2] = np.interp(coords[::2], x_indices, self.xcoords) coords[1::2] = np.interp(coords[1::2], y_indices, self.ycoords) return coords.tolist() Sigima-1.1.1/sigima/objects/image/roi.py000066400000000000000000001071141514013333200200510ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Image ROI classes ================= This module defines ROI (Region of Interest) classes and utilities for images. The module provides: - `ROI2DParam`: Parameter class for 2D image ROIs - `BaseSingleImageROI`: Base class for single image ROIs - `RectangularROI`: Rectangular ROI implementation - `CircularROI`: Circular ROI implementation - `PolygonalROI`: Polygonal ROI implementation - `ImageROI`: Container for multiple image ROIs - `create_image_roi`: Factory function for creating image ROIs - `create_image_roi_around_points`: Function for creating image ROIs around points - Utility functions for coordinate handling These classes handle ROI definitions, parameter conversion, and mask generation for image processing operations. """ # pylint: disable=invalid-name # Allows short reference names like x, y, ... # pylint: disable=duplicate-code from __future__ import annotations import abc import re from collections.abc import ByteString, Mapping, Sequence from typing import TYPE_CHECKING, Literal, Type import guidata.dataset as gds import numpy as np from skimage import draw import sigima.enums import sigima.tools.image from sigima.config import _ from sigima.objects import base if TYPE_CHECKING: from sigima.objects.image.object import ImageObj def to_builtin(obj) -> str | int | float | list | dict | np.ndarray | None: """Convert an object implementing a numeric value or collection into the corresponding builtin/NumPy type. Return None if conversion fails.""" try: return int(obj) if int(obj) == float(obj) else float(obj) except (TypeError, ValueError): pass if isinstance(obj, ByteString): return str(obj) if isinstance(obj, Sequence): return str(obj) if len(obj) == len(str(obj)) else list(obj) if isinstance(obj, Mapping): return dict(obj) if isinstance(obj, np.ndarray): return obj return None def check_points(value: np.ndarray, raise_exception: bool = False) -> bool: """Check if value is a valid 1D array of coordinates (X, Y) pairs. Args: value: value to check raise_exception: if True, raise an exception on invalid value Returns: True if value is valid, False otherwise """ if not np.issubdtype(value.dtype, np.floating): if raise_exception: raise TypeError("Coordinates must be floats") return False if value.ndim != 1: if raise_exception: raise ValueError("Coordinates must be a 1D array") return False if len(value) % 2 != 0: if raise_exception: raise ValueError("Coordinates must contain pairs (X, Y)") return False return True class ROI2DParam(base.BaseROIParam["ImageObj", "BaseSingleImageROI"]): """Image ROI parameters""" def get_comment(self) -> str | None: """Get comment for ROI parameters""" return _( "This is a set of parameters defining a Region of Interest " "(ROI) in an image. The parameters can be used to create a ROI object " "or to extract data from an image using the ROI.

" "All values are expressed in physical coordinates (floats). " "The conversion to pixel coordinates is done by taking into account " "the image pixel size and origin.
" ) title = gds.StringItem(_("ROI title"), default="") # Note: the ROI coordinates are expressed in pixel coordinates (integers) # => That is the only way to handle ROI parametrization for image objects. # Otherwise, we would have to ask the user to systematically provide the # physical coordinates: that would be cumbersome and error-prone. _geometry_prop = gds.GetAttrProp("geometry") _rfp = gds.FuncProp(_geometry_prop, lambda x: x != "rectangle") _cfp = gds.FuncProp(_geometry_prop, lambda x: x != "circle") _pfp = gds.FuncProp(_geometry_prop, lambda x: x != "polygon") # Do not declare it as a static method: not supported by Python 3.9 def _lbl(name: str, index: int): # pylint: disable=no-self-argument """Returns nameindex""" return f"{name}{index}" geometries = ("rectangle", "circle", "polygon") geometry = gds.ChoiceItem( _("Geometry"), list(zip(geometries, geometries)), default="rectangle" ).set_prop("display", store=_geometry_prop, hide=True) # Parameters for rectangular ROI geometry: _tlcorner = gds.BeginGroup(_("Top left corner")).set_prop("display", hide=_rfp) x0 = gds.FloatItem(_lbl("X", 0), default=0).set_prop("display", hide=_rfp) y0 = ( gds.FloatItem(_lbl("Y", 0), default=0).set_pos(1).set_prop("display", hide=_rfp) ) _e_tlcorner = gds.EndGroup(_("Top left corner")) dx = gds.FloatItem("ΔX", default=0).set_prop("display", hide=_rfp) dy = gds.FloatItem("ΔY", default=0).set_pos(1).set_prop("display", hide=_rfp) # Parameters for circular ROI geometry: _cgroup = gds.BeginGroup(_("Center coordinates")).set_prop("display", hide=_cfp) xc = gds.FloatItem(_lbl("X", "C"), default=0).set_prop("display", hide=_cfp) yc = ( gds.FloatItem(_lbl("Y", "C"), default=0) .set_pos(1) .set_prop("display", hide=_cfp) ) _e_cgroup = gds.EndGroup(_("Center coordinates")) r = gds.FloatItem(_("Radius"), default=0).set_prop("display", hide=_cfp) # Parameters for polygonal ROI geometry: points = gds.FloatArrayItem(_("Coordinates"), check_callback=check_points).set_prop( "display", hide=_pfp ) # Parameter for ROI mask behavior: inverse = gds.BoolItem( _("Inverse ROI logic"), default=False, help=_( "When disabled (default), the ROI defines an area inside the shape on " "which to focus (masking data outside).\n" "When enabled, the ROI logic is inverted to focus on data outside the " "shape (masking data inside)." ), ) def to_single_roi( self, obj: ImageObj ) -> PolygonalROI | RectangularROI | CircularROI: """Convert parameters to single ROI Args: obj: image object (used for conversion of pixel to physical coordinates) Returns: Single ROI """ if self.geometry == "rectangle": return RectangularROI.from_param(obj, self) if self.geometry == "circle": return CircularROI.from_param(obj, self) if self.geometry == "polygon": return PolygonalROI.from_param(obj, self) raise ValueError(f"Unknown ROI geometry type: {self.geometry}") def get_suffix(self) -> str: """Get suffix text representation for ROI extraction""" if re.match(base.GENERIC_ROI_TITLE_REGEXP, self.title) or not self.title: if self.geometry == "rectangle": return f"x0={self.x0},y0={self.y0},dx={self.dx},dy={self.dy}" if self.geometry == "circle": return f"xc={self.xc},yc={self.yc},r={self.r}" if self.geometry == "polygon": return "polygon" raise ValueError(f"Unknown ROI geometry type: {self.geometry}") return self.title def get_extracted_roi(self, obj: ImageObj) -> ImageROI | None: """Get extracted ROI, i.e. the remaining ROI after extracting ROI from image. Args: obj: image object (used for conversion of pixel to physical coordinates) When extracting ROIs from an image to multiple images (i.e. one image per ROI), this method returns the ROI that has to be kept in the destination image. This is not necessary for a rectangular ROI: the destination image is simply a crop of the source image according to the ROI coordinates. But for a circular ROI or a polygonal ROI, the destination image is a crop of the source image according to the bounding box of the ROI. Thus, to avoid any loss of information, a ROI has to be defined for the destination image: this is the ROI returned by this method. It's simply the same as the source ROI, but with coordinates adjusted to the destination image. One may called this ROI the "extracted ROI". """ if self.geometry == "rectangle": return None single_roi = self.to_single_roi(obj) roi = ImageROI() roi.add_roi(single_roi) return roi def get_bounding_box_physical(self) -> tuple[int, int, int, int]: """Get bounding box (physical coordinates)""" if self.geometry == "circle": x0, y0 = self.xc - self.r, self.yc - self.r x1, y1 = self.xc + self.r, self.yc + self.r elif self.geometry == "rectangle": x0, y0, x1, y1 = self.x0, self.y0, self.x0 + self.dx, self.y0 + self.dy else: self.points: np.ndarray x0, y0 = self.points[::2].min(), self.points[1::2].min() x1, y1 = self.points[::2].max(), self.points[1::2].max() return x0, y0, x1, y1 def get_bounding_box_indices(self, obj: ImageObj) -> tuple[int, int, int, int]: """Get bounding box (pixel coordinates)""" x0, y0, x1, y1 = self.get_bounding_box_physical() ix0, iy0 = obj.physical_to_indices((x0, y0)) ix1, iy1 = obj.physical_to_indices((x1, y1)) return ix0, iy0, ix1, iy1 def get_data(self, obj: ImageObj) -> np.ndarray: """Get data in ROI Args: obj: image object Returns: Data in ROI """ ix0, iy0, ix1, iy1 = self.get_bounding_box_indices(obj) ix0, iy0 = max(0, ix0), max(0, iy0) ix1, iy1 = min(obj.data.shape[1], ix1), min(obj.data.shape[0], iy1) return obj.data[iy0:iy1, ix0:ix1] class BaseSingleImageROI(base.BaseSingleROI["ImageObj", ROI2DParam], abc.ABC): """Base class for single image ROI Args: coords: ROI edge coordinates (floats) indices: if True, coordinates are indices, if False, they are physical values title: ROI title inverse: inverse ROI logic (default: False) .. note:: The image ROI coords are expressed in physical coordinates (floats). The conversion to pixel coordinates is done in :class:`sigima.objects.ImageObj` (see :meth:`sigima.objects.ImageObj.physical_to_indices`). Most of the time, the physical coordinates are the same as the pixel coordinates, but this is not always the case (e.g. after image binning), so it's better to keep the physical coordinates in the ROI object: this will help reusing the ROI with different images (e.g. with different pixel sizes). """ def __init__( self, coords: np.ndarray | list[int] | list[float], indices: bool, title: str = "ROI", inverse: bool = False, ) -> None: super().__init__(coords, indices, title) self.inverse = inverse def to_dict(self) -> dict: """Convert ROI to dictionary Returns: Dictionary """ result = super().to_dict() result["inverse"] = self.inverse return result @classmethod def from_dict(cls, dictdata: dict): """Convert dictionary to ROI Args: dictdata: dictionary Returns: ROI """ # Get inverse parameter inverse = dictdata.get("inverse", False) # Default: normal ROI behavior return cls(dictdata["coords"], dictdata["indices"], dictdata["title"], inverse) @abc.abstractmethod def get_bounding_box(self, obj: ImageObj) -> tuple[float, float, float, float]: """Get bounding box (physical coordinates) Args: obj: image object """ class PolygonalROI(BaseSingleImageROI): """Polygonal ROI Args: coords: ROI edge coordinates title: title inverse: inverse ROI logic (default: False) Raises: ValueError: if number of coordinates is odd .. note:: The image ROI coords are expressed in physical coordinates (floats) """ def check_coords(self) -> None: """Check if coords are valid Raises: ValueError: invalid coords """ if len(self.coords) % 2 != 0: raise ValueError("Edge indices must be pairs of X, Y values") def get_coords_html_rows(self) -> list[tuple[str, str]]: """Return HTML table rows describing the polygon coordinates.""" n_vertices = len(self.coords) // 2 coord_type = "indices" if self.indices else "physical" # Show first few vertices if there are many if n_vertices <= 4: vertices_str = ", ".join( f"({self.coords[i * 2]:.4g}, {self.coords[i * 2 + 1]:.4g})" for i in range(n_vertices) ) return [(f"Vertices ({coord_type})", vertices_str)] return [(f"Vertices ({coord_type})", f"{n_vertices} points")] def get_coords_summary(self) -> str: """Return a short summary of the polygon coordinates.""" n_vertices = len(self.coords) // 2 return f"{n_vertices} vertices" # pylint: disable=unused-argument @classmethod def from_param(cls: PolygonalROI, obj: ImageObj, param: ROI2DParam) -> PolygonalROI: """Create ROI from parameters Args: obj: image object param: parameters """ return cls( param.points, indices=False, title=param.title, inverse=param.inverse, ) def get_bounding_box(self, obj: ImageObj) -> tuple[float, float, float, float]: """Get bounding box (physical coordinates) Args: obj: image object """ coords = self.get_physical_coords(obj) x_edges, y_edges = coords[::2], coords[1::2] return min(x_edges), min(y_edges), max(x_edges), max(y_edges) def to_mask(self, obj: ImageObj) -> np.ndarray: """Create mask from ROI Args: obj: image object Returns: Mask (boolean array where True values are inside the ROI) """ roi_mask = np.ones_like(obj.data, dtype=bool) indices = self.get_indices_coords(obj) rows = np.array(indices[1::2], dtype=float) # y coordinates cols = np.array(indices[::2], dtype=float) # x coordinates rr, cc = draw.polygon(rows, cols, shape=obj.data.shape) if self.inverse: # Inverse ROI: mask inside the polygon (True inside, False outside) roi_mask[:] = False roi_mask[rr, cc] = True else: # Normal ROI: mask outside the polygon (False inside, True outside) roi_mask[rr, cc] = False return roi_mask def to_param(self, obj: ImageObj, index: int) -> ROI2DParam: """Convert ROI to parameters Args: obj: object (image), for physical-indices coordinates conversion index: ROI index """ gtitle = base.get_generic_roi_title(index) param = ROI2DParam(gtitle) param.title = self.title or gtitle param.geometry = "polygon" param.points = np.array(self.get_physical_coords(obj)) param.inverse = self.inverse return param class RectangularROI(BaseSingleImageROI): """Rectangular ROI Args: coords: ROI edge coordinates (x0, y0, dx, dy) title: title inverse: inverse ROI logic (default: False) .. note:: The image ROI coords are expressed in physical coordinates (floats) """ def check_coords(self) -> None: """Check if coords are valid Raises: ValueError: invalid coords """ if len(self.coords) != 4: raise ValueError("Rectangle ROI requires 4 coordinates") def get_coords_html_rows(self) -> list[tuple[str, str]]: """Return HTML table rows describing the rectangle coordinates.""" x0, y0, dx, dy = self.coords coord_type = "indices" if self.indices else "physical" return [ (f"Origin ({coord_type})", f"({x0:.4g}, {y0:.4g})"), (f"Size ({coord_type})", f"{dx:.4g} × {dy:.4g}"), ] def get_coords_summary(self) -> str: """Return a short summary of the rectangle coordinates.""" x0, y0, dx, dy = self.coords return f"Origin: ({x0:.4g}, {y0:.4g}), Size: {dx:.4g}×{dy:.4g}" # pylint: disable=unused-argument @classmethod def from_param( cls: RectangularROI, obj: ImageObj, param: ROI2DParam ) -> RectangularROI: """Create ROI from parameters Args: obj: image object param: parameters """ x0, y0, x1, y1 = param.get_bounding_box_physical() return cls( [x0, y0, x1 - x0, y1 - y0], indices=False, title=param.title, inverse=param.inverse, ) def get_bounding_box(self, obj: ImageObj) -> tuple[float, float, float, float]: """Get bounding box (physical coordinates) Args: obj: image object """ x0, y0, dx, dy = self.get_physical_coords(obj) return x0, y0, x0 + dx, y0 + dy def get_physical_coords(self, obj: ImageObj) -> list[float]: """Return physical coords Args: obj: image object Returns: Physical coords """ if self.indices: ix0, iy0, idx, idy = self.coords x0, y0, x1, y1 = obj.indices_to_physical([ix0, iy0, ix0 + idx, iy0 + idy]) return [x0, y0, x1 - x0, y1 - y0] return self.coords def set_physical_coords(self, obj: ImageObj, coords: np.ndarray) -> None: """Set physical coords Args: obj: object (signal/image) coords: physical coords """ if self.indices: x0, y0, dx, dy = coords ix0, iy0, ix1, iy1 = obj.physical_to_indices([x0, y0, x0 + dx, y0 + dy]) self.coords = np.array([ix0, iy0, ix1 - ix0, iy1 - iy0], dtype=int) else: self.coords = np.array(coords, dtype=float) def get_indices_coords(self, obj: ImageObj) -> list[int]: """Return indices coords Args: obj: image object Returns: Indices coords """ if self.indices: return self.coords.tolist() ix0, iy0, ix1, iy1 = obj.physical_to_indices(self.get_bounding_box(obj)) return [ix0, iy0, ix1 - ix0, iy1 - iy0] def set_indices_coords(self, obj: ImageObj, coords: np.ndarray) -> None: """Set indices coords Args: obj: object (signal/image) coords: indices coords """ if self.indices: self.coords = coords else: ix0, iy0, idx, idy = coords x0, y0, x1, y1 = obj.indices_to_physical([ix0, iy0, ix0 + idx, iy0 + idy]) self.coords = np.array([x0, y0, x1 - x0, y1 - y0]) def to_mask(self, obj: ImageObj) -> np.ndarray: """Create mask from ROI Args: obj: image object Returns: Mask (boolean array where True values are inside the ROI) """ roi_mask = np.ones_like(obj.data, dtype=bool) ix0, iy0, idx, idy = self.get_indices_coords(obj) rr, cc = draw.rectangle((iy0, ix0), extent=(idy, idx), shape=obj.data.shape) if self.inverse: # Inverse ROI: mask inside the rectangle (True inside, False outside) roi_mask[:] = False roi_mask[rr, cc] = True else: # Normal ROI: mask outside the rectangle (False inside, True outside) roi_mask[rr, cc] = False return roi_mask def to_param(self, obj: ImageObj, index: int) -> ROI2DParam: """Convert ROI to parameters Args: obj: object (image), for physical-indices coordinates conversion index: ROI index """ gtitle = base.get_generic_roi_title(index) param = ROI2DParam(gtitle) param.title = self.title or gtitle param.geometry = "rectangle" param.x0, param.y0, param.dx, param.dy = self.get_physical_coords(obj) param.inverse = self.inverse return param @staticmethod def rect_to_coords( x0: int | float, y0: int | float, x1: int | float, y1: int | float ) -> np.ndarray: """Convert rectangle to coordinates Args: x0: x0 (first corner) y0: y0 (first corner) x1: x1 (opposite corner) y1: y1 (opposite corner) Returns: Rectangle coordinates (x0, y0, Δx, Δy) with positive Δx and Δy Note: Coordinates are normalized so that Δx and Δy are always positive. This handles rectangles drawn "backwards" (from bottom-right to top-left). """ # Normalize coordinates to ensure Δx and Δy are positive x_min, x_max = min(x0, x1), max(x0, x1) y_min, y_max = min(y0, y1), max(y0, y1) return np.array([x_min, y_min, x_max - x_min, y_max - y_min], dtype=type(x0)) class CircularROI(BaseSingleImageROI): """Circular ROI Args: coords: ROI edge coordinates (xc, yc, r) title: title inverse: inverse ROI logic (default: False) .. note:: The image ROI coords are expressed in physical coordinates (floats) """ # pylint: disable=unused-argument @classmethod def from_param(cls: CircularROI, obj: ImageObj, param: ROI2DParam) -> CircularROI: """Create ROI from parameters Args: obj: image object param: parameters """ x0, y0, x1, y1 = param.get_bounding_box_physical() ixc, iyc = (x0 + x1) * 0.5, (y0 + y1) * 0.5 ir = (x1 - x0) * 0.5 return cls( [ixc, iyc, ir], indices=False, title=param.title, inverse=param.inverse, ) def check_coords(self) -> None: """Check if coords are valid Raises: ValueError: invalid coords """ if len(self.coords) != 3: raise ValueError("Circle ROI requires 3 coordinates") def get_coords_html_rows(self) -> list[tuple[str, str]]: """Return HTML table rows describing the circle coordinates.""" xc, yc, r = self.coords coord_type = "indices" if self.indices else "physical" return [ (f"Center ({coord_type})", f"({xc:.4g}, {yc:.4g})"), (f"Radius ({coord_type})", f"{r:.4g}"), ] def get_coords_summary(self) -> str: """Return a short summary of the circle coordinates.""" xc, yc, r = self.coords return f"Center: ({xc:.4g}, {yc:.4g}), R: {r:.4g}" def get_bounding_box(self, obj: ImageObj) -> tuple[float, float, float, float]: """Get bounding box (physical coordinates) Args: obj: image object """ xc, yc, r = self.get_physical_coords(obj) return xc - r, yc - r, xc + r, yc + r def get_physical_coords(self, obj: ImageObj) -> np.ndarray: """Return physical coords Args: obj: image object Returns: Physical coords """ if self.indices: ixc, iyc, ir = self.coords x0, y0, x1, y1 = obj.indices_to_physical( [ixc - ir, iyc - ir, ixc + ir, iyc + ir] ) return [0.5 * (x0 + x1), 0.5 * (y0 + y1), 0.5 * (x1 - x0)] return self.coords def set_physical_coords(self, obj: ImageObj, coords: np.ndarray) -> None: """Set physical coords Args: obj: object (signal/image) coords: physical coords """ if self.indices: xc, yc, r = coords ix0, iy0, ix1, iy1 = obj.physical_to_indices( [xc - r, yc - r, xc + r, yc + r] ) self.coords = np.array( [0.5 * (ix0 + ix1), 0.5 * (iy0 + iy1), 0.5 * (ix1 - ix0)] ) else: self.coords = np.array(coords, dtype=float) def get_indices_coords(self, obj: ImageObj) -> list[float]: """Return indices coords Args: obj: image object Returns: Indices coords """ if self.indices: return self.coords ix0, iy0, ix1, iy1 = obj.physical_to_indices( self.get_bounding_box(obj), as_float=True ) ixc, iyc = (ix0 + ix1) * 0.5, (iy0 + iy1) * 0.5 ir = (ix1 - ix0) * 0.5 return [ixc, iyc, ir] def set_indices_coords(self, obj: ImageObj, coords: np.ndarray) -> None: """Set indices coords Args: obj: object (signal/image) coords: indices coords """ if self.indices: self.coords = coords else: ixc, iyc, ir = coords x0, y0, x1, y1 = obj.indices_to_physical( [ixc - ir, iyc - ir, ixc + ir, iyc + ir] ) self.coords = np.array([0.5 * (x0 + x1), 0.5 * (y0 + y1), 0.5 * (x1 - x0)]) def to_mask(self, obj: ImageObj) -> np.ndarray: """Create mask from ROI Args: obj: image object Returns: Mask (boolean array where True values are inside the ROI) """ roi_mask = np.ones_like(obj.data, dtype=bool) ixc, iyc, ir = self.get_indices_coords(obj) yxratio = obj.dy / obj.dx rr, cc = draw.ellipse(iyc, ixc, ir / yxratio, ir, shape=obj.data.shape) if self.inverse: # Inverse ROI: mask inside the circle (True inside, False outside) roi_mask[:] = False roi_mask[rr, cc] = True else: # Normal ROI: mask outside the circle (False inside, True outside) roi_mask[rr, cc] = False return roi_mask def to_param(self, obj: ImageObj, index: int) -> ROI2DParam: """Convert ROI to parameters Args: obj: object (image), for physical-indices coordinates conversion index: ROI index """ gtitle = base.get_generic_roi_title(index) param = ROI2DParam(gtitle) param.title = self.title or gtitle param.geometry = "circle" param.xc, param.yc, param.r = self.get_physical_coords(obj) param.inverse = self.inverse return param @staticmethod def rect_to_coords( x0: int | float, y0: int | float, x1: int | float, y1: int | float ) -> np.ndarray: """Convert rectangle to circle coordinates Args: x0: x0 (top-left corner) y0: y0 (top-left corner) x1: x1 (bottom-right corner) y1: y1 (bottom-right corner) Returns: Circle coordinates (xc, yc, r) """ xc, yc, r = 0.5 * (x0 + x1), 0.5 * (y0 + y1), 0.5 * (x1 - x0) return np.array([xc, yc, r], dtype=type(x0)) class ImageROI(base.BaseROI["ImageObj", BaseSingleImageROI, ROI2DParam]): """Image Regions of Interest Args: inverse: if True, ROI is outside the region """ PREFIX = "i" @staticmethod def get_compatible_single_roi_classes() -> list[Type[BaseSingleImageROI]]: """Return compatible single ROI classes""" return [RectangularROI, CircularROI, PolygonalROI] def to_mask(self, obj: ImageObj) -> np.ndarray: """Create mask from ROI Args: obj: image object Returns: Mask (boolean array where True values are inside the ROI) """ if not self.single_rois: # If no single ROIs, the mask is empty (no ROI defined) mask = np.ones_like(obj.data, dtype=bool) mask.fill(False) return mask # Check inverse values to determine combination strategy inverse_values = [roi.inverse for roi in self.single_rois] all_normal = not any(inverse_values) # All inverse=False (normal ROI) all_inverse = all(inverse_values) # All inverse=True (inverse ROI) if all_normal: # All ROIs have inverse=False: AND them together (intersection) mask = np.ones_like(obj.data, dtype=bool) for roi in self.single_rois: mask &= roi.to_mask(obj) elif all_inverse: # All ROIs have inverse=True: OR them together (union) mask = np.zeros_like(obj.data, dtype=bool) for roi in self.single_rois: mask |= roi.to_mask(obj) else: # Mixed inverse values: complex combination # Start with all True (full mask) mask = np.ones_like(obj.data, dtype=bool) # First apply all inverse=False ROIs (intersections) for roi in self.single_rois: if not roi.inverse: mask &= roi.to_mask(obj) # Then apply inverse=True ROIs (add their areas) inside_mask = np.zeros_like(obj.data, dtype=bool) for roi in self.single_rois: if roi.inverse: inside_mask |= roi.to_mask(obj) # Combine: mask outside regions AND include inside regions mask = mask | inside_mask return mask def create_image_roi( geometry: Literal["rectangle", "circle", "polygon"], coords: np.ndarray | list[float] | list[list[float]], indices: bool = False, title: str = "", inverse: bool | list[bool] = False, ) -> ImageROI: """Create Image Regions of Interest (ROI) object. More ROIs can be added to the object after creation, using the `add_roi` method. Args: geometry: ROI type ('rectangle', 'circle', 'polygon') coords: ROI coords (physical coordinates), `[x0, y0, dx, dy]` for a rectangle, `[xc, yc, r]` for a circle, or `[x0, y0, x1, y1, ...]` for a polygon (lists or NumPy arrays are accepted). For multiple ROIs, nested lists or NumPy arrays are accepted but with a common geometry type (e.g. `[[xc1, yc1, r1], [xc2, yc2, r2], ...]` for circles). indices: if True, coordinates are indices, if False, they are physical values (default to False) title: title inverse: ROI logic behavior. Controls whether the ROI logic is inversed (default: False, meaning normal ROI that focuses on data inside the shape). When True, the ROI logic is inversed to focus on data outside the shape. Can be a single boolean (applied to all ROIs) or a list of booleans (one per ROI for individual control). Returns: Regions of Interest (ROI) object Raises: ValueError: if ROI type is unknown, if the number of coordinates is invalid, or if the number of inverse values doesn't match the number of ROIs Examples: Create a single rectangle ROI (defaults to normal behavior): >>> roi = create_image_roi("rectangle", [10, 20, 30, 40]) Create a single rectangle ROI with inverse logic explicitly: >>> roi = create_image_roi("rectangle", [10, 20, 30, 40], inverse=True) Create multiple rectangles with global inverse parameter: >>> coords = [[10, 20, 30, 40], [50, 60, 70, 80]] >>> roi = create_image_roi("rectangle", coords, inverse=False) Create multiple rectangles with individual inverse parameters: >>> coords = [[10, 20, 30, 40], [50, 60, 70, 80]] >>> inverse_values = [True, False] # First inside, second outside >>> roi = create_image_roi( ... "rectangle", coords, inverse=inverse_values ... ) Create polygons with varying vertex counts: >>> polygon_coords = [[0, 0, 10, 0, 5, 8], [20, 20, 30, 20, 30, 30, 20, 30]] >>> inverse_values = [False, True] # First outside, second inside >>> roi = create_image_roi( ... "polygon", polygon_coords, inverse=inverse_values ... ) """ # Handle coordinates - try to create numpy array, fall back to list for irregular try: coords = np.array(coords, float) if coords.ndim == 1: coords = coords.reshape(1, -1) coord_list = coords coord_count = len(coords) except ValueError: # Handle irregular case: polygons with varying vertex counts coord_list = [np.array(coord, float) for coord in coords] coord_count = len(coord_list) # Handle inverse parameter - can be single value or list if isinstance(inverse, bool): inverse_values = [inverse] * coord_count else: inverse_values = list(inverse) if len(inverse_values) != coord_count: raise ValueError( f"Number of inverse values ({len(inverse_values)}) must " f"match number of ROIs ({coord_count})" ) roi = ImageROI() if geometry == "rectangle": if isinstance(coord_list, np.ndarray) and coord_list.shape[1] != 4: raise ValueError("Rectangle ROI requires 4 coordinates") for coord_row, inverse_val in zip(coord_list, inverse_values): roi.add_roi(RectangularROI(coord_row, indices, title, inverse_val)) elif geometry == "circle": if isinstance(coord_list, np.ndarray) and coord_list.shape[1] != 3: raise ValueError("Circle ROI requires 3 coordinates") for coord_row, inverse_val in zip(coord_list, inverse_values): roi.add_roi(CircularROI(coord_row, indices, title, inverse_val)) elif geometry == "polygon": if isinstance(coord_list, np.ndarray) and coord_list.shape[1] % 2 != 0: raise ValueError("Polygon ROI requires pairs of X, Y coordinates") for coord_row, inverse_val in zip(coord_list, inverse_values): roi.add_roi(PolygonalROI(coord_row, indices, title, inverse_val)) else: raise ValueError(f"Unknown ROI type: {geometry}") return roi def create_image_roi_around_points( coords: np.ndarray, roi_geometry: sigima.enums.DetectionROIGeometry ) -> ImageROI: """Create ROIs around given point coordinates. Args: coords: Coordinates of points (shape: (n, 2)) roi_geometry: ROI geometry type (rectangle or circle) Returns: ImageROI object containing rectangles or circles around each point Raises: ValueError: If less than 2 points are provided (cannot determine ROI size), or if points are too close together resulting in too small ROI size, or if an invalid ROI geometry is specified. """ assert roi_geometry in ("rectangle", "circle") if coords.size == 0: raise ValueError("No coordinates provided to create ROIs") if coords.ndim != 2 or coords.shape[1] != 2: raise ValueError( f"Coordinates array must have shape (n, 2), got {coords.shape}" ) if coords.shape[0] < 2: raise ValueError( "At least two points are required to automatically determine ROI size" ) # Calculate ROI size based on minimum distance between points dist = sigima.tools.image.distance_matrix(coords) dist_min = dist[dist != 0].min() assert dist_min > 0 if roi_geometry == "rectangle": # For rectangles, account for diagonal to avoid overlap radius = int(0.5 * dist_min / np.sqrt(2) - 1) else: # circle # For circles, use half the minimum distance directly radius = int(0.5 * dist_min - 1) if radius < 1: raise ValueError( "Calculated ROI size is too small. Points may be too close together." ) roi_coords = [] for x, y in coords: if roi_geometry == "rectangle": x0, y0 = x - radius, y - radius dx, dy = 2 * radius, 2 * radius roi_coords.append([x0, y0, dx, dy]) else: # circle roi_coords.append([x, y, radius]) return create_image_roi(roi_geometry, roi_coords, indices=True) Sigima-1.1.1/sigima/objects/scalar/000077500000000000000000000000001514013333200170655ustar00rootroot00000000000000Sigima-1.1.1/sigima/objects/scalar/__init__.py000066400000000000000000000026431514013333200212030ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Scalar results subpackage ========================= This subpackage provides classes and functions for handling scalar results in Sigima. The subpackage is split into two main modules: - :mod:`sigima.objects.scalar.table`: Table results and related utilities - :mod:`sigima.objects.scalar.geometry`: Geometry results and related utilities For backward compatibility, all public symbols are re-exported from this __init__.py file, so existing imports like: .. code-block:: python from sigima.objects.scalar import TableResult, GeometryResult continue to work as expected. """ # Import all public symbols from both modules from sigima.objects.scalar.geometry import ( GeometryResult, KindShape, concat_geometries, filter_geometry_by_roi, ) from sigima.objects.scalar.table import ( NO_ROI, ResultHtmlGenerator, TableKind, TableResult, TableResultBuilder, calc_table_from_data, concat_tables, filter_table_by_roi, ) # Define __all__ to specify what gets imported with # "from sigima.objects.scalar import *" __all__ = [ "NO_ROI", "GeometryResult", "KindShape", "ResultHtmlGenerator", "TableKind", "TableResult", "TableResultBuilder", "calc_table_from_data", "concat_geometries", "concat_tables", "filter_geometry_by_roi", "filter_table_by_roi", ] Sigima-1.1.1/sigima/objects/scalar/common.py000066400000000000000000000200541514013333200207300ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Common utilities for scalar result objects ========================================== This module provides shared functionality for TableResult and GeometryResult classes without using inheritance or mixins, maintaining their dataclass integrity. """ from __future__ import annotations from typing import TYPE_CHECKING import pandas as pd if TYPE_CHECKING: from sigima.objects import GeometryResult, ImageObj, SignalObj, TableResult # Sentinel value for "full signal/image / no ROI" rows in result tables NO_ROI: int = -1 class DisplayPreferencesManager: """Manages display preferences for result objects.""" @staticmethod def get_display_preferences( result: GeometryResult | TableResult, headers: list[str], attr_name: str = "hidden_headers", ) -> dict[str, bool]: """Get display preferences for headers. Args: result: The result object containing attrs headers: List of header names attr_name: Name of the attribute storing hidden headers Returns: Dictionary mapping header names to visibility (True=visible, False=hidden) """ prefs = {} hidden_headers = result.attrs.get(attr_name, set()) if isinstance(hidden_headers, (list, tuple)): hidden_headers = set(hidden_headers) for header in headers: prefs[header] = header not in hidden_headers return prefs @staticmethod def set_display_preferences( result: GeometryResult | TableResult, preferences: dict[str, bool], headers: list[str], attr_name: str = "hidden_headers", ) -> None: """Set display preferences for headers. Args: result: The result object to modify preferences: Dictionary mapping header names to visibility headers: List of valid header names attr_name: Name of the attribute to store hidden headers """ hidden_headers = { header for header, visible in preferences.items() if not visible and header in headers } if hidden_headers: result.attrs[attr_name] = list(hidden_headers) elif attr_name in result.attrs: del result.attrs[attr_name] @staticmethod def get_visible_headers( result: GeometryResult | TableResult, headers: list[str], attr_name: str = "hidden_headers", ) -> list[str]: """Get list of currently visible headers. Args: result: The result object headers: List of all header names attr_name: Name of the attribute storing hidden headers Returns: List of header names that should be displayed """ prefs = DisplayPreferencesManager.get_display_preferences( result, headers, attr_name ) return [header for header in headers if prefs.get(header, True)] class DataFrameManager: """Manages DataFrame operations for result objects.""" @staticmethod def apply_visible_only_filter( df: pd.DataFrame, visible_headers: list[str] ) -> pd.DataFrame: """Apply visible-only filter to a DataFrame. Args: df: DataFrame to filter visible_headers: List of headers that should be visible Returns: Filtered DataFrame with only visible columns """ # Keep roi_index column if present if "roi_index" in df.columns: visible_headers = ["roi_index"] + visible_headers # Filter to only available visible columns available_headers = [col for col in visible_headers if col in df.columns] if available_headers: return df[available_headers] return df class ResultHtmlGenerator: """Utility class for generating HTML from result objects using composition.""" @staticmethod def generate_html( result: GeometryResult | TableResult, obj: SignalObj | ImageObj | None = None, visible_only: bool = True, transpose_single_row: bool = True, **kwargs, ) -> str: """Generate HTML from a result object. Args: result: The result object (TableResult or GeometryResult) obj: SignalObj or ImageObj for ROI title extraction visible_only: If True, include only visible headers based on display preferences. Default is False. transpose_single_row: If True, transpose the table when there's only one row **kwargs: Additional arguments passed to DataFrame.to_html() Returns: HTML representation of the result """ df = result.to_dataframe(visible_only=visible_only) # Remove roi_index column for display if "roi_index" in df.columns: roi_indices = df["roi_index"].tolist() df = df.drop(columns=["roi_index"]) else: roi_indices = None # Create row headers row_headers = ResultHtmlGenerator._get_row_headers(result, roi_indices, obj) # Transpose if single row and flag is set if transpose_single_row and len(df) == 1: # Transpose the dataframe df_t = df.T df_t.columns = [row_headers[0] if row_headers[0] else "Value"] df_t.index.name = "Item" # Get labels for the transposed view display_labels = list(df.columns) df_t.index = display_labels text = f'{result.title}:' html_kwargs = {"border": 0} html_kwargs.update(kwargs) # Format numeric columns only, avoiding float_format on mixed data types for col in df_t.select_dtypes(include=["number"]).columns: df_t[col] = df_t[col].map(lambda x: f"{x:.3g}" if pd.notna(x) else x) text += df_t.to_html(**html_kwargs) else: # Standard horizontal layout df.index = row_headers text = f'{result.title}:' html_kwargs = {"border": 0} html_kwargs.update(kwargs) # Format numeric columns only, avoiding float_format on mixed data types for col in df.select_dtypes(include=["number"]).columns: df[col] = df[col].map(lambda x: f"{x:.3g}" if pd.notna(x) else x) text += df.to_html(**html_kwargs) return text @staticmethod def _get_row_headers( result: TableResult | GeometryResult, roi_indices: list[int] | None, obj: SignalObj | ImageObj | None, ) -> list[str]: """Create row headers from ROI indices. .. note:: Handles gracefully the case where: - `obj` is None: uses generic "ROI N" headers instead of ROI titles - `roi_indices` reference ROIs that no longer exist in `obj.roi` (e.g., if HTML rendering happens before result recomputation after ROI deletion) """ row_headers = [] if roi_indices is not None: for roi_idx in roi_indices: if roi_idx == NO_ROI: header = "" else: header = f"ROI {roi_idx}" # Try to get ROI title from object if available if obj is not None and obj.roi is not None: # Check if roi_idx is valid (defensive against stale indices) if 0 <= roi_idx < len(obj.roi.single_rois): header = obj.roi.get_single_roi_title(roi_idx) # else: keep default "ROI {roi_idx}" for out-of-bounds indices row_headers.append(header) else: # Need to get DataFrame to know the number of rows df = result.to_dataframe() if "roi_index" in df.columns: df = df.drop(columns=["roi_index"]) row_headers = [""] * len(df) return row_headers Sigima-1.1.1/sigima/objects/scalar/geometry.py000066400000000000000000000554601514013333200213040ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Geometry results ================ Geometry results are compute-friendly result containers for geometric outputs. This module defines the `GeometryResult` class and related utilities: - `GeometryResult`: geometric outputs (points, segments, circles, ...) - `KindShape`: enumeration of geometric shape types - Utility functions for geometry operations (concatenation, filtering, etc.) Each result object is a simple data container with no behavior or methods: - It contains the result of a 1-to-0 processing function (e.g. `sigima.proc.image.contour_shape()`), i.e. a computation function that takes a signal or image object (`SignalObj` or `ImageObj`) as input and produces a geometric output (`GeometryResult`). - The result may consist of multiple rows, each corresponding to a different ROI. .. note:: No UI/HTML, no DataLab-specific metadata here. Adapters/formatters live in DataLab. These classes are JSON-friendly via `to_dict()`/`from_dict()`. Conventions ----------- Conventions regarding ROI and geometry are as follows: - ROI indexing: - `NO_ROI = -1` sentinel is used for "full image / no ROI" rows. - Per-ROI rows use non-negative indices (0-based). - Geometry coordinates (physical units): - `"point"` / `"marker"`: `[x, y]` - `"segment"`: `[x0, y0, x1, y1]` - `"rectangle"`: `[x0, y0, width, height]` - `"circle"`: `[x0, y0, radius]` - `"ellipse"`: `[x0, y0, a, b, theta]` # theta in radians - `"polygon"`: `[x0, y0, x1, y1, ..., xn, yn]` (rows may be NaN-padded) """ from __future__ import annotations import dataclasses import enum from typing import TYPE_CHECKING, Iterable import numpy as np import pandas as pd from sigima.objects.base import HTML_TABLE_CSS from sigima.objects.scalar.common import ( NO_ROI, DataFrameManager, DisplayPreferencesManager, ResultHtmlGenerator, ) if TYPE_CHECKING: from sigima.objects import ImageObj, SignalObj class KindShape(str, enum.Enum): """Geometric shape types.""" POINT = "point" SEGMENT = "segment" CIRCLE = "circle" ELLIPSE = "ellipse" RECTANGLE = "rectangle" POLYGON = "polygon" MARKER = "marker" @classmethod def values(cls) -> list[str]: """Return all shape type values.""" return [e.value for e in cls] @dataclasses.dataclass(frozen=True) class GeometryResult: """Geometric outputs, optionally per-ROI. Args: title: Human-readable title for this geometric output set. kind: Shape kind (`KindShape` member or its string value). coords: 2-D array (N, K) with coordinates per row. K depends on `kind` and may be NaN-padded (e.g., for polygons). roi_indices: Optional 1-D array (N,) mapping rows to ROI indices. Use NO_ROI (-1) for the "full signal/image / no ROI" row. func_name: Optional name of the computation function that produced this result. attrs: Optional algorithmic context (e.g. thresholds, method variant). Raises: ValueError: If dimensions are inconsistent or fields are invalid. .. important:: **Coordinate System**: GeometryResult coordinates are stored in **physical units** (e.g., mm, µm), not pixel coordinates. The conversion from pixel to physical coordinates is performed automatically when creating GeometryResult objects from image measurements using :func:`~sigima.proc.image.base.compute_geometry_from_obj`. This ensures that geometric measurements are: * **Scale-independent**: Results remain valid when images are resized * **Physically meaningful**: Measurements have real-world significance * **Consistent**: Same geometric features yield same results across different images .. note:: Coordinate conventions are as follows: - `KindShape.POINT`: `[x, y]` - `KindShape.SEGMENT`: `[x0, y0, x1, y1]` - `KindShape.RECTANGLE`: `[x0, y0, width, height]` - `KindShape.CIRCLE`: `[x0, y0, radius]` - `KindShape.ELLIPSE`: `[x0, y0, a, b, theta]` # theta in radians - `KindShape.POLYGON`: `[x0, y0, x1, y1, ..., xn, yn]` (rows may be NaN-padded) All coordinate values and dimensions (width, height, radius, semi-axes) are expressed in the image's physical units as defined by the image calibration. See Also: :func:`~sigima.proc.image.base.compute_geometry_from_obj`: Function that creates GeometryResult objects with automatic coordinate conversion from pixel to physical units. """ title: str kind: KindShape coords: np.ndarray roi_indices: np.ndarray | None = None func_name: str | None = None attrs: dict[str, object] = dataclasses.field(default_factory=dict) def __post_init__(self) -> None: """Validate fields after initialization.""" # --- kind validation/coercion (smooth migration) --- k = object.__getattribute__(self, "kind") if isinstance(k, str): try: k = KindShape(k) # coerce "ellipse" -> KindShape.ELLIPSE except ValueError as exc: raise ValueError(f"Unsupported geometry kind: {k!r}") from exc object.__setattr__(self, "kind", k) elif not isinstance(k, KindShape): raise ValueError("kind must be a KindShape or its string value") if not isinstance(self.title, str) or not self.title: raise ValueError("title must be a non-empty string") if not isinstance(self.coords, np.ndarray) or self.coords.ndim != 2: raise ValueError("coords must be a 2-D numpy array") if k == KindShape.POINT and self.coords.shape[1] != 2: raise ValueError("coords for 'point' must be (N,2)") if k == KindShape.MARKER and self.coords.shape[1] != 2: raise ValueError("coords for 'marker' must be (N,2)") if k == KindShape.SEGMENT and self.coords.shape[1] != 4: raise ValueError("coords for 'segment' must be (N,4)") if k == KindShape.CIRCLE and self.coords.shape[1] != 3: raise ValueError("coords for 'circle' must be (N,3)") if k == KindShape.ELLIPSE and self.coords.shape[1] != 5: raise ValueError("coords for 'ellipse' must be (N,5)") if k == KindShape.RECTANGLE and self.coords.shape[1] != 4: raise ValueError("coords for 'rectangle' must be (N,4)") if k == KindShape.POLYGON and self.coords.shape[1] % 2 != 0: raise ValueError("coords for 'polygon' must be (N,2M) for M vertices") if self.roi_indices is not None: if ( not isinstance(self.roi_indices, np.ndarray) or self.roi_indices.ndim != 1 ): raise ValueError("roi_indices must be a 1-D numpy array if provided") if len(self.roi_indices) != len(self.coords): raise ValueError("roi_indices length must match number of coord rows") @property def name(self) -> str: """Get the unique identifier name for this geometry result. Returns: The string value of the kind attribute, which serves as a unique name identifier for this geometry result type. """ return self.kind.value @property def value(self) -> float | tuple[float, float]: """Get the value from a single-row POINT, MARKER, or SEGMENT geometry result. This property provides convenient access to computed values: - For POINT: returns (x, y) coordinates as a tuple - For MARKER: returns (x, y) coordinates as a tuple - For SEGMENT: returns the length of the segment as a float Returns: For POINT/MARKER: tuple of (x, y) coordinates For SEGMENT: float length of the segment Raises: ValueError: If the result has multiple rows or is not a POINT, MARKER, or SEGMENT kind Examples: >>> # Get coordinates from x_at_y result (MARKER) >>> result = proxy.compute_x_at_y(p) >>> x, y = result.value # Get both coordinates >>> >>> # Get coordinates from peak detection (POINT) >>> result = proxy.compute_peak_detection(p) >>> x, y = result.value # Get peak coordinates >>> >>> # Get segment length (SEGMENT) >>> result = proxy.compute_fwhm(p) >>> length = result.value # Get FWHM length """ if self.kind not in (KindShape.POINT, KindShape.MARKER, KindShape.SEGMENT): raise ValueError( f"value property only valid for POINT, MARKER, or SEGMENT kinds, " f"got {self.kind}" ) if len(self.coords) != 1: raise ValueError( f"value property only valid for single-row results, " f"got {len(self.coords)} rows" ) if self.kind == KindShape.SEGMENT: return float(self.segments_lengths()[0]) # POINT or MARKER: return (x, y) tuple x, y = self.coords[0] return (float(x), float(y)) # -------- Factory methods -------- @classmethod def from_coords( cls, title: str, kind: KindShape, coords: np.ndarray, roi_indices: np.ndarray | None = None, *, func_name: str | None = None, attrs: dict[str, object] | None = None, ) -> GeometryResult: """Create a GeometryResult from raw data. Args: title: Human-readable title for this geometric output. kind: Shape kind (e.g. "point", "segment"). coords: 2-D array (N, K) with coordinates per row. roi_indices: Optional 1-D array (N,) mapping rows to ROI indices. func_name: Optional name of the computation function. attrs: Optional algorithmic context (e.g. thresholds, method variant). Returns: A GeometryResult instance. """ return cls( title=title, kind=kind, coords=np.asarray(coords, float), roi_indices=None if roi_indices is None else np.asarray(roi_indices, int), func_name=func_name, attrs={} if attrs is None else dict(attrs), ) # -------- JSON-friendly (de)serialization (no DataLab metadata coupling) ----- def to_dict(self) -> dict: """Convert the GeometryResult to a dictionary.""" return { "schema": 1, "title": self.title, "kind": self.kind.value, "coords": self.coords.tolist(), "roi_indices": None if self.roi_indices is None else self.roi_indices.tolist(), "func_name": self.func_name, "attrs": dict(self.attrs) if self.attrs else {}, } @staticmethod def from_dict(d: dict) -> GeometryResult: """Convert a dictionary to a GeometryResult.""" return GeometryResult( title=d["title"], kind=KindShape(d["kind"]), coords=np.asarray(d["coords"], dtype=float), roi_indices=None if d.get("roi_indices") is None else np.asarray(d["roi_indices"], dtype=int), func_name=d.get("func_name"), attrs=dict(d.get("attrs", {})), ) # -------- Pandas DataFrame interop -------- @property def headers(self) -> list[str]: """Get column headers for the coordinates. Returns: List of column headers """ # Create headers based on the shape type kind = self.kind.value # Define headers based on shape type headers_map = { "point": ["x", "y"], "marker": ["x", "y"], "segment": ["x0", "y0", "x1", "y1"], "rectangle": ["x", "y", "width", "height"], "circle": ["x", "y", "r"], "ellipse": ["x", "y", "a", "b", "θ"], } if kind in headers_map: return headers_map[kind] num_coords = self.coords.shape[1] if kind == "polygon": headers = [] for i in range(0, num_coords, 2): headers.extend([f"x{i // 2}", f"y{i // 2}"]) return headers[:num_coords] # Generic headers for unknown shapes return [f"coord_{i}" for i in range(num_coords)] def to_dataframe(self, visible_only: bool = False): """Convert the result to a pandas DataFrame. Args: visible_only: If True, include only visible headers based on display preferences. Default is False. Returns: DataFrame with an optional 'roi_index' column. If visible_only is True, only columns with visible headers are included. """ df = pd.DataFrame(self.coords, columns=self.headers) visible_headers = self.get_visible_headers() # For segments, add a length column if self.kind == KindShape.SEGMENT: lengths = self.segments_lengths() # Name the length column "Δx" if y0 == y1 for all rows, # "Δy" if x0 == x1 for all rows, else "length" if np.allclose(self.coords[:, 1], self.coords[:, 3]): length_name = "Δx" elif np.allclose(self.coords[:, 0], self.coords[:, 2]): length_name = "Δy" else: length_name = "length" df[length_name] = lengths visible_headers = [length_name] # always show length for segments if self.roi_indices is not None: df.insert(0, "roi_index", self.roi_indices) # Filter to visible columns if requested if visible_only: df = DataFrameManager.apply_visible_only_filter(df, visible_headers) return df def get_display_preferences(self) -> dict[str, bool]: """Get display preferences for coordinate headers. Returns: Dictionary mapping header names to visibility (True=visible, False=hidden). By default, all coordinates are visible unless specified in attrs. """ return DisplayPreferencesManager.get_display_preferences( self, self.headers, "hidden_coords" ) def set_display_preferences(self, preferences: dict[str, bool]) -> None: """Set display preferences for coordinate headers. Args: preferences: Dictionary mapping header names to visibility (True=visible, False=hidden) """ DisplayPreferencesManager.set_display_preferences( self, preferences, self.headers, "hidden_coords" ) def get_visible_headers(self) -> list[str]: """Get list of currently visible headers based on display preferences. Returns: List of header names that should be displayed """ return DisplayPreferencesManager.get_visible_headers( self, self.headers, "hidden_coords" ) # -------- User-oriented methods -------- def __len__(self) -> int: """Return the number of coordinates (rows) in the result.""" return self.coords.shape[0] def rows(self, roi: int | None = None) -> np.ndarray: """Return coords for all rows (this ROI or full-image row). Args: roi: Optional ROI index to filter rows. Returns: 2-D array of shape (M, K) with coordinates for the selected rows. """ if self.roi_indices is None: return self.coords target = NO_ROI if roi is None else int(roi) return self.coords[self.roi_indices == target] def bounding_boxes(self) -> np.ndarray: """Return bounding boxes for each shape in the result. Returns: 2-D array of shape (N, 4) with bounding boxes [x_min, y_min, x_max, y_max] for each shape. """ bboxes = [] for row in self.coords: if self.kind in (KindShape.POINT, KindShape.MARKER): x, y = row bbox = [x, y, x, y] elif self.kind == KindShape.SEGMENT: x0, y0, x1, y1 = row bbox = [min(x0, x1), min(y0, y1), max(x0, x1), max(y0, y1)] elif self.kind == KindShape.RECTANGLE: x, y, width, height = row bbox = [x, y, x + width, y + height] elif self.kind == KindShape.CIRCLE: x, y, r = row bbox = [x - r, y - r, x + r, y + r] elif self.kind == KindShape.ELLIPSE: x, y, a, b, _ = row bbox = [x - a, y - b, x + a, y + b] elif self.kind == KindShape.POLYGON: xs = row[0::2] ys = row[1::2] xs = xs[~np.isnan(xs)] ys = ys[~np.isnan(ys)] bbox = [np.min(xs), np.min(ys), np.max(xs), np.max(ys)] else: raise ValueError(f"Unsupported kind for bounding box: {self.kind}") bboxes.append(bbox) return np.array(bboxes) def centers(self) -> np.ndarray: """Return center points for each shape in the result. Returns: 2-D array of shape (N, 2) with center coordinates [x_center, y_center] for each shape. """ # To compute the centers, the most elegant and compact solution is to use the # bounding boxes. bboxes = self.bounding_boxes() x_centers = (bboxes[:, 0] + bboxes[:, 2]) / 2 y_centers = (bboxes[:, 1] + bboxes[:, 3]) / 2 return np.column_stack((x_centers, y_centers)) # Optional convenience for common kinds: def segments_lengths(self) -> np.ndarray: """For kind='segment': return vector of segment lengths.""" if self.kind != KindShape.SEGMENT: raise ValueError("segments_lengths requires kind='segment'") dx = self.coords[:, 2] - self.coords[:, 0] dy = self.coords[:, 3] - self.coords[:, 1] return np.sqrt(dx * dx + dy * dy) def circles_radii(self) -> np.ndarray: """For kind='circle': return radii.""" if self.kind != KindShape.CIRCLE: raise ValueError("circles_radii requires kind='circle'") return self.coords[:, 2] def ellipse_axes_angles(self) -> tuple[np.ndarray, np.ndarray, np.ndarray]: """For kind='ellipse': return (a, b, theta).""" if self.kind != KindShape.ELLIPSE: raise ValueError("ellipse_axes_angles requires kind='ellipse'") return self.coords[:, 2], self.coords[:, 3], self.coords[:, 4] def to_html( self, obj: SignalObj | ImageObj | None = None, visible_only: bool = True, transpose_single_row: bool = True, **kwargs, ) -> str: """Convert the result to HTML format. Args: obj: Optional SignalObj or ImageObj for ROI title extraction visible_only: If True, include only visible headers based on display preferences. transpose_single_row: If True, transpose when there's only one row **kwargs: Additional arguments passed to DataFrame.to_html() Returns: HTML representation of the result """ return ResultHtmlGenerator.generate_html( self, obj, visible_only, transpose_single_row, **kwargs ) def _repr_html_(self) -> str: """Return HTML representation for Jupyter notebook display. This method is automatically called by Jupyter when displaying the object as a cell output, providing a rich HTML rendering of the geometry result. Returns: HTML representation of the geometry result with styling. """ return HTML_TABLE_CSS + self.to_html() # =========================== # Geometry utility functions # =========================== def concat_geometries( title: str, geometries: Iterable[GeometryResult], *, kind: KindShape | None = None, ) -> GeometryResult: """Concatenate multiple GeometryResult objects of the same kind. Args: title: Title for the concatenated result. geometries: Iterable of GeometryResult objects to concatenate. kind: Optional kind label for the concatenated result. Returns: GeometryResult with concatenated data and updated metadata. """ geometries = list(geometries) if not geometries: raise ValueError("Cannot concatenate empty sequence of GeometryResult objects") k = kind if kind is not None else geometries[0].kind if any(geom.kind != k for geom in geometries): raise ValueError( "All GeometryResult objects must share the same kind to concatenate" ) fn = geometries[0].func_name if fn is None: raise ValueError( "All GeometryResult objects must have a func_name to concatenate" ) if any(geom.func_name != fn for geom in geometries): raise ValueError( "All GeometryResult objects must share the same func_name to concatenate" ) max_k = max(geom.coords.shape[1] for geom in geometries) if geometries else 0 # right-pad with NaNs to match width padded = [] for geometry in geometries: c = geometry.coords if c.shape[1] < max_k: pad = np.full((c.shape[0], max_k - c.shape[1]), np.nan, dtype=float) c = np.hstack([c, pad]) padded.append(c) coords = np.vstack(padded) if padded else np.zeros((0, max_k)) if any(it.roi_indices is not None for it in geometries): parts = [ ( it.roi_indices if it.roi_indices is not None else np.full((len(it.coords),), NO_ROI, int) ) for it in geometries ] roi = np.concatenate(parts) if len(parts) else None else: roi = None return GeometryResult( title=title, kind=k, coords=coords, roi_indices=roi, func_name=fn ) def filter_geometry_by_roi(res: GeometryResult, roi: int | None) -> GeometryResult: """Filter shapes by ROI index. If roi is None, keeps NO_ROI rows. Args: res: The GeometryResult to filter. roi: The ROI index to filter by, or None to keep all. Returns: A filtered GeometryResult. """ if res.roi_indices is None: keep_all = roi in (None, NO_ROI) coords = res.coords if keep_all else np.zeros((0, res.coords.shape[1])) indices = None if keep_all else np.zeros((0,), int) return GeometryResult( title=res.title, kind=res.kind, coords=coords, roi_indices=indices, attrs=dict(res.attrs), ) target = NO_ROI if roi is None else int(roi) mask = res.roi_indices == target return GeometryResult( title=res.title, kind=res.kind, coords=res.coords[mask], roi_indices=res.roi_indices[mask], attrs=dict(res.attrs), ) Sigima-1.1.1/sigima/objects/scalar/table.py000066400000000000000000000711371514013333200205370ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Table results ============= Table results are compute-friendly result containers for scalar table outputs. This module defines the `TableResult` class and related utilities: - `TableResult`: table of scalar metrics - `TableResultBuilder`: builder for TableResult with fluent interface - Utility functions for table operations (concatenation, filtering, etc.) Each result object is a simple data container with no behavior or methods: - It contains the result of a 1-to-0 processing function (e.g. `sigima.proc.signal.fwhm()`), i.e. a computation function that takes a signal or image object (`SignalObj` or `ImageObj`) as input and produces a scalar output. - The result may consist of multiple rows, each corresponding to a different ROI. .. note:: No UI/HTML, no DataLab-specific metadata here. Adapters/formatters live in DataLab. These classes are JSON-friendly via `to_dict()`/`from_dict()`. Conventions ----------- Conventions regarding ROI indexing: - `NO_ROI = -1` sentinel is used for "full image / no ROI" rows. - Per-ROI rows use non-negative indices (0-based). """ from __future__ import annotations import dataclasses import enum import inspect import os from typing import TYPE_CHECKING, Any, Callable, Iterable, Mapping, Sequence import numpy as np import pandas as pd from sigima.objects.base import HTML_TABLE_CSS from sigima.objects.scalar.common import ( NO_ROI, DataFrameManager, DisplayPreferencesManager, ResultHtmlGenerator, ) if TYPE_CHECKING: from sigima.objects import ImageObj, SignalObj class TableKind(str, enum.Enum): """Types of table results.""" STATISTICS = "statistics" PULSE_FEATURES = "pulse_features" CUSTOM = "results" @classmethod def values(cls) -> list[str]: """Return all table kind values.""" return [e.value for e in cls] @dataclasses.dataclass(frozen=True) class TableResult: """Table of scalar results, optionally per-ROI. Args: title: Human-readable title for this table of results. kind: Type of table result (e.g., TableKind.PULSE_FEATURES, TableKind.STATISTICS). Default is TableKind.CUSTOM. headers: Column names (one per metric). data: 2-D list of shape (N, len(headers)) with scalar values. roi_indices: Optional list (N,) mapping rows to ROI indices. Use NO_ROI (-1) for the "full image / no ROI" row. func_name: Optional name of the computation function that produced this result. attrs: Optional algorithmic context (e.g. thresholds, method variant). Raises: ValueError: If dimensions are inconsistent or fields are invalid. Notes: - No UI/presentation concerns, no persistence schema here. - Use DataLab-side adapters to store results in metadata if needed. """ title: str kind: TableKind | str = TableKind.CUSTOM headers: Sequence[str] = dataclasses.field(default_factory=list) data: list[list] = dataclasses.field(default_factory=list) roi_indices: list[int] | None = None func_name: str | None = None attrs: dict[str, object] = dataclasses.field(default_factory=dict) def __post_init__(self) -> None: """Validate fields after initialization.""" if isinstance(self.kind, str): try: object.__setattr__(self, "kind", TableKind(self.kind)) except ValueError: pass # Allow custom string values that are not in the enum if not isinstance(self.title, str) or not self.title: raise ValueError("title must be a non-empty string") if not isinstance(self.headers, (list, tuple)) or not all( isinstance(c, str) for c in self.headers ): raise ValueError("names must be a sequence of strings") if not isinstance(self.data, list): raise ValueError("data must be a list of lists") if self.data and not isinstance(self.data[0], list): raise ValueError("data must be a list of lists") if self.data and len(self.data[0]) != len(self.headers): raise ValueError("data columns must match names length") if self.roi_indices is not None: if not isinstance(self.roi_indices, list): raise ValueError("roi_indices must be a list if provided") if self.roi_indices and isinstance(self.roi_indices[0], list): raise ValueError("roi_indices must be a list if provided") if len(self.roi_indices) != len(self.data): raise ValueError("roi_indices length must match number of data rows") @property def name(self) -> str: """Get the unique identifier name for this scalar table result. Returns: The string value of the kind attribute, which serves as a unique name identifier for this scalar table result type. """ if isinstance(self.kind, TableKind): return self.kind.value return self.kind def __str__(self) -> str: """Return a string representation of the TableResult.""" df = self.to_dataframe() text = f"TableResult(title={self.title}, kind={self.kind}, shape={df.shape})" text += os.linesep * 2 text += str(df) return text # -------- Factory methods -------- @classmethod def from_rows( cls, title: str, headers: Sequence[str], rows: list[list], roi_indices: list[int] | None = None, *, kind: TableKind | str = TableKind.CUSTOM, func_name: str | None = None, attrs: dict[str, object] | None = None, ) -> TableResult: """Create a TableResult from raw data. Args: title: Human-readable title for this table of results. headers: Column names (one per metric). rows: 2-D list of lists of shape (N, len(headers)) with values. roi_indices: Optional list (N,) mapping rows to ROI indices. Use NO_ROI (-1) for the "full image / no ROI" row. kind: Type of table result (e.g., TableKind.PULSE_FEATURES). func_name: Optional name of the computation function. attrs: Optional algorithmic context (e.g. thresholds, method variant). Returns: A TableResult instance. """ return cls( title=title, kind=kind, headers=headers, data=rows, roi_indices=roi_indices, func_name=func_name, attrs={} if attrs is None else dict(attrs), ) # -------- JSON-friendly (de)serialization (no DataLab metadata coupling) ----- def to_dict(self) -> dict: """Convert the TableResult to a dictionary.""" return { "schema": 1, "title": self.title, "kind": self.kind.value if isinstance(self.kind, TableKind) else self.kind, "names": list(self.headers), "data": self.data, "roi_indices": self.roi_indices, "func_name": self.func_name, "attrs": dict(self.attrs) if self.attrs else {}, } @staticmethod def from_dict(d: dict) -> TableResult: """Convert a dictionary to a TableResult.""" return TableResult( title=d["title"], kind=d.get("kind", TableKind.CUSTOM), headers=list(d["names"]), data=d["data"], roi_indices=d.get("roi_indices"), func_name=d.get("func_name"), attrs=dict(d.get("attrs", {})), ) # -------- Pandas DataFrame interop -------- def to_dataframe(self, visible_only: bool = False): """Convert the result to a pandas DataFrame. Args: visible_only: If True, include only visible headers based on display preferences. Default is False. Returns: DataFrame with an optional 'roi_index' column. If visible_only is True, only columns with visible headers are included. """ df = pd.DataFrame(self.data, columns=self.headers) # Add roi_index column if present if self.roi_indices is not None: df.insert(0, "roi_index", self.roi_indices) # Filter to visible columns if requested if visible_only: visible_headers = self.get_visible_headers() df = DataFrameManager.apply_visible_only_filter(df, visible_headers) return df def get_display_preferences(self) -> dict[str, bool]: """Get display preferences for metrics. Returns: Dictionary mapping header names to visibility (True=visible, False=hidden). By default, all metrics are visible unless specified in attrs. """ return DisplayPreferencesManager.get_display_preferences( self, self.headers, "hidden_metrics" ) def set_display_preferences(self, preferences: dict[str, bool]) -> None: """Set display preferences for metrics. Args: preferences: Dictionary mapping header names to visibility (True=visible, False=hidden) """ DisplayPreferencesManager.set_display_preferences( self, preferences, self.headers, "hidden_metrics" ) def get_visible_headers(self) -> list[str]: """Get list of currently visible headers based on display preferences. Returns: List of header names that should be displayed """ return DisplayPreferencesManager.get_visible_headers( self, self.headers, "hidden_metrics" ) @classmethod def from_dataframe( cls, df, title: str, kind: TableKind | str = TableKind.CUSTOM, attrs: dict = None, ) -> TableResult: """Create a TableResult from a pandas DataFrame. Args: df: pandas DataFrame. If 'roi_index' column is present, it is used for roi_indices. title: Title for the TableResult. kind: Type of table result (e.g., TableKind.PULSE_FEATURES). attrs: Optional dictionary of attributes. Returns: TableResult instance. """ if not isinstance(df, pd.DataFrame): raise TypeError("df must be a pandas DataFrame") cols = list(df.columns) if "roi_index" in cols: roi_indices = df["roi_index"].tolist() names = [c for c in cols if c != "roi_index"] data = df[names].values.tolist() else: roi_indices = None names = cols data = df.values.tolist() if attrs is None: attrs = {} return cls( title=title, kind=kind, headers=names, data=data, roi_indices=roi_indices, attrs=attrs, ) # -------- User-oriented methods -------- def col(self, name: str) -> list: """Return the column vector by name (raises KeyError if missing). Args: name: The name of the column to retrieve. Returns: A list containing the column data. """ try: j = list(self.headers).index(name) except ValueError as exc: raise KeyError(name) from exc return [row[j] for row in self.data] def __getitem__(self, name: str) -> list: """Shorthand for col(name).""" return self.col(name) def __contains__(self, name: str) -> bool: """Check if a column name exists in the table. Args: name: The name of the column to check. Returns: True if the column exists, False otherwise. """ return name in self.headers def __len__(self) -> int: """Return the number of names in the table.""" return len(self.headers) def value(self, name: str, roi: int | None = None) -> float: """Return a single scalar by column name and ROI. Args: name: The name of the column to retrieve. roi: The region of interest (ROI) to filter by (optional). Use None for NO_ROI row. Returns: A single scalar value from the specified column and ROI. """ vec = self.col(name) if self.roi_indices is None: # single row (common in 'full image' stats) if len(vec) != 1: raise ValueError( "Ambiguous selection: multiple rows but no ROI indices" ) return vec[0] target = NO_ROI if roi is None else int(roi) matching_indices = [ i for i, roi_idx in enumerate(self.roi_indices) if roi_idx == target ] if not matching_indices: raise KeyError(f"No row for ROI={target}") if len(matching_indices) != 1: raise ValueError( f"Ambiguous selection: {len(matching_indices)} rows for ROI={target}" ) return vec[matching_indices[0]] def as_dict(self, roi: int | None = None) -> dict[str, Any]: """Return a {column -> value} mapping for one row (ROI or full image). Args: roi: The region of interest (ROI) to filter by (optional). Use None for NO_ROI row. Returns: A dictionary mapping column names to their corresponding values. """ if self.roi_indices is None: if len(self.data) != 1: raise ValueError( "Ambiguous selection: multiple rows but no ROI indices" ) row = self.data[0] else: target = NO_ROI if roi is None else int(roi) matching_indices = [ i for i, roi_idx in enumerate(self.roi_indices) if roi_idx == target ] if not matching_indices: raise KeyError(f"No row for ROI={target}") if len(matching_indices) != 1: raise ValueError( f"Ambiguous selection: {len(matching_indices)} rows for " f"ROI={target}" ) row = self.data[matching_indices[0]] return {name: row[j] for j, name in enumerate(self.headers)} def to_html( self, obj: SignalObj | ImageObj | None = None, visible_only: bool = True, transpose_single_row: bool = True, **kwargs, ) -> str: """Convert the result to HTML format. Args: obj: SignalObj or ImageObj for ROI title extraction visible_only: If True, include only visible headers based on display preferences. transpose_single_row: If True, transpose when there's only one row **kwargs: Additional arguments passed to DataFrame.to_html() Returns: HTML representation of the result """ return ResultHtmlGenerator.generate_html( self, obj, visible_only, transpose_single_row, **kwargs ) def _repr_html_(self) -> str: """Return HTML representation for Jupyter notebook display. This method is automatically called by Jupyter when displaying the object as a cell output, providing a rich HTML rendering of the table result. Returns: HTML representation of the table result with styling. """ return HTML_TABLE_CSS + self.to_html() # -------- Convenience methods for table type identification -------- def is_statistics(self) -> bool: """Check if this is a statistics table.""" return self.kind == TableKind.STATISTICS def is_pulse_features(self) -> bool: """Check if this is a pulse features table.""" return self.kind == TableKind.PULSE_FEATURES def is_custom(self) -> bool: """Check if this is a custom table.""" return self.kind == TableKind.CUSTOM class TableResultBuilder: """Builder for TableResult with fluent interface. Args: title: The title of the table. kind: The type of table result. """ def __init__(self, title: str, kind: TableKind | str = TableKind.CUSTOM) -> None: self.title = title self.kind = kind # We define either a list of column functions, or a single global function # that returns a dataclass instance with float/int fields. self.column_funcs: list[tuple[Callable, str]] = [] self.global_func: Callable | None = None self._hidden_columns: set[str] = set() def set_global_function(self, func: Callable) -> None: """Set a global function that returns a dataclass with float/int fields. Args: func: The function to compute the dataclass instance. """ assert not self.column_funcs, "Cannot mix global and per-column functions" assert isinstance(func, Callable), "Global function must be callable" # Check function signature: sig = inspect.signature(func) if len(sig.parameters) < 1: raise ValueError( "Global function must accept at least one argument (xydata tuple)" ) firstparam = list(sig.parameters.values())[0] if ( firstparam.annotation is not sig.empty and firstparam.annotation != "tuple[np.ndarray, np.ndarray]" ): raise ValueError( "Global function must accept a (np.ndarray, np.ndarray) tuple" ) # Check return type if sig.return_annotation is not sig.empty: ret_type = sig.return_annotation if not dataclasses.is_dataclass(ret_type): raise ValueError("Global function must return a dataclass") self.global_func = func def add(self, func: Callable, name: str) -> None: """Add a column function to the table. Args: func: The function to compute the column values. name: The name of the column. """ assert self.global_func is None, "Cannot mix global and per-column functions" assert isinstance(name, str) and name, "Column name must be a non-empty string" assert isinstance(func, Callable), "Column function must be callable" # Check function signature: sig = inspect.signature(func) if len(sig.parameters) < 1: raise ValueError( f"Column function '{name}' must accept at least one argument" ) first_param = list(sig.parameters.values())[0] if ( first_param.annotation is not sig.empty and first_param.annotation != "np.ndarray" ): raise ValueError(f"Column function '{name}' must accept a np.ndarray") # Check return type if sig.return_annotation is not sig.empty and sig.return_annotation not in ( "float", "int", ): raise ValueError(f"Column function '{name}' must return a float or int") self.column_funcs.append((name, func)) def hide_columns(self, names: list[str]) -> TableResultBuilder: """Mark multiple columns as hidden in the display. Args: names: List of column names to hide. Returns: Self for method chaining. """ self._hidden_columns.update(names) return self @staticmethod def __check_value(value) -> float | str: """Check and convert a value to float or str. Args: value: The value to check. Returns: The value converted to float or str. Raises: ValueError: If the value is not convertible to float or str. """ try: value = float(value) except ValueError as exc: if not isinstance(value, str): raise ValueError(f"Unexpected non-numeric value: {value!r}") from exc return value def __compute_row_from_column_funcs(self, data: np.ndarray) -> list: """Compute a single row using the column functions. Args: data: The input data array. Returns: A list of computed values for the row. """ row_data = [] for _name, func in self.column_funcs: value = func(data) value = self.__check_value(value) row_data.append(value) return row_data def __compute_row_from_dataclass(self, result) -> tuple[list, list]: """Compute a single row using the global function's dataclass result. Args: result: The dataclass instance returned by the global function. Returns: A tuple of (row_data, names). """ row_data = [] names = [] if not dataclasses.is_dataclass(result): raise ValueError("Global function must return a dataclass instance") for field in dataclasses.fields(result): value = getattr(result, field.name) if isinstance(value, (int, float, np.floating, np.integer, enum.Enum, str)): value = self.__check_value(value) else: value = None row_data.append(value) names.append(field.name) return row_data, names def compute(self, obj: SignalObj | ImageObj) -> TableResult: """Extract data from the image or signal object and compute the table. The ROI computation behavior depends on the TableKind: - STATISTICS: Computes results for both the whole object (NO_ROI) and each defined ROI. - PULSE_FEATURES: Computes results ONLY for ROIs if any are defined; otherwise computes for the whole object. This is because pulse features are meaningful only within specific ROI regions when multiple pulses are present. - CUSTOM: Default behavior is same as STATISTICS (whole object + ROIs). Args: obj: The image or signal object to extract data from. Returns: A TableResult object containing the extracted data. """ names = [name for name, _ in self.column_funcs] roi_indices = list(obj.iterate_roi_indices()) # Determine whether to include whole object computation based on TableKind # Convert kind to TableKind enum if it's a string if isinstance(self.kind, str): try: kind_enum = TableKind(self.kind) except ValueError: # If string doesn't match any TableKind, default to CUSTOM behavior kind_enum = TableKind.CUSTOM else: kind_enum = self.kind # Add whole object (None ROI) if: # 1. No ROIs exist, OR # 2. ROIs exist AND kind is not PULSE_FEATURES (which computes only on ROIs) has_rois = roi_indices and roi_indices[0] is not None if not has_rois or kind_enum != TableKind.PULSE_FEATURES: if has_rois: roi_indices.insert(0, None) rows = [] roi_idx = [] for i_roi in roi_indices: data = obj.get_data(i_roi) row_data = [] if self.column_funcs: row_data = self.__compute_row_from_column_funcs(data) elif self.global_func: result = self.global_func(data) row_data, names = self.__compute_row_from_dataclass(result) rows.append(row_data) roi_idx.append(NO_ROI if i_roi is None else int(i_roi)) # Remove columns with all None and/or NaN values if rows and names: valid_cols = [] for j, name in enumerate(names): col_values = [row[j] for row in rows] if any( v is not None and not (isinstance(v, float) and np.isnan(v)) for v in col_values ): valid_cols.append(j) if len(valid_cols) < len(names): names = [names[j] for j in valid_cols] rows = [[row[j] for j in valid_cols] for row in rows] result = TableResult.from_rows( title=self.title, headers=names, rows=rows, roi_indices=roi_idx, kind=self.kind, ) # Apply display preferences if self._hidden_columns: hidden_prefs = {name: name not in self._hidden_columns for name in names} result.set_display_preferences(hidden_prefs) return result # =========================== # Table utility functions # =========================== def calc_table_from_data( title: str, data: np.ndarray, labeledfuncs: Mapping[str, Callable[[np.ndarray], float]], roi_masks: list[np.ndarray] | None = None, kind: TableKind | str = TableKind.CUSTOM, attrs: dict[str, object] | None = None, ) -> TableResult: """Run scalar metrics on a full array or per-ROI masks and return a TableResult. Args: title: Result title. data: N-D array consumed by metric functions. labeledfuncs: Mapping of {label: func}, where func(data_or_masked) -> float. roi_masks: Optional list of boolean masks (same shape as data). If provided, results are computed per mask; otherwise a single full-image row is returned. kind: Type of table result (e.g., TableKind.PULSE_FEATURES). attrs: Optional algorithmic context. Returns: TableResult with rows per ROI mask (or one row if `roi_masks` is None). `roi_indices` will be the mask indices (0..M-1) or NO_ROI for the single row. """ names = list(labeledfuncs.keys()) funcs = list(labeledfuncs.values()) if roi_masks: rows = [] roi_idx = [] for i, m in enumerate(roi_masks): sub = data[m] if (isinstance(m, np.ndarray) and m.dtype == bool) else data rows.append([float(f(sub)) for f in funcs]) roi_idx.append(i) return TableResult( title=title, kind=kind, headers=names, data=rows, roi_indices=roi_idx, attrs={} if attrs is None else dict(attrs), ) # No ROI: single row with NO_ROI sentinel row = [float(f(data)) for f in funcs] return TableResult( title=title, kind=kind, headers=names, data=[row], roi_indices=[NO_ROI], attrs={} if attrs is None else dict(attrs), ) def concat_tables(title: str, items: Iterable[TableResult]) -> TableResult: """Concatenate multiple TableResult objects with identical names. Args: title: Title for the concatenated result. items: Iterable of TableResult objects to concatenate. Returns: TableResult with concatenated data and updated metadata. """ items = list(items) if not items: return TableResult(title=title, headers=[], data=[]) first = items[0] cols = list(first.headers) kind = first.kind for it in items[1:]: if list(it.headers) != cols: raise ValueError( "All TableResult objects must share the same names to concatenate" ) if it.kind != kind: kind = TableKind.CUSTOM # Default to CUSTOM if kinds don't match data = [] for it in items: data.extend(it.data) if any(it.roi_indices is not None for it in items): roi = [] for it in items: if it.roi_indices is not None: roi.extend(it.roi_indices) else: roi.extend([NO_ROI] * len(it.data)) else: roi = None return TableResult(title=title, kind=kind, headers=cols, data=data, roi_indices=roi) def filter_table_by_roi(res: TableResult, roi: int | None) -> TableResult: """Filter rows by ROI index. If roi is None, keeps NO_ROI rows. Args: res: The TableResult to filter. roi: The ROI index to filter by, or None to keep all. Returns: A filtered TableResult. """ if res.roi_indices is None: # No ROI info: either keep all or none depending on request keep_all = roi in (None, NO_ROI) data = res.data if keep_all else [] indices = None if keep_all else [] return TableResult( title=res.title, headers=list(res.headers), data=data, roi_indices=indices, attrs=dict(res.attrs), ) target = NO_ROI if roi is None else int(roi) filtered_data = [] filtered_indices = [] for i, roi_idx in enumerate(res.roi_indices): if roi_idx == target: filtered_data.append(res.data[i]) filtered_indices.append(roi_idx) return TableResult( title=res.title, headers=list(res.headers), data=filtered_data, roi_indices=filtered_indices, attrs=dict(res.attrs), ) Sigima-1.1.1/sigima/objects/shape.py000066400000000000000000000247501514013333200173020ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Coordinates objects module ========================== Coordinate objects are 2D geometric entities that are used to represent and manipulate shapes in a two-dimensional space. Coordinates are typically defined in the physical coordinate system (as opposed to the image pixel coordinate system). Geometric transformations, such as translation, rotation, and scaling, can be applied to those objects to manipulate their position and size. Applications ------------ Coordinate objects have two main applications: 1. ROIs (Regions of Interest) for image processing tasks. 2. Geometry results of signal and image processing tasks. In both cases, geometric transformations can be applied to coordinate objects (rotation, translation, horizontal flipping, vertical flipping, transposition, and scaling), in order to apply the same transformation as the one applied to the image or signal data. .. note:: Geometric transformations currently support only the necessary transformations for image processing (not for signal processing). Design choices -------------- Coordinate objects are built around a `data` attribute that holds the characteristics defining the shape in the form of a 1D array: - (x, y) coordinates are stored in a flattened format: (x1, y1, x2, y2, ..., xn, yn) - Point coordinates are represented as (x, y). - Segment coordinates are represented as (x1, y1, x2, y2), where (x1, y1) is the start point and (x2, y2) is the end point. - Rectangle coordinates are represented as (x0, y0, dx, dy), where (x0, y0) is the top-left corner and (dx, dy) are the width and height. - Circle coordinates are represented as (x, y, r), where (x, y) is the center and r is the radius. - Ellipse coordinates are represented as (x, y, a, b), where (x, y) is the center, a is the semi-major axis, and b is the semi-minor axis. - Polygon coordinates are represented as a flattened array of (x, y) pairs: (x1, y1, x2, y2, ..., xn, yn). At construction, the coordinates are validated to ensure they conform to the expected format for each shape type. """ from __future__ import annotations import abc import numpy as np from sigima.objects.base import HTML_TABLE_CSS class BaseCoordinates(abc.ABC): """Base class for 2D coordinates representation of shapes. Args: data: 1D array or list of characteristics defining the shape. """ VALID_SHAPE: tuple[int, int] | None = None # To be defined by subclasses REQUIRES_EVEN_NUMBER_OF_VALUES: bool = False def __init__(self, points: np.ndarray | list[int] | list[float]): self.data = np.array(points, dtype=float) self.validate() def validate(self) -> None: """Validate the coordinates. Raises: ValueError: If the coordinates are invalid. """ if self.data.ndim != 1: raise ValueError( f"Invalid {self.__class__.__name__} coordinates ndim: " f"{self.data.ndim} (expected 1)" ) if self.VALID_SHAPE is not None and self.data.shape != self.VALID_SHAPE: raise ValueError( f"Invalid {self.__class__.__name__} coordinates shape: " f"{self.data.shape} (expected {self.VALID_SHAPE})" ) if self.REQUIRES_EVEN_NUMBER_OF_VALUES and self.data.size % 2 != 0: raise ValueError( f"Invalid {self.__class__.__name__} coordinates: " f"even number of values expected (got {self.data.size})" ) def transform_affine(self, matrix: np.ndarray) -> None: """Apply a 2D affine transformation to the coordinates inplace. Args: matrix: 3x3 affine transformation matrix. """ coords = self.data if coords.size % 2 == 0: pts = coords.reshape(-1, 2) homo = np.c_[pts, np.ones(len(pts))] out = (homo @ matrix.T)[:, :2].reshape(-1) self.data[:] = out else: pts = coords[:2].reshape(1, 2) homo = np.c_[pts, np.ones(1)] out = (homo @ matrix.T)[:, :2].reshape(-1) self.data[:2] = out def copy(self) -> BaseCoordinates: """Return a copy of the coordinate object. Returns: BaseCoordinates: A new object with the same data. """ return self.__class__(self.data.copy()) def rotate(self, angle: float, center: tuple[float, float] = (0, 0)) -> None: """Rotate coordinates by a given angle around a center inplace. Args: angle: Rotation angle in radians (counterclockwise). center: Center of rotation (x, y). Defaults to (0, 0). """ cx, cy = center c, s = np.cos(angle), np.sin(angle) t1 = np.array([[1, 0, -cx], [0, 1, -cy], [0, 0, 1]], float) r = np.array([[c, -s, 0], [s, c, 0], [0, 0, 1]], float) t2 = np.array([[1, 0, cx], [0, 1, cy], [0, 0, 1]], float) matrix = t2 @ r @ t1 self.transform_affine(matrix) def translate(self, dx: float, dy: float) -> None: """Translate coordinates by (dx, dy) inplace. Args: dx: Translation along x-axis. dy: Translation along y-axis. """ matrix = np.array([[1, 0, dx], [0, 1, dy], [0, 0, 1]], float) self.transform_affine(matrix) def fliph(self, cx: float = 0.0) -> None: """Flip coordinates horizontally around a vertical line x=cx inplace. Args: cx: x-coordinate of the vertical axis. Defaults to 0.0. """ matrix = np.array([[-1, 0, 2 * cx], [0, 1, 0], [0, 0, 1]], float) self.transform_affine(matrix) def flipv(self, cy: float = 0.0) -> None: """Flip coordinates vertically around a horizontal line y=cy inplace. Args: cy: y-coordinate of the horizontal axis. Defaults to 0.0. """ matrix = np.array([[1, 0, 0], [0, -1, 2 * cy], [0, 0, 1]], float) self.transform_affine(matrix) def transpose(self) -> None: """Transpose coordinates (swap x and y) inplace.""" matrix = np.array([[0, 1, 0], [1, 0, 0], [0, 0, 1]], float) self.transform_affine(matrix) def scale(self, sx: float, sy: float, center: tuple[float, float] = (0, 0)) -> None: """Scale coordinates by (sx, sy) around a center inplace. Args: sx: Scaling factor along x-axis. sy: Scaling factor along y-axis. center: Center of scaling (x, y). Defaults to (0, 0). """ cx, cy = center t1 = np.array([[1, 0, -cx], [0, 1, -cy], [0, 0, 1]], float) s = np.array([[sx, 0, 0], [0, sy, 0], [0, 0, 1]], float) t2 = np.array([[1, 0, cx], [0, 1, cy], [0, 0, 1]], float) matrix = t2 @ s @ t1 self.transform_affine(matrix) def _repr_html_(self) -> str: """Return HTML representation for Jupyter notebooks.""" coord_type = type(self).__name__ # Format the data array nicely if self.data.size <= 10: data_str = ", ".join(f"{v:.4g}" for v in self.data) else: first = ", ".join(f"{v:.4g}" for v in self.data[:5]) last = ", ".join(f"{v:.4g}" for v in self.data[-5:]) data_str = f"{first}, ..., {last}" html = f""" {HTML_TABLE_CSS}
{coord_type}
PropertyValue
Size{self.data.size} values
Data[{data_str}]
""" return html class PointCoordinates(BaseCoordinates): """Class for point coordinates. Args: data: 1D array point coordinates (x, y). """ VALID_SHAPE = (2,) class SegmentCoordinates(BaseCoordinates): """Class for segment coordinates. Args: data: 1D array point coordinates (x1, y1, x2, y2). """ VALID_SHAPE = (4,) class RectangleCoordinates(BaseCoordinates): """Class for a rectangle coordinates. Args: data: 1D array point coordinates (x0, y0, dx, dy). """ VALID_SHAPE = (4,) def transform_affine(self, matrix: np.ndarray) -> None: """ Apply 2D affine transformation to rectangle coordinates. For rectangles in (x0, y0, dx, dy) format, we transform the corner points and then convert back to (x0, y0, dx, dy) format. Args: matrix: 3x3 affine transformation matrix. """ x0, y0, dx, dy = self.data # Convert to corner coordinates x1, y1 = x0, y0 x2, y2 = x0 + dx, y0 + dy # Transform both corners corners = np.array([[x1, y1], [x2, y2]]) homo = np.c_[corners, np.ones(2)] transformed = (homo @ matrix.T)[:, :2] # Get the new bounding box x_min, y_min = transformed.min(axis=0) x_max, y_max = transformed.max(axis=0) # Update data with new (x0, y0, dx, dy) self.data[:] = [x_min, y_min, x_max - x_min, y_max - y_min] def rotate(self, angle: float, center: tuple[float, float] = (0, 0)) -> None: """Rotate rectangle by a given angle around a center. For rectangles, rotation may change the bounding box, so we transform all corners and compute the new axis-aligned bounding rectangle. Args: angle: Rotation angle in radians (counterclockwise). center: Center of rotation (x, y). Defaults to (0, 0). """ cx, cy = center c, s = np.cos(angle), np.sin(angle) t1 = np.array([[1, 0, -cx], [0, 1, -cy], [0, 0, 1]], float) r = np.array([[c, -s, 0], [s, c, 0], [0, 0, 1]], float) t2 = np.array([[1, 0, cx], [0, 1, cy], [0, 0, 1]], float) matrix = t2 @ r @ t1 self.transform_affine(matrix) class CircleCoordinates(BaseCoordinates): """Class for a circle coordinates. Args: data: 1D array point coordinates (x, y, r). """ VALID_SHAPE = (3,) class EllipseCoordinates(BaseCoordinates): """Class for an ellipse coordinates. Args: data: 1D array point coordinates (x, y, a, b). """ VALID_SHAPE = (4,) class PolygonCoordinates(BaseCoordinates): """Class for a polygon coordinates. Args: data: 1D array point coordinates (x1, y1, x2, y2, ..., xn, yn). """ VALID_SHAPE = None REQUIRES_EVEN_NUMBER_OF_VALUES = True Sigima-1.1.1/sigima/objects/signal/000077500000000000000000000000001514013333200170755ustar00rootroot00000000000000Sigima-1.1.1/sigima/objects/signal/__init__.py000066400000000000000000000062221514013333200212100ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Signal objects subpackage ========================= This subpackage provides signal data structures and utilities. The subpackage is organized into the following modules: - `roi`: Region of Interest (ROI) classes and parameters for 1D signals - `object`: Main SignalObj class for handling 1D signal data - `creation`: Signal creation utilities and parameter classes All classes and functions are re-exported at the subpackage level for backward compatibility. Existing imports like `from sigima.objects.signal import SignalObj` will continue to work. """ # Import all public classes and functions from submodules from .creation import ( # Constants DEFAULT_TITLE, # Mathematical function parameter classes BaseGaussLorentzVoigtParam, BasePeriodicParam, BasePulseParam, CosineParam, CustomSignalParam, # Pulse signal classes ExpectedFeatures, ExponentialParam, FeatureTolerances, # Periodic function parameter classes FreqUnits, GaussParam, # Other signal types LinearChirpParam, LogisticParam, LorentzParam, # Base parameter classes NewSignalParam, NormalDistribution1DParam, PlanckParam, PoissonDistribution1DParam, # Polynomial and custom signals PolyParam, PulseParam, SawtoothParam, # Enums SignalTypes, SincParam, SineParam, SquareParam, SquarePulseParam, StepParam, StepPulseParam, TriangleParam, UniformDistribution1DParam, VoigtParam, # Distribution parameter classes ZeroParam, check_all_signal_parameters_classes, # Core creation functions create_signal, create_signal_from_param, # Factory and utility functions create_signal_parameters, get_next_signal_number, # Registration functions register_signal_parameters_class, triangle_func, ) from .object import ( # Main signal class SignalObj, ) from .roi import ( # ROI classes ROI1DParam, SegmentROI, SignalROI, # ROI functions create_signal_roi, ) # Define __all__ for explicit public API __all__ = [ "DEFAULT_TITLE", "BaseGaussLorentzVoigtParam", "BasePeriodicParam", "BasePulseParam", "CosineParam", "CustomSignalParam", "ExpectedFeatures", "ExponentialParam", "FeatureTolerances", "FreqUnits", "GaussParam", "LinearChirpParam", "LogisticParam", "LorentzParam", "NewSignalParam", "NormalDistribution1DParam", "PlanckParam", "PoissonDistribution1DParam", "PolyParam", "PulseParam", "ROI1DParam", "SawtoothParam", "SegmentROI", "SignalObj", "SignalROI", "SignalTypes", "SincParam", "SineParam", "SquareParam", "SquarePulseParam", "StepParam", "StepPulseParam", "TriangleParam", "UniformDistribution1DParam", "VoigtParam", "ZeroParam", "check_all_signal_parameters_classes", "create_signal", "create_signal_from_param", "create_signal_parameters", "create_signal_roi", "get_next_signal_number", "register_signal_parameters_class", "triangle_func", ] Sigima-1.1.1/sigima/objects/signal/constants.py000066400000000000000000000016201514013333200214620ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Signal I/O constants - especially for datetime metadata handling """ # Datetime metadata keys # These keys are used to store datetime-related information in SignalObj.metadata DATETIME_X_KEY = "x_datetime" # Boolean: True if x represents datetime data DATETIME_X_FORMAT_KEY = "x_datetime_format" # String: format for display # Time unit conversion factors (to seconds) # Used to convert datetime values to float timestamps TIME_UNIT_FACTORS = { "ns": 1e-9, # nanoseconds "us": 1e-6, # microseconds "ms": 1e-3, # milliseconds "s": 1.0, # seconds (base unit) "min": 60.0, # minutes "h": 3600.0, # hours } # Valid time units (ordered from smallest to largest) VALID_TIME_UNITS = list(TIME_UNIT_FACTORS.keys()) # Default datetime format string DEFAULT_DATETIME_FORMAT = "%Y-%m-%d %H:%M:%S" Sigima-1.1.1/sigima/objects/signal/creation.py000066400000000000000000001336561514013333200212710ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Signal creation utilities ======================== This module provides functions and parameter classes for creating new signals. The module includes: - `create_signal_from_param`: Factory function for creating SignalObj instances from parameters - `SignalTypes`: Enumeration of supported signal generation types - `NewSignalParam` and subclasses: Parameter classes for signal generation - Factory functions and registration utilities These utilities support creating signals from various sources: - Synthetic data (zeros, random distributions, analytical functions) - Periodic functions (sine, cosine, square, etc.) - Step functions, chirps, pulses - Custom user-defined signals """ # pylint: disable=invalid-name # Allows short reference names like x, y, ... # pylint: disable=duplicate-code from __future__ import annotations import enum from dataclasses import dataclass from typing import Literal, Type import guidata.dataset as gds import numpy as np import scipy.constants import scipy.signal as sps from sigima.config import _ from sigima.enums import SignalShape from sigima.objects import base from sigima.objects.signal.object import SignalObj from sigima.tools.signal.pulse import GaussianModel, LorentzianModel, VoigtModel def create_signal( title: str, x: np.ndarray | None = None, y: np.ndarray | None = None, dx: np.ndarray | None = None, dy: np.ndarray | None = None, metadata: dict | None = None, units: tuple[str, str] | None = None, labels: tuple[str, str] | None = None, ) -> SignalObj: """Create a new Signal object. Args: title: signal title x: X data y: Y data dx: dX data (optional: error bars) dy: dY data (optional: error bars) metadata: signal metadata units: X, Y units (tuple of strings) labels: X, Y labels (tuple of strings) Returns: Signal object """ assert isinstance(title, str) signal = SignalObj(title=title) signal.title = title signal.set_xydata(x, y, dx=dx, dy=dy) if units is not None: signal.xunit, signal.yunit = units if labels is not None: signal.xlabel, signal.ylabel = labels if metadata is not None: signal.metadata.update(metadata) return signal class SignalTypes(gds.LabeledEnum): """Signal types""" #: Signal filled with zero ZERO = "zero", _("Zero") #: Random signal (normal distribution) NORMAL_DISTRIBUTION = "normal_distribution", _("Normal distribution") #: Random signal (Poisson distribution) POISSON_DISTRIBUTION = "poisson_distribution", _("Poisson distribution") #: Random signal (uniform distribution) UNIFORM_DISTRIBUTION = "uniform_distribution", _("Uniform distribution") #: Gaussian function GAUSS = "gauss", _("Gaussian") #: Lorentzian function LORENTZ = "lorentz", _("Lorentzian") #: Voigt function VOIGT = "voigt", _("Voigt") #: Planck function PLANCK = "planck", _("Blackbody (Planck)") #: Sinusoid SINE = "sine", _("Sine") #: Cosinusoid COSINE = "cosine", _("Cosine") #: Sawtooth function SAWTOOTH = "sawtooth", _("Sawtooth") #: Triangle function TRIANGLE = "triangle", _("Triangle") #: Square function SQUARE = "square", _("Square") #: Cardinal sine SINC = "sinc", _("Cardinal sine") #: Linear chirp LINEARCHIRP = "linearchirp", _("Linear chirp") #: Step function STEP = "step", _("Step") #: Exponential function EXPONENTIAL = "exponential", _("Exponential") #: Logistic function LOGISTIC = "logistic", _("Logistic") #: Pulse function PULSE = "pulse", _("Pulse") #: Step pulse function (with configurable rise time) STEP_PULSE = "step_pulse", _("Step pulse") #: Square pulse function (with configurable rise/fall times) SQUARE_PULSE = "square_pulse", _("Square pulse") #: Polynomial function POLYNOMIAL = "polynomial", _("Polynomial") #: Custom function CUSTOM = "custom", _("Custom") DEFAULT_TITLE = _("Untitled signal") class NewSignalParam(gds.DataSet): """New signal dataset. Subclasses can optionally implement a ``generate_title()`` method to provide automatic title generation based on their parameters. This method should return a string containing the generated title, or an empty string if no title can be generated. Example:: def generate_title(self) -> str: '''Generate a title based on current parameters.''' return f"MySignal(param1={self.param1},param2={self.param2})" """ title = gds.StringItem(_("Title"), default=DEFAULT_TITLE) size = gds.IntItem( _("Npoints"), help=_("Total number of points in the signal"), min=1, default=500, ) xmin = gds.FloatItem("xmin", default=-10.0) xmax = gds.FloatItem("xmax", default=10.0).set_prop("display", col=1) xlabel = gds.StringItem(_("X label"), default="") xunit = gds.StringItem(_("X unit"), default="").set_prop("display", col=1) ylabel = gds.StringItem(_("Y label"), default="") yunit = gds.StringItem(_("Y unit"), default="").set_prop("display", col=1) # As it is the last item of the dataset, the separator will be hidden if no other # items are present after it (i.e. when derived classes do not add any new items # or when the NewSignalParam class is used alone). sep = gds.SeparatorItem() def generate_x_data(self) -> np.ndarray: """Generate x data based on current parameters.""" return np.linspace(self.xmin, self.xmax, self.size) def generate_1d_data(self) -> tuple[np.ndarray, np.ndarray]: """Compute 1D data based on current parameters. Returns: Tuple of (x, y) arrays """ return self.generate_x_data(), np.zeros(self.size) SIGNAL_TYPE_PARAM_CLASSES = {} def register_signal_parameters_class(stype: SignalTypes, param_class) -> None: """Register a parameters class for a given signal type. Args: stype: signal type param_class: parameters class """ SIGNAL_TYPE_PARAM_CLASSES[stype] = param_class def __get_signal_parameters_class(stype: SignalTypes) -> Type[NewSignalParam]: """Get parameters class for a given signal type. Args: stype: signal type Returns: Parameters class Raises: ValueError: if no parameters class is registered for the given signal type """ try: return SIGNAL_TYPE_PARAM_CLASSES[stype] except KeyError as exc: raise ValueError( f"Image type {stype} has no parameters class registered" ) from exc def check_all_signal_parameters_classes() -> None: """Check all registered parameters classes.""" for stype, param_class in SIGNAL_TYPE_PARAM_CLASSES.items(): assert __get_signal_parameters_class(stype) is param_class def create_signal_parameters( stype: SignalTypes, title: str | None = None, size: int | None = None, xmin: float | None = None, xmax: float | None = None, xlabel: str | None = None, ylabel: str | None = None, xunit: str | None = None, yunit: str | None = None, **kwargs: dict, ) -> NewSignalParam: """Create parameters for a given signal type. Args: stype: signal type title: signal title size: signal size (number of points) xmin: minimum x value xmax: maximum x value xlabel: x axis label ylabel: y axis label xunit: x axis unit yunit: y axis unit **kwargs: additional parameters (specific to the signal type) Returns: Parameters object for the given signal type """ pclass = __get_signal_parameters_class(stype) p = pclass.create(**kwargs) if title is not None: p.title = title if size is not None: p.size = size if xmin is not None: p.xmin = xmin if xmax is not None: p.xmax = xmax if xlabel is not None: p.xlabel = xlabel if ylabel is not None: p.ylabel = ylabel if xunit is not None: p.xunit = xunit if yunit is not None: p.yunit = yunit return p class ZeroParam(NewSignalParam, title=_("Zero")): """Parameters for zero signal.""" def generate_1d_data(self) -> tuple[np.ndarray, np.ndarray]: """Compute 1D data based on current parameters. Returns: Tuple of (x, y) arrays. """ x = self.generate_x_data() return x, np.zeros_like(x) register_signal_parameters_class(SignalTypes.ZERO, ZeroParam) class UniformDistribution1DParam( NewSignalParam, base.UniformDistributionParam, title=_("Uniform distribution") ): """Uniform-distribution signal parameters.""" def generate_1d_data(self) -> tuple[np.ndarray, np.ndarray]: """Compute 1D data based on current parameters. Returns: Tuple of (x, y) arrays. """ x = self.generate_x_data() rng = np.random.default_rng(self.seed) assert self.vmin is not None assert self.vmax is not None y = self.vmin + rng.random(len(x)) * (self.vmax - self.vmin) return x, y register_signal_parameters_class( SignalTypes.UNIFORM_DISTRIBUTION, UniformDistribution1DParam ) class NormalDistribution1DParam( NewSignalParam, base.NormalDistributionParam, title=_("Normal distribution") ): """Normal-distribution signal parameters.""" def generate_1d_data(self) -> tuple[np.ndarray, np.ndarray]: """Compute 1D data based on current parameters. Returns: Tuple of (x, y) arrays. """ x = self.generate_x_data() rng = np.random.default_rng(self.seed) assert self.mu is not None assert self.sigma is not None y = rng.normal(self.mu, self.sigma, len(x)) return x, y register_signal_parameters_class( SignalTypes.NORMAL_DISTRIBUTION, NormalDistribution1DParam ) class PoissonDistribution1DParam( NewSignalParam, base.PoissonDistributionParam, title=_("Poisson distribution") ): """Poisson-distribution signal parameters.""" def generate_1d_data(self) -> tuple[np.ndarray, np.ndarray]: """Compute 1D data based on current parameters. Returns: Tuple of (x, y) arrays. """ x = self.generate_x_data() rng = np.random.default_rng(self.seed) assert self.lam is not None y = rng.poisson(lam=self.lam, size=len(x)) return x, y register_signal_parameters_class( SignalTypes.POISSON_DISTRIBUTION, PoissonDistribution1DParam ) class BaseGaussLorentzVoigtParam(NewSignalParam): """Base parameters for Gaussian, Lorentzian and Voigt functions""" STYPE: Type[SignalTypes] | None = None a = gds.FloatItem("A", default=1.0) y0 = gds.FloatItem("y0", default=0.0).set_pos(col=1) sigma = gds.FloatItem("σ", default=1.0) mu = gds.FloatItem("μ", default=0.0).set_pos(col=1) def generate_title(self) -> str: """Generate a title based on current parameters.""" assert isinstance(self.STYPE, SignalTypes) return ( f"{self.STYPE.name.lower()}(A={self.a:.3g},σ={self.sigma:.3g}," f"μ={self.mu:.3g},y0={self.y0:.3g})" ) def generate_1d_data(self) -> tuple[np.ndarray, np.ndarray]: """Compute 1D data based on current parameters. Returns: Tuple of (x, y) arrays """ x = self.generate_x_data() func = { SignalTypes.GAUSS: GaussianModel.func, SignalTypes.LORENTZ: LorentzianModel.func, SignalTypes.VOIGT: VoigtModel.func, }[self.STYPE] y = func(x, self.a, self.sigma, self.mu, self.y0) return x, y def get_expected_features( self, start_ratio: float = 0.1, stop_ratio: float = 0.9 ) -> ExpectedFeatures: """Calculate expected pulse features for this signal. Args: start_ratio: Start ratio for rise time calculation stop_ratio: Stop ratio for rise time calculation Returns: ExpectedFeatures dataclass with all expected values """ if self.a is None or self.sigma is None: raise ValueError("Parameters 'a' and 'sigma' must be set") if self.a == 0 or self.sigma <= 0: raise ValueError("Parameter 'a' must be non-zero and 'sigma' positive") polarity = 1 if self.a > 0 else -1 # For Gaussian: peak amplitude is a / (sigma * sqrt(2*pi)) # This gives the actual maximum value of the Gaussian function amplitude = abs(self.a) / (self.sigma * np.sqrt(2 * np.pi)) if self.STYPE == SignalTypes.GAUSS: # Gaussian rise time: t_r = 2.563 * sigma (10% to 90%) rise_time = 2.563 * self.sigma elif self.STYPE == SignalTypes.LORENTZ: # Lorentzian rise time: 2*sigma*sqrt(1/start_ratio - 1/stop_ratio) rise_time = 2 * self.sigma * np.sqrt(1 / start_ratio - 1 / stop_ratio) elif self.STYPE == SignalTypes.VOIGT: # Voigt rise time: approximate as Gaussian for simplicity rise_time = 2.563 * self.sigma else: raise ValueError(f"Unsupported signal type: {self.STYPE}") # For Gaussian signals centered at mu x_center = self.mu if self.mu is not None else 0.0 # Gaussian-specific calculations if self.STYPE == SignalTypes.GAUSS: # Time at 50% amplitude (FWHM calculation) fwhm = 2.355 * self.sigma # Full Width at Half Maximum for Gaussian # x50 is the 50% crossing on the rise (left side of peak) x50 = x_center - self.sigma * np.sqrt(-2 * np.log(0.5)) # ~0.833σ # Rise time from left 20% to left 80% (one-sided) # For amplitude ratios: x = mu ± sigma * sqrt(-2 * ln(ratio)) t_20_left = x_center - self.sigma * np.sqrt(-2 * np.log(0.2)) # ~1.794σ t_80_left = x_center - self.sigma * np.sqrt(-2 * np.log(0.8)) # ~0.668σ actual_rise_time = abs(t_80_left - t_20_left) # Fall time (symmetric for Gaussian) fall_time = actual_rise_time # Foot duration: For Gaussian, use approximation based on sigma # Since Gaussian has no true flat foot, this is an approximation foot_duration = 1.5 * self.sigma # Empirically derived approximation else: # For Lorentzian and Voigt, use approximations x50 = x_center actual_rise_time = rise_time # Use calculated rise_time fall_time = rise_time if self.STYPE == SignalTypes.LORENTZ: fwhm = 2 * self.sigma else: fwhm = 2.355 * self.sigma foot_duration = 2 * self.sigma # Approximation return ExpectedFeatures( signal_shape=SignalShape.SQUARE, polarity=polarity, amplitude=amplitude, rise_time=actual_rise_time, offset=self.y0 if self.y0 is not None else 0.0, x50=x50, x100=x_center, # Maximum is at center for Gaussian foot_duration=foot_duration, fall_time=fall_time, fwhm=fwhm, ) def get_feature_tolerances(self) -> FeatureTolerances: """Get absolute tolerance values for pulse feature validation. Returns: FeatureTolerances dataclass with adjusted tolerances for Gaussian signals """ # Gaussian signals may need slightly more relaxed tolerances due to smoothness return FeatureTolerances( rise_time=0.3, # Slightly higher tolerance for Gaussian rise time fall_time=0.3, # Match rise time tolerance x100=0.1, # Tighter tolerance for maximum position (should be exact) fwhm=0.2, # Reasonable tolerance for FWHM ) def get_crossing_time(self, edge: Literal["rise", "fall"], ratio: float) -> float: """Get the theoretical crossing time for the specified edge and ratio. Args: edge: Which edge to calculate ("rise" or "fall") ratio: Crossing ratio (0.0 to 1.0) Returns: Theoretical crossing time for the specified edge and ratio """ if self.a is None or self.sigma is None or self.mu is None: raise ValueError("Parameters 'a', 'sigma', and 'mu' must be set") if self.a == 0 or self.sigma <= 0: raise ValueError("Parameter 'a' must be non-zero and 'sigma' positive") if not 0.0 < ratio < 1.0: raise ValueError("Ratio must be between 0.0 and 1.0") if self.STYPE != SignalTypes.GAUSS: raise NotImplementedError( "Crossing time calculation is only implemented for Gaussian signals" ) # For Gaussian: x = mu ± sigma * sqrt(-2 * ln(ratio)) delta_x = self.sigma * np.sqrt(-2 * np.log(ratio)) if edge == "rise": return self.mu - delta_x if edge == "fall": return self.mu + delta_x raise ValueError("Edge must be 'rise' or 'fall'") class GaussParam( BaseGaussLorentzVoigtParam, title=_("Gaussian"), comment="y = y0 + " "A/(σ √(2π)) exp(-((x - μ)2) / (2 σ2))", ): """Parameters for Gaussian function.""" STYPE = SignalTypes.GAUSS register_signal_parameters_class(SignalTypes.GAUSS, GaussParam) class LorentzParam( BaseGaussLorentzVoigtParam, title=_("Lorentzian"), comment="y = y0 + A/(π σ (1 + ((x - μ)/σ)2))", ): """Parameters for Lorentzian function.""" STYPE = SignalTypes.LORENTZ register_signal_parameters_class(SignalTypes.LORENTZ, LorentzParam) class VoigtParam( BaseGaussLorentzVoigtParam, title=_("Voigt"), comment="y = y0 + " "A Re[exp(-z2) erfc(-j z)] / (σ √(2π)), " "with z = (x - μ - j σ) / (σ √2)", ): """Parameters for Voigt function.""" STYPE = SignalTypes.VOIGT register_signal_parameters_class(SignalTypes.VOIGT, VoigtParam) class PlanckParam( NewSignalParam, title=_("Blackbody (Planck)"), comment="y = (2 h c2) / " "(λ5 (exp(h c / (λ kB T)) - 1))", ): """Planck radiation law.""" xmin = gds.FloatItem( "λmin", default=1e-7, unit="m", min=0.0, nonzero=True ) xmax = gds.FloatItem( "λmax", default=1e-4, unit="m", min=0.0, nonzero=True ).set_prop("display", col=1) T = gds.FloatItem( "T", default=293.0, unit="K", min=0.0, nonzero=True, help=_("Temperature") ) def generate_title(self) -> str: """Generate a title based on current parameters. Returns: Title string. """ return f"planck(T={self.T:.3g}K)" @classmethod def func(cls, wavelength: np.ndarray, temperature: float) -> np.ndarray: """Compute the Planck function. Args: wavelength: Wavelength (m). T: Temperature (K). Returns: Spectral radiance (W m-2 sr-1 Hz-1). """ h = scipy.constants.h # Planck constant (J·s) c = scipy.constants.c # Speed of light (m/s) k = scipy.constants.k # Boltzmann constant (J/K) c1 = 2 * h * c**2 c2 = (h * c) / k denom = np.exp(c2 / (wavelength * temperature)) - 1.0 spectral_radiance = c1 / (wavelength**5 * (denom)) return spectral_radiance def generate_1d_data(self) -> tuple[np.ndarray, np.ndarray]: """Compute 1D data based on current parameters. Returns: Tuple of (wavelength, spectral radiance) arrays. """ wavelength = self.generate_x_data() assert self.T is not None y = self.func(wavelength, self.T) return wavelength, y register_signal_parameters_class(SignalTypes.PLANCK, PlanckParam) class FreqUnits(enum.Enum): """Frequency units""" HZ = "Hz" KHZ = "kHz" MHZ = "MHz" GHZ = "GHz" @classmethod def convert_in_hz(cls, value, unit): """Convert value in Hz""" factor = {cls.HZ: 1, cls.KHZ: 1e3, cls.MHZ: 1e6, cls.GHZ: 1e9}.get(unit) if factor is None: raise ValueError(f"Unknown unit: {unit}") return value * factor class BasePeriodicParam(NewSignalParam): """Parameters for periodic functions""" STYPE: Type[SignalTypes] | None = None def get_frequency_in_hz(self): """Return frequency in Hz""" return FreqUnits.convert_in_hz(self.freq, self.freq_unit) # Redefining some parameters with more appropriate defaults xunit = gds.StringItem(_("X unit"), default="s") a = gds.FloatItem("A", default=1.0) offset = gds.FloatItem("y0", default=0.0).set_pos(col=1) freq = gds.FloatItem("f", default=1.0) freq_unit = gds.ChoiceItem(_("Unit"), FreqUnits, default=FreqUnits.HZ).set_pos( col=1 ) phase = gds.FloatItem("φ", default=0.0, unit="°") def generate_title(self) -> str: """Generate a title based on current parameters.""" assert isinstance(self.STYPE, SignalTypes) freq_hz = self.get_frequency_in_hz() title = ( f"{self.STYPE.name.lower()}(f={freq_hz:.3g}Hz," f"A={self.a:.3g},y0={self.offset:.3g},φ={self.phase:.3g}°)" ) return title def generate_1d_data(self) -> tuple[np.ndarray, np.ndarray]: """Compute 1D data based on current parameters. Returns: Tuple of (x, y) arrays """ x = self.generate_x_data() func = { SignalTypes.SINE: np.sin, SignalTypes.COSINE: np.cos, SignalTypes.SAWTOOTH: sps.sawtooth, SignalTypes.TRIANGLE: triangle_func, SignalTypes.SQUARE: sps.square, SignalTypes.SINC: np.sinc, }[self.STYPE] freq = self.get_frequency_in_hz() y = self.a * func(2 * np.pi * freq * x + np.deg2rad(self.phase)) + self.offset return x, y class SineParam( BasePeriodicParam, title=_("Sine"), comment="y = y0 + A sin(2π f x + φ)" ): """Parameters for sine function.""" STYPE = SignalTypes.SINE register_signal_parameters_class(SignalTypes.SINE, SineParam) class CosineParam( BasePeriodicParam, title=_("Cosine"), comment="y = y0 + A cos(2π f x + φ)", ): """Parameters for cosine function.""" STYPE = SignalTypes.COSINE register_signal_parameters_class(SignalTypes.COSINE, CosineParam) class SawtoothParam( BasePeriodicParam, title=_("Sawtooth"), comment="y = y0 + A (2 (f x + φ/(2π) - |f x + φ/(2π) + 1/2|))", ): """Parameters for sawtooth function.""" STYPE = SignalTypes.SAWTOOTH register_signal_parameters_class(SignalTypes.SAWTOOTH, SawtoothParam) class TriangleParam( BasePeriodicParam, title=_("Triangle"), comment="y = y0 + A sawtooth(2π f x + φ, width=0.5)", ): """Parameters for triangle function.""" STYPE = SignalTypes.TRIANGLE register_signal_parameters_class(SignalTypes.TRIANGLE, TriangleParam) class SquareParam( BasePeriodicParam, title=_("Square"), comment="y = y0 + A sgn(sin(2π f x + φ))", ): """Parameters for square function.""" STYPE = SignalTypes.SQUARE register_signal_parameters_class(SignalTypes.SQUARE, SquareParam) class SincParam( BasePeriodicParam, title=_("Cardinal sine"), comment="y = y0 + A sinc(f x + φ)", ): """Parameters for cardinal sine function.""" STYPE = SignalTypes.SINC register_signal_parameters_class(SignalTypes.SINC, SincParam) class LinearChirpParam( NewSignalParam, title=_("Linear chirp"), comment="y = y0 + a sin(φ0 " "+ 2π (f0 x + 0.5 k x²))", ): """Linear chirp function.""" a = gds.FloatItem("A", default=1.0, help=_("Amplitude")) phi0 = gds.FloatItem( "φ0", default=0.0, help=_("Initial phase") ).set_prop("display", col=1) k = gds.FloatItem("k", default=1.0, help=_("Chirp rate (f-2)")) offset = gds.FloatItem( "y0", default=0.0, help=_("Vertical offset") ).set_prop("display", col=1) f0 = gds.FloatItem("f0", default=1.0, help=_("Initial frequency (Hz)")) def generate_title(self) -> str: """Generate a title based on current parameters. Returns: Title string. """ return ( f"chirp(A={self.a:.3g}," f"k={self.k:.3g}," f"f0={self.f0:.3g}," f"φ0={self.phi0:.3g}," f"y0={self.offset:.3g})" ) @classmethod def func( cls, x: np.ndarray, a: float, k: float, f0: float, phi0: float, offset: float ) -> np.ndarray: """Compute the linear chirp function. Args: x: X data array. a: Amplitude. k: Chirp rate (s-2). f0: Initial frequency (Hz). phi0: Initial phase. offset: Vertical offset. Returns: Y data array computed using the chirp function. """ phase = phi0 + 2 * np.pi * (f0 * x + 0.5 * k * x**2) return offset + a * np.sin(phase) def generate_1d_data(self) -> tuple[np.ndarray, np.ndarray]: """Compute 1D data based on current parameters. Returns: Tuple of (x, y) arrays. """ assert self.a is not None assert self.k is not None assert self.f0 is not None assert self.phi0 is not None assert self.offset is not None x = self.generate_x_data() y = self.func(x, self.a, self.k, self.f0, self.phi0, self.offset) return x, y register_signal_parameters_class(SignalTypes.LINEARCHIRP, LinearChirpParam) class StepParam(NewSignalParam, title=_("Step")): """Parameters for step function.""" a1 = gds.FloatItem("A1", default=0.0) a2 = gds.FloatItem("A2", default=1.0).set_pos(col=1) x0 = gds.FloatItem("x0", default=0.0) def generate_title(self) -> str: """Generate a title based on current parameters.""" return f"step(a1={self.a1:.3g},a2={self.a2:.3g},x0={self.x0:.3g})" def generate_1d_data(self) -> tuple[np.ndarray, np.ndarray]: """Compute 1D data based on current parameters. Returns: Tuple of (x, y) arrays """ x = self.generate_x_data() y = np.ones_like(x) * self.a1 y[x > self.x0] = self.a2 return x, y register_signal_parameters_class(SignalTypes.STEP, StepParam) class ExponentialParam( NewSignalParam, title=_("Exponential"), comment="y = A exp(B x) + y0" ): """Parameters for exponential function.""" a = gds.FloatItem("A", default=1.0) offset = gds.FloatItem("y0", default=0.0) exponent = gds.FloatItem("B", default=1.0) def generate_title(self) -> str: """Generate a title based on current parameters.""" return f"exponential(A={self.a:.3g},B={self.exponent:.3g},y0={self.offset:.3g})" def generate_1d_data(self) -> tuple[np.ndarray, np.ndarray]: """Compute 1D data based on current parameters. Returns: Tuple of (x, y) arrays """ x = self.generate_x_data() y = self.a * np.exp(self.exponent * x) + self.offset return x, y register_signal_parameters_class(SignalTypes.EXPONENTIAL, ExponentialParam) class LogisticParam( NewSignalParam, title=_("Logistic"), comment="y = y0 + A / (1 + exp(-k (x - x0)))", ): """Logistic function.""" a = gds.FloatItem("A", default=1.0, help=_("Amplitude")) x0 = gds.FloatItem( "x0", default=0.0, help=_("Horizontal offset") ).set_prop("display", col=1) k = gds.FloatItem("k", default=1.0, help=_("Growth or decay rate")) offset = gds.FloatItem( "y0", default=0.0, help=_("Vertical offset") ).set_prop("display", col=1) def generate_title(self) -> str: """Generate a title based on current parameters. Returns: Title string. """ return ( f"logistic(A={self.a:.3g}," f"k={self.k:.3g}," f"x0={self.x0:.3g}," f"y0={self.offset:.3g})" ) @classmethod def func( cls, x: np.ndarray, a: float, k: float, x0: float, offset: float ) -> np.ndarray: """Compute the logistic function. Args: x: X data array. a: Amplitude. k: Growth or decay rate. x0: Horizontal offset. offset: Vertical offset. Returns: Y data array computed using the logistic function. """ return offset + a / (1.0 + np.exp(-k * (x - x0))) def generate_1d_data(self) -> tuple[np.ndarray, np.ndarray]: """Compute 1D data based on current parameters. Returns: Tuple of (x, y) arrays. """ assert self.a is not None assert self.k is not None assert self.x0 is not None assert self.offset is not None x = self.generate_x_data() y = self.func(x, self.a, self.k, self.x0, self.offset) return x, y register_signal_parameters_class(SignalTypes.LOGISTIC, LogisticParam) class PulseParam(NewSignalParam, title=_("Pulse")): """Parameters for pulse function.""" amp = gds.FloatItem("Amplitude", default=1.0) start = gds.FloatItem(_("Start"), default=0.0).set_pos(col=1) offset = gds.FloatItem(_("Offset"), default=10.0) stop = gds.FloatItem(_("End"), default=5.0).set_pos(col=1) def generate_title(self) -> str: """Generate a title based on current parameters.""" return ( f"pulse(start={self.start:.3g},stop={self.stop:.3g}," f"offset={self.offset:.3g},amp={self.amp:.3g})" ) def generate_1d_data(self) -> tuple[np.ndarray, np.ndarray]: """Compute 1D data based on current parameters. Returns: Tuple of (x, y) arrays """ x = self.generate_x_data() y = np.full_like(x, self.offset) y[(x >= self.start) & (x <= self.stop)] += self.amp return x, y register_signal_parameters_class(SignalTypes.PULSE, PulseParam) @dataclass class ExpectedFeatures: """Expected pulse feature values for validation.""" signal_shape: SignalShape polarity: int amplitude: float rise_time: float # Rise time between specified ratios offset: float x50: float x100: float # Time at 100% amplitude (maximum) foot_duration: float fall_time: float | None = None # Fall time between specified ratios fwhm: float | None = None @dataclass class FeatureTolerances: """Absolute tolerance values for pulse feature validation.""" polarity: float = 1e-8 amplitude: float = 0.5 rise_time: float = 0.2 offset: float = 0.5 x50: float = 0.1 x100: float = 0.6 # Tolerance for time at 100% amplitude foot_duration: float = 0.5 fall_time: float = 1.0 fwhm: float = 0.5 class BasePulseParam(NewSignalParam): """Base class for pulse signal parameters.""" SEED = 0 # Redefine NewSignalParam parameters with more appropriate defaults xmin = gds.FloatItem(_("Start time"), default=0.0) xmax = gds.FloatItem(_("End time"), default=10.0) size = gds.IntItem(_("Number of points"), default=1000, min=1) # Specific pulse parameters offset = gds.FloatItem(_("Initial value"), default=0.0) amplitude = gds.FloatItem(_("Amplitude"), default=5.0).set_pos(col=1) noise_amplitude = gds.FloatItem(_("Noise amplitude"), default=0.2, min=0.0) x_rise_start = gds.FloatItem(_("Rise start time"), default=3.0, min=0.0) total_rise_time = gds.FloatItem(_("Total rise time"), default=2.0, min=0.0).set_pos( col=1 ) def get_crossing_time(self, edge: Literal["rise", "fall"], ratio: float) -> float: """Get the theoretical crossing time for the specified edge and ratio. Args: edge: Which edge to calculate ("rise" or "fall") ratio: Crossing ratio (0.0 to 1.0) Returns: Theoretical crossing time for the specified edge and ratio """ if edge == "rise": return self.x_rise_start + ratio * self.total_rise_time raise NotImplementedError( "Fall edge crossing time not implemented for this signal type" ) def get_expected_features( self, start_ratio: float = 0.1, stop_ratio: float = 0.9 ) -> ExpectedFeatures: """Calculate expected pulse features for this signal. Args: start_ratio: Start ratio for rise time calculation stop_ratio: Stop ratio for rise time calculation Returns: ExpectedFeatures dataclass with all expected values """ y_end_value = self.offset + self.amplitude return ExpectedFeatures( signal_shape=SignalShape.STEP, polarity=1 if y_end_value > self.offset else -1, amplitude=abs(y_end_value - self.offset), rise_time=(stop_ratio - start_ratio) * self.total_rise_time, offset=self.offset, x50=self.x_rise_start + 0.5 * self.total_rise_time, x100=self.x_rise_start + self.total_rise_time, foot_duration=self.x_rise_start - self.xmin, ) def get_feature_tolerances(self) -> FeatureTolerances: """Get absolute tolerance values for pulse feature validation. Returns: FeatureTolerances dataclass with default tolerance values """ return FeatureTolerances() class StepPulseParam(BasePulseParam, title=_("Step pulse with noise")): """Parameters for generating step signals with configurable rise time.""" def generate_title(self) -> str: """Generate a title based on current parameters.""" return ( f"step_pulse(rise_time={self.total_rise_time:.3g}," f"x_start={self.x_rise_start:.3g},offset={self.offset:.3g}," f"amp={self.amplitude:.3g})" ) def generate_1d_data(self) -> tuple[np.ndarray, np.ndarray]: """Generate a noisy step signal with a linear rise. The function creates a time vector and generates a signal that starts at `offset`, rises linearly to `offset + amplitude` starting at `x_rise_start` over a duration of `total_rise_time`, and remains at the final value afterwards. Gaussian noise is added to the signal. Returns: Tuple containing the time vector and noisy step signal. """ # time vector x = self.generate_x_data() # Calculate final value from offset and amplitude y_final = self.offset + self.amplitude # creating the signal rise_end_time = self.x_rise_start + self.total_rise_time y = np.piecewise( x, [ x < self.x_rise_start, (x >= self.x_rise_start) & (x < rise_end_time), x >= rise_end_time, ], [ self.offset, lambda t: ( self.offset + (y_final - self.offset) * (t - self.x_rise_start) / self.total_rise_time ), y_final, ], ) rdg = np.random.default_rng(self.SEED) noise = rdg.normal(0, self.noise_amplitude, size=len(y)) y_noisy = y + noise return x, y_noisy register_signal_parameters_class(SignalTypes.STEP_PULSE, StepPulseParam) class SquarePulseParam(BasePulseParam, title=_("Square pulse with noise")): """Parameters for generating square signals with configurable rise/fall times.""" # Redefine NewSignalParam parameters with more appropriate defaults xmax = gds.FloatItem(_("End time"), default=20.0) # Specific square pulse parameters fwhm = gds.FloatItem(_("Full Width at Half Maximum"), default=5.5, min=0.0) total_fall_time = gds.FloatItem(_("Total fall time"), default=5.0, min=0.0).set_pos( col=1 ) @property def square_duration(self) -> float: """Calculate the square duration from FWHM and total rise/fall times.""" return self.fwhm - 0.5 * self.total_rise_time - 0.5 * self.total_fall_time def get_plateau_range(self) -> tuple[float, float]: """Get the theoretical plateau range (start, end) for the square signal. Returns: Tuple with (start, end) times of the plateau """ return ( self.x_rise_start + self.total_rise_time, self.x_rise_start + self.total_rise_time + self.square_duration, ) def get_crossing_time(self, edge: Literal["rise", "fall"], ratio: float) -> float: """Get the theoretical crossing time for the specified edge and ratio. Args: edge: Which edge to calculate ("rise" or "fall") ratio: Crossing ratio (0.0 to 1.0) Returns: Theoretical crossing time for the specified edge and ratio """ if edge == "rise": return super().get_crossing_time(edge, ratio) if edge == "fall": t_start_fall = ( self.x_rise_start + self.total_rise_time + self.square_duration ) return t_start_fall + ratio * self.total_fall_time raise ValueError("edge must be 'rise' or 'fall'") def get_expected_features( self, start_ratio: float = 0.1, stop_ratio: float = 0.9 ) -> ExpectedFeatures: """Calculate expected pulse features for this signal. Args: start_ratio: Start ratio for rise time calculation stop_ratio: Stop ratio for rise time calculation Returns: ExpectedFeatures dataclass with all expected values """ features = super().get_expected_features(start_ratio, stop_ratio) features.signal_shape = SignalShape.SQUARE features.fall_time = np.abs(stop_ratio - start_ratio) * self.total_fall_time features.fwhm = self.fwhm return features def get_feature_tolerances(self) -> FeatureTolerances: """Get absolute tolerance values for square signal feature validation. Returns: FeatureTolerances dataclass with square-specific tolerance values """ return FeatureTolerances( x100=0.8, # Looser tolerance for square signals ) def generate_title(self) -> str: """Generate a title based on current parameters.""" return ( f"square_pulse(rise_time={self.total_rise_time:.3g}," f"fall_time={self.total_fall_time:.3g}," f"fwhm={self.fwhm:.3g},offset={self.offset:.3g}," f"amp={self.amplitude:.3g})" ) def generate_1d_data(self) -> tuple[np.ndarray, np.ndarray]: """Generate a synthetic square-like signal with configurable parameters. Generates a synthetic square-like signal with configurable rise, plateau, and fall times, and adds Gaussian noise. Returns: Tuple containing the time vector and noisy square signal. """ # time vector x = self.generate_x_data() # Calculate high value from offset and amplitude y_high = self.offset + self.amplitude x_rise_end = self.x_rise_start + self.total_rise_time x_start_fall = self.x_rise_start + self.total_rise_time + self.square_duration # creating the signal y = np.piecewise( x, [ x < self.x_rise_start, (x >= self.x_rise_start) & (x < x_rise_end), (x >= x_rise_end) & (x < x_start_fall), (x >= x_start_fall) & (x < x_start_fall + self.total_fall_time), x >= self.total_fall_time + x_start_fall, ], [ self.offset, lambda t: ( self.offset + (y_high - self.offset) * (t - self.x_rise_start) / self.total_rise_time ), y_high, lambda t: y_high - (y_high - self.offset) * (t - x_start_fall) / self.total_fall_time, self.offset, ], ) rdg = np.random.default_rng(self.SEED) noise = rdg.normal(0, self.noise_amplitude, size=len(y)) y_noisy = y + noise return x, y_noisy register_signal_parameters_class(SignalTypes.SQUARE_PULSE, SquarePulseParam) class PolyParam(NewSignalParam, title=_("Polynomial")): """Parameters for polynomial function.""" a0 = gds.FloatItem("a0", default=1.0) a3 = gds.FloatItem("a3", default=0.0).set_pos(col=1) a1 = gds.FloatItem("a1", default=1.0) a4 = gds.FloatItem("a4", default=0.0).set_pos(col=1) a2 = gds.FloatItem("a2", default=0.0) a5 = gds.FloatItem("a5", default=0.0).set_pos(col=1) def generate_title(self) -> str: """Generate a title based on current parameters.""" coeffs = [self.a0, self.a1, self.a2, self.a3, self.a4, self.a5] terms = [] for i, coeff in enumerate(coeffs): if coeff == 0: continue # Format coefficient if i == 0: # Constant term terms.append(f"{coeff:.3g}") elif i == 1: # Linear term if coeff == 1: terms.append("x") elif coeff == -1: terms.append("-x") else: terms.append(f"{coeff:.3g}x") else: # Higher order terms if coeff == 1: terms.append(f"x^{i}") elif coeff == -1: terms.append(f"-x^{i}") else: terms.append(f"{coeff:.3g}x^{i}") if not terms: return "0" # Join terms with + or - signs result = terms[0] for term in terms[1:]: if term.startswith("-"): result += term else: result += f"+{term}" return result def generate_1d_data(self) -> tuple[np.ndarray, np.ndarray]: """Compute 1D data based on current parameters. Returns: Tuple of (x, y) arrays """ x = self.generate_x_data() y = np.polyval([self.a5, self.a4, self.a3, self.a2, self.a1, self.a0], x) return x, y register_signal_parameters_class(SignalTypes.POLYNOMIAL, PolyParam) class CustomSignalParam(NewSignalParam, title=_("Custom signal")): """Parameters for custom signal (e.g. manually defined experimental data).""" size = gds.IntItem(_("Npoints"), default=10).set_prop( "display", active=False ) xmin = gds.FloatItem("xmin", default=0.0).set_prop( "display", active=False ) xmax = gds.FloatItem("xmax", default=1.0).set_prop( "display", active=False, col=1 ) xyarray = gds.FloatArrayItem( "XY Values", format="%g", ) def setup_array( self, size: int | None = None, xmin: float | None = None, xmax: float | None = None, ) -> None: """Setup the xyarray from size, xmin and xmax (use the current values is not provided) Args: size: xyarray size (default: None) xmin: X min (default: None) xmax: X max (default: None) """ self.size = size or self.size self.xmin = xmin or self.xmin self.xmax = xmax or self.xmax x_arr = np.linspace(self.xmin, self.xmax, self.size) # type: ignore self.xyarray = np.vstack((x_arr, x_arr)).T def generate_title(self) -> str: """Generate a title based on current parameters.""" return f"custom(size={self.size})" def generate_1d_data(self) -> tuple[np.ndarray, np.ndarray]: """Compute 1D data based on current parameters. Returns: Tuple of (x, y) arrays """ self.setup_array(size=self.size, xmin=self.xmin, xmax=self.xmax) x, y = self.xyarray.T return x, y register_signal_parameters_class(SignalTypes.CUSTOM, CustomSignalParam) check_all_signal_parameters_classes() def triangle_func(xarr: np.ndarray) -> np.ndarray: """Triangle function Args: xarr: x data """ # ignore warning, as type hint is not handled properly in upstream library return sps.sawtooth(xarr, width=0.5) # type: ignore[no-untyped-def] SIG_NB = 0 def get_next_signal_number() -> int: """Get the next signal number. This function is used to keep track of the number of signals created. It is typically used to generate unique titles for new signals. Returns: int: new signal number """ global SIG_NB # pylint: disable=global-statement SIG_NB += 1 return SIG_NB def create_signal_from_param(param: NewSignalParam) -> SignalObj: """Create a new Signal object from parameters. Args: param: new signal parameters Returns: Signal object Raises: NotImplementedError: if the signal type is not supported """ # Generate data first, as some `generate_title()` methods may depend on it: x, y = param.generate_1d_data() # Check if user has customized the title or left it as default/empty use_generated_title = not param.title or param.title == DEFAULT_TITLE if use_generated_title: # Try to generate a descriptive title gen_title = getattr(param, "generate_title", lambda: "")() if gen_title: title = gen_title else: # No generated title available, use default with number title = f"{DEFAULT_TITLE} {get_next_signal_number():d}" else: # User has set a custom title, use it as-is title = param.title signal = create_signal( title, x, y, units=(param.xunit, param.yunit), labels=(param.xlabel, param.ylabel), ) return signal Sigima-1.1.1/sigima/objects/signal/object.py000066400000000000000000000452631514013333200207270ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """Signal object class =================== This module provides the main SignalObj class for handling 1D signal data. The module includes: - `SignalObj`: Main class for signal data management and operations The SignalObj class supports: - Signal data storage with x, y coordinates - Error bars (dx, dy) for uncertainty quantification - Metadata and annotations - ROI (Region of Interest) operations - Axis labels and units management - Copy operations with type conversion """ # pylint: disable=invalid-name # Allows short reference names like x, y, ... # pylint: disable=duplicate-code from __future__ import annotations from typing import Type import guidata.dataset as gds import numpy as np import pandas as pd from sigima.config import _ from sigima.objects import base from sigima.objects.signal.constants import ( DATETIME_X_FORMAT_KEY, DATETIME_X_KEY, DEFAULT_DATETIME_FORMAT, VALID_TIME_UNITS, ) from sigima.objects.signal.roi import SignalROI def validate_and_convert_dtype(x: np.ndarray) -> np.ndarray: """Check if data type is valid, convert integer to float64 if needed. Args: x: Input array Returns: Original array if data type is valid, array converted to float64 if integer Raises: ValueError: If data type is not valid """ if np.issubdtype(x.dtype, np.integer): return x.astype(np.float64) if x.dtype not in SignalObj.VALID_DTYPES: raise ValueError( f"Invalid data type: {x.dtype}. " f"Valid types: {', '.join(str(dt) for dt in SignalObj.VALID_DTYPES)}" ) return x class SignalObj(gds.DataSet, base.BaseObj[SignalROI]): """Signal object""" PREFIX = "s" VALID_DTYPES = (np.float32, np.float64, np.complex128) _tabs = gds.BeginTabGroup("all") _datag = gds.BeginGroup(_("Data and metadata")) title = gds.StringItem(_("Signal title"), default=_("Untitled")) xydata = gds.FloatArrayItem(_("Data"), transpose=True, minmax="rows") metadata = gds.DictItem(_("Metadata"), default={}) # type: ignore[assignment] annotations = gds.StringItem(_("Annotations"), default="").set_prop( "display", hide=True, ) # Annotations (JSON). Use get/set_annotations() API # type: ignore[assignment] _e_datag = gds.EndGroup(_("Data and metadata")) _unitsg = gds.BeginGroup(_("Titles / Units")) title = gds.StringItem(_("Signal title"), default=_("Untitled")) _tabs_u = gds.BeginTabGroup("units") _unitsx = gds.BeginGroup(_("X-axis")) xlabel = gds.StringItem(_("Title"), default="") xunit = gds.StringItem(_("Unit"), default="") _e_unitsx = gds.EndGroup(_("X-axis")) _unitsy = gds.BeginGroup(_("Y-axis")) ylabel = gds.StringItem(_("Title"), default="") yunit = gds.StringItem(_("Unit"), default="") _e_unitsy = gds.EndGroup(_("Y-axis")) _e_tabs_u = gds.EndTabGroup("units") _e_unitsg = gds.EndGroup(_("Titles / Units")) _scalesg = gds.BeginGroup(_("Scales")) _prop_autoscale = gds.GetAttrProp("autoscale") autoscale = gds.BoolItem(_("Auto scale"), default=True).set_prop( "display", store=_prop_autoscale ) _tabs_b = gds.BeginTabGroup("bounds") _boundsx = gds.BeginGroup(_("X-axis")) xscalelog = gds.BoolItem(_("Logarithmic scale"), default=False) xscalemin = gds.FloatItem(_("Lower bound"), check=False).set_prop( "display", active=gds.NotProp(_prop_autoscale) ) xscalemax = gds.FloatItem(_("Upper bound"), check=False).set_prop( "display", active=gds.NotProp(_prop_autoscale) ) _e_boundsx = gds.EndGroup(_("X-axis")) _boundsy = gds.BeginGroup(_("Y-axis")) yscalelog = gds.BoolItem(_("Logarithmic scale"), default=False) yscalemin = gds.FloatItem(_("Lower bound"), check=False).set_prop( "display", active=gds.NotProp(_prop_autoscale) ) yscalemax = gds.FloatItem(_("Upper bound"), check=False).set_prop( "display", active=gds.NotProp(_prop_autoscale) ) _e_boundsy = gds.EndGroup(_("Y-axis")) _e_tabs_b = gds.EndTabGroup("bounds") _e_scalesg = gds.EndGroup(_("Scales")) _e_tabs = gds.EndTabGroup("all") def __init__(self, title=None, comment=None, icon=""): """Constructor Args: title: title comment: comment icon: icon """ gds.DataSet.__init__(self, title, comment, icon) base.BaseObj.__init__(self) @staticmethod def get_roi_class() -> Type[SignalROI]: """Return ROI class""" return SignalROI def copy( self, title: str | None = None, dtype: np.dtype | None = None, all_metadata: bool = False, ) -> SignalObj: """Copy object. Args: title: title dtype: data type all_metadata: if True, copy all metadata, otherwise only basic metadata Returns: Copied object """ title = self.title if title is None else title obj = SignalObj(title=title) obj.title = title obj.xlabel = self.xlabel obj.ylabel = self.ylabel obj.xunit = self.xunit obj.yunit = self.yunit if dtype not in (None, float, complex, np.complex128): raise RuntimeError("Signal data only supports float64/complex128 dtype") obj.metadata = base.deepcopy_metadata(self.metadata, all_metadata=all_metadata) obj.annotations = self.annotations obj.xydata = np.array(self.xydata, copy=True, dtype=dtype) obj.autoscale = self.autoscale obj.xscalelog = self.xscalelog obj.xscalemin = self.xscalemin obj.xscalemax = self.xscalemax obj.yscalelog = self.yscalelog obj.yscalemin = self.yscalemin obj.yscalemax = self.yscalemax return obj def set_data_type(self, dtype: np.dtype) -> None: # pylint: disable=unused-argument """Change data type. Args: Data type """ raise RuntimeError("Setting data type is not support for signals") def set_xydata( self, x: np.ndarray | list | None, y: np.ndarray | list | None, dx: np.ndarray | list | None = None, dy: np.ndarray | list | None = None, ) -> None: """Set xy data Args: x: x data y: y data dx: dx data (optional: error bars). Use None to reset dx data to None, or provide array to set new dx data. dy: dy data (optional: error bars). Use None to reset dy data to None, or provide array to set new dy data. """ if x is None and y is None: # Using empty arrays (this allows initialization of the object without data) x = np.array([], dtype=np.float64) y = np.array([], dtype=np.float64) if x is None and y is not None: # If x is None, we create a default x array based on the length of y assert isinstance(y, (list, np.ndarray)) x = np.arange(len(y), dtype=np.float64) if x is not None: x = np.array(x) if y is not None: y = np.array(y) if dx is not None: dx = np.array(dx) if dy is not None: dy = np.array(dy) if dx is None and dy is None: xydata = np.vstack([x, y]) else: if dx is None: dx = np.full_like(x, np.nan) if dy is None: dy = np.full_like(y, np.nan) assert x is not None and y is not None xydata = np.vstack((x, y, dx, dy)) self.xydata = validate_and_convert_dtype(xydata) def __get_x(self) -> np.ndarray | None: """Get x data""" if self.xydata is not None: x: np.ndarray = self.xydata[0] # We have to ensure that x is a floating point array, because if y is # complex, the whole xydata array will be complex, and we need to avoid # any unintended type promotion. return x.real.astype(float) return None def __set_x(self, data: np.ndarray | list[float]) -> None: """Set x data""" assert isinstance(self.xydata, np.ndarray) assert isinstance(data, (list, np.ndarray)) data = np.array(data, dtype=float) assert data.shape[0] == self.xydata.shape[1], ( "X data size must match Y data size" ) if not np.all(np.diff(data) >= 0.0): raise ValueError("X data must be monotonic (sorted in ascending order)") self.xydata[0] = validate_and_convert_dtype(data) def __get_y(self) -> np.ndarray | None: """Get y data""" if self.xydata is not None: return self.xydata[1] return None def __set_y(self, data: np.ndarray | list[float]) -> None: """Set y data""" assert isinstance(self.xydata, np.ndarray) assert isinstance(data, (list, np.ndarray)) data = np.array(data) assert data.shape[0] == self.xydata.shape[1], ( "Y data size must match X data size" ) assert np.issubdtype(data.dtype, np.inexact), "Y data must be float or complex" self.xydata[1] = validate_and_convert_dtype(data) def __get_dx(self) -> np.ndarray | None: """Get dx data""" if self.xydata is not None and len(self.xydata) == 4: dx: np.ndarray = self.xydata[2] if np.all(np.isnan(dx)): return None return dx.real.astype(float) return None def __set_dx(self, data: np.ndarray | list[float] | None) -> None: """Set dx data""" if data is None: data = np.full_like(self.x, np.nan) assert isinstance(data, (list, np.ndarray)) data = np.array(data) if self.xydata is None: raise ValueError("Signal data not initialized") assert data.shape[0] == self.xydata.shape[1], ( "dx data size must match X data size" ) if len(self.xydata) == 2: self.xydata = np.vstack((self.xydata, np.zeros((2, self.xydata.shape[1])))) self.xydata[2] = validate_and_convert_dtype(data) def __get_dy(self) -> np.ndarray | None: """Get dy data""" if self.xydata is not None and len(self.xydata) == 4: dy: np.ndarray = self.xydata[3] if np.all(np.isnan(dy)): return None return dy return None def __set_dy(self, data: np.ndarray | list[float] | None) -> None: """Set dy data""" if data is None: data = np.full_like(self.x, np.nan) assert isinstance(data, (list, np.ndarray)) data = np.array(data) if self.xydata is None: raise ValueError("Signal data not initialized") assert data.shape[0] == self.xydata.shape[1], ( "dy data size must match X data size" ) if len(self.xydata) == 2: self.xydata = np.vstack((self.xydata, np.zeros((2, self.xydata.shape[1])))) self.xydata[3] = validate_and_convert_dtype(data) x = property(__get_x, __set_x) y = data = property(__get_y, __set_y) dx = property(__get_dx, __set_dx) dy = property(__get_dy, __set_dy) def _repr_html_(self) -> str: """Return HTML representation for Jupyter notebook display. This method is automatically called by Jupyter when displaying the object as a cell output, providing a rich HTML rendering of the signal object. Returns: HTML representation of the signal with summary statistics. """ n_points = len(self.x) if self.x is not None else 0 x_min = f"{self.x.min():.4g}" if n_points > 0 else "N/A" x_max = f"{self.x.max():.4g}" if n_points > 0 else "N/A" y_min = f"{self.y.min():.4g}" if n_points > 0 else "N/A" y_max = f"{self.y.max():.4g}" if n_points > 0 else "N/A" dtype_str = str(self.y.dtype) if self.y is not None else "N/A" # Build axis labels with optional title x_label = "X" if self.xlabel: x_label = f"X ({self.xlabel})" y_label = "Y" if self.ylabel: y_label = f"Y ({self.ylabel})" html = f'SignalObj: {self.title}:' html += '' html += f"" html += ( f"" f"" html += ( f"" f"" html += ( f"" ) if self.roi is not None: html += ( f"" f"" ) html += "
Points:{n_points}
{x_label} range:[{x_min}, {x_max}]" ) if self.xunit: html += f" {self.xunit}" html += "
{y_label} range:[{y_min}, {y_max}]" ) if self.yunit: html += f" {self.yunit}" html += "
Data type:{dtype_str}
ROIs:{len(self.roi)}
" return html def get_data(self, roi_index: int | None = None) -> tuple[np.ndarray, np.ndarray]: """ Return original data (if ROI is not defined or `roi_index` is None), or ROI data (if both ROI and `roi_index` are defined). Args: roi_index: ROI index Returns: Data """ if self.roi is None or roi_index is None: assert isinstance(self.xydata, np.ndarray) return self.x, self.y single_roi = self.roi.get_single_roi(roi_index) return single_roi.get_data(self) def physical_to_indices(self, coords: list[float]) -> list[int]: """Convert coordinates from physical (real world) to indices (pixel) Args: coords: coordinates Returns: Indices """ assert isinstance(self.x, np.ndarray) return [int(np.abs(self.x - x).argmin()) for x in coords] def indices_to_physical(self, indices: list[int]) -> list[float]: """Convert coordinates from indices to physical (real world) Args: indices: indices Returns: Coordinates """ # We take the real part of the x data to avoid `ComplexWarning` warnings # when creating and manipulating the `XRangeSelection` shape (`plotpy`) return self.x.real[indices].tolist() def is_x_datetime(self) -> bool: """Check if x data represents datetime values. Returns: True if x data represents datetime values, False otherwise """ return self.metadata.get(DATETIME_X_KEY, False) def set_x_from_datetime( self, dt_array: np.ndarray | list, unit: str = "s", format_str: str | None = None, ) -> None: """Set x values from datetime objects or strings. This method converts datetime data to float timestamps (Unix time: seconds since 1970-01-01) for efficient storage and computation. The datetime context is preserved through metadata. Note: X values are always stored as Unix timestamps (seconds since 1970-01-01) regardless of the 'unit' parameter. The 'unit' parameter is stored in metadata and used only for axis labeling when plotting. Args: dt_array: Array of datetime objects, datetime strings, or numpy datetime64 unit: Time unit label for display. Options: 's' (seconds), 'ms' (milliseconds), 'us' (microseconds), 'ns' (nanoseconds), 'min' (minutes), 'h' (hours). Default is 's'. This parameter only affects the axis label, not the stored data. format_str: Format string for datetime display. If None, uses default. Raises: ValueError: If unit is not valid Example: >>> from datetime import datetime >>> signal = SignalObj() >>> timestamps = [datetime(2025, 1, 1, 10, 0, 0), ... datetime(2025, 1, 1, 10, 0, 1)] >>> signal.set_x_from_datetime(timestamps, unit='s') >>> signal.is_x_datetime() True >>> # X data is stored as Unix timestamps (seconds since 1970) >>> signal.x[0] > 1.7e9 # Year 2025 True """ if unit not in VALID_TIME_UNITS: raise ValueError( f"Invalid unit: {unit}. Must be one of: {', '.join(VALID_TIME_UNITS)}" ) # Convert to pandas datetime (handles strings, datetime objects, etc.) dt_series = pd.to_datetime(dt_array) # Convert to float timestamp in seconds (pandas epoch is in nanoseconds) # Note: We always store as Unix timestamps (seconds since 1970-01-01) # regardless of the 'unit' parameter, which is only for display purposes timestamp_seconds = dt_series.astype(np.int64) / 1e9 # Convert to numpy array (pandas may return Float64Index) x_float = np.array(timestamp_seconds, dtype=np.float64) # Check if signal already has data with matching size if self.xydata is not None and self.xydata.shape[1] == len(x_float): # Signal already has matching data, just update x self.x = x_float else: # Initialize or reinitialize signal with x data (y will be zeros) y_placeholder = np.zeros_like(x_float) self.set_xydata(x_float, y_placeholder) # Store metadata self.metadata[DATETIME_X_KEY] = True self.metadata[DATETIME_X_FORMAT_KEY] = ( format_str if format_str is not None else DEFAULT_DATETIME_FORMAT ) # Store unit in xunit attribute (more intuitive than metadata) self.xunit = unit def get_x_as_datetime(self) -> np.ndarray: """Get x values as datetime objects if x is datetime data. Returns x data as numpy datetime64 array if the signal contains datetime data, otherwise returns the regular x data as floats. Returns: Array of datetime64 objects if x is datetime data, otherwise regular x array Example: >>> signal.set_x_from_datetime([datetime(2025, 1, 1, 10, 0, 0)]) >>> dt_values = signal.get_x_as_datetime() >>> isinstance(dt_values[0], np.datetime64) True """ if not self.is_x_datetime(): return self.x # X values are always stored as Unix timestamps (seconds since 1970-01-01) # regardless of the 'unit' parameter x_float = self.x # Convert seconds to datetime using pandas return pd.to_datetime(x_float, unit="s").to_numpy() Sigima-1.1.1/sigima/objects/signal/roi.py000066400000000000000000000223141514013333200202420ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Signal ROI utilities ==================== This module provides Region of Interest (ROI) classes and utilities for signal objects. The module includes: - `ROI1DParam`: Parameter class for 1D signal ROIs - `SegmentROI`: Single ROI representing a segment of a signal - `SignalROI`: Collection of signal ROIs with operations - `create_signal_roi`: Factory function for creating signal ROI objects These classes enable defining and working with regions of interest in 1D signal data, supporting operations like data extraction, masking, and parameter conversion. """ # pylint: disable=invalid-name # Allows short reference names like x, y, ... # pylint: disable=duplicate-code from __future__ import annotations from typing import TYPE_CHECKING, Type import guidata.dataset as gds import numpy as np from sigima.config import _ from sigima.objects import base if TYPE_CHECKING: from sigima.objects.signal.object import SignalObj class ROI1DParam(base.BaseROIParam["SignalObj", "SegmentROI"]): """Signal ROI parameters""" # Note: in this class, the ROI parameters are stored as X coordinates title = gds.StringItem(_("ROI title"), default="") xmin = gds.FloatItem(_("First point coordinate"), default=0.0) xmax = gds.FloatItem(_("Last point coordinate"), default=1.0) def to_single_roi(self, obj: SignalObj) -> SegmentROI: """Convert parameters to single ROI Args: obj: signal object Returns: Single ROI """ assert isinstance(self.xmin, float) and isinstance(self.xmax, float) return SegmentROI([self.xmin, self.xmax], False, title=self.title) def get_data(self, obj: SignalObj) -> np.ndarray: """Get signal data in ROI Args: obj: signal object Returns: Data in ROI """ assert isinstance(self.xmin, float) and isinstance(self.xmax, float) imin, imax = np.searchsorted(obj.x, [self.xmin, self.xmax]) return np.array([obj.x[imin:imax], obj.y[imin:imax]]) class SegmentROI(base.BaseSingleROI["SignalObj", ROI1DParam]): """Segment ROI Args: coords: ROI coordinates (xmin, xmax) title: ROI title """ # Note: in this class, the ROI parameters are stored as X indices def check_coords(self) -> None: """Check if coords are valid Raises: ValueError: invalid coords """ if len(self.coords) != 2: raise ValueError("Invalid ROI segment coords (2 values expected)") if self.coords[0] >= self.coords[1]: raise ValueError("Invalid ROI segment coords (xmin >= xmax)") def get_coords_html_rows(self) -> list[tuple[str, str]]: """Return HTML table rows describing the segment coordinates.""" xmin, xmax = self.coords coord_type = "indices" if self.indices else "physical" return [ (f"X min ({coord_type})", f"{xmin:.4g}"), (f"X max ({coord_type})", f"{xmax:.4g}"), ] def get_coords_summary(self) -> str: """Return a short summary of the segment coordinates.""" xmin, xmax = self.coords return f"X: [{xmin:.4g}, {xmax:.4g}]" def get_data(self, obj: SignalObj) -> tuple[np.ndarray, np.ndarray]: """Get signal data in ROI Args: obj: signal object Returns: Data in ROI """ imin, imax = self.get_indices_coords(obj) return obj.x[imin:imax], obj.y[imin:imax] def to_mask(self, obj: SignalObj) -> np.ndarray: """Create mask from ROI Args: obj: signal object Returns: Mask (boolean array where True values are inside the ROI) """ mask = np.ones_like(obj.xydata, dtype=bool) imin, imax = self.get_indices_coords(obj) mask[:, imin:imax] = False return mask # pylint: disable=unused-argument def to_param(self, obj: SignalObj, index: int) -> ROI1DParam: """Convert ROI to parameters Args: obj: object (signal), for physical-indices coordinates conversion index: ROI index """ gtitle = base.get_generic_roi_title(index) param = ROI1DParam(gtitle) param.title = self.title or gtitle param.xmin, param.xmax = self.get_physical_coords(obj) return param class SignalROI(base.BaseROI["SignalObj", SegmentROI, ROI1DParam]): """Signal Regions of Interest Args: inverse: if True, ROI is outside the region """ PREFIX = "s" def union(self) -> SignalROI: """Return union of ROIs""" if not self.single_rois: return SignalROI() coords = np.array([roi.coords for roi in self.single_rois]) # Merge overlapping segments: sorted_coords = coords[coords[:, 0].argsort()] merged_coords = [sorted_coords[0].tolist()] for current in sorted_coords[1:]: last = merged_coords[-1] if current[0] <= last[1]: # Overlap last[1] = max(last[1], current[1]) # Merge else: merged_coords.append(current.tolist()) # Create new SignalROI with merged segments: roi = create_signal_roi(merged_coords) return roi def clipped(self, x_min: float, x_max: float) -> SignalROI: """Remove parts of ROIs outside the signal range Args: x_min: signal minimum X value x_max: signal maximum X value Returns: SignalROI object containing ROIs clipped to the specified signal range. """ new_roi = SignalROI() for roi in self.single_rois: roi_min, roi_max = roi.coords if roi_max < x_min or roi_min > x_max: # ROI completely outside signal range: skip it continue # Clip ROI to signal range: new_roi_min = max(roi_min, x_min) new_roi_max = min(roi_max, x_max) new_roi.add_roi( SegmentROI(np.array([new_roi_min, new_roi_max], float), indices=False) ) return new_roi def inverted(self, x_min: float, x_max: float) -> SignalROI: """Return inverted ROI (inside/outside). Args: x_min: signal minimum X value x_max: signal maximum X value Returns: Inverted ROI """ clipped_roi = self.clipped(x_min, x_max) union_roi = clipped_roi.union() roi_delimiter_list = np.array( [roi.coords for roi in union_roi.single_rois] ).reshape(-1) if len(roi_delimiter_list) == 0: # No ROIs: inverted ROI is the whole signal raise ValueError("No ROIs defined, cannot invert") if len(roi_delimiter_list) % 2 != 0: # Odd number of delimiters: add signal limits raise ValueError("Internal error: odd number of ROI delimiters") if roi_delimiter_list[0] == x_min: # First delimiter is signal min: remove it roi_delimiter_list = roi_delimiter_list[1:] else: # Add signal min as first delimiter roi_delimiter_list = np.insert(roi_delimiter_list, 0, x_min) if roi_delimiter_list[-1] == x_max: # Last delimiter is signal max: remove it roi_delimiter_list = roi_delimiter_list[:-1] else: # Add signal max as last delimiter roi_delimiter_list = np.append(roi_delimiter_list, x_max) return create_signal_roi(np.array(roi_delimiter_list).reshape(-1, 2)) @staticmethod def get_compatible_single_roi_classes() -> list[Type[SegmentROI]]: """Return compatible single ROI classes""" return [SegmentROI] def to_mask(self, obj: SignalObj) -> np.ndarray: """Create mask from ROI Args: obj: signal object Returns: Mask (boolean array where True values are inside the ROI) """ mask = np.ones_like(obj.xydata, dtype=bool) if self.single_rois: for roi in self.single_rois: mask &= roi.to_mask(obj) else: # If no single ROIs, the mask is empty (no ROI defined) mask[:] = False return mask def create_signal_roi( coords: np.ndarray | list[float] | list[list[float]], indices: bool = False, title: str = "", ) -> SignalROI: """Create Signal Regions of Interest (ROI) object. More ROIs can be added to the object after creation, using the `add_roi` method. Args: coords: single ROI coordinates `[xmin, xmax]`, or multiple ROIs coordinates `[[xmin1, xmax1], [xmin2, xmax2], ...]` (lists or NumPy arrays) indices: if True, coordinates are indices, if False, they are physical values (default to False for signals) title: title Returns: Regions of Interest (ROI) object Raises: ValueError: if the number of coordinates is not even """ coords = np.array(coords, float) if coords.ndim == 1: coords = coords.reshape(1, -1) roi = SignalROI() for row in coords: roi.add_roi(SegmentROI(row, indices=indices, title=title)) return roi Sigima-1.1.1/sigima/params.py000066400000000000000000000300201514013333200160170ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Parameters (:mod:`sigima.params`) --------------------------------- The :mod:`sigima.params` module provides all the dataset parameter classes used by :mod:`sigima.proc` processing functions and DataLab's GUI. .. tip:: **Always import parameters from** :mod:`sigima.params`. While parameter classes are defined in various submodules (e.g., ``sigima.proc.signal.fourier``), they are all re-exported here for convenience. This avoids confusion about where to import from. .. code-block:: python # ✅ Recommended: import from sigima.params import sigima.params param = sigima.params.ZeroPadding1DParam.create(strategy="next_pow2") # ❌ Avoid: importing from internal modules (works but less clear) from sigima.proc.signal.fourier import ZeroPadding1DParam Introduction to ``DataSet`` Parameters ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ The datasets listed in the following sections define the parameters necessary for computation and processing operations in Sigima. Each dataset is a subclass of :py:class:`guidata.dataset.datatypes.DataSet` and needs to be instantiated before use. Creating Parameter Instances ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Parameter classes provide a ``create()`` class method for easy instantiation: .. code-block:: python import sigima.params # Create with default values param = sigima.params.NormalizeParam.create() # Create with custom values param = sigima.params.NormalizeParam.create(method="maximum") Parameters Requiring Signal/Image Context ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Some parameters need to know about the signal or image they will process in order to compute their values. For example, :class:`ZeroPadding1DParam` needs to know the signal size to calculate how many points to add for the "next_pow2" strategy. These parameters provide an ``update_from_obj()`` method that **must be called** before using the parameters: .. code-block:: python import sigima.params import sigima.proc.signal as sips # Create the parameter object param = sigima.params.ZeroPadding1DParam.create(strategy="next_pow2") # ⚠️ At this point, param.n is still the default value (1) # because the parameter doesn't know the signal size yet # IMPORTANT: Update parameters from the signal param.update_from_obj(signal) # ✅ Now param.n is computed (e.g., 24 for a 1000-point signal) result = sips.zero_padding(signal, param) Parameter classes that require ``update_from_obj()``: - :class:`ZeroPadding1DParam`: Computes ``n`` based on strategy and signal size - :class:`ZeroPadding2DParam`: Computes padding based on strategy and image size - :class:`Resampling1DParam`: Updates bounds based on signal range - :class:`Resampling2DParam`: Updates bounds based on signal range - :class:`ResizeParam`: Updates bounds based on image dimensions - :class:`TranslateParam`: Updates bounds based on image dimensions - :class:`LineProfileParam`: Updates line coordinates based on image dimensions - :class:`BandPassFilterParam`, :class:`BandStopFilterParam`, :class:`HighPassFilterParam`, :class:`LowPassFilterParam`: Update frequency bounds .. note:: Not all parameters require ``update_from_obj()``. Simple parameters like :class:`NormalizeParam` or :class:`GaussianParam` work with fixed values and don't need signal/image context. Complete Example ~~~~~~~~~~~~~~~~ Here is a complete example of how to instantiate a dataset and access its parameters with the :py:class:`sigima.params.BinningParam` dataset: .. autodataset:: sigima.params.BinningParam :no-index: :shownote: I/O parameters ^^^^^^^^^^^^^^ .. autodataset:: sigima.io.convenience.SaveToDirectoryParam :no-index: Common parameters ^^^^^^^^^^^^^^^^^ .. autodataset:: sigima.params.ArithmeticParam :no-index: .. autodataset:: sigima.params.ClipParam :no-index: .. autodataset:: sigima.params.ConstantParam :no-index: .. autodataset:: sigima.params.FFTParam :no-index: .. autodataset:: sigima.params.GaussianParam :no-index: .. autodataset:: sigima.params.HistogramParam :no-index: .. autodataset:: sigima.params.MovingAverageParam :no-index: .. autodataset:: sigima.params.MovingMedianParam :no-index: .. autodataset:: sigima.params.NormalizeParam :no-index: .. autodataset:: sigima.params.SpectrumParam :no-index: Signal parameters ^^^^^^^^^^^^^^^^^ .. autodataset:: sigima.params.AllanVarianceParam :no-index: .. autodataset:: sigima.params.AngleUnitParam :no-index: .. autodataset:: sigima.params.BandPassFilterParam :no-index: .. autodataset:: sigima.params.BandStopFilterParam :no-index: .. autodataset:: sigima.params.DataTypeSParam :no-index: .. autodataset:: sigima.params.DetrendingParam :no-index: .. autodataset:: sigima.params.DynamicParam :no-index: .. autodataset:: sigima.params.AbscissaParam :no-index: .. autodataset:: sigima.params.OrdinateParam :no-index: .. autodataset:: sigima.params.FWHMParam :no-index: .. autodataset:: sigima.params.HighPassFilterParam :no-index: .. autodataset:: sigima.params.InterpolationParam :no-index: .. autodataset:: sigima.params.LowPassFilterParam :no-index: .. autodataset:: sigima.params.PeakDetectionParam :no-index: .. autodataset:: sigima.params.PolynomialFitParam :no-index: .. autodataset:: sigima.params.PowerParam :no-index: .. autodataset:: sigima.params.PulseFeaturesParam :no-index: .. autodataset:: sigima.params.Resampling1DParam :no-index: .. autodataset:: sigima.params.Resampling2DParam :no-index: .. autodataset:: sigima.params.WindowingParam :no-index: .. autodataset:: sigima.params.XYCalibrateParam :no-index: .. autodataset:: sigima.params.ZeroPadding1DParam :no-index: Image parameters ^^^^^^^^^^^^^^^^ Base image parameters ~~~~~~~~~~~~~~~~~~~~~ .. autodataset:: sigima.params.GridParam :no-index: Detection parameters ~~~~~~~~~~~~~~~~~~~~ .. autodataset:: sigima.params.BlobDOGParam :no-index: .. autodataset:: sigima.params.BlobDOHParam :no-index: .. autodataset:: sigima.params.BlobLOGParam :no-index: .. autodataset:: sigima.params.BlobOpenCVParam :no-index: .. autodataset:: sigima.params.ContourShapeParam :no-index: .. autodataset:: sigima.params.Peak2DDetectionParam :no-index: .. autodataset:: sigima.params.HoughCircleParam :no-index: Edge detection parameters ~~~~~~~~~~~~~~~~~~~~~~~~~ .. autodataset:: sigima.params.CannyParam :no-index: Exposure correction parameters ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. autodataset:: sigima.params.AdjustGammaParam :no-index: .. autodataset:: sigima.params.AdjustLogParam :no-index: .. autodataset:: sigima.params.AdjustSigmoidParam :no-index: .. autodataset:: sigima.params.EqualizeAdaptHistParam :no-index: .. autodataset:: sigima.params.EqualizeHistParam :no-index: .. autodataset:: sigima.params.RescaleIntensityParam :no-index: .. autodataset:: sigima.params.FlatFieldParam :no-index: .. autodataset:: sigima.params.XYZCalibrateParam :no-index: Extraction parameters ~~~~~~~~~~~~~~~~~~~~~~ .. autodataset:: sigima.params.AverageProfileParam :no-index: .. autodataset:: sigima.params.LineProfileParam :no-index: .. autodataset:: sigima.params.RadialProfileParam :no-index: .. autodataset:: sigima.params.SegmentProfileParam :no-index: .. autoclass:: sigima.params.Direction :no-index: .. autodataset:: sigima.params.ROIGridParam :no-index: Filtering parameters ~~~~~~~~~~~~~~~~~~~~ .. autodataset:: sigima.params.ButterworthParam :no-index: .. autofunction:: sigima.params.GaussianFreqFilterParam :no-index: Fourier analysis parameters ~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. autodataset:: sigima.params.ZeroPadding2DParam :no-index: Geometry parameters ~~~~~~~~~~~~~~~~~~~ .. autodataset:: sigima.params.BinningParam :no-index: .. autodataset:: sigima.params.ResizeParam :no-index: .. autodataset:: sigima.params.RotateParam :no-index: .. autodataset:: sigima.params.TranslateParam :no-index: Mathematical operation parameters ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. autodataset:: sigima.params.DataTypeIParam :no-index: .. autodataset:: sigima.params.Log10ZPlusNParam :no-index: Morphological parameters ~~~~~~~~~~~~~~~~~~~~~~~~ .. autodataset:: sigima.params.MorphologyParam :no-index: Restoration parameters ~~~~~~~~~~~~~~~~~~~~~~ .. autodataset:: sigima.params.DenoiseBilateralParam :no-index: .. autodataset:: sigima.params.DenoiseTVParam :no-index: .. autodataset:: sigima.params.DenoiseWaveletParam :no-index: Threshold parameters ~~~~~~~~~~~~~~~~~~~~ .. autodataset:: sigima.params.ThresholdParam :no-index: """ __all__ = [ "AbscissaParam", "AdjustGammaParam", "AdjustLogParam", "AdjustSigmoidParam", "AllanVarianceParam", "AngleUnitParam", "ArithmeticParam", "AverageProfileParam", "BandPassFilterParam", "BandStopFilterParam", "BinningParam", "BlobDOGParam", "BlobDOHParam", "BlobLOGParam", "BlobOpenCVParam", "ButterworthParam", "CannyParam", "ClipParam", "ConstantParam", "ContourShapeParam", "DataTypeIParam", "DataTypeSParam", "DenoiseBilateralParam", "DenoiseTVParam", "DenoiseWaveletParam", "DetrendingParam", "Direction", "DynamicParam", "EqualizeAdaptHistParam", "EqualizeHistParam", "FFTParam", "FWHMParam", "FlatFieldParam", "GaussianFreqFilterParam", "GaussianParam", "GridParam", "HighPassFilterParam", "HistogramParam", "HoughCircleParam", "InterpolationParam", "LineProfileParam", "Log10ZPlusNParam", "LowPassFilterParam", "MorphologyParam", "MovingAverageParam", "MovingMedianParam", "NormalizeParam", "OrdinateParam", "Peak2DDetectionParam", "PeakDetectionParam", "PhaseParam", "PolynomialFitParam", "PowerParam", "PulseFeaturesParam", "ROIGridParam", "RadialProfileParam", "Resampling1DParam", "Resampling2DParam", "RescaleIntensityParam", "ResizeParam", "RotateParam", "SaveToDirectoryParam", "SegmentProfileParam", "SignalsToImageParam", "SpectrumParam", "ThresholdParam", "TranslateParam", "UniformCoordsParam", "WindowingParam", "XYCalibrateParam", "XYZCalibrateParam", "ZeroPadding1DParam", "ZeroPadding2DParam", ] from sigima.io.convenience import SaveToDirectoryParam from sigima.proc.base import ( AngleUnitParam, ArithmeticParam, ClipParam, ConstantParam, FFTParam, GaussianParam, HistogramParam, MovingAverageParam, MovingMedianParam, NormalizeParam, PhaseParam, SignalsToImageParam, SpectrumParam, ) from sigima.proc.image import ( AdjustGammaParam, AdjustLogParam, AdjustSigmoidParam, AverageProfileParam, BinningParam, BlobDOGParam, BlobDOHParam, BlobLOGParam, BlobOpenCVParam, ButterworthParam, CannyParam, ContourShapeParam, DataTypeIParam, DenoiseBilateralParam, DenoiseTVParam, DenoiseWaveletParam, Direction, EqualizeAdaptHistParam, EqualizeHistParam, FlatFieldParam, GaussianFreqFilterParam, GridParam, HoughCircleParam, LineProfileParam, Log10ZPlusNParam, MorphologyParam, Peak2DDetectionParam, RadialProfileParam, Resampling2DParam, RescaleIntensityParam, ResizeParam, ROIGridParam, RotateParam, SegmentProfileParam, ThresholdParam, TranslateParam, UniformCoordsParam, XYZCalibrateParam, ZeroPadding2DParam, ) from sigima.proc.signal import ( AbscissaParam, AllanVarianceParam, BandPassFilterParam, BandStopFilterParam, DataTypeSParam, DetrendingParam, DynamicParam, FWHMParam, HighPassFilterParam, InterpolationParam, LowPassFilterParam, OrdinateParam, PeakDetectionParam, PolynomialFitParam, PowerParam, PulseFeaturesParam, Resampling1DParam, WindowingParam, XYCalibrateParam, ZeroPadding1DParam, ) Sigima-1.1.1/sigima/proc/000077500000000000000000000000001514013333200151325ustar00rootroot00000000000000Sigima-1.1.1/sigima/proc/__init__.py000066400000000000000000000065061514013333200172520ustar00rootroot00000000000000""" Computation (:mod:`sigima.proc`) -------------------------------- This package contains the Sigima computation functions that implement processing features for signal, image and scalar objects. These functions are designed to operate directly on :class:`sigima.objects.SignalObj`, :class:`sigima.objects.ImageObj`, :class:`sigima.objects.GeometryResult` and :class:`sigima.objects.TableResult` objects, which are defined in the :mod:`sigima.objects` package. Even though these functions are primarily designed to be used in the Sigima pipeline, they can also be used independently. .. seealso:: See the :mod:`sigima.tools` package for some algorithms that operate directly on NumPy arrays. Each computation module defines a set of computation objects, that is, functions that implement processing features and classes that implement the corresponding parameters (in the form of :py:class:`guidata.dataset.datatypes.Dataset` subclasses). The computation functions takes a signal or image object (e.g. :py:class:`sigima.objects.SignalObj`) and a parameter object (e.g. :py:class:`sigima.params.MovingAverageParam`) as input and return a signal or image object as output (the result of the computation). The parameter object is used to configure the computation function (e.g. the size of the moving average window). In Sigima overall architecture, the purpose of this package is to provide the computation functions that are used by DataLab processor modules, based on the algorithms defined in the :mod:`sigima.tools` module and on the data model defined in the :mod:`sigima.objects` module. The computation modules are organized in subpackages according to their purpose. The following subpackages are available: - :mod:`sigima.proc.base`: Common processing features - :mod:`sigima.proc.signal`: Signal processing features - :mod:`sigima.proc.image`: Image processing features (including transformations) Common processing features ^^^^^^^^^^^^^^^^^^^^^^^^^^ .. automodule:: sigima.proc.base :members: Signal processing features ^^^^^^^^^^^^^^^^^^^^^^^^^^ .. automodule:: sigima.proc.signal :members: Image processing features ^^^^^^^^^^^^^^^^^^^^^^^^^ .. automodule:: sigima.proc.image :members: Decorators and utilities ^^^^^^^^^^^^^^^^^^^^^^^^ This package also provides some utility functions to help with the creation and introspection of computation functions: .. autofunction:: sigima.proc.decorator.computation_function .. autofunction:: sigima.proc.decorator.is_computation_function .. autofunction:: sigima.proc.decorator.get_computation_metadata .. autofunction:: sigima.proc.decorator.find_computation_functions Title Formatting System ^^^^^^^^^^^^^^^^^^^^^^^ The title formatting system provides configurable title generation for computation results, enabling different applications (Sigima standalone vs DataLab integration) to use different title formatting strategies: .. automodule:: sigima.proc.title_formatting :members: """ # Import title formatting components for easy access from sigima.proc.title_formatting import ( PlaceholderTitleFormatter, SimpleTitleFormatter, TitleFormatter, get_default_title_formatter, set_default_title_formatter, ) __all__ = [ "PlaceholderTitleFormatter", "SimpleTitleFormatter", "TitleFormatter", "get_default_title_formatter", "set_default_title_formatter", ] Sigima-1.1.1/sigima/proc/base.py000066400000000000000000000312771514013333200164300ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ .. Common computation objects (see parent package :mod:`sigima.computation`) """ # pylint: disable=invalid-name # Allows short reference names like x, y, ... # Note: # ---- # All dataset classes must also be imported in the sigima.params module. from __future__ import annotations from typing import TypeVar, cast import guidata.dataset as gds import numpy as np from sigima import ImageObj, SignalObj, create_signal from sigima.config import _, options from sigima.enums import ( AngleUnit, FilterMode, MathOperator, NormalizationMethod, SignalsToImageOrientation, ) from sigima.proc.title_formatting import get_default_title_formatter # NOTE: This module is a shared utilities library that defines common parameter classes # used by multiple other modules (signal processing, image processing, etc.). # Unlike other modules, the parameter classes DEFINED in this module should NOT be # included in __all__ because they are imported and re-exported by the modules that # use them, and including them here would create Sphinx cross-reference conflicts. # The sigima.params module serves as the central API point that imports and re-exports # all parameter classes from their canonical locations. __all__ = [ "dst_1_to_1", "dst_2_to_1", "dst_n_to_1", "new_signal_result", ] class ArithmeticParam(gds.DataSet, title=_("Arithmetic")): """Arithmetic parameters""" def get_operation(self) -> str: """Return the operation string""" o, a, b = self.operator, self.factor, self.constant b_added = False if a == 0.0: if o in ("+", "-"): txt = "obj3 = obj1" elif b == 0.0: txt = "obj3 = 0" else: txt = f"obj3 = {b}" b_added = True elif a == 1.0: txt = f"obj3 = obj1 {o} obj2" else: txt = f"obj3 = (obj1 {o} obj2) × {a}" if b != 0.0 and not b_added: txt += f" + {b}" return txt def update_operation(self, _item, _value): # pylint: disable=unused-argument """Update the operation item""" self.operation = self.get_operation() operator = gds.ChoiceItem( _("Operator"), MathOperator, default=MathOperator.ADD ).set_prop("display", callback=update_operation) factor = ( gds.FloatItem(_("Factor"), default=1.0) .set_pos(col=1) .set_prop("display", callback=update_operation) ) constant = ( gds.FloatItem(_("Constant"), default=0.0) .set_pos(col=1) .set_prop("display", callback=update_operation) ) operation = gds.StringItem(_("Operation"), default="").set_prop( "display", active=False ) restore_dtype = gds.BoolItem( _("Convert to `obj1` data type"), label=_("Result"), default=True ) class GaussianParam(gds.DataSet, title=_("Gaussian filter")): """Gaussian filter parameters.""" sigma = gds.FloatItem( "σ", default=1.0, min=0.0, help=_("Standard deviation of the Gaussian filter"), ) HELP_MODE = _("""Mode of the filter: - 'reflect': Reflect the data at the boundary - 'constant': Pad with a constant value - 'nearest': Pad with the nearest value - 'mirror': Reflect the data at the boundary with the data itself - 'wrap': Circular boundary""") class MovingAverageParam(gds.DataSet, title=_("Moving average")): """Moving average parameters""" n = gds.IntItem(_("Size of the moving window"), default=3, min=1) mode = gds.ChoiceItem( _("Mode"), FilterMode, default=FilterMode.REFLECT, help=HELP_MODE ) class MovingMedianParam(gds.DataSet, title=_("Moving median")): """Moving median parameters""" n = gds.IntItem(_("Size of the moving window"), default=3, min=1, even=False) mode = gds.ChoiceItem( _("Mode"), FilterMode, default=FilterMode.NEAREST, help=HELP_MODE ) class ClipParam(gds.DataSet, title=_("Clip")): """Data clipping parameters""" lower = gds.FloatItem(_("Lower clipping value"), check=False) upper = gds.FloatItem(_("Upper clipping value"), check=False) class NormalizeParam(gds.DataSet, title=_("Normalize")): """Normalize parameters""" method = gds.ChoiceItem(_("Normalize with respect to"), NormalizationMethod) class HistogramParam(gds.DataSet, title=_("Histogram")): """Histogram parameters""" def get_suffix(self, data: np.ndarray) -> str: """Return suffix for the histogram computation Args: data: data array """ suffix = f"bins={self.bins:d}" if self.lower is not None: suffix += f", ymin={self.lower:.3f}" else: self.lower = np.min(data) if self.upper is not None: suffix += f", ymax={self.upper:.3f}" else: self.upper = np.max(data) return suffix bins = gds.IntItem(_("Number of bins"), default=256, min=1) lower = gds.FloatItem(_("Lower limit"), default=None, check=False) upper = gds.FloatItem(_("Upper limit"), default=None, check=False) class FFTParam(gds.DataSet, title=_("FFT")): """FFT parameters""" shift = gds.BoolItem(_("Shift"), help=_("Shift zero frequency to center")) def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self.shift = options.fft_shift_enabled.get() class SpectrumParam(gds.DataSet, title=_("Spectrum")): """Spectrum parameters.""" decibel = gds.BoolItem(_("Output in decibel (dB)"), default=False) class ConstantParam(gds.DataSet, title=_("Constant")): """Parameter used to set a constant value to used in operations""" value = gds.FloatItem(_("Constant value")) class AngleUnitParam(gds.DataSet, title=_("Angle unit")): """Choice of angle unit.""" unit = gds.ChoiceItem( _("Angle unit"), AngleUnit, default=AngleUnit.RADIAN, help=_("Unit of angle measurement"), ) class PhaseParam(gds.DataSet, title=_("Phase")): """Parameters for phase computation.""" unwrap = gds.BoolItem( "unwrap", default=True, help=_("Unwrapping removes discontinuities in phase") ) unit = gds.ChoiceItem( _("Unit"), AngleUnit, default=AngleUnit.DEGREE, help=_("Unit of angle measurement"), ) class SignalsToImageParam(gds.DataSet, title=_("Signals to image")): """Parameters for assembling signals into an image.""" orientation = gds.ChoiceItem( _("Orientation"), SignalsToImageOrientation, default=SignalsToImageOrientation.ROWS, help=_("Stack signals as rows or columns in the output image"), ) _prop = gds.GetAttrProp("normalize") normalize = gds.BoolItem( _("Normalize"), default=False, help=_("Normalize each signal before combining"), ) normalize_method = gds.ChoiceItem( _("Normalization method"), NormalizationMethod, default=NormalizationMethod.MAXIMUM, help=_("Method used for normalization"), ).set_prop("display", active=_prop) # MARK: Helper functions for creating result objects ----------------------------------- Obj = TypeVar("Obj", bound="SignalObj | ImageObj") def dst_1_to_1(src: Obj, name: str, suffix: str | None = None) -> Obj: """Create a result object, for processing functions that take a single signal or image object as input and return a single signal or image object (1-to-1). .. note:: Data of the result object is copied from the source object (`src`). This initial data is usually replaced by the processing function, but it may also be used to initialize the result object as part of the processing function. Args: src: source signal or image object name: name of the function. The title format depends on the configured title formatter (SimpleTitleFormatter creates readable titles, PlaceholderTitleFormatter creates DataLab-compatible placeholder titles). suffix: suffix to add to the title. Optional. Returns: Result signal or image object """ formatter = get_default_title_formatter() title = formatter.format_1_to_1_title(name, suffix) dst = src.copy(title=title) return cast(Obj, dst) def dst_n_to_1(src_list: list[Obj], name: str, suffix: str | None = None) -> Obj: """Create a result object, for processing functions that take a list of signal or image objects as input and return a single signal or image object (n-to-1). .. note:: Data of the result object is copied from the first source object (`src_list[0]`). This initial data is usually replaced by the processing function, but it may also be used to initialize the result object as part of the processing function. Args: src_list: list of input signal or image objects name: name of the processing function. The title format depends on the configured title formatter (SimpleTitleFormatter creates readable titles, PlaceholderTitleFormatter creates DataLab-compatible placeholder titles). suffix: suffix to add to the title Returns: Result signal or image object """ if not isinstance(src_list, list) or len(src_list) <= 1: raise ValueError("src_list must be a list of at least 2 objects") all_sigs = all(isinstance(obj, SignalObj) for obj in src_list) all_imgs = all(isinstance(obj, ImageObj) for obj in src_list) if not (all_sigs or all_imgs): raise ValueError("src_list must be a list of SignalObj or ImageObj objects") formatter = get_default_title_formatter() title = formatter.format_n_to_1_title(name, len(src_list), suffix) if any(np.issubdtype(obj.data.dtype, complex) for obj in src_list): dst_dtype = complex else: dst_dtype = float dst = src_list[0].copy(title=title, dtype=dst_dtype) dst.roi = None for src_obj in src_list: if src_obj.roi is not None: if dst.roi is None: dst.roi = src_obj.roi.copy() else: dst.roi.add_roi(src_obj.roi) return dst # Note about `src2` parameter: # ---------------------------- # The `src2` parameter is currently not used in the function, but it is included # to maintain a consistent interface with other similar functions (e.g., `dst_n_to_1`). # This may be useful in the future if we want to extend the functionality. # # pylint: disable=unused-argument def dst_2_to_1(src1: Obj, src2: Obj, name: str, suffix: str | None = None) -> Obj: """Create a result object, for processing functions that take two signal or image objects as input and return a single signal or image object (2-to-1). .. note:: Data of the result object is copied from the first source object (`src1`). This initial data is usually replaced by the processing function, but it may also be used to initialize the result object as part of the processing function. Args: src1: input signal or image object src2: input signal or image object name: name of the processing function. The title format depends on the configured title formatter (SimpleTitleFormatter creates readable titles, PlaceholderTitleFormatter creates DataLab-compatible placeholder titles). suffix: suffix to add to the title Returns: Output signal or image object """ formatter = get_default_title_formatter() title = formatter.format_2_to_1_title(name, suffix) dst = src1.copy(title=title) return dst def new_signal_result( src: SignalObj | ImageObj, name: str, suffix: str | None = None, units: tuple[str, str] | None = None, labels: tuple[str, str] | None = None, ) -> SignalObj: """Create new signal object as a result of a `compute_1_to_1` function As opposed to the `dst_1_to_1` functions, this function creates a new signal object without copying the original object metadata, except for the "source" entry. Args: src: input signal or image object name: name of the processing function. The title format depends on the configured title formatter (SimpleTitleFormatter creates readable titles, PlaceholderTitleFormatter creates DataLab-compatible placeholder titles). suffix: suffix to add to the title units: units of the output signal labels: labels of the output signal Returns: Output signal object """ formatter = get_default_title_formatter() title = formatter.format_1_to_1_title(name, suffix) dst = create_signal(title=title, units=units, labels=labels) if (source := src.metadata.get("source")) is not None: dst.metadata["source"] = source return dst Sigima-1.1.1/sigima/proc/decorator.py000066400000000000000000000303721514013333200174730ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ .. Computation function decorator and utilities (see parent package :mod:`sigima.computation`) """ from __future__ import annotations import dataclasses import functools import importlib import inspect import os.path as osp import pkgutil import sys import typing from typing import Callable, Literal, TypeVar import guidata.dataset as gds import makefun from sigima.objects.scalar.geometry import GeometryResult from sigima.objects.scalar.table import TableResult if sys.version_info >= (3, 10): # Use ParamSpec from typing module in Python 3.10+ from typing import ParamSpec else: # Use ParamSpec from typing_extensions module in Python < 3.10 from typing_extensions import ParamSpec # NOTE: Parameter classes should NOT be included in __all__ to avoid Sphinx # cross-reference conflicts. All parameter classes are re-exported through # sigima.params module which serves as the single source of truth for the # public API. Only utility functions should be exported from this module. __all__ = [ "computation_function", "find_computation_functions", "get_computation_metadata", "is_computation_function", ] # Marker attribute used by @computation_function and introspection COMPUTATION_METADATA_ATTR = "__computation_function_metadata" P = ParamSpec("P") R = TypeVar("R") @dataclasses.dataclass(frozen=True) class ComputationMetadata: """Metadata for a computation function. Attributes: name: The name of the computation function. description: A description or docstring for the computation function. """ name: str description: str def _make_computation_wrapper( f: Callable, ds_cls: type, ds_param: inspect.Parameter, params: list, ds_items: list, new_sig: inspect.Signature, signature_info: str, metadata: ComputationMetadata, ) -> Callable: """ Create a computation function wrapper supporting both DataSet and expanded-kwarg signatures. Args: f: The original function. ds_cls: The DataSet class type. ds_param: The DataSet parameter in the signature. params: The full function signature parameters. ds_items: The DataSet's items (parameters). new_sig: The explicit signature (with kwargs) to expose. signature_info: The Sphinx docstring note to append. metadata: ComputationMetadata to attach to the wrapper. Returns: The wrapped function. """ @makefun.with_signature(new_sig) @functools.wraps(f) def wrapper(*args, **kwargs): """ Dispatch function supporting both DataSet parameter and expanded keyword arguments. Behavior: - If a DataSet object is provided, it is always used and keyword arguments for DataSet items are ignored. - If no DataSet is provided, DataSet items are constructed from keyword arguments. Returns: Result of the original computation function. """ ba = new_sig.bind(*args, **kwargs) ba.apply_defaults() ds_obj = ba.arguments.get(ds_param.name, None) ds_item_names = set(item.get_name() for item in ds_items) if isinstance(ds_obj, ds_cls): # DataSet object provided: ignore any keyword arguments for its items pass else: # DataSet instance not provided: build from keyword arguments ds_kwargs = { k: ba.arguments.pop(k) for k in list(ba.arguments.keys()) if k in ds_item_names } ds_obj = ds_cls.create(**ds_kwargs) # Build the final positional argument list for the original function final_args = [] for p in params: if p is ds_param: final_args.append(ds_obj) else: final_args.append(ba.arguments.get(p.name, None)) # Call the original function result = f(*final_args) # Auto-inject func_name into result objects if they support it if ( isinstance(result, (TableResult, GeometryResult)) and result.func_name is None ): # Since results are frozen dataclasses, we need to recreate them result = dataclasses.replace(result, func_name=f.__name__) return result # Attach dynamic Sphinx docstring and signature doc = f.__doc__ or "" if not doc.endswith("\n"): doc += "\n" wrapper.__doc__ = doc + signature_info wrapper.__signature__ = new_sig setattr(wrapper, COMPUTATION_METADATA_ATTR, metadata) return wrapper def computation_function( *, name: typing.Optional[str] = None, description: typing.Optional[str] = None, ) -> Callable[[Callable[P, R]], Callable[P, R]]: """ Decorator to mark a function as a Sigima computation function. This decorator enables two calling conventions: 1. With a guidata DataSet object as a parameter (classic style). 2. With the DataSet items passed as individual keyword arguments (expanded style). The decorator ensures: - An explicit and informative function signature (including all DataSet items as keyword arguments). - A Sphinx-friendly docstring documenting both call styles. - Pickle-compatibility (crucial for multiprocessing). - Conflict detection if both DataSet instance and expanded keyword arguments are used simultaneously. Args: name: Optional custom name for metadata. description: Optional custom description or docstring. Returns: The decorated, enhanced computation function. """ def decorator(f: Callable[P, R]) -> Callable[P, R]: # Gather signature and typing information sig = inspect.signature(f) params = list(sig.parameters.values()) try: type_hints = typing.get_type_hints(f) except Exception: # pylint: disable=broad-except type_hints = {} # Find DataSet parameter if any ds_param = None ds_cls = None for p in params: annot = type_hints.get(p.name, p.annotation) if ( annot is not inspect.Signature.empty and isinstance(annot, type) and issubclass(annot, gds.DataSet) and annot.__name__ not in ("SignalObj", "ImageObj") ): ds_param = p ds_cls = annot break # If a DataSet param is present, expand signature and docstring if ds_cls is not None: # Build signature exposing all DataSet items as keyword-only parameters ds_items: list[gds.DataItem] = ds_cls._items # pylint: disable=W0212 item_names = [item.get_name() for item in ds_items] items = [] for item in ds_items: if item.get_name() not in [p.name for p in params]: # Support ChoiceItem as Literal if available if hasattr(gds, "ChoiceItem") and isinstance(item, gds.ChoiceItem): choice_data = item.get_prop("data", "choices") choices = [v[0] for v in choice_data] item_type = Literal[tuple(choices)] else: item_type = item.type items.append( inspect.Parameter( item.get_name(), inspect.Parameter.KEYWORD_ONLY, annotation=item_type, default=item.get_default(), ) ) # DataSet parameter remains positional-or-keyword, but optional # (default=None) base_params = [] for p in params: if p is ds_param: base_params.append( inspect.Parameter( p.name, inspect.Parameter.POSITIONAL_OR_KEYWORD, annotation=p.annotation, default=None, ) ) else: base_params.append(p) new_params = base_params + items new_sig = sig.replace(parameters=new_params) param_class_name = ds_cls.__name__ kwarg_example = ", ".join(f"{name}=..." for name in item_names) # Sphinx-style docstring describing both call conventions signature_info = ( f".. note::\n\n" f" This computation function can be called in two ways:\n\n" f" 1. With a parameter ``{param_class_name}`` object:\n\n" f" .. code-block:: python\n\n" f" param = {param_class_name}.create({kwarg_example})\n" f" func(obj, param)\n\n" f" 2. Or, with keyword arguments directly:\n\n" f" .. code-block:: python\n\n" f" func(obj, {kwarg_example})\n\n" f" Both styles are fully supported and equivalent.\n\n" ) metadata = ComputationMetadata( name=name or f.__name__, description=description or f.__doc__, ) return _make_computation_wrapper( f, ds_cls, ds_param, params, ds_items, new_sig, signature_info, metadata ) # No DataSet parameter: simple passthrough with func_name injection @functools.wraps(f) def wrapper(*args, **kwargs): result = f(*args, **kwargs) # Auto-inject func_name into result objects if they support it if ( isinstance(result, (TableResult, GeometryResult)) and result.func_name is None ): # Since results are frozen dataclasses, we need to recreate them result = dataclasses.replace(result, func_name=f.__name__) return result metadata = ComputationMetadata( name=name or f.__name__, description=description or f.__doc__, ) setattr(wrapper, COMPUTATION_METADATA_ATTR, metadata) return wrapper return decorator def is_computation_function(function: Callable) -> bool: """Check if a function is a Sigima computation function. Args: function: The function to check. Returns: True if the function is a Sigima computation function, False otherwise. """ return getattr(function, COMPUTATION_METADATA_ATTR, None) is not None def get_computation_metadata(function: Callable) -> ComputationMetadata: """Get the metadata of a Sigima computation function. Args: function: The function to get metadata from. Returns: Computation function metadata. Raises: ValueError: If the function is not a Sigima computation function. """ metadata = getattr(function, COMPUTATION_METADATA_ATTR, None) if not isinstance(metadata, ComputationMetadata): raise ValueError( f"The function {function.__name__} is not a Sigima computation function." ) return metadata def find_computation_functions() -> list[tuple[str, Callable]]: """Find all computation functions in the `sigima.proc` package. This function uses introspection to locate all functions decorated with `@computation_function` in the `sigima.proc` package and its subpackages. Args: module: Optional module to search in. If None, the current module is used. Returns: A list of tuples, each containing the function name and the function object. """ functions = [] objs = [] for _, modname, _ in pkgutil.walk_packages( path=[osp.dirname(__file__)], prefix=".".join(__name__.split(".")[:-1]) + "." ): module = importlib.import_module(modname) for name, obj in inspect.getmembers(module, inspect.isfunction): if is_computation_function(obj): if obj in objs: # Avoid double entries for the same function continue objs.append(obj) functions.append((modname, name, obj.__doc__)) return functions Sigima-1.1.1/sigima/proc/image/000077500000000000000000000000001514013333200162145ustar00rootroot00000000000000Sigima-1.1.1/sigima/proc/image/__init__.py000066400000000000000000000235771514013333200203430ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Basic image processing ~~~~~~~~~~~~~~~~~~~~~~ .. automodule:: sigima.proc.image.base :members: :no-index: Arithmetic ~~~~~~~~~~ .. automodule:: sigima.proc.image.arithmetic :members: :no-index: Mathematical Operations ~~~~~~~~~~~~~~~~~~~~~~~ .. automodule:: sigima.proc.image.mathops :members: :no-index: Measurements ~~~~~~~~~~~~ .. automodule:: sigima.proc.image.measurement :members: :no-index: Extraction ~~~~~~~~~~ .. automodule:: sigima.proc.image.extraction :members: :no-index: Filtering ~~~~~~~~~ .. automodule:: sigima.proc.image.filtering :members: :no-index: Fourier ~~~~~~~ .. automodule:: sigima.proc.image.fourier :members: :no-index: Thresholding ~~~~~~~~~~~~ .. automodule:: sigima.proc.image.threshold :members: :no-index: Exposure correction ~~~~~~~~~~~~~~~~~~~ .. automodule:: sigima.proc.image.exposure :members: :no-index: Preprocessing ~~~~~~~~~~~~~ .. automodule:: sigima.proc.image.preprocessing :members: :no-index: Restoration ~~~~~~~~~~~ .. automodule:: sigima.proc.image.restoration :members: :no-index: Noise ~~~~~ .. automodule:: sigima.proc.image.noise :members: :no-index: Morphology ~~~~~~~~~~ .. automodule:: sigima.proc.image.morphology :members: :no-index: Edge detection ~~~~~~~~~~~~~~ .. automodule:: sigima.proc.image.edges :members: :no-index: Detection ~~~~~~~~~ .. automodule:: sigima.proc.image.detection :members: :no-index: Geometry ~~~~~~~~ .. automodule:: sigima.proc.image.geometry :members: :no-index: Transformation features ^^^^^^^^^^^^^^^^^^^^^^^ .. automodule:: sigima.proc.image.transformations :members: :no-index: """ # pylint: disable=invalid-name # Allows short reference names like x, y, ... # MARK: Important notes # --------------------- # - All `guidata.dataset.DataSet` classes must also be imported # in the `sigima.params` module. # - All functions decorated by `computation_function` defined in the other modules # of this package must be imported right here. from __future__ import annotations import guidata.dataset as gds from sigima.config import _ from sigima.enums import PadLocation2D from sigima.proc.image.arithmetic import ( addition, addition_constant, arithmetic, average, difference, difference_constant, division, division_constant, product, product_constant, quadratic_difference, standard_deviation, ) from sigima.proc.image.base import ( Wrap1to1Func, compute_geometry_from_obj, dst_1_to_1_signal, restore_data_outside_roi, ) from sigima.proc.image.detection import ( BlobDOGParam, BlobDOHParam, BlobLOGParam, BlobOpenCVParam, ContourShapeParam, HoughCircleParam, Peak2DDetectionParam, apply_detection_rois, blob_dog, blob_doh, blob_log, blob_opencv, contour_shape, hough_circle_peaks, peak_detection, ) from sigima.proc.image.edges import ( CannyParam, canny, farid, farid_h, farid_v, laplace, prewitt, prewitt_h, prewitt_v, roberts, scharr, scharr_h, scharr_v, sobel, sobel_h, sobel_v, ) from sigima.proc.image.exposure import ( AdjustGammaParam, AdjustLogParam, AdjustSigmoidParam, EqualizeAdaptHistParam, EqualizeHistParam, FlatFieldParam, NormalizeParam, RescaleIntensityParam, adjust_gamma, adjust_log, adjust_sigmoid, clip, equalize_adapthist, equalize_hist, flatfield, histogram, normalize, offset_correction, rescale_intensity, ) from sigima.proc.image.extraction import ( AverageProfileParam, Direction, LineProfileParam, RadialProfileParam, ROIGridParam, SegmentProfileParam, average_profile, extract_roi, extract_rois, generate_image_grid_roi, line_profile, radial_profile, segment_profile, ) from sigima.proc.image.filtering import ( ButterworthParam, GaussianFreqFilterParam, butterworth, gaussian_filter, gaussian_freq_filter, moving_average, moving_median, wiener, ) from sigima.proc.image.fourier import ( fft, ifft, magnitude_spectrum, phase_spectrum, psd, ) from sigima.proc.image.geometry import ( Resampling2DParam, ResizeParam, RotateParam, TranslateParam, UniformCoordsParam, XYZCalibrateParam, calibration, fliph, flipv, resampling, resize, rotate, rotate90, rotate270, set_uniform_coords, translate, transpose, ) from sigima.proc.image.mathops import ( DataTypeIParam, Log10ZPlusNParam, absolute, astype, complex_from_magnitude_phase, complex_from_real_imag, convolution, deconvolution, exp, imag, inverse, log10, log10_z_plus_n, phase, real, ) from sigima.proc.image.measurement import ( centroid, enclosing_circle, horizontal_projection, stats, vertical_projection, ) from sigima.proc.image.morphology import ( MorphologyParam, black_tophat, closing, dilation, erosion, opening, white_tophat, ) from sigima.proc.image.noise import ( add_gaussian_noise, add_poisson_noise, add_uniform_noise, ) from sigima.proc.image.preprocessing import ( BinningParam, ZeroPadding2DParam, binning, zero_padding, ) from sigima.proc.image.restoration import ( DenoiseBilateralParam, DenoiseTVParam, DenoiseWaveletParam, denoise_bilateral, denoise_tophat, denoise_tv, denoise_wavelet, erase, ) from sigima.proc.image.threshold import ( ThresholdParam, threshold, threshold_isodata, threshold_li, threshold_mean, threshold_minimum, threshold_otsu, threshold_triangle, threshold_yen, ) from sigima.proc.image.transformations import transformer __all__ = [ "AdjustGammaParam", "AdjustLogParam", "AdjustSigmoidParam", "AverageProfileParam", "BinningParam", "BlobDOGParam", "BlobDOHParam", "BlobLOGParam", "BlobOpenCVParam", "ButterworthParam", "CannyParam", "ContourShapeParam", "DataTypeIParam", "DenoiseBilateralParam", "DenoiseTVParam", "DenoiseWaveletParam", "Direction", "EqualizeAdaptHistParam", "EqualizeHistParam", "FlatFieldParam", "GaussianFreqFilterParam", "GridParam", "HoughCircleParam", "LineProfileParam", "Log10ZPlusNParam", "MorphologyParam", "NormalizeParam", "PadLocation2D", "Peak2DDetectionParam", "ROIGridParam", "RadialProfileParam", "Resampling2DParam", "RescaleIntensityParam", "ResizeParam", "RotateParam", "SegmentProfileParam", "ThresholdParam", "TranslateParam", "UniformCoordsParam", "Wrap1to1Func", "XYZCalibrateParam", "ZeroPadding2DParam", "absolute", "add_gaussian_noise", "add_poisson_noise", "add_uniform_noise", "addition", "addition_constant", "adjust_gamma", "adjust_log", "adjust_sigmoid", "apply_detection_rois", "arithmetic", "astype", "average", "average_profile", "binning", "black_tophat", "blob_dog", "blob_doh", "blob_log", "blob_opencv", "butterworth", "calibration", "canny", "centroid", "clip", "closing", "complex_from_magnitude_phase", "complex_from_real_imag", "compute_geometry_from_obj", "contour_shape", "convolution", "deconvolution", "denoise_bilateral", "denoise_tophat", "denoise_tv", "denoise_wavelet", "difference", "difference_constant", "dilation", "division", "division_constant", "dst_1_to_1_signal", "enclosing_circle", "equalize_adapthist", "equalize_hist", "erase", "erosion", "exp", "extract_roi", "extract_rois", "farid", "farid_h", "farid_v", "fft", "flatfield", "fliph", "flipv", "gaussian_filter", "gaussian_freq_filter", "generate_image_grid_roi", "histogram", "horizontal_projection", "hough_circle_peaks", "ifft", "imag", "inverse", "laplace", "line_profile", "log10", "log10_z_plus_n", "magnitude_spectrum", "moving_average", "moving_median", "normalize", "offset_correction", "opening", "peak_detection", "phase", "phase_spectrum", "prewitt", "prewitt_h", "prewitt_v", "product", "product_constant", "psd", "quadratic_difference", "radial_profile", "real", "resampling", "rescale_intensity", "resize", "restore_data_outside_roi", "roberts", "rotate", "rotate90", "rotate270", "scharr", "scharr_h", "scharr_v", "segment_profile", "set_uniform_coords", "sobel", "sobel_h", "sobel_v", "standard_deviation", "stats", "threshold", "threshold_isodata", "threshold_li", "threshold_mean", "threshold_minimum", "threshold_otsu", "threshold_triangle", "threshold_yen", "transformer", "translate", "transpose", "vertical_projection", "white_tophat", "wiener", "zero_padding", ] class GridParam(gds.DataSet): """Grid parameters""" _prop = gds.GetAttrProp("direction") _directions = (("col", _("columns")), ("row", _("rows"))) direction = gds.ChoiceItem(_("Distribute over"), _directions, radio=True).set_prop( "display", store=_prop ) cols = gds.IntItem(_("Columns"), default=1, nonzero=True).set_prop( "display", active=gds.FuncProp(_prop, lambda x: x == "col") ) rows = gds.IntItem(_("Rows"), default=1, nonzero=True).set_prop( "display", active=gds.FuncProp(_prop, lambda x: x == "row") ) colspac = gds.FloatItem(_("Column spacing"), default=0.0, min=0.0) rowspac = gds.FloatItem(_("Row spacing"), default=0.0, min=0.0) Sigima-1.1.1/sigima/proc/image/arithmetic.py000066400000000000000000000263701514013333200207270ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Arithmetic computation module ----------------------------- This module provides arithmetic operations for images, such as pixel-wise addition, subtraction, multiplication, division, as well as operations with constants and combined arithmetic formulas. Main features include: - Pixel-wise addition, subtraction, multiplication, and division between images - Application of arithmetic operations with constants to images - Support for quadratic difference and general arithmetic expressions These functions are typically used for basic algebraic processing and normalization of image data. """ # pylint: disable=invalid-name # Allows short reference names like x, y, ... # Note: # ---- # - All `guidata.dataset.DataSet` parameter classes must also be imported # in the `sigima.params` module. # - All functions decorated by `computation_function` must be imported in the upper # level `sigima.proc.image` module. from __future__ import annotations import warnings import numpy as np from sigima.enums import MathOperator from sigima.objects.image import ImageObj from sigima.proc.base import ( ArithmeticParam, ConstantParam, ) from sigima.proc.decorator import computation_function from sigima.proc.image.base import ( dst_1_to_1, dst_2_to_1, dst_n_to_1, restore_data_outside_roi, ) from sigima.tools.datatypes import clip_astype # NOTE: Only parameter classes DEFINED in this module should be included in __all__. # Parameter classes imported from other modules (like sigima.proc.base) should NOT # be re-exported to avoid Sphinx cross-reference conflicts. The sigima.params module # serves as the central API point that imports and re-exports all parameter classes. __all__ = [ "addition", "addition_constant", "arithmetic", "average", "difference", "difference_constant", "division", "division", "division_constant", "product", "product_constant", "quadratic_difference", "standard_deviation", ] # MARK: compute_n_to_1 functions ------------------------------------------------------- # Functions with N input images and 1 output image # -------------------------------------------------------------------------------------- # Those functions are perfoming a computation on N input images and return a single # output image. If we were only executing these functions locally, we would not need # to define them here, but since we are using the multiprocessing module, we need to # define them here so that they can be pickled and sent to the worker processes. # Also, we need to systematically return the output image object, even if it is already # modified in place, because the multiprocessing module will not be able to retrieve # the modified object from the worker processes. @computation_function() def addition(src_list: list[ImageObj]) -> ImageObj: """Add images in the list and return the result image object Args: src_list: list of input image objects Returns: Output image object (modified in place) """ dst = dst_n_to_1(src_list, "Σ") # `dst` data is initialized to `src_list[0]` data for src in src_list[1:]: dst.data = np.add(dst.data, src.data, dtype=float) restore_data_outside_roi(dst, src_list[0]) return dst @computation_function() def average(src_list: list[ImageObj]) -> ImageObj: """Compute the average of images in the list and return the result image object Args: src_list: list of input image objects Returns: Output image object (modified in place) """ dst = dst_n_to_1(src_list, "µ") # `dst` data is initialized to `src_list[0]` data for src in src_list[1:]: dst.data = np.add(dst.data, src.data, dtype=float) dst.data /= len(src_list) restore_data_outside_roi(dst, src_list[0]) return dst @computation_function() def standard_deviation(src_list: list[ImageObj]) -> ImageObj: """Compute the element-wise standard deviation of multiple images. The first image in the list defines the "base" image. All other images are used to compute the element-wise standard deviation with the base image. .. note:: If all images share the same region of interest (ROI), the standard deviation is computed only within the ROI. .. warning:: It is assumed that all images have the same size and x-coordinates. Args: src_list: List of source images. Returns: Image object representing the standard deviation of the source images. """ dst = dst_n_to_1(src_list, "𝜎") # `dst` data is initialized to `src_list[0]` data assert dst.data is not None y_array = np.array([src.data for src in src_list], dtype=dst.data.dtype) dst.data = np.std(y_array, axis=0, ddof=0) restore_data_outside_roi(dst, src_list[0]) return dst @computation_function() def product(src_list: list[ImageObj]) -> ImageObj: """Multiply images in the list and return the result image object Args: src_list: list of input image objects Returns: Output image object (modified in place) """ dst = dst_n_to_1(src_list, "Π") # `dst` data is initialized to `src_list[0]` data for src in src_list[1:]: dst.data = np.multiply(dst.data, src.data, dtype=float) restore_data_outside_roi(dst, src_list[0]) return dst @computation_function() def addition_constant(src: ImageObj, p: ConstantParam) -> ImageObj: """Add **dst** and a constant value and return the new result image object Args: src: input image object p: constant value Returns: Result image object **src** + **p.value** (new object) """ # For the addition of a constant value, we convert the constant value to the same # data type as the input image, for consistency. value = np.array(p.value).astype(dtype=src.data.dtype) dst = dst_1_to_1(src, "+", str(value)) dst.data = np.add(src.data, value, dtype=float) restore_data_outside_roi(dst, src) return dst @computation_function() def difference_constant(src: ImageObj, p: ConstantParam) -> ImageObj: """Subtract a constant value from an image and return the new result image object Args: src: input image object p: constant value Returns: Result image object **src** - **p.value** (new object) """ # For the subtraction of a constant value, we convert the constant value to the same # data type as the input image, for consistency. value = np.array(p.value).astype(dtype=src.data.dtype) dst = dst_1_to_1(src, "-", str(value)) dst.data = np.subtract(src.data, value, dtype=float) restore_data_outside_roi(dst, src) return dst @computation_function() def product_constant(src: ImageObj, p: ConstantParam) -> ImageObj: """Multiply **dst** by a constant value and return the new result image object Args: src: input image object p: constant value Returns: Result image object **src** * **p.value** (new object) """ # For the multiplication by a constant value, we do not convert the constant value # to the same data type as the input image, because we want to allow the user to # multiply an image by a constant value of a different data type. The final data # type conversion ensures that the output image has the same data type as the input # image. dst = dst_1_to_1(src, "×", str(p.value)) dst.data = np.multiply(src.data, p.value, dtype=float) restore_data_outside_roi(dst, src) return dst @computation_function() def division_constant(src: ImageObj, p: ConstantParam) -> ImageObj: """Divide an image by a constant value and return the new result image object Args: src: input image object p: constant value Returns: Result image object **src** / **p.value** (new object) """ # For the division by a constant value, we do not convert the constant value to the # same data type as the input image, because we want to allow the user to divide an # image by a constant value of a different data type. The final data type conversion # ensures that the output image has the same data type as the input image. dst = dst_1_to_1(src, "/", str(p.value)) dst.data = np.divide(src.data, p.value, dtype=float) restore_data_outside_roi(dst, src) return dst # MARK: compute_2_to_1 functions ------------------------------------------------------- # Functions with N input images + 1 input image and N output images # -------------------------------------------------------------------------------------- @computation_function() def arithmetic(src1: ImageObj, src2: ImageObj, p: ArithmeticParam) -> ImageObj: """Compute arithmetic operation on two images Args: src1: input image object src2: input image object p: arithmetic parameters Returns: Result image object """ initial_dtype = src1.data.dtype title = p.operation.replace("obj1", "{0}").replace("obj2", "{1}") dst = src1.copy(title=title) o, a, b = p.operator, p.factor, p.constant # Apply operator if o in (MathOperator.MULTIPLY, MathOperator.DIVIDE) and a == 0.0: dst.data = np.ones_like(src1.data) * b elif o == MathOperator.ADD: dst.data = np.add(src1.data, src2.data, dtype=float) * a + b elif o == MathOperator.SUBTRACT: dst.data = np.subtract(src1.data, src2.data, dtype=float) * a + b elif o == MathOperator.MULTIPLY: dst.data = np.multiply(src1.data, src2.data, dtype=float) * a + b elif o == MathOperator.DIVIDE: dst.data = np.divide(src1.data, src2.data, dtype=float) * a + b # Eventually convert to initial data type if p.restore_dtype: dst.data = clip_astype(dst.data, initial_dtype) restore_data_outside_roi(dst, src1) return dst @computation_function() def difference(src1: ImageObj, src2: ImageObj) -> ImageObj: """Compute difference between two images Args: src1: input image object src2: input image object Returns: Result image object **src1** - **src2** (new object) """ dst = dst_2_to_1(src1, src2, "-") dst.data = np.subtract(src1.data, src2.data, dtype=float) restore_data_outside_roi(dst, src1) return dst @computation_function() def quadratic_difference(src1: ImageObj, src2: ImageObj) -> ImageObj: """Compute quadratic difference between two images Args: src1: input image object src2: input image object Returns: Result image object (**src1** - **src2**) / sqrt(2.0) (new object) """ dst = dst_2_to_1(src1, src2, "quadratic_difference") dst.data = np.subtract(src1.data, src2.data, dtype=float) / np.sqrt(2.0) restore_data_outside_roi(dst, src1) return dst @computation_function() def division(src1: ImageObj, src2: ImageObj) -> ImageObj: """Compute division between two images Args: src1: input image object src2: input image object Returns: Result image object **src1** / **src2** (new object) """ dst = dst_2_to_1(src1, src2, "/") with warnings.catch_warnings(): warnings.simplefilter("ignore", category=RuntimeWarning) dst.data = np.divide(src1.data, src2.data, dtype=float) restore_data_outside_roi(dst, src1) return dst Sigima-1.1.1/sigima/proc/image/base.py000066400000000000000000000272611514013333200175100ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Base computation module ----------------------- This module provides core classes and utility functions that serve as building blocks for the other computation modules. Main features include: - Generic helper functions used across image processing modules - Core wrappers and infrastructure for computation functions Intended primarily for internal use, these tools support consistent API design and code reuse. """ from __future__ import annotations from collections.abc import Callable from typing import Any import numpy as np from sigima.objects import NO_ROI, GeometryResult, ImageObj, KindShape, SignalObj from sigima.proc.base import dst_1_to_1 as _dst_1_to_1_base from sigima.proc.base import dst_2_to_1 as _dst_2_to_1_base from sigima.proc.base import dst_n_to_1 as _dst_n_to_1_base from sigima.proc.base import new_signal_result # NOTE: Only parameter classes DEFINED in this module should be included in __all__. # Parameter classes imported from other modules (like sigima.proc.base) should NOT # be re-exported to avoid Sphinx cross-reference conflicts. The sigima.params module # serves as the central API point that imports and re-exports all parameter classes. __all__ = [ "Wrap1to1Func", "compute_geometry_from_obj", "dst_1_to_1", "dst_1_to_1_signal", "dst_2_to_1", "dst_n_to_1", "restore_data_outside_roi", ] def _reset_lut_range(dst: ImageObj) -> None: """Reset LUT range so the image auto-scales on display.""" dst.zscalemin = None dst.zscalemax = None def dst_1_to_1(src: ImageObj, name: str, suffix: str | None = None) -> ImageObj: """Create a result image object for 1-to-1 processing. This is the image-specific version that resets the LUT range after copying, so the result image auto-scales to fit its new data range. Args: src: source image object name: name of the function suffix: suffix to add to the title Returns: Result image object with LUT range reset """ dst = _dst_1_to_1_base(src, name, suffix) _reset_lut_range(dst) return dst def dst_2_to_1( src1: ImageObj, src2: ImageObj, name: str, suffix: str | None = None ) -> ImageObj: """Create a result image object for 2-to-1 processing. This is the image-specific version that resets the LUT range after copying, so the result image auto-scales to fit its new data range. Args: src1: first source image object src2: second source image object name: name of the function suffix: suffix to add to the title Returns: Result image object with LUT range reset """ dst = _dst_2_to_1_base(src1, src2, name, suffix) _reset_lut_range(dst) return dst def dst_n_to_1( src_list: list[ImageObj], name: str, suffix: str | None = None ) -> ImageObj: """Create a result image object for n-to-1 processing. This is the image-specific version that resets the LUT range after copying, so the result image auto-scales to fit its new data range. Args: src_list: list of source image objects name: name of the function suffix: suffix to add to the title Returns: Result image object with LUT range reset """ dst = _dst_n_to_1_base(src_list, name, suffix) _reset_lut_range(dst) return dst def restore_data_outside_roi(dst: ImageObj, src: ImageObj) -> None: """Restore data outside the Region Of Interest (ROI) of the input image after a computation, only if the input image has a ROI, and if the output image has the same ROI as the input image, and if the data types are compatible, and if the shapes are the same. Otherwise, do nothing. Args: dst: output image object src: input image object """ if src.maskdata is not None and dst.maskdata is not None: if ( np.array_equal(src.maskdata, dst.maskdata) and ( dst.data.dtype == src.data.dtype or not np.issubdtype(dst.data.dtype, np.integer) ) and dst.data.shape == src.data.shape ): dst.data[src.maskdata] = src.data[src.maskdata] class Wrap1to1Func: """Wrap a 1 array → 1 array function to produce a 1 image → 1 image function, which can be used as a Sigima computation function and inside DataLab's infrastructure to perform computations with the Image Processor object. This wrapping mechanism using a class is necessary for the resulted function to be pickable by the ``multiprocessing`` module. The instance of this wrapper is callable and returns a :class:`sigima.objects.ImageObj` object. Example: >>> import numpy as np >>> from sigima.proc.image import Wrap1to1Func >>> import sigima.objects >>> def add_noise(data): ... return data + np.random.random(data.shape) >>> compute_add_noise = Wrap1to1Func(add_noise) >>> data= np.ones((100, 100)) >>> ima0 = sigima.objects.create_image("Example", data) >>> ima1 = compute_add_noise(ima0) Args: func: 1 array → 1 array function *args: Additional positional arguments to pass to the function **kwargs: Additional keyword arguments to pass to the function .. note:: If `func_name` is provided in the keyword arguments, it will be used as the function name instead of the default name derived from the function itself. """ def __init__(self, func: Callable, *args: Any, **kwargs: Any) -> None: self.func = func self.args = args self.kwargs = kwargs self.__name__ = self.kwargs.pop("func_name", func.__name__) self.__doc__ = func.__doc__ self.__call__.__func__.__doc__ = self.func.__doc__ def __call__(self, src: ImageObj) -> ImageObj: """Compute the function on the input image and return the result image Args: src: input image object Returns: Output image object """ suffix = ", ".join( [str(arg) for arg in self.args] + [f"{k}={v}" for k, v in self.kwargs.items() if v is not None] ) dst = dst_1_to_1(src, self.__name__, suffix) dst.data = self.func(src.data, *self.args, **self.kwargs) restore_data_outside_roi(dst, src) return dst def dst_1_to_1_signal(src: ImageObj, name: str, suffix: str | None = None) -> SignalObj: """Create a result signal object, for processing functions that take a single image object as input and return a single signal object (1-to-1-signal). Args: src: input image object name: name of the processing function Returns: Output signal object """ return new_signal_result( src, name, suffix, (src.xunit, src.zunit), (src.xlabel, src.zlabel) ) def compute_geometry_from_obj( title: str, shape: KindShape, obj: ImageObj, func: Callable, *args: Any, ) -> GeometryResult | None: """Compute a geometry shape from an image object by executing a computation function on the data of the image object, for each ROI (Region Of Interest) in the image. Args: title: result title shape: result shape kind obj: input image object func: computation function *args: computation function arguments Returns: A geometry result object or None if no result is found. .. important:: **Coordinate Conversion**: This function automatically converts coordinates from pixel units (image indices) to physical units using the image object's calibration information. - **Input**: Computation function returns coordinates in pixel units - **Output**: GeometryResult with coordinates in physical units (e.g., mm, µm) The conversion is performed using the image's calibration parameters: ``physical_x = obj.dx * pixel_x + obj.x0`` and ``physical_y = obj.dy * pixel_y + obj.y0`` .. warning:: The computation function must take either a single argument (the data) or multiple arguments (the data followed by the computation parameters). Moreover, the computation function must return a single value or a NumPy array containing the result of the computation. This array contains the coordinates of points, polygons, circles or ellipses in the form [[x, y], ...], or [[x0, y0, x1, y1, ...], ...], or [[x0, y0, r], ...], or [[x0, y0, a, b, theta], ...]. Example: >>> # func returns pixel coordinates like [[10, 20], [30, 40]] >>> result = compute_geometry_from_obj( ... "Points", KindShape.POINT, image_obj, func ... ) >>> # result.coords now contains physical coordinates like [[0.5, 1.0], >>> # [1.5, 2.0]] See Also: :class:`~sigima.objects.scalar.GeometryResult`: The result object that stores physical coordinates. """ rows: list[np.ndarray] = [] num_cols: list[int] = [] roi_idx: list[int] = [] for i_roi in obj.iterate_roi_indices(): data_roi = obj.get_data(i_roi) if args is None: coords: np.ndarray = func(data_roi) else: coords: np.ndarray = func(data_roi, *args) # This is a very long condition, but it's still quite readable, so we keep it # as is and disable the pylint warning. # # pylint: disable=too-many-boolean-expressions if not isinstance(coords, np.ndarray) or ( ( coords.ndim != 2 or coords.shape[1] < 2 or (coords.shape[1] > 5 and coords.shape[1] % 2 != 0) ) and coords.size > 0 ): raise ValueError( f"Computation function {func.__name__} must return a NumPy array " f"containing coordinates of points, polygons, circles or ellipses " f"(in the form [[x, y], ...], or [[x0, y0, x1, y1, ...], ...], or " f"[[x0, y0, r], ...], or [[x0, y0, a, b, theta], ...]), or an empty " f"array." ) if coords.size: coords = np.array(coords, dtype=float) if coords.shape[1] % 2 == 0: # Coordinates are in the form [x0, y0, x1, y1, ...] colx, coly = slice(None, None, 2), slice(1, None, 2) else: # Circle [x0, y0, r] or ellipse coordinates [x0, y0, a, b, theta] colx, coly = 0, 1 coords[:, colx] = obj.dx * coords[:, colx] + obj.x0 coords[:, coly] = obj.dy * coords[:, coly] + obj.y0 if obj.roi is not None: x0, y0, _x1, _y1 = obj.roi.get_single_roi(i_roi).get_bounding_box(obj) coords[:, colx] += x0 - obj.x0 coords[:, coly] += y0 - obj.y0 rows.append(coords) num_cols.append(coords.shape[1]) roi_idx.extend([NO_ROI if i_roi is None else int(i_roi)] * coords.shape[0]) if rows: if len(set(num_cols)) != 1: # This happens when the number of columns is not the same for all ROIs. # As of now, this happens only for polygon contours. # We need to pad the arrays with NaNs. max_cols = max(num_cols) num_rows = sum(coords.shape[0] for coords in rows) array = np.full((num_rows, max_cols), np.nan) start = 0 for row in rows: array[start : start + row.shape[0], : row.shape[1]] = row start += row.shape[0] else: array = np.vstack(rows) return GeometryResult(title, shape, array, np.asarray(roi_idx, dtype=int)) return None Sigima-1.1.1/sigima/proc/image/detection.py000066400000000000000000000453471514013333200205610ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Detection computation module ---------------------------- This module provides algorithms for detecting objects or patterns in images, such as blobs, peaks, or custom structures. Main features include: - Blob and peak detection algorithms - Support for object localization and counting Detection algorithms are fundamental for many image analysis pipelines, enabling automated extraction of regions or features of interest. """ # pylint: disable=invalid-name # Allows short reference names like x, y, ... # Note: # ---- # All dataset classes must also be imported in the sigima.params module. from __future__ import annotations import guidata.dataset as gds import sigima.enums import sigima.tools.image from sigima.config import _ from sigima.objects import ( GeometryResult, ImageObj, KindShape, create_image_roi_around_points, ) from sigima.proc.decorator import computation_function from sigima.proc.image.base import compute_geometry_from_obj # NOTE: Only parameter classes DEFINED in this module should be included in __all__. # Parameter classes imported from other modules (like sigima.proc.base) should NOT # be re-exported to avoid Sphinx cross-reference conflicts. The sigima.params module # serves as the central API point that imports and re-exports all parameter classes. __all__ = [ "BaseBlobParam", "BlobDOGParam", "BlobDOHParam", "BlobLOGParam", "BlobOpenCVParam", "ContourShapeParam", "DetectionROIParam", "GenericDetectionParam", "HoughCircleParam", "Peak2DDetectionParam", "apply_detection_rois", "blob_dog", "blob_doh", "blob_log", "blob_opencv", "contour_shape", "hough_circle_peaks", "peak_detection", "store_roi_creation_metadata", ] class DetectionROIParam(gds.DataSet): """ROI creation parameters for detection algorithms. This class can be inherited by any detection parameter class to provide standardized ROI creation functionality. """ _roi_g = gds.BeginGroup(_("Regions of interest")) _prop_create_rois = gds.ValueProp(False) create_rois = gds.BoolItem( _("Create regions of interest"), default=False, help=_( "Regions of interest will be created around detected features, " "if at least two features are detected.\n" "ROI size is optimized based on feature spacing." ), ).set_prop("display", store=_prop_create_rois) roi_geometry = gds.ChoiceItem( _("ROI geometry"), sigima.enums.DetectionROIGeometry, default=sigima.enums.DetectionROIGeometry.RECTANGLE, ).set_prop("display", active=_prop_create_rois) _roi_g_e = gds.EndGroup(_("Regions of interest")) def store_roi_creation_metadata( geometry: GeometryResult | None, create_rois: bool, roi_geometry: sigima.enums.DetectionROIGeometry | None = None, ) -> GeometryResult | None: """Store ROI creation metadata in geometry result attributes. This function is called by computation functions to mark that ROI creation should be performed on the result. The actual ROI creation is done later via apply_detection_rois(). Args: geometry: Geometry result from detection create_rois: Whether to create ROIs roi_geometry: ROI geometry type (if None, uses default RECTANGLE) Returns: The same geometry object (for chaining), or None if geometry is None Example: >>> geometry = compute_geometry_from_obj(...) >>> return store_roi_creation_metadata(geometry, p.create_rois, p.roi_geometry) """ if geometry is not None and create_rois and len(geometry) > 1: geometry.attrs["create_rois"] = True if roi_geometry is None: roi_geometry = sigima.enums.DetectionROIGeometry.RECTANGLE # Store as string value for HDF5 serialization compatibility geometry.attrs["roi_geometry"] = roi_geometry.value return geometry def apply_detection_rois( obj: ImageObj, geometry: GeometryResult, force: bool = False, roi_geometry: sigima.enums.DetectionROIGeometry | None = None, ) -> bool: """Apply ROI creation from detection geometry result. This function checks if the geometry result contains ROI creation metadata and applies it to the image object by creating ROIs around detected features. Args: obj: Image object to modify geometry: Geometry result from a detection function force: If True, create ROIs even if not requested in the result attrs roi_geometry: Override ROI geometry from attrs (if None, uses attrs value) Returns: True if ROIs were created, False otherwise Example: >>> from sigima.proc.image import peak_detection, apply_detection_rois >>> from sigima.params import Peak2DDetectionParam >>> param = Peak2DDetectionParam() >>> param.create_rois = True >>> geometry = peak_detection(img, param) >>> apply_detection_rois(img, geometry) # Creates ROIs on img """ if geometry is None: return False # Check if ROI creation was requested (or forced) create_rois = force or geometry.attrs.get("create_rois", False) if not create_rois or len(geometry) < 2: return False # Get ROI geometry from parameter, attrs, or use default if roi_geometry is None: roi_geometry = geometry.attrs.get( "roi_geometry", sigima.enums.DetectionROIGeometry.RECTANGLE, ) # Get detection coordinates (centers of detected objects) coords = geometry.centers() try: obj.roi = create_image_roi_around_points(coords, roi_geometry=roi_geometry) return True except ValueError: return False class GenericDetectionParam(gds.DataSet): """Generic detection parameters""" threshold = gds.FloatItem( _("Relative threshold"), default=0.5, min=0.1, max=0.9, help=_( "Detection threshold, relative to difference between " "data maximum and minimum" ), ) class Peak2DDetectionParam(DetectionROIParam, GenericDetectionParam): """Peak detection parameters""" size = gds.IntItem( _("Neighborhoods size"), default=None, check=False, # Allow None value min=1, unit="pixels", help=_( "Size of the sliding window used in maximum/minimum filtering algorithm " "(if no value is provided, the algorithm will use a default size " "based on the image size). " ), ) @computation_function() def peak_detection(obj: ImageObj, p: Peak2DDetectionParam) -> GeometryResult | None: """Compute 2D peak detection with :py:func:`sigima.tools.image.get_2d_peaks_coords` Args: obj: input image p: parameters Returns: Peak coordinates (with ROI creation info in attrs if requested) """ geometry = compute_geometry_from_obj( "peak", KindShape.POINT, obj, sigima.tools.image.get_2d_peaks_coords, p.size, p.threshold, ) return store_roi_creation_metadata(geometry, p.create_rois, p.roi_geometry) class ContourShapeParam(GenericDetectionParam): """Contour shape parameters""" # Keep choices aligned with supported geometry kinds assert set(item.name for item in sigima.enums.ContourShape).issubset( set(item.name for item in KindShape) ) shape = gds.ChoiceItem(_("Shape"), sigima.enums.ContourShape) @computation_function() def contour_shape(image: ImageObj, p: ContourShapeParam) -> GeometryResult | None: """Compute contour shape with :py:func:`sigima.tools.image.get_contour_shapes`.""" shape: sigima.enums.ContourShape = p.shape kindshape = getattr(KindShape, shape.name) geometry = compute_geometry_from_obj( "contour", kindshape, image, sigima.tools.image.get_contour_shapes, shape, p.threshold, ) return geometry class BaseBlobParam(gds.DataSet): """Base class for blob detection parameters""" min_sigma = gds.FloatItem( "σmin", default=10.0, unit="pixels", min=0, nonzero=True, help=_( "The minimum standard deviation for Gaussian Kernel. " "Keep this low to detect smaller blobs." ), ) max_sigma = gds.FloatItem( "σmax", default=30.0, unit="pixels", min=0, nonzero=True, help=_( "The maximum standard deviation for Gaussian Kernel. " "Keep this high to detect larger blobs." ), ) threshold_rel = gds.FloatItem( _("Relative threshold"), default=0.2, min=0.0, max=1.0, help=_("Minimum intensity of blobs."), ) overlap = gds.FloatItem( _("Overlap"), default=0.5, min=0.0, max=1.0, help=_( "If two blobs overlap by a fraction greater than this value, the " "smaller blob is eliminated." ), ) class BlobDOGParam(DetectionROIParam, BaseBlobParam): """Blob detection using Difference of Gaussian method""" exclude_border = gds.BoolItem( _("Exclude border"), default=True, help=_("If True, exclude blobs from the border of the image."), ) @computation_function() def blob_dog(image: ImageObj, p: BlobDOGParam) -> GeometryResult | None: """Compute blobs using Difference of Gaussian method with :py:func:`sigima.tools.image.find_blobs_dog` Args: imageOutput: input image p: parameters Returns: Blobs coordinates (with ROI creation info in attrs if requested) """ geometry = compute_geometry_from_obj( "blob_dog", KindShape.CIRCLE, image, sigima.tools.image.find_blobs_dog, p.min_sigma, p.max_sigma, p.overlap, p.threshold_rel, p.exclude_border, ) return store_roi_creation_metadata(geometry, p.create_rois, p.roi_geometry) class BlobDOHParam(DetectionROIParam, BaseBlobParam): """Blob detection using Determinant of Hessian method""" log_scale = gds.BoolItem( _("Log scale"), default=False, help=_( "If set intermediate values of standard deviations are interpolated " "using a logarithmic scale to the base 10. " "If not, linear interpolation is used." ), ) @computation_function() def blob_doh(image: ImageObj, p: BlobDOHParam) -> GeometryResult | None: """Compute blobs using Determinant of Hessian method with :py:func:`sigima.tools.image.find_blobs_doh` Args: imageOutput: input image p: parameters Returns: Blobs coordinates (with ROI creation info in attrs if requested) """ geometry = compute_geometry_from_obj( "blob_doh", KindShape.CIRCLE, image, sigima.tools.image.find_blobs_doh, p.min_sigma, p.max_sigma, p.overlap, p.log_scale, p.threshold_rel, ) return store_roi_creation_metadata(geometry, p.create_rois, p.roi_geometry) class BlobLOGParam(BlobDOHParam): """Blob detection using Laplacian of Gaussian method""" exclude_border = gds.BoolItem( _("Exclude border"), default=True, help=_("If True, exclude blobs from the border of the image."), ) @computation_function() def blob_log(image: ImageObj, p: BlobLOGParam) -> GeometryResult | None: """Compute blobs using Laplacian of Gaussian method with :py:func:`sigima.tools.image.find_blobs_log` Args: imageOutput: input image p: parameters Returns: Blobs coordinates (with ROI creation info in attrs if requested) """ geometry = compute_geometry_from_obj( "blob_log", KindShape.CIRCLE, image, sigima.tools.image.find_blobs_log, p.min_sigma, p.max_sigma, p.overlap, p.log_scale, p.threshold_rel, p.exclude_border, ) return store_roi_creation_metadata(geometry, p.create_rois, p.roi_geometry) class BlobOpenCVParam(DetectionROIParam, gds.DataSet): """Blob detection using OpenCV""" min_threshold = gds.FloatItem( _("Min. threshold"), default=10.0, min=0.0, help=_( "The minimum threshold between local maxima and minima. " "This parameter does not affect the quality of the blobs, " "only the quantity. Lower thresholds result in larger " "numbers of blobs." ), ) max_threshold = gds.FloatItem( _("Max. threshold"), default=200.0, min=0.0, help=_( "The maximum threshold between local maxima and minima. " "This parameter does not affect the quality of the blobs, " "only the quantity. Lower thresholds result in larger " "numbers of blobs." ), ) min_repeatability = gds.IntItem( _("Min. repeatability"), default=2, min=1, help=_( "The minimum number of times a blob needs to be detected " "in a sequence of images to be considered valid." ), ) min_dist_between_blobs = gds.FloatItem( _("Min. distance between blobs"), default=10.0, min=0.0, nonzero=True, help=_( "The minimum distance between two blobs. If blobs are found " "closer together than this distance, the smaller blob is removed." ), ) _prop_col = gds.ValueProp(False) filter_by_color = gds.BoolItem( _("Filter by color"), default=True, help=_("If true, the image is filtered by color instead of intensity."), ).set_prop("display", store=_prop_col) blob_color = gds.IntItem( _("Blob color"), default=0, help=_( "The color of the blobs to detect (0 for dark blobs, 255 for light blobs)." ), ).set_prop("display", active=_prop_col) _prop_area = gds.ValueProp(False) filter_by_area = gds.BoolItem( _("Filter by area"), default=True, help=_("If true, the image is filtered by blob area."), ).set_prop("display", store=_prop_area) min_area = gds.FloatItem( _("Min. area"), default=25.0, min=0.0, help=_("The minimum blob area."), ).set_prop("display", active=_prop_area) max_area = gds.FloatItem( _("Max. area"), default=500.0, min=0.0, help=_("The maximum blob area."), ).set_prop("display", active=_prop_area) _prop_circ = gds.ValueProp(False) filter_by_circularity = gds.BoolItem( _("Filter by circularity"), default=False, help=_("If true, the image is filtered by blob circularity."), ).set_prop("display", store=_prop_circ) min_circularity = gds.FloatItem( _("Min. circularity"), default=0.8, min=0.0, max=1.0, help=_("The minimum circularity of the blobs."), ).set_prop("display", active=_prop_circ) max_circularity = gds.FloatItem( _("Max. circularity"), default=1.0, min=0.0, max=1.0, help=_("The maximum circularity of the blobs."), ).set_prop("display", active=_prop_circ) _prop_iner = gds.ValueProp(False) filter_by_inertia = gds.BoolItem( _("Filter by inertia"), default=False, help=_("If true, the image is filtered by blob inertia."), ).set_prop("display", store=_prop_iner) min_inertia_ratio = gds.FloatItem( _("Min. inertia ratio"), default=0.6, min=0.0, max=1.0, help=_("The minimum inertia ratio of the blobs."), ).set_prop("display", active=_prop_iner) max_inertia_ratio = gds.FloatItem( _("Max. inertia ratio"), default=1.0, min=0.0, max=1.0, help=_("The maximum inertia ratio of the blobs."), ).set_prop("display", active=_prop_iner) _prop_conv = gds.ValueProp(False) filter_by_convexity = gds.BoolItem( _("Filter by convexity"), default=False, help=_("If true, the image is filtered by blob convexity."), ).set_prop("display", store=_prop_conv) min_convexity = gds.FloatItem( _("Min. convexity"), default=0.8, min=0.0, max=1.0, help=_("The minimum convexity of the blobs."), ).set_prop("display", active=_prop_conv) max_convexity = gds.FloatItem( _("Max. convexity"), default=1.0, min=0.0, max=1.0, help=_("The maximum convexity of the blobs."), ).set_prop("display", active=_prop_conv) @computation_function() def blob_opencv(image: ImageObj, p: BlobOpenCVParam) -> GeometryResult | None: """Compute blobs using OpenCV with :py:func:`sigima.tools.image.find_blobs_opencv` Args: imageOutput: input image p: parameters Returns: Blobs coordinates (with ROI creation info in attrs if requested) """ geometry = compute_geometry_from_obj( "blob_opencv", KindShape.CIRCLE, image, sigima.tools.image.find_blobs_opencv, p.min_threshold, p.max_threshold, p.min_repeatability, p.min_dist_between_blobs, p.filter_by_color, p.blob_color, p.filter_by_area, p.min_area, p.max_area, p.filter_by_circularity, p.min_circularity, p.max_circularity, p.filter_by_inertia, p.min_inertia_ratio, p.max_inertia_ratio, p.filter_by_convexity, p.min_convexity, p.max_convexity, ) return store_roi_creation_metadata(geometry, p.create_rois, p.roi_geometry) class HoughCircleParam(DetectionROIParam, gds.DataSet): """Circle Hough transform parameters""" min_radius = gds.IntItem( _("Radiusmin"), unit="pixels", min=0, nonzero=True ) max_radius = gds.IntItem( _("Radiusmax"), unit="pixels", min=0, nonzero=True ) min_distance = gds.IntItem(_("Minimal distance"), min=0) @computation_function() def hough_circle_peaks(image: ImageObj, p: HoughCircleParam) -> GeometryResult | None: """Compute Hough circles with :py:func:`sigima.tools.image.get_hough_circle_peaks` Args: image: input image p: parameters Returns: Circle coordinates (with ROI creation info in attrs if requested) """ geometry = compute_geometry_from_obj( "hough_circle_peak", KindShape.CIRCLE, image, sigima.tools.image.get_hough_circle_peaks, p.min_radius, p.max_radius, None, p.min_distance, ) return store_roi_creation_metadata(geometry, p.create_rois, p.roi_geometry) Sigima-1.1.1/sigima/proc/image/edges.py000066400000000000000000000203301514013333200176530ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Edge detection computation module. ---------------------------------- This module implements edge detection computation functions, enabling the identification of boundaries in an image. Edge detection may be used for image segmentation, shape analysis, and feature extraction. Methods rely on detection of significant transitions in pixel intensity. Available filters (in alphabetical order): * canny: Canny edge detector * farid: Farid filter * farid_h: Horizontal Farid filter * farid_v: Vertical Farid filter * laplace: Laplace filter * prewitt: Prewitt filter * prewitt_h: Horizontal Prewitt filter * prewitt_v: Vertical Prewitt filter * roberts: Roberts filter * scharr: Scharr filter * scharr_h: Horizontal Scharr filter * scharr_v: Vertical Scharr filter * sobel: Sobel filter * sobel_h: Horizontal Sobel filter * sobel_v: Vertical Sobel filter """ # pylint: disable=invalid-name # Allows short names like x, y... # Note: # ---- # - All `guidata.dataset.DataSet` parameter classes must also be imported in the # `sigima.params` module. # - All functions decorated with `computation_function` must be imported in the upper # level `sigima.proc.image` module. from __future__ import annotations import guidata.dataset as gds # type: ignore[import] from skimage import feature, filters # type: ignore[import] from skimage.util import img_as_ubyte # type: ignore[import] from sigima.config import _ from sigima.enums import FilterMode from sigima.objects.image import ImageObj from sigima.proc.decorator import computation_function from sigima.proc.image.base import Wrap1to1Func, dst_1_to_1, restore_data_outside_roi # NOTE: Only parameter classes DEFINED in this module should be included in __all__. # Parameter classes imported from other modules (like sigima.proc.base) should NOT # be re-exported to avoid Sphinx cross-reference conflicts. The sigima.params module # serves as the central API point that imports and re-exports all parameter classes. __all__ = [ "CannyParam", "canny", "farid", "farid_h", "farid_v", "laplace", "prewitt", "prewitt_h", "prewitt_v", "roberts", "scharr", "scharr_h", "scharr_v", "sobel", "sobel_h", "sobel_v", ] class CannyParam(gds.DataSet): """Canny filter parameters.""" sigma = gds.FloatItem( "Sigma", default=1.0, unit="pixels", min=0.0, nonzero=True, help=_("Standard deviation of the Gaussian filter."), ) low_threshold = gds.FloatItem( _("Low threshold"), default=0.1, min=0.0, help=_("Lower bound for hysteresis thresholding (linking edges)."), ) high_threshold = gds.FloatItem( _("High threshold"), default=0.9, min=0.0, help=_("Upper bound for hysteresis thresholding (linking edges)."), ) use_quantiles = gds.BoolItem( _("Use quantiles"), default=True, help=_( "If True then treat low_threshold and high_threshold as quantiles " "of the edge magnitude image, rather than absolute edge magnitude " "values. If True then the thresholds must be in the range [0, 1]." ), ) mode = gds.ChoiceItem(_("Mode"), FilterMode, default=FilterMode.CONSTANT) cval = gds.FloatItem( "cval", default=0.0, help=_("Value to fill past edges of input if mode is constant."), ) @computation_function() def canny(src: ImageObj, p: CannyParam) -> ImageObj: """Compute Canny filter with :py:func:`skimage.feature.canny`. Args: src: Input image object. p: Parameters. Returns: Output image object. """ dst = dst_1_to_1( src, "canny", f"sigma={p.sigma}, low_threshold={p.low_threshold}, " f"high_threshold={p.high_threshold}, use_quantiles={p.use_quantiles}, " f"mode={p.mode}, cval={p.cval}", ) dst.data = img_as_ubyte( feature.canny( src.data, sigma=p.sigma, low_threshold=p.low_threshold, high_threshold=p.high_threshold, use_quantiles=p.use_quantiles, mode=p.mode, cval=p.cval, ) ) restore_data_outside_roi(dst, src) return dst @computation_function() def farid(src: ImageObj) -> ImageObj: """Compute Farid filter with :py:func:`skimage.filters.farid`. Args: src: Input image object. Returns: Output image object. """ return Wrap1to1Func(filters.farid)(src) @computation_function() def farid_h(src: ImageObj) -> ImageObj: """Compute horizontal Farid filter with :py:func:`skimage.filters.farid_h`. Args: src: Input image object. Returns: Output image object. """ return Wrap1to1Func(filters.farid_h)(src) @computation_function() def farid_v(src: ImageObj) -> ImageObj: """Compute vertical Farid filter with :py:func:`skimage.filters.farid_v`. Args: src: Input image object. Returns: Output image object. """ return Wrap1to1Func(filters.farid_v)(src) @computation_function() def laplace(src: ImageObj) -> ImageObj: """Compute Laplace filter with :py:func:`skimage.filters.laplace`. Args: src: Input image object. Returns: Output image object. """ return Wrap1to1Func(filters.laplace)(src) @computation_function() def prewitt(src: ImageObj) -> ImageObj: """Compute Prewitt filter with :py:func:`skimage.filters.prewitt`. Args: src: Input image object. Returns: Output image object. """ return Wrap1to1Func(filters.prewitt)(src) @computation_function() def prewitt_h(src: ImageObj) -> ImageObj: """Compute horizontal Prewitt filter with :py:func:`skimage.filters.prewitt_h`. Args: src: Input image object. Returns: Output image object. """ return Wrap1to1Func(filters.prewitt_h)(src) @computation_function() def prewitt_v(src: ImageObj) -> ImageObj: """Compute vertical Prewitt filter with :py:func:`skimage.filters.prewitt_v`. Args: src: Input image object. Returns: Output image object. """ return Wrap1to1Func(filters.prewitt_v)(src) @computation_function() def roberts(src: ImageObj) -> ImageObj: """Compute Roberts filter with :py:func:`skimage.filters.roberts`. Args: src: Input image object. Returns: Output image object. """ return Wrap1to1Func(filters.roberts)(src) @computation_function() def scharr(src: ImageObj) -> ImageObj: """Compute Scharr filter with :py:func:`skimage.filters.scharr`. Args: src: Input image object. Returns: Output image object. """ return Wrap1to1Func(filters.scharr)(src) @computation_function() def scharr_h(src: ImageObj) -> ImageObj: """Compute horizontal Scharr filter with :py:func:`skimage.filters.scharr_h`. Args: src: Input image object. Returns: Output image object. """ return Wrap1to1Func(filters.scharr_h)(src) @computation_function() def sobel(src: ImageObj) -> ImageObj: """Compute Sobel filter with :py:func:`skimage.filters.sobel`. Args: src: Input image object. Returns: Output image object. """ return Wrap1to1Func(filters.sobel)(src) @computation_function() def sobel_h(src: ImageObj) -> ImageObj: """Compute horizontal Sobel filter with :py:func:`skimage.filters.sobel_h`. Args: src: Input image object. Returns: Output image object. """ return Wrap1to1Func(filters.sobel_h)(src) @computation_function() def sobel_v(src: ImageObj) -> ImageObj: """Compute vertical Sobel filter with :py:func:`skimage.filters.sobel_v`. Args: src: Input image object. Returns: Output image object. """ return Wrap1to1Func(filters.sobel_v)(src) @computation_function() def scharr_v(src: ImageObj) -> ImageObj: """Compute vertical Scharr filter with :py:func:`skimage.filters.scharr_v`. Args: src: Input image object. Returns: Output image object. """ return Wrap1to1Func(filters.scharr_v)(src) Sigima-1.1.1/sigima/proc/image/exposure.py000066400000000000000000000254021514013333200204430ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Exposure computation module --------------------------- This module provides tools for adjusting and analyzing image exposure and contrast. Main features include: - Histogram computation and equalization - Contrast adjustment and normalization - Logarithmic and gamma correction Exposure processing improves the visual quality and interpretability of images, especially under variable lighting conditions. """ # pylint: disable=invalid-name # Allows short reference names like x, y, ... # Note: # ---- # - All `guidata.dataset.DataSet` parameter classes must also be imported # in the `sigima.params` module. # - All functions decorated by `computation_function` must be imported in the upper # level `sigima.proc.image` module. from __future__ import annotations import guidata.dataset as gds import numpy as np from skimage import exposure import sigima.enums import sigima.tools.image from sigima.config import _ from sigima.objects.image import ImageObj, ROI2DParam from sigima.objects.signal import SignalObj from sigima.proc.base import ( ClipParam, HistogramParam, NormalizeParam, new_signal_result, ) from sigima.proc.decorator import computation_function from sigima.proc.image.base import ( Wrap1to1Func, dst_1_to_1, dst_2_to_1, restore_data_outside_roi, ) # NOTE: Only parameter classes DEFINED in this module should be included in __all__. # Parameter classes imported from other modules (like sigima.proc.base) should NOT # be re-exported to avoid Sphinx cross-reference conflicts. The sigima.params module # serves as the central API point that imports and re-exports all parameter classes. __all__ = [ "AdjustGammaParam", "AdjustLogParam", "AdjustSigmoidParam", "EqualizeAdaptHistParam", "EqualizeHistParam", "FlatFieldParam", "RescaleIntensityParam", "adjust_gamma", "adjust_log", "adjust_sigmoid", "clip", "equalize_adapthist", "equalize_hist", "flatfield", "histogram", "normalize", "offset_correction", "rescale_intensity", ] class AdjustGammaParam(gds.DataSet): """Gamma adjustment parameters""" gamma = gds.FloatItem( _("Gamma"), default=1.0, min=0.0, help=_("Gamma correction factor (higher values give more contrast)."), ) gain = gds.FloatItem( _("Gain"), default=1.0, min=0.0, help=_("Gain factor (higher values give more contrast)."), ) @computation_function() def adjust_gamma(src: ImageObj, p: AdjustGammaParam) -> ImageObj: """Gamma correction with :py:func:`skimage.exposure.adjust_gamma` Args: src: input image object p: parameters Returns: Output image object """ dst = dst_1_to_1(src, "adjust_gamma", f"gamma={p.gamma}, gain={p.gain}") dst.data = exposure.adjust_gamma(src.data, gamma=p.gamma, gain=p.gain) restore_data_outside_roi(dst, src) return dst class AdjustLogParam(gds.DataSet): """Logarithmic adjustment parameters""" gain = gds.FloatItem( _("Gain"), default=1.0, min=0.0, help=_("Gain factor (higher values give more contrast)."), ) inv = gds.BoolItem( _("Inverse"), default=False, help=_("If True, apply inverse logarithmic transformation."), ) @computation_function() def adjust_log(src: ImageObj, p: AdjustLogParam) -> ImageObj: """Compute log correction with :py:func:`skimage.exposure.adjust_log` Args: src: input image object p: parameters Returns: Output image object """ dst = dst_1_to_1(src, "adjust_log", f"gain={p.gain}, inv={p.inv}") dst.data = exposure.adjust_log(src.data, gain=p.gain, inv=p.inv) restore_data_outside_roi(dst, src) return dst class AdjustSigmoidParam(gds.DataSet): """Sigmoid adjustment parameters""" cutoff = gds.FloatItem( _("Cutoff"), default=0.5, min=0.0, max=1.0, help=_("Cutoff value (higher values give more contrast)."), ) gain = gds.FloatItem( _("Gain"), default=10.0, min=0.0, help=_("Gain factor (higher values give more contrast)."), ) inv = gds.BoolItem( _("Inverse"), default=False, help=_("If True, apply inverse sigmoid transformation."), ) @computation_function() def adjust_sigmoid(src: ImageObj, p: AdjustSigmoidParam) -> ImageObj: """Compute sigmoid correction with :py:func:`skimage.exposure.adjust_sigmoid` Args: src: input image object p: parameters Returns: Output image object """ dst = dst_1_to_1( src, "adjust_sigmoid", f"cutoff={p.cutoff}, gain={p.gain}, inv={p.inv}" ) dst.data = exposure.adjust_sigmoid( src.data, cutoff=p.cutoff, gain=p.gain, inv=p.inv ) restore_data_outside_roi(dst, src) return dst class RescaleIntensityParam(gds.DataSet): """Intensity rescaling parameters""" _dtype_list = ["image", "dtype"] + ImageObj.get_valid_dtypenames() in_range = gds.ChoiceItem( _("Input range"), list(zip(_dtype_list, _dtype_list)), default="image", help=_( "Min and max intensity values of input image ('image' refers to input " "image min/max levels, 'dtype' refers to input image data type range)." ), ) out_range = gds.ChoiceItem( _("Output range"), list(zip(_dtype_list, _dtype_list)), default="dtype", help=_( "Min and max intensity values of output image ('image' refers to input " "image min/max levels, 'dtype' refers to input image data type range).." ), ) @computation_function() def rescale_intensity(src: ImageObj, p: RescaleIntensityParam) -> ImageObj: """Rescale image intensity levels with :py:func:`skimage.exposure.rescale_intensity` Args: src: input image object p: parameters Returns: Output image object """ dst = dst_1_to_1( src, "rescale_intensity", f"in_range={p.in_range}, out_range={p.out_range}", ) dst.data = exposure.rescale_intensity( src.data, in_range=p.in_range, out_range=p.out_range ) restore_data_outside_roi(dst, src) return dst class EqualizeHistParam(gds.DataSet): """Histogram equalization parameters""" nbins = gds.IntItem( _("Number of bins"), min=1, default=256, help=_("Number of bins for image histogram."), ) @computation_function() def equalize_hist(src: ImageObj, p: EqualizeHistParam) -> ImageObj: """Histogram equalization with :py:func:`skimage.exposure.equalize_hist` Args: src: input image object p: parameters Returns: Output image object """ dst = dst_1_to_1(src, "equalize_hist", f"nbins={p.nbins}") dst.data = exposure.equalize_hist(src.data, nbins=p.nbins) restore_data_outside_roi(dst, src) return dst class EqualizeAdaptHistParam(EqualizeHistParam): """Adaptive histogram equalization parameters""" clip_limit = gds.FloatItem( _("Clipping limit"), default=0.01, min=0.0, max=1.0, help=_("Clipping limit (higher values give more contrast)."), ) @computation_function() def equalize_adapthist(src: ImageObj, p: EqualizeAdaptHistParam) -> ImageObj: """Adaptive histogram equalization with :py:func:`skimage.exposure.equalize_adapthist` Args: src: input image object p: parameters Returns: Output image object """ dst = dst_1_to_1( src, "equalize_adapthist", f"nbins={p.nbins}, clip_limit={p.clip_limit}" ) dst.data = exposure.equalize_adapthist( src.data, clip_limit=p.clip_limit, nbins=p.nbins ) restore_data_outside_roi(dst, src) return dst class FlatFieldParam(gds.DataSet): """Flat-field parameters""" threshold = gds.FloatItem(_("Threshold"), default=0.0) @computation_function() def flatfield(src1: ImageObj, src2: ImageObj, p: FlatFieldParam) -> ImageObj: """Compute flat field correction with :py:func:`sigima.tools.image.flatfield` Args: src1: raw data image object src2: flat field image object p: flat field parameters Returns: Output image object """ dst = dst_2_to_1(src1, src2, "flatfield", f"threshold={p.threshold}") dst.data = sigima.tools.image.flatfield(src1.data, src2.data, p.threshold) restore_data_outside_roi(dst, src1) return dst # MARK: compute_1_to_1 functions ------------------------------------------------------- # Functions with 1 input image and 1 output image # -------------------------------------------------------------------------------------- @computation_function() def normalize(src: ImageObj, p: NormalizeParam) -> ImageObj: """ Normalize image data depending on its maximum, with :py:func:`sigima.tools.image.normalize` Args: src: input image object Returns: Output image object """ method: sigima.enums.NormalizationMethod = p.method dst = dst_1_to_1(src, "normalize", suffix=f"ref={method.value}") dst.data = sigima.tools.image.normalize(src.data, method) restore_data_outside_roi(dst, src) return dst @computation_function() def histogram(src: ImageObj, p: HistogramParam) -> SignalObj: """Compute histogram of the image data, with :py:func:`numpy.histogram` Args: src: input image object p: parameters Returns: Signal object with the histogram """ data = src.get_masked_view().compressed() suffix = p.get_suffix(data) # Also updates p.lower and p.upper y, bin_edges = np.histogram(data, bins=p.bins, range=(p.lower, p.upper)) x = (bin_edges[:-1] + bin_edges[1:]) / 2 dst = new_signal_result( src, "histogram", suffix=suffix, units=(src.zunit, ""), labels=(src.zlabel, _("Counts")), ) dst.set_xydata(x, y) dst.set_metadata_option("shade", 0.5) dst.set_metadata_option("curvestyle", "Steps") return dst @computation_function() def clip(src: ImageObj, p: ClipParam) -> ImageObj: """Apply clipping with :py:func:`numpy.clip` Args: src: input image object p: parameters Returns: Output image object """ return Wrap1to1Func(np.clip, a_min=p.lower, a_max=p.upper)(src) @computation_function() def offset_correction(src: ImageObj, p: ROI2DParam) -> ImageObj: """Apply offset correction Args: src: input image object p: parameters Returns: Output image object """ dst = dst_1_to_1(src, "offset_correction", p.get_suffix()) dst.data = src.data - np.nanmean(p.get_data(src)) restore_data_outside_roi(dst, src) return dst Sigima-1.1.1/sigima/proc/image/extraction.py000066400000000000000000000373001514013333200207510ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Extraction computation module ----------------------------- This module provides functions to extract sub-regions and intensity profiles from images. Main features include: - Extraction of regions of interest (ROIs) - Extraction of line, segment, average, and radial intensity profiles These functions are useful for isolating specific image zones and for analyzing signal intensity along defined paths. """ # pylint: disable=invalid-name # Allows short reference names like x, y, ... # Note: # ---- # - All `guidata.dataset.DataSet` parameter classes must also be imported # in the `sigima.params` module. # - All functions decorated by `computation_function` must be imported in the upper # level `sigima.proc.image` module. from __future__ import annotations from typing import Callable import guidata.dataset as gds import numpy as np from numpy import ma import sigima.tools.image from sigima.config import _ from sigima.objects.image import ImageObj, ImageROI, RectangularROI, ROI2DParam from sigima.objects.signal import SignalObj from sigima.proc.decorator import computation_function from sigima.proc.image.base import dst_1_to_1, dst_1_to_1_signal # NOTE: Only parameter classes DEFINED in this module should be included in __all__. # Parameter classes imported from other modules (like sigima.proc.base) should NOT # be re-exported to avoid Sphinx cross-reference conflicts. The sigima.params module # serves as the central API point that imports and re-exports all parameter classes. __all__ = [ "AverageProfileParam", "LineProfileParam", "ROIGridParam", "RadialProfileParam", "SegmentProfileParam", "average_profile", "extract_roi", "extract_rois", "generate_image_grid_roi", "line_profile", "radial_profile", "segment_profile", ] @computation_function() def extract_rois(src: ImageObj, params: list[ROI2DParam]) -> ImageObj: """Extract multiple regions of interest from data Args: src: input image object params: list of ROI parameters Returns: Output image object """ # Initialize ix0, iy0 with maximum values: iy0, ix0 = iymax, ixmax = src.data.shape # Initialize ix1, iy1 with minimum values: iy1, ix1 = iymin, ixmin = 0, 0 for p in params: x0i, y0i, x1i, y1i = p.get_bounding_box_indices(src) ix0, iy0, ix1, iy1 = min(ix0, x0i), min(iy0, y0i), max(ix1, x1i), max(iy1, y1i) ix0, iy0 = max(ix0, ixmin), max(iy0, iymin) ix1, iy1 = min(ix1, ixmax), min(iy1, iymax) suffix = None if len(params) == 1: p = params[0] suffix = p.get_suffix() dst = dst_1_to_1(src, "extract_rois", suffix) if src.is_uniform_coords: dst.set_uniform_coords( dst.dx, dst.dy, dst.x0 + ix0 * src.dx, dst.y0 + iy0 * src.dy ) else: dst.set_coords(src.xcoords[iy0:iy1], src.ycoords[ix0:ix1]) dst.roi = None src2 = src.copy() src2.roi = ImageROI.from_params(src2, params) src2.data[src2.maskdata] = 0 dst.data = src2.data[iy0:iy1, ix0:ix1] return dst @computation_function() def extract_roi(src: ImageObj, p: ROI2DParam) -> ImageObj: """Extract single ROI Args: src: input image object p: ROI parameters Returns: Output image object """ dst = dst_1_to_1(src, "extract_roi", p.get_suffix()) dst.data = p.get_data(src).copy() dst.roi = p.get_extracted_roi(src) x0, y0, _x1, _y1 = p.get_bounding_box_physical() if src.is_uniform_coords: dst.set_uniform_coords(dst.dx, dst.dy, dst.x0 + x0, dst.y0 + y0) else: dst.set_coords(src.xcoords + x0, src.ycoords + y0) return dst class Direction(gds.LabeledEnum): """Direction choice""" INCREASING = "increasing", _("increasing") DECREASING = "decreasing", _("decreasing") class ROIGridParam(gds.DataSet): """ROI Grid parameters""" # optional Python-level hook, no Qt on_geometry_changed: Callable | None = None # pylint: disable=unused-argument def geometry_changed(self, item, value) -> None: """Notify host (if any) that geometry changed.""" if callable(self.on_geometry_changed): self.on_geometry_changed() # pylint: disable=not-callable _b_group0 = gds.BeginGroup(_("Geometry")) ny = gds.IntItem(f"Ny ({_('rows')})", default=3, nonzero=True).set_prop( "display", callback=geometry_changed ) nx = ( gds.IntItem(f"Nx ({_('columns')})", default=3, nonzero=True) .set_prop("display", callback=geometry_changed) .set_pos(col=1) ) xtranslation = gds.IntItem( _("X translation"), default=50, min=0, max=100, unit="%", slider=True, ).set_prop("display", callback=geometry_changed) ytranslation = gds.IntItem( _("Y translation"), default=50, min=0, max=100, unit="%", slider=True, ).set_prop("display", callback=geometry_changed) xsize = gds.IntItem( f"X size ({_('column size')})", default=50, min=0, max=100, unit="%", slider=True, ).set_prop("display", callback=geometry_changed) ysize = gds.IntItem( f"Y size ({_('row size')})", default=50, min=0, max=100, unit="%", slider=True, ).set_prop("display", callback=geometry_changed) xstep = gds.IntItem( f"X step ({_('column spacing')})", default=100, min=1, max=200, unit="%", slider=True, help=_( "Horizontal spacing between ROI centers, as a percentage of the " "automatically computed cell width (100% = evenly distributed grid)" ), ).set_prop("display", callback=geometry_changed) ystep = gds.IntItem( f"Y step ({_('row spacing')})", default=100, min=1, max=200, unit="%", slider=True, help=_( "Vertical spacing between ROI centers, as a percentage of the " "automatically computed cell height (100% = evenly distributed grid)" ), ).set_prop("display", callback=geometry_changed) _e_group0 = gds.EndGroup(_("Geometry")) _b_group1 = gds.BeginGroup(_("ROI titles")) base_name = gds.StringItem(_("Base name"), default="ROI").set_prop( "display", callback=geometry_changed ) name_pattern = gds.StringItem( _("Name pattern"), default="{base}({r},{c})" ).set_prop("display", callback=geometry_changed) xdirection = gds.ChoiceItem(_("X direction"), Direction).set_prop( "display", callback=geometry_changed ) ydirection = ( gds.ChoiceItem(_("Y direction"), Direction) .set_prop("display", callback=geometry_changed) .set_pos(col=1) ) _e_group1 = gds.EndGroup(_("ROI titles")) def generate_image_grid_roi(src: ImageObj, p: ROIGridParam) -> ImageROI: """Create a grid of rectangular ROIs from an image object. Args: obj: The image object to create the ROI for. p: ROIGridParam object containing the grid parameters. Returns: The created ROI object. """ dx_cell = src.width / p.nx dy_cell = src.height / p.ny dx = dx_cell * p.xsize / 100.0 dy = dy_cell * p.ysize / 100.0 # Apply step multipliers to cell spacing dx_step = dx_cell * p.xstep / 100.0 dy_step = dy_cell * p.ystep / 100.0 xtrans = src.width * (p.xtranslation - 50.0) / 100.0 ytrans = src.height * (p.ytranslation - 50.0) / 100.0 lbl_rows = range(p.ny) if p.ydirection == Direction.DECREASING: lbl_rows = range(p.ny - 1, -1, -1) lbl_cols = range(p.nx) if p.xdirection == Direction.DECREASING: lbl_cols = range(p.nx - 1, -1, -1) ptn: str = p.name_pattern roi = ImageROI() for ir in range(p.ny): for ic in range(p.nx): x0 = src.x0 + (ic + 0.5) * dx_step + xtrans - 0.5 * dx y0 = src.y0 + (ir + 0.5) * dy_step + ytrans - 0.5 * dy nir, nic = lbl_rows[ir], lbl_cols[ic] try: title = ptn.format(base=p.base_name, r=nir + 1, c=nic + 1) except Exception: # pylint: disable=broad-except title = f"ROI({nir + 1},{nic + 1})" roi.add_roi(RectangularROI([x0, y0, dx, dy], indices=False, title=title)) return roi class LineProfileParam(gds.DataSet): """Horizontal or vertical profile parameters""" _prop = gds.GetAttrProp("direction") _directions = (("horizontal", _("horizontal")), ("vertical", _("vertical"))) direction = gds.ChoiceItem(_("Direction"), _directions, radio=True).set_prop( "display", store=_prop ) row = gds.IntItem(_("Row"), default=0, min=0).set_prop( "display", active=gds.FuncProp(_prop, lambda x: x == "horizontal") ) col = gds.IntItem(_("Column"), default=0, min=0).set_prop( "display", active=gds.FuncProp(_prop, lambda x: x == "vertical") ) @computation_function() def line_profile(src: ImageObj, p: LineProfileParam) -> SignalObj: """Compute horizontal or vertical profile Args: src: input image object p: parameters Returns: Signal object with the profile """ data = src.get_masked_view() p.row = min(p.row, data.shape[0] - 1) p.col = min(p.col, data.shape[1] - 1) if p.direction == "horizontal": suffix, shape_index, pdata = f"row={p.row}", 1, data[p.row, :] else: suffix, shape_index, pdata = f"col={p.col}", 0, data[:, p.col] pdata: ma.MaskedArray x = np.arange(data.shape[shape_index])[~pdata.mask] y = np.array(pdata, dtype=float)[~pdata.mask] dst = dst_1_to_1_signal(src, "profile", suffix) dst.set_xydata(x, y) return dst class SegmentProfileParam(gds.DataSet): """Segment profile parameters""" row1 = gds.IntItem(_("Start row"), default=0, min=0) col1 = gds.IntItem(_("Start column"), default=0, min=0) row2 = gds.IntItem(_("End row"), default=0, min=0) col2 = gds.IntItem(_("End column"), default=0, min=0) def csline(data: np.ndarray, row0, col0, row1, col1) -> tuple[np.ndarray, np.ndarray]: """Return intensity profile of data along a line Args: data: 2D array row0, col0: start point row1, col1: end point """ # Keep coordinates inside the image row0 = max(0, min(row0, data.shape[0] - 1)) col0 = max(0, min(col0, data.shape[1] - 1)) row1 = max(0, min(row1, data.shape[0] - 1)) col1 = max(0, min(col1, data.shape[1] - 1)) # Keep coordinates in the right order row0, row1 = min(row0, row1), max(row0, row1) col0, col1 = min(col0, col1), max(col0, col1) # Extract the line line = np.zeros((2, max(abs(row1 - row0), abs(col1 - col0)) + 1), dtype=int) line[0, :] = np.linspace(row0, row1, line.shape[1]).astype(int) line[1, :] = np.linspace(col0, col1, line.shape[1]).astype(int) # Interpolate the line y = np.ma.array(data[line[0], line[1]], float).filled(np.nan) x = np.arange(y.size) return x, y @computation_function() def segment_profile(src: ImageObj, p: SegmentProfileParam) -> SignalObj: """Compute segment profile Args: src: input image object p: parameters Returns: Signal object with the segment profile """ data = src.get_masked_view() p.row1 = min(p.row1, data.shape[0] - 1) p.col1 = min(p.col1, data.shape[1] - 1) p.row2 = min(p.row2, data.shape[0] - 1) p.col2 = min(p.col2, data.shape[1] - 1) suffix = f"({p.row1}, {p.col1})-({p.row2}, {p.col2})" x, y = csline(data, p.row1, p.col1, p.row2, p.col2) x, y = x[~np.isnan(y)], y[~np.isnan(y)] # Remove NaN values dst = dst_1_to_1_signal(src, "segment_profile", suffix) dst.set_xydata(np.array(x, dtype=float), np.array(y, dtype=float)) return dst class AverageProfileParam(gds.DataSet): """Average horizontal or vertical profile parameters""" _directions = (("horizontal", _("horizontal")), ("vertical", _("vertical"))) direction = gds.ChoiceItem(_("Direction"), _directions, radio=True) _hgroup_begin = gds.BeginGroup(_("Profile rectangular area")) row1 = gds.IntItem(_("Row 1"), default=0, min=0) row2 = gds.IntItem(_("Row 2"), default=-1, min=-1) col1 = gds.IntItem(_("Column 1"), default=0, min=0) col2 = gds.IntItem(_("Column 2"), default=-1, min=-1) _hgroup_end = gds.EndGroup(_("Profile rectangular area")) @computation_function() def average_profile(src: ImageObj, p: AverageProfileParam) -> SignalObj: """Compute horizontal or vertical average profile Args: src: input image object p: parameters Returns: Signal object with the average profile """ data = src.get_masked_view() if p.row2 == -1: p.row2 = data.shape[0] - 1 if p.col2 == -1: p.col2 = data.shape[1] - 1 if p.row1 > p.row2: p.row1, p.row2 = p.row2, p.row1 if p.col1 > p.col2: p.col1, p.col2 = p.col2, p.col1 p.row1 = min(p.row1, data.shape[0] - 1) p.row2 = min(p.row2, data.shape[0] - 1) p.col1 = min(p.col1, data.shape[1] - 1) p.col2 = min(p.col2, data.shape[1] - 1) suffix = f"{p.direction}, rows=[{p.row1}, {p.row2}], cols=[{p.col1}, {p.col2}]" if p.direction == "horizontal": x, axis = np.arange(p.col1, p.col2 + 1), 0 else: x, axis = np.arange(p.row1, p.row2 + 1), 1 y = ma.mean(data[p.row1 : p.row2 + 1, p.col1 : p.col2 + 1], axis=axis) dst = dst_1_to_1_signal(src, "average_profile", suffix) dst.set_xydata(x, y) return dst class RadialProfileParam(gds.DataSet): """Radial profile parameters""" def __init__(self, *args, **kwargs) -> None: super().__init__(*args, **kwargs) self.__obj: ImageObj | None = None def update_from_obj(self, obj: ImageObj) -> None: """Update parameters from image""" self.__obj = obj self.x0 = obj.xc self.y0 = obj.yc def choice_callback(self, item, value): # pylint: disable=unused-argument """Callback for choice item""" if self.__obj is None: return if value == "centroid": self.y0, self.x0 = sigima.tools.image.get_centroid_fourier( self.__obj.get_masked_view() ) elif value == "center": self.x0, self.y0 = self.__obj.xc, self.__obj.yc _prop = gds.GetAttrProp("center") center = gds.ChoiceItem( _("Center position"), ( ("centroid", _("Image centroid")), ("center", _("Image center")), ("user", _("User-defined")), ), default="centroid", ).set_prop("display", store=_prop, callback=choice_callback) _func_prop = gds.FuncProp(_prop, lambda x: x == "user") _xyl = "" + _("Center") + "" x0 = gds.FloatItem(f"X{_xyl}", default=0.0, unit="pixel").set_prop( "display", active=_func_prop ) y0 = gds.FloatItem(f"Y{_xyl}", default=0.0, unit="pixel").set_prop( "display", active=_func_prop ) @computation_function() def radial_profile(src: ImageObj, p: RadialProfileParam) -> SignalObj: """Compute radial profile around the centroid with :py:func:`sigima.tools.image.get_radial_profile` Args: src: input image object p: parameters Returns: Signal object with the radial profile """ data = src.get_masked_view() if p.center == "centroid": y0, x0 = sigima.tools.image.get_centroid_fourier(data) elif p.center == "center": x0, y0 = src.xc, src.yc else: x0, y0 = p.x0, p.y0 suffix = f"center=({x0:.3f}, {y0:.3f})" dst = dst_1_to_1_signal(src, "radial_profile", suffix) x, y = sigima.tools.image.get_radial_profile(data, (x0, y0)) dst.set_xydata(x, y) return dst Sigima-1.1.1/sigima/proc/image/filtering.py000066400000000000000000000136111514013333200205530ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """Filtering computation module. -------------------------------- This module provides spatial and frequency-based filtering operations for images. Filtering functions are essential for enhancing image quality and removing noise. Main features include: * Gaussian, median, moving average and Wiener filters * Butterworth and frequency domain Gaussian filters. Filtering functions are essential for enhancing image quality and removing noise prior to further analysis. """ # pylint: disable=invalid-name # Allows short names like x, y... # Note: # ---- # - All `guidata.dataset.DataSet` parameter classes must also be imported in the # `sigima.params` module. # - All functions decorated with `computation_function` must be imported in the upper # level `sigima.proc.image` module. from __future__ import annotations import guidata.dataset as gds # type: ignore[import] import scipy.ndimage as spi # type: ignore[import] import scipy.signal as sps # type: ignore[import] from skimage import filters # type: ignore[import] import sigima.tools.image from sigima.config import _ from sigima.objects.image import ImageObj from sigima.proc.base import ( GaussianParam, MovingAverageParam, MovingMedianParam, ) from sigima.proc.decorator import computation_function from sigima.proc.image.base import Wrap1to1Func, dst_1_to_1, restore_data_outside_roi # NOTE: Only parameter classes DEFINED in this module should be included in __all__. # Parameter classes imported from other modules (like sigima.proc.base) should NOT # be re-exported to avoid Sphinx cross-reference conflicts. The sigima.params module # serves as the central API point that imports and re-exports all parameter classes. __all__ = [ "ButterworthParam", "GaussianFreqFilterParam", "butterworth", "gaussian_filter", "gaussian_freq_filter", "moving_average", "moving_median", "wiener", ] # MARK: Noise reduction filters @computation_function() def gaussian_filter(src: ImageObj, p: GaussianParam) -> ImageObj: """Compute gaussian filter with :py:func:`scipy.ndimage.gaussian_filter`. Args: src: Input image object. p: Parameters. Returns: Output image object. """ return Wrap1to1Func(spi.gaussian_filter, sigma=p.sigma)(src) @computation_function() def moving_average(src: ImageObj, p: MovingAverageParam) -> ImageObj: """Compute moving average with :py:func:`scipy.ndimage.uniform_filter`. Args: src: Input image object. p: Parameters. Returns: Output image object. """ return Wrap1to1Func( spi.uniform_filter, size=p.n, mode=p.mode, func_name="moving_average" )(src) @computation_function() def moving_median(src: ImageObj, p: MovingMedianParam) -> ImageObj: """Compute moving median with :py:func:`scipy.ndimage.median_filter`. Args: src: Input image object. p: Parameters. Returns: Output image object. """ return Wrap1to1Func( spi.median_filter, size=p.n, mode=p.mode, func_name="moving_median" )(src) @computation_function() def wiener(src: ImageObj) -> ImageObj: """Compute Wiener filter with :py:func:`scipy.signal.wiener` Args: src: Input image object. Returns: Output image object. """ return Wrap1to1Func(sps.wiener)(src) class ButterworthParam(gds.DataSet): """Butterworth filter parameters.""" cut_off = gds.FloatItem( _("Cut-off frequency ratio"), default=0.005, min=0.0, max=0.5, help=_("Cut-off frequency ratio"), ) high_pass = gds.BoolItem( _("High-pass filter"), default=False, help=_("If True, apply high-pass filter instead of low-pass"), ) order = gds.IntItem( _("Order"), default=2, min=1, help=_("Order of the Butterworth filter"), ) # MARK: Frequency filters @computation_function() def butterworth(src: ImageObj, p: ButterworthParam) -> ImageObj: """Compute Butterworth filter with :py:func:`skimage.filters.butterworth`. Args: src: Input image object. p: Parameters. Returns: Output image object. """ dst = dst_1_to_1( src, "butterworth", f"cut_off={p.cut_off:.3f}, order={p.order}, high_pass={p.high_pass}", ) dst.data = filters.butterworth(src.data, p.cut_off, p.high_pass, p.order) restore_data_outside_roi(dst, src) return dst class GaussianFreqFilterParam(GaussianParam): """Parameters for Gaussian filter applied in the frequency domain.""" sigma = gds.FloatItem( "σ", default=1.0, unit="pixel⁻¹", min=0.0, help=_("Standard deviation of the Gaussian filter"), ) f0 = gds.FloatItem( _("Center frequency"), default=1.0, unit="pixel⁻¹", min=0.0, help=_("Center frequency of the Gaussian filter"), ) sigma = gds.FloatItem( "σ", default=0.5, unit="pixels⁻¹", min=0.0, help=_("Standard deviation of the Gaussian filter"), ) ifft_result_type = gds.ChoiceItem( _("Inverse FFT result"), (("real", _("Real part")), ("abs", _("Absolute value"))), default="real", help=_("How to return the inverse FFT result"), ) @computation_function() def gaussian_freq_filter(src: ImageObj, p: GaussianFreqFilterParam) -> ImageObj: """Apply a Gaussian filter in the frequency domain. Args: src: Source image object. p: Parameters. Returns: Output image object. """ dst = dst_1_to_1( src, "frequency_domain_gaussian_filter", f"sigma={p.sigma:.3f}, f0={p.f0:.3f}", ) dst.data = sigima.tools.image.gaussian_freq_filter(src.data, p.f0, p.sigma) restore_data_outside_roi(dst, src) return dst Sigima-1.1.1/sigima/proc/image/fourier.py000066400000000000000000000106021514013333200202400ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Fourier computation module -------------------------- This module implements Fourier transform operations and related spectral analysis tools for images. Main features include: - Forward and inverse Fast Fourier Transform (FFT) - Magnitude and phase spectrum calculation - Power spectral density (PSD) computation Fourier analysis is commonly used for frequency-domain filtering and periodicity analysis in images. """ # pylint: disable=invalid-name # Allows short reference names like x, y, ... # Note: # ---- # - All `guidata.dataset.DataSet` parameter classes must also be imported # in the `sigima.params` module. # - All functions decorated by `computation_function` must be imported in the upper # level `sigima.proc.image` module. from __future__ import annotations import sigima.tools.image from sigima.config import _ from sigima.objects.image import ImageObj from sigima.proc.base import FFTParam, SpectrumParam from sigima.proc.decorator import computation_function from sigima.proc.image.base import Wrap1to1Func, dst_1_to_1 # NOTE: Only parameter classes DEFINED in this module should be included in __all__. # Parameter classes imported from other modules (like sigima.proc.base) should NOT # be re-exported to avoid Sphinx cross-reference conflicts. The sigima.params module # serves as the central API point that imports and re-exports all parameter classes. __all__ = [ "fft", "ifft", "magnitude_spectrum", "phase_spectrum", "psd", ] @computation_function() def fft(src: ImageObj, p: FFTParam | None = None) -> ImageObj: """Compute FFT with :py:func:`sigima.tools.image.fft2d` Args: src: input image object p: parameters Returns: Output image object """ if p is None: p = FFTParam() dst = dst_1_to_1(src, "fft") dst.data = sigima.tools.image.fft2d(src.data, shift=p.shift) dst.save_attr_to_metadata("xunit", "") dst.save_attr_to_metadata("yunit", "") dst.save_attr_to_metadata("zunit", "") dst.save_attr_to_metadata("xlabel", _("Frequency")) dst.save_attr_to_metadata("ylabel", _("Frequency")) return dst @computation_function() def ifft(src: ImageObj, p: FFTParam | None = None) -> ImageObj: """Compute inverse FFT with :py:func:`sigima.tools.image.ifft2d` Args: src: input image object p: parameters Returns: Output image object """ if p is None: p = FFTParam() dst = dst_1_to_1(src, "ifft") dst.data = sigima.tools.image.ifft2d(src.data, shift=p.shift) dst.restore_attr_from_metadata("xunit", "") dst.restore_attr_from_metadata("yunit", "") dst.restore_attr_from_metadata("zunit", "") dst.restore_attr_from_metadata("xlabel", "") dst.restore_attr_from_metadata("ylabel", "") return dst @computation_function() def magnitude_spectrum(src: ImageObj, p: SpectrumParam | None = None) -> ImageObj: """Compute magnitude spectrum with :py:func:`sigima.tools.image.magnitude_spectrum` Args: src: input image object p: parameters Returns: Output image object """ decibel = p is not None and p.decibel dst = dst_1_to_1(src, "magnitude_spectrum", f"dB={decibel}") dst.data = sigima.tools.image.magnitude_spectrum(src.data, log_scale=decibel) dst.xunit = dst.yunit = dst.zunit = "" dst.xlabel = dst.ylabel = _("Frequency") return dst @computation_function() def phase_spectrum(src: ImageObj) -> ImageObj: """Compute phase spectrum with :py:func:`sigima.tools.image.phase_spectrum` Args: src: input image object Returns: Output image object """ dst = Wrap1to1Func(sigima.tools.image.phase_spectrum)(src) dst.xunit = dst.yunit = dst.zunit = "" dst.xlabel = dst.ylabel = _("Frequency") return dst @computation_function() def psd(src: ImageObj, p: SpectrumParam | None = None) -> ImageObj: """Compute power spectral density with :py:func:`sigima.tools.image.psd` Args: src: input image object p: parameters Returns: Output image object """ decibel = p is not None and p.decibel dst = dst_1_to_1(src, "psd", f"dB={decibel}") dst.data = sigima.tools.image.psd(src.data, log_scale=decibel) dst.xunit = dst.yunit = dst.zunit = "" dst.xlabel = dst.ylabel = _("Frequency") return dst Sigima-1.1.1/sigima/proc/image/geometry.py000066400000000000000000000515651514013333200204350ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Geometry computation module --------------------------- This module implements geometric transformations and manipulations for images, such as rotations, flips, resizing, axis swapping, binning, and padding. Main features include: - Rotation by arbitrary or fixed angles - Horizontal and vertical flipping - Resizing and binning of images - Axis swapping and zero padding These functions are useful for preparing and augmenting image data. """ # pylint: disable=invalid-name # Allows short reference names like x, y, ... # Note: # ---- # - All `guidata.dataset.DataSet` parameter classes must also be imported # in the `sigima.params` module. # - All functions decorated by `computation_function` must be imported in the upper # level `sigima.proc.image` module. from __future__ import annotations import guidata.dataset as gds import numpy as np import scipy.ndimage as spi from sigima.config import _ from sigima.enums import BorderMode, Interpolation2DMethod from sigima.objects.image import ImageObj from sigima.proc.decorator import computation_function from sigima.proc.image.base import dst_1_to_1, restore_data_outside_roi from sigima.proc.image.transformations import transformer # NOTE: Only parameter classes DEFINED in this module should be included in __all__. # Parameter classes imported from other modules (like sigima.proc.base) should NOT # be re-exported to avoid Sphinx cross-reference conflicts. The sigima.params module # serves as the central API point that imports and re-exports all parameter classes. __all__ = [ "Resampling2DParam", "ResizeParam", "RotateParam", "TranslateParam", "UniformCoordsParam", "XYZCalibrateParam", "calibration", "fliph", "flipv", "resampling", "resize", "rotate", "rotate90", "rotate270", "set_uniform_coords", "translate", "transpose", ] class TranslateParam(gds.DataSet): """Translate parameters""" dx = gds.FloatItem(_("X translation"), default=0.0) dy = gds.FloatItem(_("Y translation"), default=0.0) @computation_function() def translate(src: ImageObj, p: TranslateParam) -> ImageObj: """Translate data with :py:func:`scipy.ndimage.shift` Args: src: input image object p: parameters Returns: Output image object """ dst = dst_1_to_1(src, "translate", f"dx={p.dx}, dy={p.dy}") if src.is_uniform_coords: dst.set_uniform_coords(dst.dx, dst.dy, dst.x0 + p.dx, dst.y0 + p.dy) else: dst.set_coords(src.xcoords + p.dx, src.ycoords + p.dy) transformer.transform_roi(dst, "translate", dx=p.dx, dy=p.dy) return dst class RotateParam(gds.DataSet): """Rotate parameters""" prop = gds.ValueProp(False) angle = gds.FloatItem(f"{_('Angle')} (°)", default=0.0) mode = gds.ChoiceItem(_("Mode"), BorderMode, default=BorderMode.CONSTANT) cval = gds.FloatItem( _("cval"), default=0.0, help=_( "Value used for points outside the " "boundaries of the input if mode is " "'constant'" ), ) reshape = gds.BoolItem( _("Reshape the output array"), default=False, help=_( "Reshape the output array " "so that the input array is " "contained completely in the output" ), ) prefilter = gds.BoolItem(_("Prefilter the input image"), default=True).set_prop( "display", store=prop ) order = gds.IntItem( _("Order"), default=3, min=0, max=5, help=_("Spline interpolation order"), ).set_prop("display", active=prop) @computation_function() def rotate(src: ImageObj, p: RotateParam) -> ImageObj: """Rotate data with :py:func:`scipy.ndimage.rotate` Args: src: input image object p: parameters Returns: Output image object """ dst = dst_1_to_1(src, "rotate", f"α={p.angle:.3f}°, mode='{p.mode}'") dst.data = spi.rotate( src.data, p.angle, reshape=p.reshape, order=p.order, mode=p.mode, cval=p.cval, prefilter=p.prefilter, ) dst.roi = None # Reset ROI as it may change after rotation return dst @computation_function() def rotate90(src: ImageObj) -> ImageObj: """Rotate data 90° with :py:func:`numpy.rot90` Args: src: input image object Returns: Output image object """ dst = dst_1_to_1(src, "rotate90") dst.data = np.rot90(src.data) transformer.transform_roi(dst, "rotate", angle=-np.pi / 2, center=(dst.xc, dst.yc)) return dst @computation_function() def rotate270(src: ImageObj) -> ImageObj: """Rotate data 270° with :py:func:`numpy.rot90` Args: src: input image object Returns: Output image object """ dst = dst_1_to_1(src, "rotate270") dst.data = np.rot90(src.data, 3) transformer.transform_roi(dst, "rotate", angle=np.pi / 2, center=(dst.xc, dst.yc)) return dst @computation_function() def fliph(src: ImageObj) -> ImageObj: """Flip data horizontally with :py:func:`numpy.fliplr` Args: src: input image object Returns: Output image object """ dst = dst_1_to_1(src, "fliph") dst.data = np.fliplr(src.data) transformer.transform_roi(dst, "fliph", cx=dst.xc) return dst @computation_function() def flipv(src: ImageObj) -> ImageObj: """Flip data vertically with :py:func:`numpy.flipud` Args: src: input image object Returns: Output image object """ dst = dst_1_to_1(src, "flipv") dst.data = np.flipud(src.data) transformer.transform_roi(dst, "flipv", cy=dst.yc) return dst class ResizeParam(gds.DataSet): """Resize parameters""" prop = gds.ValueProp(False) zoom = gds.FloatItem(_("Zoom"), default=1.0) mode = gds.ChoiceItem(_("Mode"), BorderMode, default=BorderMode.CONSTANT) cval = gds.FloatItem( _("cval"), default=0.0, help=_( "Value used for points outside the " "boundaries of the input if mode is " "'constant'" ), ) prefilter = gds.BoolItem(_("Prefilter the input image"), default=True).set_prop( "display", store=prop ) order = gds.IntItem( _("Order"), default=3, min=0, max=5, help=_("Spline interpolation order"), ).set_prop("display", active=prop) @computation_function() def resize(src: ImageObj, p: ResizeParam) -> ImageObj: """Zooming function with :py:func:`scipy.ndimage.zoom` Args: src: input image object p: parameters Returns: Output image object Raises: ValueError: if source image has non-uniform coordinates """ if not src.is_uniform_coords: raise ValueError("Source image must have uniform coordinates for resampling") mode = p.mode dst = dst_1_to_1(src, "resize", f"zoom={p.zoom:.3f}") dst.data = spi.zoom( src.data, p.zoom, order=p.order, mode=mode, cval=p.cval, prefilter=p.prefilter, ) if not np.isnan(dst.dx) and not np.isnan(dst.dy): dst.set_uniform_coords(dst.dx / p.zoom, dst.dy / p.zoom, dst.x0, dst.y0) return dst @computation_function() def transpose(src: ImageObj) -> ImageObj: """Transpose image with :py:func:`numpy.transpose`. Args: src: Input image object. Returns: Output image object. """ dst = dst_1_to_1(src, "transpose") dst.data = np.transpose(src.data) dst.xlabel = src.ylabel dst.ylabel = src.xlabel dst.xunit = src.yunit dst.yunit = src.xunit if src.is_uniform_coords: dst.set_uniform_coords(src.dy, src.dx, src.y0, src.x0) else: dst.set_coords(src.ycoords, src.xcoords) transformer.transform_roi(dst, "transpose") return dst class Resampling2DParam(gds.DataSet): """Resample parameters for 2D images""" # Output coordinate system xmin = gds.FloatItem( "Xmin", default=None, allow_none=True, help=_("Minimum X-coordinate of the output image"), ) xmax = gds.FloatItem( "Xmax", default=None, allow_none=True, help=_("Maximum X-coordinate of the output image"), ) ymin = gds.FloatItem( "Ymin", default=None, allow_none=True, help=_("Minimum Y-coordinate of the output image"), ) ymax = gds.FloatItem( "Ymax", default=None, allow_none=True, help=_("Maximum Y-coordinate of the output image"), ) # Mode selection _prop = gds.GetAttrProp("mode") _modes = (("dxy", _("Pixel size")), ("shape", _("Output shape"))) mode = gds.ChoiceItem(_("Mode"), _modes, default="shape", radio=True).set_prop( "display", store=_prop ) # Pixel size mode parameters dx = gds.FloatItem( "ΔX", default=None, allow_none=True, help=_("Pixel size in X direction") ).set_prop("display", active=gds.FuncProp(_prop, lambda x: x == "dxy")) dy = gds.FloatItem( "ΔY", default=None, allow_none=True, help=_("Pixel size in Y direction") ).set_prop("display", active=gds.FuncProp(_prop, lambda x: x == "dxy")) # Shape mode parameters width = gds.IntItem( _("Width"), default=None, allow_none=True, help=_("Output image width in pixels"), ).set_prop("display", active=gds.FuncProp(_prop, lambda x: x == "shape")) height = gds.IntItem( _("Height"), default=None, allow_none=True, help=_("Output image height in pixels"), ).set_prop("display", active=gds.FuncProp(_prop, lambda x: x == "shape")) # Interpolation parameters method = gds.ChoiceItem( _("Interpolation method"), Interpolation2DMethod, default=Interpolation2DMethod.LINEAR, ) fill_value = gds.FloatItem( _("Fill value"), default=None, help=_( "Value to use for points outside the input image domain. " "If None, uses NaN for extrapolation." ), check=False, ) def update_from_obj(self, obj: ImageObj) -> None: """Update parameters from an image object.""" if self.xmin is None: self.xmin = obj.x0 if self.xmax is None: self.xmax = obj.x0 + obj.width if self.ymin is None: self.ymin = obj.y0 if self.ymax is None: self.ymax = obj.y0 + obj.height if self.dx is None: self.dx = obj.dx if self.dy is None: self.dy = obj.dy if self.width is None: self.width = obj.data.shape[1] if self.height is None: self.height = obj.data.shape[0] @computation_function() def resampling(src: ImageObj, p: Resampling2DParam) -> ImageObj: """Resample image to new coordinate grid using interpolation Args: src: source image p: resampling parameters Returns: Resampled image object Raises: ValueError: if source image has non-uniform coordinates """ if not src.is_uniform_coords: raise ValueError("Source image must have uniform coordinates for resampling") # Set output range - use source image bounds if not specified output_xmin = p.xmin if p.xmin is not None else src.x0 output_xmax = p.xmax if p.xmax is not None else src.x0 + src.width output_ymin = p.ymin if p.ymin is not None else src.y0 output_ymax = p.ymax if p.ymax is not None else src.y0 + src.height # Calculate output grid dimensions and spacing output_width_phys = output_xmax - output_xmin output_height_phys = output_ymax - output_ymin # Determine output grid parameters method: Interpolation2DMethod = p.method if p.mode == "dxy": # Calculate dimensions from pixel sizes if p.dx is None or p.dy is None: raise ValueError("dx and dy must be specified in pixel size mode") output_width = int(np.ceil(output_width_phys / p.dx)) output_height = int(np.ceil(output_height_phys / p.dy)) output_dx = p.dx output_dy = p.dy fill_suffix = f", fill_value={p.fill_value}" if p.fill_value is not None else "" suffix = f"method={method.value}, dx={p.dx:.3f}, dy={p.dy:.3f}{fill_suffix}" else: # Use specified shape if p.width is None or p.height is None: raise ValueError("width and height must be specified in shape mode") output_width = p.width output_height = p.height output_dx = output_width_phys / p.width if p.width > 0 else src.dx output_dy = output_height_phys / p.height if p.height > 0 else src.dy fill_suffix = f", fill_value={p.fill_value}" if p.fill_value is not None else "" suffix = f"method={method.value}, size=({p.width}x{p.height}){fill_suffix}" # Create destination image dst = dst_1_to_1(src, "resample", suffix) # Output coordinates (physical) - ensure we sample pixel centers, not boundaries # For an image spanning [xmin, xmax], we want to sample at pixel centers # The pixel centers should be distributed within the range, # not including the exact endpoints if output_width > 1: out_x = np.linspace( output_xmin + output_dx / 2, output_xmax - output_dx / 2, output_width ) else: out_x = np.array([(output_xmin + output_xmax) / 2]) if output_height > 1: out_y = np.linspace( output_ymin + output_dy / 2, output_ymax - output_dy / 2, output_height ) else: out_y = np.array([(output_ymin + output_ymax) / 2]) # Create meshgrids out_X, out_Y = np.meshgrid(out_x, out_y, indexing="xy") # Convert interpolation method to scipy parameter if method == Interpolation2DMethod.LINEAR: order = 1 elif method == Interpolation2DMethod.CUBIC: order = 3 elif method == Interpolation2DMethod.NEAREST: order = 0 else: order = 1 # fallback to linear # Convert physical coordinates to source image indices src_i = (out_X - src.x0) / src.dx src_j = (out_Y - src.y0) / src.dy # Perform interpolation using map_coordinates # Note: map_coordinates expects (j, i) order (row, col) coordinates = np.array([src_j.ravel(), src_i.ravel()]) # Determine fill value for interpolation cval = p.fill_value if p.fill_value is not None else np.nan # For NaN fill values, we need to work with float data to preserve NaN # Convert to float if necessary to allow NaN representation if np.isnan(cval) and not np.issubdtype(src.data.dtype, np.floating): input_data = src.data.astype(np.float64) else: input_data = src.data # Interpolate resampled_data = spi.map_coordinates( input_data, coordinates, order=order, mode="constant", cval=cval, prefilter=True ).reshape(output_height, output_width) # Set output data and coordinate system dst.data = resampled_data dst.set_uniform_coords(output_dx, output_dy, output_xmin, output_ymin) return dst class UniformCoordsParam(gds.DataSet): """Uniform coordinates parameters""" x0 = gds.FloatItem("X0", default=0.0, help=_("Origin X-axis coordinate")) y0 = gds.FloatItem("Y0", default=0.0, help=_("Origin Y-axis coordinate")) dx = gds.FloatItem("Δx", default=1.0, help=_("Pixel size along X-axis")) dy = gds.FloatItem("Δy", default=1.0, help=_("Pixel size along Y-axis")) def update_from_obj(self, obj: ImageObj) -> None: """Update default values from image object's non-uniform coordinates. This method extracts uniform coordinate approximations from non-uniform coordinate arrays, handling numerical precision issues that may arise from arrays created using linspace. Args: obj: Image object with non-uniform coordinates """ if obj.is_uniform_coords: # Already uniform, just copy the values self.x0 = obj.x0 self.y0 = obj.y0 self.dx = obj.dx self.dy = obj.dy else: # Extract from non-uniform coordinates if obj.xcoords is not None and len(obj.xcoords) >= 2: self.x0 = float(obj.xcoords[0]) # Calculate dx with rounding to handle numerical precision dx_raw = (obj.xcoords[-1] - obj.xcoords[0]) / (len(obj.xcoords) - 1) # Round to reasonable precision (12 decimal places) self.dx = float(np.round(dx_raw, 12)) else: self.x0 = 0.0 self.dx = 1.0 if obj.ycoords is not None and len(obj.ycoords) >= 2: self.y0 = float(obj.ycoords[0]) # Calculate dy with rounding to handle numerical precision dy_raw = (obj.ycoords[-1] - obj.ycoords[0]) / (len(obj.ycoords) - 1) # Round to reasonable precision (12 decimal places) self.dy = float(np.round(dy_raw, 12)) else: self.y0 = 0.0 self.dy = 1.0 @computation_function() def set_uniform_coords(src: ImageObj, p: UniformCoordsParam) -> ImageObj: """Convert image to uniform coordinate system Args: src: input image object p: uniform coordinates parameters Returns: Output image object with uniform coordinates """ dst = dst_1_to_1(src, "uniform_coords", f"dx={p.dx}, dy={p.dy}") dst.set_uniform_coords(p.dx, p.dy, p.x0, p.y0) return dst class XYZCalibrateParam(gds.DataSet): """Image polynomial calibration parameters""" axes = (("x", _("X-axis")), ("y", _("Y-axis")), ("z", _("Z-axis"))) axis = gds.ChoiceItem(_("Calibrate"), axes, default="z") a0 = gds.FloatItem("a0", default=0.0, help=_("Constant term")) a1 = gds.FloatItem("a1", default=1.0, help=_("Linear term")) a2 = gds.FloatItem("a2", default=0.0, help=_("Quadratic term")) a3 = gds.FloatItem("a3", default=0.0, help=_("Cubic term")) @computation_function() def calibration(src: ImageObj, p: XYZCalibrateParam) -> ImageObj: """Compute polynomial calibration Applies polynomial transformation: dst = a0 + a1*src + a2*src² + a3*src³ Args: src: input image object p: calibration parameters Returns: Output image object """ # Build polynomial description for metadata terms = [] if p.a0 != 0.0: terms.append(f"{p.a0}") if p.a1 != 0.0: terms.append(f"{p.a1}*{p.axis}" if p.a1 != 1.0 else p.axis) if p.a2 != 0.0: terms.append(f"{p.a2}*{p.axis}²") if p.a3 != 0.0: terms.append(f"{p.a3}*{p.axis}³") poly_str = "+".join(terms) if terms else "0" dst = dst_1_to_1(src, "calibration", f"{p.axis}={poly_str}") shape = src.data.shape if p.axis == "z": # Apply polynomial to data values data = src.data.astype(float) dst.data = p.a0 + p.a1 * data + p.a2 * data**2 + p.a3 * data**3 restore_data_outside_roi(dst, src) elif p.axis == "x": # For X-axis, polynomial calibration requires non-uniform coordinates # (unless it's linear but we don't special case that here) if src.is_uniform_coords: # Generate uniform coordinates array x_uniform = src.x0 + np.arange(src.data.shape[1]) * src.dx # Apply polynomial transformation x_new = p.a0 + p.a1 * x_uniform + p.a2 * x_uniform**2 + p.a3 * x_uniform**3 # Set non-uniform coordinates ycoords = np.linspace(src.y0, src.y0 + src.dy * (shape[0] - 1), shape[0]) dst.set_coords(x_new, ycoords) else: # Apply polynomial to existing non-uniform coordinates x_new = ( p.a0 + p.a1 * src.xcoords + p.a2 * src.xcoords**2 + p.a3 * src.xcoords**3 ) dst.set_coords(x_new, dst.ycoords) elif p.axis == "y": # For Y-axis, polynomial calibration requires non-uniform coordinates if src.is_uniform_coords: # Generate uniform coordinates array y_uniform = src.y0 + np.arange(src.data.shape[0]) * src.dy # Apply polynomial transformation y_new = p.a0 + p.a1 * y_uniform + p.a2 * y_uniform**2 + p.a3 * y_uniform**3 # Set non-uniform coordinates xcoords = np.linspace(src.x0, src.x0 + src.dx * (shape[1] - 1), shape[1]) dst.set_coords(xcoords, y_new) else: # Apply polynomial to existing non-uniform coordinates y_new = ( p.a0 + p.a1 * src.ycoords + p.a2 * src.ycoords**2 + p.a3 * src.ycoords**3 ) dst.set_coords(dst.xcoords, y_new) else: # Should not happen raise ValueError(f"Unknown axis: {p.axis}") # pragma: no cover return dst Sigima-1.1.1/sigima/proc/image/mathops.py000066400000000000000000000215141514013333200202440ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Mathematical Operations Module ------------------------------ This module implements mathematical operations on images, such as inversion, absolute value, real/imaginary part extraction, type casting, and exponentiation. Main features include: - Pixel-wise mathematical transformations (e.g., log, exp, abs, real, imag, log10) - Type casting and other value-level operations These functions enable flexible manipulation of image data at the value level. """ # pylint: disable=invalid-name # Allows short reference names like x, y, ... # Note: # ---- # - All `guidata.dataset.DataSet` parameter classes must also be imported # in the `sigima.params` module. # - All functions decorated by `computation_function` must be imported in the upper # level `sigima.proc.image` module. from __future__ import annotations import warnings import guidata.dataset as gds import numpy as np import sigima.tools.image from sigima.config import _ from sigima.config import options as sigima_options from sigima.enums import AngleUnit from sigima.objects.image import ImageObj from sigima.proc.base import AngleUnitParam, PhaseParam from sigima.proc.decorator import computation_function from sigima.proc.image.base import ( Wrap1to1Func, dst_1_to_1, dst_2_to_1, restore_data_outside_roi, ) from sigima.tools import coordinates from sigima.tools.datatypes import clip_astype # NOTE: Only parameter classes DEFINED in this module should be included in __all__. # Parameter classes imported from other modules (like sigima.proc.base) should NOT # be re-exported to avoid Sphinx cross-reference conflicts. The sigima.params module # serves as the central API point that imports and re-exports all parameter classes. __all__ = [ "DataTypeIParam", "Log10ZPlusNParam", "absolute", "absolute", "astype", "complex_from_magnitude_phase", "complex_from_real_imag", "convolution", "deconvolution", "exp", "exp", "imag", "imag", "inverse", "inverse", "log10", "log10", "log10_z_plus_n", "phase", "real", "real", ] @computation_function() def inverse(src: ImageObj) -> ImageObj: """Compute the inverse of an image and return the new result image object Args: src: input image object Returns: Result image object 1 / **src** (new object) """ dst = dst_1_to_1(src, "inverse") with warnings.catch_warnings(): warnings.simplefilter("ignore", category=RuntimeWarning) dst.data = np.reciprocal(src.data, dtype=float) dst.data[np.isinf(dst.data)] = np.nan restore_data_outside_roi(dst, src) return dst @computation_function() def absolute(src: ImageObj) -> ImageObj: """Compute absolute value with :py:data:`numpy.absolute` Args: src: input image object Returns: Output image object """ return Wrap1to1Func(np.absolute)(src) @computation_function() def real(src: ImageObj) -> ImageObj: """Compute real part with :py:func:`numpy.real` Args: src: input image object Returns: Output image object """ return Wrap1to1Func(np.real)(src) @computation_function() def imag(src: ImageObj) -> ImageObj: """Compute imaginary part with :py:func:`numpy.imag` Args: src: input image object Returns: Output image object """ return Wrap1to1Func(np.imag)(src) @computation_function() def phase(src: ImageObj, p: PhaseParam) -> ImageObj: """Compute the phase (argument) of a complex image. The function uses :py:func:`numpy.angle` to compute the argument and :py:func:`numpy.unwrap` to unwrap it. Args: src: Input image object. p: Phase parameters. Returns: Image object containing the phase, optionally unwrapped. """ suffix = "unwrap" if p.unwrap else "" dst = dst_1_to_1(src, "phase", suffix) data = src.get_data() argument = np.angle(data) if p.unwrap: argument = np.unwrap(argument) if p.unit == AngleUnit.DEGREE: argument = np.rad2deg(argument) dst.data = argument dst.zunit = p.unit restore_data_outside_roi(dst, src) return dst @computation_function() def complex_from_magnitude_phase( src1: ImageObj, src2: ImageObj, p: AngleUnitParam ) -> ImageObj: """Combine magnitude and phase images into a complex image. .. warning:: This function assumes that the input images have the same dimensions. Args: src1: Magnitude (module) image. src2: Phase (argument) image. p: Parameters (provides unit for the phase). Returns: Image object with complex-valued z. """ dst = dst_2_to_1(src1, src2, "mag_phase") assert p.unit is not None dst.data = coordinates.polar_to_complex(src1.data, src2.data, unit=p.unit) return dst @computation_function() def complex_from_real_imag(src1: ImageObj, src2: ImageObj) -> ImageObj: """Combine two real images into a complex image using real + i * imag. .. warning:: This function assumes that the input images have the same dimensions and are properly aligned. Args: src1: Real part image. src2: Imaginary part image. Returns: Image object with complex-valued z. Raises: ValueError: If the x or y coordinates of the two images are not the same. """ dst = dst_2_to_1(src1, src2, "real_imag") assert src1.data is not None assert src2.data is not None dst.data = src1.data + 1j * src2.data return dst @computation_function() def convolution(src: ImageObj, kernel: ImageObj) -> ImageObj: """Convolve an image with a kernel. The kernel should ideally be smaller than the input image and centered. Args: src: Input image object. kernel: Kernel image object. Returns: Output image object. Notes: The behavior of kernel normalization is controlled by the global configuration option ``sigima.config.options.auto_normalize_kernel``. """ # Get configuration option for kernel normalization normalize_kernel = sigima_options.auto_normalize_kernel.get() dst = dst_2_to_1(src, kernel, "⊛") dst.data = sigima.tools.image.convolve( src.data, kernel.data, normalize_kernel_flag=normalize_kernel, ) restore_data_outside_roi(dst, src) return dst @computation_function() def deconvolution(src: ImageObj, kernel: ImageObj) -> ImageObj: """Deconvolve a kernel from an image using Fast Fourier Transform (FFT). Args: src: Input image object. kernel: Kernel image object. Returns: Output image object. Notes: The behavior of kernel normalization is controlled by the global configuration option ``sigima.config.options.auto_normalize_kernel``. """ # Get configuration option for kernel normalization normalize_kernel = sigima_options.auto_normalize_kernel.get() dst = dst_2_to_1(src, kernel, "⊛⁻¹") dst.data = sigima.tools.image.deconvolve( src.data, kernel.data, normalize_kernel_flag=normalize_kernel, ) restore_data_outside_roi(dst, src) return dst @computation_function() def log10(src: ImageObj) -> ImageObj: """Compute log10 with :py:data:`numpy.log10` Args: src: input image object Returns: Output image object """ return Wrap1to1Func(np.log10)(src) @computation_function() def exp(src: ImageObj) -> ImageObj: """Compute exponential with :py:data:`numpy.exp` Args: src: input image object Returns: Output image object """ return Wrap1to1Func(np.exp)(src) class Log10ZPlusNParam(gds.DataSet): """Log10(z+n) parameters""" n = gds.FloatItem("n") @computation_function() def log10_z_plus_n(src: ImageObj, p: Log10ZPlusNParam) -> ImageObj: """Compute log10(z+n) with :py:data:`numpy.log10` Args: src: input image object p: parameters Returns: Output image object """ dst = dst_1_to_1(src, "log10_z_plus_n", f"n={p.n}") dst.data = np.log10(src.data + p.n) restore_data_outside_roi(dst, src) return dst class DataTypeIParam(gds.DataSet): """Convert image data type parameters""" dtype_str = gds.ChoiceItem( _("Destination data type"), list(zip(ImageObj.get_valid_dtypenames(), ImageObj.get_valid_dtypenames())), help=_("Output image data type."), ) @computation_function() def astype(src: ImageObj, p: DataTypeIParam) -> ImageObj: """Convert image data type with :py:func:`sigima.tools.datatypes.clip_astype` Args: src: input image object p: parameters Returns: Output image object """ dst = dst_1_to_1(src, "clip_astype", p.dtype_str) dst.data = clip_astype(src.data, p.dtype_str) return dst Sigima-1.1.1/sigima/proc/image/measurement.py000066400000000000000000000124211514013333200211130ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Measurement computation module ------------------------------ This module provides tools for extracting quantitative information from images, such as object centroids, enclosing circles, and region-based statistics. Main features include: - Centroid and enclosing circle computation - Region/property measurements - Statistical analysis of image regions These functions are useful for image quantification and morphometric analysis. """ # pylint: disable=invalid-name # Allows short reference names like x, y, ... # Note: # ---- # - All `guidata.dataset.DataSet` parameter classes must also be imported # in the `sigima.params` module. # - All functions decorated by `computation_function` must be imported in the upper # level `sigima.proc.image` module. from __future__ import annotations import numpy as np from numpy import ma import sigima.tools.image from sigima.config import _ from sigima.objects import ( GeometryResult, ImageObj, KindShape, SignalObj, TableKind, TableResult, TableResultBuilder, ) from sigima.proc.base import new_signal_result from sigima.proc.decorator import computation_function from sigima.proc.image.base import compute_geometry_from_obj # NOTE: Only parameter classes DEFINED in this module should be included in __all__. # Parameter classes imported from other modules (like sigima.proc.base) should NOT # be re-exported to avoid Sphinx cross-reference conflicts. The sigima.params module # serves as the central API point that imports and re-exports all parameter classes. __all__ = [ "centroid", "enclosing_circle", "horizontal_projection", "stats", "vertical_projection", ] def get_centroid_coords(data: np.ndarray) -> np.ndarray: """Return centroid coordinates with :py:func:`sigima.tools.image.get_centroid_auto` Args: data: input data Returns: Centroid coordinates """ y, x = sigima.tools.image.get_centroid_auto(data) return np.array([(x, y)]) @computation_function() def centroid(image: ImageObj) -> GeometryResult | None: """Compute centroid with :py:func:`sigima.tools.image.get_centroid_fourier` Args: image: input image Returns: Centroid coordinates """ return compute_geometry_from_obj( "centroid", KindShape.MARKER, image, get_centroid_coords ) def get_enclosing_circle_coords(data: np.ndarray) -> np.ndarray: """Return diameter coords for the circle contour enclosing image values above threshold (FWHM) Args: data: input data Returns: Diameter coords """ x, y, r = sigima.tools.image.get_enclosing_circle(data) return np.array([[x, y, r]]) @computation_function() def enclosing_circle(image: ImageObj) -> GeometryResult | None: """Compute minimum enclosing circle with :py:func:`sigima.tools.image.get_enclosing_circle` Args: image: input image Returns: Diameter coords """ return compute_geometry_from_obj( "enclosing_circle", KindShape.CIRCLE, image, get_enclosing_circle_coords ) def __calc_snr_without_warning(data: np.ndarray) -> float: """Calculate SNR based on /σ(z), ignoring warnings Args: data: input data Returns: Signal-to-noise ratio """ with np.errstate(divide="ignore", invalid="ignore"): snr = ma.mean(data) / ma.std(data) return snr @computation_function() def stats(obj: ImageObj) -> TableResult: """Compute statistics on an image Args: obj: input image object Returns: Result properties """ builder = TableResultBuilder(_("Image statistics"), kind=TableKind.STATISTICS) builder.add(ma.min, "min") builder.add(ma.max, "max") builder.add(ma.mean, "mean") builder.add(ma.median, "median") builder.add(ma.std, "std") builder.add(__calc_snr_without_warning, "snr") builder.add(ma.ptp, "ptp") builder.add(ma.sum, "sum") return builder.compute(obj) @computation_function() def horizontal_projection(image: ImageObj) -> SignalObj: """Compute the sum of pixel intensities along each col. (projection on the x-axis). Args: image: Input image object. Returns: Signal object containing the profile. """ dst_signal = new_signal_result( image, "horizontal_projection", units=(image.xunit, image.zunit), labels=(image.xlabel, image.zlabel), ) x = np.linspace(image.x0, image.x0 + image.width - image.dx, image.data.shape[1]) y = image.data.sum(axis=0, dtype=float) dst_signal.set_xydata(x, y) return dst_signal @computation_function() def vertical_projection(image: ImageObj) -> SignalObj: """Compute the sum of pixel intensities along each row (projection on the y-axis). Args: image: Input image object. Returns: Signal object containing the profile. """ dst_signal = new_signal_result( image, "vertical_projection", units=(image.yunit, image.zunit), labels=(image.ylabel, image.zlabel), ) x = np.linspace(image.y0, image.y0 + image.height - image.dy, image.data.shape[0]) y = image.data.sum(axis=1, dtype=float) dst_signal.set_xydata(x, y) return dst_signal Sigima-1.1.1/sigima/proc/image/morphology.py000066400000000000000000000105561514013333200207740ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Morphology computation module ----------------------------- This module provides morphological operations for image processing, such as dilation, erosion, opening, and closing. These operations are useful for removing noise, filling gaps, and extracting structures in binary and grayscale images. """ # pylint: disable=invalid-name # Allows short reference names like x, y, ... # Note: # ---- # - All `guidata.dataset.DataSet` parameter classes must also be imported # in the `sigima.params` module. # - All functions decorated by `computation_function` must be imported in the upper # level `sigima.proc.image` module. from __future__ import annotations import guidata.dataset as gds from skimage import morphology from sigima.config import _ from sigima.objects.image import ImageObj from sigima.proc.decorator import computation_function from sigima.proc.image.base import dst_1_to_1, restore_data_outside_roi # NOTE: Only parameter classes DEFINED in this module should be included in __all__. # Parameter classes imported from other modules (like sigima.proc.base) should NOT # be re-exported to avoid Sphinx cross-reference conflicts. The sigima.params module # serves as the central API point that imports and re-exports all parameter classes. __all__ = [ "MorphologyParam", "black_tophat", "closing", "dilation", "erosion", "opening", "white_tophat", ] class MorphologyParam(gds.DataSet): """White Top-Hat parameters""" radius = gds.IntItem( _("Radius"), default=1, min=1, help=_("Footprint (disk) radius.") ) @computation_function() def white_tophat(src: ImageObj, p: MorphologyParam) -> ImageObj: """Compute White Top-Hat with :py:func:`skimage.morphology.white_tophat` Args: src: input image object p: parameters Returns: Output image object """ dst = dst_1_to_1(src, "white_tophat", f"radius={p.radius}") dst.data = morphology.white_tophat(src.data, morphology.disk(p.radius)) restore_data_outside_roi(dst, src) return dst @computation_function() def black_tophat(src: ImageObj, p: MorphologyParam) -> ImageObj: """Compute Black Top-Hat with :py:func:`skimage.morphology.black_tophat` Args: src: input image object p: parameters Returns: Output image object """ dst = dst_1_to_1(src, "black_tophat", f"radius={p.radius}") dst.data = morphology.black_tophat(src.data, morphology.disk(p.radius)) restore_data_outside_roi(dst, src) return dst @computation_function() def erosion(src: ImageObj, p: MorphologyParam) -> ImageObj: """Compute Erosion with :py:func:`skimage.morphology.erosion` Args: src: input image object p: parameters Returns: Output image object """ dst = dst_1_to_1(src, "erosion", f"radius={p.radius}") dst.data = morphology.erosion(src.data, morphology.disk(p.radius)) restore_data_outside_roi(dst, src) return dst @computation_function() def dilation(src: ImageObj, p: MorphologyParam) -> ImageObj: """Compute Dilation with :py:func:`skimage.morphology.dilation` Args: src: input image object p: parameters Returns: Output image object """ dst = dst_1_to_1(src, "dilation", f"radius={p.radius}") dst.data = morphology.dilation(src.data, morphology.disk(p.radius)) restore_data_outside_roi(dst, src) return dst @computation_function() def opening(src: ImageObj, p: MorphologyParam) -> ImageObj: """Compute morphological opening with :py:func:`skimage.morphology.opening` Args: src: input image object p: parameters Returns: Output image object """ dst = dst_1_to_1(src, "opening", f"radius={p.radius}") dst.data = morphology.opening(src.data, morphology.disk(p.radius)) restore_data_outside_roi(dst, src) return dst @computation_function() def closing(src: ImageObj, p: MorphologyParam) -> ImageObj: """Compute morphological closing with :py:func:`skimage.morphology.closing` Args: src: input image object p: parameters Returns: Output image object """ dst = dst_1_to_1(src, "closing", f"radius={p.radius}") dst.data = morphology.closing(src.data, morphology.disk(p.radius)) restore_data_outside_roi(dst, src) return dst Sigima-1.1.1/sigima/proc/image/noise.py000066400000000000000000000060731514013333200177110ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Noise addition computation module. ---------------------------------- """ # pylint: disable=invalid-name # Allows short reference names like x, y... # Note: # ---- # - All `guidata.dataset.DataSet` parameter classes must also be imported in the # `sigima.params` module. # - All functions decorated by `computation_function` must be imported in the upper # level `sigima.proc.image` module. from __future__ import annotations import guidata.dataset as gds from sigima.objects.base import ( NormalDistributionParam, PoissonDistributionParam, UniformDistributionParam, ) from sigima.objects.image import ( ImageObj, NormalDistribution2DParam, PoissonDistribution2DParam, UniformDistribution2DParam, create_image_from_param, ) from sigima.proc.decorator import computation_function from sigima.proc.image.arithmetic import addition from sigima.proc.image.base import dst_1_to_1 @computation_function() def add_gaussian_noise(src: ImageObj, p: NormalDistributionParam) -> ImageObj: """Add Gaussian (normal) noise to the input image. Args: src: Source image. p: Parameters. Returns: Result image object. """ param = NormalDistribution2DParam() # Do not confuse with NormalDistributionParam gds.update_dataset(param, p) assert src.data is not None shape = src.data.shape param.height = shape[0] param.width = shape[1] param.dtype = src.data.dtype noise = create_image_from_param(param) dst = dst_1_to_1(src, "add_gaussian_noise", f"mu={p.mu},sigma={p.sigma}") dst.data = addition([dst, noise]).data return dst @computation_function() def add_poisson_noise(src: ImageObj, p: PoissonDistributionParam) -> ImageObj: """Add Poisson noise to the input image. Args: src: Source image. p: Parameters. Returns: Result image object. """ param = PoissonDistribution2DParam() # Do not confuse with PoissonDistributionParam gds.update_dataset(param, p) assert src.data is not None shape = src.data.shape param.height = shape[0] param.width = shape[1] param.dtype = src.data.dtype noise = create_image_from_param(param) dst = dst_1_to_1(src, "add_poisson_noise", f"lam={p.lam}") dst.data = addition([dst, noise]).data return dst @computation_function() def add_uniform_noise(src: ImageObj, p: UniformDistributionParam) -> ImageObj: """Add uniform noise to the input image. Args: src: Source image. p: Parameters. Returns: Result image object. """ param = UniformDistribution2DParam() # Do not confuse with UniformDistributionParam gds.update_dataset(param, p) assert src.data is not None shape = src.data.shape param.height = shape[0] param.width = shape[1] param.dtype = src.data.dtype noise = create_image_from_param(param) dst = dst_1_to_1(src, "add_uniform_noise", f"low={p.vmin}, high={p.vmax}") dst.data = addition([dst, noise]).data return dst Sigima-1.1.1/sigima/proc/image/preprocessing.py000066400000000000000000000124361514013333200214570ustar00rootroot00000000000000# -*- coding: utf-8 -*- """ Image preprocessing functions. This module consolidates preprocessing functions that were previously scattered across different modules (exposure, geometry, fourier). All functions in this module operate on high-level ImageObj objects and use parameter classes from the sigima.proc framework. """ from __future__ import annotations import guidata.dataset as gds import numpy as np import sigima.enums import sigima.tools.image from sigima.config import _ from sigima.enums import PadLocation2D from sigima.objects.image import ImageObj from sigima.proc.decorator import computation_function from sigima.proc.image.base import dst_1_to_1 __all__ = [ "BinningParam", "ZeroPadding2DParam", "binning", "zero_padding", ] class BinningParam(gds.DataSet): """Binning parameters.""" sx = gds.IntItem( _("Cluster size (X)"), default=2, min=2, help=_("Number of adjacent pixels to be combined together along X-axis."), ) sy = gds.IntItem( _("Cluster size (Y)"), default=2, min=2, help=_("Number of adjacent pixels to be combined together along Y-axis."), ) operation = gds.ChoiceItem( _("Operation"), sigima.enums.BinningOperation, default=sigima.enums.BinningOperation.SUM, ) dtypes = ["dtype"] + ImageObj.get_valid_dtypenames() dtype_str = gds.ChoiceItem( _("Data type"), list(zip(dtypes, dtypes)), help=_("Output image data type."), ) change_pixel_size = gds.BoolItem( _("Change pixel size"), default=True, help=_( "If checked, pixel size is updated according to binning factors. " "Users who prefer to work with pixel coordinates may want to uncheck this." ), ) @computation_function() def binning(src: ImageObj, p: BinningParam) -> ImageObj: """Binning: image pixel binning (or aggregation). Depending on the algorithm, the input image may be cropped to fit an integer number of blocks. Args: src: source image p: parameters Returns: Output image Raises: ValueError: if source image has non-uniform coordinates """ if not src.is_uniform_coords: raise ValueError("Binning only works with images having uniform coordinates") # Create destination image dst = dst_1_to_1( src, "binning", f"{p.sx}x{p.sy},{p.operation},change_pixel_size={p.change_pixel_size}", ) dst.data = sigima.tools.image.binning( src.data, sx=p.sx, sy=p.sy, operation=p.operation, dtype=None if p.dtype_str == "dtype" else p.dtype_str, ) if p.change_pixel_size: if not np.isnan(src.dx) and not np.isnan(src.dy): # Update coordinates with new pixel spacing new_dx = src.dx * p.sx new_dy = src.dy * p.sy dst.set_uniform_coords(new_dx, new_dy, src.x0, src.y0) return dst class ZeroPadding2DParam(gds.DataSet): """Zero padding parameters for 2D images""" def __init__(self, *args, **kwargs) -> None: super().__init__(*args, **kwargs) self.__obj: ImageObj | None = None def update_from_obj(self, obj: ImageObj) -> None: """Update parameters from image""" self.__obj = obj self.choice_callback(None, self.strategy) def choice_callback(self, item, value): # pylint: disable=unused-argument """Callback to update padding values""" if self.__obj is None: return rows, cols = self.__obj.data.shape if value == "next_pow2": self.rows = 2 ** int(np.ceil(np.log2(rows))) - rows self.cols = 2 ** int(np.ceil(np.log2(cols))) - cols elif value == "multiple_of_64": self.rows = (64 - rows % 64) if rows % 64 != 0 else 0 self.cols = (64 - cols % 64) if cols % 64 != 0 else 0 strategies = ("next_pow2", "multiple_of_64", "custom") _prop = gds.GetAttrProp("strategy") strategy = gds.ChoiceItem( _("Padding strategy"), zip(strategies, strategies), default=strategies[-1] ).set_prop("display", store=_prop, callback=choice_callback) _func_prop = gds.FuncProp(_prop, lambda x: x == "custom") rows = gds.IntItem(_("Rows to add"), min=0, default=0).set_prop( "display", active=_func_prop ) cols = gds.IntItem(_("Columns to add"), min=0, default=0).set_prop( "display", active=_func_prop ) position = gds.ChoiceItem( _("Padding position"), PadLocation2D, default=PadLocation2D.BOTTOM_RIGHT ) @computation_function() def zero_padding( src: ImageObj, p: ZeroPadding2DParam | None = None, ) -> ImageObj: """Zero-padding: add zeros to image borders. Args: src: input image object p: parameters Returns: Output image object """ if p is None: p = ZeroPadding2DParam.create() if p.strategy == "custom": suffix = f"rows={p.rows}, cols={p.cols}" else: suffix = f"strategy={p.strategy}" suffix += f", position={p.position}" dst = dst_1_to_1(src, "zero_padding", suffix) result = sigima.tools.image.zero_padding( src.data, rows=p.rows, cols=p.cols, position=p.position, ) dst.data = result return dst Sigima-1.1.1/sigima/proc/image/restoration.py000066400000000000000000000150761514013333200211500ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Restoration computation module ------------------------------ This module provides image restoration techniques, such as denoising, inpainting, and deblurring. These methods aim to recover the original quality of images by removing artifacts, noise, or distortions. """ # pylint: disable=invalid-name # Allows short reference names like x, y, ... # Note: # ---- # - All `guidata.dataset.DataSet` parameter classes must also be imported # in the `sigima.params` module. # - All functions decorated by `computation_function` must be imported in the upper # level `sigima.proc.image` module. from __future__ import annotations from typing import TYPE_CHECKING import guidata.dataset as gds import numpy as np import pywt from skimage import morphology, restoration from sigima.config import _ from sigima.enums import ShrinkageMethod, ThresholdMethod, WaveletMode from sigima.objects.image import ImageObj, ROI2DParam from sigima.proc.decorator import computation_function from sigima.proc.image.base import Wrap1to1Func, dst_1_to_1, restore_data_outside_roi if TYPE_CHECKING: import sigima.params # NOTE: Only parameter classes DEFINED in this module should be included in __all__. # Parameter classes imported from other modules (like sigima.proc.base) should NOT # be re-exported to avoid Sphinx cross-reference conflicts. The sigima.params module # serves as the central API point that imports and re-exports all parameter classes. __all__ = [ "DenoiseBilateralParam", "DenoiseTVParam", "DenoiseWaveletParam", "denoise_bilateral", "denoise_tophat", "denoise_tv", "denoise_wavelet", "erase", ] class DenoiseTVParam(gds.DataSet): """Total Variation denoising parameters""" weight = gds.FloatItem( _("Denoising weight"), default=0.1, min=0, nonzero=True, help=_( "The greater weight, the more denoising " "(at the expense of fidelity to input)." ), ) eps = gds.FloatItem( "Epsilon", default=0.0002, min=0, nonzero=True, help=_( "Relative difference of the value of the cost function that " "determines the stop criterion. The algorithm stops when: " "(E_(n-1) - E_n) < eps * E_0" ), ) max_num_iter = gds.IntItem( _("Max. iterations"), default=200, min=0, nonzero=True, help=_("Maximal number of iterations used for the optimization"), ) @computation_function() def denoise_tv(src: ImageObj, p: DenoiseTVParam) -> ImageObj: """Compute Total Variation denoising with :py:func:`skimage.restoration.denoise_tv_chambolle` Args: src: input image object p: parameters Returns: Output image object """ return Wrap1to1Func( restoration.denoise_tv_chambolle, weight=p.weight, eps=p.eps, max_num_iter=p.max_num_iter, func_name="denoise_tv", )(src) class DenoiseBilateralParam(gds.DataSet): """Bilateral filter denoising parameters""" sigma_spatial = gds.FloatItem( "σspatial", default=1.0, min=0, nonzero=True, unit="pixels", help=_( "Standard deviation for range distance. " "A larger value results in averaging of pixels " "with larger spatial differences." ), ) mode = gds.ChoiceItem(_("Mode"), WaveletMode, default=WaveletMode.CONSTANT) cval = gds.FloatItem( "cval", default=0.0, help=_( "Used in conjunction with mode 'constant', " "the value outside the image boundaries." ), ) @computation_function() def denoise_bilateral(src: ImageObj, p: DenoiseBilateralParam) -> ImageObj: """Compute bilateral filter denoising with :py:func:`skimage.restoration.denoise_bilateral` Args: src: input image object p: parameters Returns: Output image object """ return Wrap1to1Func( restoration.denoise_bilateral, sigma_spatial=p.sigma_spatial, mode=p.mode, cval=p.cval, )(src) class DenoiseWaveletParam(gds.DataSet): """Wavelet denoising parameters""" wavelets = pywt.wavelist() wavelet = gds.ChoiceItem( _("Wavelet"), list(zip(wavelets, wavelets)), default="sym9" ) mode = gds.ChoiceItem(_("Mode"), ThresholdMethod, default=ThresholdMethod.SOFT) method = gds.ChoiceItem( _("Method"), ShrinkageMethod, default=ShrinkageMethod.VISU_SHRINK ) @computation_function() def denoise_wavelet(src: ImageObj, p: DenoiseWaveletParam) -> ImageObj: """Compute Wavelet denoising with :py:func:`skimage.restoration.denoise_wavelet` Args: src: input image object p: parameters Returns: Output image object """ return Wrap1to1Func( restoration.denoise_wavelet, wavelet=p.wavelet, mode=p.mode, method=p.method )(src) @computation_function() def denoise_tophat(src: ImageObj, p: sigima.params.MorphologyParam) -> ImageObj: """Denoise using White Top-Hat with :py:func:`skimage.morphology.white_tophat` Args: src: input image object p: parameters Returns: Output image object """ dst = dst_1_to_1(src, "denoise_tophat", f"radius={p.radius}") dst.data = src.data - morphology.white_tophat(src.data, morphology.disk(p.radius)) restore_data_outside_roi(dst, src) return dst @computation_function() def erase(src: ImageObj, p: ROI2DParam | list[ROI2DParam]) -> ImageObj: """Erase an area of the image using the mean value of the image. .. note:: The erased area is defined by a region of interest (ROI) parameter set. This ROI must not be mistaken with the ROI of the image object. If the image object has a ROI, it is not used in this processing, except to restore the data outside the ROI (as in all other processing). Args: src: input image object p: parameters defining the area to erase (region of interest) Returns: Output image object """ params = [p] if isinstance(p, ROI2DParam) else p suffix = None if len(params) == 1: suffix = params[0].get_suffix() dst = dst_1_to_1(src, "erase", suffix) for param in params: value = np.nanmean(param.get_data(src)) erase_roi = param.to_single_roi(src) mask = erase_roi.to_mask(src) dst.data[~mask] = value restore_data_outside_roi(dst, src) return dst Sigima-1.1.1/sigima/proc/image/threshold.py000066400000000000000000000146331514013333200205710ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Threshold computation module ---------------------------- This module provides various thresholding techniques for image segmentation. Thresholding is a simple yet effective method to separate objects from the background in an image by converting it into a binary image based on a specified threshold value. """ # pylint: disable=invalid-name # Allows short reference names like x, y, ... # Note: # ---- # - All `guidata.dataset.DataSet` parameter classes must also be imported # in the `sigima.params` module. # - All functions decorated by `computation_function` must be imported in the upper # level `sigima.proc.image` module. from __future__ import annotations import guidata.dataset as gds import skimage.util from skimage import filters from sigima.config import _ from sigima.objects.image import ImageObj from sigima.proc.decorator import computation_function from sigima.proc.image.base import dst_1_to_1, restore_data_outside_roi # NOTE: Only parameter classes DEFINED in this module should be included in __all__. # Parameter classes imported from other modules (like sigima.proc.base) should NOT # be re-exported to avoid Sphinx cross-reference conflicts. The sigima.params module # serves as the central API point that imports and re-exports all parameter classes. __all__ = [ "ThresholdParam", "threshold", "threshold_isodata", "threshold_li", "threshold_mean", "threshold_minimum", "threshold_otsu", "threshold_triangle", "threshold_yen", ] class ThresholdParam(gds.DataSet): """Histogram threshold parameters""" methods = ( ("manual", _("Manual")), ("isodata", "ISODATA"), ("li", "Li"), ("mean", _("Mean")), ("minimum", _("Minimum")), ("otsu", "Otsu"), ("triangle", _("Triangle")), ("yen", "Yen"), ) _method_prop = gds.GetAttrProp("method") method = gds.ChoiceItem(_("Threshold method"), methods, default="manual").set_prop( "display", store=_method_prop ) bins = gds.IntItem(_("Number of bins"), default=256, min=1).set_prop( "display", active=gds.FuncProp(_method_prop, lambda x: x not in ("li", "mean", "manual")), ) value = gds.FloatItem(_("Threshold value"), default=0.0).set_prop( "display", active=gds.FuncProp(_method_prop, lambda x: x == "manual") ) operation = gds.ChoiceItem( _("Operation"), ((">", _("Greater than")), ("<", _("Less than"))), default=">", ) @computation_function() def threshold(src: ImageObj, p: ThresholdParam) -> ImageObj: """Compute the threshold, using one of the available algorithms: - Manual: a fixed threshold value - ISODATA: :py:func:`skimage.filters.threshold_isodata` - Li: :py:func:`skimage.filters.threshold_li` - Mean: :py:func:`skimage.filters.threshold_mean` - Minimum: :py:func:`skimage.filters.threshold_minimum` - Otsu: :py:func:`skimage.filters.threshold_otsu` - Triangle: :py:func:`skimage.filters.threshold_triangle` - Yen: :py:func:`skimage.filters.threshold_yen` Args: src: input image object p: parameters Returns: Output image object """ if p.method == "manual": suffix = f"value={p.value}" value = p.value else: suffix = f"method={p.method}" if p.method not in ("li", "mean"): suffix += f", nbins={p.bins}" func = getattr(filters, f"threshold_{p.method}") args = [] if p.method in ("li", "mean") else [p.bins] value = func(src.data, *args) suffix += f", op='{p.operation}'" dst = dst_1_to_1(src, "threshold", suffix) data = src.data > value if p.operation == ">" else src.data < value dst.data = skimage.util.img_as_ubyte(data) dst.zscalemin, dst.zscalemax = 0, 255 # LUT range dst.set_metadata_option("colormap", "gray") restore_data_outside_roi(dst, src) return dst @computation_function() def threshold_isodata(src: ImageObj) -> ImageObj: """Compute the threshold using the Isodata algorithm with default parameters, see :py:func:`skimage.filters.threshold_isodata` Args: src: input image object Returns: Output image object """ return threshold(src, ThresholdParam.create(method="isodata")) @computation_function() def threshold_li(src: ImageObj) -> ImageObj: """Compute the threshold using the Li algorithm with default parameters, see :py:func:`skimage.filters.threshold_li` Args: src: input image object Returns: Output image object """ return threshold(src, ThresholdParam.create(method="li")) @computation_function() def threshold_mean(src: ImageObj) -> ImageObj: """Compute the threshold using the Mean algorithm, see :py:func:`skimage.filters.threshold_mean` Args: src: input image object Returns: Output image object """ return threshold(src, ThresholdParam.create(method="mean")) @computation_function() def threshold_minimum(src: ImageObj) -> ImageObj: """Compute the threshold using the Minimum algorithm with default parameters, see :py:func:`skimage.filters.threshold_minimum` Args: src: input image object Returns: Output image object """ return threshold(src, ThresholdParam.create(method="minimum")) @computation_function() def threshold_otsu(src: ImageObj) -> ImageObj: """Compute the threshold using the Otsu algorithm with default parameters, see :py:func:`skimage.filters.threshold_otsu` Args: src: input image object Returns: Output image object """ return threshold(src, ThresholdParam.create(method="otsu")) @computation_function() def threshold_triangle(src: ImageObj) -> ImageObj: """Compute the threshold using the Triangle algorithm with default parameters, see :py:func:`skimage.filters.threshold_triangle` Args: src: input image object Returns: Output image object """ return threshold(src, ThresholdParam.create(method="triangle")) @computation_function() def threshold_yen(src: ImageObj) -> ImageObj: """Compute the threshold using the Yen algorithm with default parameters, see :py:func:`skimage.filters.threshold_yen` Args: src: input image object Returns: Output image object """ return threshold(src, ThresholdParam.create(method="yen")) Sigima-1.1.1/sigima/proc/image/transformations.py000066400000000000000000000316021514013333200220210ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Geometry transformations module =============================== This module provides a unified interface for applying geometric transformations to both geometry results (:class:`sigima.objects.GeometryResult`) and ROI objects using the shape coordinate system (:mod:`sigima.objects.shape`). """ from __future__ import annotations from typing import TYPE_CHECKING, Any import numpy as np from sigima.objects.scalar import GeometryResult, KindShape from sigima.objects.shape import ( CircleCoordinates, EllipseCoordinates, PointCoordinates, PolygonCoordinates, RectangleCoordinates, SegmentCoordinates, ) if TYPE_CHECKING: from sigima.objects import CircularROI, ImageObj, PolygonalROI, RectangularROI __all__ = [ "GeometryTransformer", "transformer", ] class GeometryTransformer: """ Singleton class for applying transformations to geometry objects. Provides a unified interface for transforming both GeometryResult and ROI objects using the shape coordinate system. """ _instance: GeometryTransformer | None = None def __new__(cls) -> GeometryTransformer: """Ensure singleton pattern.""" if cls._instance is None: cls._instance = super().__new__(cls) cls._instance._initialized = False return cls._instance def __init__(self) -> None: """Initialize the transformer (only once due to singleton).""" if self._initialized: # pylint: disable=access-member-before-definition return # Mapping from GeometryResult kinds to shape coordinate classes self._geometry_shape_map: dict[ KindShape, type[ RectangleCoordinates | CircleCoordinates | PolygonCoordinates | SegmentCoordinates ], ] = { KindShape.POINT: PointCoordinates, KindShape.RECTANGLE: RectangleCoordinates, KindShape.CIRCLE: CircleCoordinates, KindShape.ELLIPSE: EllipseCoordinates, KindShape.POLYGON: PolygonCoordinates, KindShape.SEGMENT: SegmentCoordinates, KindShape.MARKER: PointCoordinates, } # Mapping from ROI types to shape coordinate classes (lazy loaded) self._roi_shape_map: dict[type, type] = {} self._initialized = True def _get_roi_shape_map( self, ) -> dict[ type[CircularROI | RectangularROI | PolygonalROI], type[RectangleCoordinates | CircleCoordinates | PolygonCoordinates], ]: """Lazy load ROI shape mapping to avoid circular imports.""" if not self._roi_shape_map: # pylint: disable=import-outside-toplevel from sigima.objects.image import CircularROI, PolygonalROI, RectangularROI self._roi_shape_map = { RectangularROI: RectangleCoordinates, CircularROI: CircleCoordinates, PolygonalROI: PolygonCoordinates, } return self._roi_shape_map def transform_geometry( self, geometry: GeometryResult, operation: str, **kwargs: Any ) -> GeometryResult: """ Transform a GeometryResult and return a new one. Args: geometry: The GeometryResult to transform. operation: Operation name ('rotate', 'translate', 'fliph', 'flipv', 'transpose', 'scale'). **kwargs: Operation-specific parameters. Returns: New GeometryResult with transformed coordinates. Raises: ValueError: If operation is unknown or geometry kind is unsupported. """ coord_class = self._geometry_shape_map.get(geometry.kind) if coord_class is None: raise ValueError(f"Unsupported geometry kind: {geometry.kind}") # Transform each row of coordinates transformed_coords = [] for row in geometry.coords: # Create coordinate object for this row shape_coords = coord_class(row.copy()) # Apply transformation self._apply_operation(shape_coords, operation, **kwargs) transformed_coords.append(shape_coords.data) # Create new GeometryResult with transformed coordinates return GeometryResult( title=geometry.title, kind=geometry.kind, coords=np.array(transformed_coords), roi_indices=( geometry.roi_indices.copy() if geometry.roi_indices is not None else None ), attrs=geometry.attrs.copy(), func_name=geometry.func_name, ) def transform_single_roi( self, single_roi: RectangularROI | CircularROI | PolygonalROI, operation: str, **kwargs: Any, ) -> None: """ Transform ROI coordinates inplace. Args: single_roi: ROI object with .coords attribute. operation: Operation name. **kwargs: Operation-specific parameters. Raises: ValueError: If ROI type is unsupported or operation is unknown. """ roi_shape_map = self._get_roi_shape_map() coord_class = roi_shape_map.get(type(single_roi)) if coord_class is None: raise ValueError(f"Unsupported ROI type: {type(single_roi)}") # Create shape coordinates and transform shape_coords = coord_class(single_roi.coords.copy()) self._apply_operation(shape_coords, operation, **kwargs) # Update ROI coordinates inplace single_roi.coords[:] = shape_coords.data def transform_roi(self, image: ImageObj, operation: str, **kwargs: Any) -> None: """ Transform all ROI coordinates in an ImageObj inplace. Args: image: Image object whose ROI coordinates will be transformed. operation: Operation name. **kwargs: Operation-specific parameters. """ if image.roi is None or image.roi.is_empty(): return # Import here to avoid circular imports # pylint: disable=import-outside-toplevel from sigima.objects.image import ImageROI # Determine ROI type and set up appropriate classes new_roi = ImageROI() # Transform each single ROI for single_roi in image.roi.single_rois: coords = single_roi.coords.copy() roi_class = single_roi.__class__ # Create shape coordinates and transform roi_shape_map = self._get_roi_shape_map() coord_class = roi_shape_map.get(roi_class) if coord_class is None: raise ValueError(f"Unsupported ROI type: {roi_class}") shape_coords = coord_class(coords) self._apply_operation(shape_coords, operation, **kwargs) new_coords = shape_coords.data new_single_roi = roi_class(new_coords, single_roi.indices, single_roi.title) new_roi.add_roi(new_single_roi) image.roi = new_roi def _apply_operation( self, shape_coords: ( PointCoordinates | RectangleCoordinates | CircleCoordinates | EllipseCoordinates | PolygonCoordinates | SegmentCoordinates ), operation: str, **kwargs: Any, ) -> None: """ Apply the specified operation to shape coordinates. Args: shape_coords: Shape coordinate object to transform. operation: Operation name. **kwargs: Operation-specific parameters. Raises: ValueError: If operation is unknown. """ if operation == "rotate": angle = kwargs.get("angle", 0) center = kwargs.get("center", (0, 0)) shape_coords.rotate(angle, center) elif operation == "translate": dx = kwargs.get("dx", 0) dy = kwargs.get("dy", 0) shape_coords.translate(dx, dy) elif operation == "fliph": cx = kwargs.get("cx", 0.0) shape_coords.fliph(cx) elif operation == "flipv": cy = kwargs.get("cy", 0.0) shape_coords.flipv(cy) elif operation == "transpose": shape_coords.transpose() elif operation == "scale": sx = kwargs.get("sx", 1.0) sy = kwargs.get("sy", 1.0) center = kwargs.get("center", (0, 0)) shape_coords.scale(sx, sy, center) else: raise ValueError(f"Unknown operation: {operation}") # Convenience methods for common operations def rotate( self, obj: GeometryResult | RectangularROI | CircularROI | PolygonalROI, angle: float, center: tuple[float, float], ) -> GeometryResult | None: """ Rotate geometry or ROI by given angle around center. Args: obj: GeometryResult or single ROI object. angle: Rotation angle in radians. center: Center of rotation (x, y). Returns: New GeometryResult if input was GeometryResult, None if ROI (inplace). """ if isinstance(obj, GeometryResult): return self.transform_geometry(obj, "rotate", angle=angle, center=center) self.transform_single_roi(obj, "rotate", angle=angle, center=center) return None def translate( self, obj: GeometryResult | RectangularROI | CircularROI | PolygonalROI, dx: float, dy: float, ) -> GeometryResult | None: """ Translate geometry or ROI by given offset. Args: obj: GeometryResult or single ROI object. dx: Translation in x direction. dy: Translation in y direction. Returns: New GeometryResult if input was GeometryResult, None if ROI (inplace). """ if isinstance(obj, GeometryResult): return self.transform_geometry(obj, "translate", dx=dx, dy=dy) self.transform_single_roi(obj, "translate", dx=dx, dy=dy) return None def fliph( self, obj: GeometryResult | RectangularROI | CircularROI | PolygonalROI, cx: float, ) -> GeometryResult | None: """ Flip geometry or ROI horizontally around given x-coordinate. Args: obj: GeometryResult or single ROI object. cx: X-coordinate of flip axis. Returns: New GeometryResult if input was GeometryResult, None if ROI (inplace). """ if isinstance(obj, GeometryResult): return self.transform_geometry(obj, "fliph", cx=cx) self.transform_single_roi(obj, "fliph", cx=cx) return None def flipv( self, obj: GeometryResult | RectangularROI | CircularROI | PolygonalROI, cy: float, ) -> GeometryResult | None: """ Flip geometry or ROI vertically around given y-coordinate. Args: obj: GeometryResult or single ROI object. cy: Y-coordinate of flip axis. Returns: New GeometryResult if input was GeometryResult, None if ROI (inplace). """ if isinstance(obj, GeometryResult): return self.transform_geometry(obj, "flipv", cy=cy) self.transform_single_roi(obj, "flipv", cy=cy) return None def transpose( self, obj: GeometryResult | RectangularROI | CircularROI | PolygonalROI ) -> GeometryResult | None: """ Transpose geometry or ROI (swap x and y coordinates). Args: obj: GeometryResult or single ROI object. Returns: New GeometryResult if input was GeometryResult, None if ROI (inplace). """ if isinstance(obj, GeometryResult): return self.transform_geometry(obj, "transpose") self.transform_single_roi(obj, "transpose") return None def scale( self, obj: GeometryResult | RectangularROI | CircularROI | PolygonalROI, sx: float, sy: float, center: tuple[float, float], ) -> GeometryResult | None: """ Scale geometry or ROI by given factors around center. Args: obj: GeometryResult or single ROI object. sx: Scale factor in x direction. sy: Scale factor in y direction. center: Center of scaling (x, y). Returns: New GeometryResult if input was GeometryResult, None if ROI (inplace). """ if isinstance(obj, GeometryResult): return self.transform_geometry(obj, "scale", sx=sx, sy=sy, center=center) self.transform_single_roi(obj, "scale", sx=sx, sy=sy, center=center) return None #: Global singleton instance of GeometryTransformer for applying geometric #: transformations to geometry results and ROI objects. transformer = GeometryTransformer() Sigima-1.1.1/sigima/proc/signal/000077500000000000000000000000001514013333200164075ustar00rootroot00000000000000Sigima-1.1.1/sigima/proc/signal/__init__.py000066400000000000000000000161101514013333200205170ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Basic signal processing ~~~~~~~~~~~~~~~~~~~~~~~ .. automodule:: sigima.proc.signal.base :members: :no-index: Arithmetic ~~~~~~~~~~ .. automodule:: sigima.proc.signal.arithmetic :members: :no-index: Mathematical Operations ~~~~~~~~~~~~~~~~~~~~~~~ .. automodule:: sigima.proc.signal.mathops :members: :no-index: Extraction ~~~~~~~~~~ .. automodule:: sigima.proc.signal.extraction :members: :no-index: Filtering ~~~~~~~~~ .. automodule:: sigima.proc.signal.filtering :members: :no-index: Processing ~~~~~~~~~~ .. automodule:: sigima.proc.signal.processing :members: :no-index: Fourier ~~~~~~~ .. automodule:: sigima.proc.signal.fourier :members: :no-index: Fitting ~~~~~~~ .. automodule:: sigima.proc.signal.fitting :members: :no-index: Features ~~~~~~~~ .. automodule:: sigima.proc.signal.features :members: :no-index: Stability ~~~~~~~~~ .. automodule:: sigima.proc.signal.stability :members: :no-index: Analysis ~~~~~~~~ .. automodule:: sigima.proc.signal.analysis :members: :no-index: """ # pylint: disable=invalid-name # Allows short reference names like x, y, ... # MARK: Important notes # --------------------- # - All `guidata.dataset.DataSet` classes must also be imported # in the `sigima.params` module. # - All functions decorated by `computation_function` defined in the other modules # of this package must be imported right here. from __future__ import annotations # Import parameter classes from the main base module from sigima.proc.signal.analysis import ( PulseFeaturesParam, contrast, extract_pulse_features, histogram, sampling_rate_period, x_at_minmax, ) from sigima.proc.signal.arithmetic import ( addition, addition_constant, arithmetic, average, difference, difference_constant, division, division_constant, product, product_constant, quadratic_difference, signals_to_image, standard_deviation, ) from sigima.proc.signal.base import ( Wrap1to1Func, compute_geometry_from_obj, is_uncertainty_data_available, restore_data_outside_roi, ) from sigima.proc.signal.extraction import ( extract_roi, extract_rois, ) from sigima.proc.signal.features import ( AbscissaParam, DynamicParam, FWHMParam, OrdinateParam, PeakDetectionParam, bandwidth_3db, dynamic_parameters, full_width_at_y, fw1e2, fwhm, peak_detection, stats, x_at_y, y_at_x, ) from sigima.proc.signal.filtering import ( BandPassFilterParam, BandStopFilterParam, BaseHighLowBandParam, FrequencyFilterMethod, HighPassFilterParam, LowPassFilterParam, PadLocation1D, add_gaussian_noise, add_poisson_noise, add_uniform_noise, bandpass, bandstop, frequency_filter, gaussian_filter, get_nyquist_frequency, highpass, lowpass, moving_average, moving_median, wiener, ) from sigima.proc.signal.fitting import ( PolynomialFitParam, cdf_fit, evaluate_fit, exponential_fit, extract_fit_params, gaussian_fit, linear_fit, lorentzian_fit, piecewiseexponential_fit, planckian_fit, polynomial_fit, sigmoid_fit, sinusoidal_fit, twohalfgaussian_fit, voigt_fit, ) from sigima.proc.signal.fourier import ( ZeroPadding1DParam, fft, ifft, magnitude_spectrum, phase_spectrum, psd, zero_padding, ) from sigima.proc.signal.mathops import ( DataTypeSParam, PowerParam, absolute, astype, complex_from_magnitude_phase, complex_from_real_imag, exp, imag, inverse, log10, phase, power, real, sqrt, to_cartesian, to_polar, transpose, ) from sigima.proc.signal.processing import ( DetrendingParam, InterpolationParam, Resampling1DParam, WindowingParam, XYCalibrateParam, apply_window, calibration, check_same_sample_rate, clip, convolution, deconvolution, derivative, detrending, integral, interpolate, normalize, offset_correction, replace_x_by_other_y, resampling, reverse_x, xy_mode, ) from sigima.proc.signal.stability import ( AllanVarianceParam, allan_deviation, allan_variance, hadamard_variance, modified_allan_variance, overlapping_allan_variance, time_deviation, total_variance, ) __all__ = [ "AbscissaParam", "AllanVarianceParam", "BandPassFilterParam", "BandStopFilterParam", "BaseHighLowBandParam", "DataTypeSParam", "DetrendingParam", "DynamicParam", "FWHMParam", "FrequencyFilterMethod", "HighPassFilterParam", "InterpolationParam", "LowPassFilterParam", "OrdinateParam", "PadLocation1D", "PeakDetectionParam", "PolynomialFitParam", "PowerParam", "PulseFeaturesParam", "Resampling1DParam", "WindowingParam", "Wrap1to1Func", "XYCalibrateParam", "ZeroPadding1DParam", "absolute", "add_gaussian_noise", "add_poisson_noise", "add_uniform_noise", "addition", "addition_constant", "allan_deviation", "allan_variance", "apply_window", "arithmetic", "astype", "average", "bandpass", "bandstop", "bandwidth_3db", "calibration", "cdf_fit", "check_same_sample_rate", "clip", "complex_from_magnitude_phase", "complex_from_real_imag", "compute_geometry_from_obj", "contrast", "convolution", "deconvolution", "derivative", "detrending", "difference", "difference_constant", "division", "division_constant", "dynamic_parameters", "evaluate_fit", "exp", "exponential_fit", "extract_fit_params", "extract_pulse_features", "extract_roi", "extract_rois", "fft", "frequency_filter", "full_width_at_y", "fw1e2", "fwhm", "gaussian_filter", "gaussian_fit", "get_nyquist_frequency", "hadamard_variance", "highpass", "histogram", "ifft", "imag", "integral", "interpolate", "inverse", "is_uncertainty_data_available", "linear_fit", "log10", "lorentzian_fit", "lowpass", "magnitude_spectrum", "modified_allan_variance", "moving_average", "moving_median", "normalize", "offset_correction", "overlapping_allan_variance", "peak_detection", "phase", "phase_spectrum", "piecewiseexponential_fit", "planckian_fit", "polynomial_fit", "power", "product", "product_constant", "psd", "quadratic_difference", "real", "replace_x_by_other_y", "resampling", "restore_data_outside_roi", "reverse_x", "sampling_rate_period", "sigmoid_fit", "signals_to_image", "sinusoidal_fit", "sqrt", "standard_deviation", "stats", "time_deviation", "to_cartesian", "to_polar", "total_variance", "transpose", "twohalfgaussian_fit", "voigt_fit", "wiener", "x_at_minmax", "x_at_y", "xy_mode", "y_at_x", "zero_padding", ] Sigima-1.1.1/sigima/proc/signal/analysis.py000066400000000000000000000152671514013333200206170ustar00rootroot00000000000000# -*- coding: utf-8 -*- # Licensed under the terms of the BSD 3-Clause # (see sigima/LICENSE for details) """ General analysis functions ========================== This module provides general analysis functions for signal objects: - Histogram computation - Other analysis operations .. note:: Most operations use standard NumPy/SciPy functions or custom analysis routines. """ from __future__ import annotations import guidata.dataset as gds import numpy as np from sigima.config import _ from sigima.objects import ( SignalObj, TableKind, TableResult, TableResultBuilder, ) from sigima.proc.base import HistogramParam, new_signal_result from sigima.proc.decorator import computation_function from sigima.tools.signal import dynamic, features, pulse @computation_function() def histogram(src: SignalObj, p: HistogramParam) -> SignalObj: """Compute histogram with :py:func:`numpy.histogram` Args: src: source signal p: parameters Returns: Result signal object """ data = src.get_masked_view().compressed() suffix = p.get_suffix(data) # Also updates p.lower and p.upper # Compute histogram: y, bin_edges = np.histogram(data, bins=p.bins, range=(p.lower, p.upper)) x = (bin_edges[:-1] + bin_edges[1:]) / 2 # Note: we use the `new_signal_result` function to create the result signal object # because the `dst_1_to_1` would copy the source signal, which is not what we want # here (we want a brand new signal object). dst = new_signal_result( src, "histogram", suffix=suffix, units=(src.yunit, ""), labels=(src.ylabel, _("Counts")), ) dst.set_xydata(x, y) dst.set_metadata_option("shade", 0.5) dst.set_metadata_option("curvestyle", "Steps") return dst class PulseFeaturesParam(gds.DataSet, title=_("Pulse features")): """Pulse features parameters.""" signal_shape = gds.ChoiceItem( _("Signal shape"), [ (None, _("Auto")), ("step", _("Step")), ("square", _("Square")), ], default=None, help=_("Signal type: auto-detect, step, or square."), ) xstartmin = gds.FloatItem( _("Start baseline min"), default=0.0, help=_("Lower X boundary for the start baseline"), ) xstartmax = gds.FloatItem( _("Start baseline max"), default=0.0, help=_("Upper X boundary for the start baseline"), ) xendmin = gds.FloatItem( _("End baseline min"), default=1.0, help=_("Lower X boundary for the end baseline"), ) xendmax = gds.FloatItem( _("End baseline max"), default=1.0, help=_("Upper X boundary for the end baseline"), ) reference_levels = gds.ChoiceItem( _("Rise/Fall time"), [ ((5, 95), _("5% - 95% (High precision)")), ((10, 90), _("10% - 90% (IEEE standard)")), ((20, 80), _("20% - 80% (Noisy signals)")), ((25, 75), _("25% - 75% (Alternative)")), ], default=(10, 90), help=_( "Reference levels for rise/fall time measurement. " "10%-90% is the IEEE standard for digital signal analysis." ), ) def update_from_obj(self, obj: SignalObj) -> None: """Update parameters from a signal object.""" self.xstartmin, self.xstartmax = pulse.get_start_range(obj.x) self.xendmin, self.xendmax = pulse.get_end_range(obj.x) @computation_function() def extract_pulse_features(obj: SignalObj, p: PulseFeaturesParam) -> TableResult: """Extract pulse features. Args: obj: The signal object from which to extract features. p: The pulse features parameters. Returns: An object containing the pulse features. """ start_ratio, stop_ratio = p.reference_levels def func_extract_pulse_features(xydata: tuple[np.ndarray, np.ndarray]): """Extract pulse features (internal function). Args: xydata: Tuple of (x, y) data arrays Returns: Pulse features dataclass """ x, y = xydata # When processing ROI data, the start/end ranges from parameters might be # outside the ROI's x-range. In that case, use None to auto-detect ranges. start_range = [p.xstartmin, p.xstartmax] end_range = [p.xendmin, p.xendmax] # Check if ranges are within the data's x-range x_min, x_max = x.min(), x.max() if ( start_range[0] < x_min or start_range[1] > x_max or end_range[0] < x_min or end_range[1] > x_max ): # Ranges are outside ROI bounds - use auto-detection start_range = None end_range = None return pulse.extract_pulse_features( x, y, signal_shape=p.signal_shape, start_range=start_range, end_range=end_range, start_ratio=start_ratio / 100.0, stop_ratio=stop_ratio / 100.0, ) builder = TableResultBuilder(_("Pulse features"), kind=TableKind.PULSE_FEATURES) builder.set_global_function(func_extract_pulse_features) builder.hide_columns( ["xstartmin", "xstartmax", "xendmin", "xendmax", "xplateaumin", "xplateaumax"] ) return builder.compute(obj) @computation_function() def sampling_rate_period(obj: SignalObj) -> TableResult: """Compute sampling rate and period using the following functions: - fs: :py:func:`sigima.tools.signal.dynamic.sampling_rate` - T: :py:func:`sigima.tools.signal.dynamic.sampling_period` Args: obj: source signal Returns: Result properties with sampling rate and period """ table = TableResultBuilder(_("Sampling rate and period")) table.add(lambda xy: dynamic.sampling_rate(xy[0]), "fs") table.add(lambda xy: dynamic.sampling_period(xy[0]), "T") return table.compute(obj) @computation_function() def contrast(obj: SignalObj) -> TableResult: """Compute contrast with :py:func:`sigima.tools.signal.misc.contrast`""" table = TableResultBuilder(_("Contrast")) table.add(lambda xy: features.contrast(xy[1]), "contrast") return table.compute(obj) @computation_function() def x_at_minmax(obj: SignalObj) -> TableResult: """ Compute the smallest argument at the minima and the smallest argument at the maxima. Args: obj: The signal object. Returns: An object containing the x-values at the minima and the maxima. """ table = TableResultBuilder(_("X at min/max")) table.add(lambda xy: xy[0][np.argmin(xy[1])], "X@Ymin") table.add(lambda xy: xy[0][np.argmax(xy[1])], "X@Ymax") return table.compute(obj) Sigima-1.1.1/sigima/proc/signal/arithmetic.py000066400000000000000000000410071514013333200211140ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Arithmetic operations on signals ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ """ from __future__ import annotations import warnings from typing import TYPE_CHECKING import numpy as np from sigima.enums import MathOperator, SignalsToImageOrientation from sigima.objects import SignalObj, create_image from sigima.proc.base import ( ArithmeticParam, ConstantParam, SignalsToImageParam, dst_1_to_1, dst_2_to_1, dst_n_to_1, ) from sigima.proc.decorator import computation_function from sigima.proc.signal.base import ( is_uncertainty_data_available, restore_data_outside_roi, ) from sigima.proc.signal.mathops import inverse from sigima.tools.signal import scaling if TYPE_CHECKING: from sigima.objects import ImageObj def __signals_y_to_array(signals: list[SignalObj]) -> np.ndarray: """Create an array from a list of signals, extracting the `y` attribute. Args: signals: List of signal objects. Returns: A NumPy array stacking the `y` attribute from all signals. """ return np.array([sig.y for sig in signals], dtype=signals[0].y.dtype) def __signals_dy_to_array(signals: list[SignalObj]) -> np.ndarray: """Create an array from a list of signals, extracting the `dy` attribute. Args: signals: List of signal objects. Returns: A NumPy array stacking the `dy` attribute from all signals. """ return np.array([sig.dy for sig in signals], dtype=signals[0].dy.dtype) @computation_function() def addition(src_list: list[SignalObj]) -> SignalObj: """Compute the element-wise sum of multiple signals. The first signal in the list defines the "base" signal. All other signals are added element-wise to the base signal. .. note:: If all signals share the same region of interest (ROI), the sum is performed only within the ROI. .. note:: Uncertainties are propagated. .. warning:: It is assumed that all signals have the same size and x-coordinates. Args: src_list: List of source signals. Returns: Signal object representing the sum of the source signals. """ dst = dst_n_to_1(src_list, "Σ") # `dst` data is initialized to `src_list[0]` data. dst.y = np.sum(__signals_y_to_array(src_list), axis=0) if is_uncertainty_data_available(src_list): dst.dy = np.sqrt(np.sum(__signals_dy_to_array(src_list) ** 2, axis=0)) restore_data_outside_roi(dst, src_list[0]) return dst @computation_function() def average(src_list: list[SignalObj]) -> SignalObj: """Compute the element-wise average of multiple signals. The first signal in the list defines the "base" signal. All other signals are averaged element-wise with the base signal. .. note:: If all signals share the same region of interest (ROI), the average is performed only within the ROI. .. note:: Uncertainties are propagated. .. warning:: It is assumed that all signals have the same size and x-coordinates. Args: src_list: List of source signals. Returns: Signal object representing the average of the source signals. """ dst = dst_n_to_1(src_list, "µ") # `dst` data is initialized to `src_list[0]` data. dst.y = np.mean(__signals_y_to_array(src_list), axis=0) if is_uncertainty_data_available(src_list): dy_array = __signals_dy_to_array(src_list) dst.dy = np.sqrt(np.sum(dy_array**2, axis=0)) / len(src_list) restore_data_outside_roi(dst, src_list[0]) return dst @computation_function() def standard_deviation(src_list: list[SignalObj]) -> SignalObj: """Compute the element-wise standard deviation of multiple signals. The first signal in the list defines the "base" signal. All other signals are used to compute the element-wise standard deviation with the base signal. .. note:: If all signals share the same region of interest (ROI), the standard deviation is computed only within the ROI. .. warning:: It is assumed that all signals have the same size and x-coordinates. Args: src_list: List of source signals. Returns: Signal object representing the standard deviation of the source signals. """ dst = dst_n_to_1(src_list, "𝜎") # `dst` data is initialized to `src_list[0]` data dst.y = np.std(__signals_y_to_array(src_list), axis=0, ddof=0) if is_uncertainty_data_available(src_list): dst.dy = dst.y / np.sqrt(2 * (len(src_list) - 1)) restore_data_outside_roi(dst, src_list[0]) return dst @computation_function() def product(src_list: list[SignalObj]) -> SignalObj: """Compute the element-wise product of multiple signals. The first signal in the list defines the "base" signal. All other signals are multiplied element-wise with the base signal. .. note:: If all signals share the same region of interest (ROI), the product is performed only within the ROI. .. note:: Uncertainties are propagated. .. warning:: It is assumed that all signals have the same size and x-coordinates. Args: src_list: List of source signals. Returns: Signal object representing the product of the source signals. """ dst = dst_n_to_1(src_list, "Π") # `dst` data is initialized to `src_list[0]` data. y_array = __signals_y_to_array(src_list) dst.y = np.prod(y_array, axis=0) if is_uncertainty_data_available(src_list): dy_array = __signals_dy_to_array(src_list) with warnings.catch_warnings(): warnings.simplefilter("ignore", category=RuntimeWarning) uncertainty = np.abs(dst.y) * np.sqrt( np.sum((dy_array / y_array) ** 2, axis=0) ) uncertainty[np.isinf(uncertainty)] = np.nan dst.dy = uncertainty restore_data_outside_roi(dst, src_list[0]) return dst @computation_function() def addition_constant(src: SignalObj, p: ConstantParam) -> SignalObj: """Compute the sum of a signal and a constant value. The function adds a constant value to each element of the input signal. .. note:: If the signal has a region of interest (ROI), the addition is performed only within the ROI. .. note:: Uncertainties are propagated. Args: src: Input signal object. p: Constant value. Returns: Result signal object representing the sum of the input signal and the constant. """ # Uncertainty propagation: dst_1_to_1() copies all data including uncertainties. # For addition with constant: σ(y + c) = σ(y), so no modification needed. dst = dst_1_to_1(src, "+", str(p.value)) dst.y += p.value restore_data_outside_roi(dst, src) return dst @computation_function() def difference_constant(src: SignalObj, p: ConstantParam) -> SignalObj: """Compute the difference between a signal and a constant value. The function subtracts a constant value from each element of the input signal. .. note:: If the signal has a region of interest (ROI), the subtraction is performed only within the ROI. .. note:: Uncertainties are propagated. Args: src: Input signal object. p: Constant value. Returns: Result signal object representing the difference between the input signal and the constant. """ # Uncertainty propagation: dst_1_to_1() copies all data including uncertainties. # For subtraction with constant: σ(y - c) = σ(y), so no modification needed. dst = dst_1_to_1(src, "-", str(p.value)) dst.y -= p.value restore_data_outside_roi(dst, src) return dst @computation_function() def product_constant(src: SignalObj, p: ConstantParam) -> SignalObj: """Compute the product of a signal and a constant value. The function multiplies each element of the input signal by a constant value. .. note:: If the signal has a region of interest (ROI), the multiplication is performed only within the ROI. .. note:: Uncertainties are propagated. Args: src: Input signal object. p: Constant value. Returns: Result signal object representing the product of the input signal and the constant. """ assert p.value is not None # Uncertainty propagation: dst_1_to_1() copies all data including uncertainties. # For multiplication with constant: σ(c*y) = |c| * σ(y), so modification needed. dst = dst_1_to_1(src, "×", str(p.value)) dst.y *= p.value if is_uncertainty_data_available(src): dst.dy *= np.abs(p.value) # Modify in-place since dy already copied from src restore_data_outside_roi(dst, src) return dst @computation_function() def division_constant(src: SignalObj, p: ConstantParam) -> SignalObj: """Compute the division of a signal by a constant value. The function divides each element of the input signal by a constant value. .. note:: If the signal has a region of interest (ROI), the division is performed only within the ROI. .. note:: Uncertainties are propagated. Args: src: Input signal object. p: Constant value. Returns: Result signal object representing the division of the input signal by the constant. """ assert p.value is not None # Uncertainty propagation: dst_1_to_1() copies all data including uncertainties. # For division with constant: σ(y/c) = σ(y) / |c|, so modification needed. dst = dst_1_to_1(src, "/", str(p.value)) with warnings.catch_warnings(): warnings.simplefilter("ignore", category=RuntimeWarning) dst.y /= p.value dst.y[np.isinf(dst.y)] = np.nan if is_uncertainty_data_available(src): dst.dy /= np.abs(p.value) # Modify in-place since dy already copied dst.dy[np.isinf(dst.dy)] = np.nan restore_data_outside_roi(dst, src) return dst @computation_function() def arithmetic(src1: SignalObj, src2: SignalObj, p: ArithmeticParam) -> SignalObj: """Perform an arithmetic operation on two signals. The function applies the specified arithmetic operation to each element of the input signals. .. note:: The operation is performed only within the region of interest of `src1`. .. note:: Uncertainties are propagated. .. warning:: It is assumed that both signals have the same size and x-coordinates. Args: src1: First input signal. src2: Second input signal. p: Arithmetic operation parameters. Returns: Result signal object representing the arithmetic operation on the input signals. """ initial_dtype = src1.xydata.dtype title = p.operation.replace("obj1", "{0}").replace("obj2", "{1}") dst = src1.copy(title=title) a = ConstantParam.create(value=p.factor) b = ConstantParam.create(value=p.constant) if p.operator == MathOperator.ADD: dst = addition_constant(product_constant(addition([src1, src2]), a), b) elif p.operator == MathOperator.SUBTRACT: dst = addition_constant(product_constant(difference(src1, src2), a), b) elif p.operator == MathOperator.MULTIPLY: dst = addition_constant(product_constant(product([src1, src2]), a), b) elif p.operator == MathOperator.DIVIDE: dst = addition_constant(product_constant(product([src1, inverse(src2)]), a), b) # Eventually convert to initial data type if p.restore_dtype: dst.xydata = dst.xydata.astype(initial_dtype) restore_data_outside_roi(dst, src1) return dst @computation_function() def difference(src1: SignalObj, src2: SignalObj) -> SignalObj: """Compute the element-wise difference between two signals. The function subtracts each element of the second signal from the corresponding element of the first signal. .. note:: If both signals share the same region of interest (ROI), the difference is performed only within the ROI. .. note:: Uncertainties are propagated. .. warning:: It is assumed that both signals have the same size and x-coordinates. Args: src1: First input signal. src2: Second input signal. Returns: Result signal object representing the difference between the input signals. """ dst = dst_2_to_1(src1, src2, "-") dst.y = src1.y - src2.y if is_uncertainty_data_available([src1, src2]): dy_array = __signals_dy_to_array([src1, src2]) dst.dy = np.sqrt(np.sum(dy_array**2, axis=0)) restore_data_outside_roi(dst, src1) return dst @computation_function() def quadratic_difference(src1: SignalObj, src2: SignalObj) -> SignalObj: """Compute the normalized difference between two signals. The function computes the element-wise difference between the two signals and divides the result by sqrt(2.0). .. note:: If both signals share the same region of interest (ROI), the operation is performed only within the ROI. .. note:: Uncertainties are propagated. For two input signals with identical standard deviations, the standard deviation of the output signal equals the standard deviation of each of the input signals. .. warning:: It is assumed that both signals have the same size and x-coordinates. Args: src1: First input signal. src2: Second input signal. Returns: Result signal object representing the quadratic difference between the input signals. """ norm = ConstantParam.create(value=1.0 / np.sqrt(2.0)) return product_constant(difference(src1, src2), norm) @computation_function() def division(src1: SignalObj, src2: SignalObj) -> SignalObj: """Compute the element-wise division between two signals. The function divides each element of the first signal by the corresponding element of the second signal. .. note:: If both signals share the same region of interest (ROI), the division is performed only within the ROI. .. note:: Uncertainties are propagated. .. warning:: It is assumed that both signals have the same size and x-coordinates. Args: src1: First input signal. src2: Second input signal. Returns: Result signal object representing the division of the input signals. """ dst = product([src1, inverse(src2)]) return dst @computation_function() def signals_to_image(src_list: list[SignalObj], p: SignalsToImageParam) -> ImageObj: """Combine multiple signals into an image. The function takes a list of signals and combines them into a 2D image, arranging them either as rows or columns based on the specified orientation. Optionally, each signal can be normalized before combining. .. note:: All signals must have the same size (number of data points). .. note:: If normalization is enabled, each signal is normalized independently using the specified normalization method before being added to the image. Args: src_list: List of source signals to combine. p: Parameters specifying orientation and normalization options. Returns: Image object representing the combined signals. Raises: ValueError: If the signal list is empty or signals have different sizes. """ if not src_list: raise ValueError("The signal list is empty.") # Check that all signals have the same size sizes = [len(sig.y) for sig in src_list] if len(set(sizes)) > 1: raise ValueError( f"All signals must have the same size. Found sizes: {set(sizes)}" ) # Prepare data array y_array = __signals_y_to_array(src_list) # Normalize if requested if p.normalize: for i in range(len(src_list)): y_array[i] = scaling.normalize(y_array[i], p.normalize_method) # Arrange as rows or columns if p.orientation == SignalsToImageOrientation.COLUMNS: data = y_array.T else: # ROWS data = y_array # Create the result image suffix_parts = [f"n={len(src_list)}", f"orientation={p.orientation}"] if p.normalize: suffix_parts.append(f"norm={p.normalize_method}") suffix = ", ".join(suffix_parts) title = f"combined_signals|{suffix}" dst = create_image(title, data) if p.orientation == SignalsToImageOrientation.ROWS: dst.xlabel = src_list[0].ylabel else: dst.ylabel = src_list[0].ylabel dst.zlabel = src_list[0].ylabel dst.zunit = src_list[0].yunit return dst Sigima-1.1.1/sigima/proc/signal/base.py000066400000000000000000000155351514013333200177040ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Base signal processing functions and utilities ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ """ from __future__ import annotations from collections.abc import Callable from typing import Any import numpy as np from sigima.objects import NO_ROI, GeometryResult, KindShape, SignalObj from sigima.proc.base import dst_1_to_1 def restore_data_outside_roi(dst: SignalObj, src: SignalObj) -> None: """Restore data outside the Region Of Interest (ROI) of the input signal after a computation, only if the input signal has a ROI, and if the output signal has the same ROI as the input signal, and if the data types are the same, and if the shapes are the same. Otherwise, do nothing. Args: dst: destination signal object src: source signal object """ if src.maskdata is not None and dst.maskdata is not None: if ( np.array_equal(src.maskdata, dst.maskdata) and dst.xydata.dtype == src.xydata.dtype and dst.xydata.shape == src.xydata.shape ): dst.xydata[src.maskdata] = src.xydata[src.maskdata] def is_uncertainty_data_available(signals: SignalObj | list[SignalObj]) -> bool: """Check if all signals have uncertainty data. This functions is used to determine whether enough information is available to propagate uncertainty. Args: signals: Signal object or list of signal objects. Returns: True if all signals have uncertainty data, False otherwise. """ if isinstance(signals, SignalObj): signals = [signals] return all(sig.dy is not None for sig in signals) class Wrap1to1Func: """Wrap a 1 array → 1 array function (the simple case of y1 = f(y0)) to produce a 1 signal → 1 signal function, which can be used as a Sigima computation function and inside DataLab's infrastructure to perform computations with the Signal Processor object. This wrapping mechanism using a class is necessary for the resulted function to be pickable by the ``multiprocessing`` module. The instance of this wrapper is callable and returns a :class:`sigima.objects.SignalObj` object. Example: >>> import numpy as np >>> from sigima.proc.signal import Wrap1to1Func >>> import sigima.objects >>> def square(y): ... return y**2 >>> compute_square = Wrap1to1Func(square) >>> x = np.linspace(0, 10, 100) >>> y = np.sin(x) >>> sig0 = sigima.objects.create_signal("Example", x, y) >>> sig1 = compute_square(sig0) Args: func: 1 array → 1 array function *args: Additional positional arguments to pass to the function **kwargs: Additional keyword arguments to pass to the function .. note:: If `func_name` is provided in the keyword arguments, it will be used as the function name instead of the default name derived from the function itself. .. note:: This wrapper is suitable for functions that don't require custom uncertainty propagation. For mathematical functions with specific uncertainty formulas (sqrt, log10, exp, etc.), implement uncertainty propagation directly in the computation function. """ def __init__(self, func: Callable, *args: Any, **kwargs: Any) -> None: self.func = func self.args = args self.kwargs = kwargs self.__name__ = self.kwargs.pop("func_name", func.__name__) self.__doc__ = func.__doc__ self.__call__.__func__.__doc__ = self.func.__doc__ def __call__(self, src: SignalObj) -> SignalObj: """Compute the function on the input signal and return the result signal Args: src: input signal object Returns: Result signal object """ suffix = ", ".join( [str(arg) for arg in self.args] + [f"{k}={v}" for k, v in self.kwargs.items() if v is not None] ) dst = dst_1_to_1(src, self.__name__, suffix) x, y = src.get_data() # Apply function and propagate uncertainty unchanged dst.set_xydata(x, self.func(y, *self.args, **self.kwargs), src.dx, src.dy) restore_data_outside_roi(dst, src) return dst def compute_geometry_from_obj( title: str, shape: str | KindShape, obj: SignalObj, func: Callable, *args: Any, ) -> GeometryResult | None: """Calculate result geometry by executing a computation function on a signal object. Args: title: Result title shape: Result shape kind (e.g., "segment", "point", KindShape.MARKER) obj: Input signal object func: Computation function that takes (x, y, ``*args``) and returns coordinates *args: Additional computation function arguments Returns: Result geometry object or None if no result is found .. note:: The computation function must take x and y arrays as the first two arguments, followed by any additional arguments, and return a NumPy array containing coordinate pairs in the form ``[[x0, y0], [x1, y1], ...]``. """ rows: list[np.ndarray] = [] roi_idx: list[int] = [] for i_roi in obj.iterate_roi_indices(): x, y = obj.get_data(i_roi) if args: results: np.ndarray = func(x, y, *args) else: results: np.ndarray = func(x, y) if results is None: continue results = np.array(results, dtype=float) if results.size == 0: continue # Ensure results are in the correct 2D format if results.ndim == 1: # For segment shapes, expect 4 coordinates: [x0, y0, x1, y1] if shape in ("segment", KindShape.SEGMENT) and len(results) == 4: results = results.reshape(1, 4) elif len(results) % 2 == 0: # Reshape flat coordinate array to pairs for points/markers results = results.reshape(-1, 2) else: continue # Skip malformed results elif results.ndim != 2 or results.shape[1] < 2: continue # Skip malformed results rows.append(results) roi_idx.extend([NO_ROI if i_roi is None else int(i_roi)] * results.shape[0]) if not rows: return None coords = np.vstack(rows) # Convert shape to KindShape enum if isinstance(shape, KindShape): shape_kind = shape elif shape == "segment": shape_kind = KindShape.SEGMENT elif shape == "point": shape_kind = KindShape.POINT elif shape == "marker": shape_kind = KindShape.MARKER else: shape_kind = KindShape.POINT # Default fallback return GeometryResult( title=title, kind=shape_kind, coords=coords, roi_indices=np.array(roi_idx, dtype=int), ) Sigima-1.1.1/sigima/proc/signal/extraction.py000066400000000000000000000036111514013333200211420ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Signal extraction and ROI operations ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ """ from __future__ import annotations import numpy as np from sigima.objects import ROI1DParam, SignalObj from sigima.proc.base import dst_1_to_1 from sigima.proc.decorator import computation_function @computation_function() def extract_rois(src: SignalObj, params: list[ROI1DParam]) -> SignalObj: """Extract multiple regions of interest from data Args: src: source signal params: list of ROI parameters Returns: Signal with multiple regions of interest """ suffix = None if len(params) == 1: p: ROI1DParam = params[0] suffix = f"{p.xmin:.3g}≤x≤{p.xmax:.3g}" dst = dst_1_to_1(src, "extract_rois", suffix) x, y = src.get_data() xout, yout = np.ones_like(x) * np.nan, np.ones_like(y) * np.nan for p in params: idx1, idx2 = np.searchsorted(x, p.xmin), np.searchsorted(x, p.xmax) slice0 = slice(idx1, idx2) xout[slice0], yout[slice0] = x[slice0], y[slice0] nans = np.isnan(xout) | np.isnan(yout) # TODO: Handle uncertainty data dst.set_xydata(xout[~nans], yout[~nans]) # Remove ROI from destination signal: the extracted data no longer needs ROI dst.roi = None return dst @computation_function() def extract_roi(src: SignalObj, p: ROI1DParam) -> SignalObj: """Extract single region of interest from data Args: src: source signal p: ROI parameters Returns: Signal with single region of interest """ dst = dst_1_to_1(src, "extract_roi", f"{p.xmin:.3g}≤x≤{p.xmax:.3g}") x, y = p.get_data(src).copy() # TODO: Handle uncertainty data dst.set_xydata(x, y) # Remove ROI from destination signal: the extracted data no longer needs ROI dst.roi = None return dst Sigima-1.1.1/sigima/proc/signal/features.py000066400000000000000000000237371514013333200206130ustar00rootroot00000000000000# -*- coding: utf-8 -*- # # Licensed under the terms of the BSD 3-Clause # (see sigima/LICENSE for details) """ Feature extraction and analysis functions ========================================= This module provides feature extraction and analysis functions for signal objects: - Peak detection - Full Width at Half Maximum (FWHM) and related measurements - Statistical analysis - Bandwidth calculations - Dynamic parameters (ENOB, SNR, SINAD, THD, SFDR) .. note:: Most operations use functions from :mod:`sigima.tools.signal` for actual computations. """ from __future__ import annotations import guidata.dataset as gds import numpy as np import scipy.integrate as spt from sigima.config import _ from sigima.enums import PowerUnit from sigima.objects import ( GeometryResult, KindShape, SignalObj, TableKind, TableResult, TableResultBuilder, ) from sigima.proc.base import dst_1_to_1 from sigima.proc.decorator import computation_function from sigima.proc.signal.base import compute_geometry_from_obj from sigima.tools.signal import dynamic, features, peakdetection, pulse class PeakDetectionParam(gds.DataSet, title=_("Peak detection")): """Peak detection parameters""" threshold = gds.FloatItem(_("Threshold"), default=0.1, min=0.0) min_dist = gds.IntItem(_("Minimum distance"), default=1, min=1) @computation_function() def peak_detection(src: SignalObj, p: PeakDetectionParam) -> SignalObj: """Peak detection with :py:func:`sigima.tools.signal.peakdetection.peak_indices` Args: src: source signal p: parameters Returns: Result signal object """ dst = dst_1_to_1( src, "peak_detection", f"threshold={p.threshold}%, min_dist={p.min_dist}pts" ) x, y = src.get_data() indices = peakdetection.peak_indices( y, thres=p.threshold * 0.01, min_dist=p.min_dist ) dst.set_xydata(x[indices], y[indices]) dst.set_metadata_option("curvestyle", "Sticks") return dst class FWHMParam( gds.DataSet, title=_("FWHM"), comment=_( "Methods and trade-offs:

" "• Zero-crossing: Fast, sensitive to noise
" "• Gaussian fit: Good for symmetric peaks, assumes Gaussian shape
" "• Lorentzian fit: Suitable for peaks with long tails, dominated by " "collisional or lifetime broadening
" "• Voigt fit: Most accurate for spectroscopic data, or laser lines " "broadened by both Doppler and collisional effects
" ), ): """FWHM parameters""" methods = ( ("zero-crossing", _("Zero-crossing")), ("gauss", _("Gaussian fit")), ("lorentz", _("Lorentzian fit")), ("voigt", _("Voigt fit")), ) method = gds.ChoiceItem(_("Method"), methods, default="zero-crossing") xmin = gds.FloatItem( "XMIN", default=None, check=False, help=_("Lower X boundary (empty for no limit, i.e. start of the signal)"), ) xmax = gds.FloatItem( "XMAX", default=None, check=False, help=_("Upper X boundary (empty for no limit, i.e. end of the signal)"), ).set_prop("display", col=1) @computation_function() def fwhm(obj: SignalObj, param: FWHMParam) -> GeometryResult | None: """Compute FWHM with :py:func:`sigima.tools.signal.pulse.fwhm` Args: obj: source signal param: parameters Returns: Segment coordinates """ return compute_geometry_from_obj( "fwhm", KindShape.SEGMENT, obj, pulse.fwhm, param.method, param.xmin, param.xmax, ) @computation_function() def fw1e2(obj: SignalObj) -> GeometryResult | None: """Compute FW at 1/e² with :py:func:`sigima.tools.signal.pulse.fw1e2` Args: obj: source signal Returns: Segment coordinates """ return compute_geometry_from_obj("fw1e2", KindShape.SEGMENT, obj, pulse.fw1e2) # Note: we do not specify title of the dataset here because it's a generic parameter # used in multiple functions (this avoids that the same title is displayed in GUI # for different functions) class OrdinateParam(gds.DataSet): """Ordinate parameter.""" y = gds.FloatItem("y", default=0.0) @computation_function() def full_width_at_y(obj: SignalObj, p: OrdinateParam) -> GeometryResult | None: """ Compute full width at a given y value for a signal object. Args: obj: The signal object containing x and y data. p: The ordinate parameter dataset Returns: Segment coordinates """ return compute_geometry_from_obj( "∆X", KindShape.SEGMENT, obj, pulse.full_width_at_y, p.y ) @computation_function() def x_at_y(obj: SignalObj, p: OrdinateParam) -> GeometryResult | None: """ Compute the smallest x-value at a given y-value for a signal object. Args: obj: The signal object containing x and y data. p: The parameter dataset for finding the abscissa. Returns: A GeometryResult with a cross marker at the (x, y) position. """ def compute_x_at_y(x: np.ndarray, y: np.ndarray) -> np.ndarray: """Helper function to compute x at y value.""" x_values = features.find_x_values_at_y(x, y, p.y) x_result = x_values[0] if len(x_values) > 0 else np.nan return np.array([x_result, p.y]) return compute_geometry_from_obj( f"x|y={p.y}", KindShape.MARKER, obj, compute_x_at_y, ) # Note: we do not specify title of the dataset here because it's a generic parameter # used in multiple functions (this avoids that the same title is displayed in GUI # for different functions) class AbscissaParam(gds.DataSet): """Abscissa parameter.""" x = gds.FloatItem("x", default=0.0) @computation_function() def y_at_x(obj: SignalObj, p: AbscissaParam) -> GeometryResult | None: """ Compute the smallest y-value at a given x-value for a signal object. Args: obj: The signal object containing x and y data. p: The parameter dataset for finding the ordinate. Returns: A GeometryResult with a cross marker at the (x, y) position. """ def compute_y_at_x(x: np.ndarray, y: np.ndarray) -> np.ndarray: """Helper function to compute y at x value.""" y_result = features.find_y_at_x_value(x, y, p.x) return np.array([p.x, y_result]) return compute_geometry_from_obj( f"y|x={p.x}", KindShape.MARKER, obj, compute_y_at_x, ) @computation_function() def stats(obj: SignalObj) -> TableResult: """Compute statistics on a signal Args: obj: source signal Returns: Result properties object """ table = TableResultBuilder(_("Signal statistics"), kind=TableKind.STATISTICS) table.add(lambda xy: np.nanmin(xy[1]), "min") table.add(lambda xy: np.nanmax(xy[1]), "max") table.add(lambda xy: np.nanmean(xy[1]), "mean") table.add(lambda xy: np.nanmedian(xy[1]), "median") table.add(lambda xy: np.nanstd(xy[1]), "std") table.add(lambda xy: np.nanmean(xy[1]) / np.nanstd(xy[1]), "snr") table.add(lambda xy: np.nanmax(xy[1]) - np.nanmin(xy[1]), "ptp") table.add(lambda xy: np.nansum(xy[1]), "sum") table.add(lambda xy: spt.trapezoid(xy[1], xy[0]), "trapz") return table.compute(obj) @computation_function() def bandwidth_3db(obj: SignalObj) -> GeometryResult | None: """Compute bandwidth at -3 dB with :py:func:`sigima.tools.signal.misc.bandwidth` .. note:: The bandwidth is defined as the range of frequencies over which the signal maintains a certain level relative to its peak. .. warning:: The signal is assumed to be smooth enough for the bandwidth calculation to be meaningful. If the signal contains excessive noise, multiple peaks, or is not sufficiently continuous, the computed bandwidth may not accurately represent the true -3dB range. It is recommended to preprocess the signal to ensure reliable results. Args: obj: Source signal. Returns: Result shape with bandwidth. """ return compute_geometry_from_obj( "bandwidth", KindShape.SEGMENT, obj, features.find_bandwidth_coordinates, -3.0 ) class DynamicParam(gds.DataSet, title=_("Dynamic parameters")): """Parameters for dynamic range computation (ENOB, SNR, SINAD, THD, SFDR)""" full_scale = gds.FloatItem(_("Full scale"), default=0.16, min=0.0, unit="V") unit = gds.ChoiceItem( _("Unit"), [(PowerUnit.DBC, "dBc"), (PowerUnit.DBFS, "dBFS")], default=PowerUnit.DBC, help=_("Unit for SINAD"), ) nb_harm = gds.IntItem( _("Number of harmonics"), default=5, min=1, help=_("Number of harmonics to consider for THD"), ) @computation_function() def dynamic_parameters(src: SignalObj, p: DynamicParam) -> TableResult: """Compute Dynamic parameters using the following functions: - Freq: :py:func:`sigima.tools.signal.dynamic.sinus_frequency` - ENOB: :py:func:`sigima.tools.signal.dynamic.enob` - SNR: :py:func:`sigima.tools.signal.dynamic.snr` - SINAD: :py:func:`sigima.tools.signal.dynamic.sinad` - THD: :py:func:`sigima.tools.signal.dynamic.thd` - SFDR: :py:func:`sigima.tools.signal.dynamic.sfdr` Args: src: source signal p: parameters Returns: Result properties with ENOB, SNR, SINAD, THD, SFDR """ unit: PowerUnit = p.unit table = TableResultBuilder(_("Dynamic parameters")) table.add(lambda xy: dynamic.sinus_frequency(xy[0], xy[1]), "freq") table.add(lambda xy: dynamic.enob(xy[0], xy[1], p.full_scale), "enob") table.add(lambda xy: dynamic.snr(xy[0], xy[1], unit), "snr") table.add(lambda xy: dynamic.sinad(xy[0], xy[1], unit), "sinad") table.add( lambda xy: dynamic.thd(xy[0], xy[1], p.full_scale, unit, p.nb_harm), "thd" ) table.add(lambda xy: dynamic.sfdr(xy[0], xy[1], p.full_scale, unit), "sfdr") return table.compute(src) Sigima-1.1.1/sigima/proc/signal/filtering.py000066400000000000000000000344701514013333200207540ustar00rootroot00000000000000# -*- coding: utf-8 -*- # # Licensed under the terms of the BSD 3-Clause # (see sigima/LICENSE for details) """ Filtering processing functions for signal objects ================================================= This module provides filtering operations for signal objects: - Gaussian filter - Moving average and median filters - Wiener filter - Frequency filters (low-pass, high-pass, band-pass, band-stop) - Noise addition functions .. note:: Uses zero-phase filtering when possible for better phase response. """ from __future__ import annotations import warnings from typing import Callable import guidata.dataset as gds import numpy as np import scipy.ndimage as spi import scipy.signal as sps from sigima.config import _ from sigima.enums import FilterType, FrequencyFilterMethod, PadLocation1D from sigima.objects import ( NormalDistribution1DParam, PoissonDistribution1DParam, SignalObj, UniformDistribution1DParam, create_signal_from_param, ) from sigima.objects.base import ( NormalDistributionParam, PoissonDistributionParam, UniformDistributionParam, ) from sigima.proc.base import GaussianParam, MovingAverageParam, MovingMedianParam from sigima.proc.decorator import computation_function from sigima.proc.signal.arithmetic import addition from sigima.proc.signal.base import Wrap1to1Func, dst_1_to_1, restore_data_outside_roi from sigima.proc.signal.fourier import ZeroPadding1DParam, zero_padding from sigima.tools.signal import fourier @computation_function() def gaussian_filter(src: SignalObj, p: GaussianParam) -> SignalObj: """Compute gaussian filter with :py:func:`scipy.ndimage.gaussian_filter` Args: src: source signal p: parameters Returns: Result signal object """ return Wrap1to1Func(spi.gaussian_filter, sigma=p.sigma)(src) @computation_function() def moving_average(src: SignalObj, p: MovingAverageParam) -> SignalObj: """Compute moving average with :py:func:`scipy.ndimage.uniform_filter` Args: src: source signal p: parameters Returns: Result signal object """ return Wrap1to1Func( spi.uniform_filter, size=p.n, mode=p.mode, func_name="moving_average" )(src) @computation_function() def moving_median(src: SignalObj, p: MovingMedianParam) -> SignalObj: """Compute moving median with :py:func:`scipy.ndimage.median_filter` Args: src: source signal p: parameters Returns: Result signal object """ return Wrap1to1Func( spi.median_filter, size=p.n, mode=p.mode, func_name="moving_median" )(src) @computation_function() def wiener(src: SignalObj) -> SignalObj: """Compute Wiener filter with :py:func:`scipy.signal.wiener` Args: src: source signal Returns: Result signal object """ return Wrap1to1Func(sps.wiener)(src) def get_nyquist_frequency(obj: SignalObj) -> float: """Return the Nyquist frequency of a signal object Args: obj: signal object Returns: Nyquist frequency """ fs = float(obj.x.size - 1) / (obj.x[-1] - obj.x[0]) return fs / 2.0 class BaseHighLowBandParam(gds.DataSet, title=_("Filter")): """Base class for high-pass, low-pass, band-pass and band-stop filters""" TYPE = FilterType.LOWPASS _type_prop = gds.GetAttrProp("TYPE") # Must be overwriten by the child class _method_prop = gds.GetAttrProp("method") method = gds.ChoiceItem( _("Filter method"), [ (FrequencyFilterMethod.BUTTERWORTH, "Butterworth"), (FrequencyFilterMethod.BESSEL, "Bessel"), (FrequencyFilterMethod.CHEBYSHEV1, "Chebyshev I"), (FrequencyFilterMethod.CHEBYSHEV2, "Chebyshev II"), (FrequencyFilterMethod.ELLIPTIC, "Elliptic"), (FrequencyFilterMethod.BRICKWALL, "Brickwall"), ], ).set_prop("display", store=_method_prop) def get_filter_func(self) -> Callable: """Get the scipy filter function corresponding to the method.""" filter_funcs = { FrequencyFilterMethod.BESSEL: sps.bessel, FrequencyFilterMethod.BUTTERWORTH: sps.butter, FrequencyFilterMethod.CHEBYSHEV1: sps.cheby1, FrequencyFilterMethod.CHEBYSHEV2: sps.cheby2, FrequencyFilterMethod.ELLIPTIC: sps.ellip, } return filter_funcs.get(self.method) order = gds.IntItem(_("Filter order"), default=3, min=1).set_prop( "display", active=gds.FuncProp( _method_prop, lambda x: x != FrequencyFilterMethod.BRICKWALL ), ) cut0 = gds.FloatItem( _("Low cutoff frequency"), min=0.0, nonzero=True, unit="Hz", allow_none=True ) cut1 = gds.FloatItem( _("High cutoff frequency"), min=0.0, nonzero=True, unit="Hz", allow_none=True ).set_prop( "display", hide=gds.FuncProp( _type_prop, lambda x: x in (FilterType.LOWPASS, FilterType.HIGHPASS) ), ) rp = gds.FloatItem( _("Passband ripple"), min=0.0, default=1.0, nonzero=True, unit="dB" ).set_prop( "display", active=gds.FuncProp( _method_prop, lambda x: x in (FrequencyFilterMethod.CHEBYSHEV1, FrequencyFilterMethod.ELLIPTIC), ), ) rs = gds.FloatItem( _("Stopband attenuation"), min=0.0, default=60.0, nonzero=True, unit="dB" ).set_prop( "display", active=gds.FuncProp( _method_prop, lambda x: x in (FrequencyFilterMethod.CHEBYSHEV2, FrequencyFilterMethod.ELLIPTIC), ), ) _zp_prop = gds.GetAttrProp("zero_padding") zero_padding = gds.BoolItem( _("Zero padding"), default=True, ).set_prop( "display", active=gds.FuncProp( _method_prop, lambda x: x == FrequencyFilterMethod.BRICKWALL ), store=_zp_prop, ) nfft = gds.IntItem( _("Minimum FFT points number"), default=0, ).set_prop( "display", active=gds.FuncPropMulti( [_method_prop, _zp_prop], lambda x, y: x == FrequencyFilterMethod.BRICKWALL and y, ), ) def update_from_obj(self, obj: SignalObj) -> None: """Update the filter parameters from a signal object Args: obj: signal object """ f_nyquist = get_nyquist_frequency(obj) if self.cut0 is None: if self.TYPE == FilterType.LOWPASS: self.cut0 = 0.1 * f_nyquist elif self.TYPE == FilterType.HIGHPASS: self.cut0 = 0.9 * f_nyquist elif self.TYPE == FilterType.BANDPASS: self.cut0 = 0.1 * f_nyquist self.cut1 = 0.9 * f_nyquist elif self.TYPE == FilterType.BANDSTOP: self.cut0 = 0.4 * f_nyquist self.cut1 = 0.6 * f_nyquist def get_filter_params(self, obj: SignalObj) -> tuple[float | str, float | str]: """Return the filter parameters (a and b) as a tuple. These parameters are used in the scipy.signal filter functions (eg. `scipy.signal.filtfilt`). Args: obj: signal object Returns: tuple: filter parameters """ f_nyquist = get_nyquist_frequency(obj) args: list[float | str | tuple[float, ...]] = [self.order] # type: ignore if self.method == FrequencyFilterMethod.CHEBYSHEV1: args += [self.rp] elif self.method == FrequencyFilterMethod.CHEBYSHEV2: args += [self.rs] elif self.method == FrequencyFilterMethod.ELLIPTIC: args += [self.rp, self.rs] if self.TYPE in (FilterType.HIGHPASS, FilterType.LOWPASS): args += [self.cut0 / f_nyquist] else: args += [[self.cut0 / f_nyquist, self.cut1 / f_nyquist]] args += [self.TYPE.value] return self.get_filter_func()(*args) class LowPassFilterParam(BaseHighLowBandParam): """Low-pass filter parameters""" TYPE = FilterType.LOWPASS # Redefine cut0 just to change its label (instead of "Low cutoff frequency") cut0 = gds.FloatItem( _("Cutoff frequency"), min=0, nonzero=True, unit="Hz", allow_none=True ) class HighPassFilterParam(BaseHighLowBandParam): """High-pass filter parameters""" TYPE = FilterType.HIGHPASS # Redefine cut0 just to change its label (instead of "High cutoff frequency") cut0 = gds.FloatItem( _("Cutoff frequency"), min=0, nonzero=True, unit="Hz", allow_none=True ) class BandPassFilterParam(BaseHighLowBandParam): """Band-pass filter parameters""" TYPE = FilterType.BANDPASS class BandStopFilterParam(BaseHighLowBandParam): """Band-stop filter parameters""" TYPE = FilterType.BANDSTOP def frequency_filter(src: SignalObj, p: BaseHighLowBandParam) -> SignalObj: """Compute frequency filter (low-pass, high-pass, band-pass, band-stop), with :py:func:`scipy.signal.filtfilt` Args: src: source signal p: parameters Returns: Result signal object .. note:: Uses zero-phase filtering (`filtfilt`) when possible for better phase response. If numerical instability occurs (e.g., singular matrix errors), automatically falls back to forward filtering (`lfilter`) with a warning. This ensures cross-platform compatibility while maintaining optimal filtering when possible. """ name = f"{p.TYPE.value}" suffix = "" if p.method != FrequencyFilterMethod.BRICKWALL: suffix = f"order={p.order:d}, " if p.TYPE in (FilterType.LOWPASS, FilterType.HIGHPASS): suffix += f"cutoff={p.cut0:.2f}" else: suffix += f"cutoff={p.cut0:.2f}:{p.cut1:.2f}" dst = dst_1_to_1(src, name, suffix) if p.method == FrequencyFilterMethod.BRICKWALL: original_size = src.y.size src_padded = src.copy() if p.zero_padding and p.nfft is not None: size_padded = ZeroPadding1DParam.next_power_of_two(max(p.nfft, src.y.size)) n_to_add = size_padded - src.y.size if n_to_add > 0: src_padded = zero_padding( src_padded, ZeroPadding1DParam.create( location=PadLocation1D.APPEND, strategy="custom", n=n_to_add, ), ) x_padded, y_padded = src_padded.get_data() x, y = fourier.brickwall_filter( x_padded, y_padded, p.TYPE.value, p.cut0, p.cut1 ) # Trim back to original size if padding was applied x = x[:original_size] y = y[:original_size] dst.set_xydata(x, y) else: b, a = p.get_filter_params(dst) try: # Prefer zero-phase filtering dst.y = sps.filtfilt(b, a, dst.y) except np.linalg.LinAlgError: # Fallback to forward filtering if filtfilt fails due to numerical issues warnings.warn( "Zero-phase filtering failed due to numerical instability. " "Using forward filtering instead.", UserWarning, stacklevel=2, ) dst.y = sps.lfilter(b, a, dst.y) restore_data_outside_roi(dst, src) return dst @computation_function() def lowpass(src: SignalObj, p: LowPassFilterParam) -> SignalObj: """Compute low-pass filter with :py:func:`scipy.signal.filtfilt` Args: src: source signal p: parameters Returns: Result signal object """ return frequency_filter(src, p) @computation_function() def highpass(src: SignalObj, p: HighPassFilterParam) -> SignalObj: """Compute high-pass filter with :py:func:`scipy.signal.filtfilt` Args: src: source signal p: parameters Returns: Result signal object """ return frequency_filter(src, p) @computation_function() def bandpass(src: SignalObj, p: BandPassFilterParam) -> SignalObj: """Compute band-pass filter with :py:func:`scipy.signal.filtfilt` Args: src: source signal p: parameters Returns: Result signal object """ return frequency_filter(src, p) @computation_function() def bandstop(src: SignalObj, p: BandStopFilterParam) -> SignalObj: """Compute band-stop filter with :py:func:`scipy.signal.filtfilt` Args: src: source signal p: parameters Returns: Result signal object """ return frequency_filter(src, p) # Noise addition functions @computation_function() def add_gaussian_noise(src: SignalObj, p: NormalDistributionParam) -> SignalObj: """Add normal noise to the input signal. Args: src: Source signal. p: Parameters. Returns: Result signal object. """ param = NormalDistribution1DParam() # Do not confuse with NormalDistributionParam gds.update_dataset(param, p) param.xmin = src.x[0] param.xmax = src.x[-1] param.size = src.x.size noise = create_signal_from_param(param) dst = dst_1_to_1(src, "add_gaussian_noise", f"µ={p.mu}, σ={p.sigma}") dst.xydata = addition([src, noise]).xydata return dst @computation_function() def add_poisson_noise(src: SignalObj, p: PoissonDistributionParam) -> SignalObj: """Add Poisson noise to the input signal. Args: src: Source signal. p: Parameters. Returns: Result signal object. """ param = PoissonDistribution1DParam() # Do not confuse with PoissonDistributionParam gds.update_dataset(param, p) param.xmin = src.x[0] param.xmax = src.x[-1] param.size = src.x.size noise = create_signal_from_param(param) dst = dst_1_to_1(src, "add_poisson_noise", f"λ={p.lam}") dst.xydata = addition([src, noise]).xydata return dst @computation_function() def add_uniform_noise(src: SignalObj, p: UniformDistributionParam) -> SignalObj: """Add uniform noise to the input signal. Args: src: Source signal. p: Parameters. Returns: Result signal object. """ param = UniformDistribution1DParam() # Do not confuse with UniformDistributionParam gds.update_dataset(param, p) param.xmin = src.x[0] param.xmax = src.x[-1] param.size = src.x.size noise = create_signal_from_param(param) dst = dst_1_to_1(src, "add_uniform_noise", f"low={p.vmin}, high={p.vmax}") dst.xydata = addition([src, noise]).xydata return dst Sigima-1.1.1/sigima/proc/signal/fitting.py000066400000000000000000000152701514013333200204320ustar00rootroot00000000000000# -*- coding: utf-8 -*- # # Licensed under the terms of the BSD 3-Clause # (see sigima/LICENSE for details) """ Curve fitting operations ======================== This module provides curve fitting operations for signal objects: - Linear and polynomial fits - Gaussian, Lorentzian, and Voigt fits - Exponential and CDF fits .. note:: Most operations use functions from :mod:`sigima.tools.signal.fitting` for actual computations. """ from __future__ import annotations from typing import Callable import guidata.dataset as gds import numpy as np from sigima.config import _ from sigima.objects import SignalObj from sigima.proc.base import dst_2_to_1 from sigima.proc.decorator import computation_function from sigima.tools.signal import fitting from .base import dst_1_to_1 def __generic_fit( src: SignalObj, fitfunc: Callable[[np.ndarray, np.ndarray], tuple[np.ndarray, dict[str, float]]], ) -> SignalObj: """Generic fitting function. Args: src: source signal fitfunc: fitting function Returns: Fitting result signal object """ dst = dst_1_to_1(src, fitfunc.__name__) # Fit only on ROI if available x_roi = src.x[~src.get_masked_view().mask] y_roi = src.get_masked_view().compressed() _fitted_y_roi, fit_params = fitfunc(x_roi, y_roi) # Evaluate fit on full x range fitted_y = fitting.evaluate_fit(src.x, **fit_params) dst.set_xydata(src.x, fitted_y) # Store fit parameters in metadata dst.metadata["fit_params"] = fit_params return dst @computation_function() def linear_fit(src: SignalObj) -> SignalObj: """Compute linear fit with :py:func:`numpy.polyfit` Args: src: source signal Returns: Result signal object """ return __generic_fit(src, fitting.linear_fit) class PolynomialFitParam(gds.DataSet, title=_("Polynomial fit")): """Polynomial fitting parameters""" degree = gds.IntItem(_("Degree"), 3, min=1, max=10, slider=True) @computation_function() def polynomial_fit(src: SignalObj, p: PolynomialFitParam) -> SignalObj: """Compute polynomial fit with :py:func:`numpy.polyfit` Args: src: source signal p: polynomial fitting parameters Returns: Result signal object """ # Note: no need to check degree here as gds.IntItem already enforces min=1 return __generic_fit(src, lambda x, y: fitting.polynomial_fit(x, y, p.degree)) @computation_function() def gaussian_fit(src: SignalObj) -> SignalObj: """Compute Gaussian fit with :py:func:`scipy.optimize.curve_fit` Args: src: source signal Returns: Result signal object """ return __generic_fit(src, fitting.gaussian_fit) @computation_function() def lorentzian_fit(src: SignalObj) -> SignalObj: """Compute Lorentzian fit with :py:func:`scipy.optimize.curve_fit` Args: src: source signal Returns: Result signal object """ return __generic_fit(src, fitting.lorentzian_fit) @computation_function() def voigt_fit(src: SignalObj) -> SignalObj: """Compute Voigt fit with :py:func:`scipy.optimize.curve_fit` Args: src: source signal Returns: Result signal object """ return __generic_fit(src, fitting.voigt_fit) @computation_function() def exponential_fit(src: SignalObj) -> SignalObj: """Compute exponential fit with :py:func:`scipy.optimize.curve_fit` Args: src: source signal Returns: Result signal object """ return __generic_fit(src, fitting.exponential_fit) @computation_function() def cdf_fit(src: SignalObj) -> SignalObj: """Compute CDF fit with :py:func:`scipy.optimize.curve_fit` Args: src: source signal Returns: Result signal object """ return __generic_fit(src, fitting.cdf_fit) @computation_function() def planckian_fit(src: SignalObj) -> SignalObj: """Compute Planckian fit with :py:func:`scipy.optimize.curve_fit` Args: src: source signal Returns: Result signal object """ return __generic_fit(src, fitting.planckian_fit) @computation_function() def twohalfgaussian_fit(src: SignalObj) -> SignalObj: """Compute two-half-Gaussian fit with :py:func:`scipy.optimize.curve_fit` Args: src: source signal Returns: Result signal object """ return __generic_fit(src, fitting.twohalfgaussian_fit) @computation_function() def sigmoid_fit(src: SignalObj) -> SignalObj: """Compute sigmoid fit with :py:func:`scipy.optimize.curve_fit` Args: src: source signal Returns: Result signal object """ return __generic_fit(src, fitting.sigmoid_fit) @computation_function() def piecewiseexponential_fit(src: SignalObj) -> SignalObj: """Compute piecewise exponential fit (raise-decay) with :py:func:`scipy.optimize.curve_fit` Args: src: source signal Returns: Result signal object """ return __generic_fit(src, fitting.piecewiseexponential_fit) @computation_function() def sinusoidal_fit(src: SignalObj) -> SignalObj: """Compute sinusoidal fit with :py:func:`scipy.optimize.curve_fit` Args: src: source signal Returns: Result signal object """ return __generic_fit(src, fitting.sinusoidal_fit) def extract_fit_params(signal: SignalObj) -> dict[str, float | str]: """Extract fit parameters from a fitted signal. Args: signal: Signal object containing fit metadata Returns: Fit parameters """ if "fit_params" not in signal.metadata: raise ValueError("Signal does not contain fit parameters") fit_params_dict: dict[str, float | str] = signal.metadata["fit_params"] assert "fit_type" in fit_params_dict, "No valid fit parameters found" return fit_params_dict @computation_function() def evaluate_fit(src1: SignalObj, src2: SignalObj) -> SignalObj: """Evaluate fit function from src1 on the x-axis of src2. This function extracts fit parameters from `src1` (which must contain fit metadata from a previous fitting operation) and evaluates the fit function on the x-axis of `src2`. Args: src1: Signal object containing fit parameters in metadata (from a fit operation) src2: Signal object whose x-axis will be used for evaluation Returns: New signal with the fit evaluated on src2's x-axis """ fit_params = extract_fit_params(src1) dst = dst_2_to_1(src1, src2, "evaluate_fit") # Evaluate fit on src2's x-axis x = src2.x y = fitting.evaluate_fit(x, **fit_params) dst.set_xydata(x, y) dst.title = f"Fitted {fit_params['fit_type']}" # Copy fit parameters to destination metadata dst.metadata["fit_params"] = fit_params return dst Sigima-1.1.1/sigima/proc/signal/fourier.py000066400000000000000000000217461514013333200204460ustar00rootroot00000000000000# -*- coding: utf-8 -*- # # Licensed under the terms of the BSD 3-Clause # (see sigima/LICENSE for details) """ Fourier transform and frequency domain operations ================================================= This module provides Fourier transform and frequency domain operations: - FFT and inverse FFT - Magnitude and phase spectrum - Power spectral density (PSD) .. note:: Most operations use functions from :mod:`sigima.tools.signal.fourier` for actual computations. """ from __future__ import annotations from math import ceil, log2 import guidata.dataset as gds from sigima.config import _ from sigima.enums import PadLocation1D from sigima.objects import SignalObj from sigima.proc.base import FFTParam, SpectrumParam from sigima.proc.decorator import computation_function from sigima.proc.signal.base import dst_1_to_1 from sigima.tools.signal import fourier class ZeroPadding1DParam(gds.DataSet, title=_("Zero padding")): """Zero-padding parameters for signals. This class manages parameters for applying zero-padding to signals, commonly used to improve FFT resolution or prepare signals for convolution. .. important:: For strategies other than "custom", the number of points to add (``n``) is **automatically calculated** based on the signal size. However, this calculation requires knowledge of the signal, so you **must call** :meth:`update_from_obj` before using the parameters. Example usage: .. code-block:: python import sigima.params import sigima.proc.signal as sips # Create the parameter object param = sigima.params.ZeroPadding1DParam.create(strategy="next_pow2") # IMPORTANT: Update parameters from the signal to compute 'n' param.update_from_obj(signal) # Now the parameters are ready to use result = sips.zero_padding(signal, param) Attributes: - strategies: Available strategies ("next_pow2", "double", "triple", "custom"). - strategy: Choice item for selecting the zero-padding strategy. - ``"next_pow2"``: Pad to the next power of 2 (optimal for FFT) - ``"double"``: Double the signal length - ``"triple"``: Triple the signal length - ``"custom"``: Use a user-specified number of points - location: Where to add the padding ("append", "prepend", or "both"). - n: Number of points to add as padding. For "custom" strategy, this is user-specified. For other strategies, it is computed automatically by :meth:`update_from_obj`. """ def __init__(self, *args, **kwargs) -> None: """Initialize zero padding parameters. Args: *args: Variable length argument list passed to the superclass. **kwargs: Arbitrary keyword arguments passed to the superclass. """ super().__init__(*args, **kwargs) self.__obj: SignalObj | None = None def update_from_obj(self, obj: SignalObj) -> None: """Update parameters based on a signal object. This method computes the number of padding points (``n``) based on the selected strategy and the actual signal size. **This must be called before using the parameters** for strategies other than "custom". Args: obj: Signal object from which to compute the padding parameters. """ self.__obj = obj self.strategy_callback(None, self.strategy) @staticmethod def next_power_of_two(size: int) -> int: """Compute the next power of two greater than or equal to the given size. Args: size: The input integer. Returns: The smallest power of two greater than or equal to 'size'. """ return 2 ** (ceil(log2(size))) def strategy_callback(self, _, value): """Callback for strategy choice item. Args: _: Unused argument (in this context). value: The selected strategy value. """ if self.__obj is None: return assert self.__obj.x is not None size = self.__obj.x.size if value == "next_pow2": self.n = self.next_power_of_two(size) - size elif value == "double": self.n = size elif value == "triple": self.n = 2 * size strategies = ("next_pow2", "double", "triple", "custom") _prop = gds.GetAttrProp("strategy") strategy = gds.ChoiceItem( _("Strategy"), zip(strategies, strategies), default=strategies[0] ).set_prop("display", store=_prop, callback=strategy_callback) location = gds.ChoiceItem( _("Location"), PadLocation1D, default=PadLocation1D.APPEND, help=_("Where to add the padding"), ) _func_prop = gds.FuncProp(_prop, lambda x: x == "custom") n = gds.IntItem( _("Number of points"), min=1, default=1, help=_("Number of points to add") ).set_prop("display", active=_func_prop) @computation_function() def zero_padding(src: SignalObj, p: ZeroPadding1DParam) -> SignalObj: """Compute zero padding with :py:func:`sigima.tools.signal.fourier.zero_padding`. Args: src: Source signal. p: Parameters. Returns: Result signal object. """ if p.strategy == "custom": suffix = f"n={p.n}" else: suffix = f"strategy={p.strategy}" assert p.n is not None if p.location == PadLocation1D.APPEND: n_prepend = 0 n_append = p.n elif p.location == PadLocation1D.PREPEND: n_prepend = p.n n_append = 0 else: # At this point, we must have BOTH (last option) assert p.location == PadLocation1D.BOTH n_prepend = p.n // 2 n_append = p.n - n_prepend dst = dst_1_to_1(src, "zero_padding", suffix) x, y = src.get_data() x_padded, y_padded = fourier.zero_padding(x, y, n_prepend, n_append) dst.set_xydata(x_padded, y_padded) return dst @computation_function() def fft(src: SignalObj, p: FFTParam | None = None) -> SignalObj: """Compute FFT with :py:func:`sigima.tools.signal.fourier.fft1d`. Args: src: Source signal. p: Parameters. Returns: Result signal object. """ if p is None: p = FFTParam() dst = dst_1_to_1(src, "fft") x, y = src.get_data() fft_x, fft_y = fourier.fft1d(x, y, shift=p.shift) dst.set_xydata(fft_x, fft_y) dst.save_attr_to_metadata("xunit", "Hz" if dst.xunit == "s" else "") dst.save_attr_to_metadata("yunit", "") dst.save_attr_to_metadata("xlabel", _("Frequency")) return dst @computation_function() def ifft(src: SignalObj) -> SignalObj: """Compute the inverse FFT with :py:func:`sigima.tools.signal.fourier.ifft1d`. Args: src: Source signal. Returns: Result signal object. """ dst = dst_1_to_1(src, "ifft") f, sp = src.get_data() x, y = fourier.ifft1d(f, sp) dst.set_xydata(x, y) dst.restore_attr_from_metadata("xunit", "s" if src.xunit == "Hz" else "") dst.restore_attr_from_metadata("yunit", "") dst.restore_attr_from_metadata("xlabel", "") return dst @computation_function() def magnitude_spectrum(src: SignalObj, p: SpectrumParam | None = None) -> SignalObj: """Compute magnitude spectrum. This function computes the magnitude spectrum of a signal using :py:func:`sigima.tools.signal.fourier.magnitude_spectrum`. Args: src: Source signal. p: Parameters. Returns: Result signal object. """ decibel = bool(p is not None and p.decibel) dst = dst_1_to_1(src, "magnitude_spectrum", f"dB={decibel}") x, y = src.get_data() mag_x, mag_y = fourier.magnitude_spectrum(x, y, decibel=decibel) dst.set_xydata(mag_x, mag_y) dst.xlabel = _("Frequency") dst.xunit = "Hz" if dst.xunit == "s" else "" dst.yunit = "dB" if decibel else "" return dst @computation_function() def phase_spectrum(src: SignalObj) -> SignalObj: """Compute phase spectrum. This function computes the phase spectrum of a signal using :py:func:`sigima.tools.signal.fourier.phase_spectrum` Args: src: Source signal. Returns: Result signal object. """ dst = dst_1_to_1(src, "phase_spectrum") x, y = src.get_data() phase_x, phase_y = fourier.phase_spectrum(x, y) dst.set_xydata(phase_x, phase_y) dst.xlabel = _("Frequency") dst.xunit = "Hz" if dst.xunit == "s" else "" dst.yunit = "" return dst @computation_function() def psd(src: SignalObj, p: SpectrumParam | None = None) -> SignalObj: """Compute power spectral density with :py:func:`sigima.tools.signal.fourier.psd`. Args: src: Source signal. p: Parameters. Returns: Result signal object. """ decibel = p is not None and p.decibel dst = dst_1_to_1(src, "psd", f"dB={decibel}") x, y = src.get_data() psd_x, psd_y = fourier.psd(x, y, decibel=decibel) dst.set_xydata(psd_x, psd_y) dst.xlabel = _("Frequency") dst.xunit = "Hz" if dst.xunit == "s" else "" dst.yunit = "dB/Hz" if decibel else "" return dst Sigima-1.1.1/sigima/proc/signal/mathops.py000066400000000000000000000257201514013333200204420ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Mathematical operations on signals ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ """ from __future__ import annotations import warnings import guidata.dataset as gds import numpy as np from sigima.config import _ from sigima.enums import AngleUnit from sigima.objects import SignalObj from sigima.proc.base import AngleUnitParam, PhaseParam, dst_1_to_1, dst_2_to_1 from sigima.proc.decorator import computation_function from sigima.proc.signal.base import ( Wrap1to1Func, is_uncertainty_data_available, restore_data_outside_roi, ) from sigima.tools import coordinates @computation_function() def transpose(src: SignalObj) -> SignalObj: """Transpose signal (swap X and Y axes). Args: src: Source signal. Returns: Result signal object. """ dst = dst_1_to_1(src, "transpose") x, y = src.get_data() dst.set_xydata(y, x, src.dy, src.dx) dst.xlabel = src.ylabel dst.ylabel = src.xlabel dst.xunit = src.yunit dst.yunit = src.xunit return dst @computation_function() def inverse(src: SignalObj) -> SignalObj: """Compute the element-wise inverse of a signal. The function computes the reciprocal (1/y) of each element of the input signal. .. note:: If the signal has a region of interest (ROI), the inverse is performed only within the ROI. .. note:: Uncertainties are propagated. Args: src: Input signal object. Returns: Result signal object representing the inverse of the input signal. """ dst = dst_1_to_1(src, "invert") x, y = src.get_data() with warnings.catch_warnings(): warnings.simplefilter("ignore", category=RuntimeWarning) dst.set_xydata(x, np.reciprocal(y)) dst.y[np.isinf(dst.y)] = np.nan if is_uncertainty_data_available(src): err = np.abs(dst.y) * (src.dy / np.abs(src.y)) err[np.isinf(err)] = np.nan dst.dy = err restore_data_outside_roi(dst, src) return dst @computation_function() def absolute(src: SignalObj) -> SignalObj: """Compute absolute value with :py:data:`numpy.absolute` Args: src: source signal Returns: Result signal object """ return Wrap1to1Func(np.absolute)(src) @computation_function() def real(src: SignalObj) -> SignalObj: """Compute real part with :py:func:`numpy.real` Args: src: source signal Returns: Result signal object """ return Wrap1to1Func(np.real)(src) @computation_function() def imag(src: SignalObj) -> SignalObj: """Compute imaginary part with :py:func:`numpy.imag` Args: src: source signal Returns: Result signal object """ return Wrap1to1Func(np.imag)(src) @computation_function() def phase(src: SignalObj, p: PhaseParam) -> SignalObj: """Compute the phase (argument) of a complex signal. The function uses :py:func:`numpy.angle` to compute the argument and :py:func:`numpy.unwrap` to unwrap it. Args: src: Input signal object. p: Phase parameters. Returns: Signal object containing the phase, optionally unwrapped. """ suffix = "unwrap" if p.unwrap else "" dst = dst_1_to_1(src, "phase", suffix) x, y = src.get_data() argument = np.angle(y) if p.unwrap: argument = np.unwrap(argument) if p.unit == AngleUnit.DEGREE: argument = np.rad2deg(argument) dst.set_xydata(x, argument, src.dx, None) dst.yunit = p.unit restore_data_outside_roi(dst, src) return dst @computation_function() def complex_from_real_imag(src1: SignalObj, src2: SignalObj) -> SignalObj: """Combine two real signals into a complex signal using real + i * imag. .. warning:: The x coordinates of the two signals must be the same. Args: src1: Real part signal. src2: Imaginary part signal. Returns: Result signal object with complex-valued y. """ if not np.array_equal(src1.x, src2.x): warnings.warn( "The x coordinates of the two signals are not the same. " "Results may be incorrect." ) dst = dst_2_to_1(src1, src2, "real_imag") y = src1.y + 1j * src2.y dst.set_xydata(src1.x, y, src1.dx, None) return dst @computation_function() def complex_from_magnitude_phase( src1: SignalObj, src2: SignalObj, p: AngleUnitParam ) -> SignalObj: """Combine magnitude and phase signals into a complex signal. .. warning:: The x coordinates of the two signals must be the same. .. warning:: Negative values are not allowed for the radius and will be clipped to 0. Args: src1: Magnitude (module) signal. src2: Phase (argument) signal. p: Parameters (must provide unit for the phase). Returns: Result signal object with complex-valued y. """ if not np.array_equal(src1.x, src2.x): warnings.warn( "The x coordinates of the two signals are not the same. " "Results may be incorrect." ) if np.any(src1.y < 0.0): warnings.warn("Negative radius values are not allowed. They will be set to 0.") src1.y = np.maximum(src1.y, 0.0) dst = dst_2_to_1(src1, src2, "mag_phase") assert p.unit is not None y = coordinates.polar_to_complex(src1.y, src2.y, unit=p.unit) dst.set_xydata(src1.x, y, src1.x, None) return dst class DataTypeSParam(gds.DataSet, title=_("Convert data type")): """Convert signal data type parameters""" dtype_str = gds.ChoiceItem( _("Destination data type"), list(zip(SignalObj.get_valid_dtypenames(), SignalObj.get_valid_dtypenames())), help=_("Output image data type."), ) @computation_function() def astype(src: SignalObj, p: DataTypeSParam) -> SignalObj: """Convert data type with :py:func:`numpy.astype` Args: src: source signal p: parameters Returns: Result signal object """ dst = dst_1_to_1(src, "astype", f"dtype={p.dtype_str}") dst.xydata = src.xydata.astype(p.dtype_str) return dst @computation_function() def log10(src: SignalObj) -> SignalObj: """Compute Log10 with :py:data:`numpy.log10` Args: src: source signal Returns: Result signal object """ dst = dst_1_to_1(src, "log10") x, y = src.get_data() # Compute result result_y = np.log10(y) dst.set_xydata(x, result_y, src.dx, src.dy) # Uncertainty propagation: σ(log₁₀(y)) = σ(y) / (y * ln(10)) if is_uncertainty_data_available(src): with warnings.catch_warnings(): warnings.simplefilter("ignore", category=RuntimeWarning) dst.dy = src.dy / (y * np.log(10)) dst.dy[np.isinf(dst.dy) | np.isnan(dst.dy)] = np.nan restore_data_outside_roi(dst, src) return dst @computation_function() def exp(src: SignalObj) -> SignalObj: """Compute exponential with :py:data:`numpy.exp` Args: src: source signal Returns: Result signal object """ dst = dst_1_to_1(src, "exp") x, y = src.get_data() # Compute result result_y = np.exp(y) dst.set_xydata(x, result_y, src.dx, src.dy) # Uncertainty propagation: σ(eʸ) = eʸ * σ(y) if is_uncertainty_data_available(src): dst.dy = np.abs(result_y) * src.dy restore_data_outside_roi(dst, src) return dst @computation_function() def sqrt(src: SignalObj) -> SignalObj: """Compute square root with :py:data:`numpy.sqrt` Args: src: source signal Returns: Result signal object """ dst = dst_1_to_1(src, "sqrt") x, y = src.get_data() # Compute result result_y = np.sqrt(y) dst.set_xydata(x, result_y, src.dx, src.dy) # Uncertainty propagation: σ(√y) = σ(y) / (2√y) if is_uncertainty_data_available(src): with warnings.catch_warnings(): warnings.simplefilter("ignore", category=RuntimeWarning) dst.dy = src.dy / (2 * np.sqrt(y)) dst.dy[np.isinf(dst.dy) | np.isnan(dst.dy)] = np.nan restore_data_outside_roi(dst, src) return dst class PowerParam(gds.DataSet, title=_("Power")): """Power parameters""" power = gds.FloatItem(_("Power"), default=2.0) @computation_function() def power(src: SignalObj, p: PowerParam) -> SignalObj: """Compute power with :py:data:`numpy.power` Args: src: source signal p: parameters Returns: Result signal object """ dst = dst_1_to_1(src, "^", str(p.power)) dst.y = np.power(src.y, p.power) # Uncertainty propagation: σ(y^n) = |n * y^(n-1)| * σ(y) if is_uncertainty_data_available(src): with warnings.catch_warnings(): warnings.simplefilter("ignore", category=RuntimeWarning) dst.dy *= np.abs(p.power * np.power(src.y, p.power - 1)) dst.dy[np.isinf(dst.dy) | np.isnan(dst.dy)] = np.nan restore_data_outside_roi(dst, src) return dst @computation_function() def to_polar(src: SignalObj, p: AngleUnitParam) -> SignalObj: """Convert Cartesian coordinates to polar coordinates. This function converts the x and y coordinates of a signal to polar coordinates using :py:func:`sigima.tools.coordinates.to_polar`. .. warning:: X and y must share the same units for the computation to make sense. Args: src: Source signal. p: Parameters. Returns: Result signal object. Raises: ValueError: If the x and y units are not the same. """ assert p.unit is not None if src.xunit != src.yunit: warnings.warn( f"X and y units are not the same: {src.xunit} != {src.yunit}. " "Results will be incorrect." ) dst = dst_1_to_1(src, "Polar coordinates", f"unit={p.unit}") x, y = src.get_data() r, theta = coordinates.to_polar(x, y, p.unit) dst.set_xydata(r, theta) dst.xlabel = _("Radius") dst.ylabel = _("Angle") dst.yunit = p.unit return dst @computation_function() def to_cartesian(src: SignalObj, p: AngleUnitParam) -> SignalObj: """Convert polar coordinates to Cartesian coordinates. This function converts the r and theta coordinates of a signal to Cartesian coordinates using :py:func:`sigima.tools.coordinates.to_cartesian`. .. note:: It is assumed that the x-axis represents the radius and the y-axis the angle. .. warning:: Negative values are not allowed for the radius and will be clipped to 0. Args: src: Source signal. p: Parameters. Returns: Result signal object. """ dst = dst_1_to_1(src, "Cartesian coordinates", f"unit={p.unit}") r, theta = src.get_data() if np.any(r < 0.0): warnings.warn("Negative radius values are not allowed. They will be set to 0.") r = np.maximum(r, 0.0) x, y = coordinates.to_cartesian(r, theta, p.unit) dst.set_xydata(x, y) dst.xlabel = _("x") dst.ylabel = _("y") dst.yunit = src.xunit return dst Sigima-1.1.1/sigima/proc/signal/processing.py000066400000000000000000000445561514013333200211530ustar00rootroot00000000000000# -*- coding: utf-8 -*- # # Licensed under the terms of the BSD 3-Clause # (see sigima/LICENSE for details) """ Signal processing operations ============================ This module provides signal processing operations: - Zero padding - Interpolation and resampling - Convolution and deconvolution - Signal manipulation functions .. note:: Most operations use functions from :mod:`sigima.tools.signal` for actual computations. """ from __future__ import annotations import warnings import guidata.dataset as gds import numpy as np import scipy.integrate as spt import scipy.signal as sps from guidata.dataset import FuncProp, GetAttrProp from sigima.config import _ from sigima.config import options as sigima_options from sigima.enums import Interpolation1DMethod, NormalizationMethod, WindowingMethod from sigima.objects import ROI1DParam, SignalObj from sigima.proc.base import ClipParam, NormalizeParam, dst_2_to_1 from sigima.proc.decorator import computation_function from sigima.tools.signal import fourier, interpolation, scaling, windowing from .base import dst_1_to_1, is_uncertainty_data_available, restore_data_outside_roi class InterpolationParam(gds.DataSet, title=_("Interpolation")): """Interpolation parameters""" method = gds.ChoiceItem( _("Interpolation method"), [ (Interpolation1DMethod.LINEAR, "Linear"), (Interpolation1DMethod.SPLINE, "Spline"), (Interpolation1DMethod.QUADRATIC, "Quadratic"), (Interpolation1DMethod.CUBIC, "Cubic"), (Interpolation1DMethod.BARYCENTRIC, "Barycentric"), (Interpolation1DMethod.PCHIP, "PCHIP"), ], default=Interpolation1DMethod.LINEAR, ) fill_value = gds.FloatItem( _("Fill value"), default=None, help=_( "Value to use for points outside the interpolation domain " "(used only with linear, cubic and pchip methods)." ), check=False, ) @computation_function() def interpolate(src1: SignalObj, src2: SignalObj, p: InterpolationParam) -> SignalObj: """Interpolate data with :py:func:`sigima.tools.signal.interpolation.interpolate`. Args: src1: Source signal to interpolate. src2: Signal with new x-axis. p: Parameters. Returns: Result signal object. """ suffix = f"method={p.method}" if p.fill_value is not None and p.method in ( Interpolation1DMethod.LINEAR, Interpolation1DMethod.CUBIC, Interpolation1DMethod.PCHIP, ): suffix += f", fill_value={p.fill_value}" dst = dst_2_to_1(src1, src2, "interpolate", suffix) x1, y1 = src1.get_data() xnew, _y2 = src2.get_data() ynew = interpolation.interpolate(x1, y1, xnew, p.method, p.fill_value) dst.set_xydata(xnew, ynew) return dst class Resampling1DParam(InterpolationParam): """Resample parameters for 1D signals""" xmin = gds.FloatItem(_("Xmin"), allow_none=True) xmax = gds.FloatItem(_("Xmax"), allow_none=True) _prop = GetAttrProp("dx_or_nbpts") _modes = (("dx", "ΔX"), ("nbpts", _("Number of points"))) mode = gds.ChoiceItem(_("Mode"), _modes, default="nbpts", radio=True).set_prop( "display", store=_prop ) dx = gds.FloatItem("ΔX", allow_none=True).set_prop( "display", active=FuncProp(_prop, lambda x: x == "dx") ) nbpts = gds.IntItem(_("Number of points"), allow_none=True).set_prop( "display", active=FuncProp(_prop, lambda x: x == "nbpts") ) def update_from_obj(self, obj: SignalObj) -> None: """Update parameters from a signal object.""" if self.xmin is None: self.xmin = obj.x[0] if self.xmax is None: self.xmax = obj.x[-1] if self.dx is None: self.dx = obj.x[1] - obj.x[0] if self.nbpts is None: self.nbpts = len(obj.x) @computation_function() def resampling(src: SignalObj, p: Resampling1DParam) -> SignalObj: """Resample data with :py:func:`sigima.tools.signal.interpolation.interpolate` Args: src: source signal p: parameters Returns: Result signal object """ # Create new x-axis based on parameters if p.mode == "dx": assert p.dx is not None xnew = np.arange(p.xmin, p.xmax + p.dx / 2, p.dx) else: assert p.nbpts is not None xnew = np.linspace(p.xmin, p.xmax, p.nbpts) method: Interpolation1DMethod = p.method suffix = f"method={method.value}" if p.fill_value is not None and method in ( Interpolation1DMethod.LINEAR, Interpolation1DMethod.CUBIC, Interpolation1DMethod.PCHIP, ): suffix += f", fill_value={p.fill_value}" dst = dst_1_to_1(src, "resampling", suffix) x, y = src.get_data() ynew = interpolation.interpolate(x, y, xnew, method, p.fill_value) dst.set_xydata(xnew, ynew) return dst def check_same_sample_rate(src1: SignalObj, src2: SignalObj) -> None: """Check if two signals have a constant step size *and* the same sample rate. Args: src1: First signal. src2: Second signal. Raises: ValueError: If the signals do not have a constant step size or the same sample rate. """ for sig in (src1, src2): if not np.allclose(np.diff(sig.x), sig.x[1] - sig.x[0]): raise ValueError(f"Signal {sig.title} must have a constant step size (dx).") dx1 = src1.x[1] - src1.x[0] dx2 = src2.x[1] - src2.x[0] if not np.isclose(dx1, dx2): raise ValueError(f"Signals must have the same sample rate (dx): {dx1} != {dx2}") @computation_function() def deconvolution(src1: SignalObj, src2: SignalObj) -> SignalObj: """Compute deconvolution. The function computes the deconvolution of a signal using :py:func:`sigima_.algorithms.signal.fourier.deconvolve`. Args: src1: Source signal. src2: Filter signal. Returns: Result signal. Notes: The kernel normalization behavior can be configured globally using ``sigima.config.options.auto_normalize_kernel``. """ check_same_sample_rate(src1, src2) dst = dst_2_to_1(src1, src2, "⊛⁻¹", f"filter={src2.title}") x1, y1 = src1.get_data() _x2, y2 = src2.get_data() # Get kernel normalization option from configuration normalize_kernel = sigima_options.auto_normalize_kernel.get() result_y = fourier.deconvolve( x1, y1, y2, normalize_kernel_flag=normalize_kernel, reg=2.0, gain_max=None, auto_scale=True, ) dst.set_xydata(x1, result_y, None, None) restore_data_outside_roi(dst, src1) return dst @computation_function() def normalize(src: SignalObj, p: NormalizeParam) -> SignalObj: """Normalize data with :py:func:`sigima.tools.signal.level.normalize` Args: src: source signal p: parameters Returns: Result signal object """ method: NormalizationMethod = p.method dst = dst_1_to_1(src, "normalize", f"ref={method.value}") x, y = src.get_data() normalized_y = scaling.normalize(y, method) dst.set_xydata(x, normalized_y) # Uncertainty propagation for normalization # σ(y/norm_factor) = σ(y) / norm_factor if is_uncertainty_data_available(src): with warnings.catch_warnings(): warnings.simplefilter("ignore", category=RuntimeWarning) # Calculate normalization factor if method == NormalizationMethod.MAXIMUM: norm_factor = np.nanmax(y) elif method == NormalizationMethod.AMPLITUDE: norm_factor = np.nanmax(y) - np.nanmin(y) elif method == NormalizationMethod.AREA: norm_factor = np.nansum(y) elif method == NormalizationMethod.ENERGY: norm_factor = np.sqrt(np.nansum(np.abs(y) ** 2)) elif method == NormalizationMethod.RMS: norm_factor = np.sqrt(np.nanmean(np.abs(y) ** 2)) else: raise RuntimeError(f"Unsupported normalization method: {method}") if norm_factor != 0: dst.dy = src.dy / np.abs(norm_factor) else: dst.dy[:] = np.nan restore_data_outside_roi(dst, src) return dst @computation_function() def derivative(src: SignalObj) -> SignalObj: """Compute derivative with :py:func:`numpy.gradient` Args: src: source signal Returns: Result signal object """ dst = dst_1_to_1(src, "derivative") x, y = src.get_data() dst.set_xydata(x, np.gradient(y, x)) # Uncertainty propagation for numerical derivative # For gradient using finite differences: σ(dy/dx) ≈ σ(y) / Δx if is_uncertainty_data_available(src): with warnings.catch_warnings(): warnings.simplefilter("ignore", category=RuntimeWarning) # Use the same gradient approach as numpy.gradient for uncertainty dst.dy = np.gradient(src.dy, x) dst.dy[np.isinf(dst.dy) | np.isnan(dst.dy)] = np.nan restore_data_outside_roi(dst, src) return dst @computation_function() def integral(src: SignalObj) -> SignalObj: """Compute integral with :py:func:`scipy.integrate.cumulative_trapezoid` Args: src: source signal Returns: Result signal object """ dst = dst_1_to_1(src, "integral") x, y = src.get_data() dst.set_xydata(x, spt.cumulative_trapezoid(y, x, initial=0.0)) # Uncertainty propagation for numerical integration # For cumulative trapezoidal integration, uncertainties accumulate if is_uncertainty_data_available(src): # Propagate uncertainties through cumulative trapezoidal rule # σ(∫y dx) ≈ √(Σ(σ(y_i) * Δx_i)²) for independent measurements dx = np.diff(x) dy_squared = src.dy[:-1] ** 2 + src.dy[1:] ** 2 # Trapezoidal rule uncertainty # Propagated variance for trapezoidal integration dst.dy = np.zeros_like(dst.y) # Initialize uncertainty array dst.dy[0] = 0.0 # Initial value has no uncertainty dst.dy[1:] = np.sqrt(np.cumsum(dy_squared * (dx**2) / 4)) restore_data_outside_roi(dst, src) return dst class XYCalibrateParam(gds.DataSet, title=_("Calibration")): """Signal calibration parameters""" axes = (("x", _("X-axis")), ("y", _("Y-axis"))) axis = gds.ChoiceItem(_("Calibrate"), axes, default="y") a = gds.FloatItem("a", default=1.0) b = gds.FloatItem("b", default=0.0) @computation_function() def calibration(src: SignalObj, p: XYCalibrateParam) -> SignalObj: """Compute linear calibration Args: src: source signal p: parameters Returns: Result signal object """ dst = dst_1_to_1(src, "calibration", f"{p.axis}={p.a}*{p.axis}+{p.b}") x, y = src.get_data() if p.axis == "x": dst.set_xydata(p.a * x + p.b, y, src.dx, src.dy) # For X-axis calibration: uncertainties in x are scaled, y unchanged if is_uncertainty_data_available(src): dst.dx = np.abs(p.a) * src.dx if src.dx is not None else None # Y uncertainties remain the same else: dst.set_xydata(x, p.a * y + p.b, src.dx, src.dy) # For Y-axis calibration: σ(a*y + b) = |a| * σ(y) if is_uncertainty_data_available(src): if dst.dy is not None: dst.dy *= np.abs(p.a) restore_data_outside_roi(dst, src) return dst @computation_function() def clip(src: SignalObj, p: ClipParam) -> SignalObj: """Compute maximum data clipping with :py:func:`numpy.clip` Args: src: source signal p: parameters Returns: Result signal object """ dst = dst_1_to_1(src, "clip", f"[{p.lower}, {p.upper}]") x, y = src.get_data() # Compute result result_y = np.clip(y, p.lower, p.upper) dst.set_xydata(x, result_y, src.dx, src.dy) # Uncertainty propagation: σ(clip(y)) = σ(y) where not clipped, 0 where clipped if is_uncertainty_data_available(src): dst.dy = src.dy.copy() if p.lower is not None: dst.dy[y <= p.lower] = 0 if p.upper is not None: dst.dy[y >= p.upper] = 0 restore_data_outside_roi(dst, src) return dst @computation_function() def offset_correction(src: SignalObj, p: ROI1DParam) -> SignalObj: """Correct offset: subtract the mean value of the signal in the specified range (baseline correction) Args: src: source signal p: parameters Returns: Result signal object """ dst = dst_1_to_1(src, "offset_correction", f"{p.xmin:.3g}≤x≤{p.xmax:.3g}") _roi_x, roi_y = p.get_data(src) dst.y -= np.mean(roi_y) restore_data_outside_roi(dst, src) return dst class DetrendingParam(gds.DataSet, title=_("Detrending")): """Detrending parameters""" methods = (("linear", _("Linear")), ("constant", _("Constant"))) method = gds.ChoiceItem(_("Detrending method"), methods, default="linear") @computation_function() def detrending(src: SignalObj, p: DetrendingParam) -> SignalObj: """Detrend data with :py:func:`scipy.signal.detrend` Args: src: source signal p: parameters Returns: Result signal object """ dst = dst_1_to_1(src, "detrending", f"method={p.method}") x, y = src.get_data() dst.set_xydata(x, sps.detrend(y, type=p.method)) restore_data_outside_roi(dst, src) return dst class WindowingParam(gds.DataSet, title=_("Windowing")): """Windowing parameters.""" _meth_prop = gds.GetAttrProp("method") method = gds.ChoiceItem( _("Method"), WindowingMethod, default=WindowingMethod.HAMMING ).set_prop("display", store=_meth_prop) alpha = gds.FloatItem( "Alpha", default=0.5, help=_("Shape parameter of the Tukey windowing function"), ).set_prop( "display", active=gds.FuncProp(_meth_prop, lambda x: x == WindowingMethod.TUKEY) ) beta = gds.FloatItem( "Beta", default=14.0, help=_("Shape parameter of the Kaiser windowing function"), ).set_prop( "display", active=gds.FuncProp(_meth_prop, lambda x: x == WindowingMethod.KAISER), ) sigma = gds.FloatItem( "Sigma", default=0.5, help=_("Shape parameter of the Gaussian windowing function"), ).set_prop( "display", active=gds.FuncProp(_meth_prop, lambda x: x == WindowingMethod.GAUSSIAN), ) @computation_function() def apply_window(src: SignalObj, p: WindowingParam) -> SignalObj: """Compute windowing with :py:func:`sigima.tools.signal.windowing.apply_window`. Args: src: Source signal. p: Parameters for windowing. Returns: Result signal object. """ method: WindowingMethod = p.method suffix = f"method={method.value}" if method == WindowingMethod.GAUSSIAN: suffix += f", sigma={p.sigma:.3f}" elif method == WindowingMethod.KAISER: suffix += f", beta={p.beta:.3f}" elif method == WindowingMethod.TUKEY: suffix += f", alpha={p.alpha:.3f}" dst = dst_1_to_1(src, "apply_window", suffix) assert p.alpha is not None dst.y = windowing.apply_window(dst.y, method, p.alpha) restore_data_outside_roi(dst, src) return dst @computation_function() def reverse_x(src: SignalObj) -> SignalObj: """Reverse x-axis Args: src: source signal Returns: Result signal object """ dst = dst_1_to_1(src, "reverse_x") dst.y = dst.y[::-1] return dst @computation_function() def convolution(src1: SignalObj, src2: SignalObj) -> SignalObj: """Compute convolution of two signals with :py:func:`scipy.signal.convolve`. Args: src1: Source signal 1. src2: Source signal 2. Returns: Result signal. Notes: The behavior of kernel normalization is controlled by the global configuration option ``sigima.config.options.auto_normalize_kernel``. """ check_same_sample_rate(src1, src2) dst = dst_2_to_1(src1, src2, "⊛") x1, y1 = src1.get_data() _x2, y2 = src2.get_data() # Get configuration option for kernel normalization normalize_kernel = sigima_options.auto_normalize_kernel.get() ynew = fourier.convolve( x1, y1, y2, normalize_kernel_flag=normalize_kernel, ) dst.set_xydata(x1, ynew, None, None) restore_data_outside_roi(dst, src1) return dst @computation_function() def xy_mode(src1: SignalObj, src2: SignalObj) -> SignalObj: """Simulate the X-Y mode of an oscilloscope. Use the first signal as the X-axis and the second signal as the Y-axis. Args: src1: First input signal (X-axis). src2: Second input signal (Y-axis). Returns: A signal object representing the X-Y mode. """ dst = dst_2_to_1(src1, src2, "", "X-Y Mode") p = Resampling1DParam() p.xmin = max(src1.x[0], src2.x[0]) p.xmax = min(src1.x[-1], src2.x[-1]) assert p.xmin < p.xmax, "X-Y mode: No overlap between signals." p.mode = "nbpts" p.nbpts = min(src1.x.size, src2.x.size) _, y1 = resampling(src1, p).get_data() _, y2 = resampling(src2, p).get_data() dst.set_xydata(y1, y2) dst.title = "{1} = f({0})" restore_data_outside_roi(dst, src1) return dst @computation_function() def replace_x_by_other_y(src1: SignalObj, src2: SignalObj) -> SignalObj: """Create a new signal using Y from src1 and Y from src2 as X coordinates. This is useful for calibration scenarios where one signal contains calibration data (e.g., wavelengths) in its Y values, and you want to plot another signal's Y values against these calibration points. The two signals must have the same number of points. Args: src1: First signal (provides Y data for output). src2: Second signal (provides Y data to be used as X coordinates for output). Returns: A new signal with X from src2.y and Y from src1.y. Raises: ValueError: If signals don't have the same number of points. """ if src1.y.size != src2.y.size: raise ValueError( f"Signals must have the same number of points: " f"{src1.y.size} != {src2.y.size}" ) dst = dst_2_to_1(src1, src2, "replace_x_by_other_y") dst.set_xydata(src2.y, src1.y) dst.xlabel = src2.ylabel if src2.ylabel else "X" dst.xunit = src2.yunit if src2.yunit else "" # Y label and unit remain from src1 restore_data_outside_roi(dst, src1) return dst Sigima-1.1.1/sigima/proc/signal/stability.py000066400000000000000000000107361514013333200207740ustar00rootroot00000000000000# -*- coding: utf-8 -*- # # Licensed under the terms of the BSD 3-Clause # (see sigima/LICENSE for details) """ Stability analysis functions ============================ This module provides stability analysis functions for signal objects: - Allan variance and deviation - Overlapping Allan variance - Modified Allan variance - Hadamard variance - Total variance .. note:: All operations use functions from :mod:`sigima.tools.signal.stability` for actual computations. """ from __future__ import annotations import guidata.dataset as gds import numpy as np from sigima.config import _ from sigima.objects import SignalObj from sigima.proc.decorator import computation_function from sigima.tools.signal import stability from .base import dst_1_to_1 class AllanVarianceParam(gds.DataSet, title=_("Allan variance")): """Allan variance parameters""" max_tau = gds.IntItem("Max τ", default=100, min=1, unit="pts") @computation_function() def allan_variance(src: SignalObj, p: AllanVarianceParam) -> SignalObj: """Compute Allan variance with :py:func:`sigima.tools.signal.stability.allan_variance`. Args: src: source signal p: parameters Returns: Result signal object """ dst = dst_1_to_1(src, "allan_variance", f"max_tau={p.max_tau}") x, y = src.get_data() tau_values = np.arange(1, p.max_tau + 1) avar = stability.allan_variance(x, y, tau_values) dst.set_xydata(tau_values, avar) return dst @computation_function() def allan_deviation(src: SignalObj, p: AllanVarianceParam) -> SignalObj: """Compute Allan deviation with :py:func:`sigima.tools.signal.stability.allan_deviation` Args: src: source signal p: parameters Returns: Result signal object """ dst = dst_1_to_1(src, "allan_deviation", f"max_tau={p.max_tau}") x, y = src.get_data() tau_values = np.arange(1, p.max_tau + 1) adev = stability.allan_deviation(x, y, tau_values) dst.set_xydata(tau_values, adev) return dst @computation_function() def overlapping_allan_variance(src: SignalObj, p: AllanVarianceParam) -> SignalObj: """Compute Overlapping Allan variance. Args: src: source signal p: parameters Returns: Result signal object """ dst = dst_1_to_1(src, "overlapping_allan_variance", f"max_tau={p.max_tau}") x, y = src.get_data() tau_values = np.arange(1, p.max_tau + 1) oavar = stability.overlapping_allan_variance(x, y, tau_values) dst.set_xydata(tau_values, oavar) return dst @computation_function() def modified_allan_variance(src: SignalObj, p: AllanVarianceParam) -> SignalObj: """Compute Modified Allan variance. Args: src: source signal p: parameters Returns: Result signal object """ dst = dst_1_to_1(src, "modified_allan_variance", f"max_tau={p.max_tau}") x, y = src.get_data() tau_values = np.arange(1, p.max_tau + 1) mavar = stability.modified_allan_variance(x, y, tau_values) dst.set_xydata(tau_values, mavar) return dst @computation_function() def hadamard_variance(src: SignalObj, p: AllanVarianceParam) -> SignalObj: """Compute Hadamard variance. Args: src: source signal p: parameters Returns: Result signal object """ dst = dst_1_to_1(src, "hadamard_variance", f"max_tau={p.max_tau}") x, y = src.get_data() tau_values = np.arange(1, p.max_tau + 1) hvar = stability.hadamard_variance(x, y, tau_values) dst.set_xydata(tau_values, hvar) return dst @computation_function() def total_variance(src: SignalObj, p: AllanVarianceParam) -> SignalObj: """Compute Total variance. Args: src: source signal p: parameters Returns: Result signal object """ dst = dst_1_to_1(src, "total_variance", f"max_tau={p.max_tau}") x, y = src.get_data() tau_values = np.arange(1, p.max_tau + 1) tvar = stability.total_variance(x, y, tau_values) dst.set_xydata(tau_values, tvar) return dst @computation_function() def time_deviation(src: SignalObj, p: AllanVarianceParam) -> SignalObj: """Compute Time Deviation (TDEV). Args: src: source signal p: parameters Returns: Result signal object """ dst = dst_1_to_1(src, "time_deviation", f"max_tau={p.max_tau}") x, y = src.get_data() tau_values = np.arange(1, p.max_tau + 1) tdev = stability.time_deviation(x, y, tau_values) dst.set_xydata(tau_values, tdev) return dst Sigima-1.1.1/sigima/proc/title_formatting.py000066400000000000000000000124211514013333200210570ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Title formatting system for computation results ----------------------------------------------- This module provides a configurable title formatting system for computation results. It allows different applications (Sigima vs DataLab) to use different title formatting strategies while maintaining compatibility. """ from __future__ import annotations from typing import Protocol, runtime_checkable __all__ = [ "PlaceholderTitleFormatter", "SimpleTitleFormatter", "TitleFormatter", "get_default_title_formatter", "set_default_title_formatter", ] @runtime_checkable class TitleFormatter(Protocol): """Protocol for title formatting strategies used in computation functions. This protocol allows different title formatting approaches: - Simple descriptive titles for Sigima-only usage - Placeholder-based titles for DataLab integration - Custom formatting for specific use cases """ def format_1_to_1_title(self, name: str, suffix: str | None = None) -> str: """Format title for 1-to-1 computation (single input → single output). Args: name: Name of the computation function suffix: Optional suffix to add to the title Returns: Formatted title string """ def format_n_to_1_title( self, name: str, n_inputs: int, suffix: str | None = None ) -> str: """Format title for n-to-1 computation (multiple inputs → single output). Args: name: Name of the computation function n_inputs: Number of input objects suffix: Optional suffix to add to the title Returns: Formatted title string """ def format_2_to_1_title(self, name: str, suffix: str | None = None) -> str: """Format title for 2-to-1 computation (two inputs → single output). Args: name: Name of the computation function suffix: Optional suffix to add to the title Returns: Formatted title string """ class SimpleTitleFormatter: """Simple descriptive title formatter for Sigima-only usage. Creates human-readable titles without placeholders, suitable for standalone Sigima usage where object relationships are less critical. """ def format_1_to_1_title(self, name: str, suffix: str | None = None) -> str: """Format title for 1-to-1 computation.""" # Convert function names to human-readable format readable_name = name.replace("_", " ").title() base_title = f"{readable_name} Result" if suffix: base_title += f" ({suffix})" return base_title def format_n_to_1_title( self, name: str, n_inputs: int, suffix: str | None = None ) -> str: """Format title for n-to-1 computation.""" readable_name = name.replace("_", " ").title() base_title = f"{readable_name} of {n_inputs} Objects" if suffix: base_title += f" ({suffix})" return base_title def format_2_to_1_title(self, name: str, suffix: str | None = None) -> str: """Format title for 2-to-1 computation.""" if len(name) == 1: # This is an operator base_title = f"Binary Operation {name}" else: readable_name = name.replace("_", " ").title() base_title = f"{readable_name} Result" if suffix: base_title += f" ({suffix})" return base_title class PlaceholderTitleFormatter: """Placeholder-based title formatter compatible with DataLab. Creates titles with placeholders that can be resolved later by DataLab's patch_title_with_ids() function. """ def format_1_to_1_title(self, name: str, suffix: str | None = None) -> str: """Format title for 1-to-1 computation with placeholder.""" title = f"{name}({{0}})" if suffix: title += "|" + suffix return title def format_n_to_1_title( self, name: str, n_inputs: int, suffix: str | None = None ) -> str: """Format title for n-to-1 computation with placeholders.""" placeholders = ", ".join(f"{{{i}}}" for i in range(n_inputs)) title = f"{name}({placeholders})" if suffix: title += "|" + suffix return title def format_2_to_1_title(self, name: str, suffix: str | None = None) -> str: """Format title for 2-to-1 computation with placeholders.""" if len(name) == 1: # This is an operator title = f"{{0}}{name}{{1}}" else: title = f"{name}({{0}}, {{1}})" if suffix: title += "|" + suffix return title # Global default title formatter _default_title_formatter: TitleFormatter = SimpleTitleFormatter() def get_default_title_formatter() -> TitleFormatter: """Get the current default title formatter. Returns: Current default title formatter """ return _default_title_formatter def set_default_title_formatter(formatter: TitleFormatter) -> None: """Set the default title formatter. Args: formatter: Title formatter to use as default """ global _default_title_formatter # pylint: disable=global-statement _default_title_formatter = formatter Sigima-1.1.1/sigima/proc/validation.py000066400000000000000000000241221514013333200176370ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ .. Validation statistics module (see parent package :mod:`sigima.computation`) """ from __future__ import annotations import csv import dataclasses import importlib import inspect import os.path as osp import pkgutil import re from _pytest.mark import Mark import sigima.tests as tests_pkg from sigima import __version__ from sigima.proc.decorator import find_computation_functions def generate_valid_test_names_for_function( module_name: str, func_name: str ) -> list[str]: """Generate all valid test names for a computation function. Args: module_name: Module name containing the computation function (e.g., "sigima.proc.image") func_name: Function name (e.g., "compute_add_gaussian_noise") Returns: List of valid test names that could test this computation function """ family = module_name.split(".")[-1] # "signal" or "image" shortname = func_name.removeprefix("compute_") endings = [shortname, shortname + "_unit", shortname + "_validation"] beginnings = ["test", f"test_{family}", f"test_{family[:3]}", f"test_{family[0]}"] names = [f"{beginning}_{ending}" for beginning in beginnings for ending in endings] return names def check_for_validation_test( full_function_name: str, validation_tests: list[tuple[str, str]] ) -> str: """Check if a validation test exists for a compute function Args: full_function_name: Compute function name validation_tests: List of validation tests Returns: Text to be included in the CSV file or None if it doesn't exist """ # Extract module name and function name from full function name module_parts = full_function_name.split(".") module_name = ".".join(module_parts[:-1]) # e.g., "sigima.proc.image" func_name = module_parts[-1] # e.g., "compute_add_gaussian_noise" # Generate all valid test names for this computation function names = generate_valid_test_names_for_function(module_name, func_name) stable_version = re.sub(r"\.?(post|dev|rc|b|a)\S*", "", __version__) for test, path, line_number in validation_tests: if test in names: # Path relative to the `datalab` package: path = osp.relpath(path, start=osp.dirname(osp.join(tests_pkg.__file__))) name = "/".join(path.split(osp.sep)) link = ( f"https://github.com/DataLab-Platform/Sigima/blob/" f"v{stable_version}/sigima/tests/{name}#L{line_number}" ) return f"`{test} <{link}>`_" return None def get_validation_tests(package: str) -> list: """Retrieve list of validation tests from a package and its submodules Args: package: Python package Returns: List of tuples containing the test name, module path and line number """ validation_tests = [] package_path = package.__path__ for _, module_name, _ in pkgutil.walk_packages( package_path, package.__name__ + "." ): try: module = importlib.import_module(module_name) except ImportError as exc: if "viz" in module_name: # This is expected as viz requires a GUI continue raise ImportError( f"Failed to import module {module_name}. " "Ensure the module is correctly installed and accessible." ) from exc for name, obj in inspect.getmembers(module, inspect.isfunction): if hasattr(obj, "pytestmark"): for mark in obj.pytestmark: if isinstance(mark, Mark) and mark.name == "validation": module_path = inspect.getfile(obj) try: line_number = inspect.getsourcelines(obj)[1] except OSError as exc: raise RuntimeError( f"Failed to get source line for {name} in {module_name}" ) from exc validation_tests.append((name, module_path, line_number)) return validation_tests def shorten_docstring(docstring: str) -> str: """Shorten a docstring to a single line Args: docstring: Docstring Returns: Shortened docstring """ shorter = docstring.split("\n")[0].strip() if docstring else "-" for suffix in (".", ":", ",", "using", "with"): shorter = shorter.removesuffix(suffix) shorter = shorter.split(" with :py:func:")[0] # Remove function references return shorter @dataclasses.dataclass class ValidationStatus: """Data class to hold validation status of a compute function""" module_name: str function_name: str description: str test_script: str def get_pyfunc_link(self) -> str: """Get the reStructuredText link to the compute function""" return ( f":py:func:`{self.function_name} <{self.module_name}.{self.function_name}>`" ) def __str__(self) -> str: """String representation of the validation status""" return f"{self.get_pyfunc_link()} - {self.description} - {self.test_script}" def to_csv_row(self) -> list[str]: """Convert the validation status to a CSV row""" return [self.get_pyfunc_link(), self.description, self.test_script] class ValidationStatistics: """Data class to hold validation statistics of compute functions""" def __init__(self): self.submodules: dict[str, list[tuple[str, str, str]]] = {} self.t_count: dict[str, int] = {} self.v_count: dict[str, int] = {} self.signal_pct: int = 0 self.image_pct: int = 0 self.total_pct: int = 0 self.validations: dict[str, list[ValidationStatus]] = {} self.validation_info_list: list[str] = [] def collect_validation_status(self, verbose: bool = False) -> None: """Populate the statistics from the validation status""" compute_functions = find_computation_functions() validation_tests = get_validation_tests(tests_pkg) self.submodules = {"signal": [], "image": []} for modname, funcname, docstring in compute_functions: if "signal" in modname: self.submodules["signal"].append((modname, funcname, docstring)) elif "image" in modname: self.submodules["image"].append((modname, funcname, docstring)) self.t_count = t_count = {"signal": 0, "image": 0, "total": 0} self.v_count = v_count = {"signal": 0, "image": 0, "total": 0} self.validations = {"signal": [], "image": []} for submodule, functions in self.submodules.items(): for modname, funcname, docstring in functions: full_funcname = f"{modname}.{funcname}" test_link = check_for_validation_test(full_funcname, validation_tests) if test_link: v_count[submodule] += 1 v_count["total"] += 1 t_count[submodule] += 1 t_count["total"] += 1 status = ValidationStatus( module_name=modname, function_name=funcname, description=shorten_docstring(docstring), test_script=test_link if test_link else "N/A", ) self.validations[submodule].append(status) self.signal_pct = signal_pct = ( int((v_count["signal"] / t_count["signal"]) * 100) if t_count["signal"] > 0 else 0 ) self.image_pct = image_pct = ( int((v_count["image"] / t_count["image"]) * 100) if t_count["image"] > 0 else 0 ) self.total_pct = total_pct = ( int((v_count["total"] / t_count["total"]) * 100) if t_count["total"] > 0 else 0 ) self.validation_info_list = [ f"Validation statistics for Sigima {__version__}:", f" Signal: {v_count['signal']}/{t_count['signal']} ({signal_pct}%)", f" Image : {v_count['image']}/{t_count['image']} ({image_pct}%)", f" Total : {v_count['total']}/{t_count['total']} ({total_pct}%)", ] if verbose: print("\n".join(self.validation_info_list)) print() def get_validation_info(self) -> list[str]: """Get the validation information as a list of strings""" if not self.validation_info_list: self.collect_validation_status(verbose=False) return self.validation_info_list def generate_csv_files(self, path: str) -> None: """Generate CSV files for each submodule's validation status""" for submodule, validation_status_list in self.validations.items(): rows = [status.to_csv_row() for status in validation_status_list] fname = osp.join(path, f"validation_status_{submodule}.csv") with open(fname, "w", newline="", encoding="utf-8") as csvfile: writer = csv.writer(csvfile) writer.writerows(rows) def generate_statistics_csv(self, path: str) -> None: """Generate a CSV file with the validation statistics""" statistics_rows = [ [ "Number of compute functions", self.t_count["signal"], self.t_count["image"], self.t_count["total"], ], [ "Number of validated compute functions", self.v_count["signal"], self.v_count["image"], self.v_count["total"], ], [ "Percentage of validated compute functions", f"{self.signal_pct}%", f"{self.image_pct}%", f"{self.total_pct}%", ], ] fname = osp.join(path, "validation_statistics.csv") with open(fname, "w", newline="", encoding="utf-8") as csvfile: writer = csv.writer(csvfile) writer.writerows(statistics_rows) Sigima-1.1.1/sigima/tests/000077500000000000000000000000001514013333200153315ustar00rootroot00000000000000Sigima-1.1.1/sigima/tests/__init__.py000066400000000000000000000002331514013333200174400ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Sigima test suite """ SIGIMA_TESTS_GUI_ENV = "SIGIMA_TESTS_GUI" Sigima-1.1.1/sigima/tests/common/000077500000000000000000000000001514013333200166215ustar00rootroot00000000000000Sigima-1.1.1/sigima/tests/common/__init__.py000066400000000000000000000000001514013333200207200ustar00rootroot00000000000000Sigima-1.1.1/sigima/tests/common/annotations_unit_test.py000066400000000000000000000105031514013333200236250ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """Unit tests for annotation API.""" import json import pytest from sigima.objects.image.creation import create_image from sigima.objects.signal.creation import create_signal def test_get_empty_annotations(): """Test getting annotations from object without annotations.""" obj = create_signal("Test") assert obj.get_annotations() == [] assert not obj.has_annotations() def test_get_empty_annotations_image(): """Test getting annotations from image object without annotations.""" obj = create_image("Test") assert obj.get_annotations() == [] assert not obj.has_annotations() def test_set_get_annotations(): """Test setting and getting annotations.""" obj = create_signal("Test") annotations = [{"type": "label", "text": "Test"}] obj.set_annotations(annotations) assert obj.get_annotations() == annotations assert obj.has_annotations() def test_set_get_annotations_multiple(): """Test setting and getting multiple annotations.""" obj = create_signal("Test") annotations = [ {"type": "label", "x": 10, "y": 20, "text": "Peak"}, {"type": "rectangle", "x0": 0, "y0": 0, "x1": 100, "y1": 100}, ] obj.set_annotations(annotations) result = obj.get_annotations() assert len(result) == 2 assert result == annotations def test_add_annotation(): """Test adding single annotation.""" obj = create_signal("Test") obj.add_annotation({"type": "circle", "r": 5}) obj.add_annotation({"type": "rect", "w": 10}) annotations = obj.get_annotations() assert len(annotations) == 2 assert annotations[0]["type"] == "circle" assert annotations[1]["type"] == "rect" def test_clear_annotations(): """Test clearing annotations.""" obj = create_signal("Test") obj.set_annotations([{"type": "test"}]) assert obj.has_annotations() obj.clear_annotations() assert obj.get_annotations() == [] assert not obj.has_annotations() def test_invalid_json(): """Test handling of invalid JSON.""" obj = create_signal("Test") obj.annotations = "invalid{json" assert obj.get_annotations() == [] def test_non_json_serializable(): """Test rejection of non-serializable data.""" obj = create_signal("Test") with pytest.raises(ValueError): obj.set_annotations([{"func": lambda x: x}]) def test_invalid_type(): """Test rejection of non-list annotations.""" obj = create_signal("Test") with pytest.raises(TypeError): obj.set_annotations({"type": "dict"}) # type: ignore def test_versioned_format(): """Test that annotations are stored with version.""" obj = create_signal("Test") obj.set_annotations([{"type": "test"}]) # Check internal storage format data = json.loads(obj.annotations) assert "version" in data assert data["version"] == "1.0" assert "annotations" in data def test_annotation_persistence(): """Test that annotations persist through copy operations.""" obj = create_signal("Test") obj.set_annotations([{"type": "label", "text": "Original"}]) # Copy the object obj_copy = obj.copy() # Annotations should be copied assert obj_copy.get_annotations() == obj.get_annotations() def test_complex_annotation_data(): """Test complex nested annotation structures.""" obj = create_image("Test") complex_annotation = { "type": "complex", "properties": { "color": "red", "style": {"width": 2, "dash": [5, 3]}, }, "geometry": [[0, 0], [10, 10], [20, 0]], "metadata": {"created": "2025-11-02", "author": "test"}, } obj.add_annotation(complex_annotation) retrieved = obj.get_annotations() assert len(retrieved) == 1 assert retrieved[0] == complex_annotation def test_empty_annotations_field(): """Test behavior with explicitly empty annotations field.""" obj = create_signal("Test") obj.annotations = "" assert obj.get_annotations() == [] assert not obj.has_annotations() def test_malformed_json_structure(): """Test handling of valid JSON but wrong structure.""" obj = create_signal("Test") obj.annotations = json.dumps({"wrong": "structure"}) assert obj.get_annotations() == [] if __name__ == "__main__": pytest.main([__file__]) Sigima-1.1.1/sigima/tests/common/arithmeticparam_unit_test.py000066400000000000000000000012211514013333200244370ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Arithmetic parameters unit test. """ # pylint: disable=invalid-name # Allows short reference names like x, y, ... import pytest from sigima.params import ArithmeticParam from sigima.tests import guiutils from sigima.tests.env import execenv @pytest.mark.gui def test_arithmetic_param_interactive(): """Arithmetic parameters interactive test.""" with guiutils.lazy_qt_app_context(force=True): param = ArithmeticParam() if param.edit(): execenv.print(param) if __name__ == "__main__": test_arithmetic_param_interactive() Sigima-1.1.1/sigima/tests/common/basename_unit_test.py000066400000000000000000000077701514013333200230570ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """Unit tests for :py:func:`sigima.io.common.basename.format_basenames`.""" from __future__ import annotations import pytest from sigima.io.common.basename import format_basenames from sigima.objects.image import ImageObj from sigima.objects.signal import SignalObj def make_signal( title: str = "", xlabel: str = "", xunit: str = "", ylabel: str = "", yunit: str = "", metadata: dict | None = None, ) -> SignalObj: """Create a SignalObj with specified attributes for testing. Args: title: Title of the signal. xlabel: Label for the x-axis. xunit: Unit for the x-axis. ylabel: Label for the y-axis. yunit: Unit for the y-axis. metadata: Metadata dictionary. Returns: Configured SignalObj instance. """ sig = SignalObj() sig.title = title sig.xlabel = xlabel sig.xunit = xunit sig.ylabel = ylabel sig.yunit = yunit sig.metadata = {} if metadata is None else metadata return sig def make_image(title: str = "", metadata: dict | None = None) -> ImageObj: """Create an ImageObj with specified attributes for testing. Args: title: Title of the image. metadata: Metadata dictionary. Returns: Configured ImageObj instance. """ img = ImageObj() img.title = title img.metadata = {} if metadata is None else metadata return img def test_format_basenames_with_indices_and_total_count(): """Test with indexing and total count placeholders.""" objs = [make_signal("sig1"), make_signal("sig2"), make_signal("sig3")] names = format_basenames(objs, fmt="{index:02d}_of_{count:02d}") assert names == ["01_of_03", "02_of_03", "03_of_03"] def test_format_basenames_with_metadata_and_axes_placeholders(): """Test with metadata and axis placeholders.""" sig = make_signal( title="My/Signal", xlabel="Time", xunit="s", ylabel="Amp", yunit="V", metadata={"id": 42}, ) names = format_basenames( [sig], fmt="{title}_{xlabel}[{xunit}]_{ylabel}[{yunit}]_{metadata[id]}" ) assert names == ["My_Signal_Time[s]_Amp[V]_42"] def test_format_basenames_sanitization(): """Test with sanitization for titles.""" objs = [make_signal("A/B"), make_image("C/D")] # '/' must be sanitized on all OSes names = format_basenames(objs, fmt="{title}") assert names == ["A_B", "C_D"] def test_format_basenames_sanitization_with_custom_replacement(): """Test with custom replacement character.""" objs = [make_signal("a/b"), make_image("c/d")] names = format_basenames(objs, fmt="{title}", replacement="-") assert names == ["a-b", "c-d"] def test_format_basenames_with_unknown_metadata_key(): """Test that requesting a missing metadata key raises a KeyError.""" sig = make_signal(title="T", metadata={"other": 1}) with pytest.raises(KeyError): format_basenames([sig], fmt="{metadata[id]}") def test_format_basenames_with_unknown_placeholder(): """Test with unknown placeholder should raise a KeyError.""" with pytest.raises(KeyError): format_basenames([make_signal("x")], fmt="{unknown}") def test_format_basenames_with_direct_metadata_use(): """Test that direct {metadata} use returns empty string (silently ignored).""" sig = make_signal(title="Test", metadata={"key1": "value1", "key2": "value2"}) names = format_basenames([sig], fmt="{title} {metadata}") # The {metadata} placeholder should be replaced with empty string # The trailing space gets sanitized away assert names == ["Test"] if __name__ == "__main__": test_format_basenames_with_indices_and_total_count() test_format_basenames_with_metadata_and_axes_placeholders() test_format_basenames_sanitization() test_format_basenames_sanitization_with_custom_replacement() test_format_basenames_with_unknown_placeholder() test_format_basenames_with_direct_metadata_use() Sigima-1.1.1/sigima/tests/common/client_unit_test.py000066400000000000000000000373111514013333200225540ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Sigima Client Comprehensive Headless Test This test uses a stub XML-RPC server to emulate DataLab, allowing the test to run without requiring a real DataLab instance. """ # pylint: disable=invalid-name # Allows short reference names like x, y, ... # pylint: disable=duplicate-code # guitest: skip from __future__ import annotations import os.path as osp import tempfile from collections.abc import Generator from contextlib import contextmanager import numpy as np import pytest from guidata.env import execenv from sigima.client.remote import SimpleRemoteProxy from sigima.client.stub import datalab_stub_server @contextmanager def temporary_directory() -> Generator[str, None, None]: """Create a temporary directory and clean-up afterwards""" tmp = tempfile.TemporaryDirectory() # pylint: disable=consider-using-with try: yield tmp.name finally: try: tmp.cleanup() except (PermissionError, RecursionError): pass class RemoteClientTester: """Headless remote client tester class""" SIG_TITLES = ("Oscilloscope", "Digitizer", "Radiometer", "Voltmeter", "Sensor") IMA_TITLES = ( "Camera", "Streak Camera", "Image Scanner", "Laser Beam Profiler", "Gated Imaging Camera", ) def __init__(self): """Initialize the tester""" self.datalab = None self.log_messages = [] self.stub_server_port = None def log(self, message: str) -> None: """Log message for debugging""" self.log_messages.append(message) execenv.print(f"[CLIENT] {message}") def init_cdl_with_stub(self, port: int) -> bool: """Initialize DataLab connection with stub server""" try: self.stub_server_port = port self.datalab = SimpleRemoteProxy(autoconnect=False) self.datalab.connect(port=str(port), timeout=1.0, retries=1) self.log("✨ Initialized DataLab connection with stub server ✨") self.log(f" Communication port: {self.datalab.port}") # Test getting method list methods = self.datalab.get_method_list() self.log(f" Available methods: {len(methods)} found") return True except ConnectionRefusedError: self.log("🔥 Connection refused 🔥 (Stub server is not ready)") return False def init_cdl(self, port: str | None = None) -> bool: """Initialize DataLab connection Args: port: Port to connect to (if None, uses default) """ try: self.datalab = SimpleRemoteProxy(autoconnect=False) self.datalab.connect(port=port, timeout=1.0, retries=1) self.log("✨ Initialized DataLab connection ✨") self.log(f" Communication port: {self.datalab.port}") # Test getting method list methods = self.datalab.get_method_list() self.log(f" Available methods: {len(methods)} found") return True except ConnectionRefusedError: self.log("🔥 Connection refused 🔥 (DataLab server is not ready)") return False def close_datalab(self) -> None: """Close DataLab connection""" if self.datalab is not None: try: self.datalab.close_application() self.log("🎬 Closed DataLab!") except ConnectionRefusedError: self.log("Connection lost while closing DataLab") finally: self.datalab = None def test_connection_management(self) -> None: """Test connection initialization and method listing""" # If we already have a connection (from stub server), skip init if self.datalab is None: assert self.init_cdl(), "Failed to initialize DataLab connection" # Test method listing methods = self.datalab.get_method_list() assert isinstance(methods, list), "Method list should be a list" assert len(methods) > 0, "Should have at least some methods available" # Test basic server info version = self.datalab.get_version() assert isinstance(version, str), "Version should be a string" self.log(f"DataLab version: {version}") def add_test_signals(self) -> None: """Add test signals to DataLab""" if self.datalab is None: return x = np.linspace(0, 10, 1000) signals_data = [ ("Sine", np.sin(x)), ("Cosine", np.cos(x)), ("Exponential", np.exp(-x / 5)), ] for title, y in signals_data: success = self.datalab.add_signal(title, x, y) assert success, f"Failed to add signal: {title}" self.log(f"Added signal: {title}") def add_test_images(self) -> None: """Add test images to DataLab""" if self.datalab is None: return images_data = [ ("Zeros", np.zeros((100, 100))), ("Ones", np.ones((100, 100))), ("Random", np.random.random((100, 100))), ] for title, z in images_data: success = self.datalab.add_image(title, z) assert success, f"Failed to add image: {title}" self.log(f"Added image: {title}") def test_object_management(self) -> None: """Test object listing, retrieval, and manipulation""" if self.datalab is None: return # Test with signals self.datalab.set_current_panel("signal") assert self.datalab.get_current_panel() == "signal" titles = self.datalab.get_object_titles() self.log(f"Signal titles: {titles}") assert isinstance(titles, list), "Titles should be a list" uuids = self.datalab.get_object_uuids() self.log(f"Signal UUIDs: {uuids}") assert isinstance(uuids, list), "UUIDs should be a list" assert len(titles) == len(uuids), "Should have equal number of titles and UUIDs" if titles: # Test getting first object obj = self.datalab.get_object(1) # Get first object assert obj is not None, "Should be able to retrieve first object" assert hasattr(obj, "title"), "Object should have title attribute" self.log(f"Retrieved object: {obj.title}") # Test getting object by UUID first_uuid = uuids[0] obj_by_uuid = self.datalab.get_object(first_uuid) assert obj_by_uuid is not None, "Should retrieve object by UUID" assert obj_by_uuid.title == obj.title, "Objects should be the same" # Test with images self.datalab.set_current_panel("image") assert self.datalab.get_current_panel() == "image" img_titles = self.datalab.get_object_titles() self.log(f"Image titles: {img_titles}") if img_titles: img_obj = self.datalab.get_object(1) assert img_obj is not None, "Should retrieve first image" self.log(f"Retrieved image: {img_obj.title}") def test_selection_operations(self) -> None: """Test object selection operations""" if self.datalab is None: return # Test selecting objects self.datalab.set_current_panel("signal") uuids = self.datalab.get_object_uuids() if uuids: # Select first object self.datalab.select_objects([uuids[0]]) selected = self.datalab.get_sel_object_uuids() assert uuids[0] in selected, "Should have selected the object" self.log(f"Selected object: {uuids[0]}") # Test selecting multiple objects if available if len(uuids) > 1: self.datalab.select_objects([uuids[0], uuids[1]]) selected = self.datalab.get_sel_object_uuids() assert len(selected) == 2, "Should have selected 2 objects" def test_annotations_and_shapes(self) -> None: """Test annotation and shape operations""" if self.datalab is None: return # pylint: disable=import-outside-toplevel from plotpy.builder import make # Test with images (annotations are more meaningful for images) self.datalab.set_current_panel("image") uuids = self.datalab.get_object_uuids() if uuids: # Add an annotation rect = make.annotated_rectangle(10, 10, 50, 50, title="Test Rectangle") self.datalab.add_annotations_from_items([rect]) self.log("Added annotation rectangle") # Retrieve shapes shapes = self.datalab.get_object_shapes() assert isinstance(shapes, list), "Shapes should be a list" self.log(f"Retrieved {len(shapes)} shapes") # Add label self.datalab.add_label_with_title("Test Label") self.log("Added label with title") def test_file_operations(self) -> None: """Test file save/load operations""" if self.datalab is None: return with temporary_directory() as tmpdir: # Save to HDF5 file fname = osp.join(tmpdir, "test_remote.h5") self.datalab.save_to_h5_file(fname) self.log(f"Saved data to: {fname}") assert osp.exists(fname), "HDF5 file should exist" # Clear all data self.datalab.reset_all() self.log("Reset all data") # Verify data is cleared titles = self.datalab.get_object_titles("signal") assert len(titles) == 0, "Signal panel should be empty after reset" # Reload from file self.datalab.open_h5_files([fname], import_all=True, reset_all=False) self.log("Reloaded data from HDF5 file") # Verify data is restored titles = self.datalab.get_object_titles("signal") assert len(titles) > 0, "Should have signals after reload" def test_workspace_headless_api(self) -> None: """Test load_h5_workspace and save_h5_workspace headless API (Issue #275)""" if self.datalab is None: return with temporary_directory() as tmpdir: # First add some data self.add_test_signals() self.add_test_images() # Save workspace using headless API fname = osp.join(tmpdir, "test_workspace.h5") self.datalab.save_h5_workspace(fname) self.log(f"Saved workspace to: {fname}") assert osp.exists(fname), "Workspace file should exist" # Clear all data self.datalab.reset_all() titles = self.datalab.get_object_titles("signal") assert len(titles) == 0, "Signal panel should be empty after reset" # Load workspace using headless API self.datalab.load_h5_workspace([fname], reset_all=True) self.log("Loaded workspace from file") # Verify data is restored titles = self.datalab.get_object_titles("signal") assert len(titles) > 0, "Should have signals after load_h5_workspace" self.log(f"Workspace loaded with {len(titles)} signals") # Test with single file path (string instead of list) self.datalab.reset_all() self.datalab.load_h5_workspace(fname, reset_all=True) titles = self.datalab.get_object_titles("signal") assert len(titles) > 0, "Should work with single file path string" self.log("load_h5_workspace works with single file path") def test_computation_operations(self) -> None: """Test computation operations""" if self.datalab is None: return # Test signal computations self.datalab.set_current_panel("signal") uuids = self.datalab.get_object_uuids() if uuids: # Select first signal self.datalab.select_objects([uuids[0]]) # Test some basic computations try: self.datalab.calc("log10") self.log("Applied log10 computation") except Exception as exc: # pylint: disable=broad-except self.log(f"log10 computation failed: {exc}") try: self.datalab.calc("fft") self.log("Applied FFT computation") except Exception as exc: # pylint: disable=broad-except self.log(f"FFT computation failed: {exc}") def test_group_operations(self) -> None: """Test group operations""" if self.datalab is None: return # Add a group self.datalab.add_group("Test Group", panel="signal") self.log("Added test group") # Get group information group_info = self.datalab.get_group_titles_with_object_info() assert isinstance(group_info, (list, tuple)), ( "Group info should be a list or tuple" ) assert len(group_info) == 3, "Should have 3 elements (titles, uuids, titles)" self.log(f"Groups: {group_info[0]}") def test_metadata_operations(self) -> None: """Test metadata operations""" if self.datalab is None: return uuids = self.datalab.get_object_uuids() if uuids: # Select an object self.datalab.select_objects([uuids[0]]) # Delete metadata self.datalab.delete_metadata(refresh_plot=False, keep_roi=False) self.log("Deleted metadata") def run_comprehensive_test(self) -> None: """Run all tests in sequence""" self.log("Starting comprehensive remote client test") try: # Basic connection test self.test_connection_management() # Add test data self.add_test_signals() self.add_test_images() # Test object management self.test_object_management() # Test selection operations self.test_selection_operations() # Test annotations and shapes try: self.test_annotations_and_shapes() except ImportError: self.log("PlotPy not available, skipping annotations and shapes test") # Test computations self.test_computation_operations() # Test group operations self.test_group_operations() # Test metadata operations self.test_metadata_operations() # Test file operations (this will reset data) self.test_file_operations() # Test workspace headless API (Issue #275) self.test_workspace_headless_api() self.log("✅ All tests completed successfully!") finally: # Always try to clean up try: self.datalab.reset_all() self.log("Final cleanup: reset all data") except Exception: # pylint: disable=broad-except pass def test_comprehensive_remote_client(): """Comprehensive remote client test (pytest version)""" # First try with stub server (always available) with datalab_stub_server() as port: tester = RemoteClientTester() if tester.init_cdl_with_stub(port): try: tester.run_comprehensive_test() return # Test passed with stub server finally: tester.close_datalab() # If stub server test failed, try with real DataLab tester = RemoteClientTester() if not tester.init_cdl(): pytest.skip("Neither stub server nor real DataLab server is available") try: tester.run_comprehensive_test() finally: tester.close_datalab() if __name__ == "__main__": test_comprehensive_remote_client() Sigima-1.1.1/sigima/tests/common/converters_unit_test.py000066400000000000000000000060561514013333200234720ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Unit tests for I/O conversion functions """ from __future__ import annotations import numpy as np import pytest from sigima.io.common import converters from sigima.objects.image import ImageObj from sigima.objects.signal import SignalObj class TestConvertArrayToValidDType: """Test suite for convert_array_to_valid_dtype function.""" def test_int_arrays(self) -> None: """Test conversion of integer numpy arrays.""" arr = np.array([1.0, 2.0, 3.0], dtype=np.int32) result = converters.convert_array_to_valid_dtype(arr, SignalObj.VALID_DTYPES) assert isinstance(result, np.ndarray) assert result.dtype == np.float32 np.testing.assert_array_almost_equal(result, arr, decimal=6) arr = np.array([[1, 2, 3], [1.1, 2, 3]], dtype=np.uint32) result = converters.convert_array_to_valid_dtype(arr, ImageObj.VALID_DTYPES) assert isinstance(result, np.ndarray) assert result.dtype == np.uint8 np.testing.assert_array_almost_equal(result, arr, decimal=6) arr = np.array([[1, 2, 3], [1.1, 2, 1e8]], dtype=np.uint32) result = converters.convert_array_to_valid_dtype(arr, ImageObj.VALID_DTYPES) assert isinstance(result, np.ndarray) assert result.dtype == np.int32 np.testing.assert_array_almost_equal(result, arr, decimal=6) def test_float_arrays(self) -> None: """Test conversion of float numpy arrays.""" arr = np.array([1.1, 2.2, 3.3], dtype=np.float32) result = converters.convert_array_to_valid_dtype(arr, SignalObj.VALID_DTYPES) assert isinstance(result, np.ndarray) assert result.dtype == np.float32 np.testing.assert_array_almost_equal(result, arr, decimal=6) arr = np.array([[1.1, 2.2, 3.3], [1.1, 2.2, 3.3]], dtype=np.float64) result = converters.convert_array_to_valid_dtype(arr, ImageObj.VALID_DTYPES) assert isinstance(result, np.ndarray) assert result.dtype == np.float64 np.testing.assert_array_almost_equal(result, arr, decimal=6) def test_bool_arrays(self) -> None: """Test conversion of boolean numpy arrays.""" arr = np.array([True, False, True], dtype=np.bool_) result = converters.convert_array_to_valid_dtype(arr, SignalObj.VALID_DTYPES) assert isinstance(result, np.ndarray) assert result.dtype == np.uint8 def test_empty_arrays(self) -> None: """Test conversion of empty numpy arrays.""" arr = np.array([], dtype=np.float32) result = converters.convert_array_to_valid_dtype(arr, SignalObj.VALID_DTYPES) assert isinstance(result, np.ndarray) assert result.size == 0 def test_invalid_input_type(self) -> None: """Test that invalid input types raise TypeError.""" with pytest.raises(TypeError): converters.convert_array_to_valid_dtype( "not an array", SignalObj.VALID_DTYPES ) if __name__ == "__main__": pytest.main([__file__]) Sigima-1.1.1/sigima/tests/common/decorator_unit_test.py000066400000000000000000000146741514013333200232670ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Testing the decorator for computation functions. This test checks: - The decorator can be applied to a function - The function can be called with and without DataSet parameters - The metadata is correctly set and can be introspected """ from __future__ import annotations import guidata.dataset as gds import numpy as np import pytest from sigima.objects import ImageObj, SignalObj, create_image, create_signal from sigima.proc.base import dst_1_to_1 from sigima.proc.decorator import ( computation_function, get_computation_metadata, is_computation_function, ) from sigima.tests.helpers import check_array_result def this_is_not_a_computation_function() -> None: """A dummy function that is not a computation function.""" def test_non_computation_function_marker() -> None: """Test that a non-computation function is not marked as such.""" assert not is_computation_function(this_is_not_a_computation_function) with pytest.raises(ValueError): get_computation_metadata(this_is_not_a_computation_function) class DummySignalParam(gds.DataSet): """Dummy DataSet for testing purposes""" a = gds.FloatItem("X value", default=1.0) b = gds.FloatItem("Y value", default=5.0) methods = (("linear", "Linear"), ("quadratic", "Quadratic")) method = gds.ChoiceItem("Method", choices=methods, default="linear") SCF_NAME = "dummy_signal_func" SCF_DESCRIPTION = "A dummy signal function" @computation_function(name=SCF_NAME, description=SCF_DESCRIPTION) def dummy_signal_func(src: SignalObj, p: DummySignalParam) -> SignalObj: """A dummy function that adds two parameters from a DataSet. Args: src: The source SignalObj. param: The parameters from the DummySignalParam DataSet. Returns: The signal with the operation applied. """ dst = dst_1_to_1(src, SCF_NAME, f"x={p.a:.3f}, y={p.b:.3f}") if p.method == "linear": dst.y = src.y + src.x * p.a + p.b else: # Quadratic method dst.y = src.y + src.x**2 * p.a + p.b return dst class DummyImageParam(gds.DataSet): """Dummy DataSet for testing purposes""" alpha = gds.FloatItem("Alpha value", default=0.5) ICF_NAME = "dummy_image_func" ICF_DESCRIPTION = "A dummy image function" @computation_function(name=ICF_NAME, description=ICF_DESCRIPTION) def dummy_image_func(src: ImageObj, param: DummyImageParam) -> ImageObj: """A dummy function that applies a simple operation based on a DataSet parameter. Args: src: The source ImageObj. param: The parameters from the DummyImageParam DataSet. Returns: The image with the operation applied. """ dst = dst_1_to_1(src, ICF_NAME, f"sigma={param.alpha:.3f}") dst.data = src.data * param.alpha # Simplified operation for testing return dst def test_signal_decorator_marker() -> None: """Test the computation function decorator marker for signals""" # Check if the function is marked as a computation function assert is_computation_function(dummy_signal_func) def test_signal_decorator_metadata() -> None: """Test the computation function decorator metadata for signals""" # Check if the metadata is correctly set metadata = get_computation_metadata(dummy_signal_func) assert metadata.name == SCF_NAME assert metadata.description == SCF_DESCRIPTION def test_signal_decorator_signature() -> None: """Test the computation function decorator signature for signals""" x = np.linspace(0, 10, 100) orig = create_signal("test_signal", x=x, y=x) # Call the function with a DataSet parameter p = DummySignalParam.create(a=3.0, b=4.0, method="quadratic") res_ds = dummy_signal_func(orig, p) name = "Signal[DataSet parameter]" check_array_result(f"{name} x", res_ds.x, orig.x) check_array_result(f"{name} y", res_ds.y, orig.y + orig.x**2 * 3.0 + 4.0) # Call the function with keyword arguments # pylint: disable=no-value-for-parameter res_kw = dummy_signal_func(orig, a=3.0, b=4.0) name = "Signal[keyword arguments]" check_array_result(f"{name} x", res_kw.x, orig.x) check_array_result(f"{name} y", res_kw.y, orig.y + orig.x * 3.0 + 4.0) # Call the function with both DataSet and keyword arguments # The DataSet should take precedence, kwargs for DataSet items are ignored res_both = dummy_signal_func(orig, p, a=100.0, b=200.0, method="linear") # The result should match the DataSet values, not the conflicting kwargs check_array_result( "Signal[DataSet param + kwargs: DataSet wins] x", res_both.x, orig.x ) check_array_result( "Signal[DataSet param + kwargs: DataSet wins] y", res_both.y, orig.y + orig.x**2 * 3.0 + 4.0, ) def test_image_decorator_marker() -> None: """Test the computation function decorator marker for images""" # Check if the function is marked as a computation function assert is_computation_function(dummy_image_func) def test_image_decorator_metadata() -> None: """Test the computation function decorator metadata for images""" # Check if the metadata is correctly set metadata = get_computation_metadata(dummy_image_func) assert metadata.name == ICF_NAME assert metadata.description == ICF_DESCRIPTION def test_image_decorator_signature() -> None: """Test the computation function decorator signature for images""" orig = create_image("test_image", data=np.random.rand(64, 64)) # Call the function with an ImageObj and DummyImageParam p = DummyImageParam.create(alpha=0.8) res_ds = dummy_image_func(orig, p) check_array_result("Image data", res_ds.data, orig.data * p.alpha) # Call the function with keyword arguments # pylint: disable=no-value-for-parameter res_kw = dummy_image_func(orig, alpha=0.8) check_array_result("Image data", res_kw.data, orig.data * 0.8) # Call the function with both DataSet and keyword arguments # The DataSet should take precedence, kwargs for DataSet items are ignored res_both = dummy_image_func(orig, p, alpha=0.4) check_array_result( "Image data [DataSet param + kwargs: DataSet wins]", res_both.data, orig.data * p.alpha, ) if __name__ == "__main__": test_signal_decorator_marker() test_signal_decorator_metadata() test_signal_decorator_signature() test_image_decorator_marker() test_image_decorator_metadata() test_image_decorator_signature() Sigima-1.1.1/sigima/tests/common/examples_unit_test.py000066400000000000000000000060761514013333200231200ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Test for documentation examples This module automatically discovers and executes all Python files in the doc/examples directory to ensure they run without errors. """ from __future__ import annotations import importlib.util import sys from pathlib import Path import pytest import sigima from sigima.client.stub import patch_simpleremoteproxy_for_stub # Check if plotpy is available try: import plotpy # pylint: disable=unused-import # noqa: F401 PLOTPY_AVAILABLE = True except ImportError: PLOTPY_AVAILABLE = False def get_example_dir() -> Path: """Get the path to the examples directory.""" return Path(sigima.__file__).parent.parent / "doc" / "examples" def get_example_files() -> list[Path]: """Get all Python files in doc/examples directory.""" examples_dir = get_example_dir() if not examples_dir.exists(): return [] return [ f for f in examples_dir.glob("*.py") if not f.name.startswith("_") and f.name != "__init__.py" ] def test_examples_directory_exists() -> None: """Test that the examples directory exists and contains Python files.""" examples_dir = get_example_dir() assert examples_dir.exists(), "doc/examples directory should exist" python_files = list(examples_dir.rglob("*.py")) assert len(python_files) > 0, "doc/examples should contain at least one Python file" @pytest.mark.skipif(not PLOTPY_AVAILABLE, reason="PlotPy not installed") @pytest.mark.parametrize("example_file", get_example_files()) def test_example_execution(example_file: Path) -> None: """Test that each example file can be executed without errors.""" # Special handling for datalab_client.py - needs a stub server if example_file.name == "datalab_client.py": # Use the utility to patch SimpleRemoteProxy for stub server stub_server = patch_simpleremoteproxy_for_stub() try: # Load and execute the module _execute_example_module(example_file) finally: # Clean up the stub server stub_server.stop() else: # Normal execution for other examples _execute_example_module(example_file) def _execute_example_module(example_file: Path) -> None: """Execute an example module file. Args: example_file: Path to the example Python file to execute """ # Load the module spec = importlib.util.spec_from_file_location( f"example_{example_file.stem}", str(example_file) ) module = importlib.util.module_from_spec(spec) # Add the example directory to sys.path temporarily examples_dir = str(example_file.parent) if examples_dir not in sys.path: sys.path.insert(0, examples_dir) try: # Execute the module spec.loader.exec_module(module) finally: # Clean up sys.path if examples_dir in sys.path: sys.path.remove(examples_dir) if __name__ == "__main__": # Run the tests when executed directly pytest.main([__file__, "-v"]) Sigima-1.1.1/sigima/tests/common/func_name_injection_unit_test.py000066400000000000000000000022141514013333200252650ustar00rootroot00000000000000"""Test to verify func_name is systematically set by @computation_function decorator""" # Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. import sigima.objects import sigima.params import sigima.proc.signal import sigima.tests.data def test_func_name_auto_injection(): """Verify that @computation_function decorator automatically sets func_name.""" # Create a test signal obj = sigima.tests.data.get_test_signal("fwhm.txt") # Test 1: Function with parameters (fwhm) param = sigima.params.FWHMParam.create(method="gauss") result = sigima.proc.signal.fwhm(obj, param) assert result is not None assert hasattr(result, "func_name") assert result.func_name == "fwhm", f"Expected 'fwhm', got {result.func_name!r}" # Test 2: Function without parameters (fw1e2) result2 = sigima.proc.signal.fw1e2(obj) assert result2 is not None assert hasattr(result2, "func_name") assert result2.func_name == "fw1e2", f"Expected 'fw1e2', got {result2.func_name!r}" print("✓ All func_name auto-injection tests passed!") if __name__ == "__main__": test_func_name_auto_injection() Sigima-1.1.1/sigima/tests/common/kernel_normalization_unit_test.py000066400000000000000000000204751514013333200255270ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """Unit tests for kernel normalization features in convolution/deconvolution.""" from __future__ import annotations import numpy as np import pytest from sigima.config import options as sigima_options from sigima.objects import create_image, create_signal from sigima.objects.image import ImageObj from sigima.objects.signal import SignalObj from sigima.proc.image.mathops import convolution as image_convolution from sigima.proc.image.mathops import deconvolution as image_deconvolution from sigima.proc.signal import convolution as signal_convolution from sigima.proc.signal import deconvolution as signal_deconvolution def _generate_test_signal(size: int = 100) -> SignalObj: """Generate a simple test signal. Args: size: The size of the signal to generate. Returns: A signal object. """ x = np.linspace(0, 10, size) y = np.sin(x) + 0.5 * np.sin(3 * x) return create_signal("Test Signal", x, y) def _generate_unnormalized_signal_kernel(size: int = 100) -> SignalObj: """Generate an unnormalized Gaussian-like kernel for signal processing. Args: size: The size of the kernel. Returns: A signal object representing an unnormalized kernel. Notes: The kernel uses the same x-axis range and size as _generate_test_signal to ensure compatible sample rates for convolution and deconvolution. """ x = np.linspace(0, 10, size) y = np.exp(-((x - 5) ** 2) / 2) # Centered Gaussian y *= 2.0 # Make it unnormalized (sum != 1.0) return create_signal("Unnormalized Kernel", x, y) def _generate_test_image(size: int = 64) -> ImageObj: """Generate a simple test image. Args: size: The dimension of the square image to generate. Returns: An image object. """ data = np.random.rand(size, size) return create_image("Test Image", data) def _generate_unnormalized_image_kernel(size: int = 5) -> ImageObj: """Generate an unnormalized Gaussian-like kernel for image processing. Args: size: The dimension of the square kernel to generate. Returns: An image object representing an unnormalized kernel. """ kernel = np.outer( np.exp(-(np.linspace(-2, 2, size) ** 2)), np.exp(-(np.linspace(-2, 2, size) ** 2)), ) kernel *= 2.0 # Make it unnormalized (sum != 1.0) return create_image("Unnormalized Kernel", kernel) class TestKernelNormalizationSignal: """Test suite for signal kernel normalization in convolution.""" @pytest.fixture(autouse=True) def setup_and_teardown(self): """Store initial option values and restore them after each test.""" # Store initial values initial_auto_normalize = sigima_options.auto_normalize_kernel.get() yield # Restore initial values sigima_options.auto_normalize_kernel.set(initial_auto_normalize) def test_signal_convolution_auto_normalization_enabled(self): """Test that auto-normalization works correctly for convolution.""" # Setup: auto-normalization enabled sigima_options.auto_normalize_kernel.set(True) signal = _generate_test_signal() kernel = _generate_unnormalized_signal_kernel() # Execute with auto-normalization result = signal_convolution(signal, kernel) # Verify result exists and has same shape as input assert result is not None assert result.data is not None assert result.data.shape == signal.data.shape def test_signal_convolution_auto_normalization_disabled(self): """Test convolution with auto-normalization disabled.""" # Setup: auto-normalization disabled sigima_options.auto_normalize_kernel.set(False) signal = _generate_test_signal() kernel = _generate_unnormalized_signal_kernel() # Execute without auto-normalization result = signal_convolution(signal, kernel) # Verify result exists and has same shape as input assert result is not None assert result.data is not None assert result.data.shape == signal.data.shape def test_signal_deconvolution_auto_normalization_enabled(self): """Test that auto-normalization works correctly for deconvolution.""" # Setup: auto-normalization enabled sigima_options.auto_normalize_kernel.set(True) signal = _generate_test_signal() kernel = _generate_unnormalized_signal_kernel() # Execute with auto-normalization result = signal_deconvolution(signal, kernel) # Verify result exists and has same shape as input assert result is not None assert result.data is not None assert result.data.shape == signal.data.shape def test_signal_deconvolution_auto_normalization_disabled(self): """Test deconvolution with auto-normalization disabled.""" # Setup: auto-normalization disabled sigima_options.auto_normalize_kernel.set(False) signal = _generate_test_signal() kernel = _generate_unnormalized_signal_kernel() # Execute without auto-normalization result = signal_deconvolution(signal, kernel) # Verify result exists and has same shape as input assert result is not None assert result.data is not None assert result.data.shape == signal.data.shape class TestKernelNormalizationImage: """Test suite for image kernel normalization in convolution and deconvolution.""" @pytest.fixture(autouse=True) def setup_and_teardown(self): """Store initial option values and restore them after each test.""" # Store initial values initial_auto_normalize = sigima_options.auto_normalize_kernel.get() yield # Restore initial values sigima_options.auto_normalize_kernel.set(initial_auto_normalize) def test_image_convolution_auto_normalization_enabled(self): """Test that auto-normalization works correctly for convolution.""" # Setup: auto-normalization enabled sigima_options.auto_normalize_kernel.set(True) image = _generate_test_image() kernel = _generate_unnormalized_image_kernel() # Execute with auto-normalization result = image_convolution(image, kernel) # Verify result exists and has same shape as input assert result is not None assert result.data is not None assert result.data.shape == image.data.shape def test_image_convolution_auto_normalization_disabled(self): """Test convolution with auto-normalization disabled.""" # Setup: auto-normalization disabled sigima_options.auto_normalize_kernel.set(False) image = _generate_test_image() kernel = _generate_unnormalized_image_kernel() # Execute without auto-normalization result = image_convolution(image, kernel) # Verify result exists and has same shape as input assert result is not None assert result.data is not None assert result.data.shape == image.data.shape def test_image_deconvolution_auto_normalization_enabled(self): """Test that auto-normalization works correctly for deconvolution.""" # Setup: auto-normalization enabled sigima_options.auto_normalize_kernel.set(True) image = _generate_test_image() kernel = _generate_unnormalized_image_kernel() # Execute with auto-normalization result = image_deconvolution(image, kernel) # Verify result exists and has same shape as input assert result is not None assert result.data is not None assert result.data.shape == image.data.shape def test_image_deconvolution_auto_normalization_disabled(self): """Test deconvolution with auto-normalization disabled.""" # Setup: auto-normalization disabled sigima_options.auto_normalize_kernel.set(False) image = _generate_test_image() kernel = _generate_unnormalized_image_kernel() # Execute without auto-normalization result = image_deconvolution(image, kernel) # Verify result exists and has same shape as input assert result is not None assert result.data is not None assert result.data.shape == image.data.shape if __name__ == "__main__": pytest.main([__file__, "-v"]) Sigima-1.1.1/sigima/tests/common/roi_basic_unit_test.py000066400000000000000000000042461514013333200232310ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ ROI basic unit tests """ # pylint: disable=invalid-name # Allows short reference names like x, y, ... # guitest: show from __future__ import annotations import sigima.objects from sigima.tests.data import ( create_multigaussian_image, create_paracetamol_signal, create_test_image_rois, create_test_signal_rois, ) from sigima.tests.env import execenv def __conversion_methods( roi: sigima.objects.SignalROI | sigima.objects.ImageROI, obj: sigima.objects.SignalObj | sigima.objects.ImageObj, ) -> None: """Test conversion methods for single ROI objects""" execenv.print(" test `to_dict` and `from_dict` methods") roi_dict = roi.to_dict() roi_new = obj.get_roi_class().from_dict(roi_dict) assert roi.get_single_roi(0) == roi_new.get_single_roi(0) def test_signal_roi_creation() -> None: """Test signal ROI creation and conversion methods""" obj = create_paracetamol_signal() for roi in create_test_signal_rois(obj): __conversion_methods(roi, obj) def test_image_roi_creation() -> None: """Test image ROI creation and conversion methods""" obj = create_multigaussian_image() # Update to use new coordinate API instead of setting dx/dy directly if obj.data is not None: obj.set_uniform_coords(0.035, 0.035) for roi in create_test_image_rois(obj): __conversion_methods(roi, obj) def test_image_roi_modification() -> None: """Test image ROI modification methods""" obj = create_multigaussian_image() roi = list(create_test_image_rois(obj))[0] # Set image's ROI obj.roi = roi assert obj.roi == roi nb_single_rois = len(roi.single_rois) # Modify the ROI directly from the image's ROI attribute # (for example, we try to remove a single ROI) old_single_roi = obj.roi.single_rois.pop(0) assert len(obj.roi.single_rois) == nb_single_rois - 1 # Add it back obj.roi.add_roi(old_single_roi) assert len(obj.roi.single_rois) == nb_single_rois if __name__ == "__main__": test_signal_roi_creation() test_image_roi_creation() test_image_roi_modification() Sigima-1.1.1/sigima/tests/common/roi_geometry_unit_test.py000066400000000000000000000124571514013333200240060ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """Test ROI geometry transformations""" import numpy as np from sigima.objects.image import ImageObj, ImageROI, RectangularROI from sigima.proc.image import fliph, flipv, rotate90, rotate270, transpose from sigima.tests.env import execenv def test_roi_rotate90() -> None: """Test ROI transformation with 90° rotation.""" # Create test image data = np.random.rand(100, 80) # Height=100, Width=80 img = ImageObj(title="Test Image") img.data = data # Create rectangular ROI roi_obj = ImageROI() single_roi = RectangularROI([10, 20, 20, 20], indices=False) # x0, y0, dx, dy roi_obj.add_roi(single_roi) img.roi = roi_obj # Apply rotation img_rotated = rotate90(img) roi_rotated = img_rotated.roi.single_rois[0] # Verify ROI is properly transformed and dimensions change assert img_rotated.roi is not None, "90° rotation should preserve ROI object" assert len(img_rotated.roi.single_rois) == 1, ( "90° rotation should preserve ROI count" ) # The exact coordinates depend on the transformation, but the ROI should be valid coords_rotated = roi_rotated.get_physical_coords(img_rotated) assert len(coords_rotated) == 4, "Rectangular ROI should have 4 coordinates" def test_roi_rotate270() -> None: """Test ROI transformation with 270° rotation.""" # Create test image data = np.random.rand(100, 80) img = ImageObj(title="Test Image") img.data = data # Create rectangular ROI roi_obj = ImageROI() single_roi = RectangularROI([10, 20, 20, 20], indices=False) roi_obj.add_roi(single_roi) img.roi = roi_obj # Apply rotation img_rotated = rotate270(img) # Verify ROI is properly transformed assert img_rotated.roi is not None, "270° rotation should preserve ROI object" assert len(img_rotated.roi.single_rois) == 1, ( "270° rotation should preserve ROI count" ) def test_roi_fliph() -> None: """Test ROI transformation with horizontal flip.""" # Create test image data = np.random.rand(100, 80) img = ImageObj(title="Test Image") img.data = data # Create rectangular ROI roi_obj = ImageROI() single_roi = RectangularROI([10, 20, 20, 20], indices=False) roi_obj.add_roi(single_roi) img.roi = roi_obj # Apply flip img_flipped = fliph(img) # Verify ROI is properly transformed assert img_flipped.roi is not None, "Horizontal flip should preserve ROI object" assert len(img_flipped.roi.single_rois) == 1, ( "Horizontal flip should preserve ROI count" ) def test_roi_flipv() -> None: """Test ROI transformation with vertical flip.""" # Create test image data = np.random.rand(100, 80) img = ImageObj(title="Test Image") img.data = data # Create rectangular ROI roi_obj = ImageROI() single_roi = RectangularROI([10, 20, 20, 20], indices=False) roi_obj.add_roi(single_roi) img.roi = roi_obj # Apply flip img_flipped = flipv(img) # Verify ROI is properly transformed assert img_flipped.roi is not None, "Vertical flip should preserve ROI object" assert len(img_flipped.roi.single_rois) == 1, ( "Vertical flip should preserve ROI count" ) def test_roi_transpose() -> None: """Test ROI transformation with transpose.""" # Create test image data = np.random.rand(100, 80) img = ImageObj(title="Test Image") img.data = data # Create rectangular ROI roi_obj = ImageROI() single_roi = RectangularROI([10, 20, 20, 20], indices=False) roi_obj.add_roi(single_roi) img.roi = roi_obj # Apply transpose img_transposed = transpose(img) # Verify ROI is properly transformed assert img_transposed.roi is not None, "Transpose should preserve ROI object" assert len(img_transposed.roi.single_rois) == 1, ( "Transpose should preserve ROI count" ) def test_roi_comprehensive() -> None: """Comprehensive test for all ROI transformations.""" execenv.print("Testing ROI geometry transformations:") # Create test image data = np.random.rand(100, 80) # Height=100, Width=80 img = ImageObj(title="Test Image") img.data = data # Create rectangular ROI roi_obj = ImageROI() single_roi = RectangularROI([10, 20, 20, 20], indices=False) roi_obj.add_roi(single_roi) img.roi = roi_obj coords_original = single_roi.get_physical_coords(img) execenv.print(f" Original ROI: {coords_original}") # Test all transformations transformations = [ (rotate90, "rotate90"), (rotate270, "rotate270"), (fliph, "fliph"), (flipv, "flipv"), (transpose, "transpose"), ] for transform_func, name in transformations: img_transformed = transform_func(img) roi_transformed = img_transformed.roi.single_rois[0] coords_transformed = roi_transformed.get_physical_coords(img_transformed) execenv.print(f" {name}: {coords_transformed}") # Verify ROI is properly transformed assert img_transformed.roi is not None, f"{name} should preserve ROI object" assert len(img_transformed.roi.single_rois) == 1, ( f"{name} should preserve ROI count" ) execenv.print(" ✅ All ROI transformations working correctly") Sigima-1.1.1/sigima/tests/common/scalar_builder_unit_test.py000066400000000000000000000212211514013333200242420ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Unit tests for TableResultBuilder (sigima.objects.scalar). """ from numpy import ma from sigima.objects import ( NO_ROI, SignalObj, TableKind, TableResultBuilder, create_signal_roi, ) from sigima.tests.data import create_paracetamol_signal, create_test_signal_rois def create_dummy_signal() -> SignalObj: """Create a simple SignalObj with a single ROI.""" sig = create_paracetamol_signal() roi = list(create_test_signal_rois(sig))[0] sig.roi = roi return sig class TestTableResultBuilder: """Test class for TableResultBuilder basic functionality.""" def test_basic_functionality(self) -> None: """Test basic TableResultBuilder API with a SignalObj.""" sig = create_dummy_signal() builder = TableResultBuilder("Signal Stats") builder.add(ma.min, "min") builder.add(ma.max, "max") builder.add(ma.mean, "mean") table = builder.compute(sig) assert table.title == "Signal Stats" # [None, ROI_0] x 3 stats assert len(table.data) == 2 and len(table.data[0]) == 3 assert list(table.headers) == ["min", "max", "mean"] assert table.roi_indices[0] == -1 # NO_ROI assert table.roi_indices[1] == 0 # Check actual values row_none = table.data[0] row_roi = table.data[1] assert isinstance(row_none[0], float) assert isinstance(row_roi[1], float) class TestTableResultBuilderHideColumns: """Test class for TableResultBuilder hide_columns functionality.""" def setup_method(self) -> None: """Set up test data for each test method.""" # pylint: disable=attribute-defined-outside-init self.sig = create_dummy_signal() def _create_basic_builder(self) -> TableResultBuilder: """Helper method to create a basic builder with standard columns.""" builder = TableResultBuilder("Signal Stats") builder.add(ma.min, "min") builder.add(ma.max, "max") builder.add(ma.mean, "mean") builder.add(ma.std, "std") return builder def _assert_display_preferences( self, table, expected_prefs: dict[str, bool] ) -> None: """Helper method to check display preferences and visible headers.""" prefs = table.get_display_preferences() assert prefs == expected_prefs expected_visible = [name for name, visible in expected_prefs.items() if visible] visible_headers = table.get_visible_headers() assert set(visible_headers) == set(expected_visible) def test_hide_some_columns(self) -> None: """Test hiding some columns.""" builder = self._create_basic_builder() builder.hide_columns(["max", "std"]) table = builder.compute(self.sig) assert table.title == "Signal Stats" # All headers still present assert list(table.headers) == ["min", "max", "mean", "std"] self._assert_display_preferences( table, {"min": True, "max": False, "mean": True, "std": False} ) def test_hide_nonexistent_columns(self) -> None: """Test hiding non-existent columns.""" builder = TableResultBuilder("Signal Stats") builder.add(ma.min, "min") builder.add(ma.max, "max") # Try to hide non-existent column - should not cause error builder.hide_columns(["nonexistent", "min"]) table = builder.compute(self.sig) self._assert_display_preferences(table, {"min": False, "max": True}) def test_hide_empty_list(self) -> None: """Test hiding empty list of columns.""" builder = TableResultBuilder("Signal Stats") builder.add(ma.min, "min") builder.add(ma.max, "max") builder.hide_columns([]) table = builder.compute(self.sig) self._assert_display_preferences(table, {"min": True, "max": True}) def test_hide_multiple_calls(self) -> None: """Test multiple hide_columns calls accumulate.""" builder = self._create_basic_builder() # Hide columns in multiple calls builder.hide_columns(["max"]) builder.hide_columns(["std"]) table = builder.compute(self.sig) self._assert_display_preferences( table, {"min": True, "max": False, "mean": True, "std": False} ) def test_hide_all_columns(self) -> None: """Test hiding all columns.""" builder = TableResultBuilder("Signal Stats") builder.add(ma.min, "min") builder.add(ma.max, "max") builder.hide_columns(["min", "max"]) table = builder.compute(self.sig) self._assert_display_preferences(table, {"min": False, "max": False}) class TestTableResultBuilderROIComputationModes: """Test class for TableResultBuilder ROI computation modes.""" def setup_method(self) -> None: """Set up test data for each test method.""" # pylint: disable=attribute-defined-outside-init # Create signal with multiple ROIs (3 segments) self.sig = create_paracetamol_signal() # Create a ROI with 3 segments manually roi = create_signal_roi([[10, 20], [30, 40], [50, 60]], indices=False) self.sig.roi = roi def test_statistics_computes_whole_and_rois(self) -> None: """Test STATISTICS kind computes both whole object and ROIs.""" builder = TableResultBuilder("Signal Statistics", kind=TableKind.STATISTICS) builder.add(ma.min, "min") builder.add(ma.max, "max") table = builder.compute(self.sig) # Should have results for whole object (NO_ROI) + 3 ROIs = 4 rows assert len(table.data) == 4 assert table.roi_indices[0] == NO_ROI # First row is whole object assert table.roi_indices[1] == 0 # Then ROI 0 assert table.roi_indices[2] == 1 # Then ROI 1 assert table.roi_indices[3] == 2 # Then ROI 2 def test_pulse_features_computes_only_rois(self) -> None: """Test PULSE_FEATURES kind computes ONLY ROIs when they exist.""" builder = TableResultBuilder("Pulse Features", kind=TableKind.PULSE_FEATURES) builder.add(ma.min, "min") builder.add(ma.max, "max") table = builder.compute(self.sig) # Should have results ONLY for ROIs (no whole object), so 3 rows assert len(table.data) == 3 assert table.roi_indices[0] == 0 # First row is ROI 0 assert table.roi_indices[1] == 1 # Then ROI 1 assert table.roi_indices[2] == 2 # Then ROI 2 # Verify NO_ROI is not present assert NO_ROI not in table.roi_indices def test_pulse_features_computes_whole_when_no_rois(self) -> None: """Test PULSE_FEATURES kind computes whole object when no ROIs exist.""" # Remove ROI from signal sig_no_roi = create_paracetamol_signal() builder = TableResultBuilder("Pulse Features", kind=TableKind.PULSE_FEATURES) builder.add(ma.min, "min") builder.add(ma.max, "max") table = builder.compute(sig_no_roi) # Should have result for whole object only (1 row) assert len(table.data) == 1 assert table.roi_indices[0] == NO_ROI def test_custom_kind_default_behavior(self) -> None: """Test CUSTOM kind uses default behavior (whole + ROIs like STATISTICS).""" builder = TableResultBuilder("Custom Results", kind=TableKind.CUSTOM) builder.add(ma.min, "min") builder.add(ma.max, "max") table = builder.compute(self.sig) # Should have results for whole object + ROIs = 4 rows (same as STATISTICS) assert len(table.data) == 4 assert table.roi_indices[0] == NO_ROI assert table.roi_indices[1] == 0 assert table.roi_indices[2] == 1 assert table.roi_indices[3] == 2 def test_string_kind_pulse_features(self) -> None: """Test using string 'pulse_features' as kind value.""" builder = TableResultBuilder("Pulse Features", kind="pulse_features") builder.add(ma.min, "min") builder.add(ma.max, "max") table = builder.compute(self.sig) # Should behave like PULSE_FEATURES enum: only ROIs, no whole object assert len(table.data) == 3 assert NO_ROI not in table.roi_indices def test_string_kind_statistics(self) -> None: """Test using string 'statistics' as kind value.""" builder = TableResultBuilder("Signal Statistics", kind="statistics") builder.add(ma.min, "min") builder.add(ma.max, "max") table = builder.compute(self.sig) # Should behave like STATISTICS enum: whole + ROIs assert len(table.data) == 4 assert table.roi_indices[0] == NO_ROI Sigima-1.1.1/sigima/tests/common/scalar_unit_test.py000066400000000000000000001416751514013333200225540ustar00rootroot00000000000000# Copyright (c) DataLab Platform Developers, BSD 3-Clause license, see LICENSE file. """ Unit tests for scalar computation functions (GeometryResult transformations). """ from __future__ import annotations import numpy as np import pandas as pd import pytest from sigima.objects import ( NO_ROI, GeometryResult, KindShape, TableResult, calc_table_from_data, concat_geometries, concat_tables, filter_geometry_by_roi, filter_table_by_roi, ) from sigima.proc.image import transformer def create_rectangle(x0=0.0, y0=0.0, w=1.0, h=1.0) -> GeometryResult: """Create a simple rectangle GeometryResult.""" coords = np.array([[x0, y0, w, h]], dtype=float) return GeometryResult("rect", "rectangle", coords) class TestGeometryTransformations: """Test class for geometry transformation functions.""" def test_rotate(self) -> None: """Test rotation of a rectangle geometry result.""" rect = create_rectangle(0.0, 0.0, 1.0, 2.0) rotated = transformer.rotate(rect, np.pi / 2, center=(0.5, 1.0)) expected_coords = np.array([[-0.5, 0.5, 2.0, 1.0]]) assert rotated.coords.shape == rect.coords.shape assert np.allclose(rotated.coords, expected_coords) def test_fliph(self) -> None: """Test horizontal flip and its reversibility.""" rect = create_rectangle(1.0, 2.0, 2.0, 3.0) flipped = transformer.fliph(rect, cx=2.0) flipped_back = transformer.fliph(flipped, cx=2.0) np.testing.assert_allclose(flipped_back.coords, rect.coords, rtol=1e-12) def test_flipv(self) -> None: """Test vertical flip and its reversibility.""" rect = create_rectangle(1.0, 2.0, 2.0, 3.0) flipped = transformer.flipv(rect, cy=3.5) flipped_back = transformer.flipv(flipped, cy=3.5) np.testing.assert_allclose(flipped_back.coords, rect.coords, rtol=1e-12) def test_translate(self) -> None: """Test translation of a geometry result.""" rect = create_rectangle() translated = transformer.translate(rect, 1.5, -2.0) expected = rect.coords + np.array([1.5, -2.0, 0.0, 0.0]) np.testing.assert_allclose(translated.coords, expected, rtol=1e-12) def test_scale(self) -> None: """Test scaling and inverse scaling of a geometry result.""" rect = create_rectangle(1.0, 1.0, 2.0, 2.0) scaled = transformer.scale(rect, 2.0, 0.5, center=(2.0, 2.0)) unscaled = transformer.scale(scaled, 0.5, 2.0, center=(2.0, 2.0)) np.testing.assert_allclose(unscaled.coords, rect.coords, rtol=1e-12) def test_transpose(self) -> None: """Test transpose and double-transpose (should restore original).""" rect = create_rectangle(1.0, 2.0, 3.0, 4.0) transposed = transformer.transpose(rect) transposed_back = transformer.transpose(transposed) np.testing.assert_allclose(transposed_back.coords, rect.coords, rtol=1e-12) class TestTableResultInitialization: """Test class for TableResult initialization and validation.""" def test_init_valid(self) -> None: """Test TableResult initialization with valid data.""" data = [[1.0, 2.0], [3.0, 4.0]] roi_indices = [0, 1] table = TableResult( title="Test Table", headers=["col1", "col2"], data=data, roi_indices=roi_indices, attrs={"method": "test"}, ) assert table.title == "Test Table" assert list(table.headers) == ["col1", "col2"] assert table.data == data assert table.roi_indices == roi_indices assert table.attrs == {"method": "test"} def test_init_invalid_title(self) -> None: """Test TableResult initialization with invalid title.""" with pytest.raises(ValueError, match="title must be a non-empty string"): TableResult(title="", headers=["col"], data=[[1]]) def test_init_invalid_names(self) -> None: """Test TableResult initialization with invalid headers.""" with pytest.raises(ValueError, match="names must be a sequence of strings"): TableResult(title="Test", headers=[1, 2], data=[[1, 2]]) def test_init_invalid_data_shape(self) -> None: """Test TableResult initialization with invalid data shape.""" with pytest.raises(ValueError, match="data must be a list of lists"): TableResult(title="Test", headers=["col"], data=[1, 2, 3]) def test_init_invalid_data_columns(self) -> None: """Test TableResult initialization with mismatched data columns.""" with pytest.raises(ValueError, match="data columns must match names length"): TableResult(title="Test", headers=["col1", "col2"], data=[[1, 2, 3]]) def test_init_invalid_roi_indices(self) -> None: """Test TableResult initialization with mismatched ROI indices length.""" with pytest.raises( ValueError, match="roi_indices length must match number of data rows" ): TableResult( title="Test", headers=["col1", "col2"], data=[[1, 2], [3, 4]], roi_indices=[0], ) def test_init_invalid_roi_indices_type(self) -> None: """Test TableResult initialization with invalid roi_indices type.""" with pytest.raises(ValueError, match="roi_indices must be a list if provided"): TableResult( title="Test", headers=["col1", "col2"], data=[[1, 2], [3, 4]], roi_indices=(0, 1), ) def test_init_invalid_roi_indices_2d(self) -> None: """Test TableResult initialization with 2D roi_indices.""" with pytest.raises(ValueError, match="roi_indices must be a list if provided"): TableResult( title="Test", headers=["col1", "col2"], data=[[1, 2], [3, 4]], roi_indices=[[0], [1]], ) def test_from_dataframe(self) -> None: """Test TableResult.from_dataframe factory method.""" # Test without roi_index column df = pd.DataFrame({"col1": [1.0, 2.0], "col2": [3.0, 4.0]}) result = TableResult.from_dataframe(df, title="Test DataFrame") assert result.title == "Test DataFrame" assert list(result.headers) == ["col1", "col2"] # DataFrame converts row-wise: row 0 has [1.0, 3.0], row 1 has [2.0, 4.0] assert result.data == [[1.0, 3.0], [2.0, 4.0]] assert result.roi_indices is None # Test with roi_index column df_with_roi = pd.DataFrame( {"col1": [1.0, 2.0], "col2": [3.0, 4.0], "roi_index": [0, 1]} ) result_with_roi = TableResult.from_dataframe( df_with_roi, title="Test DataFrame with ROI" ) assert result_with_roi.title == "Test DataFrame with ROI" assert list(result_with_roi.headers) == ["col1", "col2"] assert result_with_roi.data == [[1.0, 3.0], [2.0, 4.0]] assert result_with_roi.roi_indices == [0, 1] # Test with attrs result_with_attrs = TableResult.from_dataframe( df, title="Test with Attrs", attrs={"method": "test"} ) assert result_with_attrs.attrs == {"method": "test"} # Test with invalid input (not a DataFrame) with pytest.raises(TypeError, match="df must be a pandas DataFrame"): TableResult.from_dataframe([[1, 2]], title="Invalid") class TestTableResultFactory: """Test class for TableResult factory methods.""" def test_from_rows(self) -> None: """Test TableResult.from_rows factory method.""" result = TableResult.from_rows( title="Test", headers=["col1", "col2"], rows=[[1.0, 2.0], [3.0, 4.0]], roi_indices=[0, 1], attrs={"method": "test"}, ) assert result.title == "Test" assert list(result.headers) == ["col1", "col2"] assert result.data == [[1.0, 2.0], [3.0, 4.0]] assert result.roi_indices == [0, 1] assert result.attrs == {"method": "test"} class TestTableResultSerialization: """Test class for TableResult serialization methods.""" def test_to_dict(self) -> None: """Test TableResult.to_dict serialization.""" table = TableResult( title="Test Table", headers=["col1", "col2"], data=[[1.0, 2.0], [3.0, 4.0]], roi_indices=[0, 1], attrs={"method": "test"}, ) expected = { "schema": 1, "title": "Test Table", "kind": "results", "names": ["col1", "col2"], "data": [[1.0, 2.0], [3.0, 4.0]], "roi_indices": [0, 1], "func_name": None, "attrs": {"method": "test"}, } assert table.to_dict() == expected def test_from_dict(self) -> None: """Test TableResult.from_dict deserialization.""" data = { "title": "Test Table", "kind": "results", "names": ["col1", "col2"], "data": [[1.0, 2.0], [3.0, 4.0]], "roi_indices": [0, 1], "attrs": {"method": "test"}, } table = TableResult.from_dict(data) assert table.title == "Test Table" assert list(table.headers) == ["col1", "col2"] assert table.data == [[1.0, 2.0], [3.0, 4.0]] assert table.roi_indices == [0, 1] assert table.attrs == {"method": "test"} def test_to_html(self) -> None: """Test TableResult.to_html serialization.""" table = TableResult( title="Test Table", headers=["col1", "col2"], data=[[1.0, 2.0], [3.0, 4.0]], ) html = table.to_html() assert " None: """Test TableResult._repr_html_ for Jupyter notebook display.""" table = TableResult( title="Test Table", headers=["col1", "col2"], data=[[1.0, 2.0], [3.0, 4.0]], ) html = table._repr_html_() # pylint: disable=protected-access # Check that CSS styling is included assert "